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 of these sources, on high-frequency meteorological measurements, and on a Gaussian plume dispersion model. The framework exploits the scatter of the positions of the individual plume cross sections, the integrals of the gas mole fractions above the background within these plume cross sections, and the variations of these integrals from one cross section to the other 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 1-week campaign in October 2018 at the TOTAL experimental platform TADI in Lacq, France. These releases typically lasted 4 to 8 min and covered a wide range of rates (0.3 to 200 g CH4/s and 0.2 to 150 g CO2/s) to test the capability of atmospheric monitoring systems to react fast to emergency situations in industrial facilities. It also allowed testing of 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 CH4 and CO2 mole fraction measurements using instruments on board a car that drove along roads ∼50 to 150 m downwind of the 40 m × 60 m area for controlled releases along with the estimates of the release locations and rates. The comparisons of these results to the actual position and rate of the controlled releases indicate ∼10 %–40 % average errors (depending on the inversion configuration or on the series of tests) in the estimates of the release rates and ∼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. However, the analysis also highlights the need for methodological improvements to increase the skill for estimating the source locations.
Highlights
Accurate detection and quantification of greenhouse gas (GHG) emissions from anthropogenic activities is essential to construct effective mitigation policies
We evaluate the inversion estimates of the rates and locations of the selected releases using the actual values provided by TOTAL
The number of plume cross sections used by the inversion for individual CH4 or CO2 releases varies from 1 to 6 with a typical range of 2–4 (Table 2)
Summary
Accurate detection and quantification of greenhouse gas (GHG) emissions from anthropogenic activities is essential to construct effective mitigation policies. CH4 emissions inventories for specific sectors combine uncertain activity data and highly uncertain emission factors (Alvarez et al, 2018). Typical emission factors used as the default values in inventories can hardly be representative of the specific configurations and processes of individual sites, and, in practice, they are usually different from those measured at specific sites Vaughn et al, 2017; Ravikumar and Brandt, 2017; Omara et al, 2018) Monitoring of CH4 emissions from individual sites and even at the scale of local facilities within the same site is recommended to assess the effectiveness of local measures applied to minimize emissions (Konschnik and Jordaan, 2018) Typical emission factors used as the default values in inventories can hardly be representative of the specific configurations and processes of individual sites, and, in practice, they are usually different from those measured at specific sites (e.g. Vaughn et al, 2017; Ravikumar and Brandt, 2017; Omara et al, 2018) Monitoring of CH4 emissions from individual sites and even at the scale of local facilities within the same site is recommended to assess the effectiveness of local measures applied to minimize emissions (Konschnik and Jordaan, 2018)
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