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Land Use Change and European Biofuel Policies

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This presentation gives a detailed overview of the 2011 report done by IFPRI (Laborde, 2011) for the European Commission on the land use consequences of EU biofuel mandates (available at …

This presentation gives a detailed overview of the 2011 report done by IFPRI (Laborde, 2011) for the European Commission on the land use consequences of EU biofuel mandates (available at http://www.ifpri.org/sites/default/files/publications/biofuelsreportec2011.pdf )
The report aims to compute iLUC (indirect land use change) factor for different feedstocks using the MIRAGE-Biof CGE model.

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  • 1. Land Use Change and EuropeanBiofuel PoliciesDavid Laborde Debucquet -d.laborde@cgiar.orgApril 2013The views expressed by the author are not those ofIFPRI or the European Commission
  • 2. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEReferences• Presentation based on the 2011 report for the EuropeanCommission: “Assessing the land use change consequences ofEuropean biofuel policies”. David Laborde.http://www.ifpri.org/publication/assessing-land-use-change-consequences-european-biofuel-policies• “Modeling land-use changes in a global CGE: Assessing the EUBiofuel mandates with the MIRAGE-BioF model” David Labordeand Hugo Valin.http://www.worldscientific.com/doi/abs/10.1142/S2010007812500170• Previous report, 2010, “Global trade and environmental impactstudy of the EU biofuels mandate”. Al-Riffai, Perrihan; Dimaranan,Betina;Laborde, Davidhttp://www.ifpri.org/publication/global-trade-and-environmental-impact-study-eu-biofuels-mandatePage 2
  • 3. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE1. Land use changes driven by biofuel policies are a serious concern.2. This finding is robust as more than 99 percent of crop LUC coefficientsare positive.3. LUC regulation and the Pandoras Box: LUC for all, LUC for none? Thereal challenge is to promote better land use practices for agriculturewidely.4. Reducing the biofuel ambition is still the most direct way to limitadditional land use emissions5. Crop specific LUC can be difficult to implement. Increasing the minimalrequirements of direct savings can be a first step.6. Despite all uncertainties, our findings show the hierarchy betweenethanol and biodiesel in terms of LUC.7. Using available technologies to increase yield (e.g. biotech) and cropconversion technology, and low carbon agricultural practices to reduceemissions.Page 3Main Policy Recommendations
  • 4. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTENew Commission proposal to minimise the climateimpacts of biofuel production 17 October 2012The Commission is therefore proposing to amend the current legislation on biofuels throughthe Renewable Energy1 and the Fuel Quality2 Directives and in particular:• To increase the minimum greenhouse gas saving threshold for new installations to60% in order to improve the efficiency of biofuel production processes as well asdiscouraging further investments in installations with low greenhouse gas performance.• To include indirect land use change (ILUC) factors in the reporting by fuel suppliersand Member States of greenhouse gas savings of biofuels and bioliquids;[ Figures from the MIRAGE Biof model}• To limit the amount of food crop-based biofuels and bioliquids that can be countedtowards the EUs 10% target for renewable energy in the transport sector by 2020, to thecurrent consumption level, 5% up to 2020, while keeping the overall renewable energy andcarbon intensity reduction targets;• [ 2010 IFPRI report: 5.6% target for 1st generation]• To provide market incentives for biofuels with no or low indirect land use changeemissions, and in particular the 2nd and 3rd generation biofuels produced from feedstockthat do not create an additional demand for land, including algae, straw, and various typesof waste, as they will contribute more towards the 10% renewable energy in transporttarget of the Renewable Energy Directive.Page 4
  • 5. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEINTRODUCTIONPage 5
  • 6. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEWhy Biofuel Policies?Page 6From a pragmatic point of view: Because there are not competitive withfossil fuels at market conditionsFrom a theoretical point of view: because they have a "social" value notcaptured by the market. Externalities lead to market failure and justifypolicies.Why Biofuels? What is the "social" value not captured by themarket?• ENERGY Policy (Energy security, Energy Prices, External TradeBalance)• FARM Policy (A new way to support agricultural prices avoiding WTOdisciplines)• ENVIRONMENTAL Policy to reduce emissions from fossil fuelsIf greenhouse gas emissions are the "market failure" aimed to becorrected, need to do proper CO2 accounting and consider the land usechange.
