Quantification of PM2.5 Bound Polycyclic Aromatic Hydrocarbons (PAHs) and Modelling of Benzo[a]pyrene in the Ambient Air of Automobile Workshops in Benin City

The activities of artisans conducted regularly in automobile workshops have been observed to generate pollutants that are not limited to particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs). Thus, this research provided data on the quantification of PAHs coupled with the building of a predictive statistical model for the prediction of benzo[a]pyrene (BaP) in Benin City. The city was divided into four zones, namely North West (NW), North East (NE), South East (SE) and South West (SW), and a total of 180 representative samples were collected from artisans’ workshops in both wet (April to November) and dry (December to March) seasons using an Apex2IS Casella standard pump fitted with a conical inhalable sampling (CIS) head at a flow rate of 3.5L/min for 8 h. Meteorological parameters were collected simultaneously with the PM_2.5 (particles with an aerodynamic diameter of less than or equal to 2.5 µm)_. PAHs were extracted and quantified using Gas Chromatography (GC) fitted with a flame-ionization detection (FID). The annual average concentration of the total PAHs bound to PM_2.5 for the NW, NE, SE, and SW zone were 519.51 (638.78), 109.13 (169.16), 158.89 (178.40) and 77.65 (89.60) ng/m³ for both the wet and dry seasons, respectively. A generalized linear model (GLiM) was used to develop a prediction model for the prediction of (BaP) air concentrations in the NW zone. The results of the selected model among the five trained models obtained with data from NW sampling sites are R² = 0.792 and adjusted R² = 0.746 for model 1, with an overall p-value of 0.01. The proposed model established an approximation to estimate Benzo[a]pyrene (BaP) concentrations in the urban automobile workshops’ atmospheres with reasonable accuracy of 60–72%.