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This content will become publicly available on October 14, 2017

Title: Methane Leaks from Natural Gas Systems Follow Extreme Distributions

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 moremore » effective design of leak detection technologies.« less
Authors:
 [1] ;  [2] ;  [3]
  1. Stanford Univ., CA (United States). Dept. of Energy Resources Engineering
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Colorado State Univ., Fort Collins, CO (United States)
Publication Date:
OSTI Identifier:
1333408
Report Number(s):
NREL/JA--6A20-65423
Journal ID: ISSN 0013-936X
Grant/Contract Number:
AC36-08GO28308
Type:
Accepted Manuscript
Journal Name:
Environmental Science and Technology
Additional Journal Information:
Journal Volume: 50; Journal Issue: 22; Journal ID: ISSN 0013-936X
Publisher:
American Chemical Society (ACS)
Research Org:
NREL (National Renewable Energy Laboratory (NREL), Golden, CO (United States))
Sponsoring Org:
USDOE Office of Energy Policy and Systems Analysis
Country of Publication:
United States
Language:
English
Subject:
03 NATURAL GAS fat tail; extreme value; methane; natural gas; statistics