United States 

Environmental Protection 

Agency 

Air and 

Radiation 

(6204J) 

EPA # 

August 2010 

Documentation for 

EPA Base Case v.4.10 

Using the Integrated Planning 

Model
Cover: EPA Base Case v.4.10 and associated policy cases are used by the U.S. Environmental 

Protection Agency to project the impact of emissions policies on the electric power sector in the 48 

contiguous states and the District of Columbia in the lower continental U.S. Representation of the 

electric power sector in Canada, Alaska, Hawaii, Puerto Rico, and U.S. Virgin Islands is also 

included for purposes of integrated projections. The map appearing on the cover shows the 32 

model regions used to characterize the operation of the U.S. electric power system in the lower 

continental U.S., 11 model regions in Canada, and the 4 self-contained model regions in Alaska, 

Hawaii, Puerto Rico, and U.S. Virgin Islands. EPA Base Case v.4.10 was developed by EPA’s 

Clean Air Markets Division with technical support from ICF International, Inc. The IPM modeling 

platform is a product of ICF International, Inc and is used in support of its public and private sector 

clients. IPM® is a registered trademark of ICF Resources, L.L.C.
Documentation for 

EPA Base Case v.4.10 

Using the Integrated Planning Model

U.S. Environmental Protection Agency 

Clean Air Markets Division 

1200 Pennsylvania Avenue, NW (6204J) 

Washington, D.C. 20460 

(www.epa.gov/airmarkets) 

August 2010
iv 

Acknowledgment

This document was prepared by U.S. EPA’s Clean Air Markets Division, Office of Air and 

Radiation. ICF Services Company, L.L.C. provided technical support under EPA Contract EP-W08-018.
v 

TABLE OF CONTENTS 

1 INTRODUCTION....................................................................................................1-1

2 MODELING FRAMEWORK...................................................................................2-1

2.1 IPM OVERVIEW....................................................................................................................2-1

2.1.1 Purpose and Capabilities.............................................................................................2-1

2.1.2 Applications..................................................................................................................2-2

2.2 MODEL STRUCTURE AND FORMULATION ...............................................................................2-2

2.2.1 Objective Function .......................................................................................................2-2

2.2.2 Decision Variables .......................................................................................................2-3

2.2.3 Constraints...................................................................................................................2-4

2.3 KEY METHODOLOGICAL FEATURES OF IPM...........................................................................2-4

2.3.1 Model Plants ................................................................................................................2-4

2.3.2 Model Run Years .........................................................................................................2-6

2.3.3 Cost Accounting...........................................................................................................2-6

2.3.4 Modeling Wholesale Electric Markets..........................................................................2-6

2.3.5 Load Duration Curves (LDC) .......................................................................................2-7

2.3.6 Dispatch Modeling .......................................................................................................2-9

2.3.7 Reliability Modeling......................................................................................................2-9

2.3.8 Fuel Modeling ............................................................................................................2-10

2.3.9 Transmission Modeling..............................................................................................2-10

2.3.10 Perfect Competition and Perfect Foresight................................................................2-10

2.3.11 Air Regulatory Modeling.............................................................................................2-10

2.4 HARDWARE AND PROGRAMMING FEATURES........................................................................2-11

2.4.1 Data Parameters for Model Inputs.............................................................................2-11

2.4.2 Model Outputs............................................................................................................2-12

Appendix 2-1 Load Duration Curves Used in EPA Base Case v.4.10 .....................................2-1

3 POWER SYSTEM OPERATION ASSUMPTIONS ................................................3-1

3.1 MODEL REGIONS .................................................................................................................3-1

3.2 ELECTRIC LOAD MODELING..................................................................................................3-1

3.2.1 Demand Elasticity ........................................................................................................3-4

3.2.2 Net Internal Demand (Peak Demand)..........................................................................3-4

3.2.3 Regional Load Shapes.................................................................................................3-5

3.3 TRANSMISSION ....................................................................................................................3-5

3.3.1 Inter-regional Transmission Capability.........................................................................3-5

3.3.2 Joint Transmission Capacity and Energy Limits ..........................................................3-9

3.3.3 Transmission Link Wheeling Charge .........................................................................3-10

3.3.4 Transmission Losses .................................................................................................3-11

3.4 INTERNATIONAL IMPORTS ...................................................................................................3-11

3.5 CAPACITY, GENERATION, AND DISPATCH ............................................................................3-11

3.5.1 Availability..................................................................................................................3-11

3.5.2 Capacity Factor..........................................................................................................3-12

3.5.3 Turndown...................................................................................................................3-13

3.6 RESERVE MARGINS............................................................................................................3-13

3.7 POWER PLANT LIFETIMES ..................................................................................................3-15

3.8 HEAT RATES......................................................................................................................3-17
vi 

3.9 EXISTING ENVIRONMENTAL REGULATIONS ..........................................................................3-17

3.9.1 SO2 Regulations ........................................................................................................3-17

3.9.2 NOx Regulations ........................................................................................................3-18

3.9.3 CO2 Regulations and Renewable Portfolio Standards...............................................3-20

3.9.4 State Specific Environmental Regulations.................................................................3-20

3.9.5 New Source Review (NSR) Settlements....................................................................3-20

3.9.6 Emission Assumptions for Potential (New) Units.......................................................3-20

3.10 CAPACITY DEPLOYMENT CONSTRAINTS ..............................................................................3-21

Appendix 3-1 NOx Rate Development in EPA Base Case v.4.10 .........................................3-1.1

Appendix 3-2 State Power Sector Regulations included in EPA Base Case v.4.10 .............3-2.1

Appendix 3-3 New Source Review (NSR) Settlements in EPA Base Case v.4.10 ...............3-3.1

Appendix 3-4 State Settlements in EPA Base Case v.4.10 ..................................................3-4.1

Appendix 3-5 Citizen Settlements in EPA Base Case v.4.10...............................................3-5.1

Appendix 3-6 Renewable Portfolio Standards in EPA Base Case v.4.10 .............................3-6.1

Appendix 3-7 Capacity Deployment Limits for Advanced Coal with CCS and New 

Nuclear in EPA Base Case v.4.10............................................................................3-7.1

Appendix 3-8 Nuclear Capacity Deployment Constraint in EPA Base Case v.4.10..............3-8.1

Appendix 3-9 Complete Availability Assumptions in EPA Base Case v.4.10........................3-9.1

4 GENERATING RESOURCES................................................................................ 4-1

4.1 NATIONAL ELECTRIC ENERGY DATA SYSTEM (NEEDS) ........................................................4-1

4.2 EXISTING UNITS ...................................................................................................................4-1

4.2.1 Population of Existing Units .........................................................................................4-1

4.2.2 Capacity .......................................................................................................................4-4

4.2.3 Plant Location ..............................................................................................................4-5

4.2.4 Online Year..................................................................................................................4-5

4.2.5 Unit Configuration ........................................................................................................4-5

4.2.6 Model Plant Aggregation..............................................................................................4-5

4.2.7 Cost and Performance Characteristics of Existing Units .............................................4-9

4.2.8 Life Extension Costs for existing units .......................................................................4-10

4.3 PLANNED-COMMITTED UNITS .............................................................................................4-13

4.3.1 Population and Model Plant Aggregation...................................................................4-13

4.3.2 Capacity .....................................................................................................................4-17

4.3.3 State and Model Region ............................................................................................4-17

4.3.4 Online and Retirement Year ......................................................................................4-18

4.3.5 Unit Configuration and Cost-and-Performance..........................................................4-18

4.4 POTENTIAL UNITS ..............................................................................................................4-18

4.4.1 Methodology Used to Derive the Cost and Performance Characteristics of 

Conventional Potential Units .....................................................................................4-18

4.4.2 Cost and Performance for Potential Conventional Units............................................4-19

4.4.3 Short-Term Capital Cost Adder..................................................................................4-21

4.4.4 Regional Cost Adjustment .........................................................................................4-21

4.4.5 Cost and Performance for Potential Renewable Generating and Non-4-

Conventional Technologies .......................................................................................4-25

4.5 NUCLEAR UNITS ................................................................................................................4-44

4.5.1 Existing Nuclear Units................................................................................................4-44

4.5.2 Potential Nuclear Units ..............................................................................................4-45

Appendix 4-1 Representative Wind Generation Profiles in EPA Base Case v.4.10..............4-1.1

Appendix 4-2 Representative Solar Generation Profiles in EPA Base v.4.10.......................4-2.1

Appendix 4-3 Characteristics of Existing Nuclear Units ........................................................4-3.1

5 EMISSION CONTROL TECHNOLOGIES .........................................................................5-1
vii 

5.1 SULFUR DIOXIDE CONTROL TECHNOLOGIES..........................................................................5-1

5.1.1 Methodology for Obtaining SO2 Controls Costs...........................................................5-2

5.2 NITROGEN OXIDES CONTROL TECHNOLOGY..........................................................................5-7

5.2.1 Combustion Controls ...................................................................................................5-7

5.2.2 Post-combustion Controls............................................................................................5-8

5.2.3 Methodology for Obtaining SCR Costs for Coal Units .................................................5-9

5.2.4 Methodology for Obtaining SCR Costs for Oil/Gas Steam units................................5-12

5.2.5 Methodology for Obtaining SNCR Costs ...................................................................5-12

5.2.6 SO2 and NOx Controls for Units with Capacities from 25 MW to 100 MW (25 M 

≤ capacity < 100 MW)................................................................................................5-13

5.3 BIOMASS CO-FIRING ..........................................................................................................5-14

5.4 MERCURY CONTROL TECHNOLOGIES..................................................................................5-15

5.4.1 Mercury Content of Fuels...........................................................................................5-16

5.4.2 Mercury Emission Modification Factors .....................................................................5-17

5.4.3 Mercury Control Capabilities......................................................................................5-18

Appendix 5-1 Example Cost Calculation Worksheets for SO2 Control Technologies in 

EPA Base Case v.4.10................................................................................................5-1

Appendix 5-2 Example Cost Calculation Worksheets for NOx Post-Combustion Control 

Technologies in EPA Base Case v.4.10......................................................................5-1

6 CO2 CAPTURE, TRANSPORT, AND STORAGE..................................................6-1

6.1 CO2 CAPTURE .....................................................................................................................6-1

6.2 CO2 STORAGE.....................................................................................................................6-2

6.3 CO2 TRANSPORT .................................................................................................................6-5

Appendix 6-1 CO2 Storage Cost Curves in EPA Base Case 4.10 ........................................6-1.1

Appendix 6-2 CO2 Transportation Matrix in EPA Base Case v.4.10 .....................................6-2.1

7 SET-UP PARAMETERS AND RULES ..................................................................7-1

7.1 RUN YEAR MAPPING ............................................................................................................7-1

7.2 RETROFIT ASSIGNMENTS .....................................................................................................7-1

7.3 TRADING AND BANKING........................................................................................................7-3

7.4 POST-2030 MODELING ASSUMPTIONS AND CAPABILITIES......................................................7-4

8 FINANCIAL ASSUMPTIONS.................................................................................8-1

8.1 SUMMARY OF KEY FINANCIAL PARAMETERS..........................................................................8-1

8.1.1 Capital Charge Rate, Book Life, and Discount Rate for Capital Expenditures ............8-1

8.1.2 ARRA Production and Investment Tax Credit (PTC and ITC) for Renewables ...........8-2

8.1.3 Discount Rate for Non-Capital Expenditures ...............................................................8-3

8.1.4 Inter-temporal Allowance Price Calculation .................................................................8-3

8.1.5 Nominal and Real Dollars ............................................................................................8-3

8.2 DEVELOPMENT OF THE FINANCIAL ASSUMPTIONS FOR EPA BASE CASE V.4.10 .....................8-3

8.2.1 Introduction ..................................................................................................................8-3

8.2.2 Method for Deriving Discount Rate and Capital Charge Rate in EPA Base 

Case v 4.10 .................................................................................................................8-4

8.2.3 Calculation of the Hybrid Capital Charge Rates ..........................................................8-7

8.2.4 Development of Merchant Financing Parameters........................................................8-8

8.2.5 Development of Utility Financing Parameters............................................................8-10

8.2.6 Development of Other Parameters ............................................................................8-10

9 COAL .....................................................................................................................9-1
viii 

9.1 COAL MARKET REPRESENTATION IN EPA BASE CASE V.4.10................................................9-1

9.1.1 Coal Supply Regions ...................................................................................................9-2

9.1.2 Coal Demand Regions.................................................................................................9-3

9.1.3 Coal Quality Characteristics.........................................................................................9-9

9.1.4 Emission Factors .......................................................................................................9-10

9.1.5 Coal Grade Assignments...........................................................................................9-15

9.2 COAL SUPPLY CURVES ......................................................................................................9-16

9.2.1 Nature of Supply Curves Developed for EPA Base Case v.4.10...............................9-16

9.2.2 Procedure Employed in Determining Mining Costs ...................................................9-17

9.2.3 Supply Curve Development .......................................................................................9-20

9.2.4 Data Sources Used to Build the Curves ....................................................................9-21

9.2.5 Procedure Used In Determining Mine Productivity ....................................................9-22

9.2.6 Procedure to Determine Total Recoverable Reserves by Region and Type .............9-22

9.2.7 New Mine Assumptions .............................................................................................9-23

9.2.8 Other Notable Procedures .........................................................................................9-23

9.2.9 Region Specific Assumptions and Outlooks ..............................................................9-23

9.2.10 Explanation of Coal Supply Curve Extensions to 2040..............................................9-25

9.3 COAL TRANSPORTATION ....................................................................................................9-25

9.3.1 Coal Transportation Matrix Overview.........................................................................9-26

9.3.2 Calculation of Supply/Demand Region Distances .....................................................9-26

9.3.3 Overview of Rail Rates ..............................................................................................9-27

9.3.4 Truck rates .................................................................................................................9-30

9.3.5 Barge and Lake Vessel Rates ...................................................................................9-30

9.3.6 Transportation Rates for Imported Coal.....................................................................9-31

9.3.7 Other Transportation Costs........................................................................................9-32

9.3.8 Long-Term Escalation of Transportation Rates .........................................................9-32

9.3.9 Market Drivers Moving Forward.................................................................................9-34

9.3.10 Other Considerations .................................................................................................9-36

9.4 COAL EXPORTS, IMPORTS, AND NON-ELECTRIC SECTORS DEMAND .....................................9-36

Appendix 9-1. Illustrative Example of Wood Mackenzie Costing Procedure Used in 

Developing EPA’s Coal Supply Curves....................................................................9-1.1

Appendix 9-2 New Mines Included in 2040 Curves...............................................................9-2.1

Appendix 9-3 Coal Transportation Matrix in EPA Base Case v.4.10 ....................................9-3.1

Appendix 9-4 Coal Supply Curves in EPA Base Case v.4.10...............................................9-4.1

10 NATURAL GAS ................................................................................................... 10-1

10.1 OVERVIEW OF IPM’S NATURAL GAS MODULE .....................................................................10-1

10.2 KEY COMPONENTS OF THE NEW IPM NATURAL GAS MODULE .............................................10-4

10.2.1 Note on the Modeling Time Horizon and Pre- and Post-2030 Input 

Assumptions..............................................................................................................10-6

10.3 RESOURCE CHARACTERIZATION AND ECONOMIC EVALUATION .............................................10-7

10.3.1 Resource and Reserves Assessment........................................................................10-8

10.3.2 Frontier Resources (Alaska and Mackenzie Delta)..................................................10-10

10.3.3 Use of the HSM resource and reserves data in EPA Base Case using IPM 

v.4.10 Natural Gas Module......................................................................................10-12

10.3.4 Undiscovered Resource Appreciation......................................................................10-13

10.4 EXPLORATION, DEVELOPMENT, AND PRODUCTION COSTS AND CONSTRAINTS ....................10-14

10.4.1 Exploration and Development Cost .........................................................................10-14

10.4.2 Resource Discovery and Drilling Constraints...........................................................10-17

10.4.3 Reserves-to-Production (R/P) Ratio ........................................................................10-19

10.4.4 Variable Costs, Natural Gas Liquid Share, and Crude Oil Share ............................10-19

10.4.5 Lease and Plant Gas Use........................................................................................10-20
ix 

10.5 LIQUEFIED NATURAL GAS (LNG) IMPORTS .......................................................................10-20

10.5.1 Liquefaction Facilities and LNG Supply ...................................................................10-20

10.5.2 Regasification Facilities ...........................................................................................10-21

10.5.3 LNG Regasification Capacity Expansions ...............................................................10-22

10.6 END USE DEMAND ...........................................................................................................10-23

10.6.1 Step 1: Developing Sector Specific Econometric Models of Non-Power Sector 

Demand...................................................................................................................10-23

10.6.2 Step 2: Use projections based on the GMM econometric models to produce 

monthly gas demand curves by sector and demand node......................................10-25

10.6.3 Step 3: Develop non-electric sector natural gas demand curves that 

correspond to the seasons and segments in the load duration curves used in 

IPM ..........................................................................................................................10-25

10.7 PIPELINE NETWORK .........................................................................................................10-27

10.7.1 Network Structure ....................................................................................................10-27

10.7.2 Pipeline Transportation Costs..................................................................................10-28

10.7.3 Pipeline Capacity Expansion Logic..........................................................................10-29

10.8 GAS STORAGE.................................................................................................................10-30

10.8.1 Storage Capacity and Injection/Withdrawal Constraints..........................................10-33

10.8.2 Variable Cost and Fuel Use.....................................................................................10-33

10.8.3 Storage Capacity Expansion Logic..........................................................................10-34

10.9 FUEL PRICES...................................................................................................................10-35

10.9.1 Crude Oil and Natural Gas Liquids Prices ...............................................................10-35

10.9.2 Natural Gas Prices...................................................................................................10-36

10.10 OUTPUTS AND PROXY NATURAL GAS SUPPLY CURVES .....................................................10-36

10.10.1 Outputs from the New IPM Natural Gas Module......................................................10-36

10.10.2 Proxy Natural Gas Supply Curves ...........................................................................10-36

Appendix 10-1 EPA Base Case v.4.10 with AEO Gas Resource Assumptions..................10-1.1

11 OTHER FUELS AND FUEL EMISSION FACTOR ASSUMPTIONS ...................11-1

11.1 FUEL OIL...........................................................................................................................11-1

11.2 BIOMASS ...........................................................................................................................11-2

11.3 NUCLEAR FUEL..................................................................................................................11-3

11.4 WASTE FUELS ...................................................................................................................11-3

11.5 FUEL EMISSION FACTORS ..................................................................................................11-5

Appendix 11-1 Biomass Supply Curve in EPA Base Case v.4.0 ...........................................11-1

i 

LIST OF TABLES 

Table 1-1 Plant Types in EPA Base Case v.4.10.........................................................................1-2

Table 1-2 Emission Control Technologies in EPA Base Case v.4.10 ..........................................1-3

Table 1-3 Key Updates in the EPA Base Case v.4.10 ..................................................................1-4

Table 3-1 Mapping of NERC Regions and NEMS Regions with EPA Base Case v.4.10 

Model Regions...........................................................................................................3-3

Table 3-2 Electric Load Assumptions in EPA Base Case v.4.10 .................................................3-4

Table 3-3 National Non-Coincidental Net Internal Demand .........................................................3-5

Table 3-4 Annual Transmission Capabilities of U.S. Model Regions in EPA Base Case 

v.4.10.........................................................................................................................3-6

Table 3-5 Annual Joint Capacity and Energy Limits to Transmission Capabilities Between 

Model Regions in EPA Base Case v.4.10 .................................................................3-9

Table 3-6 International Electricity Imports in EPA Base Case v.4.10 ........................................3-11

Table 3-7 Availability Assumptions in the EPA Base Case v.4.10 .............................................3-12

Table 3-8 Seasonal Hydro Capacity Factors (%) in the EPA Base Case v.4.10 .......................3-12

Table 3-9 Planning Reserve Margins in EPA Base Case v.4.10 ...............................................3-14

Table 3-10 Lower and Upper Limits Applied to Heat Rate Data in NEEDS v.4.10 ....................3-17

Table 3-11 Emission and Removal Rate Assumptions for Potential (New) Units in EPA 

Base Case v.4.10 ....................................................................................................3-23

Table 4-1 Data Sources for NEEDS v.4.10 for EPA Base Case v.4.10 .......................................4-2

Table 4-2 Rules Used in Populating NEEDS v.4.10 for EPA Base Case v.4.10..........................4-3

Table 4-3 Summary Population (through 2006) of Existing Units in NEEDSv.4.10 for EPA 

Base Case v.4.10 ......................................................................................................4-3

Table 4-4 Hierarchy of Data Sources for Capacity in NEEDS v.4.10...........................................4-4

Table 4-5 Capacity-Parsing Algorithm for Steam Units in NEEDS v.4.10....................................4-4

Table 4-6 Data Sources for Unit Configuration in NEEDS v.4.10 for EPA Base Case v.4.10 .....4-6

Table 4-7 Aggregation Profile of Model Plants as Provided at Set Up of EPA Base Case 

v.4.10.........................................................................................................................4-7

Table 4-8 VOM Assumptions (2007$) in EPA Base Case v.4.10 ................................................4-9

Table 4-9 FOM Assumptions Used in EPA Base Case v.4.10...................................................4-11

Table 4-10 Life Extension Cost Assumptions Used in EPA Base Case v.4.10..........................4-13

Table 4-11 Summary of Planned-Committed Units in NEEDS v.4.10 for EPA Base Case 

v.4.10.......................................................................................................................4-14

Table 4-12 Planned-Committed Units by Model Region in NEEDS v.4.10 for EPA Base 

Case v.4.10..............................................................................................................4-14

Table 4-13 Performance and Unit Cost Assumptions for Potential (New) Capacity from 

Conventional Technologies in EPA Base Case v4.10.............................................4-20

Table 4-14 Short-Term Capital Cost Adders for New Power Plants in EPA Base Case 

v.4.10 (2007$)..........................................................................................................4-23

Table 4-15 Regional Cost Adjustment Factors for Conventional and Renewable Generating 

Technologies in EPA Base Case v.4.10..................................................................4-25

Table 4-16 Performance and Unit Cost Assumptions for Potential (New) Renewable and 

Non-Conventional Technology Capacity in EPA Base Case v4.10.........................4-27

Table 4-17 Onshore Regional Potential Wind Capacity (MW) by Wind and Cost Class in 

EPA Base Case v.4.10 ............................................................................................4-29

Table 4-18 Offshore Shallow Regional Potential Wind Capacity (MW) by Wind and Cost 

Class in EPA Base Case v.4.10 ..............................................................................4-32
ii 

Table 4-19 Offshore Deep Regional Potential Wind Capacity (MW) by Wind and Cost Class 

in EPA Base Case v.4.10 ........................................................................................4-34

Table 4-20 Onshore Reserve Margin Contribution an Average Capacity Factor by Wind 

Class and Model Region..........................................................................................4-37

Table 4-21 Offshore Shallow Reserve Margin Contribution an Average Capacity Factor by 

Wind Class and Model Region ................................................................................4-37

Table 4-22 Offshore Deep Reserve Margin Contribution an Average Capacity Factor by 

Wind Class and Model Region ................................................................................4-38

Table 4-23 Capital Cost Adjustment Factors for New Wind Plants in Base Case v.4.10...........4-39

Table 4-24 Example Calculations Of Wind Generation Potential, Reserve Margin 

Contribution, And Capital Cost For Onshore Wind In CA-N At Wind Class 7, 

Cost Class 2 ............................................................................................................4-40

Table 4-25 Solar Reserve Margin Contribution and Average Capacity Factor by Model 

Region .....................................................................................................................4-41

Table 4-26 Regional Assumptions on Potential Geothermal Electric Capacity..........................4-42

Table 4-27 Potential Geothermal Capacity and Cost Characteristics by Model Region ............4-42

Table 4-28 Regional Assumptions on Potential Electric Capacity from New Landfill Gas 

Units (MW)...............................................................................................................4-43

Table 4-29 Nuclear Upratings (MW) as Incorporated in EPA Base Case v.4.10 from AEO 

2010.........................................................................................................................4-45

Table 5-1 Summary of Emission Control Technology Retrofit Options in EPA Base Case 

v.4.10 .........................................................................................................................5-1

Table 5-2 Summary of Retrofit SO2 Emission Control Performance Assumptions .......................5-2

Table 5-3 Capital Cost Modules and Their Governing Variables for SO2 and NOx Emission 

Controls .....................................................................................................................5-3

Table 5-4 Illustrative Scrubber Costs (2007$) for Representative Sizes and Heat Rates 

under the Assumptions in EPA Base Case v.4.10.....................................................5-6

Table 5-5 Cost (2007$) of NOx Combustion Controls for Coal Boilers (300 MW Size).................5-7

Table 5-6 Incremental Combustion NOx Controls in EPA Base Case v.4.10................................5-8

Table 5-7 Summary of Retrofit NOx Emission Control Performance Assumptions ......................5-8

Table 5-8 Illustrative Post Combustion NOX Controls for Coal Plants Costs (2007$) for 

Representative Sizes and Heat Rates under the Assu Assumptions in EPA 

Base Case v.4.10 ....................................................................................................5-11

Table 5-9 Post-Combustion NOX Controls for Oil/Gas Steam Units in EPA Base Case 

v.4.10 .......................................................................................................................5-12

Table 5-10 Biomass Cofiring for Coal Plants .............................................................................5-15

Table 5-11 Mercury Clusters and Mercury Content of Coal by IPM Coal Types........................5-17

Table 5-12 Assumptions on Mercury Concentration in Non-Coal Fuel in EPA Base Case 

v.4.10 .......................................................................................................................5-17

Table 5-13 Mercury Emission Modification Factors Used in EPA Base Case v.4.10.................5-19

Table 5-14 Definition of Acronyms for Existing Controls............................................................5-26

Table 5-15 Key to Burner Type Designations in Table 5-13 .....................................................5-26

Table 5-16 Illustrative Activated Carbon Injection Costs (2007$) for Representative Sizes 

under the Assumptions in EPA Base Case v.4.10...................................................5-28

Table 5-17 Assignment Scheme for Mercury Emissions Control Using Activated Carbon 

Injection (ACI) in EPA Base Case v.4.10.................................................................5-29

Table 6-1 Performance and Unit Cost Assumptions for Carbon Capture Retrofits on 

Pulverized Coal Plants...............................................................................................6-1
iii 

Table 6-2 CO2 Transport Cost Calculation Example – MACS to Louisiana Onshore ..................6-5

Table 7-1 Run Years and Analysis Year Mapping Used in the EPA Base Case v.4.10 ..............7-1

Table 7-2 First Stage Retrofit Assignment Scheme in EPA Base Case v.4.10............................7-2

Table 7-3 Second Stage Retrofit Assignment Scheme in EPA Base Case v.4.10 ......................7-3

Table 7-4 Trading and Banking Rules in EPA Base Case v.4.10 ................................................7-4

Table 7-5 Post-2030 Assumptions in EPA Base Case v.4.10......................................................7-5

Table 8-1 U.S. Discount Rates and Capital Charge Rates in EPA Base Case v4.10..................8-2

Table 8-2 Capital Structure Assumptions for EPA Base Case v4.10...........................................8-6

Table 8-3 Debt Rates for EPA Base Case v4.10 .........................................................................8-8

Table 8-4 Book Life, Debt Life and Depreciation Schedules for EPA Base Case v. 4.10..........8-11

Table 9-1 Coal Supply Regions in EPA Base Case.....................................................................9-2

Table 9-2 Coal Demand Regions in EPA Base Case ..................................................................9-3

Table 9-3 Coal Rank Heat Content Ranges...............................................................................9-10

Table 9-4 Coal Grade SO2 Content Ranges ..............................................................................9-10

Table 9-5 Coal Quality Characteristics by Supply Region and Coal Grade ...............................9-11

Table 9-6 SO2 Emission Factors of Coal Used in EPA Base Case v.4.10.................................9-13

Table 9-7 Mercury Emission Factors of Coal Used in EPA Base Case v.4.10 ..........................9-14

Table 9-8 Ash Emission Factors of Coal Used in EPA Base Case v.4.10 .................................9-14

Table 9-9 CO2 Emission Factors of Coal Used in EPA Base Case v.4.10.................................9-15

Table 9-10 Example of Coal Assignments Made in EPA Base Case ........................................9-16

Table 9-11 Basin-Level Groupings Used in Preparing v.4.0 Coal Supply Curves .....................9-17

Table 9-12 Rail Competition Definitions.....................................................................................9-28

Table 9-13 Assumed Eastern Rail Rates (2007 mills/ton-mile)..................................................9-29

Table 9-14 Assumed Midwestern Rail Rates (2007 mills/ton-mile)............................................9-29

Table 9-15 Assumed Non-PRB Western Rail Rates (2007 mills/ton-mile) ................................9-30

Table 9-16 Assumed PRB Western Rail Rates (2007 mills/ton-mile) ........................................9-30

Table 9-17 Assumed Truck Rates (2007 Real Dollars)..............................................................9-30

Table 9-18 Assumed Barge Rates (2007 Real Dollars) .............................................................9-31

Table 9-19 Assumed Transportation Rates for Imported Coal (2007 Real Dollars)...................9-31

Table 9-20 Assumed Other Transportation Rates (2007 Real Dollars)......................................9-32

Table 9-21 EIA AEO Diesel Fuel Forecast, 2012-2030 (2007 Real Dollars) .............................9-34

Table 9-22 ABARE Forecast of Iron Ore Prices.........................................................................9-35

Table 9-23 Assumed Production Growth Rates.........................................................................9-36

Table 9-24 Coal Exports.............................................................................................................9-37

Table 9-25 Residential, Commercial, and Industrial Demand....................................................9-38

Table 9-26 Coal Import Limits ....................................................................................................9-38

Table 10-1 List of Nodes ............................................................................................................10-5

Table 10-2 List of Gas Supply Regions......................................................................................10-1

Table 10-3 List of Key Pipelines.................................................................................................10-3

Table 10-4 U.S. and Canada Natural Gas Resources and Reserves......................................10-10

Table 10-5 Exploration and Development Assumptions for EPA Base Case v.4.10 ...............10-17

Table 10-6 North American LNG Regasification Facilities .......................................................10-21

Table 10-7 Summer and Winter Load Segments in EPA Base Case v.4.10 ...........................10-26

Table 10-8 List of Storage Nodes.............................................................................................10-31

Table 10-9 Storage Capacity and Injection/Withdrawal Rates (EOY 2010).............................10-33
iv 

Table 10-10 Base Year 2011 Average Levelized Storage Capital Cost...................................10-35

Table 10-11 Proxy Natural Gas Supply Curves for EPA Base Case v.4.10.............................10-37

Table 10-12 Glossary of Natural Gas Terms Used in Documentation .....................................10-38

Table 11-1 Fuel Oil Prices by NEMS Region in EPA Base Case v.4.10....................................11-1

Table 11-2 Non-Electric Biomass Demand by NEMS Region in EPA Base Case v.4.10 ..........11-2

Table 11-3 Waste Fuels in NEEDS, v.4.10 and EPA Base Case v.4.10 ...................................11-4

Table 11-4 Fuel Emission Factor Assumptions in EPA Base Case v.4.10 ................................11-5
v 

LIST OF FIGURES 

Figure 1-1 Modeling and Data Structures in EPA Base Case v.4.10...........................................1-4

Figure 2-1 Hypothetical Chronological Hourly Load Curve and Seasonal Load Duration 

Curve in EPA Base Case v.4.10................................................................................2-7

Figure 2-2 Stylized Depiction of Load Duration Curve Used in EPA Base Case v.4.10 ..............2-8

Figure 2-3 Stylized Dispatch Order in EPA Base Case v.4.10.....................................................2-9

Figure 3-1 EPA Base Case v.4.10 Model Regions ......................................................................3-2

Figure 3-2 Scheduled Retirements of Existing Nuclear Capacity Under 60-Year Life 

Assumption..............................................................................................................3-15

Figure 9-1 Map of the Coal Supply Regions in EPA Base Case v.4.10.......................................9-3

Figure 9-2 Cluster Mapping Example --- BG Coal......................................................................9-15

Figure 9-3 Cost Calculations Included When Developing Coal Supply Curves (based on a 

Powder River Basin Mine Supply Curve Example)..................................................9-18

Figure 9-4 Illustration of Preliminary Step in Developing a Cumulative Coal Supply Curve ......9-20

Figure 9-5 Illustration of Final Step in Developing a Cumulative Coal Supply Curve ................9-21

Figure 9-6 Example Coal Supply Curve in Stepped Format ......................................................9-21

Figure 9-7 Calculation of Multi-Mode Transportation Costs (Example)......................................9-26

Figure 9-8 Coal Demand Region with Multiple Coal Supply Regions ........................................9-27

Figure 9-9 Rail Cost Indices Performance (2Q2003-2Q2008) ...................................................9-33

Figure 9-10 Long-Run Marginal Cost Breakdown by Transportation Mode...............................9-34

Figure 10-1 Modeling and Data Structure in EPA Base Case v.4.10.........................................10-2

Figure 10-2 Natural Gas Module in EPA Base Case v.4.10. .....................................................10-3

Figure 10-3 Gas Transmission Network Map.............................................................................10-5

Figure 10-4 Gas Supply Regions Map .......................................................................................10-8

Figure 10-5 Gas Demand Regions Map.....................................................................................10-3

Figure 10-6 Natural Gas Storage Facility Node Map .................................................................10-7

Figure 10-7 Resource Cost Curves at the End of Year 2010...................................................10-13

Figure 10-8 Exploration & Development and Production Processes and Costs to Bring 

Undiscovered Resource into Reserves and Production ........................................10-14

Figure 10-9 E&D and Production Technology Improvement Factor.........................................10-15

Figure 10-10 Incremental E&D Cost (EOY 2010) by Percentage of Resource Found.............10-15

Figure 10-11 Drilling Rig Speed Constraint..............................................................................10-19

Figure 10-12 North American LNG Supply Curves ..................................................................10-21

Figure 10-13 North American LNG Regasification Facilities Map............................................10-22

Figure 10-14 Examples of Firm Demand Curves by Electric Load Segment...........................10-26

Figure 10-15 Examples of Interruptible Demand Curves by Electric Load Segment ...............10-27

Figure 10-16 New England Pipeline Corridors in 2020 ............................................................10-28

Figure 10-17 Example Pipeline Discount Curve.......................................................................10-29

Figure 10-18 Pipeline Cost Growth Factor...............................................................................10-29

Figure 10-19 Storage Cost Growth Factor ...............................................................................10-34

Figure 10-20 Example Maximum Storage Capacity Expansion...............................................10-34

Figure 10-21 Crude Oil and NGL Prices ..................................................................................10-36

1-1 

1 Introduction 

This document describes the nature, structure, and capabilities of the Integrated Planning Model 

(IPM) and the assumptions underlying the base case (designated EPA Base Case v.4.10) that 

was developed by the U.S. Environmental Protection Agency (EPA) with technical support from 

ICF Consulting, Inc. IPM is a multi-regional, dynamic, deterministic linear programming model of 

the U.S. electric power sector. It provides forecasts of least cost capacity expansion, electricity 

dispatch, and emission control strategies while meeting energy demand and environmental, 

transmission, dispatch, and reliability constraints. IPM can be used to evaluate the cost and 

emissions impacts of proposed policies to limit emissions of sulfur dioxide (SO2), nitrogen oxides 

(NOx), carbon dioxide (CO2), and mercury (Hg) from the electric power sector. 

Base cases, like EPA Base Case v.4.10, serve as the starting point against which policy scenarios 

are compared. It is a projection of electricity sector activity that takes into account only those 

Federal and state air emission laws and regulations whose provisions were either in effect or 

enacted and clearly delineated at the time the base case was finalized in August 2010. (Chapter 

3 contains a detailed discussion of the environmental regulations included in EPA Base Case 

v.4.10.) Regulations, mandated under the Clean Air Act Amendments of 1990 (CAAA), but whose 

provisions either have not yet been finalized or will expire due to Court action, were not included in 

the base case. These include. 

• Ozone and Particulate Matter (PM) Standards: EPA Base Case v.4.10 does not include the 

provisions of the Clean Air Interstate Rule (CAIR), a Federal regulatory measure for achieving 

the National Ambient Air Quality Standards (NAAQS) for ozone (8-hour standard of 0.08 ppm) 

and fine particles (24-hour average of 65 μg/m3 or less and annual mean of 15 μg/m3 for 

particles of diameter 2.5 micrometers or less, i.e., PM 2.5). Originally issued on March 10, 

2005, CAIR was remanded back to EPA by the U.S. Court of Appeals for the District of 

Columbia Circuit in December 2008 and EPA was required to correct legal flaws in the 

regulations that had been cited in a ruling by the Court in July 2008. Until EPA’s work was 

completed, CAIR was temporarily reinstated. However, although CAIR’s provisions were still 

in effect when EPA Base Case v.4.10 was released, it is not included in the base case to 

allow EPA Base Case v.4.10 to be used to analyze the regulations proposed to replace CAIR. 

• EPA Base Case v.4.10 includes ozone and particulate matter standards to the extent that 

some of the state regulations included in EPA Base Case v.4.10 contain measures to bring 

non-attainment areas into attainment. A summary of these state regulations can be found in 

Appendix 3-2 below. Apart from these state regulations, individual permits issued by states in 

response to ozone and PM standards are only captured (a) to the extent that they are 

reflected in the NOX rates reported to EPA under Title IV and the NOX Budget Program which 

are incorporated in the base case and (b) to the extent that SO2 permit limits are used in the 

base case to define the choice of coal sulfur grades that are available to specific power plants. 

 

• Regional Haze: On July 1, 1999, EPA issued Regional Haze Regulations to meet the national 

goal for visibility established in Section 169A of the CAAA, which calls for “prevention of any 

future, and the remedying of any existing, impairment of visibility in Class I areas [156 national 

parks and wilderness areas], which impairment results from manmade air pollution.” The 

regulations required states to submit revised State Implementation Plans (SIPs) that include 

(1) goals for improving visibility in Class I areas on the 20% worst days and allowing no 

degradation on the 20% best days and (2) assessments and plans for achieving Best 

Available Retrofit Technology (BART) emission targets for sources placed in operation 

between 1962-1977. The revised SIPs were to be submitted between 2004-2006 for areas 

designated as “attainment” and “unclassified” and between 2006-2008 for “nonattainment” 

areas. They are represented in EPA Base Case v.4.10 to the extent that SO2 permit limits 

derived from the SIPs are used in the base case to define the choice of coal sulfur grades that 

are available to specific power plants. As discussed in chapter 3, however, the base case 

includes the sulfur dioxide emission cap (144.7 MTons for all affected fossil fired generating 

units larger than 25 MW), adopted by the Western Regional Air Partnership states of Arizona, 
1-2 

New Mexico, Oregon, Utah, and Wyoming in response to Section 309 of the federal Regional 

Haze Rule. 

In effect, EPA Base Case v.4.10 offers a projection of the electric sector assuming that the only 

future environmental regulations are those that were in place at the time the base case was 

finalized and that have a high likelihood of remaining in force. This simplifying assumption 

ensures that the base case is policy neutral with respect to prospective, future environmental 

policies. Table 1-1 lists the types of plants included in the EPA Base Case v.4.10. Table 1-2 lists 

the emission control technologies available for meeting emission limits in EPA Base Case v.4.10. 

Table 1-1 Plant Types in EPA Base Case v.4.10 

Fossil Fuel Fired 

Coal Steam 

Oil/Gas Steam 

Combustion Turbine 

Combined-Cycle Combustion Turbine 

Integrated Gasification Combined-Cycle (IGCC) Coal 

Advanced Coal with Carbon Capture 

Fluidized Bed Combustion 

Non-Fossil Fuel Fired 

Nuclear 

Renewables and Non-Conventional Technologies 

Hydropower 

Pumped Storage 

Biomass IGCC 

Onshore Wind 

Offshore Shallow Wind 

Offshore Deep Wind 

Fuel Cells 

Solar Photovoltaics 

Solar Thermal 

Geothermal 

Landfill Gas 

Other1

Note:

1

 Includes fossil and non-fossil waste plants 
1-3 

Table 1-2 Emission Control Technologies in EPA Base Case v.4.10 

Sulfur Dioxide (SO2) Nitrogen Oxides (NOx) 

Limestone Forced Oxidation (LSFO) 

Lime Spray Dryer (LSD) 

Combustion controls 

Selective catalytic reduction (SCR) 

Selective non-catalytic reduction (SNCR) 

Mercury (Hg) Carbon Dioxide (CO2) 

Combinations of SO2, NOx, and particulate 

control technologies Carbon Capture and Sequestration 

Activated Carbon Injection 

Notes:

1. Though not listed in Table 1-2, biomass co-firing, which is offered as a fuel option in EPA 

Base Case v.4.10, is also used as a CO2 emission control option. See section 5.3 in Chapter 5 

for a description of the implementation of biomass co-firing in EPA Base Case v.4.10. 

2. Fuel switching between coal types and to natural gas is also a compliance option for 

reducing emissions in EPA Base Case v.4.10 

Figure 1-1 provides a schematic of the components of the modeling and data structure used for 

EPA Base Case v.4.10. This report devotes a separate chapter to all the key components shown 

in Figure 1-1. Chapter 2 provides an overview of IPM’s modeling framework (sometimes referred 

to as the “IPM Engine”), highlighting the mathematical structure, notable features of the model, 

programming elements, and model inputs and outputs. The remaining chapters are devoted to 

different aspects of EPA Base Case v.4.10. Chapter 3 covers the power system operating 

characteristics captured in EPA Base Case v.4.10. Chapter 4 explores the characterization of 

electric generation resources. Emission control technologies (chapter 5) and carbon capture, 

transport and storage (chapter 6) are then presented. Chapter 7 describes certain set-up rules 

and parameters employed in EPA Base Case v.4.10. Chapter 8 summarizes the base case 

financial assumptions. The last three chapters discuss the representation and assumptions for 

fuels in the base case. Coal is covered in chapter 9, natural gas in chapter 10, and other fuels 

(i.e., fuel oil, biomass, nuclear fuel, and waste fuels) in chapter 11 (along with fuel emission 

factors). 
1-4 

Figure 1-1 Modeling and Data Structures in EPA Base Case v.4.10 

Table 1-3 lists key updates included in EPA Base Case v.4.10 listed in the order they appear in 

this documentation report. Noted by asterisks in the second column are updates that were “nonroutine” in the sense that they constituted new modeling capabilities or notable extensions beyond 

the capabilities provided in previous EPA base cases or significant reviews of important 

assumptions. The updates that are not starred represent more routine updates. Equal in 

importance to the non-routine updates, the routine updates typically require substantial effort and 

great discipline to maintain. They are critical to the technical credibility of a detailed, bottom-up, 

data driven model like IPM. 

Table 1-3 Key Updates in the EPA Base Case v.4.10 

Description 

NonRoutine 

(*) 

For More 

Information 

Modeling Framework 

 

Use of six-segment load duration curves (2012-2030) to enable 

differentiation of peak and super-peak generating unit dispatch §2.3.5 - 2.3.6 

Power System Operation 

 Model region update and inclusion of Canada, Alaska, Hawaii, 

Puerto Rico, and U.S. Virgin Islands * §3.1 

 Updates based on recent data from EIA, NERC, FERC, etc. (multiple) 

 Capacity deployment constraints (for new advanced coal with 

carbon capture, carbon capture retrofits, and new nuclear) * 

§3.10 

App. 3-07 - 

3-08 
1-5 

Description 

NonRoutine 

(*) 

For More 

Information 

 Updated inventory of state emission regulations App.3-02 

 Updated inventories of NSR, state, and citizen settlements App. 3-03 - 

3-05 

 Nuclear retirement at age 60 * §3.7 

Generating Resources 

 Updates to NEEDS, the database of existing and plannedcommitted units and their emission control configurations §4.1- 4.3 

 

Providing life extension cost option to allow existing units to 

continue operation over the extended 2012-2050 modeling time 

horizon in the new base case 

 §4.2.8 

 

Updated cost and performance characteristics for potential (new) 

conventional and nuclear generating units, based on comparative 

cost analyses 

* §4.4.1 - 

4.4.2 

 Adding biomass gasification combined cycle and offshore (shallow 

and deep) wind as potential (new) renewable generating options * §4.4.5 

 

Expanding wind resource base to include 5 wind classes (3-7) by 

adding new wind classes 3 and 7 using data provided by NREL * §4.4.5 

Emission Control Technologies 

 

Complete update of cost and performance assumptions for SO2

and NOx emission controls based on engineering studies by 

Sargent and Lundy 

* §5.1 - 5.2 

 

Inclusion of cost and performance assumptions for SO2 and NOx

emission controls for units with capacities ranging from 25-100MW * §5.2.6 

 

Updated cost and performance assumptions for biomass co-firing 

by coal units §5.3 

Carbon Capture, Transport and Storage 

 

Update of the cost and performance characteristics used to 

represent carbon capture retrofits and new generating units with 

carbon capture 

 §6.1 

 

CO2 transport and storage represented through state level 

transportation matrix and regional storage cost curves rather than 

a single cost adder 

* §6.2 - 6.3 

Set-Up Parameters and Rules 

 

Expanded modeling time horizon out to 2050 with six model run 

years (2012, 2015, 2020, 2030, 2040, 2050) * §7.1 and 7.4 

 

Five generic placeholder future generation technologies for later 

use in comparative scenario analyses §7.4 

Financial assumptions 

 

Update of discount and capital charge rate assumptions based on 

a new hybrid capital cost model of utility and merchant finance 

structures 

 §8.1.1 and 

8.2 

 Capital cost adder for climate change uncertainty §8.1.1 
1-6 

Description 

NonRoutine 

(*) 

For More 

Information 

 

Incorporation of latest legislation based tax credits for renewables 

and nuclear generation §8.1.1 - 

8.1.2 

Coal 

 Complete update of coal supply curves and transportation matrix * §9 

Natural Gas 

 

Development of IPM natural gas module providing completely 

endogenous comprehensive modeling of North American natural 

gas system 

* §10 

 Major revision of unconventional gas resource base, particularly 

view of shale gas resources * §10.3 

 Base case variant with natural gas resource assumptions similar 

to AEO 2010 Appendix 

10.1 

Other Fuels 

 Update of biomass supply curves and price assumptions for fuel 

oil, nuclear fuel and waste fuel * §11 
2-1 

2 Modeling Framework 

ICF International developed the Integrated Planning Model (IPM) to support analysis of the electric 

sector. The EPA, in addition to other state air regulatory agencies, utilities, and public and private 

sector clients, has used IPM extensively for various air regulatory analyses, market studies, 

strategy planning, and economic impact assessments. 

The first section of this chapter provides a brief overview of the model’s purpose, capabilities, and 

applications. The following sections are devoted to describing the IPM model’s structure and 

formulation, key methodological characteristics, and programming features, including its handling 

of model inputs and outputs. Readers may find some overlap between sections. For example, 

transmission decision variables and constraints are covered in section 2.2's discussion of model 

structure and formulation, and transmission modeling is covered as a key methodological feature 

in section 2.3.9. The different perspectives of each section are designed to provide readers with 

information that is complementary rather than repetitive. 

2.1 IPM Overview 

IPM is a well-established model of the electric power sector designed to help government and 

industry analyze a wide range of issues related to this sector. The model represents economic 

activities in key components of energy markets – fuel markets, emission markets, and electricity 

markets. Since the model captures the linkages in electricity markets, it is well suited for 

developing integrated analyses of the impacts of alternative regulatory policies on the power 

sector. In the past, applications of IPM have included capacity planning, environmental policy 

analysis and compliance planning, wholesale price forecasting, and asset valuation. 

2.1.1 Purpose and Capabilities 

IPM is a dynamic linear programming model that generates optimal decisions under the 

assumption of perfect foresight. It determines the least-cost method of meeting energy and peak 

demand requirements over a specified period. In its solution, the model considers a number of 

key operating or regulatory constraints (e.g. emission limits, transmission capabilities, renewable 

generation requirements, fuel market constraints) that are placed on the power, emissions, and 

fuel markets. In particular, the model is well-suited to consider complex treatment of emission 

regulations involving trading, banking, and special provisions affecting emission allowances (like 

bonus allowances and progressive flow control), as well as traditional command-and-control 

emission policies. 

IPM represents power markets through model regions that are geographical entities with distinct 

characteristics. While they are more numerous (for purposes of picking up local transmission 

behavior and bottlenecks), the model regions representing the U.S. power market in EPA Base 

Case v.4.10 are largely consistent with the regions and sub-regions constituting the North 

American Electric Reliability Council (NERC) regions and with the organizational structures of the 

Regional Transmission Organizations (RTOs) and Independent System Operators, which handle 

dispatch on most of the U.S. grid. IPM models the electric demand, generation, transmission, and 

distribution within each region as well as the inter-regional transmission grid. All existing utility 

power generation units, including renewable resources, are modeled, as well as independent 

power producers and cogeneration facilities that sell electricity to the grid. 

IPM provides a detailed representation of new and existing resource options, including fossil 

generating options (coal steam, gas-fired simple cycle combustion turbines, combined cycles, and 

oil/gas steam), nuclear generating options, and renewable and non-conventional (e.g., fuel cells) 

resources. Renewable resource options include wind, landfill gas, geothermal, solar thermal, 

solar photovoltaic and biomass. 

IPM can incorporate a detailed representation of fuel markets and can endogenously forecast fuel 

prices for coal, natural gas, and biomass by balancing fuel demand and supply for electric 
2-2 

generation. The model also includes detailed fuel quality parameters to estimate emissions from 

electric generation. 

IPM provides estimates of air emission changes, regional wholesale energy and capacity prices, 

incremental electric power system costs, changes in fuel use, and capacity and dispatch 

projections. 

2.1.2 Applications 

IPM’s structure, formulation and set-up make it very adaptable and flexible. The necessary level 

of data, modeling capabilities exercised, and computational requirements can be tailored to the 

particular strategies and policy options being analyzed. This adaptability has made IPM suitable 

for a variety of applications. These include: 

Air Regulatory Assessment: Since IPM contains extensive air regulatory modeling features, 

state and federal air regulatory agencies have used the model extensively in support of air 

regulatory assessment. 

Integrated Resource Planning: IPM can be used to perform least-cost planning studies that 

simultaneously optimize demand-side options (load management and conservation), renewable 

options and traditional supply-side options. 

Strategic Planning: IPM can be used to assess the costs and risks associated with alternative 

utility and consumer resource planning strategies as characterized by the portfolio of options 

included in the input data base. 

Options Assessment: IPM allows industry and regulatory planners to "screen" alternative 

resource options and option combinations based upon their relative costs and contributions to 

meeting customer demands. 

Cost and Price Estimation: IPM produces realistic estimates of energy prices, capacity prices, 

fuel prices, and allowance prices. Industry and regulatory agencies have used these cost reports 

for due diligence, planning, litigation and economic impact assessment. 

2.2 Model Structure and Formulation 

IPM employs a linear programming structure that is particularly well-suited for analysis of the 

electric sector to help decision makers plan system capacity and model the dispatch of electricity 

from individual units or plants. The model consists of three key structural components: 

• A linear “objective function,” 

• A series of “decision variables,” and 

• A set of linear “constraints”. 

• The sections below describe the objective function, key decision variables, and constraints 

included in IPM for EPA Base Case v.4.10. 

2.2.1 Objective Function 

IPM’s objective function is to minimize the total, discounted net present value, of the costs of 

meeting demand, power operation constraints, and environmental regulations over the entire 

planning horizon. The objective function represents the summation of all the costs incurred by the 

electricity sector. The total resulting cost is expressed as the net present value of all the 

component costs. These costs, which the linear programming formulation attempts to minimize, 

include the cost of new plant and pollution control construction, fixed and variable operating and 

maintenance costs, and fuel costs. Many of these cost components are captured in the objective 

function by multiplying the decision variables by a cost coefficient. Cost escalation factors are 

used in the objective function to reflect changes in cost over time. The applicable discount rates 
2-3 

are applied to derive the net present value for the entire planning horizon from the costs obtained 

for all years in the planning horizon. 

2.2.2 Decision Variables 

Decision variables represent the values which the IPM model is “solving for,” given the costminimizing objective function described in section 2.2.1 and the set of electric system constraints 

detailed in section 2.2.3. The decision variables values are the model’s “outputs” and represent 

the optimal least-cost solution for meeting the assumed constraints. Key decision variables 

represented in IPM are described in detail below. 

Generation Dispatch Decision Variables: IPM includes decision variables representing the 

generation from each model power plant1

. For each model plant, a separate generation decision 

variable is defined for each possible combination of fuel, season, model run year, and segment of 

the seasonal load duration curve applicable to the model plant. (See section 2.3.5 below for a 

discussion of load duration curves.) In the objective function, each plant’s generation decision 

variable is multiplied by the relevant heat rate and fuel price (differentiated by the appropriate step 

of the fuel supply curve) to obtain a fuel cost. It is also multiplied by the applicable variable 

operation and maintenance (VOM) cost rate to obtain the VOM cost for the plant. 

Capacity Decision Variables: IPM includes decision variables representing the capacity of each 

existing model plant and capacity additions associated with potential (new) units in each model 

run year. In the objective function, the decision variables representing existing capacity and 

capacity additions are multiplied by the relevant fixed operation and maintenance (FOM) cost 

rates to obtain the total FOM cost for a plant. The capacity addition decision variables are also 

multiplied by the investment cost and capital charge rates to obtain the capital cost associated 

with the capacity addition. 

Transmission Decision Variables: IPM includes decision variables representing the electricity 

transmission along each transmission link between model regions in each run year. In the 

objective function, these variables are multiplied by variable transmission cost rates to obtain the 

total cost of transmission across each link. 

Emission Allowance Decision Variables: For emission policies where allowance trading 

applies, IPM includes decision variables representing the total number of emission allowances for 

a given model run year that are bought and sold in that or subsequent run years. In the objective 

function, these year-differentiated allowance decision variables are multiplied by the market price 

for allowances prevailing in each run year. This formulation allows IPM to capture the intertemporal trading and banking of allowances. 

Fuel Decision Variables: For each type of fuel and each model run year, IPM defines decision 

variables representing the quantity of fuel delivered from each fuel supply region to model plants 

in each demand region. Coal decision variables are further differentiated according to coal rank 

(bituminous, sub-bituminous, and lignite), sulfur grade (see section 1 and Table 9-4), and mercury 

content (see sections 5.4.1and 1 and Table 9-7). These fuel quality decision variables do not 

appear in the IPM objective function, but in constraints which define the types of fuel that each 

model plant is eligible to use and the supply regions that are eligible to provide fuel to each 

specific model plant. 

 

1

Model plants are aggregate representations of real life electric generating units. They are used 

by IPM to model the electric power sector. For a discussion of model plants in EPA Base Case 

v.4.10, see section 4.2.6. 
2-4 

2.2.3 Constraints 

Model constraints are implemented in IPM to accurately reflect the characteristics of and the 

conditions faced by the electric sector. Among the key constraints included in EPA Base Case 

v.4.10 are: 

Reserve Margin Constraints: Regional reserve margin constraints capture system reliability 

requirements by defining a minimum margin of reserve capacity (in megawatts) per year. If 

existing plus planned capacity is not enough to satisfy the annual regional reserve margin 

requirement, the model will “build” the required level of new capacity. 

Demand Constraints: The model categorizes regional annual electricity demand into seasonal 

load segments which are used to form summer (May 1 - September 30) and winter (October 1 - 

April 30) load duration curves (LDC). The seasonal load segments when taken together represent 

all the hourly electricity load levels that must be satisfied in a region in the particular season for a 

particular model run year. As such, the LDC defines the minimum amount of generation required 

to meet the region’s electrical demand during the specific season. These requirements are 

incorporated in the model’s demand constraints. 

Capacity Factor Constraints: These constraints specify how much electricity each plant can 

generate (a maximum generation level), given its capacity and seasonal availability. 

Turn Down/Area Protection Constraints: The model uses these constraints to take into 

account the cycling capabilities of the units, i.e., whether or not they can be shut down at night or 

on weekends, or whether they must operate at all times, or at least at some minimum capacity 

level. These constraints ensure that the model reflects the distinct operating characteristics of 

peaking, cycling, and base load units. 

Emissions Constraints: IPM can consider an array of emissions constraints for SO2, NOX, 

mercury, and CO2. Emission constraints can be implemented on a plant-by-plant, regional, or 

system-wide basis. The constraints can be defined in terms of a total tonnage cap (e.g., tons of 

SO2) or a maximum emission rate (e.g., lb/MMBtu of NOX). The scope, timing, and definition of 

the emission constraints depend on the required analysis. 

Transmission Constraints: IPM can simultaneously model any number of regions linked by 

transmission lines. The constraints define either a maximum capacity on each link, or a maximum 

level of transmission on two or more links (joint limits) to different regions. 

Fuel Supply Constraints: These constraints define the types of fuel that each model plant is 

eligible to use and the supply regions that are eligible to provide fuel to each specific model plant. 

 A separate constraint is defined for each model plant. 

2.3 Key Methodological Features of IPM 

IPM is a flexible modeling tool for obtaining short- and long-term projections of production activity 

in the electric generation sector. The projections obtained using IPM are not statements of what 

will happen but what might happen given the assumptions and methodologies used. Chapters 3-

11 contain detailed discussions of the cost and performance assumptions specific to the EPA 

Base Case v.4.10. This section provides an overview of the essential methodological and 

structural features of IPM, that extend beyond the assumptions that are specific to EPA Base 

Case v.4.10. 

2.3.1 Model Plants 

Model plants are a central structural component that IPM uses in three ways: (1) to represent 

aggregations of existing generating units, (2) to represent retrofit and retirement options that are 

available to existing units, and (3) to represent potential (new) units that the model can build. 
2-5 

Existing Units: Theoretically, there is no predefined limit on the number of units that can be 

included in IPM. However, to keep model size and solution time within acceptable limits, EPA 

utilizes model plants to represent aggregations of actual individual generating units. The 

aggregation algorithm groups units with similar characteristics into model plants with a combined 

capacity and weighted-average characteristics that are representative of all the units comprising 

the model plant. Model plants are defined to maximize the accuracy of the model’s cost and 

emissions estimates by capturing variations in key features of those units that are critical in the 

base case and anticipated policy case runs. For EPA Base Case v.4.10, IPM employed an 

aggregation algorithm which allowed 15,023 actual existing electric generating units to be 

represented by 4,738 model plants. Section 4.2.6 describes the aggregation procedure used in 

the EPA Base Case v.4.10. 

Retrofit and Retirement Options: IPM also utilizes model plants to represent the retrofit and 

retirement options that are available to existing units. EPA Base Case v.4.10 provides existing 

model plants with the option to retire early and with a wide range of options for retrofitting with 

emission control equipment. (See Chapters 5 and section 7.2 in Chapter 7 for a detailed 

discussion of the options that are included in the EPA Base Case v.4.10.) 

The options available to each model plant are pre-defined at the model’s set-up. The retrofit and 

retirement options are themselves represented in IPM by model plants, which, if actuated in the 

course of a model run, take on all or a portion of the capacity initially assigned to a model plant 

which represents existing generating units. EPA Base Case v.4.10 model plants that represent 

potential (new) units are not given the option to take on a retrofit or retire. In setting up IPM, 

parent-child-grandchild relationships are pre-defined between each existing model plant (parent) 

and the specific retrofit and retirement model plants (children and grandchildren) that may replace 

the parent model plant during the course of a model run. The “child” and “grandchild” modelplants are inactive in IPM unless the model finds it economical to engage one of the options 

provided, e.g., retrofit with particular emission controls or retire early. 

Theoretically, there are no limits on the number of “child,” “grandchild,” and even “greatgrandchild” model plants (i.e., retrofit and retirement options) that can be associated with each 

existing model plant. However, model size and computational considerations dictate that the 

number of successive retrofits be limited. In EPA Base Case v.4.10, a maximum of two stages of 

retrofit options are provided (child and grandchild, but not great-grandchild). For example, an 

existing model plant may be retrofit with a limestone forced oxidation (LSFO) SO2 scrubber and 

with a selective catalytic reduction (SCR) control for NOX in one model run year (stage 1) and with 

an activated carbon injection (ACI) for mercury control in the same or subsequent run year (stage 

2). However, if it exercises this succession of retrofit options, no further retrofit or retirement 

options are possible beyond the second stage. 

Potential (New) Units: IPM also uses model plants to represent new generation capacity that 

may be built during a model run. All the model plants representing new capacity are pre-defined 

at set-up, differentiated by type of technology, regional location, and years available. When it is 

economically advantageous to do so, IPM “builds” one or more of these predefined model plants 

by raising its generation capacity from zero during the course of a model run. In determining 

whether it is economically advantageous to “build” new plants, IPM takes into account cost 

differentials between technologies, expected technology cost improvements (by differentiating 

costs based on a plant’s vintage, i.e., build year) and regional variations in capital costs that are 

expected to occur over time. 

Since EPA Base Case v.4.10 results are presented at the model plant level, EPA has developed a 

post-processor “parsing” tool designed to translate results at the model plant level into generating 

unit-specific results. The parsing tool produces unit-specific emissions, fuel use, pollution control 

retrofit and capacity projections based on model plant results. Another post-processing activity 

involves deriving inputs for air quality modeling from IPM outputs. This entails using emission 

factors to derive the levels of pollutants needed in EPA’s air quality models from emissions and 
2-6 

other parameters generated by IPM. It also involves using decision rules to assign point source 

locators to these emissions. (See Figure 1-1 for a graphical representation of the relationship of 

the post-processing tools to the overall IPM structure.) 

2.3.2 Model Run Years 

Another important structural feature of IPM is the use of model run years to represent the full 

planning horizon being modeled. Mapping each year in the planning horizon into a representative 

model run year enables IPM to perform multiple year analyses while keeping the model size 

manageable. Although IPM reports results only for model run years, it takes into account the 

costs in all years in the planning horizon. (See section 2.3.3 below for further details.) 

Often models like IPM include a final model run year that is not included in the analysis of results. 

This technique reduces the likelihood that modeling results in the last represented year will be 

skewed due to the modeling artifact of having to specify an end point in the planning horizon, 

whereas, in reality, economic decisions are likely to persist beyond that end point. Due to the 

number of model run years required by EPA for analytical purposes (six in the 2012-2050 time 

period) and a greatly expanded suite of modeling capabilities, such an approach could not be 

used in EPA Base Case v.4.10. It would have increased model size too much. However 

boundary distortions are only a potential factor in 2050, the last modeled year. In addition, any 

tendency toward end-year distortions should be reduced by the longer modeling time horizon of 

this base case and by the relatively large number of calendar years (9) that are mapped into 

model run year 2050 (see Table 7-1). Nevertheless, the possibility of residual boundary effects is 

something to bear in mind when interpreting model results for 2050. 

2.3.3 Cost Accounting 

As noted earlier in the chapter, IPM is a dynamic linear programming model that finds the least 

cost investment and electricity dispatch strategy for meeting electric demand subject to resource 

availability and other operating and environmental constraints. The cost components that IPM 

takes into account in deriving an optimal solution include the costs of investing in new capacity 

options, the cost of installing and operating pollution control technology, fuel costs, and the 

operation and maintenance costs associated with unit operations. 

Several cost accounting assumptions are built into IPM’s objective function that ensures a 

technically sound and unbiased treatment of the cost of all investment options offered in the 

model. These features include: 

All costs in IPM’s single multi-year objective function are discounted to a base year. Since the 

model solves for all run years simultaneously, discounting to a common base year ensures that 

IPM properly captures complex inter-temporal cost relationships. 

Capital costs in IPM’s objective function are represented as the net present value of levelized 

stream of annual capital outlays, not as a one-time total investment cost. The payment period 

used in calculating the levelized annual outlays never extends beyond the model’s planning 

horizon: it is either the book life of the investment or the years remaining in the planning horizon, 

whichever is shorter. This treatment of capital costs ensures both realism and consistency in 

accounting for the full cost of each of the investment options in the model. 

The cost components appearing in IPM’s objective function represent the composite cost over all 

years in the planning horizon rather than just the cost in the individual model run years. This 

permits the model to capture more accurately the escalation of the cost components over time. 

2.3.4 Modeling Wholesale Electric Markets 

Another important methodological feature worth noting about IPM is that it is designed to depict 

production activity in deregulated wholesale electric markets, not in retail markets. The model 

captures transmission costs and losses between IPM model regions. It is not designed to capture 
2-7 

retail distribution costs. However, the model implicitly includes distribution losses since net energy 

for load,2

 rather than delivered sales,3 is used to represent electric demand in the model. 

Additionally, the production costs calculated by IPM are the wholesale production costs. In 

reporting costs, the model does not include embedded costs, such as carrying charges of existing 

units that may be part of the retail cost. 

2.3.5 Load Duration Curves (LDC) 

IPM uses Load Duration Curves (LDCs) to provide realism to the dispatching of electric generating 

units. Unlike a chronological electric load curve, which is simply an hourly record of electric 

demand, the LDCs are created by rearranging the hourly chronological electric load data from the 

highest to lowest (MW) value. For modeling tractability a 6-step piecewise linear representation of 

the LDC is used in EPA applications of IPM. 

IPM can include any number of separate LDCs for any number of user defined seasons. A 

season can be a single month or several months. For example, EPA Base Case v.4.10 contains 

two seasons: summer (May 1 – September 30) and winter (October 1– April 30). Separate 

summer and winter LDCs are created for each of IPM’s model regions. Figure 2-1 below presents 

side-by-side graphs of a hypothetical chronological hourly load curve and a corresponding load 

duration curve for a season consisting of 3,672 hours. 

Figure 2-1 Hypothetical Chronological Hourly Load Curve and Seasonal Load Duration 

Curve in EPA Base Case v.4.10 

National electric demand growth assumptions (from AEO for EPA Base Case v.4.10) and NERC’s 

forecasts of peak and energy demand in each region are used to derive future seasonal load 

duration curves for each IPM run year in each IPM region from the historical data. The results of 

this process are individualized seasonal LDCs that capture the unique hourly electric demand 

profile of each region. The LDCs change over time to reflect projected future variations in 

electricity consumption patterns. 

Within IPM, LDCs are represented by a discrete number of load segments, or generation blocks, 

as illustrated in Figure 2-2. EPA Base Case v.4.10 uses six load segments in its seasonal LDCs 

 

2

Net energy for load is the electrical energy requirements of an electrical system, defined as 

system net generation, plus energy received from others, less energy delivered to others through 

interchange. It includes distribution losses. 

3

Delivered sales is the electrical energy delivered under a sales agreement. It does not include 

distribution losses. 
2-8 

for model run years 2012-2030 and 4 load segments in its LDCs for model run years 2040 and 

2050. The reduced number of load segments in the later years was adopted out of model size 

considerations and a view that having a finer grained representation of dispatch was less 

important that far into the future. Figure 2-3 illustrates and the following text describes the 6-

segment LDCs used in the base case’s earlier years. Length of time and system demand are the 

two parameters which define each segment of the load duration curve. The load segment 

represents the amount of time (along the x-axis) and the capacity that the electric dispatch mix 

must be producing (represented along the y-axis) to meet system load. Segment 1 in Figure 2-3 

generally contains one percent of the hours in the period (i.e., "season") but represents the 

highest load demand value. IPM has the flexibility to model any number of load segments; 

however the greater the number of segments, the greater the computational time required to 

reach a solution. The LDC shows all the hourly electricity load levels that must be satisfied in a 

region in a particular season of a particular model run year. Segment 1 (the “super peak” load 

segment with 1% of all the hours in the season) and Segment 2 (the “peak” load segment with 4% 

of all the hours in the season) represent all the hours when load is at the highest demand levels. 

Segments 2 through 6 represent hourly loads at progressively lower levels of demand. Plants are 

dispatched to meet this load based on economic considerations and operating constraints. The 

most cost effective plants are assigned to meet load in all 6 segments of the load duration curve. 

This is discussed in greater detail in section 2.3.6 below. 

Use of seasonal LDCs rather than annual LDCs allows IPM to capture seasonal differences in the 

level and patterns of customer demand for electricity. For example, in most regions air conditioner 

cycling only impacts customer demand patterns during the summer season. The use of seasonal 

LDCs also allows IPM to capture seasonal variations in the generation resources available to 

respond to the customer demand depicted in an LDC. For example, power exchanges between 

utility systems may be seasonal in nature. Some air regulations affecting power plants are also 

seasonal in nature. This can impact the type of generating resources that are dispatched during a 

particular season. Further, because of maintenance scheduling for individual generating units, the 

capacity and utilization for these supply resources also vary between seasons. 

Appendix 2-1 contains data and graphs of the 2012 summer and winter load duration curves in 

each of the 32 model regions in the lower continental U.S. for EPA Base Case v.4.10. 

Figure 2-2 Stylized Depiction of Load Duration Curve Used in EPA Base Case v.4.10 
2-9 

2.3.6 Dispatch Modeling 

In IPM, the dispatching of electricity is based on the variable cost of generation. In the absence of 

any operating constraints, units with the lowest variable cost generate first. The marginal 

generating unit, i.e., the power plant that generates the last unit of electricity, sets the energy 

price. Physical operating constraints also influence the dispatch order. For example, IPM uses 

turndown constraints to prevent base load units from cycling, i.e., switching on and off. Turndown 

constraints often override the dispatch order that would result based purely on the variable cost of 

generation. Variable costs in combination with turndown constraints enable IPM to dispatch 

generation resources in a technically realistic fashion. 

Figure 2-3 below depicts a highly stylized dispatch order based on the variable cost of generation 

of the resource options included in the EPA Base Case v.4.10. In Figure 2-3 a hypothetical load 

duration curve is subdivided according to the type of generation resource that responds to the 

load requirements represented in the curve. Notice that the generation resources with the lowest 

operating cost (i.e., hydro and nuclear) respond first to the demand represented in the LDC and so 

are at the bottom of “dispatch stack.” They are dispatched for the maximum possible number of 

hours represented in the LDC because of their low operating costs. Generation resources with 

the highest operating cost (i.e., peaking turbines) are at the top of the “dispatch stack,” since they 

are dispatched last and for the minimum possible number of hours. 

Figure 2-3 Stylized Dispatch Order in EPA Base Case v.4.10 

2.3.7 Reliability Modeling 

Another methodological feature of IPM is its modeling of reliability through reserve margin 

requirements, which specify the amount of installed capacity that must be in excess of peak power 

demand. IPM includes regional reserve margin requirements for each run year. Section 3.6 

contains a discussion of the reserve margin assumptions in EPA Base Case v.4.10. 
2-10 

2.3.8 Fuel Modeling 

Another key methodological feature of IPM is its capability to model the full range of fuels used for 

electric power generation. The cost, supply, and (if applicable) quality of each fuel included in the 

model are defined during model set-up. Fuel price and supply are represented in EPA Base Case 

v.4.10 in one of three alternative ways: (1) through an embedded modeling capability that 

dynamically balances supply and demand to arrive at fuel prices (natural gas), (2) through a set of 

supply curves (coal and biomass) or (3) through an exogenous price stream (fuel oil and nuclear 

fuel). With the first and second approaches, the model endogenously determines the price for that 

fuel by balancing the supply and demand. IPM uses the fuel quality information (e.g., the sulfur or 

mercury content of different types of coal from different supply regions) to determine the 

emissions resulting from the combustion of that fuel. 

The EPA Base Case v.4.10 includes coal, natural gas, fuel oil, nuclear fuel, biomass, and fossil 

and non-fossil waste as fuels for electric generation. The specific base case assumptions for 

these fuels are examined in chapters 9-11. 

2.3.9 Transmission Modeling 

IPM includes a detailed representation of existing transmission capabilities between model 

regions along with options for building new transmission lines. The maximum transmission 

capabilities between regions are specified in IPM’s transmission constraints. Additions to 

transmission lines are represented by decision variables defined for each eligible link and model 

run year. In IPM’s objective function, the decision variables representing transmission additions 

are multiplied by new transmission line investment cost and capital charge rates to obtain the 

capital cost associated with the transmission addition. Due to extensive unresolved policy issues 

and long-term uncertainty surrounding the building of new transmission lines in the U.S., EPA 

Base Case v.4.10 does not exercise IPM’s capability to model the building of new transmission 

lines. The specific transmission assumptions in EPA Base Case v.4.10 are described in section 

3.3. 

2.3.10 Perfect Competition and Perfect Foresight 

Two key methodological features of IPM are its assumptions of perfect competition and perfect 

foresight. The former means that IPM models production activity in wholesale electric markets on 

the premise that these markets subscribe to all assumptions of perfect competition. The model 

does not explicitly capture any market imperfections such as market power, transaction costs, 

informational asymmetry or uncertainty. However, if desired, appropriately designed sensitivity 

analyses or redefined model parameters can be used to gauge the impact of market imperfections 

on the wholesale electric markets. Since the retail electric market is not modeled in IPM, there 

are no assumptions about the extent or timing of retail deregulation. 

IPM’s assumption of perfect foresight implies that economic agents know precisely the nature and 

timing of the constraints that will be imposed in future years. For example, under IPM there is 

complete foreknowledge of the levels, timing, and regulatory design of emission limits that will be 

imposed over the entire modeling time horizon. In making decisions, agents optimize based on 

this foreknowledge. However, by performing an iterative series of runs, in which new emission 

limits are successively added in subsequent model run years, imperfect foresight can be 

incorporated in IPM’s projections. 

2.3.11 Air Regulatory Modeling 

One of the most notable features of IPM is its detailed and flexible modeling of air regulations. 

Treatment of air regulations is endogenous in IPM. That is, by providing a comprehensive 

representation of compliance options, IPM enables environmental decisions to be made within the 

model based on least cost considerations, rather than exogenously imposing environmental 

choices on model results. For example, unlike other models that enter allowance prices as an 

exogenous input during model set-up, IPM obtains allowance prices as an output of the 

endogenous optimization process of finding the least cost compliance options in response to air 
2-11 

regulations. (In linear programming terminology, they are the “shadow prices” of the respective 

emission constraints — a standard output produced in solving a linear programming problem.) 

IPM can capture a wide variety of regulatory program designs including cap-and-trade, commandand-control and renewable portfolio standards. IPM’s representation of cap-and-trade programs 

can include allowance banking, trading, borrowing, bonus allowance mechanisms, progressive 

flow controls or emission taxes. Air regulations can be tailored to specific geographical regions 

and can be restricted to specific seasons. Many of these regulatory modeling capabilities are 

exploited in EPA Base Case v.4.10. 

2.4 Hardware and Programming Features 

IPM produces model files in standard MPS linear programming format. IPM runs on most 

PC-platforms. Its hardware requirements are highly dependent on the size of a particular model 

run. For example, with almost 7.3 million decision variables and 1.2 million constraints, EPA Base 

Case v.4.10 is run on a 64 bit Windows Enterprise Server 2008 platform with four Intel Xeon 2.93 

GHz dual core processors and 32 GB of RAM. Due to the size of the EPA base case, a 

commercial grade solver is required. (Benchmarking tests performed by EPA's National 

Environmental Scientific Computing Center using research grade solvers yielded unacceptable 

results.) For current EPA applications of IPM, the FICO Xpress Optimization Suite 7 linear 

programming solvers are used. 

Two data processors -- a front-end and the post-processing tool -- support the model. The frontend creates the necessary input files used in IPM, while the post-processing tool maps IPM 

model-plant level outputs to individual generating units (a process called “parsing,” see section 

2.3.1) and creates input files in ORL (one record line) format as needed by EPA’s air quality 

models. 

Before it can be run, the model requires an extensive set of input parameters. These are 

discussed in Section 2.4.1 below. Results of model runs are presented in a series of detailed 

reports. These are described in Section 2.4.2 below. 

2.4.1 Data Parameters for Model Inputs 

IPM requires input parameters that characterize the US electric system, economic outlook, fuel 

supply and air regulatory framework. Chapters 3-11 contain detailed discussions of the values 

assigned to these parameters in EPA Base Case v.4.10. This section simply lists the key input 

parameters required by IPM: 

Electric System

Existing Utility Generating Resources 

• Plant Capacities 

• Heat Rates 

• Maintenance Schedule 

• Forced Outage Rate 

• Minimum Generation Requirements (Turn Down Constraint) 

• Fuels Used 

• Fixed and Variable O&M Costs 

• Emissions Limits or Emission Rates for NOx, SO2, CO2, Mercury 

• Existing Pollution Control Equipment and Retrofit Options 

• Output Profile for Non-Dispatchable Resources 

New Generating Resources 

• Cost and Operating Characteristics 

• Performance Characteristics 

• Limitations on Availability 
2-12 

Other System Requirements

• Inter-regional Transmission Capabilities 

• Reserve Margin Requirements for Reliability 

• Area Protection 

• System Specific Generation Requirements 

• Regional Specification 

Economic Outlook 

Electric Demand 

• Firm Regional Electric Demand 

• Load Curves 

Financial Outlook 

• Capital Charge Rate 

• Discount Rate 

Fuel Supply 

Fuel Supply Curves for Coal, Natural Gas, and Biomass 

Fuel Price 

Fuel Quality 

Transportation Costs for Coal, Natural Gas, and Biomass 

Air Regulatory Outlook 

Air Regulations for NOx, SO2, CO2, Mercury 

Other Air Regulations 

2.4.2 Model Outputs 

IPM produces a variety of output reports. These range from extremely detailed reports, which 

describe the results for each model plant and run year, to summary reports, which present results 

for regional and national aggregates. Individual topic areas can be included or excluded at the 

user’s discretion. Since the entire model solution is stored, IPM can generate additional detailed 

reports from the stored solution as needed. Standard IPM reports cover the following topics: 

• Generation 

• Capacity mix (by plant type and presence or absence of emission controls) 

• Capacity additions and retirements 

• Capacity and energy prices 

• Power production costs (capital VOM, FOM and fuel costs) 

• Fuel consumption 

• Fuel supply and demand 

• Fuel prices for coal, natural gas, and biomass 

• Emissions (NOX, SO2, CO2, and Hg) 

• Emission allowance prices 
Appendix 2-1.1 

Appendix 2-1 Load Duration Curves Used in EPA Base Case v.4.10 

This is a small exerpt of the data and graphs in Appendix 2-1. The complete data set in spreadsheet format and complete 

downloaded via the link found at www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev410.htm

Month 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 

Hours 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 

Day 

Hours 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 

AZNM 11,182 10,866 10,659 10,628 10,724 10,969 11,250 11,306 11,553 11,707 11,533 11,294 10,977 10,643 10,367 10,304 10,515 11,676 12,475 12,511 12,414 

CA-N 11,127 11,196 11,477 11,976 12,082 12,262 12,645 12,877 12,812 12,615 12,457 12,274 12,418 13,410 15,256 15,213 14,885 14,386 13,566 12,501 11,793 

CA-S 15,323 14,636 14,234 14,056 14,129 14,347 14,275 14,448 14,940 15,427 15,690 15,785 15,713 15,619 15,598 15,599 16,951 19,009 19,111 18,803 18,261 

COMD 10,119 9,763 9,444 9,264 9,140 9,137 9,220 9,419 9,414 9,489 9,698 9,908 10,016 10,032 10,048 9,987 9,965 10,552 11,448 11,495 11,428 

DSNY 2,861 2,708 2,597 2,526 2,497 2,519 2,575 2,638 2,758 2,936 3,107 3,229 3,291 3,286 3,256 3,282 3,454 3,711 3,710 3,611 3,489 ENTG 14,747 14,695 14,588 14,491 14,478 14,554 14,924 15,411 15,669 16,072 16,337 16,392 16,108 15,654 15,183 14,898 14,956 15,495 16,581 17,184 17,320 

ERCT 29,987 29,796 29,710 29,857 30,395 31,487 32,637 33,019 33,024 33,208 32,996 32,351 31,188 30,011 28,906 28,277 28,409 30,699 34,030 34,697 35,016 

FRCC 19,757 18,688 17,471 16,766 16,412 16,476 16,780 17,054 18,787 21,128 23,288 24,514 25,262 25,431 25,229 25,051 24,845 25,636 26,465 25,716 24,569 

GWAY 9,016 8,918 8,852 8,782 8,857 8,995 9,200 9,298 9,475 9,781 10,000 10,019 9,874 9,718 9,546 9,509 9,863 10,775 10,895 10,860 10,778 

LILC 2,189 2,080 1,991 1,937 1,910 1,909 1,927 1,949 1,995 2,085 2,192 2,276 2,325 2,342 2,348 2,369 2,485 2,615 2,607 2,568 2,517 

MACE 14,997 14,408 13,928 13,663 13,575 13,629 13,818 14,003 14,204 14,781 15,363 15,771 16,002 16,044 16,064 16,133 16,702 17,567 17,540 17,324 17,013 MACS 6,474 6,267 6,056 5,908 5,885 5,961 6,070 6,114 6,194 6,458 6,742 6,963 7,051 7,022 6,934 6,938 7,038 7,519 7,543 7,500 7,355 

MACW 6,418 6,000 5,606 5,463 5,441 5,552 5,719 5,905 6,206 6,713 7,208 7,495 7,516 7,418 7,246 7,254 7,591 8,267 8,286 8,185 8,036 

MECS 9,332 9,063 8,867 8,732 8,683 8,758 8,882 9,032 9,078 9,272 9,582 9,829 9,938 9,946 9,912 9,955 10,149 10,693 10,910 10,846 10,765 

MRO 20,437 19,616 19,012 18,599 18,593 18,901 19,603 20,370 20,737 21,386 21,798 21,936 21,733 21,288 20,761 20,829 21,990 25,094 26,505 26,416 25,724 

NENG 12,380 11,716 11,272 11,035 11,020 11,181 11,502 11,867 12,438 13,283 14,097 14,625 14,769 14,685 14,545 14,670 15,597 16,268 16,043 15,595 14,985 

NWPE 6,242 6,086 6,018 5,990 6,027 6,149 6,296 6,431 6,605 6,759 6,818 6,815 6,762 6,673 6,621 6,652 7,010 7,390 7,370 7,273 7,145 

NYC 4,838 4,645 4,449 4,295 4,237 4,238 4,315 4,376 4,477 4,671 4,889 5,058 5,175 5,246 5,304 5,354 5,507 5,687 5,664 5,593 5,500 

PNW 19,729 19,289 19,068 19,035 19,342 19,827 20,403 20,925 21,531 22,174 22,697 22,843 22,768 22,505 22,248 22,334 23,178 23,768 23,545 23,064 22,354 

RFCO 17,029 16,735 16,335 16,166 16,167 16,397 16,785 17,214 17,480 17,852 18,625 19,267 19,642 19,673 19,682 19,755 20,141 21,036 21,358 21,162 20,915 

RFCP 21,425 20,589 19,799 19,483 19,512 19,932 20,607 21,420 22,257 23,435 24,540 25,256 26,276 26,255 26,253 26,421 27,018 28,753 29,207 29,066 28,838 

RMPA 5,995 5,904 5,914 6,068 6,205 6,281 6,484 6,718 6,783 6,736 6,613 6,641 6,568 6,599 7,137 8,185 8,384 8,247 8,069 7,693 6,966 

SNV 2,666 2,637 2,609 2,601 2,602 2,621 2,595 2,515 2,486 2,488 2,494 2,491 2,477 2,446 2,432 2,439 2,576 2,786 2,805 2,788 2,762 
Appendix 2-1.2 

ERCT 2012 Summer

0

10000200003000040000500006000070000

1 301 601 901 1201 1501 1801 2101 2401 2701 3001 

Hour

MW
Appendix 2-1.3 

ERCT 2012 Winter

0

100002000030000400005000060000

1 301 601 901 1201 1501 1801 2101 2401 2701 3001 3301 3601 3901 4201 4501 

Hour

MW
3-1 

3 Power System Operation Assumptions 

This section describes the assumptions pertaining to the North American electric power system as 

represented in EPA Base Case v.4.10. 

3.1 Model Regions 

EPA Base Case v.4.10 models the US power sector in the contiguous 48 states and the District of 

Columbia and the Canadian power sector in the 10 provinces (with Newfoundland and Labrador 

represented as two regions on the electricity network even though politically they constitute a 

single province4

) as an integrated network. Alaska, Hawaii, Puerto Rico, and US Virgin Islands 

are represented in Base Case v.4.10 as separate entities with their own self contained electricity 

grids. 

There are 32 IPM model regions covering the US 48 states and District of Columbia. The IPM 

model regions are approximately consistent with the configuration of the 8 NERC regions, being 

disaggregations of North American Reliability Council (NERC) control areas. An attempt has been 

made to have the US IPM model regions reflect the administrative structure of regional 

transmission organizations (RTOs) and independent system operators (ISOs). Further 

disaggregation into 32 model regions allows a more accurate characterization of the operation of 

the US power markets by providing the ability to represent transmission bottlenecks within the 8 

NERC regions and across RTOs and ISOs. 

Disaggregations that were made in the most recent previous IPM base case were retained in 

Base Case 2010. Notable disaggregations include 

• NERC region RFC (Reliability First Corporation) includes three portions of former NERC 

regions — the non-Kentucky part of ECAR, MAAC, and a portion of MAIN. The remaining 

portion of MAIN has been renamed COMD. ECAR has been disaggregated into RFCO, 

MECS, and RFCP and MAAC has been disaggregated into MACE, MACS, and MACW. 

 

• NERC subregion WECC-AZ-NM-SNV has been disaggregated into AZNM and SNV 

• NERC subregion WECC-California ISO has been disaggregated into CA-N and CA-S 

• NERC Region SERC has been disaggregated into 7 IPM regions (ENTG, SOU, VACA, 

VAPW, TVA, TVAK (formerly ECAK), and GWAY (formerly a portion of MANO). 

Several region boundaries were adjusted to reflect recent organizational changes. There were 

also several name changes: MANO to GWAY, ECAM to RFCO, ECAP to RFCP, and ECAK to 

TVAK. 

The 11 Canadian model regions are defined strictly along provincial political boundaries. 

Figure 3-1 contains a map showing all the EPA Base Case 2010 model regions. Table 3-1 

defines the abbreviated region names appearing on the map and gives an approximate crosswalk 

between the IPM model regions, the NERC regions, and regions used in the Energy Information 

Administration’s (EIA’s) National Energy Model System (NEMS) which is the basis for EIA’s 

Annual Energy Outlook (AEO) reports. 

3.2 Electric Load Modeling 

Net energy for load and net internal demand are inputs to IPM that together are used to represent 

the grid-demand for electricity. Net energy for load is the projected annual electric grid-demand, 

prior to accounting for intra-regional transmission and distribution losses. Net internal demand 

 

4

This results in a total of 11 Candian model regions being represented in EPA Base Case v.4.10 
3-2 

(peak demand) is the maximum hourly demand within a given year after removing interruptible 

demand. Table 3-2 shows the electric demand assumptions (expressed as net energy for load) 

used in EPA Base Case v.4.10. It is based on the net energy for load in AEO 20105

. 

Figure 3-1 EPA Base Case v.4.10 Model Regions 

For purposes of documentation, Table 3-2 presents the national net energy for load. However, 

EPA Base Case v.4.10 models regional breakdowns of net energy for load. The regional net 

energy for load is derived from the national net energy for load based on the regional demand 

distribution in NERC electric demand forecasts. Model regions that represent subregions of a 

NERC region are apportioned their net energy for load based on the regional load shapes, which 

are developed by aggregating load for control areas within each model region. 

 

5

The electricity demand in EPA Base Case v.4.10 for the U.S. lower 48 states and the District of 

Columbia is obtained by summing the "Total Net Energy for Load" for the NEMS Electric Market 

Module regions as reported in the "Electric Power Projections for Electricity Market Module 

Regions -- Electricity and Renewable Fuel Tables 72-84" at 

http://www.eia.doe.gov/oiaf/aeo/aeoref_tab.html. 
3-3 

Table 3-1 Mapping of NERC Regions and NEMS Regions with EPA Base Case v.4.10 Model 

Regions 

NERC 

Region 

NEMS 

Region 

Model 

Region Model Region Description 

TRE ERCOT ERCT Texas Regional Entity 

FRCC FL FRCC Florida Reliability Coordinating Council 

MAPP MRO Midwest Regional Planning Organization MRO 

MAIN WUMS Wisconsin-Upper Michigan 

NE NENG New England Power Pool 

DSNY Downstate New York 

LILC Long Island Company 

NYC New York City 

NPCC NY 

UPNY Upstate New York 

RFCO Reliability First Corporation - MISO 

ECAR MECS Michigan Electric Coordination System 

RFCP Reliability First Corporation - PJM 

MACE Legacy Mid-Atlantic Area Council - East 

MAAC MACS Legacy Mid-Atlantic Area Council - South 

MACW Legacy Mid-Atlantic Area Council - West 

RFC 

MAIN COMD Commonwealth Edison 

MAIN GWAY Gateway 

ECAR TVAK Tennessee Valley Authority - MISO-KY 

SOU Southern Company 

TVA Tennessee Valley Authority 

ENTG Entergy 

VACA Virginia-Carolinas 

SERC 

STV 

VAPW Dominion Virginia Power 

SPPN Southwest Power Pool - North SPP SPP 

SPPS Southwest Power Pool - South 

AZNM Western Electricity Coordinating Council - Arizona, New 

Mexico 

WECCAZ-NMSNV 

RA 

SNV Western Electricity Coordinating Council - Southern Nevada 

WECC- CA-N Western Electricity Coordinating Council - California North 

California 

ISO 

CNV 

CA-S Western Electricity Coordinating Council - California South 

PNW Western Electricity Coordinating Council - Pacific Northwest WECCNWPP NWP 

NWPE Western Electricity Coordinating Council - Northwest Power 

Pool East 

WECCRMPA RA RMPA Western Electricity Coordinating Council - Rocky Mountain 

Power Area 

CNAB Alberta 

CNBC British Columbia 

CNMB Manitoba 

CNNB New Brunswick 

CNNF Newfoundland 

CNNL Labrador 

CNNS Nova Scotia 

Canada 

CNON Ontario 
3-4 

NERC 

Region 

NEMS 

Region 

Model 

Region Model Region Description 

CNPE Prince Edward Island 

CNPQ Quebec 

CNSK Saskatchewan 

ALSK Alaska 

HAWI Hawaii 

VIUS U.S. Virgin Islands Other 

PRCW Puerto Rico 

 

 

Table 3-2 Electric Load Assumptions in EPA Base Case v.4.10 

Year Net Energy for Load 

(Billions of kWh) 

2012 4,043 

2015 4,086 

2020 4,302 

2030 4,703 

2040 5,113 

2050 5,568 

Note:

This data is an aggregation of the model-region-specific net energy loads 

used in the EPA Base Case v.4.10. 

3.2.1 Demand Elasticity 

EPA Base Case v.4.10 has the capability to model the impact of the price of power on electricity 

demand. However, this capability is typically only exercised for sensitivity analyses where 

different price elasticities of demand are specified for purposes of comparative analysis. The 

default base case assumption is that the electricity demand shown in Table 3-2 is not affected by 

price and must be met, i.e., the price elasticity of demand is zero6

. 

3.2.2 Net Internal Demand (Peak Demand) 

EPA Base Case v.4.10 has separate regional winter and summer peak demand values, as 

derived from each region’s seasonal load duration curve (found in Appendix 2-1). Peak projections 

were estimated based on AEO 2010 load factors and the estimated energy demand projections 

shown in Table 3-2. Table 3-3 (“National Non-Coincidental Net Internal Demand”) illustrates the 

national sum of each region’s winter and summer peak demand. Because each region’s seasonal 

peak demand need not occur at the same time, the national peak demand is defined as noncoincidental.

 

6

Occasionally, e.g., when performing modeling of climate policies, the demand assumptions 

shown in Table 3-2 will be replaced with projections of demand from economy-wide computable 

general equilibrium (CGE) models which themselves take into account demand elasticity. 

However, even in such cases the IPM demand elasticity capabilities will not be utilized and the 

resulting IPM runs will be considered “policy” rather than “base case” runs. 
3-5 

Table 3-3 National Non-Coincidental Net Internal Demand 

Peak Demand (GW) Year 

Winter Summer 

2012 646 758 

2015 655 771 

2020 693 816 

2030 768 908 

2040 843 1,001 

2050 929 1,105 

Note:

This data is an aggregation of the model-region-specific peak 

demand loads used in the EPA Base Case v.4.10. 

3.2.3 Regional Load Shapes 

EPA uses year 2007 as the meteorological year in its air-quality modeling. In order for EPA Base 

Case v.4.10 to be consistent, the year 2007 was selected as the “normal weather year”7

 for all 

IPM regions. The proximity of the 2007 cumulative annual heating degree days (HDDs) and 

cooling degree days (CDDs) to the long-term average cumulative annual HHDs and CDDs over 

the period 1971 to 2000 was estimated and found to be reasonable close. The 2007 

chronological hourly load data were assembled by aggregating individual utility load curves taken 

from Federal Energy Regulatory Commission Form 714 data. 

3.3 Transmission 

The United States and Canada can be broken down into several power markets that are 

interconnected by a transmission grid. As discussed earlier, EPA Base Case 4.10 characterizes 

the U.S. lower 48 states, the District of Columbia, and Canada into 43 different power market 

regions by means of 32 model regions in the U.S. and 11 in Canada. EPA Base Case 4.10 

includes explicit assumptions regarding the transmission grid connecting these modeled power 

markets. This section details the assumptions about the transfer capabilities, wheeling costs and 

inter-regional transmission used in EPA Base Case 4.10. 

3.3.1 Inter-regional Transmission Capability 

Table 3-48

 shows the firm and non-firm Total Transfer Capabilities (TTCs) between model regions. 

TTC is a metric that represents the capability of the power system to import or export power 

reliably from one region to another. The purpose of TTC analysis is to identify the sub-markets 

created by key commercially significant constraints. Firm TTCs, also called Capacity TTCs, 

specify the maximum power that can be transferred reliably, even after the contingency loss of a 

single transmission system element such as a transmission line or a transformer (N-1). Firm 

TTCs provide a high level of reliability and are therefore used for capacity transfers. Non-firm 

TTCs, also called Energy TTCs, represent the maximum power that can be transferred reliably 

when all facilities are under normal operation (N-0). They specify the sum of the maximum firm 

transfer capability between sub-regions plus incremental curtailable non-firm transfer capability. 

Non-firm TTCs are used for energy transfers since they provide a lower level of reliability than 

 

7

The term “normal weather year” refers to a representative year whose weather is closest to the 

long-term (e.g., 35 year) average weather. The selection of a “normal weather year” can be 

made, for example, by comparing the cumulative annual heating degree days (HDDs) and cooling 

degree days (CDDs) in a candidate year to the long-term average. For any individual day, heating 

degree days indicate how far the average temperature fell below 65 degrees F; cooling degree 

days indicate how far the temperature averaged above 65 degrees F. Cumulative annual heating 

and cooling degree days are the sum of all the HDDs and CDDs, respectively, in a given year. 

8

In the column headers in Table 3-4 the term “Energy (MW)” is equivalent to non-firm TTCs and 

the term “Capacity (MW)” is equivalent to firm TTCs. 
3-6 

Firm TTCs, and transactions using Non-firm TTCs can be curtailed under emergency or 

contingency conditions. 

Table 3-4 Annual Transmission Capabilities of U.S. Model Regions in EPA Base Case 

v.4.10 

From To Energy 

(MW) 

Capacity 

(MW) 

Wheeling Charge 

(mills/kWh) 

CA-S 3,627 2,428 2.9 

NWPE 300 300 -- 

RMPA 690 690 -- 

SNV 4,634 4,634 -- 

AZNM 

SPPS 400 400 2.9 

CA-S 3,700 3,700 -- 

CA-N NWPE 150 100 2.9 

PNW 3,675 3,675 2.9 

AZNM 3,627 2,428 2.9 

CA-N 3,000 2,400 -- 

NWPE 1,400 1,400 2.9 

PNW 3,100 3,100 2.9 

CA-S 

SNV 4,688 4,688 2.9 

GWAY 2,050 2,050 2.9 

MRO 825 825 2.9 

RFCO 1,620 1,110 2.9 

RFCP 4,500 788 -- 

COMD 

WUMS 825 825 2.9 

LILC 1,290 1,290 -- 

MACE 2,000 2,000 2.9 

NENG 1,120 1,120 2.9 

NYC 3,700 3,700 -- 

DSNY 

UPNY 3,400 3,400 -- 

GWAY 910 140 2.9 

MRO 150 150 2.9 

SOU 2,250 2,250 2.9 

SPPN 1,120 140 2.9 

SPPS 4,494 735 2.9 

ENTG 

TVA 1,681 1,681 2.9 

ENTG 1,001 1,001 2.9 ERCT SPPS 979 979 2.9 

FRCC SOU 2,000 2,000 2.9 

COMD 1,100 1,100 2.9 

ENTG 2,804 2,100 2.9 

MRO 405 405 -- 

RFCO 6,299 1,848 -- 

SPPN 285 285 2.9 

TVA 1,812 1,812 2.9 

GWAY 

TVAK 200 200 2.9 

DSNY 530 530 -- 

MACE 650 590 2.9 

LILC 

NENG 616 616 2.9 
3-7 

From To Energy 

(MW) 

Capacity 

(MW) 

Wheeling Charge 

(mills/kWh) 

NYC 420 420 -- 

DSNY 500 500 2.9 

LILC 650 521 2.9 

MACW 2,000 2,000 -- MACE 

NYC 1,200 600 2.9 

MACW 3,500 3,000 -- 

MACS RFCP 2,500 750 -- 

VAPW 2,600 2,600 -- 

MACE 6,200 5,800 -- 

MACS 5,000 1,350 -- 

RFCO 2,208 504 2.9 

RFCP 3,300 2,044 -- 

MACW 

UPNY 1,085 1,085 2.9 

CNON 1,968 1,968 2.9 

MECS RFCO 2,776 1,904 -- 

RFCP 3,900 683 2.9 

COMD 610 610 2.9 

CNON 100 100 2.9 

CNSK 165 165 2.9 

ENTG 2,000 2,000 2.9 

GWAY 320 320 -- 

NWPE 200 200 2.9 

RMPA 310 310 2.9 

SPPN 1,494 1,494 2.9 

MRO 

WUMS 800 800 -- 

CNNB 1,000 1,000 2.9 

CNPQ 803 803 2.9 

DSNY 980 980 2.9 NENG 

LILC 616 473 2.9 

AZNM 265 265 -- 

CA-N 160 120 2.9 

CA-S 1,920 1,920 2.9 

MRO 150 150 2.9 

PNW 2,002 2,002 -- 

RMPA 749 749 -- 

NWPE 

SNV 300 250 -- 

DSNY 1,999 1,999 -- NYC LILC 175 175 -- 

CA-N 4,000 4,000 2.9 

CA-S 3,100 3,100 2.9 

CNBC 2,000 1,000 2.9 PNW 

NWPE 1,505 1,505 -- 

COMD 2,760 1,360 2.9 

GWAY 7,078 3,504 -- 

MACW 3,100 2,274 2.9 

RFCO 

MECS 4,603 825 -- 
3-8 

From To Energy 

(MW) 

Capacity 

(MW) 

Wheeling Charge 

(mills/kWh) 

RFCP 12,908 7,951 2.9 

TVAK 815 270 2.9 

COMD 3,100 3,100 -- 

MACS 2,500 350 -- 

MACW 3,900 1,075 -- 

MECS 3,700 1,762 2.9 

RFCO 15,041 8,525 2.9 

TVA 1,000 1,000 2.9 

TVAK 1,000 537 2.9 

VACA 3,002 2,042 2.9 

RFCP 

VAPW 3,080 953 -- 

AZNM 690 690 -- 

RMPA MRO 310 310 2.9 

NWPE 735 735 -- 

AZNM 4,785 4,785 -- 

SNV CA-S 4,688 4,688 2.9 

NWPE 300 300 -- 

ENTG 2,950 2,950 2.9 

FRCC 3,600 3,600 2.9 

TVA 3,742 3,742 2.9 SOU 

VACA 1,358 1,358 2.9 

ENTG 3,745 1,260 2.9 

GWAY 1,200 1,200 2.9 

MRO 600 600 2.9 SPPN 

SPPS 700 700 -- 

AZNM 400 400 2.9 

ENTG 9,030 2,310 2.9 

ERCT 650 650 2.9 SPPS 

SPPN 1,200 1,200 -- 

ENTG 2,919 2,919 2.9 

GWAY 1,550 1,550 2.9 

RFCP 1,500 263 2.9 

SOU 2,258 2,258 2.9 

TVAK 2,000 1,073 -- 

TVA 

VACA 664 664 2.9 

GWAY 200 200 2.9 

RFCO 3,365 1,225 2.9 

RFCP 1,000 175 2.9 TVAK 

TVA 1,500 632 -- 

CNON 2,000 1,325 2.9 

CNPQ 1,000 1,000 2.9 

DSNY 4,550 4,550 -- 

MACW 735 735 2.9 

 UPNY 

NENG 150 150 2.9 

RFCP 4,117 438 2.9 

SOU 3,242 3,242 2.9 

VACA 

TVA 3,586 3,586 2.9 
3-9 

From To Energy 

(MW) 

Capacity 

(MW) 

Wheeling Charge 

(mills/kWh) 

VAPW 1,942 1,942 2.9 

MACS 2,100 2,100 -- 

VAPW RFCP 5,460 1,952 -- 

VACA 1,849 1,849 2.9 

COMD 1,125 1,125 2.9 WUMS MRO 270 270 -- 

The amount of energy and capacity transferred on a given transmission link is modeled on a 

seasonal (summer and winter) basis for all run years in the EPA Base Case 4.10. All of the 

modeled transmission links have the same Total Transfer Capabilities for both the winter and 

summer seasons, which means that the maximum firm and non-firm TTCs for each link is the 

same for both winter and summer. Wherever available, the maximum values for firm and non-firm 

TTCs were obtained from public sources. Where public sources were not available, the maximum 

values for firm and non-firm TTCs are based on ICF’s expert view. 

It should be noted that each transmission link between model regions shown in Table 3-4 

represents a one-directional flow of power on that link. This implies that the maximum amount of 

flow of power possible from region A to region B may be more or less than the maximum amount 

of flow of power possible from region B to region A. 

3.3.2 Joint Transmission Capacity and Energy Limits 

Table 3-5 shows the annual joint limits to the transmission capabilities between model regions, 

which are identical for the firm (capacity) and non-firm (energy) transfers. The joint limits were 

developed from the 2004 NERC Summer Assessment and 2004 NERC Winter Assessment. A 

joint limit represents the maximum simultaneous firm or non-firm power transfer capability of a 

group of interfaces. It restricts the amount of firm or non-firm transfers between one model region 

(or group of model regions) and a different group of model regions). For example, the New 

England model region is connected to multiple model regions contained in the state of New York, 

with each link between New England and a New York model region described by its own TTCs. 

However, there is a maximum limit on the total amount of transfers that the New England region 

may transfer to the whole of New York, which is represented by the annual joint capacity limit 

between the New England model region and the relevant New York model regions. 

Table 3-5 Annual Joint Capacity and Energy Limits to Transmission Capabilities Between 

Model Regions in EPA Base Case v.4.10 

Region Connections Transmission Path Joint Constraint Limit 

RFCO to MACW 

ECAR to MAAC RFCP to MACS 

RFCP to MACW 

1,385 

RFCO to COMD 

RFCP to COMD 

RFCO to GWAY ECAR to MAIN 

TVAK to GWAY 

2,593 

TVAK to TVA ECAR to TVA RFCP to TVA 3,561 

RFCP to VACA ECAR to VACAR RFCP to VAPW 2,022 

ENTG to SPPN ENTG to SPP ENTG to SPPS 338 
3-10 

Region Connections Transmission Path Joint Constraint Limit 

LILC to DSNY LILC to NYC & DSNY LILC to NYC 530 

MACS to RFCP 

MAAC to ECAR MACW to RFCO 

MACW to RFCP 

4,715 

MACE to DSNY 

MACE to LILC 

MACE to NYC MAAC to NPCC 

MACW to UPNY 

1,708 

COMD to RFCO 

COMD to RFCP 

GWAY to TVAK MAIN to ECAR 

GWAY to RFCO 

3,649 

COMD to MRO 

MAIN to MAPP GWAY to MRO 

WUMS to MRO 

962 

MRO to COMD 

MAPP to MAIN MRO to GWAY 

MRO to WUMS 

1,238 

MRO to NWPE MAPP to WECC MRO to RMPA 710 

NENG to DSNY 

NENG to NY NENG to UPNY 

NENG to LILC 

1,550 

DSNY to MACE 

LILC to MACE 

NYC to MACE NPCC to MAAC 

UPNY to MACW 

2,353 

DSNY to NENG 

NY to NENG LILC to NENG 

UPNY to NENG 

1,750 

DSNY to LILC NYC & DSNY to LILC NYC to LILC 1,465 

SPPN to ENTG SPP to ENTG SPPS to ENTG 1,362 

TVA to TVAK TVA to ECAR TVA to RFCP 1,226 

VACA to RFCP VACAR to ECAR VAPW to RFCP 4,278 

NWPE to MRO WECC to MAPP RMPA to MRO 660 

Note: 

Source: 2004 NERC Summer Assessment, 2004 NERC Winter Assessment 

3.3.3 Transmission Link Wheeling Charge 

Transmission wheeling charge is the cost of transferring electric power from one region to another 

using the transmission link. The EPA Base Case 4.10 assumes a wheeling charge of 2.9 mills per 

kWh for electricity transmission between IPM model regions that fall within different market 
3-11 

regions, such as transmission between Northern California and the Pacific Northwest. However, 

the wheeling charge is not applied to transmission between model regions that are within the 

same market region, such as transmission between Northern California (model region CA-N) and 

Southern California (model region CA-S). The wheeling charge applied between IPM model 

regions can be found in Table 3-4. 

