<p>Air particulate matter is linked to several health risks globally. Its sources are known to include industrial and vehicular emissions, biomass burning, and even the long-range transport of pollutant gases. Source apportionment studies are essential for accurately tracking sources and enabling effective mitigation. Common techniques of receptor modeling, such as Unmix, Chemical Mass Balance (CMB), and Positive Matrix Factorisation (PMF), have evolved, with increased reliability and accuracy. Recent advancements in modeling techniques, along with high-resolution measurements, have also been instrumental in enhancing the understanding of secondary aerosol formation. Despite these developments, challenges remain due to variations in source emissions, secondary atmospheric processes, and measurement uncertainties. This review examines recent advances in receptor modeling over the past decade. It also discusses their applications under different atmospheric conditions. Also, it highlights key research gaps that need to be addressed in future studies. Ongoing improvements in these models have made them more effective tools for policymaking and in the design of measures to reduce health risks linked to PM.</p> Graphical abstract