An emergy and decomposition assessment of China-Japan trade: Driving forces and environmental imbalance

Journal of Cleaner Production 141 (2017) 359e369

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An emergy and decomposition assessment of China-Japan trade: Driving forces and environmental imbalance Xu Tian a, d, Yong Geng a, *, Sergio Ulgiati b, c, ** a

School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China Department of Sciences and Technologies, Parthenope University of Naples, Centro Direzionale, Isola C4, 80143 Napoli, Italy c School of Environment, Beijing Normal University, Beijing, China d School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 3 August 2016 Received in revised form 16 September 2016 Accepted 16 September 2016 Available online 17 September 2016

With the robust development of economic globalization, international trade should be fairly conducted in order to strengthen the relations among different nations. Currently, due to different resource endowments and trade policies, different nations face different resources and environmental challenges. Previous studies suggested that even when trade seems balanced in monetary terms, it may be unequal in terms of resources exchanges due to different purchasing power of national currencies. As such, imbalance also exist in terms of environmental quality of traded resources and related environmental costs and emissions, such as embodied energy, water, land, carbon, ecosystem services. Under such circumstances, it is necessary and urgent to identify environmental imbalance of international trade and seek appropriate tools so that more balanced and fairer trade among nations can be implemented. This study investigates the quality of resource flows exchanged between China and Japan during the period 2000e2012. Emergy accounting, a well-established environmental accounting method, is used in this study to quantify the environmental work (past and present ecosystem services) embodied in traded resources. Within a broader emergy-based bio-physical perspective, a Logarithmic Mean Divisia Index (LMDI) decomposition approach is applied to identify the driving forces that affect the evolution of import-export resources balance in the investigated period. LMDI decomposes the driving forces into three factors: (a) scale factor, which depends on the total export volume; (b) technology factor, which depends on the emergy intensity of trade (emergy of traded resources); and (c) structural factor, which depends on the trade structure (mix of exchanged commodities). Results show that China was a net emergy exporter in the years 2000 and 2005, with figures of 7.46Eþ22 sej/yr and 5.76Eþ21 sej/yr, respectively, but was a net importer in the years 2008 and 2012, with imported emergy figures of 8.82Eþ22 sej/yr and 2.43Eþ23 sej/yr, respectively. Scale and technology factors are the most significant drivers to promote China-Japan trade from an emergy point of view (i.e. from the point of view of environmental quality assessment), while the influence of structural factor was relatively marginal. Trade imbalance and lack of focus on environmental value of resources cannot be the basis for stable economic relations with partner countries, which calls for compensation measures in money or resource terms. This study, by investigating the sustainability of China-Japan international trade, also suggests a methodological approach to increase worldwide trade stability and fairness. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Trade imbalance Emergy China Japan

1. Introduction

* Corresponding author. ** Corresponding author. Department of Sciences and Technologies, Parthenope University of Naples, Centro Direzionale, Isola C4, 80143 Napoli, Italy. E-mail addresses: [email protected] (Y. Geng), [email protected] (S. Ulgiati). http://dx.doi.org/10.1016/j.jclepro.2016.09.124 0959-6526/© 2016 Elsevier Ltd. All rights reserved.

With the rapid development of economic globalization, the connections between different countries are becoming stronger. Particularly, international trade plays a significant role by allowing all kinds of resource flows exchanges and redistributions (such as energy, materials, labor, money and environmental services) according to different requirements of different countries (Jomo and Rudiger, 2009; Lenzen et al., 2012). Economic growth and

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resources demand not only inevitably intensify resource use and environmental impacts globally, but also cause resources and environmental costs shifting among different countries (Arrow et al., 1995; Arto et al., 2014; Muradian and Martinez-Alier, 2001; Yu et al., 2014). Due to market failures, monetary terms cannot fully capture the complexity of the actual exchanges of resources and environmental flows in trade, and unfair exchanges of embodied resources (energy, materials, land, labor, environmental services) may be hidden in the accounting, even in cases where trade is balanced in monetary terms (Andersson and Lindroth, 2001; Giljum and Eisenmenger, 2004; Rice, 2007; Wackernagel and Rees, 1997). Therefore, more comprehensive indicators that complement market-based economic values need to be implemented for equitable trade policy-making and international stability. After China entered the World Trade Organization (WTO) in 2001, China's foreign trade has experienced unprecedented growth and made primary contribution to the economic development (WB, 2014). However, the rapid trade development brought many challenges, such as resources depletion and corresponding environmental emissions (Fu et al., 2007; Liu et al., 2015). Previous published research outcomes uncovered that China was a net virtual water, virtual land, and also embodied emissions exporting country through its foreign trade (Minx et al., 2011; Mol, 2011; Peters et al., 2011; Yu et al., 2013; Zhang et al., 2011). Therefore, it is urgent to explore the real gains or losses related to economic, resource and environmental balance of China's foreign trade. The aim of such an investigation is not to stop free trade, but to prepare suitable policies and international agreements that foresee suitable compensation measures in case of evident imbalance of resource exchanges. Emergy accounting method and its supply-side value perspective are used in this study to complement the conventional monetary accounting procedures. Different from other methods quantifying the trade imbalance from environmental point of view, such as InputeOutput Analysis (IOA) and Ecological Footprint (EF), EMA provides a global estimation of the total biosphere work supporting natural and human-made systems and helps understand the overall interactions between economic processes and environmental dynamics (Ulgiati and Brown, 2012) so that a more comprehensive trade assessment can be achieved. The China-Japan trade experienced rapid development over the past four decades. Since the two countries established diplomatic relations in 1972, especially after China's entrance to the World Trade Organization (WTO) in 2001, the economic interdependence of the two countries is becoming closer (JETRO, 2015). Table 1 shows the trends of China-Japan trade from 2000 to 2012. The total trade volume increased by about 299%, with the imported volume increased by about 332%, and the export volume increased by about 266%. Trade ratios in monetary terms for China (money spent for imports/money received for exports) were 0.99, 1.20, 1.29 and 1.17, in 2000, 2005, 2008 and 2012, respectively. These ratios mean that China spent more money for importing goods from Japan after 2000. Another key feature of China-Japan trade is that China mainly exported energy commodities to Japan in the early 2000s, while Japan exported machinery products and equipment to China at the same period. However, with the rapid development of the Chinese economy, China began to export low-value added machinery products to Japan in recent years (Marukawa, 2012). Such a trade structure change indicates that resource flows between the two countries experienced dynamic changes and deserve more policy considerations. In this study, China-Japan trade between 2000 and 2012 is investigated. Previous studies on China-Japan trade, highlighted embodied energy or emissions in traded commodities (Dong et al., 2010; Wu et al., 2016; Zhao et al., 2015), but to the best of our

