Development and Verification of a Risk Index for Evaluating the Chemical Accident Risk of Korean Chemical Enterprises
- Authors
- Shin, Saemi; Byeon, Sang-Hoon; Sohn, Jong-Ryeul; Moon, Kyong Whan
- Issue Date
- 11월-2019
- Publisher
- MDPI
- Keywords
- KCARI; chemical accident; risk index; relative ranking method; inherent safety
- Citation
- INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, v.16, no.22
- Indexed
- SCIE
SSCI
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
- Volume
- 16
- Number
- 22
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/62030
- DOI
- 10.3390/ijerph16224409
- ISSN
- 1661-7827
- Abstract
- The scale of the damage due to chemical accidents in Korea is significant, and appropriate preparation and response are required. Currently, Korean enterprises are managed on the basis of the presence of certain substances. However, chemicals other than these also cause chemical accidents. It is necessary to develop a relative ranking risk index that can be calculated through use of the chemical enterprise information on chemical enterprises that is available. The Korean chemical accident risk index (KCARI), which consists of the flammability, reactivity, explosiveness, corrosiveness, toxicity, and inventory sub-indices, was developed and verified by determining the for difference in KCARI was performed by accident, and accident severity category, calculating the correlation between the KCARI values, the factors, and some sub-indices, determining how an increase in the KCARI would impact how the incident rate changed as KCARI increased and how well the KCARI can predict the chemical accident risk of chemical handling enterprises, and confirming the consistency of the proposed index and the current system. These results indicated that the frequency and severity of chemical accidents, and the presence of accidental substances, showed significant differences in the KCARI values. However, there were limitations in the ability of the fitted model to precisely predict the accident. Thus, this model can be used as a tool for the early screening and management of enterprises with a high risk of chemical accident.
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