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Economy-wide Material Flow Accounting. Introduction and Guide. Version 1.0

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Abstract

The Institute of Social Ecology (SEC) guide for economy wide material flow accounting (EW-MFA) provides an introduction into accounting principles and practical support for students, statisticians, researchers and all others concerned with material flow accounting. This guide is a revised and modified version of the 2009 draft of the Eurostat MFA compilation guide, which served as a working document in the process of the development of the current Eurostat Guide for EW-MFA. The guidelines have been updated and adapted to fit the needs for a global application and for the reconstruction of historic time series of material flow data. The guide refers to international databases with global coverage and provides suggestions and examples for estimation procedures and coefficients for different world regions and historic time periods. Adaptations have been made in particular for the estimation of grazed biomass and crop residues, for the estimate of sand and gravel consumption in construction activities and for gross ore estimations. Material flow accounting is a dynamic field and methods and data sources are continuously improved. The guidelines should be seen as work in progress and the methods and estimation procedures described in this handbook represent the state of the art in 2014. Further improvements and adaptation of the methods is strongly encouraged.
Fridolin Krausmann, Helga Weisz, Nina Eisenmenger, Helmut Schütz,
Willi Haas and Anke Schaffartzik
Economy-wide Material Flow Accounting
Introduction and Guide
Version 1.0
S O C I A L E C O L O G Y W O R K I N G P A P E R 1 5 1
February 2015 ISSN 1726-3808
2
Fridolin Krausmann, Helga Weisz, Nina Eisenmenger, Helmut Schütz, Willi Haas
and Anke Schaffartzik (2015):
Economy-wide Material Flow Accounting
Introduction and Guide
Social Ecology Working Paper 151
Vienna, Februar 2015
ISSN 1726-3808
Institute of Social Ecology
IFF - Faculty for Interdisciplinary Studies (Klagenfurt, Graz, Vienna)
Alpen-Adria Universitaet
Schottenfeldgasse 29
A-1070 Vienna
www.aau.at/sec
workingpaper@aau.at
© 2015 by IFF – Social Ecology
3
Table of Contents
Preamble: The SEC MFA guide .......................................................................................... 6
Fundamentals .....................................................................................................................10
System boundaries ...........................................................................................................10
Stocks and flows ...............................................................................................................11
Material balance principle .................................................................................................14
Typology of flows ..............................................................................................................14
Residence principle ..........................................................................................................18
Data sources and quality of the accounts ..........................................................................19
The MFA tables ................................................................................................................20
Table A: Domestic extraction ............................................................................................23
Biomass ............................................................................................................................23
Metal ores and non-metallic minerals ................................................................................38
Fossil energy carriers ........................................................................................................66
Tables B and C: Imports and exports ...............................................................................70
Introduction .......................................................................................................................72
Data structure and sources ...............................................................................................73
Conventions, conversions .................................................................................................76
Compilation .......................................................................................................................78
Table D: Domestic processed output (DPO) ....................................................................84
Emissions to air ................................................................................................................86
Waste landfilled ................................................................................................................93
Emissions to water ............................................................................................................97
Dissipative use of products ...............................................................................................99
Dissipative losses ........................................................................................................... 104
Table E: Balancing items and net additions to stock .................................................... 106
Introduction ..................................................................................................................... 106
4
Balancing items: Input side (gases and water) ................................................................ 107
Balancing items: Output side (gases) .............................................................................. 111
Material flow indicators .................................................................................................... 115
Extensive indicators ........................................................................................................ 115
Intensive indicators ......................................................................................................... 116
References ........................................................................................................................ 118
Literature ........................................................................................................................ 118
Databases and Statistical Sources .................................................................................. 123
List of abbreviations ........................................................................................................ 124
List of Figures
Figure 1: Scope of economy-wide MFA ................................................................................. 7
Figure 2: Schematic representation of economy-wide MFA ..................................................15
Figure 3: Balancing inputs with outputs: Austria 1996 ........................................................ 106
List of Tables
Table 1: Domestic extraction of biomass ..............................................................................23
Table 2: Standard values for harvest factors (a) and recovery rates (b) for common crop
residues. ..............................................................................................................................28
Table 3a: Typical roughage intake by grazing animals .........................................................31
Table 3b: Estimate of annual intake of forage by cattle and buffalo in 1960, 1990 and 2005 31
Table 4a: Feed conversion coefficients ................................................................................33
Table 4b: Share of roughage in total feed energy supply by world region. ............................33
Table 5: Typical area yield of permanent pastures ...............................................................34
Table 6: Standard factors to convert quantities given in volume into weight. ........................35
Table 7: Domestic extraction of metal ores ...........................................................................38
Table 8: Domestic extraction of non-metallic minerals. .........................................................39
Table 9: Different system boundaries in metal mining ..........................................................42
5
Table 10: Coupled production, Metal output of hypothetical economy ..................................46
Table 11: Country-specific ore grades and occurrences of coupled production for European
countries ..............................................................................................................................47
Table 12: Specific densities of ornamental and building stone ..............................................54
Table 13: Specific densities of limestone and gypsum ..........................................................55
Table 14: Specific densities of chalk and dolomite ................................................................56
Table 15: Specific densities of slate......................................................................................57
Table 16: Requirements of sand and gravel per km of road construction in Germany ..........60
Table 17: Specific densities of sand and gravel ....................................................................60
Table 18: Specific densities of clay .......................................................................................61
Table 19: Domestic extraction of Fossil energy carriers ........................................................66
Table 20: Calorific value and density of natural gas of fossil energy carriers ........................68
Table 21: Classification of trade flows ..................................................................................70
Table 22: Selected results for DPO ......................................................................................84
Table 23: Domestic processed output: emissions to air ........................................................86
Table 24: Domestic processed output: waste landfilled ........................................................94
Table 25: Domestic processed output: emissions to water ...................................................97
Table 26: Domestic processed output: dissipative use of products .......................................99
Table 27: Daily manure production coefficients .................................................................. 101
Table 28: Domestic processed output: dissipative losses ................................................... 104
Table 29: Oxygen demand for oxidation of H compound of energy carriers to H
2
O ............ 108
Table 30: Metabolic oxygen demand of humans and livestock ........................................... 109
Table 31: Oxygen content of energy carriers (in % of weight) ............................................. 110
Table 32: Water vapour from moisture content of fuels....................................................... 112
Table 33: Water vapour from oxidised hydrogen component of fossil energy carriers ........ 113
Table 34: Metabolic CO
2
and H
2
O production of humans and livestock .............................. 114
6
Preamble: The SEC MFA guide
The Institute of Social Ecology (SEC) guide for economy wide material flow accounting (EW-
MFA) provides an introduction into accounting principles and practical support for students,
statisticians, researchers and all others concerned with material flow accounting. This guide
is a revised and modified version of the 2009 draft of the Eurostat MFA compilation guide,
which served as a working document in the process of the development of the current
Eurostat Guide for EW-MFA.
1
The guidelines have been updated and adapted to fit the
needs for a global application and for the reconstruction of historic time series of material
flow data. The guide refers to international databases with global coverage and provides
suggestions and examples for estimation procedures and coefficients for different world
regions and historic time periods. Adaptations have been made in particular for the
estimation of grazed biomass and crop residues, for the estimate of sand and gravel
consumption in construction activities and for gross ore estimations. Material flow accounting
is a dynamic field and methods and data sources are continuously improved. The guidelines
should be seen as work in progress and the methods and estimation procedures described in
this handbook represent the state of the art in 2014. Methods and estimation procedures can
and should be adapted to country specific situations. Further improvements and adaptation
of the methods is strongly encouraged.
1
Economy-wide Material Flow Accounts (EW-MFA), Compilation Guide 2013, 10 September 2013, European
Statistical Office. Available at:
http://epp.eurostat.ec.europa.eu/portal/page/portal/environmental_accounts/documents/2013_EW-
MFA_Guide_10Sep2013.pdf.
7
Introduction
In the past years the physical dimension of economic processes, in particular the socio-
economic use of materials, was increasingly recognized internationally as a key area for a
sustainable development strategy. In 2001 the Gothenburg Council adopted the Sustainable
Development Strategy which was revised in 2006 (Council of the European Union 2006).
Japanese policy makers already very early focussed on resource use and recycling and
Japan was the first country to implement a legal binding policy programme, the 3R action
plan, in 2001 (Takiguchi and Takemoto, 2008). The 6
th
environmental action programme
(European Parliament and Council 2002) specifies the sustainable use of resources as one
of six priority fields for the period 2002 to 2012. A thematic strategy on a sustainable use of
resources was published by the European Commission in 2005 (Commission of the
European Communities 2005). An OECD council recommendation on material flows and
resources productivity in April 2004 fostered the establishment of an OECD work program on
this topic by the OECD working group on environmental information and outlook. In 2007,
UNEP initiated the foundation of an international expert panel on a sustainable use of
resources. Most recently, the European Commission published the flagship initiative on “A
Resource Efficient Europe” (2011) and half a year later the Roadmap to a Resource Efficient
Europe (2011) with DMC and resource productivity as headline indicators
2
.
Figure 1: Scope of economy-wide MFA
2
see http://ec.europa.eu/environment/resource_efficiency/about/roadmap/index_en.htm and
http://ec.europa.eu/resource-efficient-europe/
8
These processes substantially increased the need for economy-wide, reliable and
comparable time-series data and indicators for material use. The backbone of an
environmental reporting system which provides such information is economy-wide material
flow accounting (MFA). Economy-wide material flow accounts are consistent compilations of
the overall material inputs into national economies, the changes of material stock within the
economic system and the material outputs to other economies or to the environment (Fig. 1).
Economy-wide MFAs, for the sake of brevity referred to as MFA in the following document,
cover all solid, gaseous, and liquid materials, except for bulk water and air; the unit of
measurement is tonnes (i.e. metric tonnes) per year. Similarly to the system of national
accounts, material flow accounts serve two major purposes. The detailed accounts provide a
rich empirical database for numerous analytical studies. They are also used to compile
different extensive and intensive material flow indicators for national economies at various
levels of aggregation. Economy-wide MFA thereby is to be seen as a satellite system to the
system of national accounts which aims at describing the total scale of socio-economic
activities in physical quantities.
The first economy-wide material flow accounts, in the contemporary sense, were published in
the early 1990s for Austria (Steurer 1992), Japan (Ministry of the Environment, 1992), and
Germany (Schütz and Bringezu 1993). Two publications by the World Resources Institute
pioneered the comparative empirical analysis of national economies in material terms and
the development of internationally comparable MFA indicators, Adriaanse et al. (1997) and
Matthews et al. (2000).
A major step towards methodological harmonization was the publication Economy-wide
material flow accounts and derived indicators: A methodological guide (Eurostat 2001). This
guide specified the underlying concept of material flow accounting and the design of material
flow indicators. Agreements were based on extensive discussion within the Eurostat MFA
task force which met twice in 2000. However, the 2001 guide lacks specific information
regarding the compilation of MFAs. The report Materials use in the EU-15. Indicators and
Analysis, published by Eurostat one year later (Eurostat 2002), presented the first official
MFA data set for the EU-15 and provided detailed information on a number of practical
aspects of the accounting methods in its technical part. In several meetings between 2004
and 2006, the Eurostat MFA task force continued its efforts on methodological
standardisation by developing a material flow classification, MFA standard tables, and
detailed procedures on how to compile an economy-wide MFA for European Union member
states. European MFA experts developed MFA compilation guidelines which have been
revised several steps and different versions of MFA compilation guidelines are available
9
(Eurostat 2007, 2009c, 2012 and 2013). In July 2011 the European Parliament established
the Regulation (EU) No 691/2011, which provides a legal base for the compilation of material
flow accounts as a key reporting tool in the European Union’s environmental and economic
accounts. At the international level, several global dataset are available covering MFA data
(Schaffartzik et al., 2014, Giljum et al., 2014, Schandl and West, 2010)
3
and a publication by
Fischer-Kowalski and colleagues (2011) summarizes the state of the art of material flow
accounting.
Information on the conceptual framework of MFA and how to technically compile the data is
spread over several reports and papers. With this guide, we want to provide a concise
summary of up to date MFA concepts and methods. Thus, the purpose of this guide is two-
fold. First, it documents the conceptual framework and methodological standards in
economy-wide MFA as they have been, for example, adopted by the European Union.
Second, it provides practical step-by-step procedures for the compilation of economy-wide
international material flow accounts.
Researchers and students from various fields who have an academic interest in MFA will find
useful information and methodological guidance in this reference manual, as well as
practitioners in the statistical office who may use this guide as well, regardless of the specific
reporting schema to which they are committed.
The remaining of the manual is organized as follows. The second chapter (Fundamentals)
summarizes the fundamental definitions and conceptual principles, applied in economy-wide
material flow accounting, and introduces the reader to the various partial accounts and the
overall structure of the MFA standard tables. The third chapter 3 (domestic extraction,
Table A) provides step-wise procedures for the accounting of domestic extraction of
biomass, minerals and fossil fuels, including the description of data sources, crosschecking
opportunities, estimation methods, information on conversions and coefficients. The forth
chapter (imports and exports, Tables B, C, D, and E) explains the relevant sources and
steps in compiling the physical accounts for imports and exports. The fifth chapter (domestic
processed output: DPO, Table F) covers the analogous accounting information for outputs
to the environment. This touches an area of MFA which is less well developed in
methodological terms. The information is based on the currently available conventions but
has to be considered as work in progress. Likewise for the sixth chapter (balancing items
and net additions to stock, Table E), which explains the complex issue of how a consistent
3
Data compilations are available at: http://www.materialflows.net/, http://www.uni-
klu.ac.at/socec/inhalt/1088.htm and http://www.cse.csiro.au/forms/form-mf-start.aspx
10
material balance for a national economy is completed. The seventh chapter (Material flow
indicators) defines and discusses the aggregated extensive and intensive indicators that
can be derived from economy-wide material flow accounts and provides some empirical
examples.
Fundamentals
System boundaries
Economy-wide material flow accounting is conceptually based on a simple systemic model of
an economy (referred to as national economy in the following document) as a biophysical
and socio-economic system embedded in its socio-economic and biophysical environment.
The term embedded indicates that socio-economic systems in general are conceived as
materially (and energetically) open systems, i.e. systems that maintain socially organized
material (and energy) exchanges with their environment. Such a biophysical understanding
of a socio-economic system is commonly referred to as social or industrial metabolism
(Fischer-Kowalski 1998; Ayres and Simonis 1994).
For the purposes of EW-MFA compilation, the specific socio-economic system under
investigation is the national economy into or from which two types of material input or output
flows are possible. On the input side, we distinguish between inputs from the natural
environment and material imports from other national economies (the rest of the world
(ROW)-economy). Likewise, on the output side, we distinguish between outputs into the
environment and material exports to other economies.
