Multi-element Isotope Analysis Research Articles

Ⅰ-1. State-of-the-art technology for multi-element isotope analysis and application to fisheries research

Ⅰ-1. State-of-the-art technology for multi-element isotope analysis and application to fisheries research

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.

Coupling of a headspace autosampler with a programmed temperature vaporizer for stable carbon and hydrogen isotope analysis of volatile organic compounds at microgram per liter concentrations.

One major challenge for the environmental application of compound-specific stable isotope analysis (CSIA) is the necessity of efficient sample treatment methods, allowing isolation of a sufficient mass of organic contaminants needed for accurate measurement of the isotope ratios. Here, we present a novel preconcentration technique--the coupling of a headspace (HS) autosampler with a programmed temperature vaporizer (PTV)--for carbon (δ(13)C) and hydrogen (δ(2)H) isotope analysis of volatile organic compounds in water at concentrations of tens of micrograms per liter. The technique permits large-volume injection of headspace samples, maintaining the principle of simple static HS extraction. We developed the method for multielement isotope analysis (δ(13)C and δ(2)H) of methyl tert-butyl ether (MTBE), benzene, toluene, ethylbenzene, and o-xylene (BTEX), and analysis of δ(13)C for chlorinated benzenes and ethenes. Extraction and injection conditions were optimized for maximum sensitivity and minimum isotope effects. Injection of up to 5 mL of headspace sample from a 20 mL vial containing 13 mL of aqueous solution and 5 g of NaCl (10 min of incubation at 90 °C) resulted in accurate δ(13)C and δ(2)H values. The method detection limits (MDLs) for δ(13)C were from 2 to 60 μg/L (MTBE, BTEX, chlorinated ethenes, and benzenes) and 60-97 μg/L for δ(2)H (MTBE and BTEX). Overall, the HS-PTV technique is faster, simpler, isotope effect-free, and requires fewer treatment steps and less sample volume than other extraction techniques used for CSIA. The environmental applicability was proved by the analysis of groundwater samples containing BTEX and chlorinated contaminants at microgram per liter concentrations.

Current challenges in compound-specific stable isotope analysis of environmental organic contaminants

Compound-specific stable-isotope analysis (CSIA) has greatly facilitated assessment of sources and transformation processes of organic pollutants. Multielement isotope analysis is one of the most promising applications of CSIA because it even enables distinction of different transformation pathways. This review introduces the essential features of continuous-flow isotope-ratio mass spectrometry (IRMS) and highlights current challenges in environmental analysis as exemplified for the isotopes of nitrogen, hydrogen, chlorine, and oxygen. Strategies and recent advances to enable isotopic measurements of polar contaminants, for example pesticides or pharmaceuticals, are discussed with special emphasis on possible solutions for analysis of low concentrations of contaminants in environmental matrices. Finally, we discuss different levels of calibration and referencing and point out the urgent need for compound-specific isotope standards for gas chromatography-isotope-ratio mass spectrometry (GC-IRMS) of organic pollutants.

Isotope Discriminations Upon Biosynthesis in Natural Systems: General Causes and Individual Factors of the Different Bioelements

The global isotope abundance of natural organic compounds is determined by that of their precursors. A prerequisite for the formation of non-statistical intermolecular and intramolecular isotope distributions is the occurance of thermodynamic and kinetic isotope effects in irreversible and branched metabolic processes. This coincidence permits the interference of external factors like climatological conditions during biosynthesis, thus leading to corresponding modulations of isotope fractionations. The general principles of the in-vivo isotope discrimination are outlined and the individual properties of the different bioelements in this system are described. The results are discussed in regard to obtain maximum information about the origin and authenticity of a natural compound by multielement isotope analysis.