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date: 20 October 2017

Material and Energy Flow Analysis

Summary and Keywords

The concept of metabolism takes root in biology and ecology as a systematic way to account for material flows in organisms and ecosystems. Early applications of the concept attempted to quantify the amount of water and food the human body processes to live and sustain itself. Similarly, ecologists have long studied the metabolism of critical substances and nutrients in ecological succession towards climax. With industrialization, the material and energy requirements of modern economic activities have grown exponentially, together with emissions to the air, water and soil. From an analogy with ecosystems, the concept of metabolism grew into an analytical methodology for economic systems.

Research in the field of material flow analysis has developed approaches to modeling economic systems by assessing the stocks and flows of substances and materials for systems defined in space and time. Material flow analysis encompasses different methods: industrial and urban metabolism, input–output analysis, economy-wide material flow accounting, socioeconomic metabolism, and more recently material flow cost accounting. Each method has specific scales, reference substances such as metals, and indicators such as concentration. A material flow analysis study usually consists of a total of four consecutive steps: (a) system definition, (b) data acquisition, (c) calculation, and (d) interpretation. The law of conservation of mass underlies every application, which implies that all material flows, as well as stocks, must be accounted for.

In the early 21st century, material depletion, accumulation, and recycling are well-established cases of material flow analysis. Diagnostics and forecasts, as well as historical or backcast analyses, are ideally performed in a material flow analysis, to identify shifts in material consumption for product life cycles or physical accounting and to evaluate the material and energy performance of specific systems.

In practice, material flow analysis supports policy and decision making in urban planning, energy planning, economic and environmental performance, development of industrial symbiosis and eco industrial parks, closing material loops and circular economy, pollution remediation/control and material and energy supply security. Although material flow analysis assesses the amount and fate of materials and energy rather than their environmental or human health impacts, a tacit assumption states that reduced material throughputs limit such impacts.

Keywords: material flow analysis, urban metabolism, socioeconomic metabolism, input–output analysis, industrial system

Introduction

The way natural resources are used and managed has economic, social, and environmental consequences on human health, resource availability, ecosystem quality, trade, and market prices or productivity. Achieving sustainable resource use and ensuring that the flows of materials are managed in an efficient way through the economic system is crucial, not only from an environmental perspective, but also from an economic and trade perspective (Organisation of Economic Co-operation and Development [OECD], 2008). As a response to those issues, a set of material flow analysis methodologies has been developed since the 1970s (Table 1). A common definition of material flow analysis (MFA) is the following:

Material Flow Analysis (MFA) is the study of physical flows of natural resources and materials into, through and out of a given system (usually the economy). It is based on methodically organized accounts in physical units, and uses the principle of mass balancing to analyze the relationships between material flows (including energy), human activities (including economic and trade developments) and environmental changes.

(OECD, 2008)

MFA is used as a general terminology encompassing several methodologies based on Lavoisier’s law of mass conservation and applicable at varying spatial and temporal scales. Variations in space and time led to different methods: industrial or urban metabolism, input–output analysis, economy-wide material flow accounting, socioeconomic metabolism, and material flow cost accounting. This overview of the current applications of MFA at different scales and organizational levels shows the breadth and depth of MFA.

The choice of a specific methodology depends on the problem to be solved, and both material and energy flows are generally considered (Bringezu & Moriguchi, 2002). The approaches differ according to (a) the scale of the system evaluated (e.g., whole economy, specific parts of the economy, regions, industrial plants, and private households), (b) the materials investigated (goods and/or substances), and (c) the data sources used (e.g., material flows derived from national or international econometric statistics, physical substance flows measured by specific sampling, and analysis campaigns; Allesch & Brunner, 2015).

As the name of several methods states, “metabolism” is another generic term widely used to characterize physical accounting methods. Transposed from the field of biology to describe human economic and organizational systems, “metabolism” refers to varying spatial scale, such as urban areas (urban metabolism); regions (regional metabolism); economic sectors (industrial metabolism); or more generally for any socioeconomic system (socioeconomic metabolism). In addition, most studies take a quasi-stationary approach, meaning that the network of processes is translated into a set of linear equations describing how the flows of energy and materials partition among them. The rate of accumulation is considered constant. When the temporal dimension is accounted for, the term “dynamic modeling” is used and the main variables become functions of time.

Table 1. Material-flow-based analysis and related issues of concern (Adapted from Bringezu & Schütz, 2010).

Issue of concern

Specific concerns related to environmental impacts, supply security, technological development

General environmental and economic concerns related to the throughput

Scale

within businesses, economic activities, countries, regions

of substances, materials, goods and services

associated with

at the level of

Main objective

Substances

Materials

Products, Goods and Services

Businesses

Economic activities

Countries, Regions

e.g., chemical elements or compounds (Cd, Cl, Pb, Zn, Hg, N, P, C, CO2, CFC)

e.g., raw materials and semi-finished goods, energy carriers, metals (ferrous and nonferrous), sand and gravel, timber, plastics

e.g., batteries, transportation, packaging

e.g., offices, plants, small and medium sized entreprises, multi-national entreprises

e.g., mining, construction, chemical industry, iron and steel industry

e.g., aggregated mass of materials and related mixed or selected materials

Type of analysis

Substance Flow Analysis

Material Flow Analysis

Life Cycle Assessment

Business level Material Flow Analysis

Input–Output Analysis

Economy-wide Material Flow Analysis

Type of analytical tools

Substance Flow Accounts

Material Flow Accounts, Industrial, Urban or Regional Metabolism

Life-Cycle Inventory, Impact Assessment (ISO 14040)

Lif-Cycle Costing

Material Flow Cost Accounting (ISO 14051)

Business Material Flow Accounting

Physical Input-Output Tables, NAMEA approaches

Economy-wide Material Flow Accounts

Source: (Adapted from Bringezu & Schütz, 2010).

MFA as Support for Decision-Making

The contribution of material flow analysis methodologies to decision-making and policy development is significant in both economic and environmental contexts.

As for economic, trade, and technology development policies, MFA allows the measurement of the physical performance of an economic system by analyzing its material requirements over time. Such analyses provide information on material availability, transformation, and use. MFA is also recognized as a valid approach for studying the effects of new technologies on material and energy consumption. In the context of environmental policies, MFA allows the mapping of stocks and flows and the identification of environmental pressures from emissions in the air, soil, or water. MFA improves the understanding of economic systems by pointing to source reduction and the substitution or recycling potential of substances, energy and materials. The results are used to improve a system’s performance, such as waste generation, as well as the entire value chain. In addition, the energy and material implications of government or industry environmental policy and regulatory instruments can be simulated with MFAs (OECD, 2008).

Many internationally known researchers in the field of MFA are members of the United Nations Environmental Programme (UNEP) International Resource Panel. They provide independent, coherent and authoritative scientific assessments of policy relevance on the sustainable use of natural resources and contribute to a better understanding of how to decouple economic growth from environmental degradation.

