Assessing company climate
policy risk – a scientificfoundation for companies,
investors, and others
And perspectives on the social cost of carbon

Steven Rose (Energy and Environmental Analysis)
Morgan M. Scott (Sustainability)
ALPS Symposium, Tokyo, Japan
February 19, 2019www.epri.com© 2019 Electric Power Research Institute, Inc. All rights reserved.

Today – stakeholder requests a part of the company landscape Stakeholders increasingly requesting thatcompanies analyze the policy cost risk ofmanaging climate change–

In particular, limiting global warming to 2˚C Similarly, companies receiving requests

to set GHG emissions reductions targets

 And, organizations creating

recommendations, methodologies, andtools they would like companies to apply(e.g., TCFD, Science Based Targets, Ceres,
UNEP FI)…and more2

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Today – stakeholder requests a part of the company landscapeDialogue lacking a scientific foundation

1.

…and more3

www.epri.com–

Analyses are technically challenging forcompanies to undertake and for stakeholders
and the public to evaluate–

Most not knowing what they are asking for–

Limited consideration of scientific knowledge

2.

Sound scientific understanding is arequisite first step for companies,
methodologies, and dialogue

3.

Need to slow down and characterize
and use current scientific knowledge
for grounded dialogue and decisions© 2019 Electric Power Research Institute, Inc. All rights reserved.

Global climate goals and the relationship to companies?

Degrees Celsius above pre-industrial

Climate goals
10 (e.g., limit < 2˚C)

4

9
8
7
6
5
4
3
2
1
0
2000

Company?
2200

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Global climate goals and the relationship to companies?
We evaluate scientific understanding of the relationship between acompany and a global average temperature goal

Degrees Celsius above pre-industrial

Climate goals
10 (e.g., limit < 2˚C)

5

9
8
7
6
5
4
3
2
1
0
2000

Company

GlobalGHGs?

2200

www.epri.com

National
GHGs?

Subnational
GHGs?

Potential energy systems, economic activity,and policy?

© 2019 Electric Power Research Institute, Inc. All rights reserved.

Significant global emissions scenario resources available,
but appropriate interpretation critical Large relevant global emissions scenarios peer literature (>1000 scenarios & 30 models) A single scenario misleading – not a prediction or prescription, a projection contingent on themodel & assumptions

 Sets of scenarios appropriate and useful – reflect uncertainty, help identify robust insights–

Sets provide ranges, but not distributions or statistics (medians, percentiles) and only partial uncertainty

 And, results represent aggregate sectors and markets, not individual companies or that allcompanies should behave the same
Global emissions scenario modeling6

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Global climate goals and the relationship to companies?
We evaluate scientific understanding of the relationship between acompany and a global average temperature goal

Degrees Celsius above pre-industrial

Climate goals
10 (e.g., limit < 2˚C)

7

9
8
7
6
5
4
3
2
1
0
2000

Company

GlobalGHGs?

2200

www.epri.com

National
GHGs?

Subnational
GHGs?

Potential energy systems, economic activity,and policy?

© 2019 Electric Power Research Institute, Inc. All rights reserved.

A broad range of global CO2 pathways consistent with 2˚CGlobal CO2 Pathways Consistent with 2˚C Broad range of global CO2 pathways,

budgets, and 2030 & 2050 reductions
consistent with 2˚C Broad ranges for regions & sectors too Ranges reflect uncertainties – climate

system, economic, energy use,technology, policy timing, as well as
differences in models (e.g., structure,
history, time horizon, solution)

Range and selectscenarios shown (n =408)

Developed from IAMC (2014) data

8

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Assumptions matter for properly using results – technology &policy design important for countries, sectors, and companies Is increasing electrification (above baseline)

consistent with the 2˚C goal?
 Should the electric sector reduce emissions by alarger fraction than the overall economy andother sectors?
 Not necessarily!
–

Current scenarios misleading with assumptions
facilitating decarbonization with electricity:
1.
2.

