Determining Contributions of Three Different Pathways to Total Degradation of a Contaminant Using Data From Triple-Element Isotope Analysis

The analysis of multi-elemental compound-specific stable isotope analysis (CSIA) has been established for the determination of contaminant degradation pathways. For systems with two pathways taking place simultaneously also a quantitative analysis of each pathway’s contribution to total degradation has been introduced using the combined information from the stable isotope fractionation of two elements. Recent experimental approaches also allow for the assessment of stable isotope fractionation of three different elements of a degraded compound, which would provide the opportunity to analyze systems with three simultaneously occurring degradation pathways using stable isotope data. Yet, approaches for a quantitative analysis of such systems are missing. Here we mathematically derive and present an approach to determine the contribution of three different degradation pathways to total degradation of a contaminant compound using the stable isotope fractionation of three different elements in the remaining compound. To verify the accuracy of the computational approach numerical simulations of virtual batch experiments were performed considering the degradation of a compound via three degradation pathways each leading to a stable isotope fractionation of three different elements. Applying the computational approach to the simulated concentration and stable isotope data allowed an exact determination of the contribution of the individual degradation pathways to total contaminant degradation regardless of the considered degradation rates. As application example we apply our approach to experimental data from the literature on the in-situ degradation of 2,4-DNT and the associated stable isotope fractionation of C, H and N. Calculated results of deoxygenation contributing 92%, partial reduction contributing 7% and CH₃-group oxidation contributing 1% to total degradation are in agreement with estimates presented in the literature. The new computational approach provides a novel tool for an improved analysis of multi-element CSIA data and for the quantitative assessment of contaminant degradation processes.