Historical Perspective: Emergence of a Set of Methodologies

Material and energy flow analysis emerged from a long and rich history of managing the supply of resources for human needs. Baccini and Brunner, in their seminal volume Metabolism of the Anthroposphere (1991), recount the story of Dottore Santorio (1561–1636) who attempted to quantify the metabolism of his own physical body. With the advent of thermodynamics in the 19th century, energy was shown to underlie human development as both an opportunity and a constraint. In 1862 Herbert Spencer stated in his first principle that societal progress is based on energy surplus (Fischer-Kowalski, 1998). Stanley Jevons in his famous book The Coal Question (1865) extrapolated the rate of extraction of coal from British mines and questioned the sustainability of coal production based on its finite availability. His main contribution was to reveal the effect, which bears his name—that is, despite increasing efficiency, coal consumption kept on growing exponentially. His concerns about the future supply of resources to the British economy were echoed in other parts of Europe.

The history of MFA is often dated back to the urban metabolism of a fictitious American city of one million people (Wolman, 1965). Lederer and Kral (2015) have pointed to the work of Theodor Weyl, who conducted the first empirical study in urban metabolism, quantifying water, food and feed as well as sewage water and wastes, for the city of Berlin in 1894. Weyl was particularly concerned with nutrition and sanitation for a city of 1.5 million people. Moreover, he was interested in comparing the results when his methodological approach was applied to other European cities. Around the turn of the century, one of the first attempts to quantify the carrying capacity of the planet—that is, the biophysical requirements necessary to sustain basic human needs—was made by the Austrian physicist Leopold Pfaundler (Martinez‑Alier, 1987).

The analogy between biological and socioeconomical metabolism defined by biologists and ecologists was clearly influential, notably in the work of Howard Odum and his brother Eugene (Odum, 1970). The link between ecosystems and economic activities was most clearly drawn in a foundational article by the physicist Robert Ayres and the economist Allen Kneese (Ayres & Kneese, 1969). They argued that economic activities relied on seemingly free common goods, such as clean air and water, which led to the suboptimal allocation of resources and externalities. In MFA, externalities have since been considered as a problem of material balance above and beyond their economic value, which is what is typically dealt with in economic analysis. Ayres and Kneese presented the first MFA study for the United States based on 1963 data and laid out a research agenda for industrial metabolism in the decades that followed, with the implicit assumption that lower externalities meant lower health and environmental impacts. Similar advances describing the interactions between economic and resource flows were also made in input–output analysis, (Victor, 1972).

As Fischer-Kowalski (1998) showed, the wealth of research in material flow analysis since the 1970s has been conducted along four axes. First, the need to set spatial boundaries to systems under investigation led to research work on various scales, from industrial processes and economic activities to regional and national, as well as global. Second, MFA has focused on industrial processes, though urban metabolism to include final consumption. Third, MFA at the household scale, essentially began in the 1990s (Di Donato, Lomas, & Carpintero, 2015). In addition to the three or more spatial scales, the fourth temporal dimension characterizes the MFA research of the late 20th century. Historical MFAs provided hindsight into the magnitude of the material requirements underlying industrialization, which sometimes broadened to industrial society’s metabolism (Fischer-Kowalski, 2002).

In parallel to the application of MFA to households and cities, material flow cost accounting (MFCA) emerged in the late 1980s as a specific methodology in the field of environmental management accounting. The methodology was first developed by the Institut für Management und Umwelt (Institute for Management and the Environment) in Germany, under the name “flow cost accounting.” In 1999, the Japanese Ministry of International Trade and Industry initiated the Environmental Management Accounting Project that is still running today. In 2005, it was recognized as one of the most basic environmental management accounting tools (Schaltegger & Wagner, 2005; Wagner, 2015). The International Organization for Standardization, which develops harmonized procedures for almost every economic activity, released an international standard for MFCA in 2011.

Overview of MFA Methods and Approaches

General Principles of Material Flow Analysis

Material flow analysis consists of four general steps on which consensus is found in the literature (Baccini & Bader H.-P., 1996; Brunner & Rechberger, 2004; OECD, 2010).

  1. 1. Definition of the system: A study begins with a definition of the problem and of adequate goals. The choices are based on the most representative or critical substance(s) or material(s) and on the definition of the system in space and time, the so-called system boundaries. Then the processes describing the relevant transformation, transport, and deposition paths within the system are defined. Finally, flows between the processes are identified.

  2. 2. Data acquisition: Substance or material stock and flow data are collected using secondary sources or empirical surveys.

  3. 3. Calculation: The quantification and overview of the stocks and flows is completed. The whole material flow system is calculated and uncertainties are evaluated.

  4. 4. Representation and interpretation: The results are represented in an appropriate way to allow visualization and ease of understanding and interpretation of the system. Sankey diagrams are commonly used. Conclusions focus on goal-oriented decisions based on the definition of the problem.

The procedure can vary from one research group to another, since no uniform standard exists. The number of steps actually varies from three to five, depending on the authors, but the general procedure remains similar. In every system calculation, the most important principle is the conservation of mass. In every process and system of processes, the inputs are equal to the sum of outputs and additions to stocks.

Moreover, Brunner and Rechberger (2004) underlined the importance of iterative optimization (see Figure 1). Also, the selections and provisions that are taken during the course of the MFA have to be checked continuously. If necessary, they must be adapted to reflect the objectives of the project. The critical role of data in establishing reliable MFAs has prompted research on how to account for data quality and uncertainty in the analysis (Laner, Rechberger, & Astrup, 2014; Patrício, Kalmykova, Rosado, & Lisovskaja, 2015). Scenario and sensitivity analyses are the most common ways to address uncertainties related to the heterogeneity of data sources and the multiple scales of application in MFA.

Material and Energy Flow AnalysisClick to view larger

Figure 1. General procedure for material flow analysis (Brunner & Rechberger, 2004).

Urban and Regional Metabolism

Empirical studies remained relatively isolated until the late 1980s and focused primarily on industrial metabolism as exemplified by estimates of material flows for the United States and Belgium (Ayres, 1989; Billen et al., 1983). The first formalization of regional metabolism, including urban and industrial, was published a short time later, in 1991 (Baccini & Brunner, 1991). Urban and regional metabolism now refers to the analysis of material and energy flows, or throughput, in process chains, from the extraction of raw materials and the harvest of biomass to transformation, manufacturing, consumption, and recycling or disposal at the end of their useful lives (Bringezu & Moriguchi, 2002).

At the urban level, the early conceptualization, by Wolman (1965), defined as metabolism for all the materials and commodities needed to sustain a city’s inhabitants at home, work, and play. Since then, many attempts to quantify material flows in cities have been done under the terminology of urban metabolism. Applying MFA at the city scale usually has one of two objectives: (a) understanding the city’s reliance on material and energy supplies from the hinterland, and (b) understanding the environmental emissions and impacts related to the inner-city metabolism of these material and energy flows (Baccini, 1996). Brunner and Rechberger (2004) suggested a set of resource categories characterizing modern regional development and living habits: water, biomass, fossil fuels, and construction materials as inputs and sewage, gases and solid wastes as outputs (see Figure 2). Simulations can then be run based on projected population or economic growth and other variables such as household composition and behavior to plan for infrastructure development and services (Heinonen & Junnila, 2011).

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Figure 2. Total flows of resources for the Canton of Geneva for the year 2000 (Erkman, 2005).

