187

The Resilience of Embodied Energy Networks: A Critical
Dimension for Sustainable Development Goals (SDGs)
Masahiro SATO1*, Ali KHARRAZI2, Hirofumi NAKAYAMA3,
Steven KRAINES4 and Masaru YARIME5
Economic and Social Research Institute (ESRI), Cabinet Office, Government of Japan,
1-6-1 Nagata-cho, Chiyoda-ku, Tokyo 100-8914, Japan
2
Graduate School of Public Policy (GraSPP), The University of Tokyo, Japan,and Advanced Systems Analysis Program, International Institute for Applied Systems Analysis (IIASA), Austria
3InterGreen Research Institute, Japan
4
Liberal Arts and Sciences, Tokyo City University, Japan
5
Graduate School of Public Policy (GraSPP), The University of Tokyo, Japan,
and the Department of Science, Technology, Engineering and Public Policy (STEaPP),
University College London, United Kingdom*e-mail: contact@intergreen.jp
1

Abstract
Access, renewables and efficiency have been identified as targets in the field of energy under the
Sustainable Development Goals (SDGs). Resilience is also a critical dimension that needs to be consideredin moving towards sustainable energy. Diversification of direct energy suppliers has been the conventional
recourse for achieving energy security. In consideration of the increasingly globalized nature of trade, energy
and supply chain networks, however, this approach would be insufficient for addressing the resilience ofenergy supplies to potential environmental, economic and social shocks and disruptions. In this paper, weinvestigate countries’ energy resilience by quantifying diversity in suppliers of both direct and embodied
energy and examine how selections of indirect energy supplies can affect the resilience of the entire
embodied-energy trade network. We find that the geographical diversity of embodied energy imports is muchgreater than that of direct energy imports, and there are considerable variations across countries in thediversification of embodied energy imports. This suggests a possible strategy for countries that depend
heavily on a few neighbors for their direct energy imports to diversify their supply chains globally in order tobenefit from larger diversity of embodied energy supplies, thereby strengthening the energy resilience of
their economies.
Key words: embodied energy, energy resilience, multi-regional input-output model

1. Introduction
Sustainability involves coming to terms with long-term
constraints on various types of resources, especiallyenergy, as one of the most critical issues at the global
level. The fundamental link between sustainable
development and sustainable energy has been recognizedinternationally since the UN General Assembly’s
declaration of 2012 as the International Year of
Sustainable Energy for All and also of 2014 – 2024 as
the UN Decade for Sustainable Energy for All. The UN
Secretary General’s Sustainable Energy for All(SE4ALL) initiative set three specific goals for the year
2030, namely, ensuring universal access to modern
energy services, doubling the global rate of improvement
in energy efficiency, and doubling the share of renewable
Global Environmental Research
19/2015: 187–198
printed in Japanenergy in the global energy mix (Secretary-General’sHigh-Level Group on Sustainable Energy for All, 2012).
The importance of promoting access, renewables andefficiency for energy has been formally adopted for Goal
7, “Ensure access to affordable, reliable, sustainable andmodern energy for all,” in the Sustainable Development
Goals (SDGs) at the United Nations General Assemblyin September 2015 (United Nations, 2015).
In addition to these three aspects, resilience is also a
critical dimension that needs to be considered in moving
towards sustainability (Kharrazi et al., 2014; Kharrazi et al.,2015; Kharrazi et al., 2013). As we live in a complex,
interconnected natural-social system, it is crucial for us
to maintain capacities for coping with various types ofshocks, disruptions and extreme events, which often
happen unexpectedly (Yarime & Kharrazi, 2015). A©2015 AIRIES188

M. SATO et al.

small-scale, unexpected disturbance to the delivery ofenergy could lead to major socio-economic andenvironmental consequences. The idea of resilience
hence is explicitly emphasized in some of the goals andtargets identified in the SDGs (United Nations, 2015). In
Goal 1 for ending poverty in all its forms everywhere,
for example, Target 1.5 is specifically aimed at building
the resilience of the poor and those in vulnerable
situations and reducing their exposure and vulnerability
to climate-related extreme events and other economic,
social and environmental shocks and disasters by 2030.
Goal 11 calls for making cities and human settlements
inclusive, safe, resilient and sustainable, and a target isset by 2020 to substantially increase the number of cities
and human settlements adopting and implementing
integrated policies and plans towards inclusion, resource
efficiency, mitigation and adaptation to climate change,
as well as resilience to disasters, in line with the Sendai
Framework for Disaster Risk Reduction 2015 – 2030.
Goal 13 also targets strengthening of resilience andadaptive capacity to climate-related hazards and natural
disasters in all countries. Goal 14 is set to sustainably
manage and protect marine and coastal ecosystems to
avoid significant adverse impacts by strengthening theirresilience by 2020.
The energy resilience of a country is, in general,
influenced by a combination of its internal and external
conditions. In addition to the physical energy
endowment, internal conditions are characterized by thecountry’s economic structure related to energy, such as
the energy intensity of production systems and thedegree of concentration on specific energy carriers.
Governments and companies can have direct andindirect influences on those conditions through domesticenergy policies and technological improvements.
External conditions are mainly characterized by thecountry’s overall dependence on foreign energy
resources and the way it ensures a secure access to them.
One of the most important components of strategies toimprove external conditions is the choice of countries/
regions to supply the country’s primary energy.
Governments and companies determine their suppliers
by considering not only the price, quality and transport
costs of energy, but also various economic, social andenvironmental factors such as diplomatic relations,security of transportation corridors, e.g., sea lanes andpipelines, the possibility of production adjustments
resulting from international energy cartels, e.g., theOrganization of the Petroleum Exporting Countries(OPEC) and the Gas Exporting Countries Forum(GECF), and risks of regional conflicts and wars.
In an increasingly globalized economy, however, theselection of direct trade partners is not sufficient forcontrolling major energy-related risks. A country’s
domestic production and consumption are built uponcomplex networks of production processes located both
inside and outside the country. Each step in the
production processes has its own energy suppliers,
which may differ from those of the country of finaldestination in the entire supply chain. If segments of
upstream production of an exporting country stagnate
due to a sudden suspension of energy supply from aparticular region, the domestic production andconsumption of the final destination country could also
be impaired, even though its own direct energy imports
are not affected. Thus, governments and companies needto consider not only the conditions of the suppliers
directly exporting energy to them, but also those
supplying energy to other manufacturers throughout thewhole supply chain. In other words, secure andsustainable energy in the global economy requires us toconsider suppliers by evaluating embodied energy
imports, which are generally defined as the sum of directenergy imports and indirect energy use in the production
process outside the final destination country.
A common practice for improving the energy securityof a country has traditionally been to diversify its supply
portfolio (Sovacool & Brown, 2010). Heavy dependence
on a single supplying country or geographical area
would make energy supplies vulnerable to risks ofparticular regions. Broadening one’s supply partners toinclude multiple regions with varying geopolitical risks
could alleviate the influence of undesirable events orshocks in a particular country or region.
In the context of the accelerating globalization of
trade, however, the practice of direct supply
diversification would not be sufficient to cope withvarious types of disruptions and disturbances that could
happen throughout the supply chain of embodied energy.
If the energy supplies of a country’s trade partners areheavily dependent on a high-risk region, the entire
supply chains of the final destination country, even if it
sufficiently diversified its direct energy suppliers, would
become vulnerable to energy-related shocks specific to
the region. On the other hand, if a country is heavily
dependent on a single region for its direct energy supply,
but it strategically differentiates its supplier portfolio of
indirect energy from that of direct energy, the indirectenergy supply network could compensate for thevulnerability of its direct energy supply and strengthen
the resilience of the entire supply chain of embodied
energy.
While the above concepts are critical to energy
policy and strategy, the selection of embodied energy
suppliers and their diversity has rarely been investigatedin the literature. In this paper, we evaluate countries’
energy resilience from the perspective of diversity insuppliers both of direct and embodied energy andexamine how selections of indirect energy supplies canweaken or strengthen the resilience of the entire
embodied-energy trade network. Specifically, we use a
multi-regional input output (MRIO) model to estimate
the quantities and directions of energy flows in the
global supply-chains of 134 countries proceeding via
three different energy channels: a) direct energy imports,b) embodied energy imports for production, and c)embodied energy imports for consumption. We thensystematically evaluate the diversity of suppliers for

