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The domestic industrial structure optimization for carbon emission reduction usually causes carbon transfer to other countries, while the global industrial structure adjustment would possibly lead to the unbalance of regional economy development. Based on the previous studies, this paper built an intermediate input source optimization model to reduce the global carbon emissions by adjusting the international input sources of countries (regions). The results showed that the proposed model could effectively realize the goals of global carbon emission reduction and economic development. After optimization, the requirements for the inputs from some sectors would significantly decrease, such as the materials in China, while the requirements for the inputs from some sectors would significantly increase, such as energy in the EU countries. The results also showed that the important sectors in the domestic industrial structures were more sensitive to the global intermediate input source adjustment. Furthermore, the global input source changes would indirectly improve the industrial structures of some countries including China, India and Russia. Our work suggested that countries should further promote the technology advantages of some important sectors to avoid the probable industrial risks bought by the global actions toward carbon neutrality.

Market competition and trade activities between different economies’ steel industries induce severe steel product price transmission between different economies. Furthermore, steel products in different phases of the industrial chain present various price transmission features. In this research, we calculate the Granger causality relationship between different steel products in different markets and the midstream industry chain. We then construct the global steel product price transmission network and regional price transmission network. We analyze the network indicators and draw the following conclusions. First, emerging economies play a major role in international steel product price transmission activities. Second, billet and plates of middle thickness transmit the most price in the steel market. Third, China imposes price transmission impacts on the most regions with the widest range. Lastly, steel products at the end of the midstream steel industrial chain are “bridges” of price transmission activities. This research will guide market individuals in the steel industry to adjust their behaviors according to market signals.

Carbon dioxide (CO2) emissions have a significant impact on global climate change. Previous studies have mostly focused on the impact of economic performance of sectors on carbon emissions, however, there is a lack of information about the influence of the structural roles on the full industrial chain. This article first built global embodied carbon emission transfer networks from 2000 to 2015, combining multi-regional input-output analysis and complex network theory, to explore the structural characteristics and recognize the structural roles of sectors. Then, panel regression analysis was applied to quantify the contributions of the structural roles of sectors to their carbon emissions. The results first showed that there were significant scale-free network characteristics in the global embodied carbon emissions transfer networks. The majority of global carbon emission transfers was concentrated on a limited number of sectors over time. Moreover, the network analysis revealed that sectors played different roles with different levels of importance in the global embodied carbon emission transfer networks. The results also suggested that the carbon emissions of sectors related to economic activity were significantly determined by some structural roles in the global embodied carbon emission transfer networks. Degree-in, strength-out and closeness-out and betweenness had significant positive influences, while degree-out, strength-in and closeness-in had significant negative impacts. These results indicated that carbon emissions mainly were increased by the domestic markets rather than international trades. Thus, adjusting the domestic consumption structures can be helpful for global carbon emission reduction. It also indicated that carbon emissions were not only driven by direct production demand from downstream sectors, but also were significantly influenced by indirect production demand in the industrial chain. Therefore, reducing carbon emissions should be established in both the direct and the indirect relationships in the production process.

Cobalt is widely recognized as a strategic mineral especially for current energy and low carbon revolution. Nonetheless, the geographically concentrated supply makes reliable access to cobalt more of a strategic concern. Understanding the systemic impacts of epicenter economies, and how crises propagate if these economies were hit by negative shocks, are thus important for policy makers. To explore this issue, we construct a global cobalt trade network using the data of 2019, upon which a cascading failure model is established. Accordingly, we simulate the avalanche process, and an avalanche network is derived to analyze the structural features of crisis propagation dynamics. Results show that (1) When the ratio r ≥ 8, avalanche sizes of major epicenter economies increase rapidly from 22 to 36; (2) Democratic Republic of Congo, Mainland of China, Germany, and United Kingdom have systemic impacts in the global cobalt trade network; (3) Out-degree, in-strength, out-strength, and betweenness show influences on the dynamics of supply crisis propagation, while in-degree and eigencentrality do not show clear influences on the propagation dynamics; (4) Indirect cascades account for a significant fraction of the avalanche sizes. These findings contribute to more efficient supply management of the strategic raw material for policy makers.