Covering the needs of urban dwellers in terms of physical resources and sinks is of high strategic value for urban planners and directly linked to industrial ecology, as explained by Andrews (2002). Hence, numerous studies are based on substance and material flow analysis in the field of urban ecology, as in the ecology of cities (Barles, 2010). The most famous include studies of the metabolisms of Hong Kong (Newcombe, Kalma, & Aston, 1978), Vienna (Obernosterer & Brunner, 1998), and Paris (Barles, 2009). Christopher Kennedy (2016) provides an extensive review of the urban metabolism literature.

Urban and regional metabolism has been widely used for waste management. MFA studies contribute to the attainment of higher recycling rates and to reduction of losses of potential secondary raw materials. The main outcomes of MFA applied to waste management are the improvement of waste management system’s performance and the comparison of collection and treatment systems. Some of the studies done in the 21st century have been related to goods, such as municipal waste or electronic waste, or specific substances such as copper, zinc, mercury, or phosphorus. There have been a number of MFA studies related to construction and demolition waste (Allesch & Brunner, 2015; Moriguchi & Hashimoto, 2016). A specific application in industrial activities has led to the creation of industrial symbioses in which materials and energy cascades from one industry or process to another in order to maximize the reuse of waste. Data collection to identify symbiosis potential includes in most cases the development of an MFA model (Chertow, 2000; Grant, Seager, Massard, & Nies, 2010; Lyons, 2007).

Finally, it is worth mentioning the use of MFA to address material transformation after natural disasters or sudden influx of waste materials into an economic system (Tanikawa, Managi, & Lwin, 2014).

Substance Flow Analysis

A specific case of MFA is substance flow analysis (SFA), which implies the choice of a specific substance or compound to be evaluated in relation to an environmental or economic problem. The focus on a single substance is essential to assess the qualitative aspects of resources management and environmental impacts. SFA aims to provide relevant information for an overall management strategy with regard to one specific substance or a limited group of substances (van der Voet, 2002). Knowledge of the transformation, transport, and storage of valuable and hazardous substances forms the base for identifying both resource potentials and risks for human health and the environment (Allesch & Brunner, 2015). SFA has been used to determine the main emission pathways to the environment; the processes associated with these emissions; and the stocks and flows within the industrial system, as well as the flows from one environmental compartment to another; and the chemical, physical, or biological transformations in the environment (Bringezu & Moriguchi, 2002).

Since the 1990s, Tom Graedel has contributed to many substance flow analyses on metals, such as iron (Wang, Muller, & Graedel, 2007), copper (Kapur, Bertram, Spatari, Fuse, & Graedel, 2003; Spatari, Bertram, Gordon, Henderson, & Graedel, 2005), zinc (van Beers, Kapur, & Graedel, 2007; Yan, Wang, Chen, & Li, 2013) or silver (Johnson, Bertram, Henderson, Jirikowic, & Graedel, 2005). Phosphorus is a mineral that attracts a lot of attention because of its resource availability and, as shown in Figure 3, low degree of recoverability due to dissipative uses, such as n agricultural fertilizers (Brunner, 2010; Chowdhury, Moore, Weatherley, & Arora, 2014; Cordell, Drangert, & White, 2009; Jedelhauser & Binder, 2015; van Dijk, Lesschen, & Oenema, 2016). Other examples of substance flow analyses and their contribution to the understanding of the economic system address nuclear-fuel material flows and rare earth elements (Guyonnet, Planchon, Rollat, Escalon, Tuduri, Charles et al., 2015; Tendall & Binder, 2011).

Material and Energy Flow AnalysisClick to view larger

Figure 3. Blueprint for the analysis of P stocks and flows on a national level (Jedelhauser & Binder, 2015).

Dynamic modeling

Dynamic analysis of substance, material and energy stocks, and flows tackles more advanced problems than does stationary or quasi-stationary MFA. The main contribution of dynamic MFA has been in the display of material trajectories and the evolution of stocks in time (van der Voet, 2002). Determining the fate of materials in a system is essential for several uses: (a) identifying the main stocks in use and residence times, (b) quantifying dissipative uses, and (c) estimating the recycling potential from anthropogenic stocks. Resource depletion, as well as pollution, takes place over long periods of time, and conservation or remediation policies depend on the concentration of materials or pollutants in the different stocks. Both backcasting and forecasting studies have been conducted by reconstructing the metabolism of cities and nations to evaluate the future availability of resources. As shown in Figure 4, historical perspectives on the metabolism of industrial societies highlight the underlying shift from biomass to mineral resources and growth in metabolic rates (Schaffartzik, Mayer, Gingrich, Eisenmenger, Loy, & Krausmann, 2014). Barles (2010) also highlights the historical significance of urban metabolism in the field of sustainable urban development.

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Figure 4. Global domestic material consumption (DMC) in tons per capita per year (t/cap/a) by material category in 2010 (left) and share in global DMC by region (right) (Schaffartzik et al., 2014).

Dynamic analyses have also focused on specific substances, such as the life cycle of steel and copper over the 20th century (Muller, Wang, Duval, & Graedel, 2006; Spatari et al., 2005). The results show that in industrial societies, such as the United States, anthropogenic stocks, in use and in landfills, are comparable to geogenic reserves and could cover demand provided efficient recycling processes were implemented. Residence times in buildings and consumer products vary significantly, in particular for copper, given increasing use of electronics. Urban and landfill mining potential is often established based on historical MFA studies (Frändegård, Krook, Svensson, & Eklund, 2013; Jones, Geysen, Tielemans, Van Passel, Pontikes, Blanpain et al., 2013). Dynamic MFA has been of particular interest in the context of decarbonizing energy sources. So-called energy metals (e.g., lithium, neodymium, gallium), essential for manufacturing renewable such energy technologies as wind turbines and photovoltaic cells, have been analyzed for long-term availability (Elshkaki & Graedel, 2013; Vidal, Goffe, & Arndt, 2013). With renewable energy technologies, security of supply means the stocks in use are of strategic value (Guyonnet et al., 2015).

Models of dynamic MFA integrate the temporal dimension in different ways. Variables such as rates of extraction and recycling can be determined exogenously according to external models of population and economic growth. In a fully dynamic MFA model, the state of the system at time t is a function of its state at time t–1. A typical example is the extraction of resources or the emission of wastes, which either depletes or saturates, therefore affecting the system itself. This behavior follows a sinusoidal curve and asymptotic behavior with respect to time. Logistic functions provide much flexibility in modeling such dynamic behavior with minimum and maximum thresholds as well as varying growth or degrowth rates. Based on initial conditions, future states of the system can be simulated to support policymaking.

Input–Output Analysis

The growing share of trade flows in economic activities has meant that production and consumption processes increasingly occur in different regions, which are sometimes located far apart. Quantifying the energy, materials, and emissions embodied in international trade has largely drawn on the methodology of input-output analysis (IOA). Developed by economist Wassily Leontief to understand the interactions between economic sectors, IOA evaluates the economic and environmental implications of changes in final demand on the structure of economic activities (Leontief, 1970). Among his colleagues were Walter Isard, who contributed substantially to the initial input–output analysis at the regional level (Isard & Cumberland, 1961). Input-output tables (IOTs), or matrices, detail the supply and use of products (goods and services) sector by sector, including imports and exports and final consumption categories such as households, government spending, and capital formation. What is true for economic sectors is also true at the process level, and supply and use tables essentially represent the transfer coefficients from one industry to another in monetary or physical terms. The availability of environmentally extended input–output tables (EE-IOT) has considerably increased the usefulness of IOTs in MFA at the level of industrial activities (Duchin, 1992). Environmental accounts typically include energy intensity and carbon emissions by sector, which is especially relevant for economic and environmental policies. Because IOA is linear in nature, the impacts of changes in the final demand can easily be estimated for specific industrial sectors or on the structure of economic activities—that is, shifts in production domestically and abroad.

