Nano-mineral assemblages in mercury- and silver-contaminated soils: records of sequestration, transformation, and release of mercury- and silver-bearing nanoparticles
Bibliographic record
Abstract
Mercury-bearing nano-mineral assemblages (Hg-NMAs) are chemically and mineralogically heterogeneous, micrometer-sized aggregates of nanoparticles (NPs) found in contaminated soils and sediments. Although these NMAs control sequestration and release of Hg that is a global contaminant, our understanding is limited with respect to the conditions of different types of Hg-NMAs, the diversity of its minerals, the size distribution of its NPs and whether mineral replacement and alteration reactions in these NMAs result in the release of Hg-bearing NPs. For this purpose, Hg-NMAs in four sediment samples from the Guanajuato Mining District (GMD) in Mexico, a region that was polluted by Hg and silver (Ag) due to historical mining involving Hg amalgamation, are characterized at the micro- and nanoscale. Microscale examinations with SEM show that the majority of Hg-NMAs occurs in mineral surface coatings (MSC) and fillings in fractures within quartz grains and are enriched in Hg and sulfur (S) relative to Ag, and in S and selenium (Se) relative to chloride (Cl). Examinations at the nanoscale show that Hg-NMAs contain (a) residuals of the patio process such as amalgam phases and elemental Ag; (b) associations of Hg- and Ag-sulfide NPs with pyrite and marcasite; (c) associations of Hg- and Ag-sulfide NPs with goethite and clay minerals along the rims of the MSC. The latter minerals replaced the Fe-Si-rich matrix at high-water rock ratios most likely due to an increase in porosity during flooding of the Pastita River. Consequently, the rims are depleted in Hg-Ag-sulfide NPs relative to the unaltered Fe-Si-rich matrices indicating that changes in the physiochemical conditions of soils and sediments in the GMD can result in the release of Hg-Ag-bearing NPs. In this context, this study discusses whether release and dissolution of Hg-Ag-bearing NPs contribute to the recently observed elevated gaseous elemental Hg concentrations in the soil, interstitial air and ambient air, and to the fate and effects of Hg in local aquatic environments.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| 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".