COMMISSION STAFF WORKING DOCUMENT Impact Assessment on the role of land use, land use change and forestry (LULUCF) in the EU's climate change commitments Accompanying the document Proposal for a DECISION OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on accounting rules and action plans on greenhouse gas emissions and removals resulting from activities related to land use, land use change and forestry
Date: 2012-03-12
Institutions: European Commission
Subjects: accounting system, agri-foodstuffs, climate change, disclosure of information, economic accounts for agriculture, environmental standard, farming sector, greenhouse gas, reduction of gas emissions, renewable energy, silviculture

EUROPEAN COMMISSION 

Brussels, 12.3.2012  
SWD(2012) 41 final 

COMMISSION STAFF WORKING DOCUMENT 

Impact Assessment on the role of land use, land use change and forestry (LULUCF) in 
the EU's climate change commitments 

Accompanying the document 

Proposal for a DECISION OF THE EUROPEAN PARLIAMENT AND OF THE 
COUNCIL 

on accounting rules and action plans on greenhouse gas emissions and removals 
resulting from activities related to land use, land use change and forestry 

{COM(2012) 93 final} 
{SWD(2012) 40 final} 

 
 
 
 
  
 
TABLE OF CONTENTS 

1. 

1.1. 

1.2. 

1.3. 

1.4. 

2. 

Procedural issues and consultation of interested parties .............................................. 3 

Introduction .................................................................................................................. 3 

Organisation and timing............................................................................................... 3 

Consultation and expertise ........................................................................................... 3 

Opinion of the Impact Assessment Board.................................................................... 3 

Problem definition........................................................................................................ 3 

2.1.  What is the issue or problem that may require action? ................................................ 3 

2.1.1.  Enhancing the environmental integrity of the EU's climate change commitments ..... 3 

2.1.2.  Strengthening synergies with wider policy objectives................................................. 3 

2.1.3.  Preparing the ground for more ambitious targets......................................................... 3 

2.2.  What issues need to be addressed to include LULUCF in accounting and what is the 

current state of play? .................................................................................................... 3 

2.2.1.  Addressing the non-permanence of emissions and removals and the influence of 

natural effects on emissions and removals................................................................... 3 

2.2.2.  Ensuring robust monitoring and reporting ................................................................... 3 

2.2.2.1.  Completeness of estimates ........................................................................................... 3 

2.2.2.2.  Accuracy of estimates .................................................................................................. 3 

2.2.2.3.  Time consistency and comparability of estimates ....................................................... 3 

2.2.3.  Ensuring robust accounting rules ................................................................................. 3 

2.2.4.  Defining the policy context for the inclusion of LULUCF in the EU's climate change 
commitment.................................................................................................................. 3 

2.3.  Who is affected?........................................................................................................... 3 

2.4. 

2.5. 

3. 

How would the problem evolve, all things equal?....................................................... 3 

Does the EU have the right to act and is EU added-value evident?............................. 3 

Objectives..................................................................................................................... 3 

3.1.  What are the general and more specific / operational objectives? ............................... 3 

4. 

Policy options............................................................................................................... 3 

4.1.  What are the possible options for tackling the problem and meeting the operational 

objectives?.................................................................................................................... 3 

4.2. 

Options for the policy context in which to include LULUCF in the EU's GHG 
emission reduction commitments................................................................................. 3 

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4.2.1.  Option 1 – No EU action.............................................................................................. 3 

4.2.2.  Option 2 – Include LULUCF as a separate policy framework .................................... 3 

4.2.3.  Option 3 – Include LULUCF in the Effort Sharing Decision...................................... 3 

4.3. 

4.4. 

Options for improving monitoring and reporting......................................................... 3 

Options for accounting................................................................................................. 3 

4.4.1.1.  Accounting option (a): Small changes to the current Kyoto Protocol rules. ............... 3 

4.4.1.2.  Accounting option (b): Likely outcome in the UNFCCC negotiations ....................... 3 

4.4.1.3.  Accounting option (c): UNFCCC+ .............................................................................. 3 

4.5.  Which options have been discarded at an early stage and why?.................................. 3 

5. 

Analysis of impacts ...................................................................................................... 3 

5.1. 

Environmental implications ......................................................................................... 3 

5.1.1. 

Impact of the different options on GHG emissions ..................................................... 3 

5.1.1.1.  Option 2.I – Separate framework for LULUCF (without mitigation targets).............. 3 

5.1.1.2.  Option 2.II – Separate framework for LULUCF (with mitigation targets).................. 3 

5.1.1.3.  Option 3 – Inclusion of LULUCF in the ESD ............................................................. 3 

5.1.2.  Other environmental impacts ....................................................................................... 3 

5.1.3.  Possible contributions to an EU target ......................................................................... 3 

5.2. 

Economic implications................................................................................................. 3 

5.2.1.  Direct abatement costs ................................................................................................. 3 

5.2.1.1.  Option 2.II – Separate framework with mitigation targets .......................................... 3 

5.2.1.2.  Option 3 – Include LULUCF in the ESD..................................................................... 3 

5.2.2.  Costs for the various sectors ........................................................................................ 3 

5.2.2.1.  Agriculture ................................................................................................................... 3 

5.2.2.2.  Forestry ........................................................................................................................ 3 

5.2.2.3.  Impacts by owner structure .......................................................................................... 3 

5.2.3.  Monitoring and reporting costs .................................................................................... 3 

5.2.3.1.  Administrative burden of changing the scope and methods of accounting ................. 3 

5.2.3.2.  Implications of improved monitoring and reporting.................................................... 3 

5.3. 

Social implications ....................................................................................................... 3 

5.3.1.  Costs by Member States............................................................................................... 3 

5.3.1.1.  Option 2.II – Separate framework with mitigation targets .......................................... 3 

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5.3.1.2.  Option 3 – LULUCF included in the ESD................................................................... 3 

5.3.2.  Employment ................................................................................................................. 3 

6. 

Comparing the options ................................................................................................. 3 

6.1.1.  Choosing the right policy context ................................................................................ 3 

6.1.2. 

Improving monitoring and reporting............................................................................ 3 

6.2. 

Concluding comments.................................................................................................. 3 

7. 

8. 

Monitoring and evaluation ........................................................................................... 3 

ANNEXES ................................................................................................................... 3 

8.1. 

Annex I – Monitoring, reporting and verification........................................................ 3 

8.1.1. 

Introduction .................................................................................................................. 3 

8.1.2.  Completeness ............................................................................................................... 3 

8.1.2.1.  Convention reporting ................................................................................................... 3 

8.1.2.2.  Kyoto Protocol reporting.............................................................................................. 3 

8.1.2.3.  Concluding comments.................................................................................................. 3 

8.1.3.  Accuracy ...................................................................................................................... 3 

8.1.3.1.  Underlying methods used to estimate activity data...................................................... 3 

8.1.4.  Underlying methods used to estimate emission factors ............................................... 3 

8.1.5.  Uncertainties ................................................................................................................ 3 

8.1.6.  Recalculations .............................................................................................................. 3 

8.1.7.  Time-series consistency and comparability between MSs........................................... 3 

8.1.7.1.  Definitions.................................................................................................................... 3 

8.1.8.  Verification activities ................................................................................................... 3 

8.1.9.  Costs of improving monitoring .................................................................................... 3 

8.1.9.1.  Step 1 – Achieving completeness in the reporting of categories and pools at a 

minimum level of tier 1................................................................................................ 3 

8.1.9.2.  Step 2 – Increasing the accuracy of the reported key categories and pools to a 

minimum of tier 2......................................................................................................... 3 

8.1.9.3.  3 – Harmonisation ........................................................................................................ 3 

8.1.9.4.  Results .......................................................................................................................... 3 

8.1.10.  Appendix 1 – Overview of problems emerged during 2010 review and answers by 

MS ................................................................................................................................ 3 

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8.2. 

Annex II – Impacts on accounting of threshold values (natural disturbances) and caps 
(forest management)..................................................................................................... 3 

8.2.1. 

Implications of different triggers for the application of provisions for large natural 
disturbances.................................................................................................................. 3 

8.2.2.  Caps on credits and debits in forest management and their implications .................... 3 

8.3. 

Annex III – Methodology (models and calibration) .................................................... 3 

8.3.1.  Description of the models, their linkages and their use ............................................... 3 

8.3.2.  Description of uncertainties in the modelling results................................................... 3 

8.3.3.  Description of the calibration method used ................................................................. 3 

8.4. 

Annex IV – Model results: projected emissions / removals and abatement costs ....... 3 

8.4.1.  Projected emissions and removals (Reference scenario) ............................................. 3 

8.4.1.1.  Models average ............................................................................................................ 3 

8.4.1.2.  G4M and EUFASOM .................................................................................................. 3 

8.4.1.3.  EFISCEN and EUFASOM........................................................................................... 3 

8.4.1.4.  Accounting results for individual MSs and the EU-27(models average) .................... 3 

8.4.2.  Distribution of costs ..................................................................................................... 3 

8.5. 

Annex V – Discarded options ...................................................................................... 3 

8.5.1.  Discarded policy options.............................................................................................. 3 

8.5.1.1.  Splitting LULUCF according to activities for the inclusion in different policy 

frameworks................................................................................................................... 3 

8.5.2.  Discarded accounting options ...................................................................................... 3 

9. 

Bibliography................................................................................................................. 3 

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COMMISSION STAFF WORKING DOCUMENT 

Impact Assessment on the role of land use, land use change and forestry (LULUCF) in 
the EU's climate change commitments 

Accompanying the document 

Proposal for a DECISION OF THE EUROPEAN PARLIAMENT AND OF THE 
COUNCIL 

on accounting rules and action plans on greenhouse gas emissions and removals 
resulting from activities related to land use, land use change and forestry 

List of acronyms 

AD 

A 

AR 

ARD 

BAU 

CAP 

CL 

CM 

COP 

COST 

D 

E 

EF 

Activity Data 

Afforestation 

Afforestation / Reforestation  

Afforestation, Reforestation and Deforestation  

Business as Usual 

Common Agricultural Policy 

Cropland 

Cropland management  

Conference of the Parties 

European Cooperation in Science and Technology 

Deforestation  

Emissions 

Emission Factor 

EFISCEN 

European Forest Information Scenario 

ESD 

EU ETS 

FAO 

FL 

FM 

G4M 

GDP 

GHG 

Effort Sharing Decision 

EU Emissions Trading System 

Food and Agriculture Organization of the United Nations.  

Forest land 

Forest Management  

Global Forest Model 

Gross Domestic Product 

Greenhouse gas 

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GL 

GM 

GPG 

HWP 

IPCC 

JRC 

KP 

Grassland 

Grazing land management  

Good Practice Guidance 

Harvested Wood Products 

Inter-governmental Panel on Climate Change 

Joint Research Centre of the European Commission 

Kyoto Protocol 

LULUCF 

Land Use, Land Use Change and Forestry 

MRV 

MS(s) 

NFI 

NGOs 

NIRs 

R 

REDD 

RES-D 

SMEs 

RV 

TFEU 

Monitoring, Reporting and Verification 

Member State(s) 

National Forest Inventories 

Non-Governmental Organizations 

National Inventory Reports  

Removals  

Reducing Emissions from Deforestation and forest Degradation 

Directive on the promotion of the use of energy from renewable sources 

Small- and Medium sized Enterprises 

Revegetation 

Treaty on the Functioning of the European Union 

UNFCCC 

United Nations Framework Convention on Climate Change 

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List of definitions1 

Accuracy 

Activity data 

Afforestation 

Biomass 

Carbon pool* 

Accuracy  is  a  relative  measure  of  the  exactness  of  an  emission  or  removal  estimate.  Estimates 
should be accurate in the sense that they are systematically neither over nor under true emissions 
or removals, so far as can be judged, and that uncertainties are reduced so far as is practicable. 
Appropriate methodologies conforming to guidance on good practices should be used to promote 
accuracy in inventories. 

Data on the magnitude of human activity resulting in emissions or removals taking place during a 
given period of time. In the LULUCF sector, data on land areas, management systems, lime and 
fertilizer use are examples of activity data. 

The direct human-induced conversion of land that has not been forested for a period of at least 50 
years  to  forested  land  through  planting,  seeding  and/or  the  human-induced  promotion  of  natural 
seed sources.  

Organic  material  both  above  ground  and  below  ground,  and  both  living  and  dead,  e.g.,  trees, 
crops, grasses, tree litter, roots etc. Biomass includes the pool definition for above - and below - 
ground biomass. 

The whole or part of a geochemical feature or system within the territory of a Member State within 
which  carbon,  any  precursor  to  a  greenhouse  gas  containing  carbon  or  any  greenhouse  gas 
containing carbon is stored.  

Carbon stock* 

The quantity of the element carbon stored in a carbon pool. 

Comparability 

Completeness 

Consistency 

Comparability means that estimates of emissions and removals reported by Parties in inventories 
should be comparable among Parties. For this purpose, Parties should use the methodologies and 
formats agreed by the Conference of the Parties (COP) for estimating and reporting inventories. 

Completeness  means  that  an  inventory  covers  all  sources  and  sinks  for  the  full  geographic 
coverage,  as  well  as  all  gases  included  in  the  IPCC  Guidelines  in  addition  to  other  existing 
relevant source/sink categories which are specific to individual Parties (and therefore may not be 
included in the IPCC Guidelines). 

Consistency  means  that  an  inventory  should  be  internally  consistent  in  all  its  elements  over  a 
period of years. An inventory is consistent if the same methodologies are used for the base year 
and all subsequent years and if consistent data sets are used to estimate emissions or removals 
from  sources  or  sinks.  Under  certain  circumstances  referred  to  in  paragraphs  10  and  11  of 
FCCC/SBSTA/1999/6/Add.1, an inventory using different methodologies for different years can be 
considered to be consistent if it has been recalculated in a transparent manner taking into account 
any good practices. 

Cropland 

This  category  includes  arable  and  tillage  land,  and  agro-forestry  systems  where  vegetation  falls 
below  the  threshold  used  for  the  forest  land  category,  consistent  with  the  selection  of  national 
definitions. 

Cropland management* 

Any activity resulting from a system of practices applicable to land on which agricultural crops are 
grown and on land that is set aside or temporarily not being used for crop production 

Deforestation 

The direct human-induced conversion of forested land to non-forested land.  

Disturbances* 

Emission factor 

Forest 

Events including wildfires, insect and disease infestations, extreme weather events and geological 
disturbances, but not harvesting. 

A coefficient that relates the activity data to the amount of chemical compound which is the source 
of later emissions. Emission factors are often based on a sample of measurement data, averaged 
to develop a representative rate of emission for a given activity level under a given set of operating 
conditions. 

An  area  of  land  of  at  least  0.05  hectare  with  tree  crown  cover  or  equivalent  stocking  level  of  at 
least  10  per  cent,  covered  with  trees  with  the  potential  to  reach  a  minimum  height  of  at  least  2 
metres at maturity at their place of growth, including groups of growing young natural trees and all 
plantations  which  have  yet  to  reach  a  tree  crown  cover  or  equivalent  stocking  of  at  least  10  per 
cent or tree height of at least 2 metres, and areas normally forming part of the forest area on which 
there are temporarily no trees as a result of human intervention, such as harvesting, or of natural 

1 

Source: IPCC (2003; 2006), with the exception definitions marked with a star (*).  

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causes, but which are expected to revert to forest 

Forest land 

The land that meets the definition of forest. This category includes all land with woody vegetation 
consistent with thresholds used to define forest land in the national GHG inventory, sub-divided at 
the national level into managed and unmanaged and also by ecosystem type as specified in the 
IPCC  Guidelines.6  It  also  includes  systems  with  vegetation  that  currently  falls  below,  but  is 
expected to exceed, the threshold of the forest land category. 

Forest management* 

Any activity resulting from a system applicable to a forest and aimed at improving any ecological, 
economic or social function of the forest 

Grassland 

Grazing land 
management* 

Key category 

Reforestation 

This  category  includes  rangelands  and  pasture  land  that  is  not  considered  as  cropland.  It  also 
includes systems with vegetation that fall below the threshold used in the forest land category and 
is  not  expected  to  exceed,  without  human  intervention,  the  thresholds  used  in  the  forest  land 
category. This category also includes all grassland from wild lands to recreational areas as well as 
agricultural and silvo-pastural systems, subdivided into managed and unmanaged, consistent with 
national definitions. 

Any activity resulting from a system applicable to land used for livestock production and aimed at 
controlling or influencing the quantity and type of vegetation and livestock produced. 

A  category  that  is  prioritised  within  the  national  inventory  system  because  its  estimate  has  a 
significant  influence  on  a  country’s  total  inventory  of  direct  greenhouse  gases  in  terms  of  the 
absolute level of emissions, the trend in emissions, or both. 

The  direct  human-induced  conversion  of  non-forested  land  to  forested  land  through  planting, 
seeding and/or the human-induced promotion of natural seed sources, on land that was forested 
but  that  has  been  converted  to  non-forested  land.  For  the  first  commitment  period,  reforestation 
activities will be limited to reforestation occurring on those lands that did not contain forest on 31 
December 1989. 

Removals* 

Used, for the purposes of this report, synonymously with "sink". 

Revegetation*  

The direct, human-induced activity intended to increase the carbon stock of any site that covers a 
minimum area of 0.05 hectares, through the establishment of vegetation, where that activity does 
not constitute afforestation or reforestation 

Sequestration 

The  process  of  increasing  the  carbon  content  of  a  carbon  pool  other  than  the  atmosphere.  It  is 
preferred to use the term “sink”. 

Sink* 

Transparency 

Wetland* 

The rate of build-up of CO2 in the atmosphere can be reduced by taking advantage of the fact that 
carbon  can  accumulate  in  vegetation  and  soils in terrestrial  ecosystems.  Any process,  activity  or 
mechanism  which  removes  a  greenhouse  gas  from  the  atmosphere  is  referred  to  as  a  "sink." 
Denoted in accounting and reporting with the negative (-) sign. 

Transparency  means  that  the  assumptions  and  methodologies  used  for  an  inventory  should  be 
clearly explained to facilitate replication and assessment of the inventory by users of the reported 
information. The transparency of inventories is fundamental to the success of the process for the 
communication and consideration of information. 

Any activity resulting from a system for draining and rewetting land that covers a minimum area of 
1 hectare and on which organic soil is present, provided the activity does not constitute any other 
activity referred to in Article 3(1), and where draining is the direct human-induced lowering of the 
soil water table, and rewetting is the direct human-induced partial or total reversal of drainage.This 
category  can  be  subdivided  into  managed  and  unmanaged  according  to  national  definitions.  It 
includes  reservoirs  as  a  managed  sub-division  and  natural  rivers  and  lakes  as  unmanaged  sub-
divisions. 

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1. 

PROCEDURAL ISSUES AND CONSULTATION OF INTERESTED PARTIES 

1.1. 

Introduction 

In  order  to  avoid  dangerous  anthropogenic  interference  with  the  climate  system,  the  overall 
global  annual  mean  surface  temperature  increase  should  not  exceed  two  degrees  Celsius 
above  pre-industrial  levels.  This  ambition  was  recognised  in  the  Cancún  Agreements2  and 
requires global greenhouse gas (GHG) emissions to be cut by at least 50% below 1990 levels 
by 2050, or by 80-95% in developed countries (IPCC, 2007), and has been embraced by the 
European  Council  as  a  long-term  goal.3  The  European  Parliament  similarly  endorsed  the  a 
long-term reduction target of at least 80% by 2050 for the EU and other developed countries.4 
As  a  step  towards  the  necessary  long-term  efforts,  the  Union  has  committed  to  reduce  its 
GHG  emissions  to  20%  below  1990  levels  by  2020,  or  to  30%  if  conditions  are  right.  The 
commitment  forms  part  of  one  of  the  European  Union's  five  headline  targets  in  the  Europe 
2020 Strategy for smart, sustainable and inclusive growth.5 

Land use, land use change and forestry (LULUCF) is not yet part of the EU's GHG emission 
reduction  target  for  2020.  However,  the  European  Council  and  Parliament  requested  the 
Commission  to  assess  the  possibility  to  include  LULUCF  in  the  2020  target  and  make  a 
legislative  proposal,  as  appropriate.  The  timing  of  this  work  was  made  conditional  on  the 
outcome of the negotiations of an international agreement on climate change. In the absence 
of such an agreement at the end of 2010, the Commission is required to report on the results 
of  its  assessment  in  2011  with  the  aim  of  the  proposed  act  entering  into  force  from  2013 
onwards.6  Whilst  substantial  progress  was  made  at  the  Conference  of  Parties  to  the  United 
Nations Framework Convention on Climate Change (UNFCCC) in Cancún in December last 
year, no comprehensive agreement was reached. In fulfilment with the requirements and for 
the  reasons  provided  in  Section  2.1,  this  impact  assessment  accompanies  a  Communication 
(agenda  planning  number 
and 
2011/CLIMA/008). 

legislative  proposal  on  accounting 

for  LULUCF 

Emissions  of  greenhouse  gases  in  the  EU  mainly  come  from  energy  production  and  other 
man-made sources, see Figure 1. But, countering some of the emissions, carbon is absorbed 
(removed)  from  the  atmosphere  through  photosynthesis  and  stored  in  vegetation  and  soils. 
Different land uses and management practices in forestry and agriculture can limit emissions 
of carbon and enhance removals from the atmosphere, see Box 1. Carbon removed from land 

2 
3 

4 

5 

6 

Decision 1/CP.16 
European Council, Brussels, 29-30 October 2009, Presidency conclusions 15265/1/09, as reaffirmed by 
the Environment Council, Brussels, 14 March 2011.  
European  Parliament  resolution  of  4  February  2009  on  "2050:  The  future  begins  today  – 
Recommendations for the EU's future integrated policy on climate change; resolution of 11 March 2009 
on  an  EU  strategy  for  a  comprehensive  climate  change  agreement  in  Copenhagen  and  the  adequate 
provision of financing for climate change policy; resolution of 25 November 2009 on the EU strategy 
for the Copenhagen Conference on Climate Change (COP 15) 
Europe 2020: A strategy for smart, sustainable and inclusive growth COM(2010) 2020 final, Brussels, 
3.3.2010, adopted by the European Council on 17 June 2010 
Article 9 of Decision 406/2009/EC of the European Parliament and of the Council of 23 April 2009 on 
the  effort  of  Member  States  to  reduce  their  greenhouse  gas  emissions  to  meet  the  Community's 
greenhouse gas emission reduction commitments up to 2020 

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can also stay bound in harvested wood products for a long period of time without being re-
emitted  to  the  atmosphere  and  the  recycling of  wood  and  production  of  long-lived  products 
can therefore contribute to mitigation efforts. These practices and uses are covered by the land 
use, land use change and forestry (LULUCF) sector.7 In 2009, LULUCF removed an amount 
of carbon from the atmosphere equal to about 9% of the EU's total greenhouse gas emissions 
in other sectors.  

Figure 1. Emissions and removals per sector in the EU-27 (2009) 

LULUCF

Solvent and Other
Product Use

Waste

Industrial Processes

Agriculture

Energy

-20% -10%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Note: Negative numbers denote net removals and positive numbers net emissions. 

Source: EEA (2011) 

In  addition,  land  resources  can  contribute  to  mitigation  efforts  in  other  sectors  through  the 
substitution of fossil fuels in energy production and greenhouse gas intensive materials such 
as steel and cement with biomass (see e.g. Sathre and O'Connor, 2010), see Box 1.  

Box 1. Possible contribution of land use, land use change and forestry to climate change mitigation 

Agriculture  contributes  in  a  number  of  ways.  Measures  include  agronomic  practices  such  as  using  improved  crop  varieties, 
extending crop rotations (a shift to perennial crops) and avoiding or reducing the use of unplanted fallow through green cover; 
agro-forestry practices which provide higher carbon stocks through the tending of livestock or growing of food crops on land that 
also  grows  trees  for  timber,  energy  or  other  wood  products;  adjustments  of  the  intensity  and  timing  of  grazing  on  lands  can 
influence  the  growth,  carbon  allocation  and  flora  of  grasslands  and  thereby  the  removals  and  storage  of  carbon  in  soils; 
enhanced productivity of croplands and grasslands through returning or leaving organic materials (farmyard manure, straw, crop 
residues) on the land; improved management of organic soils through avoiding the drainage of these soils or re-establishing a 
high water table on peat lands; and restoration of degraded lands. 

Similarly,  there  are  many  mitigation  opportunities  in  forestry.  They  include  the  conversion  of  non-forest  land  to  forest 
(afforestation); avoiding conversion of forest land to other types of land (deforestation); productiivity increases, conservation of 
carbon  in  existing  forests  e.g.through  optimized  tending  and  thinning,  continuous  crown  harvesting  (selective  logging),  longer 
rotation  periods  of  trees,  avoidance  of  clearfelling;  conversion  to  wilderness  forests  and  more  widespread  use  of  prevention 
measures to limit the impacts of disturbances such as fires, pests and storms.  

In addition to the opportunities directly linked to forestry and agriculture, there are potential mitigation benefits in the industry 
and energy sectors if agricultural land and forests are managed for production of timber and energy. In this respect enhanced 
production  in  existing  forests  through  adjusting  rotations  closer  to  the  productive  maximum,  more  production  from  low-
production forests, increasing the harvest of timber offcuts and branchwood and changing species composition and growth rate 

7 

Other greenhouse gases from agricultural activities, e.g. methane and nitrous oxide from ruminants and 
fertilisers, do not count under LULUCF, which deals primarily with carbon emissions and removals in 
vegetation and soils. 

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are equally important. While carbon is stored in vegetation and soils, it can also be stored for several decades in products, and 
industry can make an important contribution to mitigation through increasing the recycling of wood and / or production of pulp, 
paper and wood products. The bio-based industry can make use of crops grown for material substitution (e.g. hemp and grass 
for insulation instead of glass fibre, straw used for furniture production, biodegradable cutlery made from maize starch, car door 
panels made from flax or sisal plants, hemp plastic) or energy (e.g. biomass for energy instead of fossil fuels).  

The measures in the different sectors have different advantages and limitations. An important consideration is that the positive 
impacts of measures that increase carbon stocks in vegetation and soils eventually saturate and are potentially impermanent. 
Equally, measures that avoid greenhouse gas emissions through the use of wood or other biomass instead of other materials 
may have negative impacts on carbon in vegetation in soil. It is therefore important to substitute materials and energy sources 
that  have  relatively  high  greenhouse  gas  emissions  during  their  lifecycle.  See  Matthews  et  al.  (2011)  for  more  details  on  the 
different measures and their potentials.  

1.2. 

Organisation and timing 

For the preparation of this initiative, close inter-service consultation was ensured through the 
establishment of an inter-service group and impact assessment steering group which oversaw 
and  followed  the  impact  assessment  work.  DG  Environment,  DG  Agriculture  and  Rural 
Development,  the  Joint  Research  Centre  (JRC),  DG  Research  and  Innovation,  DG  Energy, 
DG Economic and Financial Affairs, DG Enterprise and Industry, DG Legal Services and the 
Secretariat General were directly involved.  

The  work  draws  on  input  from  two  contracts;  one  which  involved  investigating  different 
options  for  the  inclusion  of  the  sector  in  the  EU's  reduction  commitment  (Matthews  et  al. 
2011; Watterson et al. 2011) and one which involved modelling the projected emissions and 
removals  from  the  sector  as  well  as  the  impacts  on  the  sector  and  Member  States  (MSs)  of 
different  options  (Böttcher  et  al.,  2011).  The  work  also  builds  on  input  from  the  JRC  on 
modelling and on monitoring and reporting (JRC 2011a and 2011b, see Annexes II and IV to 
this report). 

1.3. 

Consultation and expertise 

A number of consultative initiatives were undertaken in support of the work: 

•  An  expert  group  on  climate  policy  for  LULUCF  was  established  in  2010  under  the 
European Climate Change Programme . The group involved a wide range of stakeholders: 
environmental  NGOs,  trade  associations,  experts  from  public  administrations  and 
researchers. The objective was to define and provide input on critical issues related to the 
inclusion  of  the  LULUCF  sector  in  the  EU's  climate  change  mitigation  efforts,  i.e.  a 
scoping  and  steering  exercise.  The  summary  report  is  available  on  the  Commission's 
website http://ec.europa.eu/clima/events/0029/index_en.htm 

•  In addition, an online public consultation was carried out in 2010 to collect views on the 
opportunities and challenges related to the inclusion of the sector in the EU's commitments. 
A  total  of  153  responses  were  received,  representing  the  views  of  private  companies, 
business and industry organisations, individuals and private land owners, NGOs, academia 
and  research  and  public  authorities.  The  same  questions  were  subsequently  used  in  a 
separate  consultation  with  MSs  and  received  14  responses.  The  results  of  both 
consultations  have  been  published 
and  2011b) 
in 
http://ec.europa.eu/clima/events/0029/index_en.htm 

(Entec,  2011a 

reports 

•  The Commission also held a stakeholder meeting on 28 January 2011 in Brussels. Around 
75  participants  representing  MSs,  trade  associations,  environmental  NGOs  and  research 
institutes took part in the discussions. The proceedings are available on the Commission's 
website. http://ec.europa.eu/clima/events/0029/index_en.htm  

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The key findings of the consultation process are presented in boxes at the beginning of the relevant sections of this report. 

1.4. 

Opinion of the Impact Assessment Board 

The  impact  assessment  (IA)  was  discussed  at  a  meeting  of  the  IA  Board  (IAB)  on  4  May 
2011.  Following  the  IAB's  recommendations,  the  report  now  clearly  states  that  the  option 
(2.II)  which  incorporates  mitigation  targets  for  LULUCF  is  included  for  illustrational 
purposes and to initiate further discussions. This impact assessment considers accounting for 
LULUCF  in  the  context  of  the  20%  GHG  emission  reduction  commitment  and  not  in  the 
context of a step-up of the EU's overall efforts, as discussed in Sections 4 and 6, and there are 
uncertainties  associated  with  the  modelling  and  inventories  which  affect  the  potential  to  set 
targets at this stage, see Annex III. A commentary on the model-based predicted impacts and 
references to more information is provided in Annexes III and IV. The report also provides a 
description  of  the  practical  and  political  context  in  which  the  accounting  for  LULUCF  is 
assessed throughout the report, in particular in Sections 2.1 and 6. Finally, references to the 
results of the various stakeholder consultations have been integrated in Sections 1 and 4. 

2. 

PROBLEM DEFINITION  

2.1.  What is the issue or problem that may require action?  

The purpose of this report is to assess how LULUCF may be addressed in relation to the EU's 
GHG  emission  reduction  commitments.  Accounting  for  the  sector  would  enhance  the 
environmental  integrity  of  the  commitments,  strengthen  the  overall  coherence  of  climate 
policy and improving the economic efficiency when taking on more ambitious commitments.  

2.1.1.  Enhancing the environmental integrity of the EU's climate change commitments 

The  current  partial  accounting  risks  hiding  real  emissions  and  negative  trends  in  emissions 
and  removals.  The  IPCC  Good  Practice  Guidance  (GPG)  for  estimating  GHG  inventories 
(1996; 2003, see p. 3.261) says that emissions from biomass used for energy should be noted 
but  not  included  in  accounting  for  the  Energy  sector  or  other  sectors  that  produce  biomass 
energy. In other words, emissions from biomass based energy production are recorded as zero 
and  it  is  instead  assumed  that  these  emissions  are  accounted  for  in  the  LULUCF  sector. 
Furthermore, unless harvested biomass is used for energy or industrial purposes or remains in 
situ it will ultimately end up in solid waste disposal sites (SWDS) but the waste sector does 
not estimate changes in the carbon stock in SWDS.  

In  summary,  this  means  that  unless  emissions  due  to  utilisation  of  harvested  biomass  are 
accounted  for  in  the  LULUCF  sector,  they  will  not  enter  accounting  at  all.  Important 
emissions will therefore be disregarded and apparent GHG savings in other sectors (stemming 
from the use of biomass for energy production instead of e.g. fossil fuels) may in fact not be 
real.  

2.1.2. 

Strengthening synergies with wider policy objectives 

Including  the  sector  in  accounting  would  also  enhance  the  coherence  of  the  EU's  overall 
climate policy for several reasons:  

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•  Combating  climate  change  is  one  of  the  five  headline  targets  of  the  "Europe  2020" 
strategy.8,  9 By reducing GHG emissions by 20% compared to 1990 levels, increasing the 
share  of  renewables  in  final  energy  consumption  to  20%,  and  moving  towards  a  20% 
increase  in  energy  efficiency  the  EU  will  contribute  to  the  overall  objective  of  smart, 
sustainable and inclusive growth. The Council and Parliament have agreed that all sectors 
should  contribute  to  reaching  the  targets.  This  is  important  also  for  the  EU's  role  in 
promoting a level playing field for businesses and a fair distribution of effort. 

•  Climate  change  mitigation  will  continue  to  play  an  important  role  in  the  reformed 
Common  Agricultural  Policy  (CAP).  Agricultural  emissions  of  CH4  and  N2O  from 
fertilization,  livestock  and  manure  are  already  reflected  in  targets  (because  they  are 
included in the reporting of the "Agriculture" sector) whereas CO2 emissions and removals 
from soils and vegetation are not (since they are reported under LULUCF). Thus, closely 
correlated  emissions,  often  occuring  on  the  same  land,  and  sometimes  as  a  result  of  the 
same activities, are not reflected in their entirety in accounting. The 2010 Communication 
on  the  future  CAP10  outlines  how  the  environmental  performance  of  the  CAP  could  be 
enhanced  through  a  mandatory  "greening"  component  of  direct  payments  that  supports 
environmental  measures  and  give  priority  to  actions  addressing  climate  change  and 
environmental  goals.  One  benefit  which  these  greening  components  hold  in  common  is 
carbon sequestration, see Table 1. Accounting is necessary for the efforts invested by MSs, 
foresters  and  farmers  to  be  reflected  in  the  EU's  efforts  to  reach  more  ambitious  GHG 
reduction  targets.  Measures  to  enhance  and  protect  carbon  stocks  also  demonstrate  co-
benefits for adaptation, through e.g. increased water holding capacity and reduced erosion, 
and for biodiversity (Natura 2000). 

•  In  addition,  the  provision  of  renewable  energy  is  an  integral  part  of  the  "Europe  2020" 
targets and the legitimacy of policies that directly or indirectly promote the use of biomass 
for energy production, such as the Renewable Energy Directive (RES-D)11, hinges on the 
correct accounting of resulting emissions and removals. The accounting of LULUCF can 
ensure  that  emissions  and  removals  are  correctly  reflected  and  will  balance  incentives 
between different uses of biomass.  

•  Finally, the LULUCF sector forms part of the EU's commitment under the Kyoto Protocol 
(KP) in 2008-12. Therefore, whatever reductions in emissions or increases in removals the 
EU  and  its  MSs  achieve  and  use  for  compliance  with  that  commitment  have  to  be 
maintained also in future commitment periods. Indeed, COP1612 confirmed that LULUCF 
will continue to count towards Parties' efforts in future commitment periods and this would 
need to be mirrored by the EU in its domestic commitments. 

8 
9 

10 

11 

12 

Council Conclusions 17 June 2010, http://ec.europa.eu/eu2020/pdf/council_conclusion_17_june_en.pdf 
Europe 2020 – A European strategy for smart, sustainable and inclusive growth, 
http://europa.eu/press_room/pdf/complet_en_barroso___007_-_europe_2020_-_en_version.pdf  
European  Commission  (2010),  "The  CAP  Towards  2020  –  Meeting  the  food,  natural  resources  and 
territorial challenges of the future", COM(2010) 672 final.  
Directive 28/2009/EC of the European Parliament and of the council of 23 April 2009 on the promotion 
of the use of energy from renewable sources. 
Decision 1/CMP.6 

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Table 1. Possible carbon sequestration benefits of a post-2013 CAP 

Pillar One "Greening Components" 

Permanent Pasture 

Crop Diversification 

Ecological Set-aside 

Natura 2000 

Description of 
measure 

Protect permanent 
pasture  

Several crops at the same 
time on the farm  

Share of farm area to be 
devoted to green 
infrastructure 

Assure survival of valuable 
and threatened species 
and habitats 

C sequestration 
benefits 

Maintain and enhance 
carbon stocks 

Increased soil organic 
matter 

Carbon sequestration for 
permanent crops 

Maintain but not increase 
carbon stores 

Grasslands contain 
three times the carbon 
in arable land 

Potential reduction in 
carbon losses 

Greater benefit if non 
rotational 

Extensive systems = above 
ground biomass (carbon 
storage) 

Grassland conversion is 
a hotspot for emissions 

Reduced bare soil = 
reduced carbon loss 

Of high benefit if 
encouraged on organic 
soils 

2.1.3.  Preparing the ground for more ambitious targets 

There  is  also  scope  for  economic  efficiency  gains  from  including  LULUCF  in  accounting. 
The  Roadmap  for  moving  to  a  competitive  low  carbon  economy  in  205013  shows  that 
significant  additional  climate  mitigation  efforts  will  be  required  across  all  sectors,  and  that 
agriculture  and  forestry  will  become  even  more  important  over  time  both  in  terms  of 
preservation  and  enhancement  of  carbon  stocks  and  as  a  feedstock  for  energy  and  material 
production.  Whilst  opportunities  to  remove  additional  GHGs  from  the  atmosphere  appears 
relatively limited in the short term (see Section 5 of this report), the potential cost-efficiency 
of  both  short-  and  long-term  efforts  to  reach  higher  targets  than  the  current  one  would  be 
compromised if mitigation opportunities are not taken into account.  

2.2.  What issues need to be addressed to include LULUCF in accounting and what is 

the current state of play? 

