• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

埃亚菲亚德拉冰盖火山和 9/11 事件:大型灾害对全球流动性的影响。

Eyjafjallajökull and 9/11: the impact of large-scale disasters on worldwide mobility.

机构信息

Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, Illinois, United States of America.

出版信息

PLoS One. 2013 Aug 7;8(8):e69829. doi: 10.1371/journal.pone.0069829. eCollection 2013.

DOI:10.1371/journal.pone.0069829
PMID:23950904
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3737197/
Abstract

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 Eyjafjallajökull, 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.

摘要

大规模灾害会干扰全球化的社会技术基础设施,如移动和交通网络,从而引发高社会经济成本。尽管此类事件的起源通常在地理上受到限制,但它们的影响以人们难以理解、难以评估甚至更难以预测的方式在整个网络中产生共鸣。我们研究了埃亚菲亚德拉冰盖火山爆发、9·11 恐怖袭击以及一般的地理干扰如何影响全球流动性。为此,我们从单个机场的角度跟踪全球航空运输网络中有效距离的变化。我们发现,这些事件之间存在普遍特征:机场对区域干扰的敏感性遵循相似的、强烈异质分布,缺乏规模。另一方面,机场更容易受到针对网络中最重要枢纽的攻击,表现出明确的规模。敏感性的统计行为可以用单个标度指数来描述。使用捕捉个体机场特征和航线结构属性之间相互作用的标度论点,我们可以为所有类型的干扰恢复指数。我们发现,负责有效客流的相同机制也可能使系统处于脆弱状态。我们的方法可以应用于理解金融系统、生态系统和其他具有异质组件之间复杂相互作用结构的系统中大规模相关干扰的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/6743ce8fb36d/pone.0069829.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/cd28ae7a7f34/pone.0069829.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/4e0a70b6d9cf/pone.0069829.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/afd84bba4c7d/pone.0069829.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/431b04694167/pone.0069829.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/2a89e48d880d/pone.0069829.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/6743ce8fb36d/pone.0069829.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/cd28ae7a7f34/pone.0069829.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/4e0a70b6d9cf/pone.0069829.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/afd84bba4c7d/pone.0069829.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/431b04694167/pone.0069829.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/2a89e48d880d/pone.0069829.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda8/3737197/6743ce8fb36d/pone.0069829.g006.jpg

相似文献

1
Eyjafjallajökull and 9/11: the impact of large-scale disasters on worldwide mobility.埃亚菲亚德拉冰盖火山和 9/11 事件:大型灾害对全球流动性的影响。
PLoS One. 2013 Aug 7;8(8):e69829. doi: 10.1371/journal.pone.0069829. eCollection 2013.
2
Mental health effects following the eruption in Eyjafjallajökull volcano in Iceland: A population-based study.冰岛埃亚菲亚德拉冰盖火山喷发后的心理健康影响:一项基于人群的研究。
Scand J Public Health. 2019 Mar;47(2):251-259. doi: 10.1177/1403494817751327. Epub 2018 Jan 9.
3
Ash generation and distribution from the April-May 2010 eruption of Eyjafjallajökull, Iceland.来自 2010 年 4 月至 5 月冰岛艾雅法拉火山喷发的火山灰生成与分布。
Sci Rep. 2012;2:572. doi: 10.1038/srep00572. Epub 2012 Aug 14.
4
Seasonality of sex ratio at births in Iceland and effects of the 2010 Eyjafjallajökull volcanic eruption.冰岛出生性别比的季节性及2010年埃亚菲亚德拉冰盖火山喷发的影响。
Acta Paediatr. 2016 Nov;105(11):1369-1370. doi: 10.1111/apa.13507. Epub 2016 Jul 14.
5
Respiratory health effects of volcanic ash with special reference to Iceland. A review.火山灰对呼吸系统健康的影响,特别提及冰岛。综述。
Clin Respir J. 2011 Jan;5(1):2-9. doi: 10.1111/j.1752-699X.2010.00231.x. Epub 2010 Nov 29.
6
Fractionation and Mobility of Thallium in Volcanic Ashes after Eruption of Eyjafjallajökull (2010) in Iceland.冰岛埃亚菲亚德拉冰盖火山(2010年)喷发后火山灰中铊的分级与迁移性
Bull Environ Contam Toxicol. 2016 Jul;97(1):37-43. doi: 10.1007/s00128-016-1831-6. Epub 2016 May 21.
7
Managing uncertainty: Lessons from volcanic lava disruption of transportation infrastructure in Puna, Hawaii.应对不确定性:来自夏威夷普纳地区交通基础设施遭受火山熔岩破坏的经验教训。
J Emerg Manag. 2018 Jan/Feb;16(1):29-40. doi: 10.5055/jem.2018.0351.
8
Quantitative method for resilience assessment framework of airport network during COVID-19.新冠疫情期间机场网络弹性评估框架的定量方法。
PLoS One. 2021 Dec 3;16(12):e0260940. doi: 10.1371/journal.pone.0260940. eCollection 2021.
9
Vulnerability of the worldwide air transportation network to global catastrophes such as COVID-19.全球航空运输网络对 COVID-19 等全球灾难的脆弱性。
Transp Res E Logist Transp Rev. 2021 Oct;154:102469. doi: 10.1016/j.tre.2021.102469. Epub 2021 Aug 30.
10
Resilience of natural gas networks during conflicts, crises and disruptions.天然气网络在冲突、危机和中断期间的恢复力。
PLoS One. 2014 Mar 12;9(3):e90265. doi: 10.1371/journal.pone.0090265. eCollection 2014.

