Original Methodology for Source Apportionment of Atmospheric Particulate Matter in Nigerian Urban Environments Using Receptor Modelling

The chemical characterisation and source attribution of atmospheric particulate matter in Nigerian cities is essential for evidence-based air quality management, yet existing source apportionment studies are scarce and methodologically limited in the Nigerian urban context. This study developed and applied an original receptor modelling methodology for source apportionment of PM2.5 in three geographically distinct Nigerian urban environments: Lagos in South West, Kano in North West, and Port Harcourt in South South, capturing the diverse emission source signatures of coastal industrial, savanna dust, and urban industrial environments. A comprehensive 12-month monitoring programme was conducted, generating a unique dataset of daily PM2.5 mass concentrations and elemental, ionic, and carbonaceous chemical speciation data from each city. Receptor model analysis was performed using Positive Matrix Factorisation with uncertainty estimation, conditional probability function angular analysis, and backward trajectory clustering using HYSPLIT. An original multi-city comparative analysis methodology was developed that accounts for spatially varying background contributions and uses cross-city chemical fingerprinting to differentiate local from regional sources. In Lagos, traffic emissions, marine aerosol, and biomass burning were identified as dominant sources. In Kano, Saharan dust contributions were substantial, accounting for up to 68 percent of PM2.5 mass during harmattan periods. In Port Harcourt, petroleum industry emissions and shipping contributions were uniquely characterised. The original multi-city receptor modelling framework developed constitutes a methodological advance in African atmospheric science and provides actionable source-specific emission control targets for the Nigerian environmental management authority.

Keywords: receptor modelling, source apportionment, PM2.5, Positive Matrix Factorisation, Nigerian urban air quality