Assessment of nuclear energy embodied in international trade following a world multi-regional input–output approach

Energy 91 (2015) 91e101

Contents lists available at ScienceDirect

Energy journal homepage: www.elsevier.com/locate/energy

Assessment of nuclear energy embodied in international trade following a world multi-regional inputeoutput approach
s-Borda a, G. Guille
n-Gosa
lbez a, b, *, L. Jime
nez a D. Corte a b

Departament d'Enginyeria Química, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain Centre for Process Integration, School of Chemical Engineering and Analytical Science, The University of Manchester, Manchester M13 9PL, UK

a r t i c l e i n f o

a b s t r a c t

Article history: Received 11 December 2014 Received in revised form 26 June 2015 Accepted 20 July 2015 Available online xxx

Nuclear power can contribute to cover the increasing demand of energy while keeping the carbon emissions within the desired limits. Many countries are reluctant to implement nuclear technologies in their territories, but might still use them through imports of products that embody nuclear energy in their life cycle. This work quantifies the difference between the production-based (territorial) and consumption-based (global) nuclear energy use in the main 40 economies of the world (85% of the world's GDP) through the application of a multi-regional environmentally extended inputeoutput model. The mismatch between the direct (territorial) and total (global) use of nuclear energy varies from
237% to 44% in the top economies. From a consumption-based viewpoint, 10 out of the 40 countries reduced the per-capita use of nuclear energy in the period 1995e2009, and 7 when following a production-based approach. The per-capita nuclear energy use could differ in up to 26.2 GJ/inhabitant$year, depending on whether the assessment is consumption or production based. It was also found that around 3.5% of the world's nuclear energy production is trade-embodied and that this amount is growing along with the global production of nuclear energy. Our findings might help to develop more effective environmental regulations worldwide. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Nuclear energy Inputeoutput analysis Trade-embodied energy Multi-regional economy Consumption-based accounting

1. Introduction Climate change has attracted an increasing attention due to the continuous rise in energy demand [1]. Presently, renewable and nuclear energy sources are the most promising alternatives to meet the growing energy demand and keep simultaneously GHG (greenhouse gas) emissions below the desired limits. Unfortunately, in the current energy scenario and considering the capacity already installed, these energy sources are still unable to fully replace fossil fuels. In addition, they show major shortcomings that remain unsolved and have prevented their full deployment. Renewable energy technologies are still expensive [2e5], and their energy yield is highly constrained by on-site resources availability. On the other hand, nuclear energy has raised major concerns regarding its impact on current and future generations. Mining, processing and enrichment of uranium cause substantial damage to ecosystems and waterways [6]. Moreover, nuclear power plants

* Corresponding author. Departament d'Enginyeria Química, Universitat Rovira i Virgili, Av. Països Catalans 26, 43007 Tarragona, Spain. Tel.: þ34 977 55 8618.
n-Gosa
lbez). E-mail address: [email protected] (G. Guille http://dx.doi.org/10.1016/j.energy.2015.07.117 0360-5442/© 2015 Elsevier Ltd. All rights reserved.

require large amounts of cooling water that may cause thermal pollution when discharged into the local ecosystem [7]. Life cycle assessment studies on nuclear energy have found that waste storage and disposal represent the most contentious issues for nuclear power [8], mainly because no country has a final repository for high-level waste [9]. Overall, there are two main serious externalities related to nuclear energy. The first is the risk of a nuclear accident with very high environmental impact (e.g. Three Mile Island, Chernobyl and Fukushima). The second is the generation of radioactive residues (whose final disposal poses serious environmental and safety issues in the long term). Some studies have also found that the life cycle emissions per unit of nuclear energy (including mining, milling and transporting of uranium) are similar to those associated with natural gas power plants [10], which questions the environmental benefits of a move towards nuclear energy. Recent advances in nuclear industry safety have reduced the probability of experiencing future incidents. However, there are still some risks that cannot be entirely eliminated (e.g. natural disasters). Regarding nuclear residues, safe ultra-long-term storage of nuclear waste is still an unsolved problem which may cause serious

92

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

future externalities difficult to quantify or predict (including human health negative effects, biodiversity loss, land degradation and diverse social costs, to name some). For these and other reasons, nuclear energy has led to social reactions evidencing that these activities are not well received in their neighboring areas. In today's globalized markets, industrial sectors around the world make use of a plethora of energy sources to manufacture their products, including nuclear power. In this context, countries without nuclear plants in their territory might make indirect use of nuclear energy through the consumption of goods and services imported from countries that produce it. Thereby, indirect nuclear energy consumers benefit from it (via trade) without undergoing the associated negative effects. It is clear that countries without nuclear facilities but which consume goods manufactured with nuclear energy externalize the corresponding negative effects to the manufacturing regions where nuclear facilities operate. A fair assessment of nuclear energy use should therefore consider both: (i) the amount of nuclear energy directly consumed within the geographic limits of a given nation; and (ii) the amount of nuclear energy embodied in the goods imported by the country via international trade. Thereby, nations willing to lower the environmental loads derived from nuclear energy should reduce the nuclear power share in their energy mix, but at the same time consume less products manufactured with nuclear energy. Consumption-based environmental assessments are therefore more appropriate than production-based (territorial) ones, as they capture direct as well as indirect effects. Data of territorial nuclear energy production can be retrieved from specialized databases (e.g. the International Energy Agency [11]). In contrast, consumption-based data require information on the international channels through which goods and services are traded [12]. Macroeconomic IO (inputeoutput) models [13] offer an appealing framework to gather the necessary information to perform such an analysis. They track goods and services internationally traded, thereby providing an exhaustive description of macroeconomic transactions between productive sectors and final consumers. Macroeconomic models have found many applications in different areas during the last 40 years [14], including the study of energy related topics (e.g. electricity). Han et al. [15] used an IO model to analyze the power sector in the Korean economy, where nuclear power plays a major role. Later, Yoo and Yoo [16] studied the role of nuclear power in the economic development of Korea. These IO studies focused on the economic impact of power generation and disregarded the associated environmental effects. Environmentally extended IO models assess economic and environmental issues simultaneously, thereby establishing a solid link between economic output and environmental loads [17]. Through the application of EEIO (environmentally extended inputeoutput) models, the economic output of a sector is translated into tangible environmental loads. EEIO models have been extensively used in environmental assessments due to their flexibility, accuracy and transparency [18]. In the context of energy related topics, EEIO models have been used to quantify energyrelated GHG emissions [19], and to study the direct and indirect energy consumption in households [20e23] as well as in specific sectors [24e27]. EEIO models have also been widely used in the assessment of the amount of energy and GHG emissions embodied in trade [28e33]. Other works have employed EEIO models to assess toxic emissions to air [34e36], and quantify the water footprint of several economies and sectors [37e42]. In the energy field, however, very few studies have used IO models to assess energy sources others than fossil fuels (and to the best of our knowledge, no study of this type has focused on nuclear energy). Moreover, studies published so far restricted the analysis to one single economy and one specific year [43]. Some approaches

