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SimpleTreat 4.0 评估:污水处理厂设施中药物去除的模拟。

Evaluation of SimpleTreat 4.0: Simulations of pharmaceutical removal in wastewater treatment plant facilities.

机构信息

Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands.

Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands; JSScience, Zeist, The Netherlands.

出版信息

Chemosphere. 2017 Feb;168:870-876. doi: 10.1016/j.chemosphere.2016.10.123. Epub 2016 Nov 8.

Abstract

In this study, the removal of pharmaceuticals from wastewater as predicted by SimpleTreat 4.0 was evaluated. Field data obtained from literature of 43 pharmaceuticals, measured in 51 different activated sludge WWTPs were used. Based on reported influent concentrations, the effluent concentrations were calculated with SimpleTreat 4.0 and compared to measured effluent concentrations. The model predicts effluent concentrations mostly within a factor of 10, using the specific WWTP parameters as well as SimpleTreat default parameters, while it systematically underestimates concentrations in secondary sludge. This may be caused by unexpected sorption, resulting from variability in WWTP operating conditions, and/or QSAR applicability domain mismatch and background concentrations prior to measurements. Moreover, variability in detection techniques and sampling methods can cause uncertainty in measured concentration levels. To find possible structural improvements, we also evaluated SimpleTreat 4.0 using several specific datasets with different degrees of uncertainty and variability. This evaluation verified that the most influencing parameters for water effluent predictions were biodegradation and the hydraulic retention time. Results showed that model performance is highly dependent on the nature and quality, i.e. degree of uncertainty, of the data. The default values for reactor settings in SimpleTreat result in realistic predictions.

摘要

本研究评估了 SimpleTreat 4.0 对废水中药物去除的预测能力。使用了来自文献中的 43 种药物的现场数据,这些药物在 51 个不同的活性污泥污水处理厂进行了测量。根据报告的进水浓度,使用 SimpleTreat 4.0 计算了出水浓度,并将其与实测的出水浓度进行了比较。该模型使用特定的污水处理厂参数和 SimpleTreat 默认参数,预测出的出水浓度大多在 10 倍以内,但它系统地低估了二级污泥中的浓度。这可能是由于污水处理厂运行条件的变化导致的意外吸附,以及/或 QSAR 适用性域不匹配和测量前的背景浓度所致。此外,检测技术和采样方法的变化也会导致实测浓度水平的不确定性。为了寻找可能的结构改进,我们还使用具有不同程度不确定性和变异性的几个特定数据集评估了 SimpleTreat 4.0。这项评估验证了对水排放预测影响最大的参数是生物降解和水力停留时间。结果表明,模型性能高度依赖于数据的性质和质量,即不确定性程度。SimpleTreat 中反应器设置的默认值可实现现实的预测。

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