U.S. Energy Information Administration Independent Statistics & Analysis www.eia.gov

AEO2020 First Coal Working Group Meeting

Coal and Uranium Analysis Team

April 9, 2019 | Washington, D.C.

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. 

DO NOT QUOTE OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE.
Agenda

• Introductions and overview of AEO2020 process

• Review of AEO2019 assumptions and projections

– Legislative and regulatory review

– Three key assumptions and three key industry trends

– Summary of results for coal capacity, generation, disposition, regions, labor, and exports

• Model updates and improvements for AEO2020 and beyond 

– Summary of modeling improvements for AEO2020 affecting the coal market

– Seaborne coal freight rate methodology improvements for AEO2020

– Coal transportation rate increase methodology options for AEO2020/1

– International coal supply curve estimation options for AEO2021

• Q&A opportunity at the end of each subsection 

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 2

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Overview of Annual Energy Outlook 2020 (AEO2020)

• AEO2020 will be a full release

– Flip-book published

– Core side cases will be run

• Reference

• High/Low Oil and Gas Resource Technology

• High/Low Oil Price

• High/Low Economic Growth

– Issues in Focus articles or related side cases will be published along with related side case 

results

• Assumptions and model documentation will be updated 

• Second working group session will take place in late summer

• Publication is scheduled for January 2020 (estimated)

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 3

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
What is the Reference case?

• The Reference case projection assumes trend improvement in known technologies along with a 

view of economic and demographic trends reflecting the current views of leading economic 

forecasters and demographers.

• The Reference case generally assumes that current laws and regulations affecting the energy 

sector, including sunset dates for laws that have them, are unchanged throughout the projection 

period.

• The potential impacts of proposed legislation, regulations, and standards are not included.

• EIA addresses the uncertainty inherent in energy projections by developing side sensitivity cases 

with different assumptions of macroeconomic growth, world oil prices, technological progress, and 

energy policies.

• Projections in the AEO should be interpreted with a clear understanding of the assumptions that 

inform them and the limitations inherent in any modeling effort.

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 4

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
AEO2019 sensitivity cases examine impacts of alternative 

market assumptions

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 5

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Selected Sensitivity Cases Description

Reference Assumes trend improvement in known technologies and expects current economic 

and demographic trends to continue

High Oil and Natural Gas Resource 

and Technology (HRT)

Applies lower oil and natural gas extraction costs and higher resource availability 

than in the Reference case, which allows for higher levels of oil and natural gas 

production at lower delivered prices

Low Oil and Natural Gas Resource 

and Technology (LRT)

Applies higher oil and natural gas extraction costs and lower resource availability 

than in the Reference case, which results in lower levels of oil and natural gas 

production at higher delivered prices
Legislation and regulations: AEO2019 

assumptions and outlook for AEO2020

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 6

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Affordable Clean Energy (ACE) proposed rule

• EPA proposed the Affordable Clean Energy (ACE) rule in August 2018 to replace 

the Clean Power Plan (CPP), which:

– Revises EPA’s BSER (“best system of emission reduction”) finding for GHG emissions from existing 

power plants to include only heat-rate efficiency improvements 

– Gives states a list of “candidate technologies” that can be used to establish performance standards for 

use in state plans, rather than setting specific technology-based standards, 

– EIA is addressing ACE in the Electricity Markets Module (EMM) by offering existing coal units the 

choice to either upgrade to an HRI option identified in EIA’s CPP study or retire by 2025; this approach 

relies on the 2015 EIA study of heat rate improvement (HRI) potential and costs for existing coal units

• EPA’s (ACE) Rule was not final and not included in AEO2019 Reference case 

– Final rule expected in spring of 2019

– Will be included in AEO2020 if the rule is finalized timely in 2019

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 7

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
EPA’s New Source Performance Standards (NSPS)

• All AEO2019 cases include EPA’s New Source Performance Standards (NSPS) limiting CO2 

emissions from new plants

– The EPA released proposed revisions that would eliminate the Carbon Capture and Sequestration (CCS) requirement 

and specify CO2 emission rates of 2,000 lb CO2/MWh-gross for large units (super-critical), 1,900 lb for small units (subcritical), and 2,200 lb for new coal refuse-fired units; and it would change applicability of rules to modified units

– AEO2020 assumptions would be modified to reflect the timely issuance of a final rule in 2019

• All cases in the AEO2019 apply a 3% adder to the cost of capital for new coal 

– Includes units or upgrades to existing units without maximum sequestration options (90% removal) to account for risk of 

future tightening of CO2 emissions standards and other policies affecting coal use

– Will also be applied in AEO2020

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 8

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

NSPS CO2 emission standard Proposed Seeking comment on alternative range

lbs/CO2/mmBtu (gross energy output)

Large units (super-critical) 2,000 1,700 - 1,900

Small units (sub-critical) 1,900 1,800 - 2,000

New coal refuse-fired units 2,200 2,000 - 2,200

Source: U.S. EPA, EPA Proposal: NSPS for GHG Emissions from New, Modified, and Reconstructed EGUs; p. 146.
Mercury and Air Toxics Standards (MATS) and Cross State Air 

Pollution Rule (CSAPR)

• The Mercury and Air Toxics Standards (MATS) are included in all AEO2019 cases

– “EPA issued a proposed revised Supplemental Cost Finding for the Mercury and Air Toxics 

Standards, as well as the Clean Air Act required ‘risk and technology review.’...and proposes to 

determine that it is not ‘appropriate and necessary’ to regulate HAP emissions from power plants 

under Section 112 of the Clean Air Act. The emission standards and other requirements of the 

MATS rule, first promulgated in 2012, would remain in place, however, since EPA is not proposing 

to remove coal- and oil-fired power plants from the list of sources that are regulated under Section 

112 of the Act.” (quoted from EPA website; emphasis added).