3.3.4 Transmission Losses 

The EPA Base Case 4.10 assumes a two percent inter-regional transmission loss of energy 

transferred, in line with EIA’s Annual Energy Outlook (AEO) 2010. 

3.4 International Imports 

The U.S. electric power system is connected with the transmission grids in Canada and Mexico 

and the three countries actively trade in electricity. The Canadian power market is endogenously 

modeled in EPA Base Case v.4.10 but Mexico is not. International electric trading between the 

U.S. and Mexico is represented by an assumption of net imports based on information from AEO 

2010. Table 3-6 summarizes the assumptions on net imports into the US from Mexico. 

Table 3-6 International Electricity Imports in EPA Base Case v.4.10 

 2012 2015 2020 2030 2040 2050 

Net Imports from Mexico 

(billions kWh) 1.57 1.57 1.11 0.89 0.89 0.89 

Notes:

Imports & exports transactions from Canada are endogenously modeled in IPM. 

Source: AEO 2010 

3.5 Capacity, Generation, and Dispatch 

While the capacity of existing units is an exogenous input into IPM, the dispatch of those units is 

an endogenous decision that the model makes. The capacity of existing generating units included 

in EPA Base Case v.4.10 can be found in the National Electrical Energy Data System (NEEDS 

v.4.10), a database which provides IPM with information on all currently operating and plannedcommitted electric generating units. NEEDS v.4.10 is discussed in full in Chapter 4. 

A unit’s generation over a period of time is defined by its dispatch pattern over that duration of 

time. IPM determines the optimal economic dispatch profile given the operating and physical 

constraints imposed on the unit. In EPA Base Case v.4.10 unit specific operational and physical 

constraints are generally represented through availability and turndown constraints. However, for 

some unit types, capacity factors are used to capture the resource or other physical constraints on 

generation. The two cases are discussed in more detail in the following sections. 

3.5.1 Availability 

Power plant “availability” is the percentage of time that a generating unit is available to provide 

electricity to the grid. Availability takes into account both scheduled maintenance and forced 

outages; it is formally defined as the ratio of a unit’s available hours adjusted for derating of 

capacity (due to partial outages) to the total number of hours in a year when the unit was in an 

active state. For most types of units in IPM, availability parameters are used to specify an upper 

bound on generation to meet demand. Table 3-7 summarizes the availability assumptions used in 

EPA Base Case v.4.10. They are based on data from North American Electric Reliability 

Council’s Generating Availability Data System (NERC GADS) 2001 to 2005 and AEO 2010. 

Appendix 3-9 shows the availability assumptions for all generating units in EPA Base Case v.4.10. 
3-12 

Table 3-7 Availability Assumptions in the EPA Base Case v.4.10 

Unit Type Annual Availability (%) 

Biomass 83 

Coal Steam 32 - 95 

Combined Cycle 85 

Combustion Turbine 89 - 91 

Gas/Oil Steam 78 - 92 

Geothermal 87 

IGCC 85 

Pumped Storage 90 

Solar 90 

Wind 95 

Notes:

Values shown are a range of all of the values modeled within the EPA Base Case v.4.10. 

Availabilities of coal steam units are based on historical capacity factors. 

In the EPA Base Case v.4.10, separate seasonal (summer and winter) availabilities are defined. 

For the fossil and nuclear unit types shown in Table 3-7, summer and winter availabilities differ 

only in that no planned maintenance is assumed to be conducted during the on-peak summer 

(June, July and August) months. Characterizing the availability of hydro, solar and wind 

technologies is more complicated due to the seasonal and locational variations of the resources. 

The procedures used to represent seasonal variations in hydro are presented in section 3.5.2 and 

of wind and solar in section 4.4.5. 

3.5.2 Capacity Factor 

Generation from certain types of units is constrained by resource limitations. These technologies 

include hydro, wind and solar. For such technologies, IPM uses capacity factors or generation 

profiles, not availabilities, to define the upper bound on the generation obtainable from the unit. 

The capacity factor is the percentage of the maximum possible power generated by the unit. For 

example, a photovoltaic solar unit would have a capacity factor of 27% if the usable sunlight were 

only available that percent of the time. For such units, explicit capacity factors or generation 

profiles mimic the resource availability. The seasonal capacity factor assumptions for hydro 

facilities contained in Table 3-8 were derived from EIA Form 906 from 2002 through 2006 data. A 

discussion of capacity factors and generation profiles for wind and solar technologies is contained 

in section 4.4.5 and Appendices 4-1 and 4-2. 

Table 3-8 Seasonal Hydro Capacity Factors (%) in the EPA Base Case v.4.10 

Model 

Region 

Winter Capacity 

Factor 

Summer Capacity 

Factor 

Annual Capacity 

Factor 

AZNM 27.4% 32.2% 29.4% 

CA-N 36.7% 50.1% 42.3% 

CA-S 38.7% 50.4% 43.6% 

COMD 40.6% 45.5% 42.6% 

DSNY 57.8% 50.2% 54.6% 

ENTG 35.4% 32.5% 34.2% 

ERCT 13.5% 19.6% 16.1% 

FRCC 48.4% 47.4% 48.0% 

GWAY 19.2% 22.5% 20.6% 

MACE 30.9% 29.2% 30.2% 

MACS 14.8% 18.7% 16.4% 

MACW 47.5% 33.7% 42.3% 

MECS 54.1% 56.9% 55.3% 
3-13 

Model 

Region 

Winter Capacity 

Factor 

Summer Capacity 

Factor 

Annual Capacity 

Factor 

MRO 31.8% 43.7% 36.8% 

NENG 44.9% 41.1% 43.3% 

NWPE 28.7% 47.6% 36.6% 

PNW 40.6% 44.0% 42.0% 

RFCO 66.0% 89.2% 75.6% 

RFCP 32.7% 30.9% 31.9% 

RMPA 18.0% 31.5% 23.7% 

SNV 18.0% 23.3% 20.2% 

SOU 25.3% 22.1% 24.0% 

SPPN 16.5% 17.8% 17.0% 

SPPS 21.2% 27.2% 23.7% 

TVA 43.2% 37.1% 40.7% 

TVAK 32.4% 38.6% 35.0% 

UPNY 66.8% 63.1% 65.2% 

VACA 23.7% 22.8% 23.3% 

VAPW 22.8% 19.0% 21.2% 

WUMS 52.6% 57.3% 54.6% 

Note: 

Annual capacity factor is provided for information purposes only. It is not directly used in 

modeling. 

Capacity factors are also used to define the upper bound on generation obtainable from nuclear 

units. This rests on the assumption that nuclear units will dispatch to their availability, and, 

consequently, capacity factors and availabilities are equivalent. The capacity factors (and, 

consequently, the availabilities) of existing nuclear units in EPA Base Case v.4.10 vary from 

region to region and over time. Further discussion of the nuclear capacity factor assumptions in 

EPA Base Case v.4.10 is contained in Section 4.5. 

3.5.3 Turndown 

Turndown assumptions in EPA Base Case v.4.10 are used to prevent coal and oil/gas steam units 

from operating strictly as peaking units, which would be inconsistent with their operating 

capabilities. Specifically, the turndown constraints in EPA Base Case v.4.10 require coal steam 

units to dispatch no less than 50% of the unit capacity in the five base- and mid-load segments of 

the load duration curve in order to dispatch 100% of the unit in the peak load segment of the LDC. 

 Oil/gas steam units are required to dispatch no less than 25% of the unit capacity in the five baseand mid-load segments of the LDC in order to dispatch 100% of the unit capacity in the peak load 

segment of the LDC. These turndown constraints were developed by ICF International through 

detailed assessments of the historical experience and operating characteristics of the existing fleet 

of coal steam and oil/gas steam units’ capacities. 

3.6 Reserve Margins 

A reserve margin is a measure of the system’s generating capability above the amount required to 

meet the net internal demand (peak load) requirement. It is defined as the difference between 

total dependable capacity and annual system peak load divided by annual system peak load. It is 

expressed in percent. In practice, each NERC region has a reserve margin requirement, or 

comparable reliability standard, which is designed to encourage electric suppliers in the region to 

build beyond their peak requirements to ensure the reliability of the electric generation system 

within the region. 

In IPM reserve margins are used to depict the reliability standards that are in effect in each NERC 

region. Individual reserve margins for each NERC region are derived either directly or indirectly 
3-14 

from NERC’s electric reliability reports. They are based on reliability standards such as loss of 

load expectation (LOLE), which is defined as the expected number of days in a specified period in 

which the daily peak load will exceed the available capacity. EPA Base Case v.4.10 reserve 

margin assumptions are shown in Table 3-9. 

Table 3-9 Planning Reserve Margins in EPA Base Case v.4.10 

Model Region Reserve Margin 

AZNM 15.7% 

CA-N 16.7% 

CA-S 16.7% 

CNAB 12.8% 

CNBC 12.8% 

CNMB 15.0% 

CNNB 20.0% 

CNNF 20.0% 

CNNL 20.0% 

CNNS 20.0% 

CNON 18.3% 

CNPE 20.0% 

CNPQ 10.0% 

CNSK 15.0% 

COMD 15.0% 

DSNY 16.5% 

ENTG 15.0% 

ERCT 12.5% 

FRCC 15.0% 

GWAY 15.0% 

LILC 16.5% 

MACE 15.0% 

MACS 15.0% 

MACW 15.0% 

MECS 15.0% 

MRO 15.0% 

NENG 16.0% 

NWPE 10.8% 

NYC 16.5% 

PNW 10.8% 

RFCO 15.0% 

RFCP 15.0% 

RMPA 14.3% 

SNV 15.7% 

SOU 15.0% 

SPPN 13.6% 

SPPS 13.6% 

TVA 12.0% 

TVAK 15.0% 

UPNY 16.5% 

VACA 15.0% 

VAPW 15.0% 

WUMS 16.0% 
3-15 

3.7 Power Plant Lifetimes 

EPA Base Case v.4.10 does not include any pre-specified assumptions about power plant 

lifetimes, except for nuclear units. All conventional fossil units (i.e., coal, oil/gas steam, 

combustion turbines, and combined cycle) and nuclear units can be retired during a model run for 

economic reasons. Other types of units are not provided an economic retirement option. 

Nuclear Retirement at Age 60: Existing nuclear units are forced to retire in EPA Base Case 

v.4.10 at the completion of age 60. Today’s nuclear fleet totals more than 100 GW. A 60-year 

lifetime reduces the current fleet to under 5 GW in 2050. This is illustrated in Figure 3-2. For a 

complete listing of the existing nuclear units represented in EPA Base Case v.4.10, including their 

online year and other characteristics, see Appendix 4-3. 

Figure 3-2 Scheduled Retirements of Existing Nuclear Capacity Under 60-Year Life 

Assumption 

Impact of 60-Year Lifetime on Existing Nuclear Fleet

0

1

2

3

4

5

6

7

8

9

10

2010 2015 2020 2025 2030 2035 2040 2045 2050

Year

Capacity (GW) Retired in Year

0

20

40

60

80

100

120

Total Capacity (GW) Remaining

Retired in Year Remaining Capacity

The 60-year lifetime assumption is based on several factors. At the time that this base case was 

prepared there were many instances of the U.S. Nuclear Regulatory Commission (NRC) granting 

license extensions of 20 years beyond the initial 40 year operating licenses authorized by the 

NRC for commercial nuclear power plants under the Atomic Energy Act of 1954. At the time of 

the release of EPA Base Case v.4.10, the NRC had granted license renewals to 50 operating 

reactors allowing them to operate for 60 years with fifteen additional applications under review and 

the owners of 21 other units announcing their intention to file for 20-year license extensions. All of 

these applications would allow the units to operate to age 60. 
3-16 

At the same time, there were no units in the U.S. nuclear fleet licensed to operate past age 609

. 

In keeping with the practice of the EPA base case representing legal provisions that are on the 

books or immediately pending, a conservative approach was adopted of reflecting the current 

maximum licensing period of 60 years for the nuclear units in EPA Base Case v.4.10. 

Another factor in the decision to implement the 60-year nuclear life assumption is the degree of 

uncertainty surrounding nuclear life extensions past age 60. As noted in EIA’s review of the 60 

year nuclear life question, uncertainties include: 

• The absence, to date, of publicly available plans and cost estimates for potential major capital 

expenditures involved with extensions to age 80 such as the replacement of reactor vessels, 

containment structures, or buried piping and cables. 

• Possible future additional regulatory requirements which could result in expensive upgrades at 

nuclear power plants and figure into life extension decisions. Among those mentioned in 

EIA’s review was a rule that was recently the subject of the Supreme Court case Entergy Corp 

v. Riverkeeper10, which focused on whether or not the EPA could conduct cost-benefit 

analyses to determine whether a plant needed to replace open-cycle cooling water systems 

with closed-cycle systems. 

The assumption of nuclear retirements at age 60 in EPA Base Case v.4.10 contrasts to a certain 

degree with the assumption made in AEO 2010. Due to AEO 2010’s shorter time horizon 

compared to the EPA base case (i.e., 2035 compared to 2050), EIA did not have to explicitly 

adopt an 80 year nuclear life assumption (as would have been necessary in EPA Base Case 

v.4.10), only that “the operating lives of existing nuclear power plants would be extended at least 

through 2035.11” The basis for the decision appears to be that “The nuclear industry has 

expressed strong interest in continuing the operation of existing nuclear facilities, and no particular 

technical issues have been identified that would impede their continued operation.12” 

Although the adopted assumptions differ in EPA Base Case v.4.10 and AEO 2010, there is 

agreement on the importance of performing side cases using the alternative assumptions. In the 

case of EPA Base Case v.4.10 this will mean performing sensitivity analysis runs with an 80 

nuclear lifetime assumption. 

 

9 The Energy Information Administration has an excellent review and summary of the issues 

involved in the 60 year nuclear life question. Although EPA’s base case does not adopt the same 

assumption as AEO 2010, the text in this section relied heavily on the EIA review. With respect to 

the status of applications for renewals beyond age 60, the EIA review notes the following: “In 

December 2009, the Oyster Creek Generating Station in Lacey Township, New Jersey, became 

the first nuclear power plant in the United States to begin its 40th year of operation. With Oyster 

Creek and other nuclear plants of similar vintage just beginning to enter their first period of license 

renewal, it probably will be at least 5 to 10 years before there is any clear indication as to whether 

plant operators will be likely to seek further extensions of their plants’ operating lives.” The EIA 

review also observes “. . . the NRC and the nuclear power industry are preparing applications for 

license renewals that would allow continued operation beyond 60 years, the first of which is 

scheduled to be submitted by 2013. In February 2008, DOE and the NRC hosted a joint workshop 

titled “Life Beyond 60,” with a broad group of nuclear industry stakeholders meeting to discuss this 

issue. The workshop’s summary report outlined many of the technical research needs that 

participants agreed were important to extending the life of the existing fleet of U.S. nuclear plants.” 

Energy Information Administration (EIA), U.S. Department of Energy, “U.S. nuclear power plants: 

Continued life or replacement after 60?” Annual Energy Outlook 2010 with Projections to 2035

(DOE/EIA-0383(2010)), May 11, 2010, www.eia.doe.gov/oiaf/aeo/nuclear_power.html. 

10Supreme Court of the United States, “Entergy Corp. v. Riverkeeper, Inc., et al.,” No. 07-588 

(October Term, 2008 www.supremecourtus.gov/opinions/ 08pdf/07-588.pdf. 

11EIA, op.cit. 

12EIA, ibid. 
3-17 

3.8 Heat Rates 

Heat rates, expressed in BTUs per KWh. are a metric of the efficiency of a generating unit. As in 

previous versions of NEEDS, it is assumed in NEEDS v.4.10 that heat rates of existing units will 

remain constant over time. This assumption reflects two offsetting factors: (1) plant efficiencies 

tend to degrade over time and (2) increased maintenance and component replacement work to 

maintain or improve plant efficiency. 

The heat rates in EPA Base Case v.4.10 are based on values from AEO 2008. These values were 

screened and adjusted using a procedure developed by EPA to ensure that the heat rates used in 

EPA Base Case v.4.10 are within the engineering capabilities of the generating unit types. Based 

on engineering analysis, the upper and lower heat rate limits shown in Table 3-10 were applied to 

coal steam, oil/gas steam, combined cycle, combustion turbine, and internal combustion engines. 

 If the reported heat rate for such a unit was below the applicable lower limit or above the upper 

limit, the limit was substituted for the reported value. 

Table 3-10 Lower and Upper Limits Applied to Heat Rate Data in NEEDS v.4.10 

Heat Rate (Btu/kWh) 

Plant Type Lower 

Limit 

Upper 

Limit 

Coal Steam 8,300 14,500 

Oil/Gas Steam 8,300 14,500 

Combined Cycle - Natural Gas 5,500 15,000 

Combined Cycle - Oil 6,000 15,000 

Combustion Turbine - Natural Gas - 80 MW and above 8,700 18,700 

Combustion Turbine - Natural Gas < 80 MW 8,700 36,800 

Combustion Turbine - Oil and Oil/Gas - 80 MW and above 6,000 25,000 

Combustion Turbine - Oil and Oil/Gas < 80 MW 6,000 36,800 

IC Engine - Natural Gas 8,700 18,000 

IC Engine - Oil and Oil/Gas - 5 MW and above 8,700 20,500 

IC Engine - Oil and Oil/Gas < 5 MW 8,700 42,000 

3.9 Existing Environmental Regulations 

This section describes the existing federal, regional, and state SO2, NOx, mercury, and CO2

emissions regulations that are represented in the EPA Base Case v.4.10. The first three 

subsections discuss national and regional regulations. The next two subsections describe state 

level environmental regulations and a variety of legal settlements. The last subsection presents 

emission assumptions for potential units. 

Note on Clean Air Interstate Rule (CAIR): In December 2008 the U.S. Court of Appeals for the 

District of Columbia Circuit remanded CAIR to EPA to correct legal flaws in the proposed 

regulations as cited in the Court’s July 2008 ruling. Until EPA’s work was completed, CAIR, which 

includes a cap-and-trade system for SO2 and NOx emissions, was temporarily reinstated. 

However, although CAIR’s provisions were still in effect when EPA Base Case v.4.10 was 

released, it is not included in the base case to allow EPA Base Case v.4.10 to be used to analyze 

the regulations proposed to replace CAIR. 

3.9.1 SO2 Regulations 

Unit-level Regulatory SO2 Emission Rates and Coal Assignments: Before discussing the 

national and regional regulations affecting SO2, it is important to note that unit-level SO2

regulations arising out of State Implementation Plan (SIP) requirements, which are not only state 

specific but also county specific, are captured at model set-up in the coal choices given to coal 

fired existing units in EPA Base Case v.4.10. The SIP requirements define “regulatory SO2
3-18 

emission rates.” Since SO2 emissions are dependent on the sulfur content of the fuel used, the 

regulatory SO2 emission rates are used in IPM to define fuel capabilities. 

For instance, a unit with a regulatory SO2 emission rate of 3.0 lbs/MMBtu would be provided only 

with those combinations of fuel choices and SO2 emission control options that would allow the unit 

to achieve an out-of-stack rate of 3.0 lbs/MMBtu or less. If the unit finds it economical, it may 

elect to burn a fuel that would achieve a lower SO2 rate than its specified regulatory emission limit. 

 In EPA Base Case v.4.10 there are 6 different sulfur grades of bituminous coal, 3 different grades 

of sub-bituminous coal, 3 different grades of lignite, and 1 sulfur grade of residual fuel oil. There 

are 2 different SO2 scrubber options for coal units. Further discussion of fuel types and sulfur 

content is contained in Chapter 9. Further discussion of SO2 control technologies is contained in 

Chapter 5. 

National and Regional SO2 Regulations: The national program affecting SO2 emissions in EPA 

Base Case v.4.10 is the SO2 allowance trading program established under Title IV of the Clean Air 

Act Amendments (CAAA) of 1990, which set a goal of reducing annual SO2 emissions by 10 

million tons below 1980 levels. The program, which became fully operational in year 2000, 

affects all SO2 emitting electric generating units greater than 25 MWs. The program provides 

trading and banking of allowances over time across all affected electric generation sources. 

The annual SO2 caps over the modeling time horizon in EPA Base Case v.4.10 reflect the 

provisions in Title IV. Since EPA Base Case v.4.10 uses year 2012 as the first analysis year, a 

projection of allowance banking behavior through the end of 2011 and specification of the 

available 2012 allowances are needed to initialize the modeling. EPA developed the projection of 

the banked allowances (11 million) going into 2012. Calculating the available 2012 allowances 

involved deducting allowance surrenders due to NSR settlements and state regulations from the 

2012 SO2 cap of 8.95 million tons. The surrenders totaled 270.6 thousand tons in allowances, 

leaving 8.679 million of 2012 allowances remaining. Table 7-4 shows the initial bank and 2012 

allowance specification along with the SO2 caps for the entire modeling time horizon. Specifics of 

the allowance surrender requirements under state regulations and NSR settlements can be found 

in Appendices 3-2 and 3-3. 

EPA Base Case v.4.10 also includes a representation of the Western Regional Air Partnership 

(WRAP) Program, a regional initiative involving Arizona, New Mexico, Oregon, Utah, Wyoming 

directed toward addressing visibility issues in the Grand Canyon and affecting SO2 emissions 

starting in 2018. The WRAP specifications for SO2 are presented in Table 7-4. 

3.9.2 NOx Regulations 

Much like SO2 regulations, existing NOx regulations are represented in EPA Base Case v.4.10 

through a combination of system level NOx programs and generation unit-level NOx limits. 

The system level NOx regulation represented in EPA Base Case v.4.10 is the NOx SIP Call trading 

program. This trading program affects all fossil units in 20 northeastern states13 and the District of 

Columbia. The program is only in effect during the ozone season (May - September). The 

program includes state-specific NOx budgets. However, since the program allows for trading 

among units in different states, the total annual NOX SIP Call budget of 527,580 tons is used in 

EPA Base Case v.4.10, rather than the state-specific budgets. The specifications for the SIP Call 

are presented in Table 7-4. 

 

13The states included in the SIP Call program are Alabama, Connecticut, Delaware, Illinois, 

Indiana, Kentucky, Maryland, Massachusetts, Michigan, Missouri, New Jersey, New York, North 

Carolina, Ohio, Pennsylvania, Rhode Island, South Carolina, Tennessee, Virginia, and West 

Virginia. 
3-19 

The representation of unit-level NOx limits includes Title IV unit specific rate limits and Clean Air 

Act Reasonable Available Control Technology (RACT) requirements for controlling NOx emissions 

from electric generating units in ozone non-attainment areas or in the Ozone Transport Region14

(OTR). Both of these limits are captured in the specific NOx emission rates assigned to each unit 

represented in the base case. Unlike SO2 emission rates, NOx emission rates are assumed not to 

vary with fuel, but are dependent on the combustion properties of the generating unit. Under the 

EPA Base Case v.4.10 the NOx emission rate of a unit can only change if the unit is retrofitted with 

NOx pollution control equipment. 

NOx Rates in NEEDS, v.4.10 Database: The NOx rates in the current base case were derived, 

wherever possible, directly from actual monitored NOx emission rate data reported to EPA under 

the Acid Rain and NOx Budget Program in 2007. The emission rates themselves reflect the 

impact of the applicable NOx regulations. For coal-fired units, NOX rates were used in combination 

with detailed engineering assessments of NOX combustion control performance to prepare a set of 

four possible starting NOx rates to assign to a unit depending on the specific policy affecting that 

unit in a model run. 

The reason for having four NOx rates in NEEDS is to allow all possible modeling scenarios 

involving NOx controls to be set up. The four NOx rates are designated as Mode 1–4, and are 

designed to include all the NOx rates possible for a unit with its current configuration of NOx

combustion and post-combustion controls. The four NOx rates are: 

• Mode 1: Applies to units not covered by a NOX control policy. Specifically, this is the NOX

rate with post-combustion controls shut off. For units without post-combustion controls, it’s 

their uncontrolled NOX rate. 

• Mode 2: A unit, which has post-combustion controls, runs them, but a unit without postcombustion controls operates as usual. 

• Mode 3: Applies to the off-season NOX rate for units affected by a seasonal NOX policy. For 

units with post-combustion controls, this is the NOX rate with post-combustion controls shut 

off. For units without post-combustion controls, it’s the NOX rate with state-of-the-art 

combustion controls operating. (Exception: In the SIP Call region current combustion controls 

are assumed to be retained.) 

• Mode 4: NOX rate applicable under a NOX policy. For SCR units, it’s the NOX rate with the 

SCR operating. For SNCR units, it’s the NOX rate with SNCR operating plus state-of-the-art 

combustion controls operating if required to attain rate limits. For units without postcombustion controls, it’s the NOX rate with state-of-the-art combustion controls operating. 

(Exception: In the SIP Call region current combustion controls are assumed to be retained.) 

The program that sets up a new model run uses a series of algorithms (decision rules) to 

determine which of the four NOX rates is selected: 

• A unit covered under an annual NOX emission limit is assigned the Mode 4 NOX rate (winter 

and summer seasons). 

• A unit covered by a summer season NOX emission limit, but not an annual NOX limit, is 

assigned the Mode 4 NOX rate in the summer season but the Mode 3 NOX rate in the winter 

season. 

• A unit covered by a mercury emission limit and not by a NOX emission limit is assigned the 

Mode 2 NOX rate in both winter and summer seasons. (Note: In the case of mercury limits, 

Mode 2 applies since it implies operation of an SCR or SNCR. This equipment, in 

combination with SO2 and particulate controls, offers as a co-benefit the reduction and capture 

 

14 The OTR consists of the following states: Maine, New Hampshire, Vermont, Massachusetts, 

Rhode Island, Connecticut, New York, New Jersey, Pennsylvania, Delaware, Maryland, District of 

Columbia, and northern Virginia. 
3-20 

of mercury. See Chapter 5 in the v.4.10 documentation for a discussion of the calculation 

mercury emission modification factors (EMF).) 

• A unit not covered by either an annual or a summer NOX limit nor mercury control 

requirements is assigned the Mode 1 NOX rate in both winter and summer seasons. 

The Mode 1-4 NOx rates for each generating unit are included in the NEEDS, v.4.10 database, 

described in Chapter 4. Appendix 3-1 and accompanying Tables 3-1.1, 3-1.2, and 3-1.3 give 

further information on the procedures employed to derive the four NOX rate modes and give 

specific examples of generating units that fit each of the Mode 1-4 specifications. 

Additional NOX rate assumptions include default NOX rates of 0.25 lbs/MMBtu for existing biomass 

units and 0.09 lbs/MMBtu for existing landfill gas units. 

3.9.3 CO2 Regulations and Renewable Portfolio Standards 

The Regional Greenhouse Gas Initiative (RGGI) is a year-round CO2 cap and trade program 

affecting fossil fired electric power plants 25 MW or larger in Connecticut, Delaware, Maine, New 

Hampshire, New Jersey, New York, Vermont, Rhode Island, Massachusetts, and Maryland. Table 

7-4 shows the specifications for RGGI that are implemented in EPA Base Case v.4.10. 

Renewable Portfolio Standards (RPS) generally refer to various state-level policies that require 

the addition of renewable generation to meet a specified share of state-wide generation In EPA 

Base Case v.4.10 the state RPS requirements are represented at a regional level utilizing the 

aggregate regional representation of RPS requirements that is implemented in AEO 201015 as 

shown in Appendix 3-6. This appendix shows the RPS requirements that apply to the NEMS 

(National Energy Modeling System) regions used in AEO. The RPS requirement for a particular 

NEMS region applies to all IPM regions that are predominantly contained in that NEMS region. 

3.9.4 State Specific Environmental Regulations 

EPA Base Case v.4.10 represents laws and regulations in 25 states affecting emissions from the 

electricity sector. The laws and regulations had to either be on the books or expected to come 

into force. Appendix 3-2 summarizes the provisions of state laws and regulations that are 

represented in EPA Base Case 4.10. 

3.9.5 New Source Review (NSR) Settlements 

The New Source Review, (NSR) settlements refer to legal agreements with companies resulting 

from the permitting process under the CAAA which requires industry to undergo an EPA preconstruction review of proposed environmental controls either on new facilities or as modifications 

to existing facilities where there would result a “significant increase” in a regulated pollutant. EPA 

Base Case v.4.10 includes NSR settlements with 20 electric power companies. A summary of the 

units affected and how the settlements were modeled can be found in Appendix 3-3. 

Seven state settlements and five citizen settlements are also represented in EPA Base Case 

v.4.10. These are summarized in Appendices 3-4 and 3-5 respectively. 

3.9.6 Emission Assumptions for Potential (New) Units 

Emissions from existing and planned/committed units vary from installation to installation based 

on the performance of the generating unit and the emissions regulations that are in place. In 

contrast, there are no location-specific variations in the emission and removal rate capabilities of 

potential new units. In IPM, potential new units are modeled as additional capacity and generation 

that may come on line in each model region. Across all model regions the emission and removal 

 

15Energy Information Administration, U.S. Department of Energy, Assumptions to Annual Energy 

Outlook 2010: Renewable Fuels Module (DOE/EIA-0554(2010)), April 9, 2010, Table 13.4 

“Aggregate Regional RPS Requirements, www.eia.doe.gov/oiaf/aeo/assumption/renewable.html

and www.eia.doe.gov/oiaf/aeo/assumption/pdf/renewable_tbls.pdf
3-21 

rate capabilities of potential new units are the same. It should be noted that, new coal units cannot 

be built in the CA-N, CA-S, NYC, LILC, or NENG model regions due to particularly stringent state 

emission limits placed on fossil fired units. The specific assumptions regarding the emission and 

removal rates of potential new units in EPA Base Case v.4.10 are presented in Table 3-11. (Note: 

 Nuclear, wind, solar, and fuel cell technologies are not included in Table 3-11 because they do 

not emit any of the listed pollutants.) For additional details on the modeling of potential new units 

see Chapter 4. 

3.10 Capacity Deployment Constraints 

Due to its extended time horizon and the policies that EPA Base Case v.4.10 is expected to be 

used to analyze, capacity deployment constraints for the more capital intensive generation 

technologies and retrofits (new nuclear, advanced coal with carbon capture, and carbon capture 

retrofits) were incorporated into the base case. The deployment constraints are intended to 

capture factors that are likely to place an upper bound on the amount of these technologies that 

can be built in any given model run year over the modeling time horizon. Such limiting factors 

include: 

• production capacity limitations (including the number of engineering and construction (E/C) 

firms capable of executing large power projects in the U.S., the number of large projects each 

such firm can handle, and the number of multi-billion dollar projects a firm can take on in 

parallel), 

• general limitations in the domestic infrastructure for heavy manufacturing, 

• financial limitations (number of projects that can obtain financing simultaneously at an 

acceptable level of risk), 

• workforce limitations (limitations in the skilled engineering and construction labor force, 

replacement challenges caused by an aging workforce, on the one hand, and inadequate 

training infrastructure for new entrants, on the other). 

The capacity deployment constraints are based on assessments by EPA power sector 

engineering staff of historical trends and projections of capability going forward. Conceptually, the 

procedure used to develop these constraints consisted of the following steps: 

1. Start by estimating the maximum number of E/C firms that will be available over the time 

horizon. 

2. Estimate the maximum number of a particular type of generating unit (e.g., 600 MW advanced 

coal plant with carbon capture) that a single E/C firm can complete in the first 5-year period 

(2015-2020). 

3. Multiply the number of E/C firms estimated in Step 1 by the number of units per firm found in 

Step 2 to obtain the maximum number of these generating units that can be completed in the 

first period. 

4. Determine if there will be competition from other competing technologies for the same 

productive capacity and labor force used for the technology analyzed in steps 2 and 3. If not, 

go to Step 7. If so, go to Step 5. 

5. Establish an equivalency table showing how much capacity could be built if the effort required 

to build 1 MW of the type of technology analyzed in steps 2 and 3 were instead used to build 

another type of generating technology (e.g., 1600 MW nuclear plant). 

6. Based on these calculations build a production possibility frontier showing the maximum mix 

of the two generating technologies that can be added in the first 5-year period. 

7. Over the subsequent five year periods assume that the E/C firms have increased capabilities 

relative to the previous five year period. Represent the increased capability by a capability 

multiplier. For example, it might be assumed that each succeeding 5-year period the E/C 

firms can design and build 1.4 as much as in the immediately preceding 5-year period. 

Multiply the capacity deployment limit(s) from the preceding period by the capability multiplier 

to derive the capacity deployment limit for the subsequent period. 
3-22 

8. If necessary, prevent sudden spikes in capacity in later periods when there has been little or 

no build up in preceding periods by tying the amount of capacity that can be built in a given 

period to the amount of capacity built in preceding periods. 

Appendix 3-07 shows the joint capacity deployment constraint on advanced coal with carbon 

capture and storage (CCS) and new nuclear. Appendix 3-08 shows the capacity deployment 

constraint on new nuclear in itself. The bar graph in Appendix 3-08 illustrates how building 

capacity in earlier years increases the maximum capacity that can be built over the entire 

modeling time horizon. 
3-23 

Table 3-11 Emission and Removal Rate Assumptions for Potential (New) Units in EPA Base Case 

Gas 

Controls, 

Removal, 

and 

Emissions 

Rates 

Supercritical 

Pulverized 

Coal - Wet 

Scrubber 

Supercritical 

Pulverized 

Coal - Dry 

Scrubber 

Integrated 

Gasification 

Combined 

Cycle 

Advanced 

Coal with 

Carbon 

Capture 

Advanced 

Combined 

Cycle 

Advanced 

Combustio

n Turbine 

Biomass 

Conventional 

Direct-Fired 

Boiler 

Biomass 

Gasification 

Combined 

Cycle 

SO2

Removal / 

Emissions 

Rate 

98% with a 

floor of 0.06 

lbs/MMBtu 

93% with a 

floor of 0.065 

lbs/MMBtu 

99% 99% None None 0.08 lbs/MMBtu 0.08 lbs/MMBtu 

NOx Emission Rate 0.06 lbs/MMBtu 0.06 lbs/MMBtu 0.013 lbs/MMBtu 0.013 lbs/MMBtu 0.011 lbs/MMBtu 0.011 lbs/MMBtu 0.36 lbs/MMBtu 0.102 lbs/MMBtu 

Hg 

Removal / 

Emissions 

Rate 

90% 90% 90% 90% 

Natural 

Gas: 

0.000138 

lbs/MMBtu

Oil: 

0.483 

lbs/MMBtu 

Natural 

Gas: 

.000138 

lbs/MMBtu 

Oil: 

0.483 

lbs/MMBtu 

0.57 

lbs/MMBtu 

0.57 

lbs/MMBtu 

CO2

Removal / 

Emissions 

Rate 

205.2 - 217.3 

lbs/MMBtu 

205.2 - 217.3 

lbs/MMBtu 

205.2 - 217.3 

lbs/MMBtu 90% 

Natural 

Gas: 

117.08 

lbs/MMBtu

Oil: 

161.39 

lbs/MMBtu 

Natural 

Gas: 

117.08 

lbs/MMBtu 

Oil: 

161.39 

lbs/MMBtu 

None None 
Appendix 3-1.1 

Appendix 3-1 NOx Rate Development in EPA Base Case v.4.10 

The following questions (Q) and answers (A) are intended to provide further background on the 

four NOX rates found in the NEEDS, v.4.10 database. 

Q1: Why are four NOX rates included in NEEDS? 

A1: The four NOX rates in NEEDS represent a menu of all the NOX rates applicable to a specific 

generating unit with only its current configuration of NOx combustion and post-combustion controls 

under all the conceivable policies involving NOx controls that might be modeled in the future. By 

defining this menu up front for every generating unit, the program that sets up an IPM run can 

follow a set of decision rules to select the rate(s) appropriate for the unit in the particular policy 

being modeled consistent with the unit’s existing set of combustion and post-combustion NOx

controls. 

Q2: What operational states do the four NOx rates represent? 

A2: Before answering this question, let’s name the four NOx rates that are in NEEDS: 

Mode 1= Uncontrolled Base Rate 

Mode 2= Controlled Base Rate 

Mode 3= Uncontrolled Policy Rate 

Mode 4 = Controlled Policy Rate 

The operational states associated with each of the four NOx rates are shown in the second and 

third columns in the table below. 

Q3: What NOx policies in a model run result in the assignment of each of the NOx rates? 

A3: The policies causing each rate to be assigned are shown in the last column in the table below. 

Interpreting the Mode 1 – 4 NOx Rates in NEEDS

Name Operational State of NOx

Controls 

NOx Policies Causing This Rate 

To be Assigned 

Units with post combustion 

NOx controls: Do they 

operate the controls? 

No 

Mode 1 = 

Uncontrolled 

Base Rate 

Units without postcombustion controls: Do 

they upgrade to state-offthe-art combustion controls? 

No 

If the unit is not covered by any NOx limit 

in the run, pre-assign this as its NOx rate 

Units with post combustion 

NOx controls: Do they 

operate the controls? 

Yes 

Mode 2 = 

Controlled 

Base Rate 

Units without postcombustion controls: Do 

they upgrade to state-offthe-art combustion controls? 

No 

If the unit is covered by a mercury 

policy, pre-assign this as its NOx rate 

Explanation: Post-combustion NOx

controls figure in mercury reduction but 

NOx combustion controls do not, so the 

operational state (in column 2) fits the 

requirements of the policy 

Units with post combustion 

NOx controls: Do they 

operate the controls? 

No Mode 3 = 

Uncontrolled 

Policy Rate Units without postcombustion controls: Do 

they upgrade to state-offYes 

If the unit is covered by a summer NOx

limit pre-assign this as its winter NOx

rate. 
Appendix 3-1.2 

Name Operational State of NOx

Controls 

NOx Policies Causing This Rate 

To be Assigned 

the-art combustion controls? 

Units with post combustion 

NOx controls: Do they 

operate the controls? 

Yes 

Mode 4 = 

Controlled 

Policy Rate 

Units without postcombustion controls: Do 

they upgrade to state-offthe-art combustion controls? 

Yes 

If the unit is covered by a summer NOx

limit pre-assign this as its summer NOx

rate. 

If the unit is covered by an annual NOx

limit, pre-assign this as its winter and 

summer NOx rates. 

Q4: How are the values of the Mode 1-4 NOx rates derived? 

A4: We start with the emission data reported to EPA for a specific year under Title IV of the Clean 

Air Act Amendments of 1990 (Acid Rain Program) and NOx Budget Program. Using this data, NOx

rates are derived for the summer and winter seasons. 

Calculations can get complex, so we’ll illustrate it here for coal units only and with the assumption 

that the data were absolutely complete and consistent with what engineering theory tells us its 

values should be. Otherwise, we apply additional screens. Explaining them is beyond the scope 

of this illustration. Basically, here’s how the values would be derived: 

Mode 1

For all coal units Mode 1 = Winter NOx rate 

Mode 2 

For coal units without NOx post-combustion controls 

Mode 2 = Mode 1 rate 

For coal units with NOx post-combustion controls, 

Min{max[Mode 1 NOx rate * (1-removal efficiency), floor rate], ETS Summer NOx rate} 

 Where 

For an SCR, 

Removal efficiency = 90% 

Floor rate = 0.06 lb/MMBtu; 

For an SNCR, 

Removal efficiency = 35% 

No floor rate is applicable 

Mode 3

Step 1: Pre-screen units that already have state of art (SOA) combustion controls from units that 

have non-SOA combustion controls from units that have no combustion controls 

For coal units without post-combustion NOx controls

For units listed as not having combustion controls 

 Make sure their NOx rates do not indicate that they really do have SOA control 

If Mode 1 > Cut-off (in Table 3-1.2), then Mode 1 = Base rate. Go to Step 3 

 If Mode 1 ≤ Cut-off (in Table 3-1.2), then the unit has SOA control and 

Go to Step 5 using the Mode 1 rate as the provisional SOA NOx rate. 

For coal listed with combustion controls

If Mode 1 > Cut-off (in Table 3-1.2), then unit has non-SOA combustion controls. 

Go to Step 2 
Appendix 3-1.3 

 If Mode 1 ≤ Cut-off (in Table 3-1.2), then the unit has SOA control and 

Go to Step 5 using the Mode 1 rate as the provisional SOA NOx rate. 

For coal units with post-combustion NOx controls

 For coal units with SCR

 Mode 1 = Mode 3 

 For coal units with SNCR

 If Mode 1 ≤ Cut-off (in Table 3-1.2), then the unit has SOA control and 

 Mode 1 = Mode 3 

If Mode 1 > Cut-off (in Table 3-1.2), then unit has non-SOA combustion controls. 

Go to Step 2 

Step 2: For units with non-SOA combustion controls, determine their Base NOx rate, i.e., the unit’s 

uncontrolled emission rate without combustion controls, using the appropriate equation (not in 

boldface italics) in Table 3-1.3 to back calculate their Base NOx rate. Use the default Base NOx

rate values if back calculations can’t be performed. Once the Base NOx rate is obtained, go to 

Step 3. 

Step 3: Use the appropriate equations (in boldface italics) in Table 3-1.3 to calculate the NOx rate 

with SOA combustion controls. 

Step 4: Compare the value calculated in Step 3 to the applicable NOx floor rate in Table 3-1:2. 

For units with post-combustion controls

If the value from Step 3 is ≥ floor, use the Step 3 value as Mode 3 NOx rate. Otherwise, use the 

floor as the Mode 3 NOx rate. 

For units without post-combustion controls

If the value from Step 3 is ≥ floor, use the Step 3 value as the provisional SOA NOx rate. 

Otherwise, use the floor as their provisional SOA NOx rate. 

Go to Step 5. 

Step 5: For units without post combustion controls compare the provisional SOA NOx rate 

obtained in previous steps to their Summer NOx rate. 

 If Summer NOx rate < provisional SOA NOx rate, then Mode 3 = summer NOx rate. 

 If Summer NOx rate ≥ provisional SOA NOx rate, then 

 Mode 3 = provisional SOA NOx rate. 

Mode 4

For units without post-combustion controls

Mode 4 = Mode 3 

For units with SCR post-combustion controls

Mode 4 = Mode 2 

For units with SNCR post-combustion controls

Mode 4 = minimum {(1-.35) * Mode 3, Summer NOx rate} 

Note: The (1-.35) term in the equation above represents the 35% NOx removal efficiency of 

SNCR. 

Q5: Is there anything else that might be useful to understand about the Mode 1 – 4 NOx rates. 
Appendix 3-1.4 

A5: There are several things to note about the Modes 1-4 designations. “Controlled” refers to the 

rates provided by post combustion NOx controls, i.e., selective catalytic reduction (SCR) or 

selective non-catalytic reduction (SNCR), if they are present at the unit. For generating units that 

do not have post-combustion controls, the controlled rate will be the same as the uncontrolled 

rate. For generating units that do have post-combustion controls, the controlled and uncontrolled 

rates will differ. Base and Policy NOx rates will be same if the unit has state-of-the-art NOx

combustion controls or is in the SIP Call region where current combustion controls are assumed to 

be retained. Base and policy rates will differ if a unit does not currently have state-of-the-art 

combustion controls that would be installed in response to a NOx policy. Examples of each of 

these instances are shown in Table 3-1.1. 

Other things worth noting are: 

(a) In general, winter NOx rates reported in EPA’s Emission Tracking System were used as 

proxies for the uncontrolled base NOx rates. 

(b) If a unit does not report having combustion controls, but has an emission rate below a specific 

cut-off rate (shown in Table 3-1.2), it is considered to have combustion controls. 

(c) For units with combustion controls that were not state-of-the-art, emission rates without those 

combustion controls were back-calculated and then policy rates were derived assuming the 

reductions provided by state-of-the art combustion controls. 

(d) The NOx rates achievable by state-of-the-art combustion controls vary by coal rank 

(bituminous and sub-bituminous) and boiler type. The equations used to derive these rates are 

shown in Table 3-1.3. 

Q6: What are examples of the Mode 1-4 NOx for some actual operating generating units? 

A6: Table 3-1.1 gives the Mode 1-4 NOx rates for real generating units. They are meant to 

illustrate a range of situations that can arise. 
Appendix 3-1.5 

Table 3-1.1 Examples of Base and Policy NOx Rates Occurring in EPA Base Case v.4.10 

Plant 

Name Unique ID 

PostCombustion 

Control 

Uncontrolled 

NOx Base 

Rate 

Controlled 

NOx Base 

Rate 

Uncontrolled 

NOx Policy 

Rate 

Controlled 

NOx Policy 

Rate 

Ex

Situation 1: For generating units that do not have post-combustion controls, the controlled and uncontrolled rates will be the 

Four 

Corners 2442_B_1 None 0.809 0.809 0.524 0.524 Situation 4 also app

now added OFA so 

Situation 2: For generating units that do have post-combustion controls, the controlled and uncontrolled rates will differ. 

Big Sandy 1353_B_BSU2 SCR 0.638 0.064 0.638 0.064 

(1) Has SCR so see uncontrolled and co(2) Situation 3b also 

Situation 3a: Base and Policy NOx rates will be same if the unit has state-of-the-art NOx combustion controls or . . . 

Greene 

County 10_B_2 None 0.316 0.316 0.316 0.316 Situation 1 also app

Roxboro 2712_B_1 SCR 0.900 0.084 0.900 0.084 Situation 2 also app

Situation 3b: . . . is in the SIP Call region where current combustion controls are assumed to be retained. 

Thomas Hill 2168_B_MB3 SCR 0.223 0.060 0.223 0.060 Situation 2 also app

Waukegan 883_B_17 None 0.710 0.710 0.710 0.710 

(1) Has NOx combusdoesn't get added corate because it is a c(2) Situation 1 also a

Situation 4: Base and policy rates will differ if a unit does not currently have state-of-the-art combustion controls and would inresponse to a NOx policy. 

Clay 

Boswell 1893_B_4 SNCR 0.231 0.150 0.152 0.099 

(1) Drop in uncontrocompared to uncontaddition of combustifloor.) (2) Unit has SNCR sand you see a 35% and controlled NOx r
Appendix 3-1.6 

Table 3-1.2 Cutoff and Floor NOx Rates (lb/MMBtu) in EPA Base Case v.4.10 

Cutoff Rate (lbs/MMBtu) Floor Rate (lbs/MMBtu) Boiler Type Bituminous Subbituminous Lignite Bituminous Subbituminous Lignite 

Wall-Fired 

Dry-Bottom 0.43 0.33 0.29 0.32 0.18 0.18 

TangentiallyFired 0.34 0.24 0.22 0.24 0.12 0.17 

Cell-Burners 0.43 0.43 0.43 0.32 0.32 0.32 

Cyclones 0.62 0.67 0.67 0.47 0.49 0.49 

VerticallyFired 0.57 0.44 0.44 0.49 0.25 0.25 

Table 3-1.3 NOx Removal Efficiencies for Different Combustion Control Configurations in 

EPA Base Case v.4.10 

(State of the art configurations are shown in bold italic.) 

Boiler Type Coal Type Combustion Control 

Technology 

Fraction of 

Removal 

Default 

Removal 

LNB 0.163 + 0.272* 

Base NOx 0.568 Dry Bottom 

Wall-Fired Bituminous 

LNB + OFA 0.313 + 0.272* 

Base NOx 

0.718 

LNB 0.135 + 0.541* 

Base NOx 0.574 Dry Bottom 

Wall-Fired 

Subbituminous

/Lignite LNB + OFA 0.285 + 0.541* 

Base NOx 

0.724 

LNC1 0.162 + 0.336* 

Base NOx 0.42 

LNC2 0.212 + 0.336* 

Base NOx 0.47 TangentiallyFired Bituminous 

LNC3 0.362 + 0.336* 

Base NOx 0.62 

LNC1 0.20 + 0.717* 

Base NOx 0.563 

LNC2 0.25 + 0.717* 

Base NOx 0.613 TangentiallyFired 

Subbituminous

/Lignite 

LNC3 0.35 + 0.717* 

Base NOx 0.713 

Notes:

LNB = Low NOx Burner 

OFA = Overfire Air 

LNC = Low NOx Control 
Appendix 3-2.1 

Appendix 3-2 State Power Sector Regulations included in EPA Base Case 

v.4.10 

State/ Region Bill Emission 

Type Emission Specifications Implementation Status 

Alabama 

Alabama 

Administrative 

Code Chapter 

335-3-8 

NOx

0.02 lbs/MMBtu annual PPMDV for combined 

cycle EGUs which commenced operation after 

April 1, 2003 

2003 

Arizona 

Title 18, 

Chapter 2, 

Article 7 

Hg 

90% removal of Hg content of fuel or 0.0087 

lb/GWH-hr annual reduction for all non-cogen 

coal units > 25 MW 

2017 

NOx

9.68 MTons annual cap for list of entities in 

Appendix A of "Annual RECLAIM Audit Market 

Report for the Compliance Year 2005" (304 

entities) California CA Reclaim 

Market 

SO2

4.292 MTons annual cap for list of entities in 

Appendix A of "Annual RECLAIM Audit Market 

Report for the Compliance Year 2005" (304 

entities) 

1994 

Colorado 40 C.F.R. Part 

60 Hg 

2012 & 2013: 80% reduction of Hg content of 

fuel or 0.0174 lb/GW-hr annual reduction for 

Pawnee Station 1 and Rawhide Station 101 

2014 through 2016: 80% reduction of Hg 

content of fuel or 0.0174 lb/GW-hr annual 

reduction for all coal units > 25 MW 

2017 onwards: 90% reduction of Hg content of 

fuel or 0.0087 lb/GW-hr annual reduction for all 

coal units > 25 MW 

2012 

Executive 

Order 19 and 

Regulations of 

Connecticut 

State Agencies 

(RCSA) 22a174-22 

NOx

0.15 lbs/MMBtu annual rate limit for all fossil 

units > 15 MW 

Executive 

Order 19, 

RCSA 22a-198 

& Connecticut 

General 

Statues (CGS) 

22a-198 

SO2

0.33 lbs/MMBtu annual rate limit for all fossil 

units > 15 MW 

2003 

Connecticut 

Public Act No. 

03-72 & RCSA 

22a-198 

Hg 

90% removal of Hg content of fuel or 0.0087 

lb/GW-hr annual reduction for all coal-fired 

units 

2008 

Regulation 

1148: Control 

of Stationary 

Combustion 

Turbine EGU 

Emissions 

NOx

0.19 lbs/MMBtu ozone season PPMDV for 

stationary, liquid fuel fired CT EGUs >1 MW 

0.39 lbs/MMBtu ozone season PPMDV for 

stationary, gas fuel fired CT EGUs >1 MW 

2009 

NOx

0.125 lbs/MMBtu rate limit of NOx annually for 

all coal and residual-oil fired units > 25 MW 

Delaware 

Regulation No. 

1146: Electric 

Generating 

Unit (EGU) 

Multi-Pollutant 

Regulation 

SO2

0.26 lbs/MMBtu annual rate limit for coal and 

residual-oil fired units > 25 MW 

2009 
Appendix 3-2.2 

State/ Region Bill Emission 

Type Emission Specifications Implementation Status 

Hg 

2012: 80% removal of Hg content of fuel or 

0.0174 lb/GW-hr annual reduction for all coal 

units > 25 MW 

2013 onwards: 90% removal of Hg content of 

fuel or 0.0087 lb/GW-hr annual reduction for all 

coal units > 25 MW 

Georgia 

Multipollutant 

Control for 

Electric Utility 

Steam 

Generating 

Units 

SCR, 

FGD, and 

Sorbent 

Injection 

Baghouse 

controls to 

be 

installed 

The following plants must install controls: 

Bowen, Branch, Hammond, McDonough, 

Scherer, Wansley, and Yates 

Implementation 

from 2008 

through 2015, 

depending on 

plant and control 

type 

Title 35, 

Section 

217.706 

NOx

0.25 lbs/MMBtu summer season rate limit for all 

fossil units > 25 MW 2004 

NOx

0.11 lbs/MMBtu annual rate limit and ozone 

season rate limit for all Dynergy and Ameren 

coal steam units > 25 MW 

2012 

SO2

2013 & 2014: 0.33 lbs/MMBtu annual rate limit 

for all Dynergy and Ameren coal steam units > 

25 MW 

2015 onwards: 0.25 lbs/MMBtu annual rate limit 

for all Dynergy and Ameren coal steam units > 

25 MW 

2013 

Title 35, Part 

225, Subpart 

B: Control of 

Hg Emissions 

from Coal Fired 

Electric 

Generation 

Units 

Hg 

90% removal of Hg content of fuel or 0.08 

lbs/GW-hr annual reduction for all Ameren and 

Dynergy coal units > 25 MW 

2015 

NOx

0.11 lbs/MMBtu ozone season and annual rate 

limit for all specified Midwest Gen coal steam 

units 

2012 

SO2

0.44 lbs/MMBtu annual rate limit in 2013, 

decreasing annually to 0.11 lbs/MMBtu in 2019 

for all specified Midwest Gen coal steam units 

2013 

Illinois 

Title 35 Part 

225; Subpart F: 

Combined 

Pollutant 

Standards 

Hg 

90% removal of Hg content of fuel or 0.08 

lbs/GWh annual reduction for all specified 

Midwest Gen coal steam units 

2015 

Louisiana 

Title 33 Part II - 

Chapter 22, 

Control of 

Nitrogen 

Oxides 

NOx

1.2 lbs/MMBtu ozone season PPMDV for all 

single point sources that emit or have the 

potential to emit 5 tons or more of SO2 into the 

atmosphere 

2005 

Chapter 145 

NOx Control 

Program 

NOx

0.22 lbs/MMBtu annual rate limit for all fossil 

fuel units > 25 MW built before 1995 with a heat 

input capacity < 750 MMBtu/hr 

0.15 lbs/MMBtu annual rate limit for all fossil 

fuel units > 25 MW built before 1995 with a heat 

input capacity > 750 MMBtu/hr 

0.20 lbs/MMBtu annual rate limit for all fossil 

fuel fired indirect heat exchangers, primary 

boilers, and resource recovery units with heat 

input capacity > 250 MMBtu/hr 

2005 

Maine 

Statue 585-B 

Title 38, 

Chapter 4: 

Protection and 

Improvement 

of Air 

Hg 25 lbs annual cap for any facility including 

EGUs 2010 
Appendix 3-2.3 

State/ Region Bill Emission 

Type Emission Specifications Implementation Status 

NOx

7.3 MTons summer cap and 16.7 MTons 

annual cap for 15 specific existing coal steam 

units 

SO2

2009 through 2012: 48.6 MTons annual cap for 

15 specific existing coal steam units 

2013 onwards: 37.2 MTons annual cap for 15 Maryland specific existing coal steam units Maryland 

Healthy Air Act 

Hg 

2010 through 2012: 80% removal of Hg content 

of fuel for 15 specific existing coal steam units 

2013 onwards: 90% removal of Hg content of 

fuel for 15 specific existing coal steam units 

2009 

NOx

1.5 lbs/MWh annual GPS for Bayton Point, 

Mystic Generating Station, Somerset Station, 

Mount Tom, Canal, and Salem Harbor 

SO2

3.0 lbs/MWh annual GPS for Bayton Point, 

Mystic Generating Station, Somerset Station, 

Mount Tom, Canal, and Salem Harbor 

Massachusetts 310 CMR 7.29 

Hg 

2012: 85% removal of Hg content of fuel or 

0.00000625 lbs/MWh annual GPS for Brayton 

Point, Mystic Generating Station, Somerset 

Station, Mount Tom, Canal, and Salem Harbor 

2013 onwards: 95% removal of Hg content of 

fuel or 0.00000250 lbs/MWh annual GPS for 

Brayton Point, Mystic Generating Station, 

Somerset Station, Mount Tom, Canal, and 

Salem Harbor 

2006 

Michigan 

Part 15. 

Emission 

Limitations and 

Prohibitions - 

Mercury 

Hg 90% removal of Hg content of fuel annually for 

all coal units > 25 MW 2015 

Minnesota 

Minnesota Hg 

Emission 

Reduction Act 

Hg 90% removal of Hg content of fuel annually for 

all coal units > 250 MW 2008 

Missouri 10 CSR 10-

6.350 NOx

0.25 lbs/MMBtu annual rate limit for all fossil 

fuel units > 25 MW in the following counties: 

Bollinger, Butler, Cape Girardeau, Carter, 

Clark, Crawford, Dent, Dunklin, Gasconade, 

Iron, Lewis, Lincoln, Madison, Marion, 

Mississippi, Montgomery, New Madrid, Oregon, 

Pemiscot, Perry, Phelps, Pike, Ralls, Reynolds, 

Ripley, St. Charles, St. Francois, Ste. 

Genevieve, Scott, Shannon, Stoddard, Warren, 

Washington and Wayne 

0.18 lbs/MMBtu annual rate limit for all fossil 

fuel units > 25 MW the following counties: City 

of St. Louis, Franklin, Jefferson, and St. Louis 

0.35 lbs/MMBtu annual rate limit for all fossil 

fuel units > 25 MW in the following counties: 

Buchanan, Jackson, Jasper, Randolph, and 

any other county not listed 

2004 

Montana 

Montana 

Mercury Rule 

Adopted 

10/16/06 

Hg 

0.90 lbs/TBtu annual rate limit for all non-lignite 

coal units 

1.50 lbs/TBtu annual rate limit for all lignite coal 

units 

2010 
Appendix 3-2.4 

State/ Region Bill Emission 

Type Emission Specifications Implementation Status 

RSA 125-O: 

11-18 Hg 

80% reduction of aggregated Hg content of the 

coal burned at the facilities for Merrimack Units 

1 & 2 and Schiller Units 4, 5, & 6 

2012 

NOx

2.90 MTons summer cap for all fossil steam 

units > 250 MMBtu/hr operated at any time in 

1990 and all new units > 15 MW 

3.64 MTons annual cap for Merrimack 1 & 2, 

Newington 1, and Schiller 4 through 6 

New 

Hampshire 

ENV-A2900 

Multiple 

pollutant 

annual budget 

trading and 

banking 

program SO2

7.29 MTons annual cap for Merrimack 1 & 2, 

Newington 1, and Schiller 4 through 6 

2007 

N.J.A.C. 7:27-

27.5, 27.6, 

27.7, and 27.8 

Hg 

90% removal of Hg content of fuel annually for 

all coal-fired units 

95% removal of Hg content of fuel annually for 

all MSW incinerator units 

2007 

N.J. A. C. Title 

7, Chapter 27, 

Subchapter 19, 

Table 1 

NOx

Annual rate limits in lbs/MMBtu for the following 

technologies: 

1.0 for tangential and wall-fired wet-bottom coal 

boilers serving an EGU 

0.60 for cyclone-fired wet-bottom coal boilers 

serving an EGU 

0.38 for tangential dry-bottom coal boilers 

serving an EGU 

0.45 for wall-fired dry-bottom coal boilers 

serving an EGU 

0.55 for cyclone-fired dry-bottom coal boilers 

serving an EGU 

0.20 for tangential oil and/or gas boilers serving 

an EGU 

0.28 for wall-fired oil and/or gas boilers serving 

an EGU 

0.43 for cyclone-fired oil and/or gas boilers 

serving an EGU 

2007 

New Jersey 

N.J. A. C. Title 

7, Chapter 27, 

Subchapter 19, 

Table 4 

NOx

2.2 lbs/MWh annual GPS for gas-burning 

simple cycle combustion turbine units 

3.0 lbs/MWh annual GPS for oil-burning simple 

cycle combustion turbine units 

1.3 lbs/MWh annual GPS for gas-burning 

combined cycle CT or regenerative cycle CT 

units 

2.0 lbs/MWh annual GPS for oil-burning 

combined cycle CT or regenerative cycle CT 

units 

2007 

Part 237 NOx

39.91 MTons non-ozone season cap for fossil 

fuel units > 25 MW 2004 

Part 238 SO2

131.36 MTons annual cap for fossil fuel units > 

25 MW 2005 

New York 

Mercury 

Reduction 

Program for 

Coal-Fired 

Electric Utility 

Steam 

Generating 

Units 

Hg 

786 lbs annual cap through 2014 for all coal 

fired boiler or CT units >25 MW after Nov. 15, 

1990. 

0.60 lbs/TBtu annual rate limit for all coal units 

> 25 MW developed after Nov.15 1990 

2010 

NOx

25 MTons annual cap for Progress Energy coal 

plants > 25 MW and 31 MTons annual cap for 

Duke Energy coal plants > 25 MW 

2007 

North Carolina 

NC Clean 

Smokestacks 

Act: Statute 

143-215.107D 

SO2

2012: 100 MTons annual cap for Progress 

Energy coal plants > 25 MW and 150 MTons 

annual cap for Duke Energy coal plants 

>25MW 

2013 onwards: 50 MTons annual cap for 

Progress Energy coal plants > 25 MW and 80 

2009 
Appendix 3-2.5 

State/ Region Bill Emission 

Type Emission Specifications Implementation Status 

MTons annual cap for Duke Energy coal plants 

> 25 MW 

Oregon 

Administrative 

Rules, Chapter 

345, Division 

24 

CO2

675 lbs/MWh annual rate limit for new 

combustion turbines burning natural gas with a 

CF >75% and all new non-base load plants 

(with a CE <= 75%) emitting CO2

1997 

Oregon Utility 

Mercury Rule - 

Existing Units 

Hg 

90% removal of Hg content of fuel reduction or 

0.6 lbs/TBtu limitation for all existing coal units 

>25 MW 

2012 

Oregon 

Oregon Utility 

Mercury Rule - 

Potential Units 

Hg 25 lbs rate limit for all potential coal units > 25 

MW 2009 

Pacific 

Northwest 

Washington 

State House 

Bill 3141 

CO2

$1.45/Mton cost (2004$) for all new fossil-fuel 

power plant 2004 

SO2

273.95 MTons cap of SO2 for all grandfathered 

units built before 1971 in East Texas Region Senate Bill 7 

Chapter 101 

NOx

Annual cap for all grandfathered units built 

before 1971 in MTons: 84.48 in East Texas, 

18.10 in West Texas, 1.06 in El Paso Region 

2003 

East and Central Texas annual rate limits in 

lbs/MMBtu for units that came online before 

1996: 

Gas fired units: 0.14 

Coal fired units: 0.165 

Stationary gas turbines: 0.14 

Dallas/Fort Worth Area annual rate limit for 

utility boilers, auxiliary steam boilers, stationary 

gas turbines, and duct burners used in an 

electric power generating system except for CT 

and CC units online after 1992: 

0.033 lbs/MMBtu or 0.50 lbs/MWh output or 

0.0033 lbs/MMBtu on system wide heat input 

weighted average for large utility systems 

0.06 lbs/MMBtu for small utility systems 

Houston/Galveston region annual Cap and 

Trade (MECT) for all fossil units: 

17.57 MTons 

Texas 

Chapter 117 NOx

Beaumont-Port Arthur region annual rate limits 

for utility boilers, auxiliary steam boilers, 

stationary gas turbines, and duct burners used 

in an electric power generating system: 0.10 

lbs/MMBtu 

2007 

Utah 

R307-424 

Permits: 

Mercury 

Requirements 

for Electric 

Generating 

Units 

Hg 90% removal of Hg content of fuel annually for 

all coal units > 25 MW 2013 

Wisconsin 

NR 428 

Wisconsin 

Administration 

Code 

NOx

Annual rate limits in lbs/MMBtu for coal fired 

boilers > 1,000 MMBtu/hr : 

Wall fired, tangential fired, cyclone fired, and 

fluidized bed: 2009: 0.15, 2013 onwards: 0.10 

Arch fired: 2009 onwards: 0.18 

2009 
Appendix 3-2.6 

State/ Region Bill Emission 

Type Emission Specifications Implementation Status 

Annual rate limits in lbs/MMBtu for coal fired 

boilers between 500 and 1,000 MMBtu/hr: 

Wall fired: 2009: 0.20; 2013 onwards: 0.17 in 

2013 

Tangential fired: 2009 onwards: 0.15 

Cyclone fired: 2009: 0.20; 2013 onwards: 0.15 

Fluidized bed: 2009: 0.15; 2013 onwards: 0.10 

Arch fired: 2009 onwards: 0.18 

Annual rate limits for CTs in lbs/MMBtu: 

Natural gas CTs > 50 MW: 0.11 

Distillate oil CTs > 50 MW: 0.28 

Biologically derived fuel CTs > 50 MW: 0.15 

Natural gas CTs between 25 and 49 MW: 0.19 

Distillate oil CTs between 25 and 49 MW: 0.41 

Biologically derived fuel CTs between 25 and 

49 MW: 0.15 

Annual rate limits for CCs in lbs/MMBtu: 

Natural gas CCs > 25 MW: 0.04 

Distillate oil CCs > 25 MW: 0.18 

Biologically derived fuel CCs > 25 MWs: 0.15 

Natural gas CCs between 10 and 24 MW: 0.19 

Chapter NR 

446. Control of 

Mercury 

Emissions 

Hg 

2012 through 2014: 40% reduction in total Hg 

emissions for all coal-fired units in electric 

utilities with annual Hg emissions > 100 lbs 

2015 onwards: 90% removal of Hg content of 

fuel or 0.0080 lbs/GW-hr reduction in coal fired 

EGUs > 150 MW 

80% removal of Hg content of fuel or 0.0080 

lbs/GW-hr reduction in coal fired EGUs > 25 

MW 

2010 
Appendix 3-3.1 

Appendix 3-3 New Source Review (NSR) Settlements in EPA Base Case v.4.10 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Alabama Power 

James H. 

Miller Alabama Units 3 & 4 Install and operate FGD continuously 95% 12/31/2011 Operate existing SCR continuously 0.1 5/1/2008 0.03 12/31/2006 

With 45 days of settlement entry, APC must retire 7,538 SO2 emission allowances. 

APC shall trade, or oexchange Miller excemission allowanceof the APC 

Minnkota Power Cooperative Beginning 1/01/2006, Minnkota shall not emit more than 31,000 tons of SO2/year, no more than 26,000 tons beginning 2011, no more than 11,500 tons beginning 1/01/2012. If Unit 3 is not operational by 12/31/2015, then beginning 1/01/2014, the 

Unit 1 

Install and 

continuously 

operate FGD 

95% if wet 

FGD, 90% 

if dry 

12/31/2011

Install and 

continuously operate 

Over-fire AIR, or 

equivalent 

technology with 

emission rate < .36 

0.36 12/31/2009

0.03 if 

wet 

FGD, 

.015 if 

dry FGD

Milton R. 

Young Minnesota 

Unit 2 

Design, 

upgrade, and 

continuously 

operate FGD 

90% 12/31/2010

Install and 

continuously operate 

over-fire AIR, or 

equivalent 

technology with 

emission rate < .36 

0.36 12/31/2007 0.03 Before 2008 

Plant will surrender 4,346 allowances for each year 2012 – 2015, 8,693 allowances for years 2016 – 2018, 12,170 allowances for year 2019, and 14,886 allowances/year thereafter if Units 1 – 3 are operational by 12/31/2015. If only Units 1 and 2 are operational by12/31/2015, the plant shall retire 17,886 units in 2020 and thereafter. 

Minnkota sell or tradallowanceallocated 2, or 3 thaotherwise available ftrade as a the actionthe settlindefendantcomply wirequireme

SIGECO 

FB Culley Indiana Unit 1 

Repower to 

natural gas 

(or retire) 

12/31/2006 

The provision did not specify an amount of SO2 allowances to be surrendered. It only provided that excess allowances resulting from compliance with NSR settlement provisions must be retired. 
Appendix 3-3.2 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Unit 2 

Improve and 

continuously 

operate existing 

FGD (shared by 

Units 2 and 3) 

95% 6/30/2004 

Unit 3 

Improve and 

continuously 

operate existing 

FGD (shared by 

Units 2 and 3) 

95% 6/30/2004 Operate Existing SCR Continuously 0.1 9/1/2003 Install and continuously operate a Baghouse 0.015 6/30/2007 

PSEG FOSSIL 

Bergen New Jersey Unit 2 

Repower to 

combined 

cycle 

12/31/2002 

The provision did not specify an amount of SO2 allowances to be surrendered. It only provided that excess allowances resulting from compliance with NSR settlement provisions must be retired. 

Hudson New Jersey Unit 2 

Install Dry FGD 

(or approved alt. 

technology) and 

continually 

operate 

0.15 12/31/2006

Install SCR (or 

approved tech) and 

continually operate 

0.1 5/1/2007 

Install Baghouse (or 

approved 

technology) 

0.015 12/31/2006 

Mercer New Jersey Units 1 & 2 

Install Dry FGD 

(or approved alt. 

technology) and 

continually 

operate 

0.15 12/31/2010

Install SCR (or 

approved tech) and 

continually operate 

0.13 5/1/2006 

TECO 

Units 1 & 

2 

Existing 

Scrubber 

(shared by Units 

1 & 2) 

95% (95% 

or .25) 

09/1/00 

(01/01/13) Big Bend Florida Install SCR 0.1 5/1/2009 

Unit 3 Existing Scrubber 93% if Units 3 & 4 2000 Install SCR 0.1 5/1/2009 

The provision did not 

specify an amount of 

SO2 allowances to be 

surrendered. It only 

provided that excess 

allowances resulting 
Appendix 3-3.3 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

(shared by Units 

3 & 4) 

are 

operating (01/01/10) 

Unit 4 

Existing 

Scrubber 

(shared by Units 

3 & 4) 

93% if 

Units 3 & 4 

are 

operating 

6/22/2005 Install SCR 0.1 7/1/2007 

from compliance with 

NSR settlement 

provisions must be 

retired. 

Gannon Florida Six units 

Retire all six 

coal units 

and 

repower at 

least 550 

MW of coal 

capacity to 

natural gas 

12/31/2004 

WEPCO WEPCO shall comply with the following system wide average NOx emission rates and total NOx tonnage permissible: by 1/1/2005 an emission rate of 0.27 and 31,500 tons, by 1/1/2007 an emission rate of 0.19 and 23,400 tons, and by 1/1/2013 aand 17, 400 tons. For SO2 emissions, WEPCO will comply with: by 1/1/2005 an emission rate of 0.76 and 86,900 tons, by 1/1/2007 an emission rate of 0.61 and 74,400 tons, by 1/1/2008 an emission rate of 0.45 and 55,400 tons, and by 1/1/201and 33,300 tons. 

Units 1 – 

4 

Retire or 

install SO2

and NOx

controls 

12/31/2012 

Install and 

continuously 

operate FGD (or 

approved equiv. 

tech) 

95% or 0.1 12/31/2012

Install SCR (or 

approved tech) and 

continually operate 

0.1 12/31/2012

Units 5 & 

6 

Install and operate 

low NOx burners 12/31/2003

Units 7 & 

8 

Operate existing low 

NOx burners 12/31/2005 Install Baghouse 

Presque Isle Wisconsin 

Unit 9 Operate existing low NOx burners 12/31/2006 Install Baghouse 

1 

Install and 

continuously 

operate FGD (or 

approved control 

tech) 

95% or 0.1 12/31/2006

Install and 

continuously operate 

SCR (or approved 

tech) 

0.1 12/31/2006

Pleasant 

Prairie Wisconsin 

2 

Install and 

continuously 

operate FGD (or 

approved control 

tech) 

95% or 0.1 12/31/2007

Install and 

continuously operate 

SCR (or approved 

tech) 

0.1 12/31/2003

The provision did not 

specify an amount of 

SO2 allowances to be 

surrendered. It only 

provided that excess 

allowances resulting 

from compliance with 

NSR settlement 

provisions must be 

retired. 
Appendix 3-3.4 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Units 5 & 

6 

Install and 

continuously 

operate FGD (or 

approved control 

tech) 

95% or 0.1 12/31/2012

Install and 

continuously operate 

SCR (or approved 

tech) 

0.1 12/31/2012

Unit 7 

Install and 

continuously 

operate FGD (or 

approved control 

tech) 

95% or 0.1 12/31/2012

Install and 

continuously operate 

SCR (or approved 

tech) 

Oak Creek Wisconsin 0.1 12/31/2012

Unit 8 

Install and 

continuously 

operate FGD (or 

approved control 

tech) 

95% or 0.1 12/31/2012

Install and 

continuously operate 

SCR (or approved 

tech) 

0.1 12/31/2012

Port 

Washington Wisconsin Units 1 – 4 Retire 

12/31/04 for 

Units 1 – 3. 

 Unit 4 by 

entry of 

consent 

decree 

Valley Wisconsin Boilers 1 – 4 Operate existing low NOx burner 

30 days 

after entry 

of consent 

decree 

VEPCO The Total Permissible NOx Emissions (in tons) from VEPCO system are: 104,000 in 2003, 95,000 in 2004, 90,000 in 2005, 83,000 in 2006, 81,000 in 2007, 63,000 in 2008 – 2010, 54,000 in 2011, 50,000 in 2012, and 30,250 each year there afterwill have a system wide emission rate no greater then 0.15 lb/MMBtu. 

Mount Storm West Virginia Units 1 – 3 Construct or improve FGD 95% or 0.15 1/1/2005 Install and continuously operate SCR 0.11 1/1/2008 

Unit 4 

Install and 

continuously operate 

SCR 

0.1 1/1/2013 

Unit 5 Construct or improve FGD 95% or 0.13 10/12/2012 Install and continuously operate SCR Chesterfield Virginia 0.1 1/1/2012 Unit 6 Construct or improve FGD 95% or 0.13 1/1/2010 Install and continuously operate SCR 0.1 1/1/2011 

Chesapeake 

Energy Virginia Units 3 & 4 Install and continuously operate SCR 0.1 1/1/2013 

On or before March 

31 of every year 

beginning in 2013 

and continuing 

thereafter, VEPCO 

shall surrender 

45,000 SO2

allowances. 
Appendix 3-3.5 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Clover Virginia Units 1 & 2 Improve FGD 95% or 0.13 9/1/2003 

Possum 

Point Virginia Units 3 & 4 Retire and repower to natural gas 5/2/2003 

Santee Cooper Santee Cooper shall comply with the following system wide averages for NOx emission rates and combined tons for emission of: by 1/01/2005 facility shall comply with an emission rate of 0.3 and 30,000 tons, by 1/1/2007 an emission rate of 0.18 1/1/2010 and emission rate of 0.15 and 20,000 tons. For SO2 emission the company shall comply with system wide averages of: by 1/1/2005 an emission rate of 0.92 and 95,000 tons, by 1/1/2007 and emission rate of 0.75 and 85,000 tons, by 1of 0.53 and 70 tons, and by 1/1/2011 and emission rate of 0.5 and 65 tons. 

Unit 1 

Upgrade and 

continuously 

operate FGD 

95% 6/30/2006 

Install and 

continuously operate 

SCR 

0.1 5/31/2004 

Cross South Carolina 

Unit 2 

Upgrade and 

continuously 

operate FGD 

87% 6/30/2006 

Install and 

Continuously 

operate SCR 

0.11/0.1 

05/31/04 

and 

05/31/07 

Unit 1 

Install and 

continuously 

operate FGD 

95% 12/31/2008

Install and 

continuously operate 

SCR 

0.11/0.1 

11/30/04 

and 

11/30/04 

Unit 2 

Install and 

continuously 

operate FGD 

95% 12/31/2008

Install and 

continuously operate 

SCR 

0.12 11/30/2004

Unit 3 

Upgrade and 

continuously 

operate existing 

FGD 

90% 12/31/2008

Install and 

continuously operate 

SCR 

0.14/0.12 

11/30/2005 

and 

11/30/08 

Winyah South Carolina 

Unit 4 

Upgrade and 

continuously 

operate existing 

FGD 

90% 12/31/2007

Install and 

continuously operate 

SCR 

0.13/0.12 

11/30/05 

and 

11/30/08 

Unit 1 

Operate low NOx

burner or more 

stringent technology

6/25/2004 

Grainger South Carolina 

Unit 2 

Operate low NOx

burner or more 

stringent technology

5/1/2004 

The provision did not 

specify an amount of 

SO2 allowances to be 

surrendered. It only 

provided that excess 

allowances resulting 

from compliance with 

NSR settlement 

provisions must be 

retired. 
Appendix 3-3.6 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Jeffries South Carolina Units 3, 4 Operate low NOx burner or more stringent technology 6/25/2004 

Ohio Edison Ohio Edison shall achieve reductions of 2,483 tons NOx between 7/1/2005 and 12/31/2010 using any combination of: 1) low sulfur coal at Burger Units 4 and 5, 2) operating SCRs currently installed at Mansfield Units 1 – 3 during the months of Oand/or 3) emitting fewer tons than the Plant-Wide Annual Cap for NOx required for the Sammis Plant. Ohio Edison must reduce 24,600 tons system-wide of SO2 by 12/31/2010. No later than 8/11/2005, Ohio Edison shall install and operate low NOx burners on Sammis Units 1 - 7 and overfired air on Sammis Units 1,2,3,6, and 7. No later than 12/1/2005, Ohio Edison shall install advanced combustion control optimization NOx emissions from Sammis Units 1 – 5. 

Install Induct 50% removal Install SNCR 

Scrubber (or or 1.1 lb/MMBtu (or approved 

approved equiv. alt. tech) & 

control tech) operate 

Unit 1 12/31/2008

continuously 

0.25 10/31/2007

Install Induct 50% removal Operate 

Scrubber (or or 1.1 lb/MMBtu existing SNCR 

approved equiv. continuously 

Unit 2 

control tech) 

12/31/2008 0.25 2/15/2006 

Install Induct 50% removal 

Operate low NOx

burners and overfire 

air by 12/1/05; install 

SNCR 

12/1/2005 

Scrubber (or or 1.1 lb/MMBtu (or approved and 

approved equiv. alt. tech) & 10/31/2007

control tech) operate 

Unit 3 12/31/2008

continuously by 

12/31/07 

0.25 

Install Induct 50% removal Install SNCR 

W.H. 

Sammis 

Plant 

Ohio 

Unit 4 

Scrubber (or or 1.1 lb/MMBtu 

6/30/2009 

(or approved 

0.25 10/31/2007

Beginning on 

1/1/2006, Ohio 

Edison may use, sell 

or transfer any 

restricted SO2 only to 

satisfy the 

Operational Needs at 

the Sammis, Burger 

and Mansfield Plant, 

or new units within 

the FirstEnergy 

System that comply with a 96% removal 

for SO2. For 

calendar year 2006 

through 2017, Ohio 

Edison may 

accumulate SO2

allowances for use at 

the Sammis, Burger, 

and Mansfield plants, 

or FirstEnergy units 

equipped with SO2

Emission Control 

Standards. 

Beginning in 2018, 

Ohio Edison shall 

surrender unused 

restricted SO2

allowances. 
Appendix 3-3.7 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

approved equiv. alt. tech) & 

control tech) operate 

continuously 

Install Flash 50% removal Install SNCR 

Dryer Absorber or 1.1 lb/MMBtu (or approved 

or ECO2 (or alt. tech) & 

approved equiv. Operate 

control tech) & Continuously 

operate 

Unit 5 

continuously 

6/29/2009 0.29 3/31/2008 

Install FGD3 (or Install SNCR "Minimum Operate 

approved equiv. (or approved Extent Existing 

control tech) & alt. tech) & Practicable" ESP 

operate operate Continuously 

Unit 6 

continuously 

95% 

removal or 

0.13 

lb/MMBtu 

6/30/2011 

continuously 

6/30/2005 0.03 1/1/2010 

Install FGD (or Operate "Minimum Operate 

approved equiv. existing SNCR Extent Existing 

control tech) & Continuously Practicable" ESP 

operate Continuously 

Unit 7 

continuously 

95% 

removal or 

0.13 

lb/MMBtu 

6/30/2011 8/11/2005 0.03 1/1/2010 

Upgrade 

Unit 1 

existing FGD 

95% 12/31/2005

Upgrade 

Mansfield 

Plant 

Pennsylvani

a 

Unit 2 

existing FGD 

95% 12/31/2006
Appendix 3-3.8 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Upgrade 

Unit 3 

existing FGD 

95% 10/31/2007

Install low NOx

"Minimize 

Emissions to 

the 

burners, over-fired Extent Eastlake Ohio Unit 5 

air and SNCR & 

operate continuously Practicable" 

12/31/2006

Unit 4 12/31/2011 

Burger Ohio 

Unit 5 

Repower 

with at least 

80% 

biomass 

fuel, up to 

20% low 

sulfur coal. 

12/31/2011 

MirantI1,6System-wide NOx Emission Annual Caps: 36,500 tons 2004; 33,840 tons 2005; 33,090 tons 2006; 28,920 tons 2007; 22,000 tons 2008; 19,650 tons 2009; 16,000 tons 2010 onward. System-wide NOx Emission Ozone Season Caps: 14,700 tons 12,590 tons 2006; 10,190 tons 2007; 6,150 tons 2008 – 2009; 5,200 tons 2010 thereafter. Beginning on 5/1/2008, and continuing for each and every Ozone Season thereafter, the Mirant System shall not exceed a System-wide Ozone Season Elb/MMBtu NOx. 

Unit 1 Unit 2 

Install low NOx

burners (or more Unit 3 effective tech) & 

operate continuously 

5/1/2004 

Install low NOx

burners (or more Unit 4 effective tech) & 

operate continuously 

5/1/2004 

Install low NOx

burners (or more 

effective tech) & 

Potomac 

River Plant Virginia 

Unit 5 

operate continuously 

5/1/2004 
Appendix 3-3.9 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Install SCR 

(or approved 

alt. tech) & 

Unit 1 

operate continuously 

0.1 5/1/2007 

Install SCR 

(or approved 

alt. tech) & 

Morgantown 

Plant Maryland 

Unit 2 

operate continuously 

0.1 5/1/2008 

Unit 1 

Install and 

continuously 

operate FGD (or 

equiv. 

technology) 

95% 6/1/2010 

Chalk Point Maryland 

Unit 2 

Install and 

continuously 

operate FGD (or 

equiv. 

technology) 

95% 6/1/2010 

For each year after 

Mirant commences 

FGD operation at 

Chalk Point, Mirant 

shall surrender the 

number of SO2

Allowances equal to 

the amount by which 

the SO2 Allowances 

allocated to the Units 

at the Chalk Point 

Plant are greater than 

the total amount of 

SO2 emissions 

allowed under this 

Section XVIII. 

Illinois Power System-wide NOx Emission Annual Caps: 15,000 tons 2005; 14,000 tons 2006; 13,800 tons 2007 onward. System-wide SO2 Emission Annual Caps: 66,300 tons 2005 – 2006; 65,000 tons 2007; 62,000 tons 2008 – 2010; 57,000 tons 2011; 49,52013 onward. 

Units 1 & 

2 

Install wet or dry 

FGD (or 

approved equiv. 

alt. tech) & 

operate 

continuously 

0.1 12/31/2011

Operate OFA & 

existing SCR 

continuously 

0.1 8/11/2005 

Install & 

continuously 

operate Baghouse 

0.015 12/31/2010 

Baldwin Illinois 

Unit 3 

Install wet or dry 

FGD (or 

approved equiv. 

alt. tech) & 

operate 

continuously 

0.1 12/31/2011 Operate OFA and/or low NOx burners 0.12 until 12/30/12; 0.1 from 12/31/12 08/11/05 and 12/31/12 Install & continuously operate Baghouse 0.015 12/31/2010 

By year end 2008, 

Dynergy will 

surrender 12,000 

SO2 emission 

allowances, by year 

end 2009 it will 

surrender 18,000, by 

year end 2010 it will 

surrender 24,000, 

any by year end 2011 

and each year 

thereafter it will 

surrender 30,000 

allowances. If the 
Appendix 3-3.10 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

8/11/2005 

For 

Baghouse: 

12/31/12; 

and For ESP: Havana 12/31/05 Illinois Unit 6 

Install wet or dry 

FGD (or 

approved equiv. 

alt. tech) & 

operate 

continuously 

1.2 

lb/MMBtu 

until 

12/30/2012

; 0.1 

lb/MMBtu 

from 

12/31/2012 

onward 

12/31/2012

Operate OFA and/or 

low NOx burners & 

operate existing 

SCR continuously 

0.1 8/11/2005 

Install & 

continuously 

operate Baghouse, 

then install ESP or 

alt. PM equip 

For Baghouse: 

0.015 

lb/MMBt

u; For 

ESP: 

0.03 

lb/MMBt

u 

Operate OFA "Minimum 

and/or low NOx

burners Unit 1 1.2 7/27/2005 Extent 

Practicable" 

8/11/2005 

Install ESP (or 

equiv. alt. tech) & 

continuously 

operate ESPs 

0.03 12/31/2006 

Operate OFA "Minimum 

and/or low NOx

burners Extent 

Hennepin Illinois 

Unit 2 1.2 7/27/2005 

Practicable" 

8/11/2005 

Install ESP (or 

equiv. alt. tech) & 

continuously 

operate ESPs 

0.03 12/31/2006 

Operate OFA "Minimum 

and/or low NOx

burners Vermilion Illinois Extent Units 1 & 2 1.2 1/31/2007 

Practicable" 

8/11/2005 

Install ESP (or 

equiv. alt. tech) & 

continuously 

operate ESPs 

0.03 12/31/2010 

Operate OFA "Minimum 

and/or low NOx

burners Wood River Illinois Extent Units 4 & 5 1.2 7/27/2005 

Practicable" 

8/11/2005 

Install ESP (or 

equiv. alt. tech) & 

continuously 

operate ESPs 

0.03 12/31/2005 

surrendered 

allowances result in 

insufficient remaining 

allowances allocated 

to the units 

comprising the DMG 

system, DMG can 

request to surrender 

fewer SO2

allowances. 

Kentucky Utilities Company 

EW Brown 

Generating 

Station 

Kentucky Unit 3 Install FGD 97% or 0.100 12/31/2010

Install and 

continuously operate 

SCR by 12/31/2012, 

continuously operate 

low NOx boiler and 

OFA. 

0.07 12/31/2012 Continuously operate ESP 0.03 12/31/2010 

KU must surrender 

53,000 SO2

allowances of 2008 

or earlier vintage by 

March 1, 2009. All 

surplus NOx

allowances must be 

surrendered through 

2020. 

SO2 a

allowance

be us

complia

emis

decrea

purpo

complyin

Consent 

not earn 

Salt River Project Agricultural Improvement and Power District (SRP) 
Appendix 3-3.11 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Unit 1 or 

Unit 2 

Immediately 

begin 

continuous 

operation of 

existing FGDs 

on both units, 

install new FGD.

95% or 

0.08 

New FGD 

installed by 

1/1/2012 

Install and 

continuously operate 

low NOx burner and 

SCR 

0.32 prior to 

SCR 

installation, 

0.080 after 

LNB by 

06/01/2009

, SCR by 

06/01/2014

Optimization 

begins 

immediately, 

rate limit 

begins 

01/01/12 

(date of new 

FGD 

installation) Coronado Generating 

Station 

Arizona 

Unit 1 or 

Unit 2 Install new FGD 95% or 0.08 1/1/2013 Install and continuously operate low NOx burner 0.32 6/1/2011 

Optimization and 

continuous 

operation of existing 

ESPs. 

0.03 Optimization 

begins 

immediately, 

rate limit 

begins 

01/01/13 

(date of new 

FGD 

installation) 

Beginning in 2012, all 

surplus SO2

allowances for both 

Coronado and 

Springerville Unit 4 

must be surrendered 

through 2020. The 

allowances limited by 

this condition may, 

however, be used for 

compliance at a 

prospective future 

plant using BACT 

and otherwise 

specified in par. 54 of 

the consent decree. 

SO2 a

allowance

be us

complia

emis

decrea

purpo

complyin

Consent 

not earn 

American Electric Power 

Annual Cap 

(tons) Year Annual Cap (tons) Year 

450,000 2010 96,000 2009 450,000 2011 92,500 2010 420,000 2012 92,500 2011 350,000 2013 85,000 2012 340,000 2014 85,000 2013 275,000 2015 85,000 2014 260,000 2016 75,000 2015 235,000 2017 72,000 2016 and thereafter 184,000 2018 

Eastern System-Wide 

174,000 2019 and thereafter 

NOx and SO2

allowances that 

would have been 

made available by 

emission reductions 

pursuant to the 

Consent Decree 

must be surrendered.

NOx a

allowance

be used 

with any o

impose

Consen

The C

Decree i

formu

calculatin

NOx allo

relative to 

Allocati

restricts 

some. Se

79 for 

Reducing 

below th

System

Annual 

Limitation

and SO

super co

allowa

Sporn West 

Virginia 1 – 4 

Clinch 

River Virginia 

1 – 3 

At least 

600MW from 

various units 

Indiana Tanners Creek 

Retire, 

retrofit, or 

re-power 

12/31/2018 
Appendix 3-3.12 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

1 – 3 

Kammer West 

Virginia 1 – 3 

Unit 1 

Install and 

continuously 

operate FGD 

12/31/2009

Install and 

continuously operate 

SCR 

1/1/2008 

Unit 2 

Install and 

continuously 

operate FGD 

12/31/2010

Install and 

continuously operate 

SCR 

Amos 1/1/2009 West Virginia 

Unit 3 

Install and 

continuously 

operate FGD 

12/31/2009

Install and 

continuously operate 

SCR 

1/1/2008 

Unit 1 

Burn only coal 

with no more 

than 1.75 

lb/MMBtu 

annual average

Date of 

entry 

Continuously 

operate low NOx

burners 

Date of 

entry 

Big Sandy Kentucky 

Unit 2 

Install and 

continuously 

operate FGD 

12/31/2015

Install and 

continuously operate 

SCR 

1/1/2009 

Unit 1 

Install and 

continuously 

operate FGD 

12/31/2008

Install and 

continuously operate 

SCR 

1/1/2009 Continuously operate ESP 0.03 12/31/2009 

Unit 2 

Install and 

continuously 

operate FGD 

12/31/2008

Install and 

continuously operate 

SCR 

1/1/2009 Continuously operate ESP Cardinal Ohio 0.03 12/31/2009 

Unit 3 

Install and 

continuously 

operate FGD 

12/31/2012

Install and 

continuously operate 

SCR 

1/1/2009 

Clinch River Virginia Units 1 – 3 

Plant-wide 

annual cap: 

 21,700 

tons from 

2010 to 

2014, then 

16,300 

after 

1/1/2015 

2010 – 

2014, 2015 

and 

thereafter 

Continuously 

operate low NOx

burners 

Date of 

entry 

Unit 1 

Retire, 

retrofit, or 

re-power 

Date of 

entry Conesville Ohio 

Unit 2 

Retire, 

retrofit, or 

re-power 

Date of 

entry 
Appendix 3-3.13 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Unit 3 

Retire, 

retrofit, or 

re-power 

12/31/2012 

Unit 4 

Install and 

continuously 

operate FGD 

12/31/2010

Install and 

continuously operate 

SCR 

12/31/2010

Unit 5 Upgrade existing FGD 95% 12/31/2009 Continuously operate low NOx burners Date of entry Unit 6 Upgrade existing FGD 95% 12/31/2009 Continuously operate low NOx burners Date of entry Unit 1 

Install and 

continuously 

operate FGD 

Date of 

entry 

Install and 

continuously operate 

SCR 

1/1/2009 

Gavin Ohio 

Unit 2 

Install and 

continuously 

operate FGD 

Date of 

entry 

Install and 

continuously operate 

SCR 

1/1/2009 

Glen Lyn Virginia Units 5, 6 

Burn only coal 

with no more 

than 1.75 

lb/MMBtu 

annual average

Date of 

entry 

Continuously 

operate low NOx

burners 

Date of 

entry 

Kammer West Virginia Units 1 – 3 Plant-wide annual cap: 35,000 1/1/2010 Continuously operate over-fire air Date of entry 

Kanawha 

River 

West 

Virginia Units 1, 2 

Burn only coal 

with no more 

than 1.75 

lb/MMBtu 

annual average

Date of 

entry 

Continuously 

operate low NOx

burners 

Date of 

entry 

Unit 1 

Install and 

continuously 

operate FGD 

12/31/2007

Install and 

continuously operate 

SCR 

1/1/2009 

Mitchell West Virginia 

Unit 2 

Install and 

continuously 

operate FGD 

12/31/2007

Install and 

continuously operate 

SCR 

1/1/2009 

Mountaineer West Virginia Unit 1 Install and continuously operate FGD 12/31/2007 Install and continuously operate SCR 1/1/2008 

Muskingum 

River Ohio Units 1 – 4 Retire, retrofit, or 

re-power 

12/31/2015 
Appendix 3-3.14 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Unit 5 

Install and 

continuously 

operate FGD 

12/31/2015

Install and 

continuously operate 

SCR 

1/1/2008 Continuously operate ESP 0.03 12/31/2002 

Picway Ohio Unit 9 

Continuously 

operate low NOx

burners 

Date of 

entry 

Unit 1 

Install and 

continuously 

operate FGD 

12/31/2017

Install and 

continuously operate 

SCR 

12/31/2017

Rockport Indiana 

Unit 2 

Install and 

continuously 

operate FGD 

12/31/2019

Install and 

continuously operate 

SCR 

12/31/2019

Sporn West Virginia Unit 5 Retire, retrofit, or re-power 12/31/2013 

Units 1 - 

3 

Burn only coal 

with no more 

than 1.2 

lb/MMBtu 

annual average

Date of 

entry 

Continuously 

operate low NOx

burners 

Date of 

entry 

Tanners 

Creek Indiana 

Unit 4 

Burn only coal 

with no more 

than 1.2% sulfur 

content annual 

average 

Date of 

entry 

Continuously 

operate over-fire air

Date of 

entry 

East Kentucky Power Cooperative Inc. By 12/31/2009, EKPC shall choose whether to: 1) install and continuously operate NOx controls at Cooper 2 by 12/31/2012 and SO2 controls by 6/30/2012 or 2) retire Dale 3 and Dale 4 by 12/31/2012. 

12-month 

rolling limit 

(tons) 

Start of 12-

month cycle

12-month 

rolling limit 

(tons) 

Start of 12-

month 

cycle 

57,000 10/1/2008 11,500 1/1/2008 40,000 7/1/2011 8,500 1/1/2013 

System-wide 

System-wide 12-

month rolling 

tonnage limits 

apply 

28,000 1/1/2013 

All units must 

operate low NOx

boilers 

8,000 1/1/2015 

PM control devices 

must be operated 

continuously 

system-wide, ESPs 

must be optimized 

within 270 days of 

entry date, or EKPC 

may choose to 

submit a PM 

Pollution Control 

Upgrade Analysis. 

0.03 1 year from entry date 

All surplus SO2

allowances must be 

surrendered each year, beginning in 

2008. 

SO2 a

allowance

be used 

with the 

Decre

allowan

would 

available 

of compl

the Conse

may not 

traded. 

NOx allo

allocated 

must be u

the EKPC 

Allowanc

availab

super co

may be 

trad
Appendix 3-3.15 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Unit 1 

Install and 

continuously 

operate FGD 

95% or 0.1 6/30/2011 Continuously operate SCR 

0.12 for Unit 1 

until 

01/01/2013, at 

which point the 

unit limit drops 

to 0.1. Prior to 

01/01/2013, the 

combined 

average when 

both units are 

operating must 

be no more 

than 0.1 

60 days 

after entry 

Spurlock Kentucky 

Unit 2 

Install and 

continuously 

operate FGD by 

10/1/2008 

95% or 0.1 1/1/2009 

Continuously 

operate SCR and 

OFA 

0.1 for Unit 2, 

0.1 combined 

average when 

both units are 

operating 

60 days 

after entry 

Unit 1 

Install and 

continuously operate 

low NOx burners by 

10/31/2007 

0.46 1/1/2008 

Unit 2 

Install and 

continuously operate 

low NOx burners by 

10/31/2007 

0.46 1/1/2008 

EKPC must 

surrender 1,000 NOx

allowances 

immediately under 

the ARP, and 3,107 

under the NOx SIP 

Call. EKPC must 

also surrender 

15,311 SO2

allowances. 

Unit 3 

EKPC may 

choose to 

retire Dale 3 

and 4 in lieu 

of installing 

controls in 

Cooper 2 

12/31/2012 

Dale Plant Kentucky 

Unit 4 

Cooper Kentucky Unit 1 
Appendix 3-3.16 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Unit 2 

If EKPC opts to 

install controls 

rather than 

retiring Dale, it 

must install and 

continuously 

operate FGD or 

equiv. 

technology 

95% or 

0.10 

If EKPC elects to 

install controls, it 

must continuously 

operate SCR or 

install equiv. 

technology 

0.08 (or 90% if 

non-SCR 

technology is 

used) 

12/31/2012

Nevada Power Company Beginning 1/1/2010, combined NOx emissions from Units 5, 6, 7, and 8 must be no more than 360 tons per year. 

Unit 5 5ppm 1-hour 

average 

12/31/08 

(ULNB 

installation)

, 01/30/09 

(1-hour 

average) 

Unit 6 5ppm 1-hour 

average 

12/31/09 

(ULNB 

installation)

, 01/30/10 

(1-hour 

average) 

Unit 7 5ppm 1-hour 

average 

12/31/09 

(ULNB 

installation)

, 01/30/10 

(1-hour 

average) 

Clark 

Generating 

Station 

Nevada 

Unit 8 

Units may only fire 

natural gas 

Increase water 

injection 

immediately, then 

install and operate 

ultra-low NOx

burners (ULNBs) or 

equivalent 

technology. In 2009, 

Units 5 and 8 may 

not emit more than 

180 tons combined 

5ppm 1-hour 

average 

12/31/08 

(ULNB 

installation)

, 01/30/09 

(1-hour 

average) 

Allowance

be used 

with the 

Decree

allowanc

availab

complianc

Consen

may be 

so

Dayton Power & Light Non-EPA Settlement of 10/23/2008 

Owners may not 

purchase any new 

catalyst with SO2 to 

SO3 conversion rate 

greater than 0.5% 

0.17 stationwide 30 days after entry Stuart Generating Station Ohio Station- wide Complete installation of 

FGDs on each 

unit. 

96% or 

0.10 7/31/2009 

0.17 stationwide 60 days after entry date 

0.030 lb 

per unit 7/31/2009 

NOx a

allowance

be used 

with the 

rates sp

the C

Dec
Appendix 3-3.17 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

82% 

including 

data from 

periods of 

malfunction

s 

7/31/09 

through 

7/30/11 

Install control 

technology on one 

unit 

0.10 on any 

single unit 12/31/2012

0.15 stationwide 7/1/2012 82% including 

data from 

periods of 

malfunction

s 

after 

7/31/11 0.10 stationwide 12/31/2014

Install 

rigid-type 

electrodes in 

each 

unit's 

ESP 

12/31/2015 

PSEG FOSSIL, Amended Consent Decree of November 2006 

Unit 7 Retire unit 1/1/2007 

Kearny New Jersey 

Unit 8 Retire unit 1/1/2007 

Allowances allocated 

to Kearny, Hudson, 

and Mercer may only 

be used for the 

operational needs of 

those units, and all 

surplus allowances 

must be surrendered. 

 Within 90 days of 

amended Consent 

Decree, PSEG must 

surrender 1,230 NOx

Allowances and 

8,568 SO2

Allowances not 

already allocated to 

or generated by the 

units listed here. 

Kearny allowances 

must be surrendered 

with the shutdown of 

those units. 

0.15 12/31/2010 0.1 12/31/2010

Annual Cap 

(tons) Year Annual Cap (tons) Year 

5,547 2007 3,486 2007 5,270 2008 3,486 2008 5,270 2009 3,486 2009 

Hudson New Jersey Unit 2 

Install Dry FGD 

(or approved alt. 

technology) and 

continually 

operate 

5,270 2010 

Install SCR (or 

approved tech) and 

continually operate 

3,486 2010 

Install Baghouse (or 

approved 

technology) 

0.015 12/31/2010 
Appendix 3-3.18 

Settlement Actions 

Retire/Repower SO2 control NOx Control PM or Mercury Control Allowance Retirement Allo

Company 

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date Retirement Restr

Mercer New Jersey Units 1 & 2 

Install Dry FGD 

(or approved alt. 

technology) and 

continually 

operate 

0.15 12/31/2010

Install SCR (or 

approved tech) and 

continually operate 

0.1 1/1/2007 

Install Baghouse (or 

approved 

technology) 

0.015 12/31/2010 

Westar Energy 

Units 1, 2, and 3 have a total annual limit of 

6,600 tons of SO2 starting 2011 

Units 1-3 must continuously operate Low NOx

Combustion Systems by 2012 and achieve and 

maintain a 30-Day Rolling Average Unit Emission 

Rate for NOx of no greater than 0.180 lb/MMBtu. 

Units 1, 2, and 3 must operate each ESP and 

FGD system continuously by 2011 and 

maintain a 0.030 lb/MMBtu PM Emissions 

Rate. 

Units 1, 2, and 3 must all install FGDs by 

2011 and operate them continuously. 

One of the three units must install an SCR by 2015 

and operate it continuously to maintain a 30-Day 

Rolling Average Unit Emission Rate for NOx of no 

greater than 0.080 lb/MMBtu. 

Units 1 and 2’s ESPs must be rebuilt by 2014 

in order to meet a 0.030 lb/MMBtu PM 

Emissions Rate 

Jeffrey 

Energy 

Center 

Kansas All units 

FGDs must maintain a 30-Day Rolling 

Average Unit Removal Efficiency for SO2 of 

at least 97% or a 30-Day Rolling Average 

Unit Emission Rate for SO2 of no greater 

than 0.070 lb/MMBtu. 

