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我国很多城镇污水处理厂进水中碳氮比(C/N)较低,通常采用外加碳源以提高TN去除率,所采用的碳源分为传统碳源和新型碳源。其中:传统碳源包括甲醇、乙酸、乙酸钠、葡萄糖等[1-2];新型碳源包括天然固相碳源(果皮类、秸秆类、枝干类、贝类等)[3-4]、人工合成固相碳源(PHAs类多聚物、聚己内酯(PCL)、聚丁二酸丁二脂(PBS)等)[5-6]、液相碳源(食品工业废水、餐厨废弃物水解液等废液发酵副产品)[2,7]等。选择合适的碳源是目前处理低C/N污水的关键。
低C/N污水处理常应用移动床生物膜反应器(moving bed biofilm reactor,MBBR)和反硝化生物滤池(biofilters for denitrification,DNBF)等反硝化工艺。其中DNBF具有一定的过滤能力,但需要定期进行反冲洗。而MBBR是在曝气池中加入悬浮填料作为微生物载体,使好氧、缺氧和厌氧环境同时存在,无需污泥回流,可以实现同步硝化反硝化(simultaneous nitrification and denitrification,SND)[8-9],能有效去除COD和氮等污染物,降低废水处理成本。现有污水处理厂在提标改造中广泛采用MBBR处理技术,改造过程简单且成本较低,故MBBR技术具有较大的应用潜力。在MBBR中,悬浮填料的物理化学性质会影响生物膜的形成和污染物去除性能。LIU等利用添加表面改性复合填料的MBBR在低DO水平(0.6 ~ 0.8 mg·L−1)和低C/N (≤5)条件下,可实现对有机物和总氮的高效去除[10],COD和TN去除率分别为85.7%和75.9%。SONG等开发了一种以沸石粉基聚氨酯海绵为悬浮填料的MBBR,TN的去除效果比传统的海绵悬浮填料型MBBR高出近10%[11]。
我国是酒业大国。在酒类产品中,白酒所占的比例较高。白酒酿造的原料以谷粮为主,在白酒酿造与生产过程中会产生大量白酒废水,据统计,每生产1 t白酒即可产生20~40 t废水。白酒废水可分为低浓度和高浓度废水。高浓度白酒废水(high concentration Baijiu wastewater,HCBW)包含原料冲洗浸泡水、窖底水、锅底水等,约占白酒废水排放总量的5%,含有高浓度溶解性有机物,如多糖、有机酸、乙醇、甘油等[12],具有高COD、高BOD、高色度、呈酸性、低溶解氧、总氮浓度高等特征,处理难度大,可生化性好[13]。HCBW是食品工业排放的污染最严重的废水之一[14],未经充分处理的HCBW排放会导致藻类大量繁殖,水体溶解氧大量消耗,抑制生物的光合作用[15],使水生动植物无法正常生存,对水生态系统造成严重破坏。若废水渗入土壤中,则会抑制种子的萌芽、生长,导致植被枯竭,也能对陆生动物造成一定程度损害[16]。此外,还可能导致当地独特的微生物群落发生转变,对当地白酒行业造成损害[17]。
酿酒废水处理的常用方法为物化法、生物法、生态法和联用技术等。物化处理技术包括吸附、混凝沉淀、氧化、电解、热分解、膜分离等[18-22];生物处理技术包括好氧、厌氧[23-24]及藻类微生物降解等[25-26];生态处理技术主要是人工湿地处理系统[27];联用技术主要是多种技术结合,共同实现废水污染物去除[28]。单独的物化处理或生物处理对HCBW中污染物的去除效果不理想[29],采用多种方法联合应用可对HCBW实现达标处理,但处理难度大、运行管理费用较高[30],难以在中小型企业中进行推广应用。
基于以上研究,本研究采用MBBR技术,构建了高浓度白酒窖底废水与低C/N生活污水协同处理系统,使用改性海绵填料和流化床填料分别探究了HCBW作为反硝化外加碳源对低C/N污水处理的影响,并分析了微生物群落的变化,探究了白酒窖底废水作为反硝化外加碳源与低C/N生活污水协同处理技术的可行性及功能微生物,以期为HCBW的资源化利用提供参考。
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如图1所示,反应器具有内外双层结构,内层为反应区,外层为保温层。反应区内由挡板分隔为2个反应腔,每个反应腔均装有助循环隔板,单个反应腔的有效容积为45 L,反应腔内填充悬浮填料,分别采用海绵填料和流化床填料,填料直径均为10 mm,填充密度为30%~35%。反应器底部铺设有微孔曝气管(Φ=10 mm),通过曝气为悬浮填料提供上升的动力和氧气。实验装置分A、B 2组反应器,A组反应器在进水中添加白酒窖底废水(协同组),分A1、A2反应腔;B组反应器只添加模拟低C/N生活污水(未协同组),分B1、B2反应腔,其中A1、B1填充海绵填料,A2、B2填充流化床填料(表1),4组反应器互为对照。
