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Harmonization of biomass resource assessments, Volume I, Best Practices and Methods Handbook

Authors:
  • BTG Biomass Technology Group B.V.

Abstract

This handbook has the purpose to promote harmonisation in the development of biomass resource assessments. It provides best practice methods for determination of biomass resource potentials, and gives guidance for transparent presentation of results by providing terms and definitions needed for the execution and presentation of biomass resource assessments. Methods are provided for four categories of biomass types: (1) forest biomass, (2) energy crops, (3) agricultural residues and (4) organic waste. Furthermore, five types of methods are identified: statistical methods, spatially explicit methods, cost-supply methods, energy-economics and energy system model methods, and integrated assessments. For each of the before-mentioned biomass types, the handbook shows how these methods can be applied. Furthermore, the handbook provides a detailed overview of sustainability aspects that can be implemented in future biomass assessments.
Harmonization of biomass resource assessments
Volume I
Best Practices and Methods Handbook
Del. No:
Issue/Rev:
Date:
D 5.3
1.0
November 2010
Responsible partner:
Authors:
BTG Biomass Technology Group B.V.
M.W. Vis, BTG
D. van den Berg, BTG
And others (see page 3)
Confidentiality: Public
BEE project is funded by the European Commission under the Framework Programme 7 within the
“Energy Thematic Area” and contributes to “Harmonisation of biomass resource assessment” activities
which focus on assessing and optimising theavailability of biomass resources.
FP7 GRANT AGREEMENT N˚: 213417
BEE Best Practices and Methods Handbook 2
Coordination: FELIS - Department of Remote Sensing and Landscape Information Systems
University of Freiburg
Address: Tennenbacher Str. 4, D-79085 Freiburg, Germany;
Website: http://www.felis.uni-freiburg.de
Contact Persons:
Prof. Dr. Barbara Koch, E-Mail: barbara.koch@felis.uni-freiburg.de
PD Dr. Matthias Dees, E-Mail: matthias.dees@felis.uni-freiburg.de
Partners:
Website: http://www.eu-bee.info
BEE Best Practices and Methods Handbook 3
Authors list (continued from page 1)
M.P. Anttila METLA - Finnish Forest Research Institute
H. Böttcher IIASA - International Institute for Applied Systems Analysis
M. Dees University of Freiburg
J. Domac University of Zagreb
I. Eleftheriadis CRES - Centre for Renewable Energy Sources
V. Gecevska MAGA - Macedonian Geothermal Association
V. Goltsev EFI - European Forest Institute
K. Gunia EFI - European Forest Institute
D. Kajba University of Zagreb
B. Koch University of Freiburg
S. Köppen IFEU Institut für Energie und Umweltforschung
G. Kunikowski EC BREC - Instytut Paliw i Energii Odnawialnej
A.H.S. Lehtonen METLA - Finnish Forest Research Institute
S. Leduc IIASA - International Institute for Applied Systems Analysis
D. Lemp University of Freiburg
M. Lindner EFI - European Forest Institute
J. Mustonen METLA - Finnish Forest Research Institute
T. Paappanen VTT - Technical Research Centre of Finland
J.M. Pekkanen EFI - European Forest Institute
C.I.S. Ramos University of Hamburg
N. Rettenmaier IFEU Institut für Energie und Umweltforschung
U.A. Schneider University of Hamburg
A. Schorb IFEU Institut für Energie und Umweltforschung
V. Segon University of Zagreb
E.M.W. Smeets Utrecht University
C.J.M. Torén Chalmers University of Technology
P.J. Verkerk EFI - European Forest Institute
T.A. Zheliezna SEC Biomass - Scientific Engineering Centre “Biomass”
S. Zibtsev NAUU National University of Life and Environmental Sciences of
Ukraine
BEE Best Practices and Methods Handbook 4
Table of content
List of Tables......................................................................................................................................7
List of Figures....................................................................................................................................9
List of Abbreviations........................................................................................................................10
1 Introduction............................................................................................................................12
1.1 Purpose and scope...................................................................................................................12
1.2 Target group............................................................................................................................12
1.3 How to use this handbook.......................................................................................................12
1.4 Best practise guidelines...........................................................................................................14
1.5 Acknowledgements.................................................................................................................14
2 General approach ..................................................................................................................16
2.1 Types of biomass ....................................................................................................................16
2.2 Types of biomass potentials....................................................................................................18
2.3 General approach to biomass resource assessments ...............................................................20
2.3.1 Resource-focused approach.......................................................................................20
2.3.2 Demand-driven approach...........................................................................................21
2.3.3 Integrated approach ...................................................................................................22
2.3.4 Overview of approaches and methods.......................................................................22
2.4 Basic and advanced biomass resource assessments................................................................23
2.5 Timeframe of biomass resource assessments..........................................................................23
2.6 Geographical coverage............................................................................................................23
2.7 Total resource assessments.....................................................................................................24
2.8 Sustainability...........................................................................................................................24
2.9 Use of units, conversion factors, etc.......................................................................................25
3 Forest biomass........................................................................................................................26
3.1 Scope and definitions..............................................................................................................26
3.2 Stemwood ...............................................................................................................................31
3.2.1 Stemwood - basic statistical method..........................................................................31
3.2.2 Stemwood - advanced statistical method...................................................................33
3.3 Primary forestry residues........................................................................................................36
3.3.1 Primary forestry residues - basic statistical method ..................................................36
3.3.2 Primary forestry residues - advanced statistical method ...........................................40
3.4 Stemwood and primary forestry residues................................................................................45
3.4.1 Stemwood and primary forestry residues - basic spatially explicit method ..............45
3.4.2 Stemwood and primary forestry residues - advanced spatially explicit method .......54
3.4.3 Stemwood and primary forestry residues - cost-supply method................................59
3.5 Secondary forestry residues....................................................................................................66
3.5.1 Secondary forestry residues - basic statistical method ..............................................66
3.5.2 Secondary forestry residues - advanced statistical method .......................................69
3.5.3 Secondary forestry residues - spatially explicit method............................................71
3.5.4 Secondary forestry residues - cost-supply method....................................................72
3.6 Conversion of biomass potentials fromvolume or mass estimates to energyunits................75
3.6.1 Primary forestry residues - conversion from volume units to energy units...............75
3.6.2 Secondary forestry residues - conversion from volume units to energy units...........75
3.7 Future research needs..............................................................................................................76
3.8 Improvement of data sources..................................................................................................76
4 Energy crops...........................................................................................................................78
4.1 Scope and definitions..............................................................................................................78
4.2 Energy crops - statistical method............................................................................................80
BEE Best Practices and Methods Handbook 5
4.3 Energy crops - basic and advanced spatially explicit method.................................................85
4.4 Energy crops - cost-supply method.........................................................................................87
4.5 Future research needs..............................................................................................................89
4.6 Improvement of data sources..................................................................................................90
5 Agricultural residues.............................................................................................................91
5.1 Scope and definitions..............................................................................................................91
5.2 Primary agricultural residues..................................................................................................92
5.2.1 Primary agricultural residues - basic and advanced statistical method......................92
5.2.2 Primary agricultural residues - basic spatially explicit method.................................96
5.2.3 Primary agricultural residues - advanced spatially explicit method..........................98
5.2.4 Primary agricultural residues - cost supply method.................................................101
5.3 Secondary agricultural residues............................................................................................103
5.3.1 Secondary agricultural residues - basic and advanced statistical method................103
5.3.2 Secondary agricultural residues - basic spatially explicit method...........................105
5.3.3 Secondary agricultural residues - advanced spatially explicit method....................106
5.3.4 Secondary agricultural residues - cost supply method.............................................108
5.4 Manure .................................................................................................................................110
5.4.1 Manure - statistical method .....................................................................................110
5.4.2 Manure - spatially explicit method..........................................................................112
5.5 Future research needs............................................................................................................113
5.6 Improvement of data sources................................................................................................114
6 Organic waste.......................................................................................................................115
