Long-term characterisation and discrimination of aerosol types across Africa using AERONET observations (1998–2024

Abstract

Accurate identification and classification of atmospheric aerosols remain a significant challenge across Africa, limiting the precise assessment of their climatic effects. This study presents a comprehensive analysis of aerosol characteristics and aerosol types using ground-based observations from twelve selected AErosol RObotic NETwork (AERONET) sites across Africa during 1998–2024. Key aerosol optical properties, including aerosol optical depth (AOD), Ångstr¨ om exponent (AE), fine-mode fraction (FMF), and single scattering albedo (SSA), were examined to characterize their temporal variability and identify dominant aerosol types. A multivariate scattering-based classification approach was employed to improve aerosol discrimination. The results indicate that dust, biomass-burning, and urban/industrial aerosols are the predominant aerosol categories across the continent. Fine- and coarse-mode absorbing aerosols were particularly prevalent in rural tropical regions, highlighting the coexistence of natural and anthropogenic emission sources. Moreover, extensive biomass- burning activity in tropical Africa contributes substantially to regional aerosol loading and complexity. These findings provide valuable insights for improving the representation of aerosol processes in climate models and enhancing assessments of aerosol–climate interactions over Africa. The proposed multivariate framework advances aerosol classification and source attribution, supporting a better understanding of aerosol-related environmental and climatic impacts across the continent.