Atmospheric Modelling and Remote Sensing
Anthropogenic emissions from industry, traffic, households and agriculture affect air quality and contribute to globally increasing greenhouse gas concentrations. We aim to better understand processes governing atmospheric composition to answer environmentally pressing questions and to support policy makers.
Our group specializes in the application of Lagrangian and Eulerian atmospheric models and in trace gas remote sensing in order to
- Quantify emissions of greenhouse gases using inverse methods
- Simulate the effect of sources and future scenarios on air pollution levels
- Understand atmospheric processes including transport and chemistry
- Investigate atmospheric composition using satellite and airborne remote sensing
Modelling of greenhouse gases and their sources
Quantifying current and past greenhouse gas emissions is of fundamental importance to understand future climate change. Our group applies atmospheric inversion techniques at regional to the global scale combining observations with Lagrangian Particle Dispersion Modelling (LPDM). Inverse emission estimates help improve our understanding of natural source processes and can be used to check compliance with current and future anthropogenic emission regulations. Read more on
Air pollution and urban modelling
Air pollution is a multifaceted problem involving many different pollutants, scales, processes and sources. We apply state-of-the-art numerical models to study air quality at regional to urban scales to provide guidance for policy makers and input for environmental assessments. Our main tools are the chemistry-meteorology models COSMO-ART and ICON for regional scales and the nested system GRAMM/GRAL for urban and building-resolving scales.
Satellite remote sensing has revolutionized our understanding of the distribution and sources of air pollutants and greenhouse gases. We develop retrieval algorithms for trace gas remote sensing from satellites and airborne platforms and specialize in the analysis of air pollution distributions at regional to urban scales. We also support the development of new satellite instruments with observing system simulation experiments.