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IJME 496

Paper Title: Risk Assessment Model of Coastal Sea Pollution By Black (Sewage) Waters From Vessels

 

Authors

Ž Koboević, Ž Kurtela, N Koboević, Maritime Department, University of Dubrovnik, Croatia

Summary  

Qualitative risk assessment using the risk matrices recommended by International Maritime Organization (IMO) and International Standards Organization (ISO) cannot be used for the risk assessment of the pollution of precisely determined part of the coastal sea by black waters from various vessels. Therefore, an original model has been set for risk assessment by means of multiplicative matrices at three levels, allowing risk assessment for very complex assessments with a lot more input factors unlike the classic risk matrix that has two input factors (frequency of occurrence, intensity of consequences). The proposed model of risk assessment uses matrices which first determine the vessel risk index taking into consideration the factor of device for the processing of black waters and the factor of regulations that are applied to the respective vessels. Later, the location sensitivity index is determined, which takes into consideration the sensitivity factor of the location and the factor of impact on the location. Finally, at the third level the assessed risk of sea pollution by black waters is determined according to the type of vessel at precisely defined maritime zone locations. The offered model of risk assessment using multiplicative matrices has practical application and can be used also for many other risk assessments that take into consideration many input factors that affect the risk. The result of risk assessment of the pollution of the coastal sea can be used in decision-making in risk management for undertaking measures in order to protect the coastal sea, human health, and economic activities of a certain area in the coastal sea.

 

Reference

Transactions RINA, Vol 160, Part A4, International Journal Maritime Engineering, Oct - Dec 2018 

DOI Number

DOI No: 10.3940/rina.ijme.2018.a4.496

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