Mobile atmospheric measurements and local-scale inverse estimation of the location and rates of brief CH<sub>4</sub> and CO<sub>2</sub> releases from point sources

Abstract

Abstract. We present a local-scale atmospheric inversion framework to estimate the location and rate of methane (CH4) and carbon dioxide (CO2) releases from point sources. It relies on mobile near-ground atmospheric CH4 and CO2 mole fraction measurements across the corresponding atmospheric plumes downwind the sources, on high-frequency meteorological measurements, and a Gaussian plume dispersion model. It exploits the spread of the positions of individual plume cross-sections and the integrals of the gas mole fractions above the background within these plume cross-sections to infer the position and rate of the releases. It has been developed and applied to provide estimates of brief controlled CH4 and CO2 point source releases during a one-week campaign in October 2018 at the TOTAL's experimental platform TADI in Lacq, France. These releases lasted typically 4 to 8 minutes and covered a wide range of rates (0.3 to 200 gCH4/s and 0.2 to 150 gCO2/s) to test the capability of atmospheric monitoring systems to react fast to emergency situations in industrial facilities. It also allowed testing their capability to provide precise emission estimates for the application of climate change mitigation strategies. However, the low and highly varying wind conditions during the releases added difficulties to the challenge of characterizing the atmospheric transport over the very short duration of the releases. We present our series of measurements of CH4 and CO2 mole fractions using instruments onboard a car that drives along the roads ~50 to 150 m downwind the 40 m × 60 m area of controlled releases for each of the releases and the results from the inversions of the release locations and rates. The comparisons of these results to the actual position and rate of the controlled release indicate a 20 %–30 % average error on the release rates and a ~30–40 m errors in the estimates of the release locations. These results are shown to be promising especially since better results could be expected for longer releases and under meteorological conditions more favorable to local scale dispersion modeling.

Determination of the Emission Rates of CO<sub>2</sub> Point Sources with Airborne Lidar

“…On the one hand, because the wind speed is directly included in the calculation, on the other hand, because atmospheric turbulence can broaden or constrict the spatial extent of the exhaust plume. This is a well-known problem, which contributes significantly to the measurement error (Kuhlmann et al, 2019;Luther et al, 2019;Strandgren et al, 2020;Varon et al, 2018;Jongaramrungruang et al, 2019;Kumar et al, 2020). Consequently, the observed CO2 column enhancements between subsequent plume transects may vary considerably, despite a constant emission rate.…”

Determination of the emission rates of CO<sub>2</sub> point sources with airborne lidar

“…Whenever sunlight is needed to perform the measurement, less turbulent conditions, for example in the morning after sunrise or winter, should be preferred. Further, it should be pointed out that, with a lidar, cross-sectional plume measurements can also be performed over water bodies whose detrimental reflective properties often impede the use of passive remote sensing (Gerilowski et al, 2015;Krautwurst et al, 2021;Larsen and Stamnes, 2006). Therefore, plumes from offshore installations can also be addressed with this approach.…”

Near‐field atmospheric inversions for the localization and quantification of controlled methane releases using stationary and mobile measurements

“…Several parameters have been updated in this study compared to the configuration presented in Kumar et al . (2021), mainly the enhancement of the spread of the plume for low wind speed conditions and the use of a power‐law wind profile to define the effective mean wind speed U eff at the release height.…”

“…Here, we propose a specific inversion technique, which, similar to Kumar et al . (2021), takes advantage of the variation of the wind to increase the constraint on the inversion of the locations and rates of single CH 4 release points. It thus compares modelled and observed averages of the concentrations at the measurement locations binned over relatively short periods of time or within sectors of wind directions (with two versions of this inversion technique being tested).…”