Anthropogenic and natural CH4 and CO2 emissions observed by a combination of passive, active, and in situ airborne measurements during the CoMet 2.0 Arctic mission in Canada 2022
Bibliographic record
Abstract
Anthropogenic greenhouse gas (GHG) emissions remain the main concern for global climate change. To reduce and mitigate those emissions both anthropogenic and natural sources must be identified and quantified. However, high northern latitude wetland regions may also overlap with, e.g., fossil fuel extraction sites. Consequently, commonly used passive satellite sensors are often challenged to observe and disentangle those emissions due to challenging illumination conditions and their large ground scene size, respectively.To investigate anthropogenic and wetland GHG emissions, a team of scientists deployed a comprehensive suite of instruments aboard the German Research aircraft HALO (High Altitude and Long Range Research) during the CoMet 2.0 Arctic mission conducted in Canada in August and September 2022. During the campaign, passive airborne remote sensing measurements by MAMAP2D-Light (Methane airborne mapper 2D light) were combined with active airborne remote sensing measurements by CHARM-F (CH4 Airborne Remote Monitoring – Flugzeug) and in situ GHG concentration measurements, also including an extensive suite of meteorological parameters.Those column and in-situ concentration observations of CH4 and CO2 will be used to identify and quantify emissions over a wide range of source types and scales in Canada (and Europe). This comprises single point source emissions (e.g., power plants), small areal sources such as landfills (e.g, the Valdemingomez and Pinto landfills in Madrid) and opencast coal mines, and extensive oil and gas exploration sites, including oil sand areas, which might be embedded in natural wetland regions or river deltas. The imaging capabilities of the MAMAP2D-Light instrument enable precise localisation of emissions and therefore mitigation strategies in the case of, e.g., leakages. This work will summarize and present first results and emission estimates from the CoMet 2.0 Arctic mission with a focus on localised emitters observed by the airborne imaging instrument MAMAP2D-Light.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".