Concomitant evaluation of atmospheric levels of polychlorinated biphenyls, organochlorine pesticides, and polycyclic aromatic hydrocarbons in Strasbourg (France) using pine needle passive samplers

Al Dine, Enaam Jamal; Mokbel, Haifaa; Elmoll, Ahmad; Massemin, Sylvie; Vuilleumier, Stéphane; Toufaily, Joumana; Hanieh, Tayssir; Millet, Maurice

Concomitant evaluation of atmospheric levels of polychlorinated biphenyls, organochlorine pesticides, and polycyclic aromatic hydrocarbons in Strasbourg (France) using pine needle passive samplers

2015

In this study, pine needles were used as cost-effective and reliable passive bio-monitors to concomitantly evaluate atmospheric concentrations of three classes of persistent organic pollutants, polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), and polycyclic aromatic hydrocarbons (PAHs). The extraction of persistent organic pollutants (POPs) from needle samples was performed. Eleven PCBs, 11 OCPs, and 15 PAHs were detected and followed through time in needle samples from three sites in the Strasbourg region. The urban and rural sites were more exposed to PCBs than the suburban site. The highest concentration of PCBs was found at the urban site, but the largest number of congeners (10) was detected at the rural site. PCB 189 and 156 were the predominant congeners in the rural site and PCB 70 in the urban site. For OCPs, the rural site displayed the highest concentrations (up to 22.9 ng g⁻¹) and number of compounds investigated (9). The high concentration of γ- and β-hexachlorocyclohexane (HCH) at that time in the urban site was the reason for this result. γ- and β-HCH were the two predominant compounds in all samples. The suburban and urban sites were the most exposed with PAHs with pyrene, phenanthrene, and acenaphthene being the three predominant compounds in these sites. No specific trend in terms of time was apparent for PCBs and OCPs. However, higher concentrations were detected for some compounds in the first sampling, especially for PAHs, and this is attributed to variations in meteorological conditions (e.g., temperature, wind, rain) and variable inputs from both identified and unidentified sources.

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