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基于纯有机和矿物成分的 K 编制定量评估土壤中氟喹诺酮类抗生素的吸附。

Assessing sorption of fluoroquinolone antibiotics in soils from a K compilation based on pure organic and mineral components.

机构信息

Department of Geosciences, University of Tübingen, Schnarrenbergstraße 94-96, Tübingen 72076, Germany; Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, Barcelona 08028, Spain.

Department of Chemical Engineering and Analytical Chemistry, University of Barcelona, Martí i Franquès 1-11, Barcelona 08028, Spain; Institut de Recerca de l'Aigua (IdRA), Universitat de Barcelona, Martí i Franquès 1-11, Barcelona 08028, Spain.

出版信息

Ecotoxicol Environ Saf. 2024 Jul 15;280:116535. doi: 10.1016/j.ecoenv.2024.116535. Epub 2024 Jun 12.

Abstract

The presence of fluoroquinolone (FQ) antibiotics in soils may cause a threat to human health due to overexposure and the generation of antibiotic resistance genes. Understanding their sorption behavior in soils is important to predict subsequent FQ (bio) availability. Here, FQ sorption in pure soil organic (i.e., humic substances) and mineral (i.e., metal oxides; phyllosilicates) components is evaluated through a solid-liquid distribution coefficient (K (FQ)) dataset consisting of 243 entries originated from 80 different studies, to elucidate their respective contribution to the overall K (FQ) in bulk soils. First, different factors affecting FQ sorption and desorption in each of these soil phases are critically discussed. The strong role of pH in K (FQ), due to the simultaneous effect on both FQ speciation and surface charge changes, encouraged the derivation of normalized sorption coefficients for the cationic, zwitterionic and anionic FQ species in humic substances and in different phyllosilicates. K (FQ) in metal oxides revealed a key role of metal nature and material specific surface area due to complexation sorption mechanisms at neutral pH. Cumulative distribution functions (CDF) were applied to each dataset to establish a sorption affinity range for each phase and to derive best estimate K (FQ) values for those materials where normalized sorption coefficients to FQ species were unavailable. The data analysis conducted in the different soil phases set the basis for a K (FQ) prediction model, which combined the respective sorption affinity of each phase for FQ and phase abundance in soil to estimate K (FQ) in bulk soils. The model was subsequently validated with sorption data in well characterized soils compiled from the literature.

摘要

氟喹诺酮(FQ)抗生素在土壤中的存在可能会因过度暴露和抗生素耐药基因的产生而对人类健康造成威胁。了解它们在土壤中的吸附行为对于预测随后的 FQ(生物)可用性很重要。在这里,通过一个由 243 个条目组成的固液分配系数(K(FQ))数据集评估了 FQ 在纯土壤有机(即腐殖质)和矿物(即金属氧化物;层状硅酸盐)组分中的吸附,该数据集来自 80 项不同的研究,以阐明它们各自对总体 K(FQ)在土壤中的贡献。首先,我们批判性地讨论了影响这些土壤相中的 FQ 吸附和解吸的不同因素。由于 pH 同时影响 FQ 的形态和表面电荷变化,因此 pH 对 K(FQ)的强烈影响促使我们推导出了腐殖质和不同层状硅酸盐中阳离子、两性离子和阴离子 FQ 物种的归一化吸附系数。中性 pH 下由于配合吸附机制,金属氧化物中的 K(FQ)揭示了金属性质和材料比表面积的关键作用。累积分布函数(CDF)应用于每个数据集,以建立每个相的吸附亲和力范围,并为那些没有 FQ 物种归一化吸附系数的材料推导出最佳估计 K(FQ)值。在不同土壤相中进行的数据分析为 K(FQ)预测模型奠定了基础,该模型结合了各相对 FQ 的各自吸附亲和力和土壤中各相的丰度来估计土壤总体中的 K(FQ)。随后,该模型使用文献中综合的特征化土壤中的吸附数据进行了验证。

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