Applied Energy 165 (2016) 868–877
Contents lists available at ScienceDirect
Applied Energy
journal homepage: www.elsevier.com/locate/apenergy
Features and evolution of international fossil fuel trade network based
on value of emergy
Weiqiong Zhong, Haizhong An ⇑, Wei Fang, Xiangyun Gao, Di Dong
School of Humanities and Economic Management, China University of Geosciences, Beijing, China
Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources, Beijing, China
Lab of Resources and Environmental Management, China University of Geosciences, Beijing, China
h i g h l i g h t s
Number of trade relations and trade quantities follow power law distribution.
The pattern of top relations is diversified.
The trade density of fossil fuel is increasing.
Coal is the ‘‘cheapest” fuel measuring by ‘‘energy cost” and is most widely traded.
Countries with more than 20 trade relationships tend to have hierarchy structure.
a r t i c l e
i n f o
Article history:
Received 20 July 2015
Received in revised form 8 December 2015
Accepted 17 December 2015
Available online 12 January 2016
Keywords:
Fossil fuel
International trade
Emergy
Complex network
a b s t r a c t
Fossil fuel is crucial to the development of modern society. The major types of fossil fuel are coal, crude
oil and natural gas. The uneven distribution of the production and consumption of fossil fuel makes the
fossil fuel flows between countries by international trade. This study aims to quantitatively analyse the
features and evolution of the international trade of fossil fuel by complex network and emergy. We transform the trade quantity of coal, crude oil and natural gas into emergy by transformity and the sum of the
three emergies is the emergy of fossil fuel. The complex network models of the integrated fossil fuel trade
as well as the trade of coal, crude oil and natural gas are built up based on the value of emergy. We analyse the trade relationships, trade quantity, trade density, and hierarchy structure of the networks.
We find that the number of trade relationships and the trade quantities follow the power law distribution; countries with many export relationships tend to have many import relationships; the centralization of trade quantity is becoming more intense for fossil fuel, crude oil and coal, but less intense for
natural gas; the pattern of top relationships is diversified; the trade density of fossil fuel is increasing;
and countries with more than 20 trade relationships tend to have a hierarchy structure. Our findings
implicate that as the hierarchy structure is becoming more ordered, the statuses of the countries are
clearer, and thus it is easier for policy makers to identify the roles of their own countries or the roles
of other countries. Coal is the ‘‘cheapest” fuel measuring by ‘‘energy cost” and is the most widely traded
type of fossil fuel. When two countries exchange fossil fuel and money in the international trade, they
should look further into the energy cost of them and reconsider the effectiveness of the trade. Our study
can also reveal the trade strategy of the countries.
Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction
The international trade of fossil fuel is an integrated system
with three major commodities: coal, crude oil and natural gas.
⇑ Corresponding author at: School of Humanities and Economic Management,
China University of Geosciences, Beijing, China. Tel.: +86 01082323783; fax: +86
01082321783.
E-mail address: [email protected] (H. An).
http://dx.doi.org/10.1016/j.apenergy.2015.12.083
0306-2619/Ó 2015 Elsevier Ltd. All rights reserved.
According to the statistics of U.S. Energy Information Administration, the three major types of fossil fuels account to 86% of the
world total primary energy consumption in 2012.1 There are
numerous countries and complicated relationships in the
international trade of fossil fuel which form a huge and complex system. A better understanding of the characteristics of this integrated
1
http://www.eia.gov/totalenergy/.
W. Zhong et al. / Applied Energy 165 (2016) 868–877
complex system can help us understand the international fossil fuel
market [1]. Previous studies on international fossil fuel trade focused
on energy security [2], trade patterns [3] and political factors [4].
This study aims to quantitatively analyze the features and evolution
of international fossil fuel trade by combining network analysis and
emergy transformity. It provides a new perspective for the study of
international trade of fossil fuel.
Complex network modeling has the advantage of analyzing the
complex system of international trade. In 2003, Serrano et al. [5]
introduced complex network model into the study of international
trade. Then Garlaschelli et al. [6] studied the fitness-dependent
topological properties of the international trade network. The
study of Fagiolo et al. [7,8] provided a detailed quantitative analysis of the trade links and the role of the countries topologically and
dynamically. Vidmer et al. [9] applied link prediction algorithms to
predict the future evolution of the international trade network. In
recent years, some scholars used complex network to analysis the
international trade of energy. For example, Geng et al. [10] studied
the structure and the integration of the international natural gas
market by complex network. Üster et al. [11] designed an integrated large-scale mixed-integer nonlinear optimization model to
analyze the natural gas transmission network. Zhong et al. [12]
constructed weighted and unweighted complex network models
to study the evolution of communities in the international oil
trade. Ji et al. [13] introduced a global oil trade core network to
analyze the overall features, regional characteristics and stability
of the oil trade. Zhong et al. [13] and Zhang et al. [14] introduced
complex network to analyze the competition between countries
in the oil trade.
