| Abstract | Water scarcity is a global issue affecting over 2 billion people, necessitating desalination to augment freshwater supplies in arid and semi-arid regions [1]. Conventional desalination technologies, such as reverse osmosis, are energy and capital-intensive and generate concentrated brine, which contributes to environmental pollution [2]. Microbial Desalination Cells (MDCs) offer a sustainable alternative, leveraging electroactive bacteria to simultaneously desalinate water, treat wastewater, and generate bioelectricity [3]. However, their scalability is constrained by low desalination rate, which limits overall performance [3,4]. To overcome these barriers, we are investigating the interactive effects of key operational parameters (external resistance, anolyte pH, and substrate concentration) using Responsible Surface Methodology (RSM) to optimise MDC performance. A total of 15 experimental runs are being conducted in MDCs using the Central Composite Design (CCD) to estimate linear and quadratic effects within the selected design space. The response variables include desalination rate, power density, chemical oxygen demand (COD) removal efficiency, and MtrC gene expression, a functional marker of extracellular electron transfer. Second-order polynomial regression models will be developed for each response to describe system behaviour and quantify factor interactions. Analysis of Variance (ANOVA) will be applied to assess model significance and the statistical relevance of individual and interaction terms. Response surface and contour plots will be generated to visualise the combined effects of operational parameters and to identify optimal operating regions. Model predictions will be validated through confirmatory experiments conducted under the predicted optimum conditions to evaluate predictive accuracy and robustness. The study is expected to identify significant interactions between operating parameters and MDC performance. Optimal conditions are anticipated to enhance desalination efficiency, increase power output, and improve COD removal. Variation in MtrC gene expression is expected to provide insight into the regulation of extracellular electron transfer under different operating conditions. This work will establish a systematic and statistically robust framework for optimising MDCs, thereby advancing their technical feasibility for sustainable desalination, in line with UN SDG 6 (Clean Water and Sanitation). References: [1] S. C. Izah and M. C. Ogwu, ‘Water Scarcity and Insecurity: Causes and Consequences’, in Water Quality and Safety in the Global South: Challenges, Solutions and Future Directions, M. C. Ogwu andS. Chibueze Izah, Eds, Cham: Springer Nature Switzerland, 2026, pp. 1–24. doi: 10.1007/978-3-032-10602-5_1. [2] J. Orfi, R. Sherif, and M. AlFaleh, ‘Conventional and Emerging Desalination Technologies: Review and Comparative Study from a Sustainability Perspective’, Water, vol. 17, no. 2, Jan. 2025, doi: 10.3390/w17020279. [3] I. Mudher and S. A. Ali, ‘Microbial Desalination Cells: Sustainable Water Desalination Application and Wastewater Management’, Cell Physiol Biochem, vol. 59, no. 2, pp. 131–147, Mar. 2025, doi: 10.33594/000000767. [4] P. Baboo, ‘Microbial Desalination Cells: Trends and Challenges’, in Handbook of Sustainable Industrial Wastewater Treatment, CRC Press, 2025. |
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