Use of nanofiltration predictive model for membrane selection and system cost assessment

In this paper, a predictive model based on the Donnan-Steric-Pore model (DSPM) has been used to develop general criteria for selection of optimum nanofiltration (NF) membranes and to analyse the effect of various nanofiltration membrane characteristics on the cost of NF membrane system. By using an economic assessment model for NF processes, the two most important factors determining the performance of NF membranes which are λ (the ratio of solute radius and membrane pore radius) and ζ (the ratio of membrane charge effective density to bulk concentration) were examined. The optimal conditions for minimum operation cost and optimal operating pressure were also determined. Detailed cost analysis reveals both capital and operating cost were not affected by the variation of ζ. However, decreasing the membrane pore size will increase costs. It was found that up to 30% of the capital and operating costs in recovering sodium sulphate solution can be saved by using looser membrane compared to the tight membrane structure.