Sarti Chiara, Falcon Lea, Cincinelli Alessandra, Martellini Tania, Chianella Iva
Department of Chemistry "Ugo Schiff", University of Florence, Via della Lastruccia 3, 50019, Sesto Fiorentino, Italy; Surface Engineering and Precision Centre, Faculty of Engineering and Applied Sciences, Cranfield University, MK43 0AL, Bedford, United Kingdom.
Surface Engineering and Precision Centre, Faculty of Engineering and Applied Sciences, Cranfield University, MK43 0AL, Bedford, United Kingdom.
Talanta. 2025 Apr 1;285:127375. doi: 10.1016/j.talanta.2024.127375. Epub 2024 Dec 12.
The presence of organic UV filters (OUVAs) has been detected worldwide in aquatic ecosystems. These pollutants, originating from various anthropogenic sources, can persist and transform within wastewater treatment plants (WWTPs), posing a potential environmental hazard. In this framework, this research presents electrochemical sensors based on molecularly imprinted polymers (MIPs) for the selective detection of Benzophenone-3 (BP-3) and Octocrylene (OC), two of the OUVA most spread in the aquatic environment, to overcome the analytical challenges related to the quantification of this class of contaminants in wastewater samples. Key parameters, including the selection of the electropolymerization conditions, the template washing, polymer surface blocking, and analyte re-binding conditions, were optimized to maximize the selectivity and sensitivity. Electrochemical detection was performed using electrochemical impedance spectroscopy (EIS) supported by an electrochemical probe. In addition, cross-reactivity tests were carried out in the presence of possible interferents, selected based on their size, chemical structure, and occurrence in wastewater samples. The sensors demonstrated significant selectivity and sensitivity for the target analytes, with detection limits of 30 nM for BP-3 and 1 nM for OC, while tests on complex wastewater samples showed recovery rates of 77 % and 101 % for BP-3 and OC, respectively. The study yielded interesting results that could lead to a specific, cost-effective approach to enable widespread monitoring and support early detection of these increasingly relevant contaminants in wastewater samples.
在全球范围内，水生生态系统中已检测到有机紫外线过滤剂（OUVAs）的存在。这些污染物源自各种人为来源，可在污水处理厂（WWTPs）中持续存在并发生转化，构成潜在的环境危害。在此框架下，本研究提出了基于分子印迹聚合物（MIPs）的电化学传感器，用于选择性检测二苯甲酮-3（BP-3）和桂皮酸盐（OC），这两种是在水环境中分布最广的OUVAs，以克服与废水样品中此类污染物定量分析相关的挑战。对包括电聚合条件选择、模板洗涤、聚合物表面封闭和分析物重新结合条件等关键参数进行了优化，以最大限度地提高选择性和灵敏度。使用电化学探针支持的电化学阻抗谱（EIS）进行电化学检测。此外，在可能的干扰物存在下进行交叉反应测试，这些干扰物是根据其大小、化学结构以及在废水样品中的出现情况选择的。该传感器对目标分析物表现出显著的选择性和灵敏度，BP-3的检测限为30 nM，OC的检测限为1 nM，而对复杂废水样品的测试表明，BP-3和OC的回收率分别为77%和101%。该研究产生了有趣的结果，可能会导致一种特定的、具有成本效益的方法，以实现对废水样品中这些日益相关的污染物的广泛监测并支持早期检测。
