Gas Flaring Is LikelyUnderestimated by Satellitesdue to Undetected Small Flares
Bibliographic record
Abstract
Global upstream oil and gas flaring was estimated at 148 billion m<sup>3</sup> in 2023 based on satellite observations by the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument. Accurate monitoring is critical, as both lit and unlit flares release greenhouse gases and pose health risks. However, we show that VIIRS substantially underestimates flaring in Canada, with implications for other regions. Analyzing over 65,000 annualized industry flare reports (>5000 sites per year) in western Canada over more than a decade (2012–2023), we found that VIIRS consistently estimated lower flaring volumes than industry data. In 2023, for example, industry reported 2.2-times more flaring than VIIRS estimated, across more than 14-times as many sites. Most of this discrepancy (76%) was due to undetected small and/or intermittent flares with flow rates <360 m<sup>3</sup>/h (∼220 kg methane/h); the remainder (24%) was the result of enclosed combustor use, whose shielded flames are not readily detected. Comparison with global VIIRS data revealed similar declines in flare detection at low flow rates, suggesting that underestimation may occur in other regions where similar low to medium flare flow rates are common.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.338 | 0.022 |
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; both teacher heads agree on what is shown here.
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".