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The Resilience of Embodied Energy Networks

each of these three channels by applying the ShannonWeaver index (SWI) and cosine similarities (CS) to the
supplier portfolio of each channel used to import energy
by each of the 134 countries.
Direct energy imports to a country are theimportation of energy resources such as coal, oil and gas
transported directly from energy-producing countries tothat country. The imported energy may be used indomestic electricity or heat generation, transportation
systems or domestic industrial processes as material
inputs. We define embodied energy imports for
production as the sum of the direct energy imports thatare consumed in the domestic production process of all
final goods, including ones that are exported, and theenergy that is consumed in other countries for producing
those final goods, that is, the amount of energy
consumed in the supply chains leading to the final goods
but located in other countries. We define embodied
energy imports for consumption as the sum of the directenergy imports that are consumed in the country for
producing final goods that are consumed domesticallyand the energy consumed in other countries to produce
final goods imported for consumption in the country.
The rest of the paper is structured as follows. Section
2 gives an overview of related literature that focuses on
the differences between direct energy and embodied
energy trade from the perspective of energy resilience.
Section 3 describes the model and data used in thispaper. Section 4 presents the major results and ananalysis. The conclusion follows in Section 5.

2. Related Literature
A large body of literature has proposed methodologies
of quantifying energy resilience of countries, which
include indicators such as the ratio of energy
consumption to gross domestic product (GDP), the ratioof imported primal energy to total energy consumption,and the consumption share of particular energy carriers.
Although some of these studies consider the choice of
supplier countries and their geographical diversity(Gupta, 2008; Cohen et al., 2011; Bhattacharyya, 2009;Frondel & Schmidt, 2014; Le Coq & Paltseva, 2009;
Löschel et al., 2010), their analyses have been restricted
to the diversification of direct energy imports.
As for embodied energy, Bortolamedi (2015) quantifies
the direct and indirect energy use of 25 European
countries by a MRIO model by extending three widelyused indicators of energy dependency to embodied
energy: (i) primary energy intensity (EI), which reflects
the degree to which economic activities depend on
primary energy as an input, (ii) net import dependency(NID), which reflects the domestic economy’s exposure
to price and quantity risks in global primary energy
markets, and (iii) primary energy carrier dependency(PECD), which reflects the reliance of economic
activities on specific energy carriers. Bordigoni et al.
(2012) also quantified the embodied energy flows of 28
European countries through an MRIO model. They

broke down the origin of embodied energy consumptionin each country and in each sector into national,
European Union (EU) (except national), and non-EU
categories. However, neither Bortolamedi (2015) nor
Bordigoni et al. (2012) consider geographical diversityof supplier countries.
Kharrazi et al. (2015) examined the world’s
embodied electricity trade from a perspective of thediversity of energy carriers, such as coal, oil, gas,
nuclear, hydro, solar and wind, using an MRIO modeland the SWI. This paper applies their methodologies togeographical diversity of supplier countries.
Tang et al. (2013) calculated the fossil energy
embodied in the UK’s imports and exports through asingle-region input-output (SRIO) model. They quantify
the national distribution of the UK’s embodied energy
exports, imports and net imports. China, accounting for
43% of the UK’s total net embodied energy imports, has
become the UK’s biggest net importer since 2008. Our
paper extends this perspective to a worldwide
comparison that explicitly quantifies the diversity ofembodied energy networks.

3. Model and Data
We estimate embodied energy flows between countries
using an MRIO model. The theoretical framework of
MRIO models is as follows. Suppose there are M
countries with N sectors. In equilibrium, the N × 1 output
vector x r ≡ {x ir}i=1,…N of country r can be expressed as
xr= Ζrr 1 + yrr+∑drs,

(1)

s≠r

where Zrr ≡ {Zijrr }i, j=1,…N is the N × N transaction matrix
between domestic sectors obtained from domestic inputoutput tables, 1 is a column vector of 1s (N × 1), y rr isthe vector of final demand for domestic goods (N × 1),
and drs is the vector of exports of domestic goods tocountry s (N × 1). drs can be divided into intermediate
inputs and final demand as drs = Zrs 1 + y rs, where Zrs is atransaction matrix from r’s sectors to s’s sectors, and y rs
is s’s final demand for r’s goods. Equation (1) can thus
be transformed into xr = Zrr 1 + yrr + ∑s≠r(Zrs 1 + y rs). Let
Arr ≡ { ijrr }i, j=1,…N denote the coefficient matrix of domestictransactions with each technical coefficient of ijrr ≡Zijrr /xjr ,and Ars ≡{ ijrs}i, j=1,…N be the coefficient matrix of transactions
from r’s sectors to s’s sectors with ijrs ≡Zijrs/xjs. Then we
get x r = Arr xr + ∑s≠r Ars xs + yrr + ∑s≠r yrs. By defining
X≡

x1
x2

,

A≡

xM

A11 A12
A21 A22

AM1 AM2

A1M
A2M

AMM

,

Y≡Σ
s

y1s
y2s

yMs

we have X = AX + Y. By transforming this, we obtain
the equilibrium equation of the MRIO model as
X = (I − A)− 1 Y .

