2012 using mfa for sd
TRANSCRIPT
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http://localhost/var/www/apps/conversion/tmp/scratch_7/dx.doi.org/10.1016/j.resconrec.2012.08.012mailto:[email protected]:[email protected]://www.elsevier.com/locate/resconrechttp://www.sciencedirect.com/science/journal/09213449http://localhost/var/www/apps/conversion/tmp/scratch_7/dx.doi.org/10.1016/j.resconrec.2012.08.012 -
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Table 1
Classification methods for M/SFA.
Classification based on Categories Explanation
Material typea Subs tance flow analys is (S FA) Monitor ing flows o f individuals ubst ances t hat r aise part icular concern s as r egar ds th e
environmental and health risks associated with their production and consumption.
Materialsystem analysis(MSA) Monitoringflows ofselected raw materials orsemi-finished productsthat raise particular
concerns as to the sustainability of their use, thesecurity of their supply to major economic
activity sectors, and/or the environmental consequences of their production and consumption.
Life cycle asses sm en ts ( LCA) Monitor ing flows o f m at er ials conn ected to t he pro duct ion and use of s pecifi cproducts , and
analyzing the material requirements and potential environmental pressures along the full lifecycle of theproducts.
Analytical scopea Business level material flow
analysis (B-MFA)
Monitoring material flows at various levels of detail for a company, a firm ora plant.
In putoutput analy sis ( IOA) Monitor ing m at er ialflows t o, f rom and t hr ough t he e con om y bro ken down by e co no mic
activity and final demand category or consumption function.
Economy-wide material flow
analysis (EW-MFA)
Monitoring flows of all materials entering or leaving theboundary of thenational economy.
EW-MFA serves as a basis forderiving aggregated material flow and resource productivity
indicators.
Chemical ingredientb Single s ubstance a nalysis Monitoring flows o f i ndividual e lement, m olecule o r c ompound.
Com po und mater ialanaly sis Monitor ing flows o f m at erials o r pro ducts m ade upo f s everalkinds o f e lem en ts o r com pounds.
Research purposeb Environmental problem analysis Monitoring flows of substancescausing environmental problem,i.e.ecological poisoning,
eutrophication, greenhouse effect, degradation of environmental systems, etc.
Environmental pressure analysis Monitoring flows of compoundmaterials, including energy carriers, timber, minerals, etc.
Susta inability analysis Monitoring flows of materials whose quantity and quality or fl ow characteristics can affect
regional sustainable development.
a Modified from OECD (2008).b Modified from Bringezu et al. (1997).
software development (Cencic, 2006; Liu et al., 2009). These the-
oretical studies provide a sound basis for applying M/SFA to SD
assessment.
2.2. Applied studies
M/SFA application studies also provide a foundation for enlarg-
ingtherole of M/SFA in SDassessment (Table2). Firstly, the number
of materials and substances subjected to flow analysis is continu-
ally expanding as studies are carried out in many countries around
the world. Secondly, M/SFA applications continue to grow, and areincreasingly combined with other research methods to analyze the
increasingly complex material/substance flows which result from
socioeconomic development. Thirdly, many indicators have been
derived from M/SFA applications, and most of them can be used
to support SD assessment (see Appendix A). However, outstanding
issues include: (1) how to derive SD indicators from M/SFA which
fully reflect the existence of a triple bottom line (Lee et al., 2012);
(2) how to derive comprehensive indicators from M/SFA results
which capture the whole spectrum of SD assessment; (3) how to
organize these indicators in a systematic way in order to conduct
SD assessment; and (4) how to apply these indicators in the SD
assessment process.
3. Functions ofM/SFA in SD assessment
3.1. HowM/SFA facilitates SD
Both the health and safety of the anthroposphere and the envi-
ronmental carrying capacity must be considered in SD studies,
regardless of whether the focus is on sustainable environmental
planning, resources management, or socioeconomic development.
This means that the impacts of resource extraction in theupstream
material or substance flow, and the environmental pollution and
ecological damage due to waste emission across all material or
substance flow processes, must be analyzed. As a result, there is a
close relationship between material/substance flows and SD. Based
on material flow charts or accounts (see Fig. A.1 or Table B.1), the
connections between M/SFA and SD include:
(1) Buildinga systematicdatabaseor informationpoolto help formu-
late measures to improve the efficiency of waste recycling and
reduce resources extraction and wastes emission (Table B.1).
(2) Determiningcritical linksor pathwayswhere lossesor inefficient
use of resources occur, which are often ignored by traditional
economic monitoring systems (European Communities, 2001;
see Table B.1), and identifying key materials or products in
the anthroposphere for environmental policies formulation
and sustainable environmental planning and management. For
example, the key materials and products of the Irish concrete
industry have been identified by MFA (see Table 3).
(3) Deriving meaningful and simple indicators from material flow
analysis (Sendra et al., 2007), and establishing an indicators
bank. These indicators shouldnot only be focused on increasing
recycling levels and minimizing the final volume of disposed
wastes (Appendix A), but also on promoting wiser use of
resources (Yabar et al., 2012), thereby improving the sustaina-
bility of resource extraction and energy use (Recalde et al.,
2008).
(4) Optimizing material use and processingby modeling responses
of the socioeconomic system to different models of material or
substance flows. This may take the form of a dynamic material
flow analysis model (Mller, 2006) or a closed cycle industrial
model (Mnsson, 2009).
