Assessing the Health, Safety and Environmental Risk of Ammonia and Urea Units Using the Integration of Shannon Entropy and WASPAS Based on Fuzzy Logic

Subject Areas : Environmental Impact Assessment

Farkhondeh Ebadzadeh ¹ , Seyed Masoud Monavari ² , seyed ali Jozi ³ , Maryam Robati ⁴ , razieh rahimi ⁵

1 - PH.D Candidate, Department of Environmental Science, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 - - Associate Prof., Department of Environmental Science, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran. *(Corresponding Author)
3 - Professor of Department of Environment, Faculty of Marine Science and Technology, North Tehran Branch, Islamic Azad University, Tehran, Iran.
4 - Assistant prof., Department of Environmental Science, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran.
5 - Assistant prof., Department of Environment, Food Security Research Institute, Islamic Azad University, Arak, Iran.

Received: 2022-05-11 Accepted : 2022-09-16 Published : 2022-12-22

Keywords: Fuzzy WASPAS Technique, Fuzzy Shannon Entropy, Petrochemical, Risk Assessment,

Abstract :

Background and Objective: Due to the scope and volume of activities, the petrochemical industry has a high potential risk to humans and the environment. This study aimed to evaluate and rank the health, safety and environmental risks caused by the ammonia and urea production process. Material and Methodology: The Preliminary Hazard Analysis (PHA) method was used for qualitative risk analysis and screening of the health, safety and environmental risks identified in the follow-up phase. The severity and probability of occurrence of risk factors were calculated using PHA tables, and the level of risks was determined. To rank the final risks, the criteria “severity,” “probability of occurrence,” “probability of detection,” and the “extent of contamination” for environmental aspects and the criteria “severity,” “probability of occurrence,” “probability of detection,” and the “exposure” were first weighed by the fuzzy Shannon entropy method. Then, each risk was prioritized based on the mentioned criteria and using fuzzy Weighted Aggregated Sum Product Assessment (WASPAS). Findings: According to the results, among 24 environmental aspects, CO2 emissions from the disposal tower with a value of 0.702 and among the 36 safety and health risks, falling from a height with a value of 0.713 have the highest score. Discussion and Conclusion: Finally, suggestions were made to correct and mitigate the high-level risks. Also, the research results showed that using the multi-criteria decision-making technique in the fuzzy environment increases the study’s accuracy and facilitates access to the knowledge of experts.

References:

1. Tenney A, Kværner J, Gjerstad K I. Uncertainty in environmental impact assessment predictions: the need for better communication and more transparency. Impact Assessment and Project Appraisal. 2006; 24(1), p. 45-56. https://doi.org/10.3152/147154606781765345


2. Huang R H, Yang C L, Kao CS. Assessment model for equipment risk management: Petrochemical industry cases. Safety Science. 2012; 50(4), 1056-1066. https://doi.org/10.1016/j.ssci.2010.02.024


3. Noori H, Cheraghi M, Eslami Baladeh A. A hybrid fuzzy MADM model for environmental risk assessment: a case of an oil and gas exploitation area. J Health Saf Work. 2019; 9 (3), p. 200-21. http://jhsw.tums.ac.ir/article-1-6166-fa.html. (In Persian)


4. Mete Assessing occupational risks in pipeline construction using FMEA-based AHP-MOORA integrated approach under Pythagorean fuzzy environment. HUMAN AND ECOLOGICAL RISK ASSESSMENT. 2019; 25(7), p.1645-1660. https://doi.org/10.1080/10807039.2018.1546115


5. Song W, Ming X, Wu Z, Zhu B. Failure modes and effects analysis using integrated weight-based fuzzy TOPSIS. International Journal of Computer Integrated Manufacturing. 2013; 26(12), p. 1172-1186. http://dx.doi.org/10.1080/0951192X.2013.785027