Iron is a basic substance in the manufacturing industry of a country. The industry chain of iron and steel is an integrated and complicated system with substance exchange through import and export. Features and structure of this system can reveal the global pattern of the iron and steel industry chain. This study aims to quantitatively analyze the evolution of features and structure of international iron flow by combining the theory of Substance Flow Analysis and Complex Network. The network model was constructed based on the iron substance flow embodied in the trade among all the countries in the world. Trade density, concentration of trade activities, concentration of trade volumes, and hierarchy structure of the network were studied. Results show that the trade density of iron-contained commodities can act as the “barometer” of world economy; the concentration of trade activities shows a reverse relationship with the world economic prosperity; the trade volumes are highly concentrated in a small number of countries; and the hierarchy structure of the network of international iron flow is becoming more obvious. Some policy implications according to the results were provided.

In this paper, we provide a method of statistical physics to analyze the fluctuation of transmission by constructing Granger causality network among price indices (PIGCN) from a systematical perspective, using complex network theory combined with Granger causality method. In economic system, there are numerous price indices, of which the relationships are extreme complicated. Thus, time series data of 6 types of price indices of China, including 113 kinds of sub price indices, are selected as example of empirical study. Through the analysis of the structure of PIGCN, we identify important price indices with high transmission range, high intermediation capacity, high cohesion and the fluctuation transmission path of price indices, respectively. Furthermore, dynamic relationships among price indices are revealed. Based on these results, we provide several policy implications for monitoring the diffusion of risk of price fluctuation. Our method can also be used to study the price indices of other countries, which is generally applicable.

The uneven distribution of natural gas in the world makes the gas trade between countries close, and the importance of natural gas for national economies leads to a high dependence of gas-importing countries on external natural gas resources. This dependency creates a potential structural risk in the global gas trade that can spread out along trade linkages when parts of the gas trade collapse. In this paper, we developed a simulation model for the diffusion of gas trade ruptures based on a modified bootstrap percolation network model. We used this model to detect the potential gas trade risk and observed the roles of gas trade participants in the risk transmission process. In the results, we found that Norway and Qatar have the greatest impact on price fluctuations in the risk simulation. While Russia's influence ranks lower in the global gas market, although it has larger trade partners. Meanwhile, the external gas supply risk for gas-importing countries varies greatly and shows regional characteristics (European countries are in a higher trade risk environment, while China and Japan have the largest gas supply risk in Asia). We also identified the diffusion paths of gas supply breaks and found that Singapore and India are likely to serve as the largest intermediaries, causing a wide range of trade collapse.

As a critical raw material, iron ore plays an important role in the development of the national economy, which results in intense competition between iron ore importers. Using the international iron ore trade data of the UN Comtrade from 2000 to 2015, this paper calculates the competition intensity between iron ore importers importing iron ore from the same exporters. The paper then constructs iron ore import competition networks with the importers as nodes, the import competitive relations as edges, and the competition intensity as weights of edges. Applying complex network theory, the paper analyzes the overall characteristics of the iron ore importing competition pattern, the import competition region and the main importing countries. The results reveal that the global iron ore import competition is tight, unbalanced and expanding and that the global iron ore import competitive pattern is moving from a core-periphery structure to a reticular structure. Although Australia and Brazil are both the main competition regions, the demand for Australian iron ore is more intense. The import competitive relations for iron ore exist primarily between Europe and Asia as well as intra-European and intra-Asian markets. The total import competition intensities between China and Japan and between China and South Korea are much larger than other competitive relationships with increasing trends from 2000 to 2015. We propose three policy recommendations for the importers: (1) diversifying the import channels; (2) enhancing the cooperation between importers; (3) investing in overseas equity mines to improve competitiveness.