–



9

Global 2050 electrification from current 2˚C scenarios

Idealized global economy-wide policy andcoordination
Availability of cost-effective low-carbon generation
technologies

Policy design & technology are uncertainties toevaluate, matter to cost-effective reductions,electrification, and the attainability of 2˚C pathways

Subglobal results dependent upon global
assumptions
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Developed from IAMC (2014) data

Policy design a key absent uncertainty for companies
 Policy design uncertainty absent from existing scenarios–

Most assume global economy-wide action and coordination. Unlikely.

 Uncertain policy design features…
 Sector/emissions coverage
 Sector/emissions coordination
 Eligible technologies
 Policy instrument type
 Offsets (uncovered emissions) International partnerships

 Policy design features affect cost, environmental effectiveness, and cost-effective role of sectors and companies

10

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Applying uniform GHG targets (e.g., 80% in 2050) acrosscompanies is unlikely to be cost-effective for society
2050 energy CO2 changes from 2010 for 450 ppm CO2eq scenarios(with global policy and full technology)

Scenarios find cost-effective
country % reductions differ
from global % reductions(also true for sectors and
GHG intensities)

global %reduction

Developed from EMF-27 study data (Weyant and Kriegler, 2014). Sample
of results shown. Some models did not report results for each country.
11

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Global emissions pathway attainability another uncertainty forcompanies
 Companies don’t know whether the world can achieve the global

pathways suggested–

2˚C (and below) pathways found to be extremely challenging – geophysically, technologically,
economically, and politically–And realization of near-term country pledges (NDCs) uncertain As a result, other global pathways are plausible–

12e.g., when global emissions might peak is an uncertainty for companies (e.g., 2020, 2030, 2040, 2050)

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Rising emissions abatement costs one indication of the challenge
Regional GHG emissions reduction costs and maximum global temperature
with increasing levels of regional emissions constraints

Source: Rose et al. (2017)13www.epri.com© 2019 Electric Power Research Institute, Inc. All rights reserved.

Model infeasibilities another indication of the challenge# models producing scenario / # models that tried# models producing scenario / # models that tried

Source: Krey et al. (2014)

Some cannot solve and absent
from database. 10-100% absent
when technology constrained.
14

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Uncertainty about pathway attainability implies even larger
range of global emissions pathways relevant to companies
Global net CO2 pathways consistent with 2˚CGlobal net CO2 pathways peaking before mid-century

Range and selectscenarios shown(n =408)(n =742)

For
companies,
range expands
due topathwayattainability
uncertainty.
Probabilities
could also be
considered.

Developed from
IAMC (2014)15www.epri.com© 2019 Electric Power Research Institute, Inc. All rights reserved.

Other risks (non-climate-policy) & company strategy also matter Climate policy risk for companies needs to be put in context with respect to other risks

to operations and investments
 Risk assessments also need to consider current company climate-related policy planning GHG emissions represent only one part of an asset’s or portfolio’s value to society

Ranges of 2050
changes in baseline
levels relative to 2020
for a subset of
economic andtechnologicalprojections

16

GDP
Energy Consumption
Electricity Consumption
Transportation Electricity Consumption
Natural Gas Price
Capital Cost NGCC
Capital Cost Nuclear
Capital Cost Solar CSP
Capital Cost Solar PV
Capital Cost Wind Onshorewww.epri.com

min
42%
-10%
9%
-7%
-20%
-24%
-13%
-26%
-65%
-56%

US

max
95%
26%
58%
3327%
183%
1%
34%
-3%
-10%
-6%

© 2019 Electric Power Research Institute, Inc. All rights reserved.

min
106%
41%
39%
6%
-22%
-24%
-3%
-26%
-65%
-26%

World

max
152%
72%
117%
4018%
129%
3%
50%
-3%
-10%
-6%

Developed from EMF-27
study data (Weyant andKriegler, 2014)

Despite broad ranges, there are robust insights
Insights found consistently across models and assumptions that provide a solid decision-making
foundation for companies and others

For instance An emissions pathway cost-effective for a given set of assumptions will not be cost-effective for every plausible future The cost-effective emissions reduction role of an economic sector is highly uncertain
 The more ambitious the climate objective, and the more constrained the set ofemissions mitigation options, the higher the emissions reduction costs and the rate of
scenario infeasibilities

