Application of the new scenario approach in the ReMIND ... · PDF fileapproach in the ReMIND-MAgPIE integrated assessment framework ... Which narrative to choose? 3. ... World Development

Potsdam Institute for Climate Impact ResearchResearch Domain Sustainable Solutions

Application of the new scenario approach in the ReMIND-MAgPIEintegrated assessment framework

Elmar Kriegler, Alexander Popp, David KleinLena Reuster, Jana Schwanitz, Nico Bauer

Gunnar Luderer, Marian Leimbach, Franziska PiontekWorkshop on new SMA/ SSP approach

16-17 July 2011, Changwon, Korea

Elmar KrieglerPotsdam Institute for Climate Impact Research

OverviewOverview

1. An overview of ReMIND-MAgPIE model capabilities

2. Which narrative to choose?

3. Tentative implementation of narratives in ReMIND-MAgPIE

4. SSP1 vs. SSP5: An example from EMF24

5. Outlook

Elmar KrieglerPotsdam Institute for Climate Impact Research 3

Welfare

LabourCapital

Energy system costs

Output

ConsumptionInvestments

Final energy

Energy transformations and conversion technologies

Fuelcosts

Investment costs

Operation and Maintenance

costs

Labourefficiency Emissions

Learningby doing

Ressource and potential

constraints

Macro Economy

Energy system

Exogenous Data

Energy efficiency

Trade

Trade

Trade

Climatemodule

Quick Quick introductionintroduction to to thethe modelsmodels: : ReMINDReMIND

Leimbach,Bauer, Baumstark, Edenhofer, O. (2009)


ReMIND regions

USA - USA EUR - EU27 JAP - Japan CHN - China IND - India RUS - Russia AFR - Sub-Saharan Africa (excl. Republic of South Africa) MEA - Middle East, North Africa, central Asian countriesOAS - Other Asia (mostly South East Asia)LAM - Latin America ROW - Rest of the World (Canada, Australia, New Zealand, Republic of South Africa, Rest of Europe).

Quick Quick introductionintroduction to to thethe modelsmodels usedused: : ReMINDReMIND


Cereals

Oilseeds

Pulses

Sugarbeets

Crop yieldsLand & Water constraints

+200 mm-200 -100 0 +100

CCSR

ECHAM4

Climate

LPJ (50x50 km grid)

Biophysical inputs

Income vs. Food consumption

0

500

1000

1500

2000

2500

3000

3500

4000

0 5000 10000 15000 20000 25000 30000 35000 40000

GDP / Cap / Year

Kca

l / C

ap /

Day

kcal_cap (105 countries, 1990/2000) kcal_cap (fitted values)

kcal = 802 * gdp^(0.142327) [R^2 = 0.66]

0

2

4

6

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14

16

1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100

Bill

ion

Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001)

Demography

Income and diet

Food demand, production costs

Socioeconomicinputs

MAgPIEMAgPIE – a global land use optimisation model• spatially explicit (0.5°), 10 economic regions• 30 production activities (13 crops, livestock,

irrigation, bioenergy, land conversion)• internal feed balances, international trade• endogenous land expansion• endogenous technological change

Bioenergy

Lotze-Campen , Popp et al. (2008), Agricultural Economics


Land

use

dyna

mic

s


0

500

1000

1500

2000

2500

3000

3500

4000

0 5000 10000 15000 20000 25000 30000 35000 40000

GDP / Cap / Year

Kca

l / C

ap /

Day


kcal = 802 * gdp^(0.142327) [R^2 = 0.66]

0

2

4

6

8

10

12

14

16

1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100

Bill

ion


Cereals

Oilseeds

Pulses

Sugarbeets


+200 mm-200 -100 0 +100

CCSR

ECHAM4

Climate change (GCM)Demography

Income and diet


LPJ (50x50 km grid)

Biophysical inputs

Socioeconomicinputs

Bioenergy

Lotze-Campen et al. (2008), Agricultural Economics

Land usepattern

2035



0

500

1000

1500

2000

2500

3000

3500

4000

0 5000 10000 15000 20000 25000 30000 35000 40000

GDP / Cap / Year

Kca

l / C

ap /

Day


kcal = 802 * gdp^(0.142327) [R^2 = 0.66]

