IFPRI study on Biofuels for the European Commission

Global Trade and Environmental Impact Study of the EU Biofuels Mandate MTID Brown Bag Seminar, April 2nd 2010 by Perrihan Al-Riffai, Betina Dimaranan, David Laborde Debucquet with contributions from Antoine Bouët and Hugo Valin

Overview • Introduction and Background • Modeling Choices • Database • The Baseline • Results • Concluding Remarks INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 2

INTRODUCTION INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 3

What is at stake? INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 4

What is at stake? INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 5

Goals of this study • Effects of the EU mandate • Focus on Indirect Land Use Change • The core story • Increase in yield • Increase in area Increased •Extension of crop production land •Reduction of other crops New Reduced • Hunger? Demand supply for final consumers • Substitution effects for crops Reduced • Feed supply for • Other sectors intermediate (agrifood, cosmetics) consumers • Substitution effects INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 6

Background • Works on Biofuels with MIRAGE • Initiated in 2007 • First study for the EC in 2008-2009 • This study initiated in Fall 2009 • More important than numbers, a pedagogical process • Strong interaction with EC work group on biofuels • Intense discussions • Clarification of several concepts • The CGE raise issues, underline key mechanisms and help to structure discussions INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 7

MODELING INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 8

Main Features • Global CGE MIRAGE – assume perfect competition • Improvement in demand system (food and energy) - done in previous works • Improved sector disaggregation • New modeling of Ethanol sectors • Land market and land extensions at the AEZ level • Co-products (ethanols and vegetal oils) • New modeling of fertilizers • New modeling of livestocks (extensification/intensification) INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 9

Disaggregation (Sectors) Sector Description Sector Description Sector Description Rice Rice SoybnOil Soy Oil EthanolW Ethanol - Wheat Wheat Wheat SunOil Sunflower Oil Biodiesel Biodiesel Maize Maize OthFood Other Food sectors Manuf Other Manufacturing activities PalmFruit Palm Fruit MeatDairy Meat and Dairy WoodPaper Wood and Paper products Rapeseed Rapeseed Sugar Sugar Fuel Fuel Soybeans Soybeans Forestry Forestry PetrNoFuel Petroleum products, except fuel Sunflower Sunflower Fishing Fishing Fertiliz Fertilizers OthOilSds Other oilseeds Coal Coal ElecGas Electricity and Gas VegFruits Vegetable & Oil Oil Construction Construction Fruits OthCrop Other crops Gas Gas PrivServ Private services Sugar_cb Sugar beet or OthMin Other minerals RoadTrans Road Transportation cane Cattle Cattle Ethanol Ethanol - Main AirSeaTran Air & Sea sector transportation OthAnim Other animals EthanolC Ethanol - Sugar PubServ Public services (inc. hogs and Cane poultry) PalmOil Palm Oil EthanolB Ethanol - Sugar Beet RpSdOil Rapeseed Oil EthanolM Ethanol - Maize INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 10

Disaggregation (Regions) Region Description Brazil Brazil CAMCarib Central America and Caribbean countries China China CIS CIS countries (inc. Ukraine) EU27 European Union (27 members) IndoMalay Indonesia and Malaysia LAC Other Latin America countries (inc. Argentina) RoOECD Rest of OECD (inc. Canada & Australia) RoW Rest of the World SSA Sub Saharan Africa USA United States of America But: Land markets at the AEZ level INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 11

Production Tree for an Ag. Sector Changes INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 12

Yield Changes in the Model • Exogenous technology: TFP in agriculture • Endogenous effects: • Factor accumulation: • More capital and labor by unit of land • Fertilizers INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 13

Fertilizers • Price elasticities calibrated from the IMPACT model • Logistic approach for yield effects INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 14