As a result, M/SFA has the potential to become one of the
most important tools in SD assessment. Achievements in mate-
rial flow accounting to date are already challenging traditional
economic data for national policymaking in the context of SD
(Fischer-Kowalski et al., 2011), and M/SFA also facilitates the for-
mulation of sound SD policies, including policies for economic,
trade and technology development, natural resource management,
and environmental protection (OECD, 2008).
3.2. Main functions of M/SFA in SD assessment
3.2.1. Using M/SFA to derive SD assessment indicators
TheChairmansconclusionat the OECD special session on Mate-
rials Flow Accounting (Paris, October 2000) underlined that one of
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Table 2
Summary of M/SFA application studies.
Items Subclass M/SFA study areas
Matter analyzed by
M/SFAaSubstances Biogenic or metallic elements (N, P, Al, C r, Fe, C o, C u, Zn, etc.) and their compounds, toxic a nd
harmful substances including persistent organic pollutants (POPs), macromolecule synthetic
polymers, emerging contaminants, etc.
Materials Biogenic o r metallic m ixtures, w ater, f ood, f uels, p aper, p lastic, c hemical p roducts, i ndustrial
products, agricultural materials, building materials (cement, etc.), discarded electronic motor
products,total material flow through transportsystems or economic or environmental systems of
city, region or nation, etc.
Types of M/SFA
applicationbIndependent application Analysis of pollutants source and fate based on material flow chart or accounting.b1
Status quoevaluation and trend forecast of material useand their pollutantemissions based on
relationship analysis between production and consumption, imports and exports, and loss status
analysis by indicators.b2
Discovering vulnerable spots of material flows in developing low carbon or recycling economy
using MFA indicators system.b3
Increasing resources or energy efficiency (copper, steel, nuclear fuel, etc.).b4
Assessment of prefecture progress toward a circular society.b5
Development phase assessment of society and economy, optimization of sustainable industrial
processes, recycling scenarios optimization of industrial waste by MFA.b6
Coupling application with other
methods
MFA coupled to: canonical correlation analysis to assess the effect of land use change on material
metabolism structureb7 ; ARDL to analyze therelationship between resources useand economic
increaseb8; social sciences modeling approaches and Structural Agent Analysis to understand the
impacts of economic policies and social structure on material flow and achieve sustainable
material flow management,b9 an environmentally extended inputoutput model based on
economic inputoutput tables to analyze the relationship between material flows, environmental
impacts and theeconomy in Finland.b10
Indicators derived by
M/SFAcSocial indicators R esource consumption demand, w aste product per capita, material/resource u se per cap ita, in-use
stock of resource per capita, material flow intensity percapita, saving potential of materials,
recycling levels, thefinal disposal rate of wastes, etc.
Econom ic indicat ors Dire ct m at er ialinput, t ot al m at er ialinput, t ot al m at er ialr equir em en t, t otalm at er ialconsumption,
domestic material consumption, resource consumption, net additions to stock, domestic
extraction use, domestic processed output, total domestic output, direct material output, total
material output, circulationrate of materials, physical imports and exports, physical trade balance,
raw material equivalents, raw material extraction and consumption, product usage, amount of
waste, material/resources use intensity, intensity of resources input, material flow intensity per
economic yield, materials/resources efficiencies, energy or material use, economic efficiency,
transportand storage of materials, stock change, structure or scale of material flow,
self-sufficiencyrate of raw materials, thepercentage of material loss, service life of materials,
resource productivity, etc.
Environmental indicators Environmental efficiency,environmentalload,environmentalpressure,pollutantemissionratio,
recovery ratio of waste, disposal ratio of dangerous waste,annual scrap generation, pollutant
emission and waste generation, CO2emission, etc.
a Baccini and Brunner (1991), Chang et al. (2009), Chang (2010), Cheah et al. (2009), Chen et al. (2008, 2010), Daigo et al. (2009, 2010), Dong et al. (2010), Guine et al.
(1999), Guo and Song (2008), Guo et al. (2010), Hatayama et al. (2009), He (2008), Huang and Bi (2006), Huang et al. (2007), Hung (2007), Kapur et al. (2003), Kapur et al.
(2008), Kawamura et al. (2000), Kuczenski and Geyer (2010), Kwonpongsagoon et al. (2007), Lassen and Hansen (2000), Ma and Huang (2008), Ma et al. (2007), Mnsson
(2009), Mao et al. (2008), Matsuno et al. (2012), Mathieux and Brissaud (2010), Michael and Reston (1999), Michaelis and Jackson (2000), Miyatake et al. (2004), Mutha
et al. (2006), Park et al. (2011a,b), Qiao et al. (2011), Tachibana et al. (2008), Wei and Zhu (2009), Wen et al. (2009), Woodward and Duffy (2011), Xia (2005), Xiao (2003),
Yellishetty et al. (2010), Yue et al. (2010), and Zhong (2010).b1 Chang (2010), Chen (2004), He (2008), Hung (2007), and Lu etal. (2007).b2 Chenet al. (2010), Dong etal. (2010), and Guo and Song (2008).b3 Huang and Bi (2006) and Mao et al. (2008).b4 Bader et al. (2011) and Park et al. (2011a,b).b5 Tachibana et al. (2008).b6 Lang etal. (2006) and Rodrguez et al. (2011).b7 Ma and Huang (2008).b8 Wang et al. (2011).b9 Binder (2007a,b).
b10 Seppl et al. (2011).c Bader et al.(2011), Chen et al. (2010), European Communities (2001), Guoand Song (2008), Kovanda et al. (2009), Miyatake et al.(2004), Park et al. (2011a,b). Qiao etal.