6.1 Scope and definitions............................................................................................................115
6.2 Biodegradable municipal waste............................................................................................116
6.2.1 Biodegradable municipal waste - basic statistical method ......................................116
6.2.2 Biodegradable municipal waste - advanced statistical method................................119
6.2.3 Biodegradable municipal waste - basic spatially explicit method...........................121
6.2.4 Biodegradable municipal waste - advanced spatially explicit method....................122
6.2.5 Biodegradable municipal waste - cost-supply method............................................123
6.3 Landfill gas ...........................................................................................................................123
6.3.1 Landfill gas - statistical method...............................................................................123
6.3.2 Landfill gas - basic spatially explicit method..........................................................126
6.3.3 Landfill gas - advanced spatially explicit method...................................................127
6.3.4 Landfill gas - cost-supply method ...........................................................................128
6.4 Construction and demolition wood.......................................................................................130
6.4.1 Construction and demolition wood - statistical method..........................................130
6.5 Sewage sludge and gas..........................................................................................................132
6.5.1 Sewage sludge and gas - statistical method.............................................................132
6.5.2 Sewage sludge and gas - basic spatially explicit method ........................................136
6.5.3 Sewage sludge and gas - advanced spatially explicit method ................................137
6.5.4 Sewage sludge - cost-supply method.......................................................................138
6.6 Future research needs............................................................................................................139
6.7 Improvement of data sources................................................................................................140
7 Total resource assessments..................................................................................................142
7.1 Scope and definitions............................................................................................................142
7.2 Total resource assessments using statistical and spatially explicit methods.........................142
7.3 Total resource assessments using cost-supply methods........................................................142
7.4 Demand driven energy and economic modellingmethods...................................................143
7.4.1 Description of method .............................................................................................143
7.4.2 Example: the PEEP model.......................................................................................144
7.5 Integrated assessments..........................................................................................................146
7.5.1 Description of method .............................................................................................146
BEE Best Practices and Methods Handbook 6
7.5.2 Example: the EUFASOM model.............................................................................147
7.6 Future research needs............................................................................................................154
7.7 Improvement of data sources................................................................................................154
8 Sustainability........................................................................................................................155
8.1 Scope and definitions............................................................................................................155
8.1.1 Scope .......................................................................................................................155
8.1.2 Definitions...............................................................................................................156
8.2 Political framework...............................................................................................................159
8.3 Set of sustainability parameters to be included in biomass resource assessments................164
8.3.1 General remarks - Establishment of a set of sustainability parameters...................164
8.4 Inclusion of sustainability parameters in biomass resource assessments..............................168
8.4.1 How sustainability parameters influence biomass potentials..................................168
8.4.2 Sustainability in statistical, spatially explicit and cost-supply assessments............168
8.4.3 Sustainability in demand driven energy and economic modelling methods............172
8.4.4 Sustainability in integrated assessments..................................................................173
8.5 Future research needs............................................................................................................174
8.6 Improvement of data sources................................................................................................176
9 Conclusions and recommendations....................................................................................178
9.1 Conclusions...........................................................................................................................178
9.2 Recommendations for methodology development................................................................178
9.3 Recommendations for data development..............................................................................180
9.4 Recommendations for further development of the Methods Handbook...............................182
Annex 1Use of spatial data from remote sensing in biomass resource assessments ....................183
Annex 2Sustainability themes, principles, criteria and parameters for biomass resource
assessments...........................................................................................................................187
Annex 2.1 Theme: Environment...............................................................................................187
Annex 2.2 Theme: Society........................................................................................................193
Annex 2.3 Theme: Economy.....................................................................................................194
Annex 2.4 Excursus: Other Socio-economic parameters..........................................................194
Annex 3Sustainability parameters in specific biomass resource assessments methods...............197
Annex 3.1 Sustainability in resource-focused statistical assessments.......................................197
Annex 3.2 Sustainability in resource-focused spatially explicit assessments...........................201
Annex 3.3 Sustainability in demand driven cost supply assessments.......................................206
Annex 4References.............................................................................................................................211
BEE Best Practices and Methods Handbook 7
List of Tables
Table 1 Biomass types covered in the handbook .................................................................................. 17
Table 2 An overview of the combinations of approaches and methodologies that are used in the best
practice handbook ................................................................................................................... 22
Table 3 Definitions of woody biomass.................................................................................................. 27
Table 4 Other relevant definitions related to forest biomass................................................................. 28
Table 5 Assumptions and constraints related to the potentials.............................................................. 29
Table 6 Analytic abilities and possible outputs of different methods and approaches for assessments
of woody biomass potentials................................................................................................... 30
Table 7 Sections covering specific methods forest biomass ................................................................. 30
Table 8 Data sources stemwood -basic statistical method ...................................................................32
Table 9 Data sources stemwood - advanced statistical method............................................................. 35
Table 10 Data sources primary forestry residues - basic statistical method.......................................... 39
Table 11 Data sources primary forestry residues - advanced statistical method................................... 43
Table 12 Technical and environmental constraints included in the method ......................................... 45
Table 13 Suggested extraction rates for residues and stumps depending on site suitability................. 50
Table 14 Data sources stemwood and primary forestry residues - basic spatially explicit method...... 50
Table 15 Technical and environmental constraints............................................................................... 54
Table 16 Stand data obtained for each segmented stand: example from the Finnish Illustration Case. 56
Table 17 Data sources stemwood and primary forestry residues - advanced spatially explicit method57
Table 18 An example of a cost calculation for a chipper. Source: (Röser et al. 2007)......................... 61
Table 19 Data sources stemwood and primaryforestry residues - cost-supply method....................... 64
Table 20 Data sources secondary forestry residues - basic statistical method...................................... 67
Table 21 Data sources secondary forestry residues - advanced statistical method ..............................70
Table 22 Data sources secondary forestry residues - cost-supply method............................................ 74
Table 23 Lower heat values of different types of primary forestry residues........................................ 75
Table 24 Lower heat values of different types of secondary forestryresidues.....................................76
Table 25 Definitions of energy crops .................................................................................................... 79
Table 26 Data sources for estimating the potential of energy crops using the statistical method......... 82
Table 27 Data sources for estimating the potential of energy crops using the spatially explicit
analysis.................................................................................................................................... 86
Table 28 Data sources for estimating the potential of energy crops using the cost supply method...... 88
Table 29 Definitions of agricultural residues ........................................................................................ 91
Table 30 Other relevant definitions related to agricultural residues..................................................... 92
Table 31 Data sources primary agricultural residues - basic statistical method.................................... 94
Table 32 Data sources primary agricultural residues - basic spatially explicit method ........................ 97
Table 33 Data sources primary agricultural residues - advanced spatially explicit method ................. 99
Table 34 Data sources for primary agricultural residues on demand driven cost-supply method....... 102
Table 35 Data sources secondary agricultural residues - statistical method .......................................104
Table 36 Data sources secondary agricultural residues - basic spatially explicit method................... 107
Table 37 Data sources secondary agricultural residues - cost supply method .................................... 109
Table 38 Data sources for estimation of manure in resource-focused statistical method................... 111
