Estimating emissions of methane and carbon dioxide sources using analytical Bayesian inversion system based on WRF-GHG tagged tracer simulations

During May and June 2018, the intensive campaign CoMet (Carbon dioxide and Methane mission) made atmospheric measurements of greenhouse gases over Europe, with the upper Silesian coal basin (USCB) in southern Poland as a specific focus area. CoMet aimed at characterising the distribution of CH₄ and CO₂ over significant regional sources with the use of a fleet of research aircraft, as well as to validate remote sensing measurements from state-of-the-art instrumentation installed on-board against a set of independent in-situ observations.

In order to link atmospheric mixing ratios to source emission rates, high-resolution simulations with WRF-GHG v 3.9.1.1. (10 km x10 km Europe + nested 2 km x 2 km domain over the USCB), driven by short-term meteorological forecasts from the ECMWF IFS model and forecasts from CAMS (Copernicus Atmospheric Monitoring Service) for initial and lateral tracer boundary conditions were performed. Biogenic fluxes of CO2 were calculated online using the VPRM model driven by MODIS indices. Anthropogenic emissions over Europe were taken from the database of TNO, Department of Climate, Air and Sustainability (7 km x 7 km), augmented with an internal emissions database developed within CoMet that uses coal mine ventilation shaft emission measurements in combination with recent updates of the E-PRTR (European Pollutant Release and Transfer Register).

Tagged tracers were used to simulate a robust set of over 100 distinct anthropogenic sources of CH₄ and CO₂ from the study area, and these forward simulations were then used as the transport operator in an analytical Bayesian inversion system. Here we discuss the results of an analysis performed with the use of selected in-situ data measured over the course of the three-week campaign, including results and sensitivity tests.