EW-MFA is consistent with the principles and system boundaries of the system of national
accounts (ESA 95, SEEA)
4
and follows the residence principle. It accounts for material flows
associated with the activities of all resident units of a national economy regardless of their
geographic location. In EW-MFA two types of material flows across system boundaries are
relevant:
1. Material flows between the national economy and the natural environment: This consists
of the extraction of primary (i.e., raw, crude or virgin) materials from and the discharge of
materials to the natural environment (wastes and emissions to air and water);
4
http://unstats.un.org/unsd/envaccounting/seea.asp
11
2. Material flows between the national economy and the ROW-economy. This encompasses
imports and exports.
Only flows that cross the system boundary on the input-side or on the output-side are
counted. Material flows within the economy are not represented in economy-wide MFA and
balances. This means that the national economy is treated as a black box in MFA and e.g.
inter-industry deliveries of products are not described.
Used and unused extraction:
Inputs from the natural environment are called "domestic extraction". This refers to the
purposeful extraction or movement of natural materials by humans or human-controlled
means of technology (i.e., those involving labour) insofar as they are considered resident
units. Not all materials that are deliberately extracted or moved in the extraction process
ultimately enter the economy; and not all materials are moved with the intention of using
them in the economy. We therefore distinguish between used and unused extraction.
“Used refers to an input for use in any economy, i.e. whether a material acquires the status
of a product. […] Unused flows are materials that are extracted from the environment without
the intention of using them, i.e. materials moved at the system boundary of economy-wide
MFA on purpose and by means of technology but not for use" (Eurostat 2001: 20). Examples
of unused extraction are soil and rock excavated during construction or overburden from
mining, the unused parts of fellings in forestry, the unused by-catch in fishery, the unused
parts of the straw harvest in agriculture or natural gas flared or vented. The commonly used
term "domestic extraction" – abbreviated DE – always refers to "used" extraction if not
otherwise specified (some authors also refer to this as domestic extraction used” with the
abbreviation DEU). In some early MFA publications "unused extraction" is also called "hidden
flows". This compilation guide does not include unused extraction.
Stocks and flows
The distinction between stocks and flows is another fundamental principle of any material
flow system. In general, a flow is a variable that measures a quantity per time period,
whereas a stock is a variable that measures a quantity per point in time. MFA is a pure
flow concept. It measures the flows of material inputs, outputs and stock changes within the
national economy in the unit of tonnes (= metric tonnes) per year. This means that in MFA
stock changes are accounted for but not the quantity of the socio-economic stock itself.
12
Although MFA is a flow concept, it is still important to define carefully what is regarded as a
material stock of a national economy because additions to stocks and removals from stock
are essential parts of the MFA framework. The definition of material stocks is also crucial in
identifying which material flows should or should not be accounted for as inputs or outputs.
This leads to an alternative definition of the system boundary. Input flows are all material
flows that serve as an input to produce or reproduce the socio-economic material stocks
measured at the point where they cross the MFA specific system boundary. Output flows are
discharges into the environment of the focal socio-economic system. This implies that they
are measured at the point where society loses control over the further location and
composition of the materials.
In MFA, three types of socio-economic material stocks are distinguished: artefacts, animal
livestock, and humans. Artefacts are mainly man-made fixed assets as defined in the
national accounts such as infrastructures, buildings, vehicles, and machinery as well as
inventories of durable products. Durable goods purchased by households for final
consumption are not considered fixed assets in the national accounts but are regarded as
materials stocks in economy-wide MFA.
Also the human population and animal livestock are regarded as socio-economic stocks
in national MFA. This means that for a full national material balance not only all food and
feed (including non-marketed feed such as grass directly consumed by ruminants on
pastures) but also the respiration of humans and animals must be taken into account as
material inputs and outputs (most importantly CO
2
emissions).
Theoretically, the calculation of net stock changes should also include the changes in human
population and animal livestock. However, experience shows that these stock changes are
very small compared to e.g. the stock accumulation through buildings, machinery or
consumer durables. In practice, therefore, the changes in human population and animal
livestock are often ignored.
As a consequence of this definition of socio-economic stocks, some material stocks are
considered natural and not socio-economic despite the fact that they are part of the
economic production system. This applies to agricultural plants and forests
5
, including
cultivated forests, and to fish stocks (unless they are cultivated in aquacultures). It is indeed
5
According to ESA 95 forests are regarded a socio-economic stock in national accounts; changes in
forest stocks are defined as “work in progress”. To allow for consistency between national accounts
and EW-MFA it was agreed that net changes in forest stocks should be accounted for as
memorandum item in EW-MFA (see section A 1.3 Wood).
13
not the socio-economic importance of the stock that determines its attribution to the socio-
economic system but rather the degree of control that a society exerts over the production
and reproduction of the stock.
From a more theoretical point of view, it should be kept in mind that humans colonize – in the
sense of exercising sustained and organized control over natural processes – more and
more elements of the material world of which they are a part of (Fischer-Kowalski and Weisz
2005). The intensity with which humans colonize different parts of their natural environment
is not equally distributed though. More or less intensive colonization technologies may be
applied to make use of the various material stocks provided by the natural environment. By
and large the attribution of stocks to either the natural or the socio-economic system is
intended to follow a gradient of colonisation intensities. In this respect the livestock
production system can be considered a more intensively colonized system than the plant and
timber production system.
There is another more practical reason why cultivated plants are regarded as natural stocks.
Treating plants as parts of the national economy would create the necessity to account for
water, CO
2
, and plant nutrients as the primary inputs from the environment. Effectively, this
would mean that the system boundary between a national economy and its environment
would have to be drawn at the inorganic level (i.e. plant nutrients, CO
2
and water).
Statisticians would be forced to convert rather robust and valid data on annual agricultural
and timber harvest to comparably weak estimates of the primary inputs needed to produce
these plants. Moreover, all differentiation between different types of crops would be lost, as
well as the conceptual link to the system of national accounts. It is hard to imagine how such
data could possibly be interpreted in a meaningful way, given the limitations of a black box
accounting system such as MFA.
There are some areas, where the system boundaries are difficult to define, e.g. where the
degree of control over material stocks is varying or may change over time. Cases in point are
shifts from uncontrolled to controlled landfills and the increasing importance of fish
production through aquaculture as opposed to fish catch in uncontrolled settings. Controlled
landfills are considered socio-economic stocks, which means that treatment of these stocks
is an activity within the socio-economic system. Any leaking of substances in the soil or water
vapour exhausting from organic wastes in particular, should be considered as outputs to
nature. In practical terms, these flows are considered small and thus negligible. Aquaculture
systems should also be treated as socio-economic stocks. In this case not the fish production
but the nutrients and other inputs as well as the outputs in terms of wastes would have to be
taken into account. In general, we assume that both inputs and outputs of aquaculture
14
systems are already accounted for in domestic extraction (DE), domestic processed output
(DPO) and trade flows (for definitions see below). Regarding waste flows it has been agreed
upon, that only waste going to uncontrolled landfills should be accounted for in MFA.
Material balance principle
As MFA accounts for materials entering and leaving a system, the conservation of mass
principle applies, which states that matter can neither be created nor destroyed. Although
this principle is not universally true (as nuclear reactions are able to transform mass into
energy) it is a sufficiently appropriate formulation for the material exchange relations of
macro systems.
The mass balance principle can be formulated as:
input = output + additions to stock – removals from stock
= output + net stock changes
All material inputs into a system over a certain time period equal all outputs over the same
period plus the stock increases minus the releases from stock. In principle net stock changes
can be positive, indicating net accumulation, or negative, indicating stock depletion.
In MFA, the mass balance principle is used to check the consistency of the accounts, see
Table H of the EW-MFA tables. It also provides one possibility to estimate the net additions
to stock (NAS). It has to be noted, though, that the compilation of a full national material
balance is not inevitably the outcome of an economy-wide material flow account. Often
partial accounts are compiled, mostly focusing on the input side and trade flows.
Typology of flows
The MFA framework distinguishes between different material flow categories. This chapter
summarises and completes the description of the general material flow categories and
introduces the reader to the relevant terminology. Based on this, we will describe the
structure of the economy-wide material flow accounting tables.
15
Figure 2: Schematic representation of economy-wide MFA
Source: Mathews et al. 2000, modified. Legend: DE = domestic extraction; DPO = domestic processed outputs,
i.e. wastes, emissions, dissipative uses and losses; RME = raw material equivalents; extr.= extraction
Figure 2 provides a schematic representation of the material flow accounting framework and
its main flow categories. All flows that cross the border of the socio-economic system are
called direct flows. In Figure 2 these flows are coloured in dark grey.
On the input-side, we distinguish between domestic extraction (used; DE), imports, and the
input balancing items comprised of those water and air inflows that must be taken into
account in order to complete the material balance. On the output-side, we distinguish
between exports, "domestic processed output" (DPO), and output balancing items. Finally,
inputs to and outputs from stocks are considered, resulting in net-changes of stocks. The
main material flow categories are defined as follows:
Domestic Extraction – DE: The aggregate flow DE covers the annual amount of solid, liquid
and gaseous raw materials (except for water and air) extracted from the natural environment
to be used as material factor inputs in economic processing. The term “used” refers to
acquiring value within the economic system (see Fundamentals > system boundaries).
These materials consist of biomass, non-metallic minerals (sometimes also termed
construction and industrial minerals), metallic minerals (i.e. gross ores), and fossil energy
carriers. Concerning the water content of the raw materials, the convention is to account for
all raw materials in fresh weight, with the exception of grass harvest, fodder directly taken up
16
by ruminants, and timber harvest. These biomass materials are accounted for with a
standardised water content of 15%.
Physical imports and physical exports
(Tables B and C): These aggregates cover all
imported or exported commodities in tonnes. Traded commodities comprise of goods at all
stages of processing from basic commodities to highly processed products.
Net Additions to Stock – NAS
(Table F): NAS measures the ‘physical growth of the
economy’, i.e. the quantity (weight) of new construction materials accumulating in buildings,
infrastructures and of materials incorporated into durable goods with a live time longer than a
year such as cars, industrial machinery, and household appliances. Materials are added to
the economy’s stock each year (gross additions) and old materials are removed from stock
as buildings are demolished and durable goods disposed of (removals). These
decommissioned materials, if not recycled, are accounted for in DPO. Net additions to stock
are therefore not calculated by balancing additions to stock and stock depletion (as the
arrows in Figure 2 would suggest) but as statistical balance between inputs and outputs.
Apart from materials going on stocks in the use phase, also products can be put on stocks
before being used or traded. This in particular applies for example to fossil fuels or cereals,
where stock inventories can be considerable. NAS can also be negative, i.e. net-removals
from stocks. Negative NAS have hardly been observed in any industrialized countries, where
stock changes mainly refer to increases in infrastructure.
Domestic processed output – DPO
(Table D):
DPO measures the total weight of materials,
extracted from the natural environment or imported, that have been used in the national
economy before flowing to the environment. DPO comprises all waste and emission flows
that occur in the processing, manufacturing, use, and final disposal stages of the production-
consumption chain. This includes emissions to air, industrial and household wastes
deposited in uncontrolled landfills (whereas wastes deposited in controlled landfills are
regarded as an addition to the socio-economic stock), material loads in wastewater and
materials dispersed into the environment as a result of product use (dissipative flows). Also
materials that are deployed to ecosystems intentionally, such as fertilizers should be
accounted for as DPO. Recycled material flows are considered flows within the economy
(e.g. of metals, paper, glass) and thus are not considered as output (nor input).
Input and Output balancing items
(Table E): Although bulk water and air flows are
excluded from MFA, material transformations during processing may involve water and air
exchanges which significantly affect the mass balance. Balancing items are estimations of
these flows, which are not part of DE, DPO or NAS, because they are not included in the
definition of these flows. Balancing items mostly refer to the oxygen demand of various
17
combustion processes (both technical and biological ones), water vapour from biological
respiration, and from the combustion of fossil fuels containing water and/or other hydrogen
compounds. Also flows of considerable economic importance such as nitrogen which is
withdrawn from the atmosphere to produce fertilizer in the Haber-Bosch process or
groundwater used in the production of beverages are accounted for as balancing items. In
the compilation of these flows, only a few quantitatively important processes are taken into
account and the flows are estimated using generalized stoichiometric equations.
Having defined these material flow categories, we now can write a national material balance
equation in MFA terms:
DE + Imports + Input Balancing Items = Exports + DPO + Output Balancing Items + NAS
Apart from these direct flows, further flows can be considered in a broader MFA view. These
are: unused extraction associated to direct extraction activities, and upstream material use
associated with imports and exports (Eurostat 2001). The latter are usually termed raw
material equivalents (RME) of imports and exports. Both flows do not enter the focal socio-
economic system but the first, unused extraction remains within the natural system, and the
second, RME remains in foreign economies. Unused extraction comprises materials that
are moved or extracted from the environment without the intention of using them in economic
processing. This includes, for example, overburden or unused crop residues (e.g. straw that
is burned on field or ploughed into the soil. Unused extraction can be associated with the
domestic or foreign extraction of raw materials when the latter is attributable to the
production of imported goods. Per definition, materials extracted from the environment are
always raw materials. In contrast, imported and exported materials are always products
which have already undergone a more or less intensive transformation process before
entering or leaving the focal economy. Goods are traded in various stages of processing and
the upstream material requirements of imports and exports comprise both used extraction (=
raw materials) and unused extraction, together they are referred to as indirect flows. To
denote the upstream requirements of used extraction associated with imports or exports the
term "raw material equivalents" (RME) was coined (Eurostat 2001, Weisz et al. 2004).
Both the present version of the EW-MFA tables and this compilation guide cover the direct
flows only, RME and unused extraction are not included. In the case of RME, methods are
still under fast development and results (Wiedmann et al. 2013, Wood et al. 2014) are
changing significantly depending on the methods used (Schaffartzik et al. 2014). In the case
18
of unused extraction, data availability is poor and no sufficiently standardised methods have
been developed so far.
Residence principle
Like other environmental accounting systems (e.g. air emissions accounts (Eurostat 2009a)
MFA follows the residence principle in order to ensure consistency with national accounts.
Accordingly, EW-MFAs account for all material flows associated with transactions attributed
to so called resident units. In the system of national accounts (ESA 95), resident units are
defined as those units whose center of economic interest is located on the national economic
territory. A center of economic interest is given if the unit is engaged in significant economic
activities on the economic territory for a year or more or if it holds ownership of land or
buildings on the economic territory. The national economic territory encompasses the
geographic territory without extraterritorial enclaves and including territorial enclaves as well
as air space, territorial waters, deposits over which country has rights, etc.
