TOPAS-CH4: a service for methane monitoring, source attribution and emission reduction over Europe

Methane (CH4) is the second-largest contributor to the anthropogenic greenhouse effect, and have been the focus of recent climate summits and global commitments towards emission reductions. To mitigate and study the impact of anthropogenic CH4 emissions, the European Union started AVENGERS, a research and innovation project funded under the Horizon Europe, with 13 Partners from 6 countries, whose objective is to reconcile reported greenhouse gasses (GHGs) emissions with independent information from atmospheric observations using top-down methods and process-based models, and thereby reduce the most important uncertainties of national emission inventories.

Here, we present TOPAS-CH4, an operational service developed by TNO as part of the AVENGERS project, following the example of a previous TNO source apportionment tool for particulate matter. This online public service provides users with the relevant daily information on CH4 concentrations over the EU countries, and how much different sources contribute to these observed  concentrations. TOPAS CH4 is based on the chemical transport model, LOTOS-EUROS, that runs daily to simulate source-labelled CH4 concentrations over Europe. The predicted CH4 concentrations are compared with the Integrated Carbon Observation System (ICOS) observations on a daily basis, showing that LOTOS-EUROS is able to realistically simulate the CH4 volume mixing ratios. Furthermore, the simulated CH4 concentrations are labelled per sector and country of emission, providing the users more insights about which European sectors and countries are mostly responsible for the additional CH4 concentrations above the background for a specific region. This information can be used to identify mitigation targets and, on the longer term, monitor changes in source contributions following successful abatement. We also show the comparison results for specific ICOS stations where the LOTOS-EUROS well matches the reported concentrations, as well as, locations where the model still performs poorly, finally providing some insights on how to improve the current simulation model.