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

Author

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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)

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.

Suggested Citation

  • Lidong Pan & Yu Zheng & Juan Zheng & Bin Xu & Guangzhe Liu & Min Wang & Dingding Yang, 2022. "Characteristics of Chemical Accidents and Risk Assessment Method for Petrochemical Enterprises Based on Improved FBN," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12072-:d:923822
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    References listed on IDEAS

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    1. Tao Zeng & Guohua Chen & Yunfeng Yang & Genserik Reniers & Yixin Zhao & Xia Liu, 2020. "A Systematic Literature Review on Safety Research Related to Chemical Industrial Parks," Sustainability, MDPI, vol. 12(14), pages 1-27, July.
    2. Yunmeng Lu & Tiantian Wang & Tiezhong Liu, 2020. "Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents," IJERPH, MDPI, vol. 17(15), pages 1-20, July.
    3. Weiliang Qiao & Yu Liu & Xiaoxue Ma & Yang Liu, 2020. "Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network," Risk Analysis, John Wiley & Sons, vol. 40(5), pages 957-980, May.
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    Cited by:

    1. Yimeng Shi & Hongyuan Zhang & Zheng Chen & Yueyue Sun & Xuecheng Liu & Jin Gu, 2023. "A Study on the Deployment of Mesoscale Chemical Hazard Area Monitoring Points by Combining Weighting and Fireworks Algorithms," Sustainability, MDPI, vol. 15(7), pages 1-19, March.
    2. Jie Liu & Liting Wan & Wanqing Wang & Guanding Yang & Qian Ma & Haowen Zhou & Huyun Zhao & Feng Lu, 2023. "Integrated Fuzzy DEMATEL-ISM-NK for Metro Operation Safety Risk Factor Analysis and Multi-Factor Risk Coupling Study," Sustainability, MDPI, vol. 15(7), pages 1-26, March.
    3. Dingding Yang & Yu Zheng & Kai Peng & Lidong Pan & Juan Zheng & Baojing Xie & Bohong Wang, 2022. "Characteristics and Statistical Analysis of Large and above Hazardous Chemical Accidents in China from 2000 to 2020," IJERPH, MDPI, vol. 19(23), pages 1-27, November.

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