Material and Energy Dependence of Services and Its Implications for

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Environ. Sci. Technol. 2009, 43, 4241–4246

Material and Energy Dependence of Services and Its Implications for Climate Change K E I S U K E N A N S A I , * ,† S H I G E M I K A G A W A , ‡ SANGWON SUH,§ MINORU FUJII,† ROKUTA INABA,† AND SEIJI HASHIMOTO† Research Center for Material Cycles and Waste Management, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan, Faculty of Economics, Kyushu University, 6-19-1 Hakozaki, Higashi-ku, Fukuoka, 812-8581, Japan, Department of Bioproducts and Biosystems Engineering, College of Food, Agriculture and Natural Resources Sciences, University of Minnesota, 2004 Folwell Avenue, St. Paul, Minnesota 55108, and Institute of Environmental Sciences (CML), Leiden University, PO Box 9518, 2300RA Leiden, The Netherlands

Received September 11, 2008. Revised manuscript received April 15, 2009. Accepted April 22, 2009.

As the services industry has grown and diversified, there has been a rapid rise in the share of energy and material costs in provision of services. As a result, services, which have traditionally been considered immaterial by their nature, are now absorbing substantial amounts of energy and material goods. By decomposing the CO2 emissions embodied in material goods and services, this study quantitatively analyzes the implications of energy and materials consumption in services for the change in indirect CO2 emissions by household consumers in Japan. The results show that the domestic CO2 emissions associated with the energy and material goods absorbed by services through the supply chain increased consistently during the decade 1990-2000, thereby constituting a key element in the rise in CO2 emissions due to household consumption. The energy and materials within the supply chain underlying services that have been identified as the main causes of this increase include electric power consumption, petroleum products, building renovation and repair, distribution of printed materials, plastic products and water, all of which are necessary to support the services in question. This study highlights the increasing importance of energy and materials consumption by services in the context of climate change policy.

Introduction Despite efforts to mitigate anthropogenic climate change, the past decade has seen a rise in global greenhouse gas (GHG) emissions, which in 2004 reached almost 50 gigatonne CO2-equivalent/year (1). Many nations that have set their GHG emission reduction targets under Annex B of the Kyoto Protocol (2) have had to learn the intransigent nature of GHG emissions, failing to achieve their goals by 2005. Japan, for instance, had committed itself to a 6% reduction in its GHG * Corresponding author tel: +81 29-850-2889; fax: +81 29-8502917; e-mail: [email protected]. † National Institute for Environmental Studies. ‡ Kyushu University. § University of Minnesota and Leiden University. 10.1021/es8025775 CCC: $40.75

Published on Web 05/07/2009

 2009 American Chemical Society

emissions by 2008-2012 relative to the base year 1990 (2), but instead had emissions in 2005 that were 7% higher (3). In the effort to reduce GHG emissions, much attention has been paid to sectors directly generating large quantities of GHG, such as electric utilities, transportation, and cement production. However, the increase in GHG emissions is the result of complex interactions between socio-economic and technological drivers far beyond the stacks of power plants. Recognizing this complexity, various studies have analyzed GHG emissions in relation to their socio-economic and technological drivers, including population and affluence (4), consumption and lifestyle (5), and economic structural change (6). These drivers of change are often embedded in more stable, long-term socioeconomic and technological trends that are better known than others (7). One such trend is the shift toward a service-oriented economy in high-income countries (7, 8). As service industries in themselves generate relatively small quantities of pollutants including GHG per unit value added, this shift toward a serviceoriented economy has been widely recognized as an important ingredient in efforts to decouple economic growth from environmental degradation (9-12). In 1990 total Japanese household expenditure was 229,784 billion yen (expressed in 2000 FY prices and including expenditure on imports), increasing to 275,996 billion yen in 2000, with expenditure on services accounting for 70% of the total in 1990, rising to 74% in 2000 (13). In Japan service industries have grown much faster than other industries for the last few decades, and other high-income countries have shown similar trends in the course of their economic growth (7). Although the direct GHG emissions of service industries are relatively small compared with those of other industries, substantial GHG emissions are generated indirectly to support these industries (8, 14, 15). In Japan household expenditure on services induces 14% of total domestic CO2 emissions in 2000, exceeding the 11% induced by household expenditure on electricity and public transportation combined (16). Despite the significance of service industries in highincome countries, the role of these industries in GHG emissions and their mitigation have remained largely unexplored. In particular, the pattern of development of energy and materials consumption by service industries needs to be more closely scrutinized in light of efforts to manage GHG emissions by household consumption. The aim of this study is to gain an understanding of structural trends in materials and energy metabolism in service industries and the implications of these trends for GHG emissions. To gain insights into the complex supply chain of an economy we used Structural Decomposition Analysis (SDA). Our analysis is based on data for Japan for the period 1990-2000 and focuses on CO2 emissions accounting for approximately 93% of GHG emissions in terms of Global Warming Potential (GWP) equivalent in 2000 (17), although the general methodology presented here can be applied to other countries, too.

