porosity structure of alum coagulation …...determined the porosity and structure of alum...
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POROSITY AND STRUCTURE OF ALUM COAGULATION AND
ACTIVATED SLUDGE FLOCS
Beata Gorczyca
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Department of Chernical Engineering and Applied Chemistry University of Toronto
O Copyright by Beau Gorczyca 2000
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POROSITY AND STRUCTURE OF ALUM COAGULATION AND ACTTVATED SLUDGE FLOCS
Doctor of Philosophy, 2000 Beata Gorczyca
Department of Chernical Engineering and AppIied Chemistry University of Toronto
ABSTRACT
Knowledge of floc porosity and structure is the bais for the study of floc pemeability. This study
determined the porosity and structure of alum coagulation and activated sludge tlocs. The porosity of these tlocs
can be expressed in geometric and mass terms. Yet mass porosity can be 1 O times higher than geometric porosity
due to an underestimation of floc densiry in the setîling test, Given the more diable data expressed by geometn'c
porosity, an experirnental method for studying the geometric porosity of aggregates was developed.
The average geornetric porosity was 9 % for alum flocs and 8% for activated sludge flocs. Similar average
geometric porosity and size of the primary particles in these two aggregates suggested similar permeability of these
flocs, while the sealing behaviour of these flocs suggested that activated sludge flocs were more penneable than
alum flocs. This suggested that the floc pemeability couldn't be estimated based on the average porosity of the floc.
Interpretation of the geometnc porosity data using the concepts of fiactal geornetry enabled three pore
populations - small, medium and large - to be identified within alum and activated sludge flocs. Small pores had a
cross-sections1 area smaller than 3 pm'. The medium pores of alum flocs were smaller than 10 p d . and the medium
pores of activated sludge flocs were smaller than 20 Activated sludge flocs are more permeable chan alum
flocs because the pores foming flow channels - medium and large - are bigger in activated sludge flocs than the
corresponding pores in alum flocs.
Based on the size of pores, permeability and structml models were proposed for the flocs studied. in the
activated sIudge floc mode1 flocculi were two times larger than the flocculi in dum flocs. The size of the flocculi
determines the sue of pores facilitating the interna1 flow; therefore, it should be incorporated in the floc
permeabiIity models.
This study makes two recommendations: 1) developing floc permeability models that do not require floc pomsity
estimate; 2) re-calculation of floc mass =fer and drag force predictions using an irnproved estimate of floc
permeability.
ACKNOWLEDGMENTS
First and foremost, I would like to thank my supervisors Dr. Levente Diosady
and Dr. Jerzy Ganczarczyk for giving me the oppomuiity to pursue my Doctor's Degree at the
University of Toronto. 1 would like to express my greatest gratitude and appreciation to
Dr. Jerzy Ganczarczyk, for his guidance and advice throughout this work. His constant
encouragement and positive outlook lifted up my spirit during many dificult times. The helph
comments and cntical review of the thesis provided by professon: Grant Allen, David Bagley,
Bruce Logan, Donald Kirk and Patncia Seyfbed contributed much to its successful completion.
Words of appreciation are not enough for Durga Prasad and Dr. Stan Lugowski for their
continuous support throughout the course of my studies and the words of encouragement when
things were not going well. Matthew Hilgerdenaar. Battista Calvieri, Fred Neub, Bogdan
Cherek. Stan Bleszynski and Zbigniew Bukala provided technical assistance in various aspects
of this study.
1 would like to express my indebtedness to my husband Stanislaw for the support
throughout the doctoral program. My Aunt Stefania Jaciuk, relieved me in my parenting and
household and duties, which is graciously acknowledged.
It is not easy to start a new life in a foreign country. At his point 1 am very much in debt
to al1 rny fiiends. for their wam company and support. Especially to Mona El-Haddad, who
patiently supported me through the good and the bad till the end.
Thinking back about dl those years spent at University of Toronto, I really would have to
acknowledge many people. 1 apologize to al1 those 1 have omitted to mention.
