Airborne dust particles originated from sand and gravel quarries: Mineralogical, geochemical, and size distribution constraints on their potential health impacts
Bibliographic record
Abstract
Abstract Dust particles derived from sand and gravel mining have been considered as one of the possible sources of suspended particles in Tehran, the capital city of Iran. In this research, the size, morphological, and geochemical characteristics of the airborne particles originated from open mines were investigated. Twenty-two samples from different heights (3 to 21m) were collected from a sand and gravel quarry in Shahriar as the representative of the numerous quarries in western Tehran. The selected samples were further analyzed using X-ray powder diffraction (XRD) and Scanning Electron Microscopy with Energy Dispersive X-Ray Spectroscopy (SEM-EDS). The main mineralogy of airborne dust was dominated by quartz, followed by albite and calcite. The size distribution of deposited particles at different heights ranged from 0.05 µm to 100 µm and about 80% of them were respirable (< 10 µm) and available for transfer through the atmosphere. Si/Al ratios fall mainly into a range between 4 and 10. About 80% of the total particles are below 10 µm. Most nanoparticles were settled into agglomerated forms.
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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".