위험도 매핑 기반 해상방제 의사결정지원 및 장비배치에 관한 연구

Abstract

South Korea experienced catastrophic oil spill accidents such as Sea Prince oil spill in 1995 and Hebei Spirit oil spill in 2007, and calculated the required amount of marine response equipment to prepare for the largest oil spill accident. And It have developed equipment deployment plan to prepare for the largest oil spill accident by region.

However, this plan is based only on the maximum oil spill for the largest vessels entry and departure the port, and on the response time of the equipment in the region and other areas to mobilize in case of an accident. Although it is not actually a major port, there may be a risk that environmental, biological, and ecological damages will be widened due to delays in equipment mobilization in sensitive areas.

In addition, the decision-maker, in most oil spill accident sites, depends on the intelligence gathering and his(or her) expertise and experiences while making response strategy, but it is required to provide the scientific and systematic decision support system for more effective and efficient response.

In this regards, the author examines current criteria of equipment deployment and studies to seek the more appropriate distribution method of on-water response equipments and develop decision support system for OSC and related personnel for the large oil spills.

This thesis calculate response equipment requirements and redeploy marine response equipments based on risk analysis and type using frequency factor of oil spill accident statistical data such as accident, spilled oil volume, spilled oil type, vessel type and consequence factor of economic benefit data such as fishery, aquaculture, beach, port.

In addition, the thesis conducted research that can provide quick and effective decision-making by analyzing and providing detailed risk factors for the accident area and the surrounding area.

The thesis result is as follows :

First, it quantitatively calculated the frequency of the oil spill and the consequence of damage caused by oil spill through the matrix analysis.

In order to estimate the accident occurrence and the damage result, the risk factors were identified through literature review and expert questionnaire, and risk factors capable of securing objective data were selected. And analyzed frequency factors and consequence factors in 12 years from 2004 to 2015. Based on this, It set the risk level to 5 and calculated and mapped the risk of the waters in Korea. 22 area as Incheon, Pyeongtaek, Daesan, Boryeong, Mokpo, Wando, Jeju, Seogwipo, Tongyoung, Masan, Changwon, , Gangneung, and Sokcho is required the cooperation of support forces that difficult to prepare for and respose to each region. And Moderate level risk found area including island area of northwest, southwest, Geogedo. East, West and South Seas Although oil spills have occurred in distant seas, the risk of damage is low.

Furthermore, It analyzed risk types such as high frequecy factor - low consequence factor(HL type) and low frequency factor - high consequence factor (LH type). HH type(high frequency and consequence) risk was shown mainly in major ports. And LH type as frequency is very low at level 0 or 1 and consequence is high at level 3 or 4 was concentrated in the West sea.

Second, the time required to mobilize the oil spill response equipment to the accident site is the same between existing and new model for spilled 15,000㎘ and 7,500㎘. Early in the accident, regional response system and risk-based response deployment model can mobilize response equipment similarly. Since then it has been shown that the risk-based response deployment model can be mobilized more efficiently for additional response forces. Area including main ports where oil tankers and cargo ships are frequent can mobilize more than 40% of total recovery capacity. This being so considering only major ports, it is also effective to consider only the maximum spilled oil volume and mobilization time, too.

Third, it developed a marine response decision support model that can help prioritize marine areas for quick and effective preventive response activities in case of oil spill accidents by dividing 8 risk factors into each area. Through this model, it is possible to identify the risk factors ranging from the accident area to surround 8 areas.

By being able to identify the risk by the risk factor of the sea area, it is thought that it will be helpful to establish a preparation strategy to select and concentrate more systematically and scientifically in establishment and prioritization of response strategy at the site.