Article pubs.acs.org/est
Raw Material Consumption of the European Union − Concept, Calculation Method, and Results Karl Schoer,† Jan Weinzettel,*,‡,§ Jan Kovanda,§ Jürgen Giegrich,∥ and Christoph Lauwigi∥ †
Sustainable Solutions Germany (SSG), Hasengartenstr 9b, 65189 Wiesbaden, Germany Industrial Ecology Programme (IndEcol), Norwegian University of Science and Technology (NTNU), NO-7491 Trondheim, Norway § Environment Center (CUEC), Charles University in Prague, J. Martiho 2/407, 162 00 Prague 6 ∥ Institut für Energie und Umweltforschung Heidelberg GmbH (IFEU), Wilckensstrasse 3, 69120 Heidelberg, Germany ‡
S Supporting Information *
ABSTRACT: This article presents the concept, calculation method, and first results of the “Raw Material Consumption” (RMC) economywide material flow indicator for the European Union (EU). The RMC measures the final domestic consumption of products in terms of raw material equivalents (RME), i.e. raw materials used in the complete production chain of consumed products. We employed the hybrid input-output life cycle assessment method to calculate RMC. We first developed a highly disaggregated environmentally extended mixed unit input output table and then applied life cycle inventory data for imported products without appropriate representation of production within the domestic economy. Lastly, we treated capital formation as intermediate consumption. Our results show that services, often considered as a solution for dematerialization, account for a significant part of EU raw material consumption, which emphasizes the need to focus on the full production chains and dematerialization of services. Comparison of the EU’s RMC with its domestic extraction shows that the EU is nearly self-sufficient in biomass and nonmetallic minerals but extremely dependent on direct and indirect imports of fossil energy carriers and metal ores. This implies an export of environmental burden related to extraction and primary processing of these materials to the rest of the world. Our results demonstrate that internalizing capital formation has significant influence on the calculated RMC. ability, material flow indicators − focused mostly on economywide level − have been compiled for a range of both developed and developing countries.8−12 As production becomes more geographically removed from consumption, the environmental pressure induced by a particular consumed product is hidden from the consumer.13 Therefore, “footprint” indicator types were developed to allocate environmental burdens from production to consumed products.14,15 In this article, we present the concept, calculation method, and first results of the “Raw Material Consumption” (RMC) of the European Union (EU) economy-wide material flow indicator for 2005. The RMC measures the final domestic consumption of products in terms of raw material equivalents (RME). The RME of a product indicates how much of a particular material is extracted through the product’s entire production chain and so can be thought of as the “material footprint” of the product. Therefore, we present for the first
1. INTRODUCTION A socioeconomic system and its natural surroundings are connected by material and energy flows. The consumption of materials from the environment is a prerequisite for the production of goods and services and for the sustainment and increase in standards of living. According to the laws of thermodynamics, all consumed materials must at some point become waste and be emitted back into the environment. Both input and output flows of material and energy which are associated with socioeconomic metabolism exert pressure on the environment. For these reasons, anthropogenic material and energy flows are considered to be a major cause of many environmental problems humans face today.1−5 These problems include landscape change, loss of biodiversity, acidification, eutrophication, and global climate change.6 Researchers have thus developed material flow analysis to measure material and energy flows and to mitigate the related problems. The aim of this approach is to monitor material and energy flows at various scales and levels of detail and to provide indicators that contribute to the management of resource use and output emission flows from both economic and environmental points of view.7 As convenient measures of sustain© 2012 American Chemical Society
Received: Revised: Accepted: Published: 8903
February 2, 2012 July 17, 2012 July 23, 2012 July 23, 2012 dx.doi.org/10.1021/es300434c | Environ. Sci. Technol. 2012, 46, 8903−8909
Environmental Science & Technology
Article
technology for individual product groups by using a higher level of disaggregation. While we apply world average technology for LCA products, we apply the domestic (EU27 average) technology assumption for all imported non-LCA products. Most of the above approaches have previously been applied by other authors in different contexts.27−35 The novelty of this article thus lies in the first calculation and presentation of the RMC indicator for the EU and the combination of known elements in a new and innovative manner in order to serve the specific purpose of estimating RME and addressing policy relevant issues. The following section explains the concept and details of the applied hybrid input-output life cycle assessment (IO-LCA) approach, specific data requirements, and the calculation setup. In section 3, we present and discuss the RMC of the EU in relation to other European economy-wide material flow accounts (EW-MFA) indicators and assess specific methodological elements which were applied in this study in order to improve the relevance and accuracy of the results. This article includes Supporting Information (SI) which consists of a detailed description of the data used in this analysis, the resulting highly disaggregated mixed unit IOT, and the detailed results.
