Catalytic Combustion of Fugitive Methane: Challenges and Current State of the Technology
Bibliographic record
Abstract
This review covers the current state, challenges, and future directions of catalytic combustion technologies for mitigating fugitive methane emissions from the fossil fuel industry. Methane, a potent greenhouse gas, is released from diverse sources, including natural gas production, oil operations, coal mining, and natural gas engines. The paper details the primary emission sources, and addresses the technical difficulties associated with dilute and variable methane streams such as ventilation air methane (VAM) from underground coal mines and low-concentration leaks from oil and gas infrastructure. Catalytic combustion is a useful abatement solution due to its ability to destruct methane in lean and challenging conditions at lower temperatures than conventional combustion, thereby minimizing secondary pollutant formation such as NOX. The review surveys the key catalyst classes, including precious metals, transition metal oxides, hexa-aluminates, and perovskites, and underscores the crucial role of reactor internals, comparing packed beds, monoliths, and open-cell foams in terms of activity, mass transfer, and pressure drop. The paper discusses advanced reactor designs, including flow-reversal and other recuperative systems, modelling approaches, and the promise of advanced manufacturing for next-generation catalytic devices. The review highlights the research needs for catalyst durability, reactor integration, and real-world deployment to enable reliable methane abatement.
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 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 | 0.000 |
| 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".