Nitrous oxide production, mechanisms, and modeling from a denitrifying phosphorus removal bioreactor
Farmer, M.; Sabba, F.; Wells, G. F.
Show abstract
Nitrous oxide (N2O) is a potent greenhouse gas produced as an unintentional, undesired byproduct in many nitrogen removal bioprocesses. Given the considerable challenges in managing N2O emissions from wastewater treatment, N2O could be reframed as a value-added product if intentionally generated and captured. This study assesses N2O production and mechanisms in a Coupled Aerobic-anoxic Nitrous Decomposition Operation with Phosphorus removal (CANDO+P) reactor. Optimal performance was achieved when the reactor was fed with a mixture of propionate and glucose, resulting in N2O was production up to 50% of influent nitrogen. Through 16S rRNA amplicon and shotgun metagenomic sequencing, we found that Candidatus Accumulibacter were the dominant phosphorus accumulating organism (PAO). Assembly of a high-quality metagenome-assembled genome showed that Ca. Accumulibacter encoded a full complete denitrification pathway from nitrite to nitrogen gas. We also found abundant populations of denitrifying glycogen accumulating organisms (GAO) and ordinary heterotrophic organisms (OHO). We also incorporated truncated denitrification pathways into a process model to predict N2O generation. N2O predictions were the most similar to observed results when the denitrification pathways of PAO, GAO, and OHO model populations reflected denitrification gene abundances from the metagenomic sequencing analysis. Our work demonstrates the feasibility of using non-VFA carbon for intentional N2O generation and provides broader insights into N2O generation and truncated denitrification pathways of denitrifying PAO and GAO.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Long solids retention times and attached growth phase favor prevalence of comammox bacteria in nitrogen removal systems. 97%
- Metagenomic profiling and transfer dynamics of antibiotic resistance determinants in a full-scale granular sludge wastewater treatment plant 97%
- Denitrification kinetics indicates nitrous oxide uptake is unaffected by electron competition in Accumulibacter 97%
Similar papers in this journal
- Legacy copper/nickel mine tailings potentially harbor novel iron/sulfur cycling microorganisms within highly variable communities 95%
- Seafloor incubation experiment with deep-sea hydrothermal vent fluid reveals effect of pressureand lag time on autotrophic microbial communities 94%
- Amplicon-guided isolation and cultivation of previously uncultured microbial species from activated sludge 94%
Similar papers in this journal
- Antibiotic Resistance Gene Variant Sequencing is Necessary to Reveal the Complex Dynamics of Immigration from Sewers to Activated Sludge 96%
- Thiocyanate and organic carbon inputs drive convergent selection for specific autotrophic Afipia and Thiobacillus strains within complex microbiomes 95%
- Response relationships between CO2, CH4 and N2O emissions and microbial functional groups in wetland sediments after trace metal addition. 95%
Similar papers in this journal
- Press xenobiotic disturbance favors deterministic assembly with a shift in function and structure of bacterial communities in sludge bioreactors 95%
- Reproducible microbial community dynamics of two drinking water systems treating similar source waters. 95%
- Nationwide trends in COVID-19 cases and SARS-CoV-2 wastewater concentrations in the United States 94%
Similar papers in this journal
- Physiological stress response to sulfide exposure of freshwater anaerobic methanotrophic archaea 96%
- Biotransformation of lindane (γ-hexachlorocyclohexane) to non-toxic end products by sequential treatment with three mixed anaerobic microbial cultures 95%
- Anaerobic Benzene Biodegradation Linked to Growth of Highly Specific Bacterial Clades 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.