Speciated atmospheric mercury at Waliguan Global Atmospheric Watch station in the northeastern Tibetan Plateau: implication of dust related sources for particulate bound mercury
Bibliographic record
Abstract
Abstract. To understand the ambient levels and sources of atmospheric mercury (Hg) in the Tibetan Plateau, a full-year continuous measurement of speciated atmospheric mercury was conducted at Waliguan (WLG) Baseline Observatory (3816 m a.s.l.) from May 2012 to April 2013. Mean concentrations (±1 SD) of gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM) and particulate bound mercury (PBM) during the whole study period were 1.90 ± 0.80 ng m−3, 12.0 ± 10.6 pg m−3 and 65.4 ± 63.2 pg m−3, respectively. Seasonal variations of GEM were very small, while those of PBM were quite large with mean values being four times higher in cold (102.3 ± 66.7 pg m−3) than warm (22.8 ± 14.6 pg m−3) season. Anthropogenic emissions to the east of Tibetan Plateau contributed significantly to GEM pollution at WLG, while dust particles originated from desert and Gobi regions in Xinjiang province and Tibetan Plateau to the west of WLG were responsible to PBM pollution at WLG. This finding is also supported by the significant positive correlation between daily PBM concentration and daily cumulative absorbing aerosol index (AAI) encountered by air masses transported during the preceding two days.
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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 | 0.000 |
| Research integrity | 0.001 | 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".