extended the analysis to the multi-regional case [44], but did not cover the evolution of the economies over time. Furthermore, no single study has compared the production-based vs. the consumption-based amount of nuclear energy in each country and the role played by international trade on its use. This work assesses the extent to which the world's main economies (i.e. those covering 85% of the world's GDP) consume nuclear energy either directly or indirectly (i.e., considering both, their national energy grids and the grids of the countries from where they import goods/services), paying special attention to the period 1995e2009. The analysis is carried out using EEIO tables retrieved from the WIOD database (world inputeoutput database) [45]. The remainder of this paper is organized as follows. Section 2 describes multi-regional EEIO models and how to calculate the consumption-based/production-based nuclear energy use and the amount of nuclear energy embodied in international trade. Section 3 presents the main findings of this research work, while the conclusions of the study are drawn in section 4. 2. Materials and methods This section starts by introducing the general structure of IO models in a single economy and then extends them to deal with multi-regional economies. The following section describes how to assess the total nuclear energy use according to the productionbased and consumption-based approaches. 2.1. Input output analysis IO models are well established in the literature. The interested reader is referred to the text book by Miller and Blair [14] for a detailed description of EEIO models, including the assumptions underlying them. The analysis described herein is based on the WIOD database, which considers 35 sectors and 40 countries (during the period 1995e2009.), plus an additional region representing the rest of the world [45]. From the 40 countries studied, 27 of them belong to the European Union and 13 to other major countries, which all together represent more than 85% of the world's gross domestic product. 2.1.1. Single region IO models In an IO model of a given economy, macro-economic transactions occur between selling economic sectors i and consuming sectors j, resulting into economic flows zij of goods/services measured in monetary terms (intermediate sales), in a given time period (e.g. annually). Additionally, there are other exogenous consumers (e.g. households, government and international trade) demanding products from each sector (i.e., final demand). On this basis, in a given economy with n sectors, the total economic output of a sector i is denoted by xi, while yi represents the final demand from the final consumers of sector i. as shown in Eq. (1) expresses the total output of sector i as a function of the final demand and the intermediate sales.

xi ¼ zi1 þ … þ zij þ … þ zin þ yi ¼

n X

zij þ yi ci

(1)

j¼1

Note that the number of equations of this type equals the number of sectors of the economy (n), which leads to n economic outputs, n final demands, and n2 intermediate flows. For convenience, a matrix notation is used, in which capital letters denote matrices and vectors, while lowercase letters refer to their elements (see Eq. (2)).

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

3 2 z11 x1 X ¼ 4 « 5; Z ¼ 4 « xn zn1 2

… 1 …

3 2 3 yi z1n « 5; and Y ¼ 4 « 5 znn yn

(2)

Considering all this, the n equations corresponding to each sector's output can be rewritten as in Eq. (3), where bi is the “summation vector” (a column vector of n elements taking the value of 1).

X ¼ Z$bi þ Y

(3)

In the field of macro-economics, it is commonly assumed that the intermediate sales from sector i to sector j depend only on the output of sector j [13,14]. This is expressed in mathematical terms as given in Eq. (4).

zij aij ¼ ci; j xj

(4)

The technical coefficients aij are related to the production technologies of every sector. Such coefficients are typically assumed constant in a short period of time (e.g. one year). The aij coefficients establish fixed relationships between a sector's output and its inputs (thereby neglecting the effect of economies of scale). Furthermore, production in a Leontief system operates under what is known as constant returns to scale (when the changes in the production are affected by the same proportion than changes in the inputs) [14]. The n2 technical coefficients are grouped in the matrix of technical coefficients A, as in Eq. (5).

2

… 1 …

a11 A¼4 « an1

3 a1n « 5 ann

(5)

Based on the definition of technical coefficients, Eq. (3) could be rewritten as shown in Eq. (6). Then, by applying basic algebra operations, Eq. (6) could be rewritten as in Eq. (7), where I represents an identity square matrix of n2 elements, and ðI
AÞ
1 is known as the Leontief inverse matrix [13].

X ¼ A$X þ Y

(6)

X ¼ ðI
AÞ
1 $Y

(7)

2.1.2. Multi-regional IO model The previously defined IO model can be extended to a multiregional IO model that comprises p regions, each of them with n economic sectors. In the multi-regional IO model, superscripts are used to denote regions, while subscripts denote sectors. Thus, the multi-regional matrix A is disaggregated into p2 sub-matrices of the 0 form Arr , each of them representing the economic transactions 0 between the n sectors of regions r and r (see Eq. (8)). Note that each 0 0 2 rr sub-matrix A contains n technical coefficients of the form arr ij describing the economic transactions between sector i of region r 0 and sector j of region r (see Eq. (9)).