Method and Data Decomposition of CO2 Emissions Induced by Household Consumption. Researchers have used a variety of decomposition methods to unravel the complex factors underlying CO2 and other emissions (4-7, 18-21). In its simplest form the I ) PAT equation, for instance, decomposes an impact (I) into population (P), affluence (A), and technology (T) (19, 22). Using decomposition techniques like these, the principal drivers behind complex phenomena can be isolated and their roles in the overall system can be better understood. The CO2 emissions associated with household consumption can be broken down into direct and indirect emissions. VOL. 43, NO. 12, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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Applying standard input-output techniques (23-25), in this study the indirect emissions, e1, are formulated as eq 1: ˆ )A)-1(I - m ˆ )f ) dLdfd e1 ) d(I - (I - m

(1)

Here, vector f ) [fi] is a column vector of household consumption having as its element household consumption expenditure fi on commodity i, and vector d ) [dj] is a row vector of unit CO2 emissions at the time of production having as its element the CO2 emissions dj generated directly by the production activities required for a unit of commodity j. A ) [aij] is an input coefficient matrix indicating the input of commodity i required for unit production of commodity j, and m ˆ ) [mi] is an import matrix having as its diagonal element the ratio of import to total domestic demand mi for ˆ )A)-1 commodity i. I is the identity matrix, Ld ) (I - (I - m is the so-called domestic Leontief inverse matrix and fd )(I -m ˆ )f is the domestic household consumption vector. Ld and fd allow us to calculate only Japan’s domestic CO2 emissions, without the CO2 emissions associated with imports. The “ˆ ” sign indicates a diagonal value. Furthermore, by analyzing the structure of dLdfd, the total indirect domestic emissions can be divided into a number of industry segments within the domestic production system defined by Ld. Focusing on the relationship between material goods and services in the production system, this study distinguishes four segments in the production system, viz.: (i) material goods (including energy) absorbed by material goods, (ii) material goods absorbed by services, (iii) services absorbed by material goods, and (iv) services absorbed by services. Then, by originally applying input-output partitioning techniques (see Miyazawa (26) for the seminal contribution; Sonis et al. (27, 28) for its application to regional studies; Fritz et al. (29) for its application to environmental studies) and Dietzenbacher’s full structural decomposition (30, 31) techniques, the indirect domestic CO2 emissions associated with household consumption can be additively decomposed into dfd for the on-site emissions of the industries concerned and p j kl for supply chain emissions, as expressed in eq 2, in which k, l ) 1 are the group of commodities for material goods and k, l ) 2 are the group for services. j 22 + p j 21 + p j 12 + p j 11 + dfd e1 ) p

(2)

Thus, p j 11 stands for the CO2 emissions due to the supply chain segment consisting of inputs of material goods for producing material goods, p j 12 stands for the emissions due to the segment consisting of inputs of material goods for producing services, p j 21 stands for the emissions due to the segment consisting of inputs of services for producing material goods, and p j 22 stands for the emissions due to the segment consisting of inputs of services for producing services. Alternatively, the indirect domestic CO2 emission can be multiplicatively decomposed into dfd for the on-site emissions of the industries concerned and the structural decomposition multiplier q j kl for supply chain emissions as shown in eq 3. e1 ) q j 22q j 21q j 12q j 11dfd

(3)

In this case, the effect of each of the four supply chain segments on CO2 emission is expressed as a multiplier, which represents the magnitude of amplification effect in CO2 emission due to the particular supply chain segment. For instance, q j 12 ) 1.2 means that 20% of CO2 emission is added by going through the supply chain segment that represents absorption of material goods by services. Here such amplification effect (%) is referred to as the multiplicative effect j kl. Needless to say, q j kl ) 1, means of the CO2 emission of q that no CO2 emission (0%) is added by the particular supply chain segment. Due to the way it is formulated, total supply chain CO2 emission values are highly sensitive to the 4242