Among the early contributions, Gay and Proops (1993) analyzed carbon emissions of final consumption in the United Kingdom, and Lenzen (1998) provided primary energy requirements and related carbon emissions for final consumption in Australia. Thereafter, research essentially focused on emissions embodied in trade (Baiocchi & Minx, 2010; Munksgaard, Pade, Minx, & Lenzen, 2005; Peters & Hertwich, 2008; Peters, Minx, Weber, & Edenhofer, 2011). Estimates of direct Chinese emissions indirectly attributable to the regions of final consumption of Chinese products are of particular relevance in climate-change policymaking (Minx et al., 2011; Peters, Weber, Guan, & Hubacek, 2007). Other developments have included multiregional input–output tables (MR-IOT), substituting import and export vectors with full tables for multiple regions (Wiedmann, Lenzen, Turner, & Barrett, 2007). Simultaneously, other factor inputs, such as land, materials and water consumption, as well as air emissions, were quantified to expand the analysis of material flows and compile indicators. such as the ecological footprint of nations (Wiedmann, Minx, Barrett, & Wackernagel, 2006; Wiedmann, Schandl, Lenzen, Moran, Suh, West et al., 2015).

Along with the additions to stocks or changes in inventories per economic sector, more detailed IOTs, over multiple years, became available, in particular from large research projects (Dietzenbacher, Los, Stehrer, Timmer, & de Vries, 2013; Tukker, de Koning, Wood, Hawkins, Lutter, Acosta et al., 2013). Data requirements for constructing IOTs have been a significant limiting factor; however, national and regional statistical offices now publish such tables. One of the main advantages of EE-IOTs is to provide a consumption perspective on material and energy flows, accounting for first, second, and beyond order effects in production and consumption chains. Indeed, IOA has also been combined with life-cycle assessment (LCA) for inventories for which process data is lacking or to improve overall data reliability (Suh & Huppes, 2002). In turn, the results of IOA can inform macroeconomic policies as well as microeconomic consumer choices (Tukker, Bulavskaya, Giljum, de Koning, Lutter, Simas et al., 2014; Watson, Fernández, Wittmer, & Pedersen, 2013).

Economy-wide MFA

Material flow analysis at the national level strives to represent the equivalent of national accounts in physical instead of monetary terms. The goal of so-called economy-wide MFA is to quantify the material flows and stocks underlying socioeconomic development at the national and global level. Energy use, for example, has been an important measure of socioeconomic development, correlated with economic growth since the Industrial Revolution (Warr, Ayres, Eisenmenger, Krausmann, & Schandl, 2010). As a research field, physical accounting has achieved a high level of consistency among research groups and acceptance in policy circles (Fischer-Kowalski, Krausmann, Giljum, Lutter, Mayer, Bringezu et al., 2011). However, different terminologies still exist to describe material and energy flows across national boundaries and exchanges with the environment. The terms “socioeconomic metabolism” and “societal metabolism” are used interchangeably to represent MFA of a broader geographical and temporal scope. Pauliuk and colleagues (Pauliuk, Majeau-Bettez, & Müller, 2015) provide a systematic comparison of the different models for socioeconomic metabolism. Statistical offices compile data for material flows on national and regional scales based on well-established accounting guidelines (Eurostat, 2007; OCED, 2010). The methodological approaches share a common framework that takes the economy as a whole and quantifies inputs and outputs both to and from other nations and to and from the environment (Figure 5). Note that the residence principle in the calculation of gross domestic product (GDP) implies that system boundaries between the national economy and the environment sometimes differ. As elsewhere in MFA, air and water dominate material flows and are considered separately, except for the share incorporated in economic activities, such as oxygen in combustion processes (balancing items). The remaining material flows are divided into four categories, biomass, fossil fuels, metals and mineral ores, and construction minerals, each of which has its own statistical data sources (e.g., FAO, USGS, IEA, etc.). They are extracted domestically or imported directly and indirectly through finished and semifinished goods.

Material and Energy Flow AnalysisClick to view larger

Figure 5. Economy-wide material balance framework. Adapted from Swiss Federal Statistical Office representation of EW-MFA.

By analogy with GDP, several indicators of material performance have been developed for national economies. The sum of domestic extraction (DE) and direct imports is equal to the direct material input (DMI). When subtracting exports from DMI, the results yield domestic material consumption (DMC), in other words, the physical indicator that corresponds to GDP the most. Emissions to nature or processed outputs include essentially CO2, wastes and dissipative uses, such as in fertilizers and rubber tire wear. Extractions and emissions in physical terms enter into combined national and environmental accounts under the acronym NAMEA, or national accounting matrix with environmental accounts, also known as hybrid input–output tables.

As a reference, an average value for global domestic extraction used was reported by Fischer-Kowalski and her colleagues (2011) at 51.3 billion tons for the year 2000. Biomass and construction minerals accounted for over 70% of DE. Yet little research has been dedicated to the estimation of historical accumulation of materials and net additions to stocks, partly because of methodological and empirical challenges (Fishman, Schandl, Tanikawa, Walker, & Krausmann, 2014). As they stand, the material stocks of industrialized nations, such as the United States and Japan, were estimated at between 310 and 375 tons per capita. For similar reasons, the construction of physical input–output tables is another research problem that has received little attention.

However, more efforts have focused on the total material requirements (TMR) of national economies, that is, the sum of DE, unused domestic extraction (mostly excavated materials), and imports together with their required unused extraction in the countries of origins. Subtracting exports and their required unused extraction from TMR gives total material consumption (TMC), another relevant indicator of the overall material footprint of nations. The raw material equivalents of domestic consumption, or material footprints, are increasingly derived from input–output analysis as described here (Muñoz, Giljum, & Roca, 2009; Schoer, Weinzettel, Kovanda, Giegrich, & Lauwigi, 2012; Tukker et al., 2014; Wiedmann et al., 2015).

In addition, two aspects of economy-wide MFA are extensively developed with the help of time series, dematerialization, and inequity in material consumption. Dematerialization of socioeconomic activities is either measured in absolute terms, a reduction of material consumption, or in relative terms when economic growth and material consumption are decoupled. From a consumption-based perspective few examples exist of the latter, let alone the former, showing the very material nature of the most developed economies (Steinberger, Krausmann, Getzner, Schandl, & West, 2013). Germany, for example, has shown signs of decoupling in absolute terms as it imports more semifinished products and exports premium cars (Moreau & Medeazza, 2008). With strong economic growth and export-oriented manufacturing, China exemplifies relative decoupling. The implicit assumption in MFA that lower resource use or dematerialization lightens the environmental load does not apply equally to all countries. Per capita and per year, domestic material consumption varies widely and illustrates the inequalities in metabolic rates in part due to international trade (Marina Fischer-Kowalski & Swilling, 2011). Disparities in material consumption can be represented with indices similar to Gini coefficients measuring income inequalities and with comparable results (Teixidó-Figueras, Steinberger, Krausmann, Haberl, Wiedmann, Peters et al., 2016).

