Soil washing optimization by means of attributive analysis: Case study for the removal of potentially toxic elements from soil contaminated with pyrite ash

This paper describes a feasibility study of physical soil washing techniques to separate potentially toxic elements, such as As, Cu, Hg, Pb and Sb, in a brownfield affected by pyrite ash disposal. To this end, complete pedological and geochemical analyses were conducted in order to determine the properties of the soil. Afterwards exhaustive lab-scale soil washing tests were performed with the aim to concentrate most of the contaminants into a small fraction of treated soil. The procedures used included gravity separation-heavy liquid assays-, hydrocycloning and wet and dry magnetic separation. Within this context, grain-size classification proved effective only for the treatment of the sizes below 63 mu m. Better results were obtained by heavy liquid separation, which was optimal at most grain sizes, except fractions of the soil between 1000 and 2000 gm, and below 63 gm. As regards magnetic separation, dry high-intensity magnetic separation was suitable for the treatment of grain sizes above 500 gm and gave yields similar to those achieved by heavy liquid assays in most cases. The results of the experiments were compared through the novel approach of attributive analysis, and the findings indicated that the separation procedures for pollutants yielded repeatable results. Moreover, an intuitive method of evaluating the performance of the separation techniques by introducing a "success score" was developed. This procedure takes into account not only the various scenarios contemplated by legislation but also the performance of each washing method for each element. All things considered, in feasibility studies for soil washing methods and also for mineral processing purposes, both attributive analysis and the "success score" may be useful for selecting optimal operating conditions, thus facilitating the scale-up of the results. Moreover, the method presented could be used in any operating plant that aims to reduce emissions while at the same time maximizing product outputs. (C) 2016 Elsevier Ltd. All rights reserved.