– MATS will be included in all AEO2020 cases, accordingly, unless further guidance is issued to the 

contrary

• EPA’s Cross-State Air Pollution Rule (CSAPR) is included in all AEO2019 cases 

and will be maintained in all AEO2020 cases

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 9

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Other EPA regulations affecting coal generating units and effluent 

limitation guidelines 

• Other EPA regulations assume compliance is reflected in survey Form EIA860 filings as each plant takes action to comply

– Regional Haze compliance follows from State Implementation Plans due on July 31, 2021 

with implementation by 2028 (EPA announced it is revisiting the 2017 revision)

– EPA had projected minimal coal retirements from previously-finalized Coal Combustion 

Residuals, Cooling Water Intakes, and Effluent Limitation Guidelines

• EPA is promulgating Revised Effluent Limitation Guidelines 

– Deadlines for compliance postponed until November 1, 2020 while EPA promulgates a 

revised rule starting in August, 2017; draft rule anticipated by December, 2020

– Rulemaking is considering possible revisions to the Best Available Technology (BAT) effluent 

limitations and pretreatment standards for existing sources

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 10

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
EPA’s Coal Combustion Residual Regulations 

• The EPA is reviewing 2015 Coal Combustion Residual regulations 

– The EPA gave states flexibility to apply alternative standards to achieve compliance, and states 

are allowed until 2020 to begin closing or retrofitting unlined ponds violating groundwater 

standards

– EPA is addressing an August 2018 decision that required EPA to strengthen the 2015 rule

– Individual states, such as Virginia and North Carolina, are enacting legislation or ordering 

utilities to address coal ash in unlined pits, and EPA recently raised concerns regarding certain 

provisions in Missouri’s plan

– Environmental and other groups are stepping up legal actions as states act under their 

expanded authority from EPA and under the 2015 rule

– Modeling is difficult because the potential cost implications vary considerably by individual 

electric generating unit, and are incorporated into the AEO on as-revealed basis via reporting on 

survey Form EIA-860

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 11

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
EPA’s Waters of the U.S. (WOTUS) definition and coal excise taxes

• EPA proposed a revised definition of Waters of the U.S. (WOTUS) in December, 2018 that 

would generally scale back waterways covered under the Clean Water Act

– EPA and Army Corps of Engineers recently stopped opposing the delay in enforcing the previous 

definition finalized in 2015

– Assessing the impact for the coal industry is problematic because most economic analysis to 

date appears to be based on case studies or other, anecdotal or high-level assessment at this 

time

• Coal excise tax rates for the Black Lung Disability Trust Fund declined on January 1, 2019 

from $1.25 to $0.50 per ton for underground, and from $0.55 to $0.25 for surface-mined 

coal (not applicable to lignite coal and coal intended for export)

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 12

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Other actions affecting coal producers

• U.S. District Court of Montana ruled in February 2019 that the Office of Surface Mining 

and Reclamation (OSMRE) should have better accounted for the impacts of coal 

transportation, the non-climate-combustion effects, and the social cost of carbon when it 

issued an Environmental Assessment (EA) for the Spring Creek mine expansion

– The ruling allows OSMRE to correct the National Environmental Protection Act (NEPA) violations 

and update the EA and to determine if a full Environmental Impact Statement (EIS) is required to 

seek the Court’s approval

– The potential implications for federal coal leasing will depend on the final adjudication

• U.S. Department of Interior’s Royalty Policy Committee expressed no recommended 

changes for coal leasing at its Feb. 2018 meeting and continues to evaluate 

recommendations for determining fair market value for third-party transactions and the 

bonus bid payment schedule

• Office of Surface Mining’s Stream Protection Rule was nullified in 2017 and formal 

programmatic consultation reinitiated

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 13

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
State actions to control greenhouse gas emissions (1 of 2)

• Several states are actively considering or have already passed strict carbon emission policies

– For example, New Mexico enacted legislation in March,2019 calling for investor-owned utilities and rural electric 

cooperatives to procure at least half their electricity from renewable sources by 2030 and 80% by 2040, with a 100% 

carbon-free requirement taking effect in 2045 for utilities and 2050 for electric co-ops

– Hawaii and the District of Columbia have passed similar measures

– Other states are considering similar options with targets of 50% to 100% carbon-free electricity generation that may be 

included in the AEO2020 if the states take action in time for the AEO2020 development cycle, including: AZ, FL, IL, 

MD, ME, MN, NC, NV, WA, WI

• Existing California regulations are included in AEO2019

– AB 398 Global Warming Solutions Act requires statewide greenhouse gas emissions to return to the 1990 level by 

2020 and be 40% below the 1990 level by 2030

– Cap-and-trade program under AB 32

– SB-1368 prohibits California utilities from entering into long-term financial commitments for base load generation, 

unless in compliance with CO2 emissions performance standard of 1,100 lbs/MWh

– SB-100 clean energy standard calls for a 60% renewable generation requirement by 2030, as required under previous 

legislation, and for carbon-free electric generation by 2045

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 14

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
State actions to control greenhouse gas emissions (2 of 2)

• The Northeast’s Regional Greenhouse Gas Initiative (RGGI) program included in 

AEO2019

– New Jersey and Virginia recently opted in and may be included in AEO2020

• State-level Renewable Portfolio Standards (RPS) and Zero Emission Credit (ZEC) 

programs updated each AEO cycle

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 15

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Issues affecting western U.S. coal producers

• Oregon passed S.B. 1547 in 2016 that requires utilities to exit out-of-state coal 

contracts by 2030

– Potential implications for coal holdings by PacifiCorp, including Jim Bridger (WY; 2/3 owner), Hunter, 

Huntington, Dave Johnston, Naughton, Wyodak, Craig (partial owner), Colstrip (partial owner), and Hayden 

(partial owner)

– Wyoming passed Senate File 159 requiring utilities to make a good faith attempt to sell coal plants 

purchased under an agreement approved by the state’s commission, and ratepayers in Wyoming would 

assume the costs of buying the coal plant in operation

• U.S. Pacific-Northwest coal terminal development stalled/challenged at this time

– Lawsuit is ongoing by the proposed, 44-MMtpy Millennium terminal’s stakeholders to challenge Washington 

state’s 2017 denial of the Clean Water Act Section 401 certification

– Army Corps revived its environmental review of the project in October 2018, although it cannot issue a 

permit for the project unless the Washington state’s certification denial is reversed or set aside

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 16

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
• Section 45Q tax credit for Carbon Capture and Storage is not reflected in 

AEO2019

– Revised from $20 to $50 per metric ton for secure geologic storage, and from $10 to $35 per 

metric ton for Enhanced Oil or Gas Recovery (EOR/EGR) or utilization

– Changes in tax code are planned for incorporation into AEO2020, with possible indirect 

implications for coal disposition

• Note: The modeling of CCS and 45Q occurs in the Electricity Market Module 

(EMM), Capture, Transport, Utilization and Storage Module (CTUS), and the 

Oil and Gas Supply Module (OGSM) 

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 17

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Section 45Q tax credit for Carbon Capture and Storage 
AEO2019 assumptions and trends

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 18

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Coal productivities projected to continue 

declining, except in the Eastern Interior

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Source: U.S. Energy Information Administration, AEO2019 National Energy Modeling System run REF2019.D1116A. 

