Combining high performance fertiliser with surfactants to reduce the reverse solute flux in the fertiliser drawn forward osmosis process
Shon, Ho Kyong
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Environmental Science and Engineering Program
Water Desalination and Reuse Research Center (WDRC)
Online Publication Date2018-08-15
Print Publication Date2018-11
Permanent link to this recordhttp://hdl.handle.net/10754/628514
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AbstractSolutions to mitigate the reverse diffusion of solutes are critical to the successful commercialisation of the fertiliser drawn forward osmosis process. In this study, we proposed to combine a high performance fertiliser (i.e., ammonium sulfate or SOA) with surfactants as additives as an approach to reduce the reverse diffusion of ammonium ions. Results showed that combining SOA with both anionic and non-ionic surfactants can help in reducing the reverse salt diffusion by up to 67%. We hypothesised that, hydrophobic interactions between the surfactant tails and the membrane surface likely constricted membrane pores resulting in increased rejection of ions with large hydrated radii such as SO42−. By electroneutrality, the rejection of the counter ions (i.e., NH4+) also therefore subsequently improved. Anionic surfactant was found to further decrease the reverse salt diffusion due to electrostatic repulsions between the surfactant negatively-charged heads and SO42−. However, when the feed solution contains cations with small hydrated radii (e.g., Na+); it was found that NH4+ ions can be substituted in the DS to maintain its electroneutrality and thus the diffusion of NH4+ to the feed solution was increased.
CitationChekli L, Pathak N, Kim Y, Phuntsho S, Li S, et al. (2018) Combining high performance fertiliser with surfactants to reduce the reverse solute flux in the fertiliser drawn forward osmosis process. Journal of Environmental Management 226: 217–225. Available: http://dx.doi.org/10.1016/j.jenvman.2018.08.024.
SponsorsThe research reported in this paper is part of a collaborative project between the King Abdullah University of Science and Technology (KAUST) and the University of Technology Sydney (UTS) and funded through a Center Partnership Fund provided by KAUST. Support was also provided by the Australian Research Council (ARC) through Future Fellowship (FT140101208) and UTS Chancellor's postdoctoral research fellowship.