Primary Sludge Addition for Enhanced Biosludge Dewatering

by

Parthiv Amin

A thesis submitted in conformity with the requirements for the degree of Master of Applied Science

Department of Chemical Engineering & Applied Chemistry University of Toronto

© Copyright by Parthiv Amin 2014

ii

Primary Sludge Addition for Enhanced Biosludge Dewatering

Parthiv Amin

Master of Applied Science

Department of Chemical Engineering & Applied Chemistry

University of Toronto

2014

Abstract

Biosludge disposal is a costly challenge for pulp and paper mills. Primary sludge is often

combined with biosludge, and while this is known to improve downstream dewatering,

quantification of the effects of primary sludge addition is not well studied. Evaluation of sludge

properties, including mechanical dewaterability, has shown that primary sludge improves

biosludge dewaterability by a factor of 2-4 when combined with biosludge at levels as low as 20

wt%. The improvement follows a consistent pattern between different primary sludge types,

however a model derived from filtration theory is unable to fully capture the trend. Primary

sludge pretreatment is proposed as a means to improve primary sludge usage with regards to

excess water and monovalent cations. Primary sludge pretreatment, particle size and nature,

and field trials are areas recommended for further investigation in line with the objective of

better understanding dewatering enhancement by primary sludge addition.

iii

Acknowledgments

I would like to thank my supervisor Professor D. G. Allen for his guidance throughout this work,

and to Professor Honghi Tran and Professor Arun Ramchandran for serving on my committee.

I am especially grateful to the personnel at the Tembec Temiscaming and Tembec Kapuskasing

Pulp & Paper mills. In particular I would like to thank Adrew Barquin, and Eric Duchesne for

arranging to provide samples to our lab, without which this work would not have been possible.

Furthermore I would like to thank all of the additional personnel who conducted tours of these

mills for my colleagues and I. The tours provided important insights and direction to my work.

At the University of Toronto I would like to thank Susie for her never ending patience and

assistance with equipment in Biozone, as well as my fellow lab mate Sofia for her guidance. I

must also thank Doug, Igor, and Sue for their instruction and assistance on various instruments

necessary for my work. I would also like to thank the summer students in our lab who helped

conduct experiments and gather data.

Over the course of my work, I was able to meet a number of wonderful friends who contributed

greatly to my time at the U of T. Thank you to Rosanna, Doug and all my other CEGSA

colleagues for the good times, and thanks as well to the Komisar sisters for all the laughs!

This research was funded by an Industry/Academia partnership through the Natural Sciences

and Engineering Research Council of Canada Collaborative Research and Development Grant

Program.

iv

Table of Contents

Abstract ............................................................................................................................................ ii

Acknowledgments........................................................................................................................... iii

List of Tables .................................................................................................................................. vii

List of Figures ................................................................................................................................ viii

List of Abbreviations ....................................................................................................................... xi

1 Introduction ............................................................................................................................... 1

1.1 Objectives............................................................................................................................ 2

2 Literature Review ....................................................................................................................... 3

2.1 Biosludge ............................................................................................................................. 3

2.2 Primary Sludge .................................................................................................................... 6

2.3 Filter Aids ............................................................................................................................ 7

2.4 Assessment of Dewaterability .......................................................................................... 12

3 Materials and Methods ............................................................................................................ 15

3.1 Sludge ................................................................................................................................ 15

3.1.1 Biosludge ............................................................................................................... 15

3.1.2 Primary sludge Type A .......................................................................................... 16

3.1.3 Primary sludge Type B........................................................................................... 16

3.1.4 Primary sludge Type C ........................................................................................... 16

3.2 Chemicals .......................................................................................................................... 17

3.2.1 General Reagents .................................................................................................. 17

3.2.2 Polymer ................................................................................................................. 17

3.3 Experimental Approach .................................................................................................... 18

3.4 Test Protocols ................................................................................................................... 19

v

3.4.1 Total & Volatile Suspended Solids ........................................................................ 19

3.4.2 Total and Volatile Solids ........................................................................................ 19

3.4.3 Capillary Suction Time........................................................................................... 19

3.4.4 Particle Size ........................................................................................................... 19

3.4.5 Elemental Composition ......................................................................................... 20

3.4.6 Crown Press Dewaterability & Gravity Filtration .................................................. 21

3.4.7 pH .......................................................................................................................... 25

3.4.8 Data Analysis ......................................................................................................... 25

4 Results & Discussion................................................................................................................. 26

4.1 Sludge Storage .................................................................................................................. 27

4.2 CST and TSS ....................................................................................................................... 31

4.3 Crown Press ...................................................................................................................... 39

4.3.1 Correlation of Crown Press Cake Solids to CST and TSS ....................................... 39

4.3.2 Crown Press Cake Solids – Combined Sludge Tests .............................................. 42

4.3.3 Crown Press Cake Solids – Theoretical Basis of Understanding ........................... 48

4.3.4 Gravity Filtrate and Crown Press Pressate............................................................ 56

4.4 Particle Size ....................................................................................................................... 59

4.5 Elemental Analysis ............................................................................................................ 67

5 Conclusions .............................................................................................................................. 73

6 Recommendations ................................................................................................................... 77

7 References ................................................................................................................................ 79

8 Appendices ............................................................................................................................... 90

8.1 Appendix A – Darcy’s Law Derivation for SRF ................................................................... 90

8.2 Appendix B - Linear Regression Data for CST Dilution Tests ............................................ 92

vi

8.3 Appendix C - Regression Data for Crown Press Cake Solids – Mixed Sludge ................... 93

8.4 Appendix D – Regression Data for Crown Press Cake Solids & SRF .................................. 94

8.5 Appendix E – Linear Trends for Primary Solids vs. SRF Data & SRF vs. Cake Solids Data . 95

vii

List of Tables

Table 1. Solids Classification System ............................................................................................... 4

Table 2. Performance data for belt filter presses dewatering primary and secondary sludges .... 7

Table 3. Common Filter Aids ........................................................................................................... 9

Table 4. Dosage and Performance of Common Filter Aids ........................................................... 11

Table 5. Chemical/Reagents ......................................................................................................... 17

Table 6. ICP-OES Instrument Parameters ..................................................................................... 21

Table 7. Crown Press Calibration .................................................................................................. 24

Table 8. Linear Regression Best Fit Values – CST Dilutions........................................................... 92

Table 9. Linear Regression Best Fit Values – Crown Press Cake Solids vs. Primary Sludge Content

....................................................................................................................................................... 93

Table 10. Model Equation Best Fit Parameters ............................................................................ 93

Table 11. Linear Regression Best Fit Values – Crown Press Cake Solids vs. SRF........................... 94

Table 12. Linear Regression Best Fit Values – Primary Solids Content vs. SRF ............................. 95

Table 13. Linear Regression Best Fit Values – Cake Solids vs. SRF ............................................... 95

viii

List of Figures

Figure 1. General Overview of Conventional Wastewater Treatment Process .............................. 3

Figure 2. Filter Aid Effect ................................................................................................................. 8

Figure 3. Crown Press Belt Press Simulator (Phipps & Bird, 2013) ............................................... 13

Figure 4. Overview of Central Wastewater Treatment Plant ....................................................... 15

Figure 5. Sludge Handling System ................................................................................................. 16

Figure 6. Experimental Approach ................................................................................................. 18

Figure 7. Crown Press with Attached Gravity Filtration Apparatus .............................................. 22

Figure 8. Biosludge pH - October 2012 Batch ............................................................................... 27

Figure 9. Biosludge TSS - October 2012 Batch .............................................................................. 27

Figure 10. Biosludge CST - October 2012 Batch ........................................................................... 27

Figure 11. Biosludge CST - October 2012 Batch - Outlier Removed ............................................. 27

Figure 12. Biosludge sample 1 pH - June 2013 Batch ................................................................... 28

Figure 13. Primary Sludge Type C pH - June 2013 Batch .............................................................. 28

Figure 14. Biosludge and Primary Sludge CST - June 2013 Batches ............................................. 28

Figure 15. Biosludge TSS - June 2013 Batch .................................................................................. 28

Figure 16. CST of Sludge Samples ................................................................................................. 31

Figure 17. CST of Sludge - With and Without Polymer ................................................................. 32

Figure 18. TSS of Sludge Samples ................................................................................................. 33

ix

Figure 19. Correlation of CST with TSS ......................................................................................... 34

Figure 20. CST of Sludge - Dilution Tests ...................................................................................... 35

Figure 21. CST - Optimum Polymer Dose Determination ............................................................. 38