  • 7. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 7
  • 8. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEThe Burden of Proof?• Should we prove that iLUC effects exist or thatdoes not exist?• Working in a Farm or Working in Brussels teachyou two things: Level of agricultural production istied to the amount of land• Increased demand of agricultural commoditiesHAS land use effects• The debate should be about their magnitude, nottheir existencePage 8
  • 9. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEPreamble: iLUC or LUCAn artificial differentiation from the point of view of CarbonAccounting.Total Land Use Change (LUC) = Direct Land Use Change(dLUC) + Indirect Land Use Change (iLUC)ASSUMPTION in our study : Regulations work.No Direct LUC. dLUC=0.Total Land Use Change (LUC) = 0+ Indirect Land UseChange (iLUC)Therefore the LUC computed in our study is the iLUCconsidered by policy makers.Page 9
  • 10. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEEU BIODIESEL [84% OF EU MARKET]• EU Imports of vegetable oils have acceleratedwith the biodiesel expansion• EU has started to import rape seeds (2012:imports > 15% EU production!) and rapeseed oilsince the beginning of the biodiesel policy• EU rapeseed yields have not increased2001 - 2003 = 3,06 Ton / Ha2010 - 2012 = 2,95 Ton / HaPage 10
  • 11. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 11Orange line = EU Biodiesel production – different scale
  • 12. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 12Orange line = EU Biodiesel production – different scale
  • 13. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEMODEL - COREMODIFICATIONSSince previous studiesPage 13
  • 14. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEThe MIRAGE-BIOF• The MIRAGE model has started to be developed in 2001 in CEPII,Paris. Focusing on EU Integration and Trade Policy analysis of thebeginning• Now used by several institutions around the World, numerousversions ( trade policy focused, FDI, Services, Climate Change etc.)• Biofuels assessment started in 2008• On land use:• First study for the DG Trade in 2009 (limited to ethanol)• Second study for DG Trade in 2010 (part of the public consultation)• This new study for: DG Trade in 2011• But other applications: mandates of other countries, comparison of“traditional” ag policies and biofuels etc., food prices and pricestability consequencesPage 14
  • 15. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEModeling Biofuels in MIRAGE• MIRAGE model• Multi country, Multi sectoral, and global• Recursive dynamic set-up• Modified model and data components• Improvement in demand system (food and energy)• Improved sector disaggregation• New modeling of ethanol sectors• Co-products of ethanols and vegetable oils• New modeling of fertilizers• New modeling of livestocks (extensification/intensification)• Land market and land extensions at the AEZ level
  • 16. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEMajor Efforts on Data: from Values to Quantities• Improvement from the GTAP7 database• Split for fertilizers and fossil fuels• Disaggregation with specific procedure for Maize, Soybeans, Sunflowerseed, Palm fruit, Rapeseed + relevant Oils + Co-products• Production targeting (FAO) for all relevant crops• Creation of a “harmonized” price database for calibration• Case of co-products• Creation of Ethanol and Biodiesel (2008 trade and production structure).• Correction of some I-O data (e.g. China)• Land use (AEZ GTAP database 2001  2004, + consistency withFAO and M3)• Correction for Sugar cane AEZ in BrazilPage 16
  • 17. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 17