6. Johari Z, Cheraghi M, Sobhan Ardakani S. Environmental Risk Assessment of Ilam Petrochemical Company Using Analytical Network Analysis and the Technique for Order of Preference by Similarity to Ideal Solution Methods in 2016. J Ilam Uni Med Sci. 2019; 26(5), p. 79-88. http://sjimu.medilam.ac.ir/article-1-4791-fa.html. (In Persian)


7. Khodadadi-Karimvand M, Shirouyehzad H. Well Drilling Fuzzy Risk Assessment using Fuzzy FMEA and Fuzzy TOPSIS. Journal of Fuzzy Extension and Applications. 2021; 2(2), p 144–155. http://dx.doi.org/10.22105/jfea.2021.275955.1086


8. Gharibi V, Ghaedi Jahromi M, Mohammadnia M R, Hosseini Gharbi S M. Environmental Risk Assessment of Gas Wells Drilling Effluents: Integration of Environmental Failure Mode and Effects Analysis and Analytic Network Process Models. Journal of Health Sciences & Surveillance System. 2020; 8(1), p. 49-56. https://jhsss.sums.ac.ir/article_46583.html


9. Ghosh S, Jintanapakanont J. Identifying and assessing the critical risk factors in an underground rail project in Thailand: a factor analysis approach. International Journal of Project Management. 2004; 22(8), p. 633-643. https://doi.org/10.1016/j.ijproman.2004.05.004


10. Kakaei H, Jafari Nodoushan R, Kamalvandi M, Azad P, Normohammadi P, Kakaei Z. Identification and Classification of Risks and Potential Events by using Preliminary Hazard Analysis Method (PHA) in Kermanshah Oil Refinery. jehe. 2015; 3 (1), p.1-9.  http://jehe.abzums.ac.ir/article-1-196-fa.html. (In Persian)


11. Cavallaro F, Zavadskas E K, Raslanas S. Evaluation of combined heat and power (CHP) systems using fuzzy Shannon entropy and fuzzy TOPSIS. Sustainability. 2016; 8(6), p. 556. https://doi:10.3390/su8060556.


12. Hosseinzadeh Lotfi F, Fallahnejad R. Imprecise Shannon’s entropy and multi-attribute decision making. Entropy. 2010; 12(1), p. 53-62. https://doi.org/10.3390/e12010053


13. Patil S K, Kant R. A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers. Expert Systems with Applications. 2014; 41(2), p. 679-693. https://doi.org/10.1016/j.eswa.2013.07.093


14. Safari H, Kazemi A, Mehrpoor Layeghi Performance Assessment of Iranian Gas Transmission Company’s Operational Zones through a Hybrid Method of DEA – WASPAS – SWARA. J. Industrial management studies. 2017; 16 (49), p. 139-171. https://doi.org/10.22054/jims.2018.8788. (In Persian)


15. Turskis Z, Goranin N, Nurusheva A, Boranbayev S. A fuzzy WASPAS-based approach to determine critical information infrastructures of EU sustainable development. Sustainability. 2019; 11, 424. https://doi.org/10.3390/su11020424


16. Zavadskas E K, Turskis Z, Antucheviciene J, Zakarevicius A. Optimization of weighted aggregated sum product assessment. Elektronika ir elektrotechnika. 2012; 122(6), p. 3-6. https://doi.org/10.5755/j01.eee.122.6.1810


17. Bid S, Siddique G. Human risk assessment of Panchet dam in India using TOPSIS and WASPAS multi-criteria decision-making (MCDM) methods. Heliyon. 2019; 5(6): e01956. https://doi.org/10.1016/j.heliyon.2019.e01956


18. Ighravwe D E, Oke S A. A fuzzy-grey-weighted aggregate sum product assessment methodical approach for multi-criteria analysis of maintenance performance systems. International Journal of Systems Assurance Engineering and Management. 2017; 8(S2), p. 961–973.DOI: 1007/s13198-016-0554-8