(2)The data for Zrs, which are necessary for calculating
the off-diagonal elements of A, are estimated from the190

M. SATO et al.

bilateral trade-flow data and domestic input-output
tables of the Global Trade Analysis Project (GTAP). In
particular, we estimated the amount of intermediate
good trade, Z ijrs, by using the same methodology asPeters et al. (2011); i.e., assigning the total amount oftransactions of good i from country r to country s, whichis the sum of imports for both intermediate and final
demand, to s’s individual sector in proportion to theshare of that sector in s’s total imports of that good fromthe world, which can be calculated from GTAP’sbilateral trade-flow data.
Let c r ≡ {c ir }i = 1,…N be the column vector (N × 1) withthe amount of energy (million tons oil equivalent,
MTOE) per dollar of production in the three energy
sectors, coal, gas and oil, in country r and zero in theother entries. We call this unit “amount energy
intensity.” Let C ≡ [c 1' c 2' c M' ]' be a vector of worldenergy intensities, where the primes indicate transposesof the vectors.
The vector of embodied energy for production incountry r, EPr, is obtained by using equation (2) as
E Pr = Ċ̇(I − A)− 1 Y r ,where Ċ is a diagonal matrix that has each element of
C on the diagonal. EPr and Y r are defined respectively as
r'
r'
r' ]
e P,2
e P,M
' and Y r ≡ [0' (∑s y rs )' 0' ]', whereEPr ≡ [e P,1rr}{
e P, q ≡ e P, q, i i =1,…N is the column vector (N × 1) of theenergy production in country q embodied in the final
production in country r, and 0 is a column vector of 0s(N × 1). The vector of embodied energy imports for
production ErMP is obtained by replacing erP, r with 0.
The vector of embodied energy for consumption incountry r, ErC , is obtained as
E Cr = Ċ̇(I − A)− 1 Y wr ,rr' ]where ErC is defined as [er'C,1 er'C,2
e C,M' and e C,qr≡ {e C,q, i}i =1,…N is the column vector (N × 1) of the energy
production in country q embodied in the final consumption
in country r. Y wr is the part of final production that isexported to country r ; and Y wr ≡ [ y1r' y2r' yMr' ]'. The
vector of embodied energy imports for consumption ErMCr
is obtained by replacing e C,r with 0.
Note that, as described in the introduction, the vectorof embodied energy imports for production andconsumption contains part of the direct energy importsof that country. Therefore, embodied energy imports
here are not the same as “virtual” energy imports, which
do not include any energy that is physically transported
to that country.
We used the bilateral trade-flow and domestic inputoutput data of GTAP version 8.1 with 134 countries/
regions and 57 sectors (Narayanan et al., 2012) toconstruct our MRIO model. The energy intensities were
calculated for each energy sector (coal, gas and oil) of
each country by dividing the amount of energy
production in the sector, obtained from the IEA Energy
Atlas country database (IEA, 2015), by its output indollars calculated from the GTAP database. We used theaverages of energy productions in 2002 – 2012, which
covered the five years before and after the reference year
2007 of GTAP version 8.1. The internationaltransportation pool in GTAP was incorporated into A byfollowing the steps of Peters et al. (2011).
We evaluated the geographic diversity of energy
imports in two steps. First, as a basic measure ofgeographic diversity within each energy channel, we
used the Shannon-Weaver index (SWI) (Shannon, 1948;
Simpson, 1949). The SWI of direct energy imports ofenergy type k to country r is defined as
H D,r k = −∑ p D,r q, k ln p D,r q, kqp≡e
/ ∑u≠r e D,r u, k represents the share of energy
produced in country q in the total amount of directenergy imports of type k to country r, where e D,r u, k is theamount of energy directly imported from country u tocountry r. If the distribution is completely even, it takes
the maximum value, which is H D,r max, k ≡ −∑q p D,r k ln p D,r k= −ln(1/m), where p D,r k ≡ [(1/m)∑ u≠r e D,r u, k]/ ∑ u≠r e D,r u, k .
Thus, the SWI can be normalized to a value between 0
and 1 if divided by this maximum, i.e. E D,r k = H D,r k /H D,r max, k .
This is called Shannon’s Equitability (SE), which istypically used as an index of evenness.
Similarly, the SWI of embodied energy imports (forproduction or consumption) of energy type k to countryr is defined asr
D, q, kr
D, q, k

H E,r k = −∑ p E,r q, k ln p E,r q, kq

pE,r q, k ≡ e E,r q, k / ∑u≠r e E,r u, k represents the share of energy
produced in country q in the total amount of embodied
energy imports (for production or consumption) toris the amount of energy production
country r, where e E,u,k
in country u of type k that is embodied in the final goods
that are produced or consumed in country r. SE in thiscase is given as E E,r k = H E,r k /H E,r max, k . The higher the valueof H D,r k, H P,r k and H C,r k, or, equivalently, the closer thevalue of E D,r k, E P,r k and E C,r k to one, the more diverse asystem is evaluated to be. Case 1 in Fig. 1 illustrates thisevaluation step as a comparison between (a) and (b).
Comparisons can be made between different energy
channels of a particular country (i.e., H D,r k, H P,r k, H C,r k),
and between a particular energy channel of different
countries (i.e., H P,r k H P,s k, ).
The SWI, however, is insufficient for comparing theresilience of a combination of direct energy imports andembodied energy imports. Consider one country having
a direct energy import portfolio like (c) and an embodied
energy import portfolio like (d). Another country having
a direct energy import portfolio like (d) and an embodied
energy import profile like (e) will have exactly the same
SWI. Obviously, though, the latter country is more
resilient to shocks in country A, since its embodied
energy does not depend on country A as much as theformer.
In order to distinguish such cases, we introduced the

191

The Resilience of Embodied Energy Networks
Fig. 1 Illustrative examples comparing SWI and in CS.
<Case 1>(a)<Case 2>

Country A

Country A

(c)

(b)

(d)

(e)

Country A

Country A

Country C

Country B

Country B

Country A

Country C

Country C

Country B

Country B
Country B
Country C

Country C

SWI

<

SWI

SWI

=

SWI

=

CS

>

CS

SWI

Fig. 1 Illustrative examples comparing SWI and in CS.

concept of cosine similarity (CS) as a complementaryindex to the SWI. Cosine similarity is an indicator ofsimilarity between two vectors of an inner product spacethat measures the cosine of the angle between them. It isdefined as
C kr =rr
E D,r k ∙ E E,r k∑q≠r e D, q, k ∙ e E, q, k
=
r
r
r
2
|E D, k ||E E, k| ∑ √(e D, q, k) ∙ ∑ √(e rE, q, k)2
q≠r
q≠r
,

r
r
where ED,kand EE,kdenote the vector of direct energy
imports and that of embodied energy imports (forproduction or consumption) of energy type k, respectively.
e D,r q, k is the amount of energy directly imported fromcountry q to country r, and e E,r q, k is the amount of energy
production in country q embodied in the production or
consumption of final goods in country r (Tan et al.,2005). The value of C kr ranges from 0, indicating theorthogonality, to 1, meaning the exact similarity of thetwo vectors. In the above case, the CS between (c) and(d) is 1, which is larger than the CS between (d) and (e).