By 2013 Westar shall elect to either (a) install a 

second SCR on one of the other JEC Units by 

2017 or (b) meet a 0.100 lb/MMBtu Plant-Wide 12-

Month Rolling Average Emission Rate for NOx by 

2015 

Duke Energy 

Units 1 & 

3 

Retire or 

repower as natural gas 

1/1/2012 

Gallagher Indiana 

Units 2 & 

4 

Install Dry 

sorbent injection 

technology 

80% 1/1/2012 

Notes:1) This summary table describes New Source Review settlement actions as they are represented in EPA Base Case v.4.10. The settlement actions are simplified for representation in the model. This table is not intended to be a comprehensive settlement agreements. 2) Settlement actions for which the required emission limits will be effective by the time of the first mapped run year (before 1/1/2012) are built into the database of units used in EPA Base Case v.4.10 ("hardwired"). However, future actions are gemission rates in EPA Base Case v.4.10, allowing the modeled economic situation to dictate whether and when a unit would opt to install controls versus retire. 3) Some control installations that are required by these NSR settlements have already been taken by the affected companies, even if deadlines specified in their settlement haven't occurred yet. Any controls that are already in place are built into 4) If a settlement agreement requires installation of PM controls, then the controls are shown in this table and reflected in EPA Base Case v.4.10. If settlement requires optimization or upgrade of existing PM controls, those actions are not includ5) For units for which an FGD is modeled as an emissions constraint in EPA Base Case v.4.10, EPA used the assumptions on removal efficiencies that are shown in Table 5-4 of this documentation report. 6) For units for which an FGD is hardwired in EPA Base Case v.4.10, unless the type of FGD is specified in the settlement, EPA modeling assumes the most cost effective FGD (wet or dry) and a corresponding 98% removal efficiency for wet an7) For units for which an SCR is modeled as an emissions constraint or is hardwired in EPA Base Case v.4.10, EPA assumed an emissions rate equal to 10% of the unit's uncontrolled rate, with a floor of .06 lb/MMBtu or used the emission limit if 8) The applicable low NOx burner reduction efficiencies are shown in Table A 3-1:3 in the Base Case v.4.10 documentation materials. 9) EPA included in EPA Base Case v.4.10 the requirements of the settlements as they existed at the second quarter of 2010. 10) Some of the NSR settlements require the retirement of SO2 allowances. For EPA Base Case v.4.10, EPA estimates the amount of allowances to be retired from these settlements and adjusted the total Title IV allowances accordingly. 
Appendix 3-4.1 

Appendix 3-4 State Settlements in EPA Base Case v.4.10 

State Enforcement Actions 

Company and Retire/Repower SO2 control NOx Control PM Control 

Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date 

AES 

Unit 4 Install FGD 90% 9/1/2007 Install SCR 0.15 9/1/2007 

Greenidge New York 

Unit 3 Install BACT 12/31/2009 Install BACT 12/31/2009 Unit 8 90% 12/31/2010 Install SCR 0.15 12/31/2010 

Westover New York 

Unit 7 Install BACT 12/31/2009 Install BACT 12/31/2009 

Hickling New York Units 1 & 2 Install BACT 5/1/2007 Install BACT 5/1/2007 

Jennison New York Units 1 & 2 Install BACT 5/1/2007 Install BACT 5/1/2007 

Niagara Mohawk Power NRG shall comply with the below annual tonnage limitations for its Huntley and Dunkirk Stations: 2005 is 59,537 tons of SO2 and 10,777 tons of NOx, 2006 is 34,230 of SO2 and 6,772 of NOx, 2007 is 3022,733 tons of SO2

Huntley New York Units 63 – 66 Retire Before 2008 

Public Service Co. of NM 

Unit 1 10/31/2008 10/31/2008 12/31/2009 Unit 2 3/31/2009 3/31/2009 12/31/2009 Unit 3 4/30/2008 4/30/2008 4/30/2008 

San Juan New Mexico 

Unit 4 

State-of-the-art 

technology 90% 

10/31/2007

State-of-the-art 

technology 0.3 

10/31/2007 

Operate 

Baghouse and 

demister 

technology 

0.02 

10/31/2007

ca

t

Public Service Co of Colorado 

Units 1 & 

2 

Install and 

operate FGD 

0.1 

lb/MMBtu 

combined 

average 

7/1/2009 Install low-NOx emission controls

0.15 

lb/MMBtu 

combined 

average 

7/1/2009 

I

0.1 Comanche Colorado 

Unit 3 Install and operate FGD lb/MMBtu Install and operate SCR 0.08 

Install and 

operate a 

fabric filter 

dust collection 

system 

0.01 

I
Appendix 3-4.2 

State Enforcement Actions 

Company and Retire/Repower SO2 control NOx Control PM Control 

Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date 

TVA 

Bull Run Tennessee Unit 1 Complete FGD installation 0.15 lb/MMBtu, 4,431 TPY 

FGD 

already 

active as of 

date of 

entry 

0.08 

lb/MMBtu, 

2,295 TPY

Unit 1 

0.15 

lb/MMBtu, 

1,023 TPY 

0.05 

lb/MMBtu, 

372 TPY 

Unit 2 

0.15 

lb/MMBtu, 

1,028 TPY 

0.05 

lb/MMBtu, 

374 TPY 

Unit 3 

0.15 

lb/MMBtu, 

1,081 TPY 

0.05 

lb/MMBtu, 

389 TPY 

John Sevier Tennessee 

Unit 4 

Install FGD 

0.15 

lb/MMBtu, 

1,000 TPY 

27 months 

from date 

of entry 

Install SCR 

0.05 

lb/MMBtu, 

360 TPY 

21 months 

from date of 

entry 

Unit 1 

0.15 

lb/MMBtu, 

794 TPY 

0.06 

lb/MMBtu, 

323 TPY 

Unit 2 

0.15 

lb/MMBtu, 

785 TPY 

0.06 

lb/MMBtu, 

320 TPY 

Unit 3 

0.15 

lb/MMBtu, 

822 TPY 

0.06 

lb/MMBtu, 

335 TPY 

Unit 4 

0.15 

lb/MMBtu, 

800 TPY 

0.06 

lb/MMBtu, 

326 TPY 

Unit 5 

0.15 

lb/MMBtu, 

1,021 TPY 

0.06 

lb/MMBtu, 

416 TPY 

Unit 6 

0.15 

lb/MMBtu, 

1,095 TPY 

0.05 

lb/MMBtu, 

365 TPY 

Unit 7 

0.15 

lb/MMBtu, 

1,040 TPY 

0.05 

lb/MMBtu, 

347 TPY 

Unit 8 

0.15 

lb/MMBtu, 

1,048 TPY 

0.05 

lb/MMBtu, 

349 TPY 

Kingston Tennessee 

Unit 9 

Install FGD 

0.15 

lb/MMBtu, 

1,012 TPY 

27 months 

from date 

of entry 

Operate existing 

SCR 

0.05 

lb/MMBtu, 

337 TPY 
Appendix 3-4.3 

State Enforcement Actions 

Company and Retire/Repower SO2 control NOx Control PM Control 

Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment Rate Effective Date 

Unit 1 

0.15 

lb/MMBtu, 

569 TPY 

0.06 

lb/MMBtu, 

246 TPY 

Unit 2 

0.15 

lb/MMBtu, 

608 TPY 

0.06 

lb/MMBtu, 

263 TPY 

Unit 3 

0.15 

lb/MMBtu, 

663 TPY 

0.06 

lb/MMBtu, 

287 TPY 

Unit 4 

0.15 

lb/MMBtu, 

602 TPY 

0.06 

lb/MMBtu, 

261 TPY 

Unit 5 

0.15 

lb/MMBtu, 

640 TPY 

0.06 

lb/MMBtu, 

277 TPY 

Unit 6 

Install FGD 

0.15 

lb/MMBtu, 

626 TPY 

27 months 

from date 

of entry 

Install SCR 

0.06 

lb/MMBtu, 

271 TPY 

21 months 

from date of 

entry 

Unit 7 

0.56 

lb/MMBtu, 

8950 TPY 

0.06 

lb/MMBtu, 

892 TPY 

Widows Creek Alabama 

Unit 8 

0.30 

lb/MMBtu, 

4,508 TPY 

0.06 

lb/MMBtu, 

860 TPY 

Rochester Gas & Electric 

Russell Plant New York Units 1 – 4 Retire all units 

Mirant New York 

Unit 1 Retire 5/7/2007 

Lovett Plant New York 

Unit 2 Retire 4/30/2008 
Appendix 3-5.1 

Appendix 3-5 Citizen Settlements in EPA Base Case v.4.10 

Citizen Suits Provided by DOJ 

Company Retire/Repower SO2 control NOx Control P

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment 

SWEPCO (AEP) 

Welsh Texas Units 1- 3 Install and operate CEMs 

Allegheny Energy 

Hatfield's 

Ferry Pennsylvania Units 1 - 3 Install and operate wet FGD 6/30/2010 

Install and 

operate sulfur 

trioxide injection 

systems, improve 

ESP 

performance 

2

(f

p

te

Wisconsin Public Service Corp 

Pulliam Wisconsin Units 3 & 4 Retire 12/31/2007

University of Wisconsin 

Charter 

Street 

Heating 

Plant 

Wisconsin 

Repower to 

burn 100% 

biomass 

12/31/2012
Appendix 3-5.2 

Citizen Suits Provided by DOJ 

Company Retire/Repower SO2 control NOx Control P

and Plant State Unit 

Action Effective Date Equipment Percent Removal or Rate Effective Date Equipment Rate Effective Date Equipment 

Tucson Electric Power 

Units 1 

& 2 

0.27 

lb/MMBtu 12/31/2006 0.22 lb/MMBtu 12/31/2006 

Unit 3 

Springerville 

Plant Arizona 

Future 

Unit 4 

Dry FGD, 

85% 

reduction 

required 

Four-unit 

cap of 

10,662 

tons per 

year once 

units 3 and 

4 are 

operational

SCR, LNB 

Four-unit 

cap of 

8,940 tons 

per year 

once units 

3 and 4 are 

operational

Baghouse 
Appendix 3-6.1 

Appendix 3-6 Renewable Portfolio Standards in EPA Base Case v.4.10 

NEMS 

Region IPM Regions Covered Units 2012 2015 2020 2030 2035 - 2050 

CNV CA-N and CA-S % 15.7% 17.3% 20.0% 20.0% 20.0%

ECAR MECS, RFCO, RFCP, and 

TVAK % 0.8% 3.0% 4.5% 5.7% 5.7% 

ERCOT ERCT % 3.9% 5.0% 5.0% 5.0% 5.0% 

MAAC MACE, MACS, and MACW % 7.4% 10.1% 14.8% 15.4% 15.4%

MAIN COMD, GWAY, and WUMS % 5.6% 8.9% 13.2% 17.5% 17.5%

MAPP MRO % 3.7% 4.6% 6.1% 7.2% 7.2% 

NE NENG % 7.4% 9.6% 13.4% 13.8% 13.8%

NWP NWPE and PNW % 4.6% 7.3% 12.4% 13.7% 13.7%

NY DSNY, LILC, NYC, and 

UPNY GWh 4,838 5,233 5,097 5,236 5,369 

RA AZNM, RMPA, and SNV % 3.0% 4.2% 6.0% 6.9% 6.9% 

SPP SPPN and SPPS % 1.9% 1.9% 3.8% 3.8% 3.8% 

STV ENTG, SOU, TVA, VACA, 

and VAPW % 0.5% 0.9% 1.7% 1.9% 1.9% 

Notes:

The Renewable Portfolio Standard percentages are applied to modeled electricity sale 

projections. 

The actual renewable portfolio standard targets in GWh are implemented exactly as shown in 

the model. 
Appendix 3-7.1 

Appendix 3-7 Capacity Deployment Limits for Advanced Coal with CCS and 

New Nuclear in EPA Base Case v.4.10 

Run 

Year 

Advanced 

Coal with 

CCS (MW) 

New 

Nuclear 

(MW) 

2012 0 0 

2015 2,000 0 

2020 9,750 7,500 

2030 38,220 29,400 

2040 112,367 86,436 

2050 293,652 225,886 

Note:

The 2020 through 2050 limits for Advanced Coal with 

CCS and New Nuclear technologies are a joint 

constraint, with the maximum amount of possible 

development for each technology shown by run year. If 

the maximum amount of one technology is developed 

in a given run year, zero MW of the other may be 

developed. See the production possibility chart below. 

Production Possibility Curves

(Incremental Capacity in MW by Run Year)

2020

2030

2040

2050

0

50,000

100,000

150,000

200,000

250,000

0 50,000 100,000 150,000 200,000 250,000 300,000

Advanced Coal with CCS

New Nuclear
Appendix 3-8.1 

Appendix 3-8 Nuclear Capacity Deployment Constraint in EPA Base Case v.4.1

Run 

Year 

Base New 

Nuclear 

Capacity 

Base New Nuclear 

Capacity Deployment 

Equation 

Possible Additional New Nuclear 

Capacity Deployment Equation1 Maximum Annual Incremental N

Deployment Allowed 

2020 7,500 7,500 0 7,500 2030 14,700 1.96 * 2020_Base_Capacity + 1.96 * 2020_Incremental_Capacity = 1.96 * (2020_Base_Capacity + 2022040 28,812 1.96 * 2030_Base_Capacity + 1.96 * 2030_Incremental_Capacity = 1.96 * (2030_Base_Capacity + 2032050 56,472 1.96 * 2040_Base_Capacity + 1.96 * 2040_Incremental_Capacity = 1.96 * (2040_Base_Capacity + 204

Maximum Possible New Nuclear Capacity Deployment Allowed 

Deployment Starts 2020 Deployment Starts 2030 Deployment Starts 2040 Deploy

Run Year 

Incremental Cumulative Incremental Cumulative Incremental Cumulative Incrementa

2020 7,500 7,500 0 0 0 0 0 2030 29,400 36,900 14,700 14,700 0 0 0 2040 86,436 123,336 57,624 72,324 28,812 28,812 0 2050 225,886 349,222 169,415 241,739 112,943 141,755 56,472 

Notes:No nuclear deployment is allowed before 2020 1Addtional new nuclear capacity deployment is only possible if nuclear capacity has been built in the previous run year. 
Appendix 3-8.2 

Maximum Possible Cumulative New Nuclear Capacity Each Run Year

0 50,000 100,000 150,000 200,000 250,000 300,000 

2020203020402050

Run Years

Capacity (MW)

Deployment Starts 2020 Deployment Starts 2030 Deployment Starts 2040 Deployment Starts 2050
Appendix 3-9.1 

Appendix 3-9 Complete Availability Assumptions in EPA Base Case v.4.10 

This is a small exerpt of the data in Appendix 3-9. The complete data set in spreadsheet format 

can be downloaded via the link found at 

www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev410.html 

Please see Table 3-7 for summary data

Unit ID Plant Name Plant Type Winter 

Availability 

Summer 

Availability 

Annual 

Availability 

55522_G_CT1 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT10 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT2 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT3 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT4 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT5 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT6 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT7 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT8 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55522_G_CT9 Sundance Combustion 

Turbine 89.2 90.8 89.9 

55257_G_1 Ina Road Water Pollution 

Control Fac 

Combustion 

Turbine 88.4 90.4 89.2 

55257_G_2 Ina Road Water Pollution 

Control Fac 

Combustion 

Turbine 88.4 90.4 89.2 

55257_G_3 Ina Road Water Pollution 

Control Fac 

Combustion 

Turbine 88.4 90.4 89.2 

55257_G_4 Ina Road Water Pollution 

Control Fac 

Combustion 

Turbine 88.4 90.4 89.2 

55257_G_5 Ina Road Water Pollution 

Control Fac 

Combustion 

Turbine 88.4 90.4 89.2 

55257_G_6 Ina Road Water Pollution 

Control Fac 

Combustion 

Turbine 88.4 90.4 89.2 

55257_G_7 Ina Road Water Pollution 

Control Fac 

Combustion 

Turbine 88.4 90.4 89.2 

82755_C_1 AZNM_AZ_Combustion 

Turbine 

Combustion 

Turbine 89.8 92.2 90.8 

6088_G_5 North Loop Combustion 

Turbine 89.2 90.8 89.9 

118_G_GE1 Saguaro Combustion 

Turbine 89.8 92.2 90.8 

124_G_GT2 Demoss Petrie Combustion 

Turbine 89.8 92.2 90.8 

82757_C_1 AZNM_CA_Combustion 

Turbine 

Combustion 

Turbine 89.8 92.2 90.8 

2468_G_6 Raton Combustion 

Turbine 88.4 90.4 89.2 

82759_C_1 AZNM_NM_Combustion 

Turbine 

Combustion 

Turbine 89.8 92.2 90.8 

54814_G_GENA Milagro Cogeneration Plant Combustion 

Turbine 89.2 90.8 89.9 
4-1 

4 Generating Resources 

“Existing”, “planned-committed”, and “potential” are the three general types of generating units 

modeled in EPA Base Case v.4.10. Units that are currently operational in the electric industry are 

termed as “existing” units. Units that are not currently operating but are firmly anticipated to be 

operational in the future, and have either broken ground (initiated construction) or secured 

financing are termed “planned-committed”. “Potential” units refer to new generating options used 

in IPM for capacity expansion projections of the electric industry. Existing and planned-committed 

units are entered as exogenous inputs to the model, whereas potential units are endogenous to 

the model in the sense that the model determines the location and size of all the potential units 

that end up in the final solution for a specific model run. 

This chapter is organized into the following five sections: 

(1) Section 4.1 provides background information on the National Electric Energy Data System 

(NEEDS), the database which serves as the repository for information on existing and 

planned-committed units which are modeled in the EPA Base Case v.4.10, 

(2) Section 4.2 provides detailed information on existing non-nuclear generating units 

modeled in EPA Base Case v.4.10, 

(3) Section 4.3 provides detailed information pertaining to planned-committed units which are 

assumed in EPA Base Case v.4.10, 

(4) Section 4.4 provides detailed information pertaining to the IPM assumptions for potential 

plants, and 

(5) Section 4.5 describes the handling of existing and potential nuclear units in EPA Base 

Case v.4.10 

4.1 National Electric Energy Data System (NEEDS) 

EPA Base Case v.4.10 uses the NEEDS database as its source for data on all existing and 

planned-committed units. Table 4-1 below summarizes the resources used in developing data on 

existing units in NEEDS v.4.10. The data sources for planned-committed units in NEEDS are 

discussed below in Section 4.3. The population of existing units in NEEDS v4.10 represents 

generating units that were in operation through the end of 2006. The population of plannedcommitted includes any units online or scheduled to come online from 2007 to the end of 2011 

(with two exceptions listed in the note under Table 4-2 below). 

4.2 Existing Units 

EPA Base Case v.4.10 models existing units based on information contained in NEEDS. The 

sections below describe the procedures followed in determining the population of units in NEEDS, 

as well as each unit’s capacity, location, and configuration. Details are also given on the model 

plant aggregation scheme and the cost and performance characteristics associated with the 

existing non-nuclear units represented in EPA Base Case v.4.10. 

4.2.1 Population of Existing Units 

The population of existing units was taken primarily from EIA 860 (2006) and EIA 767 (2005). A 

number of rules were used to screen the various data sources. These rules helped to ensure data 

consistency, but also made the population data adaptable for use in IPM. Table 4-2 below 

summarizes the rules used in populating the NEEDS v.4.10 database. 
4-2 

Table 4-1 Data Sources for NEEDS v.4.10 for EPA Base Case v.4.10 

Data Source1 Data Source Documentation 

DOE's Form EIA-860 

DOE's Form EIA-860 is an annual survey of utility power plants at the 

generator level. It contains data such as summer, winter and 

nameplate capacity, location (state and county), status, prime mover, 

primary energy source and in-service year. NEEDS v.4.10 uses EIA 

Form 860 (2006) data as one of the primary data inputs. 

DOE's Form EIA-767 

DOE's Form EIA-767 is an annual survey, "Steam-Electric Plant 

Operation and Design Report", that contains data for utility nuclear and 

fossil fuel steam boilers such as fuel quantity and quality; boiler 

identification, location, status, and design information; and postcombustion NOX control, FGD scrubber and particulate collector device 

information. Note that boilers in plants with less than 10 MW do not 

report all data elements. The relationship between boilers and 

generators is also provided, along with generator-level generation and 

nameplate capacity. Note that boilers and generators are not 

necessarily in a one-to-one correspondence. NEEDS v.4.10 uses EIA 

Form 767 (2005) data as one of the primary data inputs. 

NERC Electricity 

Supply and Demand 

(ES&D) database 

The NERC ES&D is released annually. It contains generator-level 

information such as summer, winter and nameplate capacity, state, 

NERC region and sub-region, status, primary fuel and on-line year. 

NEEDS v.4.10 uses NERC ES&D (2006) data as one of the primary 

data inputs. 

DOE’s Annual Energy 

Outlook (AEO) 

The Energy Information Administration (EIA) Annual Energy Outlook 

presents annually updated forecasts of energy supply, demand and 

prices covering a 20-25 year time horizon. The projections are based 

on results from EIA’s National Energy Modeling System (NEMS). 

Information from AEO such as heat rates, planned committed units, 

nuclear unit capacities and uprates were used in NEEDS v.4.10. 

Global Energy 

Decisions New 

Entrants database 

Global Energy’s New Entrants database has information on new power 

plant builds, rerates and retirements. Information on committed units is 

based on November 2009 dataset. 

EPA's Emission 

Tracking System 

(ETS 2007) 

The Emission Tracking System (ETS) database is updated quarterly. It 

contains boiler-level information such as primary fuel, heat input, SO2

and NOX controls, and SO2 and NOX emissions. 

Utility and RPO 

(Regional Planning 

Organizations) 

Comments 

Comments from selected U.S. utilities and RPOs regarding the 

population in NEEDS as well as unit characteristics were used in 

NEEDS v.4.10. 

Note:

1

 Shown in Table 4-1 are the primary issue dates of the indicated data sources that were used. 

Other vintages of these data sources were also used in instances where date were not 

available for the indicated issued date or where there were methodological reasons for using 

other vintages of the data. 
4-3 

Table 4-2 Rules Used in Populating NEEDS v.4.10 for EPA Base Case v.4.10 

Scope Rule 

Capacity Excluded units with reported nameplate, summer and winter capacity 

of zero 

Status 

Excluded units that were out of service for two or three consecutive 

years (i.e., generators with status codes “OS” in the latest three 

reporting years and boilers with status codes “OS” in the latest two 

reporting years) and units that were no longer in service and not 

expected to be returned to service (i.e., generators or boilers with 

status codes of "RE"). Status of boiler(s) and associated generator(s) 

were taken into account for determining operation status 

Planned or Committed 

Units 

Included planned units that had broken ground or secured financing 

and were expected to be online by the end of 2011; one biomass and 

one nuclear unit that are scheduled to come online after 2011 were 

also included 

Firm/Non-firm Electric 

Sales 

Excluded non-utility onsite generators that do not produce electricity 

for sale to the grid. 

Excluded all mobile and distributed generators 

Note:

1

The biomass unit is Mitchell, unit 3, and the nuclear unit is Watts Bar Nuclear Plant, unit 2. 

As with previous versions of the database, NEEDS v.4.10 includes steam units at the boiler level 

and non-steam units at the generator level. A unit in NEEDS v.4.10, therefore, refers to a boiler in 

the case of a steam unit and a generator in the case of a non-steam unit. Table 4-3 provides a 

summary of the population and capacity of the existing units included in NEEDS v.4.10 through 

2006. EIA Form 860 (2006) and Form 767 (2005) is the starting point and largest component of 

the existing unit population in NEEDS v.4.10 but the final population of existing units is 

supplemented based on information from other sources, including comments from utilities, 

submissions to EPA's Emission Tracking System, Annual Energy Outlook, and reported capacity 

in Global Energy’s New Entrants database. 

Table 4-3 Summary Population (through 2006) of Existing Units in NEEDSv.4.10 for EPA 

Base Case v.4.10 

Plant Type Number of Units Capacity (MW) 

Biomass 134 2,286 

Coal Steam 1,235 305,451 

Combined Cycle 1,532 179,557 

Combustion Turbine 5,386 132,293 

Fossil Waste 20 610 

Geothermal 196 2,264 

Hydro 3,754 77,713 

IGCC 4 529 

Landfill Gas 698 1,068 

Municipal Solid Waste 176 2,098 

Non-Fossil Waste 45 516 

Nuclear 104 101,099 

O/G Steam 682 112,371 

Pumped Storage 150 20,940 

Solar 19 412 

Tires 3 44 

Wind 330 11,637 

Grand Total 14,468 950,889 
4-4 

4.2.2 Capacity 

The NEEDS unit capacity values implemented in EPA Base Case v.4.10 reflect net summer 

dependable capacity16, to the extent possible. Table 4-4 summarizes the hierarchy of primary 

data sources used in compiling capacity data for NEEDS v.4.10. 

Table 4-4 Hierarchy of Data Sources for Capacity in NEEDS v.4.10 

Sources Presented in Hierarchy 

Capacity from Utility Comments 

2006 EIA 860 Summer Capacity 

NERC ES&D 2006 Summer Capacity 

2006 EIA 860 Winter Capacity 

NERC ES&D 2006 Winter Capacity 

2006 EIA 860 Nameplate Capacity 

Notes: 

Presented in hierarchical order that applies. 

If capacity is zero, unit is not included. 

As noted earlier, for steam units NEEDS v.4.10 includes boiler level data, while for non-steam 

units NEEDS v.4.10 contains generator level data. Capacity data in EIA and NERC data sources 

are generator specific and not boiler specific. Therefore, it was necessary to develop an algorithm 

for parsing generator level capacity to the boiler level for steam producing units. 

The capacity-parsing algorithm used for steam units in NEEDS v.4.10 took into account boilergenerator mapping. Fossil steam and nuclear steam electric units have boilers attached to 

generators that produce electricity. There are generally four types of links between boilers and 

generators: one boiler to one generator, one boiler to many generators, many boilers to one 

generator and many boilers to many generators. 

The capacity-parsing algorithm used for steam units in NEEDS utilized steam flow data with the 

boiler-generator mapping. Under EIA 767, steam units report the maximum steam flow from the 

boiler to the generator. There is, however, no further data on the steam flow of each boilergenerator link. Instead, EIA 767 contains only the maximum steam flow for each boiler. Table 4-5 

summarizes the algorithm used for parsing capacity with data on maximum steam flow and boilergenerator mapping. In Table 4-5 MFBi

 refers to the maximum steam flow of boiler i and MWGj

refers to the capacity of generator j. The algorithm uses the available data to derive the capacity 

of a boiler, referred to as MWBj

 in Table 4-5. 

Table 4-5 Capacity-Parsing Algorithm for Steam Units in NEEDS v.4.10 

Type of Boiler-Generator Links 

For Boiler B1 One-to-One One-to-Many Many-to-One Many-to-Many 

to BN linked to 

Generators 

G1 to GN

MWBi = 

MWGj

MWBi = 

ΣjMWGj

MWBi = 

(MFBi / ΣiMFBi) * MWGj

MWBi = 

(MFBi / ΣiMFBi) * ΣjMWGj

Notes:

MFBi = maximum steam flow of boiler i 

MWGj = electric generation capacity of generator j

 

16As used here, net summer dependable capacity is the net capability of a generating unit in 

megawatts (MW) for daily planning and operation purposes during the summer peak season, after 

accounting for station or auxiliary services. 
4-5 

Since EPA Base Case v.4.10 uses net energy for load as demand, NEEDS v.4.10 only includes 

generators that sell the majority of their power to the electric grid in order to be consistent with 

demand. The generators that should be in NEEDS v.4.10. by this qualification are determined 

from the 2005 EIA Form 906 non-utility source and disposition data set. 

4.2.3 Plant Location 

NEEDS v.4.10 uses state, county and model region data to represent the physical location of each 

plant. 

State and County

NEEDS v.4.10 used the state and county data in EIA 860 (2006) 

Model Region

For each unit the associated model region was derived based on NERC regions and sub-regions 

reported in NERC ES&D 2006 for that unit. For units with no NERC sub-region data, NERC 

region and state were used to derive associated model regions. For units with no NERC region 

data, state and county were used to derive associated model regions. Table 3-1 in Chapter 3 

provides a summary of the mapping between NERC regions and EPA Base Case v.4.10 model 

regions. 

4.2.4 Online Year 

The EPA Base Case v.4.10 uses online year to capture when the unit entered service. NEEDS 

includes online years for all units in the database. In NEEDS v.4.10, online years for boilers, utility 

and non-utility generators were primarily derived from reported in-service dates in EIA 767 2005 

and EIA 860 2006 respectively. 

EPA Base Case v.4.10 does not include any assumption about the retirement year for generating 

units, except for existing nuclear units which must retire when they reach age 60. (See section 

3.7 for a discussion of the nuclear lifetime assumption.) EPA Base Case v.4.10 does, however, 

provide economic retirement options to coal, oil and gas steam, combined cycle, combustion 

turbines, and nuclear units. This means that the model may elect to retire these units if it is 

economical to do so. In IPM, an early retired plant ceases to incur FOM and VOM costs. 

However, retired units do meet capital cost obligations for retrofits if the model projected a retrofit 

on the unit prior to retirement. 

4.2.5 Unit Configuration 

Unit configuration refers to the physical specification of a unit’s design. Unit configuration in EPA 

Base Case v.4.10 drives model plant aggregation, modeling of pollution control options and 

mercury emission modification factors. NEEDS v.4.10 contains information on the firing and 

bottom type of coal steam boilers in the database. Great effort was taken to see that the inventory 

of existing and committed controls represented in EPA Base Case v.4.10 was comprehensive and 

as up-to-date as possible. The hierarchy of data sources used is shown in Table 4-6. 

4.2.6 Model Plant Aggregation 

While IPM is comprehensive in representing all the units contained in NEEDS, an aggregation 

scheme is used to combine existing units with similar characteristics into “model plants”. The 

aggregation scheme serves to reduce the size of the model and makes the model manageable 

while capturing the essential characteristics of the generating units. The EPA Base Case v.4.10 

aggregation scheme is designed so that each model plant only represents generating units from a 

single state. This design makes it possible to obtain state-level results directly from IPM outputs. 

In addition, the aggregation scheme supports modeling plant-level emission limits on fossil 

generation 

The “model plant” aggregation scheme encompasses a variety of different classification 

categories including location, size, technology, heat rate, fuel choices, unit configuration, SO2
4-6 

emission rates and environmental regulations among others. Units are aggregated together only 

if they match on all the different categories specified for the aggregation. The 10 major categories 

used for the aggregation scheme in EPA Base Case v.4.10 are the following: 

(1) Model Region 

(2) Unit Technology Type 

(3) Fuel Demand Region 

(4) Applicable Environmental Regulations 

(5) State 

(6) Unit Configuration 

(7) Emission Rates 

(8) Heat Rates 

(9) Fuel 

(10) Size 

Table 4-6 Data Sources for Unit Configuration in NEEDS v.4.10 for EPA Base Case v.4.10 

Unit 

Component Primary Data Source Secondary Data Source 

Tertiary 

Data 

Source 

Other 

Sources Default 

Firing Type Utility/RPO Comments 2005 EIA 767 -- -- -- 

Bottom Type Utility/RPO Comments 2005 EIA 767 -- -- Dry 

SO2 Pollution 

Control 

NSR Settlement or 

Utility/RPO Comments 

EPA’s Emission 

Tracking System 

(ETS) - 2006 

2005 EIA 

767 See Note No Control 

NOx Pollution 

Control 

NSR Settlement or 

Utility/RPO Comments 

EPA’s Emission 

Tracking System 

(ETS) - 2006 

2005 EIA 

767 See Note No Control 

Particulate 

Matter 

Control 

NSR Settlement or 

Utility/RPO Comments 

EPA’s Emission 

Tracking System 

(ETS) - 2006 

2005 EIA 

767 

1999 Hg 

ICR -- 

Note:

In addition to the primary, secondary and tertiary data sources listed here, the following sources 

were consulted and emission controls were updated when corroborating information could be 

found: McILVAINE Utility Upgrade Database, ICAC (Institute of Clean Air Companies), and web 

sites of generating unit owners and operators. 

Table 4-7 provides a crosswalk between actual plants and the aggregated “model plants” used in 

the EPA Base Case v.4.10. For each plant type, the table shows the number of real plants and 

the number of model plants representing these real plants in EPA Base Case v.4.10.17

 

17For readers interested in the intricacies of Table 4-7, here are several observations: (1) 

Depending on its capacity and fuel types combusted, an existing coal steam model plant may be 

provided with multiple scrubber and ACI retrofit options. As a result the total number of model 

plants representing scrubber and ACI retrofits may exceed the total number of model plants 

representing existing coal steam units. (See chapter 5 for a detailed description of the sulfur 

dioxide (scrubber) and mercury (ACI) retrofit options.) (2) The “Number of IPM Model Plants” 

shown for many of the “Plant Types” in the “Retrofits” block in Table 4-7 exceeds the “Number of 

IPM Model Plants” shown for “Plant Type” “Coal Steam” in the block labeled “Existing and 

Planned/Committed Units”, because a particular retrofit “Plant Type” can include multiple 

technology options and multiple timing options (e.g., Technology A in Stage 1 + Technology B in 

Stage 2, the reverse timing, or both technologies simultaneously in Stage 1). (3) Since only a 

subset of coal plants is eligible for certain retrofits, many of the “Plant Types” in the “Retrofits” 

block that represent only a single retrofit technology (e.g., “Retrofit Coal with Selective 

Noncatalytic Reduction (SNCR)”) have a “Number of of IPM Model Plants” that is a smaller than 
4-7 

Table 4-7 Aggregation Profile of Model Plants as Provided at Set Up of EPA Base Case 

v.4.10 

Existing and Planned/Committed Units 

Plant Type Number of 

Units 

Number of IPM 

Model Plants 

Biomass 161 71 

Coal Steam 1,267 913 

Combined Cycle 1,627 610 

Combustion Turbine 5,474 2,225 

Fossil_Other 21 14 

Fuel Cell 4 4 

Geothermal 211 8 

Hydro 3,771 99 

Import 2 2 

Integrated Gas Combined Cycle 6 5 

Landfill Gas 747 59 

Non Fossil_Other1 241 73 

Nuclear2 105 105 

Oil/Gas Steam 685 435 

Pumped Storage 151 21 

Solar 92 37 

Wind 458 57 

Total 15,023 4,738 

New Units 

Plant Type Number of 

Units 

Number of IPM 

Model Plants 

New Biomass -- 64 

New Coal with Carbon Capture -- 754 

New Combined Cycle -- 32 

New Combustion Turbine -- 32 

New Fuel Cell -- 32 

New Future Technology -- 160 

New Geothermal -- 26 

New IGCC -- 58 

New Landfill Gas -- 96 

New Nuclear -- 64 

New Offshore Wind -- 690 

New Onshore Wind -- 600 

New SPC-DryFGD_SCR_ACI 27 

New SPC-WetFGD_SCR -- 27 

New Solar Thermal -- 55 

New Solar PV -- 32 

 the “Number of IPM Model Plants” shown for “Plant Type” “Coal Steam”. (4) The total number of 

model plants representing different types of new units often exceeds the 32 model regions and the 

specific totals vary from technology to technology for several reasons. First, some technologies 

have multiple vintages, which must be represented by separate model plants in each IPM region. 

Second, some technologies are not available in particular regions (e.g., geothermal is 

geographically restricted to certain regions, conventional pulverized coal is not provided as an 

option in CA-N). 
4-8 

Total -- 2,749 

 

Retrofits 

Plant Type Number of 

Units 

Number of IPM 

Model Plants 

Retrofit Coal with Activated Carbon Injection (ACI) -- 427 

Retrofit Coal with ACI + SCR -- 1,076 

Retrofit Coal with ACI + SCR + Scrubber -- 1,575 

Retrofit Coal with ACI + SCR + Scrubber + CCS -- 1,708 

Retrofit Coal with ACI + SNCR + Scrubber -- 357 

Retrofit Coal with ACI + SNCR -- 447 

Retrofit Coal with ACI + SNCR + Scrubber + CCS -- 161 

Retrofit Coal with ACI + Scrubber -- 1,570 

Retrofit Coal with ACI + Scrubber + CCS -- 1,372 

Retrofit Coal with Selective Catalytic Reduction (SCR) -- 360 

Retrofit Coal with SCR + Scrubber -- 2,281 

Retrofit Coal with SCR + Scrubber + CCS -- 2,065 

Retrofit Coal with Selective Noncatalytic Reduction (SNCR) -- 141 

Retrofit Coal with SNCR + Scrubber -- 544 

Retrofit Coal with SNCR + Scrubber + CCS -- 112 

Retrofit Coal with Scrubber -- 587 

Retrofit Coal with Scrubber + CCS -- 1,078 

Retrofit Coal with CCS -- 14 

Retrofit Oil Gas with SCR -- 281 

Total -- 16,156 

Early Retirements 

Plant Type Number of 

Units 

Number of IPM 

Model Plants 

CC Early Retirement -- 610 

Coal Early Retirement -- 6,178 

CT Early Retirement -- 2,225 

IGCC Early Retirement -- 5 

Nuke Early Retirement -- 105 

O/G Early Retirement -- 435 

Total -- 9,558 

 

Grand Total (Existing and Planned/Committed + New + Retrofits + Early Retirements): 33,201 

 Notes:

1

Non Fossil_Other includes units whose fuel is municipal solid waste, tires, and other non-fossil waste. 

2

The 105 nuclear units include 104 currently operating units plus Watts Bar Nuclear Plant, Unit 2, which is 

scheduled to come online in 2014. All are listed in Appendix 4-3. 
4-9 

4.2.7 Cost and Performance Characteristics of Existing Units 

In EPA Base Case v.4.10 heat rates, emission rates, variable operation and maintenance cost 

(VOM) and fixed operation and maintenance costs (FOM) are used to characterize the cost and 

performance of all existing units in NEEDS v.4.10. For existing units, only the cost of maintaining 

(FOM) and running (VOM) the unit are modeled. Embedded costs, such as carrying capital 

charges, are not modeled. The section below contains a discussion of the cost and performance 

assumptions for existing units used in the EPA Base Case v.4.10. 

Variable Operating and Maintenance Cost (VOM)

VOM represents the non-fuel cost variable associated with producing a unit of electricity. If the 

generating unit contains pollution control equipment, VOM includes the cost of operating the 

control equipment. Table 4-8 below summarizes VOM assumptions used in EPA Base Case 

v.4.10. The values shown in this table were obtained using a procedure developed jointly by 

EPA’s power sector engineering staff and ICF. 

Table 4-8 VOM Assumptions (2007$) in EPA Base Case v.4.10 

Capacity Type SO2 Control Hg Control NOx Control 

Variable O&M 

Range 

(mills/kWh) 

No NOx 2.63 - 7.67 Combined Cycle -- -- SCR 2.75 - 7.79 

No NOx 3.66 - 5.05 

No Hg SCR 4.34 - 5.73 

SNCR 4.73 - 6.12 

No NOx 4.62 - 6.02 

SCR 5.30 - 6.69 

Scrubbed - Dry 

ACI 

SNCR 5.70 - 7.09 

No NOx 2.48 - 3.87 

No Hg SCR 3.16 - 4.55 

SNCR 3.55 - 4.94 

No NOx 3.44 - 4.83 

SCR 4.12 - 5.51 

Scrubbed - 

Wet 

ACI 

SNCR 4.51 - 5.91 

No NOx 0.90 - 2.29 

No Hg SCR 1.58 - 2.97 

SNCR 1.97 - 3.37 

No NOx 1.87 - 3.26 

SCR 2.54 - 3.94 

Coal Steam 

Unscrubbed 

ACI 

SNCR 2.94 - 4.33 

Conventional 

Hydroelectric -- -- -- 6.66 

No NOx 2.60 - 9.59 Combined Turbine -- No Hg SCR 2.73 - 9.71 

Fuel Cell -- -- -- 9.7 

Geothermal -- -- -- 8.3 

IGCC -- -- -- 0 - 4.72 

MSW/Landfill Gas -- -- -- 8.79 
4-10 

Capacity Type SO2 Control Hg Control NOx Control 

Variable O&M 

Range 

(mills/kWh) 

Scrubbed - No NOx 0.94 - 5.07 

Wet No Hg SNCR 1.49 - 5.62 

No NOx 0.94 - 5.07 

SCR 1.06 - 5.19 

Oil/Gas Steam 

Unscrubbed No Hg 

SNCR 1.49 - 5.62 

Pumped Storage -- -- -- 8.37 

Solar Photovoltaic -- -- -- 2.09 

Solar Thermal -- -- -- 2.78 

Wind -- -- -- 3.18 

Wood/Biomass -- -- -- 6.98 

Fixed Operation and Maintenance Cost (FOM)

FOM represents the annual fixed cost of maintaining a unit. FOM costs are incurred independent 

of achieved generation levels and signify the fixed cost of operating and maintaining the unit for 

generation. Table 4-9 summarizes the FOM assumptions used in EPA Base Case v.4.10. Note 

that FOM varies by the age of the unit. The values appearing in this table include the cost of 

maintaining any associated pollution control equipment. The values in Table 4-9 are based on 

FERC (Federal Energy Regulatory Commission) Form 1 data. 

Heat Rates

Heat Rates describe the efficiency of the unit expressed as BTUs per kWh. The treatment of heat 

rates in EPA Base Case v.4.10 is discussed in Section 3.8. 

Lifetimes

Unit lifetime assumptions in EPA Base Case v.4.10 are detailed in Sections 3.7 and 4.2.8. 

SO2 Rates

Section 3.9.1 contains a detailed discussion of SO2 rates for existing units. 

NOx Rates

Section 3.9.2 contains a detailed discussion of NOx rates for existing units. 

Mercury Emission Modification Factors (EMF)

Mercury EMF refers to the ratio of mercury emissions (mercury outlet) to the mercury content of 

the fuel (mercury inlet). Section 5.4.2 contains a detailed discussion of the EMF assumptions in 

EPA Base Case v.4.10. 

4.2.8 Life Extension Costs for existing units 

The usable modeling time horizon in previous EPA Base Cases typically extended out only as far 

as 2030 and covered a period of roughly 20-25 years. In contrast, the modeling time horizon in 

EPA Base Case 4.10 extends to 2050 covers a period of almost 40 years. Due to this longer time 

horizon, provision had to be made in EPA Base Case v.4.10 for investments (beyond the routine 

maintenance of the power plant) that would be required to extend the life of existing units over this 

longer time horizon. The life extension costs for units with retirement options are summarized in 

Table 4-10 below. These costs were based on a review of FERC Form 1 data regarding annual 

capital expenditures over the last 10 – 15 years of the power plan. 
4-11 

Table 4-9 FOM Assumptions Used in EPA Base Case v.4.10 

Prime Mover 

Type 

Primary 

Fuel SO2 Control Hg Control 

NOx

Control Age of Unit FOM (2007$ /kW-Yr) 

Combined 

Cycle Oil & Gas -- -- -- All Years 12.6 

Conventional 

Hydroelectric Water -- -- -- All Years 14.3 

Fuel Cell Natural 

Gas -- -- -- All Years 18.3 

 >30 years 8.8 

Gas Turbine Oil & Gas 20-30 years 8.5 -- -- -- 

 0-20 years 3.7 

Geothermal Earth -- -- -- All Years 21.6 

IGCC Coal -- -- -- All Years 118.4 

MSW/Landfill 

Gas 

Landfill 

Gas -- -- -- All Years 23.6 

Nuclear Nuclear -- -- -- All Years 100.5 

Pumped 

Storage Water -- -- -- All Years 18.3 

Solar 

Photovoltaic Sun -- -- -- All Years 17.1 

Solar Thermal Sun -- -- -- All Years 22.6 

0 to 20 Years 42.2 

20 to 30 Years 44.2 

30 to 40 Years 55.1 

No NOx

Greater than 40 Years 60.8 

0 to 20 Years 42.9 

20 to 30 Years 44.9 

30 to 40 Years 55.7 

SCR 

Greater than 40 Years 61.4 

0 to 20 Years 42.5 

20 to 30 Years 44.5 

30 to 40 Years 55.3 

No Hg 

SNCR 

Greater than 40 Years 61.1 

0 to 20 Years 42.4 

20 to 30 Years 44.4 

30 to 40 Years 55.2 

No NOx

Greater than 40 Years 60.9 

0 to 20 Years 43.0 

20 to 30 Years 45.0 

30 to 40 Years 55.9 

SCR 

Greater than 40 Years 61.6 

0 to 20 Years 42.6 

20 to 30 Years 44.6 

30 to 40 Years 55.5 

Scrubbed - 

Dry 

ACI 

SNCR 

Greater than 40 Years 61.2 

0 to 20 Years 43.2 

20 to 30 Years 45.2 

30 to 40 Years 56.0 

No NOx

Greater than 40 Years 61.8 

0 to 20 Years 43.8 

Steam Turbine Coal 

Scrubbed - 

Wet 

No Hg 

SCR 

20 to 30 Years 45.8 
4-12 

Prime Mover 

Type 

Primary 

Fuel SO2 Control Hg Control 

NOx

Control Age of Unit FOM (2007$ /kW-Yr) 

30 to 40 Years 56.7 

Greater than 40 Years 62.4 

0 to 20 Years 43.5 

20 to 30 Years 45.5 

30 to 40 Years 56.3 

SNCR 

Greater than 40 Years 62.0 

0 to 20 Years 43.3 

20 to 30 Years 45.3 

30 to 40 Years 56.2 

No NOx

Greater than 40 Years 61.9 

0 to 20 Years 44.0 

20 to 30 Years 46.0 

30 to 40 Years 56.8 

SCR 

Greater than 40 Years 62.6 

0 to 20 Years 43.6 

20 to 30 Years 45.6 

30 to 40 Years 56.5 

ACI 

SNCR 

Greater than 40 Years 62.2 

0 to 20 Years 32.9 

20 to 30 Years 34.9 

30 to 40 Years 45.8 

No NOx

Greater than 40 Years 51.5 

0 to 20 Years 33.6 

20 to 30 Years 35.6 

30 to 40 Years 46.4 

SCR 

Greater than 40 Years 52.2 

0 to 20 Years 33.2 

20 to 30 Years 35.2 

30 to 40 Years 46.1 

No Hg 

SNCR 

Greater than 40 Years 51.8 

0 to 20 Years 33.1 

20 to 30 Years 35.1 

30 to 40 Years 45.9 

No NOx

Greater than 40 Years 51.7 

0 to 20 Years 33.7 

20 to 30 Years 35.7 

30 to 40 Years 46.6 

SCR 

Greater than 40 Years 52.3 

0 to 20 Years 33.3 

20 to 30 Years 35.3 

30 to 40 Years 46.2 

Unscrubbed 

ACI 

SNCR 

Greater than 40 Years 51.9 

0 to 20 Years 18.4 

20 to 30 Years 21.0 

30 to 40 Years 22.3 

No NOx

Greater than 40 Years 28.4 

Oil & Gas -- -- 

SCR 0 to 20 Years 19.3 
4-13 

Prime Mover 

Type 

Primary 

Fuel SO2 Control Hg Control 

NOx

Control Age of Unit FOM (2007$ /kW-Yr) 

20 to 30 Years 21.9 

30 to 40 Years 23.2 

Greater than 40 Years 29.3 

0 to 20 Years 18.6 

20 to 30 Years 21.2 

30 to 40 Years 22.5 SNCR 

Greater than 40 Years 28.6 

Wind Wind -- -- -- All Years 18.3 

Wood/Biomass Biomass -- -- -- All Years 20.1 

Table 4-10 Life Extension Cost Assumptions Used in EPA Base Case v.4.10 

Plant Type 

Lifespan 

without Life 

Extension 

Expenditures 

Life Extension 

Cost as 

Proportion of 

New Unit 

Capital Cost 

(%) 

Capital 

Cost of 

New Unit 

(2007$/kW) 

Life 

Extension 

Cost 

(2007$/kW) 

Coal Steam 40 7.0 2,918 204 

Combined Cycle 30 9.3 976 91 

Combustion Turbine & 

 IC Engine 30 4.2 698 30 

Oil/Gas Steam 40 3.4 2,699 91 

IGCC 40 7.4 3,265 242 

Nuclear 40 9.0 4,621 416 

Note:

Life extension expenditures double the lifespan of the unit. 

4.3 Planned-Committed Units 

EPA Base Case v.4.10 includes all planned-committed units that are likely to come online 

because ground has been broken, financing obtained, or other demonstrable factors indicate a 

high probability that the unit will be built before 2012. 

4.3.1 Population and Model Plant Aggregation 

Like existing units, planned-committed units are contained in NEEDS. A comprehensive update 

of planned-committed units contained in NEEDS was performed for EPA Base Case v.4.10 using 

the information sources listed in Table 4-1 . Table 4-11 summarizes the extent of inventory of 

planned-committed units in EPA Base Case v.4.10 indicating its generating capacity by unit types. 

Due to data confidentiality restrictions, NEEDS v.4.10 does not list the planned-committed units on 

a unit by unit basis. Rather, all units having similar technologies and located within the same 

model region are aggregated together as one record. Table 4-12 gives a breakdown of plannedcommitted units by IPM region, unit type, number of units, and capacity included in EPA Base 

Case v.4.10. 
4-14 

Table 4-11 Summary of Planned-Committed Units in NEEDS v.4.10 for EPA Base Case 

v.4.10 

Type Capacity (MW) Year Range Described 

Renewables/Non-conventional 

Biomass 495 2007 - 2012 

Fuel Cell 3 2011 

Geothermal 302 2007 - 2011 

Hydro 91 2007 - 2011 

Landfill Gas 279 2007 - 2011 

Municipal Solid Waste 35 2007 - 2011 

Non-Fossil Waste 235 2011 

Pumped Storage 40 2011 

Solar 687 2007 - 2011 

Wind 26,295 2007 - 2011 

Subtotal 28,462 

Fossil/Conventional 

Coal Steam 17,055 2007 - 2011 

Combined Cycle 25,088 2007 - 2011 

Combustion Turbine 9,648 2007 - 2011 

Fossil Waste 274 2011 

IGCC 1,230 2009 - 2011 

Nuclear 1,180 2014 

O/G Steam 115 2008 - 2011 

Subtotal 54,590 

Grand Total 83,052 

Table 4-12 Planned-Committed Units by Model Region in NEEDS v.4.10 for EPA Base Case 

v.4.10 

IPM Region Plant Type Capacity (MW) 

Biomass 24 

Coal Steam 400 

Combined Cycle 94 

Combustion Turbine 593 

Geothermal 95 

Solar 20 

AZNM 

Wind 130 

Combined Cycle 1,279 

Combustion Turbine 603 

Fuel Cell 1 

Geothermal 25 

Landfill Gas 17 

Solar 249 

CA-N 

Wind 2,533 

Biomass 2 

Combined Cycle 1,293 

Combustion Turbine 454 

Fuel Cell 2 

Hydro 5 

CA-S 

Landfill Gas 8 
4-15 

IPM Region Plant Type Capacity (MW) 

Pumped Storage 40 

Solar 255 

Wind 112 

Combined Cycle 573 

COMD Landfill Gas 6 

Wind 282 

DSNY Combined Cycle 635 

Biomass 14 

ENTG Coal Steam 665 

Combined Cycle 1,336 

Biomass 50 

Coal Steam 3,250 

Combined Cycle 3,266 

Combustion Turbine 639 

Fossil Waste 274 

Landfill Gas 16 

Non-Fossil Waste 10 

Solar 3 

ERCT 

Wind 7,669 

Combined Cycle 6,365 

Combustion Turbine 1,191 

Landfill Gas 21 FRCC 

Municipal Solid Waste 16 

Coal Steam 1,800 

GWAY Landfill Gas 5 

Wind 1,177 

LILC Combined Cycle 350 

Combustion Turbine 105 

Landfill Gas 27 

O/G Steam 9 MACE 

Solar 7 

Combustion Turbine 30 

MACS Landfill Gas 5 

O/G Steam 100 

Biomass 30 

Landfill Gas 22 

Municipal Solid Waste 14 

Wind 480 

Landfill Gas 10 

MACW 

Wind 480 

Biomass 107 

Coal Steam 1,782 

Combined Cycle 1,204 

Combustion Turbine 878 

Hydro 11 

Landfill Gas 7 

MRO 

Municipal Solid Waste 5 
4-16 

IPM Region Plant Type Capacity (MW) 

Non-Fossil Waste 25 

Wind 4,598 

Biomass 44 

Combined Cycle 987 

Combustion Turbine 301 

Hydro 16 

Landfill Gas 11 

O/G Steam 6 

Solar 1 

NENG 

Wind 650 

Biomass 1 

Coal Steam 1,112 

Combined Cycle 1,062 

Geothermal 182 

Hydro 12 

Solar 2 

NWPE 

Wind 266 

NYC Combustion Turbine 1 

Biomass 31 

Combined Cycle 1,262 

Combustion Turbine 175 

Hydro 19 

Landfill Gas 10 

Non-Fossil Waste 58 

Solar 2 

PNW 

Wind 2,584 

Combined Cycle 720 

IGCC 1,230 

Landfill Gas 26 

Non-Fossil Waste 3 

RFCO 

Wind 554 

Coal Steam 695 

Combined Cycle 580 

Landfill Gas 5 

Non-Fossil Waste 80 

RFCP 

Wind 264 

Coal Steam 768 

Combustion Turbine 658 

Hydro 9 

Landfill Gas 6 

Solar 15 

RMPA 

Wind 1,362 

Combustion Turbine 720 

SNV Solar 112 

Wind 189 

SOU Biomass 116 

Combined Cycle 1,237 
4-17 

IPM Region Plant Type Capacity (MW) 

Non-Fossil Waste 18 

Coal Steam 1,172 

SPPN Combustion Turbine 845 

Wind 651 

Coal Steam 660 

Combined Cycle 1,080 

Combustion Turbine 939 

Non-Fossil Waste 35 

Solar 8 

Wind 943 

Nuclear 1,180 

SPPS 

Wind 111 

Coal Steam 1,018 

TVAK Combustion Turbine 200 

Landfill Gas 5 

Biomass 25 

Hydro 13 

Landfill Gas 14 

Non-Fossil Waste 7 

UPNY 

Wind 826 

Coal Steam 1,980 

Combustion Turbine 779 

Hydro 6 

Landfill Gas 18 

Solar 12 

VACA 

Wind 38 

Combined Cycle 1,190 

Combustion Turbine 537 

Landfill Gas 31 VAPW 

Solar 1 

Biomass 50 

Coal Steam 1,753 

Combined Cycle 575 

Landfill Gas 8 

WUMS 

Wind 396 

Note:

Any unit that has an online year of 2007- 2011 was considered a Planned and Committed Unit 

4.3.2 Capacity 

The capacity of planned-committed units in NEEDS v.4.10 was obtained from the information 

sources reported above in Table 4-1 . 

4.3.3 State and Model Region 

State location data for the planned-committed units in NEEDS v.4.10 came from the information 

sources noted in Section 4.3.1. The state information was then used to assign planned-committed 

units to their respective model regions. 
4-18 

4.3.4 Online and Retirement Year 

As noted above, planned-committed units included in NEEDS v.4.10 are only those units which 

are likely to come on-line before 2012. All planned-committed units were given a default online 

year of end of 2011 since this is the first analysis year in EPA Base Case v.4.10. The 

assumptions in EPA Base Case v.4.10 do not include a lifetime for planned-committed units. 

4.3.5 Unit Configuration and Cost-and-Performance 

All planned-committed units in NEEDS v.4.10 assume the cost, performance, and unit 

configuration characteristics of potential units that are available in 2012. A detailed description of 

potential unit assumptions is provided below in Section 4.4. 

4.4 Potential Units 

The EPA Base Case v.4.10 includes options for developing a variety of potential units that may be 

“built” at a future date in response to electricity demand and the constraints represented in the 

model. Defined by region, technology, and the year available, potential units with an initial 

capacity of 0 MW are inputs into IPM. When the model is run, the capacity of certain potential 

units is raised from zero to meet demand and other system and operating constraints. This 

results in the model’s projection of new capacity. 

In Table 4-7 the block labeled “New Units” gives a breakdown of the type and number of potential 

units provided in EPA Base Case v.4.10. The following sections describe the cost and 

performance assumptions for the potential units represented in the EPA Base Case v.4.10. 

4.4.1 Methodology Used to Derive the Cost and Performance Characteristics of 

Conventional Potential Units 

Cost and performance assumptions for potential units in previous EPA base cases were based 

primarily on data from the latest available Annual Energy Outlook (AEO) published by the U.S. 

Department of Energy’s Energy Information Administration. However, an unprecedented run up in 

the costs of new generating units over the preceding 5 years prompted EPA to analyze other 

references in addition to the AEO for Base Case v.4.10. The cost escalation which was 

particularly noticeable for base load electric generating units, was generally attributed to 

international competition and, was increasingly seen as permanent. That is, there was a growing 

consensus that costs were not going to settle back to pre-2010 levels. 

With this in mind, the power sector engineering staff in EPA’s Clean Air Markets Division 

performed comparative cost analyses based on reports and discussions with government 

agencies, national technical laboratories, industry, academia, and various non-governmental 

organizations. The key sources reviewed included: 

• U.S. Energy Information Administration: Annual Energy Outlook 2008, 2009, 201018 

• National Energy Technology Laboratory, Fossil Energy Power Plant Desk Reference 

(Bituminous Coal)19

 

18 U.S. Department of Energy, Energy Information Administration, Assumptions to the Annual 

Energy Outlook 2008: Electric Market Module, DOE/EIA-0554(2008), June 2008. 

www.eia.doe.gov/oiaf/archive/aeo08/assumption/electricity.html

U.S. Department of Energy, Energy Information Administration, Assumptions to the Annual 

Energy Outlook 2009: Electric Market Module, DOE/EIA-0554(2009), March 2009. 

www.eia.doe.gov/oiaf/archive/aeo09/assumption/electricity.html

U.S. Department of Energy, Energy Information Administration, Assumptions to the Annual 

Energy Outlook 2010: Electric Market Module, #:DOE/EIA-0554(2010), April 2010. 

www.eia.doe.gov/oiaf/aeo/assumption/electricity.html. 19 U.S. Department of Energy, National Energy Technology Laboratory, Fossil Energy Power Plant 

Desk Reference, Bituminous Coal and Natural Gas to Electricity Summary Sheets DOE/NETL-
4-19 

• U.S. Environmental Protection Agency, Environmental Footprints and Costs of Coal-Based 

Integrated Gasification Combined Cycle and Pulverized Coal Technologies20

• EPRI (Electric Power Research Institute): “Economic Assessment of Advanced Coal-Based 

Power Plants with CO2 Capture”21

• Harvard University: “Realistic Costs of Carbon Capture”22

• Massachusetts Institute of Technology: ”Update on the Cost of Nuclear Power”23 

• Union of Concerned Scientists: Climate 2030 - A National Blueprint for a Clean Energy 

Economy24

4.4.2 Cost and Performance for Potential Conventional Units 

The comparative analyses described in the preceding section resulted in the cost and 

performance characteristics shown in Table 4-13. They are based on EPA’s engineering 

assessments. As seen in Table 4-13, EPA Base Case v.4.10 includes cost and performance 

characteristics for the following potential technologies: supercritical pulverized coal, advanced 

combined cycle, advanced combustion turbines, integrated gasification combined cycle (IGCC), 

advanced coal with carbon capture capabilities, and nuclear units. The cost and performance 

assumptions are based on the size (i.e., electrical generating capacity in MW) indicated in the 

table. However, the total new capacity that is added in a given model run for these technologies is 

not restricted to these capacity levels. 

This table includes several components of cost. The total installed cost of developing and building 

a new plant is captured through the capital cost. It includes expenditures on pollution control 

equipment that new units are assumed to install to satisfy air regulatory requirements. The capital 

costs shown in Table 4-13 are typically referred to as “overnight” capital costs. They include 

engineering, procurement, construction, startup, and owner’s costs (for such items as land, 

cooling infrastructure, administration and associated buildings, site works, switchyards, project 

management, licenses, etc). The capital costs in Table 4-13 do not include interest during 

construction (IDC). IDC is added to the capital costs shown in Table 4-13 during the set-up of a 

run. Calculation of IDC is based on the construction profile and the discount rate. Details on the 

discount rates used in the EPA Base Case v.4.10 are discussed in Chapter 8 under financial 

assumptions. 

 2007/1282, May 2007. http://www.netl.doe.gov/energyanalyses/pubs/Cost%20and%20Performance%20Baseline-012908.pdf

20U.S. EPA, Environmental Footprints and Costs of Coal-Based Integrated Gasification Combined 

Cycle and Pulverized Coal Technologies. EPA-430/R-06/2006, July 2006. 

21Booras, G., Economic Assessment of Advanced Coal-Based Power Plants with CO2 Capture, a 

presentation at EPRI (Electric Power Research Institute) MIT Carbon Sequestration Forum IC, 

September 16, 2008. 

22Al-Juaied, M and A Whitmore, ““Realistic Costs of Carbon Capture” Harvard Kennedy School. 

Belfer Center Discussion Paper 2009-08, July 2009. 

http://belfercenter.ksg.harvard.edu/files/2009_AlJuaied_Whitmore_Realistic_Costs_of_Carbon_C

apture_web.pdf

23Du, Y., J.E. Parsons (2009). Update on the cost of nuclear power. MIT Center for Energy and 

Environmental Policy Research (CEEPR) Working Paper 09-004, May 2009. 

http://web.mit.edu/ceepr/www/publications/workingpapers/2009-004.pdf

24Cleetus R., S. Clemmer, and D. Friedman, Climate 2030 - A National Blueprint for a Clean 

Energy Economy, Union of Concerned Scientists, May 2009. 

http://www.ucsusa.org/global_warming/solutions/big_picture_solutions/climate-2030-

blueprint.html#Download_the_Climate_2030_Blueprint_repo
4-20 

Table 4-13 Performance and Unit Cost Assumptions for Potential (New) Capacity from Conventional Technologies i

Advanced 

Combined 

Cycle 

Advanced 

Combustion 

Turbine 

Nuclear 

Integrated 

Gasification 

Combined 

Cycle –

Bituminous 

Integrated 

Gasification 

Combined Cycle 

– Subbituminous 

Advanced 

Coal with 

Carbon 

CaptureBituminous1

Advanced Coal 

 with Carbon 

Capture – 

Subbituminous1

Supe

Pulv

Coa

Bitu

Size (MW) 560 170 1350 600 600 500 500 

First Year 

Available 2015 2012 2017 2013 2013 2015 2015 2

Lead Time (Years) 3 2 6 4 4 4 4 

Vintage #1 

(years covered) 

2012 - 

2054 2012 - 2054 2012 - 2054 2012 - 2054 2012 - 2054 2012 - 2054 2015 - 2054 2012 

Availability 87% 92% 90% 85% 85% 85% 85% 8

Vintage #1 

Heat Rate 

(Btu/kWh) 6,810 10,720 10,400 8,424 8,062 10,149 9,713 8

Capital2

(2007$/kW) 976 698 4,621 3,265 3,310 4,720 4,785 2

Fixed O&M 

(2007$/kW/yr) 14.4 12.3 92.4 47.9 48.2 60.5 61.0 2

Variable O&M 

(2007$/MWh) 2.57 3.59 0.77 1.32 1.15 1.67 1.46 3

Notes:1For The term “Advanced Coal with Carbon Capture” is used here and in the output files for EPA Base Case v.4.10 to repre

technologies that are expected to provide carbon capture capabilities. These include both supercritical steam generators wintegrated gasification combined cycle (IGCC) with carbon capture. Although IGCC with carbon capture was used to define 

performance parameters that are implemented in EPA Base Case v.4.10, projections of “Advanced Coal with Carbon Captuv.4.10 are not limited to this technology. 

2Capital cost represents overnight capital cost. 
4-21 

Table 4-13 also shows fixed operating and maintenance (FOM) and variable operating and 

maintenance (VOM) components of cost. FOM is the annual cost of maintaining a generating 

unit. It represents expenses incurred regardless of the extent that the unit is run. It is expressed 

in units of $ per kW per year. VOM represents the costs incurred in running an electric generating 

unit. It is proportional to the electrical energy produced and is expressed in units of $ per MWh. 

In addition to the three components of cost, Table 4-13 indicates the first year available, lead time, 

vintage periods, heat rate, and availability for each type of unit. Lead time represents the 

construction time needed for a unit to come online. Vintage periods are used to capture the cost 

and performance improvements resulting from technological advancement and learning-by-doing. 

Mature technologies and technologies whose first year available is not at the start of the modeling 

time horizon may have only one vintage period, whereas newer technologies may have several 

vintage periods. Heat rate indicates the efficiency of the unit and is expressed in units of energy 

consumed (Btus) per unit of electricity generated (kWh). Availability indicates the percentage of 

time that a generating unit is available to provide electricity to the grid once it has come on line. 

Availability takes into account estimates of the time consumed by planned maintenance and 

forced outages. The emission characteristics of the potential units are not presented in Table 

4-13, but can be found in Table 3-11. 

4.4.3 Short-Term Capital Cost Adder 

Besides the capital costs shown in Table 4-13 and Table 4-16 EPA Base Case v.4.10 includes a 

short-term capital cost adder that kicks in if the new capacity in a specific model run year exceeds 

certain upper bounds. This is meant to reflect the added cost incurred due to short-term 

competition for scarce labor and materials. Table 4-14 shows the cost adders for each type of 

potential unit for model run years through 2030. The adder is not imposed after 2030 on the 

premise that by then market adjustments will have eliminated the short term scarcity experienced 

in earlier years. 

Here’s how these short-term adders work in Base Case v.4.10: The column labeled “Step 1” in 

Table 4-14 indicates the total amount of capacity of a particular plant type that can be built in a 

given model run year without incurring a cost adder. However, if the Step 1 upper bound is 

exceeded, then either the Step 2 or Step 3 cost adder is incurred. Above the Step 1 upper bound, 

the Step 2 cost adder applies until the cumulative capacity exceeds the Step 1 + Step 2 upper 

bound. Beyond that point, the Step 3 capital cost adder applies. For example, the Step 1 upper 

bound in 2012 for coal steam potential units is 25,301 MW. If no more than this total new coal 

steam capacity is built in 2012, only the capital cost shown in Table 4-13 is incurred. Between 

25,301 and 42,168 MW (the sum of the Step 1 and Step 2 upper bounds, i.e., 25,301 MW + 16, 

867 MW = 42,168 MW), the Step 2 cost adder of $967/MW applies. For all the new coal capacity 

built in that model run year (not just the increment of new capacity above the Step 1 upper bound 

of 25,301 MW), this extra cost is added to the capital cost shown in Table 4-13. If the total new 

coal steam capacity exceeds the Step 1 + Step 2 upper bound of 42,168 MW, then the Step 3 

capacity adder of $2,500/MW is incurred. To determine if the upper bounds for plant type “Coal 

Steam” in Table 4-14 have been reached, one must sum the capacities added in a model run year 

for plant types Supercritical Pulverized Coal - Wet Bituminous and Supercritical Pulverized Coal - 

Dry Bituminous. The upper bound for “Coal Steam” applies to the sum of the capacity added in 

the model run year for these two plant types. 

The short-term capital cost adders shown in Table 4-14 were derived from AEO assumptions. 

4.4.4 Regional Cost Adjustment 

The capital costs reported in Table 4-14 are generic. Before EPA implements these capital cost 

values they are converted to region-specific costs. This is done through the application of regional 

adjustment factors which capture regional differences in labor, material, and construction costs. 

The regional adjustment factors used in EPA Base Case v.4.10 are shown in Table 4-15. They 
4-22 

were developed from AEO and are applied to both conventional technologies shown in Table 4-13 

and to the renewable and non-conventional technologies shown in Table 4-16 below. 

 
4-23 

Table 4-14 Short-Term Capital Cost Adders for New Power Plants in EPA Base Case v.4.10 (200

2012 2015 2020 

ID 

Number Plant Type Step 1 Step 2 Step 3 Step 1 Step 2 Step 3 Step 1 Step 2 Step 3 

Upper Bound (MW) 600 400 -- 1,800 1,200 -- 3,000 2,000 -- 

1 Biomass 

Adder ($/kW) -- 1,410 3,646 -- 1,410 3,646 -- 1,410 3,646 Upper Bound (MW) 8,434 5,622 -- 25,301 16,867 -- 42,168 28,112 -- 

2 Coal Steam 

Adder ($/kW) -- 967 2,500 -- 967 2,500 -- 967 2,500 Upper Bound (MW) 46,469 30,979 -- 139,406 92,937 -- 232,344 154,896 -- 

3 Combined Cycle Adder ($/kW) -- 310 801 -- 310 801 -- 310 801 

Upper Bound (MW) 24,098 16,066 -- 72,295 48,197 -- 120,492 80,328 -- 

4 Combustion Turbine Adder ($/kW) -- 213 551 -- 213 551 -- 213 551 

Upper Bound (MW) 600 400 -- 1,800 1,200 -- 3,000 2,000 -- 

5 Fuel Cell 

Adder ($/kW) -- 1,987 5,138 -- 1,987 5,138 -- 1,987 5,138 Upper Bound (MW) 315 210 -- 946 630 -- 1,576 1,051 -- 

6 Geothermal 

Adder ($/kW) -- 1,981 5,123 -- 1,981 5,123 -- 1,981 5,123 Upper Bound (MW) 2,400 1,600 -- 7,200 4,800 -- 12,000 8,000 -- 

7 

IGCC and Advanced Coal with Carbon Capture 

Adder ($/kW) -- 1,072 2,774 -- 1,072 2,774 -- 1,072 2,774 Upper Bound (MW) 600 400 -- 1,800 1,200 -- 3,000 2,000 -- 

8 Landfill Gas 

Adder ($/kW) -- 1,135 2,936 -- 1,135 2,936 -- 1,135 2,936 Upper Bound (MW) 11,230 7,487 -- 33,690 22,460 -- 56,151 37,434 -- 

9 Nuclear 

Adder ($/kW) -- 1,579 4,083 -- 1,579 4,083 -- 1,579 4,083 Upper Bound (MW) 106 70 -- 317 211 -- 528 352 -- 

10 Solar Thermal Adder ($/kW) -- 1,608 4,158 -- 1,608 4,158 -- 1,608 4,158 

Upper Bound (MW) 54 36 -- 54 36 -- 90 60 -- 

11 Solar PV 

Adder ($/kW) -- 1,733 4,483 -- 1,733 4,483 -- 1,733 4,483 
4-24 

2012 2015 2020 

ID 

Number Plant Type Step 1 Step 2 Step 3 Step 1 Step 2 Step 3 Step 1 Step 2 Step 3 

Upper Bound (MW) 23,000 19,670 -- 29,505 19,670 -- 49,174 32,783 -- 

12 Onshore Wind Adder ($/kW) -- 646 1,672 -- 646 1,672 -- 646 1,672 

Upper Bound (MW) 600 400 -- 1,800 1,200 -- 3,000 2,000 -- 

13 Offshore Wind Adder ($/kW) -- 1,304 3,373 -- 1,304 3,373 -- 1,304 3,373 

Note:

The term “Advanced Coal with Carbon Capture” is used here and in the output files for EPA Base Case v.4.10 to represent 

technologies that are expected to provide carbon capture capabilities. These include both supercritical steam generators wintegrated gasification combined cycle (IGCC) with carbon capture. Although IGCC with carbon capture was used to define 

performance parameters that are implemented in EPA Base Case v.4.10 and shown in Table 4-13, projections of “Advance

Capture” in EPA Base Case v.4.10 are not limited to this technology. 
4-25 

Table 4-15 Regional Cost Adjustment Factors for Conventional and Renewable Generating 

Technologies in EPA Base Case v.4.10 

Model 

Region Region Description or Reliability Council Name Regional Factor 

AZNM Western Electricity Coordinating Council - Arizona, New Mexico 1.003 

CA-N Western Electricity Coordinating Council - California North 1.058 

CA-S Western Electricity Coordinating Council - California South 1.058 

COMD Commonwealth Edison 1.004 

DSNY Downstate New York 1.043 

ENTG Entergy 0.960 

ERCT Texas Regional Entity 0.986 

FRCC Florida Reliability Coordinating Council 0.961 

GWAY Gateway 1.004 

LILC Long Island Company 1.879 

MACE Legacy Mid-Atlantic Area Council - East 0.996 

MACS Legacy Mid-Atlantic Area Council - South 0.996 

MACW Legacy Mid-Atlantic Area Council - West 0.996 

MECS Michigan Electric Coordination System 1.004 

MRO Midwest Regional Planning Organization 1.004 

NENG New England Power Pool 1.145 

NWPE Western Electricity Coordinating Council - Northwest Power Pool 

East 1.026 

NYC New York City 1.989 

PNW Western Electricity Coordinating Council - Pacific Northwest 1.026 

RFCO Reliability First Corporation - MISO 1.004 

RFCP Reliability First Corporation - PJM 1.004 

RMPA Western Electricity Coordinating Council - Rocky Mountain Power 

Area 1.003 

SNV Western Electricity Coordinating Council - Southern Nevada 1.003 

SOU Southern Company 0.960 

SPPN Southwest Power Pool - North 0.997 

SPPS Southwest Power Pool - South 0.997 

TVA Tennessee Valley Authority 0.960 

TVAK Tennessee Valley Authority - MISO-KY 1.004 

UPNY Upstate New York 1.043 

VACA Virginia-Carolinas 0.960 

VAPW Dominion Virginia Power 0.960 

WUMS Wisconsin-Upper Michigan 1.004 

4.4.5 Cost and Performance for Potential Renewable Generating and Non-Conventional 

Technologies 

The renewable and non-conventional generating technologies included as potential units in the 

EPA Base Case v.4.10 are conventional biomass boilers, biomass gasification combined cycle 

(BGCC), onshore and offshore wind (shallow and deep), geothermal, fuel cells, solar photovoltaic, 

solar thermal, and landfill gas. Table 4-16 summarizes the cost and performance assumptions in 

EPA Base Case v.4.10 for these potential units. Except for biomass, the parameters shown in 

Table 4-16 are based on AEO 2009. The size (MW) presented in Table 4-16 represents the 

capacity on which unit cost estimates were developed and does not indicate the total potential 

capacity that the model can build of a given technology. Due to the distinctive nature of generation 

from renewable resources, some of the values shown in Table 4-16 are averages or ranges that 

are discussed in further detailed in the following subsections. Also discussed below are additional 
4-26 

types of data from sources other than AEO 2009 that play a role in the representation of these 

types of generation in EPA Base Case v.4.10. 
4-27 

Table 4-16 Performance and Unit Cost Assumptions for Potential (New) Renewable and Non-Conventional Techno

Base Case v4.10 

Biomass Landfill Gas 

Conventional 

Boiler1

Biomass 

Gasification 

Combined 

Cycle1

Fuel 

Cells Geothermal 

LGHI LGLo LGVLo 

Solar 

Photovoltaic 

Solar 

Therm

Size (MW) 35 120 10 50 30 5 100 

First Year Available 2013 2019 2013 2014 2013 2012 2013 

Lead Time (Years) 3 4 3 4 3 2 3 

Vintage #1 

(years covered) 

2012 - 

2019 

2012 - 

2019 

2012 - 

2019 2012 - 2019 2012 - 2019 

Vintage #2 

(years covered) 

2020 - 

2029 

2020 - 

2029 

2020 - 

2029 2020 - 2029 2020 - 2029 

Vintage #3 

(years covered) 

2012 - 2054 2020 - 2054 2012 - 2054 2012 - 2054 

2030 - 

2054 

2030 - 

2054 

2030 - 

2054 2030 - 2054 2030 - 2054 

Availability 85% 85% 87% 87% 90% 90% 90% 

Generation Capability Economic Dispatch Genera

Vintage #1 

Heat Rate (Btu/kWh) 13,500 - 7,930 29,655 - 397,035 13,648 13,648 13,648 0 0 

Capital (2007$/kW)2 4,698 - 6,259 1,624 - 20,674 2,596 3,270 5,035 5,765 5,156 

Fixed O&M (2007$/kW/yr) 85.2 - 5.7 151 - 219 114.3 114.3 114.3 11.7 56.8 

Variable O&M (2007$/MWh) 11.60 - 47.92 0.00 0.01 0.01 0.01 0 0 

Vintage #2 

Heat Rate (Btu/kWh) - 9,800 - - 13,648 13,648 13,648 0 0 

Capital (2007$/kW) 2 - 4,071 - - 2,505 3,156 4,859 5,350 4,641 

Fixed O&M (2007$/kW/yr) - 48.3 - - 114.3 114.3 114.3 11.7 56.8 

Variable O&M (2007$/MWh) - 8.83 - - 0.01 0.01 0.01 0 0 

Vintage #3 

Heat Rate (Btu/kWh) - - - - 13,648 13,648 13,648 0 0 

Capital (2007$/kW) 2 - - - - 2,019 2,544 3,916 3,777 4,383 

Fixed O&M (2007$/kW/yr) - - - - 114.3 114.3 114.3 11.7 56.8 

Variable O&M (2007$/MWh) - - - - 0.01 0.01 0.01 0 0 

Note:1 The biomass generating technologies shown in this table represent new capacity designed to burn biomass only. Assumptions for biomass co-firing at found in Table 5-14. 2Capital cost represents overnight capital cost. 
4-28 

It should be noted that the short term capital cost adder in Table 4-14 and the regional cost 

adjustment factors in Table 4-15 apply to the renewable and non-conventional generation 

technologies as they did to the conventional generation technologies 

Biomass Electricity Generation 

Two biomass generation technologies with separate vintage periods are offered as new (potential) 

units in EPA Base Case v.4.10. Conventional direct fired biomass boilers are offered in vintage 

period 1, i.e., 2012-2019. Based on engineering and market analysis that indicated that biomass 

gas combined cycle (BGCC) units will become commercially available by 2020, BGCC with its 

much more favorable heat rate and cost characteristics is provided as a potential unit from 2020 

onward. Prepared by EPA’s power sector engineering staff, the cost and performance 

characteristics of these two technology options are shown in Table 4-16. 

Wind Generation 

Previous EPA base cases only represented onshore wind generation. In addition to onshore 

wind, EPA Base Case v.4.10 includes offshore-shallow and offshore-deep wind generation. The 

following sections describe four key aspects of the representation of wind generation: wind quality 

and resource potential, generation profiles, reserve margin contribution, and capital cost 

calculation. 

Wind Quality and Resource Potential: Wind resources are conventionally categorized into wind 

quality classes, ranging from class 1 (designated to be the least productive and reliable class for 

wind generation) to class 7 (designated to be the most productive and reliable class for wind 

generation). Areas designated as wind class 3 or higher are generally suitable for commercial 

wind turbine applications. Whereas previous EPA base cases only included wind classes 4, 5, 

and 6, EPA Base Case v.4.10 also includes class 3 and 7. 

EPA worked with the U.S. Department of Energy’s (DOE) National Renewable Energy Laboratory 

(NREL), on a complete update of the wind resource assumptions for use in EPA Base Case 

v.4.10. The result is a complete representation of the potential onshore, offshore (shallow and 

deep) wind generating capacity (in MW) broken into four cost classes (described in greater detail 

below) in each IPM model region. Table 4-17, Table 4-18 , and Table 4-19 present the onshore, 

offshore shallow, and offshore deep wind resource assumptions that are used in EPA Base Case 

v.4.10.
4-29 

Table 4-17 Onshore Regional Potential Wind Capacity (MW) by Wind and Cost Class in 

EPA Base Case v.4.10 

Cost Class IPM Region Wind Class 

1 2 3 4 

3 707 1,714 44 125,761 

4 42 329 27 33,741 

5 6 2,028 1,612 2,355 

6 214 447 264 512 

AZNM 

7 4 106 144 166 

3 1,269 -- -- 8,646 

4 560 1,069 1,476 1,539 

5 79 631 746 765 

6 286 -- 795 740 

CA-N 

7 12 352 -- 399 

3 1,689 -- -- 18,014 

4 1,323 1,460 1,402 2,536 

5 380 614 653 831 

6 118 -- 435 540 

CA-S 

7 46 -- 231 233 

3 2 -- -- 62,549 COMD 4 19 260 -- 312 

3 98 599 297 500 

4 64 -- -- 268 

5 -- 60 -- 89 

6 -- -- 30 29 

DSNY 

7 -- -- -- 29 

3 1 1 -- 2 ENTG 5 -- 20 -- 30 

3 3,230 -- 1,198 321,950 

4 9,912 32,701 2,796 51,392 

5 396 1,415 899 1,484 

6 207 -- 512 582 

ERCT 

7 5 -- -- 20 

3 10 -- -- 275,467 GWAY 4 -- 621 580 922 

3 -- -- 872 567 LILC 4 -- 128 -- 194 

3 384 -- 925 1,264 

MACE 4 9 -- -- 163 

5 -- -- -- 2 

3 8 -- -- 57 

MACS 4 2 5 -- 10 

5 -- -- -- 3 

3 700 1,054 1,747 2,412 

4 182 -- 636 477 

5 71 -- 200 161 MACW 

6 -- 26 -- 46 
4-30 

Cost Class IPM Region Wind Class 

1 2 3 4 

3 3,571 -- -- 35,633 

MECS 4 -- -- 467 259 

5 -- 11 -- 12 

3 17 -- -- 2,021,548 

4 7 103 163,083 1,010,547 

5 2,052 22,146 68,431 156,014 MRO 

6 1,310 1,985 1,380 4,489 

3 1,768 -- -- 9,127 

4 737 1,128 -- 1,968 

5 364 442 -- 969 

6 28 356 471 438 

NENG 

7 147 -- -- 478 

3 1,913 -- -- 630,559 

4 1,891 6,167 7,657 236,910 

5 353 1,058 3,600 50,582 

6 122 1,239 3,823 17,728 

NWPE 

7 205 1,517 755 1,755 

3 216 902 354 74,323 

4 69 322 208 15,515 

5 11 86 122 3,483 

6 34 87 99 1,463 

PNW 

7 18 116 79 190 

3 12,199 22,865 8,334 28,239 RFCO 4 -- -- -- 64 

3 196 289 4,841 2,976 

4 82 354 -- 466 

5 44 -- 169 159 

6 41 -- 148 96 

RFCP 

7 2 24 -- 53 

3 1,327 -- -- 409,831 

4 3,222 4,769 8,447 216,430 

5 2,546 7,038 15,851 58,990 

6 3,149 8,000 11,388 14,741 

RMPA 

7 619 6,188 2,151 6,748 

3 -- -- -- 2,707 

4 -- -- -- 234 

5 9 -- -- 39 SNV 

6 1 -- -- 11 

SOU 3 1 -- 2 2 

3 1 -- -- 454,442 

SPPN 4 1,933 9,618 37,341 163,483 

5 -- -- -- 839 
4-31 

Cost Class IPM Region Wind Class 

1 2 3 4 

3 109 -- 69 452,934 

4 2,945 11,388 44,398 349,741 

5 2,660 13,184 -- 21,167 

6 3 105 111 170 

SPPS 

7 -- -- -- 34 

3 204 -- -- 637 

4 -- 121 166 155 

5 19 -- 56 62 

6 3 -- 19 16 

TVA 

7 -- 5 -- 12 

3 4 -- -- 220 

4 2 -- 17 15 

5 -- -- -- 5 

TVAK 

 

6 -- -- 1 -- 

3 -- 2,822 3,346 3,675 

4 -- 403 -- 555 

5 -- 95 -- 114 UPNY 

6 -- -- 35 25 

3 92 272 -- 879 

4 33 60 -- 124 

5 8 -- 39 44 

6 4 -- 30 27 

VACA 

7 -- 7 -- 18 

3 -- 261 -- 352 

4 13 40 -- 100 

5 5 -- 34 35 

6 5 -- 29 33 

VAPW 

7 -- 11 -- 17 

3 371 -- -- 130,624 

WUMS 4 57 49 64 84 

5 -- -- -- 41 
4-32 

Table 4-18 Offshore Shallow Regional Potential Wind Capacity (MW) by Wind and Cost 

Class in EPA Base Case v.4.10 

Cost Class IPM Region Wind Class 

1 2 4 

3 497 995 995 

4 281 561 561 

5 43 86 86 

6 29 59 59 

CA-N 

7 1 3 3 

3 280 560 560 

4 139 277 277 

5 139 278 278 

6 114 228 228 

CA-S 

7 1 3 3 

3 393 785 785 COMD 4 981 1,963 1,963 

DSNY 3 11 22 22 

3 43,021 86,041 86,041 ENTG 4 695 1,390 1,390 

3 14,372 28,745 28,745 

ERCT 4 15,191 30,382 30,382 

5 4,457 8,915 8,915 

3 43,305 86,610 86,610 FRCC 4 6,120 12,240 12,240 

3 693 1,385 1,385 

4 1,610 3,220 3,220 

5 1,851 3,703 3,703 LILC 

6 530 1,060 1,060 

3 2,745 5,490 5,490 

4 8,161 16,323 16,323 

5 8,838 17,676 17,676 MACE 

6 5,123 10,246 10,246 

3 1,066 2,132 2,132 MACS 4 187 374 374 

3 160 319 319 

4 136 271 271 

5 1,320 2,640 2,640 MACW 

6 5 11 11 

3 2,349 4,699 4,699 

4 3,850 7,701 7,701 

5 5,451 10,903 10,903 

6 1,886 3,771 3,771 

MECS 

7 6 13 13 

3 399 798 798 

4 952 1,904 1,904 

5 348 696 696 MRO 

6 1 3 3 
4-33 

Cost Class IPM Region Wind Class 

1 2 4 

3 2,326 4,652 4,652 

4 3,134 6,269 6,269 

5 2,989 5,978 5,978 

6 6,157 12,314 12,314 

NENG 

7 334 667 667 

3 99 198 198 

NYC 4 253 506 506 

5 3 5 5 

3 716 1,432 1,432 

4 1,651 3,303 3,303 

5 1,310 2,620 2,620 

6 204 407 407 

PNW 

7 112 224 224 

3 686 1,371 1,371 

4 2,298 4,595 4,595 

5 5,664 11,328 11,328 RFCO 

6 1,963 3,925 3,925 

3 8,466 16,933 16,933 

SOU 4 4,903 9,806 9,806 

5 311 621 621 

3 884 1,768 1,768 

UPNY 4 859 1,718 1,718 

5 659 1,318 1,318 

3 6,229 12,458 12,458 

4 12,064 24,129 24,129 

5 13,709 27,418 27,418 VACA 

6 3,209 6,419 6,419 

3 1,990 3,981 3,981 

4 3,422 6,843 6,843 

5 3,886 7,772 7,772 VAPW 

6 3,660 7,321 7,321 

3 2,272 4,544 4,544 

4 2,902 5,805 5,805 

5 1,832 3,664 3,664 WUMS 

6 680 1,360 1,360 
4-34 

Table 4-19 Offshore Deep Regional Potential Wind Capacity (MW) by Wind and Cost Class 

in EPA Base Case v.4.10 

Cost Class IPM Region Wind Class 

1 2 4 

3 4,039 8,077 8,077 

4 25,846 51,693 51,693 

5 9,947 19,894 19,894 

6 21,282 42,565 42,565 

CA-N 

7 19,318 38,636 38,636 

3 10,721 21,441 21,441 

4 9,247 18,494 18,494 

5 14,402 28,805 28,805 

6 10,140 20,280 20,280 

CA-S 

7 169 339 339 

4 1,028 2,055 2,055 

COMD 5 1,100 2,200 2,200 

6 950 1,900 1,900 

3 13,473 26,945 26,945 ENTG 4 10,730 21,461 21,461 

4 10,501 21,003 21,003 ERCT 5 6,548 13,096 13,096 

3 28,019 56,037 56,037 

FRCC 4 53,858 107,715 107,715 

5 1,109 2,219 2,219 

4 501 1,002 1,002 

5 431 861 861 

6 15,589 31,178 31,178 LILC 

7 5 10 10 

3 11 22 22 

4 140 280 280 

5 1,049 2,099 2,099 MACE 

6 22,490 44,979 44,979 

MACS 4 7 14 14 

4 29 58 58 MACW 5 557 1,114 1,114 

3 220 439 439 

4 701 1,403 1,403 

5 7,710 15,420 15,420 

6 33,394 66,787 66,787 

MECS 

7 45 90 90 

3 354 707 707 

4 4,882 9,765 9,765 

5 3,283 6,566 6,566 MRO 

6 1,535 3,070 3,070 

3 144 287 287 

4 1,754 3,508 3,508 

5 3,683 7,366 7,366 

6 59,338 118,676 118,676 

NENG 

7 1,762 3,524 3,524 
4-35 

Cost Class IPM Region Wind Class 

1 2 4 

NYC 4 58 116 116 

3 241 482 482 

4 813 1,625 1,625 

5 12,502 25,005 25,005 

6 34,795 69,589 69,589 

PNW 

7 25,739 51,477 51,477 

4 9 19 19 

RFCO 5 1,162 2,323 2,323 

6 507 1,014 1,014 

3 8,765 17,529 17,529 

SOU 4 15,055 30,109 30,109 

5 2,169 4,339 4,339 

3 50 100 100 

4 1,506 3,011 3,011 

5 5,993 11,986 11,986 UPNY 

6 465 930 930 

4 2 3 3 

VACA 5 6,536 13,073 13,073 

6 23,687 47,373 47,373 

5 151 302 302 VAPW 6 16,150 32,300 32,300 

3 395 790 790 

4 3,533 7,066 7,066 

5 8,073 16,145 16,145 WUMS 

6 39,059 78,119 78,119 
4-36 

Generation Profiles: Unlike other renewable generation technologies, which dispatch on an 

economic basis subject to their availability constraint, wind and solar technologies can only be 

dispatched when the wind blows and the sun shines. To represent intermittent renewable 

generating sources like wind and solar, EPA Base Case v.4.10 uses generation profiles which 

specify hourly generation patterns for a representative day in winter and summer. Each eligible 

model region is provided with a distinct set of winter and summer generation profiles for wind, 

solar thermal, and solar photovoltaic plants. 

For Hour1 through Hour 24 the generation profile indicates the amount of generation (kWh) per 

MW of available capacity. The wind generation profiles were prepared with data from NREL. This 

provided the separate winter and summer generation profiles for wind classes 3-7 for onshore and 

offshore (shallow and deep) generation in each IPM region. (As an illustrative example Appendix 

4-1 shows the generation profile for onshore wind in model region CA-N.) In IPM the seasonal 

average “kWh of generation per MW” (shown in the last row of the example in Appendix 4-1) is 

used to derive the generation from a particular wind class in a specific model region. 

To obtain the seasonal generation for the units in a particular wind class in a specific region, one 

must multiply the installed capacity by the capacity factor (which represents the ratio of actual 

productivity in a time period to the theoretical maximum in the period). Capacity factor is the 

average “kWh of generation per MW” from the applicable generation profile multiplied by the 

number of days in the time period (i.e., summer or winter) to obtain the level of generation. The 

capacity factors for wind generation that are used in EPA Base Case v.4.10 were obtained from 

AEO 2010 and are shown in Table 4-20, Table 4-21, and. Table 4-22 

Reserve Margin Contribution (also referred to as capacity credit): EPA Base Case v.4.10 uses 

reserve margins, discussed in detail in Section 3.6, to model reliability. Each region has a reserve 

margin requirement which is used to determine the total capacity needed to reliably meet peak 

demand. The ability of a unit to assist a region in meeting its reliability requirements is modeled 

through the unit’s contribution to reserve margin. If the unit has 100 percent contribution towards 

reserve margin, then the entire capacity of the unit is counted towards meeting the region’s 

reserve margin requirement. However, if any unit has less than a 100 percent contribution 

towards reserve margin, then only the designated share of the unit’s capacity counts towards the 

reserve margin requirement. 

All units except those that depend on intermittent resources have 100% contributions toward 

reserve margin. This means that all renewable resource technologies except wind and solar, 

have 100 percent contribution towards reserve margin in the EPA Base Case v.4.10. (Note Hydro, 

not considered a renewable technology, also has less than a 100% reserve margin contribution.) 

Reserve margin contribution ratios are based on AEO 2010. Table 4-20, Table 4-21, and Table 

4-22 present the reserve margin contributions apportioned to new wind plants in the EPA Base 

Case v.4.10 as derived from AEO 2010. The tables show the onshore and offshore (shallow and 

deep) reserve margins for each wind class in each model region.
4-37 

Table 4-20 Onshore Reserve Margin Contribution an Average Capacity Factor by Wind 

Class and Model Region 

Wind Class IPM Model Region 3 4 5 6 7 

AZNM 22% 24% 29% 34% 37% 

CA-N 14% 16% 19% 22% 24% 

CA-S 14% 16% 19% 22% 24% 

COMD 18% 20% -- -- -- 

DSNY 18% 20% 24% 28% 30% 

ENTG 26% -- 35% -- -- 

ERCT 19% 21% 25% 29% 32% 

GWAY 18% 20% -- -- -- 

LILC 18% 20% -- -- -- 

MACE 18% 20% 24% -- -- 

MACS 18% 20% 24% -- -- 

MACW 18% 20% 24% 28% -- 

MECS 22% 25% 30% -- -- 

MRO 19% 21% 26% 30% -- 

NENG 15% 16% 20% 23% 25% 

NWPE 25% 28% 33% 39% 42% 

PNW 25% 28% 33% 39% 42% 

RFCO 22% 25% -- -- -- 

RFCP 22% 25% 30% 35% 38% 

RMPA 22% 24% 29% 34% 37% 

SNV 22% 24% 29% 34% -- 

SOU 26% -- -- -- -- 

SPPN 24% 27% 33% -- -- 

SPPS 24% 27% 33% 38% 42% 

TVA 26% 29% 35% 41% 44% 

TVAK 22% 25% 30% 35% -- 

UPNY 18% 20% 24% 28% -- 

VACA 26% 29% 35% 41% 44% 

VAPW 26% 29% 35% 41% 44% 

WUMS 18% 20% 24% -- -- 

Average Annual 

Capacity Factor 29% 33% 39% 46% 50% 

Table 4-21 Offshore Shallow Reserve Margin Contribution an Average Capacity Factor by 

Wind Class and Model Region 

Wind Class IPM Model Region 3 4 5 6 7 

CA-N 15% 17% 20% 24% 25% 

CA-S 15% 17% 20% 24% 25% 

COMD 19% 21% -- -- -- 

DSNY 19% -- -- -- -- 

ENTG 27% 30% -- -- -- 

ERCT 20% 22% 26% -- -- 

FRCC 19% 21% -- -- -- 

LILC 19% 21% 25% 29% -- 
4-38 

Wind Class IPM Model Region 3 4 5 6 7 

MACE 19% 21% 25% 30% -- 

MACS 19% 21% -- -- -- 

MACW 19% 21% 25% 30% -- 

MECS 23% 26% 31% 37% 39% 

MRO 20% 22% 27% 32% -- 

NENG 15% 17% 21% 24% 26% 

NYC 19% 21% 25% -- -- 

PNW 26% 29% 35% 41% 44% 

RFCO 23% 26% 31% 37% -- 

SOU 27% 30% 36% -- -- 

UPNY 19% 21% 25% -- -- 

VACA 27% 30% 36% 43% -- 

VAPW 27% 30% 36% 43% -- 

WUMS 19% 21% 25% 30% -- 

Average Annual 

Capacity Factor 31% 34% 41% 48% 52% 

Table 4-22 Offshore Deep Reserve Margin Contribution an Average Capacity Factor by 

Wind Class and Model Region 

Wind Class IPM Model Region 3 4 5 6 7 

CA-N 15% 17% 20% 24% 26% 

CA-S 15% 17% 20% 24% 26% 

COMD -- 21% 26% 30% -- 

ENTG 27% 30% -- -- -- 

ERCT -- 22% 26% -- -- 

FRCC 18% 21% 25% -- -- 

LILC -- 21% 25% 30% 32% 

MACE 19% 21% 25% 30% -- 

MACS -- 21% -- -- -- 

MACW -- 21% 25% -- -- 

MECS 23% 26% 31% 37% 40% 

MRO 20% 23% 27% 32% -- 

NENG 15% 17% 21% 24% 26% 

NYC -- 21% -- -- -- 

PNW 26% 29% 35% 41% 45% 

RFCO -- 26% 31% 37% -- 

SOU 27% 30% 36% -- -- 

UPNY 19% 21% 25% 30% -- 

VACA -- 30% 36% 43% -- 

VAPW -- -- 36% 43% -- 

WUMS 19% 21% 26% 30% -- 

Average Annual 

Capacity Factor 31% 35% 41% 49% 53% 
4-39 

Capital cost calculation: EPA Base Case v.4.10 uses multipliers similar to the LT (long term) 

multipliers from the Energy Information Administration’s NEMS model25 to capture differences in 

the capital cost of new wind capacity caused by such factors as distance from existing 

transmission, terrain variability, slope and other causes of resource degradation, site accessibility 

challenges, population proximity, competing land uses, aesthetics, and environmental factors. 

Four cost classes are used in EPA Base Case v.4.10 with class 1 having the lowest cost 

adjustment factor (1) and class 4 having the highest adjustment factor (ranging from 2.48 to 2.67 

depending on the model region and whether the wind resource is onshore, offshore shallow or 

offshore deep), as shown in Table 4-23. To the obtain the capital cost for a particular new wind 

model plant, the base capital costs shown in Table 4-16 are multiplied by the cost adjustment 

factor for the wind cost class applicable to the new plant. 

Table 4-23 Capital Cost Adjustment Factors for New Wind Plants in Base Case v.4.10 

Cost Class 1 2 3 4 

Onshore 1 1.2 1.5 2.51

Offshore Deep Water 1 1.35 -- 2.5 

Offshore Shallow Water 1 1.35 -- 2.5 

Note:

1

The Cost Adjustment Factor for Cost Class 4 Onshore is 2.5 for the majority of regions. 

Exceptions are as follows: 

ERCT has a Cost Adjustment Factor for Cost Class 4 Onshore of 2.62 

AZNM, RMPA, and SNV have a Cost Adjustment Factor for Cost Class 4 Onshore of 2.66 

NWPE, PNW, SPPN, SPPS, and MRO have a Cost Adjustment Factor for Cost Class 4 

Onshore of 2.67 

Many factors figure in whether the model determines that adding wind capacity yields the greatest 

incremental improvement in the system-wide (least cost) solution available to the model at a 

particular point in the solution process. These factors include trade-offs between such items as 

the cost, capacity factor, reserve margin contribution, and dispatch capabilities and constraints on 

the new wind capacity relative to other choices. However, to perform its trade-off computations, 

the model requires the values described above. 

As an illustrative example, Table 4-24 shows the calculations that would be performed to derive 

the potential electric generation, reserve margin contribution, and cost of new (potential) onshore 

capacity in wind class 7, cost class 2 in the CA-N model region in run year 2020. 

 

25Revising the Long Term Multipliers in NEMS: Quantifying the Incremental Transmission Costs 

Due to Wind Power, Report to EIA from Princeton Energy Resources International, LLC. May 

2007. 
4-40 

Table 4-24 Example Calculations Of Wind Generation Potential, Reserve Margin 

Contribution, And Capital Cost For Onshore Wind In CA-N At Wind Class 7, Cost Class 2 

Solar Generation 

Solar Resource Potential: No explicit constraint limit is placed on solar electric capacity in EPA 

Base Case v.4.10. However, since solar thermal is only feasible in areas with sufficient direct 

isolation, EPA Base Case v.4.10 includes the assumption that new solar thermal plants can only 

be built west of the Mississippi River. Solar photovoltaic is not limited to specific parts of the 

country. 

Generation profiles: Like wind, solar is an intermittent renewal technology. Since it can only be 

dispatched when the sun shines, not on a strictly economic basis, it is represented in EPA Base 

Case v.4.10 with generation profiles which specify hourly generation patterns for typical winter and 

summer days in each eligible region. The generation profiles were prepared with data from AEO 

2010, which provided separate winter and summer generation profiles for solar thermal and 

photovoltaic in each eligible IPM region. As an illustrative example, Appendix 4-2 shows the solar 

thermal and solar photovoltaic winter and summer generation profiles in model region AZNM. 

Reserve margin contribution: The procedure described above for calculating the reserve margin 

contributions for wind generation was also used for solar generation. Table 4-25 presents the 

winter and summer average capacity factors (CFs) and reserve margin contributions by model 

Required Data

Table 4-17 Potential wind capacity (C) = 352 MW 

Appendix 4-1 Winter average generation (GW) per available MW per hour = 559 kWh/MW 

Appendix 4-1 Summer average generation (GS) per available MW per hour = 422 kWh/MW 

 Hours in Winter (HW) season (October – April) = 5,088 hours 

 Hours in Summer (HS)season (May – September) = 3,672 hours 

Table 4-20 Reserve Margin Contribution (RM) CA-N, Wind Class 7 = 24 percent 

Table 4-16 Capital Cost (Cap2020) in vintage range for year 2020 = $1,912/kW 

Table 4-23 Capital Cost Adjustment Factor (CAFON,C2) for onshore cost class 2 = 1.2 

Table 4-15 Regional Factor (RF) 1.058 

Calculations

GWh

MW kWh MW hours

MW kWh MW hours

Generation Potential C GW Hw C GS Hs

1,546

352 422 / 3672

352 559 / 5088

=

× ×

= × × +

= × × + × ×

MW

MW

RM C

84

24% 352

Reserve Margin Contribution

=

= ×

= ×

million dollars

MW

Capital Cost RF C

$854

$1,912/MW 1.2 1.058 352

Cap2020 CAFON,C2

=

= × × ×

= × × ×
4-41 

region for new solar thermal and photovoltaic units in EPA Base Case v.4.10. The region-specific 

summer and winter capacity factors included in this table are metrics that provide a shorthand 

depiction of the hourly specific generation profiles for each region. They are based on AEO 2010 

data. The assumptions in EPA Base Case v.4.10 for capacity factors and reserve margin 

contributions for existing units are also based on AEO 2010. 

Table 4-25 Solar Reserve Margin Contribution and Average Capacity Factor by Model 

Region 

Solar Thermal Solar Photovoltaic 

Model 

Region 

Winter 

Average 

Capacity 

Factor 

Summer 

Average 

Capacity 

Factor 

Reserve 

Margin 

Contribution 

Winter 

Average 

Capacity 

Factor 

Summer 

Average 

Capacity 

Factor 

Reserve 

Margin 

Contribution 

AZNM 30% 42% 43% 25% 28% 28% 

CA-N 32% 51% 53% 23% 28% 28% 

CA-S 32% 51% 53% 23% 28% 28% 

COMD 19% 23% 24% 

DSNY 17% 22% 22% 

ENTG 21% 23% 23% 

ERCT 26% 35% 36% 22% 24% 25% 

FRCC 23% 23% 23% 

GWAY 19% 23% 24% 

LILC 17% 22% 22% 

MACE 18% 22% 23% 

MACS 18% 22% 23% 

MACW 18% 22% 23% 

MECS 17% 23% 23% 

MRO 18% 34% 36% 20% 23% 24% 

NENG 19% 22% 23% 

NWPE 23% 41% 18% 18% 25% 16% 

NYC 17% 22% 22% 

PNW 23% 41% 18% 18% 25% 16% 

RFCO 17% 23% 23% 

RFCP 17% 23% 23% 

RMPA 30% 42% 43% 25% 28% 28% 

SNV 30% 42% 43% 25% 28% 28% 

SOU 21% 23% 23% 

SPPN 22% 35% 37% 22% 24% 25% 

SPPS 22% 35% 37% 22% 24% 25% 

TVA 21% 23% 23% 

TVAK 17% 23% 23% 

UPNY 17% 22% 22% 

VACA 21% 23% 23% 

VAPW 21% 23% 23% 

WUMS 19% 23% 24% 

Geothermal Generation 

Geothermal Resource Potential: Six model regions in EPA Base Case v.4.10 have geothermal 

potential. The potential capacity in each of these regions is shown in Table 4-26. The values are 

based on AEO 2010 data. 
4-42 

Table 4-26 Regional Assumptions on Potential Geothermal Electric Capacity 

IPM Model Region Capacity (MW) 

AZNM 2,216 

CA-N 662 

CA-S 124 

NWPE 4,555 

PNW 1,336 

RMPA 70 

Grand Total 8,963 

Note:

This data is a summary of the geothermal data used in EPA Base 

Case v.4.10 

Cost Calculation: EPA Base Case v.4.10 does not contain a single capital cost, but multiple 

geographically-dependent capital costs for geothermal generation. The assumptions for 

geothermal were developed using AEO 2010 cost and performance estimates for 88 known sites. 

 Both dual flash and binary cycle technologies26 were represented. In EPA Base Case v.4.10 the 

88 sites were collapsed into 26 different options based on geographic location and cost and 

performance characteristics of geothermal sites in each of the six eligible IPM regions where 

geothermal generation opportunities exist. Table 4-27 shows the potential geothermal capacity 

and cost characteristics for applicable model regions. 

Table 4-27 Potential Geothermal Capacity and Cost Characteristics by Model Region 

IPM Region Capacity 

(MW) 

Capital Cost 

(2007$) 

FO&M 

(2007$/kW-yr) 

1,404 4,002 185.1 

196 4,675 206.8 

316 5,650 201.1 

294 7,744 192.2 

AZNM 

6 9,199 218.8 

575 1,624 185.1 

CA-N 7 2,873 185.1 

80 4,214 206.2 

71 4,957 185.1 

CA-S 48 5,679 185.1 

5 6,817 185.1 

 

26In dual flash systems, high temperature water (above 400°F) is sprayed into a tank held at a 

much lower pressure than the fluid. This causes some of the fluid to “flash,” i.e., rapidly vaporize 

to steam. The steam is used to drive a turbine, which, in turn, drives a generator. In the binary 

cycle technology, moderate temperature water (less than 400°F) vaporizes a secondary, working 

fluid which drives a turbine and generator. Due to its use of more plentiful, lower temperature 

geothermal fluids, these systems tend to be most cost effective and are expected to be the most 

prevalent future geothermal technology. 
4-43 

IPM Region Capacity 

(MW) 

Capital Cost 

(2007$) 

FO&M 

(2007$/kW-yr) 

9 6,255 164.1 

24 8,337 164.1 

103 9,776 168.6 

1,165 11,465 179.6 

3,001 20,674 181.7 

137 4,523 185.1 

67 5,380 183.0 

12 3,428 218.8 

28 4,594 185.1 

NWPE 

9 8,210 185.1 

268 3,890 151.5 

36 4,782 151.5 

420 5,211 156.3 

PNW 

612 5,625 190.3 

RMPA 70 5,820 185.1 

Landfill Gas Electricity Generation 

Landfill Gas Resource Potential: Estimates of potential electric capacity from landfill gas are 

based on the AEO 2010 inventory. EPA Base Case v.4.10 represents 3 categories of potential 

landfill gas units; “hi”, “low”, and “very low”. The categories refer to the amount and rate of 

methane production from the existing landfill site. Table 4-28 summarizes potential electric 

capacity from landfill gas used in EPA Base Case v.4.10. 

