Temporal trends of Persistent Organic Pollutants (POPs) in arctic air: 20 years of monitoring under the Arctic Monitoring and Assessment Programme (AMAP)
Bibliographic record
Abstract
Temporal trends of Persistent Organic Pollutants (POPs) measured in Arctic air are essential in understanding long-range transport to remote regions and to evaluate the effectiveness of national and international chemical control initiatives, such as the Stockholm Convention (SC) on POPs. Long-term air monitoring of POPs is conducted under the Arctic Monitoring and Assessment Programme (AMAP) at four Arctic stations: Alert, Canada; Stórhöfði, Iceland; Zeppelin, Svalbard; and Pallas, Finland, since the 1990s using high volume air samplers. Temporal trends observed for POPs in Arctic air are summarized in this study. Most POPs listed for control under the SC, e.g. polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethanes (DDTs) and chlordanes, are declining slowly in Arctic air, reflecting the reduction of primary emissions during the last two decades and increasing importance of secondary emissions. Slow declining trends also signifies their persistence and slow degradation under the Arctic environment, such that they are still detectable after being banned for decades in many countries. Some POPs, e.g. hexachlorobenzene (HCB) and lighter PCBs, showed increasing trends at specific locations, which may be attributable to warming in the region and continued primary emissions at source. Polybrominated diphenyl ethers (PBDEs) do not decline in air at Canada's Alert station but are declining in European Arctic air, which may be due to influence of local sources at Alert and the much higher historical usage of PBDEs in North America. Arctic air samples are screened for chemicals of emerging concern to provide information regarding their environmental persistence (P) and long-range transport potential (LRTP), which are important criteria for classification as a POP under SC. The AMAP network provides consistent and comparable air monitoring data of POPs for trend development and acts as a bridge between national monitoring programs and SC's Global Monitoring Plan (GMP).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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".