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Correlating exoenzyme activities, operational parameters, cell viability and EPS in a membrane bioreactor treating domestic wastewater

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I. Amorós1, C. Grañana1, L. Borrás2, E. Zuriaga-Agustí3, A. Zornoza1 and J.L. Alonso1 1Instituto

INTRODUCTION

Universitario de Ingeniería del Agua y Medio Ambiente, (IIAMA). Universitat Politècnica de València, Spain (e-mail: jalonso@ihdr.upv.es) 2Departamento de Ingeniería Química, Universitat de València, 46100 Burjassot, Valencia, Spain 3Instituto de Seguridad Industrial, Radiofísica y Medioambiental (ISIRYM), Universitat Politècnica de València, Spain

Membrane biorreactors (MBR )systems are based on the combination of the activated sludge system and membrane technologies to separate the particulate material from water, avoiding the need of a secondary clarifier. The main operational problem in MBRs is the membrane fouling or biofouling. Equalization Tank

CAS

Aeration Tank

Secondary clarifier

MBR

Effluent Tank

Effluent Water

Wastewater

Equalization Tank Effluent Tank

Effluent Water

Wastewater

Activated Sludge

Activated Sludge

Figure 1. Scheme of Activated Sludge and MBR treatments

Bacteria present in the biomass of an activated sludge system produce sticky compounds denominated extracellular polymeric substances (EPS) which result from active bacterial secretion, shed from the cell surface or cell lysis and mediate their adhesion to surfaces as the submerged membrane module. After long time filtration of wastewater, both accumulation of EPS and amount of microbial populations reach to maximum, which also indicate the minimum permeating capacity of a membrane module. EPS are mainly polysaccharides, proteins, nucleic acids and lipids. Recent studies point to EPS as the main cause of membrane fouling. Relationships between them and operational parameters as potential foulants have been determined. Enzymatic activity is involved in the degradation of biopolymers and cell viability gives information about cells damaged.

MATERIALS AND METHODS

Figure 2. Biofouling

Sludge Samples from a MBR treating domestic wastewater (316 m3) have been analysed for Exoenzymatic activities (β-glucuronidase and phosphatase), protein, carbohydrates and cell viability. After that statistical analyses were carried out by using Canonical correspondance analyses (CCA), a method of direct gradient analysis. • β-glucuronidase and phosphatase: Determined by fluorogenic substrate (ELF 97) which yields and insoluble fluorescent precipitate upon cleavage the enzyme. The spatial distribution of enzymatic activity in whole flocs are detected by epifluorescence microscopy and quantification by using an optimization of Matlab®. • EPS: were extracted by chemical extraction with cation exchange resin (CER) and later analyses with BCA (proteins) and anthrone (carbohydrates). • Cell viability: Kit Backlight and fluorescence microscopy. Table 1. Operating parameters and influent characteristics Operational parameters and physicho-chemicals parameters were supplied by the treatment plant.

RESULTS

Figure 5. Cell viability Figure 4. Quantification of enzymatic activity (Matlab)

Enzymatic Activity

Standard deviation

1004

180-2326

814

HRT

56.9

47.1-65.7

6.4

OLR

0.014

0.01-0.02

0.004

mg·L-1

MLSS

9853

8232-11648

1259

mg·L-1

MLVSS

7626

6127-8796

1006.407

°C

Tr

22.0

18.3-28.4

4.0409

%

%MLVSS

77.3

74.1-80.5

2.3

pH_inf

8.1

8-8.4

0.1

mg·L-1

BOD5_inf

234

180-290

37

Units

Excess sludge production Hydraulic retention time

Kg·d-1

ESP

h Kg BOD/kg MLVSS day

Organic loading rate

Total bacteria

Range

Parameters

Acronym Average

Mixed liquor suspended solids Mixed liquor volatile suspended solids Temperature in reactor Percentage of Mixed liquor volatile suspended solids pH in influent Biological oxygen demand in influent Chemical oxygen demand in influent Conductivity in influent

mg·L-1

COD_inf

521

371-636

85

µS/cm

Cond_inf

2780

2680-2830

58

Total nitrogen in influent

mg l-1

TN_inf

69.6

60.1-79.7

6.2

Figure 3. Enzymatic activity

Glucuronidase

Carbohydrates

40

Phosphatase

3

30

2

20

1

10

0

0 1

2

3

4

5

6

7

8

9

10

11

12

13

Sample

Figure 6. EPS vs glucoronidase and phosphatase activity

% Exoenzimatic Activity

Proteins

EPS (mg/g VSS)

% Activity

EPS 4

40

Glucoronidase Phosphatase

30

3

20

2

10

1

0

0 1

2

3

4

5

6

7

8

9

10

11

12

13

Sample

Figure 7. Proteins and carbohydrates vs glucoronidase and phosphatase activity

0,8

Proteins (mg BSA/g SVS) Carbohydrates (mg Glucose/gVSS)

4

50

5

0,6

0,6

0,4

0,4

Tr

0,2 0 OLR -0,2 -0,4

0,2 Phosphatase HRT EPS Carbohydrates Cell viability MLSS Proteins MLVSS Glucuronidase %MLVSS ESP

-0,6

TP_inf

TN_inf

cond_inf

F2 (14,00 %)

50

F2 (21,10 %)

5

EPS Proteins Phosphatase Cell viability pH_inf carbohydrates Glucuronidase

0 -0,2 -0,4

BOD5_inf COD_inf

-0,6

-0,8 -1 -1,4 -1,2 -1 -0,8 -0,6 -0,4 -0,2

-0,8 0

0,2 0,4 0,6 0,8

1

1,2 1,4

-1

-0,8

-0,6

-0,4

-0,2

0,2

0,4

0,6

0,8

1

F1 (77,43 %)

F1 (73,60 %)

Figure 8. Biplot Cell viability, EPS, exoenzimatic activities - Operational parameters (axes F1 y F2: 94,71%)

0

Figure 9. Biplot Cell viability, EPS, exoenzimatic activities – Influent pysicochemical parameters (axes F1 y F2: 91,43%)

Results showed that 94% of cells from the MBR were viable and only 6% of the cells were damaged. CCA results revealed the relationships between exoenzymatic activities, cell viability and EPS with the operational parameters and wastewater influent characteristics. Phosphatase was correlated with high levels of hydraulic retention time (HRT), while βglucuronidase was related with excess sludge production (ESP). Bioreactor temperature (Tr) correlated negatively with β- gucuronidase and phosphatase in agreement with other works. Results of biplot analysis of influent water showed an inverse relationship between the concentration of total phosphorus (TP) and the phosphatase and β-gucuronidase exoenzimatic activities. The increase in the availability of C in the influent might have contribute negatively to the phosphatase activity.

CONCLUSIONS  Studies on the interacting biological, chemical and physical phenomena in MBRs and innovative techniques to determine processes can contribute to a better knowledge of biofouling and might lead to more robust MBRs operation. ACKNOWLEDGEMENTS: This work was supported by grant no. ALI CGL2011-29231-C05-01 from the Spanish Ministry of Economy and Competitiveness.


2013 - Correlating exoenzyme activities, operational parameters, cellular viability and EPS in a MBR