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实验采用人工模拟低C/N生活污水和贵州省茅台镇某酱香型白酒企业的窖底水(表2),未协同组进水仅为人工模拟低C/N生活污水,协同组进水为模拟低C/N生活污水与窖底水按1 000∶1配制的混合废水,混合后废水的C∶N∶P=100∶1.14∶0.11。采用葡萄糖、NH4Cl、KH2PO4模拟低C/N生活污水的COD、TN、TP。为维持微生物正常的生长繁殖,向人工模拟废水中添加微量元素为0.3 mg·L−1 FeSO4·7H2O、0.15 mg·L−1 CoCl2·6H2O、0.12 mg·L−1 MnCl2·4H2O、0.06 mg·L−1 Na2MoO4·2H2O、0.15 mg·L−1 H3BO3、0.15 mg·L−1 NiCl2·6H2O、0.12 mg·L−1 ZnSO4·7H2O、0.06 mg·L−1 CuSO4·5H2O、0.06 mg·L−1 Na2WO4·2H2O、0.15 mg·L−1 KI。
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先向反应器中加入接种污泥,接种污泥取自贵州省某污水处理厂浓缩池,污泥接种质量浓度为4.0 g·L−1。通过调压器调节曝气泵曝气强度,控制DO为5~6 mg·L−1,采用循环热水控制反应器内温度为(30±1) ℃。使各组反应器在该条件下曝气3 d,使接种污泥与悬浮填料充分接触混合。待系统挂膜完成后,采用间歇式运行,运行周期为“反应23.5 h+换水0.5 h”,换水比为50%。定期检测反应器中的pH、DO、T、COD、
NH+4 -N、TN、色度等水质指标。在系统运行稳定后,通过傅里叶红外光谱仪分析污水处理前后物质组分变化,并利用16S rRNA高通量测序技术分析反应器中微生物群落结构及功能。 -
1)理化指标分析。
NH+4 -N采用纳氏试剂分光光度法(HJ535-2009)分析,TN采用碱性过硫酸钾消解紫外分光光度法(HJ636-2012)分析,色度采用光电比色法(LH-SD500,陆恒生物,中国)分析,pH、DO、T采用HACH便携式多参数数字化分析仪分析(HQ40d,HACH,美国),COD采用COD快速消解分析法分析[31]。2)傅里叶红外光谱(FTIR)分析。采集反应器稳定运行阶段的进出水水样各10 mL,协同组进出水分别记为A0、A1、A2,未协同组进出水分别记为B0、B1、B2。水样分析前,先将水样冷冻成冰,再利用真空冷冻干燥机(FD-1A-50,中国)将样品冷冻干燥成固体粉末,然后采用傅里叶变换红外光谱仪(Nicolet6700,ThermoFisherScientific,美国)对样品进行分析,设置扫描次数和分辨率分别为32次和4 cm−1,在4 000~400 cm−1内对样品进行红外光谱测定[32]。
3)微生物群落分析。采用16S rRNA高通量测序技术研究微生物的多样性和差异,采集接种污泥和反应器中培养至第68天的生物膜,分别标记为S0(接种污泥)、A1、A2、B1、B2,立即置于–80 ℃条件下进行冷冻保存,然后送至上海某生物公司进行16S rRNA基因测序分析。先采用试剂盒(E.Z.N.ATMMag-BindSoilDNAKit)对样本进行DNA的提取,并对提取后的DNA进行质检和纯化,利用ABI GeneAmp®9700型PCR扩增仪,选用338F(5′-ACTCCTACGGGAGGCAGCAG-3′)和806R(5′-GGACTACHVGGGTWTCTAAT-3′)作为引物在V3~V4之间的高变区对所提取合格的DNA序列进行PCR扩增,对PCR扩增产物经3 µL上样量的2%琼脂糖凝胶电泳分析,使用AxyPrepDNA凝胶提取试剂盒进行纯化,纯化后采用QuantiFluorM-ST进行定量[33]。然后,根据所构建的Illumina测序文库,对所得到的数据进行OTU聚类统计、物种注释、物种差异、功能预测等分析[34]。
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在系统构建过程中,各反应器出水的pH、DO、温度如表3所示。其中,DO质量浓度均相差不大;但pH有明显差异。A1、A2的pH均大于6.5,呈中性;而B1、B2的pH为6.0左右,呈弱酸性。这是由于B组反应器中反硝化能力较弱,硝化过程消耗碱度导致。
各反应器的COD、