knowledge trade issues have not been analyzed from a biosphere point of view (biosphere support, natural capital extraction, ecosystem services, renewability). Under such a circumstance, this study aims to fill this gap. It should be clearly understood that trade relations where value of commodities is not sufficiently rooted in their relation with biosphere dynamics (i.e. the time and patterns of natural capital generation by nature as well as the extent ecosystem services support social and economic processes) cannot be stable over time, in that resources may be used up too quickly, inefficiently and without adequate matching of resource quality to use. In so doing, cleaner production and consumption processes are not the main resource use modality so that increased and cheaper trade only leads to faster resource degradation and depletion. Moreover, in order to identify the driving forces of promoting China-Japan trade, a decomposition analysis approach is applied. Although decomposition analysis was previously used to explore the key factors in emergy studies of region or specific production systems (Ghisellini et al., 2014; Zhang et al., 2014; Zucaro et al., 2014), no peer reviewed publication has combined emergy accounting with decomposition analysis to investigate trade issues between China and Japan. Consequently, this paper aims at investigating resource flows and driving forces of China-Japan trade so that a biophysical methodological approach for trade sustainability assessment can be tested. All in all, this study explores emergy accounting for identifying imbalance of resource exchanges from the biosphere point of view (biosphere support, ecosystem services, renewability), and complements the conventional monetary accounting procedures; besides that, after identifying the driving factors of resources exchange within China-Japan trade, implements for equitable trade policy-making and international stability are proposed. This paper is structured as follows. After this introduction section, Section 2 presents research methods, including a short description of China-Japan trade, a detailed introduction of emergy accounting and decomposition analysis, as well as data sources used in this study. Section 3 presents the research results. Section 4 discusses related policy implications. Section 5 concludes the whole paper. 2. Methods and data 2.1. Emergy accounting approach Emergy accounting (EMA) is a measure of environmental work displayed by the biosphere to generate resources and ecosystem services, and quantify energy, materials, labor and money investments within a process (Brown and Ulgiati, 2011; Geng et al., 2013; Lou and Ulgiati, 2013; Odum, 1996; Tian et al., 2016). By applying emergy accounting, it is possible to quantify how much environmental support is needed to generate a unit (and hence the totality) of a product flow or service or economic wealth within a country (Tian et al., 2016). By definition, emergy is the available energy of one kind (in general of the solar kind) required directly or indirectly to make a product or provide a service (Odum, 1996). The emergy concept of cumulative embodiment over a product supply chain supports the idea that something has a value according to what was invested into making it. In order to quantify the cumulative investment of solar equivalent, available energy, emergy accounting converts different energy and mass inflows to a system or process into a common basis (solar equivalent Joules, or solar emjoules, sej). The added value lies in its ability to include in the calculation the time embodied in resources (time for their generation by biosphere processes), the renewable resources that support ecosystem services even if not directly captured by humans through technological devices, the indirect environmental support

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361

Table 1 Import and export trade volume of China-Japan trade from 2000 to 2012 (unit: USD). Items

2000

Agriculture Livestock Forestry Fisheries Raw minerals Energy Metals Industry products Total

2005

2008

Export

Import

Export

Import

Export

Import

Export

7.06Eþ08 1.30Eþ09 3.70Eþ08 1.37Eþ08 1.54Eþ08 4.64Eþ09 2.32Eþ08 3.36Eþ10 4.12Eþ10

2.32Eþ09 1.70Eþ09 9.78Eþ08 1.96Eþ09 8.34Eþ08 2.13Eþ09 1.97Eþ09 2.96Eþ10 4.15Eþ10

8.10Eþ08 1.23Eþ09 1.27Eþ09 1.71Eþ08 3.68Eþ08 1.17Eþ10 1.29Eþ09 8.30Eþ10 9.98Eþ10

3.62Eþ09 2.13Eþ09 1.74Eþ09 2.83Eþ09 1.23Eþ09 5.66Eþ09 3.11Eþ09 6.29Eþ10 8.33Eþ10

6.82Eþ08 9.88Eþ08 2.15Eþ09 1.81Eþ08 8.40Eþ08 1.94Eþ10 4.80Eþ09 1.22Eþ11 1.51Eþ11

3.40Eþ09 2.24Eþ09 1.89Eþ09 2.68Eþ09 1.60Eþ09 8.90Eþ09 4.76Eþ09 9.13Eþ10 1.17Eþ11

5.41Eþ08 1.18Eþ09 3.02Eþ09 1.60Eþ08 8.87Eþ08 2.01Eþ10 2.11Eþ09 1.50Eþ11 1.78Eþ11

5.06Eþ09 3.56Eþ09 2.40Eþ09 4.01Eþ09 1.82Eþ09 8.96Eþ09 2.47Eþ09 1.24Eþ11 1.52Eþ11

to labor and services displayed over the entire supply chain of goods and commodities within an economy. In particular, emergy embodied in labor and services takes into account the resource investment in know-how, education, training and infrastructure. All of these categories of environmental costs are generally not fully taken into account by other biophysical accounting methods. The annual emergy used within a country's economy (U) can by divided by the total GDP generated to yield the Emergy-to-Money ratio (EMR), a measure of emergy intensity of the economic process, in other words e a measure of the efficiency of the economic process in converting resources into monetary wealth. Money flows can be converted into their supporting emergy flows by multiplying them by the EMR, and vice versa. Therefore, the EMR also expresses the average amount of emergy that can be purchased in a country by spending one unit of its currency (see Eqn. (3) below). In general, industrialized countries have low EMR due to high monetary circulation, while instead developing countries have high EMR due to low monetary circulation and high availability of primary resources. This makes trade favorable to countries that purchase primary resources and sell manufactured resources (Bargigli et al., 2004; Lou and Ulgiati, 2013; Odum, 1996; Pereira et al., 2013). The emergy imbalance in trade indicates an unequal appropriation of natural capital, generation time, ecosystem services and technological and social information by one of the trade partner countries. It refers to lack of equitable tradeoff of work potential, environmental support to the economy, possibility to create jobs and potential environmental impacts during resource processing. All of these are not easily expressed by monetary flows and remains hidden within the well-known concept of monetary terms of trade. Therefore, emergy can be used as a complement of economic evaluations and identify embodied resource flows exchanged in trade. There are mainly two steps in order to apply emergy for assessing the sustainability of trade. Firstly, all matters, energy and money flows are converted into their solar emergy equivalents, by multiplying the available energy or mass by a suitable Unit Emergy Value (UEV). UEVs are an indirect measure of the total environmental support (emergy) needed to generate a unit of product flow or storage and therefore act as conversion factors over the processing chain. When highly aggregated categories are analyzed, average UEVs can be used. Secondly, emergy indices are calculated in order to evaluate and interpret the trade performance of the investigated countries. In this study, four emergy trade indicators are applied for evaluating performance of China- Japan trade, defined as follows. (1) Exchange Emergy Ratio (EER)

EER ¼

2012

Import

Exported emergy Imported emergy

(1)

EER describes the general benefit within a trade relation: if the ratio is higher than one, that means the country under study exports more resources to its trade partner (measured in emergy units, not in monetary units), and its trade partner gains more work potential from resources received. In general, EER is calculated on a yearly basis. (2) Emergy Dependency (EmDep)

EmDep ¼

Imported emergy  100% Total emergy U of importing country

(2)

EmDep expresses how many percentage of a country's annual emergy use (U) is imported from a given trade partner. It helps understand the importance of this trade partner within the framework of the entire resource availability to the importing country. (3) Emergy Benefit Ratio (EBR)

EBR ¼

Imported emergy Money paid  EMR of importing country

(3)

EBR compares the emergy of raw and processed resources imported in a trade relationship to the emergy associated to the money paid for. The indicator is clarified in Fig. 1. Since money (GDP) is generated within the importing country's economy by using the emergy resources that are annually available (with an EMR intensity factor), the opposite is also true, i.e. the exporting country may in turn use the money received for trade in order to purchase needed resources from the country where money comes from. Benefit largely depends on the EMR of importing country. (4) Opportunity Ratio (OR)

