Evaluation of Factors Influencing Maritime Dangerous Cargo Transport Accidents-Induced Crew Fatalities and Serious Injuries

Özge Eski; Leyla Tavacioglu

doi:10.28991/CEJ-2022-08-10-05

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Özge Eski
eski16@itu.edu.tr
Faculty of Maritime, Istanbul Technical University, Istanbul,, Turkey https://orcid.org/0000-0003-2596-7851
Leyla Tavacioglu Faculty of Maritime, Istanbul Technical University, Istanbul,, Turkey https://orcid.org/0000-0002-9919-8226

Vol. 8 No. 10 (2022): October

Research Articles

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Maritime dangerous cargo transport accidents can lead to crew fatalities and serious injuries. This paper focuses on these accidents to evaluate the factors involved in these losses. To that end, the relevant reports of 2000–2020 maritime dangerous cargo transport accidents recorded in the Marine Casualties and Incidents (MCI) module of the International Maritime Organization's Integrated Shipping Information System (IMO-GISIS) database were analyzed. Six initial events in six basic ship operations were determined. This paper combined the entropy weight and Grey relational analysis methods to analyze the involved factors and evaluate the extent of influences of each initial event in various ship operations. The entropy weight (EW) method was applied to determine the weights of basic ship operations. The grey relational analysis method was applied to calculate the correlational degrees of the initial events. Most crew fatalities and severe injuries occur during bunkering, berthing, and mooring operations. Occupational accidents and fires/explosions are the most influential factors; more specifically, occupational accidents during sailing, cargo loading/unloading, anchoring, berthing, and mooring operations and fires/explosions during bunkering operations are most likely to lead to crew fatalities and serious injuries. The results of this paper can aid stakeholders in improving the required strategies to ensure the safety of seafarers during maritime dangerous cargo transport.