time the material footprint of the European Union. A detailed analysis of water footprint, land footprint, and carbon footprint of the EU27 was provided by Steen-Olsen et al.,16 who used multiregional input-output analysis and focused on intra-EU trade. The approach for RMC calculation described in this article has four important advantages over current approaches: political relevance, statistical adequacy, analytical relevance, and methodological foundation. Political relevance refers to an improvement of the existing “domestic material consumption” (DMC) material flow indicator. DMC is used by the European Commission as a central policy indicator to measure material consumption of economies and the related environmental pressure.17 The statistical office of the European Union (Eurostat) plans to supplement or replace the DMC indicator by publishing the RMC indicator on a regular basis. RME improves the statistical adequacy of the DMC indicator, which is composed of raw materials extracted in a national economy (domestic extraction used, DEU), plus all physical imports (IM) minus all physical exports (EX), all being reported in mass units.18 DEU is thus measured in virgin raw material extraction, whereas the external trade flows are measured in a simple product weight. The RMC overcomes this asymmetry by expressing both imports and exports in RME. While it is a current practice to report the DMC indicator disaggregated into only five broad material categories, we present RMC in a disaggregation of 52 raw material categories for 166 individual product groups of the domestic final demand (see the Supporting Information). The high level of disaggregation is a specific feature of this approach compared to other approaches for estimating RME. This extent of disaggregation is required for linking the material flow indicator in a meaningful manner to the environmental pressures and impacts (e.g., to pressure profiles of the different raw materials) as well as to economic production and consumption activities (economic driving forces). The input-output framework has many policy relevant advantages19 and enables subsequent analysis of the results, such as structural decomposition analysis,20−22 structural path analysis,23 or the combination of both.24 The calculation setup applied in our study is specifically tailored for estimating the RMC indicator by combining a number of existing methodological approaches. These approaches are conceptually fully integrated into the system of Integrated Environmental and Economic Accounting (SEEA),25 which is designed to depict the interaction between the economy and the environment in a systematic, coherent manner. In our calculation, we first developed a highly disaggregated, environmentally extended, mixed unit inputoutput table of 166 product groups for the EU (expHIOT). In the second step, we applied life cycle inventory data to imported products without appropriate representation within the domestic economy of the EU (LCA products). In the last step, we internalized capital into intermediate consumption. This approach of a highly disaggregated IO table is presented as an alternative to multiregional input output analysis and process LCA. Multiregional input-output analysis has a more appropriate treatment of imports but significantly lower product detail, while process LCA has the shortcoming of having extensive data requirements and limited system boundaries.26 In comparison to current state of the art of multiregional input-output analysis, we apply more appropriate
2. GENERAL CONCEPT AND SPECIFIC METHODOLOGICAL ISSUES Basic Concept. In our analysis, we apply hybrid IO-LCA method for the calculation of RMC, RME of imports (RMEIM), and RME of exports (RMEEX). This approach is based on the environmentally extended input-output model (EE-IOM) described as36 e = F ·(I − A)−1 ·y
(1)
where e contains RME of the products included in vector y, F is an environmental extension matrix per unit of domestic output, I is an identity matrix, and A is a technology coefficients matrix. The basis of the environmental extension matrix for the calculation of RME is the domestic extraction data of 42 materials. These data were derived from the Statistical office of the European Commission (Eurostat) online database.37 In the first step of the development of the F matrix, the material classification was disaggregated for metals, resulting in a total of 52 material categories. The domestic extraction was allocated to the corresponding extracting sectors. Using this approach, the materials extracted by economic sectors for the production processes are allocated to final demand products. The resulting RMEs cover all upstream material requirements from the full production chains of these products. The technology coefficients matrix can be derived directly from EU inputoutput table (IOT) provided by the Eurostat.38 However, such a basic approach yields inaccurate results due to (a) the high level of product aggregation, (b) missing RME of the consumed capital goods, and (c) domestic technology assumption for all imported products.31 We thus applied the additional steps described below in order to remove or minimize these drawbacks. Disaggregation of EU Input-Output Table. The EU IOT provided by Eurostat is a monetary IOT with 60 by 60 product groups (at 2 digit level of the European product classification CPA 2002) and is designed for economic analysis. This IOT was disaggregated into 166 by 166 product groups with a high level of detail on the product groups most relevant 8904
dx.doi.org/10.1021/es300434c | Environ. Sci. Technol. 2012, 46, 8903−8909
Environmental Science & Technology
Article
