Dokuz Eylul University, Graduate School of Social Science, Department of Maritime Business Administration, Tinaztepe Campus, Buca, Izmir, Turkey.
Dokuz Eylul University, Maritime Faculty, Department of Marine Transportation Engineering, Tinaztepe Campus, Buca, Izmir 35390, Turkey.
Mar Pollut Bull. 2024 Dec;209(Pt A):117122. doi: 10.1016/j.marpolbul.2024.117122. Epub 2024 Oct 22.
Coal self-heating presents significant risks to maritime transportation, including spontaneous combustion, environmental damage, and economic losses. This study aims to apply a Fuzzy Bow-Tie analysis to assess and mitigate the risks associated with coal self-heating during transportation. By integrating expert judgments and addressing uncertainties in the data, the Fuzzy Bow-Tie model offers a comprehensive evaluation of risk factors and safety barriers. This leads to more reliable risk assessments compared to traditional deterministic methods, which are less capable of handling imprecise data. In marine pollution, where early identification of potential hazards (e.g., self-heating coal leading to toxic gas emissions) is critical, the Fuzzy Bow-Tie approach allows for more accurate forecasting of incidents that could result in environmental harm. Key findings reveal that improper ventilation, large air gaps between coal particles, and inaccurate declarations of coal properties are major contributors to self-heating incidents. Furthermore, inadequate cargo monitoring and non-compliance with the International Maritime Solid Bulk Cargoes (IMSBC) Code exacerbate these risks. These insights provide practical guidance for maritime stakeholders, such as shipping companies and port authorities, to improve coal handling practices and enhance safety procedures. The Fuzzy Bow-Tie model provided a reliable and flexible tool for handling uncertainties and improving risk assessment in complex maritime environments. Overall, the study offers practical recommendations for shipping companies and port authorities to improve coal handling safety, reducing the potential for accidents and environmental harm.
煤自燃对海上运输构成重大风险，包括自燃、环境污染和经济损失。本研究旨在应用模糊蝴蝶结分析评估和减轻运输过程中煤自燃相关的风险。通过整合专家判断和处理数据中的不确定性，模糊蝴蝶结模型对风险因素和安全屏障进行了全面评估。与传统的确定性方法相比，这使得风险评估更加可靠，因为传统的确定性方法不太能够处理不精确的数据。在海洋污染中，早期识别潜在危害（例如，自燃煤导致有毒气体排放）至关重要，模糊蝴蝶结方法可以更准确地预测可能导致环境危害的事件。主要发现表明，通风不当、煤颗粒之间的大空气间隙以及煤性质的不准确申报是自燃事件的主要原因。此外，货物监测不足和不遵守《国际海运固体散装货物规则》（IMSBC 规则）加剧了这些风险。这些见解为航运公司和港口当局等海上利益相关者提供了实用的指导，以改善煤炭处理实践并加强安全程序。模糊蝴蝶结模型为处理复杂海上环境中的不确定性和改进风险评估提供了可靠和灵活的工具。总体而言，本研究为航运公司和港口当局提供了实用的建议，以提高煤炭处理安全性，降低事故和环境危害的风险。
