Tom Kram, Detlef van Vuuren

Meeting a 2 degree
target under climate
uncertainty
Integrated scenarios
for land-use and energy
for low stabilisation
targets

Expected warming for 550ppm CO2eq

Kram / van Vuuren, 2 degrees under uncertainty

2Probability to reach the 2°C target

Range of scenarios
in literature

Kram / van Vuuren, 2 degrees under uncertainty

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Leads to the following questions: Is it possible to identify low-greenhouse gas
stabilisation pathways (‘LCS’) based on clearly
defined technologies?
 What could be the costs and benefits?
 Role of land-use as part-of-the-problem andpart-of-the-solution
 How do LCS’s link to sustainable
development?

Kram / van Vuuren, 2 degrees under uncertainty

4Analytical framework
 MNP Integrated global modelling system 17 regions and geographic land-use
 Captures most reduction options, including non-CO2,biofuels and C-sinks, CCS and also H2
 Climate and land-use important links to key SD issues:poverty&food, biodiversity

Kram / van Vuuren, 2 degrees under uncertainty

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Scenario approach CC targets exogenous, smooth transition paths
 Scenario development on the basis of selection ofleast cost options: cost-effectiveness analysis
 Full participation from 2013 onwards
 Main set-up:BaselineMitigation potential
Stabilization scenario
Interactions with SD explored

Kram / van Vuuren, 2 degrees under uncertainty

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Main framework of the project
IMAGE 2.3 : Integrated Assessment Model (Spatially
specific land + climate model 0.5 x 0.5 degree)
TIMER : Global Energy Model
FAIR : Climate Policy Tool
1TIMER 2.0Baseline

Baseline emissions andenergy MAC curves

2FAIR-SimCap
Emission profile

Emission reductions
and marginal price3
TIMER 2.0
Mitigation scenario

Fuel trade andenergy impacts

1

Biofuel potential
Emissions andbiofuel demand

IMAGE 2.3
Baseline

Baseline emissions andCP MAC curves

2
FAIR 2.0
Costs / reductions

2Non-CO2
MAC curves

Emission reductions
and CP demand

Emissions andbiofuel demand

3
IMAGE 2.3
Mitigation scenario

Land-use andclimate impacts
Kram / van Vuuren, 2 degrees under uncertainty

7Baseline – developments without
Climate Policy
40

Central case B2:Population 2100: 9 billion (UNmedium)B2 Baseline and other baselines

Emissions (GtC-eq)

30
IMAGE 2.3 B2IMAGE 2.3 A1b
IMAGE 2.3 B1

GDP growth: 2% per year

20

10
Grey area indicates
EMF21 range

01980

2000

2020

2040

2060

2080

2100

Energy: near IEA until 2030,
conventional development after2030

Kram / van Vuuren, 2 degrees under uncertainty

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GHG contribution by source
30
25

Non-CO2 - energy/industry
CO2 - energy/industry
Non-CO2 - land
CO2 - land

GtCO2-eq

20
15
1050
2000

2020

2040

2060

2080

2100

Kram / van Vuuren, 2 degrees under uncertainty

9Emission pathways that lead tostabilisation

1515151010105550900
900
800
700

Baseline
Baseline
650 ppm CO2eq
2550 ppm CO2eq
2450 ppm CO2eq

600
500
400

3.0
2.52.01980 2000 2020 2040 2060 2080 2100

 Criteria:
Annual reduction smooth : preferably
constant over time (and always < 3%).
Smooth transition in rate of reduction
If possible, avoid rapid early reduction
Stay below conc. level target (650,550) or
allow minimum overshoot (450)

1.00.0CS = 2.5
1980 2000 2020 2040 2060 2080 2100

Cumulative reduction• 650 GtC (30%)• 850 GtC (45%)• 1200 GtC (60%)

Kram / van Vuuren, 2 degrees under uncertainty

Den Elzen, Meinshausen and Van Vuuren.Multigas stabilisation pathways.