There are several things to note about Table 4-28. Since the potential electric capacity from new 

landfill gas units is based on AEO 2009, the limits listed in Table 4-28 apply to the NEMS 

(National Energy Modeling System) regions indicated in column 1. In EPA Base Case v.4.10 the 

sum of the new landfill gas electric capacity in the corresponding IPM regions shown in column 2 

cannot exceed the limits shown in columns 3-5. As noted earlier, the capacity limits for three 

categories of potential landfill gas units are distinguished in this table based on the rate of 

methane production at three categories of landfill sites: LGHI = high rate of landfill gas production, 

LGLo = low rate of landfill gas production, and LGLVo = very low rate of landfill gas production. 

The values shown in Table 4-28 represent an upper bound on the amount of new landfill capacity 

that can be added in each of the indicated model regions for each of the three landfill categories. 

The cost and performance assumptions for adding new capacity in each of the three landfill 

categories are presented in Table 4-16. 

Table 4-28 Regional Assumptions on Potential Electric Capacity from New Landfill Gas 

Units (MW) 

NEMS Class 

Region IPM Region LGHI LGLo LGLVo 

ECAR RFCO, MECS, RFCP, TVAK 72 30 539 

ERCOT ERCT 12 26 316 

MAAC MACE, MACS, MACW 93 22 311 

MAIN WUMS, COMD, GWAY 83 92 495 

MAPP MRO 43 22 150 

NY DSNY, LILC, NYC, UPNY 54 27 142 

NE NENG 62 6 51 

FL FRCC 14 26 158 
4-44 

NEMS Class 

Region IPM Region LGHI LGLo LGLVo 

STV SOU, TVA, ENG, VACA, VAPW 68 22 447 

SPP SPPN, SPPS 5 - 185 

NWP PNW, NWPE 27 58 185 

RA AZNM, SNV, RMPA - - 91 

CNV NA-N, CA-S 131 250 749 

US 664 581 3,819 

4.5 Nuclear Units 

4.5.1 Existing Nuclear Units 

Population, Plant Location, and Unit Configuration: To provide maximum granularity in forecasting 

the behavior of existing nuclear units, all 105 nuclear units in EPA Base Case v.4.10 are 

represented by separate model plants. As noted in Table 4-7 the 105 nuclear units include 104 

currently operating units plus Watts Bar Nuclear Plant, Unit 2, which is scheduled to come online 

in 2014. All are listed in Appendix 4-3. The population characteristics, plant location, and unit 

configuration data in NEEDS, v.4.10 were obtained primarily from EIA Form 860 and AEO 2010. 

Capacity: Nuclear units are baseload power plants with high fixed (capital and fixed O&M) costs 

and low variable (fuel and variable O&M) costs. Due to their low VOM and fuel costs, nuclear 

units are run to the maximum extent possible, i.e., up to their availability. Consequently, a nuclear 

unit's capacity factor is equivalent to its availability. Thus, EPA Base Case v.4.10 uses capacity 

factor assumptions to define the upper bound on generation from nuclear units. Nuclear capacity 

factor assumptions in EPA Base Case v.4.10 are based on an Annual Energy Outlook projection 

algorithm. The nuclear capacity factor projection algorithm is described below: 

• For each reactor, the capacity factor over time is dependent on the age of the reactor. 

• Capacity factors increase initially due to learning, and decrease in the later years due to 

aging. 

• For individual reactors, vintage classifications (older and newer) are used. 

• For the older vintage (start before 1982) nuclear power plants, the performance peaks at 25 

years: 

o Before 25 years: Performance increases by 0.5 percentage point per year; 

o 25-60 years: Performance remains flat; and 

• • For the newer vintage (start in or after 1982) nuclear power plants, the performance peaks 

at 30 years: 

o Before 30 years: Performance increases by 0.7 percentage points per year; 

o 30-60 years: Performance remains flat; and 

• The maximum capacity factor is assumed to be 90 percent. That is, any given reactor is not 

allowed to grow to a capacity factor higher than 90 percent. However, if a unit began with a 

capacity factor above 90 percent, it is allowed to retain that capacity factor. Given historical 

capacity factors above 90 percent, the projected capacity factors range from 89 percent to 93 

percent. 

Cost and Performance: Unlike non-nuclear existing conventional units discussed in section 4.2.7, 

emission rates are not needed for nuclear units, since there are no SO2, NOX, CO2, or mercury 

emissions from nuclear units. 

As with other generating resources, EPA Base Case v.4.10 uses variable operation and 

maintenance (VOM) costs and fixed operation and maintenance (FOM) costs to characterize the 

cost of operating nuclear units. The heat rate, FOM, and VOM values from AEO 2010, which 

were used to characterize the cost and performance of existing nuclear units in EPA Base Case 

v.4.10 are shown in Appendix 4-03. 
4-45 

EPA Base Case v.4.10 also uses the nuclear capacity uprates from AEO 2010. These are shown 

in Table 4-29. 

4.5.2 Potential Nuclear Units 

The cost and performance assumptions for nuclear potential units that the model has the option to 

build in EPA Base Case v.4.10 are shown in Table 4-13 above. The cost assumptions were 

updated as part of the comparative analysis performed by EPA’s power sector engineering staff. 

That update is described above in section 4.4.1. 

Table 4-29 Nuclear Upratings (MW) as Incorporated in EPA Base Case v.4.10 from AEO 

2010 

Name Plant ID Unit ID Year Change in MWs 

Arkansas Nuclear One 8055 1 2016 50.0 

Arkansas Nuclear One 8055 2 2016 59.0 

Brunswick 6014 1 2014 56.3 

Brunswick 6014 2 2014 56.2 

Byron Generating Station 6023 1 2019 116.4 

Byron Generating Station 6023 2 2019 11.4 

Catawba 6036 1 2016 67.7 

Catawba 6036 2 2016 67.7 

Duane Arnold 1060 1 2015 34.8 

Fermi 1729 2 2016 67.0 

Grand Gulf 6072 1 2015 76.7 

Harris 6015 1 2017 54.0 

Joseph M Farley 6001 1 2017 51.0 

Joseph M Farley 6001 2 2017 52.0 

Limerick 6105 1 2018 113.4 

Limerick 6105 2 2018 113.4 

McGuire 6038 1 2014 110.0 

McGuire 6038 2 2014 110.0 

Oconee 3265 1 2017 51.0 

Oconee 3265 2 2017 51.0 

Oconee 3265 3 2017 51.0 

Peach Bottom 3166 2 2014 66.7 

Peach Bottom 3166 3 2014 66.7 

Perry 6020 1 2016 74.0 

PSEG Salem Generation 2410 1 2015 70.4 

PSEG Salem Generation 2410 2 2015 67.8 

Quad Cities Generation 880 1 2013 52.0 

Quad Cities Generation 880 2 2013 52.0 

Sequoyah 6152 1 2013 69.0 

Sequoyah 6152 2 2013 68.0 

South Texas Project 6251 1 2013 76.8 

South Texas Project 6251 2 2013 76.8 

Surry 3806 1 2015 47.9 

Surry 3806 2 2015 47.9 

V C Summer 6127 1 2015 58.0 

Waterford 3 4270 3 2016 69.1 

Wolf Creek Generation 210 1 2017 70.0 

Watts Bar Nuclear Plant 7722 2 2014 1,180 
Appendix 4-1.1 

Appendix 4-1 Representative Wind Generation Profiles in EPA Base Case 

v.4.10 

Illustrative Hourly Wind Generation Profile (kWh of Generation per MW of Electricity) 

 

Winter Wind Class Wind Class 

Hour 3 4 5 6 7 

Summer 

Hour 3 4 5 6 7 

01 268 361 492 504 635 01 380 410 456 591 555 

02 268 359 488 503 633 02 374 402 444 583 546 

03 269 355 483 498 629 03 366 391 422 566 523 

04 263 345 464 483 613 04 350 368 387 535 479 

05 253 326 430 454 580 05 326 334 337 489 413 

06 243 310 396 424 544 06 299 295 286 433 344 

07 236 297 374 402 518 07 282 261 250 389 295 

08 233 291 372 395 514 08 292 256 248 384 293 

09 230 282 371 391 511 09 320 270 269 408 316 

10 227 276 372 389 510 10 348 296 298 442 348 

11 225 276 374 391 510 11 368 320 320 466 368 

12 226 280 376 394 508 12 381 340 331 480 373 

13 226 283 376 396 505 13 388 354 334 484 370 

14 228 287 381 400 507 14 393 365 341 489 372 

15 227 288 385 402 511 15 393 372 350 496 383 

16 228 289 390 404 517 16 390 371 361 501 398 

17 231 289 394 406 524 17 384 358 369 501 414 

18 240 296 405 415 538 18 377 340 371 496 421 

19 250 309 423 433 558 19 375 331 378 496 431 

20 259 325 444 453 580 20 374 335 386 500 440 

21 267 339 464 473 601 21 378 354 402 518 464 

22 271 350 479 488 618 22 382 381 424 546 498 

23 271 357 488 498 629 23 384 401 444 572 529 

24 268 360 491 502 633 24 382 409 455 586 547 

Winter 

Average 246 314 421 437 559 Summer Average 362 346 361 498 422 

Notes:

Based on Onshore Wind in Model Region CA-N. 

This is an example of the wind data used in EPA Base Case v.4.10 
Appendix 4-2.1 

Appendix 4-2 Representative Solar Generation Profiles in EPA Base v.4.10 

Illustrative Hourly Solar Generation Profile (kWh of Generation per MW of Electricity) 

 

Winter 

Hour 

Solar 

Thermal 

Solar 

Photovoltaic Summer Hour 

Solar 

Thermal 

Solar 

Photovoltaic 

01 3 0 01 9 0 

02 3 0 02 9 0 

03 3 0 03 9 0 

04 3 0 04 9 0 

05 3 0 05 9 0 

06 181 29 06 284 13 

07 181 29 07 284 13 

08 601 660 08 720 610 

09 601 660 09 720 610 

10 601 660 10 720 610 

11 601 660 11 720 610 

12 601 660 12 720 610 

13 601 660 13 720 610 

14 601 660 14 720 610 

15 601 660 15 720 610 

16 601 660 16 720 610 

17 601 660 17 720 610 

18 601 660 18 720 610 

19 181 29 19 284 13 

20 181 29 20 284 13 

21 181 29 21 284 13 

22 181 29 22 284 13 

23 181 29 23 284 13 

24 181 29 24 284 13 

Winter 

Average 336 312 Summer Average 426 284 

Notes:

Based on model region AZNM. 

This is an example of the solar data used in EPA Base Case v.4.10 
Appendix 4-3.1 

Appendix 4-3 Characteristics of Existing Nuclear Units 

Region State Plant Name 

ORIS 

Code_Unit 

Id 

On-Line 

Year 

Capacit

y (MW) 

Heat Rate 

(Btu/kWh) 

FO

(20

/kW

Palo Verde 6008_1 1986 1,311 10,427 11

AZNM Arizona Palo Verde 6008_2 1986 1,352 10,427 11

Palo Verde 6008_3 1988 1,283 10,427 11Diablo Canyon 6099_1 1985 1,122 10,427 13

CA-N California 

Diablo Canyon 6099_2 1986 1,118 10,427 13San Onofre 360_2 1983 1,070 10,427 20

CA-S California 

San Onofre 360_3 1984 1,080 10,427 20Braidwood Generation Station 6022_1 1988 1,178 10,427 12Braidwood Generation Station 6022_2 1988 1,152 10,427 12Byron Generating Station 6023_1 1985 1,164 10,427 12Byron Generating Station 6023_2 1987 1,136 10,427 12LaSalle Generating Station 6026_1 1984 1,118 10,427 15LaSalle Generating Station 6026_2 1984 1,120 10,427 15Dresden Generating Station 869_2 1970 867 10,427 20Dresden Generating Station 869_3 1971 867 10,427 20Quad Cities Generating Station 880_1 1972 867 10,427 17

COMD Illinois 

Quad Cities Generating Station 880_2 1972 867 10,427 17Indian Point 2 2497_2 1973 1,020 10,427 22

DSNY New York 

Indian Point 3 8907_3 1976 1,025 10,427 19Arkansas Nuclear One 8055_1 1974 836 10,427 15

Arkansas 

Arkansas Nuclear One 8055_2 1980 988 10,427 15Waterford 3 4270_3 1985 1,152 10,427 16

Louisiana 

River Bend 6462_1 1986 967 10,427 19

ENTG 

Mississippi Grand Gulf 6072_1 1985 1,266 10,427 13
Appendix 4-3.2 

Region State Plant Name 

ORIS 

Code_Unit 

Id 

On-Line 

Year 

Capacit

y (MW) 

Heat Rate 

(Btu/kWh) 

FO

(20

/kW

Comanche Peak 6145_1 1990 1,202 10,240 12Comanche Peak 6145_2 1993 1,202 10,317 12South Texas Project 6251_1 1988 1,280 10,427 12

ERCT Texas 

South Texas Project 6251_2 1989 1,280 10,427 12St Lucie 6045_1 1976 839 10,427 14St Lucie 6045_2 1983 714 10,427 14Turkey Point 621_3 1972 693 10,427 14Turkey Point 621_4 1973 693 10,427 14

FRCC Florida 

Crystal River 628_3 1977 851 10,427 18

Illinois Clinton Power Station 204_1 1987 1,043 10,427 20

GWAY 

Missouri Callaway 6153_1 1984 1,190 10,427 13

PSEG Salem Generating Station 2410_1 1977 1,174 10,427 15PSEG Salem Generating Station 2410_2 1981 1,130 10,427 15Oyster Creek 2388_1 1969 619 10,427 25

New Jersey 

PSEG Hope Creek Generating Station 6118_1 1986 1,196 10,427 14Limerick 6105_1 1986 1,134 10,427 12

MACE 

Pennsylvania Limerick 6105_2 1990 1,134 10,427 12

Calvert Cliffs Nuclear Power Plant 6011_1 1975 885 10,427 15

MACS Maryland Calvert Cliffs Nuclear Power Plant 6011_2 1977 874 10,427 15

Peach Bottom 3166_2 1974 1,112 10,427 17Peach Bottom 3166_3 1974 1,112 10,427 17PPL Susquehanna 6103_1 1983 1,283 10,427 17PPL Susquehanna 6103_2 1985 1,288 10,427 17

MACW Pennsylvania 

Three Mile Island 8011_1 1974 786 10,427 17Fermi 1729_2 1988 1,122 10,427 15

MECS Michigan Palisades 1715_1 1972 778 10,427 19
Appendix 4-3.3 

Region State Plant Name 

ORIS 

Code_Unit 

Id 

On-Line 

Year 

Capacit

y (MW) 

Heat Rate 

(Btu/kWh) 

FO

(20

/kW

Iowa Duane Arnold 1060_1 1975 581 10,427 20

Monticello 1922_1 1971 646 10,427 18

Minnesota Prairie Island 1925_1 1974 551 10,427 16

Prairie Island 1925_2 1974 545 10,427 16Fort Calhoun 2289_1 1973 478 10,427 21

MRO 

Nebraska 

Cooper 8036_1 1974 767 10,427 22Millstone 566_2 1975 882 10,427 20

Connecticut 

Millstone 566_3 1986 1,236 10,427 19

Massachusetts Pilgrim Nuclear Power Station 1590_1 1972 685 10,427 24

New 

Hampshire Seabrook 6115_1 1990 1,244 10,427 17

NENG 

Vermont Vermont Yankee 3751_1 1972 620 10,427 20

PNW Washington Columbia Generating Station 371_2 1984 1,131 10,427 15

Donald C Cook 6000_1 1975 1,029 10,942 17

Michigan Donald C Cook 6000_2 1978 1,077 10,848 17

Perry 6020_1 1987 1,231 11,000 16

RFCO 

Ohio 

Davis Besse 6149_1 1977 887 11,000 15Beaver Valley 6040_1 1976 887 10,962 19

RFCP Pennsylvania Beaver Valley 6040_2 1987 887 10,946 19

Joseph M Farley 6001_1 1977 851 11,794 13

Alabama 

Joseph M Farley 6001_2 1981 860 11,650 13Edwin I Hatch 6051_1 1975 876 10,427 14Edwin I Hatch 6051_2 1979 883 10,427 14Vogtle 649_1 1987 1,172 10,427 14

SOU 

Georgia 

Vogtle 649_2 1989 1,169 10,427 14

SPPN Kansas Wolf Creek Generating Station 210_1 1985 1,166 10,427 13
Appendix 4-3.4 

Region State Plant Name 

ORIS 

Code_Unit 

Id 

On-Line 

Year 

Capacit

y (MW) 

Heat Rate 

(Btu/kWh) 

FO

(20

/kW

Browns Ferry 46_1 1974 1,225 10,550 99

Alabama Browns Ferry 46_2 1975 1,286 10,215 99

Browns Ferry 46_3 1977 1,337 10,215 99Sequoyah 6152_1 1981 1,150 10,123 11Sequoyah 6152_2 1982 1,127 10,202 11Watts Bar Nuclear Plant 7722_1 1996 1,121 10,266 13

TVA 

Tennessee 

Watts Bar Nuclear Plant 7722_2 2014 1,180 10,266 92Nine Mile Point Nuclear Station 2589_1 1969 621 10,427 19Nine Mile Point Nuclear Station 2589_2 1969 1,311 10,427 18James A Fitzpatrick 6110_1 1976 852 10,427 20

UPNY New York 

R. E. Ginna Nuclear Power Plant 6122_1 1970 498 10,427 20Brunswick 6014_1 1977 938 10,318 11Brunswick 6014_2 1975 937 10,397 11Harris 6015_1 1987 900 10,982 13McGuire 6038_1 1981 1,100 10,427 11

North Carolina 

McGuire 6038_2 1984 1,100 10,427 11H B Robinson 3251_2 1971 710 10,697 11Oconee 3265_1 1973 846 10,427 13Oconee 3265_2 1974 846 10,427 13Oconee 3265_3 1974 846 10,427 13Catawba 6036_1 1985 1,129 10,427 13Catawba 6036_2 1986 1,129 10,427 13

VACA 

South Carolina 

V C Summer 6127_1 1984 966 10,427 14Surry 3806_1 1972 799 10,427 12Surry 3806_2 1973 799 10,427 12North Anna 6168_1 1978 940 10,427 98

VAPW Virginia 

North Anna 6168_2 1980 925 10,427 98
Appendix 4-3.5 

Region State Plant Name 

ORIS 

Code_Unit 

Id 

On-Line 

Year 

Capacit

y (MW) 

Heat Rate 

(Btu/kWh) 

FO

(20

/kW

Point Beach 4046_1 1970 599 10,427 20

WUMS Wisconsin Point Beach 4046_2 1972 601 10,427 20

Kewaunee 8024_1 1974 556 10,427 15
5-1 

5 Emission Control Technologies 

EPA Base Case v.4.10 includes a major update of emission control technology assumptions. For 

this base case EPA contracted with engineering firm Sargent and Lundy to perform a complete 

bottom-up engineering reassessment of the cost and performance assumptions for sulfur dioxide 

(SO2) and nitrogen oxides (NOX) emission controls. In addition to the work by Sargent and Lundy, 

Base Case v.4.10 includes two Activated Carbon Injections (ACI) options (Standard and Modified) 

for mercury (Hg) control27. Capture and storage options for carbon dioxide (CO2) have also been 

added in the new base case. 

These emission control options are listed in Table 5-1. They are available in EPA Base Case 

v.4.10 for meeting existing and potential federal, regional, and state emission limits. It is important 

to note that, besides the emission control options shown in Table 5-1 and described in this 

chapter, EPA Base Case v.4.10 offers other compliance options for meeting emission limits. 

These include fuel switching, adjustments in the dispatching of electric generating units, and the 

option to retire a unit. 

Table 5-1 Summary of Emission Control Technology Retrofit Options in EPA Base Case 

v.4.10 

SO2 Control 

Technology Options 

NOX Control 

Technology Options 

Hg Control 

Technology Options 

CO2 Control 

Technology Options 

Limestone Forced 

Oxidation (LSFO) 

Scrubber 

Selective Catalytic 

Reduction (SCR) 

System 

Standard Activated 

Carbon Injection (SPACACI) System 

CO2 Capture and 

Sequestration 

Lime Spray Dryer 

(LSD) Scrubber 

Selective NonCatalytic Reduction 

(SNCR) System 

Modified Activated 

Carbon Injection 

(MPAC-ACI) System 

 

 Combustion Controls 

SO2 and NOX Control 

Technology Removal 

Cobenefits 

 

5.1 Sulfur Dioxide Control Technologies 

Two commercially available Flue Gas Desulfurization (FGD) technology options for removing the 

SO2 produced by coal-fired power plants are offered in EPA Base Case v.4.10: Limestone Forced 

Oxidation (LSFO) — a wet FGD technology — and Lime Spray Dryer (LSD) — a semi-dry FGD 

technology which employs a spray dryer absorber (SDA). In wet FGD systems, the polluted gas 

stream is brought into contact with a liquid alkaline sorbent (typically limestone) by forcing it 

through a pool of the liquid slurry or by spraying it with the liquid. In dry FGD systems the polluted 

gas stream is brought into contact with the alkaline sorbent in a semi-dry state through use of a 

spray dryer. The removal efficiency for SDA drops steadily for coals whose SO2 content exceeds 

3lb SO2/MMBtu, so this technology is provided only to plants which have the option to burn coals 

with sulfur content no greater than 3 lbs SO2/MMBtu. In EPA Base Casev.4.10 when a unit 

retrofits with an LSD SO2 scrubber, it loses the option of burning BG, BH, and LG coals due to 

their high sulfur content. 

In EPA Base Case v.4.10 the LSFO and LSD SO2 emission control technologies are available to 

existing "unscrubbed" units. They are also available to existing "scrubbed" units with reported 

removal efficiencies of less than fifty percent. Such units are considered to have an injection 

technology and classified as “unscrubbed” for modeling purposes in the NEEDS database of 

 

27The mercury emission controls options and assumptions in EPA Base Case v.4.10 do not reflect 

mercury control updates that are currently under way at EPA in support of the Utility MACT 

initiative and do not make use of data collected under EPA’s 2010 Information Collection Request 

(ICR). 
5-2 

existing units which is used in setting up the EPA base case. The scrubber retrofit costs for these 

units are the same as regular unscrubbed units retrofitting with a scrubber. Scrubber efficiencies 

for existing units were derived from data reported in EIA Form 767. In transferring this data for 

use in EPA Base Case v.4.10 the following changes were made. The maximum removal 

efficiency was set at 98% for wet scrubbers and 93% for dry scrubber units. Existing units 

reporting efficiencies above these levels in Form 767 were assigned the maximum removal 

efficiency in NEEDS v.4.10 indicated in the previous sentence. 

As shown in Table 5-2, existing units that are selected to be retrofitted by the model with 

scrubbers are given the maximum removal efficiencies of 98% for LSFO and 93% for LSD. The 

procedures used to derive the cost of each scrubber type are discussed in detail in the following 

sections. 

Table 5-2 Summary of Retrofit SO2 Emission Control Performance Assumptions 

Performance 

Assumptions 

Limestone Forced 

Oxidation (LSFO) Lime Spray Dryer (LSD) 

Percent Removal 98% 

with a floor of 0.06 lbs/MMBtu 

93% 

with a floor of 0.065 lbs/MMBtu 

Capacity Penalty 

Heat Rate Penalty 

Cost (2007$) 

Calculated based on 

characteristics of the unit: 

See Table 5-4 for examples 

Calculated based on 

characteristics of the unit: 

See Table 5-4 for examples 

Applicability Units ≥ 25 MW Units ≥ 25 MW 

Sulfur Content 

Applicability Coals ≤ 3 lbs SO2/MMBtu 

Applicable Coal Types BA, BB, BD, BE, BG, BH, SA, 

SB, SD, LD, LE, and LG 

BA, BB, BD, BE, SA, SB, SD, 

LD, and LE 

Potential (new) coal-fired units built by the model are also assumed to be constructed with a 

scrubber achieving a removal efficiency of 98% for LSFO and 93% for LSD. In EPA Base Case 

v.4.10 the costs of potential new coal units include the cost of scrubbers. 

5.1.1 Methodology for Obtaining SO2 Controls Costs 

The Sargent and Lundy update of SO2 and NOx control costs is notable on several counts. First, it 

brought costs up to levels seen in the marketplace in 2009. Incorporating these costs into EPA’s 

base case carries an implicit assumption, not universally accepted, that the run up in costs seen 

over the preceding 5 years and largely attributed to international competition, is permanent and 

will not settle back to pre-2009 levels. Second, a revised methodology, based on Sargent and 

Lundy’s expert experience, was used to build up the capital, fixed and variable operating and 

maintenance components of cost. That methodology, which employed an engineering build up of 

each component of cost, is described here and in the following sections. Detailed example cost 

calculation spreadsheets for both SO2 and NOx controls are included in Appendices 5-1 and 5-2 

respectively. The Sargent and Lundy reports in which these spreadsheets appeared can be 

downloaded via links to the Appendices 5-1A, 5-1B, 5-2A, and 5-2B links found at 

www.epa.gov/airmarkets/progsregs/epaipm/BaseCasev410.html. 

Capital Costs: In building up capital costs three separate cost modules were included for LSD and 

four for LSFO: absorber island, reagent preparation, waste handling (LSFO only), and everything 

else (also called “balance of plant”) with the latter constituting the largest cost module, consisting 

of fans, new wet chimney, piping, ductwork, minor waste water treatment, and other costs 

required for treatment. For each of the four modules the cost of foundations, buildings, electrical 

equipment, installation, minor, physical and chemical wastewater treatment, and average retrofit 

difficulty were taken into account. 
5-3 

The governing cost variables for each module are indicated in Table 5-3. The major variables 

affecting capital cost are unit size and the SO2 content of the fuel with the latter having the 

greatest impact on the reagent and waste handling facilities. In addition, heat rate affects the 

amount of flue gas produced and consequently the size of each of the modules. The quantity of 

flue gas is also a function of coal rank since different coals have different typical heating values. 

Table 5-3 Capital Cost Modules and Their Governing Variables for SO2 and NOx Emission 

Controls 

Module 

Retrofit 

Difficulty 

(1 = 

average) 

Coal Rank 

Factor 

(Bit = 1, 

PRB = 1.05, 

Lignite = 1.07) 

Heat Rate

(Btu/kWh) 

SO2 Rate 

(lb/MMBtu) 

NOx Rate 

(lb/MMBtu)5

Unit 

Size 

(MW) 

SO2 Emission Controls – Wet FGD and SDA FGD 

Absorber 

Island X X X X X 

Reagent 

Preparation X X X X 

Waste 

Handling X X X X 

Balance of 

Plant1 X X X X 

NOx Emission Controls – SCR and SNCR 

SCR/SNCR 

Island2 X X X X3

 X 

Reagent 

Preparation3 X 

Air Heater 

Modification4 X X X X X 

Balance of 

Plant5

 – SCR X X X X 

Balance of 

Plant1

 – 

SNCR 

 X X 

Notes:

1

“Balance of plant” costs include such cost items as ID and booster fans, new wet chimneys, 

piping, ductwork, minor waste water treatment, auxiliary power modifications, and other electrical 

and site upgrades. 

2

The SCR island module includes the cost of inlet ductwork, reactor, and bypass. The SNCR 

island module includes cost of injectors, blowers, distributed control system (DCS), and reagent 

system. 

3

Only applies to SCR. 

4

On generating units that burn bituminous coal whose SO2 and content exceeds 3 lbs/MMBtu, air 

heater modifications used to control SO3 are needed in conjunction with the operation of SCR and 

SNCR. 

5

For SCR, the NOx rate is frequently expressed through the calculated NOx removal efficiency. 
5-4 

Once the key variables that figure in the cost of the four modules are identified, they are used to 

derive costs for each base module in equations developed by Sargent and Lundy based on their 

experience with multiple engineering projects. The base module costs are summed to obtain total 

bare module costs. This total is increased by 30% to account for additional engineering and 

construction fees. The resulting value is the capital, engineering, and construction cost (CECC) 

subtotal. To obtain the total project cost (TPC), the CECC subtotal is increased by 5% to account 

for owner’s home office costs, i.e., owner’s engineering, management, and procurement costs. 

The resulting sum is then increased by another 10% to build in an Allowance for Funds used 

During Construction (AFUDC) over the 3-year engineering and construction cycle. The resulting 

value, expressed in $/kW, is the capital cost factor that is used in EPA Base Case v.4.10. 

Variable Operating and Maintenance Costs (VOM): These are the costs incurred in running the 

emission control device. They are proportional to the electrical energy produced and are 

expressed in units of $ per MWh. For FGD, Sargent and Lundy identified four components of 

VOM: (a) costs for reagent usage, (b) costs for waste generation, (c) make up water costs, and 

(d) cost of additional power required to run the control (often called the “parasitic load”). For a 

given coal rank and a pre-specified SO2 removal efficiency, each of these components of VOM 

cost is a function of the generating unit’s heat rate (Btu/kWh) and the sulfur content (lb 

SO2/MMBtu) of the coal (also referred to as the SO2 feed rate). For purposes of modeling, the 

total VOM includes the first three of these component costs. The last component – cost of 

additional power – is factored into IPM, not in the VOM value, but through a capacity and heat rate 

penalty as described in the next paragraph. Due to the differences in the removal processes, the 

per MWh cost for waste handling, makeup water, and auxiliary power tend to be higher for LSFO 

while reagent usage cost and total VOM (excluding parasitic load) are higher for LSD. 

Capacity and Heat Rate Penalty: The amount of electrical power required to operate the FGD 

device is represented through a reduction in the amount of electricity that is available for sale to 

the grid. For example, if 1.6% of the unit’s electrical generation is needed to operate the scrubber, 

the generating unit’s capacity is reduced by 1.6%. This is the “capacity penalty.” At the same 

time, to capture the total fuel used in generation both for sale to the grid and for internal load (i.e., 

for operating the FGD device), the unit’s heat rate is scaled up such that a comparable reduction 

(1.6% in the previous example) in the new higher heat rate yields the original heat rate28. The 

factor used to scale up the original heat rate is called “heat rate penalty.” It is a modeling 

procedure only and does not represent an increase in the unit’s actual heat rate (i.e., a decrease 

in the unit’s generation efficiency). Unlike previous base cases, which assumed a generic heat 

rate and capacity penalties for all installations, in EPA Base Case v.4.10 specific LSFO and LSD 

heat rate and capacity penalties are calculated for each installation based on equations developed 

by Sargent and Lundy that take into account the rank of coal burned, its SO2 rate, and the heat 

rate of the model plant. 

Fixed Operating and Maintenance Costs (FOM): These are the annual costs of maintaining a unit. 

 They represent expenses incurred regardless of the extent to which the emission control system 

is run. They are expressed in units of $ per kW per year. In calculating FOM Sargent and Lundy 

took into account labor and materials costs associated with operations, maintenance, and 

administrative functions. The following assumptions were made: 

 

28 Mathematically, the relationship of the heat rate and capacity penalties (both expressed as 

positive percentage values) can be represented as follows: 

1 100

100

Capacity Penalty 1

1 Heat Rate Penalty ×

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎝

⎛

−

⎟

⎠

⎞ ⎜

⎝

⎛ −

=
5-5 

• FOM for operations is based on the number of operators needed which is a function of the 

size (i.e., MW capacity) of the generating unit and the type of FGD control. For LSFO 12 

additional operators were assumed to be required for a 500 MW or smaller installation and 16 

for a unit larger than 500 MW. For LSD 8 additional operators were assumed to be needed. 

• FOM for maintenance is a direct function of the FGD capital cost 

• FOM for administration is a function of the FOM for operations and maintenance. 

Table 5-4 presents the capital, VOM, and FOM costs as well as the capacity and heat rate penalty 

for the two SO2 emission control technologies (LSFO and LSD) included in EPA Base Case v.4.10 

for an illustrative set of generating units with a representative range of capacities and heat rates. 
5-6 

Table 5-4 Illustrative Scrubber Costs (2007$) for Representative Sizes and Heat Rates under the Assumptions in E

Capacity (MW) 

100 300 500 700 

Scrubber Type Heat Rate (Btu/kWh) Capacity Penalty (%) Heat Rate Penalty (%) Variable O&M (mills/kWh) Capital Cost 

($/kW) 

Fixed 

O&M 

($/kW-yr)

Capital 

Cost 

($/kW) 

Fixed 

O&M 

($/kW-yr) 

Capital 

Cost 

($/kW) 

Fixed 

O&M 

($/kW-yr)

Capital 

Cost 

($/kW) 

Fixe

($/k

LSFO Minimum Cutoff: ≥ 25 MW 

9,000 -1.5 1.53 1.66 747 22.5 547 10.5 473 7.8 430 7

Maximum Cutoff: None 10,000 -1.67 1.7 1.84 783 22.8 573 10.8 496 8.0 451 7Assuming 3 lb/MMBtu SO2Content Bituminous Coal 

11,000 -1.84 1.87 2.03 817 23.2 598 11.0 517 8.2 470 7

LSD Minimum Cutoff: ≥ 25 MW 

9,000 -1.18 1.2 2.13 641 16.4 469 8.1 406 6.1 385 5

Maximum Cutoff: None 10,000 -1.32 1.33 2.36 670 16.7 491 8.3 424 6.3 403 5Assuming 2 lb/MMBtu SO2Content Bituminous Coal 

11,000 -1.45 1.47 2.60 698 17.0 511 8.5 442 6.5 420 5
5-7 

5.2 Nitrogen Oxides Control Technology 

The EPA Base Case v.4.10 includes two categories of NOx reduction technologies: combustion 

and post-combustion controls. Combustion controls reduce NOx emissions during the combustion 

process by regulating flame characteristics such as temperature and fuel-air mixing. Postcombustion controls operate downstream of the combustion process and remove NOx emissions 

from the flue gas. All the specific combustion and post-combustion technologies included in EPA 

Base Case v.4.10 are commercially available and currently in use in numerous power plants. 

5.2.1 Combustion Controls 

The EPA Base Case v.4.10 representation of combustion controls uses equations that are tailored 

to the boiler type, coal type, and combustion controls already in place and allow appropriate 

additional combustion controls to be exogenously applied to generating units based on the NOx

emission limits they face. Characterizations of the emission reductions provided by combustion 

controls are presented in Table 3-1.3 in Appendix 3-1. The EPA Base Case v.4.10 cost 

assumptions for NOx Combustion Controls are summarized in Table 5-5. Table 5-6 provides a 

mapping of existing coal unit configurations and incremental combustion controls applied in EPA 

Base Case v.4.10 to achieve state-of-the-art combustion control configuration. 

Table 5-5 Cost (2007$) of NOx Combustion Controls for Coal Boilers (300 MW Size) 

Boiler Type Technology Capital

($/kW) 

Fixed 

O&M 

($/kWyr) 

Variable O&M

(mills/kWh) 

Low NOx Burner without Overfire Air 

(LNB without OFA) 45 0.3 0.07 Dry Bottom WallFired Low NOx Burner with Overfire Air 

(LNB with OFA) 61 0.4 0.09 

Low NOx Coal-and-Air Nozzles with 

Close-Coupled Overfire Air (LNC1) 24 0.2 0.00 

Low NOx Coal-and-Air Nozzles with 

Separated Overfire Air (LNC2) Tangentially- 33 0.2 0.03 

Fired Low NOx Coal-and-Air Nozzles with 

Close-Coupled and Separated 

Overfire Air (LNC3) 

38 0.3 0.03 

Vertically-Fired NOx Combustion Control 29 0.2 0.06 

Scaling Factor 

The following scaling factor is used to obtain the capital and fixed operating and maintenance 

costs applicable to the capacity (in MW) of the unit taking on combustion controls. No scaling 

factor is applied in calculating the variable operating and maintenance cost. 

LNB without OFA & LNB with OFA = ($ for X MW Unit) = ($ for 300 MW Unit) x (300/X)

0.359

 LNC1, LNC2 and LNC3 = ($ for X MW Unit) = ($ for 300 MW Unit) x (300/X)

0.359

 Vertically-Fired = ($ for X MW Unit) = ($ for 300 MW Unit) x (300/X)

0.553

where 

 ($ for 300 MW Unit) is the value obtained using the factors shown in the above table and 

X is the 

 capacity (in MW) of the unit taking on combustion controls. 
5-8 

Table 5-6 Incremental Combustion NOx Controls in EPA Base Case v.4.10 

Boiler Type Existing NOx

Combustion Control Incremental Combustional Control 

LNB OFA Cell NGR LNB AND OFA 

Cyclone -- OFA 

Stoker/SPR -- OFA 

-- LNC3 

LA LNC3 

LNB CONVERSION FROM LNC1 TO LNC3 

LNB + OFA CONVERSION FROM LNC1 TO LNC3 

LNC1 CONVERSION FROM LNC1 TO LNC3 

LNC2 CONVERSION FROM LNC2 TO LNC3 

OFA LNC1 

Tangential 

ROFA LNB 

Vertical -- NOx Combustion Control - Vertically Fired Units 

-- LNB AND OFA 

LA LNB AND OFA 

LNB OFA 

LNF OFA 

Wall 

OFA LNB 

5.2.2 Post-combustion Controls 

The EPA Base Case v.4.10 includes two post-combustion retrofit control technologies for existing 

coal units: Selective Catalytic Reduction (SCR) and Selective Non-Catalytic Reduction (SNCR). In 

EPA Base Case v.4.10 oil/gas steam units are eligible for SCR only. NOx reduction in an SCR 

system takes place by injecting ammonia (NH3) vapor into the flue gas stream where the NOx is 

reduced to nitrogen (N2) and water H2O abetted by passing over a catalyst bed typically 

containing titanium, vanadium oxides, molybdenum, and/or tungsten. As its name implies, SNCR 

operates without a catalyst. In SNCR a nitrogenous reducing agent (reagent), typically ammonia 

or urea, is injected into, and mixed with, hot flue gas where it reacts with the NOx in the gas 

stream reducing it to nitrogen gas and water vapor. Due to the presence of a catalyst, SCR can 

achieve greater NOx reductions than SNCR. However, SCR costs are higher. 

Table 5-7 summarizes the performance and applicability assumptions in EPA Base Case v.4.10 

for each NOx post-combustion control technology and provides a cross reference to information on 

cost assumptions. 

Table 5-7 Summary of Retrofit NOx Emission Control Performance Assumptions 

Control 

Performance 

Assumptions 

Selective Catalytic Reduction 

(SCR) 

Selective Non-Catalytic 

Reduction 

(SNCR) 

Unit Type Coal Oil/Gas Coal 

Pulverized Coal: 35% Percent Removal 90% down to 0.06 

lb/MMBtu 80% Fluidized Bed: 50% 

Size Applicability Units ≥ 25 MW Units ≥ 25 MW Units ≥ 25 MW 

Costs (2007$) See Table 5-8 See Table 5-9 See Table 5-8 
5-9 

Potential (new) coal-fired, combined cycle, and IGCC units are modeled to be constructed with 

SCR systems and designed to have emission rates ranging between 0.01 and 0.06 lb 

NOx/MMBtu. EPA Base Case v.4.10 cost assumptions for these units include the cost of SCR 

5.2.3 Methodology for Obtaining SCR Costs for Coal Units 

As with the update of SO2 control costs, Sargent and Lundy employed an engineering build-up of 

the capital, fixed and variable operating and maintenance components of cost to update postcombustion NOx control costs. This section describes the approach used for SCR. The next 

section treats SNCR. Detailed example cost calculation spreadsheets for both technologies can 

be found in Appendix 5-2. 

For cost calculation purposes the Sargent and Lundy methodology calculates plant specific NOx

removal efficiencies, i.e., the percent difference between the uncontrolled NOx rate29 for a model 

plant and the cost calculation floor NOx rate corresponding to the predominant coal rank used at 

the plant ( 0.07 lb/MMBtu for bituminous and 0.05 lb/MMBtu for subbitumionus and lignite coals). 

For example, a plant that burns subbitumionus coal with an uncontrolled NOx rate of 0.1667 

lb/MMBtu, and a cost calculation floor NOx rate of 0.05 lb/MMBtu would have a removal efficiency 

of 70%, i.e., (0.1667 – 0.05)/0.1667 = 0.1167/0.1667 = .70. The NOx removal efficiency so 

obtained figures in the capital, VOM, and FOM components of SCR cost. 

Capital Costs: In building up SCR capital costs, four separate cost modules were included: SCR 

island (e.g., inlet ductwork, reactor, and bypass), reagent preparation, air pre-heater modification, 

and balance of plan (e.g., ID or booster fans, piping, and auxiliary power modification). Air preheater modification cost only applies for plants that burn bituminous coal whose SO2 content is 3 

lbs/MMBtu or greater, where SO3 control is necessary. Otherwise, there is no air pre-heat cost. 

For each of the four modules the cost of foundations, buildings, electrical equipment, installation, 

and average retrofit difficulty were taken into account. 

The governing cost variables for each module are indicated in Table 5-3. All four capital cost 

modules, except reagent preparation, are functions of retrofit difficulty, coal rank, heat rate, and 

unit size. NOx rate (expressed via the NOx removal efficiency) affects the SCR and reagent 

preparation cost modules. Not shown in Table 5-3, heat input (in Btu/hr) also impacts reagent 

preparation costs. As noted above, the SO2 rate becomes a factor in SCR cost for plants that 

combust bituminous coal with 3 lbs SO2/MMBtu or greater, where air pre-heater modifications are 

needed for SO3 control. 

As with FGD capital costs, the base module costs for SCR are summed to obtain total bare 

module costs. This total is increased by 30% to account for additional engineering and 

construction fees. The resulting value is the capital, engineering, and construction cost (CECC) 

subtotal. To obtain the total project cost (TPC) the CECC subtotal is increased by 5% to account 

for owner’s home office costs, i.e., owner’s engineering, management, and procurement costs. 

Whereas the resulting sum is then increased by another 10% for FGD, for SCR it is increased by 

6% to factor in an Allowance for Funds used During Construction (AFUDC) over the 2-year 

engineering and construction cycle (in contrast to the 3-year cycle assumed for FGD). The 

resulting value, expressed in $/MW, is the capital cost factor that is used in EPA Base Case 

v.4.10. 

Variable Operating and Maintenance Costs (VOM): For SCR Sargent and Lundy identified four 

components of VOM: (a) costs for the urea reagent, (b) costs of catalyst replacement and 

disposal, (c) cost of required steam, and (d) cost of additional power required to run the control 

 

29 More precisely, the uncontrolled NOX rate for a model plant in EPA Base Case v.4.10 is the 

capacity weighted average of the Mode 1 NOX rates of the generating units comprising the model 

plant. The meaning of “Mode 1 NOX rate” is discussed in section 3.9.2 and Appendix 3-1 (“NOX

Rate Development in EPA Base Case v.4.10). 
5-10 

(i.e., the “parasitic load”). As was the case for FGD, the last component – cost of additional power 

– is factored into IPM, not in the VOM value, but through a capacity and heat rate penalty as 

described earlier. Of the first three of these component costs, reagent cost and catalyst 

replacement are predominant while steam cost is much lower in magnitude. NOx rates and heat 

rates are key determinates of reagent and steam costs, while NOx rate (via removal efficiency), 

capacity factor, and coal rank are key drivers of catalyst replacement costs. 

Capacity and Heat Rate Penalty: 

Unlike previous base cases, which assumed a generic heat rate and capacity penalties for all 

installations, in EPA Base Case v.4.10 specific SCR heat rate and capacity penalties are 

calculated for each installation based on equations developed by Sargent and Lundy that take into 

account the rank of coal burned, its SO2 rate, and the heat rate of the model plant. 

Fixed Operating and Maintenance Costs (FOM): For SCR the following assumptions were made: 

• FOM for operations is based on the assumption that one additional operator working half-time 

is required. 

• FOM for maintenance is assumed to $193,585 (in 2007$) for generating units less than 500 

MW and $290,377 (in 2007$) for generating units 500 MW or greater 

• There was assumed to be no FOM for administration for SCR. 

Table 5-8 presents the SCR and SNCR capital, VOM, and FOM costs and capacity and heat rate 

penalties for an illustrative set of coal generating units with a representative range of capacities, 

heat rates, and NOx removal efficiencies. The illustrations include and identify plants that do and 

do not burn bituminous coal with 3 lbs SO2/MMBtu or greater. 
5-11 

Table 5-8 Illustrative Post Combustion NOX Controls for Coal Plants Costs (2007$) for Representative Sizes and H

Assu Assumptions in EPA Base Case v.4.10 

Capacity (MW) 

100 300 500 700 

Control Type Heat Rate (Btu/kWh) Capacity Penalty (%) Heat Rate Penalty (%) Variable O&M (mills/kWh) Capital Cost 

($/kW) 

Fixed 

O&M 

($/kWyr) 

Capital 

Cost 

($/kW) 

Fixed 

O&M 

($/kWyr) 

Capital 

Cost 

($/kW) 

Fixed 

O&M 

($/kWyr) 

Capital 

Cost 

($/kW) 

F

(

SCR Minimum Cutoff: ≥ 25 MW 

9,000 -0.54 0.54 1.15 221 2.5 177 0.8 163 0.7 155 

Maximum Cutoff: None Assuming Bituminous Coal 10,000 -0.56 0.56 1.24 240 2.5 193 0.8 178 0.7 169 NOx rate: 0.5 lb/MMBtu SO2 rate: 2.0 lb/MMBtu 

11,000 -0.58 0.59 1.33 258 2.5 209 0.8 193 0.7 184 

SNCR - Non-FBC Minimum Cutoff: ≥ 25 MW 

9,000 0.88 45 1 

Maximum Cutoff: None Assuming Bituminous Coal 

10,000 0.98 47 1 

NOx rate: 0.5 lb/MMBtu SO2 rate: 2.0 lb/MMBtu 

11,000 

-0.05 0.05 

1.08 48 1 

Size Not Modeled 

SNCR - Fluidized Bed Minimum Cutoff: ≥ 25 MW 

9,000 0.88 34 0.9 18 0.4 14 0.2 11 

Maximum Cutoff: None Assuming Bituminous Coal 10,000 0.98 35 0.9 19 0.4 14 0.2 12 NOx rate: 0.5 lb/MMBtu SO2 rate: 2.0 lb/MMBtu 11,000 

-0.05 0.05 

1.08 36 0.9 19 0.4 14 0.2 12 

Note:If a coal plant burns bituminous coal with a SO2 content above 3.0 lb/MMBtu then the capital costs will increase due to the required air preheater modificaMW coal boiler with an SCR burning bituminous coal at a heat rate of 11,000 Btu/kWh and an SO2 rate of 4.0 lb/MMBtu will have a capital cost of 296 $/kWcapital costs from an identical boiler burning coal with an SO2 rate of 2.0 lb/MMBtu. 
5-12 

5.2.4 Methodology for Obtaining SCR Costs for Oil/Gas Steam units 

The cost calculations for SCR described in section 5.2.3 apply to coal units. For SCR on oil/gas 

steam units the cost calculation procedure employed in EPA’s most recent previous base case 

was used. However, capital costs were scaled up by 2.13 to account for increases in the 

component costs that had occurred since the assumptions were incorporated in that base case. 

All costs were expressed in constant 2007$ for consistency with the dollar year cost basis used 

throughout EPA Base Case v4.10. Table 5-9 shows that resulting capital, FOM, and VOM cost 

assumptions for SCR on oil/gas steam units. The scaling factor for capital and fixed operating and 

maintenance costs, described in footnote 1, applies to all size units from 25 MW and up. 

Table 5-9 Post-Combustion NOX Controls for Oil/Gas Steam Units in EPA Base Case v.4.10 

Post-Combustion 

Control Technology 

Capital 

($/kW) 

Fixed O&M 

($/kW-yr) 

Variable O&M

(mills/kWh) 

Percent 

Removal 

SCR1 75 1.08 0.12 80% 

Notes:

The “Coefficients” in the table above are multiplied by the terms below to determine costs. 

“MW” in the terms below is the unit’s capacity in megawatts. 

This data is used in the generation of EPA Base Case v.4.0 

1 SCR Cost Equations:

SCR Capital Cost and Fixed O&M: (200/MW)0.35

The scaling factors shown above apply up to 500 MW. The cost obtained for a 500 MW 

unit applies for units larger than 500 MW. 

Example for 275 MW unit:

SCR Capital Cost ($/kW) = 75 * (200/275)0.35 ≈ 67 $/kW 

SCR FOM Cost ($/kW-yr) = 1.08 * (200/275)0.35 ≈ 0.97 $/kW-yr 

SCR VOM Cost (mills/kWh) = 0.12 mills/kWh 

Reference:

Cost Estimates for Selected Applications of NOX Control Technologies on Stationary 

Combustion Boilers, Bechtel Power Corporation for US EPA, June 1997

5.2.5 Methodology for Obtaining SNCR Costs 

In the Sargent and Lundy cost update for SNCR a generic NOX removal efficiency of 25% is 

assumed. However, the capital, fixed and variable operating and maintenance costs of SNCR on 

circulating fluidized bed (CFB) units are distinguished from the corresponding costs for other boiler 

types (e.g. cyclone, and wall fired). 

Capital Costs: Due to the absence of a catalyst and, with it, the elimination of the need for more 

extensive reagent preparation, the Sargent and Lundy engineering build up of SNCR capital costs 

includes three rather than four separate cost modules: SNCR (injectors, blowers, distributive 

control system, reagent system), air pre-heater modification, and balance of plan (e.g., ID or 

booster fans, piping, and auxiliary power modification). For CFB units, the SNCR and balance of 

plan module costs are 75% of what they are on other boiler types. The air pre-heater modification 

cost module is the same as for SCR and there is no cost difference between CFB and other boiler 

types. As with SCR the air heater modification cost only applies for plants that burn bituminous 

coal whose SO2 content is 3 lbs/MMBtu or greater, where SO3 control is necessary. Otherwise, 

there is no air pre-heat cost. For each of the three modules the cost of foundations, buildings, 

electrical equipment, installation, and average retrofit difficulty were taken into account. 

The governing cost variables for each module are indicated in Table 5-3. Unit size affects all 

three modules. Retrofit difficulty, coal rank, and heat rate impact the SNCR and air heater 

modification modules. The SO2 rate impacts the air pre-heater modification module. NOX rate 
5-13 

(expressed via the NOX removal efficiency) and heat input (not shown in Table 5-3) affect the 

balance of plan module. 

The base module costs for SNCR are summed to obtain total bare module costs. This total is 

increased by 30% to account for additional engineering and construction fees. The resulting value 

is the capital, engineering, and construction cost (CECC) subtotal. To obtain the total project cost 

(TPC) the CECC subtotal is increased by 5% to account for owner’s home office costs, i.e., 

owner’s engineering, management, and procurement costs. Since SNCR projects are typically 

completed in less than a year, there is no Allowance for Funds used During Construction 

(AFUDC) in the SNCR capital cost factor that is used in EPA Base Case v.4.10. 

Variable Operating and Maintenance Costs (VOM): Sargent and Lundy identified two components 

of VOM for SNCR: (a) cost for the urea reagent and (b) the cost of dilution water. The magnitude 

of the reagent cost predominates the VOM with the cost of dilution water at times near zero. 

There is no capacity or heat rate penalty associated with SNCR since the only impact on power 

are compressed air or blower required for urea injection and the reagent supply system. 

Capacity and Heat Rate Penalty: 

Unlike previous base cases, which assumed a generic heat rate and capacity penalties for all 

installations, in EPA Base Case v.4.10 specific SNCR heat rate and capacity penalties are 

calculated for each installation based on equations developed by Sargent and Lundy that take into 

account the rank of coal burned, its SO2 rate, and the heat rate of the model plant. 

Fixed Operating and Maintenance Costs (FOM): The assumptions for FOM for operations and 

for administration are the same for SNCR as for SCR, i.e., 

• FOM for operations is based on the assumption that one additional operator working half-time 

is required. 

• There was assumed to be no FOM for administration for SCR. 

FOM for maintenance materials and labor was assumed to be a direct function of base module 

cost, specifically, 1.2% of those costs divided by the capacity of the generating unit expressed in 

kilowatts. 

Detailed example cost calculation spreadsheets for SNCR can be found in Appendix 5-2. 

5.2.6 SO2 and NOx Controls for Units with Capacities from 25 MW to 100 MW (25 M ≤

capacity < 100 MW) 

In EPA Base Case v.4.10 coal units with capacities between 25 MW and 100 MW are offered the 

same SO2 and NOx emission control options as larger units. However, for purposes of modeling, 

the costs of controls for these units are assumed to be equivalent to that of a 100 MW unit. This 

assumption is based on several considerations. First, to achieve economies of scale, several 

units in this size range are likely to be ducted to share a single common control, so the 100 MW 

cost equivalency assumption, though generic, would be technically plausible. Second, single units 

in this size range that are not grouped to achieve economies of scale are likely to have the option 

of hybrid multi-pollutant controls currently under development.30 These hybrid controls achieve 

cost economies by combining SO2, NOX and particulate controls into a single control unit. Singly, 

the costs of the individual control would be higher for units below 100 MW than for a 100 MW unit, 

 

30 See, for example, the Greenidge Multi-Pollutant Control Project, which was part of the U.S. 

Department of Energy, National Energy Technology Lab’s Power Plant Improvement Initiative. A 

joint effort of CONSOL Energy Inc. AES Greenidge LLC, and Babcock Power Environmental, Inc., 

information on the project can be found at 

www.netl.doe.gov/technologies/coalpower/cctc/PPII/bibliography/demonstration/environmental/bib

_greenidge.html. 
5-14 

but when combined in the Multi-Pollutant Technologies (MPTs) their costs would be roughly 

equivalent to the cost of individual controls on a 100 MW unit. While MPTs are not explicitly 

represented in EPA Base Case v.4.10, single units in the 25-100 MW range that take on 

combinations of SO2 and NOX controls in a model run can be thought of as being retrofit with an 

MPT. 

Illustrative scrubber, SCR, and SNCR costs for 25-100 MW coal units with a range heats rates 

can be found by referring to the 100 MW “Capital Costs ($/kW)” and “Fixed O&M” columns in 

Table 5-4 and Table 5-8. The Variable O&M cost component, which applies to units regardless of 

size, can be found in the fifth column in these tables. 

5.3 Biomass Co-firing 

Under most climate policies currently being discussed, biomass is treated as “carbon neutral,” i.e., 

a zero contributor of CO2 to the atmosphere. The reasoning is that the CO2 emitted in the 

combustion of biomass will be reabsorbed via photosynthesis in plants grown to replace the 

biomass that was combusted. Consequently, if a power plant can co-fire biomass and thereby 

replace a portion of fossil fuel, it reduces its CO2 emissions by approximately the same proportion, 

although combustion efficiency losses may somewhat diminish the proportion of CO2 reduction. 

Roughly speaking, by co-firing enough biomass to produce 10% of a coal plant’s power output, a 

co-fired plant can realize close to an effective 10% reduction in CO2 emitted. 

Biomass co-firing is provided as a fuel choice for all coal-fired power plants in EPA Base Case 

v.4.10. However, logistics and boiler engineering considerations place limits on the extent of 

biomass that can be fired. The logistic considerations arise because it is only economic to 

transport biomass a limited distance from where it is grown. In addition, the extent of storage that 

can be devoted at a power plant to this relatively low density fuel is another limiting factor. Boiler 

efficiency and other engineering considerations, largely due to the relatively higher moisture 

content and lower heat content of biomass compared to fossil fuel, also plays a role in limiting the 

level of co-firing. 

In EPA Base Case v.4.10 the limit on biomass co-firing is expressed as the percentage of the 

facility level power output that is produced from biomass. Based on analysis by EPA’s power 

sector engineering staff, a maximum of 10% of the facility level power output (not to exceed 50 

MW) can be fired by biomass. In EPA Base Case v.4.10 “facility level” is defined as the set of 

generating units which share the same ORIS code31 in NEEDS v.4.10. 

The capital and FOM costs associated with biomass co-firing are summarized in Table 5-10. 

Developed by EPA’s power sector engineering staff32, they are on the same cost basis as the 

 

31 The ORIS plant locator code is a unique identifying number (originally assigned by the Office of 

Regulatory Information Systems from which the acronym derived). The ORIS code is given to 

power plants by EIA and remains unchanged under ownership changes. 

32 Among the studies consulted in developing these costs were: 

(a) Briggs, J. and J. M. Adams, Biomass Combustion Options for Steam Generation, Presented at 

Power-Gen 97, Dallas, TX, December 9 – 11, 1997. 

(b) Grusha, J and S. Woldehanna, K. McCarthy, and G. Heinz, Long Term Results from the First 

US Low NOx Conversion of a Tangential Lignite Fired Unit, presented at 24th International 

Technical Conference on Coal & Fuel Systems, Clearwater, FL., March 8 – 11, 1999. 

(c) EPRI, Biomass Cofiring: Field Test Results: Summary of Results of the Bailly and Seward 

Demonstrations, Palo Alto, CA, supported by U.S. Department of Energy Division of Energy 

Efficiency and Renewable Energy, Washington D.C.; U.S. Department of Energy Division Federal 

Energy Technology Center, Pittsburgh PA; Northern Indiana Public Service Company, Merrillville, 

IN; and GPU Generation, Inc., Johnstown, PA: 1999. TR-113903. 

(d) Laux S., J. Grusha, and D. Tillman, Co-firing of Biomass and Opportunity Fuels in Low NOx 
5-15 

costs shown in Table 4-16 which resulted from EPA’s comparative analysis of electricity sector 

costs as described in Chapter 4. 

Table 5-10 Biomass Cofiring for Coal Plants 

Size of Biomass Unit (MW) 5 10 15 20 25 30 35 40 45 50 

Capital Cost (2007$/kW From Biomass) 488 411 371 345 327 312 300 290 282 275 

Fixed O&M (2007$/kW-yr) 24.2 16.2 11.7 9.4 8.0 11.1 9.9 8.9 8.1 7.5 

The capital and FOM costs were implemented by ICF in EPA Base Case v.4.10 as a $/MMBtu 

biomass fuel cost adder. The procedure followed to implement this was first to represent the 

discrete costs shown in Table 5-10 as continuous exponential cost functions showing the FOM 

and capital costs for all size coal generating units between 0 and 50 MW in size. Then, for every 

coal generating unit represented in EPA Base Case 4.10, the annual payment to capital for the 

biomass co-firing capability was derived by multiplying the total capital cost obtained from the 

capital cost exponential function by an 11% capital charge rate. (This is the capital charge rate for 

environmental retrofits found in Table 8-1 and discussed in Chapter 8.) The resulting value was 

added to the annual FOM cost obtained from the FOM exponential function to obtain the total 

annual cost for the biomass co-firing for each generating unit. 

Then, the annual amount of fuel (in MMBtus) required for each generating unit was derived by 

multiplying the size of a unit (in MW) by its heat rate (in Btu/kWh) by its capacity factor (in percent) 

by 8,760 hours (i.e., the number of hours in a year). Dividing the resulting value by 1000 yielded 

the annual fuel required by the generating unit in MMBtus. Dividing this number into the previously 

calculated total annual cost for biomass co-firing resulted in the cost of biomass co-firing per 

MMBtu of biomass combusted. This was represented in IPM as a fuel cost adder incurred when a 

coal units co-fires biomass. 

5.4 Mercury Control Technologies 

As previously noted, the mercury emission controls options and assumptions in EPA Base Case 

v.4.10 do not reflect mercury control updates that are currently under way at EPA in support of the 

Utility MACT initiative and do not make use of data collected under EPA’s 2010 Information 

Collection Request (ICR). The following discussion is based on EPA’s earlier work on mercury 

controls. 

For any power plant, mercury emissions depend on the mercury content of the fuel used, the 

combustion and physical characteristics of the unit, and the emission control technologies 

deployed. In the absence of emission policies that would require the installation of mercury 

emission controls, mercury emission reductions below the mercury content of the fuel are strictly 

due to characteristics of the combustion process and incidental removal resulting from nonmercury control technologies, i.e., the SO2, NOX, and particulate controls. While the base case 

itself does not include any federal mercury control policies, it does include some State mercury 

reduction requirements. IPM has the capability to model mercury controls that might be installed 

in response to such State mercury control policies. These same controls come into play in model 

runs that analyze possible federal mercury policies relative to the base case. The technology 

specifically designated for mercury control in such policy runs is Activated Carbon Injection (ACI) 

downstream of the combustion process. 

 Burners, PowerGen 2000 - Orlando, FL, 

www.fwc.com/publications/tech_papers/powgen/pdfs/clrw_bio.pdf. 

Tillman, D. A., Cofiring Biomass for Greenhouse Gas Mitigation, presented at Power-Gen 99, New 

Orleans, LA, November 30 – December 1, 1999. 

(e) Tillman, D. A. and P. Hus, Blending Opportunity Fuels with Coal for Efficiency and 

Environmental Benefit, presented at 25th International Technical Conference on Coal Utilization & 

Fuel Systems, Clearwater, FL., March 6 – 9, 2000 
5-16 

The following discussion is divided into three parts. Sections 5.4.1 and 5.4.2 treat the two factors 

that figure into the unregulated mercury emissions resulting under EPA Base Case v.4.10. 

Section 5.4.1 discusses how mercury content of fuel is modeled in EPA Base Case v.4.10. 

Section 5.4.2 looks at the procedure used in the base case to capture the mercury reductions 

resulting from different unit and (non-mercury) control configurations. Section 5.4.3 explains the 

mercury emission control options that are available under EPA Base Case v.4.10. A major focus 

is on the cost and performance features of Activated Carbon Injection. Each section indicates the 

data sources and methodology used. 

5.4.1 Mercury Content of Fuels 

Coal: The assumptions in EPA Base Case v.4.10 on the mercury content of coal (and the majority 

of emission modification factors discussed below in Section 5.4.2) are derived from EPA’s 

“Information Collection Request for Electric Utility Steam Generating Unit Mercury Emissions 

Information Collection Effort” (ICR).33 A two-year effort initiated in 1998 and completed in 2000, 

the ICR had three main components: (1) identifying all coal-fired units owned and operated by 

publicly-owned utility companies, Federal power agencies, rural electric cooperatives, and 

investor-owned utility generating companies, (2) obtaining “accurate information on the amount of 

mercury contained in the as-fired coal used by each electric utility steam generating unit . . . with 

a capacity greater than 25 megawatts electric [MWe]), as well as accurate information on the total 

amount of coal burned by each such unit,” and (3) obtaining data by coal sampling and stack 

testing at selected units to characterize mercury reductions from representative unit 

configurations. 

The ICR second component resulted in more than 40,000 data points indicating the coal type, 

sulfur content, mercury content and other characteristics of coal burned at coal-fired utility units 

greater than 25 MW. To make this data usable in EPA Base Case v.4.10, these data points were 

first grouped by IPM coal types and IPM coal supply regions. (IPM coal types divide bituminous, 

sub-bituminous, and lignite coal into different grades based on sulfur content. See Table 5-11.) 

Next, a clustering analysis was performed on the data using the SAS statistical software package. 

Clustering analysis places objects into groups or clusters, such that data in a given cluster tend to 

be similar to each other and dissimilar to data in other clusters. The clustering analysis involved 

two steps. First, the number of clusters of mercury concentrations for each IPM coal type was 

determined based on the range of mercury and SO2 concentrations for that coal type. Each coal 

type used one, two or three clusters. To the greatest extent possible the total number of clusters 

for each coal type was limited to keep the model size and run time within feasible limits. Second, 

the clustering procedure was used to group each coal type within each IPM coal supply region into 

the previously determined number of clusters and show the resulting mercury concentration for 

each cluster. The average of each cluster is the mercury content of coal finally used in EPA Base 

Case v.4.10 for estimating mercury emissions. IPM input files retain the mapping between 

different coal type-supply region combinations and the mercury clusters. Table 5-11 below 

provides a summary by coal type of the number of clusters and their mercury concentrations. 

 

33Data from the ICR can be found at http://www.epa.gov/ttn/atw/combust/utiltox/mercury.html. 
5-17 

Table 5-11 Mercury Clusters and Mercury Content of Coal by IPM Coal Types 

Mercury Emission Factors by Coal Sulfur 

Coal Type by Sulfur Grade Grades (lbs/TBtu) 

Cluster #1 Cluster #2 Cluster #3 

Low Sulfur Easter Bituminous (BA) 3.19 4.37 -- 

Low Sulfur Western Bituminous (BB) 1.82 4.86 -- 

Low Medium Sulfur Bituminous (BD) 5.38 8.94 21.67 

Medium Sulfur Bituminous (BE) 19.53 8.42 -- 

High Sulfur Bituminous (BG) 7.10 20.04 14.31 

High Sulfur Bituminous (BH) 7.38 13.93 34.71 

Low Sulfur Subbituminous (SA) 4.24 5.61 -- 

Low Sulfur Subbituminous (SB) 6.44 -- -- 

Low Medium Sulfur Subbituminous (SD) 4.43 -- -- 

Low Medium Sulfur Lignite (LD) 7.51 12.00 -- 

Medium Sulfur Lignite (LE) 13.55 7.81 -- 

High Sulfur Lignite (LG) 14.88 -- -- 

Oil, natural gas, and waste fuels: The EPA Base Case v.4.10 also includes assumptions on the 

mercury content for oil, gas and waste fuels, which were based on data derived from previous 

EPA analysis of mercury emissions from power plants.34 Table 5-12 provides a summary of the 

assumptions on the mercury content for oil, gas and waste fuels included in EPA Base Case 

v.4.10. 

Table 5-12 Assumptions on Mercury Concentration in Non-Coal Fuel in EPA Base Case 

v.4.10 

Fuel Type Mercury Concentration (lbs/TBtu) 

Oil 0.48 

Natural Gas 0.001

Petroleum Coke 23.18 

Biomass 0.57 

Municipal Solid 

Waste 71.85 

Geothermal 

Resource 2.97 - 3.7 

Note:

1

The values appearing in this table are rounded to two 

decimal places. The zero value shown for natural gas is 

based on an EPA study that found a mercury content of 

0.00014 lbs/TBtu. Values for geothermal resources 

represent a range. 

5.4.2 Mercury Emission Modification Factors 

Emission Modification Factors (EMFs) represent the mercury reductions attributable to the specific 

burner type and configuration of SO2, NOX, and particulate matter control devices at an electric 

generating unit. An EMF is the ratio of outlet mercury concentration to inlet mercury 

concentration, and depends on the unit's burner type, particulate control device, post-combustion 

NOX control and SO2 scrubber control. In other words, the mercury reduction achieved (relative to 

 

34“Analysis of Emission Reduction Options for the Electric Power Industry,” Office of Air and 

Radiation, US EPA, March 1999. 
5-18 

the inlet) during combustion and flue-gas treatment process is (1-EMF). The EMF varies by the 

type of coal (bituminous, sub-bituminous, and lignite) used during the combustion process. 

Deriving EMFs involves obtaining mercury inlet data by coal sampling and mercury emission data 

by stack testing at a representation set of coal units. As noted above, EPA's EMFs were initially 

based on 1999 mercury ICR emission test data. More recent testing conducted by the EPA, DOE, 

and industry participants35 has provided a better understanding of mercury emissions from electric 

generating units and mercury capture in pollution control devices. Overall the 1999 ICR data 

revealed higher levels of mercury capture for bituminous coal-fired plants than for subbitumionus 

and lignite coal-fired plants, and significant capture of ionic Hg in wet-FGD scrubbers. Additional 

mercury testing indicates that for bituminous coals, SCR systems have the ability to convert 

elemental Hg into ionic Hg and thus allow easier capture in a downstream wet-FGD scrubber. 

This improved understanding of mercury capture with SCRs was incorporated in EPA Base Case 

v.4.10 mercury EMFs for unit configurations with SCR and wet scrubbers. 

Table 5-13 below provides a summary of EMFs used in EPA Base Case v.4.10. Table 5-14 

provides definitions of acronyms for existing controls that appear in Table 5-13. Table 5-15 

provides a key to the burner type designations appearing in Table 5-13. 

5.4.3 Mercury Control Capabilities 

EPA Base Case v.4.10 offers two options for meeting mercury reduction requirements: (1) 

combinations of SO2, NOX, and particulate controls which deliver mercury reductions as a cobenefit and (2) Activated Carbon Injection (ACI), a retrofit option specifically designed for mercury 

control. These two options are discussed below. 

 

35 For a detailed summary of emissions test data see Control of Emissions from Coal-Fired 

Electric Utility Boilers: An Update, EPA/Office of Research and Development, February 2005. 

This report can be found at www.epa.gov/ttnatw01/utility/hgwhitepaperfinal.pdf . 
5-19 

Table 5-13 Mercury Emission Modification Factors Used in EPA Base Case v.4.10 

Burner 

Type Particulate Control 

Post 

Combustion 

Control – 

NOX

Post 

Combustion 

Control - 

SO2

Bituminous 

EMF 

Subbitumionus 

EMF 

Lignite 

EMF 

Cyclone Cold Side ESP SNCR None 0.64 0.97 0.93 

Cyclone Cold Side ESP SNCR Wet FGD 0.46 0.84 0.58 

Cyclone Cold Side ESP SNCR Dry FGD 0.64 0.65 0.93 

Cyclone Cold Side ESP SCR None 0.64 0.97 0.93 

Cyclone Cold Side ESP SCR Wet FGD 0.1 0.84 0.58 

Cyclone Cold Side ESP SCR Dry FGD 0.64 0.65 0.93 

Cyclone Cold Side ESP None Wet FGD 0.46 0.84 0.58 

Cyclone Cold Side ESP None Dry FGD 0.64 0.65 0.93 

Cyclone Cold Side ESP None None 0.64 0.97 0.93 

Cyclone Cold Side ESP + FF SNCR Wet FGD 0.1 0.27 0.58 

Cyclone Cold Side ESP + FF SCR None 0.11 0.27 1 

Cyclone Cold Side ESP + FF SCR Wet FGD 0.1 0.27 0.58 

Cyclone Cold Side ESP + FF SCR Dry FGD 0.4 0.95 0.91 

Cyclone Cold Side ESP + FF None Wet FGD 0.1 0.27 0.58 

Cyclone Cold Side ESP + FF None Dry FGD 0.4 0.95 0.91 

Cyclone Cold Side ESP + FF None None 0.11 0.27 1 

Cyclone Cold Side ESP + FGC SNCR None 0.64 0.97 0.93 

Cyclone Cold Side ESP + FGC SNCR Wet FGD 0.46 0.84 0.58 

Cyclone Cold Side ESP + FGC SNCR Dry FGD 0.64 0.65 0.93 

Cyclone Cold Side ESP + FGC SCR None 0.64 0.97 0.93 

Cyclone Cold Side ESP + FGC SCR Wet FGD 0.1 0.84 0.58 

Cyclone Cold Side ESP + FGC SCR Dry FGD 0.64 0.65 0.93 

Cyclone Cold Side ESP + FGC None Wet FGD 0.46 0.84 0.58 

Cyclone Cold Side ESP + FGC None Dry FGD 0.64 0.65 0.93 

Cyclone Cold Side ESP + FGC None None 0.64 0.97 0.93 

Cyclone Cold Side ESP + FGC + FF SCR None 0.11 0.27 1 

Cyclone Cold Side ESP + FGC + FF SCR Wet FGD 0.1 0.27 0.58 

Cyclone Cold Side ESP + FGC + FF SCR Dry FGD 0.4 0.95 0.91 

Cyclone Cold Side ESP + FGC + FF None Wet FGD 0.1 0.27 0.58 

Cyclone Cold Side ESP + FGC + FF None Dry FGD 0.4 0.95 0.91 

Cyclone Cold Side ESP + FGC + FF None None 0.11 0.27 1 

Cyclone Fabric Filter SNCR None 0.11 0.27 1 

Cyclone Fabric Filter SNCR Wet FGD 0.03 0.27 0.58 

Cyclone Fabric Filter SNCR Dry FGD 0.4 0.95 0.91 

Cyclone Fabric Filter SCR None 0.11 0.27 1 

Cyclone Fabric Filter SCR Wet FGD 0.1 0.27 0.58 

Cyclone Fabric Filter SCR Dry FGD 0.4 0.95 0.91 

Cyclone Fabric Filter None Wet FGD 0.1 0.27 0.58 

Cyclone Fabric Filter None Dry FGD 0.4 0.95 0.91 

Cyclone Fabric Filter None None 0.11 0.27 1 

Cyclone Hot Side ESP SNCR None 0.9 1 1 

Cyclone Hot Side ESP SNCR Wet FGD 0.58 0.6 1 

Cyclone Hot Side ESP SNCR Dry FGD 0.9 1 1 

Cyclone Hot Side ESP SCR None 0.9 1 1 

Cyclone Hot Side ESP SCR Wet FGD 0.1 0.8 1 

Cyclone Hot Side ESP SCR Dry FGD 0.9 1 1 
5-20 

Burner 

Type Particulate Control 

Post 

Combustion 

Control – 

NOX

Post 

Combustion 

Control - 

SO2

Bituminous 

EMF 

Subbitumionus 

EMF 

Lignite 

EMF 

Cyclone Hot Side ESP None Wet FGD 0.58 0.6 1 

Cyclone Hot Side ESP None Dry FGD 0.9 1 1 

Cyclone Hot Side ESP None None 0.9 1 1 

Cyclone Hot Side ESP + FF None None 0.11 0.27 1 

Cyclone Hot Side ESP + FGC SNCR None 0.9 1 1 

Cyclone Hot Side ESP + FGC SNCR Wet FGD 0.58 0.6 1 

Cyclone Hot Side ESP + FGC SNCR Dry FGD 0.9 1 1 

Cyclone Hot Side ESP + FGC SCR None 0.9 1 1 

Cyclone Hot Side ESP + FGC SCR Wet FGD 0.1 0.8 1 

Cyclone Hot Side ESP + FGC SCR Dry FGD 0.9 1 1 

Cyclone Hot Side ESP + FGC None Wet FGD 0.58 0.6 1 

Cyclone Hot Side ESP + FGC None Dry FGD 0.9 1 1 

Cyclone Hot Side ESP + FGC None None 0.9 1 1 

Cyclone No Control SNCR None 1 1 1 

Cyclone No Control SNCR Wet FGD 0.45 0.6 1 

Cyclone No Control SNCR Dry FGD 1 1 1 

Cyclone No Control SCR None 1 1 1 

Cyclone No Control SCR Wet FGD 0.1 0.7 1 

Cyclone No Control SCR Dry FGD 1 1 1 

Cyclone No Control None Wet FGD 0.45 0.6 1 

Cyclone No Control None Dry FGD 1 1 1 

Cyclone No Control None None 1 1 1 

Cyclone PM Scrubber None None 0.8 1 1 

FBC Cold Side ESP SNCR None 0.65 0.65 0.62 

FBC Cold Side ESP SNCR Wet FGD 0.65 0.65 0.62 

FBC Cold Side ESP SCR Wet FGD 0.1 0.84 0.62 

FBC Cold Side ESP None Wet FGD 0.65 0.65 0.62 

FBC Cold Side ESP None Dry FGD 0.45 0.45 1 

FBC Cold Side ESP None None 0.65 0.65 0.62 

FBC Cold Side ESP + FF SNCR None 0.05 0.43 0.43 

FBC Cold Side ESP + FF SNCR Dry FGD 0.05 0.43 0.43 

FBC Cold Side ESP + FF None Dry FGD 0.05 0.43 0.43 

FBC Cold Side ESP + FF None None 0.05 0.43 0.43 

FBC Cold Side ESP + FGC SNCR None 0.65 0.65 0.62 

FBC Cold Side ESP + FGC SNCR Wet FGD 0.65 0.65 0.62 

FBC Cold Side ESP + FGC SCR Wet FGD 0.1 0.84 0.62 

FBC Cold Side ESP + FGC None Wet FGD 0.65 0.65 0.62 

FBC Cold Side ESP + FGC None Dry FGD 0.45 0.45 1 

FBC Cold Side ESP + FGC None None 0.65 0.65 0.62 

FBC Cold Side ESP + FGC + FF SNCR None 0.05 0.43 0.43 

FBC Cold Side ESP + FGC + FF SNCR Dry FGD 0.05 0.43 0.43 

FBC Cold Side ESP + FGC + FF None Dry FGD 0.05 0.43 0.43 

FBC Cold Side ESP + FGC + FF None None 0.05 0.43 0.43 

FBC Fabric Filter SNCR None 0.05 0.43 0.43 

FBC Fabric Filter SNCR Wet FGD 0.05 0.43 0.43 

FBC Fabric Filter SNCR Dry FGD 0.05 0.43 0.43 

FBC Fabric Filter SCR None 0.05 0.43 0.43 
5-21 

Burner 

Type Particulate Control 

Post 

Combustion 

Control – 

NOX

Post 

Combustion 

Control - 

SO2

Bituminous 

EMF 

Subbitumionus 

EMF 

Lignite 

EMF 

FBC Fabric Filter SCR Wet FGD 0.05 0.27 0.43 

FBC Fabric Filter SCR Dry FGD 0.05 0.43 0.43 

FBC Fabric Filter None Wet FGD 0.1 0.43 0.43 

FBC Fabric Filter None Dry FGD 0.05 0.43 0.43 

FBC Fabric Filter None None 0.05 0.43 0.43 

FBC Hot Side ESP SNCR None 1 1 1 

FBC Hot Side ESP SNCR Dry FGD 0.45 0.45 1 

FBC Hot Side ESP None Dry FGD 0.45 0.45 1 

FBC Hot Side ESP None None 1 1 1 

FBC Hot Side ESP + FGC SNCR None 1 1 1 

FBC Hot Side ESP + FGC SNCR Dry FGD 0.45 0.45 1 

FBC Hot Side ESP + FGC None Dry FGD 0.45 0.45 1 

FBC Hot Side ESP + FGC None None 1 1 1 

FBC No Control SNCR None 1 1 1 

FBC No Control SNCR Wet FGD 1 1 1 

FBC No Control SNCR Dry FGD 0.45 0.45 1 

FBC No Control SCR None 1 1 1 

FBC No Control SCR Wet FGD 0.1 0.7 1 

FBC No Control SCR Dry FGD 0.45 0.45 1 

FBC No Control None Wet FGD 1 1 1 

FBC No Control None Dry FGD 0.45 0.45 1 

FBC No Control None None 1 1 1 

PC Cold Side ESP SNCR None 0.64 0.97 1 

PC Cold Side ESP SNCR Wet FGD 0.34 0.65 0.56 

PC Cold Side ESP SNCR Dry FGD 0.64 0.65 1 

PC Cold Side ESP SCR None 0.64 0.97 1 

PC Cold Side ESP SCR Wet FGD 0.1 0.84 0.56 

PC Cold Side ESP SCR Dry FGD 0.64 0.65 1 

PC Cold Side ESP None Wet FGD 0.34 0.84 0.56 

PC Cold Side ESP None Dry FGD 0.64 0.65 1 

PC Cold Side ESP None None 0.64 0.97 1 

PC Cold Side ESP + FF SNCR None 0.2 0.75 1 

PC Cold Side ESP + FF SNCR Wet FGD 0.1 0.3 0.56 

PC Cold Side ESP + FF SNCR Dry FGD 0.05 0.75 1 

PC Cold Side ESP + FF SCR None 0.2 0.75 1 

PC Cold Side ESP + FF SCR Wet FGD 0.1 0.3 0.56 

PC Cold Side ESP + FF SCR Dry FGD 0.05 0.75 1 

PC Cold Side ESP + FF None Wet FGD 0.3 0.3 0.56 

PC Cold Side ESP + FF None Dry FGD 0.05 0.75 1 

PC Cold Side ESP + FF None None 0.2 0.75 1 

PC Cold Side ESP + FGC SNCR None 0.64 0.97 1 

PC Cold Side ESP + FGC SNCR Wet FGD 0.34 0.65 0.56 

PC Cold Side ESP + FGC SNCR Dry FGD 0.64 0.65 1 

PC Cold Side ESP + FGC SCR None 0.64 0.97 1 

PC Cold Side ESP + FGC SCR Wet FGD 0.1 0.84 0.56 

PC Cold Side ESP + FGC SCR Dry FGD 0.64 0.65 1 

PC Cold Side ESP + FGC None Wet FGD 0.34 0.84 0.56 
5-22 

Burner 

Type Particulate Control 

Post 

Combustion 

Control – 

NOX

Post 

Combustion 

Control - 

SO2

Bituminous 

EMF 

Subbitumionus 

EMF 

Lignite 

EMF 

PC Cold Side ESP + FGC None Dry FGD 0.64 0.65 1 

PC Cold Side ESP + FGC None None 0.64 0.97 1 

PC Cold Side ESP + FGC + FF SNCR None 0.2 0.75 1 

PC Cold Side ESP + FGC + FF SNCR Wet FGD 0.1 0.3 0.56 

PC Cold Side ESP + FGC + FF SNCR Dry FGD 0.05 0.75 1 

PC Cold Side ESP + FGC + FF SCR None 0.2 0.75 1 

PC Cold Side ESP + FGC + FF SCR Wet FGD 0.1 0.3 0.56 

PC Cold Side ESP + FGC + FF SCR Dry FGD 0.05 0.75 1 

PC Cold Side ESP + FGC + FF None Wet FGD 0.3 0.3 0.56 

PC Cold Side ESP + FGC + FF None Dry FGD 0.05 0.75 1 

PC Cold Side ESP + FGC + FF None None 0.2 0.75 1 

PC Fabric Filter SNCR None 0.11 0.27 1 

PC Fabric Filter SNCR Wet FGD 0.03 0.27 0.56 

PC Fabric Filter SNCR Dry FGD 0.05 0.75 1 

PC Fabric Filter SCR None 0.11 0.27 1 

PC Fabric Filter SCR Wet FGD 0.1 0.27 0.56 

PC Fabric Filter SCR Dry FGD 0.05 0.75 1 

PC Fabric Filter None Wet FGD 0.1 0.27 0.56 

PC Fabric Filter None Dry FGD 0.05 0.75 1 

PC Fabric Filter None None 0.11 0.27 1 

PC Hot Side ESP SNCR None 0.9 0.9 1 

PC Hot Side ESP SNCR Wet FGD 0.58 0.75 1 

PC Hot Side ESP SNCR Dry FGD 0.6 0.85 1 

PC Hot Side ESP SCR None 0.9 0.9 1 

PC Hot Side ESP SCR Wet FGD 0.1 0.8 1 

PC Hot Side ESP SCR Dry FGD 0.6 0.85 1 

PC Hot Side ESP None Wet FGD 0.58 0.8 1 

PC Hot Side ESP None Dry FGD 0.6 0.85 1 

PC Hot Side ESP None None 0.9 0.94 1 

PC Hot Side ESP + FF SNCR None 0.11 0.27 1 

PC Hot Side ESP + FF SNCR Wet FGD 0.03 0.27 0.56 

PC Hot Side ESP + FF SNCR Dry FGD 0.05 0.75 1 

PC Hot Side ESP + FF SCR None 0.11 0.27 1 

PC Hot Side ESP + FF SCR Wet FGD 0.1 0.15 0.56 

PC Hot Side ESP + FF SCR Dry FGD 0.05 0.75 1 

PC Hot Side ESP + FF None Wet FGD 0.03 0.27 0.56 

PC Hot Side ESP + FF None Dry FGD 0.05 0.75 1 

PC Hot Side ESP + FF None None 0.11 0.27 1 

PC Hot Side ESP + FGC SNCR None 0.9 0.9 1 

PC Hot Side ESP + FGC SNCR Wet FGD 0.58 0.75 1 

PC Hot Side ESP + FGC SNCR Dry FGD 0.6 0.85 1 

PC Hot Side ESP + FGC SCR None 0.9 0.9 1 

PC Hot Side ESP + FGC SCR Wet FGD 0.1 0.8 1 

PC Hot Side ESP + FGC SCR Dry FGD 0.6 0.85 1 

PC Hot Side ESP + FGC None Wet FGD 0.58 0.8 1 

PC Hot Side ESP + FGC None Dry FGD 0.6 0.85 1 

PC Hot Side ESP + FGC None None 0.9 0.94 1 
5-23 

Burner 

Type Particulate Control 

Post 

Combustion 

Control – 

NOX

Post 

Combustion 

Control - 

SO2

Bituminous 

EMF 

Subbitumionus 

EMF 

Lignite 

EMF 

PC Hot Side ESP + FGC + FF SNCR None 0.11 0.27 1 

PC Hot Side ESP + FGC + FF SNCR Wet FGD 0.03 0.27 0.56 

PC Hot Side ESP + FGC + FF SNCR Dry FGD 0.05 0.75 1 

PC Hot Side ESP + FGC + FF SCR None 0.11 0.27 1 

PC Hot Side ESP + FGC + FF SCR Wet FGD 0.1 0.15 0.56 

PC Hot Side ESP + FGC + FF SCR Dry FGD 0.05 0.75 1 

PC Hot Side ESP + FGC + FF None Wet FGD 0.03 0.27 0.56 

PC Hot Side ESP + FGC + FF None Dry FGD 0.05 0.75 1 

PC Hot Side ESP + FGC + FF None None 0.11 0.27 1 

PC No Control SNCR None 1 1 1 

PC No Control SNCR Wet FGD 0.58 0.7 1 

PC No Control SNCR Dry FGD 0.6 0.85 1 

PC No Control SCR None 1 1 1 

PC No Control SCR Wet FGD 0.1 0.7 1 

PC No Control SCR Dry FGD 0.6 0.85 1 

PC No Control None Wet FGD 0.58 0.7 1 

PC No Control None Dry FGD 0.6 0.85 1 

PC No Control None None 1 1 1 

PC PM Scrubber SNCR None 0.9 0.91 1 

PC PM Scrubber SCR None 0.9 1 1 

PC PM Scrubber None None 0.9 0.91 1 

Stoker Cold Side ESP SNCR None 0.65 0.97 1 

Stoker Cold Side ESP SNCR Wet FGD 0.34 0.73 0.56 

Stoker Cold Side ESP SNCR Dry FGD 0.65 0.65 1 

Stoker Cold Side ESP SCR None 0.65 0.97 1 

Stoker Cold Side ESP SCR Wet FGD 0.1 0.84 0.56 

Stoker Cold Side ESP SCR Dry FGD 0.65 0.65 1 

Stoker Cold Side ESP None Wet FGD 0.34 0.84 0.56 

Stoker Cold Side ESP None Dry FGD 0.65 0.65 1 

Stoker Cold Side ESP None None 0.65 0.97 1 

Stoker Cold Side ESP + FGC SNCR None 0.65 0.97 1 

Stoker Cold Side ESP + FGC SNCR Wet FGD 0.34 0.73 0.56 

Stoker Cold Side ESP + FGC SNCR Dry FGD 0.65 0.65 1 

Stoker Cold Side ESP + FGC SCR None 0.65 0.97 1 

Stoker Cold Side ESP + FGC SCR Wet FGD 0.1 0.84 0.56 

Stoker Cold Side ESP + FGC SCR Dry FGD 0.65 0.65 1 

Stoker Cold Side ESP + FGC None Wet FGD 0.34 0.84 0.56 

Stoker Cold Side ESP + FGC None Dry FGD 0.65 0.65 1 

Stoker Cold Side ESP + FGC None None 0.65 0.97 1 

Stoker Fabric Filter SNCR None 0.11 0.27 1 

Stoker Fabric Filter SNCR Wet FGD 0.03 0.27 0.56 

Stoker Fabric Filter SNCR Dry FGD 0.1 0.75 1 

Stoker Fabric Filter SCR None 0.11 0.27 1 

Stoker Fabric Filter SCR Wet FGD 0.1 0.27 0.56 

Stoker Fabric Filter SCR Dry FGD 0.1 0.75 1 

Stoker Fabric Filter None Wet FGD 0.1 0.27 0.56 

Stoker Fabric Filter None Dry FGD 0.1 0.75 1 
5-24 

Burner 

Type Particulate Control 

Post 

Combustion 

Control – 

NOX

Post 

Combustion 

Control - 

SO2

Bituminous 

EMF 

Subbitumionus 

EMF 

Lignite 

EMF 

Stoker Fabric Filter None None 0.11 0.27 1 

Stoker Hot Side ESP SNCR None 1 1 1 

Stoker Hot Side ESP SNCR Wet FGD 0.58 1 1 

Stoker Hot Side ESP SNCR Dry FGD 1 1 1 

Stoker Hot Side ESP SCR None 1 1 1 

Stoker Hot Side ESP SCR Wet FGD 0.1 0.8 1 

Stoker Hot Side ESP SCR Dry FGD 1 1 1 

Stoker Hot Side ESP None Wet FGD 0.58 1 1 

Stoker Hot Side ESP None Dry FGD 1 1 1 

Stoker Hot Side ESP None None 1 1 1 

Stoker Hot Side ESP + FGC SNCR None 1 1 1 

Stoker Hot Side ESP + FGC SNCR Wet FGD 0.58 1 1 

Stoker Hot Side ESP + FGC SNCR Dry FGD 1 1 1 

Stoker Hot Side ESP + FGC SCR None 1 1 1 

Stoker Hot Side ESP + FGC SCR Wet FGD 0.1 0.8 1 

Stoker Hot Side ESP + FGC SCR Dry FGD 1 1 1 

Stoker Hot Side ESP + FGC None Wet FGD 0.58 1 1 

Stoker Hot Side ESP + FGC None Dry FGD 1 1 1 

Stoker Hot Side ESP + FGC None None 1 1 1 

Stoker No Control SNCR None 1 1 1 

Stoker No Control SNCR Wet FGD 0.58 1 1 

Stoker No Control SNCR Dry FGD 1 1 1 

Stoker No Control SCR None 1 1 1 

Stoker No Control SCR Wet FGD 0.1 0.7 1 

Stoker No Control SCR Dry FGD 1 1 1 

Stoker No Control None Wet FGD 0.58 1 1 

Stoker No Control None Dry FGD 1 1 1 

Stoker No Control None None 1 1 1 

Stoker PM Scrubber None None 1 1 1 

Other Cold Side ESP SNCR None 0.64 0.97 1 

Other Cold Side ESP SNCR Wet FGD 0.34 0.73 0.56 

Other Cold Side ESP SNCR Dry FGD 0.64 0.65 1 

Other Cold Side ESP SCR None 0.64 0.97 1 

Other Cold Side ESP SCR Wet FGD 0.1 0.84 0.56 

Other Cold Side ESP SCR Dry FGD 0.64 0.65 1 

Other Cold Side ESP None Wet FGD 0.34 0.84 0.56 

Other Cold Side ESP None Dry FGD 0.64 0.65 1 

Other Cold Side ESP None None 0.64 0.97 1 

Other Cold Side ESP + FGC SNCR None 0.64 0.97 1 

Other Cold Side ESP + FGC SNCR Wet FGD 0.34 0.73 0.56 

Other Cold Side ESP + FGC SNCR Dry FGD 0.64 0.65 1 

Other Cold Side ESP + FGC SCR None 0.64 0.97 1 

Other Cold Side ESP + FGC SCR Wet FGD 0.1 0.84 0.56 

Other Cold Side ESP + FGC SCR Dry FGD 0.64 0.65 1 

Other Cold Side ESP + FGC None Wet FGD 0.34 0.84 0.56 

Other Cold Side ESP + FGC None Dry FGD 0.64 0.65 1 

Other Cold Side ESP + FGC None None 0.64 0.97 1 
5-25 

Burner 

Type Particulate Control 

Post 

Combustion 

Control – 

NOX

Post 

Combustion 

Control - 

SO2

Bituminous 

EMF 

Subbitumionus 

EMF 

Lignite 

EMF 

Other Fabric Filter SNCR None 0.45 0.75 1 

Other Fabric Filter SNCR Wet FGD 0.03 0.27 0.56 

Other Fabric Filter SNCR Dry FGD 0.4 0.75 1 

Other Fabric Filter SCR None 0.11 0.27 1 

Other Fabric Filter SCR Wet FGD 0.1 0.27 0.56 

Other Fabric Filter SCR Dry FGD 0.4 0.75 1 

Other Fabric Filter None Wet FGD 0.1 0.27 0.56 

Other Fabric Filter None Dry FGD 0.4 0.75 1 

Other Fabric Filter None None 0.11 0.27 1 

Other Hot Side ESP SNCR None 1 1 1 

Other Hot Side ESP SNCR Wet FGD 0.58 1 1 

Other Hot Side ESP SNCR Dry FGD 1 1 1 

Other Hot Side ESP SCR None 1 1 1 

Other Hot Side ESP SCR Wet FGD 0.1 0.8 1 

Other Hot Side ESP SCR Dry FGD 1 1 1 

Other Hot Side ESP None Wet FGD 0.58 1 1 

Other Hot Side ESP None Dry FGD 1 1 1 

Other Hot Side ESP None None 1 1 1 

Other Hot Side ESP + FF None None 0.11 0.27 1 

Other Hot Side ESP + FGC SNCR None 1 1 1 

Other Hot Side ESP + FGC SNCR Wet FGD 0.58 1 1 

Other Hot Side ESP + FGC SNCR Dry FGD 1 1 1 

Other Hot Side ESP + FGC SCR None 1 1 1 

Other Hot Side ESP + FGC SCR Wet FGD 0.1 0.8 1 

Other Hot Side ESP + FGC SCR Dry FGD 1 1 1 

Other Hot Side ESP + FGC None Wet FGD 0.58 1 1 

Other Hot Side ESP + FGC None Dry FGD 1 1 1 

Other Hot Side ESP + FGC None None 1 1 1 

Other Hot Side ESP + FGC + FF None None 0.11 0.27 1 

Other No Control SNCR None 1 1 1 

Other No Control SNCR Wet FGD 0.58 0.7 1 

Other No Control SNCR Dry FGD 1 1 1 

Other No Control SCR None 1 1 1 

Other No Control SCR Wet FGD 0.1 0.7 1 

Other No Control SCR Dry FGD 1 1 1 

Other No Control None Wet FGD 0.58 0.7 1 

Other No Control None Dry FGD 1 1 1 

Other No Control None None 1 1 1 

Other PM Scrubber None None 0.9 0.91 1 
5-26 

Table 5-14 Definition of Acronyms for Existing Controls 

Acronym Description 

ESP Electro Static Precipitator - Cold Side 

HESP Electro Static Precipitator - Hot Side 

ESP/O Electro Static Precipitator - Other 

FF Fabric Filter 

FGD Flue Gas Desulfurization - Wet 

DS Flue Gas Desulfurization - Dry 

SCR Selective Catalytic Reduction 

PMSCRUB Particulate Matter Scrubber 

Table 5-15 Key to Burner Type Designations in Table 5-13 

“PC” refers to conventional pulverized coal boilers. Typical configurations include wall-fired 

and tangentially fired boilers (also called T-fired boilers). In wall-fired boilers the burner’s coal 

and air nozzles are mounted on a single wall or opposing walls. In tangentially fired boilers the 

burner’s coal and air nozzles are mounted in each corner of the boiler.

 

“Cyclone” refers to cyclone boilers where air and crushed coal are injected tangentially into the 

boiler through a “cyclone burner” and “cyclone barrel” which create a swirling motion allowing 

smaller coal particles to be burned in suspension and larger coal particles to be captured on the 

cyclone barrel wall where they are burned in molten slag.

 

“Stoker” refers to stoker boilers where lump coal is fed continuously onto a moving grate or 

chain which moves the coal into the combustion zone in which air is drawn through the grate 

and ignition takes place. The carbon gradually burns off, leaving ash which drops off at the end 

into a receptacle, from which it is removed for disposal.

 

“FBC" refers to “fluidized bed combustion” where solid fuels are suspended on upward-blowing 

jets of air, resulting in a turbulent mixing of gas and solids and a tumbling action which provides 

especially effective chemical reactions and heat transfer during the combustion process.

 

“Other" refers to miscellaneous burner types including cell burners and arch- , roof- , and 

vertically-fired burner configurations. 
5-27 

Mercury Control through SO2 and NOX Retrofits 

In EPA Base Case v.4.10, units that install SO2, NOX, and particulate controls, reduce mercury 

emissions as a byproduct of these retrofits. Section 5.4.2 described how EMFs are used in the 

base case to capture the unregulated mercury emissions depending on the rank of coal burned, 

the generating unit’s combustion characteristics, and the specific configuration of SO2, NOX, and 

particulate controls (i.e., hot and cold-side electrostatic precipitators (ESPs), fabric filters (also 

called “baghouses”) and particulate matter (PM) scrubbers). These same EMFs would be 

available in mercury policy runs to characterize the mercury reductions that can be achieved by 

retrofitting a unit with SCR, SNCR, SO2 scrubbers and particulate controls. The absence of a 

federal mercury emission reduction policy means that these controls appear in the base case in 

response to SO2, NOX, or particulate limits or state-level mercury emission requirements. 

However, in future model runs where mercury limits are present these same SO2 and NOX

controls could be deliberately installed for mercury control if they provide the least cost option for 

meeting mercury policy limits. 

Activated Carbon Injection (ACI) 

The technology specifically designated for mercury control is Activated Carbon Injection (ACI) 

downstream of the combustion process in coal fired units. A comprehensive ACI update, which 

will incorporate the latest field experience through 2010, is being prepared by Sargent and Lundy 

(the same engineering firm that developed the SO2 and NOX control assumptions used in EPA 

Base Case v.4.10). It will be incorporated in a future EPA base case. The ACI assumptions in 

the current base case release are the result of a 2007 internal EPA engineering study. 

Based on this study, it is assume that 90% removal from the level of mercury in the coal is 

achievable with the application of one of three alternative ACI configurations: Standard Powered 

Activated Carbon (SPAC), Modified Powered Activated Carbon (MPAC), or SPAC in combination 

with a fabric filter. The MPAC option exploits the discovery that by converting elemental mercury 

to oxidized mercury, halogens (like chlorine, iodine, and bromine) can make activated carbon 

more effective in capturing the mercury at the high temperatures found in industrial processes like 

power generation. In the MPAC system, a small amount of bromine is chemically bonded to the 

powdered carbon which is then injected into the flue gas stream either upstream of both the 

particulate control device (ESP or fabric filter) and the air pre-heater (APH), between the APH and 

the particulate control device, or downstream of both the pre-existing APH and particulate control 

devices but ahead of a new dedicated pulsed-jet fabric filter. (The latter is known as the 

TOXECONTM approach, an air pollution control process patented by EPRI.) 

Table 5-16 presents the capital, FOM, and VOM costs as well as the capacity and heat rate 

penalty for the five Hg emission control technologies included in EPA Base Case v.4.10 for an 

illustrative set of generating units with a representative range of capacities. 
5-28 

Table 5-16 Illustrative Activated Carbon Injection Costs (2007$) for Representative Sizes under the Assumption

v.4.10 

Capacity (MW) 

100 300 500 

Control Type 

Capacit

y 

Penalty 

(%) 

Heat Rate 

Penalty 

(%) 

Capital 

Cost 

($/kW) 

Fixed 

O&M 

($/kWyr) 

Variable 

O&M cost 

(mills/kWh)

Capital 

Cost 

($/kW) 

Fixed 

O&M 

($/kW

-yr) 

Variable 

O&M cost 

(mills/kWh) 

Capital 

Cost 

($/kW) 

Fixed 

O&M 

($/k

W-yr)

Variable 

O&M cost 

(mills/kWh) 

C

($

MPAC_BaghouseMinimum Cutoff: ≥ 25 MW Maximum Cutoff: None Assuming Bituminous Coal 

-0.43 0.43 3 0.1 0.16 2 0.05 0.17 2 0.04 0.17 

MPAC_CESP Minimum Cutoff: ≥ 25 MW Maximum Cutoff: None Assuming Bituminous Coal

-0.43 0.43 8 0.1 0.57 6 0.1 0.61 5 0.1 0.61 

SPAC_BaghouseMinimum Cutoff: ≥ 25 MW Maximum Cutoff: None Assuming Bituminous Coal

-0.43 0.43 5 0.1 0.22 4 0.1 0.23 3 0.1 0.23 

SPAC_ESPMinimum Cutoff: ≥ 25 MW Maximum Cutoff: None Assuming Bituminous Coal

-0.43 0.43 27 0.5 2.29 21 0.3 2.46 18 0.3 2.44 

SPAC_ESP+ToxeconMinimum Cutoff: ≥ 25 MW Maximum Cutoff: None Assuming Bituminous Coal

-0.43 0.43 269 4.3 2.44 202 2.5 2.61 176 2.1 2.59 
5-29 

The applicable ACI option depends on the coal type burned, its SO2 content, the boiler and 

particulate control type and, in some instances, consideration of whether an SO2 scrubber (FGD) 

system or SCR NOx post-combustion control are present. Table 5-17 shows the ACI assignment 

scheme used in EPA Base Case v.4.10 to achieve 90% mercury removal. 

Table 5-17 Assignment Scheme for Mercury Emissions Control Using Activated Carbon 

Injection (ACI) in EPA Base Case v.4.10 

Applicability of Activated Carbon Injection 

Coal Type SO2 in Coal 

(lb/MMBtu) 

Boiler 

Type 

Particulate 

Control Type 

FGD 

System 

SCR 

System

Toxecon 

Required? 

ACI Type 

With 90% Hg 

Reduction 

Bit/Sub-bit/ 

Lig < 1.6 Non-CFB CS-ESP or BH (no FGC) -- No No MPAC 

Bit/Sub-bit/ 

Lig -- Non-CFB CS-ESP or BH (no FGC) LSD -- No MPAC 

Bit/Subbit/Lig -- CFB CS-ESP or BH 

(no FGC) -- -- No MPAC 

Bit < 1.6 Non-CFB CS-ESP Non-LSD Yes No SPAC 

Bit ≥ 1.6 Non-CFB CS-ESP or BH -- -- No SPAC 

Sub-bit/Lig ≥ 1.6 Non-CFB CS-ESP -- -- Yes SPAC 

Sub-bit/Lig ≥ 1.6 Non-CFB BH -- -- No SPAC 

Bit/Sub-bit/ 

Lig -- Non-CFB HESP -- -- Yes SPAC 

Bit/Sub-bit/ 

Lig -- -- HESP or CSESP (with FGC) -- -- Yes SPAC 

Bit/Sub-bit/ 

Lig < 1.6 Non-CFB BH No Yes No MPAC 

Bit/Sub-bit/ 

Lig < 1.6 Non-CFB CS-ESP (no FGC) No Yes No MPAC 

Bit/Sub-bit/ 

Lig -- -- No Control -- -- Yes SPAC 

Bit/Sub-bit/ 

Lig < 1.6 -- BH Non-LSD Yes No SPAC 

Sub-bit/ Lig < 1.6 -- CS-ESP 

(no FGC) Non-LSD Yes Yes SPAC 

Bit/Subbit/Lig -- -- Cyclone -- -- Yes SPAC 

Notes:

Legends: 

ACI Activated carbon injection 

If the existing equipment provides 90% Hg removal, no ACI 

system is required. 

BH Baghouse 

Bit Bituminous coal 

 "--" means that the category type has no effect on the ACI 

application. 

CFB Circulating fluidized-bed boiler 

CS-ESP Cold side electrostatic 

precipitator 

FGC Flue gas conditioning 

HESP Hot electrostatic precipitator 

Lig Lignite 

MPAC Modified powdered activated 

carbon 

SPAC Standard powdered activated 

carbon 

Sub-bit Subbituminous coal 
Appendix 5-1.1 

Appendix 5-1 Example Cost Calculation Worksheets for SO2 Control 

Technologies in EPA Base Case v.4.10 
Appendix 5-1.2 
Appendix 5-1.3 
Appendix 5-1.4 
Appendix 5-2.1 

Appendix 5-2 Example Cost Calculation Worksheets for NOx PostCombustion Control Technologies in EPA Base Case v.4.10 
Appendix 5-2.2 
Appendix 5-2.3 
Appendix 5-2.4 
6-1 

6 CO2 Capture, Transport, and Storage 

6.1 CO2 Capture 

Among the potential (new) units that the model can build in EPA Base Case v.4.10 are advanced 

coal-fired units with CO2 capture (carbon capture).1

 The cost and performance characteristics of 

these units are shown in Table 4-13 and are discussed in Chapter 4. 

Besides offering carbon capture capabilities on potential units that the model builds from scratch, 

EPA Base Case v.4.10 also provides carbon capture as a retrofit option for existing pulverized 

coal plants. The incremental costs and performance assumptions for these retrofits are shown in 

Table 6-1. 

