Michael ObersteinerMichael Obersteiner
IIASAIIASA
Regional Carbon Budgets: From methodologies to Regional Carbon Budgets: From methodologies to quantification.quantification.
Beijing, China, 15-18 November 2004Beijing, China, 15-18 November 2004
Coupling Carbon Coupling Carbon Processes and Processes and
EconomicsEconomics
Overview
• Motivation to manage the carbon cycle– Financial Analyst´s point of view
• Scenarios of what needs to be done– What is the biospheric contribution
• More trade offs than synergies
Effective compliance with Art. 2 UNFCCC!?
Risk analysis… the Chartist
Nokia
Ericsson Siemens
Siemens
Ericsson
Nokia
Buy Gold
Data is from the climate system!!!
GISP and IPCC data, own calculations
Concentration
s
Growing
No
AnalogueLevel&speed
High volatility
Abrupt
Chang
e
The obvious number!?
371, ….550,….750…?
Which number would you pick…..?
Gold from Science?
• IPCC for the 4th assessment emission scenarios that lead to concentrations of <450 are not planned
• No low emission climate runs
• No benchmark
Climate Risk Management -Ostriching?
Climat
e
• Stabilization target is a SOCIAL CONSTRUCTION – Plausibility of
stabilization targets
• Little preparation
How to stabilize atmospheric CO2 concentrations
• Use less energy– Improve energy efficiency– Life style changes– Stabilize population
• Use other forms of energy– Natural gas instead of coal– Renewables– Nuclear
• Capture and store carbon – From fossil fuels and/or biomass (in energy conversion plants)– From the atmosphere (in trees, soils or in CO2 capture facilities)
Spatial Distribution of GDP
• Important inputs to the spatially explicit forestry and regional agricultural model
• Necessary information for vulnerability, adaptation and impact assessment
The cost to stabilise the atmosphere
Global GDP
0
50
100
150
200
250
1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
Year
Trillio
n U
SD/y
r
Bau
350 ppm
450 ppm
550 ppm
Source Azar & Schneider, 2002. Ecological Economics
• The figure shows the The figure shows the various sources of various sources of GHGs and the GHGs and the mitigation achieved mitigation achieved from the baseline in the from the baseline in the A2 mitigation scenarioA2 mitigation scenario
• Energy represents the Energy represents the top sector for potential top sector for potential mitigationmitigation
• Sinks contribute Sinks contribute significantly in significantly in reduction of forest CO2reduction of forest CO2
-4000
6000
16000
26000
36000
46000
56000
2000 2020 2040 2060 2080 2100
To
tal
GH
G E
mis
sio
ns
(MtC
eq
uiv
.)
Energy
Industry Agriculture
Mit
igati
on o
f CO
2, CH
4,
N2O
and o
ther
GH
GS
Forest emissions (negative)
A2-Stabilization Scenario(Fossil Intensive)
CO2-concentration 350 ppm, with capture
Supply
0
100
200
300
400
500
600
700
800
2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
EJ/yr
nuclear
coal
oil
solar H2
bio fuels
solar electr.
wind
gas
solar heat
hydro
coal w capt.
gas w capt.
bio w capt.
Herzog et al Scientific American, February 2000.
with structural traps
130 – 500 Gton C
30 – 650 Gton C
Enhanced oil recovery
20 – 65 Gton C
Grimston et al (2001).
Carbon storage possibilities
• Biophysical– Climate, CO2
etc…
– Land Cover
– Relief
• Socioeconomic– Population
– GDP
– Forest sector
Forest and agri growth modeled
1. LUC2. C sequestration/GHGs3. Bio4BE production
Land values
LU competition
Management
options applied
Input OutputModeling
National Economic ModelsScenario Market
Regional Farm Type Models
Farm Models Stand level Models
Regional Forest Models
Mod
el f
or G
HG
Res
pons
e to
Man
agem
entC
om
mo
n D
ata
ba
se
a
nd
Sta
nd
ard
s
• Common Database and Data Structure• Harmonized System Boundaries• IPCC GPG and /or FGA Accounting• Consistent Baseline Assumptions• Joint Catalogue of GHG Mitigation Measures• Uniform Validation Criteria• Agreed Sustainability Constraints• Common IT Standards• Standard Scenario Assumptions and Story Lines• Joint Vision
INTEGRATED POLICY FRAMEWORK
Geo
refe
renc
ed
Dat
aba
se
EPIC simulates many processes:
Weather: simulated or actualHydrology: evapotranspiration, runoff,
percolation, 5 PET equations,...Erosion: wind and water, 6 erosion equations,...Carbon sequestration: plant residue, manure,
leaching, sediment, ...Crop growth: NPK uptake, stresses, yields,
N-fixation,...Fertilization: application, runoff, leaching,
mineralization, denitrification, volatilization, nitrification,...