 The emissions relationship with global temperature becomes increasingly uncertain thefiner the resolution of the emissions source

17

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Key insights for companies, investors, and others
 Individual company perspective: Essential for defining relevant uncertainties and company-specific context
 Scientific basis: Approaches and strategies should be based on scientific understanding to characterize

uncertainties and identify robust insights

 Cost-effective societal role of a company:–

A company’s role in reducing GHG emissions at the lowest cost to customers and society is highly uncertain–

It will be difficult to identify a unique company-level pathway or target that is cost-effective in all plausible futures (if choosing one,
uncertainties important to communicate)–

The cost-effective pathway or target for a company will likely differ from what is cost-effective at the global, country, and sector
level, as well as at other companies

 Uncertainty, flexibility, and robust strategies:–

Characterizing and incorporating the numerous uncertainties relevant to companies will be important (GHG policy one of many)–

Having flexibility in emissions reduction levels and how they are met will be important for containing societal costs–

Identifying a robust strategy that makes sense in different future contexts will be important

18

More than a target or pathway – an approach that recognizes uncertainty, provides flexibility, and can respond appropriately

www.epri.com© 2019 Electric Power Research Institute, Inc. All rights reserved.

Key insights represent principles for evaluating & developing
methodologies
A checklist for methodologies
Company analysis issues for methodologies
 Emissions scenarios used?
 Uncertainties considered and how?
––––Temperature-emissions
Global pathway attainability
Policy design
Non-climate-related Consideration of company-specific context?
 Uniform vs. varied GHG targets acrosscompanies?
 Consideration of flexibility options?
 Quantitative comparison of alternatives?
 Evaluation of strategy robustness?
19

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Scenario ranges are valuable information: lessons from Florence The set of results informs

planning by identifying
possibilities

 All decision-relevant

information. Anything lesscan mislead.

20

Note: key difference from global
emissions projections – hurricane
paths are forecasts (vs. projections)www.epri.com© 2019 Electric Power Research Institute, Inc. All rights reserved.

Summary remarks on company climate risk assessment
 Growing enthusiasm for climate risk

assessment and goals, but lacking ascientific basis

Grounding Decisions: A Scientific Foundation for Companies
Considering Global Climate Scenarios and Greenhouse Gas
Goals (#3002014510, www.epri.com)

 Need to slow down, get grounded, andeducate (companies AND stakeholders)–Significant knowledge available–

Understanding and proper use essential–

Embrace uncertainty, want flexibility, anddevelop strategies robust to alternative futures New EPRI study is an initial step in

informing analyses, discussions, decisions

 Finding the same or stronger insights for

1.5˚C scenarios

21

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Perspectives on the social cost of carbon

22

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The social cost of carbon (SCC) or other greenhouse gases
US Government global SCC estimate

US Government SCC rulemaking use
70

60

50

Frequency$42 of damages tothe world from atonne of CO2

Clean Power
Plan (2015)

40

30
Proposed
Medium- andHeavy-Duty
VehicleStandards (2015)20

23

But, what does $42 mean?

10

Little known about underlying modeling or
implied societal risks, or SCC use

0www.epri.com-20

0© 2019 Electric Power Research Institute, Inc. All rights reserved.

20

40

60

CAFE CAFE(2012) (2010)

80

100

120

140

CO2 Reduction Benefits (billion 2011$)

160

180

200

EPRI SCC estimation and use studies
EPRI study assessing SCC modeling

EPRI study assessing SCC use

Understanding the Social Cost of Carbon: A
Model Diagnostic and Inter-Comparison Study

Applying the Social Cost of Carbon: Technical
Considerations,” (www.epri.com, #3002004659)(Climate Change Economics Vol. 8, No. 2, 2017)
Available
OPEN
ACCESS

24www.epri.com© 2019 Electric Power Research Institute, Inc. All rights reserved.

