preliminary iam scenarios based on the rcp/ssp framework · 2019-12-12 · preliminary iam...

Preliminary IAM scenarios based on the RCP/SSP framework

Keywan Riahi International Institute for Applied Systems Analysis

SSP Drivers: KC Samir, Wolfgang Lutz, Rob Dellink, Marian Laimbach, Jesus

Crespo, Brian O’Neill, Leiwan Jiang… AIM: Shinichiro Fujimori, Toshihiko Masui, Mikiko Kainuma, …

GCAM: Jae Edmonds, Kate Calvin, Stephanie Waldhoff, Steve Smith, … IMAGE: Detlef van Vuuren, Elke Stehfest, David Gernaart …

MESSAGE-GLOBIOM: Volker Krey, Oliver Fricko, Petr Havlik, Shilpa Rao, Nils Johnson, …

ReMIND-MAGPIE: Elmar Kriegler, Nico Bauer, Alex Popp, Benjamin Bodirsky, WITCH-GLOBIOM: Massimo Tavoni, Johannes Emmerling, …

AGCI Workshop 5 August 2014, Aspen, Colorado

Integrated Analysis

Mi0ga0on, Adapta0on, Impacts

SSPs and Integrated Analysis

2

Representa0ve Concentra0on Pathways (RCPs)

Forcing, Emissions, concentra0ons, land

use, land cover

Socio-‐economic Pathways (SSPs)

Descrip0ons of Alterna0ve

Socioeconomic Pathways

Earth System Model Simula0ons (CMIP5)

Climate Change, climate variability

Moss, Edmonds, et al. (2010)

IAM scenarios Mi-ga-on dimension

SSP Process •  Conceptual framework and nature of the SSPs established •  Quantification of key elements of the SSPs has been completed •  Narratives completed •  Refined (but not final) IAM reference scenarios developed •  Preliminary SPAs defined •  Initial climate policy scenarios •  Preliminary IAM SSP marker selected

•  Still to do: –  Continue vetting and development of SSP IAM scenarios –  Check SPAs for refined stabilization analyses

The SSP-IAM Kitchen

IAM Models

GDP

POP

Urbanisation

SSP1 SSP2 SSP3 SSP4 SSP5

(Narratives)

Narratives

GDP

POP

Energy

Land-use

Technology, Demand, Life-

styles, Productivity

GHG Emissions

Aerosol/Pollutant Emissions

Urbanization

SSPs (Assumptions) IAM Models

SSP ASSUMPTIONS

Global Driver Assumptions

Lutz & KC, 2014

6000

7000

8000

9000

10000

11000

12000

13000

SSP1

SSP2

SSP3

SSP4

SSP5

Jiang & O’Neill

0

20

40

60

80

100

120

140

160

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

GDP per capits ($/cap -‐PPP) SSP5

SSP3

SSP2

SSP4

SSP1

OECD, PIK, IIASA

Inequality assumptions across SSPs

0

20

40

60

80

100

120

140

160

180

2010 SSP3 SSP2 SSP1 SSP4 SSP5

GD

P/ c

aptia

(PPP

)

Annex1 Non-Annex1

OECD Projections

Inequality ratio: 5.0

1.3

1.2

3.7 1.6

3.1

REFERENCE SCENARIOS (NO CLIMATE POLICY)

All results are still preliminary

Energy – SSP Reference Cases

1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000

2500Other renewablesNuclearGasOilCoalBiomass

SSP1 (Sustainability)

1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000

2500Other renewablesNuclearGasOilCoalBiomass SSP4

(Inequality)

Other renewablesNuclearGasOilCoalBiomass


Two scenarios where mitigation is relatively easy

Transition away from coal/oil Low demand

High share of poor with low emissions Low/intermediate demand Technology available to the “elite”

IMAGE GCAM


1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


SSP3 (Regional rivalry)


1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


SSP5 (Fossil-fueled growth)


Two scenarios where mitigation is relatively difficult

REMIND-MAGPIE AIM

Coal-intensive development Very high demand

Fossil-intensive High poverty Slow technological change Strong fragmentation


1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


SSP2 (Middle of the road)


A central scenarios with intermediate mitigation challenge

Balanced Technology Intermediate demand

MESSAGE-GLOBIOM


1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


SSP1 (Sustainability)

1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000

2500Other renewablesNuclearGasOilCoalBiomass SSP4

(Inequality)



1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


SSP3 (Regional rivalry)


1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


SSP5 (Fossil-fueled growth)


1850 1900 1950 2000 2050 2100

EJ

0

500

1000

1500

2000


SSP2 (Middle of the road)


Land-use Change (index 1=2010)

