1
The impacts of lignocellulosic
biomass-based biofuel production
on land use changes in Europe
By Anabelle Couleau (PhD Student)
& Dr. David Laborde (IFPRI)
International Consortium on Applied Bioeconomy Research (ICABR),
2013, Ravello
Introduction
Introduction
• 4.7% share of 1st gen biofuels is estimated to have generated 25.5
Million Tons CO2eq savings, based on NREAPs
• BUT account for ILUC may reduce or cancel GHG savings attributed
to biofuels
• Growing interest for 2nd generation biofuels and design of EU
biofuel policy led us to consider ILUC for cellulosic feedstocks
& biofuels
• Although some are arguing that second generation would not be in
competition with food markets, and so ILUC free
• Lignocellulosic biomass (2 types : Ag. Residues and Dedicated
Energy Crops) is competing on production factors and so on
land with food crops and pasture.
2
Introduction
3
EU biofuel legislation
• iLUC are not subject to
under current legislation !
reporting requirements
• Limiting 1st generation ?
• October, 2012 => European Commission :
Proposed to limit 1st gen biofuels in transport mix
at 5% by 2020 (currently 10%)
• April, 2013 => Parliament (Lepage's proposal) :
No limitation 1st gen but iLUC reporting and
binding + incentives 2nd generation
=> In both they are considering 2nd generation biofuels.
Introduction
4
European 2G biofuels consumption
forecasts ?
Biofuel estimation consumption in transportation in European countries by 2020.
(Source: NREAPs, 2011)
450
400
400
350
292
300
261
252
242
Ktoe
250
200
180
166
150
156
155
127
111
94
100
38
50
40
22
0
0
60
50
0
0
1
0 0
13
8
0
0
Austria
Belgium
Bulgaria
Cyprus
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Lithuania
Luxembourg
Malta
Netherlands
Poland
Portugal
Romania
Slovakia
Slovenia
Spain
Sweden
UK
Introduction
5
EU cellulosic ethanol plants
Plants demonstration start date
feedstock
Final product
location
Plant Owner
technology provider enzyme provider
Dec-09
Wheat straw
Lignocellulosic
Ethanol
Kalundborg,
Denmark
DONG Energy
A/S
Inbicon A/S
- Vogelbusch
Abengoa
Salamanca EC
demonstration
Sep-09
Straw (barley, wheat, Lignocellulosic
…)
Ethanol
Babilafuente,
Salamanca Spain
Abengoa
Bioenergy, S.A.
Abengoa Bioenergy
Abengoa
New Technologies,
Bioenergy, S.A.
S.A.
+ Genencor
+ Novozymes
Chemtex EC
demonstration
Jul-11
Giant Reed (perennial Lignocellulosic
Grass)
Ethanol
Technology will be
Piedmont Region,
Chemtex Italia srl developed in the
Novozymes
Italy
BIOLYFE project.
Forest residues,
Agricultural residues
Arance (64)
(France)
INBICON EC
demonstration
Abengoa Arance EC
Jun-13
demonstration
Lignocellulosic
Ethanol
Abengoa
Bioenergy, S.A.
Abengoa Bioenergy,
Abengoa
S.A.
Bioenergy, S.A.
+ Novozymes
Source : Author’s compilations from http://biomap.kcl.ac.uk, accessed in June 2013
Introduction
6
Technologies
Cellulosic
biomass
Processing routes
Thermochemical=>
gazeification (700
C, Syngas)
Crops residues
-corn stover
-wheat straw
Dedicated
energy crops
-Miscanthus
-Switchgrass
Biochemical
=> Enzymatic
digestion
Second-Generation
Biofuels
Cellulosic Fischer
Tropsch Diesel
(FTD)
Cellulosic
Ethanol
Introduction
Research Question
• Are 2nd generation really ILUC “free”?
• In the negative, what are the main drivers
related to ILUC for 2nd generation
biofuel?
From different ligno-cellulosic
materials ?
In comparison with 1st generation ?
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Literature Review
Some Results from the Literature
• Taheripour et al., (GTAP-BIO-ADV, general
equilibrium)
• Gurgel et al., (EPPA, general equilibrium)
8
Literature
Crops residues : ISSUES
• Removal rate and reduction yields
• Corn stover is considered the main feedstock for cellulosic
ethanol production, but crop residues from small grains can
also be used as bioenergy feedstock (Tarkalson et al., 2011).
• In Europe, wheat straw is expected to be a potential important
feedstock for bioenergy production (Powlson et al., 2011).
• Crops residues are a direct soil organic carbon (SOC) pool.
Large-scale removal of crop residues at high rates can deplete
SOC pools (Blanco-canqui & Lal, 2009). So, we assume the
yield will be a decreasing function of the removal rate.
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Methodology
MIRAGE-BioF: Main characteristics model
•
•
•
•
•
A computable general equilibrium model (CGE)
Multi-regions (11), multi sectors (43),
A recursive, dynamic model : up to 2020
Database used: GTAP (2004)
Used in perfect competition
• In this study : extended version of MIRAGE Biof by Laborde (2011)
• Reminder :
▫ Baseline : from 2008 up to 2020
▫ Scenario : National Renewable Energy Action Plans (each members states has to
released its own renewable biofuel consomptions estimations with this NREAPs
document, each year).
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Methodology
Main general assumptions
• At this stage, there is no trade of 2nd generation
biofuels and specific feedstocks => design of 100%
EU production
• We are first focusing on cellulosic ethanol
• Constant 1st generation ethanol consumption in the
EU is assumed but the source of ethanol can still
vary
• No competition between type of lignocellulosic
feedstocks
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Methodology
Modeling Choice
What are initial use of crops residues ?
