Abstract

ABSTRACT Bio-cathode microbial desalination cells are emerging technology that utilizes bioelectric potential from organic matter (petroleum refinery effluent) to enhance the desalination process along with the activity of microalgae (Scenedesmus abundans). In the present work, the system is assumed to be governed by interdependent key process variables such as salt concentration, anolyte concentration, and external resistance. Three different levels of salt concentration (5, 20 and 35 g L−1), anolyte concentration (250, 500 and 750 mg L−1), and external resistance (100, 560 and 1000 Ω) were analysed and optimized by the statistical and probabilistic tool such as Box Behnken design method and Genetic Algorithm to maximize the desalination performance. The optimized parameters such as salt concentration (35 g L−1), anolyte concentration (500 mg L−1), and external resistance (100 Ω) produced maximum desalination efficiency of 59.6%. The model also distinguished the influence of input parameters on the output responses such as significant responses (Salinity, Total dissolved solids, and Electrical conductivity) and non-significant responses (Chemical oxygen demand removal, power density, and algal growth). The model predicted the desalination efficiency with ±1.25% error. The high impact of bio-fouling was observed in Anion Exchange Membrane on comparison with Cation Exchange Membrane.

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