Livestock Sector and Intensification Traditional approach Intensification approach • Feedstock  Intermediate • Like fertilizers consumption • Ratio price of land/price of • Intermediate consumption & feedstocks  Producer choice Value Added (including Land) • Increase in price of feedstock  complementary Substitution effect = • Increase in feedstock prices  Intensification + Overall price Increase in production cost  effect = reduction in production Decrease in demand   Overall, potential increase in Decrease in production  Land use Decrease in Land Use + Limitations in the interactions between pasture land and crop lands (P0/P1/P2) INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 15

Biodiesel Production Oil Crops sector Biofuel (+meals) Sunflower Sunflower seed oil Soybean Soybean oil Biodiesel Rapeseed Rapeseed oil Palm fruit Palm oil & Kernel INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 16

Ethanol Production Biofuels Crops Blending (+ DDG) Ethanol Wheat W Maize Ethanol M Sugar Ethanol B Ethanol Beet Sugar Ethanol C Cane Imported Imported Ethanol* Ethanol* INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 17

Land Markets – at the AEZ Level Wheat Corn Oilseeds CET Sugar Substitutable Vegetables Other Livestock1 LivestockN crops crops and fruits crops CET CET Cropland Pasture CET Agricultural Managed land forest CET Land extension Unmanaged land Managed land Natural forest - Grasslands INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 18

Land Extension Coefficients (from Winrock Intl. – EPA report) ForestManaged ForestPrimary Other Pasture Savannah & Grassland Argentina 16.4% 0.0% 24.7% 35.6% 23.3% Brazil 0.5% 16.3% 11.2% 23.5% 48.5% CAMCarib 0.0% 30.4% 10.7% 16.1% 42.9% Canada 1.4% 7.8% 42.5% 32.2% 16.1% China 5.6% 2.2% 27.3% 39.0% 26.0% CIS 3.7% 5.6% 33.3% 30.7% 26.7% EU27 8.4% 0.4% 23.5% 36.8% 30.9% IndoMalay 3.2% 51.7% 7.0% 7.0% 31.0% LAC 17.8% 10.8% 14.3% 23.4% 33.8% Oceania 9.0% 0.0% 32.6% 36.0% 22.5% RoOECD 14.6% 0.0% 18.8% 20.8% 45.8% RoW 3.4% 3.7% 36.9% 39.3% 16.7% SEasia 1.1% 20.4% 21.5% 23.1% 33.8% SouthAfrica 1.1% 5.1% 28.4% 43.2% 22.2% SouthAsia 12.7% 0.0% 32.4% 31.0% 23.9% SSA 0.1% 13.0% 16.7% 28.6% 41.7% USA 5.4% 2.5% 21.1% 47.4% 23.7% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 19

Computing Marginal ILUC by Crop EU Biofuel demand: x% mandate in 2020 Foreign + 106 GJ extra demand in feedstock 2 consumption Exports Domestic biofuel Foreign biofuel production production Feedstock Feedstock Feedstock Feedstock Feedstock Feedstock 1 2 3 1 2 3 Domestic land Foreign land INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 20

Emissions • Direct savings: Feedstock Set 1 • 1 MJ of fossile fuel: 25gCo2 eq Wheat (EU) -45% • What about biofuels? Wheat (Other) -32% • Life cycle analysis (LCA) Maize (EU) -56% • Consumption vs Production place Maize (USA)* -46% • Kyoto vs RED? Maize (Other)** -29% • Indirect emissions: Sugar Beet -61% • Land use effects: Sugar Cane -71% • Forest (Primary + Managed) Soya -40% • Other biotopes (Grassland… Peatlands effects) Rapeseed -45% • Direct savings (reductions) + Palm Oil -62% ILUC effects/20years Sunflower -58% (emissions) = Net effects Role of certification ? INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 21

DATA INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 22

Major Efforts on Data: from Values to Quantities • Improvement from GTAP7 • Split for fertilizers and fossil fuels • Disaggregation with specific procedure for Maize, Soybeans, Sunflower seed, 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 with FAO and M3) • Correction for Sugar cane AEZ in Brazil INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 23

