High-resolution inversion of methane emissions in the Southeast US using SEAC <sup>4</sup> RS aircraft observations of atmospheric methane: anthropogenic and wetland sources
Bibliographic record
Abstract
Abstract. We use observations of boundary layer methane from the SEAC4RS aircraft campaign over the Southeast US in August–September 2013 to estimate methane emissions in that region through an inverse analysis with up to 0.25∘×0.3125∘ (25×25 km2) resolution and with full error characterization. The Southeast US is a major source region for methane including large contributions from oil and gas production and wetlands. Our inversion uses state-of-the-art emission inventories as prior estimates, including a gridded version of the anthropogenic EPA Greenhouse Gas Inventory and the mean of the WetCHARTs ensemble for wetlands. Inversion results are independently verified by comparison with surface (NOAA∕ESRL) and column (TCCON) methane observations. Our posterior estimates for the Southeast US are 12.8±0.9 Tg a−1 for anthropogenic sources (no significant change from the gridded EPA inventory) and 9.4±0.8 Tg a−1 for wetlands (27 % decrease from the mean in the WetCHARTs ensemble). The largest source of error in the WetCHARTs wetlands ensemble is the land cover map specification of wetland areal extent. Our results support the accuracy of the EPA anthropogenic inventory on a regional scale but there are significant local discrepancies for oil and gas production fields, suggesting that emission factors are more variable than assumed in the EPA inventory.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".