Table 39 Data sources for estimation of manure in resource-focused spatial explicit method........... 112
Table 40 Definitions of organic waste types....................................................................................... 115
Table 41 Other relevant definitions related to organic waste.............................................................. 116
Table 42 Data sources biodegradable municipal waste - basic statistical method.............................. 117
Table 43 Data sources biodegradable municipal waste - advanced statistical method .......................120
Table 44 Data sources biodegradable municipal waste - basic spatially explicit method................... 121
Table 45 Data sources biodegradable municipal waste - advanced spatially explicit method............ 122
Table 46 Data sources landfill gas -statistical method....................................................................... 124
Table 47 Data sources landfill gas - basic spatially explicit method................................................... 126
Table 48 Data sources landfill gas -advanced spatially explicit method............................................ 128
BEE Best Practices and Methods Handbook 8
Table 49 Data sources construction and demolition wood - basic statistical method......................... 130
Table 50 Data sources sewage sludge and gas - statistical method..................................................... 133
Table 51 Data sources sewage sludge and gas - basic spatially explicit method................................ 136
Table 52 Major indices used in the biomass module ..........................................................................153
Table 53 Major variables used in the biomass module .......................................................................153
Table 54 Bioenergy processing pathways used in the biomass model................................................ 153
Table 55 Themes, principles, criteria and parameters to be included in biomass resource
assessments ........................................................................................................................... 166
Table 56 Sustainability parameters to be included in the different types of biomass resource
assessments for forestry and primary forestry residues ........................................................169
Table 57 Sustainability parameters to be included in the different types of biomass resource
assessments for energy crops and primary agricultural residues ..........................................170
Table 58 Sustainability parameters to be included in the different types of biomass resource
assessments for waste ........................................................................................................... 171
Table 59 Satellite Missions and Sensors useful for biomass assessments .......................................... 184
Table 60 Primary and Secondary remote sensing products................................................................. 185
Table 61 Overview on spatially explicit approaches that use remote sensing data............................. 186
Table 62 Impacts associated with local bioenergy production............................................................ 195
Table 63 Sustainability parameters to be included in statistical analyses for forestry and primary
forestry residues;................................................................................................................... 198
Table 64 Sustainability parameters to be included in statistical analyses for energy crops and
agricultural residues;............................................................................................................. 199
Table 65 Sustainability parameters to be included in statistical analyses for waste ........................... 200
Table 66 Data sources for statistical analyses..................................................................................... 200
Table 67 Sustainability parameters to be included in spatially explicit analyses for forestry and
forestry residues.................................................................................................................... 201
Table 68 Sustainability parameters to be included in spatially explicit analyses for energy crops and
agricultural residues.............................................................................................................. 203
Table 69 Sustainability parameters to be included in spatially explicit analyses for waste................ 205
Table 70 Data sources for spatially explicit analyses.......................................................................... 205
Table 71 Sustainability parameters to be included in cost-supply analyses for forestry and forestry
residues ................................................................................................................................. 208
Table 72 Sustainability parameters to be included in cost-supply analyses for energy crops and
agricultural residues.............................................................................................................. 209
Table 73 Sustainability parameters to be included in cost-supply analyses for waste........................210
BEE Best Practices and Methods Handbook 9
List of Figures
Figure 1 Illustration of the different biomass potentials........................................................................ 18
Figure 2 The integration of sustainability criteria in biomass potential assessments............................ 19
Figure 3 The classification ‘demand-driven’ and ‘resource-focused’ that is used in this study ........... 20
Figure 4 An example of a set of feasible supply chains and related work phases.................................59
Figure 5 An example of a cost-supply curve......................................................................................... 63
Figure 6 Steps to indentify degraded and abandoned farmland for potential bioenergy feedstock
production ............................................................................................................................... 81
Figure 7 Flow chart for food and feed area requirements calculation procedures................................84
Figure 8 Schematic overview of cost factors inthe agricultural production system............................. 87
Figure 9 Output of IKONOS image process .........................................................................................99
Figure 10 The EUFASOM model structure........................................................................................ 147
Figure 11 The three pillars of sustainability........................................................................................ 155
Figure 12 Environmental, social and economic impacts and feedbacks of bioenergy production...... 156
Figure 13 Hierarchy of categories related to sustainability................................................................. 165
BEE Best Practices and Methods Handbook 10
List of Abbreviations
BEE Biomass Energy Europe
BMW Biodegradable Municipal Waste
CAP Common Agricultural Policy
CAPSIM Common Agricultural Policy SIMulation model
CEEC Central and Eastern European Countries
CEOS Committee on Earth Observation Satellites
CLC CORINE Land Cover
CO2Carbon dioxide emission (a greenhouse gas)
CORINE Coordination of Information on the Environment
DBH Diameter at Breast Height
DEM Digital Elevation Model
DM Dry matter
DOM Dry Organic Matter
DSM Digital Surface Model
DTM Digital Terrain Model
EC European Commission
EEA European Environment Agency
EO Earth Observation
EU European Union
Eurostat Statistical institute of the EU
FAO Food and Agriculture Organisation of the United Nations
FAOSTAT Statistical institute of the FAO
FOD First Order Degradation (model)
FP7 The Seventh Framework Programme of the European Union for the funding of
research and technological development in Europe
GEO Group on Earth Observations
GHG Greenhouse gas
GLC2000 Global Land Cover 2000
GMES Global Monitoring for Environment and Security
GSD Ground Sampling Distance
Ha Hectare
HCV High Conservation Value
HHV Higher Heating Value
HNV High Nature Value
IAM Integrated Assessment Model
IGOL Integrated Global Observation of Land
IPCC Intergovernmental Panel on Climate Change
KNN K nearest neighbours
BEE Best Practices and Methods Handbook 11
LAI Leaf Area Index
LFG Landfill gas
LHV Lower heating value (also: net caloric value)
LIDAR Light detection and ranging
MSW Municipal Solid Waste
Mtoe Million tonnes of oil equivalent
nDSM normalized DSM
NDVI Normalized Difference Vegetation Index
NLCD National Land Cover Database
NUTS Nomenclature of Territorial Units for Statistics
ODT Oven Dry Tonne
PEEP Perspectives on European Energy Pathways (model)
Radar Radio detection and ranging
RES Renewable Energy Sources
RS Remote Sensing
SAR Secondary Agricultural Residue
SRC Short rotation coppice
SRES Special Report on Emission Scenarios
SRF Short Rotation Forestry
SWDS Solid Waste Disposal Site
tce Tonnes of coal equivalent
toe Tonnes of oil equivalent
TOF Trees Outside Forests
UNFCCC United Nations Framework Convention on Climate Change
VI Vegetation Index
WDVI Weighted Difference Vegetation Index
WP Work package
Tonne 1000 kg
Gg Gigagram (1000 kg)
GJ GigaJoule
BEE Best Practices and Methods Handbook 12
1 Introduction
Existing biomass resource assessments use a broad variety of approaches, methodologies, assumptions
and datasets that lead to different estimates of future biomass potentials. The overall objective of the
Biomass Energy Europe (BEE) project is to improve the accuracy and comparability of future biomass
resource assessments for energy by reducing heterogeneity of terms and definitions, increasing
harmonisation of data and calculations and exchanging knowledge on methods and approaches.
1.1 Purpose and scope
This handbook has the purpose to promote harmonisation in the development of biomass resource
assessments. It provides best practice methods for determination of biomass resource potentials, and
gives guidance for transparent presentation of results by providing terms and definitions needed for the
execution and presentation of biomass resource assessments.
Methods are provided for four categories of biomass types: (1) forest biomass, (2) energy crops, (3)
agricultural residues and (4) organic waste. Furthermore, five types of methods are identified:
statistical methods, spatially explicit methods, cost-supply methods, energy-economics and energy
system model methods, and integrated assessments. For each of the before-mentioned biomass types,
the handbook shows how these methods can be applied. Furthermore, the handbook provides a
detailed overview of sustainability aspects that can be implemented in future biomass assessments.
The handbook will focus on methods that can be applied to national and European level biomass
resource assessments. If data source availability allows it, the methods can be used at a more local
level and outside Europe as well.
1.2 Target group
The target group consists of both the groups that prepare biomass resource assessments, like
researchers and consultants, as well as their sponsors and clients that will use the results for policy
making and business purposes. The methods handbook presents a variety of biomass assessments that
could be used, from simple statistical approaches to advanced spatially explicit methods and more.
Each method has its own merits and costs. The methods handbook seeks to provide guidance to policy
makers and companies that need to specify their need for biomass resource assessments. In parallel it
serves scientists and consultants in providing detailed descriptions of methods and a large selection of
useful data sources for the performance of biomass resource assessments.
1.3 How to use this handbook
The handbook has multiple functions:
The handbook can be used as a reference work on the use of terminology in the field of bioenergy
resource assessments.
The handbook provides an overview of best practice methods in the range of relatively
straightforward resource-focused biomass assessments to complex integrated assessments.
The handbook presents a detailed overview of sustainability themes, criteria and parameters that
are relevant for biomass resource assessments, and shows how they can be implemented in future
biomass resource assessments.