OR ¼

ðExported emergy=EMR of exporting countryÞ Exported Trade VolumeðUSDÞ

(4)

OR compares the GDP growth potentially achievable if resources were processed within a country, instead of being exported, to the money actually received for exports. The rationale of this indicator is that, at least virtually, resources can be processed within the country of extraction instead of being sold at a low price. Processing inside may generate jobs and yield products that can be sold at a higher price. Of course, it also generates environmental emissions as a side negative outcome. It is evident that full processing of resources inside the extraction country is not always possible and also may generate conflicts about “global market freedom” (just consider the international controversy about China's limits to exports of rare earth minerals neodymium and dysprosium used for

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wind energy generators worldwide (http://blogs.ei.columbia.edu/ 2012/09/19/rare-earth-metals-will-we-have-enough/; http:// www.globalresearch.ca/shortages-of-rare-minerals-china-sstrategic-control-over-terbium-yttrium-dysprosium-europiumand-neodymium/29033). The indicators aim to disclose an opportunity for alternative use of resources that needs to be suitably understood and managed.

(unit technology factor of the i-th category expressing its emergy intensity); Si ¼ Qi/Q focuses on the contribution of the commodity category Qi to the total export trade volume Q, thus representing the proportion of the i-th commodity in the total commodity trade (unit structure factor). Equations (7)e(9) show how to quantify the three main emergy change drivers of the investigated trade relation.

DEsca ¼

2.2. Index decomposition analysis (IDA)

X i

The decomposition analysis is an important method to explore the most important factors that determine changes of energy and material consumption, carbon emissions, labor demand, and land use in a process or country's economy (Ang and Zhang, 2000; Cialani, 2007; Hoffren et al., 2000; Jungnitz, 2008; Tian et al., 2015; Weinzettel and Kovanda, 2011; Wu et al., 2016). It mainly includes two widely used methods, namely Structure Decomposition Analysis (SDA) and Index Decomposition Analysis (IDA). SDA mainly focuses on Input-Output tables, and the requirement of data is very strict. IDA focuses on both sector or regional level data and therefore it is easier to interpret results and collect data (Ang and Xu, 2013). This study adopted IDA due to such data advantages. IDA was proposed in the late 1970s, mainly in the form of two widely used methods, i.e. the Laspeyres Index Method, and the Logarithmic Mean Divisia Index (LMDI) method (Ang et al., 1998). Compared with Laspeyres Index Method, the LMDI method has a specific advantage that the replacing of the zero value by a small positive number would give satisfactory decomposition results for the LMDI method (Ang, 2004). LMDI is used in the present study in order to analyze the driving forces of emergy changes in export and import trade over time. Emergy changes, DE, in trade can be attributed to three main factors: scale factor (DEsca ), structure factor ðDEstr Þ and technology factor (DEtec ). The total change of emergy in bilateral trade can be calculated by using Equation (5).

DEtot ¼ ER  E0 ¼ DEsca þ DEstr þ DEtec

(5)

where, R and 0 represent the last study year and the first study year, respectively. DEsca represents the contribution of export volume change (scale factor); ðDEstr Þ represents the contribution of export commodity structural change (structure factor); DEtec represents the emergy intensity change (technology factor). Equation (6) shows how to conduct decomposition analysis by using LMDI method

E¼

X i

Q

Qi Ei X  ¼ Q  Si  Ti Q Qi i

(6)

where Q represents the total export volume and refers to the scale factor; Ei is the emergy assigned to the i-th commodity category; Qi indicates the export trade volume of the i-th category; Ta ¼ Ei/Qi

DEstr ¼

DEtec ¼

 R Q ln R 0 Q0 ln Ei  ln Ei EiR  Ei0

X

EiR  Ei0

i

ln EiR  ln Ei0

X

EiR  Ei0

i

ln EiR  ln Ei0

(7)

!

ln

SRi

ln

TiR

(8)

S0i !

Ti0

(9)

2.3. Data collection and treatment In this study China's customs statistics yearbooks for the years 2000, 2005, 2008 and 2012 are used as main data sources. UEVs of commodities are mainly based on published research (BrandtWilliams, 2001; Brown and Bardi, 2001; Lou and Ulgiati, 2013; Odum, 1996; Vilbiss and Brown, 2015). The total emergy use data and the Emergy-to-Money Ratio (EMR) data of Japan are from the National Environmental Accounting Database (NEAD, 2016), developed by the University of Florida, USA. For China, data from NEAD were also compared with (Lou and Ulgiati, 2013). Unfortunately, both sources do not refer to the most recent years (NEAD is updated to 2008, Lou and Ulgiati's referred to 2009). In order to provide a reliable estimation for most recent years, we calculated the EMRs of two countries for the year 2012 through a linear regression method adjusted according to the population and GDP values of each country in 2012 (Parameter R2 ¼ 0.58 in linear regression of Japan's EMR; Parameter R2 ¼ 0.97 in linear regression of China's EMR). In particular, since EMR is defined as the ratio (Total emergy)/GDP, and GDP is known for the year 2012, the unknown variable ends up being the total emergy in 2012, which may be adjusted (increased or decreased) according to the population increase or decrease, assuming a linear relation between emergy use and population between 2000 and 2012. The adjusted value of the total emergy use in 2012 was then divided by the GDP of the year 2012, to yield a sufficiently reliable EMR2012. The GDP values are from World Bank database (WB, 2012). All UEVs were updated to the 12.00Eþ24 sej yr1biosphere emergy baseline calculated by (Brown and Ulgiati, in press). 3. Results 3.1. Flows changes in China-Japan commodity trade

Fig. 1. Traded resource and counter flow of money paid.

To assess embodied resources in China-Japan trade, emergy flows (with and without L&S) during the period 2000e2012 are presented in Table 2. It can be observed that both total import emergy of China, with and without L&S, show increasing trends during the investigated period, increased by 2.56 times and 2.31 times, respectively. Different import items show different trends. For example, industrial products are the category with the highest increase, while agriculture and livestock products experienced decreasing trends. Concerning export emergy, total export emergy of China

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363

Table 2 Emergy flows of trade (with and without L&S) during 2000 and 2012 (unit: sej). Items Import Agriculture Livestock Forestry Fisheries Raw mineral Energy Metals Industry products Service in import Total import (with L&S) Total import (with without L&S) Export Agriculture Livestock Forestry Fisheries Raw mineral Energy Metals Industry products Service in export Total export (with L&S) Total export (with without L&S)

2000

2005

2008

2012

2.27Eþ21 1.11Eþ22 9.18Eþ20 4.15Eþ20 3.39Eþ19 3.08Eþ21 3.73Eþ20 1.33Eþ23 5.62Eþ22 2.07Eþ23 1.51Eþ23

2.25Eþ21 1.05Eþ22 9.82Eþ21 8.62Eþ20 1.67Eþ20 1.24Eþ22 7.98Eþ20 2.73Eþ23 1.44Eþ23 4.53Eþ23 3.09Eþ23

