Issue 5, 2023

An electromembrane microextraction-based green method for the determination of trace copper in natural waters

Abstract

Driven by the search for an environmentally-friendly methodology, electromembrane extraction (EME) has recently emerged as a green and versatile tool for the analysis of trace pollutants in water samples, being mainly applied to the preconcentration and determination of organic compounds. Recently, EME has also shown its applicability to the analysis of inorganic species, allowing a considerable reduction in both reagent consumption and extraction times, and without loss of efficacy, in comparison with other liquid phase microextraction techniques. In this study, an EME system for trace copper analysis in natural waters has been optimised by the modified simplex method. A chemical modifier, di-2-pyridyl ketone benzoylhydrazone (dPKBH) was synthesized and dissolved in 1-nonanol, to be used as an organic phase impregnated into the pores of a polymeric hollow fibre. With only 15 min of extraction, an enrichment factor of 77.1 ± 10.8 was obtained for a wide salinity range (0–35), allowing its application in a variety of different waters, including seawater. Optimum operating conditions were a sample pH of 6.26, an electric potential of 95 V, 0.08 M nitric acid as the acceptor phase, 4.01 mM dPKBH in 1-nonanol as the organic phase and a stirring rate of 1500 rpm. A LOD of 0.004 μg L−1 was obtained, and the system was successfully applied to the analysis of several water samples containing copper at low ppb levels (tap water and river water) or even at sub-ppb levels (seawater).

Graphical abstract: An electromembrane microextraction-based green method for the determination of trace copper in natural waters

Article information

Article type
Paper
Submitted
25 Oct 2022
Accepted
15 Dec 2022
First published
15 Dec 2022

Anal. Methods, 2023,15, 618-625

An electromembrane microextraction-based green method for the determination of trace copper in natural waters

M. Silva, C. Mendiguchía and C. Moreno, Anal. Methods, 2023, 15, 618 DOI: 10.1039/D2AY01733D

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