Climate Stabilization Scenarios:
New Integrated Assessment Approaches
f IPCC AR5 andfordR
Recentt IIASA SScenariosiNebojšša NakiNeboj
Nakiććenovi
enovićć
International Institute for Applied Systems Analysis xx
Technische Universität Wien xx
naki@iiasa.ac.at

IIASA--RITE International Symposium, Keidanren Kaikan – 3 March 2009
IIASA

Scenarios:• Provide a framework for decision
makingki whichhi h ill
illuminatesi t ththeimpact associated with alternative
courses off actionti• Facilitate the interpretation ofpossible future states• Include
I l d elements
lt ththatt cannott beb
formally modeled• Aimed at challenging prevailingmind sets
Nakicenovic

#2

2009

Proximate and Ultimate Drivers
Proximate Drivers
Population

ValuesVlanddNeeds

EconomyTechnology

Governance

Knowledge andUnderstanding

PowerP
Structure

CultureUlti
Ultimatet D
Driversi

Source: Paul Raskin, 2002

Urbanization
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1800

Nakicenovic

1850

1900

1950

2000

Source: Grübler, 2007

2050

#4

2100

2150

2009

Education
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1800

Nakicenovic

1850

1900

1950

2000

Source: Lutz, 2007

2050

#521002150

2009Democratization
100%
90%80%70%60%50%40%30%20%
10%
0%
1800

Nakicenovic

1850

1900

1950

2000

Source: Modelski, 2002

2050

#621002150

2009

World Primary Energy
500
Renewable

Primary Energy (EJ)P

400

Microchip Nuclear

Commercial
aviation

300

200

100

NuclearenergyGas

Oil

Television

Steam
engineElectric
motor

GasolineengineVacuum
tube

Coal

01850

Nakicenovic

Biomass

1900

1950

2000

#7

2009

Warmest 12 years:

1998,2005,2003,2002,2004,2006,, Rising,
Global Mean Temperatures
p, , , , areg
2001,1997,1995,1999,1990,2000

PeriodRate

50 0.1280.026
100 00.0740.0180740 018

Years /decade

INTERGOVERNMENTAL PANEL ON CLIMATE CHNGE (IPCC)

...and with financial woes spreadingt thetoth "real" l economy “ …
Developing
countries

Real GDP (% change), 1980-2009
86

High-income
countries

42

1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008

0Nakicenovic

Source: World Bank, 2009

#92009Dimensions of Transition
TechnologyGovernance
Economic
SocialDemographic
Knowledge
Values

Source: Paul Raskin, 2002

Global Population Projections
World Population (SRES, n=40) (pre SRES, n=62)

20

pre SRES range

pre SRES

10SRESSbillion

15

50
1940

1960

Nakicenovic

1980

2000

2020

2040

2060

2080

#1121002009

Global Population Projections
World Population (post SRES, non intervention, n=64)

20

post SRES, non intervention range
Medianbillion
n

15

10

50
1940

Nakicenovic

1960

1980

2000

2020

2040

2060

2080

#1221002009GDP Growth Rates and Affluence
A1

Annual growth rateAe of GDP, percent

10

Case A

China
8

B1

6JapanChina,
TaiwanGermany

DCs

B2

Italy

4

Case AOECD

Case B

2India

A2

0100

REFs
Case C1000

10000100000GDP per capita, US(1990)$

Nakicenovic

#13

2009

GDP Growth Rates and Affluence
A1

Annual growth rateAe of GDP, percent

10

Case A

China
8B16Japan
China,Taiwan
GermanyDCs

B2Italy

4Case AOECD

Case B

2India

A2

0100

REFs
Case C

1000

10000

100000GDP per capita, US(1990)$

Nakicenovic

#14

2009

Surface Temperature
pChangeg

AOGCM projections for illustrative SRES scenarios

INTERGOVERNMENTAL PANEL ON CLIMATE CHNGE (IPCC)

Globbal warm
ming (oC))

Vulnerabilityy of Key
y Sectors

A2
B1
B1
520

INTERGOVERNMENTAL PANEL ON CLIMATE CHNGE (IPCC)

Long-Term Stabilization Profiles
A2

B1~$100/tCO$100/tCO2

RCP Stabilization Profiles

Initial Scenarios
4 RCPs
RCP – few
fstabilizationbili i targets (3)All modeling groups
Sensitivity Scenarios with specific research focus
Selected group of models for each topic
Baseline Uncertainty

Interim-targets andO
OvershootTechnology (e.g.,limited portfolio)

Limited regional
participation??...