Figure 22. Crown Press Cake Solids vs. CST - All Sludge Samples ................................................. 40

Figure 23. Crown Press Cake Solids vs. CST - All Sludge Samples - Outlier Removed .................. 40

Figure 24. Crown Press Solids vs. Total Suspended Solids - All Sludges ....................................... 41

Figure 25. Crown Press Cake Solids vs. Primary Solids % - Primary Sludge Type A ...................... 42

Figure 26. Crown Press Cake Solids vs. Primary Solids % - Primary Sludge Type B ...................... 43

Figure 27. Crown Press Cake Solids vs. Primary Solids % - Primary Sludge Type C ...................... 43

Figure 28. Crown Press Cake Solids vs. Primary Solids % - All Sludges with Polymer .................. 45

Figure 29. Correlation of Primary Sludge Mass Fraction with Specific Resistance to Filtration .. 48

Figure 30. Correlation of Gravity Filtration Specific Resistance with Crown Press Cake Solids ... 50

Figure 31. Correlation of Gravity Filtration Specific Resistance with Crown Press Cake Solids -

Outlier Removed ........................................................................................................................... 50

Figure 32. Estimated trend versus empirical data for cake solids as a function of primary solids –

Without polymer treatment ......................................................................................................... 53

Figure 33. Estimated trend versus empirical data for cake solids as a function of primary solids -

With polymer treatment ............................................................................................................... 53

Figure 34. TSS of Gravity Filtrate + Crown Press Pressate ............................................................ 56

Figure 35. Particle Size Distribution - Biosludge with & without Polymer ................................... 60

x

Figure 36. Particle Size Distribution - Primary Sludge .................................................................. 60

Figure 37. PSD - June Biosludge - Raw and with 40% Primary Sludge .......................................... 62

Figure 38. PSD - June Biosludge - Raw and with 40% Primary Sludge and Polymer .................... 62

Figure 39. PSD - July Biosludge - Raw and with 40% Primary Sludge ........................................... 62

Figure 40. PSD - July Biosludge - Raw and with 40% Primary Sludge and Polymer ...................... 62

Figure 41. Percent of Particles in the Settleable Size Range (>100μm equivalent particle

diameter) for Various Sludge Mixtures......................................................................................... 64

Figure 42. Cation Species Concentration - Type A Primary Sludge .............................................. 67

Figure 43. Cation Species Concentration - Type B Primary Sludge............................................... 67

Figure 44. Cation Species Concentration - Type C Primary Sludge ............................................... 68

Figure 45. Cation Species Concentration – Biosludge .................................................................. 68

Figure 46. Monovalent to Divalent Cation Ratios ......................................................................... 69

Figure 47. Cation Species Concentration - Raw Sludge versus Sludge Supernatant .................... 70

Figure 48. T/V vs. V for Gravity filtration of 30%:70% Type A Primary:Biosludge mix ................. 91

xi

List of Abbreviations

ASP – Activated Sludge Process

BCTMP – Bleached Chemi-Thermo-Mechanical Pulping

COD – Chemical Oxygen Demand

CPGR – Crown Press Gauge Reading

CST – Capillary Suction Time

DO – Dissolved Oxygen

EPS – Extracellular Polymeric Substances

ICPOES – Inductively Coupled Plasma Optical Emission Spectroscopy

M:D – Monovalent to Divalent

ODT – Oven Dried Tonne

PSD – Particle Size Distribution

SN - Supernatant

SRF – Specific Resistance to Filtration

TPD – Tonnes Per Day

TS – Total Solids

TSS – Total Suspended Solids

VS – Volatile Solids

VSS – Volatile Suspended Solids

xii

WAS – Waste Activated Sludge also referred to as Biosludge

1

1 Introduction

Biosludge, also known as secondary sludge or waste activated sludge (WAS), is a byproduct of

aerobic secondary effluent treatment by the activated sludge process. Biosludges are generally

comprised of microorganisms, extracellular polymeric substances (EPS), organic and inorganic

matter, and water. The challenge posed to treatment plants by biosludge arises from the water

content, which can be greater than to 98% (Elliott & Mahmood, 2007). Disposal of the sludge

generally occurs via three methods: landfill, incineration, or landspreading. Prior to utilizing any

of the methods, the water must be removed so as to minimize the mass and volume of sludge,

and increase dryness. In the case of landfilling, transportation and disposal fees are normally

charged per unit mass, and landfill operators may also impose limits on the maximum moisture

content to prevent excessive leaching. Disposal by incineration requires increased dryness as

biomass fuels typically need a minimum of 40-60% dry solids to maintain autogeneous

combustion (depending on the type of combustor used) (ADI Limited, 2005). Dewatering of

sludge to the extent necessary for disposal can be costly, requiring dedicated equipment and an

array of treatment chemicals.

In the pulp and paper industry in Canada, incineration has commonly been used as a means of

sludge disposal with 49% of pulp and paper mills employing this method in 1998 (ADI Limited,

2005). Effective combustion, however, is still limited by high and variable moisture content,

which in turn limits the potential for energy recovery, and complicates boiler operations. Co-

combustion with higher quality fuels (e.g. natural gas, coal, bark, etc.) is sometimes necessary

to overcome excess moisture in sludge. Inefficiencies and challenges in sludge dewatering

systems are thus capable of creating cascades of challenges for mill operators. More effective

sludge dewatering is therefore an important goal for mill operations.

One method employed by mills to enhance biosludge dewatering has been to add in primary

sludge with the biosludge prior to dewatering. Primary sludge is generally much easier to

dewater as are mixes of biosludge and primary sludge with higher primary to secondary ratios

(Amberg, 1984)(Mahmood & Elliott, 2006).

2

Despite being a common practice at mills, and being known to provide significant

improvements in biosludge handling, there has been limited study into the mechanisms behind

the benefits conferred by primary sludge addition.

1.1 Objectives

The primary goal of this work is to enhance the understanding of biosludge & primary sludge

dewatering in the context of pulp and paper mills. This is in line with the overarching aims of

mill operators to improve sludge handling so as to generate opportunities for cost savings and

enhanced energy recovery in boilers.

Working towards this goal, the general objective is to identify key parameters that affect the

dewatering performance of primary sludge, biosludge, and mixtures thereof. This is

accomplished specifically through: a) the identification and quantification of a set of metrics to

characterize sludge and dewatering properties; and b) correlation of sludge properties to

dewatering performance to elucidate and quantify mechanisms by which primary sludge

enhances biosludge dewaterability.

A better understanding of the practice of primary sludge addition will allow for greater

opportunities for sludge handling optimization and improve downstream mill operations.

2 Literature Review

2.1 Biosludge

Wastewater treatment in pulp and paper

on effluent discharge quality. Prior to the 1970s, the pulp and paper industry was not subject to

regulations on wastewater effluent discharge, however, damage to fish and fish habitats

prompted the 1971 Pulp and Paper Effluents Regulation under the Fisheries Act in Canada

(Environment Canada, 2012). Amendments to the regulations in 1992 made effluent quality

standards more stringent and enforceable for all mills, with the net result that mills ad

secondary treatment to meet the new standards

treatment, in the form of aerobic biological treatment (commonly the activated sludge process

or ASP), is now a standard component of the overall effluent trea

Figure 1. General Overview of Conventional Wastewater Treatment Process

The activated sludge process uses microorganisms (bacteria and protozoa) and aeration to

biologically degrade organic matter into c

the overall content of organic matter in the effluent stream; however, the process generates

biosludge (waste activated sludge) as a byproduct. Canadian pulp and paper mills typically

generate less than 100 kg of oven dried sludge per tonne of pulp/paper product, of which the

mean secondary sludge component has been approximately 37%. These mills produce

secondary sludge in a range of 1

Literature Review

Wastewater treatment in pulp and paper mills is necessary to meet environmental regulations

on effluent discharge quality. Prior to the 1970s, the pulp and paper industry was not subject to

regulations on wastewater effluent discharge, however, damage to fish and fish habitats

Pulp and Paper Effluents Regulation under the Fisheries Act in Canada

. Amendments to the regulations in 1992 made effluent quality

standards more stringent and enforceable for all mills, with the net result that mills ad

secondary treatment to meet the new standards (Environment Canada, 2012). Secondary

treatment, in the form of aerobic biological treatment (commonly the activated sludge process

), is now a standard component of the overall effluent treatment process at mills.

