污泥絮體特征與微型動物運動速度相關性研究——以自由運動型微型動物為例

胡小兵,汪 坤,李晶晶,陳紅偉,宋維維,江用彬,2,常 靜,鐘梅英

污泥絮體特征與微型動物運動速度相關性研究——以自由運動型微型動物為例

胡小兵1,2*,汪 坤1,李晶晶1,陳紅偉1,宋維維1,江用彬1,2,常 靜1,鐘梅英1

(1.安徽工業(yè)大學建筑工程學院,安徽 馬鞍山 243002；2.生物膜法水質凈化及利用技術教育部工程研究中心,安徽 馬鞍山 243032)

絮體微觀形態(tài)參數(shù)；PCA法；微型動物；運動速度；活性污泥

活性污泥絮體是由微生物(細菌、真菌和微型動物等)與其代謝產物及所吸附的有機、無機物混合組成[1],表面凹凸不平,形態(tài)結構多樣[2].絮體作為活性污泥法中的微型生物處理單元,承擔著有機污染物降解的重要作用[3].絮體的結構特征可用于污泥物理特性、生化活性以及廢水處理效果的判斷[4].目前活性污泥絮體的結構特征分析主要有定量圖像分析法[5]和分形理論法[6-7],后者對于絮體結構特征描述主要集中于理論分析與計算機數(shù)值模擬分析,缺少對分形結構理論完整性的系統(tǒng)表達[8].前者主要運用顯微成像系統(tǒng)采集絮體圖片,利用定量圖像分析法(QIA)對絮體的平均面積、孔隙面積率、圓度、當量直徑、最大Feret直徑等基本參數(shù)進行測量[9-10].但分析過多的基本描述參數(shù)將會加大分析負擔與難度,且容易造成基本描述參數(shù)攜帶信息的重復,因此需要運用數(shù)據(jù)降維方法高效提取基本描述參數(shù)重要特征,降低分析難度[11].主成分分析(PCA)線性降維由于具有簡單性、可解釋性和高延展性等優(yōu)點,使其成為應用廣泛的數(shù)據(jù)降維方法[12].

處于較高營養(yǎng)級的微型動物(包括原生動物和后生動物)作為細菌的主要捕食者,在以活性污泥絮體構建的微生態(tài)系統(tǒng)中起著重要作用,其中指示作用是微型動物最為重要的功能[13].有研究認為溝鐘蟲()、表殼蟲屬(sp.)和累枝蟲屬(sp.)、輪蟲(Rotifer)的出現(xiàn)預示著出水效果和污泥絮體結構特性良好[14-16].小口鐘蟲()和褶累枝蟲()則會出現(xiàn)于低MLSS、高SVI的活性污泥絮體環(huán)境中[13,17].另有研究提出累枝蟲屬(sp.)和輪蟲(Rotifer)的大量出現(xiàn)是活性污泥絮體結構惡化,即將解絮膨脹的征兆[18].溝鐘蟲()和褶累枝蟲()對環(huán)境的適應能力較強,不適宜作為指示生物[19].在絮體結構不太密實的活性污泥中也出現(xiàn)了累枝蟲屬(sp.)和鐘蟲屬(sp.)[20].同時,通過微型動物群落多樣性來指示活性污泥絮體運行狀態(tài)[21],又往往存在微型動物的鑒別誤判、分類和統(tǒng)計分析工作量大、耗時長等問題,限制了其在工程中的實用性.所以需要采用更為簡便、準確的方法表征微型動物對活性污泥絮體結構特性變化的指示作用.

運動行為反應被視為環(huán)境擾動影響的首要指標[22-23].當環(huán)境條件發(fā)生改變時,微型動物在行為學上的應答與反應優(yōu)先于物種群落結構變化[24].在污水處理中,活性污泥絮體結構特性變化是影響微型動物運動的一個重要外部環(huán)境因子.所以采用微型動物的運動方式指示活性污泥絮體結構特性變化,能夠提高分析效果.

