EFECT OF REACTOR FEEDING PATTERN ON

PERFORMANCE OF AN ACTIVATED SLUDGE SBR

By

Francisco José Cubas Suazo

Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in

partial fulfillment of the requirements for the degree of

Master of Science

In

Environmental Engineering

Dr. John T. Novak, Chair

Dr. Gregory D. Boardman

Dr. Matthew J. Higgins

September 6, 2006

Blacksburg, Virginia

Keywords: Activated sludge, cations, feeding pattern, sodium, bioflocculation, settling,

biopolymers, sequencing batch reactor, divalent cation bridging.

Copyright © 2006, Francisco José Cubas Suazo

EFECT OF REACTOR FEEDING PATTERN ON PERFORMANCE OF AN

ACTIVATED SLUDGE SBR

Francisco José Cubas Suazo

ABSTRACT

The possible effects of changes in the feeding pattern on activated sludge properties related to

bioflocculation have been analyzed in lab scale sequencing batch reactors (SBR) in order to

determine if these changes in effluent water quality and settling and dewatering properties are

significant, so they can be considered in future studies or if they can be recommended as

crucial when operating and designing wastewater treatment plants. The activated sludge

process is widely used to treat wastewater from both industrial and municipal sources.

Biomass from industrial facilities containing high monovalent to divalent ion content usually

settles poorly, which leads to low quality effluents that fail to meet environmental

requirements. Therefore, the combined effect of feeding pattern plus the addition of sodium

to activated sludge reactors was studied in this experiment.

A series of SBRs were operated at different sodium concentrations that ranged from 1.5 – 15

meq/L and different feeding times that ranged from 1 minute to 4 hours. Biomass samples

were taken from each reactor to study the settling and dewatering properties and effluent

samples were used to analyze the amount of organic matter and exocellular polymeric

substances present due to deflocculation. As expected, the changes in feeding strategies

affected all of the properties measured. When the feeding time was maintained low (pulse

feed) the effluent quality and settling properties were the best. As the feeding time was

increased the effluent quality, settling, and dewatering properties increased suggesting that the

way in which the reactors were fed affected the overall bioflocculation process. The causes of

the high deflocculation observed are not well understood, but data suggest that a microbial

community change could have affected exocellular biopolymers which are believed to play an

important role on bioflocculation.

iii

This research demonstrates the importance of the interaction between cation content and

feeding pattern when operating a wastewater treatment plants and when reporting lab-scaled

results related to settling and bioflocculation.

iv

ACKNOWLEDGEMENTS

The author would like to express his appreciation to Dr. John T. Novak, academic and

research advisor, for his support, guidance and constant collaboration to make possible the

completion of this work. Special recognition to both committee members, Dr. Matthew J.

Higgins for his valuable time, recommendations, and contribution on the microbiological

analysis related to this study and Dr. Gregory D. Boardman for his contribution and ideas

used on the methodologies and analysis performed on this study.

Thanks to the staff of the OAS-LASPAU program, especially to Mrs. Jennifer Havlicek,

Placement Advisor, and Ms. Juliana Vanegas, Program Advisor, for her continuous support.

Thanks to the staff of the National Autonomous Service of Aqueducts and Sewage (SANAA)

of Honduras, especially to the authorities for providing the support through out the entire

scholarship. Gratitude to Dr. Nancy Love for providing input on this research. Special thanks

to Julie Petruska and Jody Smiley for their continuous help and guidance through out the

entire experimental analysis phase, Jeff Parks for the analyses on the Inductively Coupled

Plasma instrumentation, Paolo Scardina for performing Zeta Potential analysis. Special

recognition to José Cerrato for his friendship, technical assistance, and exceptional

contribution on the statistical analysis performed in this study and Nestor Murray for his help

and support. Special recognition and gratitude to all of my lab mates and friends Sathya

Easwaran, Chris Wilson, Chris Muller, and Chul Parks for their technical support, help,

support, and contribution to all the lab skills learned through the entire research process.

The author wants to dedicate this work to the Cubas family for their perpetual support and for

being the source of inspiration always; Marcela Girón for providing the strength, knowledge,

and wisdom to his life; and the impoverished people of Honduras for providing the motivation

to pursue and contribute to a better global water quality and environment. And above

everything mentioned the author wants to thank and dedicate his entire work to God. Funding

for my scholarship was provided by the Organization of American States and the help of

Virginia Polytechnic Institute of Technology through its fellowship program OAS-LASPAU.

Any opinions, findings, conclusions or recommendations expressed in this material are those

v

of the authors and do not necessarily reflect the views of the Organization of American States

and LASPAU.

vi

Table of Contents

CHAPTER I................................................................................................................................1

Literature Review .......................................................................................................................1

1.1 Background information on wastewater treatment.....................................................1

1.2 Solid-Liquid separation ..............................................................................................3

1.3 Bioflocculation ...........................................................................................................4

1.4 Role of Filamentous Bacteria and SRT ......................................................................7

1.5 Cations and there effect in settling .............................................................................9

1.6 Sequencing Batch Reactors (SBR) and Feeding Pattern..........................................14

CHAPTER II ............................................................................................................................18

Combined Effect of Reactor Feeding Pattern and Cations on the Performance of an Activated

Sludge SBR ..............................................................................................................................18

Introduction ..........................................................................................................................19

Materials and Methods .........................................................................................................22

Results and Discussion.........................................................................................................26

Implications: .........................................................................................................................50

Engineering and Scientific Significance. .............................................................................52

Conclusions ..........................................................................................................................53

References ................................................................................................................................55

Appendix ..................................................................................................................................58

vii

List of Tables

Table 1-1 Minimum national standards for secondary treatment a............................................2

Table 2-1 SBR operating times ...............................................................................................22

Table 2-2 Cations used in the feed. .........................................................................................23

Table 2-3 Sodium concentrations for each of the three phases. ..............................................24

Table 2-4 Average pH for each reactor in all 3 phases ...........................................................27

Table 2-5 Average MLSS for each reactor with an SRT of 18 days.......................................28

Table 2-6. Summary of effluent quality and settling parameters for steady state conditions .30

Table A-1. Cations concentration in bactopeptone used on feed ............................................58

List of Figures

Figure 1-1. Capsules and slime layers produced by bacteria. ...................................................5

Figure 1-2. Potential role of cations in bioflocculation...........................................................13

Figure 1-3. Typical sequence of events in a SBR ...................................................................15

Figure 2-1. Activated sludge and settling properties as a function of time for phase II. Steady

state conditions between day 30 and day 55. ...........................................................................25

Figure 2-2. MLSS vs. time in the reactors with the highest sodium concentration ................29

Figure 2-3. Effluent TSS comparison......................................................................................32

Figure 2-4. Effluent COD (mg/L) for A-Phase I, B-Phase II, and C-Phase III.......................33

Figure 2-5. Total effluent COD for each phase. ......................................................................34

Figure 2-6. Effluent soluble COD for each phase ...................................................................35

viii

Figure 2-7. Effluent quality parameters comparison for a M:D ratio of 5.2 ...........................36

Figure 2-8. Settling properties as a function of feeding time and sodium concentration........37

Figure 2-9. CST comparison for three different feeding patterns ...........................................39

Figure 2-10. CST comparison for a M:D ratio of 5.2..............................................................40

Figure 2-11. Optimum dose for phase II and phase III ...........................................................40

Figure 2-12. Zeta-potential values for phase II and phase III .................................................41

Figure 2-13. Effluent polysaccharides (mg/L) for A-Phase I, B-Phase II, and C-Phase III....43

Figure 2-14. Effluent proteins (mg/L) for A-Phase I, B-Phase II, and C-Phase III ................44

Figure 2-15. Total effluent polysaccharides for each phase....................................................45

Figure 2-16. Soluble effluent polysaccharides for each phase ................................................45

Figure 2-17. Total effluent proteins for each phase ................................................................46

Figure 2-18. Soluble effluent proteins for each phase.............................................................47

Figure 2-19. Proteins and Polysaccharides comparison for a M:D ratio of 5.2 ......................48

Figure 2-20. Effect of feeding pattern on bioflocculation for 1.5 meq/L Na+.........................50

Figure 2-21. Effect of feeding pattern on bioflocculation for 6.0 meq/L Na+.........................51

Figure 2-22. Effect of feeding pattern on bioflocculation for 15 meq/L Na+..........................51

1

CHAPTER I

Literature Review

1.1 Background information on wastewater treatment

Wastewater treatment is a combination of unit operations and processes to treat polluted water

collected from municipalities and industries in order to be returned to receiving waters or to

the land for future reuse. Water treatment consists of the removal of pollutants that can harm

the aquatic environment. The ultimate goal of wastewater engineering is the protection of

public health while maintaining a balance with the environment considering social,

economical and political aspects.

Unit operations and processes, which are linked together in a process train, involve physical,

chemical, and biochemical reactions that achieve the destruction, stabilization, collection or

transformation of soluble or suspended pollutants some of which are classified as oxygen-

demanding or nutrients that contribute oxygen depletion or eutrophication of water bodies.

For this reason most of the unit operations used for the stabilization of organic matter are

biochemical which can be classified, within a wide range of options, as attached or suspended

growth, with activated sludge the most common process within the suspended growth

bioreactors.

Effluents discharged into a receiving body of water are regulated by the authorities whose

goals are to protect human health and the environment. As research has become more

extensive and as technology for analyzing specific constituents have become more

comprehensive, more stringent limits have been imposed, requiring higher water quality and

the use of the latest available technology in order to achieve the standards. Table 1-1 shows

an example of minimum national standards for secondary treatment. (Metcalf and Eddy,

2003)

2

Table 1-1 Minimum national standards for secondary treatment a

Characteristics of discharge

Unit of

measurements

Average 30-day

concentration

Average 7-day

concentration c

BOD5 mg/L 30 d 45

Total Suspended Solids mg/L 30 d 45

Hydrogen-ion concentration pH units 6.0 – 9.0 all times e 6.0 – 9.0 all times e

CBOD5 mg/L 25 40 a Federal Register (1988, 1989). c Not to be exceeded. d Average removal shall not be less than 85 percent. e Only enforced if caused by industrial wastewater or by in-plant inorganic chemical addition. f May be substituted for BOD5 at the option of the permitting authority.

Most municipal wastewater is generated from domestic sources but there has been increasing

amounts of industrial wastewater discharged to these municipal collection systems

introducing large amounts of heavy metals and synthetic organic compounds. Many of the

compounds generated from industrial processes are difficult and costly to treat; therefore,

effective pretreatment becomes an essential part of water quality management (Metcalf and

Eddy, 2003).

Differences exist between the characteristics of industrial and municipal wastewaters. Most

of these waters differ in the amount of cations (monovalent, divalent, trivalent), chemical

oxygen demand (COD) or biological oxygen demand (BOD) in the influent. It has also been

suggested that there is no substantial concentrations of proteins and polysaccharides in the

influent stream of many industrial plants while their presence has been observed in the

effluent (Murthy and Novak, 2001). Differences are also found in the effluent quality.

Researchers have found that the effluent quality at municipal plants is generally better than

most of industrial plants containing similar concentrations of monovalent and divalent

cations, and also it has been suggested that activated sludge from industrial facilities often

exhibit poor flocculation compared to domestic wastewater systems and this is attributed to

the absence of extra cellular polymeric substances (Park et al., 2006).

3

One characteristics of some industrial wastewaters is the high concentrations of sodium, with

concentrations up to 2,000 mg/L (Murthy et al., 1998). The high sodium concentration is the

result of adding many sodium based compounds such as sodium hydroxide (NaOH) or

sodium bicarbonate (NaHCO3) for manufacturing processes, prevention of volatilizations of

acetic acid or for pH control which requires some base addition. The effect of cations in

wastewater treatment will be discussed later.