2

A11 A¼4 « Ap1 2

rr 0

A

… 1 … 0

arr 11 ¼4 « 0 arr n1

… 1 …

3 A1p « 5 App 0 3 arr 1n « 5 cr; r 0 rr0 ann

93 0

(8)

(9)

In a multi-regional scenario, each region r can cover its demand with products produced by national and/or foreign sectors. Let us 0 0 denote by Y r the final demand of region r , which is a column vector of np elements (in this particular case, 1435 elements). The final demand of all of the regions is a matrix composed by p sub-vectors 0 0 of the form Y rr , where each of them has n elements of the form yrr i 0 that represent the products demanded by r to all of the n sectors of r (see Eqs. (10) and (11)).

2

0

Y 1r 6 « 6 rr0 0 Yr ¼ 6 6Y 4 « 0 Y pr 2 6 6 0 Y rr ¼ 6 6 4

0

yrr 1 « 0 yrr i « 0 yrr n

3 7 7 7 cr 0 7 5

(10)

3 7 7 7 cr; r 0 7 5

(11)

Finally, the total economic output X is given by a set of p subvectors (each of them with n elements) that represent the economic output of each region r (X r ), as shown in Eq. (12).

2

X1 6 « 6 X ¼ 6 Xr 4 « Xp

3 7 7 7 5

(12)

2.2. Nuclear energy use estimation through EEIO models 2.2.1. Production-based nuclear energy use The nuclear energy intensity of a sector is defined as the amount of energy required to generate one unit of economic output (typically expressed in Tera Joules of nuclear energy spent to generate goods/services that worth one million Euros). EI is the vector (of np elements) representing the energy intensity of all of the sectors and regions. Yearly nuclear energy intensity vectors for the period 1995e2009 were retrieved from WIOD. In wider detail, the EI vector can be further divided into p sub-vectors EI r corresponding to the energy intensity of each region r (see Eq. (13)). Each EIr subvector contains n elements of the type eiri , one for each sector.

 EI ¼ EI 1

…

EI r

…

EI p



(13)

The production-based nuclear energy use in region r (Nuclear P r ) corresponds to the product of the energy intensity sub-vector of region r (EI r ) and the corresponding output subvector X r as shown in Eq. (14).

Nuclear P r ¼ EI r $X r cr

(14)

2.2.2. Consumption-based approach The consumption-based assessment of nuclear energy takes into account all the international transactions taking place in the whole multi-regional economy to meet the final demand of a re0 gion. Hence, the consumption-based nuclear energy of region r r0 (Nuclear_C ) accounts for the nuclear energy consumed in all of the stages in the life cycle of the products demanded by such region, regardless of the physical location where these activities take place. 0 To quantify the nuclear energy embodied in the final demand of r 0 0 (denoted as Y r ), Y is replaced by Y r in Eq. (7). The resulting output 0 X *r (which represents the output generated in the whole multi-

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

94 0

regional economy to meet the demand of r ) is then multiplied by the nuclear energy intensity vector, as shown in Eq. (15). 0

0

Nuclear C r ¼ EI$X *r c r 0

(15)

2.3. Nuclear energy embodied in international trade The trade-embodied nuclear energy corresponds to the amount of nuclear energy used to produce products that are exported rather than consumed locally. The amount of nuclear energy 0 embodied in the goods/services traded between regions r and r 0 rr (denoted as Nuclear ) is obtained from the summation of the amount of nuclear energy embodied in intermediate sales (the first term on the right hand side of Eq. (16)) and the amount embodied in the final demand (the second term of Eq. (16)).

 0  0 0 Nuclearrr ¼ EI r $ Z rr $bi þ EI r $Y rr c r; r 0

(16)

0

The p2 elements of type Nuclear rr are grouped in a square matrix denoted by N in Eq. (17). It is worth noting that the main 0 diagonal of N (elements for which r ¼ r ) represents the sales (or purchases) within the same region; while the rest of the elements of N represent the nuclear energy embodied in international trade.

2

Nuclear11 4 N¼ « Nuclearp1

… 1 …

3 Nuclear1p 5 « Nuclearpp

(17)

The total amount of nuclear energy embodied in international trade (Nuclear_T) is given by the summation of the elements of N 0 that are not in the main diagonal (elements where r s r ) as given in Eq. (18).

Nuclear T ¼

p X p X

0

Nuclearrr c rsr 0

(18)

r¼1 r0 ¼1

3. Results and discussion Before performing the detailed numerical calculations, the consumption-based and production-based nuclear energy use data were validated with external sources. To this end, the productionbased data retrieved from WIOD were contrasted, via multi-factor ANOVA (analysis of variance), with data retrieved from the International Energy Agency [11]. The ANOVA test showed no significant differences between our data and the data from the International Energy Agency, with a 99% of significance (a ¼ 0.01). These results hence confirm the validity of the production-based data. The validation of the consumption-based nuclear energy use is more challenging, as there are no external references containing this information. Hence, the consumption-based data were validated by comparing the summation of the consumption-based nuclear energy use of all of the nations with the world's nuclear energy use (note that the consumption-based nuclear energy use essentially reallocates the production-based nuclear energy use among the nations, but the summation must be the same regardless of the approach followed). The difference between the total energy use obtained from the consumption-based values and the total nuclear use retrieved from the IEA was <0.007%, which confirms the validity of our data. 3.1. Comparison of the nuclear energy use from the productionbased and consumption-based viewpoints The production-based and consumption-based nuclear energy use of the 40 countries of the WIOD was calculated via Eqs. (14) and

