Atmospheric Particulate Matter Chemical Composition and Source Identification in Aba Industrial Zone, Abia State, South East Nigeria

Industrial emissions, traffic exhaust, open burning, and dust re-suspension from unpaved surfaces contribute complex particulate matter mixtures to the atmosphere of industrial cities in South East Nigeria, yet receptor modelling-based source identification studies remain sparse for this geopolitical zone. This study characterises the chemical composition of PM2.5 and PM10 particles collected at five sampling sites in the Aba industrial zone, Abia State, South East Nigeria, and applies receptor modelling to identify dominant pollution sources. Particulate matter is collected on pre-weighed Teflon and quartz fibre filters using cascade impactors and sampled gravimetrically. Chemical analysis of filter extracts by inductively coupled plasma mass spectrometry determines concentrations of trace elements including aluminium, silicon, calcium, iron, titanium, manganese, lead, zinc, chromium, copper, and nickel. Water-soluble ionic species including sulphate, nitrate, chloride, ammonium, sodium, and potassium are measured by ion chromatography. Organic carbon and elemental carbon fractions are determined by thermal-optical reflectance. Positive matrix factorisation receptor modelling is applied to the full chemical dataset to resolve source profiles and quantify source contributions. Five source factors are anticipated: secondary sulphate, traffic exhaust, crustal dust, industrial metal emissions, and biomass burning. Seasonal source contribution profiles are calculated for both wet and dry sampling periods. Findings provide the first comprehensive receptor modelling-based source apportionment study for PM in the Aba industrial zone, supporting evidence-based emission reduction strategies in the South East geopolitical zone. Keywords: particulate matter, source apportionment, positive matrix factorisation, Aba, atmospheric chemistry