General Overview of Conventional Wastewater Treatment Process

The activated sludge process uses microorganisms (bacteria and protozoa) and aeration to

biologically degrade organic matter into carbon dioxide and water (Bitton, 2005)

the overall content of organic matter in the effluent stream; however, the process generates

e (waste activated sludge) as a byproduct. Canadian pulp and paper mills typically

kg of oven dried sludge per tonne of pulp/paper product, of which the

mean secondary sludge component has been approximately 37%. These mills produce

secondary sludge in a range of 1-60 odt per day (Dorica, Harland, & Kovacs, 1999)

3

mills is necessary to meet environmental regulations

on effluent discharge quality. Prior to the 1970s, the pulp and paper industry was not subject to

regulations on wastewater effluent discharge, however, damage to fish and fish habitats

Pulp and Paper Effluents Regulation under the Fisheries Act in Canada

. Amendments to the regulations in 1992 made effluent quality

standards more stringent and enforceable for all mills, with the net result that mills adopted

. Secondary

treatment, in the form of aerobic biological treatment (commonly the activated sludge process

tment process at mills.

The activated sludge process uses microorganisms (bacteria and protozoa) and aeration to

(Bitton, 2005). This reduces

the overall content of organic matter in the effluent stream; however, the process generates

e (waste activated sludge) as a byproduct. Canadian pulp and paper mills typically

kg of oven dried sludge per tonne of pulp/paper product, of which the

mean secondary sludge component has been approximately 37%. These mills produce

(Dorica, Harland, & Kovacs, 1999). A survey of

4

Finnish plants found secondary sludge from activated sludge plants to be produced at a rate of

6 kg/tonne of product (5.9 tpd) and 9.5 kg/tonne of product (11.5 tpd) for paper and pulp mills

respectively (Saunamaki, 1997). Overall the mills in the above surveys typically processed on

average between 26 and 41 odt of total sludge per day. A more recent survey of Canadian mills

found that approximately 50 dry kg of sludge (70:30 primary:secondary) is produced per tonne

of production (Elliott & Mahmood, 2005).

As biosludge is a dilute slurry with a water content that usually exceeds 98% (Mahmood &

Elliott, 2007), mills often must process tens to hundreds of tonnes per day of wet biosludge

from secondary clarifiers. The requirement for high throughput as well as high water removal

efficiency in sludge handling systems necessitates expensive dewatering equipment as well as

ongoing costs for dewatering aids and conditioners. Effective removal of water from biosludge

is a challenge due to the composition and properties of biosludge. Physical properties including

particle size, compressibility, water content; biological properties including biomass content

and composition; as well as chemical composition/ properties are all contributory factors that

can influence dewaterability of biosludge.

Particle size distribution plays an important role in both the settleability of sludge as well as

filtration. In the context of wastewater sludges, the following classification system (Karr &

Keinath, 1978) has been used to describe particle sizes:

Table 1. Solids Classification System

Solids Fraction Size (μm)

Settleable ≥100

Supracolloidal 1-100

True colloidal 0.001-1

Dissolved ≤0.001

5

In general, activated sludge is comprised of particles that fall primarily in the supracolloidal and

settleable range (Liao, Droppo, Leppard, & Liss, 2006)(Dursun, Ayol, & Dentel, 2004)(Karr &

Keinath, 1978). Karr & Keinath (1978) investigated the influence of particle size fraction on

dewatering characteristics and found that particles in the supracolloidal range of 1-100 μm had

the greatest effect. Their findings indicate that higher fractions of supracolloids is correlated

with poor dewatering characteristics, due to the ability of particles of this size range to blind

filtration media and sludge cakes and increase filtrate flow resistance.

Particle size in combination with other properties can also have a negative effect on dewatering

properties. Biosludge particles are generally negatively charged due to EPS and other

biochemical components (Liao, Allen, Droppo, Leppard, & Liss, 2001; Liao, Allen, Leppard,

Droppo, & Liss, 2002). The negative charge can, by means of the electrical double layer and

subsequent electrostatic repulsion, cause the sludge to behave in a manner similar to colloidal

suspensions (Neyens & Baeyens, 2003)(Wilén, Jin, & Lant, 2003). In general, lower magnitude

surface charge is related to improved settling (Neyens & Baeyens, 2003).

In addition to fine particles, biosludge also demonstrates a high degree of compressibility.

Highly compressible sludge particles blind filter media and the sludge cake by means of reduced

porosity as sludge particles deform and close voids in the sludge cake (Qi, Thapa, & Hoadley,

2011)(Smollen & Kafaar, 1997)(Sorensen & Hansen, 1993). Compressibility is known to be

influenced by floc size, the presence of filaments, and extracellular polymeric substances (EPS)

(Jin, Wilén, & Lant, 2003). Extracellular polymeric substances can have a negative effect on

sludge compressibility. This is caused by the EPS preventing nearby cells from packing closely

together, as well as the formation of a gel matrix which retains water (Liao et al., 2001).

The EPS gel matrix is itself affected by cations, which in turn affect the biosludge bulk

properties. Cations, specifically divalent cations such as Ca2+

and Mg2+

, are known to act as

bridging agents that interact with negatively charged EPS and stabilize the gel matrix (Cousin &

Ganczarczyk, 1999)(Nguyen, Hilal, Hankins, & Novak, 2008)(Murthy, Novak, & De Haas, 1998).

Monovalent cations such as Na+ and K

+ have the opposite effect and destabilize the matrix

leading to deflocculation, increased turbidity, poorer settling, and a decrease in filterability, and

6

it is generally accepted that a monovalent to divalent (M:D) cation ratio of 2 (on a charge

equivalence basis) is the threshold at which dewatering properties deteriorate (Cousin &

Ganczarczyk, 1999)(Nguyen et al., 2008)(Murthy et al., 1998). As noted by Murthy et al. (1998),

a high M:D ratio and the associated problems are generally seen in scenarios where caustic

soda was added for pH control. For the pulp and paper industry, this is especially relevant as

wastewater streams entering the activated sludge process contain pulping chemicals which

commonly include sodium hydroxide, sodium sulphide, sodium sulphite, and/or sodium

bicarbonate. All of these pulping chemicals can contribute to a poor M:D ratio, and therefore

poor dewatering performance.

2.2 Primary Sludge

Primary sludge is generated by the primary treatment (clarification) of raw wastewater. After

screening for large debris, raw effluent is pumped into a primary clarifier and solids are allowed

to settle under gravity. The clarified effluent is pumped on to secondary treatment, and the

solids collected in the clarifier are removed and referred to as primary sludge. At a pulp and

paper mill, primary sludge is primarily composed of fibres and fines that have been lost from

the pulping and/or papermaking process (Mahmood & Elliott, 2006).

In sludge handling systems primary sludge is added to biosludge for two reasons: 1) as a

dewatering aid, and 2) to consolidate sludge streams prior to sludge processing. At the mill level

this practice has been shown to improve the dewaterability of sludge, reduce the costs for

additional chemical sludge treatments, and improve overall sludge throughput as seen in Table

2 (Amberg, 1984).

Primary sludge has been shown to improve dewatering of biosludge (H. Zhao, 2000)(Amberg,

1984) and to minimize the complexity of sludge handling systems, primary sludge and biosludge

are usually combined. In fact, sludge processing equipment (dewatering apparatus), are

commonly designed to operate with a specific mix ratio. As primary sludge and biosludge have

typically been produced at a ratio of 70:30 (Elliott & Mahmood, 2005), it would follow that

equipment would be optimized around this ratio.

7

Table 2. Performance data for belt filter presses dewatering primary and secondary sludges

Sludge Ratio Polymer cost

$/metric tonne

Actual cake solids

%

Output, metric

tonnes/metre width

Primary sludge 5-11 25-35 10-20

P:S – 2.0 22-33 20-25 8-15

P:S – 1.5 28-39 18-25 7-15

P:S – 1.0 33-44 16-20 5-10

Secondary Sludge 33-100 13-16 4-8

Designing equipment around this ratio presents the challenge whereby the mix ratio needs to

be maintained to ensure optimal performance, and yet primary sludge is a diminishing resource

at mills. In recent times, mills are engaged in efforts to optimize product yields, and minimize

fibre loss to maximize economics of mill operations (Mahmood & Elliott, 2006). The resulting

decrease in primary sludge to biosludge ratio can affect sludge handling operations, and

anecdotal evidence from select Canadian mill operators would suggest that a lower ratio results

in reduced sludge throughput, increased demand for dewatering chemicals/aids, and a lower

final cake solids. At low ratios, dewatering equipment can even be rendered completely

ineffective in solid/liquid separation.