Whilst  there  are  good  reasons  to  account  for  LULUCF  in  the  EU's  climate  change 
commitments, accounting is not trivial. The Council and Parliament require14 that three issues 
are addressed in this impact assessment; in particular (1) how to ensure permanence and the 
environmental  integrity  of  the  sector's  contribution  to  the  commitments,  how  to  achieve 
robust  (2)  monitoring  and  (3)  accounting.  Another  important  issue  is  to  determine  (4)  the 
policy context in which to include the sector. These aspects are elaborated in this section.  

2.2.1.  Addressing  the  non-permanence  of  emissions  and  removals  and  the  influence  of 

natural effects on emissions and removals 

Non-permanence  refers  to  the  reversibility  of  carbon  sequestered  in,  or  released  from,  the 
biosphere (Schlamadinger et al., 2007a). Reversals can be caused by natural disturbances such 
as  fires,  droughts,  pests  etc.  and  to  some  extent  storms.  Events  which  may  increase  in 

13 

14 

Communication  from  the  Commission  to  the  European  Parliament,  the  Council,  the  European 
Economic  and  Social  Committee  and  the  Committee  of  the  Regions,  Brussels  8.3.2011,  COM(2011) 
112 final. 
Decision No 406/2009/EC of the European Parliament and of the Council of 23 April 2009 on the effort 
of Member States to reduce their greenhouse gas emissions to meet the Community's  greenhouse gas 
emission reduction commitments up to 2020. 

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frequency  and  magnitude  in  the  future  (see  e.g.  IPCC,  2007),  but  also  as  a  result  of 
management decisions, e.g. to harvest or plant trees. The IPCC (2003; 2010) has concluded 
that  there  is  currently  no  practicable  methodology  that  can  factor  out  direct  human-induced 
from indirect human-induced effect and natural emissions and removals at one point in time. 
The  IPCC  GPG  has  therefore  introduced  estimates  of  GHG  on  managed  land  as  an 
approximation of human-induced emissions and removals. Accounting methods are important 
to  factor  out  natural  influences  between  different  points  in  time  (see  e.g.  Canadell  et  al., 
2007). 

Fluctuations in emissions and removals in forests are significant. Figure 2 shows year-on-year 
changes in emissions and removals between 1990 and 2008 relative to the total emissions in 
the  non-trading  sectors  (regulated  by  the  Effort  Sharing  Decision;  ESD).  Whereas  the  EU 
average over the period  varies between 1  and 4%,  the fluctuations in individual MSs are as 
large as 60%, as illustrated by the spread of dots (each representing a MS) in the figure.  

The high variability of removed or emitted  GHGs  caused  by  natural  phenomena  may  affect 
countries'  ability  to  comply  with  commitments  and  raise  the  question  of  how  to  deal  with 
large natural disturbances in a commitment regime. The inter-annual fluctuations complicates 
the possibility of including LULUCF in the commitment on the basis of annual compliance – 
a key feature of both the ESD and the EU ETS which currently regulate the EU's 2020 target. 

Figure 2. Year-on-year fluctuations in emissions and removals (in forests remaining forests) over the period 1990-2008 
as a percentage of 2008 emissions in the non-trading sectors (ESD)  

70%

60%

50%

40%

30%

20%

10%

0%

0
1990

5
1995

10
2000

15
2005

Note: Each dot represents the inter-annual fluctuations of a MS in a given year. Percentages are expressed in absolute terms. 

Source: Calculations are based on data from EEA (2011) and the EU ETS data viewer (2010) 

2.2.2.  Ensuring robust monitoring and reporting 

GHG dynamics in the LULUCF sector involve vegetation and soil carbon pools and often a 
complex  web  of  emissions  and  removals  (for  a  detailed  description,  see  Matthews  et  al., 
2011).  Their  estimation  requires  investments  in  monitoring  and  reporting  capacity.  MSs  are 
obliged  to  report  annually  to  the  UNFCCC  on  emissions  and  removals  from  forest  land, 
cropland,  grassland  and  all  land  use  changes.  The  Kyoto  Protocol  adds  additional  reporting 
requirements for afforestation, reforestation and deforestation activities and, where applicable, 

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forest management, cropland and grazing land management and revegetation. Three important 
aspects of the current state of monitoring and reporting are discussed below, and more details 
are provided in Annex I. 

2.2.2.1.  Completeness of estimates 

In  2010  reporting  under  the  UNFCCC  was  nearly  complete  for  forest  land  but  there  were 
important  gaps  in  reporting  for  cropland  and  grassland  (see  Table  A1.2  in  Annex  I).  At  the 
same  time,  the  expert  review  of  the  first  reporting  under  the  KP  pointed  to  the  need  for 
improvements, particularly as regards soil and dead organic matter (JRC, 2011a). There were 
differences in reported data between MSs where reporting in the new MSs was generally less 
complete than in the EU-15. However, the completeness of reporting improved in recent years 
(Ciencala et al., 2010; and JRC, 2011a), especially for land use changes, likely as a result of 
the  requirements  to  report  under  the  KP  which  is  expected  to  bring  about  further 
improvements in the next few years. 

2.2.2.2.  Accuracy of estimates 

The IPCC GPG defines accuracy as a relative measure which means that estimates should not 
be  systematically  over  nor  under  true  emissions  or  removals  (see  List  of  definitions). 
Countries  should  seek  to  provide  the  highest  possible  accuracy  of  the  estimates  with  the 
resources  available.  This  is  captured  by  two  methodological  concepts:  “key  category”15  and 
“tier”16. A higher  tier  generally  provides  more  accurate  estimates.  Key  categories  should  be 
estimated with higher tiers (i.e. tier 2 or 3). Usually, MSs use a combination of different tiers 
(depending on the land use category or carbon pool) and higher tiers are more often used in 
the EU-15 than in the new MSs. Higher tiers are commonly applied to calculate emissions for 
forest biomass, whereas the lower tiers are frequently used for dead organic matter and soils. 
Currently, in some MS lower tiers than those required are applied17.  

Another  measure  of  the  accuracy  of  the  data  is  the  level  of  uncertainty  associated  with 
estimates.  Based  on  information  included  in  MSs’  GHG  inventories,  the  uncertainty  in 
LULUCF  is  35%,  with  estimates  for  forest  land  at  26%  and  for  cropland  and  grassland 
combined  at  64%,  see  Table  2.  The  uncertainty  is  high  compared  to  e.g.  fuel  combustion, 
transport  and  industrial  processes,  but  similar  to  fugitive  emissions  and  smaller  than  that  of 
agriculture (non-CO2 GHGs), all which are already part of the EU's GHG reduction target for 
2020. 

15 

16 

17 

The key categories are those categories that have a significant influence on a country’s total inventory 
of greenhouse gases in terms of the absolute level or trend of emissions and removals (the uncertainty 
of estimates may also be taken into account). Having accurate estimates for the key categories should be 
priority  for  countries  during  inventory  resource  allocation.  Methods  to  estimate  key  categories  are 
provided by IPCC. 
A  tier  represents  a  level  of  methodological  complexity  to  estimate  emissions  or  removals.  In  this 
respect, it is useful to recall the two basic inputs required to estimate emissions or removals: “activity 
data”  and  “emissions  factors”.  For  LULUCF,  activity  data  typically  refers  to  the  area  of  a  category; 
emission factors refer to emissions/removals per unit area. Any estimate of emissions or removals can 
be expresses as activity data multiplied by the relevant emission factor. Tier 1 is the basic IPCC method 
(associated to spatially coarse activity data and default IPCC emission factors), Tier 2 is an intermediate 
method (i.e. often using the same method as tier 1, but with higher resolution activity data are country-
specific emission factors), and Tier 3 is the most demanding method in terms of complexity and data 
requirements (i.e. country-specific methods or models that use high-resolution and finely disaggregated 
activity data and emissions factors). 
Compare Tables A1.10 and A1.11 in Annex I where tiers 2 or 3 should be applied to key categories. 

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Table 2. Uncertainty of GHG emission estimates at the EU level  

Sector  

Fuel combustion 

Transport 

Industrial processes 

Waste 

Fugitive emissions 

Agriculture (all categories) 

Enteric fermentation 

Manure management 

Rice cultivation 

Agricultural soils 

LULUCF (all categories) 

Forest land 

Cropland and grassland 

Level of uncertainty (%) 

2

6 

5 

21 

32 

68 

12 

26-61* 

20 

50-157* 

35 

26 

64 

Note: * The level of uncertainty varies with the type of GHG. The estimates are for the EU-15 and indicative, but are similar 
for the EU-12 (JRC, 2011a). 

Sources: EEA (2010), JRC (2011a) and Leip (2010) 

2.2.2.3.  Time consistency and comparability of estimates 

The  term  “consistency”  of  data  means  that  the  same  methodologies  and  consistent  datasets 
should  be  used  in  the  calculation  of  whole  time  series.  The  consistency  of  data  over  time 
within MSs appears to be reasonably good. Recalculations of reported data are frequent and 
sometimes substantial (see Annex I) but as long as the whole time series of data is updated 
this is not an issue for time consistency. However, the variability in tiers applied by different 
MSs and the existing flexibilities in definitions (see Annex I and e.g. Lawrence et al. 2010) 
suggest  that  data  may  not  be  fully  comparable  among  MSs.  For  instance,  National  Forest 
Inventories  have  been  developed  for  different  purposes  (socio-economic,  historical  and 
ecological) and over different time periods. This has resulted in variations in definitions (e.g. 
forest,  growing  stock  volume  and  land  use  change)  and  in  methodological  approaches. 
Official  frameworks,  exist  for  comprehensive  monitoring  of  soils  in  most  MSs  Soil 
inventories  exist  in  very  few  MS.  They  are  generally  heterogeneous  in  methodology  and 
coverage,  both  between  and  within  countries  (Arrouays  et  al.,  2008).  However,  for  the 
purpose of UNFCCC and KP reporting, the term “comparability” essentially refers to the fact 
that  countries  should  use  IPCC  methodologies  and  agreed  formats  for  estimating  and 
reporting inventories. Compliance by MSs with the IPCC GPG is therefore a priority. 

In summary, monitoring and reporting improved significantly in the last years and will likely 
continue  to  do  so  during  the  first  commitment  period  of  the  KP.  The  current  situation  is 
sufficient for accounting for LULUCF; indeed, it is already being done in the KP. However, 
further  consideration  is  needed  in  terms  of  how  to  improve  the  reporting  of  carbon  pools, 
particularly  dead  organic  matter  and  soils,  especially  so  in  the  view  of  the  more  stringent 
reporting  requirements  for  tier  1  level  set  in  the  2006  IPCC  Good  Practice  Guidance.  The 
level of uncertainty in estimates of emissions and removals is higher than in other sectors (in 
particular  those  regulated  under  the  EU  ETS)  but  notably  lower  than  that  of  the  agriculture 
sector  which  is  already  part  of  the  EU's  climate  change  commitments.  Recalculations  are 
more common and significant in LULUCF than in other sectors and make it problematic to 

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incorporate LULUCF in a system of annual compliance, a requirement which underpins the 
ESD and EU ETS. 

2.2.3.  Ensuring robust accounting rules 

Although LULUCF does not yet count towards the EU's GHG emission reduction target for 
2020,  it  does  count  towards  the  EU  and  other  Parties'  commitments  under  the  KP  in  2008-
2012 and will do so for the second commitment period. For the first commitment period under 
the  KP,  a  set  of  rules  is  used  to  account  for  different  directly  human-induced  activities: 
afforestation, reforestation, deforestation, forest management, cropland management, grazing 
land management and revegetation. The rules differ for the different activities (see Watterson 
et al. 2011 for a description). They have been subject to much criticism18 and, as reflected in 
the  international  negotiations  over  the  last  years,  there  is  generally  a  consensus  that 
improvements are needed.  

Rules for the second  commitment period, addressing some of these improvements, was laid 
down with the draft decision in Durban in December 2011. However, these rules will apply 
internationally  only  when  a  second  commitment  period  is  finally  agreed  on  and  enters  into 
force  through  ratification  by  the  Parties.  Therefore,  when  considering  the  inclusion  of 
LULUCF in the EU's climate change commitments, the below points and possible alignment 
with the revised rules decided upon in Durban need to be considered: 

•  Accounting for forest management does not reflect human-induced emissions and removals 
in the first commitment period. Far from all emissions and removals in LULUCF are the 
result  of  human  intervention.  As  noted  above  (see  Section  2.2.1),  the  anthropogenic  and 
natural  factors  cannot  be  separated  at  a  single  point  in  time.  The  rules  laid  down  for  the 
second commitment period address this issue by introducing accounting using a reference 
level.  A  reference  level  is  an  estimate  of  future  emissions  or  removals  based  on  a 
continuation  of  historical  emissions  and  the  effect  of  the  implementation  of  known 
measures. Credits or debits are thus calculated based on whether the actual performance in 
the sector provides for more emissions or removals than anticipated.  

•  The provision of incentives for mitigation efforts in forest management is insufficient. With 
current accounting rules, credits are generated as long as a party reports removals that are 
greater than emissions, whether or not they are the result of human intervention. They are 
limited by a politically established cap. There is no incentive to mitigate once removals (or 
emissions) exceed the cap as the resulting changes will not be counted. This principle will 
be carried into a second commitment period also, as it was confirmed in the draft decision 
on LULUCF in Durban in December 2011. 

•  Emissions  resulting  from  deforestation  may  be  understated  in  accounting.  Despite  the 
existence of a cap on credits from forest management (see above bullet), countries may use 
removals above the cap to compensate emissions from debits that result from deforestation. 
The maximum allowance (equivalent to 165 MtCO2) for each Party over the commitment 
period is very generous, meaning that large emissions from deforestation may potentially 
not be accounted for. The so-called compensation rule was left out of the Draft Decision on 
LULUCF and will not apply for a second commitment period under the Kyoto Protocol. 

18 

See Watterson et al. (2011) and e.g. Schlamadinger et al. (2007b), Höhne et al. (2007) and Fry (2002 
and 2007) for an overview. 

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•  Accounting of emissions and removals is partial and inconsistent. Accounting is currently 
partly mandatory (afforestation, reforestation and deforestation) and partly voluntary (any 
or  all  of  forest  management,  cropland  management,  grazing  land  management  and 
revegetation). Just over half of the MSs account for forest management and only three for 
cropland and / or grazing land management (see Table 3). Whilst there are some benefits 
associated with the voluntary nature of accounting of some activities, e.g. countries have 
the option not to take on the burden of reporting and accounting if emissions and removals 
are deemed to be insignificant, it also gives little incentive for parties to select an activity if 
it  is  thought  to  generate  debits.  In  addition,  it  introduces  inconsistency  and  limited 
comparability between countries in the sense that some MSs account and others not, and 
because non-CO2 emissions from managed land must be accounted in the agriculture sector 
but  CO2  from  the  same  land  may  be  ignored.  The  Durban  decision  made  accounting  for 
Forest Management activities mandatory, and thereby adressed the issue partly. However, 
accounting for CO2 emissions from agricultural land and wetlands remain voluntary. 

•  Accounting does not always reflect the actual time of emissions. Current accounting rules 
make the assumption that carbon is released to the atmosphere instantaneously as a result 
of  harvesting.  Whilst  this  may  be  a  good  proxy  for  very  short-lived  products  such  as 
biomass  that  is  used  for  energy  purposes,  wood  used  for  more  durable  products  such  as 
sawn-wood  or  wood  panels  used  for  construction  can  retain  carbon  for  several  decades 
(IPCC, 2006). The different life time of products and the time at which emissions occure 
are  not  reflected  in  the  KP  rules  for  the  first  commitment  period.  In  Durban  the  parties 
agreed that it should be possible to account gradually for emissions from harvested wood 
products  better  reflecting  the  actual  time  of  emission.  In  future  reporting,  internationally 
agreed half lifes of products, or equivalent country specific data of sufficient quality can be 
used to  calculate  the amount of carbon still retained in a given category of products at a 
given point in time for each country. 

Table 3. Overview of activities that MSs have chosen to account for during the first commitment period of the KP 

Forest management 

Cropland 
management 

Grazing land 
management 

Denmark, Portugal 
and Spain 

Denmark and 
Portugal 

Member  States 
chosen 
have 
account 
for 
different activities 

that 
to 
the 

Czech Republic, 
Denmark, Finland, 
France, Germany, 
Greece, Hungary, 
Italy, Latvia, 
Lithuania, Poland, 
Portugal, Romania, 
Slovenia, Spain, 
Sweden and the 
United Kingdom 

Revegetation 

Romania 

Total number  

17 

3 

2 

1 

Note: Accounting is mandatory for afforestation, reforestation and deforestation 

2.2.4.  Defining the policy context for the inclusion of LULUCF in the EU's climate change 

commitment 

Once monitoring and accounting  have been addressed, the overarching question is in which 
policy context the sector should be brought in to the EU's GHG reduction commitments. The 
current commitments are regulated through the EU ETS and the ESD which require trading 
sectors  to  jointly  reduce  emissions  by  21%  below  2005  levels  and  non-trading  sectors  to 
reduce emissions by 10%, see Figure 3. In theory, LULUCF could either form part of these 
existing  policy frameworks, although  the EU ETS as an option has been discarded early on 

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(see Annex V), or be brought in under a new framework which is separate from the existing 
ones.  Watterson  et  al.  (2011)  outlines  the  key  features  of  the  ESD  and  EU  ETS  that  are 
relevant  for  the  incorporation  of  LULUCF.  Defining  the  policy  context  requires  the 
consideration of the following issues:  

•  Link  to  the  overall  commitment.  How  would  the  link  with  the  EU's  overall  target  be 
regulated? Would targets be set? If so, how (taking into account the varying circumstances 
between MSs)?  

•  Compliance and compliance risk. How would compliance be defined? How could risks, in 
particular  related  to  the  high  inter-annual  variability  of  emissions  and  removals  in  the 
sector, be mitigated? 

•  Flexibilities.  Would  credits  and  debits  generated  be  transferrable,  either  between  policy 
frameworks  (i.e.  EU  ETS,  ESD  and  a  potential  separate  policy  framework)  or  between 
MSs to create flexibility?  

Figure 3. Illustration of how the EU's current GHG reduction commitment is regulated 

GHG Target:

-20% compared to 1990

-14% compared to 2005

EU ETS
-21% compared 
to 2005

Non ETS sectors 
-10% compared to 2005

27 Member State targets, ranging from -20% to +20%

2.3.  Who is affected?  

The  accounting  of  LULUCF  in  the  EU's  GHGs  reduction  target  would  affect  MSs  directly. 
Firstly, it would extend the scope of the accounted emissions and removals by about 10% at 
the EU level but with varying importance across MSs. Both natural conditions, relating to e.g. 
climate  and  vegetation  cover,  and  the  size  of  LULUCF  relative  to  other  sectors  in  Member 
States play an important role in this regard. For instance, in Sweden and Finland net removals 
in LULUCF are more than half the total emissions in other sectors and in Latvia the double, 
see  Figure  4.  This  highlights  the  importance  of  considering  national  circumstances  when 
assessing the role of the sector in the climate change commitments. Also, accounting rules are 
of key importance. For example, accounting for LULUCF in the first commitment period of 
the  KP  is  expected  to  generate  credits  of  about  1%  at  the  EU  level,  although  there  are 
variations across MSs (JRC, 2011a). Also, MSs would be required to improve monitoring and 
reporting  in  accordance  with  2006  IPCC  GPG  in  order  to  fulfil  obligations.  For  some  MS's 
some of these data are currently not yet routinely collected. Additional data collection would 
be done at country level as part of national reporting rather than at landholding level, which 

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could  impose  an  initial  administrative  burden  on  authorities  and  farmers.  No  impacts  are 
expected on large businesses or small- and medium-sized enterprises (SMEs). 

Figure  4.  Relative  importance  of  LULUCF:  emissions  and  removals  of  the  sector  relative  to  total  GHG  emissions 
(excl. LULUCF) in MSs, 2008 

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t
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i

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o
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e
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a
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l

a
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r
t
s
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A

50%

0%

-50%

-100%

-150%

-200%

-250%

Note: A negative number indicates that removals are greater than emissions in LULUCF for that Member State. (2) Due to 
inter-annual variations in emissions and removals the share varies between years. 

Source: EEA (2011) 

Secondly, it would adjust accounting to better reflect real changes in emissions and removals 
and to provide a level playing field between different mitigation options (i.e. sequestration / 
conservation in carbon in vegetation and soils in agriculture and forestry vis-a-vis substitution 
of materials with biomass in the energy and industrial sectors). In principle, this would affect 
agriculture  and  forestry  and  users  of  biomass  for  energy  production,  manufacture  of  pulp, 
paper  and  paper  products,  manufacture  of  wood  and  wood  products  or  substitution  of 
materials  in  construction.  However,  the  extent  to  which  these  different  sectors  would  be 
affected  depends  on  at  least  three  factors;  firstly,  how  accounting  rules  are  formulated, 
secondly, whether a target for LULUCF is introduced (either sector specific or more indirect 
via the ESD) and, thirdly, whether MSs translate the accounting framework into incentives at 
sector level (or else the impact will be on government expenditures and revenues).  

2.4. 

How would the problem evolve, all things equal?  

As noted in Section 2.1 above, omitting the sector from accounting would risk undermining 
the environmental integrity of the commitments, reducing the coherence of EU climate policy 
and  limiting  the  economic  efficiency  in  reaching  more  ambitious  targets.  This  section 
elaborates on how these aspects might evolve further if no action is taken.  

Figure 5 shows the results of the projected emissions and removals in the reference scenario 
(see Annex IV for more detailed results of the projections and Annex III for the models and 
methodology used). Models project a decrease in the EU by 2020 under a business-as-usual 

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scenario.19 For the LULUCF sector as a whole, a decline of about 10% is expected in 2020 
compared  to  the  period  2005-2009,  equivalent  to  emitting  33  MtCO2  more  per  year.  This 
roughly amounts to all greenhouse gas emissions in Latvia and Lithuania put together or twice 
those of Estonia in 2009.  

A  closer  look  at  this  projection  shows  that  there  are  big  differences  between  the  individual 
activities  within  the  sector.  The  decrease  is  expected  to  be  very  pronounced  in  forest 
management,  for  which  a  decrease  in  net  removals  of  about  60  MtCO2  is  expected,  i.e. 
roughly the equivalent of the total GHG emissions of Bulgaria, Denmark, Ireland or Sweden 
in 2009. Whilst this is partly the result of ageing forests (and related saturation in CO2 uptake) 
it is also partly  the  effect of EU and MS  policies, notably  the expected impact  of increased 
wood demand related to reaching the targets for renewable energy (Böttcher et.  al,  2011, p. 
19). This is partly compensated by plantation of "new" forests (afforestation). Emissions and 
removals  from  agricultural  activities  such  as  cropland  management  and  grazing  land 
management  are  expected  to  remain  fairly  stable  or  to  improve.  The  predicted  trend  is 
consistent with findings of other studies, see Box 2, and illustrates the increasing importance 
of the problem discussed under environmental integrity; negative trends and emissions risk 
being disregarded unless LULUCF is part of climate policy and accounting.  

Figure 5. Projected emissions and removals in LULUCF 2000-2020  

2010

2015

2020

100000

0

2005

)
r
a
e
y
r
e
p
2
O
C
g
G

(
s
n
o
i
s
s
i
m
E

-100000

-200000

-300000

-400000

-500000

Notation key: ●–●–● LULUCF (sum of all activities), ▲–▲–▲ Deforestation, +–+–+ Cropland management, ––– Grazing 
land management, ♦–♦–♦ Afforestation, and ■–■–■ Forest management. Unconnected points show reported / historical data.  

Note:  (1)  A  negative  number  indicates  that  removals  are  greater  than  emissions  for  that  activity.  (2)  Instant  oxidation  is 
assumed  for  the  harvested  wood  products  (HWP)  pool.  If  this  pool  were  included  the  projected  forest  management  curve 
would shift downwards (increased removals) by approximately 55 Mt in the period 2013-2020 and by a similar amount for 
reported data (Rüter, 2011). 

Source: Böttcher et al. (2011) and JRC (2011b) 

19 

In this context "Business as Usual" assumes that Member States will reach their 20% reduction targets, 
including the targets for renewable energy.  

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Box 2. How do the model results in this report compare with other studies? 

In  2011  MSs  and  other  Parties  to  the  UNFCCC  submitted  projected  emissions  and  removals  from  forest  management  to 
facilitate the decision on accounting rules at the global climate change conference in Durban in december this year.20 Some 10 
MSs used country-specific models but 15 MSs based their submissions on the models used for this report (see Annex IV for 
more  detailed  results  of  the  projections  and  Annex  III  for  the  models  and  methodology  used  here).  The  decline  in  the  sink  in 
Figure 5 is consistent with (although smaller than) the results obtained when combining the country-specific model results with 
the  ones  used  here.  Also  the  expected  increase  in  wood  demand  for  both  material  and  energy  use  (i.e.  a  key  driver  for  the 
evolution of the sink) is consistent with work undertaken by Mantau et al. (2010) The magnitude of potential supply in the latter 
study  varies  with  assumptions  about  environmental,  social  and  economic  factors.  As  shown  in  the  Roadmap  for  moving  to  a 
competitive low-carbon economy in 2050 (Op cit.), this trend is expected to continue in the long run and the role of agriculture 
and forestry in energy production is expected to increase. 

The  projected  development  of  the  sink  would  increasingly  affect  policy  coherence  and 
economic  efficiency.  If  the  decline  in  net  removals  stemming  from  non-action  remain 
unaccounted  for  this  would  risk  disincentivizing  preservation  and  enhancement  of  carbon 
stocks and thereby creating an unlevel playing field between different mitigation options, that 
could result in an excessive use of resources for mitigation measures that count towards other 
objectives (substitution of fossil fuels in energy production and of GHG intensive materials in 
industry). This risks resulting in economic efficiency losses that may increase over time given 
that significant additional efforts will be required in all sectors to meet the long-term climate 
objectives.  

2.5. 

Does the EU have the right to act and is EU added-value evident? 

The  legal  basis  for  this  initiative  is  Article  192(1)  of  the  Treaty  on  the  Functioning  of  the 
European Union (TFEU). Article 9 of the ESD, also based on Article 192(1) TFEU, tasks the 
Commission  with  assessing  if  and  how  LULUCF  should  be  included  in  the  EU's  GHG 
reduction commitment, and to make a legislative proposal, as appropriate. Climate change is a 
trans-boundary issue which requires joint action by countries. In particular, since the EU has a 
common emission reduction target any changes will require Union wide action. The principles 
of subsidiarity and proportionality have been duly considered.  

3. 

OBJECTIVES  

3.1.  What are the general and more specific / operational objectives? 

The general objective of the proposal which accompanies this impact assessment is to support 
the  EU's  ambition  of  limiting  global  warming  to  a  maximum  of  two  degrees  Celsius  above 
pre-industrial temperatures. The EU's short term commitment for 2020 is to reduce its overall 
GHG  emissions  by  at  least  20%  below  1990  levels.  As  agreed  by  the  European  Parliament 
and Council, the contribution of all sectors should be reflected in the efforts of reaching the 
target.  

For this objective to be achieved, the emissions and removals related to LULUCF would need 
to  be  reflected  in  accounting.  However,  they  must  be  included  so  as  to  address  the  issues 
identified in Section 2.2; namely to ensure permanence and the environmental integrity of the 
EU's  GHG  reduction  commitments  as  well  as  accurate  monitoring  and  accounting.  The 

20 

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The  submission  is  the  basis  for  forest  management  accounting  and  has  undergone  a  review  in 
accordance 
website 
http://unfccc.int/meetings/ad_hoc_working_groups/kp/items/5896.php for information 

UNFCCC 

2/CMP.6, 

Decision 

with 

see 

the 

24 

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correct  policy  context  also  needs  to  be  defined.  To  this  end,  the  following  operational 
objectives have been identified:  

•  Monitoring  and  reporting  activities  undertaken  by  MSs  should  comply  with  the  latest 
IPCC  methodological  guidance  approved  by  UNFCCC  to  ensure  the  transparency, 
completeness, consistency and comparability and accuracy of estimates; 

•  Accounting rules should: 

(1) 

(2) 

(3) 

be  extensive  in  terms  of  emissions  and  removals  covered  and,  to  this  end, 
shall include at least all main LULUCF activities (afforestation, reforestation, 
deforestation,  forest  management,  cropland  management  and  grazing  land 
management)21,  

ensure that the non-permanence of emissions and removals is fully reflected 
in accounting, 

provide incentives for climate change mitigation whilst avoiding bias towards 
any  particular  measure  to  ensure  an  appropriate  balance  of  measures  in  the 
contribution to climate change mitigation,22 

•  The policy context in which LULUCF is included should be such that the ability of MSs 
to comply with GHG reduction targets is not put at risk due to inter-annual variability of 
emissions and removals or large natural disturbances. 

4. 

POLICY OPTIONS 

4.1.  What  are  the  possible  options  for  tackling  the  problem  and  meeting  the 

operational objectives? 

The problem definition shows that accounting for the sector would enhance the environmental 
integrity,  policy  coherence  and  economic  efficiency  of  the  EU's  GHG  emission  reduction 
commitments.  In  the  light  of  this,  different  objectives  have  been  defined.  Options  can  be 
divided into two levels to address, on the one hand, the objective related to the policy context 
and, on the other hand, the objectives related to accounting and monitoring and reporting.  

Firstly, it is necessary to define the policy context in which the sector should be accounted 
since there is already legislation in place to regulate the existing commitment to reduce GHG 
emissions  by  20%  in  2020.  Three  options  have  been  defined.  Option  2  involves  creating  a 
legislative framework for LULUCF which is separate from the existing frameworks provided 

21 

22 

The choice of activities is based on key categories at the EU level in UNFCCC reporting. In this report, 
monitoring and reporting are generally discussed in terms of the UNFCCC rather than the KP since the 
former is the basis for all reporting and an important part of the latter is currently done on a voluntary 
basis (which means that data are not reported). The following subcategories of the LULUCF sector of 
the  EU  15  GHG  inventory  were  key  categories  for  the  trend  and  the  level  assessment  in  2008  (for 
CO2): forest land, cropland, grassland and land converted to settlements.  
A  mitigation  strategy  aimed  at  maintaining  or  increasing  carbon  stocks  while  producing  a  annual 
sustained yield of timber, fibre or energy is expected to generate the largest sustained mitigation benefit 
(Nabuurs et al., 2007). However, the correct formulation of such a strategy requires that emissions from 
the different uses are accurately reflected in accounting. 

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by the ESD and the EU ETS. This option was divided into one without targets (Option 2.I) 
and one with targets (Option 2.II). It should be noted that the target option was included in the 
analysis  for  illustrational  purposes  only  and  to  initiate  discussions.  Option  3  involves 
including  LULUCF  in  the  existing  legislative  framework  of  the  ESD.  The  EU  ETS  as  an 
option was discarded at an early stage (see Annex V for further details). It is good practice to 
consider also a non-regulatory / "no EU action" option (Option 1).  

Secondly,  different  sub-options  have  been  developed  to  assess  how  robust  accounting 
(options (a) to (c)) and monitoring and reporting can be achieved. The sub-options are the 
same for Options 2 and 3 but their impacts differ depending on the policy context. Figure 6 
illustrates how the two levels of options relate to one another.  

A  summary  of  stakeholder  views  on  the  different  options  is  given  at  the  beginning  of  each 
section to explain why particular options have been included in the assessment. 

Figure 6. Outline of options 

Should LULUCF be 
included in the 2020 

commitment? 

No

Yes

Option 1 - No EU action

Option 2  - LULUCF in a 
separate framework

Option 3 - LULUCF in 
ESD 

Does monitoring and reporting need to be improved? 

Yes

No

No 

Improve monitoring and 
reporting and increase 
harmonisation

Yes

Are small changes to the 
KP accounting rules 
sufficient?

Yes 

Accounting option (a)

No

Accounting option (a)

Yes

Are moderate changes to 
the KP accounting rules 
sufficient?

Yes 

Accounting option (b)

No

Accounting option (a)

Yes

Are significant changes to 
the KP accounting rules 
necessary?

Yes 

Accounting option (c)

Accounting option (c)

4.2. 

Options  for  the  policy  context  in  which  to  include  LULUCF  in  the  EU's  GHG 
emission reduction commitments 

This section describes the options for including LULUCF in the EU's commitments as regards 
the policy context. Option 1 involves no EU action. The implementation of Options 2 and 3 
are described in terms of their link to the overall commitments, compliance and compliance 
risk and flexibilities. Both options would require new or amended legal acts. 

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What are the views of stakeholders? 

The majority in both the consultation with the public and with MSs responded that LULUCF should be part of the EU's GHG 
emissions reduction target in 2020. In both consultations, but most notably in the consultation with MSs, there was a majority 
in favour of making the sector part of the target only if the EU were to take on a more ambitious commitment than the current 
one of a 20% reduction compared to 1990. 

In the public stakeholder consultation there was a slight preference for regulating the role of LULUCF in the climate change 
commitments  through  a  policy  framework  which  is  separate  from  those  that  currently  regulate  the  EU's  GHG  reduction 
commitment (i.e. the ESD and the EU ETS), preferably with a sector target of some sort. The option of regulating the sector 
through the ESD was second. The reverse was true for the MS consultation where the ESD was the favoured option. Only a 
small share of the respondents in the public consultation and none in the MS consultation wanted the sector to form part of 
the EU ETS. 

See Section 1.3 for links to more detailed information. 

4.2.1.  Option 1 – No EU action  

This option involves not accounting for LULUCF in the EU's climate change commitments at 
all. In practice, this is only realistic in the absence of an international agreement; given that 
the EU is a Party to the KP, any commitment there would have to be shared between MSs and 
would necessitate a common approach to both  accounting  rules (determined internationally) 
and to how debits and credits would be treated in relation to existing commitments under the 
ESD and the EU ETS. Therefore, "do nothing" really translates into delaying all action until 
an international agreement on a second commitment period has been reached.  

4.2.2.  Option 2 – Include LULUCF as a separate policy framework 

This  option  involves  establishing  a  policy  framework  which  is  separate  from  the  ones 
currently  regulating  the  EU's  GHG  reduction  target  (the  ESD  and  the  EU  ETS).  Emissions 
and removals would be accounted for at the level of MSs. 

In  terms  of  linkages  to  the  EU's  climate  change  commitments,  two  sub-options  are 
considered. 

Sub-option  2.I  –  No  mitigation  targets:  The  EU  is  already  on  track  to  achieve  its  20% 
reduction target of GHG emissions without the contribution of LULUCF. Before the level of 
ambition is increased beyond that target conditions need to be right. In Sub-option 2.I credits 
and debits generated by LULUCF would therefore not count towards the current level of the 
EU's  commitments.  As  a  first  step,  the  objective  would  be  to  ensure  that  emissions  and 
removals  from  the  sector  will  be  properly  accounted  for.  Any  credits  or  debits  generated  in 
LULUCF would be treated as a memo item. However, as a second step, and as part of a step-
up of the EU's climate  change commitments  beyond 20%, a specific target for the sector to 
increase net removals or reduce net emissions could be envisaged as illustrated by Sub-option 
2.II below, or the sector could be included in Option 3. As an intermediate step, action plans 
would be formulated by MSs to ensure that mitigation action is taken in the sector. 

Sub-option 2.II – Sector mitigation targets (included for illustrational purposes only): Targets 
could  be  set  as  part  of  an  economy-wide  step-up  of  efforts  beyond  20%.  This  impact 
assessment does not analyse targets that support a legislative proposal to this end. Rather, the 
option of setting targets is analysed in a preliminary way and only to initiate discussions. If 
targets were to be introduced at a later stage, a similar approach to the ESD could be adopted 
such  that  targets  set  for  individual  MSs  would  be  fair  and  achievable.  Credits  and  debits 
generated  by  LULUCF  would  count  towards  the  EU's  GHG  reduction  commitment  in 
accordance with agreed accounting modalities. Targets to increase net removals (or decrease 

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net emissions) could be set explicitly for individual MSs based on one of several parameters; 
for instance the estimated mitigation potential in LULUCF (underpinned by modelling), GDP 
per  capita,  or  a  uniform  percentage  change  compared  to  business-as-usual  projections. 
However,  sufficient  flexibilities  would  have  to  be  ensured  to  minimise  adverse  risks  of  the 
uncertainty  in  estimates  (see  Section  2.2.2  and  Annex  III)  which  would  otherwise  have 
implications  for  reaching  targets.  For  illustrational  purposes  only,  this  report  takes  a  closer 
look at the possible impact of introducing targets based on mitigation potential, underpinned 
by modelling (see Annexes IV).  

Flexibility  mechanisms  are  only  relevant  in  the  case  of  Sub-option  2.II  where  they  would 
safeguard  cost-efficiency  and  ensure  that  a  failure  to  meet  sector-specific  targets  could  be 
compensated  by  efforts  in  other  sectors  to  preserve  the  overall  EU  target.  This  could  be 
allowed  through  purchases  and  sales  of  LULUCF  credits  among  MSs  to  facilitate  their 
compliance with LULUCF targets, or through compensation with credits resulting from over-
compliance  in  the  ESD.  Again  for  illustrational  purposes  only,  this  report  looks  at  the 
possibility of transferring LULUCF credits between MSs. 

As  regards  compliance  (again  relevant  when  accounting  towards  a  target),  Section  2.2.1 
shows  that  the  inter-annual  variability  of  emissions  and  removals  is  very  high.  This  makes 
annual  compliance  unsuitable  (see  the  discussion  in  Option  3  for  more  details).  Instead, 
compliance would be based on the average of emissions and removals over the period 2013 to 
2020. Annual reporting would still be required as currently done under the UNFCCC and the 
KP. Compliance risk due to large natural disturbances would be addressed by way of specific 
accounting provisions (see below).  

4.2.3.  Option 3 – Include LULUCF in the Effort Sharing Decision 

This  option  involves  amending  the  ESD  in  order  to  include  LULUCF  among  the  sectors 
covered by existing commitments. Hence, liability for both emissions and removals would fall 
on  MSs.  An  overview  of  the  key  features  of  the  legislation  is  provided  in  Watterson  et  al. 
(2011).  

