Potsdam Institute for Climate Impact Research Research Domain Sustainable Solutions
Overview of the PIK REMIND-MAgPIE-LPJml
integrated assessment framework
Elmar Kriegler, Wolfgang Lucht
The World in 2050 Workshop IIASA, 11 March 2015
Elmar Kriegler Potsdam Institute for Climate Impact Research
IAM TEAM AT PIK
Nico Bauer, Gunnar Luderer, Christoph Bertram, Jerome Hilaire, Antoine Levesque, Ioanna Mouratiadou, Michaja Pehl, Robert Pietzcker, Jessica Strefler
Alexander Popp, Hermann Lotze-Campen, Anne Biewald, Benjamin Bodirsky, Florian Humpenöder, Ulrich Kreidenweis, Christoph Müller, Miodrag Stefanovic, Isabelle Weindl
Marian Leimbach, Franziska Piontek, Anselm Schultes, Niklas Roming, Gregor Schwerhoff
Jan Philipp Dietrich, Lavinia Baumstark, Anastasis Giannousakis, David Klein
Scientific coordination Laura Delsa
Energy Land use Economy M o d e l operations
Elmar Kriegler Potsdam Institute for Climate Impact Research
Cer
eals
Oils
eeds
Puls
es
Suga
r bee
ts
Crop yields Land & Water constraints
LPJ (50x50 km grid)
Bioenergy price, land use emissions
MAgPIE – 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
Bioe
nerg
y
Lotze-Campen, Popp et al. (2008), Agricultural Economics
LPJmL - global vegetation and hydrology model
Model framework
REMIND - global energy-economy-climate model • Ramsey optimal growth model • 11 economic regions • detailed energy sector (~70 conversion techs) • international trade (capital, emissions allowances, oil, coal, gas, biomass)
Biophysical inputs
Bioenergy demand, emissions price
Climate projection
Leimbach, Bauer, Baumstark, Edenhofer (2010) Environ. Modeling and Assessment Bauer, Baumstark, Leimbach (2012) Climatic Change Luderer, Pietzcker, Kriegler, Haller, Bauer (2012) Energy Economics
TRANSFORMATION PATHWAYS in REMIND-MAgPIE
Modeling the land-‐energy-‐water-‐climate nexus with climate change and mi6ga6on targets as star6ng point
Energy use
Land use
2°
4° 3°
Selected References • Luderer et al. (2012) Energy Economics • Popp et al. (2011) Environmental Research Letters
Energy use Land use
2°
4° 3°
• Energy supply & demand changes
• Energy prices
• VRE integration1
• International energy market effects2
• Energy security
• Technology development & policies3,4
Energy transforma6on in mi6ga6on pathways
Ø Mitigation reduces fossil fuel rents. Ø Overcompensated by emerging carbon rent
Bauer et al., Climatic Change (2014)
References 1. Pietzcker et al. (2014) Energy 2. Bauer et al. (2015) TFSC 3. Bauer et al. (2012) PNAS 4. Bertram et al. (2015) NCC
REMIND
Land use transforma6on
Energy use
Land use
2°
4° 3°
• Land use changes and emissions • Trade-offs between bioenergy,
afforestation, food production1,2
• Agricultural productivity increases3
• Land protection regimes & reduced deforestation2,4
• Impact of dietary changes5
• International agricultural trade6
• Climate impacts on land References 1. Humpenöder et al. (2014) Environmental Research Letters 2. Popp et al. (2014) Environmental Research Letters 3. Dietrich et al. (2014) TFSC 4. Popp et al. (2014) Nature Climate Change 5. Popp et al. (2010) Global Environmental Change, 6. Schmitz et al. (2012) Global Environmental Change
Non-forest leakage due to REDD
Popp et al. 2014, NCC
MAgPIE
Elmar Kriegler Potsdam Institute for Climate Impact Research
Further sustainability dimensions • Water demand of energy and agricultural sector1, Environmental flow constraints2
• Air pollution (joint work with IIASA & PBL, e.g. in LIMITS project) • Material flows and resource requirements (ADVANCE project) • Nitrogen pollution3
Agricultural water use
(Bonsch et al., 2014) 300 EJ/yr bioenergy in 2100
References 1. Bonsch et al. (2014) GCB Bioenergy 2. Bonsch et al. (2015) Global Environmental Change 3. Bodirsky et al. (2014) Nature Communications
Global quan8fica8on of the food-‐land-‐water nexus (LPJmL) (D. Gerten, W. Lucht and the LPJmL-‐4 team)
yield increase or LU expansion avoided
Example: Can water management improving efficiency in produc8ve water flows increase yield?
