Assessing Reliability of Non-targeted High-Resolution Mass Spectrometry Fingerprints for Quantitative Source Apportionment in Complex Matrices

Effective management of contaminated sites requires differentiating and deconvoluting contaminant source impacts in complex environmental systems. The existing source apportionment approaches that use targeted analyses of preselected indicator chemicals are limited whenever target analytes are below the detection limits or derived from multiple sources. However, non-targeted analyses that leverage high-resolution mass spectrometry (HRMS) yield rich datasets that deeply characterize sample-specific chemical compositions, providing additional potential end-members for source differentiation and apportionment. Previous work demonstrated that HRMS fingerprints can define sample uniqueness and support accurate, quantitative source concentration estimates. Here, using two aqueous film-forming foams as representative complex sources, we assessed the qualitative fidelity and quantitative accuracy of HRMS source fingerprints in increasingly complex background matrices. Across all matrices, HRMS-derived source concentration estimates were 0.81 ± 0.11-fold and 0.64 ± 0.24-fold of actual in samples impacted solely by analytical matrix effects (MEs) or by sample processing recovery and analytical MEs, respectively. Isotopic internal standards were not easily paired to individual unidentified non-target features, but bulk internal standard-based abundance corrections improved apportionment accuracy in higher matrix samples (to 0.90 ± 0.12-fold of actual) and/or informed concentration estimate relative errors. HRMS fingerprint mining could identify, based on the dilution behavior, effective individual chemical end-members across 16 homologous series. Although method development is needed, the results further demonstrate the potential applications of non-targeted HRMS data for source apportionment and other quantitative outcomes.受污染场地的有效管理，需要在复杂环境系统中区分并解析污染物源的影响。现有基于对预选指示性化学品进行靶向分析的源解析（source apportionment）方法，在目标分析物低于检测限或源自多类污染源时存在局限性。然而，借助高分辨质谱（high-resolution mass spectrometry, HRMS）的非靶向分析可生成丰富数据集，能够深入表征样品专属的化学组成，为源区分与源解析提供额外的潜在端元（end-members）。既往研究表明，HRMS指纹图谱可界定样品的独特性，并支持精准的定量源浓度估算。 本研究以两种水成膜泡沫作为典型复杂污染源，评估了HRMS源指纹图谱在日益复杂的背景基质中的定性保真度与定量准确性。 在所有基质中，仅受分析基质效应（matrix effects, MEs）影响的样品中，HRMS衍生的源浓度估算值为实际值的0.81±0.11倍；而同时受样品前处理回收率与分析基质效应影响的样品中，该估算值为实际值的0.64±0.24倍。 同位素内标难以与单个未识别的非靶向特征峰匹配，但基于整体内标的丰度校正可提升高基质样品中的源解析准确性（校正后估算值为实际值的0.90±0.12倍），并/或可辅助优化浓度估算的相对误差。 HRMS指纹图谱挖掘可基于稀释行为，在16个同系物系列中识别出有效的单一化学端元。尽管仍需开展方法学优化，但本研究结果进一步证明了非靶向HRMS数据在源解析及其他定量研究场景中的应用潜力。