Statistical atmospheric inversion of local gas emissions by coupling the tracer release technique and local-scale transport modelling: a test case with controlled methane emissions

Abstract

Abstract. This study presents a new concept for estimating the pollutant emission rates of a site and its main facilities using a series of atmospheric measurements across the pollutant plumes. This concept combines the tracer release method, local-scale atmospheric transport modelling and a statistical atmospheric inversion approach. The conversion between the controlled emission and the measured atmospheric concentrations of the released tracer across the plume places valuable constraints on the atmospheric transport. This is used to optimise the configuration of the transport model parameters and the model uncertainty statistics in the inversion system. The emission rates of all sources are then inverted to optimise the match between the concentrations simulated with the transport model and the pollutants' measured atmospheric concentrations, accounting for the transport model uncertainty. In principle, by using atmospheric transport modelling, this concept does not strongly rely on the good colocation between the tracer and pollutant sources and can be used to monitor multiple sources within a single site, unlike the classical tracer release technique. The statistical inversion framework and the use of the tracer data for the configuration of the transport and inversion modelling systems should ensure that the transport modelling errors are correctly handled in the source estimation. The potential of this new concept is evaluated with a relatively simple practical implementation based on a Gaussian plume model and a series of inversions of controlled methane point sources using acetylene as a tracer gas. The experimental conditions are chosen so that they are suitable for the use of a Gaussian plume model to simulate the atmospheric transport. In these experiments, different configurations of methane and acetylene point source locations are tested to assess the efficiency of the method in comparison to the classic tracer release technique in coping with the distances between the different methane and acetylene sources. The results from these controlled experiments demonstrate that, when the targeted and tracer gases are not well collocated, this new approach provides a better estimate of the emission rates than the tracer release technique. As an example, the relative error between the estimated and actual emission rates is reduced from 32 % with the tracer release technique to 16 % with the combined approach in the case of a tracer located 60 m upwind of a single methane source. Further studies and more complex implementations with more advanced transport models and more advanced optimisations of their configuration will be required to generalise the applicability of the approach and strengthen its robustness.

Methane Mitigation: Methods to Reduce Emissions, on the Path to the Paris Agreement

“…The methane emission is then proportional to the ratio of the integrated concentration of the emitted methane to the integrated concentration of the released tracer gas, as measured across the dispersion plume (Scheutz & Kjeldsen, 2019). Tracer release can be coupled with spectroscopy to calibrate fluxes from individual sites such as landfill and oil and gas facilities (Ars et al, 2017;Foster-Wittig et al, 2015;Rees-White et al, 2018;Roscioli et al, 2015;Scheutz et al, 2011). Indeed, Scheutz and Kjeldsen (2019) suggest that the tracer gas dispersion measuring technique should be a core methodology in monitoring to determine emissions.…”

PMIF v1.0: an inversion system to estimate the potential of satellite observations to monitor fossil fuel CO<sub>2</sub> emissions over the globe

“…The σ j is a function of downwind distance i and atmospheric stability parameter. We take the form for σ j from Ars et al (2017).…”

Supplementary material to "The Global Methane Budget 2000–2017"

“…New technologies have also developed systems based on cavity ring down spectroscopy (CRDS), opening a large ensemble of new activities to estimate methane emissions such as drone measurements (using a lightweight version of CRDS), as land-based vehicles for real-time, mobile monitoring over oil and gas facilities, as well as ponds, landfills, livestock, (e.g. Ars et al, 2017).…”