LPJmL4 agro-‐hydro-‐biosphere BGC model Low = 10% Med = 25% High = 50%
vapour shiW and rain water harves8ng
Water management:
Figures and preliminary results: J. Jägermeyr, D. Gerten, J. Heinke et al. PIK 2014
Elmar Kriegler: The Challenge of Mi8ga8ng Climate Change 9
Agreement in 2015 and 2oC
(LIMITS; Clim. Change Econ. 4(4)/5(1))
Role of Technology Availability
(EMF27; Clima8c Change 123(3-‐4) )
Global policy landscape & 6ming (AMPERE; Tech. For. &
Soc. Change 90A )
Recent studies of the energy-‐land transforma6on
Role of emissions drivers
(RoSE; Clima8c Change)
• ca. 950 emissions scenarios
• Major contribu8on to IPCC AR5 report of Working Group 3 AR5 Scenario Database: hips://secure.iiasa.ac.at/web-‐apps/ene/AR5DB
Forc
ing
leve
l (W
/m2 )
8.5
6.0
4.5
2.6
Shared Socio-economic Pathways
6 - 7.5 W/m2 >8 W/m2
5.2 – 6.2 W/m2 ~5.8 W/m2
Climate Policy Scenarios
Courtesy: Keywan Riahi
Development of new scenarios for climate change research
SSP1 Sustainability
SSP2 Middle of the Road
SSP3 Regional Rivalry
SSP4 Inequality
SSP5 Fossil-‐fueled Development
Marker scenario by REMIND-MAgPIE
PIK's Project "Co-‐Evolu8onary Pathways" (W. Lucht, J. Donges, J. Heitzig)
Dynamic Systems Analysis for t=2050: "Ask not what state you'll be in, but what flow you'll be in"
undesired states
desired states
Can we get into the desired flow by rowing?
(1) What are the proper8es of the flow? What are the system proper8es of BAU? (2) What is possible with rowing at 8me t? (3) What is the robustness of the path against an interrup8on of rowing? We could contribute a topological discussion of flow regimes and dilemmata faced
Elmar Kriegler Potsdam Institute for Climate Impact Research
Considerations on TWI 2050
• Embedding mitigation pathway work in broader sustainability context is area of active work and strategic interest at PIK
è excellent fit with TWI 2050, high interest in the project
• Development of full modeling capabilities will be a multi-year multi-person project èscope of TWI contribution somewhat contingent on timeline and availability of funding
• Large potential synergies with current SSP work by IIASA, PIK, PBL è would be very helpful to exploit them as much as possible in TWI50
• Communication strategy of TWI 2050 è communication of model results coordinated by modeling teams
Elmar Kriegler Potsdam Institute for Climate Impact Research
Backup Slides on Model Framework
Elmar Kriegler Potsdam Institute for Climate Impact Research
Nitrogen pollution Only ambitious mitigation action may reduce nitrogen pollution below critical thresholds. Even then, the risk remains that thresholds are exceeded.
Bodirsky et al. (2014), Nature Communications
Elmar Kriegler Potsdam Institute for Climate Impact Research
Variation of SSP input assumptions Indicator Parameter SSP1 SSP5 SSP 2
Population Population growth (IIASA scenarios)
Low Low Medium
Economy GDP growth (OECD scenarios) Very High High Medium
Convergence of per capita income (OECD scenarios)
Fast Fast Medium
Convergence of capital intensities Yes Yes No
Technology Resource extraction Coal/oil/gas
Low/low/low High/high/medium Medium/medium/medium
Solar (PV and CSP) and wind power
Optimistic / low cost
Pessimistic / high cost
Optimistic / medium cost
Environment Fossil fuel subsidies Phase out until 2030
Constant Phase out until 2050
Petrol / diesel taxes Convergence to 10 $/GJ by 2050
Constant Constant
Taxes on air pollutants High High Medium
Energy intensity Low High Medium
Forest/ecosystem protection High Low.-Medium Low-Medium
Behaviour Food demand incl food waste (Total calory per capita)
Low High Medium
Per capita demand for livestock products
Low High Medium
Globalization/Trade Free trade pool (MAgPIE) Medium High Low
Elmar Kriegler Potsdam Institute for Climate Impact Research
SSP Population Scenarios (IIASA)
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
SSP1 AFR
LAM
MEA
OAS
USA
RUS
JPN
IND
CHN
EUR 0
2000
4000
6000
8000
10000
12000
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
SSP2
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
SSP5
Population in million
Elmar Kriegler Potsdam Institute for Climate Impact Research
SSP GDP scenarios (OECD)
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
500000
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
SSP1 AFR
LAM
MEA
OAS
USA
RUS
JPN
IND
CHN
EUR 0
50000
100000
150000
200000
250000
300000
350000
400000
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
SSP2
0
100000
200000
300000
400000
500000
600000
700000
800000
2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