Table 6-1 Performance and Unit Cost Assumptions for Carbon Capture Retrofits 

on Pulverized Coal Plants 

Applicability (Original MW Size) 450-750 MW > 750 MW

Incremental1 Capital Cost (2007 $/kW) 1,972 1,599 

Incremental1 FOM (2007 $/kW-yr) 3.00 1.98

Incremental1 VOM (2007 (mills/kWh) 2.35 2.35

Capacity Penalty (%) -25% -25%

Heat Rate Penalty (%) 33% 33%

CO2 Removal (%) 90% 90%

Note:

1

Incremental costs are applied to the derated (after retrofit) MW size. 

The capital costs shown in Table 6-1 are based on the costs reported for Case 1 in a study2

performed for the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory 

(NETL) by a team consisting of Alstom Power, Inc., American Electric Power (AEP), ABB Global, 

and the Ohio Coal Development Office. For Case 1 this comprehensive engineering study, 

conducted from 1999-2001, evaluated the impacts on plant performance and the required cost to 

add facilities to capture greater than 90% of the CO2 emitted by AEP’s Conesville Ohio Unit #5. 

This is a 450 MW subcritical3

 pulverized bituminous coal plant with a lime based FGD, and an 

electrostatic precipitator for particulate control. The carbon capture method that was evaluated 

was an amine-based scrubber using the Kerr-McGee/ABB Lummus Global commercially available 

monoethanolamine (MEA) process. In this system the flue gas leaves the FGD (which has been 

modified to reduce the SO2 concentration as required by the MEA process) and is cooled and 

ducted to the MEA system where more than 96% of the CO2 can be removed. For use in EPA 

Base Case v.4.10 the capital cost was scaled to be applicable to the MW capacity sizes shown in 

Table 6-1 and converted to constant 2007$ from the 2006$ costs reported in the NETL study. 

 

1

The term “New Advanced Coal with CCS” encompasses various technologies that can provide 

carbon capture. These include supercritical steam generators with carbon capture and integrated 

gasification combined cycle (IGCC) with carbon capture. For purposes of characterizing the cost 

and performance characteristics of advanced coal with carbon capture, IGCC with carbon capture 

was used in Table 4-13. 

2“Carbon Dioxide Capture from Existing Coal-Fired Power Plants” DOE/NETL-401/110907. Final 

Report (Original Issue Date, December 2006) Revision Date, November 2007 

(http://www.netl.doe.gov/energyanalyses/pubs/CO2%20Retrofit%20From%20Existing%20Plants%20Revised%20November%202

007.pdf. A summary of costs for each of the cases appears in Table 3-65 (p. 139). 

3

“Subcritical” refers to thermal power plants that operate below the ”critical temperature” and 

“critical pressure” (220 bar) where boiling, i.e., the formation of steam bubbles in water, no longer 

occurs. Such units are less efficient than “supercritical” and “ultra supercritical” steam generators. 
6-2 

A capacity derating penalty of 25% was assumed, based on reported research and field 

experience as of the summer of 2010. The corresponding heat rate penalty was 33%. (For an 

explanation of the capacity and heat rate penalties and how they are calculated, see the 

discussion under VOM in section 5.1.1.) 

Since the fixed (FOM) and variable operating and maintenance (VOM) costs from the Conesville 

study were given without documentation, another NETL study4

 which fully documented these 

costs was used to obtain the FOM and VOM values shown in Table 6-1. For FOM and VOM, the 

cost differential was calculated between Case 9, a 550 MW subcritical pulverized coal plant with 

CO2 capture, and Case 10, a comparable unit but without CO2 capture. These differentials 

provided the VOM and FOM costs for the “450-750 MW” case in Table 6-1. For the “greater than 

750 MW” case these costs were scaled up by the ratio of a unit with an effective capacity of 750 

MW to the effective capacity of the 450-750 MW case raised to a power (k), where k reflects the 

elasticity of the costs due to economies of scale. (The same approach was used to scale the 

capital costs.) For capital, FOM, and VOM, the value of k was 0.65, 0.30, and 1 respectively. 

6.2 CO2 Storage 

The capacity and cost assumptions for CO2 storage in EPA Base Case v.4.10 are based on 

GeoCAT (Geosequestration Cost Analysis Tool), a spreadsheet model developed for EPA by ICF 

International in support of EPA’s draft Federal Requirements Under the Underground Injection 

Control (UIC) Program for Carbon Dioxide Geologic Storage Wells.5

 The GeoCAT model 

combines detailed characteristics of sequestration capacity by state and geologic setting for the 

U.S. with costing algorithms for individual components of geologic sequestration of CO2. The 

outputs of the model are regional sequestration cost curves that indicate how much potential 

storage capacity is available at different CO2 storage cost points. 

The GeoCAT model includes three modules: a unit cost specification module, a project scenario 

costing module, and a geologic and regional cost curve module. The unit cost module includes 

data and assumptions for 120 unit cost elements falling within the following cost categories: 

• Geologic Site Characterization 

• Monitoring the movement of CO2 in the subsurface 

• Injection Well Construction 

• Area of Review and Corrective Action (including fluid flow and reservoir modeling during and 

after injection and identification, evaluation, and remediation of existing wells within the area 

of review) 

• Well Operation 

• Mechanical Integrity Testing 

• Financial Responsibility (to maintain sufficient resources for activities related to closing and 

remediation of the site) 

• General and Administrative 

 

4

“Cost and Performance Baseline for Fossil Energy Plants” DOE/NETL-2007/1281, Volume 1: 

Bituminous Coal and Natural Gas to Electricity, Final Report (Original Issue Date, May 2007) 

Revision 1, August 2007 (http://www.netl.doe.gov/energyanalyses/pubs/Bituminous%20Baseline_Final%20Report.pdf). The VOM and FOM cost 

calculations for Case 9 appear in Exhibits 4-14 (p. 349) and for Case 10 in Exhibit 4-24 (p. 373). 

5

“Federal Requirements Under the Underground Injection Control (UIC) Program for Carbon 

Dioxide (CO2) Geologic Sequestration (GS) Wells,” Federal Register, July 25, 2008 (Volume 73, 

Number 144), pp. 43491-43541. www.epa.gov/fedrgstr/EPA-WATER/2008/July/Day25/w16626.htm and www.epa.gov/safewater/uic/wells_sequestration.html#regdevelopment. 
6-3 

Of the ten cost categories for geologic CO2 sequestration listed above, the largest cost drivers (in 

roughly descending order of magnitude) are well operation, injection well construction, and 

monitoring. 

The costs derived in the unit cost specification module are used in the GeoCAT project scenario 

costing module to develop commercial scale costs for seven sequestration scenarios of geologic 

settings: 

• saline reservoirs, 

• depleted gas fields, 

• depleted oil fields, 

• enhanced oil recovery, 

• enhanced coal bed methane recovery, 

• enhanced shale gas, and 

• basalt 

EPA’s application of GeoCAT includes only storage capacity for the first four scenarios. The last 

three reservoir types are not included because they are considered technically uncertain and 

minor for the foreseeable future. 

The results of the project scenario costing module are taken as inputs into the geologic and 

regional cost curve module of GeoCAT which generates national and regional “cost curves” 

indicating the volume of sequestration capacity in each region and state in the U.S. as a function 

of cost. This module contains a database of sequestration capacity by state and geologic 

reservoir type. It incorporates assessments from the U.S. Department of Energy’s “Carbon 

Sequestration Atlas of the United States and Canada”6

, enhanced by ICF International to include 

assessments of the Gulf of Mexico, shale gas sequestration potential, and the use of distribution 

of proved oil and gas recovery by region to estimate CO2 potential in areas not covered in the 

DOE atlas. The geologic and regional cost curve module also has a characterization of 

regionalized costs, drilling depths, and other factors that go into the regional cost curves.7

For EPA Base Case v.4.10 GeoCAT identified storage opportunities in 33 of the lower 48 

continental states and storage cost curves were developed for each of them.8

 The storage curve 

for California is designated as California offshore. Louisiana and Texas have both onshore and 

offshore storage cost curves. In addition, there are Atlantic offshore and Pacific offshore storage 

 

6

“Carbon Sequestration Atlas of the United States and Canada”, U.S. Department of Energy, 

National Energy Technology Laboratory, Morgantown, WV, March, 2007. 

7

Detailed discussions of the GeoCAT model and its application for EPA can be found in U.S. 

Environmental Protection Agency, Office of Water, “Geologic CO2 Sequestration Technology and 

Cost Analysis, Technical Support Document” (EPA 816-B-08-009) June 2008, 

http://www.epa.gov/ogwdw000/uic/pdfs/support_uic_co2_technologyandcostanalysis.pdf and 

Harry Vidas, Robert Hugman and Christa Clapp, “Analysis of Geologic Sequestration Costs for the 

United States and Implications for Climate Change Mitigation,” Science Digest, Energy Procedia, 

Volume 1, Issue 1, February 2009, Pages 4281-4288. Available online at www.sciencedirect.com. 8

The states without identified storage opportunities in EPA Base Case v.4.10 are Connecticut, 

Delaware, Idaho, Iowa, Maine, Maryland, Massachusetts, Minnesota, Missouri, New Hampshire, 

New Jersey, North Carolina, Rhode Island, Vermont, and Wisconsin. This implies that these 

states did not present storage opportunities for the four sequestration scenarios included in EPA’s 

inventory, i.e., saline reservoirs, depleted gas fields, depleted oil fields, and enhanced oil 

recovery. 
6-4 

cost curves. The result is a total of 37 storage cost curves which are shown in Appendix 6-1 

(“CO2 Storage Cost Curves in EPA Base Case”).9

The cost curves shown in Appendix 6-1 are in the form of step functions. This implies that in any 

given year a specified amount of storage is available at a particular step price until either the 

annual storage limit (column 4) or the total storage capacity (column 5) is reached. In determining 

whether the total storage capacity has been reached, the model tracks the cumulative storage 

used up through the current year. Once the cumulative storage used equals the total storage 

capacity, no more storage is available going forward at the particular step price. 

There are several additional things to note about the cost curves in Appendix 6-1. First, besides 

electric sector demand for CO2 storage, there is expected to be demand from the industrial sector 

as well. Therefore, before being incorporated into EPA Base Case v.4.10, the original CO2

storage capacity in each storage region was reduced by an estimate of the storage required for 

CO2 generated by industrial sector sources. To do this, ICF first estimated the level of industrial 

demand in each CO2 storage region expected at an allowance price of $150 per ton.10 (An 

allowance price of $150/ton was chosen to provide a conservative estimate of the amount of 

storage available to the electricity sector, since under most CO2 policies that would be analyzed 

with EPA Base Case v.4.1.0 the allowance price is expected to be below $150/ton.) Then, for 

each region ICF calculated the ratio of the industrial demand to total storage capacity available for 

less than $10/ton. (An upper limit of $10/ton was chosen because the considerable amount 

storage available up to that price could be expected to exhaust the industrial demand.) Converting 

this to a percent value and subtracting from 100%. ICF obtained the percent of storage capacity 

available to the electricity sector for less than $10/ton. Finally, the “Annual Step Bound 

(MMTons)” and “Total Storage Capacity (MMTons)” was multiplied by this percentage value for 

each step below $10/ton in the cost curves for the region to obtain the reduced storage capacity 

that went into the storage cost curves for the electric sector in EPA Base Case v.4.10. Thus, the 

values shown in Table 6-1 represent the storage available to the electric sector. 

Second, price steps from region to region are the same. (That is, CO2STEP5 (column 2) has a 

step cost value of $4.54/Ton (column 3) across all storage regions (column 1). This across-region 

price equivalency holds for every step.) However, the amount of storage available in any given 

year (labeled “Annual Step Bound (MMTons)” in column 4) and the total storage available over all 

years (labeled “Total Storage Capacity (MMTons)” in column 5) vary from region to region. Third, 

in any given region, the cost curves are the same for every year. Thus, the step cost, step bound, 

and total storage capacity shown in columns 4 and 5 in Appendix 6-1 remain the same from year 

to year. This feature implies the assumption that over the modeling time horizon, i.e., 2012-2050, 

no new storage will need to be added to augment the storage that is in today’s storage inventory. 

This assumption is not meant to imply that additional storage is unavailable. It only implies that for 

purposes of modeling the assumption will only be revisited if model runs requiring storage exhaust 

key components in the storage inventory. 

Finally, in each storage cost curve included in Appendix 6-1, CO2STEP1 through CO2STEP3 

show a negative cost, and CO2STEP4 shows a zero cost. These steps in the cost curves 

represent storage available from enhanced oil recovery (EOR) where oil producers either pay or 

 

9

For consistency across the emission costs represented in v.4.10, the costs shown in Appendices 

9-1 and 9-2 are expressed in units of dollars per short ton. In IPM documentation and outputs the 

convention is to use the word “tons” to indicate short tons and the word “tonnes” to indicate metric 

tons. In discussing CO2 outside of the modeling framework, the international convention is to use 

metric tons. To obtain the $/tonne equivalent multiply the $/ton values shown In Appendices 9-1 

and 9-2 by 1.1023. 

10The approach that ICF employed to estimate industrial demand for CO2 storage is described in 

ICF International, “Methodology and Results for Initial Forecast of Industrial CCS Volumes,” 

January 2009. 
6-5 

offer free storage for CO2 which they inject into mature oil wells to enhance the amount of oil 

recovered.11

6.3 CO2 Transport 

Each of the 32 IPM model regions can send CO2 to the 37 regions represented by the storage 

cost curves in Appendix 6-1. The associated transport costs (in 2007$/Ton) are shown in 

Appendix 6-2 (CO2 Transportation Matrix in EPA Base Case v.4.0). 

These costs were derived by ICF International by first calculating the pipeline distance from each 

of the CO2 Production Regions to each of the CO2 Storage Regions listed in Appendix 6-2. (For 

example, the distance from MACS to Louisiana Onshore was estimated as 997 miles.) Since 

there are large economies of scale for pipelines, CO2 transportation costs would depend on how 

many power plants and industrial CO2 sources could share a pipeline over a given distance. 

Consequently, ICF’s method assumes that the longer the distance from the source of the CO2 (in 

our example MACS) to the sink for the CO2 (in our example Louisiana Onshore), the more chance 

there is for other sources to share in the transportation costs with the pipeline diameter growing 

with distance as more sources are fed into the same system. Cost components include pipeline 

costs (in $/inch-mile) and cost of service (in $/ton per 75 miles). These cost components in turn 

are functions of the required diameter and thickness of the pipeline and the flow capacity of the 

pipeline, which themselves are functions of the assumed number of power plants using the 

pipeline. Table 6-2 illustrates the build-up of cost for the MACS to Louisiana Onshore example. 

This example comes to $20.11 per ton of CO2 (in 2007$) for the overall miles pipeline distance 

traveled. (This is the short ton equivalent to the $22.17 metric tonne value shown in Table 6-2.) 

Table 6-2 CO2 Transport Cost Calculation Example – MACS to Louisiana Onshore 

 Outside 

Dia. 

Inches 

 Inside 

Dia. 

Inches 

 Wall 

Thickness 

Inches 

 Pipeline 

Cost in 

$/Inch-Mile 

 Total Cost of 

Service in $/metric 

ton per 75 miles or 

121 km 

 Flow 

Capacity in 

metric 

tons/day 

 Flow Capacity in 

million standard cubic 

feet per day 

(60 degrees F and 

14.73 psi) 

 Number of 500 

MW IGCC plants 

accomodated 

12.75 12.0 0.39 75,000 $ $4.36 10,775 203 0.97 

16 15.0 0.49 78,116 $ $3.25 19,139 361 1.73 

24 22.5 0.73 84,119 $ $2.02 53,385 1,007 4.83 

30 28.2 0.92 86,399 $ $1.56 93,887 1,771 8.49 

36 33.8 1.10 88,678 $ $1.27 148,913 2,808 13.46 

42 39.4 1.28 90,958 $ $1.10 219,942 4,148 19.88 

Note: 500 MW IGCC plant would produce 512 metric tonnes of CO2 per hour. Of this, 90% or 461 tonnes would be captured.

Maximum CO2 tranport needs would be 11,064 tonnes per power plant per day. Cost of service based on 7 cents per kWh electricity.

 Miles $/Mile per Tonne Cost per 

Tonne 

 Annual Cost per 

Power Plant @85 

Utilization Rate 

Single Power Plant Pipeline (12 inch, small gathering) distance in miles 25 $0.058 $1.45 $4,986,315

Two Power Plant Pipeline (16 inch, large gathering) distance in miles 25 $0.043 $1.08 $3,717,211

Eight Power Plant Pipeline (30 inch, mainline) distance in miles 947 $0.021 $19.64 $67,400,166

Total Distance & Costs 997 $0.022 $22.17 $76,103,692

CARBON DIOXIDE PIPELINES

Example Spacial Assumptions

 

11There is also a market for CO2 injection in enhanced coal bed methane (ECBM) production. 

ECBM is excluded from EPA’s inventory as discussed earlier. 
Appendix 6-2.1 

Appendix 6-1 CO2 Storage Cost Curves in EPA Base Case 4.10 

Note: The curves for each region are applicable in each model run year 2012 - 2050. 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP1 -13.61 1 45 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 6 

STEP5 4.54 31 1,568 

STEP6 9.07 39 1,967 

STEP7 13.61 38 1,895 

STEP8 18.14 0 9 

STEP9 22.68 4 186 

STEP10 27.22 13 639 

STEP11 31.75 0 7 

STEP12 36.29 0 14 

STEP13 40.82 0 0 

STEP14 45.36 1 68 

STEP15 49.90 0 0 

STEP16 54.43 0 14 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Alabama 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 121 6,026 

STEP6 9.07 145 7,275 

STEP7 13.61 113 5,659 

STEP8 18.14 0 0 

STEP9 22.68 38 1,887 

STEP10 27.22 0 1 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Arizona 

STEP19 68.04 0 0 

STEP1 -13.61 1 62 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 146 7,297 

Arkansas 

STEP6 9.07 177 8,863 
Appendix 6-2.2 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP7 13.61 142 7,110 

STEP8 18.14 1 35 

STEP9 22.68 51 2,568 

STEP10 27.22 3 128 

STEP11 31.75 0 0 

STEP12 36.29 1 53 

STEP13 40.82 0 0 

STEP14 45.36 1 71 

STEP15 49.90 0 0 

STEP16 54.43 1 53 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 1,832 91,580 

STEP6 9.07 2,211 110,528 

STEP7 13.61 1,706 85,311 

STEP8 18.14 0 0 

STEP9 22.68 0 0 

STEP10 27.22 569 28,437 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Atlantic Offshore 

STEP19 68.04 0 0 

STEP1 -13.61 19 941 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 2 121 

STEP5 4.54 1,227 61,357 

STEP6 9.07 1,966 98,304 

STEP7 13.61 367 18,335 

STEP8 18.14 11 531 

STEP9 22.68 70 3,516 

STEP10 27.22 30 1,507 

STEP11 31.75 0 0 

STEP12 36.29 16 797 

STEP13 40.82 0 0 

California 

Onshore 

STEP14 45.36 21 1,063 
Appendix 6-2.3 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP15 49.90 0 0 

STEP16 54.43 16 797 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 0 0 

STEP1 -13.61 3 136 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 13 627 

STEP6 9.07 16 801 

STEP7 13.61 16 804 

STEP8 18.14 1 35 

STEP9 22.68 7 353 

STEP10 27.22 1 59 

STEP11 31.75 0 0 

STEP12 36.29 0 22 

STEP13 40.82 0 0 

STEP14 45.36 1 30 

STEP15 49.90 0 0 

STEP16 54.43 0 22 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Colorado 

STEP19 68.04 0 0 

STEP1 -13.61 2 105 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 456 22,813 

STEP6 9.07 550 27,479 

STEP7 13.61 426 21,317 

STEP8 18.14 0 13 

STEP9 22.68 143 7,172 

STEP10 27.22 1 33 

STEP11 31.75 0 0 

STEP12 36.29 0 20 

STEP13 40.82 0 0 

STEP14 45.36 1 26 

STEP15 49.90 0 0 

STEP16 54.43 0 20 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Florida 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

Georgia 

STEP3 -4.54 0 0 
Appendix 6-2.4 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP4 0.00 0 0 

STEP5 4.54 42 2,117 

STEP6 9.07 51 2,555 

STEP7 13.61 40 2,000 

STEP8 18.14 0 0 

STEP9 22.68 0 0 

STEP10 27.22 13 667 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 0 0 

STEP1 -13.61 3 165 

STEP2 -9.07 0 16 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 309 15,455 

STEP6 9.07 373 18,653 

STEP7 13.61 303 15,168 

STEP8 18.14 1 73 

STEP9 22.68 108 5,420 

STEP10 27.22 4 180 

STEP11 31.75 0 0 

STEP12 36.29 2 109 

STEP13 40.82 0 0 

STEP14 45.36 3 144 

STEP15 49.90 0 0 

STEP16 54.43 2 108 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Illinois 

STEP19 68.04 0 0 

STEP1 -13.61 0 17 

STEP2 -9.07 0 2 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 164 8,195 

STEP6 9.07 198 9,890 

STEP7 13.61 167 8,332 

STEP8 18.14 0 1 

STEP9 22.68 56 2,781 

STEP10 27.22 0 2 

Indiana 

STEP11 31.75 0 0 
Appendix 6-2.5 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP12 36.29 0 1 

STEP13 40.82 0 0 

STEP14 45.36 0 1 

STEP15 49.90 0 0 

STEP16 54.43 0 1 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 0 0 

STEP1 -13.61 6 287 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 37 1,863 

STEP6 9.07 50 2,513 

STEP7 13.61 66 3,323 

STEP8 18.14 14 685 

STEP9 22.68 32 1,620 

STEP10 27.22 0 0 

STEP11 31.75 0 0 

STEP12 36.29 12 620 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Kansas 

STEP19 68.04 0 0 

STEP1 -13.61 0 7 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 54 2,694 

STEP6 9.07 86 4,310 

STEP7 13.61 16 808 

STEP8 18.14 1 26 

STEP9 22.68 4 208 

STEP10 27.22 1 64 

STEP11 31.75 0 0 

STEP12 36.29 4 182 

STEP13 40.82 0 0 

STEP14 45.36 1 52 

STEP15 49.90 0 0 

STEP16 54.43 1 39 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Kentucky 

STEP19 68.04 2 86 
Appendix 6-2.6 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP1 -13.61 20 1,012 

STEP2 -9.07 0 0 

STEP3 -4.54 3 130 

STEP4 0.00 0 0 

STEP5 4.54 918 45,891 

STEP6 9.07 1,127 56,334 

STEP7 13.61 949 47,463 

STEP8 18.14 7 353 

STEP9 22.68 47 2,342 

STEP10 27.22 334 16,704 

STEP11 31.75 0 0 

STEP12 36.29 8 397 

STEP13 40.82 0 0 

STEP14 45.36 26 1,292 

STEP15 49.90 3 134 

STEP16 54.43 11 530 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Louisiana 

Onshore 

STEP19 68.04 8 397 

STEP1 -13.61 23 1,128 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 0 0 

STEP6 9.07 0 0 

STEP7 13.61 661 33,069 

STEP8 18.14 2,535 126,766 

STEP9 22.68 0 0 

STEP10 27.22 677 33,829 

STEP11 31.75 2,208 110,376 

STEP12 36.29 992 49,604 

STEP13 40.82 20 1,012 

STEP14 45.36 1,695 84,765 

STEP15 49.90 0 0 

STEP16 54.43 1,338 66,898 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Louisiana 

Offshore 

STEP19 68.04 1,159 57,975 

STEP1 -13.61 1 62 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 339 16,935 

STEP6 9.07 409 20,471 

STEP7 13.61 323 16,130 

Michigan 

STEP8 18.14 0 4 
Appendix 6-2.7 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP9 22.68 108 5,380 

STEP10 27.22 0 7 

STEP11 31.75 0 6 

STEP12 36.29 0 4 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 2 

STEP16 54.43 0 0 

STEP17 58.97 0 3 

STEP18 63.50 0 0 

STEP19 68.04 0 2 

STEP1 -13.61 2 117 

STEP2 -9.07 0 0 

STEP3 -4.54 0 18 

STEP4 0.00 0 0 

STEP5 4.54 552 27,623 

STEP6 9.07 668 33,410 

STEP7 13.61 522 26,080 

STEP8 18.14 1 63 

STEP9 22.68 4 221 

STEP10 27.22 178 8,877 

STEP11 31.75 0 0 

STEP12 36.29 1 71 

STEP13 40.82 0 0 

STEP14 45.36 3 157 

STEP15 49.90 0 0 

STEP16 54.43 2 95 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Mississippi 

STEP19 68.04 1 71 

STEP1 -13.61 4 194 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 1,608 80,381 

STEP6 9.07 1,941 97,053 

STEP7 13.61 1,505 75,253 

STEP8 18.14 8 396 

STEP9 22.68 513 25,652 

STEP10 27.22 23 1,131 

STEP11 31.75 0 0 

STEP12 36.29 8 391 

STEP13 40.82 0 0 

STEP14 45.36 13 652 

STEP15 49.90 0 0 

Montana 

STEP16 54.43 10 522 
Appendix 6-2.8 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 8 391 

STEP1 -13.61 5 241 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 91 4,549 

STEP6 9.07 110 5,499 

STEP7 13.61 91 4,538 

STEP8 18.14 8 376 

STEP9 22.68 41 2,068 

STEP10 27.22 22 1,110 

STEP11 31.75 0 0 

STEP12 36.29 8 384 

STEP13 40.82 0 0 

STEP14 45.36 13 640 

STEP15 49.90 0 0 

STEP16 54.43 10 512 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

North Dakota 

STEP19 68.04 8 384 

STEP1 -13.61 0 11 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 15 734 

STEP6 9.07 18 881 

STEP7 13.61 17 859 

STEP8 18.14 0 11 

STEP9 22.68 7 337 

STEP10 27.22 1 25 

STEP11 31.75 0 0 

STEP12 36.29 0 15 

STEP13 40.82 0 0 

STEP14 45.36 0 20 

STEP15 49.90 0 0 

STEP16 54.43 0 15 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Nebraska 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

Nevada 

STEP5 4.54 60 3,024 
Appendix 6-2.9 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP6 9.07 73 3,650 

STEP7 13.61 56 2,821 

STEP8 18.14 0 0 

STEP9 22.68 19 940 

STEP10 27.22 0 0 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 0 0 

STEP1 -13.61 13 672 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 36 1,791 

STEP6 9.07 67 3,338 

STEP7 13.61 103 5,130 

STEP8 18.14 6 285 

STEP9 22.68 59 2,960 

STEP10 27.22 21 1,033 

STEP11 31.75 0 0 

STEP12 36.29 6 293 

STEP13 40.82 0 0 

STEP14 45.36 8 391 

STEP15 49.90 0 0 

STEP16 54.43 6 293 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

New Mexico 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 0 0 

STEP6 9.07 0 8 

STEP7 13.61 1 54 

STEP8 18.14 0 15 

STEP9 22.68 1 39 

STEP10 27.22 0 7 

STEP11 31.75 0 0 

STEP12 36.29 0 23 

New York 

STEP13 40.82 0 0 
Appendix 6-2.10 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 213 10,634 

STEP6 9.07 257 12,835 

STEP7 13.61 206 10,320 

STEP8 18.14 0 13 

STEP9 22.68 71 3,551 

STEP10 27.22 1 33 

STEP11 31.75 0 0 

STEP12 36.29 3 130 

STEP13 40.82 0 0 

STEP14 45.36 1 26 

STEP15 49.90 0 0 

STEP16 54.43 0 20 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Ohio 

STEP19 68.04 1 66 

STEP1 -13.61 18 898 

STEP2 -9.07 2 116 

STEP3 -4.54 3 154 

STEP4 0.00 0 0 

STEP5 4.54 2 117 

STEP6 9.07 10 502 

STEP7 13.61 41 2,070 

STEP8 18.14 8 387 

STEP9 22.68 35 1,767 

STEP10 27.22 36 1,779 

STEP11 31.75 0 0 

STEP12 36.29 9 436 

STEP13 40.82 0 0 

STEP14 45.36 22 1,116 

STEP15 49.90 0 0 

STEP16 54.43 12 581 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Oklahoma 

STEP19 68.04 9 436 

Oregon STEP1 -13.61 0 0 

STEP2 -9.07 0 0 
Appendix 6-2.11 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 171 8,530 

STEP6 9.07 206 10,294 

STEP7 13.61 161 8,036 

STEP8 18.14 0 0 

STEP9 22.68 54 2,679 

STEP10 27.22 0 0 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 0 0 

STEP6 9.07 0 0 

STEP7 13.61 309 15,432 

STEP8 18.14 331 16,535 

STEP9 22.68 573 28,660 

STEP10 27.22 0 2 

STEP11 31.75 0 3 

STEP12 36.29 198 9,921 

STEP13 40.82 331 16,537 

STEP14 45.36 265 13,234 

STEP15 49.90 0 0 

STEP16 54.43 2 83 

STEP17 58.97 0 8 

STEP18 63.50 2 110 

Pacific Offshore 

STEP19 68.04 222 11,123 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 52 2,611 

STEP6 9.07 84 4,178 

STEP7 13.61 19 972 

STEP8 18.14 1 34 

STEP9 22.68 5 262 

Pennsylvania 

STEP10 27.22 2 86 
Appendix 6-2.12 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP11 31.75 0 0 

STEP12 36.29 4 206 

STEP13 40.82 0 0 

STEP14 45.36 1 69 

STEP15 49.90 0 0 

STEP16 54.43 1 52 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 2 93 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 43 2,126 

STEP6 9.07 51 2,565 

STEP7 13.61 40 2,000 

STEP8 18.14 0 0 

STEP9 22.68 13 667 

STEP10 27.22 0 0 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

South Carolina 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 219 10,933 

STEP6 9.07 264 13,196 

STEP7 13.61 206 10,313 

STEP8 18.14 0 0 

STEP9 22.68 69 3,438 

STEP10 27.22 0 1 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

South Dakota 

STEP18 63.50 0 0 
Appendix 6-2.13 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 21 1,035 

STEP6 9.07 33 1,657 

STEP7 13.61 6 319 

STEP8 18.14 0 0 

STEP9 22.68 0 0 

STEP10 27.22 0 0 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Tennessee 

STEP19 68.04 0 0 

STEP1 -13.61 113 5,633 

STEP2 -9.07 0 0 

STEP3 -4.54 14 724 

STEP4 0.00 0 0 

STEP5 4.54 1,800 90,016 

STEP6 9.07 2,195 109,766 

STEP7 13.61 1,913 95,669 

STEP8 18.14 25 1,258 

STEP9 22.68 228 11,406 

STEP10 27.22 690 34,524 

STEP11 31.75 0 0 

STEP12 36.29 38 1,887 

STEP13 40.82 0 0 

STEP14 45.36 81 4,041 

STEP15 49.90 0 0 

STEP16 54.43 38 1,887 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Texas Onshore 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 0 0 

STEP6 9.07 0 0 

Texas Offshore 

STEP7 13.61 397 19,842 
Appendix 6-2.14 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP8 18.14 1,521 76,059 

STEP9 22.68 0 0 

STEP10 27.22 400 19,999 

STEP11 31.75 1,324 66,192 

STEP12 36.29 595 29,762 

STEP13 40.82 4 197 

STEP14 45.36 1,000 49,998 

STEP15 49.90 0 0 

STEP16 54.43 796 39,801 

STEP17 58.97 3 133 

STEP18 63.50 0 0 

STEP19 68.04 627 31,338 

STEP1 -13.61 4 195 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 2 106 

STEP6 9.07 4 184 

STEP7 13.61 5 251 

STEP8 18.14 1 36 

STEP9 22.68 3 137 

STEP10 27.22 1 46 

STEP11 31.75 0 0 

STEP12 36.29 0 12 

STEP13 40.82 0 0 

STEP14 45.36 0 16 

STEP15 49.90 0 0 

STEP16 54.43 0 12 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Utah 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 0 0 

STEP6 9.07 0 0 

STEP7 13.61 0 21 

STEP8 18.14 0 9 

STEP9 22.68 1 53 

STEP10 27.22 0 23 

STEP11 31.75 0 0 

STEP12 36.29 0 14 

STEP13 40.82 0 0 

STEP14 45.36 0 18 

Virginia 

STEP15 49.90 0 0 
Appendix 6-2.15 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP16 54.43 0 14 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 162 8,101 

STEP6 9.07 196 9,777 

STEP7 13.61 155 7,738 

STEP8 18.14 0 0 

STEP9 22.68 52 2,579 

STEP10 27.22 0 0 

STEP11 31.75 0 0 

STEP12 36.29 0 0 

STEP13 40.82 0 0 

STEP14 45.36 0 0 

STEP15 49.90 0 0 

STEP16 54.43 0 0 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

Washington 

STEP19 68.04 0 0 

STEP1 -13.61 0 0 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

STEP4 0.00 0 0 

STEP5 4.54 47 2,351 

STEP6 9.07 75 3,761 

STEP7 13.61 14 721 

STEP8 18.14 1 38 

STEP9 22.68 5 227 

STEP10 27.22 2 94 

STEP11 31.75 0 0 

STEP12 36.29 1 73 

STEP13 40.82 0 0 

STEP14 45.36 2 75 

STEP15 49.90 0 0 

STEP16 54.43 1 57 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

West Virginia 

STEP19 68.04 0 10 

STEP1 -13.61 6 324 

STEP2 -9.07 0 0 

STEP3 -4.54 0 0 

Wyoming 

STEP4 0.00 0 0 
Appendix 6-2.16 

CO2 Storage 

Region 

Step 

Name 

CO2 Storage 

Step Cost 

(2007$/Ton) 

Annual Step Bound

(MMTons) 

Total Storage Capacity 

(MMTons) 

STEP5 4.54 2,644 132,195 

STEP6 9.07 3,198 159,909 

STEP7 13.61 2,486 124,304 

STEP8 18.14 2 100 

STEP9 22.68 836 41,794 

STEP10 27.22 10 496 

STEP11 31.75 0 0 

STEP12 36.29 1 65 

STEP13 40.82 0 0 

STEP14 45.36 7 339 

STEP15 49.90 0 0 

STEP16 54.43 2 87 

STEP17 58.97 0 0 

STEP18 63.50 0 0 

STEP19 68.04 1 65 
Appendix 6-2.1 

Appendix 6-2 CO2 Transportation Matrix in EPA Base Case v.4.10 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Alabama 26.30 

Arizona 3.50 

Arkansas 19.34 

Atlantic Offshore 35.66 

California Onshore 13.36 

Colorado 9.43 

Florida 34.30 

Georgia 32.10 

Illinois 23.54 

Indiana 25.54 

Kansas 11.13 

Kentucky 29.06 

Louisiana Onshore 22.58 

Louisiana Offshore 23.19 

Michigan 28.53 

Mississippi 23.21 

Montana 18.29 

North Dakota 18.73 

Nebraska 11.58 

Nevada 9.20 

New Mexico 3.30 

New York 34.34 

Ohio 30.66 

Oklahoma 12.63 

Oregon 20.63 

Pacific Offshore 12.18 

Pennsylvania 33.49 

South Carolina 32.35 

South Dakota 16.24 

Tennessee 27.12 

Texas Onshore 15.99 

Texas Offshore 21.22 

Utah 7.90 

Virginia 32.84 

West Virginia 30.89 

AZNM 

Wyoming 12.76 

Alabama 37.36 

Arizona 11.27 

Arkansas 30.35 

Atlantic Offshore 46.55 

California Onshore 4.67 

Colorado 17.69 

Florida 45.34 

Georgia 43.10 

Illinois 33.75 

CA-N 

Indiana 35.78 
Appendix 6-2.2 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Kansas 21.53 

Kentucky 39.54 

Louisiana Onshore 33.61 

Louisiana Offshore 34.04 

Michigan 37.98 

Mississippi 34.28 

Montana 22.73 

North Dakota 23.59 

Nebraska 19.92 

Nevada 5.18 

New Mexico 13.42 

New York 43.93 

Ohio 40.66 

Oklahoma 23.52 

Oregon 14.68 

Pacific Offshore 5.49 

Pennsylvania 43.47 

South Carolina 43.30 

South Dakota 22.18 

Tennessee 37.87 

Texas Onshore 26.74 

Texas Offshore 31.95 

Utah 12.50 

Virginia 43.36 

West Virginia 41.28 

Wyoming 18.13 

Alabama 33.45 

Arizona 7.46 

Arkansas 26.55 

Atlantic Offshore 42.90 

California Onshore 6.99 

Colorado 15.09 

Florida 41.31 

Georgia 39.32 

Illinois 30.57 

Indiana 32.59 

Kansas 18.18 

Kentucky 36.20 

Louisiana Onshore 29.58 

Louisiana Offshore 29.90 

Michigan 35.22 

Mississippi 30.34 

Montana 21.82 

North Dakota 22.54 

Nebraska 17.41 

Nevada 4.60 

CA-S 

New Mexico 9.72 
Appendix 6-2.3 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

New York 41.12 

Ohio 37.62 

Oklahoma 19.87 

Oregon 17.43 

Pacific Offshore 5.27 

Pennsylvania 40.45 

South Carolina 39.59 

South Dakota 20.67 

Tennessee 34.35 

Texas Onshore 22.59 

Texas Offshore 27.79 

Utah 10.69 

Virginia 40.00 

West Virginia 38.01 

Wyoming 16.62 

Alabama 15.38 

Arizona 26.11 

Arkansas 13.19 

Atlantic Offshore 16.86 

California Onshore 34.86 

Colorado 18.43 

Florida 22.02 

Georgia 16.05 

Illinois 4.75 

Indiana 4.82 

Kansas 15.43 

Kentucky 8.40 

Louisiana Onshore 16.98 

Louisiana Offshore 20.13 

Michigan 4.81 

Mississippi 15.10 

Montana 18.69 

North Dakota 17.74 

Nebraska 16.28 

Nevada 30.94 

New Mexico 23.94 

New York 10.57 

Ohio 7.45 

Oklahoma 15.12 

Oregon 34.88 

Pacific Offshore 35.76 

Pennsylvania 10.14 

South Carolina 15.15 

South Dakota 16.60 

Tennessee 9.56 

Texas Onshore 20.39 

COMD 

Texas Offshore 20.75 
Appendix 6-2.4 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Utah 23.86 

Virginia 11.68 

West Virginia 9.22 

Wyoming 19.55 

Alabama 20.59 

Arizona 39.27 

Arkansas 23.19 

Atlantic Offshore 13.07 

California Onshore 48.11 

Colorado 31.74 

Florida 22.09 

Georgia 16.20 

Illinois 16.14 

Indiana 14.22 

Kansas 28.47 

Kentucky 11.74 

Louisiana Onshore 24.54 

Louisiana Offshore 27.30 

Michigan 11.58 

Mississippi 22.44 

Montana 30.66 

North Dakota 29.63 

Nebraska 29.57 

Nevada 44.25 

New Mexico 37.07 

New York 5.72 

Ohio 8.97 

Oklahoma 27.58 

Oregon 47.39 

Pacific Offshore 48.99 

Pennsylvania 6.18 

South Carolina 14.74 

South Dakota 29.17 

Tennessee 14.78 

Texas Onshore 30.61 

Texas Offshore 28.92 

Utah 37.14 

Virginia 9.36 

West Virginia 9.81 

DSNY 

Wyoming 32.53 

Alabama 7.84 

Arizona 21.51 

Arkansas 3.44 

Atlantic Offshore 16.70 

California Onshore 31.99 

Colorado 17.06 

ENTG 

Florida 16.30 
Appendix 6-2.5 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Georgia 13.09 

Illinois 8.81 

Indiana 9.87 

Kansas 11.85 

Kentucky 11.53 

Louisiana Onshore 6.63 

Louisiana Offshore 9.61 

Michigan 15.04 

Mississippi 5.45 

Montana 22.95 

North Dakota 22.36 

Nebraska 16.04 

Nevada 27.84 

New Mexico 19.32 

New York 19.12 

Ohio 14.70 

Oklahoma 9.24 

Oregon 35.90 

Pacific Offshore 31.01 

Pennsylvania 17.17 

South Carolina 13.34 

South Dakota 19.94 

Tennessee 8.76 

Texas Onshore 10.31 

Texas Offshore 9.93 

Utah 22.29 

Virginia 14.87 

West Virginia 13.49 

Wyoming 20.78 

Alabama 11.70 

Arizona 17.85 

Arkansas 6.89 

Atlantic Offshore 22.16 

California Onshore 28.61 

Colorado 16.48 

Florida 19.08 

Georgia 18.02 

Illinois 15.08 

Indiana 16.40 

Kansas 11.44 

Kentucky 18.11 

Louisiana Onshore 7.38 

Louisiana Offshore 7.88 

Michigan 21.40 

Mississippi 8.61 

Montana 24.73 

North Dakota 24.42 

ERCT 

Nebraska 16.44 
Appendix 6-2.6 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Nevada 24.59 

New Mexico 15.94 

New York 25.74 

Ohio 21.33 

Oklahoma 8.37 

Oregon 34.69 

Pacific Offshore 26.55 

Pennsylvania 23.80 

South Carolina 18.68 

South Dakota 21.63 

Tennessee 15.19 

Texas Onshore 4.33 

Texas Offshore 6.27 

Utah 20.59 

Virginia 21.28 

West Virginia 20.06 

Wyoming 21.08 

Alabama 7.71 

Arizona 33.74 

Arkansas 14.94 

Atlantic Offshore 8.78 

California Onshore 44.39 

Colorado 29.83 

Florida 4.12 

Georgia 5.33 

Illinois 16.83 

Indiana 15.92 

Kansas 24.61 

Kentucky 13.10 

Louisiana Onshore 11.59 

Louisiana Offshore 12.45 

Michigan 20.06 

Mississippi 10.73 

Montana 34.81 

North Dakota 34.07 

Nebraska 28.72 

Nevada 40.31 

New Mexico 31.64 

New York 20.09 

Ohio 16.78 

Oklahoma 21.91 

Oregon 48.66 

Pacific Offshore 42.80 

Pennsylvania 17.31 

South Carolina 6.76 

South Dakota 31.99 

Tennessee 11.23 

FRCC 

Texas Onshore 19.12 
Appendix 6-2.7 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Texas Offshore 14.75 

Utah 35.06 

Virginia 12.94 

West Virginia 13.74 

Wyoming 33.33 

Alabama 12.18 

Arizona 23.91 

Arkansas 9.40 

Atlantic Offshore 16.05 

California Onshore 33.36 

Colorado 17.01 

Florida 19.59 

Georgia 14.19 

Illinois 3.25 

Indiana 4.03 

Kansas 13.08 

Kentucky 7.95 

Louisiana Onshore 13.27 

Louisiana Offshore 16.40 

Michigan 8.25 

Mississippi 11.47 

Montana 19.47 

North Dakota 18.64 

Nebraska 15.15 

Nevada 29.31 

New Mexico 21.68 

New York 13.25 

Ohio 9.20 

Oklahoma 12.12 

Oregon 34.74 

Pacific Offshore 33.66 

Pennsylvania 12.01 

South Carolina 13.61 

South Dakota 16.90 

Tennessee 7.49 

Texas Onshore 16.70 

Texas Offshore 16.94 

Utah 22.59 

Virginia 11.76 

West Virginia 9.55 

GWAY 

Wyoming 19.15 

Alabama 20.91 

Arizona 40.31 

Arkansas 23.89 

Atlantic Offshore 12.75 

California Onshore 49.26 

Colorado 32.87 

LILC 

Florida 21.86 
Appendix 6-2.8 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Georgia 16.18 

Illinois 17.12 

Indiana 15.16 

Kansas 29.50 

Kentucky 12.40 

Louisiana Onshore 24.99 

Louisiana Offshore 27.68 

Michigan 12.79 

Mississippi 22.91 

Montana 31.94 

North Dakota 30.91 

Nebraska 30.72 

Nevada 45.37 

New Mexico 38.10 

New York 6.99 

Ohio 9.97 

Oklahoma 28.52 

Oregon 48.65 

Pacific Offshore 50.04 

Pennsylvania 7.14 

South Carolina 14.74 

South Dakota 30.42 

Tennessee 15.36 

Texas Onshore 31.26 

Texas Offshore 29.36 

Utah 38.30 

Virginia 9.62 

West Virginia 10.45 

Wyoming 33.74 

Alabama 18.55 

Arizona 38.48 

Arkansas 21.68 

Atlantic Offshore 10.69 

California Onshore 47.66 

Colorado 31.26 

Florida 19.72 

Georgia 13.89 

Illinois 15.24 

Indiana 13.24 

Kansas 27.66 

Kentucky 10.19 

Louisiana Onshore 22.64 

Louisiana Offshore 25.32 

Michigan 11.60 

Mississippi 20.57 

Montana 30.99 

North Dakota 29.97 

MACE 

Nebraska 29.18 
Appendix 6-2.9 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Nevada 43.73 

New Mexico 36.26 

New York 6.45 

Ohio 8.24 

Oklahoma 26.53 

Oregon 47.58 

Pacific Offshore 48.24 

Pennsylvania 5.49 

South Carolina 12.45 

South Dakota 29.27 

Tennessee 13.07 

Texas Onshore 29.00 

Texas Offshore 27.02 

Utah 36.75 

Virginia 7.30 

West Virginia 8.23 

Wyoming 32.43 

Alabama 16.44 

Arizona 36.43 

Arkansas 19.46 

Atlantic Offshore 9.47 

California Onshore 45.76 

Colorado 29.37 

Florida 18.22 

Georgia 12.14 

Illinois 13.21 

Indiana 11.19 

Kansas 25.61 

Kentucky 7.98 

Louisiana Onshore 20.47 

Louisiana Offshore 23.18 

Michigan 10.24 

Mississippi 18.39 

Montana 29.61 

North Dakota 28.61 

Nebraska 27.33 

Nevada 41.79 

New Mexico 34.20 

New York 6.22 

Ohio 6.46 

Oklahoma 24.39 

Oregon 46.05 

Pacific Offshore 46.19 

Pennsylvania 4.10 

South Carolina 10.68 

South Dakota 27.73 

Tennessee 10.85 

MACS 

Texas Onshore 26.78 
Appendix 6-2.10 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Texas Offshore 24.84 

Utah 34.89 

Virginia 5.40 

West Virginia 6.02 

Wyoming 30.75 

Alabama 18.02 

Arizona 36.52 

Arkansas 20.34 

Atlantic Offshore 11.63 

California Onshore 45.53 

Colorado 29.13 

Florida 20.31 

Georgia 14.14 

Illinois 13.33 

Indiana 11.38 

Kansas 25.71 

Kentucky 8.92 

Louisiana Onshore 21.83 

Louisiana Offshore 24.66 

Michigan 9.25 

Mississippi 19.72 

Montana 28.62 

North Dakota 27.60 

Nebraska 27.00 

Nevada 41.62 

New Mexico 34.31 

New York 4.24 

Ohio 6.18 

Oklahoma 24.75 

Oregon 45.23 

Pacific Offshore 46.26 

Pennsylvania 3.35 

South Carolina 12.68 

South Dakota 26.94 

Tennessee 12.01 

Texas Onshore 27.78 

Texas Offshore 26.20 

Utah 34.58 

Virginia 7.16 

West Virginia 7.03 

MACW 

Wyoming 30.15 

Alabama 16.68 

Arizona 29.60 

Arkansas 15.92 

Atlantic Offshore 15.62 

California Onshore 38.19 

MECS 

Colorado 21.83 
Appendix 6-2.11 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Florida 22.17 

Georgia 15.84 

Illinois 7.49 

Indiana 6.33 

Kansas 18.94 

Kentucky 7.85 

Louisiana Onshore 19.10 

Louisiana Offshore 22.23 

Michigan 3.25 

Mississippi 17.07 

Montana 21.14 

North Dakota 20.13 

Nebraska 19.62 

Nevada 34.33 

New Mexico 27.44 

New York 7.11 

Ohio 4.97 

Oklahoma 18.56 

Oregon 37.67 

Pacific Offshore 39.24 

Pennsylvania 7.16 

South Carolina 14.68 

South Dakota 19.37 

Tennessee 10.21 

Texas Onshore 23.33 

Texas Offshore 23.15 

Utah 27.18 

Virginia 10.10 

West Virginia 7.73 

Wyoming 22.60 

Alabama 19.01 

Arizona 19.94 

Arkansas 13.69 

Atlantic Offshore 23.49 

California Onshore 27.89 

Colorado 11.66 

Florida 26.95 

Georgia 21.76 

Illinois 9.29 

Indiana 10.96 

Kansas 10.29 

Kentucky 15.09 

Louisiana Onshore 18.68 

Louisiana Offshore 21.50 

Michigan 11.53 

Mississippi 17.42 

MRO 

Montana 11.90 
Appendix 6-2.12 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

North Dakota 11.07 

Nebraska 9.34 

Nevada 24.07 

New Mexico 17.93 

New York 17.48 

Ohio 14.76 

Oklahoma 11.48 

Oregon 27.61 

Pacific Offshore 29.28 

Pennsylvania 17.42 

South Carolina 21.18 

South Dakota 9.43 

Tennessee 15.05 

Texas Onshore 18.97 

Texas Offshore 21.26 

Utah 16.81 

Virginia 18.68 

West Virginia 16.31 

Wyoming 12.27 

Alabama 23.42 

Arizona 42.41 

Arkansas 26.33 

Atlantic Offshore 14.98 

California Onshore 51.13 

Colorado 34.79 

Florida 24.11 

Georgia 18.58 

Illinois 19.32 

Indiana 17.41 

Kansas 31.63 

Kentucky 14.85 

Louisiana Onshore 27.50 

Louisiana Offshore 30.19 

Michigan 14.53 

Mississippi 25.42 

Montana 33.26 

North Dakota 32.21 

Nebraska 32.59 

Nevada 47.30 

New Mexico 40.21 

New York 8.58 

Ohio 12.16 

Oklahoma 30.77 

Oregon 50.04 

Pacific Offshore 52.11 

Pennsylvania 9.37 

NENG 

South Carolina 17.16 
Appendix 6-2.13 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

South Dakota 31.93 

Tennessee 17.84 

Texas Onshore 33.71 

Texas Offshore 31.88 

Utah 40.15 

Virginia 12.11 

West Virginia 12.91 

Wyoming 35.40 

Alabama 27.91 

Arizona 9.77 

Arkansas 20.78 

Atlantic Offshore 35.44 

California Onshore 14.70 

Colorado 5.96 

Florida 36.36 

Georgia 32.67 

Illinois 21.61 

Indiana 23.58 

Kansas 11.09 

Kentucky 27.62 

Louisiana Onshore 25.29 

Louisiana Offshore 26.89 

Michigan 25.00 

Mississippi 25.18 

Montana 10.32 

North Dakota 10.93 

Nebraska 7.21 

Nevada 10.98 

New Mexico 9.06 

New York 30.95 

Ohio 28.06 

Oklahoma 13.98 

Oregon 15.84 

Pacific Offshore 16.89 

Pennsylvania 30.80 

South Carolina 32.53 

South Dakota 8.96 

Tennessee 26.57 

Texas Onshore 20.66 

Texas Offshore 25.42 

Utah 3.71 

Virginia 31.39 

West Virginia 29.15 

NWPE 

Wyoming 5.44 

Alabama 20.30 

Arizona 39.63 

NYC 

Arkansas 23.21 
Appendix 6-2.14 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Atlantic Offshore 12.36 

California Onshore 48.61 

Colorado 32.22 

Florida 21.44 

Georgia 15.67 

Illinois 16.43 

Indiana 14.47 

Kansas 28.82 

Kentucky 11.72 

Louisiana Onshore 24.35 

Louisiana Offshore 27.05 

Michigan 12.18 

Mississippi 22.27 

Montana 31.39 

North Dakota 30.36 

Nebraska 30.08 

Nevada 44.72 

New Mexico 37.42 

New York 6.46 

Ohio 9.29 

Oklahoma 27.83 

Oregon 48.09 

Pacific Offshore 49.37 

Pennsylvania 6.46 

South Carolina 14.22 

South Dakota 29.83 

Tennessee 14.69 

Texas Onshore 30.58 

Texas Offshore 28.72 

Utah 37.65 

Virginia 9.02 

West Virginia 9.77 

Wyoming 33.13 

Alabama 42.14 

Arizona 20.11 

Arkansas 35.04 

Atlantic Offshore 48.98 

California Onshore 13.81 

Colorado 20.04 

Florida 50.59 

Georgia 46.59 

Illinois 34.78 

Indiana 36.61 

Kansas 25.36 

Kentucky 40.75 

Louisiana Onshore 39.59 

Louisiana Offshore 41.10 

PNW 

Michigan 36.69 
Appendix 6-2.15 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Mississippi 39.46 

Montana 17.43 

North Dakota 18.47 

Nebraska 21.01 

Nevada 14.85 

New Mexico 21.07 

New York 42.34 

Ohio 40.36 

Oklahoma 28.28 

Oregon 3.25 

Pacific Offshore 19.55 

Pennsylvania 42.86 

South Carolina 46.30 

South Dakota 19.07 

Tennessee 40.20 

Texas Onshore 34.51 

Texas Offshore 39.51 

Utah 15.41 

Virginia 44.36 

West Virginia 42.03 

Wyoming 16.74 

Alabama 13.04 

Arizona 28.50 

Arkansas 12.94 

Atlantic Offshore 13.05 

California Onshore 37.78 

Colorado 21.38 

Florida 18.74 

Georgia 12.54 

Illinois 5.27 

Indiana 3.35 

Kansas 17.68 

Kentucky 4.66 

Louisiana Onshore 15.63 

Louisiana Offshore 18.73 

Michigan 5.43 

Mississippi 13.56 

Montana 22.47 

North Dakota 21.53 

Nebraska 19.37 

Nevada 33.79 

New Mexico 26.28 

New York 8.87 

Ohio 4.60 

Oklahoma 16.70 

Oregon 38.47 

Pacific Offshore 38.25 

RFCO 

Pennsylvania 7.40 
Appendix 6-2.16 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

South Carolina 11.52 

South Dakota 20.26 

Tennessee 6.58 

Texas Onshore 20.46 

Texas Offshore 19.79 

Utah 26.91 

Virginia 7.97 

West Virginia 5.45 

Wyoming 23.00 

Alabama 13.89 

Arizona 32.04 

Arkansas 15.58 

Atlantic Offshore 10.62 

California Onshore 41.38 

Colorado 24.98 

Florida 17.85 

Georgia 11.42 

Illinois 8.80 

Indiana 6.79 

Kansas 21.22 

Kentucky 4.32 

Louisiana Onshore 17.34 

Louisiana Offshore 20.29 

Michigan 6.87 

Mississippi 15.22 

Montana 25.71 

North Dakota 24.74 

Nebraska 22.97 

Nevada 37.39 

New Mexico 29.81 

New York 6.63 

Ohio 3.25 

Oklahoma 20.08 

Oregon 41.93 

Pacific Offshore 41.80 

Pennsylvania 4.25 

South Carolina 10.11 

South Dakota 23.65 

Tennessee 7.49 

Texas Onshore 23.05 

Texas Offshore 21.68 

Utah 30.52 

Virginia 5.46 

West Virginia 3.25 

RFCP 

Wyoming 26.52 

RMPA Alabama 23.85 

Arizona 9.55 
Appendix 6-2.17 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Arkansas 16.71 

Atlantic Offshore 31.63 

California Onshore 17.46 

Colorado 3.49 

Florida 32.29 

Georgia 28.72 

Illinois 18.09 

Indiana 20.10 

Kansas 7.05 

Kentucky 24.03 

Louisiana Onshore 21.22 

Louisiana Offshore 22.89 

Michigan 22.12 

Mississippi 21.10 

Montana 11.42 

North Dakota 11.64 

Nebraska 4.18 

Nevada 13.38 

New Mexico 7.86 

New York 28.07 

Ohio 24.84 

Oklahoma 9.92 

Oregon 19.92 

Pacific Offshore 18.51 

Pennsylvania 27.64 

South Carolina 28.64 

South Dakota 8.93 

Tennessee 22.77 

Texas Onshore 16.93 

Texas Offshore 21.49 

Utah 6.49 

Virginia 27.84 

West Virginia 25.67 

Wyoming 6.65 

Alabama 32.28 

Arizona 6.22 

Arkansas 25.26 

Atlantic Offshore 41.46 

California Onshore 7.58 

Colorado 13.07 

Florida 40.30 

Georgia 38.00 

Illinois 28.82 

Indiana 30.84 

Kansas 16.51 

Kentucky 34.55 

SNV 

Louisiana Onshore 28.58 
Appendix 6-2.18 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Louisiana Offshore 29.13 

Michigan 33.30 

Mississippi 29.20 

Montana 19.63 

North Dakota 20.35 

Nebraska 15.37 

Nevada 3.47 

New Mexico 8.34 

New York 39.22 

Ohio 35.81 

Oklahoma 18.42 

Oregon 16.35 

Pacific Offshore 7.40 

Pennsylvania 38.63 

South Carolina 38.20 

South Dakota 18.48 

Tennessee 32.81 

Texas Onshore 21.87 

Texas Offshore 27.10 

Utah 8.50 

Virginia 38.36 

West Virginia 36.31 

Wyoming 14.43 

Alabama 4.18 

Arizona 27.42 

Arkansas 8.43 

Atlantic Offshore 10.90 

California Onshore 37.87 

Colorado 22.64 

Florida 11.34 

Georgia 7.18 

Illinois 9.70 

Indiana 9.30 

Kansas 17.56 

Kentucky 8.20 

Louisiana Onshore 7.81 

Louisiana Offshore 10.55 

Michigan 14.28 

Mississippi 5.77 

Montana 27.31 

North Dakota 26.58 

Nebraska 21.36 

Nevada 33.74 

New Mexico 25.23 

New York 16.41 

Ohio 12.17 

SOU 

Oklahoma 15.13 
Appendix 6-2.19 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Oregon 41.36 

Pacific Offshore 36.88 

Pennsylvania 13.91 

South Carolina 7.47 

South Dakota 24.49 

Tennessee 5.17 

Texas Onshore 14.74 

Texas Offshore 12.18 

Utah 28.01 

Virginia 10.43 

West Virginia 9.83 

Wyoming 25.93 

Alabama 13.64 

Arizona 18.28 

Arkansas 7.41 

Atlantic Offshore 20.61 

California Onshore 28.02 

Colorado 11.97 

Florida 22.01 

Georgia 17.82 

Illinois 7.70 

Indiana 9.68 

Kansas 7.49 

Kentucky 13.26 

Louisiana Onshore 12.47 

Louisiana Offshore 15.15 

Michigan 13.35 

Mississippi 11.49 

Montana 16.91 

North Dakota 16.32 

Nebraska 10.49 

Nevada 23.89 

New Mexico 16.05 

New York 18.80 

Ohio 14.87 

Oklahoma 6.58 

Oregon 30.49 

Pacific Offshore 28.03 

Pennsylvania 17.68 

South Carolina 17.65 

South Dakota 13.92 

Tennessee 11.76 

Texas Onshore 12.94 

Texas Offshore 14.83 

Utah 17.50 

Virginia 17.08 

SPPN 

West Virginia 15.04 
Appendix 6-2.20 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Wyoming 15.10 

Alabama 11.20 

Arizona 17.67 

Arkansas 4.43 

Atlantic Offshore 20.65 

California Onshore 28.28 

Colorado 14.16 

Florida 19.48 

Georgia 16.93 

Illinois 11.33 

Indiana 12.87 

Kansas 8.86 

Kentucky 15.21 

Louisiana Onshore 8.21 

Louisiana Offshore 10.25 

Michigan 17.63 

Mississippi 8.21 

Montana 21.41 

North Dakota 20.99 

Nebraska 13.59 

Nevada 24.13 

New Mexico 15.52 

New York 22.34 

Ohio 18.01 

Oklahoma 5.82 

Oregon 32.92 

Pacific Offshore 27.08 

Pennsylvania 20.64 

South Carolina 17.26 

South Dakota 18.31 

Tennessee 12.63 

Texas Onshore 7.79 

Texas Offshore 9.48 

Utah 19.01 

Virginia 18.71 

West Virginia 17.18 

SPPS 

Wyoming 18.39 

Alabama 8.35 

Arizona 27.00 

Arkansas 9.27 

Atlantic Offshore 11.57 

California Onshore 37.00 

Colorado 21.01 

Florida 14.92 

Georgia 9.38 

TVA 

Illinois 5.89 
Appendix 6-2.21 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Indiana 5.11 

Kansas 16.43 

Kentucky 4.98 

Louisiana Onshore 11.03 

Louisiana Offshore 14.09 

Michigan 10.09 

Mississippi 8.93 

Montana 24.27 

North Dakota 23.45 

Nebraska 19.38 

Nevada 32.90 

New Mexico 24.77 

New York 12.91 

Ohio 8.49 

Oklahoma 14.64 

Oregon 39.25 

Pacific Offshore 36.71 

Pennsylvania 10.73 

South Carolina 8.86 

South Dakota 21.65 

Tennessee 3.25 

Texas Onshore 16.66 

Texas Offshore 15.30 

Utah 26.56 

Virginia 8.43 

West Virginia 6.94 

Wyoming 23.64 

Alabama 10.73 

Arizona 27.75 

Arkansas 11.08 

Atlantic Offshore 12.03 

California Onshore 37.41 

Colorado 21.13 

Florida 16.77 

Georgia 10.78 

Illinois 4.94 

Indiana 3.25 

Kansas 16.98 

Kentucky 3.82 

Louisiana Onshore 13.38 

Louisiana Offshore 16.47 

Michigan 7.71 

Mississippi 11.30 

Montana 23.31 

North Dakota 22.43 

Nebraska 19.30 

TVAK 

Nevada 33.35 
Appendix 6-2.22 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

New Mexico 25.51 

New York 10.73 

Ohio 6.29 

Oklahoma 15.60 

Oregon 38.86 

Pacific Offshore 37.51 

Pennsylvania 8.79 

South Carolina 9.94 

South Dakota 20.88 

Tennessee 4.40 

Texas Onshore 18.59 

Texas Offshore 17.60 

Utah 26.71 

Virginia 7.66 

West Virginia 5.56 

Wyoming 23.27 

Alabama 20.03 

Arizona 36.09 

Arkansas 21.28 

Atlantic Offshore 14.72 

California Onshore 44.58 

Colorado 28.28 

Florida 23.17 

Georgia 16.86 

Illinois 13.43 

Indiana 11.72 

Kansas 25.39 

Kentucky 10.47 

Louisiana Onshore 23.46 

Louisiana Offshore 26.43 

Michigan 7.98 

Mississippi 21.34 

Montana 26.70 

North Dakota 25.66 

Nebraska 26.05 

Nevada 40.78 

New Mexico 33.92 

New York 3.25 

Ohio 6.70 

Oklahoma 24.84 

Oregon 43.46 

Pacific Offshore 45.73 

Pennsylvania 4.90 

South Carolina 15.43 

South Dakota 25.31 

Tennessee 13.63 

Texas Onshore 28.78 

UPNY 

Texas Offshore 27.77 
Appendix 6-2.23 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Utah 33.58 

Virginia 9.76 

West Virginia 8.90 

Wyoming 28.77 

Alabama 10.50 

Arizona 34.30 

Arkansas 15.62 

Atlantic Offshore 4.12 

California Onshore 44.44 

Colorado 28.53 

Florida 11.33 

Georgia 5.19 

Illinois 12.80 

Indiana 11.12 

Kansas 23.89 

Kentucky 7.14 

Louisiana Onshore 14.99 

Louisiana Offshore 17.26 

Michigan 13.65 

Mississippi 13.12 

Montana 31.22 

North Dakota 30.33 

Nebraska 26.88 

Nevada 40.35 

New Mexico 32.07 

New York 12.49 

Ohio 9.80 

Oklahoma 21.89 

Oregon 46.66 

Pacific Offshore 43.93 

Pennsylvania 9.72 

South Carolina 3.74 

South Dakota 28.79 

Tennessee 7.53 

Texas Onshore 22.16 

Texas Offshore 19.21 

Utah 34.09 

Virginia 5.81 

West Virginia 6.77 

VACA 

Wyoming 31.03 

Alabama 14.71 

Arizona 36.20 

Arkansas 18.50 

Atlantic Offshore 7.13 

California Onshore 45.84 

Colorado 29.54 

VAPW 

Florida 15.91 
Appendix 6-2.24 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Georgia 9.93 

Illinois 13.24 

Indiana 11.24 

Kansas 25.45 

Kentucky 7.42 

Louisiana Onshore 18.94 

Louisiana Offshore 21.50 

Michigan 11.51 

Mississippi 16.92 

Montana 30.58 

North Dakota 29.61 

Nebraska 27.61 

Nevada 41.82 

New Mexico 33.96 

New York 8.42 

Ohio 7.43 

Oklahoma 23.95 

Oregon 46.77 

Pacific Offshore 45.95 

Pennsylvania 5.91 

South Carolina 8.48 

South Dakota 28.52 

Tennessee 9.77 

Texas Onshore 25.61 

Texas Offshore 23.29 

Utah 35.10 

Virginia 4.65 

West Virginia 5.67 

Wyoming 31.30 

Alabama 18.36 

Arizona 26.16 

Arkansas 15.53 

Atlantic Offshore 19.56 

California Onshore 34.18 

Colorado 18.00 

Florida 25.05 

Georgia 19.02 

Illinois 7.54 

Indiana 7.86 

Kansas 15.92 

Kentucky 11.21 

Louisiana Onshore 19.69 

Louisiana Offshore 22.81 

Michigan 5.49 

Mississippi 17.89 

Montana 16.61 

WUMS 

North Dakota 15.61 
Appendix 6-2.25 

CO2 Production Region CO2 Storage Region Cost (2007$/Ton) 

Nebraska 15.69 

Nevada 30.42 

New Mexico 24.08 

New York 11.28 

Ohio 9.37 

Oklahoma 16.23 

Oregon 33.18 

Pacific Offshore 35.61 

Pennsylvania 11.68 

South Carolina 18.07 

South Dakota 14.90 

Tennessee 12.58 

Texas Onshore 22.36 

Texas Offshore 23.26 

Utah 23.14 

Virginia 14.13 

West Virginia 11.73 

Wyoming 18.28 

Note: 

Production Regions are equal to IPM model regions 
7-1 

7 Set-up Parameters and Rules 

The EPA Base Case v.4.10 includes a number of assumptions that affect the way IPM treats the 

analysis time horizon, retrofit assignments, and environmental specifications for trading and 

banking. This section provides an overview of those assumptions. 

7.1 Run Year Mapping 

Although IPM is capable of representing every individual year in an analysis time horizon, 

individual years are typically grouped into model run years to increase the speed of modeling. 

While the model makes decisions only for run years, information on non-run years can be 

captured by mapping run years to the individual years they represent. 

The analysis time horizon for EPA Base Case v.4.10 extends from 2012 through 2054 with IPM 

seeking the least cost solution that meets all constraints and minimizes net present values over 

this 43-year period. The six years designated as “model run years” and the mapping of calendar 

years to run years is shown in Table 7-1. 

Table 7-1 Run Years and Analysis Year Mapping Used in the EPA Base Case v.4.10 

Run Year Years Represented 

2012 2012 - 2013 

2015 2014 - 2016 

2020 2017 - 2024 

2030 2025 - 2034 

2040 2035 - 2045 

2050 2046 - 2054 

7.2 Retrofit Assignments 

In IPM, model plants that represent existing generating units have the option of maintaining their 

current system configuration, retrofitting with pollution controls, or retiring early. The decision to 

retrofit or retire is endogenous to IPM and based on the least cost approach to meeting the 

system and other operating constraints included in the EPA Base Case v.4.10. IPM is capable of 

modeling retrofits and early retirements in two stages, enabling model plants to install two different 

sets of retrofits incrementally at different points in time. At each stage a retrofit set may consist of 

a single retrofit (e.g. LSFO Scrubber) or pre-specified combinations of retrofits (e.g., ACI + LSFO 

Scrubber +SCR). In EPA Base Case v.4.10 first stage retrofit options are provided to existing 

coal-steam and oil/gas steam plants. These plants, as well as combined cycle plants, combustion 

turbines, and nuclear plants, are also given early retirement as an option in stage 1. Second 

stage retrofit options are provided to coal-steam plants only. 

Table 7-2 and Table 7-3 present the first and second stage retrofit options respectively. The costs 

of multiple retrofits on the same model plant, whether installed in one or two stages, are assumed 

to be additive. In linear programming models like IPM, projections of pollution control equipment 

capacity and early retirements that can occur over the modeling time horizon are limited to those 

retrofit and retirement options that have been pre-specified when setting up the modeled scenario. 

 While the model decides endogenously whether and how much of each retrofit option to install, it 

cannot provide a retrofit that was not pre-specified before the modeling scenario was run. Table 

7-2 and Table 7-3 show all the retrofit options available in EPA Base Case v.4.10. 
7-2 

Table 7-2 First Stage Retrofit Assignment Scheme in EPA Base Case v.4.10 

Plant Type Retrofit Option 1st Stage Criteria 

Coal Early Retirement All coal steam boilers 

Coal Steam SCR All coal steam boilers that are 25 MW or larger and 

do not possess an existing SCR control option 

Coal Steam SNCR – 

Cyclone Boilers 

All cyclone coal steam boilers that are 25 MW or 

larger and smaller than 100 MW, and do not 

possess an existing post combustion NOx control 

option 

Coal Steam SNCR – Non 

Cyclone Boilers and Non 

FBC Boilers 

All non cyclone and non FBC coal steam boilers 

that are 25 MW or larger and smaller than 100 MW, 

and do not possess an existing post combustion 

NOx control option 

Coal Steam SNCR – FBC 

Boilers 

All coal FBC units that are 25 MW or larger and do 

not possess an existing post combustion NOx

control option 

LSD Scrubber 

All unscrubbed and non FBC coal steam boilers 25 

MW or larger and burning less than 3 lbs/MMBtu 

SO2 coal 

LSFO Scrubber All unscrubbed and non FBC coal steam boilers 25 

MW or larger 

CO2 Capture and Storage All scrubbed coal steam boilers 400 MW or larger 

ACI - Hg Control Option 

(MPAC/ SPAC/ SPAC+ 

Toxecon) 

All coal steam boilers larger than 25 MW that do not 

have an ACI and have an Hg EMF greater than 0.1. 

Actual ACI technology type will be based on the 

boilers fuel and technology configuration. See 

discussion in Chapter 5. 

LSD Scrubber + SCR 

LSD Scrubber + SNCR 

LSFO Scrubber + SCR 

LSFO Scrubber + SNCR 

ACI + SCR 

ACI + SNCR 

ACI + LSD Scrubber 

ACI + LSFO Scrubber 

ACI + LSD Scrubber + 

SCR 

ACI + LSFO Scrubber + 

SCR 

ACI + LSD Scrubber + 

SNCR 

Coal Steam 

ACI + LSFO Scrubber + 

SNCR 

Combination options – Individual technology level 

restrictions apply 

Combined 

Cycle CC Early Retirement All combined cycle units 

Combustion 

Turbine CT Early Retirement All combustion turbine units 

Nuclear Nuclear Early Retirement All nuclear power units 

Oil/Gas Early Retirement All O/G steam boilers 

Oil and Gas 

Steam Oil and Gas Steam SCR 

All O/G steam boilers 25 MW or larger that do not 

possess an existing post combustion NOx control 

option 
7-3 

Table 7-3 Second Stage Retrofit Assignment Scheme in EPA Base Case v.4.10 

Plant Type Retrofit Option 1st Stage Retrofit Option 2nd Stage5

NOx Control Option1

SO2 Control Option and/or Hg 

Control Option and/or CO2 Control 

Option 

SO2 Control Option2

NOx Control Option and/or Hg 

Control Option and/or CO2 Control 

Option 

Hg Control Option3 CO2 Control Option 

CO2 Control Option4 None 

NOx Control Option1 + SO2 Control Option2 Hg Control Option 

NOx Control Option1 + Hg Control Option3 CO2 Control Option 

SO2 Control Option2 + Hg Control Option3 CO2 Control Option 

Coal Steam 

NOx Control Option1 + SO2 Control Option2

+ Hg Control Option3 CO2 Control Option 

Notes: 

1

"NOx Control Option" implies that a model plant may be retrofitted with one of the following NOx

control technologies: 

SCR, SNCR - cyclone, SNCR - non-cyclone, or SNCR - FBC 

2

"SO2 Control Option" implies that a model plant may be retrofitted with one of the following SO2

control technologies: 

LSFO scrubber or LSD scrubber 

3

"Hg Control Option" implies that a model plant may be retrofitted with one of the following 

activated carbon injection technology options for reduction of mercury emissions: 

MPAC, SPAC, or SPAC + Toxecon 

4

"CO2 Control Option" implies that a model plant may be retrofitted with carbon capture and 

storage technology 

5 Retrofits with multiple 2nd stage options may install any combination of the listed options. 

7.3 Trading and Banking 

Four regional or national environmental air regulations included in EPA Base Case v.4.10 involve 

trading and banking of emission allowances47: NOx SIP Call program, the Title IV SO2 program, 

the West Region Air Partnership’s (WRAP) program regulating SO2 (as part of the federal 

Regional Haze Rule), and the Regional Greenhouse Gas Initiative (RGGI) for CO2. Table 7-4 

below summarizes the key parameters of these four trading and banking programs as 

incorporated in EPA Base Case v.4.10. Trading and banking are modeled on a U.S. system-wide 

basis for the Title IV SO2 program and on a regional basis for the other three programs. EPA 

Base Case v.4.10 does not include any explicit assumptions on the allocation of emission 

allowances among model plants under any of the four programs.

 

47For a detailed discussion of the assumptions of all the environmental air regulations included in 

the EPA Base Case v.4.10, see chapter 3. 
7-4 

Table 7-4 Trading and Banking Rules in EPA Base Case v.4.10 

 

SIP Call - 

Ozone 

Seasons NOx

Title IV - SO2 WRAP- SO2 RGGI - CO2

Coverage All fossil units 

> 25 MW1

All fossil units 

> 25 MW 

All fossil units 

> 25 MW2

All fossil units 

> 25 MW3

Timing 

Ozone Season 

(May - 

September) 

Annual Annual Annual 

Size of 

Initial Bank 

The bank 

starting in 2012 

is assumed to 

be zero 

The bank starting 

in 2012 is 

assumed to be 11 

million tons 

The bank 

starting in 2018 

is assumed to 

be zero 

The bank starting in 

2012 is assumed to 

be zero 

Total 

Allowances 

(MTons) 

2012 - 2054: 

527.5 

2012: 19,679

2013: 8,407

2014: 8,397

2015: 8,327

2016: 8,312

2017: 8,287

2018: 8,169

2019: 8,155

2020 - 2054: 8,153 

2018 - 2054: 

144.7 

2012 - 2014: 188,077

2015: 183,375

2016: 178,673

2017: 173,971

2018 - 2054: 169,269 

Notes: 

1

 Alabama, Connecticut, Delaware, District of Columbia, Illinois, Indiana, Kentucky, Maryland, 

Massachusetts, Michigan, Missouri, New Jersey, New York, North Carolina, Ohio, 

Pennsylvania, Rhode Island, South Carolina, Tennessee, Virginia, West Virginia 

2

 Arizona, New Mexico, Oregon, Utah, Wyoming 

3

 Connecticut, Delaware, Maine, New Hampshire, New Jersey, New York, Vermont, Rhode 

Island, Massachusetts, Maryland 

7.4 Post-2030 Modeling Assumptions and Capabilities 

Previous EPA base cases had at most a usable modeling time horizon out to year 2030. EPA 

Base Case v.4.10 has the capability to model out to 2050. However, bottom up models like IPM, 

which is used to build the EPA base case, require input data at the finest possible level of 

granularity. Preferably, such data would be based on gathered information obtained through 

regulatory submittals, surveys, and scientific, engineering, economic, and commercial 

assessments specifically related to the particular characteristics of the issue being modeled. Past 

2030 or 2035 such information is rarely available. 

As a result, a two tiered approach was taken to the inputs used to build EPA Base Case v.4.10. 

Prior to 2030 assumptions would be based to the greatest extent possible on verifiable empirical 

data gathered from the best available sources vetted using cross-checks against alternative data 

sources. Beyond 2030 a pragmatic approach was taken. Where credible empirical data was 

available, it would be used. Where empirical data was not available, technically plausible, 

explicitly articulated assumptions would be used to extrapolate pre-2030 assumptions out to 2050. 

 While perhaps not optimal, such an approach was seen as potentially valuable, if only because it 

would focus attention on the long-range assumptions needed for bottom-up modeling and, in 

doing so, elicit comments from the interested public and technical experts. This could lead to 

future improvements in the long-range inputs with possible side benefits for all projections whether 

based on bottom-up, top-down or hybrid modeling approaches. 

A corollary of this two tiered approach to input assumptions is that the modeling results past 2030 

should be viewed somewhat differently from those prior to 2030. The pre-2030 modeling results 
7-5 

are expected to bear scrutiny at a fine level of granularity (answering questions like the plausibility 

of a particular generating unit being retrofit with a dry SO2 scrubber and a SCR in a particular 

model run year or of another generating unit being retired by IPM in a certain year). 

The post-2030 modeling results are not intended to be examined at such a fine grain level. 

Instead, the post-2030 modeling capability is designed to serve two purposes: The first purpose is 

to ensure that EPA Base Case v.4.10 takes into account the potential impact of post-2030 policy 

provisions on pre-2030 modeling results. For example, it would be useful to have the capability to 

project the impact on pre-2030 modeling results of a provision in a Climate Change bill that takes 

effect in 2042. The second purpose is to give a broad sense of directional trends beyond 2030. 

For example, using current technology cost and performance assumptions, the long-range 

modeling capability could provide a picture of the likely composition of the power sector in 2040 or 

2050 with and without policy intervention. To take fuller advantage of this capability, five generic 

placeholder future generation technologies have been included in EPA Base Case v.4.10. While 

not playing a role in the base case itself, their presence allows a user to define their cost and 

performance characteristics at a later time and to perform sensitivity analysis to see the possible 

impact of new technologies on post-2030 trends. 

Table 7-5 shows the underlying post-2030 modeling assumptions incorporated in EPA Base Case 

v.4.10 for key modeling parameters. 

Table 7-5 Post-2030 Assumptions in EPA Base Case v.4.10 

Topic Post-2030 Assumptions 

POWER SYSTEM OPERATION 

Model Regions Same as pre-2030 

Electric Load Modeling 

 Electric Load Growth Post 2035 growth rate is based on AEO 

2010 2025-2035 growth rate 

 Net Internal Demand (Peak Demand) Post 2035 growth rate is based on AEO 

2010 2025-2035 growth rate 

 Load Duration Curves (LDCs) 

2007 load curves adjusted to post 2030 

energy and peak load projections. LDCs 

include six segments per season in run 

years 2012, 2015, 2020, and 2030 and 

four segments in 2040 and 2050. 

Transmission 

 Interregional Transmission Capability Same as pre-2030 

 Transmission Link Wheeling Charge Same as pre-2030 

 Transmission Losses Same as pre-2030 

International Imports 

 Mexico Same as 2030 

 Canada Endogenously Modeled 

Capacity, and Dispatch 

 Availability 

Same as pre-2030 for all plant types 

except nuclear 

Same as 2030 for nuclear 

 Capacity Factor Same as 2030 

 Turndown Same as pre-2030 

Reserve Margins Same as pre-2030 

Power Plant Lifetimes Same as pre-2030 

Existing Environmental Regulation 

 SO2 Regulations Same as 2030 
7-6 

Topic Post-2030 Assumptions 

 NOx Regulations Same as 2030 

 State Specific Environmental Regulations Same as 2030 

 New Source Review (NSR) Same as 2030 

 Emission Assumptions for Potential (New) Units Same as pre-2030 

Capacity Deployment Constraints Run year specific 

GENERATING RESOURCES 

National Electric Energy Data System (NEEDS) Same as pre-2030 

Existing Units and Planned/Committed Units 

 Population of Existing Units Same as pre-2030 

 Capacity Same as pre-2030 

 Plant Location Same as pre-2030 

 Online Year Same as pre-2030 

 Unit Configuration Same as pre-2030 

 Model Plant Aggregation Same as pre-2030 

 Cost and Performance of Existing Units Same as pre-2030 

 Heat Rates Same as pre-2030 

 NOx Rates Same as pre-2030 

Potential Units 

 Cost and Performance of Potential Conventional 

Technologies Same as pre-2030 

 Cost and Performance of Potential Renewable 

Technologies 

 Biomass Same as 2030 

 Wind Same as 2030 

 Solar Same as 2030 

 Geothermal Same as pre-2030 

 Landfill Gas Same as 2030 

 Short Term Cost Adder None 

 Regional Adjustment Factor Same as pre-2030 

Nuclear Units 

 Existing Nuclear Units 

 VOM and FOM Cost Assumptions for 

Nuclear Units 

Same as pre-2030 (adjusted for life 

extension costs) 

 Nuclear Upratings (MW) None 

 Nuclear Scheduled Retirements (MW) Retirement at age 60 years 

 Potential Nuclear Units Same as 2030 

EMISSION CONTROL TECHNOLOGIES 

Sulfur Dioxide Control Technologies 

 Limestone Forced Oxidation (LSFO) Same as pre-2030 

 Lime Spray Drying (LSD) Same as pre-2030 

 FGD Engineering Cost Equations Same as pre-2030 

Nitrogen Oxides Control Technology 

 Combustion Controls Same as pre-2030 

 Post-combustion Controls Same as pre-2030 

 SCR and SNCR Engineering Cost Equations Same as pre-2030 

Mercury Control Technologies 

 Mercury Content of Fuels Same as pre-2030 
7-7 

Topic Post-2030 Assumptions 

 Mercury Emission Modification Factors Same as pre-2030 

 Mercury Control Capabilities Same as pre-2030 

 ACI Engineering Cost Equations Same as pre-2030 

CO2 Sequestration 

 CO2 capture Same as pre-2030 

 CO2 transport Same as pre-2030 

 CO2 storage cost curves Same as pre-2030 

SETUP PARAMETERS AND RULES 

Run Year Mapping Run year specific 

Retrofit Assignments Same as pre-2030 

FINANCIAL ASSUMPTIONS 

Methodology 

 Capital Charge Rates for Investments Same as 2030 

 Discount Rate for Capital and Non-Capital Costs Same as pre-2030 

FUEL ASSUMPTIONS 

Coal 

 Coal Markets Same as pre-2030 

 Coal Supply Curves 2030 cost-adjusted for labor productivity 

 Coal Transportation Costs 2030 cost-adjusted for fuel price changes 

 Coal Assignments Same as pre-2030 

 Emission Factors Same as pre-2030 

Natural Gas 

 Resources Data and Reservoir Description 

 Field Development and Production Forecast 

Methodology Same as pre-2030 

 Lower 48 States U.S. Resources Same growth as pre-2030 

 Canada Resources Same growth as pre-2030 

 Treatment of Frontier Resources Alaska North Slope starts 2040 

 Exploration and Production (E&P) Technology 

Characterization Same as 2030 

 End Use Demand Characterization Same growth as pre-2030 

 Pipeline and Transport 

 Existing pipelines Same as pre-2030 

 Potential pipeline costs Same growth as pre-2030 

 Emission Factors Same as pre-2030 

Fuel Oil 

 Prices Same as 2035 

 Emission Factors Same as pre-2030 

Biomass 

 Biomass Supply Curves Same as 2035 

 Emission Factors Same as pre-2030 

Nuclear Fuel Prices Same as 2030 
8-1 

8 Financial Assumptions 

This chapter presents the financial assumptions used in EPA Base Case v.4.10. The first section 

gives a summary of each of the key financial parameters. The remainder of the chapter presents 

an in-depth explanation of the theoretical underpinnings and methods used to develop the two 

most important financial parameters – the discount rate and capital charge rate. 

8.1 Summary of Key Financial Parameters 

8.1.1 Capital Charge Rate, Book Life, and Discount Rate for Capital Expenditures 

EPA Base Case v.4.10 models a diverse set of generation and emission control technologies, 

each of which requires financing.1

 Table 8-1 presents the capital charge rate, discount rate, and 

book life assumptions for the technologies in base case v.4.10. As will be discussed more fully 

later in this chapter, the capital charge rate is used to convert the capital cost of a technology into 

a stream of levelized annual payments that ensure capital recovery. The discount rate is used to 

translate future cash flows into current dollars by taking into account factors (like inflation and the 

ability to earn interest), which make one dollar tomorrow worth less than one dollar today. The 

discount rate allows inter-temporal tradeoffs and represents the risk adjusted time value of money. 

 The book life is the payback period on an investment. 

There are several things to note about Table 8-1. The technology differentiated capital charge 

rates are used in v.4.10 to derive the associated capital charge rates shown in the table. 

However, while the technology-differentiated discount rates appearing in the table were used in 

deriving these capital charge rates, in EPA Base Case v.4.10 a single U.S. discount rate of 6.15% 

is used across all technologies.

 

1

 The capital charge rates discussed here apply to new (potential) units and environmental 

retrofits that IPM installs. The capital cost of existing and planned/committed generating units and 

the emission controls already on these units are considered “sunk costs” and are not represented 

in the model. 
8-2 

Table 8-1 U.S. Discount Rates and Capital Charge Rates in EPA Base Case v4.10 

Investment Technology Capital 

Charge Rate 

Discount 

Rate 

Book 

Life 

Environmental Retrofits 11.3% 5.5% 30 

Advanced Combined Cycle 12.1% 6.2% 30 

Advanced Combustion Turbine 12.9% 6.9% 30 

Supercritical Pulverized Coal and Integrated Gasification 

Combined Cycle without Carbon Capture1 14.1% 7.8% 40 

Advanced Coal with Carbon Capture 11.1% 5.5% 40 

Nuclear without Production Tax Credit (PTC) 10.8% 5.5% 40 

Nuclear with Production Tax Credit (PTC)2 9.1% 5.5% 40 

Biomass with ARRA Loan Guarantees3 9.3% 4.6% 40 

Biomass without ARRA Loan Guarantees 11.1% 6.2% 40 

Wind and Landfill Gas with ARRA Loan Guarantees2 10.1% 4.6% 20 

Wind and Landfill Gas without ARRA Loan Guarantees 12.2% 6.2% 20 

Solar and Geothermal with ARRA Loan Guarantees2 10.1% 4.6% 20 

Solar and Geothermal without ARRA Loan Guarantees 12.2% 6.2% 20 

Notes:

The discount rates appearing in the table were used in deriving these capital charge rates. 

However, as noted in the text, a single U.S. discount rate of 6.15% is used across all 

technologies in EPA Base Case v.4.10. 

1

The capital charge rate for these technologies includes a 3% climate change uncertainty 

adder. (See text.) 

2

The capital charge rate for this technology reflects the impact of the PTC provided under the 

Energy Policy Act of 2005. (See text.) 

3

The capital charge rate for these technologies reflects the impact of ARRA loan guarantees. 

(See text.) 

Capital Cost Adder for Climate Change Uncertainty: Adopting the procedure followed in EIA’s 

Annual Energy Outlook 2010, the capital charge rates shown in Table 8-1 for Supercritical 

Pulverized Coal and Integrated Gasification Combined Cycle (IGCC) without Carbon Capture 

include a 3% adder to the cost of debt and equity (see section 8.2.3 for discussion of debt and 

equity). This capital cost adder reflects increased financing costs for investment decisions 

involving coal plants without carbon capture caused by uncertainty surrounding possible future 

climate change policies that could limit CO2 emissions from the power sector 

ARRA Loan Guarantees for Renewables and Biofuels: The American Recovery and 

Reinvestment Act (ARRA) of 2009 (Public Law 111-5) provides loan guarantees for renewables 

and biofuels. Following the procedure implemented in AEO 2010, these loan guarantees are 

reflected in a reduction of 2% in the cost of debt and equity for biomass, wind, landfill gas, solar, 

and geothermal technologies. Capital charge rates with and without the 2% reduction appear in 

Table 8-1 because the loan guarantees expires in 2016. 

Energy Policy Act Production Tax Credit for Nuclear: The Energy Policy Act of 2005 

(Sections 1301, 1306, and 1307) provides a production tax credit (PTC) of 18 mills/kWh for 8 

years up to 6,000 MW of new nuclear capacity. The financial impact of the credit is reflected in 

the capital charge rate shown in Table 8-1 for “Nuclear with Production Tax Credit (PTC).” 

8.1.2 ARRA Production and Investment Tax Credit (PTC and ITC) for Renewables 

In addition to the loan guarantees that are reflected in the capital charge rates for renewables 

shown in Table 8-1, ARRA 2009 (Division B, Title I, Sec. 1101, 1102, and 1603) also provides 

extensions of the PTC and 30 percent ITC to renewables. These are represented in EPA Base 

Case, v.4.10 as a 30% reduction in the capital cost of these technologies in 2012. 
8-3 

8.1.3 Discount Rate for Non-Capital Expenditures 

The discount rate for non-capital expenditures (e.g., annual fuel, variable operations and 

maintenance, and fixed operations and maintenance costs) in EPA Base Case v.4.10 is assumed 

to be 6.15%. This serves as the default discount rate for all non-capital expenditures. 

8.1.4 Inter-temporal Allowance Price Calculation 

Under a perfectly competitive cap-and-trade program that allows banking, the allowance price 

always increases by the discount rate between periods if affected sources have allowances 

banked between those two periods. This is a standard economic result for cap-and-trade 

programs and prevents sources from profiting by arbitraging allowances between two periods. 

The EPA Base Case v.4.10 uses the default discount rate of 6.15 percent in computing the 

increase in allowance price for cap-and-trade programs when banking is engaged as a 

compliance strategy. 

8.1.5 Nominal and Real Dollars 

EPA Base Case v.4.10 uses real 2007 dollars as its real dollar baseline. See Chapter 2 for further 

discussion on how IPM uses the real dollars for inter-temporal analysis. 

8.2 Development of the Financial Assumptions for EPA Base Case v.4.10 

This section explains the method used to derive the capital charge rate and discount rate as well 

as the assumptions underlying these financial parameters. 

8.2.1 Introduction 

As noted in section 8.1, the discount rate and the capital charge rate are the two parameters that 

encapsulate the financing assumptions for an investment option in EPA Base Case, v.4.10. The 

discount rate allows inter-temporal tradeoffs and represents the risk adjusted time value of money. 

 The capital charge rate is used to convert the capital cost into a stream of levelized annual 

payments that ensures capital recovery of an investment. 

Discount Rate 

The discount rate is a function of the following parameters: 

• Capital structure (Share of Equity vs. Debt) 

• Post-tax cost of debt (Pre-tax cost of debt*(1-tax rate)) 

• Post-tax cost of equity 

The weighted average cost of capital (WACC) is used as the discount rate and is calculated as 

follows: 

 WACC = [Share of Equity * Cost of Equity] 

 + [Share of Preferred Stock * Cost of Preferred Stock] 

 + [Share of Debt *After Tax Cost of Debt] 

The focal point is on debt and equity (common stock) because preferred stock is generally a small 

share of capital structures. 

Capital Charge Rate 

The capital charge rate is a function of the parameters that overlap in part with the discount rate, 

but also include parameters related to the amortization of capital: 

• Capital structure (Debt/Equity shares of an investment) 

• Pre-tax debt rate (or interest cost) 

• Debt Life 
8-4 

• Post-tax Return on Equity (ROE) (or cost of equity) 

• Other costs such as property taxes and insurance 

• State and Federal corporate income taxes 

• Depreciation Schedule 

• Book Life 

The capital charge rate is calculated by solving for earnings before interest, taxes, and 

depreciation (EBITDA) or pure operating earnings such that the project is able to recover the cost 

of equity as the internal rate of return over the lifetime of the project. The sum of discounted cash 

flows to the equity holders over the lifetime of the project, discounted at the cost of equity is set 

equal to the initial investment. The capital charge rate so calculated is defined as follows: 

• Capital Charge Rate = EBITDA/Total Investment 

In other words, the capital charge rate is the rate of return required on invested capital, resulting 

from pure operations. 

8.2.2 Method for Deriving Discount Rate and Capital Charge Rate in EPA Base Case v 4.10 

Introduction to Risk 

The risk of an investment in the power sector is heavily dependent on market structure risks. The 

range of risks has increased due to deregulation which has resulted in approximately 35 percent 

to 40 percent of capacity being deregulated IPP (Independent Power Producer) capacity. For 

example, merchant IPP's selling into spot market have more market risk than regulated plants or 

IPP’s having long-term, known-price contracts with credit worthy counter parties. There are also 

technology risks and financing structure risks (corporate vs. project financings). Lastly, there is 

financial risk related to the extent of leverage. 

The risk, especially to the extent it is correlated with overall market conditions, is an important 

driver of financing costs. Other risks are handled in the cash flows and are treated as noncorrelated with the market. This emphasis on correlated market risk is based on the Capital Asset 

Pricing model and associated financial theory. This analysis takes into account differences in 

technology and market structure risks. 

Differences between corporate and project financings are highlighted but no specific adjustment 

has been made for them. 

Market Structure Risks 

The power sector in North America can be divided into the traditional regulated sector (as known 

as “cost of service” sector) and deregulated merchant sector (as known as “competitive” sector). 

• Traditional Regulated - The traditional regulated market structure is typical of the vertically 

integrated utilities where generation (and transmission and distribution, abbreviated T&D) 

investments are approved through a regulatory process and the investment is provided a 

regulated rate of return. Returns on investment in this form of market structure are cost plus 

regulated returns that are administratively determined. Returns are affected by market 

conditions due to regulatory lag and other imperfections in the process, but overall are less 

exposed to the market than deregulated investments, all else equal. In this report, we use the 

term “utility financing” to refer to this type of market structure. A closely related market 

structure is the situation where a plant is built under a power purchase agreement (PPA) with 

a utility with known pricing that allows for a very high degree of investment amortization during 

the contract period. In such an arrangement, the risks are more credit and performance 

related and much less market related. 

• Deregulated Merchant - In a deregulated merchant market structure, investments bear the 

full or a very high degree of market risk as the price that they can sell electricity at is 

dependent on what the short-term markets will bear. Return on investment in this form of 

market structure is not only dependent on the state of the economy, but also on commodity 
8-5 

prices, as well as on capital investment cycles and remaining price related regulation, e.g., 

FERC price caps on capacity prices. The capital investment cycle can create a “boom and 

bust” cycle which imparts source risk or uncertainty to the sector. The operational cash flows 

from investments in this sector are more volatile as compared to in the traditional regulated 

sector, and hence, carry more business or market risk. In this report, we use the term 

“merchant financing” to refer to this type of market structure. 

Technology Risks 

The selection of new technology investment options is partially driven by the risk profile of these 

technology investments. For instance, in a deregulated merchant market, an investment in a 

combustion turbine is likely to be much more risky than an investment in a combined cycle unit 

because while a combustion turbine operates as a peaking unit and is able to generate revenues 

only in times of high demand, a combined cycle unit is able to generate revenues over a much 

larger number of hours in a year. An investor in a combined cycle unit, therefore, would require a 

lower risk premium than an investor in a combustion turbine. 

Financing Structure Risks and Approach 

While investments in new units differ based on market structure and technology risks, differences 

also may occur because of financing schemes available. There are two major types of financing 

schemes: 

• Corporate finance is a category of financing where a developer raises capital on the strength 

of the balance sheet of a company rather than a single project. In this type of financing, the 

debtors have recourse to the entire company’s assets. 

• Project finance, as this category of financing is often labeled, allows developers to seek 

financing using only the project as recourse for the loan. For instance, a project developer 

may wish to develop a new combined cycle unit, but will seek to use project financing in such 

a way that if it defaults on the loan, debtors have recourse only to the project itself and not 

against the larger holdings of the project developer. This approach can be more risky than 

corporate finance, all else being equal, because there is less diversification than the 

corporation which can be thought as a collection of projects. However, there are some 

projects more suitable for project financing because: (1) they may have a self-sustaining 

revenue stream that is greater than the corporate average, or (2) risk is reduced through a 

long-term PPA with a credit worthy counterparty such as a vertically integrated utility or a 

regulated affiliate of a merchant company. 

There are many benefits of a project financing structure but there are also costs associated with it. 

 A project financing structure typically has higher transaction costs (and even higher debt costs as 

debt financing is largely privately placed), but it also solves some of the agency problems and 

underinvestment issues that corporate financed structures face1. 

However, as noted above, this analysis does not make an effort to quantify the relative costs and 

benefits of one structure over the other. Rather, the approach used is based on the premise that 

regardless of financial structure, each project has its own risks based on market structure and 

technology. Further, because corporate financing is more observable than project financing2 and 

has evolved in the power sector to the level of making key risk inferences possible (e.g., IPP and 

utility stock trades), assessment of market correlated risks should be based on IPP and utility 

corporate financing. 

 

1

 For more information on project financing, see paper titled “The Economic Motivations for Using 

Project Finance” by Benjamin C. Esty, Harvard Business School, Feb 2003 

2

Project Financing data is less observable as it’s not explicitly traded. Also, often key financing 

parameters are unavailable due to confidentiality reasons. 
8-6 

Approach to Market Structure Risk 

In EPA Base Case 4.10, a hybrid financing model is used, i.e., it is assumed that future 

development activity would be roughly evenly split between utility financings and pure merchant 

financings. This is designed to reflect a shift in the market in ownership and risk profiles for power 

generation assets, and recent development trends and emphasis on long term contracts3. In this 

approach, for modeling purposes, we assume that new units are financed as a weighted average 

of utility and merchant financing parameters. For new units we assume that both utility and 

merchant components get equal weights. For retrofits, we assume that utility component gets 2/3 

and merchant component gets 1/3 weight4. 

• Example 1: The debt to equity capital structure of a combustion turbine is 55/45 under utility 

financing and 30/70 under merchant financing. Under the assumption that utility and 

merchant components get equal weights, the debt to equity ratio under hybrid financing is D = 

(55 + 30)/2 = 42.5 / E = (45 + 70)/2 = 57.5. 

• Example 2: The debt to equity capital structure of a retrofit is 55/45 under utility financing and 

45/55 under merchant financing. Under the assumption of a 2/3, 1/3, utility/merchant 

weighting, the debt to equity ratio under hybrid financing is D = (55 * 2/3) + (45 * 1/3) = 51.6 / 

E = (45 * 2/3) + (55 * 1/3) = 48.3. A full summary for all technologies appears in Table 8-2 

below. 

Capital Charge Rate – A More Detailed Description 

The capital charge rate is calculated by solving for earnings before interest, taxes, and 

depreciation (EBITDA) or pure operating earnings such that the project is able to recover the cost 

of equity as the internal rate of return over the lifetime of the project. The sum of discounted cash 

flows to the equity holders over the lifetime of the project, discounted at the cost of equity is set 

equal to the initial investment. The capital charge rate so calculated is defined as follows: 

Table 8-2 Capital Structure Assumptions for EPA Base Case v4.10 

Technology Utility Merchant Hybrid 

Combustion Turbine 55/45 30/70 42.5/57.5 

Combined Cycle 55/45 45/55 50/50 

Coal & Nuclear 55/45 60/40 57.5/42.5 

Renewables 55/45 45/55 50/50 

Retrofits 55/45 45/55 51.7/48.3 

• Capital Charge Rate = EBITDA/Total Investment 

In other words, the capital charge rate is the rate of return required on invested capital, resulting 

from pure operations. 

 

3

An alternate approach is to categorize the United States into the two previously discussed 

financial regions – Cost-of-service and competitive. The cost-of-service region will have capital 

charge rates based on utility financial assumptions and the competitive region will have capital 

charge rates based on merchant financial assumptions. Such an approach could result in 

overbuilding in the cost-of-service region due to lower capital charge rates in the absence of 

regulatory prohibitions or external sales. This is similar to the public vs. IOU financing arbitrage 

problem, i.e. what stops government utilities from supplying all power? In fact, there are formal 

and informal limits, and because fully characterizing these limits is extremely complex, a hybrid 

approach is used. 

4

Retrofits are largely associated with coal fired plants and most coal fired plants are currently 

owned and operated by utilities in a “utility financing” structure. Moreover, since the magnitude of 

the retrofit investment is not as large as a plant investment, the financing of a retrofit is more likely 

to happen from a firm’s internal cash flows instead of external financing. 
8-7 

The discounted cash flow to the equity holders of the project is characterized in terms of the Free 

Cash Flow to Equity (FCFE). FCFE is a valuation technique to estimate cash flows paid to the 

equity shareholders of a company after all expenses, reinvestment, and debt repayment have 

been made. The FCFE approach is suited for valuation of assets that have finite economic lives 

and where debt levels vary from year to year. In the FCFE approach, it is assumed that the asset 

has a finite life and debt reduces over time based on a mortgage-style repayment structure. 

Specifically the cash flows to the equity5 are calculated as follows: 

Cash Flows to Equity = EBIT (1-tax rate) 

 - Interest (1-tax rate) 

 + Depreciation 

 - Capital Expenditures 

 - Working Capital Change 

 - Principal Payments 

 + New Debt Issued 

Discount Rates and Capital Charge Rates 

Based on the above approach, the discount rates and capital charge rates summarized in Table 

8-1 above were obtained for investments in the U.S. The procedures and assumptions used to 

calculate the rates in Table 8-1 are discussed in the sections below. 

8.2.3 Calculation of the Hybrid Capital Charge Rates 

ROE 

The first step was the calculation of a return on equity (ROE) using an average ROE under utility 

financing (10.3%) and merchant financing (15.2%) assuming a 50:50 debt/equity ratio. This 

resulted in a ROE of 12.75%6. This ROE is kept the same across each technology7 but the risk 

differences across technologies are implemented through the capital structure. See the discussion 

of capital structures in this subsection under “Debt Equity Share” and the discussion of “Debt and 

Equity Shares and Technology Risk” in section 8.2.4. 

Note that a 50:50 mix (corresponding to the hybrid capital structure for a combined cycle – see 

Table 8-2) has been chosen. This is because we assumed that the overall IPP risk was on 

average reflective of the risk profile of combined cycle units which in turn was assumed to be 

intermediate between base load and peaking. The combined cycle technology is considered to 

have “average” market risk being an intermediate type technology. Also, in the aggregate, the five 

selected IPP companies8

 have more combined cycle capacity in their supply mix than any other 

technology. Additionally, going forward, it is expected that gas will continue to play an 

increasingly important role in the supply mix of both utilities and merchant companies, with 

combined cycle technology playing a dominant role. For all of these reasons, it was considered 

appropriate to use the ROE corresponding to a combined cycle facility. 

 

5

An alternative definition of free cash flow to equity is as follows: Net Income + Depreciation – 

capital expenditures – working capital change – Principal Payments + New Debt Issued 

6

The Pennsylvania-New Jersey-Maryland Interconnection (PJM) uses a 12% ROE for a combined 

cycle at a 50:50 debt/equity ratio to calculate the cost of new entry (CONE) for their capacity 

markets. Hence, the estimates are fairly close to those used by a major RTO. 

7

Even though ROE is kept the same across all technologies, it doesn’t mean that the market risks 

are considered the same for each technology. See capital structure discussion in the next 

paragraph. 

8

Our merchant parameters are derived from market observations of five IPP companies – see 

discussion on development of merchant financed parameters. 
8-8 

Debt Equity Share 

Second, the capital structures (D/E)9 for the various technology types were calculated using an 

average of utility and merchant financing. The utility debt capacity (and returns) is assumed to be 

independent of technology type based on the theoretical assumption that regulation will provide an 

average return to the entire rate base. The merchant debt capacity is based on market risk where 

a base load plant is likely to have a higher debt capacity than a combustion turbine plant. Table 

8-2 presents the capital structure assumptions used in EPA Base Case v4.10. 

The risk differences across technologies are implemented by varying the capital structure. As 

shown in Table 8-2 and discussed above, a peaking unit such as a combustion turbine is 

estimated to have a capital structure of 42.5/57.5 while a base load unit such as nuclear and coal 

is assumed to have a capital structure of 57.5/42.5. This is based on the intuition that less risky 

technologies can carry more leverage. As debt is less expensive than equity, this will 

automatically translate into a lower capital charge rate (and a lower discount rate) for base load 

technologies and a higher capital charge rate (and a higher discount rate) for peaking technology, 

assuming other components of the capital charge rate calculation remain the same. 

Cost of Debt 

Third, the cost of debt was adjusted to reflect the average cost of debt for utility and merchant 

financings for each technology. The utility cost of debt is assumed to be the same across all 

technologies while the merchant cost of debt is higher than utility and is higher for a combustion 

turbine unit than for a combined cycle or a coal plant. Table 8-3 summarizes the debt rates used 

in EPA Base Case v4.10. 

