Linking the nitrous oxide production and mitigation with the microbial community in wastewater treatment: A review

Diversity and Ecophysiology of the Genus OLB8 and Other Abundant Uncultured Saprospiraceae Genera in Global Wastewater Treatment Systems

The Saprospiraceae family within the phylum Bacteroidota is commonly present and highly abundant in wastewater treatment plants (WWTPs) worldwide, but little is known about its role. In this study, we used MiDAS 4 global survey with samples from 30 countries to analyze the abundance and distribution of members of Saprospiraceae. Phylogenomics were used to delineate five new genera from a set of 31 high-quality metagenome-assembled genomes from Danish WWTPs. Newly designed probes for fluorescence in situ hybridization (FISH) revealed rod-shaped morphologies for all genera analyzed, including OLB8, present mostly inside the activated sludge flocs. The genomes revealed potential metabolic capabilities for the degradation of polysaccharides, proteins, and other complex molecules; partial denitrification; and storage of intracellular polymers (glycogen, polyphosphate, and polyhydroxyalkanoates). FISH in combination with Raman microspectroscopy confirmed the presence of intracellular glycogen in Candidatus Brachybacter, Candidatus Parvibacillus calidus (both from the former genus OLB8), and Candidatus Opimibacter, and the presence of polyhydroxyalkanoates in Candidatus Defluviibacterium haderslevense and Candidatus Vicinibacter. These results provide the first overview of the most abundant novel Saprospiraceae genera present in WWTPs across the world and their potential involvement in nutrient removal and the degradation of macromolecules.

Cometabolic biodegradation of antibiotics by ammonia oxidizing microorganisms during wastewater treatment processes

Studies on antibiotic removal during wastewater treatment processes are crucial since their release into the environment could bring potential threats to human health and ecosystem. Cometabolic biodegradation of antibiotics by ammonia oxidizing microorganisms (AOMs) has received special attentions due to the enhanced removal of antibiotics during nitrification processes. However, the interactions between antibiotics and AOMs are less well-elucidated. In this review, the recent research proceedings on cometabolic biodegradation of antibiotics by AOMs were summarized. Ammonia oxidizing bacteria (AOB), ammonia oxidizing archaea (AOA) and complete ammonia oxidizers (comammox) played significant roles in both nitrification and cometabolic biodegradation of antibiotics. Antibiotics at varying concentrations might pose inhibiting or stimulating effect on AOMs, influencing the microbial activity, community abundance and ammonia monooxygenase subunit A gene expression level. AOMs-induced cometabolic biodegradation products were analyzed as well as the corresponding pathways for each type of antibiotics. The effects of ammonium availability, initial antibiotic concentration, sludge retention time and temperature were assessed on the cometabolic biodegradation efficiencies of antibiotics. This work might provide further insights into the fate and removal of antibiotics during nitrification processes.

Temporal triggers of N2O emissions during cyclical and seasonal variations of a full-scale sequencing batch reactor treating municipal wastewater

To investigate the major triggers of nitrous oxide (N₂O) production in a full-scale wastewater treatment plant, N₂O emissions and wastewater characteristics (ammonia, nitrite, nitrate, total nitrogen, dissolved inorganic carbon, dissolved organic carbon, pH, temperature, dissolved oxygen and specific oxygen uptake rate), the results of variations in the cycling of a sequential batch reactor (SBR, where only full nitrification was performed), were monitored seasonally for 16 months. Major triggers of N₂O production were investigated based on a seasonal measured database using a random forest (RF) model and sensitivity analysis, which was applied to identify important input variables. As the result of seasonal monitoring in the full-scale SBR, the N₂O emission factor relative to daily total nitrogen removal ranged from 0.05 to 2.68%, corresponding to a range of N₂O production rate from 0.02 to 0.70 kg-N/day. Results from the RF model and sensitivity analysis revealed that emissions during nitrification were directly or indirectly related to nitrite accumulation, temperature, ammonia loading rate and the specific oxygen uptake rate ratio between ammonia oxidizing bacteria and nitrite oxidizing bacteria (sOUR-ratio). However, changes in the microbial community did not significantly impact N₂O emissions. Based on these results, the sOUR-ratio could represent the major trigger for N₂O emission in a full-scale BNR system: a higher sOUR-ratio value with an average of 3.13 ± 0.23 was linked to a higher N₂O production rate with an average value of 1.27 ± 0.12 kg-N/day (corresponding to 3.96 ± 1.20% of N₂O emission factor relative to daily TN removal), while a lower sOUR-ratio with an average value of 2.39 ± 0.27 was correlated with a lower N₂O production average rate of 0.17 ± 0.11 kg-N/day (corresponding to 0.74 ± 0.69% of N₂O emission factor) (p-value = 0.00001, Mann-Whitney test).

