COMMISSION STAFF WORKING DOCUMENT IMPACT ASSESSMENT Accompanying the document Proposal for a Directive of the European Parliament and of the Council amending Directive 98/70/EC relating to the quality of petrol and diesel fuels and amending Directive 2009/28/EC on the promotion of the use of energy from renewable sources
Date: 2012-10-17
Institutions: European Commission
Subjects: atmospheric pollutant, biofuel, energy crop, environmental standard, greenhouse gas, reduction of gas emissions, renewable energy, utilised agricultural area

EUROPEAN 
COMMISSION 

Brussels, 17.10.2012  
SWD(2012) 343 final 

COMMISSION STAFF WORKING DOCUMENT 

IMPACT ASSESSMENT 

Accompanying the document 

Proposal for a 

Directive of the European Parliament and of the Council 

amending Directive 98/70/EC relating to the quality of petrol and diesel fuels and  
amending Directive 2009/28/EC on the promotion of the use of energy from renewable 
sources  

{COM(2012) 595 final} 
{SWD(2012) 344 final} 

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COMMISSION STAFF WORKING DOCUMENT 

IMPACT ASSESSMENT 

Accompanying the document 

Proposal for a 

Directive of the European Parliament and of the Council 

amending Directive 98/70/EC relating to the quality of petrol and diesel fuels and  
amending Directive 2009/28/EC on the promotion of the use of energy from renewable 
sources  

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TABLE OF CONTENTS 

1. 

1.1. 

1.2. 

1.3. 

2. 

2.1. 

2.2. 

2.3. 

2.4. 

2.5. 

Section: Procedural issues and consultation of interested parties................................ 5 

Background .................................................................................................................. 5 

Organisation and timing............................................................................................... 5 

Consultation of the Impact Assessment Board ............................................................ 6 

Section: Problem definition ......................................................................................... 7 

Introduction .................................................................................................................. 7 

Scene setter .................................................................................................................. 7 

The characteristics of Indirect Land-use Change....................................................... 10 

Modelling of indirect land-use change emissions...................................................... 10 

Underlying drivers ..................................................................................................... 15 

2.6.  Who is affected by indirect land-use change?............................................................ 16 

2.7. 

2.8. 

2.9. 

3. 

3.1. 

3.2. 

3.3. 

4. 

How are existing policies and legislation affecting indirect land-use change? ......... 17 

Baseline scenario for the assessment of indirect land-use change............................. 17 

The right to act ........................................................................................................... 26 

Section: Policy objectives .......................................................................................... 27 

Treaty based general objectives ................................................................................. 28 

General objectives...................................................................................................... 28 

Specific and operational objectives............................................................................ 29 

Section - Policy options ............................................................................................. 30 

4.1.  What are the possible options for achieving the policy objectives? .......................... 30 

4.2. 

4.3. 

4.4. 

4.5. 

4.6. 

Option A – take no action for the time being; while continuing to monitor.............. 30 

Option B - increase the minimum greenhouse gas saving threshold for biofuels...... 30 

Option C - introduce additional sustainability requirements on certain categories of 
biofuels....................................................................................................................... 31 

Option D - attribute a quantity of greenhouse gas emissions to biofuels reflecting the 
estimated indirect land-use impact............................................................................. 33 

Option E - Limit the contribution from conventional biofuels to the Renewable 
Energy Directive targets............................................................................................. 34 

5. 

Analysis of impacts .................................................................................................... 35 

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5.1. 

5.2. 

5.3. 

5.4. 

5.5. 

5.6. 

5.7. 

6. 

7. 

8. 

9. 

10. 

11. 

12. 

13. 

14. 

15. 

16. 

17. 

18. 

19. 

20. 

21. 

22. 

23. 

Assessment methodology........................................................................................... 35 

Option A - Take no action for the time being, while continuing to monitor ............. 37 

Option B - Increase the minimum greenhouse gas saving threshold for biofuels ..... 39 

Option C – introduce additional sustainability requirements on certain categories of 
biofuels....................................................................................................................... 45 

Option D - Attribute a quantity of greenhouse gas emissions to biofuels reflecting the 
estimated indirect land-use impact............................................................................. 48 

Option E - Limit the contribution from conventional biofuels to the Renewable 
Energy Directive targets............................................................................................. 57 

Combination of option D with C2 - Attribute a quantity of greenhouse gas emissions 
to biofuels reflecting the estimated indirect land-use impact whilst providing 
exemptions to those biofuels feedstocks produced under criteria covered by option 
C2. .............................................................................................................................. 60 

Comparison of policy options .................................................................................... 62 

Conclusion ................................................................................................................. 64 

Future monitoring and evaluation .............................................................................. 67 

Glossary ..................................................................................................................... 68 

Annex I – Consultation and use of external expertise................................................ 72 

Annex II – The concept of Indirect and direct land-use change emissions ............... 75 

Annex III – Model limitations and uncertainties ....................................................... 76 

Annex IV – Results from estimating indirect land-use change with models............. 80 

Annex V – The IFPRI-MIRAGE-BioF model: assumptions and results................... 83 

Annex VI – Fossil fuel comparator............................................................................ 88 

Annex VII – Trends in land-use- availability and expansion globally ...................... 89 

Annex VIII – Interactions between existing legislation and indirect land-use change94 

Annex IX – biofuels and related industries baseline tables ....................................... 99 

Annex X – Impacts on biodiversity ......................................................................... 103 

Annex XI – Monte-Carlo analysis of indirect land-use change emissions estimates105 

Annex XII – Potential for mitigating indirect land-use change emissions at project 
level .......................................................................................................................... 109 

Annex XIII – Assessment methodology .................................................................. 111 

Annex XIV – Possible response scenarios to reduced biofuel availability through the 
introduction of additional requirements ................................................................... 111 

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24. 

25. 

Annex XV – Developing indirect land-use change emission factors from the results 
of the Monte-Carlo analysis ..................................................................................... 116 

Annex XVI – Potential effects of including the estimated indirect land use change 
greenhouse gas emissions in the reporting of the greenhouse gas emission savings of 
biofuels..................................................................................................................... 118 

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1. 

SECTION: PROCEDURAL ISSUES AND CONSULTATION OF INTERESTED PARTIES 

1.1. 

Background 

Directive  2009/28/EC  on  the  promotion  of  the  use  of  energy  from  renewable  sources  (the 
"Renewable  Energy  Directive")  established  mandatory  targets  to  be  achieved  by  2020  for  a 
20% overall share of renewable energy in the EU and a 10% share for renewable energy in the 
transport sector. At the same time, an amendment was adopted to Directive 98/70/EC1 ("the 
Fuel  Quality  Directive")  which  introduced  a  mandatory  target  to  achieve  by  2020  a  6% 
reduction in the greenhouse gas intensity of fuels used in road transport. 

The  contribution  towards  these  targets  from  biofuels2  is  expected  to  be  significant.  Whilst 
both  Directives  (hereafter  referred  to  as  the  Directives)  include  sustainability  criteria 
including  minimum  greenhouse  gas  saving  thresholds,  the  greenhouse  gas  emissions 
associated  with  indirect  land-use  change  are  currently  ignored  by  the  legislation.  However, 
the Directives request the Commission to review3 by 31 December 2010 the greenhouse gas 
emissions  associated  with  indirect  land-use  change  and,  if  appropriate,  propose  ways  to 
address  them.  The  Commission  published  a  report  on  indirect  land-use  change  on  the  22 
December  20104.  That  report  (i)  identified  a  number  of  uncertainties  and  limitations 
associated with the available numerical models used to quantify indirect land-use change; (ii) 
acknowledged  that  indirect  land-use  change  can  reduce  greenhouse  gas  emissions  savings 
associated with biofuels; and (iii) indicated that if action is required, indirect land-use change 
should be addressed under a precautionary approach. Most importantly, it concluded that the 
Commission would prepare an Impact Assessment based on the four options identified in the 
report, accompanied, if appropriate, by a legislative proposal to amend the Directives.  

1.2. 

Organisation and timing 

In  order  to  better  understand  the  potential  indirect  land-use  changes  and  impacts  associated 
with  the  production  of  biofuels,  a  number  of  analytical  studies  were  commissioned  by 
different Commission Services. An inter-service working group5 was established in 2009 and 
met  regularly  during  2009  and  2010.  Discussions  in  this  group  have  provided  an  important 
input to these studies.  

Following the publication of these studies in mid-2010, the group focused on the production 
of the impact assessment report, with meetings of the Impact Assessment Steering Committee 
taking place in 2011 on 3 February, 17 February, 9 March, 18 March and 16 May. The Impact 
Assessment is relying mainly on the work of the International Food Policy Institute (IFPRI). 

1 
2 

3 
4 
5 

Directive 2009/30/EC. 
The requirement in the Renewable Energy Directive also applies to bioliquids. References to 'biofuels' 
in this document should be taken as also applying to bioliquids. 
Article 7d(6) of Directive 2009/30/EC and Article 19(6) of Directive 2009/28/EC. 
COM(2010) 811. 
Meetings  of  this  group  were  jointly  chaired  by  DG  ENER  and  DG  CLIMA.  Other  Commission 
Directorates  General  who  were  part  of  this  group  included  the  Secretariat  General,  DG  ENV,  DG 
MOVE, DG ENTR, DG ECFIN, DG AGRI, DG DEVCO, DG TRADE and the Joint Research Centre. 

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This  work  ("Global  trade  and  environmental  impact  study  of  the  EU  biofuels  mandate")6 
takes  into  account  stakeholder  feedback  collected  through  the  different  consultation  events 
outlined above, and has used the most recent biofuel demand estimates up to 2020 as outlined 
by  the  Member  States  in  their  national  renewable  energy  action  plans7.  The  Commission 
considers  this  work  to  represent  the  best  available  science  with  regards  to  the  estimated 
indirect land-use change impacts associated with biofuels consumed in the EU. The findings 
of the IFPRI-report were presented to stakeholders at a meeting on 18 November 20118.  

The Commission also carried out two public consultation exercises on approaches for dealing 
with  indirect  land-use  change  in  2009  and  2010.  Moreover,  the  Joint  Research  Centre 
organised  various  expert  consultation  meetings  with  academics  and  experts  in  the  field  in 
2009 and 2010. Further detail on these exercises can be found in Annex I. 

1.3. 

Consultation of the Impact Assessment Board 

The  present  Impact  Assessment  takes  into  account  the  recommendations  formulated  by  the 
Impact Assessment Board on 4 May 2011 and on 24 August 20119. The comments from the 
Board were incorporate in this Impact Assessment as follows: 

• 

• 

• 

• 

• 

• 

6 
7 
8 
9 

An option evaluating imposing a limit on the contribution of first generation biofuels 
has been introduced.  

Restructuring  of  text  and  further  clarifications  regarding  the  nature  of  the  problem 
and  the  framing  of  biofuels  and  ILUC  in  a  broader  context  (i.e.  the  Climate  and 
Energy  package,  global  and  EU  overall  land  use  change  and  associated  emissions, 
global trade, linkages with LULUCF, etc). 

The  description  of  the  baseline  scenario  was  restructured  and  extended  to  better 
describe  the  state  of  industry  sectors  involved  throughout  the  entire  biofuel 
production  and  deployment  chain  i.e.  agricultural  production,  processing  capacity 
(i.e. crushing of oilseeds), production plants for biodiesel, bioethanol and advanced 
biofuels  and  developments  on  the  car  fleet,  down  to  Member  State  level  where 
possible. 

The  presentation  of  options  has  been  clarified  and  the  impact  analysis  and 
presentation have been restructured to assist readability and enhance the link with the 
objectives. 

More  detail  has  been  provided  on  the  assessment  of  environmental,  economic  and 
social  impacts.  Further  work  from  the  Joint  Research  Centre  on  the  biodiversity 
impacts has also been included in the assessment. 

A glossary of technical terms has been added. 

http://trade.ec.europa.eu/doclib/docs/2011/october/tradoc_148289.pdf. 
http://ec.europa.eu/energy/renewables/transparency_platform/action_plan_en.htm. 
http://ec.europa.eu/energy/renewables/studies/land_use_change_en.htm. 
Insert reference before publication. 

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2. 

SECTION: PROBLEM DEFINITION 

2.1. 

Introduction 

The Directives impose a number of sustainability criteria aimed at preventing the conversion 
of  land  characterised  by  high  carbon  stock  and  high  biodiversity  for  biofuel  production. 
Moreover, they also require biofuels to achieve minimum greenhouse gas emission savings of 
35% compared to fossil fuels10.  

The  methodology  defined  in  the  Directives  to  determine  the  greenhouse  gas  saving  takes 
account  of  emissions  associated  with  direct  land-use  change,  as  well  as  emissions  coming 
from the production of biofuels. However, emissions associated with indirect changes in land-
use are currently not included (a figure explaining both direct and indirect land-use change is 
provided in Annex II).  

In  the  context  of  the  mandatory  targets  set  by  the  Directives  to  achieve  the  specified 
greenhouse  gas  savings,  and  the  6%  reduction  in  greenhouse  gas  intensity  required  by  the 
Fuel  Quality  Directive,  the  key  problem  addressed  by  this  impact  assessment  is  whether 
greenhouse gas emissions associated with indirect land-use change should be addressed, and 
if so in which way. As this impact assessment is focused on the specific requirement related to 
greenhouse  gas  emissions  from  indirect  land-use  change,  it  does  not  consider  any  wider 
environmental and social impacts associated with the promotion of biofuels. The Commission 
intends to consider these aspects in the Renewable Energy Directive's biennial reports to the 
European Parliament and the Council from 2012 onwards.  

2.2. 

Scene setter 

2.2.1.  The Climate and Energy Package targets 

In March 2007 the EU’s leaders endorsed an integrated approach to climate and energy policy 
aimed  at  combating  climate  change  and  increasing  the  EU’s  energy  security  while 
strengthening  its  competitiveness  and  transforming  itself  into  a  highly  energy-efficient,  low 
carbon economy. As part of this process, a series of demanding climate and energy targets to 
be met by 2020 were set, including, 

• 

• 

• 

a reduction in EU greenhouse gas emissions of at least 20% below 1990 levels  

a 20% of EU energy consumption to come from renewable resources  

and  a  20%  reduction  in  primary  energy  use  compared  with  projected  levels,  to  be 
achieved by improving energy efficiency.  

Biofuels represent around 1 and 2.5 percentage points of the 20% greenhouse gas reduction 
and  renewable  energy  targets  respectively.  However,  they  are,  as  estimated  in  the  National 
Renewable  Energy  Action  Plans11,  expected  to  be  the  major  contributor  towards  the  sub-
targets  for  10%  and  6%  renewable  energy  and  greenhouse  gas  emission  reductions  in  the 

10 
11 

This requirement is progressive as it increases to 50% in 2017 and 60% in 2018 for new installations. 
See table 1 in chapter 2.8, introducing the baseline, for the estimates contained in the plans. 

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transport  sector  to  2020,  as  set  by  the  Renewable  Energy  and  Fuel  Quality  Directives 
respectively.  

2.2.2.  Transport emissions reductions to 2050 

The  EU  is  committed  to  achieving  by  2050  an  80  to  95%  reduction  in  greenhouse  gas 
emissions economy wide compared to 1990 levels. The recent "A Roadmap for moving to a 
competitive low-carbon economy in 2050"12 foresees that the transport sector needs to reduce 
its  greenhouse  gas  emissions  by  around  60%  compared  to  1990  levels  by  2050  to  ensure  a 
comparable  cost-effectiveness  of  greenhouse  gas  emissions  abatement  in  that  sector.  This 
objective has been confirmed in the recently published transport white paper "Roadmap to a 
Single  European  Transport  Area  –  Towards  a  competitive  and  resource  efficient  transport 
system"13.  

Transport emissions can be reduced through measures which affect i) the amount of transport 
activity,  ii)  the  energy  efficiency  with  which  that  transport  is  carried  out  and  iii)  the 
greenhouse gas intensity of the energy used to perform the transport. Biofuels are one of the 
alternative  energy  carriers  available  that  offer  the  potential  to  reduce  the  greenhouse  gas 
intensity of the fuel. The use of biofuels may reduce greenhouse gas emissions provided that 
direct  and indirect greenhouse gas emissions are lower than those from the fossil fuels they 
replace. Given the overall transport greenhouse gas reduction goal, the degree to which one of 
the  three  levers  to  reduce  emissions  is  not  deployed,  the  more  action  that  will  be  required 
from the other two.  

2.2.3.  Global land-use and land-use change emissions 

The  globe  has  approximately  13  200  Mha  of  land,  of  which  around  1600  Mha  is  used  for 
cropping14,15. The IPCC special report on renewable energy16 estimates that 780 Mha of land 
are  available  for  bioenergy  production  without  irrigation  worldwide,  mostly  consisting  of 
unprotected  grassland  and  woodland  found  in  Africa  (35%),  Latin  America  (21%),  North 
America  (16%)  and  Europe  (14%),  having  the  potential  to  deliver  bioenergy  amounting  to 
more  than  4000  Mtoe.  The  estimated  total  biofuel  use  in  the  EU  in  2020  (27  Mtoe)  is  in 
comparison expected to cause a total land use change of less than 3 Mha of land globally17.  

The IEA biofuels for Transport - Technology Roadmap assumes that 27% of total transport 
fuel  demand  will  be  covered  by  biofuels  in  2050.  The  biofuel  demand  and  resulting  land 
requirements are shown for comparison below.  

12 
13 
14 

15 
16 
17 

Available at http://ec.europa.eu/clima/documentation/roadmap/docs/com_2011_112_en.pdf. 
Available at http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2011:0144:FIN:EN:PDF. 
WWF/Ecofys 2011 - The Energy Report, available here: http://www.ecofys.com/com/publications/The 
Energy-Report-Ecofys.htm. 
For comparison, total cropland in the EU represents around 107 Mha.  
Available at http://srren.ipcc-wg3.de/report.  
This estimate takes into account productivity increases, substitution effects and the estimated land saved 
by the production of co-products of biofuels. 

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Figure  1:  Demand  for  biofuels  (left)  and  resulting  land  demand  (right)  assumed  in  the  IEA  biofuel 
technology roadmap (Source: IEA Technology Roadmap18) 

The  production  of  conventional  bioethanol  and  biodiesel  increases  towards  2020,  and  then 
decreases,  disappearing  around  2045,  while  bioethanol  from  sugar  cane  increases  over  the 
whole  period.  Land-use  for  biofuels  increases  from  30  Mha  today19  to  around  110  Mha  in 
2050, which corresponds to around 7% of current cropland.  

With regard  to annual  global  emissions (50.000 Mt CO2)20, annual emissions from land-use 
change represent around 15%21 of the total (7500 Mt CO2). In this context, estimated indirect 
land-use  change  emissions  from  EU  biofuel  consumption  in  2020  are  likely  to  represent  a 
very small share (0.1%  if  based  on  annual estimated emissions by IFPRI-MIRAGE-BioF at 
50  Mt  CO2).  However,  this  level  of  emissions  deserves  consideration  in  the  context  of 
greenhouse  gas  emissions  savings  offered  by  biofuels.  This  is  discussed  in  more  detail  in 
section 2.4.3 and 2.8.6. 

2.2.4.  Bioenergy and biofuel production in a global context 

Bioenergy is the dominant renewable energy source, amounting to 10% (1200 Mtoe) of global 
primary energy supply. The IPCC estimates that the use of sustainable bioenergy will triple22 
towards 2050 in order to meet climate change objectives23. Careful policy making, including 
considerations of indirect land-use change impacts, is necessary to mobilise such quantities in 
a sustainable way.  

Most  of  today's  biofuels  are  produced  from  agricultural  crops  like  maize,  sugar  cane  and 
rapeseed.  Total  global  production  of  biofuels  reached  70  Mtoe  in  2008,  which  represents 
1.7% of global oil consumption. While less than 3% of global cropland is used for producing 

18 
19 

20 
21 
22 

23 

Available here: http://www.iea.org/papers/2011/biofuels_roadmap.pdf.  
Note that the land savings of co-products produced from conventional biofuels are not considered in the 
figure. 
IPCC Fourth Assessment Report (AR4). Available here: www.ipcc.ch.  
Van der Werf et.al. CO2 emissions from forest loss, Nature Geoscience, vol 2, 2009.  
The  median  value  of  164  scenarios  is  at  around  150  EJ,  while  the  whole  span  is  35  EJ  –  300  EJ  for 
2050. 
To halt GHG concentration to below 440 ppm. Executive summary. For reference see footnote 16. 

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biofuels, the relative importance of biofuels within certain global markets is significant. For 
example, globally 16% of vegetable oils (rapeseed, soybean, palm and sunflower oil) are used 
for biodiesel, 15% of maize and some 2% of wheat is used for bioethanol24.  

Biofuels are traded globally, as can be seen in figure 2 below, which depicts the production 
and trade of biofuels in 2009. 

Figure 2: 2009 production and trade of biofuels. Source: IPCC (see footnote 16) 

The US (maize) and Brazil (sugar cane) are the main biofuel producers, producing more than 
the rest of the world combined. The EU is the largest global market for biodiesel because of 
the dominance of diesel in the car fleet. In 2009, the EU imported soy biodiesel mainly from 
Argentina  and  US,  and  to  a  significantly  lesser  extent  palm  oil  from  South  East  Asia. 
Bioethanol, to be blended with petrol, was imported from Brazil. Two thirds of the biofuels 
consumed in the EU are currently produced domestically, with the share of imports expected 
to grow towards 2020 (IFPRI-MIRAGE-BioF estimates that half of biofuels will be imported 
in 2020).  

2.3. 

The characteristics of Indirect Land-use Change 

Most of today's  biofuels  are  produced  from crops grown on agricultural land  such as wheat 
and  rapeseed.  When  agricultural  or  pasture  land  previously  destined  for  the  food,  feed  and 
fibre markets is diverted to the production of biofuels, the non-fuel demand will still need to 
be  satisfied.  Although  this  additional  demand  can  be  met  through  intensification  of  the 
original production, bringing non-agricultural land into production elsewhere is also possible. 
It is in the latter case that land-use change occurs indirectly, (hence the term indirect land-use 
change).  

While most biofuel feedstocks are being produced in the EU, the estimated indirect land-use 
change  emissions  are  mostly  expected  to  take  place  outside  the  EU,  where  the  additional 
production is likely to be realised at the lowest cost. In the case that this production is realised 
through  the  use  of  additional  land,  its  conversion  could  lead  to  substantial  greenhouse  gas 
emissions being released if high carbon stock areas such as forests are affected as a result.  

24 

Laborde, D.D. Domestic policies in a globalized world: what you do is what I get (2011). 

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2.4.  Modelling of indirect land-use change emissions 

Estimating  the  greenhouse  gas  impact  due  to  indirect  land-use  change  requires  projecting 
impacts  into  the  future,  which  is  inherently  uncertain,  since  future  developments  will  not 
necessarily  follow  trends  of  the  past.  Moreover,  estimated  land-use  change  can  never  be 
validated, as indirect land-use change is a phenomenon that is impossible to directly observe 
or measure. Therefore modelling is necessary to estimate its occurrence. 

No macro-economic models used to estimate indirect land-use change emissions are currently 
capable  of  modelling  the  effects  of  the  EU  sustainability  criteria,  so  these  criteria  are 
consequently assumed not to have any effect. As such, the models are not able to distinguish 
between  direct  and  indirect  land-use  change.  Nevertheless,  the  current  estimates  from  the 
models  are  considered  the  best  approximation  for  estimating  indirect  land-use  change 
emissions.  

Several non-economic factors influence what land-use change takes place and where it occurs. 
Some  of  these  drivers  are  related  to  political  choices  (land-use  and  agricultural  policy,  land 
rights, etc.), others to institutional features (proximity to infrastructure and markets, land-use 
legislation).  Therefore  conceptual  limitations  will  always  remain.  Annex  III  provides  more 
details on the various modelling approaches, and the related uncertainties and limitations.  

2.4.1.  Results from modelling indirect land-use change 

As set out above, the Commission launched a number of studies in 2009, 2010 and 2011 on 
indirect land-use change. Further details on the assumptions and results from these studies are 
provided in Annex IV. A description of one of them in particular, the IFPRI-MIRAGE-BioF 
model,  which  is  the  basis  for  the  modelling  establishing  the  baseline  used  in  this  Impact 
Assessment, can be found in Annex V.  

The MIRAGE-BioF model, developed by the ATLASS consortium, has been improved over 
the last three years in consultation with the Commission to model the consumption of biofuels 
used  in  the  EU.  Although  a  number  of  limitations  and  uncertainties  remain,  this  model  has 
been found to be the most suitable one to estimate the indirect land-use change emissions in 
the EU context.  

The  IFPRI-MIRAGE-BioF  model  is  a  general  equilibrium  model,  which  encompasses  all 
economic sectors and markets and their inter-actions at a global scale. The model is run in a 
"baseline  scenario",  and  a  "policy  scenario",  where  the  only  difference  is  the  EU  biofuel 
policy.  The  resulting  difference  in  land-use  change  emissions  is  then  divided  by  the 
additionally produced biofuels. In addition, the Commission has identified a number of other 
sources  illustrating  different  (indirect)  land-use  change  emissions  from  different  feedstocks. 
Figure  3  provides  a  summary  of  the  most  relevant  modelling  exercises  undertaken25.  It  sets 
out  calculations  of  estimated  indirect  land-use  change  emissions  in  gCO2/MJ  for  a  range  of 
different feedstocks showing the range of volumes obtained, and converted where necessary 
to a 20 year timeframe26.  

25 

26 

Lines illustrate ranges when Monte Carlo analysis of the uncertainty has been carried out; shaded bar 
areas  illustrate  maximum  and  minimum  values  from  the  analysis  when  different  scenarios  have  been 
considered. 
The  methodology  set  out  in  the  Directives  for  calculating  land-use  change  prescribes  that  such 
emissions shall be divided by 20 years.  

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Oko 2010 Biofuels average "50% risk" (2030)
ECOM ETRICA 2009 (palm oil)
ECOM ETRICA 2009 (soy)

ECOMETRICA 2009 (rapeseed)
ECOM ETRICA 2009 (sugar cane)

ECOM ETRICA 2009 (maize)
ECOM ETRICA 2009 (sugar beet)

ECOM ETRICA 2009 (wheat)
E4Tech 2010 (sugar cane)

E4Tech 2010 (wheat)
E4Tech 2010 (soybean)

E4Tech 2010 (Rapeseed)
E4Tech 2010 (Palm Oil)

PBL (2011) Bioethanol
PBL (2011) Biodiesel

JRC 2011 (IFPRI-M IRAGE-BioF Sunflower)

JRC 2011 (IFPRI-M IRAGE-BioF Rapeseed)
JRC 2011 (IFPRI-MIRAGE-BioF Palm Oil)

JRC 2011 (IFPRI-MIRAGE-BioF Soybean)
IFPRI-MIRAGE-BioF 2011 (Sunflower)

IFPRI-MIRAGE-BioF 2011 (Rapeseed)
IFPRI-M IRAGE-BioF 2011 (Palm Oil)

IFPRI-M IRAGE-BioF 2011 (Soybean)
IFPRI-MIRAGE-BioF 2010 (Sunflower)

IFPRI-MIRAGE-BioF 2010 (Rapeseed)
IFPRI-M IRAGE-BioF 2010 (Palm Oil)

IFPRI-MIRAGE-BioF 2010 (Soy)
LCFS (2009) (Soy)

RFS 2 (soy)

JRC 2011 (IFPRI-MIRAGE-BioF sugar beet)
JRC 2011 (IFPRI-MIRAGE-BioF sugar cane)

IFPRI-M IRAGE-BioF 2011 (sugar beet)
IFPRI-M IRAGE-BioF 2011 (sugar cane)
IFPRI-M IRAGE-BioF 2010 (sugar beet)

IFPRI-M IRAGE-BioF 2010 (sugar cane)
LCFS (2009) (Sugar Cane)

RFS 2 (Sugar Cane)
RFS 2 (Switchgrass))

JRC 2011 (IFPRI-MIRAGE-BioF wheat)
JRC 2011 (IFPRI-M IRAGE-BioF Maize)

IFPRI-M IRAGE-BioF 2011 (wheat)
IFPRI-MIRAGE-BioF 2011 (Maize)

IFPRI-M IRAGE-BioF 2010 (wheat)
IFPRI-MIRAGE-BioF 2010 (Maize)

Plevin 2010 (US Maize)
Searchinger 2009 (US Maize)

Hertel 2010 (Maize) 
Tyner 2010 (US M aize) GTAP 2006

Tyner 2010 (US M aize) GTAP 2001
LCFS 2009 (Maize)

RFS 2 (Maize)

IIASA (biofuel mix)
JRC-AGLINK (biofuel mix)

JRC "IFPRI-M IRAGE-BioF 8.6%" (biofuel mix)
JRC "IFPRI-M IRAGE-BioF 5.6%" (biofuel mix)

IFPRI-MIRAGE-BioF 2010 "8.6%" (biofuel mix)
IFPRI-MIRAGE-BioF 2010 "5.6%" (biofuel mix)

JRC 2011 "IFPRI-MIRAGE-BioF full mandate"
IFPRI-MIRAGE-BioF 2011 "full mandate" (biofuel mix)

Figure 3: Summary of estimated (indirect) land-use change emissions. Source: various 

-60

-30

0

30

60

90
gCO2/MJ

120

150

180

210

240

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2.4.2. 

Short and long term developments to deal with limitations and uncertainties 

There  are  a  range  of  key  assumptions  used  in  the  indirect  land-use  change  models  that  can 
have  a  substantial  impact  on  the  indirect  land-use  change  estimates.  A  first  step  in  dealing 
with  this  cause  of  uncertainty  is  to  understand  the  parameters  involved.  The  Commission's 
model comparison exercise and the literature review have provided an indication of a limited 
number of key factors that are of high importance. These include, but are not limited to: co-
products,  yield  developments,  carbon  stocks  and  displacement/substitution  of  other 
commodities.  These  aspects  have  also  been  considered  by  the  Low  Carbon  Fuel  Standard 
Expert  Workgroups  established  as  part  of  California  Air  Resource  Board's  attempts  to 
improve the modelling of indirect land-use change27. 

In relation to uncertainty in the model results due to data and assumptions, an approach that 
enables  the  parameters  being  considered  to  be  varied  randomly  according  to  an  expected 
probability function can be used. This so-called Monte Carlo analysis is a standard approach 
to  dealing  with  uncertainty  in  modelling,  and  the  method  chosen  by  the  US  Environmental 
Protection Agency in their attempt to estimate indirect land-use change emissions.  

2.4.3.  Overall greenhouse gas balance of using biofuels in the EU 

The emissions associated with the cultivation, processing and transport of biofuels have been 
extensively explored by the Commission making use of the JEC's Well to Wheel study28, and 
form  the  basis  for  the  greenhouse  gas  intensity  values  established  in  EU  legislation.  These 
values for land using first generation biofuels29 vary from around 20 g/MJ to 60 g/MJ, and do 
not include emissions for either direct or indirect land-use change.  

The  Directives  require  that  biofuels  counted  towards  the  targets  need  to  save  at  least  35% 
greenhouse  gas  emissions  compared  to  average  fossil  fuel  emissions,  using  a  fossil  fuel 
comparator  (FFC),  which  is  currently  set  at  83.8g/MJ30.  However,  more  recent  research 
indicates that a higher number would be more accurate31.  

Different  models  assume  different  fossil  fuels  being  substituted  by  biofuels.  The  literature 
review finds that to some degree higher production cost is linked with higher greenhouse gas 
emissions,  but  not  systematically.  For  example,  "deep  water"  and  "artic"  sources  are  more 
costly for other reasons than high energy consumption per barrel extracted crude. However, 
the general picture is that more expensive crudes are connected with higher emissions. 

In  the  context  of  analysing  indirect  land-use  change,  a  consequential  lifecycle  analysis  is 
applied for the land resources, which implies that the global net effect is analysed. This is why 
land-use changes taking place in areas where no biofuel is produced still has an impact on the 
estimated  indirect  land-use  change  emissions  of  biofuels.  Applying  the  same  framework  to 
fossil  fuel,  it  is  appropriate  to  compare  overall  emissions  from  biofuels  to  global  marginal 

27 
28 
29 
30 

31 

CARB Expert Workgroups: http://www.arb.ca.gov/fuels/lcfs/workgroups/ewg/expertworkgroup.htm.  
Reports available here: http://ies.jrc.ec.europa.eu/jec-research-collaboration/downloads-jec.html.  
A list of typical values for a range of most common biofuel pathways is discussed in table 4. 
In addition, the fossil fuel comparators for bioliquids are 91, 77 and 85 g/MJ depending on whether they 
are used for electricity production, heat production or cogeneration. 
JRC estimates on expected fossil fuel comparator in 2020 can be found in Annex VI. 

EN 

14 

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emissions  from  fossil  fuels  not  being  extracted  as  a  consequence  of  using  biofuels.  Set  out 
below is a simplified figure depicting the application of the above approach32. 

150

100

50

0

-50

-100

J
M

/
.

q
e
2

O
C
m
a
r
g

Average

high

low

A: Assumed
Biofuel
production
emissions

B: Possible
indirect land-use
change
emissions

C = A + B: Sum
of land use
change and
biofuel
production
emissions

D: Substituted
fossil fuel
production
emissions

E = C - D: GHG
emissions

Figure 4: Emissions balance of biofuels in 2020, including estimated indirect land-use change emissions, 
compared to the emissions of fossil fuels not extracted. 

The  global  marginal  emissions  from  fossil  fuels  are  expected  to  be  higher  than  average 
emissions of fossil fuels used in the EU, the latter being reflected in the fossil fuel comparator 
(FFC), which in this assessment has been assumed to be 90.3 g/MJ in 2020. As can be seen 
from  figure  4,  the  overall  greenhouse  gas  emissions  balance  of  the  estimated  biofuel  mix 
compared to fossil fuels is expected to be positive in 2020, implying that the use of biofuels 
will save emissions also when the estimated indirect land-use change emissions are taken into 
account. Irrespective of the emissions from conventional sources of fossil fuels, if biofuels are 
to  lower  the  overall  greenhouse  gas  emissions  from  transport  fuels  significantly  and  to  an 
increasing  degree,  the  greenhouse  gas  intensity  has  to  be  reduced  over  time33.  It  is  in  this 
context that indirect land-use change emissions pose a challenge. 

32 

33 

A: average direct emissions in 2020 based on the Member States National Renewable Energy Action 
Plans  (NREAPs,  27.2Mtoe,  ¾  of  biodiesel  vs  ¼  bioethanol).  All  biofuels  are  assumed  to  meet  the 
greenhouse gas emissions thresholds in the Directives - no changes to current sustainability scheme but 
fossil fuel comparator is set at 90..3g CO2/MJ. B: possible range (5th to 95th percentile) of estimated 
indirect  land-use  change  emissions  according  to  latest  IFPRI-MIRAGE-BioF  2011  study  based  on 
NREAPs (27.2Mtoe, ¾ of biodiesel vs ¼ bioethanol). Averaged over 20 year period according to the 
Directive's  greenhouse  gas  emissions  methodology.  C:  Sum  of  average  direct  emissions  in  2020  and 
estimated indirect land-use change emissions (A+B). D: marginal fossil fuel emissions from crudes not 
being  extracted  based  on  the  assumed  2020  fossil  fuel  comparator  (lower  end)  and  high  emitting  oil 
sands  from  Brandt  et  al  (upper  end).  E:  overall  greenhouse  gas  emissions  balance  of  the  expected 
biofuel  mix  in  2020  compared  to  fossil  fuels;  range  comes  from  comparing  high  indirect  land-use 
change emissions with low fossil fuel emissions and vice versa.  
See the EU 2050 Roadmap for an indication of the required reduction in transport emissions. 

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2.5. 

Underlying drivers  

The drivers behind indirect land-use change can be summarised as the increased demand for 
crops  resulting  from  increased  biofuel  use,  coupled  with  poor  land-use  governance  in  areas 
with high carbon stock land and  lack of complete accounting rules and emission targets for 
land-use change globally.  

2.5.1.  Land availability globally 

The basic driver for indirect land-use change is the increased demand for agricultural crops as 
a  result  of  increasing  biofuel  production  in  a  situation  where  potential  yield  increases  are 
limited and demands (most notably for food and feed) are not fully elastic. Some  other  key 
factors, such as achieving maximum profit from the production and complying with relevant 
legislation,  are  also  likely  to  play  a  role  in  determining  how  the  increased  demand  is  to  be 
realised.  

The  extent  to  which  land  availability  is  limited  in  various  regions  of  the  world  is  much 
debated. Compared to 1981 the harvested land has significantly declined in Europe, CIS and 
North America, thus suggesting that there would be low carbon stock land available34. With 
regard to the EU, it is expected that the agricultural area will continue to reduce by around 0.5 
million hectares each year. Further details on this can be found in Annex VII. 

2.5.2.  Where is agricultural land expanding? 

Although it is clear that a significant amount of land is available in certain areas of the world, 
it is difficult to govern the proper use of these land areas. Recent studies suggest that tropical 
forests  were  the  primary  sources  of  new  agricultural  land  in  1980-90s,  with  various  studies 
highlighting  a  significant  role  for  soy  production  and  cattle  ranging,  as  well  as  palm  oil,  as 
drivers  behind  the  expansion  of  agricultural  land  into  the  Amazon  and  South  East  Asia 
respectively35.  

The lack of effective protection of forests and carbon rich areas is another factor that allows 
damaging indirect land-use change to take place.  If  conversion  of carbon rich areas such as 
forests and wetlands were to be limited, the risk of damaging indirect land-use change would 
be lower. Further information, including international developments in this area, can be found 
in Annex VII. 

2.5.3.  Accounting for land-use, land-use change and forestry (LULUCF) 

In  national  greenhouse  gas  inventories  (which  are  the  basis  for  countries'  emission 
commitments, such as the EU's greenhouse gas target) emissions from the burning of biofuels 
are reported under the energy sector as zero. This means that emissions are not added to the 
total national emissions and that it is assumed that any greenhouse gas emissions from land 

34 

35 

However, if it is the least fertile land that has been recently abandoned, then its future production could 
be  expected  to  show  typical  yields  below  average,  leading  to  either  increased  land  requirements  or 
increased  use  of  fertilisers.  In  addition,  if  the  land  is  under  a  process  of  managed  reforestation,  its 
reversion to agricultural production could result in the release of carbon emissions. 
Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. H. K. Gibbs, 
A. S.Rueschb, F. Achardc, M. K. Claytond, P. Holmgrene, N. Ramankuttyf, and J. A. Foleyg 2010. 

EN 

16 

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(including any direct and indirect land-use change) are captured under the "land-use, land-use 
change and forestry" (LULUCF) sector of the inventory36.  

So, while incentives exist to promote the use of bio-energy37, a coherent approach to climate 
change  mitigation  in  the  LULUCF  sector  via  measures  in  agriculture,  forestry  and  related 
industries at the global level is only in the making.  The  LULUCF  sector has a positive and 
significant impact on the EU's greenhouse gas emissions. The sector removes the equivalent 
of 9% of greenhouse gases emitted in other parts of the economy38. Although emissions and 
removals from LULUCF are reported under the UNFCCC and partially accounted under the 
Kyoto Protocol, the sector was left out of the EU's climate commitments for 2020 under the 
Climate and Energy Package39 due to the recognition of serious deficiencies in international 
accounting rules of emissions from this sector (accounting for emissions and removals is only 
mandatory  for  some  land  use  change  activities  including  afforestation,  deforestation  and 
reforestation). Developing countries do not account at all.  

Taken together, this means that emissions from land-use changes in developed countries due 
to agricultural expansion is unlikely to be fully reflected in the accounting, and that land-use 
change emissions in developing countries are not accounted for. 

An  international  agreement  on  revised  accounting  rules  for  LULUCF  for  the  second 
commitment period under the Kyoto Protocol post 2012 was achieved at the 17th Conference 
of  the  Parties  to  the  UNFCCC  ("COP17")  in  Durban  in  December  2011.  In  particular 
accounting  for  forest  management  activities,  including  harvested  wood  products,  will  be 
mandatory and definitions for natural disturbances and "wetland drainage and rewetting" have 
been established.  

Following this agreement  the  Commission tabled a proposal on 12 March 2012  on how  the 
LULUCF sector increasingly could be integrated in the EU's climate policy using a step-wise 
approach. As a first step, it proposes establishing robust, common accounting, monitoring and 
reporting rules mandatory for forests, forest management, croplands and grassing land as well 
as national LULUCF action plans (LAP). In view of the sector's specific emissions profile, the 
Commission  proposed  a  dedicated  legal  framework,  rather  than  including  it  in  the  EU 
Emissions Trading Scheme or the rules created by the Effort Sharing Decision. 

The second step would be to formally include LULUCF in the EU's greenhouse gas reduction 
target.  It  is  proposed  to  take  this  step  when  the  Member  States  have  implemented  the 
accounting framework and it has proven to be robust.  

Accounting  for  LULUCF  would  clarify  the  benefits  of  sustainable  bio-energy  by  better 
reflecting related emissions, in particular resulting from the combustion of biomass, which is 
unaccounted  for  at  the  moment.  This  would  strengthen  the  incentives  provided  by 
sustainability  criteria  in  the  context  of  renewable  energy  targets.  However,  implementing 
LULUCF accounting, monitoring and reporting in the EU is likely to have a limited effect on 
the estimated indirect land-use change emissions globally, as these take place mostly outside 
of  the  EU.  An  implementation  of  LULUCF  accounting  on  a  global  scale,  combined  with 

36 
37 
38 
39 

1996 IPCC Guidelines for National Greenhouse Gas Inventories (Vol. 3, Energy, p. 1.10). 
Directive 2009/28/EC.  
National total excluding the LULUCF sector. 
Unlike  non-CO2  greenhouse  gases  from  agricultural  activities  e.g.  methane  and  nitrous  oxide  from 
ruminants and fertilisers. 

EN 

17 

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commitments for reducing emissions, could significantly reduce the indirect land-use change 
emissions, as converting high carbon stock land would have a cost. 