With modern industry's increasing demand for products from all sectors of the copper industry chain, the trade relationships between countries for copper material are becoming increasingly closer. Additionally, different trade characteristics exist in different sectors of the industrial chain. Based on the data for the global copper trade in 2019and from the perspective of the copper industry chain, this paper analyzes the trade characteristics of the global copper industry chain and of important countries by constructing the trade networks for different links. In addition, we establish a two-dimensional evaluation index system to evaluate the comprehensive trade risks of the major importing countries for each link of the industrial chain, including their supply risks and vulnerability to supply constraints. The following conclusions are drawn. Copper processing is the link with the highest density in the global industrial chain supply chain network and the best connectivity and differentiation among trading countries. In the risk assessment of global copper import trade, Germany is a low risk country in the whole industrial chain. The United States and China are countries with relatively low risks in the whole industrial chain, and the trade risks are relatively high only in the selection link. Malaysia and Poland are high risk countries of the whole copper material industry chain, while Japan, the republic of Korea and Spain are the “critical” countries of trade risk, and it is necessary to focus on the control of trade supply risk.

The international heat pump trade transports equipment and new energy technology to urban renewable energy systems around the world. However, this trade is unstable because of technology transfer, the ever-changing economic environment and policies. Thus, to quantitatively explore the stability of the international heat pump trade, three stability indices are designed to reflect changes in trade volume and relations. Then, the stability of international heat pump pattern is analyzed in three aspects, global, communities and countries. We found that (1) The global heat pump trade is relatively stable, which offers big opportunities for countries to develop new technology. Traditional energy trade and trade in new energies technologies like photovoltaic have influence on the stability of heat pump trade. (2) The European community is more stable than the East Asian-North community. The urgent mandate for energy savings and technical progress have made the East Asian-North American community the market with the greatest potential for the global heat pump trade. The US plays an important role in the East Asian-North American market. Thus, when countries like the US change trade policies, it might be a market signal for other countries that they should take measures against the potential shocks. (3) It is essential to maintain stable trade relationships with partners. Greenland, Canada and Mexico are the three most stable countries. Finally, the stability indices and network modeling could be introduced to study other international energy trade patterns.

Dramatic oil price movements could spill over to the stock market, which may be weakened or reinforced by the exchange rate, particularly for net oil importing and exporting countries. Unlike previous studies considering the relationship between the stock market and the oil price quoted in USD, we explore the impact of real oil price quoted in corresponding currency on the stock markets of China and Russia by involving the nominal exchange rates through various time horizons during the sample period from January 2000 to October 2015. Furthermore, the relationship between the effective exchange rate and the oil-stock nexus is examined in a dynamic manner. The main results are as follows: first, Russian stock market responds greater to the combined influence of the oil price and exchange rate than Chinese stock market. Specifically, the bidirectional Granger causality relations running between the real oil price and stock markets are in scale 1 and 6 for China, but exist in scales 1–6 for Russia. Compared with previous studies, we infer that the exchange rate weakens the response of Chinese stock market to the oil price but close Russian oil-stock nexus. Moreover, the oil price increase could depress Chinese stock market in scale 6, while such increase has positive effect on Russian stock market in scales 2–6. Further dynamic analysis demonstrates that the correlations between the effective exchange rates and the oil-stock nexuses for both China and Russia are high and fluctuated in scales 1–4, but decrease after 2014 when the effective exchange rates of China and Russia move in the opposite direction in the long term.

