Weathering of leaded paint and chromate primer: Transformation of engineered into incidental nanoparticles
Bibliographic record
Abstract
Nanoparticles (NPs) containing Pb are concerning due to the exceptionally hazardous nature of the element and its widespread use. This study characterizes the weathering of Pb-bearing paint chips (PCs) into Pb-bearing NPs in the surficial soils of Germantown, Philadelphia, USA. The PCs are composed of nano- to micrometer-size engineered particles (EPs) of massicot (PbO, Pb-pigment), Zn-chromates (ZnCrO 4 , primer) and white paint components (rutile, TiO 2 , barite, BaSO 4 , wurtzite, ZnS). These EPs transform into incidental nanoparticles (INPs) of litharge and massicot (both PbO), crocoite (PbCrO 4 ), and phoenicochroite (Pb 2 CrO 5 ), Zn-(hydr)oxides, Cr-(hydr)oxides and anatase/brookite (TiO 2 ) INPs. With increasing degree of weathering, the altered PCs become depleted in Zn and Pb relative to layers composed of massicot and Zn-chromates with the latter two elements being released as INPs or solutes into the bulk soil. Chemical and mineralogical characterization of colloidal fractions leached from collected soil samples indicate that pyromorphite (Pb 5 (PO 4 ) 3 OH) is the only observed Pb-bearing phase, suggesting that the observed Pb-bearing INPs in the PCs are either not mobile or transform into the former phase. The results of this study suggest that the transformation of larger Pb-, Cr- and Zn-bearing EPs into INP’s increase the reactivity, bioaccessibility and their health risks. • Weathering sequence of paint chips containing leaded paint and chromate primer. • Transformation of engineered into incidental nanoparticles. • Formation of Pb-bearing nanoparticles of litharge, massicot, minium. • Formation of Pb-chromate nanoparticles in disequilibrium with the bulk soil. • Weathering of paint chips decreases average size of Pb, Cr and Zn bearing particles.
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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 | 0.000 | 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) | 0.000 | 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 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".