0.6

0.7

0.8

0.9

1

1.1

1.2

SSP1-‐IMAGESSP2-‐MESSAGE-‐GLOBIOMSSP3-‐AIMSSP4-‐GCAMSSP5-‐REMIND-‐MAGPIE

0.6

0.8

1

1.2

1.4

1.6

1.8

SSP1-‐IMAGESSP2-‐MESSAGE-‐GLOBIOMSSP3-‐AIMSSP4-‐GCAMSSP5-‐REMIND-‐MAGPIE

Forest land Cropland

SSP1: sustainability

SSP1: sustainability

SSP3: high pop low productivity

RCP CO2 Emissions, World (Fossil fuels and Industry)

2000 2020 2040 2060 2080 2100

CO

2 em

issi

ons

(GtC

O2)

-20

0

20

40

60

80

100

120

140

160

RCP 8.5

RCP 2.6

RCP 4.5

RCP 6.0

AIM/CGE GCAM IMAGE MESSAGE-GLOBIOM REMIND-MAGPIE SSP1 SSP2 SSP3 SSP4 SSP5

SSP5

SSP3 SSP2

SSP1

Fossil fuels and Industry CO2 Emissions, World (Reference Scenarios)

2000 2020 2040 2060 2080 2100

Em

issi

ons|

CO

2|Fo

ssil

Fuel

s an

d In

dust

ry

-20

0

20

40

60

80

100

120

140

SSP4

CH4 Emissions, World Reference Scenarios

2000 2020 2040 2060 2080 2100

Em

issi

ons|

CH

4

0

100

200

300

400

500

600

700

800

900


SSP5

SSP3

SSP2

SSP1 SSP4

N2O Emissions, World Reference Scenarios

2000 2020 2040 2060 2080 2100

Em

issi

ons|

N2O

0

5000

10000

15000

20000

25000

30000


SSP5

SSP3

SSP2

SSP1

SSP4

Policy Targets (exposure/concentrations) Technological Innovation

Policy Strength

High Income Countries Medium and Low Income

Strong Much lower than current targets in order to minimize adverse effects on both general population, vulnerable groups, and ecosystems.

Comparatively quick catch-up with the developed world (relative to income)

Pollution control technology costs drop substantially with control performance increasing.

Central Lower than current targets

Catch-up with the developed world at income levels lower than when OECD countries began controls (but not as quick as in the strong control case).

Continued modest technology advances.

Weak Regionally varied policies. High emissions levels and/or institutional limitations substantially slower progress in pollution control.

Lower levels of technological advance overall.

Air pollution policy assumptions (Storylines, exposure, targets)

World Emissions|NOx SSP reference scenarios

2000 2020 2040 2060 2080 2100

Em

issi

ons|

NO

x

0

20

40

60

80

100

120

140

160

180


SSP5

SSP3

SSP2

SSP1

SSP4

World Emissions|Sulfur SSP Reference Scenarios

2000 2020 2040 2060 2080 2100

Em

issi

ons|

Sul

fur

0

20

40

60

80

100

120

140

160


World Radiative Forcing Reference Scenarios

2000 2020 2040 2060 2080 2100

Forc

ing

(W/m

2)

0

2

4

6

8

10


SSP5

SSP3, SSP2

SSP1, SSP4

SSP/RCP combinations based on reference IAM scenarios

Forc

ing

leve

l (W

/m2 )

8.5

6.0

4.5

2.6

SSP1 SSP2 SSP3 Shared Socio-economic Pathways

SSP4 SSP5

6 - 7.5 W/m2 >8 W/m2

5.2 – 6.2 W/m2 ~5.8 W/m2

Climate Policy Scenarios

?

CLIMATE POLICY SCENARIOS

All results are still preliminary

Shared Policy Assumptions SPAs SSPs describe worlds with widely different challenges to mitigation due to eg fragmentation, lack of institutions, inequity, lack of technology, etc..

SPAs reflect these differences

Two main SPA dimensions

Accession/ Regional Participation

Effectiveness of land policies

F1: Early Accession, Global collaboration as of 2020 SSP1, SSP4

L1 highly effective SSP1

F2: Some delays, poor regions join in 2030

SSP2,5

L2 Intermediately effective (limited REDD) SSP2,4

F3: Late Accession, poor regions join in 2040 SSP3

L3 Low effectiveness (implementation failures, high transaction costs)

SSP3

Shared Policy Assumptions Accession

2000 2020 2040 2060 2080 2100

GHG emissions (GtCO2 equiv.)