(15) (respectively), for every year in the period 1995e2009. The three-letter country codes defined in the ISO 3166-1 [46] are used to refer to the countries (in addition, region ROW represents the countries of the rest of the world). When comparing both assessment approaches, it comes into evidence that 15 out of the 40 countries (i.e. AUS, AUT, CYP, DNK, EST, GRC, IDN, IRL, ITA, LUX, LVA, MLT, POL, PRT and TUR) do not have territorial production of nuclear energy, but they do consume a given amount of nuclear energy via trade. In terms of the total nuclear energy use, USA is by far the largest producer (and consumer) of nuclear energy, with an average production of 8.5$106 TJ/year in the period 1995e2009. The following largest producers are FRA (4.5$106 TJ/year) and JPN (4.5$106 TJ/ year). The remaining countries produce less than 200 TJ/year of nuclear energy. For a better analysis of the results (due to the differences in nuclear production between countries), the consumption-based and production-based nuclear energy use were “normalized” by the population of each country. Fig. 1 presents a color-scale world map contrasting the yearly per-capita nuclear energy use assessed according to the two approaches. The color-scale ranges between 0 GJ/inhabitant$year (dark green) and 85 GJ/inhabitant$year (dark red). The figure shows that SWE has the largest per-capita nuclear power production (83.2 GJ/inhabitant$year), followed by FRA (74.2 GJ/inhabitant$year). Note that from a consumption perspective, both SWE and FRA show lower per-capita nuclear use (72 GJ/ inhabitant$year and 64 GJ/inhabitant$year, respectively). In addition, the gap between FRA and the next country in the ranking (i.e. BEL) gets narrower (from 25.2 to 22.7 GJ/inhabitant$year) by changing the assessment approach. This mismatch between production-based and consumption-based nuclear energy is due to the fact that some goods manufactured in the top producing countries are exported overseas. This situation becomes more evident in the countries with no nuclear energy in their local grid. As an example, LUX and AUT (which from a production viewpoint have no nuclear energy use) show a per-capita use of nuclear energy of 26.2 and 9.5 GJ/inhabitant$year, respectively (values that are similar to those of other nuclear producers like CAN or NLD, with 25.5 GJ/inhabitant$year and 8.8 GJ/inhabitant$year, respectively). In other words, from a production-based viewpoint, LUX and AUT could argue that are “nuclear-free”. The consumptionbased analysis, however, reveals that they do consume nuclear energy, which is embodied in the goods imported from countries that have nuclear facilities. The difference between the consumption-based and production-based nuclear energy use (ratio (Nuclear_Pr
Nuclear_Cr)/Nuclear_Pr) is investigated next. Countries with a positive difference produce more nuclear energy in their inland territory than the amount consumed (which is embodied in the supply chain of the products they consume). The discrepancy between the approaches is mathematically undefined in countries with no nuclear production (because a division by zero occurs). Hence, we assign to such countries a large negative difference (i.e.
300%, which is greater than the largest difference of
237% that can be calculated, which corresponds to NLD). Fig. 2 shows the percentage difference (in average in the period of study) between the global and territorial nuclear energy use of each country in a color scaled world map. In countries whose nuclear energy consumption is greater than their production, there are differences that are particularly high, especially in NLD (
237%), BRA (
112%), MEX (
72%) and CHN (
48%), while in others the differences are smaller, like in IND (
18%), GBR (
13%) and ROU (
10%), and even lower in ESP (
4%) and USA (
3%).

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

95

Fig. 1. Average per-capita nuclear energy use in the 40 countries of the WIOD. The units of the color scale are expressed in GJ/inhabitant$year. a: production-based approach; b: consumption-based approach. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

The remaining 16 countries produce more nuclear energy than that consumed. This implies that part of the nuclear energy generated within their limits is used to manufacture goods that are ultimately used to meet the demand of other countries. Countries like DEU, JPN, HUN and CZE show very little differences between the nuclear energy use assessed by the two methods (less than 10%). Other countries like BEL, CAN, FIN, FRA, SWE, KOR, LTU and SVN show differences ranging between 10 and 20%, while the

largest differences (from 20% to 44%) are observed in BGR, RUS, SVK and TWN, being BGR the country with the greatest difference. There are two remarkable observations to mention from these results. First, there are more countries (24 out of 40) consuming more nuclear energy from the consumption-based perspective than that produced internally. Second, the greatest differences between both assessment approaches (with respect to their territorial production) occur in these countries. Hence, our results

96

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

Fig. 2. Difference between the production-based and consumption-based nuclear energy use expressed as the ratio: (Nuclear_Pr e Nuclear_Cr)/Nuclear_Pr. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

reveal that the amount of nuclear energy consumed in a country can greatly differ from the amount of nuclear energy produced in it.

3.2. Time evolution of nuclear energy use The time evolution of nuclear energy use was assessed next to determine whether a country is intensifying its nuclear energy use (both from the production-based and consumption-based perspectives). Fig. 3 presents a bar chart for each assessment approach, in which the length of the bars represents the per-capita average nuclear energy use in the period of study, and the color of the bars follows a color-scale indicating the slope with which nuclear power increases (or decreases) every year. As seen, the use of nuclear energy has in general increased among countries regardless of the assessment approach. Only 7 countries are reducing their nuclear energy use from a productionbased approach, and 10 from a consumption-based standpoint. However, the global nuclear energy use is increasing, since the reductions in nuclear energy use taking place in some countries do not compensate for the increase in the remaining ones. SWE shows the highest per-capita nuclear energy use and is also the country reducing the use of such energy the most from both the production and consumption perspectives (1.12 GJ/inhabitant$year and 1.06 GJ/inhabitant$year). Other nuclear energy producers like CAN, DEU, ESP, GBR, JPN and LTU are also reducing their production-based nuclear energy use, but not to the same extent as in SWE (between 0.05 and 0.53 GJ/inhabitant$year). On the contrary, the remaining producers tend to increase their per-capita (production-based) nuclear energy use, especially CZE (1.42 GJ/ inhabitant$year) and KOR (1.34 GJ/inhabitant$year), followed by SVK (0.86 GJ/inhabitant$year), SVN (0.47 GJ/inhabitant$year) and RUS (0.40 GJ/inhabitant$year). From a consumption-based perspective, however, the evolution of nuclear energy use is different. More precisely, the maximum slope with which the nuclear energy use increases (which corresponds to CZE) is 1.05 GJ/inhabitant$year; and the minimum slope

