Document Type
Dataset
Source Publication Title
DOI
https://doi.org/10.32855/dataset.2024.05.016
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