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106 C.-L. Huang et al. / Resources, Conservation andRecycling68 (2012) 104116

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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C.-L. Huang et al. / Resources, Conservation andRecycling68 (2012) 104116 107

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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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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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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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.

References

Baccini P, Brunner P. Metabolism of the anthroposphere. Germany: Springer VerlagBerlin Heidelberg; 1991.

Bader HP, Scheidegger R, Wittmer D, Lichtensteiger T. Copper flows in buildings,infrastructureand mobiles:a dynamic modeland its applicationto Switzerland.Clean Technologies and Environmental Policy 2011(13):87101.

Balmford A, Bruner A, Cooper P, Costanza R, Farber S, Green RE, et al. Economicreasons for conserving wild nature. Science 2002;297(5583):9503.

Barnes B, Sidhu HS, Roxburgh SH. A model integrating patch dynamics, compet-ing species and the intermediate disturbance hypothesis. Ecological Modelling2006;194(4):41420.

Behrens A, Giljum S, Kovanda J, Niza S. The material basis of the global economy:worldwide patterns of natural resource extraction and their implications forsustainable resource use policies. Ecological Economics 2007;64(2):44453.

Binder CR. From material flow analysis to material flow management part I: socialsciences modeling approaches coupled to MFA. Journal of Cleaner Production

2007a(15):1596604.Binder CR. Frommaterialflow analysisto material flow management partII: theroleofstructural agent analysis. Journal of Cleaner Production 2007b(15):160517.

Bond R, Curran J, Kirkpatrick C, Lee N, Francis P. Integrated impact assessmentfor sustainable development: a case study approach. World Development2001;29(6):101124.

Bouman M, Heijungs R, van der Voet E, van den Bergh J CJM, Huppes G. Materialflows and economic models: an analytical comparison of SFA, LCA and partialequilibrium models. Ecological Economics 2000(32):195216.

B ringezu S , edit or . Neue Ans aet ze de r Umm elts tatistik. Ber lin, Ger many:Birkhaeuser Verlag;1995. pp. 179.

Regional and national material flow accounting: from paradigm to practice of sus-tainability.BringezuS, Fischer-KowalskiM, Kleijn R, PalmV, editors.Proceedingsofthe ConAccount Workshop; 1997.

Bringezu S. Ressourcennutzung in Wirtschaftsraeumen.Berlin, Germany: Springer-Verlag;2000. pp. 1329.

Bringezu S, MoriguchiY. Material flowanalysis. In:Robert UA, Leslie WA, editors. Ahandbookof industrialecology. Chelenham,UK/NorthamptonMA, USA:EdwardElgar;2002. pp. 7990.

Bringezu S. Industrial ecology and material flow analysis-basic concepts, policy rel-evance and some case studies. Germany: Greenleaf Publishing; 2003.

Browne D, ORegan B, Moles R. Material flow accounting in an Irish city-region19922002. Journal of Cleaner Production 2011;19(910):96776.

Brunner P, Ma HW. Substanceflow analysis an indispensabletool forgoal-orientedwaste management. Journal of Industrial Ecology 2008;13(1):114.

BrunnerP,RechbergerH.Practicalhandbookofmaterialflowanalysis.FL,USA:LewisPublishers; 2004.

Cencic DIO. STAN a tailored software for substance flow analysis. TU-Vienna,Austria: Institute for Water Quality, Resources and Waste Management;2006. pp. 112, http://www.mendeley.com/research/tailored-software-substance-flow-analysis

Chang CH. Material flow analysis and environmental impact assessment. Taiwan,China: Graduate Institute of Environmental Engineering of National TaiwanUniversity; 2010.

Chang TC, You SJ, Yu BS, Yao KF. A material flow of lithium batteries in Taiwan.Journal of Hazardous Materials 2009;91(163):05.

C hea h L, Heyw ood J, Kirchain R. Alu minum stock and flow s in U.S. passen-ger vehicles and implications for energy use. Journal of Industrial Ecology

2009;13(5):71834.Chen M, Chen J, SunF. Agricultural phosphorus flow andits environmental impacts

in China. Science of the Total Environment 2008;405(13):14052.ChenPC. Studyof MFAand RiskAssessmentfor Chromiumin Taiwan. Taiwan, China:

Graduate Institute of Environmental Engineering, National Taiwan University;2004.

