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The metal concentrations and isotopic compositions (¹³C, ^207/206Pb) of urban dust, topsoil, and PM₁₀ samples were analyzed in a residential area near Donghae port, Korea, which is surrounded by various types of industrial factories and raw material stockpiled on empty land, to determine the contributions of the main pollution sources (i.e., Mn ore, Zn ore, cement, coal, coke, and topsoil). The metal concentrations of urban dust in the port and residential area were approximately 85~112 times higher (EF > 100) in comparison with the control area (EF < 2), especially the Mn and Zn ions, indicating they were mainly derived from anthropogenic source. These ions have been accumulating in urban dust for decades; furthermore, the concentration of PM₁₀ is seven times higher than that of the control area, which means that contamination is even present. The isotopic (¹³C, ^207/206Pb) values of the pollution sources were highly different, depending on the characteristics of each source: cement (−19.6‰, 0.8594‰), Zn ore (−24.3‰, 0.9175‰), coal (−23.6‰, 0.8369‰), coke (−27.0‰, 0.8739‰), Mn ore (−24.9‰, 0.9117‰), soil (−25.2‰, 0.7743‰). As a result of the evaluated contributions of pollution source on urban dust through the Iso-source and SIAR models using stable isotope ratios (¹³C, ^207/206Pb), we found that the largest contribution of Mn (20.4%) and Zn (20.3%) ions are derived from industrial factories and ore stockpiles on empty land (Mn and Zn). It is suggested that there is a significant influence of dust scattered by wind from raw material stockpiles, which are stacked near ports or factories. Therefore, there is evidence to support the idea that port activities affect the air quality of residence areas in a city. Our results may indicate that metal concentrations and their stable isotope compositions can predict environmental changes and act as a powerful tool to trace the past and present pollution history in complex contexts associated with peri-urban regions. Full article

This study used elemental and stable isotope composition to characterize Slovenian truffles and used multi-variate statistical analysis to classify truffles according to species and geographical origin. Despite the fact that the Slovenian truffles shared some similar characteristics with the samples originating from other countries, differences in the element concentrations suggest that respective truffle species may respond selectively to nutrients from a certain soil type under environmental and soil conditions. Cross-validation resulted in a 77% correct classification rate for determining the geographical origin and a 74% correct classification rate to discriminate between species. The critical parameters for geographical origin discriminations were Sr, Ba, V, Pb, Ni, Cr, Ba/Ca and Sr/Ca ratios, while from stable isotopes δ¹⁸O and δ¹³C values are the most important. The key variables that distinguish T. magnatum from other species are the levels of V and Zn and δ¹⁵N values. Tuber aestivum can be separated based on the levels of Ni, Cr, Mn, Mg, As, and Cu. This preliminary study indicates the possibility to differentiate truffles according to their variety and geographical origin and suggests widening the scope to include stable strontium isotopes. Full article