Eyjafjallajokull and 9/11: The Impact of Large-Scale Disasters on Worldwide Mobility

被引:18
作者
Woolley-Meza, Olivia [1 ,2 ]
Grady, Daniel [1 ,2 ]
Thiemann, Christian [1 ,3 ]
Bagrow, James P. [1 ,2 ]
Brockmann, Dirk [1 ,2 ,4 ]
机构
[1] Northwestern Univ, Evanston, IL 60208 USA
[2] Northwestern Univ, Northwestern Inst Complex Syst, Evanston, IL USA
[3] Max Planck Inst Dynam & Self Org, Gottingen, Germany
[4] Robert Koch Inst, Berlin, Germany
来源
PLOS ONE | 2013年 / 8卷 / 08期
关键词
TRANSPORTATION NETWORK; COMPLEX NETWORKS; CENTRALITY; INTERNET;
D O I
10.1371/journal.pone.0069829
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Large-scale disasters that interfere with globalized socio-technical infrastructure, such as mobility and transportation networks, trigger high socio-economic costs. Although the origin of such events is often geographically confined, their impact reverberates through entire networks in ways that are poorly understood, difficult to assess, and even more difficult to predict. We investigate how the eruption of volcano Eyjafjallajokull, the September 11th terrorist attacks, and geographical disruptions in general interfere with worldwide mobility. To do this we track changes in effective distance in the worldwide air transportation network from the perspective of individual airports. We find that universal features exist across these events: airport susceptibilities to regional disruptions follow similar, strongly heterogeneous distributions that lack a scale. On the other hand, airports are more uniformly susceptible to attacks that target the most important hubs in the network, exhibiting a well-defined scale. The statistical behavior of susceptibility can be characterized by a single scaling exponent. Using scaling arguments that capture the interplay between individual airport characteristics and the structural properties of routes we can recover the exponent for all types of disruption. We find that the same mechanisms responsible for efficient passenger flow may also keep the system in a vulnerable state. Our approach can be applied to understand the impact of large, correlated disruptions in financial systems, ecosystems and other systems with a complex interaction structure between heterogeneous components.
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页数:7
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