A study on antimony migration in soils using an artificial neural network model and a convection-dispersion diffusion model

Zaijin Sun, Yuxian Shangguan, Yuan Wei, Benying Su, Changzhi Zhou and Hong Hou

Ecological Modelling, 2018, vol. 389, issue C, 1-10

Abstract: We conducted a small soil column penetration test and lysimeter experiment in four soils (Isohumosol, Ferrosol, Primosol, and Sandy soil), to generate a migration model for antimony (Sb) in soil based on the convection-diffusion equation. Variation of the Sb concentration was also simulated by the Artificial neural networks model (ANN) model. The convection-dispersion model will provide a reference for the transfer of Sb in the environment. The results agreed with the laboratory measurements with an R2 of 0.79–0.98 in the Isohumosol, Ferrosol, and Primosol. It was found that the convection-dispersion model could be used to explain the migration of Sb in soil. The areas of high potential ecological risk for the Ferrosol, Isohumosol, and Primosol soils were at the soil surface, and there was a low to moderate potential ecological risk for the deep soil profile. Artificial neural network model fitting results showed that Sb migration was rapid in Sandy soil because these soils have a weak Sb-adsorption capacity. The Sb concentration in the surface soil was much higher than at other soil depths. Little variation was observed in the Sandy soil and Isohumosol, indicating a weak Sb-adsorption capacity for these soils. The Sb migration model will help us to describe and predict Sb pollution in the soil environment, providing the basis for managing Sb-contaminated soil.

Keywords: Heavy metals; Migration and transformation; Prediction; Convection-dispersion model (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:389:y:2018:i:c:p:1-10

DOI: 10.1016/j.ecolmodel.2018.09.025

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