Environ. Sci. Technol. 2007, 41, 1465-1472
Simple Indicator To Identify the Environmental Soundness of Growth of Consumption and Technology: “Eco-velocity of Consumption” 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 , ‡ S A N G W O N S U H , §,⊥ R O K U T A I N A B A , † A N D YUICHI MORIGUCHI† 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, and Department of Bioproducts and Biosystems Engineering, College of Food, Agriculture and Natural Resources Sciences, University of Minnesota, 2004 Folwell Avenue, St. Paul, MN 55108, and Institute of Environmental Sciences (CML), Leiden University, P.O. Box 9518, 2300RA Leiden, The Netherlands
Today’s material welfare has been achieved at the expense of consumption of finite resources and generation of environmental burdens. Over the past few decades the volume of global consumption has grown dramatically, while at the same time technological advances have enabled products with greater efficiencies. These two directions of change, consumption growth and technological advance, are the foci of the present paper. Using quantitative measures for these two factors, we define a new indicator, “eco-velocity of consumption”, analogous to velocity in physics. The indicator not only identifies the environmental soundness of consumption growth and technological advance but also indicates whether and to what extent our society is shifting toward sustainable consumption. This study demonstrates the practicability of the indicator through a case study in which we calculate the eco-velocities of Japanese household consumption in 2 years: 1995 and 2000. The rate of technological advance during the periods concerned is quantified in terms of the embodied carbon dioxide emission per yen of product. The results show that the current growth rate of Japanese household consumption is greater than the rate of technological advance to mitigate carbon dioxide emissions. The eco-velocities at the level of individual commodity groups are also examined, and the sources of changes in ecovelocity for each commodity are identified using structural decomposition analysis.
1. Introduction As household consumption has grown, so too have global resource consumption and environmental burdens. The implications of rising consumption have been a topic of * Corresponding author phone: +81 29-850-2889; fax: +81 29850-2917; e-mail:
[email protected]. † National Institute for Environmental Studies. ‡ Kyushu University. § University of Minnesota. ⊥ Leiden University. 10.1021/es0615876 CCC: $37.00 Published on Web 01/19/2007
2007 American Chemical Society
discussion for many decades (e.g., refs 1-4). After the oil shocks of the 1970s, energy analysis quantitatively elucidated the relationship between energy requirements and consumption (e.g., refs 5-8). In the 1990s with the growing concern about global warming, many studies analyzed the linkage between consumption, particularly household consumption, and CO2 emissions and other environmental burdens (e.g., refs 9-13). In recent years there has been growing emphasis on the concept of sustainable consumption, owing in part to the reconfirmation of the need to promote a shift toward sustainable patterns of both consumption and production at the World Summit for Sustainable Development (WSSD) held in Johannesburg in 2002 (14). Against this background, not only has there since been a surge in the number of studies analyzing the environmental impacts of household consumption (15) but also the quality of the data and the methodologies employed have improved (16). Very useful for a basic understanding of the connection between consumption and environmental impact is the I ) PAT equation, developed by Ehrlich and Holdren (17) in the early 1970s. This equation implies that to stabilize or reduce environmental impact (I) as population (P) and affluence (A) increase, technology (T) needs to be dematerialized (18). As P×A is conceptually equivalent to consumption, it would seem important to focus on the relationship between consumption and technology. In examining the environmental implications of consumption, especially, we believe the interplay between the growth of consumption volume and the level of technology needs further scrutiny. Over the past few decades we have seen two competing trends. On the one hand, the volume of consumption has grown dramatically on a global scale, while on the other technological advances have permitted products with greater efficiencies. These two directions of change, consumption growth and technology advance, are the foci of the present paper. This study proposes a new environmental indicator for consumption that focuses particularly on the relationship between consumption growth and technological advance. We first define the respective “velocities” of growth and advance, based on an analogy with the notion of velocity in physics, and then formulate an indicator identifying the environmental soundness of consumption growth. We then demonstrate the practicability of this indicator by means of a case study in which we calculate its actual value for Japanese household consumption in terms of CO2 emissions. Next, using the indicator’s value, we characterize current Japanese household consumption. In conclusion, we mention two implications of the results and examine prospects for further application of the indicator to other countries and other dimensions of consumption analysis.