Doi: 10.28991/CEJ-2022-08-10-05

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[1] Eski, Ö., & Tavacioglu, L. (2021). Evaluation of port workers' general awareness of dangerous cargo transport: A Turkish port example. Pomorstvo, 35(2), 231–240. doi:10.31217/p.35.2.5.
[2] Erkut, E., Tjandra, S. A., & Verter, V. (2007). Chapter 9 Hazardous Materials Transportation. Handbooks in Operations Research and Management Science, 14(C), 539–621, Elsevier, Amsterdam. Netherlands. doi:10.1016/S0927-0507(06)14009-8.
[3] Zhao, B. (2016). Facts and lessons related to the explosion accident in Tianjin Port, China. Natural Hazards, 84(1), 707–713. doi:10.1007/s11069-016-2403-0.
[4] Mehan, A., & Jansen, M. (2020). Beirut Blast: A port city in crisis. The Port City Futures Blog. Available online: https://philpapers.org/rec/MEHBBA-2 (accessed on May 2022).
[5] Yang, J., Wan, J., Ma, Y., Zhang, J., & Hu, Y. (2020). Characterization analysis and identification of common marine oil spill types using hyperspectral remote sensing. International Journal of Remote Sensing, 41(18), 7163–7185. doi:10.1080/01431161.2020.1754496.
[6] Lecue, M., & Darbra, R. M. (2019). Accidents in European ports involving chemical substances: Characteristics and trends. Safety Science, 115(1), 278–284. doi:10.1016/j.ssci.2019.02.015.
[7] Saruchera, F. (2020). Determinants of effective high-risk cargo logistics at sea ports: A case study. Journal of Transport and Supply Chain Management, 14. doi:10.4102/jtscm.v14i0.488.
[8] Khan, R. U., Yin, J., Mustafa, F. S., & Wang, S. (2022). Analyzing human factor involvement in sustainable hazardous cargo port operations. Ocean Engineering, 250, 111028. doi:10.1016/j.oceaneng.2022.111028.
[9] Weng, J., Yang, D., Chai, T., & Fu, S. (2019). Investigation of occurrence likelihood of human errors in shipping operations. Ocean Engineering, 182, 28–37. doi:10.1016/j.oceaneng.2019.04.083.
[10] Khan, R. U., Yin, J., Mustafa, F. S., & Ahmad Farea, A. O. (2022). A data centered human factor analysis approach for hazardous cargo accidents in a port environment. Journal of Loss Prevention in the Process Industries, 75, 104711. doi:10.1016/j.jlp.2021.104711.
[11] Zhou, L., Fu, G., & Xue, Y. (2018). Human and organizational factors in Chinese hazardous chemical accidents: a case study of the ‘8.12' Tianjin Port fire and explosion using the HFACS-HC. International Journal of Occupational Safety and Ergonomics, 24(3), 329–340. doi:10.1080/10803548.2017.1372943.
[12] Huang, P., & Zhang, J. (2015). Facts related to August 12, 2015 explosion accident in Tianjin, China. Process Safety Progress, 34(4), 313–314. doi:10.1002/prs.11789.
[13] Hua, W., Chen, J., Qin, Q., Wan, Z., & Song, L. (2021). Causation analysis and governance strategy for hazardous cargo accidents at ports: Case study of Tianjin Port's hazardous cargo explosion accident. Marine Pollution Bulletin, 173(4), 113053. doi:10.1016/j.marpolbul.2021.113053.
[14] Ellis, J. (2010). Undeclared dangerous goods - Risk implications for maritime transport. WMU Journal of Maritime Affairs, 9(1), 5–27. doi:10.1007/BF03195163.
[15] Ellis, J. (2011). Analysis of accidents and incidents occurring during transport of packaged dangerous goods by sea. Safety Science, 49(8–9), 1231–1237. doi:10.1016/j.ssci.2011.04.004.
[16] Ronza, A., Carol, S., Espejo, V., Vílchez, J. A., & Arnaldos, J. (2006). A quantitative risk analysis approach to port hydrocarbon logistics. Journal of Hazardous Materials, 128(1), 10–24. doi:10.1016/j.jhazmat.2005.07.032.
[17] Chen, J., Zheng, H., Wei, L., Wan, Z., Ren, R., Li, J., Li, H., Bian, W., Gao, M., & Bai, Y. (2020). Factor diagnosis and future governance of dangerous goods accidents in China's ports. Environmental Pollution, 257, 113582. doi:10.1016/j.envpol.2019.113582.
[18] Xie, T., Lu, X., Wang, G., & Lin, F. (2021). Research on Safety Risk, Prevention and Control in Port Dangerous Goods Container Yard. Journal of Physics: Conference Series, 1910(1), 12029. doi:10.1088/1742-6596/1910/1/012029.
[19] Rí¸mer, H., Brockhoff, L., Haastrup, P., & Styhr Petersen, H. J. (1993). Marine transport of dangerous goods. Risk assessment based on historical accident data. Journal of Loss Prevention in the Process Industries, 6(4), 219–225. doi:10.1016/0950-4230(93)80003-5.