While primary sludge is known to improve dewatering, minimal study has been conducted on

the mechanisms behind this benefit. There is a lack of knowledge in the literature that

quantitatively assesses changes in biosludge properties upon addition of primary sludge.

Studies that have been conducted in biosludge dewatering are more often focused on the

addition of other physical conditioners in the context of the filter-aid effect.

2.3 Filter Aids

A filter aid is a type of physical conditioner which serves two primary functions: 1) increase cake

porosity, and 2) decrease cake compressibility (Qi et al., 2011). Mixing in filter aids prior to

mechanical dewatering prevents the sludge cake structure from collapsing under pressure. This

ensures that pores and voids remain available for water to drain throug

pressures to be utilized than would otherwise be allowed with a compressible sludge

2011).

While an extensive range of filter aids are known to improve the dewaterability of sludges as

outlined in Table 3, it should be noted again that there

primary sludge as a filter aid.

ensures that pores and voids remain available for water to drain through, and allow for higher

pressures to be utilized than would otherwise be allowed with a compressible sludge

Figure 2. Filter Aid Effect

While an extensive range of filter aids are known to improve the dewaterability of sludges as

, it should be noted again that there is limited study on pulp and paper

8

h, and allow for higher

pressures to be utilized than would otherwise be allowed with a compressible sludge (Qi et al.,

While an extensive range of filter aids are known to improve the dewaterability of sludges as

is limited study on pulp and paper

9

Table 3. Common Filter Aids

Filter Aid Material Reference

Inorganic

Fly Ash

(Sludge or Coal boilers)

(Benitez, Rodriguez, & Suarez,

1994; Chen et al., 2010; Nelson

& Brattlof, 1979; Tenney &

Cole, 1968)

Gypsum (Y.Q Zhao & Bache, 2001; Y.Q.

Zhao, 2002)

Cement Kiln Dust (Benitez et al., 1994)

Lime (Deneux-Mustin et al., 2001;

Zall, Galil, & Rehbun, 1987)

Alum Sludge (Lai & Liu, 2004)

Carbonaceous

Coal Fines

(Albertson & Kopper, 1983;

Sander, Lauer, & Neuwirth,

1989)(Hirota, Okada, Misaka, &

Kato, 1975)

Wood Chips (Jing et al., 1999; Lin, Jing, &

Lee, 2001)

Wheat Dregs (Jing et al., 1999; Lin et al.,

2001)

Bagasse (Benitez et al., 1994)(Y.Q. Zhao,

2002)

Rice Shells & Barn (Lee, Lin, Jing, & Xu, 2001)

Sawdust, Hog fuel, Primary

sludge (H. Zhao, 2000)

Char (Smollen & Kafaar, 1997)

These literature examples are generally in consensus with Qi et al (2011), noting that the

addition of filter aids results in an increase in structural strength, permeability, and porosity of

the cake while reducing compressibility. In an effort to determine the mechanisms behind these

benefits, Tenney & Cole (1968) further investigated particle size of the filter aid (fly ash), and

10

concluded that fly ash with a higher carbon content and a 10-30μm particle size is best. This

indicates that the relationship between particle size of the sludge and the filter aid is important

in determining how effective a particular filter aid will be. Chen et al (2010) conducted an in

depth study to elicit further understanding into the mechanisms by which filter aid action is

occurring. They found, using a modified coal fly ash filter aid, that specific resistance to

filtration decreased, and proposed that the mechanisms causing this include charge

neutralization, adsorption bridging leading to improved floc formation; as well as skeleton

building. Adsorption and charge neutralization as processes generally involve electrostatic

forces and/or chemical bonding/interaction of functional groups. Thus, the chemical makeup of

a material will likely influence its ability to adsorb or neutralize charge. As Chen et al (2010)

demonstrate, chemical modification of coal fly ash was able to improve its effect as a filter aid.

In the context of primary sludge, this is an opportunity to develop more knowledge as there is a

lack of study in the literature on these properties as they relate to primary sludge. The

chemistry and physical properties of primary sludge are largely un-studied, and furthermore

there is a lack of knowledge on how any of the proposed mechanisms above may translate to

primary sludge and biosludge mixtures. The study of particle size, and sludge chemistry are

therefore a good starting point for evaluation of primary sludge as a dewatering aid.

In addition to mechanisms, important aspects in the use of filter aids are the quantity used and

final result with respect to dewatered sludge cake. For the references listed in Table 3,

information on the filter aid dosage, and resulting dewatered cake solids content has been

extracted and presented in Table 4.

11

Table 4. Dosage and Performance of Common Filter Aids

Filter Aid Dose Test Range

(Mass Fraction - %)

Optimum

Dose

(Mass

Fraction - %)

Sludge Cake

Solids

(Mass Fraction -

%)

Reference

Char 33% N/A ~29-42% (Smollen & Kafaar,

1997)

Primary Sludge,

Sawdust & Hog

fuel

67-87% primary

sludge

20-40% sawdust

and hog fuel

N/A

~33-36% with

primary sludge

~36% with 40%

sawdust

~32% with 42%

hog fuel

(H. Zhao, 2000)

Wood Chips &

Wheat Dregs

0-75% wood chips

0-47% wheat dregs >75%

~25% with 75%

wood chips

~15% with 47%

wheat dregs

(Lin et al., 2001)

Wood Chips,

Wheat Dregs, Coal

Ash

0-63% wood chips

& wheat dregs

0-38% coal ash

63% for Wood

chips &

Wheat Dregs

Coal ash

provided no

benefit

N/A (Jing et al., 1999)

Alum sludge 20-67% N/A N/A (Lai & Liu, 2004)

Gypsum 60% N/A 15-40% (Y.Q. Zhao, 2002)

Fly Ash 0-175 g/L 50 g/L ~27% (Tenney & Cole,

1968)

Fly Ash 0-70% 64% ~40% (Nelson & Brattlof,

1979)

Modified Coal Fly

Ash

Up to 91% mass

fraction 73% ~43% (Chen et al., 2010)

Fly Ash, Cement

Kiln Dust, Bagasse

53-64% for Fly ash

Not stated for kiln

dust or bagasse

60% for fly

ash

63% for kiln

dust

27% for

bagasse

36% with 60%

fly ash

44% with 63%

kiln dust

15% with 27%

bagasse

(Benitez et al.,

1994)

Notes:

• Sludge cake solids data includes conditioning with both the filter aid and another

chemical conditioner with the exception of (Tenney & Cole, 1968) and (Chen et al.,

2010) where only the filter aid was used.

• Dose test range and optimum dose have been reprocessed from sources to be

expressed as a mass fraction of total solids.

12

• For sources reporting sludge cake solids, the method of dewatering was filtration at the

lab scale (i.e. benchtop vacuum, pressure or filter press filtration apparatuses).

From Table 4 we see that dosages of filter aids vary dramatically between studies. In general,

higher dosages appear to be preferable with the range of 60-80% being reported most often.

Despite these high doses however, it appears rare in the literature to achieve a sludge cake

with a solids content above 40-45% which is generally the minimum threshold required to

achieve self-sustaining combustion for biomass (ADI Limited, 2005).

In the context of sludge dewatering at mills, while primary sludge has traditionally been used in

proportions around 70%, with production of primary sludge being reduced, using such large

quantities is generally not an option for the future (Mahmood & Elliott, 2006). Finding methods

by which primary sludge can be more effectively used at lower proportions is thus important in

a mill setting. Achieving the minimum 40% solids content in dewatered sludge cake is also of

great importance for mills as incineration in biomass boilers is a common disposal method.

2.4 Assessment of Dewaterability

A number of tests have been developed that assess various aspects of sludge dewaterability.

These tests include sludge volume index, zone settling velocity, capillary suction time (CST),

specific resistance to filtration (SRF), wedge zone simulation, Crown Press, piston press, and

gravity drainage among others. While these are all capable of providing information regarding

the dewaterability, settleability, and/or filterability of sludges, the Crown Press test is one of

the few that is specifically designed to simulate conditions inside an industrial scale dewatering

apparatus (belt filter press).

The Crown Press is a simple benchtop device that allows the user to press the sludge between

two belts over a crown. This action is designed to replicate the various stages in a commercial

belt filter press including the wedge zone, and pressure zone. Application of tension to the belts

over the crown replicates the shearing motion achieved as belts travel around rollers in a belt

filter press.

