CalTOX 모델을 이용한 대산 석유화학단지의 활동단계에 따른 벤젠 흡입 노출평가
Prediction of Inhalation Exposure to Benzene by Activity Stage Using a Caltox Model at the Daesan Petrochemical Complex in South Korea
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초록
Background: Chemical emissions in the environment have rapidly increased with the accelerated industrialization taking place in recent decades. Residents of industrial complexes are concerned about the health risks posed by chemical exposure. Objectives: This study was performed to suggest modeling methods that take into account multimedia and multi-pathways in human exposure and risk assessment. Methods: The concentration of benzene emitted at industrial complexes in Daesan, South Korea and the exposure of local residents was estimated using the Caltox model. The amount of human exposure based on inhalation rate was stochastically predicted for various activity stages such as resting, normal walking, and fast walking. Results: The coefficient of determination (R2) for the CalTOX model efficiency was 0.9676 and the root-mean- square error (RMSE) was 0.0035, indicating good agreement between predictions and measurements. However, the efficiency index (EI) appeared to be a negative value at –1094.4997. This can be explained as the atmospheric concentration being calculated only from the emissions from industrial facilities in the study area. In the human exposure assessment, the higher the inhalation rate percentile value, the higher the inhalation rate and lifetime average daily dose (LADD) at each activity step. Conclusions: Prediction using the Caltox model might be appropriate for comparing with actual measurements. The LADD of females was higher ratio with an increase in inhalation rate than those of males. This finding would imply that females may be more susceptible to benzene as their inhalation rate increases.
Abstract
Background: Chemical emissions in the environment have rapidly increased with the accelerated industrialization taking place in recent decades. Residents of industrial complexes are concerned about the health risks posed by chemical exposure. Objectives: This study was performed to suggest modeling methods that take into account multimedia and multi-pathways in human exposure and risk assessment. Methods: The concentration of benzene emitted at industrial complexes in Daesan, South Korea and the exposure of local residents was estimated using the Caltox model. The amount of human exposure based on inhalation rate was stochastically predicted for various activity stages such as resting, normal walking, and fast walking. Results: The coefficient of determination (R2) for the CalTOX model efficiency was 0.9676 and the root-mean- square error (RMSE) was 0.0035, indicating good agreement between predictions and measurements. However, the efficiency index (EI) appeared to be a negative value at –1094.4997. This can be explained as the atmospheric concentration being calculated only from the emissions from industrial facilities in the study area. In the human exposure assessment, the higher the inhalation rate percentile value, the higher the inhalation rate and lifetime average daily dose (LADD) at each activity step. Conclusions: Prediction using the Caltox model might be appropriate for comparing with actual measurements. The LADD of females was higher ratio with an increase in inhalation rate than those of males. This finding would imply that females may be more susceptible to benzene as their inhalation rate increases.
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