引用本文的文献

1
The impact of COVID-19 on the worldwide air transportation network.新型冠状病毒肺炎对全球航空运输网络的影响。
R Soc Open Sci. 2021 Nov 10;8(11):210682. doi: 10.1098/rsos.210682. eCollection 2021 Nov.
2
Airport user experience unpacked: Conceptualizing its potential in the face of COVID-19.剖析机场用户体验:面对新冠疫情,构想其潜力。
J Air Transp Manag. 2020 Oct;89:101919. doi: 10.1016/j.jairtraman.2020.101919. Epub 2020 Aug 27.
3
Congestion transition in air traffic networks.空中交通网络中的拥堵转变

本文引用的文献

1
Robust classification of salient links in complex networks.复杂网络中显著链路的鲁棒分类。
Nat Commun. 2012 May 29;3:864. doi: 10.1038/ncomms1847.
2
Individual versus systemic risk and the Regulator's Dilemma.个体风险与系统风险及监管者的困境。
Proc Natl Acad Sci U S A. 2011 Aug 2;108(31):12647-52. doi: 10.1073/pnas.1105882108. Epub 2011 Jul 18.
3
Collective response of human populations to large-scale emergencies.人类群体对大规模紧急情况的集体反应。
PLoS One. 2015 May 20;10(5):e0125546. doi: 10.1371/journal.pone.0125546. eCollection 2015.
4
Local difference measures between complex networks for dynamical system model evaluation.用于动态系统模型评估的复杂网络之间的局部差异度量
PLoS One. 2015 Apr 9;10(4):e0118088. doi: 10.1371/journal.pone.0118088. eCollection 2015.
5
Spatiotemporal detection of unusual human population behavior using mobile phone data.利用手机数据对异常人群行为进行时空检测。
PLoS One. 2015 Mar 25;10(3):e0120449. doi: 10.1371/journal.pone.0120449. eCollection 2015.
6
Estimation of global network statistics from incomplete data.从不完整数据估计全球网络统计量。
PLoS One. 2014 Oct 22;9(10):e108471. doi: 10.1371/journal.pone.0108471. eCollection 2014.
PLoS One. 2011 Mar 30;6(3):e17680. doi: 10.1371/journal.pone.0017680.
4
Mitigation of malicious attacks on networks.网络恶意攻击的缓解。
Proc Natl Acad Sci U S A. 2011 Mar 8;108(10):3838-41. doi: 10.1073/pnas.1009440108. Epub 2011 Feb 22.
5
Catastrophic cascade of failures in interdependent networks.相互依存网络中的灾难性故障级联。
Nature. 2010 Apr 15;464(7291):1025-8. doi: 10.1038/nature08932.
6
Predicting the behavior of techno-social systems.预测技术社会系统的行为。
Science. 2009 Jul 24;325(5939):425-8. doi: 10.1126/science.1171990.
7
Extracting the multiscale backbone of complex weighted networks.提取复杂加权网络的多尺度骨干
Proc Natl Acad Sci U S A. 2009 Apr 21;106(16):6483-8. doi: 10.1073/pnas.0808904106. Epub 2009 Apr 8.
8
Complex systems: ecology for bankers.复杂系统:银行家的生态学
Nature. 2008 Feb 21;451(7181):893-5. doi: 10.1038/451893a.
9
Controlling pandemic flu: the value of international air travel restrictions.控制大流行性流感:国际航空旅行限制的价值。
PLoS One. 2007 May 2;2(5):e401. doi: 10.1371/journal.pone.0000401.
10
Modeling the worldwide spread of pandemic influenza: baseline case and containment interventions.模拟大流行性流感的全球传播:基线病例与遏制干预措施。
PLoS Med. 2007 Jan;4(1):e13. doi: 10.1371/journal.pmed.0040013.