2. Methods and Data 2.1. Definition of an “Eco-velocity” Indicator. The prime concern of this study is to examine the soundness of the rates of consumption growth and technological advance. For this purpose we propose a metric that relates these two changes from an analogy of velocity in physics. In general terms, if technological advance is to prevent any further increase in the environmental impacts of consumption growth, the velocity of technological advance in terms of the rate at which those impacts are reduced must exceed the rate, or velocity, of consumption growth. If vCt denotes the velocity of consumption growth and vDt the velocity of environmental technological advancement at time t, it is VOL. 41, NO. 4, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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important, in other words, that the two velocities have the conceptual relationship of vDt being greater than vCt at any given time. If the velocity is positive, we can take this to mean that consumption is growing or the level of environmental technology improving. Conversely, if the velocity is negative, it means consumption is decreasing or the level of environmental technology declining. If we consider the change of consumption volume from time t-1 (Ct-1) to t (Ct) as a distance from Ct-1 to Ct, we can represent vCt in terms of Ct and Ct-1 as eq 1, based on an analogy with the relationship between velocity, distance, and time. Similarly, with respect to the change in environmental technology from time t-1 (Dt-1) to t (Dt), we can express vDt in terms of Dt and Dt-1 as eq 2.
vCt ) (Ct - Ct-1)/{ t - (t - 1)}
(1)
vDt ) (Dt - Dt-1)/{ t - (t - 1)}
(2)
The value of Ct increases with each increment of consumption growth, and the value of Dt increases with every improvement in environmental technology. Ct, Ct-1, Dt, and Dt-1 are not less than zero. In contrast to physical distance, however, the consumption volume (Ct) and the level of environmental technology (Dt) are usually quantified on the basis of different criteria or using different units. In comparing the two velocities here, this difference in units becomes problematical. As a means of solving this problem, this study quantifies the “distance” from value at time t-1 to value at time t by setting the value at time t-1 at 1, as a benchmark. Thus, as proxies for vCt and vDt, this study uses vCt|t-1 and vDt|t-1, which can be defined by eqs 3 and 4. Use of these normalized distances enables the two velocities to be measured using a common unit or non-dimensional unit [-]. The values of both vCt|t-1 and vDt|t-1 are not less than minus 1.
vCt|t-1 ) Ct/Ct-1 - 1
(3)
vDt|t-1 ) Dt/Dt-1 - 1
(4)
The values to be assigned to Ct and Dt depend on the type of environmental burden being examined. A practical approach is to measure Ct, as the quantity of goods and services of relevance to the environmental burden of interest that are purchased directly by consumers. Such data are available in the form of government and industry statistics. Either physical or monetary units can be used, as long as they explain the volume of consumption. Although measurement of Dt is discussed more fully in the case study below, a suitable value for Dt can be derived from the environmental productivity of the technologies supplying these goods and services. Thus, the reciprocal of Life Cycle Assessment (LCA) results for the goods and services in question or their ecoefficiency could be taken, for instance. Given the desired relationship of inequality between vDt and vCt introduced above, the relationship between vCt|t-1 and vDt|t-1 should satisfy the requirement expressed by eq 5. For the sake of simplicity in handling the inequality sign, we add 1 to both sides of eq 5 to obtain eq 6, which ensures that both sides are no less than zero.
vCt|t-1 < vDt|t-1
(5)
0 evCt|t-1 + 1 < vDt|t-1 + 1
(6)
By applying the relationship of eq 6, we here propose a new simple indicator for expressing the environmental status of consumption. This indicator, ecoVt|t-1, can be defined by eq 7 and evaluates the appropriateness of the relationship 1466
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between vCt and vDt at time t.
