Han, Gyuseong Shin, Seung Gu Cho, Kyungjin Lee, Joonyeob Kim, Woong Hwang, Seokhwan 2024-01-19T21:03:20Z 2024-01-19T21:03:20Z 2021-09-05 2019-01 0944-1344 https://pubs.kist.re.kr/handle/201004/120531 To investigate the effects of temporal variations of process parameters on microbial community structures in the two types of full-scale anaerobic digester treating swine wastewater, three full-scale anaerobic digesters were monitored. An anaerobic filter (AF)-type digester located in Gong-Ju (GJ) showed the highest COD removal among three digesters and maintained stable efficiency. A digester in Hong-Seong (HS) was of the same type as it GJ and showed improved efficiency over the sampling period. A continuously stirred tank reactor (CSTR)-type digester in Soon-Cheon (SC) showed decreasing efficiency due to a high residual concentration of VFAs and NH4+. These process efficiencies were closely correlated to the Simpson indices of the methanogenic communities. Genera Bacillus, Methanosaeta, and Methanospirillum that have filamentous morphology were dominant in both AF-type digesters, but genera Acholeplasma, Methanosarcina, and Methanoculleus that have spherical or coccoid morphology were dominantly abundant in the CSTR-type digester. Correlation between populations suggests a possible syntrophic relationship between genera Desulfobulbus and Methanosaeta in digesters GJ and HS. English Springer Verlag Temporal variation in bacterial and methanogenic communities of three full-scale anaerobic digesters treating swine wastewater Article 10.1007/s11356-017-1103-y 1 Environmental Science and Pollution Research, v.26, no.2, pp.1217 - 1226 Environmental Science and Pollution Research 26 2 1217 1226 N scie scopus 000455814700021 2-s2.0-85040335689 Environmental Sciences Environmental Sciences & Ecology Article MICROBIAL COMMUNITY FOOD WASTE POPULATION-DYNAMICS PROCESS PERFORMANCE BIOGAS PRODUCTION CO-DIGESTION REACTOR SLUDGE BIOREACTOR DIVERSITY Full-scale swine wastewater Digester type Anaerobic digestion Microbial community Multivariate analysis