Download Understanding the Social Cost of Carbon

Understanding the Social Cost of Carbon:
A Technical Assessment
Steven Rose
Energy & Environmental Analysis Research Group, EPRI
U.S. Energy Association
December 8, 2014
The Social Cost of Carbon (SCC)
$37 per metric ton of CO2
U.S. Government’s “central” SCC estimate of the global societal
damages from a metric ton of today’s CO2 emissions
© 2014 Electric Power Research Institute, Inc. All rights reserved.
2
US Government SCC Values
US Government Social Costs of Carbon by Discount Rate
$200
$180
$160
3% (95th
percentile)
Solid = USG (2013) estimates
Dashed = USG (2010) estimates
2007$ / CO2
$140
$120
$100
2.5%
$80
“Central”
values
3%
$60
$37
$40
5%
$20
$0
2010
2020
2030
2015
Source: Developed from USG (2010) and USG (2013)
© 2014 Electric Power Research Institute, Inc. All rights reserved.
3
2040
2050
Why Should We Care?
• SCC is an estimate of the damages to society from CO2
• SCC is in use broadly in USG rulemakings (going back to 2008) –
states and others using as well
• For foreseeable future, CO2 (all GHGs) will be regulated under the
Clean Air Act and efficiency policies
• USG legally obligated to value CO2 (9th Circuit)
• USG SCC values recently updated in 2013 (significantly higher)
– Revised SCC estimates attracting a great deal of attention
– Variety of issues being raised – legal, process, & technical
• Two key technical challenges
– Robustness – establishing confidence in SCC estimates
– Application – using estimates properly
• General lack of technical information and understanding
© 2014 Electric Power Research Institute, Inc. All rights reserved.
4
The Social Cost of Carbon (SCC)
$37 per metric ton of CO2
U.S. Government’s “central” SCC estimate of the global societal
damages from a metric ton of today’s CO2 emissions
What does this mean?
© 2014 Electric Power Research Institute, Inc. All rights reserved.
5
Trying to Better Understand the SCC
• Currently difficult to interpret and evaluate the SCCs
• EPRI has undertaken an initiative aimed at better
understanding and advancing methods
– Developing detailed understanding of modeling
– Evaluating alternatives
Team: Steven Rose, Delavane Turner, Geoffrey Blanford,
John Bistline, Francisco de la Chesnaye, Tom Wilson
© 2014 Electric Power Research Institute, Inc. All rights reserved.
6
The Social Cost of Carbon (SCC)
Definition: The net present value of global climate change
impacts from one additional net global tonne of carbon dioxide
emitted to the atmosphere at a particular point in time
Socioeconomics
Emissions (CO2, etc.)
Temperature
Climate damages
Population
Income
2000
2000
2000
2000
2000
Dashed = after
CO2 pulse
CO2 pulse
2300
2300
2300
© 2014 Electric Power Research Institute, Inc. All rights reserved.
2300
2300
2000
2000
2300 2000
2300
2000
2300
2300
SCC in 2020 is the discounted value of the
additional impacts from the marginal
emissions increase in 2020
7
Types of Impacts Being Monetized
• Health
Based on sector specific
• Agriculture
impacts studies in the
literature
• Forestry
• Sea level
• Water resources
• Energy consumption
(space cooling & heating)
• Migration
• Hurricanes
• Ecosystems
• Catastrophic
Impact types included and formulations vary by model
© 2014 Electric Power Research Institute, Inc. All rights reserved.
8
Number of estimates
Vast Range of SCC Estimates Have Been
Produced
40
Histogram of SCC Estimates in the Literature
35
(Derived from Tol 2008)
30
Note: not a distribution
25
Range reflects differences in
models, assumptions, and
impacts included
(and not apples-to-apples)
20
15
10
5
-$3 to $655/tCO2
$(3)
$25
$52
$79
$106
$134
$161
$188
$215
$243
$270
$297
$325
$352
$379
$406
$434
$461
$488
$515
$543
$570
$597
$625
$652
$679
0
1995$ per metric ton CO2 for 1995 emissions
Developed from Tol (2008) meta
analysis of SCC estimates
© 2014 Electric Power Research Institute, Inc. All rights reserved.
