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促进水中新兴污染物自由基驱动降解的关键结构特征。

Key structural features promoting radical driven degradation of emerging contaminants in water.

机构信息

Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10000 Zagreb, Croatia.

Faculty of Chemical Engineering and Technology, University of Zagreb, Marulićev trg 19, 10000 Zagreb, Croatia.

出版信息

Environ Int. 2019 Mar;124:38-48. doi: 10.1016/j.envint.2018.12.043. Epub 2019 Jan 9.

DOI:10.1016/j.envint.2018.12.043
PMID:30639906
Abstract

Diverse contaminants of emerging concern (CECs) can be found in nowadays aquatic environment, possessing high potential to cause adverse ecological and human health effects. Due to their recalcitrance, conventional water treatment methods are shown to be inadequately effective. Thus, their upgrade by advanced oxidation processes, involving the generation of highly reactive species (HO and SO), is highly demanded. In order to assess the susceptibility of CECs by HO and SO, as well as to determine the corresponding reaction rate constants k and k, the complex experimental studies has to be maintained. The alternative is the application of modeling approaches which correlate structural characteristics with activities/properties of interest, i.e. quantitative structure activity/property relationship (QSAR/QSPR). In this study k and k of fifteen selected CECs were determined by competitive kinetics, and afterward used to elucidate key structural features promoting their degradation. In that purpose, QSPR models were constructed using multiple linear regression (MLR) combined with genetic algorithm (GA) approach. The models were submitted to the internal and external validation (using additional set of 17 CECs). Selected 3-variable models predicting k and k were characterized with high accuracy and predictivity (R = 0.876 and Q = 0.847 and R = 0.832 and Q = 0.778, respectively). Although selected models at the first sight include descriptors derived through complicated calculation procedures, their weighting schemes indicate on their relevance and transparency toward established reaction theories and differences regarding radical type.

摘要

现如今,水生环境中存在着多种多样的新兴关注污染物(CECs),它们具有很高的潜在风险,可能对生态和人类健康造成不良影响。由于它们的稳定性,传统的水处理方法效果不佳。因此,人们强烈要求通过高级氧化工艺(涉及高活性物质(HO 和 SO)的生成)对其进行升级。为了评估 CECs 对 HO 和 SO 的敏感性,并确定相应的反应速率常数 k 和 k,必须进行复杂的实验研究。另一种方法是应用建模方法,将结构特征与感兴趣的活性/性质相关联,即定量结构活性/性质关系(QSAR/QSPR)。在本研究中,通过竞争动力学确定了十五种选定 CECs 的 k 和 k 值,然后利用这些值来阐明促进其降解的关键结构特征。为此,使用多元线性回归(MLR)结合遗传算法(GA)方法构建了 QSPR 模型。将模型提交给内部和外部验证(使用另外一组 17 种 CECs)。预测 k 和 k 的选定 3 变量模型具有很高的准确性和预测能力(R=0.876 和 Q=0.847 和 R=0.832 和 Q=0.778)。尽管选定的模型乍一看包括通过复杂计算程序得出的描述符,但它们的加权方案表明它们与既定反应理论的相关性和透明度,以及与自由基类型的差异。

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