**4. Discussion**

Scans by both CSM and Boliden AB covered only about 75 % of the sample due to limitations of their sample holders (Figure 4). Obtaining representative samples of the rock/ore is challenging and samples have to be selected carefully. Structures, textures and mineral distribution are often heterogeneous and some features may be observed only in a small area of a sample. Although the edges are usually of poorer polish quality, a 75% scan can result in a significant loss of information and hence, an e ffort should be made to analyze the entire sample area (or as large an area as possible), using for instance, properly designed sample holders.

For Boliden AB, the backscattered electron image of the sample area showed several fields with shifts in grey-levels likely caused by poor vacuum conditions or a fluctuating beam current. However, the shifts were not reflected in the mineral map; therefore, the X-ray yield was not significantly a ffected and/or within the tolerance of the SIP. It is possible that this artefact would have been more problematic in an MLA system, as it relies primarily on the BSE signal for particle distinction. There are a plethora of possible interactions of components within and outside the instrument that can a ffect vacuum and beam stability, such as vacuum pumps in need of repair and unexpected highs/lows in the power supply or an old filament. Although the results of this analysis were not a ffected, future complications are possible. Thus, troubleshooting to find the root of the problem is recommended, although it exceeds the scope of this paper.

Regarding the spatial resolution of the scan, CSM opted for a pixel size of 10 μm compared to 5 μm for Boliden AB. The 10 μm resolution was chosen based on the findings of unpublished work by one of the authors (G.K.R.) and a study by Boni et al. [21], which showed the di fference between a 10 μm and a 1 μm scan to be marginal from a bulk mineralogical point of view for most samples. Furthermore, this study did not show any significant di fferences in bulk mineralogy directly attributable to the di fference in resolution between Boliden AB and CSM. However, this is deceiving when it comes to the identification and quantification of trace phases. Due to accuracy issues with quantities <100 ppm, no more precise values were reported for many trace phases. In fact, two Au grains detected by Boliden AB (after re-processing the data several times) were misidentified by CSM despite a grain size at CSM scan resolution. Additionally, dependent on the Au signal threshold value in the SIP of Boliden AB, many pixels were erroneously identified as Au. However, all Au grains detected by CSM were confirmed by SEM-EDS. Furthermore, this study showed that with the right SIP, the 5 μm scan at Boliden AB was able to exclude errors and resolve many more Au grains compared to the 10 μm scan at CSM, although quantitatively, they both were below 100 ppm. This means, a scan resolution <10 μm can improve quantification of trace phases if the SIP is of su fficient quality and the data is verified by another method. In fact, for studies focused only on the quantification of Au, even higher resolutions of 1–2 μm are used [8,12,22]. However, this is not realistic with the QEMSCAN ® technology for comprehensive routine analyses of uncrushed samples in the mining industry as the runtime would drastically increase. In this study, the 5 μm scan required already more than twice the amount of time compared to the 10 μm scan. Whether the benefit of a better trace mineral quantification outweighs the downside of a longer scan time is up to the mining company to decide. There is also always the option to follow up a fieldscan with a high-resolution scan in TMS mode or a high-resolution fieldscan of smaller areas of interest.

Concerning mineralogy, the di fferences between the QEMSCAN ® analyses at Boliden AB and at CSM are apparent. Camborne School of Mines as a research institution has the ambition to achieve the highest level of detail with as little unknowns ("Others") as possible for every analysis. In this study, 23 phases were distinguished with less than 100 ppm mineral mass that was left unidentified. Most trace minerals were at or below the scan resolution in terms of grain size; however, they were often possible to separate from the surrounding phases and are marked as single pixels in the mineral map. While some single pixels were misclassified, all pixels of valuable trace minerals such as Au and Ag were confirmed by manual SEM-EDS. This was achieved by detailed work with the SIP using the SMART approach [23]. At CSM, the same SIP is used for every sample, regardless of type and origin (geology, archaeology, agriculture, forensics, etc.). However, with every analysis, the SIP is edited and adapted to account for natural compositional variations of minerals between samples. Unknown pixels are individually reviewed to try to deduct the mineral phase (or phases) responsible for the EDS signal and, if successful, a corresponding SIP-entry is added. With detailed mineralogical knowledge of a sample prior to QEMSCAN ® analysis, through thorough optical microscopy and SEM work, the

output data will contain much fewer uncertainties. For this study, previous mineralogical studies by Warlo et al. [16] were initially used to better constrain the SIP entries of some phases.