4. Results
4.1 Overview(a) Geographical diversity of global energy endowment,
production and exports
Before analyzing direct and embodied energy trade,
we considered the underlying geographical diversity of
the world energy endowment, production and exportation
on a country basis and a regional basis. Table 1 illustrates
the SWI values of production and exportation of coal,oil and gas on a country-by-country basis and a regional
basis. For production, oil is the most diversified,followed by gas and then coal. This reflects the situation
shown in Fig. 2, where East Asia produces 43.4 percentof the world’s coal, almost all of which is from China.
Looking at exports, oil is still the most diversified on acountry-by-country basis, but the positions of coal andgas become reversed. One of the reasons is that China,

Table 1 SWIs of world energy production and exports*.

Coal
Oil
Gas

Country basis
Production
Exports

Regional basis
Production
Exports

2.12 [0.43]
3.23 [0.66]
3.05 [0.62]

1.78 [0.36]
2.01 [0.41]
1.99 [0.41]

2.40 [0.49]
2.94 [0.60]
1.97 [0.40]

1.94 [0.40]
1.75 [0.36]
1.35 [0.28]* Figures in square brackets are SEs, which take values between 0 and 1.

Table 2 Mean and variance of countries’ SWIs through the threeenergy channels (country basis)*.
Direct energy
imports
Coal
Oil
Gas
Coal
Standard Oil
deviation
Gas

Mean

1.14 [0.23]
1.41 [0.29]
0.89 [0.18]
0.72 [0.15]
0.81 [0.16]
0.61 [0.13]

Embodied
Embodiedenergy imports energy imports
for production for consumption
2.01 [0.41]
2.43 [0.50]
2.41 [0.49]
0.37 [0.08]
0.47 [0.10]
0.73 [0.15]

2.02 [0.41]
2.56 [0.52]
2.52 [0.51]
0.35 [0.07]
0.41 [0.08]
0.68 [0.14]* Figures in square brackets are SEs, which take values between 0 and 1.

the world largest coal-producing country, consumes
most of the coal it produces domestically and exports
only a small fraction of its production. In fact, the totalexports from China amount to only 9.8 MTOE, nearly
60 percent of which goes to South Korea, while
Australia, the largest coal-exporting country, exports
115.4 MTOE of coal. This significantly increases thediversity of coal exporting regions. In addition, most of
the large gas-producing regions, including North
America, Europe and Russia and other former Soviet
Union countries, do not export gas to countries outside
the region. This increases the share of the Middle East
from 12.6 percent for production to 48.4 percent forexport, resulting in a decrease in the SWI of gas from3.05 to 1.97.
(b) Geographical diversity of direct and embodied
energy imports
In general, the geographical diversity of energy

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M. SATO et al.

imports is more important for a country that depends onimported energy for most of its domestic energy use. We
therefore focus our analysis, unless specified otherwise,on countries with an energy self-sufficiency rate of lessthan 10 percent.
Table 2 illustrates some basic statistics of the SWI
values of the three import channels. The mean SWI
values of embodied energy imports are much higher thanthose of direct energy imports. This is because theformer reflect the compositions of energy imports ofeach of the countries located in the global supply-chains,while the latter reflect only those of a single country.
This tendency is reflected in the overall distributions ofcountries in Fig. 3, in which almost all countries arelocated above the 45-degree line. In addition, embodied
energy imports for consumption are slightly morediversified than those for production (except coal). This
is in part because most countries consume a broader
range of final goods than they produce due tointernational production specializations.

Fig. 2 Shares of regional energy endowment, production and export.
Coal proved reserves

Oil proved reserves
Oceania0.3%

Sub-sahara
3.6%

North Africa
1.2%

Oceania
8.8%

Russia &former Soviet
Union
22.9%

Gas proved reserves

Sub-sahara
6.7%

East Asia
13.2%

North
America
16.4%

South Asia
7.2%

Europe12.2%

Coal export

Oceania
0.4%

Oceania26.7%

Europe11.4%
Middle East
0.0%

North Africa
0.0%Central &South
America
8.6%

NorthAmerica
11.0%South Asia
0.2%

Russia &former Soviet
Union
23.5%

Oil export

Sub-sahara
6.6%
Russia &former Soviet
Union
12.5%

Middle East
46.1%

Europe1.3%
Russia &former Soviet
Union
9.1%

Middle East
54.9%

North
America
27.7%

North Africa
0.0% Central &SouthAmerica
0.9%

Europe
3.7%

Central &South
America
7.6%Southeast
Asia
3.4%
Middle East
0.1%

Southeast
Oceania
East Asia Asia
Sub-sahara 1.6%
4.3% South Asia
1.0%
3.3%
1.4%
North Africa
5.7%
Central &
North
South
America
America
4.8%
4.4%

East Asia Southeast
Asia
1.2%
South Asia
1.1%
0.4%

Southeast
Asia
19.7%

Gas export

Southeast
Asia
2.2%

Russia &former Soviet
Union
14.7%

East Asia
0.1%
South Asia
0.0%

Middle East
37.5%

Oceania
1.4%

North Africa
10.8%

Central &South
America
6.3%

Sub-sahara
22.0%North Africa
5.3%
East Asia
3.4%

Sub-sahara
0.6%

North
America
6.2%

Southeast
Asia
26.5%

Europe5.3%
South Asia
0.0%

Middle East
48.4%

East Asia
Central &
0.0%
South
America
0.0%

Fig. 2 Shares of regional energy endowment, production and export.

Sources: proven reserves: BP (2015); production and exports: IEA (2015) and Narayanan et al. (2012).
Sources: proven reserves: BP (2015); production and exports: IEA (2015) and Narayanan et al. (2012).