Baseline
Baseline
650 ppm CO2-eq2550 ppm CO22-eq
450 ppm CO2-eq

1.50.53001980 2000 2020 2040 2060 2080 2100

3.5

Increase
Increase ((ooCC ))GtC-eq
GtC-eq2020

Baseline
Baseline
Baseline
Baseline
650
COeq
650
650CO
CO222eqeq
550
COeq
550 CO22eq
450 CO2eq

ppmppm COCO22-eq-eq

25

Temperature

Concentration

Emissions10Low stabilization targets cut into land use
related emissions
3025

Non-CO2 - energy/industry
CO2 - energy/industry
Non-CO2 - land
CO2 - land

GtCO2-eq

2015650 ppm

10550 ppm
5450 ppm
02000

2020

2040

2060

2080

Kram / van Vuuren, 2 degrees under uncertainty

2100

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Reduction potentials (typical values)
Energy efficiency:
Wind/solar:
Biomass:
Nuclear:Non-CO2:
Sinks:CCS:
Fuel switch:
Other renewables:

300 GtC (20% improvement)
100 GtC - > 1000 GtC
200 GtC - 700 GtC (350 GtC)
>300 GtC
200 GtC-eq20-200 GtC
500-600 GtC
0-50 GtC>100 GtC

Compare: total required 650 – 1200 GtC

Kram / van Vuuren, 2 degrees under uncertainty

12Determining land use options: C-sinks
1. Determine where C-plantations can potentiallyabsorb more carbon than natural vegetation (bestspecies per climate zone)
2. Consider only abandoned agricultural land orgrassland ecosystems
3. Establish costs (labour, capital, rent and yield)

Kram / van Vuuren, 2 degrees under uncertainty

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Attractive locations for C-plantations

Ecal. camaldunensis
Ecal. grandis
Pinus radiata
Populus nigra
Picea abies
Larix Kaempferi

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Land use projection
Nature reserve
Forests
Ag. landSteppe/grassland
Improductive
Abondoned ag. land

Kram / van Vuuren, 2 degrees under uncertainty

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Establishing supply-cost curves

Kram / van Vuuren, 2 degrees under uncertainty

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Similar actions for bio-energy
Biomass, 2000

Biomass, 2050

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Mitigation scenarios – integrated analysis
450 CO2-eq

550 CO2-eq
3030252525201510
5Emissions (GtC-eq)

30
Emissions (GtC-eq)

Emissions (GtC-eq)

650 CO2-eq

201510520
151050007 0 90 10 3 0 5 0 70 90
19 1 9 2 0 20 2 0 20 20

7 0 90 10 3 0 50 70 9 0
19 1 9 2 0 20 2 0 20 20

7 0 90 1 0 30 50 7 0 90
19 1 9 20 2 0 2 0 20 2 0Sinks

OtherCCS

Nuclear, renewable

Non-CO2

Fuel switch

Biofuels

Efficiency

 Combination of options based on technical feasibility and costeffectiveness Main options short term: non-CO2, fuel switch (to NG); efficiency
 Main options long term: CO2 storage; Biofuels, Nuclear, (Efficiency)[Van Vuuren et al. Stabilising GHG emissions]
Kram / van Vuuren, 2 degrees under uncertainty

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Land use pattern in 450 ppm mitigation scenario(2100)

Forests
GrassDesert

Ice
TundraAgriculture
Ext. grassland
Kram / van Vuuren, 2 degrees under uncertainty

Bio-energy
C-plantation

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Marginal cost of stabilisation

Carbon tax ($/tC-eq)

800
700600650 CO2-eq
550 CO2-eq
450 CO2-eq

500
400
300
200
1000
1970 1990 2010 2030 2050 2070 2090

Van Vuuren et al. Stabilising GHG emissions. Kram / van Vuuren, 2 degrees under uncertainty

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Costs of stabilising emissions
Net present value of mitigation costs / NPV of GDP(5 % discount rate)
3.0%
2.5%
2.0%