BEE Best Practices and Methods Handbook 13
The following guidance is given on the use of this handbook:
Chapter 2 presents the general approach of the handbook, introducing a classification of biomass
types and biomass potentials, and an overview of the approaches and methods as used in this
handbook.
Biomass types are clearly divided into four categories: forestry, energy crops, agricultural residues
and wastes. The methods related to these biomass categories are presented in chapters 3 to 6. This
way the reader can easily switch to the methods related to the biomass types he/she is interested
in. Within these chapters, generally, a further division of biomass types can be found. For
instance, forest biomass can be divided in stemwood, primary forestry residues (that originate
from wood harvesting) and secondary forestry residues (that originate from wood processing).
For most biomass types the followingassessment methods are described:
obasic statistical method
oadvanced statistical method
obasic spatially explicit method
oadvanced spatially explicit method
ocost-supply method.
For each biomass type, these methods are presented in separate sections which can be identified
easily using the table of contents of this handbook. Each section has the same format, showing the
method, data sources, remarks, advantages, disadvantages, information for estimation of future
biomass potentials, sustainability aspects, key uncertainties and future research needs.
The statistical method can be applied using statistical data only, which are usually available on
national level. The spatially explicit method allows presentation of the geographic location of the
biomass, at least on a regional level and often at a more detailed level.
The direct use of remote sensing data or the use of remote sensing data derived products is
necessary for spatially explicit assessments; this is shown in the sections on spatially explicit
methods and is presented as a cross-sectorialissue in Annex 1.
A distinction is made between basic methods that allow a quick estimation of biomass availability
with a minimum of effort, and advanced methods that allow a more accurate but often more time-
consuming estimation of biomass availability. It is recognised that both types of methods have
their own merits; the selection of methods will depend on factors like the purpose of the biomass
resource assessment and the time and/or financial means available. For some types of biomass the
distinction between basic and advanced methods is not relevant and therefore omitted.
The cost-supply method shows how biomass availability for energy or other purposes depends on
the costs to make the biomass available. Its shows the economic/implementation potential rather
than the theoretical/technical potential that is determined using the statistical and spatially explicit
methods.
Some biomass resource assessments aim to cover biomass availability in all sectors. The use of
total resource assessments gives opportunity to avoid double counting and to study the interaction
of biomass availability between sectors. The total resource assessments are presented in chapter 7
and include advanced energy and/or economics modelling methods and integrated assessments.
The presented methods are closely linked with data sources available on European level. In this
methods handbook the data sources are briefly introduced, while in the accompanying data
sources handbook detailed descriptions of the used data sources can be found.
The use of sustainability criteria for the production and use of biomass is a recent development
promoted by increased environmental awareness and European and national legislation. Chapter 8
shows an overview of the political framework and a detailed set of sustainability themes,
principles, criteria and parameters that could be taken into account in biomass resource
assessments.
Furthermore, chapter 8 and its accompanying annexes show to what degree the different
sustainability parameters can actually be implemented in different types of biomass resource
assessment methods. For instance, exclusion of Natura2000 areas requires the use of a spatially
explicit method, and cannot be (easily) implemented using a statistical method.
The Methods Handbook, Data Sources Handbookand other deliverables of the BEE project can be
downloaded from http://www.eu-bee.com/.
BEE Best Practices and Methods Handbook 14
1.4 Best practise guidelines
Based on the analysis of existing biomass resource assessments, the following best practise guidelines
for the performance of biomass resource assessment have been developed:
Describe clearly what biomass types are included in the biomass resource assessment (for
suggested terminology, see section 2.1 and the first section of chapters 3 to 7.
Indicate what type of resource potential is assessed (e.g. theoretical, technical, economic or
implementation potential; see section 2.2)
Describe the general approach (resource focused, demand driven or integrated approach) and the
type of method that is used. (e.g. statistical, spatially explicit; see section 2.3).
Describe the method followed including its main advantages and disadvantages, and indicate
which sustainability criteria have been included.
Provide detailed insight into the datasources used and pay special attention to the use of
conversion units, including those for conversion from cubic meters and metric tonnes toward
energy values (e.g. explicitly show which LHV valuesand densities have been used).
Describe the timeframe of the resource assessment and how extrapolation to future biomass
potentials has been carried out.
Provide results not only in graphs, but also in (annexes with) detailed tables.
Provide detailed results on country levelin biomass resource assessments covering the EU.
1.5 Acknowledgements
The Best Practices and Methods Handbook and the Data Sources Handbook have been produced as
part of the Biomass Energy Europe project, which is supported by the European Commission under
the 7th Framework Programme (FP7) and coordinated by the Albert Ludwig-Universität Freiburg. The
Best Practices and Methods Handbook (“Methods Handbook”) and Data Sources Handbook form the
two main deliverables (D5.1 and D5.2) of Work Package 5 ‘Harmonisation of biomass resource
assessments’ of the BEE-project. BTG Biomass Technology Group B.V. is work package leader of
this work package. All BEE project participants have contributed parts to the different chapters of the
Methods Handbook and Data Sources Handbooks. Below, the organisations responsible for the
different chapters of the Methods Handbookare listed.
Chapter Responsible
organisation Contact person
1. Introduction BTG M.W. Vis
2. General approach BTG M.W. Vis
3. Forest biomass (excl. section 3.4.2 & 3.4.3) EFI M. Lindner
3.4.2 & 3.4.3 Stemwood and primary forest
residues - advanced spatially explicit and cost
supply method
METLA P. Anttila
4. Energy crops Utrecht University E.M.W. Smeets
5.2 Primary agricultural residues CRES I. Eleftheriadis
5.3 Secondary agricultural residues SEC Biomass T.A. Zheliezna
5.4 Manure CRES I. Eleftheriadis
6.2 Biodegradable municipal waste BTG M.W. Vis
6.3 Landfill gas BTG M.W. Vis
6.4 Construction and demolition wood IFEU S. Köppen
6.5 Sewage sludge and gas IFEU S. Köppen
7. Total resource assessments Utrecht University E.M.W. Smeets
8. Sustainability IFEU S. Köppen
9. Discussion University of Freiburg M. Dees
Annex 1 University of Freiburg M. Dees
Annex 2 & 3 IFEU S. Köppen
BEE Best Practices and Methods Handbook 15
We would like to thank those who have participated in the external review of the Methods Handbook,
in particular the European Commission, Ökoinstitut, European Topic Centre on Sustainable
Consumption and Production, and Deutsches BiomasseForschungsZentrum. Ms. A. Abbink
(ahavertalingen@live.nl) has performed a finallinguistic check of both Handbooks.
BEE Best Practices and Methods Handbook 16
2 General approach
This chapter contains a general classification of biomass types, types of biomass potentials and types
of biomass resource assessments that is applied throughout the handbook. Furthermore, a number of
relevant issues like the timeframe of biomass resource assessments, current use of biomass and
bioenergy, the geographical coverage of used methods, and the use of units and conversion factors are
introduced in separate subsections.
2.1 Types of biomass
Biomass can be defined as ‘the biodegradable fraction of products, waste and residues from
agriculture (including vegetal and animal substances), forestry and related industries, as well as the
biodegradable fraction of industrial and municipal waste’ (2001/77/EC 2001).
In this handbook, the different biomass types are divided into four biomass categories:
Forest biomass and forestry residues
Energy crops
Agricultural residues
Organic waste.
Forest biomass
In the context of bioenergy, forest biomass includes several types of raw woody materials derived
from forests or from processing of timber that can be used for energy generation:
Stemwood: biomass from pre-commercial and commercial thinnings and final fellings, available
for energy production, including whole trees and delimbed stemwood from pre-commercial
thinnings.
Primary forestry residues: logging residues, stumps.
Secondary forestry residues: wood processing industry by-products and residues, like sawdust &
cutter chips, bark, slabs, lump wood residues, and black liquor.
Woody biomass from short rotation plantations on forest lands.
Trees outside of forests such as trees in settlement areas, along roads and on other infrastructural
areas.
