Land Use Change and European Biofuel Policies

Land Use Change and European

Biofuel Policies

David Laborde Debucquet -

[email protected]

April 2013

The views expressed by the author are not those of

IFPRI or the European Commission

mailto:[email protected]

INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE

References

• Presentation based on the 2011 report for the European

Commission: “Assessing the land use change consequences of

European 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 EU

Biofuel mandates with the MIRAGE-BioF model” David Laborde

and Hugo Valin.

http://www.worldscientific.com/doi/abs/10.1142/S2010007812500170

• Previous report, 2010, “Global trade and environmental impact

study of the EU biofuels mandate”. Al-Riffai, Perrihan; Dimaranan,

Betina;Laborde, David

http://www.ifpri.org/publication/global-trade-and-environmental-impact-

study-eu-biofuels-mandate

http://www.ifpri.org/publication/assessing-land-use-change-consequences-european-biofuel-policies















http://www.worldscientific.com/doi/abs/10.1142/S2010007812500170

http://www.ifpri.org/publication/global-trade-and-environmental-impact-study-eu-biofuels-mandate


















1. Land use changes driven by biofuel policies are a serious concern.

2. This finding is robust as more than 99 percent of crop LUC coefficients

are positive.

3. LUC regulation and the Pandora's Box: LUC for all, LUC for none? The

real challenge is to promote better land use practices for agriculture

widely.

4. Reducing the biofuel ambition is still the most direct way to limit

additional land use emissions

5. Crop specific LUC can be difficult to implement. Increasing the minimal

requirements of direct savings can be a first step.

6. Despite all uncertainties, our findings show the hierarchy between

ethanol and biodiesel in terms of LUC.

7. Using available technologies to increase yield (e.g. biotech) and crop

conversion technology, and low carbon agricultural practices to reduce

emissions.

Main Policy Recommendations


New Commission proposal to minimise the climate

impacts of biofuel production 17 October 2012

The Commission is therefore proposing to amend the current legislation on biofuels through

the Renewable Energy1 and the Fuel Quality2 Directives and in particular:

• To increase the minimum greenhouse gas saving threshold for new installations to

60% in order to improve the efficiency of biofuel production processes as well as

discouraging further investments in installations with low greenhouse gas performance.

• To include indirect land use change (ILUC) factors in the reporting by fuel suppliers

and 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 counted

towards the EU's 10% target for renewable energy in the transport sector by 2020, to the

current consumption level, 5% up to 2020, while keeping the overall renewable energy and

carbon 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 change

emissions, and in particular the 2nd and 3rd generation biofuels produced from feedstock

that do not create an additional demand for land, including algae, straw, and various types

of waste, as they will contribute more towards the 10% renewable energy in transport

target of the Renewable Energy Directive.

http://europa.eu/rapid/press-release_IP-12-1112_en.htm



INTRODUCTION


Why Biofuel Policies?

From a pragmatic point of view: Because there are not competitive with

fossil fuels at market conditions

From a theoretical point of view: because they have a "social" value not

captured by the market. Externalities lead to market failure and justify

policies.

Why Biofuels? What is the "social" value not captured by the

market? • ENERGY Policy (Energy security, Energy Prices, External Trade

Balance)

• FARM Policy (A new way to support agricultural prices avoiding WTO

disciplines)

• ENVIRONMENTAL Policy to reduce emissions from fossil fuels

If greenhouse gas emissions are the "market failure" aimed to be

corrected, need to do proper CO2 accounting and consider the land use

change.


The Burden of Proof?

• Should we prove that iLUC effects exist or that

does not exist?

• Working in a Farm or Working in Brussels teach

you two things: Level of agricultural production is

tied to the amount of land

• Increased demand of agricultural commodities

HAS land use effects

• The debate should be about their magnitude, not

their existence


Preamble: iLUC or LUC

An artificial differentiation from the point of view of Carbon

Accounting.

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 Use

Change (iLUC)

Therefore the LUC computed in our study is the iLUC

considered by policy makers.