with which it decreases (that from SWE) is 1.06 GJ/inhabitant$year. The evolution patterns provide valuable insight into the nuclear energy panorama in the close future, which in general tends to increase the nuclear energy use in most of the countries. Nuclear energy can help reduce GHG emissions by replacing fossil fuels by a less carbon-intensive energy source [47]. Hence, it is interesting to study the evolution of nuclear energy in association with the GHG emissions. To this end, we retrieved from the Ecoinvent Database [48] the life-cycle GHG emissions associated to the production of nuclear energy in each country and compared them with those (also retrieved from the Ecoinvent Database) that would take place if the amount of energy that is covered with nuclear sources were supplied by fossil resources (in particular, hard coal, fossil oil and natural gas). The GHG emissions savings that would be attained are therefore given by the difference between the emissions that would take place by using fossil resources and those associated with the nuclear energy production. Fig. 4 shows the evolution of the GHG savings. As seen, significant savings in CO2-eq emissions (from 4.4 103 Mt if natural gas were used, to 1.0 103 Mt if hard coal were used) can be attained by replacing fossil fuels by nuclear energy. It is important to mention that some authors have argued that the life cycle emissions of nuclear energy could be greater than those from other renewable sources (e.g. wind power) [49]. Hence, further reductions could be attained by using renewable sources instead of nuclear energy.

3.3. Sensitivity analysis of the world's nuclear energy production A sensitivity analysis was next performed on some parameters of the IO model. Particularly, we studied the effect of changes in the energy intensities of the industrial sectors (i.e., amount of nuclear energy use per unit of money traded) on the global nuclear energy production in a given year (i.e. 2009) (Eq. (13)). To this end, the methodology described by Mattila (2012) [50] was followed, which assesses the relative changes in a given indicator (i.e., the total nuclear energy production) that take place under a 1% perturbation

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

97

Fig. 3. Temporal evolution of the per-capita nuclear energy in the 40 countries that appear in the WIOD. The length of the bars represents the per-capita average nuclear energy use (1995e2009), and the color of the bars indicates the slope of the increase (or decrease) of per-capita nuclear energy used. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 4. CO2-eq emissions saved by using nuclear energy instead of 3 different types of fossil fuels.

in a given parameter (i.e., the energy intensity parameters). Hence, the relative changes in the total nuclear production attained by increasing (one at a time) each of the 1435 energy intensities by 1% with respect to its original value were determined. Table 1 shows the results of the sensitivity analysis along with the energy intensity of the Electricity, Gas and Water Supply sector, and its corresponding economic output. What first comes into evidence is that the total nuclear power production is only affected by the sector Electricity, Gas and Water Supply (the only sector with direct use of nuclear energy) of those countries with nuclear power production in their territories. Results reveal that the worldwide nuclear energy production is more sensible to changes in the energy intensity of the Electricity, Gas and Water Supply sector of USA, FRA and JPN. That is, a reduction of 1% in the nuclear energy intensity of USA would save up to 0.31% of the global nuclear energy production by 2009 (9.13$104 TJ), the same reduction in FRA would save up to 0.15% (4.42$104 TJ), and in JPN 0.10% (2.94$104 TJ). The output of the electricity sector of countries like BRA, ROU, LTU, MEX, SVN and NLD is quite low, so changes in their energy intensities have little impact on the total nuclear energy production (despite of the fact that some of them have high nuclear energy intensity, e.g. LTU).

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

98 Table 1 Sensitivity analysis results. Country

Sensitivity [% nuclear energy increase/%energy intensity increase]

Energy intensity [TJ/MV]

Sector's output [MV]

BEL BGR BRA CAN CHN CZE DEU ESP FIN FRA GBR HUN IND JPN KOR LTU MEX NLD ROU RoW RUS SVK SVN SWE TWN USA

0.02 0.01 0.00 0.03 0.03 0.01 0.05 0.02 0.01 0.15 0.03 0.01 0.01 0.10 0.05 0.00 0.00 0.00 0.00 0.05 0.06 0.01 0.00 0.02 0.02 0.31

28.25 39.00 1.66 25.66 1.59 15.27 8.30 5.87 23.93 40.01 6.17 14.43 3.12 11.60 31.67 38.43 3.92 0.86 7.57 3.18 16.25 10.10 20.08 30.41 28.49 23.38

18,240.91 4292.79 85,358.90 38,445.02 481,828.29 19,509.90 177,279.07 98,001.89 10,728.80 111,737.73 122,107.20 11,700.18 65,127.46 263,040.06 50,912.53 3131.46 29,263.71 53,479.42 16,941.55 471,798.36 110,650.28 15,440.03 3118.82 18,721.04 15,922.26 387,527.00

3.4. Nuclear energy embodied in the international trade network This section quantifies the amount of trade-embodied nuclear energy and provides details on the international channels through which nuclear energy is marketed. To this end, Eq. (18) was used to estimate the total share of nuclear energy embodied in international trade and its temporal evolution in the period 1995e2009. Fig. 5 shows the temporal evolution of the trade-embodied nuclear energy along with the world's nuclear energy production in the period 1995e2009. It is observed that the total nuclear energy production has increased in general terms, with a small drop taking place during the world-wide crisis (in 2007). The evolution of the share of nuclear energy internationally traded shows a pattern similar to that associated with nuclear energy production. Generally speaking, there is a low portion of nuclear energy embodied in international trade (the highest value of the temporal series is 3.4% in 2006). This is because nuclear power is mostly consumed domestically in the countries that generate it. However, note that this percentage is not negligible at all. As an example, in 2006 the nuclear energy embodied in trade was around 1.1$106 TJ, which exceeds the amount of nuclear energy produced by any producer, excluding DEU, FRA, JPN, KOR, RUS and USA. Moreover, it is remarkable that the trade-embodied nuclear energy use has been growing in tandem with the global nuclear power production. Noteworthy, the trade-embodied nuclear energy assessment conducted so far is based on historical data. A predictive assessment of the trade-embodied nuclear energy could be helpful for policy makers. We rely on external energy forecasts [51] to predict the total nuclear energy production by 2035. On the other hand, the trade-embodied nuclear energy share is predicted according to 3 scenarios (A, B and C) based on different trends of trade-embodied nuclear energy in the period 1995e2009. Fig. 6 presents the nuclear energy forecasting for the total nuclear energy and its share embodied in trade until 2035. The predicted scenarios of the trade-embodied nuclear share have been