Table 8-3 Debt Rates for EPA Base Case v4.10 

Technology Utility Merchant Hybrid 

Combustion Turbine 6.25% 9% 7.63% 

Combined Cycle 6.25% 8% 7.13% 

Coal & Nuclear 6.25% 8% 7.13% 

Wind 6.25% 8% 7.13% 

Retrofits 6.25% 8% 6.83% 

 

These financing parameters were then combined with taxation assumptions and technology 

specific assumptions on depreciation, book life and debt life to yield the capital charge rates 

outlined in Table 8-1 above. 

8.2.4 Development of Merchant Financing Parameters 

Merchant ROE 

The Independent Power Producer (IPP) return on equity parameter was estimated to be 15.2%10. 

This was based on empirical analysis of stock price data of five pure play comparable merchant 

generation companies, namely Reliant, NRG, Dynegy, Mirant, and Calpine. First, levered betas11

(a measure of total corporate risk which includes business and financial risk) for the five 

companies were calculated using five years of historical stock price data. Second, unlevered 

betas (a measure of business risk, i.e., those affected by a firm’s investment decisions) were 

 

9

A project’s capital structure is the appropriate debt capacity given a certain level of equity, 

commonly represented as “D/E,” i.e., debt/equity. The debt is the sum of all interest bearing short 

term and long term liabilities while equity is the amount that the project sponsors inject as equity 

capital. 

10Merchant ROE, as additionally observed by EIA, have risen over time. 

11Levered beta is directly measured from the company’s stock returns with no adjustment made 

for the debt financing undertaken by the company. It is also known as equity beta. Hence, levered 

beta incorporates both business and financing risk undertaken by the company. 
8-9 

calculated using the estimated levered beta, the companies’ market debt/equity ratio, and the 

riskiness of debt. As most comparables historically had periods of financial distress, the 

unlevering12 approach was modified to include the riskiness of debt, instead of purely using the 

Hamada equation.13 The unlevered betas were then relevered14 at the target debt/equity ratio of 

50/50 to get the relevered equity betas and return on equity. The return on equity was determined 

using the Capital Asset Pricing Model (CAPM). 

The CAPM parameters used to estimate the ROE are as follows: 

• Risk Free Rate based on 20 year T bond rate: 4.9%15

• Market Risk Premium 1926-200616: 7.1% 

• Size Premium: 0.65%17

The estimation of the IPP ROE described here is fairly close to what EIA has published. EIA 

estimates a 2010 ROE of roughly 14.8% at a D/E ratio of 45/55 and increasing to approximately 

16% by 2012.18

Merchant Cost of Debt 

The cost of debt for the merchant sector was computed assuming an average 3-month LIBOR 

(London Interbank Offered Rate) of 4.9-5% and an average spread of 3% reflecting the low 

medium grade or low grade nature of merchant bonds. An additional one percent spread was 

assumed for combustion turbine units due to the high price risk for combustion turbine units. 

Debt and Equity Shares and Technology Risk 

The capitalization structure for merchant financings was estimated to be 45/55 based on empirical 

analyses. This capitalization structure was assumed to be on average reflective of the combined 

cycle for reasons discussed earlier in this document. 

Each generation technology was considered to have its own risk profile. Some evidence indicated 

that the greater the base load share, the lower the asset risk. This is consistent with having 

revenues that are more related to variable cost advantages as well as the value of capacity as 

opposed to peaking units which are more dependent on scarcity or capacity revenue, which, in 

turn, has very high systemic risk. 

There are two main mechanisms for reflecting the greater risk for peakers and the lower risk for 

base load. First, the ROE could have been adjusted such that for a given target leverage, the 

ROE would be higher for peakers, and lower for base load. For example, an unlevered beta and 

 

12The unlevering process removes a company’s financing decision from the beta calculation. The 

calculation therefore, attempts to isolate the business (operating risk) of the firm. 

13The Hamada equation is described at http://www.answers.com/topic/hamada-equation as “A 

fundamental analysis method of analyzing a firm's costs of capital as it uses additional financial 

leverage, and how that relates to the overall riskiness of the firm. The measure is used to 

summarize the effects this type of leverage has on a firm's cost of capital (over and above the cost 

of capital as if the firm had no debt).” 

14The relevering process estimates the levered beta of the firm given a target capital structure and 

the pure business risks of the firm as determined from the unlevering process 

15Federal Reserve Statistical Release (H15 data), May 2007 

16Source: Stocks, Bonds, Bills, and Inflation, 2007 Yearbook Valuation Edition, 

Morningstar/Ibbotson’s Associates 

17Source: Stocks, Bonds, Bills, and Inflation, 2007 Yearbook Valuation Edition, 

Morningstar/Ibbotson’s Associates 

18See Electricity Market Module of NEMS, EIA Annual Energy Outlook, May 2009 
8-10 

ROE (which assumes zero leverage) could have been calculated using the risk differentiated 

capital structures and then relevered at some target leverage. This would have yielded a different 

ROE for each technology but the same capital structure across all technologies. 

The second option was to keep the same ROE while varying the capital structure. This was the 

adopted approach. Thus, even though the leverage of peakers was lowered, the ROE was not 

lowered. This raised the weighted average cost of capital and the resulting capital charge rate. 

This effectively also raised the unlevered beta for peakers relative to combined cycle. For base 

load, leverage was raised without raising ROE, effectively lowering the unlevered beta and the 

cost of capital. 

8.2.5 Development of Utility Financing Parameters 

Utility ROE 

The utility return on equity was calculated to be 10.3%. This was based on empirical analysis of 

correlation of returns on the S&P utility Index vs. the broader S&P 500 market index for the last 

five years to determine the levered beta and then unlevering and relevering based on a process 

similar to that for merchant sector. The ROE is also consistent with what state commissions have 

awarded the shareholder-owned electric utilities recently.19

Utility Cost of Debt 

The cost of debt for the utility sector was estimated to be 6.25%. The utility bonds were 

categorized into various credit rating rungs based on information obtained from the Edison Electric 

Institute.20 Historical yields were analyzed for the various rungs based on data obtained from 

Bloomberg. A weighted average cost of debt was then determined based on the historical yields 

and percentages of utility credit rating classes. The estimated value was also corroborated against 

the yield to maturity of Moody’s average utility bond index. 

Debt and Equity Shares 

The target capitalization structure for utilities was determined using US utility capitalization ratios 

derived from Bloomberg data. Similar CAPM parameters were used to estimate the ROE of the 

utility sector. The capitalization structure for utility financings was estimated to be 55/45 based on 

empirical analyses and this capitalization structure was assumed to be on average reflective of all 

technologies. 

Technology Risks 

For the utility financing, we assumed that the required returns for regulated utilities are 

independent of technology. This assumption was a simplifying assumption, and further empirical 

work may be warranted here. 

8.2.6 Development of Other Parameters 

Taxation and Insurance Costs 

Corporate and State Income Taxes: The maximum US corporate income tax rate is 35%.21 State 

taxes vary but on a national average basis, the state taxes are 6.50%.22 This yields a net effective 

tax rate of 39.3%. 

 

19See page 35, 2006 Financial Review, Annual Report of the U.S Shareholder Owned Electric 

Utility Industry 

202006 Financial Review, Annual Report of the U.S Shareholder Owned Electric Utility Industry 

21Internal Revenue Service, Publication 542. 

22Population weighted average based on 2008 state taxes information available at Federation of 

Tax Administrators, ttp://www.taxadmin.org/fta/rate/corp_inc.html. 
8-11 

State Property Taxes: US state property taxes are approximately 0.9% based on a national 

average basis. This is based on extensive primary and secondary research conducted by ICF 

using property tax rates obtained from various state agencies. 

Insurance Costs: Insurance costs are approximately 0.3%. This is based on estimates of 

insurance costs on a national average basis. 

Inflation 

The inflation rate of 2.25% is based on an assessment of implied inflation from an analysis of 

yields on 5 year and 10 year Treasury securities and Treasury Inflation Protected Securities 

(TIPS). 

Book life, Debt Life and Depreciation 

Table 8-4 presents a summary of various assumed lives at the national level. 

Table 8-4 Book Life, Debt Life and Depreciation Schedules for EPA Base Case v. 4.10 

Technology Book Life 

(Years) 

Debt Life 

(Years) 

US - MACRS 

Depreciation Schedule 

Combined Cycle 30 20 20 

Combustion Turbine 30 15 15 

Coal Steam and IGCC 40 20 20 

Nuclear 40 20 15 

Solar and Geothermal 20 20 5 

Biomass 40 20 7 

Wind and Landfill Gas 20 20 7 

Retrofits 30 20 20 

Book Life or Useful Life of Plant: 

The book life or useful life of a plant was estimated based on researching financial statements of 

utility and merchant generation companies. The financial statements23 typically list the period over 

which long lived assets are depreciated for financial reporting purposes. The research conducted 

broadly supports the numbers outlined in the table above. 

Debt Life: The debt life is assumed to be on a 20 years schedule except in the case of combustion 

turbine where debt life is lower. 

Depreciation Schedule: 

The US MACRS24 depreciation schedules were obtained from IRS Publication 94625 that lists the 

schedules based on asset classes. The document specifies a 5 years depreciation schedule for 

wind energy projects and 20 years for Electric Utility Steam Production plants. These exclude 

combustion turbines which have a separate listing at 15 years. Nuclear Power Plants are 

separately listed at 15 years as well. 

 

23SEC 10K filings of electric utilities and pure merchant companies. For example, Calpine’s 10K 

lists 35 years of useful life for base load plants, DTE energy uses 40 years for generation 

equipment; Dynegy gives a range of 20-40 years for power generation facilities; Mirant reports 14-

35 years for power production equipment; Reliant: 10-35 years 

24MACRS refers to the Modified Accelerated Cost Recovery System, issued after the release of 

the Tax Reform Act of 1986. It allowed faster depreciation than with previous methods. 

25IRS Publication 946, “How to Depreciate Property”, Table B-2, Class Lives and Recovery 

Periods. 
9-1 

9 Coal 

The next three chapters cover the representation and underlying assumptions for fuels in EPA 

Base Case v.4.10. The current chapter focuses on coal, chapter 10 on natural gas, and chapter 

11 on other fuels (fuel oil, biomass, nuclear fuel, and waste fuels) represented in the base case. 

This chapter presents four main topics. The first is a description of how the coal market is 

represented in EPA Base Case v.4.10. This includes a discussion of coal supply and demand 

regions, coal quality characteristics, and the assignment of coals to power plants. 

The next topic is the coal supply curves which were developed for EPA Base Case v.4.10 and the 

painstaking bottom-up, mine-based approach used to develop curves that would depict the coal 

choices and associated prices that power plants will face over the modeling time horizon. Included 

are discussions of the methods and data used to quantify the economically recoverable coal 

reserves, characterize their cost, and build the 84 coal supply curves that are implemented in EPA 

Base Case v.4.10. Illustrative examples are included of the step-by-step approach employed in 

developing a supply curves.

 The third topic is coal transportation. It includes a description of the transport network, the 

methodology used to assign costs to the links in the network, and a discussion of the geographic, 

infrastructure, and regulatory considerations that come into play in developing specific rail, barge 

and truck transport rates. The last topic covered in this chapter is coal exports, imports, and nonelectric sector demand. 

The assumptions for the coal supply curves and coal transportation were finalized in September 

2008, and were developed through a collaborative process with EPA supported by the following 

team of coal experts (with key areas of responsibility noted in parenthesis): PA Consulting Group 

(coal transportation and team coordination), Wood Mackenzie (coal supply curve development), 

Hellerworx (coal transportation and third party review), and ICF Consulting (representation in 

IPM). The coal supply curves and transportation matrix implemented in EPA Base Case v.4.10 

are included in appendices at the end of this chapter. 

9.1 Coal Market Representation in EPA Base Case v.4.10 

Coal supply, coal demand, coal quality, and the assignment of specific types of coals to individual 

coal fired generating units are the four key components of the endogenous coal market modeling 

framework in EPA Base Case v.4.10. The modeling representation attempts to realistically reflect 

the actual options available to each existing coal fired power plant while aggregating data 

sufficiently to keep the model size and solution time within acceptable bounds. 

Each coal power plant modeled is assigned to one of 151 coal demand regions. The demand 

regions are defined to reflect the coal transportation options (rail, barge, truck, conveyer belt) that 

are available to the plants that they serve. These demand regions are interconnected by a 

transportation network to at least one of the 31 geographically dispersed coal supply regions. The 

model’s supply-demand region links reflect actual on-the-ground transportation configurations. 

Every coal supply region can produce and each coal demand region can demand at least one 

grade of coal. Based on historical and engineering data (as described in Section 9.1.5 below), 

each coal fired unit is also assigned several coal grades which it may use if that coal type is 

available within its demand region. 

In EPA Base Case v.4.10 the endogenous demand for coal is generated by coal fired power 

plants interacting with a set of exogenous supply curves (see Appendix 9-4 for coal supply curve 

data) for each coal grade in each supply region. The curves show the supply of coal (by coal 

supply region and coal grade) that is available to meet demand at a given price. The supply of and 

demand for each grade of coal is linked to and affected by the supply of and demand for every 

other coal grade across supply and demand regions. The transportation network or matrix (see 

Appendix 9-3 for coal transportation matrix data) also factors into the final determination of 
9-2 

delivered coal prices, given coal demand and supply. IPM derives the equilibrium coal 

consumption and prices that result when all electric system operating, emission, and other 

requirements are met and total electric system costs over the modeling time horizon are 

minimized. 

9.1.1 Coal Supply Regions 

There are 31 coal supply regions in EPA Base Case v.4.10, each representing geographic 

aggregations of coal-mining areas that supply one or more coal grades. Coal supply regions may 

differ from one another in the types and quality of coal they can supply. Table 9-1 lists the coal 

supply regions included in EPA Base Case v.4.10. Figure 9-1 provides a map showing the 

location of both the coal supply regions listed in Table 9-1 and the broader supply basins 

commonly used when referring to U.S. coal reserves. 

Table 9-1 Coal Supply Regions in EPA Base Case 

Region State Supply Region 

Central Appalachia Kentucky, East KE 

Central Appalachia Tennessee TN 

Central Appalachia Virginia VA 

Central Appalachia West Virginia, South WS 

Dakota Lignite Montana, East ME 

Dakota Lignite North Dakota ND 

East Interior Illinois IL 

East Interior Indiana IN 

East Interior Kentucky, West KW 

East Interior Mississippi MS 

Gulf Lignite Louisiana LA 

Gulf Lignite Texas TX 

Northern Appalachia Maryland MD 

Northern Appalachia Ohio OH 

Northern Appalachia Pennsylvania, Central PC 

Northern Appalachia Pennsylvania, West PW 

Northern Appalachia West Virginia, North WN 

Rocky Mountains Colorado, Green River CG 

Rocky Mountains Colorado, Raton CR 

Rocky Mountains Colorado, Uinta CU 

Rocky Mountains Utah UT 

Southern Appalachia Alabama AL 

Southwest Arizona AZ 

Southwest New Mexico, San Juan NS 

West Interior Kansas KS 

West Interior Oklahoma OK 

Western Montana Montana, Bull Mountains MT 

Western Montana Montana, Powder River MP 

Western Wyoming Wyoming, Green River WG 

Wyoming Northern PRB Wyoming, Powder River Basin WH 

Wyoming Southern PRB Wyoming, Powder River Basin WL 
9-3 

Figure 9-1 Map of the Coal Supply Regions in EPA Base Case v.4.10 

9.1.2 Coal Demand Regions 

Coal demand regions are designed to reflect coal transportation options available to power plants. 

Existing coal plants with similar transportation infrastructures (i.e., rail, barge, or truck/conveyor 

belt), proximity to mine (i.e., mine mouth or not mine mouth), transportation competitiveness levels 

(i.e., non-competitive, low-cost competitive, or high-cost competitive), and within the same 

geographic area are grouped into a coal demand region. Table 9-2 below lists the 135 coal 

demand regions used in EPA Base Case v.4.10 by code and descriptive name. 

When IPM is run, it determines the amount and type of new generation capacity to add within 

each of IPM’s 32 model regions. These model regions reflect the administrative, operational, and 

transmission geographic structure of the electricity grid. Since the coal demand regions do not 

typically coincide or overlap with the IPM model regions, new coal plants that IPM “builds” in 

specific model regions must be assigned to a particular coal demand region. The IPM-region-tocoal-demand-region assignments for new coal generating capacity are indicated in column 3 of 

Table 9-2. Also shown in the last column of Table 9-2 are instances where only one existing 

power plant is contained in a coal demand region. Forty-seven of the coal demand regions contain 

only one power plant. 

Table 9-2 Coal Demand Regions in EPA Base Case 

Coal 

Demand 

Region 

Codes 

Descriptive Name 

IPM Model 

Regions with 

Potential Plants 

Assigned to this 

Coal Demand 

Region 

Plant Name when 

Coal Demand 

Region Just 

Includes One Plant 

ALR1 Alabama High-Cost Competitive_Not 

Mine Mouth_Rail -- 

ALR2 Alabama Low-Cost Competitive_Not 

Mine Mouth_Barge -- Greene County Plant 

ALR3 Alabama Low-Cost Competitive_Not 

Mine Mouth_Rail -- E C Gaston Plant 

AMM1 New Mexico High-Cost 

Competitive_Mine Mouth_Rail -- 
9-4 

Coal 

Demand 

Region 

Codes 

Descriptive Name 

IPM Model 

Regions with 

Potential Plants 

Assigned to this 

Coal Demand 

Region 

Plant Name when 

Coal Demand 

Region Just 

Includes One Plant 

AMM2 Arizona, New Mexico High-Cost 

Competitive_Not Mine Mouth_Rail -- Navajo Plant 

AMM4 

New Mexico Low-Cost 

Competitive_Mine 

Mouth_Truck/Conveyor Belt 

-- San Juan Plant 

AMM5 New Mexico Low-Cost Competitive_Not 

Mine Mouth_Truck/Conveyor Belt -- Raton Plant 

AMN1 Arizona High-Cost Competitive_Not 

Mine Mouth_Rail -- Apache Station 

AMN2 Arizona Low-Cost Competitive_Not Mine 

Mouth_Rail -- H Wilson Sundt Generating Station 

AMN3 Arizona Non-Competitive_Not Mine 

Mouth_Rail AZNM 

CAI1 Virginia High-Cost Competitive_Not 

Mine Mouth_Rail -- 

CAI2 Kentucky Low-Cost Competitive_Not 

Mine Mouth_Rail -- 

CAI3 Kentucky Low-Cost Competitive_Not 

Mine Mouth_Truck/Conveyor Belt -- Tyrone Plant 

CAR1 North and South Carolina High-Cost 

Competitive_Not Mine Mouth_Rail -- 

CAR2 North and South Carolina Low-Cost 

Competitive_Not Mine Mouth_Rail -- 

CAR3 North and South Carolina NonCompetitive_Not Mine Mouth_Rail VACA 

CC1 Colorado High-Cost Competitive_Not 

Mine Mouth_Rail -- 

CC2 Colorado Low-Cost Competitive_Not 

Mine Mouth_Truck/Conveyor Belt -- 

CC3 Colorado Non-Competitive_Not Mine 

Mouth_Rail RMPA 

CU1 Utah High-Cost Competitive_Not Mine 

Mouth_Rail -- KUCC Plant 

CU2 Utah Low-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt -- Huntington Plant 

CU4 Utah Non-Competitive_Not Mine 

Mouth_Rail -- 

DAL1 

North Dakota High-Cost 

Competitive_Mine 

Mouth_Truck/Conveyor Belt 

-- Milton R Young 

Plant 

DAL2 

Montana, North Dakota Low-Cost 

Competitive_Mine 

Mouth_Truck/Conveyor Belt 

-- 

DAL4 North Dakota Non-Competitive_Not 

Mine Mouth_Rail -- 

EIM1 Iowa, Missouri High-Cost 

Competitive_Not Mine Mouth_Rail -- Prairie Creek Plant 

EIM2 Iowa Low-Cost Competitive_Not Mine -- Fair Station Plant 
9-5 

Coal 

Demand 

Region 

Codes 

Descriptive Name 

IPM Model 

Regions with 

Potential Plants 

Assigned to this 

Coal Demand 

Region 

Plant Name when 

Coal Demand 

Region Just 

Includes One Plant 

Mouth_Barge 

EIM3 Iowa, Missouri Low-Cost 

Competitive_Not Mine Mouth_Rail -- 

EIM4 Iowa Low-Cost Competitive_Not Mine 

Mouth_Truck/Conveyor Belt -- Pella Plant 

EIM5 Iowa, Missouri Non-Competitive_Not 

Mine Mouth_Rail -- 

FL1 Florida High-Cost Competitive_Not Mine 

Mouth_Rail FRCC 

FL2 Florida Low-Cost Competitive_Not Mine 

Mouth_Barge -- 

FL3 Florida Low-Cost Competitive_Not Mine 

Mouth_Rail -- 

GAR1 Georgia, Mississippi Low-Cost 

Competitive_Not Mine Mouth_Rail -- 

GAR2 Georgia Non-Competitive_Not Mine 

Mouth_Rail SOU 

GFB1 Alabama Low Cost Competitive_Not 

Mine Mouth_Rail -- Barry Plant 

GFB3 Mississippi Low-Cost Competitive_Not 

Mine Mouth_Barge -- Jack Watson Plant 

GFB4 Mississippi Non-Competitive_Not Mine 

Mouth_Rail -- Victor J Daniel Jr Plant 

GFR1 Mississippi, Texas High-Cost 

Competitive_Not Mine Mouth_Rail ERCT 

GFR2 Arkansas, Louisiana, Texas Low-Cost 

Competitive_Not Mine Mouth_Rail -- 

GFR3 Arkansas, Louisiana, Texas NonCompetitive_Not Mine Mouth_Rail ENTG 

GWAY Illinois, Mine Mouth GWAY 

IBB1 Kentucky High-Cost Competitive_Not 

Mine Mouth_Rail -- Cane Run Plant 

IBB2 Kentucky Low Cost Competitive_Not 

Mine Mouth_Rail -- Mill Creek Plant 

IBB3 Indiana, Kentucky Low-Cost 

Competitive_Not Mine Mouth_Barge -- 

IBB4 Illinois, Indiana, Kentucky Low-Cost 

Competitive_Not Mine Mouth_Rail -- 

III1 Illinois, Indiana High-Cost 

Competitive_Not Mine Mouth_Rail -- 

III2 Kentucky High-Cost Competitive_Not 

Mine Mouth_Truck/Conveyor Belt -- Green River Plant 

III3 Illinois, Indiana, Kentucky Low-Cost 

Competitive_Not Mine Mouth_Barge -- 

III4 Illinois, Indiana Low-Cost 

Competitive_Not Mine Mouth_Rail COMD & RFCO 
9-6 

Coal 

Demand 

Region 

Codes 

Descriptive Name 

IPM Model 

Regions with 

Potential Plants 

Assigned to this 

Coal Demand 

Region 

Plant Name when 

Coal Demand 

Region Just 

Includes One Plant 

III5 

Illinois, Indiana, Kentucky Low-Cost 

Competitive_Not Mine 

Mouth_Truck/Conveyor Belt 

-- 

III6 Indiana Non-Competitive_Mine 

Mouth_Truck/Conveyor Belt -- Rank E Ratts Plant 

III7 Illinois, Indiana, Kentucky NonCompetitive_Not Mine Mouth_Rail TVAK 

IMB1 Illinois, Iowa, Missouri High-Cost 

Competitive_Not Mine Mouth_Rail MRO 

IMB2 Iowa, Missouri Low-Cost 

Competitive_Not Mine Mouth_Rail -- 

IMB3 Missouri Low-Cost Competitive_Not 

Mine Mouth_Truck/Conveyor Belt -- 

IMB4 Iowa Non-Competitive_Not Mine 

Mouth_Rail -- 

MA-1 Maryland Low-Cost Competitive_Not 

Mine Mouth_Rail -- 

MA-2 Maryland Low-Cost Competitive_Not 

Mine Mouth_Truck/Conveyor Belt -- 

MA-3 Maryland Non-Competitive_Not Mine 

Mouth_Rail MACS 

MAB1 Maryland Low-Cost Competitive_Not 

Mine Mouth_Rail -- 

MIB1 Michigan High-Cost Competitive_Not 

Mine Mouth_Rail -- 

MIB2 Michigan, Wisconsin Low-Cost 

Competitive_Not Mine Mouth_Barge -- 

MIB3 Michigan, Wisconsin Low-Cost 

Competitive_Not Mine Mouth_Rail MECS 

MIB4 Michigan Low-Cost Competitive_Not 

Mine Mouth_Truck/Conveyor Belt -- Endicott Station 

MNR1 Minnesota, South Dakota High-Cost 

Competitive_Not Mine Mouth_Rail -- 

MNR2 Minnesota Low-Cost Competitive_Not 

Mine Mouth_Barge -- Silver Bay Power Plant 

MNR3 Minnesota Low-Cost Competitive_Not 

Mine Mouth_Rail -- 

MNR5 Minnesota, South Dakota NonCompetitive_Not Mine Mouth_Rail -- 

MWR1 

Iowa, Kansas, Missouri, Nebraska, 

Oklahoma High-Cost Competitive_Not 

Mine Mouth_Rail 

SPPN 

MWR2 

Kansas, Missouri High-Cost 

Competitive_Not Mine 

Mouth_Truck/Conveyor Belt 

-- 

MWR3 

Kansas, Missouri, Nebraska, Oklahoma 

Low-Cost Competitive_Not Mine 

Mouth_Rail 

SPPS 
9-7 

Coal 

Demand 

Region 

Codes 

Descriptive Name 

IPM Model 

Regions with 

Potential Plants 

Assigned to this 

Coal Demand 

Region 

Plant Name when 

Coal Demand 

Region Just 

Includes One Plant 

MWR5 Kansas, Missouri Non-Competitive_Not 

Mine Mouth_Rail -- 

NAI1 West Virginia High-Cost 

Competitive_Mine Mouth_Rail RFCP 

NAI2 West Virginia High-Cost 

Competitive_Not Mine Mouth_Rail -- Mt Storm Plant 

NAI3 Pennsylvania, West Virginia Low-Cost 

Competitive_Not Mine Mouth_Barge -- 

NAI4 West Virginia Low-Cost 

Competitive_Not Mine Mouth_Rail -- Willow Island Plant 

NAI5 

West Virginia Low-Cost 

Competitive_Not Mine 

Mouth_Truck/Conveyor Belt 

-- Albright Plant 

NAI6 Ohio Non-Competitive_Not Mine 

Mouth_Rail -- Muskingum River Plant 

NE1 

Maine, Massachusetts, New Hampshire, 

New Jersey High-Cost Competitive_Not 

Mine Mouth_Rail 

-- 

NE2 

Connecticut, Massachusetts, New 

Hampshire, New Jersey Low-Cost 

Competitive_Not Mine Mouth_Barge 

-- 

NE3 Connecticut, New York Low-Cost 

Competitive_Not Mine Mouth_Rail DSNY 

NII1 Indiana High-Cost Competitive_Not 

Mine Mouth_Rail -- 

NII2 Illinois Low-Cost Competitive_Not Mine 

Mouth_Barge -- 

NII3 Illinois, Indiana Low-Cost 

Competitive_Not Mine Mouth_Rail -- 

NNR1 Nevada Non-Competitive_Not Mine 

Mouth_Rail -- North Valmy Plant 

NOR1 Ohio High-Cost Competitive_Not Mine 

Mouth_Rail -- 

NOR2 Ohio Low-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt -- Conesville Plant 

NOR3 Ohio Low-Cost Competitive_Not Mine 

Mouth_Barge -- 

NOR4 Ohio Low-Cost Competitive_Not Mine 

Mouth_Rail -- Hiles Plant 

NOR5 Ohio Low-Cost Competitive_Not Mine 

Mouth_Truck/Conveyor Belt -- 

NOR6 Ohio Non-Competitive_Not Mine 

Mouth_Rail -- O H Hutchings Plant

NU1 New York High-Cost Competitive_Not 

Mine Mouth_Rail UPNY 

NU2 New York Low-Cost Competitive_Not 

Mine Mouth_Rail -- AES Westover Plant

ORP1 Ohio, Pennsylvania, West Virginia High- -- 
9-8 

Coal 

Demand 

Region 

Codes 

Descriptive Name 

IPM Model 

Regions with 

Potential Plants 

Assigned to this 

Coal Demand 

Region 

Plant Name when 

Coal Demand 

Region Just 

Includes One Plant 

Cost Competitive_Not Mine Mouth_Rail 

ORP2 Ohio, Pennsylvania, West Virginia Low 

Cost Competitive_Not Mine Mouth_Rail -- 

ORP3 Ohio, West Virginia Low-Cost 

Competitive_Not Mine Mouth_Barge -- 

ORP4 Ohio, Pennsylvania, West Virginia LowCost Competitive_Not Mine Mouth_Rail -- 

PC1 Pennsylvania High-Cost 

Competitive_Not Mine Mouth_Rail MACW 

PC2 

Pennsylvania High-Cost 

Competitive_Not Mine 

Mouth_Truck/Conveyor Belt 

-- Homer City Station 

PC3 Pennsylvania Low-Cost 

Competitive_Not Mine Mouth_Barge -- 

PC4 Pennsylvania Low-Cost 

Competitive_Not Mine Mouth_Rail -- P H Glatfelter Plant 

PC6 Pennsylvania Non-Competitive_Not 

Mine Mouth_Rail -- PPL Montour Plant 

PE1 New Jersey, Pennsylvania High-Cost 

Competitive_Not Mine Mouth_Rail -- 

PE2 

Pennsylvania Low-Cost 

Competitive_Not Mine 

Mouth_Truck/Conveyor Belt 

-- Shawville Plant 

PE3 Delaware, New Jersey, Pennsylvania 

Non-Competitive_Not Mine Mouth_Rail MACE 

PRB1 Wyoming High-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt -- 

PRB3 Montana Low-Cost Competitive_Not 

Mine Mouth_Truck/Conveyor Belt -- Colstrip Plant 

PRB4 Wyoming Non-Competitive_Not Mine 

Mouth_Rail -- 

SNR1 Nevada Non-Competitive_Not Mine 

Mouth_Rail SNV Reid Gardner 

TAB1 Alabama High-Cost Competitive_Not 

Mine Mouth_Rail -- Charles R Lowman 

TAB2 Alabama Low Cost Competitive_Not 

Mine Mouth_Rail -- Widows Creek 

TAB3 Alabama, Tennessee Low-Cost 

Competitive_Not Mine Mouth_Barge -- 

TKI1 Tennessee Low-Cost Competitive_Not 

Mine Mouth_Rail -- 

TKI2 Tennessee Non-Competitive_Not Mine 

Mouth_Rail TVA 

TXL1 Mississippi, Texas High-Cost 

Competitive_Mine Mouth_Rail -- 

TXL2 Texas High-Cost Competitive_Not Mine 

Mouth_Rail -- 
9-9 

Coal 

Demand 

Region 

Codes 

Descriptive Name 

IPM Model 

Regions with 

Potential Plants 

Assigned to this 

Coal Demand 

Region 

Plant Name when 

Coal Demand 

Region Just 

Includes One Plant 

TXL3 Texas High-Cost Competitive_Not Mine 

Mouth_Truck/Conveyor Belt -- Twin Oaks Power One Plant 

TXL4 

Louisiana, Texas Low-Cost 

Competitive_Mine 

Mouth_Truck/Conveyor Belt 

-- 

TXL5 Texas Non-Competitive_Not Mine 

Mouth_Rail -- Gibbons Creek 

VAPW Virginia, Mine Mouth VAPW 

VEP1 South Carolina, Virginia High-Cost 

Competitive_Not Mine Mouth_Rail -- 

VEP2 Virginia Non-Competitive_Not Mine 

Mouth_Rail -- 

WIR1 Wisconsin High-Cost Competitive_Not 

Mine Mouth_Rail -- 

WIR2 Wisconsin Low-Cost Competitive_Not 

Mine Mouth_Rail WUMS 

WIR4 Wisconsin Non-Competitive_Not Mine 

Mouth_Rail -- 

WOM1 Michigan Low-Cost Competitive_Not 

Mine Mouth_Rail -- Eckert Station 

WOM2 Michigan Non-Competitive_Not Mine 

Mouth_Rail -- Erickson Station 

WON1 California High-Cost Competitive_Not 

Mine Mouth_Rail -- 

WON2 California Low-Cost Competitive_Not 

Mine Mouth_Rail -- ACE Cogeneration Facility 

WON3 Montana, Oregon, Washington NonCompetitive_Not Mine Mouth_Rail PNW 

WYG1 Wyoming High-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt NWPE 

WYG2 Wyoming High-Cost Competitive_Not 

Mine Mouth_Rail -- Osage Plant 

WYG3 Wyoming Low-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt -- 

WYG4 Wyoming Non-Competitive_Mine 

Mouth_Rail -- Jim Bridger 

9.1.3 Coal Quality Characteristics 

Coal varies by heat content, SO2 content and mercury content among other characteristics. To 

capture differences in the sulfur and heat content of coal, a two letter “coal grade” nomenclature is 

used. The first letter indicates the “coal rank” (bituminous, subbitumionus, or lignite) with their 

associated heat content ranges (as shown in Table 9-3). The second letter indicates their “sulfur 

grade,” i.e., the SO2 ranges associated with a given type of coal. (The sulfur grades and 

associated SO2 ranges are shown in Table 9-4.) 
9-10 

Table 9-3 Coal Rank Heat Content Ranges 

Coal Type Heat Content (Btu/lb) Classification 

Bituminous >10,260 – 13,000 B 

Sub-bituminous > 7,500 – 10,260 S 

Lignite less than 7,500 L 

Table 9-4 Coal Grade SO2 Content Ranges 

SO2 Grade SO2 Content Range (lbs/MMBtu) 

A 0.00 – 0.80 

B 0.81 – 1.20 

D 1.21 – 1.66 

E 1.67 – 3.34 

G 3.35 – 5.00 

H > 5.00 

 

The assumptions in EPA Base Case v.4.10 on the heat, mercury, SO2, and ash content of coal 

are derived from EPA’s “Information Collection Request for Electric Utility Steam Generating Unit 

Mercury Emissions Information Collection Effort” (ICR)1. A two-year effort initiated in 1998 and 

completed in 2000, the ICR had three main components: (1) identifying all coal-fired units owned 

and operated by publicly-owned utility companies, Federal power agencies, rural electric 

cooperatives, and investor-owned utility generating companies, (2) obtaining “accurate information 

on the amount of mercury contained in the as-fired coal used by each electric utility steam 

generating unit... with a capacity greater than 25 megawatts electric, as well as accurate 

information on the total amount of coal burned by each such unit,”, and (3) obtaining data by coal 

sampling and stack testing at selected units to characterize mercury reductions from 

representative unit configurations. Data regarding the SO2 and ash content of the coal used was 

obtained along with mercury content. 

The ICR resulted in more than 40,000 data points indicating the coal type, sulfur content, mercury 

content, ash content, and other characteristics of coal burned at coal-fired utility units greater than 

25 MW. 

9.1.4 Emission Factors 

To make this data usable in EPA Base Case v.4.10, the ICR data points were first grouped by IPM 

coal grades and IPM coal supply regions. Using the grouped ICR data, the average heat, SO2, 

mercury, and ash content were calculated for each coal grade/supply region combination. In 

instances where no data were available for a particular coal grade in a specific supply region, the 

national average SO2 and mercury values for the coal grade were used as the region’s values. 

The resulting values are shown in Table 9-5. 

 

1

 Data from the ICR can be found at http://www.epa.gov/ttn/atw/combust/utiltox/mercury.html. 
9-11 

Table 9-5 Coal Quality Characteristics by Supply Region and Coal Grade 

Coal 

Supply 

Region 

Coal 

Grade 

Heat Content 

(MMBtu/Ton) 

SO2 Content 

(lbs/MMBtu) 

Mercury 

Content 

(lbs/TBtu) 

Ash Content 

(lbs/MMBtu) 

Cluster 

Number

BB 24.82 1.1 4.2 9.8 2 

AL BD 24 1.4 7.3 10.8 2 

BE 23.82 2.7 12.6 10.7 2 

AZ BB 24.64 1.1 5.3 7.9 2 

BA 21.49 0.7 3.1 7.3 1 CG 

BB 22.01 0.9 4.1 8.4 2 

BA 25.5 0.7 3.5 7 1 CR 

BD 22.2 1.4 7 8.3 1 

BA 23.8 0.7 2.6 6.3 1 

CU BB 23.22 0.9 4 7.8 2 

BD 23.21 1.3 3.1 8.1 1 

BE 23 2.2 6.5 6.6 2 

IL BG 23.01 4.6 6.5 8.1 1 

BH 22.19 5.6 5.4 9.1 1 

BD 22.62 1.4 3.8 7.4 1 

BE 23.43 2.3 5.2 8 2 

BG 23.37 4.3 7.2 8.2 1 IN 

BH 23.41 6.1 7.1 8.6 1 

BA 25.32 0.7 3 6.1 1 

BB 25.79 1 4.8 6.4 2 

BD 25.33 1.4 6 7.4 1 

BE 25.14 2.1 7.9 7.7 2 

KE 

BG 24.09 3.8 12 10.2 3 

KS BG 25.32 4.8 4.1 8.5 1 

BD 24.23 1.6 5.6 6.2 1 

BE 24.45 2.8 7.1 7.4 2 

BG 23.93 4.5 6.9 8 1 KW 

BH 22.84 5.7 8.2 10.2 1 

LA LE 14.09 2.5 7.3 17.1 2 

BB 24.64 1.1 5.3 7.9 2 

BD 26.32 1.6 7.8 9.5 2 

BE 24.85 2.8 15.6 11.7 1 MD 

BG 23.26 3.6 16.6 16.6 3 

ME LD 13.36 1.4 8.6 11.3 1 

SA 18.9 0.6 4.2 4 1 MP 

SD 17.23 1.5 4.5 10.1 1 

MS LE 13.19 2.8 12.4 21.5 1 

MT BB 21 1.1 5.3 7.9 2 

LD 13.7 1.5 6.4 10.7 1 ND 

LE 13.46 2.3 8.3 12.8 1 

NS BB 26.4 1.1 5.3 7.9 2 

BD 18.1 1.6 5.5 19.6 1 
9-12 

Coal 

Supply 

Region 

Coal 

Grade 

Heat Content 

(MMBtu/Ton) 

SO2 Content 

(lbs/MMBtu) 

Mercury 

Content 

(lbs/TBtu) 

Ash Content 

(lbs/MMBtu) 

Cluster 

Number

BE 18.1 1.8 8.2 18.8 2 

BB 24.68 1.1 5.7 9.8 1 

BD 25.55 1.4 6.4 10.3 1 

BE 25.24 3.1 18.7 7.1 1 

BG 24.34 4 18.5 8 2 

OH 

BH 23.92 6.4 13.9 9.1 2 

OK BE 22.15 2.7 25.8 11.3 1 

BD 25.06 1.4 21.7 49.3 3 

BE 25.66 2.6 18 9.2 1 

BG 25.33 3.8 21.5 9.6 2 PC 

BH 23.39 6.3 34.7 13.9 3 

BD 24.26 1.6 11.2 10 2 

PW BE 26.22 2.5 8.4 5.4 2 

BG 25.86 3.7 8.6 6.5 1 

BB 24.18 1.1 3.8 10.4 2 

TN BD 23.91 1.3 6.3 10.4 1 

BE 26.75 2.1 8.4 6.5 2 

LD 13.06 1.6 12 22.3 2 

TX LE 13.22 3 14.7 25.6 1 

LG 12.27 3.9 14.9 25.5 1 

BA 23.68 0.7 4.4 7.4 2 

BB 23.23 0.9 3.9 8.6 2 

BD 23.05 1.4 4.4 10.5 1 UT 

BE 25.06 2.3 9.2 7.4 2 

BA 22.7 0.7 3.5 7 1 

BB 25.97 1 4.6 7 2 

BD 25.76 1.4 5.7 8 1 VA 

BE 26.03 2.1 8.4 8.1 2 

BB 21.67 1.1 1.8 5.6 1 WG 

SD 18.5 1.3 4.3 10 1 

SA 17.43 0.6 5.6 5.5 2 WH 

SB 17.43 0.9 6.4 6.5 1 

WL SB 17.15 0.9 6.4 6.5 1 

BD 25.01 1.5 10.3 9.2 2 

BE 25.67 2.5 10.3 7.9 2 

BG 26.03 4 9.3 6.9 1 WN 

BH 25.15 6.1 8.8 9.6 1 

BA 26.2 0.7 3.5 7 1 

BB 24.73 1.1 5.7 9.2 2 

BD 24.64 1.3 8.1 9.3 2 

BE 24.38 1.9 8.8 9.9 2 

WS 

BG 25.64 4.7 7.1 6.4 1 

 
9-13 

Next, a clustering algorithm was used to further aggregate the data in EPA Base Case v.4.10 for 

model size management purposes. The clustering analysis was performed on the mercury and 

SO2 data shown in Table 9-5 using the SAS statistical software package. Clustering analysis 

places objects into groups or clusters, such that data in a given cluster tend to be similar to each 

other and dissimilar to data in other clusters. The clustering analysis involved two steps. (In the 

following write-up BG coal is used to illustrate how the procedure worked.) First, the number of 

clusters of mercury and SO2 concentrations for each IPM coal type was determined based on the 

range in average mercury and SO2 concentrations across all coal supply regions for a specific 

coal type. Each coal type used either one or two clusters. The total number of clusters for each 

coal grade was limited to keep the model size and run time within feasible limits. (Two clusters 

were used for BG coal.) Second, for each coal grade the clustering procedure was applied to all 

the regional SO2 and mercury values shown in Table 9-5 for that coal grade. (In the BG coal 

example there are 11 such regional SO2 and mercury values.) Using the SAS cluster procedure, 

each of the constituent regional values was assigned to a cluster and the cluster average SO2 and 

mercury values were recorded. The resulting values are shown in Table 9-6 and Table 9-7. (For 

BG coal the Cluster #1 average SO2 and mercury values are 4.36 lb/MMBtu and 7.10 lb/TBtu 

respectively. The Cluster #2 average SO2 and mercury values are 3.89 lb/MMBtu and 20.04 

lb/TBtu respectively. The Cluster #3 average SO2 and mercury values are 3.68 lb/MMBtu and 

14.31 lb/TBtu respectively.) Although not used in determining the clusters, ash and CO2 values 

were calculated for each of the clusters. These values are shown in Table 9-8 and Table 9-9. (The 

CO2 values were derived from data in the Energy Information Administration’s Annual Energy 

Outlook 2009 (AEO 2009), not from data collected in the ICR.) 

IPM input files retain the mapping between different coal grade/supply region combinations and 

the clusters. The mapping can be seen in the last column of Table 9-5 which shows the cluster 

number associated with the coal grade/supply region combination indicated in the first and second 

columns of this table. (For BG coal, the SAS cluster procedure mapped supply regions IL, IN, KS, 

KW, PW, WN, and WS to Cluster #1, supply regions OH and PC to Cluster #2, and MD and KE to 

Cluster #3. See Figure 9-2 for an illustration of this mapping.) Table 9-6 to Table 9-9 show the 

mercury, SO2, ash, and CO2 values assigned to coal grades and regions based on this cluster 

mapping. The values shown in Table 9-6 to Table 9-9 are used in EPA Base Case v.4.10 for 

calculating emissions. 

Table 9-6 SO2 Emission Factors of Coal Used in EPA Base Case v.4.10 

Sulfur Emission Factors (lbs/MMBtu) Coal Type by Sulfur Grade Cluster #1 Cluster #2 Cluster # 3 

Low Sulfur Eastern Bituminous (BA) 0.7 0.67 -- 

Low Sulfur Western Bituminous (BB) 1.13 1.03 -- 

Low Medium Sulfur Bituminous (BD) 1.43 1.45 1.42 

Medium Sulfur Bituminous (BE) 2.78 2.3 -- 

High Sulfur Bituminous (BG) 4.36 3.89 3.68 

High Sulfur Bituminous (BH) 5.89 6.43 6.29 

Low Sulfur Subbituminous (SA) 0.62 0.58 -- 

Low Sulfur Subbituminous (SB) 0.94 -- -- 

Low Medium Sulfur Subbituminous (SD) 1.41 -- -- 

Low Medium Sulfur Lignite (LD) 1.46 1.61 -- 

Medium Sulfur Lignite (LE) 2.88 2.38 -- 

High Sulfur Lignite (LG) 3.91 -- -- 
9-14 

Table 9-7 Mercury Emission Factors of Coal Used in EPA Base Case v.4.10 

Mercury Emission Factors (lbs/TBtu) Coal Type by Sulfur Grade 

Cluster #1 Cluster #2 Cluster #3 

Low Sulfur Eastern Bituminous (BA) 3.19 4.37 -- 

Low Sulfur Western Bituminous (BB) 1.82 4.86 -- 

Low Medium Sulfur Bituminous (BD) 5.38 8.94 21.67 

Medium Sulfur Bituminous (BE) 19.53 8.42 -- 

High Sulfur Bituminous (BG) 7.1 20.04 14.31 

High Sulfur Bituminous (BH) 7.38 13.93 34.71 

Low Sulfur Subbituminous (SA) 4.24 5.61 -- 

Low Sulfur Subbituminous (SB) 6.44 -- -- 

Low Medium Sulfur Subbituminous (SD) 4.43 -- -- 

Low Medium Sulfur Lignite (LD) 7.51 12 -- 

Medium Sulfur Lignite (LE) 13.55 7.81 -- 

High Sulfur Lignite (LG) 14.88 -- -- 

Table 9-8 Ash Emission Factors of Coal Used in EPA Base Case v.4.10 

Ash Emission Factors by Coal Sulfur 

Coal Type by Sulfur Grade Grades (lbs/MMBtu) 

Cluster #1 Cluster #2 Cluster #3 

Low Sulfur Eastern Bituminous (BA) 6.77 7.39 -- 

Low Sulfur Western Bituminous (BB) 5.59 8.1 -- 

Low Medium Sulfur Bituminous (BD) 9.64 9.77 49.31 

Medium Sulfur Bituminous (BE) 9.84 8.69 -- 

High Sulfur Bituminous (BG) 7.51 8.8 13.41 

High Sulfur Bituminous (BH) 9.38 9.13 13.89 

Low Sulfur Subbituminous (SA) 3.98 5.47 -- 

Low Sulfur Subbituminous (SB) 6.5 -- -- 

Low Medium Sulfur Subbituminous (SD) 10.08 -- -- 

Low Medium Sulfur Lignite (LD) 11.01 22.33 -- 

Medium Sulfur Lignite (LE) 23.58 15 -- 

High Sulfur Lignite (LG) 25.51 -- -- 
9-15 

Table 9-9 CO2 Emission Factors of Coal Used in EPA Base Case v.4.10 

CO2 Emission Factors by Coal 

Coal Type by Sulfur Grade Sulfur Grades (lbs/MMBtu) 

Cluster #1 Cluster #2 Cluster #3 

Low Sulfur Eastern Bituminous (BA) 205.4 205.4 -- 

Low Sulfur Western Bituminous (BB) 205.8 205.8 -- 

Low Medium Sulfur Bituminous (BD) 206.6 206.6 206.6 

Medium Sulfur Bituminous (BE) 206.3 206.3 -- 

High Sulfur Bituminous (BG) 205.2 205.2 205.2 

High Sulfur Bituminous (BH) 205.2 205.2 205.2 

Low Sulfur Subbituminous (SA) 213.1 213.1 -- 

Low Sulfur Subbituminous (SB) 212.7 -- -- 

Low Medium Sulfur Subbituminous (SD) 213.1 -- -- 

Low Medium Sulfur Lignite (LD) 217 217 -- 

Medium Sulfur Lignite (LE) 214.8 214.8 -- 

High Sulfur Lignite (LG) 213.5 -- -- 

 

Figure 9-2 Cluster Mapping Example --- BG Coal 

9.1.5 Coal Grade Assignments 

The grades of coal that may be used by specific generating units were determined by an expert 

assessment of the ranks of coal that a unit had used in the past, the removal efficiency of the 

installed FGD, and the SO2 permit rate of the unit. Examples of the coal grade assignments made 

for individual plants in EPA Base Case v.4.10 are shown in Table 9-10. Not all of the coal grades 
9-16 

allowed to a plant by the coal grade assignment are necessarily available in the plant’s assigned 

coal demand region (due to transportation limitations). IPM endogenously selects the coal burned 

by a plant by taking into account both the constraint of the plant’s coal grade assignment and the 

constraint of the coals actually available within a plant’s coal demand region. 

Table 9-10 Example of Coal Assignments Made in EPA Base Case 

Plant Name Unique ID 

SIP SO2

Limit 

(lbs/MMBtu) 

Scrubber? Fuels Allowed 

Salem Harbor 1626_B_1 1.2 No BA,BB 

Dickerson 1572_B_3 2.8 No BA,BB,BD,BE 

Glen Lyn 3776_B_51 1.75 No BA,BB,BD 

Danskammer 

Generating Station 2480_B_3 1.1 No BA,BB 

R E Burger 2864_B_5 9.02 No BA,BB,BD,BE,BG,BH 

Moutaineer 6264_B_1 1 Yes BA,BB,BD,BE,BG,BH,

SA,SB,SD 

Big Brown 3497_B_1 3 No LD,LE,SA,SB,SD 

Black River 

Generation 10464_B_E0001 3.8 Yes BA,BB,BD,BE,BG,BH 

E D Edwards 856_B_1 4.71 No BA,BB,BD,BE,BG,SA,

SB,SD 

R Gallagher 1008_B_1 4.71 No BA,BB,BD,BE,BG,SA,

SB,SD 

 

9.2 Coal Supply Curves 

9.2.1 Nature of Supply Curves Developed for EPA Base Case v.4.10 

In keeping with IPM’s data-driven bottom-up modeling framework, a bottom-up approach (relying 

heavily on detailed economic and resource geology data and assessments) was used to prepare 

the coal supply curves for EPA Base Case v.4.10. Wood Mackenzie was chosen to develop the 

curves based on their extensive experience in preparing mine-by-mine estimates of cash 

operating costs for operating mines in the U.S., their access to both public and proprietary data 

sources, and their active updating of the data both through research and interviews. 

In order to establish consistent nomenclature, Wood Mackenzie first mapped its internal list of coal 

regions and qualities to EPA’s 31 coal supply regions (described above in sections 9.1.1) and 12 

coal grades (described above in section 9.1.3). The combined code list is shown in Table 9-11 

below with the IPM supply regions appearing in the rows and the coal grades in the columns. 

Wood Mackenzie then created supply curves for each region and coal-grade combination 

(indicated by the “x” in Table 9-11) for forecast years 2012, 2015, 2020, 2030, and 2040. 
9-17 

Table 9-11 Basin-Level Groupings Used in Preparing v.4.0 Coal Supply Curves 

9.2.2 Procedure Employed in Determining Mining Costs 

Wood Mackenzie estimates mine production costs on a mine-by-mine basis utilizing proprietary 

bottom-up engineering cost models. A mine’s cash costs are the sum of its direct operating costs 

(DOCs), royalty tax, severance tax, property tax, reclamation tax and black lung fees. Using these 

mine costing models, costs curves are developed by summing the individual and incremental 

costs that make up mine cash-costs and assuming a built-in 10% discounted rate-of-return. As an 

illustration of the break-down of costs included in the mine costing models, Figure 9-3 lists the 

cost components included and calculations performed for a Powder River Basin mine supply 

curve. Appendix 9-1 contains a more detailed illustration of the procedure used to derive a supply 

curve from its constituent mine costing models. 

Coal Supply Regions and Coal Grades in EPA IPM, v.4.0

Coal Code 1 2 3 4 5 6 7 8 9 10 11 12 13

Geo. Region Geo. Sub-Region Region Code BA BB BD BE BG BH SA SB SD LD LE LG LH

Appalachia Southern Appalachia 1 AL XXXX

West Southwest 2 AZ X

West Rocky Mountain 3 CG X X

West Rocky Mountain 4 CR X X

West Rocky Mountain 5 CU XXX

Interior East Interior (Illinois Basin) 6 IL XXX

Interior East Interior (Illinois Basin) 7 IN XXXX

Interior Gulf Lignite 8 LA X

Appalachia Northern Appalachia 9 MD XXXX

West Dakota Lignite 10 ME X

Appalachia Central Appalachia 11 KE XXXXX

Interior West Interior 12 KS X

Interior East Interior (Illinois Basin) 13 KW XXXX

West Western Montana 14 MP X X

Gulf Gulf Coast Lignite 15 MS X

West Western Montana 16 MT X

West Dakota Lignite 17 ND X X

West Southwest 18 NS XXX

Appalachia Northern Appalachia 19 OH XXXXX

Interior West Interior 20 OK X

Appalachia Northern Appalachia 21 PC XXXX

Appalachia Northern Appalachia 22 PW XXX

Appalachia Central Appalachia 23 TN XXX

Gulf Gulf Coast Lignite 24 TX XXXX

West Rocky Mountain 25 UT XXXX

Appalachia Central Appalachia 26 VA XXXX

West Western Wyoming 27 WG X X

West Wyoming Powder River Basin 28 WH X X

West Wyoming Powder River Basin 29 WL X

Appalachia Northern Appalachia 30 WN XXXX

Appalachia Central Appalachia 31 WS XXXXX

BITUMINOUS SUB-BITUMINOUS LIGNITE
9-18 

Figure 9-3 Cost Calculations Included When Developing Coal Supply Curves (based on a 

Powder River Basin Mine Supply Curve Example) 

10% DCFROR All cost curves assume mine operators are able to earn a minimum 10% discounted rate-of-return.

Cash Cost

Royalty = Revenue * Royalty %

Severance Tax = (Revenue - Royalty) * Sevr Tax Rate1 * % Adjustment if needed

Property Tax = (Revenue - Royalty)* property tax rate

Reclamation Tax = Production * reclamation rate2 

Black Lung = Production * (the lesser of 0.55, or 4.4% * sales price of coal)

DOCs (surface mines)

Labor = Production * (Wages + Benefits) / Productivity

Unit Removal Costs

= Cost per yard by equipment type * Amount removed

Added coal haul = year-over-year mileage increase * haul rate * production 

On-going reclamation = production * reclamation rate (as a function of coal depth)

< OR >

DOCs (deep mines)

Labor = Production * (Wages + Benefits) / Productivity

Materials & Supplies

Trucking costs = haul distance from mine to load-out * haul rate

Mine overhead = Cost associated with mine support

Division overhead = Company dependent costs for operations 

Pension = company's portion of employee retirement 

General Definitions:

Revenues = Tons coal produced * sale price/ton

Productivity (TPMH) = Tons coal produced / man hours worked in reporting period 

Stripping Ratio = Overburden Yard / Coal Production

Production = Amount of coal removed from the mine in a given period

Cash cost: is the sum of a mine's Direct Operating Costs (DOCs), Royalty tax, Severance Tax, Property Tax,

 Reclamation Tax and Black Lung fees. 

 1 Severance Tax Rate is state specific

 2 Reclamation Tax used was 0.15 for Deep Mines & 0.35 for Surface Mines

It is important to note that although the formula for calculating mine costs is consistent across 

regions, some tax rates and fees vary by state and mine type. In general, there are two mine 

types: underground (deep) or surface mines. Underground mining is categorized as being either a 

longwall (LW) or a continuous room-and-pillar mine (CM). Geologic conditions and characteristics 

of the coal seams determine which method will be used. Surface mines are typically categorized 

by the type of mining equipment used in their operation such as draglines (DL), or truck & shovels 

(TS). These distinctions are important because the equipment used by the mine affects 

productivity measures and ultimately mine costs. 

Several methods are employed for cost estimation depending on the availability of information and 

the diversity of mining operations. When possible, Wood Mackenzie analysts develop detailed lists 

of mine related costs. Costs such as employee wages & benefits, diesel fuel, spare parts, roof 

bolts and explosives among a host of others are summed to form a mine’s direct operating costs. 
9-19 

Direct costs categories include: mine labor, salaries, material and supplies, and mine overhead. 

The costs are estimated based on labor productivity and mining methods. Labor productivity is 

used to calculate mine labor and salaries by applying an average cost per employee hour to the 

labor productivity figure reported by MSHA or estimated based on comparable mines. For surface 

mines, material and supply costs are estimated based on the mining method (dragline, truckshovel and other) and the number of yards of overburden1

 moved by each method. A cost per 

yard moved is estimated for each mining method and mining region. Where coal is washed, 

washing costs are based on the type of plant being used and the average washing cost per ton for 

the mining region. Overhead costs are estimated based on mine size. 

Labor costs are estimated based on employment data reported to MSHA. MSHA data provides 

employment numbers, employee hours worked and tons of coal produced. These data are 

combined with labor rate estimates from various sources such as union contracts, census data 

and other sources such as state employment websites to determine a cost per ton for mine labor. 

Hourly labor costs vary between United Mine Workers of America (UMWA) and non-union mines, 

and include benefits and payroll taxes. Employees assigned to preparation plants, surface 

activities, and offices are excluded from this category and are accounted for under coal washing 

costs and mine overhead. These preparation plants may be located at the mine site or a central 

preparation plant that washes coal from a number of mines. If the coal is transported to an offsite 

location for washing, transportation costs to the plant are included in the total costs. 

Supply costs are adjusted annually to reflect movements in the price of steel, diesel, natural gas 

and other commodities. Cost adjustments are averaged on an annual basis and analyzed to 

ensure that anomalous spikes in commodity prices are not carried forward in the cost analysis. 

Royalties, severance taxes, black lung fees, reclamation taxes and property taxes are estimated 

using federal, state and local parameters. 

In the Western United States, capital requirements are estimated for each mine and a life-of-mine 

discounted cash flow analysis is used to determine the price required to yield a 10% DCFROR2

, 

including income taxes. In the Eastern United States, the required price is estimated based on 

operating costs and production levels. 

Where information is incomplete, cost items are grouped into categories that can be compared 

with industry averages by mine type and location. These averages can be adjusted up or down 

based on new information or added assumptions. The adjustments take the form of cost 

multipliers or parameter values. Specific cost multipliers are developed with the aid of industry 

experts and proprietary formulas. This method is at times used to convert materials and supplies, 

on-site trucking costs and mine and division overhead categories into unit removal costs by 

equipment type. (This was done in the example shown in Figure 9-3 above.) To check the 

accuracy of these cost estimates, cash flow analysis of publicly traded companies is used. Mine 

cash-costs are extracted from corporate cash flows and compared with the initial estimates. 

Adjustments for discrepancies are made on a case-by-case basis. 

Many of the cost assumptions associated with labor and productivity were taken from the Mine 

Safety Health Administration (MSHA) database. All active mines report information specific to 

production levels, number of employees and employee hours worked. Wood Mackenzie 

supplements the basic MSHA data with information obtained from mine personnel interviews and 

industry contacts. Phone conversations and conferences with industry professionals provide 

 

1

 Overburden refers to the surface soil and rock that must be removed to uncover the coal. 

2

 DCFROR stands for discounted cash flow rate of return (also called “internal rate of return” (IRR) 

and “rate of return”). It is the annualized effective coupounded return that can be earned on 

invested capital. 
9-20 

additional non-reported information such as work schedules, equipment types, percentages of 

washed coal, and trucking distances from the mine to wash-plants and load-out terminals. 

For each active or proposed mine, Wood Mackenzie reports the estimated cost to take coal from 

the mine to a logical point-of-sale. The logical point-of-sale may be a truck or railcar load-out or 

even a barge facility. This is done to produce a consistent cost comparison between mines. Any 

transport costs beyond the point-of-sale terminal are not part of this analysis and are not reflected 

in the supply curves themselves. (Transport costs are taken into account using a separate 

procedure which is described below in section 9.3.) 

In cases where new mines are planned or recoverable reserves are available to support new 

mines (see sections 9.2.6 and 9.2.7 below), Wood Mackenzie uses nearby mines with similar 

geography and geology to estimate mine operating costs and productivity levels. Production levels 

for new mines are estimated based on known reserves, historic precedent, and region specific 

knowledge. 

9.2.3 Supply Curve Development 

Once costs are estimated for all new or existing mines, they are sorted by cash cost, lowest to 

highest, and plotted cumulatively by production to form a supply curve. The supply curve then 

represents all mines – new or existing as well as both underground and surface mines– 

irrespective of market demand. Mines located toward the bottom of the curve have the lowest cost 

and are most likely to be developed while the mines at the top of the curve are higher cost and will 

likely wait to be developed. The process for developing a cumulative supply curve is illustrated in 

Figure 9-4 and Figure 9-5 below. 

Figure 9-4 Illustration of Preliminary Step in Developing a Cumulative Coal Supply Curve 

•

In the table and graph above, mine costs and production are sorted alphabetically by mine name. 

To develop a supply curve from the above table the values must be sorted by mine costs from 

lowest to highest. A new column for cumulative production is added, and then a supply curve 

graph is created which shows the costs on the ‘Y’ axis and the cumulative production on the ‘X’ 

axis. Notice below that the curve contains all mines – new or existing as well as both underground 

and surface mines. The resulting curve is a continuous supply curve but can be modified to show 

costs as a stepped supply curve. (Supply curves in stepped format are used in linear 

programming models like IPM.) See Figure 9-6 for a stepped version of the supply curve example 

shown in Figure 9-5. Here each step represents an individual mine, the width of the step reflects 

the mine’s production, and its height shows the cost of production. (See Appendix 9-1 for a more 

detailed example of how a supply curve is derived from constituent mine costing models.) 
9-21 

Figure 9-5 Illustration of Final Step in Developing a Cumulative Coal Supply Curve 

•

Figure 9-6 Example Coal Supply Curve in Stepped Format 

•

9.2.4 Data Sources Used to Build the Curves 

For active mines, data relating to labor and productivity is taken from MSHA databases. MSHA 

reports on individual mine production, number of employees and employee-hours worked. 

Corporate financial statements of publicly traded companies are listed with the Securities and 

Exchange Commission (SEC). Supplemental information on work schedules, equipment, 

percentages of washed coal, trucking distances between mine and preparation plants is obtained 
9-22 

in interviews performed for Wood Mackenzie’s annually published county-by-county studies. 

Information on recoverable reserves comes from several sources such as Environmental Impact 

Statements (EIS), company annual reports, applications filed at state permitting offices or Lease 

by Application (LBA) filings for mines on federal lands. 

For areas where public information is not available or is incomplete, reserves are estimated using 

geologic reports of nearby properties and some extrapolation by mining engineers and geologists. 

9.2.5 Procedure Used In Determining Mine Productivity 

Projected production and stripping ratios3

 are the key determinants of surface mine productivity. 

Wood Mackenzie assumes mining costs increase as stripping ratios increase. The stripping ratio 

is the quantity of overburden removed relative to the quantity of coal recovered. Assuming that 

reserves are developed where they are easiest to mine and deliver to market, general theory 

suggests that as the easy reserves are depleted, greater amounts of overburden must be handled 

for the same amount of coal production; thus causing a decrease in mining productivity. However, 

this productivity loss is often offset by technology improvements in labor saving equipment. 

While an understanding of the forces affecting productivity is important, no attempt is made to 

develop a complex algorithm that tries to balance increased stripping ratios with added technology 

improvements. Instead, Wood Mackenzie uses reported aggregate productivity (in tons per 

employee hour) provided by MSHA as a starting point and divides the production by the 

productivity calculation to obtain aggregate employee-hours. Allocating aggregate employee hours 

among specific mines, production forecasts for these mines can be converted back into minespecific productivity forecasts. These forecasts are then examined on a mine-by-mine basis by an 

industry expert with region specific knowledge. 

A similar approach is used for underground mines. First, as background, the specific factors 

affecting productivity at such mines are identified. For example, underground mines do not have 

stripping ratios. Productivity estimates for these mines largely depend on the type of mining 

technique used (which is a function of the region’s geology). For instance, longwall-mines can 

produce a high volume of low cost coal but geologic constraints like small reserve blocks and the 

occurrence of faulting tends to limit this technique to certain regions. In addition to geologic 

constraints, there are many variables that can impact underground-mine productivity but they are 

often difficult to quantify and forecast. 

These factors are not used directly but provide a backdrop for deriving productivity estimates. As 

with surface mines Wood Mackenzie relies on MSHA data for its productivity estimates. 

Productivity estimates for underground mines start with the MSHA estimates and are carried 

forward into the forecast years without adjustment. 

9.2.6 Procedure to Determine Total Recoverable Reserves by Region and Type 

Before mine operators are allowed to mine coal, they must request various permits, conduct 

environmental impact studies (EIS) and, in many cases, notify corporate shareholders. In each of 

these instances, mine operators are asked to estimate annual production and total recoverable 

reserves. Wood Mackenzie uses the mine operators’ statements as the starting point for 

production and reserves forecasts. If no other material is available, interviews with company 

personnel will provide an estimate. 

Region and coal type determinations for unlisted reserves are based on public information 

reported for similarly located mines. Classifying reserves this way means considering not only a 

 

3

 Stripping ratio is the amount of waste material (rock and/or soil) that must be removed to recover 

one unit (commonly expressed in short tons) of coal. For example, a stripping ratio of 9.8 means 

that to recover 1 ton of coal you must remove 9.8 tons of waste material. A lower stripping ratio 

means that less waste has to be removed. 
9-23 

mine’s geographic location but also its geologic conditions such as depth and type of overburden 

and the specific identity of the coal seam(s) being mined. For areas where public information is 

not available or is incomplete, Wood Mackenzie engineers and geologists estimate reserve 

amounts based on land surveys and reports of coal depth and seam thickness provided by the 

U.S. Geologic Service (USGS). This information is then used to extrapolate reserve estimates 

from known coal sources to unknown sources. Coal quality determinations for unknown reserves 

are assigned in much the same way. 

Once a mine becomes active, actual production numbers reported in corporate SEC filings and 

MSHA reports are subtracted from the total reserve number to arrive at current reserve amounts. 

Wood Mackenzie consistently updates the reserves database when announcements of new or 

amended reserves are made public. As a final check, the Wood Mackenzie supply estimates are 

balanced against the Demonstrated Reserve Base (DRB)4

 estimates to ensure that they do not 

exceed the DRB estimates. 

9.2.7 New Mine Assumptions 

New mines have been included based on information that Wood Mackenzie maintains on each 

supply region. They include announced projects, coal lease applications and unassigned reserves 

reported by mining companies. Where additional reserves are known to exist, additional 

incremental steps have been added. These incremental steps were added based on 

characteristics of the specific region, typical mine size, and cost trends. They do not necessarily 

imply a specific mine or mine type. 

9.2.8 Other Notable Procedures 

Cost Rounding 

For simplification, the estimated mine costs were rounded so that costs less than 20 $/Ton were 

rounded to the nearest $0.25. Costs that fell between 20 and 50 $/Ton were rounded to the 

nearest $0.50 and costs greater than $50 were rounded to the nearest $1.00. 

Future Cost Adjustments 

For consistency with the cost basis used in EPA Base Case v.4.10, costs are converted to real 

2007$. Wood Mackenzie has assumed that improved productivity will lead to cost reductions in all 

regions except Central Appalachia where depleting reserves will lead to falling productivity and 

increased costs. Costs for all regions except Central Appalachia have been reduced at a rate of 

0.4%/year. Central Appalachia’s costs have been increased at a rate of 0.4%/year based on the 

assumption that labor costs on average account for 40% of the Cost of Production. These regional 

cost adjustments are derived from specific factors affecting costs in regions based on information 

maintained by Wood Mackenzie and their on-going dialog with industry professionals. 

9.2.9 Region Specific Assumptions and Outlooks 

Powder River Basin (PRB) 

Powder River Basin cost curves are based on cost models run for each of the identified projects in 

Wood Mackenzie’s coal supply database. These cost models are run on five year increments over 

a 20 year mine life. These models assume that federal lease tracts are acquired as necessary to 

achieve a 20 year mine life. In preparing the curves for EPA, it was assumed that existing mines 

would operate at projected levels through 2011 and reserves were adjusted to reflect remaining 

reserves at that time. Ten years additional reserves were then added to the remaining reserves 

 

4

Posted by the Energy Information Administration (EIA) in its January, 2007 Coal Production 

Report. 

<=$20, round to nearest $0.25 

>$20 and <=$50, round to nearest $0.50 

>$50, round to nearest $1.00 
9-24 

based on the assumption that additional reserves would be available for lease and the mines 

would continue to operate. Costs for the added reserves were increased by $3.00/ton to reflect 

increased coal leasing costs and increasing mining ratios in the PRB. 

One existing mine, Decker, is expected to close prior to 2012 and was therefore not included in 

the cost curves. 

A MT region was added to accommodate two proposed mines in Montana that do not fit the 

quality specifications for the ME or MP regions. 

There is an annual limit of 612 million tons per year on Wyoming PRB coal production (i.e., coal 

codes WH and WL in Table 9-11) based on expected maximum production from existing mines 

plus potential production from four identified projects. 

Western Bituminous Coalfields 

The Western Bituminous Coalfields include the Colorado, Utah, southern Wyoming, New Mexico 

and Arizona coalfields. Life-of-mine costs are used for all operating mines and identified projects. 

Reserves have been reduced based on projected production through 2011 for existing mines and 

mines that are expected to go into production before 2012. Unlike the PRB no additional reserves 

have been added to the reserve base for existing mines. 

Arizona mine costs are FOB5

 mine. 

In Utah all costs except Deer Creek’s include transportation to a loadout facility. Deer Creek costs 

are based on delivery to the Huntington Canyon power plant. 

In New Mexico, all costs are FOB rail or FOB mine. It is assumed that the Navajo, San Juan 

Underground and the proposed Navajo South/Desert Rock mine will serve their respective minemouth power plants. One existing mine, McKinley, will be mined out by 2012. The proposed 

Carrizozo mine in SE New Mexico is included in the curve. 

In Colorado all costs are FOB mine. This includes the Deserado mine which currently ships all of 

its production to the Bonanza power plant via a private railroad. A CR region has been added to 

accommodate two proposed mines in or near the Raton Basin.

Louisiana (LA)/ Mississippi (MS) 

Louisiana cost curves are based on Wood Mackenzie cost models for existing and planned mines 

in Louisiana. Where a mine’s reserves exceed production requirements over the forecast period, it 

has been assumed that a second mine could be opened on the reserves. A high cost mine with 

cost of $50/ton was added. 

A Mississippi cost curve was added.

Montana Lignite (ME) 

Montana Lignite curves are based on Wood Mackenzie cost estimates for GNP lignite properties. 

All costs are FOB mine. Because lignite typically does not ship well, it is assumed that any new 

mines will be developed to serve mine mouth customers. 

 

5

 FOB stands for “Free On Board” or “Freight on Board.” It indicates the point at which 

responsibility and costs for a goods is transferred from the seller (or shipper) to the buyer. “FOB 

mine” implies that the price includes costs up to the mine and that the buyer assumes costs 

beyond the mine. “FOB rail” implies the prices includes the cost of loading the coal onto a rail car. 

 
9-25 

North Dakota Lignite (ND) 

North Dakota curves are based on Wood Mackenzie cost estimates for the region. Where a 

mine’s reserves exceed production requirements over the forecast period, it has been assumed 

that a second mine could be opened on the reserves. Costs for the new mines were increased by 

$2.00/ton. A GNP project was added as a high cost new mine. 

Oklahoma/Kansas (OK, KS) 

The 2006 set of coal supply curves developed for EPA by Hill and Associates (now a unit of Wood 

Mackenzie) was updated by increasing costs 30% and adding a high cost mine with a cost of 

$100/ton. 

Texas Lignite 

Texas Lignite cost curves are based on cost models run for each of the existing mines and 

identified projects in Wood Mackenzie’s coal supply database. Big Brown was deleted for the 

existing mines as its reserves will be depleted before 2011. 

Illinois Basin (IL, IN, KW) 

Illinois Basin cost curves are based on cost models run for each of the existing mines and 

identified projects in Wood Mackenzie’s coal supply database. Where additional reserves are 

known to be available, additional next step mines were added based on information maintained by 

Wood Mackenzie on the region.

Appalachia (AL, OH, PC, PW, TN, VA, WN & WS) 

Appalachian cost curves are based on Wood Mackenzie’s extensive database of existing and 

planned mines. 2012 production and cost curves were prepared for each region and coal grade 

using the regional model to estimate cost, production and reserve data for existing mines. To 

protect the proprietary nature of the regional curves, mine data were aggregated to produce a 

curve similar to the regional curve without disclosing specific mine data. Cost and production 

estimates for each of the next step mines were prepared for each region and coal type based on 

information maintained by Wood Mackenzie’s knowledge for each region. 

9.2.10 Explanation of Coal Supply Curve Extensions to 2040 

Wood Mackenzie added additional reserves at increased costs on a mine-by-mine basis for each 

region based on its extensive coal resource database and knowledge of the coal industry. A list of 

the mines added by region and coal grade can be found in Appendix 9-2. For modeling purposes 

the 2040 coal supply curves are used in 2050 as well. 

9.3 Coal Transportation 

Within the United States, steam coal for use in coal-fired power plants is shipped via a variety of 

transportation modes, including barge, conveyor belt, rail, truck, and lake/ocean vessel. A given 

coal-fired plant typically only has access to a few of these transportation options and, in some 

cases, only has access to a single type. The number of transportation options that a plant has 

when soliciting coal deliveries influences transportation rate levels that plant owners are able to 

negotiate with transportation providers. 

Within the Eastern United States, rail service is provided predominately by two major rail carriers 

in the region, Norfolk Southern (NS) and CSX Transportation (CSX). Within the Western United 

States, rail service is also provided predominately by two major rail carriers, Burlington Northern 

Santa Fe (BNSF) and Union Pacific (UP). Plants in the Midwestern United States may have 

access to rail service from BNSF, CSX, NS, UP, the Canadian National (CN), Canadian Pacific 

(CP), or short-line railroads. Barge, truck, and vessel service is provided by multiple firms, and 

conveyor service is only applicable to coal-fired plants directly located next to mining operations 

(e.g., mine-mouth plants). 
9-26 

In recent years, transportation rates (especially rail rates) have increased significantly due to 

significant increases in input costs (including fuel prices, steel prices and labor costs), as well as a 

number of Surface Transportation Board (STB) rail rate case decisions that have allowed higher 

rail rates to be charged at plants that are served only by a single railroad. 

The transportation methodology and rates presented below reflect expected long-run equilibrium 

transportation rates as of September 2008, when the coal transportation rate assumptions for EPA 

Base Case v.4.10 were finalized. It is important to remember that these rates do not reflect rates 

that transporters and coal-fired owners may currently be negotiating in the near-term (pre-2012). 

Instead, these rates reflect expected long-term equilibrium levels, including the long-term market 

dynamics that will drive these pricing levels. 

All rates are represented in 2007 real dollars. 

9.3.1 Coal Transportation Matrix Overview 

Description 

In order to model coal transportation rates within the EPA’s modeling construct, a coal 

transportation matrix was developed, which represents a matrix of all the coal demand regions 

and coal supply regions modeled within the IPM model for EPA Base Case v.4.10. The matrix 

includes the associated transportation costs between these supply and demand nodes. Each coal 

demand region covers a set of coal plants having similar transportation infrastructure, 

transportation competitiveness levels, and geographic location; in addition to these criteria, coal 

demand regions are also classified as either “mine-mouth” or “non mine-mouth” regions. Coal 

supply regions are represented by the major coal mining basins modeled in IPM; a more detailed 

discussion on these regions can be found in previous sections. 

Methodology 

Each coal supply region and coal demand region is connected via a transportation link, which can 

include multiple transportation modes. For each transportation link, cost estimates, in terms of 

$/ton, were calculated utilizing mode-based transportation cost factors, analysis of the competitive 

nature of the moves, and overall distance that the coal type must move over each applicable 

mode. An example of the calculation methodology for movements including multiple transportation 

modes is shown in Figure 9-7. 

Figure 9-7 Calculation of Multi-Mode Transportation Costs (Example) 

9.3.2 Calculation of Supply/Demand Region Distances 

Definition of applicable supply/demand regions 

Coal demand regions are linked to coal supply regions based on historical coal deliveries, as well 

as based on the potential for new coal supplies to serve a demand region going forward. A 

demand region may have transportation links with more than one supply region, depending on the 

various coal types that can be physically delivered and burned by generators within a given coal 

demand region. 

Barge Cost ($/ton) =

Loading Cost ($/ton) + Barge Mill Rate + (mills/ton-mile) x Barge Mileage

Transloading

Cost ($/ton)

Rail Cost ($/ton) =

Rail Mill Rate (mills/ton-mile) x Rail 

Mileage +

Barge Cost ($/ton) =

Loading Cost ($/ton) + Barge Mill Rate + (mills/ton-mile) x Barge Mileage

Transloading

Cost ($/ton)

Rail Cost ($/ton) =

Rail Mill Rate (mills/ton-mile) x Rail 

Mileage +
9-27 

Figure 9-8 Coal Demand Region with Multiple Coal Supply Regions 

Transportation Links for Existing Coal-Fired Plants 

Transportation routings for given coal supply regions and coal demand regions were developed 

based on third-party software6

 and other industry knowledge available to Hellerworx and PA 

Consulting Group. Origins for each coal supply region were based on significant mines or other 

significant delivery points within the supply region, and destinations for each coal demand region 

were based on geographical points located near, and with similar key delivery transportation 

characteristics, as the coal plants located within the given coal demand region. For routes utilizing 

multiple modes (e.g. rail-to-barge, truck-to-rail, etc.), distances were developed separately for 

each transportation mode. 

Transportation Links for New Coal-Fired Plants 

Within each coal demand region, coal transportation links representative of the typical 

transportation costs expected to be incurred by new coal plants within that region were developed. 

For coal demand regions where new coal plant construction is not expected to include minemouth plants, the transportation links for new plants are based on transportation links in the 

existing coal demand region that are expected to have costs most similar to those incurred by new 

plants. For coal demand regions where new coal plant construction is expected to consist 

primarily of mine-mouth plants, new transportation links reflecting short-distance transportation of 

local coal supplies were created as needed to properly represent the transportation costs incurred 

by new plants. This methodology helps ensure that coal transportation costs for new coal plants 

are properly integrated with and assessed fairly vis-à-vis existing coal-fired assets within the IPM 

modeling structure. 

9.3.3 Overview of Rail Rates 

Competition within the railroad industry is limited. Two major railroads in the Western U.S. (BNSF 

and UP) and two major railroads in the Eastern U.S. (CSX and NS) currently originate most of the 

U.S. coal traffic that moves by rail. 

In recent years, railroads have increased coal transportation rates in real terms wherever they 

have the opportunity. However, rail rates at plants captive to a single rail carrier are now close to 

the maximum levels prescribed by the STB, which limits the potential for further real increases in 

these rates. Moreover, between 2004 and 2008, the differential between rates at captive plants 

and rates at competitively-served plants narrowed. For all of the coal supply regions except the 

 

6

 Rail routing and mileage calculations utilize ALK Technologies PC*Miler software. 

Coal 

Demand 

Region

Coal Supply 

Region #1

Coal Supply 

Region #2

Coal Supply 

Region #3

Coal 

Demand 

Region

Coal Supply 

Region #1

Coal Supply 

Region #2

Coal Supply 

Region #3
9-28 

Powder River Basin (PRB), the current relatively small differentials between captive and 

competitive rates are expected to persist over the long-term. 

All of the rail rates discussed below include railcar costs, and include fuel surcharges at expected 

2012 fuel price levels. 

Overview of Rail Competition Definitions 

Within the transportation matrix, rail rates are classified as being either captive or competitive, 

depending on the ability of a given coal demand region to solicit supplies from multiple suppliers. 

Competitive rail rates are further subdivided into high- and low-cost competitive subcategories. 

Competition levels are affected both by the ability to take delivery of coal supplies from multiple 

rail carriers, the use of multiple rail carriers to deliver coal from a single source (e.g., BNSF/UP 

transfer to NS/CSX for PRB coal moving east), or the option to take delivery of coal via alternative 

transportation modes (e.g., barge, truck or vessel). 

Table 9-12 Rail Competition Definitions 

Competition Type Definition 

Captive 

Demand source can only access coal supplies through a single 

provider; demand source has limited power when negotiating 

rates with railroads. 

High-Cost 

Competitive 

Demand source has some, albeit still limited, negotiating power 

with rail providers; definition typically applies to demand sources 

that have the option of taking delivery from either of the two major 

railroads in the region. 

Low-Cost 

Competitive 

Demand source has a strong position when negotiating with 

railroads; typically, these demand sources also have the option of 

taking coal supplies via modes other than rail (e.g., barge, truck, 

or lake/ocean vessel). 

 

Rail Rates 

As previously discussed, rail rates are subdivided into three competitive categories: captive, highcost competitive, and low-cost competitive. Moves are further subdivided based on the distance 

that the coal supply must move over rail lines: <200 miles, 200-299 miles, 300-399 miles, 400-699 

miles, and 700+ miles. Within the Western U.S., mileages are only subdivided into two categories 

(<300 miles and 300+ miles), given the longer distances that these coal supplies typically move. 

Initial rate level assumptions were determined based on an analysis of recent rate movements, 

current rate levels in relation to maximum limits prescribed by the STB, expected coal demand, 

diesel prices, recent capital expenditures by railroads, and projected productivity improvements. In 

general, shorter moves result in higher applicable rail rates due to the lesser distance over which 

fixed costs can be spread. As previously discussed, rail rates reflect anticipated 2012 costs in 

2007 real dollars. 

Rates applicable to Eastern moves 

Rail movements within the Eastern U.S. are handled predominately by the region’s two major 

carriers, NS and CSX. Some short movements are handled by a variety of short-line railroads. 

Most plants in the Eastern U.S. are served solely by a single railroad (i.e., they are captive plants). 
9-29 

Table 9-13 Assumed Eastern Rail Rates (2007 mills/ton-mile) 

Mileage Block Captive High-Cost Competitive Low-Cost Competitive 

< 200 72 72 58 

200-299 55 55 43 

300-399 55 55 43 

400-699 37 37 30 

700+ 35 35 28 

 

Rates applicable to Midwestern moves 

Plants in the Midwestern U. S. may be served by BNSF, CN, CP, CSX, NS, UP or short-line 

railroads. However, the rail network in the Midwestern U.S. is very complex, and most plants are 

served by only one of these railroads. The Midwestern U.S. also includes a higher proportion of 

barge-served and truck-served plants than is the case in the Eastern or Western U.S. 

Table 9-14 Assumed Midwestern Rail Rates (2007 mills/ton-mile) 

Mileage Block Captive High-Cost Competitive Low-Cost Competitive 

< 200 72 72 58 

200-299 55 55 43 

300-399 55 55 43 

400-699 36 36 29 

700+ 34 34 27 

 

Rates applicable to Western moves 

Rail moves within the Western U.S. are handled predominately by BNSF and UP. In addition to 

these incumbent carriers, CP acquired the Dakota, Minnesota and Eastern Railroad (DM&E) in 

October 2007, which increases the probability that DM&E’s project to build a third rail line into the 

PRB will be completed. The analysis assumes that DM&E’s entry into the market will influence 

transportation rates for PRB coal by 2012,7

 and the rail rate forecast for PRB coal shipments to 

competitively-served destinations reflects this expectation. 

Rates for Western coal shipments from the PRB are forecast separately from rates for Western 

coal shipments from regions other than the PRB. This reflects the fact that in many cases coal 

shipments from the PRB are subject to competition between BNSF and UP (with the possible 

future entry of DM&E as a third competitor within this region), while rail movements of Western 

coal from regions other than the PRB consist primarily of Colorado and Utah coal shipments that 

originate on UP, and New Mexico coal shipments that originate on BNSF. PRB coal shipments 

also typically involve longer trains moving over longer average distances than coal shipments from 

the other Western U.S. coal supply regions, which means these shipments typically have lower 

costs per ton-mile than non-PRB coal shipments. 

 

7 Note that this is not equivalent to assuming that DM&E’s PRB project would be operational by 

2012. Construction of the DM&E’s PRB project is expected to be a three-year process. However, 

in order to obtain financing and begin construction, DM&E would likely have to negotiate some rail 

contracts for PRB coal shipments. Thus, DM&E’s presence as a third competitor in the market for 

PRB coal shipments might affect rail rates well before DM&E’s additional rail line into the PRB 

became operational 
9-30 

Non-PRB coal moves 

Table 9-15 Assumed Non-PRB Western Rail Rates (2007 mills/ton-mile) 

Mileage Block Captive High-Cost Competitive Low-Cost Competitive 

< 300 43 43 35 

300+ 25 21 21 

 

PRB moves confined to BNSF/UP rail lines 

Table 9-16 Assumed PRB Western Rail Rates (2007 mills/ton-mile) 

Mileage Block Captive High-Cost Competitive Low-Cost Competitive 

< 300 43 43 35 

300+ 23 14 14 

 

PRB moves transferring to Eastern railroads 

For PRB coal moving west-to-east, the coal transportation matrix assumes that the applicable lowcost competitive assumption is applied to the BNSF/UP portion of the rail mileage, and an 

assumption of either $2.16 per ton or 28 mills per ton-mile (whichever is higher) is applied to the 

portion of the movement that occurs on railroads other than BNSF and UP. (The $2.16 per ton 

assumption is a minimum rate for short-distance movements of PRB coal on Eastern railroads.) 

9.3.4 Truck rates 

Truck rates include loading and transport components, and all trucking flows are considered 

competitive because highway access is open to any trucking firm. The truck rates shown in Table 

9-17 are expected long-term equilibrium levels reflective of current rates as of September 2008, 

and expected changes in labor costs, fuel prices, and steel prices. The slightly higher truck rates 

in Utah reflect market conditions specific to that market, which is relatively remote. 

Table 9-17 Assumed Truck Rates (2007 Real Dollars) 

Market Loading Cost ($/ton) Transport (mills/ton-mile) 

Outside of Utah Market 1.03 134 

Utah Market 1.54 134 

 

9.3.5 Barge and Lake Vessel Rates 

As with truck rates, barge rates include loading and transport components, and all flows are 

considered competitive because river access is open to all barge firms. The transportation matrix 

subdivides barge moves into three categories, which are based on the direction of the movement 

(upstream vs. downstream) and the size of barges that can be utilized on a given river. As with the 

other types of transportation rates forecast in this analysis, the barge rate levels shown in Table 

9-18 are expected long-term equilibrium levels reflective of current rates as of September 2008, 

and expected changes in labor costs, fuel prices, and steel prices. 

Rates for transportation of coal by lake vessel on the Great Lakes were forecast on a plantspecific basis, taking into account the lake vessel distances applicable to each movement, the 

expected backhaul economics applicable to each movement (if any), and the expected changes in 

labor costs and fuel and steel prices over the long-term. 
9-31 

Table 9-18 Assumed Barge Rates (2007 Real Dollars) 

Type of Barge Movement Loading Cost 

($/ton) 

Transport 

(mills/ton-mile) 

Mississippi River, and Downstream on the Ohio River 1.75 7.9 

Smaller Size Barges (Allegheny, Kanawha, and 

Monongahela Rivers) 1.85 6.9 

Upstream on Ohio River 1.95 10.4 

 

9.3.6 Transportation Rates for Imported Coal 

Transportation rates for imported coal reflect expectations regarding the long-term equilibrium 

level for ocean vessel rates, taking into account expected long-run equilibrium levels for fuel and 

steel prices, and expected continued strong demand for shipment of dry bulk commodities 

(especially coal and iron ore) from China and other Asian nations. 

In EPA Base Case v.4.10, it is assumed that imported coal is likely to be used only at plants that 

can receive this coal by direct water delivery (i.e., via ocean vessel or barge delivery to the plant). 

This is based on an assessment of recent transportation market dynamics, which suggests that 

railroads are unlikely to quote rail rates that will allow imported coal to be cost-competitive at railserved plants. Moreover, import rates are higher for the Alabama and Florida plants than for New 

England plants because many of the Alabama and Florida plants are barge-served (which 

requires the coal to be transloaded from ocean vessel to barge at an ocean terminal, and then 

moved by barge to the plant), whereas most of the New England plants can take imported coal 

directly by vessel. Transportation rates for imported coal moving to each coal demand region are 

shown in Table 9-19. 

Table 9-19 Assumed Transportation Rates for Imported Coal (2007 Real Dollars) 

Coal Demand 

Region Coal Demand Region Description Transportation Rate 

($/ton) 

ALR2 Alabama rail plants (ALRL)_Low-Cost 

Competitive Not Mine Mouth Barge 15.43 

FL2 Florida plants (FL)_Low-Cost Competitive Not 

Mine Mouth Barge 15.43 

FL3 Florida plants (FL)_Low-Cost Competitive Not 

Mine Mouth Rail 15.43 

GFB1 Gulf barge plants (GFBG)_Low Cost Competitive 

Not Mine Mouth Rail 15.43 

GFB3 Gulf barge plants (GFBG)_Low-Cost Competitive 

Not Mine Mouth Barge 15.43 

NE2 

New England / Hudson River plants / Hudson 

plant (NE)_Low-Cost Competitive Not Mine 

Mouth Barge 

11.32 

NE3 

New England / Hudson River plants / Hudson 

plant (NE)_Low-Cost Competitive Not Mine 

Mouth Rail 

13.37 

TAB1 

Tennessee and Northern Alabama river plants 

(TABG)_High-Cost Competitive Not Mine Mouth 

Rail 

15.43 

 
9-32 

9.3.7 Other Transportation Costs 

In addition to the transportation rates already discussed, the transportation matrix assumes 

various other rates that are applied on a case-by-case basis, depending on the logistical nature of 

a move. These charges apply when coal must be moved between different transportation modes 

(e.g., rail-to-barge or truck-to-barge) – see Table 9-20. 

Table 9-20 Assumed Other Transportation Rates (2007 Real Dollars) 

Coal Demand Region Rate ($/ton) 

Rail-to-Barge 1.23 

Rail-to-Vessel 1.23 

Rail-to-Rail 1.44 

Truck-to-Barge 1.49 

Conveyor 1.13 

 

9.3.8 Long-Term Escalation of Transportation Rates 

Overview of market drivers 

According to data published by the Association of American Railroads (AAR), labor costs 

accounted for about 34% of the rail industry’s operating costs in 2006, and fuel accounted for an 

additional 19%. The remaining 47% of the rail industry’s costs relate primarily to locomotive and 

railcar ownership and maintenance, and track construction and maintenance. 

The RCAF8

 Unadjusted for Productivity (RCAF-U), which tracks operating expenses for the rail 

industry, has increased at an annualized rate of 6.2%/year over the past five years, more than 

double the increase of 2.8%/year in general inflation (GDP-IPD) over the same period. However, 

this largely resulted from steep increases in diesel fuel prices. Excluding fuel, the rail industry’s 

operating costs (as measured by the All-Inclusive Index Less Fuel, or AII-LF), increased by only 

3.5%/year. 

 

8

 The Rail Cost Adjustment Factor (RCAF) refers to several indices created for regulatory 

purposes by the STB, calculated by the AAR, and submitted to the STB for approval. The indices 

are intended to serve as measures of the rate of inflation in rail inputs. The meaning of various 

RCAF acronyms that appear in this section can be found in the insert in Figure 9-9. 
9-33 

Figure 9-9 Rail Cost Indices Performance (2Q2003-2Q2008) 

In addition to diesel fuel price increases, world prices for steel (which is a significant component of 

locomotive, railcar, and track construction and maintenance costs) also increased steeply over the 

past five years, rising from about $290/metric tonne as of June 2003 to about $650/metric tonne 

as of June 2007, and over $1,000/metric tonne as of June 2008. However, during the previous five 

years (2Q1998-2Q2003), when steel prices were less volatile, the AII-LF closely tracked general 

inflation, rising at about 2.1%/year compared with 2.0%/year for the GDP-IPD. 

Additionally, over the past five years, the rate of increase in the rail industry’s labor costs 

(3.0%/year) has closely tracked the increase in the GDP-IPD (2.8%/year.) 

The other major transportation modes used to ship coal (barge and truck) have cost drivers 

broadly similar to those for rail transportation (labor costs, fuel costs, and equipment costs). 

However, a significant difference in cost drivers between the transportation modes relates to the 

relative weighting of fuel costs for the different transportation modes. Estimates show that, at 2006 

fuel prices, fuel costs accounted for about 20% of long-run marginal costs for the rail industry, 

35% of long-run marginal costs for barges, and 50% of long-run marginal costs for trucks. 
9-34 

Figure 9-10 Long-Run Marginal Cost Breakdown by Transportation Mode 

9.3.9 Market Drivers Moving Forward 

Diesel fuel prices 

The Energy Information Administration’s (EIA’s) Annual Energy Outlook (AEO)9

 forecast of longterm equilibrium prices for diesel fuel shows expected prices ranging from about $2.62/gallon in 

2012 to about $2.77/gallon in 2030 (2007 real dollars). This range of prices is comparable to the 

actual average on-highway diesel fuel price for 2006 which was $2.78/gallon (2007 real dollars). 

The coal transportation rate forecast for EPA Base Case v.4.10 assumes that diesel fuel prices 

will return to these long-run equilibrium levels by 2012. 

Table 9-21 EIA AEO Diesel Fuel Forecast, 2012-2030 (2007 Real Dollars) 

Year Rate ($/gallon) 

2012 2.62 

2015 2.49 

2020 2.57 

2025 2.61 

2030 2.77 

Annualized % Change, 2025-2030 1.10% 

Source: EIA 

 

9

 As noted at the beginning of this section, the coal transportation rate assumptions for EPA Base 

Case v.4.10 were finalized in September 2008. At that time, the Annual Energy Outlook 2008 

forecast was the latest available. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Rail Barge Truck

Fuel Other
9-35 

Iron ore prices 

ABARE’s10 forecast of iron ore prices shows an expectation that iron ore prices will return to late 

2007/early 2008 levels (i.e., to the levels prevailing before the most recent price spike) by 2012, 

and to decline by about 18% in real terms for their 5-year forecast period (2008-2013) as a whole. 

Table 9-22 ABARE Forecast of Iron Ore Prices 

2007 $/metric tonne 

ABARE Estimate of Average Price for Australian 

Iron Ore Exports, Year Ending (YE) March 2008 67.72 

ABARE Forecast for YE Mar 2009 98.68 

ABARE Forecast for YE Mar 2010 91.19 

ABARE Forecast for YE Mar 2011 73.73 

ABARE Forecast for YE Mar 2012 61.84 

ABARE Forecast for YE Mar 2013 55.52 

Total Percent Change (2008-2013) -18.00% 

Source: ABARE, Australian Commodities, vol. 15 no. 1 and 2, March and 

June Quarters 2008 

Labor costs 

Labor costs for the rail industry are expected to continue to escalate at approximately the same 

rate as overall inflation (i.e., labor costs are expected to be approximately flat in real terms). Due 

to the fact that competition is stronger in the barge and trucking industries than in the rail industry, 

labor costs in the barge and truck industries are likely to increase at rates similar to or slightly 

slower than the increase in rail labor costs. 

Productivity gains 

The most recent data published by AAR (covering 2002-2006) shows that rail industry productivity 

increased at an annualized rate of approximately 1.2% per year during this period. However, due 

to limited competition in the rail industry, these productivity gains were generally not passed 

through to shippers. In addition, the potential for significant productivity gains in the trucking 

industry is relatively limited since truck load sizes, operating speeds, and truck driver hours are all 

regulated by law. 

Long-Term Escalation of Coal Transportation Rates 

Based on the foregoing discussion, the transportation rate forecast assumes flat real escalation of 

rail and truck rates, and a 1% per year real decline in barge and lake vessel rates, which reflects 

some pass-through of productivity gains in those highly competitive industries, over the 2012-2025 

period. 

However, EIA’s forecast of diesel fuel prices, which is essentially flat in real terms during the 

2012-2025 period, predicts a relatively steep rise in diesel fuel prices (annualized increase of 

1.1%/year) between 2025 and 2030. Because of this, coal transportation rates are assumed to 

escalate as follows during the 2026-2062 period: 

• Rail: 1.1% annual real increase in fuel prices x 20% fuel cost weighting = real rate increase of 

0.2%/year. 

• Truck: 1.1% annual real increase in fuel prices x 50% fuel cost weighting = real rate increase 

of 0.5%/year. 

 

10 ABARE is a branch of the Australian government that forecasts prices and trade volumes for a 

wide variety of commodities that Australia exports. Australia is a major exporter of iron ore, 

accounting for about 32% of total worldwide iron ore exports in 2007. See 

www.abareconomics.com 
9-36 

• Barge and lake vessel: 1.1% annual real increase in fuel prices x 35% fuel cost weighting = 

real input cost increase of 0.4%/year, less 1% per year for pass-through of productivity gains 

= real rate decline of 0.6%/year. 

• Conveyor: no change in real terms throughout the study period. 

9.3.10 Other Considerations 

Transportation constraints limiting the growth of PRB coal use 

The rate at which coal shipments from the PRB (Montana and Wyoming) regions can be 

increased is somewhat limited in the near-term by the capacity of the rail lines that transport the 

coal from these regions. Hence, the following limits on the growth of PRB coal production are 

implemented in IPM: 

• Wyoming PRB coal growth is limited to 15 million short tons additional production capacity 

each year. 

• Montana coal growth is limited to 2 million short tons additional production capacity each year. 

Table 9-23 Assumed Production Growth Rates 

Coal Supply Source Growth/Year (MM short tons) 

Wyoming PRB 15 

Montana 2 

Other transportation constraints 

This analysis does not consider the February 10, 2009 announcement by Norfolk Southern and 

Canadian National Railway to share rail lines and enhance the efficiency of service out of the 

Illinois Basin coal supply region (Mid-American Corridor). This announcement has the potential to 

alleviate an existing bottleneck (both rate-based and logistical-based) that has historically 

prevented large volumes of coal moving from the Illinois Basin to Southeastern coal-fired facilities, 

although it is too early to know the full impact of this arrangement. 

Global recession 

The analysis underlying the coal transportation assumptions as described above was completed 

prior to experiencing the full impact of the current global recession on the energy industry. In 

addition to downward pressure on fuel and steel prices, the recession led to large declines in 

industrial coal and electricity demand. Coal-fired plants, already faced with a glut of stockpiled 

coal, saw excess supply further balloon due to relatively mild temperatures throughout 2009 and 

historically low gas prices that led to some gas-fired facilities displacing more marginal, highercost, coal-fired facilities. In the face of declining demand, coal transporters saw movements fall 

dramatically as contracted tonnage was deferred and contracts were reworked. However, it 

remains to be seen how, or if, transporters will adjust rates in the face of changing demand 

dynamics. For example, railroads demonstrated little desire to lower rates in recent contract 

negotiations even as coal volumes shipped by rail were off 9.3% from year-to-date 2008 levels as 

of September 12, 2009. 

9.4 Coal Exports, Imports, and Non-Electric Sectors Demand 

The coal supply curves used in EPA Base Case v.4.10 represent the total steam coal supply in 

the United States. While the U.S. power sector is the largest consumer of native coal – roughly 

93% of mined U.S. coal in 2007 was used in electricity generation – non-electric demand must 

also be taken into consideration in IPM modeling in order to determine the market clearing price. 

Furthermore, some coal mined within the U.S. is exported out of the domestic market, and some 

foreign coal is imported for use in electricity generation, and these changes in the coal supply 

must also be detailed in the modeling of the coal supply available to coal power plants. The 

projections for imports, exports, and non-electric sector coal demand are based on EIA’s AEO 

2010. 
9-37 

In EPA Base Case v.4.10 coal exports and coal-serving residential, commercial and industrial 

demand are designed to correspond as closely as possible to the projections in AEO 2010 both in 

terms of the coal supply regions and coal grades that meet this demand. The projections used 

exclude exports to Canada, as the Canadian market is modeled endogenously within IPM. First, 

the subset of coal supply regions and coal grades in EPA Base Case v.4.10 are identified that are 

contained in or overlap geographically with those EIA Coal Market Module (CMM) supply regions 

and coal grades that are projected as serving exports and non-electric sector demand in AEO 

2010. Next, coal for exports and non-electric demand are constrained by CMM supply region and 

coal grade to meet the levels projected in AEO 2010. These levels are shown in Table 9-24 and 

Table 9-25. (Since the AEO 2010 time horizon extends to 2035 and EPA Base Case v.4.10 to 

2050, the AEO projected levels for 2035 are maintained through 2050.). IPM then endogenously 

determines which IPM coal supply region(s) and coal grade(s) will be selected to meet the 

required export or non-electric sector coal demand as part of the cost-minimization coal market 

equilibrium. Since there are more coal supply regions and coal grades in EPA Base Case v.4.10 

than in AEO 2010 the specific regions and coal grades that serve export and non-electric sector 

demand are not pre-specified but modeled. 

Imported coal is assumed to cost 30.81 2007$/Ton, and is only available to plants in the eight 

demand regions which are eligible to receive imported coal. The eight coal demand regions which 

may receive imported coal, along with the cost of transporting this coal to the demand regions, are 

summarized in Table 9-19. The total US imports of steam coal are limited as shown in Table 9-26. 

Table 9-24 Coal Exports 

Name 2012 2015 2020 2030 2040 -2050 

Rocky Mountains - Bituminous Low Sulfur 1.24 0.97 0.45 0.84 1.08 

Central Appalachia - Bituminous Medium Sulfur 6.69 7.74 7.4 7.31 6.96 

East Interior - Bituminous Medium Sulfur 6.46 4.29 0 0 0 

Northern Appalachia - Bituminous Medium Sulfur 4.57 3.02 0 0 0 

Wyoming Southern PRB - Subbituminous Low Sulfur 0.03 0.04 0.05 0.09 0.12 

 
9-38 

Table 9-25 Residential, Commercial, and Industrial Demand 

Name 2012 2015 2020 2030 2040 - 

2050 

East Interior - Bituminous High Sulfur 6.84 7.06 7.1 6.97 6.88 

Northern Appalachia - Bituminous High Sulfur 1.12 1.16 1.16 1.14 1.12 

West Interior - Bituminous High Sulfur 1.59 1.85 1.99 1.98 1.95 

Central Appalachia - Bituminous Low Sulfur 4.8 4.98 5.01 4.89 4.8 

Southern Appalachia - Bituminous Low Sulfur 0.21 0.22 0.22 0.21 0.21 

Rocky Mountain - Bituminous Low Sulfur 3.78 4.03 4.1 4.06 3.97 

Arizona/New Mexico - Bituminous Low Sulfur 0.41 0.43 0.44 0.44 0.43 

Central Appalachia - Bituminous Medium Sulfur 13.3 13.84 13.93 13.66 13.42 

East Interior - Bituminous Medium Sulfur 0.82 0.84 0.84 0.83 0.82 

Northern Appalachia - Bituminous Medium Sulfur 4.02 4.16 4.17 4.05 3.97 

Southern Appalachia - Bituminous Medium Sulfur 1.36 1.41 1.42 1.4 1.37 

Gulf Lignite - High Sulfur 2.46 2.57 2.59 2.54 2.49 

Dakota Lignite - Medium Sulfur 5.26 5.43 5.46 5.36 5.3 

Western Montana - Subbituminous Low Sulfur 0.43 0.19 0.03 0 0 

Western Wyoming - Subbituminous Low Sulfur 0.92 0.98 1 1 0.98 

Wyoming Northern PRB - Subbituminous Low Sulfur 3.85 3.99 4.01 3.94 3.88 

Western Wyoming - Subbituminous Medium Sulfur 1.03 1.11 1.14 1.13 1.1 

Arizona/New Mexico - Subbituminous Medium Sulfur 0.1 0.11 0.11 0.11 0.11 

 

Table 9-26 Coal Import Limits 

2012 2015 2020 2030 2040 - 

2050 

Annual Coal Imports Cap (Million Short Tons) 30.0 28.9 36.0 36.2 51.5 
Appendix 9-1.1 

Appendix 9-1. Illustrative Example of Wood Mackenzie Costing Procedure 

Used in Developing EPA’s Coal Supply Curves 

To further demonstrate the procedures used in preparing Wood Mackenzie’s cost tables, a sample 

was prepared for the Colorado, Green River Basin, 0.81-1.20 lbs. SO2/MMbtu coals. This region 

was selected because it contains both surface and underground mines as well as existing (E) and 

planned new mines (N). 

The initial step was to prepare cost models for the selected mines. The mine names have been 

replaced with mine step designations: E01, E02, E03, N01, N02 and N03. Production and 

productivity assumptions for the mines have been modified to mask the mines selected for this 

sample procedure. Cost models were prepared for E01, E02, E03, N02 and N03. N01 was not 

modeled because it is a proposed replacement for E03 and is expected to have a cost structure 

very similar to E03. The cost model was run in 2008$ and used to solve for the sales price 

required to return a 10% DCFROR for the mine. 