(2011), Recalde et al. (2008), Rodrguez et al. (2011), Scasnyet al. (2003), Tachibana et al. (2008), Woodward and Duffy (2011), Yabar et al. (2012), and Yue et al. (2010).
Table 3
Production andusage of concrete in Ireland in 2007.
Materials Million metric tones Concrete products Million metric tones
Crushed stone 11.06 Construction Ready-mix 18.08
Gravel 7.49 Blocks/bricks 13.00
Sand 4.44 Precast/prefabricated 0.73
Water 5.25 Tiles and flagstones 0.63
Total 28.23 Pipes 0.28
Cement 4.57 Non-construction Statues, ornaments 0.09
Concrete 32.80 Total 32.80
Adapted from Woodward and Duffy (2011).
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Fig. 1. A simplified model of relationship between material or substance flows and SD assessment indicators. Note: Thisfigureis based on European Communities (2001),
Matthews et al. (2000), Bond et al. (2001), Huang et al. (2006), Brunner and Rechberger (2004), Wallis et al. (2011). Light dashed circle refers to internal material/substance
flows in a single system, and heavy dashedcirclerefers to material/substanceflows across two or three systems.
the main uses of M/SFA is the derivation of indicators, and that
the derivation of sustainability indicators is a promising applica-
tion of M/SFA (European Communities, 2001). By using an M/SFA
inputoutput balance table, the material or substanceflow through
the whole economic system can be understood. Based on this
understanding, more compact,detailed,and accurate indicators for
SD assessment can be obtained (Hinterberger et al., 1997; Schmidt-
Bleek, 1994; Tachibana et al., 2008). Main functions of indicators
derived by M/SFA in SD assessment include:
(1) Widening the scope of SD assessment. Material flow indicators
can help in monitoring the material basis and material produc-
tivity of national economies and industries, the implications
of trade and globalization for material flows, the management
of selected resources and materials, and the environmental
impacts of material resource use (OECD, 2008). Material flow
indicators can contribute to management of resource use and
output emission flows from economic, environmental, and
broader sustainability perspectives (Kovanda et al., 2012).(2) Making SD assessment results testable and verifiable. Because
material flowindicatorsare based on mass units,they avoidthe
accumulating error problem of attempting to compare mone-
tary units in different areas at different times. The indicators
therefore make it possible to found SD assessment on a natural
science basis (Xia, 2005).
(3) Making SD assessment results comparable (Appendix A). M/SFA
provides a similar analyzing framework and identical units
(Figs. A.1 and A.2), and indicators derived from M/SFA are so
capable of being quantified, disaggregated, and aggregated that
they can link overall environmental pressure from material or
substance flow to concrete environmental impacts (Kovanda
et al., 2009). This makes it possible to compare assessment
results of a specific material/substance in a specific social
and/or economic subsystem with the assessment results of
the same material/substance in an entire environmental sys-
tem in a specific area (Fig. 1). For example, the indicator of
material or substance recycling efficiency canbe derived from
the material or substance flow, which is composed of the
production, consumption, and recycling processes across the
social and economic subsystems. This indicator can also be
derived from any single material or substance flow cycle in
the environmental system. As a result, material or substance
recycling efficiency can be used as a comparable indicator
when drawing a sustainability comparison between different
materials or substances flows in the same system or between
a given material or substance flow in different subsystems
(Fig. 1).
3.2.2. Using M/SFA to improve reliability of SD assessment results
Using M/SFA-related software, such as EMIS (Page and
Wohlgemuth, 2010), increasingly complex social, economic,
resource or environmental information can be compiled intoa sim-pler uniformed form by M/SFA. As a result, M/SFA-related software
helps M/SFA provide more systematic information for SD assess-
ment, and improve the reliability of SD assessment results.
In addition, the method design of M/SFA can itself boost the
quality of information by providing more detailed, intact and accu-
rate data. For example, M/SFA allows hidden flows to be identified,
making the data series more intact and detailed. At present, dif-
ferent data sources have different statistical standards and rules
and/or different calculating methods, which can result in different
values for a same indicator. M/SFA mass balance allows the identi-
fication of a definite, consistent value for each indicator, that is, the
valuewhichcan meetthe massbalance results of differentflow pro-
cesses/links of bothupstream and downstream material/substance
flows.
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4. Outlooks
4.1. Strengthening simultaneous analysis of various features of
material/substance flows
To enhance the functions of M/SFA in SD assessment, attention
should be paid to the following study fields.
(1) Simultaneous analysis of material/substance input and output
flows.
The human population and its lifestyle is the driving force
of material cycles (Mller, 2006), which means that con-
sumption demand is the fundamental driver of environmental
exploitation, resource use, and waste generation. Simultaneous
assessment of the three SD intrinsic features requires analy-
sis of the consumption structure and consumption levels, and
M/SFA provides a means to perform this analysis at the indi-
vidual, community, city, and national levels by simultaneous
analysis of inputoutput flows. Based on inputoutput flows
accounting, M/SFA also makes it possible to assess the equity
and harmony of the consumption structure at different levels of
analysis in a givenstudy area, and to assess whether the supply
of consumable materials will be able to continuously meet the
demands of the socioeconomicsystem. However, little researchhas so far been conducted in this area.
(2) Simultaneous analysis of the socioeconomic benefit and envi-
ronmental impact of per unit material/substance flow (Van der
Voet et al., 2009).