consumption can be internalized, i.e. included in the intermediate consumption matrix. For earlier study on the treatment of capital goods as intermediate inputs of production processes, see Stahmer,43 which is relevant to growth models developed by von Neumann44 and Lancaster.45 The approach of internalized fixed capital consumption is based on the assumption that the capital services provided by the capital stock can also be viewed as an input into the production process. Capital services can be measured by the item “consumption of fixed capital” within the input-output table, which indicates how much of the capital stock was consumed for production during the current period according to standard accounting principles. Following that consideration, it would be desirable from an environmental perspective to assign consumption of fixed capital to the production activities in addition to the intermediate consumption of products. This incorporation of fixed capital consumption to intermediate consumption can be achieved by disaggregating the “consumption of fixed capital” row in a value added block of expHIOT according to the same classification as the intermediate consumption matrix. This procedure reveals which capital products are consumed by which branches. This matrix should be treated similarly to the import matrix. Such an approach is a simplification in the sense that it assumes the current production technology for capital that was created in the past. Since information on the disaggregation of fixed capital consumption was not available, we approximated the internalized capital consumption by internalizing GFCF. Note that in a steady state economy, a matrix of capital consumption disaggregated by the consumed capital products would be equal to a matrix of GFCF disaggregated by the purchasing sectors, since the consumed capital would be exactly replaced by the new created capital. Although GFCF is fully treated as a final demand category in the standard IOT concept of the System of National Accounts (SNA), “internalization” means that it was treated as an intermediate consumption in this study. Therefore GFCF was disaggregated by purchasing sectors using investors’ matrices which show the GFCF by product groups and industries and added to the intermediate transaction matrix. The investors’ matrices were provided by Eurostat on a special request. Regarding calculation of RME, applying this method has the effect that raw materials which were originally allocated to the final demand category GFCF by the EE-IOM are now allocated to the products of consumption expenditures and exports, augmented by RME of capital which was used in production of imported products. While we include in the RMC indicator the RME of capital which was created in the past and consumed in production processes during the analyzed accounting period, we exclude from the RMC indicator the RME of capital created during the analyzed period, since it will serve for future production and consumption. Therefore, we excluded the GFCF from the domestic final demand in RMC calculation using eq 1. Note that the name “raw material consumption” refers to raw materials which were extracted during the whole production chain of all goods consumed by a nation. GFCF is not consumed in the current year, and it is not classified as “consumption”. It is created, and it will be consumed in future production processes when it should be appropriately accounted for. We used two approximations in the capital treatment. First, we approximate the consumption of capital by GFCF, as explained above. Second, we approximate the past technology
for RME calculation. These product groups include raw material extraction (agriculture, mining, and quarrying); primary processing of raw materials (manufacturing of food products, metal products, and other mineral products); secondary energy carriers; the chemical industry; and the metal industry. The disaggregation of raw material product groups follows the breakdown of materials within the environmental extension matrix (52 materials according to the EW-MFA). The disaggregation of the EU 60 by 60 input-output table was based on total output of detailed product groups and on the detailed, internal and unpublished German supply and use tables from the Input-Output Department of the German Federal Statistical Office. The latter data were provided on special request. The monetary units in the use structures (rows) were replaced by physical nonmonetary units for raw materials, basic metals, and energy carriers, resulting in a mixed unit (hybrid) IOT. As argued by Hawkins and colleagues,39 mixed unit input-output analysis is more appropriate for tracking upstream material requirements. More details on the method can be found in Miller and Blair.40 Details on the disaggregation procedure are provided in the Supporting Information. A disaggregated IOT has two important advantages with respect to RME calculation: the accuracy of the allocation of raw materials to the final use products is improved and the analytical relevance of the RMC indicator is strengthened by establishing an “economic link” at a much more detailed level. The application of the German economic structure on the entire EU is justified by Lenzen,41 who proved that the disaggregation of input-output tables adds to the quality of the subsequent analysis, even if the data used for disaggregation is not ideal (different country and year) or even if only partial disaggregation is applied. The main objective is to reflect the major differences between the disaggregated product groups. Since the flow matrix was disaggregated, the different technology in Germany and the rest of EU27 is kept on the aggregate level. A similar approach of disaggregating product groups and sectors with a strong connection to the