• Journal of Environmental Health Sciences
• /
• v.46 no.2
• /
• pp.136-149
• /
• 2020

Objectives: The purpose of this study was to perform an aggregate human risk assessment for benzene in an industrial complex using the CalTOX model and to improve the reliability and predictability of the model by analyzing the uncertainty and sensitivity of the predicted assessment results. Methods: The CalTOX^TM 4.0 beta model was used to evaluate a selected region, and @Risk 7.6 software was used to analyze uncertainty and sensitivity. Results: As a result of performing the aggregate risk assessment on the assumption that 6.45E+04 g/d of benzene would be emitted into the atmosphere over two decades, 3% of the daily source term to air remained in the selected region, and 97% (6.26E+04 g/d) moved out of the region. As for exposure by breathing, the predicted LADD_inhalation was 2.14E-04 mg/kg-d, and that was assessed as making a 99.99% contribution to the LADD_total. Regarding human Risk_cancer assessment, the predicted human cancer risk was 5.19E-06 (95% CI; 4.07E-06-6.81E-06) (in the 95th percentile corresponding to the highest exposure level, a confidence interval of 90%). As a result of analyzing sensitivity, 'source term to air' was identified as the most influential variable, followed by 'exposure time, active indoors (h/day)', and 'exposure duration (years)'. Conclusions: As for the results of the human cancer risk assessment for the selected region, the predicted human cancer risk was 5.19E-06 (95% CI; 4.07E-06-6.81E-06) (in the 95th percentile, corresponding to the highest exposure level, a confidence interval of 90%). As a result of analyzing sensitivity, 'source term to air' was found to be most influential.

• Journal of Environmental Health Sciences
• /
• v.45 no.5
• /
• pp.497-510
• /
• 2019

Objectives: The aim of this study was to secure the reliability of using the CalTOX model when evaluating LADD (or ADD) and Risk (or HQ) among local residents for the emission of BTEX (Benzene, Toluene, Ethylbenzene, Xylene) and by closely examining the difference in the confidence interval of the assessment outcomes according to the difference in the probability density function of input variables. Methods: The assessment was made by dividing it according to the method ($I^{\dagger}$) of inputting the probability density function in meteorological variables of the model with log-normal distribution and the method of inputting ($II^{\ddagger}$) after grasping the optimal probability density function using @Risk. A T-test was carried out in order to analyze the difference in confidence interval of the two assessment results. Results: It was evaluated to be 1.46E-03 mg/kg-d in LADD of Benzene, 1.96E-04 mg/kg-d in ADD of Toluene, 8.15E-05 mg/kg-d in ADD of Ethylbenzene, and 2.30E-04 mg/kg-d in ADD of Xylene. As for the predicted confidence interval in LADD and ADD, there was a significant difference between the $I^{\dagger}$ and $II^{\ddagger}$ methods in $LADD_{Inhalation}$ for Benzene, and in $ADD_{Inhalation}$ and ADD for Toluene and Xylene. It appeared to be 3.58E-05 for risk in Benzene, 3.78E-03 for HQ in Toluene, 1.48E-03 for HQ in Ethylbenzene, and 3.77E-03 for HQ in Xylene. As a result of the HQ in Toluene and Xylene, the difference in confidence interval between the $I^{\dagger}$ and $II^{\ddagger}$ methods was shown to be significant. Conclusions: The human risk assessment for BTEX was made by dividing it into the method ($I^{\dagger}$) of inputting the probability density function of meteorological variables for the CalTOX model with log-normal distribution, and the method of inputting ($II^{\ddagger}$) after grasping the optimal probability density function using @Risk. As a result, it was identified that Risk (or HQ) is the same, but that there is a significant difference in the confidence interval of Risk (or HQ) between the $I^{\dagger}$ and $II^{\ddagger}$ methods.

• Journal of Environmental Health Sciences
• /
• v.48 no.3
• /
• pp.151-158
• /
• 2022

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.

• Journal of Soil and Groundwater Environment
• /
• v.12 no.1
• /
• pp.53-63
• /
• 2007

Soil risk assessment models were used to determine the goals of soil remediation and to establish the soil quality standards in developed countries. Recently, Korean Ministry of Environment prepared the guideline for soil risk assessment. Soil risk assessment model applicable to Korean situation will be needed in the near future. In this study, three models for soil risk assessment were extensively compared to suggest the fundamental components that required for the soil risk assessment in Korea. The models considered in this study were CalTOX in the United States, CLEA (Contaminated Land Exposure Assessment) in the United Kingdom, and CSOIL in the Netherlands. The major exposure routes and the intake estimation equations suitable for Korean situation were suggested. The exposure routes suggested were intake of the crops, underground water, indoor outdoor soil ingestion, dust inhalation and a volatile matter inhalation. The equations for intake estimation used in CalTOX and CSOIL seem to be applicable for the calculation of the human intake in Korea.

• Journal of Environmental Health Sciences
• /
• v.46 no.5
• /
• pp.576-587
• /
• 2020

Objectives: This study calculated local residents exposures to VOCs (Volatile Organic Compounds) released into the atmosphere using the CalTOX model and carried out uncertainty analysis and sensitivity analysis. The model validity was analyzed by comparing the predicted and the actual atmospheric concentrations. Methods: Uncertainty was parsed by conducting a Monte Carlo simulation. Sensitivity was dissected with the regression (coefficients) method. The model validity was analyzed by applying r² (coefficient of determination), RMSE (root mean square error), and the Nash-Sutcliffe EI (efficiency index) formula. Results: Among the concentrations in the atmosphere in this study, benzene was the highest and the lifetime average daily dose of benzene and the average daily dose of xylene were high. In terms of the sensitivity analysis outcome, the source term to air, exposure time, indoors resting (ETri), exposure time, outdoors at home (ETao), yearly average wind speed (v_w), contaminated area in ㎡ (Area), active breathing rate (BRa), resting breathing rate (BRr), exposure time, and active indoors (ETai) were elicited as input variables having great influence upon this model. In consequence of inspecting the validity of the model, r² appeared to be a value close to 1 and RMSE appeared to be a value close to 0, but EI indicated unacceptable model efficiency. To supplement this value, the regression formula was derived for benzene with y=0.002+15.48x, ethylbenzene with y ≡ 0.001+57.240x, styrene with y=0.000+42.249x, toluene with y=0.004+91.588x, and xylene with y=0.000+0.007x. Conclusions: In consequence of inspecting the validity of the model, r² appeared to be a value close to 1 and RMSE appeared to be a value close to 0, but EI indicated unacceptable model efficiency. This will be able to be used as base data for securing the accuracy and reliability of the model.