The material needs of more than seven billion people
continue to drive loss and degradation of remaining natu-
ral habitats, and the challenge is to manage the trade-offs
between providing for immediate human needs and maintain-
ing the capacity of the biosphere to provide goods and services
in the long-term (Balmford et al., 2002; Foley et al., 2005;
United States Census Bureau, 2012). Part of the solution to
the sustainability challenge is dematerialising the economy,
namely, lowering the environmental burden while providing
consumers with the same level of performance, by reducingthe material/substance flows in the production-consumption
chain (Mont, 2002). A necessary component of SD assessment
is therefore to simultaneously analyze the economic, environ-
mental, and social consequences per unit material/substance
flow.
(3) Simultaneous analysis of the quantity and quality of materials
or substances flows.
It is generally accepted that reducing the amount of materi-
als consumed by the anthroposphere will lead to less human
disturbance of the environment, making development more
sustainable (Huang et al., 2007). However, in addition to the
impacts caused by gross flow volumes, the properties and
quality of the materialor substance flow alsohave environmen-
tal impacts. For example, although the volume of agriculturalwater use in a watershed may be much greater than the urban
water use, agricultural water use may have less impact on the
natural water system if farm wastewater or runoff contains
fewer pollutants than urban sewage. The SD of the integrated
socioeconomicenvironmental system is therefore affected by
the properties and quality of material and substance flows,
and this should be reflected in SD assessment. This can some-
times be achieved by coupling the application of M/SFA and
other SD assessment tools. For example, Van der Voet et al.
(2004) developed a method which combines aspects of mate-
rial flow accounting (MFA) and life-cycle assessment (LCA) and
attempted to add a set of environmental weights to the flows
of the materials. Then, impacts per kilogram of a number of
extracted materials were calculated, and the analysis indicated
that the impact per mass unit of bulk materials was generally
lower than that of materials which were only used in small
quantities. However, most of the published M/SFA literature
focuses on quantitative analysis rather than material or sub-
stance properties and quality.
(4) Simultaneous analysis of material/substance flow intensity and
environmental capacity.
Environmental sustainability is not only impacted by the
environmental disturbance caused by material/substance flow
intensity, but also depends on the environmental capac-
ity. Environmental capacity is impacted by biogeochemical
processes, self-organizing patterns within the ecosystem, envi-
ronmental resilience, and the intensity of the interaction
between the executor and receiver of environmental impacts.
To estimate the extent to which environmental sustainability
is impacted by a particular material or substance flow process,
it is necessary to consider both the magnitude and intensity of
the material flowand the environmental capacity to absorb the
stress. According to the intermediate disturbance hypothesis
(Barnes et al., 2006; Shea et al., 2004), moderate disturbance
from the economic system will not impede or harm environ-
mental sustainability as long as environmental capacity limits
and ecological thresholds are not exceeded. However, little
has been reported about M/SFA application in environmentalcapacity studies.
4.2. Improved integration ofM/SFA with other SD assessment
methods
Since all SD assessment methods have their merits and short-
comings, it is often necessary to employ several methods of SD
assessment at the same time, in order to meet the assessment
requirements of the multidimensional characteristics of SD objec-
tives and targets (Bond et al., 2001), and the requirements of a
comprehensive sustainability policy-making process (Yabar et al.,
2012). M/SFA is an attractive SD assessment method as it is based
on the mass measure, whichin classical physics is considered to be
immutable in time and space, can be measured using simple tech-nical means, and requires very little explanation to comprehend.
In addition, M/SFA indicators can show environmental pressures
in terms of both mass flows per unit of time and mass flow qual-
ity (Fischer-Kowalski et al., 2011), although much less research has
been carried on the latter. These features make it convenient to
integrate M/SFA with other methods in SD assessment, and several
such studies have already been carried out (see Table 2).
4.2.1. Integrated application ofM/SFA with LCA
LCA can be used to assess whether certain technical solutions
might lead to other environmental problems, and is comple-
mentary to using M/SFA models to identify problem-causing
mechanisms based on mass conservation (Bouman et al., 2000).
Although LCA fails to holistically recognize abiotic resource deple-tion as a potential problem of sustainability, by clearly addressing
a products life stages, it helps inform M/SFA process division
from raw material acquisition through manufacture, use, end-
of-life treatment, recycling, and final disposal; In addition, LCA
is conducted in accordance with agreed international standards
(Yellishetty et al., 2011). Thus, combining LCA withdynamic M/SFA
contributes to the better design of sustainable resource use path-
ways (Hatayama et al., 2010), the achievement of more precise
M/SFA results (such as anthropogenic stocks estimation based on
dynamicMFA;see Mller,2006), andthe derivationof environmen-
tal burden allocation indicators (Weinzettel and Kovanda, 2009).
Environmental burden allocation indicators reflect the uneven spa-
tial allocation of the environmental burdens associated with all
inputs and outputs processes at every stage of the life cycle of a
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product in those world regions from whichthe inputsare imported
(for resource depletion-related impact categories) and to which
the emissions are output (for emission-related impact categories)
(OECD,2008;Raugei and Ulgiati, 2009). As a result, LCA can expand
the role of M/SFA in SD assessment by providing a means to assess
environmental equity.