19

 -

 1.0

 2.0

 3.0

 4.0

 5.0

 6.0

 7.0

 8.0

1996 2002 2008 2014 2020 2026 2032 2038 2044 2050

short tons per miner hour

Eastern Interior

Northern Appalachia

Central Appalachia

 -

 5.0

 10.0

 15.0

 20.0

 25.0

 30.0

 35.0

 40.0

 45.0

 50.0

1996 2002 2008 2014 2020 2026 2032 2038 2044 2050

[Annual Growth 2017-2050]

Short tons per miner hour

Powder River Basin

Gulf Lignite

Rocky Mountain

Dakota Lignite

2018 

History Projections

2018 

History Projections

0.6%

-2.5%

-2.7%

Major eastern producing regions Major western producing regions

-0.9%

-0.8%

-0.8%

-1.9%

[Annual Growth 2017-2050]

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
International seaborne coal trade projected to increase 31% 

(400 million short tons) in AEO2019 (2017–2050)

20

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2017 2020 2030 2040 2050

rest of world

India

other nonOECD Asia

China

South Korea

Japan

OECD Europe 0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2017 2020 2030 2040 2050

rest of world

United States

South America

Eurasia

Southern 

Africa

Indonesia

Australia

Coal imports 

billion short tons

Coal exports 

billion short tons

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019.

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Coal and Uranium Analysis Team, 

Washington, D.C., May 17, 2018
Relatively high levelized cost of electricity for coal prohibits the addition of 

coal in any case evaluated in AEO2019

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Source: U.S. Energy Information Administration, “Levelized Cost and Levelized Avoided Cost of New Generation Resources in the AEO2019”, February 2019, Excerpted from 

Table 1b (2023) and Table B1b (2040)

21

0 2 4 6 8 10

Advanced CC

Wind, Onshore

Solar PV

Adv. Nuclear...

Coal 90% CCS

Advanced CC

Wind, Onshore

Solar PV

Adv. Nuclear...

Coal 90% CCS

2040

New power plant costs

2018 cents per kilowatt-hour

Incremental

transmission

costs

Fixed

costs

Variable costs,

including fuel 2023 Capital costs

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 22

After decades of slowing growth, electricity consumption is 

expected to grow gradually through 2050 across all sectors

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019.

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

-1

0

1

2

3

4

5

1990 2000 2010 2020 2030 2040 2050

Electricity use growth rate 

percent growth (three-year rolling average)

2018

history projections

High 

Economic 

Growth

Reference

Low Economic 

Growth

0

400

800

1,200

1,600

2,000

199020182050199020182050199020182050199020182050

Electricity use by end-use demand sector 

(Reference case) 

direct use

electricity 

sales

residential industrial

commercial transportation
0

500

1,000

1,500

2,000

2,500

2010202020352050202020352050202020352050202020352050202020352050

Renewables electricity generation (all sectors) by case

billion kilowatthours

solar

wind 

other

history projections

Reference Low

Economic

Growth

High

Economic

Growth

Low Oil and

Gas Resource

and Technology

High Oil and

Gas Resource

and Technology

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Increasing cost competitiveness of renewables leads to growth in generation 

even with projection for low electricity demand and low natural gas prices

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019.

23

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Average delivered coal and natural gas prices to the electric power 

sector indicate limited competitive opportunity for coal

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 24

0

2

4

6

8

10

12

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Low Oil and Gas Resource

and Technology

Reference

High Oil and Gas Resource

and Technology

Average delivered fuel prices to the electric power sector

2018 dollars per million British thermal units

natural gas

coal

Source: U.S. Energy Information Administration, AEO2019 National Energy Modeling System run REF2019.D1116a, highrt.1116a, and lowrt.1116a. 

2018 

history projections

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
AEO2019 results with emphasis on coal

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 25

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Generating capacity decreases through 2030 in all AEO side cases 

and is sensitive to the projection for natural gas prices

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 26

0

5

10

15

20

25

30

0

50

100

150

200

250

300

350

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Low Oil and Gas Resource

and Technology

Reference

High Oil and Gas Resource

and Technology

Electric generating capacity Average delivered natural gas prices to the electric power sector

Gigawatts (GW) 2018 dollars per million British thermal units

natural gas prices

coal-fired capacity

Source: U.S. Energy Information Administration, AEO2018 National Energy Modeling System run REF2019.D1116a, highrt.1116a, and lowrt.1116a. 

2018 

history projections

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
-300

-200

-100

0

Economics and policy drive changes to electric generation capacity

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019.

27

0

200

400

600

800

1,000

Low Oil and 

Gas Resource/

Technology

Cumulative generating capacity 

additions and retirements (2018-50)

gigawatts

Reference High Oil and

Gas Resource/

Technology

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

-30

-20

-10

0

10

20

30

40

50

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

solar

wind

oil and gas

nuclear

other

coal

Annual electricity generating capacity additions and retirements 

(Reference case) 

gigawatts 2018

history projections additions

retirements
Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Net summer coal-fired generating capacity in the electric power sector declines 

disproportionately by region in the AEO2019 Reference case

Source: U.S. Energy Information Administration, AEO2019 Reference case (ref2019.d1116a); 

28

0 10 20 30 40 50 60 70

ERCOT

FRCC

MRO (MROE/MROW)

Northeast (RFCE,NPCC)

North Central (RFCW,RFCM)

SERC Gateway (SRGW)

SERC SE (SRSE)

SERC Central (SRCE)

SERC VACAR (SRVC)

South (SPNO,SPSO,SRDA)

WECC

(AZNM,CAMX,NWPP,RMPA)

2018 2050 retirements

U.S. Total 

2018: 240 MW

AEO2019 2050: 151 MW

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Overview of AEO2018 Coal Projections, Greg Adams 

Washington D.C. October 25, 2018 29

Comparison of electric generating capacity across the Reference 

and High/Low Oil and Natural Gas Resource and Technology cases

• In the High Oil and Natural Gas Resource and Technology case, coal-fired capacity declines by an additional 28 GW to 125 GW as 

plentiful low-cost natural gas dominates with 103 GW of additional capacity through 2050. Nuclear also declines by an additional 24 GW.

• In the Low Oil and Natural Gas Resource and Technology case, coal-fired capacity declines by 32 GW declining to 185 GW through 2050. 

Nuclear capacity increases by 10 GW and renewables increase by and additional 222 GW.

0

200

400

600

800

1000

1200

1400

1600

1800

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

High Oil and Gas Resource and 

Technology

renewables

natural gas

coal

nuclear

generation capacity (GW)

0

200

400

600

800

1000

1200

1400

1600

1800

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Low Oil and Gas Resource and 

Technology

renewables

natural gas

coal

nuclear

generation capacity (GW)

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019 (ref2019.d1116a); .

0

200

400

600

800

1000

1200

1400

1600

1800

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Reference

renewables

natural gas

coal

nuclear

generation capacity (GW)

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Although coal capacity declines, capacity factors for remaining coal 

units recover as much as natural gas prices allow

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 30

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019. 

