418. Marine Oil Spill Response: How to Apply Hazwoper Training Requirements

ABSTRACT The Maritime Safety Authority of New Zealand (MSA) has a mandate to promote a safe and clean marine environment and to provide an effective marine pollution response capability. As part of its obligations, the MSA is responsible for the New Zealand Marine Oil Spill Response Strategy and the preparation of a National Marine Oil Spill Contingency Plan for Tier 3 spill events (Maritime Transport Act 1994, S.283). The MSA is currently working on the design of an extensive coastal information database—including information such as marine and natural resource inventories and coastal human-built infrastructures—that can be mapped in a GIS system. A customised toolset is also being developed to streamline the management of the database. The benefits of GIS-based information management systems in oil spill response have been demonstrated by a number of overseas response agencies. However, many of these rely on discrete components or only fulfil specific individual requirements, such as the provision of coastal resource information. Having reviewed these approaches, New Zealand has embarked on the development of a more integrated and comprehensive oil spill information management system that will deliver a broad range of applications and serve to provide a framework for the seamless management and reporting of all the types of data that are generated throughout the life cycle of an oil spill response. The system combines GIS and database technology. It includes field survey management support, as well as automated treatment mechanisms to produce reports and maps to support planning and operations. The system also integrates a pre-spill shoreline segmentation database. The benefits of such a system will include the recording and presentation of all types of response data that is more responsive to the needs of operational decision makers; the ability to better track the progress of spill cleanup activities in both a temporal and spatial context; and the generation of customised reports to assist in cost recovery claims on termination of response activities.

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New Learning Methods for Marine Oil Spill Response Training

TransNav the International Journal on Marine Navigation and Safety of Sea Transportation ◽

10.12716/1001.11.02.18 ◽

2017 ◽

Vol 11 (2) ◽

pp. 153-159

Author(s):

Justiina Halonen ◽

Antti Lanki ◽

Emmi Rantavuo

Keyword(s):

Oil Spill ◽

Learning Methods ◽

Marine Oil ◽

Response Training ◽

New Learning ◽

Oil Spill Response

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A robust optimization approach to locating and stockpiling marine oil-spill response facilities

Transportation Research Part E Logistics and Transportation Review ◽

10.1016/j.tre.2020.102005 ◽

2020 ◽

Vol 141 ◽

pp. 102005 ◽

Cited By ~ 2

Author(s):

Hassan Sarhadi ◽

Joe Naoum-Sawaya ◽

Manish Verma

Keyword(s):

Robust Optimization ◽

Oil Spill ◽

Optimization Approach ◽

Marine Oil ◽

Oil Spill Response

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A Survey of Classical and New Response Methods for Marine Oil Spill Cleanup

Marine Technology and SNAME News ◽

10.5957/mt1.1994.31.2.79 ◽

1994 ◽

Vol 31 (02) ◽

pp. 79-93

Author(s):

Emilio A. Tsocalis ◽

Thomas W. Kowenhoven ◽

Anastassios N. Perakis

Keyword(s):

Oil Spill ◽

Oil Recovery ◽

Heavy Oil ◽

Heavy Oil Recovery ◽

New Materials ◽

Marine Oil ◽

Methods And Techniques ◽

Oil Spill Response ◽

Oil Spill Cleanup

Both classical and new marine oil spill cleanup response methods and techniques are discussed. The intention is mainly to answer the fundamental questions of when, where, and how to apply the different methods. A brief review of the stages of the oil spill response problem is first presented, followed by the factors that influence the different methods. This is followed by an analysis of some new cleanup methods and improvements to existing methods, specifically: bioremediation, the use of more efficient ships for skimming, the use of fishing nets for heavy oil recovery, and new materials and designs of sorbents. Some cases are also analyzed to evaluate the performance of some methods under real conditions.

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