North
America
0.1%

Europe1.9%
Russia &former Soviet
Union
10.4%

Fig. 3 DistributionTheof countries’
through Energy
the threeNetworks
channels (country basis).
ResilienceSWIsof Embodied

Fig. 3 Distribution of countries’ SWIs through the three channels (country basis).
For visibility, country names are omitted (gray dots), except for the countries mentioned in the text (black dots).

193

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M. SATO et al.

One striking fact compared to the diversity of worldenergy production in Table 1 is that the direct
importation of gas is the least diversified with a mean
SWI value of 0.89. In fact, the percentage of countries
that directly import more than 90 percent of each energy
type from a single country is 35 percent for gas but only
23 percent and 17 percent for coal and oil, respectively.
This is mainly due to the low diversity of world gas
exports themselves, as shown in Table 1. In contrast to
the low diversity of direct gas imports, embodied gas
imports maintain higher diversity. The mean SWI valueof embodied gas is 2.41 for production and 2.52 for
consumption, almost the same as those for embodied oil.
Of the three energy types, embodied coal imports are
the least diversified, while direct coal imports are at anintermediate position between oil and gas. There are two
factors behind that. First, as we will explain in thefollowing sections, for coal there is only a limited extent
of correlation between direct and embodied energy
imports, mainly due to its relative position in the supply
chain. Second, the weak correlation makes the situationof embodied coal imports reflect that of world coalproduction, whereas direct coal imports reflect world
coal exports. Although China’s large share of world coalproduction makes its SWI the lowest of the three energy
types, the world’s coal exports are well diversified,
especially on a regional basis (Table 1), since China
exports only a small fraction of the coal it produces. China
does export coal in the form of embodied energy, however,reflecting its position as the “world's factory,” which inturn decreases the diversity of embodied coal imports.
(c) Correlation between direct energy imports andembodied energy imports
Table 3 compares the correlation coefficients of the
SWI values of the two types of embodied energy imports
with those of direct energy imports, which are calculated
both for all countries and for only those whose SWI of
direct energy imports is less than the median.
Of the three energy types, coal has generally the
weakest correlation between direct energy imports andembodied energy imports. For countries with lower
diversity in direct energy imports, however, thecorrelation of gas is the weakest. In contrast, oil has highcorrelation between direct energy imports and embodied
energy imports.
Table 4 illustrates the average CS between the vector
of direct energy imports and that of embodied energy
imports. If we focus on the countries with lower
diversity in direct energy imports, the CS values of oil
and gas are much higher than that of coal. In fact, as we
will see in the following section, for most countries theprimary suppliers of embodied coal imports do notcoincide with those of direct coal imports, in sharp
contrast to the cases of oil and gas.

4.2 Analysis of Selected Countries(a) Coal
Because for coal there is only limited correspondence

between direct and embodied energy imports, countries
with similar SWI values of direct coal imports often
have variation in the SWI values of embodied coal
imports. For instance, Lithuania and Tunisia, whose
SWI values of direct imports are 0.08 and 0.16
respectively, have SWI values of embodied coal importsthat are as high as some European countries with much
more diverse suppliers of direct imports, such as France,
Italy, Austria and Sweden (Fig. 3 and Table 5 (a)). On
the other hand, Togo, Namibia and Nepal, whose SWI
values of direct imports are 0.00, 0.02 and 0.15,
respectively, also have the lowest SWI values forembodied coal imports, obtaining 65 – 83 percent of theirembodied coal imports from a single country.
Another important feature of coal is that the large
variation across countries is not limited to those withlow diversity in direct imports. Specifically, the coalimporting countries in Europe, including France, Italy,
Austria and Sweden, are much more diversified in theirembodied coal imports than East Asian countries like
Japan, Korea and Taiwan, even though their SWI valuesof their direct coal imports differ little from those of
their European counterparts (Fig. 3). The low diversity
in the embodied coal imports of East Asian countries isdue to the heavier dependency on coal production in
nearby resource-rich countries in the Asia-Pacific region,
notably China, Australia and Indonesia (Table 6). The
higher dependency leads to higher efficiencies of theirglobal supply-chains with respect to energy delivery in
the region. On the other hand, that would also indicate aweaker degree of energy resilience for these countries,
because some shocks related to coal production in theregion, for example, strengthened emission regulations
for coal-fired power plants in China, may affect thesecountries through direct and embodied energy importchannels simultaneously.
(b) OilA striking feature of oil is the high dependency ofsome Eastern European countries on a single country
both for direct and embodied oil. For instance, Latvia,
Table 3 Correlation coefficients between the SWIs of directenergy imports and embodied energy imports.
Embodied energy
Embodied energy
imports for production imports for consumption
SWI of realenergy imports
Coal
Oil
Gas

All
0.47
0.60
0.63

Not above
median
0.54
0.63
0.43

All
0.37
0.55
0.62

Not above
median
0.37
0.61
0.43

Table 4 Mean of the CSs between direct energy import vector andembodied energy import vector.
Embodied energy
Embodied energy
imports for production imports for consumption
SWI of realenergy imports
Coal
Oil
Gas

All
0.65
0.61
0.66

Not more thanthe median
0.57
0.80
0.81

All
0.59
0.59
0.66

Not more thanthe median
0.49
0.78
0.80

195

The Resilience of Embodied Energy Networks
Table 5 Primary suppliers of the countries with smallest SWIs in direct energy imports (bottom 20)*.
(a) Coal
Importingcountry

SWI

Togo
Mauritius
Namibia
SenegalLaos
Cambodia
Lithuania
UAE
Honduras
Nepal
TunisiaPeru
Sri Lanka
MalawiMadagascar
GuatemalaGuineaKenya
Switzerland
Hong Kong

0.00
0.02
0.02
0.04
0.04
0.07
0.08
0.10
0.12
0.15
0.16
0.17
0.22
0.37
0.44
0.45
0.57
0.67
0.67
0.70

Direct energy imports
Primary supplier

Share

South Africa
South Africa
South Africa
South Africa
Viet Nam
Indonesia
RussiaSouth Africa
Colombia
India
South Africa
Colombia
Indonesia
Mozambique
South Africa
Colombia
Australia
South Africa
Indonesia
Indonesia

100.0%
99.8%
99.7%
99.5%
99.5%
99.1%
98.9%
98.5%
98.4%
97.9%
97.7%
97.1%
96.5%
91.4%
88.2%
87.8%
90.0%
71.7%
81.8%
79.8%

Embodied energy imports for production Embodied energy imports for consumption
SWI

CS

Primary supplier

Share

SWI

CS

Primary supplier

Share

1.06
1.98
0.92
2.38
1.87
1.80
2.26
1.98
1.95
0.96
2.55
1.52
1.82
1.44
1.73
1.80
2.12
1.94
2.53
1.44