B2A1b
B1

1.5%
1.0%
0.5%
0.0%
450

500

550

600

650

CO2-eq concentration

 Baseline just as important for costs as stabilisation level
Van Vuuren et al. Stabilising GHG emissions. Kram / van Vuuren, 2 degrees under uncertainty

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Costs of stabilising emissions (CO2!) compareswell with range in literature
NPV Abatement costs (Trillion US$)

25This article
IMAGE 2.2
Azar et al., in press
Rao and Riahi, 2006

20

15

10EMF-16/TAR(highest values)

50350

EMF-16/TAR(lowest values)

400

450

500

550

600

650

CO2 concentration (ppmv)
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Findings on LCS:
• Stabilizing GHG concentration at low levels in order tomeet 2 degree target technically feasible– possible with ‘known techniques’• Portfolio of options needed:– substantial contribution CCS and efficiency• Abatement-costs are in the order of a few percent of worldGDP, strongly depending on baseline developments• Uncertainties are crucial• Creating the right conditions is more challenging– Large changes in energy system required– Other barriers than costs– Sense of urgency needed– Linking with SD needs further investigation

Kram / van Vuuren, 2 degrees under uncertainty

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Linking CC policies with SD• Pay-off between costs and uncertainty:– 650 : 0.3% of GDP, 0-10% chance of meeting 2oC– 550 : 0.7% of GDP, 0-30% chance of meeting 2oC– 450 : 1.4% of GDP, 20-70% chance of meeting 2oC• CC impacts uncertain, disproportional on LDC
with lower coping capacity (IPCC-TAR)• How do CC mitigation actions interfere withother SD concerns like poverty, food&water,biodiversity?
• Some interactions tested, starting frombiodiversity in study for GBO-2 of CBD

Kram / van Vuuren, 2 degrees under uncertainty

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6 options elaborated until 2050 for GBO-2:
1. WTO liberalisation agricultural marked (land-use efficiency?)
2. WTO + Poverty alleviation in Africa (1.+SSA action)
3. More sustainable meat production (diet shift)
4. Climate mitigation (450 ppm as shown)
5. Sustainable forest (wood plantations)
6. Protected areas (20% per biome)

Kram / van Vuuren, 2 degrees under uncertainty

25Baseline: ongoing global loss of biodiversity (as MSA)

63%

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Option 1: Trade liberalization
Full implementation of WTO Doha Round from 2015:+ 6.5% agricultural area in Latin America & Southern Africa- 20% ag-land in OECD-Europe & N-America- 1.3% biodiversity (due to lower productivity)

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Option 2: Trade lib. + poverty alleviation SS-Africa
As option 1, plus:• ODA: investment 0,7% GNP• used to finance “plan Sachs” in SSA (example)+ 3% agricultural area (+ 25% SS Africa)+ 40% SS-African GDP- 0.4% biodiversity (-6% SS Africa)

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Option 4: Climate mitigation
Max temperature rise:
2 oC (after 2100) <-> 450 ppm
World energy use: 900 -> 650 EJ (efficiency increase)
Energy crops:
23% of total energy use
Expectation:• less CC: biodiv up• habitat loss for biofuel/C-plantations: biodiv down

+ 10% agricultural area (L-Am, S-Africa)
Area loss outweighs gains from less CC (long term?)

Kram / van Vuuren, 2 degrees under uncertainty

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climate option
Loss by:75%
Biodiversity

Level 2000

70%

agriculture

Energie crops
other65%

climate60%

55%
climate option
50%
2000

2010

2020

2030

2040

2050

Time
Kram / van Vuuren, 2 degrees under uncertainty

Time30Preliminary findings on LCS – SD linkage:• Inertia of climate and natural ecosystems pose
special problem: investments only pay on the very
long run at uncertain rate-of-return• Major challenge as both LCS, trade liberalizationand poverty reduction tend to increase pressure
on land and ecosystem values• Key factor: agriculture (land) productivity• Other positive linkages: air pollution and energy
security (not treated here)

Kram / van Vuuren, 2 degrees under uncertainty

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