• Option 1 : Crop residues (Wheat Straw or Corn
Stover) stay on field as a SOIL FERTILIZER
• Option 2 : Off-field use of Crops residues : livestock
(feed, litter, …) => too many uncertainties are
surrounding this option
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Methodology
Modeling Choice
What are initial use of crops residues ?
• Option 1 : Crop residues (Wheat Straw or Corn
Stover) stay on field as a SOIL FERTILIZER
• Option 2 : Off-field use of Crops residues : livestock
(feed, litter, …) => too many uncertainties are
surrounding this option
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Methodology
Modeling Choice
What are initial use of crops residues ?
• Option 1 : Crop residues (Wheat Straw or Corn Stover) stay on field
as a SOIL FERTILIZER
▫ Soil fertilizer is not directly compensated by fertilizers. The dominant
effect is a decrease in yield
▫ SOIL FERTILIZER =
 Carbon and Nitrogen
 Soil Humidity  Can not be compensated by Mineral Fertilizers
• Option 2 : Off-field use of Crops residues : livestock (feed, litter, …)
=> too many uncertainties are surrounding this option
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Methodology
Modeling Choice
What are initial use of crops residues ?
• Option 1 : Crop residues (Wheat Straw or Corn Stover)
stay on field as a SOIL FERTILIZER
▫ Soil fertilizer is not directly compensated by fertilizers. The
dominant effect is a decrease in yield
▫ Soil fertilizer is directly compensated by an add-on
fertilizers. Assumption : no direct effect on the price of
wheat
• Options 2 : Off-field use of Crops residues : livestock
(feed, litter, …) => too many uncertainties are
surrounding this option
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Methodology
How to integrate crops residues in the
model ?
▫ We assume a removal rate of 30% for the EU grain
harvested area supplying 2nd generation plants
▫ We account for the technical constraint of carrying
biomass
▫ The yield is a decreasing function of the removal
rate
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Methodology
How to integrate crops residues in the
model ?
Two options allow to have yield endogenous to the scale of
second generation production at the EU level:
1. Assume a homogenous removal rate of X% on each hectare
of wheat (e.g) and yield will be a decreasing function of the
removal rate (X);
2. Assume two management techniques for wheat/corn and
endogenous choice of management method for each ha:
▫
▫
normal management (crop residues stay on the field),
removal of crop residues with a fixed rate of 30%.
The second option has been selected since it has two main advantages:
▫
▫
well suited to account for technical constraint of carrying
biomass (minimal threshold of removal to cover logistics costs).;
Do not need to define the full relation between removal rate and
yield decrease at the field level. Only a point estimate is needed.
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Results
18
Cropland Expansion in Ha by TJ
0.6
0.5
Ha by TJ
0.4
0.3
0.2
0.1
0
Source: MIRAGE-BioF Simulation
Wheat Straw Ethanol
Corn Stover ethanol
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Cropland Expansion in Ha by TJ
• The increase in demand for cellulosic ethanol leads
to a net extension of the land area used for crops.
• This is the result of an increase in land area for
wheat production (wheat straw scenario) and corn
production (corn stover scenario) but a decrease in
cropland mainly absorbed by oilseed crop
production.
• In the first generation ethanol scenario (DL, 2011),
the increased demands led to the extension of the
land area used for the production sugar beet.
Results
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Annual LUC of EU consumption, 20 years
16
1st generation Ethanol
14
12
gCO2eq/MJ
10
8
2nd generation Ethanol
6
4
2
0
-2
-4
Series1
Ethanol_Maize
Ethanol_Wheat
Ethanol_WheatStra
w
Ethanol_CornStove
r
Ethanol_Corn
Stover_GTAP
10.3
14.4
4.26
3.90
-1.9
Interpretation / Discussion
Discussion on ILUC results
• Differences within 2nd gen. : yield/conversion rate.
• Differences 1st vs 2nd gen. :
▫ No DDGS effects in 2nd generation case,
▫ Required cropland expansion for 2nd generation case is
significantly reduced,
▫ Conversion rate.
• Differences 2nd gen in MIRAGE-Biof & GTAP-BIOADV : design of cropland-pasture land use
allocation.
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Sensitivity Analysis
Sensitivity Analysis
• We still need to test the sensitivity of ILUC
results with respect to changes in :
▫ Conversion rate of biomass into cellulosic ethanol,
▫ Relaxing assumptions that no added fertilizer to
offset the reduction in yields.
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Conclusion
Conclusion : ongoing stages
• Account for cellulosic ethanol co-products (Molasse, Lignin pellets)
• New feedstocks => working differently than crops residues :
perennial grasses « Miscanthus » (high biomass potential in EU
compared to Switchgrass)
• Integrating new technology : cellulosic biodiesel => Biomass to
Liquid Fuel (FTD)
• Cellulosic biofuel (ethanol and biodiesel) industry design
• Alternatives closures
• Non linearity behavior for second gen. Biofuels
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Thank you for your attention !!
Conclusion
Caveats
May drive ILUC factors results of 2nd gen biofuels :
• Design of fertilizers markets (inherent to the
model)
• Multicropping, crop rotation: general problem
for land use. For 2nde gen., specific crops rotation
could resolve the problem of soil fertilizer.
(Farmers => crop protection, especially
designed for crop residues).
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Results
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EU Crop Residues specific LUC
emissions
Breakdown by source of emissions
4%
Annual carbon release
from forest biomass
(gCO2eq/MJ)
6%
49%
50%
46%
45%
Annual carbon release
from carbon in mineral
soil (gCO2eq/MJ)
Annual carbon release
from Palm extension on
Peat (gCO2eq/MJ)
Wheat straw
Corn Stover