NH+4 -N、TN和色度变化如图2所示。由图2(a)可看出,从第10天开始,出水COD逐渐趋于稳定,A1、A2的COD由358.94 mg·L−1分别降低至31.02 mg·L−1和33.75 mg·L−1,平均去除率分别为91.29%和90.51%;而B1、B2的COD由68.34 mg·L−1分别降低至22.51 mg·L−1和23.31 mg·L−1,平均去除率分别为65.92%和64.73%。由图2(b)可看出,从第24天开始,出水中NH+4 -N浓度逐渐趋于稳定,A1、A2的NH+4 -N质量浓度由36.31 mg·L−1分别降低至0.33 mg·L−1和0.52 mg·L−1,平均去除率分别为99.08%和98.58%;而B1、B2的NH+4 -N质量浓度由33.58 mg·L−1分别降低至10.88 mg·L−1和10.67 mg·L−1,平均去除率分别为67.20%和67.74%。由图2(c)可看出,在稳定后,A1、A2的TN质量浓度由38.73 mg·L−1分别降低至3.83 mg·L−1和9.29 mg·L−1,平均去除率分别为89.81%和75.73%;而B1、B2的TN质量浓度由35.85 mg·L−1分别降低至27.90 mg·L−1和27.97 mg·L−1,平均去除率分别为24.63%和26.92%。由图2(d)可看出,A1、A2的色度呈逐渐下降趋势,在稳定后,A1、A2的色度(稀释倍数)由175.12分别降低至34.01和42.06,平均去除率分别为80.66%和76.07%。综上所述,协同处理组A1、A2反应器对COD、
NH+4 -N和TN的去除效果均较好,出水达到《城镇污水处理厂污染物排放标准》(GB 18918-2002)一级A标准要求,说明窖底水与低C/N生活污水协同处理有利于提高TN的去除效率;而B1、B2出水中TN浓度均未达到一级A标准要求,这主要是由于系统缺乏碳源,导致未协同组对TN的去除率较低[35]。此外,A1出水中的TN浓度和色度均比A2低,说明在MBBR系统中,海绵填料的TN和色度去除效果均比流化床填料好。其原因为:流化床填料是由聚乙烯制成的,这种材料通常表现出疏水性且表面带负电荷,不利于污染物的转移,抑制亲水性和负电性生物膜的形成[36];流化床填料表面粗糙度较差,在换水和曝气过程中产生的水力剪切作用容易将表面附着的生物膜冲刷脱落,不利于生物膜初始黏附[37]。而海绵填料是由改性亲水聚氨酯制成的,其比表面积大、表面粗糙、对微生物黏附性好;此外,由于立方海绵填料中的高溶解氧(DO)梯度,为各种微生物创造生存条件[38-39],填料上出现硝化菌与反硝化菌等不同微生物,使其具有SND特性[40]。由此可见,悬浮填料作为微生物生长载体,是MBBR工艺的核心,生物膜的形成和污染物去除性能取决于载体的物理化学性质。 -
采用FTIR分析了协同组进出水中污染物官能团的变化,其FTIR谱图如图3所示。混合废水经过MBBR处理后, 3 413 cm−1(O—H伸缩振动)和1 632 cm−1处(NH2变角振动或
NH+2 变角振动或NH+3 不对称变角振动)的峰的强度有一定程度增强,说明废水经过处理后,具有该类官能团的物质的相对比例增加。1 385 cm−1和1 402 cm−1处(NO3−反对称伸缩振动或者NH+4 不对称变角振动)的峰宽变窄,且强度明显变弱,说明出水中硝酸盐类和铵类物质的相对比例明显减小。1 147 cm−1和1 120 cm−1处(SO−4 反对称伸缩振动)的峰的强度有一定程度增强,而峰宽无明显变化,说明出水中SO4−基团的相对比例增加。671 cm−1 (醇COH面外弯曲振动)和604 cm−1处(PO−4 的PO4不对称变角振动)的波峰强度均有微弱增强,说明出水中醇类物质、磷酸盐的相对比例有一定程度增加[41]。上述FTIR分析结果进一步佐证了混合废水经过MBBR系统处理后,NH+4 -N和TN均得到有效去除,且可推测出水中的醇类、硫酸盐和磷酸盐的物质相对比例有一定程度的增加。 -
1)微生物群落结构。系统运行68 d后,采用16S rRNA高通量测序技术对系统中微生物进行分析,在门水平上(图4(a)),接种污泥(S0)、海绵填料协同组(A1)、流化床填料协同组(A2)、海绵填料未协同组(B1)、流化床填料未协同组(B2)中相对丰度占主导的均为Proteobacteria、Chloroflexi和Actinobacteriota。其中,S0分别为24.36%、23.61%和14.63%,A1分别为24.56%、19.31%、和25.51%,A2分别为26.90%、17.63%和18.85%,B1分别为12.52%、5.71%和36.26%,B2分别为22.39%、9.87%和29.34%。与S0相比,A1和A2中的Actinobacteriota和Proteobacteria的相对丰度均增加,而Chloroflexi的相对丰度均降低,B1和B2 Actinobacteriota的相对丰度均增加,而Proteobacteria和Chloroflexi的相对丰度均降低。此外,未协同组B1和B2中Proteobacteria和Chloroflexi的相对丰度明显低于协同组A1和A2,未协同组B1和B2中Patescibacteria和Actinobacteriota的相对丰度明显高于协同组A1和A2,说明添加窑底废水会导致Proteobacteria和Chloroflexi的比例增加,导致Patescibacteria和Actinobacteriota的比例降低。Actinobacteriota属于异养需氧菌门,是降解污染物的主要功能菌。Proteobacteria广泛存在于受污染的水体环境中,在德国污水处理厂和我国养殖场废水中均检测出了Proteobacteria[42-43]。
