Regional and intercontinental modelling
Including historic trends, current and future scenarios, and impacts on air quality standards.
Local and urban scale modelling
Including the effects of building wakes, urban development scenarios, (green) urban infrastructures, and megacities.
Emission modelling and processing
Including emissions from ships and aircraft, temporal and spatial allocation of emissions, and projections related to climate change
Data assimilation and air quality forecasting
Including combining ground- and satellitebased observations with model outputs, use of data assimilation techniques to identify measurement needs.
Model assessment and verification
Including performance evaluation, diagnostic, dynamical, and probabilistic evaluation.
Aerosols in the atmosphere
Including aerosol dynamics, aerosol formation,interaction with multiphase chemistry, and aerosol-cloud interactions.
Modelling air pollution in a changing climate
Including effects of air pollution on climate and the impact of changing climate on future air quality.
Air quality effects on human health and ecology
Including integrated and multimedia modelling, atmospheric deposition and the effects of regulatory programs on ambient air quality and human exposure.
Machine learning and AI in air quality modelling
Use of machine learning algorithms and techniques to support, improve and speed up air pollution modelling.