General Remarks • CGE: • A world of value and prices • But rarely “real” prices • Calibration issue X • Here, physical linkages dX pY are crucial • Substitution effects dY pX • Transformation effects • Limits of CES and CET • Constraints on the choice of elasticities Y INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 24

BASELINE INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 25

Defining a Relevant Baseline • Macroeconomic targets • Growth • Oil prices • EU fuel consumption for Road transportation • Technology and yields • Ludena and al. • EU specific case • Policies • Trade policies • Ag policies • Biofuel policies INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 26

EU AD/CD on US Biodiesel 2.00 1.80 1.60 EU imports, Mtoe 1.40 USA 1.20 RoOECD 1.00 LAC 0.80 IndoMalay 0.60 China Brazil 0.40 0.20 0.00 2008 2020 INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 27

Other Policies in the Baseline • Agricultural policies • Sugar reform in the EU • End of the land set-aside • Biofuel policies • Status quo in the EU (3.3%=10.13 Mtoe in 2020) • Mandate of 5% in OECD countries, China, Indonesia and Malaysia • US mandate (51.64 Mtoe by 2020) • Brazilian policy (14.05 Mtoe by 2020) • World market: 88.79 Mtoe in 2020 (80% ethanol) INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 28

RESULTS INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 29

Defining a Central Scenario • Policy uncertainties • Trade policies • Status quo • Full liberalization of biofuel (not feedstocks) in the EU • Degree of ambition • 5.6% ? • 316 Mtoe in 2020: Total EU consumption for Road Transportation • 31.6 Mtoe of renewable energies: 10% target • 17.8 Mtoe of biofuels first generation by 2020 • Compared to the current situation: 9.23 Mtoe in baseline 2008 (3.3%) • Ethanol/Biodiesel mix: 45%/55% • Parameter uncertainties • Weak estimations on many parameters INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 30

Biofuels Production REF Mandate 5.6% Mandate 5.6%+ Trade liberalization Lev Lev Var Lev Var Biodiesel Brazil 0.36 0.37 1.81% 0.37 2.92% Biodiesel China 0.23 0.23 -0.72% 0.23 -0.76% Biodiesel EU27 8.15 9.04 10.92% 9.07 11.27% Biodiesel IndoMalay 3.58 3.65 2.06% 3.65 2.07% Biodiesel LAC 0.45 0.48 5.91% 0.48 6.10% Biodiesel RoOECD 3.24 3.24 -0.01% 3.24 0.12% Biodiesel USA 3.46 3.45 -0.18% 3.46 -0.03% Biodiesel World 19.46 20.45 5.08% 20.49 5.30% Ethanol Brazil 28.51 32.78 14.97% 34.36 20.50% Ethanol CAMCarib 7.25 7.45 2.64% 7.19 -0.89% Ethanol China 10.81 10.83 0.18% 10.83 0.16% Ethanol EU27 0.84 2.17 156.89% 0.44 -48.23% Ethanol LAC 0.69 0.69 0.95% 0.70 2.21% Ethanol RoOECD 5.66 5.78 2.03% 5.84 3.03% Ethanol RoW 1.51 1.50 -0.54% 1.50 -0.49% Ethanol USA 29.10 29.57 1.64% 29.72 2.14% Ethanol World 84.38 90.77 7.58% 90.57 7.34% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 31

EU Imports (2020) Mandate 5.6%+ Trade REF Mandate 5.6% liberalization Lev Lev Var Lev Var Biodiesel Brazil 0.00 0.00 6.21% 0.00 5.49% Biodiesel China 0.00 0.00 14.45% 0.00 14.59% Biodiesel IndoMalay 0.44 0.51 15.29% 0.51 15.46% Biodiesel LAC 0.19 0.22 15.69% 0.22 16.04% Biodiesel RoOECD 0.00 0.00 12.92% 0.00 82.07% Biodiesel USA 0.00 0.00 11.78% 0.00 12.10% Biodiesel World 0.64 0.74 15.40% 0.74 15.79% Ethanol Brazil 0.92 5.53 502.82% 7.56 724.32% Ethanol CAMCarib 0.04 0.27 517.35% 0.01 -83.48% Ethanol USA 0.00 0.01 546.96% 0.00 111.89% Ethanol World 0.96 5.82 503.58% 7.57 685.98% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 32

