Multivariate statistical characterization of analytical methods for C₁₀-C₁₃ polychlorinated alkanes (PCAs) using...

Polychlorinated alkanes (PCAs) are persistent environmental pollutants with numerous congeners and homologues, making their analysis challenging. Among these, carbon chain length congener groups (i.e., C₁₀-C₁₃) can be analysed using both gas chromatography (GC) and liquid chromatography (LC), but differences in ionization methods between these techniques can introduce analytical biases. To address this issue, we reanalysed data from the earlier interlaboratory comparisons using a common quantification standard and applied multivariate statistical analysis to elucidate methodological differences. First, we characterized the common quantification standard across different ionization methods and identified its distinctive features. Subsequently, we extracted results from participating laboratories that employed identical analytical methods in the earlier interlaboratory comparison and conducted a multivariate statistical analysis. Our case study with limited analytical samples revealed that specific chain length congener and homologue groups are associated with different ionization techniques. Recognizing these homologue group patterns is crucial for accurate source identifications in environmental monitoring and appropriate estimations of key ecological factors such as biomagnification.