Evaluating the Mobile Flux Plane (MFP) Method to Estimate Methane Emissions Using Large Eddy Simulations (LES)


Kumar R, Mitchell DA, Steinhoff DF, Saide P, Kosovic B, Downey N, Blewitt D, Delle Monache L. Evaluating the Mobile Flux Plane (MFP) Method to Estimate Methane Emissions Using Large Eddy Simulations (LES). Journal of Geophysical Research: Atmospheres [Internet]. 2021;126 (5) :e2020JD032663.


Abstract This study evaluates the efficacy of the mobile flux plane (MFP) method to derive methane emissions from oil and gas production fields using a first-of-its-kind high-resolution methane concentration data set. Transport and dispersion of methane emissions from seven hypothetical well pads generated with an oil field emission simulator is simulated every second at 10 m resolution using the Weather Research and Forecasting (WRF) model in large eddy simulation mode. The time varying WRF-generated methane concentration data set is sampled by a simulated MFP system downwind of the seven well pads at five sampling distances of 50, 75, 100, 125, and 150 m. Several key findings highlight the significant variability in MFP emission rate estimates induced by atmospheric turbulence and variable source emission rates. Natural atmospheric turbulence alone was found to generate significant variability (33%–75%) in the MFP emission estimates with constant emission rates at the source location. It was also found that turbulent wind speed fluctuations over the duration of a transect can also affect MFP estimates up to about ±50% through convergence (divergence) that increases (decreases) methane concentrations, and by its effect on the assumption of steady winds over the duration of the transect. It was further found that the MFP method typically estimated about 19%–33% and 51%–75% of known site emission rates using the trapezoidal and Gaussian fit integration methods, respectively. Thus, methane concentrations would need to be measured to a much higher elevation to generate robust and accurate methane emission rate estimates.


e2020JD032663 2020JD032663