TABLE OF CONTENTS
ACKNOWLEDGMENTS ........................................................................................................... II
TABLE OF CONTENTS ......................~..~............................................................................III
LIST OF TABLES .................................................................................................................... VI1
LIST OF FIGURES ..................................................................................................................... X
NOTATION.. ............................................................................................................................ XII1
1 . INTRODUCTION ................................................................................................................. 1
1.1 Background ....................................................................................................................... 1
........................................................................................................................... Objectives 8
Structure of the Thesis .................................................................................................... 10
2 . LITERATURE REVIEW .................................................................................................. 1 1
2.1 Porosity and Structure of Alum Coagulation Flocs and Other Inorganic Aggregates
......................................................................................................... 11
2.1 -1 Mass Porosity (E) ..................................................................................................... 1 1
2.1.2 Geometric Porosity (P) of Alum Coagulation Flocs ............................................... 16
2.1.3 Porosity and Structure of Alum and Other Inorganic Flocs ..................................... 19
2.2 Porosity and Structure of Activated Sludge Flocs and Other Biological
Aggregates- ................................................................................................................................. 21
2.2.1 Mass Porosity (E) of Activated Sludge Flocs ................................ ... ................... 21
37 ............................. 2.2.2 Geometric Porosity (P) of Activated Sludge Flocs and Biofilms -- 2.2.3 Porosity and Structure of Activated Sludge and Other Biological Flocs .................. 26
2.4 Flow Tbrough Settling Flocs ..b....................................................................................... 28
2.5 Fractal Geometry and Porosity of Flocs b.....m................................................................ 30
............................................................................. 2.5.1 Permeability of Sierpinski Carpet 40
2.6 The Porosity of Flocs and Their Resistance to Shear ..........................................m....... 11
3 . EXPERIMENTAL PROCEDURES AND ANALYTICAL METHODS .................... .. 53 3.1 Outline of Experiments and Analysis Conducted ........................................................ 53
3.2 Design of Experiments to Study Geometric Porosity of Flocs ......................m........b... 54
3.2.1 Description of the Project ......................................................................................... 54
3 2 . 2 Statistical Analysis of Preliminary Data ............................................................... 55
. *
3 .2.2.1 Sarnple Size Determination .................................................................................. 56
3.2.3 Statistical Experiment Design . Conclusions ............................................................ 58
3 3 Porosity and Structure of Alum Coagulation Flocs .............................. .................. 59
3 1 Experimental Methods .................................................................. ... ......................... 59
3 3 . 2 Data Processing ......................................................................................................... 64
33.4 Sierpinski Fractal Dimensions for Alum Coagulation Flocs .................................... 76 iv
................................................................................................................. 3.3.5 Discussion 8 1
3.4 Porosity and Structure of Activated Sludge Flocs 0 0 8 0 0 0 0 ~ 8 8 0 ~ 8 ~ 8 8 8 ~ ~ 8 8 0 8 8 0 8 * 8 9 8 8 0 8 0 0 8 8 8 0 0 8 8 8 8 8 8 8 8 0 0 ~ 0 84
............................................................................................ 3.41 Experimental Methods 84
3.4.2 Mechanical Dispersion of Activated Sludge Flocs ................................................... 87
3.4.2.1 Data Processing ..................................................................................................... 91
3 3 3.L.- Results ................................................................................................................... 92
3.4.2.3 Sierpinski Fractal Dimension for Activated Sludge Flocs .................................... 99
3.4.2.4 Discussion ........................................................................................................... 103
3.4.3 Sonic Dispersion of Activated Sludge Flocs ...................................................... 105
3.4.3.1 Data Processing .................................................................................................. 106
3.4.3.2 Results ................................................................................................................. 106
3.4.3.3 Efiects of Sonication on Response Oscillation of the Activated Sludge ............ 111
3.4.3.4 Effects of Sonication on Sierpinski Fractai Dimensions of Activated Sludge Flocs