The following woody biomass types are not included as ‘forest biomass and forestry residues’:
Woody biomass from non forest areas:
oShort rotation coppice on agricultural and marginal land, these are covered in the energy
crops chapter (chapter 4).
oOrchards and vineyards on agricultural lands.
Tertiary residues: recovered wood (old furniture, wood used in construction etc.), these are
considered in chapter 6 on organic waste.
Energy crops
Five main types of energy crops can be distinguished, and are further classified as annual (a) and
perennial (p) crops:
Oil containing crops: like sunflower (a), rape (a), soy (a), oil palm (p), and jatropha (p).
Sugar crops: like sugar cane (p), sugar beet (a), and sweet sorghum (a).
Starch crops: like corn (a), wheat (a), barley (a), and cassava (a).
Woody crops: like poplar (p), and eucalyptus (p).
Grassy crops: like miscanthus (p), and switchgrass (p).
Part of the woody energy crops can also be considered as ‘forest biomass’. The following distinction is
made: Short rotation coppice (SRC) production systems are included as energy crops, while short
rotation forestry (SRF) production systems are included as forest biomass. In an SRC plantation the
BEE Best Practices and Methods Handbook 17
trees are planted in much higher densities compared to an SRF system. After harvesting, an SRF needs
to be replanted, while an SRC crop will regenerate as new growth emerges from the original stools
(stumps).
Agricultural residues
Agricultural residues are the by-products of agricultural practice. A distinction is made between
primary or harvest residues (like straw) that are produced in the fields and secondary residues from the
processing of the harvested product (like bagasse, rice husks) that are produced at a processing
facility. Manure is included as a separate category. By-products from further processing of agricultural
products like molasses, vinasse, etc. are not included. They are regarded as residues from the food
industry.
Organic waste
Organic waste includes biodegradable waste from households, industry and trade activities. The waste
fractions covered in this handbook include biodegradable municipal waste, construction and
demolition wood, and sewage sludge. Biogas from sewage treatment plants as well as landfill gas are
also included in the handbook as energy carriers from organic waste.
Table 1 shows examples of biomass types that are covered in this handbook. A detailed description of
each biomass type can be found in the introduction of each chapter that covers its biomass potential.
Table 1 Biomass types covered in the handbook
Main type
Sub
-
type
Examples
Forestry Primary forest products Stemwood, thinnings.
Primary forestry residues Leftovers from harvesting activities: twigs,
branches, stumps, etc.
Secondary forestry residues Residues resulting from any processing step:
sawdust, bark, black liquor, etc.
Energy
crops Oil, sugar and starch crops Jatropha, rapeseed, sunflower seed, sugar cane,
cereals (wheat, barley, etc.), maize, etc.
Energy grasses Miscanthus, switchgrass, etc.
Short rotation coppice Poplar, eucalyptus, etc.
Agricultural
residues Primary or harvesting residues, by-product of
cultivation and harvesting activities Wheat straw, etc.
Secondary processing residues of
agricultural products, e.g. for food or feed
production
Rice husks, peanut shells, oil cakes, etc.
Manure Pig manure, chicken manure, cow manure, etc.
Organic
waste Tertiary residues, released after the use
phase of products Biodegradable municipal waste, landfill gas,
demolition wood, sewage gas and sewage sludge.
For practical reasons this Methods Handbook does not cover all possible biomass types. For instance,
aquatic biomass (algae, seaweed, etc.) is not covered in this handbook, because the potential of this
type of biomass is highly uncertain and data availability is scarce. Residues from the food industry are
also not covered because they consist of a large variety of different biomass types (over 100), for
which hardly any national or international resource assessment has been carried out so far. Peat is also
excluded, since peat is not a renewable type of biomass within the timeframes relevant for climate and
energy policies.
BEE Best Practices and Methods Handbook 18
2.2 Types of biomass potentials
The type of biomass potential is an important parameter in biomass resource assessments, because it
determines to a large extend the approach and methodology and thereby also the data requirements.
Four types of biomass potentials are commonly distinguished:
Theoretical potential
Technical potential
Economic potential
Implementation potential.
Moreover, the concept of a fifth type of potential, ‘the sustainable implementation potential’, is
introduced in this section.
Theoretical potential
The theoretical potential is the overall maximum amount of terrestrial biomass which can be
considered theoretically available for bioenergy production within fundamental bio-physical limits.
The theoretical potential is usually expressed in joule primary energy, i.e. the energy contained in the
raw, unprocessed biomass. Primary energy is converted into secondary energy, such as electricity and
liquid and gaseous fuels. In the case of biomass from crops and forests, the theoretical potential
represents the maximum productivity under theoretically optimal management taking into account
limitations that result from soil, temperature, solar radiation and rainfall. In the case of residues and
waste, the theoretical potentials equal the total amount that is produced.
Other materials
Forestry policies
Biodiversity policies
Energy policy
Climate change policy
Energy
Food
Conversion process
Wood
(materials)
Population
Economy
Water
Climate
Potential primary bioenergy
Potential secondary bioenergy
GPP / NPP
Soil type
Agricultural
policies
Land
(bioenergy
production)
Yield
(bioenergy
production)
Land
(food and
wood
production)
Yield
(food and
wood
production)
Biodiversity
Biodiversity
policies
GHG emissions and
climate change
Other limitations;
social criteria,
environmental criteira,
institutional barriers,
etc.
Management
TECHNIAL POTENTIAL THEORETICAL POTENTIAL
ECONOMIC POTENTIAL
IMPLEMENTATION
POTENTIAL
Other materials
Forestry policies
Biodiversity policies
Energy policy
Climate change policy
Energy
Food
Conversion process
Wood
(materials)
Population
Economy
Water
Climate
Potential primary bioenergy
Potential secondary bioenergy
GPP / NPP
Soil type
Agricultural
policies
Land
(bioenergy
production)
Yield
(bioenergy
production)
Land
(food and
wood
production)
Yield
(food and
wood
production)
Biodiversity
Biodiversity
policies
GHG emissions and
climate change
Other limitations;
social criteria,
environmental criteira,
institutional barriers,
etc.
Management
TECHNIAL POTENTIAL THEORETICAL POTENTIAL
ECONOMIC POTENTIAL
IMPLEMENTATION
POTENTIAL
Figure 1 Illustration of the different biomass potentials
Technical potential
The technical potential is the fraction of the theoretical potential which is available under the regarded
techno-structural framework conditions with the current technological possibilities (such as harvesting
techniques, infrastructure and accessibility, processing techniques). It also takes into account spatial
confinements due to other land uses (food, feed and fibre production) as well as ecological (e.g. nature
BEE Best Practices and Methods Handbook 19
reserves) and possibly other non-technical constraints. The technical potential is usually expressed in
joule primary energy, but sometimes also in secondary energy carriers.
Economic potential
The economic potential is the share of the technical potential which meets criteria of economic
profitability within the given framework conditions. The economic potential generally refers to
secondary bioenergy carriers, although sometimes also primary bioenergy is considered.
Implementation potential
The implementation potential is the fraction of the economic potential that can be implemented within
a certain time frame and under concrete socio-political framework conditions, including economic,
institutional and social constraints and policy incentives. Studies that focus on the feasibility or the
economic, environmental or social impacts of bioenergy policies are also included in this type.
The classification in types of biomass potentials helps the reader to understand what information is
presented. For instance, some biomass types show high technical potentials while their economic
potential is rather limited due to the high costs of extraction and transport. Therefore it is
recommended that the type of potential is explicitly mentioned in every biomass resource assessment.
In existing resource assessments, it is often difficult to distinguish between theoretical and technical
potential and between economic and implementation potential. The technical and theoretical potential
and the economic and implementation potential formtwo pairs of potential types. However, even more
important than making this distinction between four types is the provision of insight into explicit
conditions and assumptions made in the assessment.