0

10

20

30

40

50

60

70

80No Policy

Extrapolation of current policies

Strong global actiontoward 2ºC

Global GHG emissions

(AMPERE, Kriegler et al)

SSP1,4 SSP2,5

SSP3

World Forcing 6.0

2000 2020 2040 2060 2080 2100

Forc

ing

(W/m

2)

0

2

4

6

8

10


World Forcing 4.5

2000 2020 2040 2060 2080 2100

Forc

ing

(W/m

2)

0

2

4

6

8

10


World Forcing 3.7

2000 2020 2040 2060 2080 2100

Forc

ing

(W/m

2)

0

2

4

6

8

10


World Forcing 2.6

2000 2020 2040 2060 2080 2100

Forc

ing

(W/m

2)

0

2

4

6

8

10


SSP/RCP combinations based on reference IAM scenarios

Forc

ing

leve

l (W

/m2 )

8.5

6.0

4.5

2.6

SSP1 SSP2 SSP3 Shared Socio-economic Pathways

SSP4 SSP5

6 - 7.5 W/m2 >8 W/m2

5.2 – 6.2 W/m2 ~5.8 W/m2

Special Issue in GEC SSPs + IAM Scenarios

•  Narratives: O’Neill et al (submitted) •  Population: KC & Lutz (accepted) •  GDP: (1) Leimbach et al, (2) Dellink et al, (3) Crepo

(submitted) •  Urbanization: Jiang & O’Neill (submitted) •  5 x IAM marker papers •  Crosscut papers:

–  Energy –  Land-use –  Air Pollution/Aerosols

Data availability and resolution

https://secure.iiasa.ac.at/web-apps/ene/SspDb

All data will be publicly available at the SSP database Already available (national data) GDP Population (structure, education, tot) Urbanization IAM scenario data by end of the year Energy Land-use Emissions Forcing & Temperature Other relevant indicators (energy/carbon price, economic feedbacks, etc..) Resolution: 5 World Regions (more details available from IAM teams 10-26 regions) At the moment there are no concrete plans for spatial downscaling (assess on user needs) (individual efforts for downscaling: NCAR, IMPRESSIONs, IIASA, and other projects)

Timeline •  Beta-version of IAM scenarios will become

available for comments by end of 2014 •  Submission of selected papers (eg

overview paper) around the same time •  Parallel community/paper review •  Present beta-SSP scenarios at the IPCC

Scenarios Meeting in February (not fixed yet!)

•  Finalization of scenarios and SI mid 2015

Additional Slides

Inequality across models Global GINI

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1980

1985

1990

1995

2000

2005

2010

2015

2020

2025

2030

2035

2040

2045

2050

2055

2060

2065

2070

2075

2080

2085

2090

2095

2100

IIASA

SSP1

SSP2

SSP3

SSP4

SSP5

Country Groupings •  For defining these scenarios we distinguish

among three groups of countries: •  High Fertility Countries (HiFert): Countries

with current level of fertility less than 2.9 children per woman (2005-2010).

•  Low Fertility Countries (LoFert) Countries with current level of fertility less than or equal to 2.9 not belonging to Rich OECD countries (see below)

•  High Income-OECD Countries (Rich-OECD) As per the definition of World Bank.

Education Scenarios •  The fast track (FT) scenario is extremely ambitious; it assumes that

all countries expand their school systems at the fastest possible rate, which would be comparable with best performers in the past such as Singapore and South Korea .

•  The global education trend (GET) scenario is more moderately optimistic and assumes that countries will follow the average path of school expansion that other countries already somewhat further advanced in this process have experienced.

•  The constant enrollment rate (CER) scenario assumes that countries only keep the proportions of cohorts attending school constant at current levels.

•  The most pessimistic scenario, constant enrollment numbers (CEN), assumes that no more schools at all are being built and that the absolute number of students is kept constant, which under conditions of population growth means declining enrollment rates.

0

20

40

60

80

100

120

140

160

1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

SSP -‐ Per Capita GDP (billion US$2005PPP / million people)

SSP2 -‐ IIASA -‐ World SSP2 -‐ IIASA -‐ WorldSSP2 -‐ PIK -‐ World SSP2 -‐ PIK -‐ WorldSSP2 -‐ OECD -‐ World SSP2 -‐ OECD -‐ World

0

20

40

60

80

100

120

140

160

1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100



0

20

40

60

80

100

120

140

160

1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100



0

20

40

60

80

100

120

140

160

1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100



0

20

40

60

80

100

120

140

160

1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100



Global GDP levels by scenario

Source: preliminary SSP database 39

Population assumptions consistent with SSP Storylines

Low challenges for adaptation

High challenges for adaptation

China - population for five SSPs

Lutz & KC

0

200

400

600

800

1000

1200

1400

1600

SSP1

SSP2

SSP3

SSP4

SSP5

World 2050

SSP1 Pop=8673 Mio SSP3 Pop=10603 Mio

Lutz & KC

Common interpretation of the SSPs OECD – IIASA - PIK

43

Frontier TFP growth Speed of convergence

SSP1: Sustainability Medium high High

SSP2: Middle of the road Medium Medium

SSP3: Fragmentation Low Low

SSP4: Inequality Medium Low Income: Low

Middle Income: Medium High Income: Medium

SSP5: Conventional development High High

N.B. Quantitative interpretations and methodology differ between models, illustrating the uncertainties in making economic projections