In terms of linkages to the EU's climate change commitments, the ESD specifies binding 
targets for MSs between plus / minus 20% in 2020 relative to emissions in 2005, estimated on 
the basis of GDP per capita. If LULUCF were to be included, the distribution of individual 
MSs'  efforts  would  have  to  be  adjusted  accordingly.23  In  theory,  this  could  be  done  by 
changing the MS targets (based on GDP per capita) on the basis of the estimated mitigation 
potential  in  LULUCF,  underpinned  by  modelling  (see  Annexes  VI  and  VII).  Or,  given 
sufficient flexibilities, the targets could also be adjusted based on simpler metrics such  as a 
uniform  percentage  change  compared 
to  business-as-usual  projections.  The  most 
straightforward  option  is  to  maintain  the  current  targets  based  on  GDP  per  capita.  This 
approach  would  mean  that  the  challenge  for  MSs  to  reach  their  targets  would  most  likely 
change  with  the  inclusion  of  the  sector,  the  reason  being  that  diverse  natural  conditions 
relating  to  e.g.  climate,  vegetation  cover,  age  of  forests  and  soil  throughout  the  EU  play  an 
important  role  in  the  mitigation  potential  of  MSs.  Given  the  difficulties  associated  with 
including LULUCF in the ESD in its current form, particularly in relation to the requirements 
of annual compliance (see discussion in Section 2.2 and below), the present analysis is limited 
to the impacts of maintained targets only. 

23 

See Article 9 of Decision 406/2009/EC. 

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The ESD contains different flexibility mechanisms. Within a MS, over-achievement during 
2013-19  can  be  carried  over  to  the  subsequent  years,  up  to  2020.  Up  to  5%  of  the  annual 
emission allocations of the following year may be brought forward during 2013-19. A transfer 
of up to 5% of annual emission allocations for a given year can be transferred between MSs. 
Such a transfer may be used for the implementation of a MS's obligations for the same year or 
any subsequent years until 2020. These flexibilities would continue to apply if LULUCF were 
included  in  the  commitment,  but  the  possibility  for  borrowing  and  lending  between  years 
would need to be significantly expanded in several MSs due to the inter-annual variability of 
emissions and removals. 

In  terms  of  compliance,  MSs  are  required  to  annually  limit  their  GHG  emissions,  in 
accordance with a linear trajectory for 2013-2020. This includes also making use of specified 
flexibilities  in  order  to  make  sure  that  emissions  do  not  exceed  their  limit  in  2020.  The 
starting point for the trajectory is the average emission level in 2008-2010. To address some 
compliance risks, there are provisions for extreme meteorological events so a MS may request 
an increased carry-forward rate in excess of 5% in 2013 and 2014 if substantially increased 
GHG emissions occur in those years compared to normal years. This provision would not be 
adequate if it were to apply also to large natural disturbances such as wildfires and storms. It 
would be difficult to recover emissions related to such events through removals, both because 
of the short time span and because of the high global warming potential of non-CO2 emissions 
associated with fires which would take a long time to recover (since removals of CO2 is the 
only  way  to  compensate).  As  this  provision  was  designed  for  sectors  other  than  LULUCF, 
changes would be needed to address disturbances (see accounting options below). 

4.3. 

Options for improving monitoring and reporting 

This section outlines an approach for meeting the monitoring and reporting objectives defined 
in  this  report.  In  practice,  the  implementation  would  involve  revising  the  Monitoring 
Mechanism  Decision24.  A  separate  impact  assessment  and  proposal  from  the  Commission 
address this issue but complementary information is provided here. 

What are the views of stakeholders? 

Whilst  both  the  public  consultation  and  the  consultation  with  MSs  have  shown  that  the  majority  favours  an  inclusion  of 
LULUCF in the EU's GHG commitment, a common reason amongst those who did not wish to include the sector related to 
perceptions about the reliability and comparability of data. This suggests that improvements to monitoring and reporting may 
be needed.25 In both the public and MS consultations the majority agreed that there is a need for further harmonisation and 
standardisation between MSs in terms of monitoring, reporting and verification of emissions and removals. 

See Section 1.3 for links to more detailed information. 

There is no unique way of reaching the objective because the IPCC methodological guidance 
allows  for  different  methodologies  and  approaches  to  be  applied  according  to  national 
circumstances.  For  instance,  a  number  of  tools  exist  for  representing  land  areas  (e.g.  use  of 
existing  data,  remote  sensing  and  ground-based  surveys)  and  for  deriving  emission  factors 

24 

25 

Decision 280//2004/EC of the European Parliament and of the Council of 11 February 2004 concerning 
a  mechanism  for  monitoring  Community  greenhouse  gas  emissions  and  for  implementing  the  Kyoto 
Protocol. 
This  view  was  confirmed  also  in  a  different  but  related  public  consultation  on  the  Green  Paper  on 
Forest  Protection  and  Information  in  the  EU:  Preparing  Forests  for  Climate  Change25,  where  a 
majority  argued  for  more  harmonised  and  more  readily  available  information  about  EU  forests,  with 
links  being  made 
including  climate  change  mitigation,  see 
http://ec.europa.eu/environment/forests/fprotection.htm. 

to  a  variety  of  policies, 

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29 

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(e.g.  default  values,  literature,  measurements  and  models),  and  these  can  be  combined  in  a 
number  of  ways.  However,  in  a  broader  sense,  a  three-step  approach  can  be  envisaged  (see 
Annex I for more details). 

A first step is to ensure complete reporting of land categories and carbon pools using at least 
simple  methodologies.  The  objective  of  this  step  is  to  ensure  the  level  of  completeness 
stipulated  by  the  IPCC  /  UNFCCC  to  a  minimum  level  of  tier  1.  Fulfilling  this  objective 
require increased collection of activity data. 

A  second  step  would  involve  increasing  the  accuracy  of  the  reported  key  categories  and 
carbon pools to a minimum of tier 2. Tier 1 methodologies only distinguish between the broad 
categories  of  land  management,  which  means  that  the  effects  of  some  of  the  available 
mitigation  activities  are  not  reflected  in  the  inventories.  This  step  would  therefore  mainly 
imply requirements to improve the level of accuracy of monitoring and reporting of emissions 
and removals related to soils as this is where most efforts are needed. This step would ensure 
the  completeness  stipulated  by  the  IPCC  methodological  guidance  and  a  methodology 
consistent  with  key  category  analysis.26  Moving  to  tier  3  (including  modelling)  would  be 
encouraged to further increase accuracy (and in some cases for cost efficiency), but it is not an 
essential requirement of Step 2. 

A  third  step  would  aim  to  improve  the  comparability  between  MSs  by  harmonising 
monitoring,  reporting  and  related  nomenclature.  Cienciala  et  al.  (2010)  investigated 
harmonised  methods  for  assessing  carbon  sequestration  in  European  forests.  Tomppo  et  al. 
(2010)  showed  that  harmonisation  is  possible  and  on-going  in  COST  Action  43,  which 
reviewed the potential for common reporting in the context of National Forest Inventories. In 
addition,  Kibblewhite  et  al.  (2008)  have  described  requirements  for  a  harmonised  soil 
monitoring  system  in  the  EU.  Steps  1  and  2  would  go  some  way  towards  harmonisation. 
However,  processes  leading  to  change  in  inventory  practices,  such  as  acceptance  of  new 
definitions,  are  usually  slow.  McRoberts  et  al.  (2010)  concluded  that  whilst  important 
differences  in  national  forest  inventories  remain,  because  of  the  use  of  different  national 
definitions  and  methodologies,  prospects  are  generally  positive  for  developing  procedures 
leading  to  compatible  estimates  among  countries.  This  step  should  be  seen  as  a  gradual 
process which will need to take place over the next compliance period and beyond and could 
involve  collaborative  efforts  between  the  Commission  and  MSs  through  workshops  and 
working groups. 

4.4. 

Options for accounting 

This  section  outlines  different  options  for  meeting  the  objectives  related  to  accounting. 
Consultations  carried  out  with  a  range  of  stakeholders  and  MSs  and  on-going  discussions 
under the auspices of the UNFCCC suggest that there are three main options to account for 
emissions  and  removals  resulting  from  afforestation,  reforestation,  deforestation,  forest 
management, cropland management, grazing land management, revegetation, changes in the 
harvested wood products (HWPs) pool, and disturbance events. The practical implications of 
implementing  either  of  the  options  would  be  to  define  the  accounting  modalities  in  EU 
legislation. 

26 

Moving up higher tiers means that the same methodological approach as tier 1 may be used (for tier 2) 
but emission and stock change factors must be based on country- or region-specific data, should have a 
higher temporal and spatial resolution and should use more disaggregated activity data as compared to 
tier 1 (IPCC, 2006). 

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30 

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What are the views of stakeholders? 

In  the  public  stakeholder  consultation,  the  majority  of  respondents  suggested  that  emissions  and  removals  related  forestry 
activities  should  be  accounted  for  on  a  mandatory  basis.  About  half  wanted  accounting  for  GHG  associated  with  some 
agricultural  activities  to  be  mandatory.  The  tendency  was  similar  across  MSs,  but  few  wanted  agricultural  activities  to  be 
included on a mandatory basis.  

As regards how accounting should be done, in particular for forest management, the public consultation showed that there were 
two dominant groups; one that thought that changes in emissions and removals should be measured against a benchmark of 
some  sort,  either  emissions  in  a  base  year  (1990)  or  a  business-as-usual  projection  ("reference  level"),  and  one  group  that 
believed that no benchmark should be used (meaning that credits would be generated as long as forests remove more carbon 
from the atmosphere than they emit, regardless of the trend in emissions and removals). MSs felt that accounting for changes 
against a benchmark ("reference level") was the most appropriate option. 

See Section 1.3 for links to more detailed information. 

Table 4. Summary of accounting options 

Activity/Provision 

Accounting option (a) 
Small changes to the current KP 
rules 
Accounting  for  emissions  and 
removals  without  a  benchmark 
(so-called 
"Gross/Net 
accounting") 
Mandatory 
Accounting  for  emissions  and 
removals  without  a  benchmark 
(so-called 
"Gross/Net 
accounting") 
Mandatory 

Accounting without a benchmark 
(so-called 
"Gross/Net 
accounting")  but  emissions  and 
removals are discounted by 85% 
Mandatory 

Accounting rules by option 
Accounting option (b) 
Likely outcome in the UNFCCC 
negotiations 
Accounting  for  emissions  and 
removals  without  a  benchmark 
(so-called 
"Gross/Net 
accounting") 
Mandatory 
Accounting  for  emissions  and 
removals  without  a  benchmark 
(so-called 
"Gross/Net 
accounting") 
Mandatory 

Accounting option (c) 
UNFCCC+ 

Accounting  for  emissions  and 
removals  without  a  benchmark 
(so-called 
"Gross/Net 
accounting") 
Mandatory 
Accounting  for  emissions  and 
removals  without  a  benchmark 
(so-called 
"Gross/Net 
accounting") 
Mandatory 

relative 

a 
to 
based 
on 
projections 

Accounting 
reference 
level 
business-as-usual 
for 2013 to 2020 
Mandatory 

relative 

a 
to 
based 
on 
projections 

Accounting 
reference 
level 
business-as-usual 
for 2013 to 2020 
Mandatory 

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Voluntary 

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Voluntary  

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Mandatory 

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Voluntary 

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Voluntary  

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Mandatory 

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Voluntary 

Accounting  for  emissions  from 
harvested  wood  at  the  time  of 
harvest  

No specific provisions for 
emissions related to natural 
disturbances 

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Voluntary  
Accounting  for  emissions  from 
harvested wood at the time they 
actually occur (depending on the 
lifetime of wood products) 
Emissions from natural 
disturbances exeeding a 
background level, may be 
excluded from accounting  
Voluntary 

Accounting  for  emissions  and 
removals  relative  to  1990  (so-
called Net/Net accounting) 
Voluntary 
Accounting  for  emissions  from 
harvested wood at the time they 
actually occur (depending on the 
lifetime of wood products) 
Emissions from natural 
disturbances, exceeding a 
background level, may be 
excluded from accounting  
Voluntary 

Afforestation and 
reforestation 

Deforestation 

Forest Management 

Cropland 
Management 

Grazing Land 
Management 

Revegetation 

Changes in the 
Harvested Wood 
Products carbon 
pool 

Natural 
disturbances 

Note: Shaded areas indicate a change from the accounting rules under the Kyoto Protocol in the period 2008-12. 

In  Table  4  above,  shaded  areas  indicate  where  the  options  differ  from  the  accounting  rules 
under  the  KP  in  the  period  2008-12.  A  more  detailed  explanation  and  rationale  for  the 
different rules is given under each option. Background reading is provided also by Watterson 
et  al.  (2011).  Some  options,  such  as  accounting  for  the  specific  activity  of  rewetting  and 
drainage on land with organic soils, were excluded at an early stage for the reasons given in 

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31 

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Annex V. It should be noted that where cropland and grazing land management are accounted 
for the vast majority of emission from organic soils are captured anyway.  

4.4.1.1.  Accounting option (a): Small changes to the current Kyoto Protocol rules. 

In  this  option,  accounting  for  forest  management  would  be  done  on  the  basis  of  so-called 
Gross/Net accounting and discounted at a rate of 85%. This means that credits (debits) would 
be calculated as 15% of all net removals in the commitment period without consideration of 
net removals in a base year or period, i.e. no benchmark. In the example given in Figure 7, 
this translates to credits equal to "b" which is a fraction (15%) of "a". As discussed in Section 
2.1,  in  the  absence  of  a  benchmark  it  will  be  impossible  to  separate  anthropogenic  from 
natural  factors  but  the  discount  factor  is  a  proxy  for  the  share  of  human-induced  emissions 
and removals. This accounting option for Forest Management is no longer on the table in the 
international negotiations.  

Afforestation and reforestation involve establishing forests on land that was not forested at 
the very beginning of 1990, and deforestation involves converting areas, which in 1990 were 
covered  by  forest,  for  other  uses  or  activities.  Emissions  and  removals  related  to  these 
activities  in  the  commitment  period  would  be  accounted  for  in  their  entirety  ("Gross/Net 
accounting")  as  they  are  a  direct  result  of  human  activities  (i.e.  it  is  possible  to  determine 
human-induced impacts).  

Figure 7. Illustration of accounting methods 

a

c

Discount factor 
= X% of “a”

b

l

s
a
v
o
m
e
r

t
e
N

1990

Commitment period

Note: Gross/Net – Credits are equal to all net removals during the commitment period = "a"; Gross/Net with a 
discount factor – Credits are equal to all net removals during the commitment period and discounted by a factor 
of  X%  =  "  b";  Net-net  compared  to  1990  –  Credits  are  equal  to  the  difference  between  the  removals  during 
commitment period and the net removals in 1990 = "c".  

As  under  the  accounting  rules  of  the  first  commitment  period  of  the  KP,  accounting  for 
emissions  and  removals  in  cropland  and  grazing  land  management  and  revegetation 
would be voluntary and done on the basis of changes relative to 1990 (see "c" in Figure 7). 
This means that credits (debits) would be generated to the extent that net removals are higher 
(lower)  in  the  commitment  period  as  compared  to  the  base  year.  Soils  have  different 
characteristics to biomass and the inter-annual variations in cropland and grassland are much 
smaller than those of forests. This means that accounting will not be as sensitive to the choice 
of base year (cf. fluctuations in forest management in Figure A5.1 in Annex V). 

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4.4.1.2.  Accounting option (b): Likely outcome in the UNFCCC negotiations 

This accounting option reflects aligning to the outcome on accounting rules in the UNFCCC 
negotiations in Durban in December 2011. It differs from accounting option (a) in three ways. 
Firstly,  accounting  for  emissions  and  removals  in  forest  management  is  done  relative  to  a 
reference  level  in  order  to  factor  out  the  impact  of  natural  influences  on  removals  and 
emissions,  see  Box  2  and  Figure  8.  The  reference  level  is  combined  with  a  quantitative 
limitation  ("cap")  on  credits  corresponding  to  3,5  %  of  base  year  emissions  (excluding 
LULUCF) to limit the effects of the inherent uncertainty of (any) projections and to avoid that 
unwarranted credits arise. The quantitative limitation is expressed as a percentage of a MS's 
total  GHG  emissions  in  1990  in  order  to  ensure  the  link  to  compliance  risk  (because  GHG 
reduction targets are expressed relative to this year). The cap ensures that some incentives for 
improvements in management practices are provided., see Annex III for more details on the 
impacts of different caps. 

Figure 8. Accounting emissions and removals in forest management against a reference level  

i

s
n
o
s
s
m
e

i

t
e
N

l

s
a
v
o
m
e
r

t

e
N

1990

Reference level = average of 
projected net removals

s
t
i
b
e
D

s
t
i

d
e
r
C

Historical data

Projected data for commitment 
period

Note: Accounted emissions and removals are equal to the average of actual net removals in the commitment period minus the 
projected emissions and removals under business-as-usual, the so-called reference level. Credits are obtained when actual net 
removals exceed the reference level, and debits are obtained when actual net removals are less than the reference level. 

Box 2. Accounting for forest management on the basis of a reference level 

What is a reference level?  

The  reference  level  is  set  as  the  average  of  the  projected  removals  and  emissions  under  business  as  usual in  the  period  for 
which  the  EU  commits  to  reduce  its  overall  emissions,  in  this  case  the  period  from  2013  to  2020,  see  Figure  8.  In  essence, 
accounting against the reference level means that a Member State will receive neither credits nor debits if the average of actual 
net removals in the compliance period equals the reference level,  but that if net  removals are higher (lower) this will result  in 
credits (debits). In fact, in response to a decision27 in the Cancun Agreements, Member States submitted numbers for reference 
levels to the UNFCCC for review by expert teams for consideration prior to the decision on accounting rules at the Conference 
of  Parties  in  Durban  last  December.  The  outcome  of  the  review  process  (http://unfccc.int/bodies/awg-kp/items/5896.php)  has 
been  assessed  by  the  CMP7.  The  reference  levels  take  into  account  the  effect  of  removals  or  emissions  from  forest 
management  as  shown  in  greenhouse  gas  inventories  and  relevant  historical  data;  forest  characteristics  such  as  age  class 
structure,  increments  and  rotation  lengths;  and  domestic  policies  implemented  and  adopted  no  later  than  June  2009. 
Importantly, the cut-off date means the expected impacts on harvesting of reaching the renewable energy targets (as set out in 
Directive 28/2009/EC) are not included in the reference levels.  

27 

Decision 2/CMP.6. 

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What is the rationale behind reference levels?  

Emissions  and  removals  depend  on  a  number  of  natural  (regional/geographical)  circumstances  such  as  variations  in  growing 
conditions  (temperature,  precipitation  and  droughts)  and  natural  disturbances  (storms,  fires)  as  well  as  past  and  present 
management practices (e.g. rotation lengths which affect the distribution of age classes in forest stands) and therefore the rate 
of  removals.  Ultimately,  the  capacity  of  forests  and  soils  on  a  given  area  of  land  to  remove  carbon  from  the  atmosphere  will 
saturate because a steady state will occur in the balance of emissions and removals. By measuring changes in emissions and 
removals relative to business-as-usual projections these circumstances are "factored out" so that only changes related directly 
human-induced activities are measured. This also provides incentives for improving on the current situation and gives an equal 
value to mitigation whether through sequestration or conservation or material and energy substitution.  

Secondly, provisions for disturbance events would be needed to deal with substantial natural 
disturbances  that  are  beyond  the  control  of  and  not  materially  influenced  by  MSs  and  the 
resulting compliance risks, see Box 3. 

Box 3. Accounting for natural disturbances 

In the case of extraordinary occurrences whose associated total annual GHG emissions and removals are a minimum of e.g. 3-
5%  per  cent  of  the  total  national  emissions  (excl.  LULUCF)  in  1990,  it  should  be  possible  to  exclude  part  of  the  associated 
emissions from accounting. The trigger for the application of these provisions would be defined in terms of base year emissions 
because  it  is  designed  to  address  compliance  risk  with  the  EU's  climate  change  commitments  (which  are  determined  on  the 
basis  of  total  GHG  emissions  in  1990).  MSs  would  be  able  to  exclude  part  of  emissions  from  the  lands  affected  minus  any 
subsequent removals on those lands until the end of the commitment period. However, in the case of land-use change following 
substantial  natural  disturbances,  MSs  would  not  be  able  to  exclude  emissions.  The  application  of  this  provision  would  be 
voluntary but requires solid and evidence-based justification28. In the rules laid down for the second commitment period under 
the Kyoto Protocol, a corresponding provision is set that includes the use of a background level to be calculated fro each party. 
The 3-5% mentioned above, can be seen as such a background level. 

Carbon is stored in various "pools", primarily in above- and below-ground biomass, such as 
wood, leaves, roots, and in soils (see Matthews et al. (2011) for more details). But carbon is 
also stored in products made from harvested wood. In the KP rules emissions are accounted as 
if they occur at the time of harvest. However, harvesting does not generate emissions per se, it 
is a transfer of carbon from one pool (e.g. above-ground biomass) to another (harvested wood 
products). In accounting option (b) and (c), emissions would instead be accounted for when 
they  occur,  as  also  decided  for  the  next  KP  commitment  period  by  COP17/CMP7  at  the 
Durban  meeting  in  December  2011.  In  accounting  option  (b)  and  (c)  and  in  the  next 
commitment period, sawn wood, wood panels and paper would be accounted for on the basis 
of  exponential  decay  (i.e.  loss)  or  emission  with  default  half-lives  of  35,  25  and  2  years 
respectively. Wood that is used for energy production, which is generally combusted within a 
year,  and  wood  put  in  land-fills  would  still  be  accounted  for  at  the  time  of  harvest.  Net 
removals will occur as long as the transfer of carbon to the harvested wood products pool is 
greater than the loss from the pool. The Durban decision allows for substitution of the default 
half lives values, where transparent and verifiable country specific data are available. 

4.4.1.3.  Accounting option (c): UNFCCC+ 

This  accounting  option  is  based  on  the  outcome  in  the  UNFCCC  negotiations  in  Durban 
(Accounting  option  (b))  but  goes  further  in  addressing  the  criticisms  against  the  accounting 
rules under the first commitment period of the KP. In particular, the scope of accounting and 
coverage  of  emissions  and  removals  would  be  extended  to  accounting  for  cropland 

28 

In particular to determine the extent of the event (in terms of areas of land affected), estimate the GHG 
emissions resulting from disturbance of that land, formally declare the emissions as resulting from the 
disturbance,  remove  these  emissions  from  the  calculated  GHG  balance  for  the  period,  provided 
evidence can be presented to show that the emissions were beyond the control of MSs, demonstrate that 
actions are being taken to remediate the impacts of the event (e.g. restore carbon stocks on the affected 
land), and show that emissions associated with salvage logging were not excluded. 

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management  (already  accounted  for  by  Denmark,  Spain  and  Portugal)  and  grazing  land 
management (accounted for by Denmark and Portugal) on a mandatory basis. Regardless of 
the outcome of the  ongoing  international negotiations, the EU (as a Party) is  able  to decide 
whether  to  account  for  all  activities.  Such  a  choice  would  be  fully  compatible  with  the 
international system. 

4.5.  Which options have been discarded at an early stage and why? 

Annex  V  contains  a  description  of  discarded  accounting  options.  In  terms  of  defining  the 
appropriate  policy  context,  the  annex  summarises  the  key  points  for  not  considering  the 
inclusion of LULUCF in the EU ETS in this impact assessment, as discussed in three earlier 
studies29. 

5. 

ANALYSIS OF IMPACTS  

This section presents an analysis of the impacts related to the different options presented in 
Section  4.  It  is  in  the  mandate  of  this  impact  assessment  to  address  how  LULUCF  may  be 
included in the EU's overall GHG reduction target. The environmental, macro-economic and 
social  implications  of,  in  particular,  different  accounting  options  depend  on  if  and  how 
LULUCF is linked to the overall climate change commitments. Therefore, this section brings 
together  the  analysis  of  accounting  options  and  the  steps  for  improving  monitoring  and 
reporting  with  the  different  overall  policy  options  (cf.  Figure  7)  of  (1)  taking  no  action,  (2) 
accounting  for  LULUCF  in  a  separate  framework  I)  without  mitigation  targets  and  II)  with 
mitigation targets, and (3) including LULUCF in the ESD. As noted in Section 4, the analysis 
of sub-option 2.II, which sets mitigation targets for LULUCF, is preliminary and serves as a 
basis for discussion only. 

Impacts are assessed relative to the reference scenario outlined in Section 2.4 (and elaborated 
in Annexes III and IV) as the most likely outcome in the absence of policy interventions. 

5.1. 

Environmental implications  

5.1.1. 

Impact of the different options on GHG emissions 

5.1.1.1.  Option 2.I – Separate framework for LULUCF (without mitigation targets) 

The  aim  of  this  option  is  to  introduce  and  improve  accounting,  monitoring  and  reporting 
methods in the EU's GHG reduction commitment without changing the agreed efforts already 
introduced  under  the  Climate  and  Energy  Package.  In  other  words,  it  does  not  involve 
revising targets upwards or downwards and rather records emissions and removals as a memo 
item. This would prepare the ground for a more inclusive step-up of the EU-wide efforts in 
the pursuit of the long-term targets when conditions are right. Table 5 presents the expected 
credits  and  debits  per  year  over  the  period  2013-20  in  the  reference  scenario,  i.e.  without 
additional mitigation efforts. The level of credits is uncertain because of uncertainties in the 

29 

The  three  studies  are:  (1)  Impact  Assessment  of  the  Directive  of  the  European  parliament  and  of  the 
Council amending Directive 2003/87/EC so as to improve and extend the EU greenhouse gas emission 
allowance trading system. {COM(2008) 16 final}{SEC(2008) 53}, (2) Extended Impact Assessment on 
the Directive of the European Parliament and of the Council amending Directive establishing a scheme 
for greenhouse gas emission allowance trading within the Community in respect of the Kyoto Protocol's 
project based mechanisms {COM(2003) 403 final}{SEC(2003) 785}, and (3) Watterson et al. (2011).  

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emission  inventories  and  in  the  projections  in  particular  in  relation  to  future  wood  demand 
(including the demand for biomass energy) and the possible role of natural disturbances (see 
Annex III for a description of uncertainties). 

Accounting option (a) is expected to result in credits of around -79 MtCO2 per year for the 
EU  as  a  whole  This  adds  up  to  credits  of  some  629  MtCO2  over  the  whole  commitment 
period. The main reason is that credits in existing forests are calculated without a benchmark, 
i.e. all net removals in the commitment period are converted into credits regardless of whether 
they are the result of changes in management practices or natural factors and then discounted 
by 85%. This approach would create credits which are largely unrelated to actual management 
practices, i.e. windfalls. It would also reduce the incentive for mitigation efforts in the sector 
as each tonne of CO2 mitigation achieved at any price level would be discounted and, hence, 
made  more  expensive  relative  to  mitigation  measures  in  other  sectors.  Estimates  show  that 
accounting option (a) is expected to generate credits for most MSs or have hardly any impacts 
at all, see Table A4.4 in Annex IV for more details. 

Table 5.  Estimated annual credits (MtCO2 per year) in 2013-20 for the three accounting options 

MS 

Accounting 
option (a) 

Accounting option (b) 

Accounting option (c) 

Small 
changes 

Outcome of the UNFCCC 
negotiations 

Annual average over commitment 
period 

Cumulative 2013-20 

-78.7 

-629 

(I) 

-14.5 

-116 

(II) 

-85.8 

-686 

UNFCCC+ 

(I) 

-35.0 

-280 

(II) 

-106.3 

-850 

Notes: Negative values denote net credits (and positive values net debits). Options take into account that some MS already 
have  voluntary  accounting  of  GM  and  FM  in  the  baseline.  Credits  for  Forest  management  are  calculated  in  two  different 
ways (in both cases, the impact of the cap on credits equal to 3.5% of base year emission is included): 

(I) (modelled emissions and removals in reference scenario) - (modelled emissions and removals in baseline scenario) 

(II)  (modelled  emissions  and  removals  in  reference  scenario)  -  (forest  management  reference  levels  in  LULUCF  decision  of 
CMP.7)  

Differences between (I) and (II) reflect different assumptions or methods used in the models' projections as compared to country-
specific projections. 

Source:  Calculations  based  on  Böttcher  et  al.  (2011)  and  JRC  (2011b)  and,  for  those  MSs  that  based  their  submissions  of 
reference levels  on  this  work,  have  been adjusted  following  the expert  review  of  forest  management  projections  under  the 
UNFCCC. 

Accounting option (b) is expected to result in credits of around 10 MtCO2 per year and 77 
MtCO2 cumulatively over the whole commitment period if credits are calculated using model 
projection for forest management reference levels ((b(I)). Credits would be nearly 86 MtCO2 
per  year  and  686  MtCO2  cumulatively  over  the  whole  commitment  period  if  the  forest 
management reference levels agreed in UNFCCC decision CMP7 would be used (option b(I). 
For 10 countries the decision uses forest management reference levels projected by member 
states  rather  than  model  projections.Under  option  (b)  credits  are  substantially  smaller  than 
option  (a)  because  this  option  measures  changes  in  emissions  and  removals  relative  to  a 
reference  level.  In  fact,  debits  are  expected  from  forest  management  as  a  result  of  an 
increasing  demand  for  wood  for energy  purposes.  When  provided  for  energy  purposes  such 

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wood  will  avoid  CO2  emissions  in  the  energy  sector  while  substituting  fossil  fuels.  The 
overall  credits  of  the  sector  are  explained  by  net  removals  from  afforestation  efforts  since 
1990  which  exceed  the  expected  emissions  from  deforestation.  There  are  significant 
variations  between  Member  States  (see  Table  A4.4  in  the  Annex  for  details).  For  instance, 
estimates show that 17 countries (e.g. Germany, Poland, UK, Austria and France) would have 
credits whereas in ten countries (e.g. Italy, Spain and Romania) debits may arise. 

Accounting  option  (c)  (UNFCCC+)  results  in  expected  credits  of  35  MtCO2  per  year  with 
modelled projections (column I) and 106 Mt using the reference projections submitted to the 
UNFCCC (mix country and model projections). Overall credits are higher than in option (b) 
because  this  option  includes  the  effects  of  mitigation  achievements  in  cropland  and  grazing 
land  management.  The  latter  activity  in  particular  is  expected  to  lead  to  an  increase  in  net 
removals compared to 1990. The cumulative credits for the commitment period would be 315 
MtCO2. The distribution of debits and credits amongst MSs is similar to that in option (b). 

Contrary  to  option  (a)  which  is  based  on  discounting,  both  options  (b)  and  (c)  fully  reflect 
changes in forest management practices (1 ton change = 1 ton accounted), here in response to 
the  expected  increase  in  demand  for  wood  for  energy  purposes.  The  results  also  clearly 
illustrate the difference between accounting against a reference level, where only changes in 
management  practices  will  count,  and  accounting  for  emissions  and  removals  without  any 
benchmark.  In  particular,  option  (b)  and  (c)  ensure  that  the  use  of  biomass  in  other  sectors 
than LULUCF is mirrored in accounting and therefore provides a level playing field between 
different uses of biomass. The expected increase in the use of biomass for energy associated 
with  reaching  the  RES-D  targets  is  estimated  to  involve  a  reduction  in  net  removals  of  on 
average about 15 MtCO2 per year in the period 2013-2020 (based on the JRC LULUCF tool 
calibrating model results see JRC (2011b) and Böttcher et al, 2011, p.39). One should recall 
that such biomass allows to save GHG emissions in the energy sector while replacing fossil 
fuels.  Finally,  the  effects  of  the  more  inclusive  accounting  in  option  (c)  is  reflected  in  the 
higher level of net removals (credits) compared to option (b). 

The analysis shows that all accounting options are expected to generate a surplus of credits at 
the EU level and, in the absence of an explicit link to the EU's overall target or a sector target, 
this option would not per se create additional incentives to increase net removals or reduce net 
emissions  compared  to  the  reference  scenario.  In  other  words,  the  expected  impact  of  this 
option  on  real  GHG  emissions  compared  to  the  reference  scenario  is  zero  but  because  of 
efforts  that  have  already  been  undertaken  some  credits  would  arise,  depending  on  the 
accounting  option  chosen.  Option  2.I  would  mean  that,  for  the  time  being,  the  net  result  of 
LULUCF  accounting  would  be  a  memo  item  in  the  context  of  the  existing  overall 
commitment. 

Box 4. How have the illustrative targets been set?  

In  Option  2.II  the  MS  targets  are  based  on  two  components;  the  estimated  mitigation  potential  of  LULUCF  per  MS  at  a 
30 in the different accounting options (see Annex IV for details on MSs) plus the expected credits 
carbon price of €5 per tCO2
or  debits  generated  in  the  reference  scenario  in  the  different  accounting  options  (at  zero  cost).The  sum  of  these 
components, i.e. the target, can then be expressed as a percentage of the total GHG emissions in 1990. 

30 

This carbon price is equal to the expected EU-wide carbon price of meeting the targets under the effort 
sharing decision, based on the analysis underlying Commission Staff Working Document (SEC(2010) 
650  accompanying  the  Communication  (2010)  265  final  "Analysis  of  options  to  move  beyond  20% 
greenhouse gas emission reductions and assessing the risk of carbon leakage." 

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5.1.1.2.  Option 2.II – Separate framework for LULUCF (with mitigation targets) 

Box  4  explains  how  the  target  was  simulated  in  Option  2.II.  The  impact  on  net  emissions 
depends on the carbon price and on the accounting rules. Figure 9 shows the real abatement 
potential expected at different price levels in accounting options (b) and (c). A target based 
on  €5  per  tCO2  would  generate  an  increase  in  net  removals  of  about  5  MtCO2  in  2020 
compared to the reference scenario. Based on a target which includes the credits generated in 
the  reference  scenario  plus  the  mitigation  potential  at  €5  per  tCO2  (see  Box  5),  this  would 
correspond  to  a  target  of  credits  equal  to  -0.3%  in  accounting  option  (b)  and  -0.8%  in 
accounting  option  (c)  for  the  EU  as  a  whole.  The  largest  share  of  abatement  potential  is 
expected  to  come  from  changes  in  forest  management  practices  followed  by  efforts  to  limit 
deforestation.  Cropland  management  and  afforestation  play  only  a  minor  role.  It  should  be 
noted  that  the  difference  between  the  two  accounting  options  is  small  because  no  estimates 
were made of the mitigation potential through changes in grazing land management. Also, the 
modelling  of  mitigation  measures  in  cropland  management  measures  is  limited.  The 
mitigation potential of accounting option (c) may therefore be underestimated. 

Figure 9 also shows the marginal cost of abatement efforts in accounting option (a). In this 
case,  mitigation  efforts  in  forest  management  are  discounted  by  85%,  which  means  that  the 
accounted contribution to the overall target decreases at any given carbon price. To reach an 
(accounted) reduction in the EU of 5 MtCO2, and a target of a credits equal to -1.5% (i.e. the 
credits  in  the  reference  scenario  plus  actual  reductions  of  7  MtCO2)  of  total  emissions  in 
1990, a carbon price of some €12 rather than €5/t CO2 would be required. 

Considering the current uncertainties related to incomplete and uncertain emission inventories 
and  uncertainty  in  the  projections  (although  they  are  partially  addressed  by  calibrating  the 
model  results  on  the  basis  of  reported  data,  see  Annex  III  for  details)  it  is  premature  to  set 
quantitative  national  targets  similar  to  ESD  targets  at  this  stage.  Further  analysis  would  be 
required because the differences in the LULUCF projections between the models and methods 
used are high compared to the potential mitigation potential of around 5 MtCO2 that can be 
achieved at marginal costs of up to €5 per tCO2. Fixing a quantitative target therefore carries a 
risk  of  under-  and  overshooting  targets  and  therefore  potentially  of  associated  costs. 
Nevertheless, the preliminary analysis has been carried out to inform the discussion on target 
setting. 

5.1.1.3.  Option 3 – Inclusion of LULUCF in the ESD 

In Option 3, the assumption is that MSs keep their current targets under the ESD and that any 
credits  or  debits  generated  by  LULUCF  count  towards  those  targets.  A  redistribution  of 
targets  has  not  been  considered  under  the  current  20%  commitments.  The  carbon  price  is 
assumed to be €5.3 per tCO2 reflecting the price expected of transfers under the ESD to meet 
the national targets agreed under the Climate & Energy Package. 

If  the  credits  could  be  used  to  meet  the  national  targets  agreed  under  the  ESD,  accounting 
option  (a)  would  have  a  significant  impact.  The  credits  generated  in  the  reference  scenario 
(Table 6) could be as high as 90% of the cumulative emission reduction needed between 2010 
and  2020  under  the  ESD  plus  the  mitigation  efforts  at  the  assumed  carbon  price.  The 
accounting would therefore substantially reduce the actual emission reduction achieved in the 
ESD sectors compared to 2005 and compared to the efforts that have already been agreed in 
the Climate and Energy Package. 

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For accounting options (b) and (c) the impact would be smaller but not insignificant as the 
effect on the cumulative effort between 2010 and 2020 would be between 14 to 44% of the 
total required reductions in the ESD, see Table 6. The emission reduction in the ESD would 
be reduced rather than simply replaced by efforts in LULUCF because all accounting options 
allow for at least some degree of decrease in net removals whilst still generating credits; this 
is particularly the case for forest management under accounting option (a) for which credits 
are generated as long as forest management is a sink but also, although to a smaller extent, in 
accounting options (b) and (c) where no debits are awarded for forest management as long as 
the sink declines according to the reference level. 