EU BIODIESEL [84% OF EU MARKET]

• EU Imports of vegetable oils have accelerated

with the biodiesel expansion

• EU has started to import rape seeds (2012:

imports > 15% EU production!) and rapeseed oil

since the beginning of the biodiesel policy

• EU rapeseed yields have not increased

2001 - 2003 = 3,06 Ton / Ha

2010 - 2012 = 2,95 Ton / Ha


Orange line = EU Biodiesel production – different scale


MODEL - CORE

MODIFICATIONS

Since previous studies


The MIRAGE-BIOF

• The MIRAGE model has started to be developed in 2001 in CEPII,

Paris. Focusing on EU Integration and Trade Policy analysis of the

beginning

• Now used by several institutions around the World, numerous

versions ( 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 price

stability consequences


Modeling 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


Major 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, 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


Sectoral Disaggregation (43)

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 products WoodPaper Wood and Paper

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 & Fruits Oil Oil Construction Construction

OthCrop Other crops Gas Gas PrivServ Private services

Sugar_cb Sugar beet or cane OthMin Other minerals RoadTrans Road Transportation

Cattle Cattle Ethanol Ethanol - Main sector AirSeaTran Air & Sea transportation

OthAnim Other animals (inc.

hogs and poultry)

EthanolC Ethanol - Sugar Cane PubServ Public services

PalmOil Palm Oil EthanolB Ethanol - Sugar Beet

RpSdOil Rapeseed Oil EthanolM Ethanol - Maize


Biodiesel Production

Feedstock Crops

Veg.Oil sector

(+meals) Biofuel

Biodiesel

Sunflower oil

Sunflower seed

Soybean oil

Soybean

Rapeseed oil

Rapeseed

Palm oil Palm fruit & Kernel


Ethanol Production

Feedstock Crops

Ethanol (+ DDGS)

Biofuel

Blending

Ethanol

Ethanol W

Wheat

Ethanol M Maize

Ethanol B Sugar Beet

Ethanol C Sugar Cane

Imported Ethanol*

Imported Ethanol*

* for Central America and Caribbean


Production Tree for an Ag. Sector

Changes


Livestock Sector and Intensification

Traditional approach

• Feedstock Intermediate

consumption

• Intermediate consumption &

Value Added (including Land)

complementary

• Increase in feedstock prices

Increase in production cost

Decrease in demand

Decrease in production

Decrease in Land Use

Intensification approach

• Like fertilizers

• Ratio price of land/price of

feedstocks Producer choice

• Increase in price of feedstock

Substitution effect =

Intensification + Overall price

effect = reduction in production

Overall, potential increase in

Land use


Land Markets – at the AEZ Level

Managed land

Cropland

Managedforest

Othercrops

Pasture

Wheat Corn

Livestock1 LivestockN

Unmanaged landNatural forest - Grasslands

Land extension

CET

CET

Oilseeds

Substitutablecrops

CET

Vegetablesand fruits

CET

Agricultural land

CET

Sugarcrops


Technical issue: Land Extension

Total land available

for agriculture

Land

Crop

Land

price

Cropland


Land Extension Allocation

from Winrock Intl. – EPA report

Forest

Primary

Other Savannah &

Grassland

Argentina 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 supply

based 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 consider

land availability constraint at

the AEZ level


Technical issues: land substitution (1)

• CET function: concavity

• Aimed to capture imperfect transformation

• Adjustment costs / stylised facts

• Changes in productivity

• Nested CET: consequences of

concavity

• 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 issue

wheat

corn


Modifications 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 availability


SIMULATION DESIGN


Baseline

• 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 central

scenario

• Stronger Brazilian domestic consumption: but still large export

supply response

• Modification of initial profitability in Argentina

• New yield changes: Aglink Cosimo

• VERY IMPORTANT EFFECTS but no SENSITIVITY ANALYSIS on this

assumption

• ISSUE ON EU WHEAT New Members catch up


Scenarios

• Biofuel mandate:

• Member states Action Plan

• Trade policy options:

• Status Quo

• Full Liberalization in the EU of Ethanol and Biodiesel


Sensitivity 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 related

to LUC, but even more regarding net emissions…)

• About the land (amount, location, carbon values)

