不同水力停留时间和进水硝酸盐浓度下香蕉杆为碳源的固相反硝化性能研究

高书伟; 张凯; 李志斐; 谢骏; 王广军; 李红燕; 夏耘; 郁二蒙; 田晶晶; 龚望宝

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不同水力停留时间和进水硝酸盐浓度下香蕉杆为碳源的固相反硝化性能研究
高书伟^1,2, 张凯², 李志斐³, 谢骏⁴, 王广军⁵, 李红燕⁶, 夏耘⁷, 郁二蒙⁸, 田晶晶⁹, 龚望宝¹⁰
1.上海海洋大学水产科学国家级实验教学示范中心上海 201306;2.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510380;3.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510381;4.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510382;5.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510383;6.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510384;7.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510385;8.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510386;9.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510387;10.中国水产科学研究院珠江水产研究所农业农村部热带亚热带水产资源利用与养殖重点实验室广东省水产动物免疫技术重点实验室广东广州 510388

摘要:

固相反硝化去除水产养殖尾水中硝酸盐氮(NO33–-N)具有广阔的应用前景，水力停留时间(hydraulic retention time, HRT)和进水硝酸盐浓度(influent nitrate concentration, INC)是影响反硝化系统反硝化性能的主要因素之一，需要对HRT进行优化，掌握其最大NO3–-N处理能力。本研究首次以香蕉杆为反硝化反应器的外加碳源，在流场环境下，测定不同HRT和INC下反硝化系统对NO3–-N、亚硝酸盐氮(NO2–-N)、氨氮(NH4+-N)、总氮(TN)、总磷(TP)和化学需氧量(COD)的去除效果。并采用基于Illumina Miseq测序平台的高通量测序技术，对反硝化系统运行初期及末期的细菌群落进行16S rDNA V3和V4区测序分析。结果显示，香蕉杆反应器的最佳HRT为20 h，对应NO3–-N去除率为(96.71±1.36)%，且无NO2–-N积累。在最佳HRT的基础上，反应器的出水硝酸盐浓度(effluent nitrate concentration, ENC)和硝酸盐去除速率(nitrate removal rate, NRR)均随INC的增加而显著增加(P<0.05)，出水COD随INC的增加而降低。此外，反应器在整个实验期间能完全去除NH4+-N。高通量测序结果显示，经过长期运行后，反应器内的优势菌门包括变形菌门(Proteobacteria)、拟杆菌门(Bacteroidetes)、弯曲杆菌门(Campilobacterota)和厚壁菌门(Firmicutes)，它们的相对丰度分别增至31.20%、6.67%、3.08%和4.26%，保证了反应器的高效运行。此外，在属水平上，反应器初期和末期的优势菌存在明显差异。本研究为农业废弃物作为养殖尾水反硝化碳源的工艺优化提供了理论参考。

关键词: 固相反硝化水力停留时间进水硝酸盐浓度硝酸盐去除率微生物群落

DOI：10.19663/j.issn2095-9869.20211227005

分类号:

基金项目:

Investigation of the performance of solid phase denitrification under different hydraulic retention times and influent nitrate concentration using banana stalk as a carbon source

GAO Shuwei,ZHANG Kai,LI Zhifei,XIE Jun,WANG Guangjun,LI Hongyan,XIA Yun,YU Ermeng,TIAN Jingjing,GONG Wangbao

1.National Demonstration Center for Experimental Fisheries Science Education, Shanghai Ocean University, Shanghai 201306, China;2.Key Laboratory of Tropical and Subtropical Fishery Resource Application and Cultivation, Ministry of Agriculture and Rural Affairs, Pearl River Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangdong Key Laboratory of Aquatic Animal Immunity Technology, Guangzhou 510380, China

Abstract:

