Our group completes its observational analysis with the use of models of different nature.

Modeling analysis plays an extremely important role in the study of atmospheric chemical composition, impact on human health and climate change, allowing to identify the most significant mechanisms of experimental observations.

At the Laboratory of Atmospheric Physics-Chemistry and Climatology of the University "G. d'Annunzio" Chieti-Pescara different mathematical models are used, based on different approaches and methodologies that allow to obtain complementary information. In particular, we use an extremely detailed box model (F0AM), developed by the group of Prof. Glenn Wolfe (UMBC, USA) and based on the complex chemical mechanisms of the MCM model created by the University of Leeds, to model the chemistry in place in a specific site and understand the dominant processes. At the same time, models based on machine learning, such as multiple regression or neural networks, are used to evaluate the relationship between different parameters (chemical and non-chemical), identifying the most significant ones for the description of the phenomenon under analysis.