  • 18. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTESectoral Disaggregation (43)Sector Description Sector Description Sector DescriptionRice Rice SoybnOil Soy Oil EthanolW Ethanol - WheatWheat Wheat SunOil Sunflower Oil Biodiesel BiodieselMaize Maize OthFood Other Food sectors Manuf Other ManufacturingactivitiesPalmFruit Palm Fruit MeatDairy Meat and Dairy products WoodPaper Wood and PaperRapeseed Rapeseed Sugar Sugar Fuel FuelSoybeans Soybeans Forestry Forestry PetrNoFuel Petroleum products,except fuelSunflower Sunflower Fishing Fishing Fertiliz FertilizersOthOilSds Other oilseeds Coal Coal ElecGas Electricity and GasVegFruits Vegetable & Fruits Oil Oil Construction ConstructionOthCrop Other crops Gas Gas PrivServ Private servicesSugar_cb Sugar beet or cane OthMin Other minerals RoadTrans Road TransportationCattle Cattle Ethanol Ethanol - Main sector AirSeaTran Air & Sea transportationOthAnim Other animals (inc.hogs and poultry)EthanolC Ethanol - Sugar Cane PubServ Public servicesPalmOil Palm Oil EthanolB Ethanol - Sugar BeetRpSdOil Rapeseed Oil EthanolM Ethanol - MaizePage 18
  • 19. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEBiodiesel ProductionPage 19FeedstockCropsVeg.Oilsector(+meals)BiofuelBiodieselSunfloweroilSunflowerseedSoybeanoilSoybeanRapeseedoilRapeseedPalm oilPalm fruit& Kernel
  • 20. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEEthanol ProductionPage 20FeedstockCropsEthanol(+ DDGS)BiofuelBlendingEthanolEthanolWWheatEthanol MMaizeEthanol BSugarBeetEthanol CSugarCaneImportedEthanol*ImportedEthanol** for Central America and Caribbean
  • 21. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEProduction Tree for an Ag. SectorPage 21Changes
  • 22. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTELivestock Sector and IntensificationTraditional approach• Feedstock  Intermediateconsumption• Intermediate consumption &Value Added (including Land)complementary• Increase in feedstock prices Increase in production cost Decrease in demand Decrease in production Decrease in Land UseIntensification approach• Like fertilizers• Ratio price of land/price offeedstocks  Producer choice• Increase in price of feedstock Substitution effect =Intensification + Overall priceeffect = reduction in production Overall, potential increase inLand usePage 22
  • 23. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTELand Markets – at the AEZ LevelPage 23Managed landCroplandManagedforestOthercropsPastureWheat CornLivestock1 LivestockNUnmanaged landNatural forest - GrasslandsLand extensionCETCETOilseedsSubstitutablecropsCETVegetablesand fruitsCETAgriculturallandCETSugarcrops
  • 24. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTETechnical issue: Land ExtensionPage 24Total land availablefor agricultureLandCropLandpriceCropland
  • 25. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTELand Extension Allocationfrom Winrock Intl. – EPA reportForestPrimaryOther Savannah &GrasslandArgentina 0.0% 24.7% 23.3%Brazil 16.3% 11.2% 48.5%CAMCarib 30.4% 10.7% 42.9%Canada 7.8% 42.5% 16.1%China 2.2% 27.3% 26.0%CIS 5.6% 33.3% 26.7%EU27 0.4% 23.5% 30.9%IndoMalay 51.7% 7.0% 31.0%LAC 10.8% 14.3% 33.8%Oceania 0.0% 32.6% 22.5%RoOECD 0.0% 18.8% 45.8%RoW 3.7% 36.9% 16.7%SEasia 20.4% 21.5% 33.8%SouthAfrica 5.1% 28.4% 22.2%SouthAsia 0.0% 32.4% 23.9%SSA 13.0% 16.7% 41.7%USA 2.5% 21.1% 23.7%Methodology• Amount of land extension:“isoelastic” land supplybased on cropland price• Evolution of the elasticity• Where the land is taken:• Ad Hoc coefficients: Winrock• Limitations• Done at the AEZ level• RAS procedure to considerland availability constraint atthe AEZ levelPage 25