2.6.  Who is affected by indirect land-use change? 

Climate change is a global problem, while the socio-economic consequences of indirect land-
use change have regional and national effects affecting the global population. Regulations to 
address  indirect  land-use  change  emissions  in  the  field  of  biofuels  may  affect  local 
communities,  biofuel  feedstock  producers,  the  biofuel  industry,  Member  States  and  third 
countries in various ways. These will be incorporated in the assessment of the policy options 
in section 5. 

Although  land-use  change  can  have  a  wide  range  of  positive  and  negative  impacts  (i.e. 
greenhouse gas emissions, biodiversity, economics, social issues, etc), this report focuses on 
the consequences for the greenhouse gas emissions of biofuels, as required by the Directives. 
The Commission will analyse wider sustainability impacts associated with the promotion of 
biofuels in the Renewable Energy Directive's biennial reports to the European Parliament and 
the Council from 2012 onwards.  

2.7. 

How are existing policies and legislation affecting indirect land-use change?  

Developments  driven  by  existing  legislation  in  a  number  of  areas  could  have  a  significant 
impact on indirect land-use change. These include existing EU legislation relating to biofuels 
(the  Renewable  Energy  and  Fuel  Quality  Directives),  as  well  as  wider  agricultural  (i.e. 
Common Agricultural Policy), environmental (i.e. biodiversity, forestry, REDD+), trade (i.e. 
agricultural  tariffs),  developmental  (i.e.  investment  into  agriculture)  and  research  (i.e. 
agricultural research and advanced biofuels) policies. Further details are found in Annex VIII. 

2.8. 

Baseline scenario for the assessment of indirect land-use change  

In  order  to  be  able  to  assess  the  full  impacts  of  the  policy  options  being  considered  in  this 
assessment, this section aims to provide an overview of the EU biofuel and related industries, 
and the estimated indirect land-use change emissions associated with the increased feedstock 
demand for biofuels.  

2.8.1.  Overview of biofuels and related industries  

The production of biofuels involves economic activity and employment all along the supply 
chain;  in  agriculture,  logistics  and  at  biofuels  production  facilities,  but  also  in  sectors  that 
supply to or support biofuels supply chains, and is generally more labour intensive than fossil 
fuels. The expected employment related to biofuels in EU in 2020 could be around 400,000 
jobs in total40.  

40 

EmployRES study (p. 133). 
http://ec.europa.eu/energy/renewables/studies/doc/renewables/2009_employ_res_report.pdf. This figure 
represents estimated gross effects and does neither take into account adjustments in other parts of the 
economy  (i.e.  reduced  opportunities  in  fossil  fuel  industry)  nor  adjustments  for  tax  incentives  and 
subsidies given to the production of biofuels.  

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2.8.1.1.  EU production and consumption - 2008 and 2020  

Reported  2008  and  estimated  2020  consumption  figures  for  biofuels  and  other  renewable 
energy sources (RES) in transport are shown in table 1 below. The 2020 figures are based on 
the National Renewable Energy Action Plans (NREAPS), which have been submitted by the 
Member States41. The NREAPs are also the basis for the baseline established in this Impact 
Assessment. Compared to the expected increase of biofuels, bioliquids are expected to play a 
small role in contributing towards the overall 20% RES target at around 5.5 Mtoe (4.4 Mtoe 
and  1.1  Mtoe  going  into  the  production  of  heat  and  power,  and  electricity  generation 
respectively).  This  does  not  represent  a  significant  increase  compared  to  2008  levels.  The 
production  of  biofuels  from  waste  feedstocks  and  advanced  biofuel  technologies  is  not 
expected to be significant and lower than anticipated, reaching 2.3 Mtoe (approximately 1.5 
percentage  point  with  double  counting)  in  2020.  It  appears  that  the  current  incentives, 
particularly,those set out in Article 21(2)42 of the Renewable Energy Directive, are not enough 
to spur the desired level of investment in advanced 2nd generation biofuels. 

Total transport fuels (Mtoe) 

1st generation biofuels (Mtoe) 

of which biodiesel (Mtoe) 

of which bioethanol (Mtoe) 

1st generation biofuel (p.p of RES-T) 

Biofuels from waste and 2nd generation share (p.p of RES-T) 

Renewable electricity in transport (p.p of RES-T inc)  

 Table 1: RES in transport 2008 and 2020. 

2.8.1.2.  EU agricultural production  

2008 

239  

10 

8.2  

1.8  

3.5 

0 

0.4 

2020 

312  

26.5  

19.8  

6.7  

8.6 

1.5 

1.4 

Biofuel  feedstocks  currently  used  are  typically  'first  generation'  and  include  biodiesel  and 
bioethanol  derived  mostly  from  crops,  (i.e.  cereals,  sugars  and  oil  crops)  except  those 
produced from waste feedstocks. 
In  the  EU,  the  share  of  the  cereal  production43,44  consumed  in  the  bioethanol  market  was 
around  9.4  Mt  during  the  2009/10  marketing  year  (3.2%  of  a  total  EU  cereal  production  at 
292  Mt),  with  wheat  being  the  most  common  feedstock  used.  Moreover,  estimated 
consumption of sugarbeet in the EU bioethanol market is about 6 Mt (5.4% of the total EU 

41 

42 

43 

44 

in 

the 

and 

both 

plans, 

original 

language 

All 
are 
English 
http://ec.europa.eu/energy/renewables/transparency_platform/action_plan_en.htm. 
Biofuels  made  from  certain  feedstocks  (waste,  residues  and  woody  material)  are  counted  double 
towards the 10% target of the Renewable Energy Directive. 
Data for cereals from: Prospects for agricultural markets and income 2010-2020, 
http://ec.europa.eu/agriculture/publi/caprep/prospects2010/fullrep_en.pdf.  
Bioethanol figures are for fuel use only. Data on cereals, sugar beet and oil crops divided by member 
states,  data  available  at  http://epp.eurostat.ec.europa.eu/cache/ITY_OFFPUB/KS-ED-10-001/EN/KS-
ED-10-001EN.PDF. 

available 

here:  

EN 

19 

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sugar beet production at 110 Mt)45. Across the EU, the largest producers of cereals and sugar 
beet respectively were France (70Mt and 33 Mt), Germany (50 Mt and 25 Mt), Poland (30 Mt 
and 11 Mt) and the UK (18 Mt and 8 Mt). 

With  regard  to  biodiesel,  the  share  of  vegetable  oils  destined  for  this  market  represented 
around 9 Mt. This equals to 38% of the estimated EU consumption of vegetable oils 23.4Mt 
in 2010/1146. Of this oils market, around 41% is imported as oil, and around 10% is imported 
as  beans  (mainly  soya)47.  EU  oil  crops  production  concerns  mainly  rapeseed  (20.4  Mt  in 
2010/2011), sunflower seed (6.7 Mt) and soya (1.1. Mt). Across the EU, the largest producers 
of  rapeseed  were  Germany  (6.3  Mt),  France  (5.6  Mt),  Poland  (2.5  Mt)  and  UK  (2  Mt).  For 
sunflower, these were France (1.6 Mt), Bulgaria (1.3 Mt), Hungary (1.3 Mt), Romania (1 Mt) 
and Spain (0.8 Mt). 

The EU-27 is traditionally a net exporter of cereals, but a net importer of vegetable oils and 
oilseeds  (despite  recently  achieving  record  production  levels  of  oil  crops),  and  to  a  lesser 
extent of sugar. Current forecasts predict that this trend, with regard to cereals and vegetable 
oils, will continue to 2020. 

2.8.1.3.  Trade in biofuels 

The table below shows the current and estimated split of biofuels across feedstocks in 2020. 

2008 (%) 

Source 2008 

2020 (%)  

Source 2020* 

Biodiesel 

Rapeseed 

Soya 

Palm oil 

Sunflower 

Bioethanol 

Sugar cane 

Wheat 

Sugar beet 

Maize 

83 

57 

20 

4 

2 

17 

6 

5 

3 

3 

Europe

Argentina, USA

South East Asia

Europe and imports

Brazil

Europe

Europe

Europe and imports

72 

40

11

17

4

28 

13

6

5

4

Europe and imports

Argentina, USA

South East Asia

Europe and imports

Brazil 

Europe and imports

Europe 

Europe and imports

 Table 2: Land using biofuels currently used in the EU48 and estimations for 202049. 

With  regard  to  imports  vs.  domestic  production,  IFPRI-MIRAGE-BioF  estimates  that 
biodiesel  imports  will  grow  from  0.75  Mtoe  in  2008  to  2.5  Mtoe  in  2020  (mostly  from 
Indonesia, Malaysia and Latin America); whereas bioethanol imports will increase from under 

45 

46 
47 

48 

49 

" 

of 

sustainability 

environmental 

Commission's calculations based on total bioethanol volumes from "The EU Beet and Sugar Sector: A 
model 
http://www.cibe-
europe.eu/Press/Brochure%20CIBE-CEFS%20Final_05.05.2010.pdf.  
Oil World March 2011. 
In  comparison,  global  production  of  cereals  reached  2240  million  tons,  vegetable  oils  at  141  million 
tons and sugars at 174 million tons in 2009. OECD-FAO Agricultural Outlook 2010-2019. 
Source:  Progress  report  on  Renewable  Energy  and  supporting  material.  The  Communication  and  the 
here: 
documents 
accompanying 
http://ec.europa.eu/energy/renewables/reports/reports_en.htm.  
Source: IFPRI-MIRAGE-BioF simulations. 

available 

available 

working 

staff 

are 

at 

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20 

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1 Mtoe in 2008 to around 3.5 Mtoe in 2020 (mostly from Brazil). In addition, a total of 14 Mt 
of  feedstocks  will  also  be  imported  into  the  EU  (rapeseed,  oil  palm  and  maize  having  the 
largest share) as a result of the additional demand50. Therefore, it is expected that about half 
of the biofuels consumed in the EU in 2020 would be domestically produced, with rapeseed 
being the main feedstock.  

2.8.1.4.  Biofuel installed production capacity 

Production capacity in the EU, both installed and under construction, currently stands at 24.5 
Mtoe,  of  which  19.8  Mtoe  is  for  biodiesel  and  4.3  Mtoe  for  bioethanol.  With  regard  to  its 
distribution  across  Member  States,  most  of  the  EU  biodiesel  capacity  can  be  found  in 
Germany  (4.5  Mtoe),  Spain  (3.7  Mtoe),  France  (2.3  Mtoe),  Italy  (2.1  Mtoe)  and  the 
Netherlands  (1.2  Mtoe)51.  The  smaller  bioethanol  capacity  is  distributed  across  France  (0.9 
Mtoe),  Germany  (0.7  Mtoe),  UK  (0.5  Mtoe),  Spain  (0.4  Mtoe)  and  Poland  (0.4  Mtoe)52. 
Advanced biofuels installed capacity is currently negligible and limited to a few pilot plants.  

Although the installed biodiesel production capacity in Europe increased rapidly from 2006-7 
onwards, it seems to have slowed down in 2010. In some countries such as Germany, it has 
shown  a  slight  decrease  in  2010,  where  some  biodiesel  facilities  have  been  closed  down, 
decommissioned or retrofitted to other production processes. Moreover, it is worth noting that 
due to a slow market uptake, capacity utilisation is at around 50%, with total 2009 European 
production  standing  at  8.2  Mtoe  and  1.9  Mtoe  for  biodiesel  and  bioethanol  respectively. 
Germany and France alone accounted for over 50% of EU biofuel production in 2009.  

Other  related  industries  include  those  involved  in  the  processing  of  the  feedstocks, 
particularly  oil  crops  into  vegetable  oils  before  they  are  chemically  treated  to  produce  the 
final biodiesel product. In this context, there are some 150 oil crops processing and vegetable 
oils and fats production facilities across Europe, for which the trade in biodiesel products will 
be one of their major markets. Of a total of 13Mt of vegetable oil being pressed in the EU in 
2008,  the  main  producing  country  was  Germany  (4Mt),  followed  by  France  (1.9Mt),  the 
Netherlands  (1Mt),  Spain  (1Mt)  and  UK  (0.8Mt).  The  main  vegetable  oils  being  produced 
were rapeseed oil (8Mt), followed by soya oil (2.5Mt) and sunflower oil (2Mt)53. Full datasets 
for all Member States can be found in Annex IX.  

2.8.1.5.  Deployment of biofuels  

There is some uncertainty regarding how much biofuel can be blended with petrol and diesel, 
while  maintaining  associated  warrantees  from  car  manufactures.  Based  on  the  biofuel 
volumes estimated by Member States for 2020, it seems that, in volume terms, blends beyond 
10% for diesel (currently at 7%) and around 15% for petrol (currently at 10%) will be needed 
to  achieve  the  Renewable  Energy  targets  EU-wide54.  This  is  an  important  issue  due  to  the 
long lead-times both in changing specification of car engines, the slow turnover of cars, and 
the  long  lead-time  needed  for  changing  fuel  specifications.  The  use  of  various  fuels  as 

50 

51 
52 

53 
54 

Although the model does not differentiate between commodities according to their market uses, imports 
of these feedstocks are attributed to the additional demand from biofuels. 
Source European Biodiesel Board. Units adjusted to Mtoe. 
Source Epure. Part of the installed bioethanol capacity quoted here is not only destined to the biofuel 
markets.Units adjusted to Mtoe.  
Statistics from Fediol's website at www.fediol.be. 
JEC Reference scenario: http://ies.jrc.ec.europa.eu/uploads/jec/JEC%20Biofuels%20Programme.pdf.  

EN 

21 

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estimated by JEC (JRC/EUCAR/Concawe) towards 2020, taking the turnover of vehicles into 
account, is shown in the figure below55. 

Energy demand by fuel type in road transport sector

]
e
o
t
M

[
d
n
a
m
e
d

l
e
u
f
d
a
o
R

350

300

250

200

150

100

50

0

Electricity

Biofuel

LPG to HD

LPG to LD

CNG to HD

CNG to LD

Diesel to HD

Diesel to LD

Gasoline to LD

2005

2010

2015

2020

Figure 5: Energy demand by fuel type in road transport towards 2020 (source: JEC) Heavy duty and light 
duty vehicles are referred to as HD and LD 

The  use  of  petrol  is  expected  to  decline,  while  the  use  of  diesel  increases.  With  regard  to 
biodiesel blends, work is currently underway to develop standards for B10 for cars and B30 
for heavy duty engines.  There  are also a number of plants currently  producing hydrotreated 
vegetable oils, which can be used at any blending levels. However, the latter fuel is likely to 
be  in  demand  from  the  aviation  sector,  which  may  limit  the  supply  available  to  the  road 
transport sector.  

In the case of bioethanol, the situation remains more challenging as the petrol/diesel split is 
estimated to increase in favour of diesel cars towards 2020, and in addition bioethanol has a 
lower energy content. Work on bioethanol blend standards is ongoing. While manufacturers 
can produce vehicles that are compliant with EU emission standards at petrol and bioethanol 
blends  up  to  95%,  the  sales  of  these  vehicles  are  low  in  the  EU.  Certain  countries  such  as 
Brazil and Sweden have shown that vehicles can readily be built to be compatible with higher 
levels of oxygenates and alcohols at a low additional cost (around 100€ pe r vehicle or lower). 
It is also possible to convert heavy duty vehicles to run on bioethanol.  

In  terms  of  current  supply  infrastructure  available  for  E85  in  the  EU,  total  sales  were 
estimated to be about 100 ktoe in 200856. Sweden had by far the most selling points for E85, 
with  1300,  followed  by  France  with  320  and  Germany  (100).  The  UK,  Ireland,  Hungary, 
Norway,  Spain  and  the  Netherlands  had  fewer  than  20  stations  in  2008.  The  situation  in 
Sweden seems to be driven by current incentives which include reduced registration charges 
and  road  taxes,  free  parking  in  some  cities  and  waived  congestion  charges  for  flexi-fuel 
vehicles57. 

55 
56 

57 

EN 

The study can be found here: http://ies.jrc.ec.europa.eu/about-jec.  
On the basis of extrapolation of the known sales in Germany (where the 100 filling stations selling E85 
– 5% of the European total of such filling stations – sold about 5.5 ktoe of the fuel. 
EC 
report 
http://ec.europa.eu/energy/renewables/reports/doc/sec_2011_0130.pdf. 

available 

progress 

2010 

RES 

at      

22 

   EN 

 
 
 
 
 
 
                                                 
Biofuels  may  also  be  employed  in  the  shipping  and  aviation  sectors.  In  terms  of  blending 
requirements, they have opposite features; most ships can run on most hydrocarbons, but the 
safety  requirements  for  aviation  are  strict  and  only  certain  types  of  biofuels  can  be  used. 
Three  types  of  biofuels  are  favoured  to  be  used  in  aviation  engines,  when  blended  with 
kerosene:  Synthetic  Fischer-Tropsch  (FT)  based  kerosene,  Hydrogenated  Vegetable  Oils 
(HVO)  and  Hydrogenated  Pyrolysis  Oils  (HPO)  produced  from  lignocellulosic  biomass.  At 
the moment only HVO is available, but the two other biofuels are expected to be available by 
2020.  So  far  no  targets  have  been  established  for  either  the  shipping  or  aviation  sector. 
However, the aviation sector aims to use around 2Mtoe of biofuels by 2020.  

2.8.2. 

Indirect land-use change greenhouse gas emissions assumed in the baseline 

The evaluation of the policy options requires a baseline scenario that the policy options can be 
compared against. As discussed in section 2.3, indirect land-use change can only be estimated 
through  modelling,  and  the  Commission  has  taken  the  view  that  although  a  number  of 
limitations  and  uncertainties  remain,  the  IFPRI-MIRAGE-BioF  is  considered  to  be  the  best 
available  estimation  of  the  baseline.  Further  results  as  well  as  the  key  assumptions  of  the 
IFPRI-MIRAGE-BioF model are summarised in Annex V. 

The  ATLASS  consortium  has,  since  the  publication  of  the  Commission  report  on  indirect 
land-use change last year, conducted more analysis. The latest results provide an estimate of 
overall land-use change emissions based on the additional 2020 biofuel volumes estimated by 
the  Member  States  compared  to  200858.  However,  it  is  important  to  note  that  since  the 
modelling  assumes  that  the  sustainability  criteria  have  no  effect,  the  baseline  assumes 
consumption of some biofuels that might not meet the greenhouse gas savings and the land-
use criteria in 2020. 

It is also worth noting that no further implementation of LULUCF accounting in the run up to 
2020 is assumed in the model. However, if complete accounting for land-use, land-use change 
and forestry, in the framework of a system of global emissions targets was implemented, this 
would send price signals providing disincentives for such conversions. As described in more 
detail in section 2.5.3 a move towards including LULUCF in the EU's GHG reduction target 
can only be considered once Member States have implemented the accounting framework and 
it  has  proven  to  be  robust  within  the  EU.  Other  initiatives,  such  as  the  moratorium  for 
peatland  and  primary  forests  agreed  between  Norway  and  Indonesia,  in  the  context  of 
REDD+, might also impact on indirect land-use change emissions59. Such agreements are not 
reflected in the modelling. 

2.8.2.1.  Total estimated indirect land-use change impacts 

IFPRI-MIRAGE-BioF estimates the indirect land-use change emissions from 2008 to 2020 to 
amount  to  around  500  Mt  of  CO2eq.  These  emissions  are  equally  divided  between  peatland 
emissions (in South East Asia), losses of biomass below ground, and changes in above ground 
biomass.  Emissions  from  peat  conversion  have  a  larger  impact  on  the  overall  emissions 
attributed  to  oil  crops,  particularly  for  palm  oil,  than  for  bioethanol  crops.  The  range  of 

58 

59 

EN 

In  their  modelling,  it  was  assumed  that  half  of  those  biofuels  double  counted  under  the  RED  were 
considered  to  come  from  waste  and  residues,  having  no  ILUC  impact,  whereas  the  other  half  was 
modelled as increased bioethanol demand.  
here: 
See 
http://www.regjeringen.no/upload/MD/2011/vedlegg/klima/klima_skogprosjektet/Press_Release_Inpres
_Mo_atorium_ENG.pdf.  

release 

press 

23 

   EN 

 
                                                 
estimated indirect  land-use change emissions is 24 g/MJ to 50 g/MJ, with an average of 38 
gram CO2eq/MJ based on the assumed biofuel mix. This estimate of indirect land-use change 
emissions is based on conversion of around 1.7 Mha of land, which is taking place in a range 
of regions globally, mostly in Brazil and the Commonwealth of Independent States (CIS).  

With regard to the  estimated biodiversity impacts, IFPRI-MIRAGE-BioF  study showed  that 
this  new  cropland  is  taken  from  pasture  (42%),  managed  forest  (39%),  primary  forest  (3%) 
and  savannah  and  grassland  (16%),  which  will  have  biodiversity  and  wider  environmental 
impacts. A qualitative estimation of these impacts made by the JRC using the Mean Species 
Abundance  (MSA)  values  provided  by  the  Global  Biodiversity  Model  (GLOBIO  3)60,61, 
shows  that  the  largest  biodiversity  losses  will  be  associated  with  the  conversion  of  primary 
forest,  and  savannah  and  grassland  (both  at  100%  MSA),  pasture  land  (70%  MSA)  and 
managed  forest  (50%  MSA)  in  order  of  decreasing  significance.  Cultivated  and  managed 
areas  receive  a  score  of  10%  MSA  under  the  same  classification62.  Please  see  Annex  X  for 
more detail. 

Forest 
managed 

Forest 
primary 

Pasture 

Savannah 
Grassland 

Other 

TOTAL 

Brazil 

3% 

1% 

10% 

3% 

0% 

18% 

Central 
America 
and 
Caribbean 

China 

CIS 

EU27 

Indonesia 
and 
Malaysia 

Latin 
America  

Rest  of  the 
OECD 

Rest  of  the 
World  

0% 

6% 

11% 

4% 

5% 

3% 

1% 

4% 

0% 

0% 

0% 

0% 

0% 

1% 

0% 

0% 

1% 

2% 

9% 

1% 

2% 

1% 

1% 

4% 

0% 

0% 

3% 

2% 

0% 

4% 

1% 

1% 

0% 

0% 

0% 

0% 

0% 

0% 

0% 

0% 

1% 

8% 

23% 

7% 

7% 

9% 

3% 

9% 

60 

61 

62 

GLOBIO  3  is  developed  by  a  consortium  made  up  of  UNEP  world  Conservation  Monitoring  Centre 
(WCMC), UNEP/GRID-Arendal and the Netherlands Environmental Agency (PBL). [Alkemade et al, 
2009]. 
Biodiversity is described in GLOBIO3 on the basis of the remaining mean species abundance (MSA) of 
original species, relative to their abundance in pristine or primary vegetation, which are assumed to be 
not disturbed by human activities for a prolonged period. MSA is therefore considered as the indicator 
for biodiversity. 
For  example,  according  to  the  MSA  values  in  the  table, a  transition from  pastureland (MSA 70%)  to 
cropland  (MSA  10%)  will  cause  a  loss  of  60%  of  MSA  on  top  of  the  30%  already  lost  from  the 
conversion from natural land to pastureland. 

EN 

24 

   EN 

 
 
                                                 
Sub-
Saharan 
Africa  

USA 

TOTAL 

1% 

1% 

39% 

0% 

0% 

3% 

11% 

0% 

42% 

1% 

1% 

17% 

0% 

0% 

0% 

13% 

2% 

100% 

Table 3: Percentage land converted by type and world region. Source: IFPRI-MIRAGE-BioF 

2.8.2.2.  Estimated indirect land-use change impacts by feedstock 

The  overall  estimated  indirect  land-use  change  emission  impact  is  the  aggregate  of  a  set  of 
sub-results,  such  as  country  of  origin  and  feedstock.  It  is  therefore  relevant  to  present  the 
crop-specific  indirect  land-use  change  emission  estimates,  as  these  are  components  of  the 
overall baseline impact. The IFPRI-MIRAGE-BioF model has recently been combined with a 
Monte Carlo simulation, to provide a better description of the probability distribution of the 
uncertainty associated with the variables. More information on this analysis can be found in 
Annex XI.  

Figure 6: Results of the Monte-Carlo analysis: estimated indirect land-use change emissions (gCO2/MJ)- 
under scenario of current trade policy. The bars indicate 1st and 99th percentile, while the boxes are 25th 
and 75th percentiles.  

It is important to note that these crop specific values are estimated based on the increase of 
biofuel consumption towards 2020 compared to the existing consumption in 2008. They are 
therefore not representative for the around 10 Mtoe already consumed in 2008. Indeed, it is 
pointed out that for rapeseed, which is the most important feedstock used in 2008 (5.7 Mtoe 
out of a total of 10 Mtoe), the average land-use change is significantly lower in the baseline.  

EN 

25 

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With  regard  to  the  values  for  cereal  crops,  it  should  also  be  born  in  mind  that  some  of  the 
assumptions  on  the  yields  of  EU  wheat  and  US/Brazil  maize  are  considered  strongly 
optimistic. Although these assumptions can significantly influence the estimated indirect land-
use  change  emissions  for  these  crops,  they  have  not  been  included  in  the  Monte  Carlo 
analysis.  

2.8.2.3.  Establishing a greenhouse gas emissions baseline for biofuels in 2020  

In  order  to  establish  a  greenhouse  gas  emissions  baseline  for  biofuels,  it  is  necessary  to 
compare the estimated indirect land-use change emissions to the expected direct greenhouse 
gas savings from substituting fossil fuels in 2020. In this context, assumptions regarding the 
expected  improvements  in  greenhouse  gas  emissions  performance  of  biofuels,  as  well  as 
changes in the carbon intensity of fossil fuels to 2020 need to be made.  

With  regard  to  the  expected  improvements  in  greenhouse  gas  emissions  performance  of 
biofuels towards 2020, COWI63 estimated how various feedstocks would develop. However, 
those values do not take into account more recent developments (such as the ETS proposals 
for ammonia and nitric acid plants in EU), and do not cover improvements for all feedstocks. 
As such, these have been adjusted by JRC to allow for comparison across all biofuels64. The 
results combined with the estimated indirect land-use change emissions are summarised in the 
table below65.  

Average estimated 
ILUC emissions 

Direct 
emission 
savings  

Total 
emissions 

Maize 

Sugar beet 

Sugar cane 

Wheat - Not specified 

Wheat - Natural gas/CHP 

Wheat - Straw/CHP 

Waste/2nd generation bioethanol - land using 

Waste/2nd  generation  bioethanol  -  non-land 

Waste/2nd generation biodiesel - land using 

Waste/2nd generation biodiesel- non-land using 

Palm oil 

10 

7 

15 

14 

14 

14 

15 

0 

15 

0 

54 

-57 

-63 

-70 

-40 

-56 

-68 

-73 

-81 

-85 

-81 

-39 

-47 

-56 

-54 

-26 

-43 

-55 

-58 

-81 

-69 

-81 

15 

63 

64 
65 

to 

promote 

schemes 

See  details  on  assumptions  in  chapter  2.2  of  the  report:  Technical  assistance  for  an  evaluation  of 
international 
(2009) 
http://ec.europa.eu/energy/renewables/bioenergy/sustainability_criteria_en.htm.  
The fossil fuel comparator for biofuels in 2020 has also been estimated. Please see Annex VI. 
Values  that  were  not  included  in  the  COWI  set  are  based  on  the  typical  values  in  the  Directives, 
however, improved with the same percentage as other bioethanol fuels or biodiesel fuels respectively. 
Although  the  specific  indirect  land-use  change  emissions  associated  with  typical  land  using  second 
generation biofuels were not modelled, these are assumed to be at the same level as for sugarcane in the 
assessment of the options (i.e. high yielding crops with no land saving co-products).  

sustainability 

biomass 

EN 

26 

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Palm oil with methane capture 

Rapeseed 

Soybean 

Sunflower 

54 

55 

56 

54 

-61 

-50 

-43 

-58 

-7 

5 

13 

-4 

 Table  4:  Typical  annual  direct  savings  compared  to  estimated  indirect  land-use  change  emissions  per 
crop (gCO2/MJ). Source: ATLASS (2011), COWI and Commission's calculations  

2.8.2.4.  Sensitivity of the baseline scenario 

The uncertainty of estimating indirect land-use change implies that several sensitivities should 
be investigated. In the assessment of the options, sensitivity analysis is limited to the changes 
of the assessment of the efficiency of the different options by the range of estimated indirect 
land-use change impacts (5th and 95th percentiles) from the Monte Carlo analysis (see figure 
6).  With  regard  to  the  average  estimated  indirect  land-use  change  emissions  at  38  g/MJ 
respectively, the 5th and the 95th percentile values of the distribution are a range of 24 g/MJ to 
50 g/MJ66.  

2.9. 

The right to act  

Articles 19(6) and 7d(6) of the Directives particularly require the Commission to address the 
issue of indirect land-use change, as explained in Chapter 1. The overall objective of the Fuel 
Quality and Renewable Energy Directives is to contribute to the goal of reducing economy-
wide greenhouse gas emissions through the promotion of renewable energy sources. As a way 
to  achieve  that,  they  create  an  EU-wide  fuel  market  and  market  for  renewable  energy,  the 
Member  States  per  se  are  not  able  to  meet  these  challenges  individually  for  the  following 
reasons:  

• 

• 

the sustainability criteria of the Directives have their legal basis in Article 114 of the 
Treaty:  internal  market.  The  indirect  land-use  change  impacts  necessarily  have 
transnational  aspects  which  cannot  be  dealt  with  satisfactorily  by  Member  States, 
when  the  EU  wants  to  establish  a  functional  EU-wide  market  for  biofuels.  Since 
there will also be international trade in biofuels with countries outside the EU, this 
can also not be properly regulated at Member State level. 

it has to be considered whether and how the objectives could be better achieved by 
action on the part of the EU: the “test of European added value”. The rationale for 
European action in the field of biofuels has already been decided with the adoption 
of  the  Fuel  Quality  and  Renewable  Energy  Directives.  This  stems  from  the 
transnational nature of the identified problem and the desire to create a single market 
in renewable and lower greenhouse gas intensity energies for transport.  

For these reasons, the policy objectives set out in section 3 of the present Impact Assessment 
report cannot be sufficiently achieved by actions of the Member States alone, but have to be 
coordinated and harmonised across the EU.  

66 

It is also worth noting that average emissions reached 116g/MJ under an extreme scenario not included 
in the sensitivity analysis where the increased demand for biofuels did not lead to either yield increases, 
food consumption reductions or intermediate consumption of agro-foods compared to the baseline.  

EN 

27 

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2.9.1.  Precautionary principle 

Article 191(2) of the Treaty states that EU policy on the environment shall be based on the 
precautionary principle. In view of this, the Commission noted in its December 2010 report 
on indirect land-use change that action should be based on the precautionary approach. 

EN 

28 

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3. 

SECTION: POLICY OBJECTIVES 

As explained in more detail in section 2.1, the Directives contain a number of sustainability 
criteria  which  are  aimed  at  preventing  direct  land-use  change  of  areas  of  high  carbon  stock 
and  high  biodiversity  value  for  the  production  of  biofuels,  as  well  as  setting  minimum 
greenhouse gas emission savings compared to fossil fuels67. Although the current greenhouse 
gas  emissions  performance  methodology  takes  account  of  emissions  associated  with  direct 
land-use  change,  as  well  as  emissions  coming  from  the  production  of  biofuels,  it  does  not 
include emissions from indirect land-use change.  

In response to the requirement for the Commission to review the impact of indirect land-use 
change on greenhouse gas emissions and to propose ways to minimise them if appropriate68, 
the  Commission  published  a  report69  in  December  2010  which  (i)  identified  a  number  of 
uncertainties and limitations associated with the available numerical models used to quantify 
indirect  land-use  change;  (ii)  acknowledged  that  indirect  land-use  change  can  reduce 
greenhouse gas emissions savings associated with biofuels; and (iii) indicated that if action is 
required,  indirect  land-use  change  should  be  addressed  under  a  precautionary  approach.  In 
view of the above, the fundamental policy objective for the Commission's continued work on 
indirect  land-use  change  is  to  provide  a  full  response  to  the  request  laid  down  in  the 
Directives70: 

The  Commission  shall,  by  31  December  2010,  submit  a  report  to  the  European  Parliament 
and  to  the  Council  reviewing  the  impact  of  indirect  land-use  change  on  greenhouse  gas 
emissions and addressing ways to minimise that impact. The report shall, if appropriate, be 
accompanied,  by  a  proposal,  based  on  the  best  available  scientific  evidence,  containing  a 
concrete methodology for emissions from carbon stock changes caused by indirect land-use 
changes, ensuring compliance with this Directive, in particular Article 17(2). 

Such  a  proposal  shall  include  the  necessary  safeguards  to  provide  certainty  for  investment 
undertaken  before  that  methodology  is  applied.  With  respect  to  installations  that  produced 
biofuels  before  the  end  of  2013,  the  application  of  the  measures  referred  to  in  the  first 
subparagraph  shall  not,  until  31  December  2017,  lead  to  biofuels  produced  by  those 
installations  being  deemed  to  have  failed  to  comply  with  the  sustainability  requirements  of 
this  Directive  if  they  would  otherwise  have  done  so,  provided  that  those  biofuels  achieve  a 
greenhouse  gas  emission  saving  of  at  least  45  %.  This  shall  apply  to  the  capacities  of  the 
installations of biofuels at the end of 2012. 

The  Articles  and  the  corresponding  recitals71  allude  to  the  development  of  a  calculation 
methodology for capturing indirect land-use change emissions. However, due to the right of 
initiative, the Commission wishes to consider other options which the Commission believes 
can  also  meet  the  policy  objectives  in  a  suitable  way.  The  Commission  evaluates  four 
different options in this Impact Assessment, as laid down in chapter 4; "Policy Options". 

To  enable  the  assessment  of  the  options,  it  is  desirable  to  understand  the  general  policy 
objectives and narrow these down to a description of more specific, operational objectives. 

67 
68 
69 
70 
71 

This requirement is progressive as it increases to 50% in 2017 and 60% in 2018 for new installations. 
Article 7d(6) of Directive 2009/30/EC and Article 19(6) of Directive 2009/28/EC. 
COM(2010) 811. 
Article 19(6) of the Renewable Energy Directive and Article 7(d)6 of the Fuel Quality Directive.  
Recital 85 of the Renewable Energy Directive and Recital 22 of the Fuel Quality Directive.  

EN 

29 

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3.1. 

Treaty based general objectives 

The EU's policies on the promotion of the use of biofuels have always been developed in the 
context  of  EU  energy  policy  and  EU  policy  aimed  at  protection  of  the  environment.  The 
development of new and renewable forms of energy is specifically foreseen as an objective in 
the Treaty and it is clear that this goal is pursued with regard to the need to enhance security 
of energy supply and that of preserving and improving the environment. The Treaty foresees 
that environmental protection must be built into all policy areas and action to reduce climate 
change is specifically foreseen within the Treaty as an environmental objective. 

The  provisions  on  sustainability  criteria,  including  the  requirement  to  analyse  indirect  land-
use  change  emissions,  are  based  on  the  functioning  of  the  internal  market  provisions  of  the 
Treaty.  Any  legislative  proposal  that  addresses  indirect  land-use  change  emissions  must 
therefore also be based on these provisions. 

3.2. 

General objectives 

The  general  objectives  are  those  of  the  Directives.  In  context  of  the  Renewable  Energy 
Directive,  Recital  65  summarises  the  general  environmental  objective  related  to  the  use  of 
biofuels: 

Biofuel  production  should  be  sustainable.  Biofuels  used  for  compliance  with  the 
targets  laid  down  in  this  Directive,  and  those  that  benefit  from  national  support 
schemes, should therefore be required to fulfil sustainability criteria. 

The content of Recital 65 is reflected in Article 17 of the Directive, which requires biofuels to 
be  sustainable,  and  in  particular  Article  17(2)  thereof,  which  in  context  of  greenhouse  gas 
savings requires biofuels to save at least 35% compared to fossil fuels, increasing to 50% in 
2017 and 60% in 2018 for new installations. 

The objectives of the Fuel Quality Directive in relation to the use of biofuels are reflected in 
Recitals 9 and 10: 

Biofuel  production  should  be  sustainable.  Biofuels  used  for  compliance  with  the 
greenhouse  gas  reduction  targets  laid  down  in  this  Directive  should  therefore  be 
required to fulfil sustainability criteria.(…). 

Suppliers should, by 31 December 2020, gradually reduce life cycle greenhouse gas 
emissions  by  up  to  10  %  per  unit  of  energy  from  fuel  and  energy  supplied.  This 
reduction should amount to at least 6 % by 31 December 2020, compared to the EU-
average  level  of  life  cycle  greenhouse  gas  emissions  per  unit  of  energy  from  fossil 
fuels in 2010, obtained through the use of biofuels, alternative fuels and reductions 
in flaring and venting at production sites.(…). 

Recital 4 is reflected in Article 7b, which sets identical sustainability requirements as Article 
17 of the Renewable Energy Directive. Recital 10 is reflected in article 7a which states that 
Member  States  shall  require  fuel  suppliers  to  reduce  as  gradually  as  possible  life  cycle72 

72 

The Fuel Quality Directive defines "life cycle greenhouse gas emissions" as the net emissions of CO2, 
CH4 and N2O that can be assigned to the fuel, included any blended components, or energy supplied. 
This  includes  all  relevant  stages  from  extraction  or  cultivation,  including  land-use  changes,  transport 
and distribution, processing and  combustion,  irrespective where  those  emissions  occur  (Article  1.2  of 
the Fuel Quality Directive). 

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greenhouse gas emissions per unit of energy from fuel and energy supplied by up to 10 % by 
31 December 2020, compared with the fossil fuel baseline representing 2010.  

3.3. 

Specific and operational objectives  

As described in section 2.1, this impact assessment is focused on the specific requirement in 
the Directives related to greenhouse gas emissions from indirect land-use change and does not 
consider any wider environmental and social impacts associated with the use of biofuels. As 
such, the general objectives presented above translate into the following specific/operational 
objective to:  

Minimise  the  impact  of  indirect  land-use  change  on  greenhouse  gas  emissions  of 
biofuels, within the wider policy objectives of the targets that by 2020 at least 10% of 
transport  fuels  are  renewable  and  that  greenhouse  gas  intensity  in  road  transport 
fuels is reduced by at least 6% compared to 2010.  

The policy options will be evaluated in context of the extent to which the options fulfil this 
specific objective. 

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4. 

SECTION - POLICY OPTIONS  

4.1.  What are the possible options for achieving the policy objectives?  

Further to the option referred to in the Directives, the development of a concrete methodology 
for  emissions  from  carbon  stock  changes  caused  by  indirect  land-use  change  from  biofuels 
that could be included in the greenhouse gas calculation, the Commission wishes to consider 
the  effectiveness  of  a  number  of  options  aimed  at  minimising  indirect  land-use  change 
impacts.  The  policy  options,  including  those  initially  set  out  in  the  Commission's  report  on 
this topic adopted in December 2010, are: 

A. 

B. 

C. 

take no action for the time being, while continuing to monitor, 

increase the minimum greenhouse gas saving threshold for biofuels, 

introduce additional sustainability requirements on certain categories of biofuels, 

attribute  a  quantity  of  greenhouse  gas  emissions  to  biofuels  reflecting  the  estimated 

D. 
indirect land-use impact. 

limit the contribution from conventional biofuels to the Renewable Energy Directive 

E. 
targets to current production levels. 

4.2. 

Option A – take no action for the time being; while continuing to monitor 

This  option  refers  to  the  Commission's  bi-annual  monitoring  and  reporting  of  impacts, 
including indirect land-use change, as required by the Renewable Energy Directive73, the first 
of  which  is  due  in  2012.  The  option  also  implies  continued  monitoring  of  the  scientific 
developments related to estimating indirect land-use change emissions. 

During the latest consultation on policy options, option A was preferred by those stakeholders 
who believed that the current state of development of the models was not appropriate to base 
policy approaches upon. This included most of the industry, farmers' associations and biofuel 
producing third countries.  

4.3. 

Option B - increase the minimum greenhouse gas saving threshold for biofuels  

This  option  consists  of  increasing  the  current  minimum  greenhouse  gas  savings  thresholds 
provided in the Directives74, currently at 35% compared to average fossil fuels. According to 
the Directives, this requirement is increased to 50% in 2017, and 60% in 2018 for installations 
that started production in 2017.  

Option  B  aims  at  a)  compensating  for  the  estimated  indirect  land-use  change  emissions 
through  requiring  higher  direct  savings,  and  thereby  improving  the  overall  greenhouse  gas 
performance  of  the  biofuels  consumed  and;  b)  reducing  indirect  land-use  change  emissions 
through  raising  the  threshold  to  such  a  level  that  many  of  the  biofuels  with  estimated  large 
indirect land-use change emissions are excluded. 

73 
74 

Article 23 of 2009/28/EC. 
Article 17.2 of 2009/28/EC and Article 7b.2 of 2009/30/EC.  

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The increased level of the threshold should be achievable for a set of feedstocks, while at the 
same  time  maximizing  the  direct  greenhouse  gas  savings.  The  level  must  be  technically 
feasible for a range of feedstocks, but require improvements beyond what is required by the 
Directives today. A discussion of the exact level of the threshold is set out in chapter 5.  

This option implies changing Article 17 of the Renewable Energy Directive and Article 7b of 
the Fuel Quality Directive.  

Option B was not supported by any particular stakeholder group during the last consultation 
exercise, as stakeholders generally favoured option A or option D. 

4.4. 

Option  C  -  introduce  additional  sustainability  requirements  on  certain 
categories of biofuels 

This  policy  option  consists  of  introducing  additional  sustainability  requirements  aimed  at 
mitigating the risk of indirect land-use change emissions. As such, compliance with a number 
of additional criteria could be required at national (country) level or at project/farm level as 
detailed in sub-options C1 and C2 below. These options are very different in their approach 
and  are  therefore,  being  treated  as  two  separate  sub-options.  Both  these  options  require 
changing  Article  17  of  the  Renewable  Energy  Directive  and  Article  7b  of  the  Fuel  Quality 
Directive.  

4.4.1.  Option C1- country level actions 

Given  that  indirect  land-use  change  emission  impacts  associated  with  biofuels  manifest 
themselves through unwanted direct land-use change across countries, and often as a result of 
inadequate  land  governance,  option  C1  is  aimed  at  addressing  such  negative  effects  by 
improving land-use governance and protection of high carbon stock lands. More specifically, 
under  option  C1  biofuel  producing  countries  including  Member  States,  are  requested  to 
implement LULUCF methodology based (see chapter 2.5.3 for description) reporting (if not 
already in place) and protection of high carbon stock land. Simultaneously, efforts to increase 
the supply of biofuels with low risk of indirect land-use change emissions at a national level 
could be implemented.  

