Myriophyllum aquaticum constructed wetland effectively removes nitrogen in swine wastewater

Abstract

Removal of nitrogen (N) is a critical aspect in the functioning of constructed wetlands (CWs), and the N treatment in CWs depends largely on the presence and activity of macrophytes and microorganisms. However, the effects of plants on microorganisms responsible for N removal are poorly understood. In this study, a three-stage surface flow CW was constructed in a pilot-scale within monospecies stands of Myriophyllum aquaticum to treat swine wastewater. Steady-state conditions were achieved throughout the 600-day operating period, and a high (98.3%) average ammonia removal efficiency under a N loading rate of 9 kg ha-1 d-1 was observed. To determine whether this high efficiency was associated with the performance of active microbes, the abundance, structure, and interactions of microbial community were compared in the unvegetated and vegetated samples. Real-time quantitative polymerase chain reactions showed the abundances of nitrifying genes (archaeal and bacterial amoA) and denitrifying genes (nirS, nirK, and nosZ) were increased significantly by M. aquaticum in the sediments, and the strongest effects were observed for the archaeal amoA (218-fold) and nirS genes (4620-fold). High-throughput sequencing of microbial 16S rRNA gene amplicons showed that M. aquaticum greatly changed the microbial community, and ammonium oxidizers (Nitrosospira and Nitrososphaera), nitrite-oxidizing bacteria (Nitrospira), and abundant denitrifiers including Rhodoplanes, Bradyrhizobium, and Hyphomicrobium, were enriched significantly in the sediments. The results of a canonical correspondence analysis and Mantle tests indicated that M. aquaticum may shift the sediment microbial community by changing the sediment chemical properties. The enriched nitrifiers and denitrifiers were distributed widely in the vegetated sediments, showing positive ecological associations among themselves and other bacteria based on phylogenetic molecular ecological networks.