1 Background
As the consumption activities in metropolitan regions are typically larger than those of rural regions, so too is consumer responsibility of metropolitan regions larger than that in rural regions. From the late 1990s to the early 2000s, numerous studies examined consumer responsibility and the associated environmental loads (Hertwich
2011; Nijdam et al.
2005; Wiedmann et al.
2006,
2013; Wiedmann
2009), especially those associated with carbon dioxide (Lenzen and Murray
2001; Peters and Hertwich
2006a,
b,
2008; Wiedmann et al.
2007; McGregor et al.
2008; Peters
2008; Weber and Matthews
2007,
2008; Wilting and Vringer
2009), water consumption (Cazcarro et al.
2013; Daniels et al.
2011; Feng et al.
2012; Guan and Hubacek
2007; Lenzen
2009; López-Morales and Duchin
2011), land consumption (Bicknell et al.
1998; Wilting and Vringer
2009), and loss of biodiversity (Lenzen et al.
2012). Although most of these studies examined these aspects at a global level between countries, the consumer responsibility associated with these consumption activities at a local level, such as consumption by the cities and country regions concerned, has received comparatively little attention (Minx et al.
2009). However, the cities and regions within a country have their own local environmental policies, and these policies play an important role in dealing with the problems associated with waste treatment. Although many cities in developed countries, such as Stockholm and Adelaide, are attempting to become “zero waste” cities (Zaman and Lehmann
2011), cities such as Tokyo are confronted with serious problems related to sharing responsibilities between local regions.
Tokyo is one of the largest metropolitan regions in the world with a population exceeding 12 million people (Statistics Bureau of Ministry of Internal Affairs and Communications (MIC) Japan
2014), and it is both directly and indirectly responsible for serious negative environmental impacts in regions outside Tokyo.
The direct environmental impacts are attributable to the transport of wastes from Tokyo to other regions. In 2007, 81 % of the waste generated by Tokyo was exported to landfill sites in other regions (Bureau of Environment (BoE)
2012; Tokyo Metropolitan Government (TMG)
2011,
2012). A simple solution to this problem would be to construct a final disposal facility in Tokyo, but the high population density and land prices in the city have precluded any provisions for such a facility in the waste treatment plan for Tokyo (TMG
2008). The population density of Tokyo in 2011 was 6029 people/km
2, which was markedly higher than the 343 people/km
2 average for Japan as a whole. In addition, the land prices in Tokyo in 2011 were also the highest in Japan, averaging 208,900 yen/m
2 for industrial land. Although two new landfill sites were constructed in Tokyo in 2004, the absence of any plans to construct additional landfill sites in the future (TMG
2008) means that direct exports of waste generated in Tokyo will continue, and likely increase, in the future. Using a choice experiment, Sasao (
2004) assessed public opinion regarding the construction of landfills in a rural region in northern Japan. He found that residents were considerably more opposed to accept industrial waste from Tokyo than they were to landfilling their own municipal solid waste (MSW). The problem of waste treatment, especially landfilling, is a very contentious issue and source of confrontation between Tokyo and rural regions.
Since these direct effects are easy to recognize, they can be addressed directly through cooperation between the local governments involved. However, the indirect effects that are responsible for consumption in metropolitan regions and that are related to the problem of consumer responsibility are both difficult to recognize and overlooked as problems. The average income of Tokyo residents is approximately 15 % higher than that of residents elsewhere in Japan. Similarly, total consumption by Tokyo residents, which is associated with increases in waste generation and environmental loads, is 12 % higher than the average per capita consumption of other regions. Although consumption in Tokyo stimulates industrial activity in other regions, it also increases the amount of industrial waste produced by those regions. Since these wastes are treated outside of Tokyo, Tokyo indirectly exports industrial waste and consumes the landfill sites of other regions. To the best of our knowledge, however, the effect of consumption by Tokyo residents has not yet been accurately quantified. As a result, most Tokyo residents are unaware of how much of their waste is transported to, and disposed of in, other regions, and how their lifestyles affect waste generation, waste treatment, and landfill utilization in those regions. To prepare a basis for a discussion of these topics, it is, therefore, very important to consider the usage and development of landfill sites within an interregional context.