Climate and ESS Models
Baseline and stabilization climate projections
Carbon fluxes and other feedbacks
Source: After Keywan Riahi, 2006

Intended uses and limits
Intended uses
 Input to CMs
 To facilitate ppattern scalingg
 To explore ranges of socioeconomic conditions
 To explore
pclimate implications
pof spatialpforcinggpatterns

Limits Not forecasts or absolute bounds
 Not policy prescriptive
 Socioeconomics underlying each RCP are notunique; and, across RCPs, are not a set

20

REPRESENTATIVE
CONCENTRATITON PATHWAYSFORCING AGENTS

GHG Emissions and Concentrations from IAMs
 Greenhouse gases:

CO2, CH4, N2O, CFCs, HFC’s,PFC’s, SF6
 Emissions of chemically active gases: CO, NOx, NH4,VOCs Derived
D i d GHG’
GHG’s: ttropospherich i O3
 Emissions of aerosols: SO2, BC, OC Land use and land cover21

2 6 W/m2 or 2
2.6
2.9
9 W/m2?
Which scenario for the low (<3W/m2) RCP?
Noordwijkerhout debate over what it means to be “compatible“
tibl with
ith theth full
f ll range off stabilization,t bili ti

mitigation, and baseline emissions scenarios available
in the current literature”

22ProposedpExtensions to 2300!


RCP8.5: fix emissions at 2100
levels, derive concentrations

16RCP8.5

RCP 4.5 / 6.0: fixconcentrations, deriveconsistent emissions
RCP2.6/2.9:
 Fix emissions at 2100
levels, derive consistentconcentrations
 Other 2.9 option: allow
emissions to fall to zeroor negative, and fix
LandL
Landd-use: scalel croplandl d andd
pasture land with population(current proposal); or holdconstant (alternative)
For ESM data, harmonize theunique IAM extended
emissions and concentration
data with a single
g climatemodel (e.g. MAGICC)

Nakicenovic

14RCP6.0
RCP4.5
RCP2.9-const2100

12

Radiative forciing (W/m2)R



RCP2.9-zero2300
RCP2.9zero2300
RCP2.9-negative2300
RCP2.610864202005

2055

2105

2155

#232205

2255

2305

2009

International IAM Consortium

Facilitate
ac tate tthe
e coocoordinationd at o oof sce
scenarioa o dedevelopmente op e t eefforts
o ts
International Institute for Applied Systems
Analysis (IIASA)

Energy Modeling Forum (EMF)
Stanford University

Australian Bureau of Agricultural and Resource
Economics (ABARE)- Hom Pant
Bundeswehr
B dh University,U ii Munich
M i h- Stefan Pickl
Business Council for Sustainable Development –Argentina- Virginia Vilariño
CEA
CEA--LERNA, University of Social Sciences- Marc Vielle
Centre for International Climate and Energy Research(CICERO), University of Oslo
- H.Asbjorn Aaheim
Argonne National Laboratory- Donald Hanson
Centre International de Recherche surl'Environnementl Environnement et le Developpement,Developpement EHESS - U.A.
UA
CNRS 940 (CIRED)- JeanJean--Charles Hourcade
CRA International- Brian FischerDepartment of Energy, Transport, Environment, DIW
Berlin- Claudia
Cl di KKemfertf tElectric Power Research Institute (EPRI)- Richard Richels, Francisco de la Chesnaye
Energy Research Institute, National Development andReform Commission (NDRC)- Kejun Jiang
ETH Zurich- Thomas Rutherford

