Hannes B

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Scenarios of global climate change mitigation
through competing biomass management options

• Hannes Böttcher1, Petr Havlík1, Arturo Castillo
  Castillo2, Jeremy Woods2,
• Robert Matthews3, Jo House4, Michael Obersteiner1
• 1 International Institute for Applied Systems
  Analysis, Schlossplatz 1, A-2231 Laxenburg,
  Austria
• 2 Centre for Environmental Policy, Faculty of
  Natural Sciences, Imperial College London, South
  Kensington campus, London SW7 2AZ, United Kingdom
• 3 Forest Research, Alice Holt Lodge, Farnham,
  Surrey GU10 4LH, United Kingdom
• 4 Department of Earth Sciences, University of
  Bristol, Wills Memorial Building, Queen's Road,
  Clifton, Bristol BS8 1RJ, United Kingdom
• bottcher_at_iiasa.ac.at
• IIASA Forestry Program
• Laxenburg, Austria

QUEST AIMES Earth System Science Conference
Edinburgh, May 10-13 2010
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Background

• Many countries have set up bioenergy policies to
  support and regulate the production and use of
  fuels from biomass feedstocks (e.g. US, EU,
  Brazil, China, India)
• But biofuels are hotly debated today because
  their overall impacts are uncertain and difficult
  to assess, being highly dependant on both the
  bioenergy fuel chain (choice of crop and
  technology), and on the existing land use
• Direct biofuel benefits are linked to indirect
  land use impacts and adverse externalities
  regarding GHG emission balances, ecosystem
  services, and security of food and water
• In particular, the implementation of biofuel
  targets might conflict with other mitigation
  options like avoided deforestation or enhancing
  forest carbon stocks

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Effective mitigation
Obersteiner, Böttcher et al. accepted COSUST
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High hopes
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QUATERMASS Overview
Atmospheric greenhouse gases
Synthesis Policy Analysis (Imperial College)

• Global-regional scale impacts opportunities
  modelling
• (IIASA)

Regional to local impacts opportunities
modelling (Forest Research and Aberdeen)
Local impacts opportunities modelling Ground-tr
uthing / Case studies (Ecometrica)
Feedback Communication
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Model description GLOBIOM

• Global Biomass Optimisation Model
• Coverage global, 28 regions
• 3 land based sectors
• Forestry traditional forests for sawnwood, and
  pulp and paper production
• Agriculture major agricultural crops
• Bioenergy conventional crops and dedicated
  forest plantations
• Optimization Model (FASOM structure)
• Recursive dynamic spatial equilibrium model
• Maximization of the social welfare (Producer
  plus consumer surplus)
• Partial equilibrium model (land use sector
  only) endogenous prices
• Output
• Production
• Consumption
• Prices, trade flows, etc.

Havlik et al. 2010 Energy Policy
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GLOBIOM Global Biomass Optimisation Model

• Integrated land-use and bioenergy modelling
• World divided into 28 regions

Havlik et al. 2010 Energy Policy
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Model description Supply chains
Unmanaged Forest
Forest products Sawnwood Woodpulp
Wood Processing
Managed Forest
Energy products Ethanol (1st gen.) Biodiesel
(1st gen.) Ethanol (2nd gen) Methanol Heat Power G
as Fuel wood
Short Rotation Tree Plantations
Bioenergy Processing
Cropland
Crops Barley Corn Cotton
Grassland
Livestock Feeding
Livestock Animal Calories
Other Natural Vegetation
Havlik et al. 2010 Energy Policy
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Model description EPIC Agriculture

• Crop related parameters SimU ? EPIC
• Major inputs
• Weather
• Soil
• Topography
• Land management
• Major outputs
• Yields
• Environmental variables
• 4 management systems
• High input, Low input, Irrigated, Subsistence

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Model description EPIC - Yields
Yields
Emissions
Carbon stock
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Model description Forest plantations
Productivity distribution
Productivity m3/ha
Area Mha
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Uncertainty of land cover

• Mapping errors
• Classification errors
• Validation of global land cover www.geo-wiki.org
• Associated land use allocation

Bellarby et al. 2010, see poster
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Detailed bioenergy chains (not yet fully
implemented)
Feedstock Process Current land use Energy generation Chains
Sweet sorghum 1 Convntl. Ethanol 1st G 2 Advanced Ethanol 2nd G 1 Degraded pasture 2 Existing cropland 3 Marginal/abandoned 4 Grassland 1 Residue boiler CHP 2 Residue boiler grid electricity 3 Diesel genset 24
Wheat 1 Convntl. Ethanol 1st G 2 Advanced Ethanol 2nd G 1 Degraded pasture 2 Set-aside 3 Grassland 4 Existing cropland 1 NG boiler ST 2 NG grid electricity 3 CCGT 4 Straw boiler ST 5 Biogas CHP 40
Palm oil 1 Convntl. Biodiesel 1st G 1 Existing cropland 2 Degraded pasture 3 Forest 4 Grassland (Imperata) 1 Oil boiler ST 2 Oil CHP 3 Residue boiler ST 12
Soy 1 Convntl. Biodiesel 1st G 1 Grassland 2 Existing cropland 3 Set-aside 4 Forest 1 NG boiler ST 2 NG grid electricity 3 CCGT 4 Straw boiler ST 16
Castillo et al. 2010, see poster
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Policy scenarios

