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Abstract
The subject of studies was one-year-old needles of Scots pine (Pinus sylvestris L.), collected from various characteristic landscape zones of Poland, reflecting different conditions of air pollutant emission and deposition (Integrated Monitoring of the Natural Environment base stations, industrial centers, and large cities). Analyses were carried out using a Quanta 250 FEI scanning electron microscope equipped with an EDAX Genesis X-ray spectroscopy microanalyzer. The needle surfaces were examined to identify natural structures (e.g., stomata, pollen, fungi) and anthropogenic structures (e.g. particulates with heavy metals) under conditions of diversified anthropopressure. In samples from areas with no significant local pollution sources (Wigry, Borecka Forest, Parsęta, Tuchola Forest), particles of mineral origin (resulting from rock weathering) containing Si, Al, Ca were identified. Needles collected in Roztocze, Łysogóry, Kampinos and Karkonosze, contained round technogenic particles (spherules) containing Fe, Al and Si, which had traveled significant distances. In Katowice, Poznań and Kraków, particles deposited on the bioindicators’ surfaces were composed of Ca, Si, Al, Fe, Cu, and other heavy metals. Micrographs obtained from the analysis were used to develop a model for identifying air pollutants using artificial intelligence.
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