0.05
0.59
1.00
0.91
0.24
0.25
0.83
0.15
0.69
0.99
0.27
0.92
0.26
0.67
0.49
0.83
0.55
0.58
0.18
0.73

China
China
South Africa
South Africa
China
China
RussiaChina
Colombia
India
China
Colombia
China
South Africa
China
Colombia
China
China
China
China

65.1%
31.5%
82.8%
48.6%
42.7%
50.6%
35.6%
39.0%
32.4%
82.4%
28.4%
56.4%
38.8%
42.8%
50.8%
42.0%
36.9%
34.4%
21.2%
43.9%

1.21
2.04
0.82
2.00
1.89
1.68
2.27
1.93
1.94
1.02
2.52
1.84
1.78
1.58
1.66
1.93
1.91
1.94
2.53
1.47

0.03
0.54
1.00
0.72
0.19
0.34
0.72
0.12
0.55
0.97
0.25
0.63
0.24
0.53
0.49
0.63
0.22
0.52
0.17
0.52

China
China
South Africa
South Africa
China
China
Russia
China
China
India
China
China
China
South Africa
China
China
China
China
China
China

75.6%
32.6%
82.9%
33.6%
35.9%
40.6%
29.0%
41.8%
27.8%
71.1%
30.9%
36.7%
35.1%
47.2%
49.8%
31.7%
53.9%
36.4%
28.2%
55.2%

(b) Oil
Importingcountry

SWI

LatviaSlovakia
Belarus
Lithuania
Uruguay
Estonia
Tanzania
Bulgaria
Kenya
PolandCosta Rica
ZambiaNicaragua
MoroccoSenegalSri Lanka
El Salvador
IsraelCzech Republic
Ethiopia

0.00
0.03
0.04
0.06
0.07
0.08
0.23
0.25
0.26
0.28
0.35
0.63
0.71
0.73
0.75
0.82
0.84
0.86
0.87
0.93

Direct energy imports
Primary supplier

Share

RussiaRussiaRussiaRussiaVenezuela
Belarus
Qatar
RussiaUAE
RussiaVenezuela
UAE
MexicoSaudi Arabia
Nigeria
Saudi Arabia
EcuadorKazakhstan
RussiaIran

100.0%
99.7%
99.6%
99.3%
99.2%
98.9%
95.6%
94.0%
94.1%
94.5%
90.5%
77.0%
78.3%
51.5%
65.3%
54.1%
66.4%
74.8%
64.4%
61.7%

Embodied energy imports for production Embodied energy imports for consumption
SWI

CS

Primary supplier

Share

SWI

CS

Primary supplier

Share

1.77
1.53
0.50
1.22
1.55
2.12
2.44
1.60
1.88
1.48
1.86
2.61
2.02
1.80
2.62
2.06
2.19
2.11
1.99
3.07

0.99
0.99
1.00
1.00
0.97
0.02
0.05
1.00
0.92
1.00
0.95
0.87
0.92
0.98
0.91
0.94
0.94
0.97
0.97
0.50

RussiaRussiaRussiaRussiaVenezuela
RussiaSaudi Arabia
RussiaUAE
RussiaVenezuela
UAE
MexicoSaudi Arabia
Nigeria
Saudi Arabia
EcuadorKazakhstan
RussiaSaudi Arabia

63.3%
66.6%
91.2%
77.6%
62.3%
56.3%
34.5%
68.0%
46.5%
68.2%
46.4%
29.8%
40.9%
34.7%
28.9%
36.0%
35.0%
45.1%
47.9%
13.4%

1.94
2.26
2.12
1.69
1.93
2.12
2.53
2.41
1.85
2.09
1.68
2.17
2.03
1.58
1.84
2.00
2.04
1.91
2.06
2.53

0.99
0.99
1.00
0.99
0.95
0.02
0.06
0.99
0.86
0.99
0.92
0.81
0.87
0.96
0.87
0.90
0.88
0.95
0.97
0.49

China
South Africa
Ukraine
China
China
China
China
China
South Africa
China
China
China
South Africa
South Africa
ChinaSouth Africa
China
China
China
China

36.4%
27.5%
33.4%
42.2%
41.8%
44.7%
28.2%
31.9%
44.1%
43.8%
40.6%
30.4%
28.2%
47.2%
50.0%
33.6%
40.9%
53.9%
35.1%
20.2%

(c) GasImportingcountry

SWI

Kyrgyzstan
Lithuania
Finland
Slovakia
Belarus
Armenia
SwedenEstonia
Czech Republic
Ireland
GreeceLatviaUruguay
Kenya
Botswana
Laos
Nepal
CyprusSlovenia
Namibia

0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.02
0.04
0.05
0.06
0.06
0.06
0.13
0.25
0.25
0.31
0.32
0.34
0.45

Direct energy import
Primary supplier

Share

Uzbekistan**
RussiaRussiaRussiaRussiaKazakhstan
Denmark
RussiaRussiaUnited Kingdom
RussiaRussiaArgentina
Tanzania
South Africa
ThailandIndia
RussiaRussiaSouth Africa

100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
99.8%
99.8%
99.4%
99.3%
99.1%
99.0%
99.1%
98.0%
95.3%
95.2%
93.8%
93.7%
92.2%
90.2%

Embodied energy import for production Embodied energy import for consumption
SWI

CS

Primary supplier

Share

SWI

CS

Primary supplier

Share

0.78
0.93
1.36
1.22
0.37
0.76
2.50
1.25
1.65
0.83
2.30
1.03
1.93
3.15
2.74
2.06
2.69
3.10
2.46
2.78

0.97
1.00
1.00
0.99
1.00
0.99
0.66
1.00
0.99
1.00
0.97
1.00
0.95
0.04
0.46
0.91
0.79
0.78
0.96
0.42

Uzbekistan**
RussiaRussiaRussiaRussiaKazakhstan
Denmark
RussiaRussiaUnited Kingdom
RussiaRussiaArgentina
Saudi Arabia
MozambiqueThailandIndia
RussiaRussiaMozambique

77.2%
81.4%
72.7%
71.1%
91.3%
79.6%
24.5%
75.3%
61.5%
80.2%
47.9%
79.3%
52.8%
22.2%
28.4%
46.9%
25.6%
21.3%
45.4%
22.3%

1.04
1.16
1.52
1.59
0.49
1.11
2.70
1.42
1.96
1.37
2.50
1.26
2.06
3.06
2.64
2.04
2.90
3.08
2.41
2.82

0.91
1.00
0.99
0.99
1.00
0.97
0.55
1.00
0.99
1.00
0.94
1.00
0.95
0.03
0.46
0.91
0.77
0.86
0.96
0.44

Uzbekistan**
RussiaRussiaRussiaRussiaKazakhstan
RussiaRussiaRussiaUnited Kingdom
RussiaRussiaArgentina
Saudi Arabia
MozambiqueThailandIndia
RussiaRussiaMozambique

63.5%
74.3%
69.0%
69.2%
90.3%
68.2%
23.1%
71.7%
62.7%
74.4%
40.9%
75.4%
50.6%
21.9%
28.7%
46.4%
23.2%
25.0%
42.8%
23.3%

* The table shows only countries with a self-sufficiency rate for gas of less than 10%.
** Since the primary trade partner of Kyrgyzstan in the GTAP database is only referred to as “Rest of former Soviet Union,” we specify the country fromUN Comtrade database.

