Journal of Applied Science and Engineering

Published by Tamkang University Press

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Chemical Engineering

Özge Eski This email address is being protected from spambots. You need JavaScript enabled to view it.1 and Leyla Tavacioglu1

1Istanbul Technical University, Faculty of Maritime, Department of Basic Sciences

 

Received: June 30, 2022
Accepted: September 4, 2022
Publication Date: September 21, 2022

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Download Citation: ||https://doi.org/10.6180/jase.202306_26(6).0014  


ABSTRACT

Maritime dangerous cargo transport accidents can lead to chemical spills in port areas. This paper focuses on these accidents to evaluate the contributing factors involved in these spills. For this purpose, 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 contributing factors in five 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 impacts of each contributor 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 contributing factors. Most chemical spills in port areas occur during cargo unloading, berthing, and unberthing operations. Contacts and occupational accidents are the most influential factors; more specifically, contact during berthing and unberthing operations and occupational accidents during cargo unloading operations are most likely to lead to chemical spills in port areas. The results of this paper can aid stakeholders in developing the required strategies to prevent chemical spills in port areas during maritime dangerous cargo transport.


Keywords: Chemical spill, dangerous goods, port accident, entropy weight method, grey relational analysis


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