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structural decomposition multipliers. Changes in second decimal digit of a structural multiplier, for example, may represent several million tons of CO2 emission. To identify key material goods, in this study e1 was broken down as shown in eq 4, in a parallel fashion to eq 2, and the volume emission p j i,12 due to the input of individual material denotes the emissions goods (i) to services was calculated. p j (i) kl associated with the segment consisting of inputs of k for producing l, excluding the emissions due to input of material (i) generated by household goods (i). The CO2 emissions jr12 consumption in the observed supply chain were then quantified using eq 5 to identify the main material goods (i) . with a large value of jr12 (i) (i) (i) (i) j i,12 + p j 22 +p j 21 +p j 12 +p j 11 + dfd e1 ) p

(4)

(i) (i) jr12 )p j 12 - p j 12

(5)

(i) j kl, p j i,12, and p j kl ) is Detailed derivation of the variables (p j kl, q provided in the Supporting Information (SI). Data Compilation for an Empirical Analysis. To model the entire Japanese production system this study considered 395 commodities. The characteristics of these commodities were identified, as shown in Table S1 of the SI, with 291 commodities being categorized as material goods and 104 as nonmaterial goods (services in a broad sense). Utilityrelated commodities such as electric power, gas, steam, water supply, and sewage disposal were included as material goods. The input-output structure among commodities, describing the production system, was determined using the Japan 1990-1995-2000 linked Input-Output Tables (13). This table is presently the most recent linked input-output table available with a detailed sector resolution. The intersectoral transaction values in the tables were expressed in real terms by adjusting inflation and deflation among the terms. To calculate the vector d in eq 1 we used the result of a previous study (6, 16, 32). Here, we provide only a brief description of the method used to estimate emissions. First, we considered 20 fossil fuels, two types of waste, and limestone as being materials leading to CO2 emissions. Emissions from land-use change are not considered in this study, as Land Use and Land Cover Change (LULCC) associated with forestland, which is the largest sources of GHG emission from LULCC, has been relatively small during the period considered (33). Second, we allocated the annual inputs of the above fuels and materials to a sector j. Third, in order to calculate the net consumption of the fuels and materials which actually generate CO2, the amount of fuels converted into other energy resources or petrochemical feedstocks was deducted from the inputs. By multiplying the respective net consumption of fuels and materials by their CO2 emission factors we then determined the annual CO2 emissions from the fuels and materials respectively. Finally, dividing the sum of these annual emissions by the total output of the sector j allowed us to obtain the unit direct CO2 emissions of the sector.

Results and Discussion Historical Change in Material and Energy Costs in Services. Analyzing the materials and energy content of services between 1990 and 2000 using Japanese linked Input-Output Tables (13), we investigated the materials and energy costs in a unit price of a tertiary product on a real-price basis. Figures S1a-d in the SI show the percentage share of primaryproduct, secondary-product, and utility costs in each tertiary product (the 104 commodities defined as services above) and the historical trend between 1990 and 2000. On average this share was 10.6% in 1990, but by 1995 it was 11.3%, and by 2000 it was 11.6%. Over this period there was thus a steady rise in the material and energy costs embodied in a tertiary

FIGURE 2. Change in the contribution of the four segments’ supply chain to the CO2 emissions generated in the domestic production system associated with Japanese household consumption. p¯kl represents the emissions attributable to the supply chain segment consisting of inputs of commodities from group k to group l (k, l ) 1 are the group of commodities for material goods, k, l ) 2 are the group for services).

FIGURE 1. Frequency distribution of the amount of change in the percentage share of primary-product (P), secondary-product (S), and utility (U) costs in the price of a tertiary product: (a) change between 1990 and 1995, (b) change between 1990 and 2000. The labels on the x-axis denote the minimum value of each interval. product. In other words, over time Japanese service industries have become more dependent on materials and energy inputs. As a whole, the service sectors required on average 9.4% more inputs from the primary, secondary, and utility sectors in 2000 than in 1990 on a real-price basis. Considering the change in the share of these inputs for individual products, it shows that in 1995 (Figure 1a) 70 out of 104 tertiary products required at least 20% more nonservice inputs per unit price than in 1990, while in 2000 (Figure 1b) 73 out of 104 tertiary products required at least 20% more nonservice inputs than in 1995, with highest frequency at 30-40% increase. In 2000 the number of tertiary products with over 80% increase in nonservice input also increased. Additive Decomposition of the CO2 Emissions. Figure 2 shows 1990, 1995, and 2000 annual domestic CO2 emissions throughout the supply chains associated with Japanese household consumption (Mt/y), broken down into four j 12, p j 21, and p j 22; see Method and Data section). segments (p j 11, p The CO2 emissions contributed by way of the material goods (including energy) absorbed by services, p j 12, rose from 68 Mt in 1990 to 79 Mt in 1995 to 87 Mt in 2000. These amounts represent 31-36% of the total supply chain emissions due to household consumption. In contrast, the CO2 emissions due to the material goods absorbed by material goods themselves, p j 11, increased from 110 to 114 Mt between 1990 and 1995, but subsequently declined to 106 Mt in 2000. Although there has been a steady rise in the total supply chain emissions induced by household consumption, the emissions from the various supply chains did not all simply mirror this trend, instead suggesting different pattern of changes in each segment, as witnessed j 12. Thus, in the supply by the decrease in p j 11 and increase in p chains for the production of material goods there does appear to have been some success in mitigating the CO2 emissions associated with consumption of raw materials and energy. When it comes to the production of services, however, the growing materials and energy dependence of this sector has

