Return to search

Surface Complexation Modelling of the Adsorption of Cd(II), Cu(II), and Ni(II) to the Roots of Triticum turgidum

The goal of this study was to characterize the binding sites on the surface of wheat roots, Triticum turgidum, involved in the adsorption of protons and metals, and quantify the thermodynamic constants needed for a surface complexation model to predict metal binding.
The adsorption of protons, Cd(II), Cu(II), and Ni(II) to the root surface as a function of pH and ionic strength in single metal exposure scenarios was quantitatively described using potentiometric titrations, batch metal adsorption experiments, and the least squares fitting program FITEQL. Model predictions from single metal exposures were compared to measured metal adsorption concentrations when roots were exposed to binary and ternary combinations of the metals.
Proton dissociation was a function of three discrete monoprotic acid sites on the root surface with log proton dissociation constants of -4.50, -6.23, and -7.37 respectively, upon which varied ionic strength had no effect. The total proton binding capacities for the three sites were 2.58 x 10-4, 1.29 x 10-4, and 2.58 x 10-4 M, respectively. Metal complexation was best described by a two-site model having conditional stability constant log values of 3.04 and 3.30 for Cd(II), 3.21 and 3.25 for Cu(II), and 2.83 and 2.84 for Ni(II) at ionic strength 0.01M. At ionic strength 0.1 M the conditional stability constants log values were 2.37 and 3.36 for Cd(II), 3.11 and 2.56 for Cu(II), and 2.18 and 3.00 for Ni(II). When roots were exposed to binary or ternary mixtures of the metals, the two monoprotic acid single metal model did not provide ideal fits to the data indicating that adsorption in a metal mixture scenario cannot be considered additive and is dependent on the combination of metals present in the exposure environment.
The experimentally determined proton dissociation constants and metal stability constants could be used in commercial geochemical speciation programs such as Visual MINTEQ to predict
metal adsorption to plants. / Natural Sciences and Engineering Research Council of Canada, The Mining Association of Canada, Ontario Power Generation, Environment Canada.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OGU.10214/5315
Date14 January 2013
CreatorsBoyle, David
ContributorsHale, Beverley
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeThesis

Page generated in 0.0021 seconds