However, as far as we know, most of the previous studies on
international energy trade are based on single commodity. Our
study provides an integrated view of the international trade of fossil fuel by considering the trade quantity of coal, crude oil and natural gas together in the model, and reveals features of the
integrated system.
A unified unit to measure the commodities of coal, crude oil and
natural gas is needed because they are in different forms and qualities. Traditionally, money is applied to measure the integrated
trade volume, however the fluctuating price and exchange rate
[15] will affect the results. The unit of ‘‘joule” can be used to measure energy content of the fuels, however it only measures the ability to cause work. Exergy is another concept which measure the
maximum useful work of the fuels [16]. These methods cannot
reflect the ‘‘cost” of the energy which means how much energy is
needed in order to produce a certain amount of fossil fuel. The
main idea of Emergy is ‘‘energy cost” which regards the difference
of energy quality and the accumulative cost of energy [17]. It measures the values of resources in common units of the solar energy
used to make them (in unit of seJ) [18,19]. Transformity (in unit of
seJ/J) can be used to transform the trade quantity of coal, crude oil
and natural gas into emergy. The sum of the three emergies can be
used to measure the emergy flow of fossil fuel. If a country exports
fossil fuel, it not only exports the energy currently existing in the
commodities, but also exports the energy consumed in forming,
mining and producing the commodities. If a country imports fossil
fuel, it also imports the embodied ‘‘energy cost” in the commodities. As far as we know, most of the previous studies of international energy trade use money, energy or exergy as trade
quantity. Our study goes further in considering the accumulative
amount of solar energy (Emergy) as trade quantity.
In this study, we design the integrated complex network model
of fossil fuel as well as the single commodity network models of
coal, crude oil and natural gas based on the emergy flows among
countries. The characteristics of the international fossil fuel trade
can be reflected by network analysis. Section 2 introduces the data
and the process of modeling. Four indexes of network analysis are
869
introduced: degree and strength are indicators of the individual
countries, and network density and hierarchy structure are indicators of the whole network. Section 3 is the analysis of trade relationships, trade quantity, trade density, and hierarchy structure
of the network. Section 4 is the discussion and conclusion remarks.
2. Data and method
2.1. Data and transformity
The data of international trade of coal, crude oil and natural gas
is from the website of UN Comtrade which contains all the export
and import flows among 226 countries. The trade volumes are
measured by kilogram. We selected the annual data of all the available countries from 2000 to 2013. We transformed the trade quantities of the three fuels into emergy and the sum of them is the
emergy of fossil fuel. The description of the data source, the energy
content of the commodities and the transformity of coal, crude oil
and natural gas are shown in Table 1. In our data, only crude oil is
included in the HS Code 2709, and there are several categories of
coal in the HS Code 2701. We use the average energy content
and the average emergy transformity of crude oil and coal in our
study.
The total emergy in fossil fuel trade increased during
2000–2008 as the world economy grew, and the total emergy
declined in 2009 after the US mortgage subprime crisis.2 The
majority of fossil fuel trade emergy was contributed by crude oil,
coal contributed the least emergy, and natural gas contributed a
little more than coal (please see Fig. 1).
2.2. International trade network model
The complex network model G = (V, E) contains the nodes V and
the edges E, where V = {vi:i = 1, 2, . . ., n}, n is the number of nodes,
E = {ei:i = 1, 2, . . ., m}, and m is the number of edges. In our model,
the nodes are the countries, the edges are the trade relationships,
the directions of the edges are the directions of the emergy flows,
and the weights of the edges are the value of emergies. We constructed network models of the integrated fossil fuel trade as well
as the single commodities based on the transformed data.
An example of the integrated fossil fuel trade network in 2012 is
shown in Fig. 2. We filtered the network with trade quantity in
order to make it more readable by showing the top 50 countries
in trade quantity in the network. The size of the node is the total
trade quantity of the country. The larger the node is, the more
emergy the country has trade in this year. The width of the edge
is the value of the emergy of this trade link. The wider the edge
is, the higher value of emergy this trade link has.
2.2.1. Degree: the range of the direct impact
Degree is the number of direct trade relationships of a country.
It reflects the range of a country’s direct impact. The out-degree is
the number of export links a country has with others, and the indegree is the number of import links. The higher value of outdegree or in-degree indicates a wider range of the country’s direct
impact. These values are computed by [21]
out
ki ðtÞ ¼
n
X
dij ðtÞ
ð1Þ
j¼1
in
ki ðtÞ ¼
n
X
dji ðtÞ
ð2Þ
j¼1
2
The U.S. subprime mortgage crisis was a nationwide banking emergency that
coincided with the U.S. recession of December 2007–June 2009 (explanation from
Wikipedia).
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W. Zhong et al. / Applied Energy 165 (2016) 868–877
Table 1
Data description, energy content and transformity.
