QUANTIFYING ENVIRONMENTAL SIGNATURE OF NI-CU +PGE MINERAL DEPOSITS AND MINES

Magmatic Ni-Cu deposits are critical resources foundational to the green infrastructure transition, however mine permitting requires large capital investments. A primary expenditure is meeting environmental review criteria and, more specifically, determining how best to manage mined materials to mitigate environmental impact. Current industry standard best practice includes the development of forward-looking hydrogeochemical models aimed at predicting potential impacts from a proposed project. Hydrogeochemical model construction and parameterization requires up-scaling from bench testing of site-specific materials, takes years and millions of dollars to complete, and ultimately requires buy-in from regulating government agencies.

Material characterization at proposed mine sites typically includes mineralogical characterization as well as static and kinetic tests, including leaching studies. The geochemical source terms used in hydrogeochemical models are derived from relatively small amounts of rock (commonly 1-10 kilograms) leached using standardized methods (e.g. humidity cell tests). Results are “scaled up” to account for the significant differences between laboratory- and operational-scale processes, which are many orders of magnitude larger. Scaling up is complex, non-linear, and a source of uncertainty in predictive forecasts.

While every deposit (and future mine) requires unique site-specific consideration, the similarities in mineral assemblages between host lithologies provide an opportunity to develop a general framework by which to forecast the environmental geochemistry of magmatic Ni-Cu PGE mines. We looked at operational water quality data from 10 global Ni-Cu mines - located in generally similar climatic regions - to evaluate trends in environmental signatures and identify characteristic geochemical controls (i.e. sorption and secondary mineral formation); results may be used to parameterize and/or contextualize predictive water quality modeling efforts at proposed Ni-Cu mines. Quantifying distributions of the specific set of analytes that may be elevated in contact water from Ni-Cu mines can assist mine planners to anticipate these constituents of concern and plan for potential mitigation earlier in the process.