Published in

CSIRO Publishing, Environmental Chemistry, 2(11), p. 137, 2014

DOI: 10.1071/en13154

Links

Tools

Export citation

Search in Google Scholar

Lead electrochemical speciation analysis in seawater media by using AGNES and SSCP techniques

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Environmental context Metal contamination of seawater can present severe environmental problems owing to the high toxicity of metals and their persistence in the environment. This study explores the possibility of analysing lead in seawater media using two recently developed electrochemical methods. The methods are shown to be very useful tools to monitor the behaviour and fate of lead and other metals in seawater. Abstract The speciation of PbII in synthetic and real seawater is studied by absence of gradients and Nernstian equilibrium stripping (AGNES) and stripping chronopotentiometry at scanned deposition potential (SSCP). The usefulness of the combination of both techniques in the same electrochemical cell for trace metal speciation analysis is assessed at different pH values (2.7, 5.0, 6.0, 7.0 and 8.6). The AGNES (free metal ion concentrations) and SSCP (stability constants) results for synthetic seawater agree reasonably with each other and with the theoretical predictions of the software Visual MINTEQ 3.0. This is also true for real seawater media below pH 7.0. Because of the influence of natural organic matter (2.01mgL–1 total organic carbon) in the real seawater at pH 7.0 and 8.6 the SSCP signal showed that the PbII complexes became less labile and were formed by chemically heterogeneous ligands. At these pH values, free metal concentrations determined by AGNES agreed with concentrations predicted by Visual MINTEQ using a generic fulvic acid concentration.