To guarantee that option C1 reduces indirect land-use change emissions completely the option 
would need to be implemented globally, thus preventing any leakage. However, indirect land-
use change emissions could be reduced and even over-compensated if the implementation of 
option  C1  is  successful,  as  it  may  reduce  indirect  land-use  change  emissions  from  other 
commodities. An example of this is provided below, where peatland emissions in Indonesia 
are halved.  

Stopping  conversion  of  peatlands  in  Indonesia  would  have  a  considerable  impact  on  the 
estimated  indirect  land-use  change  emissions  from  all  oil  crops,  as  their  production  is 
assumed by the models to cause indirect conversion of peatland (i.e. more than the third of the 
estimated indirect land-use change emissions are from peatland). Moreover, the protection of 
peatland would also limit the land-use change emissions from other agricultural commodities 
(both  directly  and  indirectly),  as  demand  for  biofuels  is  only  one  of  many  drivers  for 
increased  production  of  vegetable  oils  globally.  Wetlands  International75  reports  that 
emissions from peatlands in Indonesia alone in 2008 amounted to 500 Mt. This implies that 
one year of emissions from peatland in Indonesia is ten times higher than the estimated annual 

75 

Wetlands International (2010). 

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33 

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indirect land-use change emissions in 2020. However, the overall effectiveness of this option 
relies on whether countries choose to comply or not, which is outside the control of the EU 
and therefore it is not possible to guarantee that the results will develop in a certain way. This 
is further analysed in chapter 5. 

During the latest consultation on policy options, most of the industry and farmers' associations 
supported  the  use  of  international  action  to  address  indirect  land-use  change  emissions, 
although not necessarily in the same terms as outlined in this sub-option.  

4.4.2.  Option C2- project level actions 

This sub-option refers to practices that could prevent indirect land-use change by producing 
feedstocks without the need for additional land. Potential mitigation measures would include: 

(a) 

(b) 

(c) 

Using  land  without  provisioning  services76  that  would  be  unlikely  to  be  taken  into 
production in the absence of biofuel demand (i.e. typically land that either requires 
some  form  of  remediation  prior  to  being  used  or  where  significant  barriers  exist). 
Expanding  production  on  unused  land  may  lead  to  direct  land-use  change,  but  the 
latter would be addressed by the current sustainability criteria and therefore directed 
to those areas where effects are acceptable. 

Increasing  yields  above  projected  future  trends  which  would  not  have  happened  in 
the  absence  of  biofuel  demand.  This  could  lead  to  the  production  of  biofuel 
feedstocks  without  increasing  the  pressure  on  land  and  therefore  limiting  indirect 
land-use  change  emissions.  In  this  case,  only  the  additional  feedstock  production 
should be considered as meeting this requirement.  

Integrating biofuels and non-bioenergy production systems (i.e. land-used for cattle 
farming)  in  ways  that  lead  to  a  higher  overall  land  productivity.  Again  this 
integration would be additional to what would have happened in the absence of the 
biofuel demand. 

In order for indirect land-use change to be prevented, it would also be necessary to ensure that 
the  actions  put  in  place  are  additional  and  that  would  not  have  been  implemented  in  the 
absence of these criteria. Both the reporting and verification processes could be foreseen to be 
incorporated  into  the  existing  reporting  and  verification  systems  established  under  the 
sustainability scheme, which already requires the collection of detailed information across the 
supply  chain  by  economic  operators  or  managers  of  sustainability  schemes  on  land-use  and 
cultivation  practices  in  order  to  demonstrate  compliance77.  In  addition,  the  process  for 
verification would require that an assessment at project level is carried out before the project 
is approved, although it would seem reasonable to assume that additionality would only need 
to be proven once within the legislative period.  

The  literature78  indicates  that  the  potential  for  producing  biofuels  in  this  way  is  significant, 
and that the share of non-EU crops would increase if this option was to be implemented (i.e. 

76 

77 

78 

EN 

The  Millennium  Ecosystem  Assessment  distinguishes  four  categories  of  ecosystem  services: 
provisioning  services,  regulation  services,  cultural  services  and  supporting  services.  Provisioning 
services are defined as harvestable goods such as fish, timber, bush meat, genetic material, etc. 
can 
Further 
http://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:C:2010:160:0008:0016:EN:PDF. 
Please see description of this option under Annex XII for further detail. 

found 

detail 

be 

at 

34 

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sugarcane, soy and palm oil) as opportunities for intensification seem to be greater in certain 
world regions (i.e. Brazil, South East Asia).  

The full details for implementing these criteria would need to be developed at a later date. A 
more  detailed  description  of  these  measures  as  well  as  a  summary  of  their  potential  can  be 
found in Annex XII. 

Most NGOs supported sub-option C2 during the last consultation in combination with option 
D. The rationale behind this approach is that biofuels produced under the conditions outlined 
above, would in theory mitigate the risk that their production would trigger indirect land-use 
change. Option D was by these stakeholders believed to be a strong incentive for the actions 
described  under  sub-option  C2  to  be  implemented,  which  in  some  cases  would  require 
significant changes in current production practices.  

4.5. 

Option  D  -  attribute  a  quantity  of  greenhouse  gas  emissions  to  biofuels 
reflecting the estimated indirect land-use impact. 

This is the option referred to in the Directives, which would require incorporating estimated 
indirect  land-use  change  emissions  values  in  the  reporting  of  existing  greenhouse  gas 
methodology79,80, including ensuring compliance with minimum greenhouse gas thresholds81. 
A  new  Annex  VIII  would  need  to  be  added  to  the  Renewable  Energy  Directive  and  a  new 
Annex V to the Fuel Quality Directive.  

This option implies incorporating the estimated indirect land-use change emissions of biofuels 
into the emission calculation. However, there are a number of issues that need to be described, 
as  the  use  of  a  factor  may  not  be  appropriate  in  some  circumstances  (i.e.  non-land  using 
feedstocks such as algae).  

These various elements are set out below: 

• 

• 

79 
80 

81 

Evaluate the introduction of different estimates of factors (eiluc) into the greenhouse 
gas  calculation  representing  the  estimated  indirect  land-use  change  greenhouse  gas 
emissions  and  taking  into  account  the  results  of  the  Monte  Carlo  analysis  from  the 
IFPRI-MIRAGE-BioF.  

Define  the  situations  where  eiluc  should  have  a  value  of  zero  because  there  is  no 
displacement of agricultural activity. This is likely to be appropriate for the following 
circumstances, 

i.)  Waste and residual materials are used as feedstocks. 

ii.)  The feedstock does not require land for its production (i.e. algae). 

iii.)  The production of the feedstock has led to 'direct land-use change', and as such 
an  el  value  has  been  calculated  in  accordance  to  greenhouse  gas  emissions 
methodology.  

Annex V C of 2009/28/EC and Annex IV C of 2009/30/EC. 
Member  States  are  required  to  report  the  greenhouse  gas  emissions  savings  from  biofuels  under  the 
general  reporting  requirements  set  by  Article  22  of  the  Renewable  Energy  Directive  and  for 
demonstrating compliance with the greenhouse gas emissions reduction target set by Article 7a of the 
Fuel Quality Directive.  
The minimum greenhouse gas savings threshold is 35%, raising to 50% in 2017. 

EN 

35 

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When assessing this option, consideration will be given at setting the indirect land-use change 
emission  factors  eiluc  at  levels  which  mitigate/anticipate  the  risk  of  a  possible  model  i) 
overestimation  (50%,  25%,  5%  percentiles)  and  ii)  underestimation  (50%,  75%,  95% 
percentiles)  of  crop-specific  indirect  land-use  change  factors.  In  addition,  consideration  will 
be given to the degree of disaggregation these factors should be set at (i.e. feedstock specific 
or crop group level i.e. oil crops, sugars and cereals). 

As  with  the  current  methodology  for  default  greenhouse  gas  emissions  values,  it  would  be 
required to consider whether a review process82 needs to be established within the Directives 
for updating these values. Consideration will be given as to whether safeguards for investment 
from  the  introduction  of  this  particular  option,  as  stated  in  the  Directives83,  should  be 
introduced.  

Most  NGOs  and  a  few  industrial  stakeholders  from  the  non-biofuel  sectors  supported  this 
option  during  the  last  consultation.  This  was  also  the  most  supported  option  during  the 
international scientific expert workshop with academics and experts organised by the JRC in 
November 2010.  

4.6. 

Option E - Limit the contribution from conventional biofuels to the Renewable 
Energy Directive targets. 

This option aims at minimising the indirect land use change impacts of biofuels by limiting 
the  amount  of  conventional  biofuels  that  can  be  counted  towards  the  Renewable  Energy 
Directive targets to current production levels. The risk of indirect land use change is mostly 
associated with conventional biofuel feedstocks grown on high yielding agricultural land. To 
limit  the  consumption  of  such  biofuels  therefore  also  limits  the  risk  of  indirect  land-use 
change emissions. Moreover, such a limit will require that the remaining amount of biofuels 
needed to achieve the 10% Renewable Energy Directive transport target would need to come 
from  advanced  biofuels  with  lower  indirect  land  use  change  risks,  which  will  significantly 
improve the biofuel mix that can be expected in 2020.  

This option implies changing Article 3 of the Renewable Energy Directive.  

Although Option E was not included as one of the shortlisted options by the Commission in 
the last consultation exercises, options aimed at limiting the amount of conventional biofuels 
while  increasing  the  incentives  for  advanced  biofuels  were  favoured  by  NGOs  and  certain 
industrial stakeholders. 

82 
83 

Article 19.7 of 2009/28/EC and Article 7d. 6 of 2009/30/EC.  
The  Directives  include  a  clause  that  would  mean  that  biofuels  should  not  be  regarded  as  failing  to 
comply with the sustainability criteria until 2018 (as long as they achieve 45% minimum savings when 
direct  savings  are  looked  at  and  are  produced  in  a  plant  installed  prior  to  2013),  should  such 
methodology be introduced. 

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5. 

ANALYSIS OF IMPACTS 

5.1. 

Assessment methodology 

5.1.1. 

Introduction 

The  baseline  estimated  indirect  land-use  change  greenhouse  gas  emissions  impacts  are 
outlined  in  chapter  2.  Consequently,  the  different  policy  options  assessed  here  focus  on 
potential ways of minimising these impacts. The assessment focuses on the impacts resulting 
from the potential changes in feedstock availability84 following intervention.  

The assessment of the policy options has been carried out according to their effectiveness, in 
achieving  the  policy  objectives  in  chapter  385  and  their  likely  wider  environmental, 
economic86  and  social  impacts,  as  well  as  their  consistency  with  other  EU  policies.  Further 
detail can be found in Annex XIII. 

The  particular  question  of  administrative  burden  and  associated  costs  is  addressed  to  the 
extent possible for options B and C2. In the case of option B, this is because it is not possible 
to  know  precisely  to  what  extent  certain  feedstocks  will  be  excluded  (in  which  case  there 
would  be  economic  impacts  but  no  administrative  costs)  or  the  extent  to  which  economic 
operators  would  need  to  report  actual  greenhouse  gas  emissions  values  to  meet  increased 
requirements.  With  regard  to  option  C2,  the  potential  certification  system  is  still  being 
developed  and  therefore  some  costs  from  current  pilots  are  presented  as  an  indication  only. 
Option C1 has administrative costs related to the verification of LULUCF reporting. All other 
options are considered to have insignificant additional administrative costs because they are 
all  based  on  the  current  framework  for  verifying  compliance  with  existing  sustainability 
criteria under the Directives87. 

5.1.2.  Development of scenarios  

In  most  cases,  it  is  expected  that  options  will  limit  the  availability  of  qualifying  biodiesel 
feedstocks as these typically present both higher direct and estimated indirect land-use change 
emissions.  In  order  to  compensate  for  the  reduced  availability  of  biodiesel  and  so  to  still 
achieve  the  targets  of  the  Directives,  the  contribution  from  all  the  available  Renewable 
Energy  transport  technologies  (i.e.  bioethanol,  advanced  biodiesel  and  electric  cars)  is 
increased  by  similar  amounts  to  maintain  the  5.4%  reductions  in  greenhouse  gas  intensity 
towards the Fuel Quality Directive found in the baseline. It should be stressed that this is a 

84 

85 

86 

87 

Note that "availability" refers to whether the feedstock meets the greenhouse gas saving threshold, and 
is not related to physical availability of the feedstock. 
The effectiveness criteria assesses whether policy options are minimising the greenhouse gas impact of 
biofuels,  while  ensuring  that  emissions  from  biofuels  are  below  the required  thresholds  set  out  in  the 
Directives,  as  well  as  respecting  the  greenhouse  gas  emissions  reduction  target  set  out  in  the  Fuel 
Quality Directive.  
As the level of uncertainty of the indirect land-use change emission estimates included in the baseline is 
already  high,  the  introduction  of  further  uncertain  results  through  assumptions  on  costs  gives  rise  to 
counterintuitive  results,  and  risks  of  misinformed  assessment.  The  assessment  of  costs  is  therefore 
limited to a qualitative level. 
related  guidance 
Please  see  article  7b  of  2009/30/EC,  Article  18  of  2009/28/EC  and 
(http://eurlex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:C:2010:160:0001:0007:EN:PDF). 
An 
assessment  of  the  administrative  burden  associated  with  the  current  verification  framework  can  be 
found  in  the  impact  assessment  of  the  energy  and  climate  package  (Chapter  6.7.1.5.  How  should 
performance be verified? – page 149). 

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purely theoretical exercise which does not necessarily lead to realistic results. Alternatively, 
but  not  assessed  here,  a  higher  contribution  from  the  use  of  LPG  and  venting  and  flaring 
reductions could contribute towards the carbon intensity reduction targets in the Fuel Quality 
Directive88.  

With  regard  to  the  final  biofuel  mix,  key  factors  are  expected  to  include  the  ability  of  the 
biofuel industry to improve the greenhouse gas emissions performance of pathways associated 
with  conventional  feedstocks  (i.e.  particularly  oil  crops)  in  order  to  comply  with  higher 
greenhouse  gas  emissions  standards,  and  the  ability  of  technologies  using  alternative 
feedstocks  (i.e.  non-land  using  feedstocks)  to  come  to  market  within  given  timescales.  In 
those cases where the availability of conventional biodiesel feedstocks is severely restricted, a 
number  of  car  fleet  compatibility  issues  associated  with  higher  bioethanol  blends  or  higher 
shares of certain feedstocks, such as palm oil, may arise. Further information on the current 
situation can be found in Annex XIV.  

5.1.3.  Assessment limitations  

In  order  to  appropriately  interpret  this  assessment,  the  following  limitations/simplifications 
should be born in mind;  

• 

• 

• 

• 

88 

89 

in  reality,  the  indirect  land-use  change  emissions  could  be  higher  or  lower.  As 
discussed  in  chapter  2  and  particularly  Annex  III,  there  are  still,  and  will  possibly 
always  remain,  considerable  limitations  and  uncertainties  related  to  estimating 
indirect land-use change emissions. However, given the need to analyse the issue in a 
quantitative  manner,  it  has  been  necessary  to  use  the  latest  results  from  IFPRI-
MIRAGE-BioF as the baseline.  

the  modelling  of  indirect  land-use  change  emissions  assumes  that  the  sustainability 
scheme has no effect. Still, in this assessment it is assumed that it actually reduces 
both direct emissions and indirect land-use change emissions through a reduction in 
consumption  in  the  EU  of  biofuels  from  a  particular  feedstock,  according  to  the 
estimates made by IFPRI-MIRAGE-BioF. 

although measures considered here for biofuels are also applicable to bioliquids, no 
calculations have been specifically made using their fossil fuel comparators89. This is 
not  likely  to  give  rise  to  any  leakage  issues  (i.e.  where  excluded  biofuels  may  be 
diverted to bioliquid market), as the assumed fossil fuel comparator value for 2020 
here (90.3 g/MJ) is very close to the highest value provided for bioliquids.  

the  question  of  whether  a  particular  feedstock  passes  or  not  is  a  simple  yes  or  no 
question.  However,  there  are  several  conditions  that  determine  the  greenhouse  gas 
emissions  performance  associated  with  different  feedstocks,  including  potential 
improvements in greenhouse gas emissions performance, and hence whether they can 
ultimately  meet  the  minimum  thresholds  set  out  in  the  Directives.  Moreover,  the 

In the baseline, which is based on how the MS are planning to meet the RED targets, the fulfilment of 
the  Fuel  Quality  Directive  is  -5.4%.  As  such,  it  is  therefore  assumed  that  the  remaining  contribution 
percentage point will be achieved through non-RES technologies qualifying for the FQD such as flaring 
and venting. This is uncertain and should this not be the case, even more biofuels or electric vehicles 
would be needed to meet the Fuel Quality Directive.  
See footnote 31. 

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38 

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potentially 
contaminated land greenhouse gas bonus90 is not assessed.  

increased  attractiveness  of  e.g. 

the  severely  degraded/heavily 

• 

• 

the  analysis  is  based  on  the  year  2020  (i.e.  for  analytical  purposes,  as  all  the 
assumptions  made  are  related  to  that  year).  All  indirect  land-use  change  emissions 
are  assumed  to  be  mitigated  when  action  is  taken  in  2020.  This  is  an 
oversimplification, as indirect land-use change impacts are of cumulative nature and 
irreversible  in  the  period  to  202091.  Moreover,  it  should  be  noted  that  although  the 
assessment  is  done  for  only  one  year,  the  indirect  land-use  change  emissions 
included in the greenhouse gas emissions balance of biofuels are averaged over a 20 
year period in accordance with the existing methodology in the Directives.  

some of the options result in biofuels made from certain feedstocks being unable to 
meet  the  sustainability  criteria  of  the  Directives.  The  deficit  that  this  might  lead  to 
would need to be covered by other feedstocks or means to comply with the targets. A 
range  of  factors,  such  as  costs,  technical  blending  possibilities,  technical  vehicle 
specifications  and  infrastructure  developments  influence  how  the  deficit  can  or 
cannot be covered. None of these factors have been assessed in detail in this Impact 
Assessment.  

Given all these uncertainties, it is important to bear in mind that the results presented in this 
section should be used with the utmost caution.  

5.2. 

Option A - Take no action for the time being, while continuing to monitor 

Option  A  is  the  "no  policy  change"  option,  which  implies  that  no  further  action  to  mitigate 
indirect land-use change emissions is taken, while continuing to monitor the development of 
key factors determining the indirect land-use change impact and the science needed to assess 
the scale and nature of the phenomenon.  

5.2.1.  Effectiveness in reducing greenhouse gas emissions  

The main results in terms of reducing greenhouse gas emissions are shown in the table below.  

Direct  emissions  only-  biofuels 
only 

Average emissions 2020 (g/MJ) 

Average emission savings 2020 [%] 

Total direct emissions 2020 (Mt) 

Indirect 
emissions- biofuels only 

land-use 

emissions- 

Total 
indirect- biofuels only 

direct 

change 

Average ILUC emissions 2020 [g/MJ] 

Total ILUC emissions 2020 [Mt] 

and 

Average emissions 2020 [g/MJ] 

Average savings 2020 [%] 

Change against baseline 

Indirect 

land-use  change  emissions 

Total emissions (Mt) 

Table 5: Effectiveness analysis of option A 

35

61%

42

42

48

77

15%

0

0

90 

91 

See  Annex  V  and  Annex  IV  of  the  Renewable  Energy  Directive  and  Fuel  Quality  Directive 
respectively. 
It  is  important  to  consider  the  date  of  adoption  and  the  date  by  which  it  enters  into  force,  as  both 
influence the response of economic actors. This is not taken into account. 

EN 

39 

   EN 

 
                                                 
Both direct and indirect land-use change emissions are as described in the baseline in section 
2.8, as no action is taken. Estimated indirect land-use change emissions are not reported, but 
even if they were to be included in the methodology, the average reported savings for biofuels 
compared  to  fossil  fuels  would  be  at  15%92.  Similarly,  with  regard  to  the  Fuel  Quality 
Directive target, the total emission savings offered by biofuels would be at 1.1%.  

5.2.2. 

Impacts on achieving the Renewable Energy Directive transport target 

The fulfilment of the 10% renewable energy in transport target can be met, as envisaged in the 
NREAPs,  as  neither  the  emission  reduction  thresholds  nor  the  GHG  methodology  are 
changed. 

5.2.3.  Economic impacts 

Option  A  continues  the  existing  policy  framework,  leaving  the  sustainability  scheme  as 
currently laid down in the Directives unchanged. The biofuel and related industries, as well as 
farmers  are  thus  ensured  a  stable  policy  framework,  which  enables  investor  certainty.  This 
also implies that Member States and industry can continue to follow the submitted National 
Renewable Action Plans93 (NREAPs), and the EU installed biofuel production capacity can be 
utilised.  

Security  of  supply  is  maintained  as  foreseen,  with  10%  of  the  energy  used  in  the  transport 
sector being renewable, from diversified energy sources, with about half of the total demand 
being met by domestic production and half by imported.  

Option  A  has  no  specific  implications  for  trade  policies  and  trade  relations.  Imports  of 
biofuels and biofuel feedstocks, particularly biodiesel, are expected to increase significantly. 
This  option  has  no  additional  implications  for  technological  development  and  innovation  as 
both  developments  in  greenhouse  gas  emissions  performance  and  advanced  biofuel 
production remain as planned. No additional impacts on car manufacturers with regard to the 
levels of biofuel blending required other than those described in the baseline. 

5.2.4. 

Social impacts 

EU  rural  development  and  employment  opportunities  are  not  affected  under  this  option,  as 
activities in the agricultural and industrial sectors associated with the production of biofuels in 
the EU are not affected and continue to develop as planned. An estimated 400 000 jobs could 
thus be maintained in the sector. 

The  expected  increase  in  demand  for  biodiesel  and  bioethanol  to  2020  will  increase  the 
pressure  on  global  commodity  markets,  particularly  for  vegetable  oil  as  the  EU  demand  for 
biodiesel  represents  a  more  significant  share  of  the  total  production.  As  biofuel  demand  is 
inelastic, this increased demand could impact on certain manufacturers of food, cosmetics and 
daily care products who rely on the same raw materials, particularly vegetable oils.  

Development  objectives  in  third  countries  are  difficult  to  assess,  as  such  impacts  are 
dependent on local factors. However, the current framework, which is continued under option 

92 

93 

EN 

If the sustainability criteria were assumed to have an effect (by eliminating certain feedstocks with high 
direct emissions), the emissions balance in the baseline is improved to 22%.  
All 
http://ec.europa.eu/energy/renewables/transparency_platform/action_plan_en.htm.  

NREAPs 

available 

here: 

are 

40 

   EN 

 
                                                 
A allows for  a range of crops typically grown  in developing countries to be supplied to the 
EU, as they typically fulfil the sustainability criteria.  

5.2.5.  Environmental impacts  

According to the models, the estimated additional cropland requirements globally amount to 
1.7 Mha, mainly in regions of the Commonwealth of Independent States, Sub-Saharan Africa 
and  Brazil,  and  would  be  taken  from  pasture  (42%),  managed  forest  (39%),  primary  forest 
(3%)  and  savannah  and  grassland  (16%).  The  JRC  analysis  of  the  land  cover  classification 
used  by  IFPRI-MIRAGE-BioF,  suggests  that  the  largest  biodiversity  losses  would  be 
associated  with  the  conversion  of  primary  forest,  and  savannah  and  grassland,  pasture  land 
and managed forest to cropland in order of decreasing biodiversity value94.  

Although  it  is  not  possible  to  provide  any  specific  information  on  wider  environmental 
impacts  based  on  the  model  results,  adverse  water,  soil  and  air  impacts  would  be  expected 
from the conversion of primary and managed forests, as well as the conversion of grassland.  

5.2.6.  Other impacts 

As emission savings offered by biofuels would not reflect indirect land-use change, biofuels 
would contribute less to the integrated approach for CO2 in cars95. 

5.3. 

Option B - Increase the minimum greenhouse gas saving threshold for biofuels 

Option  B  follows  the  principles  of  the  already  existing  sustainability  criteria  which  contain 
thresholds  for  minimum  greenhouse  gas  savings  from  biofuels  compared  to  fossil  fuels.  To 
raise the threshold further would exclude certain feedstocks with higher direct emissions. The 
table below illustrates how increasing the threshold affects compliance for various feedstocks. 
As  shown  in  table  4  in  chapter  2.8,  vegetable  oils  have  high  estimated  indirect  land-use 
change emissions; these are highlighted in red colour and bold letters in the table below.  

Feedstock 

l
e
s
e
i
d
o
i
B

Palm oil 

Soybean 

Rapeseed 

Sunflower 

Direct 
greenhou
se 
gas 
emission
s (2020) 

Allowe
d  with 
50% 
thresho
ld 

Allow
ed 
with 
55% 
thresh
old 

Allowe
d  with 
60% 
threshol
d 

Allo
wed 
with 
65% 
thres
hold 

Allowe
d  with 
70% 
threshol
d 

(g/MJ) 

45,4 

40,8 

36,3 

31,7 

27,2 

51,1

46,9

40,2

32,4

94 
95 

Please see Annex X for more detail. 
Commission Communication of 7.2.2007 on Results of the review of the Community Strategy to reduce 
CO2  emissions  from  passenger  cars  and  light-commercial  vehicles  COM(2007)19,  proposed  a  CO2 
goal of 130g/km for passenger cars, together with a "further reduction of 10g CO2/km, or equivalent if 
technically necessary, by other technological improvements and by an increased use of biofuels. This 
would  need  to  be  measurable,  monitorable,  accountable  and  non-double-counting  the  reductions  of 
CO2."  

EN 

41 

   EN 

 
 
  
 
 
 
 
 
 
 
 
 
                                                 
 
 
Palm oil with methane capture 

2G biodiesel - non-land using 

2G biodiesel - land using 

Wheat - Process fuel not specified 

Wheat - Natural  gas  as process  fuel  in 

Corn (maize) 

Sugar beet 

Sugar cane 

Wheat  -  Straw  as  process  fuel  in  CHP 
plant 

2G bioethanol - land using 

2G bioethanol - non-land using 

l
o
n
a
h
t
e
o
i
B

29,3

9,3

5,4

50,3

33,5

32,7

27,1

20,2

21,6 

16,7

9,0 

Table 6: Direct emissions are shown in the first column, the allowed direct emissions as a function of the 
threshold is shown in the second row (in bold). The colouring is indicating whether the feedstock named in 
the left column achieves the threshold indicated in first row. Grey colour indicates that the feedstock is not 
reaching the threshold (however, the feedstock could be in compliance by improving performance by less 
than 5 g/MJ), while red/dark grey colour means that the feedstock is below the threshold by more than 5 
g/MJ.  

5.3.1.  Level of threshold  

It should be noted that these figures are estimates for 2020, and represent typical values, and 
not default values96. From the table it can be observed that certain types of wheat bioethanol, 
palm oil biodiesel and soy bean biodiesel have difficulties achieving 50% savings. No further 
changes are occurring when the threshold is raised from 50% to 55%, but rapeseed97 is likely 
to  be  excluded  when  the  threshold  reaches  60%.  At  65%  corn  bioethanol,  wheat  bioethanol 
produced with natural gas and sunflower biodiesel are unable to achieve the threshold, where 
only the latter has estimated high indirect land-use change emissions.  

At 70%, all vegetable oils are below the threshold of required savings, while only bioethanol 
from sugar cane and efficient wheat can be produced with sufficiently savings to be above the 
threshold. A 70% threshold thus appears to be too ambitious, if a certain variety of feedstocks 
for both bioethanol and biodiesel should be available, whereas 60% savings could be achieved 
with several feedstocks, especially if improvements and more efficient production techniques 
are implemented.  

To  increase  the  threshold  to  60%  lowers  the  direct  emissions  by  almost  10  g/MJ,  thus 
compensating  for  a  certain  amount  of  indirect  land-use  change  emissions.  But  more 
importantly  it  is  expected  to  exclude  palm  oil  without  methane  capture,  rapeseed  oil  and 
soybean oil from being used, all of which the IFPRI-MIRAGE-BioF model estimate to have 
large  indirect  land-use  change  impacts.  To  ensure  a  smooth  transition  to  higher  thresholds, 

96 
97 

See definitions of default and typical values laid down in Article 2 of the Renewable Energy Directive.  
The  crop  specific  values  are  estimated  based  on  the  increase  of  biofuel  consumption  towards  2020 
compared  to  the  existing  consumption  in  2008,  and  not  necessarily  representative  for  those  in  the 
baseline.  Indeed,  IFPRI-MIRAGE-BioF  points  out  that  for  rapeseed,  which  is  the  most  important 
feedstock  used  in  2008  (5.7  Mtoe  out  of  a  total  of  12  Mtoe  in  2020),  the  estimated  indirect  land-use 
change emissions in the baseline should be significantly lower. 

EN 

42 

   EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                                 
option  B  entails  that  the  required  minimum  savings  are  raised  already  in  2013,  to  60%  up 
from 35% today98.  

It  should  be  noted  that  in  accordance  with  the  intention  of  the  Directives  to  safeguard 
investments99 and allow time for industry to adjust, biofuels produced at plants that were in 
operation by the end of 2012 would only need to comply with a threshold of 45% until the 
end  of  2017,  at  which  point  the  60%  threshold  would  apply  also  to  those  installations.  The 
proposed level of threshold increase would exclude certain feedstocks, which will need to be 
substituted.  For  the  purpose  of  the  analysis  of  impacts  certain  assumptions  as  to  how  this 
could take place need to be made. The following section explains this in more detail. Again, it 
should be noted that the analysis has several shortcomings as explained in chapter 5.1.  

5.3.2.  Potential scenario – meeting the targets of the Directives 

A  range  of  possible  scenarios  for  how  to  achieve  the  targets  under  option  B,  can  be 
developed.  Essentially  they  imply  increasing  the  use  of  bioethanol,  advanced  biodiesel  or 
electric vehicles. A set of theoretical and extreme scenarios exploring the use of these options 
are found in Annex XIV. The least unrealistic based on contributions from other technologies 
(electric vehicles) is set out below.  

Bioethanol [Mtoe]  Double 

counted 

biodiesel [Mtoe] 

Electricity  in  road 
[Mtoe] 

Baseline 

Option B 

6.7 

13.6 

1.8

3.8

2.1 

2.7 

This would require both more (a doubling of) bioethanol blended into the vehicle fleet, and 
more  than  doubling  the  amount  of  'double-counted'  biodiesel  produced  (both  are  doubled 
compared  to  the  baseline  –  which  means  twice  the  amount  of  what  is  estimated  in  the 
NREAPs).  

The increased consumption of ethanol is a question of blending possibilities, as the share of 
petrol  consumption  in  the  EU  is  decreasing,  and  expected  to  continue  to  decline.  It  implies 
that  the  average  bioethanol  blends  in  petrol  cars  would  be  needed  to  increase  from  11%  to 
22%. The JEC Analysis of scenarios for transport in the EU towards 2020100, finds that in a 
scenario with an E85 grade (flexi-vehicles) introduced now, and E20 in 2017, the EU would 
consume  8-9  Mtoe  of  ethanol.  If  E20  is  introduced  in  2015  rather  than  in  2017  (2  years 
earlier), it leads to additional 0.7 Mtoe of ethanol being consumed in 2020. This indicates how 
challenging the consumption of 13.6 Mtoe of ethanol would be. 

The  availability  of  double-counted  biodiesel  is  a  question  of  supply,  both  in  terms  of 
availability  of  raw-material  e.g.  waste  oil,  but  also  a  technical  question  whether  enough 
production capacity can be cost-efficiently installed by 2020. Achieving a supply of 3.8 Mtoe 
of double counted biodiesel would therefore be challenging. 

98 

99 

100 

To  ensure  a  consistent  increase  of  the  level  of  ambition,  also  the  threshold  for  new  installations  is 
increased.  New  installations  after  2018  would  be  required  to  save  at  least  65%,  instead  of  currently 
planned requirement of 60%.  
Article  19(6)  and  Article  7d(6)  of  the  Renewable  Energy  Directive  and  Fuel  Quality  Directive 
respectively. 
EU  renewable  energy  targets  in  2020:  Analysis  of  scenarios  for  transport  –  JEC  biofuels  programme 
http://ies.jrc.ec.europa.eu/uploads/jec/JECBiofuels%20Report_2011_PRINT.pdf.  

EN 

43 

   EN 

 
 
                                                 
The  scenario  also  needs  0.6  Mtoe  of  additional  electricity  in  road  transport  by  2020.  This 
would be equivalent to deploying an additional 2.3 million electric cars101 by 2020 on top of 
what is foreseen in the NREAPS. The NREAPs estimate that around 2.1 Mtoe of electricity102 
is  consumed  in  electric  vehicles  in  2020,  which  implies  around  8  million  electric  cars.  It 
should be noted that 2.1 Mtoe includes plug-in hybrids, as well as other road vehicles using 
electricity.  Again,  this  means  that  this  scenario  is  not  very  likely  and  these  figures  are 
included here for illustrative purposes only.  

It  is  also  possible  that  the  increased  threshold  would  lead  to  additional  contributions  from 
other  available  technologies  in  meeting  the  Fuel  Quality  Directive  target  (i.e.  flaring  and 
venting reductions). An additional 0.5 percentage points reduction through such means, would 
reduce  the  contribution  illustrated  in  the  table  above  by  0.7  Mtoe  of  electricity  in  road 
transport (back to baseline levels) or with almost 2 Mtoe of double counting biodiesel.  

The  shortfall  could  also  be  met  by  increased  use  of  sunflower  and  palm  oil  with  methane 
capture, as both meet the threshold at 60%. However, there are technical constraints as to how 
much palm oil can be used, due to high CFPP (cold filter plugging point) properties, which 
makes  it  inappropriate  in  colder  climates.  While  this  is  true  for  FAME  and  pure  vegetable 
oils,  palm  oil  that  has  been  hydro-treated  into  HVO  (hydro-treated  vegetable  oil),  does  not 
give  rise  to  issues  with  CFPP  in  colder  climates,  but  such  fuels  are  also  expected  to  be  in 
demand from the aviation sector, as it is one of the few available biofuels that jet engines can 
use. Having regard to the expected capacity of HVO plants and the assumed amount of palm 
oil with methane capture in the baseline, it is assumed that 2.3 Mtoe of palm oil with methane 
capture is used in the EU in 2020. Although there are no technical constraints associated with 
blending  in  more  sunflower  oil,  its  volume  is  assumed  not  to  increase  and  is  maintained  at 
baseline  levels  of  1.1  Mtoe.  A  total  of  3.4  Mtoe  of  oil  crops  derived  biodiesel  is  therefore 
consumed under option B. Alternative levels of consumption of oil crops derived biodiesel is 
analysed in the sensitivity section. 

5.3.3.  Effectiveness in reducing greenhouse gas emissions  

Increasing  the  threshold  to  60%  implies  that  overall  emissions  are  reduced  by  56  Mt 
compared to the baseline. 33 Mt (70%) of the estimated indirect land-use change emissions 
occurring in the baseline would be avoided in 2020. The biofuels used are on average saving 
56%  compared  to  fossil  fuels  when  indirect  land-use  change  emissions  are  considered.  The 
emissions reported towards the Fuel Quality Directive target will not reflect estimated indirect 
land-use change emissions. 

The main results are shown in the table below.  

Direct emissions- biofuels  

Direct emissions 2020 (g/MJ)

Direct emission savings 2020 [%]

22

76%

101 

102 

Assumptions:  Electricity  consumption  of  an  electric  car  can  be  assumed  to  be  approximately  0.20 
kWh/km.  Average  annual  electric  distance  travelled  is  assumed  to  be  15.000km.  Annual  electricity 
consumption  of  one  electric  car  will  be  roughly  3000  kWh.  Expressed  in  toe,  this  is  3  *  8.6  *  10-5 
which gives 0.258 toe. Therefore 1 Mtoe electricity consumption by cars implies 3.9 million cars on the 
road. 
The NREAPs estimate a total of 0.7 Mtoe of renewable electricity in road vehicles by 2020. In order to 
convert this figure to overall electricity it has to be divided by the fraction of renewable energy in the 
electricity  mix  of  2020,  assumed  to  be  34%  for  the  EU  in  the  NREAPs.  This  gives  2.1  Mtoe  of 
electricity.  The  real  figure  is  likely  to  be  lower,  as  countries  with  higher  than  average  share  of 
renewable energy in the electricity mix, will use national values rather than the EU-average.  

EN 

44 

   EN 

 
                                                 
Indirect land-use change emissions 
– biofuels 

Average ILUC emissions 2020 [g/MJ] 

Total ILUC emissions 2020 [Mt]

Total direct emissions 2020 (Mt)

Total 
indirect- biofuels  

emissions- 

direct 

and 

Average emissions 2020 [g/MJ]

Change against baseline 

Table 7: Effectiveness analysis of option B 

Overall savings 2020 [%]

Indirect land-use change emissions (Mt) 

Total emissions (Mt)

19

18

14

40

56%

-33

-56

It should be noted that if rapeseed was to improve performance sufficiently, or the deficit of 
rapeseed was to be filled with other oil crops that pass the increased threshold (sunflower and 
palm  oil  with  methane  capture),  the  reductions  in  estimated  indirect  land-use  change 
emissions would be reduced accordingly. This analysed in the sensitivity section of option B.  

5.3.4. 

Impacts on achieving the Renewable Energy Directive transport target 

There is a risk that the transport target of the Renewable Energy Directive is not achieved, if 
industry does not manage to produce sufficient amounts of biofuels with at least 60% direct 
greenhouse  gas  savings  or  the  technological  developments  needed  to  achieve  required 
increased bioethanol blends and electric vehicles do not take place.  

5.3.5.  Economic impacts  

The  change  in  cost  compared  to  the  baseline  is  expected  to  be  moderate  as  a  range  of 
feedstocks  is  still  available.  The  increased  use  of  electricity  in  road  transport,  and  2nd 
generation  biofuels  will  increase  aggregate  costs,  depending  on  how  the  costs  of  these 
technologies develop. 

Financial  investment  stability  is  affected,  as  the  use  of  conventional  biodiesel  feedstocks 
would be significantly reduced, as well as less efficient bioethanol production pathways. This 
would  have  significant  implications  for  the  existing  EU  biofuel  industry  that  is  not  able  to 
increase  its  efficiency.  In  that  case,  considerable  stranded  investment  would  result.  It  also 
implies  that  Member  States  and  industry  cannot  continue  to  follow  the  submitted  National 
Renewable Action Plans (NREAPs), which may have political implications.  

The  raising  of  the  threshold  to  60%  would  thus  require  industrial  adjustment,  and  those 
countries with the largest biodiesel installed capacity (i.e. Germany, Spain, France, Italy and 
the  Netherlands)  would  be  most  affected.  Moreover,  activity  will  be  reduced  in  related 
industries such as those involved in the production of vegetable oils/crushing of oil crops for 
all  food/feed/biofuels  markets  (mainly  being  present  in  Germany,  France,  Spain,  the 
Netherlands and the UK). 

The increased threshold is likely to require more producers to report actual values, rather than 
default values, as the default values are below the threshold103. This is more burdensome, as 
more  data  needs  to  be  submitted  and  verified.  In  the  Impact  Assessment  on  biomass 
sustainability104  it  was  estimated  that  the  increased  cost  of  using  actual  values  rather  then 

103 
104 

Annex V of the Renewable Energy Directive and Annex IV of the Fuel Quality Directive. 
Impact  Assessment  -  Report  from  the  Commission  to  the  Council  and  the  European  Parliament  on 
sustainability requirements for the use of solid and gaseous biomass sources in electricity, heating and 

EN 

45 

   EN 

 
                                                 
default  values  would  be  10-20  %  higher,  i.e.  not  substantially  more  than  in  the  baseline, 
particularly since only a share of the market will need to use actual values.  

Impacts  on  security  of  supply  can  be  adversely  affected  if  the  necessary  bioethanol  blend 
levels  are  not  available  in  terms  of  specification  of  the  vehicle  fleet,  or  the  required  high-
saving biodiesel volumes are not supplied.  

Option  B  would  also  have  a  number  of  trade  impacts.  Imports  of  conventional  biodiesel 
feedstocks  into  the  EU  would  be  limited,  while  the  feedstocks  and  biofuels  with  higher 
savings are expected to increase.  

5.3.6. 

Social impacts  

With  regard  to  EU  employment,  the  resulting  impacts  would  depend  on  whether  the 
opportunities created through the increase in the bioethanol and advanced biodiesel industry 
are able to make up for the reduction in activity in the conventional biodiesel industry. The 
foreseen grandfathering of installed capacity would be expected to help with the transition. 

While  rapeseed  is  likely  to  be  excluded,  the  adverse  employment  effects  within  the  EU  for 
famers are likely to be limited, as farmers would respond to the shift in demand from rapeseed 
to cereals. Rural development is dependent on the same set of variables, and thus difficult to 
assess. 

The  reduction  in  vegetable  oil  demand  will  lower  the  pressure  on  global  vegetable  oil 
markets. Conversely, pressure on coarse grains and sugar prices is likely to increase, although 
the  impacts  are  expected  to  be  moderate  as  the  demand  for  biofuels  of  these  commodity 
groups represents a lower share of the global markets than for oil crops.  

5.3.7.  Environmental impacts  

Adverse  biodiversity  impacts  are  reduced  as  it  is  expected  that  reduced  indirect  land-use 
change emissions are correlated with reduced conversion of bio-diverse areas. Certain crops 
such as sunflower and palm oil with methane capture which have associated high estimated 
indirect land-use change impacts would continue to qualify, but the quantities are assumed to 
be limited. This option would also contribute towards avoiding other environmental impacts 
associated with land conversion (i.e. adverse water, soil and air impacts).  

5.3.8.  Other impacts  

As option B follows the principles of the already existing sustainability criteria which already 
contain  thresholds  for  minimum  greenhouse  gas  savings,  the  option  is  simple  in  design  and 
implementation.  