1.2 Solid-Liquid separation

The solid-liquid separation is a physical process which involves the removal of solid particles

that can be in a suspended or colloidal state after every stage of treatment. The removal of

this suspended and colloidal material primarily composed of biological particles from the

biochemical operations is mostly done by gravity sedimentation. The efficiency of the

activated sludge treatment process is correlated to a good solid-liquid separation, which is

strongly determined by the settling properties (Govoreanu et al., 2003). For a successful

separation the microorganisms must clump together to form flocs of a defined size, porosity,

density and strength to allow them to settle and compact well without leaving a high

concentration of suspended solids in the effluent. Since single bacterial are relatively small (≈

0.5 – 1.0μ) (Madigan et al., 2003), it would be practically impossible to remove them in this

way if they grew individually. Fortunately, for practical and operational aspects, bacteria in

suspended cultures under the appropriate growth conditions grow and attach to each other

forming clumps or gelatinous particles called bioflocs. The bacteria responsible for this

phenomenon are called floc-forming bacteria and a variety of species fall into this category.

An ideal biofloc is one that is strong and compacts well so that it settles properly producing a

dense sludge for recycle to the bioreactor and a high quality effluent (Grady et al., 1999).

Unfortunately, not all bacteria present in suspended growth environments are beneficial when

related to floc formation. One type of organism is filamentous bacteria that grow in long

strands that become intermeshed with the floc particles and affect sedimentation, although

4

some number of filaments is necessary to give strength to the floc. These filaments can act as

a backbone that holds the floc together.

1.3 Bioflocculation

Bioflocculation is one of the most important steps in building a big, strong, dense, and

compact settleable floc in order for the wastewater treatment process to achieve a good solid-

liquid separation and therefore reach the desired effluent water quality. For a better

understanding on microbial flocculation, the structure and components of the floc must be

defined in order to propose means to change their properties and improve the settling and

dewatering properties of the activated sludge.

Activated sludge floc consist primarily of biopolymer produced by the cells, cations

(monovalent, divalent, and trivalent), microorganisms (floc forming bacteria and filamentous

bacteria), and other substances or particles such as polymeric substances that are part of the

influent wastewater or any suspended solid or debris trapped within the floc that would affect

its properties. Bioflocs are highly hydrated and very heterogeneous (Park et al., 2006) and

flocs with very different properties and morphologies may occur, depending on the conditions

in the activated sludge treatment plant and wastewater composition (Wilén et al., 2003).

Bioflocs are held together by means of exocellular polymers and divalent cations that interact

each other by electro potential forces (Bruus et al., 1992). Although most of the biopolymer

is incorporated within the activated sludge floc matrix a portion of the biopolymer remains

unattached in solution as biocolloids (Murthy and Novak, 1999).

Researchers have used the concept of microstructure and macrostructure to describe the

formation of bioflocs. The microstructure of the floc is considered to be the matrix composed

of microbes and exocellular polymers substances (EPS) bound together (bioflocculation

process), while the macrostructure consists of the microorganism such as filamentous bacteria

that provide the backbone for developing a larger and stronger floc. The literature suggests

that an improvement in the microstructure of the floc may overcome the negative impacts of

having too many filamentous organisms in the macrostructure that causes bulking. This area

5

needs further research in order to establish a well defined relationship among the EPS, cations

and filamentous microorganisms (Higgins et al., 2004b). Other authors suggest that two

different polymers exist; one that is very firmly bound to cells and within micro colonies of

cells and one that is more loosely bound in the floc matrix (Wilén et al., 2003).

Complex microbial aggregates, as activated sludge flocs, are poorly described and understood

in terms of the individual components and the flocculation mechanisms; however, there is a

point of agreement in that exocellular polymer substances (EPS) are the central to aggregation

of individual bacteria into floc particles (Grady et al., 1999). Researchers suggest that EPS,

both in terms of quantity and quality, are very important for the floc properties of the

activated sludge.

Figure 1-1. Capsules and slime layers produced by bacteria.

The EPS are mainly composed of carbohydrates, proteins, nucleic acids, lipids and humic

substances. The production of EPS is believed to be dependent on the growing phase of the

bacteria and the growth environment. The biopolymers produced by the cells form a matrix

which encapsulates the microbes and aids in the aggregation of the microorganisms or are

excreted into the surrounding medium as slime. Figure 1-1 illustrates these capsules formed

by bacteria. The floc formed is very heterogeneous and is made up of microbial colonies that

are embedded in cloud of EPS where a number of intermolecular interactions contribute to the

binding of the flocs components. Researchers agree that these interactions are hydrophobic,

steric and are a consequence of cations interactions (Wilén et al., 2003) and have been

6

explained by either the Double Layer Theory (DVLO), Alginate Theory, and Divalent Cation

Bridging Theory (Sobeck and Higgins, 2002).

The sum of the total proteins, humic compounds, carbohydrates, and DNA is considered to

represent the total mass of EPS in a floc. These materials have been found to represent up to

80% of the mass of activated sludge (Sobeck and Higgins, 2002). Some studies have tried to

define the chemical composition of sludge and EPS suggesting that protein was for most

sludges the major EPS component (19–45%) followed by humic compounds (19–45%) and

carbohydrates (7–32%). Uronic acids make up 1–3% of the EPS or 8–26% of the

carbohydrates; and, in some cases, high concentrations of DNA (0-32%) have been detected.

To obtain these results, 10-30% of the sludge’s organic fraction was extracted as EPS (Wilén

et al., 2003).

These results are in accordance with many studies that show that several types of EPS’s are

involved in bioflocculation. Polysaccharides are one of the most important structural

components of this polymer. Other recent studies suggest that proteins also play an important

role in bioflocculation (Grady et al., 1999). Some researchers have suggested polysaccharides

play a major role in flocculation; however, others suggest that polysaccharides forming only a

small part of the floc matrix are not as important as proteins for the aggregation on bacteria.

Since proteins are the most abundant macromolecule in EPS, several authors have tried to

identify the different classes that are present in the exocellular environment of bacteria. These

include extracellular enzymes, proteinaceous S-layers, lectins, or polypeptide capsular

material. The exocellular protein extracted from activated sludge samples could be from a

combination of these sources, and of these possible proteins, lectins are one of the most likely

types to be involved in bioflocculation (Higgins and Novak, 1997b). Lectins are

nonenzymatic proteins that bind sugar residues and play a role in attachment and colonization

of bacteria in both animals and plants, and other microorganisms. The lectins produced by

bacteria are typically located on appendages such as the pili and fimbriae of bacteria

(Madigan et al., 2003). The data suggest lectins or bacterial fimbriae play a very important

role in flocculation in activated sludge systems.

7

Researchers have proposed that biopolymers originate from release of bacterial growth, decay

and lysis, and from the influent wastewater, creating a matrix in which microorganisms can be

aggregated (Park et al., 2006). The most important sources of ECP are metabolism and cell

lysis products produced by protozoa and bacteria (Grady et al., 1999). Biopolymers have a

number of functional groups such as hydroxyl and negatively charge carboxyl groups that

contribute to the binding of floc constituents by means of cationic bridges in a way that

biopolymers can bind through specific protein and polysaccharide interaction, hydrophobic

interactions, hydrogen bonding, and ionic interactions (Park et al., 2006). EPS are very

hydrophilic due to their negative charge causing a negative effect on bioflocculation, but it

has been shown that the interactions between EPS and divalent cations can bind the

biopolymers to microbial cells and to other biopolymers. Therefore, because the majority of

exocelluar biopolymers are negatively charged, cations then become an important structural

component as a binding agent within the biopolymeric network (Novak et al., 1998). These

biopolymers are thought to be the glue that holds bioflocs together.

The sole presence of ESP’s is not the only mechanism to ensure a strong floc. Since bacteria

have a negative charge, the environment that surrounds the microorganisms, the bioreactor

configuration, cations, ionic strength, solids retention time, and suspended growth play an

important role.

1.4 Role of Filamentous Bacteria and SRT

As noted earlier in this document the relative proportion of floc-forming bacteria and

filamentous bacteria compose the macrostructure of flocs. Some of the filamentous bacteria

are enmeshed inside the floc providing a solid structure. If the filamentous bacteria grow and

extend beyond the biofloc, the particles compact poorly, increasing the sludge volume index

(SVI) and negatively impacting the solid-liquid separation process. In suspended growth

reactors the SRT affects the macrostructure of the floc. Studies show that low SRTs between

0.25 and 2 days produced large dispersion of suspended growth biomass producing

inadequate flocculation, and relative high SRTs between 9 and 12 produce irregularly shaped

pin point floc (Grady et al., 1999).

8

Different types of filamentous bacteria that are found in activated sludge have high affinities

for different limiting nutrients or dissolved oxygen which makes them out-compete the floc-

forming bacteria. Therefore, to better understand the communities of microorganisms present

in activated sludge, some knowledge of the growth kinetics of filamentous and floc-forming

bacteria is needed. For example when a particular substrate is present, floc-forming bacteria

have higher specific growth rate coefficient (μ) and half saturation coefficient for substrate

(Ks) values than filamentous bacteria which means that the floc-forming bacteria will grow

faster when the substrate concentration is high, but when filamentous bacteria have a higher

affinity for the substrate it can grow faster when the substrate concentration is low (Grady et

al., 1999).

When comparing growth kinetics of floc forming bacteria and filamentous bacteria based on

the Monod equation different tendencies are observed. If a substrate gradient is allowed in a

way that the influent concentration is high, floc-forming bacteria can grow at the expense of

the filamentous bacteria. A configuration of this type can be obtained in many different ways;

for example, a reactor can be set to work like an ideal plug-flow reactor, or by adjusting the

feeding pattern to obtain the desired influent substrate concentration.

Analysis suggests that filamentous bacteria have less capacity to accumulate and store carbon

reserves and have a lower substrate uptake rate than floc formers. Floc-forming bacteria have

the ability to store substrate when exposed to a high substrate concentration environment,

balancing the growth rate at a more constant rate, which gives them an advantage under

dynamic conditions (Martins et al., 2003). The latter should not be considered as an absolute

rule and also it remains uncertain whether the proliferation of filamentous bacteria is due to a

higher substrate affinity or just to its morphology; therefore, further analysis is required.

Under low substrate concentrations there is also a substrate diffusion limitation inside the

floc.

9

Under this condition filamentous bacteria can easily protrude into the bulk liquid and gain

access to the substrate outside the floc, and if the filamentous bacteria grow beyond the floc

they can out-compete the floc forming bacteria. It is believed that these substrate diffusion

gradients inside the flocs are an important factor for the growth of filamentous microorganism

within the floc, whereas in an environment where substrate diffusion is not an issue the

filamentous bacteria remain mostly inside the floc (Martins et al., 2003).

1.5 Cations and there effect in settling

Before examining in detail the effect of cations (monovalent, divalent, and trivalent) in the

performance of an activated sludge process three proposed theories should be evaluated.

a. Double layer theory (DLVO). Named after there developers (Derjaguin, Landau,

Verwey, and Overbeek) is a classical colloidal theory (Sobeck and Higgins, 2002).

In a colloidal suspension there cannot be a net imbalance in the overall electrical

charge and therefore the primary charge of the particle must be counterbalanced in

a system. The primary charges accumulate in an interfacial region together with

the opposite charged ions forming an electrical double layer (AWWA, 1999). The

first layer is comprised of a tightly associated layer of counterions, and the second

layer (diffuse layer) results from the electrostatic attraction of ions of opposite

charge to the particle (less tightly associated counterions). An electrostatic

potential exists between the surface of the particle, where the potential is

maximum, and the solution surrounding the particle. This potential decreases with

distance from the surface until the concentration of ions equals the bulk solution.

When colloidal particles approach each other, their diffuse layers begin to interact

and their charges create a repulsive potential energy that inhibits aggregation. As

the ionic strength increases, the double layer decreases and the repulsion potential

decreases allowing other forces, like the van der Waals forces, to interact and

promote aggregation.

b. Alginate Theory. This theory was first proposed by Bruus (Bruus et al., 1992).

