Mars has a peculiar tendency, in one in every three Martian year, the entire planet is covered by dust suspended in the atmosphere. These events are referred as Global Dust Storms (GDS). The dust is lifted by fierce winds from the ground up to 80 km high. The mixture of water ice crystals and dust particle in the air of Mars change how the incoming Sun light warms the atmosphere. It is then of a crucial importance to properly characterize the nature and size of the aerosols, especially during a GDS, to better understand the dynamics of the Martian atmosphere. The spacecraft (ESA/Roscosmos) ExoMars Trace Gas Orbiter (TGO) has been studying the Martian atmosphere since April 2018 and observed a GDS but also other and less intense dust storms. These data help us distinguish the aerosols nature (dust and water ice) and sizes during these distinct types of dust events. Our study confirms that, globally, the particles of dust and water ice are quite small, close to 1micro-meter or even less. Their distribution varies a lot, meaning that one may find a lot of different particle sizes or lot of similar sized particles.

To understand the atmospheric evolution of a given air cell, one need to implement a complex set of chemical equation and try to solve this system. This is the work for a chemical solver. but, what if you want to quantify which sub-set of equation are of importance and for what chemical species. This is where the chemical pathways analysis comes into play. Initially based on the work of Lehmann, 2004 I develop a similar program in Python. Available on my Github repo