9
US Government SCC Values
US Government Social Costs of Carbon by Discount Rate
$200
$180
$160
Solid = USG (2013) estimates
Dashed = USG (2010) estimates
$140
2007$ / CO2
3% (95th
percentile)
Each point (e.g., $37)
result of significant
aggregation
$120
$100
2.5%
$80
“Central”
values
3%
$60
$37
$40
5%
$20
$0
2010
2020
2030
2015
Source: Developed from USG (2010) and USG (2013)
© 2014 Electric Power Research Institute, Inc. All rights reserved.
10
2040
2050
USG SCC Approach
Feature
Detail
Multiple SCC models
3 models – DICE, FUND, PAGE
Standardized uncertainties
- 5 reference socioeconomic and emissions scenarios (each
extended from 2100 to 2300)
- 1 distribution for the climate sensitivity parameter
Model specific parametric uncertainties
In FUND and PAGE climate and damage components
Standardized discounting
3 constant discount rates – 2.5%, 3%, and 5%
Thousands of SCC results
150,000 SCC estimates for a given discount rate and year (3
models x 5 socioeconomic scenarios x 10,000 runs each)
Aggregation of results
- Average of 150,000 results for each discount rate and year
th
th
- “3% (95 percentile)” value is 95 percentile from distribution
of 150,000 results with 3% discounting
 USG estimates are the result of significant aggregation – over
time, world regions, impact categories, many scenarios, & models.
 Making sense of the estimates requires delving into these details.
© 2014 Electric Power Research Institute, Inc. All rights reserved.
11
Our Study’s Assessment Approach
• Examine the inner workings of the models to elucidate the
key drivers and assess the main elements
• Specifically, learn about and assess the raw modeling
and results – i.e., undiscounted and disaggregated to
underlying facets
• 4 separate technical assessments
– 3 assessments of modeling causal chain components
• Reviewing modeling, programming component, running
diagnostics, comparing
• Exploring many perspectives
– 1 overall assessment of the USG experimental design
© 2014 Electric Power Research Institute, Inc. All rights reserved.
12
Technical Assessment by Causal Component
Elucidating and assessing each component
Socioeconomics
Emissions (CO2, etc.)
Temperature
Climate damages
Population
Income
2000
2000
2000
2000
2000
Dashed = after
CO2 pulse
CO2 pulse
2300
2300
2300
2000
2000
2300 2000
2300
2000
2300
2300
Component 1
© 2014 Electric Power Research Institute, Inc. All rights reserved.
Component 2
13
Component 3
2300
2300
Study Objective
• Improved understanding of SCC modeling and estimates
that informs public discussion, future SCC modeling and
application, and future climate research
© 2014 Electric Power Research Institute, Inc. All rights reserved.
14
Key Questions
• How do the models behave, and are they different?
• What drives differences?
• Are differences useful information?
• Are there alternative uncertainties to consider?
• Are there additional uncertainties to consider?
• Are the estimates robust (insensitive to alternatives)?
• Are there opportunities to improve the overall USG SCC
approach?
© 2014 Electric Power Research Institute, Inc. All rights reserved.
15
Socioeconomics & Emissions Component
Assessment
Elucidating and assessing each component
Socioeconomics
Emissions (CO2, etc.)
Temperature
Climate damages
Population
Income
2000
2000
2000
2000
2000
Dashed = after
CO2 pulse
CO2 pulse
2300
2300
2300
2000
2000
2300
2300
Component 1
© 2014 Electric Power Research Institute, Inc. All rights reserved.