Sustainable implementation potential
In theory, a fifth type of potential can be distinguished, which is the sustainable implementation
potential. It is not a potential on its own but rather the result of integrating environmental, economic
and social sustainability criteria in biomass resource assessments. This means that sustainability
criteria act like a filter on the theoretical, technical, economic and implementation potentials leading in
the end to a sustainable implementation potential. Depending on the type of potential, sustainability
criteria can be applied to different extents. For example, for deriving the technical potential, mainly
environmental constraints and criteria are integrated that either limit the area available and/or the yield
that can be achieved. Applying economic constraints and criteria leads to the economic potential and
for the sustainable implementation potential, additional environmental, economic and social criteria
may be integrated (see Figure 2).
Theoretical
potential Technical
potential Economic
potential
Sustainable
implementation
potential
Technical
constraints &
environmental
constraints /
sustainability
criteria
Economic
constraints /
sustainability
criteria
Socio-political
constraints /
environmental,
economic and
social
sustainability
criteria
Figure 2 The integration of sustainability criteria in biomass potential assessments
There is a strong demand for inclusion of sustainability aspects in bioenergy potential. Especially after
bioenergy in general and biofuels in particular have lost some of their good reputation due to the food
versus fuel debate and due to an increased awareness of land use changes, both industry and politics
strive for more sustainable practises. The concept of sustainable biomass contains multiple
BEE Best Practices and Methods Handbook 20
environmental, economic and social aspects, though integrating these aspects may be complex. An
overview of sustainability aspects that can be included in biomass resource assessments as well as
relevant approaches and methods are presented in chapter 8, Annex 2 and Annex 3.
2.3 General approach to biomass resource assessments
Methodologies to assess biomass resources (further referred to as ‘methods’) generally use one of the
following three main approaches: the resource focused approach, the demand driven approach, or the
integrated approach. The general approach determines to a large extent the methodology that is used
and in turn, the methodology determines to alarge extent the data that are used.
Figure 3 The classification ‘demand-driven’ and ‘resource-focused’ that is used in this study
Source: (Berndes et al. 2003)
2.3.1 Resource-focused approach
In the resource-focused approach, the bioenergy resource and the competition between different uses
of the resources are investigated, i.e. the focus is on the supply of biomass for bioenergy. Resource-
focused assessments typically estimate the theoretical or technical potential to produce biomass for
energy, thereby usually taking into account the demand for land for food production and biomass
needed for the production of food and materials. Sometimes also environmental limitations or
economic criteria are included; for instance costs of stump extraction can be far too high to be
seriously considered, and areas needed for the protection of biodiversity are often included as
important limitation for the production of biomass energy.
Within the resource-focused approach statistical and spatially explicit methods can be distinguished.
Statistical methods
Statistical methods make use of data from statistics on land use, crop yields, crop production and from
forest inventories and literature. The statistical data is combined with conversion factors, like yields
per ha, residue to crop factors, etc. These factors are based on expert judgement, field studies or
literature review. In addition, further assumptions are made on the fraction of biomass available for
energy production, taking into account biomass or land needed for other purposes.
BEE Best Practices and Methods Handbook 21
Spatially explicit methods
Spatially explicit methods present data on biomass availability in a location specific, two dimensional
way, for instance on maps. This makes it possible to take into account various location specific factors
that affect biomass availability. Spatially explicit methods include area specific data on the availability
and accessibility of agricultural land and forests in combination with calculations of the yields of
energy crops and forests, based on growth models that use spatially explicit data on e.g. climate, soil
type, vegetation type, and management. When statistic data are available at a detailed level (e.g.
regional or municipal level), results from statistical assessments can be presented in a spatially explicit
way.
2.3.2 Demand-driven approach
In the demand-driven approach, the competitiveness of biomass-based energy systems is compared
with conventional fossil fuel based energy systems, other renewable energy systems and/or nuclear
options. Alternatively, the production and use of biomass required to meet exogenous targets on
bioenergy are estimated, i.e. the focus is on the biomass energy demand side. Thus, demand-driven
studies typically focus on economic and implementation potentials, more than on the theoretical and
technical potentials. However, some studies start with an evaluation of the feasibility of the projected
use of bioenergy, by reference to other studies or by estimating the technical biomass potential.
Within the demand-driven approach, cost supply methods and energy and/or economic modelling
methods can be distinguished.
Cost supply methods
Cost-supply methods start with a bottom-up analysis of the bioenergy potential and costs, based on
assumptions on the availability of land for energy crop production, including crop yields, forest
biomass and forestry residues. The demand of land and biomass for other purposes and other
environmental and technical limitations are included, ideally by scenario analysis. The resulting
bioenergy cost-supply curves are combined with estimates of the costs of other energy systems or
policy alternatives, often with specific attention for policy incentives (e.g. tax exemptions, carbon
credits, and mandatory blending targets).
The transportation of biomass can be a crucial factor for the economic performance. Some studies
investigate this by taking into account spatially explicit data on the availability of biomass for energy,
combined with data on the costs of transportation and the location of the facilities where the biomass
will be converted into bioenergy. Spatially explicit data and analysis are crucial for the optimisation of
biomass production chains.
Energy and/or economic modelling methods
Several demand driven assessments use energy-economics and energy-system models. Other
(agricultural) economic models are also sometimes applied. Energy-economics and energy-system
models mimic the dynamics of the demand and supply of energy, including bioenergy, by means of
investigating economic and non-economic correlations.
Most energy-economics and energy-system models use scenarios, whereby typical scenario variables
include the fundamental drivers of energy demand and supply, such as population growth and income
growth, as well as technological developments and policy incentives. These variables are often
integrated into a coherent set of scenario assumptions. Some models also include greenhouse gas and
energy balances for different energy systems, which allows for the optimisation of costs towards
greenhouse gas reduction or energy security targets.
An ideal agricultural economic model takes into account the effects on prices, production and markets
of other crops. This allows a comparison of the net-returns of alternative options a land owner can
choose from. The competition with other biomass (food, feed, timber, pulp and paper) and energy
BEE Best Practices and Methods Handbook 22
markets (gas, coal, oil, etc.) - determining the output prices of competing markets and products - is
decisive for the economic viability of bioenergy options.
2.3.3 Integrated approach
In the integrated approach integrated assessment models (IAMs) are used. IAMs in the field of energy
include mathematical correlations between the socio-economic drivers of economic activity and
energy use. Energy output is associated with emissions and other pressure on environmental factors
that might again have a feedback on productivity and supply of energy. In that way, IAMs combine
information from different sectors (economic, energy, land use and climate) across various time and
spatial scales. IAMs are particularly useful for the purpose of addressing policy questions, mostly by
means of scenario analysis. These aspects are not all necessarily included in all IAM-biomass potential
assessments, but a clear difference with other approaches/methods is that the various aspects and
dimensions of bioenergy are included in an integrated manner, e.g. by combining results from
different models.
IAMs are typically applied to aggregated world or continental regions or countries, depending on the
resolution of data.
2.3.4 Overview of approaches and methods
An overview of the different combinations of approaches and methodologies to assess biomass
resources (methods), and the resulting type of biomass potential is presented in Table 2.
Table 2 An overview of the combinations of approaches and methodologies that are used in the best
practice handbook
General approach
General methodology
Theoretical-
technical biomass
potentials
Economic-
implementation
biomass potentials
Resource-focused Statistical methods Yes No
Resource-focused Spatially explicit methods Yes No
Resource-focused Cost-supply methods No
a
Yes
Demand-driven Energy-economics and
energy-system model
methods
No Yes
b
Integrated assessment Integrated assessment
model methods Yes
c
Yes
c
aOften demand-driven cost-supply analyses start with a statistical analysis or spatially explicit analysis of technical biomass
energy potentials, although this is not the key focus of these studies.
bSome demand-driven energy-economics and energy-system model analysis use the results of cost-supply analysis.
cIntegrated assessments typically focus on the economic and/or implementation potential, although IAMs are also used for the
theoretical and/or technical biomass energy potential.
Based on this classification of approaches, the Methods Handbook contains best practice guidance on
the following methods:
(Resource-focused) statistical methods
(Resource-focused) spatially explicit methods
(Demand-driven) cost-supply methods
(Demand driven) energy and/or economic modelling methods
Integrated assessments
The methods are presented in separate sections for each relevant type of biomass. This way each
method can be found easily using the table of contents of this Handbook.