As one of the renewable energy, solar energy is experiencing increased but exploratory development worldwide. The positive or negative influences of regional characteristics, like economy, production capacity and allowance policies, make them have uneven solar energy development. In this paper, we aim at quickly exploring the features of provincial solar energy development, and their concerns about solar energy. We take China as a typical case, and combine text mining and two-actor networks. We find that the classification of levels based on certain nodes and the amount of degree avoids missing meaningful information that may be ignored by global level results. Moreover, eastern provinces are hot focus for the media, western countries are key to bridge the networks and special administrative region has local development features; third, most focus points are more about the application than the improvement of material. The exploration of news provides practical information to adjust researches and development strategies of solar energy. Moreover, the bi-level exploration, which can also be expanded to multi-level, is helpful for governments or researchers to grasp more targeted and precise knowledge.

The oil–stock interaction characterized by complexity and nonlinearity makes relevant research difficult; this is caused by the intricate components of the entire market from a variety of time horizons. However, the heterogeneous influence of the multiscale market components on the entire oil–stock interaction has still been covered. Our objective is to further explore that which time scale is more essential to the integrated market interaction and the dynamic evolution of decisive time scale over time. The Brent spot oil price and the Morgan Stanley Capital International world stock index on a daily frequency were selected as the sample data, and the wavelet transform, the gray correlation, and network analyses were applied succinctly to conduct holistic and dynamical analyses. The primary findings are as follows: The wavelet-decomposed results indicate that impacts of oil price shocks on the oil–stock nexus differ in the long- and short-terms. From the holistic aspect, the growing wavelet variance with time scales demonstrates that long-term changes could lead to structure changes in trend of original market interactions. The wavelet correlation proves that short-term components are dominant in the original interaction and capture the dynamic information effectively. There are no significant lead–lag relations between the original oil–stock interaction and its components. From the dynamic perspective, it is confirmed that components from both the long and short terms are determined. The low and high transmission ability could be helpful to discover the structure changes caused by long-term components and modes controlling more information associated with the short-term components, respectively. The clustering effect limits major modes into a small amount.

The diffusion of breaking news largely relies on propagation behaviors in the media. The tremendous and intricate propagation relationships in the media form a complex network. An improved understanding of breaking news diffusion characteristics can be obtained through the complex network research. Drawing on the news data of Bohai Gulf oil spill event from June 2011 to May 2014, we constructed a weighted and directed complex network in which media are set as nodes, the propagation relationships as edges and the propagation times as the weight of the edges. The primary results show (1) the propagation network presents small world feature, which means relations among media are close and breaking news originating from any node can spread rapidly; (2) traditional media and official websites are the typical sources for news propagation, while business portals are news collectors and spreaders; (3) the propagation network is assortative and the group of core media facilities the spread of breaking news faster; (4) for online media, news originality factor become less important to propagation behaviors. This study offers a new insight to explore information dissemination from the perspective of statistical physics and is beneficial for utilizing the public opinion in a positive way.

Liquefied natural gas (LNG) has been categorized as a global commodity because of the continuous globalization of the LNG trade, and there is very close competition between LNG exporters worldwide. However, the overall competition structure and degree of the global LNG trade system were not well portrayed or quantified in the existing literature. This paper examined the trade competition pattern of the global LNG trade by building LNG trade competition networks (LTCN) from 2005 to 2014. Overall, the competitive relationship growth and competitive globalization features of the LNG trade were analyzed, and the main LNG exporter group and its evolution were studied. Moreover, the market competitiveness of LNG exporters was measured, and accordingly, these exporters were divided into three categories to depict their different development prospects, which would form a more complicated competition pattern of LNG trade in the future.

Different quality, reserves and production force countries to import fossil fuels to advance their economic development. It is exergy of fossil fuels that is essentially important to economy. Thus, it forms an international exergy flow network embodied in the global fossil energy trade. Based on complex network theory, we built a global fossil energy exergy flow network with countries as nodes, the international exergy flows as edges and the exergy of each flow as the weight of the edges. We analyzed the distribution of countries, the overall structure, major countries and major exergy flow paths of the network from 1996 to 2012. The results show that even if the fossil energy trade becomes more frequent and larger, there are always a few trade relationships and countries that play critical roles in the fossil energy trade. The trade relationship intensity at the global level is relatively lower than the corresponding intensity at the regional level. There are four main fossil energy trade groups, and these groups have the Russian Federation, the United States, Japan and Saudi Arabia as their core countries. If an energy war, an energy crisis or other problems occur in the countries with more partners, their impacts are likely to spread to other countries and even affect the global fossil energy trade.