Chen WQ, Shi L, Qian Y. Substanceflow analysis of aluminiumin mainland Chinafor2001, 2004 and 2007: exploring itsinitial sources, eventual sinks and thepath-ways linking them. Resources Conservation and Recycling 2010;54(9):55770.

Chen XQ, Zhao TT, Guo YQ, Song SY. Material input and output analysis of Chi-nese economy system. Acta Scientiarum Naturalium Universitatis Pekinedsis2003;39(4):53847.

Colantonio A. Social sustainability: exploring the linkages between research, pol-icy and practice. In: Jaeger CC, et al., editors. European research on sustainabledevelopment. European Union. Berlin, Heidelberg: Springer-Verlag; 2011. p.3557.

Commission of the European Communities, International Monetary Fund, OECD,United Nations and World Bank. System of National Accounts 1993. Manufac-

tured in United Statesof America, 1993.
http://dx.doi.org/10.1016/j.resconrec.2012.08.012http://dx.doi.org/10.1016/j.resconrec.2012.08.012http://www.mendeley.com/research/tailored-software-substance-flow-analysishttp://www.mendeley.com/research/tailored-software-substance-flow-analysishttp://www.mendeley.com/research/tailored-software-substance-flow-analysishttp://www.mendeley.com/research/tailored-software-substance-flow-analysishttp://dx.doi.org/10.1016/j.resconrec.2012.08.012http://dx.doi.org/10.1016/j.resconrec.2012.08.012


12/13
http://localhost/var/www/apps/conversion/tmp/scratch_7/dx.doi.org/10.1007/978-94-007-0567-8_21


13/13


Park BH, Gao FX, Kwon EH, Ko WI. Comparative study of different nuclearfuel cycle options: quantitative analysis on material flow. Energy Policy2011a;39(11):691624.

Park J, Hong S, KimI, LeeJY, HurT. Dynamic material flowanalysisof steel resourcesin Korea. Resources Conservation and Recycling 2011b;55(4):45662.

Parris TM, Kate s RW. Characterizing and measuring sustainable development.Annual Review of Environment and Resource 2003;28:55986.

Qiao M, Zheng YM, Yong-G uan Zh u. Mat erial flow analys is o f pho sphor usthrough food consumption in two megacities in northern China. Chemosphere2011;84(6):7738.

RaugeiM, Ulgiati S.A novel approachto theproblemof geographicallocationof envi-

ronmentalimpact in lifecycle assessment and material flow analysis.EcologicalIndicators 2009;9(6):125764.

Recalde K, Wang JL,GraedelTE. Aluminiumin-usestocks inthe stateof Connecticut.Resources Conservation and Recycling 2008;52(11):127182.

Rodrguez MTT, Andrade LC, Bugallo PMB, Long JJC. Combining LCT tools for theoptimization of anindustrialprocess:materialand energy flowanalysisand bestavailable techniques. Journal of Hazardous Materials 2011;192(3):170519.

Scasny M, Kovanda J, Hk T. Materi al flow accounts, b alances and derivedindicators for the Czech Republic during the 1990: results and recommen-dations for methodological improvements. Ecological Economics 2003;45(1):4157.

Schmidt -Blee k F . W ievie l Umwelt Br aucht der Mensch? MIPS das Mas s FuerOekologisches Wirtschaften. Berlin, Germany/Basel, Switzerland/Boston, USA:Birkhaeuser Verlag; 1994.

Seager T, Theis T. A taxonomy of metrics for testing industrial ecology hypothesesand application to design of freezer insulation. Journal of Cleaner Production2004;12(8):6575.

SendraC, GabarrellX, VicentT. Material flowanalysisadapted to an industrial area.Journal of Cleaner Production 2007(15):170615.

Seppl J, Menp I, Koskela S, Mattila T, Nissinen A, Katajajuuri JM, et al. Anassessment of greenhouse gas emissions and material flows caused by theFinnish economy using the ENVIMAT model. Journal of Cleaner Production2011;19(16):183341.

Shea K, Roxburgh SH, Rauschert ESJ. Moving from pattern to process: coexis-tence mechanisms under intermediate disturbance regimes. Ecology Letters2004;7(6):491508.

Sumaila U. Rashid taking the earths pulse: scientists unveil a new eco-nomic and environmental index. In: Presentation at the Annual Meetingof t he Ame rican Asso ciat ion fo r t he Advancemen t o f S cien ce (AAAS) ;2012., http://www.physorg.com/news/2012-02-earth-pulse-scientists-unveil-economic.html (20.02.12).