Figure 9. Mitigation in the EU LULUCF sector in 2020 (MtCO2 per year) 

Options b & c

Option a

)
2
O
C

t
/
€
(

e
c
i
r

P
2
O
C

160

140

120

100

80

60

40

20

0

0

10

20

30

40

50

60

Mitigation in MtCO2 per year

Note: Effects measures that lead to increases in the HWP pool have not been considered.  

Source: Böttcher et al. (2011), based on the G4M-EUFASOM models 

5.1.2.  Other environmental impacts 

The impact on land use change is expected to be minimal in the short term and at low carbon 
prices.  In  Option  2.II  combined  with  accounting  options  (b)  and  (c),  the  additional 
afforestation  efforts  and  reduced  deforestation  are  projected  to  have  a  limited  effect  on  the 
forest area (an increase by some 0.05%) in 2020 compared to the reference scenario, and by 
about 0.15% in accounting option (a), see Table 6. Land use change is expected to be zero in 
all other options. 

From a wider environmental perspective, a reduction of soil organic matter levels because of 
land use or land use change is a cause of concern not only for its link to climate change, but 
also because soil organic matter is a major contributor to wide environmental safeguards such 
as soil fertility as it binds nutrients to the soil, thus ensuring their availability to plants; it is 
the  home  for  soil  organisms,  from  bacteria  to  worms  and  insects,  and  allows  them  to 
transform  plant  residues.  And  it  also  maintains  soil  structure,  thereby  improving  water 
infiltration,  decreasing  evaporation,  increasing  water  holding  capacity  and  avoiding  soil 
compaction.  Accounting  for  LULUCF  is  therefore  likely  to  enhance  these  properties.  Not 

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including the sector in the commitments (Option 1) would discourage the protection and/or 
enhancement  of  soil  and  biomass  carbon  stocks  directly  or  indirectly  by  not  reflecting  the 
effects  of  certain  agricultural  practices.  Even  simple  monitoring  and  reporting  would  create 
meaningful  incentives  to  reduce  certain  activities  (e.g.  the  conversion  of  grassland  to 
cropland, the cultivation of organic soils) that are generally undesirable both from a GHG and 
other  environmental  perspectives.  Accounting  option  (c)  would  ensure  that  changes  in  soil 
organic matter would be taken into account throughout the EU whereas accounting options 
(a) and (b) would not as they allow MSs to account for agricultural activities (cropland and 
grazing land management) on a voluntary basis. 

Table 6.  Environmental impacts of the options 

Option 1 

No EU action 

Option 2.I 

Option 2.II 

Option 3 

Include LULUCF as a 
separate framework 
(No target) 

Include LULUCF as a 
separate framework 
(Target = 5 MtCO2 
accounted credits) 

Include LULUCF in the 
ESD 
Assuming carbon price of 
€5 per tCO 2  

Accounting 
option 

n/a 

(a) 

(b) 

(c) 

0 

0 

0 

0 

0 

0 

(a) 

-7 

(b) 

-5 

(c) 

-5 

(a) 

80 

(b) 

13 

(c) 

39 

-54* 

-43 

-43 

642 

102 

315 

n/a 

n/a 

n/a 

n/a 

n/a 

n/a 

51% 

8% 

25% 

n/a 

n/a 

n/a 

n/a 

n/a 

n/a 

90% 

14% 

44% 

0 

0 

n/a 

n/a 

MtCO2/year 

MtCO2 from 
2013-2020 
(MtCO2) 

% of ESD effort 
in 2020 

% of ESD effort 
2013-2020 
Land use 
change (forest 
area change as 
compared to 
reference 
scenario, %) 

0 

0 

0 

0 

0.15% 

0.05% 

0.05% 

0 

0 

0 

Note: Option 2.II is based on a target of -5.4 MtCO2 accounted credits. This equals a carbon price of €5 per tCO2 for accounting options (b) 
and (c), as assumed for Option 3, but a carbon price of €12 per tCO2 for accounting option (a) due to the discounting of forest management. 
Negative values denote net removals (and positive values net emissions). Source: Calculations based on updated version of Böttcher et al. 
(2011) and JRC (2011b), reflecting the UNFCCC review, and PRIMES-GAINS model results 

5.1.3.  Possible contributions to an EU target 

The possible contributions to the EU target will differ depending on the accounting option and 
the context in which LULUCF is accounted. As shown above, some credits will be generated 
also  at  a  zero  carbon  price.  In  Option  1  (No  EU  action)  there  will  be  no  impact,  and  in 
Option 2.I (Separate framework without mitigation targets) the impact will be equal to that of 
the reference scenario which would be a memo item on top of the 20% target. 

Table  7.  Possible  contribution  of  options  to  the  EU's  GHG  reduction  target  in  2020  for  different  accounting  rules 
(based on the reference scenario) 

Accounting options 

Policy options 

Option 1 

Option 2.I 

Option 2.II 

Option 3 

(a) Small changes to current rules 

(b) Outcome in the UNFCCC (I) 

(b) Outcome in the UNFCCC (II) 

(c) UNFCCC+ (I) 

n/a

n/a 

n/a 

n/a

-1.4%

-0.3% 

-1.5% 

-0.6%

-1.5%

-0.3% 

-1.6% 

-0.8%

0 

0 

0 

0 

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(c) UNFCCC+ (II) 

n/a 

-1.9% 

-1.9% 

0 

Note: A minus sign denotes credits and would contribute to reaching the EU's overall GHG reduction target. (I) relies only 
model  results.  (II)  relies  on  a  mix  of  model  results  and  national  submissions  for  forest  management  reference  levels  (see 
Table 5 for details) Source: Calculations based on Böttcher et al. (2011) and update of JRC (2011b) 

Option 2.II (Separate  framework with mitigation targets) with accounting  options (b) and 
(c) would contribute about -0.3% to -1,6% and -0.8% to -1.9% (c) respectively. Accounting 
option (a) generates a higher target (-1.4%) due to windfall credits in the reference scenario. 
In Option 3 (inclusion in the ESD), part of the efforts in other sectors would be replaced by 
LULUCF credits, which means that there would be no addition to the target and, indeed, the 
efforts in other sectors would decrease. 

By way of sensitivity analysis, Table 8 shows the changes in emissions and removals resulting 
from  a  10%  change  in  the  EU  harvest  rates.  A  decrease  (increase)  in  the  harvest  rate 
compared  to  the  reference  scenario  would  result  in  credits  (debits)  of  about  50  MtCO2  per 
year  (0.9%  of  total  EU  GHG  emission  in  1990)  in  accounting  options  (b)  and  (c).  For 
accounting  option  (a)  the  accounted  amount  would  be  about  7.5  MtCO2  as  a  result  of 
discounting. 

Table 8. Impact on GHG emissions of changes in harvest rates 

Change in harvest rate 

Associated change in emissions (+) and 
removals (-), MtCO2 

Percent of EU total GHG emissions in 
1990 

10% increase 

10% decrease 

52.5 

-52.3 

Source: Calculations based on Böttcher et al. (2011) and JRC (2011b) 

0.9% 

-0.9% 

Box 5. Methodological note 

Forest management 

Importantly, the methodology used to estimate the abatement potential (and, hence, costs and impacts) of forest management 
imply  no  direct  changes  in  harvesting  rates  as  models  are  set  up  to  keep  harvest  close  to  the  reference  scenario  when  the 
carbon  price  increases.  Whilst  harvest  rates  remain  unchanged,  the  geography  of  harvest  changes  and  forest  management 
parameters  such  as  rotation  length  and  the  amount  of  wood  removed  through  thinning  are  changed  for  different  locations  of 
forests to secure a given level of wood supply. This shifts harvest to more expensive and less productive sites. This approach is 
conservative  compared  to  approaches  which  would  involve  reducing  the  harvest  rate  (and  which  would  instead  lead  to  the 
displacement  of  EU  production  to  non-EU  countries).  Note  that  this  does  not  mean  that  in  the  reference  scenario  wood 
production is constant over time. On the contrary, wood production for biomass and  other uses is expected to  be  around 5% 
higher in 2020 than in 2005 (reflected in the decrease in net removals in the reference scenario).31 

If,  however,  the  increased  costs  of  forest  management  would  be  reflected  in  increased  timber  prices  the  timber  demand  and 
harvest  might  however  decrease  slightly.  Imports  might  increase  and  exports  reduced  (see  section  5.2.2.2  for  details).  The 
effect  is  expected  to  be  detectable  only  in  Option  2.II  with  accounting  option  (a)  where  timber  production  might  decrease  by 
0.1%. This might indirectly increase the LULUCF sink and reduce the efforts needed to meet quantitative reduction target.  

Cropland and grazing land management 

It  should  be  noted  that  the  mitigation  potential  of  changes  in  grazing  land  management  has  not  been  modelled.  Also,  the 
modelling  of  cropland  management  measures  is  limited.  The  mitigation  potential  for  agriculture  may  therefore  be 
underestimated. 

A detailed description of the modelled mitigation measures is given in Böttcher et al. (2011). 

31 

See Böttcher et al (2011), p.29 based on PRIMES results for energy and forest models for non-energy 
timber demand. 

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5.2. 

Economic implications 

This section discusses the abatement costs for the EU as a whole and the costs for the most 
affected sectors (forestry and agriculture) and costs of monitoring and reporting. As noted in 
Section 2.3, this report does not attempt to assess the impact on individual businesses such as 
SMEs  because  legislation  would  involve  an  accounting  framework  at  MS  level  rather  than 
provide  incentives  directly  to  different  sectors  or  companies.  Subsequent  choices  on  policy 
instruments  will  have  to  be  made  by  MSs  and  the  implications  cannot  be  predicted  at  this 
stage. However, a brief mention is given to possible impacts by owner structure. 

5.2.1.  Direct abatement costs 

Abatement costs are only relevant for Options 2.II and 3 as they are the only options which 
would provide additional mitigation incentives for LULUCF, see Table 9. 

5.2.1.1.  Option 2.II – Separate framework with mitigation targets 

The costs of setting a target for the LULUCF sector, based on a marginal cost of €5 per tCO2 
(= 5.4 MtCO2 per year) for accounting options (b) and (c) are shown in Table 9. The annual 
costs  are  expected  to  be  about  €27  million  per  year.  For  accounting  option  (a)  the  costs 
would  be  higher  since  net  removals  in  forest  management  are  discounted  by  85%.  This 
increases the marginal costs to some €12 per tCO2 to achieve the same accounted reduction of 
5  MtCO2.  Consequently,  annual  costs  would  be  higher  and  around  €37  million  per  year.  It 
should be noted that the costs of accounting option (a) would be significantly higher at higher 
mitigation targets. However, the results are uncertain (see Annex III) and this will affect the 
ability of MSs to achieve targets as well as the costs associated with reaching those targets. 

Table 9.  Abatement costs per year in 2020 (€2008) 

Option 2.II 

Include LULUCF as a separate framework 
(Target) 

Option 3 

Include LULUCF in the ESD 

Accounting 
option 

Marginal costs 
€/tCO2  

Abatement 
costs (mln€/yr) 

(a) 

12 

40 

(b) 

5 

27 

(c) 

5 

27 

(a) 

0.3 

-166 

(b) 

3.8 

-55 

(c) 

1.0 

-156 

(as % of GDP)  

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

0.00% 

Source: PRIMES, GAINS and G4M model results 

5.2.1.2.  Option 3 – Include LULUCF in the ESD 

Meeting  the  targets  under  the  ESD,  whilst  assuming  unlimited  transfers  between  MSs  to 
offset  debits,  is  expected  to  result  initially  in  a  market  price  of  around  €5  per  tCO2.  Under 
Option 3 the price is affected in two ways. First, the accounting rules create credits that lower 
the  need  to  reduce  emissions  in  the  ESD  sectors.  Secondly,  the  inclusion  of  LULUCF  will 
create an incentive to undertake abatement also in the LULUCF sector, if the marginal costs 
of  abatement  are  lower  than  in  the  ESD  sectors.  As  a  result,  some  abatement  will  be 

EN 

42 

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undertaken  in  the  LULUCF  sector.  Both  effects  will  lower  the  carbon  price  in  the  ESD 
sectors. 

Table  9  shows  that  the  impact  is  the  biggest  in  accounting  option  (a)  because  of  the  large 
amount  of  LULUCF  credits.  As  a  result  the  price  could  drop  to  below  €0.3  per  tCO2.32 
Depending  on  the  price  there  is  an  additional  supply  of  LULUCF  reductions  ranging  from 
close to zero in accounting option (a) to around 4 MtCO2 in accounting option (b). 

For  all  options,  the  macroeconomic  implications  will  be  insignificant  since  the  changes  in 
costs are small compared to the expected GDP in 2020. 

5.2.2.  Costs for the various sectors 

Following on from Section 5.2.1, costs are only relevant for Options 2.II and 3 as they are 
the only options which would provide additional mitigation incentives for LULUCF. 

The  two  sectors  that  would  be  directly  affected  by  legislation  are  agriculture  and,  broadly 
defined,  forestry.  Table  10  shows  the  abatement  costs  for  the  sectors  in  2020.  The  greatest 
contribution to mitigation is expected to come from forestry and forest management whereas 
the potential for cropland and grassland management is expected to be limited (see Box 5). As 
mentioned above, the abatement costs are uncertain since the projections are uncertain. 

5.2.2.1.  Agriculture 

Under Option 2.II and  accounting option (c) agriculture can contribute to some degree by 
improved cropland management to enhance the sink and so faces some costs (€1 million per 
year)(see  Böttcher  et  al.  (2011).  i.e.  pp  10-11  and  p.  47  for  details).  Under  accounting 
options  (a)  and  (b)  costs  would  only  arise  if  countries  choose  to  account  for  agricultural 
activities (which are voluntary). The effect would be most significant for accounting option 
(a) since the carbon price is higher and therefore induces higher abatement also for cropland 
management. However, costs are expected to be small compared to the gross value added of 
the sector in 2020. 

Under  Option  3  the  costs  for  agriculture  are  negative.  Any  additional  costs  for  cropland 
management are expected to be more than compensated by the cost savings of reducing non-
CO2 GHG emissions in agriculture under the ESD. If the marginal costs drop below  €5 per 
tCO2 (expected in all accounting options) several non-CO2 abatement measures, e.g. reducing 
nitrous oxides from fertilizer application, do not appear to pay off anymore. Note, however, 
that  the  marginal  costs  of  measures  are  country  specific.  Results  might  therefore  differ 
between countries and the analysis on the impacts per sector which was made at an aggregate 
EU  level.  The  credits  and  the  inclusion  of  LULUCF  options  in  the  ESD  (Option  3)  would 
reduce the carbon price in the ESD sector and the need to reduce emissions in agriculture as 
well as other sectors. The costs for other sectors covered by the ESD are reduced the most, 
especially  the  energy  sector  that  emits  non-CO2  GHGs.  The  impact  on  CO2  reduction  from 
energy is expected to be small. 

32 

The effect on the price of the ESD sectors was based on a set of dedicated runs of the PRIMES-GAINS 
models and are driven mainly by the expected marginal costs for reducing non-CO2 GHG emissions in 
the ESD sectors.  

EN 

43 

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5.2.2.2.  Forestry 

Impacts will differ between different options also in the forestry sector. In Option 2.II with 
accounting  option  (a)  abatement  efforts  are  estimated  to  lead  to  a  cost  increase  of  0.2% 
relative to the production value in 2020. Elasticities of demand for timber vary by region and 
product between -0.3 and -0.6 (with an average of -0.5).33 Subsequently, the indirect effects of 
passing on a cost increase of 0.2% in the timber price is estimated to lead to a reduction in 
demand  of  around  0.1%  for  this  particular  accounting  option.  If  international  markets  are 
competitive relative to the EU market, part or all of the estimated decline in demand would 
instead  be  shifted  to  the  international  market  (leakage).  In  all  other  accounting  options  in 
Option  2.II  and  Option  3,  the  additional  cost  for  the  forest  sector  are  much  smaller  in 
absolute terms and relative to the value of production. Indirect effects are minimal. 

Table 10. Abatement costs per sector 

Option 2.II 

Include LULUCF as a separate framework 
(Target) 

Option 3 

Include LULUCF in the ESD 

Accounting  
option 

Agriculture (€million/year) 

Forestry (€million /year) 

Other (ESD) Sectors 
(€million/year) 

SUM (€million/year) 

Agriculture (% of gross 
value added) 

Forestry (% of gross 
value added) 

(a) 

2* 

38 

0 

40 

(b) 

1* 

26 

0 

27 

(c) 

1 

26 

0 

27 

(a) 

-49 

0 

-117 

-166 

(b) 

-47 

16 

-24 

-55 

(c) 

-49 

1 

-108 

-156 

0.00% 

0.00% 

0.00% 

-0.03% 

-0.02% 

-0.03% 

0.13% 

0.09% 

0.09% 

0.00% 

0.06% 

0.00% 

Note: * Assumes that MSs choose to account for cropland management where there is a mitigation potential at €5 per tCO2.  

Source: Calculations based on Böttcher et al. (2011), using the G4M&EUFASOM, PRIMES and GAINS. Numbers may not 
add up to rounding 34  

Whilst  Table  10  presents  all  forest  related  impacts  in  terms  of  "forestry",  the  incidence  is 
likely  to  be  spread  over  different  uses.  Table  11  presents  costs  according  to  the  projected 
market shares of energy (41%) and other wood uses (59%) in 2020. The latter group of uses 
consists of sawn wood, pulp wood and other industrial roundwood. 

33 

34 

EN 

Based on the GLOBIOM model and consistent with UN/FAO data (Kangas and Baudin, 2003; p. 49-
51). 
Based  on 
http://ec.europa.eu/clima/documentation/docs/non_co2emissions_may2010_en.pdf  

the  detailed  non-GHG  cost  curves 

the  GAINS  model,  see 

for  2020 

from 

44 

   EN 

 
  
 
                                                 
Table 11. Costs by wood use (€ million per year) 

 Sector 

Option 2.II 

Option 3 

Include LULUCF as a separate framework  
(Target) 

Include LULUCF in the ESD 

Accounting option 

Energy 

Other wood uses 

(a) 

15 

22 

(b) 

11 

15 

(c) 

11 

15 

(a) 

0 

0 

(b) 

7 

9 

(c) 

0 

1 

Sawn wood 

Pulp wood 

Other industrial 
roundwood 

13 

8 

1 

9 

6 

1 

9 

6 

1 

0 

0 

0 

5 

3 

1 

0 

0 

0 

Source: Calculations based on Böttcher et al. (2011) and Capros et al. (2010) 

It should be noted that the extent to which accounting and hence the forestry sector is affected 
will depend on the rate of change in the pool of harvested wood products. An increased use 
of  wood  products  would  enhance  the  rate  and  generate  credits  which  could  potentially  be 
recycled into industry. Rüter (2011) calculated changes in this pool for the years leading up to 
2020  based  on  projections  of  harvest  rates  provided  by  Böttcher  et  al.  (2011)  and  various 
country-specific  models.35  The  current  increase  is  expected  to  continue.  As  shown  in  Table 
12,  with  a  net  pool  increase  estimated  at  approximately  52  MtCO2  in  2020.  However, 
emissions / removals fluctuate between single years and it may therefore be more appropriate 
to refer to the average of 2013-2020 of 55 MtCO2. The HWP pool can increase in the short to 
medium term and may stabilise in the long term when removals from new wood products can 
compensate emissions from old wood products (i.e. inflow equals outflow). 

Table 12 Historic (up to 2009) and projected net emissions from the HWP pool (MtCO2)*, ** 

EU total 

2000 

-52.9 

2005 

-59.6 

Year 

2010 

-64.3 

2015 

-56.8 

2020 

-52.0 

Average 

2013-20 

-54.9 

Note: * Negative values denote a pool increase. ** The calculations are subject to change following the UNFCCC review 
process of reference levels (incl. HWP) as submitted by MSs.  

Source: Rüter (2011) 

Another  important  factor  to  consider  is  the  potential  benefits  in  terms  of  GHG  savings  that 
can be achieved as a result of substitution of materials and / or energy sources for biomass 
that  will  appear  in  the  accounting  of  other  (non-LULUCF)  sectors.  These  emission  savings 
would be accurately reflected in accounting only once  the related emissions  are  recorded in 
LULUCF. In a review of some 20 studies, Sathre and O'Connor (2010) found that the amount 
of carbon emissions avoided by the use of wood instead of non-wood material averaged at a 

35 

As  noted  in  Box  3,  MSs  have  submitted  reference  levels  (excluding  and  including  harvested  wood 
products)  to  the  UNFCCC  for  review  in  anticipation  of  a  decision  on  accounting  rules  at  the  world 
climate summit in Durban later this year. Some 15 MSs base their harvest projections on Böttcher et al. 
(2011),  the  remaining  MSs  use  national  models  (see  submissions  to  the  UNFCCC  as  requested  by 
Decision  2/CMP.6,  http://unfccc.int/meetings/ad_hoc_working_groups/kp/items/5896.php).  Based  on 
the harvest projections, the pool of HWP in use was calculated, following the approach suggested by 
FCCC/KP/AWG/2010/CRP.4/Rev.4 (p.31, paragraph 7).  

EN 

45 

   EN 

 
 
 
                                                 
factor of two. In other words, for each tC in wood products that substitute non-wood products, 
an  average  GHG  emission  reduction  of  2.1  tC  can  be  expected.  The  primary  reason  is  that 
wood  products  generally  require  less  total  energy  (in  particular  fossil  fuel  consumption)  in 
manufacturing  compared  to  products  made  from  alternative  materials.  The  energy  recovery 
from biomass residues associated with wood products, e.g. wood processing residues, and the 
use of post-use wood products for energy purposes are also important. 

5.2.2.3.  Impacts by owner structure 

Any  positive  direct  costs  of  accounting  for  LULUCF  (Options  2.II  and  3)  will  mainly  be 
borne by the forest sector. Some 46% of the forest is owned by individuals and families, some 
11% is owned by forest industries and private institutions whereas local communities own 2% 
and the remaining 41% is public ownership (UNECE, 2011). Roughly half of any additional 
costs  incurred  for  the  forest  sector  (see  Table  10)  could  therefore  be  borne  by  individual  / 
family  forest  owners  and  10%  by  private  business  entities  and  institutions  (including  SMEs 
and micro-firms), and another 40% by the public sector. Estimates suggest that the number of 
private  forest  owners  might  be  around  15  million36.  The  most  costly  Option  2.II  with 
accounting option (a) would involve an average additional cost per (private) forest owner of 
around €2 per year. Accounting options (b) and (c) would imply average costs of only some 
€1 per forest owner per year.  

5.2.3.  Monitoring and reporting costs 

The implications of changes in monitoring and reporting requirements need to be assessed in 
two  ways;  some  impacts  stem  from  the  administrative  burden  of  changes  in  the  scope  of 
mandatory accounting and the accounting methods applied, and others relate to the additional 
efforts required by MSs to reach the objective defined in this impact assessment of reporting 
according to the IPCC GPG. The costs are the same for Options 2 and 3, although they vary 
depending on accounting option, and zero for Option 1. 

5.2.3.1.  Administrative burden of changing the scope and methods of accounting  

Some  reporting  costs  would  arise  as  a  result  of  changing  the  scope  and  modalities  of 
accounting because the data needs for reporting on land use activities under the KP go beyond 
those  for reporting on  land use categories under the UNFCCC.  The associated  costs largely 
form  part  of  the  impact  assessment  of  revising  the  Monitoring  and  Mechanism  Decision 
(208/2004/EC) but are included also here for reasons of transparency, see Table 13. 

No  additional  reporting  requirements  would  be  implemented  for  afforestation,  reforestation 
and  deforestation.  Today,  accounting  for  forest  management  is  not  mandatory,  but  17  MSs 
have  already  chosen  to  account  for  associated  emissions  and  removals.  Making  this  a 
mandatory activity would involve additional efforts for 10 MSs at a total cost of about €0.4 
million per year. Necessary updates of the data on forest management required for accounting 
options  (b)  and  (c)  is  expected  to  be  negligible  (a  total  €20  thousand  per  year)  and  the 
mandatory reporting of changes in the HWP pool is estimated to cost roughly €0.3 million per 
year.  There  will  be  additional  costs  from  the  introduction  of  mandatory  accounting  and 
reporting  of  cropland  and  grazing  land  management  activities  in  accounting  option  (c)  at 

36 

See http://www.micro-fuel.eu/about-the-project 

EN 

46 

   EN 

 
                                                 
approximately  €0.7  million  per  year.  Following  the  adoption  of  the  2006  IPCC  GPG  costs 
could become higher but are not estimated here. 

Table 13. Administrative burden of additional mandatory reporting requirements (€ million per year for the EU-27) 

Reporting item 

Accounting option (a) 

Accounting option (b)* 

Accounting option (c)* 

Small changes 

Likely outcome in the 
UNFCCC negotiations 

UNFCCC+ 

Report emissions and 
removals from forest 
management activities on 
a mandatory basis 

Report data on changes in 
the harvested wood 
products pool 

Updating of forest 
management reference 
levels 

Reporting emissions and 
removals for cropland and 
grazing land management 

0.35 

- 

- 

- 

EU total 

0.35 

0.35 

0.30 

0.00 

- 

0.65 

0.35 

0.30 

0.00 

0.70* 

1.35 

Note:  The  cost  of  reporting  items  equal  to  accounting  option  (a)  have  been  addressed  in  the  impact  assessment  of  the 
proposal  for  the  revised  Monitoring  and  Mechanism  Decision  (208/2004/EC)  and  related  Commission  Decision 
(2005/166/EC) and are included here for reasons of transparency. Note that an international agreement is likely generate the 
same additional administrative burden as accounting option (b). * This estimate is an approximation based on the estimated 
costs associated with reporting for rewetting and draining on land with organic soils.  

Source:  European  Commission  impact  assessment  of  the  proposed  revision  of  the  Monitoring  and  Mechanism  Decision 
(208/2004/EC)  

5.2.3.2.  Implications of improved monitoring and reporting  

Whilst  additional  efforts  will  be  required  by  MSs  to  improve  the  various  aspects  of 
monitoring  and  reporting,  it  must  be  noted  that  the  related  costs  would  not  be  the  result  of 
including  LULUCF  in  the  EU's  GHG  emission  reduction  commitments.  MSs  are  already 
required to use higher tiers for key categories, corresponding to Steps 1 and 2 of improving 
monitoring  and  reporting  as  outlined  in  Section  4.3  (as  a  result  of  existing  reporting 
obligations and commitments under the UNFCCC and the KP). However, since improvements 
will generally be required by MSs, estimates of the costs for improving the reporting on soils 
are presented here and in Annex I by way of illustration.  

In tems of the first step, reporting on biomass in forest land is generally complete today, but 
many  MSs  do  not  report  on  soil  in  one  or  two  of  the  sub-categories  under  forest  land, 
cropland  and  grassland.  Applying  tier  1  requires  compiling  activity  data  (i.e.  area 
disaggregated  by  broad  climate  and  soil  type  and  by  broad  management  regime)  from 
different sources in MSs and / or from European initiatives such as LUCAS37 and CORINE 

37 

EN 

The Land Use/Cover Area frame statistical Survey. The name reflects the methodology used to collect 
the information. Estimates of the area occupied by different land use or land cover types are computed 
on the basis of observations taken at more than 250 000 sample points throughout the EU rather than 
mapping the entire area under investigation. By repeating the survey every few years, changes to land 
(see 
use 

management 

identified 

land 

and 

can 

be 

47 

   EN 

 
                                                 
for recent years, to be combined with IPCC default values for carbon stock and stock changes. 
Some MS still have difficulties in tracking the history of land over time in order to calculate 
land conversion. While the effort needed to improve the completeness for mineral soils can be 
assumed  to  be  reasonable,  it  must  be  understood  that  tier  1  reporting  provides  limited 
information  about  the  effects  of  mitigation  measures.  On  organic  soils,  and  for  land 
conversion, higher tiers need to be applied. However, as organic soils only make up 2% of the 
total surface, the additional efforts should be limited. This first essential step could be taken 
rather swiftly. 

As regards the second step, MSs such as Sweden, the UK, Denmark, Finland and Germany, 
already apply high level tiers to the soil pool in all land categories, but most MSs use tier 1 or 
do  not  report  at  all  on  soil  in  at  least  one  of  the  land  categories.  There  is  also  a  need  for 
improved  reporting  on  dead  organic  matter  in  forest  land,  although  the  significance  varies 
and,  in  cropland  and  grassland,  simpler  methods  are  acceptable  also  under  tier  2  (IPCC, 
2003). Country-specific data are generally available in the EU-15, but less so for the EU-12. 
Finally, additional efforts may be needed for measuring stock changes in perennial vegetation 
in  cropland  and  grassland.  Data  needed  to  calculate  the  soil  emissions  factors  could  be 
collected e.g. through repeated soil sampling campaigns in order to capture the annual rates of 
emissions and removals. Substantial work has already been carried out for the proposal of a 
European  Soil  Framework  Directive  and  shows  that  there  is  capacity  to  build  on  (see  e.g. 
Kibblewhite  et  al.,  2008;  Hiederer  et  al.,  2011,  EC,  2003).  Activity  data  would  have  to  be 
collected making use of existing data sources (IACS, FSS, FADN, crop statistics). More work 
is required to integrate existing data on soil types (e.g. EU soil map, LUCAS, national land 
surveys) with activity data on field management. 

Annex I provides estimates of soil sampling costs resulting from the calculation of country-
specific  emission  factors  for  soil,  equivalent  to  Steps  1  and  2.  However,  the  required 
frequency  and  scope  of  soil  sampling  will  vary  across  MSs.  If,  for  the  purpose  of  GHG 
inventories,  emission  factors  are  developed  through  targeted  research  and  combined  with 
modelling tools, soil sampling will play the role of verifying, improving  and calibrating the 
estimated  data.  Other  methods,  including  eddy  covariance  measurements  (used  e.g.  in 
CarboEurope) and chronosequencing38 can contribute in providing the necessary inputs. 

If  all  MSs  require  investments  in  soil  monitoring  to  move  to  country  specific  data  in 
reporting, the annual cost for the EU-27 are expected to amount to between €0.5-2.1 million 
per  year  using  a  sampling  interval  of  eight  years  (which  corresponds  to  the  commitment 
period  of  2013-20).  However,  and  as  shown  in  Table  A1.10  in  Annex  I,  a  number  of  MSs 
already  use  country-specific  data  which  means  that  the  cost  is  likely  to  be  lower,  between 
€0.4-0.5 million per year at the EU level. 

Arrouays et al. (2008) estimated the number of additional sampling sites needed to detect a 
relative  decrease  of  5%  in  soil  organic  carbon.  If  the  same  cost  assumptions  are  applied  to 
their  estimate,  the  resulting  costs  would  be  €0.9-1.2  million  per  year,  i.e.  about  double  the 

38 

http://epp.eurostat.ec.europa.eu/portal/page/portal/lucas/introduction  for  further  information).  In  2009, 
the survey was extended to include soil sampling on 22 000 sites across the Union. 
Defined  by  IPCC  (2003)  as  "…consisting  of  measurements  taken  from  similar  but  separate  locations 
that represent a temporal sequence in land use or management, for example, years since deforestation. 
Efforts are made to control all other between-site differences (e.g., by selecting areas with similar soil 
type, topography, previous vegetation). Chronosequences are often used as a surrogate for experimental 
studies or measurements repeated over time at the same location."  

EN 

48 

   EN 

 
                                                                                                                                                         
costs  compared  to  the  most  conservative  baseline  assumption.  On  the  other  hand,  a  soil 
sampling campaign was carried out under LUCAS39 in 2009 at an additional (soil-sampling 
specific) cost of only €1.2 million (or €0.2 million per year) which is much lower than any of 
the estimates given above. This shows that there are significant potential cost savings through 
the  use  of  coordinated  and  systematic  schemes.  Although  costs  will  vary  between  MSs  and 
with the methods applied, the above estimates provide a cost interval with an average of €1.1 
million  per  year  of  the  additional  investments  required  in  MSs.  The  costs  also  depend  vey 
nuch on the parameteres assessed and the depth of soil sampling. LUCAS was restricted to 0-
30 cm and a reduced number of parameters. For example soil bulk density was not included 
which  accounts  for  as  sizeable  part  of  the  costs  of  soil  survey.  However,  the  parameters 
assessed may be sufficient for the purpose since change in soil carbon may only occur in the 
layer  addressed  for  the  time  frame.  On  top  of  meeting  the  IPCC  GPG  standards,  additional 
efforts to harmonise monitoring and reporting in the EU should be promoted (Step 3). It has 
not been possible to estimate the associated costs at this stage. 

5.3. 

Social implications 

In this section the social implications of Options 2.II and 3 are examined in terms of impacts 
on  employment  and  the  distribution  of  costs  and  cost  savings  (or  revenues)  over  the  MSs. 
Option 2.I is formulated such that the results of accounting are treated as a memo item to the 
EU's  current  overall  GHG  reduction  target  and  there  are  therefore  no  distributional  costs  of 
this option. Similarly, costs are zero for Option 1. 

5.3.1.  Costs by Member States  

5.3.1.1.  Option 2.II – Separate framework with mitigation targets 

In Option 2.II the distribution of cost per MS depends on the estimated mitigation potential. 
The  target  for  each  country  is  set  on  the  assumption  that  all  countries  would  face  the  same 
marginal costs of €5 per tCO2. This is then translated into an amount to be reduced by each 
country over and above the credits generated in the reference scenario. The total amount to be 
reduced  is  some  5  MtCO2  at  the  EU  level  on  top  of  the  credits  generated  in  the  reference 
scenario.  It  should  be  noted  that  uncertainties  on  the  expected  costs  per  MS  are  larger  than 
uncertainties at the EU level. 

Under  accounting  option  (a)  reductions  from  forest  management  are  discounted  by  85%. 
This means that more real reductions (around 14 Mt) are needed to meet the accounting target 
of  around  5  MtCO2  and  this  generates  a  higher  carbon  price  of  around  €12  per  tCO2. 
Consequently, overall costs for the EU (€40 million per year in 2020) and for MSs are higher 
here than in the other accounting options. The illustrative targets are based on the mitigation 
potential at a given carbon price. The largest absolute costs would fall on the following MSs: 
Finland, Bulgaria, Rumania, Estonia, France and Italy (see Table A4.6 in Annex IV). Under 
accounting  options  (b)  and  (c)  the  total  cost  for  the  EU  would  be  smaller  at  about  €27 
million in 2020. Most of the costs would fall on Finland, Bulgaria, Estonia, France and Italy 
(see Table A4.6). 

39 

During the 2009 survey, soil samples were collected from more than 22 000 LUCAS point locations. 

EN 

49 

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5.3.1.2.  Option 3 – LULUCF included in the ESD 

In Option 3 all MSs benefit from a reduction in the cost of meeting the ESD targets but some 
MSs benefit more than others. This is because there are net credits at an EU level that reduce 
the need to cut emissions for sectors covered by the ESD. In this case it is assumed that the 
price  of  ESD  transfers  is  not  fixed  at  €5.3  per  tCO2  (as  expected  to  meet  the  agreed  ESD 
targets) but is lowered for two reasons: the net LULUCF credits at EU level that lower total 
demand for emission reductions and the marginal costs and the additional supply of LULUCF 
sink  enhancement  measures  induced  by  a  positive  carbon  price  in  that  sector.  This  is 
particularly relevant for accounting option (a) where credits are high (50% of the emission 
reduction needed in the ESD sectors in 2020, and 90% of the accumulated emission reduction 
over the period 2013-20) and the ESD price is reduced to less than €0.3 per tCO2 in 2020 in 
the ESD sector. Total cost savings are estimated at €166 million, see Table A4.6 in Annex IV 
for  MS  results.  Note  that  some  MSs  face  additional  costs  since  they  have  net  debits  rather 
than credits. Under accounting option (c) the net LULUCF credits are limited compared to 
the total reduction required under the ESD (around 10% of the reduction effort in 2020, and 
15%  of  the  accumulated  emission  reduction)  so  the  impact  on  the  carbon  price  and  MSs 
abatement  efforts  is  smaller.  The  costs  savings  of  accounting  option  (b)  are  in  between 
options (a) and (c). 

5.3.2.  Employment  

Since the costs of the policy options are negligible in terms of share of GDP (see Table 9) the 
overall impacts on employment will be very small as well. Under Option 2.II combined with 
accounting  option  (a)  costs  are  the  highest  and  this  is  expected  to  lead  to  a  loss  of  timber 
production  in  the  EU  in  the  forest  sector  of  around  0.1%.  For  the  two  other  accounting 
options output changes are even smaller at about 0.01-0.02%. Calculations (based on Eurostat 
(2009;  p.37)  show  that  Option  2.II  combined  with  accounting  option  (a)  could  lead  to  a 
direct loss of some 175 (full-time) jobs in forestry. For accounting options (b) and (c) direct 
jobs losses are estimated at around 125 jobs. 

However,  any  job  losses  will  also  be  (partially)  compensated  by  the  additional  demand  for 
labour  related  to  changes  in  forest  management  (e.g.  increased  thinning)  to  enhance  the 
carbon  sink.  Based  on  the  share  of  labour  costs  in  forest  management  costs  and  the  labour 
costs  per  person  the  number  of  jobs  created  in  forest  management  could  be  around  210  for 
Option  2.II  combined  with  accounting  option  (a)  and  around  180  for  accounting  options 
(b) and (c). Whilst uncertainties are big, the assessment suggests that the overall impact on 
employment are very small and may be positive or neutral. For Option 3 there could be job 
increases since costs are reduced in agriculture and other ESD sectors. Based on the analysis 
carried of options to move beyond 20% greenhouse reductions one can estimate the possible 
impacts.40  Stepping  up  to  25%  would  entail  additional  cost  of  €33  billion  and  could  create 
160000 jobs or reduce 160000 jobs depending on how tax revenues would be used. Option 3 
would reduce these costs by respectively 166 million in accounting (a), 55 million (option b) 
and 156 million (option c), see Table 9. Depending on how tax revenues changes are used the 
number of (net) jobs by around 800, 760 or by around 270 jobs respectively. The impacts are 
hence very small. 