13

Work conducted at the University of Illinois – Urbana Champaign in the 1990s (Emery, 1994),

(Galla, 1996), (Galla, Freedman, Severin, & Kim, 1996), and (Graham, 1998) demonstrated that

the crown press was able to simulate the wedge and high-pressure zones in a belt filter press,

as well as evaluate polymer performance and belt fabric performance. The crown press tests

were able to accurately predict belt filter performance at multiple wastewater treatment

plants. Graham (1998) came to the additional conclusions that Crown Press tests were capable

of evaluating the effect of divalent cations on final cake solids, and provided better prediction

of dewatering performance than capillary suction time.

Figure 3. Crown Press Belt Press Simulator (Phipps & Bird, 2013)

14

Capillary suction time is a commonly used indicator of sludge filterability. Capillary suction time

is defined as the time taken for filtrate to travel from a sludge reservoir and transverse a

defined distance via capillary action in a standard filter paper. CST, however, is not a

fundamental measure of dewaterability, and as such there are limitations to the usefulness of

CST data, most significantly the dependence of the method on the sludge solids content, and

inability to compare results with other sources (Vesilind, 1988). That being said, it is

nonetheless a rapid and practical tool that can provide some useful information about sludge

conditioning. It has been used for decades for this purpose to evaluate chemical conditioners

and their effects on sludge dewaterability (Vesilind, 1988).

3 Materials and Methods

3.1 Sludge

Sludge samples were obtained from a multi

The mill is equipped with a central wastewater treatment plant with primary and secondary

(Aerobic) treatment. The sludge handling system is fed by sludge lines from the central

wastewater treatment plant as well as dedicated prim

lines. As a result, the mill generates and processes 3 different types of primary sludge and one

type of secondary sludge (biosludge). Samples were shipped in pails via courier from the mill to

the laboratory, with an average travel time of 2 days. Samples not used immediately were

stored in a 4°C cold-room.

Figure 4. Overview of

3.1.1 Biosludge

Biosludge is generated in the aerated sludge process. This

influents, as well as effluent from an upstream anaerobic d

chemical oxygen demand (COD)

with an average sludge age of approximate

of 2ppm. The effluent from the aerated sludge process is then sent to two secondary clarifiers,

from which the sludge is combined and pumped to the sludge handling system.

Materials and Methods

Sludge samples were obtained from a multi-process integrated pulp and paper mill in Canada.

The mill is equipped with a central wastewater treatment plant with primary and secondary

(Aerobic) treatment. The sludge handling system is fed by sludge lines from the central

wastewater treatment plant as well as dedicated primary clarifiers from two additional process

lines. As a result, the mill generates and processes 3 different types of primary sludge and one

type of secondary sludge (biosludge). Samples were shipped in pails via courier from the mill to

h an average travel time of 2 days. Samples not used immediately were

Overview of Central Wastewater Treatment Plant

is generated in the aerated sludge process. This process is fed with low solids

influents, as well as effluent from an upstream anaerobic digester which serves to reduce

prior to aerobic treatment. The aeration basins are operated

with an average sludge age of approximately 12.5-13 days with a target dissolved oxygen (DO)

of 2ppm. The effluent from the aerated sludge process is then sent to two secondary clarifiers,

from which the sludge is combined and pumped to the sludge handling system.

15

nd paper mill in Canada.

The mill is equipped with a central wastewater treatment plant with primary and secondary

(Aerobic) treatment. The sludge handling system is fed by sludge lines from the central

ary clarifiers from two additional process

lines. As a result, the mill generates and processes 3 different types of primary sludge and one

type of secondary sludge (biosludge). Samples were shipped in pails via courier from the mill to

h an average travel time of 2 days. Samples not used immediately were

process is fed with low solids

igester which serves to reduce

prior to aerobic treatment. The aeration basins are operated

13 days with a target dissolved oxygen (DO)

of 2ppm. The effluent from the aerated sludge process is then sent to two secondary clarifiers,

from which the sludge is combined and pumped to the sludge handling system.

Figure

3.1.2 Primary sludge Type A

Type A primary sludge is generated in a dedicated process clarifier which is fed from a

paperboard process. The clarifier influent contains

(BCTMP) pulp residues (hydrogen

condensate, post extraction washer

produced onsite, while the Kraft pulp is sourced from another mill.

3.1.3 Primary sludge Type B

Type B primary sludge is generated in

a hardwood BCTMP pulping process (hydrogen peroxide, sodium sulphite

3.1.4 Primary sludge Type C

Type C primary sludge is generated in the prima

plant (See Figure 4 North Wemco Clarifier)

lines including but not limited to: pulping effluent

Figure 5. Sludge Handling System

Primary sludge Type A

Type A primary sludge is generated in a dedicated process clarifier which is fed from a

paperboard process. The clarifier influent contains bleached chemi-thermo-mechanical pulp

en peroxide, sodium sulphite, sodium hydroxide

asher filtrate, as well as Kraft pulp residues. The BCTMP pulp is

produced onsite, while the Kraft pulp is sourced from another mill.

Primary sludge Type B

Type B primary sludge is generated in an additional dedicated process clarifier which is fed from

pulping process (hydrogen peroxide, sodium sulphite, sodium hydroxide

Primary sludge Type C

Type C primary sludge is generated in the primary clarifier in the central wastewater treatment

North Wemco Clarifier). This clarifier is fed by the remaining mill process

ot limited to: pulping effluent, and chemical production effluent.

16

Type A primary sludge is generated in a dedicated process clarifier which is fed from a

mechanical pulp

, sodium hydroxide), acid

iltrate, as well as Kraft pulp residues. The BCTMP pulp is

s clarifier which is fed from

, sodium hydroxide).

ry clarifier in the central wastewater treatment

. This clarifier is fed by the remaining mill process

chemical production effluent.

17

3.2 Chemicals

3.2.1 General Reagents

Chemicals and reagents used in this study are summarized below.

Table 5. Chemical/Reagents

Reagent Type Reagent

Identifier

Description Supplier

Acid 7525-1 Nitric Acid – ACS Reagent Grade Caledon Laboratories

Ltd., Georgetown, ON,

Canada

Acid 6025-1 Hydrochloric Acid – ACS Reagent

Grade

Caledon Laboratories

Ltd., Georgetown, ON,

Canada

Dye 89640 Toluidine Blue Sigma-Aldrich Canada

Co., Oakville, ON,

Canada

Surface

Charge Titrant

271969 Poly(vinyl sulfate) Potassium Salt

Mw~170,000

Sigma-Aldrich Canada

Co., Oakville, ON,

Canada

Surface

Charge Titrant

409022 Poly(diallyldimethylammonium

chloride) solution 20wt% in water.

Mw~200,000-350,000.

Sigma-Aldrich Canada

Co., Oakville, ON,

Canada

Surface

Charge Titrant

H9268 Hexadimethrine Bromide Sigma-Aldrich Canada

Co., Oakville, ON,

Canada

3.2.2 Polymer

The polymer utilized in this study was BASF OrganoPol 5400 (BASF Corporation, Charlotte, NC,

USA ). It is a commercially available cationic polyacrylamide based flocculant. This polymer is

distributed in dry powdered form. Organopol 5400 is utilized as a flocculant for sludge

dewatering by the mill providing the sludge samples. It is for this reason that this polymer was

utilized, so as to be able to provide some measure of comparison from lab tests to the mill

operations.

3.2.2.1 Polymer Preparation

OrganoPol 5400 was prepared as

powder was measured in an aluminium pan, before being added to the water under high vortex

using a magnetic stir bar and stir plate

to ensure complete emulsification

minimum of 2 hours prior to use. The polymer emulsion was used within 5 days.

3.3 Experimental Approach

Figure

As outlined in Figure 6, the general experimental approach begins with biosludge and primary

sludge, the various physical and chemical properties of which are assessed. These properties

include capillary suction time, total suspended solids, pH, particle size distribution, and cation

concentrations. These properties are analyzed for trends in properties apparent between

batches of sludge, and between types of sludge. The biosludge and primary sl

combined to form mixtures at predetermined mix ratios. The mixtures are then subject to the

utilized, so as to be able to provide some measure of comparison from lab tests to the mill

Polymer Preparation

OrganoPol 5400 was prepared as a 0.5 wt% concentration in distilled water (or 5g/L). The dry

powder was measured in an aluminium pan, before being added to the water under high vortex

using a magnetic stir bar and stir plate. The mixture was vortexed for a minimum of 60 seconds

emulsification. The emulsion was then allowed to rest and age for a

minimum of 2 hours prior to use. The polymer emulsion was used within 5 days.

