Marine mammals as global bioindicators of PFAS pollution: A review of advanced analytical methods and machine learning for source apportionment

Marine mammals have become critical bioindicators of global Per- and polyfluoroalkyl substances (PFAS) contamination due to their long lifespans, trophic positions, and transoceanic movements. Elevated PFAS burdens have been reported in several studies of Southern Hemisphere marine mammal species, despite the absence of large-scale local production. Such patterns likely reflect the combined influence of multiple processes, including inputs from regional activities, long-range oceanic transport, species-specific bioaccumulation, and current sampling constraints. We synthesize advances in extraction and analytical workflows, including Total Oxidizable Precursor (TOP) assay, Total Organic Fluorine (TOF) quantification, and high-resolution non-target screening, which expand the detectable PFAS spectrum. We further review recently published machine learning (ML)-enabled source apportionment approaches—such as Non-Negative Matrix Factorization (NMF) clustering, Principal Component Analysis (PCA)-Bayesian inference, and ionization efficiency prediction—which reconstruct complex PFAS mixtures and trace pollution origins. By linking oceanic transport processes with observed bioaccumulation patterns and computational analyses, we outline a unified monitoring framework that conceptualizes marine mammals as integrative chemical archives and early-warning indicators. The framework is intended to guide future PFAS surveillance and risk assessment, with its applicability shaped by ongoing advances in analytical standardization and data integration.