Jong-Hyun Kim, Hae-Woon Choi
Aerosols play critical roles in atmospheric chemistry, climate regulation, industrial processes, and public health, necessitating accurate and real-time characterization of their physicochemical properties. This review presents a comprehensive overview of photonics-based diagnostic methods, with a particular emphasis on Laser-Induced Breakdown Spectroscopy (LIBS), for aerosol analysis. We examine the underlying principles of LIBS, including plasma generation, laser–particle interactions, and spectroscopic emission processes, alongside recent developments in single-particle and standoff detection. The integration of LIBS with optical trapping, Raman spectroscopy, and laser-induced fluorescence (LIF) is discussed as a strategy to enhance selectivity, sensitivity, and species identification. Moreover, we explore the role of machine learning and chemometric algorithms in improving data interpretation and automated aerosol classification. Applications spanning environmental monitoring, biomedical diagnostics, industrial emission control, and planetary exploration are highlighted. Finally, we address current limitations such as matrix effects, calibration challenges, and sensitivity constraints, and propose future directions for the development of compact, multi-modal, and AI-enhanced LIBS systems for advanced aerosol diagnostics.