For the most part, the sources of statistical data employed in MFA compilation are consistent
with the residence principle. In some cases, however, data adjustments are required. In
particular, this applies to fuel consumed in international transport (water, air, and road).
According to the residence principle, fuel that is consumed by resident units abroad (e.g.
bunkering of aviation fuel by domestic airlines on ROW-economic territory) has to be
accounted for in EW-MFA, while vice versa fuel provided to non-resident units domestically
has to be excluded. These flows, which can be of considerable size in some countries, are
usually not captured by production or trade statistics and have to be estimated. This
handbook provides some suggestions on how to estimate these flows, but the information
required for these estimates are difficult to obtain for most countries. In practical terms many
EW-MFAs still ignore these adaptations. Other areas, where standard statistical sources
provide data not fully consistent with the residence principle are tourism and activities in
extraterritorial enclaves (such as embassies or consulates). However, the related flows are of
a comparatively small size in most cases and statistical data or standardized estimation
procedures are hardly available. For these reasons, deviations from the residence principle
other than for fuel use are currently not considered in EW-MFA. The adjustments that are
required in order to ensure consistency with the residence principle are discussed in greater
detail in the section dealing with trade flows.
19
Data sources and quality of the accounts
Economy-wide materials flow accounts are meta-compilations of data from various official
statistics, most of which are regularly provided and updated by national statistical offices. DE
is mainly based on data from agricultural, forestry, fishery production, mining (including
geological surveys), and energy statistics. DPO is mainly based on emission inventories
(including NAMEA of Eurostat) and waste statistics. Import and export data are taken from
foreign trade statistics.
Basically, three types of data sources are useful for compiling MFAs. Data provided by the
national statistical offices of the country for which the MFA is complied, international
databases (such as those from Eurostat or different UN bodies such as the FAO or IEA,
Minerals statistics offered by different geological services such as the USGS or BGS, etc.)
and third, data from scientific reports, case studies, and other non-periodical data
compilations. Additionally, "educated guesses" by experts may occasionally turn out to be
the only means to complete the accounts.
National databases usually have the most reliable data for individual countries because they
dispose of the best primary sources and knowledge on national structures and individual
characteristics. However, international data sources can provide high quality data which have
the advantage of being standardized across countries and thus provide a good basis for
cross country comparisons. Often it is necessary to combine national and international data
sources in order to close data gaps or for cross checking. In this guide we refer mainly to
international databases.
One particular important quality criterion for MFA is its consistency. This includes ensuring
that the following general requirements are met.
(1) Only those data must be included which comply with the system boundary definition of
MFA.
(2) All data are measured in the same unit of tonnes (i.e. metric tonnes). If data are reported
in units other than tonnes they must be converted using appropriate coefficients.
(3) The compilation must be free of double counts. This means that each relevant flow is
accounted for only once.
(4) The compilation must be comprehensive. Often there are relevant material flows for
which statistical sources provide no or no appropriate data. The compilation of an MFA
therefore also involves estimated missing data. As such estimations are a common source of
20
incomparability, we particularly emphasise the description of possible estimation methods,
here. Whereas these estimation methods should provide some guidance as to how to
complete data gaps, they are not intended to represent the one solution that works best.
Different and possibly more accurate estimation methods may be applied based on national
data and national expertise.
(5) It must be ensured that the data are of sufficient quality. This is probably the most difficult
task. Judging the quality of statistical and other data requires profound knowledge and
sufficient experience in the respective fields. Moreover, the specific nature of the problems
typically varies across statistical data sources, countries, and points in time. For these
reasons it is hardly possible to provide standardised methods to judge the quality of all data
which are relevant for MFA.
The following chapters describe the most common and partly standardized methods based
on the guidelines developed for Eurostat (Eurostat 2012) but adapted to better fit a global
rather than a European perspective that we suggest for the evaluation of some of the most
common and quantitatively most severe data quality problems.
The future value of economy-wide material flow accounting will depend largely on its internal
consistency, its international comparability, and its potential to reflect a large variety of real
world processes. These are at times conflicting goals.
The MFA tables
Together with this manual, we provide a set of different tables that help compiling economy
wide Material Flow accounts. These tables are designed to facilitate data organisation, they
represent a structuring of material flows and thus are an important tool in the process of MFA
compilation. Six tables (A through F) and annexes (0 through 6) form a file in spreadsheet
format into which the collected MFA data can be entered according to the type of aggregate
to which they belong. These tables and especially the annexes provide valuable information
on the individual items to be included in an MFA, including their assigned codes in different
systems of notation. The MFA Tables have a hierarchical structure and differentiate between
four levels of detail.
Data on domestic extraction (DE) of biomass, metal ores, non-metallic minerals, and of
fossil energy carriers must be entered into Table A. The individual items which make up
each of these kinds of domestic extraction are listed under the respective heading. DE of
biomass, for example, consists of primary crops (A. 1.1), of used crop residues, fodder crops
21
and grazed biomass (A.1.2), wood (A.1.3) and of the biomass extracted through fish capture
(A.1.4) and hunting and gathering (A.1.5). For reasons of consistency, all tables are
organized in the same way and along the same number of items.
Tables B and C are designed for the organisation of data on trade flows (imports and
exports). In Table B (imports) and Table C (exports) data on total trade flows are requested.
All trade data is organised into similar categories as the data on domestic extraction, the
major difference being that the items traded comprise not only primary but also processed
material. The latter may consist of either biomass, metal ores and concentrates, non-metallic
minerals, fossil energy carriers, or waste imported for final treatment or disposal. Products
which cannot be clearly identified as belonging to one of these four categories should be
included under “other products”. The procedure for determining where a given trade flow
should be entered is described in annexes of the MFA tables for different trade classification
systems (CPA, SITC and HSCN).
Data on discharges into the environment are organised in Table D as domestic processed
output and may consist in emissions to air (D.1.) or water (D.3.), in landfilled waste (D.2.) or
in discharges that result from the dissipative use of products (D.4.) as would be the case in
the application of fertilizer, for example. Additionally, data on dissipative losses (D.5.) are
entered into this table.
Finally, balancing items are represented in Table E. These data are organised according to
whether they comprise those gases required on the input side (E.1.) to balance an output
which is already accounted for or gases which must be considered on the output side (E.2.)
to balance a given input.
All of the data collected and organised in Tables A through E can then be aggregated
permitting for the derivation of indicators in Table F. Based on known volumes of domestic
extraction (F.1.), imports (F.2.), and exports (F.3.), the direct material input (F.4.), domestic
material consumption (F.5.), and the physical trade balance (F.6.) can be calculated. By
additionally considering domestic processed output (F.7.) and balancing items (Table E), net
additions to stock (F.8.) may be determined.
In order to facilitate the proper organisation of data from different sources within one
harmonious system, a set of annexes in spreadsheet format provides information on the
correspondence between the various statistical codes used to designate relevant items. In
Annex 0 the structure of Tables A to F is shown in correspondence with the structure of
the MFA tables. Annex 1 and b show the Classification of Products by Activity (CPA
2002 and 2008) in its correspondence to domestic extraction and trade flows. Domestic
22
extraction of biomass may also be labelled with FAO codes; the according correspondence
is provided in Annex 2. In Annex 3a and b the trade flows (Tables B and C) are presented
in correspondence with the Standard International Trade Classification (SITC) rev. 1, rev.
3 and rev. 4 codes as well as CN and HS classification. Annex 4a and b provide information
on the correspondence between MFA classification and FAOSTAT classification of trade with
agricultural and forestry products. Annex 5 is a correspondence table between MFA
categories and the fossil energy carrier classification according to IEA. Annex 6 contains a
correspondence table for mineral and fossil materials as listed in the United Nations
Industrial Commodities Production Statistics and material flow groups.
23
Table A: Domestic extraction
Biomass
Table 1: Domestic extraction of biomass
1 digit 2 digit 3 digit
A.1 Biomass
A.1.1 Primary crops
A.1.1.1 Cereals
A.1.1.2 Roots, tubers
A.1.1.3 Sugar crops
A.1.1.4 Pulses
A.1.1.5 Nuts
A.1.1.6 Oil bearing crops
A.1.1.7 Vegetables
A.1.1.8 Fruits
A.1.1.9 Fibres
A.1.1.10 Other crops (Spices, Stimulant crops,
Tobacco, Rubber and other crops)
A.1.2 Crop residues (used)
A.1.2.1 Straw
A.1.2.2 Other crop residues (sugar and fodder beet
leaves, other)
A.1.3 Fodder crops and
grazed biomass
A.1.3.1 Fodder crops (incl. harvest from grassland)
A.1.3.2 Grazed biomass
A.1.4 Wood
A.1.4.1 Timber (Industrial roundwood)
A.1.4.2 Wood fuel and other extraction
A.1.5 Fish capture and
other aquatic animals and
plants
A.1.5.1 Fish capture
A.1.5.2 All other aquatic animals and plants
A.1.6 Hunting and
gathering
Introduction
Biomass comprises organic non-fossil material of biological origin. According to MFA
conventions, domestic extraction (DE) of biomass includes all biomass of vegetable origin
24
extracted by humans and their livestock, fish capture, and the biomass of hunted animals.
Biomass of livestock and livestock products (e.g. milk, meat, eggs, hides) are not accounted
for as domestic extraction (see below).
Biomass accounts for 30% of total global DE (Krausmann et al. 2009). Values of per capita
biomass harvest average at 3 t and range between 0.5 and 20 t. Typically, the share of
primary crops of total harvest amounts to 35%, crop residues 20%, fodder crops and grazed
biomass 32%, and wood 10%. Fishing and hunting and gathering are of minor quantitative
importance in most cases. The actual quantitative and qualitative structure of biomass
harvest may vary significantly depending on the regional characteristics of the land use
system. In general, DE of biomass is highest in countries with low population densities or
high livestock numbers per capita.
DE of biomass includes a number of raw materials which differ significantly in terms of their
technical, economical, and environmental properties, which are reflected in the 2 to 4 digit
structure of the MFA Table (see Table A.1.).
Economic value: The economic value of biomass ranges from very low (less than 10€/t, e.g.,
crop residues) to medium high (e.g., spices, stimulants, fish catch); the vast majority of
extracted biomass is comprised of bulk raw materials with low value (10-100€/t, e.g., cereals,
roundwood).
Socio-economic use: Biomass provides raw materials for the food system, but also energy
carriers and industrial raw material for a wide range of processes and products (e.g., fibres,
chemical compounds, construction material, industrial raw material).
Environment: The extraction of biomass materials can be related to specific land use and
land cover types (cropland, grassland, and woodland) and environmental pressures
(deforestation, soil erosion, ground water pollution, biodiversity loss, over-fishing).
Data sources
Statistical reporting of biomass extraction has a long tradition. Most fractions of biomass
harvest are reported by national statistical offices (or national offices concerned with
agriculture and forestry) in their series of agricultural, forestry, and fishery statistics.
Additional information useful for biomass accounts may be provided by national food, feed,
and wood balances. The accounting frameworks are well established and show a high
degree of international standardisation and accuracy. Both national and international data
sources generally cover the harvest of all types of primary crops (1.1) and wood (1.4), and
biomass extraction by fishing and hunting activities (1.5 and 1.6). In some cases crop
residues (1.2.1) and harvested fodder crops and biomass harvested from grassland (1.2.2.1)
25
are reported in statistical accounts as well, but grazed biomass (1.2.2.2) is usually not
estimated by official statistics. For these items, which usually are of considerable quantitative
significance, this guide provides standard estimation procedures.
The most consistent international source of data on biomass extraction is the statistical
database provided by the United Nations Food and Agricultural Organization. The FAO
database covers a huge range of data concerning agriculture, forestry, and fishery, and the
food system on the level of nation states in time series since 1961. The structure of the EW-
MFA tables is compatible with the data provided by the FAO (see Annex 2 for a detailed
correspondence table).
In discussing the aggregation and estimation procedures, the guide follows the two and three
digit level of the MFA tables.
Conventions
Terminology and classification: The terminology and classification of biomass items and
aggregates used in this guide by and large follow the terminology used by the FAO and may
differ from the terminology used in national statistics.
Moisture content: A characteristic feature of all types of biomass is its considerable
moisture content (mc), which may account for more than 95% in the case of fresh living plant
biomass. However, the moister content is very variable across plant parts and species and
vegetation periods. In many cases, biomass is harvested at low moisture content (e.g.,
cereals) or dried during the harvesting process (e.g., hay making). In accordance with
agricultural statistics, biomass is accounted for at its “as is weight” at the time of harvest.
Few crops may be harvested at different water contents (fresh weight (80-95% mc) or air dry
(15% mc)); in these cases, moisture content has to be standardised according to MFA
conventions. This applies only for the categories A.1.2.2.1 fodder crops, A.1.2.2.2 grazed
biomass, and A. 1.4. wood.
Primary harvest and crop-residues: In many cases, primary harvest (i.e. the used fraction
accounted for in MFA) is only a fraction of total plant biomass. However, the remaining crop-
residue or a certain fraction of it may be subject to further socio-economic use and is
accounted for in MFA. The most prominent example for this is (cereal)straw, which may
either be used as bedding material for livestock, feed stuff, for energy generation or as raw
material used for other purposes (crop residues which are ploughed into the field or burnt are
not accounted for as DE). This also applies to wood harvest, where fellings and removals are
distinguished.
26
Livestock: According to MFA system boundaries and conventions, livestock is considered
an element of the physical compartment of the socio-economic system. Consequently, all
direct biomass uptake by livestock is accounted for as domestic extraction, whereas livestock
and livestock products are considered secondary products and not accounted for as
domestic extraction. Exceptions are hunted animals and fish capture, which are considered
an extraction from the natural environment and, therefore, are accounted for as DE. Biomass
uptake by livestock consists of market feed (cereals, food processing residues, etc.), fodder
crops (fodder beets, leguminous fodder crops, etc.), crop residues used as feed (straw, beet
leaves, etc.), and grazed biomass. Domestic extraction of market feed is included in the
extraction of primary crops (item A.1.1), crop residues used for feed in item A.1.2.1 and
fodder crops, grassland harvest and grazed biomass in item A.1.2.2.
Data Compilation
A 1.1 Crops
Harvest of primary crops is comprised of primary harvest of all crops from arable land and
permanent cultures. This includes major staple foods from crop- and garden land such as
cereals, roots and tubers, pulses, vegetables as well as commercial feed crops, industrial
crops and all fruits and nuts from permanent cultures. The FAO’s crop production database
distinguishes roughly 160 different types of primary crops (including fruits and nuts from
permanent cultures). In most countries, the numbers of primary crops will be much smaller;
for European countries, it typically ranges between 30 and 50.
