Soil Factors Affecting Heavy Metal Solubility in Some New Zealand Soils

• Published in: Water, air, and soil pollution Vol. 175; no. 1-4; pp. 3 - 14
• Main Authors: Gray, C.W, Mclaren, R.G
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer 01-09-2006; Springer Nature B.V
• Subjects: adsorption; aluminum oxide; Applied sciences; Biological and physicochemical properties of pollutants. Interaction in the soil; Cadmium; Carbon; Chromium; Contamination; Copper; Earth sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Environmental monitoring; equations; Exact sciences and technology; Heavy metal content; Heavy metals; iron oxides; Lead; mathematical models; Metal concentrations; polluted soils; Pollution; Pollution, environment geology; prediction; Soil and sediments pollution; Soil contamination; Soil environment; Soil pH; Soil pollution; Soil properties; Soil quality; soil solution; water solubility; New Zealand; Oceania; Pollutant behavior; Linear regression; Solubility; Property of soil; Competitive reaction; Environmental factor; total carbon; Forecast model; Soil pollution; Multiple regression; Heavy metal; Adsorption; soil oxide; Water solubility; pH; Semiempirical method
• ISSN: 0049-6979; 1573-2932
• DOI: 10.1007/s11270-005-9045-2

Heavy metal contamination of soils is usually quantified and guidelines set solely on the basis of total heavy metal content. However, it is recognised that water soluble heavy metal concentrations may provide a better indication of the potential risk that heavy metals may pose to the soil environment. The aim of this study was to use a semi-empirical model based on the competitive adsorption of metal and H super(+) ions [dependent on solution pH, total metal content, total carbon content and soil oxide content] to predict water soluble Cu, Cr, Cd, Pb, Ni and Zn concentrations in a range of field contaminated soils. The results of multiple linear regressions showed that basic soil properties could predict 85, 72, 66, 78, 50 and 75% of the variation in soluble Ni, Cu, Cr, Pb, Cd and Zn concentrations respectively. Water soluble metal concentrations were best predicted using empirical linear regressions which included total metal content, while the importance of other soil properties such as soil pH, total carbon and oxalate extractable Fe and Al oxides varied between metals. The models have the potential to provide valuable information on metal availability in contaminated soils and offer an indication of the potential risk a metal may pose to a given soil environment, along with providing a basis for developing soil quality guidelines for the prevention, investigation and clean-up of soil metal contamination.