In China, aquaculture is the primary source of aquatic products due to the decrease in wild fishery resources. In 2018, the total output of aquatic products in China expanded to 47.6 million tons, accounting for 58% of global aquaculture production. Intensive culture methods generally use significant quantities of feed however, approximately 75% of nitrogen in the feed is retained in aquaculture water, mainly as soluble nitrogen, such as ammonia nitrogen (NH4+-N) and nitrate (NO3–-N), owing to low feed-utilization rates during cultivation. At the same time, fishes generate a substantial amount of excreta, which will cause the increase of nitrogen compounds in water and negatively affects the quality of aquatic products. Serious problems could occur if nitrogen compounds are discharged into the environment, including the eutrophication of rivers, the deterioration of drinking water sources, and hazards to human health. Furthermore, nitrates can form potentially carcinogenic compounds, such as nitrosamines and nitrosamides, and nitrate consumption can cause methemoglobinemia in infants. The Second National Census of Pollution Sources survey showed that the total nitrogen emission from aquaculture was 99 100 tons in 2017. To protect the environment and human health, it is important to remove nitrogen from aquaculture tailwater before discharging it to the surrounding waters. Biological denitrification is considered the most promising approach since nitrate can be reduced to harmless nitrogen gas by bacteria. A sufficient carbon source is necessary during the heterotrophic denitrification process. To solve the problems mentioned above, external liquid carbon sources such as methanol, acetic acid, and glucose are added to the tailwater, but they are costly, require high-energy, and have high operating requirement. In contrast, agricultural wastes as a carbon source have exhibited significant economic advantages and high efficiency. Many aquaculture tailwater treatment systems often face variations in hydraulic retention times (HRT) and influent nitrate concentration (INC), which are caused by acute changes in tailwater characteristics and production, and HRT and INC often exert a profound effect on the treatment performance of biological treatment systems. Extensive research has confirmed that adding agricultural waste (such as corncob, woodchip and rice straw) to municipal sewage and industrial wastewater can effectively improve denitrification efficiency. However, the effect of using agricultural waste as denitrifying carbon source to treat aquaculture tail water remains unclear. Banana stalk (BS), a typical agricultural waste product, is used as a denitrifying carbon source for the first time in this study. The study investigated the effects of HRT and INC on the denitrification performance of BS, and provided a theoretical basis for the application of agricultural waste in aquaculture tailwater treatment. In this study, using BS as a carbon source and a towel as biological carrier, the performance of solid-phase denitrification under dynamic flow conditions was studied by using a 1-D column experiment. In the HRT optimization experiment, INC was maintained at 50 mg/L and operated under four HRTs (16 h, 20 h, 24 h and 28 h) for 14 days. The effluent NO3–-N, nitrite (NO2–-N), NH4+-N, Total nitrogen (TN), Total phosphorus (TP), and chemical oxygen demand (COD) removal efficiency were measured every 2 days. The optimal HRT of BS-DR (banana stalk-denitrification reactor) was optimized by one-way ANOVA analysis. Then, based on the optimization of HRT, the reactor was operated for 14 days under different INC (75 mg/L, 100 mg/L, and 125 mg/L). The sampling time interval and measurement indexes were the same as those of the HRT optimization experiment. The Illumina MiSeq high-throughput sequencing method was used to sequence and analyze the two hyper-variable regions (V3-V4) of the 16S rRNA gene of bacteria in the initial and final stages of the BS-DR. The results indicated that HRT and INC are the key factors affecting the denitrification performance of BS-DR. There was no significant difference in nitrate removal efficiency when the HRT was 20 h (96.71±1.36)%, 24 h (94.57±4.73)%, and 28 h (99.41±0.64)%, but they were significantly higher than that when the HRT was 16 h (87.53±7.95)%. Therefore, the optimal HRT for BS-DR was 20 h, and no nitrite accumulation. The second set of experiments was conducted using the optimal HRT obtained from the first set of experiments. The effluent nitrate concentration (ENC) and nitrate removal rate (NRR) of BS-DR increased significantly with increase in INC (P<0.05), and the effluent COD decreased with increase in INC, and the proper INC for BS-DR was ≤50 mg/L. It is worth noting that BS-DR could completely remove NH4+-N in both experiments. In addition, HRT significantly affects the removal efficiency of TP, but INC has little effect. According to pyrosequencing analysis, the microbial community structure of BS-DR changed after long-term operation, with the relative abundances of Proteobacteria, Bacteroidetes, Campilobacterota, and Firmicutes increasing to 31.20%, 6.67%, 3.08%, and 4.26%, respectively, ensuring the efficient operation of the reactor. On the contrary, the relative abundances of Halobacterota, Desulfobacterota, Sva0485, Chloroflexi, and Verrucomicrobiota decreased to 10.39%, 5.13%, 2.82%, 2.00%, and 1.17 %, respectively, in the reactor. In addition, at the genus level, most of the dominant bacteria at the end of reactor operation play a role in denitrification and degradation of agricultural waste, which is significantly different from that at the beginning of the reactor operation.

Key words: Solid phase denitrification Hydraulic retention time Influent nitrate concentration Nitrate removal efficiency Microbial community