Material Flow Cost Accounting

The concept of material flow cost accounting (MFCA) began with the idea of assessing the costs, as well as the physical properties, of material flows at the corporate and value chain levels. MFCA goes a step further than MFA and LCA since it also quantifies and assesses potentials for monetary savings (M. Schmidt, 2015).

Considered as a corporate management tool, MFCA helps managers make the link between the physical information on material flows and the data from managerial accounting. Thus, MFCA highlights the material costs aggregated along the production processes, from purchase to disposal. It is a powerful method for identifying material and system costs and facilitating eco-efficient decision-making related to waste material, energy and water supply, as well as emissions (Christ & Burritt, 2015; Wan, Ng, Ng, & Tan, 2015). Because procurement costs are a major driver in the industry, focusing on material and energy flows and their related costs is of high priority for managers. Proper allocation of the costs associated with the material and energy flows is a necessary starting point for material and cost optimization.

In September 2011, the ISO released the ISO 14051 standard for material flow cost accounting. The ISO offers a general framework for MFCA, providing information on terminologies, objectives, principles and fundamental elements. It defines MFCA as a tool for quantifying the flows and stocks of materials in processes or production lines in both physical and monetary terms: “MFCA is a management tool that can assist organizations to better understand the potential environmental and financial consequences of their material and energy use practices, and seek opportunities to achieve both environmental and financial improvements via changes in those practices” (ISO 14051, 2011).

The main principles for MCFA implementation are (a) understanding material flow and energy use by developing a material flow model; (b) linking physical and monetary data; (3) ensuring accuracy, completeness, and comparability of physical data; and (d) estimating and attributing costs to material losses (ISO 14051, 2011).

MFCA is applicable to all industries that use materials and energy, including extractive, manufacturing, and service industries, among others. The first step for implementation is defining the system boundaries. According to (Kokubu & Tachikawa, 2013) the system boundaries associated with any MFCA experiment are determined by both the organizational context and the underlying objectives for implementation. The implementation phase includes the following steps: (a) identification of inputs and outputs for each process, (b) quantification of material and energy flows in physical units, and (c) quantification of material and energy flows in monetary units. Complete reviews of MFCA methodological developments and practices have been published by (Christ & Burritt, 2015; Schaltegger & Zvezdov, 2015). For more information on implementation procedures in the industry, please refer to the technical literature (Jasch, 2009; Ministry of Economy, Trade and Industry [METI], 2007, 2010; A. Schmidt, Götze, & Sygulla, 2015).

MFCA requires the strong involvement of the company management because it represents efforts beyond conventional environmental management systems. One essential success factor of MFCA is that the method shows not only the direct costs of wastes (losses), but also the lost added value for the company, including costs of materials, labor and capital. However, if a few case studies exist that demonstrate the potential of MCFA to deal with eco-efficiency in the industry, the degree of adoption by managers remains low. The management perspective for MFCA is, however, very promising (Kokubu & Kitada, 2015).

Research and Policy Perspectives

Material flow analysis qualifies and quantifies the physical basis of socioeconomic systems at multiple scales, providing both research opportunities and rationale for policymaking.

In terms of research, three promising avenues are relevant for MFA. First, one lesson can be drawn from the field of life cycle assessment, in which standardization and harmonization work has been necessary for comparison purposes (e.g., Hauschild, Huijbregts, Jolliet, Macleod, Margni, van de Meent et al., 2008). In 2002, the ISO 14040 series defined the principles and methodologies used to perform a standardized life cycle assessment. By contrast, a diversity of methodological approaches exists in MFA and much remains to be done in order to achieve conceptual and methodological harmonization. Only MFCA has been standardized recently, with ISO 14051. However, the implementation of MFCA requires broader applications before fully integrating material flow analysis in practice. The theoretical foundations of MFCA still need to be developed to delineate clear spatial and temporal boundaries and where MFCA and MFA interconnect (Christ & Burritt, 2015). Similarly, if economy-wide MFA has reached a high level of maturity, robust comparisons at the urban and regional scale require more harmonized approaches in space and time (Barles, 2010). Conceptual, methodological, and analytical work is still needed to reach a high degree of convergence among the multiple and individual MFA initiatives. Establishing a consensus-based methodology is important, not only for comparison and validation purposes, but also to improve understanding and credibility among policymakers.

A second research avenue started with a recurrent problem in MFA but also seen in LCA and other fields. As Brunner (2012) stated, “You can’t manage what you can’t measure.” Effective resource management requires reliable data from both primary and secondary sources. Physical process data as well as economic data feed into the methodological approaches described here, sometimes substituting for gaps in one data source or another. Large databases are now available for material flow accounting and input–output analysis, but primary data collection remains an important step in MFA at the urban or industrial scale. In parallel to improving the quality of data sources, more systematic uncertainty analysis would increase the reliability of MFA.

The third way forward links the material and energy flows underlying economic activities, urban and industrial systems with human or household consumer behavior. Several approaches have been coupled with MFA in an attempt to show the physical impacts of behavioral changes (Binder, 2007a). Research in the social sciences have coupled methods, such as agent-based modeling, with MFA (Binder, 2007b). The results of material flows and stocks analysis provide visually powerful representations to describe the far-reaching implications of household consumption and decision-making in the private and public sector. Yet the analysis of (un)sustainable consumption patterns in MFA calls for new methodological development (Di Donato et al., 2015). The consumption of a few specific substances has received the attention it deserves and reached a wide audience, such as the water footprint of consumer goods like meat or clothing. Many products, goods and services, would benefit from similar studies and wide dissemination in the future.

Thus, research in MFA is often steps away from policy, targeting both intermediate industrial processes, and final household consumption. Along with growing constraints on material sources and sinks, major shifts in production and consumption are expected and seriously needed. Dynamic MFA has contributed to the development of scenarios for future material and energy requirements, taking into account technological shifts and changes in urban planning and development, as well as consumption habits at the household level. Historical MFA illustrates the great transition from biomass and renewables to mineral and nonrenewable resources and the extent of the changes required to close material cycles at the level of consumption seen in 2015. The policy relevance of MFA increases substantially as institutions around the world call for implementing circular economy. At the industrial level, MFA remains the analytical tool to evaluate the potential savings, both physical and monetary, in planning and implementing sustainable production sites, such as eco-industrial parks, and other types of industrial symbiosis.

Measuring embodied material and energy flows in trade relies on MFA using input–output analysis or the economy-wide methodology, and becomes essential in setting trade policies that support sustainable consumption. More specifically, in the energy sector, study of the carbon footprint of our energy systems has been an active field research that is directly linked to climate policy. The energy transition toward a low-carbon economy trades off fossil energy flows for materials stocked in renewable energy technologies, and MFA researchers and practitioners contribute to the bigger picture of biophysical constraints and policy implications.