BEE Best Practices and Methods Handbook 23
2.4 Basic and advanced biomass resource assessments
The degree of detail, accuracy and comparability of biomass resource assessments that can be
achieved depends on the applied methods, but also on the available budget and time requirements.
Depending on the wishes of the client and the purpose of the assignment or research, either a basic or
advanced approach is appropriate. Therefore, in the categories (resource-focused) statistical methods
and (resource-focused) spatially explicit methods a distinction is made between ‘basic’ and ‘advanced’
methods.
The basic method provides an estimation of the bioenergy potential with limited effort and with
data sources that are easily accessible. The basic method is applicable to all European countries
and the use of commonly available data leads to biomass potentials that are comparable between
European countries, at least within EU27.
The advanced method represents best practice, using state of the art methods. Advanced methods
generally require more data of a higher quality. The methods are applicable in all European
countries, however, it depends on the availability and quality of data sources whether the methods
can actually be applied in a specific country. The application of advanced methods will increase
the accuracy of the biomass resource assessment on country level.
The advanced methods could be an extension of the basic method or be based on another (more
complex) approach.
For the other types of resource assessments, the demand driven cost-supply methods, demand-driven
energy and/or economic modelling methods and integrated assessments, no distinction is made
between ‘basic’ and ‘advanced’ methods. In general, these methods can be regarded as advanced.
2.5 Timeframe of biomass resource assessments
Biomass resource assessments can show snapshots of biomass potential in the past, present and as it is
anticipated in the future, or can provide a more consistent view on the development of the biomass
potential on a regular (yearly) base.
Resource-focused statistical and spatially explicit methods are generally focused on the determination
of the current theoretical and/or technical potential. In fact, the reference years of the used datasets
determine the (base) year for which the biomass potential is presented. However, future theoretic and
technical biomass potentials are often presented as well, based on assumptions on the development of
the resource potential, for instance by relating it to economic growth, population size, or any other
relevant indicator. In demand-driven cost-supply methods and energy and/or economic modelling
methods the time factor is generally already integrated in sets of assumptions called scenarios.
2.6 Geographical coverage
All methods discussed in this handbook are basically applicable at any geographic level, as long as
sufficiently detailed data are available.
The handbook will focus on methods that can mainly be applied on national and European level
biomass resource assessments. However, the presented level of detail of biomass availability can be
much higher, especially when using spatially explicit methods. Generally, most methods can be
applied outside Europe as well, provided that the needed datasets are available. Part of these methods
might be applicable on a sub-national, regional and local level as well. Advanced methods, especially
those determining the bioenergy potential of energy crops, use models on a global level since
availability of especially energy crops is strongly interlinked with global food production and markets.
BEE Best Practices and Methods Handbook 24
2.7 Total resource assessments
Total resource potentials cover the energy potential of biomass available from energy crops, forest
biomass and forestry residues, agricultural residues, and organic wastes. Specific attention can be
given to competition between and co-benefits from the different types of biomass. Instead of summing
up the potentials separately, this approach takes interactions into account (e.g. competition over land).
This way, an overestimation due to overlap of different biomass potentials can be avoided, for instance
areas used for agricultural land cannot be used for forestry and vice versa.
The statistical and spatially explicit methods for the estimation of total resources will mainly be based
on the separate methods presented for forestry, energy crops, agricultural and waste sectors. Total
resource assessments provide opportunities especially for demand-driven and integrated assessments,
since with these types of assessments, cross-sectoral economic effects can be accounted for in an
optimal way. The demand-driven and integrated total resource assessments are presented in chapter 7.
2.8 Sustainability
Sustainable development is generally defined as being a ‘development that meets the needs of the
present without compromising the ability of future generations to meet their own needs’ (WCED
1987). The concept of sustainability is commonly defined within ecological, social and economic
contexts – also referred to as the ‘three pillars’ of sustainability. The three pillars are connected via
feedback mechanisms, trade-offs and synergies. Because of the large range of aspects, connections and
feedback mechanisms to be considered within different approaches, it is difficult to assess a single
‘sustainable bioenergy potential’. However, since the production and use of biomass for bioenergy
purposes affects all dimensions of sustainability, there is a strong demand for inclusion of
sustainability aspects in assessments of the different bioenergy potentials.
Based on an extensive research on current regulations, agreements, guidelines and research in the field
of sustainability, a set of parameters has been defined that aims to cover sustainability as completely
as possible. The following impacts are covered:
Environmental sustainability
oBiodiversity
oClimate change
oSoil (quality and quantity)
oWater (quality and quantity)
oAir quality
oResource use
Social sustainability
oCompetition with the demand for food, feed and fibres
oLabour conditions
Economic sustainability
oBioenergy costs
Sustainability aspects can be included in biomass potential assessments to different extents depending
on the type of potential to be assessed as well as on the method applied. Often, the inclusion of
sustainability parameters leads to a decrease of the biomass potential: they either limit the area
available (e.g. since protected areas are excluded from bioenergy production) or the yields (e.g. via
extensive management methods in sensitive areas).
Within the description of biomass assessment methods for single biomass categories (chapters 3 to 7)
basic sustainability aspects are included directly in the methods. Moreover, additional parameters are
listed that could be included in order to obtain an even more sustainable potential. In these chapters,
the focus is on simply listing relevant parameters. More detailed information can be found in chapter
8, Annex 2 and Annex 3. Chapter 8 provides a description of the theoretical background of
BEE Best Practices and Methods Handbook 25
sustainability including the political framework, data gaps and future research needs as well as the
whole set of sustainability parameters that could be included in biomass potential assessments. In the
annexes, extensive background information is given on all sustainability parameters as well as detailed
instruction on how to include them in the various assessment methods.
2.9 Use of units, conversion factors, etc.
The theoretical and technical biomass potentials will be expressed both as its total mass including
moisture (tonnesw) and as its total net calorific content (PJ).
Along with the mass, the average moisture content of the biomass will be expressed on a wet
basis.
The lower heating value of the biomass resource will be used to calculate the total net calorific
content.
The theoretical and technical biomass potentials will be expressed on primary energy basis (before
conversion into electricity, heat or transport fuels in Joules (mainly PJ, but also TJ, GJ etc, when
appropriate).
Economic and implementation potentials will be expressed as secondary energy.
Electric energy will be expressed in TWh (or MWh, GWh, when appropriate);
Thermal energy will be expressed in PJ (or GJ, etc);
Biofuels for transportation purposes will be expressed as primary energy (in PJ, GJ, etc).
BEE Best Practices and Methods Handbook 26
3 Forest biomass
3.1 Scope and definitions
Scope
This chapter describes methods for estimations of potentials of woody biomass derived from forests
(further – woody biomass). The described methodology was developed on basis of methods of
biomass assessments (e.g.(Asikainen 2008); (Ericsson and Nilsson 2006); analysed in work packages
3 and 4 of the Biomass Energy Europe project (BEE 2008), (BEE 2009). In theory, the methods are
applicable also to estimate potentials of woody biomass from other wooded lands and trees outside
forests (TOF), but in practice it is often not possible due to very limited data. The methods are based
on information about actual or future net annual increment and fellings. Reliable forest statistic data
are easily available from public sources, e.g. the Statistic Committee of the European Commission and
different studies. On the contrary, availability of statistics on TOF for wide scales (e.g. at international
level) is low and the data are often inaccurate due to the methods used in assessments of biomass
potentials from TOF (FAO 2002).
In the context of bioenergy, forest biomass includes all kinds of woody raw materials derived from
forests or from processing of timber and used for energy generation. Thereby, the term “forest
biomass” covers several types of biomass:
Stemwood: biomass from pre-commercial and commercial thinnings and final fellings, available
for energy production, including whole trees and delimbed stemwood from pre-commercial
thinnings.
Primary forestry residues: logging residues, stumps.
Secondary forestry residues: wood processing industry by-products and residues – sawdust and
cutter chips, bark, slabs, lump wood residues, and black liquor.
Woody biomass from short rotation plantations on forest lands.
Trees outside of forests such as trees of settlement areas, along roads and on other infrastructural
areas.