EU Production by Feedstock – Biodiesel 2020 Biodiesel 100% 0.38 0.45 0.45 90% Share of EU production (MToe) by feedstock 80% 2.58 2.96 2.98 70% 60% Sunflower 50% Soybeans Rapeseed 40% 4.33 4.58 4.60 PalmFruit 30% 20% 10% 0.86 1.04 1.04 0% REF Mandate 5.6% Mandate 5.6%+ Trade liberalization INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 33

EU Production by Feedstocks - Ethanol 2020 Ethanol 100% 90% Share of EU production (Mtoe) by feestock 80% 0.99 0.43 0.24 70% 60% Wheat 50% Sugar_cb 40% Maize 30% 0.98 0.35 0.16 20% 10% 0.07 0.20 0.04 0% REF Mandate 5.6% Mandate 5.6%+ Trade liberalization INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 34

Agricultural Production (2020) Crops Region REF Mandate 5.6% Mandate 5.6%+ Trade liberalization Lev Lev Var Lev Var Sugar_cb Brazil 913385 1001556.15 9.65% 1045492.08 14.46% Rapeseed CIS 571 583.00 2.06% 583.42 2.13% PalmFruit Brazil 3117 3196.06 2.53% 3181.86 2.07% Rapeseed Brazil 151 153.15 1.59% 152.85 1.39% Rapeseed SSA 108 108.87 1.10% 108.89 1.12% Sunflower Brazil 153 155.23 1.24% 154.91 1.03% Rapeseed RoOECD 13848 13969.92 0.88% 13975.74 0.92% Soybeans RoOECD 3999 4020.98 0.54% 4025.62 0.66% Sunflower USA 2142 2155.86 0.64% 2156.20 0.65% Soybeans CIS 1129 1134.41 0.46% 1135.71 0.58% Soybeans LAC 77981 78349.47 0.47% 78428.70 0.57% Sunflower LAC 5883 5916.54 0.57% 5916.34 0.57% Rapeseed LAC 141 142.09 0.52% 142.10 0.53% OthCrop Brazil 9090 9034.08 -0.61% 9002.90 -0.96% Wheat IndoMalay 1 0.55 -5.92% 0.55 -6.81% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 35

Agricultural Value-Added (2020) 1.20% Mandate 5.6% 1.00% Mandate 5.6%+ Trade liberalization 0.80% 0.60% 0.40% 0.20% 0.00% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 36

Real Income Impacts (2020) Mandate 5.6%+ Trade REF Mandate 5.6% liberalization Lev Lev Var Lev Var Brazil 856 857 0.06% 857 0.08% CAMCarib 444 444 -0.01% 444 -0.02% China 4593 4592 0.00% 4592 -0.01% CIS 1093 1091 -0.18% 1091 -0.17% EU27 15182 15184 0.01% 15182 0.00% IndoMalay 564 564 -0.02% 564 -0.03% LAC 1605 1604 -0.05% 1604 -0.06% RoOECD 8590 8589 -0.01% 8588 -0.01% RoW 5639 5633 -0.11% 5633 -0.11% SSA 912 911 -0.12% 911 -0.12% USA 15219 15218 0.00% 15218 -0.01% World 54697 54687 -0.02% 54684 -0.02% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 37

Livestock Value-Added (2020) – Scenario without trade liberalization 0.10% 0.05% 0.00% Brazil USA EU27 World Cattle Other Animals -0.05% -0.10% -0.15% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 38

