Quantification of PM 2.5 bound Polycyclic Aromatic Hydrocarbons (PAHs) and Modelling of Benzo[a]pyrene in the Ambient Air of Automobile Workshops in Benin City

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Abstract The activities of artisans conducted regularly in automobile workshops had been observed to generate pollutants that are not limited to particulate matter (PM), 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 and dry seasons using Apex2IS Casella standard pump fitted with conical inhalable sampling (CIS) head at a flow rate of 3.5L/min for 8 hours. Meteorological parameters were collected simultaneously with the PM2.5. PAHs were extracted and quantified using GC-FID. The annual average concentration of the total PAHs bounded to PM2.5 for NW, NE, SE and SW zones were 519.51 (638.78), 109.16 (169.16), 158.89 (178.40) and 77.65 (89.60) ng/m3for both wet and dry season respectively. A generalized linear model (GLiM) was used to develop a predicted 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 a reasonable accuracy of 60–72%.

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