本研究使用顯微鏡采集典型微型動物的運動視頻、活性污泥絮體圖片,利用圖像分析軟件進行形態(tài)結構特征參數(shù)量化分析,并采用PCA法進行活性污泥絮體微觀結構降維處理.探究活性污泥絮體與微型動物共存的微生態(tài)系統(tǒng)中,污泥絮體微觀指標與微型動物運動參數(shù)的相互影響關系,為采用典型微型動物定量運動參數(shù)指示活性污泥絮體結構特性提供技術支持.

1 材料與方法

1.1 試驗裝置與用水

本試驗采用由透明有機玻璃制成的高度為90.00cm,外徑為7.50cm,有效容積為3.0L的序批式活性污泥法反應器(SBR).反應器運行周期為12h,包括進水5min,曝氣10h,沉淀110min和排水5min.曝氣時間通過智能控制開關控制,采用電磁式空氣泵(ACO-005,中國)供氣,通過轉子流量計(LZB-3WB,中國)控制曝氣強度(0.2L/min),維持反應器DO在(4.67±0.65)mg/L,反應器在室溫(20±5)℃下運行.

試驗用水取自校園生活區(qū)化糞池,按照化糞池出水與自來水以1:1的比例混合.為了確保進水中營養(yǎng)平衡,按照BOD:TN:TP質量比為100:5:1的比例在試驗用水中添加C6H12O6、NH4Cl和KH2PO4(均為分析純),采用NaHCO3/Na2CO3緩沖劑(pH=9.12)調節(jié)進水pH值.試驗用水主要水質指標如表1所示.

表1 試驗進水水質

1.2 微型動物鑒別與運動參數(shù)分析

在均勻曝氣狀態(tài)下從反應器中分時段取出20mL活性污泥樣品進行混合后置于燒杯中,研究的90d中,等間隔的采集了45個樣品.使用微量移液器(DRAGON,中國)吸出25μL的活性污泥樣品于玻璃載玻片的中央,覆上蓋玻片,置于光學顯微鏡(OLYMPUS,BX53,日本)下進行觀察,參照《微型生物監(jiān)測新技術》[25]與《環(huán)境微生物圖譜》[26]鑒別到種,屬或是類群.

使用顯微CCD攝像頭(Mshot DC30,中國)與明美成像系統(tǒng)(Mshot Digital Imaging System,中國)進行微型動物顯微鏡拍攝視頻圖像采集工作,結合Image J軟件(National Institutes of Health,美國)完成微型動物運動行為參數(shù)的定量表征分析.具體操作和分析方法見文獻[27].

1.3 污泥絮體采集與微觀形態(tài)特征參數(shù)表征

微型動物顯微視頻拍攝采集完成后,將顯微鏡調整至40倍進行污泥絮體顯微圖像拍攝,為保證絮體顯微圖像拍攝的完整性,對載玻片所有區(qū)域進行逐行不重復拍攝,每個載玻片拍攝約60個圖像,共采集了約2700個圖像.使用Image-pro Plus 6.0(Media Cybernetics,美國)軟件對所拍攝的圖像進行8bit調整和直方圖均衡的預處理[28]、自動閾值分割[29],中值濾波和開閉運算的形態(tài)學處理[30]、標尺轉換、殘缺絮體剔除后續(xù)處理操作后,最后導出軟件參數(shù)計算結果[31].

研究中共分析16個絮體微觀形態(tài)參數(shù)[9,32-33].根據(jù)各參數(shù)所表征的物理意義,將其歸屬為絮體大小(SZ)、絮體密實性(CP)、絮體規(guī)則性(RG)和絮體伸長性(ST)4類特征指標[34].對于單個載玻片所拍攝的60張顯微圖像所提取的16個微觀形態(tài)特征參數(shù)取平均值作為單次污泥樣品的參數(shù)值.試驗中共獲得45組圖像和720組數(shù)據(jù)用于絮體微觀形態(tài)特征參數(shù)相關性分析.