However, integrated application of M/SFA with LCA should
go beyond the scope of current studies. For example, the ENVI-
MAT model, which is based on an environmental life-cycle impact
assessment and monetary inputoutput tables associated with
material flows, can improve data on production and consump-
tion. That is, environmental impact information can be derived
by combining mass data from M/SFA (Table B.1) with greenhouse
gas emissions data from LCA (Table B.2), and then be used to
make environmental impact comparisons between different prod-
ucts or services, and assess environmental impact equity between
different industries or between imports and exports (Seppl
et al., 2011). However, integrated applications of M/SFA with
LCA still have limitations which require further study. For exam-
ple, Economic InputOutput analysis (EIO)LCA analysis considers
the inter-industry effects of product/process decisions based on
standard national sector-based data sources, but is hampered by
limited disaggregation of the economy, depends on cost infor-
mation, and omits environmental interventions associated withcapital goods. As a result, hybrid EIOLCA is used now, as it allows
for full interaction between a process-based LCA model and an
inputoutput model (Ferro and Nhambiu, 2009). However, an
additional limitation of EIOLCA is the temporal difference. Nei-
ther traditional LCAnor the staticLeontief IOmodel(whichis in fact
one type of M/SFA model) contains explicit temporal information
to describe how the production activity and its related impacts are
distributed over time. As a result, a Sequential InterindustryModel,
which describes how various direct and indirect inputs, outputs,
and associated impacts of such events are distributed in time, has
been proposed, and may provide a useful extension of the EIOLCA
methodology(Levineetal.,2009). Inorder to improve sustainability
comparisons between industries in different countries, it will be
necessary to gain a better understanding of the structural featuresof industry and their impacts in each country, by finding methods
to integrate M/SFALCA with other models.
4.2.2. Integrated application of M/SFA and risk estimation
Ness et al. (2007) developed a framework for sustainability
assessment tools, and indicated that while risk analysis is a
prospective sustainability assessment tool, regional M/SFA is a
retrospective tool. As a result, while risk analysis is capable of inte-
grating naturesociety systems into a single evaluation, M/SFA is
not. However, integrating M/SFA with risk estimation can facilitate
examination of the risks from all human activities in a systematic
way and provide a comprehensive understanding of risk genera-
tion and distribution corresponding to flows of substances in the
anthroposphere and the environment (Ma et al., 2007). The sys-
tematic risk examination of material/substanceflows controlled by
human activities makes SD assessment results more holistic and
objective. However, the study of this field is only just beginning.
4.3. Using M/SFA to improve SD assessment indicators
Indicators used in SD assessment should be reliable, clear, accu-
rate, measurable, effective, comparable, universal, variable, and
understandable (Hk et al., 2007; Huang and Deng, 2008; Parris
and Kates, 2003; Sendra et al., 2007; United Nation Division for
Sustainable Development, 2001; Xia, 2005). M/SFA allows environ-
mental, economic, and social indicators with these characteristics
to be derived (Fig. 1). However, improving the usefulness of M/SFA
indicators in SD assessment will require the following issues to be
addressed.
(1) Making SD assessment indicators more systematic.
The factors and data involved in SD assessment are becom-
ing more and more complex as the natural environment is
disturbed more widely and deeply by the ongoing processes
of globalization, industrialization, and urbanization. Indicator
systems have proved to be practical tools for simplifying com-
plex factors and data, and there is an extensive literature on
indicators research (Olsthon et al., 2001; Seager and Theis,
2004). However,the complexity of evaluationpurposes, incom-
plete data and method limitations in building an indicator
system mean that the derived indicators are not yet suffi-
cientlysystematic. M/SFAallowsSD assessmentindicatorsto be
systematically extracted from the material or substance flows
through the social, economic, and environmental systems (see
Fig. 1). The indicators can be derived not only from a single
material or substance flow through one of the three systems,
but also from the flows across two or three systems.
(2) Using M/SFA to improve the comprehensiveness of SD assess-
ment indicators.
Many indicators derived by M/SFA are not comprehensive
enough to assess SD. For example, the sustainability of aregion is largely determined by the condition of the environ-
ment (Wallis et al., 2011), but the indicators derived from
M/SFA (see Table 2) mainly reflect the sustainability of the
economic system, rather than the overall sustainability of the
socioeconomicenvironmental system. Thus, an importantgoal
for M/SFA is to extract or design comprehensive indicators
which can mirror the sustainability of both the socioeconomic
system and the environmental system, and some researchers
are currently active in this area. For example, Van der Voet
et al.(2009) have developed Environmental-weighed Materials
Consumption (EMC), an aggregated environmental impact indi-
cator based on MFA which is linked to environmental impacts.
EMC is the most comprehensive indicator currently available,
which in principle shows environmental impacts and side-effects, and is able to detect burden shifting abroad. However,
in its present shape it is insensitive to technological improve-
ments, sometimes in non-obvious ways, and the main obstacle
to using EMC is the incompleteness of available MFA data (Van
der Voet et al., 2009).
(3) Using M/SFA to achieve a universal framework for SD assess-
ment indicators.
A universal or general indicator would help to improve the
verifiability and reliability of SD assessment results. There has
been some discussion on why and how a universal indica-
tors system should be established in the SD assessment and
M/SFA literature. This includes, for example: a case study on
establishing an indicators system with a universal and opera-
ble framework for sustainabilityassessment of water resourcesused in agriculture (Huang and Deng, 2008); a general com-
prehensive resource use indicators framework which can be
applied consistently from the micro level of products andcom-
panies up to the macro level of countries and world regions
(Giljum et al., 2011); and a product generational demate-
rialization indicator, intended to improve on the available
sustainability indicators which could not be used as a univer-
sal approach to solve substitution problems (Ziolkowska and
Ziolkowski, 2011). However, all indicators have limitations, and
no indicator has yet been put forward that has been gener-
ally accepted.Environmentally extended inputoutputanalysis
may provide the best framework for a general M/SFA indicator,
butthese areless suitable formorespecificpolicy areas because
they presently include a very limited number of emissions,
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sometimes suffer from lack of detail in the sector classifica-
tion, and may make simplifying assumptions, for example that
foreign technology is identical to domestic technology (Vander
Voet et al., 2009).
