Abstract
Algae-based membrane bioreactor (AMBR) has shown a potential for simultaneous wastewater treatment and production of algal biomass. However, the effectiveness of AMBR has yet to be further explored for greywater treatment. The present study assessed the algal biomass production, greywater treatment efficiency, and fouling characteristics of a laboratory-scale AMBR. The 12 h dark/12 h light cycle continuous experiments were performed with an AMBR operating at 48 h hydraulic retention time. The average algal biomass and chlorophyll-a production rates were 47.9 mg/L/d and 49.9 μg/L/d, respectively. The distribution of different pigments in the biomass showed an abundance of chlorophyll-a (92.2%) in the reactor. AMBR achieved 96% biological oxygen demand (BOD5) removal and 99% anionic surfactants removal by bacterial oxidation without any external aeration source. Algal assimilation achieved a total nitrogen removal of 52% and total phosphorus removal of 36%. More than 85% of nitrite (NO3-N) in the effluent revealed the absence of nitrification and denitrification processes in the reactor. Further, the reactor accomplished a higher than the 3.5-log reduction of total coliform and E-coli. The greenish cake layer of algal–bacterial biomass primarily caused the membrane fouling and accounted for 80–93% of total fouling resistance. Membrane fouling frequency decreased with the operation time, and physical cleaning effectively recovered the flux. The energy efficiency of AMBR in terms of net energy return (1.04) supported its application for the treatment and recycling of greywater. The present study provides the basis for establishing the guidelines for AMBR design for the treatment of greywater.
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Authors gratefully acknowledge Professor Jun Nakajima, Ritsumeikan University, Japan, for his valuable academic advice and technical guidance.
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Shafiquzzaman, M., Ashadullah, A.K.M., Haider, H. et al. Assessment of biomass production and greywater treatment capability of algal-based membrane bioreactor. Int. J. Environ. Sci. Technol. 19, 7637–7648 (2022). https://doi.org/10.1007/s13762-021-03678-4
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DOI: https://doi.org/10.1007/s13762-021-03678-4