A comprehensive literature mining and analysis of nitrous oxide emissions from different innovative mainstream anammox-based biological nitrogen removal processes.

The biological nitrogen removal (BNR) process in wastewater treatment plants generates a substantial volume of nitrous oxide (NO), which possesses a potent greenhouse gas effect. A limited number of studies have systematically investigated the NO emissions of anammox-based systems with different BNR processes under mainstream conditions. Based on extensive big data statistical analysis, it had been revealed that simultaneous nitritation, anammox and denitrification (SNAD), partial nitritation anammox (PNA) and partial denitrification anammox (PDA), exhibit significantly lower NO emission factors when compared to traditional BNR processes. The median values for NO emission factors were determined to be 1.01 %, 1.15 % and 1.43 % for SNAD, PNA and PDA, respectively. Based on nitrogen removal data and NO emission factors, the NO emissions from PNA, SNAD and PDA processes were calculated to be 0.016 g·d, 0.037 g·d and 0.008 g·d, respectively. Furthermore, the machine learning models (SVM and ANN) exhibited excellent predictive performance for NO emissions in the BNR processes. However, after removing environmental factors, the R value of the SVM model sharply decreased. The SHAP feature analysis demonstrated the significant impact of environmental factors on the accuracy of predictive performance in machine learning models. Spearman correlation analysis was employed to investigate the relationship between NO emissions and operational factors as well as microbial communities. The results demonstrated a negative correlation between HRT, temperature and C/N with NO emissions. Moreover, strong associations were observed between Nitrosomonas, Nitrospira, Denitratisoma, Thauera species and NO emissions. The contribution of NO production via AOB pathways played a key role that was quantitatively calculated to be 93 %, 80 % and 48 % in the PNA, SNAD and PDA processes, respectively. These findings highlight the potential of these innovative BNR processes in mitigating NO emissions.