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Consideration on the Regulated Quantity of Preparation for Accidents by Risk Assessment

위험도 평가를 통한 사고대비물질별 규정수량 고찰

  • Ahn, Gwangjae (Department of Environmental Engineering, Ajou University) ;
  • Kim, Jungwook (Department of Environmental Engineering, Ajou University) ;
  • Lee, Keunwon (Department of Environmental and Safety Engineering, Ajou University) ;
  • Jung, Seungho (Department of Environmental and Safety Engineering, Ajou University)
  • 안광재 (아주대학교 환경공학과) ;
  • 김정욱 (아주대학교 환경공학과) ;
  • 이근원 (아주대학교 환경안전공학과) ;
  • 정승호 (아주대학교 환경안전공학과)
  • Received : 2022.06.14
  • Accepted : 2022.07.14
  • Published : 2022.11.01

Abstract

In the Chemicals Control Act, a system was implemented to unify off-site risk assessment and risk management plan into the prevention and management system for chemical accidents. Among the hazardous chemicals which have been covered in system, the accident preparation substances are designated as chemical substances that are likely to occur and of which damage scale are likely to be large in the event of chemical accidents. In this study, risks were compared by selecting accident preparation substances with similar regulated quantities. In addition, risk assessment studies were conducted applying the accident scenarios. Four types of materials such as ammonia, hydrogen chloride, carbon disulfide and benzene were selected for the study, and risks were finally analyzed using Safeti 8.0, a quantitative risk assessment program by DNV. As a result, some materials are identified to have high risks comparing to other substances having similar regulated quantities.

화학물질관리법에서 장외영향평가서 및 위해관리계획서를 화학사고예방관리계획서로 일원화하는 제도가 시행되었다. 화학사고예방관리계획서에서 다루는 유해화학물질 중 사고대비물질은 화학사고의 발생 가능성이 높거나 화학사고가 발생한 경우에 그 피해 규모가 클 것으로 우려되는 화학물질로서 지정하고 있다. 본 연구에서는 사고대비물질별 규정수량 기준에 따른 위험도를 비교하고자 상위/하위 규정수량이 비슷한 화학물질을 특정하여 동일한 사고 시나리오를 선정하고 위험도 평가를 실시하였다. 연구대상물질은 암모니아, 염화수소, 이황화탄소, 벤젠 등 총 4종의 물질을 선정하였으며, DNV 사의 정량적 위험성 평가 프로그램인 Safeti 8.0을 활용하여 위험도를 비교 분석하였다. 그 결과, 비슷한 상위/하위규정수량임에도 불구하고 상대적으로 높은 위험도를 가지고 있는 물질을 확인할 수 있었다.

Keywords

Acknowledgement

이 논문은 2022년도 산업통상자원부의 재원으로 한국산업기술진흥원의 지원을 받아 수행된 연구임(P0012787, 산업혁신인재성장지원사업).

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