Occurrence and risk assessment of pesticides and pharmaceuticals in viticulture impacted watersheds from Northwest Spain
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Elsevier
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An automated analytical methodology was developed, validated and applied to monitor 73 organic pollutants (pesticides and pharmaceuticals) in surface and groundwater samples obtained in watersheds from an intensive viticulture, rural region, in the Northwest of Spain. Filtered samples were concentrated using a reusable solid-phase extraction sorbent, on-line combined with liquid chromatography tandem mass spectrometry (LC-MS/MS). The analytical procedure achieved limits of quantification between 1 ng L−1 and 10 ng L−1, with a throughput of 2 samples hour−1, providing accurate recoveries for more than 90% of the 73 selected compounds, using calibration solutions prepared in ultrapure water (in presence of methanol and formic acid) as neat solvent. The distribution and the concentrations of pesticides in small streams impacted by discharges of treated municipal wastewaters were different in rural and residential areas. On the other hand, pharmaceuticals showed a similar distribution in both streams. In surface waters from viticulture impacted watersheds, with a limited influence of municipal wastewaters, pulses of pesticides were noticed, with values above 100 ng L−1 for several fungicides. Cardiovascular pharmaceuticals, psychiatric drugs and/or their transformation products were also ubiquitous in these samples, with low, but relatively stable concentrations among sampling campaigns. Within the suite of investigated compounds, maximum pesticide residues remained below their predicted-non effect concentration (PNEC) in all samples. On the other hand, the environmental concentrations of the cardiovascular drug olmesartan stayed systematically above its PNEC in fresh water samples
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Chemosphere, Volume 341, 2023, 140098
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https://doi.org/10.1016/j.chemosphere.2023.140098Sponsors
Economic support from projects TED2021-129962B-C42, funded by the Spanish Ministry of Science and Innovation, through the UE Next Generation program; and ED431C2021/06, from Xunta de Galicia, co-financed the EU FEDER program, is acknowledged. R. Cela thanks funds received from Galician Innovation Agency, Xunta de Galicia, through project 001_IN853D-2022. We thank Agilent Technologies for giving access to the LC-MS/MS system employed in this study
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© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/bync/4.0/)
Atribución-NoComercial 4.0 Internacional
Atribución-NoComercial 4.0 Internacional