3 .4. 3.5 Discussion ........................................................................................................ 114
4 . COMPARISON OF SOME PROPERTIES OF ALUM COAGULATION AND ACTIVATED SLUDGE FLOCS 8 ~ 8 O 8 8 8 8 O 8 O 8 8 8 ~ 8 O 8 O 8 8 8 O ~ 8 8 8 O 8 8 O 8 8 8 8 O O 8 O 8 O O 8 O O 8 ~ O 8 O 8 O O 8 8 O 8 O O 8 O O 8 8 O 8 8 8 8 O O 8 O O 8 8 O 8 O O 8 O 8 8 O 8 O 120
4.1 Cornparison of the Sizes of Alum Coagulation and Activated Sludge Flocs mm........ 120
4.2 Comparison of the Average Geometric Porosity of Alum Coagulation and Activated
Sludge F~OCS ~ ~ o ~ o m o ~ ~ o ~ ~ ~ o o ~ m ~ o o ~ o ~ o o ~ ~ o o o ~ o ~ ~ ~ o o o o o o o o m o o o m o o o o o o o o o o m 122
4.1 Comparison of the Pore Sizes in Alum Coagulation. Activated Sludge Flocs and
Biofdrns ...................................................................................................................................... 129
4.5 Estimation of Relative Permeability and Flow Rate through Alum Coagulation and
............................................................................. Activated Sludge Flots.................................. 130
4-51 Permeability of Flocs .............................................................................................. 130
- 45.2 intra-floc h iow Rates ............................................................................................. 130
. . 4 . 3 Floc Penneabihty Mode1 ....................................................................................... 132
4.6 Comparison of the Structures of Alum Coagulation and Activated Sludge Flocs .. 135
5 . CONCLUSIONS. RECOMMENDATIONS AND ENGINEERING SIGNIFICANCE ........................................................................................................... 138
.................................................................................................................... 5.1 Conclusions 138
........................................................................................................ 5 3 Recommendations 140
5 3 Engineering Signifieance of this Smdy ....................................................................... 141
5 3 Modelling of Activateci Sludge Process .................................................................. 141
5.3.2 Modelling of Secondary Settling .......................................................................... 141
.......................................................................................................................... REFERENCES 144
APPENDICES ........................................................................................................................... 154
LIST OF TABLES
Table 1
Table 2
Table 3
Table 4
Table 5
Table 6
Table 7
Table 8
Table 9
Table 10
Table 11
Table 12
Table 13
Table 14
Table 15
Table 16
Table 17
Table 18
Table 19
Table 20
Floc permeability models (Lee et al.. 1996) .................................................................. 4
............................................................................... Porosity of aium coagulation flocs 18
................................................................................. Porosity of activated sludge flocs 25
Strength parameten c and n for alum coagulation flocs ............................................... 51
Strength parameters c and n for activated sludge flocs ................................................. 52
Outline of experiments and analysis conducted in this thesis ....................................... 53
Jar coagulation test data .............................................................................................. 60
................................... Effects of mixing speed on size (D?) of alun coagulation flocs 67
Effect of mixing speed on geometric porosity (P ,) and size (Dl) of alum coagulation
flocs .............................................................................................................................. 67
Effects of mixing speed on geometric porosity (Pz) of alum coagulation flocs ........... 68
Effects of mixing speed on geometric porosity (P3) of aium coaguiation flocs ........... 69
Effects of mixing speed on geometric porosity (P4) of alun coagulation flocs ........... 69
Effects of mixing speed and the floc size on the geometric porosity - results of the
.................................................................................................... analysis of variance 74
Sire of transition pores on Sierpinski plots for alun coagulation flocs ....................... 80
Sierpinski h c t a l dimension of alurn coagulation flocs &ter mWng ........................... 80
Porosity of alurn coagulation flocs - surnmary ............................................................. 83
Operation data for the Peterborough Wastewater Treatrnent Plant .............................. 85
Effects oîmixing speed on size (Dz) of activated sludge flocs .................................. 93
Effects of mbûng speed on geornetric porosity (Pz) and size (Di) of activated sludge
flocs .........*..............................................................*..................................................... 94
............. Effects of mixing speed on geometric porosity (P3) of activated sludge fiocs 94
Table 21 Effects of mixing speed on geometric porosity (P4) of activated sludge flocs ............. 95
Table 22 Effects of rnixing speed and the size of flocs on the geomeûîc porosity . results of the
analysis of variance ...................................................................................................... 95
Table 23 Size of transition pores on Sierpinski plot for activated sludge flocs in this smdy ... 10 1