FIGURE 3. Change in the structural decomposition multiplier q¯kl and its multiplicative effect of CO2 emission [% indicated at the top of the bar graph] of the four segments’ supply chain in the domestic production system associated with Japanese household consumption. q¯kl represents the structural decomposition multiplier of the segment consisting of inputs of commodities from group k to group l (k, l ) 1 are the group of commodities for material goods, k, l ) 2 are the group for services). led to higher supply chain emissions, which now account for a significant share of the total CO2 emissions associated with household consumption. Multiplicative Decomposition of the CO2 Emission. Figure 3 shows the results of the structural decomposition j 12, q j 21, and q j 22 and their multiplicative effects multipliers q j 11, q of the CO2 emission [% indicated at the top of the bar graph] (see Method and Data section) of the four segments of the supply chain. In contrast to p j kl, this indicator is independent of the total expenditure of households and thus allows the structure of supply chain CO2 emission by each segment to be compared from year to year. Observing the historical data, although the CO2 emissions due to the material goods absorbed by material goods rose in 1995, as noted in the previous section, the multiplicative effect of the CO2 emission by the segment of material goods absorbed by material goods consistently decreased, from 51% (q j 11 ) 1.51) in 1990 to 40% (1.40) in 2000. This implies a steady reduction in the carbon emissions arising in the production of material goods alone. However, between 1990 and 2000 the change in multiplicative effect of the CO2 emission by the segment of material goods absorbed by services gradually increased by approximately from 28% (q j 12 ) 1.28) to 31% (1.31). This change is relatively VOL. 43, NO. 12, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Top 20 Material Goods Contributing in 2000 to the CO2 Emissions Due to the Supply-Chain Segment Consisting of Inputs of Material Goods to Services, and Change in Contribution between 1990 and 2000 rank

commodity number

commodity (material goods) name

(i) r¯12 : 2000 y [Mt-CO2/y]

(i) ∆r¯12 : 2000 y/ 1990 y [-]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

291 283 138 105 297 292 253 129 141 394 25 104 5 142 96 295 64 106 294 94

electric power for commercial use building renovation and repair petroleum refinery products (incl. greases) printing, plate making and book binding sewage disposal on-site power generation motor vehicle parts and accessories pharmaceuticals plastic products office supplies marine fisheries newspapers vegetables tires and inner tubes paper water supply beer publishing steam and hot water supply metallic furniture and fixtures

49 5.7 4.7 2.2 1.9 1.8 1.4 1.1 0.91 0.89 0.81 0.75 0.60 0.60 0.55 0.51 0.48 0.43 0.39 0.38

1.27 1.33 1.37 1.29 1.61 2.25 1.28 2.12 1.15 0.943 1.31 1.26 2.04 1.88 1.44 0.849 1.19 1.18 4.36 2.03

