Water desalination by forward osmosis: Dynamic performance assessment and experimental validation using MgCl2 and NaCl as draw solutes

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Highlights

  • ▪ A forward osmosis dynamic model originally developed for acid concentration has been adapted to water desalination using two draw solutes, MgCl2 and NaCl.

  • ▪ The FO dynamic model performances are assessed using experimental data obtained via a test bench using both NaCl and MgCl2.

  • ▪ NaCl and MgCl2 have been compared in terms of osmotic performance through the average overtime of the specific reverse solute flux.

  • ▪ The influence of the draw solute concentration on the water and reverse solute flux has been dynamically evaluated.

Abstract

Although the FO process steady state performance has been extensively investigated, there is a huge gap in forward osmosis dynamic studies especially for water desalination applications. In this paper, an appropriate dynamic model was developed based on the phenomena involved in the FO process. For its validation, an experimental study was carried out using a FO test bench and flat-sheet membrane for two draw solutes (MgCl2 and NaCl), to measure the water flux, Jw, and the reverse solute flux (RSF), Js. The time evolution of these two experimentally obtained fluxes were compared to those calculated using a dynamic model developed using Python language for both draw solute. This comparison shows that the mean absolute error did not exceed 5.25% for water flux and 5.63% for RSF. The dynamic model can thus be considered reliable when considering experimental errors. The resulting model can thus analyze the influence of the initial draw solute (DS) concentration on both water flux and reverse solute flux dynamics, and subsequently compare the osmotic performances of MgCl2 and NaCl based on the specific RSF ratio. The water flux obtained with MgCl2 is on average 8.23% lower than for NaCl. MgCl2 nevertheless performed better in terms of reverse solute flux and has been demonstrated to be 28.87% lower than NaCl. The calculated specific RSF ratio is shown to be independent of both time and DS concentration.

Introduction

Among the various membrane desalination technologies under development, forward osmosis (FO) has emerged as an important technology for desalination of brackish water (Shaffer et al., 2015). This is mainly due to its promising low energy consumption (Zhou et al., 2015), interesting water flux (Chakrabortty et al., 2015; Lee et al., 2018) and low fouling rate (Lee et al., 2020). It is also considered in the food processing industry as a promising technology for concentrating products (Chen et al., 2019). Many constraints are however related to the performances of the membrane and the draw solute, the main components of this process. These constraints limit the large-scale industrialization of this technology (Su et al., 2013; Cai and Hu, 2016). A good draw solution should exhibit a high osmotic pressure, be easily recoverable with low energy consumed and be nontoxic (Johnson et al., 2018). On the other hand, a good membrane for industrial FO applications should be highly selective for salts, highly permeable to water, have a minimum reverse solute flux (RSF) and insensitive to pH. All these criteria can be summarized into the structural parameter Sof the membrane. This parameter depends in fact on the thickness of the membrane support layer dL, its tortuosity τ and its porosity ɛ, and is given by Deshmukh et al. (2015) as S=τdL/ε. A forward osmosis membrane is thus considered more efficient when its structural parameter is low. This can be attained through a low support layer thickness, less tortuosity and high permeability to water while having a low permeability to reverse solute. Another challenge for FO is the lack of a suitable nontoxic and thermally separable draw solution. This also hinders the development and commercialization of forward osmosis separation units (Cai and Hu, 2016; Field and Wu, 2013; Qasim et al., 2017).

The dilutive internal concentration polarization (ICP) and concentrative external concentration polarization (ECP) are major factors reducing the osmotic pressure difference between the two sides of the membrane (Field and Wu, 2018; Nagy, 2019; Tan and Ng, 2008). As this driving force is reduced, a significant decrease in the water flux is observed (McCutcheon and Elimelech, 2006). In order to predict the effect of the concentration polarization and attenuate its effect on water flux, many studies have been carried out (Tan and Ng, 2008; Gao et al., 2014; Arjmandi et al., 2020). The FO process performance has been significantly improved through optimizing the thickness of the support layer of the membrane based on different membrane manufacturing methods and new improved DS.

