Abstract
A robust and efficient extraction method was developed to detect a broad range of pollutants of emerging interest in three freshwater invasive species: American red crab (Prokambarus clarkii), Asian clam (Corbicula fluminea), and pumpkinseed fish (Lepomis gibbosus). One native species, “petxinot” clam (Anodonta cygnea), was also evaluated. Invasive species are often more resistant to contamination and could be used in biomonitoring studies to assess the effect of contaminants of emerging concern on aquatic ecosystems while preserving potentially threatened native species. So far, most extraction methods developed for this purpose have focused on analyzing fish and generally focus on a limited number of compounds, especially analyzing compounds from the same family. In this sense, we set out to optimize a method that would allow the simultaneous extraction of 87 PhACs, 11 flame retardants, 21 per- and poly-fluoroalkyl substances, and 54 pesticides. The optimized method is based on ultrasound-assisted solvent extraction. Two tests were performed during method development, one to choose the extraction solvent with the best recovery efficiencies and one to select the best clean-up. The analysis was performed by high-performance liquid chromatography coupled to high-resolution mass spectrometry. The method obtained recoveries between 40 and 120% and relative standard deviations of less than 25% for 85% of the analytes in the four validated matrices. Limits of quantification between 0.01 ng g−1 and 22 ng g−1 were obtained. Application of the method on real samples from the Albufera Natural Park of Valencia (Spain) confirmed the presence of contaminants of emerging concern in all samples, such as acetaminophen, hydrochlorothiazide, tramadol, PFOS, carbendazim, and fenthion. PFAS were the group of compounds with the highest mean concentrations. C. fluminea was the species with the highest detection frequency, and P. clarkii had the highest average concentrations, so its use is prioritized for biomonitoring studies.Graphical abstract
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