Using Common Boundaries to Assess Methane Emissions: A Life Cycle Evaluation of Natural Gas and Coal Power Systems
Bibliographic record
Abstract
Summary There is consensus on the importance of upstream methane (CH 4 ) emissions to the life cycle greenhouse gas (GHG) footprint of natural gas systems, but inconsistencies among recent studies explain why some researchers calculate a CH 4 emission rate of less than 1% whereas others calculate a CH 4 emission rate as high as 10%. These inconsistencies arise from differences in data collection methods, data collection time frames, and system boundaries. This analysis focuses on system boundary inconsistencies. Our results show that the calculated CH 4 emission rate can increase nearly fourfold not by changing the magnitude of any particular emission source, but by merely changing the portions of the supply chain that are included within the system boundary. Our calculated CH 4 emission rate for extraction through pipeline transmission is 1.2% for current practices. Our model allows us to identify GHG contributors in the upstream supply chain, but also allows us to tie upstream findings to complete life cycle scenarios. If applied to the life cycles of power systems and assessed in terms of cumulative radiative forcing, the upstream CH 4 emission rate can be as high as 3.2% before the GHG impacts from natural gas power exceed those from coal power at any point during a 100‐year time frame.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".