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author:

Xu, Y. (Xu, Y..) [1] | Peng, P. (Peng, P..) [2] | Xie, X. (Xie, X..) [3] | Lu, F. (Lu, F..) [4]

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Scopus

Abstract:

Liquefied natural gas (LNG) is a critical component of the global sustainable energy industry, with substantial implications for global energy development. Although the maritime transportation system has played an important role in promoting global LNG trade, it remains highly vulnerable to international political events, major disasters, and other emergencies. To better understand the robustness and security of the global LNG transport system, this study provides a new analysis paradigm for evaluating the robustness of the LNG transport network in the face of disruptive events. We examine a variety of network parameters for the global LNG transport network between 2013 and 2023 to capture changes in topological structure and evolution. Then, we introduce three centrality indices which can capture distinct characteristics of the maritime ports including connectivity, transfer, and cohesion, and combine these three centralities into a TOPSIS framework to achieve a multidimensional port centrality for identifying essential ports. Finally, we evaluate the robustness of the LNG transport network against several sequential intentional attacks using diverse strategies. We found that we can loosely separate the collapse process of the LNG transport network into three stages: initial collapse, ongoing fragmentation, and final collapse. In 2013, intentional attacks based on degrees and TOPSIS centralities were the most likely to cause the LNG transport network to collapse. In 2023, intentional attacks based on betweenness and TOPSIS centralities are the most likely to cause the LNG transport network to collapse, and the LNG transport network is more robust than it was in 2013. © 2025 Elsevier Ltd

Keyword:

Complex networks LNG transport network Robustness assessment Vessel trajectory data

Community:

  • [ 1 ] [Xu Y.]State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
  • [ 2 ] [Xu Y.]University of Chinese Academy of Sciences, Beijing, 100049, China
  • [ 3 ] [Peng P.]State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
  • [ 4 ] [Peng P.]University of Chinese Academy of Sciences, Beijing, 100049, China
  • [ 5 ] [Xie X.]State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
  • [ 6 ] [Xie X.]University of Chinese Academy of Sciences, Beijing, 100049, China
  • [ 7 ] [Lu F.]State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
  • [ 8 ] [Lu F.]University of Chinese Academy of Sciences, Beijing, 100049, China
  • [ 9 ] [Lu F.]The Academy of Digital China, Fuzhou University, Fuzhou, 350002, China
  • [ 10 ] [Lu F.]Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China

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Source :

Ocean and Coastal Management

ISSN: 0964-5691

Year: 2025

Volume: 263

4 . 8 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 0

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