Approach

Figure 6. Experimental Approach

, the general experimental approach begins with biosludge and primary

sludge, the various physical and chemical properties of which are assessed. These properties

capillary suction time, total suspended solids, pH, particle size distribution, and cation

concentrations. These properties are analyzed for trends in properties apparent between

batches of sludge, and between types of sludge. The biosludge and primary sludges are then

combined to form mixtures at predetermined mix ratios. The mixtures are then subject to the

18

utilized, so as to be able to provide some measure of comparison from lab tests to the mill

concentration in distilled water (or 5g/L). The dry

powder was measured in an aluminium pan, before being added to the water under high vortex

. The mixture was vortexed for a minimum of 60 seconds

and age for a

minimum of 2 hours prior to use. The polymer emulsion was used within 5 days.

, the general experimental approach begins with biosludge and primary

sludge, the various physical and chemical properties of which are assessed. These properties

capillary suction time, total suspended solids, pH, particle size distribution, and cation

concentrations. These properties are analyzed for trends in properties apparent between

udges are then

combined to form mixtures at predetermined mix ratios. The mixtures are then subject to the

19

same tests for physical properties as the raw sludge, and are tested both with and without

polymer treatment. Again the properties are analyzed for trends. The sludge mixtures are then

evaluated for dewaterability using the Crown Press. This data is analyzed for trends, and it is

also correlated against physical properties so as to determine and quantify which physical

properties are factors in determining dewaterability.

3.4 Test Protocols

3.4.1 Total & Volatile Suspended Solids

Total suspended solids (TSS) and volatile suspended solids (VSS) were measured as per

Standard Methods 2540D (APHA, AWWA, & WEF, 1999) using Whatman Grade 934-AH Glass

Microfiber Filters (GE Healthcare Life Sciences, Piscataway, NJ, USA).

3.4.2 Total and Volatile Solids

TS and VS were measured as per Standard Methods 2540B and 2540E respectively (APHA et al.,

1999).

3.4.3 Capillary Suction Time

Capillary suction time (CST) was measured with a Type 304M Laboratory CST Meter and 7x9 cm

CST Paper (Triton Electronics Ltd., Essex, England). Sludge samples were tested in triplicate with

3mL aliquots at 23 + 2°C.

3.4.4 Particle Size

Particle size distribution was measured with a Malvern Mastersizer S equipped with a Large

Volume Dispersion Unit (Malvern Instruments Ltd., Worcestershire, UK). The instrument was

capable of measuring particles up to an equivalent diameter of 900 µm. Sludge samples at 23 +

2°C were added to the dispersion unit and stirred at low speed to evenly disperse the flocs

without disrupting them. Tap water was used to dilute the samples. Sample was added until the

laser obscuration was within the optimal range of 0.1-0.3 (a target range of 0.16-0.22 was used

to maintain consistency between samples). Samples were measured within 15 seconds of being

added to the dispersion unit to minimize time or agitation related sample degradation.

20

3.4.5 Elemental Composition

Elemental composition, specifically cation analysis, was conducted using Inductively Coupled

Plasma – Optical Emission Spectroscopy (ICP-OES). A 720 ICP-OES instrument with SPS-3

Autosampler and ICP Expert II Software was used for these analyses (Agilent Technologies

Canada Inc., Mississauga, ON, Canada).

Samples were prepared by the following protocol:

• A known volume of sample was transferred to a Pyrex tube and weighed.

• Aqua Regia was freshly prepared in a fume hood using Nitric Acid and Hydrochloric Acid

in a 1:3 volume ratio.

• 5mL of Aqua Regia was added to each tube.

• Tubes were placed in a hot water bath and brought to 95°C and allowed to digest for 2

hours.

• Additional Aqua Regia was added in 1mL increments and additional digesting time

allowed as necessary until all solid matter in the samples had been digested.

• The tubes were then removed from the hot water bath and allowed to cool to room

temperature.

• The digested samples were then diluted in a 5% Nitric Acid solution. A minimum of two

different dilution ratios were used to ensure cation concentrations fell within the

calibration limits of the ICP-OES Instrument.

• Diluted samples were transferred to 15mL conical centrifuge tubes and loaded into the

autosampler for analysis.

Samples were measured using the following instrument parameters:

21

Table 6. ICP-OES Instrument Parameters

Parameter Value

Power (kW) 1.20

Plasma Flow (L/min) 15.0

Auxiliary Flow (L/min) 1.50

Nebulizer Flow (L/min) 0.75

Replicate Read Time (s) 10.00

Instrument Stabilization

Delay (s) 15

Sample Uptake Delay (s) 30

Pump Rate (rpm) 15

Rinse Time (s) 10

Replicates 3

3.4.6 Crown Press Dewaterability & Gravity Filtration

A Crown Press belt press simulator and accompanying gravity filtration apparatus (Phipps &

Bird, Inc., Richmond, VA, USA) was utilized as the primary indication of dewaterability. The belt

filter fabric supplied with the Crown Press was a HF7-7040 white polyester belt with a 64x24

count in a 6x2 H’bone weave pattern (Clear Edge Filtration, Tulsa, OK).

22

Figure 7. Crown Press with Attached Gravity Filtration Apparatus

3.4.6.1 Crown Press Calibration

The Crown Press is designed in such a way that the gauge reading does not indicate the

filtration pressure, nor the lineal belt tension. As a result, a calibration must be performed to

correlate the Crown Press Gauge Reading (CPGR) to the pressure and lineal belt tension. The

calibration was conducted using the method and equations as described by Graham (1998):

A spring scale was utilized to apply tension to the top belt while the corresponding CPGR (lbs)

was recorded. The resulting curve is linear of the form:

���� = � ∗ � + � Equation 1

23

with

m = the regression slope, calculated as 0.7158 for this instrument

Ta = applied belt tension (lbf)

b = regression y-axis intercept, calculated as -21.88 lbs for this instrument

The pressure P (psi) can be expressed using the equation:

� = � ∗ ���� − �� ∗�� ∗ �� Equation 2

with

Wb = belt width, 5.75 inches

Dc = crown diameter, 6.625 inches

Lineal belt tension in lb/in Tl is then calculated as follows:

�� = � ∗ �� Equation 3

Crown Press tests were conducted using CPGRs.

CPGR, pressure, and belt tension values used in this study are presented in Table 7.

24

Table 7. Crown Press

CalibrationCrown Press Gauge

Reading

(lb / N)

Pressure Applied

(psi / kPa)

Lineal Belt Tension

(lb∙in-1 / kN∙m-1)

100 / 446 8.9 / 61.4 59.2 / 10.4

150 / 669 12.6 / 86.9 83.5 / 14.6

200 / 892 16.3 / 112.4 107.8 / 18.9

3.4.6.2 Test Protocol

Gravity Filtration & Crown Press tests were conducted using the following test protocol:

• Sludge samples were retrieved from cold storage and transferred to 1L Pyrex beakers.

• Sample beakers were placed in a warm water bath and brought up to room temperature

(23+2°C).

• Beakers were then transferred to a PB-900 Programmable JarTester (Phipps & Bird Inc.,

Richmond, VA, USA) and stirred with 1 inch x 3 inch impellers at 60rpm for 1.5 hours to

allow the sludge to equilibrate.

• 250 mL samples were then withdrawn and transferred to 500mL Erlenmeyer flasks.

Samples requiring mixing of multiple sludge types were mixed to produce a total volume

of 250mL of the desired mix ratio.

• Samples were mixed using a 1.5 inch magnetic stir bar on a stir plate at high speed for

30 seconds. Polymer flocculant, if utilized, was added to the flasks at this stage.

• The mixed samples were then poured into the gravity filtration apparatus and allowed

to filter for 10 minutes. Filtrate was collected in a graduated container.

• The resulting wet cake was transferred to the Crown Press Belts and subject to 100lb

(CPGR) for 30 seconds followed by rapid release, then 150lb for 30 seconds followed by

25

rapid release, and finally 200lb for 30 seconds. Pressate was collected into the same

container as the gravity filtrate.

• The dewatered cake was then extracted from the belts with the aid of a spatula for

analysis.

Small aliquots of sample were withdrawn at various stages during the test protocol to analyze

for suspended solids, total solids and capillary suction time.

3.4.7 pH

A ThermoScientific Orion 370 Advanced PerpHecT LogR pH/ISE instrument with Orion 9206BN

PerpHecT Combination pH electrode (Thermo Fisher Scientific Inc., Waltham, MA, USA) was

used to measure pH.

