Simulation of Greenhouse Gases in the Atmosphere (Vardag - Group) Research topics

Greenhouse gas concentrations are influenced by both meteorology and greenhouse gas sources and sinks. Therefore, it is essential to simulate the meteorological transport of gases in order to study these sources and sinks and to quantify natural and anthropogenic emissions. Depending on the application, we use both Eulerian and Lagrangian models. Eulerian models operate on a fixed grid and simulate entire concentration fields, whereas Lagrangian models track individual air masses to better understand their composition.

To quantify emissions, we use inverse estimation methods such as Bayesian inversion, in which the differences between observations and model results are minimized—taking all uncertainties into account—by appropriately scaling the emissions. For example, satellite data can be used to study CO₂ emissions on a continental scale to better understand natural processes. Inverse estimation methods can also support the design of measurement networks tailored to specific objectives—such as optimizing the detection of anthropogenic emissions from urban areas. This is a goal of the "Integrated Greenhouse Gas Monitoring System" (ITMS) project, as well as the "University Network for CO₂ in the Rhine-Neckar Metropolitan Area" (UNICORN), which is establishing a CO₂ monitoring network in Heidelberg and Mannheim.

The resulting information on greenhouse gas emissions can be used for independent verification in the spirit of the Paris Agreement. At the same time, the data can also serve as an incentive for individuals, political stakeholders, or companies to reduce their emissions. The social, political, and economic aspects involved are being explored in the HCE project “Climate-Life-Nexus.”