16
2300 2000
2300
2000
2300
2300
USG’s Standardized Socioeconomic & Emissions
Inputs into SCC Models
500
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17
2300
2250
0.0
2300
2300
2250
2200
2150
2100
2050
0.5
2200
-3
1.0
2150
-2
2300
2250
2200
2150
2100
-1
2050
0
We observe
inconsistencies in
implementation across
models
1.5
2100
1
20
2.0
2000
2
Non- CO2 Kyoto Forcing (W/m2)
3
2000
Land Net CO2 (GtCO2)
4
40
Non-CO2 forcing
2.5
2050
Global land CO2
5
60
0
2000
2300
2250
2200
2150
2100
2050
2000
0
80
2250
0
100
2200
2
1000
120
2150
USG1
USG2
USG3
USG4
USG5 (550 avg)
1500
140
2100
6
2000
2050
8
Global FF&I CO2
160
Fossil & Industrial CO2 (GtCO2 )
GDP (trillion 2005 US$)
Population (billion)
10
4
Global GDP
2500
2000
Global population
12
Socioeconomic and Emissions Uncertainty
EMF-22 baselines
USG1
USG2
USG3
USG4
USG5 (550 avg)
120
100
80
USG2
USG1
60
40
Global GDP (trillion 2005 US$)
400
USG1
350
300
USG2
250
200
150
100
20
50
USG2  high emissions from low econ growth
Uncertainty in socioeconomic
structure not considered
2100
2090
2080
2070
2060
2050
2040
10
USG2
USG1
8
6
4
2
2100
2090
2080
2070
2060
2050
2040
2030
18
2020
0
2000
© 2014 Electric Power Research Institute, Inc. All rights reserved.
Global population (billion)
USG1  low emissions from high econ growth
2030
Baseline global population
12
Very different socioeconomic structures
2020
2100
2090
2080
2070
2060
2050
2040
2030
2020
2010
0
2010
2000
0
2010
140
Baseline global fossil & industrial CO2
2000
Fossil & Industrial CO2 (GtCO2)
Baseline global GDP
450
Is Socioeconomic Structure Important?
• Defines the relationship between society & emissions
• Implications for both climate AND damage results
– Socioe structure  Emissions  Climate change
– Socioe structure  Societal size & composition  climate
vulnerability & adaptation
Drivers of climate damages in the models
Total
Per Capita
Pop
Temp
CO2 Conc
Income
Income Size/Comp
DICE
X
X
FUND
X
PAGE
X
X
X
X
X
X
Other
X
Sensitivity of damages explicitly evaluated in damage
component assessment
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19
X
Socioeconomic/Emissions Component
Assessment Key Observations
• Inconsistencies to address
– Implementation of standardized socioe/emissions inputs
– Socioe/emissions extensions to 2300
• Additional uncertainties to consider
– Range of socioe/emissions, socioe structure, 2300 extensions
• Some futures not equally likely and shouldn’t be weighted
as such
• Average “policy” socioeconomic & emissions scenario is
problematic
© 2014 Electric Power Research Institute, Inc. All rights reserved.
20
Climate Modeling Component Assessment
Elucidating and assessing each component
Socioeconomics
Emissions (CO2, etc.)
Temperature
Climate damages
Population
Income
2000
2000
2000
2000
2000
Dashed = after
CO2 pulse
CO2 pulse
2300
2300
2300
2000
2000
2300
2300
Component 2
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21
2300 2000
2300
2000
2300
2300
Climate Modeling Structure
Climate Modeling Structural
Characteristics
Atmospheric concentrations
• Structural differences
across the three models in
all characteristics
CO2
Non-CO2 Kyoto
• Different model specific
parametric uncertainties
considered across models
Non-CO2 non-Kyoto
Radiative forcing
CO2
Non-CO2 Kyoto
Non-CO2 non-Kyoto
Global mean temperature
Regional temperatures
Climate feedback
Time steps
© 2014 Electric Power Research Institute, Inc. All rights reserved.