Table 24 Size of transition pores on Sierpinski plot for activated sludge flocs in earlier studies
.........*........................................................................................ 101
Table 25 Sierpinski fracta1 dimensions for activated sludge flocs ............................................. 102
Table 26 Geometric porosity of activated sludge flocs . summary ............. .. ................... 104
Table 27 Size (Dt) of activated sludge flocs after sonication ................................................ 108
Table 28 Geornetric porosity (Pz) and size (Di ) of activated sludge flocs f i e r sonication ...... 109
Table 29 Geometric porosity (P3 ) of activated sludge flocs after sonication ............................. 109
Table 30 Georneaic porosity (Pd) of activated sludge flocs after sonication ............................. 110
Table 3 1 Oscillation decay and BODs of activated sludge mixed liquor supernatant f i e r
................................................................................ sonication ................................ .., 110
...... Table 32 Size of transition pores on Sierpinski plots for sonicated activated sludge flocs 116
Table 33 Sierpinski h c t a l dimension for activated sludge flocs &er sonication .................... 116
Table 34 Effects of sonication time and the size of flocs on the geometric porosity and
............................ Sierpinski fracta1 dimensions - results of the analysis of variance 118
Table 35 Size of pores in activated sludge flocs .................... .. ............................................. 119
Table 36 Cornparison of geometric porosity determined with different image d y s i s systems
Table 37 Cornparison of the geometric porosity of alum coagulation and activated sludge fiocs
.................................................................................................... 123
Table 38 Settling Rates of Alum Coagulation and Activated Sludge Flocs .............................. 124
Table 39 Pore cross-sectional area for aiurn. activated sludge flocs and biofilms .................... 129
... ml1
Table 40 Estimated intemal flow vdocities and rates for flocs and biofilrns ............................ 13 1
Table 41 Permeability. pore area and cluster sizes for a square Sierpinski carpet .................... 134
Table 42 Parameten used in the batch settling models and properties of individual flocs ....... 143
LIST OF FIGURES
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Senling function incorporating both dispersed and floccdated settling of activated
sludge (Ekama et al.. 1997) ......................................................................................... 3
Multi-level mode1 of floc formation (Li and Logan. 1997) ............................................ 7
Images of a single alurn coagulation floc photographed during settling ...................... 13
Relationship between mass porosity and size of flocs ............................................... 20
Intra-aggregate fluid velocities for settling and sheared aggregates (Logan and Hunt.
Construction of the Cantor set ...................................................................................... 32
Examples of Sierpinski carpets ..................................................................................... 35
Determination of Sierpinski fractal dimension ......................................................... 37
Sierpinski plot for the biofilms formed in Rotating Biological Contactors (Zahid and
Images of this sections of alum coagulation flocs .................................................... 63
Distribution of geometric porosity (PI) of alum coagulation 8ocs at an increasing
mixing speed ............................................................................................................ 70
Average geometric porosity and size of flocs vs . mixing energy input . alum
coagulation flocs ....................................................................................................... 72
Average geometric porosity vs . size of aium flocs ........................... ... ......... 75
Sierpinski plot for an alum coagulation floc ......................................................... 77
Sierpinski Carpets S.FI. and S.Fr in the Mode1 Floc ................................................ 79
Experimentai apparatus used in experiments with the activated sludge flocs .......... 86
Size (D2) of activated sludge flocs during refloccdation after breakup ................... 88
Breakup and re-growth of a floc .................................................................. 9 0
X
Figure 19
Figure 20
Figure 21
Figure 22
Figure 23
Figure 24
Figure 25
Figure 26
Figure 27
Figure 28
Distribution of geometric porosity (Pz) of activated sludge flocs at an increasing
. . ............................................................................................................. m g speed 96
Average geometric porosity and size of flocs vs . mixing energy input . activated
sludge flocs ............................................................................................................... 98
............................................................. Sierpinski plot for an activated sludge floc 100
Average geometric porosity and size of flocs vs . acoustic energy input . activated
sludge flocs ............................................................................................................. 113
Sierpinski plot for an activated sludge floc subjected to sonication ....................... 117
Typical floc size distributions for alum coagulation and activated sludge flocs .... 121
