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Methane leaks from natural gas systems follow extreme distributions

Natural gas production site equipment with methane leak shot with a FLIR camera.

Methane leaks in oil and natural gas production contribute heavily to climate change. (Photo: Stanford Univ.)

Even relatively
small leaks from the natural gas system can create large climate concerns because natural gas is
comprised mostly of methane (CH 4 ), a gas with high global warming potential (GWP, ~34 times
that of CO 2 over 100 years, ~86 times on a 20-year basis). Using a very big sample, this study shows that 5 % of leaking sites contribute 50 % of the methane this industry emits to the atmosphere. Furthermore, this study shows a methodological shortcoming of previous studies on methane leakage that seem to have missed heavy emitters so far.

Future energy systems may rely on natural gas as a low-cost fuel to support variable renewable power. However, leaking natural gas causes climate damage because methane (CH4) has a high global warming potential. In this study, we use extreme-value theory to explore the distribution of natural gas leak sizes.

By analyzing ~15,000 measurements from 18 prior studies, we show that all available natural gas leakage datasets are statistically heavy-tailed, and that gas leaks are more extremely distributed than other natural and social phenomena. A unifying result is that the largest 5% of leaks typically contribute over 50% of the total leakage volume. While prior studies used lognormal model distributions, we show that lognormal functions poorly represent tail behavior.

Our results suggest that published uncertainty ranges of CH4 emissions are too narrow, and that larger sample sizes are required in future studies to achieve targeted confidence intervals. Additionally, we find that cross-study aggregation of datasets to increase sample size is not recommended due to apparent deviation between sampled populations. Understanding the nature of leak distributions can improve emission estimates, better illustrate their uncertainty, allow prioritization of source categories, and improve sampling design. Also, these data can be used for more effective design of leak detection technologies.

DOI: 10.1021/acs.est.6b04303
Brandt AR, Heath GA, Cooley D.
Methane leaks from natural gas systems follow extreme distributions.
Environ Sci Technol. 2016 Oct 14. [Epub ahead of print]

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