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Analytical Methodology for Monitoring and Distribution Pattern Analysis of Polycyclic Aromatic Hydrocarbons in River
Ebru Calkan Yıldırım1,2, Fusun Pelit1,2, Durmus Ozdemır3
1Faculty of Science Department of Chemistry, Ege University, Izmir, Türkiye.
None:
With the increase in urbanization and industrialization, the environmental quality of river basins, which serve as a crucial source of irrigation for agricultural activities, has been deteriorating progressively. Thus, monitoring persistent toxic substances in urban water resources is crucial for maintaining ecological stability and protecting human health. In recent years, particular attention has been directed toward the prevention of polyaromatic hydrocarbons (PAHs), highlighting the importance of analyzing these compounds in water samples through more environmentally sustainable techniques. In this study, we report a green, rapid, cost-effective and simple dispersive liquid-liquid extraction (DLLME) method to monitor PAHs in river waters taken from 21 stations located within the geographical boundaries of the Gediz River Basin in Izmir Province, Türkiye. Methodological parameters were optimized by chemometric techniques including Plackett-Burman (PBD) and Box-Behnken design. The method's accuracy was tested upon spiked river samples, and the recoveries ranged from 80% to 102%. The calibration curves were linear, with correlation coefficients greater than 0.98. The limit of detection values were between 0.01 and 0.05 ng mL-1. The reproducibility (RSD%) varied from 4.0% to 19%. Multivariate classification methods such as principal component analysis (PCA) and hierarchical cluster analysis (HCA), along with the supervised classification method partial least squares discriminant analysis (PLS-DA) were applied to elucidate the general distribution patterns of individual PAHs in the basin water samples. The chemometric evaluation conducted across four seasons revealed that PAH contamination was higher in the fall and winter months, resulting in a clear separation from spring and summer samples by using the first two principal components.
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