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Title: Modeling the interaction of dissolved organic matter with cations

Miscellaneous ·
OSTI ID:5296909

The last couple of decades have seen a variety of models for the binding of metals and protons by dissolved organic matter (DOM). This dissertation examined the continuing evolution of one of these models (Continuous Gaussian Distribution) (CGD), some of the underlying assumptions inherent in modeling DOM, and the incorporation of continuous distribution models into comprehensive, speciation computer programs. This thesis consisted of two distinct parts, one which deals with metal binding by DOM as it relates to the overall chemistry of rivers and ash ponds, and the other which concerns Suwannee river DOM binding of Pb. Initially, DOM was collected from the Clinch river in Tennessee and an adjacent power plant ash pond using a portable reverse osmosis unit. The concentrated DOM samples were subjected to alkalimetric and Cu(II) titrations using ionic selective electrodes to measure metal and proton complexation properties of the dissolved organic acids. The data were fit to the CGD models of Perdue and coworkers to determine the pK[sub a] distributions of major classes of acidic functional groups and to estimate the abundance and Log K distribution of metal binding sites in the DOM. Concentration based Gaussian and activity based competitive Gaussian modeling were compared. Fitting parameters from these modeling efforts were integrated into MINEQL and MINTEQA2 to examine the overall metal speciation in the river and ash pond. The other aspect of this study concerned Pb binding by Suwannee river DOM which had previously been isolated and characterized in relation to proton and Cu binding. Pb titrations were conducted at two ionic strengths, three pH's and two DOM concentrations. Fitting these data to the Competitive Gaussian model while varying parameters such as organic charge, stoichiometry and the number of binding sites helped to elucidate the effect of various solution conditions on the binding of Pb by DOM and to procure optimum fitting parameters.

Research Organization:
Georgia Inst. of Tech., Atlanta, GA (United States)
OSTI ID:
5296909
Resource Relation:
Other Information: Thesis (Ph.D.)
Country of Publication:
United States
Language:
English