From the late 1990s to the early 2000s, numerous studies examined the consumer responsibility of environmental loads. Bicknell et al. (
1998) calculated the ecological footprint of New Zealand using an IO analysis. Lenzen and Murray (
2001) estimated land use and greenhouse gas emissions using a single-region IO analysis. Nijdam et al. (
2005) employed an IO model to investigate the environmental loads associated with Dutch private consumption considering the technology differences among three regions (i.e., The Netherlands, OECD and non-OECD countries). From the early 2000s, investigators interested in the consumer responsibility associated with environmental loads began to recognize the importance of environmental loads and the extent to which they are embodied in trade. Indeed, it was this realization that prompted the development of the multi-regional input–output (MRIO) approach. Lenzen et al. (
2004) estimated the consumer responsibility associated with greenhouse gas emissions (GHG) embodied in trade. In addition, they also applied the IO approach to trade and found that MRIO models were more accurate than single-region IO models. Peter and Hertwich (
2006a,
b) applied the MRIO model developed by Lenzen et al. (
2004) to examine the pollution embodied in Norwegian trade, considering the regional differences in the production technologies of different countries. Wiedmann et al. (
2006) estimated the repercussion effects of household expenditure using existing ecological footprint data and a supply-and-use table for the United Kingdom (UK). All of these studies contributed to the development of the MRIO framework. Weber and Matthews (
2007,
2008) used an MRIO model to analyze the environmental effects and carbon footprint of households in the United States and its seven largest trading partners. Turner et al. (
2007) proposed that the MRIO accounting approach was the most appropriate method for estimating ecological footprints. McGregor et al. (
2008) applied a two-region IO framework to enumerate the CO
2 pollution content of interregional trade flows between Scotland and the rest of the UK in their provisional investigation. Peters (
2008) developed a multi-regional input–output analysis (MRIOA) that considered carbon leakage for the consumption-based National Emission Inventory initiative and compared it with emissions embodied in bilateral trade. Wilting and Vringer (
2009) applied an MRIO model to 12 world regions to compare the outcomes of a producers-and-consumers approach for considering GHG emissions and land use; for GHG emissions, they evaluated 87 countries and regions. Daniels et al. (
2011) proposed that the process-based methods of MRIOA were well suited for estimating water footprints and clarifying the components of the virtual water supply chain. Lenzen et al. (
2012) used threatened animal species data to generate an MRIOT to evaluate the biodiversity footprint of 187 countries. Wiedmann et al. (
2013) presented a time series analysis of the material footprint, which is a consumption-based indicator of resource use, using an MRIOA for 186 countries.
As stated in the beginning of the introduction, most of the aforementioned studies considered these various relationships at the country level; however, some investigators have employed an MRIOA to evaluate consumer responsibility between different regions within a country. Guan and Hubacek (
2007) investigated virtual water flow in China using a two-region MRIOA for 40 industrial sectors. Yi et al. (
2007) developed an expanded interregional IO method (EIOM) based on the life cycle assessment (LCA) methodology to evaluate four environmental burdens (CO
2, NO
X, SO
X and SPM) in the 47 prefectures of Japan. In a case study of the Australian state of Victoria using an MRIOA, Lenzen (
2009) enumerated virtual water flows in eight regions, each with 344 sectors. Minx et al. (
2009) provided a thorough overview of IO applications for analyzing carbon footprints, including the regional and local carbon footprints of 434 local authorities in the UK. Feng et al. (
2012) investigated supply chain effects and regional virtual water flows using an MRIOA of three river reaches in the Yellow River Basin. López-Morales and Duchin (
2011) implemented an MRIO model based on the World Trade Model to evaluate policy scenarios for 13 hydro-economic regions. Hasegawa et al. (
2011) constructed an MRIOT for the 47 prefectures of Japan to estimate the carbon footprint and carbon leakage. Cazcarro et al. (
2013) employed an MRIO approach to estimate the water footprint of 16 regions in Spain, and clarified the interregional and international trade of virtual water.
However, few studies have applied an MRIOA to clarify the various waste issues of local regions. Waste input–output analysis (Nakamura and Kondo
2002,
2009) has been used extensively to measure waste footprints at national and regional levels. Kagawa et al. (
2007) and Kagawa and Kondo (
2007) produced a multi-regional waste input–output (WIO) table for nine regions in Japan, and investigated the effect of consumption within each region on the other regions for the year 1995. Reynolds et al. (
2012) illustrated the theoretical background of a multi-regional WIO analysis model and clarified the difficulties associated with the construction of a multi-regional WIO table for eight Australian regions. Lenzen and Reynolds (
2014) and Reynolds et al. (
2014) developed waste supply-use tables (WSUTs), which expanded on the WIO framework by incorporating a supply-use table, to analyze economic and waste data in Australia in 2008–2009. Fry and Lenzen (
2014) described a method for constructing a multi-regional WIO framework utilizing Australian waste data; the framework was compiled using the System of Environmental–Economic Accounting (SEEA).
In line with these WIO studies, we constructed a new multi-regional WIO database for Tokyo and the other regions in Japan, and quantified waste generation and landfill consumption induced by final demand in Tokyo and these other regions, respectively. Within the context of the existing body of literature, our study differs from previous studies in that Japan is divided into 47 administrative regions called prefectures, each of which has a local government that promulgates its own environmental and waste treatment policies; the capital of the country, Tokyo, is also a prefecture, and it has the largest economy of all the prefectures. Previous studies on Japan, such as that of Kagawa et al. (
2007) and Kagawa and Kondo (
2007) employed nine regions. These regions are commonly employed by the Japanese government for the sake of convenience. However, some of the prefectures within these regions are markedly different, both economically and environmentally, from the other prefectures in the same region (Hasegawa et al.