The statistic of each stock

The statistic of each stock

Microscopic factors are the basis of macroscopic phenomena. We proposed a network analysis paradigm to study the macroscopic financial system from a microstructure perspective. We built the cointegration network model and the Granger causality network model based on econometrics and complex network theory and chose stock price time series of the real estate industry and its upstream and downstream industries as empirical sample data. Then, we analysed the cointegration network for understanding the steady long-term equilibrium relationships and analysed the Granger causality network for identifying the diffusion paths of the potential risks in the system. The results showed that the influence from a few key stocks can spread conveniently in the system. The cointegration network and Granger causality network are helpful to detect the diffusion path between the industries. We can also identify and intervene in the transmission medium to curb risk diffusion.

This study introduces an approach to study the multiscale transmission characteristics of the correlation modes between bivariate time series. The correlation between the bivariate time series fluctuates over time. The transmission among the correlation modes exhibits a multiscale phenomenon, which provides richer information. To investigate the multiscale transmission of the correlation modes, this paper describes a hybrid model integrating wavelet analysis and complex network theory to decompose and reconstruct the original bivariate time series into sequences in a joint time–frequency domain and defined the correlation modes at each time–frequency domain. We chose the crude oil spot and futures prices as the sample data. The empirical results indicate that the main duration of volatility (32–64 days) for the strongly positive correlation between the crude oil spot price and the futures price provides more useful information for investors. Moreover, the weighted degree, weighted indegree and weighted outdegree of the correlation modes follow power-law distributions. The correlation fluctuation strengthens the extent of persistence over the long term, whereas persistence weakens over the short and medium term. The primary correlation modes dominating the transmission process and the major intermediary modes in the transmission process are clustered both in the short and long term.

Electrolysis experiments can be performed at room temperature and under various voltages using natural fibrous (NF) gypsum with a pointed anode and a flat cathode. The NF gypsum is colored electrolytically. SO4−, SO3−, SO2−, O3− and O− defect centers are produced in colored NF gypsum. The characteristic absorption bands of the defect centers are observed in the absorption spectra of the colored NF gypsum. The defect centers come mainly from electric-field-induced decomposition and/or direct electron loss of SO42− radicals. Current is measured during electrolytic coloration. Electron exchanges from electron and charged radicals to electrodes induce complete current.

Phytostabilization has great practical significance and flexibility in the ecological restoration of mining tailings and remediation of heavy metals polluted soils. However, potential use of metallophytes in phytostabilization is limited by a lack of knowledge of many basic plant processes. A mining ecotype (ME) Athyrium wardii, Pb/Cd phytostabilizer, and a non-mining ecotype (NME) A. wardii were grown in a pot experiment to investigate the chemical characteristics of the rhizosphere when exposed to the Cd polluted soils. Rhizobags were used to collect rhizosphere and bulk soils, separately. The results indicated that the ME A. wardii was more efficient in Cd accumulation in the root than NME after growing in Cd polluted soils for 50 days in a green house. Soil solution pH and dissolved organic carbon (DOC) concentration in the rhizosphere of ME A. wardii were higher than in the bulk soil and initial values (before planting), whereas the increment in the ME A. wardii were greater than NME. Owing to the increasing of rhizosphere soil pH, exchangeable Cd significantly decreased, whereas the other Cd species were increased with increasing soil DOC values. It is assumed that the ME A. wardii was effective in stabilizing Cd from the mobile fraction to non-mobile fractions. Results from this study suggest that rhizosphere alkalinization and the exudation of high amounts of dissolved organic matter (DOM) to reduce heavy metal mobility might be the two important mechanisms involved in the metal tolerance/accumulation of ME A. wardii.

