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. 2015 Jun;22(11):8044-57.
doi: 10.1007/s11356-014-2814-y. Epub 2014 Apr 30.

Estimates of pesticide concentrations and fluxes in two rivers of an extensive French multi-agricultural watershed: application of the passive sampling strategy

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Estimates of pesticide concentrations and fluxes in two rivers of an extensive French multi-agricultural watershed: application of the passive sampling strategy

Gaëlle Poulier et al. Environ Sci Pollut Res Int. 2015 Jun.

Abstract

In this study, the passive sampling strategy was evaluated for its ability to improve water quality monitoring in terms of concentrations and frequencies of quantification of pesticides, with a focus on flux calculation. Polar Organic Chemical Integrative Samplers (POCIS) were successively exposed and renewed at three sampling sites of an extensive French multi-agricultural watershed from January to September 2012. Grab water samples were recovered every 14 days during the same period and an automated sampler collected composite water samples from April to July 2012. Thirty-nine compounds (pesticides and metabolites) were analysed. DEA, diuron and atrazine (banned in France for many years) likely arrived via groundwater whereas dimethanamid, imidacloprid and acetochlor (all still in use) were probably transported via leaching. The comparison of the three sampling strategies showed that the POCIS offers lower detection limits, resulting in the quantification of trace levels of compounds (acetochlor, diuron and desethylatrazine (DEA)) that could not be measured in grab and composite water samples. As a consequence, the frequencies of occurrence were dramatically enhanced with the POCIS compared to spot sample data. Moreover, the integration of flood events led to a better temporal representation of the fluxes when calculated with the POCIS compared to the bimonthly grab sampling strategy. We conclude that the POCIS could be an advantageous alternative to spot sampling, offering better performance in terms of quantification limits and more representative data.

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