Fig. 5. Temporal evolution of the world's total nuclear energy and trade-embodied nuclear energy in the period 1995e2009. The percentage of trade-embodied nuclear energy is read in the left Y axis. The world's total nuclear energy production is read in the right Y axis.

obtained by performing a linear regression of different sets of data in the period 1995e2009. In particular, the linear regression corresponding to scenario A (R2 ¼ 0.9695) establishes an upper bound by considering only the values that tend to grow with higher slope (i.e. those between 1995 and 2006). Scenario C establishes a lower bound by considering in the linear regression (with an R2 ¼ 0.9671) the values growing less (i.e. values in the range 1995e1998 and 2007e2009). Scenario B considers all the values in the period 1995e2009 (R2 ¼ 0.6299). Note that some values in the period 2007e2009 tend to decrease, but in all the scenarios the total nuclear production increases. By 2035 the worldwide nuclear energy production is

Fig. 6. Forecasting of global nuclear energy production and nuclear energy embodied in trade until 2035. The percentage of trade-embodied nuclear energy along with the series forecasting the 3 different scenarios of trade-embodied nuclear energy are read in the left Y axis. The world's total nuclear energy production and its forecasting data (retrieved from the BP's 2035 energy outlook) are read in the left Y axis.

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

predicted to be around 35 million of TJ [51]. Under this premise, by 2035, the trade-embodied energy in scenario A (8.96% embodied in trade) will be 3.16$106 TJ; and that in scenario C (4.88% embodied in trade) will be 1.72$106 TJ. In general, regardless of the scenario, the trade-embodied nuclear energy share is expected to grow from double to triple with respect to 2009. Hence, quantifying the amount of nuclear energy that one country displaces to others is of increasing interest.

99

Finally, the international transactions that embody nuclear energy in the period 1995e2009 are quantified (those corresponding to the matrix N in Eq. (17)). Fig. 7a shows a “heat map” constructed from the elements of the N matrix of international transactions (using average values in the period 1995e2009); and Fig 7b shows a bar chart representing the total imports/exports of trade embodied nuclear energy of each country. Fig. 7b also displays a series of values (secondary Y axis) representing the total nuclear

0

Fig. 7. a: Heat map representation of the matrix of international transactions of embodied nuclear energy. Rows represent the sales from country r to each of the r countries. 0 Similarly the columns represent the purchases of embodied nuclear energy. The heat map excludes the sales/purchases within the same country (when r ¼ r ). Countries are sorted in a descending order according to their embodied nuclear energy sales/purchases starting from the bottom left corner. b: Total nuclear energy embodied in the imports and exports of each country. The height of the bars represents the average (in the period 1995e2009) of the trade embodied nuclear energy (read in the left Y axis). The series (read in the right axis) represents, in average, the domestic nuclear energy production/consumption (the values in the main diagonal of matrix N).

100

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101

energy that each country produces for domestic use (i.e. the values of the diagonal of matrix N). In Fig. 7a, the darkest cells of the heat map indicate greater flows of embodied nuclear energy. For convenience in the presentation of the matrix, the energy produced and consumed within the same 0 country is omitted (elements of matrix N for which r ¼ r are not displayed, since they show much larger orders of magnitude). In other words, Fig. 7a omits the values in the main diagonal of matrix N. The rows and columns of the matrix are sorted in descending order, so that the greatest values are in the bottom left corner. The rows in the figure denote sales and the columns purchases. It is observed that the top 15 rows of the matrix correspond to countries without nuclear power production. As seen, all the countries (regardless of whether they produce nuclear energy internally) consume products manufactured to some extent with nuclear power. Particularly, some countries without nuclear energy production are among the top importers of embodied nuclear energy. As an example ITA, with no nuclear power production, is in the fifth place of the top consumers of embodied nuclear energy. Similarly, AUT does not produce nuclear power, but it is the 6th consumer of nuclear energy produced externally. It is worth mentioning that the environmental burdens that are displaced due to trade-embodied nuclear energy may ultimately require investments in public health and social security [52] in the countries with nuclear power production. Hence, by quantifying the trade-embodied nuclear share, such countries could assess the net profit of international trade and evaluate the need to define special taxes on exported goods in order to adopt the necessary corrective actions within their limits. In other words, the analysis of the trade-embodied nuclear energy helps to assess the extent to which an economic activity is in line with the principles of sustainability, by balancing the economic benefit with the environmental and social welfare.

4. Conclusions This work has assessed the territorial (production-based) and global (consumption-based) use of nuclear energy of the main 40 economies in the world using EEIO models. The approach followed considers the energy embodied in the life cycle of the goods and services consumed worldwide, thereby shedding light on the international channels through which nuclear energy (and the associated environmental pressures) is internationally traded. This information could facilitate the design of more effective policies that transparently allocate the environmental responsibility of impacts among the parties involved. Our findings showed that there are 15 countries that do not produce nuclear power internally but still consume it through the imports of goods. In total, 25 countries consume more nuclear energy than the amount they produce, and in some cases the mismatch can be quite significant (up to 237%). Such situations could lead to unfair scenarios in which countries externalize the environmental pressures associated to nuclear power production by displacing their manufacturing tasks to other regions. Nuclear energy use has grown in the period 1995e2009. There are only 7 countries that reduced their nuclear energy production in that period. Their reductions, however, did not compensate for the increase of nuclear energy use in the remaining countries. In addition, the share of nuclear energy embodied in international trade has also grown from 1.4% to 2.5%, with a maximum peak of 3.4% in 2006. Forecasts by 2035 suggest an increase in the worldwide nuclear energy production and in its share trade-embodied. The latter, under different scenarios, falls within the range 4.88% to 8.96% of the world's nuclear energy production.

