Resolving the long-term trend of PAHs in the Canadian Arctic atmosphere.
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbon (PAH) air concentrations measured over the period 1992-2000 at the Canadian High Arctic station of Alert were subject to time-series analysis using dynamic harmonic regression (DHR). For most of the PAHs, the DHR model fit to the observed data was good, with DHR capable of interpolating over missing data points during periods when air concentrations were below detection limits. As expected, DHR identified seasonal increases in PAH air concentrations. However, it has also identified additional, subtler "seasonal" patterns as a series of harmonics with varying periodicity. For example, a regular summer high in air concentrations was apparent for many PAHs, particularly the lower molecular weight (two- to three-ringed) compounds, which may be attributed to summertime regional combustion events such as forest fires and/or revolatilization from surfaces (e.g., soil and oceans, as well as arctic surfaces). Comparison of wintertime PAH concentrations (where PAH ranged from 260 to 516 pg m-3) with an earlier arctic study did not reveal a reduction in PAH levels. However, removal of the seasonal components by DHR revealed a declining trend in PAH concentrations over the 1992-2000 period. For many lighter PAHs, this was typified by a linear decrease over the whole time series, although, for the higher molecular weight PAHs, a marked reduction was apparent in the first few years of sampling followed by a leveling off in concentrations by the mid/late-1990s. This behavior is similar to reported trends of other air pollutants in the Arctic, may be attributed to the decline in Soviet industry during the early 1990s, and has implications regarding the major PAH sources affecting the Arctic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".