Indicators easily lose universality (or generality) because
they may not be able to capture important burden shifting
processes. These include burden shifting to other parts of
the production-consumption chain (technical detail), bur-
den shifting across impact categories (displacement between
impacts), andburdenshiftingto other geographicalareas (geo-
graphical displacement) (Van der Voet et al., 2009). However,
M/SFA provides a framework to detect burden shifts to other
processes from both a chain and global perspective, by discov-
ering different impact types along material/substance flows,
and by quantifying shifts in environmental pressure from one
region to another.
4.4. Developing new M/SFA application paths
4.4.1. Methodological development of measuring indirect flows
and unused flows
Economy-wide material flow accounting methods are now
mature, meaning that material flow indicators can now com-
plement traditional economic and demographic information inproviding a basis for sustainable resource use policies (Fischer-
Kowalskietal.,2011). However,as faras thelevel of standardization
of measurement and estimation methods is concerned, only mea-
surements of direct material inputs are mature enough to justify
input flow data being used to deliver reasonably reliable results in
time series for all countries of the world (Fischer-Kowalski et al.,
2011). In other words, much less efforthas been invested in studies
of material outputs measurements thaninputs measurements, and
further research is needed to increase methodological harmoniza-
tion. In particular, a measurement method for indirect flows and
unused flows still needs to be improved in order to include indirect
material flows in M/SFA accounts (see Section 4.2.1).
4.4.2. Standardization issues ofM/SFA for joint SD assessmentThe core of SD thinking is to harmonize human-nature and
human-human relationships (Huang et al., 2005). The disturbance
caused by industrialization and urbanization has led to the read-
justment of the receiving natural systems (atmosphere, biosphere,
hydrosphere, pedosphere, etc.) toward a new equilibrium at the
planetary scale, which inevitably causes local imbalances, includ-
ing climate anomalies, ecosystem degradation, and shortage of
resources. Therefore, the objective should be to try to coordinate
humannature and humanhuman relationships so that humans
can successfully adapt when local imbalances occur. While social
scientists naturally emphasize harmonizing humanhuman rela-
tionships (Colantonio, 2011; Lufer, 2010), natural scientists focus
on howto adapt to local changesin thehumannature relationships
(Li and Dovers, 2011). Because SD assessment needs to considerboth humanhuman and humannature relationships, it is nec-
essary to formulate standardized M/SFA procedures, data format,
classification of various materials, and so on, to enable social and
natural scientists to jointly conduct SD assessment in different
countries.
For instance, consider the problem of how to establish
an industrial ecosystem which is similar to a natural ecosys-
tem (Frosch and Gallopoulos, 1989). If social and natural
scientists from different countries cooperated to establish stan-
dardized procedures to handle the different processes in the
productionconsumption chain, and standardized methods to
measure the different types of environmental impacts in differ-
ent regions at different times, the industrial ecosystem designed
by these standardized procedures and methods would be able to
deliver the harmonization of humannature and humanhuman
relationships.
While there is an extensive literature on both industrial and
natural ecosystems, little has been written on how M/SFA can
inform adaptation to local changes (i.e. improved understanding
of the humannature relationship). While M/SFA accounting and
indicators have already been standardized to some extent (see
e.g. European Communities, 2001), future standardization efforts
should address mass data acquisition and processing, classifica-
tion of various materials, and standardization of the measurement
of changes in the physical, chemical, and biological properties of
materials and substances during the course of their flow.
4.5. MakingM/SFA data more systematic
Assessment of environmental sustainability requires system-
atic and comprehensive data, which can be acquired by analysis
of material and matter flows in both the environmental and socio-
economic systems. This data can be compiled into a consistent
model of material flows, based on resources input indicators and
wastes output indicators. For example, economically extended
M/SFA includes economic information, and reduces the short-
comings of a technically oriented MFAby includinga description of
the inputs and outputs in money units, without changing the sys-tem structure. This enables e.g. a food production chain model to
be developed from data obtained from corporate information sys-
tems, market research institutes and national statistics, together
with assumptions basedon primary energy consumption, land use,
material costs, other costs, and turnover indicators (Kytzia et al.,
2004).
However, not only there is low data availability and rela-
tively high data uncertainty at present (Binder, 2007a), but most
countries also lack a national data-collection system for tracking
and monitoring material and substance flows, especially unused
flows (Kovanda et al., 2009). This may be due to the lack of a
general criterion or method for systematic mass data collection
by the relevant administrative department. The lack of system-
atic data, even in urban areas (Browne et al., 2011), is the biggestobstacle to using M/SFA to assess SD. Physical inputoutput tables
(PIOTs) of material flow record all physical flows associated with
the economic activities defined in the System of National Accounts
(Commission of the European Communities et al., 1993), including
flows of physical products, extraction of raw materials, the sup-
ply and use of wastes and residuals, waste emissions and stock
change (Hoekstra and van den Bergh, 2006). However, PIOTs have
only been compiled for a few European countries (Hinterberger
et al., 2003), including the Netherlands, Germany, Denmark, Italy
and Finland (Hoekstra and van den Bergh, 2006), and mass data
for these tables are not based on directly tracking and monitoring
material or substance mass flows, but rather on indirect conver-
sions from other data sources, including monetary inputoutput
tables. Nevertheless, M/SFA can be directly affiliated to existingeconomic accounting schemes by consistent and comprehensive
data organization (Weisz, 2000). Thus, in future attention should
be paid to further systematization and serialization of M/SFA data
obtained from existing economicaccounting schemes. Looking fur-
therahead, we anticipate the establishment of a monitoring system
to collect systematic andcomprehensive massdata for materialand
substance flows in other countries beyond the European Union.
