흡입 노출 모델 알고리즘의 구성과 시나리오 노출량 비교 (Model Algorithms for Estimates of Inhalation Exposure and Comparison between Exposure Estimates from Each Model)

Objectives: This study aimed to review model algorithms and input parameters applied to some exposure models and to compare the simulated estimates using an exposure scenario from each model. Methods: A total of five exposure models which can estimate inhalation exposure were selected; the Korea Ministry of Environment(KMOE) exposure model, European Centre for Ecotoxicology and Toxicology of Chemicals Targeted Risk Assessment(ECETOC TRA), SprayExpo, and ConsExpo model. Algorithms and input parameters for exposure estimation were reviewed and the exposure scenario was used for comparing the modeled estimates. Results: Algorithms in each model commonly consist of the function combining physicochemical properties, use characteristics, user exposure factors, and environmental factors. The outputs including air concentration (mg/m3) and inhaled dose(mg/kg/day) are estimated applying input parameters with the common factors to the algorithm. In particular, the input parameters needed to estimate are complicated among the models and models need more individual input parameters in addition to common factors. In case of CEM, it can be obtained more detailed exposure estimates separating user’s breathing zone(near-field) and those at influencing zone(far-field) by two-box model. The modeled exposure estimates using the exposure scenario were similar between the models; they were ranged from 0.82 to 1.38 mg/m3 for concentration and from 0.015 to 0.180 mg/kg/day for inhaled dose, respectively. Conclusions: Modeling technique can be used for a useful tool in the process of exposure assessment if the exposure data are scarce, but it is necessary to consider proper input parameters and exposure scenario which can affect the real exposure conditions.

Objectives: This study aimed to review model algorithms and input parameters applied to some exposure models and to compare the simulated estimates using an exposure scenario from each model. Methods: A total of five exposure models which can estimate inhalation exposure were selected; the Korea Ministry of Environment(KMOE) exposure model, European Centre for Ecotoxicology and Toxicology of Chemicals Targeted Risk Assessment(ECETOC TRA), SprayExpo, and ConsExpo model. Algorithms and input parameters for exposure estimation were reviewed and the exposure scenario was used for comparing the modeled estimates. Results: Algorithms in each model commonly consist of the function combining physicochemical properties, use characteristics, user exposure factors, and environmental factors. The outputs including air concentration (mg/m3) and inhaled dose(mg/kg/day) are estimated applying input parameters with the common factors to the algorithm. In particular, the input parameters needed to estimate are complicated among the models and models need more individual input parameters in addition to common factors. In case of CEM, it can be obtained more detailed exposure estimates separating user’s breathing zone(near-field) and those at influencing zone(far-field) by two-box model. The modeled exposure estimates using the exposure scenario were similar between the models; they were ranged from 0.82 to 1.38 mg/m3 for concentration and from 0.015 to 0.180 mg/kg/day for inhaled dose, respectively. Conclusions: Modeling technique can be used for a useful tool in the process of exposure assessment if the exposure data are scarce, but it is necessary to consider proper input parameters and exposure scenario which can affect the real exposure conditions.