A sensitivity analysis of the nuclear energy intensity revealed that, by 2009, a 1% reduction of the nuclear energy use in the electricity sector in USA, FRA and JPN could reduce up to 9.13$104 TJ, 4.42$104 TJ and 2.94$104 TJ the nuclear energy use worldwide (respectively). Our analysis provides details on the international channels through which nuclear energy is traded between nations. The findings presented here are intended to guide policy makers in the definition of more effective environmental regulations. Acknowledgments The authors would like to acknowledge the financial support received from the Spanish Ministry of Economy and Competitiveness (CTQ2012-37039-C02 and DPI2012-37154-313C02). Nomenclature

Abbreviations EEIO environmentally extended inputeoutput GHG greenhouse gases IO inputeoutput WIOD world inputeoutput database Equations A matrix of technical coefficients 0 0 Arr technical coefficients between regions r and r 0 rr aij technical coefficients relating sector i of region r and 0 sector j of region r aij technical coefficients between sectors i and j of a single region EI multi-regional energy intensity vector EIr energy intensity vector of region r eiri energy intensity of sector i and region r I identity matrix i selling sector bi summation vector j n p r 0 r N

consuming sector number of sectors in an economy number of regions selling region demanding region matrix of nuclear energy being traded between regions 0 (includes r ¼ r ) 0 r0 Nuclear_C consumption-based nuclear energy use of region r r Nuclear_P production-based nuclear energy use in region r 0 0 Nuclearrr nuclear energy traded between r and r Nuclear_T total nuclear energy embodied in international trade xi total output of sector i (single region) Xr vector of output of the region r X total output vector 0 0 X* r consumption-based output of region r Y total final demand vector 0 0 Yr final demand vector of region r 0 0 Y rr sub-vectors of the final demand Y r 0 0 rr yi goods/services that r demands from sector i of region r yi final demand of sector i (single region) zij intermediate sales between sectors i and j Z matrix of intermediate sales References [1] Herring H. Energy efficiencyda critical view. Energy 2006;31(1):10e20.

D. Cort
es-Borda et al. / Energy 91 (2015) 91e101 [2] Li C-T, Peng H, Sun J. Life cycle cost analysis of wind power considering stochastic uncertainties. Energy 2014;75:411e8. http://dx.doi.org/10.1016/ j.energy.2014.07.090. ~o P. The impact of demand side management strategies in [3] Pina A, Silva C, Ferra the penetration of renewable electricity. Energy 2012;41(1):128e37. [4] Sarkar S, Kumar A, Sultana A. Biofuels and biochemicals production from forest biomass in Western Canada. Energy 2011;36(10):6251e62. [5] Cossio-Vargas E, Hernandez S, Segovia-Hernandez JG, Cano-Rodriguez MI. Simulation study of the production of biodiesel using feedstock mixtures of fatty acids in complex reactive distillation columns. Energy 2011;36(11): 6289e97. [6] Hondo H. Life cycle GHG emission analysis of power generation systems: Japanese case. Energy 2005;30(11e12):2042e56. [7] Kirillin G, Shatwell T, Kasprzak P. Consequences of thermal pollution from a nuclear plant on lake temperature and mixing regime. J Hydrol 2013;496: 47e56. [8] Stamford L, Azapagic A. Sustainability indicators for the assessment of nuclear power. Energy 2011;36(10):6037e57. [9] Office of Public Sector Information. Climate change act. 2008. Availabe from: http://www.legislation.gov.uk/ukpga/2008/27/contents [accessed 10.12.14]. [10] Oxford Research Group. In: Barnaby F, Kemp J, editors. Secure energy? Civil nuclear power, security and global warming; 2007. London, UK. [11] International Energy Agency. Renewables information 2013 edition documentation for beyond 2020 files. 2013. Available from: http://wds.iea.org/ wds/pdf/Documentation for Renewables Information 2013.pdf [accessed 10.12.14]. [12] Hertwich EG. Life cycle approaches to sustainable consumption: a critical review. Environ Sci Technol 2005;39(13):4673e84. [13] Dietzenbacher Erik, Lahr M. Wassily Leontief and input-output economics. Cambridge Press; 2008. [14] Miller RE, Blair PD. Input-output analysis: foundations and extensions. Cambridge, UK: Cambridge University Press; 2009. [15] Han S-Y, Yoo S-H, Kwak S-J. The role of the four electric power sectors in the Korean national economy: an inputeoutput analysis. Energy Policy 2004;32(13):1531e43. [16] Yoo S-H, Yoo T-H. The role of the nuclear power generation in the Korean national economy: an inputeoutput analysis. Prog Nucl Energy 2009;51(1): 86e92. [17] Peters GP, Minx JC, Weber CL, Edenhofer O. Growth in emission transfers via international trade from 1990 to 2008. Proc Natl Acad Sci U S A 2011;108(21): 8903e8. [18] Croft McKenzie E, Durango-Cohen PL. An input-output approach for the efficient design of sustainable goods and services. Int J Life Cycle Assess 2010;15(9):946e61.
nchez-Cho
liz J. The role of consumption patterns, de[19] Duarte R, Mainar A, Sa mand and technological factors on the recent evolution of CO2 emissions in a group of advanced economies. Ecol Econ 2013;96:1e13. [20] Lenzen M, Murray SA, Korte B, Dey CJ. Environmental impact assessment including indirect effectsda case study using inputeoutput analysis. Environ Impact Assess Rev 2003;23(3):263e82. [21] Zhu Q, Peng X, Wu K. Calculation and decomposition of indirect carbon emissions from residential consumption in China based on the inputeoutput model. Energy Policy 2012;48:618e26. [22] Liu L-C, Wu G. Relating five bounded environmental problems to China's household consumption in 2011e2015. Energy 2013;57:427e33. [23] Parikh J, Panda M, Ganesh-Kumar A, Singh V. CO2 emissions structure of Indian economy. Energy 2009;34(8):1024e31. [24] Cellura M, Guarino F, Longo S, Mistretta M, Orioli A. The role of the building sector for reducing energy consumption and greenhouse gases: an Italian case study. Renew Energy 2013;60:586e97. [25] Huang Y-H, Wu J-H. Analyzing the driving forces behind CO2 emissions and reduction strategies for energy-intensive sectors in Taiwan, 1996e2006. Energy 2013;57:402e11. [26] Logar I, van den Bergh JCJM. The impact of peak oil on tourism in Spain: an inputeoutput analysis of price, demand and economy-wide effects. Energy 2013;54:155e66. [27] Meng FY, Zhou DQ, Zhou P, Bai Y. Sectoral comparison of electricity-saving potentials in China: an analysis based on provincial inputeoutput tables. Energy 2014;72:772e82.