Data on the extraction of primary crops are provided in good quality by national and
international statistical sources and can be used directly for MFA compilation without further
processing. With respect to aggregation of the harvest of individual crops to the 3 digit level
of the standard tables, we follow the classification scheme suggested by the FAO which is
also compatible with CPC classification. The table in the Annex 2 of the EW-MFA tables lists
all common crop types according to the 3 digit level of the standard tables (A.1.1.1 to
A.1.1.10). Crops not identified in this list, but reported by national statistics should be
classified with regard to the 3 digit level or, if this is not possible, subsumed under A.1.1.10
(other crops) (e.g. flowers or nursery products).
A 1.2 Crop residues
In most cases, primary crop harvest is only a fraction of total plant biomass of the respective
cultivar. The residual biomass, such as straw, leaves, stover etc., often is subject to further
economic use. A large fraction of crop residues is used as bedding material in livestock
husbandry but crop residues may also be used as feed, for energy production or as industrial
27
raw material. The used fraction of crop residues is accounted for as DE. In many countries
this is a considerable flow which may account for 10-20% of total biomass DE. Residues
which are left in the field and ploughed into the soil or burned in the field are not accounted
for as DE.
MFA accounts distinguish between two types of crop-residues:
A.1.2.1 Straw of cereals: all harvested straw of cereals including maize
A.1.2.2 All other crop-residues: For most European countries this will refer to tops and leaves
of sugar beets and only occasionally to residues from other crops (e.g. sugar cane, etc.).
In some cases, all or some harvested crop-residues are accounted for in national agricultural
statistics. However, FAOSTAT nor national agricultural statistics in most countries report any
data on harvested crop-residues. In case national statistics provide data on the used fraction
of crop-residues, these can directly be used for MFA compilation without further processing.
For most countries, however, crop-residues and the assigned fraction will have to be
estimated:
Step 1: Identification of crops which provide residues for further socio-economic use. In most
cases this will include all types of cereals (A.1.1.1), sugar crops (A.1.1.3) and oil bearing
crops (A.1.1.6), only in exceptional cases will other crops have to be considered.
Step 2: Estimation of available crop residues via harvest factors
The procedure to estimate the amount of crop residues available is based on assumptions
on the relation between primary harvest and residues of specific crops. In agronomics,
different measures for this relation are used: the most prominent are the harvest index, which
denotes the share of primary crop harvest of total aboveground plant biomass, and the grain
to straw ratio. This relation is typical for each cultivar, however, subject to changes over time
as plant breeding aims specifically at increasing the harvest index of cultivars. Based on this,
we can calculate a harvest factor, which allows for the extrapolation of total residue biomass
from primary crop harvest (equation (1)). Typical harvest factors for crops in different world
regions, which can be used in absence of national information, are provided in Table 2a.
Note: The harvest factors in Table 2a refer to dry matter of both crop and crop residue. MFA
reports crops and crop residues with the moisture content at harvest (as is weight). In most
cases the moisture content of crop and crop residues is equal (e.g. cereal straw and grain
both have a mc of roughly 16%). In this case the factors in Table 2a can be applied without
modification; if the moisture content between crop and crop residue differs, however,
corresponding adjustments have to be made.
(1) Available crop residues [t (as is weight)] = primary crop harvest [t (as is weight)] * harvest factor
28
Table 2: Standard values for harvest factors (a) and recovery rates (b) for common
crop residues.
E. Asia E. Europe
Latin
America
N. Africa
W. Asia
N. America
Oceania
S. and C.
Asia
Subsahara
n Africa
W.
Europe
a) Harvest factors. Crop residue [g dry matter (DM) per year] = primary crop harvest [g DM/yr] * harvest factor.
Wheat, other cereals 1.5 1.5 1.5 1.5 1.2 1.7 2.3 1.0
Rice, Paddy 1.0 1.2 1.2 1.2 1.2 1.5 1.5 1.2
Maize 3.0 1.9 3.0 3.0 1.2 3.5 3.5 1.2
Millet 3.0 1.9 3.0 3.0 1.2 3.5 3.5 1.2
Sorghum 3.0 1.9 3.0 3.0 1.2 3.5 3.5 1.2
Roots and Tubers 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
Cassava 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
Sugar Cane 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7
Sugar Beets 0.7 0.5 0.7 0.7 0.5 0.7 0.7 0.5
Pulses 0.4 1.0 0.4 0.4 1.0 0.4 0.4 1.0
Soybeans 1.2 1.5 1.5 1.5 1.2 1.5 1.5 1.2
Groundnuts in Shell 1.2 1.2 1.5 1.5 1.2 1.5 1.5 1.2
Oil Palm Fruit 1.5 1.9 1.9 1.9 1.9 1.9 1.9 1.9
Castor Beans 0.4 1.0 0.4 0.4 1.0 0.4 0.4 1.0
Rapeseed, oil crops 2.3 1.9 2.3 2.3 1.9 2.3 2.3 1.9
Permanent crops 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5
b) Recovery rates: Used crop residues [g DM] = available residues [g DM] * recovery rate.
Cereals 0.8 0.75 0.8 0.8 0.7 0.9 0.9 0.7
Roots and Tubers 0.75 0.25 0.75 0.75 0 0.75 0.75 0
Sugar Cane 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9
Sugar Beets 0.75 0.25 0.75 0.75 0 0.75 0.75 0
Sugar Crops nes 0.8 0.3 0.8 0.8 0 0.8 0.8 0
Beans, Dry 0.5 0.5 0.5 0.5 0 0.5 0.5 0
Other pulses 0.8 0.75 0.8 0.8 0.7 0.9 0.9 0.7
Other oil crops 0.8 0.75 0.8 0.8 0.7 0.9 0.9 0.7
Oil Palm Fruit 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9
Sunflower Seed 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5
Rape seed 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7
Source: based on data provided in Krausmann et al. 2013 and Wirsenius 2000.
Step 3: Estimation of fraction of used residues
In most cases, only a certain fraction of the totally available crop-residue will be harvested
and subject to further use. The actual fraction of residues used (recovery rate) can be
estimated based on expert knowledge or specific studies. In cases in which no reliable
information on the country-specific share of used residues is available, recovery rates
provided in Table 2b can be applied, but It has to be noted that these are only rough
29
approximations and actual rates may vary considerably across countries and over time. The
amount of used crop residues can be calculated using equation (2).
(2) Used crop-residues [t (as is weight)] = available crop-residues [t (as is weight)] * recovery rate
A.1.3 Fodder crops (incl. biomass harvested from grassland) and grazed
biomass
This category subsumes different types of roughage including fodder crops, biomass
harvested from natural or improved grassland (meadows) and biomass directly grazed by
livestock. Coverage of these large flows in statistics is usually poor. The most important
types of fodder crops may be reported in harvest statistics (e.g. maize for silage, leguminous
fodder crops, hay) and for some countries national feed balances exist from which data on
biomass harvested from grassland and grazed biomass can be derived. In case no reliable
data for both fodder crops (A 1.3.1) and grazed biomass (A 1.3.2) exist, formula (5) (see
section A 1.3.2 below) can be used to estimate the total amount of biomass subsumed under
A 1.3. In this case, the calculated total requirement for roughage is assumed to be equal to
the total amount of harvested fodder crops and grazed biomass (A 1.3).
A.1.3.1 Fodder crops (incl. harvest from grassland)
This category includes all types of fodder crops including maize for silage, grass type and
leguminous fodder crops (clover, alfalfa etc.), fodder beets and also mown grass harvested
from meadows for silage or hay production. All commercial feed crops such as barley, maize,
soy bean etc. which may also be used for food production or as industrial raw material are
not included in this category. Fodder crops are typically reported by national agricultural
statistics. In some cases, standardisation of moisture content is required:
Step 1: Fodder crops which require a standardisation of moisture content must be identified:
All grass type fodder crops and biomass harvested from meadows (FAO codes 638-643 and
857-859, see Annex 2 of the EW-MFA tables) can be harvested and used either fresh (i.e.
with a high moisture content; for immediate feeding or silage production) or at air dry weight
(hay). According to MFA conventions, these crops are accounted for at air dry weight, i.e., at
a standardised moisture content of 15%. In case no information on the moisture content of
the reported data on fodder crops is available, a rough check can be made by looking at
yields per area unit: The yield of grass type fodder crops at air dry weight [t/ha/yr] is typically
in the range of 2-3 times the yield of cereals (e.g., wheat or barley). Fresh weight yields are
significantly higher and are 5-15 times the yield of cereals.
30
Step 2: The weight of fodder crops which are reported in fresh weight (i.e., at a moisture
content of 80%) has to be reduced to a moisture content of 15% by applying equation (3) and
then (4):
(3) Factor
mc
= (1-mc
fresh
) / (1-mc
air dry
) = 0,2 / 0,85 = 0,235
(4) Air dry weight (at 15% mc) = fresh weight (at 80% mc) * Factor
mc
A.1.3.2 Grazed biomass
According to MFA conventions, biomass grazed by livestock is accounted for in material flow
accounts. This type of biomass extraction is not reported in standard agricultural statistics. In
some cases, information on grazing is available from national feed balances or can be
obtained from local agricultural experts. These data can be used for MFA accounts,
eventually quantities given in other units (e.g. dry weight or digestible energy) have to be
converted to air dry weight (15% mc) with the support of information from feed composition
tables or expert knowledge or by using equation (4).
Different methods are available to estimate the amount of biomass grazed by livestock: One
method uses the number of animals, which is well documented in agricultural statistics, and
calculates an average feed or roughage demand by using information on daily feed intake
per head. This approach is described in detail as method A in this manual. The second
approach uses data on the amount of animal products (meat, milk, eggs) produced and
information on the ratio of feed required to produce one unit of output (feed conversion rate).
These methods have been used in material flow accounts and allow for a rough estimate of
biomass uptake by grazing.
Method A: Demand-driven feed balance to identify grazing gap.
Information on livestock numbers are typically well reported in national and international
agricultural statistics. Based on information on roughage requirements of ruminants and
other grazing animals and the number of livestock, the demand for grazed biomass can be
estimated. Daily biomass intake by grazing depends on the age and live weight of the
animal, animal productivity (e.g., weight gain, milk yield), and the feeding system (e.g., feed
composition) and therefore may vary considerably within one species even within a country
depending on the prevalent livestock production systems. The procedure described here is a
simplified version of a feed balance model used in estimates of global biomass harvest (see
Krausmann et al. 2008 and Krausmann et al. 2013, see this literature for more information
and detailed feed balances). Table 3 provides information of average roughage uptake by
31
livestock species in different production systems (3a) and averages for different world
regions over time (3b). The values refer to air dry weight (i.e. at a moisture content of 15%)
and already take into consideration that the share of market feed and crop residues in feed
ratios ranges between 5 and 50% (dry matter basis, average across all species). The
coefficients in Table 3 can be used to calculate total roughage requirement (equation (5)).
Table 3a: Typical roughage intake by grazing animals
Annual intake
Traditional livestock
system
[t/head and year]
Annual intake
Industrial livestock
system
[t/head and year]
Cattle (and buffalo) 1.5 5.5
Sheep and goats 0.43 0.64
Horses 3.0 4.3
Mules and asses 1.8 2.6
Values represent annual intake of air dry biomass (15% mc) in t / head and year. Sources: The values
are typical for industrialised livestock production systems and derived from national feed balances and
literature (Wirsenius 2000; Hohenecker 1981; Wheeler et al. 1981; BMVEL 2001).
Table 4b: Estimate of annual intake of forage by cattle and buffalo in 1960, 1990 and
2005
t/head/y
South
&
Central
Asia
East
Europe
North
Africa
&
West
Asia
North
America
&
Oceania
West
Europe
Sub-
Saharan
Africa
Latin
America &
Caribbean
East
Asia
World
1960 1.6 2.3 2.3 3.4 3.3 2.4 3.1 2.0 2.5
1990 1.5 2.9 2.6 5.1 4.5 2.4 3.4 2.6 2.9
2005 1.6 2.8 2.5 5.6 5.1 2.3 3.8 3.8 3.3
Forage intake includes grazed biomass, hay and forage crops. Values are given in in t (at 15%mc)
/head /y. Intake of market feed and crop residues is already discounted for. Source: derived from
Krausmann et al. 2013.
(5) Roughage requirement = livestock [number] * annual feed intake [t per head and year]
Roughage uptake may be covered from grass type fodder crops, hay or silage or from
grazing. To estimate biomass uptake by grazing, total roughage uptake has to be reduced by
the amount of available fodder crops and biomass harvest from grassland (item A.1.3.1)
(equation (6)).
(6) Demand for grazed biomass = roughage requirement [t at 15% mc] – fodder crops [t at 15% mc].
32
Method B: Extrapolation from animal production (feed conversion efficiency):
National and international agricultural statistics also report data on primary animal products
such as meat and milk. From this information and appropriate feed conversion coefficients
(feed demand per unit of product) the demand for feed and subsequently also grazed
biomass can be extrapolated. It is important that the applied feed conversion coefficients
take the demographic structure of the herd into account. This means, for example, that not
only the feed consumed by the cows which produce milk is taken into account, but also the
feed required for the calves, heifers and steers required to maintain the herd of cows. Data
on domestic production of animal products needs to be corrected for trade with live animals:
an imported steer which is slaughtered after import will be recorded in production statistics,
but the feed required to produce the steer was not consumed in the importing but in the
exporting country. Therefore, the slaughter weight of imports and exports of live animals has
to be subtracted or added, respectively, from domestic meat production. Another source of
underestimation of this method concerns livestock services other than meat and milk. In
particular in low income countries, a significant share of the total livestock may be used
primarily to provide draught power (e.g. horses, oxen, buffaloes) or wool (sheep). The feed
demand to provide these services will not be accounted for with this method and needs to be
estimated separately (e.g. using method A).
Method B has been applied in the MFA accounts of the CSIRO and UNEP Asia-Pacific
Material Flows database (CSIRO 2010) using coefficients derived from Wirsenius 2000. We
here present a simplified version of this method: In a first step the amount of feed energy
(digestible energy) required to produce each type of primary animal product (carcass in
slaughter weight or whole milk by animal species) is calculated using conversion coefficients
given in Table 4a (equation (7)). The share of grazed biomass in total feed is calculated
using equation (8) using information on the region specific share of roughage in feed (Table
4b). The amount of grazed biomass is converted from digestible energy into mass at 15%
moisture content using an average value of digestible energy per unit of roughage of 10.4
MJ/kg DM (Wirsenius 2003, Table B.5) and the moisture content value of 0.85 (equation (9).
