Trace Metals in Fine and Respirable Ambient Air Particulates on Trinidad’s West Coast
Bibliographic record
Abstract
The paper analyzed the concentrations of trace metals in fine and respirable particulates (fine-PM1 and PM2.5; respirable-PM10) to determine baseline concentrations in the ambient air and the factors impacting its distribution such as land use and time of year when levels may be concerning to public health. Measurements of particulates along with meteorological parameters were made at four sites over the heavily populated west coast of Trinidad (10䓠'N, 61䓒'W) during March ’15-May ’16, representing rural, urban, mixed background and industrial land uses. The study found mean levels of trace metals to be highest at the industrial and urban stations. Public health exceedances (referenced to the Canadian AAQ public health standards (Ontario-MoE, 2012)) were measured for beryllium, cadmium, chromium, iron, manganese and nickel (in PM10). Iron, manganese and nickel, most associated with particulates at the industrial station, were in frequent exceedance. Beryllium—concentrated in coarse PM (PM2.5-10) with only a single measured exceedance at the mixed background station likely poses minimal threat to the health of the nearby population. Cadmium—concentrated in fine PM which peaked once only at the rural station was likely due to an irregular event within a narrow timeframe during the time of sampling. Iron and manganese were frequently above the Canadian public health threshold, but predominated in the coarse PM fraction, suggesting localised sources. Nickel, concentrated in the fine PM fraction, was frequently in exceedance particularly at the industrial station. Cadmium and nickel are genotoxic and should be regulated in order to reduce the burden of toxic carcinogens to which the population can be exposed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".