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Updated: Jan 20, 2026

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions
Published on: June 12, 2016
Temporal Variations in Methane Emissions from an Unconventional Well Site
Derek Johnson1, Robert Heltzel1, Dakota Oliver1
1Center for Alternative Fuels, Engines, and Emissions, Mechanical and Aerospace Engineering Department, West Virginia University, P.O. Box 6106, Morgantown, West Virginia 26506, United States.
Abstract:
Studies have aimed to quantify methane emissions associated with the growing natural gas infrastructure. Quantification is completed using direct or indirect methods-both of which typically represent only a snapshot in time. Most studies focused on collecting emissions data from multiple sites to increase sample size, thus combining the effects of geospatial and temporal variability (spatio-temporal variability). However, we examined the temporal variability in methane emissions from a single unconventional well site over the course of nearly 2 years (21 months) by conducting six direct quantification audits. We used a full flow sampling system that quantified methane mass emissions with an uncertainty of ±10%. Results showed significant temporal variation in methane mass emissions ranging from 86.2 to 4102 g/h with a mean of 1371 g/h. Our average emissions rate from this unconventional well pad tended to align with those presented in the literature. The largest contributor to variability in site emissions was the produced water tank which had emissions rates ranging from 17.3 to 3731 g/h. We compared our methane mass emissions with the total production for each audit and showed that relative methane loss rates ranged from 0.002 to 0.088% with a mean of 0.030%, typically lower than reported by the literature, noting that our data excluded well unloadings. We examined natural gas production, water production, and weather conditions for trends. The strongest correlation was between methane emissions and historical water production. Our data shows that even for a single site, a snapshot in time could significantly over-predict (3×) or under-predict (16×) methane emissions as compared to a long-term temporal average.
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