Athyrium wardii (Hook.) is a promising herbaceous plant species for phytostabilization of cadmium (Cd)-contaminated sites with large biomass and fast growth rate. However, little information is available on its tolerance mechanisms toward Cd. To further understand the mechanisms involved in Cd migration, accumulation and detoxification, the present study investigated subcellular distribution and chemical forms of Cd in the mining ecotypes and corresponding non-mining ecotypes of A. wardii via greenhouse pot experiment. Subcellular fractionation of Cd-containing tissues demonstrated that the majority of the element was mainly located in soluble fraction in cell walls. This indicated that both the vacuoles and cell walls might be evolved the Cd tolerance mechanisms to protect metabolically active cellular compartments from toxic Cd concentrations. Meanwhile, Cd taken up by the plant existed in different chemical forms. Results showed that the majority of Cd in plant was in undissolved Cd–phosphate complexes (extracted by 2 % CH3COOH), followed by water-soluble Cd–organic acid complexes, Cd(H2PO4)2, pectates and protein form (extracted by deionized water and 1 M NaCl), whereas only small amount of Cd in roots was in inorganic form (extracted by 80 % ethanol), which suggests low capacity to be transported to aboveground tissues. It could be suggested that Cd integrated with undissolved Cd–phosphate complexes in cell wall or compartmentalization in vacuole might be responsible for the adaptation of the mining ecotypes of A. wardii to Cd stress.

Ammonium alum crystals are colored electrolytically using a pointed cathode and a flat anode at low temperatures and under various voltages. SO3−, SO2− and O3− hole-trapped centers are produced in colored ammonium alum crystals. Characteristic absorption bands of SO3−, SO2− and O3− hole-trapped centers are observed in absorption spectra of colored ammonium alum crystals. Production and conversion of hole-trapped centers are explained. Current–time curves for electrolytic coloration of ammonium alum crystal and their relationship with electrolytic coloration process are given.

Energy stock investor sentiment reflects the investment desires and expectations of investors and plays a significant role in the investment decision-making process and in asset value. There are many ways to measure investor sentiment; for example, the development of the Internet makes it possible to use the online comments of investors to portray their sentiments. Taking a complex network perspective, this paper selected the PetroChina Company Limited as the research object, obtained 96839 investor online comments and analyzed their emotional tendencies and sentiment transmission process. In addition, on this basis, we examined the relationship between investor sentiment and stock price volatility to analyze the transmission characteristics of investor sentiment. The results show that, overall, PetroChina investor sentiment experienced stable fluctuations over the past five years, and stock returns fluctuated within the range of investors' acceptable volatility. In addition, a weak positive correlation is found between investor sentiment and stock returns. The investor sentiment transmission network has scale-free characteristics and cluster effects. This paper is helpful for understanding the behavior of investors in the stock market, and it provides a new perspective on the relevance of unstructured text and structured data.

Fluctuations of the nonlinear time series are driven by the traverses of multiscale conformations from one state to another. Aiming to characterize the evolution of multiscale conformations with changes in time and frequency domains, we present an algorithm that combines the wavelet transform and the complex network. Based on defining the multiscale conformation using a set of fluctuation states from different frequency components at each time point rather than the single observable value, we construct the conformational evolution complex network. To illustrate, using data of Shanghai’s composition index with daily frequency from 1991 to 2014 as an example, we find that a few major conformations are the main contributors of evolution progress, the whole conformational evolution network has a clustering effect, and there is a turning point when the size of the chain of multiscale conformations is 14. This work presents a refined perspective into underlying fluctuation features of financial markets.

