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Inter-comparison of Atmospheric Trace Gas Dispersion Models: Barnett Shale Case Study
Published
Author(s)
Anna Karion, Thomas Lauvaux, Israel Lopez Coto, Colm Sweeney, Kimberly L. Mueller, Sharon M. Gourdji, Wayne Angevine, Zachary R. Barkley, Aijun Deng, Ariel Stein, James R. Whetstone
Abstract
Greenhouse gas emissions mitigation requires understanding dominant processes controlling fluxes of these trace gases into the atmosphere at increasingly finer spatial and temporal scales. Trace gas fluxes can be estimated using a variety of approaches that translate observed atmospheric species mole fractions into fluxes or emission rates, often identifying the spatial and temporal characteristics of the emissions sources as well. Meteorological models are commonly combined with tracer dispersion models to derive fluxes using an inverse approach that optimizes emissions to best fit the trace gas mole fraction observations. To better evaluate the accuracy of atmospheric flux estimation methods, there is a need to compare results from independent methods, including methods in which different meteorological and tracer dispersion models are used. In this work, we use a rich data set of atmospheric methane observations collected during an intensive airborne campaign to compare methane emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, U.S.A., based on a variety of different meteorological and dispersion models. Previous estimates of methane emissions from this region relied on a simpler model (a mass balance analysis) as well as on ground-based measurements and statistical data analysis (an inventory). We find that meteorological and tracer dispersion model choice has a significant impact on the predicted downwind methane concentrations given the same emissions field. The Lagrangian dispersion models tested often under-predicted the observed methane enhancements and therefore over-estimated the emissions from the domain when used in an inverse analysis. An in-line Eulerian transport and dispersion model, however, compared well with mass balance and inventory methods. We examine possible causes for this result and find that the dispersion models differ in their simulation of vertical dispersion, indicating that additional work i
Karion, A.
, Lauvaux, T.
, Lopez, I.
, Sweeney, C.
, Mueller, K.
, Gourdji, S.
, Angevine, W.
, Barkley, Z.
, Deng, A.
, Stein, A.
and Whetstone, J.
(2019),
Inter-comparison of Atmospheric Trace Gas Dispersion Models: Barnett Shale Case Study, Atmospheric Chemistry and Physics, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=925968
(Accessed October 11, 2025)