Asymmetrical contamination of anionic PFAS across global freshwater reservoirs

Freshwater reservoirs worldwide are increasingly threatened by contamination from anionic per- and polyfluoroalkyl substances (PFAS), yet the fragmented nature of existing data limits a comprehensive understanding of their distribution and sources. Here, we develop a workflow of Data compilation, Imputation approach, and Multiscale statistics (DIM) to synthesize and quantify anionic PFAS occurrence across spatial scales. By compiling sparse data from 813 samples across 74 reservoirs spanning five continents and applying a tested multiple imputation by chained equations-based method to construct an anionic PFAS concentration matrix, we identify three distinct contamination paradigms. Perfluorooctanoic acid (PFOA)-dominated paradigm typifies early-stage contamination linked to domestic and industrial discharges. PFOA and perfluorooctane sulfonate (PFOS)-co-dominated paradigm signals ongoing accumulation from mixed sources. Perfluorobutanoic acid (PFBA)-dominated paradigm reflects long-term buildup under partial abatement, driven by dry deposition, industrial inputs, and internal cycling. These paradigms reveal marked asymmetry in anionic PFAS contamination across global reservoirs, shaped by source dominance and contamination history. The DIM workflow enables data robustness and integrative reliability, providing a transparent framework for scale-aware monitoring and developing tailored PFAS management strategies that reflect the spatial heterogeneity and data limitations of reservoir contamination worldwide.