Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/3195
Título: Electrochemical methodology to study labile trace metal/natural organic matter complexation at low concentration levels in natural waters
Autor: Domingos, R. F.
Benedetti, M. F.
Croué, J. P.
Pinheiro, J. P.
Palavras-chave: Trace metal speciation
NOM
Complex-diffusion coefficients
Modeling
Stripping chronopotentiometry
Lability
Data: 2004
Editora: Elsevier Masson
Citação: Domingos, R. F.; Benedetti, M. F.; Croué, J. P.; Pinheiro, J. P. Electrochemical methodology to study labile trace metal/natural organic matter complexation at low concentration levels in natural waters, Analytica Chimica Acta, 521, 1, 77-86, 2004.
Resumo: A new electrochemical methodology to study labile trace metal/natural organic matter complexation at low concentration levels in natural waters is presented. This methodology consists of three steps: (i) an estimation of the complex diffusion coefficient (DML), (ii) determination at low pH of the total metal concentration initially present in the sample, (iii) a metal titration at the desired pH. The free and bound metal concentrations are determined for each point of the titration and modeled with the non-ideal competitive adsorption (NICA-Donnan) model in order to obtain the binding parameters. In this methodology, it is recommended to determine the hydrodynamic transport parameter, α, for each set of hydrodynamic conditions used in the voltammetric measurements. The methodology was tested using two fractions of natural organic matter (NOM) isolated from the Loire river, namely the hydrophobic organic matter (HPO) and the transphilic organic matter (TPI), and a well characterized fulvic acid (Laurentian fulvic acid, LFA). The complex diffusion coefficients obtained at pH 5 were 0.4 ± 0.2 for Pb and Cu/HPO, 1.8 ± 0.2 for Pb/TPI and (0.612 ± 0.009) × 10−10 m2 s−1 for Pb/LFA. NICA-Donnan parameters for lead binding were obtained for the HPO and TPI fractions. The new lead/LFA results were successfully predicted using parameters derived in our previous work.
Peer review: yes
URI: http://hdl.handle.net/10400.1/3195
DOI: http://dx.doi.org/10.1016/j.aca.2004.05.027
ISSN: 0003-2670
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