In the following pages of this appendix individual cost models (in the form of a series of 

spreadsheets) are provided for mines E01_S, EO2_UG, EO3_UG, NO2_UG, and NO3_UG, 

Each mine’s spreadsheet consists of 4 pages that capture the costs and cash flows for the mines 

over the 2008 – 2035 time period. The first page in each spreadsheet model provides production 

and productivity data for the mine. The second page shows its capital requirements. The third 

page contains a summary of capital expenditures. The fourth page pulls together all costs and 

cash flows and (in the third row from the top) derives the required sales price on the assumption of 

a 10% rate of return. 

The model results obtained for each mine were then loaded into the “EPA Cost Curve Worksheet,” 

which appears on the last page of this appendix. (The “sales prices ($/ton)” from the mine costing 

models can be seen in the 11th column (“Cost of Production (2008$)”) of the cost curve worksheet. 

 This worksheet also contains EPA’s coal region and coal type data as well as Wood Mackenzie 

region and type codes. (The Wood Mackenzie codes were included to assist in the proper 

assignment of costs for areas where cost data was prepared and grouped based on Wood 

Mackenzie codes.) Additional data includes mine names, step names, codes for existing or new 

mines, mine type (used for western mines), heat content, production rate and reserves. 

In conjunction with transferring the costs generated for each mine to the “EPA Cost Curve 

Worksheet,” a number of adjustments were made to support their use in EPA’s IPM electric sector 

model: 

(1) There are a number of differences in the values appearing in the 11th column and the 

corresponding “sales price” values that appeared in the individual mine costing models. For 

example, it was assumed the N01 production costs would be the same as the mine it is replacing 

but additional transportation will be required to move the coal to the mine loadout and partial 

washing would take place. To account for these additional costs $1.00/ton was added to the Cost 

of Production of E03 to estimate the cost for N01. In the case of N03, it was assumed that 

additional transportation from the mine mouth to the loadout will be required so an additional 

$1.00/ton was added to the model results. This adjustment was based on a separate modeling 

analysis that Wood Mackenzie performed to estimate the cost of production at N03. Because this 

modeling contained mine specific and proprietary data, it could not be included in this appendix. 

(2) Because the mine costing model estimates were prepared in 2008$, the costs were converted 

(deflated) to constant 2007$, which is the cost basis used in EPA Base Case v.4.10. (This 

conversion can be seen in the 11th (“Cost of Production (2008$)”) and 12th (“Cost of Production 

(2007$)”) columns of the Cost Curve Worksheet.) 
Appendix 9-1.2 

(3) In running the individual cost models for new mines, Wood Mackenzie makes certain 

assumptions regarding the start-up date for the mine. In transferring the costs generated by the 

cost models to the EPA Cost Curve Worksheet it is assumed that the new mines could be opened 

by 2012 if demand exists and EPA’s IPM model is allowed to determine when the mine will be 

opened. 

(4) Wood Mackenzie has assumed that labor productivity in all Producing Regions except Central 

Appalachia will increase at a rate of 1% per year. Productivity in Central Appalachia is expected to 

fall 1% per year. These productivity assumptions affect future Cost of Production estimates. All 

regions except Central Appalachia were deflated 0.4% per year while it was inflated by 0.4% per 

year. The 0.4% adjustment is based on the assumption that labor costs on average account for 

40% of the Cost of Production. In the EPA Cost Curve Worksheet the productivity adjustments 

appear in the 13th (“deflator”) and 14th (“deflated cost”) columns. The 0.4% productivity growth 

assumption means that in the 4 years between 2008 (the net present value year used in the mine 

costing spreadsheets) and 2012 (the first model year in EPA’s IPM base case) productivity would 

increase by a factor of 1.02 (shown in the 13th column) and, consequently, the cost shown in the 

12th column would have to be divided by this deflator (13th column) to obtain the deflated costs 

shown in the 14th column 

(5) Costs were then rounded by the procedure described above in section 9.3.8 to obtain the 

“Final Cost” values shown in the 15th column. 

Besides the adjustments described above and shown in the cost curve worksheet, other 

adjustments to costs were made to meet EPA’s need for cost and production data out to 2040 and 

beyond. Wood Mackenzie’s cost models are generally run for a maximum of 20 years even 

though additional, higher cost reserves are known to exist. When production and reserve data 

were pushed past reserve estimates typically used in the cost models, additional reserves were 

added and costs were increased. Appendix 9-2 lists the new mines that were included in the 2040 

curves. As a quality assurance check, if additional reserves were assigned to any coal region and 

type, the resulting totals were tested against EIA Reserve Estimate – 2006 (Table 15_06) to 

insure reserves were not overstated and to establish an upper geologic limit for reserves in any 

area. 
Appendix 9-1.3 

Mine: E01_SProduction Data

Year Tons In-Situ Effective

(000) DL Yds T/S Yds Total Yds Ratio DL % DL Yds T/S Yds Total Yd

(000) (000) (000) Rehandle (000) (000) (000)

2008 2,500 24,500 0 24,500 9.8 10% 26,950 0 22009 2,500 24,500 0 24,500 9.8 10% 26,950 0 22010 2,500 24,500 0 24,500 9.8 10% 26,950 0 22011 2,500 24,500 0 24,500 9.8 10% 26,950 0 22012 2,500 24,500 0 24,500 9.8 10% 26,950 0 22013 2,500 24,500 0 24,500 9.8 10% 26,950 0 22014 2,500 24,500 0 24,500 9.8 10% 26,950 0 22015 2,500 24,500 0 24,500 9.8 10% 26,950 0 22016 2,500 24,500 0 24,500 9.8 10% 26,950 0 22017 2,500 24,500 0 24,500 9.8 10% 26,950 0 22018 2,500 24,500 0 24,500 9.8 10% 26,950 0 22019 2,500 24,500 0 24,500 9.8 10% 26,950 0 22020 2,500 24,500 0 24,500 9.8 10% 26,950 0 22021 2,500 24,500 0 24,500 9.8 10% 26,950 0 22022 2,500 24,500 0 24,500 9.8 10% 26,950 0 22023 2,500 24,500 0 24,500 9.8 10% 26,950 0 22024 2,500 24,500 0 24,500 9.8 10% 26,950 0 22025 2,500 24,500 0 24,500 9.8 10% 26,950 0 22026 2,500 24,500 0 24,500 9.8 10% 26,950 0 22027 2,500 24,500 0 24,500 9.8 10% 26,950 0 220282029203020312032

50,000 490,000 0 490,000 9.8 539,000 0 539

$/ton

Appendix 9-1 (Cont’d) Illustrative Example 
Appendix 9-1.4 

Mine: E01_SCapital Requirements ($ X 1000)Capital Contingency: 0%Miles of Rail spur: 0Coal Storage: 10000

Year Acqisition Develop. Rail Facilities Truck Shovel Dragline Coal Load & Haul Miscellaneous 

Initial Repl Initial Repl Initial Repl Initial Repl 

2008 0 0 15,878 0 64,680 9,720 16,368 2009 0 0 0 0 2010 0 0 0 0 2011 0 0 0 0 2012 0 0 0 0 2013 0 0 0 0 2014 0 0 0 0 2015 0 0 0 0 16,368 2016 0 0 0 0 0 2017 0 0 0 0 0 2018 0 0 0 0 4,082 0 0 2019 0 0 0 0 0 0 0 2020 0 0 0 0 0 0 0 2021 0 0 0 0 0 0 0 2022 0 0 0 0 0 0 16,368 2023 0 0 0 0 0 0 0 2024 0 0 0 0 0 0 0 2025 0 0 0 0 0 0 0 2026 0 0 0 0 0 0 0 2027 0 0 0 0 0 0 0 20282029203020312032

0 0 0 15,878 0 0 64,680 0 9,720 4,082 16,368 32,736 

0.00 0.00 0.00 0.32 0.00 0.00 1.29 0.00 0.19 0.08 0.33 0.65 
Appendix 9-1.5 

Mine: E01_SCapital Expenditure Summary

Year Acquisition Development Depreciable Property Tax Depreciation Working Total

Assets Base Capital Capital

2008 0 0 106,646 106,646 14,025 3,993 110,6392009 0 0 0 106,646 14,025 0 02010 0 0 0 106,646 14,025 0 02011 0 0 0 106,646 14,025 0 02012 0 0 0 106,646 14,025 0 02013 0 0 0 106,646 14,025 0 02014 0 0 0 106,646 14,025 0 02015 0 0 16,368 106,646 3,397 0 16,3682016 0 0 0 106,646 3,397 0 02017 0 0 0 106,646 3,397 0 02018 0 0 4,082 106,646 3,980 0 4,0822019 0 0 0 106,646 3,980 0 02020 0 0 0 106,646 3,980 0 02021 0 0 0 106,646 3,980 0 02022 0 0 16,368 106,646 3,980 0 16,3682023 0 0 0 106,646 2,921 0 02024 0 0 0 106,646 2,921 0 02025 0 0 0 106,646 2,338 0 02026 0 0 0 106,646 2,338 0 02027 0 0 0 106,646 2,338 -3,993 -3,99320282029203020312032

0 0 143,464 141,126 0 143,464
Appendix 9-1.6 

Mine: E01_SRequired Sales PriceSales Price ($/ton): $20.716 Sev. Taxes: Rate ($/ton) $0.54Discount Rate: 10% Adjustment 0%Net Present Value: $0 Property Taxes Mill Levy (in mills): 44Cost Contingency Factors: 10% Assessment rate: 25%Initial Labor Productivity (t/mh): 9 Income Taxes: Federal 34%Average Coal Thickness (ft): 45 State 6%UMWA (Y or N): N Royalty: 12.5%

Year Tons Revenue Direct Royalty Taxes (other than income) Development Depreciation Depletion Taxes Net Income Op

Operating Severance Black Recl. Property Cost 

Cost Lung 

2008 2,500 51,789 23,958 6,474 702 1,375 875 570 0 14,025 306 122 184 2009 2,500 51,789 23,958 6,474 702 1,375 875 570 0 14,025 306 122 184 2010 2,500 51,789 23,958 6,474 702 1,375 875 570 0 14,025 306 122 184 2011 2,500 51,789 23,958 6,474 702 1,375 875 570 0 14,025 306 122 184 2012 2,500 51,789 23,958 6,474 702 1,375 875 570 0 14,025 306 122 184 2013 2,500 51,789 23,958 6,474 702 1,375 875 570 0 14,025 306 122 184 2014 2,500 51,789 23,958 6,474 702 1,375 875 570 0 14,025 306 122 184 2015 2,500 51,789 23,958 6,474 702 1,375 875 570 0 3,397 3,625 3,046 4,569 2016 2,500 51,789 23,958 6,474 702 1,375 875 570 0 3,397 3,625 3,046 4,569 2017 2,500 51,789 23,958 6,474 702 1,375 875 570 0 3,397 3,625 3,046 4,569 2018 2,500 51,789 23,958 6,474 702 1,375 875 570 0 3,980 3,625 2,813 4,219 2019 2,500 51,789 23,958 6,474 702 1,375 875 570 0 3,980 3,625 2,813 4,219 2020 2,500 51,789 23,958 6,474 702 1,375 875 570 0 3,980 3,625 2,813 4,219 2021 2,500 51,789 23,958 6,474 702 1,375 875 570 0 3,980 3,625 2,813 4,219 2022 2,500 51,789 23,958 6,474 702 1,375 875 570 0 3,980 3,625 2,813 4,219 2023 2,500 51,789 23,958 6,474 702 1,375 875 570 0 2,921 3,625 3,236 4,855 2024 2,500 51,789 23,958 6,474 702 1,375 875 570 0 2,921 3,625 3,236 4,855 2025 2,500 51,789 23,958 6,474 702 1,375 875 570 0 2,338 3,625 3,470 5,205 2026 2,500 51,789 23,958 6,474 702 1,375 875 570 0 2,338 3,625 3,470 5,205 2027 2,500 51,789 23,958 6,474 702 1,375 875 570 0 2,338 3,625 3,470 5,205 20282029203020312032

50,000 1,035,785 479,159 129,473 14,040 27,500 17,500 11,394 0 141,126 49,271 40,943 61,414 

20.72 9.58 2.59 0.28 0.55 0.35 0.23 0.00 2.82 0.99 0.82 1.23 
Appendix 9-1.7 
Appendix 9-1.8 

Mine: E02_UGProduction & Productivity Data% Washed 70%Plant Recovery: 70%Production by Equipment at Full Production % Longwall Production: 80% % CM Production: 20% % CV Production: 0%

Year Clean CV ROM CM ROM LW ROM Total ROM Overall Haul

Tons Tons Tons Tons Tons Recovery Distance

(000) (000) (000) (000) (000) % (miles)

2008 2,000 0 506 2,026 2,532 79% 2009 2,000 0 506 2,026 2,532 79% 2010 2,000 0 506 2,026 2,532 79% 2011 2,000 0 506 2,026 2,532 79% 2012 2,000 0 506 2,026 2,532 79% 2013 2,000 0 506 2,026 2,532 79% 2014 2,000 0 506 2,026 2,532 79% 2015 2,000 0 506 2,026 2,532 79% 2016 2,000 0 506 2,026 2,532 79% 2017 2,000 0 506 2,026 2,532 79% 2018 2,000 0 506 2,026 2,532 79% 2019 2,000 0 506 2,026 2,532 79% 2020 2,000 0 506 2,026 2,532 79% 2021 2,000 0 506 2,026 2,532 79% 2022 2,000 0 506 2,026 2,532 79% 2023 2,000 0 506 2,026 2,532 79% 2024 2,000 0 506 2,026 2,532 79% 2025 2,000 0 506 2,026 2,532 79% 2026 2,000 0 506 2,026 2,532 79% 2027 2,000 0 506 2,026 2,532 79% 2028 2,000 0 506 2,026 2,532 79% 2029203020312032

42,000 10,634 42,538 53,172 79%

$/ton
Appendix 9-1.9 

Mine: E02_UGCapital Requirements ($ X 1000)

production

Capital Contingency: 0% CV Mining Ht: 8.0 Capital Contingency: -75% < 500kMiles of Rail spur: 0 CM Mining Ht: 8.0 -50% 500k<= & < 750kCoal Storage: 0 LW Mining Ht: 8.0 0% >750kDepth to Shafts: 100No. of Men/Supply Shafts 1No. of Air Shafts 1 Shafts: if prod < 1000k, 1 M&S + 1 Air

if prod > 1000k, 2 M&S + 1 Air

Year Acqisition Exploration Development Shaft Surface Prep Plant Rail Conventional Sections Continuous Miners Longwalls Fixe

& Labor Capital Facilities Units Initial Repl Units Initial Repl Units Initial Repl In

Engineering Cost & Equip. Required $ $ Required $ $ Required $ $ 

2008 1,920 59,940 13,774 11,391 18,990 0 0 0 2 9,000 1 37,500 2009 00 20 10 2010 00 20 10 2011 00 20 10 2012 00 20 10 2013 00 20 10 2014 00 20 10 2015 0 0 0 2 0 9,000 1 0 37,500 2016 0002001002017 0002001002018 0002001002019 0002001002020 0002001002021 0002001002022 0 0 0 2 0 9,000 1 0 37,500 2023 0002001002024 0002001002025 0002001002026 00 20 10 2027 00 20 10 2028 00 20 10 2029203020312032

0 1,920 59,940 13,774 11,391 18,990 0 0 0 9,000 18,000 37,500 75,000 

0.00 0.05 1.43 0.33 0.27 0.00 0.00 0.00 0.21 0.43 0.89 1.79 
Appendix 9-1.10 

Mine: E02_UGCapital Expenditure Summary

Year Acquisition Exploration Depreciable Assets Property Tax Depreciation W

& 7 Year Life 15 Year Life Total Base 7 Year Life 15 Year Life Total C

Engineering

2008 0 1,920 67,129 104,095 171,224 171,224 9,590 6,940 16,529 2009 0 0 0 0 0 171,224 9,590 6,940 16,529 2010 0 0 0 0 0 171,224 9,590 6,940 16,529 2011 0 0 0 0 0 171,224 9,590 6,940 16,529 2012 0 0 0 0 0 171,224 9,590 6,940 16,529 2013 0 0 0 0 0 171,224 9,590 6,940 16,529 2014 0 0 0 0 0 171,224 9,590 6,940 16,529 2015 0 0 67,129 0 67,129 171,224 9,590 6,940 16,529 2016 0 0 0 0 0 171,224 9,590 6,940 16,529 2017 0 0 0 0 0 171,224 9,590 6,940 16,529 2018 0 0 0 0 0 171,224 9,590 6,940 16,529 2019 0 0 0 0 0 171,224 9,590 6,940 16,529 2020 0 0 0 0 0 171,224 9,590 6,940 16,529 2021 0 0 0 0 0 171,224 9,590 6,940 16,529 2022 0 0 67,129 0 67,129 171,224 9,590 6,940 16,529 2023 0 0 0 0 0 171,224 9,590 0 9,590 2024 0 0 0 0 0 171,224 9,590 0 9,590 2025 0 0 0 0 0 171,224 9,590 0 9,590 2026 0 0 0 0 0 171,224 9,590 0 9,590 2027 0 0 0 0 0 171,224 9,590 0 9,590 2028 0 0 0 0 0 171,224 9,590 0 9,590 2029203020312032

0 1,920 201,386 104,095 305,481 201,386 104,095 305,481 

0.00 0.05 4.79 2.48 7.27 4.79 2.48 7.27 
Appendix 9-1.11 

Mine: E02_UGRequired Sales Price ($ X 1000)Sales Price ($/ton): $36.476 Sev. Taxes: Rate $0.27Discount Rate: 10.00% Adjustment 100.0%Net Present Value: $0 Prop. Taxes Tax Rate (in mills) 60Cost Contingency Factors: 10% % of revenue basis for taxAverage Coal Thickness (ft): 6 Assessment rate: 25.0%Tons/Man-hour 6.0 Income TaxesFederal 34.00%

UMWA (Y or N): Y State 6.00%Product (Steam or Met) S Royalty 8.0%

% of Reserve owned: 0%

Year Tons Revenue Direct Royalty Taxes (other than income) Corp G&A, Development Depreciation Depletion Taxes Net Income 

Operating Severance Black Recl. Property Selling & Cost 

Cost Lung Acc. Pen. 

2008 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 1,920 16,529 4,004 1,601 2,402 2009 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2010 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2011 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2012 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2013 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2014 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2015 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2016 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2017 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2018 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2019 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2020 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2021 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2022 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 16,529 4,964 1,985 2,978 2023 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 9,590 5,369 4,599 6,899 2024 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 9,590 5,369 4,599 6,899 2025 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 9,590 5,369 4,599 6,899 2026 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 9,590 5,369 4,599 6,899 2027 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 9,590 5,369 4,599 6,899 2028 2,000 72,953 34,737 5,836 216 2,200 300 1,007 2,200 0 9,590 5,369 4,599 6,899 2029203020312032

42,000 1,532,003 729,469 122,560 4,536 46,200 6,300 21,142 46,200 1,920 305,481 105,712 56,993 85,490 

36.48 17.37 2.92 0.11 1.10 0.15 0.50 1.10 0.05 7.27 2.52 1.36 2.04 
Appendix 9-1.12 

Mine: E03_UGProduction & Productivity Data% Washed 0%Plant Recovery: 100%Production by Equipment at Full Production % Longwall Production: 80% % CM Production: 20% % CV Production: 0%

Year Clean CV ROM CM ROM LW ROM Total ROM Overall Haul

Tons Tons Tons Tons Tons Recovery Distance

(000) (000) (000) (000) (000) % (miles)

2008 9,000 0 1,800 7,200 9,000 100% 2009 9,000 0 1,800 7,200 9,000 100% 2010 9,000 0 1,800 7,200 9,000 100% 2011 9,000 0 1,800 7,200 9,000 100% 2012 9,000 0 1,800 7,200 9,000 100% 2013 9,000 0 1,800 7,200 9,000 100% 2014 9,000 0 1,800 7,200 9,000 100% 2015 9,000 0 1,800 7,200 9,000 100% 2016 9,000 0 1,800 7,200 9,000 100% 2017 9,000 0 1,800 7,200 9,000 100% 2018 9,000 0 1,800 7,200 9,000 100% 2019 9,000 0 1,800 7,200 9,000 100% 2020 9,000 0 1,800 7,200 9,000 100% 2021 9,000 0 1,800 7,200 9,000 100% 2022 9,000 0 1,800 7,200 9,000 100% 2023 9,000 0 1,800 7,200 9,000 100% 2024 9,000 0 1,800 7,200 9,000 100% 2025 9,000 0 1,800 7,200 9,000 100% 2026 9,000 0 1,800 7,200 9,000 100% 2027 9,000 0 1,800 7,200 9,000 100% 2028 9,000 0 1,800 7,200 9,000 100% 2029203020312032

189,000 37,800 151,200 189,000 100%

$/ton
Appendix 9-1.13 

Mine: E03_UGCapital Requirements ($ X 1000)

production

Capital Contingency: 0% CV Mining Ht: 10.0 Capital Contingency: -75% < 500kMiles of Rail spur: 0 CM Mining Ht: 10.0 -50% 500k<= & < 750kCoal Storage: 0 LW Mining Ht: 10.0 0% >750kDepth to Shafts: 100No. of Men/Supply Shafts 1No. of Air Shafts 1 Shafts: if prod < 1000k, 1 M&S + 1 Air

if prod > 1000k, 2 M&S + 1 Air

longwall initial 100 million $

Year Acqisition Exploration Development Shaft Surface Prep Plant Rail Conventional Sections Continuous Miners Longwalls Fixed 

& Labor Capital Facilities Units Initial Repl Units Initial Repl Units Initial Repl In

Engineering Cost & Equip. Required $ $ Required $ $ Required $$

2008 2,590 91,705 9,183 11,878 0 0 0 0 4 12,000 1 100,000 2009 00 40 10 2010 00 40 10 2011 00 40 10 2012 00 40 10 2013 00 40 10 2014 00 40 10 2015 0 0 0 4 0 12,000 1 0 100,000 2016 0004001002017 0004001002018 0004001002019 0004001002020 0004001002021 0004001002022 0 0 0 4 0 12,000 1 0 100,000 2023 0004001002024 0004001002025 0004001002026 00 40 10 2027 00 40 10 2028 00 40 10 2029203020312032

0 2,590 91,705 9,183 11,878 0 0 0 0 12,000 24,000 100,000 200,000 

0.00 0.01 0.49 0.05 0.06 0.00 0.00 0.00 0.06 0.13 0.53 1.06 
Appendix 9-1.14 

Mine: E03_UGCapital Expenditure Summary

Year Acquisition Exploration Depreciable Assets Property Tax Depreciation Working 

& 7 Year Life 15 Year Life Total Base 7 Year Life 15 Year Life Total Capital 

Engineering

2008 0 2,590 143,562 112,766 256,327 256,327 20,509 7,518 28,027 19,092 2009 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2010 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2011 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2012 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2013 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2014 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2015 0 0 143,562 0 143,562 256,327 20,509 7,518 28,027 0 2016 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2017 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2018 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2019 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2020 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2021 0 0 0 0 0 256,327 20,509 7,518 28,027 0 2022 0 0 143,562 0 143,562 256,327 20,509 7,518 28,027 0 2023 0 0 0 0 0 256,327 20,509 0 20,509 0 2024 0 0 0 0 0 256,327 20,509 0 20,509 0 2025 0 0 0 0 0 256,327 20,509 0 20,509 0 2026 0 0 0 0 0 256,327 20,509 0 20,509 0 2027 0 0 0 0 0 256,327 20,509 0 20,509 0 2028 0 0 0 0 0 256,327 20,509 0 20,509 -19,092 2029 

2030 2031 2032 

0 2,590 430,685 112,766 543,451 430,685 112,766 543,451 0 

0.00 0.01 2.28 0.60 2.88 2.28 0.60 2.88 0.00 
Appendix 9-1.15 

Mine: E03_UGRequired Sales Price ($ X 1000)Sales Price ($/ton): $21.439 Sev. Taxes: Rate $0.27Discount Rate: 10.00% Adjustment 100.0%Net Present Value: ($0) Prop. Taxes Tax Rate (in mills) 60

Cost Contingency Factors: 10% % of revenue basis for taxAverage Coal Thickness (ft): 10 Assessment rate: 25.0%Tons/Man-hour 6.9 Income TaxesFederal 34.00%

UMWA (Y or N): N State 6.00%Product (Steam or Met) S Royalty 8.0%

% of Reserve owned: 0%

Year Tons Revenue Direct Royalty Taxes (other than income) Corp G&A, Development Depreciation Depletion Taxes Net Income 

Operating Severance Black Recl. Property Selling & Cost 

Cost Lung Acc. Pen. 

2008 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 2,590 28,027 6,669 2,667 4,001 2009 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2010 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2011 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2012 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2013 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2014 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2015 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2016 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2017 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2018 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2019 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2020 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2021 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2022 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 28,027 7,964 3,185 4,778 2023 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 20,509 11,722 4,689 7,033 2024 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 20,509 11,722 4,689 7,033 2025 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 20,509 11,722 4,689 7,033 2026 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 20,509 11,722 4,689 7,033 2027 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 20,509 11,722 4,689 7,033 2028 9,000 192,950 114,552 15,436 2,106 8,490 1,350 2,663 4,400 0 20,509 11,722 4,689 7,033 2029203020312032

189,000 4,051,948 2,405,584 324,156 44,226 178,286 28,350 55,917 92,400 2,590 543,451 188,494 75,398 113,096 

21.44 12.73 1.72 0.23 0.94 0.15 0.30 0.49 0.01 2.88 1.00 0.40 0.60 
Appendix 9-1.16 

Mine: N02_UGProduction & Productivity Data% Washed 0%Plant Recovery: 100%Production by Equipment at Full Production % Longwall Production: 80% % CM Production: 20% % CV Production: 0%

Year Clean CV ROM CM ROM LW ROM Total ROM Overall Haul

Tons Tons Tons Tons Tons Recovery Distance

(000) (000) (000) (000) (000) % (miles)

20112012201320142015 500 0 500 0 500 100% 2016 3,000 0 600 2,400 3,000 100% 2017 5,000 0 1,000 4,000 5,000 100% 2018 5,000 0 1,000 4,000 5,000 100% 2019 5,000 0 1,000 4,000 5,000 100% 2020 5,000 0 1,000 4,000 5,000 100% 2021 5,000 0 1,000 4,000 5,000 100% 2022 5,000 0 1,000 4,000 5,000 100% 2023 5,000 0 1,000 4,000 5,000 100% 2024 5,000 0 1,000 4,000 5,000 100% 2025 5,000 0 1,000 4,000 5,000 100% 2026 5,000 0 1,000 4,000 5,000 100% 2027 5,000 0 1,000 4,000 5,000 100% 2028 5,000 0 1,000 4,000 5,000 100% 2029 5,000 0 1,000 4,000 5,000 100% 2030 5,000 0 1,000 4,000 5,000 100% 2031 5,000 0 1,000 4,000 5,000 100% 2032 5,000 0 1,000 4,000 5,000 100% 2033 5,000 0 1,000 4,000 5,000 100% 2034 5,000 0 1,000 4,000 5,000 100% 2035 5,000 0 1,000 4,000 5,000 100% 

98,500 20,100 78,400 98,500 100%

$/ton
Appendix 9-1.17 

Mine: N02_UGCapital Requirements ($ X 1000)

production

Capital Contingency: 0% CV Mining Ht: 8.0 Capital Contingency: -75% < 500kMiles of Rail spur: 0 CM Mining Ht: 8.0 -50% 500k<= & < 750kCoal Storage: 0 LW Mining Ht: 8.0 0% >750kDepth to Shafts: 1000No. of Men/Supply Shafts 1No. of Air Shafts 1 Shafts: if prod < 1000k, 1 M&S + 1 Air

if prod > 1000k, 2 M&S + 1 Air

Year Acqisition Exploration Development Shaft Surface Prep Plant Rail Conventional Sections Continuous Miners Longwalls Fixed 

& Labor Capital Facilities Units Initial Repl Units Initial Repl Units Initial Repl Ini

Engineering Cost & Equip. Required $ $ Required $ $ Required $ $ 

2011 350 0 0 0 0 0 0 0 0 0 0 2012 350 0 0 0 0 0 0 0 0 0 0 2013 350 0 0 0 0 0 0 0 0 0 0 2014 1,030 30,085 45,174 6,777 0 0 0 0 0 0 0 0 2015 0 0 2 6,000 0 0 2016 0 0 2 0 1 25,000 2017 0 0 3 3,000 1 0 2018 0 0 0 3 0 0 1 0 0 2019 0003001002020 0003001002021 0003001002022 0 0 0 3 0 6,000 1 0 0 2023 0 0 0 3 0 0 1 0 25,000 2024 0 0 0 3 0 3,000 1 0 0 2025 0 0 0 3 0 0 1 0 0 2026 0003001002027 0003001002028 0003001002029 00 30 10 2030 00 30 10 2031 00 30 10 2032 00 30 10 2033 00 30 10 2034 00 30 10 2035 00 30 10 

0 2,080 30,085 45,174 6,777 0 0 0 0 9,000 9,000 25,000 25,000 

0.00 0.02 0.31 0.46 0.07 0.00 0.00 0.00 0.09 0.09 0.25 0.25 
Appendix 9-1.18 

Mine: N02_UGCapital Expenditure Summary

Year Acquisition Exploration Depreciable Assets Property Tax Depreciation Working 

& 7 Year Life 15 Year Life Total Base 7 Year Life 15 Year Life Total Capital 

Engineering

2011 0 350 1,109 0 1,109 1,109 158 0 158 0 2012 0 350 0 0 0 1,109 158 0 158 0 2013 0 350 0 0 0 1,109 158 0 158 0 2014 0 1,030 0 82,036 82,036 53,060 158 5,469 5,627 0 2015 0 0 7,631 0 7,631 60,691 1,249 5,469 6,718 1,015 2016 0 0 31,798 0 31,798 92,489 5,791 5,469 11,260 4,840 2017 0 0 3,816 0 3,816 96,304 6,336 5,469 11,805 3,903 2018 0 0 1,109 0 1,109 96,304 6,336 5,469 11,805 0 2019 0 0 0 0 0 96,304 6,336 5,469 11,805 0 2020 0 0 0 0 0 96,304 6,336 5,469 11,805 0 2021 0 0 0 0 0 96,304 6,336 5,469 11,805 0 2022 0 0 7,631 0 7,631 96,304 6,336 5,469 11,805 0 2023 0 0 31,798 0 31,798 96,304 6,336 5,469 11,805 0 2024 0 0 3,816 0 3,816 96,304 6,336 5,469 11,805 0 2025 0 0 1,109 0 1,109 96,304 6,336 5,469 11,805 0 2026 0 0 0 0 0 96,304 6,336 5,469 11,805 0 2027 0 0 0 0 0 96,304 6,336 5,469 11,805 0 2028 0 0 0 0 0 96,304 6,336 5,469 11,805 0 2029 0 0 0 0 0 96,304 5,246 0 5,246 0 2030 0 0 0 0 0 96,304 704 0 704 0 2031 0 0 0 0 0 96,304 158 0 158 0 2032 0 0 0 0 0 96,304 0 0 0 0 2033 0 0 0 0 0 96,304 0 0 0 0 2034 0 0 0 0 0 96,304 0 0 0 0 2035 0 0 0 0 0 96,304 0 0 0 -9,759 

0 2,080 89,816 82,036 171,852 89,816 82,036 171,852 0 

0.00 0.02 0.91 0.83 1.74 0.91 0.83 1.74 0.00 
Appendix 9-1.19 

Mine: N02_UGRequired Sales Price ($ X 1000)Sales Price ($/ton): $20.007 Sev. Taxes: Rate $0.27Discount Rate: 10.00% Adjustment 100.0%Net Present Value: ($0) Prop. Taxes Tax Rate (in mills) 60Cost Contingency Factors: 10% % of revenue basis for taxAverage Coal Thickness (ft): 8 Assessment rate: 25.0%Tons/Man-hour 8.0 Income TaxesFederal 34.00%

UMWA (Y or N): N State 6.00%Product (Steam or Met) S Royalty 8.0%

% of Reserve owned: 0%

Year Tons Revenue Direct Royalty Taxes (other than income) Corp G&A, Development Depreciation Depletion Taxes Net Income O

Operating Severance Black Recl. Property Selling & Cost 

Cost Lung Acc. Pen. 

2011 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2012 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2013 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2014 0 0 0 0 0 0 0 0 0 1,030 5,627 0 -2,663 -3,994 2015 500 10,003 6,089 800 0 440 75 138 550 0 6,718 0 -1,923 -2,884 2016 3,000 60,021 35,131 4,802 486 2,641 450 828 3,300 0 11,260 562 225 337 2017 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2018 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2019 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2020 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2021 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2022 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2023 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2024 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2025 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2026 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2027 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2028 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 11,805 4,859 1,944 2,915 2029 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 5,246 7,363 3,566 5,349 2030 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 704 7,363 5,383 8,074 2031 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 158 7,363 5,601 8,401 2032 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 0 7,363 5,664 8,496 2033 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 0 7,363 5,664 8,496 2034 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 0 7,363 5,664 8,496 2035 5,000 100,035 58,551 8,003 1,026 4,402 750 1,380 4,400 0 0 7,363 5,664 8,496 

98,500 1,970,686 1,153,690 157,655 19,980 86,710 14,775 27,195 87,450 2,080 171,852 110,405 55,557 83,336 

20.01 11.71 1.60 0.20 0.88 0.15 0.28 0.89 0.02 1.74 1.12 0.56 0.85 
Appendix 9-1.20 

Mine: N03_UGProduction & Productivity Data% Washed 0%Plant Recovery: 100%Production by Equipment at Full Production % Longwall Production: 80% % CM Production: 20% % CV Production: 0%

Year Clean CV ROM CM ROM LW ROM Total ROM Overall Haul

Tons Tons Tons Tons Tons Recovery Distance

(000) (000) (000) (000) (000) % (miles)

20072008200920102011 0 0 0 0 #DIV/0! 2012 0 0 0 0 #DIV/0! 2013 0 0 0 0 #DIV/0! 2014 1,000 0 200 800 1,000 100% 2015 5,000 0 1,000 4,000 5,000 100% 2016 5,000 0 1,000 4,000 5,000 100% 2017 5,000 0 1,000 4,000 5,000 100% 2018 5,000 0 1,000 4,000 5,000 100% 2019 5,000 0 1,000 4,000 5,000 100% 2020 5,000 0 1,000 4,000 5,000 100% 2021 5,000 0 1,000 4,000 5,000 100% 2022 5,000 0 1,000 4,000 5,000 100% 2023 5,000 0 1,000 4,000 5,000 100% 2024 5,000 0 1,000 4,000 5,000 100% 2025 5,000 0 1,000 4,000 5,000 100% 2026 5,000 0 1,000 4,000 5,000 100% 2027 5,000 0 1,000 4,000 5,000 100% 2028 5,000 0 1,000 4,000 5,000 100% 2029 5,000 0 1,000 4,000 5,000 100% 2030 5,000 0 1,000 4,000 5,000 100% 2031 5,000 0 1,000 4,000 5,000 100% 

86,000 17,200 68,800 86,000 100%

$/ton
Appendix 9-1.21 

Mine: N03_UGCapital Requirements ($ X 1000)

production

Capital Contingency: 0% CV Mining Ht: 10.0 Capital Contingency: -75% < 500kMiles of Rail spur: 0 CM Mining Ht: 10.0 -50% 500k<= & < 750kCoal Storage: 0 LW Mining Ht: 10.0 0% >750kDepth to Shafts: 100No. of Men/Supply Shafts 1No. of Air Shafts 1 Shafts: if prod < 1000k, 1 M&S + 1 Air

if prod > 1000k, 2 M&S + 1 Air

Year Acqisition Exploration Development Shaft Surface Prep Plant Rail Conventional Sections Continuous Miners Longwalls Fixe

& Labor Capital Facilities Units Initial Repl Units Initial Repl Units Initial Repl In

Engineering Cost & Equip. Required $ $ Required $ $ Required $ $ 

2007 350 0 0 0 0 0 0 0 0 0 0 2008 350 0 0 0 0 0 0 0 0 0 0 2009 350 0 0 0 0 0 0 0 0 0 0 2010 350 0 0 0 0 0 0 0 0 0 0 2011 350 0 0 0 0 0 0 0 0 0 0 2012 350 0 0 0 0 0 0 0 0 0 0 2013 1,530 49,835 9,183 8,412 0 0 0 0 0 0 0 0 2014 0 0 0 1 3,000 0 1 50,000 0 2015 0 0 0 3 6,000 0 1 0 0 2016 0003001002017 0003001002018 0003001002019 0003001002020 0003001002021 0 0 0 3 0 3,000 1 0 50,000 2022 0 0 0 3 0 6,000 1 0 0 2023 0003001002024 0003001002025 00 30 10 2026 00 30 10 2027 00 30 10 2028 00 30 10 2029 00 30 10 2030 00 30 10 2031 00 30 10 

0 3,630 49,835 9,183 8,412 0 0 0 0 9,000 9,000 50,000 50,000 

0.00 0.04 0.58 0.11 0.10 0.00 0.00 0.00 0.10 0.10 0.58 0.58 
Appendix 9-1.22 

Mine: N03_UGCapital Expenditure Summary

Year Acquisition Exploration Depreciable Assets Property Tax Depreciation 

& 7 Year Life 15 Year Life Total Base 7 Year Life 15 Year Life Total 

Engineering

2007 0 350 1,109 0 1,109 1,109 158 0 158 2008 0 350 0 0 0 1,109 158 0 158 2009 0 350 0 0 0 1,109 158 0 158 2010 0 350 0 0 0 1,109 158 0 158 2011 0 350 0 0 0 1,109 158 0 158 2012 0 350 0 0 0 1,109 158 0 158 2013 0 1,530 0 67,429 67,429 18,703 158 4,495 4,654 2014 0 0 68,520 0 68,520 86,114 9,789 4,495 14,284 2015 0 0 7,631 0 7,631 93,745 10,879 4,495 15,374 2016 0 0 0 0 0 93,745 10,879 4,495 15,374 2017 0 0 0 0 0 93,745 10,879 4,495 15,374 2018 0 0 0 0 0 93,745 10,879 4,495 15,374 2019 0 0 0 0 0 93,745 10,879 4,495 15,374 2020 0 0 0 0 0 93,745 10,879 4,495 15,374 2021 0 0 68,520 0 68,520 93,745 10,879 4,495 15,374 2022 0 0 7,631 0 7,631 93,745 10,879 4,495 15,374 2023 0 0 0 0 0 93,745 10,879 4,495 15,374 2024 0 0 0 0 0 93,745 10,879 4,495 15,374 2025 0 0 0 0 0 93,745 10,879 4,495 15,374 2026 0 0 0 0 0 93,745 10,879 4,495 15,374 2027 0 0 0 0 0 93,745 10,879 4,495 15,374 2028 0 0 0 0 0 93,745 1,090 0 1,090 2029 0 0 0 0 0 93,745 0 0 0 2030 0 0 0 0 0 93,745 0 0 0 2031 0 0 0 0 0 93,745 0 0 0 

0 3,630 153,411 67,429 220,841 153,411 67,429 220,841 

0.00 0.04 1.78 0.78 2.57 1.78 0.78 2.57 
Appendix 9-1.23 

Mine: N03_UGRequired Sales Price ($ X 1000)Sales Price ($/ton): $19.670 Sev. Taxes: Rate $0.27Discount Rate: 10.00% Adjustment 100.0%Net Present Value: $0 Prop. Taxes Tax Rate (in mills) 60Cost Contingency Factors: 10% % of revenue basis for taxAverage Coal Thickness (ft): 8 Assessment rate: 25.0%Tons/Man-hour 10.0 Income TaxesFederal 34.00%

UMWA (Y or N): N State 6.00%Product (Steam or Met) S Royalty 8.0%

% of Reserve owned: 0%

Year Tons Revenue Direct Royalty Taxes (other than income) Corp G&A, Development Depreciation Depletion Taxes Net Income 

Operating Severance Black Recl. Property Selling & Cost 

Cost Lung Acc. Pen. 

2007 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2008 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2009 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2010 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2011 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2012 0 0 0 0 0 0 0 0 0 350 158 0 -203 -305 2013 0 0 0 0 0 0 0 0 0 1,530 4,654 0 -2,473 -3,710 2014 1,000 19,670 10,473 1,574 0 865 150 271 990 0 14,284 0 -3,575 -5,362 2015 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2016 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2017 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2018 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2019 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2020 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2021 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2022 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2023 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2024 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2025 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2026 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2027 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 15,374 5,441 2,177 3,265 2028 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 1,090 7,238 7,171 10,757 2029 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 0 7,238 7,607 11,411 2030 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 0 7,238 7,607 11,411 2031 5,000 98,349 52,364 7,868 1,026 4,327 750 1,357 4,400 0 0 7,238 7,607 11,411 

86,000 1,691,596 900,654 135,328 17,442 74,430 12,900 23,344 75,790 3,630 220,841 99,690 51,019 76,528 

19.67 10.47 1.57 0.20 0.87 0.15 0.27 0.88 0.04 2.57 1.16 0.59 0.89 

Note: Mine cost ($19.67/ton) plus transportation and loadout costs ($1.00/ton) = Total FOB cost ($20.67/ton)
Appendix 9-1.24 

deflator =- 0.004/yr for all regi2012 Prob. 

Year Abbrev CoalType_Gr

ade

CODER CODEF Mine Step Name Existing 

or New

Mine Type

Heat Content (MMBtu/Ton)

Cost of Production (2008$/Ton)

Cost of Production (2007$/Ton)

deflator deflated 

cost

Final Cost (Rounded)

Coal Production (Million Tons/Year)

2012 CG BB CGH SCZ N02 N02 N U 22.01 $20.01 $19.59 1.02 $19.21 $19.25 52012 CG BB CGH SCZ N03 N03 N U 22.01 $20.67 $20.24 1.02 $19.84 $19.75 52012 CG BB CGM SCZ E01 E01 E S 22.01 $20.72 $20.29 1.02 $19.89 $20.00 22012 CG BB CGH SCZ E03 E03 E U 22.01 $21.44 $20.99 1.02 $20.58 $20.50 92012 CG BB CGH SCZ N01 N01 N U 22.01 $22.44 $21.97 1.02 $21.54 $21.50 92012 CG BB CGM SCZ E02 E02 E U 22.01 $36.48 $35.72 1.02 $35.01 $35.00 2

EPA CODES WM CODES

2012 Final Cost (Rounded)

$0$5

$10$15$20$25$30$35$40

5.0 10.0 12.5 21.5 30.5 32.5

Cumulative Production (Million Tons)

Cash Costs $/ton
Appendix 9-2.1 

Appendix 9-2 New Mines Included in 2040 Curves 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 AL BB N01 24.82 $39.50 4 13 

2040 AL BB N02 24.82 $42.00 0 25 

2040 AL BB N03 24.82 $44.50 4 50 

2040 AL BB N04 24.82 $47.00 0 50 

2040 AL BD N01 24 $47.00 2 49 

2040 AL BD N02 24 $58.00 2 50 

2040 AL BD N03 24 $70.00 2 50 

2040 AL BD N04 24 $82.00 2 50 

2040 AL BE N01 23.82 $63.00 0.5 121 

2040 AL BE N02 23.82 $69.00 0.5 115 

2040 AL BE N03 23.82 $75.00 0.5 115 

2040 AL BE N04 23.82 $82.00 0.5 98 

2040 AZ BB N01 24.64 $16.75 5 450 

2040 CG BA N01 21.49 $18.25 12 70 

2040 CG BA N02 21.49 $29.00 1 40 

2040 CG BA N03 21.49 $23.00 3 350 

2040 CG BB N01 22.01 $19.25 9 70 

2040 CG BB N02 22.01 $16.75 5 50 

2040 CG BB N03 22.01 $17.75 5 95 

2040 CR BA N02 25.5 $27.00 3 60 

2040 CR BD N01 22.2 $27.00 0.3 10 

2040 CU BB N01 23.22 $19.25 8 100 

2040 IL BE N01 23 $32.50 1 55 

2040 IL BE N02 23 $32.00 1 15 

2040 IL BE N03 23 $33.50 1 15 

2040 IL BE N04 23 $35.00 1 15 

2040 IL BE N05 23 $37.00 1 15 

2040 IL BE N06 23 $38.50 1 15 

2040 IL BE N07 23 $40.50 1 15 

2040 IL BE N08 23 $42.00 1 15 

2040 IL BE N09 23 $44.00 1 15 

2040 IL BE N10 23 $45.50 1 15 

2040 IL BE N11 23 $47.00 1 15 

2040 IL BE N12 23 $49.00 1 15 

2040 IL BE N13 23 $51.00 1 15 

2040 IL BE N14 23 $52.00 1 15 

2040 IL BE N15 23 $86.00 1 15 

2040 IL BG N01 23.01 $24.00 5 398 

2040 IL BG N02 23.01 $27.00 2.5 9.6 

2040 IL BG N03 23.01 $28.50 3 38 

2040 IL BG N04 23.01 $37.50 4 130 

2040 IL BG N05 23.01 $46.00 0.5 8 

2040 IL BG N06 23.01 $28.50 4 200 

2040 IL BG N07 23.01 $32.50 4 200 
Appendix 9-2.2 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 IL BG N08 23.01 $37.00 4 200 

2040 IL BG N09 23.01 $41.00 4 200 

2040 IL BG N10 23.01 $45.50 4 200 

2040 IL BG N11 23.01 $54.00 4 200 

2040 IL BG N12 23.01 $86.00 4 200 

2040 IL BH N01 22.19 $24.00 5 177.4 

2040 IL BH N02 22.19 $24.00 5 253.2 

2040 IL BH N03 22.19 $24.00 5 221.9 

2040 IL BH N04 22.19 $24.50 3.7 107.5 

2040 IL BH N05 22.19 $24.00 3 70 

2040 IL BH N06 22.19 $24.00 3 60 

2040 IL BH N07 22.19 $27.50 7.8 460 

2040 IL BH N08 22.19 $29.00 0.5 2 

2040 IL BH N09 22.19 $31.50 2.2 125 

2040 IL BH N10 22.19 $35.00 0.2 3 

2040 IL BH N11 22.19 $38.50 1.9 37.8 

2040 IL BH N12 22.19 $48.50 0.8 20 

2040 IL BH N13 22.19 $53.00 0.5 4 

2040 IL BH N14 22.19 $86.00 5 250 

2040 IN BD N01 22.62 $30.00 0.5 10 

2040 IN BD N02 22.62 $32.00 0.5 10 

2040 IN BD N03 22.62 $34.50 0.5 10 

2040 IN BD N04 22.62 $86.00 0.5 10 

2040 IN BE N01 23.43 $24.00 0.1 0.5 

2040 IN BE N02 23.43 $34.50 1 15 

2040 IN BE N03 23.43 $37.00 1 26 

2040 IN BE N04 23.43 $86.00 1 15 

2040 IN BG N01 23.37 $27.50 1.5 30 

2040 IN BG N02 23.37 $30.50 1.5 30 

2040 IN BG N03 23.37 $33.00 0.5 6 

2040 IN BG N04 23.37 $35.00 1.6 9.5 

2040 IN BG N05 23.37 $38.00 1 418.1 

2040 IN BG N06 23.37 $84.00 1 5 

2040 IN BH N01 23.41 $31.00 1.5 60 

2040 IN BH N02 23.41 $34.00 0.2 3 

2040 IN BH N03 23.41 $49.50 0.8 11 

2040 IN BH N04 23.41 $28.50 1.5 60 

2040 IN BH N05 23.41 $29.50 1.5 60 

2040 IN BH N06 23.41 $30.00 1.5 60 

2040 IN BH N07 23.41 $31.00 1.5 60 

2040 IN BH N08 23.41 $32.00 1.5 60 

2040 IN BH N09 23.41 $33.00 1.5 60 

2040 IN BH N10 23.41 $34.00 1.5 60 

2040 IN BH N11 23.41 $35.00 1.5 60 

2040 IN BH N12 23.41 $36.00 1.5 60 
Appendix 9-2.3 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 IN BH N13 23.41 $37.00 1.5 60 

2040 IN BH N14 23.41 $38.00 1.5 60 

2040 IN BH N15 23.41 $39.00 1.5 60 

2040 IN BH N16 23.41 $40.00 1.5 60 

2040 IN BH N17 23.41 $40.50 1.5 60 

2040 IN BH N18 23.41 $41.50 1.5 60 

2040 IN BH N19 23.41 $42.50 1.5 60 

2040 IN BH N20 23.41 $43.50 1.5 60 

2040 IN BH N21 23.41 $44.50 1.5 60 

2040 IN BH N22 23.41 $45.50 1.5 60 

2040 IN BH N23 23.41 $46.50 1.5 60 

2040 IN BH N24 23.41 $47.50 1.5 60 

2040 IN BH N25 23.41 $48.50 1.5 60 

2040 IN BH N26 23.41 $49.50 1.5 60 

2040 IN BH N27 23.41 $50.00 1.5 60 

2040 IN BH N28 23.41 $51.00 1.5 60 

2040 IN BH N29 23.41 $52.00 1.5 60 

2040 IN BH N30 23.41 $53.00 1.5 60 

2040 IN BH N31 23.41 $54.00 1.5 60 

2040 IN BH N32 23.41 $86.00 1.5 60 

2040 KE BA N01 25.32 $68.00 0.3 11.9 

2040 KE BA N02 25.32 $88.00 0.3 15 

2040 KE BA N03 25.32 $108.00 0.3 15 

2040 KE BA N04 25.32 $128.00 0.3 15 

2040 KE BB N01 25.79 $87.00 0.5 71.1 

2040 KE BB N02 25.79 $99.00 0.5 80 

2040 KE BB N03 25.79 $111.00 0.5 80 

2040 KE BB N04 25.79 $123.00 0.5 80 

2040 KE BD N01 25.33 $74.00 4.1 192.7 

2040 KE BD N02 25.33 $87.00 3 170 

2040 KE BD N03 25.33 $100.00 2 180 

2040 KE BD N04 25.33 $114.00 1 152 

2040 KE BE N01 25.14 $71.00 4.1 351.8 

2040 KE BE N02 25.14 $91.00 3 320 

2040 KE BE N03 25.14 $111.00 2 150 

2040 KE BE N04 25.14 $130.00 1 145 

2040 KE BG N01 24.09 $57.00 0.3 4 

2040 KE BG N02 24.09 $87.00 0.3 4 

2040 KE BG N03 24.09 $117.00 0.3 4 

2040 KE BG N04 24.09 $148.00 0.3 4 

2040 KS BG N01 25.32 $36.50 0.1 1.2 

2040 KS BG N02 25.32 $44.50 0.1 1.2 

2040 KS BG N03 25.32 $52.00 0.1 1.2 

2040 KS BG N04 25.32 $59.00 0.1 1.2 

2040 KS BG N05 25.32 $67.00 0.1 1.2 
Appendix 9-2.4 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 KS BG N06 25.32 $86.00 0.1 1.2 

2040 KW BD N01 24.23 $59.00 0.7 10 

2040 KW BD N02 24.23 $67.00 0.5 105 

2040 KW BD N03 24.23 $86.00 0.5 105 

2040 KW BE N01 24.45 $30.50 2 300 

2040 KW BE N02 24.45 $33.50 0.5 30 

2040 KW BE N03 24.45 $34.00 0.5 30 

2040 KW BE N04 24.45 $34.50 0.5 30 

2040 KW BE N05 24.45 $35.00 0.5 30 

2040 KW BE N06 24.45 $35.50 0.5 30 

2040 KW BE N07 24.45 $36.50 0.5 30 

2040 KW BE N08 24.45 $37.00 0.5 30 

2040 KW BE N09 24.45 $37.50 0.5 30 

2040 KW BE N10 24.45 $38.00 0.5 30 

2040 KW BE N11 24.45 $38.50 0.5 30 

2040 KW BE N12 24.45 $39.00 0.5 30 

2040 KW BE N13 24.45 $39.50 0.5 30 

2040 KW BE N14 24.45 $40.00 0.5 30 

2040 KW BE N15 24.45 $40.50 0.5 30 

2040 KW BE N16 24.45 $41.50 0.5 30 

2040 KW BE N17 24.45 $42.00 0.5 30 

2040 KW BE N18 24.45 $42.50 0.5 30 

2040 KW BE N19 24.45 $43.00 0.5 30 

2040 KW BE N20 24.45 $86.00 0.5 30 

2040 KW BG N01 23.93 $26.00 3 24.8 

2040 KW BG N02 23.93 $30.00 3 195 

2040 KW BG N03 23.93 $32.00 3 156.8 

2040 KW BG N04 23.93 $36.50 4 104.5 

2040 KW BG N05 23.93 $37.00 2 20 

2040 KW BG N06 23.93 $50.00 3 180 

2040 KW BG N07 23.93 $86.00 3 180 

2040 KW BH N01 22.84 $29.50 5 17 

2040 KW BH N02 22.84 $32.00 1 4 

2040 KW BH N03 22.84 $34.00 2 22 

2040 KW BH N04 22.84 $38.00 1 7.8 

2040 KW BH N05 22.84 $53.00 1 30 

2040 KW BH N06 22.84 $53.00 2 240 

2040 KW BH N07 22.84 $53.00 2 240 

2040 KW BH N08 22.84 $53.00 2 240 

2040 KW BH N09 22.84 $53.00 2 240 

2040 KW BH N10 22.84 $53.00 2 240 

2040 KW BH N11 22.84 $54.00 2 240 

2040 KW BH N12 22.84 $86.00 2 240 

2040 LA LE N01 14.09 $19.00 2 75 

2040 LA LE N02 14.09 $43.00 2 75 
Appendix 9-2.5 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 MD BB N01 24.64 $71.00 0.3 5 

2040 MD BB N02 24.64 $76.00 0.3 5 

2040 MD BB N03 24.64 $80.00 0.3 5 

2040 MD BB N04 24.64 $85.00 0.3 5 

2040 MD BD N01 26.32 $65.00 0.7 2.5 

2040 MD BD N02 26.32 $70.00 0.7 7.5 

2040 MD BD N03 26.32 $76.00 0.7 8 

2040 MD BD N04 26.32 $85.00 0.7 7 

2040 MD BE N01 24.85 $44.00 0.3 3 

2040 MD BE N02 24.85 $58.00 0.3 3 

2040 MD BE N03 24.85 $73.00 0.3 3 

2040 MD BE N04 24.85 $88.00 0.3 3 

2040 MD BG N01 23.26 $55.00 0.4 15 

2040 MD BG N02 23.26 $62.00 0.4 15 

2040 MD BG N03 23.26 $69.00 0.4 15 

2040 MD BG N04 23.26 $78.00 0.4 15 

2040 ME LD N01 13 $11.75 15 550 

2040 ME LD N02 13.55 $12.50 15 550 

2040 ME LD N03 13.85 $14.75 15 400 

2040 ME LD N04 13.1 $15.00 1 50 

2040 ME LD N05 14.2 $15.50 15 3500 

2040 ME LD N06 13 $16.00 15 970 

2040 ME LD N07 13.4 $17.00 15 1400 

2040 ME LD N08 13.3 $17.00 15 455 

2040 ME LD N09 13.2 $24.00 10 215 

2040 MP SA N01 18.9 $13.75 15 450 

2040 MP SA N02 18.9 $14.75 15 450 

2040 MP SA N03 18.9 $17.00 15 450 

2040 MP SD N01 17.23 $14.25 15 450 

2040 MP SD N02 17.23 $13.00 15 450 

2040 MP SD N03 17.23 $15.25 15 450 

2040 MS LE N01 12.8 $15.75 3 96 

2040 MS LE N02 12.8 $43.00 1 40 

2040 MT BB N01 21 $23.50 5 450 

2040 ND LD N01 13.7 $15.75 18 500 

2040 ND LD N02 13.7 $15.25 9 565 

2040 ND LD N03 13.7 $13.75 1 512 

2040 ND LE N01 13.46 $13.75 6 589 

2040 ND LE N02 13.46 $17.00 4 500 

2040 ND LE N03 13.46 $26.50 2 51 

2040 NS BB N01 26.4 $43.00 0.6 22 

2040 NS BD N01 22 $23.00 0.4 16 

2040 NS BD N02 22 $43.00 0.4 20 

2040 NS BE N01 17 $14.25 6 180 

2040 NS BE N02 22 $43.00 0.4 20 
Appendix 9-2.6 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 OH BB N01 24.68 $76.00 1 50 

2040 OH BB N02 24.68 $83.00 1 50 

2040 OH BB N03 24.68 $91.00 1 50 

2040 OH BB N04 24.68 $100.00 1 50 

2040 OH BD N01 25.55 $63.00 0.3 94 

2040 OH BD N02 25.55 $69.00 0.3 100 

2040 OH BD N03 25.55 $75.00 0.3 100 

2040 OH BD N04 25.55 $82.00 0.3 100 

2040 OH BE N01 25.24 $57.00 0.5 208 

2040 OH BE N02 25.24 $69.00 0.5 210 

2040 OH BE N03 25.24 $81.00 0.5 210 

2040 OH BE N04 25.24 $94.00 0.5 230 

2040 OH BG N01 24.34 $49.00 4 446 

2040 OH BG N02 24.34 $60.00 4 450 

2040 OH BG N03 24.34 $70.00 4 450 

2040 OH BG N04 24.34 $82.00 4 450 

2040 OH BH N01 23.92 $50.00 4 500 

2040 OH BH N02 23.92 $60.00 4 500 

2040 OH BH N03 23.92 $72.00 4 500 

2040 OH BH N04 23.92 $86.00 4 500 

2040 OK BE N01 22.15 $45.00 0.3 3.6 

2040 OK BE N02 22.15 $48.00 0.3 3.6 

2040 OK BE N03 22.15 $51.00 0.3 3.6 

2040 OK BE N04 22.15 $55.00 0.3 3.6 

2040 OK BE N05 22.15 $86.00 0.3 3.6 

2040 PC BD N01 25.06 $64.00 0.5 7.6 

2040 PC BD N02 25.06 $73.00 0.5 5 

2040 PC BD N03 25.06 $83.00 0.5 5 

2040 PC BD N04 25.06 $94.00 0.5 5 

2040 PC BE N01 25.66 $39.50 1.5 15 

2040 PC BE N02 25.66 $54.00 1.5 15 

2040 PC BE N03 25.66 $69.00 1.5 15 

2040 PC BE N04 25.66 $84.00 1.5 15 

2040 PC BG N01 25.33 $51.00 1 22 

2040 PC BG N02 25.33 $60.00 1 25 

2040 PC BG N03 25.33 $68.00 1 20 

2040 PC BG N04 25.33 $77.00 1 20 

2040 PC BH N01 23.39 $51.00 0.5 10 

2040 PC BH N02 23.39 $60.00 0.5 10 

2040 PC BH N03 23.39 $68.00 0.5 10 

2040 PC BH N04 23.39 $77.00 0.5 10 

2040 PW BD N01 24.26 $38.50 0.8 122 

2040 PW BD N02 24.26 $43.00 0.8 126 

2040 PW BD N03 24.26 $47.00 0.8 130 

2040 PW BD N04 24.26 $51.00 0.8 134 
Appendix 9-2.7 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 PW BE N01 26.22 $37.00 2 744 

2040 PW BE N02 26.22 $40.50 2 784 

2040 PW BE N03 26.22 $44.00 2 824 

2040 PW BE N04 26.22 $46.00 2 864 

2040 PW BG N01 25.86 $37.00 5 567 

2040 PW BG N02 25.86 $39.50 5 667 

2040 PW BG N03 25.86 $42.50 5 767 

2040 PW BG N04 25.86 $64.00 1 767 

2040 TN BB N01 24.18 $101.00 0.3 3.8 

2040 TN BB N02 24.18 $106.00 0.3 3.8 

2040 TN BB N03 24.18 $112.00 0.3 3.8 

2040 TN BB N04 24.18 $118.00 0.3 3.8 

2040 TN BD N01 23.91 $101.00 0.3 4.5 

2040 TN BD N02 23.91 $104.00 0.3 4.5 

2040 TN BD N03 23.91 $107.00 0.3 4.5 

2040 TN BD N04 23.91 $110.00 0.3 4.2 

2040 TN BE N01 26.75 $85.00 0.3 6.3 

2040 TN BE N02 26.75 $93.00 0.3 6 

2040 TN BE N03 26.75 $101.00 0.3 6 

2040 TN BE N04 26.75 $110.00 0.3 6 

2040 TX LE N01 13.22 $11.50 11 219 

2040 TX LE N02 13.22 $14.75 4 150 

2040 TX LE N03 13.22 $15.75 6 127 

2040 TX LE N04 13.22 $15.25 7 114 

2040 UT BA N01 23.68 $20.00 1 10 

2040 UT BA N02 23.68 $24.50 4 80 

2040 UT BA N03 23.68 $24.50 4 25 

2040 UT BB N01 23.23 $25.50 4 50 

2040 UT BB N02 23.23 $21.50 2 22 

2040 UT BD N01 23.05 $24.00 4 45 

2040 UT BD N02 23.05 $41.00 3 50 

2040 UT BE N01 25.06 $28.50 2 40 

2040 VA BA N01 22.7 $103.00 0.3 44.4 

2040 VA BA N02 22.7 $108.00 0.3 40 

2040 VA BA N03 22.7 $115.00 0.3 40 

2040 VA BA N04 22.7 $121.00 0.3 39 

2040 VA BB N01 25.97 $94.00 0.8 87.2 

2040 VA BB N02 25.97 $103.00 0.8 85 

2040 VA BB N03 25.97 $112.00 0.8 85 

2040 VA BB N04 25.97 $120.00 0.8 84 

2040 VA BD N01 25.76 $85.00 1.1 68.4 

2040 VA BD N02 25.76 $94.00 0.8 50 

2040 VA BD N03 25.76 $103.00 0.8 50 

2040 VA BD N04 25.76 $112.00 0.8 42 

2040 VA BE N01 26.03 $68.00 0.5 40.6 
Appendix 9-2.8 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 VA BE N02 26.03 $78.00 0.5 26 

2040 VA BE N03 26.03 $89.00 0.5 26 

2040 VA BE N04 26.03 $112.00 0.5 26 

2040 WG BB N01 21.67 $24.50 0.5 15 

2040 WG BB N02 21.67 $23.50 6 190 

2040 WG BB N03 21.67 $22.50 3 55 

2040 WG SD N01 18.5 $19.75 1 13 

2040 WL SB N01 17.15 $17.75 15 450 

2040 WL SB N02 17.15 $10.75 15 450 

2040 WL SB N03 17.15 $11.75 15 450 

2040 WL SB N04 17.15 $13.00 15 450 

2040 WN BD N01 25.01 $45.50 0.4 1.6 

2040 WN BD N02 25.01 $65.00 0.4 2 

2040 WN BD N03 25.01 $85.00 0.4 2 

2040 WN BD N04 25.01 $104.00 0.4 2 

2040 WN BE N01 25.67 $29.00 2 40 

2040 WN BE N02 25.67 $49.00 2 40 

2040 WN BE N03 25.67 $69.00 2 40 

2040 WN BE N04 25.67 $89.00 2 40 

2040 WN BG N01 26.03 $32.50 6.5 600 

2040 WN BG N02 26.03 $48.00 5 600 

2040 WN BG N03 26.03 $64.00 5 600 

2040 WN BG N04 26.03 $80.00 5 600 

2040 WN BH N01 25.15 $34.00 5 125 

2040 WN BH N02 25.15 $53.00 5 125 

2040 WN BH N03 25.15 $72.00 5 125 

2040 WN BH N04 25.15 $91.00 5 75 

2040 WS BA N01 26.2 $98.00 0.3 4.7 

2040 WS BA N02 26.2 $107.00 0.3 4.7 

2040 WS BA N03 26.2 $112.00 0.3 4.7 

2040 WS BA N04 26.2 $122.00 0.3 4.6 

2040 WS BB N01 24.73 $90.00 0.5 106.8 

2040 WS BB N02 24.73 $107.00 0.5 100 

2040 WS BB N03 24.73 $114.00 0.5 100 

2040 WS BB N04 24.73 $122.00 0.5 100 

2040 WS BD N01 24.64 $82.00 1.5 384.8 

2040 WS BD N02 24.64 $89.00 1.5 333 

2040 WS BD N03 24.64 $120.00 1.5 333 

2040 WS BD N04 24.64 $147.00 1.5 333 

2040 WS BE N01 24.38 $69.00 1.4 420.7 

2040 WS BE N02 24.38 $84.00 1.3 420 

2040 WS BE N03 24.38 $99.00 1.3 420 

2040 WS BE N04 24.38 $113.00 1.3 420 

2040 WS BG N01 25.64 $69.00 0.8 80 

2040 WS BG N02 25.64 $80.00 0.8 79 
Appendix 9-2.9 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name 

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton) 

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million Tons) 

2040 WS BG N03 25.64 $92.00 0.8 79 

2040 WS BG N04 25.64 $104.00 0.8 80 
Appendix 9-3.1 

Appendix 9-3 Coal Transportation Matrix in EPA Base Case v.4.10 

This is a small excerpt of the data in Appendix 9-3. The complete data set in spreadsheet format 

can be downloaded via the link found at www.epa.gov/airmarkets/progsregs/epaipm/BaseCasev410.html 

Coal Supply 

Region – 

Description 

Coal 

Demand 

Region 

Coal Demand Region Description Total Cost 

(2007$/Ton) 

Escalation/ 

Year (2012-

2025) 

Escalation/ 

Year (2026-

2054) 

Arizona AMM1 AMMM_High-Cost Competitive_Mine 

Mouth_Rail 1.13 1 1 

New Mexico, San 

Juan AMM1 AMMM_High-Cost Competitive_Mine Mouth_Rail 1.13 1 1 

West Virginia, 

North NAI1 NAIN_High-Cost Competitive_Mine Mouth_Rail 1.13 1 1 

Wyoming, 

Powder River 

Basin (8400) 

NAI1 NAIN_High-Cost Competitive_Mine 

Mouth_Rail 36.93 1 1.0021 

Louisiana TXL1 TXLG_High-Cost Competitive_Mine 

Mouth_Rail 1.13 1 1 

Wyoming, 

Powder River 

Basin (8400) 

TXL1 TXLG_High-Cost Competitive_Mine 

Mouth_Rail 24.58 1 1.0021 

Wyoming, 

Powder River 

Basin (8800) 

NAI1 NAIN_High-Cost Competitive_Mine 

Mouth_Rail 37.3 1 1.0021 

Wyoming, 

Powder River 

Basin (8800) 

TXL1 TXLG_High-Cost Competitive_Mine 

Mouth_Rail 22.63 1 1.0021 

Montana, East DAL1 DALG_High-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt 4.83 1 1.0042 

Wyoming, 

Powder River 

Basin (8400) 

DAL1 DALG_High-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt 10.79 1 1.002 

Wyoming, 

Powder River 

Basin (8400) 

PRB1 PRB_High-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt 2.21 1 1.0011 

Wyoming, 

Powder River 

Basin (8400) 

WYG1 WYGR_High-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt 2.21 1 1.0011 

Wyoming, 

Powder River 

Basin (8800) 

DAL1 DALG_High-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt 11.23 1 1.002 

Wyoming, 

Powder River 

Basin (8800) 

PRB1 PRB_High-Cost Competitive_Mine 

Mouth_Truck/Conveyor Belt 1.13 1 1 

Alabama ALR1 ALRL_High-Cost Competitive_Not 

Mine Mouth_Rail 0 1 1 

Colorado, Green 

River ALR1 ALRL_High-Cost Competitive_Not Mine Mouth_Rail 33.86 1 1.0022 

Colorado, Uinta ALR1 ALRL_High-Cost Competitive_Not 

Mine Mouth_Rail 39.76 1 1.0022 

Illinois ALR1 ALRL_High-Cost Competitive_Not 

Mine Mouth_Rail 25.73 1 1.0022 

Indiana ALR1 ALRL_High-Cost Competitive_Not 

Mine Mouth_Rail 23.32 1 1.0022 

Kentucky East ALR1 ALRL_High-Cost Competitive_Not 

Mine Mouth_Rail 26.57 1 1.0022 
Appendix 9-4.1 

Appendix 9-4 Coal Supply Curves in EPA Base Case v.4.10 

This is a small excerpt of the data in Appendix 9-4. The complete data set in 

spreadsheet format and complete set of graphs can be downloaded via the link found at 

www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev410.html 

Year 

Coal 

Supply 

Region 

Coal 

Grade 

Step 

Name

Heat Content 

(MMBtu/Ton) 

Cost of 

Production 

(2007$/Ton)

Coal 

Production 

(Million 

Tons/Year) 

Coal 

Reserves 

(Million 

Tons) 

2012 AL BB E01 24.82 43.1 1.0 111 

2012 AL BB N01 24.82 44.5 4.0 13 

2012 AL BB N02 24.82 47.0 0.0 25 

2012 AL BB E02 24.82 48.9 0.9 51 

2012 AL BB E03 24.82 49.9 5.6 73 

2012 AL BB N03 24.82 49.9 4.0 50 

2012 AL BB E04 24.82 50.9 1.0 5 

2012 AL BB N04 24.82 52.9 0.0 50 

2012 AL BB E05 24.82 53.8 0.8 22 

2012 AL BD E01 24 43.1 0.4 233 

2012 AL BD E02 24 44.5 0.3 9 

2012 AL BD E03 24 48.9 0.4 16 

2012 AL BD E04 24 52.9 0.9 10 

2012 AL BD N01 24 52.9 2.0 49 

2012 AL BD E05 24 53.8 0.3 1 

2012 AL BD E06 24 56.8 0.7 26 

2012 AL BD E07 24 64.6 0.4 24 

2012 AL BD N02 24 65.6 2.0 50 

2012 AL BD E08 24 73.4 0.1 6 

2012 AL BD N03 24 78.3 2.0 50 

2012 AL BD E09 24 85.1 0.5 26 

2012 AL BD N04 24 92.0 2.0 50 

2012 AL BE E01 23.82 36.2 1.8 93 

2012 AL BE E02 23.82 43.1 0.4 14 

2012 AL BE E03 23.82 45.5 0.1 0 

2012 AL BE E04 23.82 50.9 0.4 10 

2012 AL BE E05 23.82 54.8 0.9 16 

2012 AL BE E06 23.82 62.6 0.2 5 

2012 AL BE N01 23.82 70.5 0.5 121 
Coal Supply Curve - WH_SA

$0$5

$10$15$20$25

0 100 200 300 400 500 600

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WH_SB

$0$2$4$6$8

$10$12$14$16$18$20

0 10 20 30 40 50 60 70 80 90 100

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WL_SB

$0$5

$10$15$20$25

0 100 200 300 400 500 600

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - MP_SA

$0$2$4$6$8

$10$12$14$16$18$20

0 10 20 30 40 50 60 70 80 90

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - MP_SD

$0$5

$10$15$20$25

0 10 20 30 40 50 60 70 80 90 100

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - MT_BB

$0$5

$10$15$20$25$30

0 2 4 6 8 10 12 14 16 18 20

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WG_BB

$0$5

$10$15$20$25$30

0 1 2 3 4 5 6 7 8 9 10

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WG_SD

$0$5

$10$15$20$25$30

0 2 4 6 8 10 12 14 16 18

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KS_BG

$0

$20$40$60$80

$100$120

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - OK_BE

$0

$20$40$60$80

$100$120

0 0.5 1 1.5 2 2.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - NS_BB

$0

$10$20$30$40$50$60

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - NS_BD

$0

$10$20$30$40$50$60

0123456789

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - NS_BE

$0

$10$20$30$40$50$60

0 5 10 15 20 25 30

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - AZ_BB

$0$2$4$6$8

$10$12$14$16$18$20

0 2 4 6 8 10 12 14

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - CG_BA

$0$5

$10$15$20$25$30$35$40

0 5 10 15 20 25 30 35 40

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - CG_BB

$0$5

$10$15$20$25$30$35$40

0 10 20 30 40 50 60

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - CR_BA

$0$5

$10$15$20$25$30$35

0 0.5 1 1.5 2 2.5 3 3.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - CR_BD

$0$5

$10$15$20$25$30

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - CU_BA

$0$5

$10$15$20$25$30

0 2 4 6 8 10 12 14

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - CU_BB

$0$5

$10$15$20$25$30

0 2 4 6 8 10 12 14 16

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - CU_BD

$0$2$4$6$8

$10$12$14$16

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - UT_BA

$0$5

$10$15$20$25$30$35$40$45

0 2 4 6 8 10 12 14 16 18

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - UT_BB

$0$5

$10$15$20$25$30$35$40$45

0 5 10 15 20 25 30 35 40 45

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - UT_BD

$0$5

$10$15$20$25$30$35$40$45$50

0 5 10 15 20 25

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - UT_BE

$0$5

$10$15$20$25$30$35$40

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - PC_BD

$0

$20$40$60$80

$100$120

0123456

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - PC_BE

$0

$10$20$30$40$50$60$70$80$90

$100

0 5 10 15 20 25

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - PC_BG

$0

$10$20$30$40$50$60$70$80$90

$100

0123456789

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - PC_BH

$0

$10$20$30$40$50$60$70$80$90

$100

0 0.5 1 1.5 2 2.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - PW_BD

$0

$10$20$30$40$50$60$70

0 2 4 6 8 10 12

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - PW_BE

$0

$10$20$30$40$50$60$70

0 5 10 15 20 25 30 35 40 45

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - PW_BG

$0

$10$20$30$40$50$60$70$80

0 2 4 6 8 10 12 14 16 18

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - OH_BB

$0

$20$40$60$80

$100$120

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - OH_BD

$0

$10$20$30$40$50$60$70$80$90

$100

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - OH_BE

$0

$20$40$60$80

$100$120

012345678

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - OH_BG

$0

$10$20$30$40$50$60$70$80$90

$100

0 5 10 15 20 25 30 35 40 45

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - OH_BH

$0

$20$40$60$80

$100$120

0 2 4 6 8 10 12 14 16 18

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - MD_BB

$0

$10$20$30$40$50$60$70$80$90

$100

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - MD_BD

$0

$10$20$30$40$50$60$70$80$90

$100

0 0.5 1 1.5 2 2.5 3

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - MD_BE

$0

$20$40$60$80

$100$120

0 0.5 1 1.5 2 2.5 3 3.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - MD_BG

$0

$10$20$30$40$50$60$70$80$90

$100

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WN_BD

$0

$20$40$60$80

$100$120$140

0 2 4 6 8 10 12

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WN_BE

$0

$20$40$60$80

$100$120

0 5 10 15 20 25 30

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WN_BG

$0

$10$20$30$40$50$60$70$80$90

$100

0 10 20 30 40 50 60 70

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WN_BH

$0

$20$40$60$80

$100$120

0 5 10 15 20 25

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - TX_LD

$0$5

$10$15$20$25

0 1 2 3 4 5 6 7 8 9 10

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - TX_LE

$0$5

$10$15$20$25

0 10 20 30 40 50 60 70

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - TX_LG

$0$2$4$6$8

$10$12

0 2 4 6 8 10 12

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - LA_LE

$0

$10$20$30$40$50$60

0123456789

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KW_BD

$0

$20$40$60$80

$100$120

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KW_BE

$0

$20$40$60$80

$100$120

0 2 4 6 8 10 12 14

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KW_BG

$0

$20$40$60$80

$100$120

0 10 20 30 40 50 60

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KW_BH

$0

$20$40$60$80

$100$120

0 5 10 15 20 25 30 35 40 45

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - IL_BE

$0

$20$40$60$80

$100$120

0 5 10 15 20 25 30

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - IL_BG

$0

$20$40$60$80

$100$120

0 10 20 30 40 50 60 70 80 90

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - IL_BH

$0

$20$40$60$80

$100$120

0 20 40 60 80 100 120

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - IN_BD

$0

$20$40$60$80

$100$120

0123456789

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - IN_BE

$0

$20$40$60$80

$100$120

0123456789

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - IN_BG

$0

$10$20$30$40$50$60$70$80$90

$100

0 5 10 15 20 25

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - IN_BH

$0

$20$40$60$80

$100$120

0 10 20 30 40 50 60 70 80

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - MS_LE

$0

$10$20$30$40$50$60

0123456789

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - ND_LD

$0$2$4$6$8

$10$12$14$16$18

0 10 20 30 40 50 60

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - ND_LE

$0$5

$10$15$20$25$30

0 5 10 15 20 25

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - ME_LD

$0$5

$10$15$20$25$30

0 20 40 60 80 100 120 140

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WS_BA

$0

$20$40$60$80

$100$120$140

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WS_BB

$0

$20$40$60$80

$100$120$140

0 2 4 6 8 10 12 14 16 18 20

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WS_BD

$0

$20$40$60$80

$100$120$140$160

0 10 20 30 40 50 60

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WS_BE

$0

$20$40$60$80

$100$120

0123456

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - WS_BG

$0

$20$40$60$80

$100$120

0 0.5 1 1.5 2 2.5 3 3.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - VA_BA

$0

$20$40$60$80

$100$120$140

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - VA_BB

$0

$20$40$60$80

$100$120$140

0 0.5 1 1.5 2 2.5 3 3.5 4

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - VA_BD

$0

$20$40$60$80

$100$120

0 2 4 6 8 10 12 14 16

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - VA_BE

$0

$20$40$60$80

$100$120

0 0.5 1 1.5 2 2.5 3

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KE_BA

$0

$20$40$60$80

$100$120$140

0 0.5 1 1.5 2 2.5 3 3.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KE_BB

$0

$20$40$60$80

$100$120$140

0 2 4 6 8 10 12

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KE_BD

$0

$20$40$60$80

$100$120$140

0 10 20 30 40 50 60 70 80

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KE_BE

$0

$20$40$60$80

$100$120$140

0 5 10 15 20 25 30

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - KE_BG

$0

$20$40$60$80

$100$120$140$160$180

0 0.5 1 1.5 2 2.5

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - TN_BB

$0

$20$40$60$80

$100$120

0 0.2 0.4 0.6 0.8 1 1.2

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - TN_BD

$0

$20$40$60$80

$100$120

0 0.5 1 1.5 2 2.5 3 3.5 4

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - TN_BE

$0

$20$40$60$80

$100$120

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - AL_BD

$0

$10$20$30$40$50$60$70$80$90

$100

0 2 4 6 8 10 12 14

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - AL_BE

$0

$10$20$30$40$50$60$70$80$90

$100

01234567

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
Coal Supply Curve - AL_BB

$0

$10$20$30$40$50$60

0 2 4 6 8 10 12 14 16 18 20

Cumulative Production (MMTons)

Cost (2007$/Ton)

2012 Curve 2015 Curve 2020 Curve 2030 Curve
10-1 

10 Natural Gas 

This chapter describes how natural gas supply, demand, and costing are modeled in EPA Base 

Case v.4.10. Section 10.1 indicates that natural gas supply dynamics are directly (i.e., 

endogenously) modeled in the new base case. This contrasts to previous EPA base cases where 

natural gas supply curves and related assumptions were developed outside of IPM and then 

treated as an (exogenous) input to the base case. Section 10.2 gives an overview of the new 

natural gas module. Section 3.9 treats in detail the specific components of the module that are 

only briefly described in Section 10.2. Specifically, Sections 10.3 and 10.4 describe the very 

detailed process-engineering model and data sources used to characterize North American 

conventional, unconventional, and frontier natural gas resources and reserves and to derive all the 

cost components incurred in bringing natural gas from the ground to the pipeline. These sections 

also discuss resource constraints affecting production and the assumptions (in the form of cost 

indices) used to depict expected changes in costs over the 2012-2050 modeling time horizon. 

Section 10.5 describes how liquefied natural gas (LNG) imports are represented in the natural gas 

module. The section covers the assumptions regarding liquefaction facilities, LNG supply, 

regasification capacity, and related costs. Section 10.6 turns to demand side issues, in particular, 

how non-power sector residential, commercial, and industrial demand is represented. Section 

10.7 describes the detailed characterization of the natural gas pipeline network, the pipeline 

capacity expansion logic, and the assumptions and procedures used to capture pipeline 

transportation costs. Section 10.8 treats issues related to natural gas storage: capacity 

characterization and expansion logic, injection/withdrawal rates, and associated costs. Section 

10.9 describes the crude oil and natural gas liquids (NGL) price projections that are exogenous 

inputs in the natural gas module. They figure in the modeling of natural gas because they are a 

source of revenue which influence the exploration and development of hydrocarbon resources. 

The chapter concludes in Section 10.10 with a discussion of key gas market parameters in the 

report and proxy natural gas supply curves from the new integrated model based on results in 

EPA Base Case v.4.10. The proxy curves are meant to provide a point of comparison with the 

natural gas supply curves used in previous EPA IPM base case. 

10.1 Overview of IPM’s Natural Gas Module 

In previous EPA base cases natural gas supply curves and related assumptions were developed 

outside of IPM and provided in an iterative fashion as static inputs to the base case. Regional gas 

price forecast, in the form of basis differentials1

, was also provided as static inputs for delivered 

gas price calculations. The iteration process began with a set of supply curves and basis 

differentials generated from a series of runs using external stand-alone gas model. Results from 

the IPM run such as power sector gas demand and heat rates were fed back to the gas model as 

inputs for the next iteration. It was a time consuming process as it took several iterations to 

converge and involving human interaction between iterations. 

In EPA Base Case v.4.10 natural gas supply, demand, transportation, storage, and related costs 

are modeled directly in IPM through the incorporation of a new natural gas module. In the new 

system, natural gas supply curves are generated endogenously for each region, and the balance 

between the natural gas supply and demand is solved in all regions simultaneously. Integrating 

natural gas modeling into IPM as illustrated in Figure 10-1 and Figure 10-2 has some advantages 

over the previous modeling approach. The direct interaction between the electric and the gas 

modules captures the overall gas supply and demand dynamic and requires no iteration. The 

 

1 In natural gas discussions “basis” refers to differences in the price of natural gas in two different 

geographical locations. In the marketplace “basis” typically means the difference between the 

NYMEX futures price at the Henry Hub and the cash price at other market points. In the modeling 

context “basis” means the difference in natural gas prices between any two nodes at the same 

instance in time. 
10-2 

model solves for gas price in each region, therefore, it does not need to import gas price basis 

differentials as in the previous approach. 

The result from a modeling standpoint is a new integrated natural gas module with a linear 

programming (LP) structure that is fully consistent and compatible with that used in IPM. Natural 

gas LP components, which include objective function parameters consistent in form with IPM’s 

cost minimization, a series of decision variables, and a set of constraints, have been added to the 

original LP structure of the IPM electricity module. This integration makes the gas module a 

working component of the IPM modeling framework. 

To a certain extent, the design and assumptions of the new natural gas module are similar to 

those in ICF International’s private practice Gas Market Model (GMM) which has been used 

extensively for forecasting and market analyses in the North American natural gas market. To 

provide these new natural gas modeling capabilities within IPM and still maintain an acceptable 

model size and solution time, however, simplifications of some of the GMM design and 

assumptions were made. 

Seasonality in the gas module is made consistent with that in IPM and is currently modeled with 

two seasons (summer and winter), each with up to six IPM load periods that correspond to the 

IPM electric sector load duration curve (LDC) segments. The gas module also employs a similar 

run year concept as in IPM where, in order to manage model size, individual calendar years over 

the entire modeling period are mapped to a lesser number of run years. In the current version, 

both modules use the same run year mapping. 

Figure 10-1 Modeling and Data Structure in EPA Base Case v.4.10. 
10-3 

Figure 10-2 Natural Gas Module in EPA Base Case v.4.10. 
10-4 

10.2 Key Components of the New IPM Natural Gas Module 

The new gas module is a full supply/demand equilibrium model of the North American gas market. 

 Most of the structure and data for the gas module are derived from ICF’s Gas Market Model 

(GMM). It consists of 114 supply/demand/storage nodes and 14 LNG regasification facility 

locations that are tied together by a series of links that represent the North American natural gas 

transmission network as shown in Figure 10-3. The list of the 114 nodes is tabulated in Table 

10-1. 

Key elements of the natural gas module (which are described in detail in Sections 10.3-10.9) 

include: 

Natural Gas Resources are modeled by a set of base year resource cost curves, which 

represent undiscovered resource availability or recoverable resource as a function of exploration 

& development (E&D) cost for 77 supply regions. “Resource Appreciation”2 is added to the 

resource base to account for additional resources from plays that are not included in the resource 

base estimates due to lack of knowledge and technology to economically recover the resources. 

The construction of the resource cost curves are based on resource characterizations and 

economic evaluations from the Hydrocarbon Supply Model (HSM) of the GMM. (The HSM is 

discussed in greater detail in Sections 10.3 and 10.4 below.) Figure 10-4 depicts the geographic 

locations of the supply regions and Table 10-2 provides a list of the supply regions and a mapping 

of the regions to the modeling nodes. 

Natural Gas production from the 77 supply regions is calculated from the resource cost curves 

based on exploration and development activities that are a function of drilling success rate, rigs 

availability, reserves-to-production (R/P) ratio, and the costs of exploration, reserves development, 

and production that are applicable in the specific regions. 

LNG import level for each of the LNG regasification facilities is calculated from LNG supply 

availability curves (derived from the LNG supply curve module of GMM) based on the solution gas 

price and the regasification capacity at the corresponding LNG node. Availability and 

regasification capacity of the facilities are specified as inputs. The model has the capability to 

expand regasification capacity. However, due to excess of LNG regasification capacity already in 

the system and a relatively low electricity demand growth assumption in the EPA Base Case 

v.4.10, the regasification expansion feature is turned off. If future economic demands more LNG 

capacity, it can be turned back on. 

End use natural gas demand for the non-power sectors (i.e. the residential, commercial, and 

industrial sectors) is incorporated in the IPM LP structure through node-level interruptible and firm 

demand curves derived from the GMM natural gas demand module. (These are discussed in 

greater detail in Section 10.6 below.) The gas consumption in the non-power sectors is calculated 

within the gas module and the power sector consumption is calculated within the IPM electricity 

dispatch module. Figure 10-5 shows the geographic locations of the demand regions. 

 

2

 Resource appreciation represents growth in ultimate resource estimates attributed to success in 

extracting resource from known plays such as natural gas from shales, coal seams, offshore 

deepwater, and gas hydrates that are not included in the resource base estimates. 
10-5 

Figure 10-3 Gas Transmission Network Map 

Not all LNG nodes are shown

Table 10-1 List of Nodes 

Node Name Supply Demand 

Transit, 

Import/ 

Export 

Underground 

Storage 

Peakshaving 

Storage 

1 New England X X 

2 Everett TRANS X 

3 Quebec X X 

4 New York City X X 

5 Niagara X X X X 

6 Leidy X X X X 

7 Cove Point TRANS X 

8 Georgia X X 

9 Elba Is TRANS X 

10 South Florida X X 

11 East Ohio X X X X 

12 Maumee/Defiance X X X 

13 Lebanon X X X 

14 Indiana X X X X 

15 South Illinois X X X X 

16 North Illinois X X X X 

17 Southeast Michigan X X X X 

18 Tennessee/Kentucky X X X X 

19 MD/DC/Northern VA X X 

20 Wisconsin X X X 
10-6 

Node Name Supply Demand 

Transit, 

Import/ 

Export 

Underground 

Storage 

Peakshaving 

Storage 

21 Northern Missouri X X X 

22 Minnesota X X X X 

23 Crystal Falls X X X 

24 Ventura X X X X 

25 Emerson Imports X 

26 Nebraska X X X X 

27 Great Plains X 

28 Kansas X X X X 

29 East Colorado X X X X 

30 Opal X X X X 

31 Cheyenne X X X 

32 San Juan Basin X X X 

33 EPNG/TW X X X 

34 North Wyoming X X X 

35 South Nevada X X X 

36 SOCAL Area X X X X 

37 Enhanced Oil Recovery Region X X 

38 PGE Area X X X X 

39 Pacific Offshore X 

40 Monchy Imports X 

41 Montana/North Dakota X X X X 

42 Wild Horse Imports X 

43 Kingsgate Imports X 

44 Huntingdon Imports X 

45 Pacific Northwest X X X X 

46 NPC/PGT Hub X X 

47 North Nevada X X X 

48 Idaho X X X 

49 Eastern Canada Offshore X 

50 Atlantic Offshore X 

51 Reynosa Imp/Exp X 

52 Juarez Imp/Exp X 

53 Naco Imp/Exp X 

54 North Alabama X X X X 

55 Alabama Offshore X 

56 North Mississippi X X X X 

57 East Louisiana Shelf X 

58 Eastern Louisiana Hub X X X X 

59 Viosca Knoll/Desoto/Miss 

Canyon X 

60 Henry Hub X X X X 

61 North Louisiana Hub X X X X 

62 Central and West Louisiana 

Shelf X 

63 Southwest Texas X X X 

64 Dallas/Ft Worth X X X X 

65 E. TX (Katy) X X X X 
10-7 

Node Name Supply Demand 

Transit, 

Import/ 

Export 

Underground 

Storage 

Peakshaving 

Storage 

66 S. TX X X X 

67 Offshore Texas X 

68 NW TX X X X 

69 Garden Banks X 

70 Green Canyon X 

71 Eastern Gulf X 

72 North British Columbia X X X 

73 South British Columbia X X 

74 Caroline X X X 

75 Empress X 

76 Saskatchewan X X X 

77 Manitoba X X X 

78 Dawn X X X 

79 Philadelphia X X 

80 West Virginia X X X X 

81 Eastern Canada Demand X X 

82 Alliance Border Crossing X 

83 Wind River Basin X X X 

84 California Mexican Exports X 

85 Whitehorse X 

86 MacKenzie Delta X 

87 South Alaska X X 

88 Central Alaska X 

89 North Alaska X 

90 Arctic X 

91 Norman Wells X 

92 Southwest VA X X X X 

93 Southeast VA X X 

94 North Carolina X X 

95 South Carolina X X 

96 North Florida X X X 

97 Arizona X X X 

98 Southwest Michigan X X X X 

99 Northern Michigan X X X X 

100 Malin Interchange X 

101 Topock Interchange X 

102 Ehrenberg Interchange X 

103 SDG&E Demand X X 

104 Eastern New York X X 

105 New Jersey X X 

106 Toronto X X 

107 Carthage X X X X 

108 Southwest Oklahoma X X X X 

109 Northeast Oklahoma X X X X 

110 Southeastern Oklahoma X X X X 

111 Northern Arkansas X X X X 
10-8 

Node Name Supply Demand 

Transit, 

Import/ 

Export 

Underground 

Storage 

Peakshaving 

Storage 

112 Southeast Missouri X X X X 

113 Uinta/Piceance X X X X 

114 South MS/AL X X X X 

Figure 10-4 Gas Supply Regions Map 

Canadian Arctic and Alaskan Supply Regions not shown
10-1 

Table 10-2 List of Gas Supply Regions 

Supply 

Region 

Number 

Node 

Number Region Name 

1 5 Niagara 

2 6 Leidy 

3 96 Florida 

4 11 East Ohio 

5 12 Maumee/ Defiance 

6 13 Lebanon 

7 14 Indiana 

8 15 South Illinois 

9 16 North Illinois 

10 17 Southeast Michigan 

11 18 Tennessee/Kentucky 

12 92 SW Virginia 

13 20 Wisconsin 

14 21 Northern Missouri 

15 22 Minnesota 

16 23 Crystal Falls 

17 24 Ventura 

18 26 Nebraska 

19 28 Kansas 

20 29 East Colorado 

21 30 Opal 

22 31 Cheyenne 

23 32 San Juan Basin 

24 33 EPNG/TW 

25 34 North Wyoming 

26 97 Arizona 

27 36 SOCAL Area 

28 38 PGE Area 

29 39 California Offshore 

30 41 Montana/ North Dakota 

31 45 Pacific Northwest 

32 47 North Nevada 

33 48 Idaho 

34 49 Eastern Canada Offshore 

35 50 Atlantic Offshore 

36 54 North Alabama 

37 55 Alabama Offshore 

38 56 North Mississippi 

39 57 East Louisiana Shelf 

40 58 Eastern Louisiana Hub 

41 59 Viosca Knoll S./ Desoto Canyon/Mississippi 

Canyon 

42 60 Henry Hub 

43 61 North Louisiana Hub 

44 62 Central and West Louisiana Shelf 
10-2 

Supply 

Region 

Number 

Node 

Number Region Name 

45 63 Southwest Texas 

46 64 Dallas/Fort Worth 

47 65 E. TX (Katy) 

48 66 S. TX 

49 67 Offshore Texas 

50 68 NW TX 

51 69 Garden Banks 

52 70 Green Canyon 

53 71 Florida off-shore moratorium area 

54 72 North British Columbia 

55 74 Caroline 

56 76 Saskatchewan 

57 77 Manitoba 

58 78 Dawn 

59 80 West Virginia 

60 83 Wind River Basin 

61 86 McKenzie Delta 

62 87 Southern Alaska 

63 88 Central Alaska 

64 89 Northern Alaska 

65 90 Arctic 

66 91 Norman Wells 

67 37 Enhanced Oil Recovery Region 

68 98 Southwest Michigan 

69 99 Central Michigan 

70 107 Carthage 

71 108 Southwest Oklahoma 

72 109 Northeast Oklahoma 

73 110 Southeastern Oklahoma 

74 111 Northern Arkansas 

75 112 Southeast Missouri 

76 113 Uinta/Piceance 

77 114 South MS/AL 
10-3 

Figure 10-5 Gas Demand Regions Map 

Natural gas pipeline network is modeled by 343 transmission links or segments (excluding 

pipeline connections with LNG nodes) that represent major interstate transmission corridors 

throughout North America (Figure 10-3). The pipeline corridors represent a group of interstate 

pipelines along the corridor. The list of key interstate pipelines by links is tabulated in Table 10-3. 

 Each of the links has an associated discount curve (derived from GMM natural gas transportation 

module), which represents the marginal value of gas transmission on that pipeline segment as a 

function of the pipeline’s load factor.1

 Starting year of operation and transmission capacity (in 

units of BBtu/day) are specified as inputs and the model allows for capacity expansions. 

Table 10-3 List of Key Pipelines 

Link Pipeline 

6 - 5 DOMINION TRANS (CNG) 

6 - 5 COLUMBIA GAS TRANS CORP 

5 - 6 NATIONAL FUEL GAS SUPPLY CO 

11 - 6 DOMINION TRANS (CNG) 

11 - 6 COLUMBIA GAS TRANS CORP 

6 - 19 DOMINION TRANS (CNG) 

6 - 79 TEXAS EASTERN TRANS CORP 

6 - 79 TRANSCONTINENTAL GAS P L CO 

 

1

 In this context “load factor” refers to the percentage of the pipeline capacity that is utilized at a 

given time. 
10-4 

Link Pipeline 

6 - 79 TENNESSEE GAS PIPELINE CO 

80 - 6 COLUMBIA GAS TRANS CORP 

80 - 6 EQUITRANS INC 

96 - 8 SOUTHERN NATURAL GAS CO 

96 - 10 FLORIDA GAS TRANS CO 

80 - 11 COLUMBIA GAS TRANS CORP 

17 - 12 ANR PIPELINE CO 

98 - 12 ANR PIPELINE CO 

14 - 13 PANHANDLE EASTERN P L CO 

98 - 14 TRUNKLINE GAS CO 

16 - 15 NAT GAS P L CO OF AMERICA 

16 - 20 ANR PIPELINE CO 

16 - 98 ANR PIPELINE CO 

78 - 17 BLUEWATER PIPELINE CO 

99 - 17 MICHCON 

18 - 80 COLUMBIA GAS TRANS CORP 

18 - 92 EAST TENNESSEE NAT GAS CO 

79 - 19 EASTERN SHORE NAT GAS CO 

19 - 79 TRANSCONTINENTAL GAS P L CO 

19 - 79 COLUMBIA GAS TRANS CORP 

92 - 19 COLUMBIA GAS TRANS CORP 

23 - 99 GREAT LAKES GAS TRANS LTD 

106 - 23 GREAT LAKES GAS TRANS LTD 

41 - 27 WILLISTON BASIN P L CO 

28 - 29 COLORADO INTERSTATE GAS 

68 - 28 COLORADO INTERSTATE GAS 

31 - 30 COLORADO INTERSTATE GAS 

31 - 30 SOUTHERN STAR CENTRAL (WILLIAMS) 

30 - 31 WYOMING INTERSTATE CO 

30 - 48 NORTHWEST PIPELINE CORP 

113 - 30 NORTHWEST PIPELINE CORP 

113 - 32 NORTHWEST PIPELINE CORP 

63 - 33 EL PASO NAT GAS CO 

63 - 33 TRANSWESTERN PIPELINE CO 

68 - 33 TRANSWESTERN PIPELINE CO 

37 - 36 SOCAL GAS 

37 - 38 PACIFIC GAS & ELECTRIC 

40 - 41 NORTHWEST ENERGY 

41 - 83 WILLISTON BASIN P L CO 

73 - 43 TERASEN (BC GAS) 

46 - 45 NORTHWEST PIPELINE CORP 

46 - 48 NORTHWEST PIPELINE CORP 

66 - 51 TENNESSEE GAS PIPELINE CO 

51 - 66 TEXAS EASTERN TRANS CORP 

54 - 114 TRANSCONTINENTAL GAS P L CO 

58 - 56 GULF SOUTH (KOCH) 

60 - 58 TRANSCONTINENTAL GAS P L CO 
10-5 

Link Pipeline 

60 - 58 SOUTHERN NATURAL GAS CO 

60 - 58 FLORIDA GAS TRANS CO 

60 - 58 TENNESSEE GAS PIPELINE CO 

60 - 58 TEXAS EASTERN TRANS CORP 

60 - 58 GULF SOUTH (KOCH) 

60 - 65 NAT GAS P L CO OF AMERICA 

61 - 107 CENTERPOINT ENERGY (RELIANT) 

64 - 63 TXU LONESTAR GAS PIPELINE 

64 - 63 EPGT TEXAS PIPELINE (VALERO) 

65 - 63 OASIS 

66 - 63 EPGT TEXAS PIPELINE (VALERO) 

68 - 63 TRANSWESTERN PIPELINE CO 

63 - 68 EL PASO NAT GAS CO 

63 - 97 EL PASO NAT GAS CO 

65 - 64 TXU FUEL CO 

65 - 64 TXU LONESTAR GAS PIPELINE 

108 - 68 NAT GAS P L CO OF AMERICA 

108 - 68 EL PASO NAT GAS CO 

68 - 108 ANR PIPELINE CO 

106 - 78 UNION GAS 

102 - 84 BAJA NORTE 

99 - 98 ANR PIPELINE CO 

99 - 98 MICHIGAN GAS STORAGE 

101 - 102 EL PASO NAT GAS CO 

Natural gas storage is modeled by 180 underground and LNG peak shaving2

 storage facilities 

that are linked to individual nodes. The underground storage is grouped into three categories 

based on storage “Days Service”3

: (1) 20-day for high deliverability4 storage such as salt caverns, 

(2) 80-day for depleted5

 and aquifer6 reservoirs, and (3) over 80 days mainly for depleted 

reservoirs. Figure 10-6 shows natural gas storage facility node map. The level of gas storage 

withdrawals and injections are calculated within the supply and demand balance algorithm based 

on working gas7 levels, gas prices, and extraction/injection rates and costs. Starting year of 

 

2

 LNG peak shaving facilities supplement deliveries of natural gas during times of peak periods. 

LNG peak shaving facilities have a regasification unit attached, but may or may not have a 

liquefaction unit. Facilities without a liquefaction unit depend upon tank trucks to bring LNG from 

nearby sources.

3

 “Days Service” refers to the number of days required to completely withdraw the maximum 

working gas inventory associated with an underground storage facility. 

4

 High deliverability storage is depleted reservoir storage facility or Salt Cavern storage whose 

design allows a relatively quick turnover of the working gas capacity. 

5

 A gas or oil reservoir that is converted for gas storage operations. Its economically recoverable 

reserves have usually been nearly or completely produced prior to the conversion. 

6

 The underground storage of natural gas in a porous and permeable rock formation topped by an 

impermeable cap rock, the pore space of which was originally filled with water. 

7 The term “working gas” refers to natural gas that has been injected into an underground storage 

facility and stored therein temporarily with the intention of withdrawing it. It is distinguished from 

“base (or cushion) gas” which refers to the volume of gas that remains permanently in the storage 
10-6 

operation and working gas capacity (in units of BBtu) are specified as inputs and the model allows 

for capacity expansions. The location of the storage facilities is shown in Figure 10-6. 

Natural gas prices are market clearing prices derived from the supply and demand balance at 

each of the model’s nodes for each segment of IPM’s electricity sector’s seasonal load duration 

curve (LDC). On the supply-side, prices are determined by production and storage price curves 

that reflect prices as a function of production and storage utilization. Prices are also affected by 

the “pipeline discount” curves discussed earlier, which represent the marginal value of gas 

transmission as a function of a pipeline’s load factor and result in changes in basis differential. On 

the demand-side, the price/quantity relationship is represented by demand curves that capture the 

fuel-switching behavior of end-users at different price levels. The model balances supply and 

demand at all nodes and yields market clearing prices determined by the specific shape of the 

supply and demand curves at each node. 

10.2.1 Note on the Modeling Time Horizon and Pre- and Post-2030 Input Assumptions 

The time horizon of previous EPA IPM base cases extended no further than 2030. This made 

possible a detailed bottom-up development of natural gas assumptions from available data 

sources. To support analysis of climate change policies, which have a longer time horizon than 

previously analyzed policies for conventional air pollutants, the time horizon of EPA’s new Base 

Case v.4.10 extends to 2050. The same detailed bottom-up approach that was employed 

previously is employed out to 2030. Beyond 2030, where detailed data is not readily available, 

various technically plausible simplifying assumptions were made. For example, natural gas 

demand growth from 2030 to 2050 for the non-power sectors (i.e. residential, commercial, and 

industrial) is assumed to be the same as the level of growth from 2020 to 2030. Resource growth 

assumptions (for resource appreciation) that were applied for pre-2030 are extended beyond 

2030. Post 2030 price projections for crude oil and natural gas liquid8

 (NGL) are assumed to be 

flat at 2030 price levels. The pre-2030 price projections were adapted from AEO 2010.

 reservoir in order to maintain adequate pressure and deliverability rates throughout the withdrawal 

season. 

8

 Those hydrocarbons in natural gas that are separated from the gas as liquids in gas processing 

or cycling plants. Generally such liquids consist of propane and heavier hydrocarbons and are 

commonly referred to as lease condensate, natural gasoline, and liquefied petroleum gases. 
10-7 

Figure 10-6 Natural Gas Storage Facility Node Map 

7 7

7

7

7

3

8

10

7

20-Day

80-Day

Over 80 Days

LNG Peak Shaving

10.3 Resource Characterization and Economic Evaluation 

The GMM Hydrocarbon Supply Model (HSM) provides data related to resource characterization 

and economic evaluation for use in the IPM natural gas module. The current section describes 

data sources and methods used in the HSM to characterize the North American natural gas 

resource base. This section concludes with a description of how the HSM resource 

characterization is used in the EPA Base Case v.4.10 gas module. The next section (i.e., Section 

10.4) describes the economic evaluation procedures applied to Exploration and Development 

(E&D) activities in the HSM and various constraints affecting E&D activities. 

The HSM was designed for the simulation, forecasting and analysis of natural gas, crude oil and 

natural gas liquids supply and cost trends in the United States and Canada. The HSM includes a 

highly detailed description of both the undiscovered and discovered resources in the US and 

Canada. The resource base is described on a field-by-field basis. The individual fields are 

characterized by type (i.e., oil or gas), size, and location. Location is defined both geographically 

and by depth. The HSM is a process-engineering model with a very detailed representation of 

potential gas resources and the technologies with which those resources can be proven9

 and 

produced. The degree and timing by which resources are proven and produced are determined in 

the model through discounted cashflow analyses of alternative investment options and behavioral 

assumptions in the form of inertial and cashflow constraints, and the logic underlying producers' 

market expectations (e.g., their response to future gas prices). 