environment was applied within the EXIOPOL project.42 However, EXIOPOL aimed at a multiregional supply and use framework with about 129 product groups and was not yet finished at the time this study was conducted. Furthermore, the classification in EXIOPOL is less detailed for metals and metal ores; there are about 20 product groups in contrast to about 46 in our approach. The classification of metals and metal ores is important for the accuracy of RME estimation as the grades of metal ore differ substantially. Internalization of Gross Fixed Capital Formation (GFCF). Capital is treated specially, and it is not included in the intermediate consumption matrix in the economic IOTs published by national statistical offices. Capital, which is consumed, is part of the value added and therefore has no inputs of other products. This implies that the RME of consumed capital is excluded from the resulting RME of products calculated by eq 1. On the other hand, capital that is created during the accounting period is treated as the final demand category, “gross fixed capital formation” (GFCF). This capital is mainly intended to replace current capital and for future production of domestically used and exported products. In order to account for RME of products, including RME of the capital used in the production processes, the capital 8905
dx.doi.org/10.1021/es300434c | Environ. Sci. Technol. 2012, 46, 8903−8909
Environmental Science & Technology
Article
denoted by the symbol ′ in the following equations. The superscript ′ thus indicates the use of LCA inventories and the internalization of GFCF into expHIOT in our model. RMC, RMEIM, and RMEEX were calculated by replacing the vector y in eq 1 by a vector of domestic final demand reduced by GFCF (yd), imports (IM), and exports (EX), respectively
which was used to create the consumed capital by the current technology. We argue that our approximation is a good starting point for further considerations of accounting for environmental interventions related to capital products. The resulting full expHIOT is presented in the Supporting Information to this article. The expHIOT is predominantly conceived for converting product flows into RME by the described EE-IOM, but it is also suitable for other types of environmental IOA, e.g. estimating environmental pressures or energy embodied in products. Imported Products. Within a basic single region inputoutput analysis, all imported products are treated under the domestic technology assumption, i.e. imports are assumed to be produced using the same technology as the domestic products. In some cases, this assumption may not be adequate for several reasons: (a) the imported product is not produced by the domestic economy; (b) the imported product is produced under climatic, geophysical, or other conditions which are considerably different from domestic conditions; (c) the composition (structure) of the product group is significantly different for imports and domestic production; and (d) the production technology is different for other reasons (technological development, etc.). The drawbacks of the domestic technology assumption for RME calculation were emphasized by Weinzettel and colleagues.31 The domestic technology assumption can be avoided by using multiregional input-output analysis, but this approach is data intensive and current multiregional input-output data sets have low product resolution. Another approach, which was applied in several previous studies,20,27,31 is to use data from life cycle inventories and other sources for imports that do not have appropriate equivalents within the domestic economy. In our study, we follow the latter approach and apply supplementary data for selected imported products, denoted as “LCA products”, derived from LCA inventories. These “LCA products” were added to the EE-IOM as new product groups and technically treated as “domestic production”. These product groups do not have any inputs of other products, since their environmental extension encompasses all materials extracted throughout the entire production chain (derived from LCA inventories). Ecoinvent 2.0 (www.ecoinvent.ch) was chosen as the principal life cycle inventory database. We further developed a special treatment for metals and metal ores, since Ecoinvent is not reliable for RME of metal ores, which is a set of product groups that have significant influence on the results (for more details, see the SI). Life cycle inventory data were collected for 62 products which were aggregated to 37 product groups of the IOT classification. LCA products comprise crude oil, natural gas, metal ores, and all basic metals. One specific methodological aspect addressed in our study is the treatment of scrap and secondary metals, which has a considerable impact on the results. For the purpose of this study, the RME of all metal scrap and all secondary metals which consist of recycled metal was assumed to be zero. As in the external trade statistics, imports and exports of scrap metal are reported separately so they can be simply deduced. However, secondary metal is not usually reported separately. Therefore the proportion of secondary metals was estimated using the world average for each metal. For more details regarding LCA data, see the Supporting Information. Calculation of RMC, RME of Imports and Exports. The resulting environmentally extended input-output model (EEIOM), which is specifically tailored for calculating RME, is
RMC = F ′·(I − A′)−1 ·yd
RME IM = F ′·(I − A′)−1 ·IM RME EX = F ′·(I − A′)−1 ·EX
3. RESULTS AND DISCUSSION RMC and Other Central EW-MFA Indicators in RME. Figure 1 presents the central EW-MFA indicators by aggregated
Figure 1. Central EW-MFA indicators, EU27, 2005. Source for DE and DMC: Eurostat.