significant representing over 10% increase in structural multiplier effect by this particular segment, and such trend suggests that materials consumption by services is gradually becoming more important in overall CO2 emissions throughout the supply chain. Furthermore, the multiplicative effect j 12 in 2000 is thus gradually of the CO2 emission of 31% for q approaching the effect of 40% for q j 11. This implies that, in the future, the consumption of materials and energy to provide services may become equivalent to or more important than that involved in the production of material goods in terms of associated CO2 emissions. Identification of Key Material Goods Absorbed by Services. The results for the year 2000 are presented in Table 1, which lists the top 20 inputs of material goods to services (see Method and that generate substantial CO2 emissions, jr(i) 12 Data section). The numerical values in the right-hand column, (i) , indicate the rates of increase of the emissions in each ∆rj12 commodity between 1990 and 2000. The commodity generating the largest emissions in absolute terms was, as commonly perceived, “no. 291: electric power for commercial use”, accounting for approximately 49 Mt/y and increasing by 27% during the period in question. These data reveal that while electric power consumption by individual service providers is not as great as that by the manufacturing industry, the climate change impact of the former can still be significant. This also underscores the importance of energy conservation efforts at individual business establishments. The second largest emitter identified was “no. 283: building renovation and repair”, accounting for approximately 5.7 Mt/y and increasing at a rate of 33%, followed by “no. 138: petroleum refinery products”, with approximately 4.7 Mt/y and a rate of increase of 37%. These commodities show high rates of increase, despite volume emissions substantially lower than those from power consumption. The emissions generated through building renovation and repair ultimately prove greater than those from consumption of material goods like paper, water, and plastics used in the normal course of business operations. Although building renovation and repair will generally be accompanied by lower emissions than the construction of new buildings would entail, any situation in which service outlets have a short business life-cycle, with frequent renovation of premises, can give rise to significant CO2 emissions. The share of the commodity “no. 138: petroleum refinery products” refers to the emissions caused by the production of gasoline, diesel fuel, and natural gas. This implies that a substantial 4244

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fraction of total life-cycle CO2 emissions occurs during the precombustion phase (refining, etc.) and reducing fossil fuel consumption in services would therefore reduce not only the direct emissions due to combustion but also those associated with upstream, precombustion activities. The commodity “no. 105: printing, plate making and book binding”, representing the production of instruction manuals, brochures, and other printed materials, contributed approximately 2.2 Mt/y, which is relatively high, considering that biomass for pulp and paper production was considered carbon-neutral in this study. This figure represents an increase of 29% since 1990. The commodity fifteenth from the top, “no. 96: paper,” which includes wrapping paper, emitting approximately 0.55 Mt/y, and the eighteenth commodity, “no. 106: publishing,” emitting 0.43 Mt/y, suggest that the overall use of paper by services contributes approximately 3.2 Mt/y of CO2 emissions. As a nonenergy input to services, the contribution of paper and allied products to the total life-cycle CO2 emissions embodied in services is identified as being rather substantial, and reducing the use of paper and printed materials by services is therefore to be deemed an effective means of reducing the CO2 emissions associated with this industry. The commodity ranking fifth was “no. 297: sewage disposal”, with an emission of 1.9 Mt/y. This represents a 61% increase since 1990, mirroring the rapid expansion of public sewerage systems in Japan during this period. Adding emissions of approximately 0.51 Mt/y from the sixteenth commodity, “no. 295: water supply,” the consumption of water generates aggregate emissions of 2.41 Mt/y. As the CO2 emissions associated with water supply and treatment derive largely from on-site use of electricity for pumps and blowers, reducing water consumption, and thus the amount of wastewater produced, through water conservation would be an effective strategy for not only protecting the freshwater environment but also reducing GHG emissions. Furthermore, “no. 141: plastic products”, including the plastic containers and bags and sundries that are now being actively reduced by some supermarkets, was ranked ninth, with emissions of 0.91 Mt/y. This figure represents a 15% increase over 1990, implying that the effect of these reduction efforts was not yet observable in 2000. Emissions by the commodity “no. 394: office supplies,” which includes copy paper, forms, and writing instruments, was 0.89 Mt/y, sufficiently high to be ranked in the top ten; this is still 6% lower than the figure for 1990, however, making it the only

