A review of biochemical diversity and metabolic modeling of EBPR process under specific environmental conditions and carbon source availability

Enhanced biological phosphorus removal (EBPR) is one of the most promising technologies as an economical and environmentally sustainable technique for removal of phosphorus from wastewater (WW). However, with high capacity of EBPR, insufficient P-removal is a major yet common issue of many full-scale wastewater treatment plants (WWTP), due to misinterpreted environmental and microbial disturbance. By developing a rather extensive understanding on biochemical pathways and metabolic models governing the anaerobic and aerobic/anoxic processes; the optimal operational conditions, environmental changes and microbial population interaction are efficiently predicted. Therefore, this paper critically reviews the current knowledge on biochemical pathways and metabolic models of phosphorus accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) as the most abundant microbial populations in EBPR process with an insight on the effect of available carbon source types in WW on phosphorus removal performance. Moreover, this paper critically assesses the gaps and potential future research in metabolic modeling area. With all the developments on EBPR process in the past few decades, there is still lack of knowledge in this critical sector. This paper hopes to touch on this problem by gathering the existing knowledge and to provide farther insights on the future work onto chemical transformations and metabolic strategies in different conditions to benefit the quantitative model as well as WWTP designs. • EBPR may face disruption in full-scale system as a lack of microbiological insight. • Understanding of P-removal stoichiometry and kinetic optimizes operation. • Development and design are feasible by biochemical conversion definition/modeling. • Generally approved biochemical transformation model for EBPR is not available. • Efficient biological process performance requires well-established metabolic model.