• 한국대기환경학회지
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• 제15권2호
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• pp.151-158
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• 1999

Offsite consequences resulting form worst-case scenarios involving release of toxic substances in the Yochon area were estimated using the ALOHA(Areal Locations of Hazardous Atmospheres) model. Eight toxic substances, including NH3, were considered; five were toxic gases and three were toxic liquids at ambient temperature. For toxic gases, the entire quantity was assumed to be released at a constant rate during a 10-minute period. For toxic liquids, the entire quantity stored in the tank was assumed to be spilled and spread and spread instantaneously to form a pool with a depth of 1cm, and then evaporated over some period of time. Except for phosgene and toluene 2,4-diisocyanate, for which concentration levels corresponding to human health effects are very low, average distances of the area at risk of adverse health effects for a 1- tom release were predicted to be $2.3{\pm}1.1 km$ for the worst-case meteorological conditions and $0.93{\pm}0.69km$ under typical meteorological conditions of the Yochon are. Because a large number of people were predicted to be affected in the current analysis, refined analyses considering both realistic accident scenarios and topographic effects were warranted.

• 한국대기환경학회지
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• 제15권5호
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• pp.687-696
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• 1999

Characteristics of four publicly-available accidental release models, ALOHA, SLAB, HGSYSTEM, and DEGADIS, are compared. These models are world-widely used and recently recommended by the Chemical Dispersion and Consequence Assessment(CDCA) Working Group of the United States as models applicable to generally broad safety-basis documentation applicatons. Four release scenarios are assumed by referring to the usage and storage conditions of toxic substances in the field as well as the USEPA model guideline(1993). Sensitivity of impact radius by varying meteorological conditions is tested in typical and worst-case meteorological conditions. The results show that ALOHA generally gives conservative estimates and the results from HGSYSTEM are sensitive to variations in meteorological conditions.