OSHIN, TAIWO TOYIN

Industrial activities contribute deeply to high emission rates of particulate matter (PM) and other pollutants into the ambient air. The siting of industrial plants in proximity to a populated area can have adverse effects on human health and the environment at large. The industrialization and urbanization of Sagamu city in Ogun state, has led to increased pressure on the city especially on air quality. The chemical complexity of airborne particles makes it necessary to consider their composition and sources of emission. This study was aimed at quantifying Fine particulate (PM2.5) and its heavy metals content in ambient air of industrial areas in Sagamu, Ogun state. The study locations of this research work were Ikorodu- Sagamu industrial area (majorly metal recycling industries) and Sagamu- Abeokuta interchange industrial area (majorly a mixed of Food, Agro￾allied and Brewery industries). The control site is located at Ode-lemo farm settlement in Sagamu, Ogun state. A total of 108 air samples of fine air particulate (PM2.5) were collected. Triplicate samples were collected each month with the aid of Conical Inhalable Sampling (CIS) head at a flowrate of 3.5Lmin-1 for 8hrs per day and for a period of one year. Meteorological data were collected simultaneously with PM2.5 via a specialised weather monitoring equipment (Automated Meteorological station). The PM2.5 filter papers collected were carefully sealed in a polythene bag and preserved prior to the laboratory for analysis. The PM2.5 mass concentration was computed gravimetrically. The loaded filters were subjected to acid digestion prior to analysis. Sixteen (16) metals were identified and quantified using Inductively Coupled Plasma- Optical Emission Spectrometer ICP-OES). Pollution indices such as Contamination factor (CF), Degree of contamination (DC) and Pollution index load (PLI) were assessed on the two industrial areas. Source identification and profiling of PM2.5- bound metals were determined using multivariate analysis which included Enrichment factor, inter-metallic correlation matrix, Principal component analysis (PCA) and Cluster analysis (CA). The two predictive models, Linear Regression Model (LRM) and Gamma Regression Model(GLM) were acquired and tested using the data produced from this work and a software tool R version 2024 which is user friendly.