This  option  would  be  expected  to  motivate  technological  development.  Firstly,  it  would 
provide  incentives  for  accelerating  the  introduction  of  advanced  biodiesel.  Moreover,  the 
increased  greenhouse  gas  emissions  requirements  should  encourage  improvements  in  the 
performance of 1st generation feedstocks.  

cooling. 
http://ec.europa.eu/energy/renewables/transparency_platform/doc/2010_report/sec_2010_0065_1_impa
ct_assessment_en.pdf.  

Available 

here: 

EN 

46 

   EN 

 
                                                                                                                                                         
This option does not change the existing calculation methodology and thus it is not likely to 
be  challenged  by  the  WTO.  Moreover,  this  option  does  not  depend  on  modelling  for  the 
design of the policy measure. However, it does not distinguish between feedstocks according 
to their estimated indirect land-use change impacts.  

The greenhouse gas performance of the different biofuel pathways is only dependent on the 
actions taken by the biofuel producers themselves. As such the option B follows the existing 
methodology.  

As emission savings offered by biofuels would not reflect indirect land-use change, biofuels 
would contribute less to the integrated approach for CO2 in cars. As such, larger contributions 
towards  achieving  greenhouse  gas  emissions  savings  will  be  needed  from  energy  efficiency 
and other available technologies.  

5.3.9. 

Sensitivity of option B 

5.3.9.1.  Uncertainty related to the use of oil crops under option B 

Three uncertainties are dominant regarding the effectiveness of option B.  

Firstly,  the  direct  emissions  from  the  various  feedstocks  might  change  due  to  technological 
progress  beyond  what  is  assumed  in  this  impact  assessment,  leading  to  changes  in  which 
feedstocks  are  used  and  thus  changes  in  the  estimated  indirect  land-use  change  emissions. 
This  is  particularly  important  aspect  for  rapeseed,  which  can  comply  if  sufficient 
improvements in performance are made. Rapeseed has assumed direct emissions of around 41 
g/MJ,  while  the  threshold  of  60%  is  allowing  maximum  36  g/MJ,  i.e.  5  g/MJ  lower.  In  the 
production of rapeseed, cultivation is particularly important, although around 5 g/MJ can be 
saved  by  using  bio-methanol  instead  of  fossil  derived  methanol  for  the  processing  of 
vegetable  oil  into  FAME.  Reductions  of  up  to  10-15  g/MJ  compared  to  the  29  g/MJ  of 
cultivation emissions reported under the default values in the Directives can be found in the 
literature105.  In  total  is  would  therefore  be  theoretically  possible  to  reduce  emissions  by 
around 20 g/MJ.  

Secondly, there is uncertainty related to the replacement feedstocks of rapeseed. Substitution 
could  take  place,  using  more  oil  crops  based  biodiesel  (rapeseed  with  improved  efficiency 
and/or sunflower and palm oil with methane capture which would still be expected to pass the 
threshold)  than  what  is  assumed  in  B.  Assuming  that  e.g.  all  rapeseed  passes  the  increased 
threshold,  the  effectiveness  of  option  B  would  be  reduced;  with  overall  emission  savings 
being  halved,  from  56%  to  28%.  Moreover,  the  annual  estimated  indirect  land-use  change 
emissions in 2020 would be reduced by 11Mt (23%) instead of 33Mt (69%). The uncertainty 
related to these aspects could be reduced by further increasing the threshold.  

While  estimated  indirect  land-use  change  emissions  would  increase  significantly,  as  well  as 
the adverse environmental impacts such as biodiversity loss associated with them. However, 
the negative effect on European biodiesel industry would be considerably limited. The targets 
under  the  Fuel  Quality  Directive  and  the  Renewable  Energy  Directive  would  be  easier  to 
meet, as more conventional biodiesel would be available for blending. 

105 

IEA Task 39 – Don O'Connor, Biodiesel GHG emissions, past, present and future January 2011. 

EN 

47 

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Thirdly, the increase in demand for double counted biodiesel such as that  made from waste 
and  residues  would  most  likely  increase  the  price  for  such  oils,  which  in  turn  could  lead 
indirectly to increased use of virgin vegetable oils, as the relative price106 for virgin oils would 
decrease. 

5.3.9.2.  Sensitivity related to the estimated indirect land-use change emissions 

If  the  indirect  land-use  change  emissions  are  smaller  or  larger  than  the  estimated  central 
value,  the  resulting  changes  in  emissions  in  response  to  option  B  are  set  out  in  the  table 
below:  

Indirect 
emissions only- biofuels 

land-use  change 

Total  emissions-  direct  and 
indirect- biofuels only 

Change against baseline 

Average ILUC emissions 2020 [g/MJ] 

Total ILUC emissions 2020 [Mt] 

Average emissions 2020 [g/MJ] 

Low  Central  High

11 

9 

33 

18 

14 

40 

26

20

48

Overall savings 2020 [%] 

64% 

56% 

47%

Indirect land-use change emissions (Mt) 

Total emissions (Mt) 

-21 

-43 

-33 

-56 

-46

-68

Option  B  gives  significant  emission  savings  across  the  whole  range  of  sensitivity.  The 
baseline  has  29  Mt  and  66  Mt  of  estimated  indirect  land-use  change  emissions  for  low  and 
high  estimates  respectively.  For  both  extremes,  B  is  reducing  indirect  land-use  change 
emissions  with  around  70%.  Looking  at  the  "high"  scenario,  it  leads  to  overall  savings  of 
using  biofuels  of  47%,  which  is  not  significantly  different  than  56%  as  is  the  result  in  the 
central case107. 

5.4. 

Option  C  –  introduce  additional  sustainability  requirements  on  certain 
categories of biofuels 

Option  C  involves  introducing  additional  sustainability  requirements  for  biofuels.  As 
explained  in  section  4,  option  C1  builds  on  LULUCF  reporting  and  on  taking  measures  to 
reduce  deforestation.  This  operates  on  a  national  level.  Option  C2  places  additional 
requirements  on  producers.  That  option  thus  operates  at  the  level  of  economic  operators 
(project level).  

Option  C1,  the  requirement  of  LULUCF  reporting  and  reducing  deforestation  in  biofuel 
producing countries would need to be implemented globally to ensure optimal effectiveness 
by  avoiding  "leakage".  However,  this  risk  could  be  mitigated  against  by  ensuring  that 
additional measures aimed at increasing the availability of overall agricultural production are 
put in place simultaneously. 

In  addition,  it  would  seem  appropriate  to  allow  for  the  provision  of  exemptions  from 
increased requirements resulting from the combination of B and C1 for producers in countries 
that may not be in compliance if they can demonstrate that their biofuels present a low risk of 

106 

107 

If the price of waste and residual oil increases, the total cost of using virgin oil goes down, as the cost of 
using virgin oils is the difference in price between virgin oil and waste/residual oil.  
If estimated indirect land-use change emissions were to be considered in the calculation of emissions, 
the reported savings to the Fuel Quality Directive target would be -4.5% and -3.4% for overestimating 
and underestimating indirect land-use change emissions respectively. 

EN 

48 

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indirect land-use change emissions under C2. Although preliminary work suggests that large 
quantities of biofuels could be produced in this way and this option has therefore significant 
potential  to  reduce  indirect  land-use  change  emissions,  a  methodology  for  certification  of 
biofuels  produced  under  these  conditions  is  not  yet  available.  As  such,  this  option  is  only 
assessed in combination with other options in chapter 5.6.  

Option C1 Measures aimed at reducing deforestation in biofuel producing countries 

Severe indirect land-use change emissions takes place as a result of cropland expanding into 
forests.  A  global  reduction  in  deforestation  and  improved  land  planning  would  therefore 
significantly  reduce  indirect  land-use  change  emissions.  Option  C1  requires  governments 
supplying biofuels to the EU market to reduce deforestation, by means of implementing the 
following: 

• 

• 

• 

Member States and Third countries should report emissions by sources and removals 
by sinks of greenhouse gases resulting from LULUCF activities, in accordance with 
rules laid down for Annex I parties in Article 4 of the UNFCCC, and following the 
IPCC Good practice guidance for LULUCF reporting108. This should start as soon as 
possible, preferably by 2015. 

Member States and Third countries should limit the rate of greenhouse gas emissions 
from losses of wetlands and forests (as defined in the Directives). This should start as 
soon as possible, preferably by 2015. 

Member  States  and  Third  countries  should  in  parallel  undertake  appropriate 
measures  aimed  at  increasing  the  availability  of  feedstocks  that  are  suitable  for 
biofuel production without increasing pressure on agricultural land through putting in 
place additional109 measures in line with their national circumstances. Such measures 
would  for  example  include  increasing  yields  in  a  sustainable  manner  and 
intensification  of  pasture  land;  encouraging  the  remediation  of  degraded  and 
contaminated land; reduction of waste of agricultural products at farm level and post 
harvest (particularly for developing countries), and post consumer level (in the case 
of developed countries). The assessment should be finalised by 2015, and published 
in  an  appropriate  manner.  This  provision  shall  not  apply  if  similar  practices  are 
already in place. 

The  paragraph  on  LULUCF  reporting  is  necessary  in  order  to  establish  the  statistics  of 
sufficient quality to assess the fulfilment of second paragraph110. It is thus not requiring third 
countries taking on commitments under the Kyoto Protocol. 

The  year  2015  as  year  of  implementing  LULUCF  reporting  is  necessary  to  allow  third 
countries  to  build  the  necessary  capacity  to  comply.  The  advantage  of  linking  it  to  the 
methodology required from Annex I countries, is that methodology and verification is catered 
for by a competent international body, where due considerations to both practical and political 

108 
109 

110 

Available here: http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf.html.  
As  in  the  description  of  C2,  the  word  "additional"  makes  reference  to  measures  and  developments 
beyond progress under a likely business as usual scenario. 
The  dissemination  of  the  accounting  rules  of  LULUCF  is  beneficial  in  itself:  improved  data,  more 
awareness  in  the  countries  in  question,  and  possible  easier  transition  to  commitments  under  a  new 
agreement. 

EN 

49 

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limitations  needs  to  be  taken  into  account.  Moreover,  review  and  verification  of  data  is 
qualified by existing institutions.  

5.4.1.  Effectiveness in reducing greenhouse gas emissions  

Adding a requirement on all Member States and Third countries to reduce deforestation and 
put  measures  in  place  to  increase  the  availability  of  agricultural  commodities,  could  reduce 
emissions considerably. However there are three uncertainties: 

(1) 

(2) 

(3) 

The  effectiveness  of  this  option  relies  on  whether  countries  are  choosing  to  be  in 
compliance or not, something that is outside of the control of the EU; 

The  mitigation  in  terms  of  greenhouse  gas  emissions  depends  on  the  level  of 
implementation  in  each  country  (i.e.  if  implementation  goes  beyond  minimum 
requirements), and finally; 

To  what  extent  will  leakages  take  place,  i.e.  biofuels  exporting  countries  comply, 
while indirect effects are displaced to other countries. This can be mitigated depending 
on the extent that measures put in place to increase production are successful.  

In  order  to  understand  the  possible  magnitude  of  potential  impacts,  additional  estimations 
have been done using IFPRI-MIRAGE-BioF. Assuming compliance by Indonesia, Malaysia, 
Brazil  and  Central  American  countries,  the  overall  land-use  change  emissions  would  be 
reduced considerably more than the baseline indirect land-use change emissions, i.e. not only 
those related to biofuels. For example, a reduction of deforestation rate to below 0.5% of land 
area would lead to 730 Mt of land-use change emissions being avoided each year according to 
the  model.  By  comparison,  the  total  estimated  annual  indirect  land-use  change  emissions  in 
2020 are likely to reach 48 Mt.  

However,  reducing  the  deforestation  has  economic  costs  for  these  countries  and  access  to  a 
relatively small (in global terms) biofuel EU market might not represent a rational choice for 
all  third  countries.  Therefore  in  some  particular  cases,  if  imports  from  certain  countries 
(Brazil,  Indonesia,  Malaysia  and  Central  America)  are  not  allowed,  resulting  in  trade 
distortions  and  potential  transmittance  of  impacts  to  other  countries,  IFPRI-MIRAGE-BioF 
estimates that the total land-use change emissions may actually increase by 3 Mt compared to 
the  baseline  land-use  change  emissions.  However,  this  risk  could  be  mitigated  by  ensuring 
that additional measures aimed at increasing the availability of overall agricultural production 
put in place simultaneously are successful. 

To combine option C1 with other incentives through trade agreements could prove effective 
in persuading countries to comply with option C1. Examples of such preferential treatment is 
explained below in context of the GSP+ (Generalised System of Preferences). 

5.4.2. 

Impacts on achieving the Renewable Energy Directive transport target 

The  impacts  on  meeting  the  Renewable  Energy  Directive  transport  target  would  depend  on 
the  number  of  countries  that  would  qualify  with  the  above  criteria  as  well  as  the  ability  of 
others  to  increase  their  production  should  any  of  the  major  suppliers  to  the  EU  market  be 
disqualified. 

EN 

50 

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5.4.3.  Economic impacts  

The economic impacts of option C1 would be moderate, although feedstock costs would be 
expected  to  increase  as  trade  in  biofuels  and  biofuel  feedstocks  with  countries  that  are  not 
implementing the necessary measures would be halted.  

The option might pose a risk in the context of WTO compliance, as the measure  is country 
wide.  However,  country  wide  trade  arrangements  are  not  new.  The  FLEGT  and  GSP+ 
(Generalised  System  of  Preferences)111  have  several  similarities  to  the  proposed  option  C1. 
Access to EU markets for timber is dependent on bilateral trade agreements in the context of 
FLEGT, and additional trade preferences to countries committed to sustainable development 
and good governance112 is given to countries in compliance with GSP+.  

Administrative costs are limited to those related to reviewing the submitted LULUCF reports, 
which  is  done  by  the  UNFCCC.  Review  of  all  Annex  I  countries'  reports  is  already 
implemented.  

5.4.4. 

Social impacts 

Social impacts of option C1 depends on how effective the measures are, as discussed above. 
Employment  in  the  EU  is  expected  to  increase  if  few  third  countries  comply,  since  more 
production  must  take  place  within  the  EU.  If  most  exporting  countries  are  in  compliance, 
employment will be as in the baseline. Reducing deforestation may also have positive impacts 
on the short term economic and social growth of developing countries.  

5.4.5.  Environmental impacts 

Also environmental impacts of option C1 are dependent on its effectiveness. Deforestation is 
one  of  the  major  reasons  for  loss  of  biodiversity.  The  reduction  of  deforestation  in  biofuel 
producing  countries  could  therefore  reduce  such  losses,  with  additional  positive  impacts 
related to soil, water and air. In this context, it is important that the risk of indirect land-use 
change emissions transmission to other countries is appropriately mitigated. 

5.4.6.  Other impacts 

If  option  C1  was  to  result  in  increased  implementation  of  LULUCF  reporting  it  could  have 
wider positive impacts, as this would be likely to improve awareness of carbon losses related 
to land-use and land governance. The implementation of this option could add some countries 
to the group of 42 Annex I countries113.  

As emission savings offered by biofuels would not reflect indirect land-use change, biofuels 
would contribute less to the integrated approach for CO2 in cars. As such, larger contributions 
towards  achieving  greenhouse  gas  emissions  savings  will  be  needed  from  energy  efficiency 
and other available technologies. 

111 

112 

113 

countries:  African,  Caribbean 

and  Pacific  Group  of  States.  Secretariat: 

For  ACP 
http://www.acpsec.org/.  
To benefit from GSP+ conditions, countries have to ratify and implement 27 international conventions 
and  undergo  a  rigorous  vetting  and  application  process.  GSP+  eligibility  is  reviewed  every  3  years. 
Further 
here: 
http://trade.ec.europa.eu/doclib/docs/2007/september/tradoc_136097.pdf.  
List 
http://unfccc.int/parties_and_observers/parties/annex_i/items/2774.php.  

explanation 

countries 

available 

Annex 

found 

here: 

can 

be 

of 

I 

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51 

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5.5. 

Option  D  -  Attribute  a  quantity  of  greenhouse  gas  emissions  to  biofuels 
reflecting the estimated indirect land-use impact. 

This option builds in the estimated indirect land-use change emissions into the greenhouse gas 
emissions  accounting  methodology  for  biofuels.  According  to  the  assumptions  made  in  this 
impact  assessment,  these  estimates  (factors)  are  added  to  the  expected  2020  baseline  direct 
emissions (cultivation, processing and transport) as described in table 4 of chapter 2114. This 
would require incorporating the estimated indirect land-use change emissions values in both 
the  reporting  of  greenhouse  gases,  as  well  as  ensuring  compliance  with  the  minimum 
greenhouse gas thresholds of the sustainability criteria.  

The initial assessment of this option focuses on the impacts in terms of exclusion of certain 
feedstocks. This depends on whether eiluc (the indirect land-use change emission factors) are 
set  at  a  level  which  mitigates/anticipates  the  risk  of  a  possible  model  overestimation  (50%, 
25%  and  5%  percentiles)  and  underestimation  (95%,  75%  and  50%  percentiles)  of  crop-
specific indirect  land-use change  emission factors based on the latest IFPRI-MIRAGE-BioF 
report. At the end of this section, the impacts from setting these levels based on crop group 
(i.e. starch, oil crops and sugar crops) are also explored.  

5.5.1.  Level of indirect land-use change emission factors per feedstock 

The results in table 8 below show whether feedstocks would comply with the thresholds set 
out  in  the  Directives  respectively  when  the  range  of  estimated  indirect  land-use  change 
emissions  resulting  from  the  Monte-Carlo  analysis  are  considered.  Table  8  is  thus  the  crop 
specific values in Annex XV added to the direct emissions. All values are shown in grams of 
CO2-eq./MJ. 

 Feedstocks 

Palm oil 

Palm oil with methane capture 

Soybean 

Rapeseed 

Sunflower 

l
e
s
e
i
d
o
i
B

2G biodiesel - land using 

2G biodiesel - non-land using 

i Wheat Process fuel not specified 
B

5th 

25th 
percentile 

Central 

75th 
percentile 

95th 

98 

76 

85 

68 

63 

12 

9 

59 

102 

105 

108 

80 

97 

85 

79 

18 

9 

62 

83 

103 

95 

86 

21 

9 

64 

86 

108 

106 

93 

24 

9 

66 

111 

90 

121 

121 

104 

32 

9 

69 

114 

In this context, it is important to note that the crop specific values are estimated based on the increase of 
biofuel  consumption  towards  2020  compared  to  the  existing  consumption  in  2008.  IFPRI-MIRAGE-
BioF  reports  that  for  those  feedstocks  that  display  a  strong  non-linearity  effect  (i.e.  rapeseed),  the 
indirect land-use change emissions in 2020 would be higher than those observed at lower consumption 
levels.  Due  to  the  limitations  of  this  assessment  (i.e.  snapshot  at  2020),  this  effect  is  not  considered 
further in this document. 

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52 

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Wheat Natural- gas process fuel CHP plant 

42 

Corn (maize) 

Sugar cane 

Wheat Straw as process fuel in CHP plant 

Sugar beet 

2G bioethanol - land using 

2G bioethanol - non-land using 

39 

27 

30 

28 

23 

9 

45 

41 

33 

33 

31 

29 

9 

47 

43 

36 

35 

34 

32 

9 

49 

44 

39 

37 

37 

35 

9 

52 

46 

47 

40 

40 

43 

9 

Table 8: impacts on the availability of feedstocks when different ILUC factors based on feedstock specific 
values are computed with expected typical direct emissions in 2020. Feedstocks in red/dark grey fail to 
achieve required levels of savings at 50% by more than 5g; in grey the fail by less than 5g, and; in 
green/light grey those than meet the 50% threshold. 

From the table above, it is possible to draw a number of preliminary conclusions.  

• 

• 

Firstly,  when  the  estimated  indirect  land-use  change  emissions  are  added  to  the 
expected direct emissions in 2020, none of the oil crops feedstocks would be able to 
meet  the  50%  greenhouse  gas  emissions  savings  as  required  by  the  Directives, 
regardless  of  the  range  of  indirect  land-use  change  estimates  used.  This  is  because 
these  feedstocks  present  relatively  high  direct  emissions  (e.g.  soybean  fails  even 
when  the  50%  threshold  is  applied  to  the  direct  emissions,  before  the  estimated 
indirect  land-use  change  emissions  are  included),  and  are  attributed  relatively  high 
estimated indirect land-use change emissions.  

The contrary is true for bioethanol feedstocks. There only the least efficient wheat to 
bioethanol pathway is estimated not to achieve the required minimum savings, unless 
the most conservative indirect land-use change emission values (95th) are applied, in 
which  case  corn  and  sugarcane  also  marginally  fail  to  pass.  All  other  bioethanol 
pathways would otherwise be expected to achieve the required savings in 2020.  

In light of the above, the evaluation of option D is carried out using the central values.  

Table 8 above shows how certain feedstocks would be excluded (in red) from being counted 
towards  the  Directive  targets.  In  addition,  attributing  estimated  indirect  land-use  change 
emissions to feedstocks would also lead to incentives for biofuels with lower indirect land-use 
change emissions due to the accounting and reporting by fuel suppliers under the Fuel Quality 
Directive  which  is  likely  to  bring  about  a  significant  price  differentiation  in  favour  of  low-
ILUC  transport  fuels  because  those  biofuels  will  contribute  much  more  than  others  to  the 
attainment  of  a  supplier's  obligation  to  reduce  the  greenhouse  gas  intensity  of  the  fuels  it 
supplies.  This  second  element  is  more  sophisticated  than  the  exclusion  showed  in  table  8 
above  as  the  emission  estimates  provide  incentives  for  biofuels  with  low  estimated  indirect 
land-use  change  emissions.  Although  the  effectiveness  of  this  second  element  cannot  be 
assessed  under  the  methodology  being  used  in  this  impact  assessment,  further  discussion  is 
included in the sensitivity section of this option. 

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53 

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5.5.2.  Potential scenario - meeting the targets of the Directives  

A range of possible scenarios for how to comply with option D, while meeting the targets, can 
be developed. As  no vegetable oils can be used, it implies increasing the use of  bioethanol, 
advanced biodiesel or electric vehicles. A set of theoretical and extreme scenarios exploring 
the  use  of  these  options  are  found  in  Annex  XIV. The least unrealistic scenario  including a 
contribution  from  other  technologies  (electric  vehicles)  that  would  also  achieve  the 
Renewable Energy Directive transport target is set out below (these figures are included here 
for  illustrative  purposes  only  as  it  is  not  possible  to  determine  what  the  final  mixture  of 
technologies would look like in reality).  

Bioethanol [Mtoe]  Double 

counted 

biodiesel [Mtoe] 

Electricity  in  road 
[Mtoe] 

Baseline 

Option D 

6.7 

13.6 

1.8 

9 

2.1 

2.6 

The scenario described above would require a doubling in the levels of bioethanol and almost 
a fivefold increase in the production of double counted biodiesel compared to the volumes set 
out in the NREAPs.  

The  increased  consumption  of  ethanol  is  question  of  blending  possibilities,  as  the  share  of 
petrol  consumption  in  the  EU  is  decreasing,  and  expected  to  continue  to  decline.  The  JEC 
Analysis of scenarios for transport in the EU towards 2020115, finds that in a scenario with an 
E85  grade  (flexi-vehicles)  introduced  now,  and  E20  in  2017,  the  EU  would  consume  8-9 
Mtoe of ethanol. If E20 is introduced in 2015 rather than in 2017 (2 years earlier), it leads to 
additional 0.7 Mtoe of ethanol being consumed in 2020. This indicates how the consumption 
of 13.6 Mtoe of ethanol would be very challenging. 

The  availability  of  double-counted  biodiesel  is  a  question  of  supply,  both  in  terms  of 
availability  of  raw-material  e.g.  waste  oil,  but  also  a  technical  question  whether  enough 
production capacity can be cost-efficiently installed by 2020. Achieving a supply of 9 Mtoe of 
double counted biodiesel would therefore be very challenging.  

The  scenario  also  needs  increased  efforts  i.e.  0.6  Mtoe  of  additional  electricity  in  road 
transport by 2020. This would be the equivalent of deploying an additional 2.3 million electric 
cars116 by 2020 on top of what is foreseen in the NREAPs. The NREAPs estimate that around 
2.1  Mtoe  of  electricity117  is  consumed  in  electric  vehicles  in  2020,  which  implies  8  million 
electric cars. It should be noted that 2.1 Mtoe includes plug-in hybrids, as well as other road 

115 

116 

117 

EU  renewable  energy  targets  in  2020:  Analysis  of  scenarios  for  transport  –  JEC  biofuels  programme 
http://ies.jrc.ec.europa.eu/uploads/jec/JECBiofuels%20Report_2011_PRINT.pdf.  
Assumptions:  Electricity  consumption  of  an  electric  car  can  be  assumed  to  be  approximately  0.2 
kWh/km.  Average  annual  electric  distance  travelled  is  assumed  to  be  15.000km.  Annual  electricity 
consumption of one electric car will be roughly 3 kWh.. Expressed in toe, this is 3 * 8.6 * 10-5 which 
gives 0.26 toe. Therefore 1 Mtoe electricity consumption by cars implies 3.9 million cars on the road. 
The NREAPs estimate a total of 0.7 Mtoe of renewable electricity in road vehicles by 2020. In order to 
convert this figure to overall electricity it has to be divided by the fraction of renewable energy in the 
electricity  mix  of  2020,  assumed  to  be  34%  for  the  EU  in  the  NREAPs.  This  gives  2.1  Mtoe  of 
electricity.  The  real  figure  is  likely  to  be  lower,  as  countries  with  higher  than  average  share  of 
renewable energy in the electricity mix, will use national values rather than the EU-average.  

EN 

54 

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vehicles  using  electricity.  Again,  this  means  that  this  scenario  is  not  very  likely  and  these 
figures are included here for illustrative purposes only.  

5.5.3.  Effectiveness in reducing greenhouse gas emissions  

This is the most effective option in reducing the estimated indirect land-use change emissions, 
with  40  Mt  (85%)  of  the  estimated  indirect  land-use  change  emissions  taking  place  in  the 
baseline  being  avoided  in  2020  as  a  result.  Overall  emissions  would  be  reduced  by  66  Mt 
compared  to  the  baseline,  with  biofuels  saving  an  average  of  70%  emissions  compared  to 
fossil fuels. Moreover, the reported savings towards the Fuel Quality Directive target remain 
at -5.4% when indirect land-use change emissions are included.  

The main results in terms of greenhouse gas emissions are shown in the table below.  

Direct emissions- biofuels  

Direct emissions 2020 (g/MJ)

Direct emission savings 2020 [%]

Total direct emissions 2020 (Mt)

Indirect 
emissions- biofuels 

land-use 

emissions-  direct 

Total 
indirect- biofuels  

Change against baseline 

change 

Average ILUC emissions 2020 [g/MJ] 

Total ILUC emissions 2020 [Mt]

and 

Average emissions 2020 [g/MJ]

Overall savings 2020 [%]

Indirect land-use change emissions (Mt) 

Total emissions (Mt)

17

82%

16

10

8

27

70%

-40

-66

Table 9: Effectiveness analysis of option D 

5.5.4. 

Impacts on the Renewable Energy Directive transport target  

There  is  a  high  risk  that  the  transport  target  of  the  Renewable  Energy  Directive  is  not 
achieved,  as  it  will  be  challenging  for  industry  to  produce  enough  advanced  biofuels, 
particularly since all conventional biodiesel is excluded and 70-75% of the transport fuels are 
expected  to  be  diesel  in  2020,  the  technological  developments  needed  to  achieve  required 
increased bioethanol blends and electric vehicles do not take place.  

5.5.5.  Economic impacts  

The viability of existing investments would be affected in the long run, as Member States and 
industry cannot continue to follow the submitted National Renewable Action Plans (NREAPs) 
since  no  conventional  biodiesel  feedstocks  would  be  available.  This  would  have  significant 
implications  for  the  existing  EU  biodiesel  industry,  and  those  countries  with  the  largest 
biodiesel installed capacity (i.e. Germany, Spain, France, Italy and the Netherlands) would be 
most affected. Moreover, activity will be reduced in related industries such as those involved 
in  the  production  of  vegetable  oils/crushing  of  oil  crops  for  all  food/feed/biofuels  markets, 
mainly being present in Germany, France, Spain, the Netherlands and the UK). As foreseen in 
the  Directives118,  the  introduction,  if  appropriate,  of  an  indirect  land-use  change  emission 
methodology  would  need  to  consider  the  provision  of  safeguards  to  investment  undertaken 
from  existing  installations  involved  in  the  production  chain  that  would  otherwise  have 
complied with the greenhouse gas emissions requirements.  

118 

See chapter 3 for further detail. 

EN 

55 

   EN 

 
                                                 
On  the  one  hand,  it  could  be  argued  that  certainty  for  new  investments  would  be  increased 
since  the  estimated  full  greenhouse  gas  emissions  impacts  are  being  taken  into  account. 
Bioethanol production capacity would need to be increased  significantly  to make  up for the 
increased demand, which would create economic opportunities in this area. In addition, there 
would  also  be  significant  opportunities  for  the  second  generation  biofuel  industry  as  their 
better  performance  compared  with  conventionally  produced  biodiesel  would  be  made 
apparent.  On  the  other  hand,  the  introduction  of  indirect  land-use  change  emission  factors, 
and  the  update  of  these  values,  would  create  uncertainty  regarding  what  an  updating  might 
bring  in  terms  of  consequences  to  the  industry.  This  process  would  therefore  need  to  be 
managed carefully. 

With  regard  to  production  costs,  the  change  compared  to  the  baseline  is  expected  to  be 
moderate as most bioethanol feedstocks required to make up for the missing biodiesel remain 
available  once  indirect  land-use  change  emission  factors  have  been  applied.  However,  the 
need  for  electric  vehicles  and  2nd  generation  biofuels  will  increase  the  aggregate  cost, 
depending  on  how  the  costs  of  these  technologies  develop.  There  are  no  additional 
administrative  costs  associated  with  this  option,  as  requirements  under  the  current 
sustainability scheme are neither changed nor increased. 

Impacts  on  security  of  supply  can  be  adversely  affected  if  the  necessary  bioethanol  blend 
levels  are  not  available  in  terms  of  specification  of  the  vehicle  fleet,  or  the  required  high-
saving  biodiesel  volumes  are  not  supplied  in  time.  In  any  case,  the  need  to  accelerate 
developments  in  order  to  make  the  existing  fleet  to  be  compatible  with  higher  bioethanol 
blends  will  have  increased  costs  for  the  vehicle  manufacturers.  Again,  the  foreseen 
application of the grandfathering clause on installed capacity would be expected to help with 
this transition.  

Similarly,  this  option  would  have  a  number  of  trade  impacts.  Imports  of  conventional 
biodiesel  feedstocks  into  the  EU  would  be  severely  limited.  However,  trade  in  second 
generation  biodiesel  feedstocks  and/or  second  generation  biodiesel  if  available  would 
increase,  as  well  as  in  bioethanol  feedstocks,  and/or  processed  bioethanol  if  EU  processing 
capacity does not increase in time.  

In  terms  of  WTO  compatibility,  option  D  may  lead  to  issues  related  to  its  reliance  on 
modelling for the determination of the factors. However, similarly constructed indirect land-
use  change  emission  factors  applying  in  US  federal  and  Californian  Low  Carbon  Fuel 
Standard  have  not  been  challenged  to  date.  That  said,  although  the  abovementioned 
legislation leads to a preferential treatment of feedstocks with estimated low-ILUC impacts, it 
does  not  lead  to  certain  biofuel  feedstocks  being  totally  excluded  from  receiving  financial 
support or counted towards mandatory targets.  

5.5.6. 

Social impacts  

With  regard  to  EU  employment,  the  resulting  impacts  would  depend  on  whether  the 
opportunities created through the increase in the bioethanol and advanced biodiesel industry 
are able to make up for the reduction in activity in the conventional biodiesel industry. Again, 
the foreseen application of the grandfathering clause on installed capacity would be expected 
to help with the transition.  

While rapeseed and sunflower is excluded, the adverse employment effects within the EU for 
famers are likely to be limited, as farmers would respond to the shift in demand from rapeseed 
to  cereals  and  sugar  beet.  Notably,  the  main  Member  States  producing  rapeseed  (i.e. 

EN 

56 

   EN 

 
Germany,  France,  Poland  and  United  Kingdom)  are  also  the  main  producers  of  cereals  and 
sugar beet. On the other hand, reduced production of oil crops can be problematic in terms of 
crop rotation in some  areas  where sugar beet cannot be grown because of  soil requirements 
(i.e. rapeseed and sugar beet are used as a break crops), and could increase the deficit in feed 
protein (i.e. oil crops yield higher quality meals compared to cereals), as farmers are unlikely 
to switch to protein crops (i.e. peas, beans). 

Rural  development  is  dependent  on  the  same  set  of  variables,  and  thus  difficult  to  assess. 
However,  the  required  increased  use  of  advanced  biodiesel  would  be  expected  to  have 
positive impacts. 

Pressure on vegetable oil prices will be reduced in commodity markets as a result of reduced 
biodiesel  demand.  Conversely,  pressure  on  coarse  grains  and  sugar  prices  will  increase, 
although to a lesser extent as the demand for biofuels of these commodity groups represents a 
lower  share  of  the  global  markets  than  for  oil  crops.  As  such,  the  reliance  of  the  EU  on 
imported vegetable oils would improve, as well as reducing the excess production of cereals 
and sugars.  

5.5.7.  Environmental impacts  

Based  on  the  results  above,  this  option  would  also  be  expected  to  be  the  most  effective  in 
reducing  the  biodiversity  impacts  associated  with  indirect  land-use  change.  Due  to  their 
irreversible  and  cumulative  nature,  the  extent  by  which  these  impacts  are  addressed  would 
depend on when action is taken.  

In  addition,  this  option  would  also  significantly  contribute  towards  avoiding  other 
environmental  impacts  associated  with  land  conversion  (i.e.  adverse  water,  soil  and  air 
impacts).  

5.5.8.  Other impacts  

This  option  would  be  expected  to  motivate  technological  development.  Firstly,  it  would 
provide strong incentives for accelerating the introduction of advanced biodiesel. Moreover, 
the increased greenhouse gas emissions requirements should encourage improvements in the 
performance of 1st generation bioethanol feedstocks. The implementation of the 6% target of 
the  Fuel  Quality  Directive  provides  strong  price  signals  for  improved  greenhouse  gas 
emissions performance for biofuels as a result of the incorporation of indirect land-use change 
emissions  factors,  as  well  as  incentives  for  transport  fuels  and  energy  with  low  estimated 
indirect land-use change emissions, as explained in section 5.5.1119.  

All biofuels that would be counted towards these targets meet the greenhouse gas emissions 
thresholds  when  estimated  indirect  land-use  change  emissions  are  included.  As  a  result, 
emission  savings  offered  by  qualifying  biofuels  would  be  coherent  with  the  integrated 
approach for CO2 in cars.  

Option D would imply that the greenhouse gas calculation methodology would be modified 
from  the  existing  principles  of  greenhouse  gas  performance  being  the  result  of  the  biofuel 
producer's  actions,  to  a  system  where  the  greenhouse  gas  performance  is  also  dependent  on 
the  actions  of  actors  outside  the  producer's  control.  Adding  the  indirect  impact  to  the  direct 
emissions,  implies  that  if  the  same  principles  of  accounting  greenhouse  gas  emissions  as 

119 

For example, it is worth noting that following the implementation of the Californian Low Carbon Fuel 
Standard in 2010, a price differential emerged between biofuels of different carbon intensity.  

EN 

57 

   EN 

 
                                                 
under option D, were to be applied to all commodities, it would result in double-counting, as 
the indirect emissions of biofuels are the direct emissions of another commodity. 

In practical terms it might be less relevant as greenhouse gas emissions from the majority of 
commodities  may  never  be  accounted  for  globally.  However,  as  discussed  in  the  LULUCF 
section:  If  LULUCF  accounting  were  to  be  implemented  globally  together  with  option  D, 
indirect  land-use  change  emissions  would  be  accounted  for  both  as  part  of  the  biofuel 
greenhouse gas performance, and as LULUCF emissions in the country where indirect land-
use change took place.  

Whether  or  not  to  estimated  indirect  land-use  change  emissions  should  be  included  in  the 
greenhouse gas accounting of the biofuels, also relates to the principle of carbon-neutrality of 
biofuels. Currently it is assumed that tailpipe carbon emissions are zero, as a similar amount 
of  carbon  is  absorbed  by  the  feedstocks  as  they  are  grown.  In  a  context  of  biofuels  using 
existing cropland, where crops would have been grown anyway, a similar amount of carbon 
would also have been extracted from the atmosphere. While it is difficult to assess the overall 
carbon impact of the land remaining as non-biofuel cropland, option D would to some extent 
capture this.  

The greenhouse gas accounting methodology has to balance the need for ensuring significant 
savings  from  the  use  of  biofuels  with  a  stable  and  predictable  policy  framework.  There  are 
broader implications of option D in that introducing indirect land-use change emission factors 
for  biofuels  could  lead  to  similar  factors  being  introduced  for  other  types  of  bioenergy, 
especially  due  to  use  of  the  same  feedstocks.  However,  in  order  to  ensure  that  biofuels  and 
bioenergy  successfully  contribute  towards  the  EU  climate  objectives  and  related  specific 
greenhouse  gas  emissions  reduction  targets  as  set  out  in  the  "  A  Roadmap  for  moving  to  a 
competitive low carbon economy in 2050", it is necessary to ensure that biofuels do not lead, 
directly  or  indirectly,  to  a  decrease  of  the  net  greenhouse  gas  benefits.  This  could  be 
challenging  if  the  indirect  emissions  associated  with  land  using  biofuel  are  not  minimised. 
Moving  forward  towards  2050,  it  is  currently  considered  that  indirect  emissions  could  be 
accounted  for  through  global  LULUCF  accounting  or  through  adding  factors  as  foreseen  in 
option D.  

5.5.9. 

Sensitivity of option D 

5.5.9.1.  Uncertainty related to the effectiveness of option D 

The  considerable  increase  in  demand  for  double  counting  biodiesel  such  as  that  made  from 
waste and residues would most likely increase the price for such oils, which in turn could lead 
indirectly to increased use of virgin vegetable oils, as the relative price120 for virgin oils would 
decrease. 

5.5.9.2.  Sensitivity related to the estimated indirect land-use change emissions 

If  the  indirect  land-use  change  emissions  are  smaller  or  larger  than  the  estimated  central 
value,  the  resulting  changes  in  emissions  in  response  to  option  D4  are  set  out  in  the  table 
below:  

Low   Central  High  

120 

If the price of waste and residual oil increases, the total cost of using virgin oil goes down, as the cost of 
using virgin oils is the difference in price between virgin oil and waste/residual oil.  

EN 

58 

   EN 

 
 
 
                                                 
Indirect  land-use  change 
emissions- biofuels 

Total  emissions-  direct 
and indirect- biofuels  

Average ILUC emissions 2020 [g/MJ] 

Total ILUC emissions 2020 [Mt] 

Average emissions 2020 [g/MJ] 

4.4 

3 

21 

10 

8 

27 

17

13

34

Overall savings 2020 [%] 

77% 

70% 

62%

Change against baseline 

Indirect land-use change emissions (Mt) 

Total emissions (Mt) 

-26 

-52 

-40 

-66 

-53

-79

The introduction of D4 gives overall savings from 62% to 77%. The main conclusion is that 
under all circumstances, levels higher than 50% greenhouse gas emissions savings would be 
achieved121.  

Scenario D4 would correspond to levels of an indirect land-use change emission factor being 
set at 50th percentile. Applying the factors at lower or upper end of the sensitivity range as set 
out in table 7, are not expected to have major impacts on the overall situation described above 
(i.e. conventional oil crops would still need to be replaced by equivalent levels of bioethanol, 
double counted biodiesel and electricity in roads).  

5.5.9.1.  The  impacts  of  including  the  estimated  indirect  land  use  change  greenhouse  gas 
emissions in the reporting of the greenhouse gas emission savings of biofuels.  

The reporting of the emissions towards the Fuel Quality Directive would be expected to create 
a strong price premium for those biofuels with the lowest estimated indirect land-use change 
emissions.  The  reason  for  that  is  that  biofuels  with  low  estimated  indirect  land-use  change 
emissions will contribute much more than others to the attainment of a supplier's obligation to 
reduce  the  greenhouse  gas  intensity  of  the  fuels  it  supplies.  As  it  has  not  been  possible  to 
assess  this  aspect  of  option  D  with  the  assessment  methodology  applied  in  this  Impact 
Assessment, this element is further outlined in the text and figure below.  

Figure 7: Greenhouse gas savings obtained under the Fuel Quality Directive 

• 

fuels  A,  B  and  C  offer  similar  greenhouse  gas  emission  savings  when  only 
direct emissions are taken into account; 

121 

With regard to the Fuel Quality Directive carbon intensity reductions, the 5.4% contribution achieved 
under  the  central  scenario  (factors  at  50th  percentile)  includes  indirect  land-use  change  emissions, 
which  are  now  being  reported.  The  Fuel  Quality  Directive  reduction  under  the  biofuel  mix  obtained 
would range between 4.8% and 5.9% depending on whether we have overestimated or underestimated 
the "real" indirect land-use change emissions. 

EN 

59 

   EN 

 
 
                                                 
• 

• 

when  the  estimated  indirect  land-use  change  emissions  are  included  in  the 
reporting, the contribution to the attainment of a supplier's obligation to reduce 
the  greenhouse  gas  intensity  of  the  fuels  it  supplies  differs  considerably 
between  the  three  fuels.  Fuel  A  would  be  completely  excluded  under  this 
option as it would fail to comply with the greenhouse gas emissions thresholds 
under the sustainability criteria. 

as  such,  a  fuel  supplier  would  need  twice  the  amount  of  fuel  B  to  obtain  the 
same savings as by using one volume of fuel C. This is therefore expected to 
result in a high price premium for fuel C, as it would count twice as much as B 
towards these targets, hence maximising its share over B in the final mix. 

Although it has not been possible to assess the impact on the effectiveness of this aspect of 
option  D  in  isolation  in  a  quantitative  manner  with  the  assessment  methodology  applied  in 
this Impact Assessment, some possible outcomes are presented in Annex XVI. The findings 
strongly  suggest  that  significant  amounts  of  further  improved  biofuels  with  low  risk  of 
indirect land-use change emissions would be expected in the final mix as a result.  

