ORCID Identifier(s)

ORCID 0000-0002-8319-0940, ORCID 0000-0003-1684-1843, ORCID 0000-0003-2832-048X

Document Type


Source Publication Title

Elementa: Science of the Anthropocene

Production/Collection Date


Production/Collection Location

University of Texas at Arlington and Colorado State University


Kathleen Smits

Deposit Date


Data Type

Modeling and experimental


Methane (CH4) leakage from natural gas (NG) pipelines poses an environmental, safety, and economic threat to the public. While previous leak detection and quantification studies focus on the aboveground infrastructure, the analysis of underground NG pipeline leak scenarios is scarce. Furthermore, no data from controlled release experiments have been published on the accuracy of methods used to (1) quantify emissions from an area source and (2) use these emissions to quantify the size of a subsurface leak. This proof-of-concept work uses CH4 mole fraction, as measured by a single gas sensor, as an input to a simple dispersion-based model (WindTrax) under ideal conditions (i.e., in a field) and compares the calculated emissions to the known controlled NG release rates. The aboveground and surface CH4 mole fractions were measured for 5 days at a field testbed using controlled underground release rates ranging from 0.08 to 0.52 kg hr–1 (3.83–24.94 ft3 hr–1). Results confirmed that the mean normalized CH4 mole fraction increases as the atmosphere transitions from the Pasquill–Gifford (PG) stability class A (extremely unstable) to G (extremely stable). The estimated surface CH4 emissions showed large temporal variability, and for the emission rates tested, at least 6 h of data are needed to have a representative estimate from subsurface pipeline leaks (±27% of the controlled release rate on average). The probability that the emission estimate is within ±50% of the controlled release rate (P±50%) is approximately 50% when 1 h of data is collected; the probability approaches 100% with 3–4 h of data. Findings demonstrate the importance of providing enough data over time for accurate estimation of belowground leak scenarios. By adopting the estimation method described in this study, operators can better estimate leakage rates and identify and repair the largest leaks, thereby optimizing annual greenhouse gas emissions reductions and improving public safety.


Earth Sciences | Engineering | Environmental Sciences

Publication Date





Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.