Measured and Modeled Trends of Seven Tropospheric Pollutants in the High Arctic From 1999 to 2022
Bibliographic record
Abstract
Abstract The long‐term trends and seasonality of many tropospheric pollutants are not well characterized in the high Arctic due to a dearth of trace‐gas measurements in this remote region. In this study, the inter‐ and intra‐annual variabilities of carbon monoxide (CO), acetylene (C2H2), ethane (C2H6), methanol (CH3OH), formaldehyde (H2CO), formic acid (HCOOH), and peroxyacetyl nitrate (PAN) in the high Arctic region were derived from the total column time‐series of ground‐based Fourier transform infrared (FTIR) measurements at Eureka, Nunavut (80.05°N, 86.42°W, 2006–2020) and Thule, Greenland (76.53°N, 68.74°W, 1999–2022). Consistent seasonal cycles were observed in the FTIR measurements at both sites for all species. Negative trends were observed for CO, C2H2, and CH3OH at both sites, and for HCOOH at Eureka. Positive trends were detected for C2H6 and H2CO at both sites, and for PAN at Eureka. Additionally, a 19‐year simulation was performed using the novel GEOS‐Chem High Performance model v14.1.1 for the period of 2003–2021. The model was able to reproduce the observed seasonality of all gases, but all species showed negative biases relative to observations, and CH3OH was found to have a particularly large bias of approximately −70% relative to the FTIR measurements. The GEOS‐Chem modeled trends broadly agreed with observations for all species except C2H6, H2CO, and PAN, which were found to have opposite trends in the model. For some species, the measurement‐model differences are suspected to be the result of errors or underestimations in the emissions inventories used in the simulation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".