  • 26. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTETechnical issues: land substitution (1)• CET function: concavity• Aimed to capture imperfect transformation• Adjustment costs / stylised facts• Changes in productivity• Nested CET: consequences ofconcavity• Sum (i, Land_i) ≠ CET (Land_I)• In the model / out of the model rescaling• In MIRAGE: in the model• CET:• Good in static• More problematic in dynamics:• Adjustment costs based on calibration year.• Recalibration issuePage 26wheatcorn
  • 27. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEModifications in Modelling for this new report• Dynamic baseline and food demand• Dynamic recalibration to maintain price elasticity in the CES LES.Standard of living evolution• Co-products substitution: one level• Two type of effects:• Displacement of other crops• Intensification• Modification of central values for elasticities• Marginal shock simulations• From a marginal 1 to 60 Mios GJ• But still, concept to manipulation with precaution:• Substitution effects vs expansion effects• Peat emissions and Indonesia land availabilityPage 27
  • 28. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTESIMULATION DESIGNPage 28
  • 29. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEBaseline• Sugar reform (still a source of numerical problems)• End of the Land Set Aside• EU trade measures vs US Biodiesel• No change in trade policy for Ethanol• Some restrictions on Brazilian exports to the US in the baseline:• Partially capture the change in the real exchange rate real/USD• Avoid too much confusion between corn and sugar cane ethanol for the centralscenario• Stronger Brazilian domestic consumption: but still large exportsupply response• Modification of initial profitability in Argentina• New yield changes: Aglink Cosimo• VERY IMPORTANT EFFECTS but no SENSITIVITY ANALYSIS on thisassumption• ISSUE ON EU WHEAT  New Members catch upPage 29
  • 30. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEScenarios• Biofuel mandate:• Member states Action Plan• Trade policy options:• Status Quo• Full Liberalization in the EU of Ethanol and BiodieselPage 30
  • 31. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTESensitivity Analysis• On linearity/non linearity issue• Estimation of crop LUC at a “half mandate”, at a full mandate• But still weak on Ethanol: no saturation effects• On food consumption• Endogenous vs Fixed to Baseline level• On Co-products: with or without• Monte Carlo simulations on selected parameters• But in reality, much more uncertainties (see Box 2, 25 items relatedto LUC, but even more regarding net emissions…)• About the land (amount, location, carbon values)• About future technologies• Both behavioral and technical uncertaintiesPage 31
  • 32. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEMonte Carlo Simulations• 1000 runs = 240 days of computations time• Some restrictions for the model version• Iterative process during the earlier stage• Any modification of the model or data has to be doneof the core version and for the sensitivity analysis• Log Uniform distribution• Wide uncertainty• We focus mainly on elasticities• We do not have distribution estimatesPage 32
  • 33. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTERESULTSPage 33
  • 34. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEScenario Design(Table 3) EU consumption pattern by feedstock. PercentPalm Oil Rapeseed Soya Sun-flowerAllBiodieselMaize SugarBeetSugarCaneWheat AllEthanolStructure of consumption in 2008 – Total =11.7 MTOEBaseline 4 57 20 2 83 3 3 5 5 17Structure of consumption in 2020 – Total =27.2 MTOEBaseline 11 60 10 3 83 3 3 7 4 17No Tradeliberalization17 41 11 4 72 4 5 13 6 28Full TradeLiberalization17 41 11 4 72 1 1 25 1 28Additional Mandate Composition +10 Mtoe +5MtoeNo Tradeliberalization22 26 12 5 65 4 6 18 7 35Full TradeLiberalization22 26 12 5 65 -1 -1 38 -135Page 34