40 

CEC  (2010)  Analysis  of  options  to  move  beyond  20%  greenhouse  emission  reductions  and  assessing 
the risk of carbon leakage, background information and analysis. Part II (COM (2010) 265) final. See 
page 46 and page 55 i.e. 

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6. 

COMPARING THE OPTIONS  

This section provides a comparison of the extent to which the different options answer to the 
problem definition and operational objectives. The impact assessment shows how accounting 
for  LULUCF  can  enhance  the  environmental  integrity,  policy  coherence  and  economic 
efficiency  of  the  EU's  GHG  emission  reduction  commitments,  as  defined  in  the  problem 
definition. 

6.1.1.  Choosing the right policy context 

The analysis shows that only two broad options would meet the overall objective set out by 
the  European  Council  and  Parliament  that  all  sectors  should  contribute  to  the  EU's  overall 
GHG reduction commitment; namely the inclusion of LULUCF in the EU's GHG reduction 
commitment  via  a  separate  framework  (Option  2)  or  though  the  ESD  (Option  3).  The 
environmental,  economic  and  social  impacts  of  the  options  differ  largely  depending  on  the 
accounting rules applied, as shown in Section 5. 

The  objective  to  limit  the  impact  of  the  high  inter-annual  variability  of  emissions  and 
removals  in  LULUCF  and  their  inherent  reversibility  on  compliance  poses  an  important 
challenge for the inclusion in the policy frameworks that currently regulate the EU's reduction 
targets. The ESD (Option 3) is based on annual compliance and requires MSs to decrease (or 
limit increases in) emissions according to a linear trajectory. This is a key feature to ensure 
that  the  targets  are  met  in  2020  and  to  limit  the  cumulative  emissions  in  the  commitment 
period. However, there is a significant compliance risk associated with applying this approach 
to LULUCF. Annual compliance would be difficult to apply where, over the period 1990 to 
2008,  many  MSs  experienced  variability  in  net  emission  between  two  adjacent  years  of 
around 20% (Sweden, Austria and Portugal), 40% (Finland), 50% (Latvia) or 60% (Estonia) 
compared  to  their  total  ESD  emissions  in  2008.  This  and  the  frequent  and  significant 
recalculations  of  reported  data  clearly  pose  a  challenge  for  annual  compliance  with  a  linear 
trajectory and would in many cases greatly exceed the flexibilities of the ESD. In addition, the 
long  lead-time  of  many  measures  in  LULUCF  means  that  annual  accounting  is  not  as 
meaningful as in other sectors, and a linear trajectory with required emission reductions each 
year will generally not be relevant. Option 2 (a separate framework) would be able to address 
these issues by averaging emissions and removals over the commitment period and therefore 
meet  the  objective  related  to  inter-annual  variability.  Another  issue  to  note  associated  with 
Option 3, particularly as long as the EU's emission reduction target remains at 20%, is that 
the inclusion of LULUCF would reduce the agreed efforts for the sectors that are already part 
of the existing commitments and so effectively reduce the EU's commitment. Option 2 would 
avoid this issue.Ensuring robust accounting. 

The objectives of accounting are to ensure an extensive coverage of emissions and removals, 
thereby  providing  a  level  playing  field  between  mitigation  options,  and  to  ensure  that  non-
permanence  is  reflected  in  accounting  and  to  prevent  large  natural  disturbances  from 
negatively affecting the compliance risk of MSs. Three options were considered to meet the 
objectives:  (a)  small  changes  to  the  rules  under  the  KP's  first  commitment  period,  (b)  rules 
which correspond to the expected outcome in the UNFCCC negotiations, and (c) rules which 
correspond  to  the  expected  outcome  of  the  UNFCCC  but  with  an  improved  scope  of  the 
emissions and removals accounted for. Table 14 provides a summary assessment of the extent 
to which the different accounting options meet the objectives. 

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Table 14. Performance of the different accounting options 

Objectives 

Extent to which the objectives are met by the different accounting options 

Accounting option (a) 

Accounting option (b) 

Accounting option (c) 

Small changes 

Likely outcome in the 
UNFCCC negotiations 

UNFCCC+ 

Provide  a  level  playing  field  between 
different mitigation options 

Ensure  extensive  coverage  of  emissions 
and removals 

Ensure  that  non-permanence  is  reflected 
in accounting 

Prevent  large  natural  disturbances  from 
negatively affecting the compliance risk of 
MSs 

X 

● 

X 

● 

● 

● 

● 

●● 

●● 

●● 

●● 

●● 

Notation key: x Objective not or insufficiently addressed by option, ● Objective partially addressed by option, ●● 
Objective sufficiently addressed by option 

As  regards  providing  a  level  playing  field  between  different  mitigation  options,  the  most 
important activity is forest management. This is treated differently in the different accounting 
options.  Table  5  shows  that  accounting  option  (a)  generates  substantial  credits,  about  80 
MtCO2 per year between 2013 and 2020. These are largely a "windfall" (free) as they include 
removals  that  would  have  occurred  without  any  change  in  management  activities.  Any 
mitigation  efforts  will  be  discounted  by  85%  and  this  will  make  mitigation  very  expensive 
and  so  limit  incentives  for  additional  mitigation  efforts.  It  would  also  allow  for  substantial 
decreases in net removals and increases in net emissions without any real economic impacts. 
Finally,  it  would  not  meet  the  objective  of  ensuring  that  non-permanence  is  reflected  in 
accounting  because  no  emissions  and  removals  related  to  agricultural  activities,  and  only  a 
fraction of those related to forest management, will be accounted.  

Accounting options (b) and (c) allow for a change in the sink due to natural saturation and 
existing  policies  without  generating  debits  or  credits.  They  do  so  to  factor  out  changes  in 
emissions  and  removals  that  are  not  human-induced.  However,  for  forest  management  they 
require full accounting for any deviations from the "reference level". In practice, this means 
that  in  the  reference  scenario  all  abatement  options  and  uses,  whether  sequestration  or 
additional  use  of  biomass  for  energy  production  (e.g.  for  reaching  the  RES-D  targets)  or 
material substitution, will face the same opportunity cost and this will ensure a level playing 
field between different mitigation options. In line with the agreement in Durban is the cap on 
credits from forest managment. An additional dimension to accounting for forest management 
is to put a quantitative limitation ("cap") on the emissions and removals accounted. The cap 
limits  the  undue  benefits  (credits)  related  to  the  uncertainty  associated  with  the  projections 
which underpin the "reference levels". Annex II describes the impact on accounting of the cap 
on credits of 3.5% agreed in Durban. 

In  terms  of  ensuring  extensive  coverage  of  emissions  and  removals  in  accounting  and  that 
non-permanence  is  reflected  in  accounting,  only  accounting  option  (c)  requires  MSs  to 
account  for  emissions  and  removals  in  both  agriculture  and  forestry  on  a  mandatory  basis 
whereas both accounting options (a) and (b) allow accounting for agriculture to be voluntary. 
Voluntary accounting may put the credibility of the EU's commitment at risk as the choice of 
which activity to account for can be perceived as opportunistic. A wider scope of accounting 

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52 

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would  increase  the  consistency  between  MSs  as  some  account  for  these  activities  under  the 
first commitment period of the KP and others not. It is important that all sectors in all MSs are 
recognised  as  contributing  to  reaching  the  targets  of  the  "Europe  2020"  strategy,  both  to 
secure  a  level  playing  field  for  business  and  MSs  and  a  fair  distribution  of  efforts,  and  to 
ensure  a  consistent  treatment  of  agriculture,  forestry  and  industry  within  the  EU's  internal 
market, i.e. to provide a level playing field. In the longer term, a more inclusive accounting 
would also be conducive to increasing the cost-efficiency in reaching any given overall target.  

As  regards  the  objective  of  reducing  the  impact  of  natural  disturbances  on  compliance  risk, 
accounting  options  (b)  and  (c)  would  include  provisions  for  accounting  for  large  natural 
disturbances and so limit the risk of non-compliance with GHG reduction targets if emissions 
occur as a result of large natural disturbances which are beyond the control of MSs. Annex II 
provides  more  details  on  the  effects  on  accounting  of  different  thresholds  for  excluding 
emissions from accounting. However, the application of the provisions is likely to be limited 
to a handful of MSs and to have only a small impact on accounting for the EU as a whole. If 
the emissions beyond 5% of the total emissions of a MS in 1990 were to be used the impact 
on  the  EU's  overall  accounting  would  be  negligible  whilst  at  the  same  time  provide  the 
necessary safeguards for those MSs most affected (in particular Portugal). 

6.1.2. 

Improving monitoring and reporting 

This impact assessment outlines a three-step approach to meet the objective of ensuring that 
monitoring  and  reporting  comply  with  IPCC  methodological  guidance.  A  first  step  would 
involve achieving complete reporting using at least simple methodologies. This first essential 
step could be taken rather swiftly. A second step would mean increasing the accuracy of the 
reported data using more sophisticated methods. Essential progress is expected during the first 
commitment period of the KP but efforts will have to continue also during the commitment 
period  2013-20.  Lastly,  further  improvements  of  the  comparability  between  MSs  can  be 
achieved by harmonising monitoring, reporting and related nomenclature. Although important 
steps towards harmonisation have already been taken and is part of compliance with the IPCC 
guidelines (steps 1 and 2), further efforts will be required over the next commitment period. 

The  above  steps  would  essentially  form  part  of  the  Commission's  proposal  for  a  revised 
Monitoring  Mechanism  Decision,  see  separate  proposal  and  impact  assessment,  but  are 
included  here  for  illustrational  purposes.  It  should  be  noted  also  that  MSs  are  generally 
obliged to take the first two steps as part of their commitments under the UNFCCC and the 
KP and the cost of introducing the requirements in EU legislation are therefore close to zero. 
This  said,  further  improvements  are  generally  needed  in  MSs  but  could  be  achieved  at  low 
costs.  Changes  in  the  scope  and  methods  of  accounting  would  however  generate  additional 
but  small  administrative  /  reporting  costs,  estimated  at  approximately  €0.4  million  to  €1.4 
million per year for the EU as a whole, with the more extensive accounting option (c) at the 
upper end of the interval. 

6.2. 

Concluding comments 

There  were  two  important  reasons  for  initially  leaving  LULUCF  out  of  the  EU's  climate 
change  commitments.  Firstly,  the  deficiencies  of  existing  accounting  rules  under  the  KP 
needed  to  be  addressed.  Secondly,  the  expectation  was  that  the  Copenhagen  world  climate 
summit  in  2009  would  deliver  an  international  agreement  on  climate  change,  including 
revised accounting rules for LULUCF which could then be adopted by the EU. This did not 
happen,  and  despite  the  progress  achieved  through  the  Copenhagen  Accord  and  the  Cancun 

EN 

53 

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Agreements there is still not an agreement in place. It is clear that the views of both developed 
and  developing  countries  are  converging  and  there  is  widespread  support  for  the  EU's 
favoured  options  on  the  key  remaining  issues.  But  LULUCF  is  only  one  part  of  wider  and 
very  complex  discussions.  As  a  result,  an  accounting  framework  for  LULUCF  risks  being 
further delayed. 

There  are  good  reasons  to  include  LULUCF  in  the  EU's  GHG  emission  reduction 
commitments  to  improve  the  policy  coherence,  environmental  integrity  and  economic 
efficiency of the EU's GHG emission reduction commitment. But the inclusion requires that 
the  special  features  of  LULUCF  and  circumstances  of  MSs  are  suitably  addressed.  It  is 
therefore important to ensure that robust accounting rules and monitoring and reporting are in 
place. 

In terms of accounting, accounting option (c) involves inclusive accounting of emissions and 
removals  from  both  forestry  and  agricultural  activities  and  gives  equal  weight  to  mitigation 
efforts  whether  undertaken  in  the  forestry,  agriculture,  industry  or  energy  sectors.  This  is 
conducive  to  cost-efficiency  and  will  ensure  a  level  playing  field  for  both  MSs  and  the 
different  sectors  of  the  EU's  internal  market.  It  will  also  provide  a  framework  in  which 
mitigation efforts by farmers and foresters and industry are incentivised, visible and correctly 
reflected. A wide coverage of emissions and removal will also ensure that potential reversals 
are reflected in accounting. 

Monitoring and reporting needs to be improved in support of the accounting framework and 
of  indicators  for  progress  in  agriculture  and  forestry.  The  Commission  proposes  to  achieve 
this through separate legislation, i.e. a revision of the Monitoring Mechanism  Decision. For 
reasons  of  both  comparability  and  cost-efficiency,  better  use  should  be  made  of  EU  wide 
monitoring instruments such as LUCAS and CORINE. 

Robust  accounting  and  monitoring  are  important  steps,  but  not  sufficient.  For  strong 
incentives  to  be  provided,  the  results  of  efforts  by  sectors  need  to  count  towards  the  EU's 
GHG emission reduction commitments. This will only be possible if the right policy context 
for LULUCF is established. The high variability of emissions and removals in forests means 
that  annual  emissions  reduction  targets  that  apply  to  other  sectors  are  unsuitable.  The  long 
lead  times  needed  for  mitigation  measures  to  take  effect  also  set  LULUCF  apart  from  most 
other sectors. The results of this impact assessment suggest that a separate framework would 
be best suited to address the special circumstances of LULUCF.  

However,  the  EU  has  already  committed  to  reducing  greenhouse  gas  emissions  by  20%  by 
2020  compared  to  1990  through  efforts  in  other  sectors  and  is  on  track  to  reach  that 
commitment without the contribution of LULUCF. Before the level of ambition is increased 
beyond 20% conditions need to be right. The sector should therefore be formally included in 
the target only once the EU decides to increase the level of ambition (Option 2.I). This does 
not  mean  that  mitigation  action  should  be  put  on  hold.  National  action  plans  could  be 
prepared  to  provide  a  strategy  and  outlook  for  LULUCF  as  well  as  an  intermediate  step 
towards the full inclusion of the sector and its integration with current policies. 

7. 

MONITORING AND EVALUATION  

Reporting  will  be  reviewed  and  monitoring  will  be  carried  out  as  part  of  the  existing 
requirements and arrangements under the UNFCCC and successor to the KP in terms of: 

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54 

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•  Completeness,  accuracy  and  consistency  of  monitoring  and  reporting  (in  line  with  the 

relevant IPCC methodological guidance), 

•  The correct application of accounting rules 

As  appropriate,  monitoring  and  evaluation  will  also  be  ensured  through  the  proposed 
amendments of the Monitoring Mechanism Decision (280/2004/EC) and related Commission 
Decision (2005/166/EC). 

8. 

ANNEXES 

8.1. 

Annex I – Monitoring, reporting and verification 

With  the  exception  of  Section  8.2.8,  this  Annex  has  been  authored  by  the  Joint 
Research Centre and is referred to in the main text as JRC (2011a). 

8.1.1. 

Introduction 

The following text presents an overview of the status of monitoring, reporting and verification 
of GHGs in LULUCF in the EU-27,41 By monitoring is meant activities that are carried out to 
estimate emissions and removals, by reporting the inclusion of information collected during 
the  monitoring  phase  in  the  national  annual  GHG  inventory42,  and  by  verification  the 
comparison  of  the  emissions/removals  estimates  reported  in  the  GHG  inventory  with 
estimates derived from independent assessments. The assessment focuses on four aspects of 
monitoring and reporting, namely completeness of land categories/activities and carbon pools 
reported,  accuracy  of  estimates,  consistency  of  estimates  over  time  and  comparability  of 
estimates among MSs. A brief discussion on existing verification activities is also provided. A 
more detailed compilation of data from the UNFCCC and KP reporting can be found in the 
annual  European  Union  greenhouse  gas  inventory  1990  –  2008  and  inventory  report  2010 
(http://www.eea.europa.eu/publications) 
tool 
and 
(http://afoludata.jrc.ec.europa.eu/index.php/models/detail/7). 

LULUCF 

JRC 

the 

in 

8.1.2.  Completeness 

8.1.2.1.  Convention reporting 

Reporting  under  the  convention  is  mandatory  for  the  land  categories  for  which  IPCC  GPG 
exists,  i.e.  forest  land,  cropland  and  grassland,  and  all  land  use  changes  (for  all  land 
categories).  According  to  IPCC  GPG-LULUCF,  emissions  and  removals  from  key 
categories43  should  be  estimated  with  higher-tiers  methods  (i.e.  tier  2  or  3)  44.  Table  A1.1 

41 

42 

43 

Based  on  the 2010  GHG  inventories  submitted  to  UNFCCC.  Note  that  Cyprus  and Malta  are  not  yet 
Annex-I  countries  and  thus  do  not  submit  GHG  inventories  to  UNFCCC.  The  information  collected 
here for these countries come from the GHG reporting under the EU monitoring mechanism. 
The GHG inventory includes the Common Reporting Format (CRF) tables, containing the estimates of 
emissions/removals,  and  the  National  Inventory  Report  (NIR),  containing  the  description  of  how  the 
estimates  were  obtained  along  with  other  information  (e.g.,  on  uncertainties,  QA/QC,  time-series 
consistency, recalculations, verification, etc.). 
The IPCC's GPG and Uncertainty Management in National Greenhouse Gas Inventories (IPCC GPG, 
2000) identifies a key category as “one that is prioritised within the national inventory system because 
its  estimate  has  a  significant  influence  on  a  country's  total  inventory  of  direct  GHGs  in  terms  of  the 

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gives  a  detailed  account  of  the  reporting  requirements  associated  with  land  use  categories, 
either with tier 1 or tier 2 methods. It should, however, be noted that Cyprus and Malta are not 
part of Annex I to the Convention and therefore not obliged to report in the same way. It is 
therefore relevant to discuss the 25 MSs that are obliged to report. 

Table  A1.2  shows  reported  emissions  (E)  and  removals  (R)  as  well  as  the  key  categories 
(shaded  cells)  for  the  three  main  UNFCCC  land  categories  (“wetlands”,  "settlements"  and 
"other" have been omitted). Reporting by the 25 MS obliged to report under the UNFCCC for 
the various land and sub categories shows complete coverage for forest remaining forest and 
nearly complete coverage (24 MS) for land converted to forest. Coverage is reasonably good 
also for cropland (22 MS reported cropland remaining cropland and 18 MS land converted to 
cropland)  and  grassland  (corresponding  numbers  are  18  and  22).  Whilst  the  coverage  of 
categories was significantly improved in 2008, especially for land use changes, likely due to 
the  first  reporting  under  the  KP,  there  are  still  some  gaps  in  the  reporting  of  mandatory 
categories.  

Table  A1.3  shows  reported  emissions  (E)  and  removals  (R)  by  carbon  pools45.  Note  that  in 
some  cases  the  assumption  of  no  C  stock  change  is  allowed  by  IPCC  46.  Reporting  for 
biomass is by far the most complete across land categories, in particular for forest land, and 
less so for soil and dead organic matter. However, for grasslands soils are more important and 
this is reflected in reporting. Most of the EU-12 reported less sub-categories and pools than 
the EU-15 MS. This difference is not only because of lack of national data, but also because 

absolute  level  of  emissions,  the  trend  in  emissions,  or  both”.  The  approaches  to  determine  key 
categories  in  LULUCF  are  described  in  Chapter  5.4  of  IPCC  GPG-LULUCF.  In  the  context  of  the 
Kyoto  Protocol,  each  activity  under  Articles  3.3  and  3.4  (if  elected)  is  a  category.  Furthermore,  it  is 
good practice to evaluate possible further disaggregation into subcategories (e.g. forest land converted 
to cropland) for purposes of choosing appropriate methods and prioritizing resources. In this regard, it is 
good practice to identify any subcategory as “key” if it accounts for 25-30% of the overall emissions or 
removals of the corresponding category.  
For each C pool, IPCC GPG-LULUCF provides methods according to 3 Tiers of increasing complexity 
and certainty in estimates.  
Under  the  Convention  reporting  the  C  pools  to  be  reported  are:  Living  Biomass  (above-  and  below-
ground), Dead Organic Matter (DOM, including litter and dead wood) and Soil (including mineral and 
organic soils). 
IPCC GPG-LULUCF assumes no change in C stocks for the following cases: (i) Tier 1 for DOM and 
mineral soils in FLrFL, for DOM in LcFL, and for Biomass in GLrGL; (ii) Tier 1 and 2 for DOM in 
CLrCL and GLrGL. See table A1.1 for more details. 

44 

45 

46 

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56 

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of  lack  of  resources  for  processing  the  existing  data  (e.g.  available  from  national  statistics) 
and to adapt and develop it according to the UNFCCC/IPCC reporting needs. 

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Table A1.1 Mandatory categories and carbon pools to be reported under the Convention, using tier 1 or tier 2 methods (tier 2 is mandatory if the category is “key category”) 

TIER 1 

LB 

DOM 

SOM 

AB

BB 

DW 

L 

mineral 

organic 

CO2 

liming 

N2O 

CH4 

LB 

DOM 

SOM 

fertilization 

conversion 

drainage 

fires 

fires 

AB

BB 

DW 

L 

mineral 

organic 

CO2 

liming 

fertilization 

conversion 

drainage 

fires 

fires 

N2O 

CH4 

1
R
E
T

I

2
R
E
T

I

EN 

Forest land

Cropland

Grassland 

Wetlands

Settlement

Other land 

FLrFL 

LcFL 

CLrCL 

LcCL 

GLrGL 

LcGL 

WLrWL 

LcWL 

SLrSL 

LcSL 

OLrOL 

LcOL 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y

Y 

Y 

Y 

Y 

Y 

Y 

Y

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 

Y 1

Y 

Y 

Y 

T 4 

4 

4 

4 

Y 1

Y 

Y 

Y 

4 

4 

4 

4 

Y 2

Y 2 

X 2 

X 2 

Y 

Y 

Y 

4 

Y 

4 

4 

4 

Y 

Y  

X 2 

X 2 

Y 

Y 

Y 

4 

Y 

4 

4 

4 

Y 2 

Y 2 

X 2 

X 2 

Y 

Y 

Y 

4 

Y 

4 

Y 5 

Y 5 

Y  

Y  

X 2 

X 2 

Y 

Y 

Y 

4 

Y 

4 

Y 5 

Y 5 

Y 

Y 

Y 

4 

4 

Y 5 

Y 5 

Y

Y 

Y 

Y 

Y 

4 

4 

Y 5 

Y 5 

58 

Y 2

Y 2 

Y

Y 

Y 2

Y 2 

Y 

Y 

Y

Y 

Y 

Y 

Y 2 

Y 2 

Y 3 

Y 

Y 

Y 

EN 

 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Living biomass (AB: Above ground biomass; BB: Below ground biomass) 

Soil organic matter 
Mandatory 
To be mandatorily reported only in the conversion year (from forest) 

Notation keys: 
FLrFL: forest land remain forest land; LcFL: land converted to forest land (and so on for the other categories) 
LB 
DOM  Dead organic matter (DW: Dead wood; L: Litter) 
SOM 
Y 
X 
blank  Non mandatory (or IPCC assumes no change in carbon stock) 
1 
2 
3 
4 
5 

Perennial woody crops, only 
To be reported as instantaneously oxidized in the year of conversion  
To be reported fully oxidized in conversion 
To be reported under the agriculture sector 
Savanna burning shall be reported under the agriculture sector  

EN 

59 

EN 

 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table  A1.2.  Completeness  of  reporting  in  each  MS  by  land  use  categories  (data  for  the  year  2008,  from  the  GHG 
inventory 2010). In each land use category, first column (e.g. F-F) identifies a land remaining in the same category, 
while second column (e.g. L-F) identifies a land converted to a new category. 

Reporting category 

Forest land 

Cropland 

Grassland 

5.A.1. 

FLrFL 

5.A.2. 

LcFL 

5.B.1. 

CLrCL 

5.B.2. 

LcCL 

5.C.1. 

GLrGL 

5.C.2. 

LcGL 

R 

R 

E 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

E 

E 

R 

R 

R 

E 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

E 

E 

E 

E 

R 

R 

R 

E 

R 

R 

E 

E 

E 

R 

E 

R 

E 

R 

E 

R 

E 

E 

E 

R 

E 

R 

R 

E 

E 

E 

E 

E 

E 

E 

E 

E 

E 

E 

E 

E 

R 

E 

E 

E 

E 

E 

R 

E 

R 

E  

R 

R 

E 

E 

E 

E 

E 

E 

E 

R 

R 

R 

R 

R 

E 

E 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

E 

Party 

Austria 

Belgium 

Denmark 

Finland 

France 

Germany 

Greece 

Ireland 

Italy 

Luxembourg 

Netherlands 

Portugal 

Spain 

Sweden 

UK 

Bulgaria  

Cyprus 

Czech Rep. 

Estonia 

Hungary 

Latvia 

Lithuania 

Malta 

Poland  

Romania 

Slovakia 

Slovenia  

Notation  key:  R=  Removals,  E  =  Emissions.  The  first  column  of  each  category  denotes  land  remaining  in  the  same  land 
category whereas the second column denotes land converted to that land category. Shaded area indicates that the category is a 
key category. Note that Cyprus and Malta do not have the same reporting obligations under the UNFCCC. 

EN 

60 

   EN 

 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Table A1.3. Completeness of reporting in each MS by pools for main land use categories (data for the year 2008, from the GHG inventory 2010). For transparency, the soil pool is separated into mineral 
and organic soil. 

FL-FL 

L-FL 

CL-CL 

L-CL 

GL-GL 

L-GL 

Forest land 

Cropland 

Grassland 

Biomass  DOM 

SOM 
Min 

SOM 
Org 

Biomass  DOM 

SOM 
Min 

SOM 
Org 

Biomass  DOM 

SOM 
Min 

SOM 
Org 

Biomass  DOM 

SOM 
Min 

SOM 
Org 

Biomass  DOM 

SOM 
Min 

SOM 
Org 

Biomass  DOM 

SOM 
Min 

SOM 
Org 

AT 

BE 

DK 

FI 

FR 

DE 

GR 

IE 

IT 

LU 

NL 

PT 

ES 

SE 

UK 

BG 

CY 

CZ 

EE 

HU 

LV 

LT 

MT 

PL 

RO 

SK 

SI 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

E 

E 

E 

R 

E 

R 

E 

E 

E 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

E 

ie 

R 

R 

R 

R 

R 

E 

R 

R 

R 

R 

R 

R 

R 

E 

R 

R 

R 

R 

E 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

E 

E 

E 

R 

E 

R 

E 

E 

R 

R 

ie 

R 

R 

R 

R 

E 

R 

R 

ie 

R 

R 

R 

R 

E 

E 

R 

R 

E 

R 

R 

R 

R 

R 

R 

E 

R 

R 

R 

R 

E 

E 

R 

R 

R 

R 

E 

R 

R 

R 

R 

E 

R 

E 

R 

R 

R 

R 

ie 

R 

E 

E 

ie 

R 

E 

R 

R 

R 

R 

R 

R 

E 

R 

E 

Ie 

R 

R 

R 

E 

E 

E 

E 

E 

ie 

E 

E 

E 

E 

R 

E 

E 

E 

E 

R 

E 

R 

R 

R 

R 

ie 

E 

E 

E 

E 

E 

R 

E 

R 

ie 

E 

E 

ie 

E 

E 

E 

ie 

E 

ie 

E 

E 

R 

R 

R 

E 

E 

E 

E 

ie 

E 

ie 

E 

E 

E 

E 

R 

E 

R 

R 

E 

E 

E 

E 

E 

E 

E 

E 

E 

E 

R 

E 

E 

R 

E 

R 

ie 

R 

R 

R 

ie 

E 

E 

E 

E 

E 

R 

R 

R 

E 

R 

E 

R 

E 

R 

E 

E 

E 

E 

E 

E 

E 

R 

E 

R 

R 

E 

E 

E 

E 

R 

E 

E 

E 

R 

R 

R 

E 

E 

E 

E 

E 

E 

ie 

E 

ie 

E 

E 

R 

E 

ie 

E 

E 

E 

E 

ie 

E 

ie 

R 

E 

E 

E 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R 

R, E - carbon pools changes result in either Removal or Emissions; "ie" means "included elsewhere"; empty cells show either "not estimated" (reported in CRF as "NE" alone or in combination with other keys), 
assumed as "no C stock change" (following IPCC tier 1), or assumed as "not occuring" (notation keys used "NO" and/or "NA") 

EN 

61 

EN 

 
  
 
 
  
  
  
  
 
  
  
  
 
  
  
  
  
  
 
  
  
  
  
 
  
  
  
  
 
 
 
  
 
  
  
  
  
 
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
 
  
  
  
  
  
  
  
  
 
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
 
  
  
  
  
  
  
  
  
  
 
  
  
  
  
 
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
 
  
  
  
  
  
 
  
 
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
 
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
 
  
  
  
  
  
  
  
 
  
  
  
 
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
 
  
  
  
  
  
  
  
  
  
  
  
 
  
  
  
  
 
  
  
  
  
  
  
 
  
  
  
 
  
  
  
8.1.2.2.  Kyoto Protocol reporting  

Table  A1.4  shows  activities  accounted  for  by  MSs  and  key  categories  for  the  EU-25. 
Reporting and accounting of LULUCF eligible activitites are mandatory for afforestation and 
reforestation  (AR)  and  deforestation  (D)  under  Art  3.3,  and  optional  for  forest  management 
(FM),  cropland  management  (CM),  grazing  land  management  (GM)  and  revegetation  (RV) 
under Art 3.4. Forest activities, in particular AR and FM, are key categories for most MSs. 

Table A1.4 Activities accounted for by MSs (white cells) and key categories (K) 

All MSs except one reported on all mandatory activities, and all but two reported on elected 
voluntary activities. In general, biomass carbon stock changes are directly estimated whereas 
the three other pools are frequently included elsewhere (IE) or not reported (NR). Under the 
KP,  a  country  must  always  provide  transparent  and  verifiable  information  that  any  non-
reported pool, for mandatory and elected activities, is not a source (in which case the notation 
key  NR  should  be  used).  Although  most  MSs  reported  most  of  the  carbon  pools,  the 
completeness of reporting will need to improve in subsequent inventories.  

The supplementary reporting required under the KP as compared to the Convention reporting 
was submitted for the first time in 2010 (for the first year of the commitment period 2008-12) 
and, inevitably, certain areas were problematic the first time around. The expert reviews show 
that the key difficulties appear to be to provide information which demonstrates that:  

•  units  of  lands  are  identifiable  (i.e.  that  relevant  units  of  land  or  lands  are  precisely 

identified and can be traced in the future) 

•  non-reported pools (SOM, DOM) are not sources  

•  afforestation/reforestation activities are of a direct, human-induced nature 

See Appendix 1 to this Annex and the Annual European Union GHG inventory 1990 – 2008 
and inventory report 2010 (Technical report No 6/2010) for more information.  

EN 

62 

   EN 

 
 
Table A1.5. Completeness on reporting pools on KP forest activities 

Aff/Reforestation            Deforestation                   Forest management
Change in C pool reported
Change in C pool reported

Change in C pool reported

d
n
u
o
r
g
-
e
v
o
b
A

R

R

d
n
u
o
r
g
-
w
o
e
B

l

s
s
a
m
o
b

i

s
s
a
m
o
b

i

d
o
o
w
d
a
e
D

r
e
t
t
i
L

l
i

o
S

R

R

IE

R

NO

NR

R

R

d
n
u
o
r
g
-
e
v
o
b
A

d
n
u
o
r
g
-
w
o
e
B

l

s
s
a
m
o
b

i

s
s
a
m
o
b

i

R

R

R

R

d
o
o
w
d
a
e
D

IE

R

r
e
t
t
i
L

IE

R

l
i

o
S

R

R

d
n
u
o
r
g
-
e
v
o
b
A

d
n
u
o
r
g
-
w
o
e
B

l

s
s
a
m
o
b

i

s
s
a
m
o
b

i

d
o
o
w
d
a
e
D

r
e
t
t
i
L

l
i

o
S

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

R,R

R,R R,IE R,R R,NR

R,NO R,NO R,NO R,NO R,NO

R,R

R,R R,IE

R,R R,NR

R

R

R

R

R

R

R

R

R

R

R

R

IE

R

R

R

R

R

IE

R

R

R

R

IE

IE

R

R

IE

R

NO

R

R

R

NR NR NR

R

R

IE

R

R

NO

R

R

R

NR NR NR

NE NE

NE

NR NR NR

R

R

R

IE

R

R

R

R

R

R

R

R

R

R

R

R

R

R

IE

R

R

R

R

R

IE

R

R

IE

R

IE

IE

R

R

IE

R

R

R

R

R

NR

NR

NR

R

R

IE

R

NE

NR

R

IE

R

R

R

R

NE

NR

R

IE

R

R

R

NR

NE

NR

R

R

R

R

R

R

NA

R

NA

NA

R

R

R

R

IE

R

R

R

NA

R

NA

NA

R

IE

R

IE

IE

R

NO

NR

NA

R

NA

NA

NR

NR

R

R

IE

R

R

NR

NA

R

NA

NA

NR

NR

R

IE

R

R

R

NR

NA

R

NA

NA

NR

NR

R

R

Change in C pool reported

Change in C pool reported

Change in C pool reported

d
n
u

ve-gro

o
b
A
R

R

R

R

R

0

R

R

R

ass
m
io
b

d
n
u

-gro
w
elo
B
IE

R

R

R

R

0

R

IE

IE

ass
m
io
b

Litter

d
o
o
 w
ead
D

il
So

IE

IE

IE

NO

R

NO

R

R

R

NR NR NR

R

0

R

R

R

0

R

IE

NR NR

R

0

R

NR

R

NO

NO

NO NO NO

d
n
u

ve-gro

o
b
A
R

R

R

R

R

0

R

R

R

R

ass
m
io
b

d
n
u

-gro
w
elo
B
IE

R

R

R

R

0

R

R

IE

R

ass
m
io
b

Litter

d
o
o
 w
ead
D

il
So

IE

IE

IE

R

R

IE

NR

NR

R

0

IE

R

NR

NR

R

0

R

IE

NR

R

R

R

R

R

R

0

R

R

R

R

d
n
u

ve-gro

o
b
A
NA

R

NA

R

R

0

R

R

ass
m
io
b

d
n
u

-gro
w
elo
B
NA

R

NA

R

R

0

R

R

NA

R

NA

R

ass
m
io
b

Litter

d
o
o
 w
ead
D

il
So

NA

NR

NA

NR

R

0

R

NR

NA

NR

NA

R

NA

NR

R

0

R

NR

NA

R

NA

NR

NA

NR

R

0

R

R

NA

NR

Austria

Belgium

Denmark

Finland

France

Germany

Greece

Ireland

Italy

Luxemburg

Netherlands

Portugal

Spain

Sweden

United Kingdom

Bulgaria 

Czech Republic 

Estonia 

Hungary 

Latvia 

Lithuania 

Poland 

Romania 

Slovakia 

Slovenia 

R (reported), NR (not reported), IE (included elsewhere)  , NO (not occurring), NA (not applicable)

8.1.2.3.  Concluding comments  

The tables above suggest that: 

•  for  the  coverage  of  land  categories  reported  under  the  UNFCCC:  despite  significant 
improvements in recent years, further efforts are required from some MS (especially from 
the  EU-12)  to  report  GHG  emissions  from  all  the  “mandatory”  categories  under  the 
Convention  (i.e.  forest  land,  cropland,  grassland  and  all  land  use  changes;  the  other 
categories are considered “voluntary” under the Convention). One particular aspect where 

EN 

63 

   EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
further improvements are needed is that areas of all land use categories should be reported, 
and the sum should be constant over time and match the total area of the country. 

•  for  the  coverage  of  activities  under  KP:  all  MSs  except  one  (Lithuania)  reported  the 
mandatory  activities  (AR,  D);  however, other two countries  (Portugal and Spain) did not 
report  data  for  1990  for  elected  activities.  Given  the  stringent  mandatory  nature  of  KP 
reporting, it is expected that these gaps will be filled in the next 1 or 2 years. 

•  for the coverage of C pools: under both the UNFCCC and  the KP, the  assumption of no 
change in C stock can only be used in specific cases47. Furthermore, beyond these specific 
cases, under the KP a country may omit the accounting of a pool (for a mandatory or any 
elected activity) provided that transparent and verifiable information is given showing that 
the pool is not a source (in this case, the notation key “NR”, not reported, should be used). 
As a matter of fact, many MSs apply the assumption of no change in C stock even when it 
should not be applied, e.g. if forest land remaining forest land (or forest management under 
the KP) is a “key category”, the tier 1 method (assuming no change in C stock) cannot be 
used for DOM and mineral soil. Under the KP, this approach represents a problem if it is 
not  accompanied  by  transparent  and  verifiable  information  which  shows  that  the  pool  is 
not a source. In the first year of reporting under the KP, the UNFCCC reviews raised this 
problem for several MS (see later sections). 

8.1.3.  Accuracy 

Accuracy is defined by the IPCC GPG as “a relative measure of the exactness of an emission 
or  removal  estimate.  Estimates  should  be  accurate  in  the  sense  that  they  are  systematically 
neither  over  nor  under  true  emissions  or  removals,  so  far  as  can  be  judged,  and  that 
uncertainties  are  reduced  so  far  as  is  practicable.  Appropriate  methodologies  conforming  to 
guidance on good practices should be used to promote accuracy in inventories.”48 In this sense 
estimates  should  be  accurate  so  long  as  GPG  is  followed.  However  the  degree  of  accuracy 
may differ according to the approaches and methodologies applied. 

GHG  emissions/removals  on  land  are  estimated  as  AD  x  EF,  where  AD  is  activity  data 
(“area” in LULUCF), and EF is emission factor (derived either as C stock change).  

