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Pilot-scale Microbial Fuel Cells (MFCs): A meta-analysis study to inform full-scale design principles for optimum wastewater treatment

Lookup NU author(s): Hannah Bird, Dr Elizabeth Heidrich, Daniel Leicester, Dr Pavlina TheodosiouORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© Elsevier Ltd. Microbial Fuel Cells (MFCs) directly convert wastewater into electricity, reducing its chemical oxygen demand (COD), thus concomitantly treating it. Increasing global demands for clean water and energy has driven research interest in MFCs over the last 25 years, transitioning from a laboratory innovation into pilot-scale demonstrations, and even some commercial units. However, the technology still lacks the proper framework for design that existing treatment processes have. To address this gap, this paper systematically analyses pilot-scale MFC data, showing that despite large variation in environments/climates, operational parameters, wastewater types, architecture, and performance in terms of current production, strong correlations exist between both the amount and the rate of wastewater treatment. Using these correlations, a framework was developed for designing MFCs to give reactor size and hydraulic retention time for treating any given wastewater at any scale. In this meta-analysis, vastly different studies have been compared standardising the data presented and using this to draw generalisations about MFC design and performance. Improved consistent reporting could further strengthen this framework, making data more accessible and ultimately aid future research and commercialisation of MFCs as a wastewater treatment technology.

Publication metadata

Author(s): Bird H, Heidrich ES, Leicester DD, Theodosiou P

Publication type: Review

Publication status: Published

Journal: Journal of Cleaner Production

Year: 2022

Volume: 346

Print publication date: 20/04/2022

Online publication date: 08/03/2022

Acceptance date: 04/03/2022

ISSN (print): 0959-6526

Publisher: Elsevier Ltd


DOI: 10.1016/j.jclepro.2022.131227