References

Allesch, A., & Brunner, P. H. (2015). Material flow analysis as a decision support tool for waste management: A literature review. Journal of Industrial Ecology, 19, 753–764.Find this resource:

Andrews, C. J. (2002). Industrial ecology and spatial planning. In R. U. Ayres & L. W. Ayres (Eds.), A handbook of industrial ecology (pp. 476–487). Cheltenham, U.K.: Edward Elgar.Find this resource:

Ayres, R. U. (1989). Industrial metabolism. In J. H. Ausubel & H. E. Sladovich (Eds.), Technology and environment (pp 23–49). Washington: National Academy Press.Find this resource:

Ayres, R. U., & Kneese, A. V. (1969). Production, consumption, and externalities. American Economic Review, 59, 282–297.Find this resource:

Baccini, P. (1996). Understanding regional metabolism for a sustainable development of urban systems. Environmental Science and Pollution Research, 3, 108–111.Find this resource:

Baccini, P., & Bader H.-P. (1996). Regionaler Stoffhaushalt: Erfassung, Bewertung, und Steuerung. Heidelberg, Germany: Spektrum Akademischer Verlag.Find this resource:

Baccini, P., & Brunner, P. H. (1991). Metabolism of the anthroposphere. Berlin: Springer-Verlag.Find this resource:

Baiocchi, G., & Minx, J. C. (2010). Understanding changes in the UK’s CO2 emissions: A global perspective. Environmental Science and Technology, 44, 1177–1184.Find this resource:

Barles, S. (2009). Urban metabolism of Paris and its region. Journal of Industrial Ecology, 13, 898–913.Find this resource:

Barles, S. (2010). Society, energy and materials: The contribution of urban metabolism studies to sustainable urban development issues. Journal of Environmental Planning and Management, 53, 439–455.Find this resource:

Billen, G., Toussaint, F., Peeters, P., Sapir, M., Steenhout, A., & Vanderborght, J.-P. (1983). L’écosystème Belgique: Essai d’écologie industrielle. Brussels, Belgium: Centre de recherche et d’information sociopolitiques.Find this resource:

Binder, C. R. (2007a). From material flow analysis to material flow management part I: Social sciences modeling approaches coupled to MFA. From Material Flow Analysis to Material Flow Management, 15, 1596–1604.Find this resource:

Binder, C. R. (2007b). From material flow analysis to material flow management part II: The role of structural agent analysis. From Material Flow Analysis to Material Flow Management, 15, 1605–1617.Find this resource:

Bringezu, S., & Moriguchi, Y. (2002). Material flow analysis. In R. U. Ayres & L. W. Ayres (Eds.), A handbook of industrial ecology (p. 680). Cheltenham, U.K.: Edward Elgar.Find this resource:

Bringezu, S., & Schütz, H. (2010). Material use indicators for measuring resource productivity and environmental impacts, Resource Efficiency paper no 6.1 (p. 57). Wuppertal Institute for Climate, Environment and Energy. Berlin.Find this resource:

Brunner, P. H. (2010). Substance flow analysis as a decision support tool for phosphorus management. Journal of Industrial Ecology, 14, 870–873.Find this resource:

Brunner, P. H. (2012). Substance flow analysis. Journal of Industrial Ecology, 16, 293–295.Find this resource:

Brunner, P. H., & Rechberger, H. (2004). Practical handbook for material flow analysis. Boca Raton, FL: CRC Press.Find this resource:

Chertow, M. (2000). Industrial symbiosis: Literature and taxonomy. Annual Review of Energy and the Environment, 25, 313–337.Find this resource:

Chowdhury, R. B., Moore, G. A., Weatherley, A. J., & Arora, M. (2014). A review of recent substance flow analyses of phosphorus to identify priority management areas at different geographical scales. Resources, Conservation and Recycling, 83, 213–228.Find this resource:

Christ, K. L., & Burritt, R. L. (2015). Material flow cost accounting: A review and agenda for future research. Material Flow Cost Accounting, 108, Part B, 1378–1389.Find this resource:

Cordell, D., Drangert, J.-O., & White, S. (2009). The story of phosphorus: Global food security and food for thought. Global Environmental Change, 19, 292–305.Find this resource:

Di Donato, M., Lomas, P. L., & Carpintero, Ó. (2015). Metabolism and environmental impacts of household consumption: A review on the assessment, methodology, and drivers. Journal of Industrial Ecology, 19, 904–916.Find this resource:

Dietzenbacher, E., Los, B., Stehrer, R., Timmer, M., & de Vries, G. (2013). The construction of world input–output tables in the WIOD project. Economic Systems Research, 25(1), 71–98.Find this resource:

Duchin, F. (1992). Industrial input–output analysis: Implications for industrial ecology. Proceedings of the National Academy of Sciences, 89, 851–855.Find this resource:

Elshkaki, A., & Graedel, T. E. (2013). Dynamic analysis of the global metals flows and stocks in electricity generation technologies. Journal of Cleaner Production, 59, 260–273.Find this resource:

Erkman, S. (2005). Industrial ecology in Geneva, initial findings and prospects. Report from the Ecosite Workgroup, State waste management service, Rebulic and State of Geneva, Switzerland.Find this resource:

Eurostat. (2007). Economy-wide material flow accounting: A compilation guide. Luxembourg: Eurostat.Find this resource:

Fischer-Kowalski, M. (1998). Society’s metabolism: The intellectual history of materials flow analysis part I, 1860–1970. Journal of Industrial Ecology, 2, 61–78.Find this resource:

Fischer-Kowalski, M. (2002). Exploring the history of industrial metabolism. In R. U. Ayres & L. W. Ayres, A handbook of Industrial Ecology (p. 680). Cheltenham, U.K.: Edward Elgar.Find this resource:

Fischer-Kowalski, M., & Hüttler, W. (1998). Society’s metabolism: The intellectual history of materials flow analysis part II, 1970–1998. Journal of Industrial Ecology, 2(4), 107–136.Find this resource:

Fischer-Kowalski, M., Krausmann, F., Giljum, S., Lutter, S., Mayer, A., Bringezu, S., et al. (2011). Methodology and indicators of economy-wide material flow accounting. Journal of Industrial Ecology, 15(6), 855–876.Find this resource:

Fischer-Kowalski, M., & Swilling, M. (2011). Decoupling: Natural resource use and environmental impacts from economic growth. United Nations Environment Programme. Retrieved from http://www.unep.org/resourcepanel/decoupling/files/pdf/Decoupling_Report_English.pdf.

Fishman, T., Schandl, H., Tanikawa, H., Walker, P., & Krausmann, F. (2014). Accounting for the material stock of nations. Journal of Industrial Ecology, 18(3), 407–420.Find this resource:

Frändegård, P., Krook, J., Svensson, N., & Eklund, M. (2013). Resource and climate implications of landfill mining. Journal of Industrial Ecology, 17(5), 742–755.Find this resource:

Gay, P. W., & Proops, J. L. R. (1993). Carbondioxide production by the UK economy: An input–output assessment. Energy and Environmental Management, 44(2), 113–130.Find this resource:

Grant, G. B., Seager, T. P., Massard, G., & Nies, L. (2010). Information and communication technology for industrial symbiosis. Journal of Industrial Ecology, 14, 740–753.Find this resource:

Guyonnet, D., Planchon, M., Rollat, A., Escalon, V., Tuduri, J., Charles, N., et al. (2015). Material flow analysis applied to rare earth elements in Europe. Journal of Cleaner Production, 107, 215–228.Find this resource:

Hauschild, M. Z., Huijbregts, M., Jolliet, O., Macleod, M., Margni, M., van de Meent, D., et al. (2008). Building a model based on scientific consensus for life cycle impact assessment of chemicals: The search for harmony and parsimony. Environmental Science and Technology, 42, 7032–7037.Find this resource:

Heinonen, J., & Junnila, S. (2011). Implications of urban structure on carbon consumption in metropolitan areas. Environmental Research Letters, 6, 14018.Find this resource:

Isard, W., & Cumberland, J. H. (Eds.). (1961). Regional economic planning: Techniques of analysis. Paris: Organisation of Economic Co-operation and Development.Find this resource:

International Organization for Standardization 14051. (2011). ISO 14051: Environmental Management: Material Flow Cost Accounting: General Framework (14051). International Organization for Standardization, Geneva, Switzerland.Find this resource:

Jasch, C. (2009). Environmental and material flow cost accounting: Principles and procedures. Vol. 25. Springer Netherlands.Find this resource:

Jedelhauser, M., & Binder, C. R. (2015). Losses and efficiencies of phosphorus on a national level: A comparison of European substance flow analyses. Losses and Efficiencies in Phosphorus Management, 105, Part B, 294–310.Find this resource:

Jevons, W. S. (1865). The coal question: An inquiry concerning the progress of the nation, and the probable exhaustion of our coal mines. London: Macmillan.Find this resource:

Johnson, J., Bertram, M., Henderson, K., Jirikowic, J., & Graedel, T. E. (2005). The contemporary Asian silver cycle: 1-year stocks and flows. Journal of Material Cycles and Waste Management, 7, 93–103.Find this resource:

Jones, P. T., Geysen, D., Tielemans, Y., Van Passel, S., Pontikes, Y., Blanpain, B., et al. (2013). Enhanced landfill mining in view of multiple resource recovery: A critical review. [Special issue]. Urban and Landfill Mining, 55, 45–55.Find this resource:

Kapur, A., Bertram, M., Spatari, S., Fuse, K., & Graedel, T. E. (2003). The contemporary copper cycle of Asia. Journal of Material Cycles and Waste Management, 5, 143–156.Find this resource:

Kennedy, C. (2016). Industrial ecology and cities. In R. Clift & A. Druckman (Eds.), Taking stock of industrial ecology (pp. 69–86). Springer International. Retrieved from http://dx.doi.org/10.1007/978-3-319-20571-7_4Find this resource:

Kokubu, K., & Kitada, H. (2015). Material flow cost accounting and existing management perspectives. Material Flow Cost Accounting, 108, Part B, 1279–1288.Find this resource:

Kokubu, K., & Tachikawa, H. (2013). Material flow cost accounting: Significance and practical approach. In J. Kauffman & K.-M. Lee (Eds.), Handbook of sustainable engineering (pp. 351–369). [Springer ebook]. Retrieved from http://dx.doi.org/10.1007/978-1-4020-8939-8_96Find this resource:

Laner, D., Rechberger, H., & Astrup, T. (2014). Systematic evaluation of uncertainty in material flow analysis. Journal of Industrial Ecology, 18, 859–870.Find this resource:

Lederer, J., & Kral, U. (2015). Theodor Weyl: A pioneer of urban metabolism studies. Journal of Industrial Ecology, 19, 695–702.Find this resource:

Lenzen, M. (1998). Primary energy and greenhouse gases embodied in Australian final consumption: An input–output analysis. Energy Policy, 26, 495–506.Find this resource:

Leontief, W. (1970). Environmental repercussions and the economic structure: An input–output approach. Review of Economics and Statistics, 52, 262–271.Find this resource:

Lyons, D. (2007). A spatial analysis of loop closing among recycling, remanufacturing, and waste treatment firms in Texas. Journal of Industrial Ecology, 11, 43–54.Find this resource:

Martinez‑Alier, J. (1987). Ecological economics: Energy, environment and society. Oxford: Blackwell.Find this resource:

Ministry of Economy, Trade and Industry. (2007). Guide for material flow cost accounting: Ministry of Economy, Trade and Industry (Version 1. March 2007). Tokyo, Japan: METI.Find this resource:

Ministry of Economy, Trade and Industry. (2010). Environmental management accounting: MFCA Case Examples. Toyko, Japan: METI.Find this resource:

Minx, J. C., Baiocchi, G., Peters, G. P., Weber, C. L., Guan, D., & Hubacek, K. (2011). A “carbonizing dragon”: China’s fast growing CO2 emissions revisited. Environmental Science and Technology, 45, 9144–9153.Find this resource:

Moreau, V., & Medeazza, G. M. von. (2008). Is the economy (de)materializing? A comparison of Germany, China and Spain (pp. 156–164). Presented at the first conference on economic de-growth for ecological sustainability and social equity, Paris, France. Retrieved from http://events.it-sudparis.eu/degrowthconference/appel/Degrowth%20Conference%20-%20Proceedings.pdfFind this resource:

Moriguchi, Y., & Hashimoto, S. (2016). Material flow analysis and waste management. In R. Clift & A. Druckman (Eds.), Taking stock of industrial ecology (pp. 247–262). Springer International. Retrieved from http://dx.doi.org/10.1007/978-3-319-20571-7_12Find this resource:

Muller, D. B., Wang, T., Duval, B., & Graedel, T. E. (2006). Exploring the engine of anthropogenic iron cycles. Proceedings of the National Academy of Sciences of the United States of America, 103, 16111–16116.Find this resource:

Munksgaard, J., Pade, L. L., Minx, J., & Lenzen, M. (2005). Influence of trade on national CO2 emissions. International Journal of Global Energy Issues, 23, 324.Find this resource:

Muñoz, P., Giljum, S., & Roca, J. (2009). The raw material equivalents of international trade. Journal of Industrial Ecology, 13, 881–897.Find this resource:

Newcombe, K., Kalma, J., & Aston, A. (1978). The metabolism of a city: The case of Hong Kong. Ambio, 7, 3–15.Find this resource:

Obernosterer, R., & Brunner, P. H. (1998). Materials accounting as a tool for decision-making in environmental policy: Case study report 1: Urban metabolsim of the city of Vienna. Vienna: Vienna University of Technology, Institute for water quality and waste management.Find this resource:

Odum, H. T. (1970). Environment, power, and society. Wiley Interscience.Find this resource:

Organisation of Economic Co-operation and Development (OECD). (2008). Measuring material flows and resource productivity: Vol. 1. The OECD guide. Paris: OECD.Find this resource:

Organisation of Economic Co-operation and Development (OECD). (2010). Measuring material flows and resource productivity (p. 164). Paris: OECD.Find this resource:

Patrício, J., Kalmykova, Y., Rosado, L., & Lisovskaja, V. (2015). Uncertainty in material flow analysis indicators at different spatial levels. Journal of Industrial Ecology, 19, 837–852.Find this resource:

Pauliuk, S., Majeau-Bettez, G., & Müller, D. B. (2015). A general system structure and accounting framework for socioeconomic metabolism. Journal of Industrial Ecology, 19, 728–741.Find this resource:

Peters, G. P., & Hertwich, E. G. (2008). CO2 embodied in international trade with implications for global climate policy. Environmental Science and Technology, 42(5), 1401–1407.Find this resource:

