Quantitative structure-property relationships for predicting sorption of pharmaceuticals to sewage sludge during waste water treatment processes

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• 作者：L. Berthod^a ; ^b ; D.C. Whitley^b ; ^{david.whitley@port.ac.uk} ; G. Roberts^a ; ¹ ; A. Sharpe^a ; ² ; R. Greenwood^c ; G.A. Mills^b
• 关键词：Pharmaceuticals ; Sewage sludge ; Sorption ; Partition coefficient ; Quantitative structure-property relationship (QSPR) ; Artificial neural networks
• 刊名：Science of The Total Environment
• 出版年：2017
• 出版时间：1 February 2017
• 年：2017
• 卷：579
• 期：Complete
• 页码：1512-1520
• 全文大小：642 K
• 卷排序：579

文摘

Understanding sorption of pharmaceuticals to sludge is important in risk assessment. Predicting sorption on molecular properties limited by heterogeneous nature of sludge Models based only on the partition coefficient gave poor predictive models. Non-linear artificial neural network models improve predictability. Descriptors that influenced sorbate-sorbent interactions were identified.