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Updated: Sep 19, 2025

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
Published on: September 1, 2020
Competitive transport of heavy metals in soil: Cadmium dynamics with numerical modeling
Yiren Li1, Jiawen Zhang2, Yuke Lv2
1State Key Laboratory of Soil Pollution Control and Safety, Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Engineering Technology Center for Pollution Prevention and Control of Taizhou, Taizhou University, Jiaojiang, Zhejiang Province 318000, China; Department of Environmental Systems Science, ETH Zürich, Zurich 8092, Switzerland.
Abstract:
Transport of composite heavy metals in the soil profile is a complex process that poses significant risks to groundwater and deep soil layer. This study conducts an in-depth simulation and analysis of Cd transport behavior in single and composite contamination through soil penetrate tests and leaching tests, combined with the HYDRUS and CXTFIT models. The study found that Pb significantly promoted the transport rate of Cd in the soil profile, reducing the initial breakthrough time from 12 to 5 pore volumes (PV). During leaching, the presence of Pb increased the Cd concentration in the pore water by 70.2 %, further enhancing Cd's transport potential and groundwater contamination risk. The study further validated the applicability of the HYDRUS model, finding that Pb promotes the proportion of the instantaneous equilibrium site (f) and the first-order reaction rate coefficient (α) of Cd. An increase in the instantaneous adsorption ratio of heavy metals accelerates the adsorption process from the kinetic control phase. By incorporating competitive adsorption isotherms and heavy metal speciation into the HYDRUS prediction model, the model achieved a high prediction accuracy (R2 = 0.84) for heavy metal transport pathways in polluted sites, providing a reliable tool for the long-term evolution prediction of polluted sites.
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