3.1.5. Modal Mineralogy

A qualitative comparison between modal mineralogy calculated for the data sets from CSM and Boliden AB showed variation between the data sets (Table 2, columns "CSM" and "Boliden AB (original)"). For the major and minor ore minerals, a ~4 % higher mineral mass of pyrrhotite for CSM and half the mineral mass of chalcopyrite are notable. Other di fferences were the variations in silicates, especially chlorite and tourmaline, and a higher mass of unidentified phases for Boliden AB ("Others" 0.45 % compared to <0.01% for CSM). Also, as mentioned above, no Au- or Ag-minerals were detected for Boliden AB.

**Table 2.** Modal mineralogy based on mineral mass determined by QEMSCAN ®. Data is normalized and quoted to two decimal places only (100 ppm). The columns show the results of the analyses by CSM and for Boliden AB before and after reprocessing. For the Boliden AB data, some minerals were grouped together. The 1st update of the Boliden data includes an extension of the mineral list. The 2nd and 3rd updates include the "boundary phase processor" and a specific SIP-entry for Au. Phases with "N.A." were not included in the Boliden AB SIP and hence, not analyzed.


\* the category "Silicates" was used instead of "Biotite".

For the silicates, the variations were likely caused by differences in pixel classification, e.g., grains classified as chlorite by CSM were classified as tourmaline by Boliden AB (Figure 7d,e). This is a common issue caused by overlapping spectra of chlorite and tourmaline. To achieve good separation, calibration to a real tourmaline standard and cross-checking against real samples is required. Similar peaks are also an issue for pyrite and pyrrhotite. But neither the mineral maps nor the quantitative data suggested this to have been an issue in this study. Rather, the difference in the area analyzed was likely responsible for the variation of pyrrhotite.

#### *3.2. Results past Optimisation*

Based on the supposedly better-quality data from CSM, results from the Boliden AB analysis were reprocessed in several iterations in an attempt to achieve similar or higher quality data compared to those of CSM.

## 3.2.1. Mineral List

An attempt was made to reproduce the mineral list used at CSM (Figure 7). Ankerite and jacobsite could not be differentiated from the category "Fe-Ox/CO3" and also, gold and silver minerals remained undifferentiated. The change of the phase of "silicates" to "biotite" resulted in a loss in mineral mass. An equivalent mass was gained in the "others" category (Table 2 column "Boliden AB (1st update)"). This shows, that most pixels initially classified as "silicates" did not meet the requirements to be classified as "biotite" in the Boliden AB data. While the total mass of carbonates, oxides and phosphates was similar between the data sets (9.58% for Boliden, 8.25% for CSM), separation showed a large variation between individual phases (Table 2, column "Boliden AB (1st update)"). Regarding the Bi-minerals, separation into "Tellurobismuthite" and "Bismuth/Bismuthinite" produced similar quantitative results. However, this was somewhat deceiving due to masses only being quoted to 100 ppm because of a significant risk of misidentification of grains at or below the scan resolution. In fact, for Boliden AB, hardly any "Bismuth/Bismuthinite" was found and most Bi-pixels were attributed to "Tellurobismuthite". Subsequent evaluation by SEM-EDS showed many of these pixels to actually be native Bi rather than Bi-tellurides. But even for the CSM data, the classification was not always correct.

#### 3.2.2. Boundary Phase Processor

The Boliden AB data was reprocessed using the "boundary phase processor", which is a post-analysis processing tool that aims to counter false pixel identification caused by mixed spectra at grain boundaries and erroneous energy dispersive spectra. A spurious signal may be collected due to the electron beam being deflected from topography in the sample, e.g., holes, or due to sudden fluctuations in beam intensity. The method works by reclassifying individual pixels (to a mineral defined by the person processing the data), if the surrounding pixels are homogeneous and not of the same phase, e.g., a single pixel of chalcopyrite in a homogeneous pyrite grain. It also reclassifies pixels if they sit between two or more otherwise homogeneous phases, such as grain boundaries. The pixel is then either reclassified to the surrounding phase or to unknown. The method can be applied to individual phases. It is not possible for the method to distinguish between true and erroneous signals; therefore, there is a risk of wrongly reclassifying pixels. Thus, if and when the method is applied, it must be carefully assessed by the operator. Boliden AB applies this method frequently on a case by case basis if modification of the SIP is too time-intensive and/or yields little result. In their experience, the ratio of erroneous to true signals for such single pixels is mostly in favor of the error, hence warranting application of the "boundary phase processor" in most cases. While some errors could be fixed by improving the SIP, using the "boundary phase processor" is faster and easier.

Here, this method was applied on the chalcopyrite and trace phases. For chalcopyrite, it resulted in a drop in mineral mass from 1.58% to 0.80%, very close to the 0.72% from CSM (Table 2, column "Boliden AB (2nd + 3rd update)"). This means that about every second pixel that was originally identified as chalcopyrite was reclassified, mostly as pyrite and quartz. In the original mineral map, many pyrite grains appeared coated with a pixel-thick layer of chalcopyrite that was neither present in the mineral map of CSM nor in optical images. The chalcopyrite pixels were consequently reclassified as pyrite by the "boundary phase processor". However, many chalcopyrite-filled micro cracks within pyrite and quartz were also removed due to this method, despite them showing in the BSE and optical images (Figure 7a,b). For the trace phases, the change in bulk mineralogy was not noticeable due to most phases being <100 ppm. In the mineral map, the change was more apparent since many pixels of trace phases were reclassified to a major phase.

At CSM, issues with spurious signals were resolved through manual evaluation of the data and editing of the SIP. As a result, pyrite grains were uncoated and fine cracks filled with chalcopyrite were resolved. This shows the advantage of having an experienced operator spend time processing the data over relying on automated processing. Nevertheless, if either time or experience is lacking, the "boundary phase processor" is a helpful tool to improve the quality of analysis.