SSP5
GDP in billion USD(2005) at MER
Elmar Kriegler Potsdam Institute for Climate Impact Research
SSP1 SSP2 SSP5
450ppm
Reference
Energy demand in SSP reference and policy cases
Preliminary results
Elmar Kriegler Potsdam Institute for Climate Impact Research
Cell-specific share of total agricultural land (crop & pasture)
Preliminary results
SSP1-bau - 2095
Elmar Kriegler Potsdam Institute for Climate Impact Research
Cell-specific share of total agricultural land (crop & pasture)
Preliminary results
SSP5-bau - 2095
Elmar Kriegler Potsdam Institute for Climate Impact Research 21
Welfare
Labour Capital
Energy system costs
Output
Consumption Investments
Final energy
Energy transformations and conversion technologies
Fuel costs
Investment costs
Operation and Maintenance
costs
Labour efficiency Emissions
Learning by doing
Ressource and potential
constraints
Macro Economy
Energy system
Exogenous Data
Energy efficiency
Trade
Trade
Trade
Climate module
Quick introduction to the models: ReMIND
Leimbach,Bauer, Baumstark, Edenhofer, O. (2010)
Elmar Kriegler Potsdam Institute for Climate Impact Research
Quick introduction to the models used: ReMIND
ReMIND Energy System / Macro Interface
Elmar Kriegler Potsdam Institute for Climate Impact Research
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 countries OAS - 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 introduction to the models used: ReMIND
Elmar Kriegler Potsdam Institute for Climate Impact Research
Cer
eals
Oils
eeds
Puls
es
Suga
r bee
ts
Crop yields Land & 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
8
10
12
14
16
1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100
Billion
Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001)
Demography
Income and diet
Food demand, production costs
Socioeconomic inputs
MAgPIE – 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
Bioe
nerg
y
Lotze-Campen , Popp et al. (2008), Agricultural Economics
Elmar Kriegler Potsdam Institute for Climate Impact Research
Land
use
dyn
amic
s
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
8
10
12
14
16
1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100
Billion
Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001)
Cer
eals
Oils
eeds
Puls
es
Suga
r bee
ts
Crop yields Land & Water constraints
+200 mm-200 -100 0 +100
CCSR
ECHAM4
Climate change (GCM) Demography
Income and diet
Food demand, production costs
LPJ (50x50 km grid)
Biophysical inputs
Socioeconomic inputs
Bioe
nerg
y
Lotze-Campen et al. (2008), Agricultural Economics
Land use pattern
2035
Elmar Kriegler Potsdam Institute for Climate Impact Research
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
8
10
12
14
16
1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100
Billion
Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001)
+200 mm-200 -100 0 +100
CCSR
ECHAM4
Climate change (GCM) Demography
Income and diet
Food demand, production costs
Biophysical inputs
Socioeconomic inputs
Lotze-Campen and Popp, World Development Report 2010
Cer
eals
Oils
eeds
Puls
es
Suga
r bee
ts
Crop yields Land & Water constraints
LPJ (50x50 km grid)
Bioe
nerg
y
Elmar Kriegler Potsdam Institute for Climate Impact Research
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
8
10
12
14
16
1900 1920 1940 1960 1980 2000 2020 2040 2060 2080 2100
Billion
Low fertility, low mortality High fertility, high mortality Central fertility, central mortality (Lutz et al. 2001)
+200 mm-200 -100 0 +100
CCSR
ECHAM4
Climate change (GCM) Demography
Income and diet
Food demand, production costs
Biophysical inputs
Socioeconomic inputs
Popp et al. 2010, GEC
Cer
eals
Oils
eeds
Puls
es
Suga
r bee
ts
Crop yields Land & Water constraints
LPJ (50x50 km grid)
Bioe
nerg
y
2055 Agricultural N2O [Mt CO2-e]
Elmar Kriegler Potsdam Institute for Climate Impact Research
MAgPIE world regions
Elmar Kriegler Potsdam Institute for Climate Impact Research
Bondeau et al. 2007, GCB
Input: climate, CO2, soil, land-use
Natural vegetation
Managed grasland
Cropland
LPJmL
Elmar Kriegler Potsdam Institute for Climate Impact Research
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
Elmar Kriegler Potsdam Institute for Climate Impact Research
Models can provide maps of the „solu8on space“.
Policy makers can use them to navigate through this space.
Mi6ga6on scenarios for the 21st century are of value to draw the link between short term ac6on and long term goals
How can global models inform the negotiation process?
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