1.56Eþ21 7.19Eþ21 9.91Eþ21 8.27Eþ20 1.76Eþ20 1.80Eþ22 8.92Eþ20 4.11Eþ23 2.17Eþ23 6.67Eþ23 4.50Eþ23

7.91Eþ20 5.86Eþ21 1.31Eþ22 5.45Eþ20 9.60Eþ19 7.37Eþ21 4.31Eþ20 5.11Eþ23 1.48Eþ23 6.87Eþ23 5.39Eþ23

3.86Eþ21 1.67Eþ22 5.07Eþ20 4.23Eþ21 1.73Eþ21 6.52Eþ22 5.03Eþ20 1.33Eþ23 3.10Eþ23 5.36Eþ23 2.26Eþ23

6.87Eþ21 1.99Eþ22 2.18Eþ21 4.63Eþ21 2.39Eþ21 5.39Eþ22 4.07Eþ20 2.25Eþ23 5.51Eþ23 8.66Eþ23 3.15Eþ23

5.13Eþ21 1.72Eþ22 3.12Eþ21 4.26Eþ21 2.29Eþ21 2.96Eþ22 2.87Eþ20 3.00Eþ23 5.22Eþ23 8.83Eþ23 3.62Eþ23

3.77Eþ21 1.90Eþ22 6.61Eþ20 4.89Eþ21 2.28Eþ21 1.71Eþ22 2.28Eþ20 2.48Eþ23 1.45Eþ24 1.75Eþ24 2.96Eþ23

Footnotes about traded categories: See Appendix.

(without L&S) increased from 2000 to 2008 and then decreased from 2008 to 2012, while total export emergy of China (with L&S) increased over the entire period. For the different export items, the industrial products experienced the highest increase, while metals and energy decreased. In addition, comparing exports with imports (without L&S), it is clear that the total trade in China experienced net export in 2000 and 2005, with figures of 7.46Eþ22 sej and 5.76Eþ21 sej, respectively. Conversely, total trade in China experienced net import in 2008 and 2012, with figures of 8.82Eþ22 sej and 2.43Eþ23 sej respectively. Instead, trade emergy values in China (with L&S) always experienced net export for the entire investigated period.

3.2. Emergy based assessment of China-Japan commodity trade In order to evaluate the real trade benefits from bio-sphere perspective, the above-mentioned emergy indicators were

6.00 5.00

EER

4.00

adopted, including Exchange Emergy Ratio (EER), Emergy Dependency (EmDep), Emergy Benefit Ratio (EBR) and Opportunity Ratio (OR). From the point of view of total trade benefit, the ratio of EER without L&S (emergy export/emergy import) is depicted in Fig. 2. The total EER of trade presents decreasing trends from 2000 to 2012, especially with values of higher than 1 in years 2000 and 2005 and lower than 1 in years 2008 and 2012, indicating that China shifted from a net emergy export country to a net import country for the China-Japan commodity trade. Fig. 2 also shows the structure of EER, in which the EER of manufactured products for China presents net emergy import, while the EER of primary products for China presentss net emergy export. Such results imply that China exported more emergy to Japan through exporting primary resources, and imported embodied emergy resources from Japan through importing more industrial products. Ratios with L&S is shown in Fig. 3. In terms of Emergy Dependency (EmDep), the EmDeps of China (without L&S) accounted for 1.69%, 2.07%, 2.21% and 0.67%, respectively in the years 2000, 2005, 2008 and 2012. Instead, the EmDeps of Japan (without L&S) accounted for 3.55%, 4.78%, 5.13% and 5.97%, respectively in the same years, indicating that Japan relied more on its trade relation with China. The Emergy Benefit Ratios (EBR) of China-Japan trade are listed in Table 3. It is clear that Japan received much more benefits than

3.00 8.00

2.00

7.00 6.00

1.00

EER

5.00

0.00 2000 Primary products

2005

2008 manufacture products

2012

Primary products

4.00

manufacture products

3.00

Total

Fig. 2. The Emergy Exchange Ratio (EER ¼ Emergy Exports/Emergy Imports) of Chinese trade from 2000 to 2012 (without L&S). EERs of primary products indicates dominance of exports from China to Japan (although declining over time), while the opposite is true for manufactured products (EERs < 1).

Total

2.00 1.00 0.00 2000

2005

2008

2012

Fig. 3. China's exchange emergy ratio (EER) from 2000 to 2012 (with L&S).

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Table 3 The emergy benefit ratio (EBR) of China and Japan from 2000 to 2012 (without L&S). Items

2000

2005

2008

2012

Table 5 The opportunity ratio (OR) of China and Japan from 2000 to 2012 (without L&S). Items

2000

China Japan China Japan China Japan China Japan Agriculture Livestock Forestry Fisheries Raw mineral Energy Metals Industry products Total

0.43 1.14 0.33 0.41 0.03 1.78 0.01 0.53 4.65

1.22 7.23 0.38 1.58 1.52 24.21 0.17 3.30 39.62

0.48 1.22 4.01 0.95 0.16 8.09 0.03 1.23 16.16

1.32 6.46 0.87 1.13 1.35 12.03 0.05 2.48 25.68

0.51 1.63 1.03 1.03 0.05 0.84 0.01 0.76 5.85

1.05 5.32 1.15 1.10 1.00 4.32 0.02 2.28 16.24

0.15 0.52 0.45 0.36 0.01 0.37 0.01 0.36 2.22

0.90 6.39 0.33 1.46 1.51 8.32 0.03 2.41 21.36

China, with approximately 8.52, 1.59, 2.77 and 9.61 times higher than China's in years of 2000, 2005, 2008, 2012, respectively. When the EBR is more than 1, the import emergy is higher than the average emergy returned to the exporting country via the money received. The opposite is true when EBR is less than 1. It is worth noting that in some cases both countries achieved an EBR with more than 1, indicating the emergy of the traded product is higher than the emergy embodied in the money paid for (market does not adequately value the commodity); in other cases, EBR is less than 1 for both countries, suggesting a very high price paid compared to the emergy content (market overvaluing the resource) and in several cases only one partner benefits (EBR > 1), while the other partner definitely lost (EBR < 1), due to the combined effect of market prices, EMRs and emergy values of the commodities (primary or manufactured). Ratios with L&S are shown in Table 4. The Opportunity Ratios (OR) for China-Japan trade are listed in Table 5. If China processed inside the country the (primary) commodities instead of exporting them, this would generate a GDP increase depending to the state of its economy in a given year (expressed by the EMR). If the emergy exported from China (sej) is divided by the EMRChina (sej/$), a “virtual” amount of GDP increase could be obtained, to be compared to the real money received for actual export [see Eqn. (4)]. An OR with a figure more than 1 indicates a net benefit in processing domestically, while an OR with a figure of less than 1 indicates the opposite effect. Similar to previous indicators, such values depend on the combined effect of the emergy values of traded commodities, the EMRs of the country and the actual prices paid for, so that the real benefits only show up for some commodities (no matter primary or manufactured) in each country. According to Table 5, this virtual GDP increase for China would have amounted to about 7.23 times, 5.60 times, 5.23 times and 1.86 times the actual increase due to exports, in the years 2000, 2005, 2008 and 2012 respectively, at the scale of total trade. In a similar manner, the virtual GDP increase for Japan would have been approximately 25.48 times, 26.03 times, 18.16 times and 25.50 times higher than the actual income from export, in the years 2000,