0

2

4

6

8

10

12

14

16

1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100

Bill

ion


+200 mm-200 -100 0 +100

CCSR

ECHAM4


Income and diet


Biophysical inputs

Socioeconomicinputs

Lotze-Campen and Popp, World Development Report 2010

Cereals

Oilseeds

Pulses

Sugarbeets


LPJ (50x50 km grid)

Bioenergy



0

500

1000

1500

2000

2500

3000

3500

4000

0 5000 10000 15000 20000 25000 30000 35000 40000

GDP / Cap / Year

Kca

l / C

ap /

Day


kcal = 802 * gdp^(0.142327) [R^2 = 0.66]

0

2

4

6

8

10

12

14

16

1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100

Bill

ion


+200 mm-200 -100 0 +100

CCSR

ECHAM4


Income and diet


Biophysical inputs

Socioeconomicinputs

Popp et al. 2010, GEC

Cereals

Oilseeds

Pulses

Sugarbeets


LPJ (50x50 km grid)

Bioenergy

2055 Agricultural N2O [Mt CO2-e]


InfluenceInfluence of of dietsdietsCombinationCombination

A – Pop. growth & diet shifts B – Less livestock productsC – Technological mitigation D – Combination of B & C


Bondeau et al. 2007, GCB

Input: climate, CO2, soil, land-use

Naturalvegetation

Managedgrasland

Cropland

LPJmL


Agricultural yields Carbon content

Run-off

Müller, Bondeau, Popp et al. WDR 2010

Bondeau et al. 2006, GCB

Füssel, Popp, Heinke (2010)

Gumpenberg, Popp et al. 2010, ERL

LPJmL


Model Model couplingcoupling

Objective: Model framework to explore potential contribution of bioenergyto climate change mitigation, including its costs and trade-offs

LPJmL - global vegetation and hydrology model

MAgPIE - global land use optimization model

REMIND- global energy-economy-climate model


WhichWhich storylinesstorylines to to choosechoose??


WhichWhich storylinesstorylines to to choosechoose??

Increasing socio-economic adaptation challenges

Incr

easi

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SSP 5Coal & gaspoweredgrowth

SSP 1Sustainabledevelopment

SSP 3Fragmented

world

SSP 4Divided in rich & poor

SSP 2


EstablishedEstablished scenariosscenarios oftenoften spanspan thethe „„diagonaldiagonal““


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SSP 3Fragmented

world

SSP 4Divided in rich & poor

SSP 2


OffOff--diagonal diagonal scenariosscenarios far far lessless consideredconsidered


Incr

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SSP 3Fragmented

world

SSP 4Divided inrich & poor

SSP 2


TentativeTentative implementationimplementation of of

narratives in narratives in ReMINDReMIND and and MAgPIEMAgPIE


ContrastingContrasting SSPsSSPs: High : High vsvs lowlow adaptive adaptive capacitycapacity

High adapativecapacity

Low adapativecapacity


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SSP 5

SSP 1

SSP 3

SSP 4


High adaptative capacity

• low to medium populationgrowth

• well-functioning markets and institutions

• globalized and cooperativeworld

• High inter-/ intraregional convergence

• rapid technological progress

Low adaptative capacity

• high population growth

• distorted markets and institutions

• fragmented world prone to conflicts

• Low inter-/ intraregional convergence

• slow technological progress

ContrastingContrasting SSPsSSPs: High : High vsvs lowlow adaptive adaptive capacitycapacity

Narrative matches ReMINDdefault assumptions


HowHow to to differentiatedifferentiate betweenbetween thethe twotwo verticalsverticals

• Low exogenous populationscenario

• High exogenous labourproductivity with fast convergence betweenregions

• free capital and commoditytrade

• technology spill-overs• Convergence of energy

service and food demand

• High exogenous populationscenario

• Low exogenous labourproductivity with slowconvergence betweenregions

• regionally differentiated trade costs and capital taxesreducing the rate of return on capital, import / export quotas on capital and commodities

• No technology spill-overs• Persisting regional

differences in energy serviceand food demand

High adapative capacity Low adapative capacity


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RoSE GDP Scenarios – Basic methodology

Based on Methodology by PricewaterhouseCoopersHawksworth, J. (2006), The World in 2050 How big will the major emerging market economies get and how can the OECD compete.