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

0

1

2

3

4

0

50

100

150

200

250

300

350

2000 2010 2020 2030 2040 2050

2018

history projections

Low Oil and Gas Resource

and Technology

Reference

High Oil and Gas Resource

and Technology

Electric generating capacity Total electricity generation

gigawatts trillion kilowatthours

0%

20%

40%

60%

80%

100%

2000 2010 2020 2030 2040 2050

2018

history projections

Capacity utilization rate - coal-fired 

generation

percent

coal capacity

coal generation 
0

1,000

2,000

3,000

4,000

5,000

6,000

2010 2020 2030 2040 2050

2018

history projections

Electricity generation from selected fuels 

(Reference case)

billion kilowatthours

natural gas

renewables

nuclear

coal

39%

31%

12%

17%

19%

18%

34%

28%

Electricity generation from natural gas and renewables increases steadily with coal 

and nuclear projected to remain relatively flat in the AEO2019 Reference case 

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019.

31

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

0

500

1,000

1,500

2,000

2,500

3,000

1990 2000 2010 2020 2030 2040 2050

2018

history projections

Reference

Electricity generation from selected fuels

billion kilowatthours

natural gas

coal

nuclear

renewables
The projected mix of electricity generation varies widely across cases

because differences in fuel prices result in significant substitution

32 Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019. 

0

500

1,000

1,500

2,000

2,500

3,000

1990 2000 2010 2020 2030 2040 2050

2018

history projections

Reference

Electricity generation from selected fuels

billion kilowatthours

natural gas

coal

nuclear

renewables

0

500

1,000

1,500

2,000

2,500

3,000

2015 2050

2018

projections

High Oil and Gas 

Resource and 

Technology

0

500

1,000

1,500

2,000

2,500

3,000

2015 2050

2018

projections

Low Oil and Gas 

Resource and 

Technology
Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Electricity sector consumption drives total U.S. coal disposition 

with stable industrial and slowly-increasing export demand

33

0

200

400

600

800

1,000

1,200

2000 2010 2020 2030 2040 2050 2020 2030 2040 2050 2020 2030 2040 2050

electric power sector 

consumption

net exports

other consumption

High Oil and Gas 

Resource and 

Technology 

Low Oil and Gas 

Resource and 

Technology

AEO2019

Reference case

U.S. coal consumption and net exports 

million short tons

2018

history projection

• Source: U.S. Energy Information Administration, AEO2019 National Energy Modeling System run REF2019.D1116a, highrt.1116a, and lowrt.1116a. 

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Interior region coal production is projected to increase at the expense of the West 

and Appalachia regions in the Reference case

34 Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Source: U.S. Energy Information Administration, Annual Energy Outlook 2019.

0

200

400

600

800

1,000

1,200

1,400

2015 2050

2018

projections

High Oil and Gas 

Resource and 

Technology

0

200

400

600

800

1,000

1,200

1,400

2015 2050

2018

projections

Low Oil and Gas 

Resource and 

Technology

0

200

400

600

800

1,000

1,200

1,400

2000 2010 2020 2030 2040 2050

Coal production by region

million short tons

2018

history projections

Appalachia

Reference

total

West

Interior
Coal mine employment trends reflect impact of declining 

labor productivity against backdrop of declining production

35 Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

0

10

20

30

40

50

60

70

80

90

100

2000 2010 2020 2030 2040 2050

Thousands

Coal mine employment

number of miners

2018

history projections total

Appalachia

West

Interior

AEO 2019 Reference case

0

10

20

30

40

50

60

70

80

90

100

2000 2010 2020 2030 2040 2050

Thousands

Coal mine employment

number of miners

2018

history projections

total

Underground

Mines

Surface

Mines

AEO 2019 Reference case

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Source: U.S. Energy Information Administration, AEO2019 Reference case (ref2019.d1116a).
Average U.S. minemouth coal prices remain relatively stable in 

light of declining production volumes

2018 dollars per short ton

Appalachia

Interior

West

0

10

20

30

40

50

60

70

80

90

100

1980 1990 2000 2010 2020 2030 2040 2050

AEO2019

U.S. Average

2018

History Projections

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 36

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Source: U.S. Energy Information Administration, AEO2019 Reference case (ref2019.d1116a).
U.S. coal exports driven by strong demand for coking coal for steel production

million short tons

0

20

40

60

80

100

120

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

coking

steam

History Projections

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 37

Sources: U.S. Energy Information Administration (EIA); Projections – AEO2019 Reference case (ref2019.d1116a).; 

History –. Quarterly Coal Report.

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Model updates

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 38

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Coal Market Module (CMM) updates and improvements 

planned for AEO2020 and beyond

• Implementing 2018 base year updates, including base year coal transportation rates and 

contracts, and revisiting regional coal export constraints in the CMM 

• Progressing on three CMM upgrade priorities

– Implementing a revised approach to modeling seaborne coal shipping costs in AEO2020

– Evaluating a revised approach to escalating real domestic coal transportation rates

– Developing a revised approach for modeling international coal supply curves (ICSC) in the CMM in AEO2021

• Developing an International Coal Market Module (ICMM) in WEPS+

– Developing a linear programming-based approach using EIA’s Global Hydrocarbon Supply Model (GHySMo) 

platform and taking advantage of efforts to improve the modeling of ICSC and seaborne coal shipping costs

– Anticipating for inclusion in IEO2020/1 cycle

• Initiating plans for a Short-Term Energy Outlook (STEO) coal forecasting working group 

in summer 2019

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 39

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Pending AEO2020 model enhancements to NEMS 

Electricity Market Module (EMM)

• Regional redefinition of EMM supply regions

• Updated capital cost and performance for new electric generating 

technologies

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 40

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
What will the new regions look like in EMM?

CURRENT PROPOSED

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Source: Current: U.S. Energy Information Administration, Assumptions to the Annual Energy Outlook 2019: Electricity Markets Module. 

Proposed: Proposed Approach for the EMM Regional Redefinition and Renewable Resource Mapping, On-Location- Oct 15, 2018 (unpublished)

41

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Generation technologies proposed for updated capital cost 

estimates for AEO2020

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Source: U.S. Energy Information Administration.