2005

2008

2012

China Japan China Japan China Japan China Japan Agriculture Livestock Forestry Fisheries Raw mineral Energy Metals Industry products Total trade

0.22 1.32 0.07 0.29 0.28 4.42 0.03 0.60 7.23

2.36 6.23 1.82 2.22 0.16 9.73 0.06 2.90 25.48

0.29 1.41 0.19 0.25 0.29 2.62 0.01 0.54 5.60

1.93 5.93 5.36 3.50 0.31 6.67 0.05 2.28 26.03

0.34 1.72 0.37 0.36 0.32 1.39 0.01 0.73 5.23

1.58 5.05 3.21 3.18 0.15 2.61 0.03 2.35 18.16

0.08 0.56 0.03 0.13 0.13 0.73 0.01 0.21 1.86

1.76 5.99 5.21 4.08 0.13 4.21 0.03 4.10 25.50

Table 6 Opportunity ratio (OR) of China and Japan from 2000 to 2012 (with L&S). Items

2000

Agriculture Livestock Forestry Fisheries Raw minerals Energy Metals Industry products Total

1.22 2.32 1.07 1.29 1.28 5.42 1.03 1.60 15.23

2005

2008

2012

China Japan China Japan China Japan China Japan 3.36 7.23 2.82 3.22 1.16 10.73 1.06 3.90 33.48

1.29 2.41 1.19 1.25 1.29 3.62 1.01 1.54 13.60

2.93 6.93 6.36 4.50 1.31 7.67 1.05 3.28 34.03

1.34 2.72 1.37 1.36 1.32 2.39 1.01 1.73 13.23

2.58 6.05 4.21 4.18 1.15 3.61 1.03 3.35 26.16

1.08 1.56 1.03 1.13 1.13 1.73 1.00 1.21 9.86

2.76 6.99 6.21 5.08 1.13 5.21 1.03 5.10 33.50

2005, 2008 and 2012, respectively. Ratios with L&S are shown in Table 6.

3.3. Driving forces for trade emergy changes In order to explore the driving forces of trade emergy changes of China-Japan trade over time, LMDI method was adopted by using Equations (6)e(9) mentioned in section 2.3. According to the trade emergy volume changes during 2000e2012, this study divides the investigated period into three phases: phase one (2000e2005), phase two (2005e2008), and phase three (2008e2012). The time evolution of the absolute values of trade volume and emergy flows are shown in Tables 1 and 2, including total export trade volumes (Q), export emergy (Ei ), and export trade volumes of each kind of commodity (Qi ). Table 7 shows the performance parameters over time. The positive or negative contributions of three driving factors are listed in Table 8. Finally, Fig. 4 shows a diagram with trends of driving factors (for imports and exports without L&S). The driving forces of export and import emergy (with L&S) are presented in Fig. 5. Focusing on drivers of emergy export from China to Japan (Fig. 4a), the contributions in the three phases were very different.

Table 4 Emergy benefit ratio (EBR) of China and Japan from 2000 to 2012 (with L&S). Items

Agriculture Livestock Forestry Fisheries Raw minerals Energy Metals Industry products Total

2000

2005

2008

2012

China

Japan

China

Japan

China

Japan

China

Japan

0.61 1.32 0.51 0.59 0.21 1.96 0.19 0.71 6.11

6.70 12.71 5.86 7.06 7.00 29.69 5.65 8.78 83.44

0.64 1.51 1.39 0.98 0.29 1.67 0.23 0.71 7.42

5.90 11.05 5.46 5.72 5.94 16.62 4.64 7.07 62.38

0.83 1.95 1.36 1.35 0.37 1.16 0.33 1.08 8.43

4.15 8.43 4.25 4.20 4.10 7.42 3.12 5.38 41.05

0.24 0.61 0.54 0.44 0.10 0.45 0.09 0.44 2.92

12.36 17.86 11.80 12.93 12.97 19.79 11.50 13.88 113.10

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Table 7 Trends of driving factors of export emergy in 2000e2012 trade. Trend of driving factors

2000

China's export Agriculture Livestock Forestry Fisheries Raw mineral Energy Metals Industry products Japan's export Agriculture Livestock Forestry Fisheries Raw mineral Energy Metals Industry products

Q 4.15Eþ10 4.15Eþ10 4.15Eþ10 4.15Eþ10 4.15Eþ10 4.15Eþ10 4.15Eþ10 4.15Eþ10 Q 4.12Eþ10 4.12Eþ10 4.12Eþ10 4.12Eþ10 4.12Eþ10 4.12Eþ10 4.12Eþ10 4.12Eþ10

2005 Si 0.06 0.04 0.02 0.05 0.02 0.05 0.05 0.71 Si 0.02 0.03 0.01 0.01 0.01 0.01 0.11 0.82

Ti 1.67Eþ12 9.87Eþ12 5.18Eþ11 2.16Eþ12 2.07Eþ12 3.30Eþ13 2.36Eþ11 4.50Eþ12 Ti 3.22Eþ12 8.51Eþ12 2.48Eþ12 3.04Eþ12 2.21Eþ11 1.33Eþ13 8.04Eþ10 3.96Eþ12

Q 8.33Eþ10 8.33Eþ10 8.33Eþ10 8.33Eþ10 8.33Eþ10 8.33Eþ10 8.33Eþ10 8.33Eþ10 Q 9.98Eþ10 9.98Eþ10 9.98Eþ10 9.98Eþ10 9.98Eþ10 9.98Eþ10 9.98Eþ10 9.98Eþ10

2008 Si 0.04 0.03 0.02 0.03 0.01 0.04 0.07 0.76 Si 0.01 0.01 0.01 0.01 0.01 0.01 0.12 0.83

Ti 1.90Eþ12 9.32Eþ12 1.25Eþ12 1.63Eþ12 1.95Eþ12 1.74Eþ13 7.19Eþ10 3.57Eþ12 Ti 2.78Eþ12 8.55Eþ12 7.73Eþ12 5.05Eþ12 4.54Eþ11 9.62Eþ12 6.84Eþ10 3.29Eþ12

Q 1.17Eþ11 1.17Eþ11 1.17Eþ11 1.17Eþ11 1.17Eþ11 1.17Eþ11 1.17Eþ11 1.17Eþ11 Q 1.51Eþ11 1.51Eþ11 1.51Eþ11 1.51Eþ11 1.51Eþ11 1.51Eþ11 1.51Eþ11 1.51Eþ11

2012 Si 0.03 0.02 0.02 0.02 0.01 0.04 0.08 0.78 Si 0.01 0.01 0.01 0.01 0.01 0.03 0.13 0.81

Ti 1.51Eþ12 7.67Eþ12 1.65Eþ12 1.59Eþ12 1.43Eþ12 6.22Eþ12 3.22Eþ10 3.28Eþ12 Ti 2.28Eþ12 7.27Eþ12 4.62Eþ12 4.58Eþ12 2.09Eþ11 3.75Eþ12 4.60Eþ10 3.38Eþ12

Q 1.52Eþ11 1.52Eþ11 1.52Eþ11 1.52Eþ11 1.52Eþ11 1.52Eþ11 1.52Eþ11 1.52Eþ11 Q 1.78Eþ11 1.78Eþ11 1.78Eþ11 1.78Eþ11 1.78Eþ11 1.78Eþ11 1.78Eþ11 1.78Eþ11

Si 0.03 0.02 0.02 0.03 0.01 0.02 0.06 0.81 Si 0.01 0.01 0.02 0.01 0.01 0.01 0.11 0.84

Ti 7.45Eþ11 5.32Eþ12 2.76Eþ11 1.22Eþ12 1.25Eþ12 6.93Eþ12 2.54Eþ10 2.01Eþ12 Ti 1.46Eþ12 4.98Eþ12 4.33Eþ12 3.40Eþ12 1.08Eþ11 3.50Eþ12 2.15Eþ10 3.41Eþ12

Footnote: Q indicates total export trade volume in each given year, unit: USD; Si refers to export trade volume of the i-th commodity category divided by total export trade volume; Ti equals to export emergy of the i-th commodity category divided by export trade volume of the same category, unit: sej/USD.

