The STEPS project aims to use new satellite measurements to detect and quantify emissions of carbon dioxide (CO₂) and nitrogen oxides (NO_x) from large point sources such as industrial plants and power plants. These pollutants contribute significantly to climate change and air pollution. The next generation of satellites will provide high-resolution images of CO₂ and NO₂ concentrations. In order to calculate reliable emission values from these images, STEPS is developing advanced methods based on mass balance techniques and machine learning. These methods are trained using realistic simulations that replicate satellite observations as accurately as possible. The resulting image library will be made publicly available and will provide a basis for the development and validation of models for determining emissions. The aim is to provide robust and scalable methods that can be used worldwide with future satellite missions to monitor emissions in near real time.

More than half of global CO₂ emissions come from point sources such as power plants and industrial facilities. Accurate monitoring of these sources is crucial for implementing international climate mitigation targets – such as those set out in the Paris Agreement – and for reducing air pollutants that are harmful to health. STEPS addresses key scientific challenges in satellite-based emission measurement. These include uncertainties in wind fields, the chemical conversion of NOx in the atmosphere and the transferability of simulation data to real satellite images. The methods developed will meet the high requirements for transparency, traceability and openness in accordance with the guidelines for open research data and will make an important contribution to international initiatives such as the Copernicus CO₂ Monitoring System and the WMO's Global Greenhouse Gas Watch.