Hamburg University and Economic and Social
Research Institute (ESRI)- Richard Tol
IndianI di InstituteI ioff ManagementM- Priyadarshi Shukla
Institut d'Economie et de Politique de l'Energie,
IEPE--CNRSIEPE- Patrick Criqui
International Institute for Applied Systems Analysis((IIASA))- Nebojsa Nakicenovic, Keywan Riahi
San Marcos University- Eduardo Calvo
National Institute for Environment Studies (NIES)- Mikiko Kainuma
National Center for Atmospheric Research (NCAR)- Brian O’NeillO NeillOhio State University- Brent Sohngen
Pacific Northwest National Laboratory, Joint Global
Change Research Institute at the University ofMaryland- Jae Edmonds, Hugh Pitcher, Ronald Sands, Steve
S ithSmith
Potsdam Institute for Climate Impact Research (PIK)- Ottmar Edenhofer, Elmar Kriegler, Brigitte Knopf
Programa de Planejamento Energético PPE/COPPE/UFRJ- Emilio Lèbre La RoverePurdue Universityy- Thomas Hertel
RAND- Rob Lempert

Nakicenovic

National Institute for Environmental Studies(NIES)
Research Institute of Innovative Technology for theEarth (RITE)- Keigo Akimoto
Stanford
S f d University
U ii- John Weyant
Tellus Institute- Richard Rosen
Texas A&M University- Bruce McCarl
The Institute of Applied Energy- Atsushi Kurosawa
The Netherlands Environmental Assessment Agency(MNP)- Detlef van Vuuren
Tyndall Centre for Climate Change Research, The
University of East Anglia- Andrew Watkinson,Watkinson Robert T
T. Watson
Universidad de Los Andes / Universidad Nacional deColombia- Jose Eddy Torres
Universidad Iberoamericana Puebla- Maria Eugenia Ibarraran Viniegra
Universityy of Cambridgeg- Andreas Schafer
University of Oldenburg- Christoph Boehringer
US Environmental Protection Agency- Allen Fawcett, Steven RoseVTT- Sanna Syri
World Bank- Dominique van der Mensbrugghe#242009

Timeline for New Scenarios
Product 1:RCPs
delivered toCMC

Product 2: RCP-based
CMC ensemble runs

Product 5: Integrationof CMC Ensembles
with New IAM
Scenarios Available

Product 3: New IAM
Scenarios
Product 4: Story Lines

Integration Phase

Source: Moss et al., 2007#25

12 month

Publication
Lag

Sp
pring 201
13

Parallel Phase

18 months

Sp
pring 201
12

Nakicenovic

24 months

F
Fall20100PreparatooryPhaseeF
Fall2007

Fall 2008

12 months

2009RCP Database• Central data repository to share information andto provide easy access to the data
• Interactive & web-based
web based “workingworking environment
environment”– detailed comparisons between RCPs and base year
inventory data
– quick data visualization– help to understand major data differences (eg. identify
definitional issues across RCPs)• At the moment limited access, since all data ispreliminary• Plan to make the database publicly accessible fordata dissemination once the data is final

Central IAM Data Repository

IAM working environment & data dissemination

Nakicenovic#272009IIASA IAM Data Repository

IAM working environment & data dissemination2007 Special Issue of Technological Forecasting and Social
Changeg Journal ((Nakicenovic and Riahi, eds., 2007):)
http://www.sciencedirect.com/science/journal/00401625))
http://www.sciencedirect.com/science/journal/00401625
Web-based database:Webhttp://www.iiasa.ac.at/Research/ENE/GGIDB_index.html
http://www iiasa ac at/Research/ENE/GGIDB index html

Nakicenovic

#28

2009

Carbon--Free Energy in A2r
Carbon

100

3oC

4oC

2oC

Share [%%]

90
80
7060

2030
2050
2100

504030201001430

1390

1090

970820

670

590

520

480

450

ppmv - CO2 Equivalent

Nakicenovic

#29

2009

Carbon--Free Energy in B1Carbon
B1r

100

3oC

4oC

2oC

Share [%%]

9080
7060

2030
2050
2100

5040
30
20
100
1430

1390

1090

970

820

670

590

520

480

450

ppmv - CO2 Equivalent

Nakicenovic

#30

2009

GHG emissions in A2r

250

3oC

4oC

2oC

Chang
ge vs. 2000
0 [%]

200
150
100
2030
2050
2100

500-50

1430

1390

1090

970

820

670

590

520

480

450-100-150
ppmv - CO2 Equivalent

Nakicenovic

#31

2009

GHG emissions in B1r
B1

250

3oC4oC

2oC

Chang
ge vs. 2000
0 [%]

