Fingerprinting of Compound-Specific Chlorine Isotopologue Distribution of Organochlorines by GC-HRMS

TL;DR

This paper presents a novel GC-HRMS method for measuring compound-specific chlorine isotopologue distributions in organochlorines, enabling improved source identification and apportionment with high precision and reliability.

Contribution

The study introduces a new high-resolution mass spectrometry technique for detailed isotopologue fingerprinting of organochlorines, enhancing source tracking capabilities.

Findings

Successfully detected complete chlorine isotopologues of organochlorines.

Achieved high precision with low standard deviations in measurements.

Differentiated sources based on isotopologue patterns with statistical significance.

Abstract

This study developed a method to measure compound-specific chlorine isotopologue distribution of organochlorines for source identification and apportionment. Complete chlorine isotopologues of individual model organochlorines were detected by gas chromatography-high resolution mass spectrometry (GC-HRMS). The measured relative abundances (RAmea), simulated relative abundances (RAsim), and relative variations between RAmea and RAsim (${\Delta}$RA) were obtained on basis of the detected MS signal intensities of individual isotopologues. The method has been partially validated in precision, injection-amount dependency and temporal drifts. The standard deviations (SDs) of RAmea of all istotopologues of perchlorethylene (PCE) and trichloroethylene (TCE) from different manufacturers were 0.002%-0.069%. The SDs of ${\Delta}$RA of the first three isotopologues of PCE and TCE from different manufacturers were 0.026%-0.155%. The ${\Delta}$RA and ${\Delta}$RA patterns of the standards of PCE and TCE from different manufacturers were able to be differentiated with statistical significance. The method has been successfully applied to an analogous case of source identification and apportionment for two trichlorodiphenyls that exhibited significant chlorine isotope fractionation on the GC-HRMS system. The results demonstrate that the ${\Delta}$RA in conjunction with isotope ratios can be applied to source identification and present high-validity identification outcomes. Moreover, the RAmea can be used to implement source apportionment for organochlorines from more sources with more reliable outcomes compared with the methods using isotope ratios only. This method opens a new way to perform fingerprinting analysis of compound-specific chlorine isotopologue distribution of organochlorines, and will be a promising high-performance approach in source delineation and apportionment for chlorinated organic compounds.