Replication Data for "Estimating methane emissions from underground natural gas pipelines using an atmospheric dispersion-based method"

Authors

Shanru Tian, University of Texas at Arlington
Kathleen M. Smits, University of Texas at Arlington
Younki Cho, University of Texas at Arlington
Stuart Riddick, Colorado State University
Daniel Zimmerle, Colorado State University
Aidan Duggan, Colorado State University

ORCID Identifier(s)

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

Document Type

Dataset

Source Publication Title

Elementa: Science of the Anthropocene

Related Publication(s)

Tian, S., K.M. Smits, Y. Cho, S. Riddick, D. Zimmerle, A. Duggan, Estimating methane emissions from underground natural gas pipelines using an atmospheric dispersion-based method, Elementa, 2022

Production/Collection Date

03/01/2022

Production/Collection Location

University of Texas at Arlington and Colorado State University

Depositor

Kathleen Smits

Deposit Date

3-1-2024

Data Type

Modeling and experimental

Abstract

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.

Disciplines

Earth Sciences | Engineering | Environmental Sciences

Publication Date

5-18-2022

Language

English

License

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

Recommended Citation

Tian, Shanru; Smits, Kathleen M.; Cho, Younki; Riddick, Stuart; Zimmerle, Daniel; and Duggan, Aidan, "Replication Data for "Estimating methane emissions from underground natural gas pipelines using an atmospheric dispersion-based method"" (2022). Earth & Environmental Sciences Datasets. 2.
https://mavmatrix.uta.edu/ees_datasets/2