1.4 污泥絮體微觀形態(tài)參數(shù)PCA分析

為了更加簡潔、高效地表征絮體結構,便于分析絮體對微型動物運動的影響,擬采用PCA法在保留大部分信息的情況下進一步進行降維分析.在考察污泥絮體微觀形態(tài)參數(shù)之間的相互關系基礎上進行PCA,將多項參數(shù)指標降維至幾個綜合參數(shù)指標[35].使用SPSS 24(IBM,美國)進行主成分分析操作的具體步驟如下:1)進行絮體微觀形態(tài)特征參數(shù)的Pearson相關性分析,計算相關系數(shù)矩陣,判斷是否適合進行主成分分析;2)對SC和SR指標所對應的原始參數(shù)矩陣進行標準化處理后求出相關矩陣的特征根和特征向量;3)通過判斷主成分特征值是否大于1確定SC和SR指標的主成分個數(shù),并使得累計貢獻率達到75%以上[36];4)得出SC和SR的主成分表達式,獲得污泥絮體微觀形態(tài)綜合指標.

采用Pearson相關性分析污泥絮體微觀形態(tài)綜合指標(SC,SR)與自由運動型微型動物運動速度之間的相關性特征.

2 結果與討論

2.1 污泥絮體微觀形態(tài)特征參數(shù)分析

2.1.1 PCA相關性分析 使用PCA法進行絮體微觀形態(tài)特征參數(shù)降維處理的前提是要保證各個參數(shù)間存在一定的相關性.

圖1 絮體微觀形態(tài)特征參數(shù)相關性

此外,FD與Ext間呈顯著負相關(=-0.80,< 0.01),說明隨著絮體的分形維數(shù)增加,絮體形狀越規(guī)則,絮體結構緊湊,但絮體充實度降低[38-39].

表征絮體微觀形態(tài)特征的2類綜合指標(SC,SR)不僅內部參數(shù)間存在較強相關性,不同類別參數(shù)間也具有一定的相關性,約50%的微觀形態(tài)參數(shù)間相關系數(shù)大于0.3,適合利用PCA法進行降維分析,建立絮體大小密實度(SC)和形狀規(guī)則度(SR)綜合指標[40].

2.1.2 基于PCA法的絮體形態(tài)特征指標分析 利用PCA法進行絮體大小密實度指標(SC)9個參數(shù)(Amean、Deq、Fmax、、Pconv、、、HR和Ext)的降維分析(表2).

表2 SC參數(shù)的主成分信息提取

注:選取特征值31的成分,下同.

9個參數(shù)在不同主成分上的因子載荷如圖2所示.

圖2 SC參數(shù)因子載荷圖

式中:Z表示標準化參數(shù)數(shù)據(jù),下同.

故降維后的絮體大小密實度綜合指標

表征絮體形狀規(guī)則度指標(SR)的7個參數(shù)(Asp、ST、RR、BR、FF、RO和FD)經過PCA法降維成2個主成分(表3),累計保留76.364%信息.

表3 SR參數(shù)的主成分信息提取

7個參數(shù)在不同主成分上的因子載荷如圖3所示.

圖3 SR參數(shù)因子載荷圖

PC1和PC2表達式為:

故降維后的絮體形狀規(guī)則度綜合指標

2.2 絮體對微型動物運動影響

圖4 銳利楯纖蟲(A. lynceus)運動參數(shù)

a:絮體間游泳;b:絮體上爬行;c:游泳-爬行互變

2.3 絮體結構與微型動物運動速度的相關性

圖5 SC和SR與微型動物運動速度(V和W)的相關系數(shù)

圖6 凹扁前口蟲(F. depressa)運動軌跡圖

左圖為未受絮體干擾;右圖為受絮體干擾

3 結論

[1] 完顏徤飛.基于圖像分析技術的活性污泥沉降性能微觀參數(shù)響應研究[D]. 馬鞍山:安徽工業(yè)大學,2015.

