Methane emissions from abandoned hydrocarbon wells in Italy: inventory, measurement techniques and the role of mega-emitters
Bibliographic record
Abstract
Abandoned hydrocarbon (oil and gas) wells (AOG) represent a poorly studied source of atmospheric methane, potentially contributing to total anthropogenic fossil methane emission and related climatic impact. Methane leakage from AOG was measured only in a few countries (U.S.A., Canada, the Netherlands, United Kingdom), and available inventories in other countries are incomplete or need quality checks. Methodologies for gas flux measurement are not standardized. New studies have recently started in Italy in order to inventory onshore AOG, design multiple and versatile techniques for methane flux measurement, which can be adaptable to different typologies of well-heads, and to execute first measurements. Preliminary data revealed the existence of several AOW releasing relevant amounts of methane (orders of 101 ton yr-1), which are up to two orders of magnitude above those typically observed in North America. Contextualization of such “mega-emitters” (their percentage with respect to total AOW, technical conditions, possible existence in other countries) is necessary to assess average emission factors and derive bottom-up methane emission estimates at national and global scale.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".