5.5.10.  Exploring  different  levels  of  disaggregation  -  Indirect  land-use  change  emissions 

aggregated per crop group (oil crops, starch and sugars)  

The results in table 10 show whether feedstocks would comply with the thresholds set out in 
the  Directives  respectively  when  the  weighted  per  crop  group  average  of  estimated  indirect 
land-use change emissions resulting from the Monte-Carlo analysis are considered. Table 10 
below is thus the crop group average values in Annex XV added to the direct emissions. 

 Feedstocks 

Palm oil 

Palm oil with methane capture 

l
e
s
e
i
d
o
i
B

Soybean 

Rapeseed 

Sunflower 

2G biodiesel - land using 

2G biodiesel - non-land using 

Wheat Process fuel not specified 

Wheat Natural- gas process fuel CHP plant

l
o
n
a
h
t
e
o
i
B

Corn (maize) 

Sugar cane 

Wheat Straw as process fuel in CHP plant

Sugar beet 

2G bioethanol - land using 

5th 

85

64

81

75

67

10

9

58

41

40

25

29

32

22

25th 
percentil
e 

Central 

75th 
percentil
e 

95th 

98

76

94

87

80

16

9

61

44

43

30

32

37

27

106

84

102

95

87

18

9

63

46

45

33

34

40

30

114 

92 

109 

103 

95 

22 

9 

64 

48 

47 

36 

36 

43 

33 

125

104

121

115

107

28

9

67

50

49

43

38

50

39

2G bioethanol - non-land using 

9
Table 10: impacts on the availability of feedstocks when different ILUC factors based on feedstock specific 
values are computed with expected typical direct emissions in 2020. Feedstocks in red/dark grey fail to 

9 

9

9

9

EN 

60 

   EN 

 
 
 
 
 
achieve required levels of savings at 50% by more than 5g; in grey the fail by less than 5g, and; in 
green/light grey those than meet the 50% threshold. All values are shown in grams of CO2-eq./MJ. 

None of the oil crops feedstocks are either able to achieve the 50% minimum greenhouse gas 
emissions thresholds. Similarly, none of the bioethanol crops other than the least efficient 
wheat processes seem to have any difficulties to meet the required thresholds until 
conservative indirect land-use change emission estimates are applied.  

5.6. 

Option E - Limit the contribution from conventional biofuels to the Renewable 
Energy Directive targets. 

Option  E  involves  limiting  the  us  of  conventional  biofuels  from  food  crops  by  setting  the 
maximum  contribution  of  such  biofuels  towards  the  10%  target  of  the  Renewable  Energy 
Directive to current production levels at 5%. To ensure coherence, the equivalemt quantity in 
energy content is the maximum that can contribute towards the Member States' overall targets 
for renewable energy.  

5.6.1.  Potential scenario - meeting the targets of the Directives  

A range of possible scenarios for how to comply with option E, while meeting the targets, can 
be developed. The cap is assumed to be equivalent to around 14 Mtoe. As less conventional 
biofuels  are  likely  to  be  used,  it  implies  increasing  the  use  of  advanced  biofuels  or  electric 
vehicles.  A  scenario  including  contribution  from  other  technologies  (electric  vehicles)  that 
would  meet  the  Fuel  Quality  Directive  target  and  achieve  the  Renewable  Energy  Directive 
transport target is set out below (these figures are included here for illustrative purposes only 
as  it  is  not  possible  to  determine  what  the  final  mixture  of  technologies  would  look  like  in 
reality).  

Bioethanol [Mtoe]  Double 

counted 

biofuels [Mtoe] 

Electricity  in  road 
[Mtoe] 

Baseline 

Option E 

6.7 

6.7 

1.8 

6.0 

2.1 

2.6 

The scenario described above would require more than a tripling of the production of double 
counted biofuels compared to the volumes set out in the NREAPs. If combined with optoin 
C2,  the  reliance  on  advanced  biofuels  would  be  reduced,  which  would  in  turn  reduce  costs 
and make it easier to comply with the targets of the Directives. 

5.6.2.  Effectiveness in reducing greenhouse gas emissions  

Capping the use of conventional biofuels implies that overall emissions are reduced by 48 Mt 
compared to the baseline. 27 Mt (56%) of the estimated indirect land-use change emissions 
occurring in the baseline would be avoided in 2020. The biofuels used are on average saving 
44%  compared  to  fossil  fuels  when  indirect  land-use  change  emissions  are  considered.  The 
emissions reported towards the Fuel Quality Directive target will not reflect estimated indirect 
land-use change emissions. 

The main results are shown in the table below.  

Direct emissions- biofuels  

Direct emissions 2020 (g/MJ)

24

EN 

61 

   EN 

 
 
Direct emission savings 2020 [%]

Total direct emissions 2020 (Mt)

Indirect land-use change emissions 
– biofuels 

Average ILUC emissions 2020 [g/MJ] 

Total ILUC emissions 2020 [Mt]

direct 

and 

Average emissions 2020 [g/MJ]

emissions- 

Total 
indirect- biofuels  

Change against baseline 

Overall savings 2020 [%]

Indirect land-use change emissions (Mt) 

Total emissions (Mt)

74%

21

27

20

51

44%

-27

-48

Table 11: Effectiveness analysis of option E 

5.6.3. 

Impacts on achieving the Renewable Energy Directive transport target 

There is a risk that the transport target of the Renewable Energy Directive is not achieved, if 
the  technological  development  required  for  the  significant  increase  in  deploying  advanced 
biofuels  is  not  be  achieved.  However,  this  option  is  the  least  challenging  from  a  blending 
perspective  as  it  does  not  require  additional  levels  of  bioethanol,  and  the  overall  levels  of 
biodiesel  would  be  expected  to  be  lower  than  in  the  baseline  scenario  as  a  higher  share  of 
double counted biofuels would be expected.  

5.6.4.  Economic impacts  

The  change  in  cost  compared  to  the  baseline  is  expected  to  be  moderate  as  a  range  of 
feedstocks  would  still  available.  The  increased  use  of  electricity  in  road  transport,  and  2nd 
generation  biofuels  will  increase  aggregate  costs,  depending  on  how  the  costs  of  these 
technologies develop. 

Financial  investment  stability  is  affected,  as  the  expected  use  of  conventional  biofuel 
feedstocks would be reduced by a third in 2020. This would have implications for the existing 
EU  biofuel  industry,  although  the  impact  is  limited,  as  the  cap  would  maintain  today's 
production  levels  of  conventional  biofuels.  It  also  implies  that  Member  States  and  industry 
may not be able to follow the submitted National Renewable Action Plans (NREAPs), which 
may have political implications.  

Certainty  for  new  investments  would  be  increased  as  it  would  be  clear  what  levels  of  both 
conventional and advanced biofuels that would be needed by 2020. In addition, there would 
also be very strong opportunities for the second generation biofuel industry who would as a 
result  of  the  limit  of  conventional,  have  a  garanteed  share  of  the  market.  There  are  no 
additional administrative costs associated with this option, as requirements under the current 
sustainability scheme are neither changed nor increased. 

Adverse impacts on security of supply and trade may take place if the necessary volumes of 
advanced biofuels are  not  available.  In both cases, the limit  of  on the conventional biofuels 
would ensure that today's energy security levels and trade volumes are mantained. 

5.6.5. 

Social impacts  

With  regard  to  EU  employment,  current  production  levels  and  associated  jobs  woud  be 
mantained through the cap. The extent of which the additional incentives for opportunities to 

EN 

62 

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be created through the increase in the advanced biofuel industry are able to make up for the 
reduction in activity in the conventional biofuel industry would determine the overall impacts.  

While  the  share  of  conventional  biofuels  is  reduced  by  a  third,  the  adverse  employment 
effects within the EU for famers are likely to be limited, as farmers would respond to the shift 
in demand from growing conventional to growing and collecting advanced biofuel feedstocks.  

Rural  development  is  dependent  on  the  same  set  of  variables,  and  thus  difficult  to  assess. 
However,  the  required  increased  use  of  advanced  biodiesel  would  be  expected  to  have 
positive impacts. 

The reduction in food based biofuels will lower the pressure on global food and feed markets, 
in  particular  for  oil  crops  where  the  biodiesel  production  represents  a  larger  share  of  the 
global supply, but also for cereals and sugars as bioethanol crops would also be capped.  

5.6.6.  Environmental impacts  

Adverse  biodiversity  impacts  are  reduced  as  it  is  expected  that  reduced  indirect  land-use 
change  emissions  are  correlated  with  reduced  conversion  of  bio-diverse  areas.  This  option 
would  also  contribute  towards  avoiding  other  environmental  impacts  associated  with  land 
conversion (i.e. adverse water, soil and air impacts) as the share of biofuels that need land for 
their production is limited.  

5.6.7.  Other impacts  

This  option  would  be  expected  to  motivate  technological  development.  Firstly,  it  would 
provide very strong incentives for accelerating the introduction of advanced biofuels through 
limiting  the  contribution  of  conventional  alternatives.  Secondly,  it  provides  clear  signals  to 
industry as to what volumes of conventional and advanced biofuels are needed to 2020. 

The option is simple in design and implementation.  

This option does not change the existing calculation methodology and thus it is not likely to 
be  challenged  by  the  WTO.  Moreover,  this  option  does  not  depend  on  modelling  for  the 
design of the policy measure. However, it does not distinguish between feedstocks according 
to their estimated indirect land-use change impacts.  

As emission savings offered by biofuels would not reflect indirect land-use change, biofuels 
would contribute less to the integrated approach for CO2 in cars. As such, larger contributions 
towards  achieving  greenhouse  gas  emissions  savings  will  be  needed  from  energy  efficiency 
and other available technologies.  

5.7. 

Combination  of  option  D  with  C2  -  Attribute  a  quantity  of  greenhouse  gas 
emissions  to  biofuels  reflecting  the  estimated  indirect  land-use  impact  whilst 
providing  exemptions  to  those  biofuels  feedstocks  produced  under  criteria 
covered by option C2. 

The  rational behind  combining option D with option  C2 is that biofuels produced under C2 
requirements  could  be  considered  to  cause  minimal  indirect  land-use  change  impacts  which 
would justify such factors not being applied.  

EN 

63 

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It is difficult to provide an accurate quantification of the impacts arising from this option, as it 
is  not  possible  to  estimate  the  actual  changes  in  biofuels'  supply  compared  to  the  baseline. 
And although this approach remains promising, it is worth noting that currently there are no 
biofuels in the market that have been certified to be compliant with these rules. However, a 
number  of  pilots  to  develop  detailed  methodological  rules  for  the  certification  of  biofuels 
produced are underway.  

5.7.1.  Effectiveness in reducing greenhouse gas emissions 

The  biofuels  that  are  produced  respecting  the  criteria  under  option  C2  would  have  minimal 
risk  of  displacement  effect  and  thus  indirect  land-use  change  emissions122.  A  successful 
implementation  of  this  option  would  therefore  be  expected  to  further  achieve  reductions 
beyond  those  achieved  by  option  D  (40  Mt,  or  85%  of  annual  indirect  land-use  change 
emissions in 2020).  

5.7.2.  Economic impacts 

As  described  in  more  detail  under  Annex  XII,  a  number  of  case  studies  have  shown  that 
production costs will generally not be significantly higher under C2 requirements than current 
practices although these are likely to be project specific.  

On the other hand, there will be higher administrative costs associated with the certification of 
feedstocks  produced  under  C2,  as  additional  proof  of  compliance  to  those  requirements 
already  in  place  under  the  current  system  would  be  required.  Preliminary  data  from  pilots 
carried  out  to  date123  suggest  that  the  additional  costs  for  these  requirements  could  be 
moderate (i.e. 10-15% increase from current certification costs) if they were integrated as part 
of current certification schemes as to maximise audit costs already in place. Costs would be 
expected to be much greater if this certification had to be separated from current process, as it 
would result in duplication of audit costs.  

With  regard  to  investments,  providing  exemptions  to  option  D  is  likely  to  improve  the 
availability  of  conventional  biodiesel  feedstocks  and  so  assist  with  the  viability  of  existing 
investments  in  installed  biodiesel  production  capacity.  Although  this  would  also  help 
maintaining activity in related biodiesel industries such as those involved in the production of 
vegetable oils/crushing of oil crops for all food/feed/biofuels markets, costs may be incurred 
by these industries if their processes need to be adjusted to deal with different feedstocks (i.e. 
rapeseed crushing to soy). In addition, the foreseen application of the grandfathering clause on 
installed capacity could be a useful way of helping with the transition for establishing a robust 
implementation method for the certification and verification of the additional C2 criteria.  

Similarly, the combination of these options would reduce the impacts on trade and is likely to 
increase  imports  of  conventional  biodiesel  feedstocks  into  the  EU.  In  terms  of  WTO 
compatibility, any potential issues related to its reliance on modelling for the determination of 
the factors as mentioned under option D may be reduced by the introduction of the possibility 
to be exempted.  

122 

123 

In the case of "yield increases", only the additional production to the average yield levels assumed in 
the baseline would be considered to have met these additional sustainability criteria.  
Preliminary results from pilots as communicated by the Roundtable for Sustainable Biofuels. Most of 
the cost is based on travel and administration in addition to the auditor time.  

EN 

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5.7.3. 

Social impacts 

The social impact would be as for option D, with the exception that the employment effects 
within the EU for famers will be determined by the degree to which European production can 
be adjusted to these criteria, and how the industry is adapting to the opportunities created by 
exemptions created through option C2.  

5.7.4.  Environmental impacts  

The environmental impacts are expected to be improved further than for option D.  

5.7.5.  Other impacts 

Other impacts would be as for option D. 

EN 

65 

   EN 

 
6. 

COMPARISON OF POLICY OPTIONS 

The table below summarises the main issues related to the different options. 

A
n
o
i
t
p
O

B
n
o
i
t
p
O

1
C
n
o
i
t
p
O

D
n
o
i
t
p
O

Effectiveness 

Advantages 

Disadvantages 

Average  total  of 
savings 
GHG 
(incl. 
estimated 
ILUC) of 22%.  

Biofuel and other related industries' 
investment not affected. Development 
opportunities inside and outside the EU 
not affected.  

ILUC emissions and biodiversity impacts not 
mitigated. No incentives for further technological 
development (i.e. improved GHG savings and/or 
advanced biofuels).  

48  Mt  of  annual 
estimated 
ILUC 
emissions by 2020 
(BAU). 

Average  total  of 
savings 
GHG 
(incl. 
estimated 
ILUC) of 56%.  

14  Mt  of  annual 
ILUC 
estimated 
emissions 
by 
2020.  

Estimated ILUC 
emissions ranging 
between a 
reduction of 
740Mt to an 
increase of 3 Mt 
annual ILUC 
emissions. 

Average total of 
GHG savings 
(incl. estimated 
ILUC) of 70%. 

8 Mt of annual 
estimated ILUC 
emissions by 
2020. 

RED transport targets and FQD are 
achieved according to NREAPS. No 
stranded investments. 

Pressure on vegetable oil prices.  

Estimated ILUC emissions not reported. 

Simple in design and implementation, 
as it is coherent with existing 
methodology. Reported GHG 
performance of biofuels is only 
dependent on action taken by the 
biofuel producers themselves. Does not 
exclude all 1st generation biodiesel. 
Clear incentives for producers to 
improve direct GHG savings. 

Risk of not achieving RED transport target and FQD 
from reduced biofuel availability. Most oil crops 
excluded, including all rapeseed which currently 
represents more than half of the biofuel feedstocks 
used in the EU. This would require industrial 
adjustment. The exclusion of rapeseed with a 
threshold of 60%, and its corresponding 
environmental and GHG impacts, are sensitive to 
technological progress in production pathways. 
Increased administrative costs as certain operators 
need to report actual direct greenhouse gas emission 
performance. Estimated ILUC emissions not 
reported.  

Potentially large emissions savings if 
countries implement good governance 
for land-use, reduce deforestation, and 
limit land-use change emissions from 
other commodities.  

Risk of WTO incompatibility. Potential leakage 
effects as the exclusion of production from certain 
countries can increase distortions and even in some 
cases lead to increased emissions.  

Most efficient in reducing estimated 
ILUC emissions and other 
environmental impacts such as 
biodiversity. Strong incentives for 
development of bioethanol and 
advanced biofuels, particularly 
biodiesel. The option for addressing 
ILUC referred to in the Directives. 
Targets biofuels with high estimated 
ILUC directly, reducing demand for 
such feedstocks. 

High risk of not achieving RED transport target and 
FQD from significant reduction in biofuel 
availability. Policy methodology dependent on 
actions outside the control of biofuel producers. 
Uncertainty for industry due to expected updates of 
ILUC factors. All oil crops excluded, including all 
rapeseed which currently represents more than half 
of the biofuel feedstocks used in the EU. This would 
require major industrial adjustment. 

Potential WTO compatibility issues. 

EN 

66 

   EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
Average total of 
GHG savings 
(incl. estimated 
ILUC) of 44%. 

20 Mt of annual 
estimated ILUC 
emissions by 
2020. 

. 

Improved 
efficiency from D 
expected but not 
possible to 
quantify.  

Efficient  in  reducing  estimated  ILUC 
emissions  and  other  environmental 
impacts such as biodiversity.  

Moderate industrial adjustment required 
to  2020  as  current  production  levels  of 
be 
conventional 
mantained.  

biofuels  would 

Least demanding option with regards to 
the  technical  blending  compatibility  of 
vehicles.  

Very strong incentives for development 
of  advanced  biofuels  and  clarity  for 
future investors. 

No increase in administrative costs. 

As for option D but in addition: 
Increased availability of conventional 
biodiesel and so lower impacts on 
biodiesel and related industries. 
Possibilities for biodiesel derived from 
vegetable oils to supply the EU, which 
increases security of supply compared 
to D. Provides a method under the 
control of biofuel producers to avoid 
uncertainty around ILUC factors.  

E
s
n
o
i
t
p
O

2
C
+
D
n
o
i
t
p
O

Some risk of not achieving RED transport target and 
FQD from reduced biofuel availability.  

Estimated ILUC emissions not reported. No 
difference in treatment across conventional biofuels 
acording to their ILUC impacts.  

As for option D but in addition: Certification 
methodology for production of low ILUC risk 
biofuels remains to be developed. Potentially costly 
and administratively burdensome to comply with 
C2. 

EN 

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   EN 

 
 
 
 
 
 
 
7. 

CONCLUSION 

On the basis of the analytical work presented in this Impact Assessment, it is possible to draw 
a number of conclusions:  

(1) 

(2) 

(3) 

(4) 

the  estimated  indirect  land-use  change  emissions  are,  despite  the  better 
understanding  and  recent  improvements  in  the  science,  vulnerable  to  the 
modelling framework and the assumptions made; 

the  use  of  biofuels  in  the  EU  saves  emissions,  also  when  estimated  indirect 
land-use  change  emissions  are  included.  In  addition,  the  models  indicate  a 
hierarchy of biofuel types according to their indirect land-use change impacts, 
these  being  considerably  higher  for  typical  biodiesel  feedstocks  (oil  crops), 
than for bioethanol feedstocks (cereals, and sugar crops);  

given  the  strong  reliance  on  conventional  biodiesel,  and  to  a  lesser  extent 
conventional bioethanol, in projected biofuel volumes to 2020, there is a high 
risk  that  the  estimated  indirect  land-use  change  emissions  will  significantly 
reduce the expected savings from the policy if no action is taken to mitigate 
indirect land-use change emissions; and; 

the  development  of  advanced  biofuels,  using  low-value  resources  as  straw, 
wood  and  forestry  residues  is  slower  than  previously  expected,  as  the  costs 
associated  with  producing  such  fuels  is  higher  than  the  alternative 
conventional biofuels.  

There are reasonable grounds to believe that indirect land-use change emissions could partly 
undermine  the  greenhouse  gas  savings  offered  by  using  biofuels.  In  application  of  the 
precautionary principle, option A) is therefore discarded. 

Consideration  has  also  been  given  to  options  for  introducing  additional  sustainability 
requirements  on  certain  categories  of  biofuels,  including  certain  actions  that  could  be 
implemented  at  both  country  and  project  level.  With  regard  to  country-wide  sustainability 
criteria,  the  assessment  showed  that  this  option  would  need  to  be  implemented  globally  in 
order to be fully effective. In respect of project level actions, the Impact Assessment showed 
that although biofuels produced under these conditions could be effectively promoted through 
being  considered  as  exemptions  to  the  application  of  ILUC  factors,  these  criteria  are 
insufficiently developed at this time to be included in legislative proposal as no certification 
scheme currently exists. As such, option C) must also be discarded. 

With  regards  to  a  threshold  increase,  as  described  for  option  B),  this  option  would  seem 
effective in reducing indirect land-use change as long as it leads to the replacement of those 
biofuels with estimated high indirect land-use change emissions (i.e. vegetable oils) by those 
with  estimated  low  emissions  (i.e.  cereals,  sugars  and  advanced  biofuels).  However,  the 
effectiveness  of  a  threshold  increase  to  60%  (i.e.  a  reduction  of  indirect  land-use  change 
emissions of 70%, from 46 Mt of CO2-eq./yr to 14 Mt CO2-eq./yr in 2020) would be reduced by 
two thirds if further improvements in the greenhouse gas balance of main vegetable oil crops 
to  levels  which  seem  technologically  feasible,  can  be  achieved.  As  such,  the  uncertainty 
around  the  effectiveness  of  this  approach  would  always  remain  high  unless  much  higher 
thresholds are applied across the board, which would discriminate against biofuels with low 

EN 

68 

   EN 

 
estimated  indirect  land-use  change  emissions.  This  option  in  isolation  has  therefore  been 
discarded. 

Option  D  concerns  the  introduction  of  factors  to  demonstrate  compliance  with  the 
sustainability criteria as well as the reporting of greenhouse gas emissions towards emission 
reduction  targets.  This  would  seem  the  most  effective  option  in  reducing  indirect  land  use 
change emissions (i.e. a reduction of indirect land-use change emissions of 85%, from 46 Mt 
of CO2-eq./yr to 8 Mt CO2-eq./yr in 2020). However, the application of this option in isolation 
would  require  major  industrial  adjustment  which  does  not  seem  achievable  in  the  period  to 
2020.  This  is  because  it  would  require  a)  the  exclusion  of  all  vegetable  oil  biodiesel  which 
today represents the vast majority of the market; b) unrealistic levels of bioethanol given the 
current  blend  limits;  and  c)  unrealistic  levels  of  advanced  biofuels  coming  into  the  market. 
Moreover, the introduction of factors in the sustainability criteria would not take into account 
the  limits  of  the  modelling  in  the  policy  design.  As  such,  the  application  of  this  option  in 
isolation has been discarded.  

The  remaining  option  E,  i.e.  limiting  the  amount  of  conventional  biofuels  counting  towards 
the Renewable Energy Directive transport target to current production levels, would also be 
effective  in  reducing  indirect  land-use  change  (i.e.  a  reduction  of  indirect  land-use  change 
emissions of 55%, from 46 Mt of CO2-eq./yr to 21 Mt CO2-eq./yr in 2020). In addition, this option 
would require moderate industrial adjustment as it would only exclude vegetable oil biodiesel 
beyond  current  production  levels  in  the  run  up  to  2020  and  would  not  necessarily  pose  a 
technical challenge from a blending limit perspective, while providing a strong incentive for 
increasing  the  share  of  advanced  biofuels.  The  incentives  for  producing  advanced  biofuels 
would be strong, as the amount of double counted advanced biofuels would need to increase 
significantly124. Option E thus appears to provide a basis of a suitable way forward.  

This Impact Assessment shows that a balanced approach based on option E, accompanied by 
complementary elements of options B and D and additional incentives for advanced biofuels, 
would  be  the  best  way  to  minimise  estimated  indirect  land-use  change  emissions.  This  is 
because 

(1) 

(2) 

(3) 

option E avoids any additional ILUC-impacts to happen for the period up to 
2020 as it limits the use of conventional biofuels to current production levels, 
while  at  the  same  time  the  targets  for  renewable  energy  of  the  Renewable 
Energy Directive remain achievable; 

it protects existing investments, while giving a clear message that after 2020 
only advanced biofuels will be supported. This provides the needed certainty 
for  new  investments  in  the  sector  as  no  further  changes  would  occur  up  to 
2020; 

it distinguishes between feedstocks according to their estimated indirect land-
use  change  impacts  which  would  be  reported,  thereby  providing  more 
transparency; 

124 

Around  2-3  %  of  the  10%  target  of  double  counted  advanced  biofuels  would  be  needed.  This  is 
equivalent  to  6  to  9  Mtoe.  For  comparison,  the  US  RFS2  is  requiring  36  billion  gallons  by  2022,  of 
which  at  least  16  billion  gallons  have  to  be  advanced  biofuels  from  cellulosic  material.  16  billion 
gallons of ethanol is equivalent to around 30 Mtoe, i.e. an energy quantity similar to what is required to 
reach the 10% transport target of the Renewable Energy Directive.  

EN 

69 

   EN 

 
                                                 
(4) 

(5) 

sustainability  of  biofuels  remains  a  question  of  verifiable  and  measureable 
direct emissions; 

the enhanced incentives and accounting for advanced non-land using biofuels 
to four times the contribution of conventional biofuels will spur development 
of  such  biofuels  with  zero  risk  of  indirect  land-use  change  emissions,  as  no 
land is used for their production.  

Although  it  has  not  been  possible  to  assess  the  effectiveness  of  this  package  of  measures 
under  the  current  methodology,  it  is  expected  to  reduce  indirect  land-use  change  emissions 
significantly.  As  a  minimum,  the  package  of  measures  will  reduce  indirect  land  use  change 
emissions as option E in isolation (55% by 2020). However, it is expected that the additional 
incentives  for  advanced  biofuels  will  lead  to  a  further  shift  away  from  biofuels  with  high 
estimated indirect land-use change emissions.  

In  conclusion  this  combination  would  minimise  the  risks  of  indirect  land-use  change 
emissions,  while  protecting  existing  investments  and,  at  the  same  time,  acknowledging  and 
taking into account in the policy design the limits of the modelling.  

EN 

70 

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8. 

FUTURE MONITORING AND EVALUATION 

The Commission will monitor the impacts of indirect land-use change in the framework of its 
bi-annual reports referred to in Article 23 (1) of the Renewable Energy Directive: 

The  Commission  shall  monitor  the  origin  of  biofuels  and  bioliquids  consumed  in  the 
Community and the impact of their production, including impact as a result of displacement, 
on land-use in the Community and the main third countries of supply. Such monitoring shall 
be  based  on  Member  States’  reports  [..]  and 
third  countries, 
intergovernmental  organisations,  scientific  studies  and  any  other  relevant  pieces  of 
information.  

those  of  relevant 

Related  to  this  and  other  monitoring  and  reporting  requirements  of  the  Renewable  Energy 
Directive,  a  study  for  the  development  of  baseline  data  is  being  carried  out125.  The  first 
Commission report on the basis of this monitoring and analysis is due in 2012. In addition to 
ex-post assessment of impacts, the monitoring would include the development of the scientific 
work on ex-ante estimations of the effects of indirect land-use change. In the context of the 
current understanding of modelling indirect land-use change emissions, including the relative 
importance  of  the  various  parameter  involved  in  estimating  indirect  land-use  change 
emissions, there is a need to monitor a range of elements, including, but not limited to; the use 
of co-products, yield increases  induced by the biofuel  policy,  displacement of cropland  (i.e. 
what  used  to  be  the  land-use  of  the  cropland  where  biofuels  are  now  grown)  and 
developments on protecting high carbon stock land. 

125 

EN 

Tender 
http://ec.europa.eu/dgs/energy/tenders/doc/specifications/2009/s112_160619_specifications.pdf. 

specifications 

available 

71 

at: 

   EN 

 
                                                 
9. 

GLOSSARY  

Advanced biofuel technologies = biofuels typically produced from non-food/feed feedstocks 
such as wastes and residues (i.e. wheat straw, municipal waste), non-food crops (i.e. grasses, 
miscanthus) and algae. Most technologies are at pilot scale or in development. 

Bioethanol  =  alcohol-based  biofuel  typically  produced  from  starch  and  sugar  crops  such  as 
wheat and sugar beet, and used as a petrol additive for its use in motor vehicles. 

Biodiesel  =  oil-based  biofuels  typically  produced  from  vegetable  and  animal  fats,  such  as 
rapeseed oil and tallow, and used as a diesel additive for its use in motor vehicles. 

Biofuels = liquid or gaseous fuel used for transport purposes produced from biomass.  

Bioliquids = liquid fuels used for energy purposes other than transport, including electricity, 
heating  and  cooling,  produced  from  biomass.  These  are  typically  produced  from  vegetable 
oils such as palm and waste oils.  

Biomass = the biodegradable fraction of products, waste and residues from biological origin 
from agriculture (including vegetable and animal substances), forestry and related industries 
including  fisheries  and  aquaculture,  as  well  as  the  biodegradable  fraction  of  industrial  and 
municipal waste. 

Conventionally  produced  biofuels  =  biofuels  typically  produced  from  land  using  feedstocks 
which are also used in other markets (i.e. food and feed). These also include the use of certain 
waste and residues which do not require complex technological processes (i.e. biodiesel from 
used cooking oil or animal fat).  

Direct  land-use  change  =  land-use  change  occurring  directly,  i.e.  mostly  referred  to  in  the 
context of the conversion of land areas to cropland. 

Direct  emissions  from  biofuels  =  greenhouse  gas  emissions  associated  directly  with  the 
production  of  biofuels.  These  may  include  greenhouse  gas  emissions  associated  with  the 
cultivation  and  harvest  of  feedstocks,  with  the  processing  and  production  of  the  biofuel,  its 
transportation, direct land-use change.  

High carbon stock land = Land with large amounts of carbon stored in biomass (trees, grass, 
roots etc.) and/or soil.  

Indirect land-use change = land-use change occurring indirectly i.e. mostly referred to in the 
context  of  land-use  change  as  a  result  of  displaced  demand  previously  destined  for 
food/feed/fibre market as a result of biofuel demand. 

Land-use  change  =  the  conversion  of  land  from  one  use  to  another,  e.g.  from  forestry  to 
cropping. 

EN 

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ACRONYMS 

ACP  African, Caribbean and Pacific States 

AEZ  Agro-environmental zones 

B10 and B30  Diesel blends containing 10% and 30% biodiesel in volume. 

CAP  Common Agricultural Policy 

CARB Californian Air Resources Board 

CEPII  French: Institute for Research on the International Economy 

CFPP  Cold Filter Plugging Point 

CGE  Computable General Equilibrium models 

CHP  Combined heat and power 

CIS  Commonwealth of Independent States (Ex-USSR) 

CO2  Carbon dioxide 

COP  Conference of Parties 

COWI Consultancy within Engineering, Environmental Science and Economics 

CNG  Compressed natural gas 

DDGS Dried Distillers Grains with Solubles 

EBB  European Biodiesel Board 

EC 

European Commission 

EJ 

Exajoule (1018 joules) 

Epure  European Bioethanol association 

ETS  European Emissions Trading Scheme 

EU/EU-27 

European Union 

E10 and E85  Petrol blends containing 10% and 85% bioethanol in volume 

FAME Fatty acid methyl esther  

Fediol  EU Oil and Protein Meal association 

FFC  Fossil fuel comparator 

FLEGT 

Forest Law Enforcement, Governance and Trade 

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FQD  Fuel Quality Directive 

FT 

Fischer-Tropsch 

g 

Grams 

GAEC Good agricultural and environmental condition 

GHG  Greenhouse gas  

GSP+  Generalised System of Preferences 

GTAP  Global Trade Analysis Project 

ha 

Hectare 

HD  High Density 

HPO  Hydrogenated Pyrolisis Oil 

HVO  Hydrotreated Vegetable Oil 

H2 

Hydrogen (referred to in the context of liquid hydrogen as a fuel)  

IEA 

International Energy Agency 

IFPRI  International Food Policy Research Institute 

IPCC  Intergovernmental Panel on Climate Change  

JEC  Consortium  of  JRC,  EURCAR  (the  European  Council  for  Automotive  R&D)  and 
CONCAWE  (the  Oil  Companies’  European  Organisation  for  Environment,  Health  and 
Safety) 

JRC  The Joint Research Centre of the European Commission 

LCFS  Low Carbon Fuel Standard 

LD 

Low Density 

LPG  Liquified Petroleum Gas 

LULUCF 

Land-use, land-use change and forestry 

Mha  Million hectares 

MJ  Megajoule (106 joules) 

MS  Member States of the European Union 

MSA  Mean Species Abundance 

Mt  Million tonnes 

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   EN 

 
Mtoe  Million tonnes of oil equivalent 

NGO  Non-governmental Organisation 

NREAPS 

National Renewable Energy Action Plans 

OWL  Other wooded land 

PBL  Netherlands Environmental Agency 

PE 

Partial Equilibrium models 

Pg 

Petagram (1015 grams) 

Ppm  Parts per million 

RED  Renewable Energy Directive 

REDD+  The  United  Nations  Collaborative  Programme  on  Reducing  Emissions  from 
Deforestation and Forest Degradation in Developing Countries 

RES  Renewable Energy  

RSB  Round Table for Sustainable Biofuels 

TJ 

Terajoule (1012 joules) 

UNFCCC 

United Nations Framework Convention for Climate Change 

UNEP  United Nations Environment Programme 

UK  United Kingdom of Great Britain and Northern Ireland 

US 

United States of America 

WCMC 

World Conservation Monitoring Centre 

WTO  World Trade Organisation 

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10. 

ANNEX I – CONSULTATION AND USE OF EXTERNAL EXPERTISE 

10.1.  Summary of responses from indirect land-use change "pre-consultation" 

The  Commission  sought  public  views  on  possible  approaches  to  address  indirect  land-use 
change  in  a  "pre-consultation"  exercise  between  14  June  and  31  July  2009.  The  approaches 
considered were: 

(a) 

(b) 

(c) 

(d) 

(e) 

(f) 

(g) 

Extend to other commodities/countries the restrictions on land-use change that 
will be imposed on biofuels consumed in the European Union. 

International agreements on protecting carbon-rich habitats. 

Do nothing. 

Increase the minimum required level of greenhouse gas savings. 

Extending the use of bonuses. 

Additional  sustainability  requirements  for  biofuels  from  crops/areas  whose 
production is liable to lead to a high level of damaging land-use change. 

Include an indirect land-use change factor in greenhouse gas calculations for 
biofuels. 

(h) 

Other policy elements that respondents may wish to raise. 

A total of 71 responses were received126, 28% from EU Member States  and third  countries, 
6% from public bodies, and the rest from organisations among which 45% were from industry 
and  businesses,  13%  from  non-governmental  organisations,  and  8%  from  research 
institutions. Most industry, farmers' associations and third countries supported either no action 
or  dealing  with  indirect  land-use  change  through  wider  policy  action  (either  through 
international  action  on  protection  of  high  carbon  stock  land  and/or  extending  sustainability 
criteria  to  all  agricultural  commodities).  Most  NGOs  and  an  industrial  stakeholder  from  the 
non-biofuel  sector  supported  the  inclusion  of  greenhouse  gas  emissions  associated  with 
indirect  land-use  change  within  the  existing  legislative  scheme  for  determining  the 
greenhouse  gas  emission  for  biofuels.  Certain  NGOs  and  research  institutions  supported  to 
lower  the  10%  target  or  set  a  maximum  contribution  conventional  biofuels.  Member  States 
were divided on this issue. 

10.2.  Analytical work 

In order to base its work on the best available scientific evidence, the Commission services 
launched a number of analytical exercises and a review of existing literature on the subject of 
indirect land-use change during 2009 and 2010127,128. 

The  International  Food  Policy  Institute  (IFPRI)  was  commissioned  to  look  at  the  "Global 
trade  and  environmental  impact  study  of  the  EU  biofuels  mandate".  The  final  report  was 
published in October 2011129, and has used the most up to date biofuel demand estimates up 

126 

127 
128 
129 

EN 

responses 

All 
http://ec.europa.eu/energy/renewables/consultations/2009_07_31_iluc_pre_consultation_en.htm. 
http://ec.europa.eu/energy/renewables/studies/land_use_change_en.htm. 
http://re.jrc.ec.europa.eu/bf-tp/html/documents_main.htm. 
http://trade.ec.europa.eu/doclib/docs/2011/october/tradoc_148289.pdf. 

available 

are 

76 

at: 

   EN 

 
                                                 
to 2020 as outlined by the Member States in the national renewable energy action plans130. In 
addition, the study aims to provide a better characterisation of the uncertainty associated with 
the crop specific indirect land-use change emission values.  

A number of other studies were launched by several Commission services: 

– 

– 

– 

– 

"Impacts  of  the  EU  biofuel  target  on  agricultural  markets  and  land-use:  a 
comparative  modelling  assessment",  by 
for  Prospective 
Technological Studies of the EC's Joint Research Centre; 

Institute 

the 

"The  impact  of  land-use  change  on  greenhouse  gas  emissions  from  biofuels 
and bioliquids– an in-house review conducted for DG Energy; 

"Indirect  land-use  change  from  increased  biofuels  demand  –  comparison  of 
models and results for marginal biofuels production from different feedstocks" 
by the EC's Institute for Energy of the Joint Research Centre; 

"Biofuels- a new methodology to estimate GHG emissions from global land-use 
change"  by  the  Institute  for  Environment  and  Sustainability  and  Institute  for 
Energy of the EC's Joint Research's Centre131.  

10.3.  Summary of responses from main indirect land-use change consultation 

Following  the  publication  of  the  relevant  analytical  work  in  July  2010,  the  Commission 
launched  a  second  public  consultation  exercise  between  30  July  and  31  October  2010.  This 
sought  views  on  whether  this  analytical  work  provided  a  good  basis  for  determining  the 
significance of indirect land-use change; whether action was required, and if so what course 
of  action  would  be  appropriate.  It  also  set  out  a  reduced  number  of  possible  policy 
approaches: 

(a) 

(b) 

(c) 

Take no action for the time being, while monitoring impacts including trends in 
certain key parameters and, if appropriate, proposing corrective action later; 

Take action by encouraging greater use of some categories of biofuel; 

Discourage the use of some categories of biofuel by: 

– 

– 

– 

increasing the minimum greenhouse gas saving threshold for biofuels; 

imposing additional sustainability requirements on certain categories of 
biofuel. 

attributing  a  quantity  of  greenhouse  gas  emissions  from  indirect  land-
use change to all biofuels that use land. 

(d) 

Take some other form of action. 

A total of 145 responses were received132 comprising 9% from EU Member States and third 
countries,  2%  from  public  bodies,  and  the  rest  from  organisations  among  which  60%  were 

130 
131 

http://ec.europa.eu/energy/renewables/transparency_platform/action_plan_en.htm. 
In 2011, the JRC carried out additional application of their Spatial Allocation Methodology (SAM) to 
additional IFPRI-MIRAGE-BIOF scenarios. 

EN 

77 

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from  industry  and  businesses,  23%  from  non-governmental  organisations,  and  6%  from 
research institutions.  

Responses fell into two broad groups. Most respondents from industry, farmers' associations 
and  third  countries  considered  that  the  analytical  work  did  not  provide  a  good  basis  for 
determining  the  significance  of  indirect  land-use  change.  They  considered  that  no  further 
action  specific  to  biofuel  policy  should  be  taken,  although  many  supported  action  on 
international agreements towards the protection of land with high carbon stock. On the other 
hand, most NGOs and a few industrial stakeholders from non-biofuel sectors considered that 
further  action  was  needed  and  supported  the  inclusion  of  the  indirect  land-use  change 
emissions  within  the  existing  greenhouse  gas  emission  calculation.  A  number  of  other 
respondents recognised that action may be needed, favouring a variety of other measures, in 
particular options aimed at limiting the amount of conventional biofuels while increasing the 
share  of  advanced  biofuels,  which  were  mainly  favoured  by  NGOs  and  certain  industrial 
stakeholders. 

Member States were divided on this.  

10.4.  External expertise 

Following  this  public  consultation,  in  November  2010  the  JRC  organised  an  expert 
consultation  on  behalf  of  the  Commission,  which  brought  together  world-recognised 
academics  and  experts  in  the  field.  This  consultation  aimed  at  discussing  the  main 
uncertainties related to the estimation of indirect land-use change133. 

In  February  2010,  the  JRC  organized  a  workshop  on  “The  Effects  of  increased  demand  for 
biofuels feedstocks on world agricultural markets and areas” with the participation of leading 
experts and modellers from the EU and US. The workshop discussed the results of the JRC 
modelling comparison study and reasons for differences between models results.  

132 

133 

EN 

responses 

All 
http://ec.europa.eu/energy/renewables/consultations/2010_10_31_iluc_and_biofuels_en.htm. 
All  contributions,  including  the  workshop's  report  "Critical  Issues  in  Estimating  ILUC  Emissions. 
Outcomes  of 
available  via 
http://re.jrc.ec.europa.eu/biof/html/documents_publications.htm. 

an  Expert  Consultation"  EU 

JRC64429, 

report  n. 

available 

are 

are 

at 

78 

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11. 

ANNEX II – THE CONCEPT OF INDIRECT AND DIRECT LAND-USE CHANGE EMISSIONS  

The figure below illustrates in a highly simplified manner how both direct and indirect land-
use change takes place. 

In  this  highly  simplified  example  we  look  at  a  global 
agricultural  system  with  only  grazing  land  and  forest 
land.  At  the  outset  there  is  no  biofuel  production  on 
neither of the two land types. 

The  introduction  of  the  biofuel  production  on  grazing 
land leads to direct land-use change and may cause a loss 
or  an  increase  of  soil  organic  carbon.  If  the  biofuel 
production  is  introduced  onto  the  forest  land,  then  the 
direct  land-use  change  emissions  may  be  large  because 
there is a loss of forest biomass. Both these direct land-
use  change  emissions  are  included  in  the  overall 
greenhouse gas calculation of the produced biofuel (part 
of the sustainability criteria). 