ecoVt|t-1 )
vCt|t-1 + 1 vDt|t-1 + 1
(7)
From eq 6 we can infer that if our society is to achieve a better balance between consumption and environmental mitigation, then ecoVt|t-1 must be less than unity (1) at any time t. If ecoVt|t-1 is less than unity, it implies our consumption is moving toward a pattern creating less environmental burden. Conversely, if ecoVt|t-1 is greater than unity, we can recognize that our consumption is excessive in term of its harmonization with the level of environmental technology. Conceptually, it indicates a societal trend toward environmental degradation, alerting us that our consumption may cause a greater increase in environmental burden during the next period. This is because the indicator not only specifies the present status of consumption growth in light of its relationship with environmental technological advance but also provides a means of predicting trends in the change in environmental burden over time. The existence of a desired value to attain, viz., less than unity and the ability to use the current value to predict changes in the environmental burden associated with consumption are, indeed, two noteworthy features of the indicator. Below, we refer to this proposed environmental indicator as “eco-velocity of consumption”. In analogy to the risks involved in driving a car over the speed limit, if the eco-velocity exceeds unity it signifies “eco-speeding” of consumption. 2.2. Case Study: Eco-velocity of Japanese Household Consumption in Terms of CO2 Emissions. Japan’s ratification of the Kyoto Protocol in 2002 committed the country to reducing its greenhouse gas (GHG) emissions by 6% relative to 1990 levels between 2008 and 2012. By 2003, however, Japanese GHG emissions had increased by 12.8% relative to this benchmark. Although the energy efficiency of Japanese GHG-emitting sectors is believed to be among the world’s best, the growing volume of consumption and its associated production continue to use up the GHG credits gained by efficiency gain through technological advance. In a way it is like a rat race, with the technological developments leading to efficiency gains and the consumption growth leading to volume growth competing to determine the nation’s aggregate GHG emissions. Considering Japan’s current predicament, it would be valuable to examine the extent to which Japanese consumption growth is in harmony with improvements in environmental technological efficiency. To this end, below we compute the eco-velocity of Japanese household consumption with regard to CO2 emissions. With this case study, we seek to clarify the practicability and usefulness of the eco-velocity concept. Taking household consumption in 1990, the reference year for the United Nations Framework Convention on Climate Change (UNFCCC), as a benchmark, we investigated eco-velocities for 1995 and 2000. In doing so, we used the “Japanese 1990-1995-2000 Linked Input-Output Tables” (the linked IOT) (19) as our main source of data on both the velocity of consumption growth and environmental technological advance. This linked IOT includes transaction tables showing monetary transactions among the commodity sectors in each year, with 1990 and 1995 monetary values in the transaction tables adjusted for inflation and deflation to the 2000 market price. For the sake of simplicity, 1990, 1995, and 2000 are written below as time 0 (t)0), time 1 (t)1), and time 2 (t)2), respectively. We began by deriving the volume of annual household consumption for these 3 years from the transaction tables of the linked IOT and then substituted these for C0, C1, and C2 in eq 3. Although these quantities are expressed in monetary terms, they can be directly compared with one
another because they are adjusted values, as just mentioned. Environmental technology levels D0, D1, and D2 in eq 4 were then quantified based on the “ecoefficiency” of the technology. The concept of ecoefficiency was developed by the World Business Council for Sustainable Development (WBCSD) in 1992 (20). Eco-efficiency is expressed as the ratio between the value of a product or service and its environmental impact, taking as the numerator the quantity of goods or services produced or provided to customers or, more generally, net sales. Here, we use the former. We evaluated Dt as the quantity of goods and services produced at the expense of unit CO2 emissions. Eq 8 thus determined Dt
Dt )
Yt (t)0,1,2) Pt
(8)
where Yt denotes the quantity of goods and services provided to households as measured in monetary units and Pt is the aggregate CO2 emissions due to Yt. As set out in the WBCSD report (20), it is important that the environmental impact of a product or service in the use phase is also considered. Pt therefore includes the CO2 emissions due to both production and use of the commodities consumed by Japanese households. Because of the limited data available on imported commodities, in calculating Pt this case study assumes the same technology for the imported commodity and its domestically produced equivalent. To calculate Pt we applied an input-output analysis (e.g., refs 21 and 22), represented by eq 9 n
Pt )
∑ i)1
n
dt,iqt,i +
∑e
t,ift,i
(9)
i)1