Alginate is a polysaccharide generally made up of glucuronic acids and repeating

10

mannuronic produced by bacteria that result in a formation of alginate gel when

calcium is present. This model implies that when high concentrations of sodium

are present in activated sludge and calcium is replaced by sodium within the floc,

this result in deterioration of the biofloc. Alginate aggregation is exclusively by

calcium so researchers stated that calcium induced aggregation of alginate is

important (more than magnesium) for the bioflocculation process (Sobeck and

Higgins, 2002).

c. Divalent cation bridging theory (DCBT). The first researchers to propose this

theory were McKinney and Tezuka (Sobeck and Higgins, 2002). According to

this theory divalent cations, such as calcium and magnesium, work as a bridge and

link negatively functional groups with the EPS and by this means create a more

stable biopolymer matrix enhancing bioflocculation. This model proposes that

non-specific binding occurs rather than a specific interaction of gel formation

between calcium and alginate. Some researchers agree and have contributed with

some studies that support this theory (Higgins and Novak, 1997). They

demonstrated that sodium addition caused a deterioration of flocs because of the

displacement of divalent cations from binding sites within the floc.

Cations significantly affect bioflocculation and alter the settling and dewatering

characteristics of activated sludge systems. Cations imbalances are a common cause of

sludge settling problems especially in industrial activated sludge plants where these

unbalances are most likely to occur (Higgins and Novak, 1997a). It is believed that cations

interact with the negatively charged biopolymers in activated sludge and change the structure

of the floc matrix through an exchange of biopolymers between flocs and the environment.

Altering the cations in the wastewater has been to be an economical way to enhance settling

and dewatering properties (Higgins et al., 2004a) and a decrease in microbial soluble product

would result in a lower effluent COD. This was demonstrated in many studies where

monitoring the cations and the changes in biofloc characteristics affected the effluent water

quality through an exchange of biopolymers between flocs and the environment (Murthy et

al., 1998). Most of these studies refer to a surrounding environment where filamentous

11

bacteria are not the main cause of the deterioration in settling and all of the settling properties

area attributed to biopolymer and cations interaction.

Historically, most of the research done is related to monovalent and divalent cations in

activated sludge. The divalent cations that are mostly considered are calcium (Ca2+) and

Magnesium (Mg2+). The divalent cations bridge across negatively charged sites on the

biopolymers to form a dense, large, and compact floc structure more resistance to shear and

therefore promotes bioflocculation and enhance settling and dewatering properties (Higgins

and Novak, 1997c, Murthy and Novak, 2001). Both of these divalent cations are required for

the adhesion of certain bacterial monocultures depending mainly on the sensitivity of each

type of bacteria in the absence of calcium and magnesium (Higgins and Novak, 1997c).

Researchers suggest that cations help bioflocculation by bridging the negative sites on

exocellular biopolymers (DLVO) while others agree in that cations induced flocculation by

the double compression theory or by alginate theory, the latter when dealing with calcium

only (Park et al., 2006, Sobeck and Higgins, 2002). Most of the data that exists in the

literature report that when activated sludge is fed with either Ca2+ or Mg2+ the settling

properties improve in a similar manner, which lead to the conclusion that cation bridging best

explains the role of divalent cations in the floc structure (Higgins and Novak, 1997c) (Park et

al., 2006).

One of the questions that arose from these previous studies was the amount of divalent cations

that must be present in order to have good settling and good dewatering properties. To this

question Higgins and Novak suggest a value between 0.7 – 2.0 meq/L of calcium and

magnesium necessary for acceptable settling and dewatering, suggesting that increasing the

feed concentrations of these cations above these levels improved the floc strength, settling,

dewatering properties, and increased the bound protein concentration (Higgins and Novak,

1997c). Divalent cation addition has also been proved to decrease the polymer demand used

for conditioning by 30-75% (Higgins and Novak, 1997a). Other data also suggest that adding

calcium and magnesium to an activated sludge system can help reduce the settling properties

and effluent problems related to bulking and filamentous bacteria, while not controlling the

12

filamentous organism concentration (Higgins et al., 2004b). Calcium and magnesium ions are

also related to lectin interactions, enhancing the activity of these proteins within the

extracellular matrix.

One concern that resulted from previous studies was the point of application of the divalent

cations in order to produce a better effect in settling and dewatering. In many laboratory

studies improvements in settling properties were observed when calcium and magnesium

were added to the feed rather than directly to the reactor (Murthy and Novak, 2001). This can

be explained as follows: when cations are applied in the feed, they are able to become

enmeshed in the polymer network while the bacteria are producing the biopolymer and

therefore can be incorporated to the floc as it is formed (Novak et al., 1998). In contrast, when

cations are applied in the reactor as a slug dose, the incorporation of cations occurs only in the

outer portions of the floc. Therefore, the incorporation of cations during floc formation must

be considered important (Murthy and Novak, 2001).

It has been demonstrated that high concentrations of sodium present in activated sludge

results in a deterioration of properties such as floc density, capillary suction time (CST),

sludge volume index (SVI), effluent TSS and effluent COD. Sodium in the influent

wastewater also causes an increase in proteins and polysaccharides in the effluent and

therefore increases the total suspended solids (TSS) and effluent COD concentration (Murthy

and Novak, 2001). This increase in the TSS is considered to be a sign of weak floc and it is

attributed to a decrease in the bonding strength of exopolymer functional groups. Like the

case of divalent cations, a concentration value that represented the amount of sodium that will

create a considerable deterioration in the settling properties was needed. Research suggests

that at values lower than 10 meq/L sodium did not greatly impact the settling properties of

activated sludge, but at concentrations higher than 10 meq/L there may be problems related to

poor settling (Higgins and Novak, 1997c). Other authors suggest that problems related to

settling and dewatering will appear on activated sludge systems when the concentration of

monovalent to divalent cations exceeded 1:1 and will get worst when exceeding 2:1,

expressed on an equivalent basis (Higgins and Novak, 1997a). Therefore, the poor settling

and dewatering can be improved by raising the concentration of divalent cations (adding

13

calcium and magnesium). Some authors had also observed in some cases that addition of

sodium can improve settling. This might be due to the fact that flocs become more compact

and therefore denser, or there might be an increase in permeability that can reduce drag while

settling, by allowing water to flow better through the floc structure. This phenomenon can be

associated to the physiological reaction of bacteria to sodium (Novak et al., 1998). Therefore

a certain amount of sodium and other monovalent cations could be beneficial for

bioflocculation. Figure 1-2 depicts the relationship between EPS and cations. Other

monovalent ions considered to cause problems related to settling in activated sludge systems

are ammonium and potassium. It has been suggested that these cations, act like sodium,

replacing divalent cations and creating problems with settling (Novak, 2001).

Figure 1-2. Potential role of cations in bioflocculation

Recently, and since most of the studies has been related to monovalent and divalent cations,

specialist have studied the effect of trivalent cations in settling and dewatering properties.

Some of the trivalent cations that have been studied include aluminum (Al3+) and iron (Fe3+)

because they are abundant in activated sludge and because it is assumed that due to their

higher valence, their contribution to floc stability would be better (Park et al., 2006). Recent

studies have demonstrated that as the concentration of iron and aluminum increased, the

biopolymer found in solution decreased, suggesting that Al and Fe are good absorbers of

negatively charged organic particles. Related studies show that poor biopolymer binding was

observed when there was an absence of Al and Fe (Park et al., 2006). These studies suggest

Repulsive Force

14

that Al and Fe have considerable impacts on activated sludge characteristics regardless of the

relationship between monovalent and divalent cations.

As the M:D ratio increases, the effluent TSS and COD increases as a result of microorganism

and biopolymers that are released from the floc into solution. This COD concentration is

believed to be proportional to the biopolymer in solution (Murthy and Novak, 2001).

Therefore, the retention of biopolymers within the floc matrix will result in an improvement

in effluent quality measured as oxygen demand (Higgins et al., 2004a). The absence or

removal of beneficial cations from wastewater can result in a release of the primary

biopolymer constituents such as proteins, polysaccharides, DNA, RNA, and lipids into

solution (Murthy and Novak, 2001). Some authors observed that when divalent cations

increase, the bound protein concentration also increases and that there is little effect on the

polysaccharide bound concentration. These data suggest that divalent cations bind together

exocellular protein with flocs explaining the relationship biopolymers and cations and

highlighting that that proteins and not the polysaccharides are dominant in bioflocculation

(Higgins and Novak, 1997b). Following this statement it can be inferred that calcium and

magnesium bind lectins, and lectins bind polysaccharides within the floc matrix depending on

the type of microorganism present and the lectin produced. And with this a extension of the

previous model can be added, stating that lectinlike proteins would bind polysaccharides that

are cross-linked to adjacent proteins (Higgins and Novak, 1997b). Meanwhile other authors

believe that the main biopolymer constituent released into solution is polysaccharides.

1.6 Sequencing Batch Reactors (SBR) and Feeding Pattern

Sequencing batch reactors (SBR) are those reactors that are operated in a sequence of steps.

Figure 1-3 shows the typical sequencing of a SBR. One of the most important steps in a SBR

is the fill period. One of the aspects that are affected by the filling period, which is governed

by the length of time that is required to reach a specified volume, is the process loading factor

which is part of the hydraulic characteristic of the bioreactor. A high and instantaneous

process loading factor will occur when the filling period is short. In this short time the

biomass in the reactor will receive a high initial amount of organic matter and nutrients and

15

the concentration of these constituents will reduce over time after the filling period is over. In

this case the SBR will be analogous to a continuous feed system with a configuration of tanks

in series or a plug flow reactor. Conversely, if the filling period is long, then the process

loading factor will be small and the SBR will be analogous to a completely mixed reactor

(Grady et al., 1999). This analogy is valid, providing an equal SRT for both types of reactors.

An activated sludge system with a selector placed at the head of the system (for bulking

control) followed by the aeration basin can also be simulated by a SBR. It is important to take

in account that most of the reactions such as substrate utilization and biomass growth will take

place during the filling period.

Figure 1-3. Typical sequence of events in a SBR

According to Grady et al., (1999), the process loading factor is the mass of the substrate

applied per unit time divided by the mass of microorganisms in the bioreactor. As mentioned

earlier in this document, the process loading factor will influence the competition between the

microorganisms and will affect the settling properties.

SBR are chosen in many laboratory models because they can be operated in many different

ways that replicate many situations and processes if the SRT and HRT (hydraulic retention

time) are the same. Also the variation of the length of the filling period will allow the SBR to

operate in a range between a plug flow reactor and a completely mixed reactor. Historically it

has been observed that a SBR generally produced better settling biomass than other

completely mixed systems, especially when the filling ratio was minimal and this resulted to

be a turning point in the study of wastewater treatment using SBRs. Many studies have been

Influent

Fill React Settle Decant

Effluent

16

made in SBRs to find out how the communities of microorganism, that conform the activated

sludge, respond to the operation and conditions of the SBR. One of the main objectives of

these studies is to determine a link between changes in activated sludge settling properties,

floc structure, microbial community dynamics and the operation of a SBR. This combination

should lead to a more detailed understanding of the treatment process performance.

In a recent study (Govoreanu et al., 2003), a series of SBRs were operated for approximately

200 days under stable condition in which they were able to observe three different stages

characterized by changes in floc structure and microbial community. In the first stage, a

predominant presence of floc-forming bacteria was observed which controlled the floc

structure. The second stage was a short period where filamentous bacteria appeared in almost

the same amounts as floc-forming bacteria, creating a good floc that improved settling

properties. A highly dynamic microbial community started to emerge at this point. Finally,

during the last stage, a high amount of filamentous bacteria was observed and therefore

bulking was an issue (Govoreanu et al., 2003). This study suggested a dynamic microbial

environment in this type of reactors which had a great influence in settling properties and

therefore in effluent quality.

