Landfill leachate is one of the major point sources of per- and polyfluoroalkyl substances (PFAS) pollution. In this study, powdered activated carbon (PAC), granular activated carbon (GAC), anion exchange resin (AIX), nanofiltration (NF), ozonation, and foam fractionation were tested for treatment of the same leachate.
These methods were compared in terms of PFAS removal efficiencies and treatment cost. More than 75% removal of long-chain PFAS (6-9 CF2) could be achieved with all the studied methods, though with high resource consumption. It was demonstrated that PFAS breakthrough was up to 27 times faster when the leachate was treated with GAC and AIX compared to groundwater treatment. Nanofiltration was the only method which could be practically applied for removal of PFAS with the shortest fluorinated carbon chain (3-4 CF2). Foam fractionation and AIX offered the most economical treatment, with an estimated cost of < 1 €/m3 for PFOS and PFOA reduction to ≥90%. The cost of treatment was shown to increase exponentially if the goal of > 60% ΣPFAS11 removal was applied. It was also discussed that composite parameters that include expected toxicity of different PFAS, such as ΣPFOAeq, should be used to obtain a cost-efficient reduction of PFAS-induced water toxicity.
Knowledge of exposure to a wide range of chemicals, and the spatio-temporal variability thereof, is urgently needed in the context of protecting and restoring aquatic ecosystems. This paper discusses a computational material flow analysis to predict the occurrence of thousands of man-made organic chemicals on a European scale, based on a novel temporally and spatially resolved modelling framework. The goal was to increase understanding of pressures by emerging chemicals and to complement surface water monitoring data. The ambition was to provide a first step towards a “real-life” mixture exposure situation accounting for as many chemicals as possible. Comparison of simulated concentrations and chemical monitoring data for 226 substance/basin combinations showed that the simulated concentrations were accurate on average. For 65% and 90% of substance/basin combinations the error was within one and two orders of magnitude respectively. An analysis of the relative importance of uncertainties revealed that inaccuracies in use volume or use type information contributed most to the error for individual substances. To resolve this, we suggest better registration of use types of industrial chemicals, investigation of presence/absence of industrial chemicals in wastewater and runoff samples and more scientific information exchange.