3.4.8 Data Analysis

Statistical and graphical analysis of data was performed using GraphPad Prism 6 (GraphPad

Software Inc.). Statistical comparison of the mean of data sets was conducted using the built-in

t-test and ANOVA functionality with results reported at the 95% confidence level unless

otherwise stated. Correlation analysis was performed using the built-in Pearson correlation

tests with a two-tailed confidence level of 95%. Regression analysis of graphical data was

performed using the method of least squares, with confidence bands displayed that represent

the 95% confidence level unless otherwise stated.

26

4 Results & Discussion

Data obtained from laboratory testing is presented and discussed herein. First the issue of

sludge storage and use over extended periods of time is discussed with supporting data to show

that stored sludge maintains its properties over time. Evaluation of CST as an indicator of

dewaterability is presented next, with an emphasis on the challenges and limitations associated

with using CST to compare different types of sludges.

Crown Press dewaterability testing data follows and is divided into several subcategories. First,

relationships between CST, TSS and Crown Press cake solids are examined to establish whether

or not CST is capable of predicting mechanical dewaterability. Trends in cake solids are

presented next, showing data for mixtures of three types of primary sludge with biosludge,

both with and without polymer treatment. These data are analyzed to provide quantification of

the effect of primary sludge addition, and along this line of analysis, an empirical model has

been generated that is able to describe the effect of primary sludge addition on dewatered

cake solids. Suggestions for further investigation into the model are discussed, with attention

given to how this model might be validated and used in a mill setting.

A theoretical basis for the trends observed in cake solids data is developed next. Darcy’s Law is

derived to a form with which SRF can be extracted from filtration data. SRF is correlated against

cake solids, and sludge primary sludge content, in an effort to explain the trends in

dewaterability. This theoretical evaluation, however has some shortcomings, for which

strategies for future investigation are proposed so as to be able to refine and solidify the

theoretical explanation for cake solid trends.

Data for filtrate/pressate quality, particle size distribution, and elemental composition are

presented in sequential order. Attention is devoted to the ease with which low solids

filtrate/pressate can be extracted from primary sludge, and how this in combination with a

favourable disposition of monovalent cations could be used to better optimize how primary

sludge is used. Particle size distribution data is evaluated and discussed as it pertains to the

filter aid effect, demonstrating that primary sludge addition increases the proportion of larger

27

particles in mixed sludge. A shortcoming in the particle size instrument is also discussed with

regards to how the data may be skewed, and methods are proposed to compensate for or

eliminate this skew in future investigations.

4.1 Sludge Storage

As sludge was sourced from a mill over 400km from the laboratory, it was necessary to procure

large samples of sludge and store them under refrigeration for use over the course of several

weeks. Sludge properties change over time, necessitating tests to ensure that any changes from

extended storage would be insignificant. Twice, over the course of experimental work, a sample

of sludge was stored under refrigeration. These samples were monitored in daily and weekly

intervals for three bulk properties: CST, TSS, and pH. A trend in these properties with a slope

that is non-zero would indicate changes in the sludge that may influence dewaterability

properties.

Figure 8. Biosludge pH - October 2012 Batch

Figure 9. Biosludge TSS - October 2012

Batch

Figure 10. Biosludge CST - October 2012

Batch

0 30 60 90 120 150 1800

10

20

30

40

50

Days after Sampling

Figure 11. Biosludge CST - October 2012

Batch - Outlier Removed

28

Biosludge obtained October 12, 2012 was tested over the course of 180 days from the sample

date. 8 measurements for pH and TSS and 7 measurements of CST were recorded. pH

measurements for biosludge varied between 7.05 and 7.46 (Figure 8). Measurements of TSS

varied between 19.3 and 24.9 g/L (Figure 9). CST data has been presented twice in Figure 10

and Figure 11, with an outlier having been removed in the latter. CST values ranged between

16.2 and 24.6s. Regression analysis on all four data sets yielded trends that do not significantly

deviate from a slope of zero. Dashed lines indicate the 95% confidence interval on the linear

regression trends.

Figure 12. Biosludge sample 1 pH - June

2013 Batch

Figure 13. Primary Sludge Type C pH - June

2013 Batch

Figure 14. Biosludge and Primary Sludge

CST - June 2013 Batches

0 5 10 15 20 2510

11

12

13

14

15

Days after Sampling

Figure 15. Biosludge TSS - June 2013 Batch

The second sludge storage test was conducted with three sludge samples obtained June 11,

2013, consisting of two samples of biosludge and one sample of primary sludge (Type C). Both

samples of biosludge originated from the same wastewater treatment process at the mill,

however were sourced from the two separate secondary clarifiers (denoted by sample labels 1

and 2) employed by the mill. These samples were tested over a shorter time frame of 10 days.

29

pH values for biosludge sample 1 varied between 6.8 and 8.0 (Figure 12) and 6.1 and 6.4 for

type C primary sludge (Figure 13). CST varied between 9.0 and 11.1s for biosludge sample 1,

10.4 and 12.5s for biosludge sample 2, and 6.4-7.1s for type C primary sludge (Figure 14). TSS

data was collected only for biosludge sample 1 as shown in Figure 15, and over the course of 25

days after sampling, the TSS remained consistently around 12.5g/L. Regression analysis of all

pH, CST and TSS data sets yielded linear trends which did not deviate significantly from a slope

of zero. Dashed lines indicate the 95% confidence band on the linear regression trends.

As values for pH, CST, and TSS remained statistically unchanged over both the short term, and

long term for both biosludge and primary sludge, we may assume with reasonable confidence

that the overall bulk properties of sludge are stable when stored under refrigeration at 4

degrees Celsius. This assumption is valid for periods up to at least a month, if not more.

However, as the properties of the sludge samples were not tested immediately upon sampling,

it is not possible to comment on changes in sludge properties that may occur between sampling

at the mill, and arrival at the laboratory (a time period of around 2-3 days on average). Thus, to

ensure that there is not a significant change in properties during this time frame, a similar

storage experiment would need to be conducted with the initial tests of properties performed

at the sampling time, and then at regular time intervals thereafter.

While these tests do not provide any indication of changes occurring at a more microscopic

level (including changes in microbial composition), the bulk properties are preserved. While

bulk properties are not necessarily encompassing with regards to dewaterability, the consistent

properties provide a basis for comparison of data. Thus, results obtained from a batch of sludge

may be compared to results obtained a few days later from the same batch. It is important to

note at this point, that the variability of sludge properties between two different batches is

greater than the variability within a single batch stored over time. This is evident in Figure 14

where biosludge was sampled at the same time but from two different clarifiers in the same

treatment process. The two clarifiers produced two biosludges, the properties of which were

significantly different from each other. The variability between batches is also evident when

comparing between the October 2012, and June 2013 batches of sludge, i.e. Figure 9 vs. Figure

30

15 and Figure 11 vs. Figure 14, where a significant difference can be seen in average CST and

TSS values.

The greater variability in the samples presents an opportunity for improved confidence in the

data: if the results obtained from different batches of sludge demonstrate similar or identical

trends with regards to dewatering, results may then be pooled into one set, and any

conclusions drawn may be assumed as valid for the entire range of sludge bulk properties. This

is of particular utility as mill operators must contend with sludge which has properties that can

vary dramatically from day to day. Development of dewatering protocols that are valid across

the entire range of biosludge properties would therefore be useful for mill operations.

31

4.2 CST and TSS

CST data, collected as per Section 3.4.3, and TSS data, collected as per Section 3.4.1, are

presented below. CST is commonly used as an measure of the ability of water to release from

sludges and is accepted as a tool to evaluate the performance of dewatering processes (APHA

et al., 1999). Figure 16 displays the CST for sludge samples as received from the mill, and

includes biosludge and primary sludges. Data is incomplete as not all primary sludges were

sampled at the mill in each batch. Error bars represent the 95% confidence interval. For

reference, the CST for pure water was measured at 4.4-4.7 seconds, and represents the lowest

possible value for CST.

Figure 16. CST of Sludge Samples

Between October 2012, and June 2013, there is a lack of consistency in the CST of biosludge

and Type C primary sludge with values varying dramatically. Between June and July of 2013,

measurements appear more consistent and with the exception of biosludge, are statistically no

different from one month to the next. Type A primary sludge is unique in that it has a

32

significantly higher CST than the other sludge types which generally tend to fall in the range of

7-15s for the June and July 2013 batches.

The addition of polymer affects the CST of sludge samples, as particles are flocculated and

water is generally more easily released from the sludge. For the June 2013 batch of sludge, the

CST of biosludge and the three types of primary sludge was evaluated with and without

polymer. The results are presented in Figure 17, with error bars representing the 95%

confidence interval.