In case information on the harvest of forage crops (grasses, legumes, corn for silage) is
available and reported under A1.3.1, these have to be subtracted from total roughage
demand.
(7) Feed requirement for product i [GJ] = kg product i [t] * feed conversion coefficient product i [KJ/kg]
(8) Roughage demand product i [GJ] = Total feed requirement i [GJ] * share of roughage [%]
(9) Grazed biomass product i [t at 15% mc] = roughage demand product i [GJ] / 10.4 [MJ / kg dry
matter] / 0.85 - fodder crops [t at 15% mc]
33
Table 5a: Feed conversion coefficients
South &
Central
Asia
East
Europe
North
Africa &
West
Asia
North
America
&
Oceania
West
Europe
Sub-
Sahara
Africa
Latin
America
&
Caribb.
East
Asia
Cattle
meat
MJ/kg
carcass
499.0 160.0 151.0 132.0 126.0 373.0 264.0 313.0
Cow
milk
MJ/kg
milk
13.8 10.0 14.3 6.9 7.4 29.1 13.2 11.0
Sheep
and goat
meat
MJ/kg
carcass
998.0 320.0 570.0 264.0 252.0 746.0 528.0 626.0
Sheep
and goat
milk
MJ/kg
milk
27.6 19.9 28.6 13.8 14.8 58.2 26.4 21.9
Feed energy requirement per unit of animal product (MJ digestible energy per kg of product) by world
region. Meat refers to carcass weight (slaughter weight), milk to whole, fresh milk. Based on Table 3.9
in Wirsenius 2000.
Table 6b: Share of roughage in total feed energy supply by world region.
% of
digestible
energy
South &
Central
Asia
East
Europe
North
Africa &
W. Asia
North
America
& Oceania
West
Europe
Sub-
Saharan
Africa
Latin
America
& Carrib.
East Asia
Milk cattle 65%
80%
64%
39%
43%
69%
77%
73%
Beef cattle
67%
79%
64%
60%
58%
69%
77%
69%
Sheep and
goats 100%
100%
100%
80%
80%
100%
100%
100%
Roughage includes forage crops such as grasses, legumes, corn for silage and grazed biomass.
Values in % of total digestible energy. Based on figure 3.28 in Wirsenius 2000 (p. 139), weighted by
digestible energy content (table B5 in Wirsenius 2003).
Note: Both methods are strongly simplified versions of full scale feed balances. Results
obtained with method A and B for a specific country can differ considerably. Reasons for
inconsistency may lie in primary data (inconsistencies between livestock numbers and
animal production), simplified assumptions on feed requirements, feed composition and
energy content of feed stuff and also differences in terms of comprehensiveness (e.g.
method B focusses on meat and milk and ignores other services such as draught power).
Also limitations in the application of the provided region specific coefficients to individual
countries and their temporal variability can cause inconsistencies between the two methods.
Both methods have their specific shortcomings and the described procedures are strong
simplifications of feed balances and provide only rough estimates of grazed biomass. More
detailed methods which take national data, information of feeding systems and the full range
of animal species and animal products into account are presented in Wirsenius 2000 and
2003, Krausmann et al. 2013 and Herrero 2013.
34
Cross check: Supply estimate via grazed area and information on area yield.
In many countries, land use statistics provides data on the extent of grazing land (often
differentiated by quality or intensity) in their agricultural or land use statistics. Based on
information on the extent of pastures and typical biomass yield per unit of area, the
potentially available biomass for grazing can be calculated, assuming an optimum utilization
of pasture resources. Country or region specific area yields of pastures and rangelands can
be estimated based on expert knowledge and literature data. Table 5 provides information on
typical grazing yields for different quality types of pastures in Central Europe (based on data
for Austria). These data serve only as an example as pasture yields vary largely according to
climate, soil conditions and management (irrigation, fertilization). To apply this crosscheck,
country specific information is indispensable. Grazing potential can be calculated using
equation (10).
(10) Grazing potential [t at 15% mc] = pasture area [ha] * pasture yield [t at 15% mc / ha]
Table 5: Typical area yield of permanent pastures
Yield range
[t at 15%mc / ha]
Average yield
[t at 15%mc / ha]
Rough grazing, alpine pasture <1 0,5
Extensive pasture 1-5 2,5
Improved pasture 5-10 7,0
Source: The values are derived from data for Austrian grassland systems given in Buchgraber et al.
(1994) and can be assumed typical for Central Europe.
The calculated demand for grazed biomass should be lower or equal to the calculated
potential supply of grazable biomass. If this is not the case, two aspects should be
considered, which may, after expert consultation, lead to an adaptation of the estimates:
a) the yield factors have been estimated too low
b) the daily intake factors of livestock have been assumed too high.
Other reasons may be an exceptionally high share of market feed and feed concentrate in
feed ratios, overgrazing of pasture resources or significant grazing on areas other than those
reported as pasture in land use statistics (woodlands, waste lands etc.).
If no revisions are plausible or possible, the lower of the two estimates should be considered.
35
A.1.4 Wood
This category comprises of timber or industrial roundwood (A.1.4.1) and fuel wood (A.1.4.2).
It includes wood harvest from forests and also from short rotation plantations or wood from
agricultural land.
Extraction of wood is reported in forestry statistics which usually differentiate between
coniferous and non-coniferous wood. Wood from short rotation plantations may also be
recorded in agricultural statistics, because short rotation forests are considered cropland in
many countries. National wood balances, if available, often provide more comprehensive
datasets, because they also include wood harvested from non-forested land.
Wood is usually reported in terms of volume rather than weight. Units used are stacked (or
piled) cubic meters and solid cubic meters (scm). One stacked cubic meter is considered
equal 0.70 solid cubic meters. For MFA accounts, volume measures have to be converted
into weight measures using standard conversion factors given in Table 6.
Table 6: Standard factors to convert quantities given in volume (scm) into weight (at
15% mc) for coniferous and non-coniferous wood.
Density [t DM / scm]* Density [t at 15% mc / scm]
Coniferous 0,44 0,52
Non-coniferous 0,58 0,68
EU25 average (80% coniferous) 0,47 0,55
*These factors refer to t DM per scm green volume. Source: Based on factors used in IPCC
greenhouse gas inventories (Penman et al. 2003).
Fellings vs. removals, bark:
Forestry statistics, especially forest inventories, sometimes distinguish between fellings and
removals. MFA considers only the biomass removed from forests for further socio-economic
use, i.e. wood removals. All biomass not removed (branches, root-stock, etc.), i.e. fellings
minus removals, is not accounted for in MFA. This differentiation has to be considered.
Special care must be taken concerning the issue of bark, which accounts for approximately
10% of stem wood weight. Wood removals are usually reported in scm under bark (i.e.
without bark), although wood is removed including bark and a significant fraction of the bark
is subject to further socio-economic use (e.g., energy production). In order to correct wood
removals reported under bark for bark, we use an extension factor derived from typical
values for the bark fraction of stem wood (equation (11):
(11) wood removals incl. bark [t at 15% mc] = wood removals under bark [t at 15% mc] * 1.1
36
A.1.5 Fish capture and other aquatic animals/plants
Fish capture and extraction of other aquatic animals and plants is reported in national fishery
statistics and by FAO fishery statistics (FISHSTAT; http://www.fao.org/fi/default.asp). Fish
and seafood production from aquaculture is not considered domestic extraction but a
secondary product of the livestock sector (see section fundamentals). Therefore, only fish
capture (including recreational fishing) and other animals and plants extracted from
unmanaged fresh and seawater systems should be reported under item 1.5 in Table A of the
EW-MFA tables. In accordance with the residence principle, all landings of national vessels
should be included, regardless of the geographic location of landings.
A.1.6 Hunting and gathering
This type of extraction is quantitatively of minor significance and is only accounted for if data
are available in national statistics. A conversion from pieces or other physical units into
tonnes might be necessary. The 2013 version of the Eurostat MFA compilation guide
provides a long list of average weight of hunted animal species (see Eurostat 2013).
Specific issues related to DE of biomass
Biomass production from subsistence agriculture and home gardening: According to
MFA system boundaries, biomass harvest from subsistence agriculture and home gardening
is regarded as domestic extraction of biomass. In industrialized countries, these flows usually
are of minor economic and physical significance and usually not included in agricultural
statistics. Currently, for European countries, no reliable data and estimation procedures to
quantify these flows exist and they are not considered in MFA accounts for practical reasons.
In developing countries, though, this category can be of significant size. Estimation
procedures might have to be developed.
Biomass waste from management of parks, infrastructure areas, gardens etc.: A
significant amount of biomass is generated as a by-product of management of home
gardens, infrastructure areas, public parks, and sports facilities etc. A certain fraction of this
biomass flow, which comprises mown grass, woody biomass, residues from pruning and
foliage etc., may be subject to further socio-economic use, e.g. for energy generation or the
production of compost or it may appear in waste statistics. According to MFA system
boundaries, these fractions are regarded as domestic extraction of biomass (domestic
processed output, respectively). However, due to lack of reliable data and estimation
37
procedures they are currently not accounted for. Recently, this biomass flow has received
increasing attention in the context of strategies for sustainable resource use and might be
included at a later stage of MFA method development.
Biomass harvest from set-aside agricultural land: An increasing amount of agricultural
land in the European Union is set-aside. In many cases, this land, however, does not remain
uncultivated but is used for the production of renewable resources, such as oil crops or short
rotation forests etc. Usually, the biomass from these areas will be considered in national
agricultural statistics, in some cases it might be recorded in separate statistical accounts or
sources. In any case, it has to be accounted for as domestic extraction and subsumed under
the respective item (e.g. under A.1.1.6 oil bearing crops or A.1.4.2 wood fuel).
38
Metal ores and non-metallic minerals
Table 7: Domestic extraction of metal ores
1 digit 2 digit 3 digit
A.2 Metal ores
(gross ores)
A.2.1 Iron ores
A 2.1 Iron ores – gross ore
M2.1 Iron ores – metal content
A.2.2 Non-ferrous metal ores
A.2.2.1 Copper ores - gross ore
M.2.2.1 Copper ores - metal content
A.2.2.2 Nickel ores - gross ore
M.2.2.2 Nickel ores - metal content
A.2.2.3 Lead ores - gross ore
M.2.2.3 Lead ores - metal content
A.2.2.4 Zinc ores - gross ore
M.2.2.4 Zinc ores - metal content
A.2.2.5 Tin ores - gross ore
M.2.2.5 Tin ores - metal content
A.2.2.6 Gold, silver, platinum and other precious metal ores
- gross ore
M.2.2.6 Gold, silver, platinum and other precious metal ores
- metal content
A.2.2.7 Bauxite and other aluminium ores - gross ore
M.2.2.7 Bauxite and other aluminium ores - metal content
A.2.2.8 Uranium and thorium ores - gross ore
M.2.2.8 Uranium and thorium ores - metal content
A.2.2.9 Other metal ores - gross ore
M.2.2.9 Other metal ores - metal content
39
Table 8: Domestic extraction of non-metallic minerals.
1 digit 2 digit 3 digit
A.3 Non-metallic
minerals
A.3.1 Ornamental or building stone
A.3.2 Limestone, gypsum, chalk, and dolomite
A.3.3 Slate
A.3.4 Gravel and sand
A.3.5 Clays and kaolin
A.3.6 Chemical and fertilizer minerals
A.3.7 Salt
A.3.8 Other mining and quarrying products n.e.c.
A.3.9 Excavated soil, only if used (e.g for construction work)
Introduction
Metal ores and non-metallic minerals are the two major groups of minerals that are
distinguished at the 1 digit level of the MFA classification. All minerals together accounted for
about 51% of the global DE in 2005 (Krausmann et al. 2009), to which metal ores contribute
a share of around 17%. Still, a separate representation of metals at the 1 digit level is
justified due to their outstanding strategic importance for the industrial metabolism and their
comparatively high economic value.
It should be noted that the classification of minerals presented in Tables A.2 and A.3 of the
EW-MFA tables does not explicitly distinguish between non-metallic industrial minerals and
construction minerals, a distinction that has been applied widely in material flow studies in
particular in early years. The reason is that this distinction never was unambiguously and
properly defined, as the same mineral often can be used for both industrial and construction
purposes. Additionally, construction materials also go through some industrial processing.
For a rough indication of the magnitude of minerals mainly destined for the use in the
construction sector, the sum of A.3.1, A.3.2, A 3.4, A 3.5 and A 3.9 can be taken. At the
detailed level of data compilation, as described below, a more accurate distinction is also
possible.
It is important to keep in mind that the category “domestic extraction of minerals” does not
include the extraction of gases from the atmosphere for industrial purposes, such as the
extraction of nitrogen in the Haber-Bosch process. These flows, if quantitatively important,
are accounted for as balancing items (see the chapter on table G).
40
Per capita minerals extraction in Europe averaged at 8.1 t and ranged typically between 4
and 24 t in 2005. Non-metallic minerals used in the construction industry by far dominate
domestic extraction of minerals (e.g. 94% for the EU-15 in 2000). The extraction of industrial
minerals and metal ores varies greatly across countries, depending on the availability of
exploitable mineral deposits. Only a few large countries like Russia or Australia mine a broad
spectrum of ores and industrial minerals, most countries only mine a few of the listed
materials.
DE of minerals includes a number of raw materials which differ significantly in terms of their
chemical, technical, economic and environmental properties:
Economic value: The economic value of minerals ranges from very low (less than 10€/t, e.g.
sand and gravel) to very high (e.g., precious metal ores and diamonds); the vast majority of
extracted minerals comprises of bulk raw materials with low value (< 100€/t, e.g., sand,
mixed gravel, crushed stone).
Socio-economic use: Minerals provide raw materials for constructing buildings and
infrastructures, materials that enter a wide range of industrial processes and final products
(e.g., inorganic chemicals, ceramics, salt for food), and metal ores for also a wide range of
uses (e.g. constructions, vehicles, machinery, electrical appliances).
Environment: The extraction of mineral materials can be associated with a number of
environmental pressures depending on the kind of mineral and the location and type of
mining and quarrying activities (ecosystems destruction, sealing of land, toxic waste
emissions). A large fraction of these minerals is accumulated in societal stocks of buildings,
infrastructures and durable goods; at the end of their lifetime they turn into wastes and are
then a potential source for recycling and reuse of fractions of the disposed good. Any
recycling and reuse flows are considered to be a flow within the socio-economic system and
do not cross the system boundary between the societal system and nature.
Data sources
Statistical reporting of minerals extraction has a long tradition with regards to statistics of the
mining industries. On the national level, these commonly report with high reliability on
industrial minerals and metal ores, and should be taken as the primary data source.
