economics of ghg management in the lulucf sector michael obersteiner jrc improving the quality of...
TRANSCRIPT
![Page 1: Economics of GHG Management in the LULUCF sector Michael Obersteiner JRC Improving the Quality of Community GHG Inventory… 22-23 rd Sept. 2005](https://reader033.vdocuments.net/reader033/viewer/2022051819/55153250550346a87d8b593a/html5/thumbnails/1.jpg)
Economics of GHG Management in the
LULUCF sector
Michael Obersteiner
JRCImproving the Quality of Community GHG Inventory…
22-23rd Sept. 2005
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INSEA-toolbox
Land Use/cover
Soil DB, Management
Ancillary Cost / Technology data
Non C-GHGs
Biomass crops
Sequestered carbon
20302000
2050
Climate
Change
Geography of Production Possibilities
Link to Energy Models
Food Crops / Wood
AgriculturalforestMarketModel
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Common Platform
Existing
Data
Engineering
Models
Biophysical Models
EconomicParameters
EnvironmentalImpact Data
Basic Technologies
Alternative Technologies
Existing
Data
Engineering
Models
Biophysical Models
EconomicParameters
EnvironmentalImpact Data
Basic Technologies
Alternative Technologies
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National Economic ModelsFASOM
Regional Farm Type Model
AROPAj
Farm ModelEFEM-DNDC
Stand level ModelPICUS
Regional Forest ModelEURO - FOR
Mod
el f
or G
HG
Res
pons
e to
Man
agem
ent
EP
ICC
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
All
Par
tne
rs
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National Economic ModelsAGRIPOL FASOM
Regional Farm Type Model
AROPAj
Farm ModelEFEM-DNDC
Stand level ModelPICUS
Regional Forest ModelEURO - FOR
Mod
el f
or G
HG
Res
pons
e to
Man
agem
ent
EP
ICC
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
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EPIC simulates many Processes:
on a daily time step
Weather: simulated or actualHydrology: evapotranspiration, runoff,
percolation, 5 PET equations,...Erosion: wind and water, 7 erosion equationsCarbon sequestration: plant residue, manure,
leaching, sediment,...Crop growth: NPK uptake, stresses, yields,
N-fixation,...Fertilization: application, runoff, leaching,
mineralisation, 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, trees,...
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EPIC/APEX Input data - Management
Crop rotation (crops, grass/legumes, trees)
• date of planting • date & amount of fertilization (kg/ha)• date & amount of irrigation (mm)• date & amount of pesticides (kg/ha of active
ingredients)• date of tillage operation (plough, harrow spike,
field cultivator, thinning,...) • date of harvesting (expected yield), grazing,...
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Yield Validation
0 2 4 6 8 10
02
46
81
0
FADN Yield (tha)
EP
IC Y
ield
(t/h
a)
BARLCORNCSILCSUNFALWFPEAGRCLPOTASGBTWRAPWRYEWWHT
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Erosion Conventional / Reduced Tillage
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Soil Organic Carbon Conventional / Reduced Tillage
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SOC
25
27
29
31
33
35
37
39
41
43
45
-30 -25 -20 -15 -10 -5 0 5 10
Years
SO
C i
n t
/ha
convTill redTill minTill covCrop
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National Economic ModelsAGRIPOL FASOM
Regional Farm Type Model
AROPAj
Farm ModelEFEM-DNDC
Stand level ModelPICUS
Regional Forest ModelEURO - FOR
Mod
el f
or G
HG
Res
pons
e to
Man
agem
ent
EP
ICC
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
