Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis

Gao, Cuixia; Sun, Mei; Shen, Bo

doi:10.1016/j.apenergy.2015.07.054

Cited by 118 publications

(38 citation statements)

References 25 publications

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“…Cluster analysis is employed to identify China's key trade interrelations within the global land footprint network. The cluster supports the idea that nodes within the same cluster have more dense links than the nodes outside this cluster (Blondel et al, 2008;Gao et al, 2015). According to our previous studies, a two phased cluster analysis based on undirected networks is applied for this study (Tian et al, 2018b).…”

Section: Cluster Analysissupporting

confidence: 69%

Trends and driving forces of China’s virtual land consumption and trade

et al. 2019

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Land resources are important for China's rapid economic development, especially for food and construction. China's land resources are under tremendous pressures, and therefore land use is increasingly displaced to other parts of the world. This study analyses the evolution and driving forces of China's land consumption from 1995 to 2015. The main results show that China's land footprint increased from 8.8% of the global land resources under human use in 1995 to 15.7% in 2015. China's domestic land resources are mainly used for serving domestic consumption. Moreover, China needs to import virtual land from foreign countries to satisfy 30.8% of its land demand. Among the three land use types of cropland, grassland and forests, grassland had the largest fraction in China's land footprint from 1995 to 2000, while forest has become the largest one from then on. Trends in China's virtual land trade reveal a sharp increase in net imports from 9.4E+04 km 2 in 1995 to 3.4E+06 km 2 in 2015. Observing China's virtual land network by a cluster analysis, this study concludes that China keeps tight relationships with Australia, Japan, Brazil and Korea for its cropland consumption, and Canada, USA, Mexico, Australia, Korea and Japan are relevant for its grassland consumption. In addition, a decomposition analysis shows that affluence is the major driving factor for China's land consumption, while changes in land use intensity could mitigate some of the related effects. Lastly, governance implications and policy recommendations are proposed so that China can move toward sustainable land management.

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Section: Cluster Analysissupporting

confidence: 69%

Trends and driving forces of China’s virtual land consumption and trade

et al. 2019

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“…However, the AGHG network is vulnerable to coordinated adjustments on key nodes; that is, adjustments in trade patterns and emission intensities of hub economies will reshape the network structure and generate profound impacts on global AGHG emissions. Similarly detected in the trade network of natural gas, oil, rare earths, and embodied energy (Chen et al, 2018b;Gao et al, 2015;Geng et al, 2014;Hou et al, 2018), this scale-free topology occurs as the results of preferential treatments and globalization trends. Comparative advantages such as natural resources, geographical location, and climate suitability promote positive feedbacks on the production of agricultural products, leading to preferential attachment that typically appears in the high-degree nodes (Serrano & Boguñá, 2003).…”

Section: Discussionmentioning

confidence: 82%

Linking Agricultural GHG Emissions to Global Trade Network

Zhao

Guan

et al. 2020

Earth's Future

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As part of the climate policy to meet the 2 °C target, actions in all economic sectors, including agriculture, are required to mitigate global greenhouse gas emissions. While there has been an ever‐increasing focus on agricultural greenhouse gas (AGHG) emissions, limited attention has been paid to their economic drivers in the globalized world economy and related mitigation potentials. This paper makes a first attempt to trace AGHG emissions via global trade networks using a multiregional input‐output model and a complex network model. Over one third of global AGHG emissions in 2012 can be linked with products traded internationally, of which intermediate trade and final trade contribute 64.2% and 35.8%, respectively. Japan, the United States, Germany, the United Kingdom, and Hong Kong are the world's five largest net importers of embodied emissions, while Ethiopia, Australia, Pakistan, India, and Argentina are the five largest net exporters. Some hunger‐afflicted developing countries in Asia and Africa are important embodied emission exporters, due to their large‐scale exports of agricultural products. Trade‐related virtual AGHG emission transfers shape a highly heterogenous network, due to the coexistence of numerous peripheral economies and a few highly connected hub economies. The network clustering structure is revealed by the regional integration of several trading communities, while hub economies are collectors and distributors in the global trade network, with important implications for emission mitigation. Achieving AGHG emission reduction calls for a combination of supply‐ and demand‐side policies covering the global trade network.

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“…To date, a few studies on natural resource trade have focused on a limited number of countries and products [23][24][25][26][27][28][29][30], but a systematic exploration of global scope is lacking. For example, the research into trade networks has been confined to local areas and organizations, such as the Belt and Road trade network [29][30][31][32][33][34] and North American Free Trade Area (NAFTA) [35][36][37].…”

Section: Introductionmentioning

confidence: 99%

An Exploratory Analysis of Networked and Spatial Characteristics of International Natural Resource Trades (2000–2016)

et al. 2020

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Natural resources, as the material basis of human life and production, play a crucial role in national economic and social development. It is essential to reveal the structural characteristics of global natural resource supply and demand, which has become one of the most critical factors affecting every country’s policy strategy and economic development. However, mining the characteristics of international natural resource trades is a huge challenge because of the availability and quality of trade data. In this study, the international natural resource trade system is modeled as networks based on the available bilateral trade data from 2000 to 2016. Complex network methods and spatial analysis are utilized to explore the networked and spatial characteristics of different international natural resource trade networks (INRTNs). First, we quantitatively present the overall evolution trend of INRTNs by calculating several indicators of network features at the macrolevel. Then, as the intermediate-level characteristics of INRTNs, the core–periphery structures are explored by applying hierarchical clustering and a visual matrix heatmap. Finally, at the microlevel, the imbalance in direction is detected through the combination of node importance in a complex network with bivariate choropleth maps of spatial analysis. The empirical evidence from INRTNs of different product types in this paper will help governments and business administrations to perceive the complex natural resource trade environment, which can instruct policymakers to formulate effective import–export policies and ensure national resource security and sustainable development.

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Features and evolution of international fossil energy trade relationships: A weighted multilayer network analysis

Cited by 118 publications

References 25 publications

Trends and driving forces of China’s virtual land consumption and trade

Trends and driving forces of China’s virtual land consumption and trade

Linking Agricultural GHG Emissions to Global Trade Network

An Exploratory Analysis of Networked and Spatial Characteristics of International Natural Resource Trades (2000–2016)

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