2011; Tsukui and Nakamura
2009; Tsukui
2009). While Kagawa et al. (
2007) and Kagawa and Kondo (
2007) estimated the effect of per capita consumption on the amount of waste to be treated and the landfill volume required, their nine-region WIO table did not facilitate a detailed assessment of the effect of consumption on waste generation in a specific prefecture. Yi et al. (
2007) and Hasegawa et al. (
2011) investigated environmental loads in the 47 prefectures of Japan, but they did not consider aspects of waste related to environmental loads (e.g., waste generation and landfill volume). To quantitatively clarify the interregional dependence between Tokyo and the other regions in terms of waste treatment, it is considered important to construct an MRIO table and model for the prefectures being considered.
In this study, we quantitatively investigated the direct and indirect economic and environmental effects of consumption induced by Tokyo residents on other regions in Japan using the interregional WIO (IRWIO) approach. This paper is structured as follows. In Sect.
2, we describe the IRWIO model that was employed in this study. We also describe the data that were used to compile the WIO Tokyo 2000 table, and explain how the table was compiled. In Sect.
3, we present the results showing the effect of consumption in Tokyo on landfill utilization in both Tokyo and in the other regions. We also examine the effect of consumption in Tokyo on waste generation, economic activity and greenhouse gas emissions in both Tokyo and in the other regions, within the context of the differences in the economic and waste treatment activities in Tokyo and in the other regions. In Sect.
4, we summarize our findings and propose several topics for future research. We provide the compilation results of the Tokyo 2000 IRWIO table and the detailed results of the direct and indirect effects in Additional file
1.
4 Conclusions
We compiled an interregional WIO table for Tokyo in the year 2000 and evaluated the effect of consumption by the metropolitan region on other regions using the table. The results showed that the consumption activities in Tokyo induced fewer economic benefits in the regions outside Tokyo, while markedly increasing the induced environmental loads in these regions, especially the utilization of landfills. Although consumption by Tokyo residents promoted production activities in other regions, the value of that induced production in industrial sectors was only half as much as that in Tokyo, and the value added was only about third that of Tokyo. Moreover, the final demand of Tokyo consumption generated almost the same amount of CO2 in the other regions as in Tokyo. Although economic benefits were induced by Tokyo consumption, the associated burden on other regions due to Tokyo consumption was considerable. In developing waste treatment policies, it is important to conduct quantitative investigations of the waste treatment efficiency of an entire country, as well as to determine how to share responsibility between regions. As such, Tokyo should assume more responsibility for the additional environmental loads in other regions, especially considering the volume of landfill that it uses.
One of the ways in which this responsibility could be shared more equitably between the metropolitan regions and other regions is to levy taxes for interregional waste treatment and landfill utilization. In Japan, the decision of whether or not to impose such landfill taxes would be up to individual prefectures. Previous studies on landfill taxes in Japan mainly evaluated the effectiveness of those taxes on waste reduction in each prefecture (Kurasaka
2003; Nagasaki
2003; Fujioka and Hagihara
2007; Sasao
2014). In this study, we were able to quantitatively demonstrate that Tokyo depends, both directly and indirectly, on other regions for waste transportation and waste treatment. These results highlighted the importance of the interdependent relationships that exist between regions, such as Tokyo and the other regions, as well as the need to consider the indirect effects of these interdependent economic relationships and how this information can be used to formulate more effective waste treatment policies between regions. Future research will involve detailed regional analyses of the interdependent relationships that exist among the 46 prefectures in Japan, excluding Tokyo, within the context of waste treatment at a national scale.
Another potentially effective solution is to encourage recycling. As we demonstrated in this study, if economic activities are stimulated by consumption in metropolitan regions, then the increase in recycled wastes will reduce the amount of waste that needs to be treated. Concerted efforts by Japan to reduce landfill waste have reduced the rate of landfilling of industrial waste by 10 % to just 3 % in 15 years (MOE Japan
2001a,
2012a,
2014a). About 55 % of all industrial waste generated is recycled, and 42 % of that is processed by waste treatment. The results of this study showed that 30 % of the induced waste in Tokyo is generated by the construction industry, indicating that waste reduction and recycling of “construction and demolition wastes” are still important. In other regions, the recycling rate of slag from “publishing, printing” also needs to be improved to reduce the amount of waste that needs to be processed in those areas. Unlike the recycling rates for industrial waste, the average recycling rate for MSW in Japan is only 20.6 %, which is about 10 % less than it was 15 years previously (MOE Japan
2001b,
2012b,
2014b). The study also demonstrated the importance of improving MSW recycling rates, particularly in the business waste categories of “food waste” and “waste cardboard” from industries such as “retail trade” and “eating and drinking places” in Tokyo, as the amount of induced waste in these categories is large in Tokyo.
We demonstrated that the economic activities of Tokyo are mainly centered on tertiary industries. These activities are associated with high levels of consumption, which increase the environmental loads of other regions, particularly in the areas to which the resulting waste is transported, treated and landfilled. Importantly, the economic benefits induced by metropolitan consumption activities in Tokyo were smaller in other regions than they were in Tokyo. Using the methodology developed in this study, the interdependence between economic activities and environmental loads between regions can be quantitatively analyzed (Additional file
1).