  • 35. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Table 5) EU biofuel production in 2020 byfeedstock. Energy content. Percent.Baseline No TradeLiberalizationTrade LiberalizationBiodiesel 79.29 69.25 92.54PalmFruit 7.55 12.87 16.96Rapeseed 62.04 44.37 59.58Soybeans 6.52 7.45 9.90Sunflower 3.17 4.56 6.09Ethanol 20.71 30.75 7.46Maize 5.83 7.59 2.16Sugar_cb 6.53 10.96 2.17Wheat 8.35 12.20 3.12Page 35
  • 36. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Table 6) Commodity balance sheet - World -Full mandate - No trade liberalization. 1000 tonsBiofueldemandAdditionalSupplyTotal DemanddisplacementLivestockdemanddisplacementRatio AdditionalSupply / BiofueldemandShare of livestockdemanddisplacement intotal demanddisplacementWheat 5,366.6 -1,595.9 -6,962.5 -6,326.6 -30 90.9Maize 4,353.0 -2,986.3 -7,339.3 -6,471.7 -69 88.2Sugar Cane& Beet76,616 69,574 -7,042 -6.6 91 0.1Soybeans 4,677.6 4,677.6* -1,889.9 -40.4Sunflower 2,676.0 2,676.0* -344.2 -12.9Rapeseed 7,135.4 7,135.4* -544.2 -7.6PalmFruit 22,207.0 22,207.0* -208 -0.9Rice -101.9 -101.9 418.1 -410.4OthCrop -765.9 -765.9 -363.4 47.5OthOilSds -395.4 -395.4 -322.4 81.5VegFruits -3,372.2 -3,372.2 25.6 -0.8OilPalm 3,850.6 5,342.0 1,491.4 139 0.0OilRape 4,456.9 2,474.4 -1,982.5 56 0.0OilSoyb 2,063.5 1,270.8 -792.8 62 0.0OilSunf 933.3 1,172.4 239.1 126 0.0Page 36back
  • 37. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 37
  • 38. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 5) Land use changes for maincrops, 1000 HaPage 38
  • 39. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 6) Location of cropland extension.Changes compared to the baseline. Km2Page 39
  • 40. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 7) Distribution of source ofcropland (world)Page 4043.8%41.8%36.2%38.6%3.7%3.0%16.3%16.5%FullTradeLiberalizationNo TradeLiberalizationPasture(1) Managed Forest(1) Primary Forest(2) Savannah and Grassland (includes Cerrado in Brazil) (2)
  • 41. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 8) Cropland extension vs.Exploited land extension. Km2Page 41
  • 42. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTELUC coefficient (grCO2/MJ)Page 42495 MtCo2 for15.5 MToe
  • 43. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 10) Source of emissionsPage 43with a value of peatland emissions of 55gTCO2 HA/an
  • 44. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 11) Intensification and Extensification drivers. Normalizedeffects: Additional Mandate, Trade Policy Status QuoPage 44
  • 45. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 14) Crop specific LUC. Source ofemissionsPage 455 4 26 818 19 1775371322232221203316 10 15Wheat Maize Sugar Beet Sugar Cane Palmfruit Soybean Sunflower RapesedAnnual carbon release from palmextension on peat lands (gCO2Eq/MJ)Annual carbon release from forestbiomass (gCO2Eq/MJ)Annual carbon release from carbonmineral soil (gCO2Eq/MJ)
  • 46. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEEmissions grCO2/MJPage 46Ifconsidering oilleakageeffects
  • 47. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEDifferences? DEMAND effectPage 47Table 10 RatioAdditionalSupply/Biofueldemand. Percent.Sugar Beet 94.40Sugar Cane 98.30Maize 56.69Wheat 51.38Palm Fruit 96.6Rapeseed 78.2Soybeans 40.3Sunflower 71.0mandateEthanolMaizeEthanolWheatBiodieselRapeseedBiodieselSoybeanMaize -2693 -213 -2000 -4431Wheat -333 -2799 -2228 -1740Palm Fruit -1 -2 -81 -110Rapeseed -4 -5 -465 -126Soybeans 11 12 -810 -2747Sunflower -6 -6 -126 -131DDGS 3485 2419 1 -32Meal-Palm 1 1 23 29Meal-Rape -37 -78 3841 813Meal-Soyb -187 -105 2431 8954Meal-Sunf -1 -5 253 272OtherCrops174 411 -154 -834Table 10 Evolution of Livestock consumption of feedstocks. Selected Cropspecific scenarios (60GJ incremental demand of biofuel in the EU). Tons.
