Mining Residues Characterization and Sentinel-2A Mapping for the Valorization and Efficient Resource Use by Multidisciplinary Strategy

Abstract

Raw materials are essential for all sectors of the economy as well as for all innovative technologies. Currently, industry is largely dependent on imports and consumption of these materials, and in the future, following the global energy transition, this trend will drastically increase. For this reason, it is necessary to develop new strategies to meet the supply–demand of raw materials by strategic sectors and technologies. To this end, mining residues are turning into viable raw materials sources as they represent reliable access to valuable resource supply. This work aims to validate a methodology providing more in-depth quali-quantitative information about 100 samples of mining residues collected in the Joda West mine (India) by multidisciplinary strategy in order to valorize and promote efficient resource use. In this paper, physicochemical and mineralogical characterization and hyperspectral signatures have been integrated with satellite Sentinel-2A data. In particular, the X-ray powder diffraction (XRPD), X-ray fluorescence (XRF), and scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS) analyses indicated the presence of mining residues samples rich in raw materials that were possible to spectrally distinguish in order to use them as input for the object-oriented classification of a satellite image. The satellite resulting map highlighted four different classes of mining residues with mean concentrations of around 36% for hematite, 23.5% for quartz, 9% for kaolinite and 5% for pyrolusite. These results represent the possibility of transforming an environmental problem (mining residues) into a resource potentially exploitable by industries knowing their composition and position in the study area. Moreover, by doing so, it will be possible to ensure sustainable consumption of the raw materials and to build resilient economies and societies, minimizing environmental degradation.

Keywords

• raw materials supply
• remote sensing classification
• circular economy