Cropland Extension by 2020 Brazil CAMCarib China CIS EU27 IndoMalay LAC RoOECD RoW SSA USA Mandate with trade liberalization EU27: 460 Brazil 6,866 Mandate without trade liberalization EU27: 780 Brazil: 4813 0 2,000 4,000 6,000 8,000 10,000 12,000 Km2 INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 39

Where the Land Extension Occurs? Forest managed Brazil EU27 1% Grassland Forest Pasture 0% 0% primary 15% Forest managed 34% Other 12% Savanah Grassland 58% Forest primary Other Pasture 66% 0% 14% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 40

Extension vs Intensification Mandate 5.6% Mandate 5.6%+ Trade liberalization Yield Yield Land use Total Yield Yield Land use Total Factors Fertilizer Change Production Factors Fertilizer Change Production increase increase increase Increase Rapeseed 0.32% 0.04% 0.54% 0.90% 0.34% 0.02% 0.61% 0.97% PalmFruit 0.10% 0.21% 0.31% 0.10% 0.20% 0.30% Maize 0.04% 0.03% 0.01% 0.08% 0.03% 0.03% -0.01% 0.05% OthCrop 0.01% 0.00% 0.00% 0.01% 0.02% 0.02% -0.01% 0.03% OthOilSds 0.01% 0.01% -0.03% -0.01% 0.01% 0.02% -0.03% 0.00% Rice 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Soybeans 0.04% 0.06% 0.12% 0.22% 0.05% 0.07% 0.15% 0.27% Sugar_cb 0.66% 0.54% 2.67% 3.87% 0.62% 0.37% 3.98% 4.97% Sunflower 0.11% -0.10% 0.37% 0.38% 0.11% -0.10% 0.39% 0.40% VegFruits 0.00% 0.05% -0.06% -0.01% 0.00% 0.05% -0.06% -0.01% Wheat 0.06% 0.05% 0.00% 0.11% 0.00% 0.04% -0.09% -0.05% INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 41

Land Use Emissions – Mios tCO2eq – by 2020 5.6% EU Mandate 5.6% EU Mandate + Full trade liberalization on biofuels Forest Biomass Organic Carbon in Total land use Forest Biomass Organic Carbon in Total land use change Mineral Soil emissions change Mineral Soil emissions Brazil 23.97 33.33 57.30 28.50 46.02 74.52 CAMCarib 0.52 0.52 0.22 0.22 China 1.57 0.65 2.22 1.43 0.60 2.03 CIS 3.18 5.08 8.26 2.91 4.52 7.43 EU27 3.03 7.60 10.63 1.80 4.50 6.30 IndoMalay 3.39 1.53 4.92 3.38 1.53 4.90 LAC 2.63 3.58 6.21 2.71 3.70 6.41 RoOECD 1.08 2.47 3.55 0.87 2.34 3.22 RoW 1.20 0.94 2.14 0.88 0.71 1.59 SSA 1.49 4.50 5.99 1.36 4.04 5.41 USA 1.88 2.89 4.76 2.24 3.47 5.71 World 43.41 63.09 107.50 46.07 71.66 117.74 Additional MtCo2 emissions from peatlands IPCC method 0.17 Values are identical in both scenarios at 0.01 MtCO2eq Couwenberg(2009): 1.38 INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 42

Carbon Balance Sheet (2020) Mandate 5.6%+ Trade REF Mandate 5.6% liberalization Total carbon release from forest biomass (MtCO2eq) 43.41 46.07 Total carbon release from organic carbon in mineral soil (MtCO2eq) 63.09 71.66 EU Consumption of biofuel in 2020 (million GJ) 443 743 746 Annual carbon release from forest biomass (gCO2eq/MJ) 7.23 7.61 Annual carbon release from organic carbon in mineral soil (gCO2eq/MJ) 10.50 11.84 Annual direct savings (gCO2/MJ) -60.55 -66.38 Total emission balance on a 20 years period (gCO2/MJ) -42.82 -46.93 INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 43

