Characteristics of Chemical Accidents and Risk Assessment Method for Petrochemical Enterprises Based on Improved FBN

Lidong Pan, Yu Zheng, Juan Zheng, Bin Xu, Guangzhe Liu, Min Wang and Dingding Yang ()
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Lidong Pan: National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Provincial Key Laboratory of Petrochemical Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, China
Yu Zheng: School of Naval Architecture and Maritime, Zhejiang Ocean University, Zhoushan 316022, China
Juan Zheng: National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Provincial Key Laboratory of Petrochemical Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, China
Bin Xu: Sinochem Zhoushan Dangerous Chemical Emergency Rescue Base Co., Ltd., Zhoushan 316022, China
Guangzhe Liu: Sinochem Zhoushan Dangerous Chemical Emergency Rescue Base Co., Ltd., Zhoushan 316022, China
Min Wang: National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Provincial Key Laboratory of Petrochemical Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, China
Dingding Yang: National & Local Joint Engineering Research Center of Harbor Oil & Gas Storage and Transportation Technology, Zhejiang Provincial Key Laboratory of Petrochemical Pollution Control, School of Petrochemical Engineering & Environment, Zhejiang Ocean University, Zhoushan 316022, China

Sustainability, 2022, vol. 14, issue 19, 1-18

Abstract: Refining and chemical integration is the major trend in the development of the world petrochemical industry, showing intensive and large-scale development. The accident risks caused by this integration are complex and diverse, and pose new challenges to petrochemical industry safety. In order to clarify the characteristics of the accident and the risk root contained in the production process of the enterprise, avoid the risk reasonably and improve the overall safety level of the petrochemical industry, in this paper, 159 accident cases of dangerous chemicals in China from 2017–2021 were statistically analyzed. A Bayesian network (BN)-based risk analysis model was proposed to clarify the characteristics and root causes of accident risks in large refining enterprises. The prior probability parameter in the Bayesian network was replaced by the comprehensive weight, which combined subjective and objective weights. A hybrid method of fuzzy set theory and a noisy-OR gate model was employed to eliminate the problem of the conditional probability parameters being difficult to obtain and the evaluation results not being accurate in traditional BN networks. Finally, the feasibility of the methods was verified by a case study of a petrochemical enterprise in Zhoushan. The results indicated that leakage, fire and explosion were the main types of accidents in petrochemical enterprises. The human factor was the main influencing factors of the top six most critical risk root causes in the enterprise. The coupling risk has a relatively large impact on enterprise security. The research results are in line with reality and can provide a reference for the safety risk management and control of petrochemical enterprises.

Keywords: characteristics of hazardous chemical accidents; fuzzy theory set; Bayesian network; risk identification (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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