The DiSCPersal model: A simple model for the small-scale atmospheric transport of spheroidal carbonaceous particles (SCPs).

Spheroidal carbonaceous particles (SCPs) are atmospherically mobile by-products of anthropogenic, high-temperature fossil fuel combustion. Since they are preserved in many geologic archives across the globe, SCPs have been identified as a potential marker for the onset of the Anthropocene. Our ability to reliably model the atmospheric dispersal of SCPs remains limited to coarse spatial scales (i.e., 102-103 km). We address this gap by developing the DiSCPersal model, a multi-iterative and kinematics-based model for dispersal of SCPs at local spatial scales (i.e., 10°-102 km). Although simple and limited by available measurements of SCPs, the model is nonetheless corroborated by empirical data of the spatial distribution of SCPs from Osaka, Japan. We find that particle diameter and injection height are the primary controls of dispersal distance, whereas particle density is of secondary importance. Further, stark differences in the modelled dispersal distances of SCPs between non-point vs. smokestack sources could explain the ambiguity of dispersal distances and the relative magnitude of long-range vs. localized sourcing of SCPs reported in the literature. This research underscores the need to incorporate understanding of the localized dispersal patterns of SCPs when interpreting their preservation in geologic archives. By extension, our findings have implications for the reliability of SCPs as a globally synchronous marker for the onset of the Anthropocene.

Sterols and sterol ratios to trace fecal contamination: pitfalls and potential solutions.

Fecal pollution in surface waters is a major threat to recreational and drinking water resources, with Escherichia coli being a primary concern. The best way to mitigate fecal pollutant loading is to identify the sources and tailor remediation strategies to reduce loading. Tracking E. coli back to its source is notoriously difficult in a mixed-use watershed where input from humans, wildlife, and livestock all contribute to E. coli loading. One proposed tracking method for E. coli contamination is the use of fecal sterols and sterol ratios. This study uses fecal sterol data published globally to assess how well sterol compositions for different species clusters along with the effectiveness of sterol ratios as tracking tools. Hierarchical cluster analysis produces stronger clusters based on sterol ratios than raw sterol concentration, but the global dataset results in clustering of the same species in different levels. The accuracy of the sterol ratios was also compared to understand the rate of false negatives and false positive assignments. Overall, these ratios did not have a high success rate for determining the correct source, which was also reflected in the poor clustering trends observed. Establishing local end-member sterol profiles is essential when using sterol signatures to unravel fecal loading.

Implications of regression bias for multi-element isotope analysis for environmental remediation.

Measuring changes in the stable isotope ratios of multiple elements (e.g. Δδ13C, Δδ37Cl, and Δδ2H) during the (bio)transformation of environmental contaminants has provided new insights into reaction mechanisms and tools to optimize remediation efforts. Dual-isotope analysis, wherein changes in one isotopic system are plotted against another (to derive an interpretational parameter expressed as Λ), is a key tool in multi-element isotopic assessment. To date, most dual-isotope analyses use ordinary linear regression (OLR) for the calculation, which can be subject to regression attenuation and thus an inherent artifact that depresses slope values, expressed as Λ. Here, a series of Monte Carlo simulations were constructed to represent common data conditions and variations within dual-isotope data to test the degree of bias when deriving Λ using OLR compared to an alternative regression technique, the York method. The degree of bias was quantified compared to the modeled or "true" Λ value. For all simulations, the York method provided the least bias in slope estimates (<1%) over all data conditions tested. In contrast, OLR produced unbiased estimates only under a limited set of conditions, which was validated through a mathematical model proof. Both the mathematical model and simulations show that bias of at least 5% in OLR occurs when the extent of enrichment in the x-variable (XM) is equal to or less than ≈15 times the 1σ precision in the isotope measurement (σX), for both Cl/C and C/H plots. The results give practitioners tools to evaluate whether bias is present in data and to estimate the extent to which this negatively impacts the interpretations and predictions of remediation potential for new and previously published datasets. This study demonstrates that integration of such robust statistical tools is essential for dual-isotope interpretations widely used in contaminant hydrogeology but relevant to other disciplines including environmental chemistry and ecology.

Multi-element (C, H, Cl, Br) stable isotope fractionation as a tool to investigate transformation processes for halogenated hydrocarbons.

Compound-specific isotope analysis (CSIA) is a powerful tool to evaluate transformation processes of halogenated compounds. Many halogenated hydrocarbons allow for multiple stable isotopic systems (C, H, Cl, Br) to be measured for a single compound. This has led to a large body of literature describing abiotic and biotic transformation pathways and reaction mechanisms for contaminants such as chlorinated alkenes and alkanes as well as brominated hydrocarbons. Here, the current literature is reviewed and a new compilation of Λ values for multi-isotopic systems for halogenated hydrocarbons is presented. Case studies of each compound class are discussed and thereby the current strengths of multi-element isotope analysis, continuing challenges, and gaps in our current knowledge are identified for practitioners of multi-element CSIA to address in the near future.

Sources of Uncertainty in Biotransformation Mechanistic Interpretations and Remediation Studies using CSIA.

Compound-specific isotope analysis (CSIA) is a powerful tool to understand the fate of organic contaminants. Using CSIA, the isotope ratios of multiple elements (δ13C, δ2H, δ37Cl, δ15N) can be measured for a compound. A dual-isotope plot of the changes in isotope ratios between two elements produces a slope, lambda (Λ), which can be instrumental for practitioners to identify transformation mechanisms. However, practices to calculate and report Λ and related uncertainty are not universal, leading to the potential for misinterpretations. Here, the most common methods are re-evaluated to provide the basis for a more accurate best-practice representation of Λ and its uncertainty. The popular regression technique, ordinary linear regression, can introduce mathematical bias. The York method, which incorporates error in both variables, better adapts to the wide set of data conditions observed for dual-isotope data. Importantly, the existing technique of distinguishing between Λs using the 95% confidence interval alone produces inconsistent results, whereas statistical hypothesis testing provides a more robust method to differentiate Λs. The propensity for Λ to overlap for a variety of conditions and mechanisms highlights the requirement for statistical justification when comparing data sets. Findings from this study emphasize the importance of this evaluation of best practice and provide recommendations for standardizing, calculating, and interpreting dual-isotope data.

New media for classical coordination chemistry: phase transfer of Werner and related polycations into highly nonpolar fluorous solvents.

Optimized procedures for the previously reported conversions of 1,3-diiodobenzene and perfluorohexyliodide (Rf6I; copper, DMSO, 140 °C) to 1,3-C6H4(Rf6)2 (3; 86-70%) and 3 to Br(3,5-C6H3(Rf6)2 (2; NBS, H2SO4/CF3CO2H; 88-75%) are described. The latter is converted (t-BuLi, BCl3) to the "fluorous BArf" salt NaB(3,5-C6H3(Rf6)2)4 (1 or NaBArf6; 77-70%), as given earlier. When orange aqueous solutions of [Co(en)3]Cl3 (en = ethylenediamine) are treated with perfluoro(methylcyclohexane) (PFMC) solutions of 1 (1:3 mol ratio), the aqueous phase decolorizes and [Co(en)3](BArf6)3 can be isolated from the fluorous phase (96%). Similar reactions with the trans-1,2-cyclohexanediamine analogue [Co(R,R-chxn)3]Cl3 and [Ru(bipy)3]Cl2 give [Co-(R,R-chxn)3](BArf6)3 (92%) and [Ru(bipy)3](BArf6)2 (95%). All of these salts are isolated as hydrates and exhibit toluene/PFMC partition coefficients of ≤1:≥99, establishing that the anion BArf6(-) can efficiently transport polar polycations into highly nonpolar fluorous phases. When equal volumes of CH2Cl2 and PFMC are charged with the "nonfluorous" BArf (B(3,5-C6H3-(CF3)2)4) salt [Co(en)3](BArf)3 and 3.0 equiv of the fluorous salt NaBArf6, the cobalt trication partitions predominantly into the fluorous phase (64:36). The arene 2 crystallizes in a polar space group (tetragonal, I4, Z = 8) with fluorous and nonfluorous domains and all eight bromine atoms located essentially on one face of the unit cell.