Data Assimilation in Modern Atmospheric Quality Forecasting Models

The paper analyzes the modern estimating and forecasting air quality mathematical models for building maps of high spatial-temporal resolution. The tasks that must be solved in the future to control air pollution effects are outlined. The emphasis is on the need to assimilate heterogeneous data, including low accuracy, to improve the models' quality.