top-ten commodity to show a decrease. This result suggests that active promotion of green procurement and other continuous activities by service industries, along with efforts to gain consumer understanding for measures like the phasing out of throwaway plastic products, will lead to effective emissions reduction. Importance of Services in Climate Change Policy. The results of this study have explained quantitatively that, in Japan, the provision of services has become increasingly dependent on material goods and energy, contributing to a rise in the supply chain CO2 emissions associated with household consumption. This significant trend may become a critical impediment to future efforts to reduce CO2 emissions in Japan. The trend may not be restricted to Japan, moreover, but might be observed in other industrialized countries as well. Furthermore, the emissions associated with services are often indirect, via the supply chain, making them more difficult to detect and manage using simple measures. It is also notable that there is a cognitive dissonance between the consumption of services and the resultant impact on climate change, making it difficult to expect change in consumer behavior using climate change as an argument. The interindustry network sitting between the final provision of services and the end of the stack is sufficiently complex to obscure consumer perceptions of the linkage between consumption and climate change. If demand for services continues to rise while the trend toward growing material and energy dependence of services at the same time persists, there is therefore concern that the coming years may see a rapid increase in the domestic CO2 emissions associated with Japanese household consumption. The awareness of service providers of their indirect impact on climate change is also an issue that needs to be addressed. Services in Japan are often delivered by small to mediumsized business establishments, and material and energy consumption at such small establishments might appear negligible. When these are added up, though, the Japanese services sector proves to absorb substantial quantities of material goods and energy. Efforts to reduce the volume of materials and energy consumed by services will thus have a key role to play in managing future CO2 emissions due to household consumption. Another finding is the importance of building infrastructure and material goods in the supply chain emissions of services. The principal drivers of rising CO2 emissions by services have been identified as electricity consumption and building renovation and repair, along with the use of petroleum products, printed materials, water, plastic products, and office supplies in providing the services. In other words, it is not only energy conservation that is essential for reducing the CO2 emissions associated with household consumption, but also a reduction of the material goods consumed by services and efficient use of building infrastructure by the businesses concerned. Assuming continued growth in demand for services in the future, it will become increasingly important for service providers to reduce their inputs of material goods, while still producing economic benefits. Service industries need to take the initiative of adopting new business models and management strategies that can reduce the amount of material goods and energy employed in adding value to the services they provide. This study indicates that climate change policies would do well to focus more on how materials and energy are metabolized in an economy. Environmental impacts, including climate change, occur as a result of complex interactions among numerous agents, and policies aiming at mitigating environmental impacts need to take due account of this complexity. In the effort to mitigate the impacts of climate change, much attention has been paid to industries directly generating substantial emissions, such as electric

utilities, transportation, and cement production. While these industries are certainly important GHG sources, they are symptoms of the problem rather than causes. We believe it is important to understand the intricate web of linkages behind these sources that ultimately induce them to generate these emissions. Current national and international climate change policies such as cap-and-trade schemes and the Clean Development Mechanism (CDM) are concerned almost exclusively with direct emissions, with life-cycle aspects of GHG emissions largely ignored (34). Climate change policies would be further invigorated if life-cycle perspectives were suitably incorporated. In this context we welcome the new methodologies for CDM that are based on Life Cycle Assessment (LCA) studies (35, 36). Among the life-cycle-based tools to be further explored are carbon labeling and so-called carbon footprint analysis. The usefulness of these tools depends very much on methodological competence in efficiently and accurately quantifying supply chain GHG emissions. The carbon footprint of a product represents the total life-cycle GHG emissions associated with that product, and it should be calculated, in principle, taking all direct and indirect emissions into account. It is notable, however, that some of the existing carbon footprinting guidelines and reference databases recommended for use in completeness evaluation by such guidelines are drawn solely from process analysis, with services relatively weakly represented (37). To date, the most comprehensive coverage of services can be found in certain input-output LCA databases, although the Publicly Available Specification (PAS) of the United Kingdom on carbon footprinting (37) does not allow use of input-output databases for carbon footprint calculation. We believe it is important to recognize that process analysis and input-output analysis each have their own strengths and weaknesses and that their respective strengths can be combined by adopting a hybrid approach (38, 39). Such findings need to be reflected in the international carbon footprinting standards currently being developed under the leadership of the World Resources Institute (WRI), World Business Council for Sustainable Development (WBCSD), and International Organization for Standardization (ISO). Furthermore, given the material and energy consumption of the Japanese services sector, extending carbon labeling to include service industries would also be desirable. Future Technical Work. In this study we focused solely on domestic Japanese CO2 emissions, reflecting the country’s GHG reduction target under the Kyoto Protocol. While we believe the current study contributes to a better understanding of the structure of the domestic CO2 emissions induced by Japanese household consumption, we also recognize that today’s supply chains know no national borders. What is needed, therefore, is an understanding of structural trends in materials and energy metabolism in service industries from a global perspective. As shown in Figures S2 and S3, the emissions embedded in imports can be included in calculations by substituting e1 ) d(I - A)-1f ) dLf for eq 1, under the assumption that domestic and imported products are equivalent in terms of the technology used to produce them. Given Japan’s import share of about 4.4-5.7% of total output during 1990-2000, we believe that including imports in the analysis does not change the overall findings. Even then, however, using such calculations to provide a realistic quantitative estimate of the global impact of the supply chain is by no means straightforward. Although one way of estimating this impact would be to use environmentally extended international input-output tables (40), those currently available vary substantially in data quality and sectoral resolution. An internationally coordinated effort to develop highquality international input-output tables is highly desirable. Second, it should be noted that the input-output model formulated in eq 1 does not endogenously treat capital VOL. 43, NO. 12, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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investments, owing to our focus on the production technologies of material goods and services. However, the formation of capital goods often requires large inputs of materials and services. As the establishment of some service industries is accompanied by new office and shop construction, above and beyond the relationship between material goods and capital goods, the relation between services and capital goods could also be important. As Lenzen (41) and Lenzen and Treloar (42) have demonstrated, capital goods are often significant sources of environmental impacts within a product life-cycle. In this context use can be made in the future of the input-output model with inclusion of the capital formation sectors that we employed in a previous study (43).