在科水平上(图4(b)),在S0中主要为Saprospiraceae(4.19%)、Rhodanobacteraceae(3.07%)和SC-I-84(2.07%),A1和A2中主要为Propionibacteriaceae(9.76%、2.56%)、Nakamurellaceae(6.90%、11.94%)和Gemmatimonadaceae(6.70%、5.14%),B1和B2中主要为Nakamurellaceae(32.10%、19.03%)、Gemmatimonadaceae(2.04%、3.95%)和Caldilineaceae(1.48%、2.73%)。协同组系统中的Propionibacteriaceae和Gemmatimonadaceae的相对丰度均比未协同组高,而Nakamurellaceae的相对丰度均比未协同组低。Nakamurellaceae能够在细胞中积累大量的多糖,从而能够快速吸收废水中糖原和多磷酸盐,然后通过其代谢过程来进行细胞体的合成,对生物脱氮及污水中有机物的去除具有重要作用[44]。Propionibacteriaceae主要以酸类物质作为底物进行生长,由于协同组添加了窑底废水,废水中存在大量的酸类物质,为其生长提供了条件。Gemmatimonadaceae通过好氧和厌氧呼吸生长,能直接利用硝酸盐和亚硝酸盐,故经常在污水处理系统的活性污泥中被检测到[45]。
在属水平上(图4(c)),S0中主要为Ahniella(2.84%)、Ellin6067(2.44%)和Phaeodactylibacter(1.77%)。协同处理组A1和A2中主要为Micropruina(8.88%、2.26%)、Nakamurella(6.90%、11.94%)和Amaricoccus(3.48%、3.82%),未协同组B1和B2中主要为Nakamurella(32.10%、19.03%)、TM7a(8.46%、1.63%)和Thermomonas(0.64%、1.49%)。A1和A2中的硝化菌属主要为Nakamurella(6.90%、11.94%)、Nitrospira(0.46%、0.21%)[46],反硝化菌属主要为Amaricoccus(3.48%、3.82%)、Dokdonella(0.15%、0.41%)、Thermomonas(0.25%、0.75%)[47-48]。B1和B2中的硝化菌属主要为Nakamurella(32.10%、19.03%)、Nitrospira(1.83%、0.37%),反硝化菌属主要为Amaricoccus(0.35%、0.25%)、Dokdonella(0.23%、1.39%)、Thermomonas(0.64%、1.49%)。Nitrospira和Nakamurella是硝化作用过程中的重要功能菌,Thermomonas是还原硝酸盐或亚硝酸盐的缺氧反硝化菌[49],Amaricoccus被认为是废水处理中将硝酸盐还原为亚硝酸盐的关键消耗者[47]。协同组系统中同时存在硝化菌和反硝化菌,说明协同组系统中存在SND现象[50],对TN的去除效率较高;而未协同组中主要存在硝化菌属,反硝化菌属较少,对TN的去除效率较低。此外,Micropruina在A1和A2中的相对丰度明显高于B1和B2,由于 Micropruina能在细胞内储存大量的糖类聚合物,可以很好的吸收水体中的有机营养物,说明Micropruina可能是参与有机物去除的功能菌属[51-52]。
2)微生物的功能预测。系统运行68 d后,采用16SrRNA高通量测序技术对系统中微生物进行分析后,基于PICRUSt对协同处理系统A1、A2中细菌的KEGG功能进行了分析(图5)。分别检测到48 535 583、51 425 375个基因。在1层级下,共预测出5大功能。其中占主导的功能均是代谢,其次是遗传信息处理、环境信息处理、细胞过程和有机体系统。协同海绵组A1中比例分别为40.75%、15.94%、14.23%、2.96%和0.85%;协同流化床组A2中比例分别为40.45%、15.93% 、14.06%、3.24%和0.82%。在2层级下,共预测出25种通路,主要代谢通路均为氨基酸代谢、碳水化合物代谢和能量代谢。其中,A1中比例分别为11.05%、10.96%和5.90%,A2中比例分别为10.93%、10.92%和5.91%;主要的环境信息处理通路均为复制与修复和转译,其中,A1中比例分别为6.97%和2.30%,A2中比例分别为6.95%和2.33%;主要的遗传信息处理通路均为膜运输,A1和A2中比例分别为12.18%和11.95%。上述功能信息推测结果表明,A1、A2无明显差别,所预测通路在污水处理厂中普遍存在,反应器中细菌具有丰富的代谢功能、繁殖能力和环境适应力较强,且存在多种代谢通路,说明存在功能冗余。这可能与HCBW有机物成分复杂有关,反应器中有大量的微生物,有机物的代谢任务由多种细菌共同承担,这些微生物可以构建复杂的功能营养网络,最终导致高功能冗余。当环境条件发生变化时,功能冗余可以维持微生物群落的生理能力,这表明微生物的功能结构比微生物群落结构更稳定[53]。
