Abstract

Fast and cost-effective detection of industrial pollution can significantly promote its ecological, economic, and social assessment. A magnetometric method, used for qualitative determination of anthropogenic contamination, meets these requirements but needs further development in more quantitative terms. It could be used successfully in numerous cases when the heavy metals coexist with strongly magnetic iron oxide particles in the source dust. We present an integrated magnetic and geochemical study that examines the utility of magnetometric techniques for rapid, qualitative detection of metallic pollutants in soils and vegetation. The new aspect of our approach, in comparison with previously published articles on this subject, is the combined investigation (magnetic and geochemical) of both soils and vegetation, thus using an additional medium for employing the magnetometry as a pollution proxy at a site. The study area is a small (approximately 3 km2) region in the suburbs of Sofia (Bulgaria), with the main pollution source being a metallurgical factory. Soil samples have been taken from the topmost 20 cm from private gardens, located at different distances from the factory. Vegetation samples were taken from ryegrass (both leaves and roots) and leaves from two kinds of deciduous trees (maple and acacia). The results show that both vegetation and soils are characterized by enhanced magnetic properties, compared to background material, which is due to the presence of magnetite particles of anthropogenic origin accompanying heavy metal emissions. SEM images and microprobe analyses reveal the presence of a significant amount of particles, containing heavy metals (including iron) in vegetation samples taken close to the main pollution source. Correlation analyses show a statistically significant link (correlation coefficients ranging from 0.6 to 0.7) between magnetic susceptibility and the main heavy metals (Cu, Zn, Pb) in soil samples, indicating that the magnetic susceptibility can provide a proxy method for identifying the relative contribution of industrial pollution in soils and vegetation, that is reliable, inexpensive, and less time-consuming than standard chemical analyses.

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