The total contribution of the three factors in each phase showed a decreasing trend from phase one to phase three, with the contribution of phase one being the highest (around DE1 ¼ 4.14Eþ23 sej), and the contribution of phase three the smallest (around DE3 ¼ 2.77Eþ23 sej), the latter mainly due to technology factor increase. The scale factor was the biggest driver for emergy change in all phases and made positive contributions in the entire investigated period although with a decreasing trend from phase one to phase three. Technology was the second largest driver of emergy changes and played a key role in reducing emergy export from China to Japan. Finally, compared with these two factors, structure did not make any significant contribution over the investigated years, with marginal contribution to decrease the total trade change for the periods 2000e2005 and 2008e2012, and with marginal contribution to increase the total trade change for the period 2005e2008. Likewise, for emergy export from Japan to China (Fig. 4b), the total contribution showed an increasing trend from phase one to phase three. The contribution in phase three is the largest fraction of the total, accounting for 6.05Eþ23 sej, while the contribution in phase one is the smallest with a figure of 5.09Eþ23 sej. Scale factor was the largest driver, showing an increasing trend from phase one to phase three, with positive impacts in all phases; technology factor also played a significant role, but becoming weaker in most recent years; structure impact was marginal, showing negative impact during phase one and two, but a positive one in phase three. 4. Policy implications From a monetary perspective, China presented a trade deficit during 2000e2012. From an emergy perspective, China presented a net resource export in 2000 and 2005, while showing a net resource import in 2008 and 2012 (without inclusion of labor and

services). But when labor and service are included, China presented a resource net export for the entire period of 2000e2012. The additional emergy from L&S may be firstly attributed to increased living standard in China, requiring higher emergy support to L&S. For some categories (mainly primary commodities, e.g. energy), the labor intensity contributed to the calculated additional emergy. Finally, for other commodities (such as refined metals, industrial products), a significant contribution came from emergy supporting highly skilled labor forces. Such results indicate that assessing trade benefits only by means of monetary indicators cannot evaluate the true contributions of resources to international trade. The emergy accounting method was employed in this study to assess the environmental balance of China-Japan trade. The emergy method provides a complementary measure to monetary evaluations. While mass-based trade measures may not appear very telling, albeit large masses may involve huge environmental loadings, extraction and transport, emergy-based losses should be the real concern in trade relations. Emergy-based losses may involve loss of work potential, environmental support and economic development ability. A partial consideration of the potential imbalance of trade is also shared by other approaches, such as carbon footprint, exergy or thermo-economical accounting, although they only focus on one specific aspect (e.g. work potential, in the exergy approach; contribution to global warming in carbon footprint, etc) and disregard the past biosphere work as a factor affecting the overall quality of resources. Such special comprehensiveness of the emergy approach is confirmed by a large number of papers published in the last years (Bargigli et al., 2004; Lou and Ulgiati, 2013; Pereira et al., 2013; Geng et al., 2013; Zucaro et al., 2014; among others) and make emergy a sufficiently bold method to address issues of resource quality, environmental sustainability and equity of trade. By means of its built-in assessment of environmental concentration and embodied time, the emergy approach goes beyond the

Table 8 Positive or negative contributions of each driving factor in different phases. 2000e2005

Scale factor Technology factor Structure factor Total contribution

2005e2008

2008e2012

China's export

Japan's export

China's export

Japan's export

China's export

Japan's export

5.10Eþ23 7.99Eþ22 1.61Eþ22 4.14Eþ23

5.45Eþ23 3.41Eþ22 1.88Eþ21 5.09Eþ23

4.76Eþ23 6.91Eþ22 2.06Eþ21 4.09Eþ23

5.78Eþ23 1.19Eþ22 2.10Eþ21 5.64Eþ23

4.29Eþ23 1.46Eþ23 5.53Eþ21 2.77Eþ23

5.97Eþ23 1.47Eþ21 9.29Eþ21 6.05Eþ23

X. Tian et al. / Journal of Cleaner Production 141 (2017) 359e369

Export Emergy unit: sej

6E+23

(a)

Import Emergy unit: sej

366

5E+23 4E+23

3E+23 2E+23 1E+23 0 -1E+23

2000-2005 2005-2008 2008-2012

-2E+23

(b) 7E+23 6E+23 5E+23 4E+23 3E+23 2E+23 1E+23 0 -1E+23 2000-2005 2005-2008 2008-2012 Scale Technology Structure Total

Fig. 4. Drivers of changes of emergy trade (without L&S) in China's exports (a) and imports (b).

reductionistic picture of looking at one characteristic per time and generates a global understanding of the role and diversity of resources within an economic system and its relation with other interacting systems. Therefore, more comprehensive evaluation methods which combine both biophysical and economic perspectives are needed to complement monetary description of trade dynamics, in so supporting the relevant governmental departments to formulate policies for sustainable resources management. Also, labor and services are important embodied aspects of the economy. When labor and services are included, China was a net resources exporter, due to more labor and services embodied in China's commodities than Japan's. Due to the different levels of economic development and resource endowment, China mainly exports resource intensive and labor intensive products to Japan, while Japan mainly exports capital intensive and technology intensive products. Such a trade pattern led to imbalanced exchanges of embodied resources between China and Japan. Taking labor productivity in manufacturing industry as an example, the labor productivity in Japan was about 23e24 percent of the US level (¼$ 1.24 per hour), while the labor productivity in China was less than 7 percent of the US level (Yuan et al., 2010). In Japan, almost all heavy or “commodity producing” sectors had higher labor productivity than light or “commodity consuming” sectors. In China, only “wood” and “building materials” sectors had higher labor productivity than the average manufacturing sector (Yuan et al., 2010). If taking labor productivity as a conventional measure of economic efficiency, this means the efficiency of commodity production in Japan is higher than in China. It helps explain why China was a net resources exporter when labor and services are included. In order to fill such a gap, it is urgent to implement policies that improve labor skills in all the Chinese economic sectors through capacity building efforts. From a commodity structure perspective, China exported more primary resources to Japan, while Japan exported more industrial resources to China, due to different economic development levels

(a)

8E+23 6E+23 4E+23 2E+23 0 2000-2005 2005-2008 2008-2012 -2E+23

(b)