• About future technologies

• Both behavioral and technical uncertainties


Monte 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 done

of the core version and for the sensitivity analysis

• Log Uniform distribution

• Wide uncertainty

• We focus mainly on elasticities

• We do not have distribution estimates


RESULTS


Scenario Design

(Table 3) EU consumption pattern by feedstock. Percent

Palm Oil Rapeseed Soya Sun-

flower

All

Biodiesel

Maize Sugar

Beet

Sugar

Cane

Wheat All

Ethanol

Structure of consumption in 2008 – Total =11.7 MTOE

Baseline 4 57 20 2 83 3 3 5 5 17

Structure of consumption in 2020 – Total =27.2 MTOE

Baseline 11 60 10 3 83 3 3 7 4 17

No Trade

liberalization

17 41 11 4 72 4 5 13 6 28

Full Trade

Liberalization

17 41 11 4 72 1 1 25 1 28

Additional Mandate Composition +10 Mtoe +5Mtoe

No Trade

liberalization

22 26 12 5 65 4 6 18 7 35

Full Trade

Liberalization

22 26 12 5 65 -1 -1 38 -

1

35


(Table 5) EU biofuel production in 2020 by

feedstock. Energy content. Percent.

Baseline No Trade

Liberalization

Trade Liberalization

Biodiesel 79.29 69.25 92.54

PalmFruit 7.55 12.87 16.96

Rapeseed 62.04 44.37 59.58

Soybeans 6.52 7.45 9.90

Sunflower 3.17 4.56 6.09

Ethanol 20.71 30.75 7.46

Maize 5.83 7.59 2.16

Sugar_cb 6.53 10.96 2.17

Wheat 8.35 12.20 3.12


(Table 6) Commodity balance sheet - World -

Full mandate - No trade liberalization. 1000 tons

Biofuel

demand Additional

Supply Total Demand

displacement Livestock

demand

displacement

Ratio Additional

Supply / Biofuel demand

Share of livestock

demand

displacement in

total demand displacement

Wheat 5,366.6 -1,595.9 -6,962.5 -6,326.6 -30 90.9 Maize 4,353.0 -2,986.3 -7,339.3 -6,471.7 -69 88.2 Sugar Cane & Beet

76,616 69,574 -7,042 -6.6 91 0.1

Soybeans 4,677.6 4,677.6* -1,889.9 -40.4 Sunflower 2,676.0 2,676.0* -344.2 -12.9 Rapeseed 7,135.4 7,135.4* -544.2 -7.6 PalmFruit 22,207.0 22,207.0* -208 -0.9 Rice -101.9 -101.9 418.1 -410.4 OthCrop -765.9 -765.9 -363.4 47.5 OthOilSds -395.4 -395.4 -322.4 81.5 VegFruits -3,372.2 -3,372.2 25.6 -0.8 OilPalm 3,850.6 5,342.0 1,491.4 139 0.0 OilRape 4,456.9 2,474.4 -1,982.5 56 0.0 OilSoyb 2,063.5 1,270.8 -792.8 62 0.0 OilSunf 933.3 1,172.4 239.1 126 0.0

back


(Figure 5) Land use changes for main

crops, 1000 Ha


(Figure 6) Location of cropland extension.

Changes compared to the baseline. Km2


(Figure 7) Distribution of source of

cropland (world)

43.8%

41.8%

36.2%

38.6%

3.7%

3.0%

16.3%

16.5%

Full Trade Liberalization

No Trade Liberalization

Pasture (1) Managed Forest (1) Primary Forest (2) Savannah and Grassland (includes Cerrado in Brazil) (2)


(Figure 8) Cropland extension vs.

Exploited land extension. Km2


LUC coefficient (grCO2/MJ)

495 MtCo2 for

15.5 MToe


(Figure 10) Source of emissions

with a value of peatland emissions of 55gTCO2 HA/an


(Figure 11) Intensification and Extensification drivers. Normalized

effects: Additional Mandate, Trade Policy Status Quo


(Figure 14) Crop specific LUC. Source of

emissions

5 4 26 8

18 19 1775

3

7

13

2223

22

2

12

0

33

16 10 15

Wheat Maize Sugar Beet Sugar Cane Palm fruit Soybean Sunflower Rapesed

Annual carbon release from palm extension on peat lands (gCO2Eq/MJ)

Annual carbon release from forest biomass (gCO2Eq/MJ)

Annual carbon release from carbon mineral soil (gCO2Eq/MJ)


Emissions grCO2/MJ

If

considerin

g oil

leakage

effects


Differences? DEMAND effect

Table 10 Ratio

Additional

Supply/Biofuel

demand. Percent.