-
1)采用MBBR构建白酒废水与低C/N生活污水协同处理系统,此系统对COD、
NH+4 -N和TN的去除效果均较好,均达到《城镇污水处理厂污染物排放标准》(GB 18918—2002)一级A标准要求,且改性海绵填料组对污染物的去除效果优于流化床填料组。2)进出水中所含物质官能团种类无明显变化,进出水红外光谱特征变化可进一步佐证混合废水经过MBBR系统处理后,NH+4 -N和TN均得到有效的去除。3)在协同处理系统A1和A2中,主要的硝化菌属均为Nakamurella(6.90%、11.94%)、Nitrospira(0.46%、0.21%),主要反硝化菌属均为Amaricoccus(3.48%、3.82%)、Dokdonella(0.15%、0.41%)、Thermomonas(0.25%、0.75%),可能参与有机物去除的功能菌属均为Micropruina(8.88%、2.26%)。4)通过功能预测发现协同处理系统A1、A2中,微生物占主导的功能是代谢,主要代谢通路均为氨基酸代谢(14.78%、14.67%)、碳水化合物代谢(14.67%、14.65%)和能量代谢(7.90%、7.93%)。此外,主要的环境信息处理通路均为复制与修复(9.33%、9.32%)和转译(5.84%、5.84%),主要的遗传信息处理通路均为膜运输(16.29%、16.04%)。
基于MBBR技术的白酒窖底废水与低C/N生活污水协同处理系统的构建及功能微生物分析
Construction of a MBBR-based synergic treatment system for Baijiu pits bottom wastewater and low C/N domestic sewage and analysis on its functional microbes
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摘要: 为解决低C/N污水和高浓度白酒废水(HCBW)处理所面临的问题,采用移动床生物膜反应器(MBBR),构建了白酒窖底废水与模拟低C/N生活污水协同处理系统,以改性海绵填料和流化床填料分别探究HCBW作为反硝化外加碳源对低C/N生活污水处理的影响。结果表明:海绵填料协同处理系统(A1)对COD、
NH+4 -N、TN和色度的平均去除率分别为91.29%、99.08%、89.81%和80.66%,流化床填料系统(A2)的平均去除率分别为90.51%、98.58%、75.73%和76.07%,改性海绵填料的去除效果优于流化床填料;混合废水经过MBBR系统处理后,NH+4 和TN得到了有效去除,出水中的醇类、硫酸盐和磷酸盐物质的相对比例有一定程度增加;协同处理系统A1和A2的硝化优势菌属均为Nakamurella、Nitrospira,反硝化优势菌属均为Amaricoccus、Dokdonella和Thermomonas,可能参与有机物去除的优势功能菌属均为Micropruina。通过功能预测得出:协同处理系统A1、A2中的主要代谢通路均为氨基酸代谢、碳水化合物代谢和能量代谢,主要的环境信息处理通路均为复制与修复和转译,主要的遗传信息处理通路均为膜运输。以上研究结果可为HCBW的资源化利用、低C/N生活污水处理提供参考。Abstract: In order to solve the problems faced by low C/N sewage and Baijiu pits bottom wastewater, a mobile bed biofilm reactor (MBBR) was used to build a collaborative treatment system for the liquor pits bottom wastewater and simulated low C/N sewage. Effect of HCLW as denitrification plus carbon source on low C/N wastewater treatment was investigated by using modified sponge filler or fluidized bed filler. The results showed the average removal rates