42

NEW

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE AS MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

EMM Generating Technology Plant Types Proposed

Fossil/Nuclear

Fuel Type Plant Type description Proposed Configuration Case Description

Coal Coal w/o CCS 650 MW Net Ultra-supercritical coal (NSPS for NOX, Sox, PM, Hg)

Coal Coal w/Partial Sequestration 650 MW Net

NSPS compliant ultra-supercritical coal (with 30% CCS or other compliance 

technology)

Coal Coal w/90% Sequestration 650 MW Net Ultra-supercritical coal (with 90% CCS)

Gas-Peaking Internal Combustion Engine 20 MW (4x 5.6 MW) Internal combustion engine (natural gas or oil-fired diesel)

Gas-Peaking Conv Combustion Turbine 100 MW, 2 x LM6000 Combustion oil/natural gas turbine

Gas- Baseload Adv Gas/Oil Comb Cycle 1100 MW, H-Class, 2x2x1 Combined-cycle oil/natural gas turbine

Gas-Baseload Adv Gas/Oil Comb Cycle 430 MW, H-Class 1x1x1 Combined cycle single shaft

Gas- Baseload Adv CC w/Sequestration 430 MW, H-Class 1x1x1 Combined-cycle gas turbine (with 90% CCS) 

Nuclear Advanced Nuclear 2 x 1117 MW, PWR Advanced Nuclear AP 1000

Nuclear SMR Nuclear 600 MW Small Modular Reactor (SMR)
Changes to the Coal Market Module: 

seaborne coal transportation rates

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 43

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Improving the projections for seaborne coal trade freight 

rates in the CMM • Currently, the CMM specifies fixed, annual rates by route exogenously 

• EIA worked with Hellerworx, Inc. to suggest an improved methodology

– Hellerworx, Inc., DOE/EIA Coal Market Module: Coal Transportation Rate Methodology Assessment, 

September 29, 2017 (Unpublished)

• The proposed method would estimate rates endogenously by major vessel category 

(Panamax or Cape sizes) 

– Component for costs at sea represented as a function of trip distance, vessel size, average speed, bunker 

and marine gas oil fuel consumption per day at sea, fuel cost per metric ton, and vessel hire costs per day

– Component for costs in port represented as a function of days in port, port fees per metric ton, lading tonnes, 

marine gas oil fuel consumption per day in port, and vessel hire costs per day (note: does not include 

loading and unloading costs – only the vessel costs)

– Fuel costs by year determined endogenously by other modules in NEMS

– Daily vessel hire rates in each year determined exogenously based on analyst assessments 

• EIA proposes to implement this method in-house in time for AEO2020

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 44

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Ports and Estimated Shipping Distances for Selected Routes

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 45

CMM coal export location

CMM coal import location

proposed CMM coal 

export location

4,850 nm

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Stylized example of the proposed seaborne coal trade 

freight rates in the CMM

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Source: Stylized example based on unpublished analysis for EIA by Hellerworx, Inc., DOE/EIA International Coal Supply Curve and Transportation 

Modeling – Australia Pilot Study, Ocean Freight Forecast & Coal Data Survey Study Methodology and Documentation, September 8, 2016. 

46

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Seaborne coal trade freight rate assumptions

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 47

Source: Stylized example based on unpublished analysis for EIA by Hellerworx, Inc., DOE/EIA International Coal Supply Curve and Transportation 

Modeling – Australia Pilot Study, Ocean Freight Forecast & Coal Data Survey Study Methodology and Documentation, September 8, 2016. 

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Seaborne coal trade freight rates: costs at sea

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 48

Source: Stylized example based on unpublished analysis for EIA by Hellerworx, Inc., DOE/EIA International Coal Supply Curve and Transportation 

Modeling – Australia Pilot Study, Ocean Freight Forecast & Coal Data Survey Study Methodology and Documentation, September 8, 2016. 

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Seaborne coal trade freight rates: costs in port

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 49

Source: Stylized example based on unpublished analysis for EIA by Hellerworx, Inc., DOE/EIA International Coal Supply Curve and Transportation 

Modeling – Australia Pilot Study, Ocean Freight Forecast & Coal Data Survey Study Methodology and Documentation, September 8, 2016. 

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Plan for implementing freight rate framework for seaborne 

coal in the CMM

• EIA staff will work to implement this approach in CMM to include in the 

AEO2020, using endogenous fuel prices within NEMS

• EIA has determined a matrix of distances and assigned a vessel type for 

each route in the model

• Historic daily hire rates will be reviewed and calibrated to reported freight 

rates to establish a general long-term trajectory for annual values

• Feedback from the working group will be addressed during the 

implementation

• Model documentation and assumptions will be updated accordingly

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 50

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Any questions on the proposed approach for modeling 

seaborne coal transportation costs?

• The projections will depend to a significant degree on the projection of daily 

hire rates in the model framework. What approaches should EIA consider for 

projecting daily hire rates?

• Should EIA incorporate measures of technological improvement over time, 

such as improvement in fuel consumption or vessel size?

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 51

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Changes to the Coal Market Module: 

coal transportation rate escalation 

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 52

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Taking a fresh look at modeling coal transportation rate 

escalation in times of declining domestic rail volumes

• EIA worked with Hellerworx, Inc. to examine EIA’s existing approach and to 

recommend improvements in light of declining coal production volumes shipped in the 

United States

– Hellerworx, Inc., “DOE/EIA Coal Market Module: Coal Transportation Rate Methodology Assessment,” 

September 29, 2017 (Unpublished)

• Current econometric approach to rate escalation would be replaced by a shareweighted approach with diesel fuel costs accounted for directly

• EIA staff also reviewed the specification of Tier II rates in the model to evaluate an 

alternative approach suggested by Hellerworx

• EIA is proposing to implement the Hellerworx approach to rate escalation in-house by 

the AEO2021 cycle

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 53

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Why are coal transportation rates important?

• Electric power consumption represents 90% of all coal deliveries to coal 

users in the United States, with approximately 70% delivered in whole or in 

part by rail

• The cost of coal transportation averaged an estimated 41% in 2017 to 

electric power consumers based on survey Form EIA-923 data

• Long-term escalation at 1% per year would result in 35% higher rates in 30 

years, or about 14% higher delivered coal costs assuming about a 41% cost 

share, e.g., the difference between $2.25/MMBtu and $2.57/MMBtu

• In increasingly competitive markets, such changes could have noticeable 

impacts on coal retirements and capacity factors

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Sources: U.S. Energy Information Administration, Today in Energy, August 3, 2018, U.S. coal shipments reach their lowest levels in years, 

Primary Contributor: Elias Johnson. Also, U.S. Energy Information Administration, July 17, 2018 Transportation Costs to Electric Power Sector.

54

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
How are base year coal transportation rates estimated? • Base year coal transportation rates, aggregated across all modes, are estimated between each coal 

supply curve and each coal demand region and plant group type

– Base year rates are currently estimated as the difference between delivered coal prices reported by electric 

utility generators on survey Form EIA-923 and minemouth coal prices provided on Form EIA-7A

– Coal supply curves are delineated by coal supply region, coal type, mine type, and sulfur class

– Plant groups within each coal demand region are delineated by pollution control configuration

– Base year rates are adjusted to remove the estimated impact of railroad fuel surcharges before the real 

escalation rates are applied, and they are added back after the adjusted base year rates have been adjusted for 

second-tier rate adders and escalated

• Second-tier rate adders adjust rates to account for shipping distances within a coal demand region, as 

well as incremental costs associated with upgrading a coal unit to burn PRB coal

– Increased shipping distances are accounted for by adjusting transportation rates to the difference between the 

estimated shipping distance and the geographic centroid for the relevant coal demand region

– Assumed adder of $0.10/MMBtu accounts for incremental capital for coal pulverization volumes and boiler 

modifications, and operating costs from changes in slagging/fouling and heat rate impacts necessary to burn 

PRB coal

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Sources: U.S. Energy Information Administration, Coal Market Module of the National Energy Modeling System: Model Documentation 2005 

(April) and 2009 (June), Appendix D.

