A practical examination of the use of geostatistics in the remediation of a site with a complex metal contamination history

Targeted remediation strategies offer the potential to treat only those areas where contamination exceeds predefined threshold levels. We used geostatistical techniques to characterize spatial distribution of heavy metals across a contaminated site, with the aim of delineating the contaminants, which is essential for successful implementation of targeted remediation strategies. Samples collected from three depths, 0-20 cm, 20-40 cm and 40-60 cm at 50 sample locations, were analyzed for As, Sb, Hg, Pb, Cd and Cu contents. The geostatistical analysis of this data enabled the identification of a number of contamination hotspots and trends. The visual interpretation of the data was supported by the statistical analysis in the form of Spearman's rank correlation coefficient. Additionally, classical statistics, based on the central limit theorem, showed that, in terms of obtaining the true mean for each of the contaminants within acceptable limits of precision, the site has been more than adequately sampled. It has been demonstrated that kriging can offer the potential to map the spatial distribution of contaminants. However the possibility of an undetected hotspot remains, even when probabilistic modelling and a secondary phase of validatory sampling are employed. This together with the large number of samples required may preclude the commercial use of geostatistics in the remediation of contaminated land.