Tachibana J, Hirota K, Goto N, Fujie K. A method for regional-scale material flowand decoupling analysis: a demonstration case study of Aichi prefecture, Japan.Resources Conservation and Recycling 2008;52(12):138290.

Udo de Haes H, van der Voet E, Kleijn R. From quality to quantity: substance flowanalysis (SFA), an analytical toolfor integratedchain management. In: BringezuS, Fischer-Kowalski M, Kleijn R, Palm V, editors. Regional and national mate-

rial flow accounting: from paradigm to practice of sustainability. Leiden, theNetherlands: The ConAccount Workshop; 1997. p. 3242.UN. Reportof theworld summit on sustainable development.Johannesburg, South

Africa, 26 August4 September 2002. UnitedNations, New York, 2002.

United Nation Division for Sustainable Development. Environmental managementaccounting principle andprocedures.New York, USA: UnitedNations; 2001.

United States Census Bureau. U.S. & World Population Clocks; 2012,http://www.census.gov/main/www/popclock.html (18.05.12).

Van der Voet E, vanOersL, De Bruyn S, de Jong F, Tukker A. Environmental impactoftheuse of natural resources andproducts.Report commissionedby Eurostatto support the Data Centres on Products and Natural Resources, Luxembourg,Eurostat; 2009.

Vander Voet E, van Oers L, Nikolic I. Dematerialization:not just a matterof weight.Journal of Industrial Ecology 2004;8(4):12137.

Wallis AM, Graymore MLM, Richards AJ. Significance of environment in theassess-

ment of sustainable development: the case for south west Victoria. EcologicalEconomics 2011;70(4):595605.

Wang Y, Guo PK, Zhou J, Zhu XD, Lu GF. Relationship between resources use andeconomic growth in Fujian province: an ARDL approach. China EnvironmentalScience 2011;31(1):15662.

Wei T, Zhu XD. Material flow analysis of Xiamen citys eco-economic system. ActaEcologica Sinica 2009;29(7):380010.

Weinzettel J, Kovanda J. Assessing socioeconomic metabolism through hybrid lifecycle assessment: the case of the Czech Republic. Journal of Industrial Ecology2009;13(4):60721.

Weisz H. MFA und Umweltindikatoren. Verortung und Positionierung von Mate-rialflussanalysen (MFA) in der europischen Umweltindikatoren-Diskussion.Wien: Interdisziplinres Institut fr Forschung und Fortbildung; 2000.

Wen ZG,Li RJ,HuangLY, Xu HL.Materialmetabolismin theChinesehighwaytraffic.Journal of Tsinghua University(Science and Technology) 2009;49(9):847.

Woodward R, Duffy N. Cement and concrete flow analysis in a rapidly expand-ing economy: Ireland as a case study. Resources Conservation and Recycling2011;55(4):44855.

World Commission on Environmental Development. Our common future. London,

UK: Oxford University Press; 1987.XiaCY. Review onstudiesof economy-widematerialflow analysis.Journalof Natural

Resources 2005;20(3):41521.Xiao DY. A study on industrial ecology analyzing and modeling materials flows

for construction aggregates in Taiwan. Taiwan, China: Graduate Institute ofEnvironmental Engineering of National Taiwan University; 2003.

Yabar H, H ara K , Uwasu M. Comparative assessment of the co-evolution of envi-ronmental indicator systems in Japan and China. Resources Conservation andRecycling 2012;61(4):4351.

YellishettyM, Ranjith PG,TharumarajahA. Iron oreand steel production trendsandmaterial flows in the world: is this really sustainable? Resources Conservationand Recycling 2010;54(12):108494.

YellishettyM, Gavin Mudd M, Ranjith PG. The steel industry,abiotic resource deple-tion and life cycle assessment: a real or perceived issue? Journal of CleanerProduction 2011;19(1):7890.

YueQ,WangHM, LuZW. Aluminumflow analysisbased onaverageservicelifeof alu-minum products in China. Journal of Northeastern University (Natural Science)2010;31(9):13048.

Zhong RY. Resources productivity and sustainable development in the EU-15countries. European Study 2010(4):5670.ZiolkowskaJ, ZiolkowskiB. Product generational dematerialization indicator:a case

ofcrude oil in theglobaleconomy. Energy 2011;36(10):592534.

2012 using mfa for sd

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