To make M/SFA a more useful tool for SD assessment, and
to inform the optimization of patterns of production and con-
sumption, improved materials use efficiency, and the design of SD
scenarios(Bader et al.,2011; Bringezu andMoriguchi, 2002; Liu and
Chen, 2006; Matthewset al., 2000; Park BH et al., 2011; Park J et al.,
2011; Rodrguezet al.,2011; Tachibana et al.,2008), future research
should focus on: (1) quantification of environmental pressure
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112 C.-L. Huang et al. / Resources, Conservation andRecycling68 (2012) 104116
Zinc System Boundary: STAF world
Import/Export +57
Lithosphere -7800 +3,030Environment
Fabrication &
Manufacturing
48
Concentrate 82
Refined Zinc
84
Finished Products
Semis
27
660Discards490 770
8501,210Old Scrap
360Landfilled
Waste,
Dissipated
1660
Waste
Management
120
Discards
2320
Use
4650
stock
Products
6970
Refined Zinc
7210
Zinc
Scrap 16
330 Slag
Tailings
1030
Ore
7800
ProductionMill,
Smelter, 150
Refinerystock
200
100 280 -794 2240 -6499
100 -279 795 -2239 6500
Scale, Gg Zn/y
Fig.A.1. Thecontemporaryglobal levelzinc cycle.Note: Thisfigureshows thecriticallinks ofzinc lossin theproductionconsumptionchain andthereforeprovidessystematic
information of both used flows and unusedflows forSD assessment.
Adapted from Graedel et al. (2005).
Fabrication &
Manufacturing940
Refined
ZincOre
1290
52 Slag
Tailings
170
3
Production
Mill,
Smelter, 4
Refinerystock
Import/Export +320
Lithosphere -1290 +340Environment
47
Concentrate 300
Refined Zinc
6
Finished Products
Zinc
Scrap 20
Discards
130
Products
840
220
120
340Old Scrap
230DiscardsLandfilled
Waste,
Dissipated
120
Use
710
stock
Waste
Management
84
Zinc System Boundary: China, 1994-98 average
Scale, Gg Zn/y
10 31 - 99 310 -999
10-30.9 100 - 309 1000
Fig.A.2. The contemporary country-level zinc cycle. Note: This figure shows that it hasa similar analyzing frameworkcomparing with Fig. A.1.
Adapted from Graedel et al. (2005).
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C.-L. Huang et al. / Resources, Conservation andRecycling68 (2012) 104116 113
Table B.1
M/SFA accounting table of theFinnish economy from domestic natural sources and aboard in 2002 and 2005. Unit: million tons.
2002 2005
DMI HF TMR DMI HF TMR
Domestic extraction
Cultivated plants 4.5 1.5 6.1 6.7 1.6 8.4
Fodder plants 10.4 1.8 12.2 10.4 1.8 12.2
Wild fishes and animals 0.2 0.0 0.2 0.2 0.0 0.2
Wood 51.8 22.3 74.1 51.4 21.6 73
Peat 9.2 0.5 9.6 9.0 0.5 9.5
Metal ores 3.2 5.6 8.8 3.3 1.2 4.5
Lime 3.7 1.8 5.5 3.8 5.5 9.3
Industry minerals 10.8 3.5 14.3 11.6 6.4 18.1
Construction stones 0.7 2.9 3.6 0.9 3.7 4.6
Gravel, sand 90.0 0.0 90.0 98.0 0.0 98.0
Other earth resources 7.8 25.8 33.6 12.0 24.4 36.4
Total domestic 192.3 65.8 258.1 207.4 66.7 274.1
Biotic 66.9 22.8 89.6 68.7 22.1 90.8
Abiotic 125.4 43 168.4 38.7 44.6 183.3
Imports
Agriculture products 2.3 14.8 17.1 2.7 18.0 20.7
Wood 12.0 7.7 19.7 13.4 8.6 22.0
Energy minerals and products 26.9 23.4 50.3 25.0 26.0 51.1
Coal 5.8 9.6 15.4 5.6 9.3 14.9
Crude oil 11.7 2.2 13.9 10.96 2.0 13.0
Natural gas 3.1 0.9 4.0 3.1 0.9 4.0Coke 0.5 4.2 4.7 0.9 7.5 8.4
Refined oil 5.7 3.5 9.3 4.5 2.8 7.4
Nuclear fuel 0.0001 2.1 2.1 0.0002 2.3 2.3
Electricity 0.0 1.0 1.0 0.0 1.2 1.2
Metal concentrates 5.2 51.8 57.0 5.7 42.9 48.6
Iron 3.8 6.4 10.2 4.2 4.7 8.9
Copper 0.5 34.1 34.6 0.5 26.9 27.4
Nickel 0.2 3.1 3.3 0.1 1.8 2.0
Zinc 0.4 5.0 5.4 0.5 5.8 6.3
Other metal 0.3 3.2 3.6 0.4 3.7 4.1
Other quarrying products 4.2 11.1 15.3 4.1 10.8 15.0
Products of forest industry 1.9 3.7 5.6 3.3 5.2 8.5
Products of chemical industry 5.4 24.2 29.6 5.6 25.5 31.2
Products of metal industry 3.5 42.5 46.1 4.0 44.4 48.4
Products of electric industry 0.3 48.3 48.6 0.3 47.6 47.9
Other manufactured products 1.3 7.2 8.5 1.7 8.9 10.6
Services 0.0 6.0 6.0 0.0 8.4 8.4
Total imports 63.0 240.8 303.7 65.8 246.5 312.3Biotic 16.2 14.8 31.1 22.3 17.6 39.8
Abiotic 46.8 225.9 272.7 43.5 228.9 272.5
Adapted from Sepplet al. (2011).
