Stochastic assessment of groundwater PFAS concentrations in North-Eastern Italy

Per- and poly-fluoroalkyl substances (PFAS) and in particular their perfluoroalkyl acids (PFAA), are among the most concerning sources of groundwater pollution, due to their persistence and to their negative effects on human health. Since 2013 the Regional Agency for Environmental Protection of the Veneto Region (North-Eastern Italy) systematically monitors groundwater PFAA concentrations at water-supply wells. The present work is the first stochastic assessment, based on real data, of spatially distributed hazardous areas ever made for this territory. A geostatistical variogram-based approach has been employed to appraise the spatial correlation of quality data, and stochastically simulated concentrations at a scale of 1 km2, through Sequential Gaussian Simulations. The results have been evaluated upon multiple hazardousness criteria, coming from exceeding threshold concentrations provided by the latest regulations defined by (i) the European Union, (ii) the United States Environmental Protection Agency (USEPA), and (iii) the Veneto Region (Italy). Simulations’ results enabled the evaluation of best-estimated concentration spreads and the probability of exceeding EU, EPA, or Veneto Region limits. Moreover, the role of these regulation limits in delineating the spatial extension of probable over-threshold groundwater contaminated areas was evaluated. Only Verona and Vicenza provinces, located within the Adige and Brenta river basins, significantly exceed regulatory limits. Particularly high PFAA concentrations ​​are estimated to occur in the aquifers underlying the medium-high reaches of the Adige, Brenta, and Agno-Guà-Frassine-Gorzone rivers. The soundness of the results and the methodological approach was supported by demonstrating the consistency of widespread contamination across the domain with groundwater flow directions inferred from the most recent numerical model available. This work provides an example of how to deal with PFAA groundwater contamination from a stochastic and probabilistic perspective through geostatistics and to spatially appraise groundwater contamination leveraging available data.