Solute rejection by porous thin film composite nanofiltration membranes at high feed water recoveries

The authors developed a rigorous framework to model nanofiltration (NF) membrane selectivity at high feed water recoveries and verify it experimentally. The phenomenological model and the Donnan steric partitioning pore model (DSPM) were incorporated into a differential element approach for predicting removal of a variety of solutes from single salt solutions and natural water by NF membranes up to 90% feed water recovery in the temperature range 5–41 °C. In this approach, the entire membrane ensemble was divided into numerous sub-elements analogous to real-world full-scale NF installations, where concentrate (or reject) from one element feeds into the next element. Fundamental membrane properties (average pore radius, surface charge density, and ratio of thickness to porosity) and the reflection coefficient and permeability coefficient were first independently obtained for each solute–membrane–temperature combination using separate low recovery experiments with negligible concentration polarization and later used as model inputs to calculate solute removal in a purely predictive fashion for 5–90% recovery. This modeling approach accurately predicted removals from single salt solutions of NaCl and MgSO4 as well as natural organic matter, disinfection by-product precursors, and several ions from pretreated Lake Houston water in a wide range of operating conditions demonstrating its use to simulate NF permeate water quality under real-world conditions of high feed water recovery.

The phenomenological model and the Donnan steric partitioning pore model were incorporated into a differential element approach for accurately predicting removal of a variety of solutes from single salt solutions and natural water by nanofiltration membranes up to 90% feed water recovery.Figure optionsDownload as PowerPoint slide