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Simulation and prediction of phenolic compounds fate in Songhua River, China

Wang, Ce, Feng, Yujie, Gao, Peng, Ren, Nanqi, Li, Bai-Lian
The Science of the total environment 2012 v.431 pp. 366-374
water pollution, Monte Carlo method, rivers, simulation models, pollution control, uncertainty analysis, pollutants, water flow, statistical models, prediction, phenolic compounds, China
The demand for numerical models to simulate and predict the transport and fate of organic pollutants in the environment is a reflection of certain restrictions of experimental research. Various phenolic pollutants have been detected at different concentration levels in the Songhua River, China. A multimedia fate model is coupled with the kinematic wave transport equations to accurately and simply characterize dynamic water flow, velocity and depth. The resulting model is applied to describe the temporal and spatial behavior of eight phenol compounds in the Songhua River. The predictive power of this model is evaluated by statistical tests using field observations during different hydrological seasons of the year 2007. The goodness-of-fit of model prediction for phenolic contaminants is, in general, agreeable. For one focal compound, the pathways and mass fluxes from the river system to the surrounding environment are also evaluated. Uncertainty analysis is performed by Monte Carlo stimulation to judge the influence of variability of input parameters on modeled results. The results indicate that the model has the ability to provide decision makers with valuable reference data for consideration of water pollution controls. Model simulation indicates that phenolic pollution in the river during the low-flow period of 2009 is remarkably reduced when compared to the same period of 2007.