PeerJ (Sep 2023)
Essential role of multi-element data in interpreting elevated element concentrations in areas impacted by both natural and anthropogenic influences
Abstract
Background This article presents a detailed analysis of a dataset consisting of 27 elements found in soils, soil eluates, and vegetables from private gardens in a region with a long history of coal mining and burning. With coal being one of the world’s most significant energy sources, and previous studies highlighting elevated element levels in vegetables from this region, the objective of this study was to identify the factors that impact soil geochemistry and metal(loid) uptake in plants. Methods Total major and trace element concentrations were analyzed in soils, soil eluates and vegetables by high resolution inductively coupled plasma mass spectrometry. The vegetable samples included six species: fennel, garlic, lettuce, parsley, onion, and radicchio. Each plant was divided into roots, stems, leaves, and/or bulbs and analyzed separately. In addition, the soil pollution status, bioavailable fractions and transfer factors from soil and soil eluates to different plant parts were determined. Results The comprehensive dataset revealed that, apart from the substrate enriched with various elements (Al, As, Co, Cr, Mo, Ni, Pb, Sb, Sn, Ti, U, V, and Zn), other anthropogenic factors such as the legacy of coal mining and combustion activities, associated industries in the area, transport, and agricultural practices, also influence the elevated element concentrations (Cd, Cu, Fe, Mn, and Se) in locally grown vegetables. The transfer factors based on element concentrations in aqueous soil eluates and element bioavailable fractions confirmed to be an effective tool for evaluating metal uptake in plants, emphazising to some extent the effects of plant species and revealing unique patterns for each pollution source within its environmental context (e.g., Cd, Mo, S, and Se in this case). The study highlights the crucial importance of utilizing comprehensive datasets that encompass a multitude of factors when interpreting the impacts of element uptake in edible plants.
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