DISTRIBUTION OF METALS AND METALLOIDS IN SMELTER-DERIVED PARTICULATE MATTER IN SOILS AND MINERALOGICAL INSIGHTS INTO THEIR RETENTION AND RELEASE IN A LOW-T ENVIRONMENT
Bibliographic record
Abstract
Over 10,000 tons of particulate matter (PM) has been emitted over the last 100 years as a result of mining activities in Sudbury, Ontario, Canada. Much of the PM has been deposited in the local soils, causing elevated concentrations of Cu, Ni, Zn, Se, As, and Pb. The goal of this study is to determine the distribution of metals and metalloids in PM in order to draw conclusions about their formation, their weathering, and the mobility of these elements in the local soils. The PM and associated secondary phases have been studied using optical microscopy, SEM, micro-Raman spectroscopy, and laser ablation inductively coupled plasma mass spectrometry. Spherical PM forms during the rapid cooling of hot gasses and is predominantly composed of Cu- and Ni-bearing spinel, silicate, and sulfide mineral inclusions. The collision of precursors of spherical PM with aerosols of residual matte and slag results in the formation of metal- and metalloid-rich outer rims on each sphere. These rims, as well as Fe-silicate and spinel minerals in the silicate-oxide matrix, weather to hematite during a dissolution-precipitation process. Metals and metalloids are released during this process in non-stoichiometric proportions relative to their initial concentration in the spinel, as they have different affinities to sorb on surface sites during their diffusion through the hematite precipitate. Metal-bearing sulfide inclusions alter to sulfate and occasionally into oxide minerals, which are enriched in Ni, Co, and Cu. Particulate matter composed of angular sulfide minerals and NiO particulates is often coated with Fe-Al-hydroxide and aluminosilicate minerals. The coatings contain higher trace-metal and metalloid concentrations than the underlying PM and are thus sinks for metals and metalloids released by other types of PM. The mobility of metals and metalloids in the soils decreases in the sequence Zn > Cu > Ni > Pb and is the result of differences in element adsorption affinities and dissolution rates of phases in the PM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".