Metal measurement in aquatic environments by passive sampling methods: Lessons learning from an in situ intercomparison exercise
2016
Dabrin, A. | Ghestem, Jean Philippe | Uher, E. | González, J. | Allan, I. J. | Schintu, M. | Montero, N. | Balaam, J. | Peinerud, E. | Miege, Cecile | Coquery, Marina | Milieux aquatiques, écologie et pollutions (UR MALY) ; Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA) | Bureau de Recherches Géologiques et Minières (BRGM) (BRGM) | Hydrosystèmes et Bioprocédés (UR HBAN) ; Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA) | Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER) | School of Earth, Atmospheric and Environmental Sciences [Manchester] (SEAES) ; University of Manchester [Manchester] | Norwegian Institute for Water Research (NIVA) | Università degli Studi di Cagliari = University of Cagliari (UniCa) | AZTI - Tecnalia | Centre for Environment, Fisheries and Aquaculture Science [Lowestoft] (CEFAS) | ALS Scandinavia
[Departement_IRSTEA]Eaux [TR1_IRSTEA]BELCA
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Afficher plus [+] Moins [-]anglais. Passive sampling devices (PS) are widely used for pollutant monitoring in water, but estimation of measurement uncertainties by PS has seldom been undertaken. The aim of this work was to identify key parameters governing PS measurements of metals and their dispersion. We report the results of an in situ intercomparison exercise on diffusive gradient in thin films (DGT) in surface waters. Interlaboratory uncertainties of time-weighted average (TWA) concentrations were satisfactory (from 28% to 112%) given the number of participating laboratories (10) and ultra-trace metal concentrations involved. Data dispersion of TWA concentrations was mainly explained by uncertainties generated during DGT handling and analytical procedure steps. We highlight that DGT handling is critical for metals such as Cd, Cr and Zn, implying that DGT assembly/dismantling should be performed in very clean conditions. Using a unique dataset, we demonstrated that DGT markedly lowered the LOQ in comparison to spot sampling and stressed the need for accurate data calculation.
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