Anthropogenic and Natural Factors Affecting Trends in Atmospheric Methane in Barrow, Alaska
Bibliographic record
Abstract
This study examined the long-term trends in Arctic ambient methane (CH4) mixing ratios over 1986–2014 and investigated their potential causes. Significant correlations between carbon monoxide (CO) and CH4 in Barrow, Alaska (r = −0.59, p = 0.007) and Alert, Canada (r = −0.62, p = 0.004) with the strongest correlations occurring in April (r = −0.81, p = 0.000, and r = −0.80, p = 0.000) suggest local to global anthropogenic contributions to ambient CH4 during the cold months. Backward trajectories indicate a significant influence (27% of total trajectories) of local emissions from the Prudhoe Bay Oil Field on ambient CH4 in Barrow in winter, and this influence was dominated by other factors in summer. The mean CH4 wetland emission flux in Barrow over 1986–2014 was estimated to be 0.008 ± 0.002 µg m−2 s−1 while in Tiksi, Russia it was 0.010 µg m−2 s−1 over 2012–2016, which is comparable to the lower end of measurements in the literature. Note that in Barrow, there was a decrease in wetland flux from 0.0083 ± 0.002 µg m−2 s−1 over 1986–1998 to 0.0077 ± 0.002 µg m−2 s−1 from 1999–2006 followed by an increase to 0.0081 ± 0.002 µg m−2 s−1 over 2007–2014. Although the difference between the three values is not statistically significant due to small sample size, it is indicative of possible warm season wetland emissions contributing to the zero-growth period. Strong support for this hypothesis is that these changes are consistent with a concurrent drop in summertime temperature possibly causing a decrease in wetland emissions over 1998–2006 based on the statistically significant correlations between temperature and CH4 during August through November (r ~ 0.36–0.56, p = ≤0.05). In a warming climate, permafrost thawing can increase CH4 wetland emissions and also decrease wetlands making it a complex problem, and, hence, further study is needed to better understand the mechanisms driving long-term trends in Arctic CH4.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".