  • 48. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEDifferences? Supply effect• Yield reactivity• Land displacementPage 48Table 14 Land Usedisplacement Summary.Value by feedstock. Ha by TjScenarioFeedstockNet EnergyCropsNetCroplandPasture Net ExploitedLandBiodiesel_RapeseedEU27 4.42 2.94 0.51 -0.10 0.14World 10.91 11.72 3.90 -1.39 0.64Biodiesel_SoybeanEU27 0.14 0.77 0.10 -0.02 0.03World 11.61 11.41 3.86 -1.50 0.76Ethanol_MaizeEU27 2.40 1.13 0.08 -0.02 0.01World 6.52 3.69 0.88 -0.40 0.00Ethanol_WheatEU27 3.27 1.77 0.17 -0.04 0.03World 7.64 4.99 1.39 -0.54 0.10
  • 49. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEDifferences: Carbon stocksPage 49Note : The bars (left y-axis) show the amount of additional net cropland by TJ of biofuelproduced for one feedstock. The line (right x-axis) shows the average tons of CO2equivalent by net Ha of cropland.(Figure 16) More cropland or More Carbon (Ha by TJ and TonsCO2 eq by Ha of cropland)
  • 50. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTESensitivity AnalysisPage 50
  • 51. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 21) Correlation matrix of LUC factor,grCO2eg/MJ. Trade policy Status quo.Page 51
  • 52. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE(Figure 22) Consequences of alternativeclosures on LUC (grCO2e/MJ)Page 52Worst case (all demand fixed, nocoproducts) can x3 total LUC
  • 53. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTEPOLICY RECOMMENDATIONSFrom model results to the policy spacePage 53
  • 54. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE1. Land use changes driven by biofuel policies are a serious concern.2. This finding is robust as more than 99 percent of crop LUC coefficientsare positive.3. LUC regulation and the Pandoras Box: LUC for all, LUC for none? Thereal challenge is to promote better land use practices for agriculturewidely.4. Reducing the biofuel ambition is still the most direct way to limitadditional land use emissions5. Crop specific LUC can be difficult to implement. Increasing the minimalrequirements of direct savings can be a first step.6. Despite all uncertainties, our findings show the hierarchy betweenethanol and biodiesel in terms of LUC.7. Using available technologies to increase yield (e.g. biotech) and cropconversion technology, and low carbon agricultural practices to reduceemissions.Page 54Main Policy Recommendations
  • 55. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTENew Commission proposal to minimise the climateimpacts of biofuel production 17 Octobre 2012The Commission is therefore proposing to amend the current legislation on biofuels throughthe Renewable Energy1 and the Fuel Quality2 Directives and in particular:• To increase the minimum greenhouse gas saving threshold for new installations to60% in order to improve the efficiency of biofuel production processes as well asdiscouraging further investments in installations with low greenhouse gas performance.• To include indirect land use change (ILUC) factors in the reporting by fuel suppliersand Member States of greenhouse gas savings of biofuels and bioliquids;[ Figures from the MIRAGE Biof model}• To limit the amount of food crop-based biofuels and bioliquids that can be countedtowards the EUs 10% target for renewable energy in the transport sector by 2020, to thecurrent consumption level, 5% up to 2020, while keeping the overall renewable energy andcarbon intensity reduction targets;• [ 2010 IFPRI report: 5.6% target for 1st generation]• To provide market incentives for biofuels with no or low indirect land use changeemissions, and in particular the 2nd and 3rd generation biofuels produced from feedstockthat do not create an additional demand for land, including algae, straw, and various typesof waste, as they will contribute more towards the 10% renewable energy in transporttarget of the Renewable Energy Directive.Page 55