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Electromembrane Extraction of Naphthenic Acids in Produced Water Followed by Ultra-High-Resolution Mass Spectrometry Analysis

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journal contribution
posted on 2022-07-22, 12:09 authored by Giovanna L. de Araújo, Gabriel F. dos Santos, Rafael O. Martins, Gesiane da Silva Lima, Iris Medeiros, Rogério M. de Carvalho, Rosineide C. Simas, Lívia F. Sgobbi, Andréa R. Chaves, Boniek G. Vaz
Naphthenic acids comprise one of the most toxic compounds of the produced water released from offshore oil platforms. Therefore, developing and applying faster, simpler, and more efficient analytical methods for analyzing naphthenic acids are urgently needed. Electromembrane extraction (EME) uses the electrokinetic migration of target ions through a porous membrane. Herein, the EME method was applied to extract naphthenic acids from produced water. The EME method was optimized, and the optimal conditions encompassed decanol as the organic solvent, the sample with pH 10.0, 5 min of extraction at 200 V, and the ratio 4:1 (borate buffer/matrix, v/v). Electrochemical impedance spectroscopy confirmed charged species’ migration from produced water through the EME. Subsequently, all extracts were analyzed by ultra-high-resolution mass spectrometry. The EME efficiency was assessed by comparing the extraction results to the liquid−liquid extraction (LLE) method results. Analytical results showed good linearity for both solvent and matrix curves (R2 > 0.98). Low detection limits ranged from 0.10 to 0.13 μg mL–1 and quantification limits from 0.36 to 0.45 μg mL–1. Precision and accuracy values ranged from −13.3% to 16.5%. These values fit the proposed method, demonstrating that the EME was more efficient than LLE in naphthenic acid extraction. The EME method preferably extracted aromatic compounds with double-bond equivalence from 6 to 8. The EME coupled with ultra-high-resolution mass spectrometry was demonstrated as a promising analytical approach to naphthenic acid extraction as an efficient and more environmentally friendly alternative to conventional extraction methods.

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