However, mining statistics often do not include (total) numbers for bulk minerals like sand
and gravel or crushed stones. Additional information useful for getting comprehensive data
on domestic extraction of minerals may be provided by industrial associations (e.g. for the
gravel and sand industry or natural stones industry). These may provide figures covering the
complete field of activities involved in minerals extraction, for example also small scale
enterprises not considered by other statistics. In case statistics of industrial associations or
41
related data sources are used, it should be ensured that these report continuously on the
same items. In some cases, however, data for minerals for construction will have to be
estimated (see below).
Apart from national mining statistics, useful data for metallic and industrial minerals may also
be obtained from international mining statistics which are mainly:
European Mineral Statistics, a product of the World Mineral Statistics, published
annually by the British Geological Survey (BGS)
http://www.bgs.ac.uk/mineralsuk/statistics/wms.cfc?method=searchWMS
Minerals Yearbook (Volume III: Area Reports: International), by the U.S. Geological
Survey (USGS) http://minerals.usgs.gov/minerals/pubs/country/index.html#pubs
United Nations Industrial Commodity Production Statistics
http://unstats.un.org/unsd/industry/ics_intro.asp
Eurostat statistics on the production of manufactured goods (PRODCOM)
http://epp.eurostat.ec.europa.eu/portal/page/portal/prodcom/data/database
The statistics compiled by the BGS represent, so far as this is possible, the official data for
the countries concerned. BGS reports production as well as imports and exports of a wide
range of mineral commodities (including fossil energy carriers). In the case of metals,
production data of different steps in metal processing can be selected (mine production,
smelter, refining – only mine production is considered an extraction from the natural system,
see below), each expressed in terms of metal content. Data are reported for all countries in
the world and can be downloaded for free for the years 1980 onwards. The years prior to
1980 are available in pdf files. BGS archives even provide data (in pdf form) from the 1910s
onwards.
The USGS provides comparable data on the country level along with detailed information on
the mineral industry within the studied country, in particular about the structure of the mineral
industry in terms of commodity, major operating companies and major equity owners,
location of main facilities, and annual capacity. This often provides important detailed
information, especially for the metal contents and coupled mining of ores. Time coverage of
the data accessible via the internet is usually from 1990 to 2006, but only for most recent
years (from 2000 on) in a format that directly allows for data processing (earlier publications
are available in PDF format only). USGS archives even contain data tables (pdf) that go back
to the 1930s.
For longer time series, the United Nations Industrial Commodity Production Statistics
provide a valuable source of information (from 1950 onward). The UN, however, publishes
42
updates roughly one or two years later than the USGS or BGS. For overlapping long time
periods up to the most recent year, compatibility between the different databases has to be
ensured by analysing and eventually adjusting the different datasets.
Eurostat provides the statistics on the production of manufactured goods (PRODCOM).
It covers data for the 27 European Union member states and a number of additional
countries according to the European PRODCOM system, which is largely identical with the
CPA classification system. Production data are available for more than 1000 products in
physical and monetary units. However, the completeness of the data varies considerably
across countries and years.
Conventions
Terminology and classification: Mining statistics do not use the same terminology or
classification internationally. UN statistics use the ISIC Rev.2-based commodity codes,
Eurostat uses PRODCOM and CPA codes respectively, and the BGS and USGS do not refer
to standard statistical codes at all. Therefore some caution is required when working with
more than one data base to avoid either incomprehensive or double accounting. The
terminology and classification of mineral items and aggregates used in this guide by and
large follow the terminology used in the CPA.
System boundaries: Minerals mining involves the mobilisation of huge amounts of
materials. For the compilation of comparable data sets and indicators it is instrumental that
the same system boundary is applied. Table 9 gives an overview of the terminology used in
MFA with regard to the different flows involved in the extraction of metals.
Table 9: Different system boundaries in metal mining
Description of the material Common terminology MFA terminology
Materials removed to get access
to metal reserve
overburden, interburden unused extraction
the metal containing material run of mine, gross ore, crude ore used extraction
the pure metal net ore or metal content metal component of used
extraction, not specifically reported
in the MFA in the indicators, but
reported in the MFA tables as metal
content
Accounting for domestic used extraction of minerals always refers to the run-of-mine
production. Run-of-mine production means that the total amount of extracted crude mineral
43
that is submitted to the first processing step is accounted for. Material extracted but not used
as an input for subsequent processing is termed unused domestic extraction and is not
accounted for. Unused extraction may, for example, include overburden removed and
deposited or interburden removed and filled. Databases on mineral production often also
include production from further metal processing such as production of smelters or refineries.
In MFA only the extraction from the natural system, i.e. mine production in gross ore, is
considered as domestic extraction.
Please note! Table A.2 of the MFA tables requests that the amount of extracted metals is
reported in gross ore (i.e. run-of-mine). Additionally metal content should be reported in the
corresponding memorandum items. Although EW-MFA accounts for gross ore, both values
are important for crosschecking and for further analysis of the MFA data. But only the run-of-
mine value is used to calculate Domestic Extraction and aggregated indicators!
MFA convention requires the inclusion of metals as run-of-mine production”. Mining
statistics may report the run-of-mine production, the mass of a concentrate, or the metal
content of the gross ore. In the latter two cases, the run-of-mine production has to be derived
by calculating the mass of gross ore based on the concentrate or metal content by using ore
grades. A proposal for the respective accounting procedure is explained below. The run-of-
mine concept concerns metals in particular, but principally holds true for all minerals. For
minerals other than metallic ores, it may generally be assumed that the difference between
run-of-mine production and reported production is not relevant.
The ore grade specifies the metal content of a specific gross ore. This information is
required to estimate the mass of gross ore from metal content. Ore grades are variable
across ores, mines, and time; an overview of ore grades of different metals (metal content in
% of gross ore) in European countries is provided in Table 11. For calculation purposes, ore
grades in decimal form should be used (% divided by 100). Please note! Statistical sources
sometimes report the mass of metal concentrate rather than metal content. Concentrates
have a higher metal content than gross ores, but the metal content can vary considerably
depending on the nature and composition of the concentrates; typical ore grades of
concentrates are provided in the sections dealing with the specific metals.
Coupled production: Coupled production refers to ores that contain more than one metal of
economic value. For example, lead is often associated with zinc, or tin is often associated
with copper in the same deposit. While it is comparatively straight forward to collect data for
the mine production of specific metals, coupled production hampers the unambiguous
classification of gross ores according to MFA categories. The identification and adequate
treatment of coupled production is aggravated by the circumstance that the composition of
specific ores may differ between deposits within one national economy. For example, at site
44
A, an ore containing copper, lead, and zinc may be mined, while at site B, lead and zinc are
mined together with gold. In most cases it will not be possible or too time-consuming to
quantify the portion of each metal mined in a given form of coupled production. Therefore, in
the compilation of material flow accounts, it is advisable to determine which form of mining is
dominant for each metal, i.e. that type of ore from which the major part of the metal in
question is mined. In case this type of information is not available from the national statistical
unit responsible for mining, it can be obtained from the USGS country reports. Holding the
dominant form of mining true for all mining of a particular metal is, of course, a simplification,
but usually unavoidable due to data constraints.
Estimations: Metals are mostly reported in metal content and have to be converted to gross
ores by using ore grades as already mentioned above. Additionally, coupled production has
to be considered and the gross ore has to be allocated according to a standardized
procedure. Bulk minerals for construction are often under-represented in statistics. In these
cases it is necessary to estimate the actual amounts of material that has been extracted.
This refers mainly to sand and gravel, limestone, and clays for construction. Respective
estimation procedures are described in detail in the section concerned with the specific
material group.
Moisture content: Minerals have specific moisture content that is usually not subject to high
variability. Therefore data for the extraction of minerals are simply taken as they are
reported.
Data compilation A.2 metal ores
Run-of-mine estimation under consideration of coupled production
Run-of-mine or gross ore can be calculated on the basis of data on metal extraction (in
tonnes) and the country specific average ore grade. If coupled production for a specific metal
can be excluded (that is, only a single metal is extracted from the given ore), equation (12)
holds true:
(12)
grade ore
[t] content metal
[t] ore gross =
If more than one metal is extracted from the same gross ore, care must be taken to ensure
that the same run-of-mine is not accounted for more than once. In the case that coupled
production has been identified for two or more metals, the following calculation procedure
can be applied.
45
Step 1:
Calculation of the total gross ore: The amount of gross ore required to provide the
reported amounts of metals is calculated according to equation (13):
(13) gm
tot
[t] = m
tot
[t] / og
tot
[%]
gmtot = mass of total gross ore which contains metals m1 to mn
mtot = sum of metals m1 to mn contained in the gross ore
The sum of all metal content m1 to mn (in tonnes) extracted in coupled production
corresponds to the total amount of metal contained in the gross ore in question. The
data can be obtained from mining statistics or specific allocation studies.
ogtot = sum of ore grades (og1 to ogn)
The sum of all ore grades (in %) og1 to ogn contained within the same ore
corresponds to the total ore grade ogtot. The respective ore grades can be obtained
from statistics or literature.
Step 2:
Allocation of gross ore to metals from coupled production: The total amount of gross
ore must be attributed to the metals mined in coupled production. This can be done in an
aliquot way, based on the fraction of the total ore grade which the respective metal
represents. For example, for metal m1, the attributable fraction of total gross ore (gm1) should
be calculated using equation (14):
(14) gm
1
[%] = og
1
/ (og
1
+ og
2
+ … + og
n
) [%]
Because gm1 is the fraction of the total gross ore attributable to the extraction of metal m1,
the amount of gross ore associated with the extraction of this metal can be obtained by
multiplying gm1 with the total gross ore (equation (15)):
(15) gm
1
[t] = gm
tot
[t] * gm
1
[%]
In the MFA tables, the values for metal content and gross ore (both in tonnes) are reported
separately (see section conventions).
The following example illustrates the calculation procedure. Table 10 represents the metal
output of a hypothetical economy. Since the data is provided in terms of metal content, it is
necessary to calculate the associated gross ore.
46
Table 10: Coupled production, Metal output of hypothetical economy
Metal Mine Output, Metal
Content [t] Ore Grade Coupled Production
with:
Copper 10 000 0.01 Tin
Iron 300 000 0.5 no coupled production
Lead 30 000 0.08 Zinc
Zinc 150 000 0.05 Lead
Tin
500
0.0002
Copper
In the example given in Table 10 iron is the only metal which is not mined in coupled
production (single metal ore). Copper occurs together in one deposit with tin, and lead occurs
together with zinc, so that the procedure for coupled production calculation must be followed.
a) Calculation of iron gross ore
t 000 600
0.5
t 000 300
[t] ore gross iron ==
b) Calculation of Coupled Production Ores
t 412 029 1
0.0002
0.01
t 500t 000 10
[t] ore gross tin and copper
+
+
=
Of this result, 98% (=0.01/(0.01+0.0002)) are allocated to copper and the remaining 2% are
allocated to tin.
t 615 384 1
0.05
0.08
t 000 150t 000 30
[t] ore grosszinc and lead
+
+
=
Of this result, 62% (=0.08/(0.08+0.05)) are allocated to lead and 38% are allocated to zinc.
Following these steps, the following gross ore results are obtained:
Metal
Mine Output, Gross
Ore [t]
Copper 1 009 227
Iron 600 000
Lead 852 071
Zinc 532 544
Tin
20 185
Table 11 provides country-specific ore grades and occurrences of coupled production in
Europe. Coupled production is listed for the dominant ore which accounts for the majority of
extraction of a specific metal in a country. This information is based on data from
international statistical sources. More precise information both on ore grades and coupled
production may be available from national statistical sources and should be given preference
over the data provided here.
47
Table 11: A selection of country-specific ore grades and occurrences of coupled
production according to international statistical sources for European countries
Metal Ore Grade [%] Coupled Production
Austria W – Tungsten 0.27 to 0.31
Fe – Iron 32 with Mn (total gross ore
reported under iron ore)
Mn – Manganese 0.8 with Fe (total gross ore
reported under iron ore)
Bulgaria Cu – Copper 0.45 with Au, Ag
Ag – Silver 0.001 with Au, Cu
Au – Gold 0.0004 with Ag, Cu
Pb – Lead 7 with Zn
Zn – Zinc 7 with Pb
Fe – Iron 27 to 33 mining ceased in 2005
Mn – Manganese 27 to 30 no coupled production
Czech
Republic
U – Uranium 0.48 to 0.52 no coupled production
Fe – Iron 30 mining ceased in 2002
Spain Ag – Silver 0.01169 with Au, Cu, Ge, Pb, Zn
Au – Gold 0.000576 with Ag, Cu, Ge, Pb, Zn
Cu – Copper 1.58 with Ag, Au, Ge, Pb, Zn
Ge – Germanium 0.005 with Ag, Au, Cu, Pb, Zn
Hg – Mercury 0.4 no coupled production
Pb – Lead 1.48 with Ag, Au, Cu, Ge, Zn
Sn – Tin 0.016 no coupled production
Sr – Strontium 43.88 no coupled production
Zn – Zinc 5.71 with Ag, Au, Cu, Ge, Pb
Finland Cr – Chromium 35 to 36 (Cr
2
O
3
) no coupled production
Cu – Copper 1.17 with Zn and with Ni
Au – Gold 0.00007 no coupled production
Ni – Nickel 0.22 with Cu
Zn – Zinc 0.49 with Cu
France Al – Aluminium reprocessed, gross weight
Au – Gold mine closed
Ag – Silver (probably with gold)
U – Uranium mine closed
Germany Fe – Iron 11 to 14 no coupled production
48
Metal Ore Grade [%] Coupled Production
Greece Ni – Nickel 0.8 with Fe
with Fe, Mn
Zn – Zinc 9.0 with Pb, Au, Ag
Pb – Lead 8 to 10 with Zn, Au, Ag
Au – Gold 0.00036 with Pb, Zn, Ag
Ag – Silver 0.02 with Pb, Zn, Au (also with
barite and bentonite)
Al – Aluminum 53 (alumina) no coupled production
Mn – Manganese 15 to 19 with Fe, Ni
Hungary Mn – Manganese 26 to 27 no coupled production
Ireland Pb – Lead 8 to 15 with Zn, Ag
Zn – Zinc 13.6 with Pb, Ag
Ag – Silver 0.5 with Pb, Zn
Italy Au – Gold 0.00025 no coupled production
Mn – Manganese 35.0 no coupled production
Norway Co – Cobalt 1.38 no coupled production
Fe – Iron 32.6 no coupled production
Ti - Titanium 18.0 no coupled production
Ni – Nickel 0.5 no coupled production
Poland Pb – Lead 1.7 with Cu (33%) & Zn
Cu – Copper 1.8 to 1.9 with Pb, Ag, Au
Zn – Zinc 4.2 with Pb
Au – Gold 0.0001 by-product of copper
Ag – Silver with Cu (mainly), with Pb, Zn
(less)
Cd – Cadmium by-product of lead/zinc
Portugal Cu – Copper 6 with Sn, Zn
Sn – Tin with Cu, Zn
Zn – Zinc 8 with Sn, Cu
W – Tungsten 0.25 (WO
3
) no coupled production
U – Uranium no coupled production
49
Metal Ore Grade [%] Coupled Production
Romania Cu – Copper 0.6 to 1 with Pb, Zn (partly)
Pb – Lead 0.4 to 1 with Zn, Cu (partly)
Zn – Zinc 0.6 to 1.2 with Pb, Cu (partly)
Au – Gold associated with Pb, Zn
Ag – Silver associated with Pb, Zn
Antimony associated with Pb, Zn
Bismuth associated with Pb, Zn
Cadmium associated with Pb, Zn
Mn – Manganese 16 to 25 no coupled production
Slovakia Au – Gold 0.00014 --
Cu – Copper 1 no coupled production
Fe – Iron 26.68 no coupled production
Sweden Cu – Copper 25 to 28
(concentrate)
--
with Au
with Au, Pb, Zn
with Pb, Zn
Pb – Lead 5 with Zn
with Cu,Zn
with Cu, Au, Zn
with Cu, Au
Zn – Zinc 8 with Pb
with Pb, Cu
with Pb, Au, Cu
Au – Gold --
with Cu
with Cu, Pb, Zn
Ag – Silver probably with Au
United
Kingdom
Pb – Lead 27 (concentrate) --
Source: according to USGS Minerals Yearbook, Volume III, Area reports: International.