Assessing SCC modeling component-by-component & overall
Reviewingmodeling & code,
programmingcomponents,
running diagnostic
scenarios,
comparing,
exploring multiple
perspectives

Component 1

Component 2

Component 3

 Examining the inner workings of the modeling 4 separate technical assessments – elucidating & assessing individual modeling components & overall

USG experimental design

 Learning about the raw intermediate modeling and behavior – undiscounted & disaggregated25

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Climate component assessment – global temperature responses
to 2100
Global mean temperature change

DICE
FUND
PAGE

Incremental global temperature change(from 2020 1 billion tC pulse)High emissions
futureLow emissions

High emissions
Low emissions
futureMeaningful differences in outcomes and sensitivity for the same inputs. Trace to modeling &implementation features (e.g., carbon cycle, non-CO2, forcing translation, pulse implementation).
26

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Damage component assessment – annual incremental damages
to 2300

$3.5

$3.5

$3.0

$3.0

$2.5

$2.5

$2.0

$2.0

$2.0
$1.5

$-

$(0.5)$(0.5)$(0.5)

2250

2200

2150

2100

2050

2000

2300
2000

$-

2250

$-

2200

$0.5

2150

$0.5

SLR

$0.5

2100

$1.0

2050

$1.0

2300
2000

$1.0

Agriculture

Cooling

SLR

Model specific features dominate incremental damages

27

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Noneconomic

Economic

2300

$1.5

2250

NonSLR$1.5

Discontinuity

2200

$4.0

Discontinuity
OECD non-economic
OECD economic
ROW non-economic
ROW economic
China non-economic
China economic
Sea level rise

PAGE

2150

FUND

2100

DICE

$4.5

OECD coolingOECD agriculture$4.0
ROW cooling
ROW agriculture$3.5
China cooling
China agriculture
Other benefits $3.0
Other damages
Sea level rise $2.5

$4.0incremental damages ($/tCO2)$4.5

Non-SLRSea level rise

2050

$4.5

Found fundamental SCC estimation & use issues that need to beaddressed
Issues that impact the scientific reliability of SCC estimates, CO2 reduction benefit
and net benefit calculations, and insights and conclusions
SCC estimation issues
 Individual model issues–––

Model-specific issues
Transparency and justification
Damage representations dated & dependent Multi-model framework issues
–
–
–
–
–
–

Transparency and justification
Structural uncertainty representation
Input and parametric uncertainty representation
Comparability and independence of results
Robustness of results unlikely
Multi-model approach – reconsider.

Source: “Understanding the Social Cost of Carbon: A Model Diagnostic and InterComparison Study,” Climate Change Economics, Vol. 8, No. 2, 2017.
28www.epri.com

SCC use issues
 Conceptual and methodological issues
 Different types of SCC estimates How to use multiple SCC values
 Consistency between benefit & cost calculations
 Accounting for net global CO2 changes (leakage =lower CO2 benefits)
 Valuing/pricing CO2 more than once Valuing non-CO2 GHGs

Source: “Applying the Social Cost of Carbon: Technical Considerations,”
http://eea.epri.com (under “Research,” “Integrated Assessment”).

© 2019 Electric Power Research Institute, Inc. All rights reserved.

Summary remarks on SCC (SC-GHG) estimation and use
 For the first time we understand the inner workings of the SCC (and SC-GHG) modelingused by both the Trump & Obama Administrations

 We find fundamental issues with the modeling and use
 Issues that undermine confidence in current results and insights
 We need to pursue immediate improvements given the need for estimates today–

Note: difficult to assess bias in current estimates given the issues and biases in both directions

 There are opportunities for immediate improvement
 Longer term improvement is also important, however, there are significant challenges toovercome

29

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Concluding comments
 For company climate policy risk assessment and GHG goal setting,companies, stakeholders, and methodologies need to slow down
and get grounded in science For the social cost of carbon, current model and use has

fundamental technical issues, but there are immediate
opportunities for improvement30

www.epri.com© 2019 Electric Power Research Institute, Inc. All rights reserved.

Thank you!
Steven Rose, Senior Research Economist
Energy & Environmental Analysis Research Groupsrose@epri.com, (202) 257-7053

31

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Resources32

Bistline, J and SK Rose, 2018. Social Cost of Carbon Pricing of Power Sector CO2: Accounting for Leakage and Other Social Implications
from Subnational Policies, Environmental Research Letters 13 014027.