22
We Isolate the Component & Run Diagnostics
Diagnostic Scenarios: We standardize the set of emissions & radiative forcing
inputs (CO2 & non-CO2) and run deterministic and probabilistic scenarios
160
E.g., standardized total CO2 projection input
140
USG2
billion metric tons CO2
120
100
2 Scenarios
80
USG2 = higher
emissions scenario
60
USG5 = lower
emissions scenario
40
USG5
20
0
2000
2050
© 2014 Electric Power Research Institute, Inc. All rights reserved.
2100
2150
23
2200
2250
2300
Projected Global Temperatures
5
Driven by modeling
differences in
carbon cycle, nonCO2 forcing, forcing
to temperature
translation, and
climate sensitivity
responsiveness
deg C above pre-industrial
4
3
For the same
emissions
scenario, 1˚C
variation
USG2
DICE
FUND
PAGE
2
USG5
1
0
2000
2010
2020
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2030
2040
2050
2060
24
2070
2080
2090
2100
Projected Incremental Temperatures
(for a 1 billion tC pulse in 2020)
0.0025
For the same incremental emissions
scenario, significant differences in the
incremental temperature change over time
Always higher response off
lower emissions scenario
USG5
0.002
DICE
0.0015
deg C
FUND
USG2
PAGE
0.001
Driven by differences in
incremental emissions
implementation and climate
modeling
0.0005
0
2000
2010
2020
© 2014 Electric Power Research Institute, Inc. All rights reserved.
2030
2040
2050
2060
25
2070
2080
2090
2100
Sensitivity of Climate Responses
The climate models are not equally
sensitive to alternative assumptions
Incremental change in global temperature
in 2100 varying climate sensitivity
Temperature to emissions
0.006
Change in temperature (Deg C)
Most – DICE, Least - FUND
Temperature to climate sensitivity
Most – PAGE, Least – FUND
0.005
PAGE most
sensitive
0.004
1.5
0.003
3.0
4.5
0.002
6.0
0.001
0
© 2014 Electric Power Research Institute, Inc. All rights reserved.
26
Climate
sensitivity
DICE FUND PAGE
DICE FUND PAGE
USG2
USG5
Model Specific Uncertainty – Temperature
(e.g., USG2 with climate sensitivity 3˚C)
FUND
PAGE
6
6
5
5
5
5%
4
4
4
25%
3
2
6
FUND - USG2
PAGE - USG2
degrees C
degrees C
degrees C
DICE
3
2
50%
3
1
1
0
2000
0
2000
0
2000
2100
2050
2100
Models considering significantly different
uncertainty – PAGE substantially more
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27
75%
95%
2
1
2050
1%
99%
Mean
Det
2050
2100
Model Specific Uncertainty – Incremental Temp
(e.g., USG2 with climate sensitivity 3 degC)
DICE
0.0030
DICE - USG2
PAGE
0.0030
FUND - USG2
0.0025
0.0025
0.0020
0.0020
0.0020
0.0015
0.0010
0.0015
0.0010
0.0005
0.0005
0.0000
2000
degrees C
0.0025
degrees C
degrees C
0.0030
FUND
2050
2100
0.0000
2000
-0.0005
PAGE - USG2
5%
25%
50%
0.0015
75%
0.0010
95%
0.0005
2050
2100
0.0000
2000
-0.0005
Models considering significantly different
uncertainty – PAGE substantially more
© 2014 Electric Power Research Institute, Inc. All rights reserved.
1%
28
99%
Mean
2050
2100
Det
USG vs Other Modeling – Incremental Temp
(for a 1 billion tC pulse in 2020)
0.0025
RCP3PD
0.002
DICE
0.0015
deg C
FUND
PAGE
0.001
RCP8.5
0.0005
RCP8.5 = higher emissions scenario
RCP3PD = lower emissions scenario
0
2000
2010
2020
© 2014 Electric Power Research Institute, Inc. All rights reserved.
2030
2040
2050
29
2060
2070
2080
2090
2100
USG vs Other Modeling – Incremental Temp
(for a 1 billion tC pulse in 2020)
0.0025
RCP3PD
0.002
DICE
0.0015
deg C
FUND
PAGE
0.001
MAGICC
(Default)
MAGICC
(Hadley)
RCP8.5
0.0005
Notably different responses from more
sophisticated climate modeling
0
2000
2010
2020
© 2014 Electric Power Research Institute, Inc. All rights reserved.
