Deksissa T, Vanrolleghem P A
BIOMATH, Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure Links 653, B-9000 Gent, Belgium.
Water Sci Technol. 2005;52(12):73-81.
A new conceptual dynamic integrated model is presented which can be used to describe both conventional pollutants and organic contaminant fate in rivers. The model is designed to assess the short-term fate of organic contaminants in two compartments (bulk water and benthic sediment), taking into account the effect of nutrient dynamics. The biodegradation submodel was refined using a microcosm (artificial river) study and Linear Alkylbenzene Sulphonate (LAS) as an example. Based on data generated during the microcosm study, the model was calibrated and validated in both steady state (continuous constant load) and dynamic (pulse load) conditions. The results show that the simulated data set agrees well with the measured data set. Furthermore, thorough investigation of the model output sensitivity to the model inputs was made, and the results show that the fate of LAS is sensitive to the following model input variables: ammonia nitrogen, dissolved oxygen, microbial biomass and readily biodegradable soluble COD, and the model parameters mainly related to the biodegradation submodel. The model provides good understanding of the interaction between conventional pollutants and organic contaminants fate in rivers.
提出了一种新的概念性动态综合模型，该模型可用于描述河流中常规污染物和有机污染物的归宿。该模型旨在评估两个隔室（水体和底栖沉积物）中有机污染物的短期归宿，同时考虑营养物质动态的影响。以线性烷基苯磺酸盐（LAS）为例，利用微宇宙（人工河）研究对生物降解子模型进行了优化。基于微宇宙研究期间生成的数据，在稳态（连续恒定负荷）和动态（脉冲负荷）条件下对模型进行了校准和验证。结果表明，模拟数据集与实测数据集吻合良好。此外，还对模型输出对模型输入的敏感性进行了深入研究，结果表明，LAS的归宿对以下模型输入变量敏感：氨氮、溶解氧、微生物生物量和易生物降解的可溶性化学需氧量，以及主要与生物降解子模型相关的模型参数。该模型有助于深入了解河流中常规污染物与有机污染物归宿之间的相互作用。