As mentioned earlier in this chapter, the competition and selections of microorganism inside a

reactor will be associated to properties such as growth rate, substrate intake rate, and substrate

affinity. Experiments suggest that the filling ratio in an SBR may have an impact on the

settling properties of the sludge. Increasing the length time of the feed which creates a low

substrate concentration can negatively affect the settling properties of the activated sludge.

However, when the fill time is short, a high substrate gradient is present which promotes the

substrate intake close to the maximum specific rate of bacteria, leading to good settleability.

Under these conditions, floc-forming bacteria prevail and filamentous organisms are less

abundant or are incorporated within the floc. This is consistent with the idea that the feeding

pattern had an influence on the microbial population dynamics and kinetics of activated

sludge (Martins et al., 2003).

17

When the feeding pattern was changed from a long fill time to a pulse feed (short fill time), a

decrease in the abundance of filamentous bacteria was observed. The few filaments present

were mostly around the floc and suddenly incorporated within the floc instead of growing far

beyond the floc structure (Martins et al., 2003). Also, a gradual change in the morphology of

the flocs was observed. Large flocs (with filaments incorporated in the floc) were observed

during the pulse feed; these flocs were strong, round and compact. When the feeding pattern

was changed to a large filling time, the flocs were more irregular and porous suggesting that

morphology changes in flocs also affected the settling properties of sludge.

It is obvious that small difference in the aerobic fill time will have a dramatic effect on the

sludge setting properties, considering that other factors such as aeration and nutrients

provided will not affect the community of microorganism present in the activated sludge

system.

18

CHAPTER II

Combined Effect of Reactor Feeding Pattern and Cations on the Performance of an Activated Sludge SBR

ABSTRACT: Laboratory scale sequencing batch reactors (SBR) were used to study the effect

of feeding pattern on activated sludge containing different concentrations of monovalent

cations. Effluent wastewater quality and settling and dewatering properties were analyzed to

determine if extending the feeding time to an SBR would have an impact on the effects of

adding high amounts of sodium (Na+) to an activated sludge system, simulating wastewater

treatment plants containing high quantities of monovalent cations in their influent. Data

suggest that excess amounts of sodium caused poor flocculation in general, but when the

feeding time was raised from 1 min (pulse feed) to 1hr and 4hr, an increase in deflocculation

was observed. Deflocculation caused by the combined effect of sodium and feeding pattern

was less when the sodium concentration was low. As sodium was increased to 6 meq/L, the

negative effects on bioflocculation caused by the feeding strategy were offset. As the amount

of sodium was further increased, a dramatic effect on settling and effluent water quality was

observed reflected by an increment in effluent total suspended solids (TSS) and effluent

chemical oxygen demand (COD) accompanied by an increase in sludge volume index (SVI)

and capillary suction time (CST). An increase in effluent biopolymers (proteins and

polysaccharides) was also observed. A better understanding of the effects produced by

changing the feeding strategy on bioflocculation will help wastewater plant operators meet

effluent requirements when struggling against high amounts of monovalent cations in their

influent. Also, when performing analysis related to settling and dewatering in lab scale

activated sludge reactors, the feeding pattern should always be reported in order to

standardize procedures and compare results where the effects of changing the feeding

strategies have been considered.

KEYWORDS: Activated sludge, cations, feeding pattern, sodium, bioflocculation, settling,

biopolymers, sequencing batch reactor.

19

Introduction The activated sludge process is widely used to treat both industrial and municipal wastewater.

While most municipal treatment plants perform well, industrial facilities often struggle to

meet effluent requirements. One reason for this is that the biomass from industrial facilities

settles poorly. One reason for this poor performance has been attributed to a high monovalent

to divalent ion ratio in many industrial wastewaters (Higgins and Novak, 1997).

The quality of the effluent from activated sludge treatment plants is highly dependent on the

efficiency of the solid-liquid separation process. If this process is poor, wastewater treatment

will be ineffective, resulting in failure to achieve regulatory effluent requirements. Solid-

liquid separation is a physical process which involves the removal of solids particles that can

be in a suspended, colloidal or soluble state. This is usually accomplished by gravity

sedimentation. For a successful separation the microorganisms must clump together to form

flocs of a defined size, porosity, density and strength to allow them to settle and compact well

without leaving a high concentration of suspended solids in the effluent. Bacteria in

suspended cultures, under the appropriate growth conditions, are able to grow and attach each

other to form flocs. Flocs with very different properties and morphologies may occur,

depending on the conditions in the activated sludge treatment plant and wastewater

composition (Wilén et al., 2003).

Bioflocculation is one of the most important steps in building large, strong, dense, and

compact settleable floc. For a better understanding on microbial flocculation, the structure

and components of the floc must be defined in order to propose means to change their

properties and improve the settling and dewatering properties of the activated sludge.

Activated sludge floc consists primarily of biopolymer, cations, microorganisms (floc forming

bacteria and filamentous bacteria), and debris trapped within the floc. These biopolymers

referred to as exocellular polymeric substances (EPS), are produced when the active biomass

converts complex organic matter into low molecular weight compounds (Sponza, 2004),

forming a matrix that encapsulates the microbes and aids in the aggregation of the

microorganisms.

20

The production of EPS, which is mainly composed of carbohydrates, proteins, nucleic acids,

lipids and humic substances, is believed to be dependent of the growing phase, decay and

lysis of bacteria. Researchers suggest that EPS, both in terms of quantity and quality, are very

important for the floc properties of the activated sludge (Liao et al., 2000). A combination of

floc-forming bacteria and filamentous bacteria compose the macrostructure of flocs, with

some of the filamentous bacteria enmeshed inside the floc to provide a solid structure. The

relative abundance of filamentous organisms will depend on several factors such as solids

retention time and substrate concentration. Several studies also suggest that feeding patterns

also have a strong influence on the microbial community of activated sludge (Martins et al.,

2003).

Cations significantly affect bioflocculation and alter the settling and dewatering

characteristics of activated sludge systems. Cations imbalances are a common cause of

sludge settling problems especially in activated sludge plants related to industrial activities

(Higgins and Novak, 1997a). High concentrations of monovalent cations such as sodium

(Na+) are detrimental to activated sludge properties (Park et al., 2006). It has been

demonstrated that high concentrations of sodium present in activated sludge result in a

deterioration of sludge properties such as, capillary suction time (CST), sludge volume index

(SVI), effluent TSS and effluent COD. Sodium in the influent wastewater also causes an

increase in proteins and polysaccharides in the effluent (Murthy and Novak, 2001).

Researchers suggested that at values lower than 10 meq/L sodium did not impact greatly the

settling properties of the activated sludge, but at concentrations higher than 10 meq/L, poor

settling will occur (Higgins and Novak, 1997c).

It has been proposed that the divalent cations act as a bridge between the negatively charged

particles within the biopolymer network but in the presence of monovalent cations they are

displaced by an ion exchange process that reduces the ability of biopolymer to bind and form

a good floc matrix (Higgins and Novak, 1997c). Higgins and Novak (1997b) suggested that a

relationship between the sum of monovalent and divalent cations (M:D) could be a good

indicator to evaluate the problems related to settling and dewatering; they suggested that with

21

a ratio greater than 2 there would be considerable problems in effluent quality associated to

settling (Higgins and Novak, 1997a).

The above-mentioned studies describe many of the mechanisms involved in bioflocculation,

which consider several aspects that will influence the floc formation process, but these are not

the only factors that will affect effluent water quality, settling and dewatering properties of

activated sludge. While performing lab-scale studies related to cations in sequencing batch

reactors (SBR), Higgins and Novak (personal communication) observed that the way in which

the SBR was fed influenced the results obtained for analysis related to effluent quality and

stated that differences in feeding pattern will probably have a dramatic effect on the sludge

setting properties in SBRs. They observed that by increasing the length of time of the feed,

which creates a low substrate concentration in the reactor, affected negatively the settling

properties of the activated sludge. However, when the fill time was short, a high substrate

gradient was present which results in the substrate intake to be close to the maximum specific

rate of bacteria and appears to lead to good sludge settleability. These studies supported the

idea that the feeding pattern had an influence on the microbial population dynamics and

kinetics of activated sludge (Martins et al., 2003). The competition and selection of

microorganism inside a reactor will be associated with properties such as growth rate,

substrate intake rate, and substrate affinity, which will then affect the quality and quantity of

EPS produced.

The objective of this study was to determine if the effluent quality, settling and dewatering

properties of lab-scale SBR reactors at different sodium concentrations were to experience

any change when subject to different feeding patterns, and to determine which feeding

configuration yields the best results regarding effluent quality. If the deterioration was

eminent, then considerations in controlling influent flows should be taken when operating

industrial or municipal plants where the M:D ratio might be high due to the usage of sodium

based chemicals for pH control, and to encourage other researchers to include the impact of

feeding pattern when performing studies related to solid liquid separation in activates sludge

systems.

22

Materials and Methods Experimental Approach. Experiments were conducted using four sequencing batch reactors

(SBR), each one containing a 1 L volume. Since the purpose of this study was to analyze the

effect of the feeding pattern in the effluent quality and sludge settling properties when

exposed to different sodium concentrations, different feed configurations were required. A

phase, as denoted, represents the period of time when four reactors containing different

amounts of sodium are operated under the same flow conditions. Each phase has a unique

feeding pattern which is maintained constant through the entire operational period. Each

phase is characterized by different filling time duration, as shown in table 2-1. A pulse feed

was used for phase one (feeding time: one minute), for phase two, one hour, and for phase

three, a four hour feed time was used.

The reactors were seeded with mixed liquor obtained from the Blacksburg, VA., municipal

wastewater treatment plant. The SBR were operated with two cycles per day, each cycle

lasting for 12 hours. The reactors were operated using a 1 day hydraulic retention time (HRT)

and an 18 day solids retention time (SRT). This SRT was chosen to maintain a mixed liquor

suspended solid concentration of around 2,000 mg/L to allow nitrification and therefore

reduce the effects of the ammonium (NH4+) ion, and to reduce the effect of SRT in floc

formation.

Table 2-1 SBR operating times

Fill time Reaction time Settling time Decant time

Phase I 1 min 11 hrs 45 min 15 min

Phase II 60 min 11 hrs* 45 min 15 min

Phase III 240 min 11 hrs* 45 min 15 min

* Aeration was applied for 40 min of the filling time for phase II.

** Aeration was applied for 220 min of the filling time for phase III.

Oxygen was provided using compressed air fed through diffuser stones to allow a dissolved

oxygen concentration greater than 2.0 mg/L and to provide enough mixing to keep the

biomass in suspension without disturbing the process of floc formation. The oxygen input

was regulated in a way that it did not favor the growth of filamentous organisms. The pH was

23

monitored but was not controlled (one of the added salts contained HCO3 which added some

buffer capacity). The temperature for the entire study was maintained at 20º C.

Feed and Cations. Bactopeptone, a microbiological enzymatic digest of protein for use in

culture media, was used as feed (electron donor, carbon, and nutrient source) for the reactors

at a concentration of 300 mg/l as COD. Several COD (chemical oxygen demand) analysis

were done to determine the required bactopeptone concentration that would give the desired

value. It was determined from this analysis that 273 mg/L of bactopeptone provided a COD

of 300 mg/L. The low concentration of cations in the bactopeptone allowed control of cations

to the feed as described in table 2-2.

Table 2-2 shows the cations that were added to the feed. The concentrations of all the cations

were maintained constant during the three phases of the experiment. The inorganic salt

concentrations in the feed (excluding sodium) were chosen in a way that they had a minimal

impact on the settling and effluent properties of activated sludge following the recommended

values found in the literature (Higgins and Novak, 1997c, Murthy and Novak, 1998, Park et

al., 2006) .

Table 2-2 Cations used in the feed.

