Seasonal Variation of (Benzo[a]Pyrene) in Ambient Air of Urban to Peri-urban Areas of Panvel Municipal Corporation, Raigad with Reference to Particulate Matter

Abstract

Polyaromatic Hydrocarbons (PAHs) in the environment have been linked to severe health effects. This study aims to assess the atmospheric pollutant and analyze the variation in PAHs, focussed on benzo[a]pyrene [B(a)P]. Among all PAHs, B(a)P is regarded as a marker for human carcinogenicity. This study reflects the B(a)P concentration and its correlation with the particulate matter (PM10 and PM2.5) in rural, peri-urban, and urban areas of Panvel Municipal Corporation, Maharashtra, India. Samples were collected during the pre & post-monsoon season for two consecutive years (Yr. 2020 and Yr. 2021). B(a)P level was determined using high-performance liquid chromatography coupled with a diode array detector. It was observed that PM2.5 and PM10 show a strong positive correlation (r=0.8-0.9) with B(a)P. It is observed that B(a)P concentrations were high in pre-monsoon w.r.t. post-monsoon, and this concentration increased spatially as we moved from rural to urban areas. Pre-monsoon B(a)P concentration varies somewhat by 5% between rural to urban areas as compared to post-monsoon. High levels of vehicular emissions and industry were associated with the distribution of B(a)P in urban areas, whereas a combination of local emissions and metropolitan area diffusion was responsible for the presence of B(a)P in peri-urban and rural areas. Also, this study captures the variation of B(a)P levels during the period of COVID-19. In future studies, Artificial Intelligence (AI) can augment the determination of PAHs in soil by improving the accuracy and speed of analysis using predictive modeling based on different input parameters to determine outliers in soil PAH data, building sensor networks for real-time monitoring of PAH levels, leverage robotics for automated sample preparations, and rapid testing of samples to identify hotspots.