Evaluating the feasibility of using downwind methods to quantify point source oil and gas emissions using continuous monitoring fence-line sensors

The accurate reporting of methane (CH4) emissions from point sources, such
as fugitive leaks from oil and gas infrastructure, is important for
evaluating climate change impacts, assessing CH4 fees for regulatory
programs, and validating methane intensity in differentiated gas programs.
Currently, there are disagreements between emissions reported by different
quantification techniques for the same sources. It has been suggested that
downwind CH4 quantification methods using CH4 measurements on the
fence-line of production facilities could be used to generate emission
estimates from oil and gas operations at the site level, but it is
currently unclear how accurate the quantified emissions are. To
investigate model accuracy, this study uses fence-line simulated data
collected during controlled release experiments as input for eddy
covariance, aerodynamic flux gradient, backward Lagrangian stochastic
model, and the Gaussian plume inverse methods in a range of atmospheric
conditions. Eddy covariance’s data failed the quality test based on Mauder
and Foken (2004) (0-1-2 system) quality test and could not be used for
quantification. The aerodynamic flux gradient method quantified within a
relative factor (estimated emission/actual emission) of 0.4 to 0.85 for a
single release single emission, and at between 2.51 and 4.21 for multiple
releases single emissions. The backward Lagrangian stochastic model for
point sources using WindTrax performed well for single release single
emissions, relative factor of between 0.82 to 1.07, but largely
overestimated emissions for multiple releases single emissions, relative
factor of 418.8, 2156.7, and 3.91 at 5, 10, and 15-minute averaging.
Similar to the backward Lagrangian stochastic model, the Gaussian plume
inverse model performed well for single point sources, average relative
factor of 3. However, the model largely overestimated emissions when
multiple releases were happening, relative factor between 20 and 30. As
continuous monitoring of oil and gas sites involves complex emissions
where plumes are not defined due to multiple sources, this study shows
that the common downwind point source dispersion models could largely
overestimate emissions. Aerodynamic flux gradient provided promising
results for multiple releases quantification, and this study recommends
more testing of flux quantification models for oil and gas continuous
monitoring quantification.