Quality adjusted input of labor

L = h(s) ( e1N(15-64 yr) + e2N(65+ yr) )s = average years of school (data from Barro and Lee, 2001; Scenario after 2010)

e1 = labor particapation rate working age population (Varies from 55% –75% across regions. Cultural factors dominating? Assumed constant after 2010) e2 = labor participation rate of population 65+ years old(Varies from 3% – 50% across regions. Dominated by per capita income. 3%-20% in developed countries. Scenario assumed after 2010)


RoSE GDP per capita scenarios - World

Preliminary results


RoSE GDP per capita scenarios - China

Preliminary results


ContrastingContrasting narratives: SSP1 vs. SSP5narratives: SSP1 vs. SSP5

Low mitigative capacity

High mitigative capacity

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SSP 5

SSP 1


ContrastingContrasting narratives: SSP1 vs. SSP5narratives: SSP1 vs. SSP5

SSP 1• Environment: lifecycle

perspective and closed-loop industries, high external costs of fossil energy, fossil fuel availability limited

• Technology: rapid technological progress on RE, high TC in agricultural sector

• Behaviour: sustainableconsumption patterns

SSP 5• Environment: problem-oriented

environmental regulation (end-of pipe approach), external costs of fossil fuels well controlled, gasification world, NIMBY perpective with RE

• Technology: strong reliance on fossil fuels, broad access to cheap fossil energy, maximizationof resource extraction

• Behaviour: energy intensive consumption patterns (buildings, cars,…), meat rich diet


HowHow to to differentiatedifferentiate betweenbetween thethe twotwo horizontalshorizontals

Low mitigativecapacity

High mitigativecapacity

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• large fossil fuel availability, no fossil resource extractionconstraints

• high energy intensity/ end energy demand• scenario for high calory demand, high lifestock share,

high consumer waste share• high exogenous scenarios for RE investment costs,

efficiencies, adjustment costs and expansion constraints

• low fossil fuel availability, fossil resource extractionconstraints

• low final energy intensity/ end energy demand• scenario for low calory demand, low lifestock share, low

consumer waste share• low exogenous scenarios for RE investment costs,

efficiencies and adjustment costs, and no expansion constraints


EMF24 EMF24 exampleexample: Low vs. high : Low vs. high mitigativemitigative capacitycapacitywithwith unchangedunchanged adaptive adaptive capacitycapacity

SSP1 EMF24 run R2G2, low energy intensity

SSP5 EMF24 run R2G6, high energy intensity, pessimistic RE, low biomass


SummarySummary and and conclusionsconclusions

• Fun work to try to translate SSP narratives in modelassumptions

• Hard work to implement it and ensure that model results arereasonable and reflective of the narrative

• Need guidance and coordination: Where would it best to focus, where are other groups focusing

• Need dialogue and cooperation with a range of non-IAMgroups: demography, growth accounting, institutionalanalysis, human development, IAV

• Concern about lock-in in low, medium, high UN populationscenarios (e.g. divided world scenarios)


Thank you!Thank you!


Backup SlidesBackup Slides


CrucialCrucial indicatorsindicators forfor SSPsSSPs

Population: total population, age structure, urbanization

Economy: GDP, sectoral structure, investment rate, income

convergence, labor participation rates

Environment: external costs (fossils, RE), energy intensity of

consumption patterns, pollution, land use footprints

Equity: intra- and interregional income distribution, energy

and food prices

Technology: energy resources and technologies, agricultural productivity,

diffusion rates, direction of technological change

Governance: rule of law, political stability, international regimes, market

regimes

Globalisation: trade patterns / limitations, knowledge transfer, capital markets

Behaviour: consumption patterns, health indicators

Category Indicators

Documents

Application of the new scenario approach in the ReMIND ... · PDF fileapproach in the ReMIND-MAgPIE integrated assessment framework ... Which narrative to choose? 3. ... World Development