Repair Failures Call for New Policies to Tackle Leaky Natural Gas Distribution Systems
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Methane leaks in natural gas systems are low-hanging fruit for near-term, locally driven climate policy. Recent work suggests this emissions source is larger than previously believed and that repairing a small number of high emitters can cost-effectively reduce system-wide leakage. How successful are these repairs on the ground? Here, we assess the effectiveness of repair policies in the Massachusetts distribution system. Our analysis leverages state-wide utility data, on-site empirical measurements, stakeholder interviews, and document and legal analysis. We use these mixed methods to investigate the rate of repair failure, where a gas utility identifies and fixes a leak, but on-site emissions are not eliminated. We find that repair failures are relatively common, yet they are repeatedly neglected in policy. By not accounting for repair failures, policy may overestimate the effectiveness of distribution system repairs in meeting local greenhouse gas reduction targets. These results also underscore the importance of data transparency for monitoring and verifying subnational climate policies.
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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 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.016 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".