Cation Concentration Compound used Concentration

(mg/L)

Calcium (Ca2+) 1.5 meq/L CaCl2 · 2H2O 110

Magnesium (Mg2+) 1.5 meq/L MgSO4 · 7H2O 185

Potassium (K+) 0.5 meq/L KHSO4 68

Iron (Fe3+) 6 mg/L FeCl3 17.5

Aluminum (AL3+) 3 mg/L Al2(SO4)3 · 18H2O 37

The sodium concentration for each reactor is shown in table 2-3. These concentrations were

maintained constant during each of the three phases. In the third phase of the study the

sodium concentration in reactor 2 was increased from 3 to 10 meq/L. This change was done

24

because little difference was observed between the results obtained from the 1.5 and 3.0

meq/L sodium reactors for the first two phases; so, in order to have a better understanding of

the impact of high sodium concentrations, a higher value was selected.

Table 2-3 Sodium concentrations for each of the three phases.

Reactor ID NaHCO3

Conc. (meq/L)

NaHCO3

Conc. (mg/L) M:D ratio

Reactor 1 1.5 126 0.7

Reactor 2* 3.0 252 1.2

Reactor 3 6.0 504 2.2

Reactor 4 15.0 1260 5.2

* The concentration of this reactor was increased to10 meq/L in the third phase of the experiment.

The monovalent to divalent cation ratio for each of the different sodium concentrations was

calculated in order to compare it with values selected in the literature that would provide a

range of settling and dewatering properties.

Steady state determination. The reactors in each phase were operated until it was

determined that a steady state has been achieved. The system was considered to be at steady

state when visual inspections of settling properties plotted as a function of time were stable

and variability no greater than ≈ 25 % occurred. An example of steady state determination for

phase II in two of the reactors is shown in figure 2-1. For this example, the steady state

period was considered to be between about 30 and 55 days. Steady state for the reactors was

usually achieved at 2 SRT’s. The samples for analysis were taken once the steady state was

reached. The samples used for effluent quality evaluation were taken at the end of each SBR

cycle just before the decanting process, whereas the samples for MLSS analysis were taken at

the end of a cycle before the settling period started.

25

0

500

1000

1500

2000

2500

3000

0 10 20 30 40 50 60 70 80 90

Time (d)

MLS

S (m

g/L)

-

50

100

150

200

250

300

350

400

Na 6 meq/L MLSS Na 15 meq/L MLSSNa 6 meq/L SVI Na 15 meq/L SVI

Steady State

Figure 2-1. Activated sludge and settling properties as a function of time for phase II. Steady state conditions between day 30 and day 55.

Settling and dewatering properties. Total suspended solids (TSS), mixed liquor suspended

solids (MLSS), and volatile suspended solids (VSS) were analyzed using Method 2540D and

2540E, respectively, from Standard Methods (1995). The settling properties of the activated

sludge were characterized by the sludge volume index (SVI) and the dewatering properties

were determined using the capillary suction time (CST) analysis based on method 2710D and

2710G, respectively according to Standard Methods (1995). Soluble chemical oxygen

demand (COD) was measured based on the method 5220C of Standard Methods (1995). For

conditioning and dewatering of the activated sludge, a dry cationic polymer (clarifloc 3275)

was used. The polymer solution was prepared at 0.01% by weight. The optimum dose of

polymer was determined by plotting the values of the CST for each corresponding dose and

obtaining the minimum CST reading. This analysis was done under low shear conditions.

Soluble protein was measured using the Hartree modification of the Lowry method (Hartree,

1972). Polysaccharides were measured using the Dubois method (Dubois et al., 1956).

Bovine serum albumin and glucose were used as protein and polysaccharide standards,

respectively. For soluble analysis of COD, proteins, and polysaccharides samples were

26

filtered through 1.5 μm, 0.45 μm, and 1,000 Dalton (1-k) filter membranes. The 1-k ultra

filtration was performed at 55 psi.

Filamentous organism observation and particle charges. Microscopic observations of the

flocs were performed periodically on a regular basis to quantify filamentous organism in the

activated sludge. The filamentous organism content was quantified using the method of

Jenkins (Jenkins et al., 1986) where the presence of filamentous is rated on a scale of 0-6; 0

corresponds to no filamentous organisms present and 6 to excessive presence of filamentous.

Denaturing gradient gel electrophoresis (DGGE) analysis was used to examine temporal

differences within the activated sludge bacterial community. This method generates a

community fingerprint pattern, in which a band generally corresponds to one bacterial

ribotype (population), which allows the detection of changes in the presence of the dominant

bacterial population in the community. This procedure is based on the electrophoresis of

polymerase chain reaction (PCR) amplified 16S rDNA fragments, obtained form total sludge

DNA in a polyacrylamide gel (Muyzer et al., 1993). The particles charges within the

biopolymer were measured by a zeta potential analysis.

Statistical analysis. A series of pooled t-tests and analysis of variance (AOV) for more than

two populations means were used for statistical comparison and to determine differences in

the results obtained for the settling and dewatering properties of the activated sludge for each

phase and sodium concentrations. A type I error value of 0.05 was used (α = 0.05).

Results and Discussion Laboratory reactors were operated for approximately 90 days for each of the three phases of

the experiment. Each phase, as denoted, consisted of four reactors that were fed with

bactopeptone and a series of cations where sodium was applied at different concentrations

raging from 1.5 meq/L to 15 meq/L. For each phase the feeding pattern was different. A

pulse feed was used for phase one (feeding time: one minute), for phase two a one hour feed

time was used and for phase three, a four hour feed time was used. The shortest feed period

resembles the substrate gradient similar to the one occurring in a plug flow reactor, while the

longer feeding system can be compared to a completely-mixed flow reactor with low soluble

27

substrate concentration. The effect of the sodium concentration and the impact it has when

applied at different flows is analyzed in this study. Settling properties and effluent quality

parameter were measured and analyzed.

Table 2-4 Average pH and Na+ concentrations for each reactor

Reactor #

Na Conc.

(meq/L) pH Feed pH

Reactor 1 1.5 7.70 7.70

Reactor 2a 3.0 7.94 7.94

Reactor 3 6.0 8.47 8.20

Reactor 4 15.0 9.00 8.40 a The concentration for reactor 2 was increased from 3.0 to 10.0 meq/L in the third phase of the

experiment. The average pH for the reactors is shown in Table 2-4. It can be seen that the pH was

generally between 7.7 and 9.0. The pH generally increased as the sodium bicarbonate

concentration increased. The solids retention time (SRT) was maintained constant at 18 days

although the amount of wastage in those reactors where the deflocculation was high made it

hard to maintain a constant SRT for the high sodium system. The amount of biomass

maintained in the reactors in each phase is shown in Table 2-5.

A comparison of the mixed liquor suspended solids (MLSS) concentration was made between

the reactors fed with the same amount of sodium for each phase to eliminate any impact on

the results introduced by a difference in the amount of biomass present. A statistical analysis

was used to determine if there was a difference between these values. The MLSS

concentrations for the sodium feeds of 1.5, 6.0, and 15 meq/L were compared. The

corresponding p-values obtained for the analysis of variance (ANOVA) were found to be

0.418, 0.124, and 0.086, respectively. This shows that there is no significant difference in the

MLSS concentrations for the reactors containing the above stated amounts of sodium.

28

Table 2-5 Average MLSS for each reactor with an SRT of 18 days

Reactor

Na Conc

(meq/L) MLSS (mg/L)

1 - Phase I 1.5 1621 ± 266

2 - Phase I 3.0 1493 ± 301

3 -Phase I 6.0 1839 ± 254

4 - Phase I 15.0 2126 ± 398

1 - Phase II 1.5 1959 ± 297

2 - Phase II 3.0 1991 ± 344

3 - Phase II 6.0 2022 ± 481

4 - Phase II 15.0 1917 ± 255

1 - Phase III 1.5 1715 ± 643

2 - Phase III 10.0 2197 ± 285

3 - Phase III 6.0 1809 ± 291

4 - Phase III 15.0 1705 ± 375

At the end of each phase, the amount of suspended solids removed from the reactors through

the decant process plus the wastage was so high that it lead to a decline in the MLSS. This

was common after the 90 days of operation for the reactors with a low sodium concentration;

but, in the reactors containing higher amounts of sodium this period was even shorter, about

60 days. At this point the reactor data were not considered useful for analysis. Figure 2-2

shows how the MLSS concentration in the reactors containing the highest sodium

concentration changed over time for each phase; it can be seen from the plot that at the end of

each phase the amount of biomass began to decline.

The influence of filamentous organisms on the floc structure and properties was minimized by

several strategies, but not eliminated. The seed wastewater contained few filaments and there

was no evidence from the Blacksburg wastewater treatment plant personnel that they had

problems with bulking. The dissolved oxygen was not limiting (greater than 2.0 mg/L O2),

but also it was not in excess to allow nuisance organism to proliferate.

29

0

500

1000

1500

2000

2500

3000

0 10 20 30 40 50 60 70 80 90

Time (d)

MLS

S (m

g/L)

-

50

100

150

200

250

300

350

400

SVI (

mL/

g M

LSS)

Na 6 meq/L MLSS Na 15 meq/L MLSSNa 6 meq/L SVI Na 15 meq/L SVI

Steady State

Figure 2-2. MLSS vs. time in the reactors with the highest sodium concentration

A change in microbial community during each phase was expected because of the differences

in the F/M ratio introduced by the change in feeding pattern. Therefore, actions to reduce the

presence of nuisance microorganisms were taken only when the presence of these organisms

was too high. The presence of red worm was observed, especially in the phase were the

feeding time was greatest, but it was controlled by adding a few drops of bleach when their

presence was excessive.

Effect on filamentous organisms. Quantification of filamentous organisms was done in the

second and third phase when some episodes of filaments and nuisance organisms occurred.

This quantification was done by direct observation through a microscope and based on a

subjective scoring of filaments abundance described by Jenkins, et al. (1986). During the

second phase of this study the presence of filaments was constant between 1 and 2 while in

the third phase the presence of filamentous organisms ranged from 1 to 3. In this last phase,

the amount of filaments was higher in the reactors where the sodium concentration was lower,

usually between 2 and 3, and lower where sodium was highest. This suggests that the

filaments did not impact the settleability and effluent quality parameters of the activated

sludge when the sodium concentration was higher, but might have a small impact when the

sodium concentration was lower.