Wanyan J F. Microscopic parameters response to activated sludge settling ability based on image analysis technology [D]. Ma'anshan: Anhui University of Technology,2015.

[2] 彭永臻,郭建華.活性污泥膨脹機理、成因及控制 [M]. 北京:科學出版社,2012.

Peng Y Z,Guo J H. Activated sludge expansion mechanism,causes and control [M]. Beijing: Science Press,2012.

[3] Yan X,Zheng S,Yang J,et al. Effects of hydrodynamic shear stress on sludge properties,N2O generation,and microbial community structure during activated sludge process [J]. Journal of Environmental Management,2020,274:111215.

[4] Jin B,Wilén B,Lant P. Impacts of morphological,physical and chemical properties of sludge flocs on dewaterability of activated sludge [J]. Chemical Engineering Journal,2004,98(1/2):115-126.

[5] Leal C,Val Del Río A,Ferreira E C,et al. Validation of a quantitative image analysis methodology for the assessment of the morphology and structure of aerobic granular sludge in the presence of pharmaceutically active compounds [J]. Environmental Technology & Innovation,2021,23:101639.

[6] Hriber?ek M,?ajdela B,Hribernik A,et al. Experimental and numerical investigations of sedimentation of porous wastewater sludge flocs [J]. Water Research,2011,45(4):1729-1735.

[7] Vahedi A,Gorczyca B. Predicting the settling velocity of flocs formed in water treatment using multiple fractal dimensions [J]. Water Research,2012,46(13):4188-4194.

[8] 阮曉東,劉俊新.活性污泥絮體的分形結構分析[J]. 環(huán)境科學,2013,34(4):1457-1463.

Ruan X D,Liu J X. Analysis of the fractal structure of activated sludge flocs [J]. Environmental Science,2013,34(4):1457-1463.

[9] Costa J C,Mesquita D P,Amaral A L,et al. Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment: a review [J]. Environmental Science and Pollution Research,2013,20(9):5887-5912.

[10] Mesquita D P,Amaral A L,Ferreira E C. Activated sludge characterization through microscopy: A review on quantitative image analysis and chemometric techniques [J]. Analytica Chimica Acta,2013,802:14-28.

[11] Mesquita D P,Amaral A L,Ferreira E C. Identifying different types of bulking in an activated sludge system through quantitative image analysis [J]. Chemosphere,2011,85(4):643-652.

[12] Lee L C,Jemain A A. On overview of PCA application strategy in processing high dimensionality forensic data [J]. Microchemical Journal,2021,169:106608.

[13] Hu B,Qi R,An W,et al. Dynamics of the microfauna community in a full-scale municipal wastewater treatment plant experiencing sludge bulking [J]. European Journal of Protistology,2013,49(4):491-499.

[14] Araújo Dos Santos L,Ferreira V,Pereira M O,et al. Relationship between protozoan and metazoan communities and operation and performance parameters in a textile sewage activated sludge system [J]. European Journal of Protistology,2014,50(4):319-328.

[15] Lee S,Basu S,Tyler C W,et al. Ciliate populations as bio-indicators at Deer Island Treatment Plant [J]. Advances in Environmental Research,2004,8(3):371-378.

[16] Zhou K,Xu M,Dai J,et al. The microfauna communities and operational monitoring of an activated sludge plant in China [J]. European Journal of Protistology,2006,42(4):291-295.

[17] Foissner W. Protists as bioindicators in activated sludge: Identification,ecology and future needs [J]. European Journal of Protistology,2016,55:75-94.

[18] 王基成,周彥波,盧傳敬,等.活性污泥系統(tǒng)中微型動物監(jiān)測與指示生物的應用[J]. 煉油技術與工程,2009,39(2):59-62.