In contrast, for Boliden AB, a rough understanding of the mineralogy of a sample is often considered su fficient. Gangue phases such as silicates, carbonates and oxides have no economic value for the company and similarly, minor and trace ore minerals are often too low in abundance to be economic. Boliden AB, therefore, does not prioritize a detailed characterization and separation of these particular phases. Furthermore, due to the much higher required sample throughput compared to CSM, thorough manual editing of the SIP for every analysis is too time consuming and, therefore, economically unfeasible for Boliden AB. Instead, for each deposit or process-mineralogical type of ore, an individual SIP is developed and consequently, used for the quantitative mineral analysis of the whole deposit. The time it takes to develop a customized SIP is strongly dependent on the mineralogical complexity of the deposit. These customized SIPs are commonly based on prior analysis by optical microscopy. In this case, the SIP for the nearby Aitik Cu-Au deposit was used as a basis due to its somewhat similar mineralogy to the Liikavaara deposit and the SIP being supported by several mineralogical studies even though the two deposits are genetically di fferent. The SIP was then slightly adapted for this particular study, based on previous mineralogical studies by Warlo et al. [16]. The SIP is then typically used for every sample from the same deposit with editing focused mostly on adjusting for mineralogical variations between samples. This saves time (editing of ~14 samples per day) and commonly delivers data of su fficient quality for the mining operation. Nevertheless, the quality of analysis is dependent on how well mineralogy and chemical composition of the minerals in the sample fit with their definitions in the SIP. Major ore minerals are usually well-constrained but especially, mineralogy of gangue and minor and trace phases is not always fully studied/understood and consequently, their SIP-entries are vague or missing.

Furthermore, fine textures with phases smaller than the excitation volume of the electron beam (e.g., trace minerals) commonly produce mixed X-ray signals and thus, are not identified by conventional SIP entries. This explains the shorter mineral list of Boliden AB compared to CSM in this study and the larger variations in modal mineralogy for gangue and trace phases compared to major ore phases. It is also the reason for the amount of unidentified phases. However, although not of economic value, there is definitely a benefit in distinguishing the various gangue phases and trace ore minerals in a sample. The hardness of the gangue phases, for example, dictates crushing of the ore, sheet silicates a ffect the flotation, and some trace metals are deleterious to primary metals (main commodity). The importance of understanding the mineralogy of trace minerals and gangue minerals especially in Cu-Au ores is also highlighted by Agorhom et al. [24] in their review on trace element recovery in copper flotation. Hence, recognizing these potential problems should be of interest in a mining venture. Boliden AB showed the potential of their QEMSCAN ® system to separate between di fferent gangue phases and minor ore minerals by expanding the mineral list to match CSM. However, it also showcased their limitations caused by a less-developed SIP. Ankerite and jacobsite, for example, could not be di fferentiated from "Fe-Ox/CO3" since no SIP-entries existed for these phases and no reference material was available to create new entries. To compensate for this less comprehensive SIP compared to CSM and its inability to handle mixed signals and also to deal with signal errors caused by a deflected beam, Boliden AB often applies the "boundary phase processor". The results showed that it helped to increase similarity in the bulk mineralogy for chalcopyrite between Boliden AB and CSM and to remove falsely classified rims of chalcopyrite around pyrite grains, but at the expense of also removing previously resolved micro-cracks of chalcopyrite. Hence, a comprehensive SIP is a key requirement to high quality and meaningful data. This is, however, not limited to the QEMSCAN ® system. Although the means of mineral identification may di ffer between ASEM systems, all rely on a comparison of the recorded signal with a database for classification. If minerals are defined by grey-scale values, X-ray intensities, or stoichiometry is marginal. In fact, a study by Kern et al. [25], using the MLA system showed improvements in calculating Sn deportment in a skarn deposit by including mixed phases in their mineral reference list in order to resolve mixed spectra at grain boundaries rather than relying on so-called touchups (similar to a "boundary phase processor").

Generally, the "scientific" and the "industrial" approach by CSM and Boliden AB, respectively, are both justified for their respective purpose. However, with the rising economic importance of many trace metals and their implications on ore processing and the environment, control over their occurrence and distribution should be of interest to the mining industry and consequently, aimed for with the use of some advanced automated quantitative mineralogical type of analysis. This study explored the potential of routinely identifying economic trace minerals in rocks prior to processing with industrial QEMSCAN ® settings. It was shown that by including single-element SIP-entries as filters at the top of the SIP detection, at best quantification of trace minerals is indeed possible, albeit without being able to distinguish between minerals of similar element composition (e.g., native Au and electrum). One challenge is erroneous signals that cause the misidentification of pixels. While for major ore minerals, Boliden AB utilizes the "boundary phase processor" to correct for these errors, it cannot be applied to trace minerals as they are themselves adversely a ffected by this method. Instead, a threshold value for the X-ray signal intensity of the trace metal mineral must be added to the single-element SIP-entry. The optimal threshold value to exclude all erroneous signals while including as many true signals as possible may di ffer between trace metals. To determine the optimal threshold value, QEMSCAN ® data has to be reviewed by other analytical methods, e.g., SEM-EDS to separate true from erroneous pixels. It is not plausible to fully implement this in an industrial routine. However, in this study, even with a threshold value 60% higher than the ideal value (40% compared to 25%), around half of the Au-pixels were captured (20 of 39 pixels). Thus, implementing SIP-entries with conservative threshold values for all economic trace metals in a deposit would already be beneficial with a minimum amount of work. While this, without follow-up analysis, will not provide reliable quantitative mineralogical information and data on grain size and shape, it should provide a basic overview of trace mineral association and distribution and allow for targeted follow-up studies.