The following woody biomass types are not included:
Woody biomass from non forest areas:
oShort rotation coppice on agricultural and marginal land, these are covered in the energy
crops chapter (chapter 4).
oOrchards and vineyards on agricultural lands.
Tertiary residues: recovered wood (old furniture, wood used in construction etc.), these are
considered in chapter 6 on organic waste.
It should be noted that in contrast to stemwood and the primary forestry residues, which are in most
cases domestic resources, the secondary residues can originate from processing of imported timber.
There is a difference between the total potential of wood available as energy source and additional
potential of wood for energy. The difference is the volume of woody biomass that is already used as a
fuel. This volume of wood cannot be considered as a resource for new bioenergy facilities being
established.
The total potential of woodybiomass is:
yxyxyxyx SFRTPPFRTPSWTPFWBTP ,,,, ____ (Equation 3.1.1)
Where:
TP_FWBx,y = total p-potential of forest woody biomass in country x in year y, (m3/year)
TP_SWx,y = potential of stemwood in country x in year y, (m3/year)
BEE Best Practices and Methods Handbook 27
TP_PFRx,y = potential of primary forestry residues in country x in year y, (m3/year)
TP_SFRx,y = potential of secondary forestry residues in country x in year y, (m3/year)
When determining the theoretical potential from stemwood for energy use, the amount of wood
needed for material use is already deducted, as this constraint is regarded as fundamental in the
forestry sector. Thus this theoretical potential can be characterised as a “complementary” theoretical
potential from stemwood for energy use. Alternatively, a theoretical potential without such a
constraint could also be defined. When determining economic potentials, the constraint to exclude the
material use is not made when defining the upper limits of the economic models. At the same time
such unconstrained potential can be regarded an overall theoretical potential considering a full
implementation of a cascade use after a material use of wood (receylcing where appropriate and in the
end energy use).
Potentials of woody biomass can be estimated in terms of volume, mass, primary or secondary energy.
Conversion factors are used to convert different measurement units (e.g. volume to primary energy).
Conversion to alternative measurement units always causes uncertainties in results and should be
carried out with attention to many specific aspects, e.g. type of biomass, moisture of wood, tree
species, state and type of wood to energy conversion technologies etc. (Hagauer et al. 2008).
All the calculations in the first section of this chapter will use volume units, because most of forest
inventory data are presented in terms of volume. The last section (3.6) will then provide information
on how to perform the conversion to the energy unit GJ or PJ.
Definitions
Table 3 and Table 4 provide terms and definitions related to forest woody biomass.
Table 3 Definitions of woody biomass
Biomass type
Definition
Source (Reference)
Forest
Land spanning more than 0.5 hectares with trees higher than 5
metres and a canopy cover of more than 10 percent, or trees able
to reach these thresholds in situ. It does not include land that is
predominantly under agricultural or urban land use.
(FAO 2006a)
Forests available
for wood supply
(FAWS)
Forest where any legal, economic or specific environmental
restrictions do not have a significant impact on the supply of wood.
Includes: areas where, although there are no such restrictions,
harvesting is not taking place.
(FAO 1999)
Other wooded
land
Land not classified as forest, spanning more than 0.5 hectares;
with trees higher than 5 m and a canopy cover of 5–10 percent, or
trees able to reach these thresholds in situ; or with a combined
cover of shrubs, bushes and trees above 10 percent. It does not
include land that is predominantly under agricultural or urban land
use.
(FAO 2006a)
Trees outside
forests
Trees outside forests (TOF) are defined by default, as all trees
excluded from the definition of forest and other wooded lands.
TOF are located on “other lands”, mostly on farmlands and built-
up areas, both in rural and urban areas. A large number of TOF
consists of planted or domesticated trees. TOF include trees in
agroforestry systems, orchards and small woodlots.
(FAO 2000)
Woody biomass
The mass of the woody parts (wood, bark, branches, twigs,
stumps and roots) of trees, alive and dead, shrubs and bushes,
measured to a minimum diameter of 0 mm (d.b.h.).
Includes: Above-stump woody biomass, and stumps and roots.
Excludes: Foliage.
Stemwood Part of tree stem from the felling cut to the tree top with the
branches removed, including bark.
Biomass from
pre-commercial
thinnings Stems, branches, bark, needles/leafs.
Logging residues Woody biomass by-products that are created during harvest of
merchantable timber. (FAO 2004)
Stumps Part of the tree stem below the felling cut. (FAO 2004)
BEE Best Practices and Methods Handbook 28
Pre-commercial
thinnings Selective cuttings in young stands, felled trees have no value for
wood processing industry.
Commercial
thinnings
Selective cuttings in middle age and maturing stands, a part of
felled trees have value for wood processing industry, mainly as
pulpwood.
Wood processing
industry by-
products and
residues
Woody biomass by-products originating from the wood processing
industry as well as the pulp and paper industry. (FAO 2004)
Sawdust Fine particles created when sawing wood. (FAO 2004)
Cutter chips Wood chips
1
made as a by-product of the wood processing
industry, with or without bark.
Bark Organic cellular tissue that is formed by taller plants (trees,
bushes) on the outside of the growth zone (cambium) as a shell
for the wooden body.
Slabs
Parts of woody biomass created when cuts are made into the
edges of logs and whereby one side shows the original rounded
surface of the tree, either completely or partly, with or without
bark.
(FAO 2004)
Lump wood
residues Cut-offs created during sawing of timber.
Black liquor
Alkaline spent liquor obtained from digesters in the production of
sulphate or soda pulp during the process of paper production, in
which the energy content mainly originates from the content of
lignin removed from the wood in the pulping process.
Table 4 Other relevant definitions related to forest biomass
Item
Definition
Source (Reference)
Growing stock The living tree component of the standing volume. UNECE/FAO,
http://www.unece.org
/timber/fra/definit.htm
Standing volume Volume of standing trees, living or dead, above-stump measured
overbark to top (0 cm). Includes all trees with diameter over 0 cm
(d.b.h.).
Includes: Tops of stems, large branches; dead trees lying on the
ground that can still be used for fibre or fuel.
Excludes: Small branches, twigs and foliage.
UNECE/FAO,
http://www.unece.org
/timber/fra/definit.htm
Net annual
increment Average annual volume over the given reference period of gross
increment less that of natural losses on all trees to a minimum
diameter of 0 cm (d.b.h.).
UNECE/FAO,
http://www.unece.org
/timber/fra/definit.htm
Industrial wood Wood, of which quality satisfies quality requirements of the wood
processing industry (paper and pulp industry).
Non-industrial
wood Wood, of which quality does not correspond to quality
requirements of the wood processing industry (pulp and paper
industry, sawmills, construction).
Surplus of stem
wood Unutilised part of the net annual increment that can be potentially
used for energy in a sustainable way.
Recovery rate Ratio of collected biomass to volume of biomass available for
collection.
Biomass
expansion factor Multiplication factor that expands growing stock, or commercial
round-wood harvest volume, or growing stock volume increment
data, to account for non-merchantable biomass components such
as branches, foliage, and non-commercial trees.
(IPCC 2003). Good
Practice Guidance
for LULUCF -
Glossary
Fuel wood Stemwood and branches used as a fuel.
Wood fuel A fuel made of woody biomass: wood chips, pellets, briquets,
chopped wood, etc.
In order to estimate a biomass potentialone can choose from three approaches – resource focused,
demand-driven and integrated assessment models, and several methods – statistical analysis, spatially
1Wood chips is chipped woody biomass in the form of pieces with a defined particle size produced by
mechanical treatment with sharp tools such as knives. Wood chips have a subrectangular shape
with a typical length 5 to 50 mm and a low thickness compared to other dimensions FAO (2004). Unified
bioenergy terminology UBET. Wood Energy Programme, Food and agriculture Organization of the United
Nations, Forestry Department:58.
BEE Best Practices and Methods Handbook 29
explicit analysis, cost-supply analysis, energy-economics and energy-system model analysis,
feasibility and impact analysis and integrated assessment model analysis. Depending on the selected