Geochemical indices and regression tree models for estimation of ambient background concentrations of copper, chromium, nickel and zinc in soil

Mikkonen, H, van de Graaff, R, Clarke, B, Dasika, R, Wallis, C and Reichman, S 2018, 'Geochemical indices and regression tree models for estimation of ambient background concentrations of copper, chromium, nickel and zinc in soil', Chemosphere, vol. 210, pp. 193-203.


Document type: Journal Article
Collection: Journal Articles

Title Geochemical indices and regression tree models for estimation of ambient background concentrations of copper, chromium, nickel and zinc in soil
Author(s) Mikkonen, H
van de Graaff, R
Clarke, B
Dasika, R
Wallis, C
Reichman, S
Year 2018
Journal name Chemosphere
Volume number 210
Start page 193
End page 203
Total pages 11
Publisher Pergamon Press
Abstract Geochemical ratios between elements of environmental concern and Fe have been recommended for estimation of "background" concentrations of Cr, Cu, Ni and Zn in soil. However, little research has occurred to assess the consistency of geochemical ratios across soils developed in different environments. Broad application of generic geochemical ratios could result in under or over estimation of anthropogenic impacts to soil and subsequent inaccurate assessment of risk to the environment. A soil survey was undertaken in Victoria, Australia, including collection of samples (n = 622) from surface (0-0.1 m below ground level) and sub-surface (0.3-0.6 m below ground level) soils, overlying Tertiary-Quaternary basalt, Tertiary sediments and Silurian siltstones and sandstones. Samples were analyzed for metals and soil physical and chemical properties (particle size, cation exchange capacity, organic matter and pH). Geochemical correlations between elements in soils from different parent materials and environments were compared against geochemical relationships reported in Australia and internationally. Ratios of Cr and Fe were relatively consistent across parent materials, and comparable to published models for estimation of background Cr. Conversely, ratios between Cu, Ni, and Zn with Fe, were variable between soils developed in different weathering environments and/or soil depths. Alternative regression equations and rule based regression tree models were developed as an improved means for prediction of ambient background Cu, Ni and Zn concentrations in soil. Ambient background concentrations of Ni and Cr were predictable across parent materials and depths, allowing these models to be extended to soils across Australia and potentially internationally.
Subject Environmental Science and Management not elsewhere classified
Keyword(s) Australia
Background
Correlation
Geochemical indices
Model
Prediction
DOI - identifier 10.1016/j.chemosphere.2018.06.138
Copyright notice © 2018 Elsevier Ltd. All rights reserved.
ISSN 0045-6535
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