where dt,i denotes the direct CO2 emission per unit production of commodity i, reflecting the technology level at time t; qt,i is the total output of commodity i required for Yt; et,i is the direct CO2 emission per unit consumption or use of commodity i; and ft,i denotes the household demand for commodity i. Assuming equilibrium between commodity supply and demand, the summation of ft,i from i ) 1-n equals Yt, where n ()395) is the number of commodities considered in the study. It is noteworthy that, given eq 9, based on inputoutput analysis, the environmental technology level Dt determined in eq 8 reflects not only the environmental performance of an individual technology, e.g., unit CO2 emission per production and use at time t, but also the production structure, e.g., the nature of the product supply chain at that time. Details of the formulas used for deriving qt,i are described in the Supporting Information. In computing dt,i and et,i, this case study took into account 20 fossil fuels, two forms of waste, and limestone as materials leading to CO2 emissions. Previous studies (23, 24) have already estimated the amount of consumption of the materials and other factors required to calculate the CO2 emissions associated with commodity i based on the Japanese IOTs for 1990, 1995, and 2000 (25-27). Hence, we determine the consumption and other factors for t ) 0, 1, and 2 by converting the existing data into values based on the linked IOT. The linked IOT defines electricity, petroleum fuels (gasoline, diesel, kerosene, liquid petroleum gas, etc.), and city gas as three separate sectors (commodities) but with no further breakdown of quantitative consumption or the uses to which the respective energy carriers are put, either nationally or at the household level. Given the limited data available, it is no easy matter to compile such a detailed breakdown for 395 sectors. As demand in the electrical power sector, this study therefore simply takes total household power consumption and therefore calculates the CO2 emis-
sions of power consumption based on the demand of that sector. The reasoning here is that using et,i for electricityconsuming commodity i does not include the CO2 emissions associated with final consumption of that power. Similarly, in the case of petroleum fuels and city gas, the CO2 emissions due to their combustion have been attributed to the et,i of the petroleum refinery sector and the city gas supply sector, respectively. In other words, et,i for commodity i consuming fuels and city gas in the use phase is not allocated the CO2 emissions associated with burning these fuels. The method used to calculate dt,i and et,i is also explained in detail in the Supporting Information. 2.2.1. Measuring the Eco-velocities of Commodity Consumption. We can now calculate the eco-velocities of the commodities consumed by Japanese households. Measuring the eco-velocity of each commodity helps us to better understand the relationship between consumption growth and technological advance and to explore which commodities are most in need of further technological improvement in the future. Extension of eq 8 into eq 10 determines the environmental technology level of commodity i, Dt,i, so that the eco-velocity of commodity i, ecoVt,i|t-1, can be expressed by eq 11
Dt,i ) ecoVt,i|t-1 )
Yt,i Pt,i
(10)
( )( )
vCt,i|t-1 + 1 Ct,i Dt,i / ) vDt,i|t-1 + 1 Ct-1,i Dt-1,i
(11)
where scalar Yt,i is the quantity of commodity i supplied to a household at time t; Pt,i is the CO2 emissions due to production and use of that commodity; and Ct,i and Ct-1,i are the consumption volume of commodity i at time t and t-1, respectively. In the equilibrium state, Yt,i becomes equivalent to Ct,i. Since Dt,i is determined using the ecoefficiency defined in this paper, the value of Dt,i/Dt-1,i in eq 11 represents a concept similar to the so-called Factor X (e.g., ref 28). The method used to calculate Pt,i in this study is described in the Supporting Information. 2.2.2. Change of Eco-velocity and Its Source Analysis. This case study calculated the eco-velocities of a set of commodities in two particular years (t)1,2). We subsequently focused on several sectors whose eco-velocities changed significantly during the period in question and examined which factors were mainly responsible for the change. As is clear from eq 11, each year’s eco-velocities were quantified based on conditions in the previous period, and the values are hence to be considered nominal. To compare ecovelocities between different times we first therefore need to convert these nominal values into real values. If t ) 0 is set at the benchmark year considered real, conversion to the eco-velocity for t ) n can be achieved by means of eq 12. n
ecoVn,i|0 )
∏ ecoV
t,i|t-1
(12)
t)1
In this study we calculated the change in eco-velocity of commodity i from t ) m to n using eq 13: n
∆ecoV[mfn] i
)
ecoVn,i|0 ecoVm,i|0
∏ ecoV )
t,i|t-1
t)1 m
∏ ecoV
n
) t,i|t-1
∏
ecoVt,i|t-1
t)m+1
t)1
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TABLE 1. Top 10 Sectors with Greatest Eco-velocity in Terms of CO2 Emissions for 1995 and 2000 t ) 1 (1995) sector no. (i)
no. 1
228
2 3 4 5 6 7 8 9 10
215 332 362 294 223 107 9 151 249
a
t ) 2 (2000)
sector name
ecoV1,i|0
sector no. (i)
radio communication equipment (except cellular phones) copy machines cable broadcasting information services steam and hot water supply personal computers chemical fertilizers other edible crops other glass products trucks, buses, and other vehicles
22.5
362
information services
11.2 6.08 3.30 3.20 2.97 2.95 2.61 2.53 2.25
223 227 19 352 135 71 379 53 328
personal computers cellular phones other livestock health and hygiene (profit-making) agricultural chemicals organic fertilizers, neca theatrical companies dextrose, syrup, and isomerized sugar telecommunications
sector name
ecoV2,i|1 25.1 3.95 3.36 2.88 2.77 2.63 2.55 2.12 1.98 1.92
Not elsewhere classified, nec.