Acknowledgments We appreciate the three anonymous reviewers for their helpful comments. We are grateful to Mr. Harle for his review and comments on an earlier version of the manuscript.

Supporting Information Available Because of space constraints, certain information has been omitted here: detailed formulations of the proposed SDA, the explanation of its difference from directly additive decomposition of the Leontief inverse matrix (15), a table of the commodity categories defined in this study as material goods versus services, and several supporting figures. This material is available free of charge via the Internet at http:// pubs.acs.org.

Literature Cited (1) Intergovernmental Panel on Climate Change (IPCC). Climate Change 2007; Fourth Assessment, Synthesis Report; Geneva, 2007. (2) United Nations. Kyoto Protocol to the United Nations Framework Convention on Climate Change; United Nations: Geneva, 1998. (3) UNFCCC. Greenhouse Gas Inventory Data - Detailed data by Party;available at http://www.unfccc.int. (4) Dietz, T.; Rosa, E. A. Effects of population and affluence on CO2 emissions. Proc. Natl. Acad. Sci. USA 1997, 94, 175–179. (5) Bin, S.; Dowlatabadi, H. Consumer lifestyle approach to US energy use and the related CO2 emissions. Energy Policy 2005, 33, 197–208. (6) Nansai, K.; Kagawa, S.; Suh, S.; Inaba, R.; Moriguchi, Y. Simple indicator to identify the environmental soundness of growth of consumption and technology: “Eco-velocity of Consumption”. Environ. Sci. Technol. 2007, 41 (4), 1465–1472. (7) Kates, R. W.; Parris, T. M. Science and technology for sustainable development special feature: long-term trends and a sustainability transition. Proc. Natl. Acad. Sci. USA 2003, 100, 8062– 8067. (8) Suh, S. Are services better for climate change? Environ. Sci. Technol. 2006, 40 (21), 6555–6560. (9) Panayotou, T. Economic Growth and the Environment; United Nations Economic Commission for Europe: Geneva, 2003. (10) Bernardini, O.; Galli, R. Dematerialization: long-term trends in the intensity of use of materials and energy. Futures 1993, 25, 431–448. (11) Ja¨nicke, M.; Binder, M.; Monch, H. ‘Dirty industries’: patterns of change in industrial countries. Environ. Resour. Econ. 1997, 9, 467–491. (12) Pacala, S.; Socolow, R. Stabilization wedges: solving the climate problem for the next 50 years with current technologies. Science 2004, 305, 968–972. (13) Ministry of Internal Affairs and Communications Japan. 19901995-2000 Linked Input-Output Tables; National Federation of Statistical Associations: Tokyo, 2005. (14) Rosenblum, J.; Horvath, A.; Hendrickson, C. Environmental implications of service industries. Environ. Sci. Technol. 2000, 34 (22), 4669–4676. (15) Alca´ntara, V.; Padilla, E. Input-output subsystems and pollution: an application to the service sector and CO2 emissions in Spain. Ecol. Econ. 2009, 68 (3), 905–914. (16) Nansai, K. Environmental Input-Output Database Building in Japan. In Suh, S., Ed.; Handbook of Input-Output Economics for Industrial Ecology; Springer, 2009.

