Airborne particles affect the health of the population. As particles decrease in size, they can penetrate deeper into the respiratory system, reaching the terminal bronchioles and alveoli. Particles as small as 0.1 µm in diameter may translocate into the bloodstream, potentially impacting various organs. Additionally, the smaller the particle size, the longer they remain suspended in the air, thereby increasing their deleterious damages. The aim of this work is to study the size distribution of airborne particles emitted from anthropogenic sources of air pollution, with a special emphasis on estimating the distribution of micro and nanoparticles considered the most harmful to health. The Bidimensional Empirical Mode Decomposition (BEMD) algorithm was used on micrographs of the particles obtained by Scanning Electron Microscopy (SEM). BEMD is a current empirical computational tool applied to image analysis that allows extracting non-linear heterogeneous oscillations of brightness. We studied ROFA (Residual Oil Fly Ash) from industrial sources and DEP (Diesel Exhaust Particles) from vehicular emissions as airborne particles. After collecting the particles on filters, micrographs were taken using SEM at different magnifications to which the BEMD algorithm was applied. Particle size and asymmetry distributions were obtained for each mode, allowing the identification of the most deleterious particles. The methodology employed herein is relatively simple and effective for inferring the impact of airborne particulate matter on health and the environment.
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