Yes / Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCGA) based optimisation framework to optimise the design and operational parameters of the process. To provide a deeper insight of the process to the readers, the influences of membrane design parameters on dimethylphenol rejection, water recovery rate and the level of specific energy consumption of the process for two different sets of operating conditions are presented first which were achieved via simulation. The membrane parameters taken into consideration include membrane length, width and feed channel height. Finally, a multi-objective function is presented to optimise the membrane design parameters, dimethylphenol rejection and required energy consumption. Simulation results affirmed insignificant and significant impacts of membrane length and width on dimethylphenol rejection and specific energy consumption, respectively. However, these performance indicators are negatively influenced due to increasing the feed channel height. On the other hand, optimisation results generated an optimum removal of dimethylphenol at reduced specific energy consumption for a wide sets of inlet conditions. More importantly, the dimethylphenol rejection increased by around 2.51% to 98.72% compared to ordinary RO module measurements with a saving of around 20.6% of specific energy consumption.

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Reverse Osmosis (RO) filtration is capable of producing high quality drinking water with an ultra-low nutrient level. Therefore, a very low bacterial growth potential (BGP). BGP is a key bioassay to evaluate microbial quality and the biological stability of drinking water. Current methods to assess BGP in drinking water need to be adapted to the wide variety of water types due to results could highly vary from each, providing unreliable insights to the biological stability of the assessed water. This study evaluates the application of an FCM-based BGP assay for RO produced chlorinated drinking water. The approach combines (i) the standardization of a quenching agent concentration, (ii) the impact of sample pre-treatment such as filtration and pasteurization on the BGP of RO produced chlorinated water, (iii) the effect of different inoculums (an indigenous community and a mixture with bottled water) on the bacterial growth and their longevity after being stored, (iv) the use of BGP to assess the performance of carbon filters in removing chlorine and (v) the use of BGP to assess the effect of the addition of magnesium on bacterial growth. The results showed that high concentrations of sodium metabisulphite (> 7.5 mg/L) decrease the pH levels of the water,thus, inhibiting bacterial growth. Filtration had a significant effect on BGP values (2.62 x10^5 intact cells/mL) in comparison to pasteurization (9.02 x 10^4 intact cells/mL), when compared to the control. Using a mixture of water types as inoculum might provide a better insight to bacterial growth potential in water due to a higher consumption of nutrients. BGP demonstrated to be a sensitive tool to test the performance of carbonfilters applied to remove chlorine and its applicability to evaluate the biological stability of RO produced chlorinated drinking water. The concentrations of magnesium chloride tested in this study did not have a significant effect on cell numbers.

Yes / The use of Reverse Osmosis (RO) membrane processes for the clarification and the concentration of apple juice is proposed as an alternative to the conventional concentration technique, which is based on evaporation and freezing. Several models have been published on RO process models relying on different assumptions that predict the permeate flux and aroma compounds rejections for aqueous solutions apple juice. The solution-diffusion model (Lumped model) has been applied for the previous models. The main instrument of this study is the use of the gPROMS software to develop a new distributed steady state model that will relax a number of earlier assumptions. The model has been validated with an observational data of apple juice filtration derived from the literature by analysing the permeate flux and the performance of membrane rejection at different concentrations, temperatures and pressures for a laboratory scale of spiral-wound RO module. Simulated results corroborate with experimental and model predictions.

Yes / Reverse osmosis system has been widely used for the separation of organic and non-organic pollutants present in wastewater. The main aim of this study is to develop a one dimensional steady state model based on the three-parameter Spiegler-Kedem methodology using the gPROMS software and validate it by assessing the performance of membrane rejection for the separation data of aqueous solutions of phenol under different concentrations and pressures. Considerations of the variance of pressure, flow rate, solute concentration, solvent and solute fluxes and mass transfer coefficient along the feed channel were included in the model. Furthermore, an optimization methodology for the gEST parameter estimation tool has been developed in the gPROMS and used with experimental data in order to estimate the best values of the separation membrane parameters and the friction parameter. The simulation results of this model have been corroborated by experimental data.

Yes / Reverse osmosis (RO) has become a common method for treating wastewater and removing several harmful organic compounds because of its relative ease of use and reduced costs. Chlorophenol is a toxic compound for humans and can readily be found in the wastewater of a wide range of industries. Previous research in this area of work has already provided promising results in respect of the performance of an individual spiral wound RO process for removing chlorophenol from wastewater, but the associated removal rates have stayed stubbornly low. The literature has so far confirmed that the efficiency of eliminating chlorophenol from wastewater using a pilot-scale of an individual spiral wound RO process is around 83 %, compared to 97 % for dimethylphenol. This paper explores the potential of an alternative configuration of two-stage/two-pass RO process for improving such low chlorophenol rejection rates via simulation and optimisation. The operational optimisation carried out is enhanced by constraining the total recovery rate to a realistic value by varying the system operating parameters according to the allowable limits of the process. The results indicate that the proposed configuration has the potential to increase the rejection of chlorophenol by 12.4 % while achieving 40 % total water recovery at an energy consumption of 1.949 kWh/m³.

Yes / N-nitrosamine in wastewater treatment processes can contribute to several public health impacts including human carcinogens even at very low concentration. In this work, spiral-wound reverse osmosis (SWRO) process is used to remove N-nitrosamine compounds from wastewater. Effects of operating parameters of the SWRO process on the removal of N-nitrosamine, total water recovery, and specific energy consumption for a SWRO configurations are evaluated via simulation and optimisation. For this purpose, the one-dimensional distributed model developed earlier by the authors is modified by including different mass transfer coefficient correlation, temperature dependent water and solute permeability correlations and energy equations. The model is first validated by estimating a new set of model parameters using eight set of experimental data from the literature and is then used to simulate the process with and without energy recovery device to facilitate deeper insight of the effect of operating conditions on the process performance. The model is then embedded within an optimisation framework and optimisation problems to maximise N-nitrosamine rejections and to minimise specific energy consumption are formulated and solved while the operating conditions are optimized simultaneously.

Yes / Phenol and phenolic derivatives found in different industrial effluents are highly toxic and extremely harmful to human and the aquatic ecosystem. In the past, trickle bed reactor (TBR), reverse osmosis (RO) and other processes have been used to remove phenol from wastewater. However, each of these technologies has limitations in terms of the phenol concentration in the feed water and the efficiency of phenol rejection rate. In this work, an integrated hybrid TBR-RO process for removing high concentration phenol from wastewater is suggested and model-based simulation of the process is presented to evaluate the performance of the process. The models for both TBR and RO processes were independently validated against experimental data from the literature before coupling together to make the hybrid process. The results clearly show that the combined process significantly improves the rejection rate of phenol compared to that obtained via the individual processes.