raw material categories for EU27, 2005. Note that in our analysis we consider the EU27 as one region and therefore we assess extra EU27 trade flows only. We do not consider intra EU27 import and export flows. Therefore, the values for imports and exports appear lower than the sum of total imports and exports of all EU27 countries. Figure 1 shows that as far as biomass, sand, gravel and other minerals are concerned, the European Union is nearly selfsufficient. It means that consumption of these material categories is mostly covered by domestic extraction. The European Union is, however, extremely dependent on direct and indirect imports for fossil-derived energy carriers and metal ores. The deficit amounts to about 50% for fossil energy carriers and to over 80% for metal ores. The total RME of imports were about double of the RME of exports, which indicates that the European Union was a net importer of embodied raw materials and a net exporter of environmental pressure related to extraction and processing of these raw materials. The difference was most pronounced for metal ores and fossil energy resources, which contributed 33% and 46%, respectively, to raw materials embodied in imported products. Figure 1 further presents results for DMC − the “traditional” EW-MFA indicator based on imports and exports in traded weight of products − and RMC indicators, for which imports and exports are expressed in RME. It is revealed that RMC is higher than the DMC by about 7%. The main difference is attributed to the material category “metal ores” and exists due to large differences between direct imports of metal ores and metal 8906
dx.doi.org/10.1021/es300434c | Environ. Sci. Technol. 2012, 46, 8903−8909
Environmental Science & Technology
Article
products and the metal ores embodied in all imported products. Therefore, it could be concluded that the DMC indicator considerably underestimates environmental pressures related to metal ores. Direct extra EU imports and exports were about 1.7 and 0.5 billion tons, respectively.37 This reveals that the role of international trade is underestimated in case the trade flows are presented in the weight of traded products instead of raw material equivalents. Figures 2-4 show the ten product groups that induce the largest RMEIM, RMEEX, and RMC in absolute volumes. The
Figure 4. RMC by product groups of final consumption expenditure, EU27, 2005.
The highest RMEEX, on the other hand, are related to manufactured goods like machinery and equipment, motor vehicles, petroleum products, etc., as well as water transport services. This mix of product groups reflects the fact that EU27 consists of developed countries, which tend to export processed goods and services related to high revenue. RMC is by far dominated by real estate services, which are directly related to construction activities and include trade of construction products. Therefore the upstream material requirements of real estate services have a high demand of sand and gravel and other minerals. Other product groups, which contribute significantly to RMC, comprise public administration and defense services, health and hotel services, food products such as meat, other food and dairy products, and commodities related to ensuring energy needs, such as electricity and petroleum products. Figure 5 shows the aggregation of detailed product groups into broader categories in order to emphasize the importance of
Figure 2. RMEIM by product groups, EU27, 2005.
Figure 3. RMEEX by product groups, EU27, 2005. “Machinery*” stands for “Machinery and equipment not elsewhere classified (n.e.c.) (excl. domestic appliances n.e.c.)”.
columns represent total (direct and upstream) material requirements from the whole production chain, broken down into material type (colors). Product groups responsible for the highest RMEIM include fossil fuels, metal ores, products from ores and some other manufactured products like radio, television, and communication devices. While the RMEIM for fossil fuels and metal ores is approximately equal to the weight of the commodities themselves, there are significant upstream flows for other product groups. Metal products, for instance, have significant upstream flows caused by the need to produce them from lowconcentration ores.