Tillage: mixing, harvest efficiencies,...Irrigation and furrow diking,...Drainage: depth,... Pesticide: application, movement,
degradation,...Grazing: trampling, efficiency,...Manure application and transport,...Crop rotations: inter-cropping, weed,
competition, annual and perennial crops,...on a daily time
step
Geography of Analysis
Soil H R UTopography H R UC lim ate H R U
Intersection
etc.
EPIC HRU
PICUS 2.0
Overview of the Regional Agri-Model
Data(FADN)
- Yields- Area- Variable costs- Producing activities- Size of farms- Altitude- …
Other sources
- Emissions coefficients- Soils characteristics- Fertilizer uses and prices- …
Typology15 countries, 101
regions734 farm-types
Model inputs- Prices- Technical parameters- CAP-related parameters
Calibration
734 modelsMaximize gross margin
Subject to :- Technical constraints
- Policy constraints
Model output- Optimal area- Livestock numbers- Animal feeding- Net emissions
Estimation
Basic Modeling
Processing
Markets
Feed Mixing
Other Resources
AUM Grazing
Labor
Pasture Land
Natl. Inputs
Forestland
Water
Livestock Production
CropProduction
Export
DomesticDemand
Import
Biofuel/GHGDemand
ForestProduction
Cropland
Mitigation Strategy Equilibrium
0
100
200
300
400
500
0 20 40 60 80 100 120 140 160 180 200
Car
bon
pri
ce (
$/tc
e)
Emission reduction (mmtce)
CH4N2O
Ag-Soil sequestration
Afforestation
Biofuel offsets
Afforestation in B1
Carbon SequestrationTotal Carbon Supply: B1/A2
Cumulative C-sequestration potential in B1
0
50
100
150
200
250
300
350
0 100 200 300 400
GtC
C-p
ric
e [
$/t
C]
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
Cumulative C-sequestration potential in A2
0
50
100
150
200
250
300
350
-100 0 100 200 300
GtCC
-pri
ce
[$
/tC
]
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
Bioenergy Supply for 2000-2100 B1 (Price < 6$/GJ)
Land Use Change until 2100 for B1Intensity map: (affected) ha x C-uptake
Existing forestAfforestationDeforestation
Wrap-up
• Slumbering Beast
• Much lower stabilization targets are NECESSARY AND PLAUSIBLE
• The Problem is currently with the fossil fuels and a large(st) potential of the solution is in the Agri&Forestry&Bioenergy sector.
Winning is not easy
• Carbon price (tax or
cap-and-trade system)
• Energy efficiency standards
• Support technology development
• Agi&Forestry market reform
• Minimize associated social and environmental costs
-4000
6000
16000
26000
36000
46000
56000
2000 2020 2040 2060 2080 2100
To
tal
GH
G E
mis
sio
ns
(MtC
eq
uiv
.)
Energy
Industry Agriculture
Mit
igati
on o
f CO
2, CH
4,
N2O
and o
ther
GH
GS
Forest emissions (negative)
0
5
10
15
20
25
30
35
1980 1990 2000
GW
THANK YOU!
371, ….550,….750…?
Carbon permitElectricityElectricity Pulp / paper
Biomass
Energy Market
Policy
Climate PolicySector Policy /
Technology
Land use Policy
Modular Commitment Strategy
CO2 El
BM \pi
Diversity of Approaches
• Engineering models & Biophysical Model
• Equilibrium Approaches (Static – Dynamic)
• Spatially Explicit and Multisectoral
• Risk and Uncertainty Augmented
Goal
• Contribute to integrate sinks in ETS– GPG (accounting, certification, verification)– Cost competitiveness and potentials– Transaction Cost
• Contribute to policy formulation– CAP– Energy– Climate – Forestry– Clean Air– …
Policy Integration
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