2030
2040
2050
30
2060
2070
2080
2090
2100
USG vs Other Modeling – Temp Uncertainty
(e.g., RCP8.5)
8
Deg C above pre-industrial
7
6
5
Running climate
components
probabilistically
(including climate
sensitivity uncertainty)
Dashed = 17th-83rd
percentiles
Medians
MAGICC
FUND
4
PAGE
3
DICE
2
1
0
2000
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
Notably different probabilistic result from more
sophisticated climate & probabilistic modeling
© 2014 Electric Power Research Institute, Inc. All rights reserved.
31
Climate Component Assessment Key
Observations
• Significant differences in climate responses across models
(to 2100 and 2300, in total and incremental climate)
• Important climate component structural differences
• Implementation inconsistencies affecting results
• Models representing & sampling different uncertainty
spaces
• Alternative climate modeling produces different results
• Additional uncertainties to consider
– Alternative climate modeling, alternative parametric uncertainty,
alternative climate sensitivity distribution assumption
© 2014 Electric Power Research Institute, Inc. All rights reserved.
32
Climate Damages Component Assessment
Elucidating and assessing each component
Socioeconomics
Emissions (CO2, etc.)
Temperature
Climate damages
Population
Income
2000
2000
2000
2000
2000
Dashed = after
CO2 pulse
CO2 pulse
2300
2300
2300
2000
2000
2300 2000
2300
2000
2300
2300
Component 3
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33
2300
2300
Damage Modeling
Structure
Structural differences across models
Different model specific parametric
uncertainties
DICE
FUND
PAGE
Regions
1 global region
16 regions
8 regions
Sectors
2 sectors
14 sectors
4 sectors
Sea Level Rise,
Aggregate nonSLR
Sea Level Rise, Agriculture, Forests,
Heating, Cooling, Water Resources,
Tropical Storms, Extratropical Storms,
Biodiversity, Cardiovascular
Respiratory, Vector Borne Diseases,
Morbidity, Diarrhea, Migration
Sea Level Rise,
Economic,
Non-economic,
Discontinuity
Damage
drivers
Temperature, total
income
Temperature (global & regional), CO2
conc, ocean temp, population (size,
composition), income (total, per
capita), technological change
Regional temperature,
income (total, per capita),
regional damages scaled
off EU
Damage
specifications
Quadratic functions
Various functional forms
Power functions
Adaptation
Implicit (within
calibrated net
responses)
Mostly implicit, explicit for agriculture &
SLR, increased resiliency with per
capita income
Exogenous adaptation
policy
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34
We Isolate the Component & Run Diagnostics
Diagnostic Scenarios: We standardize climate & socioeconomic
inputs and run deterministic and probabilistic scenarios
Standardized input projections
6
USG2
4
USG5
1500
ppm
5
1000
3
2
500
1
2100
2150
2200
2250
2300
2100
2150
2200
2250
2300
2000
2300
2250
2200
2150
2100
1600
Global Population
Global GDP
1400
1200
trillion $2005
8
Regional population
& GDP
6
4
2
1000
800
600
400
200
35
2300
2250
2200
2150
2100
2050
2000
© 2014 Electric Power Research Institute, Inc. All rights reserved.