Commodity
HS code
Description
Energy content [20]
Transformity [19]
Coal
Crude oil
Natural gas
2701
2709
271,111
271,121
Coal; briquettes, ovoids and similar solid fuels manufactured from coal
Petroleum oils and oils obtained from bituminous minerals, crude
Natural gas, liquefied (LNG)
Natural gas in gaseous state (NG)
2.094E4 J/g
4.337E4 J/g
8.17E4 seJ/J
1.48E5 seJ/J
3.883E7 J/m3
1.71E5 seJ/J
Note: Data source is http://comtrade.un.org/. In the data source, the unit of the commodities is kilogram, thus we convert the units by 1 kg of NG = 1400 L of NG, 1 kg of
LNG = 2.35 L of LNG, and 1 L of LNG = 600 L of NG. The geobiosphere baseline is 15.2E24 seJ/yr. The transformity of coal is the average of hard coal and soft coal according to
[19].
where if country i exports oil to country j during year t, a link from i
to j is drawn, and dij(t) = 1. Otherwise, no link is drawn, and dij(t) = 0.
out
The out-degree ki ðtÞ of country i in the year t is the sum of dij(t),
in
and the in-degree ki ðtÞ of country i in the year t is the sum of dji(t).
If the network has a degree distribution that can be fit with a
power law distribution (4), it implies that the network is a scalefree network, where c is the power law index and k is the degree
of the nodes [10].
c
PðkÞ k
ð3Þ
2.2.2. Strength: the quantity of emergy
The total trade quantity of emergy of a country can be measured
by strength in the network. The out-strength sout
i ðtÞ and in-strength
sin
ðtÞ
of
country
i
reflect
a
node’s
importance
in the network coni
sidering both relationships and quantities of emergy. The higher
in
the value is, the more important the country is. sout
i ðtÞ and si ðtÞ
are computed by [21]
sout
i ðtÞ ¼
Crude oil
Natural gas
n
X
dji ðtÞ wji ðtÞ
ð5Þ
j¼1
where wi,j(t) is the weight of dij(t), which is the total amount of
emergy that country i exports to country j during the year t.
2.50E+25
Total Emergy (seJ)
ð4Þ
j¼1
sin
i ðtÞ ¼
Coal
n
X
dij ðtÞ wij ðtÞ
2.00E+25
2.2.3. Network density: the tightness of relationships among countries
Network density can be used to measure the tightness of the
trade relationships among the countries in the fossil fuel trade network. It equals to ‘‘total number of relationships that actually
exist” divided by ‘‘maximum number of relationships that theoretically can exist‘‘. If the number of actual relationship is m, the number of nodes is n, then the network density is [10]:
1.50E+25
1.00E+25
5.00E+24
0.00E+00
Year
Fig. 1. Total emergy in the 4 types of trade networks.
D¼
2m
nðn 1Þ
Fig. 2. Filtered network model of international fossil fuel trade in 2012.
ð6Þ
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W. Zhong et al. / Applied Energy 165 (2016) 868–877
fossil fuel are shown in Table 2. We can see that the top 10 countries were mainly from North America, Europe and East Asia area.
From 2000 to 2009, the USA was the country with the largest number of import relationships. However, in 2010 and 2013 China
became No. 1, and in 2011 and 2012 India was No. 1 in import relationship. The top 10 countries in number of export relationships of
fossil fuel are shown in Table 3. An interesting phenomenon is that
many importing countries were also with high out-degrees. The
USA ranked No. 1 in the number of export relationships through
the whole observation period. The rank of China was also increasing, and became No. 2 since 2006.
2.2.4. Hierarchy structure: the order of the trade network
Clustering coefficient of a country is the probability of trade
relationship existing between the countries connecting to this
country in the network. It reflects the connectivity of the neighboring countries of this country. If a country’s neighbors are closely
related, the country has a higher clustering coefficient; on the contrary, if a country’s neighbors are loosely related, the clustering
coefficient of this country is lower. If nodes with the same degree
have similar clustering coefficient, the hierarchy structure of the
network is more ordered because similar roles have similar
connectivity.
The clustering coefficient Ci of node i with degree ki is computed
by:
C i ¼ ni =ki ðki 1Þ
3.2. Trade quantity
ð7Þ
The trade quantities of emergy are carried by the trade links
(edges), thus we analyzed the accumulative distributions of the
weights of the edges in the 4 types of networks each year. The
results of 3 years (2000, 2006, and 2013) are shown in Fig. 4. We
should focus on the gaps of the curves which were moving toward
up left corner. This implies that the trade of coal, crude oil and fossil fuel were becoming more concentrated from 2000 to 2013.
However, the tendency of natural gas was in opposite direction.
It was less concentrated.
The proportions of edges shouldering 80% of the trade quantity
are shown in Fig. 5. A small number of trade links shoulder a large
part of the trade quantities. This phenomenon is less obvious in the
network of crude oil, and is more obvious in the network of natural
gas. We can see that less than 8% of the trade relationships contain
up to 80% of the trade quantity of emergy in the fossil fuel trade
network.
The top 10 countries in importing emergy of fossil fuel are
shown in Table 4. We can see that the top 10 countries are mainly
where ni is the number of the edges among the neighbors of node i.
