Frontiers in Earth Science (Jan 2023)

Research on lethal levels of buildings based on historical seismic data

  • Xia Chaoxu,
  • Xia Chaoxu,
  • Nie Gaozhong,
  • Nie Gaozhong,
  • Li Huayue,
  • Li Huayue,
  • Li Huayue,
  • Fan Xiwei,
  • Fan Xiwei,
  • Zhou Junxue,
  • Zhou Junxue,
  • Zhou Junxue,
  • Yang Rui,
  • Yang Rui,
  • Zeng Xun,
  • Zeng Xun

DOI
https://doi.org/10.3389/feart.2022.767586
Journal volume & issue
Vol. 10

Abstract

Read online

Due to the influences of buildings, geographical and geomorphological environments, road conditions, etc., the probabilities and numbers of casualties in different areas after an earthquake are different. Accordingly, we propose the concept of the lethal level, which attains different grades representing the mortality rate of differing intensities. Different regions have unique lethal levels, and regional lethal levels are affected mainly by the proportion of each building type and the corresponding lethal level, as different types of buildings also have unique lethal levels. Based on data of 52 historical earthquake disasters, we constructed a lethal level calculation model and obtained the lethal level of each building type. The results reveal that the lethal level ranges of different building types are fixed and unequal; moreover, the ranges of different building types overlap each other. The lethal level range of adobe structures is 0.85–1, that of civil structures is 0.75–0.95, that of brick-wood structures is 0.6–0.9, that of brick-concrete structures is 0.33–0.6, that of wood structures is 0.2–0.35, and that of reinforced concrete structures is 0.1–0.25. Based on the lethal levels of these building types, the overall level of a region can be quantified and graded, and this classification does not depend on the geographical location or administrative boundaries. In pre-earthquake evaluation efforts, the lethal level of an area can be derived through field research. After an earthquake, the number of casualties can be quickly assessed based on the mortality rate corresponding to the intensity of the area. This approach can further provide scientific support for risk zoning and risk assessment research.

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