2050
0
0
2000
10
2050
0
0
12
billion
CO2 Concentration
2000
7
2050
USG5 = lower
temp scenario
(~2 deg C by
2100)
Global Mean Temperature
8
2000
USG2 = higher
temp scenario
(~4 deg C by
2100)
2500
9
degrees C above pre-industrial
2 Scenarios
Projected Total Global Damages
For the same
temperature &
socioeconomic
scenario, ~3x
variation in
damages
Driven by differences in
damage modeling
structure &
parameterization
For the same
temp &
socioecon
scenario, net
damages to
net benefits
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36
Projected Incremental Global Damages
(standardized climate signal from a 1 billion tC pulse in 2020)
For the same
incremental
temperature
change scenario,
~4x variation in
incremental
damages
Driven by differences
in damage modeling
structure &
parameterization
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37
Damage Responsiveness to Temperature –
Global Damages
Total climate damages as a function of global temperature
2050 w/ GDP
~$120T
2100 w/ GDP
~$270T
DICE and PAGE damages more responsive to
warming
Figures with a USG2 reference socioeconomic condition
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38
Damage Responsiveness to Income –
Global Damages
Total climate damages as a function of non-OECD income
2050 w/ 1.8˚C
2100 w/ 4˚C
FUND with increasing benefits with income at lower warming levels.
DICE & PAGE more responsive to income at higher warming levels.
Figures with a USG2 reference climate condition
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39
Damage Responsiveness to Temperature –
Sectoral Damages
2050 sectoral climate damages as a function of global temperature
Sectoral damages differ in
sign (damage or benefit) and
responsiveness to warming
2050 USG2
Non-SLR
ALL
DICE
FUND
Cooling
Non-economic
Economic
SLR
Discontinuity
Heating
Agriculture
Particular sectors driving results
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40
PAGE
Water resources
SLR
Damage Responsiveness to Temperature –
Regional Damages
2050 regional climate damages as a function of global temperature
China
PAGE
2050 USG2
US
FUND
EU
Regional damages not equally responsive to warming. FUND with net
benefits for some regions. PAGE with net damages for all regions. FUND
modeling individual regions. PAGE scaling damages off EU damages.
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41
Key Parts of Incremental Damages
(USG2 scenario to 2300)
2100
2100
2100
Discontinuity
NonSLR
China
cooling
Non-econ
China
agriculture
ROW
cooling
SLR
Economic
ROW
agriculture
Model specific features dominate incremental damages
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42
SLR
Model Specific Uncertainty – Incremental Global
Damages (e.g., USG2 temperature & socioeconomics)
FUND has
broader
distribution
with larger tails
Means
Models considering significantly different damage
uncertainty – FUND modeling significantly more than PAGE
and DICE, but PAGE has higher mean
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43
Damage Specification Literature Sources
Model
(version)
Damage
formulations based
on older climate
impacts literature,
with some
formulations based
on those from the
other models
Damage type
Study
Basis
DICE
(2010)
Aggregate non-SLR
IPCC (2007b), Tol (2009)1
SLR coastal impacts
FUND
(v3.8)
Agriculture
Undocumented
Kane et al. (1992), Reilly et al. (1994),
Morita et al. (1994), Fischer et al.
(1996), Tsigas et al. (1996)
Tol (2002b)
Perez-Garcia et al. (1995), Sohngen et
al. (2001)
Tol (2002b)
Downing et al. (1995), (1996)
Hodgson and Miller (1995)
Downing et al. (1995, 1996)
Downing et al. (1995, 1996)
Hoozemans et al. (1993), Bijlsma et al.
