Characterisation and prediction of crystallisation fouling in reverse osmosis and nanofiltration membrane processes
Alhseinat, Emad Yousef Mahmoud
Membrane technologies are considered a promising solution for water scarcity in arid regions. However, fouling is a major challenge facing the application of membrane technologies. Fouling limits the economic viability and reduces the overall efficiency of membrane processes. Therefore, fouling mitigation is a crucial factor in spreading the use of membrane technologies for new applications. The first step in fouling mitigation is to predict the propensity of fouling. Unfortunately, there are immense limitations in current industrial practises for fouling propensity prediction. These limitations come from using outdated and inapplicable approaches, in which crucial assumptions are made. For example, in the case of crystallisation fouling or “scaling” one of the major simplifications is the use of pure scaling salt data to predict the propensity of scaling when, in reality, co-precipitation is present. This research work aims to introduce a new approach to systematic assessment of the fouling problem under real and complex conditions and to enhance understanding of the importance of including interactive effects and co-precipitation in the prediction of scaling propensity. In this research work a novel procedure accounting for the local variation of thermodynamic properties along a long membrane channel is proposed. A new approach considering ion interaction and process hydrodynamics for the prediction of the scaling propensity is then introduced. This new approach provides for the first time a completely theoretical assessment for pure salt scaling propensity along a full scale filtration channel without the use of any empirical constants. A new procedure for including the effect of co-precipitation on scaling propensity prediction is developed. The effect of process pressure on solubility products is included theoretically for the first time to enhance the accuracy of scaling propensity prediction during the full scale RO process. This research work helps to produce more reliable and accurate prediction of the onset of scaling which will help strategies to mitigate scaling and increase the overall efficiency of RO/NF processes. The new approach can be applied in practical situations and could be developed to a user-friendly programme able to give an accurate prediction of the fouling propensity in full scale processes allowing the optimisation of membrane processes accordingly. Moreover, comprehensive experimental work has been carried out during this PhD research work to enhance understanding of crystallisation fouling and coprecipitation. The effect of salinity and dissolved organics (DO) in CaSO4 and SrSO4 precipitation and co-precipitation are studied and discussed. Quantitative and qualitative thermodynamic and kinetic analyses combined with structural analyses of deposits are carried out to investigate the effect of salinity, DO presence and coprecipitation on SrSO4 and CaSO4 precipitation. The observations in this experimental study are very important for a deeper understanding of the effect of scaling salts’ coexistence, salinity and DO presence on the behaviour of the scaling salts. This is crucial to reaching a reliable prediction of the scaling propensity within RO/NF processes. Finally, the new developed approaches in this thesis have been validated using set of hydrodynamic tests. This set of tests has been carried out using a newly installed laboratory membrane rig. Moreover, a new technique to simulate full scale membrane processes is proposed using a laboratory membrane rig combined with the programs previously developed in this thesis. This new technique can be used to study the effect of process hydrodynamics on scaling and process performance of full scale membrane processes using a laboratory membrane rig. The outcomes of this research work can be used to investigate the optimal operating conditions and to guide design criteria for different RO/NF practical scenarios.