Modeling nitrate/nitrite dependent anaerobic methane oxidation and Anammox process in a membrane granular sludge reactor

The granular bioreactor, characterized by excellent settling velocity, high rate and low cost is an ideal choice for achieving coupled nitrate/nitrite dependent denitrifying anaerobic methane oxidation (n-DAMO) and anaerobic ammonium oxidation (Anammox) process. To fundamentally understand its underlining mechanisms and provide suggestions for process optimization, a granule-based model framework was developed to describe simultaneous anaerobic methane and ammonium oxidation by functional microbes. The proposed model was evaluated based on long-term experimental data from two membrane granular sludge reactors (MGSRs) with different operational conditions. The model possessed of good predictive ability to reproduce removal rates and effluent concentrations of nitrogen species. The predicted biomass abundance in two MGSRs and stratified microbial distribution along granule depth were consistent with experimental observations. The estimated parameter values, with good identifiability and reliability indicated a stimulated growth of DAMO archaea in MGSRs. Both hydraulic retention times (HRTs) and granule sizes have influences on microbial abundance in the MGSR and community distribution inside granules. Within the investigated HRTs from 1.4 h to 20 h and granule sizes from 500 mu m to 2900 mu m, it was revealed that a proper control of relatively short HRTs and small granule sizes resulted in an increased fraction of DAMO archaea and a reduced DAMO bacteria abundance with AnAOB less impacted, which would lower the required nitrite nitrogen to ammonium nitrogen ratio in the nitritation reactor (prior unit) and thus minimize operational cost in sidestream treatment lines.

Automated summary

The granular bioreactor is an ideal choice for achieving coupled nitrate/nitrite dependent denitrifying anaerobic methane oxidation and anaerobic ammonium oxidation processes. A model framework was developed to understand the mechanisms and provide suggestions for process optimization, showing good predictive ability and consistency with experimental observations. Control of hydraulic retention times and granule sizes can impact microbial abundance and community distribution, leading to reduced operational costs in treatment lines.