Globally, drinking water sources are polluted with poly- and perfluoroalkyl substances (PFAS). The toxicity and persistent properties of these industrial chemicals raised concerns about environmental and public health. As a result, drinking water companies are removing PFAS from drinking water using separation technologies. Anion exchange and nanofiltration membranes have been proven to be effective drinking water treatment methods for the removal of PFAS. However, these drinking water technologies produce large volumes of PFAS-containing waste streams, which poses new challenges for the drinking water industry. To prevent toxic PFAS from re-entering the environment, these waste streams must be treated. This can be done by PFAS destruction, however, due to the large volumes of the waste streams, this is very expensive and energy-intensive. Therefore, concentrating the drinking water waste streams before destruction is desired. This research examined existing PFAS-concentration technologies and compared their PFAS removal efficiency, volume reduction, and cost-effectiveness in concentrating the PFAS waste streams produced during drinking water treatment. These waste streams include the concentrate of nanofiltration and the brine from anion exchange. The analysed concentration technologies are foam fractionation, adsorption of PFAS onto DEXSORB+ and all-silica BEA zeolites, and nanofiltration.
Foam fractionation removes PFAS from the waste stream by injecting air bubbles. Two laboratory setups were made for the injection mechanism of the air bubbles. First, by passing pressurized air through an air stone, and second, by adding pressurized water (i.e. white water) to the waste stream. The adsorbents were tested in the laboratory by conducting equilibrium batch experiments with different adsorbent dosages. The laboratory experiments were performed on both drinking water waste streams. The performance of concentrating the anion exchange brine solution with nanofiltration membranes was evaluated with the use of IMS Design models.