Rose SK and J Bistline, 2016. Applying the Social Cost of Carbon: Technical Considerations. EPRI Report #3002004659 (Palo Alto, CA),
http://epri.co/3002004659.

Rose, SK, DB Diaz, GJ Blanford, 2017. Understanding the Social Cost of Carbon: A Model Diagnostic and Inter-Comparison Study,
Climate Change Economics 8 (2). doi: 10.1142/S2010007817500099.

Rose, SK, M Scott, 2018. Grounding Decisions: A Scientific Foundation for Companies Considering Global Climate Scenarios andGreenhouse Gas Goals. EPRI, Palo Alto, CA. #3002014510.



USG Interagency Working Group on Social Cost of Carbon, 2015. Technical Update of the Social Cost of Carbon for Regulatory Impact
Analysis Under Executive Order 12866, July.



USG Interagency Working Group on Social Cost of Carbon, 2016. Technical Update of the Social Cost of Carbon for Regulatory Impact
Analysis Under Executive Order 12866, August.

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Appendix

33

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Technical issues for companies & others to consider

34

1.

What is the relationship between a company and a climate goal?

2.

What does the 2˚C goal represent?

3.

How do potential alternative company strategies compare?

4.

How might non-climate-policy related risks and current
strategy be considered?

5.

Given uncertainties, what is a robust strategy?

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A broad range of global CO2 budgets consistent with 2˚C Wide range of cumulative emissions (carbon budgets) consistent with a temperature
IPCC scenarios category(CO2eq concentration in
2100, ppm)
1430-480

504-1423

63-88%

97-99%

2

480-530465-1692

39-68%

90-97%

3

530-580809-199916-46%

81-92%

4580-650

1037-1925

7-26%

65-86%

5

650-7201245-1767

5-12%

57-74%

6

720-1000

1424-2026

0-3%

17-45%

7> 10001524-2694

0%

2-8%

IPCC WGI (2013)35

www.epri.com

2011-2050 CO2
Probability of Probability ofbudgets instaying
staying
scenarios (GtCO2)
below 2˚C
below 3˚C

© 2019 Electric Power Research Institute, Inc. All rights reserved.

Developed from IPCC WGIII (2014) and IAMC (2014)

Model infeasibilities another indication of the challengee.g., Energy Modeling Forum 33rd Study on Feasibility of Large-Scale Global Bioenergy# models producing scenario / # models that tried
Full default
technology< 2˚C< 1.5˚C

High energy CO2budget(1600 GtCO2)
Low energy CO2budget(1000 GtCO2)
Very low energy
CO2 budget(400 GtCO2)

Advancedbioenergy
100% higher technology not No biofuel fromadvancedavailable until lingo-cellulosic
bioenergy tech2050
biomass

Bioenergy w/
CCS
technologies
not available

No advanced
bioenergy
technologies

Modernbiomass supply
max. 100 EJ/yr

11/11

10/10

10/10

11/11

10/11

10/11

9/9

11/11

8/10

7/9

10/11

6/11

5/11

8/9

6/10

6/10

5/10

5/10

0/10

0/10

2/10*

40% can’t solve and absent
from database. 50-100% whentechnology constrained.
36

www.epri.com* The two feasible scenarios had extremely high CO2 prices

Developed from Bauer, Rose, Fujimori et al. (2018)© 2019 Electric Power Research Institute, Inc. All rights reserved.

