economics of ghg management in the lulucf sector michael obersteiner jrc improving the quality of...

Economics of GHG Management in the

LULUCF sector

Michael Obersteiner

JRCImproving the Quality of Community GHG Inventory…

22-23rd Sept. 2005

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

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

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

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

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,...

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,...

Yield Validation

0 2 4 6 8 10

02

46

81

0

FADN Yield (tha)

EP

IC Y

ield

(t/h

a)

BARLCORNCSILCSUNFALWFPEAGRCLPOTASGBTWRAPWRYEWWHT

Erosion Conventional / Reduced Tillage

Soil Organic Carbon Conventional / Reduced Tillage

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

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

Emission trajectorium - Agriculture

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)

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

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)

EU-15 agricultural abatement supply

-8% / 2001(-15% /1990)

55 EUR/tCO2eq

Infra-regional downscaling(e.g. Baden-Württemberg)

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

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

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

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

PICUS 2.0

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

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

.

.

.

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

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%

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

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

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

Land Use Change until 2100 for B1Intensity map: (affected) ha x C-uptake

Existing forestAfforestationDeforestation

Spatial Distribution of GDP

• Important inputs to the spatially explicit forestry and regional agricultural model

• Necessary information for vulnerability, adaptation and impact assessment

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

Summary

• Detailed Biophysical Models– Yield Impacts– Environmental Impact Assessment

• Integrated from Farm – Global Agriculture/Forestry/Energy Model

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)

Carbon permitElectricityElectricity Pulp / paper

Biomass

Energy Market

Policy

Climate PolicySector Policy /

Technology

Land use Policy

Modular Commitment Strategy

CO2 El

BM \pi

Model description

Objective: Maximize the value of the forest

Source: www.whrc.org/science/ neforest

Results

Red – postpone decision Blue - harvest

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

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

Cost in €/GJMEOH

Cost in € / lMEOH

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….

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

…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

Distribution of BARLEY_REST and MAIZETOT on arable land of Baden-Württemberg as a result of LUCAS Data Broker

BARLEY_REST MAIZETOT

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

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