Peters, G. P., Minx, J. C., Weber, C. L., & Edenhofer, O. (2011). Growth in emission transfers via international trade from 1990 to 2008. Proceedings of the National Academy of Sciences, 108, 8903–8908.Find this resource:

Peters, G. P., Weber, C. L., Guan, D., & Hubacek, K. (2007). China’s growing CO2 emissions: A race between increasing consumption and efficiency gains. Environmental Science and Technology, 41, 5939–5944.Find this resource:

Schaffartzik, A., Mayer, A., Gingrich, S., Eisenmenger, N., Loy, C., & Krausmann, F. (2014). The global metabolic transition: Regional patterns and trends of global material flows, 1950–2010. Global Environmental Change, 26, 87–97.Find this resource:

Schaltegger, S., & Wagner, M. (2005). Current trends in environmental cost accounting and its interaction with ecoefficiency performance measurement and indicators. In P. Rikhardsson, M. Bennett, J. Bouma, & S. Schaltegger (Eds.), Implementing environmental management accounting: Status and challenges (Vol. 18, pp. 45–62). Springer Netherlands. Retrieved from http://dx.doi.org/10.1007/1-4020-3373-7_3Find this resource:

Schaltegger, S., & Zvezdov, D. (2015). Expanding material flow cost accounting. Framework, review and potentials. Material Flow Cost Accounting, 108, Part B, 1333–1341.Find this resource:

Schmidt, A., Götze, U., & Sygulla, R. (2015). Extending the scope of material flow cost accounting—methodical refinements and use case. Material Flow Cost Accounting, 108, Part B, 1320–1332.Find this resource:

Schmidt, M. (2015). The interpretation and extension of material flow cost accounting (MFCA) in the context of environmental material flow analysis. Material Flow Cost Accounting, 108, Part B, 1310–1319.Find this resource:

Schoer, K., Weinzettel, J., Kovanda, J., Giegrich, J., & Lauwigi, C. (2012). Raw material consumption of the European Union: Concept, calculation method, and results. Environmental Science and Technology, 46(16), 8903–8909.Find this resource:

Spatari, S., Bertram, M., Gordon, R. B., Henderson, K., & Graedel, T. E. (2005). Twentieth-century copper stocks and flows in North America: A dynamic analysis. Ecological Economics, 54(1), 37–51.Find this resource:

Steinberger, J. K., Krausmann, F., Getzner, M., Schandl, H., & West, J. (2013). Development and dematerialization: An international study. PLOS ONE, 8(10).Find this resource:

Suh, S., & Huppes, G. (2002). Missing inventory estimation tool using extended input–output analysis. International Journal of Life Cycle Assessment, 7, 134–140.Find this resource:

Tanikawa, H., Managi, S., & Lwin, C. M. (2014). Estimates of lost material stock of buildings and roads due to the great East Japan earthquake and tsunami. Journal of Industrial Ecology, 18, 421–431.Find this resource:

Teixidó-Figueras, J., Steinberger, J. K., Krausmann, F., Haberl, H., Wiedmann, T., Peters, G. P., et al. (2016). International inequality of environmental pressures: Decomposition and comparative analysis. Ecological Indicators, 62, 163–173.Find this resource:

Tendall, D. M., & Binder, C. R. (2011). Nuclear energy in Europe: Uranium flow modeling and fuel cycle scenario trade-offs from a sustainability perspective. Environmental Science and Technology, 45(6), 2442–2449.Find this resource:

Tukker, A., Bulavskaya, T., Giljum, S., de Koning, A., Lutter, S., Simas, M., et al. (2014). The global resource footprint of nations. Carbon, water, land and materials embodied in trade and final consumption calculated with EXIOBASE 2.1. European Union FP7 CREEA Project report Leiden/Delft/Vienna/Trondheim.Find this resource:

Tukker, A., de Koning, A., Wood, R., Hawkins, T., Lutter, S., Acosta, J., et al. (2013). EXIOPOL—Development and illustrative analyses of a detailed global MR EE SUT/IOT. Economic Systems Research, 25(1), 50–70.Find this resource:

van Beers, D., Kapur, A., & Graedel, T. E. (2007). Copper and zinc recycling in Australia: Potential quantities and policy options. Journal of Cleaner Production, 15, 862–877.Find this resource:

van der Voet, E. (2002). Substance flow analysis methodology. In R. U. Ayres & L. W. Ayres, A handbook of industrial ecology (p. 680). Cheltenham, U.K.: Edward Elgar.Find this resource:

van Dijk, K. C., Lesschen, J. P., & Oenema, O. (2016). Phosphorus flows and balances of the European Union member states. Special Issue on Sustainable Phosphorus Taking Stock: Phosphorus Supply from Natural and Anthropogenic Pools in the 21st Century, 542, Part B, 1078–1093.Find this resource:

Victor, P. A. (1972). Input-output analysis of economic and environmental interactions. In P. A. Victor (Ed.), Economics of pollution (pp. 55–72). London: Macmillan Education UK. Retrieved from http://dx.doi.org/10.1007/978-1-349-01531-3_4Find this resource:

Vidal, O., Goffe, B., & Arndt, N. (2013). Metals for a low-carbon society. Nature Geoscience, 6, 894–896.Find this resource:

Wagner, B. (2015). A report on the origins of material flow cost accounting (MFCA) research activities. Material Flow Cost Accounting, 108, Part B, 1255–1261.Find this resource:

Wan, Y. K., Ng, R. T. L., Ng, D. K. S., & Tan, R. R. (2015). Material flow cost accounting (MFCA)–based approach for prioritisation of waste recovery. Journal of Cleaner Production, 107, 602–614.Find this resource:

Wang, T., Muller, D. B., & Graedel, T. E. (2007). Forging the anthopogenic iron cycle. Environmental Science and Technology, 41, 5120–5129.Find this resource:

Warr, B., Ayres, R., Eisenmenger, N., Krausmann, F., & Schandl, H. (2010). Energy use and economic development: A comparative analysis of useful work supply in Austria, Japan, the United Kingdom and the US during 100 years of economic growth. Ecological Economics, 69(10), 1904–1917.Find this resource:

Watson, D., Fernández, J. A., Wittmer, D., & Pedersen, O. G. (2013). Environmental pressures from European consumption and production (Technical report No. 2). Copenhagen, Denmark: European Environment Agency.Find this resource:

Wiedmann, T., Lenzen, M., Turner, K., & Barrett, J. (2007). Examining the global environmental impact of regional consumption activities—Part 2: Review of input–output models for the assessment of environmental impacts embodied in trade. Ecological Economics, 61(1), 15–26.Find this resource:

Wiedmann, T., Minx, J., Barrett, J., & Wackernagel, M. (2006). Allocating ecological footprints to final consumption categories with input–output analysis. Ecological Economics, 56(1), 28–48.Find this resource:

Wiedmann, T. O., Schandl, H., Lenzen, M., Moran, D., Suh, S., West, J., et al. (2015). The material footprint of nations. Proceedings of the National Academy of Sciences, 112(20), 6271–6276.Find this resource:

Wolman, A. (1965). The metabolism of cities. Scientific American, 213(3), 178–193.Find this resource:

Yan, L., Wang, A., Chen, Q., & Li, J. (2013). Dynamic material flow analysis of zinc resources in China. Resources, Conservation and Recycling, 75, 23–31.Find this resource: