In this section
@article{Ojeda:2019:10.1021/acs.analchem.9b01756,
author = {Ojeda, AS and Phillips, E and Mancini, SA and Lollar, BS},
doi = {10.1021/acs.analchem.9b01756},
journal = {Anal Chem},
pages = {9147--9153},
title = {Sources of Uncertainty in Biotransformation Mechanistic Interpretations and Remediation Studies using CSIA.},
url = {http://dx.doi.org/10.1021/acs.analchem.9b01756},
volume = {91},
year = {2019}
}
TY - JOUR
AB - 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.
AU - Ojeda,AS
AU - Phillips,E
AU - Mancini,SA
AU - Lollar,BS
DO - 10.1021/acs.analchem.9b01756
EP - 9153
PY - 2019///
SP - 9147
TI - Sources of Uncertainty in Biotransformation Mechanistic Interpretations and Remediation Studies using CSIA.
T2 - Anal Chem
UR - http://dx.doi.org/10.1021/acs.analchem.9b01756
UR - https://www.ncbi.nlm.nih.gov/pubmed/31274296
VL - 91
ER -
Climate Science
Earth and Life Sciences
Energy and Low-Carbon Futures
Resources and Pollution
Economics and Finance
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