SRON researcher Ivar van der Velde has been awarded an NWO ENW-M grant to apply machine learning methods on carbon monoxide measurements from the Dutch satellite instrument TROPOMI.
The project aims to detect, quantify, and monitor carbon monoxide emissions from steel plants and urban areas worldwide. By applying advanced machine learning techniques, carbon monoxide plumes can be detected automatically and their emissions quantified. Carbon monoxide is a key tracer of air pollution and combustion-related greenhouse gas emissions. Unlike CO2, carbon monoxide has a much lower natural background concentration in the atmosphere, making emission-related plumes easier to see from space. This makes carbon monoxide an important tracer gas for identifying emission sources worldwide. It enables independent assessment of the effectiveness of emission reduction measures and compliance with environmental regulations in the steel industry.