Accordingly, by converting the eco-velocities for 1995 (t)1) and 2000 (t)2) into real values based on 1990 values, we can quantify the changes in eco-velocities from 1995 to 2000. Here, the most important thing is to understand why ecovelocities have increased or decreased during the period in question. The input-output analysis we use to calculate ecovelocities permits structural decomposition analysis of the reasons for growth in environmental impact due to such aspects as growth in consumption, changes in the structure of consumption, changes in the emission factors of processes and products, and changes in economic production structures (e.g., refs 29-32). Hence, the main sources of changes in eco-velocity can be investigated. We therefore performed the structural decomposition analysis on the fluctuations in eco-velocity using a multiplicative structural decomposition framework (33). This study classified the sources into four factors and calculated the effect of each factor on the change, as formulated by eq 14
∆ecoV[1f2] ) ∆C[1f2] ∆L[1f2] ∆d[1f2] ∆e[1f2] i i i i i
(14)
where ∆C[1f2] , ∆L[1f2] , ∆d[1f2] , and ∆e[1f2] denote, respeci i i i tively, the effects of changes in C (consumption volume), L (product supply chain), d (unit CO2 emission in the production phase), and e (unit CO2 emission in the use phase). The formulas used to determine the respective effects are described in detail in the Supporting Information.
3. Results and Discussion 3.1. Eco-velocities of Japanese Household Consumption from 1990 to 2000. Since the consumption volumes for each of the years investigated, C0, C1, and C2, were 229 784, 265 237, and 275 996 billion yen (expressed in the 2000 FY price), the velocities of consumption growth measured by eq 3, vC1|0 and vC2|1, were calculated as 0.15 and 0.041, respectively. We calculated the levels of environmental technology quantified by eq 8, D0, D1, and D2, as 0.396, 0.386, and 0.384 million yen (MY)/t-CO2, respectively, and the velocities of environmental technological advance based on eq 4, vD1|0 and vD2|1, as -0.025 and -0.0047. This implies not only that consumption has increased but also that the overall level of technology in terms of CO2 emissions has declined. Accordingly, from eq 7, the eco-velocities of Japanese household consumption in t ) 1 (1995) and t ) 2 (2000), ecoV1|0 and ecoV2|1, were calculated as 1.18 and 1.05. Because both these values exceed unity, consumption in 1995 and 2000 was classified as “eco-speeding” in terms of CO2 emissions. These ecovelocities implicitly warn that the CO2 emissions associated with consumption will increase during the next term. For instance, the CO2 emissions of household consumption did actually increase from 843 Mt-CO2 in 1995 to 891 1468
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Mt-CO2 in 2000. These CO2 emission values were calculated under the assumption that the production technologies for imported commodities are the same as those used for their domestic equivalents, and they denote aggregate CO2 emissions due to household consumption. This consistency between the implications of eco-velocity and the actual status of CO2 emission change indicates that eco-velocity can be used to roughly estimate the increase and decrease in a studied environmental burden associated with consumption in the following period as well as to understand the present environmental status of consumption. Eco-velocity in 2000 (1.05) was less than in 1995 (1.18), so Japanese society may have shifted slightly toward more sustainable consumption during this period. Because there is no IOT subsequent to t ) 2, we cannot examine the actual state of t ) 3 in the same manner. The latest figure for total Japanese CO2 emissions submitted to UNFCCC was 1259 Mt-CO2 for 2003 (34), an increase from 1239 Mt-CO2 in 2000 (34). These figures cover domestic CO2 emissions only and therefore provide no direct indication of any