The black rock coatings in Rouyn-Noranda, Québec: fingerprints of historical smelter emissions and the local ore
Bibliographic record
Abstract
Smelting of base metal sulfide rich ore in Rouyn-Noranda, Québec, has led to the formation of black rock coatings on exposed rocks to a maximum distance of 6 km from the smelter centre. This study has shown that these coatings are excellent mineralogical and chemical fingerprints of smelter emissions, ore types, and elemental partitioning into mineral phases. The black coatings are composed of a silica-rich matrix that formed due to the intense chemical weathering of exposed silicate rocks interacting with acidic meteoric waters. They contain metal sulfate rich layers along the atmosphere-coating interface (ACI) and rock-coating interface (RCI) formed by the in situ dissolution and precipitation of metal(loid)-bearing phases. Entombed within the silica matrix are spherical particulates and particles composed of Cu- and Zn-bearing Fe oxides (e.g., spinels), Fe oxides (e.g., hematite), Pb silicates (e.g., alamosite), sulfates (anglesite (PbSO4) and minerals of the jarosite group), amphiboles, pyroxenes, micas, Na feldspar, and clinochlore. Concentrations of elements are low in proximity to the smelter but drastically increase ∼2 km from the stack, most likely the result of a shadow effect of the smelter. This shadow effect is more pronounced if an element is highly compatible with minerals of the jarosite and spinel groups; it is called the smelter-compatibility effect. Elements displaying a high smelter-compatibility effect are Ag, Cu, Se, and As, whereas elements such as Hg, which is incompatible with the jarosite and spinel groups, show a low smelter-compatibility effect. High δ34S (5.5‰) values in proximity to the smelter and their decrease with distance is the result of mixing processes between primary and secondary sulfates in the atmosphere. The relative enrichments of metal(loid)s in coatings at Rouyn-Noranda and Sudbury, Ontario, when normalised to the MUd standard from Queensland, Australia, (MUQ) reflect the composition of the smelter emissions, ore, and lithologies. Black rock coatings of the Rouyn-Noranda and Sudbury study areas are enriched, for example, in Pb and Fe, respectively, reflecting higher abundances of galena and Fe-bearing minerals in the respective ore, emissions, and rocks in the region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".