IPCC  (2003)  recommends  three  approaches  for  consistent  land  representation  as  basis  for 
activity data estimation at national level: 

APPROACH  1:  BASIC  LAND-USE  DATA:  area  datasets  likely  to  have  been  prepared  for  other  purposes  such  as  forestry  or 
agricultural  statistics.  Frequently,  several  datasets  will  be  combined  to  cover  all  land  classifications  and  regions  of  a  country. 
There is no information on land use changes. 

APPROACH 2: SURVEY OF LAND USE AND LAND-USE CHANGE consists in a national or regional-scale assessment of not 
only the losses or gains in the area of specific land categories but what these changes represent (i.e., changes from and to a 
category). Thus, it includes more information on changes between categories. Tracking land-use changes in this explicit manner 
will normally require estimation of initial and final land-use categories.  

APPROACH 3: GEOGRAPHICALLY EXPLICIT LAND USE DATA requires spatially explicit observations of land use and land-
use  change.  The  data  may  be  obtained  either  by  sampling  of  geographically  located  points,  a  complete  tally  (wall-to-wall 
mapping) or a combination of the two. 

47 

48 

IPCC GPG-LULUCF assumes no change in C stocks for the following cases: (i) Tier 1 for DOM and 
mineral soils in FLrFL, for DOM in LcFL, and for Biomass in GLrGL; (ii) Tier 1 and 2 for DOM in 
CLrCL and GLrGL. See table A1.1 for more details. 
IPCC GPG for LULUCF, Annex A: Glossary, p. G.2. 

EN 

64 

   EN 

 
                                                 
The quality of GHG estimates is reflected by the methodological tiers used. IPCC LULUCF 
GPG 2003 introduces three methodological tiers: 

The Tier 1 approach employs the basic method provided in the IPCC Guidelines (Workbook) and the default emission factors 
provided in the IPCC Guidelines (Workbook and Reference Manual) with updates in this chapter of the report. For some land 
uses and pools that were only mentioned in the IPCC Guidelines (i.e., the default was an assumed zero emissions or removals), 
updates are included in this report if new scientific information is available. Tier 1 methodologies usually use activity data that 
are  spatially  coarse,  such  as  nationally  or  globally  available  estimates  of  deforestation  rates,  agricultural  production  statistics, 
and global land cover maps.  

Tier 2 can use the same methodological approach as Tier 1 but applies emission factors and activity data which are defined by 
the  country  for  the  most  important  land  uses/activities.  Tier  2  can  also  apply  stock  change  methodologies  based  on  country-
specific data. Country-defined emission factors/activity data are more appropriate for the climatic regions and land use systems 
in  that  country.  Higher  resolution  activity  data  are  typically  used  in  Tier  2  to  correspond  with  country-defined  coefficients  for 
specific regions and specialised land-use categories. 

At  Tier  3,  higher  order  methods  are  used  including  models  and  inventory  measurement  systems  tailored  to  address  national 
circumstances,  repeated  over  time,  and  driven  by  high-resolution  activity  data  and  disaggregated  at  sub-national  to  fine  grid 
scales.  These  higher  order  methods  provide  estimates  of  greater  certainty  than  lower  tiers  and  have  a  closer  link  between 
biomass  and  soil  dynamics.  Such  systems  may  be  GIS-based  combinations  of  age,  class/production  data  systems  with 
connections  to  soil  modules,  integrating  several  types  of  monitoring.  Pieces  of  land  where  a  land-use  change  occurs  can  be 
tracked  over  time.  In  most  cases  these  systems  have  a  climate  dependency,  and  thus  provide  source  estimates  with  inter-
annual variability. Models should undergo quality checks, audits, and validations. 

Behind the approaches and tiers there are various datasets and methods, used separately or in 
combination, to meet the GPG requirements for estimation and reporting of GHG. Estimates 
from country-specific data and methods (if calculated in accordance with GPG) are likely to 
be more accurate than if they were prepared using default methods and aggregated data sets. 

8.1.3.1.  Underlying methods used to estimate activity data 

Given  the  heterogeneity  of  ecological  and  socio-economic  conditions  in  the  EU-27,  and  for 
historical reasons, there is no unique definition of different land uses across MSs. For the EU-
15  the  activity  data  is  estimated  using  approaches  2  or  3  (national  forest  inventories  (NFI), 
earth  observation  methods  (EO)  and  land  surveys  (LS))  while  some  EU-12  MS  still  use 
approach 1 (national statistics (NS)), see Table A1.6. Nevertheless, data is provided through 
various official sources and may be underpinned by several methods. 

Table A1.6. Data sources for activity data in National Inventory Reports (NIR) 2010 

MS 

Austria 

Belgium 

Denmark 

Finland 

France 

Germany 

NFI 

Reporting categories 

5A Forest land 

5B Cropland  

5C Grassland 

5.A.1 

5.A.2 

NFI 

EO 

NFI 

EO 

Distur-
bances 
NS 

5.B.1 

5.B.2 

5.C.1 

5.C.2 

NS 

NS 

NS 

NS 

EO, NS 

EO, NS 

NS, NFI 

NS,NFI 

NFI 

NFI, LS 

NFI 

NFI 

NFI 

NS 

NFI, NS 

NFI, NS 

EO 

NS 

NS, NM, 
EO 
NS 

EO 

NFI, NM 

NFI, NM 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NFI, EO 

EO, NS 

NS 

NS, EO 

NFI, NS 

NFI, LS 

NS, NM, 
EO 

NS 

NS 

NS 

EO 

NM 

EO 

NFI, 
LS 
NS, 
NM, 
EO 

NM 

NS 

EO 

NM 

EO 

NFI, 
LS 
NS, 
NM, 
EO 

NM, 
EO 
NS 

EO 

NM 

EO 

NS, EO 

NS 

NFI, LS 

NS, NM, 
EO 

NS 

NS 

NS 

EO 

NM 

EO 

65 

Greece 

Ireland 

Italy 

Luxembourg 

The 
Netherlands 
Portugal 

EN 

Other LU 
categories 

NS 

NS 

NS, EO 

NFI, NS 

NFI, LS 

NS, NM, EO 

NS 

NS, EO 

NS, EO 

EO 

NM 

EO 

   EN 

 
 
 
 
 
 
 
 
 
 
 
 
Spain 

Sweden 

United 
Kingdom 
Bulgaria 

Czech 
Republic 
Estonia 

Hungary 

Latvia 

Lithuania 

Poland 

Romania 

Slovakia 

Slovenia 

NFI, EO, 
NM 
NFI 

NS 

NS 

NS 

NS 

NS 

NS 

NFI 

NS 

NS 

NS 

NS 

NS 

NFI, EO 

NFI, EO 

NS, NFI 

NS, NFI 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NFI 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

EO, NS 

EO 

NFI 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

EO 

NFI 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

EO, NS 

EO 

NFI 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

EO, 
NS 

EO 

NFI 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

EO, NS 

NFI 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

NS 

EO, 
NS 

EO, NS 

EO, NS 

EO, NS 

Notation  keys:  NFI  –  National  Forest  Inventory;  NS  –  National  Statistics  (agricultural  and  forest  statistics,  management 
plans,  cadastral data);  EO  –  Earth  Observation methods  (i.e.  Corine  Land  Cover);  LS  –Land  Survey (i.e.  permanent  grid); 
NM – National Maps; and Empty cells –No information reported/no reported pool. 

Land area 

Underlying methods used to determine the “activity data” (i.e. land area) could be grouped 
according their characteristics, as follows: 

•  National  statistics:  for  forest  land  data  is  provided  by  ground  measurement  of  area  via 
stand-wise management plans of forests, updated cyclically. Specifically data refers only to 
a  certain  type  of  land  class  (i.e.  usually  forest  and  from/to  conversions)  and  thus  do  not 
fully  cover  the  country  territory.  Data  is  then  aggregated  bottom  up,  but  could  be 
heterogeneous in accuracy. National statistics provide data of areas at the end of year, thus 
additional information on conversions must be derived from underlying sectoral statistics 
with  additional  effort,  e.g.  the  forest  or  land  census.  Data  is  presented  in  tabular  form, 
under various possible aggregations. For cropland and grassland national statistics refers 
to datasets that are collected via census or surveys on farms/land owners/administrators or 
public authorities, based on questionnaires. In general, the method implies partial sampling 
every  year  and  a  complete  survey  every  5-10  years.  Data  could  be  only  presented  as 
registry or tabular, under various aggregations. Under cropland it covers the information on 
land use and crops type, management approaches. 

•  Systematic  grids:  data  is  provided  by  complex  mathematic-statistical  procedure  derived 
from  geo-referenced  systematic  grids  (i.e.  NFI,  Land  surveys)  that  cover  entire/partial 
territory  of  the  country.  The  method  offers  the  possibility  to  recalculate  previous  cycles 
with improved approaches or tools for example geo-referenced virtual grids (without field 
sampling points). The grid design differs from country to country, as well as the number of 
cycles  achieved.  Data  are  presented  in  tabular  form  with  the  option  of  mapping  by 
additional effort. 

•  Earth Observation: data are provided by mapping of land cover or changes with successive 
images (satellite, aerial). The resolution is different through time, with 1990 or earlier less 
accurate.  Data  is  mapped,  with  the  option  to  develop  tables  and  interoperate  with  other 
instruments. 

•  Cadastral  systems:  “wall-to-wall”  databases  with  ground  measurement  of  the  land  area. 
Additional  methods  are  used  for  land  classification  (remote  sensing,  field  checks).  Data 

EN 

66 

   EN 

 
 
covers  all  type  of  land  categories  within  the  national  territory.  Measurements  methods 
implement  homogenous  accuracy  standards.  Data  is  both  mapped  and  in  tabular  format, 
possible to enhance by use of other instruments. 

Methods are combined in different ways from one MS to another for each land sub-category, 
see Table A1.7, however, approach 2 and 3 are most prevalent. 

Table A1.7. Methods used to determine the “activity data” for forestland (FL), cropland (CL) and grassland (GL) and 
category and their characteristics (N= no. of MS reporting under respective method) 

Main 
datasets/source 

Land 
definition 

Land 
identi-
fication 

Land 
classi-
fication 
risk 

Land 
conversion 
detection 

Land 
traceability 

Timing of 
data 
collection 

Coverage 
of land 
category 

Uncer-
tainty 

Main characteristics of the method 

National 
statistics 
(NFL=5) 
(NCL,GL=8) 

Systematic grids 
(NFL=11) 
(NCL,GL=6) 

Earth 
Observation 
(NFL=5) 
(NCL,GL=6) 

Cadastral 
systems  
(NFL=4) 
(NCL,GL=5) 

LU 

Non 
explicit 

High 

Low 

Non 
traceable 

Annual/ 
Periodic 

Partial/ 
Total 

Low 

LC/LU 

Explicit 

Low 

High 

Traceable 

Periodic 

Total 

Low-
Medium 

LC 

Explicit 

High 

High 

Traceable 

Periodic 
/Annual 

Total 

Medium-
High 

LC/LU 

Explicit 

Low 

High 

Traceable 

Annual 

Total 

Low 

Soil type distribution 

The activity data (area) of each subcategory requires to be further disaggregated by main soil 
types  (e.g.  mineral  vs.  organic  soils).  The  available  information  on  the  methods  used  to 
determine the area of mineral and organic soils suggest the following distinction: 

•  Associations  of  soil  characteristics  with  land  cover  or  administrative  units  (regions, 
provinces,  national)  -  expert  judgement  association  of  land  cover  with  certain  soil  type 
(especially  used  for  organic  soils)  or  link  to  the  soil  databases  with  regional  or  national 
administrative  boundary  (in  order  to  derive  unique  values  of  reference  C  stocks  at  such 
level for each land categories). Data are presented in a tabular format. 

•  Soil  maps  -  digital  or  digitized  maps  of  soils  at  various  scales  and  mapping  precisions. 
They may be very old (now digitized) and time change of soil classification systems may 
affect their accuracy. Data could be presented on various  aggregation of soils (i.e. types, 
subtypes) and mapping scales at certain moment in time (they could be very old). Data is 
presented in map format and optionally in tabular format. 

•  Systematic  grids  -  data  are  collected  via  a  systematic  grid  or  networks  of  permanent  or 
temporary  geo-referenced  sampling  points,  with  repetitive  sampling.  The  grid  may  cover 
total or partial territory of the country (e.g. NFIs) and sampling points serve for other data 
collection  too.  Data  could  be  presented  on  type  and  subtype  of  soils  in  tabular  formats, 
with optional mapping (i.e. GIS). 

EN 

67 

   EN 

 
 
MSs more frequently apply approach 2 or 3, but several MS do not determine activity data for 
different soil types at all. 

Table  A1.8.  Synthesis  of  the  datasets/methods  used  to  determine  the  “activity  data”  for  SOILS  and  their 
characteristics  (N=  no.  of  MS  reporting  under  respective  method).  To  note  that  not  reporting  MS,  i.e.  assuming  no 
change in SOM pools (N= 8) 

Main source/datasets  

Association with the land use/ 
cover/administrative data  
(NFL= 6) 

Soil maps  
(NFL= 8) 

Systematic grids  
(NFL= 3) 

Soils definition 

Soil type 
mapping 

Traceability of 
sampling 

Interopera-
bility 

Uncertainty 

Main characteristics 

Low 

Low 

Low 

Low 

High 

High 

High 

Low 

High 

Low/Medium 

High 

High 

High 

High 

Low/Medium 

Determination of "activity data" for disturbance on forest land 

Major  forest  disturbances  in  the  EU-27  are  forest  fires  and  windstorms,  with  characteristic 
random  occurrence  in  time  and  space.  Adequate  information  on  the  methods  used  to  detect 
disturbances is not always transparently and explicitly reported in National Inventory reports 
(NIRs);  often  the  CO2  loss  from  these  events  is  included  in  the  annual  biomass  loss  and 
therefore is not quantified separately. Nevertheless, accurate reporting of the underlying data 
(i.e. area) is an essential requirement for KP reporting. 

Table  A1.9.  Synthesis  of  the  datasets/methods  used  to  determine  the  “activity  data”  for  disturbance  and  their 
characteristics (N= no. of MS reporting under respective method) 

Datasets 

Data not estimated  

(NFL=3) 

Sectoral statistics  

(NFL=19) 

National Forest Inventory  

(NFL=3) 

Comments on methods 

Data not available or reported as “NO” 

Either affected area or volume is usually (rarely both) measured or 
estimated by ground measurement or visual assessment and made 
available in sectoral (not national) statistics 

Area affected by disturbances is either directly derived by mathematic-
statistical procedure in geo-referenced grids, often with the help of 
remote sensing datasets 

8.1.4.  Underlying methods used to estimate emission factors 

Methods used by MSs to estimate emissions and removals in the categories 5A, 5B and 5C in 
biomass,  soil  and  dead  organic  matter  pools  vary  from  default  (Tier  1)  to  country  specific 
(Tiers 2 and 3). 

Common  Reporting  Format  (CRF)  tables  in  GHG  inventories  include  a  summary  with 
methods  and  factors  used.  However,  the  aggregation  of  this  information  (only  by  land  use 
category  and  gas)  is  not  appropriate  for  a  detailed  analysis  involving  specific  C  pools. 
Therefore,  the  detailed  table  A1.10  below  has  been  elaborated  by  JRC  taking  into  account 
more specific information provided by each MS in its 2010 National Inventory Report (NIR). 
“NE” is this tables indicates a reporting which is not complete according to the IPCC methods 
and to the key category analysis done by the MS. Note that it is often difficult to assign the 
method  used  for  a  pool  to  a  specific  tier,  and  this  table  is  subject  of  change  upon 
improvements in time.  

EN 

68 

   EN 

 
 
 
Table A1.10. Analysis of methods and data used for reporting C pools (based on NIR 2010 and CRF tables 2011 for the year 2009). Analysis carried out by JRC, March 2011.  

Forest land 

Cropland 

Grassland 

FLrFL 

LcFL 

CLrCL 

LcCL 

GLrGL 

LcGL 

Biomass 

DOM 
(1) 

SOM 
Min 

SOM 
Org
(2) 

Biomass  DOM 

SOM 
Min 

SOM 
Org
(2) 

Biomass  DOM 

SOM 
Min 
(3) 

SOM 
Org
(2) 

Biomass  
(4) 

DOM 

SOM 
Min 

SOM 
Org
(2) 

Biomass  DOM 

AT 

BE 

DK 

FI 

FR 

DE 

GR 

IE 

IT 

LU 

NL 

PT 

ES 

SE 

UK 

BG 

CY 

CZ 

EE 

HU 

LV 

LT 

MT 

PL 

RO 

SK 

SI 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS,D 

CS,D 

CS,D 

CS 

CS,D 

CS,D 

D 

CS,D 

D,CS 

D 

CS 

CS 

D 

CS 

CS 

D 

D 

D 

CS,D 

D 

D 

CS 

D 

D 

D 

D 

CS 

D 

CS 

D 

CS 

D 

D 

D 

D 

CS 

D 

D 

CS 

D 

CS 

CS 

D 

D 

D 

D 

D 

D 

CS 

D 

CS 

D 

D 

D 

NO 

NO 

CS 

CS 

NO 

CS 

NO 

CS 

NO 

NO 

NE 

NO 

NO 

CS 

CS 

NO 

NE 

NO 

CS,D 

NO 

CS 

CS 

NE 

NE 

NE 

NO 

NO 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

NE 

CS 

CS 

CS 

CS 

CS 

NO 

CS 

NE 

CS 

CS 

CS 

D 

CS 

CS 

CS 

CS 

D 

CS 

CS 

D 

D 

CS 

D 

CS 

CS 

D 

D 

D 

CS 

D 

D 

D 

NO 

CS 

D 

D 

CS 

CS 

CS 

CS 

CS 

CS 

CS 

D 

CS 

CS 

CS 

NE 

CS 

CS 

CS 

CS 

CS 

NE 

CS 

NE 

D 

NE 

NE 

NO 

CS 

NE 

CS 

CS 

NO 

NO 

CS 

CS 

NO 

CS 

NO 

CS 

NO 

NO 

NE 

NO 

NO 

CS 

CS 

NO 

NO 

NO 

CS,D 

NO 

CS 

NE 

NO 

NE 

NE 

NO 

NO 

D 

NE 

CS 

CS 

CS 

D 

CS 

NO 

CS 

CS 

NE 

CS 

CS 

CS 

CS 

CS 

NE 

CS 

NE 

CS 

D 

NE 

CS 

CS 

NE 

CS 

CS 

D 

D 

D 

D 

D 

D 

D 

D 

CS 

D 

D 

CS 

D 

CS 

D 

CS 

D 

D 

D 

D 

D 

D 

D 

CS 

D 

D 

D 

CS,CS 

CS 

CS 

CS,D 

NE 

CS 

D,D 

CS,D 

CS 

NE 

NE 

CS 

CS 

CS 

CS 

CS 

NE 

CS,D 

NE 

D,D 

NE 

NE 

NE 

CS 

NE 

NE 

CS 

NO 

NO 

CS 

CS 

NO 

CS 

CS 

NO 

CS 

NO 

CS 

NO 

NO 

CS 

CS 

NO 

NO 

NO 

CS,CS 

CS,NO 

CS,CS 

CS,NE 

CS,NE 

CS,CS 

CS,NE 

NO,NE 

NO,NO 

CS 

CS,NE 

CS,CS 

NO,NO 

CS,CS 

CS,CS 

CS,D 

NE 

CS, D 

CS,D  NO,NO 

NO 

CS 

NE 

NO 

CS 

NE 

NO 

CS 

CS,D 

CS,NO 

NE,NE 

NE 

NE,NO 

NE,NE 

CS,D 

CS,D 

CS 

NE 

CS 

CS 

CS 

CS 

NE 

NO 

NO 

CS 

CS 

CS 

NO 

CS 

CS 

NE 

NE 

CS 

NO 

CS 

CS 

NE 

NE 

NE 

NE 

CS 

NE 

CS 

CS 

CS 

CS 

CS 

CS 

NE 

CS 

NO 

CS 

NE 

CS 

NO 

CS 

CS 

CS 

NE 

CS 

NO 

NO 

CS 

CS 

NO 

CS 

NO 

NO 

NO 

NO 

NE 

NO 

NO 

CS 

CS 

NO 

NO 

NO 

D 

D 

CS 

D 

D 

CS 

D 

D 

CS 

D 

D 

D 

D 

D 

D 

D 

D 

D 

CS 

D 

D 

D 

D 

D 

D 

CS 

CS 

D 

D 

D 

D 

D 

D 

D 

D 

NO 

CS,D 

CS,D 

CS 

D 

NE 

NE 

NE 

NE 

NE 

CS 

CS 

NO 

CS 

NE 

NO 

NE 

NE 

NO 

NO 

D 

D 

D 

D 

D 

D 

D 

D 

D 

D 

D 

D 

CS 

D 

D 

D 

SOM 
Min 
(3) 

SOM 
Org
(2) 

CS,CS 

CS 

CS 

CS,D 

NE 

NE 

NO 

NE 

CS 

NO 

CS 

CS 

NO 

CS 

NO 

CS,D 

NO 

NO 

CS 

NO 

NO 

CS 

NO 

NO 

NO 

NO 

CS,D 

NO 

CS 

NE 

NO 

CS 

NE 

NO 

CS 

NE 

NE 

NE 

NE 

CS 

NE 

NE 

NE 

CS,D 

NE 

D,D 

NE 

NE 

NE 

NE 

NE 

NE 

NE 

Biomass  DOM  

SOM 
Min 

SOM 
Org 
(2) 

CS 

CS 

CS 

CS 

CS 

CS 

NE 

CS 

CS 

CS 

CS 

CS 

NE 

CS 

CS 

CS 

NE 

CS 

CS 

CS 

NE 

NE 

NO 

NE 

NE 

CS 

CS 

CS 

NE 

CS 

CS 

CS 

CS 

NE 

NE 

NE 

CS 

CS 

CS 

NE 

CS 

CS 

NE 

NE 

CS 

NE 

CS 

NE 

NE 

NE 

CS 

NE 

CS 

NE 

CS 

CS 

CS 

CS 

CS 

CS 

NE 

CS 

CS 

CS 

NE 

CS 

CS 

CS 

CS 

CS 

NE 

CS 

NE 

D 

NE 

NE 

NE 

NE 

NE 

CS 

CS 

NO 

NO 

CS 

CS 

NO 

CS 

NO 

CS 

NO 

NO 

NE 

NO 

NO 

CS 

CS 

NO 

NO 

NO 

CS,D 

NO 

CS 

NE 

NO 

NE 

NE 

NO 

NO 

CS 

CS,D 

Notation key: DOM: dead organic matter; SOM: soil; Min = mineral; Org: organic; "CS" country specific data, associated either with IPCC method (tier 2) or country-specific method (tier 3, if data are 
highly  disaggregated).  Note  that sometimes not  all  parameters involved  in  the  estimation are  truly  "CS"  (e.g.  root/shoot  ratio and  BEF  are  often  taken  by  IPCC). However  it  is  expected  that if  "CS"  is 

EN 

69 

EN 

 
  
 
 
  
reported,  the  most  important  parameters  are  truly  "CS".  "D"  means  that  the  default  IPCC  emission  factors  are  used  in  the  estimation.  D  is  tipically  associated  with  IPCC  default  method  (tier  1).  If  the 
heading  is  in  grey,  D  means  that  NO  change in C  stock is  assumed.  "NE"  means  either  country assumes  the emission/removal  is  negligible  or  not enough  data  is available  for  estimation.  "NO"  means 
emissions or removals "not occuring" in a country (it includes also "NA" - not applicable).  

Black heading means that for these pools the IPCC allows the assumption of no change in C stock under tier 1 (note that if the category is a key categroy, in theory higher tiers should be used). For DOM in 
CL and GL, the assumption of no C stock change is also valid under tier 2. 

Grey cells denote key categories according to either level or trend analysis done by the country (FR, DK, LT did not yet perform a key category analysis, as of March 2011). In general, key categories 
should be reported using higher tiers. However note that, when reviewers assess the adequacy of the methodological choice (tiers) in relation to key categories, should also consider "national circumstances" 
(i.e. the availability of data/resources/capacity in the country). This means that in some cases tier 1 may be also accepted for key categories. 

Notes: (1) for DOM under "FLrFL" the 2 notations separated by a comma mean: first one refers to DW (dead wood), second to LT (litter); (2) for organic soil "NE" is used if the country reports some area 
of organic soil but no emissions are associated to it; (3) for mineral soil on CL and GL the 2 notation keys separated by comma mean that the country uses IPCC default method (i.e. tier 1 if associated with 
D data, or tier 2 if associated with CS data); in this case, the first notation key refers to "reference C stock", and second to "C stock change factor" (see IPCC-GPG for details). A cell with a single "CS" 
indicate a country-specific method and data (i.e. tier 3 if data are highly disagreagated); and (4) for biomass under L c CL, "conversion to cropland", the 2 notation keys used mean: first one refers to FLcCL 
and second to GLcCL. 

EN 

70 

EN 

 
  
When comparing the absolute levels or trends of Implied Emission Factors (IEFs) across MS, 
much caution should be used. Indeed, in some cases, large differences may be attributable to 
the  different  estimating  or  reporting  methodology  and  they  do  not  truly  reflect  the  different 
intensity of emissions and removals. For example, some IEFs may be significantly affected by 
new areas entering a given category. Furthermore, the fact that not all countries use the 20-
year  IPCC  default  transition  period  for  land  use  change  categories  means  that  the 
corresponding emission factors are not fully comparable across all MSs. 

Determination of “C stock change factors” for Forest Land 

Based  on  MS’  NIRs,  information  on  underlying  methods  used  to  determine  the  C  stock 
change factors in forest land is generally available for biomass, but less for SOM and DOM. 

•  Biomass: Information on C stock change in the biomass pool is the most complete in NIRs, 
with rich information on the underlying method used for collection (Table A1.11). In fact, 
all MS apply Tier 2 or 3 methods. 

Table  A1.11.  Synthesis  of  the  datasets/methods  used  to  determine  the  “C  stock  change  factors”  for  BIOMASS  and 
their characteristics (N= no. of MS reporting under respective method) 

Data source 

Method 

Comments on method  

National Forest 
Inventory  

(NFL=17) 

Stand wise forest 
inventory  

(NFL=6) 

Various statistics  

(NFL=2) 

Statistical procedures 
in geo-referenced grid 

Data obtained by complete and repetitive field measurements in permanent 
and/or temporary plots. Proxy parameters are the dimensions of individual 
trees in the sampling plots. 

Partial sampling of 
stands 

Data is obtained by both field measurements (i.e. old stands) and derived 
from yield tables (i.e. for young stands). Proxy parameters are the stand 
descriptive characteristics. 

Modeling 

Source data could be NFI or combination of other data (i.e. afforestation data, 
yield tables, wood harvest) 

Despite  the  few  basic  methods,  there  is  a  lot  of  heterogeneity  on  implementation 
characteristics  of  each  method  across  MS  (i.e.  grid  density,  plot  characteristics,  sampling 
procedures). 

•  Dead  organic  matter:  Information  on  underlying  methods  C  stock  change  in  this  pool  is 
rather poor in the NIRs, still with many MS not reporting. The majority of MSs does not 
report a change (Tier 1), see Table A1.12. 

Table A1.12. Synthesis of the datasets/methods used to determine the “C stock change factors” for DEAD ORGANIC 
MATTER and their characteristics (N= no. of MS reporting under respective method) 

Data source 

Not reported  

(NFL=16) 

Method 

NA 

Comments on method 

Reporting according Tier 1 IPCC (no change)  

National Forest Inventory  

(NFL=7) 

Various data  

(NFL=4) 

Statistical procedure in geo-
referenced grids 

Usually only dead wood data is collected (not the litter). 
Annual estimates are derived by mass or C stock difference 
over successive cycles and interpolation 

Modeling (process based or 
bookkeeping models) 

Source data could be NFI, other statistics (i.e. afforestation, 
harvest, yield tables) or simple regressions based on other 
data (i.e. stand aboveground biomass) 

•  Mineral  soils:  It  is  rarely  clear  from  NIRs  what  soil  classification  systems  are  used  and 
how data is processed, while the method to collect data is provided (Table A1.13). For land 
conversion  to/from  forest  the  most  used  method  is  that  of  “reference  C  stocks”  which 

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allows an annual constant linear change between “initial” and “final” C stocks. More than 
half of MS apply Tier 1 (no change in C stock) in forest remaining forest. 

Table A1.13. Synthesis of the datasets/methods used to determine the “C stock change factors” for MINERAL SOIL 
and their characteristics (N= no. of MS reporting under respective method) 

Data source 

Not estimated  

(NFL=13) 

IPCC default values  

(NFL=1) 

National Forest Inventory and soils 
databases  

(NFL=11) 

National Forest Inventory and other 
various data  

(NFL=5) 

Method 

NA 

Comments on method 

Reporting according Tier 1 IPCC (no change) 

IPCC default values 

Unique national reference C stocks assumed equal to 
IPCC default value 

Statistical procedure in geo-
referenced grids 

Time difference and annual interpolation based on 
repetitive sampling (i.e. national soil database, NFI, ICP 
Forests, research projects) 

Process based or 
bookkeeping modeling 

Source data could be NFI, or other statistics (i.e. 
afforestation, harvest, yield tables) or simple regressions 

•  Organic  soils:  The  definition  of  soil  C  pool  differs  across  MS  in  terms  of  the  threshold 
between  organic  and  mineral  soils  and  the  treatment  of  peatland  and  drained  areas  with 
organic  soils.  There  are  only  a  few  methods  used  for  estimation  of  organic  soils  (Table 
A1.14). Tier 1 is the most used method for organic soils. 

Table A1.14. Synthesis of the datasets/methods used to determine the “C stock change factors” for ORGANIC SOIL 
and their characteristics (N= no. of MS reporting under respective method) 

Data source 

Not estimated  

(NFL=18) 

IPCC default emission factor  

(NFL=4) 

Method 

Comments on method 

NA 

Not reporting or not occurring or (in disagreement with IPCC 
GPG LULUCF) assumed neutral 

IPCC default values 

Reporting under Tier 1  

National Forest Inventory or other 
data 

Modeling 

(NFL=3) 

Process based modeling with inputs from NFI or other data (i.e. 
afforestation, harvest, yield tables) 

•  Emission factors for disturbances on forest land: The main source of data are the NFIs or 
stand  wise  forest  inventories,  combined  with  specific  statistics  managed  by  forest 
authorities. The wood volume lost in disturbance events is usually measured or estimated 
by  ground  measurement  or  visual  assessment  and  provided  in  statistics.  Another  method 
considers the average estimate of standing stock (derived from NFIs database). 

Determination of “C stock change factors” for cropland and grassland 

Information  on  C  stock  change  factors  in  cropland  is  rather  poor  in  NIRs.  The  basic 
underlying  methods  do  not  differ  significantly  between  cropland  and  grassland  on  C  stock 
change in soils. 

•  Biomass:  On  cropland,  only  C  stock  change  in  woody  permanent  crops  is  estimated  (i.e. 
orchards,  vineyards,  olive  groves).  Annual  biomass  is  only  computed  by  few  MS,  and 
sometimes it is done with the purpose to assess the organic matter input into soils (which 
drives  a  model  for  soil  emissions).  Changes  in  biomass  are  mainly  reported  as  not 

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occurring  on  grassland  (following  IPCC  tier  1),  and  default  values  are  also  commonly 
applied to cropland (Tier 1). 

Table A1.15. Datasets/methods used to determine the “C stock change factors” for BIOMASS (N= no. of MS 
reporting under respective method on CL or GL) 

Datasets 

Not reported  

(NCL= 8)  

(NGL= 22) 

IPCC default values  

(NCL=10)  

(NGL=0) 

Basic country specific data  

(NCL= 5)  

(NGL=0) 

Various inputs to models  

(NCL=2)  

(NGL=3) 

Comments on method  

Not yet estimated or assumed “no change” 

IPCC default factors. 2 MS included here report CS data for bioenergy/biomass 
plantations  

National data available (i.e. from research). 2 MS included here report some type of 
permanent crops by modeling 

Process based modeling with various inputs (i.e. non-forest NFI sampling, research 
data) 

•  Mineral soils: Reporting of this pool is still rather poor because of lack of consistent and 
adequate  data.  Also,  the  methodological  information in  the NIRs is not  always adequate. 
Where  available,  the  data  is  often  provided  by  heterogeneous  databases  (i.e.  various 
methodologies,  sampling  year).  Tier  1  is  applied  by  four  MS;  Tier  2  or  3  methods  are 
applied by about half MS. 

Table  A1.16.  Datasets/methods  used  to  determine  the  “C  stock  change”  for  MINERAL  SOILS  (N=  no.  of  MS 
reporting under respective method on CL or GL) 

Datasets for C stock in mineral soils 

Comments on method 

Not reporting  

(NCL= 8)  

(NGL= 11) 

IPCC C stock default values  

(NCL= 4)  

(NGL= 4) 

Country specific reference C stocks  

(NCL= 9)  

(NGL= 6) 

Various inputs to models  

(NCL= 4)  

(NGL= 4) 

Adjustment factors data  

(Flu, Fmngm, Fi)  

Not yet estimated or assumed (in discordance with IPCC 
LULUCF GPG) “no change” for CL 

IPCC default values 

C stock reference is developed on each land use either on 
province or national scale from soil database 

Process based modeling with various inputs (i.e. NFI, agricultural 
data; research data for GL) 

Expert based adjustment of IPCC default values 

Only 1 MS developed own factors based on time series of field 
measurements  

•  Organic  soils:  while  few  MS  report  emission  from  organic  soils  under  cropland  or 
grassland,  the  emissions  are  usually  relevant.  On  grassland,  reporting  of  organic  soils  is 

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particularly poor because of lack of consistent and adequate data. Lack of transparency and 
explicit information characterizes this issue in NIRs. 

Table  A1.17.  Datasets/methods  used  to  determine  the  “emission  factors”  for  ORGANIC  SOILS  (N=no.  of  MS 
reporting under respective method on CL or GL) 

Datasets/source  

Comments on method 

Not reporting  

(NCL= 12)  

(NGL= 12) 

IPCC default values  

(NCL= 7)  

(NGL= 8) 

Country specific data  

(NCL= 6)  

(NGL= 5) 

8.1.5.  Uncertainties 

Not yet estimated or assumed “no occurring” 

Emission factor provided by the IPCC GPG 

Data from research used for reporting either based on CS emission factors (i.e. 
heterotrophic respiration) or by modeling (i.e. input from NFI)  

This  section  presents  the  estimated  uncertainties  at  EU-15  level,  based  on  the  (often 
incomplete) information available in MS’ NIRs. Uncertainties for AD and EF are reported as 
simple  averages  of  MS’  reported  data,  while  uncertainties  for  GHG  emission/removals  are 
estimated based on the aggregation (by error propagation) of MS estimates. In general, these 
estimates  at  EU-15  level  can  be  considered  broadly  valid  also  for  the  whole  EU.  More 
infomation can be found in the EU NIR 2010. 

The uncertainty of the activity data (AD) varies across MS and land (sub)categories within the 
MSs. The uncertainty level depends on the original purpose of datasets, land use definitions 
and  their  consistent  use  in  time,  spatial  resolution,  reference  years  as  well  as  land  data 
processing techniques which usually introduce additional uncertainty in GHG estimations. For 
forest land remaining forest land the uncertainty at EU-15 level is estimated to be about 12%, 
as a simple average, with the lowest value reported by Germany and the UK (~1%). For lands 
under  conversion  to  forest  land,  MS  reported  very  different  values,  with  an  overall  simple 
average of 15% and the highest value reported by Italy (75%). For all other land categories, 
the average uncertainty is around 20% for lands remaining the same land and apparently less 
than 20% for lands under conversion. 

The  uncertainty  associated  with  the  emission  factors/C  stock  change  factors(EF)  is  in  the 
order of 60–85%, as a simple average, for all GHG and land uses in the EU-15, and a little 
higher on lands under conversion. It also shows a rather high fluctuation among MSs, because 
of the generally high number of parameters involved in its calculation and the variety of the 
methodological  approaches.  Again,  the  direct  comparability  among  MS  is  low  as  often  it 
reflects combined uncertainty with the activity data. The uncertainty of the EF is higher for 
the  land  subcategories  in  the  territories  of  MS  with  high  disturbance  levels  like  forest  fires 
(i.e. Portugal and Greece) or organic soils (i.e. Finland). 

The aggregated estimated uncertainty of the annual EU-15 emissions and removals is 32% for 
forest land, grassland and cropland combined; however, it ranges from 25% in land converted 
to forest to 105% in cropland remaining cropland (see Table A1.18). For the new 10 MS (i.e. 
excluding Malta and Cyprus) similar ranges of uncertainty of activity data can be expected, 
but higher levels for C stock change factors (JRC 2010a). 

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Table A1.18. Uncertainty across the EU-15 by subcategories and GHG in 2008 (half of 95 % confidence interval of 
averages, by error propagation with individual MS E/R) 

Inventory category 

Category 
uncertainty for EU (%) 

Total estimated emission (+)/ 
removal (-) in 2008 (Gg CO2) 

Uncertain amount 
(GgCO2) 

FL r.FL (5A1) 

LcFL (5A2)  

CLrCL (5B1)  

LcCL (5B2)  

GLrGL (5C1)  

LcGL (5C2)  

Total**  

Forest land (5A)  

Cropland  and  grassland 
(5B+5C)  

30% 

25% 

105% 

30% 

87% 

49% 

32% 

26% 

63% 

-276,794 

-49,779 

19,184 

45,341 

11,923 

-22,077 

-280,018 

-326,573 

46,555 

81675 

12446 

20216 

13484 

13756 

10796 

88590 

84761 

31784 

*It  should  be  noted  that  estimates  of  the  aggregated  EU-15  level  uncertainties  may  slightly  vary  also  depending  on  the 
method used to aggregate the available information at MS level. Subcategory uncertain amounts do not sum up to the overall 
EU  15's  unceratin  amount  due  to  compensation  over  the  error  propagation  procedure.  Uncertainty  is  computed  as  two 
standard deviations (2σ for 95 % confidence interval). 

