Understanding the fate of persistent organic pollutants in temperate and tropical mountains
Bibliographic record
Abstract
Mountains are ideal settings to study contaminant transport and behavior along gradients of climate and surface cover. In both the mountains of Western Canada and Central America, surface soil samples were collected along several elevational gradients and air was sampled for an entire year using XAD-based passive air samplers. The soil and XAD extracts were analyzed for PAHs and organochlorine pesticides in past and present use. Field results and computer modeling point to windows of enhanced contaminant accumulation at high altitudes for compounds with an equilibrium air-water partition cooefficient at 25°C between 10-3 and 10-6 and an octanol-air partition coefficient between 10+9 and 10+11, in both temperate and tropical locations. Chemicals with partitioning properties in these ranges are not efficiently scavenged at the temperature prevalent in the lowlands. They travel upslope with prevailing winds and, at the low temperatures of high elevations, scavenging efficiency increases, and the chemicals are deposited onto soil. Modeling results show maximum mountain accumulation for mountains with a large temperature range and greatest increase in precipitation with altitude. Lower precipitation rates increase air/soil concentration ratios of organochlorine pesticides on the eastern side of the continental divide in western Canada. Snow plays an important role in contaminant accumulation in temperate mountains, by efficiently scavenging organic contaminants at low temperatures. The snow pack functions as a temporary storage reservoir that releases contaminants accumulating over the winter, which may result in temporarily elevated concentrations in air, water and soil. Contaminant signatures differ in tropical mountains due to different source contribution. Tropical soils have a higher relative abundance of lighter PAHs compared to temperate locations, a result of greater source contribution from biomass burning in the tropics, as well as preferential loss of lighter PAHs from temperate soils that experienced high deposition in the past.
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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 | 0.001 | 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".