Key SSP elements (three main products + IAV variables)

SSP Narratives

Population (age, sex,

mortality, fertility, education)

Urbanization (national)

Economic development (regional/national)

Quantitative drivers

Energy (technology,

resources, etc)

Emissions (forcing,

temperature)

Land-use (productivity,

diets, etc)

IAM Scenarios

1

2 3

Iterative Process

Air pollutant Uncertainties of the RCPs

BC

OC

CO

SOx

NOx

NMVOCs

RCP 2.6 RCP 4.5 RCP 8.5

Rogelj et al (NCC, 2014)

Sulfur Emissions Uncertainties in RCP 2.6 and 8.5

RCP 2.6

RCP 8.5

Rogelj et al (NCC, 2014)

Original RCP

Current legislation

Original RCP

Current legislation

World Emissions|Sulfur 2.6

2000 2020 2040 2060 2080 2100

Em

issi

ons|

Sul

fur

0

20

40

60

80

100

120

140

160


Assumptions about other drivers

SSP Element Low Med High Low Med High Low Med High Low Med High Low Med High

Traditional Fuel Usecontinued traditional fuel use

Lifestyles low service demands

low

Energy Intensity of ServicesIndustry high

Buildings medium

Transportation mediumlow/mediu

m

SSP 1 SSP 2 SSP 3 SSP 4 SSP 5

Country Income Groupings

Non-‐climate Policies

Energy Demand Side

fast phase-‐out, driven by policies and economic

development

intermediate phase-‐out, regionally diverse speed

continued realiance on traditional fuels

some traditional fuel use among low income housholds

fast phase-‐out, driven by development priority

medium (low for global level/high for local level)

modest service demands (less material intensive)

medium service demands (generally material intensive)

medium service demands (material intensive)

modest service demands

high service demands (very material intensive)

Environmental Awareness high medium low high

low medium high low medium

low medium high low/medium medium

low medium high low high

General Comments some regional diversity retained

Energy demand (access, intensity of services, environmental awareness, etc..)

SSP 1 SSP 2 SSP 3 SSP 4 SSP 5Country Income

Groupings


CoalMacro-‐economy cost driver neutra l cost reducing cost reducing neutra l cost driver cost reducing

Technology medium medium high medium very high

National & environmental policy

very restrictive supportive very supportive supportive supportive restrictive very restrictive

Conv. HydrocarbonsMacro-‐economy neutra l neutra l neutra l cost driver cost reducing

Technology medium medium medium fast very high


restrictive supportive mixed (not supported in MEA/FSU) supportive supportive restrictive very restrictive

Non-‐conv. HydrocarbonsMacro-‐economy neutra l neutra l neutra l cost driver cost reducing

Technology s low medium medium medium very high


very restrictive supportive very supportive supportive supportive restrictive very restrictive

GeneralTrade barriers Free Barriers High Barriers Barriers Free

Fossil resources (availability, costs, trade, etc..)

Qualitative descriptions Modeling teams were flexible to make own interpretations

More assumptions…. Energy technologies (Innovation, acceptance, costs, etc…)

Land use change (productivity, regulation, trade, diets, etc…)


Low Med MedHigh Low Low

High High HighHigh High High

Non-‐bio Renewables ConversionHigh High HighHigh High High

Nuclear PowerLow Low Med High High HighHigh High High High Med Med

CCS (under climate policy only)High High HighHigh Med Med

Conventional and Unconventional Fossil Fuel Conversion (synfuel and syngas in parenthesis if different)

SSP 1 SSP 2 SSP 3 SSP 4 SSP 5Country Income Groupings

Social Acceptance Low Med High HighTechnology Development Med Med Low Med (High)

Low Med

Technology Development High Med Low MedSocial Acceptance Low Med High Med

Technology Development High MedSocial Acceptance High Med

Med

Technology Development Med Med Med

Commercial Biomass Conversion

Social Acceptance Low Med Med Med

Med Low

High

Technology Development Med Med MedSocial Acceptance Low Med


Land use change regulation

strong medium weak weak medium strong medium

Agriculture

Land productivity growth rapid rapid medium medium slow slow medium rapid rapid

Environmental Impact of food consumption

low medium high medium high

International Trade globalized regionalized regionalizedlimited access

globalized

globalized

globalized

SSP 1 SSP 2 SSP 3 SSP 4 SSP 5Country Income Groupings

preliminary iam scenarios based on the rcp/ssp framework · 2019-12-12 · preliminary iam...

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