55

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
How have coal transportation rate escalation methods evolved? (1 of 2)

• Before 1997, EIA relied on a regression model to estimate 

real, inflation-adjusted escalation rates based on the 

American Association of Railroads' Railroad Cost Recovery 

Index, with separate escalators for East and West

• In 1997, EIA adjusted its econometric approach to 

incorporate the effects of rail productivity improvements on 

rail costs

– Corrected for the widening gap between the input cost trends 

and trends in actual rates

– Modeled the real Producer Price Index (PPI) for coal 

transportation as a function of the real wage cost index, the 

real price of distillate fuel, the real producer price index for 

transportation equipment, and a time trend to account for 

productivity; benchmarked to the base year

– A parameter was included that allowed user to adjust the 

effects of the productivity trend variable over time

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Source: Watkins, Jim, “Forecasting Annual Energy Outlook Coal Transportation Rates,” Issues in Midterm Analysis and Forecasting 1997, DOE/EIA-0607(97), (Washington, DC, 

Energy Information Administration), July 1997, pp. 75-82.

56

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
How have coal transportation rate escalation methods evolved? (2 of 2) • In 2005, EIA incorporated differentiated East/West escalators to account for longer shipping 

distances in the West, transformed the PPI for transportation into a User Cost of Capital for the 

railroad equipment variable, and used ton-miles per employee to model productivity

– Both eastern and western deliveries were modeled as functions of (2SD-adjusted) productivity and the usercost of capital, but the function for eastern deliveries also included contract duration, while western deliveries 

included a distance variable

– The UCC adjusts the Producer Price Index (PPI) for Rail Equipment (RE) as a function of the cost of capital 

tied up in rail as a function of the real AA utility bond rate premium, the cost of depreciation at a rate of 10%, 

and the change in the PPI-RE

• In 2009, EIA functions for East/West were modified further based on additional analysis

– The East index function substituted diesel fuel price for contract duration; diesel fuel prices are zeroed out in 

the Eastern econometric projection equation to avoid double-counting the effect of fuel surcharges 

– The West index function substituted gross capital investment by Class I railroads for UCC and substituted 

the western share of coal demand for distance

– Productivity is assumed to stay flat reflecting an assumption that changes in productivity are not passed on 

to shippers

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Sources: U.S. Energy Information Administration, Coal Market Module of the National Energy Modeling System: Model Documentation 2005 (April) and 2009 (June), Appendix D.

57

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Summary of coal the current transportation rate escalation method

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 58

Base Year Transportation Rates

Adj. Base Year Transportation Rates

Remove Estimated Fuel Surcharges

Adjust Cost for Shipping Distances

Add Cost for 1st Use of Sub-Bit Coal

First Tier

Second Tier

EIA923/7A

Apply Regional Escalation Indices

East

 Railroad Productivity

 User cost of capital

 Diesel fuel price

West

 Railroad Productivity

 Investment

 West U.S. Mkt. Share

Escalated Transportation Rates

Apply Annual Fuel Surcharges

Modeled Transportation Rates

Current method

Econometric

Functions

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
What are the differences between the rate escalation methods?

• Current method

– Estimates separate coal transportation rate 

escalators for eastern and western coal shipments

– Applies to all modes of coal transport

– Uses econometric model to estimate the 

relationship between the projected inputs

• East modeled as a function of rail productivity, 

the User Cost of Capital, and diesel fuel 

prices

• West modeled as a function of rail 

productivity, investment, and the western 

share of U.S. coal shipments

• User Cost of Capital is based on the Producer 

Price Index (PPI) for railroad equipment, a 

proxy for interest rates based on the AA Utility 

Bond Rate and 3% risk premium, and the 

estimated annual depreciation (10%)

– Has separate accounting for fuel cost adjustments

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 59

• Proposed method

– Estimates single, national transportation rate 

escalation profile using rail as a proxy for other 

modes of transportation

– Applies to all modes of coal transport

– Uses a structural approach to weight key projected 

cost and productivity inputs

• Weight fuel, labor, and equipment cost 

percentage changes by the latest component 

weightings for the rail industry published by 

the American Association of Railroads (AAR) 

adjusted for EIA’s outlook for diesel fuel prices 

• Add 50% of estimated average, annual STB 

productivity improvements (%) over the past 

10 years

• Weights are fixed parameter inputs for the 

duration of the projections

– Eliminates separate fuel cost adjustments

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Comparison of coal transportation rate escalation methods

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 60

Base Year Transportation Rates

Adj. Base Year Transportation Rates

Remove Estimated Fuel Surcharges

Adjust Cost for Shipping Distances

Add Cost for 1st Use of Sub-Bit Coal

First Tier

Second Tier

EIA923/7A

Apply Regional Escalation Indices

East

 Railroad Productivity

 User cost of capital

 Diesel fuel price

West

 Railroad Productivity

 Investment

 West U.S. Mkt. Share

Escalated Transportation Rates

Apply Annual Fuel Surcharges

Modeled Transportation Rates

Current method

Base Year Transportation Rates

Adj. Base Year Transportation Rates

Adjust Cost for Shipping Distances

Add Cost for 1st Use of Sub-Bit Coal

Apply National Escalation Indices

 Calculate the cost component-weighted real 

escalation factor, across Fuel, Labor, and 

Equipment/Other indices

 Subtract share of passed-through rail 

productivity gains to calculate annual 

escalation rates 

Modeled Transportation Rates

Proposed method

Econometric

Functions

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
How are the cost component weights derived in the proposed method?

• Cost component weights in 2017 from AAR were 35.0% for labor, 13.4% for fuel, and 

51.6% for equipment and other costs based on 2015 data from AAR*

• Component weights adjusted for AEO2017 projected prices were 33% for labor, 

18.3% for fuel, and 48.7% for equipment and other costs

• Adjust weights to reflect AEO projections for historical and projected diesel fuel price 

to the transportation sector (diesel prices) – example based on AEO2017 ($2016) 

– Adjusted Fuel Weight = AAR Value –Fuel (13.4%) x Average AEO2017 projected diesel prices from 

2017–2050 ($3.76/gallon) x AEO2017 2015 diesel price ($2.76/gallon) = 13.4% x 1.362 = 18.3%

– Allocation Amount = Adjusted Fuel Weighting (18.3%) – AAR Value (13.4%) = 4.9%

– Allocation Share-Labor = AAR Value-Labor (35%) / [AAR Value-Labor + AAR-Value-Equip (51.6%)] 

= 35% / 86.6% = 40.4%

– Adjusted Labor Component Weight = AAR Value-Labor (35%) – [Allocation Amount (4.9%) x Allocation 

Share-Labor (40.4%)] = 35.0% - 2.0% = 33.0%

– Adjusted Equipment/Other Component Weight = 100% - Adjusted Fuel Weighting (18.3% - Adjusted 

Labor Component Weight (33%) = 48.7% 

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 61

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

*Source: Association of American Railroads (AAR), Rail Cost Indexes, RCAF Quarterly Filings & Decisions.
How would the cost component input variables be projected 

under the proposed method? 