196

M. SATO et al.

Table 6 Suppliers of embodied coal to the countries of East Asia and Europe.
(a) Embodied coal imports for production
Japan
SWI
1.60
CS
0.95

Supplier
Australia
China
Indonesia
RussiaCanada

Share
42.5%
24.4%
16.5%
6.0%
3.3%

Korea
SWI
1.67
CS
0.95

Supplier
China
Indonesia
Australia
RussiaCanada

Share
40.0%
23.3%
18.9%
6.6%
3.8%

Taiwan
SWI
1.47
CS
0.97

Supplier
Indonesia
China
Australia
RussiaS. Africa

Share
37.2%
28.1%
24.1%
2.7%
2.3%

Austria
SWI
2,39
CS
0.79

Supplier
Czech R.
PolandChina
Germany
Russia

Share
21.7%
14.0%
13.7%
12.6%
7.6%

France
SWI
2.44
CS
0.72

Supplier
China
S. Africa
Australia
USA
Russia

Share
24.5%
17.2%
11.8%
10.7%
8.1%

Italy
SWI
CS

Supplier
China
S. Africa
Indonesia
USA
Australia

2.50
0.76

Share
20.7%
18.1%
12.9%
10.0%
7.3%

Sweden
SWI
2.42
CS
0.65

Supplier
China
Australia
USA
RussiaPoland

Share
25.0%
17.7%
11.7%
11.3%
5.9%

(b) Embodied coal imports for consumption
Japan
SWI
1.69
CS
0.88

Supplier
Australia
China
Indonesia
RussiaCanada

Share
37.2%
31.4%
14.9%
5.4%
2.9%

Korea
SWI
1.69
CS
0.93

Supplier
China
Indonesia
Australia
RussiaCanada

Share
42.2%
21.9%
17.8%
6.3%
3.5%

Taiwan
SWI
1.59
CS
0.96

Supplier
Indonesia
China
Australia
RussiaS. Africa

Share
34.9%
30.8%
22.8%
2.7%
2.2%

Austria
SWI
2.53
CS
0.66

Supplier
China
Czech R.
Germany
PolandRussiaSlovakia, Belarus, Lithuania, Bulgaria and Poland obtain
more than 94% of direct oil imports and 63 – 91% of
embodied oil imports for production from Russia (SeeTable 5 (b)), with their CS values being almost one.
Although this probably reflects the economic integrityof this area that is mediated by the cheap oil supply from
Russia, it also indicates that these countries may bevulnerable to shocks in Russia’s oil production via both
direct and embodied import channels.
(c) GasThe high dependency of Eastern European countries
on a single supplier is also distinctive for gas. In fact,
Kyrgyzstan, Lithuania, Finland, Slovakia, Belarus,
Armenia, Estonia and Latvia have both their direct andembodied gas imports significantly concentrated either
on Russia, Uzbekistan or Kazakhstan (See Table 5 (c)).
On the other hand, in contrast to oil, some othercountries with small diversity in their direct imports,
have high diversity in their embodied gas supplies. For
instance, Kenya, Cyprus, Nepal and Sweden havediversified their suppliers of embodied gas as much as,
or even more than, countries in Europe and East Asia,
such as Spain, France, Japan, Korea and Taiwan. Thissuggests a possibility for countries that depend heavily
on a few neighbors for their direct energy imports totake a strategy of diversifying their supply-chainsglobally in order to benefit from larger diversity for their
supply of embodied gas, thereby strengthening theenergy resilience of their economies.

5. Conclusions
Resilience is a crucial component to consider forsustainable energy. This paper evaluates the energy
resilience of countries from the perspective of diversity
in suppliers both of direct and embodied energy andexamines how selections of indirect energy supplies can

Share
17.9%
16.9%
13.8%
11.6%
7.7%

France
SWI
2.44
CS
0.60

Supplier
China
S. Africa
Australia
USA
Russia

Share
29.5%
14.7%
10.3%
9.7%
8.0%

Italy
SWI
CS

Supplier
China
S. Africa
Indonesia
USA
Australia

2.53
0.65

Share
25.4%
15.4%
11.0%
9.3%
6.9%

Sweden
SWI
2.47
CS
0.50

Supplier
China
Australia
RussiaUSA
S. Africa

Share
29.7%
13.5%
10.2%
9.9%
6.4%

affect the resilience of the entire embodied-energy trade
network. First, we find that the geographical diversity ofembodied energy imports is much greater than that of
direct energy imports. Second, while the supply
diversification level of direct gas imports is low mainly
due to the low diversity of world gas exports themselves,embodied gas imports maintain as high a diversity as
embodied oil imports. Third, embodied coal imports are
the least diversified, while direct coal imports are at anintermediate position between oil and gas. The situationof embodied coal imports reflects the small diversity ofworld coal production, while that of direct coal imports
reflects the large diversity of world coal exports. The
reason behind that is the fact that China, the world
largest coal-producing country, exports only a small
fraction of the coal it produces, but it does export coal in
the form of embodied energy, reflecting its position as
the “world᾿s factory.” Fourth, for coal (and gas in the
countries having lower direct energy diversities) there islower correlation between direct energy imports andembodied energy imports than for oil. Fifth, thediversification of embodied energy imports of coal (andgas) varies considerably across countries. This suggeststhat countries heavily dependent on a few neighbors fortheir direct energy imports might diversify their supply
chains globally in order to benefit from larger diversity intheir supply of embodied energy, thereby strengthening
the energy resilience of their economy.
As noted in the previous sections, geographicaldiversity of supplying countries is just one componentof energy resilience. For a comprehensive evaluation ofenergy resilience, it would be essential to combine thediversification indicators presented in this paper withother measurement methodologies that have mostly beenpracticed in a context of direct energy trade. One possibility
would be to incorporate geopolitical risk measures into
the diversification indicators. For instance, Gupta (2008)
quantifies the degree of supply concentration through a