Figure 5. RMC by four broad product groups (RES stands for real estate services, other services for all services except RES), EU27, 2005.
services, which are often assumed as immaterial. Even though the largest contribution to material requirements of services is from sand and gravel, which is, per unit of mass, related to significantly lower impacts on the environment and human health than biomass, metal ores, and fossil energy resources,46 8907
dx.doi.org/10.1021/es300434c | Environ. Sci. Technol. 2012, 46, 8903−8909
Environmental Science & Technology
Article
Our results indicate that the role of services in a dematerialization process of our economies might be limited, since the upstream material requirements of services account for about one-third of the total RMC of the EU. This emphasizes the need to focus on the full production chains and dematerialization of services. Results with full details by 166 product groups and 52 raw material categories are presented in the Supporting Information for RMC, RMEIM, and RMEEX. From a methodological perspective (see the SI), our results suggest that a substantial part of material extraction caused by consumption activities is not linked to these activities if RME of the consumed capital is excluded from the analysis, as is the practice in most current input-output analyses. More effort should therefore be put into the treatment of capital in environmentally focused input-output analyses in the future. Based on the above considerations and empirical results, it can be concluded that the methodological elements introduced in this article, specifically highly disaggregated input output tables with additional LCA data for imported commodities and internalized capital, are suitable for estimating RME-based material flow indicators and other environmental pressures embodied in products.
there is a notable portion also of all other materials. Sand and gravel, and to some extent, other minerals (limestone utilized for cement production, for instance) are used to build infrastructure to operate these services, such as administrative buildings, hospitals, hotels, etc. The Role of Gross Fixed Capital Internalization. Figure 6 compares the results for RMC broken down by the main final
■
Figure 6. RMC of final consumption expenditure and gross capital formation by product groups calculated with and without internalized gross fixed capital formation, EU27, 2005.
ASSOCIATED CONTENT
S Supporting Information *
Detailed results with (also without internalized GFCF), a detail description of the methods applied, the data used in the calculation, and a comparison of the results with an approach without GFCF internalization. This material is available free of charge via the Internet at http://pubs.acs.org.
demand categories (consumption expenditure and gross capital formation - GCF) and by broad product categories. Gross capital formation is composed of GFCF and “changes in inventories and valuables”. The results were obtained using the expHIOT both with and without internalized GFCF. It is important to note that when GFCF was not internalized, it was included in the domestic final demand in the RMC calculation. According to the approach without internalized GFCF, the raw materials embodied in consumption expenditure amount to nearly 5 billion metric tons. About 56% of these raw materials is embodied in goods from agriculture and mining and manufacturing and about 44% is embodied in real estate and other services. Only a negligible part of these raw materials is embodied in construction work. Gross capital formation (GFCF plus changes in inventories and valuables) accounts for about 3.9 billion metric tons, of which 78% is embodied in construction work. In the approach with internalized GFCF, the RME of GFCF and the materials embodied in infrastructure used in production of imports are allocated to consumption expenditures and exports (the latter is not shown in the graph). The RME of consumption expenditure thus increased to about 8.9 billion tons, of which 38% is embodied in goods from agriculture, mining, and manufacturing. The remaining 62% is embodied in real estate and other services while construction work dropped to a very low level. This implies that RME of GFCF was mostly reattributed to services, which went up by about 150% from approximately 2.2 billion metric tons to 5.5 billion metric tons. The most distinct change is that of real estate services, which are directly linked to construction activities. The RME of real estate services accounts for 1.6 billion metric tons compared to 0.2 billion metric tons in the approach without internalization of GFCF. There is a minor difference (about 1%) between the total RMC with and without internalized GFCF, which is due to RME of imports and exports.
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS This work has been financed by Eurostat under the project “Conceptual framework for measuring the environmental impact of the use of Natural Resources and Products” (Contract no. 50304.2008.008-2008.717). Our work also highly benefited from cooperation with Sarka Buyny and Helmut Mayer (Department of environmental − economic accounting of the German Federal Statistical Office). The views of the authors do not need to represent the views of Eurostat.
