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点源炼油废水处理系统微生物多样性及代谢功能研究
引用本文:宋佳宇,秦榕,杜显元,吴慧君,梁立宝. 点源炼油废水处理系统微生物多样性及代谢功能研究[J]. 环境科学研究, 2021, 34(10): 2389-2396. DOI: 10.13198/j.issn.1001-6929.2021.05.23
作者姓名:宋佳宇  秦榕  杜显元  吴慧君  梁立宝
作者单位:石油石化污染物控制与处理国家重点实验室,北京 102206;中国石油集团安全环保技术研究院有限公司,北京 102206;中国石油大学(北京)化学工程与环境学院,北京 102206;中国石油新疆油田公司百口泉采油厂,新疆 克拉玛依 834011
基金项目:中国石油天然气集团有限公司科学研究与技术开发项目2019D-5006-62
摘    要:为了探明点源炼油废水处理系统(简称"系统")沿程微生物多样性及其活动规律,采用高通量测序技术开展废水微生物群落结构及代谢功能研究.结果表明:①各单元出水Shannon-Wiener指数和Ace指数基本呈上升趋势,均表现为进水 < 涡凹气浮池 < 斜板气浮池 < 调节池 < A/O池.②微生物群落组成显示,各单元出水微生物群落结构差异显著(Bray-Curtis ANOSIM=0.388 1,P=0.008);进水中变形菌门(Proteobacteria)相对丰度最高,为90.55%.沿程各单元出水优势菌组成发生变化,其中,调节池、涡凹气浮池、斜板气浮池出水中Proteobacteria相对丰度分别降至54.90%、62.59%、52.89%,Epsilonbacteraeota相对丰度分别增至17.03%、29.60%、41.53%,厚壁菌门(Firmicutes)相对丰度分别增至26.13%、6.02%、2.33%;A/O池出水中Proteobacteria相对丰度降至39.69%,髌骨细菌门(Patescibacteria)和拟杆菌门(Bacteroidetes)相对丰度分别增至23.95%、15.65%.③db-RDA分析表明,化学需氧量(COD,P < 0.05)、氨氮(NH3-N,P < 0.05)显著影响微生物群落结构,其中,NH3-N去除率与Bacteroidetes(r=0.588,P < 0.05)呈显著正相关,COD去除率与Patescibacteria(r=0.530,P < 0.05)、Bacteroidetes(r=0.706,P < 0.01)均呈显著正相关.④KEGG基因数据库分析可知,各单元出水代谢机制相关基因相对丰度最高,均高于60%,其中,能量代谢相关基因相对丰度大小表现为进水>涡凹气浮池>调节池>斜板气浮池>A/O池;外源化合物生物降解相关基因在一级处理过程中相对丰度波动较小,均在3.00%以下,而生物处理后相对丰度迅速增至15.38%.研究显示:系统沿程微生物多样性基本呈上升趋势,且影响废水中微生物群落变化的最显著因素为COD和NH3-N;生物处理后外源化合物生物降解相关基因占比迅速增加,表明生物处理单元存在潜在冲击风险. 

关 键 词:点源炼油废水  微生物群落  功能基因  环境因子
收稿时间:2021-01-20

Microbial Diversity and Metabolic Function in Point Source Wastewater Treatment System of Oil Refinery
Affiliation:1.State Key Laboratory of Petroleum Pollution Control, Beijing 102206, China2.CNPC Research Institute of Safety and Environment Technology, Beijing 102206, China3.College of Chemical Engineering and Environment, China University of Petroleum-Beijing, Beijing 102206, China4.Baikouquan Oil Production Plant of Xinjiang Oilfield, PetroChina, Karamay 834011, China
Abstract:In order to investigate the microbial diversity and activity of different process units in the point source wastewater treatment system of oil refinery, high-throughput sequencing technology was used to study the microbial community structure and metabolic function. The results were as follows: (1) The Shannon-Wiener and ACE index in the effluent of each process unit showed a gradually ascendant trend, showing as influent < cavitation air flotation tank < slanting board air flotation tank < regulating tank < A/O tank. (2) The microbial community structure in various process units was significant different (Bray-Curtis ANOSIM=0.3881, P=0.008). The relative abundance of Proteobacteria was the highest in the influent (90.55%). Along the treatment process, the relative abundance of Proteobacteria in cavitation air flotation tank, slanting board air flotation tank, and regulating tank decreased to 62.59%, 52.89% and 54.90%, respectively, but Epsilonbacteraeota (17.03%, 29.60% and 41.53%) and Firmicutes (26.13%, 6.02% and 2.33%) increased. In addition, the relative abundance of Proteobacteria in the effluent of A/O tank decreased to 39.69%, but Patescibacteria and Bacteroidetes increased to 23.95% and 15.65%, respectively. (3) db-RDA analysis showed that chemical oxygen demand (COD, P < 0.05) and ammonia nitrogen (NH3-N, P < 0.05) obviously affected microbial community structure. Among them, NH3-N removal was positively correlated with the relative abundance of Bacteroidetes (r=0.588, P < 0.05), and COD removal was positively correlated with Patescibacteria (r=0.530, P < 0.05) and Bacteroidetes (r=0.706, P < 0.01). (4) KEGG database analysis found that the relative abundance of the genes related to metabolism in the effluent of each process unit was the highest, with more than 60%. The relative abundance of the genes related to energy metabolism was in the order of influent > cavitation air flotation tank > regulating tank > slanting board air flotation tank > A/O tank. The relative abundance of the genes related to biodegradation of exogenous compounds exhibited small fluctuation in the primary treatment process, with less than 3.00%, and it increased rapidly to 15.38% after biological treatment. In summary, the microbial diversity along the treatment process had an ascendant trend. COD and NH3-N were the predominant influencing factors to microbial community structure. The relative abundance of the genes related to biodegradation increased rapidly after biological treatment, indicating potential shock risks in the biological treatment unit. 
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