30

A - Phase I

Reactor- Na Conc. (meq/L)

Effluent TSS

(mg/L)

SVI (mL/g MLSS)

CST (sec)

Soluble Effluent

COD (mg/L)

Effluent COD

(mg/L)

Effluent Soluble Poly-saccharides

(mg/L)

Effluent Poly-

saccharides (mg/L)

Soluble Effluent Proteins (mg/L)

Effluent Proteins (mg/L)

Zeta Potential

(mv) 1 – 1.5 23.8 ± 10.3 74 ± 14 17.5 ± 4.4 17.4 ± 5.4 36.4 ± 5.2 6.85 ± 2.4 11.3 ± 6.3 2.6 ± 1.0 11.8 ± 3.5 ND 2 – 3.0 37.7 ± 14.5 97 ± 14 23.7 ± 3.9 ND ND ND ND ND ND ND 3 – 6.0 29.0 ± 5.5 76 ± 20 18.0 ± 0.1 22.1 ± 3.8 46.0 ± 2.2 5.75 ± 4.0 12.4 ± 7.4 3.5 ± 1.8 16.8 ± 3.5 ND

4 – 15.0 49.0 ± 10.8 90 ± 24 49.3 ± 4.7 23.5 ± 2.0 69.3 ± 5.2 6.21 ± 2.7 13.6 ± 3.2 6.0 ± 1.2 15.1 ± 2.4 ND ND – not determined

B - Phase II

Reactor- Na Conc. (meq/L)

Effluent TSS

(mg/L)

SVI (mL/g MLSS)

CST (sec)

Soluble Effluent

COD (mg/L)

Effluent COD

(mg/L)

Effluent Soluble Poly-saccharides

(mg/L)

Effluent Poly-

saccharides (mg/L)

Soluble Effluent Proteins (mg/L)

Effluent Proteins (mg/L)

Zeta Potential

(mv) 1 – 1.5 31.7 ± 11.4 76 ± 36 10.7 ± 1.8 22.5 ± 4.5 33.9 ± 0.5 5.73 ± 3.0 10.8 ± 5.9 6.1 ± 1.0 11.4 ± 1.0 -9.3 ±1.8 2 – 3.0 24.2 ± 13.1 112 ± 20 11.3 ± 1.3 20.4 ± 5.5 33.9 ± 8.7 7.71 ± 2.1 11.9 ± 3.4 6.4 ± 0.4 16.3 ± 3.0 -10.0 ± 1.9 3 – 6.0 34.2 ± 12.4 124 ± 41 21.9 ± 7.6 24.2 ± 1.9 39.8 ± 10.9 6.94 ± 4.7 10.4 ± 9.5 6.7 ± 1.0 13.2 ± 1.7 -13.1 ± 2.1

4 – 15.0 78.8 ± 29.7 90 ± 19 30.0 ± 3.3 30.1 ± 14.2 80.9 ± 22.2 7.61 ± 6.7 17.5 ± 0.7 12.4 ± 1.5 46.8 ± 0.7 -12.1 ± 2.5 C - Phase III

Reactor- Na Conc. (meq/L)

Effluent TSS (mg/L)

SVI (mL/g MLSS)

CST (sec)

Soluble Effluent

COD (mg/L)

Effluent COD

(mg/L)

Effluent Soluble Poly-saccharides

(mg/L)

Effluent Poly-

saccharides (mg/L)

Soluble Effluent Proteins (mg/L)

Effluent Proteins (mg/L)

Zeta Potential

1 – 1.5 53.3 ± 22.9 64 ± 18 10.3 ± 0.4 25.1 ± 4.6 46.7 ± 13.1 5.9 ± 1.8 13.5 ± 3.0 5.6 ± 1.6 13.2 ± 1.3 -9.9 ± 1.7 2 – 10.0 60.4 ± 16.8 95 ± 9 34.4 ± 0.2 28.0 ± 1.3 54.8 ± 8.6 7.0 ± 0.4 12.1 ± 1.6 8.8 ± 1.2 21.2 ± 12.1 -13.7 ± 3.1 3 – 6.0 34.6 ± 11.1 113 ± 24 10.5 ± 2.2 27.2 ± 5.0 36.6 ± 2.2 8.0 ± 2.5 11.6 ± 2.4 6.5 ± 1.2 13.9 ± 1.3 -15.2 ± 1.4

4 – 15.0 120.0 ± 44.1 63 ± 13 96.9 ± 4.5 46.4 ± 3.9 105.2 ± 21.1 8.8 ± 1.2 19.9 ± 2.3 15.1 ± 2.7 45.7 ± 9.4 -20.9 ± 3.2

Table 2-6. Summary of effluent quality and settling parameters under steady state condition for each phase

31

Effect on water quality, settling, and dewatering properties. Laboratory reactors were

operated until a steady state condition was achieved. A summary of the results obtained from

the laboratory reactors is shown in table 2-6. Table 2-6 A shows the results obtained for the

first phase. In this phase, after 35 days of operation, the biomass of the second reactor was

suddenly washed out of the system, resulting in a deterioration of the reactors properties. The

cause for this deterioration was unknown; therefore, this reactor was shut down and no further

data were collected for this reactor. Measurements of particle charge were not made in the

first phase because it was after analyzing the data from this phase that it was realized that it

would be of importance to analyze the particles charge and determine if there was a difference

in the charge for the flocs formed. The effects of the feed patterns are discussed in the

following sections.

Effluent TSS. The effluent total suspended solid (TSS) was measured from the beginning

until the end of each phase and was used to determine steady state conditions. Table 2-6

shows the average TSS results; these values represent the average during the steady state

period. Figure 2-3 shows a comparison of the TSS for each phase at different monovalent to

divalent ratios. A statistical difference was found among the values for the reactors

containing the lowest sodium concentration (M:D ratio of 0.7) with a corresponding p-value

of 0.0078. These data show that the third phase reactors with the longest feed time contained

the highest TSS values. The high effluent TSS concentration in these reactors was caused

mainly by deflocculation, although some filaments were observed.

The effluent TSS for each of the three phases decreased as the sodium concentration was

increased from 1.5 meq/L to 6.0 meq/L. At this concentration there was no difference among

all of the TSS values (p-value 0.50) suggesting that the feeding pattern did not have an impact

on the effluent TSS at values over a range of sodium from 1.5 to 6 meq/L or a M/D from 0.7 -

2.2. An improvement in TSS was observed when the M:D ratio was increased from 0.7 – 2.2

for the third phase, suggesting that some sodium is needed to enhance flocculation. As the

sodium concentration increased to above a M:D of 2.2, deflocculation was observed.

32

-

20

40

60

80

100

120

140

- 1.0 2.0 3.0 4.0 5.0 6.0

Monovalent : Divalent ratio (eq/eq)

TSS

(mg/

L)

Phase I Phase II Phase III

Figure 2-3. Effluent TSS comparison High TSS values were recorded for the reactors containing the highest sodium concentration

(M:D ratio of 5.2) and these values were different for each phase (p-value 0.0015). The

lowest TSS values were obtained when the feeding time was the shortest (pulse feed) and

increased as the feeding time was raised, suggesting that the negative impact on

deflocculation caused by high sodium concentration is magnified by the way the reactors are

fed. The effluent TSS increased by 70% and by more than 100% when changing from a pulse

feed to a four hour feed when the monovalent to divalent ratio in the reactors was 0.7 and 5.2,

respectively.

High effluent TSS is a sign of weak flocs which results in the formation of less dense particles

that are harder to settle (Novak et al., 1998). These small particles usually stay in suspension

and are washed out of the reactors through the wastage process which leads to a reduction in

the biomass of the system.

Chemical oxygen demand. Effluent soluble and total chemical oxygen demand

measurements were also used to assess the effluent quality of the reactors. Effluent samples

from each reactor were filtered through a 1.5 μm, 0.45 μm, and through a 1k Dalton

membrane. The results for each phase are shown in Figure 2-4; the error bars represent one

standard deviation.

33

A

-

20

40

60

80

100

120

1.5 6.0 15.0

Sodium Concentration (meq/L)

CO

D (m

g/L)

1 K Filter 0.45 μ Filter No Filtration

B

-

20

40

60

80

100

120

1.5 3.0 6.0 15.0

Sodium Concentration (meq/L)

COD

(mg/

L)

1 K Filter 0.45 μ Filter No Filtration

C

-

20

40

60

80

100

120

1.5 6.0 10.0 15.0

Sodium Concentration (meq/L)

COD

(mg/

L)

1 K Filter 0.45 μ Filter No Filtration

Figure 2-4. Effluent COD (mg/L) for A-Phase I, B-Phase II, and C-Phase III

34

Data collected showed little difference between the samples that passed through 0.45 and 1.5

μm filters; therefore, the results corresponding to the 1.5 μm samples are not shown. Figure

2-4 shows, for each phase, the COD decreased as the effluent passed through a smaller pore

size filter, demonstrating that the COD is a result of a combination of suspended organic

particles and soluble microbial products. It can be seen from this plot that the soluble COD

(samples passed through a 0.45 μm filter) is usually half the value of the total COD (unfiltered

samples), indicating that at least 50 % of the total COD is introduced by larger suspended

particles that result from deflocculation and poor settling. The difference between the

samples passed through the 1k membrane and the 0.45 μm filter is approximately 30% for the

reactors containing a sodium concentration less than 10 meq/L, but increases as the sodium

concentration is increased to 15 meq/L. These results were constant for all three phases.

-

20

40

60

80

100

120

- 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

COD

(mg/

L)

Phase I Phase II Phase III

Figure 2-5. Total effluent COD for each phase.

The results for the soluble COD (SCOD) and total COD (TCOD) for each phase are

summarized in Table 2-6. Figure 2-5 shows the different TCOD concentrations for the three

phases. It can be seen from this plot that the TCOD corresponding to the third phase is

slightly greater than for phase I and II at the lowest M:D ratio, but a statistical analysis reveals

that there is no significant difference among the three phases (p-value = 0.08). The small

COD increment observed in the third phase is due mainly to the change in feeding pattern, but

is not as significant because of the low sodium concentration. When the sodium

concentration is increased to 6 meq/L (M:D ratio of 2.2), the COD for each phase is similar, at

around 22 to 27 mg/L (p-value = 0.65).

35

-

10

20

30

40

50

- 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

COD

(mg/

L)

Phase I Phase II Phase III

Figure 2-6. Effluent soluble COD for each phase

As the M:D ratio is increased to 5.2, the effluent TCOD increased and the difference among

the three feeding strategies can be seen. A statistical analysis to compare the three phases was

not done because there were not enough data for the first phase; only the last two phases were

compared. No significant difference was found between phase II and III (p-value = 0.16), but

the trends shown in Figure 2-5 suggests that a difference between the phases exists. For this

sodium concentration, the highest TCOD value was obtained for the third phase, which

corresponds to the longest feeding time. These results show that the feeding pattern has a

greater impact in the effluent COD when the sodium concentration increases.

The soluble chemical oxygen demand (SCOD) shows a similar trend as the TCOD. This can

be seen in Figure 2-6. At the lowest M:D ratio, there is a slight difference between the first

phase and both phases II and III. This difference is due to the effect of the feeding strategy

because the sodium concentration is low in these reactors. As the sodium concentration is

increased to 6 meq/L (M:D ratio of 2.2), the SCOD concentration for all three phase

approaches a value of approximately 25 mg/L as COD. There is no statistical difference

between these values (p-value = 0.39). Once again, as the sodium concentration is increased

to 15 meq/L (M:D ratio of 5.2), the SCOD starts to increase for all three phases, but this

increment is greater in the phase where the reactors are under a longer feeding time. At this

sodium concentration there is no significant difference between phase II and III (p-value =

0.10), but Figure 2-6 reveals that there is a considerable difference between phase I and phase

36

III. This difference might be greater than the difference from the TCOD results, which

suggests that soluble microbial products like exocellular polymers contribute to the SCOD

and TCOD. Figure 2-6 also shows that the SCOD for the third phase is greater than the other

two phases.

0

40

80

120

160

Phase I Phase II Phase III

CO

D (m

g/L)

SCOD TCOD TSS

Figure 2-7. Effluent quality parameters comparison for a M:D ratio of 5.2

The results obtained for the COD and TSS analysis are strongly related, and both show

similar trends. When the sodium concentration and the feeding time are increased, the

amount of effluent TSS and COD also increases. In the third phase at lower sodium

concentration, the effluent TSS and COD concentrations are not the lowest. Both decrease as

the M:D ratio is increased to 2.2, but increase again as the sodium increases. The similarity in

these trends suggest that effluent COD is mostly representative of organics products produced

by microorganisms and released from the activated sludge floc to solution, rather than

undegraded influent. The large fractions of the effluent COD (> 50 %) from the reactors may

be generated from the biomass washed-out from the system as effluent TSS. An increase in

COD is likely related to an increase in the sum of solution protein and polysaccharides

(Murthy and Novak, 2001). When the amount of sodium present in the reactors was the

highest (M:D ratio of 5.2), the feeding pattern had a greater impact in the effluent water

quality parameter. Figure 2-7 shows that the effluent quality parameters measured as effluent

TSS, SCOD, and TCOD increased as the feeding time also increased. It can be seen from this

37

figure that the worst effluent quality parameters, at a sodium concentration of 15 meq/L, were

obtained when the feeding time to the SBRs was the longest (phase III).

Sludge Volume Index (SVI). The sludge volume index is a common parameter used to

report results obtained when evaluating floc and settling properties. Many researchers have

tried to correlate the SVI to many other effluent quality parameters. The SVI was also used to

determine steady state conditions. Table 2-6 shows a summary of the SVI values obtained

throughout the steady state period. Figure 2-8 shows a comparison of the SVI for each phase.