Wang J C,Zhou Y B,Lu C J,et al. Study on microfauna monitoring and application of bioindicator in activated sludge plant [J]. Petroleum Refinery Engineering,2009,39(2):59-62.

[19] Madoni P. A sludge biotic index (SBI) for the evaluation of the biological performance of activated sludge plants based on the microfauna analysis [J]. Water Research,1994,28(1):67-75.

[20] Ogleni N,Arifoglu Y D,Ileri R. Microbiological and performance evaluation of sequencing batch reactor for textile wastewater treatment [J]. Water Environment Research,2012,84(4):346-353.

[21] Canals O,Salvado H,Auset M,et al. Microfauna communities as performance indicators for an A/O Shortcut Biological Nitrogen Removal moving-bed biofilm reactor [J]. Water Research,2013,47(9): 3141-3150.

[22] Villarroel M J,Ferrando M D,Sancho E,et al. Daphnia magna feeding behavior after exposure to tetradifon and recovery from intoxication [J]. Ecotoxicology and Environmental Safety,1999,44(1):40-46.

[23] Bownik A. Daphnia swimming behaviour as a biomarker in toxicity assessment: A review [J]. Science of the Total Environment,2017,601-602:194-205.

[24] Pan Y,Zhang L,Lin C,et al. Influence of flow velocity on motor behavior of sea cucumber Apostichopus japonicus [J]. Physiology & Behavior,2015,144:52-59.

[25] 沈韞芬,章宗涉,龔循矩,等.微型生物監(jiān)測新技術[M]. 北京:中國建筑工業(yè)出版社,1990.

Shen W F,Zhang Z S,Gong X J,et al. New technology of micro biological monitoring [M]. Beijing: China Architecture & Building Press,1990.

[26] 馬 放,楊基先,魏 利.環(huán)境微生物圖譜[M]. 北京:中國環(huán)境科學出版社,2010.

Ma F,Yang J X,Wei L. et al. Environmental microorganisms Atlas [M]. Beijing: China Environmental Science Press,2010.

[27] Hu X,Wang K,Chang J,et al. Establishment of a comprehensive analysis method for the microfaunal movement in activated sludge [J]. Environmental Science and Pollution Research,2021,28(14):17084-17097.

[28] Pandolfi D,Pons M. Gram-staining characterisation of activated sludge filamentous bacteria by automated colour analysis [J]. Biotechnology letters,2004,26(24):1841-1846.

[29] Yu R,Chen H,Cheng W,et al. Simultaneously monitoring the particle size distribution,morphology and suspended solids concentration in wastewater applying digital image analysis (DIA) [J]. Environmental Monitoring and Assessment,2009,148(1-4):19-26.

[30] Maini R,Aggarwal H. A comprehensive review of image enhancement techniques [J]. Journal of Computing,2010,2(3):8-13.

[31] 張新喜,完顏健飛,胡小兵,等.基于活性污泥絮體微觀參數(shù)的污泥沉降性能判別[J]. 環(huán)境科學學報,2015,35(12):3815-3823.

Zhang X X,Wanyan J F,Hu X B,et al. Discriminant of activated sludge settling ability based on floc microscopic parameters [J]. Acta Scientiae Circumstantiae,2015,35(12):3815-3823.

[32] Boztoprak H,?zbay Y,Gü?lü D,et al. Prediction of sludge volume index bulking using image analysis and neural network at a full-scale activated sludge plant [J]. Desalination and Water Treatment,2015,57(37):17195-17205.

[33] Koivuranta E,Keskitalo J,Haapala A,et al. Optical monitoring of activated sludge flocs in bulking and non-bulking conditions [J]. Environmental Technology,2013,34(5):679-686.

[34] 胡小兵,張 琳,汪 坤,等.基于絮體結構指標的絲狀菌膨脹污泥SVI預測[J]. 中國給水排水,2022,38(1):16-22.

Hu X B,Zhang L,Wang K,et al. Sludge volume index prediction of filamentous bulking sludge based on floc structure index [J]. China Water & Wastewater,2022,38(1):16-22.