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(17) Greenhouse Gas Inventory Office of Japan. National Greenhouse Gas Inventory Report of Japan; CGER-Report (CGERI068-2006); Center for Global Environmental Research, National Institute for Environmental Studies: Tsukuba, Japan, 2006. (18) Baumert, K. A.; Herzog, T.; Pershing, J. Navigating the Numbers: Greenhouse Gas Data and International Climate Policy; World Resources Institute: Washington, DC, 2005. (19) Waggoner, P. E.; Ausubel, J. H. A framework for sustainability science: a renovated IPAT identity. Proc. Natl. Acad. Sci. USA 2002, 99, 7860–7865. (20) Canadell, J. G.; Que´re´, C. L.; Raupach, M. R.; Field, C. B.; Buitenhuis, E. T.; Ciais, P.; Conway, T. J.; Gillett, N. P.; Houghton, R. A.; Marland, G. Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc. Natl. Acad. Sci. USA 2007, 104, 18866–18870. (21) Casler, S.; Rose, A. Carbon dioxide emissions in the U.S. economy: a structural decomposition analysis. Environ. Resour. Econ. 1998, 11 (3), 349–363. (22) Ehrlich, P. R.; Holdren, J. P. One dimensional ecology. Bull. At. Sci. 1972, 25 (5), 16–27. (23) Leontief, W.; Duchin, F.; Szyld, D. B. New approaches in economic analysis. Science 1985, 26, 419–422. (24) Carter, A. P. Applications of input-output analysis to energy problems. Science 1974, 19, 325–330. (25) Costanza, R. Embodied energy and economic valuation. Science 1980, 210, 1219–1224. (26) Miyazawa, K. Internal and external matrix multipliers in the input-output model. Hitotsubashi J. Econ. 1966, (June), 38–55. (27) Sonis, M.; Oosterhaven, J.; Hewings, G. J. D. Spatial economic structure and structural changes in the EC: feedback loop input-output analysis. Econ. Syst. Res. 1993, 5 (2), 173–184. (28) Sonis, M.; Hewings, G. J. D.; Guo, J.; Edison, H. Interpreting spatial economic structure: feedback loops in the Indonesian inter-regional economy. Regional Sci. Urban Econ. 1997, 27, 325–342. (29) Fritz, O. M.; Sonis, M.; Hewings, G. J. D. A Miyazawa analysis of interactions between polluting and non-polluting sectors. Struct. Change Econ. Dynamics 1998, 9 (3), 289–305. (30) Dietzenbacher, E.; Los, B. Structural decomposition techniques: sense and sensitivity. Econ. Syst. Res. 1998, 10 (4), 307–323. (31) Dietzenbacher, E.; Hoen, A. R.; Los, B. Labor productivity in Western Europe 1975-1985: An intercountry, interindustry analysis. J. Regional Sci. 2000, 40 (3), 425–452. (32) Nansai, K.; Moriguchi, Y.; Tohno, S. Compilation and application of Japanese inventories for energy consumption and air pollutant emissions using input-output tables. Environ. Sci. Technol. 2003, 37 (9), 2005–2015. (33) Ministry of Land, Infrastructure, Transport and Tourism (MLIT). Land and Real Properties in Japan; Tokyo, Japan, 2007. (34) Promotion of the Business Support Plan for Clean Development Mechanisms (CDM), Joint Implementation (JI), and Emissions Trading (ET) Scheme (Fiscal Year 2003 Policy); Ministry of Environment, Japanese government: Tokyo, Japan. (35) UNFCCC. Clean Development Mechanism Project Design Document Form (CDM-SSC-PDD); 2006;available at http://cdm.unfccc.int/UserManagement/FileStorage/ GTQ3Z7CWIP15YUMFL4DBH8AJVE6ROK. (36) US EPA. Solid Waste Management and Greenhouse Gases - A life Cycle Assessment of Emissions and Sinks, 3rd ed.; Washington, DC, 2006. (37) BSI. PAS 2050 - Assessing the Life Cycle Greenhouse Gas Emissions of Goods and Services; BSI Publications, 2009. (38) Suh, S.; Lenzen, M.; Treloar, G. J.; Hondo, H.; Horvath, A.; Huppes, G.; Jolliet, O.; Klann, U.; Krewitt, W.; Moriguchi, Y.; Munksgaard, J.; Norris, G. System boundary selection in lifecycle inventories. Environ. Sci. Technol. 2004, 38 (3), 657–664. (39) Suh, S.; Huppes, G. Methods for life cycle inventory of a product. J. Cleaner Prod. 2005, 13, 687–697. (40) 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 in trade. Ecol. Econ. 2007, 61, 15–26. (41) Lenzen, M. A generalized input-output multiplier for Australia. Econ. Syst. Res. 2001, 13 (1), 65–92. (42) Lenzen, M.; Treloar, G. J. Endogenising capital: a comparison of two methods. J. Appl. Input-Output Anal. 2004, 10, 1–11. (43) Nansai, K.; Inaba, R.; Kagawa, S.; Moriguchi, Y. Identifying common features among household consumption patterns optimized to minimize specific environmental burdens. J. Cleaner Prod. 2008, 16 (4), 538–548.

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