3. Results and analysis
3.1. Trade relations
Degree is the number of edges of a node in the network. It is an
index measuring how many countries have trade relationships
with a given country. It indicates the activeness of a country in
the network. Countries with higher degrees possess important
roles, because they have wider range of trade, and their impacts
can directly reach more partners.
The trade relationships in the 4 types of networks each year follow power law distribution. A small number of countries own
many trade partners and most of the countries own a few trade
partners (the figures of 2000, 2006 and 2013 are shown in
Fig. 3). The top 10 countries in number of import relationships of
ln (p(k))
0
0
4
6
0
y = -0.7363x - 2.1871
R² = 0.7843
-4
2
-2
4
0
6
y = -0.6854x - 2.2784
R² = 0.7389
-4
-2
ln (k)
2
ln (k)
0
-2
ln (k)
ln (p(k))
ln (p(k))
0
4
6
y = -0.6164x - 2.5196
R² = 0.7035
-4
-6
-6
-6
-8
-8
-8
2000
2
2013
2006
Fig. 3. Power law of the number of trade partners.
Table 2
Top 10 countries in in-degree in fossil fuel trade.
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Rank
1
2
3
4
5
6
7
8
9
10
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
China
India
India
China
Italy
France
Germany
China
France
France
China
Germany
Germany
China
USA
USA
China
Netherlands
France
UK
France
Germany
Germany
Germany
Germany
China
China
India
India
China
Netherlands
USA
Germany
Italy
Spain
Spain
China
China
France
UK
France
Germany
UK
UK
USA
Germany
UK
Spain
Italy
Italy
Spain
UK
UK
France
India
UK
France
Germany
France
South Korea
Spain
Germany
Netherlands
France
UK
Spain
Spain
Italy
Canada
Spain
Italy
France
Germany
India
China
China
China
UK
Italy
Netherlands
Canada
Spain
Netherlands
France
Germany
Italy
South Korea
France
Netherlands
Netherlands
South Korea
Canada
South Korea
Italy
Netherlands
Canada
Spain
South Korea
Canada
Netherlands
Italy
UK
South Korea
South Korea
UK
Netherlands
Canada
Canada
South Africa
Netherlands
UK
Canada
Spain
South Korea
UK
Canada
Singapore
Thailand
Canada
Belgium
Netherlands
South Korea
Italy
India
Italy
Netherlands
South Korea
Spain
Japan
Italy
872
W. Zhong et al. / Applied Energy 165 (2016) 868–877
Table 3
Top 10 countries in out-degree in fossil fuel trade.
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Rank
1
2
3
4
5
6
7
8
9
10
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
South Africa
UK
South Africa
UK
UK
South Africa
China
China
China
China
China
China
China
China
Russia
Russia
UK
Russia
Russia
China
South Africa
South Africa
South Africa
UK
UK
South Africa
South Africa
UK
UK
South Africa
Russia
South Africa
China
Germany
UK
UK
UK
South Africa
South Africa
Russia
UK
South Africa
Germany
Germany
Germany
Germany
South Africa
UK
Germany
Germany
Germany
Nigeria
Russia
UK
Russia
Russia
China
China
Italy
China
Germany
Russia
Russia
India
Russia
Russia
Germany
Germany
Germany
Netherlands
France
Australia
China
Australia
Australia
Italy
Netherlands
Russia
France
Germany
Nigeria
Colombia
France
Germany
Netherlands
Italy
Australia
Indonesia
Italy
Ukraine
Italy
Italy
UAE
UAE
Ukraine
Netherlands
Netherlands
France
Australia
France
UAE
Italy
Netherlands
Australia
UAE
France
Australia
Italy
Italy
Ukraine
Italy
Italy
Italy
Netherlands
Indonesia
Netherlands
France
France
Indonesia
Netherlands
Netherlands
Australia
Netherlands
Italy
Ukraine
Ukraine
Fig. 4. Accumulative distribution of the weights (emergy).
from North America, East Asia and Europe. The USA ranked No. 1 in
most of the years, and China became No. 1 importing country in
2013. Japan ranked No. 2 in most of the years except in 2012.
The top 10 countries in exporting emergy of fossil fuel are shown
in Table 5. Russia replaced Saudi Arabia and became the No. 1
exporting country since 2001, and Saudi Arabia had been No. 2
ever since.
Top 10 trade relationships in value of emergy in fossil fuel trade
are shown in Table 6. We can see that the trade relationship with
highest value of emergy is from Canada to the USA. In the early
years, the flows from North America and South America to the
USA were the top flows with high emergy. However, as the imports
of the USA and some other developed countries decreased and the
imports of some developing countries increased, the ranks of top
10 relationships were changing.
3.3. Trade density
The trade density of the fossil fuel trade was increasing from
2000 to 2013 (please see Fig. 6). The trade densities of coal and
crude oil were at the same level, while the trade density of natural
gas was much lower than the others. This may due to the
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W. Zhong et al. / Applied Energy 165 (2016) 868–877
Fossil
Coal
Oil
second most, and the natural gas was the least (please see Fig. 7
(a)).