Macro-economic effects cause an increase in the value of 
grazing  animals  (i.e.  meat),  as  less  is  now  being 
produced.  This  creates  an  incentive  to  increase  the 
production  of  meat.  This  can  be  done  through  yield 
increases  (e.g.  more  animals  per  hectare)  or  conversion 
of more land to grazing land. The latter is indirect land-
use  change  and  causes  in  this  example  a  loss  of  forest 
carbon  stocks,  since  grazing  has  now  expanded  into 
forest areas.  

There  is  not  a  one-to-one  relationship  between  the 
pasture/cropland  area  converted  to  biofuel  and  the  area 
converted  to  new  pasture/cropland.  This  relationship 
depends  on  the  relative  productivity  of  the  old  vs.  new 
pasture/cropland,  markets  for  co-products  and  to  what 
extent  the  macro-economic  pressure  induces  increased 
productivity and changes in consumption. 

Figure 8: Examples of direct and indirect land-use changes arising as a consequence of a biofuel project 
(pictures from IEA Bioenergy Berndes et.al. 2010) 

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12. 

ANNEX III – MODEL LIMITATIONS AND UNCERTAINTIES 

12.1.  Economic models to estimate indirect land-use change emissions  

Modelling of indirect land-use change is usually based on an assessment of what the situation 
would have been expected to be without policies promoting biofuels and comparing it with an 
assessment carried out with such policies. Such an assessment can be carried out with more or 
less  degrees  of  sophistication.  Simple  calculations  based  upon  the  land  area  that  biofuel 
demand will, assuming displacement of all crops previously grown, represent the theoretical 
uppermost boundary of the indirect land-use impacts. However, the actual land area required 
is  likely  to  be  much  lower  due  to  constraints  encouraging  higher  levels  of  inputs,  higher 
yields,  the  production  of  co-products  along  with  biofuels  and  the  fact  that  the  higher 
commodity  prices  will  have  a  dampening  effect  on  other  demand  for  the  agricultural 
commodities. A first approximation of these effects can be taken into account in a spreadsheet 
based approach to give an improved understanding of the indirect land-use change although 
there are limitations of such an approach. 

To further improve the understanding of indirect land-use change it is necessary to make use 
of  economic  models  which take account of  price impacts to alter the expected behaviour of 
different parts of the economy. While spreadsheet-models are typically more transparent with 
regard  to  key  assumptions,  and  allow  for  relations  between  parameters  to  be  established 
without  having  regard  to  the  ability  of  the  model  to  solve  all  the  equations  (as  in  a  macro-
economic  models),  they  do  not  capture  important  knock-on  effects  and  feedbacks  between 
sectors, as macro-economic models do. 

There are mainly two groups of macro-economic models that try to capture various feedbacks 
between  economic  sectors.  These  are  "Partial  Equilibrium  models"  (PE)  and  "Computable 
General  Equilibrium  models"  (CGE).  The  former  typically  covers  certain  sectors  of  the 
economy,  which  are  most  relevant  for  the  purpose  of  the  modelling  effort  (e.g.  agricultural 
markets, or energy markets). The CGE models cover the whole economy, although often at a 
coarser resolution than the specific sectors covered by PE models. Often, various PE models 
are interlinked in order to capture broader effects. 

The models that have been employed to estimate changes in domestic and international crop 
acreage have not been used in a regulatory context until recently. Rather they have been used 
to give policymakers an idea of the likely consequences of changes in agricultural and trade 
policy. As a guide to policy development and understanding, these models have proved very 
valuable in facilitating such policy agreements.  

It  is  generally  accepted  that  economic  models  offer  the  best  prospect  of  understanding  the 
scale  and  nature  of  indirect  land-use  change  in  terms  of  land  area  as  well  as  other  impacts. 
However, it is also known that in reality several non-economic factors influence what land-
use  change  takes  place  and  where  it  occurs.  Some  of  these  drivers  are  related  to  political 
choices  (land-use  and  agricultural  policy,  land  rights,  etc.),  others  to  institutional  features 
(proximity  to  infrastructure  and  markets,  land-use  legislation).  Therefore  conceptual 
limitations will always remain.  

Models typically base their assumption on existing correlations, which are based on historical 
trends, and are therefore not capturing potential changes in policies that may take place in the 
future.  They  therefore  have  limitations  and  uncertainties  which  are  further  explained  in  the 

EN 

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next section and which would affect this impact assessment by making it difficult to assess the 
scale of the indirect land-use change phenomena related to biofuels, and the effectiveness and 
efficiency  of  the  policy  options.  Furthermore,  the  risk  of  contra-productive  policies  is 
dependent on the certainty of the science, and to what extent the policies are based on these 
findings.  

12.2.  Why models differ in their results  

Models attempt to describe the reality in various ways. Fundamentally they vary in structure 
(CGE,  PE,  spreadsheet  model  etc.)  coverage  (geographical,  economic  sectors,  time-span), 
data  (carbon  stocks,  transport  demand  etc.)  and  assumptions  on  economic  cause  and  effect 
relations (elasticities, future projections etc.).  

In the context of estimating indirect land-use change emissions, there will always be a range 
of  unsolved  issues,  which  influence  the  results  considerably.  Aspects  where  modelling  is 
based  on  uncertain  assumptions,  that  however  are  likely  to  improve  over  time  as  more 
resources  are  invested  in  data  and  statistical  analysis,  are;  the  treatment  of  co-products134, 
existing  yields135,  marginal  yields136,  type  of  land  converted137,  classification  of  land138, 
elasticities139, carbon stock values140, and the modelling of pasture141.  

Aspects that are likely to still be at the centre of dispute also in the longer run are; the drivers 
of  deforestation  and  the  implied  causality142,  food  and  feed  consumption143,  and  the 
technology response to higher prices144. 

134 

135 

136 
137 

138 

139 

140 

141 

142 

143 

144 

Most biofuel feedstocks co-produce considerable quantities of co-products. Most models do now take 
this  into  account,  although  at  various  ratios,  greatly  influencing  model  results.  Co-products  normally 
replace animal feed, freeing up land that would otherwise be needed for its production. 
Baseline yield increases are normally assumed to continue at historic rates whereas such predictions are 
uncertain. 
There is little empirical evidence on developments of marginal yields.  
The type of land that is converted to cropland has a major influence, as carbon stocks vary considerably 
across  land  types.  Due  to  too  course  spatial  resolution  regional  differences  risk  getting  lost  in  the 
geographical aggregations. 
Land availability and land classification is an essential input for land-use change modelling, however, 
figures and terminology are not consistent across datasets.  
Elasticities  are  often  estimated  on  basis  of  data  from  developed  countries,  while  models  suggest  that 
indirect land-use change typically takes place in developing countries. 
Carbon  stock  values  attributed  to  different  vegetation  and  soils  vary  considerably  across  studies,  and 
play an essential part in determining the indirect land-use change impact. 
Pasture for  animals  covers  large parts of  the  globe,  and offer  potential  supply  of  land for  cultivation. 
However, how pasture is modelled and its interlinkages with feed markets and cropland differ between 
models. The assumptions has major impacts on the overall results, as pasture is covering a large fraction 
of the terrestrial surface, and has relatively low carbon stocks. 
Drivers behind deforestation are complex, where local authorities, land-use rights and political economy 
all play a role. It is not possible to properly reflect this real world effects in the models, where decision 
making is reduced to a purely rational economic question. 
Economic models assume demand being a function of price, with different assumptions as to how the 
additional demand for biofuels will impact on food and feed commodity markets. The feedback from 
lowered oil-price to potential lowered food-price also needs consideration (Recommendations from the 
Food  Consumption 
– 
http://www.arb.ca.gov/fuels/lcfs/workgroups/ewg/010511-final-rpt-food-consumption.pdf). 
Most models include yields to increase as a result of factor increase (labour, fertiliser, capital), but none 
reflect the possibility for technology change in response to higher prices. 

Subgroup  ARB  Expert  Workgroup 

on  Land-use  Change 

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In addition, the Literature review found that current macro economic models145 are incapable 
of capturing a number of factors, including the conversion of forest on peat-land which can 
lead  to  considerable  carbon  emissions.  However,  the  majority  of  such  factors  would,  if 
captured,  reduce  the  estimated  land-use  change  impact.  These  include  the  allocation  of  all 
emissions  to  crop  expansion,  whereas  deforestation  can  be  driven  simultaneously  by  crop 
expansion  and  logging;  rate  of  yield  improvements  in  response  to  increased  demand  for 
biofuels146;  structural  changes147;  and,  the  protein  content  of  various  feeds  and  co-products, 
which is rarely fully reflected148. In addition, the effects of the binding sustainability criteria 
for biofuels in the Directives have not been taken into account.  

The literature review also found that the geographical origin of the feedstock could also be a 
significant variable in estimating the (indirect) land-use change impact of a specific biofuel, 
i.e. whether the origin of the feedstock matters, as most feedstocks can be produced in various 
regions  of  the  world.  However,  none  of  the  modelling  done  so  far  has  explored  this 
variability, which may in fact not be possible with today's models.  

Furthermore,  the  modelling  comparison  study  found  that  current  models  do  not  capture  a 
number of factors, which if taken into account, would increase the estimated land-use change 
impact. These factors include emissions from the conversion of peat-lands149. Moreover, apart 
from (indirect) land-use change emissions as discussed in this report, models do not consider 
at least two additional sources of increased emissions: the emissions from yield intensification 
due to crop price rises, and the extra emissions from growing crops on marginal land rather 
than on existing cropland.  

The uncertainty in modelling indirect land-use change led the Commission to ask the JRC to 
organize a workshop with leading indirect land-use change experts to try to explore the main 
uncertainties. The workshop was held in November 2010150. The main topics being discussed 
were;  cropland  allocation  (including  amount  of  expansion  on  peatland),  emissions  factors 
(including emissions from peatland), yield developments (including marginal yields), as well 
as the influence of reduced food consumption and how pasture land interacts with cropland. 
The workshop also discussed briefly the various policy options.  

In the last results from the IFPRI-MIRAGE-BioF, there have been attempts to address these 
concerns. Most notably: 

• 

145 

146 

147 

148 

149 

150 

Peatland  emissions,  both  in  terms  of  the  fraction  of  expansion  taking  place  on 
peatland, as well as the emissions from drainage. 

The  literature  review  did  not  analyse  spreadsheet  models,  as  very  few  were  published  at  the  time  of 
writing. 
Increased  yields  are  a  function  of  a  complex  set  of  variables,  among  them  increased  investment  and 
research, both of which take place as a response to the biofuel policy. It is however difficult to capture 
this effect in the models.  
Structural changes are typically difficult to predict by models as elasticities are based on historical data. 
Considerable  increase  in  use  of  land  in  e.g.  CIS  is  therefore  unlikely  according  to  the  models,  while 
such a structural change could take place both in the baseline and in the policy scenario. 
This is underestimating the land saved by co-products. For example, in the EU soy meal is a key source 
of protein, of which around 97% is imported. There is thus considerable scope of substitution. 
Many models do not properly take into account the emissions from peat oxidation following drainage 
process required in the cultivation of palm oil, which could underestimate real emissions by an order of 
magnitude.  Although  the  estimated  emissions  from  peatlands  have  been  adjusted  upwards  in  recent 
modelling, the uncertainty as to what the value should be remains. 
Presentations 
the  workshop 
tp/html/documents_main.htm. 

http://re.jrc.ec.europa.eu/bf-

found 

here: 

from 

can 

be 

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• 

• 

Food demand is more inelastic 

More co-products from cereals are able to replace meals from oilseeds.  

However,  a  number  of  issues  remain.  ATLASS  highlights  some  of  them  in  the  final  report, 
noting  that  "the  model  has  tested  the  limits  of  the  CES/CET  (constant  elasticity  of 
supply/transformation) framework. Both for co-products but also for land-use allocation, this 
conventional modeling approach leads to too many simplifications. For co-products, the two 
level CES approach has helped to reinforce the substitution at the protein contents between 
meals  and  DDGS.  Unfortunately,  it  has  also  forced  to  simplify  the  representation  of 
substitution  between  proteins  and  carbo-hydrates.  Similarly  for  land-use,  even  if  our  multi-
nested  CET  has  helped  to  capture  substitution  between  crops,  it  is  not  flexible  enough  to 
provide  the  right  full  substitution  matrix  across  crops.  More  important  from  a  long  run 
perspective,  it  is  not  designed  to  capture  issues  such  as  multi-cropping  and  crop  rotation, 
both important issues for land-use considerations in a dynamic approach".  

It is also worth noting that the elasticity of substitution and transformation were taken from 
the – limited – estimates in the literature. The same elasticity of substitution was assumed for 
all  crops  and  all  countries.  To  what  extent  these  elasticities,  which  are  based  on  a  limited 
numbers  of  sources  in  the  literature,  are  valid,  and  more  importantly  represents  the  likely 
development towards 2020 remains an open question. In addition, the sensitivity analysis on 
the  demand  side  has  been  limited  (rigid  food  demand,  changes  in  price  elasticities  of 
intermediate demands). This is key for certain crops, such as cereals, as a large share of their 
additional production for biofuels is assumed not to be replaced, which would result in higher 
indirect land-use change impacts if this was not the case.  

12.3.  How can indirect land-use change emissions estimates be negative? 

It  is  worth  noting  that  one  of  the  most  recent  spreadsheet  models  (E4tech)  suggest  that  the 
likely  indirect  land-use  change  values  for  wheat  ethanol  range  from  -53  to  -5.1  g/MJ  (-5.1 
g/MJ  being  identified  as  the  most  likely  scenario).  These  surprising  results  are  identified  in 
the report to be the result of the large credits given to wheat ethanol by assuming that its co-
products are replacing soy being grown in Argentina and Brazil for animal feed purposes, to 
which the same study allocates high land-use change emissions of around 55 g/MJ.  

However, some of the assumptions made by this report around the rate of land abandonment 
in the EU, the amount of carbon lost to foregone sequestration by this land, assumptions on 
the  yields  on  this  land,  and  how  much  land  would  come  from  yield  increases  and  not  area 
increases  have  been  questioned.  Although  negative  results  are  rare,  they  can  also  be  the 
results from estimating indirect land-use change emissions with macro-economic models, as 
can  be  seen  in  the  Monte  Carlo  results  shown  in  Annex  XI  where  sugar  beet  has  negative 
indirect  land-use  change  emissions  at  one  of  the  extremes  of  the  probability  distribution 
range. 

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13. 

ANNEX  IV  –  RESULTS  FROM  ESTIMATING  INDIRECT  LAND-USE  CHANGE  WITH 
MODELS 

13.1.  Total indirect land-use change emissions 

To understand the overall size of total indirect land-use change emissions associated with the 
additional  biofuel  demand,  various  scenarios  were  modelled  in  2009  using  the  general 
equilibrium  IFPRI-MIRAGE-BioF  model  and  the  partial  equilibrium  AGLINK-COSIMO 
model.  Although  only  the  IFPRI-MIRAGE-BioF  model  was  able  to  directly  estimate  the 
overall  greenhouse  gas  emissions  resulting  from  the  modelled  land  requirements,  the  JRC 
have  estimated  these  impacts  through  the  application  of  their  newly  developed  Spatial 
Allocation Model. A further run of the IFPRI-MIRAGE-BioF model was carried out in 2011 
based  on  the  2020  biofuel  estimates  submitted  by  the  National  Renewable  Energy  Action 
Plans (results are included in this section for comparison and are described in more detail in 
the baseline section of section 2).  

The  total  estimated  land  requirements  from  the  additional  demand  (i.e.  change  between  the 
projected 2020 levels with the policy and those presumed in the absence of no biofuels policy) 
as well as the key assumptions are summarised in the table below. 

MODEL 

Change 
in 
volume [%]a 

Bioethanol 
vs Biodieselb 

(I)LUC  area 
(Mha) 

Total  GHGc 
(Mt CO2eq)  

Total  GHGc 
(JRC  SAM) 
(Mt CO2eq) 

2.3 

87/13 

0.8-1 

107-118 

201-248 

5.2 

60/40 

2.8-3 

435-454 

731-806d 

5.7 

28/72  

1.7-1.9 

500d 

421-472d  

5.4 

35/65 

5.2 

n/a 

1092 

IFPRI-
MIRAGE-
BioF (5.6%) 

IFPRI- 
MIRAGE- 
BioF (8.6%) 

IFPRI- 
MIRAGE-
BioF 
(NREAPs) 

AGLINK-
COSIMO 
(7%) 

Table 12: Summary of overall GHG impacts from (indirect) land-use change. Source: IFPRI-MIRAGE-
BIOF and JRC. 
a Change in conventional biofuels demand as % of EU 2020 transport fuel consumption. 
b Estimated mix of bioethanol vs biodiesel in the additional demand. 
c Emissions from Business as Usual and Free trade scenarios. 
d Including peat emissions. 

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MODEL 

IFPRI-
MIRAGE-BioF 
(5.6%) 

IFPRI- 
MIRAGE-BioF 
(8.6%) 

IFPRI- 
MIRAGE-BioF 
(NREAPs) 

AGLINK-
COSIMO (7%) 

Original model  18 

JRC SAM 

34-41 

31-33 

53-58 

24-50 

32-36 

n/a 

63 

Table 13: Summary of average greenhouse gas impacts from (indirect) land-use change (gCO2eq /MJ). 
Source: ATLASS and JRC 

The  differences  between  the  IFPRI-MIRAGE-BioF  runs  are  driven  by  the  different 
bioethanol/biodiesel  composition  and  overall  mandate  volume  as  described  in  table  13.  In 
addition, peat land emissions were underestimated compared to current values.  

13.2.  Marginal indirect land-use change values for feedstocks 

To better understand whether indirect land-use change emissions are similar across different 
biofuel  pathways  or  differ  between  feedstocks,  a  modelling  assessment  of  the  indirect  land-
use change caused by individual types of biofuels was carried out. The IFPRI-MIRAGE-BioF 
model  was  used  to  determine  values  for  additional  volumes  of  biofuels  based  on  different 
feedstocks. The resulting indirect land-use change values from this were as shown in table 14 
below. 

Ethanol 

Biodiesel 

Sugar 
Cane 

Sugar 
Beet 

Maize  Wheat 

Palm 
oil 

Rapese
ed oil 

Soy 
oil 

Sunflo
wer oil 

18 

16 

54 

37 

46 

53 

75 

60 

14 

7 

10 

14 

54 

54 

56 

52 

22-26  5-6 

13-14 

16-17 

21-45  43-53 

44-53  51-59 

IFPRI- 
MIRAGE-BioF 
(5.6%) 

IFPRI- 
MIRAGE- 
BioF 
(NREAPS) 

JRC-SAM 
(from 
IFPRI-
MIRAGE-BioF 
NREAPs 

Table 14: Summary of IFPRI-MIRAGE-BioF marginal (indirect) land-use change emissions (gCO2eq 
/MJ). Source: IFPRI-MIRAGE-BioF and JRC. 

As it can be seen from the table, models tend to allocate different (indirect) land-use change 
emissions to different feedstocks. This is one of the reasons that average emissions in table 14 
vary according to the overall feedstock composition predicted in the final mix.  

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At the crop level, we see much larger differences due to the fact that some parameters have 
been  altered  between  the  studies  (i.e.  new  yields,  increased  displacement  potential  between 
crops,  better  replacement  ratio  for  co-products),  as  well  as  the  method  used  to  compute  the 
crop  LUC  now  being  based  on  a  much  larger  share.  In  addition,  it  is  worth  noting  that  the 
authors  consider  some  of  the  new  key  assumptions affecting  the cereal  crops to  be  strongly 
optimistic, including very high yields for wheat in the EU, and maize in the US and Brazil. 
This is important as these variations have not been included in the sensitivity analysis but play 
a significant role in the estimation of indirect land-use change emissions.  

The difference between biodiesel crops and ethanol crops has increased. For nearly all crops, 
except palm oil due to the increase in peat emissions, the estimated indirect land-use change 
emissions have been reduced, when one compares results from IFPRI-MIRAGE-BIOF from 
2010 and from 2011. Estimated indirect land-use change emissions for soybean has been cut 
by half while maize has been cut by five. However, the ranking between feedstocks remains 
the same (sugars being the best and oilseeds the worst). 

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14. 

ANNEX V – THE IFPRI-MIRAGE-BIOF MODEL: ASSUMPTIONS AND RESULTS  

14.1.  The principles of the MIRAGE model 

The MIRAGE model was initially developed at CEPII. This section summarizes the features 
of  the  standard  version  relevant  for  this  study.  MIRAGE  is  a  multisector,  multiregion 
Computable General Equilibrium (CGE) Model for trade policy analysis. The model operates 
in  a  sequential  dynamic  recursive  set-up:  it  is  solved  for  one  period,  and  then  all  variable 
values,  determined  at  the  end  of  a  period,  are  used  as  the  initial  values  of  the  next  one.  In 
order  to  evaluate  the  impact  of  public  policies  regarding  first  generation  biofuels,  ATLASS 
has  developed  an  extended  version  of  the  global  CGE  MIRAGE,  nicknamed  IFPRI-
MIRAGE-BioF,  by  improving  the  standard  version  in  several  directions.  A  detailed 
description  of  this  version  of  the  model  is  provided  in  Bouët  et  al.  (2010)151  and  in  other 
studies (Al-Riffai, Dimaranan, and Laborde 2010a)152. 

The MIRAGE model relies on the Global Trade Analysis Project (GTAP) database for global, 
economy-wide  data.  The  GTAP  database  combines  domestic  input-output  matrices  which 
provide details on the intersectoral linkages within each region, and international datasets on 
macroeconomic aggregates, bilateral trade, protection, and energy. We started from the latest 
available database, GTAP 7, which describes global economic activity for the 2004 reference 
year in an aggregation of 113 regions and 57 sectors (Narayanan and Walmsley, 2008). The 
database  was  then  modified  to  accommodate  the  sectoral  changes  made  to  the  IFPRI-
MIRAGE-BioF  model.  Twenty-three  new  sectors  were  carved  out  of  the  GTAP  sector 
aggregates  --  the  liquid  biofuels  sectors  (an  ethanol  sector  with  four  feed-stock  specific 
sectors,  and  a  biodiesel  sector),  major  feedstock  sectors  (maize,  rapeseed,  soybeans, 
sunflower,  palm  fruit  and  the  related  oils),  co-  and  by-products  of  distilling  and  crushing 
activities, the fertilizer sector, and the transport fuels sector. This process did not consist of a 
simple disaggregation of parent sectors, but required a full rescaling of agricultural production 
data  according  to  FAO  statistics  on  quantity  and  prices,  harmonization  of  prices  on 
substitutable  homogenous  goods  such  as  biofuels  or  vegetable  oils,  and  bottom-up 
reconstruction of production costs for biofuel sectors and crushing sectors for oilseeds.  

Goods are consumed by final consumers (public and private agent) and firms or are exported 
to foreign markets. The final consumption demand system is represented through a LES-CES 
that  is  recalibrated  each  year  along  the  baseline  to  reproduce  consistent  income  and  price 
elasticities. Imported goods are differentiated from domestic goods following the Armington 
assumption, which allows us to distinguish different levels of market integration. The sector 
sub-utility  function  used  in  MIRAGE  is  a  nesting  of  four  CES  functions.  In  this  study, 
Armington elasticities are drawn from the GTAP 7 database and are assumed to be the same 
across  regions.  But  a  high  value  of  Armington  elasticity,  i.e.  10,  is  assumed  for  all 
homogenous sectors (single crops, single vegetal oils, ethanol). For biodiesel, we assume the 
same elasticity as that for other fossil fuels. 

151 

152 

Bouët,  A.,  Dimaranan,  B.  V.  and  Valin,  H.  (2010),  Modeling  the  global  trade  and  environmental 
impacts  of  biofuel  policies,  IFPRI  Discussion  Paper  (01018),  International  Food  Policy  Research 
Institute. 
Al-Riffai, P., Dimaranan, B. and Laborde, D. (2010), Global Trade and Environmental Impact Study of 
the  EU  Biofuels  Mandate,  Final  Report  for  the  Directorate  General  for  Trade  of  the  European 
Commission, International Food Policy Research Institute.  

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From the supply side in each sector, the production function is a Leontief function of value-
added  and  intermediate  inputs:  one  output  unit  needs  for  its  production  x  percent  of  an 
aggregate  of  productive  factors  (labor,  unskilled  and  skilled;  capital;  land  and  natural 
resources)  and  (1  –  x)  percent  of  intermediate  inputs.  The  intermediate  inputs  function  is  a 
nested system of CES function of all goods: it means that substitutability exists between two 
intermediate  goods,  depending  on  the  relative  prices  of  these  goods.  This  substitutability  is 
constant  and  at  the  same  level  for  any  pair  of  intermediate  goods.  Particular  care  has  been 
paid  in  the  final  and  intermediary  consumption  nesting  to  the  substitution  possibilities  of 
similar products on the one side (vegetable oils, oilseed meals, ethanol feedstocks) and to the 
rigidity relative to certain inputs in the production chain (vegetable oil to produce biodiesel, 
sugar  raw  products  to  produce  refined  sugar,  etc).  Similarly,  in  the  generic  version  of  the 
model, value-added is a constant elasticity of substitution (CES) function of unskilled labor, a 
logistic bundle of land and intensification inputs (fertilizer for crops, feedstuff for livestock), 
natural  resources,  and  of  a  CES  bundle  of  skilled  labor  and  capital.  This  nesting  allows  the 
modeler to introduce less substitutability between capital and skilled labor than between these 
two and other factors. In other words, when the relative price of unskilled labor is increased, 
this  factor  is  replaced  by  a  combination  of  capital  and  skilled  labor,  which  are  more 
complementary.  

Moreover, the model relies on many features specifically introduced to adequately represent 
the effects of biofuel policies. In particular, it includes a detailed description of the insertion 
of  biofuel  in  the  consumption  chain,  a  modeling  of  binding  incorporation  mandates,  and  a 
representation of co-products production for the bioethanol sector by type of pathway (wheat, 
corn,  sugar  beet)  and  for  the  four  oilseed  processing  sectors  that  have  been  explicitly 
introduced (rapeseed, soybean, sunflower, and palm fruit).  

Factor endowments are fully employed.  The  only factor whose supply is constant is natural 
resources.  Capital  supply  is  modified  each  year  because  of  depreciation  and  investment. 
Growth  rates  of  labor  supply  are  fixed  exogenously.  Skilled  labor  is  the  only  factor  that  is 
perfectly  mobile.  Installed  capital  and  natural  resources  are  sector  specific.  New  capital  is 
allocated among sectors according to an investment function. Unskilled labor is imperfectly 
mobile between agricultural and nonagricultural sectors according to a constant elasticity of 
transformation  (CET)  function:  unskilled  labor’s  remuneration  in  agricultural  activities  is 
different  from  that  in  nonagricultural  activities.  This  factor  is  distributed  between  these  two 
series of sectors according to the ratio of remunerations.  

To capture the interactions between biofuels production and land-use change, the model has 
specific  features  focusing  on  a  decomposition  of  land-use  and  land-use  change  dynamics. 
Land  resources  are  differentiated  between  different  agro-environmental  zones  (AEZ).  The 
possibility of extension in total land supply to take into account the role of marginal land (and 
potential lower yield) is also introduced. The modelling of land-use change captures both the 
substitution  effect  involved  in  changing  the  existing  land  allocation  to  different  crops  and 
economic  uses,  and  the  expansion  effect  of  using  more  arable  land  for  cultivation.  Land 
allocation decision across crops, pasture and managed forest is based on a three level nested 
CET  structure.  Land  extension  into  pristine  environment  is  based  on  an  elastic  land  supply 
function, depending on the cropland price and having an elasticity decreasing with the amount 
of suitable agricultural land potentially available. 

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With  regard  to  yields  projections,  the  ATLASS  consortium  based  them  on  the  2010  new 
baseline  of  the  Aglink-Cosimo  used  in  the  Agricultural  Outlook  of  DG  AGRI's  forecast. 

Maize 

Palm-
Fruit 

Rape
-seed 

Soy-
beans 

Sugar 
beet/cane 

Sun-
flower 

Wheat 

EU27 

Brazil 

8.1 

10.5 

41.4 

Central America and Caribbean countries 

3.0 

China 

Commonwealth  of  Independent  States 
(inc Russia) 

Indonesia/Malaysia 

Other Latin America countries 

6.8 

5.2 

5.0 

5.7 

Rest of OECD (inc. Canada & Australia) 

11.6 

26.1 

36.4 

34.1 

26.0 

6.4 

4.7 

6.6 

6.8 

2.4 

13.7 

7.7 

20.5 

Rest of the World 

Sub-Saharan Africa 

USA 

World 

3.9 

3.5 

2.5 

1.9 

2.6 

2.4 

2.6 

1.9 

2.7 

2.8 

1.9 

3.5 

4.7 

2.3 

1.4 

1.9 

3.2 

3.4 

2.0 

2.0 

2.7 

2.9 

70.4 

96.7 

121.0 

146.0 

54.2 

94.5 

120.1 

129.3 

130.7 

99.5 

84.9 

108.4 

2.3 

3.1 

2.1 

2.2 

1.8 

2.9 

2.0 

1.7 

1.6 

2.1 

8.0 

5.0 

5.2 

5.4 

2.6 

3.8 

2.4 

4.9 

3.1 

3.9 

4.3 

Table 15: Yields. tonnes per Ha. 2020. Baseline. Source: IFPRI-MIRAGE-BIOF (2011) (Sugar cane and 
sugar beet according to region where it grows; i.e. sugar beet in the EU and sugar cane in Brazil) 

14.2.  More results from IFPRI-MIRAGE-BioF  

The global effects of changing land-uses are shown in an informative manner in table below, 
where the amount of displaced land per TJ of biofuels is shown. The columns are indicating: 

Explanation 

Column 1 

Column 2 

Column 3 

Amount of land needed to produce 1 TJ of biofuel using the specific 
feedstock indicated. 

Amount of land changed to energy crops as a result of using 1 TJ of 
the biofuel feedstock.  

Change in total amount of cropland. This amount of land will have to 
be converted from managed or unmanaged (natural) land 

Column 4 

Change in total amount of pasture 

Column 5 

Change  in  total  amount  of  exploited  land  (i.e.  land  not  previously 
used like primary forest) 

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Column 1 

Column 2 

Column 3 

Column 4 

Column 5 

Scenario 
Feedstock 

Net 
Crops 

Energy 

Net 
Cropland 

Pasture 

Net  Exploited 
Land 

Biodiesel_PalmFruit 

EU27 

World 

Biodiesel_Rapeseed 

EU27 

World 

Biodiesel_Soybean 

EU27 

World 

Biodiesel_Sunflower 

EU27 

World 

Ethanol_Beet 

EU27 

World 

Ethanol_Cane 

EU27 

World 

Ethanol_Maize 

EU27 

World 

Ethanol_Wheat 

EU27 

World 

3.89 

4.42 

10.91 

0.14 

11.61 

4.28 

13.59 

5.34 

5.75 

2.40 

6.52 

3.27 

7.64 

0.35 

5.74 

2.94 

11.72 

0.77 

11.41 

2.53 

12.42 

2.23 

2.97 

0.01 

2.70 

1.13 

3.69 

1.77 

4.99 

0.08 

1.97 

0.51 

3.90 

0.10 

3.86 

0.33 

4.90 

0.17 

0.41 

0.03 

1.48 

0.08 

0.88 

0.17 

1.39 

-0.01 

-0.91 

-0.10 

-1.39 

-0.02 

-1.50 

-0.06 

-2.04 

-0.05 

-0.13 

-0.01 

-0.88 

-0.02 

-0.40 

-0.04 

-0.54 

0.03 

0.12 

0.14 

0.64 

0.03 

0.76 

0.09 

0.71 

0.02 

-0.13 

0.00 

0.15 

0.01 

0.00 

0.03 

0.10 

Table 16: Global effects of changing land-use in amount of displaced land per TJ of biofuels 

The table above shows that of the additional land needed to produce 1 TJ of biofuels (column 
1),  only  a  fraction  is  needed  in  terms  of  additional  cropland  (column  3)  and  out  of  the 

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additional  cropland  an  even  smaller  fraction  comes  from  natural  areas  (primary  forests  and 
grassland – column 5). Note e.g. that 1 TJ of maize does not take any new unused land into 
production,  while  sugar  beet  returns  0.11  ha  back  to  natural  areas.  Rapeseed  and  soy  bean 
and sunflower are the crops that takes the most new land into production, with aroud 0.8 ha 
per TJ of biofuel.  

However, it is not only the amount of land that is important, but also what amout of carbon 
stock  is  on  that  particular  land.  These  aspects  are  shown  in  the  figure  below,  indicating  the 
balance between amount of land needed by certain crops (column 3 above), and the average 
carbon stock of that land. 

Figure 9: Amount of land converted, and the corresponding carbon stock. Source: IFPRI-MIRAGE-BIOF 

The figure below is showing the relation between cropland expansion (column 3), compared 
to additional exploited land (natural land – primary forest and grassland – column 5). One can 
observe  that  most  of  the  expansion  takes  place  into  managed  forest  and  pasture,  since  the 
changes in these two land-uses explains the gap between exploited land and crop land. 

Figure 10: Cropland extension versus exploited land extension [Km2]. Source: IFPRI-MIRAGE-BIOF 

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15. 

ANNEX VI – FOSSIL FUEL COMPARATOR 

The  Joint  Research  Centre  (JRC)  has  calculated  the  expected  fossil  fuel  comparator  (FFC) 
used in this impact assessment. It is estimated to be 90.3 g/MJ. The main assumptions are set 
out below. 

The  extraction  emissions  for  existing  oilfields  gradually  rise  with  time  because  the  energy 
needed to extract the crude increases. The resulting average production emissions from fields 
supplying  EU  in  2020  are  expected  to  reach  6.8  gCO2/MJ  crude,  or  7.2  g/MJ  final  fuel, 
ignoring any potential effect of the Fuel Quality Directive. 

Updated figures from Concawe suggest that the production (upstream emissions) greenhouse 
gas intensity (not including transport) is 5.6 g/MJ final fuel. The 2020 gasoline value would 
become 87.6-5.6+7.2 = 89.2 and the 2020 diesel value becomes 89.1-5.6+7.2 = 90.7 

If the diesel/gasoline split is 75:25 the weighted average is 90.3 g/MJ final fuel. 

The assumed baseline for calculating the contributions to the Fuel Quality Directive is set at 
88.3 g/MJ which is a weighted average of fossil fuels used in the EU in 2008.  

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16. 

ANNEX VII – TRENDS IN LAND-USE- AVAILABILITY AND EXPANSION GLOBALLY  

16.1.  Land-use change emissions 

Land-use  change  and  the  use  of  fossil  fuels  are  the  main  contributors  to  anthropogenic 
greenhouse  gas  emissions.  The  figure  below  shows  the  accumulated  anthropogenic  carbon 
emissions  to  the  atmosphere  since  1850.  Land-use  change  emissions  –  primarily  associated 
with the conversion of forests to agricultural land – have contributed roughly one-third during 
this period, with land-use change's share of the total diminishing over the last decades.  

Figure  11:  Accumulated  anthropogenic  carbon  emissions  to  the  atmosphere  since  1850.  Source:  IEA 
Bioenergy Berndes et.al. 2010 

In the next decades it is foreseen that a higher world population and standards of living will 
lead to increasing demand for food, feed, energy and fibre from the earth's ecosystems. Global 
agricultural  production  must  increase  by  70  percent  –  almost  100  percent  in  developing 
countries  –  by  2050  to  feed  the  world’s  forecast  9.1  billion  people,  and  current  levels  of 
investment  are  not  enough  to  reach  these  levels.  FAO  estimates153  that  net  investments  to 
agriculture must top USD 83 billion per year – up roughly 50 percent from current levels – to 
meet  future  demand154.  Furthermore,  in  developing  countries,  one  fifth  of  the  increase  in 
production  will  come  from  increase  in  agricultural  land  and  four  fifths  from  improved 
productivity  on  existing  land.  The  increased  use  of  biofuels  in  the  EU  adds  to  this  existing 
demand for agricultural commodities155.  

16.2.  Trends in land availability globally 

153 
154 
155 

http://www.fao.org/fileadmin/templates/wsfs/docs/expert_paper/How_to_Feed_the_World_in_2050.pdf 
FAO Investment Centre website: http://www.fao.org/tc/tci/whyinvestinagricultureandru/en/. 
This  is  also  clear  from  the  modelling  referred  to  in  the  chapters  below,  where  the  overall  land-use 
change in the baseline (what would happen without a policy promoting biofuels in the EU) is 20 times 
larger than then additional land-use change caused by biofuels. 

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The  extent  to  which  land  availability  is  limited  in  various  regions  of  the  world  is  much 
debated.  Figure  5  below156  depicts  the  harvested  area  in  different  regions  of  the  world. 
Compared  to  1981  the  harvested  land  has  significantly  declined  in  Europe,  CIS  and  North 
America, thus suggesting that there would be low carbon stock land available157. 

The time-series is divided into three segments, where distinct trends can be observed: 

• 

• 

• 

1961  –  1981  (20  years)  harvested  area  increases  rapidly  with  roughly  150  million 
hectare (Mha) globally (on average 7.4 Mha per year). 

1981  –  2001  (20  years)  harvested  area  increases  slowly  with  56  Mha  globally  (on 
average 2.8 Mha per year). 

2001 – 2008 (7 years) harvested area increases rapidly with 95 Mha (13.6 Mha per 
year) 

It is worth to note that the rapid increase in harvested area seen for the period 2001 – 2008 has 
not been continued into 2009, when harvested area actually decreased by -1.2 Mha. However, 
this  might  be  the  result  of  the  economic  crises  unfolding  in  2008,  as  farmers  responded  to 
reduced  demand.  Countries  taking  part  in  the  global  agricultural  trade  had  the  steepest 
decrease with e.g. 2.6 Mha less area harvested in North America.  

Globally harvested area (FAOSTAT)

East and South Asia

]
a
h
M

[
e
r
a
t
c
e
h
n
o

i
l
l
i

M

500

450

400

350

300

250

200

150

100

50

0

Eastern Europe and CIS

Latin America and
Caribbean

North Africa and West Asia

North America

Northern, Western and
Southern Europe

Oceania

South-East Asia

Sub-Saharan Africa

1961

1981

2001

2009

Figure 12: Globally harvested area from 1961 to 2009 

156 

157 

FAO  Statistics.  Note  that  there  is  an  important  difference  between  "harvested  area"  and  "cultivated 
area".  Double-cropping  in  a  field  would  double  the  amount  of  harvested  area,  while  cultivated  area 
remains constant.  
However, if it is the least fertile land that has been recently abandoned, then its future production could 
be  expected  to  show  typical  yields  below  average,  leading  to  either  increased  land  requirements  or 
increased  use  of  fertilisers.  In  addition,  if  the  land  is  under  a  process  of  managed  reforestation,  its 
reversion to agricultural production could result in the release of carbon emissions. 

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With  regard  to  the  EU,  DG  AGRI  has  estimated  that  the  EU  will  continue  to  reduce 
agricultural area with around 0.5 million ha each year. 

2010 

Cereals 

56.3 

which 

of 
EU-15 

34.3 

which 

of 
EU-12 

22.0 

Soft wheat 

23.0 

Durum 
wheat 

2.9 

2012 

57.1 

34.8 

2014 

57.4 

34.9 

2016 

57.8 

35.1 

2018 

58.0 

35.3 

2020 

58.3 

35.4 

22.3 

22.5 

22.7 

22.8 

22.9 

23.3 

2.9 

23.4 

2.8 

23.7 

2.8 

23.8 

2.8 

24.0 

2.8 

Barley 

12.4 

12.8 

12.8 

12.7 

12.7 

12.7 

8.3 

2.6 

7.3 

10.9 

6.0 

5.0 

7.0 

3.6 

0.3 

1.4 

1.1 

8.5 

2.6 

7.3 

11.0 

6.0 

5.0 

7.1 

3.5 

0.3 

1.4 

1.0 

8.7 

2.6 

7.2 

11.0 

6.0 

5.0 

7.1 

3.5 

0.4 

1.4 

1.0 

9.0 

2.5 

7.2 

11.0 

6.0 

5.0 

7.2 

3.4 

0.4 

1.4 

1.0 

9.2 

2.5 

7.1 

11.1 

6.0 

5.0 

7.3 

3.4 

0.4 

1.3 

1.0 

69.8 

70.5 

70.8 

71.2 

71.4 

71.6 

188.3 

187.2 

186.1 

185.0 

183.9 

182.8 

Maize 

Rye 

Other 
cereals 

8.1 

2.6 

7.3 

Oilseeds 

10.9 

which 

of 
EU-15 

5.9 

which 

of 
EU-12 

5.0 

Rapeseed 

6.9 

Sunseed 

3.7 

Soyabeans 

0.4 

Sugar beet 

1.4 

1.1 

Protein 
crops 

Total 
selected 
arable 
crops 

Total 
utilized 
agricultural 
area 

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Table 17: Area under arable crops in the EU, 2009-2020 (million hectare) Source DG AGRI 
There  are  also  estimates  of  marginal  land158  that  is  available  for  bioenergy  production. 
Hoogwijk (2003; 2004 cited in Hennenberg et.al (2010)) estimates that between 430 and 580 
Mha  of  land  is  marginal  and  can  potentially  be  used.  However,  Okoinstitut  in  the  report 
"Sustainable Biomass Production from degraded lands" (Hennenberg et.al (2010)) concluded 
that it is very challenging to quantify the amount of degraded land available, while at the same 
time suggesting that the estimates done by Hoogwijk are at least 10-times too high.  

16.3.  Trends in agricultural land expansion 

Although land is available it is not necessarily the case that the marginal supply of agricultural 
crops  is  planted  on  marginal  land.  However,  it  is  clear  that  a  significant  amount  of  land  is 
available in certain areas of the world, although it is difficult to govern the proper use of these 
land areas. In fact, recent studies suggest that tropical forests were the primary sources of new 
agricultural  land  in  1980-90s  (i.e.  over  80%  of  land  coming  from  forests  across  the  tropics, 
see  figure  6  below),  with  various  studies  highlighting  a  significant  role  of  soy  and  cattle 
ranging,  and  palm  into  the  expansion  of  agricultural  land  into  the  Amazon  and  South  East 
Asia respectively159. However, since 2005 deforestation rates in the Amazon have been going 
down significantly160.  