**  This  estimate  excludes  Wetland,  Settlements  and  Other  land.  Taking  these  land  categories  into  account,  the  total 
uncerainty estimate amounts to 35%. 

Notes: Much care should be used when comparing uncertainties of specific LULUCF categories with others sectors. While 
all the other sectors are sources of GHG, LULUCF may either be a source or a sink. This may profoundly affect the estimate 
of % uncertainty, depending at which level the analysis is done. E.g. If the subcategory “cropland remaining cropland” is a 
sink  of  -50  MtCO2  +/-10%,  and  “land  converted  to  cropland”  is  a  source  of  +55  MtCO2  +/-10%,  the  whole  cropland 
category will be a source of +5 MtCO2 with a level of uncertainty close to 100%. 

By  way  of  comparison,  Table  A1.19  shows  the  uncertainty  related  to  estimates  in  the 
agricultural sector (non-CO2 GHG).  Uncertainty in  this  sector  is 68% on  average but varies 
from 12% (enteric fermentation) and 156% (agricultural soils). Table A1.20 shows the overall 
uncertainty estimates for other sectors, based on the magnitude  of emissions. It is clear that 
the  level  of  uncertainty  in  LULUCF  is  relatively  large  compared  to  e.g.  fuel  combustion 
(1.5%),  transport  (6%),  industrial  processes  (5%)  and  waste  (21%),  but  is  similar  to  that  of 
fugitive emissions (32%) and smaller than the uncertainty in the agriculture sector. All sectors 
other than LULUCF are already part of the EU's GHG reduction commitment. 

Table  A1.19.  Uncertainty  across  the  EU-15  by  subcategories  and  GHG  in  2008  (half  of  95  %  confidenceinterval  of 
averages, by error propagation with individual MS E/R) 

Inventory category 

Enteric fermentation (4A) 

Manure management (4B) 

Manure management (4B) 

Rice cultivation (4C) 

Agricultural soils (4D) 

Agricultural soils (4D) 

Total 

Source: Leip (2010) 

GHG 

CH4 

CH4 

N2O 

CH4 

CH4 

N2O 

CH4+N2O 

Category 
uncertainty for EU (%) 

12% 

26% 

61% 

20% 

50% 

156% 

68% 

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Table A1.20. Uncertainty estimates of EU-15 GHG emissions and removals 

Source category

Gas

Emissions
1990

Emissions
2008

Emission 
trends 1990-
2008

Level uncertainty 
estimates based on 
MS uncertainty 
estimates

Trend uncertainty 
estimates based on 
MS uncertainty 
estimates

all
all
all
all
all
all
all
all 
all 

2,458,079
698,421
97,527
374,779
430,533
-212,334
171,257
4,018,264
4,230,597

2,311,118
861,374
49,936
329,992
377,803
-251,002
103,923
3,783,144
4,034,145

1.5%
-6%
6%
23%
32%
-49%
5%
-12%
68% (45%-102%)
-12%
35%
18%
-39%
21%
-6% 7.4%  (5.6% -10.7% )
-5% 6.9%  (4.8% -10.2% )

0.5
3.4
23.3
12.2
8.4
-
10.7

1.7

Fuel combustion stationary
Transport
Fugitive emissions
Industrial processes
Agriculture
LULUCF
Waste
Total (incl LULUCF)
Total (excl LULUCF)

Source: EEA (2010) 

8.1.6.  Recalculations 

A large number of countries carried out important recalculations in the last GHG inventory. 
Recalculation are usually due to change in methods (e.g. from stock change to gain-loss), new 
C pools reported for the first time, or new data (e.g. new NFI). Recalculations are an inherent 
characteristic of the LULUCF sector and are generally more significant than in other sectors. 
This is illustrated by Figure A1.1 which shows differences between 2009 and 2010 amounting 
to five, ten and 25% of MSs' 1990 GHG emissions. This has implications for the possibility of 
including  LULUCF  in  existing  policy  frameworks  to  the  extent  that  they  require  annual 
compliance with emission limits as well as corrective action when a MS's (under the ESD) or 
installation's (under the EU ETS) emissions exceed its limit. 

Figure  A1.1.  Extent  of  recalculations  for  the  year  2007  in  “forest  remaining  forest”  (difference  2010-2009 
submissions), expressed as % of total 1990 GHG emission of each MS. 

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8.1.7.  Time-series consistency and comparability between MSs 

Comparability  can  be  looked  in  at  least  two  ways;  within  a  MS  over  time  ("time-series 
consistency") and between different MSs. The former can be generally considered scarcely a 
problem  and  the  following  sections  therefore  focus  on  some  of  the  factors  that  affect 
comparability between MS. It follows from earlier sections that there is diversity in estimation 
methods amongst MS. This is highlighted by e.g. Lawrence et al. (2010) who also note that 
variations  in  definitions  make  direct  comparability  difficult.  Some  of  the  differences  in 
definitions are discussed below. 

8.1.7.1.  Definitions 

Forest definition 

The parameters used to define forest under the KP are presented in Table A1.21. Definitions 
vary across MSs. While consistency within the country in terms of time and space is achieved 
by most MS, direct comparability accross the MSs is currently not possible as the parameters 
vary  across  minimum  crown  cover,  minimum  hieght,  minimum  area  and  minimum  width. 
Although diversity in methods inevitably contributes to differences in estimates, if forest area 
sampling and estimators are unbiased, then detrimental effects on harmonised reporting as a 
result of their diversity are minimal (Lawrence et al., 2010). 

Table A1.21. Selection of parameters for defining “forest” under the Kyoto Protocol 

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Definition of land use changes 

Definitions of land use changes may differ among MS, and this introduces some difficulty in 
comparing  estimates.  For  example,  some  MS  define  deforestation  based  on  specific 
documentation (e.g. permissions), while other MSs consider that if after a given lapse of time 
from harvest (e.g. 5 or 10 yrs) regeneration did not occur, than it is deforestation. Data on AR 
and D areas suggest there may be a problem of comparability among MS (e.g. France has D 
area hundreds times that of Italy, Portugal hundreds  times that of Spain). It is clear that for 
some MS data for AR and D are still preliminary. Many MS noted the difficulty of reporting 
on land use changes, because they are usually small and scattered events. 

Figure A1.2. Comparison of ARD area in the EU-27  

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Definitions of carbon pools 

The  wide  variation  of  definition  of  the  pools  amongst  MSs  (aboveground  and  belowground 
biomass, soil organic matter, dead organic matter) is notable. The effect on overall accuracy 
of the estimation of carbon stock changes and other GHG emissions related to various pools 
definition  is  likely  low,  but  also  difficult  to  assess  in  quantitative  terms  (i.e.  for  non-
considered  part  of  the  pools,  like  trees  under  the  threshold  diameter).  The  variation  in 
definitions  affects  the  comparability  amongst  MS  but  likely  not  the  completeness,  to  the 
extent that the share of pools which is reported by one MS under some category is reported by 
others  under  a  different  category.  Nevertheless,  a  pool  reported  under  other  pools  may 
introduce higher uncertainty in the estimation (caused mainly by the different turnover), but it 
can be duly justified for practical reasons (i.e historical data availability, measurement errors). 
For example, the minimum DBH (breast height diameter) for trees measurement in NFI varies 
from 0 cm for 5 MS, < 5 cm for 3 MS and < 10 cm for 5 MS. Also, soil organic matter (SOM) 
is  estimated  for  different  depth  (30  cm  to  100  cm)  across  MS.  Dead  organic  matter  pool 
(DOM,  litter  and  dead  wood)  also  differs  in  terms  of  type  (standing,  laying),  threshold 
diameter  and  height,  and  duration  since  laying  down  (which  defines  the  decomposition 
period). 

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8.1.8.  Verification activities 

Currently,  there  is  poor  implementation  of,  or  at  least  little  information  on,  verification 
activities  by  EU  MS.  Despite  IPCC  GPG  LULUCF  provides  a  number  of  possible  specific 
approaches  for  verification,  several  MS  included  verification  activities  in  the  Quality 
Assurance (QA)/Quality Control (QC) process and only focus on double checks of input data 
used  for  the  estimation  of  GHG.  There  are  few  specific  cases  of  verification  of  the  outputs 
(e.g.  C  stocks  changes):  Germany  reports  on  the  calculation  of  the  C  stocks  and  C-stock 
changes  in  biomass  for  forestland  by  two  different  forestry  institutes  and  estimates  are  in 
“good agreement”. Italy reports on current implementation of an interregional project to carry 
out atmospheric emission inventories at local scale, with a module on the estimation of forest 
land related emission/removals (in 7 out of the 20 Italian regions), the results of which will 
allow the validation of both methodology and estimates at country level. Finland reports the 
establishing of a network for GHG monitoring of drained organic soils. The UK implements a 
number  of  research  projects  on  the  effect  of  afforestation,  effect  of  cultivation  and  re-
sampling in the framework of National Soil Inventory as part of GHG inventory programme. 
Sweden confirms the trend of estimated removals by implementing the default method with 
own  data.  Also,  it  reports  that  process  based  models  and  field  measurements  agreed  on 
organic matter and soil organic carbon in forests. Denmark performs field collecting samples 
in order to check the outputs of the model which is used for reporting. 

In  terms  of  disturbances,  Forest  fire  -  EFFIS  (European  Forest  Fire  Information  System, 
http://effis.jrc.ec.europa.eu/) is a potential candidate for verification at the continental scale. It 
is a tool for rapid damage assessment and active fire detection which may be assessed in the 
way  of  verification  of  emissions  from  fires.  Practically  all  the  data  are  delivered  in  a 
harmonized  scheme  and  in  the  standard  European  spatial  reference  system  ETRS-LAEA 
which ensures the most recent MODIS coverage of Europe. 

In conclusion, although verification activities are clearly a key element for ensuring inventory 
quality and increasing confidence on results, currently there is still poor implementation of, or 
at  least  little  information  on,  verification  activities  at  EU  level.  It  is  expected  that  more 
attention will be paid on verification in coming years, and that a larger role in this context will 
be played by models. 

8.1.9.  Costs of improving monitoring 

Reporting under the UNFCCC is mandatory for land categories for which IPCC GPG exists, 
i.e. forest land, grassland and cropland, and all land use changes (for all land categories). In 
addition, the KP requires reporting for a number of mandatory and elected activities and adds 
obligations to the UNFCCC reporting. This requires action by MSs. Tier 1 should be applied 
as a minimum in reporting but it is good practice to use tier levels 2 or 3 for key categories.49 
The  objective  for  monitoring  and  reporting  set  out  in  this  impact  assessment  is  that  MSs 
comply with the IPCC GPG. More efforts are required to meet this objective. 

A  two-step  approach  was  used  in  order  to  estimate  the  associated  costs  (see  discussion  in 
Section 4.2 of the main text): 

49 

Both  IPCC  GPG-LULUCF  and  UNFCCC  guidelines  for  reviewing  GHG  inventories  recommend  to 
consider national circumstances when evaluating the methodological choice (i,e. tier level) in relation to 
the  key  category  analysis,  This  means  assessing  the  resources  and  capacities  needed  to  improve  the 
GHG inventory in relation to the Party’s possibilities. 

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•  Step 1 – Achieving completeness in the reporting of all mandatory categories and pools at 

a minimum level of tier 1, 

•  Step 2 – Increasing the accuracy of the reported key categories and pools to a minimum of 

tier 2. 

It is, however, a challenge to estimate the related costs and the following limitations should be 
borne in mind when interpreting the results: 

•  There  is  no  unique  way  of  reaching  the  objective  because  the  IPCC  GPG  allows  for 
different methodologies and approaches to be applied according to national circumstances. 
A  number  of  tools  exist  for  representing  land  areas  (e.g.  use  of  existing  data,  remote 
sensing and ground-based surveys) and for deriving emission factors (e.g. default values, 
literature, measurements and models), and these can be combined in a number of ways. For 
the purpose of this assessment, repeated soil sampling campaigns were simulated to derive 
country  specific  emission  factors  for  soils  (required  for  tier  2)  and  that  can  be  combined 
with largely existing activity data. 

•  It is a complex task to establish the current monitoring capacity, or the baseline, in MSs. 
Here the information on methodologies and approaches reported by MSs to the UNFCCC 
in  2010,  and  analysed  by  JRC  (2011a),  was  used,  see  Table  A1.3  (completeness  of 
reporting) and Tables A1.6 and A1.10 (type of approaches and methodologies). 

•  The availability of literature on monitoring costs is limited. A mixture of sources, based on 
actual experience and studies, was used to obtain the necessary assumptions to derive an 
interval indicating the potential costs. 

8.1.9.1.  Step  1  –  Achieving  completeness  in  the  reporting  of  categories  and  pools  at  a 

minimum level of tier 1 

Reporting on biomass in forest land is generally complete. Only a few MSs did not report (in 
2010) on this pool in one of the sub-categories under forest land. On the contrary, most MSs 
did  not  report  on  soil  in  one  or  both  of  the  sub-categories  under  forest  land,  cropland  and 
grassland.  

The cost of improving the completeness to a minimum of tier 1 level of accuracy is, however, 
assumed to be reasonable, both for biomass and for soils; whilst it requires compiling activity 
data  from  different  sources,  the  data  is  generally  available  in  MSs  and/or  from  European 
initiatives (e.g. LUCAS50 and CORINE) and can be combined with IPCC default values (tier 
1). 

50 

The Land Use/Cover Area frame statistical Survey. The name reflects the methodology used to collect 
the information. Estimates of the area occupied by different land use or land cover types are computed 
on the basis of observations taken at more than 250,000 sample points throughout the EU rather than 
mapping the entire area under investigation. By repeating the survey every few years, changes to land 
use and land management can be identified.  

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8.1.9.2.  Step  2  –  Increasing  the  accuracy  of  the  reported  key  categories  and  pools  to  a 

minimum of tier 2 

This  step  focuses  on  improving  the  level  of  accuracy  of  monitoring  and  reporting  of  stock 
changes  in  soils  in  forest  land,  cropland  and  grassland  as  this  is  where  the  most  significant 
gaps in reporting exist, see Table A1.10. SE, DK, FI, DE and the UK apply high level tiers to 
the soil pool in all land categories but most MSs use tier 1 or do not report at all on soil in at 
least one of the land categories. 

On  the  basis  of  what  is  required  by  the  IPCC  GPG  (2003),  it  is  assumed  that  activity  data 
from  different  sources  available  in  MSs  and/or  from  European  initiatives  (e.g.  updates  of 
LUCAS and CORINE) would provide sufficient information and spatial resolution to be used 
for tier 2 and that the cost for this component therefore is low. For the purpose of simulating 
the cost of increasing the level of accuracy and to derive country-specific emission factors it is 
assumed that the required data would be collected through repeated soil sampling campaigns 
in order to capture the annual rates of emissions and removals, calculated as the difference in 
stocks  over  time  divided  by  the  inventory  time  period.  A  comprehensive  review  of  the  soil 
inventory  and  monitoring  activities  in  the  EU  was  carried  out  under  ENVASSO51  and 
evaluated  the  extent  to  which  existing  soil  monitoring  networks  adequately  represent 
European  soil  typological  units,  land  use/cover,  specific  soil  criteria  such  as  soil  organic 
carbon  and  bulk  density  (which  are  needed  to  measure  changes  in  carbon  stocks).  It  also 
detailed the  existing national networks, their purpose, sampling strategy, analytical methods 
used and number of monitoring sites (around 35 000 for soil organic carbon). Procedures and 
protocols appropriate for inclusion in a European soil monitoring system were identified and 
documented  and,  finally,  a  soil  monitoring  system  was  defined  that  comprises  a  network  of 
geo-referenced sites at which qualified sampling  process is being or  could be conducted. In 
addition,  the  BioSoil  demonstration  project  (Hiederer  et  al.,  2011)  is  one  of  several  studies 
under Forest Focus52 and was initiated to develop the monitoring scheme by means of studies, 
experiments,  demonstration  projects  and  testing  on  a  pilot  basis  and  establishment  of  new 
monitoring activities. 

The following steps were taken: 

1. 

51 

52 

The  sampling  density  was  determined  based  on  a  review  of  plot  sizes  ranging 
between  6  400  ha,  18  000  ha  (LUCAS),  19  600  ha  (Forest  Focus  and  Biosoil)  and 
30 000 ha (which is the EU median density, Arrouays et al., 2008) per plot. Although 
it  should  be  noted  that  the  number  of  plots  also  depends  on  the  desired  level  of 
certainty  and  the  sampling  interval  (Mäkipää  et  al.,  2008).  A  consideration  for 
monitoring and estimating soil organic carbon is that it may be desirable to stratify 
mineral and organic soils and sample within those strata to obtain sufficient data for 
the organic soils. 

The  ENVironmental  Assessment  of  Soil  for  mOnitoring  (ENVASSO) project  was  funded  2006-08 as 
Scientific Support to Policy under the European Commission 6th Framework Programme of Research. 
Regulation (EC) No 2152/2003 of the European Parliament and of the Council of 17 November 2003 
concerning  monitoring  of  forests  and  environmental  interactions  in  the  Community,  now  funded  via 
LIFE+, provides for measures to e.g. promote harmonised collection, handling and assessment of data; 
improve data evaluation at Community level; improve the quality of data and information gathered; and 
develop forest monitoring activities. 

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2. 

3. 

4. 

5. 

The  number  of  samples  per  plot  was  set  at  1  composite  soil  carbon  sample 
(consisting  of  2-4  soil  samples)  and  1  composite  sample  for  bulk  density  (IPCC, 
2003). 

Case  studies  show  that  the  cost  per  sample  ranges  between  €6-16  as  regards  the 
laboratory cost (Stolbovoy et al., 2007) which constitutes about 25% of the total cost 
(Mäkipää et al., 2008), i.e. total cost per sample amounts to €24-64. Mäkipää et al. 
(2008) found that the cost per sample was €47 but estimated a fixed cost per plot at 
€230. 

The  number  of  sites  needed  per  MS  was  determined  by  dividing  the  total  area  of 
forest land, cropland and grassland by the sampling plot density where the land area 
is a key category. 

The cost per MS was calculated by multiplying the number of sites with the total cost 
per  site,  divided  by  the  time  interval  between  two  different  sampling  campaigns, 
ranging between 20 years for tiers 1 and 2 (IPCC, 2003), 10 years (Arrouays et al., 
2008) and 3-5 years for tier 3 (IPCC, 2003). 

However,  the  cost  obtained  from  1-5  above  assumes  that  all  MSs  would  require 
investments in soil monitoring. As shown in A1.10 this is not the case, neither for all 
MSs nor for all land categories. Therefore an additional step was taken: 

6. 

The  cost  related  to  those  land  categories  for  which  MSs  already  apply  tier  2  or  3 
methodologies was deducted from the cost obtained in 1-5. 

As noted above, MSs are required to report to report under the UNFCCC and the KP, using 
tier  1  as  a  default  and  tiers  2  or  3  for  all  key  categories.  The  cost  of  meeting  these  criteria 
should  therefore  be  attributed  to  the  ratification  of  the  Convention  and  the  KP  and  the 
adoption  of  the  IPCC  GPG,  and  not  the  potential  inclusion  of  LULUCF  in  the  EU's  GHG 
reduction commitment. 

The fixed costs of monitoring a network of plots were not assessed, but it is assumed that use 
could be made of existing networks, as shown by Kibblewhite et al. (2008), and so limiting or 
cancelling the cost of additional plots. Additional reporting costs (e.g. to adapt UNFCCC data 
to KP format) are also judged to be negligible given the current reporting requirements under 
the UNFCCC and the KP. 

8.1.9.3.  3 – Harmonisation 

In addition to the IPCC GPG, additional efforts to harmonise monitoring and reporting in the 
EU should be promoted and this would require resources. The associated costs have not been 
estimated.  Great  effort  has  already  gone  into  harmonizing  forest  and  soil  surveys.  The 
findings  from  BioSoil  (EC,  2003)  clearly  ask  for  better  harmonization  of  methods  to  allow 
arriving  at  comparable  results  between  national  surveys,  but  also  to  provide  temporal 
consistency. Otherwise differences in methods overshadow changes in the field and cannot be 
separated to estimate C stocks and GHG emissions. 

Table A1.22 summarises the assumptions made for two cost scenarios, one low and one high. 

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Table A1.22 Summary of assumptions about sampling parameters 

Parameter 

Value 

Sampling density 

Number of samples per plot 

Sample cost 

Fixed cost per plot 

Sampling interval 

8.1.9.4.  Results 

Low cost 

19 600 ha 

High cost 

6 400 ha 

2 composite samples (1 soil 
carbon, 1 bulk density) 

2 composite samples (1 soil 
carbon, 1 bulk density) 

€24 

€238 

€64 

€238 

20 years 

8 years 

4 year 

Table A1.23 shows the results of Step 2, using two different assumptions about the baseline. 
If all MSs require investments in soil monitoring to move from tier 1 to tier 2 or 3, the annual 
cost for the EU-27 would be between 0.5 and 2.1 mln €/year, assuming a sampling interval of 
8 years. However, and as shown in Table A1.10, a number of MSs already have the required 
capacity which means that the additional cost is likely to be lower, between 0.4 and 0.5 mln 
€/year.  As  noted  above,  MSs  are  already  obliged  to  use  tier  2  or  3  for  key  categories  in 
UNFCCC  and  KP  reporting.  Hence,  whilst  the  costs  to  MSs  of  improving  monitoring  are 
positive, the cost of the policy objective is zero. 

Arrouays  et  al.  (2008)  estimated  the  number  of  additional  sites  needed  to  detect  a  relative 
decrease of 5% of the national mean of topsoil organic carbon contents according to national 
statistics on variances. If the same cost assumptions are applied to their estimate, the resulting 
costs would be €0.9 to 1.2 mln per year with an 8 year sampling interval. On the other hand, 
soil sampling was carried out under the auspices of LUCAS53 in 2009 at an additional cost of 
only €1.2 mln (€0.2 mln per year). This shows that significant cost savings to be had through 
coordinated and systematic schemes. 

Table A1.23. Indicative costs of improving the level of accuracy of MRV 

Frequency of sampling* 

Annual cost for EU-27 (mln €/yr) 

Low 

High 

every 4 yrs 

every 8 yrs 

every 20 yrs 

every 4 yrs 

every 8 yrs 

Baseline assumption: all MSs require investments in soil monitoring 

1,1 

0,5 

0,2 

4,2 

2,1 

0,8 

Baseline assumption: some MSs (based on Table A1.9) require 
investments in soil monitoring 

0,7 

0,4 

0,9 

0,5 

53 

During the 2009 survey, soil samples were collected from more than 22,000 LUCAS point locations. 

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every 20 yrs 

Cost  of  policy  requiring  improved  MRV 
according  to  IPCC  GPG  standard  under 
both baseline assumptions** 

0,1 

0 

0,2 

0 

Cost of harmonisation 

Not estimated 

Not estimated 

Notes: *According to Arrouays et al. (2008) a time interval of about 10 years would enable the detection of some simulated 
large changes in soil organic carbon in most European countries. IPCC uses 20 years as a default (tiers 1 and 2) and 3-5 years 
for tier 3. An 8 year interval is used here as the central scenario to match the compliance period of 2013 to 2020. ** The cost 
of  the  policy  is  what  would  be  required  in  addition  to  the  meeting  the  obligations  under  the  UNFCCC  and  KP;  MSs  are 
already required to apply tier 2 or 3 for key land categories, but only some MS comply. 

8.1.10.  Appendix 1 – Overview of problems emerged during 2010 review and answers by MS 

The EU QA/QC and UNFCCC review 2010 revealed several issues related to achievement of 
the reporting requirements under the KP: 

•  To  demonstrate  that  a  non-reported  C  pool  is  not  a  source.  This  is  a  problem  for  soil  C, 

especially for land remaining in the same category (e.g. forest remaining forest). 

•  To identify and track LUC over time ("land identification") 

•  To estimate appropriate EF for organic soils 

A summary is provided in Table A1.24. MSs have since provided more detailed explanations 
for the issues raised. It is likely that at least in part the problems are related to transparency in 
reporting (i.e. not enough background explanations provided). 

Table A1.24. LULUCF issues raised in the review of the 2010 submission for the Kyoto Protocol 

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MS 

Main issues 

Specific issues 

Austria 

AR 

Land identification  

Likely 
and accounting  

impact  on  reporting 

Notation key: 

Small < 1 MtCO2eq. 

Medium 1-5 MtCO2eq. 

Large > 5 MtCO2eq. 

Medium 

Denmark 

ARD, FM, 
CM, GM 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (ABG, BGB, LT, DW, SOM) 

Small 

AR 

AR 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (SOM –organic soils) 

Small 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (LT) 

Small 

CM, 1990, 
2008 

GM, 1990, 
2008 

SOM 

SOM  

Finland 

No issues  

No issues 

Land identification 

Emissions from fires 

France 

AR 

FM 

D 

D 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (DW) 

Small 

Lime application 

Small 

Probably medium 

Probably medium 

Large 

Small-Medium 

Germany  

ARD, FM 

National system - land identification  

Difficult to assess 

Greece 

D 

Incomplete land coverage  

Probably small 

ARD, FM 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (LT, DW, SOM) 

Small 

Ireland 

D 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (LT, DW, SOM) 

Small 

Italy 

No issues  

No issues  

Netherlands  AR,D 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (LT, DW, SOM) 

Small 

Portugal 

CRF table 
1990 

ARD, FM 

Only notation keys 

Difficult to assess 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (LT, DW, SOM) 

Small 

Spain 

AR 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (SOM) 

Medium 

FM 

“C  pool  not  reported”  w/o  demonstrating  that  it  is  not  a 
source (SOM) 

Medium 

CL, 1990 

SOM, ABG, BGB 

Probably medium 

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Sweden 

UK 

Czech 
Republic 

No 
issues 

No issues 

D 

D 

D 

Incomplete land coverage 

Probably small 

Information that demonstrates that deforestation activities began on or after 1 
January 1990 

Probably small 

Emissions from wildfires on deforestation lands 

Small 

AR, FM 

“C pool not reported” w/o demonstrating that it is not a source (LT, DW, SOM) 

Small 

Estonia 

ARD 

Land identification 

Probably small 

ARD 

“C pool not reported” w/o demonstrating that it is not a source (LT, DW, SOM) 

Small 

D 

Distinguishing of harvesting/forest disturbance from deforestation 

Potentially large 

Hungary 

Latvia 

KP 
tables  

AR 

D 

National system  

Difficult 
assess 

to 

“C pool not reported” w/o demonstrating that it is not a source (LT, DW, SOM) 

Small 

“C pool not reported” w/o demonstrating that it is not a source (ABG, BGB, LT, 
DW, SOM) 

Probably small 

FM 

“C pool not reported” w/o demonstrating that it is not a source (LT, DW, SOM) 

Small 

Poland 

ARD, FM 

“C pool not reported” w/o demonstrating that it is not a source (LT, DW, SOM)  Medium 

Romania 

KP 
tables 

National system 

Land identification 

AR 

AR 

FM 

FM 

Land areas 

Slovakia 

ARD, FM  National System 

“C pool not reported” w/o demonstrating that it is not a source (LT, DW,SOM) 

Medium 

“C pool not reported” w/o demonstrating that it is not a source (LT, DW, SOM)  Medium 

Difficult 
assess 

to 

Probably small 

Unknown 

Difficult 
assess 

to 

ARD 

“C pool not reported” w/o demonstrating that it is not a source (LT, DW) 

Small 

Slovenia  

D 

“C pool not reported” w/o demonstrating that it is not a source (LT) 

Small 

Luxemburg 

ARD 

KP tables not submitted in time 

Lithuania 

ARD, FM  National system  

Bulgaria  

ARD 

Land identification and “direct human induce” 

Likely small 

to 

Difficult 
assess 

Medium 

ARD 

“C pool not reported” w/o demonstrating that it is not a source (DW) 

Small 

Notation keys: ABG – Above ground biomass; BGB – Below ground biomass; LT – Litter; DW – Deadwood; and SOM – 
Soil organic matter.  

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8.2. 

Annex  II  –  Impacts  on  accounting  of  threshold  values  (natural  disturbances) 
and caps (forest management) 

8.2.1. 

Implications of different triggers for the application of provisions for large natural 
disturbances 

A  key  point  in  the  discussions  on  provisions  for  large  natural  disturbances  is  what  would 
trigger their application. Discussions have centred on a trigger set on the basis of total GHG 
emissions  of  parties  in  1990  (excl.  LULUCF),  i.e.  as  a  percentage  of  1990  emissions.  This 
makes  sense  because,  in  the  absence  of  methods  for  separating  natural  and  human  induced 
effects  (IPCC,  2010),  the  cap  would  relate  to  and  limit  compliance  risk.  As  noted  above, 
events  of  large  disturbances  could  result  from  major  grass  or  forest  fires,  storms  and 
pest/disease  outbreaks.  Reporting  on  the  related  effects  on  emissions  is  currently  scarce, 
which would suggest that the application of the provisions may be limited unless monitoring 
and reporting is improved. Also, in cases where wood can be salvaged, for instance following 
storms, the related emissions would be spread out over a number of years (up to 35 years) if 
MSs  can  account  for  changes  in  the  HWP  pool.  However,  wildfire  is  a  common  and  big 
source  of  natural  disturbance  emissions  and  for  which  reported  data  are  more  frequently 
available. Figure A2.4 shows that only some six countries in the EU had fire related emissions 
in  the  period  1990-2008  that  exceeded  one  percent  of  total  1990  GHG  emissions,  and  only 
Portugal and Austria had emissions that at some point exceeded five percent. 

Figure A2.4 Fire related emissions (MtCO2eq.) in the period 1990-2008 as % of 1990 GHG emissions 

s
n
o
i
s
s
i
m
e
G
H
G
0
9
9
1
l
a
t
o
t

f
o
%
s
a
s
n
o
i
s
s
i
m
e
e
r
i
F

20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0

Austria

Bulgaria

Italy

Portugal

Slovenia

Spain

0
9
9
1

2
9
9
1

4
9
9
1

6
9
9
1

8
9
9
1

0
0
0
2

2
0
0
2

4
0
0
2

6
0
0
2

8
0
0
2

Projections  of  natural  disturbances  are  difficult  (or  impossible).  However,  for  the  sake  of 
illustration reported data in 1990-2008 can be used to estimate the impact on accounting. If, 
during  this  period,  a  trigger  of  one  percent  had  been  used,  on  average  5.5  MtCO2  per  year 
would have been excluded from accounting at the EU level, see Table A2.2, whereas a trigger 
of five percent would have excluded about 1 MtCO2 per year on average. 

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Table A2.2 Fire emissions that would have been excluded from EU accounting per year as a result of different trigger 
values in the period 1990-2008 

Trigger values (set as % of a MS's 1990 
GHG emissions excl. LULUCF) 

Emissions that would have been excluded from accounting per year in 
the period 1990-2008 (MtCO2eq.) 

1% 
2% 
3% 
4% 
5% 

Average 

5588 
2992 
1737 
1327 
980 

min  

276 
0 
0 
0 
0 

max 

15474 
12459 
11037 
9663 
8325 

8.2.2.  Caps on credits and debits in forest management and their implications 

Given  that  there  is  always  a  degree  of  uncertainty  associated  with  projections,  some  parties 
have  called  for  quantitative  limitations  ("caps")  on  credits  and  debits  generated  by  forest 
management.  Whilst  technical  corrections  of  reference  levels  and  provisions  for  big  natural 
disturbances should eliminate most of the risks of setting "erroneous" reference levels, some 
uncertainty  remains  (projections  inherently  involve  a  degree  of  uncertainty).  Caps  could  be 
put  in  place  to  ensure  that  credits  are  not  issued  beyond  a  reasonable  level  of  expected 
mitigation potential relative to the projected emissions and removals, or indeed that debits are 
not issued beyond a reasonable level of a potential deterioration in the sink. 

Such  caps  could  be  designed  in  a  number  of  ways;  similar  to  the  current  cap  on  forest 
management, developing countries have called for a cap on credits only, whereas the EU has 
expressed  a  preference  for  caps  on  both  credits  and  debits,  albeit  with  a  higher  degree  of 
stringency on the credit side than on the debit side.54 Discussions have centred on caps set on 
the basis of total GHG emissions of parties in 1990 (excl. LULUCF), i.e. as a percentage of 
1990  emissions.  As  in  the  case  of  natural  disturbances  this  makes  sense  because  the  cap 
relates  to  compliance  (risk).  Also,  base  year  emissions  are  fixed  and  not  subject  to  changes 
due to recalculations. A possible disadvantage of the construction is that countries with low 
total  GHG  emissions  and  large  forest  areas  are  likely  to  be  more  affected  by  caps  than 
countries with high total emissions. The Durban negotiations in December 2011 settled with a 
3.5% credit cap only, applying no cap on debits. 

Different  cap  levels  have  been  discussed  previously  in  the  EU,  e.g.  4-6%  on  credits  and  8-
12%  on  debits.  Table  A2.3  shows  the  impact  on  accounting  of  different  caps.55  The 
calculations  are  based  on  a  10%  change  in  the  harvest  rate  compared  to  the  forest 
management reference level which should be regarded as a conservative approach given that 
the reference scenario (including reaching the renewable energy targets in the RES-D) in this 
impact assessment is expected to lead to an increase in the harvest rate of about 4%. 

54 
55 

See the March 2011 Environment Council Conclusions.  
Based on Böttcher et al. (2011) and JRC (2011b) who also provide the forest management reference levels 
for 15 MSs. 

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Table A2.3 Possible debits and credits arising from a 10% change in the harvest rate 

MS 

Possible debits 

Possible credits 

Resulting from a 10% increase in the harvest 
rate (in % of total MS GHG emissions in 
1990) 

Resulting from a 10% decrease in the 
harvest rate (in % of total MS GHG 
emissions in 1990) 

Netherlands 

Greece 

Belgium 

United Kingdom 

Luxembourg 

Denmark 

Italy 

Ireland 

Romania 

Bulgaria 

Germany 

Poland 

Slovakia 

Spain 

Hungary 

Lithuania 

Czech Republic 

France 

Austria 

Slovenia 

Portugal 

Estonia 

Latvia 

Sweden 

Finland 

0% 

0% 

0% 

0% 

0% 

0% 

0% 

1% 

1% 

1% 

1% 

1% 

1% 

1% 

1% 

1% 

1% 

1% 

2% 

2% 

2% 

2% 

5% 

9% 

11% 

0% 

-1% 

0% 

0% 

-1% 

-1% 

0% 

-1% 

-1% 

-1% 

-1% 

-1% 

-2% 

-1% 

-1% 

-1% 

-1% 

-2% 

-2% 

-2% 

-2% 

-2% 

-5% 

-10% 

-9% 

Source: Calculations based on Böttcher et al. (2011) and JRC (2011b) 

If the harvest rate is decreased by 10%, only Latvia, Sweden and Finland would exceed a cap 
on credits of 3% by some 0.5, 5 and 4 Mt respectively (see Table A2.4). Only Sweden and 
Finland would exceed a cap of 5% by some 3.6 and 2.6 Mt respectively. 

Table A2.4 Possible net removals excluded from accounting at different cap values, arising from a 10% decrease in 
the harvest rate 

Emissions excluded from accounting per year at different caps on credits (MtCO2) 

Latvia 

Sweden 

Finland 

EU 

3% 

0.5 

5.1 

4.0 

9.6 

3.5% 

0.4 

4.7 

3.6 

8.8 

4% 

0.3 

4.4 

3.3 

8.0 

Source: Calculations based on Böttcher et al. (2011) and JRC (2011b) 

With  the  Durban  decision  all  increases  in  harvest  beyond  the  expected  levels  in  the  Forest 
Management reference level would be accounted for in full. 

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8.3. 

Annex III – Methodology (models and calibration) 

8.3.1.  Description of the models, their linkages and their use 

The core models used to project emissions and removals from afforestation, deforestation and 
forest  management  are  G4M  (from  IIASA)  and  EFISCEN  (from  the  European  Forest 
Institute,  EFI).  The  EUFASOM  model  is  used  to  project  emissions  and  removals  from 
cropland and grassland. Table A3.1 and Figure A3.1 below provide the essential features of 
the  main  models  involved  and  an  overview  of  the  modelling  architecture.  This  section  first 
describes  the  models  and  then  explains  how  they  have  been  linked  to  generate  projections. 
Details can be found in Böttcher et.al. (2011). 

EFISCEN  (European  Forest  Information  SCENario)  is  developed  and  applied  by  the 
European  Forest  Institute  (EFI).  It  is  a  large-scale  forest  scenario  model  that  projects  forest 
resource  development  on  regional  to  European  scales.  EFISCEN  describes  the  state  of  the 
forest as an area distribution over age- and volume-classes based on national forest inventory 
data. Transitions of areas during simulations represent different natural processes influenced 
by  management  regimes  and  changes  in  forest  area.  Management  scenarios  are  specified  at 
two  levels  in  the  model.  First,  a  basic  management  regime  defines  the  period  during  which 
thinnings  can  take  place  and  a  minimum  age  for  final  fellings.  These  act  as  constraints  for 
total harvest levels. Second, the demand for wood is specified for thinnings and final fellings 
and  EFISCEN  may  fell  the  demanded  wood  volume  if  available.  Harvest  residues  from 
thinning  and  final  fellings  can  also  be  extracted.  EFISCEN  projects  stem  wood  volume, 
increment, age-class distributions, removals, forest area, natural mortality and deadwood for 
every five year time-step. With the help of biomass expansion factors, stem wood volume is 
converted into whole-tree biomass and subsequently to carbon stocks. EFISCEN is used for 
projecting  the  net  emissions  due  to  forest  management,  afforestation  and  reforestation 
activities. During the last years initial forest inventory have been updated with new inventory 
data for a number of countries. The model was used to project the forest carbon sinks. 

