Separation of organic pollutants by reverse osmosis and nanofiltration membranes: Mathematical models and experimental verification

Predictive reverse osmosis (RO) models have been well-developed for many systems. However, the applications to dilute organic-water systems require the modification of transport models and the understanding of solute-polymer interactions. Studies with various substituted, nonionized phenolic compounds showed that these could cause substantial membrane water flux drop, even in dilute solutions with negligible osmotic pressure. Further, the organics could significantly adsorb on the cross-linked aromatic polyamide active layer. In some cases, even concentrations as low as 0.2 mM, 2,4-dinitrophenol (solution in particle-free, double-distilled water) can cause as much as a 70% flux drop with an aromatic polyamide membrane. Two models are presented in this paper: a modified steady-state solution diffusion model and an unsteady-state diffusion adsorption model which are able to predict flux and permeate concentrations from a single RO experiment. Further, the development of these models allows for the understanding of the mechanisms of organic-membrane interactions; For instance, it has been proposed that increased adsorption inherently leads to an increase in flux drop. However, we have found, on one hand, that due to specific interactions with membrane water transport groups, chloro- and nitro-substituted phenols cause significant flux drops. On the other hand, benzene had a high physical adsorption but caused negligible flux drop. The results were further extended to nanofiltration experiments with an aromatic pollutant containing two types of charge groups. The adsorption and separation results are explained according to an ionization model.