Aerosols are a significant component of the atmosphere. The full understanding of their effects on climate, air quality, and human health requires retrieving their microphysical properties. Studying these characteristics is fundamental to forecasting and minimizing aerosols' environmental impacts. This thesis represents the first attempt to retrieve range-resolved aerosol microphysical properties using lidar-only data at Universitat Politècnica de Catalunya. We undertake an investigation into the Basic Algorithm for REtrieval of Aerosol with Lidar (BOREAL), developed at the University of Lille, focusing on its applicability to common aerosols in the Mediterranean area, such as Saharan Dust. The algorithm's performance is assessed through an exploratory analysis that aims to explore the influence of various input parameters on its accuracy. Furthermore, the research compares BOREAL's results with those of an established inversion algorithm (AERONET), offering new insights into the retrieval process. These findings contribute to a deeper understanding of aerosol characterization and lay the framework for BOREAL's future use in aerosol studies.