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The risk impacts of global natural and technological disasters

  • Guoqiang Shen
  • , Long Zhou*
  • , Xianwu Xue
  • , Yu Zhou
  • *此作品的通讯作者
  • Zhejiang University
  • City University of Macau
  • National Oceanic and Atmospheric Administration
  • Chinese University of Hong Kong

科研成果: 期刊稿件文章同行评审

摘要

This research develops an expected risk model and estimates risk impacts of single or multiple disasters in terms of human fatality, injury, affected, and economic damage for nearly 200 nations. Both natural hazards, including geophysical, meteorological, hydrological, and technological disasters, such as industrial, transport, and structural, are considered. Relevant measures of expected risk, such as standard deviation, coefficient of variance, range, and rank are also calculated to assess a country's overall risk. Social-economic-physical factors from the World Development Index developed by the United Nations (UN) are then regressed with occurrences and risks of natural and tech disasters to seek plausible associations. The results show that (1) the model performs reasonably well in fitting observed and modeled risks and risk impacts, relatively better for natural disaster and affected people and economic damage; (2) while natural disasters are far more risky than tech ones in total risk impacts; specific risks for subgroups of natural or tech disasters vary widely in magnitude and by country; (3) high natural and/or tech risks concentrate in a small number of countries, such as China, India, Bangladesh in Asia; U.S., Mexico, Canada in North America; Turkey, Russia, France, Germany in Europe, and Algeria, Egypt, and Ethiopia in Africa, which are relatively large in population, fast in development, or advanced in industrialization; yet (4) high risk deviations per unit risk impacts reveal that many small, developing, and tech backward countries need to prepare even more for both natural and tech disasters. Finally, (5) while many country-level development factors, together with disaster occurrence, are statistically significant, only some can provide weak predictability of disaster risk impacts under robust regression. The research findings provide useful risk references to countries for resilient national policies for disaster preparation, mitigation, and recovery.

源语言英语
文章编号101653
期刊Socio-Economic Planning Sciences
88
DOI
出版状态已出版 - 8月 2023
已对外发布

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