101

[28] Liu Z, Geng Y, Lindner S, Zhao H, Fujita T, Guan D. Embodied energy use in China's industrial sectors. Energy Policy 2012;49:751e8. €o €k M. Analysis of energy embodied in the international [29] Tang X, Snowden S, Ho trade of UK. Energy Policy 2013;57:418e28. [30] Su B, Ang BW. Inputeoutput analysis of CO2 emissions embodied in trade: a multi-region model for China. Appl Energy 2014;114:377e84. [31] Dong H, Geng Y, Fujita T, Jacques DA. Three accounts for regional carbon emissions from both fossil energy consumption and industrial process. Energy 2014;67:276e83. €o €k M. Net oil exports embodied in [32] Tang X, Zhang B, Feng L, Snowden S, Ho China's international trade: an inputeoutput analysis. Energy 2012;48(1): 464e71. [33] Li Z, Pan L, Fu F, Liu P, Ma L, Amorelli A. China's regional disparities in energy consumption: an inputeoutput analysis. Energy 2014;78:426e38. [34] Roca J, Serrano M. Income growth and atmospheric pollution in Spain: an inputeoutput approach. Ecol Econ 2007;63(1):230e42. [35] Tukker A, Emmert S, Charter M, Vezzoli C, Sto E, Munch Andersen M, et al. Fostering change to sustainable consumption and production: an evidence based view. J Clean Prod 2008;16(11):1218e25. [36] Chang Y, Ries RJ, Wang Y. The embodied energy and environmental emissions of construction projects in China: an economic inputeoutput LCA model. Energy Policy 2010;38(11):6597e603. [37] Yu Y, Hubacek K, Feng K, Guan D. Assessing regional and global water footprints for the UK. Ecol Econ 2010;69(5):1140e7. [38] Lenzen M. A guide for compiling inventories in hybrid life-cycle assessments: some Australian results. J Clean Prod 2002;10(6):545e72. [39] Zhang Z, Shi M, Yang H, Chapagain A. An inputeoutput analysis of trends in virtual water trade and the impact on water resources and uses in china. Econ Syst Res 2011;23(4):431e46. [40] Peters GM, Wiedemann SG, Rowley HV, Tucker RW. Accounting for water use in Australian red meat production. Int J Life Cycle Assess 2010;15(3):311e20. [41] Zhao X, Chen B, Yang ZF. National water footprint in an inputeoutput frameworkda case study of China 2002. Ecol Modell 2009;220(2):245e53. [42] Rowley HV, Lundie S, Peters GM. A hybrid life cycle assessment model for comparison with conventional methodologies in Australia. Int J Life Cycle Assess 2009;14(6):508e16. [43] Chen GQ, Chen ZM. Carbon emissions and resources use by Chinese economy 2007: a 135-sector inventory and inputeoutput embodiment. Commun Nonlinear Sci Numer Simul 2010;15(11):3647e732. [44] Huysman S, Schaubroeck T, Dewulf J. Quantification of spatially differentiated resource footprints for products and services through a macro-economic and thermodynamic approach. Environ Sci Technol 2014;48(16):9709e16. [45] Dietzenbacher E, Los B, Stehrer R, Timmer M, de Vries G. The construction of world inputeoutput tables in the WIOD project. Econ Syst Res 2013;25(1): 71e98. [46] International Standards Organization. Country codes-ISO 3166. 2013. Available from: http://www.iso.org/iso/country_codes [accessed 10.12.14]. [47] Lior N. Sustainable energy development: the present (2009) situation and possible paths to the future. Energy 2010;35(10):3976e94. http://dx.doi.org/ 10.1016/j.energy.2010.03.034. [48] Frischknecht R, Jungbluth N, Althaus H-J, Doka G, Dones R, Heck T, et al. The ecoinvent database: overview and methodological framework (7 pp). Int J Life Cycle Assess 2004;10(1):3e9. http://dx.doi.org/10.1065/lca2004.10.181.1. [49] Lenzen M. Life cycle energy and greenhouse gas emissions of nuclear energy: a review. Energy Convers Manage 2008;49(8):2178e99. http://dx.doi.org/ 10.1016/j.enconman.2008.01.033. [50] Mattila T. Any sustainable decoupling in the Finnish economy? A comparison of the pathways and sensitivities of GDP and ecological footprint 2002e2005. Ecol Indic 2012;16:128e34. http://dx.doi.org/10.1016/j.ecolind.2011.03.010. [51] Energy outlook 2035 j about BP j BP Global. http://www.bp.com/en/global/ corporate/about-bp/energy-economics/energy-outlook.html [accessed 04.03.15]. [52] Dones R, Hec T, Bauer C, Hirschberg S, Bickel P, Preiss P, et al. ExternE-Pol externalities of energy: extension of accounting framework and policy applications new energy technologies. 2006. Available at: http://www.externe. info/externe_d7/sites/default/files/expolwp6.pdf [accessed 10.12.14].