RESUMO
Here, we propose two-parameter penalized attributive analysis, PPAA-U, a novel heuristic tool for selecting the best upgrading conditions (BUCs) for soil washing. Given a multi-component feed and a specific set of operating conditions, PPAA-U generates a quality index based on how well recoveries for key components are maximized while minimizing the yield. We demonstrate, through the calculation of families of curves, that this quality index is related linearly to recovery and to the inverse of the yield, meaning that reducing yield values is more important than maximizing recovery. To evaluate our method, electrostatic separation at 12 different voltages was carried out on soil samples from an ex-industrial site in Spain. Values of recovery, yield, and grade were analyzed using basic attributive analysis and PPAA-U with and without target-to-distance correction. Both methods identified the same optimal separation voltage, and the power of PPAA-U to correct for high variation in yields and recoveries was observed as a divergence between results produced by each method at low voltages where variation in these values was greatest. PPAA-U thus offers a convenient tool for soil washing optimization, and we suggest that it could be applied successfully to other industrial processes.