The prediction of aquatic sediment‐associated trace element concentrations using selected geochemical factors

Abstract

Abstract Multiple linear regression models calculated from readily obtainable chemical and physical parameters can explain a high percentage (70 per cent or greater) of observed sediment‐trace element variance for Cu, Zn, Pb, Cr, Ni, Co, As, Sb, Se, and Hg in a widely divergent suite of 61 sediment samples. The independent variables used in the models may be single parameters, principal component scores, or principal component scores combined with their cross‐products. The most useful type of variable must be determined on a case‐by‐case basis. The independent variables (geochemical parameters) incorporated in the models calculated during this study probably are applicable to many aquatic sediments; albeit, use of a larger data set (>61) could alter the magnitude of the calculated coefficients. The geochemical parameters included in the models were of a physical (e.g. grain size, surface area) and a chemical (e.g. organic matter, amorphous iron oxides) nature. Comparison between actual and predicted trace element concentrations obtained from the models may provide a means of defining ‘average’ sediment‐trace element concentrations. In this context, the models may also help identify either naturally or anthropogenically impacted sites for additional study.