Despite broad ranges, there are robust insights
Insights found consistently across models and assumptions that provide a solid decision-making
foundation for companies and others

Global emissions must peak and decline for goals equal to or more ambitious than a 50% chance of limiting global
warming to 3˚CA range of emissions pathways is consistent with a particular temperature because of uncertainty about the futureAn emissions pathway cost-effective for a given set of assumptions will not be cost-effective for every plausible future

The cost-effective emissions reduction role of an economic sector is highly uncertainThe cost-effective annual GHG reduction level (%) for a country/sector will not equal the cost-effective global level (%)–

37

Assigning a global or other aggregate goal across countries and/or sectors will not be cost-effective

The more ambitious the climate objective, and the more constrained the set of emissions mitigation options, thehigher the emissions reduction costs and the rate of scenario infeasibilities

For the most ambitious temperature targets (2˚C and lower), the largest rate of scenario infeasibilities occurs whennegative emissions technologies (e.g., bioenergy with CCS, afforestation) are unavailable or constrainedThe emissions relationship with global temperature becomes increasingly uncertain the finer the resolution of theemissions source as more factors and interactions separate the source from global average temperature
www.epri.com© 2019 Electric Power Research Institute, Inc. All rights reserved.

Operationalizing the insights
The insights represent principles for evaluating methodologies, developing analyses, setting expectations

Company analysis issues for methodologies
 Emissions scenarios used?
 Uncertainties considered and how?
Temperature-emissions– Global pathway attainability– Policy design– Non-climate-related

General steps for operationalizing insights
1. Utilize existing science
2. Develop emissions ranges

–

–

3.

 Consideration of company-specific context?
 Uniform vs. varied GHG targets acrosscompanies?
 Consideration of flexibility options?
 Quantitative comparison of alternatives?
 Evaluation of strategy robustness?
38

www.epri.com

4.
5.
6.
7.
8.

Uncertainties in the literature support emissions
futures that exhibit slower growth, no growth,and declining, low, zero, and negative emissions

Specify alternative policy designs
Overlay company-specific context
Run preliminary analysis
Implement a scenario design
Identify risk management alternatives
Develop a robust strategy© 2019 Electric Power Research Institute, Inc. All rights reserved.

Evaluating methodologies – sample
Attainability uncertainty widens ranges even further
Issue to consider
Uncertainty in global
temperature-CO2 relationship for2˚C (cumulative 2011-2050
GtCO2)
Uncertainty in global
temperature-CO2 relationship for2˚C (annual changes in 2050
relative to 2010)

Uniform vs. varied GHG targets
across companies

39

EmissionsGlobal net

This study
Consistent with 2˚C
465 to 1692

SBTi

Ceres

UNEP FI pilot

–

–

1139

Global energy

324 to 1636

1085

–

1022

Global electric
Global net
Global energy
Global electric

94 to 642
14% to -96%
9% to -99%
-2% to -163%

335
–
-52%
-89%

–
–
–

261
-72%
-58%
-94%

U.S. net CO2eq-58% to -110%–

U.S. electric-44% to -170%–

Uniform targets found unlikely to be costeffective

Proposes globally
uniform sectoral
targets-81% (80%relative to 1990)-92% (90%relative to 1990)

Recent methodologies do not represent the uncertainty evident in the literature regarding
emissions pathways consistent with limiting warming to 2˚C.

•

They also propose applying uniform targets across companies© 2019 Electric Power Research Institute, Inc. All rights reserved.

–

Proposes uniform Implies uniform
target for all
targets within
utilities
sector segments•www.epri.com–

Fundamental issues with SCC models and USG framework
The study offers perspectives on models & differences not previously available
We observe fundamental scientific issues, and improvement opportunities for greater confidence in results

Fundamental Multi-Model Framework Issues

Fundamental Individual Model IssuesModel-specific issues–––

DICE – no climate feedback, CO2 pulse, quadratic
damages, implied adaptation, limited parametric
uncertainty, damages dependent on other models
FUND – partial radiative forcing, long temperature lag,potential for climate benefits and adaptation
PAGE – non-CO2 forcing, ECS implementation, slow
carbon cycle, CO2 pulse, regional damage scaling,
undefined damages, fixed adaptation, damages
dependent on other models

 Transparency and justification for individualmodel structure and behavior

Transparency and justification
 Structural uncertainty representation
 Input and parametric uncertainty representation
 Comparability and independence of results Robustness of results unlikely
 Multi-model approach – reconsider.


Damage representations dated and dependent

Challenges (transparency, justification, comparability, andindependence)– Consider developing a model component-by-component–

NAS SCC Committee agreed that a new approachand model components were needed (NAS, 2017)
Rose et al (2017)40

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