200
150
100
2030
2050
2100

50
0-50

1430

1390

1090

970

820

670

590

520

480

450

-100
-150
ppmv - CO2 Equivalent

Nakicenovic

#32

2009

Energy Investments in A2r

4000

3oC

4oC

2oC

3500
billion US$b$90

3000
2500

2000
2030
2050
2100

2000
1500
1000
500
0
1430

1390

1090

970

820

670

590

520

480

450

ppmv - CO2 Equivalent

Nakicenovic

#33

2009

Energy Investments in B1r
B1

4000

3oC

4oC

2oC

3500
billion US$b$90

3000
2500

2000
2030
2050
2100

2000
1500
1000
500
01430

1390

1090

970

820

670

590520480450ppmv - CO2 Equivalent

Nakicenovic

#34

2009

Integrated Assessment Framework
Scenario Storyline

Economic development
Demographic changeTechnological change
Policies

Feedbacks

Feedbacks

Global and Regional Scenarios

Population

EconomyDownscaling Tools
Spatially explicit and national scenarios

National, regional & spatiallyexplicit socio-economic drivers

Spatially explicit socio-economicdrivers

DIMA
ForestManagement
Model

CLIMATE andACIDIFICATIONIMPACT
MODELS

Emissions

Carbon andbiomass pricePotential and costs offorest bioenergy andsinks

AEZ-BLS
Consistency of land-cover changes(spatially explicit maps ofagricultural, urban, and forest land)

MESSAGE-MACRO
Systems Engineering / Macro-Economicode g Frameworka ewo (a(all GGHGsGs aandd aall
Modelingsectors)

Endogenous Climate Model

Agricultural
Modeling
Framework

Agricultural bioenergy
potentials and costs

NATIONAL
POLICY MODELS(GAINS)

Drivers for land-use related
non-CO2 emissions

Emissions & Abatement Costs

Determinants of Demand

Demographic-Energy
Demographic
Energy Linkages
Scenario Drivers

Scenarios

Scenario Overview
Downscaling

Linkages Energy – Agriculture - Forestry
Forests

IMPACTS

AgricultureEnergy Scenarios and Technology Portfolios
EnergyPolicy Synergies& Co-benefits
NATIONAL
POLICIES

Global GDP Density
yNakicenovic

#37

2009

Global BuildBuild-Up
p AreaNakicenovic

#38

2009

Global Arable Land

Nakicenovic

#39

2009

Global Bioenergygy LandNakicenovic

#40

2009

Energygy and Food Land Conflicts

Nakicenovic

#41

2009

Government R&D in IEA countries
ini billi
billion US$ (2006)

Nakicenovic

Source: R. Doornbosch, et al., 2008 #42

2009

History of US Federal Government R&D
Homeland Security

Reagan “StarWars” Program

JFK ApollopProgram
Carter Energy
Program

Nakicenovic

#43

2009

...accounting for oneone-third of totalinternational bank financing
Bank lending to energyenergy-sector and total bank lending to emerging markets$ billions
300

Total bank lending
250
200
150
10050

Energy sector bank lending
02000

2001

2002

2003

2004

2005

2006

2007

2008*
* As of September

Nakicenovic

Source: World Bank, 2009

#442009

www.GlobalEnergyAssessment.org

TTowards
d a more SustainableS t i bl F
Futuret● The magnitude of the change required in the global
energy system will be huge
● The challenge is to find a way forward that addresses
simultaneously climate change, security and equity
issues.
● Paradigm change is needed: radical improvements inenergy end-use
end use efficiency
efficiency, new renewables
renewables, advanced
nuclear and carbon capture and storage.
● Needs to be globally integrated but with maximum
support of countries and local levels.
● InI theth bestb t spirit
i it off science:
if tb
fact-basedd andd peerreviewed
45

Confronting the Challenges of Energy for
Sustainable Development:
The Role of Scientific and Technical Analysis

IIASA
International Institute for Applied Systems Analysis
and its international partners present

www.GlobalEnergyAssessment
www.
GlobalEnergyAssessment.org.orgwww GlobalEnergyAssessment org
www.GlobalEnergyAssessment.org
Towards a more Sustainable Future● The magnitude of the change required
is huge.
huge● The challenge is to find a way forward
th t addresses
thatddallll ththe iissues
simultaneously.
● A paradigm shift is needed: energy enduse efficiency, new renewables, and, if
concerns can be resolved, carbon
capture and storage and nuclear.