change in CO2 emissions due to household consumption. On the whole, however, the future implication of the eco-velocity for 2000 is consistent with the actual status of CO2 emissions in 2003. This finding supports the usefulness of eco-velocity as an indicator for roughly estimating environmental burden changes in the subsequent time period. Table 1 lists the 10 commodities (sectors) with the greatest eco-velocity in 1995 and 2000. The number one in the top ten for 1995 was the radio communication equipment (except cellular phones) sector, with an eco-velocity of 22.5. Next on the list for that year were the copy machine sector (11.2), the cable broadcasting sector (6.08), the information services sector (3.30), and the steam and hot water supply sector (3.20). In the year 2000, the information services sector was fastest at 25.1. The second fastest sector was personal computers (3.95), followed by cellular phones (3.36), the ‘other livestock’ sector (2.88), and the health and hygiene (profit-making) sector (2.77). Factors behind the “ecospeeding” of these top-scoring commodities may include the spread of the Internet, short-cycle release of new cellular phone models and rapid improvements in the performance of personal computers in Japan, all of which may be driving consumer demand. We also demonstrated that in Japanese households utilities-related sectors are eco-speeding, viz. the electric power sector (1.24 for 1995, 1.05 for 2000), the petroleum refinery products sector (1.33 for 1995, 1.16 for 2000), and the city gas sector (1.09 for 1995, 1.10 for 2000). As an aid to understanding the status of each commodity, Figures 1 and 2 plot the numerator of ecoVt,i|t-1 (or vCt,i|t-1 +1) for each sector on the horizontal axis and the reciprocal of its denominator (or vDt,i|t-1 +1) on the vertical axis in double logarithmic plot for 1995 (Figure 1) and 2000 (Figure
FIGURE 1. Visualized relationship between eco-velocity, velocity of consumption growth (vC), and velocity of environmental technological advance (vD) for each commodity consumed by Japanese households in 1995 (t)1). 2). To facilitate distinction between the various commodities, we categorized them into five types: food, “livingware” (comprising mainly textile products, pulp and paper products, plastics and glass), equipment and appliances, services, and others. With these figures, we can visually confirm whether a commodity was eco-speeding and, for a given commodity, which velocity was faster: vCt,i|t-1 or vDt,i|t-1. The line in each figure represents ecoVt,i|t-1 )1, so sectors above the line can be readily seen to be eco-speeding. Furthermore, four quadrants clearly characterize the velocities of consumption growth and environmental technological improvement for each commodity. Commodities in the first quadrant (I) are characterized by expanding consumption and declining environmental technology levels. They are all eco-speeding. Those in the second quadrant (II) were consumed less, but their carbon efficiencies have declined; some commodities in this quadrant are therefore eco-speeding. Third quadrant (III) commodities show falling consumption and rising levels of environmental technology, so none are eco-speeding. Commodities in the fourth quadrant (IV), finally, show growing consumption, but their environmental technology levels are also improving. As in quadrant II, some commodities in this quadrant are eco-speeding, while some are not. In 1995, 168 of 238 (71%) commodities consumed by Japanese households were eco-speeding. In 2000, 123 of 248 (50%) commodities were eco-speeding. Tables 2 (1995) and 3 (2000) summarize the number of commodities ecospeeding by type of commodity and quadrant. It is remarkable that approximately 78% (1995) and 70% (2000) of commodities included in the services category were eco-speeding. Most of the services commodities (55% for 1995 and 39% for 2000) are in the first quadrant (I). This
