Pollution Levels and Potential Health Risks of Potentially Toxic Elements in Indoor and Outdoor Dust during the COVID-19 Era in Gómez Palacios City, Mexico
Bibliographic record
Abstract
The COVID-19 pandemic has caused a decrease in outdoor activities, but an increase in indoor ones. This change in the intensity of land use has caused changes in pollution patterns. Urban dust contaminated with heavy metals can be a risk to the human population. Therefore, the objective of this work was to evaluate the pollution caused by heavy metals in urban dust indoors and outdoors due to changes in land use during the pandemic. Sampling was carried out by the Gomez Palacio citizens. The total number of urban dust samples was 330, 50% indoor samples and 50% outdoor sample. The elements studied were Ca, Cu, Fe, K, Mn, Ni, Pb, Rb, Sr, Ti, Y, Zn, and Zr. The heavy metals were measured through a portable XRF; the contamination factor and the load pollution index were used to assess the pollution level. The human health risk was evaluated with the USEPA methodology. Cu, Pb, and Zn presented higher concentrations indoors than outdoors, probably due to domestic factors, such as the age of the houses and the paint on the walls. Zn presented the highest pollution level among all the metals, outdoors and indoors; spatially, the sites sampled in the northwest, close to agricultural areas, presented the highest Zn pollution. Pb had a moderate pollution level in most of the samples (60%), but some samples showed a high Pb pollution. The health risk was considered within the acceptable levels for Cu, Fe, Ni, Pb, Zn. However, Mn deserves attention because the average of the samples slightly exceeded the USEPA safety limits for children. Children are at higher risk compared to adults. Indoor environments need to be better analyzed because they were shown to represent a higher risk to the population than outdoor ones due to heavy metal pollution by Zn, Cu, and Pb. The pandemic impacted land use intensity; this study reports an apparent effect of the pandemic on the amount and type of heavy metals indoors and outdoors.
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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 | 0.000 |
| 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 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".