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Spatial and Seasonal Abundance of Microplastics in Sand and Aqueous Matrices from Coastal Areas of Northern Greece
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Researchers collected and analyzed microplastics from wastewater effluents, beach sand, and seawater in Northern Greece over one year to capture seasonal variation. MP abundance varied seasonally, with higher concentrations in summer months likely linked to increased tourism and beach activity.
This study provides comprehensive information on the abundance of microplastics (MPs) in wastewater effluents, sand, and seawater samples collected from areas in Northern Greece. Sampling was conducted over a one-year period to account for seasonal variations in MP abundance. The collected samples were analyzed using microscopic and spectroscopic techniques, yielding valuable insights into the physicochemical characteristics of MPs. MPs concentrations in sand samples ranged from 15.5 ± 6.2 to 174.7 ± 17.3 items kg of dry sand, while the highest concentrations were recorded in winter. Among aqueous matrices, the highest MP concentrations were found in wastewater effluents, ranging from 0.43 ± 0.17 to 1.72 ± 0.45 items L, with greater loads detected during wet seasons. In seawater samples, MP abundance ranged from 0.078 ± 0.011 to 0.989 ± 0.35 items m, with the highest concentrations recorded during the summer season. Regarding polymer identification, the analysis of MPs was conducted using micro-FTIR instrumentation, and the most frequently detected polymers in the examined samples were PE (poly(ethylene), PP (polypropylene), PET (poly(ethylene terephthalate)), and PA (polyamide). Morphological analysis revealed that fibers were the dominant MP shape across all matrices. Size distribution analysis indicated that most MPs particles were small-sized (< 1 mm). The morphological and chemical characteristics of MPs indicate strong links among matrices. SEM-EDX analysis revealed metals on MPs from sand samples, reinforcing these connections. This study investigates MP abundance across environments, uncovering their sources, inter-matrix relationships, and interactions with pollutants, offering insights into patterns of environmental contamination.
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