Although the number of countries was increasing slightly, the
number of trade links among them was increasing obviously. As
a result the trade density was increasing. Consistent with the feature of the number of countries, the number of trade links of coal,
crude oil and natural gas had the same features. The number of
trade links of coal was the most, the number of trade links of crude
oil was the second most, and the number of trade links of natural
gas trade was much less than the others (please see Fig. 7(b)).
Gas
14%
Proporon
12%
10%
8%
6%
4%
2%
0%
3.4. Hierarchy structure
Year
Fig. 5. Proportion of edges shouldering 80% of emergy.
restriction of transportation. This is because the majority of natural
gas was transported by pipeline and LNG tankers. The cost of transportation made it is harder for natural gas to be widely traded
between distant countries. To look further into the trade density,
we plotted the number of countries and the number of trade relationships of the 4 types of networks.
There were around 200 countries participating in the fossil fuel
trade during the observation years. The total numbers of countries
were slightly increasing in the four types of networks during the
observation period. The numbers of countries in the three types
of single commodities were similar. The crude oil trade was the
Degree indicates the direct impact of a country. Countries with
higher degree play important roles, because they directly affect
more countries. Clustering coefficient reflects the connectivity of
the neighboring countries of this country. If nodes with the same
degree have similar clustering coefficient, the hierarchy structure
of the network is more ordered because similar roles have similar
connectivity.
We plotted the degree and the clustering coefficient of all the
countries in scatter diagrams chronologically in Fig. 8. The abscissa
is degree and the ordinate is the value of clustering coefficient [22].
From the distribution of the points we can see that countries with
higher degree tend to have lower clustering coefficient. The centrality of the points in Fig. 8 reflects the hierarchy structure of
the network. We can see that the hierarchy structure of fossil fuel
trade network is not obvious because nodes have similar degree
Table 4
Top 10 countries in in-strength in fossil fuel trade.
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Rank
1
2
3
4
5
6
7
8
9
10
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
USA
China
Japan
Japan
Japan
Japan
Japan
Japan
Japan
Japan
Japan
Japan
Japan
Japan
China
Japan
South Korea
South Korea
South Korea
South Korea
South Korea
France
France
Italy
France
China
China
China
Japan
USA
Germany
France
Germany
Germany
France
Italy
South Korea
France
China
South Korea
Italy
South Korea
India
India
Italy
Germany
France
France
Germany
South Korea
Italy
South Korea
South Korea
India
South Korea
India
South Korea
South Korea
France
Italy
Netherlands
Italy
Italy
Germany
Netherlands
China
Italy
Italy
India
Italy
Italy
Germany
Netherlands
Netherlands
Italy
Netherlands
Netherlands
Netherlands
China
Germany
India
France
Netherlands
France
Netherlands
Italy
Spain
Spain
Spain
China
China
China
Germany
India
Germany
Germany
France
Netherlands
Germany
Croatia
China
UK
UK
Spain
Spain
Belgium
Belgium
Netherlands
Netherlands
Netherlands
Germany
Germany
UK
France
UK
Ukraine
Ukraine
Belgium
UK
Spain
UK
Spain
Spain
UK
UK
UK
Spain
UK
Table 5
Top 10 countries in out-strength in fossil fuel trade.
Year
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Rank
1
2
3
4
5
6
7
8
9
10
Saudi Arabia
Russia
Russia
Russia
Russia
Russia
Russia
Russia
Russia
Russia
Russia
Russia
Russia
Russia
Russia
Saudi Arabia
Saudi Arabia
Saudi Arabia
Saudi Arabia
Saudi Arabia
Saudi Arabia
Saudi Arabia
Canada
Saudi Arabia
Saudi Arabia
Saudi Arabia
Saudi Arabia
Saudi Arabia
Norway
Norway
Norway
Canada
Canada
Canada
Canada
Canada
Saudi Arabia
Norway
Norway
Qatar
Norway
Qatar
Canada
Canada
Canada
Norway
Norway
Norway
Norway
Algeria
Norway
Canada
Canada
Norway
Indonesia
Norway
Algeria
UK
UK
Algeria
Algeria
Algeria
Algeria
Norway
Qatar
Australia
Algeria
Canada
Australia
Indonesia
UK
Venezuela
Australia
Iran
Iran
UAE
Nigeria
Iran
Algeria
Indonesia
Qatar
Indonesia
Qatar
Australia
UAE
Australia
Mexico
Australia
Nigeria
Iran
UAE
Nigeria
UAE
Algeria
Indonesia
Australia
Canada
Canada
Iran
UAE
Algeria
UAE
UAE
Venezuela
Iran
UAE
Australia
Iran
Australia
Nigeria
UAE
UAE
Indonesia
Iran
UAE
Mexico
Australia
Australia
Australia
Australia
Nigeria
Nigeria
Nigeria
Algeria
Nigeria
Kazakhstan
Australia
Mexico
Indonesia
UK
Venezuela
Nigeria
Venezuela
Indonesia
Iran
UAE
Iran
Kazakhstan
Kazakhstan
Netherlands
874
W. Zhong et al. / Applied Energy 165 (2016) 868–877
Table 6
Top 10 trade relationships in value of emergy in fossil fuel trade.