implies that we should actively address innovation in environmental technology for the services sector, at least in terms of CO2 emissions, given that consumption of these commodities will be increasing in the next term. In 1995 the petroleum refinery sector was classified in this quadrant. On the other hand, about 72% (1995) and 52% (2000) of commodities in the equipment and appliances category were in quadrant IV. This means that companies producing these commodities are improving their environmental technology levels, but that the need for efforts to slow down household consumption of these commodities is greater than ever. For instance, the petroleum refinery sector in 2000, the electric power sector in 1995 and 2000, and the city gas supply in 1995 and 2000 could all be assigned to quadrant IV. Some of the sectors illustrated in Figures 1 and 2 underwent a major change in eco-velocity between 1995 and 2000. We therefore focused on these sectors and quantified the respective effects of four factors on their change in ecovelocity. According to eq 13, the top 10 commodities showing the greatest increase in eco-velocity are the same as those shown in Table 1 for 2000. Figure 3 shows the quantified effects of the four factors for the top 10 sectors with ecovelocities that increased or decreased most. These sectors are specified in the Supporting Information. Among commodities with increased eco-velocity, the effect of ∆ C[1f2] was notably greater than 1, while that of ∆d[1f2] was i i less than 1. We found that although reduction of direct CO2 emissions in the production phase certainly contributed to slowing down eco-velocity, it was insufficient to compensate for growth in consumption. Furthermore, we found that the effect of ∆L[1f2] was to either increase or decrease the ecoi velocity, depending on the commodity. For commodities VOL. 41, NO. 4, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 2. Visualized relationship between eco-velocity, velocity of consumption growth (vC), and velocity of environmental technological advance (vD) for each commodity consumed by Japanese households in 2000 (t)2).
TABLE 2. Number (and Percentage Share) of Commodities in Ecospeeding by Type of Commodity and Quadrant for 1995
TABLE 3. Number (and Percentage Share) of Commodities in Ecospeeding by Type of Commodity and Quadrant for 2000
quadranta commodity category food
I
II
III
16 10 0 (43) (27) livingware 27 5 0 (69) (13) equipment and 8 0 0 appliance (28) services 34 12 0 (55) (19) others 0 0 0 a
quadranta
IV 11 (30) 7 (18) 21 (72) 16 (26) 1 (100)
total no. of ecospeeding total no. sectors in 1995 of sectors 37 (70) 39 (59) 29 (76) 62 (78) 1 (50)
53 66 38 79 2
For an explanation of quadrants, please see the text.
with a declining eco-velocity, not only ∆d[1f2] but also ∆ i C[1f2] greatly contributed to reducing eco-velocity. Overall, i ∆L[1f2] made little contribution to reducing eco-velocity. i The effect of ∆e[1f2] is not visible in Figure 3, for two reasons. i Some sectors in fact emit no CO2 at the stage of household consumption, while in the case of other sectors this impact cannot be attributed owing to the method used to count the CO2 emissions associated with household use of electricity, petroleum fuels, and city gas, as stated previously. 3.2. Discussion and Outlook. This paper has proposed an environmental indicator designed from the perspective of consumption, the “eco-velocity of consumption”. This indicator was formulated to evaluate the appropriateness of 1470
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commodity category food
I
6 (40) livingware 9 (36) equipment and 9 appliance (39) services 22 (39) others 2 (67) a
II
III
IV
2 (13) 12 (48) 2 (9) 16 (28) 1 (33)
0
7 (47) 4 (16) 12 (52) 19 (33) 0
0 0 0 0
total no. of ecospeeding total no. sectors in 2000 of sectors 15 (28) 25 (37) 23 (53) 57 (70) 3 (100)
53 68 43 81 3
For an explanation of quadrants, please see the text.