Marginal – Crop-Specific ILUC, in 2020 Mandate 5.6% Mandate 5.6%+ Trade liberalization Without With Peatland Without Peatland With Peatland Peatland effects effect effect effect Ethanol 17.74 17.74 19.16 19.18 Ethanol SugarBeet 16.07 16.08 65.48 65.47 Ethanol SugarCane 17.78 17.78 18.86 18.86 Ethanol Maize 54.11 54.12 79.10 79.15 Ethanol Wheat 37.26 37.27 16.04 16.12 Biodiesel 58.67 59.78 54.69 55.76 Palm Oil 46.40 50.13 44.63 48.31 Rapeseed Oil 53.01 53.68 50.60 51.24 Soybean Oil 74.51 75.40 67.01 67.86 Sunflower Oil 59.87 60.53 56.27 56.89 INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 44

Net Emissions – Marginal, by Crop, in 2020 Mandate 5.6% Mandate 5.6%+ Trade liberalization Without Peatland With Peatland Without Peatland With Peatland effects effect effect effect Ethanol -49.69 -49.68 -53.55 -53.53 Ethanol Sugar Beet -35.86 -35.85 21.84 21.83 Ethanol SugarCane -53.95 -53.95 -55.53 -55.53 Ethanol Maize 3.64 3.65 62.82 62.87 Ethanol Wheat -7.00 -6.99 -5.02 -4.95 Biodiesel 5.95 7.06 3.63 4.70 Palm Oil -21.98 -18.25 -22.43 -18.76 Rapeseed Oil 8.76 9.42 7.42 8.06 Soybean Oil 24.07 24.96 18.95 19.80 Sunflower Oil 8.73 9.38 7.74 8.37 INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 45

Non-linearity? (No Trade Liberalization) 4.60% 5.60% 6.60% 7.60% 8.60% 40.00 20.00 0.00 -20.00 -40.00 -60.00 Annual carbon release (gCO2eq/MJ) Annual direct savings (gCO2/MJ) -80.00 Total emission balance on a 20 years period (gCO2/MJ) INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 46

Why Non-linearity? • Biofuel mix • Share of biodiesel vs ethanol in the marginal increase • Modeling framework • CES & CET • Land use • Productivity of new land: small or equal to existing average productivity • To which extent the model reflects reality? • Marginal productivity and utility INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 47

FINAL REMARKS INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 48

Conclusions • Mechanisms more important than numbers • A lot of research is needed to improve the quality of the parameters and modeling can still evolve too • Limited amount of biofuels = positive effects • But all biofuels are not equal • We simulate a mandate with a strong ethanol component • In our simulations, clear superiority of sugarcane ethanol from Brazil • Limited environmental impacts • Energy efficiency • Cost efficiency • No world wide effects on food prices INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 49

Answering Comments • Already a lot echoes in the news and more pedagogy is needed • “UNICA welcomed the Commission's efforts to engage independent experts in its assessments but called for improvements in the current analysis. "The report currently contains a certain number of inaccuracies, so once these are corrected, we anticipate even higher benefits resulting from the use of Brazilian sugarcane ethanol. For example, the type of land for sugarcane expansion highlighted in the report does not take into consideration the agro-ecological zoning for sugarcane in Brazil, which prevents cane from expanding into any type of native vegetation," Desplechin added.” “A 2008 study published by The Netherlands' Wageningen University forecast that about 62% of the expansion of sugarcane in South-Central Brazil, the heart of the country's sugarcane harvesting region, would take place primarily on pasture land, while 37,8% would happen in lands previously occupied by other crops. The projection covered the period from 2008 to 2018. • We do model land extension at the AEZ level and it plays a strong role in the reduction of emissions in our simulations. • The fact that sugar cane will displace “pasture lands and other crops” is not a good argument. This is exactly the problem of ILUC and potentially the difficulty to implement good certification. INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE Page 50

IFPRI study on Biofuels for the European Commission

by David Laborde Debucquet

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IFPRI study on Biofuels for the European Commission Presentation Transcript