Metagenomic insights into the "window" effect of static magnetic field on nitrous oxide emission from biological nitrogen removal process at low temperature

This study aimed to explore whether the "window" effect of static magnetic field (SMF) on nitrous oxide (N₂O) emission from the biological nitrogen removal process at low temperature existed and reveal its biological mechanism at the gene level. Four sequencing batch reactors (SBRs) with SMFs of 0, 10, 45, and 75 mT were operated continuously for 110 days at 10 °C and the lowest N₂O-Gas cumulative emission (5.50 mg N/day) and N₂O conversion rate (4.28 %) in 45 mT SMF-SBR verified the existence of the "window" effect. In 45 mT SMF-SBR, nearly all enzymatic activities related to N₂O reduction and corresponding functional gene abundances improved significantly. Metagenomic high-throughput sequencing analysis revealed that Alicycliphilus denitricans, Paracoccus denitrificans, Rhodopseudomonas palustris, Pseudomonas stutzeri, and Dechloromonas aromatica, as species related to N₂O reduction, could be separately enriched by applying suitable SMF intensity. Gene functions annotation based on KEGG and CAZy databases indicated that SMF not only accelerated the rate of free ammonia into ammonia-oxidizing bacteria and electrons delivered to the corresponding denitrification reductases, but also enhanced the degradation of complex organic matter into smaller molecules, and thus reducing the production of N₂O via nitrifier denitrification and incomplete denitrification pathways at 10 °C. These findings provided a guideline and presented a blueprint of ecophysiology for the future application of magnetic field to the reduction of N₂O emission in wastewater treatment plants in the cold region.

A knowledge discovery framework to predict the N2O emissions in the wastewater sector

Data Analytics is being deployed to predict the dissolved nitrous oxide (N₂O) concentration in a full-scale sidestream sequence batch reactor (SBR) treating the anaerobic supernatant. On average, the N₂O emissions are equal to 7.6% of the NH₄-N load and can contribute up to 97% to the operational carbon footprint of the studied nitritation-denitritation and via-nitrite enhanced biological phosphorus removal process (SCENA). The analysis showed that average aerobic dissolved N₂O concentration could significantly vary under similar influent loads, dissolved oxygen (DO), pH and removal efficiencies. A combination of density-based clustering, support vector machine (SVM), and support vector regression (SVR) models were deployed to estimate the dissolved N₂O concentration and behaviour in the different phases of the SBR system. The results of the study reveal that the aerobic dissolved N₂O concentration is correlated with the drop of average aerobic conductivity rate (spearman correlation coefficient equal to 0.7), the DO (spearman correlation coefficient equal to -0.7) and the changes of conductivity between sequential cycles. Additionally, operational conditions resulting in low aerobic N₂O accumulation (<0.6 mg/L) were identified; step-feeding, control of initial NH₄⁺ concentrations and aeration duration can mitigate the N₂O peaks observed in the system. The N₂O emissions during aeration shows correlation with the stripping of accumulated N₂O from the previous anoxic cycle. The analysis shows that N₂O is always consumed after the depletion of NO₂^- during denitritation (after the "nitrite knee"). Based on these findings SVM classifiers were constructed to predict whether dissolved N₂O will be consumed during the anoxic and anaerobic phases and SVR models were trained to predict the N₂O concentration at the end of the anaerobic phase and the average dissolved N₂O concentration during aeration. The proposed approach accurately predicts the N₂O emissions as a latent parameter from other low-cost sensors that are traditionally deployed in biological batch processes.