■
REFERENCES
(1) Fischer-Kowalski, M.; Haberl, H. Metabolism and Colonization. Modes of Production and the Physical Exchange between Societies and Nature. Innovation 1993, 6 (4), 415−442. (2) Ayres, R. U.; Simonis, U. E. Industrial metabolism: Restructuring for sustainable development; Tokio: UNU Press: 1994. (3) Schmidt-Bleek, F. Wieviel Umwelt Brecht der Mensch? MIPS das Mass für ökologisches Wirtschaften [How much environment Leeds humankind? MIPSThe measure for ecological economic activities]. 1994. (4) Weizsäcker, E. U.; Lovins, A. Factor four: Doubling wealth − halving resource use; Earthscan: London, 1997. (5) van der Voet, E.; van Oers, L.; Nikolic, I. Dematerialization Not Just a Matter of Weight. J. Ind. Ecol. 2004, 8 (4), 121−137. (6) Giljum, S.; Hak, T.; Hinterberger, F.; Kovanda, J. Environmental governance in the European Union: Strategies and instruments for absolute decoupling. Int. J. Sustainable Dev. 2005, 8 (1−2), 31−46.
8908
dx.doi.org/10.1021/es300434c | Environ. Sci. Technol. 2012, 46, 8903−8909
Environmental Science & Technology
Article
(7) OECD, In Measuring material flows and resource productivity. Vol. I: The OECD guide. OECD: Paris, 2008. (8) Adriaanse, A.; World Resources Institute, Resource flows: the material basis of industrial economies; World Resources Institute: Washington, DC, 1997; p vi, 66 p. (9) Matthews, E. The weight of nations: material outflows from industrial economies; World Resources Institute: Washington, DC, 2000; p xii, 125 p. (10) Giljum, S. Trade, materials flows, and economic development in the south: The example of Chile. J. Ind. Ecol. 2004, 8 (1−2), 241−261. (11) Weisz, H.; Krausmann, F.; Amann, C.; Eisenmenger, N.; Erb, K. H.; Hubacek, K.; Fischer-Kowalski, M. The physical economy of the European Union: Cross-country comparison and determinants of material consumption. Ecol. Econ. 2006, 58 (4), 676−698. (12) Xu, M.; Zhang, T. Material flows and economic growth in developing China. J. Ind. Ecol. 2007, 11 (1), 121−140. (13) Kissinger, M.; Rees, W. E. Importing terrestrial biocapacity: The U.S. case and global implications. Land Use Policy 2010, 27 (2), 589− 599. (14) Wackernagel, M.; Rees, W. Our Ecological Footprint - Reducing Human Impact on the Earth; New Society Publishers: Gabriola Island, 1996; p 160. (15) Hertwich, E.; Peters, G. Carbon Footprint of Nations: A Global, Trade-Linked Analysis. Environ. Sci. Technol. 2009, 43 (16), 6414− 6420. (16) Steen-Olsen, K.; Weinzettel, J.; Cranston, G.; Ercin, A. E.; Hertwich, E., Carbon, Land, and Water Footprint Accounts for the European Union: Consumption, Production, and Displacements through International Trade. Environ. Sci. Technol. submitted. (17) EC, Sustainable development in the European Union − 2009 monitoring report of the EU sustainable development strategy; European Commission: Luxenbourg, 2009. (18) Eurostat, In Economy-wide material flow accounts and derived indicators. A methodological guide; Eurostat: Luxembourg, 2001. (19) Ewing, B. R.; Hawkins, T. R.; Wiedmann, T. O.; Galli, A.; Ertug Ercin, A.; Weinzettel, J.; Steen-Olsen, K. Integrating ecological and water footprint accounting in a multi-regional input−output framework. Ecol. Indic. 2012, 23 (0), 1−8. (20) Weinzettel, J.; Kovanda, J. Structural Decomposition Analysis of Raw Material Consumption. J. Ind. Ecol. 2011, 15 (6), 893−907. (21) Wood, R.; Lenzen, M.; Foran, B. A Material History of Australia. J. Ind. Ecol. 2009, 13 (6), 847−862. (22) Munoz, P.; Hubacek, K. Material implication of Chile’s economic growth: Combining material flow accounting (MFA) and structural decomposition analysis (SDA). Ecol. Econ. 2008, 65 (1), 136−144. (23) Peters, G. P.; Hertwich, E. G. The importance of imports for household environmental impacts. J. Ind. Ecol. 2006, 10 (3), 89−109. (24) Wood, R.; Lenzen, M. Structural path decomposition. Energy Econ. 2009, 31 (3), 335−341. (25) United Nations, Handbook of National Accounting: Integrated Environmental and Economic Accounting 2003. United Nations; European Commission; International Monetary Fund; Organisation for Economic Co-operation and Development; World Bank: 2003. (26) Majeau-Bettez, G.; Strømman, A. H.; Hertwich, E. G. Evaluation of process- and input-output-based life cycle inventory data with regard to truncation and aggregation issues. Environ. Sci. Technol. 2011, 45 (23), 10170−10177. (27) Joshi, S. Product Environmental Life-Cycle Assessment Using Input-Output Techniques. J. Ind. Ecol. 1999, 3 (2−3), 95−120. (28) Schoer, K. Calculation of direct and indirect material inputs by type of raw material and economic activities. In London Group Meeting 19−21 June 2006, 2006. (29) Giljum, S.; Lutz, C.; Jungnitz, A.; Bruckner, M.; Hinterberger, F. Global dimensions of European natural resource use. First results from the Global Resource Accounting Model (GRAM); Sustainable Europe Research Institute: Vienna, 2008. (30) Munoz, P.; Giljum, S.; Roca, J. The Raw Material Equivalents of International Trade. J. Ind. Ecol. 2009, 13 (6), 881−897.