[20] Rí¸mer, H., Haastrup, P., & Styhr Petersen, H. J. (1995). Accidents during marine transport of dangerous goods. Distribution of fatalities. Journal of Loss Prevention in the Process Industries, 8(1), 29–34. doi:10.1016/0950-4230(95)90059-X.
[21] Li, K. X., & Wonham, J. (2001). Maritime legislation: new areas for safety of life at sea. Maritime Policy and Management, 28(3), 225–234. doi:10.1080/03088830110048880.
[22] Nielsen, D., & Roberts, S. (1999). Fatalities among the world's merchant seafarers (1990-1994). Marine Policy, 23(1), 71–80. doi:10.1016/S0308-597X(98)00017-7.
[23] Li, K. X. (1998). Seamen's accidental deaths worldwide: A new approach. Maritime Policy and Management, 25(2), 149–155. doi:10.1080/03088839800000025.
[24] Zheng, Y., Talley, W. K., Jin, D., & Ng, M. W. (2016). Crew injuries in container vessel accidents. Maritime Policy & Management, 43(5), 541–551. doi:10.1080/03088839.2016.1150610.
[25] Chen, J., Zhang, W., Li, S., Zhang, F., Zhu, Y., & Huang, X. (2018). Identifying critical factors of oil spill in the tanker shipping industry worldwide. Journal of Cleaner Production, 180, 1–10. doi:10.1016/j.jclepro.2017.12.238.
[26] Shemshadi, A., Shirazi, H., Toreihi, M., & Tarokh, M. J. (2011). A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Systems with Applications, 38(10), 12160–12167. doi:10.1016/j.eswa.2011.03.027.
[27] Zhang, H., Gu, C., Gu, L., & Zhang, Y. (2011). The evaluation of tourism destination competitiveness by TOPSIS & information entropy – A case in the Yangtze River Delta of China. Tourism Management, 32(2), 443–451. doi:10.1016/j.tourman.2010.02.007.
[28] Wu, H. Y., & Lin, H. Y. (2012). A hybrid approach to develop an analytical model for enhancing the service quality of e-learning. Computers & Education, 58(4), 1318–1338. doi:10.1016/j.compedu.2011.12.025.
[29] Hsiao, S. W., & Tsai, H. C. (2004). Use of gray system theory in product-color planning. Color Research & Application, 29(3), 222–231. doi:10.1002/col.20009.
[30] Kuo, Y., Yang, T., & Huang, G. W. (2008). The use of grey relational analysis in solving multiple attribute decision-making problems. Computers & Industrial Engineering, 55(1), 80–93. doi:10.1016/j.cie.2007.12.002.
[31] Vatansever, K., & AkgŠ±l, Y. (2018). Performance evaluation of websites using entropy and grey relational analysis methods: The case of airline companies. Decision Science Letters, 7(2), 119–130. doi:10.5267/j.dsl.2017.6.005.
[32] Chae, S., & Yoshida, T. (2010). Application of RFID technology to prevention of collision accident with heavy equipment. Automation in Construction, 19(3), 368–374. doi:10.1016/j.autcon.2009.12.008.
[33] Youssef, S. A. M., & Paik, J. K. (2018). Hazard identification and scenario selection of ship grounding accidents. Ocean Engineering, 153, 242–255. doi:10.1016/j.oceaneng.2018.01.110.
[34] Li, J., & Huang, Z. (2012). Fire and explosion risk analysis and evaluation for LNG ships. Procedia Engineering, 45, 70–76. doi:10.1016/j.proeng.2012.08.123.
[35] European Maritime Safety Agency. (2020). Annual overview of marine casualties and incidents. European Maritime Safety Agency (EMSA), Lisbon, Portugal.
[36] Paolo, F., Gianfranco, F., Luca, F., Marco, M., Andrea, M., Francesco, M., Vittorio, P., Mattia, P., & Patrizia, S. (2021). Investigating the Role of the Human Element in Maritime Accidents using Semi-Supervised Hierarchical Methods. Transportation Research Procedia, 52, 252–259. doi:10.1016/j.trpro.2021.01.029.
[37] Hansen, H. L., Nielsen, D., & Frydenberg, M. (2002). Occupational accidents aboard merchant ships. Occupational and Environmental Medicine, 59(2), 85–91. doi:10.1136/oem.59.2.85.

Publication Start Year:	2015
JCR 2023 Impact Factor (IF):	4.3
JIF QUARTILE:	Q1
SJR 2023 Quartile:	Q1
Acceptance Rate:	27%
Review Speed (Average):	76 days
Issue Per Year:	12
Number of Volumes:	10
Number of Issues:	107
Number of Articles:	1552
Number of Reviewers:	3417
Number of Contributors:	3604
Contributing Countries:	86
No. of WoS Citations:	7986
WoS h-index:	34
Scopus CiteScore:	7.0
No. of Google Citations:	17324
Google h-index:	47
Google i10-index:	393
Abstract Views:	5,819,908
PDF Download:	3,790,637

Evaluation of Factors Influencing Maritime Dangerous Cargo Transport Accidents-Induced Crew Fatalities and Serious Injuries

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