• Diesel fuel prices to the transportation sector would be projected endogenously based on 

historical and projected values in NEMS to adjust the fuel weighting

• Labor costs would be projected based on the performance of the BLS Employment Cost 

Index during the most-recent, 10-year period available*

– Hellerworx analysis indicated that the BLS index increased at an average rate of 2.1% per year from 2006Q4 to 

2016Q4, compared with the BEA GDP-IDP average inflation rate of 1.6% during the same period, suggesting a 

0.5% rate of real increase

– Hellerworx recommended the BLS index instead of the AAR Labor Index because the AAR index showed a large 

discontinuity between pre- and post-recession periods compared with the BLS index

– Hellerworx also suggested that the unionized rail transportation sector should be able to secure wage increases 

in line with the private sector on average over the long-term

• Equipment/other costs would be projected to increase at the general rate of inflation, i.e., 

constant in real dollar terms

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

*BLS Series ID CIS2010000000000I, which tracks the cost of wages, salaries, and benefits for all private sector workers in the United States.

62

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
How would railroad productivity trends be projected and 

accounted for in the proposed method?

• Rail productivity would be based on the estimated, average productivity 

gains published by the Surface Transportation Board (STB) during the mostrecent, 10-year period available

– Hellerworx estimated an average annual productivity gain of 1.4% more than the 2006-2015 

period

– This gain was 0.8% from 2006-2010 and 2.0% from 2011 to 2015

• Half of estimated rail productivity improvements would be passed to coal 

shippers under the proposed method (0.7% per year)

– Hellerworx believed that railroads will be strongly pressured to pass along a portion of gains 

to customers to remain competitive in an environment of decreasing coal demand in a 

declining market for coal transportation

– Value subtracted from the weighted cost component calculations to determine the national 

escalation factor in each year

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 63

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
How does this compare to the Surface Transportation 

Board’s (STB) All-Inclusive Index?

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

Source: American Association of Railroads, Restated 2018Q4, 2019Q1, and 2019Q2, All-Inclusive Index, Ex Parte No. 290 (Sub-No. 5) (2019-

2), Quarterly Rail Cost Adjustment Factor, Surface Transportation Board, March 26, 2019. 

64

RCAF Variable 2017 Share AAR Short-Term Escalator Basis

Labor 34.8% Sector analysis of subcomponents for rail sector

Fuel 12.9% Ultra-Low Sulfur Diesel Fuel referenced, but otherwise, based on a survey of 

rail purchasers and petroleum experts

Materials & 

Supplies

4.9% Not clear, but references change in prices for Metal Products and Misc. 

Products

Equipment Rentals 5.7% Price index for Industrial Commodities less Fuel and Related Products and 

Power (PPI-LF)

Depreciation 15.7% Power Price Index for Railroad Equipment (PPI-RE)

Interest 2.1% Interest rates for 10- and 30-year U.S. Treasury Bonds are referenced, but the 

latest historical value based on annual reports from railroads is carried forward

Other 23.% Price index for Industrial Commodities less Fuel and Related Products and 

Power (PPI-LF)

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Could the proposed structural approach be endogenized in 

NEMS-CMM using projected indices?

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 65

RCAF Variable 2017 Share NEMS Long-Term Projections Escalator Basis

Labor 34.8% Employment Cost Index--Total Private Compensation (2005=1.00)

Fuel 12.9% Indexed Ultra-Low Sulfur Diesel Fuel Price

Materials & Supplies 4.9% Wholesale Price Index – Metals and Metal Products (1982=1.00)

Equipment Rentals 5.7% Wholesale Price Index – Industrial Commodities less Energy (1982=1.00)

Depreciation 15.7% Wholesale Price Index – Fuel and Power (1982=1.00)

Interest 2.1% Indexed 10-year U.S. Treasury Bond Rate

Other 23.% Wholesale Price Index – Industrial Commodities less Energy (1982=1.00)

• At the start of each NEMS cycle, EIA could calculate the real rate of change in selected 

indices relative to the Gross Domestic Product Deflator, apply the base year shares to 

project the first projection year’s escalation rate, and use the share-weighted values for 

that year to generate shares for application in the next projection year, and so on

• Productivity adjustment would still be necessary based in part on analyst judgment

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Plan for implementing a revised coal transportation rate 

escalation method in the CMM

• EIA staff will be preparing a summary of the proposed approach and seek 

additional feedback

• EIA will assess any feedback and a decide on whether to use an 

econometric or a structural approach and how to project and apply 

productivity trends under either approach

• EIA will incorporate any changes to the CMM into the AEO2020/1 release; 

the selected method will be tested and revised as appropriate

• Model documentation and assumptions will be updated, accordingly

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 66

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Key questions on coal transportation rate escalation?

• Is the proposed structural, weighted-average method preferred to the 

current, econometrics method?

• How should we treat productivity and what assumptions should be made 

regarding its value and weighting in the projections?

• What rate of real wage escalation should be assumed for coal transportation 

labor?

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 67

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Changes to the Coal Market Module: 

international coal supply curves 

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 68

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Improvements to the international coal supply curve 

specification planned for AEO2021

• Currently, the CMM specifies fixed supply curves for each non-U.S., coal-producing 

region exogenously, adjusting each AEO cycle based on analyst judgment 

• EIA worked with Hellerworx, Inc. to suggest an improved methodology

– Hellerworx, Inc., “DOE/EIA International Coal Supply Curve Modeling Study Methodology,” June 30, 2017 

(unpublished)

– Hellerworx, Inc., “DOE/EIA International Coal Supply Curve and Transportation Modeling – Australia Pilot 

Study, Ocean Freight Forecast & Coal Data Survey Study Methodology and Documentation,” September 8, 

2016 (unpublished)

• The proposed approach would specify econometric functions for each nonU.S. coal producing region in the CMM 

– Econometric specifications based on either publicly-available data or data already available 

to EIA under contract from private vendors to ensure it can be updated over time

– Supply curves for some regions, such as China, may still be set exogenously depending on 

each region’s political or economic constraints or its limited coal export volumes

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 69 WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
How are international coal supply curves used in the CMM?

