Quantification of Pb pollution sources in complex urban environments through a multi-source isotope mixing model based on Pb isotopes in lichens and road sediment

Despite a growing focus on anthropogenic toxic metal pollution in urban environments, few studies have addressed the problem of quantification when more than two pollution sources are likely present, particularly within complex urban settings in the United States (U.S.). In this study, we utilize the MixSIAR package in R for source apportionment based on Pb isotopic signatures in lichen and road sediment in two urban-industrial centers in SW Ohio (OH). We show that ranges of pollutant contributions are more useful than only visualizing mean or raw values of source apportionment, because this avoids overinterpretation of data when certain sources have a large range of uncertainty. We point out both the dominance of industrial pollution as well as the legacy of leaded gasoline pollution in typical mid-sized U.S. cities, which is evident in both road sediment and lichens. Leaded gasoline contribution to Pb in Middletown, OH lichens mostly vary between ~10 and 25%, while in Hamilton, OH the contribution to lichens and road sediment tends to be relatively negligible except for two road sediment samples and one lichen sample, where median contributions are ~20–30%. Industrial combustion pollution source contributions vary between ~25 and 75% in Hamilton, and ~50–100% in Middletown, OH. Furthermore, comparing pollution sources in lichens to modern particulate matter can provide a record of how pollutant sources change over time, such as our traffic lichen (Sample Li-9) plotting closer to leaded gasoline on a bivariate mixing diagram than modern traffic particulate matter, or our coke plant lichen containing slightly less Pb contribution from industrial combustion sources relative to modern coke plant particulate matter. Lastly, when applicable, multi-source mixing models should be complimented in future studies with additional isotopic source tracers such as Cu, Zn, Nd, and Os to further elucidate unique sources of metal pollutants in addition to Pb.