Adhesion and Enrichment of Metals on Human Hands from Contaminated Soil at an Arctic Urban Brownfield
Bibliographic record
Abstract
Human exposure to contaminated soils drives clean up criteria at many urban brownfields. Current risk assessment guidelines assume that humans ingest some fraction of soil smaller than 4 mm but have no estimates of what fraction of soil is ingested by humans. Here, we evaluated soil adherence to human hands for 13 agricultural soils from Saskatchewan, Canada and 17 different soils from a brownfield located in Iqaluit, Nunavut, Canada. In addition, we estimated average particle size adhering to human hands for residents of a northern urban setting. Further, we estimated how metal concentrations differed between the adhered and bulk (< 4 mm) fraction of soil. The average particle size for adhered agricultural soils was 34 microm, adhered brownfield soils was 105 microm, and particles adhered to human residentswas 36 microm. Metals were significantly enriched in these adhered fractions with an average enrichment [(adhered-bulk)/bulk] in metal concentration of 184% (113% median) for 24 different elements. Enrichment was greater for key toxicological elements of concern such as chromium (140%), copper (140%), nickel (130%), lead (110%), and zinc (130%) and was highest for silver (810%), mercury (630%), selenium (500%), and arsenic (420%). Enrichment were positively correlated with carbonate complexation constants (but not bulk solubility products) and suggests that the dominant mechanism controlling metal enrichment in these samples is a precipitation of carbonate surfaces that subsequently adsorb metals. Our results suggest that metals of toxicological concern are selectively enriched in the fraction of soil that humans incidentally ingest. Investigators should likely process soil samples through a 45 microm sieve before estimating the risk associated with contaminated soils to humans. The chemical mechanisms resulting in metal enrichment likely differ between sites but at our site were linked to surface complexation with carbonates.
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 | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".