Greenland Snow Evidence of Large Scale Atmospheric Contamination for Platinum, Palladium, and Rhodium
Bibliographic record
Abstract
Since 1976 in the United States, Canada, and Japan, and later in other countries, the exhaust system of gasoline powered cars has been equipped with catalytic converters containing Pt and/or Pd and/or Rh. This has resulted in a very significant decrease in urban air pollution for various chemical species such as NOx, CO, and hydrocarbons. There has however been concern that their ever increasing use might lead to Platinum Group Metals (PGMs) becoming widely dispersed in the environment. From the analysis of Pt, Pd, and Rh in central Greenland recent snow and ancient ice using the ultrasensitive inductively coupled plasma sector field mass spectrometry technique, we show here that the concentrations of these metals in snow dated from the mid 1990s are indeed approximately 40-120 times higher than in ice dated from 7000 years ago. The fact that such an increase is observed far away from populated areas at a high altitude location indicates there is now a large scale contamination of the troposphere of the Northern Hemisphere for PGMs. Pt/Rh mass ratio in the most recent snow samples is close to the same ratio documented for catalytic converter exhausts in a recent study, which suggests that a large fraction of the recent increase for Pt and Rh might originate from automobile catalytic converters.
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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 | 0.000 | 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) | 0.001 | 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".