-

20

40

60

80

100

120

140

0 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

SVI (

mL/

g M

LSS)

Phase 1 Phase 2 Phase 3

Figure 2-8. Settling properties as a function of feeding time and sodium concentration.

The results from the SVI analysis show that there is a difference among the reactors for each

phase. For the reactor containing a M:D ratio of 2.2, there is a statistical difference (p-value =

0.06) between phases I and II, phases I and III, but there is no difference between phases II

and III. For the reactor containing a M:D of 5.2, there is a statistical difference (p-value =

0.056) between phases I and III, phases II and III, but no difference between phases II and III.

There was no statistical difference for the reactors containing the lowest M:D ratio (p-value =

0.40). This last result suggests that when there is low sodium, there is no significant

difference in the SVI when the feeding time is changed. The data for phase I follow an

expected trend, as the sodium concentration increases, the SVI increases showing a negative

38

impact on the settling properties. For phases II and III the same trend is observed until

reaching a concentration of 6.0 meq/L of sodium (M:D ratio of 2.2).

During phases II and III the SVI started to decrease when the M:D ratio > 2.2. This was not

the expected trend. This decrease was due to a change in particle properties (e.a., size,

porosity, and density) which affected the settling properties of the activated sludge. Particles

experience an increase in their porosity reducing the effect of water on settling by reducing

settling drag (Higgins and Novak, 1997c). The change in feeding pattern and the large

amount of sodium stimulated deflocculation that resulted in small, denser flocs that settled

and compacted very easily, leaving high amount of suspended solids in suspension. This

gives a false sense of the sludge volume index because only a part of the particles settled

which represents only a fraction of the biomass. This is in accordance with authors who state

that the SVI is an incomplete measurement of the settling behavior of activated sludge

(Novak, 2001). No analysis related to floc size and densities were done, but changes in

particle properties were so evident that a visual inspection of the flocs and a microscopic

analysis was sufficient to substantiate these changes.

This situation makes it almost impossible to estimate if changes on the feeding strategies

under high concentration of sodium affected the SVI. From this analysis it can only be stated

that the change in feeding pattern affected the SVI at sodium concentrations less than 6

meq/L, though it cannot be stated which phase introduced a greater deterioration because

there is no significant difference between the values from phases II and III at this sodium

concentrations. The presence of some filamentous organisms during the third phase did not

contribute to changes in the SVI for each reactor.

Capillary Suction Time. The dewatering characteristics of the biological suspension were

determined by capillary suction time (CST). The results obtained for each phase are

summarized in Table 2-6. Figure 2-9 shows a comparison among the reactors containing the

same concentration of sodium for each phase. When the M:D ratio was less than 2.2, the CST

was not affected by the change in feeding pattern, although Figure 2-9 shows little

improvement in the CST as the feeding time was extended. A statistical analysis was done to

39

demonstrate that there is no difference between the CST for the 1.5 and 6.0 meq/L sodium

reactors (M:D ratio of 0.7 and 2.2) for phase II and phase III (p-values = 0.73 and 0.10

respectively). There were not enough data to include phase I in the statistical comparison.

0

20

40

60

80

100

0 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

CST

(sec

) Phase 1 Phase 2 Phase 3

Figure 2-9. CST comparison for three different feeding patterns

at different sodium concentrations.

When the sodium concentration was raised from 6 - 15 meq/L or a M/D from 0.7 - 2.2, the

CST continued to increase in all three phases. Figure 2-9 reveals that phases I and II shared a

similar trend; when the amount of sodium was increased, the CST also increased. Phase I has

a higher CST for every sodium concentration when compared to phase II, but this difference

is not considered to be significant.

Phase III experienced a higher value in CST as the amount of sodium increased. Figure 2-10

shows that when the M:D ratio was equal to 5.2, the CST for phase III was more than twice

the value of phase I and II. The CST for phase III was considerably higher than for phase II

(p-value = 0.0001). These results suggest that an increase in the feeding time will affect the

dewatering properties of activated sludge containing a M:D ratio greater than 2.2. The high

deflocculation might be the cause of the deterioration in dewatering properties since smaller

particles are associated with poor dewatering.

40

0

20

40

60

80

100

120

Phase I Phase II Phase III

CST

(sec

)

Capillary Suction Time

Figure 2-10. CST comparison for a M:D ratio of 5.2 Figure 2-10 reveals that phase III has the highest CST as expected. This figure also shows

that as the feeding time was increase from 1 – 60 minutes the CST decreased at this M:D

ratio, but from the results obtained it was not possible to demonstrate if there was a significant

difference between the values from phases I and II.

0

0.05

0.1

0.15

0.2

0.25

0 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

Pol

ymer

Opt

imum

Dos

e (m

g/gT

SS)

Phase 2 Phase 3

Figure 2-11. Optimum dose for phase II and phase III

A CST and optimum polymer dose analysis was done to measure the impact that might exist

in conditioning due to the difference found in CST between phase II and III. After adding a

cationic polymer and gently mixing for a short period of time, the CST was measured, the

polymer dose versus CST profile was developed, and the optimum polymer dose was

determined as the dose corresponding to the minimum CST value. The results are plotted in

41

Figure 2-11. According to Figure 2-11, as the feeding time is reduced and it approximates to

a pulse feed (phase II), the polymer required to improve the dewatering properties of the

activated sludge decreased. An increase in polymer conditioning demand implies a greater

number of negative charged sites available in the floc and an increase in negative biological

colloids in solution, confirming that the feeding strategy influences dewatering properties.

Particle charge. A zeta-potential analysis was done to characterize the biopolymer by

determining the particle surface charge. Surface charge is related to the production,

composition and physical characteristics of EPS, and it is related to the ionizable groups

present on sludge surfaces. Surface charges increase the polar interactions of EPS with water

molecules. Therefore, the more charged the sludge surface, the lower the hydrophobicity.

-25

-20

-15

-10

-5

00 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

Z-P

oten

tial (

mv)

Phase II Phase III

Figure 2-12. Zeta-potential values for phase II and phase III

Table 2-6 summarizes the results obtained for the zeta-potential analysis performed only in

the last two phases of the study. A comparison of the results from phases II and III is shown

in Figure 2-12. Like most of the previous results, there is no difference between the values

that correspond to a M:D ratio of < 2.2, (p-value = 0.38 and 0.52), but as the amount of

sodium is increased, a difference in zeta-potential is observed. When the Na+ concentration

reaches a value of 15 meq/L (M:D ratio of 5.2) there is a significant difference between these

values (p-value = < 0.0001). Results show that the feeding pattern affected also the particle’s

charge when the M:D ratio was higher than 2.2. This result is related to previous analyses

42

were there was a deterioration on the settling, dewatering and effluent quality of the activated

sludge, as the feeding pattern and sodium concentration changes.

Effluent biopolymer substances. Unbound proteins and polysaccharides were measured to

determine if the feed Na+ and feeding strategy were related to sludge and effluent properties.

Biopolymer in solution phase and effluent can be used to characterize the extent of

biopolymer binding in activated sludge floc because biopolymer will remain in solution if

flocculation is poor. High soluble and colloidal biopolymers suggest that flocculation is poor

and that a substantial fraction of organic matter is being washed out of the system. Effluent

samples from each reactor were filtered through a 1.5 μm, 0.45 μm, and through a 1k Dalton

membrane and as in the COD analysis, the data related to the effluent that passed through the

1.5 μm filter are not shown. The results for each phase are shown in Figures 2-13 and 2-14;

the error bars represent one standard deviation.

Figures 2-13 and 2-14 show that the polysaccharides and proteins are reduced as they are

filtered through different openings. Like the COD, the soluble polysaccharide concentration

is approximately 50 % of the total polysaccharides, suggesting that the effluent contains half

soluble and half colloidal polysaccharides. That is not the case for the proteins concentration

where the amount of soluble proteins was less than 50 % of the total proteins, especially in the

reactors where sodium was high. The amount of polysaccharides that passed the 1k

membrane remained almost constant for each phase, showing little change as the sodium

concentration was increased. The protein concentrations has a similar trend with the

exception that at higher sodium concentrations the amount of protein that passed through the

1k membrane increased, and were magnified as the feeding time also increased.

The results for soluble and total polysaccharide and for soluble and total proteins for each

phase are summarized in Table 2-6. Figure 2-15 shows the different polysaccharide

concentrations for the three phases. It can be seen from this figure that at the lowest M:D

ratio the amount of total effluent polysaccharides is higher for the third phase, but no

statistical difference was found among the three phases (p-value = 0.78).

43

A

-

5

10

15

20

25

1.5 6.0 15.0

Sodium Concentration (meq/L)

Poly

sacc

harid

es (m

g/L)

1 K Filter 0.45 Filter No Filter

B

-

5

10

15

20

25

1.5 3.0 6.0 15.0

Sodium Concentration (meq/L)

Pol

ysac

char

ides

(mg/

L)

1 K Filter 0.45 Filter No Filter

C

-

5

10

15

20

25

1.5 6.0 10.0 15.0

Sodium Concentration (meq/L)

Poly

sacc

hari

des

(mg/

L)

1 K Filter 0.45 Filter No Filter

Figure 2-13. Effluent polysaccharides (mg/L) for A-Phase I, B-Phase II, and C-Phase III

44

A

-

10

20

30

40

50

1.5 6.0 15.0Sodium Concentration (meq/L)

Prot

ein

Conc

(mg/

L)

1 K Filter 0.45 Filter No Filter

B

-

10

20

30

40

50

1.5 3.0 6.0 15.0

Sodium Concentration (meq/L)

Pro

tein

Con

c (m

g/L)

1 K Filter 0.45 Filter No Filter

C

-

10

20

30

40

50

1.5 6.0 10.0 15.0

Sodium Concentration (meq/L)

Prot

ein

Conc

(mg/

L)

1 K Filter 0.45 Filter No Filter

Figure 2-14. Effluent proteins (mg/L) for A-Phase I, B-Phase II, and C-Phase III

45

-

4

8

12

16

20

- 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

Poly

sacc

harid

es (m

g/L)

Phase I Phase II Phase III

Figure 2-15. Total effluent polysaccharides for each phase

As the M:D ratio increases to a value of 2.2, there is a slight decrease in total effluent

polysaccharides for phase II and III. At this sodium concentration there is no apparent

difference among the polysaccharides concentrations for each phase (p-value = 0.9199),

suggesting that the feed pattern does not affect the amount of polysaccharides released into

solution when the M:D ratio is less than 2.2. When the M:D is further increased to 5.2 by

increasing the Na+ concentration, the total effluent polysaccharides start to increase and a

difference among the three feeding strategies is clear.

4

5

6

7

8

9

10

- 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

Poly

sacc

harid

es (m

g/L)

Phase I Phase II Phase III

Figure 2-16. Soluble effluent polysaccharides for each phase

46

The effluent soluble polysaccharide shows a different trend than the total polysaccharides. It

can be seen from Figure 2-16 that for phase I there is no change in soluble polysaccharides as

the sodium concentration increases. For phases II and III there is a slight increase in soluble

polysaccharides when the M:D ratio is increased from 0.7 to 1.2, followed by a sudden

decrease as sodium increases the M:D ratio to 2.2. Finally, the polysaccharide in solution

increases as the sodium reaches its highest value. No significant difference was obtained for

any of the three M:D ratios being compared (p-value = 0.92, 0.73, 0.77).

Figure 2-17 shows the effluent proteins as the M:D ratio changes for each phase. For phase I

the amount of proteins released into solution slightly varies as the sodium concentration is

increased, similar to what happened with the effluent polysaccharides. When the feeding

strategy is changed from a pulse feed to a slower feeding pattern, the amount of effluent

proteins start to increase as the sodium concentration is raised. When the M:D ratio is

minimal, there is no difference in the amount of proteins in the effluent among the three

phases (p-value = 0.13). There is also no statistical difference when M:D ratio increases to

2.2 (p-value = 0.99).