[35] Jolliffe I T,Cadima J. Principal component analysis: a review and recent developments [J]. Philosophical Transactions,Series A,Mathematical,Physical,and Engineering Sciences,2016,374:20150202.

[36] 謝春生,楊志遠,劉 錕,等.航班運行控制風險評估精度提升方法[J]. 安全與環(huán)境學報,2022,22(3):1227-1234.

Xie C S,Yang Z Y,Liu K,et al. A method of flight operations control risks assessment accuracy improvement [J]. Journal of Safety and Environment,2022,22(3):1227-1234.

[37] Mu Y,Yu H. Biological hydrogen production in a UASB reactor with granules. I: Physicochemical characteristics of hydrogen-producing granules [J]. Biotechnology and Bioengineering,2006,94(5):980-987.

[38] Niu M,Zhang W,Wang D,et al. Correlation of physicochemical properties and sludge dewaterability under chemical conditioning using inorganic coagulants [J]. Bioresource Technology,2013,144:337-343.

[39] Wilén B,Jin B,Lant P. The influence of key chemical constituents in activated sludge on surface and flocculating properties [J]. Water Research,2003,37(9):2127-2139.

[40] 胡小兵,朱榮芳,葉 星,等.基于降維分析的活性污泥絮體結構特征指標[J]. 中國環(huán)境科學,2017,37(5):1759-1768.

Hu X B,Zhu R F,Ye X,et al. Characteristic indexes of floc structure in activated sludge based on dimensionality reduction methods [J]. China Environmental Science,2017,37(5):1759-1768.

[41] Martín-Cereceda M,Serrano S,Guinea A. A comparative study of ciliated protozoa communities in activated-sludge plants [J]. FEMS Microbiology Ecology,1996,21(4):267-276.

[42] Hu B,Qi R,Yang M. Systematic analysis of microfauna indicator values for treatment performance in a full-scale municipal wastewater treatment plant [J]. Journal of Environmental Sciences (China),2013,25(7):1379-1385.

[43] Araújo Dos Santos L,Ferreira V,Pereira M O,et al. Relationship between protozoan and metazoan communities and operation and performance parameters in a textile sewage activated sludge system [J]. European Journal of Protistology,2014,50(4):319-328.

[44] Espinosa-Rodríguez C A,Sarma S S S,Nandini S. Interactions between the rotifer Euchlanis dilatata and the cladocerans Alona glabra and Macrothrix triserialis in relation to diet type [J]. Limnologica,2012,42(1):50-55.

[45] Chen J,Wang Z,Li G,et al. The swimming speed alteration of two freshwater rotifers Brachionus calyciflorus and Asplanchna brightwelli under dimethoate stress [J]. Chemosphere,2014,95:256-260.

Microscopic characteristics of sludge flocs as related to the movement velocity of microfauna: A case study of free-moving microfauna.

HU Xiao-Bing1,2*,WANG Kun1,LI Jing-Jing1,CHEN Hong-Wei1,SONG Wei-Wei1,JIANG Yong-Bin1,2,CHANG Jing1,ZHONG Mei-Ying1

(1.College of Architectural Engineering,Anhui University of Technology,Ma'anshan 243002,China；2.Engineering Research Center of Water Purification and Utilization Technology based on Biofilm Process,Ministry of Education,Ma'anshan 243032,China).,2022,42(8)：3666～3673

microscopic characteristics of flocs；PCA；microfauna；movement velocity；activated sludge

X703

A

1000-6923(2022)08-3666-08

2022-01-05

教育部工程研究中心項目(BWPU2021ZY01,02; BRT19-02);安徽省重點研究與開發(fā)計劃(202004h07020027)

* 責任作者,副教授,hxb6608@163.com

胡小兵(1966-),男,安徽涇縣人,副教授,博士,主要從事水處理生物學與污水生態(tài)處理研究.發(fā)表論文50余篇.