To face the problem of harmful emissions in jet engine applications, the LPP combustor concept gained more importance during the last years. Them, being more prone to thermoacoustic instabilities, the need to predict them has become of primary importance. The purpose of this work is to provide support in the understanding of these phenomena, in particular experimental data regarding the influence of air instabilities on the produced spray. These experimental data can be used to develop and train machine learning algorithms that will be able to better predict those instabilities. Outcomes concerning the spray properties such as Sauter Mean Diameter, mean diameter, distributions, droplet velocities, volume flow, mass flux and number of droplets are shown.