-

5

10

15

20

25

30

35

40

45

50

0 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

Pro

tein

s C

onc

(mg/

L)

Phase I Phase II Phase III

Figure 2-17. Total effluent proteins for each phase

However, when the M:D ratio is increased to a value greater than 2.2, the total effluent

proteins start to increase and a difference among the three feeding strategies is clear. There is

a significant difference in the amount of effluent proteins between phase I and phase II and

47

between phases I and III, when sodium reaches a value of 15 meq/L (M:D ratio of 5.2) (p-

value = 0.0006); there is no different between phases II and III. This result suggests that

increasing the feeding time magnified the effect of sodium in bioflocculation, as reflected by

the amount of proteins released into the effluent.

The effluent soluble protein shows a similar trend to the total effluent proteins. Figure 2-18

shows that for the three phases, the amount of soluble proteins increases as the sodium

concentration also increase with a slight difference in the rate for each phase.

-

2

4

6

8

10

12

14

16

0 1 2 3 4 5 6

Monovalent : Divalent ratio (eq/eq)

Prot

eins

Con

c(m

g/L)

Phase I Phase II Phase III

Figure 2-18. Soluble effluent proteins for each phase

According to this plot the rate of increase of soluble proteins versus sodium concentration is

higher for the third phase, followed by the second phase. This plot also reveals that the

concentration of soluble proteins for phase I is lower than for phase II and III for all sodium

concentrations. At a M:D ratio of 5.2 there is a significant difference between phase I and II,

and between phase I and III (p-value = 0.0026). There was no difference found between

phase II and III at any M:D ratio (p-value = 0.66, and 0.79). This result suggests that

changing the feeding pattern has also an impact in effluent soluble proteins, but with a lower

rate when comparing it to the increase in total effluent proteins.

Proteins and polysaccharides were both affected by the feeding pattern at the highest M:D

ratio. Figure 2-19 shows a comparison of the total proteins and polysaccharides for each

48

phase at the highest M:D ratio where the feeding pattern has the highest impact. Figure 2-19

shows that the total polysaccharides increased as the feeding time was increased and as stated

earlier, there is a significant difference among these values. The release of proteins to the

effluent seems to be more sensitive than the polysaccharides, this can be seen from Figure 2-

19 that increasing the feeding time from 1 – 60 minutes resulted in a high amount of effluent

proteins, but increasing further the feeding time did not resulted in a further increase of

proteins in the effluent.

0

10

20

30

40

50

60

Phase I Phase II Phase III

Bio

poly

mer

Con

c. (m

g/L)

Total Polysaccharides Total Proteins

Figure 2-19. Proteins and Polysaccharides comparison for a M:D ratio of 5.2

The results obtained for the effluent biopolymer substances analysis are strongly related since

the results for both proteins and polysaccharides showed similar trends. The amount of

proteins and polysaccharides released into solution was very sensitive to the change in feeding

pattern, with protein being the one that experienced a higher change. From our study it can be

determined that the effluent proteins and polysaccharides increased dramatically when

changed from phase I to phase II. When the feeding time was further increased from one hour

to four hours, a slight change in the amount of soluble proteins and polysaccharides was

observed. Statistical analysis demonstrated that this latter change in proteins and

polysaccharides concentrations was not significant. Although these values remained very

close as the substrate gradient was decreased, the effluent quality, settling, and dewatering

properties continued to deteriorate, as reflected by increases in effluent TSS and COD and

CST.

49

The changes in these properties could be related to the differences in EPS composition of the

activated sludge which depends on the microbial community. Researchers agree that the

quantity of EPS plays a very important role in flocculation, but may not be the only thing to

consider when relating EPS to settling (Sponza, 2004). The presence of a similar amount of

soluble proteins and polysaccharides along with a continuous deterioration on effluent quality

as the feeding time is increased agree with studies that state that settling and effluent quality

parameters depend not only on the quantity of EPS, but also on the composition and physical

configuration of specific EPS molecules. In some cases the composition of EPS is more

important than the quantity of EPS in activated sludge (Sponza, 2004). A change in the

microbial community, which is expected as a result from changing the feeding pattern due to

a change in substrate intake, might be expected to contribute to some change in the EPS.

Some authors (Liao et al., 2000) suggest that lower microbial growth rates can produce large

amount of cell lysis which contribute to proteins accumulation due to secretion and cell lysis.

This accumulation of proteins can change the proportions of biopolymers forming the EPS

and different EPS components may have different roles (Morgan et al., 1990).

The results obtained for the effluent biopolymers analysis reveals that that the proteins and

polysaccharides in solution contribute to the TCOD and SCOD measured for each phase.

Also, the higher amount of proteins and polysaccharides in the effluent coincide with the high

amount of solids in the effluent measured as TSS which is in accordance with many studies

which suggest that biopolymers in solution is a sign of poor flocculation (Park et al., 2006).

The poor floc formation results in a release of organic matter to the effluent, which is a

fraction of the biomass composed mainly by particles rich in proteins and polysaccharides

which are reflected in the effluent COD, and effluent proteins and polysaccharides. The

increase in microbial soluble products (exocellular proteins and polysaccharides) is a result of

a decrease in retention of biopolymers in the floc which increase the effluent COD, suggesting

that this increase is not due to a change in kinetics of microbial degradation (Higgins et al.,

2004b). Figures 2-11 and 2-12 also show an expected trend that is related to effluent proteins

and polysaccharides where an increase in the amount of EPS released in the effluent could be

directly related to increased values of negative surface charge of the flocs. This indicates that

50

the EPS contain mainly negatively charged groups that contribute to the binding of the

different floc constituents.

Implications: The effect of various cations on activated sludge characteristics was not

expected to be independent of the feeding pattern. It has been shown that excess sodium in

activated sludge systems has a negative impact on the characteristics related to effluent

quality, settling, and dewatering properties, explained by deterioration in bioflocculation due

to high concentration of monovalent to divalent cations present in the feed. Also, from the

results obtained, it can be stated that small difference in the aerobic fill time had a dramatic

effect on the activated sludge properties. In general, it can be stated from the overall results

that effluent quality parameter such as effluent TSS, effluent COD, and effluent biopolymers

along with the dewatering properties measured by the CST, were affected by the negative

effect of excess sodium and this effects were magnified by the rate at which the reactors were

fed, especially at higher sodium concentrations, usually above 6 meq/L (M:D ratio 2.2).

Figures 2-20 – 2-22 helps confirm these negative effects.

Reactor 1, Phase II - 4x Reactor 1 Phase III – 4x

Reactor 1, Phase II - 10x Reactor 1, Phase III – 10x

Figure 2-20. Effect of feeding pattern on bioflocculation for 1.5 meq/L Na+.

51

Reactor 3, Phase II - 4x Reactor 3, Phase III – 10x

Reactor 3, Phase II - 10x Reactor 3, Phase III – 10x

Figure 2-21. Effect of feeding pattern on bioflocculation for 6.0 meq/L Na+.

Reactor 4, Phase II - 4x Reactor 4, Phase III – 4x

Reactor 4, Phase II - 10x Reactor 4, Phase III – 10x

Figure 2-22. Effect of feeding pattern on bioflocculation for 15 meq/L Na+.

52

From these microscopic pictures, it can be seen that for an equal amount of sodium there is

change on the floc morphology introduced by the different feeding strategies. A greater

deflocculation can be observed in the phase where the feeding time was greater confirming

the negative effect on bioflocculation due to a high monovalent to divalent ratio and a larger

feeding time.

Data obtained reflect that changing the feeding strategy when the M:D ratio was 2.2 produced

no effect in the activated sludge properties. When comparing the three phases, there is no

significant evidence to prove that there is a difference in the effluent quality and dewatering

properties among the three phases. Some authors suggest that some quantity of monovalent

cations appears to be beneficial for several floc properties (Murthy and Novak, 2001),

although excessive amounts of monovalent cations can cause deterioration in most floc

properties (Higgins et al., 2004b). The sodium aided flocculation in phase III until reaching a

M:D ratio of approximately 2.2. Above this, flocculation deteriorated.

Engineering and Scientific Significance. The implications of the previous study are

significant for wastewater treatment plants that have high concentrations of monovalent

cations. When the M:D ratio is greater than 2, besides adjusting the amount of divalent

cations, plant operators can adjust their influent flows to improve floc properties. This can be

done by building equalizations basin to store certain amounts of wastewater and released it a

high flows in short periods of time resembling a pulse feed. It has been demonstrated that

considerable changes in feeding pattern results in noticeable changes in flocculation, but

considering the restrictions and economical constraints, designers should look for the

adequate balance between influent flows, storage, polymers aids, and effluent quality.

Designers should consider up to what extent they can reduce their influent flow without

increasing the costs of operation. Industrial wastewater treatment plants operating continuous

mixed reactors with a low influent flow rate (similar to a SBR with a very long feeding

period), should consider changing their reactor configuration or simply reduce their feeding

time in order to approximate to a plug flow reactor, which has been demonstrated to have

better effluents quality and better settling properties.

53

The implications of this study are also significant when performing research studies on

activated sludge flocculation. It has been demonstrated that the feeding pattern has an effect

on settling and dewatering properties and also in effluent quality; therefore, when reporting

data collected in lab-scale reactors, the feeding time should be reported in order to compare

results that have the same initial considerations. Also, if researchers want to reduce any effect

when performing any study on bioflocculation using lab-scaled reactors, they should consider

eliminating any variable that will affect their study, including the effects introduced by

changes in the feeding pattern which can be minimized by standardizing the influent flow and

feeding time.

Conclusions The results obtained from lab-scale reactors for this study demonstrated that changing the

feeding pattern will have an impact on the settling and dewatering properties of activated

sludge. Increasing the substrate gradient in the system by increasing the feeding time or

reducing the influent flow has a strong negative impact on effluent water quality, and the

settling and dewatering properties of the activated sludge.

Sodium, at higher amounts, have a negative effect on activated sludge properties and effluent

quality, measured as effluent TSS, COD, SVI, CST and soluble effluent biopolymers.

Deflocculation resulting from the presence of a high M:D ratio in the influent is magnified as

the feeding time is increased. Poor flocculation is a result of changes in particle properties,

filamentous organisms, and changes in the amount and quality of EPS as a result of microbial

community changes due to the variation in substrate rate intake by bacteria. Therefore,

linking these processes with the microbial physiology and microbial population dynamics

might be the key to explain the different degrees of sludge settleability and dewatering

improving effluent quality. In order to prove this, more bacterial community analysis should

be done and a deeper understanding in microbial kinetics is needed. A value of 6.0 meq/L of

sodium is suggested as a point where the change in feeding pattern, as the sodium

concentration is increased, will start to affect bioflocculation at a higher rate resulting in poor

settling and bad effluent quality.

54

The knowledge of this effect is relevant to define strategies to prevent poor effluent quality

and improve settling qualities. From an engineering point of view a better understanding of

how the feeding pattern affects flocculation might be useful to operate wastewater treatment

plants. By increasing the flow and reducing the feeding time through an equalization basin or

a storage tank, operators in a wastewater treatment plant can improve water effluent quality

without the aid of any flocculants especially in industrial wastewater treatment plant where

sodium concentration are usually high due to chemicals used for pH control. From a

laboratory and research point of view, reporting the feeding flow and feeding time of lab-

scaled reactors might be useful to a better understanding of the results and can be useful to

standardize procedures to better compare data.

55

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58

Appendix

Table A-1. Cations concentration in bactopeptone used on feed,

measured with an Inductively Coupled Plasma instrumentation

Constituent mg/L meq/L

Na+ 4.80 0.21

K+ 0.57 0.02

Ca2+ 0.16 0.01

Mg2+ 0.02 0.002

Al3+ 0.0017 0.0002

COD 300