Rank
Exporter
Importer
Fossil emergy (seJ)
Rank
Exporter
Importer
Fossil emergy (seJ)
2000
1
2
3
4
5
6
7
8
9
10
Canada
Saudi Arabia
Venezuela
Mexico
UAE
Saudi Arabia
Nigeria
Australia
Norway
Norway
USA
USA
USA
USA
Japan
Japan
USA
Japan
UK
Germany
1.09E+24
4.45E+23
4.43E+23
4.17E+23
3.80E+23
3.45E+23
3.03E+23
3.00E+23
2.95E+23
2.69E+23
2001
1
2
3
4
5
6
7
8
9
10
Canada
Saudi Arabia
Venezuela
Mexico
UAE
Saudi Arabia
Australia
Norway
Nigeria
Norway
USA
USA
USA
USA
Japan
Japan
Japan
UK
USA
Germany
1.24E+24
5.14E+23
4.65E+23
4.42E+23
3.68E+23
3.49E+23
3.08E+23
3.06E+23
2.80E+23
2.78E+23
2002
1
2
3
4
5
6
7
8
9
10
Canada
Saudi Arabia
Mexico
Venezuela
UAE
Saudi Arabia
Norway
Australia
Norway
Russia
USA
USA
USA
USA
Japan
Japan
Germany
Japan
UK
Ukraine
1.19E+24
4.77E+23
4.73E+23
4.55E+23
3.45E+23
3.39E+23
3.26E+23
3.06E+23
3.05E+23
2.88E+23
2003
1
2
3
4
5
6
7
8
9
10
Canada
Saudi Arabia
Mexico
Venezuela
UAE
Norway
Saudi Arabia
Russia
Norway
Australia
USA
USA
USA
USA
Japan
UK
Japan
Ukraine
Germany
Japan
1.46E+24
5.55E+23
4.98E+23
4.55E+23
3.62E+23
3.54E+23
3.53E+23
3.25E+23
3.22E+23
3.14E+23
2004
1
2
3
4
5
6
7
8
9
10
Canada
Venezuela
Mexico
Saudi Arabia
UAE
Norway
Saudi Arabia
Russia
Nigeria
Australia
USA
USA
USA
USA
Japan
UK
Japan
Ukraine
USA
Japan
1.52E+24
5.17E+23
4.97E+23
4.84E+23
3.77E+23
3.67E+23
3.59E+23
3.54E+23
3.48E+23
3.31E+23
2005
1
2
3
4
5
6
7
8
9
10
Canada
UAE
Venezuela
Mexico
Saudi Arabia
Saudi Arabia
Norway
Netherlands
Australia
Nigeria
USA
Japan
USA
USA
USA
Japan
UK
Belgium
Japan
USA
1.94E+24
6.10E+23
5.12E+23
4.88E+23
4.64E+23
4.14E+23
3.97E+23
3.92E+23
3.58E+23
3.58E+23
2006
1
2
3
4
5
6
7
8
9
10
Canada
Mexico
Venezuela
Saudi Arabia
Saudi Arabia
Norway
Netherlands
Belgium
UAE
Australia
USA
USA
USA
USA
Japan
UK
Belgium
France
Japan
Japan
1.74E+24
5.03E+23
4.67E+23
4.52E+23
4.36E+23
4.24E+23
4.16E+23
3.88E+23
3.85E+23
3.72E+23
2007
1
2
3
4
5
6
7
8
9
10
Canada
Algeria
Belgium
Mexico
Venezuela
Saudi Arabia
Norway
Netherlands
Australia
Saudi Arabia
USA
Italy
France
USA
USA
USA
UK
Belgium
Japan
Japan
1.86E+24
5.67E+23
5.28E+23
4.65E+23
4.61E+23
4.53E+23
4.39E+23
4.09E+23
4.01E+23
3.79E+23
2008
1
2
3
4
5
6
7
8
9
10
Canada
Belgium
Saudi Arabia
Norway
Netherlands
Venezuela
Australia
Mexico
Saudi Arabia
UAE
USA
France
USA
UK
Belgium
USA
Japan
USA
Japan
Japan
2.55E+24
5.07E+23
4.80E+23
4.50E+23
4.25E+23
4.22E+23
4.10E+23
3.87E+23
3.83E+23
3.66E+23
2009
1
2
3
4
5
6
7
8
9
10
Canada
Norway
Venezuela
Australia
Saudi Arabia
Mexico
Russia
Russia
Saudi Arabia
UAE
USA
UK
USA
Japan
Japan
USA
Netherlands
Italy
USA
Japan
8.58E+23
4.02E+23
3.94E+23
3.71E+23
3.68E+23
3.42E+23
3.39E+23
3.29E+23
3.27E+23
2.91E+23
2010
1
2
3
4
5
6
7
8
9
10
Canada
Algeria
Mexico
Norway
Australia
Russia
Venezuela
Saudi Arabia
Saudi Arabia
Nigeria
USA
Italy
USA
UK
Japan
Netherlands
USA
Japan
USA
USA
1.07E+24
4.81E+23
4.55E+23
4.55E+23
4.19E+23
3.84E+23
3.58E+23
3.54E+23
3.47E+23
3.23E+23
2011
1
2
3
4
5
6
7
8
9
10
Canada
Mexico
Norway
Australia
Saudi Arabia
Saudi Arabia
Venezuela
Qatar
Saudi Arabia
UAE
USA
USA
UK
Japan
USA
Japan
USA
Japan
China
Japan
1.15E+24
4.63E+23
4.38E+23
3.94E+23
3.83E+23
3.73E+23
3.41E+23
3.33E+23
3.23E+23
3.09E+23
2012
1
2
3
4
5
Canada
Australia
Norway
Saudi Arabia
Saudi Arabia
USA
Japan
UK
USA
Japan
6.91E+23
4.37E+23
4.32E+23
4.27E+23
3.82E+23
2013
1
2
3
4
5
Canada
Australia
Mozambique
Hungary
Qatar
USA
Japan
South Africa
Croatia
Japan
7.90E+23
4.76E+23
4.28E+23
4.26E+23
4.25E+23
875
W. Zhong et al. / Applied Energy 165 (2016) 868–877
Table 6 (continued)
Rank
Exporter