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Emission trajectorium - Agriculture
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Animal numbers
Crop area
Pasture/Forage
Purchased Feed
On-farm consumption
Emissions RHS
Constraints C NC CH4 N2O
Objective + + + + - - -t -t
CH4 Enteric fermentation emissions
Cattle + + + + + + -1/23 = 0
Non-Cattle + + + + + + -1/23 = 0
CH4 Manure-management emissions
Cattle + + + + + + -1/23 = 0
Non-Cattle + + + + + + -1/23 = 0
CH4 rice production + + -1/23 = 0
N2O Manure management emissions + + -1/296 = 0
N2O Agr soils direct emissions + + + + -1/296 = 0
N2O Agr soils indirect emissions + + + + -1/296 = 0
N2O Agr soils animal production + + -1/296 = 0
Emission accounting: Overview
Emissions factors
GWPs
Tax (€/tCO2)
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Constraints Animal numbers
Crop area
Pasture/Forage
Purchased Feed
On-farm consumption
Emissions RHS
C NC CH4 N2O
Objective + + + + - - - -
Feed requirementsEnergy
+ + - - - - - - <= 0
Protein + + - - - - - - <= 0
Maximum ingested matter (cattle) + - - - - - - => 0
Demography (cattle) +/- = 0
CH4 Enteric fermentation emissions + + + + + + - = 0
CH4 Manure management emissions + + + + + + - = 0
N2O Manure management emissions + + - = 0
N2O Agr soils emissions + + + + - = 0
Animal feeding : current modelling approach (cont’d)
Needs
Energy and protein contents of feed
CapacityTotal matter in feed
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Animal numbers
Crop area
Pasture/Forage
Forest area
Purchased Feed
On-farm consumption
Emissions RHS
Constraints C NC C CH4 N2O
Objective + + + + + - - +t -t -t
Carbon sequestration + -12/44 =0
CH4 Ent fermentation emissions
Cattle + + + + + + -1/23 = 0
Non-Cattle + + + + + + -1/23 = 0
CH4 Man-manag emissions
Cattle + + + + + + -1/23 = 0
Non-Cattle + + + + + + -1/23 = 0
CH4 rice production + + -1/23 = 0
N2O Man man emissions + + -1/296 = 0
N2O Agr soils dir emissions + + + + ? -1/296 = 0
N2O Agr soils indir emissions + + + + ? -1/296 = 0
N2O Agr soils anim production + + -1/296 = 0
Emission accounting: including forestry activitiesPremium
(€/tCO2)
Sequestration rate (tC/ha/yr)
NPV (€/ha/yr)
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EU-15 agricultural abatement supply
-8% / 2001(-15% /1990)
55 EUR/tCO2eq
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Infra-regional downscaling(e.g. Baden-Württemberg)
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Baseline emissions by source (GWP: CH4=23, N2O=296)
CH4 Enteric ferment. Total
Dairy
Non-dairy
CH4 Manure management Total
Dairy
Swine
N2O Manure management Total Synth fertilizers
Anim. wastes applied to soils
Crop ResidueN2O Agr. soils Dir. Emiss. Subtot
Atm. depositionLeaching and run-off
N2O Agr. soils Indir. Emiss. Subtot
N2O Agr. soils Animal production
other N2O
N2O fertilizer productionCO2 fertilizer prod.CO2 energy plantsCO2 plant dryining
CO2 Pflanze
CO2 purchase feedstuffCO2 energy animals
CO2 animal production
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
UHOH Emissions INRA (1) Emissions INRA (2) Emissions
ktC
O2
INRA/UHOH comparison:Baseline emissions by sources
Common emission coverage
UHOH: 5092 ktCO2eq INRA: 5115
ktCO2eq
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0,000
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
0 10 20 30 40 50 60 70 80 90 100
Tax (EUR/tCO2)
Ab
atem
ent
(ktC
O2)
0%
2%
4%
6%
8%
10%
12%
14%
INRA estimates of marginal abatement costs
BW
Germany
EU-15
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Cost are different for different farmers…..