2.5E+24 Export emergy unit: sej

Import emergy unit: sej

1E+24

and resource endowments. China is rich in resources and labor, while Japan (less rich with primary resources) has to develop advanced technologies and skills in order to respond its limited resources reserve. It is normal that each country chooses to purchase those commodities that can increase its economic competitiveness when it engages in foreign trade. The emergy trade indicators, such as EBR and OR, can help identify the benefits associated to specific commodities in each country. For instance, in order to decrease the potential GDP loss, both countries should adjust their export structures according to the results of emergybased indicators, even within the existing market dynamics. In the case of China-Japan trade, Japan is the country more dependent on China's resource, indicating that Japan should diversify its import policies on natural resources. From a driving factors perspective, scale and technology factors are important for both partners, while structure factor only played a marginal role and can be neglected. Such results indicate that future trade policies should focus on how to control the overall scales and improve technologies. Trade is not sustainable if one country always takes advantage over another, leading to the need of appropriate compensation measures. For instance, technology transfer can help those developing countries grasp cutting-edge technologies so that they can process more resources domestically. Another example is that resources-importing countries may provide financial support to rescue the degraded ecosystems in the developing countries due to mining activities so that ecosystem services can be recovered in such areas. Otherwise, the degraded ecosystem in developing countries may eventually threaten the global ecosystem. Of course, the developing countries should support technological innovation by themselves. In this regard, innovative efforts, such as eco-design, cleaner production, process integration, industrial symbiosis, eco-industrial parks, sustainable consumption and regional implementation of circular economy, should be further promoted so that the overall eco-efficiency of their economies can be improved.

2E+24 1.5E+24

Scale Technology

1E+24

Structure

5E+23

Total

0 2000-2005 2005-2008 2008-2012 -5E+23

Fig. 5. Drivers of changes of emergy trade (with L&S) in China's exports (a) and imports (b).

X. Tian et al. / Journal of Cleaner Production 141 (2017) 359e369

5. Conclusions

Appendix

China and Japan are the most important economies in the world, listed as top 2 and 3 globally. The trade relations are very close with huge amounts of commodities exchanged between the two countries. However, no studies have been undertaken to uncover the embodied resources exchanges between the two countries. Under such a circumstance, emergy accounting and LMDI methods were applied to evaluate the real benefits of resources exchanges between the two countries. The imbalance of ChinaJapan resource exchanges from a biosphere value point of view (biosphere support, ecosystem services, natural capital, renewability) and the importance of an emergy assessment of trade to complement the conventional monetary accounting procedures are clearly shown in this study, by also identifying the main factors driving the evolution of China-Japan trade over time. Suggestions for equitable trade policy-making and international stability are also proposed. Results show the trade complex nature beyond the monetary accounting. In emergy terms, China experienced a decreasing trend of its EER (export/import ratio), shifting from a net exporter to a net importer without considering L&S. The inclusion of L&S changes the picture, making China a net exporter for the entire study period, since the emergy values for supporting L&S increased over the entire study period. Emergy-based indicators further help understand the interplay of monetary and biophysical values so that the true benefits of China-Japan trade can be revealed. Scale and technology factors are the dominating drivers to induce the rapid development of China-Japan trade, while structure factor only played a marginal role. Such results indicate that future trade policies should address the imbalanced embodied resources exchanges among the two countries. Appropriate measures include technology transfer and financial aids to compensate ecosystem losses in the mining sites of export countries. Although this study focuses on China-Japan trade, it has valuable policy implications to many other foreign trade partners, especially those between developed and developing countries. The proposed measures can help those decision makers to prepare feasible trade policies so that sustainable resource management can be achieved globally. Some limitations to this research provide challenges for future research. In fact, our results do not aim to limit international trade, but suggest that other measures be added for more comprehensive understanding and implementation of trade benefits and stability as well as for compensation of the less favored partner in bilateral trade. Moreover, if the dyadic trade relationship become clear, a more global perspective may emerge, beyond bilateral agreements towards multi-player partnership. Finally, the emergy cost of infrastructure and services supporting the various assets such as e for example - culture, know-how, broadcasting, the banking system services, require better understanding in terms of their resource use in order to provide more effective support to non-monetary evaluations.

Footnotes of traded categories in Table 2

Acknowledgements This study is funded by the Natural Science Foundation of China (71461137008, 71325006). Sergio Ulgiati also acknowledges the contract by the School of Environment, Beijing Normal University, within the framework of the National “One Thousand Foreign Experts Plan” as well as the financial support received from the EU Project EUFORIE e European Futures for Energy Efficiency, funded under EU Horizon 2020 programme, call identifier H2020-EE-20142-RIA, topic EE-12-2014, Socio-economic research on energy efficiency.

367

Imports 1. Imported Agriculture. 2000: 2.36Eþ08 kg (CCSY, 2000); average UEV ¼ 9.64Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 2.40Eþ08 kg (CCSY, 2005); average UEV ¼ 9.37Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 1.56Eþ08 kg (CCSY, 2008); average UEV ¼ 9.94Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 7.81Eþ07 kg (CCSY, 2012); average UEV ¼ 1.01Eþ10 sej/g (Vilbiss and Brown, 2015). 2. Imported Livestock. 2000: 4.16Eþ08 kg (CCSY, 2000); average UEV ¼ 2.66Eþ10 sej/g (Vilbiss and Brown, 2015). 2005: 3.89Eþ08 kg (CCSY, 2005); average UEV ¼ 2.70Eþ10 sej/g (Vilbiss and Brown, 2015). 2008: 2.37Eþ08 kg (CCSY, 2008); average UEV ¼ 3.03Eþ10 sej/g (Vilbiss and Brown, 2015). 2012: 2.32Eþ08 kg (CCSY, 2012); average UEV ¼ 2.53Eþ10 sej/g (Vilbiss and Brown, 2015). 3. Imported Forestry. 2000: 2.01Eþ08 kg (CCSY, 2000); average UEV ¼ 4.57Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 3.37Eþ09 kg (CCSY, 2005); average UEV ¼ 2.91Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 3.36Eþ09 kg (CCSY, 2008); average UEV ¼ 2.95Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 4.44Eþ09 kg (CCSY, 2012); average UEV ¼ 2.95Eþ09 sej/g (Vilbiss and Brown, 2015). 4. Imported Fisheries. 2000: 4.72Eþ07 kg (CCSY, 2000); average UEV ¼ 8.79Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 1.06Eþ08 kg (CCSY, 2005); average UEV ¼ 8.16Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 1.12Eþ08 kg (CCSY, 2008); average UEV ¼ 7.41Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 8.76Eþ07 kg (CCSY, 2012); average UEV ¼ 6.22Eþ09 sej/g (Vilbiss and Brown, 2015). 5. Imported raw mineral. 2000: 7.42Eþ08 kg (CCSY, 2000); average UEV ¼ 4.57Eþ07 sej/g (Vilbiss and Brown, 2015). 2005: 1.36Eþ09 kg (CCSY, 2005); average UEV ¼ 1.23Eþ08 sej/g (Vilbiss and Brown, 2015). 2008: 1.51Eþ09 kg (CCSY, 2008); average UEV ¼ 1.17Eþ08 sej/g (Vilbiss and Brown, 2015). 2012: 1.32Eþ09 kg (CCSY, 2012); average UEV ¼ 7.26Eþ07 sej/g (Vilbiss and Brown, 2015). 6. Imported Metals. 2000: 6.91Eþ09 kg (CCSY, 2000); average UEV ¼ 5.40Eþ07 sej/g (Vilbiss and Brown, 2015). 2005: 1.08Eþ10 kg (CCSY, 2005); average UEV ¼ 7.36Eþ07 sej/g (Vilbiss and Brown, 2015). 2008: 1.08Eþ10 kg (CCSY, 2008); average UEV ¼ 8.24Eþ07 sej/g (Vilbiss and Brown, 2015). 2012: 1.04Eþ10 kg (CCSY, 2012); average UEV ¼ 4.15Eþ07 sej/g (Vilbiss and Brown, 2015). 7. Imported Energy. 2000: 8.92Eþ08 kg (CCSY, 2000); average UEV ¼ 3.45Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 3.60Eþ09 kg (CCSY, 2005); average UEV ¼ 3.45Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 5.23Eþ09 kg (CCSY, 2008); average UEV ¼ 3.45Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 2.12Eþ09 kg (CCSY, 2012); average UEV ¼ 3.47Eþ09 sej/g (Vilbiss and Brown, 2015). 8. Imported Industry products. 2000: 4.36Eþ10 kg (CCSY, 2000); average UEV ¼ 3.05Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 9.34Eþ10 kg (CCSY, 2005); average UEV ¼ 2.92Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 1.49Eþ11 kg (CCSY, 2008); average UEV ¼ 2.76Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 1.89Eþ11 kg (CCSY, 2012); average UEV ¼ 2.70Eþ09 sej/g (Vilbiss and Brown, 2015). 9. Services associated to imports (as money paid for). 2000: 4.12Eþ10 USD (CCSY, 2000); updated Japan EMR ¼ 1.36Eþ12 sej/$ (NEAD, 2016). 2005: 9.98Eþ10 USD (CCSY, 2005); Japan