Importer
Fossil emergy (seJ)
Rank
Exporter
Importer
Fossil emergy (seJ)
6
7
8
9
10
Saudi Arabia
Russia
Mexico
UAE
Netherlands
China
Netherlands
USA
Japan
Belgium
3.46E+23
3.44E+23
3.07E+23
3.01E+23
2.84E+23
6
7
8
9
10
Saudi Arabia
Norway
Saudi Arabia
Norway
Saudi Arabia
USA
UK
Japan
Germany
China
3.96E+23
3.77E+23
3.66E+23
3.65E+23
3.46E+23
4. Discussion and conclusion
Fossil
Coal
Crude oil
Natural gas
In this paper, we constructed the integrated trade network of
fossil fuel based on emergy value, as well as the single commodity
networks of coal, crude oil and natural gas. The trade quantity of
coal, crude oil and natural gas were transformed into emergy and
the sum of them was the emergy of fossil fuel. We studied trade
relationships, trade quantity, trade density and hierarchy structure
of the networks. These indexes reflected the individual and entire
features of the fossil fuel trade network. Our observation period
was from 2000 to 2013, we looked further into the evolution of
these features over time. Our conclusions and discussions are as
follows:
0.07
0.06
0.04
0.03
0.02
0.01
0
(1) The numbers of trade relationships of the single countries
follow power law distribution. A small number of countries
own many trade partners and most of the countries own a
few trade partners. The top 10 countries with the largest
number of import or export relationships are mainly in
North America, Europe and East Asia area. Countries with
high in-degree also tend to have high out-degree, for example the USA, China and Germany. The number of trade relationships can reflect a country’s activeness in international
trade. If a country is active, although it is a net importing
country, it will still have many export flows with small value
of emergy to other countries especially to its neighboring
countries. Also, these countries tend to have many big
energy companies, which not only target to domestic market, but also target to the world market.
(2) A small number of trade links shoulder most of the trade
quantities. Less than 8% of the trade relationships contain
up to 80% of the trade quantity of emergy in the fossil fuel
trade network. The centralization of trade quantity of fossil
fuel was becoming more intense, however, natural gas had
Year
Fig. 6. Trade density of the 4 types of networks.
appear to have various clustering coefficient. However, we can still
find some clues of hierarchy structure when we observe the low
degree and high degree separately.
Take the year 2013 as an example. The R2 of linear regression of
all the nodes was 0.0649 (please see Fig. 9(a)), which indicates that
there was no linear relation between degree and clustering coefficient. However, as we deleted the nodes with low degree, the R2 of
linear regression is increasing. When there were nodes with degree
above 17, the R2 of linear regression was 0.6174 (please see Fig. 9
(b)), which indicates that there was linear relation between degree
and clustering coefficient. We recorded the R2 when we deleted
nodes with degree from 1 to 50 in the year 2000, 2006 and 2013
(please see Fig. 10). The R2 reached 0.6 when there were nodes
with degree more than about 20. It was faster for R2 to reach 0.6
from 2000 to 2013, which means the hierarchy structure was
becoming more ordered.
Fossil
Crude oil
Coal
Fossil
Coal
Natural gas
Crude oil
Natural gas
Total number of edges
3000
200
150
100
50
2500
2000
1500
1000
500
Year
Year
(a)
(b)
Fig. 7. Total number of countries and trade links of the 4 types of networks.
