Bulk scanning method of a heavy metal concentration in tailings of a gold mine using SWIR hyperspectral imaging system

This work introduces a bulk data acquisition method using a hyperspectral imaging system (HIS) to measure chromium (Cr) concentration in the soil samples obtained from tailings of a gold mine considering of the spectral competition between heavy metal elements. The chemical, mineralogical, and spectroscopic analyses in a laboratory environment revealed that heavy metal elements' competitive geochemical behaviors were manifested as spectral competitions between heavy metal elements in tailings. The heavy metal elements can be classified into two groups based on their geochemical behaviors: chromium-nickel (Cr-Ni) and zinc-arsenic-cadmium-lead (ZnAs-Cd-Pb). We found an inverse relationship between the two groups in their spectral absorption depth changing patterns, possibly caused by their competition in bonding with the agent minerals. The prediction model of Cr concentrations in the tailing samples using a short-wave infrared (SWIR) HIS was developed from the sample data analysis. The imaging model of Cr concentration is statistically significant with R-2 = 0.7 and NRMSE = 11% to 12%. The future use of HIS for massive data acquisition of heavy metal concentration in a natural environment is made possible with such pilot spectroscopic analyses presented in this work.

Automated summary

This study introduces a bulk data acquisition method using a hyperspectral imaging system to measure chromium concentration in soil samples from a gold mine tailings, highlighting the competitive geochemical behaviors of heavy metal elements and developing a prediction model with statistical significance. The pilot spectroscopic analyses presented in this work show the potential for massive data acquisition of heavy metal concentration in a natural environment using HIS.