Sucrose crystals are colored electrolytically at low temperatures and various voltages by using a pointed cathode and a flat anode. Caramels, carbonyl compounds, glycosylamines and free radicals are produced in colored sucrose crystals. No obvious characteristic absorption band in UV and visible wavelength regions is observed in absorption spectrum of uncolored sucrose crystal. Intense characteristic absorption bands of glycosylamines, carbonyl compounds and caramels are observed in absorption spectra of colored sucrose crystals. Production of caramels, carbonyl compounds, glycosylamines and free radicals are explained. Current–time curve for electrolytic coloration of sucrose crystal and its relationship with electrolytic coloration process are given.

Ammonium alum crystals are colored electrolytically below 0°C and under various voltages using a pointed anode and a flat cathode. SO2(-), O3(-), O2(-), O(-) hole-trapped centers and O(0), O(2-), H(+) radicals are produced in colored ammonium alum crystals. The absorption bands of the SO2(-) and O3(-) hole-trapped centers are observed in the absorption spectra of the colored ammonium alum crystals. The hole-trapped centers and radicals come mainly from the electric-field-induced decomposition of the SO4(2-) radicals and crystalline water molecules. Current is measured during electrolytic coloration. Electron exchanges from electrons and small charged radicals to electrodes induce complete current.

The Cadmium (Cd) accumulation capacity and subcellular distribution in the mining ecotype (ME) and non-mining ecotype (NME) of Kyllinga brevifolia Rottb were investigated in pot experiments. The results showed that average Cd contents in shoots of the two ecotypes of K. brevifolia were higher than those in roots, whereas Cd concentrations in roots were greater than those in shoots. Also, shoot Cd contents in NME of K. brevifolia were 1.65-45.45 times greater than those in ME when the plants were grown at 5, 25, 50, and 100 mg Cd kg(-1) soil. Moreover, Cd contents in the roots in NME were 1.75-45.45 times higher than those in ME. Subcellular distribution of Cd demonstrated that the majority of Cd in the two ecotypes of K. brevifolia was distributed in the cell walls and soluble fraction, and a small percentage of Cd existed in organelle fraction. In addition, proportions of Cd distributed in shoots and roots cell walls of NME were greater than those in ME. It could be assumed that compared with ME, NME of K. brevifolia has better Cd accumulation capacity, and the subcellular distribution of Cd might be one of the mechanisms to explain such phenomena.

This paper employs an un-weighted and weighted exergy network to study the properties of ferrous metal ores in countries worldwide and their evolution from 2002 to 2012. We find that there are few countries controlling most of the ferrous metal ore exports in terms of exergy and that the entire exergy flow network is becoming more heterogeneous though the addition of new nodes. The increasing of the average clustering coefficient indicates that the formation of an international exergy flow system and regional integration is improving. When we contrast the average out strength of exergy and the average out strength of currency, we find both similarities and differences. Prices are affected largely by human factors; thus, the growth rate of the average out strength of currency has fluctuated acutely in the eleven years from 2002 to 2012. Exergy is defined as the maximum work that can be extracted from a system and can reflect the true cost in the world, and this parameter fluctuates much less. Performing an analysis based on the two aspects of exergy and currency, we find that the network is becoming uneven.

The expansion of the international PV trade encourages governments to focus on their trade roles in this market, which has increasing impact on their future development of sustainable energy. Thus, an exploration of top traders and their influence on global PV trade pattern is essential as governments seek to develop strategies to improve their global PV market’s discourse power. This study introduces the complex network theory to examine top traders whose default would lead to the collapse of trade pattern and their impactful ways. Moreover, the potential structural reason for top traders’ influence on trade is explored via link prediction. We find that a group of European countries account for 80% of global importation and are the most influential traders and bridges; a group of Asian countries are among the top exporters with half of the global share; and European countries’ high influence is due to their large number of trade partners instead of their trade volume. Above all, a high number of trade partners is more important than trade volume for countries seeking to be top traders. Finally, we discuss these results given the recent promising development of international PV trade.