the rate of consumption growth based on its mutual relationship with the rate of advance of environmental technology. We then calculated the eco-velocities of Japanese household consumption in terms of CO2 emissions for 1995 and 2000 by applying an input-output framework composed of 395 sectors, thereby demonstrating that the velocity of consumption growth exceeded that of technological advance vis-a`-vis CO2 emissions abatement. Further consideration of individual commodities demonstrated that it was the ICT (Information and Communication Technology)-related sectors such as information services, personal computers, cellular phones, and telecommunications, in particular, that showed the greatest eco-velocities. This implies that Japanese policy should seek to promote further environmental im-
FIGURE 3. Effects on change in eco-velocity from 1995 to 2000 for the top 10 sectors whose eco-velocities increased or decreased most for the following four factors: C (consumption volume), L (product supply chain), d (unit CO2 emission in production phase), and e (unit CO2 emission in use phase). Sector numbers match those used in Table S1 in the Supporting Information. provement in the technologies of these sectors. The results of the decomposition analysis undertaken to identify the sources of changing eco-velocities showed, however, that the effects of technological advance in reducing direct CO2 emissions and of changing supply chains were smaller than those of changes in consumption. We need to recognize that without a shift of consumption patterns it may be very hard to reduce CO2 emissions and secure the target set in the Kyoto Protocol. Although the country could, of course, meet the target by increasing the share of imports in household consumption, such a move would be essentially meaningless. By considering CO2 emissions from the consumption perspective rather than the conventional, geographical-border perspective on which the UNFCCC’s greenhouse gas accounting is based, as we have done in this paper, we can gain greater insight into the emission outsourcing problem. Under the current UNFCCC GHG accounting scheme, a nation can meet the Kyoto Protocol while still inducing greater GHG emissions if some (enough) of these emission occur across its national borders by way of international trade. In order to address absolute changes in the CO2 emissions associated with a society’s economic activity, inducement-based accounting needs to play a role. On the other hand, when it comes to further application of eco-velocity we are confident that measurement of this indicator is possible for other countries, for other environmental burdens such as air and water pollution, wastes, and so on, and for other dimensions of consumption analysis. We were able to identify which environmental burden associated with which technology should be preferentially mitigated in the next period by calculating the eco-velocity of each environmental burden. We also used integrated environmental impact values, such as the Ecological Footprint (e.g., refs 35-37) or the single index (e.g., ref 38) used in life-cycle impact assessment, to evaluate the level of environmental technology (Dt). This allowed us to show the difference between the velocities of consumption growth and environmental technological advance, quantified on the basis of overall environmental impact. It would be useful to examine directly whether there will be a shift toward more sustainable consumption in the future. In countries where the environmental data relevant for input-output analysis have been complied (e.g., refs 39-46), macroscopic mea-
surement of the eco-velocity of household consumption, as done in this study, is readily feasible. LCA data based on a process approach (e.g., refs 47 and 48) are available for understanding the eco-velocity of consumption for individual goods and services. Periodic monitoring of the eco-velocity of consumption in a region could be useful for regional environmental management. Our future work should consider the following points. First, domestic and imported commodities may differ considerably in the level of environmental technology they embody (e.g., ref 49). This paper assumes, for simplicity, that the same technologies are used for producing both. Second, with regard to the eco-velocity of commodities we need to identify the amount of electricity, petroleum fuels, and city gas consumed directly in each of them. Because of the limited amount of data collected, given the very detailed nature of sectoral classification, this study took aggregate household consumption of electricity, fuels, and gas to be the demand in the electrical power sector, the petroleum refinery products sector, and the city gas supply, respectively. However, in order to demonstrate realistic changes in the eco-velocity of each commodity, we will have to precisely examine the breakdown of household consumption of electricity, fuels, and gas. Chambers et al. (50) mention that a good indicator must be resonant, valid, and motivational. This means the indicator should have a clear meaning and be readily interpretable, that it employ reasonable and available data, that it be characterized by methodological transparency, and that it reflect issues that are within the sphere of influence of users. Eco-velocity could meet all these requirements. At the country level, the velocity of consumption growth relates to the scale of the national economy, at the company level to corporate sales, and at the regional level to regional economic activity. By ensuring that this velocity remains larger than unity whenever possible, through changing consumption patterns and by developing new technology and product service systems that avoid “eco-speeding”, we could contribute to moving toward sustainable levels of consumption.
Acknowledgments This research was supported by the Global Environment Research Fund of the Japanese Ministry of Environment VOL. 41, NO. 4, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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(Grant No. H-9). Thanks are due to the three anonymous reviewers for their excellent and helpful comments on the manuscript. We are also grateful to Mr. Nigel Harle in The Netherlands for his editing of the English.
Supporting Information Available Methods used in the case study and the formulas used in the multiplicative decomposition scheme to identify the key factors driving changes in eco-velocity. This material is available free of charge via the Internet at http://pubs.acs.org.
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Received for review July 5, 2006. Revised manuscript received November 13, 2006. Accepted December 5, 2006. ES0615876
