Commercially available options and processes in development for sortation of automobile steel scrap were evaluated to determine if there may be a viable method to remove some of the undesirable impurities prior to feeding to an electric arc furnace. This evaluation included industry surveys of current practice and literature, patent and vendor surveys. The issues with sortation relate to the size of the material and the mode of occurrence of the impurities in the scrap. If this method for the reduction of impurities is possible, then the amount of primary iron (along with energy use) could be reduced. Two potential methods were evaluated (optical recognition - machine learning and blue laser diodes), For the treatment of molten steel containing Cu, several alternatives (chemical and metallurgical) were evaluated and two methods were selected for study Theoretical concepts and methods of steel scrap purification were investigated along with details regarding the practical applicability and energy and emissions impacts. This would allow control of alloy composition to closer limits, with the benefit of improving the properties and simultaneously reducing the need for degassing and grain refinement additives.