-80 -60 -40 -20 0
01
00
02
00
03
00
04
00
05
00
06
00
0
Per-tC net impact on revenue (minimum tillage, population-weighted)
EUR/tC
Nu
mb
er
of f
arm
s
Mean: StdVar: Min: Max: N: Total:
Sample -4.3 EUR/tC 12.1 EUR/tC -86 EUR/tC 8.6 EUR/tC
561 farms -0.49 10^6 EUR
Total -3.8 EUR/tC 11.9 EUR/tC -86 EUR/tC 8.6 EUR/tC
22728 farms -13.4 10^6 EUR
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National Economic ModelsAGRIPOL FASOM
Regional Farm Type Model
AROPAj
Farm ModelEFEM-DNDC
Stand level ModelPICUS
Regional Forest ModelEURO - FOR
Mod
el f
or G
HG
Res
pons
e to
Man
agem
ent
EP
ICC
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
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PICUS 2.0
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Forestry modeling framework
Forestry output:•C storage (soil, biomass)•Wood •Energy biom.•Forested area
Alternatives:•C storage •Wood •Energy biom.
•managementscenarios: (harvest, thinning, species)
•potential NPP•Initial state forest and soil
climate
FASOM model-economic optimization of land use
OSKAR model-forestry scenarios NPP model
•management costs
•prices
•alternative land uses
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OSKAR model output for a HRU
area size
(m2)
Biomass Management scenario and predicted production (wood, carbon storage, energy)
1 A1 B1 m1 p1 m2 p3 m3 p3 m4 p4 ...
2 A1 B2
3
.
.
.
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Forest growth
•Density dependent growth
0 50 1000
1
22
0
GN b 1 1( )
GN b 1 0.1( )
GN b 2 0.01( )
GN b 2 1( )
1000 b
biomass
biom
ass
incr
emen
t
0 50 1000
1
22
0
GN b 1 1( )
GN b 1 0.1( )
GN b 2 0.01( )
GN b 2 1( )
1000 b
biomass
biom
ass
incr
emen
t
0 100 2000
50
10099.989
0
B 0.1 1 t 0.01( )
B 0.1 2 t 0.01( )
B 0.1 1 t 1( )
B 0.1 2 t 1( )
2000 ttimest
andi
ng b
iom
ass
0 100 2000
50
10099.989
0
B 0.1 1 t 0.01( )
B 0.1 2 t 0.01( )
B 0.1 1 t 1( )
B 0.1 2 t 1( )
2000 ttimest
andi
ng b
iom
ass
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Density and stand development
•Thinning and Self-thinning•Artificial and Natural regeneration•Impact of Management of Soil carbon
•Regeneration and final Cutting•Species Change•Flexible Rotation Periods
growth thinning
self-thinning
biomass
soil carbon
mortality
decomposition
CO2
density
ste
m b
iom
ass 20%
70%
0%
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National Economic Models
FASOM
Regional Farm Type Model
AROPAj
Farm ModelEFEM-DNDC
Stand level ModelPICUS
Regional Forest ModelEURO - FOR
Mod
el f
or G
HG
Res
pons
e to
Man
agem
ent
EP
ICC
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
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Basic Modeling
Processing
Markets
Feed Mixing
Other Resources
Grazing
Labor
Pasture Land
Natl. Inputs
Forestland
Water
Livestock Production
CropProduction
Export
DomesticDemand
Import
Biofuel/GHGDemand
ForestProduction
Cropland
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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
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Land Use Change until 2100 for B1Intensity map: (affected) ha x C-uptake
Existing forestAfforestationDeforestation
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Spatial Distribution of GDP
• Important inputs to the spatially explicit forestry and regional agricultural model
• Necessary information for vulnerability, adaptation and impact assessment
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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
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Summary
• Detailed Biophysical Models– Yield Impacts– Environmental Impact Assessment
• Integrated from Farm – Global Agriculture/Forestry/Energy Model
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Conclusion
• No free lunches after CP1– transfer from Energy sector
• Trade-offs (Ammonia vs N2O, Minimum tillage vs. Pesticides, Carbon vs. Bioenergy)
• Heterogeneity in biophysical and economic responses.