Figure  13:  The  origins  of  new  agricultural  land,  1980–2000,  of  which  80%  took  place  in  tropical  areas. 
Bars  show  the  average  proportion  of  land  sources  comprising  new  agricultural  land  in  major  tropical 
regions (Source: Gibbs et.al. 2010). 

Further to the spatial limited availability of low-carbon stock land in some areas, the lack of 
effective  protection  of  forests  and  carbon  rich  areas  is  another  factor  that  allows  damaging 
indirect land-use change to take place. If conversion of carbon rich areas were to be limited, 
the  risk  of  damaging  indirect  land-use  change  would  be  minimized.  This  is  particularly 
applicable to forests and wetlands although significant carbon stocks can be lost from other 
land  types,  in  particular  grasslands.  However,  progress  towards  such  a  situation  is  slow.  It 

158 

159 

160 

Definitions  of  marginal  land  vary  across  studies.  Figures  from  the  Okoinstitut  report  are  specifically 
referred to as abandoned cropland and particularly unused degraded land.  
Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. H. K. Gibbs, 
A. S. Rueschb, F. Achardc, M. K. Claytond, P. Holmgrene, N. Ramankuttyf, and J. A. Foleyg 2010. 
Based on official data from the Brazilian National Institute of Space Research. 

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should also be noted that as long as these areas represent an important source for increasing 
total  agricultural  production,  reducing  such  conversions  is  likely  to  increase  global 
agricultural commodity prices. 

There  are  highly  relevant  lessons  to  be  learned  from  the  long  standing  policy  and  research 
work  done  on  limiting  deforestation.  The  Commission  has  taken  part  in  various  efforts  to 
reduce  deforestation,  through  development  cooperation,  trade  policies  and  international 
negotiations,  most  notably  through  the  UNFCCC,  where  the  discussions  of  the  REDD 
mechanism  (Reduction  of  Emissions  from  Deforestation  and  forest  Degradation)  is  the 
centrepiece. Extensive information on activities aimed at reducing deforestation can be found 
in the Communication on "Addressing the challenges of deforestation and forest degradation 
to tackle climate change and biodiversity loss"161, which notes that the most important direct 
cause of forest destruction is changes in land-use to pursue profitable alternative uses of land, 
such as obtaining commodities, while the most important underlying cause of deforestation is 
ineffective governance, linked to poorly enforced land-use policies and uncertain land tenure 
regimes.  

161 

EN 

COM(2008) 
lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2008:0645:FIN:EN:PDF.  

Available 

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17. 

ANNEX  VIII  –  INTERACTIONS  BETWEEN  EXISTING  LEGISLATION  AND  INDIRECT 
LAND-USE CHANGE  

17.1.  Existing EU legislation 

The  Renewable  Energy  Directive  and  the  Fuel  Quality  Directive,  are  at  the  origin  of  the 
debate on potential indirect land-use change caused by EU biofuels policy. So far there is no 
existing  regulatory  legislation  either  at  EU  level  or  at  Member  State  level  that  effectively 
addresses the issue, although the legislation  does  include  a  measure in order to increase the 
amount  of  land  available  for  the  cultivation  in  form  of  a  greenhouse  gas  bonus  to  biofuel 
produced on severely degraded and heavily contaminated land.  

Measures  which  are  taken  to  control  land-use  change  for  biofuels  directly,  for  example  to 
protect  forest  or  grassland  in  the  EU,  will  have  limited  impact  on  indirect  land-use  change 
emissions.  This  is  because  while  they  may  prevent  this  land  from  being  converted  to 
agriculture,  they  do  not  limit  the  total  demand  for  agricultural  commodities  and  the  extra 
demand might be supplied where it is most cost effective to do so. In some cases that is likely 
to  be  from  conversion  of  new  land  to  agriculture,  while  in  others  it  can  come  from  yield 
increases. 

The sustainability criteria adopted under the Directives hinders biofuels that come from land 
where damaging land-use change has taken place, also referred to as 'direct land-use change', 
to be used in the EU through the requirement to calculate the carbon stock change of the land-
use change. 

The  estimated  indirect  land-use  change  emissions  coming  from  the  implementation  of  the 
Directives are shown in the section laying down the baseline for this Impact Assessment. 

17.1.1. The Renewable Energy Directive 

The Renewable Energy Directive requires Member States to achieve jointly a 20% renewable 
energy  share  of  total  energy  consumption  over  all  sectors  by  2020.  Specifically  in  the 
transport sector, Member States are required to achieve a minimum of 10% renewable energy 
by  2020.  In  line  with  overall  EU  energy  policy,  the aim  of  these  targets  is  threefold,  i.e.  to 
reduce  greenhouse  gas  emissions,  to  promote  the  security  of  energy  supply,  to  promote 
technological  development  and  innovation  and  provide  opportunities  for  employment  and 
regional development, especially in rural and isolated areas.  

Based  on  the  demand  estimate  figures  supplied  by  the  Member  States  (NREAPs),  it  seems 
that the vast majority of the 10% transport target (around 9%) will be met through the use of 
conventional biofuels. In contrast, bioliquids are expected to play a small role in contributing 
towards the 20% target.  

17.1.2. The Fuel Quality Directive 

The  Fuel  Quality  Directive  requires  fuel  suppliers  to  achieve  a  6%  reduction  in  greenhouse 
gas  intensity  of  the  energy  they  supply  by  2020  compared  to  a  2010  baseline.  Blending  of 
biofuels is expected to be the main route of compliance, where volumes needed are expected 
to be similar to those estimated by Member States to comply with the 10% renewable energy 
target under the Renewable Energy Directive. Proper accounting of emissions is necessary for 

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the Fuel Quality Directive to work in the desired way, i.e. providing incentives for fuels that 
have less greenhouse gas intensity.  

17.2.  Other policies 

17.2.1. Agricultural policies 

Agriculture policies are essential in influencing the indirect land-use change impact. There are 
basically  three  theoretical  possibilities  to  mitigate  indirect  land-use  change.  First,  bringing 
back  into  cultivation  idle  low-carbon  stock  land.  Second,  agricultural  policy  could  target 
improvements  in  land  productivity  beyond  the  rate  which  would  have  prevailed  otherwise. 
Third,  agricultural  policy  can  provide  incentives  for  the  production  of  biofuels  with  low 
indirect land-use change emissions. 

The  Common  Agricultural  Policy  (CAP)  is  currently  in  its  final  phase  of  almost  entirely 
decoupling  its  support  to  farmers  from  production.  Farmers  have  to  ensure  that  their  land 
remains  in  good  agricultural  and  environmental  condition  (GAEC).  This  provision  aims  at 
ensuring  that  agricultural  land  which  becomes  idle  remains  available  for  production  in  the 
future. Furthermore, Member States are required to report on changes in grassland and to take 
measure against, if conversion occurs. Although the effectiveness of this requirement varied 
across  all  Member  States,  this  provision  has  helped  to  slow  down  and  reverse  the  loss  of 
grassland in the EU. 

The introduction of direct payments was accompanied by a reduction of guaranteed prices to 
farmers. Lower agricultural prices contributed to less input use. Lowering cereal prices in the 
EU  to  world  market  level  also  led  to  a  strong  increase  in  cereal  use,  especially  for  feed, 
substituting imports of feedstuffs. 

All in all, EU farmers are free to decide whether, how much and for what purpose they grow 
crops.  The  decoupling  of  support  significantly  improved  their  responsiveness  to  changing 
market  signals.  A  re-introduction  of  coupled  support, e.g. for  biofuel  crops would  not be in 
line with WTO rules. 

It is through the Rural Development Policy of the CAP where the EU offers financial support 
to  farmers  who  engage,  amongst  others,  into  increasing  their  competitiveness,  including  by 
improving yields, or into taking agri-environmental commitments.  

17.2.2. Environmental policies 

EU environmental legislation, including the new EU biodiversity strategy, is aimed to reduce 
environmental  degradation,  including,  damaging  land-use  change  impacts  in  the  EU. 
However,  it  is  neither  intended  nor  possible  for  biodiversity  actions  alone  to  prevent  the 
impacts  of  other  policies.  For  that  to  happen  biodiversity  considerations  must  be  integrated 
and  mainstreamed  into  the  development  and  implementation  of  all  national  an  EU  policies 
related to natural resource management, such as agriculture, food security, forestry, fisheries 
and  energy,  as  well  as  spatial  planning,  transport,  tourism  trade  and  development.  At 
international  level,  the  recently  adopted  post-2010  global  biodiversity  Strategic  Plan  of  the 
Biodiversity Convention may help reducing the loss of carbon and biodiversity rich habitats 

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including  forests.  As  part  of  its  2008  Communication  on  tropical  deforestation,  the 
Commission committed to studying the impact of EU consumption of imported food and non-
food commodities (e.g. meat, soy beans, palm oil, and metal ores) that are likely to contribute 
to deforestation. Such work could lead to considering policy options that reduce indirect land-
use change effects. 

With regard to forest policy in the EU, it is the competence of Member States to implement 
sustainable forest management. A number of MS have tight restrictions on deforestation. The 
EU currently contains 5 % of the world's forests and EU forests have continuously expanded 
for over 60 years, although recently at a lower rate. EU Forests and other wooded land (OWL) 
now  cover  155  million  ha  and  21  million  ha,  respectively,  together  more  than  42  %  of  EU 
land  area162.  Most  of  EU  forests,  including  those  under  continuous  management,  have  also 
grown  in  terms  of  wood  volume  and  carbon  stock,  thus  effectively  removing  CO2  from  the 
atmosphere. 

According to FAO data (Forest Resource Assessment 2010), EU27 has reported a net increase 
of  almost  7.3  million  ha  of  forest  area  (+5%)  between  1990-2000,  and  only  2.5  (+3%) 
between  2000-2010.  This  includes  both  afforestation  and  natural  reforestation,  e.g.  on 
abandoned  land.  The  area  of  protected  and  protective  forests  in  the  EU  has  also  increased 
during the last decade163. 

However,  the  overall  spending  on  afforestation  measures  through  rural  development 
programmes under Common Agricultural Policy in the EU has declined. According to current 
target  figures,  Member  States  expect  that  about  0.9  Mha  of  new  forests  will  be  established 
during the current programming period through Rural Development Programmes. 

Currently, an average of 0.5 Mha of forest burn in the EU annually with associated emissions, 
most affected are Spain, Italy, Greece, France and Portugal.  

17.2.3. Climate policies 

Climate change legislation may also help reducing the risk of indirect land-use change. At the 
16th Conference of the Parties to the UNFCCC ("COP16" ) in 2010 it was agreed to support 
developing countries to better protect their tropical forests by establishing a global mechanism 
to Reducing Emissions from Deforestation and Forest Degradation (REDD)164. The UNFCCC 
decision affirms "(...) that all Parties should collectively aim to slow, halt and reverse forest 
cover  and  carbon  loss"  and  therefore  encourages  them  to  "(...)  address  drivers  of 
deforestation".  

International accounting rules applicable to annex 1 parties for land use, land use change and 
forestry (LULUCF) for the post 2012 period were agreed at the 17th Conference of the Parties 
to the UNFCCC ("COP17") in Durban in December 2011. 

In order to transpose this decision into EU law, the Commission is proposing as a first step 
robust, common accounting, monitoring and reporting rules for LULUCF within the EU and 
compulsory  LULUCF  action  plans  in  Member  States.  The  Commission  propose  that 

162 
163 

164 

TBFRA 2000 - http://www.unece.org/timber/fra/welcome.htm.  
Protected  forest  area  was  38.1  million  hectares  in  2005  compared  with  the  30.1  million  hectares  in 
2000,  forests  with  protective  functions  increased  by  one  million  hectares  to  21.6  million  hectares  by 
2005. Forest habitat types designated as Natura 2000 sites cover over 22 million ha in 2008, according 
to Eurostat. Forests undisturbed by man/, account for about 9 million ha. 
http://www.un-redd.org/. 

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accounting  for  croplands  and  grasslands  become  mandatory  within  the  EU,  while  left 
voluntary  at  international  level.  This  will  ensure  that  perennial  energy  crops  grown  on 
agricultural  lands  will  enter  accounting165.  As  a  second  step  it  may  consider  how  LULUCF 
could be taken into account in the EU’s GHG emission reduction commitment.  

LULUCF accounting can reduce land-use changes by internalising the environmental cost of 
the  related  emissions  at  the  national  level,  therefore  making  activities  that  increase  such 
emissions  less  attractive,  but  only  once  a  target  is  agreed  for  the  sector  in  the  context  of  a 
second step. However, it should be noted that LULUCF accounting alone is not likely to be 
effective  at  controlling  LUC  emissions.  LULUCF  accounting  acts  at  the  national  level  and 
costs are born by the government, while land-use decisions are taken at the local level by land 
managers.  In  the  absence  of  dedicated  policy  instruments,  the  GHG  cost  of  LUC,  even  if 
internalised,  will  be  passed  on  to  the  government  budget.  In  addition,  LULUCF  accounting 
provides only a price signal commensurate to the average abatement cost at the national level. 
The GHG abatement cost of biofuels is significantly higher than the prevailing carbon price, 
and  demand  for  biofuels  is  highly  inelastic  due  to  binding  targets  and  mandates.  Therefore, 
the incentive to convert land is likely to be generally higher than the disincentive provided by 
LULUCF  accounting.  Therefore,  while  accounting  for  LULUCF  ensures  that  land-use 
emissions  are  monitored  the  actual  land-use  changes  and  resulting  collateral  environmental 
impacts may not be effectively reduced.  

17.2.4. Trade policies 

Changes  in biofuels  import  tariffs affect  the  land-use  change  impact of  the  overall  biofuels 
mandate  because  it  induces  changes  in  the  composition  of  the  supply  of  biofuels,  from 
different  origins  and  feedstocks. While  EU  tariffs  are  low  on  biodiesel  imports,  they  are 
relative  high  on  bioethanol. Reducing  these  tariffs would  consequently  have  significant 
effects  on  bioethanol  imports  and  production,  less  so  for  biodiesel. Imported  bioethanol  is 
mainly  produced  from  tropical  sugarcane,  a  feedstock  with  very  high  direct  emission 
savings. Though  the indirect  land-use  emissions may  be  higher  than  for  EU-produced 
bioethanol  feedstocks  (wheat,  sugar  beet),  the  net emission  savings are  higher  for  imported 
sugarcane ethanol. 

The  risks  of indirect  land-use  changes  in  producing  countries  vary.  The EU  has  effective 
protection of carbon rich areas and land-use expansion is strictly controlled. Land-use control 
systems  may  be  less  effective  in  developing  countries. Sustainability  Impact  Assessments 
of trade  agreements  can  help to  detect  and  understand  these  potential negative  side  effects, 
including on  tropical  deforestation. They enable  the  EU  to  develop  policies and  flanking 
measures  to  enhance  the  sustainability  and  reduce  land-use  emissions  of  biofuels  exports  to 
the EU. 

The 2003 EU action plan for Forest Law Enforcement, Governance and Trade (FLEGT) sets 
out a process and a package of measures to address the problem of illegal logging and related 
trade.  The  cornerstone  of  the  Action  Plan  is  the  establishment  of  voluntary  FLEGT 
Partnership  Agreements  (VPA)  between  the  EU  and  timber  producing  countries,  aimed  at 
stopping  illegal  logging.  In  December  2005,  the  Council  adopted  a  Regulation  (No 
2173/2005)  that  establishes  a  licensing  scheme  and  a  mechanism  to  verify  the  legality  of 
timber  imports  into  the  EU  from  partner  countries.  The  VPAs  together  with  the  recently 
approved  EU  Timber  Regulation  (No  995/2010)  will  discourage  unregulated  and 

165 

Only perennial crops will enter, as international accounting rules consider annual crops carbon neutral. 

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unsustainable exploitation of forests and thus address one of the drivers of deforestation and 
forest degradation. In addition, the negotiations provide an opportunity to challenge the legal 
framework,  particularly  with  respect  to  land  conversion  and  environmental  sustainability  of 
forest  management  and  where  the  frameworks  are  not  clear  or  judged  insufficient  by 
stakeholders. 

17.2.5. Development policies 

Under its development policy, the EU is committed to increasing expenditure on demand-led 
agricultural  research,  extension  and  innovation  by  50%  by  2015.166  Focus  is  placed  on 
"ecologically  efficient  agricultural  intensification  for  smallholder  farmers"  that  improves 
equitable and sustainable access to resources, including land, water, (micro) credit and other 
agricultural inputs with the aim of reducing food insecurity and poverty. The projected annual 
budget in this area is a minimum of € 87  million per year between 2011 – 2013. Although not 
aimed  only  at  yield  increases,  development  policy  reduces  indirect  land-use  change  by 
improving  agricultural  productivity,  especially  by  stepping  up  research  to  improve  the 
productivity and sustainability of agriculture in developing countries. 

17.2.6. Research policies 

The  research  into  feedlots  and  animal  diets  in  order  to  maximise  the  use  of  biofuel  co-
products  to  feed  European  livestock  will  reduce  the  imports  of  protein  rich  animal  feed, 
notably soya (Weightman167 et.al. 2010), which can significantly influence the indirect land-
use change. Weightman et.al. calculate that today's diets for pigs, poultry and ruminants can 
reduce land-use change in South America by 64 – 138 g/MJ of biofuel produced from wheat 
in  the  EU.  The  average  credit  is  82  g/MJ  and  if  higher  usage  is  made  possible  through 
nutritional research the credit can nearly double (Weightman et.al. 2010).  

Since the inception of 7th Framework Programme for Research ("FP7"), the Commission has 
issued  calls  for  demonstration  projects  that  put  particular  emphasis  on  biofuel  production 
from  lignocellulosic  biomass  and  addresses  practically  all  value  chains  from  sustainable 
biomass  resources  to  a  final  marketable  biofuel  that  meets  the  thresholds  laid  down  in  the 
Directives  for  2018,  i.e.  minimum  60%  reduction  compared  to  fossil  fuels  for  new 
installations.  Sustainability  is  a  key  issue  in  all  calls.  Under  FP7  the  Commission  has 
supported projects for sustainable biofuels in excess of €150 million.  

At  the  end  of  2007,  the  European  Commission  proposed  the  European  Strategic  Energy 
Technology Plan (SET-Plan)168 targeting a strategic approach to technology development and 
deployment in order to ensure the achievement of energy objectives. Bioenergy was covered 
by  the  SET  Plan  and  it  was  accompanied  by  "A  Technology  Roadmap  for  Bioenergy" 
presenting  the  fundamental  roadmaps  which  serve  as  a  basis  for  strategic  planning  and 
decision making169. The main tool for the implementation of the SET Plan are the Industrial 

166 
167 

168 

169 

http://ec.europa.eu/development/icenter/repository/COMM_PDF_COM_2010_0127_EN.PDF. 
Opportunities for avoidance of land-use change through substitution of soya bean meal and cereals in 
European livestock diets with bioethanol coproducts, GCB Bioenergy (2010). 
COM(2007)723,  Communication  from  the  Commission  to  the  Council,  the  European  Parliament  the 
European  Economic  and  Social  Committee  and  the  Committee  of  the  Regions,  "European  Strategic 
Energy Technology Plan (SET-Plan), Towards a low carbon future" 2009. 
SEC(2009)1295,  Commission  Staff  Working  Document  Accompanying  document 
the 
Communication  from  the  Commission  to  the  European  Parliament,  the  Council,  the  European 
Economic and Social Committee and the Committee of the Regions on Investing in the Development of 
Low Carbon Technologies (SET Plan) "A Technology Roadmap", 2009. 

to 

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Initiatives,  public-private  initiatives  led  by  industry,  aiming  to  accelerate  industrial  research 
and  innovation  at  the  EU  and  Member  States  level170.  Most  relevant  for  biofuels  is  the 
European  Industrial  Bioenergy  Initiative  (EIBI),  which  is  characterised  by  innovative 
technologies and high-risk investments aiming to bring new technologies onto the market for 
the  first  time.  The  focus  (related  to  biofuels)  is  primarily  on  second-generation  biofuel 
production from lignocellulosic biomass and algae171. 

In  addition,  and  in  line  with  the  priorities  identified  by  the  SET  Plan,  at  least  four 
lignocellulose-to-biofuels  demonstration  projects  at  pre-commercial  scale  are  potentially 
eligible  for  co-financing  under  the  so-called  NER  300  funding  programme,  which  provides 
financing for commercial-scale carbon capture and storage (CCS) and innovative renewables 
technology demonstration projects from 300 million allowances reserved in the new entrants 
reserve of the EU Emissions Trading System172. 

170 

171 

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EN 

"SET-Plan, 

For  an  overview  of  the  European  Industrial  Initiatives,  see  the  Commission  website:  European 
Commission, 
here: 
http://ec.europa.eu/energy/technology/set_plan/doc/setplan_brochure.pdf. 
Kyriakos  Maniatis  &  Stefan  Tostmann,  "  EU  Technology  Strategy  on  Bioenergy:  From  Blue-Sky 
Research to Targeted Technology Development", in Renewable Energy Law and Policy Review, Vol 1, 
N°2, p169-179. 
For more information see: http://ec.europa.eu/clima/funding/ner300/index_en.htm.  

low-carbon 

available 

towards 

future", 

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18. 

ANNEX IX – BIOFUELS AND RELATED INDUSTRIES BASELINE TABLES  

2002 

2003 

2004 

2005 

2006 

2007 

2008 

2009 

Austria 

Belgium 

Bulgaria 

Cyprus 

0.0 

0.0 

0.0 

0.0 

Czech Republic 

0.0 

Denmark/Sweden  0.0 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Ireland 

Italy 

Latvia 

Lithuania 

Luxemburg 

Malta 

Netherlands 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia 

Spain 

UK 

TOTAL 

0.0 

0.0 

0.3 

0.4 

0.0 

0.0 

0.0 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

1.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.3 

0.6 

0.0 

0.0 

0.0 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

1.3 

0.1 

0.0 

0.0 

0.0 

0.1 

0.1 

0.0 

0.0 

0.3 

0.9 

0.0 

0.0 

0.0 

0.3 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

1.7 

0.1 

0.0 

0.0 

0.0 

0.1 

0.1 

0.0 

0.0 

0.4 

1.5 

0.0 

0.0 

0.0 

0.4 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.1 

0.0 

0.1 

0.0 

2.9 

0.1 

0.0 

0.0 

0.0 

0.1 

0.1 

0.0 

0.0 

0.7 

2.4 

0.0 

0.0 

0.0 

0.4 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.1 

0.0 

0.1 

0.0 

0.1 

0.2 

4.4 

0.2 

0.1 

0.0 

0.0 

0.1 

0.1 

0.0 

0.0 

0.8 

2.6 

0.1 

0.0 

0.0 

0.3 

0.0 

0.0 

0.0 

0.0 

0.1 

0.1 

0.2 

0.0 

0.0 

0.0 

0.2 

0.1 

5.2 

0.2 

0.3 

0.0 

0.0 

0.1 

0.2 

0.0 

0.1 

1.6 

2.5 

0.1 

0.1 

0.0 

0.5 

0.0 

0.1 

0.0 

0.0 

0.1 

0.2 

0.2 

0.1 

0.1 

0.0 

0.2 

0.2 

7.0 

0.3 

0.4 

0.0 

0.0 

0.1 

0.2 

0.0 

0.2 

1.8 

2.3 

0.1 

0.1 

0.0 

0.7 

0.0 

0.1 

0.0 

0.0 

0.3 

0.3 

0.2 

0.0 

0.1 

0.0 

0.8 

0.1 

8.2 

Figure 14: European biodiesel production by country (in Mtoe). Source: EBB 

EN 

104 

   EN 

 
 
2003 

2004 

2005 

2006 

2007 

2008 

2009 

2010 

Austria 

Belgium 

Bulgaria 

Cyprus 

Czech 
Republic 

Denmark  

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Ireland 

Italy 

Latvia 

Lithuania 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.5 

0.9 

0.0 

0.0 

0.0 

0.4 

0.0 

0.0 

Luxemburg 

0.0 

Malta 

0.0 

Netherlands 

0.0 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia 

Spain 

Sweden 

UK 

TOTAL 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

1.8 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.5 

1.0 

0.0 

0.0 

0.0 

0.4 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

2.0 

0.1 

0.0 

0.0 

0.0 

0.2 

0.1 

0.0 

0.0 

0.5 

1.7 

0.0 

0.0 

0.0 

0.7 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.1 

0.0 

0.1 

0.0 

0.1 

3.8 

0.1 

0.1 

0.0 

0.0 

0.2 

0.1 

0.0 

0.0 

0.7 

2.4 

0.1 

0.0 

0.0 

0.8 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.1 

0.0 

0.1 

0.0 

0.2 

0.0 

0.4 

5.5 

0.3 

0.3 

0.1 

0.0 

0.2 

0.1 

0.0 

0.0 

0.7 

3.9 

0.4 

0.0 

0.0 

1.2 

0.0 

0.0 

0.0 

0.0 

0.1 

0.2 

0.2 

0.1 

0.1 

0.0 

0.5 

0.2 

0.6 

9.3 

0.4 

0.6 

0.2 

0.0 

0.2 

0.1 

0.1 

0.2 

1.8 

4.8 

0.5 

0.2 

0.1 

1.4 

0.1 

0.1 

0.0 

0.0 

0.5 

0.4 

0.4 

0.1 

0.2 

0.1 

1.1 

0.2 

0.7 

0.6 

0.6 

0.4 

0.0 

0.3 

0.1 

0.1 

0.3 

2.3 

4.7 

0.6 

0.2 

0.1 

1.7 

0.1 

0.1 

0.0 

0.0 

0.9 

0.5 

0.4 

0.3 

0.2 

0.1 

3.3 

0.2 

0.5 

0.5 

0.6 

0.4 

0.0 

0.4 

0.2 

0.1 

0.3 

2.3 

4.5 

0.6 

0.1 

0.1 

2.1 

0.1 

0.1 

0.0 

0.0 

1.2 

0.6 

0.4 

0.3 

0.1 

0.1 

3.7 

0.3 

0.5 

14.4 

18.9 

19.8 

Figure 15: European biodiesel capacity by country (in Mtoe). Source: EBB  

EN 

105 

   EN 

 
  
2004 

2005 

2006 

2007 

2008 

2009 

Austria 

Belgium 

Bulgaria 

Czech 
Republic 

Denmark 

Finland 

France 

Germany 

Hungary 

Ireland 

Italy 

Latvia 

Lithuania 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

Netherlands 

0.0 

Poland 

Romania 

Slovakia 

Slovenia 

Spain 

Sweden 

UK 

TOTAL 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.3 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.2 

0.1 

0.0 

0.5 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.2 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.2 

0.1 

0.0 

0.8 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.3 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.2 

0.1 

0.0 

0.9 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.5 

0.3 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.0 

0.0 

0.2 

0.0 

0.0 

1.4 

0.1 

0.1 

0.0 

0.1 

0.0 

0.0 

0.6 

0.4 

0.1 

0.0 

0.0 

0.0 

0.0 

0.0 

0.1 

0.0 

0.1 

0.0 

0.2 

0.1 

0.0 

1.9 

Figure 16: European bioethanol production by country (in Mtoe). Source: ePure 

EN 

106 

   EN 

 
 
 
 
 
 
  
2005 

2006 

Austria 

Belgium 

Bulgaria 

Czech 
Republic 

Denmark 

Finland 

France 

Germany 

Hungary 

Ireland 

Italy 

Latvia 

Lithuania 

0.0 

0.0 

0.0 

>0.0 

0.0 

0.0 

0.4 

0.2 

0.0 

0.0 

0.2 

>0.0 

>0.0 

Netherlands 

0.0 

Poland 

Romania 

Slovakia 

Slovenia 

Spain 

Sweden 

UK 

TOTAL 

0.0 

0.0 

0.0 

0.0 

0.1 

0.1 

0.0 

1.0 

0.0 

0.0 

>0.0 

>0.0 

0.0 

0.0 

0.4 

0.4 

0.1 

0.0 

0.2 

>0.0 

>0.0 

>0.0 

0.1 

0.0 

0.0 

0.0 

0.3 

0.1 

0.0 

1.5 

2007 

0.1 

>0.0 

>0.0 

>0.0 

0.0 

>0.0 

0.7 

0.4 

0.1 

0.0 

0.2 

>0.0 

>0.0 

>0.0 

0.1 

>0.0 

0.1 

0.0 

0.3 

0.1 

>0.0 

2.1 

2008 

2009 

2010 

0.1 

0.3 

>0.0 

0.1 

0.0 

>0.0 

0.9 

0.6 

0.1 

0.0 

0.2 

>0.0 

>0.0 

>0.0 

0.1 

>0.0 

0.1 

0.0 

0.3 

0.2 

>0.0 

2.9 

0.1 

0.3 

>0.0 

0.1 

0.0 

>0.0 

1.0 

0.6 

0.1 

0.0 

0.2 

>0.0 

>0.0 

>0.0 

0.2 

>0.0 

0.1 

0.0 

0.3 

0.2 

>0.0 

3.1 

0.1 

0.3 

>0.0 

0.1 

0.0 

>0.0 

1.0 

0.6 

0.1 

>0.0 

0.2 

>0.0 

>0.0 

0.3 

0.2 

>0.0 

0.1 

0.0 

0.3 

0.2 

0.2 

3.6 

Figure 15: European bioethanol capacity by country (in Mtoe). Source: ePure 

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107 

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Soya 

Rape 

Sunflo
wer 

Palm-
kernel 

Linseed 

Castor 

Maize 
germ 

Grape 
pips 

Palm 

TOTAL 

(x 1000 
tonnes) 

Austria* 

Belgium  

Bulgaria ** 

Cyprus  

Czech 
Republic** 

Denmark  

Estonia** 

Finland  

0 

21 

0 

0 

8 

9 

0 

2 

136 

356 

0 

0 

284 

214 

37 

104 

30 

0 

147 

0 

15 

0 

0 

4 

France  

49 

1329 

472 

Germany  

643 

3185 

Greece* 

63 

22 

88 

14 

Hungary* 

Ireland  

0 

0 

Italy  

259 

Latvia** 

Lithuania** 

Malta  

2 

0 

0 

110 

315 

0 

18 

30 

60 

0 

0 

157 

1 

1 

0 

Netherlands  

572 

336 

127 

Poland** 

1 

693 

Portugal* 

Romania** 

Slovakia** 

Slovenia** 

Spain  

Sweden*  

UK 

199 

37 

4 

0 

549 

0 

106 

35 

70 

71 

5 

35 

100 

678 

10 

63 

222 

39 

0 

361 

0 

0 

EU-27 

2524 

7914 

2065 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

1 

136 

0 

0 

1 

0 

0 

0 

0 

53 

0 

0 

0 

6 

0 

0 

0 

0 

2 

0 

0 

0 

0 

1 

0 

4 

204 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

49 

6 

0 

0 

0 

1 

0 

49 

13 

4 

17 

0 

50 

0 

0 

0 

0 

0 

4 

0 

0 

0 

17 

0 

23 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

12 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

233 

12 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

167 

562 

153 

0 

308 

223 

38 

110 

1899 

3982 

103 

442 

0 

502 

33 

61 

0 

1035 

706 

301 

329 

114 

5 

963 

100 

811 

12947 

Figure 16: 2008 production of crude vegetable oils and fats. Source: Fediol 

EN 

108 

   EN 

 
 
 
Soyabeans 

Rapeseed 

Sunflower-
seeds 

Palm kernel 

Linseed  Castor 

Maize 
germs 

Grape 

pips 

Palm 

TOTAL 

(x 1000 
tonnes) 

Austria 

Belgium  

Bulgaria** 

Cyprus  

Czech 
Republic** 

Denmark  

Estonia** 

Finland  

France  

0 

109 

1 

0 

47 

55 

0 

10 

332 

869 

12 

0 

720 

465 

91 

275 

72 

0 

350 

0 

35 

0 

1 

9 

280 

3157 

1060 

Germany  

3364 

7705 

Greece 

351 

Hungary* 

Ireland  

Italy  

Latvia** 

Lithuania** 

Malta  

0 

0 

1787 

13 

0 

0 

54 

270 

0 

45 

74 

148 

0 

Netherlands  

2898 

799 

Poland** 

6 

1732 

Portugal 

Romania** 

Slovakia** 

Slovenia** 

1170 

217 

22 

0 

Spain  

3026 

90 

179 

180 

13 

91 

Sweden*  

0 

250 

UK 

559 

1654 

198 

37 

750 

0 

388 

2 

3 

0 

289 

24 

157 

532 

92 

0 

903 

0 

0 

EU-27 

13915 

19205 

4902 

*estimate**Source: Oilworld 

Figure 17: 2008 crushing of oilseeds. Source: Fediol 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

4 

367 

0 

0 

2 

0 

0 

0 

0 

150 

0 

0 

0 

15 

0 

0 

0 

0 

6 

0 

1 

1 

0 

3 

0 

10 

559 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

103 

12 

0 

0 

0 

2 

0 

102 

27 

8 

35 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

120 

89 

0 

0 

0 

0 

0 

8 

0 

0 

0 

35 

0 

48 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

500 

89 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

408 

1448 

375 

0 

804 

520 

94 

294 

4599 

11444 

450 

1055 

0 

2444 

89 

151 

0 

3986 

1768 

1425 

929 

295 

5 

4058 

250 

2271 

39162 

EN 

109 

   EN 

 
 
171 

42 

231 

0 

29 

51 

209 

416 

18 

0 

12 

(x 1000 
tonnes) 

Wheat 

Barley 

Grain 
maize 

Rye and 
maslin 

Cereals total 
(including 
rice) 

Sugar beet 

Rape 

Sunflower 

Austria 

Belgium 

Bulgaria 

Cyprus 

Czech 
Republic 

1523 

1928 

4000 

15 

835 

451 

815 

40 

1891 

754 

1273 

0 

4358 

2003 

890 

Denmark  

5996 

3421 

346 

887 

380 

2171 

0 

0 

0 

Estonia 

Finland 

France 

3 

15 

0 

178 

245 

39 

42 

195 

5144 

3083 

3221 

4569 

5273 

57 

0 

0 

7832 

3038 

1128 

10200 

2011 

879 

4261 

0 

559 

637 

136 

140 

38325 

12880 

15300 

130 

70000 

33146 

5562 

1676 

Germany 

25190 

12288 

4527 

4325 

49748 

25550 

6307 

565 

1306 

Greece 

1830 

280 

2352 

Hungary 

4396 

1033 

7543 

Ireland 

Italy 

Latvia 

Lithuania 

Luxembourg 

Malta 

951 

1089 

0 

6341 

1049 

7878 

1036 

2100 

91 

0 

265 

858 

54 

0 

0 

24 

3 

0 

Netherlands 

1402 

310 

245 

37 

75 

0 

12 

162 

208 

7 

0 

11 

4820 

13571 

2384 

902 

708 

45 

15892 

3308 

1663 

3806 

189 

0 

0 

682 

0 

0 

2089 

5735 

9790 

3984 

1707 

3968 

29827 

10849 

2497 

Poland 

Portugal 

110 

76 

594 

Romania 

5205 

1183 

8035 

Slovakia 

Slovenia 

1538 

137 

676 

71 

988 

303 

Spain 

4797 

7400 

3479 

Sweden 

2284 

1677 

UK 

14379 

6769 

0 

0 

18 

36 

57 

2 

181 

219 

36 

1057 

14934 

3330 

533 

137 

685 

899 

262 

17833 

4089 

0 

572 

387 

10 

29 

5249 

2406 

302 

22036 

8330 

1951 

71 

0 

1301 

0 

61 

0 

0 

0 

57 

16 

0 

280 

0 

0 

0 

0 

0 

4 

14 

1083 

187 

0 

876 

0 

2 

EU-27 

138 954 

62057 

57782 

10202 

295828 

110992 

21399 

6934 

Figure 18: Harvested production of some of the main crops, in 1 000 tonnes, 2009. Source: Eurostat 

EN 

110 

   EN 

 
  
 
19. 

ANNEX X – IMPACTS ON BIODIVERSITY 

According  to  the  central  scenario  of  IFPRI-MIRAGE-BioF  model,  the  estimated  additional 
cropland requirements globally amount to 1.7 Mha, mainly taking place in Commonwealth of 
Independent  States,  Sub-Saharan  Africa  and  Brazil  regions.  New  cropland  is  allocated  by 
IFPRI-MIRAGE-BioF  estimating  changes  in  the  economic  use  of  land,  i.e.  among  forestry, 
cropland  and  pasture  uses.  The  results  of  the  IFPRI-MIRAGE-BioF  study  showed  that  this 
new  cropland  is  taken  from  pasture  (42%),  managed  forest  (39%),  primary  forest  (3%)  and 
savannah  and  grassland  (16%),  which  will  have  biodiversity  and  wider  environmental 
impacts.  

A  qualitative  estimation  of  the  impacts  to  biodiversity  of  land-use  changes  calculated  by 
IFPRI-MIRAGE-BioF  was  made  by  the  JRC173  using  the  Mean  Species  Abundance  (MSA) 
values provided by the Global Biodiversity Model (GLOBIO 3)174. This model is built on a 
set  of  equations  which 
impacts.  The 
environmental drivers used as input for GLOBIO3 are land-use change (including forestry), 
climate change, N deposition, harvesting, energy use etc. 

link  environmental  drivers  and  biodiversity 

Biodiversity is described in GLOBIO3 on the basis of the remaining mean species abundance 
(MSA) of original species, relative to their abundance in pristine or primary vegetation, which 
are assumed to be not disturbed by human activities for a prolonged period. MSA is therefore 
considered as the indicator for biodiversity. 

The  following  table  was  extracted  from  Alkemade  et  al,  2009  and  adapted  to  IFPRI-
MIRAGE-BioF  lands  uses  to  evaluate  MSA  values  for  the  land-use  transitions  (and  LU 
classes) in IFPRI-MIRAGE-BioF scenario.  

IFPRI-MIRAGE-
BIOF Land-use class 

Sub-
category 

Description 

MSALU

Pasture 

Grasslands  where  wildlife  is  replaced  by 
grazing livestock 

70% 

Managed Forest 

Secondary 
forest 

Areas  originally  covered  with  forest  or 
woodlands,  where  vegetation  has  been 
removed,  forest 
is  re-growing  or  has  a 
different cover and is no longer in use  

50% 

Agroforestry Agricultural  production 

intercropped  with 
(native)  trees.  Trees  are  kept  for  shade  or  as 

50% 

173 

174 

Literature: EU Commission, DG ENVIRONMENT: Land-use Modelling – Implementation. Preserving 
and enhancing the environmental benefits of “land-use services". Final report, 1 April 2010. Alkemade, 
R.,  Van  Oorschot  M.,  Miles  L.,  Nellemann  C.  ,  Bakkenes  M.  and  Ten  BrinkB.:  GLOBIO3:  A 
Framework  to  Investigate  Options  for  Reducing  Global  Terrestrial  Biodiversity  Loss.Ecosystems 
(2009)  12:  374–390.  Van  Oorschot  M.,Ros  J.  and  Notenboom  J.:Evaluation  of  the  indirect  effects  of 
biofuel  production  on  biodiversity:  assessment  across  spatial  and  temporal  scales.  PBL  (Netherlands 
Environmental Assessment Agency), Final report 27 May 2010. Campbell A., Doswald N.: The impacts 
of biofuel production on biodiversity: A review of the current literature. United Nations Environment 
Programme – World Conservation Monitoring Center. Final report, December 2009. 
GLOBIO  3  is  developed  by  a  consortium  made  up  of  UNEP  world  Conservation  Monitoring  Centre 
(WCMC), UNEP/GRID-Arendal and the Netherlands Environmental Agency (PBL). [Alkemade et al, 
2009]. 

EN 

111 

   EN 

 
 
                                                 
IFPRI-MIRAGE-
BIOF Land-use class 

Sub-
category 

Description 

wind shelter 

MSALU

Primary Forest  

Minimal  disturbance,  where  flora  and  fauna 
species abundance are near pristine 

100% 

Scrublands 
grasslands  

and 

Grassland  or  scrubland-dominated  vegetation 
(for example, steppe, tundra, or savannah) 

100% 

Cultivated 
managed areas  

and 

High  external  input  agriculture,  conventional 
agriculture,  mostly  with  a  degree  of  regional 
specialization, 
irrigation-based  agriculture, 
drainage-based agriculture*.  

10% 

Table 18: Land-use classes used to determine mean species abundance (MSA) 

*  The  JRC  assumes  land  management  factor  for  cropland  as  “medium  or  high  input  with  manure”  in  its 
calculations (JRC report n.24483). For consistency the same assumption is taken here.  

For example, according to the MSA values in the table, a transition from pastureland (MSA 
70%) to cropland (MSA 10%) will cause a loss of 60%of MSA on top of the 30% already lost 
from the conversion from natural land to pastureland..  

An  estimation  of  the  land-use  transition  biodiversity  loss  in  the  additional  croplands  which 
may result from IFPRI-MIRAGE-BIOF scenario has been calculated with a weighted average 
of MSA values for IFPRI-MIRAGE-BIOF land-use changes as: 

Where:  

MSAi = Mean Species Abundance of land-use type i 

%i = % of land conversion according to IFPRI-MIRAGE-BIOF results 

MSAca = Mean Species Abundance of cultivated and managed areas 

Considering that 42% of new cropland will come from pasture, 39% from managed forest, 3% 
from primary forest and 16% from savannah and scrublands, this will results in a “weighted” 
MSA value of 68%, and the transition to cropland will cause 58% decrease in the MSA index 
in affected areas. In addition to this there will also be indirect losses when part or all of the 
pasture  and  managed  forest  that  was  converted  is  moved  elsewhere  into  natural  areas. 
Considering this, total loss could build up to 90% when all pasture and forestry is moved into 
natural land (gradual land-use conversion in several steps). These results are just preliminary 
rough  estimates,  and  more  research  is  needed  to  provide  a  qualitative  and  more  precise 
assessment in particular of the indirect effects. 

This result, in line with the conclusions of GLOBIO3 study, shows that the extensive use of 
bioenergy  crops  will  increase  the  rate  of  loss  of  biodiversity,  and  often  the  GHG  reduction 
from biofuels production are insufficient to compensate for the losses due to land-use change 
(Van Oorschot et al., 2010).  

