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  • Title: Multimedia fate model for hexachlorocyclohexane in Tianjin, China.
    Author: Cao H, Tao S, Xu F, Coveney RM, Cao J, Li B, Liu W, Wang X, Hu J, Shen W, Qin B, Sun R.
    Journal: Environ Sci Technol; 2004 Apr 01; 38(7):2126-32. PubMed ID: 15112816.
    Abstract:
    A level III fugacity model was applied to characterize the fate of gamma-HCH in Tianjin, China, before the 1990s when the contamination reached its maximum at steady state. Geometric means were used as model inputs. The concentrations of gamma-HCH in air, surface water, soil, sediment, crops, and fish as well as transfer fluxes across the interface between the compartments were derived under the assumption of steady state. The calculated concentrations were validated by independent data collected from the literature. There was generally good agreement between the estimated and the observed concentrations, and the differences were all less than 0.6 log units for air, water, soil, sediment, and fish and approximately 1 order of magnitude for crops. Around 97% of gamma-HCH accumulated in soil and sediment. Wastewater irrigation was not an important pathway for delivering gamma-HCH to soil as compared to the dominant source of agricultural application. Degradation and advective airflow carried much gamma-HCH out of the system. Sensitivities of the model estimates to input parameters were tested, and a coefficient of variation normalized sensitivity coefficient was defined for the test. The most influential parameters were degradation rates in sediment and soil, application rates, concentrations in wastewater, and adsorption coefficients. Monte Carlo simulation was conducted for model uncertainty analysis. The model was run 20 000 times using randomly generated data from predefined log-normal distribution density functions. All calculated concentrations and fluxes were log-normally distributed. The dispersions of the calculated and observed concentrations were compared in terms of coefficients of variation to distinguish between true variability and model uncertainty.
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