Lagrangian back-trajectory dispersion and mass balance models for methane emission localization and quantification
Bibliographic record
Abstract
Methane (CH₄), a potent greenhouse gas with 86 times the global warming potential of carbon dioxide over 20 years, contributes significantly to global temperature rise. As part of the Global Methane Pledge (GMP), Canada aims to reduce CH₄ emissions from oil and gas production by 75% and from the waste sector by 50% by 2030. This research develops and applies advanced CH₄ quantification and localization methods, addressing critical gaps across diverse spatial scales and emission source types. Chapter 1 provides the basic explanation about Lagrangian back-trajectory model (TERRAFEX) that was used in this study. In this chapter the concept of shape function and footprint calculation based on the pre-calculated footprint tables is described in brief. Chapter 2 focuses on localizing emissions within oil and gas facilities using a TERRAFEX and a Gradient Indicator (GI) tool. Results indicate a 90% probability of detection within 25–75 meters of sources under favorable atmospheric conditions, providing valuable insights for optimizing Continuous Emissions Monitoring (CEM) systems. Chapter 3 applies TERRAFEX to mobile surveys at landfills, achieving R² values of 0.77–0.86 between measured and modeled rates, with hotspots identified within ~50 meters of aerial detections. Chapter 4 scales TERRAFEX to regional assessments, finding underestimations in oil and gas inventory values, where TERRAFEX-derived inventories align more closely with field-measured values. Wetlands were underestimated by a factor of 1.43, while emissions from agriculture and waste were also significantly underestimated, emphasizing the need for improved spatial datasets. Chapter 5 uses mass balance and Gaussian dispersion methods to quantify CH₄ emissions from offshore oil platforms and calculate production-weighted emission intensities. Measured emissions ranged between 860 and 8,500 m³ CH₄ day⁻¹, with key contributors identified as venting, flaring, and fugitive emissions. This work bridges methodological gaps in CH₄ quantification and localization, providing insights for policymakers and helps to advance mitigation strategies across oil and gas, waste, and offshore sectors.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".