New insights in correlating greenhouse gas emissions and microbial carbon and nitrogen transformations in wetland sediments based on genomic and functional analysis

Abstract

Greenhouse gas (GHG) emissions from constructed wetlands (CWs) lower the environmental and ecological benefits of CWs and thus have raised increasing environmental concern. To prevent GHGs emissions, it is important to assess and quantify the correlation of GHGs emission and microbial carbon and nitrogen transformations. In this study, two typical wetland substrate samples (mud sampled from Xiaomei River CW and sand sampled from Dongwen River CW) were used to build lab-scale vertical subsurface flow CW microcosms, labeled as XRCW and DRCW, respectively. The mean COD removal rate of the DRCW group (76.1%) was higher than that of XRCW group (60.6%). Both groups achieved a high extent of nitrogen nutrient removal, indicating a higher metabolic activity of nitrifying and denitrifying microorganisms in the system, especially in XRCW. The mean emission fluxes of N2O, CH4 and CO2 in the XRCW group were 52.7 μg/m2-h, 1.6 mg/m2-h and 100.4 mg/m2-h, which were higher than that in the DRCW group (30.0 μg/m2-h, 1.0 mg/m2-h and 28.0 mg/m2-h, respectively). The relation of GHG emissions to microbial carbon and nitrogen transformation was assessed by genomics and functional analysis. The release of GHGs by the XRCW group had a positive correlation with the relative abundance of Proteobacteria, while for the DRCW group a positive correlation was found with the relative abundance of Cyanobacteria. Nitrogen fixation by Cyanobacteria could be an approach to reduce GHG emissions. The release of CH4 and CO2 was positively correlated with glucose metabolism. N2O gas emission was affected by the species of denitrifiers. This study is of great importance to clarify the emissions of GHGs in vertical subsurface flow CWs, as it is relating to microbial carbon and nitrogen transformation. The connection is of great significance to control the emission of GHGs in wetlands.