Methane Leaks from Natural Gas Systems Follow Extreme Distributions

Brandt, Adam R.; Heath, Garvin A.; Cooley, Daniel

doi:10.1021/acs.est.6b04303

Title: Methane Leaks from Natural Gas Systems Follow Extreme Distributions

Journal Article · Fri Oct 14 00:00:00 EDT 2016 · Environmental Science and Technology

DOI:https://doi.org/10.1021/acs.est.6b04303· OSTI ID:1333408

Brandt, Adam R. ^[1]; Heath, Garvin A. ^[2]; Cooley, Daniel ^[3]

Stanford Univ., CA (United States). Dept. of Energy Resources Engineering
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Colorado State Univ., Fort Collins, CO (United States)

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. Finally, 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.

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Policy and Systems Analysis

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1333408

Report Number(s):: NREL/JA-6A20-65423

Journal Information:: Environmental Science and Technology, Vol. 50, Issue 22; ISSN 0013-936X

Publisher:: American Chemical Society (ACS)Copyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 47 works

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