Figure 17. CST of Sludge - With and Without Polymer

The addition of polymer had a significant effect on Type A primary sludge, with a reduction in

CST from 38.5s to 10.1s. The CST for biosludge and Type C primary sludge are also reduced,

however the change is not statistically significant. While the CST for Type B primary sludge

increased (generally indicative of worsening dewaterability), the change was not statistically

different. In this set of experiments, a significant improvement was only present for the Type A

primary sludge. This suggests two things: first, that there may be a specific component of Type

A primary sludge that is well suited to the polymer treatment used in this study; and second,

33

that in the case of biosludge, CST may not be able to fully represent changes in dewaterability

arising from polymer treatment. This shall be further discussed in Section 4.3.1.

Another tool for assessing sludge is TSS, which is a measure of the solids content suspended

within the sludge. TSS itself is not a measure of dewaterability, however, the solids content of

sludge is known to have an influence on other tests including CST (APHA et al., 1999; Vesilind,

1988). Considering the variable nature of biosludge, it is important to assess TSS alongside CST

to determine the influence, if any, of the former on the latter. TSS for several sludge batches

has been summarized in Figure 18, with error bars representing the 95% confidence interval.

Figure 18. TSS of Sludge Samples

As was the case with CST, the TSS of the different batches of sludge varies dramatically. The TSS

for Type A primary sludge is generally above 35 g/L, with biosludge falling between 12 and 24

g/L. It is noted in the standard method for measuring CST that solids content has a strong

influence on CST (APHA et al., 1999). As such, the TSS data presented above is correlated with

CST data and is presented in Figure 19, so as to determine if this relationship holds true in this

study. This figure includes data from all types of primary sludge, biosludge, and mixtures of

34

biosludge and primary sludge, both with and without polymer. The solid line indicates the best

fit linear regression, with the dashed lines indicating the 95% confidence interval on this

regression. Error bars on data points represent one standard deviation.

Figure 19. Correlation of CST with TSS

As demonstrated above, there exists a linear relationship between solids content and the CST.

Correlation tests yielded a statistically significant Pearson coefficient of 0.7208.

Further evidence of this linear relationship was collected by performing a series of dilutions on

sludge samples and measuring the resulting CST. In order to preserve any effects that the

aqueous phase of the sludge had on CST (i.e. from dissolved salts and/or soluble organic

compounds), the diluent utilized was supernatant collected from an aliquot of the same sludge

that had been allowed to settle under gravity for 24 hours in the refrigerator. Figure 20 displays

the results of this experiment, along with regression trendlines. Error bars represent one

standard deviation.

35

CST (s)

Figure 20. CST of Sludge - Dilution Tests

As can be seen from the regression analysis for biosludge, Type A primary sludge, and Type B

primary sludge, there is a linear relationship between TSS and CST. A single data point is

presented for Type C primary as dilution was not possible due to an already low TSS of ~5g/L.

The horizontal orange line represents the CST value for pure water, and serves as a threshold

line for comparison. If extrapolated towards the y-axis, the trendlines for biosludge and Type A

primary sludge would intersect at approximately the same CST value as pure water. This is in

contrast to Type B primary sludge where the intercept would be significantly higher, indicating

that the aqueous phase of this sludge may have components that influence CST unlike

biosludge and Type A primary where this does not seem to be the case. Furthermore, while the

trendlines for the sludges are all linear, it is important to note that their slopes are statistically

different from one another (see Section 8.2).

The linear relationship between solids and CST as seen in Figure 20 is consistent with literature

(Vesilind, 1988) in which it is also noted that this relationship can be explained by Darcy’s

equation for flow through a porous medium under the assumption that solids concentration is

36

directly proportional to deposited cake depth. Thus as solids increases, so too does cake depth,

resulting in a corresponding decrease in flowrate through the cake, which manifests as an

increased CST value which is linearly proportional to the sludge solids content (Vesilind, 1988).

The exact nature of these linear trends can provide some insight into the sludge. As the

concentration of each type of sludge increases, so too does the CST, albeit at a different rate

when compared between sludge types. Generally speaking, the higher the CST, the worse the

sludge performs under dewatering, as the CST value relates to the rate at which water is

released from the sludge. Thus, a sludge with a lower CST can be expected to dewater easier.

Extending this principle over a range of solids concentrations, a sludge which exhibits a

marginal increase in CST as a function of solids would logically perform better than a sludge

which exhibits a more pronounced increase in CST. For example, consider Type B primary

sludge vs. Type A primary sludge in Figure 20. Over the range of solids concentrations from

approximately 2 g/L to 20 g/L, the CST of Type B primary sludge increases from 7.3 g/L to 9.4

g/L whereas the CST for Type A primary sludge increases from 5.5 g/L to 18.5 g/L. Over this

range one may state that the CST of Type B sludge is less dependent on solids than Type A

primary sludge, and that for a given solids concentration, Type B primary sludge is able to

release water at a greater rate than Type A primary sludge.

For a given solids concentration, it is relatively straight forward to compare the CST of multiple

types of sludge, however this is an ideal scenario. The solids concentration of different sludges

will likely be different, and even for an individual sludge, the solids concentration will vary with

time due to changes in operating parameters at the mill. Comparing the CST of multiple types

of sludge without correcting for solids concentration is not meaningful as it would be difficult to

determine the extent to which the nature of the sludge was influencing CST as oppose to the

solids concentration. Correcting for the solids concentration requires the use of a solids vs. CST

calibration chart similar to Figure 20. From such a chart it is simple to interpolate (due to the

linear trends) the estimated CST value for multiple types of sludge at a specified solids

concentration. While this allows for comparison of sludges which may not have similar solids

contents, the issue with this approach of correcting CST values for solids concentration arises

37

from the original intent of CST. CST is meant to be a rapid assessment tool which can be used

within a few minutes to assess sludge water release. The need to correct for solids

concentration when comparing CST values adds a layer of complexity to this tool, especially

when considering the time and effort required to generate a calibration chart for each type of

sludge being evaluated. Furthermore, if testing mixtures of sludge, a calibration curve must be

generated for each mixture. The amount of effort required to correct CST values for solids

concentration and solids type quickly compounds, limiting the utility and swiftness of CST as an

assessment tool.

Despite these complexities when using CST to evaluate sludges, there are scenarios in which it

is still useful and can be used with relative ease. An example of such a scenario is when CST is

used to determine optimal polymer dose rates for sludges. In this case, typically only one type

of sludge/mixture is being tested with the only manipulated variable being the polymer dose.

Since the solids concentration and type of sludge is the same for each test sample, there is no

need to perform a correction and the CST values can be measured and compared as is. For the

majority of this work, the optimal polymer dose was determined from an initial sampling of the

sludge, and then used for all subsequent tests. Samples of sludge were prepared in the same

manner as for Crown Press tests (see Section 3.4.6.2), and then divided into several aliquots of

equal volume. Polymer was added to each aliquot, in increasing quantities, and the CST was

measured and plotted. When a minimum CST value was achieved, denoting the optimum dose,

testing ceased. As polymer was added on a volumetric basis in an emulsion, the data was

subsequently reprocessed to express it in units of dry polymer per unit of dry solids in the

sludge. Figure 21 displays this data, with error bars representing one standard deviation.

Type A primary sludge began with a high TSS, and Type C with a low TSS, and once the data was

reprocessed on a mass basis, these curves were horizontally compressed, and expanded

respectively as a result. In finding the optimal polymer dose, the most important values are for

that of biosludge, as the polymer is selected and dosed based on the properties of biosludge,

and in the context of this study biosludge serves as the reference which we are trying to

improve upon. From the blue data set for biosludge, it can be seen that the CST dips slightly at a

38

dose of 4 g/kg, before rising again which is an indication of exceeding the optimum dose. Type

B and Type C primary sludge do not exhibit an optimum point, and trend upwards in a linear

fashion. Type A primary sludge responds dramatically to the polymer and reaches an optimum

at a polymer dose of only 1.3 g/kg. This confirms the previous suspicions based on Figure 17

that perhaps the polymer is better suited to the Type A primary sludge than the biosludge.

However, for the remainder of experiments, the optimum dose achieved with biosludge, 4 g/kg,

has been used, and is in general agreement with the quantities used at the mill (3-5 g/kg).

Figure 21. CST - Optimum Polymer Dose Determination

39

4.3 Crown Press

The Crown Press Belt Press Simulator was utilized as per Section 3.4.6.2 to evaluate the

dewaterability of sludge samples in a manner which simulated the action of a larger scale