Supply results from the HSM model include undeveloped resource accounting and detailed well, 

reserve addition, decline rate, and financial results. These results are utilized to provide estimates 

 

9 The term “proven” refers to the estimation of the quantities of natural gas resources that analysis 

of geological and engineering data demonstrate with reasonable certainty to be recoverable in 

future years from known reservoirs under existing economic and operating conditions. Among the 

factors considered are drilling results, production, and historical trends. Proven reserves are the 

most certain portion of the resource base. 
10-8 

of base year economically recoverable natural gas resources and remaining reserves as a 

function of E&D cost for the 77 supply regions in the IPM natural gas module. The HSM also 

provides other data such as the level of remaining resource that could be discovered and 

developed in a year, exploration and development drilling requirements, production operation and 

maintenance (O&M) cost, resource share of crude oil and natural gas liquids, natural gas reserves 

to production ratio, and natural gas requirement for lease and plant use.10

10.3.1 Resource and Reserves11 Assessment 

Data sources: The HSM uses the U.S. Geological Survey (USGS), Minerals Management 

Service (MMS), and Canadian Gas Potential Committee (CGPC) play-level12 resource 

assessments as the starting point for the new field/new pool13 assessments. Beyond the resource 

assessment data, ICF has access to numerous databases that were used for the HSM model 

development and other analysis. Completion-level production is based on IHS Energy completion 

level oil and gas production databases for the U.S. and Canada. The U.S. database contains 

information on approximately 300,000 U.S. completions. A structured system is employed to 

process this information and add certain ICF data (region, play, ultimate recovery, and gas 

composition) to each record. ICF also performs extensive quality control checks using other data 

sources such as the MMS completion and production data for Outer Continental Shelf (OCS) 

areas and state production reports. 

In the area of unconventional gas14, ICF has worked for many years with the Gas Research 

Institute (GRI)/Gas Technology Institute (GTI) to develop a database of tight gas, coalbed 

methane, and Devonian Shale reservoirs in the U.S. and Canada. Along with USGS 

assessments of continuous plays, the database was used to help develop the HSM’s “cells”, 

which represent resources in a specific geographic area, characterizing the unconventional 

resource in each basin, historical unconventional reserves estimates and typical decline curves.15

 

10 As discussed more fully in Section 10.4, natural gas for “lease and plant use” refers to the gas 

used in well, field, and lease operations (such as gas used in drilling operations, heaters, 

dehydrators, and field compressors) and as fuel in gas processing plants. 

11 When referring to natural gas a distinction is made between “resources” and “reserves.” 

“Resources” are concentrations of natural gas that are or may become of potential economic 

interest. “Reserves” are that part of the natural gas resource that has been fully evaluated and 

determined to be commercially viable to produce. 

12 A “play” refers to a set of known or postulated natural gas (or oil) accumulations sharing similar 

geologic, geographic, and temporal properties, such as source rock, migration pathway, timing, 

trapping mechanism, and hydrocarbon type. 

13 A “pool” is a subsurface accumulation of oil and other hydrocarbons. Pools are not necessarily 

big caverns. They can be small oil-filled pores. A “field” is an accumulation of hydrocarbons in 

the subsurface of sufficient size to be of economic interest. A field can consist of one or more 

pools. 

14 Unconventional gas refers to natural gas found in geological environments that differ from 

conventional hydrocarbon traps. It includes: (a) “tight gas,” i.e., natural gas found in relatively 

impermeable (very low porosity and permeability) sandstone and carbonate rocks; (b) “shale gas,” 

i.e., natural gas in the joints, fractures or the matrix of shales, the most prevalent low permeability 

low porosity sedimentary rock on earth; and (c) “coalbed methane,” which refers to methane (the 

key component of natural gas) found in coal seams, where it was generated during coal formation 

and contained in the microstructure of coal. Unconventional natural gas is distinguished from 

conventional gas which is extracted using traditional methods, typically from a well drilled into a 

geological formation exploiting natural subsurface pressure or artificial lifting to bring the gas and 

associated hydrocarbons to the wellhead at the surface. 

15 A decline curve is a plot of the rate of gas production against time. Since the production rate 

decline is associated with pressure decreases from oil and gas production, the curve tends to 

smoothly decline from a high early production rate to lower later production rate. Exponential, 
10-9 

 ICF has recently revised the unconventional gas resource assessments based on new gas 

industry information on the geology, well production characteristics, and costs. The new 

assessments include major shale units such as the Fort Worth Barnett Shale, the Marcellus Shale, 

the Haynessville Shale, and Western Canada shale plays. ICF has built up a database on gas 

compositions in the United States and has merged that data with production data to allow the 

analysis of net versus raw gas production.16

In Canada, gas composition data are obtained from provincial agencies. These data were used to 

develop dry gas17 production/reserves by region and processing costs in the HSM and to 

characterize ethane rejection18 by regions. Information on oil and gas fields and pools in the U.S. 

come originally from Dwight’s Energydata (now IHS Energy) TOTL reservoir database. ICF has 

made extensive modifications to the database during the creation of the Gas Information System 

(GASIS) database for the U.S. Department of Energy (DOE) and other projects. Field and 

reservoir data for Canada comes from the provincial agency databases. These data are used to 

estimate the number and size of undiscovered fields or pools and their rate of discovery per 

increment of exploratory drilling. Additional data were obtained from the Significant Field Data 

Base of NRG Associates. 

Methodology and assumptions: Resources in the HSM model are divided into three general 

categories: new fields/new pools, field appreciation, and unconventional gas. The methodology 

for resource characterization and economic evaluation differs for each. 

Conventional resource – new fields/new pools: The modeling of conventional resource is based 

on a modified “Arps Roberts” equation19 to estimate the rate at which new fields are discovered. 

The fundamental theory behind the find-rate methodology is that the probability of finding a field is 

proportional to the field's size as measured by its area extent, which is highly correlated to the 

field's level of reserves. For this reason, larger fields tend to be found earlier in the discovery 

process than smaller fields. Finding that the original Arps-Roberts equation did not replicate 

historical discovery patterns for many of the smaller field sizes, ICF modified the equation to 

improve its ability to accurately track discovery rates for mid- to small-size fields. Since these are 

the only fields left to be discovered in many mature areas of the U.S. and Western Canada 

Sedimentary Basin (WCSB), the more accurate find-rate representation is an important 

component in analyzing the economics of exploration activity in these areas. An economic 

evaluation is made in the model each year for potential new field exploration programs using a 

standard discounted after-tax cash flow (DCF) analysis. This DCF analysis takes into account 

how many fields of each type are expected to be found and the economics of developing each. 

 harmonic, and hyperbolic equations are typically used to represent the decline curve. 

16 Raw gas production refers to the volumes of natural gas extracted from underground sources, 

whereas net gas production refers to the volume of purified, marketable natural gas leaving the 

natural gas processing plant. 

17 Natural gas is a combustible mixture of hydrocarbon gases. Although consisting primarily of 

methane, the composition of natural gas can vary widely to include propane, butane, ethane, and 

pentane. Natural gas is referred to as 'dry' when it is almost pure methane, having had most of the 

other commonly associated hydrocarbons removed. When other hydrocarbons are present, the 

natural gas is called 'wet'. 

18 Ethane rejection occurs when the ethane component in the natural gas stream is not recovered 

in a gas processing plant but left in the marketable natural gas stream. Ethane rejection is 

deployed when the value of ethane is worth more in the gas stream than as an a separate 

commodity or as a component of natural gas liquids (NGL), which collectively refers to ethane, 

propane, normal butane, isobutane, and pentanes in processed and purified finished form. 

Information that characterizes ethane rejection by region can play a role in determining the 

production level and cost of natural gas by region. 

19 “Arps-Roberts equation” refers to the statistical model of petroleum discovery developed by J. J. 

Arps, and T. G. Roberts, T. G.,in the 1950’s. 
10-10 

Conventional resource – field appreciation: The model maintains inventories of potential 

resources that can be proved from already discovered fields. These inventories are referred to as 

appreciation, growth-to-known or “probables.” As the model simulation proceeds, these probables 

inventories are drawn down as the resources are proved. At the same time, the inventories of 

probables are increased due to future year appreciation of new fields that are added to the 

discovered fields’ data set during the model simulation. 

Unconventional resource: The Enhanced Recovery Module (or ERM) within the HSM, covers that 

portion of the resource base which falls outside the scope of the "conventional" oil and gas field 

discovery process dealt with elsewhere in the model. The ERM includes coalbed methane, shale 

gas, and tight gas. These resources generally correspond to the “continuous plays” designated by 

the USGS in its resource assessments. The ERM is organized by "cells", which represent 

resources in a specific geographic area. A cell can represent any size of area ranging from the 

entire region/depth interval to a single formation in a few townships of a basin. Each cell is 

evaluated in the model using the same discounted cashflow analysis used for new and old field 

investments. The ERM cells also are subject to the inertial and cashflow constraints affecting the 

other types of investment options in the model. The model reports total wells drilled, reserve 

additions, production, and dollars invested for each type of ERM cell (e.g., coalbed methane) 

within a region. 

10.3.2 Frontier Resources (Alaska and Mackenzie Delta) 

Besides the three general categories of resources described above, the handling of frontier 

resources in the HSM is worth noting. Frontier resources such as Alaska North Slope and 

Mackenzie Delta are subject to similar resource assessment and economic evaluation procedures 

as applied to other regions. Results from HSM simulation for the two frontier regions can be seen 

in Table 10-4. It shows an undiscovered resource potential is 126.8 Tcf for Alaska North Slope 

and 32.9 Tcf for Mackenzie Delta and remaining gas reserves of 25.5 Tcf and 0.4 Tcf for Alaska 

North Slope and Mackenzie Delta, respectively. However, unlike other regions, the resources 

from these regions are stranded to date due to lack of effective commercial access to markets. In 

fact, 6-8 Bcf/d of gas that is currently produced as part of the oil activities in the Alaska North 

Slope is re-injected back into the Slope’s oil reservoirs as part of the pressure maintenance 

programs. Several development proposals have been put forward for bringing this gas to market 

in order to realize the long-held goal of monetizing the Alaska North Slope and Mackenzie Delta 

gas. 

In developing the gas resource assumptions for EPA Base Case v.4.10, two gas pipeline projects 

were identified for bringing the two frontier gas supply resources to the markets in the U.S. and 

Canada. A diagnostic run was made with both potential pipeline projects turned on, letting the 

model decide the starting year of the projects and subsequent pipeline capacity expansions. 

Analysis of pipeline capacities and flows indicated that the Alaska gas pipeline project would be 

feasible starting from 2035, but the Mackenzie Delta pipeline project would not be feasible at all 

due to relatively low pipeline flows. These were the assumptions used for EPA Base Case v.4.10. 

Table 10-4 U.S. and Canada Natural Gas Resources and Reserves 

End of Year 2008 End of Year 2010 

Region 

Undiscovered 

Dry Gas 

Resource 

(Tcf) 

Dry Gas 

Reserves 

(Tcf) 

Undiscovered 

Dry Gas 

Resource 

(Tcf) 

Dry Gas 

Reserves 

(Tcf) 

Lower 48 Onshore Non 

Associated 1,629.0 208.5 1,616.2 208.0 

Conventional 313.3 50.1 306.6 50.0 

Northeast 15.4 3.8 15.0 3.8 

Gulf Coast 133.9 16.4 131.5 16.4 

Midcontinent 54.4 11.2 52.7 11.2 
10-11 

End of Year 2008 End of Year 2010 

Region 

Undiscovered 

Dry Gas 

Resource 

(Tcf) 

Dry Gas 

Reserves 

(Tcf) 

Undiscovered 

Dry Gas 

Resource 

(Tcf) 

Dry Gas 

Reserves 

(Tcf) 

Southwest 19.2 5.6 18.6 5.6 

Rocky Mountain 84.0 10.7 82.6 10.7 

West Coast 6.4 2.4 6.2 2.3 

Shale Gas 921.2 38.5 917.2 38.4 

Northeast 254.8 3.5 254.4 3.5 

Gulf Coast 433.1 13.5 431.6 13.4 

Midcontinent 133.9 10.9 132.9 10.8 

Southwest 61.3 10.7 60.3 10.6 

Rocky Mountain 37.9 - 37.7 - 

West Coast 0.3 - 0.3 - 

Coalbed Methane 73.9 20.5 73.1 20.4 

Northeast 9.5 2.0 9.5 2.0 

Gulf Coast 4.3 1.2 4.2 1.2 

Midcontinent 9.6 2.2 9.5 2.2 

Southwest - - - - 

Rocky Mountain 49.8 15.1 49.3 15.0 

West Coast 0.7 - 0.6 - 

Tight Gas 320.7 99.5 319.2 99.2 

Northeast 33.7 6.6 34.0 6.6 

Gulf Coast 59.6 28.9 58.2 28.9 

Midcontinent 4.6 7.5 4.6 7.5 

Southwest 6.1 15.2 5.9 15.1 

Rocky Mountain 205.1 41.2 204.9 41.1 

West Coast 11.5 - 11.6 - 

Lower 48 Offshore Non 

Associated 137.1 10.5 136.3 10.5 

Lower 48 AssociatedDissolved Gas 145.1 17.9 143.5 17.9 

Total Lower 48 1,911.2 237.0 1,895.9 236.3 

Alaska 153.6 35.2 153.3 35.2 

Alaska North Slope 126.8 25.2 126.8 25.2 

Alaska - Other 26.8 9.9 26.5 9.9 

Total U.S. 2,064.8 272.1 2,049.2 271.5 

 

Canada Non Associated 667.9 56.7 667.3 56.5 

Conventional 121.4 43.6 119.6 43.5 

Shale Gas 508.8 0.5 511.1 0.5 

Coalbed Methane 27.4 12.5 26.7 12.5 

Tight Gas 10.3 - 9.9 - 

Canada AssociatedDissolved Gas 8.1 2.7 8.0 2.7 

Eastern Canada Offshore 71.8 2.5 71.6 2.5 

MacKenzie Delta 32.9 0.4 32.9 0.4 

Total Canada 780.8 62.3 779.8 62.1 
10-12 

10.3.3 Use of the HSM resource and reserves data in EPA Base Case using IPM v.4.10 

Natural Gas Module 

The base year for the integrated gas-electricity module in EPA Base Case using IPM v.4.10 is 

2012. Having a base year in the future has implications on how the model is run and how the gas 

reserves and resources data are set up. The IPM run begins with a gas module only run for year 

2011 to provide end of year (EOY) 2011 reserves and resources as the starting point for the 

integrated run from 2012 onward. This in turn requires the reserves and resources data to be 

provided for the EOY 2010. Since the data from the HSM are as of EOY 2008, a two-year 

production forecast needs to be conducted to estimate the EOY 2010 gas resources and 

reserves. This production forecast is done using the GMM with the EPA Base Case assumptions. 

 In the future if an IPM sensitivity analysis case is performed whose assumptions are likely to have 

a significant impact on gas reserves and resources in the 2009-2010 timeframe, the HSM 

projection of EOY 2010 gas resources and reserves may have to be re-run. 

The last two columns in Table 10-4 give a snapshot of the starting natural gas resource and 

reserve assumptions that were provided by HSM to EPA Base Case v.4.10 for EOY 2010. In this 

table, undiscovered resources represent the economic volume of dry gas that could be discovered 

and developed with current technology through exploration and development at a specified 

maximum wellhead gas price. The reserves are remaining dry gas volumes to be produced from 

existing developed fields. For EPA Base Case the maximum wellhead price for the resource cost 

curves is capped at around $14/MMBtu (in real 2007 dollars). The ultimate potential undiscovered 

resources available are actually higher than those presented in Table 10-4 but it would cost more 

than $14/MMBtu to recover them. (It is important to note that this price is for wet20 gas at the 

wellhead in the production nodes and is found to be high enough to cover the range of wellhead 

prices for EPA scenarios. The dry gas price at the receiving nodes can be higher than 

$14/MMBtu which depends on the share of dry gas, lease and plant use, gas processing cost, 

production O&M cost, and pipeline transportation costs.) The approach used in the HSM to derive 

these costs is described more fully in section 10.4 below. 

Since the new IPM natural gas module differentiates conventional gas from unconventional gas, 

these are shown separately in Table 10-4. The conventional gas is subcategorized into nonassociated gas from gas fields and associated gas21 from oil fields. The unconventional gas is 

subdivided into coalbed methane, shale gas, and tight gas. The U.S. and Canada natural gas 

undiscovered resources and remaining reserves as of EOY 2008 and their estimates for the EOY 

2010 are also shown in Table 10-4. 

Figure 10-7 presents resource cost curves for the EOY 2010 initializing gas assumptions that the 

HSM provides for EPA Base Case v.4.10. The cost curves show the recoverable resources at 

different price levels. Separate resource cost curves are shown for key regions as well as for 

conventional and unconventional gas. The recoverable resources shown at maximum wellhead 

prices in these graphs are those tabulated in Table 10-4 under EOY 2010 column. The y-axis of 

the resource cost curves shows the cost at the wellhead of bringing the volume of undiscovered 

resource indicated on the x-axis into the reserves category. Figure 10-8 diagrams the exploration 

& development and production processes and the associated costs required to bring undiscovered 

resource into reserves and production. 

 

20 A mixture of hydrocarbon compounds and small quantities of various nonhydrocarbons existing 

in the gaseous phase or in solution with crude oil in porous rock formations at reservoir conditions. 

 The principal hydrocarbons normally contained in the mixture are methane, ethane, propane, 

butane, and pentane. Typical nonhydrocarbon gases that may be present in reservoir natural gas 

are water vapor, carbon dioxide, hydrogen sulfide, nitrogen and trace amounts of helium. 

21 Associated gas refers to natural gas that is produced in association with crude oil production, 

whereas non-associated gas is natural gas that is not in contact with significant quantities of crude 

oil in the reservoir. 
10-13 

Figure 10-7 Resource Cost Curves at the End of Year 2010 

10.3.4 Undiscovered Resource Appreciation 

Undiscovered resource appreciation is additional resources from hydrocarbon plays that were not 

included in the resource base estimates. It differs from field appreciation or reserves appreciation 

category discussed above which comes from already discovered fields. Natural gas from shales, 

coal seams, offshore deepwater, and gas hydrates may not be included in the resource base 

assessments due to lack of knowledge and technology to economically recover the resource. As 

new technology becomes available, these untapped resources can be produced economically in 

the future. One example is the advancements in horizontal drilling and hydraulic fracture 

technologies to produce gas from shale formations. For EPA Base Case, the undiscovered gas 

resource is assumed to grow at 0.2% per year for conventional gas and 0.75% per year for 

unconventional gas. The EOY 2010 undiscovered resources in Table 10-4 and Figure 10-7 

include resource appreciation in 2009 and 2010. 
10-14 

Figure 10-8 Exploration & Development and Production Processes and Costs to Bring 

Undiscovered Resource into Reserves and Production 

Production

(Wet)

- Reserves-to-production ratio

- Production cost

Production

Reserves Undiscovered

Resource

- Resource potential

- Resource discovery factor

- Exploration & Development drilling requirement

- Exploration & Development costs

Exploration & Development

Production

(Dry)

- Dry gas share

- Lease and plant use

- Gas processing cost

Processing

10.4 Exploration, Development, and Production Costs and Constraints 

10.4.1 Exploration and Development Cost 

Exploration and development (E&D) cost or resource cost is the expenditure for activities related 

to discovering and developing hydrocarbon resources. The E&D cost for natural gas resources is 

a function of many factors such as geographic location, field type, size, depth, exploratory success 

rates, and platform, drilling and other costs. The HSM contains base year cost for wells, 

platforms, operating costs and all other relevant cost items. In addition to the base year costs, the 

HSM contains cost indices that adjust costs over time. These indices are partly a function of 

technology drivers such as improved exploratory success rates, cost reductions in platform, 

drilling and other costs, improved recovery per well, and partly a function of regression-based 

algorithms that relate cost to oil and gas prices and industry activity. As oil and gas prices and 

industry activity increase, the cost for seismic, drilling & completion services, casing and tubing 

and lease equipment goes up. 

Other technology drivers affect exploratory success rates and reduce the need to drill exploratory 

wells. A similar adjustment is made to take into account changes over time in development 

success rates, but the relative effect is much smaller because development success rates are 

already rather high. The technology drivers that increase recovery per well are differentiated in 

the HSM by region and by type of gas. Generally, the improvements are specified as being 

greater for unconventional gas because their recovery factors are much lower than those of 

conventional gas. 

The HSM model provides estimates of E&D cost and the level of economically viable gas resource 

by region as a function of E&D cost. The HSM increased recovery as a function of technology 

improvement by region is converted to E&D and production technology improvement over time in 

the form of cost reduction factors by onshore, offshore shelf, and offshore deepwater as shown in 
10-15 

0.5

0.6

0.7

0.8

0.9

1.0

2010 2020 2030 2040 2050 2060

E&D Cost Multiplier

Onshore Offshore Shelf Offshore Deepw ater

Figure 10-9. The average cost reduction factors for onshore, offshore shelf, and offshore 

deepwater E&D activities are -0.9% per year, -0.7% per year, and -0.4% per year, respectively. 

These factors are predominantly affected by the level of E&D investments in the regions. The 

expected aggressive onshore E&D activities to find and produce unconventional gas resources, 

such as shale gas, will lead to more research in horizontal drilling and hydraulic fracturing 

technologies to improve productions and lower the costs. This is reflected in higher cost reduction 

factors for the onshore regions. 

Figure 10-10 shows E&D cost needed to discover and develop 2.5%, 5%, and 7.5% of the 

remaining undiscovered resource in 2011 by natural gas supply region. 

Figure 10-9 E&D and Production Technology Improvement Factor 

Figure 10-10 
10-16 

Incremental E&D Cost (EOY 2010) by Percentage of Resource Found 

0 2 4 6 8 10

(5) Niagara

(6) Leidy

(11) East Ohio

(14) Indiana

(15) South Illinois

(16) North Illinois

(18) Tennessee/Kentucky

(21) Northern Missouri

(28) Kansas

(29) East Colorado

(30) Opal

(32) San Juan Basin

(34) North Wyoming

(36) SOCAL Area

(37) Enhanced Oil Recovery Region

(38) PGE Area

(41) Montana/ North Dakota

(45) Pacific Northw est

(49) Eastern Canada Offshore

(54) North Alabama

(55) Alabama Offshore

(57) East Louisiana Shelf

(58) Eastern Louisiana Hub

(59) Viosca Knoll S./ Desoto

(60) Henry Hub

(61) North Louisiana Hub

(62) Central and West Louisiana Shelf

(63) Southw est Texas

(64) Dallas/Fort Worth

(65) E. TX (Katy)

(66) S. TX

(67) Offshore Texas

(68) NW TX

(69) Garden Banks

(70) Green Canyon

(71) Florida off-shore moratorium

(72) North British Columbia

(74) Caroline

(76) Saskatchew an

(80) West Virginia

(83) Wind River Basin

(86) McKenzie Delta

(87) Southern Alaska

(89) Northern Alaska

(90) Arctic

(92) SW Virginia

(96) Florida

(98) Southw est Michigan

(99) Central Michigan

(107) Carthage

(108) Southw est Oklahoma

(109) Northeast Oklahoma

(110) Southeastern Oklahoma

(111) Northern Arkansas

(113) Uinta/Piceance

(114) South MS/AL

Resource Cost at Wellhead

(2007$/MMBtu)

2.5% 5.0% 7.5%
10-17 

10.4.2 Resource Discovery and Drilling Constraints 

As mentioned above the simulation in HSM also provides other data such as resource discovery 

factors which describe the maximum share of remaining undiscovered resource that could be 

discovered and developed in a year and drilling requirements which describe the drilling required 

for successful exploration and development. These two parameters are constraints to the 

development of the resource and their values are not time dependent. The resource discovery 

constraint is the same for all regions and is assumed to be 4% of the remaining undiscovered 

resource (column 4 in Table 10-5). The drilling requirement constraint (column 5 in Table 10-5) is 

10,000 feet for every billion cubic feet of incremental resource discovered for onshore and 2,500 

feet/Bcf for offshore. 

Table 10-5 Exploration and Development Assumptions for EPA Base Case v.4.10 

Fraction of 

Hydrocarbons 

that are 

Natural Gas 

Liquids 

(NGLs) 

Fraction of 

Hydrocarbons 

that are Crude 

Oil 

Max Share of 

Resources 

that can be 

Developed 

per Year 

Exploration, 

Development 

Drilling 

Required 

Lease 

and Plant 

Use Region 

(Fraction) (Fraction) (Fraction) (Ft/Bcf) (Fraction) 

(5) Niagara 0.01 0.04 0.04 10,000 0.05 

(6) Leidy 0.00 0.05 0.04 10,000 0.03 

(11) East Ohio 0.00 0.23 0.04 10,000 0.01 

(14) Indiana 0.05 0.81 0.04 10,000 0.02 

(15) South Illinois 0.10 0.10 0.04 10,000 0.30 

(16) North Illinois 0.10 0.10 0.04 10,000 0.30 

(18) 

Tennessee/Kentucky 0.12 0.10 0.04 10,000 0.04 

(21) Northern Missouri 0.15 0.46 0.04 10,000 0.04 

(28) Kansas 0.13 0.17 0.04 10,000 0.04 

(29) East Colorado 0.09 0.10 0.04 10,000 0.05 

(30) Opal 0.09 0.10 0.04 10,000 0.05 

(32) San Juan Basin 0.09 0.10 0.04 10,000 0.13 

(34) North Wyoming 0.09 0.10 0.04 10,000 0.05 

(36) SOCAL Area 0.01 0.91 0.04 10,000 0.13 

(37) Enhanced Oil 

Recovery Region 0.02 0.81 0.04 10,000 0.13 

(38) PGE Area 0.03 0.88 0.04 10,000 0.13 

(41) Montana/ North 

Dakota 0.04 0.72 0.04 10,000 0.13 

(45) Pacific Northwest 0.26 0.00 0.04 10,000 0.02 

(49) Eastern Canada 

Offshore 0.01 0.88 0.04 2,500 0.06 

(54) North Alabama 0.04 0.22 0.04 10,000 0.03 

(55) Alabama 

Offshore 0.04 0.22 0.04 2,500 0.03 

(57) East Louisiana 

Shelf 0.07 0.52 0.04 2,500 0.04 

(58) Eastern Louisiana 

Hub 0.11 0.27 0.04 10,000 0.04 

(59) Viosca Knoll S./ 

Desoto 

Canyon/Mississippi 

Canyon 

0.07 0.52 0.04 2,500 0.04 

(60) Henry Hub 0.11 0.27 0.04 10,000 0.04 
10-18 

Fraction of 

Hydrocarbons 

that are 

Natural Gas 

Liquids 

(NGLs) 

Fraction of 

Hydrocarbons 

that are Crude 

Oil 

Max Share of 

Resources 

that can be 

Developed 

per Year 

Exploration, 

Development 

Drilling 

Required 

Lease 

and Plant 

Use Region 

(Fraction) (Fraction) (Fraction) (Ft/Bcf) (Fraction) 

(61) North Louisiana 

Hub 0.08 0.08 0.04 10,000 0.04 

(62) Central and West 

Louisiana Shelf 0.07 0.52 0.04 2,500 0.04 

(63) Southwest Texas 0.12 0.52 0.04 10,000 0.05 

(64) Dallas/Fort Worth 0.07 0.06 0.04 10,000 0.05 

(65) E. TX (Katy) 0.17 0.19 0.04 10,000 0.05 

(66) S. TX 0.12 0.07 0.04 10,000 0.05 

(67) Offshore Texas 0.06 0.25 0.04 2,500 0.05 

(68) NW TX 0.22 0.05 0.04 10,000 0.05 

(69) Garden Banks 0.06 0.25 0.04 2,500 0.04 

(70) Green Canyon 0.07 0.52 0.04 2,500 0.04 

(71) Florida off-shore 

moratorium area 0.07 0.52 0.04 2,500 0.04 

(72) North British 

Columbia 0.01 0.05 0.04 10,000 0.08 

(74) Caroline 0.03 0.19 0.04 10,000 0.10 

(76) Saskatchewan 0.00 0.73 0.04 10,000 0.07 

(80) West Virginia 0.07 0.04 0.04 10,000 0.04 

(83) Wind River Basin 0.09 0.10 0.04 10,000 0.05 

(86) McKenzie Delta 0.00 0.00 0.04 10,000 0.08 

(87) Southern Alaska 0.00 0.00 0.04 10,000 0.08 

(89) Northern Alaska 0.00 0.00 0.04 10,000 0.08 

(90) Arctic 0.05 0.55 0.04 10,000 0.08 

(92) SW Virginia 0.00 0.01 0.04 10,000 0.02 

(96) Florida 0.02 0.82 0.04 10,000 0.21 

(98) Southwest 

Michigan 0.04 0.11 0.04 10,000 0.04 

(99) Central Michigan 0.04 0.11 0.04 10,000 0.04 

(107) Carthage 0.08 0.08 0.04 10,000 0.05 

(108) Southwest 

Oklahoma 0.13 0.17 0.04 10,000 0.04 

(109) Northeast 

Oklahoma 0.13 0.17 0.04 10,000 0.04 

(110) Southeastern 

Oklahoma 0.13 0.17 0.04 10,000 0.04 

(111) Northern 

Arkansas 0.00 0.13 0.04 10,000 0.04 

(113) Uinta/Piceance 0.09 0.10 0.04 10,000 0.05 

(114) South MS/AL 0.04 0.22 0.04 10,000 0.03 

Other drilling constraints include rig capacity, rig retirement, rig growth, and drilling speed. Values 

for the constraints are specified for each of the three drilling category: (1) onshore, (2) offshore 

shelf, and (3) offshore deepwater. The drilling rig capacity constraint shows the number of drilling 

rigs initially available in the base year 2011. The initial rig counts are 3,798 rigs for onshore, 115 

rigs for offshore shelf, and 115 rigs for offshore deepwater and the numbers can change over time 

controlled by rig retirement and rig growth constraints. The drilling rig retirement constraint is the 
10-19 

share of rig capacity that can retire in a year. The drilling rig growth constraint is the maximum 

increase of total rig count in a year. The drilling retirement and growth are assumed to be the 

same for all drilling category and the constraints are set to 0.5% per year and 3.5% per year, 

respectively. 

Another growth constraint, minimum drilling capacity increase, is implemented to force the rig 

count to grow by at least one rig in each drilling category. The drilling speed constraint is the 

required speed in feet/day/rig for successful exploration and development. The drilling speed 

required for successful E&D grows over time, as shown in Figure 10-11 and differs for onshore 

and offshore (which in this case includes both shelf and deep shelf). 

Figure 10-11 Drilling Rig Speed Constraint 

0

100

200

300

400

500

600

700

2000 2010 2020 2030 2040 2050 2060

Drilling Speed (Feet/Day/Rig)

Onshore Offshore

10.4.3 Reserves-to-Production (R/P) Ratio 

The reserves-to-production ratio is the remaining amount of reserves, expressed in years, to be 

produced with a current annual production rate. In the IPM gas module, the R/P data obtained 

from the HSM is provided in the form of production-to-reserves (P/R) ratio (or reciprocal of the R/P 

ratio). The P/R ratio is used to calculate annual wet gas production from the reserves and the 

value varies by resource type and production node. For conventional gas the P/R ratio ranges 

from 0.04 (or 25 years of R/P) to 0.25 (or 4 years of R/P) with average of 0.13 (or 8 years of R/P). 

 The P/R ratio of shale and tight gas is half of that of the conventional gas with average P/R ratio 

of 0.06 (or 16 years of R/P). Coalbed methane gas has the lowest P/R ratio with average of 0.03 

(or 32 years of R/P) or half of that of the tight and shale gas. 

10.4.4 Variable Costs, Natural Gas Liquid Share, and Crude Oil Share 

In the IPM natural gas module, the variable costs include production operations and maintenance 

(O&M) cost and gas processing cost. The production O&M cost for 2011 is estimated to be 

$0.51/MMBtu (in real 2007 dollars) and is assumed to be the same for all supply regions. The 

production O&M cost is expected to decline over time due to improvements in production 

technology. In the model the same technology improvement factor shown in Figure 10-9 is 

applied to the production O&M cost. 

The resource data from the HSM is provided in the form of total hydrocarbon (oil, gas, and NGL) 

resource. The HSM also provides the allocations of the hydrocarbon for dry gas, oil, and NGL. 
10-20 

Table 10-5 shows the shares of NGL (column 2) and crude oil (column 3) by supply region. 

Associated gas from crude oil and NGL from wet gas are processed in gas processing plants to 

produce pipeline quality dry gas. Node level gas processing cost for IPM natural gas module is 

obtained from the GMM. The processing cost varies from $0.07/MMBtu (of wet gas in real 2007 

dollars) to $0.56/MMBtu with average of $0.22/MMBtu. 

10.4.5 Lease and Plant Gas Use 

The term “lease and plant gas” refers to the gas used in well, field, and lease operations (such as 

gas used in drilling operations, heaters, dehydrators, and field compressors) and as fuel in gas 

processing plants. The data for lease and plant gas use is derived for the HSM as a fraction of 

wet gas production and varies by region. The value ranges from 0.01 to as high as 0.3 with an 

average of around 0.06 (column 6 in Table 10-5). 

10.5 Liquefied Natural Gas (LNG) Imports 

As described earlier, most of the data related to North American LNG imports is derived from the 

GMM LNG model. Based on a comprehensive database of existing and potential liquefaction and 

regasification facilities and worldwide LNG import/export activities, the model uses a simulation 

procedure to create the base year 2011 North American LNG supply curves and projections of 

regasification capacity and costs. 

Key elements of the LNG model are described below. 

10.5.1 Liquefaction Facilities and LNG Supply 

The supply side of the GMM LNG model takes into account capacities from existing as well as 

potential liquefaction facilities. The lower and upper boundaries of supply capacity allocated for 

each North American regasification facility are set by available firm contracts and swing supplies. 

Three point LNG supply curves are generated within this envelope where: (1) the lower point is 

the amount of firm LNG supply, (2) the upper bound is the firm imports plus the maximum swing 

imports available for that facility, and (3) the midpoint is the average of the minimum and 

maximum values. Prices for the minimum and maximum points are tied to Refiner Acquisition 

Cost of Crude (RACC) price.22 The minimum price represents minimum production cost for 

liquefaction facilities and is set at 0.5 of RACC price and the maximum price is set at 1.5 of RACC 

price. The prices are then shifted up for winter months and shifted down in the summer months to 

represent the seasonal variation in competition from European LNG consumers. 

The individual LNG supply curves from the GMM LNG model are aggregated to create total North 

American LNG supply curves describing LNG availability serving the North American 

regasification facilities. The three point curves are converted to six points by linear interpolation to 

provide more supply steps in the IPM natural gas module. Two LNG supply curves, one for winter 

and one for summer, are specified for each year starting from 2011 until 2054 to capture growth 

as well as seasonal variation of the LNG supplies. Figure 10-12 shows the North American LNG 

supply curves for the winters and summers of 2011 and 2050. 

 

22 Refiner Acquisition Cost of Crude Oil (RACC) is a term commonly use in discussing crude oil. It 

is the cost of crude oil to the refiner, including transportation and fees. The composite cost is the 

weighted average of domestic and imported crude oil costs. 
10-21 

Figure 10-12 North American LNG Supply Curves 

Winter 2011

0

10

20

30

40

50

0 5 10 15 20 25 30

Max quantity LNG (Bcf/day)

LNG Price (2007 $/MMBtu)

Winter 2050

0

10

20

30

40

50

0 5 10 15 20 25 30

Max quantity LNG (Bcf/day)

LNG Price (2007 $/MMBtu)

Summer 2011

0

10

20

30

40

50

0 5 10 15 20 25 30

Max quantity LNG (Bcf/day)

LNG Price (2007 $/MMBtu)

Summer 2050

0

10

20

30

40

50

0 5 10 15 20 25 30

Max quantity LNG (Bcf/day)

LNG Price (2007 $/MMBtu)

 

10.5.2 Regasification Facilities 

For the EPA Base Case, ten existing and four potentials North American LNG regasification 

facilities are considered in the IPM natural gas module. Table 10-6 lists the 14 facilities (current 

existing facilities are highlighted), the destination nodes where the LNG are delivered, and the 

base year 2011 capacity for each of the regasification facility. Figure 10-13 provides a map of 

these facilities. Existing Penuelas LNG facilities in Puerto Rico are not included because they are 

not part of the natural gas network in the IPM gas module. However, the electric generating units 

that consume gas from the Penuelas LNG facilities are included in the IPM electric module. In 

EPA Base Case v.4.10. the Penuelas LNG facilities are modeled with a fixed 150 MMcfd gas 

supply into Florida node and a link to connect the gas supply to the electric generating units in 

Puerto Rico. 

Table 10-6 North American LNG Regasification Facilities 

No LNG Regasification 

Facility Node Location 

Base Year 

(2011) 

Regasification 

Capacity 

(Bcf/day) 

1 Cove Point (7) Cove Point TRANS 1.50 

2 Elba Island (9) Elba Is TRANS 2.10 

3 Everett (2) Everett TRANS 0.70 
10-22 

No LNG Regasification 

Facility Node Location 

Base Year 

(2011) 

Regasification 

Capacity 

(Bcf/day) 

4 Gulf Gateway (69) Garden Banks 0.50 

5 Lake Charles (60) Henry Hub 2.10 

6 Altamira (51) Reynosa Imp/Exp 1.00 

7 Costa Azul (84) California Mexican Exports 2.00 

8 Cameron LNG (60) Henry Hub 1.50 

9 Freeport LNG (65) E. TX (Katy) 1.50 

10 Golden Pass (65) E. TX (Katy) 2.00 

11 Canaport (49) Eastern Canada Offshore 1.00 

12 Sabine Pass (60) Henry Hub 2.60 

13 Gulf LNG Energy 

LLC (56) North Mississippi 1.00 

14 Northeast Gateway (1) New England 0.80 

 

Figure 10-13 North American LNG Regasification Facilities Map 

(1) Cove Point

(2) Elba Island

(3) Everett

(14) NE Gateway

(4) Gulf Gateway

(5) Lake Charles

(6) Altamira

(7) Costa Azul

(8) Cameron LNG

(10) Golden Pass

(9) Freeport LNG

(11) Canaport

(12) Sabin Pass

(13) Gulf LNG Energy

Existing 

Potential

10.5.3 LNG Regasification Capacity Expansions 

The IPM natural gas module has two constraints for the regasification capacity expansion: (1) 

minimum LNG regasification facility capacity expansion and (2) maximum LNG regasification 

facility capacity expansion. The values are specified for each facility and year where the minimum 

constraint is used to force the model to add regasification capacity and the maximum constraint is 

the upper bound for the capacity expansion. 
10-23 

The decision of whether to expand regasification capacity is controlled by the two constraints and 

by a levelized capital cost for regasification capacity expansion. The base year 2011 levelized 

capital cost for capacity expansion (in real 2007 dollars per MMBtu of capacity expansion) is 

specified for each facility. A cost multiplier can be applied to represent the increase in levelized 

capital cost over time. The constraints for the capacity expansion can be used to turn on or off the 

regasification capacity expansion feature in the model. Setting both constraints to zero will 

deactivate this feature. 

If the regasification capacity is allowed to expand, the model can add capacity to a facility within 

the minimum and maximum constraints if the cost of the regasification expansion contributes to 

the optimal solution, i.e., minimizes the overall costs to the power sector, including the capital cost 

for adding new regasification capacity less their revenues. The model takes into account all 

possible options/projects (including regasification capacity expansions) in any year that do not 

violate the constraints and selects the combination of options/projects that provide the minimum 

objective function value. In this way, regasification capacity expansion projects will compete with 

each other and even with other projects such as pipeline expansions, storage expansions, etc. 

Due to excess LNG regasification capacity already in the system the regasification capacity 

expansion feature is not deployed in EPA Base Case v.4.10. EPA scenario results show very low 

total LNG utilizations, less than 15%, throughout the projection period which suggest the base 

year LNG regasification capacity is already high and requires no expansion. 

10.6 End Use Demand 

Non-power sector demand (i.e. the residential, commercial, and industrial) is modeled in the new 

gas module in the form of node-level firm and interruptible demand curves23. The firm demand 

curves are developed and used for residential, commercial, and some industrial sources, while the 

interruptible demand curves are developed and used exclusively for industrial sources. 

A three step process is used to prepare these curves for use in the IPM gas module. First, GMM 

is used to develop sector specific econometric models representing the non-power sector 

demand. Since the GMM econometric models are functions of weather, economic growth, price 

elasticity, efficiency and technology improvements, and other factors, these drivers, in effect, are 

embedded in the resulting IPM natural gas module demand curves. Second, projections are 

made using the GMM econometric models and assembled into monthly gas demand curves by 

sector and demand node. Third, using a second model, seasonal and load segment specific 

demand curves are derived from the monthly gas demand curves. The sections below describe 

each of these steps in further detail. 

10.6.1 Step 1: Developing Sector Specific Econometric Models of Non-Power Sector 

Demand 

Residential/Commercial Sector 

The GMM econometric models of residential and commercial demand are based on regression 

analysis of historical data for 41 demand regions and are adjusted to reflect conservation, 

efficiency, and technology changes over time. The regional data is allocated to the node level 

based on population data and information from the Energy Information Administration’s “Annual 

Report of Natural and Supplemental Gas Supply & Disposition” (EIA Form-176). Specifically, the 

econometric models used monthly Department of Energy/Energy Information Administration 

(DOE/EIA) data from January 1984 through December 2002 for the U.S. and monthly Statistics 

Canada data from January 1988 through December 2000 for Canada. 

 

23 “Firm” refers to natural gas demand that is not subject to interruptions from the supplier, 

whereas “interruptible” refers to natural gas demand that is subject to curtailment or cessation by 

the supplier. 
10-24 

The GMM econometric models showed node-level residential and commercial gas demand to be 

a function of heating degree days, elasticity of gas demand relative to GDP, and elasticity of gas 

demand relative to gas price. The GDP elasticity was generally about 0.4 for the residential sector 

and 0.6 for the commercial sector. The gas price elasticity was generally less than 0.1 for both 

sectors. Since gas demand in these sectors is relatively inelastic, GDP and price changes have 

small effects on demand. 

U.S. Industrial Sector 

The GMM econometric model of U.S. industrial gas demand employed historical data for 11 

census-based regions and ten industry sectors, focusing on gas-intensive industries such as: 

• Food 

• Pulp and Paper 

• Petroleum Refining 

• Chemicals 

• Stone, Clay and Glass 

• Iron and Steel 

• Primary Aluminum 

• Other Primary Metals 

• Other Manufacturing 

• Non-Manufacturing 

For each of these sectors three end-use categories (process heat, boilers, and other end uses) 

are modeled separately: 

• Process heat: This includes all uses of gas for direct heating as opposed to indirect heating 

(e.g., steam production). The GMM econometric modeling indicated that forecasts for 

process heat for each industrial sector are a function of growth in output, the energy intensity 

trend, and the price elasticity. Growth in output over time for most industries is controlled by 

industrial production indices. Energy intensity is a measure of the amount of gas consumed 

per unit of output. Energy intensity tends to decrease over time as industries become more 

efficient. 

• Boilers: This category includes natural gas-fired boilers whose purpose is to meet industrial 

steam demand. GMM econometric models indicated that gas demand for boilers is a function 

of the growth in industrial output and the amount of gas-to-oil switching. Industry steam 

requirements grow based on industrial production growth. A large percentage of the 

nominally “dual-fired” boilers cannot switch due to environmental and technical constraints. 

• Other end uses: This category includes all other uses for gas, including non-boiler 

cogeneration, on-site electricity generation, and space heating. Like the forecasts for process 

heat, the GMM econometric modeling showed “other end uses” for each industrial sector to be 

a function of growth in output, the energy intensity trend, and the price elasticity. 

In addition to these demand models, a separate regression model was use to characterize the 

chemicals sector’s demand for natural gas as a feedstock for ammonia, methanol, and nonrefinery hydrogen. Growth in the chemicals industry is represented by a log-linear regression 

model that relates the growth to GDP and natural gas prices. As GDP growth increases, chemical 

industry production increases; and as gas prices increase, chemical industry production 

decreases. 

The GMM econometric models for the U.S. industrial sector used DOE/EIA monthly data from 

January 1991 through December 2000. 

Canada Industrial Sector 

The industrial sector in Canada is modeled in less detail. Canada is divided into 6 regions based 

on provincial boundaries. The approach employs a regression fit of historic data similar to that 
10-25 

used in the residential/commercial sectors. Sub-sectors of Canadian industrial demand are not 

modeled separately. The Canadian industrial sector also includes power generation gas demand. 

 The model used Statistics Canada monthly data from January 1991 through December 2000. 

10.6.2 Step 2: Use projections based on the GMM econometric models to produce 

monthly gas demand curves by sector and demand node 

The regression functions resulting from the econometric exercises described in Step 1 are used to 

create monthly sector- and nodal-specific gas demand curves. To do this the functions are first 

populated with the macroeconomic assumptions that are consistent with those used in EPA Base 

Case 4.10. For these purposes a U.S. annual GDP growth rate of 3.0%, a U.S. annual industrial 

production growth rate of 2.3%, and a Canadian annual GDP growth rate of 2.5 % are assumed. 

Then, a range of natural gas prices are fed into the regression functions. At each gas price the 

regression functions report out projected monthly demand by sector and node. These are the 

GMM’s nodal demand curves. 

10.6.3 Step 3: Develop non-electric sector natural gas demand curves that correspond to 

the seasons and segments in the load duration curves used in IPM 

A second model, the Daily Gas Load Model (DGLM), is used to create daily gas load curves 

based on the GMM monthly gas demand curves obtained in Step 2. The DGLM uses the same 

gas demand algorithms as the GMM, but uses a daily temperature series to generate daily 

variations in demand, in contrast to the seasonal variations in gas demand that are obtained from 

the GMM. 

The resulting daily nodal demand data for each non-power demand sector are then re-aggregated 

into the two gas demand categories used in the IPM gas module: all of the residential and 

commercial demand plus 10% of the industrial demand is allocated to the firm gas demand 

curves, and the remaining 90% of the industrial demand is allocated to the interruptible gas 

demand curves. 

IPM, the power sector model, has to take into account natural gas demand faced by electric 

generating units that dispatch in different segments of the load duration curves, since demand for 

natural gas and its resulting price may be very different for units dispatching in the peak load 

segment than it is for units dispatching in the base, high shoulder, mid shoulder, or low shoulder 

load segments. In addition, since seasonal differences in demand can be significant, IPM requires 

separate load segment demand data for each season that is modeled. In EPA Base Case v.4.10, 

there are two seasons: Summer (May 1 – September 30) and winter (October 1 – April 30). 

Therefore, the firm and interruptible daily gas demand and associated prices are allocated to the 

summer and winter load segment based on the applicable season and prevailing load conditions 

to produce the final non-electric sector gas demand curves that are used in IPM. 

In EPA Base Case v.4.10, each of the summer and winter periods uses 6 load segments for pre2030 and 4 load segments for post-2030 as shown in Table 10-7. The “Peak” load segment in 

post-2030 is an aggregate of “Needle Peak“ and “Near Peak” load segments in the pre-2030. The 

“High Shoulder” load segment in post-2030 is an aggregate of “High Shoulder“ and “Middle 

Shoulder” load segments in the pre-2030. The same definitions of “Low Shoulder” and “Base” 

load segments are applied to both pre-2030 and post-2030. Input data for firm and interruptible 

demand curves are specified for all six load segments listed in the pre-2030 column of Table 10-7.
10-26 

Table 10-7 Summer and Winter Load Segments in EPA Base Case v.4.10 

Pre 2030 Post 2030 

1 Needle Peak 

2 Near Peak 

1 Peak 

3 High Shoulder 

4 Middle Shoulder 

2 High Shoulder 

5 Low Shoulder 3 Low Shoulder 

6 Base 4 Base 

Aggregation of summer and winter load segments from six in the pre-2030 to four in the post-2030 

is performed endogenously in the model. 

The non-electric sector demand curves (firm and interruptible) are generated based on GMM 

regressions described above with macroeconomic assumptions consistent with those of EPA 

Base Case v.4.10. A set of firm and interruptible gas demand curves is generated for each node 

and year. Examples of node-specific firm and interruptible demand curves for summer and winter 

load segments are shown in Figure 10-14 and Figure 10-15. It should be noted that firm gas 

demand (Figure 10-14) is very inelastic; only a small fraction of demand is shed as prices 

increase. The interruptible gas demand in the peak segments is also very inelastic as expected 

with higher elasticities in the shoulder and base load segments. 

It is important to note that the non-electric gas demand curves provided to the IPM/Gas model are 

static inputs. The implied elasticities in the curves represent short-term elasticities based on EPA 

Base Case v.4.10 macroeconomic assumptions. Long-term elasticity is not factored into the gas 

demand curves. In other words, changes in the assumptions that affect the price/volume solutions 

have no effect to the long-term gas demand elasticity. Sensitivity runs with slight modifications to 

the macroeconomic assumptions can still use the same curves if the gas demand forecast is 

expected not to be much different than that from the base case. In this case, changes in the gas 

demand solutions have minor effect to the long-term elasticity. However, a sensitivity run (e.g. 

carbon policy run) with major changes in CO2 allowance prices should not use the same gas 

demand curves because it will have higher impact to the long-term gas demand elasticity. A new 

set of non-electric gas demand curves needs to be generated for this type of run. 

Figure 10-14 Examples of Firm Demand Curves by Electric Load Segment 

New England (Node 1), Winter 2011

0

5

10

15

20

25

30

35

0.00 0.05 0.10 0.15 0.20 0.25 0.30

Firm Demand (Bcf)

Gas Price

(2007 $/MMBtu)

Needle Peak Near Peak High Shoulder

Middle Shoulder Low Shoulder Base

New England (Node 1), Summer 2011

0

5

10

15

20

25

30

35

0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07

Firm Demand (Bcf)

Gas Price

(2007 $/MMBtu)

Needle Peak Near Peak High Shoulder

Middle Shoulder Low Shoulder Base

 
10-27 

Figure 10-15 Examples of Interruptible Demand Curves by Electric Load Segment 

New England (Node 1), Winter 2011

0

5

10

15

20

25

30

35

0.00 5.00 10.00 15.00 20.00 25.00 30.00

Interruptible Demand (Bcf)

Gas Price

(2007 $/MMBtu)

Needle Peak Near Peak High Shoulder

Middle Shoulder Low Shoulder Base

New England (Node 1), Summer 2011

0

5

10

15

20

25

30

35

0.00 5.00 10.00 15.00 20.00 25.00 30.00

Interruptible Demand (Bcf)

Gas Price

(2007 $/MMBtu)

Needle Peak Near Peak High Shoulder

Middle Shoulder Low Shoulder Base

 

10.7 Pipeline Network 

10.7.1 Network Structure 

The pipeline network in the IPM natural gas module represents major transmission corridors (not 

individual pipelines) throughout North America. It contains 3431

 gas pipeline corridors (including 

bi-directional links) between the 114 nodes (Figure 10-3). Each corridor is characterized by 

maximum capacity and a “value of service” (discount curve) relationship that determines the 

market value of capacity as a function of load factor.2

 The node structure is developed to reflect 

points of change or influence on the pipeline system such as: 

• Major demand and supply centers 

• Pipeline Hubs and market centers 

• Points of divergence in pipeline corridors 

To illustrate the relationship of corridors and pipelines, Figure 10-16 shows the flow and capacity 

of five pipeline corridors in New England in 2020. Gas flows into New England along three 

pipeline corridors (indicated in Figure 10-16 by 3 of the 4 arrows that point into the region) 

representing a total of seven pipeline systems (indicated by name labels in Figure 10-16). New 

England also receives gas via the Everett LNG terminal (indicated in Figure 10-16 by the 4th 

arrow that points into the region). Also, some of the gas that flows into New England on the 

Iroquois system flows through the region and back to downstate New York; this is represented on 

the map as an export from New England (indicated in Figure 10-16 by the arrow that points away 

from the region). 

 

1

Excluding LNG import Terminal nodes and their pipeline connections. 

2

 See footnote #3 above for a definition of “load factor.” 
10-28 

Figure 10-16 New England Pipeline Corridors in 2020 

Maritimes & Northeast

Everett LNG

• Portland Natural Gas

• Granite State

• Vermont Gas

• Algonquin

• Iroquois

• Tennessee

Iroquois

59

858

 MMCFD

 Flow

 Capacity

700

950

143

249

1,228

3,524 587

953

10.7.2 Pipeline Transportation Costs 

In the IPM natural gas module, the natural gas moves over the pipeline network at variable cost. 

The variable cost as a function pipeline throughput (or pipeline discount curve) is used to 

determine transportation basis3

 (i.e., the market value of capacity) for each period in the forecast 

for each pipeline link. The 4-point pipeline discount curves in the IPM natural gas module are 

simplified forms of the more robust continuous discount curves from the GMM pipeline module. 

The GMM pipeline discount curves have been derived in the course of extensive work to calibrate 

the model to actual history. The curves have been fit to basis differentials observed from actual 

gas prices and to annual load factors from pipeline electronic bulletin boards via Lippman 

Consulting, Inc. 

The GMM continuous discount curves are converted to 4-point linear curves for the IPM natural 

gas module capturing deflection points in the GMM discount curves. Figure 10-17 depicts the 

base year 2011 discount curve for the pipeline corridor connecting nodes (61) North Louisiana 

Hub and (18) Tennessee/Kentucky. Cost growth factors shown in Figure 10-18 are applied to the 

pipeline discount curves to reflect cost increase over time. The cost is assumed to grow at an 

average rate of 0.5 percent per year. 

 

3

 See footnote #1 above for a definition of “basis.” 
10-29 

Figure 10-17 Example Pipeline Discount Curve 

N LA Hub (61) to TN/KY (18)

0.00

0.20

0.40

0.60

0.80

1.00

0 20 40 60 80 100

Pipeline Utilization (%)

Variable Cost (2007 $/MMBtu)

Figure 10-18 Pipeline Cost Growth Factor 

1.00

1.05

1.10

1.15

1.20

1.25

1.30

2010 2020 2030 2040 2050 2060

10.7.3 Pipeline Capacity Expansion Logic 

Base year pipeline capacity, derived from GMM, includes existing capacities and planned 

capacities that are expected to be operational from the beginning of 2011. The IPM natural gas 

module has the capability to endogenously expand the pipeline capacity. The decision of whether 

to expand pipeline capacity is controlled by two constraints, which stipulate minimum and 

maximum capacity additions and by the levelized capital cost of expanding pipeline capacity in the 

specific corridor and year. The minimum capacity addition constraint forces the model to add 

capacity in a specified corridor and year. The maximum capacity constraint is the upper bound on 

capacity additions in a specified corridor and year. For most pipeline corridors there is no 

minimum or maximum capacity requirement, and so they are assigned a value of zero as their 

minimum capacity addition requirement and infinity4

 as their maximum capacity addition 

requirement. Where this occurs, the pipeline expansion is only controlled by the pipeline capital 

cost. 

 

4

In the model this is achieved by assigning a large number, e.g., 100 Bcfd, for every year where 

there is no constraint on maximum capacity. 
10-30 

The model is allowed to add capacity to a pipeline corridor within the minimum and maximum 

capacity addition constraints if the cost of the pipeline expansion contributes to the optimal 

solution, i.e., minimizes the overall costs to the power sector, including the capital cost for pipeline 

capacity expansion, less their revenues. The model takes into account all possible 

options/projects including capacity additions for pipeline corridors in any year that do not violate 

the constraints and selects the combination of options/projects that provide the minimum objective 

function. In this way, pipeline corridor expansion projects will compete with each other and even 

with other projects such as LNG regasification capacity expansions, storage expansions, etc. 

For EPA Base Case v.4.10, pipeline corridors connecting North Alaska (node 89) and Mackenzie 

Delta (node 86) to North British Columbia (node 72) have the minimum and maximum capacity 

addition constraints. Based on diagnostic run analysis discussed in Section 3, the Mackenzie 

Delta pipeline project is not made available throughout the projection. Both capacity addition 

constraints for Mackenzie delta are set to zero. Based on the same analysis, the Alaska pipeline 

corridors (connecting nodes 89, 88, 87, and 72) are set to come online from 2035. The minimum 

capacity constraint is set to zero throughout the projection. The maximum capacity constraint is 

initially set to zero to restrict pipeline builds and then set to infinity from 2035. 

Expansions in other pipeline corridors are not restricted. The model is allowed to build capacity to 

any pipeline corridors at any time as long as it contributes to minimization of the objective function. 

 There is no reason for restricting the upper bound for capacity expansion since the IPM/Gas 

model was designed to be used as a long-term policy tool rather than a pipeline analysis tool. 

Having no restriction to the minimum capacity expansion, however, is a limitation of the model as 

it may lead to unrealistic capacity expansions especially for large pipeline projects such as Alaska 

and Mackenzie Delta. Without restricting the starting dates and the capacities, the model may 

build unrealistically low incremental capacities throughout the projection. This was the reason for 

conducting the diagnostic run for Alaska and Mackenzie Delta projects. Theoretically, it is 

possible to add capability in the model to make decisions on minimum incremental pipeline 

capacity expansions. However, it requires adding a lot more constraints to the LP which may 

result in prohibitively large model. The workaround for ensuring reasonable capacity expansion 

results is to perform diagnostic runs such as that for Alaska and Mackenzie Delta. 

The base year 2011 levelized pipeline capital cost (in real 2007 dollars per MMBtu/Day of pipeline 

capacity addition) is specified for each of the 343 pipeline links. The cost growth factors shown in 

Figure 10-18 are applied to derive the cost increase over time. The average levelized capital cost 

for pipeline capacity expansion for 2011 is $154 per MMBtu/Day. The expected levelized capital 

cost for North Alaska pipeline for 2035 is $305 per MMBtu/Day. 

10.8 Gas Storage 

The IPM natural gas module has 108 underground storage facilities that are linked to 48 nodes. 

The underground storage is grouped into three categories based on storage “Days Service.”5

• “20-Day” high deliverability storage – 35 storage facilities 

• “80-Day” depleted/aquifer reservoirs – 38 storage facilities 

• “Over 80 Days” depleted/aquifer reservoirs – 35 storage facilities 

The model also includes existing and potential LNG peak shaving storage facilities. The existing 

facilities are linked to 24 nodes with allocations based on historical capacity data. There are 48 

other nodes that are linked to LNG peakshaving storage. These facilities do not currently have 

capacity but are included in the storage database for the purpose of future expansion. The map of 

storage facility locations is shown in Figure 10-6 and the list of storage facility nodes is shown in 

Table 10-8. 

 

5

 See footnote #5 above for a definition of “Days Service.” 
10-31 

In Table 10-8 an X in columns 2 (“20-Day”), 3 (“80-Day”), or 4 (“Over 80-Days”) represents an 

underground storage facility. There are 108 such X’s which correspond to the 108 underground 

storage facilities noted in the previous paragraph. These 108 X’s appear in 48 rows, which 

represent the linked nodes noted in the previous paragraph. The identities of these nodes are 

found in column 1 (“Node”). Similarly, 24 X’s in columns 5 (“Existing”) represent the 24 existing 

LNG peakshaving facilities and 48 X’s in column 6 (“Potential”) represent the 48 prospective LNG 

storage facilities. 

Table 10-8 List of Storage Nodes 

Underground Storage 

Facility 

LNG Peakshaving 

Facility 

Node 

20-

Day 

80-

Day 

Over 

80 

Days 

Existing Potential

(1) New England X 

(3) Quebec X X X 

(4) New York City X 

(5) Niagara X X X X 

(6) Leidy X X X X 

(8) Georgia X 

(10) South Florida X 

(11) East Ohio X X X X 

(12) Maumee/Defiance X 

(13) Lebanon X 

(14) Indiana X X X 

(15) South Illinois X X X X 

(16) North Illinois X X X X 

(17) Southeast Michigan X X X 

(18) Tennessee/Kentucky X X X X 

(19) MD/DC/Northern VA X 

(20) Wisconsin X 

(21) Northern Missouri X 

(22) Minnesota X X 

(23) Crystal Falls X 

(24) Ventura X X X 

(26) Nebraska X X 

(28) Kansas X X X X 

(29) East Colorado X X X X 

(30) Opal X X X 

(31) Cheyenne X X X 

(32) San Juan Basin X 

(33) EPNG/TW X 

(34) North Wyoming X 

(35) South Nevada X 

(36) SOCAL Area X X X 

(38) PGE Area X X X 

(41) Montana/North Dakota X X X 

(45) Pacific Northwest X X X 
10-32 

Underground Storage 

Facility 

LNG Peakshaving 

Facility 

Node 

20-

Day 

80-

Day 

Over 

80 

Days 

Existing Potential 

(46) NPC/PGT Hub X 

(47) North Nevada X 

(48) Idaho X 

(54) North Alabama X X X X 

(56) North Mississippi X X X 

(58) Eastern Louisiana Hub X X X 

(60) Henry Hub X X X X 

(61) North Louisiana Hub X X X 

(63) Southwest Texas X X X 

(64) Dallas/Ft Worth X X X X 

(65) E. TX (Katy) X X X X 

(66) S. TX X 

(68) NW TX X 

(72) North British Columbia X 

(73) South British Columbia X X 

(74) Caroline X X X X 

(76) Saskatchewan X X X X 

(77) Manitoba X 

(78) Dawn X X X X 

(79) Philadelphia X 

(80) West Virginia X X X X 

(81) Eastern Canada Demand X 

(83) Wind River Basin X 

(92) Southwest VA X X X 

(93) Southeast VA X 

(94) North Carolina X 

(95) South Carolina X 

(96) North Florida X 

(97) Arizona X X X 

(98) Southwest Michigan X X X X 

(99) Northern Michigan X X X X 

(103) SDG&E Demand X 

(104) Eastern New York X 

(105) New Jersey X 

(106) Toronto X 

(107) Carthage X X X 

(108) Southwest Oklahoma X X 

(109) Northeast Oklahoma X X X 

(110) Southeastern Oklahoma X X X 

(111) Northern Arkansas X X X 

(112) Southeast Missouri X X 

(113) Uinta/Piceance X X X 
10-33 

Underground Storage 

Facility 

LNG Peakshaving 

Facility 

Node 

20-

Day 

80-

Day 

Over 

80 

Days 

Existing Potential

(114) South MS/AL X X X 

10.8.1 Storage Capacity and Injection/Withdrawal Constraints 

Working gas capacity is initially allocated in the GMM to individual nodes based on historical data. 

 Since the base year in EPA Base Case using IPM v.4.10 gas module is 2011, a projection of 

natural gas storage capacity at the end of 2010 is needed as a starting point. The expected 

working gas capacity as of EOY 2010 by location and storage type is obtained from the GMM as 

are injection and withdrawals rates. These serve as inputs to the IPM gas module, which uses 

them to endogenously derive gas storage withdrawals, injections, storage expansions, and 

associated costs. To give a sense of the EOY 2010 GMM storage input assumption in the IPM 

gas module, Table 10-9 shows the total working gas capacity and the average daily injection and 

withdrawal rates as percentage of working gas capacity for the four types of storage. Note that 

these are aggregated values (i.e., totals and averages); the actual GMM EOY 2010 inputs to the 

IPM gas module vary by location and storage type. 

Table 10-9 Storage Capacity and Injection/Withdrawal Rates (EOY 2010) 

 Working Gas 

Capacity (Bcf) 

Average Daily 

Injection Rate 

(Percent of WG 

Capacity) 

Average Daily 

Withdrawal Rate 

(Percent of WG 

Capacity) 

Underground Storage 

20 Day 458 6.7 9.3 

80 Day 3,353 1.3 2.2 

Over 80 Days 944 0.5 0.9 

Total 4,755 

LNG Peakshaving Storage 84 0.5 12.5 

10.8.2 Variable Cost and Fuel Use 

In the IPM natural gas module, the natural gas is injected to storage or withdrawn from storage at 

variable cost. The base year 2011 variable cost or commodity6

 charge for underground storage 

facilities is assumed to be 1.54 cents/MMBtu and is the same for all underground storage nodes 

and types. The variable cost for LNG peakshaving facility is much higher at 36 cents/MMBtu as it 

includes variable costs for gas liquefaction (in gas injection process) and LNG regasification (in 

gas withdrawal process). The variable cost is assumed to be the same for all LNG peakshaving 

nodes. A storage cost growth factor shown in Figure 10-19 is applied to the injection/withdrawal 

cost to reflect cost increase over time. The cost is assumed to grow at an average rate of 0.5 

percent per year. 

 

6 Storage commodity (variable) charge is generally a charge per unit of gas injected and/or 

withdrawn from storage as per the rights and obligations pertaining to a gas storage lease. 

Analogous to commodity charges for gas pipeline service 
10-34 

Figure 10-19 Storage Cost Growth Factor 

1.00

1.05

1.10

1.15

1.20

1.25

1.30

2010 2020 2030 2040 2050 2060

Fuel use for injection and withdrawal for underground storage is 1% of the gas throughput. The 

withdrawal fuel use for the LNG peakshaving storage is also 1% but the injection fuel use is much 

higher at 11% of the injection gas as it includes fuel use for gas liquefaction. 

10.8.3 Storage Capacity Expansion Logic 

The endogenous modeling decision of whether to expand working gas storage capacity is 

controlled by two constraints, which stipulate minimum and maximum capacity additions for each 

storage facility and year, and by the levelized capital cost of the storage expansion. The two 

constraints are specified as input data for each storage facility and year. The minimum constraint 

forces the model to add working gas capacity to the specified facility and year and the maximum 

constraint is the cap for the expansion. Figure 10-20 shows projected maximum storage 

expansion constraints for the “80-day” category storage facility in supply area Katy, Texas. 

Figure 10-20 Example Maximum Storage Capacity Expansion 

Storage category: “80-day”

Supply area: Katy, Texas

0

10

20

30

40

50

60

2010 2020 2030 2040 2050 2060

Bcf

The model is allowed to add working gas capacity to a storage facility within the two constraints if 

the cost of storage expansion contributes to the optimal solution, i.e., minimizes the overall costs 

to the power sector, including the capital cost for working gas capacity expansion less their 

revenues. The model takes into account all possible options/projects including working gas 

capacity additions for storage facilities in any year that do not violate the constraints and selects 

the combination of options/projects that provide the minimum objective function value. In this way, 
10-35 

storage capacity expansion projects will compete with each other and even with other projects 

such as LNG regasification capacity expansions, pipeline expansions, etc. 

The base year 2011 levelized storage capital cost (in real 2007 dollars per MMBtu of storage 

capacity addition) is specified for each of the 180 storage facilities. Table 10-10 lists the average 

base year 2011 levelized storage capital cost for the four types of storage facility. Amongst the 

underground storage facilities the higher capital costs represent more storage cycles7

 that could 

be achieved in a year. On average, the capital costs for the “80-Day” and “20-Day” storage 

facilities are assumed to be 20 percent and 50 percent, respectively, higher than that of the “Over 

80 Days” storage facility. The levelized capital cost for LNG peakshaving storage is much higher 

due to higher capital cost for the liquefaction unit. The cost growth factors shown in Figure 10-19 

are applied to the capital cost to derive the cost increase over time. The capital cost is assumed 

to grow at an average rate of 0.5 percent per year. 

Table 10-10 Base Year 2011 Average Levelized Storage Capital Cost 

Storage Type 

Average Levelized 

Storage Capital Cost 

(2007$/MMBtu) 

Underground Storage 

20-Day 1.09 

80-Day 0.86 

Over 80 Days 0.72 

LNG Peakshaving Storage 5.13 

10.9 Fuel Prices 

10.9.1 Crude Oil and Natural Gas Liquids Prices 

Since a fraction of the hydrocarbons produced in the natural gas exploration and development 

process are crude oil and NGLs (see columns 2 and 3 in Table 10-5), revenues from crude oil and 

NGL production play a key role in determining the extent of exploration and development for 

natural gas. To take into account these revenues, crude oil and NGL price projections are 

provided as inputs to the IPM natural gas module and factored into the calculation of costs in the 

IPM objective function. 

The crude oil and NGL price projections used in the IPM natural gas module are shown in Figure 

10-21. These price projections were adapted from AEO 2009. No attempt was made to project 

prices beyond 2030 other than to assume that prices remain at their 2030 levels. The projected 

prices shown in Figure 10-21 are expressed in units of 2007$ per MMBtu. Using a crude oil Btu 

content of 5.8 MMBtu/Bbl, the projected crude oil prices in Figure 10-21 can be translated into the 

more familiar units of dollars per barrel (Bbl), in which case, prices in this figure are equivalent to 

$62/Bbl in 2011, $97/Bbl in 2015, $114/Bbl in 2020, and constant at $124/Bbl from 2030 (in real 

2007 dollars) onward. 

 

7

 One storage cycle is the theoretical time required to completely inject and withdraw the working 

gas quantity for any given underground gas storage facility or the turnover time for the working 

gas capacity rating of the facility. The cycle rate of any storage facility is usually expressed in 

cycles per year and is the number of times the working gas volumes can theoretically be turned 

over each storage year. The cycle rating for Porous Storage varies from 1 to 6 per year while that 

for Salt Cavern Storage are as high as 12 per year. 
10-36 

Figure 10-21 Crude Oil and NGL Prices 

0.00

5.00

10.00

15.00

20.00

25.00

2000 2010 2020 2030 2040 2050 2060

Prices (2007 $/MMBtu)

Crude Oil Natural Gas Liquids

10.9.2 Natural Gas Prices 

Node-level natural gas prices are outputs of the model and are obtained from the optimal solution 

of the combined IPM electric power sector and natural gas linear programming (LP) model. From 

a technical modeling standpoint, the node gas prices are what are called “shadow prices” or “dual 

variable values” associated with the node mass balance constraints at the optimal LP solution. 

10.10 Outputs and Proxy Natural Gas Supply Curves 

10.10.1 Outputs from the New IPM Natural Gas Module 

Previous EPA IPM base cases reported natural gas consumption (in TBtu), Henry Hub and 

delivered natural gas prices (in $/MMBtu). In addition to these reports, the new natural gas 

module in EPA Base Case v.4.10 is capable of reporting natural gas supply (in Tcf), disposition (in 

Tcf), prices (in $/MMBtu), production (in Tcf) by supply region, end-of-year reserves and annual 

reserve additions (in Tcf), imports and exports (in Tcf), consumption by end-use sector and 

census division (in Tcf), prices by census division (in $/MMBtu), and inter-regional pipeline flows 

and LNG imports (in Bcf). 

10.10.2 Proxy Natural Gas Supply Curves 

In previous EPA IPM base cases a set of gas supply curves was generated outside of IPM (most 

recently by ICF’s NANGAS (North American Natural Gas Analysis System) model) and then used 

in IPM as part of the base case input assumptions. (For a description of this approach see 

Appendix 8-2.9 “Technical Background Paper on the Development of Natural Gas Supply Curves 

for EPA Base Case 2004, v.2.1.9” in Standalone Documentation for EPA Base Case 2004 

(V.2.1.9) Using the Integrated Planning Model EPA 430-R-05-011, September 2005. It is 

available for viewing and downloading at www.epa.gov/airmarkets/progsregs/epaipm/docs/bc8appendix.pdf.) The incorporation of the new fully integrated natural gas module into 

IPM eliminates the use of explicit gas supply curves, replacing them with more dynamic and 

responsive representation of an integrated natural gas supply chain and the U.S. power sector. 

However, it is recognized that it would be useful to have a set of proxy natural gas supply curves 

from the new integrated approach that could be compared to the natural gas supply curves used 

in previous EPA Base Cases. The proxy curves would only represent a one-time snapshot of 

supply/price relations resulting from the new integrated approach, but at least it would provide a 

point of comparison with the natural gas supply curves used in previous EPA IPM base cases. 
10-37 

Table 10-11 contains the proxy supply curves for the electric power sector for 2015 and 2020. 

(These are years that would be directly comparable with supply curves from previous base cases.) 

 The curves were generated based on GMM supply elasticities and gas demand and price 

solutions from the IPM/Gas model. The supply elasticity is calculated from GMM for each of the 

IPM run years. The gas supply curve, for each IPM run year, is constructed by applying the 

supply elasticity around the price/quantity solution of gas consumption in the power sector from 

the IPM/Gas model (highlighted rows in 

Table 10-11) varying the price from $3/MMBtu to $15/MMBtu (in real 2007 dollar). The supply 

elasticity, in the same run year, is assumed to be constant within the price range. 

The proxy supply curves below specify annual price and volume relationships at the Henry Hub. 

For each listed step the price applies for all increments of supply greater than the value shown in 

the preceding step up to and including the supply level indicated in the current step. 

Table 10-11 Proxy Natural Gas Supply Curves for EPA Base Case v.4.10 

2015 2020 

Gas Price 

(2007$/MMBtu) 

Gas Supply to 

Electric Sector 

(TBtu) 

Gas Price 

(2007$/MMBtu) 

Gas Supply to 

Electric Sector 

(TBtu) 

3.00 4,385 3.00 5,688 

3.11 4,469 3.08 5,762 

3.23 4,552 3.16 5,836 

3.34 4,633 3.23 5,909 

3.45 4,713 3.31 5,981 

3.56 4,792 3.39 6,052 

3.68 4,870 3.47 6,123 

3.79 4,946 3.55 6,192 

3.90 5,022 3.63 6,261 

4.02 5,096 3.70 6,329 

4.13 5,169 3.78 6,397 

4.24 5,242 3.86 6,464 

4.36 5,313 3.94 6,530 

4.47 5,384 4.02 6,595 

4.58 5,453 4.09 6,660 

4.69 5,522 4.17 6,724 

4.81 5,590 4.25 6,788 

5.08 5,741 4.53 7,000 

5.34 5,887 4.82 7,205 

5.61 6,030 5.10 7,405 

5.88 6,171 5.38 7,601 

6.15 6,308 5.66 7,791 

6.42 6,442 5.95 7,977 

6.69 6,574 6.23 8,159 

6.95 6,703 6.51 8,337 

7.22 6,831 6.80 8,511 

7.49 6,956 7.08 8,682 

7.76 7,078 7.36 8,850 

8.03 7,199 7.64 9,014 

8.29 7,318 7.93 9,176 
10-38 

2015 2020 

Gas Price 

(2007$/MMBtu) 

Gas Supply to 

Electric Sector 

(TBtu) 

Gas Price 

(2007$/MMBtu) 

Gas Supply to 

Electric Sector 

(TBtu) 

8.56 7,435 8.21 9,335 

8.83 7,551 8.49 9,492 

9.10 7,665 8.78 9,646 

9.37 7,777 9.06 9,798 

9.64 7,888 9.34 9,947 

9.90 7,997 9.63 10,094 

10.17 8,105 9.91 10,240 

10.44 8,212 10.19 10,383 

10.71 8,317 10.47 10,524 

10.98 8,421 10.76 10,664 

11.25 8,524 11.04 10,802 

11.51 8,626 11.32 10,938 

11.78 8,726 11.61 11,073 

12.05 8,826 11.89 11,206 

12.32 8,924 12.17 11,337 

12.59 9,022 12.45 11,467 

12.85 9,118 12.74 11,596 

13.12 9,214 13.02 11,723 

13.39 9,308 13.30 11,849 

13.66 9,402 13.59 11,973 

13.93 9,495 13.87 12,097 

14.20 9,587 14.15 12,219 

14.46 9,678 14.43 12,340 

14.73 9,768 14.72 12,460 

15.00 9,859 15.00 12,581 

Glossary of Terms Used in this Section 

For ease of reference Table 10-12 assembles in one table terms that have been defined in 

footnotes throughout this chapter. 

Table 10-12 Glossary of Natural Gas Terms Used in Documentation 

Term Definition 

Arps-Roberts equation 

“Arps-Roberts equation” refers to the statistical model of petroleum 

discovery developed by J. J. Arps, and T. G. Roberts, T. G., in the 

1950’s. 

Associated gas 

Associated gas refers to natural gas that is produced in association 

with crude oil production, whereas non-associated gas is natural gas 

that is not in contact with significant quantities of crude oil in the 

reservoir. 

Basis 

In natural gas discussions “basis” refers to differences in the price of 

natural gas in two different geographical locations. In the marketplace 

“basis” typically means the difference between the NYMEX futures 

price at the Henry Hub and the cash price at other market points. In 

the modeling context “basis” means the difference in natural gas 

prices between any two nodes at the same instance in time. 
10-39 

Term Definition 

Decline curve 

A decline curve is a plot of the rate of gas production against time. 

Since the production rate decline is associated with pressure 

decreases from oil and gas production, the curve tends to smoothly 

decline from a high early production rate to lower later production 

rate. Exponential, harmonic, and hyperbolic equations are typically 

used to represent the decline curve. 

Depleted reservoir 

storage 

A gas or oil reservoir that is converted for gas storage operations. Its 

economically recoverable reserves have usually been nearly or 

completely produced prior to the conversion. 

Dry gas 

Natural gas is a combustible mixture of hydrocarbon gases. Although 

consisting primarily of methane, the composition of natural gas can 

vary widely to include propane, butane, ethane, and pentane. Natural 

gas is referred to as 'dry' when it is almost pure methane, having had 

most of the other commonly associated hydrocarbons removed. 

When other hydrocarbons are present, the natural gas is called 'wet'. 

Ethane rejection 

Ethane rejection occurs when the ethane component in the natural 

gas stream is not recovered in a gas processing plant but left in the 

marketable natural gas stream. Ethane rejection is deployed when 

the value of ethane is worth more in the gas stream than as an a 

separate commodity or as a component of natural gas liquids (NGL), 

which collectively refers to ethane, propane, normal butane, 

isobutane, and pentanes in processed and purified finished form. 

Information that characterizes ethane rejection by region can play a 

role in determining the production level and cost of natural gas by 

region. 

Firm and interruptible 

demand 

“Firm” refers to natural gas demand that is not subject to interruptions 

from the supplier, whereas “interruptible” refers to natural gas 

demand that is subject to curtailment or cessation by the supplier. 

High deliverability 

storage 

High deliverability storage is depleted reservoir storage facility or Salt 

Cavern storage whose design allows a relatively quick turnover of the 

working gas capacity. 

Lease and plant use 

Natural gas for “lease and plant use” refers to the gas used in well, 

field, and lease operations (such as gas used in drilling operations, 

heaters, dehydrators, and field compressors) and as fuel in gas 

processing plants. 

Liquefied Natural Gas 

(LNG) 

LNG is natural gas converted to liquid form by cooling it down to 

about -260° F. Known as liquefaction, the cooling process is 

performed in an “LNG train” (the liquefaction and purification facilities 

in LNG plants), which reduces the gas to 1/600th of its original 

volume. The volume reduction resulting from liquefaction makes it 

cost effective to transport the LNG over long distances, typically by 

specially designed, double-hulled ships known as LNG carriers. Once 

the carriers reach their import terminal destination, the LNG is 

transferred in liquid form to specially designed storage tanks. When 

needed for customers, the LNG is warmed back to a gaseous state in 

a regasification facility and transported to its final destination by 

pipelines. 

LNG peakshaving 

facility 

LNG peakshaving facilities supplement deliveries of natural gas 

during times of peak periods. LNG peak shaving facilities have a 

regasification unit attached, but may or may not have a liquefaction 

unit. Facilities without a liquefaction unit depend upon tank trucks to 

bring LNG from nearby sources. 
10-40 

Term Definition 

Load factor In the natural gas context “load factor” refers to the percentage of the 

pipeline capacity that is utilized at a given time. 

Natural gas liquid 

(NGL) 

Those hydrocarbons in natural gas that are separated from the gas 

as liquids in gas processing or cycling plants. Generally such liquids 

consist of propane and heavier hydrocarbons and are commonly 

referred to as lease condensate, natural gasoline, and liquefied 

petroleum gases. 

Play 

A “play” refers to a set of known or postulated natural gas (or oil) 

accumulations sharing similar geologic, geographic, and temporal 

properties, such as source rock, migration pathway, timing, trapping 

mechanism, and hydrocarbon type. 

Pool 

A “pool” is a subsurface accumulation of oil and other hydrocarbons. 

Pools are not necessarily big caverns. They can be small oil-filled 

pores. A “field” is an accumulation of hydrocarbons in the subsurface 

of sufficient size to be of economic interest. A field can consist of one 

or more pools. 

Proven (or proved) 

The term “proven” refers to the estimation of the quantities of natural 

gas resources that analysis of geological and engineering data 

demonstrate with reasonable certainty to be recoverable in future 

years from known reservoirs under existing economic and operating 

conditions. Among the factors considered are drilling results, 

production, and historical trends. Proven reserves are the most 

certain portion of the resource base. 

RACC price 

Refiner Acquisition Cost of Crude Oil (RACC) is a term commonly use 

in discussing crude oil. It is the cost of crude oil to the refiner, 

including transportation and fees. The composite cost is the weighted 

average of domestic and imported crude oil costs. 

Raw gas 

Raw gas production refers to the volumes of natural gas extracted 

from underground sources, whereas net gas production refers to the 

volume of purified, marketable natural gas leaving the natural gas 

processing plant. 

Reserves-toproduction (R/P) ratio 

Reserves-to-production ratio is the remaining amount of reserves, 

expressed in years, to be produced with a current annual production 

rate. 

Resource and 

reserves 

When referring to natural gas a distinction is made between 

“resources” and “reserves.” “Resources” are concentrations of natural 

gas that are or may become of potential economic interest. 

“Reserves” are that part of the natural gas resource that has been 

fully evaluated and determined to be commercially viable to produce. 

Resource appreciation 

Resource appreciation represents growth in ultimate resource 

estimates attributed to success in extracting resource from known 

plays such as natural gas from shales, coal seams, offshore 

deepwater, and gas hydrates that are not included in the resource 

base estimates. 

Storage "Days 

Service" 

Storage “Days Service” refers to the number of days required to 

completely withdraw the maximum working gas inventory associated 

with an underground storage facility. 

Storage commodity 

charge 

Storage commodity (variable) charge is generally a charge per unit of 

gas injected and/or withdrawn from storage as per the rights and 

obligations pertaining to a gas storage lease. Analogous to 

commodity charges for gas pipeline service 
10-41 

Term Definition 

Storage cycle 

One storage cycle is the theoretical time required to completely inject 

and withdraw the working gas quantity for any given underground gas 

storage facility or the turnover time for the working gas capacity rating 

of the facility. The cycle rate of any storage facility is usually 

expressed in cycles per year and is the number of times the working 

gas volumes can theoretically be turned over each storage year. The 

cycle rating for Porous Storage varies from 1 to 6 per year while that 

for Salt Cavern Storage are as high as 12 per year. 

Unconventional gas 

Unconventional gas refers to natural gas found in geological 

environments that differ from conventional hydrocarbon traps. It 

includes: (a) “tight gas,” i.e., natural gas found in relatively 

impermeable (very low porosity and permeability) sandstone and 

carbonate rocks; (b) “shale gas,” i.e., natural gas in the joints, 

fractures or the matrix of shales, the most prevalent low permeability 

low porosity sedimentary rock on earth; and (c) “coal bed methane,” 

which refers to methane (the key component of natural gas) found in 

coal seams, where it was generated during coal formation and 

contained in the microstructure of coal. Unconventional natural gas is 

distinguished from conventional gas which is extracted using 

traditional methods, typically from a well drilled into a geological 

formation exploiting natural subsurface pressure or artificial lifting to 

bring the gas and associated hydrocarbons to the wellhead at the 

surface. 

Underground storage 

The underground storage of natural gas in a porous and permeable 

rock formation topped by an impermeable cap rock, the pore space of 

which was originally filled with water. 

Wet gas 

A mixture of hydrocarbon compounds and small quantities of various 

nonhydrocarbons existing in the gaseous phase or in solution with 

crude oil in porous rock formations at reservoir conditions. The 

principal hydrocarbons normally contained in the mixture are 

methane, ethane, propane, butane, and pentane. Typical 

nonhydrocarbon gases that may be present in reservoir natural gas 

are water vapor, carbon dioxide, hydrogen sulfide, nitrogen and trace 

amounts of helium. 

Working gas 

The term “working gas” refers to natural gas that has been injected 

into an underground storage facility and stored therein temporarily 

with the intention of withdrawing it. It is distinguished from “base (or 

cushion) gas” which refers to the volume of gas that remains 

permanently in the storage reservoir in order to maintain adequate 

pressure and deliverability rates throughout the withdrawal season. 
Appendix 10-1.1 

Appendix 10-1 EPA Base Case v.4.10 with AEO Gas Resource Assumptions 

For purposes of comparison a variant of EPA Base Case v.4.10 was prepared with natural gas 

resource assumptions that were set to approximate those in the Energy Information 

Administration’s Annual Energy Outlook 2010. 

To set up this case, EPA asked ICF International, who had developed the natural gas module for 

EPA Base Case v.4.10, to determine how best to represent the AEO 2010 resource assumptions 

in IPM in view of structural differences between the two models. It should be noted that the only 

change between the original EPA base case and this variant are the natural gas resource 

assumptions. The base year proved reserves assumptions were not changed.1

 The following is a 

summary of the findings of ICF’s comparison and the approach that was implemented in setting 

up the AEO 2010 gas resource base case variant. 

ICF’s analysis of the AEO 2010 natural gas resource assumptions was based on the AEO 2010 

assumptions document.2

 ICF found that the gas resource base in AEO 2010 is defined as 

technically recoverable resources (as of beginning of year 2008) without reference to economic 

profitability, whereas the gas resource base in IPM is defined as the economically recoverable 

resource (as of end of year 2010) which represents that portion of the original-gas-in-place that is 

economic to develop at wellhead prices3

 below $14/MMBtu (in 2007 dollars) given current 

technologies and industry costs. 

ICF made adjustments to convert the AEO technically recoverable gas resources so that it could 

be used in the IPM Natural Gas Module. Their analysis found that the economically recoverable 

gas resource as defined in the IPM natural gas module was about 15% to 30% lower than the 

technically recoverable gas resource without economic consideration as used in AEO 2010. 

However, since the resource base for conventional, tight gas, and coalbed methane gas in the 

EPA base case was already 15% to 30% lower than the gas resources in the AEO 2010, ICF did 

not change the gas resource base for these resource types. 

On the other hand, ICF found that the shale gas resource in the EPA base case was much higher 

than in AEO 2010. To quantify the difference in shale gas resource, ICF first calculated that a 

20% reduction was needed in order both to translate the AEO technically recoverable shale gas 

resource into the equivalent economically recoverable resource used in IPM and to account for 

resource development between 2008 (base year for the AEO gas resources) and 2011 (base year 

for the IPM gas resource). Once the two resource bases were expressed so they could be 

compared, ICF found that the AEO shale gas resource assumption was about 31% of that used in 

the EPA base case. 

To implement this in the alternative base case, the total shale gas resource was set so it would be 

31% of the shale gas resource base assumed in EPA Base Case v.4.10. No attempt was made 

 

1

 The base year proved reserves assumptions are described in section 10.3 of this chapter under 

the header “Use of the HSM resource and reserves data in EPA Base Case using IPM v.4.10 

Natural Gas Module.” 

2 Energy Information Administration, Assumptions to the Annual Energy Outlook 2010: Natural 

Gas Transmission and Distribution Module, DOE/EIA-0554(2010), April 9, 2010. 

www.eia.doe.gov/oiaf/aeo/assumption/nat_gas.html

3 The wellhead price is the price required to cover total wellhead resource costs including capital 

expenditures, cost of capital, operating costs, royalties, severance taxes and income taxes. 

Wellhead economics are based upon standard discounted cash flow analysis. Costs include 

drilling and completion, operating, geological and geophysical (G&G), and lease costs. 

Completion costs include hydraulic fracturing, and such costs are based upon cost per fracture 

stage and number of fracture stages. Drilling costs, well lateral length, number of fracture stages, 

and cost per fracture stage are based on analysis and data from industry. 
Appendix 10-1.2 

to adjust shale gas resources by supply region so that the regional shale gas resources in AEO 

2010 and EPA’s AEO Supply Case would match. 

Table 10-1.1 shows the resulting shale gas resource base assumptions for AEO 2010, EPA Base 

Case v.4.10, and the AEO Supply Case of the EPA base case. The location of the U.S. natural 

gas supply regions listed in Table 10-1.1 are shown in the map in Figure 10-1.1. 

Table 10-1.1 Shale Gas Resource Base in Tcf (does not include proved reserves) 

AEO 2010(a)

(as of BOY 2008)

EPA Base Case(b)

(as of EOY 2010)

AEO Supply Case(b)

(as of EOY 2010)

U.S. 346.5 917.2 284.9

Northeast 73.2 254.4 79.0

Gulf Coast 90.3 431.6 134.1

Midcontinent 51.0 132.9 41.3

Southwest 59.5 60.3 18.7

Rocky Mountain 21.6 37.7 11.7

West Coast 50.9 0.3 0.1

Canada NA 511.1 158.7

(a) Technically recoverable resources without reference to economic profitability.

(b) Economically recoverable resources under wellhead gas price of $14/MMBtu (2007 dollars).

Figure 10-1.1 U.S. Supply Region 
11-1 

11 Other Fuels and Fuel Emission Factor Assumptions 

Besides coal (chapter 9) and natural gas (chapter 10) EPA Base Case v.4.10 also includes 

assumptions for residual fuel oil, biomass, nuclear fuels, and various waste fuels. The 

assumptions described in this chapter pertain to fuel characteristics, fuel market structures, and 

fuel prices for these fuels. As seen in the previous chapter, there is an endogenous resource 

costing model for natural gas built into EPA Base Case v.4.10. Coal is represented via an 

elaborate set of supply curves and a detailed representation of the associated coal transport 

network. Together they are designed to capture the intricacies of the resource base and market 

for this fuel which currently powers about 45% of U.S. electric generating capacity. As with coal, 

the price and quantity of biomass combusted is determined by balancing supply and demand 

using a set of geographically differentiated supply curves. In contrast, fuel oil and nuclear fuel 

prices are exogenously determined and entered into IPM during model set-up as constant price 

points which apply to all levels of supply. Generally, the waste fuels are also modeled using price 

points. In this chapter each of the remaining fuels is treated in turn. The chapter concludes with 

a discussion of the emission factors for all the fuels represented in EPA Base Case v.4.10. 

11.1 Fuel Oil 

Two petroleum derived fuels are included in EPA Base Case v.4.10: As its name implies distillate 

fuel oil is distilled from crude oil, whereas residual fuel oil is left as a residue of the distillation 

process. The fuel oil prices in EPA Base Case v.4.10 are from AEO 2010 and are shown in Table 

11-1. They are regionally differentiated according to the NEMS (National Energy Modeling 

System) regions used in AEO 2010 and are mapped to their corresponding IPM regions for use in 

EPA Base Case v.4.10.

Table 11-1 Fuel Oil Prices by NEMS Region in EPA Base Case v.4.10 

Residual Fuel Oil Prices (2007$/MMBtu) 

NEMS Region 2012 2015 2020 2030 2040 - 2050 

ECAR 16.40 30.04 41.07 54.20 63.77 

ERCOT 20.00 21.96 23.40 25.42 26.91 

MAAC 9.85 11.84 13.63 15.65 17.05 

MAIN 91.20 104.84 115.87 129.00 138.57 

MAPP 17.14 8.61 8.61 8.61 16.19 

NY 9.63 11.73 13.59 15.61 16.99 

NE 9.80 11.91 13.77 15.80 17.19 

FL 10.50 12.48 13.92 15.95 17.44 

SERC 10.96 12.83 14.28 16.32 17.81 

SPP 17.36 21.73 23.15 25.14 26.60 

NWP 19.56 21.58 23.06 25.00 26.50 

RA 19.68 21.67 23.14 25.09 26.59 

CA 21.63 23.83 25.10 27.24 28.56 

Distillate Fuel Oil Prices (2007$/MMBtu) 

NEMS Region 2012 2015 2020 2030 2040 - 2050 

ECAR 14.8 16.96 19.87 22.25 24.19 

ERCOT 14.75 16.86 19.71 22.09 24.03 

MAAC 14.82 16.99 19.9 22.3 24.25 

MAIN 14.86 17.04 19.94 22.31 24.24 

MAPP 14.88 17.05 19.95 22.32 24.25 

NY 14.87 17.05 19.98 22.38 24.33 

NE 15.07 17.23 20.13 22.53 24.49 
11-2 

Distillate Fuel Oil Prices (2007$/MMBtu) 

NEMS Region 2012 2015 2020 2030 2040 - 2050 

FL 14.67 16.78 19.65 22.04 23.99 

SERC 14.65 16.8 19.69 22.08 24.03 

SPP 14.8 16.93 19.8 22.18 24.12 

NWP 15.84 17.85 20.29 22.84 24.74 

RA 15.59 17.73 20.6 23.02 24.97 

CA 16.21 17.95 19.99 22.66 24.53 

11.2 Biomass 

Biomass is offered as a fuel for existing dedicated biomass power plants and potential (new) 

biomass direct fired boilers (built by the model prior to 2020) and to potential (new) biomass 

gasification combined cycle units built by the model from 2020 forward. (See chapter 4 for a 

presentation of the cost and performance characteristics for these two technologies.) In addition 

to its use as the prime mover fuel for these plants, it is also offered for co-firing to all coal fired 

power plants. (See section 5.3 for a discussion of the representation of biomass co-firing in EPA 

Base Case v.4.10.) As noted in the discussion in chapter 5, the combustion of biomass fuel is 

considered to have a net zero impact on atmospheric carbon dioxide levels since the emissions 

released are equivalent in carbon content to the carbon absorbed during fuel crop growth1

.

EPA Base Case v.4.10 uses biomass supply curves based on those in AEO 2010. There are 

fourteen regional biomass fuel supply curves, one for each of the 14 NEMS coal demand regions 

represented in AEO 2010. Plants demand biomass from the supply curve corresponding to the 

NEMS coal demand region in which they are located. No inter-regional trading of biomass is 

allowed. Each biomass supply curve depicts the price-quantity relationship for biomass and varies 

over time. There is a separate curve for each model run year. The supply component of the curve 

represents the aggregate supply in a region of four types of biomass fuels: forestry residue, 

agricultural residue, urban wood waste, and mill residue and energy crops. The price component 

of the curve includes transportation cost and represents the delivered fuel cost at the plant gate. 

The original AEO 2010 supply curves contained 48 price steps, and are modeled as-is in EPA 

Base Case v.4.10. Appendix 11-1 contains the 2012-2035 biomass supply curves. 

The supply curves in Appendix 11-1 represent the biomass available to both the electric and nonelectric sectors. In any given region at any point in time the power sector demand from IPM has 

to be combined with the non-electric sector demand for biomass to obtain the price faced by the 

power sector. The non-electric sector demand distribution is by NEMS coal demand region based 

on AEO 2010. The total national projection from AEO 2010 was scaled up to the projections 

obtained from the Forest and Agricultural Sector Optimization Model (FASOM), a dynamic, 

nonlinear programming model of the U.S. forest and agricultural sectors developed for EPA by 

Bruce A. McCarl, Professor of Agricultural Economics at Texas A&M University. Table 11-2 shows 

the non-electric sector demand by run year and NEMS region. 

Table 11-2 Non-Electric Biomass Demand by NEMS Region in EPA Base Case v.4.10 

Non-Electric Biomass Demand (TBtu) 

NEMS Coal Demand Region 2012 2015 2020 2030 2040 - 2050 

1 CT, MA, ME, NH, RI, and VT -- -- -- 17.1 15.7 

2 NY, PA, and NJ -- -- -- -- 0.0 

3 WV, MD, DC, DE, VA, NC, and SC 19.4 126.7 336.1 354.1 324.2 

4 GA and FL 12.7 80.3 201.7 202.4 185.3 

 

1

Hughes, E., Role of Renewables in Greenhouse Gas Reduction, Electric Power Research 

Institute (EPRI): November, 1998. Report TR-111883, p. 28. 
11-3 

Non-Electric Biomass Demand (TBtu) 

NEMS Coal Demand Region 2012 2015 2020 2030 2040 - 2050

5 OH -- -- -- -- 0.0 

6 IN, IL, MI, and WI -- -- -- -- 0.0 

7 KY and TN -- -- -- -- 0.0 

8 AL and MS -- -- -- -- 0.0 

9 MN, IA, ND, SD, NE, MO, and KS 131.8 184.3 63.8 48.0 43.9 

10 TX, LA, OK, and AR 0.9 0.3 0.1 0.1 0.1 

11 MT, WY, and ID 0.4 0.1 0.0 13.2 12.1 

12 CO, UT, and NV 0.3 0.1 0.0 11.8 10.8 

13 AZ and NM 0.3 0.1 0.0 9.0 8.2 

14 WA, OR, and CA 0.2 22.7 506.7 467.6 428.1 

Once the non-electric demand for biomass is factored in, biomass prices in EPA Base Case 

v.4.10 are derived endogenously based on the aggregate power sector demand for biomass in 

each region. The results are unique market-clearing prices for each supply region. All plants 

using biomass from that supply region face the same market-clearing price. 

11.3 Nuclear Fuel 

The AEO 2009 price assumption for nuclear fuel is used as the nuclear fuel price assumption for 

2012-2050 in EPA Base Case v.4.10. The 2012, 2015, 2020, and 2030 prices are 0.71, 0.75, 

0.76, and 0.84 lbs/MMBtu, respectively. 

11.4 Waste Fuels 

Among the “modeled fuels” shown for existing generating units in the NEEDS, v.4.10 (the 

database which serves as the source of data on existing units for EPA Base Case v.4.10) are a 

number of waste fuels, including waste coal, petroleum coke, fossil waste, non-fossil waste, tires, 

and municipal solid waste (MSW). Table 11-3 describes these fuels, shows their extent of their 

representation in NEEDS, and then indicates the assumptions adopted in EPA Base Case v.4.10 

to represent their use and pricing. It should be noted that these fuels are only provided to existing 

and planned committed units in EPA Base Case v.4.10. Potential new generating units that the 

model “builds” are not given the option to burn these fuels. In IPM reported output, tires, MSW, 

and non-fossil waste are all included under existing non-fossil other, while waste coal and 

petroleum coke is included under coal. 
11-4 

Table 11-3 Waste Fuels in NEEDS, v.4.10 and EPA Base Case v.4.10 

Modeled Supply and Cost 

Fuel in 

NEEDS 

Number 

of Units 

in NEEDS 

Total 

Capacity 

in NEEDS 

Description Modeled 

By 

Assumed 

Price 

Waste 

Coal 3 2,205 MW 

“Usable material that is a 

byproduct of previous coal 

processing operations. Waste coal 

is usually composed of mixed 

coal, soil, and rock (mine waste). 

Most waste coal is burned as-is in 

unconventional fluidized-bed 

combustors. For some uses, 

waste coal may be partially 

cleaned by removing some 

extraneous noncombustible 

constituents. Examples of waste 

coal include fine coal, coal 

obtained from a refuse bank or 

slurry dam, anthracite culm, 

bituminous gob, and lignite 

waste.” 

http://www.eia.doe.gov/glossary/in

dex.cfm?id=W 

Supply 

Curve 

Based 

on AEO 

2010 

AEO 2010

Petroleum 

Coke 29 3,442 MW 

A residual product, high in carbon 

content and low in hydrogen, from 

the cracking process used in 

crude oil refining 

Price 

Point 

$42.24/ 

MMBtu 

Fossil 

Waste 28 982 MW 

Waste products of petroleum or 

natural gas including blast furnace 

and coke oven gas. They do not 

include petroleum coke or waste 

coal which are specified 

separately among the “Modeled 

Fuels” 

Price 

Point 0 

Non-Fossil 

Waste 66 874 MW 

Non-fossil waste products that do 

not themselves qualify as 

biomass. These include waste 

products of liquid and gaseous 

renewable fuels (e.g., red and 

black liquor from pulping 

processes, digester gases from 

waste water treatment). They do 

not include urban wood waste 

which is included in biomass. 

Price 

Point 0 

Tires 3 44 MW Discarded vehicle tires. Price 

Point 0 

Municipal 

Solid 

Waste 

183 2,197 MW 

“Residential solid waste and some 

nonhazardous commercial, 

institutional, and industrial 

wastes.” 

http://www.eia.doe.gov/glossary/in

dex.cfm 

Price 

Point 0 
11-5 

11.5 Fuel Emission Factors 

Table 11-4 brings together all the fuel emission factor assumptions as implemented in EPA Base 

Case v.4.10. For sulfur dioxide and mercury in coal, where emission factors vary widely based on 

the rank, grade, and supply seam source of the coal, cross references are given to tables that 

provide more detailed treatment of the topic. Nitrogen oxides (NOX) are not included in Table 11-4 

because NOX levels are not primarily fuel based but are a factor of the combustion process. 

Table 11-4 Fuel Emission Factor Assumptions in EPA Base Case v.4.10 

Fuel Type Heat Content 

(Btu/lb)1

Carbon 

Dioxide 

(lbs/MMBtu)2

Sulfur 

Dioxide 

(lbs/MMBtu)3

Mercury 

(lbs/TBtu)3

Coal 

Bituminous >10,260 - 13,000 205.2 - 206.6 0.67 - 6.43 1.82 - 34.71 Subbituminous > 7,500 - 10,260 212.7 - 213.1 0.58 - 1.41 4.24 - 6.44 

 Lignite < 7,500 213.5 - 217.0 1.46 - 3.91 7.51 - 14.88 

Natural Gas -- 117.08 0 0.00014 

Fuel Oil 

 Distillate -- 161.4 0 0.48 

 Residual -- 161.4 - 173.9 0.3 - 2.65 0.48 

Biomass -- 0 0.08 0.57 

Waste Fuels 

 Waste Coal 6,175 205.7 5.36 63.9 

 Petroleum Coke 14,150 225.1 7.27 23.18 

 Fossil Waste -- 321.1 0.08 0 

 Non-Fossil Waste -- 0 0 0 

 Tires -- 189.5 1.65 3.58 

 Municipal Solid Waste -- 91.9 0.35 71.85 

Notes:

1

Distillate and Residual Oils, Biomass, Fossil Waste, Non-Fossil Waste, Tires, and Municipal Solid 

Waste (MSW) are priced at a $/MMBtu basis and hence heat content is not required for modeling. 

2

Also see Table 9-9 

3

Also see Table 9-6, and Table 9-7 

Biomass fuel is considered to have a net zero impact on atmospheric carbon dioxide levels since 

the emissions released are equivalent in carbon content to the carbon absorbed during fuel crop 

growth. (See, for example, Hughes, E., Role of Renewables in Greenhouse Gas Reduction, 

Electric Power Research Institute (EPRI): November, 1998. Report TR-111883, p. 28.) 

"

Biomass Co-firing," Chapter 2 in Renewable Energy Technology Characterizations, U.S. 

Department of Energy and Electric Power Research Institute (EPRI), 1997. 

Analysis of Emissions Reduction Option for the Electric Power Industry, Office of Air and Radiation, 

U.S. Environmental Protection Agency, March 1999. 
Appendix 11-1 

Appendix 11-1 Biomass Supply Curves in EPA Base Case v.4.10 

This is a small excerpt of the data in Appendix 11-1. The complete data set in spreadsheet format 

can be downloaded via the link found at www.epa.gov/airmarkets/progsregs/epaipm/BaseCasev410.html 

Year Biomass Supply Region Step Name 

Cost of 

Production 

(2007$/MMBtu) 

Biomass 

Production 

(TBtu/Year) 

2012 AL, MS BM01 0.00 0 

2012 AL, MS BM02 1.83 21.28 

2012 AL, MS BM03 2.12 21.04 

2012 AL, MS BM04 2.39 19.44 

2012 AL, MS BM05 2.68 13.27 

2012 AL, MS BM06 2.97 10.35 

2012 AL, MS BM07 3.26 7.33 

2012 AL, MS BM08 3.54 78 

2012 AL, MS BM09 3.83 2.95 

2012 AL, MS BM010 4.11 1.22 

2012 AL, MS BM011 4.40 0.2 

2012 AL, MS BM012 4.68 0 

2012 AL, MS BM013 4.97 0 

2012 AL, MS BM014 5.26 0 

2012 AL, MS BM015 5.54 0 

2012 AL, MS BM016 5.82 0 

2012 AL, MS BM017 6.11 0 

2012 AL, MS BM018 6.40 0 

2012 AL, MS BM019 6.82 5 

2012 AL, MS BM020 7.24 5 

2012 AL, MS BM021 7.66 5 

2012 AL, MS BM022 8.07 5 

2012 AL, MS BM023 8.49 5 

2012 AL, MS BM024 8.91 5 

2012 AL, MS BM025 9.33 5 

2012 AL, MS BM026 9.76 5 

2012 AL, MS BM027 10.18 5 

2012 AL, MS BM028 10.60 5 

2012 AL, MS BM029 11.02 5 

2012 AL, MS BM030 11.44 5 

2012 AL, MS BM031 11.86 5 

2012 AL, MS BM032 12.28 5 

2012 AL, MS BM033 12.70 5 

2012 AL, MS BM034 13.12 5 

2012 AL, MS BM035 13.54 5 

2012 AL, MS BM036 13.97 5 

2012 AL, MS BM037 14.38 5 

2012 AL, MS BM038 14.80 5 

2012 AL, MS BM039 15.22 5 

2012 AL, MS BM040 15.64 5