Many modeling and simulation studies of forward osmosis process have been carried out to assess the water flux and reverse solute flux. Simulations were performed, using steady state models based on transport phenomena (Su et al., 2013; Li et al., 2017; Kim et al., 2017). These models were mainly focused on the three aforementioned parameters of the membrane. In most modeling work, the three parameters are determined through experiment using NaCl or NH4Cl as draw solution, with the help of non-linear least-square algorithm to estimate values of the water permeability coefficient A, the salt back-diffusion coefficient B and the membrane structural parameter S while minimizing the error between the measured and predicted water flux. Among the commonly used models, the one developed by Tiraferri et al. (2013) seems the most realistic one. Although the FO steady state performances have been extensively investigated, only a few studies have been conducted to investigate water and solute transport dynamic behavior. Assessing the impact of draw solution type on the FO performance over time could be of great importance for enhancing water quantity and quality production using FO. To extend the use of FO technology to water desalination, the influence on the water and reverse solute flux dynamics of the draw solution performance (i.e. osmotic pressure) and of its concentration and temperature on both sides of the membrane is highly critical. This should thus be carefully taken into account in order to drive FO application to a mature stage in water desalination.

In the present work, a brief literature review of the FO process dynamic studies is carried out, followed by the development of a FO dynamic model for water desalination applications based on existing models. The dynamic model reliability is assessed using data obtained during 30 h of operation for experiments performed with two DS, namely MgCl2 and NaCl. The aforementioned model is used to investigate the influence of DS concentration on both water flux and RSF through sensitivity analysis study, and comparing MgCl2 and NaCl in terms of osmotic dynamic performances.

Section snippets

Existing FO dynamic models analysis

Continuous or batch operation of a FO desalination process requires dynamic tracking of the water flux and RSF for control purposes and optimal performances. To better understand the FO dynamic behavior, a review of all FO dynamic models adaptable to water desalination was performed to the best of our knowledge.

Good control in continuous FO process helps maintain drinking water production and water quality through various means. While water flux can be maintained by preventing a reduction in

Dynamic Model development for FO process

The dynamic model is based on phenomena involved in the forward osmosis process, leading to diffusion and material balance equations. Model equations are written to account for the substances in the mixture and their associated variables during the operation of forward osmosis process (such as viscosity diffusivity, density…, of each substance). The dynamic model of Ruprakobkit et al. (2016) was developed for the operation of forward osmosis process and simulated a low concentration of single

Methodology

Reliability and accuracy of the dynamic model must be evaluated before its use. This is performed through an experimental study combined with simulation.

Experimental results

The measured variables are feed and draw solutions weights and their electrical conductivities, flowrates and temperatures. To convert electrical conductivities to concentrations for both membrane cell sides, two correlations are obtained using data adopted from (Haynes, 2014) with an R² equal to 0.9264 and 0.9986 for MgCl2 and NaCl, respectively. The resulting equations for concentration expressed in weight percentage (%wt.) of the solution are:CMgCl2(%wt)=0.0193σ1.421CNaCl(%wt)=2106σ34104σ2

Dynamic performance of MgCl2 and NaCl

The performance analysis of the two draw solution for FO desalination process must be conducted using a reliable dynamic model. The DS osmotic performances have been extensively analyzed in the literature in steady state (Cornelissen et al., 2011; Hancock and Cath, 2009; Ge et al., 2013), but dynamic performances have not been studied. In order to evaluate and compare the dynamic osmotic performance of both MgCl2 and NaCl, the specific reverse salt flux (Js/Jw)and its evolution with time as

Conclusion

From a literature survey, few studies have considered the investigation of FO dynamics, especially for water desalination applications. In this work, a simple yet robust FO dynamic model has been derived from an existing model selected among those available on the basis that it was experimentally validated. This model was subsequently improved and adapted to water desalination application, before been validated through experiments with both MgCl2 and NaCl. The derived model involves the time

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors would like to thank IRESEN, the Research Institute for Solar Energy and New Energies for the continuous funding.

Funding

This work was supported by the Institut de Recherche en Energie Solaire et Energies Nouvelles (IRESEN), Rabat, under InnoProjet Series.

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