The Scenario Construction and Evolution Method of Casualties in Liquid Ammonia Leakage Based on Bayesian Network

Pengxia Zhao (), Tie Li, Biao Wang, Ming Li, Yu Wang, Xiahui Guo and Yue Yu
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Pengxia Zhao: School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
Tie Li: School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
Biao Wang: School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Ming Li: School of Emergency Management and Safety Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Yu Wang: Institute of Urban Safety and Environmental Science, Beijing Academy of Science and Technology (Beijing Municipal Institute of Labour Protection), Beijing 100077, China
Xiahui Guo: Safety Culture Research Center, Beijing Academy of Emergency Management Science and Technology, Beijing 100052, China
Yue Yu: Institute of Smart Ageing, Beijing Academy of Science and Technology, Beijing 100000, China

IJERPH, 2022, vol. 19, issue 24, 1-22

Abstract: In China, food-freezing plants that use liquid ammonia, which were established in the suburbs in the 1970s, are being surrounded by urban built-up areas as urbanization progresses. These plants lead to extremely serious casualties in the event of a liquid ammonia leakage. The purpose of this thesis was to explore the key factors of personnel protection failure through the scenario evolution analysis of liquid ammonia leakage. The chain of emergencies and their secondary events were used to portray the evolutionary process of a full scenario of casualties caused by liquid ammonia leakage from three dimensions: disaster, disaster-bearing bodies, and emergency management. A Bayesian network model of liquid ammonia leakage casualties based on the scenario chain was constructed, and key nodes in the network were derived by examining the sensitivity of risk factors. Then, this model was applied to a food-freezing plant in Beijing. The results showed that inadequate risk identification capability is a key node in accident prevention; the level of emergency preparedness is closely related to the degree of casualties; the emergency disposal by collaborative onsite and offsite is the key to avoiding mass casualties. A basis for emergency response to the integration of personnel protection is provided.

Keywords: liquid ammonia leaked; scenario construction; Bayesian network; emergency management; personnel protection (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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