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20. 

ANNEX XI – MONTE-CARLO ANALYSIS OF INDIRECT LAND-USE CHANGE EMISSIONS 
ESTIMATES 

ATLASS  created  1000  baselines,  and  then  performed  simulations,  using  1000  set  of  seven 
parameters. The parameters are drawn from a log uniform distribution, centered on the default 
value of the model, and the range of values is defined based on a literature review of potential 
meaningful figures (see CARB 2011, for a discussion on elasticity values175). Key elements of 
the  parameter  distribution  are  displayed  in  Table.  As  shown  by  the  ratio  average/median, 
nearly  all  distributions  of  the  sample  have  a  right  tail-feature176  driven  by  the  log  uniform 
assumption of the probability used to build these samples. The same set of parameters is used 
for assessing the indirect land-use change emissions uncertainty of the full mandate as well as 
for each individual crop. 

Shifter  in 
the  share 
of 
extension 
occurring 
in 
primary 
forest 

Shifter 
in 
intermediate 
demand 
price 
elasticity  of 
agricultural 
inputs 

Ratio 
between 
yield  on 
new 
cropland 
and 
average 
yield 

of 

Elasticity 
substitution 
land 
between 
other 
and 
factors  (factor 
intensification) 

of 

key 

Elasticity 
substitution 
between 
inputs 
(feedstuff 
or 
fertilizer)  and 
land 
(input 
intensification) 

Elasticity 
of 
transformation 
of 
land 
(intermediate 
level) 

Land 
extension 
elasticity 

Average 
DC 
DV 

Median 
DC 
DV 

Maximal 
Value 
DC 
DV 

Minimal 
value 
DC 
DV 

Standard 
Deviation 
DC 
DV 

0.99 
0.99 

0.91 
0.91 

1.81 
1.81 

0.46 
0.46 

0.39 
0.39 

1.18 
1.18 

1.21 
1.21 

1.83 
1.83 

0.47 
0.47 

0.41 
0.41 

0.75 
0.75 

0.75 
0.75 

0.99 
0.99 

0.50 
0.50 

0.13 
0.13 

0.07 
0.07 

0.06 
0.04 

0.18 
0.33 

0.01 
0.01 

0.05 
0.06 

0.11 
0.20 

0.08 
0.15 

0.29 
0.59 

0.02 
0.04 

0.08 
0.16 

0.30 
0.30 

0.25 
0.25 

0.74 
0.74 

0.09 
0.09 

0.18 
0.18 

0.02 
0.05 

0.01 
0.04 

0.04 
0.17 

0.00 
0.01 

0.01 
0.04 

Table  19:  Range  of  parameters  for  Monte  Carlo  analysis.  Source:  IFPRI-Mirage-BioF  Monte  Carlo 
parametersNote: DC=Developed countries. DV=Developing countries 

Before discussing the list of parameters and their expected effects, one needs to indicate how 
the draws are done. A first solution would have been to consider that the value of a parameter 
for  each  sector  (if  relevant)  and  each  region  and  AEZ  is  independent  of  the  value  for  other 
sectors/regions.  For  instance  it  would  have  implied  that  the  value  used  for  the  elasticity  of 
land  transformation  into  European  AEZ  are  independent  or  that the  level  of  potential  factor 

175 

176 

EN 

CARB  (2011),  Final  Recommendations  from  the  Elasticity  Values  Subgroup,  ARB  LCFS  Expert 
Workgroup, 
here: 
http://www.arb.ca.gov/fuels/lcfs/workgroups/ewg/expertworkgroup.htm.  
However,  since  some  parameters  can  increase  indirect  land-use  change  emissions  when  other  can 
reduce it, the right tail distribution of the parameter distribution does not involved a right tail biased in 
the LUC expected distribution. 

California. 

Available 

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intensification in the wheat sector in the US is uncorrelated with the level for the corn market. 
In such a case, we will have drawn for each parameter a specific value for each sector/region 
combination  considering  systematic  uncertainty.  This  approach  is  not  followed.  Rather 
ATLASS considered that the key uncertainty is not about the exact value for a country/sector 
and  its  correlation  with  other  regions/sectors  but  about  the  real  location  of  the  parameters 
distribution in the space of potential value and that all sectors/regions are affected in a similar 
way. It implies that we consider a perfect correlation between parameter values across sectors 
and across countries (or group of countries). For instance, for each draw, ATLASS shifted the 
value of a parameter, e.g. land elasticity of transformation, for all developed countries in the 
same direction. All developed countries will be able to relocate land more easily among crops 
(or  less)  at  the  same  time.  However,  the  distribution  for  each  parameter  is  considered  from 
other  parameters:  the  shifter  in  demand  behavior  is  drawn  independently  from  the  value  of 
fertilizer intensification parameter. If parameter values would have been uncorrelated, a high 
elasticity in one region may have been compensated by a lower in another. Consequently, for 
each draw the world median would have been closer to the distribution median and the overall 
land-use effects would have been closer to the median value (even if the geographical pattern 
of  the  land-use  will  have  been  much  more  dispersed)177.  ATLASS  have  chosen  full 
correlation, since we the key challenge for many parameters, e.g. yield price response, is to 
know  the  change  in  average  magnitude  and  not  the  question  about  the  correlation  and  the 
heterogeneity  among  countries/sectors.  There  are  still  independent  draws  across  parameters. 
A large yield response can still be combined to a strong sensitivity of cropland extension to 
land  prices.  The  combination  of  effects  among  parameters  is  not  biased  in  a  way  that  will 
increase/decrease the results dispersion. 

ATLASS  selected  seven  parameters  to  study,  most  of  them  –  except  the  two  first  of  the 
following 
the 
– 
extensification/intensification trade-off: 

agricultural 

response 

focused 

supply 

and 

list 

the 

on 

• 

• 

• 

177 

178 

Shifter  in  the  share  of  extension  occurring  in  primary  forest,  this  coefficient 
multiplies178  the  initial  share  of  land  extension  taken  place  in  primary  forest  in  the 
Winrock  coefficient  dataset.  It  does  not  affect  the  economic  response  of  the  model 
and  only  modify  the  carbon  release  by  unit  of  exploited  land  expansion:  a  value 
above one will increase the share of primary forest and the carbon release; 

Shifter  in  intermediate  demand  price  elasticity  of  agricultural  inputs,  this  shifter 
multiplies  the  price  elasticity  of  intermediate  demand  (by  non  primary  sectors)  for 
agricultural  commodities.  In  the  model,  the  elasticity  of  substitution  in  the 
intermediate consumption nested CES structure is recalibrated accordingly. A value 
above  one  implies  that  processing  sectors  will  release  more  easily  inputs  (crops  or 
vegetable oils) following the biofuel demand shock, and therefore reduces the LUC 
effect; 

Ratio  between  yield  on  new  cropland  and  average  yield:  this  parameter  gives  the 
marginal  productivity  of  new  hectare  of  cropland  compared  to  existing  one.  The 
expected  direct  effect  is  that  reduced  yield  will  lead  to  larger  requirement  of  new 
land to meet the additional crop demand and will increase indirect land-use change 
emissions.  However,  more  complex  effects  take  place  in  the  model.  Indeed,  in  the 

Indeed, assuming perfect correlation among crops or regions does not affect the relative properties, and 
comparative  advantages  of  different  crops.  The  geographical  pattern  of  effects  and  the  feedstock  mix 
for the overall scenario will not be subject to large modifications in this framework. 
Other shares (grassland, shrub) are rescaled to be sure that the sum of share is equal to one. 

EN 

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• 

• 

• 

• 

• 

dynamic  baseline,  assuming  lower  yield  on  marginal  land  leads  to  more  land 
extension179. Since the “managed land” supply elasticity in the model is not constant 
but decreases with the ratio between used agricultural land and total suitable land for 
agriculture,  the  large  expansion  in  the  baseline  needed  to  compensate  the  low 
productivity  of  new  land  reduces  the  remaining  amount  of  available  land  in  the 
baseline and decreases the price elasticity  of land expansion that prevails when the 
biofuel scenario takes place. Therefore, the net effect of a low/high marginal yield is 
ambiguous;180 

Elasticity of substitution between land and other factors (factor intensification) 
This is a core parameter in the endogenous yield response of the model; it shows how 
production can increase through additional capital/labor use by unit of land. A larger 
value  describes  a  more  flexible  production  system  that  will  reduce  the  land-use 
change effect(more intensification); 

. 

Elasticity of substitution between key inputs (feedstuff or fertilizer) and land (input 
intensification).  This  is  the  other  driver  of  intensification,  both  in  crop  production 
and livestock sector, since it allows to substituting land to inputs (fertilizer or feed). 
A  larger  value  is  associated  to  a  lower  indirect  land-use  change  emissions  (more 
intensification); 

Elasticity  of  transformation  of  land  (intermediate  level)  among  broad  categories  of 
agricultural  production.  A  larger  value  is  associated  to  a  lower  indirect  land-use 
change  emissions  since  increased  production  of  energy  crops  can  displace  other 
agricultural production before requiring new cropland (more land reallocation). 

Land  extension  elasticity.  This  parameter  describes  the  land  supply  response  – 
extension  of  managed  agricultural  land  to  pristine  environments  –  following  an 
increase  in  cropland  price.  Even  if  this  value  is  not  constant  in  the  model,  as 
discussed above it evolves the ratio between used and available land for agriculture, 
the change in the Monte Carlo modifies the initial value and its path of evolution. A 
larger elasticity value reinforces the indirect land-use change emission effect (more 
extension). 

Last,  for  several  parameters,  ATLASS  assumed  more  uncertainty  i.e.  a  more 
dispersed  distribution  for  developing  countries  parameters;  it  should  lead  to  more 
dispersed land-use change for crops produced in these regions (e.g. sugar cane) than 
for  others.  The  parameters  involved  are  the  intensification  parameters  (fertilizers, 
feed, and factors) and the land extension elasticity. Similar crops with similar initial 
technology (share of fertilizer in total cost) and production location (concentrated in 
developed  countries  or  in  developing  countries  e.g.  tropical  crops)  are  expected  to 
display high correlation in land-use change in the Monte Carlo simulations. ATLASS 
did not implement uncertainty of the household demand behavior, neither uncertainty 
on substitution among subset of inputs (animal fat versus vegetable oil for instance). 
Other aspects such as carbon stocks or direct saving coefficients from the life cycle 

179 

180 

Indeed, cropland extension in the baseline, driven by economic and demographic growth is much larger 
than the effects of the biofuels scenario studied here. 
It also emphasises the role of the baseline behavior in our assessment and the importance to understand 
that  we  compute  the  effects of  the biofuel policy  as  a  marginal  deviation  from  this  baseline  when  all 
other ongoing changes have already been taken into account. 

EN 

115 

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analysis  are  considered  as  known  even  if  their  role  in  overall  land-use  change 
uncertainty competition should not be neglected (see Plevin et al, 2010181). 

181 

Plevin, R. J., OHare, M., Jones, A. D., Torn, M. S. and Gibbs, H. K. (2010), Greenhouse Gas Emissions 
from  Biofuels  Indirect  Land-use  Change  Are  Uncertain  but  May  Be  Much  Greater  than  Previously 
Estimated, Environmental Science and Technology 44(21), 8015-8021. 

EN 

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21. 

ANNEX XII – POTENTIAL FOR MITIGATING INDIRECT LAND-USE CHANGE EMISSIONS 
AT PROJECT LEVEL 

A number of measures can in theory be put in place at the production site in order to prevent 
indirect land-use change. A short description of these, which are being assessed under section 
5, as well as a comment on their potential is included in this section. 

21.1.  Increase use of unused/degraded land  

Using  land  without  provisioning  services182  that  would  be  unlikely  to  be  taken  into 
production in the absence of biofuel demand (i.e. typically land that either requires some form 
of remediation prior to being used or where significant barriers exist). Expanding production 
on unused land may lead to direct land-use change, but the latter would be addressed by the 
current  sustainability  criteria  and  therefore  directed  to  those  areas  where  effects  are 
acceptable. 

Another potential way for mitigating against (indirect) land-use change would be to increase 
the production of biofuels in areas that are not in agricultural production and would be likely 
to remain the same in the absence of intervention. This could be because of the existence of 
some  sort  of  "barriers"  for  this  land  to  become  into  cultivation  (i.e.  remediation  is  needed 
prior to cultivation or regulatory barriers).  

In terms of potential, a recent project183 highlighted that a total 35Mha of Imperata grassland 
(a type of invasive grassland of low biodiversity value) could be available for the cultivation 
of palm oil in South East Asia, with about 4Mha being available in Indonesia alone184. This 
would present a significant opportunity for mitigating against indirect land-use change as the 
baseline  predicts  a  very  significant  part  of  the  emissions  to  be  associated  with  peatland 
drainage. Opportunities for intensification through this method would seem to be more limited 
in  densely  populated/exploited  regions  such  as  the  EU,  although  it  would  be  difficult  to 
estimate what the availability may be.  

Moreover,  the  reduction  in  cropland  expected  in  the  EU  from  2010  to  2020  of  around  5.5 
million hectares. It is however important to note that the potential to mitigate indirect land-use 
change emissions through using more land in the EU (besides institutional, political and social 
factors)  would  depend  on  the  opportunity  costs  of  and  yields  on  this  land,  as  well  as  what 
would the carbon content and GHG balance of the land be if not used for biofuel production. 
It should be noted that the source of the steady expansion of the forest area of the EU in the 
past  decades,  and  the  resulting  forest  sink  amounting  to  10%  of  the  EU’s  total  GHG 
emissions,  was  the  reduction  of  agricultural  land-use.  A  reduction  or  reversal  of  this  trend 
would involve significant carbon costs. As can be recalled from figure 5 in chapter 2.4; there 
has also been abandonment of agricultural land in the CIS countries as well as in the US.  

21.2.  Increasing yields 

182 

183 

184 

EN 

The  Millennium  Ecosystem  Assessment  distinguishes  four  categories  of  ecosystem  services: 
Provisioning  services,  regulation  services,  cultural  services  and  supporting  services.  Provisioning 
services are defined as harvestable goods such as fish, timber, bush meat, genetic material, etc. 
Ecofys 
http://www.ecofys.nl/com/publications/Responsible_Cultivation_Areas.htm. 
Total amount of land in oil palm cultivation in Indonesia is supposed to be 4.5Mha. 

Available 

Winrock. 

here: 

and 

117 

   EN 

 
                                                 
Increasing  yields  above  projected  future  trends  which  would  not  have  happened  in  the 
absence  of  biofuel  demand.  This  would  in  theory  suggest  that  the  biofuel  feedstocks  are 
produced  without  increasing  the  pressure  on  land  and  therefore  limiting  indirect  land-use 
change emissions. In this case, only the additional feedstock production should be considered 
as meeting this requirement.  

Although there are certain technical ceilings beyond which yields cannot be improved due to 
regional  characteristics  (i.e.  soil,  climate,  water  availability,  etc),  the  baseline  yield  data  in 
table  3  suggests  that  there  could  be  significant  potential  for  certain  crops  to  improve  their 
yields if the right policy tools were put in place. For example, typical yields of certain crops 
such as palm fruit are assumed to be over 5 times higher in Indonesia/Malaysia compared to 
those achieved in sub-Saharan Africa.  

A project investigating the potential for achieving yield improvements in the palm oil harvest 
in  Liberia,  found  that  an  average  increase  of  2t/ha  of  crude  palm  oil  would  be  achievable 
through  improved  mechanisation  and  the  introduction  of  high  yielding  palm  varieties.  This 
seems significant as a total of 100,000 ha are under palm oil cultivation. Other countries in the 
region that show a similar potential could be Democratic Republic of Congo, parts of Guinea, 
Cote d’Ivoire, Benin, Nigeria and Cameroon185. 

Although opportunities for intensification through yield increases are less readily available in 
regions already achieving yields above the world's average (i.e. EU and USA), improvements 
would seem possible. For example, recent research trials suggest that oil seed rape and winter 
wheat  yields  could  be  improved  significantly  through  improved  agronomy  in  areas  of  EU 
where the yields are already very high186.  

21.3.  Integration of biofuel production with non-bioenergy systems  

Integrating  biofuels  with  non-bioenergy  production  systems  in  ways  that  would  lead  to 
higher  land  productivity.  This  integration  would  need  to  be  additional  to  what  would  have 
happened in the absence of the biofuel demand. 

In  theory,  it  would  seem  possible  to  mitigate  against  indirect  land-use  change  through  the 
integration  of  biofuel  production  with  non-bioenergy  systems  (i.e.  land  used  for  cattle 
farming). This could present particularly significant opportunities for regions, such as Brazil, 
where extensive ranching areas are available. It is in this context that a recent project looked 
at the potential for integration of cattle farming with the production of sugarcane. This project 
reported  a  total  potential  of  over  140Mha  of  pasture  land  could  be  freed  for  sugarcane 
production  in  Brazil  alone  through  this  method  (total  current  land  used  for  sugarcane 
production  is  estimated  to  be  at  8Mha).  This  is  significant  as  Brazil  is  one  of  the  regions 
where most cropland extension is likely to take place187. 

21.4.  Production costs  

A  number  of  case  studies  have  shown  that  production  costs  will  not  be  significantly  higher 
under C2 requirements than current practices although these are likely to be project specific. 
For example, a review of previous case studies exploring the feasibility of the development of 

185 

186 
187 

Ecofys  and  Winrock  2009.  Mitigating  indirect  impacts  of  biofuel  production.  Case  studies  and 
Methodology. 
Agrovista and Northeast biofuels grower network research programme in North East England. 2011.  
See table 3 in chapter 2 of this impact assessment. 

EN 

118 

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oil palm on degraded land in Indonesia suggested that barriers to extension could be more of a 
cultural/social  nature  as  costs  could  in  fact  be  relatively  low.  In  fact,  total  planting  costs 
reported  were  between  500-1000€/ha  cheaper  when  previous  status  was  Imperata  grassland 
compared  to  secondary  forest  and  heathland.  Similarly,  operating  costs  were  up  to  500€/ha 
cheaper on Imperata grassland188.  

188 

Sustainable Oil Palm development on degraded land in Kalimantan (Fairhurst T, McLaughlin D, 2009). 

EN 

119 

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22. 

ANNEX XIII – ASSESSMENT METHODOLOGY 

The  assessment  of  the  policy  options  described  in  section  4  can  give  raise  to  a  range  of 
environmental,  economic,  social  and  wider  impacts.  The  most  relevant  impacts  are  listed  in 
table 20 below.  

s
s
e
n
e
v
i
t
c
e
f
f

E

l
a
t
n
e
m
n
o
r
i
v
n
E

c
i
m
o
n
o
c
E

l
a
i
c
o
S

r
e
h
t
O

Minimise the impact of indirect land-use change on greenhouse gas emissions of 
biofuels,  within  the  wider  policy  objectives  of  the  targets  that  by  2020  at  least 
10% of transport fuels are renewable and that greenhouse gas intensity in road 
transport is reduced by at least 6% compared to 2010. 

Achievement of the 10% target of the Renewable Energy Directive 

Greenhouse gas emissions balance (quantified)  

Biodiversity 

Other (water, soil, air, etc) 

Costs (including production and administrative as appropriate). 

Financial investment stability 

Security of supply (energy and food/feed) 

Trade policies 

Employment 

EU rural development 

Third countries: development objectives  

Commodity markets 

Promoting technological development and innovation 

Coherence with existing GHG methodology 

Table 20: List of key impacts being considered in this assessment. 

23. 

ANNEX  XIV  –  POSSIBLE  RESPONSE  SCENARIOS  TO  REDUCED  BIOFUEL 
AVAILABILITY THROUGH THE INTRODUCTION OF ADDITIONAL REQUIREMENTS 

As explained in section 5, it is expected that options will limit the availability of qualifying 
biofuel  feedstocks,  particularly  biodiesel  feedstocks  as  these  typically  present  both  higher 
direct  and  estimated  indirect  land-use  change  emissions.  Assumptions  are  then  needed  to 

EN 

120 

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develop  potential  scenarios  as  to  where  the  additional  contributions  required  to  meet  the 
legislative targets will come from. 

Figure 19: Possible responses to a limited supply of biofuels 

Therefore, the state of play on a number of issues, such as vehicle compatibility with higher 
biofuel  blends  and  relevant  R&D  developments,  as  well  as  possible  developments  on 
greenhouse gas emissions performance of conventional biofuels need to be considered.  

23.1.  Option B: Possible extreme scenarios 

The main scenario considered here implies that when the threshold is raised to 60%, the least 
efficient palm oil, soy and rapeseed are excluded and not replaced by an increased share of the 
available  conventional  biodiesel  feedstocks  (i.e.  sunflower  and  palm  oil  with  methane 
capture)  but  by  other  available  technologies  (i.e.  non-biofuel,  bioethanol,  etc).  As  such,  for 
analytical purposes the following extreme scenarios have been considered, 

Targets  set  out  in  the  Directives  are  met  through  fossil  fuels  and/or  other  renewable 
B1) 
energies,  without  increasing  bioethanol  blends,  or  the  use  of  waste/residues  biodiesel  or  2nd 
generation  biodiesel  beyond  what  is  already  necessary  to  reach  the  levels  estimated  in  the 
NREAPs. 

B2) 
Targets  set  out  in  the  Directives  are  met  through  higher  bioethanol  blends.  No 
development of 2nd generation biodiesel or waste/residues biodiesel beyond what is estimated 
in the NREAPs.  

B3) 
Targets  set  out  in  the  Directives  are  met  through  increased  use  of  waste/residues 
biodiesel  and  2nd  generation  biodiesel.  Other  renewable  energies  and  bioethanol  blends 
remains as estimated in the NREAPs. 

The  tables  below  outline  the  required  contribution  from  each  technology  for  biofuels  to 
maintain their contribution to the Fuel Quality Directive on the baseline (5.4%).  

Bioethanol [Mtoe]  Double 

counted 

biodiesel [Mtoe] 

Electricity  in  road 
[Mtoe] 

Baseline 

6.7 

1.8

0.7 

EN 

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B1 

B2 

B3 

6.7 

18.3 

6.7 

1.8

1.8

11

1.9 

0.7 

0.7 

These scenarios are included for illustrative purposes only. None of the scenarios above are 
considered realistic as only the contribution from one technology at a time is increased, giving 
rise to very significant additional requirements by 2020, notably:  

•  B1: Increased contribution of 3.9 Mtoe of electricity in road would be required by 2020. 
This would be the equivalent to deploying an additional 9 million electric cars by 2020189. 
For comparison, EU annual car sales are roughly 15 million per year.  

•  B2:  Increased  levels  of  bioethanol,  with  the  average  bioethanol  blends  in  petrol  cars 
increasing from 11% to 25%, as well as an increase in bioethanol processing capacity in 
the EU. 

•  B3:  Increased  contribution  of  9.2  Mtoe  of  biodiesel  coming  from  waste/residues  and  2nd 

generation.  

23.2.  Option D: Possible extreme scenarios 

Based  on  the  preliminary  analysis  of  the  impacts  of  different  indirect  land-use  change 
emission factors at feedstock level, the overarching trend seems to be the need to replace the 
oilseeds  that  fail  to  qualify  with  either  other  biodiesel  feedstocks  available  and/or  increased 
the volume of bioethanol. In line with the broad approach as set out at the beginning of this 
Annex, a number of extreme scenarios have been considered. 

D1)  Targets  set  out  in  the  Directives  are  met  through  fossil  fuels  and/or  other  renewable 
energies, without increasing bioethanol volumes, or the use of waste/residues biodiesel or 2nd 
generation  biodiesel  beyond  what  is  already  necessary  to  reach  the  levels  estimated  in  the 
NREAPs. 

D2)  Targets  set  out  in  the  Directives  are  met  through  higher  bioethanol  volumes.  No 
development of 2nd generation biodiesel or waste/residues biodiesel beyond what is estimated 
in the NREAPs.  

D3)  Targets  set  out  in  the  Directives  are  met  through  increased  use  of  waste/residues 
biodiesel  and  2nd  generation  biodiesel.  Other  renewable  energies  and  bioethanol  volumes 
remain at estimated levels in the NREAPs. 

The  tables  below  outline  the  required  contribution  from  each  technology  for  biofuels  to 
maintain  their  contribution  to  the  Fuel  Quality  Directive  on  the  baseline  (-5.4%).  However, 
the  contribution  from  biofuel  technologies  towards  this  target  is  much  smaller  under  this 
option than under all others, as the estimated indirect land-use change emissions are not only 
included in the greenhouse gas emissions methodology to check whether the biofuel feedstock 

189 

Assumptions:  Electricity  consumption  of  an  electric  car  can  be  assumed  to  be  approximately  0.13 
kWh/km.  Average  annual  electric  distance  travelled  is  assumed  to  be  10,000km  since  they  cannot  be 
used for long distances. Annual electricity consumption of one electric car will be roughly 1300kWh.. 
Expressed  in  toe,  this  is  1300  *  8.6  *  10-5  which  gives  0.12  toe.  Therefore  1  Mtoe  electricity 
consumption by cars implies 8 million cars on the road.  

EN 

122 

   EN 

 
                                                 
in  question  would  pass  or  not,  but  also  included  in  the  reported  carbon  intensity  reduction 
(using the 50th percentile values of sensitivity).  

Bioethanol [Mtoe]  Double 

counted 

biodiesel [Mtoe] 

Electricity  in  road 
[Mtoe] 

Baseline 

D1 

D2 

D3 

6.7 

6.7 

26 

6.7 

1.8

1.8

1.8

16

0.7 

2.3 

0.7 

0.7 

These scenarios are included for illustrative purposes only, as only the contribution from one 
technology at a time is increased, giving rise to scenarios with following requirements to 2020 
of either, i.e.  

•  increased contribution of 5.4 Mtoe of electricity in road would be required by 2020. This 
would be the equivalent to deploying an additional 13 million electric cars by 2020190 for 
D1. For comparison, EU annual car sales are roughly 15 million per year.  

•  D2  requires  increased  levels  of  bioethanol,  with  the  average  bioethanol  blends  in  petrol 
cars needed to increase accordingly (it would need to increase from 11% to 32% for this 
tool alone to achieve given bioethanol volumes). Bioethanol processing capacity in the EU 
would also need to increase (current levels at 4.3 Mtoe) or the total amount of bioethanol 
imports. 

•  increased  contribution  of  14  Mtoe  would  be  needed  from  biodiesel  coming  from 

waste/residues and 2nd generation for D3.  

23.3.  Vehicle compatibility limitations with increasing usage of higher biofuel volumes 
in current fleet  

In  the  context  of  the  policy  options,  the  issues  around  the  compatibility  of  higher  ethanol 
volumes  with  current  fleet,  as  well  as  higher  uptake  of  certain  biodiesel  feedstocks  such  as 
palm  oil,  should  be  considered.  These  issues  are  discussed  in  more  detail  in  the  baseline 
section in chapter 2. 

23.4.  Biodiesel from non-conventional sources  

There are a number of ways in which developments in research and development could help 
replacing  the  production  of  biodiesel  from  feedstocks  with  estimated  high  indirect  land-use 
change  impacts.  These  include  bringing  forward  commercialisation  pathways,  currently  at 
pilot stage, for producing biodiesel from non-land using feedstocks (i.e. algae, pyrolysis oil, 
etc). In addition, research into the development of biodiesel from sugars is also ongoing and at 
pilot  stage  but  could  come  into  the  market  before  2020.  In  addition,  it  may  be  possible  to 
increase  the  contribution  from  waste  feedstocks,  such  as  used  cooking  oil,  for  which  no 
technological developments are needed.  

190 

Assumptions:  Electricity  consumption  of  an  electric  car  can  be  assumed  to  be  approximately  0.13 
kWh/km.  Average  annual  electric  distance  travelled  is  assumed  to  be  10,000km  since  they  cannot  be 
used for long distances. Annual electricity consumption of one electric car will be roughly 1300kWh.. 
Expressed  in  toe,  this  is  1300  *  8.6  *  10-5  which  gives  0.12  toe.  Therefore  1  Mtoe  electricity 
consumption by cars implies 8 million cars on the road. 

EN 

123 

   EN 

 
 
                                                 
23.5.  Potential improvements in greenhouse gas performance  

According to the assessment methodology being applied, the question of compliance with the 
threshold is binary (i.e. whether biofuel feedstocks are in compliance or not), independently 
of  how  close  to  compliance  the  feedstock  might  be.  This  is  an  important  point  for  further 
consideration  as  in  practice  biofuel  producers  can  put  in  place  measures  to  improve  their 
greenhouse gas emissions performance beyond the levels assumed in 2020.  

Although  it  is  difficult  to  establish  where  such  "performance  ceiling"  of  different  biofuel 
feedstocks  may  be,  it  is  believed  that  emission  saving  levels  of  around  75%-80%  can  be 
reached  if  certain  agricultural  practices  (including  using  organic  fertiliser),  using  bio-
methanol  for  trans-etherification  (for  producing  biodiesel  from  vegetable  oil),  and  better 
processing technologies available today (including processing the feedstocks using biomass) 
are used.  

23.6.  Potential contribution to Fuel Quality Directive targets from non-RES sources  

The  potential  for  achieving  additional  reductions  in  fossil  fuel  carbon  intensity  is  high.  The 
main areas of opportunity are at source (up-stream savings) and where the fuel is consumed 
(combustion  savings).  During  the  Fuel  Quality  Directive  negotiations,  the  Commission 
estimated  that  a  total  of  300  Mt  CO2eq  greenhouse  gas  emissions  associated  with  global  oil 
production  from  both  flaring  and  venting  was  possible,  and  that  a  third  of  these  emissions 
could  be  avoided  through  alternative  uses  of  the  gas  at  relatively  low  costs.  Further 
contributions are also possible from capture and storage of refinery emissions depending on 
the  development  of  this  technology,  and  the  supply  of  alternative  fuels  other  than  biofuels 
(LPG, CNG and H2)191. 

191 

Assuming life-cycle GHG emissions for CNG around 76.7gCO2eq/MJ and for LPG 73.6g CO2eq/MJ, 
each 1% increase in the sales of use of natural gas and LPG across the EU as road transport fuel sales, 
would result in a potential reduction of around 0.1% in greenhouse gas intensity. 

EN 

124 

   EN 

 
                                                 
24. 

ANNEX XV – DEVELOPING INDIRECT LAND-USE CHANGE EMISSION FACTORS FROM 
THE RESULTS OF THE MONTE-CARLO ANALYSIS 

There  are  two  basic  approaches  towards  developing  indirect  land-use  change  emissions 
factors according to the level of disaggregation desired. The results in table below show the 
range  of  estimated  feedstock  specific  indirect  land-use  change  emissions  from  the  Monte 
Carlo analysis used for the assessment. All values are shown in grams of CO2-eq./MJ. 

[g/MJ] 

Maize 

Sugar beet 

Sugar cane192 

Wheat - Not specified 

Wheat - Natural gas/CHP 

Wheat - Straw/CHP 

Palm oil 

Palm  oil  with  methane 
capture 

Rapeseed 

Soybean 

Sunflower 

5th 

6 

1 

7 

8 

8 

8 

47 

47 

28 

38 

31 

25th 
percentile 

Central 

75th 
percentile 

95th 

8 

4 

13 

12 

12 

12 

51 

51 

45 

50 

46 

10 

7 

15 

14 

14 

14 

54 

54 

55 

56 

54 

12 

10 

18 

16 

16 

16 

57 

57 

66 

61 

60 

13 

13 

26 

18 

18 

18 

60 

60 

81 

74 

72 

Table  21:  Estimated  indirect  land-use  change  emissions  per  feedstock.  Source:  IFPRI-MIRAGE-
BioF(2011)  

There are a number of ways for developing ILUC factors from these estimates. For example, 
one  way  would  be  to  directly  incorporate  these  numbers  into  the  greenhouse  gas  emissions 
performance  calculation  for  biofuels.  In  that  case,  no  further  adjustment  would  be  required. 
However,  it  could  also  be  argued  that  average  values  for  each  specific  crop  group  could  be 
developed from weighted average of the feedstock data. These are outlined in the table below.  

Maize 

Sugar beet 

Sugar cane 

5th 

7 

5 

5 

25th 
percentile 

Central 

75th 
percentile 

95th 

10 

10 

10 

12 

13 

13 

14 

16 

16 

16 

23 

23 

192 

Although  the  estimated  land-use  impacts  associated  with  second  generation  feedstocks  were  not 
specifically  modelled, they have been assumed to be equal to Brazilian sugar cane in this assessment 
(i.e. high yield energy crop with non-land saving co-products). 

EN 

125 

   EN 

 
 
                                                 
Wheat - Not specified 

Wheat - Natural gas/CHP 

Wheat - Straw/CHP 

Palm oil 

Palm  oil  with  methane 
capture 

Rapeseed 

Soybean 

Sunflower 

7 

7 

7 

34 

34 

34 

34 

34 

10 

10 

10 

47 

47 

47 

47 

47 

12 

12 

12 

55 

55 

55 

55 

55 

14 

14 

14 

63 

63 

63 

63 

63 

16 

16 

16 

74 

74 

74 

74 

74 

Table 22: Estimated indirect land-use change emissions per feedstock. Source: Commission's calculations 
based on weighted average of IFPRI-MIRAGE-BioF (2011) crop specific values.  

The  impacts  associated  with  both  approaches  have  been  considered  in  the  assessment  of 
option D. 

EN 

126 

   EN 

 
25. 

ANNEX XVI – POTENTIAL EFFECTS OF INCLUDING THE ESTIMATED INDIRECT LAND 
USE  CHANGE  GREENHOUSE  GAS  EMISSIONS 
IN  THE  REPORTING  OF  THE 
GREENHOUSE GAS EMISSION SAVINGS OF BIOFUELS  

Option  D  provides  incentives  for  low  indirect  land-use  change  emissions  biofuels  in  two 
ways, as described in chapter 5.5.1 and chapter 5.5.9.1, through; a) the exclusion of biofuels 
with  too  low  savings,  ILUC  included,  compared  to  the  fossil  fuels  they  replace  and  b)  the 
incentives for biofuels with lower ILUC due to the accounting and reporting by fuel suppliers 
under  the  Fuel  Quality  Directive  which  is  likely  to  bring  about  a  significant  price 
differentiation  in  favour  of  low-ILUC  transport  fuels.  This  is  because  these  biofuels  will 
contribute  much  more  than  others  to  the  attainment  of  a  supplier's  obligation  to  reduce  the 
greenhouse  gas  intensity  of  the  fuels  it  supplies.  As  it  was  only  possible  to  analyse  the 
effectiveness  of  the  first  element  using  the  methodology  in  this  Impact  Assessment,  the 
effectiveness of the second element is explored further in this Annex.  

The  discussion  here  focuses  on  the  market  incentives  (element  b)  and  thus  ignores  the 
exlusion  of  certain  feedstocks  resulting  from  element  a.  The  allocation  of  feedstocks  is 
therefore  rather  done  through  cost-minimisation  of  fuel  supplier's  expenditure  on  fuels  as 
required  to  achieve  the  greenhouse  gas  emissions  reductions  mandated  by  the  Fuel  Quality 
Directive. This exercise obviously depends on a range of assumptions, of which some of them 
are  listed  in  a  footnote193.  As  the  methodology  used  in  this  analysis  is  very  sensitive  to 
variation  in  feedstock  price  (i.e.  those  feedstocks  with  lowest  carbon  abatement  costs  are 
prioritised  witrhout  looking  at  any  other  variables  and  their  availability  is  assumed  to  be  in 
most cases unlimited), conclusions presented here are only intended as an illustration of the 
likely impacts.  

The feedstocks are limited to the list know from chapter 5 of the Impact Assessment (i.e. with 
the same estimated GHG performance once the estimated indirect land use change impacts are 
included),  however  with  3  additions:  "Improved  vegetable  oil1",  "Improved  vegetable  oil2" 
and  "ILUC-free  vegetable  oil",  whose  assumed  GHG  performance  fro  this  exercise  is 
included in the table below. The inclusion of the two first categories is intended to reflect the 
possibility of vegetable oil producers to improve their direct greenhouse gas emissions, while 
still  including  the  ILUC  estimate  in  the  reported  emissions.  The  last  category  reflects  the 
potential succesfull development of "ILUC" free biofuels, where the biofuels are produced in 
ways  that  are  certified  not  to  lead  to  indirect  land-use  change  emissions  (with  additional 
certification  costs).  However,  the  latter  catergory  is  not  included  in  the  mix,  as  no  such 
certification scheme has been developed yet. 

193 

Prices of ethanol and vegetable oils are mostly based on F.O Lichts "World ethanol & biofuels report, 
vol.  10  no.  16  April  2012,  page  335  and  "Oils  &  Fats  Int  June  2012  Vol25  No5,  page32.  Cost  of 
crushing  is  assumed  to be 20  $/ton. When costs have not  been  available,  an  estimate  has been  made. 
Biodiesel from FAME is limited to 12.8 Mtoe due to blending constraints (B7 – scenario 2 of the JEC 
study),  ethanol  is  limited  to  max  7.1  Mtoe  in  line  with  scenario  2  of  the  JRC  study  (see  reference  in 
chapter  2.8.1.5),  2nd  generation  non-land  using  biodiesel,  which  in  this  case  refers  to  biodiesel  from 
residues  and  wastes,  and  improved  vegetable  oil2,  are  limited  to  3  and  7  Mtoe  respectively  due  to 
resource  constraints,  sugar  cane  import  is  limited  to  3.5  Mtoe,  which  is  similar  level  as  found  in  the 
IFPRI study. Fossil fuel price is assumed to be 120 $/barrel, and finally it is assumed that 4%points of 
the  6%  target  of  the  FQD  are  achieved  with  the  use  of  biofuels,  the  rest  being  achieved  through 
increased use of electricity in road transport and reduction in flaring and venting emissions). 

EN 

127 

   EN 

 
 
                                                 
Direct 
emissions 
[gCO2/MJ] 

Estimated 
ILUC 
emissions 
[gCO2/MJ] 

Total 
emissions 
[gCO2/MJ] 

Estimated  CO2  abatement 
costs  of  different  biofuels 
[gCO2/€] 

9.3 

0.0 

9.3 

354 

Biodiesel 
- 
non-land  using 
(UCO etc.) 

Sugar cane 

Sugar beet 

Wheat Straw as 
process  fuel  in 
CHP plant 

20.2 

27.1 

21.6 

Corn (maize) 

32.7 

33.5 

Wheat  Natural 
gas  as  process 
in  CHP 
fuel 
plant 

2G  ethanol 
- 
non-land using 

9.0 

15.4 

7.2 

13.8 

10.1 

13.8 

35.6 

34.3 

35.3 

42.7 

47.3 

540 

580 

644 

683 

755 

0.0 

9.0 

882 

Wheat  Process 
fuel 
not 
specified 

50.3 

13.8 

64.0 

1124 

2G  ethanol 
land using 

- 

16.7 

15.4 

32.1 

1272 

2G  biodiesel  - 
land using 

5.4 

Improved 
vegetable oil 2 

25 

15.4 

20.8 

1753 

54.9 

79.9 

4153 

Palm  oil  with 
methane 
capture 

29.3 

54.0 

83.3 

5004 

Improved 
vegetable oil 1 

28 

54.9 

82.9 

5443 

Sunflower 

Fossil fuels 

32.4 

90.3 

53.5 

0 

85.9 

90.3 

6699 

0 

EN 

128 

   EN 

 
 
  
Rapeseed 

Soybean 

Palm oil 

40.2 

46.9 

51.1 

54.9 

56.3 

54.0 

95.1 

103.2 

105.1 

No abatement 

No abatement 

No abatement 

Table 23: Estimated carbon abatement costs of biofuels when ILUC emissions are included. 

A  rough  assessment  of  the  impacts  of  the  estimated  costs  and  greenhouse  gas  emissions 
performance outlined above suggests that the production of bioethanol, and that of advanced 
biodiesel and vegetable oils with an improved greenhouse gas performance would be greatly 
favoured. A number of observations can be made:  

• 

• 

• 

Firstly, advanced 2nd generation land using biodiesel194 with high costs (3 times the 
cost  of  1st  generation  biofuels)  would  seem  to  become  competitive  for  the  fuel 
suppliers due to their good greenhouse gas performance compared to other available 
sources of biodiesel.  

The  use  of  conventional  vegetable  oils  would  be  strongly  discouraged  unless  their 
greenhouse gas performance is improved, as otherwise  they would seem to  be of a 
higher  or  similar  carbon  intensity  than  conventional  fossil  fuel  sources.  However 
improved vegetable oil pathways are being used, and every gram they save is highly 
appreciated by the fuel suppliers. This is highlighted by the fact that the "improved 
vegetable  oil2"  is  only  saving  3  g/MJ  more  than  "improved  vegetable  oil1",  while 
being 7% more expensive, it is still more competitive.  

Analysing the boundary conditions, i.e. what value would it have if one could change 
one of the them (the shadow price), it is clear that the fuel costs for complying with 
the  Fuel  Quality  Directive  would  be  greatly  reduced  if  more  ethanol  could  be 
blended in. This is because the ethanol feedstocks are assumed to be cheaper and in 
general delivers higher greenhouse gas savings, ILUC included, which would result 
in a more favourable carbon abatement price compared to biodiesel alternatives. 

Another question is the availability of so-called "ILUC-free" vegetable oil based biofuels195. 
In the assessment above they are excluded from the mix as no such biofuels currently exist. 
Should  these  become  available  at  moderately  higher  costs  compared  to  uncertified 
alternatives,  they  would  become  more  attractive  to  fossil  fuel  operators  than  advanced 
biodiesel  (i.e.  as  their  price  would  be  lower  for  similar  carbon  abatement  costs)  and  non-
ILUC-free  conventional  biodiesel  (i.e.  as  their  carbon  abatement  cost  would  be  three  times 
higher for the moderate increase in costs).  

194 

195 

The amount of non-land using biodiesel from waste (i.e. UCO and animal fat) is thought to be limited 
and  as  such  has  been  capped  at  3Mtoe.  Should  more  of  this  cheaper  alternative  be  available,  it  is 
expected to take priority over the more expensive 2nd generation land using biodiesel alternative.  
Such biofuels could be similar to the biofuels described under option C2. They are here assumed to cost 
on average 30% more than other vegetable oils. 

EN 

129 

   EN