• Catastrophic events (e.g. fire)• Transaction costs
• Use economic instruments or very well planned traditional (supported by precise scientific tools)
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Carbon permitElectricityElectricity Pulp / paper
Biomass
Energy Market
Policy
Climate PolicySector Policy /
Technology
Land use Policy
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Modular Commitment Strategy
CO2 El
BM \pi
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Model description
Objective: Maximize the value of the forest
Source: www.whrc.org/science/ neforest
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Results
Red – postpone decision Blue - harvest
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ResultsTime State of forest Price Decision
0 1040 15 Delay1 1051.861 15.624 Delay2 1063.262 17.97 Delay3 1074.212 17.662 Delay4 1084.723 19.157 Delay5 1094.806 22.161 Harvest6 60.976 26.303 Delay7 78.218 30.217 Delay8 96.536 31.244 Delay9 115.787 31.272 Delay
10 135.859 30.129 Delay11 156.656 36.132 Delay12 178.097 35.237 Delay13 200.11 44.464 Delay14 222.627 46.306 Delay15 245.586 43.225 Delay16 268.927 47.859 Delay17 292.594 52.41 Delay18 316.533 57.341 Delay19 340.69 60.63 Delay20 365.014 58.197 No dec. possible
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Example with 5 biofuel plants
Cars Fuel (MW)Bio
(ODT/year)
461500 185 521100
514300 206 580800
1E+06 463 1307600
462300 185 522100
362800 145 409700
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Cost in €/GJMEOH
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Cost in € / lMEOH
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Assessing abatement costs in LULUCF sector
• Can agriculture&forestry contribute to lower the costs of meeting the KP targets? ….beyond
• How much EU LULUCF abatement for a given carbon price?
• Regional and technological distribution of abatement potential?
• Link between GHG sector– Bioenergy supply– CAP– Soil thematic strategy, CAFE, Water directive….
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Background
• The Kyoto Protocol requires that EU-15 reduces its GHG emissions by 8% / 1990 levels (time horizon 2008-12)
• Agriculture represents ~10% of EU GHG emissions – No commitment despite possible wellfare increases
• Agricultural and climate/env policies at a crossroad– Emission Trading Scheme (inclusion of agricultural emissions
and sinks? – 23 EURO/tC)– CHP directive, Biomass Action Plan– Clean Air, Nitrate etc…directives, STS– CAP reform and cross-compliance
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…the Challenge ahead….
• Identification of integrative, effective and efficient Policies– Competitiveness & New Markets– Rural Development– Environmental Performance
• Transition planning– Mechanism design– Timing– Precise Planning and Forecasting
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Distribution of BARLEY_REST and MAIZETOT on arable land of Baden-Württemberg as a result of LUCAS Data Broker
BARLEY_REST MAIZETOT
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National Economic ModelsAGRIPOL FASOM
Regional Farm Type Model
AROPAj
Farm ModelEFEM-DNDC
Stand level ModelPICUS
Regional Forest ModelEURO - FOR
Mod
el f
or G
HG
Res
pons
e to
Man
agem
ent
EP
ICC
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
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Farm-level model
EFEMEFEM EPIC
soil mapsoil map land use mapland use map climate dataN- depositionclimate data
N- deposition
GISdatabase
GISdatabase
crop areafertilizer intensityC + N of manure
crop areafertilizer intensityC + N of manure
C-balanceSOC, C- pools
emissions (soil)N2 O, CH4 , CO2
leachingNO3 , DOC
C-balanceSOC, C- pools
C-balanceSOC, C- pools
emissions (soil)N2 O, CH4 , CO2
emissions (soil)N2 O, CH4 , CO2
leachingNO3 , DOC
leachingNO3 , DOC
farm emissionsN2 O, CH4 , CO2 , NH3
return ratesshadow prices
mitigation costseconomic indicators
farm emissionsN2 O, CH4 , CO2 , NH3
farm emissionsN2 O, CH4 , CO2 , NH3
return ratesshadow prices
mitigation costseconomic indicators
return ratesshadow prices
mitigation costseconomic indicators
EFEM-DNDC/EPICmanagement
phenologymanagement
phenology
farmstructures
farmstructures
politicalenvironment
politicalenvironment
economicindicatorseconomicindicators
emissionfactors
emissionfactors