G4M  (Global  Forest  Model)  estimates  the  annual  above  ground  wood  increment  and 
harvesting costs. By comparing the income of managed forest (difference of wood price and 
harvesting costs and income by storing carbon in forests) with income by alternative land use 
on  the  same  place  a  decision  of  afforestation  or  deforestation  is  made.  G4M  is  spatially 
explicit  (currently  on  a  30"x30"  resolution).  The  model  can  use  external  information  (like 
wood prices, prescribed land-use change) from other models or data bases, which guarantee 
food security and land for urban development or account for disturbances. As outputs, G4M 
produces estimates of land-use change, carbon sequestration/emissions in forests, impacts of 
carbon  incentives  (e.g.,  avoided  deforestation),  and  supply  of  biomass  for  bio-energy  and 
timber. The model includes age classes with one year width. Afforestation and disasters cause 
an uneven age-class distribution over a forest landscape. The model performs final cuts so that 
all  age  classes  have  the  same  area  after  one  rotation  period.  During  this  age  class 
harmonization time the standing biomass, increment and amount of harvest is fluctuating due 
to changes in age-class distribution and afterwards stabilizing. The main forest management 
options considered are species selection, variation of thinning and choice of rotation length. 
G4M does not model species explicitly but a change of species can be emulated by adapting 
net primary productivity (NPP), wood price and harvesting costs. The rotation length can be 
individually  chosen  but  the  model  can  estimate  optimal  rotation  lengths  to  maximize 
increment,  maximize  stocking  biomass  or  maximize  harvestable  biomass.  The  model  was 
used to project the forest carbon sinks and the carbon sink enhancement potential and costs 
(forest management, afforestation and deforestation. 

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resource  endowments,  production  capacities, 

EUFASOM simulates detailed land use and land management adaptations, commodity market 
and trade equilibrium adjustments, and environmental consequences in response to political, 
technical,  societal,  and  environmental  change  scenarios  related  to  agriculture,  forestry,  and 
nature  conservation.  EUFASOM  represents  the  Member  States  of  the  European  Union  but 
also includes commodity supply and demand functions for non-EU regions covering the entire 
globe. Likely land use impacts are determined through constrained welfare maximization. The 
objective  function  maximizes  the  net  economic  surplus  from  all  agricultural  and  forestry 
markets  and  includes  the  impact  of  policy  incentives  and  disincentives.  Technological 
inter-temporal 
opportunities,  physical 
relationships,  and  political  regulations  form  important  constraints  of  EUFASOM.  Model 
output consists of optimal land use allocations and associated management intensities, related 
environmental  impacts,  regional  resource  usage,  commodity  supply,  equilibrium  market 
prices,  and  trade  volumes  of  the  agricultural  and  forest  commodities  covered  in  the  model. 
Technological  options  include  agricultural  and  forest  management  alternatives,  livestock 
production, bioenergy and forest industry processing. The objective function incorporates all 
major drivers for these changes, i.e. cost coefficients for land use and commodity processing 
alternatives,  adjustment  costs  for  major  land  use  changes,  market  price  changes  for 
commodities  and  production  factors,  trade  costs,  political  incentives  and  disincentives,  and 
terminal values for standing forests. EUFASOM was used to project the net emissions from 
cropland  and  grassland  for  each  EU  country  and  to  assess  the  potential  and  costs  for 
increasing the agricultural carbon sink. 

Table A3.1. Essential features of the core models involved in the projection of LULUCF emissions and removals and 
estimates of potential sink enhancement and their cost. 

Model 

Description 

G4M 

EFISCEN 

The  Global Forest Model (G4M)  provides spatially explicit estimates of annual above- and  belowground  wood 
increment, development of above- and belowground forest biomass and costs of forestry options such as forest 
management, afforestation and deforestation by comparing the income of alternative land uses. 

The European Forest Information Scenario Model (EFISCEN) is a large-scale model that assesses the supply of 
wood and biomass from forests and projects forest resource development on regional to European scale, based 
on  forest  inventory  data.  EFISCEN  provides  projections  on  basic  forest  inventory  data  (stemwood  volume, 
increment, age-structure), as well as carbon in forest biomass and soil. 

EUFASOM 

EUFASOM  simulates  detailed  land  use  and  land  management  adaptations,  in  this  project  limited  to  cropland 
and grazing land management. The model represents the Member States of the European Union in detail. Land 
use  impacts  are  determined  through  constrained  welfare  maximization.  Crop  yields,  water  and  fertilizer 
requirements, and environmental impacts are simulated with the Environmental Policy Integrated Climate (EPIC) 
model. 

The projections build on macro projections of GDP and population which are exogenous to 
the  models  used  and  consistent  with  PRIMES  information  (see  Figure  A3.1  below).  They 
reflect the recent economic downturn, followed by sustained economic growth resuming after 
2010.  The  GLOBIOM56  model  uses  these  projections  to  translate  them  into  demand  for 
timber.57 Bio-energy demand and supply was  projected by the PRIMES biomass model and 

56 

57 

GLOBIOM is a global static partial equilibrium model integrating the agricultural, livestock, bioenergy 
and forestry sectors with the aim to give policy advice on global issues concerning land use competition 
between the major land-based production sectors.  
See main assumptions in Capros et al. (2010) . 

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other timber demand by GLOBIUM combined with EFISCEN and G4M.58 The EU biomass 
supply  model  is  consistent  with  the  baseline  and  reference  scenarios  of  the  PRIMES  large 
scale energy model for Europe.59 It is an economic supply model that computes the optimal 
use of resources and investment in secondary and final transformation, so as to meet a given 
demand of final biomass energy products, driven by the rest of sectors as in PRIMES model. 
The  primary  supply  of  biomass  and  waste  has  been linked with resource origin, availability 
and  concurrent  use  (land,  forestry,  municipal  or  industrial  waste  etc).  The  total  primary 
production levels for each primary commodity are restricted by the technical potential of the 
appropriate primary resource. 

Figure A3.1. Flowchart of information exchange between models 

For  the  baseline  and  reference  scenarios,  the  economic  land  use  models  (G4M  and 
GLOBIOM)  project  domestic  production  and  consumption,  net  exports  and  prices  of  wood 
products and changes in land use for EU member states and other world regions. The sector 
specific information from the economic models is used by the forest models (EFISCEN and 
G4M) to project GHG emissions and removals. This requires a complex interaction between 
models for different sectors with different geographical resolutions and degrees of detail (see 
Figure)  Data  exchange  from  EFISCEN  to  EU-FASOM  includes:  areas  and  volumes  by  age 
class, species, owner for 2005, rotation lengths and theoretical harvest potentials. EFISCEN 
deliveres  to  G4M  data  on  wood  densities  as  weighted  average  by  country.  GLOBIOM 
receives  from  G4M  data  on  forest  management  parameters,  initial  NPV  of  agricultural  land 
and  initial  wood  prices.  After  baseline  calculations  in  GLOBIOM  to  integrate  global 
competition of world regions for different commodities the model provides country level total 
wood  demand  to  the  two  detailed  forestry  models  G4M  and  EFISCEN.  In  addition,  G4M 

58 

59 

See 
http://www.e3mlab.ntua.gr/e3mlab/PRIMES%20Manual/THE_NEW_PRIMES_BIOMASS_MODEL.p
df 
See http://www.e3mlab.ntua.gr/e3mlab/PRIMES%20Manual/The_PRIMES_MODEL_2008.pdf 

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receives from GLOBIOM information on the development of land and wood prices. Finally, 
G4M sends data on the areas of afforestation and deforestation to EFISCEN. 

8.3.2.  Description of uncertainties in the modelling results 

The original model results for each MS are shown in Böttcher et al. (2011). That report also 
provides a detailed overview of the original model-based predicted impacts, their influences 
and the underlying assumptions and data. The major elements that affect the uncertainty and 
sensitivity  of  the  results  can  be  summarized  as  follows  (see  Böttcher  et  al.  (2011)  for  more 
details). The modelling approach used is to a large degree data-driven. Hence, the quality of 
the  results  presented  depends  heavily  on  the  quality  of  the  datasets  that  were  used.  Efforts 
were made to harmonise data on forest area, basic national forestry inventory data (area, age-
class structure, growing stock, increment), wood density, biomass expansion factors and wood 
removals between models and where possible with estimates and data from member states in 
number  of  bilateral  meetings  and  e-mail  exchanges  with  MSs.  Harmonisation  with  datasets 
used  by  MSs  was  not  always  possible  in  all  cases  and  differences  in  datasets  used  explain 
differences  in  reported  and  projected  emissions  and  removals.  For  instance,  historical 
roundwood  removals  were  used  to  initialize  the  forest  models  and  to  estimate  the  future 
roundwood removals. A comparison of FAO data on historical wood removals with national 
statistics  included  in  the  EU  submission  to  UNFCCC  showed  significant  differences. 
Sensitivity  analysis  indicated  that  projections  were  rather  sensitive  to  the  assumed  harvest 
rates. Hence, such differences can have substantial impacts on the projected CO2 emissions or 
removals.  Given  these  uncertainties  in  the  national  inventories  and  differences  between 
models and inventories, the setting of absolute targets (in relation to a past year) such as done 
for  the  ESD  runs  the  risk  that  targets  are  not  met  (while  infeasible)  or  costs  are  higher  (or 
lower) than expected. 

Furthermore, the evolution of the future forest management sink in MSs depends on several 
elements. It is uncertain which role biomass will play in the EU’s energy portfolio. For 2020 
MSs  have  presented  their  views  and  projections  in  their  National  Renewable  Action  Plans. 
For  2030  (and  also  2020)  the  demand  for  2030  depends  to  some  degree  on  the  economic 
viability of second generation type of technologies that would utilize wood in an efficient way 
and  the  share  of  other  renewable  and  non-renewable  energy  sources.  Total  wood  demand 
depends further on the degree other wood uses will grow and this demand change might also 
be negative if the increased wood demand for bio-energy would result in higher overall wood 
prices. Improving resource efficiency through increased recycling rates can also contribute to 
limit the growth in demand of wood. The impact on the EU forest carbon stocks depends on 
whether the demand growth will be met by internal production or increased imports. Whether 
there is an impact on the forest sink or not depends further on whether increased production is 
achieved  through  changes  in  forest  management  or  rather  through  increased  afforestation. 
Given  the  relatively  high  baseline  afforestation  rates  MSs  and  rather  long  rotations  in  new 
forests including species with rather moderate growth rates, significant additional supply from 
afforestation is negligible.  

In  addition,  future  roundwood  production  is  based  on  projections  by  GLOBIOM  and 
PRIMES.  The  projection  by  these  two  models  depends  on  the  same  macro-economic 
developments. Furthermore, it was ensured that GLOBIOM reproduced the same numbers on 
bio-energy  production.  However,  the  development  of  the  forest  sector  was  not  harmonized 
between  the  models.  This  could  lead  to  discrepancies  in  the  availability  of  e.g.  black  liquor 
and/or  wood  waste  between  GLOBIOM  and  PRIMES.  Further  harmonisation  between 
PRIMES  and  GLOBIOM  could  change  the  projections  of  CO2  emission  or  removals  by 

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forests. The GLOBIOM model projected future wood production for the entire EU. In doing 
so it was assumed that production of wood for material use in all EU countries will increase 
by the same factor. However, the rate is likely to vary between countries. For some countries 
“ceilings” on maximum wood removals might have be built in to constrain the production of 
wood  to  reflect  environmental,  technical,  social  and  economical  constraints  that  limit  wood 
supply.  The  models  EFISCEN  and  G4M  have  been  developed  mainly  for  even-aged  forests 
and application of the models to situations other than even-aged forests should be done with 
great  care.  For  shorter  periods,  simulation  of  increment  and  growing  stock  are  probably 
reasonable,  but  the  age-class  distribution  will  be  unreliable  and  this  will  influence  growth 
rates and growing stocks at the longer term. 

Finally,  the  impact  of  growth  changes  and  large-scale  disturbances  due  to  environmental 
and/or  climate  change  on  the  estimated  CO2  emissions  and  removals  were  not  included. 
Growth may decrease in Southern Europe due to reduced water availability, whereas growth 
in  Northern  regions  may  increase  much  more.  This  will  affect  in  changes  in  future  CO2 
removals and emissions. Disturbances were also not included in the analysis, but could have 
an  important  impact.  The  impact  of  growth  changes  and  large-scale  disturbances  on  the 
development  of  the  LULUCF  sector  is  difficult  to  model.  The  model  approach  does  not 
account for natural forest disturbance, i.e. losses through fire, storm and insects. Especially in 
boreal  and  Mediterranean  forest  ecosystems  fire  plays  a  major  role  in  the  carbon  cycle.  By 
omitting  fire  losses,  both  terms  might  be  biased:  forest  productivity  and  net  carbon  storage. 
To  account  for  fire  implies  also  a  consideration  of  likely  management-fire  feedbacks. 
Management  can  both  enhance  and  suppress  the  natural  fire  regime,  through  anthropogenic 
timber  exploitation  and  debris 
ignition,  fire  suppression  and  fire  management  by 
abandonment.  This  does  not  allow  a  simple  ex-post  calibration  or  correction  for  fire  losses. 
Storm events and insect damage affect the carbon balance in a different way. The biomass is 
not  lost  but  timber  quality  drops  and  harvest  schedule  is  shifted.  At  the  regional  level 
however, shifts in the harvest schedule re likely to be balanced through market mechanisms. 
More intense harvest in the affected area is thus compensated by reduced timber extraction in 
intact regions. 

8.3.3.  Description of the calibration method used 

To  align  differences  between  models  and  inventories  the  original  model  results  were 
calibrated. The calibration was carried out by the JRC and is referred to as JRC (2011b) in the 
main text and is consistent with the EU's submission of forest management reference levels to 
the UNFCCC.60 

In  order  to  ensure  consistency  between  models’  results  and  historical  data  on  net  GHG 
emissions reported to the UNFCCC by countries, the emissions and removals estimated by the 
models for the entire time series (up to 2020) were "calibrated" (i.e. adjusted) using historical 
data from the country for the period 2000-2008 (for which we had both data from the GHG 
inventories and data projected by the models). To this end, an "offset" was calculated for two 
components: 

•  biomass: offset calculated as difference between the average of a country’s emissions and 
removals from biomass for the period 2000-2008 and the average of the models’ estimated 
emissions and removals from biomass for the period 2000-2008 

60 

See http://unfccc.int/meetings/ad_hoc_working_groups/kp/items/5896.php . 

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•  non-biomass  pools  and  GHG  sources:  offset  calculated  as  the  sum  of  non-biomass  pools 
and GHG sources as reported by the country for the period 2000-2008, and not estimated 
by models. 

The calibrated average of the models, which is used for the setting of the reference level (for 
the  credit  calculation),  is  obtained  by  adding the  total  offset  (biomass  offset  +  non-biomass 
pools and GHG sources offset) to the models’ average. In other words, models' results were 
adjusted to match the average historical data provided by each country for the period 2000-
2008.  This  ensures  consistency  between  country  data  and  models’  data  in  terms  of:  (i) 
absolute  level  of  emissions  and  removals  from  biomass,  i.e.  the  calibration  „reconciles” 
differences  in  estimates  which  may  be  due  to  a  large  variety  of  factors,  including  different 
input  data,  different  parameters,  different  estimation  methods  (e.g.,  some  country  uses  a 
"stock-change approach", while the models use a "gain-loss approach"); (ii) coverage of non-
biomass  pools  and  GHG  sources.  The  calibration  procedure  automatically  incorporates  into 
the  projections  the  average  rate  (for  the  period  2000-2008)  of  the  GHG  impact  of  past 
disturbances, not estimated by the model (e.g. emissions from fires). 

The future trend of emissions and removals up to 2020 as predicted by the underlying models 
is not affected (but the absolute level is affected) by this calibration procedure, but only by the 
current forest characteristics (e.g. age structure) and the expected future harvest demand (be it 
for materials or energy purposes. 

This way of calibration implies that model projections are now more consistent with reported 
emission inventories (2000 to 2008). The uncertainty in the emission inventory itself (around 
35%) still exists and the fact that national emission inventories do not cover all sources is also 
not resolved. Adjusted in this way the model results are closer to reported data (EEA, 2011) 
and the difference is less than 5% in 2005 for forest management. The calibrated G4M model 
estimates  the  EU's  forest  management  sink  at  378  MtCO2,  EFISCEN  estimates  387  MtCO2 
and  the  reported  data  suggest  394  MtCO2  for  2005.  For  afforestation  and  deforestation 
uncertainty is also less than 5%.For grazing land management uncertainty is higher (10%) but 
not all countries report this. 

Still,  as  with  any  projections  there  is  uncertainty.  This  can  best  be  illustrated  for  forest 
management, the most significant activity. The calibrated G4M model projects a sink of -297 
MtCO2 in 2020 in the EU. The EFISCEN model projects -378 MtCO2. The average is -338 
MtCO2.  For  the  UNFCCC  process  10  MSs  also  made  their  own  projections.61  Combining 
these  10  estimates  with  the  model  projections  for  the  other  countries  (average  of  G4M  and 
EFISCEN model) gives a FM sink of -253 MtCO2 (the sum of FM reference levels without 
HWP). The result of these 3 projections is a mean of -313 MtCO2 and an uncertainty of +/- 58 
MtCO2 (standard deviation). The uncertainty is a factor ten higher than the reduction of 5.4 
MtCO2 that could be expected from setting a reduction target for the EU on the basis of €5 per 
tCO2. Given this uncertainty at an EU level the setting of absolute targets at an EU level runs 
the risks of not meeting the target or meeting the target at higher costs than expected certainly 
when the majority of the sink enhancement is expected to come from forest management in 
2020. Agreeing on a reduction of 5 MtCO2 could then imply doing nothing (if the sink is 58 
MtCO2 higher than expected) or having to increase the sink by 63 MtCO2 in 2020 which is 
not feasible or would require very high marginal costs (above €150/t CO2), see Böttcher et al. 
(2011). 

61 

http://unfccc.int/files/meetings/ad_hoc_working_groups/kp/application/pdf/awgkp_eu_2011_rev.pdf  

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The figure below shows the results of the models for forest management before calibration. 

Figure A3.2. Model results for forest management before calibration  

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The figure below shows the results after calibration to fit data for the period 2000-2008. 

Figure A3.3. Model results for forest management after calibration 

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8.4. 

Annex IV – Model results: projected emissions / removals and abatement costs 

8.4.1.  Projected emissions and removals (Reference scenario) 

This  annex  presents  the  model  predictions  of  emissions  and  removals  in  the  "reference 
scenario"  for  the  period  leading  up  to  2020.  A  description  of  the  assumptions  underpinning 
the scenario is given by Böttcher et al. (2011), see also Capros et al (2010). The models and 
their calibration are explained in Annex III to this report and in Böttcher et al. (2011). 

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8.4.1.1.  Models average  

Table A4.1. Net emissions and emissions for the EU-27 in the reference scenario (models average) (KtCO2/year) 

Average  

 Activity 

2005 (reported) 

2010 

2015 

2020 

2013-20 

Afforestation/reforestation 

-40569 

-43267 

-50727 

-60128 

Deforestation 

25237 

18056 

23990 

26954 

-53559 

24617 

Forest management 

-383469 

-363818 

-347351 

-325996 

-340721 

Cropland management 

66089 

59038 

58282 

54609 

Grazing land management 

-30872 

-33081 

-33081 

-33081 

56961 

-33081 

Total LULUCF 

-363584 

-363072 

-348887 

-337641 

-345782 

Note: A minus sign denotes net emissions and plus sign net removals. 

Source: Böttcher et al. (2011) and JRC (2011b) 

8.4.1.2.  G4M and EUFASOM 

Table A4.2. Net emissions and emissions for the EU-27 in the reference scenario (G4M + EUFASOM) (KtCO2/year) 

Average  

 Activity 

2005 (reported) 

2010 

2015 

2020 

2013-20 

Afforestation/reforestation 

-40569 

-43267 

-50727 

-60128 

Deforestation 

25237 

18056 

23990 

26954 

-53559 

24617 

Forest management 

-383469 

-343959 

-313983 

-285295 

-305759 

Cropland management 

66089 

59038 

58282 

54609 

Grazing land management 

-30872 

-33081 

-33081 

-33081 

56961 

-33081 

Total LULUCF 

-363583 

-343213 

-315518 

-296940 

-310820 

Note: A minus sign denotes net emissions and plus sign net removals. 

Source: Böttcher et al. (2011) and JRC (2011b) 

8.4.1.3.  EFISCEN and EUFASOM 

Table  A4.3.  Net  emissions  and  emissions  for  the  EU-27  in  the  reference  scenario  (EFISCEN  +  EUFASOM) 
(KtCO2/year) 

Average 

 Activity 

2005 (reported) 

2010 

2015 

2020 

2013-20 

Afforestation/reforestation 

-40569 

-43267 

-50727 

-60128 

Deforestation 

25237 

18056 

23990 

26954 

-53559 

24617 

Forest management 

-383469 

-383677 

-380718 

-366696 

-375682 

Cropland management 

66089 

59038 

58282 

54609 

Grazing land management 

-30872 

-33081 

-33081 

-33081 

56961 

-33081 

Total LULUCF 

-363583 

-382931 

-382254 

-378341 

-380743 

Note: A minus sign denotes net emissions and plus sign net removals. 

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Source: Böttcher et al. (2011) and JRC (2011b) 

8.4.1.4.  Accounting results for individual MSs and the EU-27(models average) 

See table on next page

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Table A4.4. 

Credits (KtCO2 per year) for three accounting options  

Accounting 
option  

Accounting 
option (a) 

Accounting option (b) 

Accounting option (c) 

Small changes 

Likely  outcome 
negotiations 

in 

the  UNFCCC 

UNFCCC+ 

(I) models 

(II) mix 

(I) models 

(II) mix 

Austria 

Belgium 

Bulgaria 

Cyprus  

Czech Republic 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Ireland 

Italy 

Latvia 

Lithuania 

Luxembourg 

Malta 

Netherlands 

Poland 

Portugal 

Romania 

Slovakia 

Slovenia 

Spain 

Sweden 

UK 

EU27 

Cumulative 
(2013 2020)

-3953 

-671 

284 

-1 

-114 

-92 

-1326 

-4155 

-13763 

-10542 

-570 

349 

-2989 

-7946 

-2167 

-274 

-28 

0 

-184 

-7409 

-4292 

-1251 

-16 

247 

-6984 

-7519 

-3292 

-1258 

-652 

2830 

-4 

1309 

-1041 

-2199 

-1564 

-4253 

-3687 

-274 

961 

-2576 

7008 

1051 

67 

35 

0 

10 

-7495 

-4969 

2483 

-390 

2112 

1457 

-2833 

-617 

-78658 

-14487 

-6292666 

-115892 

-5083 

-651 

944 

155 

1310 

-1481 

-2199 

-1833 

-4253 

-42780 

-415 

961 

-3603 

7008 

-678 

95 

-90 

49 

-74 

-18867 

-5645 

1487 

-390 

761 

1586 

-2833 

-9263 

-85781 

-686248 

-1363 

-726 

3766 

-4 

761 

-1041 

-3171 

-1457 

-6834 

-4217 

-760 

1053 

-2678 

-3887 

888 

-232 

53 

0 

-54 

-8307 

-4969 

3817 

-308 

2324 

684 

-3990 

-4307 

-34958 

-279667 

-5188 

-726 

1881 

155 

762 

-1481 

-3171 

-1726 

-6834 

-43310 

-901 

1052 

-3705 

-3888 

-841 

-204 

-72 

49 

-139 

-19679 

-5645 

2821 

-308 

972 

813 

-3990 

-12953 

-106253 

-850023 

EN 

99 

   EN 

 
 
 
 
Note:  A  minus  sign  denotes  net  credits  and  a  plus  sign  net  debits.  Credits  for  forest  management  are  calculated  in  two 
different ways. In both cases the impact of the cap on credits of 3.5% of base year emissions is included: 

(1) ( Modeled emissions and removals in reference scenario) – (modeled emissions and removales in the baseline scenario) 

(2)  (  Modeled  emissions  and  removals  in  reference  scenario)  –  (forest  management  reference  levels  in  LULUCF  decision 
CMP.7).  

Source: Calculations based on Böttcher et al. (2011) and JRC (2011) 

Differences  between  columns  (I)  and  (II)  are  mainly  due  to  different  assumptions  in  future 
harvest  rates  between  model  projections  and  the  country's  projections  used  to  set  forest 
management  reference  levels.  Some  MS  (e.g.,  Germany,  Poland,  Slovenia,  Austria,  United 
Kingdom)  used  in  their  forest  management  reference  levels  higher  future  harvest  rates  than 
assumed  by  the  G4M  and  Efiscen  models.  Differences  between  option  (c)  and  option  (b) 
reflect the impact of cropland and grazing management. The large difference between option 
(c)  and  option  (b)  for  Italy  reflects  the  potential  credits  from  grassland  management, 
essentially  due  to  the  fact  that  Italy  reported  a  large  increase  of  the  sink  in  grassland  from 
1990 to now (more than 15 MtCO2 increase). While part of this increase is explainable by the 
increased area of other wooded lands since 1990 (which Italy reports under grassland), further 
checks  may  reveal  the  need  for  some  corrections.  Abatement  costs  and  emission  reductions 
per Member State 

Table A4.5. Emission reductions and annual costs in 2020 by Member States at various carbon prices 

MS 

Austria 

Belgium 

Bulgaria 

Cyprus  

Czech Rep. 

Denmark 

Estonia 

Finland 

France 

Germany 

Greece 

Hungary 

Ireland 

Italy 

Latvia 

Lithuania 

Luxembourg 

Malta 

Netherlands 

Poland 

Portugal 

Emissions reduction (MtCO2) at different 
prices 

Annual cost (mln €) at different prices 

€5/tCO2 

€15/tCO2 

€30/tCO2 

€5/tCO2 

€15/tCO2 

€30/tCO2 

0.0 

0.0 

1.3 

0.0 

0.3 

0.1 

0.7 

1.3 

0.3 

0.0 

0.0 

0.1 

0.0 

0.5 

0.2 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

0.0 

1.3 

0.0 

0.4 

0.1 

0.7 

1.9 

0.6 

0.0 

0.0 

0.1 

0.0 

0.5 

0.3 

0.2 

0.0 

0.0 

0.0 

0.0 

0.0 

0.2 

0.1 

2.4 

0.0 

0.4 

0.1 

0.9 

2.3 

0.6 

0.5 

0.0 

0.4 

0.0 

0.5 

0.3 

0.2 

0.0 

0.0 

0.0 

0.2 

0.1 

0.0 

0.0 

0.6 

0.0 

1.7 

0.6 

3.7 

6.7 

1.3 

0.0 

0.0 

0.3 

0.0 

2.4 

1.1 

0.9 

0.0 

0.0 

0.0 

0.0 

0.2 

0.0 

0.0 

0.6 

0.0 

2.2 

0.6 

3.7 

15.7 

6.9 

0.0 

0.0 

0.3 

0.0 

2.4 

2.4 

0.9 

0.0 

0.0 

0.0 

0.4 

0.2 

6.1 

4.1 

4.1 

0.0 

2.2 

4.1 

7.3 

24.2 

6.9 

16.3 

0.0 

6.3 

0.0 

2.4 

2.4 

0.9 

0.0 

0.0 

0.0 

5.9 

3.3 

EN 

100 

   EN 

 
 
Romania 

Slovakia 

Slovenia 

Spain 

Sweden 

UK 

EU27 

0.0 

0.2 

0.0 

0.1 

0.0 

0.1 

5.4 

0.5 

0.2 

0.0 

0.1 

0.0 

0.1 

7.0 

0.5 

0.3 

0.0 

0.1 

0.4 

0.2 

0.0 

1.0 

0.0 

0.4 

0.0 

0.6 

4.8 

1.0 

0.0 

0.4 

0.2 

0.6 

4.8 

3.7 

0.0 

0.4 

11.4 

4.1 

10.7 

26.4 

58.2 

150.9 

Note: Costs are in €2008. 

Source: Böttcher et al. (2011). 

8.4.2.  Distribution of costs 

Table A4.6. Distribution of (net) abatement costs (in million € in 2008 prices) 

Option 2.II 

Option 3 

Include LULUCF as a separate framework  

Include LULUCF in the ESD 

Accounting 
option 

Austria  

Belgium  

Bulgaria  

Cyprus  

Czech Rep. 

Denmark  

Estonia  

Finland  

France  

Germany  

Greece  

Hungary  

Ireland  

Italy  

Latvia  

Lithuania  

Luxembourg  

Malta  

Netherlands  

Poland  

Portugal  

Romania  

Slovakia  

Slovenia  

Spain  

Sweden  

UK  

EU-27 

(Target) 

(a) 

(b) 

(c) 

0 

0 

6 

0 

2 

0 

4 

11 

4 

0 

0 

0 

0 

2 

2 

1 

0 

0 

0 

0 

0 

5 

1 

0 

0 

0 

1 

0 

0 

6 

0 

2 

0 

4 

7 

1 

0 

0 

0 

0 

2 

1 

1 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

1 

0 

0 

6 

0 

2 

0 

4 

7 

1 

0 

0 

0 

0 

2 

1 

1 

0 

0 

0 

0 

0 

0 

1 

0 

0 

0 

1 

(a) 

-8 

-1 

0 

0 

0 

0 

-3 

-9 

-29 

-22 

-1 

1 

-6 

-16 

-1 

-2 

1 

0 

0 

-15 

-9 

-8 

0 

1 

-14 

-16 

-7 

40 

27 

27 

-166 

(b) 

-5 

-3 

12 

0 

6 

-1 

-14 

-7 

-24 

-16 

-1 

4 

-11 

29 

11 

-3 

2 

0 

0 

-32 

-17 

8 

-1 

9 

19 

-18 

-3 

-55 

(c) 

-5 

-3 

15 

0 

4 

-4 

-17 

-6 

-32 

-17 

-3 

4 

-11 

-17 

10 

-4 

2 

0 

0 

-33 

-20 

7 

-1 

9 

3 

-21 

-17 

-156 

EN 

101 

   EN 

 
  
  
Source: Calculations based on an updated version of Böttcher et al. (2011), JRC (2011b) reflecting the UNFCCC review mid 
2011 and results of the PRIMES-GAINS models. 

8.5. 

Annex V – Discarded options 

This annex outlines the policy and accounting options that have not been considered in detail 
in this impact assessment and the reasons why. 

8.5.1.  Discarded policy options 

The option of including LULUCF in the EU ETS has not been considered in detail in this 
impact assessment. It has already been the subject of two studies by the Commission.62 Both 
argue against including LULUCF in the EU ETS for the following reasons (applicable to the 
use of LULUCF for project off-sets such as CDM and/or as a fully included sector): 

•  There  are  considerable  risks  related  to  the  temporary  and  reversible  nature  of  LULUCF 
activities  in  a  company-based  trading  system  designed  to  handle  permanent  emissions 
reductions. No modalities have been developed to mitigate the impacts of non-permanence, 
high  uncertainties  (including  the  likelihood  of  necessary  recalculations),  jeopardising  the 
environmental effectiveness of the EU ETS. 

•  Simplicity, transparency and predictability of the EU ETS would be reduced considerably. 

•  The  inclusion  of  LULUCF  in  the  EU  ETS  would  require  land  holdings  to  be  subject  to 
monitoring rules. This would require a quality of monitoring and reporting at the holding 
level that is comparable to the monitoring and reporting of emissions from the installations 
currently  covered  by  the  system.  The  currently  available  guidance  for  monitoring 
LULUCF (IPCC, 2003; IPCC, 2006) has been designed for national inventory systems and 
are  not  applicable  to  monitoring  at  the  farm/land  holding  level.  This  has  three  major 
implications: 

(1) A whole new monitoring system and protocol would need to be developed for use 

on all types of land, a resource and time demanding process.  

(2) As  LULUCF  monitoring  systems  and  approaches  are  scale-dependent,  the 
compatibility/consistency  of  farm/holding  level  estimates  with  those  of  national 
data  could  not  be  guaranteed,  and  therefore  would  require  a  separate  system  to 
handle the unavoidable discrepancies. 

(3) Because of the much higher resolution of monitoring, the cost of the system (both 
monitoring  and  administrative)  would  be  orders  of  magnitude  more  expensive 
than  that  of  a  national  inventory,  and  significantly  higher  than  monitoring  and 
transaction costs in the current EU ETS sectors (see e.g. Annex I for a comparison 
of uncertainties between sectors). 

62 

Impact Assessment of the Directive of the European parliament and of the Council amending Directive 
2003/87/EC  so  as  to  improve  and  extend  the  EU  greenhouse  gas  emission  allowance  trading  system. 
{COM(2008)  16  final}{SEC(2008)  53}  and  Extended  Impact  Assessment  on  the  Directive  of  the 
European Parliament and of the Council amending Directive establishing a scheme for greenhouse gas 
emission  allowance  trading  within  the  Community  in  respect  of  the  Kyoto  Protocol's  project  based 
mechanisms {COM(2003) 403 final}{SEC(2003) 785} 

EN 

102 

   EN 

 
                                                 
•  Because of the relatively high variability of credits/debits potentially affecting the system 
(and quantity in the case of project off-sets), the functioning of the carbon market might be 
undermined. 

These findings have subsequently been confirmed by an additional review (Watterson et al., 
2011)  which,  based  on  the  EU  ETS  legislation,  looked  at  implications  of  incorporating 
LULUCF directly within the scheme. An overview of the key features of the legislation and 
related difficulties in integrating LULUCF is also provided in that report.  

8.5.1.1.  Splitting  LULUCF  according  to  activities  for  the  inclusion  in  different  policy 

frameworks 

The  mandate  requires  the  Commission  to  see  if  and  how  the  sector  can  be  included  in  the 
EU's  GHG  reduction  commitment.  It  may  be  possible  to  argue  that  different  LULUCF 
activities  could  be  addressed  under  different  frameworks  just  like  the  energy  and  industry 
sectors are currently divided between the ETS and the ESD. For  instance,  new  guidance on 
reporting  has  been  produced  by  the  IPCC  (2006)  in  which  non-CO2  GHG  emissions  from 
agriculture  and  GHG  emissions  from  LULUCF  are  merged  into  one  sector.  However,  this 
guidance  has  yet  to  be  adopted  by  the  UNFCCC  and  the  EU  has  advocated  for  continued 
reporting  according  to  the  present  sub-sectors.  As  no  compelling  reason  for  dividing  the 
sector has been found, this option was not considered further. 

8.5.2.  Discarded accounting options  

The following accounting options have been discarded for the reasons given below: 

•  Gross/Net accounting without constraints or with a cap. As in the case of the current KP 
rules, this accounting approach does not reflect anthropogenic emissions and removals as it 
involves accounting emissions and removals that occur naturally in the commitment period 
without comparison to a reference year/period. The accounting results therefore represent a 
windfall and limits the incentives for mitigation efforts since the noise from natural factors 
is  too  large  for  human  interventions  to  be  detected.  Such  incentives  would  be  further 
limited with the addition of a cap beyond which no changes will register in the accounting. 

•  Net/Net accounting for forest management for relative to a single base year or historical 
period. As noted above, emissions and removals in forests depend on a number of natural 
(regional/geographical)  circumstances  such  as  variations 
in  growing  conditions 
(temperature, precipitation and droughts) and natural disturbances (storms, fires) as well as 
past  and  present  management  practices  (rotation  lengths,  which  affect  the  distribution  of 
age  classes  in  forest  stands  and  therefore  the  rate  of  removals).  A  single  base  year  or 
historical  period  is  not  able  to  reflect  these  factors  and  resulting  cyclical  impacts  on 
emissions  and  removals  or  their  inter-annual  variations  (see  Figure  3  in  the  main  text). 
Instead,  such  an  approach  would  create  a  random  impact  on  accounting.  Figure  A5.1 
illustrates  this  point  by  showing  the  effects  on  accounting  of  forest  management  for  a 
fictive  commitment  period  of  1990-2008  (reported  data)  by  changing  the  base  year  from 
1990 to 1991. The effects of management practices are limited between two years, yet the 
differences in accounting would be as high as 70% in terms of debits / credits.  

•  Inclusion  of  wetland  or  rewetting  and  drainage  on  land  with  organic  soil.  The  activity 
relating to wetland management was defined in the negotiations under the KP in Durban in 
December  2011,  but  the  IPCC  Guidance  (IPCC,  2006)  on  reporting  of  Wetlands  has  not 

EN 

103 

   EN 

 
yet been adopted by Parties to the UNFCCC (earlier IPCC guidance does not fully address 
Wetland).  In  addition,  a  mandatory  inclusion  of  agricultural  and  forestry  activities  (and 
their soils) would implicitly cover around 90% of emissions from organic soils in the EU 
(JRC,  2011a).  The  activity  should  however  be  considered  for  mandatory  inclusion  in 
subsequent commitment periods.  

Figure A5.1. Illustration: Impact on accounting of changing from 1990 to 1991 as a base year (using reported data in 
1990 to 2008 as a fictive commitment period)  

o
w

t

w
t
b
e
g
n
a
h
c

f
o
t
l

u
s
e
r

a

s
a

s
t
i

b
e
d
/
s
t
i

d
e
r
c

n

i

e
g
n
a
h
C

s
r
a
e
y

e
s
a
b
t
n
e
c
a
j

d
a

80%

70%

60%

50%

40%

30%

20%

10%

0%

0

5

10

15

20

25

30

Note: Each observation shows the impact on accounting for a MS. 

Source: Based on EEA (2011) 

EN 

104 

   EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
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