Articles | Volume 18, issue 20
Research article
22 Oct 2018
Research article |  | 22 Oct 2018

Quantifying uncertainties from mobile-laboratory-derived emissions of well pads using inverse Gaussian methods

Dana R. Caulton, Qi Li, Elie Bou-Zeid, Jeffrey P. Fitts, Levi M. Golston, Da Pan, Jessica Lu, Haley M. Lane, Bernhard Buchholz, Xuehui Guo, James McSpiritt, Lars Wendt, and Mark A. Zondlo

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Cited articles

Agee, E. and Gluhovsky, A.: LES Model Sensitivities to Domains, Grids, and Large-Eddy Timescales, J. Atmos. Sci., 56, 599–605,<0599:LMSTDG>2.0.CO;2, 1999a.
Agee, E. and Gluhovsky, A.: Further Aspects of Large Eddy Simulation Model Statistics and Inconsistencies with Field Data, J. Atmos. Sci., 56, 2948–2950,<2948:FAOLES>2.0.CO;2, 1999b.
Albertson, J. D., Harvey, T., Foderaro, G., Zhu, P., Zhou, X., Ferrari, S., Amin, M. S., Modrak, M., Brantley, H., and Thoma, E. D.: A Mobile Sensing Approach for Regional Surveillance of Fugitive Methane Emissions in Oil and Gas Production, Environ. Sci. Technol., 50, 2487–2497,, 2016.
Allen, D. T., Torres, V. M., Thomas, J., Sullivan, D. W., Harrison, M., Hendler, A., Herndon, S. C., Kolb, C. E., Fraser M. P., Hill, A. D., and Lamb, B. K.: Measurements of methane emissions at natural gas production sites in the United States, Proc. Natl. Acad. Sci. USA, 110, 17768–17773,, 2013.
Allen, D. T., Pacsi, A. P., Sullivan, D. W., Zavala-Araiza, D., Harrison, M., Keen, K., Fraser, M. P., Hill, A. D., Sawyer, R. F., and Seinfeld, J. H.: Methane emissions from process equipment at natural gas production sites in the United States: Pneumatic controllers, Environ. Sci. Technol., 49, 633–640,, 2014.
Short summary
Mobile laboratory measurements have been widely used to quantify methane emissions from point sources such as oil and gas wells, but the emission uncertainties are poorly constrained. We designed a hierarchical measurement strategy to sample natural gas emissions in the Marcellus Shale play based upon high-resolution modeling of select sites. Our study quantifies the largest sources of error with this approach and provides guidance on how to best implement mobile laboratory sampling protocols.
Final-revised paper