Predicting PbII adsorption on soils: the roles of soil organic matter, cation competition and iron (hydr)oxides
Zhenqing Shi A D , Herbert E. Allen B , Dominic M. Di Toro B , Suen-Zone Lee C and James B. Harsh A
+ Author Affiliations
- Author Affiliations
A Department of Crop and Soil Sciences, Johnson Hall 131, PO Box 646420, Washington State University, Pullman, WA 99164-6420, USA.
B Center for the Study of Metals in the Environment, Department of Civil and Environmental Engineering, 356 DuPont Hall, University of Delaware, Newark, DE 19716, USA.
C Chia Nan University of Pharmacy and Science, President Office, Number 60, Section 1, Erren Road, Rende District, Tainan City 71710, Taiwan.
D Corresponding author. Email: zhenqing.shi@wsu.edu
Environmental Chemistry 10(6) 465-474 https://doi.org/10.1071/EN13153
Submitted: 13 August 2013 Accepted: 17 October 2013 Published: 17 December 2013
Environmental context. Lead is a common and persistent soil and water contaminant. This study provides a unique set of parameters for chemical models that can be used for predicting Pb adsorption by soil. The suggested modelling approach can be used to quantitatively predict Pb retention and release in soils with changing environmental conditions.
Abstract. Lead (PbII) adsorption on 14 non-calcareous New Jersey soils was studied with a batch method. Both adsorption edge and adsorption isotherm experiments were conducted covering a wide range of soil compositions, Pb concentrations and solution pHs. Visual MINTEQ was used to calculate the Pb adsorption equilibrium by coupling the Stockholm Humic Model, the CD-MUSIC model, a diffuse layer model and a cation exchange model for Pb reactions with soil organic matter (SOM), Fe (hydr)oxides, Al hydroxides and clay minerals. For model predictions, reactive organic matter (ROM), the fraction of SOM responsible for Pb binding, and reactive Al and FeIII in soils were quantified. The models predicted Pb adsorption to soils reasonably well with varying SOM and mineral content at various pHs and Pb concentrations. For 3.0 < pH < 6.0, the log partition coefficient root mean square error was 0.34. However at higher pHs the models were less successful. Both ROM and Al competition had a significant effect on model predictions. ROM was the dominant adsorption phase at pHs between 3.0 and 5.0. For pH > 5.0, Pb adsorption to Fe (hydr)oxides became significant. The modelling approach presented in this study can be used to understand and quantitatively predict Pb adsorption on soil.
Additional keywords: lead(II), partition coefficient, reactive organic matter, Stockholm Humic Model.
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