of COD, ammonia nitrogen, total nitrogen and chroma by the modified sponge packing system (A1) were 91.29%, 99.08%, 89.81% and 80.66%, respectively; and by the fluidized bed packing system (A2) were 90.51%, 98.58%, 75.73% and 76.07%, respectively. The removal effect of the modified sponge filler was better than that of the fluidized bed filler. Ammonia nitrogen and total nitrogen could be effectively removed from the mixed wastewater after MBBR treatment, with a certain increase of alcohols, sulfate and phosphate contents in the effluent. Analysis results of 16S rRNA high-throughput sequencing technology showed that in the synergistic systems of A1 and A2, the dominant nitrifying bacteria were Nakamurella and Nitrospira; the dominant denitrifying bacteria were Amaricoccus, Dokdonella and Thermomonas; and the dominant functional bacteria for organic matter removal were Micropruina. Function prediction indicated that in the system A1 and A2, Amino Acid Metabolism, Carbohydrate Metabolism and Energy Metabolism were the top three metabolic pathways. Replication and Repair as well as Translation processed major environmental information. Membrane Transport was primarily responsible for the genetic information processing pathways. It was supposed to provide a technical support and theoretical basis for resource utilization of high-concentration Baijiu wastewater and treatment of low C/N domestic sewage. -
表 1 填料物理参数
Table 1. Filler physical parameters
填料类型 材质 规格尺寸/mm 比表面积/ (m2·m−3) 孔隙率/% 密度/(kg·m−3) 海绵填料 改性亲水聚氨酯 10×10×10 >90 000 >96 15~20 流化床填料 聚乙烯 Φ10×10 >500 >95 >960 表 2 实验用水水质参数
Table 2. Parameters of test water
实验用水 氮磷及好氧有机物质量浓度/(mg·L−1) 色度 COD -N TN TPNH+4 协同组进水(A) 350±20 37.5 40 4 200±20 未协同组进水(B) 65±10 35 35 2 10~20 窖底水 270 000 2500 6 500 2 400 150 000 表 3 各组系统出水的pH、DO、温度
Table 3. pH, DO and temperature of the effluent of each system
反应器 pH DO/(mg·L−1) 温度/℃ 协同海绵组(A1) 7.54±0.44 3.25±1.35 27±2 协同流化床组(A2) 6.99±0.99 3.15±1.38 27±2 未协同海绵组(B1) 6.06±1.52 3.03±1.45 27±2 未协同流化床组(B2) 5.88±1.6 3.06±1.54 27±2 -
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