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Automated Scanning Electron Microscopy (ASEM) systems are applied in the mining industry to quantify the mineralogy of the ore feed and products. With society pushing towards sustainable mining, this quantification should be comprehensive and include trace minerals since they are often either deleterious or potential by-products. Systems like QEMSCAN® offer a mode for trace mineral analysis (TMS mode); However, it is unsuitable when all phases require analysis. Here, we investigate the potential of detecting micron-sized trace minerals in fieldscan mode using the QEMSCAN® system with analytical settings in line with the mining industry. For quality comparison, analysis was performed at a mining company and a research institution. This novel approach was done in full collaboration with both parties. Results show that the resolution of trace minerals at or below the scan resolution is difficult and not always reliable due to mixed X-ray signals. However, by modification of the species identification protocol (SIP), quantification is achievable, although verification by SEM-EDS is recommended. As an add-on to routine quantitative analysis focused on major ore minerals, this method can produce quantitative data and information on mineral association for trace minerals of precious and critical metals which may be potential by-products in a mining operation.

Purpose The methods for assessing the impact of using abiotic resources in life cycle assessment (LCA) have always been heavily debated. One of the main reasons for this is the lack of a common understanding of the problem related to resource use. This article reports the results of an effort to reach such common understanding between different stakeholder groups and the LCA community. For this, a top-down approach was applied. Methods To guide the process, a four-level top-down framework was used to (1) demarcate the problem that needs to be assessed, (2) translate this into a modeling concept, (3) derive mathematical equations and fill these with data necessary to calculate the characterization factors, and (4) align the system boundaries and assumptions that are made in the life cycle impact assessment (LCIA) model and the life cycle inventory (LCI) model. Results We started from the following definition of the problem of using resources: the decrease of accessibility on a global level of primary and/or secondary elements over the very long term or short term due to the net result of compromising actions. The system model distinguishes accessible and inaccessible stocks in both the environment and the technosphere. Human actions can compromise the accessible stock through environmental dissipation, technosphere hibernation, and occupation in use or through exploration. As a basis for impact assessment, we propose two parameters: the global change in accessible stock as a net result of the compromising actions and the global amount of the accessible stock. We propose three impact categories for the use of elements: environmental dissipation, technosphere hibernation, and occupation in use, with associated characterization equations for two different time horizons. Finally, preliminary characterization factors are derived and applied in a simple illustrative case study for environmental dissipation. Conclusions Due to data constraints, at this moment, only characterization factors for “dissipation to the environment” over a very-long-term time horizon could be elaborated. The case study shows that the calculation of impact scores might be hampered by insufficient LCI data. Most presently available LCI databases are far from complete in registering the flows necessary to assess the impacts on the accessibility of elements. While applying the framework, various choices are made that could plausibly be made differently. We invite our peers to also use this top-down framework when challenging our choices and elaborate that into a consistent set of choices and assumptions when developing LCIA methods.