• The CMM represents coal supply available for seaborne coal 

trade between international regions with exogenouslyspecified export supply curves for steam coal and 

metallurgical coal types by producing region; each curve 

may have up to 10 steps, but most only have a few steps

• The CMM international coal distribution submodule (ICDS) 

satisfies seaborne coal demand from each import demand 

region that are determined exogenously based on EIA’s 

International Energy Outlook 

• The coal trade flows in the ICDS currently represent only 

seaborne trade of coal, and rail or other movements 

between regions are not modeled, e.g., shipments from 

Mongolia to China or Russia to Europe are not represented.

• The ICDS includes 5 U.S. and 12 non-U.S. export regions

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 70

CMM Label Export Region 

AU Australia

NW Canada, Western

NI Canada, Interior

SF Southern Africa1

PO Poland

RE Eurasia2 (exports to Europe)

RA Eurasia2 (exports to Asia)

HI China

CL Colombia

IN Indonesia

VZ Venezuela

VI Vietnam

1Southern Africa includes South Africa, Mozambique, and Botswana.

2Eurasia includes Armenia, Azerbaijan, Belarus, Estonia, Georgia, 

Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russia, Tajikistan, 

Turkmenistan, Ukraine, and Uzbekistan.

International Regions

Source: CMM Model Documentation

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
How would the coal export supply curves be estimated 

using the proposed method?

• The approach suggested by Hellerworx would generate 

supply curves endogenously in the ICDS for key regions 

based on regional, econometric regression equations 

representing coal export quantities as a function of price 

(free on board, FOB) and other independent variables 

based on availability of data and analysis

• The approach uses two-stage least squares, and 

worldwide steel production is required as an 

instrumented variable

• Other data series are needed to estimate and maintain 

the supply curves, including coal export quantities, coal 

miner counts, and coal production by country (to 

compute base-year productivity) 

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 71 WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Q exported = f (Price FOB, MTPA, Wage, 

ExpCap, Fuel)

Where

• MTPA: productivity in metric tons per 

miner-year (mtpa, metric tons per 

annum)

• Wage: coal miner wages–annual by 

country converted to real U.S. dollars

• ExpCap: export capacity based on 

port, rail, and production capacity for 

the region

• Fuel: diesel fuel price – annual 

average by country/region
Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019

How would the new coal export supply regions be specified?

72

• The suggested approach 

would model 15 unique coal 

export supply curves 

specified across 8 regions 

and 2 coal types

• The remaining five regions 

have small or declining coal 

exports or other policy 

considerations that 

constrain coal exports that 

will continue to be modeled 

using exogenous, static coal 

supply curves

• The Australia region will be 

divided into two distinct 

producing and export 

regions (AQ: Queensland 

and AN: New South Wales)

CMM Label Export Region 

AN Australia - NSW

AQ Australia - Queensland

CL Colombia3

IN Indonesia

NW Canada - West Coast

RE Eurasia2 (exports to Europe)

RA Eurasia2 (exports to Asia)

SF Southern Africa1

1Southern Africa includes South Africa, Mozambique, and Botswana.

2Eurasia includes Armenia, Azerbaijan, Belarus, Estonia, Georgia, 

Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russia, Tajikistan, 

Turkmenistan, Ukraine, and Uzbekistan. 3Columbia and Venezuela have only thermal curves.

International Regions

Regions getting new Formulations

CMM Label Export Region 

HI China

NI Canada - Interior

PO Poland

VZ Venezuela3

VI Vietnam

International Regions

Regions using exogenous P/Q inputs

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Plan for implementing a revised international coal supply 

curve specifications in the CMM

• EIA staff will be preparing a summary of the proposed approach and may 

seek additional feedback

• A test version of the proposed approach will be incorporated into the CMM 

and tested to evaluate and revise the specifications before using in the AEO

• Any changes to the CMM will be targeted for incorporation into the AEO2021 

release

• Model documentation and assumptions will be updated, accordingly

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 73

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
For more information

Greg Adams, Team Lead, Coal and Uranium Analysis | Greg.Adams@eia.gov | (202) 586-7343

David Fritsch, AEO Coal Models and Projections | David.Fritsch@eia.gov | (202) 587-6538

Elias Johnson, STEO Coal Models and Projections | Elias.Johnson@eia.gov | (202) 586-7277

Bonnie West, STEO and IEO Coal Models and Projections | Bonnie.West@eia.gov | (202) 586-2415 

Kien Chau, IEO Coal Models and Projections | Kien.Chau@eia.gov | (202) 586-4280

_______________________________________________________________________________________________

U.S. Energy Information Administration home page | www.eia.gov

Annual Energy Outlook | www.eia.gov/aeo

Short-Term Energy Outlook | www.eia.gov/steo

International Energy Outlook | www.eia.gov/ieo

Monthly Energy Review | www.eia.gov/mer

Today in Energy | www.eia.gov/todayinenergy

State Energy Profiles | www.eia.gov/state

Coal Data Browser | www.eia.gov/coal/data/browser

U.S. Energy Mapping System | www.eia.gov/state/maps.php?v=Coal (new rail layers)

International Energy Portal | www.eia.gov/beta/international/?src=home-b1

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 74

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Supplemental slides

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 75

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
0.0

50.0

100.0

150.0

200.0

250.0

300.0

350.0

400.0

450.0

500.0

1970 1980 1990 2000 2010 2020 2030 2040 2050

Northern Appalachia

Central Appalachia

Southern Appalachia

Total Appalachia

Appalachian coal production shows big declines through 2016, with the 

recent uptick from increased coal exports

million short tons

Source: U.S. Energy Information Administration, AEO2019 Reference case (ref2019.d1116a), 

2017

history projections

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 76

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Interior coal production declines in 2016 and 2017 but comes back in the Illinois 

Basin while lignite regions show continued decline

million short tons

Total Interior

0

50

100

150

200

250

300

1970 1980 1990 2000 2010 2020 2030 2040 2050

Eastern Interior

Gulf Lignite

2017

history projections

Source: U.S. Energy Information Administration, AEO2019 Reference case (ref2019.d1116a)

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 77

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 
Western coal production has seen the greatest rate of decline since 2009

million short tons

0

100

200

300

400

500

600

700

1970 1980 1990 2000 2010 2020 2030 2040 2050

Other West

2017

history projections

Wyoming PRB

Total West

Coal and Uranium Analysis Team, 

Washington, D.C., April 9, 2019 78

WORKING GROUP PRESENTATION FOR DISCUSSION PURPOSES. DO NOT QUOTE 

OR CITE. MODELING ASSUMPTIONS AND INPUTS ARE SUBJECT TO CHANGE. 

Source: U.S. Energy Information Administration, AEO2019 Reference case (ref2019.d1116a)