AI for Atmospheric Science

Molecules may aggregate into aerosols in the atmosphere. Such cluster formation affects air quality and the climate. We develop and apply artificial intelligence (AI) methods to model molecular processes in the atmosphere and to predict and understand molecular cluster formation. We are also developing digital twins of molecular processes and scientific instruments for a virtual laboratory in atmospheric science. The CEST group is part of the Virtual Laboratory for Molecular Level Atmospheric Transformations (VILMA) Centre of Excellence.

Predicting gas–particle partitioning coefficients of atmospheric molecules with machine learning, E. Lumiaro, M. Todorović, T. Kurten, H. Vehkamäki, and P. Rinke, Atmos. Chem. Phys. 21, 13227 (2021)