Abbreviations: DMI, direct material input; HF, hiddenflows; TMR, total material requirement.
shifting resulting from foreign trade; (2) bringing M/SFA indica-
tors closer to environmental impacts; (3) integrated studies on the
optimization of material or substanceflow pathways; and(4) anal-
ysis of the relationship between material/substance consumption
and SD,because consumptionis themain driving force of resources
depletion and waste discharge.
5. Summary
This paper has presented a review of the current state of M/SFA
research, and has discussed how to use M/SFA to underpin SD and
its assessment. The literature review has indicated that M/SFA can
play a very important role in sustainability assessment, and the
recent theoretical and application studies of M/SFA form a sound
basis for using M/SFA to support SD assessment. However, M/SFA
could play a greater role in the environmental and social aspects
of SD assessment than at present. The extension of M/SFA appli-
cations will facilitate the derivation of better SD indicators, and
improve the functions of M/SFA in SD assessment. We propose
that the scope and role of M/SFA should be enlarged by empha-sizing simultaneous analysis of features of material/substance
flows, integration of M/SFA with other SD assessment methods,
Table B.2
Finnish industry products and services with thegreatestGHG emission intensity in 2002 identified by LCA. Unit: kgCO2eq per D value of product.
Industry products Services
Product group kg CO2eq/D Service group kg CO2eq/D
Cement, lime and plaster 13 Air transport services 1.5
Products of animal farming 4 Freight transportation services by road 0.98
Fertilizers and nitrogen compound 3 Railway transportation services 0.7
Basic iron; and steel and ferro-alloys 3 Restaurant services 0.7
Basic chemicals 3 Business services 0.3
Adapted from Sepplet al. (2011).
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114 C.-L. Huang et al. / Resources, Conservation andRecycling68 (2012) 104116
improvingthe quality and function of indicators derived by M/SFA,
and developing newapplication paths of M/SFA.In addition,M/SFA
data collection and processing should be conducted in a more sys-
tematic way.
Acknowledgements
This research is supported by the CAS/SAFEAInternational Part-
nership Program for Creative Research Teams (KZCX2-YW-T08).Authors wouldlike to thankEricMasanet andthe threeanonymous
reviewers for their valuable suggestions and comments.
Appendix A. M/SFA results for SD assessment
Figs. A.1 and A.2 show the contemporary global and country-
level zinc cycles by SFA (Graedel et al., 2005). Discard flows in
the multilevel cycle of anthropogenic zinc can be understood by
M/SFA (Graedel et al., 2005), allowing sustainability indicators,
including accumulationratio, secondaryinput ratios, recycling per-
centage, utilization efficiency, prompt scrap ratio, and so on, to be
derived. Using these indicators, it is possible to assess the retriev-
ability of zinc that is discarded in various forms during the flowprocess of productionfabrication and manufacturing-use-waste,
and the extraction requirements for zinc. The potential economic
and social drivers for zinc flows can also be explored. Thus, the
sustainability of zinc use can be assessed by comparing these indi-
cators at different levels of the zinc cycle (such as at the global
level, as shown in Fig. A.1, and country level, as shown in Fig. A.2).
Because SD assessment follows the relativity principle (we can
never know whether the subject of the assessment is absolutely
sustainable, but we can definitely say that one subject is more
sustainable than another according to some designated terms in a
specific spacetime frame), the researcher can determine whether
zinc use in country A is more sustainable or efficient than in coun-
tryB (assumingthat other indicators do notshow other differences
between these two countries).
Appendix B. The integration of M/SFA with LCA for SD
assessment
Many indicators derived by M/SFA are not sufficient in them-
selves for SD assessment. For example, relationships between total
material requirement (TMR) and greenhouse gas emissions vary
so much between different products and services that TMR should
not be used to make environmental impact comparisons between
products and services. According to the European Commission
(2001) calculation rules for direct material consumption (DMC),
DMC includes the indirect material input of exports, and does not
measure the direct material use of the domestic final use of prod-
ucts. Thus, theresults of the DMCas a measure of domesticmaterialconsumption are too high, especially for the country with a strong
export industry using a significant amount of natural resources.
However, a correction can be applied to DMC using the ENVI-
MAT model. The ENVIMAT model is an environmentally extended
inputoutput (EEIO) model based on an environmental life-cycle
impact assessment and monetary inputoutput tables associated
with material flows. Thus, the model can be used to analyze the
relationship between material flows, environmental impacts, and
the economy. The corrected domestic direct material consumption
for Finland was 32 tons per capita instead of 44tons per capita in
2005. The correction improves the results of the DMC (an M/SFA
indicator) as a measure of domestic material consumption, making
the assessment results of environmental impacts resulting from
material flows more accurate. This provides one example of how
the integration of MFA with other SD assessment methods, in this
case LCA, can facilitate and improve assessment results.
Appendix C. Supplementary data
Supplementary data associated with this article can be
found, in the online version, at http://dx.doi.org/10.1016/
j.resconrec.2012.08.012.
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