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Bio-energy in the context of the IMAGE 2 model

Detlef van Vuuren. Bio-energy in the context of the IMAGE 2 model. Bio-energy modelling in IMAGE. Potential for bio-energy use Integrated scenarios Model improvements. Bio-energy - key issues. What is the potential for bio-energy; and from which sources (types of land)?

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Bio-energy in the context of the IMAGE 2 model

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  1. Detlef van Vuuren Bio-energy in the context of the IMAGE 2 model

  2. Bio-energy modelling in IMAGE • Potential for bio-energy use • Integrated scenarios • Model improvements Van Vuuren, Mitigation scenarios

  3. Bio-energy - key issues • What is the potential for bio-energy; and from which sources (types of land)? • Does bio-energy production lead to competion over land with food? • What is the net impacts of bio-energy on GHG emissions and use of fossil fuels? • What is the impact of bio-energy on biodiversity? • How can bio-energy best be applied? In which sectors? Van Vuuren, Mitigation scenarios

  4. Bio-energy - key issues • Questions surrounding bio-energy are complex: involve energy systems, agricultural systems, details on land use, details on technology. • Different methods (economic modelling, IAM, LCA etc.) are therefore likely to give only partial answers. • IMAGE/TIMER strenght: • Coupling land / energy model • Spatial explicit Van Vuuren, Mitigation scenarios

  5. Emissions IMAGE Land use Climate TIMER Energy Potential for bioenergy GHG emissions+ Demand for bio-energy land Food demand& Production (GTAP, IFPRI) Bio-energy in IMAGE 2.3 Van Vuuren, Mitigation scenarios

  6. 1. Determining bio-energy potential Van Vuuren, Mitigation scenarios

  7. Rain fed energy crop productivity Climate change Geographical potential Land use scenario Food demand, trade and technology Land-claim exclusion factor Technological change: management factor Energy potential from biomass: calculation procedure Step 1 Determine land for food production based on land use model – and set aside Step 2 For other land use types, determine for each land category its suitability for energy crops based on yields and choice to use this category Step 3 Translate grid-cell information into cost-supply curves on the basis of costs estimates and differences in yields. Van Vuuren, Mitigation scenarios

  8. Energy potential from biomass: calculation procedure Electric power Industry Residues BSF Feedstock Transport Woody BLF Maize Sugar Van Vuuren, Mitigation scenarios

  9. Dev-ing Dev-ed 90000000 60000000 80000000 50000000 TG 70000000 60000000 40000000 50000000 30000000 40000000 20000000 30000000 20000000 10000000 10000000 0 0 2000 2050 2000 2050 Dev-ing Dev-ed 90000000 60000000 80000000 50000000 70000000 60000000 40000000 50000000 30000000 OS 40000000 20000000 30000000 20000000 10000000 10000000 0 0 2000 2050 2000 2050 Land use scenarios Other land Ab. Agriculture land Inproductive Agriculture Forest Nature reserve Van Vuuren, Mitigation scenarios

  10. 2080 2020 2060 2040 2100 2000 Land use pattern (AM scenario) Van Vuuren, Mitigation scenarios

  11. Land for woody biomass energy crops: areas vs. productivity Change in land productivity from improved technology/management and fertilization effect 1.2 A1_2000 1 A1_2050 climate + CO2 effect only 0.8 Area (Gha) 0.6 A1_2050 climate + CO2 fert. and technological improvement 0.4 0.2 0 0 5 10 15 20 25 30 35 40 45 50 55 -1 -1 Productivity of woody energy crops (ton ha y ) The simulated productivity of woody biomass energy crops at the total global terrestrial surface for two SRES scenarios (A1 and B2). A curve is given for both the current (2000) and future (2050) situation, with and without technological improvements taking into account CO2 fertilisation effect. Van Vuuren, Mitigation scenarios (Hoogwijk et al. 2004)

  12. Land cost = Land price / yield Capital / labour cost = Calibrated Cobb-Douglas Transport costs = Local transport costs Regional costs of bio-energy production Woody biomass ($/GJ) Van Vuuren, Mitigation scenarios (Hoogwijk et al. 2004)

  13. Energy crops: World cost-supply curves 2050 (Woody) World 2000: total energy use: 400 EJ trad biomass: 38 EJ comm biomass: 7 EJ Van Vuuren, Mitigation scenarios (Hoogwijk et al. 2004)

  14. Regional and crop specific cost curves Van Vuuren, Mitigation scenarios

  15. Energy crop potential World: cost A1 scenario 2050 (Woody) From biomass cost point-of-view: potential biotrade flows Van Vuuren, Mitigation scenarios (Hoogwijk et al. 2004)

  16. Biofuel potential for transport (2050) Van Vuuren, Mitigation scenarios

  17. Biofuel potential by region (A1 vs A2) Van Vuuren, Mitigation scenarios

  18. 2. Integrated analysis Stabilisation scenarios: Measures taken on the basis of least costs Van Vuuren, Mitigation scenarios

  19. Use of bio-energy in transport sector Western Europe Baseline 2.9 W/m2 / 450 CO2-eq Oil Oil BLF Van Vuuren, Mitigation scenarios