Sugar Beet 94.40

Sugar Cane 98.30

Maize 56.69

Wheat 51.38

Palm Fruit 96.6

Rapeseed 78.2

Soybeans 40.3

Sunflower 71.0

mandate

Ethanol Maize

Ethanol Wheat

Biodiesel Rapeseed

Biodiesel Soybean

Maize -2693 -213 -2000 -4431

Wheat -333 -2799 -2228 -1740

Palm Fruit -1 -2 -81 -110

Rapeseed -4 -5 -465 -126

Soybeans 11 12 -810 -2747

Sunflower -6 -6 -126 -131

DDGS 3485 2419 1 -32

Meal-Palm 1 1 23 29

Meal-Rape -37 -78 3841 813

Meal-Soyb -187 -105 2431 8954

Meal-Sunf -1 -5 253 272

Other Crops

174 411 -154 -834

Table 10 Evolution of Livestock consumption of feedstocks. Selected Crop

specific scenarios (60GJ incremental demand of biofuel in the EU). Tons.


Differences? Supply effect

• Yield reactivity

• Land displacement

Table 14 Land Use

displacement Summary.

Value by feedstock. Ha by Tj

Scenario

Feedstock

Net Energy

Crops

Net

Cropland

Pasture Net Exploited

Land

Biodiesel_Rapeseed

EU27 4.42 2.94 0.51 -0.10 0.14

World 10.91 11.72 3.90 -1.39 0.64

Biodiesel_Soybean

EU27 0.14 0.77 0.10 -0.02 0.03

World 11.61 11.41 3.86 -1.50 0.76

Ethanol_Maize

EU27 2.40 1.13 0.08 -0.02 0.01

World 6.52 3.69 0.88 -0.40 0.00

Ethanol_Wheat

EU27 3.27 1.77 0.17 -0.04 0.03

World 7.64 4.99 1.39 -0.54 0.10


Differences: Carbon stocks

Note : The bars (left y-axis) show the amount of additional net cropland by TJ of biofuel

produced for one feedstock. The line (right x-axis) shows the average tons of CO2

equivalent by net Ha of cropland.

(Figure 16) More cropland or More Carbon (Ha by TJ and Tons

CO2 eq by Ha of cropland)


Sensitivity Analysis


(Figure 21) Correlation matrix of LUC factor,

grCO2eg/MJ. Trade policy Status quo.


(Figure 22) Consequences of alternative

closures on LUC (grCO2e/MJ)

Worst case (all demand fixed, no

coproducts) can x3 total LUC


POLICY RECOMMENDATIONS

From model results to the policy space


1. Land use changes driven by biofuel policies are a serious concern.

2. This finding is robust as more than 99 percent of crop LUC coefficients

are positive.

3. LUC regulation and the Pandora's Box: LUC for all, LUC for none? The

real challenge is to promote better land use practices for agriculture

widely.

4. Reducing the biofuel ambition is still the most direct way to limit

additional land use emissions

5. Crop specific LUC can be difficult to implement. Increasing the minimal

requirements of direct savings can be a first step.

6. Despite all uncertainties, our findings show the hierarchy between

ethanol and biodiesel in terms of LUC.

7. Using available technologies to increase yield (e.g. biotech) and crop

conversion technology, and low carbon agricultural practices to reduce

emissions.

Main Policy Recommendations


New Commission proposal to minimise the climate

impacts of biofuel production 17 Octobre 2012

The Commission is therefore proposing to amend the current legislation on biofuels through

the Renewable Energy1 and the Fuel Quality2 Directives and in particular:

• To increase the minimum greenhouse gas saving threshold for new installations to

60% in order to improve the efficiency of biofuel production processes as well as

discouraging further investments in installations with low greenhouse gas performance.

• To include indirect land use change (ILUC) factors in the reporting by fuel suppliers

and 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 counted

towards the EU's 10% target for renewable energy in the transport sector by 2020, to the

current consumption level, 5% up to 2020, while keeping the overall renewable energy and

carbon 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 change

emissions, and in particular the 2nd and 3rd generation biofuels produced from feedstock

that do not create an additional demand for land, including algae, straw, and various types

of waste, as they will contribute more towards the 10% renewable energy in transport

target of the Renewable Energy Directive.



Land Use Change and European Biofuel Policies

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