GEM/POPs: a global 3-D dynamic model for semi-volatile persistent organic pollutants – Part 2: Global transports and budgets of PCBs
Bibliographic record
Abstract
Abstract. Global transports and budgets of three PCBs were investigated with a 3-D dynamic model for semi-volatile persistent organic pollutants – GEM/POPs. Dominant pathways were identified for PCB transports in the atmosphere with a transport flux peaking below 8 km for gaseous and 14 km for particulate PCB28, and peaking below 4 km for gaseous and 6 km for particulate PCB180. The inter-continental transports of PCBs in the Northern Hemisphere (NH) are dominated in the zonal direction with their route changes regulated seasonally by the variation of westerly jet. The transport pathways from Europe and North Atlantic contributed the most PCBs to the Arctic. Inter-hemispheric transports of PCBs originated from the regions of Europe, Asia and North America in three different flow-paths, accompanying with easterly jet, Asian monsoon winds and trade winds. PCBs from the Southern Hemisphere (SH) could also be exported into the NH. According to the PCB emissions of year 2000, Europe, North America and Asia are the three largest sources of the three PCBs, contributing to the global background concentrations in the atmosphere, soil and water. Globally, PCB28 in soil and water has become a comparable source to the anthropogenic emissions while heavier PCBs such as PCB153 and 180 are still transporting into soil and water. For all three congeners, particulate PCBs are concentrated in the higher levels than gaseous PCBs. More than half of the particulate PCB28 could reach up to the stratosphere, while most of the heavier counter-parts (PCB153 and PCB180) are stored in the troposphere including boundary layer with more than 99% gaseous PCB180 below 6 km.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".