  20. Use of bio-energy in power sector Western Europe Baseline 2.9 W/m2 / 450 CO2-eq Wind Wind Hydro Hydro Coal Bio Coal Bio Gas Gas Gas Bio Van Vuuren, Mitigation scenarios

  21. CO2 CO2 BioEnergy + CCS (BECS 5% Discount rate Wild card: Bio-energy and CCS Van Vuuren, Mitigation scenarios

  22. Sectoral use IMAGE/TIMER: Baseline - Elec power Mit. - Transport BECS - Elec power Azar et al.: Mitigation: CHP BECS : Elec. power Van Vuuren, Mitigation scenarios

  23. Overall picture 1600 1600 450 CO2-eq Baseline 1400 1400 1200 1200 1000 1000 Energy use (EJ) Energy use (EJ) 800 800 600 600 400 400 200 200 0 0 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Nuclear Biofuels + CCS Oil+CCS Biofuels Oil Renewables Natural gas+CCS Coal+CCS Natural gas Coal • Bio-energy plays an important role in mitigation Van Vuuren, Mitigation scenarios

  24. Land use pattern in 450 ppm mitigation scenario (2100) Bio-energy Agriculture Ice Forests C-plantation Ext. grassland Tundra Grass Desert Van Vuuren, Mitigation scenarios

  25. Consequences for land use Nature: 83.2 75.1 73.9 72.3 55.7 47.6 46.4 44.8 Nature in 2000: 92.2 / 63.6 Van Vuuren, Mitigation scenarios

  26. Implications • Thus, bio-energy uses • Either abondoned agr. Land (which becomes forest in baseline) • Natural grassland •  Loss of biodiversity • And… regrowing forest does take up carbon. • Could be in the order of 1-2 GtC/GJ Van Vuuren, Mitigation scenarios

  27. 3. Current work Add more production routes Add indirect GHG effects Van Vuuren, Mitigation scenarios

  28. Chains assessed Rapeseed Palm oil Esterification Biodiesel Soy oil Wheat Sugar beet Fermentation Ethanol Maize Sugar cane Wood Gasification + synthesis Methanol Wood Gasification + synthesis FT diesel Hydrogen Wood Gasification + separation Ethanol Wood Hydrolysis + fermentation Van Vuuren, Mitigation scenarios

  29. Greenhouse gas balanceLogical regions 2020 100% 80% End-use Fossil indirect 60% Fuel distribution 40% GHG emissions (relative to reference) Conversion 20% Feedstock transport 0% Feedstock production Reference Diesel Reference Gasoline 4. Ethanol from wheat 6. Ethanol from maize 11. Ethanol from wood 8. Methanol from wood 9. FT-diesel from wood 10. Hydrogen from wood 2. Biodiesel from palm oil 3. Biodiesel from soybean 5. Ethanol from sugar beet 1. Biodiesel from rapeseed 7. Ethanol from sugar cane Van Vuuren, Mitigation scenarios

  30. Production costsLogical regions 2020 40 Material 30 Energy 3. Biodiesel from soybean 20 O&M Co-product 10 Biofuel production costs (€/GJ) Feedstock 0 -10 wheat maize sugar beet sugar cane wood wood wood palm oil 5. Ethanol from 6. Ethanol from 7. Ethanol from 4. Ethanol from rapeseed -20 wood 11. Ethanol from 1. Biodiesel from 2. Biodiesel from 8. Methanol from 9. FT-diesel from 10. Hydrogen from -30 Van Vuuren, Mitigation scenarios

  31. GHG emission reduction costsLogical regions 2050 1000 Material 800 wheat sugar beet palm oil 4. Ethanol from 5. Ethanol from soybean rapeseed 2. Biodiesel from 3. Biodiesel from 1. Biodiesel from Energy 600 O&M 400 Co-product Biofuel production costs (€/tonne CO2 avoided) 200 Feedstock 0 -200 maize sugar cane wood 6. Ethanol from wood wood -400 7. Ethanol from wood 11. Ethanol from 8. Methanol from 9. FT-diesel from 10. Hydrogen from -600 Van Vuuren, Mitigation scenarios

  32. Bio-energy - key issues • What is the potential for bio-energy; and from which sources (types of land)? • ~ 100-500 EJ • Does bio-energy production lead to competion over land with food? • Not nesserarily • What is the net impacts of bio-energy on GHG emissions and use of fossil fuels? • Net gains compared to fossil, but not 100% • What is the impact of bio-energy on biodiversity? • Depends on reference – but likely losses • How can bio-energy best be applied? In which sectors? • Depends on scenario : mitigation vs. baseline Van Vuuren, Mitigation scenarios

  33. Climate mitigation Van Vuuren, Mitigation scenarios

  34. Climate mitigation Van Vuuren, Mitigation scenarios

  35. Climate mitigation Van Vuuren, Mitigation scenarios

  36. Area under red curve: potential for biomass on abandoned agricultural land in 2050 Energy crop productivity distribution These curves indicate how much area is categorized in a certain productivity class. The surface under the dotted red curve is an indication of the biofuel potential from abandoned agricultural land in 2050 in each scenario Van Vuuren, Mitigation scenarios (Hoogwijk et al. 2004)

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