Geochemistry and mineralogy of arsenic in mine wastes and stream sediments in a historic metal mining area in the UK

- Stream sediments in a former mining area remain polluted with up to 25 g As per kg.
- The main arsenic mineral in adjacent mine wastes appears to be scorodite.
- Low solubility scorodite was inversely correlated with potentially mobile As.
- Combining mineralogical & chemical methods helps understand environmental threats.

Mining generates large amounts of waste which may contain potentially toxic elements (PTE), which, if released into the wider environment, can cause air, water and soil pollution long after mining operations have ceased. The fate and toxicological impact of PTEs are determined by their partitioning and speciation and in this study, the concentrations and mineralogy of arsenic in mine wastes and stream sediments in a former metal mining area of the UK are investigated. Pseudo-total (aqua-regia extractable) arsenic concentrations in all samples from the mining area exceeded background and guideline values by 1-5 orders of magnitude, with a maximum concentration in mine wastes of 1.8 × 105 mg kg− 1 As and concentrations in stream sediments of up to 2.5 × 104 mg kg− 1 As, raising concerns over potential environmental impacts. Mineralogical analysis of the wastes and sediments was undertaken by scanning electron microscopy (SEM) and automated SEM-EDS based quantitative evaluation (QEMSCAN®). The main arsenic mineral in the mine waste was scorodite and this was significantly correlated with pseudo-total As concentrations and significantly inversely correlated with potentially mobile arsenic, as estimated from the sum of exchangeable, reducible and oxidisable arsenic fractions obtained from a sequential extraction procedure; these findings correspond with the low solubility of scorodite in acidic mine wastes. The work presented shows that the study area remains grossly polluted by historical mining and processing and illustrates the value of combining mineralogical data with acid and sequential extractions to increase our understanding of potential environmental threats.