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
0
2001
0
2000
Total number of nodes
250
2000
Density
0.05
876
W. Zhong et al. / Applied Energy 165 (2016) 868–877
Fig. 8. Scatterplots of degree and clustering coefficient of fossil fuel trade network.
k>0
k>17
0.8
Clustering coefficient
Clustering coefficient
1.2
1
0.8
y = -0.002x + 0.5058
R² = 0.0649
0.6
0.4
0.2
0.6
y = -0.0029x + 0.5629
R² = 0.6174
0.4
0.2
0
0
0
100
200
0
50
100
Degree (k)
Degree (k)
(a)
(b)
150
200
Fig. 9. The linear regression of degree and clustering coefficient in fossil fuel trade network in 2013.
2000
2006
2013
0.8
0.7
0.6
R2
0.5
0.4
0.3
0.2
0.1
0
1
6
11
16
21
26
31
36
41
46
51
Degree
Fig. 10. R2 of the linear regression of degree and clustering coefficient in fossil fuel
trade (the abscissa is the threshold of degree, countries with degrees equal to or
higher than the threshold is remain in the regression).
an opposite tendency. The centralization of trade quantity of
natural gas was less intense. The increasing of production,
especially the development of unconventional gas (such as
shale gas in the USA), reshaped the supply pattern of natural
gas and made it less centralized to a small number of trade
relationships.
(3) The trade density of fossil fuel is increasing, and coal is the
‘‘cheapest” energy measured by ‘‘energy cost” which is being
most widely traded. Due to the globalization of fossil fuel
trade, more countries were participating in the world fossil
fuel trade, and more relationships among countries were
built up. In the traditional study of single fuel, we can only
analyse the features of one part of the fossil fuel market,
our study can reveal the tendency of the integrated market
and it also easily to compare the features of different fuels.
In our results, an interesting phenomenon is that although
crude oil contributes the most to the total emergy of fossil
W. Zhong et al. / Applied Energy 165 (2016) 868–877
fuel trade, the number of countries and the number of relationships of crude oil is not the largest. Coal contributes the
least emergy to the total, however, it has the largest number
of countries and relationships. This phenomenon indicates
that when considering the ‘‘energy cost” of the geobiosphere
and the producing process, coal is the ‘‘cheapest” energy that
is being traded most widely. This conclusion is based on the
concept of emergy and cannot obtained by the traditional
study based on money or exergy. When we look further into
the calculation of emergy values of the three types of fuels,
we can see that the energy content of coal is not that small,
however, when transformed into emergy, its emergy value is
much less than crude oil and natural gas. This means that
coal consumed less energy in the geobiosphere process
and the producing process. This is the reason for the small
contribution of coal in the total emergy of fossil fuel.
Another point is that the energy cost in the trade quantity
should be considered when making international trade policies.
Emergy flows contain the energy cost in the producing process of
the exporting countries. At the same time, the money of a country
also contains emergy in it. Both of the energy costs in fossil fuel
and money can reflect the energy cost of this country. Thus when
two countries exchange fossil fuel and money in the international
trade, they should look further into the energy cost of them and
reconsider the effectiveness of the trade.
877
relationships. Mexico was one of the top 10 countries only
in 2001–2003, however, it was on the list of top 10 relationships in most of the years. This is because Indonesia equally
exported its fossil fuel to Southeast Asian countries such as
India, China, Japan and South Korea. Although the value of
the single emergy flow was not high, the total amount of
its export was large. On the contrary the fossil fuel export
of Mexico was concentrated on the link with the USA. The
emergy values of its trade links with other countries were
much lower.
Due to the limit of data, the observation period of this paper is
only from 2000 to 2013. In the future, we can expand the observation period to several decades and introduce more indexes of network analysis in order to find more features of the international
fossil fuel trade network.
Acknowledgements
This research is supported by grants from the National Natural
Science Foundation of China (Grant No. 71173199) and the
Humanities and Social Sciences Planning Funds project under the
Ministry of Education of the PRC (Grant No. 10YJA630001). The
authors would like to express their gratitude to Mark T. Brown
who helped a lot during their work.
References
(4) The evolution tendency of the trade density of natural gas is
denser, and according to the accumulative distribution of
trade quantity the trade of natural gas is becoming more
diversified. This implicates that more trade relationships of
natural gas will be built and the trade volume will not be
concentrated in a few trade links. Thus, for exporting countries it is an opportunity to extend their sales markets and
enhance their status. For importing countries, it is also an
opportunity to seek for more importing sources and increase
the importing volume of the existing trade links. More
pipelines are needed to be built, and the progress of the
technology of liquefaction and regasification will extend
the trade scale of LNG.
(5) Countries with more than 20 trade relationships tend to
have a hierarchy structure, which means countries with similar roles tend to have similar connectivity. This phenomenon was becoming more pronounced during the
observation period. Another interesting finding is that countries with more trade relationships tend to have lower connectivity among its neighboring countries. This is because
countries with high degree have wider trade ranges. Their
trade partners are located all over the world, thus the probability of building up trade relationships between neighboring countries is lower. As the hierarchy structure of the
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were increasing fast due to the booming of Chinese economy
and China’s rocketing demand for fossil fuel. Another example is that although Indonesia was one of the top 10 countries in exporting fossil fuel, it was not on the list of top 10
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