A.2.1 Iron ores
The two main iron ores are hematite and limonite. Sweden is the only significant producer of
iron ore within the EU and the only net exporter of ore. Iron ores are chiefly used to produce
steel in integrated steel plants; cast iron is a minor part of production. Data for the extraction
of iron ores are provided in good quality by national and international statistical sources and
generally refer to gross ore production which commonly contains around 25% to 35% Fe.
Iron ore concentrate contains around 64% Fe by weight.
50
A.2.2 Non-ferrous metal ores
A.2.2.1 Copper ores
There are several copper ores, but they all fall into two main categories: oxide ores and
sulphide ores. Azurite, malachite, and chrysocolla are a few examples of oxide ores.
Chalcocite, bornite, idaite, covellite, and chalcopyrite are all examples of sulphide ores.
Currently, the most common source of copper ore is the mineral chalcopyrite, which
accounts for about 50% of global copper production. Copper is used in the electrical,
electronics, transportation, and construction industries. Within the EU, Poland has the largest
mine production of copper, other relevant producers are Sweden, Portugal, and Finland.
Copper ores mine production is usually reported in metal content. Typical copper content in
gross ores is around 1%. Copper concentrates commonly contain between 20 and 40%
copper by weight.
A.2.2.2 Nickel ores
Two important nickel ores are the iron-nickel sulphides, pentlandite and pyrrhotite; the ore
garnierite is also commercially important. The most important use of nickel is in steel alloys, it
is further used in plating, both metals and plastics, and combined with copper in cupro-nickel
alloys.
Within the EU, the only significant mine producer of nickel ores is Greece, smaller production
is reported for Finland. Nickel ores mine production is usually reported in metal content.
Typical metal content in gross ores is around 0.5%. Nickel concentrates typically contain
10% to 15% Ni by weight.
A.2.2.3 Lead ores
The most common lead ore is galena, a sulphide. The other minerals of commercial
importance are cerussite, a carbonate and anglesite, a sulphate. Lead also occurs in various
uranium and thorium minerals, arising directly from radioactive decay. Commercial lead ores
may contain as little as 3% lead, but a lead content of about 10% is most common. The ores
are concentrated to 40% by weight or greater lead content before smelting. Lead is mainly
used in lead-acid batteries, but also widely in architecture, plumbing, solder, radiation
shielding, and insecticides. Within the EU, significant mine producers of lead ores are
Ireland, Poland, and Sweden.
A.2.2.4 Zinc ores
Chief sources of zinc are zinc blende, a sulphide ore (called also sphalerite or “Black Jack”),
zincite, an oxide, calamine, a silicate, and smithsonite, the zinc carbonate. Zinc ores are
51
widely and abundantly distributed throughout the world. Chief use of zinc is for steel coating
(galvanising), but it is also used as zinc die-casting, and alloyed with copper to make brass
which is widely used in the electrical, engineering, and construction industries. Within the EU,
significant mine producers of zinc ores are Ireland, Poland, and Sweden. Zinc ores mine
production is usually reported in metal content. Metal contents in gross ores may be around
13% as in Ireland, but also significantly lower. Zinc concentrates typically contain around
55% Zn by weight.
A.2.2.5 Tin ores
The most important tin-bearing mineral is cassiterite. No high-grade deposits of this mineral
are known. The bulk of the world's tin ore is obtained from low-grade alluvial deposits. The
chief use of tin is to coat metals that are more susceptible to corrosion, especially steel. It is
also widely used as an alloying agent (e.g. with lead to make pewter) and its use in solders is
rapidly growing as it replaces lead. Tin chemicals are used as fungicides and other biocides.
Within the EU, the only mine producer of tin ores is Portugal, where tin is produced in minor
amounts along with copper from the same mine and therefore treated as a by-product. Tin
concentrate from cassiterite typically contains 70-77% tin by weight.
A.2.2.6 Gold, silver, platinum and other precious metal ores
Gold: Native, or metallic, gold and various telluride minerals are the only forms of gold found
on land. Native gold may occur in veins among rocks and ores of other metals, especially
quartz or pyrite, or it may be scattered in sands and gravel (alluvial gold). Gold is highly
valued as an investment commodity, in jewellery and in specialised electronic appliances.
Gold mining in the EU represented a very low share of less than 1% of the world output in
2003. Sweden was the largest producer with about 6000 kg gold content followed closely by
Spain. In Europe, gold mining is chiefly a by-product of base metal mining, for which the
accounting procedure for coupled production is applied. In some cases, gold is however from
sole gold mines like in Finland, Italy and Slovakia and has to be accounted as gross ore.
Silver: The principal silver ores are argentite, cerargyrite or horn silver, and several minerals
in which silver sulphide is combined with sulphides of other metals. About three-fourths of the
silver produced is a by-product of the extraction of other metals, copper and lead in
particular. This also applies to silver mining in Europe. Silver is widely used in electronics
although the most important uses are in photography (silver nitrate) and making mirrors.
Significant mine producers of silver within the EU are Poland, and, to a much lesser extent,
Sweden. In Sweden, silver stems from a lead-zinc mine. Poland ranks among the major
52
world producers of silver and accounted for about 6% of world mine production in 2004.
Silver mine production in the EU amounts to less than 2000 tonnes per year.
Platinum: There is no primary mine production in the EU. South Africa is the largest producer
of platinum in the world. Platinum, often accompanied by small amounts of other platinum
family metals, occurs in alluvial placer deposits in the Witwatersrand of South Africa,
Colombia, Ontario, the Ural Mountains, and in western USA. Platinum is produced
commercially as a by-product of nickel ore processing in the Sudbury deposit. The huge
quantities of nickel ore processed makes up for the fact that platinum is present as only 0.5
ppm in the ore.
Other precious metal ores: These include the (other) Platinum Group Metals (PGM),
palladium, rhodium, ruthenium, osmium and iridium. There is likewise no mine production in
the EU.
Of the PGM family, platinum and palladium are the most commercially significant, having
important applications as catalysts and in electronics and jewelry and as investment
commodities.
A.2.2.7 Bauxite and other aluminium ores
The only important mineral source of aluminium is bauxite, which contains 40-60%
aluminium oxide (Ayres et al. 2006). The chief uses of aluminium are in packaging,
transportation, and construction. Greece is the most significant producer of bauxite within the
EU followed by Hungary and France. However, on a global scale EU mine production is of
minor importance. Data for the extraction of bauxite are provided in good quality by national
and international statistical sources and generally refer to gross ore production.
A.2.2.8 Uranium and thorium ores
Minerals that contain uranium or thorium as an essential component of their chemical
composition are called radioactive minerals. Examples are uraninite or thorite. Uranium is
chiefly used as the fuel source for nuclear power stations and in weapons. Within the EU, a
small amount of uranium is mined in the Czech Republic where the only mine has an output
of around 500 tonnes metal content per year. Aside from this, there may be (unrecorded)
production from decommissioning operations in France, Germany, and Spain. Typical metal
content in gross ores is around 0.17%. Yellowcake concentrate is produced in all countries
where uranium is mined and contains about 80% uranium oxide.
53
A.2.2.9 Other metal ores
Other non-ferrous metal ores may include (according to the BGS commodity list for
European mineral statistics): antimony, arsenic, bismuth, cadmium, chromium, cobalt,
lithium, magnesium, manganese, mercury, molybdenum, rare earths (yttrium and scandium),
selenium, strontium, tantalum (and niobium), titanium (ilmenite), tungsten, vanadium,
zirconium. Some important metals in group A.2.2.9. are briefly described below.
Arsenic: is produced in minor quantities in Belgium, France, and Germany (altogether about
2000 tonnes). Arsenic is found native as the mineral scherbenkobalt, but generally occurs
among surface rocks combined with sulphur or metals. Its principal uses are as compounds
in wood preservatives and pesticides, and in semi-conductors as gallium arsenide.
Chromium: Finland is the only EU country with significant mine production of chromite, the
only ore mineral of chromium. It is an essential component of stainless steel and other alloy
steels. It is also used in superalloys and metal plating, as pigments and in refractories.
Lithium: is, in the EU, only mined in Portugal as Lepidolite mineral. Lithium may profitably be
extracted from ores containing as little as 1% lithium (measured as lithium oxide). Some
commercially important minerals are lepidolite, petalite, spodumene, and amblygonite.
Lithium is also produced from brines such as those in Searles Lake, Calif., and in the Great
Salt Lake, Utah. Its uses are as fluxes in the ceramics and glass industries, in lubricants, as
alloying agent in primary aluminium, and in rechargeable batteries.
Magnesium: is a light metal commonly mined as magnesite in some EU countries. Although
magnesium is found in over 60 minerals, only dolomite, magnesite, brucite, carnallite, talc,
and olivine are of commercial importance. It is most commonly used in refractory bricks in
furnaces, but also in fertilisers.
Manganese: is sometimes reported together with iron ores as iron-maganese ores.
Manganese occurs principally as pyrolusite and to a lesser extent as rhodochrosite. Its
principal use is in the steel industry as desulphuriser and as an alloy, further as an aluminium
alloy, in dry-cell batteries, and in the chemical industry.
Mercury: is mined in minor amounts of around 770 tonnes in the EU (Spain and Finland). It is
mainly used in electrical switches and other control apparatus, and in dental amalgam, but
also in chlor-alkali plants and in batteries where the use is being phased out.
Strontium: Within the EU, only Spain has significant mine production of strontium minerals.
Its dominant use is in the faceplate glass of cathode ray tubes where it blocks X-ray
emissions. Other uses are in pigments, pyrotechnics, and fluorescent tubes.
54
Tungsten: mine production occurs in Austria and in Portugal at around 2000 tonnes metal
annually. Metal contents may range from 0.25 to 2.5 % tungsten oxide; for Austria values of
1.8% have been reported. Its largest use is in cemented carbides in cutting tools, but also as
an alloying agent with steel for tools and in superalloys. Its most familiar use is in light bulb
filaments.
Data compilation A.3 non-metallic minerals
A.3.1.Ornamental or building stone
This category comprises almost any competent rock type that may be used in the form of
shaped and/or sized blocks for either structural or decorative purposes. It includes marble
and other calcareous ornamental or building stone (e.g. travertine, ecaussine, and
alabaster), and granite, sandstone, and other ornamental or building stone (e.g. porphyry,
basalt), as well as roofing stone.
Data are often given in cubic meters (m
3
) and have to be converted to tonnes (see table 12
for conversion factors).
Table 12: Specific densities of ornamental and building stone
kg per cubic meter
Marble, solid 2563
Granite, solid 2691
Sandstone, solid 2323
Porphyry, solid 2547
Basalt, solid 3011
Stone (default value if no other
specifications are available)
2500
Source: SIMETRIC
A.3.2 Limestone, gypsum, chalk and dolomite
Limestone: In Europe, limestone is mostly used for cement production, followed by its use as
crushed rock aggregate. Limestone requires special attention in the account for non-metallic
minerals. Statistics often underreport amounts of limestone extracted for construction
purposes, in particular for cement production. This position, however, commonly represents
55
a large mass flow accounting for a considerable share of DE of non-metallic minerals. To
check and eventually correct for missing limestone extraction for cement production, the
following estimation can be applied:
Estimate of limestone extraction based on (finished) cement production: The German
Federal Institute for Geosciences and Natural Resources (BGR) explicitly reports limestone
used for the production of Portland cement. Using corresponding production figures for
cement from the BGR, a ratio of 1.19 tonnes of limestone for the production of 1 tonne of
cement can be identified. The extraction of limestone can be calculated based on data for
cement production in tonnes and the ratio of limestone to cement (equation (16)):
(16) Limestone for cement production [t] = cement production [t] * 1.19
Data for cement production are reported for example in USGS statistics. A comprehensive
source of global cement data is the European Cement Association (CEMBUREAU) which
publishes yearly updates of global cement production, imports, exports and apparent
consumption for individual countries. The World Statistical Review of 1998 (CEMBUREAU
1998) includes data for the period 1910-1995; later editions of this annual publication provide
data in 10year intervals and yearly updates. For EU countries also production statistics can
be used and should include PRODCOM-2007 items 26511210 (White Portland cement);
26511230 (Grey Portland cement including blended cement); 26511250 (Alumina cement)
and 26511290 (Other hydraulic cements).
It is recommended to compare the estimated figure for limestone extraction for cement with
the figure for limestone reported in statistics. The higher number should be selected as data
for the domestic extraction of limestone (with a tolerance of about 10% in favour of using the
original statistics figure). If limestone for other use than for cement is clearly indicated in
statistics, this figure has to be added to the estimate for limestone for cement.
For minerals of category A.3.2. data are often reported in cubic meters (m
3
) and have to be
converted to tonnes (see table 13 for conversion factors).