• Baseline without any additional bioenergy NO
  bioshock
• Bioenergy demand increased by 50 in 2030
  compared to baseline 50 bioshock
• REDD, decreasing deforestation emissions by
  50/90 in 2020/2030 compared to baseline NO
  bioshock RED
• Combination of Bioenergy and REDD 50 bioshock
  RED
• Two alternative modeling settings
• without biofuel feedstock trade
• with biofuel feedstock trade

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Land use change implications of bioenergy
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Impact of bioenery demand on land use
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Land expansion localisation cropland
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Impacts of REDD policies
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Deforestation from cropland expansion
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Effect of REDD policydifference between
bioenergy and bioenergyREDD scenario
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Importance of trade
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Deforestation due to biofuel expansion
Mha, based on WEO 2020 targets, If not
constrained (e.g. by REDD) important
deforestation occurs
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Deforestation due to EU biofuel expansion
In Mha, EU mandates in 2020 put pressure on
deforestation elsewhere even without trade iLUC!
With trade
Without trade
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World biofuel expansion and crop prices
Crop price index, avoiding deforestation further
increases the effect of biofuels on crop prices
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Conclusions (1)

• Biofuel expansion generates important indirect
  GHG emissions (iLUC)
• Trade lowers global deforestation pressure by
  iLUC
• Dimension of iLUC depends more on efficient
  sourcing of biofuels than on the global scale of
  production
• Policies (like REDD) aiming at (i)LUC effects
  will put pressure on crop prices
• How will management systems adapt?

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Conclusions (2)

• Decreasing the human footprint on the atmosphere
  will necessitate active management of terrestrial
  C pools and GHG fluxes
• Most options might appear as competitive
  mitigation measures from an economic point of
  view
• But issues of governance remain most contentious
  as they induce competition for land and other
  ecosystem services

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Status of global forest certification
Certified forest area relative to area of forest
available for wood supply
Kraxner et al., 2008
compiled from FAO 2005, 2001 CIESIN 2007, ATFS
2008 FSC 2008 PEFC 2008
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• Thank you!
• bottcher_at_iiasa.ac.at

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Additional slides
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The perfect assessment

• Space Including indirect land use effects by
  budgeting all land categories to achieve global
  consistency of local action.
• Time Integrate benefits of measures over time
  and allow for the probability of innovative new
  technologies to occur.
• Sector Sector interaction needs to be considered
  in terms of direct provisioning services such as
  timber, bioenergy, food and more indirect such as
  biodiversity, water, cultural heritage. In
  addition, accounting for market feedback effects
  such as price increases of agricultural
  commodities due to bioenergy policy shocks need
  to be considered.
• Technology The full chain of GHG emissions from
  cradle to grave and production systems need to be
  assessed with respect to polyproduction.
  Interaction with the rest of the technosphere and
  social sphere need to be considered within
  integrated assessments.

Obersteiner, Böttcher et al. accepted COSUST
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Model presentation Livestock (ILRI)
Livestock Production System Approach (14 systems)
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Baseline description (1)

• Baseline is consistent with POLES energy
  projection
• Base year 2000 (determined by land cover
  information)

Variable  2000  2020  2030 Source 
General Population (billion) 6.1 7.6 8.3 POLES
General GDP (USD per Capita) 6720 11282 13928 POLES
General Vegetable calories (kcal per capita) 2322 2446 2467 FAO
General Animal calories (kcal per capita) 385 447 477 FAO
Bioenergy Biofuels 1st GEN (1000 ktoe final energy) 10 88 139 POLES
Bioenergy Biomass electricity (Heat) (1000 ktoe primary energy) 51 273 515 POLES
Bioenergy Direct Biomass Use (1000ktoe primary energy) 945 1172 1278 POLES
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Baseline description (2)
Variable 2000 Source 2020 2030 Source
Wood (logs) demand (1000 m3) Demand for sawn wood, pulp wood, other IR 1588947 FAO 2126868 2426985 GLOBIOM
Traditional use (1000 m3) Fuel wood use 2061440 FAO 2182681 2379203 FAO GLOBIOM
Variable Value Source
Protected land World Database on Protected Areas areas excluded WDPA
Forestry Current rotation length to be applied in G4M, Carbine?  
Forestry Rotation maximizing timber supply not applied  
Forestry Rotation maximizing carbon storage not applied  
Deforestation Deforestation rate based on past data FAO, national data
Deforestation Deforestation reduction not applied  
Deforestation Degradation rate not included  
Afforestation Afforestation rate based on past data FAO, national data
Biodiversity Biodiversity not constrained  
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Further developments
Infrastructure scenarios

• Current status from GIS database (circa 2000)
• Projected road network proposed by the African
  Development Bank (Buys et.al, 2006)
• Mean accessibility in the region will be reduced
  from 40 to 23 hours

Current road network
Planned road network
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