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EMR ¼ 1.44Eþ12 sej/$ (NEAD, 2016). 2008: 1.51Eþ11 USD (CCSY, 2008); Japan EMR ¼ 1.44Eþ12 sej/$ (NEAD, 2016). 2012: 1.78Eþ11 USD (CCSY, 2012); Japan EMR ¼ 8.32Eþ11 sej/$ (calculated by this study).

Exports 10. Exported Agriculture. 2000: 2.57Eþ09 kg (CCSY, 2000); average UEV ¼ 1.50Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 4.40Eþ09 kg (CCSY, 2005); average UEV ¼ 1.56Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 2.66Eþ09 kg (CCSY, 2008); average UEV ¼ 1.93Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 2.88Eþ09 kg (CCSY, 2012); average UEV ¼ 1.31Eþ09 sej/g (Vilbiss and Brown, 2015). 11. Exported Livestock. 2000: 1.51Eþ09 kg (CCSY, 2000); average UEV ¼ 1.11Eþ10 sej/g (Vilbiss and Brown, 2015). 2005: 1.70Eþ09 kg (CCSY, 2005); average UEV ¼ 1.17Eþ10 sej/g (Vilbiss and Brown, 2015). 2008: 1.54Eþ09 kg (CCSY, 2008); average UEV ¼ 1.11Eþ10 sej/g (Vilbiss and Brown, 2015). 2012: 1.89Eþ09 kg (CCSY, 2012); average UEV ¼ 1.01Eþ10 sej/g (Vilbiss and Brown, 2015). 12. Exported Forestry. 2000: 1.55Eþ09 kg (CCSY, 2000); average UEV ¼ 3.27Eþ08 sej/g (Vilbiss and Brown, 2015). 2005: 1.51Eþ09 kg (CCSY, 2005); average UEV ¼ 1.44Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 1.12Eþ09 kg (CCSY, 2008); average UEV ¼ 2.80Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 6.31Eþ08 kg (CCSY, 2012); average UEV ¼ 1.05Eþ09 sej/g (Vilbiss and Brown, 2015). 13. Exported Fisheries. 2000: 5.52Eþ08 kg (CCSY, 2000); average UEV ¼ 7.66Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 6.46Eþ08 kg (CCSY, 2005); average UEV ¼ 7.17Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 6.23Eþ08 kg (CCSY, 2008); average UEV ¼ 6.85Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 6.39Eþ08 kg (CCSY, 2012); average UEV ¼ 7.65Eþ09 sej/g (Vilbiss and Brown, 2015). 14. Exported raw mineral. 2000: 1.31Eþ10 kg (CCSY, 2000); average UEV ¼ 1.32Eþ08 sej/g (Vilbiss and Brown, 2015). 2005: 1.41Eþ10 kg (CCSY, 2005); average UEV ¼ 1.70Eþ08 sej/g (Vilbiss and Brown, 2015). 2008: 7.84Eþ09 kg (CCSY, 2008); average UEV ¼ 2.92Eþ08 sej/g (Vilbiss and Brown, 2015). 2012: 6.08Eþ09 kg (CCSY, 2012); average UEV ¼ 3.76Eþ08 sej/g (Vilbiss and Brown, 2015). 15. Exported Metals. 2000: 3.25Eþ09 kg (CCSY, 2000); average UEV ¼ 1.55Eþ08 sej/g (Vilbiss and Brown, 2015). 2005: 4.60Eþ09 kg (CCSY, 2005); average UEV ¼ 8.85Eþ07 sej/g (Vilbiss and Brown, 2015). 2008: 4.21Eþ09 kg (CCSY, 2008); average UEV ¼ 6.81Eþ07 sej/g (Vilbiss and Brown, 2015). 2012: 3.22Eþ09 kg (CCSY, 2012); average UEV ¼ 7.07Eþ07 sej/g (Vilbiss and Brown, 2015). 16. Exported Energy. 2000: 2.57Eþ10 kg (CCSY, 2000); average UEV ¼ 2.54Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 2.88Eþ10 kg (CCSY, 2005); average UEV ¼ 1.87Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 1.81Eþ10 kg (CCSY, 2008); average UEV ¼ 1.64Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 6.30Eþ09 kg (CCSY, 2012); average UEV ¼ 2.72Eþ09 sej/g (Vilbiss and Brown, 2015). 17. Exported Industry products. 2000: 4.38Eþ10 kg (CCSY, 2000); average UEV ¼ 3.04Eþ09 sej/g (Vilbiss and Brown, 2015). 2005: 7.39Eþ10 kg (CCSY, 2005); average UEV ¼ 3.04Eþ09 sej/g (Vilbiss and Brown, 2015). 2008: 9.34Eþ10 kg (CCSY, 2008); average UEV ¼ 3.21Eþ09 sej/g (Vilbiss and Brown, 2015). 2012: 8.13Eþ10 kg (CCSY, 2012); average UEV ¼ 3.05Eþ09 sej/g (Vilbiss and Brown, 2015).

18. Services associated to exports (as money paid for). 2000: 4.15Eþ10 USD (CCSY, 2000); updated China EMR ¼ 7.47Eþ12 sej/$ (Lou and Ulgiati, 2013). 2005: 8.33Eþ10 USD (CCSY, 2005); China EMR ¼ 6.62Eþ12 sej/$ (Lou and Ulgiati, 2013). 2008: 1.17Eþ11 USD (CCSY, 2008); China EMR ¼ 4.47Eþ12 sej/$ (Lou and Ulgiati, 2013). 2012: 1.52Eþ11 USD (CCSY, 2012); China EMR ¼ 9.54Eþ12 sej/$ (calculated by this study).

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