Physical and practical constraints on atmospheric methane removal technologies
Bibliographic record
Abstract
Abstract Despite their apparent utility in mitigating climate change, technologies for removing methane from air are in early stages of development. Here we evaluate the limiting physical constraints, for three types of systems: two- and three-dimensional infrastructure and atmospheric oxidation enhancement, focusing on removing low ( x CH4 < 1000 ppm) and ambient ( x CH4 < 2 ppm) methane from air. With the space velocities and removal efficiencies of current three-dimensional technologies, volumes of 7–350 km3 are required to remove 1 Tg CH4 yr−1. Two-dimensional solutions are limited by the transport rate of methane to a surface. If every molecule of methane that collides with the surface is removed, an area of 1130 km2 is needed to remove 1 Tg CH4 yr−1 at ambient concentration. However, research shows that per-collision reaction probabilities are < 10−8 requiring a surface area of 1010–1015 km2. Finally, we examine atmospheric oxidation enhancement, where 4.8 Tg yr−1 of Cl ⋅ or 8.8 Tg yr−1 of OH ⋅ is required to remove 1 Tg CH4 yr−1, with precursors such as H2O2 or O3. However, limitations arise concerning multiple environmental impacts. We conclude that the physical and practical constraints are considerable, and identify the main barriers that must be addressed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".