PFAS-selective single-use ion exchange resin is now a proven and cost-effective method for the removal of PFAS from water. While piloting can help assure reliable performance, several months to years are generally needed for completion due to the high operating capacity of such resins. Ironically, this results in intolerable delays in the planning and implementation of cleanup measures. Fortunately, modeling of trace contaminant removal with single-use ion exchange resin has been used successfully for at least two decades for perchlorate and chromate and indeed is the preferred alternative to piloting as resin vendors are confident enough to provide throughput guarantees based on modeling. Similar modeling software is now being used to predict breakthrough curves and operating capacities for a variety of PFAS commonly found in drinking water.<br/>In this presentation, we compare PFAS modeling versus piloting for a variety of different water chemistries and we conclude that such modeling exhibits a high degree of correlation with actual pilot results. We demonstrate how using such software is beneficial in predicting relative performance and operating cost of various treatment plant designs such as using a single ion exchange vessel, or a lead-lag pair of vessels in series, or three vessels in series (lead-lag-polisher). While piloting will by design demonstrate performance for the specific water chemistry encountered during piloting, reliable simulation software can instead be used to predict performance for a wider envelope of scenarios such as for the maximum, minimum, and average water qualities expected. Plant operators can therefore have much greater confidence in forecasting their O&M cost for cleanup. We conclude that ion exchange modeling is a valuable decision-making tool that allows plant operators, consultants, and regulators to quickly compare the merits of ion exchange versus alternative technologies.

Modeling PFAS removal by selective ion-exchange resins vs piloting: Reliable O&M cost estimates for cleanup

ACS Spring 2022

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