(31) Weinzettel, J.; Kovanda, J. Assessing Socioeconomic Metabolism Through Hybrid Life Cycle Assessment The Case of the Czech Republic. J. Ind. Ecol. 2009, 13 (4), 607−621. (32) Hornborg, A.; McNeill, J. R.; Martínez Alier, J. Rethinking environmental history: world-system history and global environmental change; AltaMira Press: Lanham, 2007; p xi, 408 p. (33) Wiedmann, T.; Lenzen, M.; Turner, K.; Barrett, J. 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. Ecol. Econ. 2007, 61 (1), 15−26. (34) Bruckner, M.; Giljum, S.; Lutz, C.; Wiebe, K., Materials embodied in international trade - Global material extraction and consumption between 1995 and 2005. Global Environ. Change forthcoming. (35) Wiebe, C.; Bruckner, M.; Giljum, S.; Lutz, C.; Polzin, C., Carbon and materials embodied in the international trade of emerging economies: A multi-regional input-output assessment of trends between 1995 and 2005. J. Ind. Ecol. forthcoming. (36) Hertwich, E. G. Life cycle approaches to sustainable consumption: A critical review. Environ. Sci. Technol. 2005, 39 (13), 4673−4684. (37) Eurostat, Eurostat statistics database. In 2011. http://epp. eurostat.ec.europa.eu/portal/page/portal/statistics/search_database (accessed March 2011). (38) Eurostat, Eurostat statistics database. In 2011.http://epp. eurostat.ec.europa.eu/portal/page/portal/esa95_supply_use_input_ tables/data/database (accessed December 2011). (39) Hawkins, T.; Hendrickson, C.; Higgins, C.; Matthews, H.; Suh, S. A Mixed-Unit Input-Output Model for Environmental Life-Cycle Assessment and Material Flow Analysis. Environ. Sci. Technol. 2007, 41 (3), 1024−1031. (40) Miller, R. E.; Blair, P. Input output analysis; Prentice Hall: NJ, 1985. (41) Lenzen, M. Aggregation versus disaggregation in input-output analysis of the environment. Econ. Syst. Res. 2011, 23 (1), 73−89. (42) Tukker, A.; Poliakov, E.; Heijungs, R.; Hawkins, T.; Neuwahl, F.; Rueda-Cantuche, J. M.; Giljum, S.; Moll, S.; Oosterhaven, J.; Bouwmeester, M. Towards a global multi-regional environmentally extended input-output database. Ecol. Econ. 2009, 68 (7), 1928−1937. (43) Stahmer, C. The Magic Triangle of Input-Output Tables. In 13th International Conference on Input-Output Techniques; University of Macerata, Italy, 2000. (44) Von Neumann, J. A model of general economic equilibrium. Rev. Econ. Stud. 1945, 13, 1−9. (45) Lancaster, K. Mathematical economics; Macmillan: New York, 1968; p xiii, 411 p. (46) Bringezu, S.; Bleischwitz, R. Sustainable resource management: Global trends, visions and policies; Greenleaf Publishing Limited: Sheffield, 2009.
8909
dx.doi.org/10.1021/es300434c | Environ. Sci. Technol. 2012, 46, 8903−8909