(1995), Leatherman and Nicholls
(1995), Nicholls and Leatherman
(1995), Brander et al. (2006)
WHO Global Burden of Disease
(2000)2
WHO Global Burden of Disease (2000)
Martin and Lefebvre (1995), Martens et
al. (1995, 1997), Morita et al. (1995)
Link and Tol (2004)
Forestry
Energy
Water resources
Coastal impacts
Diarrhoea
Vector-borne diseases
PAGE
(2009)
Calibration
Income elasticity
Calibration
Income elasticity
Calibration
Income elasticity
Calibration
Income elasticity
Calibration
Calibration
Income elasticity
Calibration
Income elasticity
Cardiovascular and
respiratory mortality
Martens (1998)
Storms
Ecosystems
CRED EM-DAT database, WMO
(2006)
Toya and Skidmore (2007)
Pearce and Moran, (1994), Tol (2002a)
SLR
Anthoff et al. (2006)4
Income elasticity
Calibration
Calibration &
income elasticity
Economic
Warren et al. (2006)5
Calibration
Noneconomic
Warren et al. (2006)
Calibration
DICE, FUND,
PAGE
DICE, FUND,
PAGE
Calibration
DICE, FUND
Discontinuity
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Calibration
Links to SCC
models
DICE, FUND,
PAGE
Adaptation costs
Calibration
3
Lenton et al. (2008), Nichols et al.,
(2008), Anthoff et al. (2006), Nordhaus
(1994)6
44 Parry et al. (2009)
Calibration
Calibration
FUND
Damage Component Assessment Key
Observations
• Significant differences in damage responses across models
(to 2100 and 2300, in total and incremental damages)
• Important damage component structural differences
• Model specific features driving results, e.g.,
– DICE – damages increase quadratically
– FUND – agricultural CO2 fertilization, cooling demand, China
damages, adaptation
– PAGE – regional scaling, non-economic damages, discontinuity
damages, adaptation
• Models representing & sampling different uncertainty spaces
• Additional uncertainty to consider – 2013 revisions
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Overall Experimental Design Assessment
1.
2.
3.
4.
5.
6.
USG SCC experimental design features
Multiple models
Standardized uncertainties
Model specific parametric uncertainties
Standardized discounting
Tens of thousands of SCC estimates
Aggregation of estimates into USG SCC values
© 2014 Electric Power Research Institute, Inc. All rights reserved.
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Experimental Design Issues
• Significant structural differences across models – Do they reflect
differences in expert opinion? e.g.,
– Socioeconomic/emissions – different sets of emissions and radiative forcing
– Climate – carbon cycle, climate sensitivity, feedbacks, uncertainty
– Damages – unique model specific factors that dominate results
• Consideration of uncertainty – we find reasonable alternative specifications,
additional uncertainties, and artificial variation
• Comparability and independence of model results – Inconsistencies across
modeling (implementation, structural, uncertainties) & inter-model relationships
raise questions about statistical comparability which is required for averaging
• Robustness of overall results – Current results may not be robust (i.e.,
insensitive to reasonable alternatives) given our observations regarding (1)
model sensitivity, and (2) existence of alternative assumptions and modeling
• Experimental design challenges – Issues with the overall design, in particular
the multi-model approach (with consistency and comparability issues)
© 2014 Electric Power Research Institute, Inc. All rights reserved.
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Recommendations
1. Internal review of the modeling – to evaluate differences, improve
comparability and uncertainty representation, and enhance robustness
2. Revisit experimental design – worth revisiting given challenges of
multi-model approach (e.g., chose best approach for each component)
3. Evaluate robustness – useful given sensitivity of models and issues
with uncertainty considered. Will increase confidence in results.
4. Peer review the approach and models – USG SCC approach is
novel and peer review would be valuable. Model review also practical
given regulatory use.
5. Provide additional documentation and justification – will facilitate
communications & interpretation, and increase public confidence
6. Provide application guidance – SCC application also an issue,
guidance on proper application needed
© 2014 Electric Power Research Institute, Inc. All rights reserved.
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Concluding Remarks
• The social cost of carbon is important
• However, the USG estimates are difficult to interpret and
assess
• Better understanding of the modeling and what the estimates
represent is needed
– To inform public discussion,
– Improve SCC modeling and application, and
– Facilitate climate research broadly – impacts analyses in
general, climate science, climate economics, & integrated
assessment
© 2014 Electric Power Research Institute, Inc. All rights reserved.
49
New Study
Understanding the Social Cost of
Carbon: A Technical Assessment
http://epri.co/3002004657
(full report & ES downloads)
 Objective: inform public social cost
of carbon (SCC) discussion, future
SCC modeling and use, and climate
research broadly
© 2014 Electric Power Research Institute, Inc. All rights reserved.
50
Thank You!
Questions/comments:
Steven Rose
[email protected]
202-293-6183
© 2014 Electric Power Research Institute, Inc. All rights reserved.
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