Table 13: Specific densities of limestone and gypsum
kg per cubic meter
Gypsum, crushed 1602
Limestone, broken 1554
Limestone (default value if no
other specifications are available)
1500
Source: SIMETRIC
56
Chalk is a soft, white, porous form of limestone composed of the mineral calcite. It is also a
sedimentary rock. Uses are widespread and comprise blackboard chalk, to mark boundaries,
in sports, applied to the hands or to instruments to prevent slippage, and as tailor's chalk.
Dolomite is the name of both a carbonate rock and a mineral consisting of calcium
magnesium carbonate found in crystals. Dolomite rock (also dolostone) is composed
predominantly of the mineral dolomite. Limestone which is partially replaced by dolomite is
referred to as dolomitic limestone. Limestone and dolomite are commonly used as crushed-
rock aggregate, for cement production, and for other industrial and agricultural uses.
Limestone and dolomite are often combined in statistical reporting. They are, however,
differentiated in statistics by CPA codes at the 5 digits level.
Please note! In case data for limestone are derived from an estimate described under
A.3.2., it should be figured out if this estimate includes use of dolomite (for cement
production). Data reported for dolomite under A.3.2 then eventually have to be corrected for
double counts. It is recommended to consult a national expert for clarification of this issue.
For minerals of category A.3.2 data are often reported in cubic meters (m
3
) and have to be
converted to tonnes (see table 14 for conversion factors).
Table 14: Specific densities of chalk and dolomite
kg per cubic meter
Chalk, lumpy 1442
Dolomite, lumpy 1522
Chalk and dolomite (default value
if no other specifications are
available)
1500
Source: SIMETRIC
A.3.3 Slate
Slate is a fine-grained, homogeneous, metamorphic rock derived from an original shale-type
sedimentary rock composed of clay or volcanic ash through low grade regional
metamorphism. Slate can be made into roofing slates, also called roofing shingles. Fine slate
can also be used as a whetstone to hone knives. Because of its thermal stability and
chemical inertness, slate has been used for laboratory bench tops and for billiard table tops.
Slate tiles are often used for interior and exterior flooring or wall cladding. Slate for
construction purposes may be included in statistics as building or dimension stone (A.3.1)
57
and should, if possible included there. Depending on the predominant characteristics of slate,
conversions from m
3
to tonnes may be performed as shown in table 15.
Table 15: Specific densities of slate
kg per cubic meter
Slate, solid 2691
Slate, broken 1290-1450
Slate, pulverized 1362
Slate (default value if no other
specifications are available)
1400
Source: SIMETRIC
A.3.4 Gravel and sand
There are two major groups of gravel and sand (sometimes also subsumed under the notion
natural aggregates) which are distinguished by their principal uses:
Industrial sand and gravel: Industrial sands and gravels show specific material properties that
are required for use in iron production and manufacturing including fire resistant industrial
use, in glass and ceramics production, in chemical production, for use as filters, and for other
specific uses. Statistical sources (e.g. the USGS) often report the amount of sand and gravel
in industrial production processes explicitly.
Sand and gravel for construction: Sand and gravel for construction is used in structural
engineering (e.g. buildings) and civil engineering (e.g. roads). Use of sand and gravel in
structural engineering is mainly for the production of concrete. In civil engineering gravel is
mainly used for different kinds of layers in road construction, as filling materials, in concrete
elements and for asphalt production.
Note: Sand and gravel can contain considerable amounts of moisture (15-25%). In material
flow accounts, sand and gravel is accounted for in dry weight. If necessary, an appropriate
correction should be applied.
Statistics for sand and gravel may not report the total amount extracted for both industrial
and construction use adequately. Often, only special sand and gravel for industrial use is
included (see above). Statistics also may report numbers for sand and gravel for construction
but not report total numbers due to e.g., limitations in the census. To find out if sand and
gravel is not adequately reported or underestimated in statistical sources, the following
checks can be performed:
58
The amount of sand and gravel per capita of the population in the respective year can be
taken as an indicator. As a rule of thumb, if this amount is significantly below 1 ton per capita,
it can be assumed that sand and gravel for construction purposes is not adequately reported
and has to be estimated. Additionally stakeholders and experts concerned with this economic
activity should be consulted to clarify the significance of the reported numbers. If no
adequate statistical data are available, the total amount of sand and gravel extracted for
construction can be estimated.
Estimation of sand and gravel for construction:
The following simple procedure to estimate the amount of sand and gravel used in
construction takes into account the two most important uses of sand and gravel. It combines
an estimate of sand and gravel required for the production of concrete (step 1) with an
estimate of sand and gravel used in asphalt production (step 2). In step 3 the total amount of
sand and gravel is calculated as the sum of the results obtained from step 1 and step 2. It is
important to note that this is a conservative estimate which does not consider sand and
gravel used as fillings and base material. In industrial countries, this approach typically
underestimates the overall extraction of sand, gravel and crushed stone for construction by
20-40%.
Step 1: Estimation of sand and gravel required for the production of concrete: Concrete is a
mixture of 6% air, 11% Portland cement, 41% gravel or crushed stone (coarse aggregate),
26% sand, and 16% water (PCA 2007). Thus, sand and gravel make up about 67% of the
produced concrete. Based on these relations two ways for calculating sand and gravel
required for concrete production are possible:
Method 1a) Estimation of sand and gravel based on the consumption of cement: The
required input of sand and gravel to produce one ton of concrete is 6.09 times the input of
cement (PCA 2007). Accordingly, sand and gravel input into concrete production can be
calculated following equation (17):
(17) Sand and gravel input [t] = cement consumption [t] x 6.09
Cement consumption can be derived from data on production of and trade with cement using
equation (18):
(18) Apparent cement consumption = cement production + cement imports – cement exports
Data on cement flows can be obtained from statistical sources, e.g. the world statistical
review of the European Cement Association (CEMBUREAU 1998, 2013). If industrial
production and trade statistics are used, production includes PRODCOM-2007-items
26511210 (White Portland cement); 26511230 (Grey Portland cement including blended
cement); 26511250 (Alumina cement) and 26511290 (Other hydraulic cements); Trade flows
59
include HS-CN-items 252321 (White Portland cement); 252329 (Portland cement excl.
white); 252330 (Aluminous Cement); 252390 (Cement weather or not coloured excl.
Aluminous and Portland cement).
Method 1b) Alternatively, sand and gravel can be estimated on the basis of concrete
production data using equation (19):
(19) Sand and gravel input [t] = concrete production [t] x 0.67
Data on concrete production can be obtained from production statistics (PRODCOM-2007-
item 26631000 Ready-mixed concrete); in general, method 1a tends to underestimate the
amount of sand gravel, because concrete reported in statistics commonly refers to transport
concrete and does not include concrete produced directly at the construction site. If method 1
is used, clarification of the quality of concrete production data is required.
Step 2: Estimation of sand and gravel for asphalt production: Asphalt or asphalt concrete is a
composite material commonly used in construction projects, above all for road surfaces.
Asphalt consists of bitumen, a product of the petrochemical industry, which is mixed with
mineral aggregate (gravel, crushed stone, etc.). To encompass at least some of the sand
and gravel used in road construction and maintenance sand and gravel demand for asphalt
production can be estimates by combining data on bitumen consumption and the ratio of
bitumen to sand and gravel in asphalt, which is typically around 1:20. Data on bitumen
production are reported for example in IEA’s international energy statistics database or the
United Nations energy statistics database (UNSD 2008). Sand and gravel input is calculated
using equation (20):
(20) Sand and gravel input [t] = bitumen consumption [t] x 20
Additional information: Estimation of sand and gravel for road layers (freezing protection and
carrying layers):
Also information on the length of newly built roads (by type of road and year) can be used to
estimate the amount of sand and gravel used in the construction of roads. Data on the length
and enlargement of the road network are commonly provided by national transport or road
statistics. Data for the EU Member States and other countries are e.g. available from the
publication “EU energy and transport in figures” (DG TREN 2008). The International Road
Federation publishes the world road statistics, which could also be used as a data source;
information on road length is also available from the World Development Indicators database
(The World Bank Group 2014). Quality of road length data and comparability across
60
countries is, however, quite poor and this method should only be applied when expert
knowledge is available.
In addition to information on the length of the road network, data on the amount of sand and
gravel required to build one kilometre of a certain road type have to be acquired. The
following table 16 provides examples for Germany but sand and gravel requirements for the
construction and maintenance can vary significantly across regions and countries:
Table 16: Requirements of sand and gravel per km of road construction in Germany
Sources: Ulbricht 2006; Steger et al. 2009.
Step 3 Finalization and cross check: Estimated figures for sand and gravel for concrete
production (step 1) and sand and gravel for asphalt production (step 2) are finally added and
compared with the figure for sand and gravel reported in statistics. The higher number should
be selected as data for the domestic extraction of sand and gravel for construction (with an
eventual tolerance of about 10% in favour of using the original statistics figure). In case sand
and gravel for industrial uses is given as a specific position in statistics, this figure has to be
added to the estimated figure.
In this category of minerals, data may be given in cubic meters (m
3
) and have to be
converted to tonnes. Reference values are given in table 17.
Table 17: Specific densities of sand and gravel
kg per cubic meter
Gravel, loose, dry 1522
Gravel, with sand, natural 1922
Gravel, dry 1,3 to 5,1 cm 1682
Gravel, wet 1,3 to 5,1 cm 2002
Sand, wet 1922
Sand, wet, packed 2082
61
kg per cubic meter
Sand, dry 1602
Sand, loose 1442
Sand, rammed 1682
Sand, water filled 1922
Sand with Gravel, dry 1650
Sand with Gravel, wet 2020
Sand and gravel (default value if no
other specifications are available)
1900
Source: SIMETRIC
A.3.5 Clays and kaolin
Kaolinite is a clay mineral, rocks that are rich in kaolinite are known as china clay or kaolin.
Other kaolinic clays are kaolin minerals such as kaolinite, dickite and nacrite, anauxite, and
halloysite-endellite.
The largest use is in the production of paper, as it is a key ingredient in creating “glossy”
paper (but calcium carbonate, an alternative material, is competing in this function). Other
uses are in ceramics, medicine, bricks, as a food additive, in toothpaste, in other cosmetics,
and since recently also as a specially formulated spray applied to fruits, vegetables, and
other vegetation to repel or deter insect damage.
In statistics, kaolin may be grouped together with other clays under the heading “industrial or
special clays”. Other industrial or special clays can be: ball clay, bentonite, sepiolite and
attapulgite, ceramic clay, fire clay, flint clay, fuller’s earth, hectorite, illite clay, palygorskite,
pottery clay, refractory clay, saponite, sepiolite, shale, special clay, slate clay.
Kaolin and other special clays are commonly well documented in statistics. Data may be
given in cubic meters (m
3
) and have to be converted to tonnes (see table 18).
Table 18: Specific densities of clay
kg per cubic
meter
Clay, dry excavated 1089
Clay, wet excavated 1826
Clay, dry lump 1073
Clay, fire 1362
62
kg per cubic
meter
Clay, wet lump 1602
Clay, compacted 1746
Clay (default value if no other
specifications are available)
1500
Source: SIMETRIC
Distinct from special or industrial clays are common clays and loams for construction
purposes, in particular for bricks and tiles. These are often not or under-represented in
statistics. To check for this, the following estimation procedure developed by the Federal
Statistical Office Germany may be applied (Klinnert 1993).
(a) For the production of full and lug bricks 2.2 tonnes crude clay are required to produce 1
m
3
of bricks. Full and lug bricks include PRODCOM-2007-items 26401110 (non-refractory
clay building bricks); 26401113 (ceramic bricks and blocks for common masonry: formed
units, with or without perforation, for walls with rendering or cladding); 26401115 (ceramic
facing bricks: formed units, with or without performation, for use without rendering);
26401117 (ceramic paving bricks: formed units for floor and road surfacing).
(b) For the production of roof bricks 1.05 tonnes crude clay are required to produce 1 t of
bricks, and 2.73 kg crude clay are required to produce one single roof brick respectively.
Roof bricks include PRODCOM-2007-items 26401130 (non-refractory clay flooring blocks);
26401250 (non-refractory clay roofing tiles); 26401270 (non-refractory clay constructional
products (including chimneypots, cowls, chimney liners and flue-blocks, architectural
ornaments, ventilator grills, clay-lath; excluding pipes, guttering and the like).
(c) For the production of ceiling bricks (in case reported this way): 0.22 tonnes crude clay are
required to produce 1 m
2
of bricks, and 2.2 t crude clay are required to produce 1 m
3
of bricks
respectively.
The overall estimation result is compared with the figure for common clays and loams
extraction reported in statistics (excluding industrial or special clays). The higher number
should be selected as data for the domestic extraction used of common clay and loam (with
an eventual tolerance of about 10% for using the original statistics figure).
63
A.3.6 Chemical and fertiliser minerals
This group of minerals mainly comprises:
Natural calcium or aluminium calcium phosphates, often combined under the heading
“phosphate rock”. Most of it (over 90%) is used to produce fertiliser; the remainder is used in
the production of detergents, animal feedstock, and many other minor applications.
Note: Under phosphate mineral statistics may report gross ore of phosphate production,
phosphate rock or produced phosphate. In MFA accounts the mined gross ore should be
reported which typically contains about 15-30% phosphate rock, which contains about 30%
phosphate (P2O5).
Carnallite, sylvite, and other crude natural potassium salts are often combined under the
heading “potash”. Potassium is essential in fertilisers and is widely used in the chemicals
industry and in explosives. Data for potash are often reported in K
2
O contents. In this case,
as for metals, the run-of-mine production has to be calculated to obtain the used domestic
extraction. Germany is by far the biggest producer of potash in the EU and the third biggest
in the world. The K
2
O content in run of mine production of potash in Germany is about 55%.
Unroasted iron pyrite which is an iron disulfide. Pyrite is used for the production of sulphur
dioxide, e.g. for the paper industry, and in the production of sulphuric acid, though such
applications are declining in importance.
Crude or unrefined sulphur is a fundamental feedstock to the chemical industry. Please
note! Not all domestic sulphur production is accounted for in category A.3.6. For the purpose
of MFA three principle types of sulphur can be distinguished: (1) Sulphur from mining: This
sulphur should be accounted for in category A.3.6. (2) Sulphur produced in the refinery
through desulphurisation of petroleum resources. This sulphur is included in the amounts of
extracted petroleum resources and should not be reported under A.3.6. (3) In some cases
sulphur can occur as an unused by-product of the extraction of petroleum resources. This
sulphur is considered unused extraction and is not accounted for in the MFA tables.
Other chemical minerals are mainly: Baryte, used in a variety of industries for its properties of
high specific gravity, witherite, a barium carbonate mineral which is the chief source of
barium salts and is mined in considerable amounts in Northumberland. It is used for the
preparation of rat