The Resilience of Embodied Energy Networks

modified Herfindahl-Hirschman index with the market
shares adjusted for political risk in the oil-exporting
countries using the International Country Risk Guide(ICRG) ratings.
Finally, we observe that the correlations between the
SWI values of embodied energy imports and those of
direct imports are larger for oil (and to a lesser extentgas) than for coal and that the CS values of coal aremuch lower than those of oil and gas. It is difficult tofind a single systematic reason for this. One possible
factor, however, is the difference in the relative position
in a supply chain at which each energy type tends to be
used most intensively. As mentioned before, embodied
energy imports contain a part of the direct energy
imports, but how much of the direct energy is includedin embodied energy depends on the stage of the supply
chain at which the direct imports occur. In general, thecloser the stage is to the domestic final production or
final consumption, the more likely it is that the directenergy imports are included in the embodied energy ofthat country. If energy is used in more upstream stages,on the other hand, it is more likely that the intermediate
goods that are produced are exported and used for final
production in other countries.
It is possible that the differences in the correlations
can be explained in part by a tendency for oil and gas tobe used more intensely in the downstream stages of
production than coal. In many countries, a significant
amount of oil is used for road transportation, which isneeded for transporting construction materials such as
cement and for distribution of various wholesale
products. Similarly, a certain amount of gas istransformed into town gas for domestic and industrialuse, especially in developed countries. In both cases theenergy is used at stages relatively close to domestic final
production or consumption. In contrast, coal is mainly
used for power generation and steel-making. Electricity
generally is used in a broad range of industries fromupstream to downstream, and the steel industry is one of
the most upstream stages of production. To verify that, it
would be necessary to track the locations ofconsumption of direct energy imports in each country. It
is expected that this issue will be addressed in future
research.

Acknowledgements
The authors are grateful to the Ministry of theEnvironment, Japan, for supporting this research throughthe Environment Research and Technology Development
Fund, S-11 Project.

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Masahiro SATO
Research officer, Economic and Social ResearchInstitute, Cabinet Office / Fields of Research:
Natural capital use in open economy, Water
resilience, Economics of intelligence / 2014 –the present post; 2011– 2014 Associate professor,
Institute of Economic Research, Kyoto University;
2009 – 2011 Deputy director, Financial Markets
Division, Financial Services Agency; 2008 – 2009 Deputy director,
Quality- of- Life Bureau, Cabinet Office / Recent publications: SATO
(2015), International Economics of Water Resources: Building Water
Resilience for an Uncertain World, Keio University Press; SATO andNAKAYAMA (2014), Theory of inter-regional conjunctive use of water
resources, Vol. 1: Flow- flow type, KIER Discussion Paper No.1407,
Kyoto University; SATO and NAKAYAMA (2014), Theory of inter-regional
conjunctive use of water resources, Vol. 2: Stock- flow type, KIER
Discussion Paper No.1408, Kyoto University.

Ali KHARRAZIAli KHARRAZI is a Researcher at the Graduate
School of Public Policy, University of Tokyo,
Japan and Research Assistant at the Advanced
Systems Analysis Group, International Instituteof Applied Systems Analysis (IIASA), Austria.
His research focus is on advancing the conceptof resilience through data driven approaches for
Sustainable Development Goals in energy, trade, and urban systems. Ali
has made several research visits to countries including the USA, Austria,
and Germany. He is the recipient of the 2013 Green Talents Awards fromthe German Ministry of German Federal Ministry of Education andResearch and selected as a 2015 World Social Science Fellow by theInternational Social Science Council. Ali holds a PhD in Sustainability
Science from University of Tokyo, graduate degrees from the London
School of Economics in Information Systems and University ofCambridge in Innovation, Strategy, and Organization, and a bachelor’s
degree from the City University of New York in Economics.

Hirofumi NAKAYAMA

Steven KRAINES
Dr. Steven KRAINES received his doctorate in
Chemical Systems Engineering, the Universityof Tokyo under the supervision of Professor
Hiroshi KOMIYAMA in 1998. He wassubsequently hired as Assistant Professor in thesame department, where he worked mainly on
web- based model integration techniques andapplications in the area of designing low carbon urban systems withProfessor David WALLACE (Department of Mechanical Engineering,
Massachusetts Institute of Technology) and Professor Daniel FAVRAT(Laboratoire d'énergétique industrielle, L'École Polytechnique Fédérale
de Lausanne). Presently, Dr. KRAINES is working primarily in the field ofknowledge management and sharing using web- based semantic
technologies. Dr. KRAINES is currently working as an associate professor
at Tokyo City University.
Masaru YARIME
Masaru YARIME is Project Associate Professorof Science, Technology, and Innovation
Governance (STIG) at the Graduate School of
Public Policy in the University of Tokyo. He
also has an appointment as Honorary Reader inthe Department of Science, Technology,
Engineering and Public Policy (STEaPP) at
University College London. He has been awarded Abe Fellow by the U.S.
Social Science Research Council. He contributes to international
initiatives, including UNEP Finance Initiative on Environmental Risk
Integration in Sovereign Credit Analysis, Greenhouse Gas Protocol
Technical Working Group on GHG Risk Management, IPCC Working
Group III Fifth Assessment Report, and IPBES Expert Group on
Catalogue of Policy Support Tools and Methodologies. He received
B.Eng. and M.S. in Chemical Engineering from the University of Tokyoand the California Institute of Technology, respectively, and Ph.D. in
Economics and Policy Studies of Technological Change from Maastricht
University in the Netherlands. Previously he worked at the National
Institute of Science and Technology Policy.

Research fellow, InterGreen Research Institute /Fields of Research: Natural capital use anddisaster risk in open economy, Water resilience,
Economics of intelligence / 2014 – the present
post; 2013 – 2014 Research fellow, Institute of
Economic Research, Kyoto University / Recent
publications: SATO and NAKAYAMA (2014),
Theory of inter- regional conjunctive use of water resources, Vol. 1:
Flow- flow type, KIER Discussion Paper No.1407, Kyoto University;
SATO and NAKAYAMA (2014), Theory of inter-regional conjunctive useof water resources, Vol. 2: Stock- flow type, KIER Discussion Paper
No.1408, Kyoto University; Sato and Nakayama (2014), Estimation of world
virtual water and virtual land trade using a multi-regional input-output(MRIO) model, KIER Discussion Paper No.1405, Kyoto University;
SATO, HOMMA, and NAKAYAMA (2014), Estimation of world virtualwater and virtual land trade using a multi-regional input-output (MRIO)
model, KIER Discussion Paper No.1406, Kyoto University.
(Received 8 September 2015, Accepted 30 November 2015)