Shape factors vs . floc size for alum coagulation flocs ........................................ 127
Shape factors of activated sludge flocs .............................................................. 128
Sierpinski carpet used in the floc penneability mode1 (Equation 25) ..................... 133
Structural models proposed for alum and activated sludge flocs ........................... 137
LIST OF APPENDICES
Appendix 1
Appendix 2
Appendix 3
Appendix 4
Appendix 5
Appendix 6
Appendix 7
Appendix 8
Appendix 9
Statistical design of experixnents - data set ............................................ . .......... . 1 55
Statistical design of fioc sarnpling - results of analysis of variance ...................... 157
Effects of mixing intensity on the size of dum coagulation flocs - resdts of
analysis of variance ............................................................................................... 159
Effects of floc size and rnixing energy input on the geometric porosity of alum
coagulation flocs - results of anaiysis of variance .............................................. . 160
Sierpinski fracta1 dimensions (S.Fo. , S.FI. and S.F2.) for alum coagulation flocs
results of analysis of variance ...................... ........ . ..................................... . 1 6 1
Effects of m k h g intensity on the size of activated sludge flocs - results of analysis
of variance ......... . .......... ...... *... ... ................................................................ *.. ...... 1 62
Effects of floc size and mixing energy input on the geometric porosity of activated
sludge flocs - results of analysis of variance ........................................................ 163
Effects of sonic energy input on the size of activated sludge flocs - results of
analysis of variance ...................................... .. ................................................... . 164
Effects of floc size and sonic energy input on the geometric porosity of activated
sludge flocs - results of analysis of variance ......................... .. ........ . .............. 165
Appendix 10 Effects of the sonic energy input on the osciilation amplitude of the activated
sludge - results of analysis of variance ..................................... . . . . .............. 166
Appendix 11 Effects of image analysis software (Global Lab Image vs. Bioquant IV) on the
value of the geometric porcsity - results of analysis of variance .......................... 167
xii
A - cross-sectional area of the floc [m'] a - matment effect size [ml a,, - diameter of primary particle in the aggregate[m] a, K, - floc deasity function constants p - floc hydrauIic diameter B - floc binding force FJ1 c - strength constant C - substrate concentration [rng/L] CD - drag coefficient exened on an impermeable sphere cs, n, - strength parameters as determined in sonication experiments D - floc dimeter Dr - diffusion coefficient [m'ls] d - three-dimensional fracta1 dimension d2 - two-dimensional fracta1 dimension Dl - equivalent diameter measured on thin sections of flocs [pm] Dz - equivalent diarneter measured on flocs embedded in agar [ p l D3 - equivalent diameter measured on flocs photographed during settling [pl Djg - floc diameter such that 50% of aggregates population has diametet [pm] kup - diarneter of flocs aAer breakup. D* - floc drainage diameter E - energy dissipation rate, loss of energy per unit volume of liquid or mass of suspended soIids F - hydrodynamic force exened on a floc FC] FD - drag force IN] g - gravitational acceleration [m/s2] G - Iiquid velocity gradient [Ils]. k - floc permeability [m'] K - Carman constant KI - coefficient k, - substrate uptake rate consmt kl - sludge settling model constant Kr - turbulent drag coefficient & - shape correction factor. L - characteristic length of an aggregate m - dope of a data line on Sierpinski plot Mf -mas of a floc [kg] Ms - mass of solids in the floc kg] MW - mass of water in the floc [kg] n - floc size coefficient nl - sludge settling model constant N - number of primary particles in the aggregate N(L) - number of primary particle in the aggregate N(r) - number of reduced versions of an object required to completely cover the object p - perimeter of a floc section [ pn] P - power input PK] p(D) - pressure difference on the opposite rides of a flocs m/m' ] PI - total area of pores lfioc area ratio as determined by Global Lab Image software (hole ratio) [%] Pz - porosity of a rectangular window pIaced within floc section [%] Pj - was determined like Porosity 2, but pores larger than 10 pin2 in a cross-sectionai area were excluded [%] P4 - was determined like Porosity 2, but pores smailer than 10 pn' in a cross-sectional area were excluded [%] Ps - effective stress ~ l r n ' ] .q - flow rate through a floc [pm3/s]
r*' - contraction ratioSr - floc surface area [m2] S - pore specific surface area [ llm1S.F. - Sierpinski fiactal dimension V - volume of an aggregate [m3]. V - flocculator volume [m3] u - intrafloc Iiquid velocity [ d s j vl, v2 - liquid velocities at points separated h m each other by distance D [Ws]
v, - volume of primary particles [ml] v, - terminal settling velocity [Ws] Vzs - zone setrling velocity of sludge solid liquid interface [ d s ] W - dry weight of an aggregate [kg] x- diffusion path length [ml E - maSs porosity of a floc (void volume ratio) [%] R - drag force correction factor & - scale of turbulence (site of eddy) [ml p - liquid viscosity Fg/m/s] v - kinemaric viscosity [m2/s] o - floc mean binding mength ~ l r n ' ] pf, pw. ps - density of a floc. water and dry solid respectively [g,/cm3] (pf-pw) -effective density of a floc wc/cm3]
1. INTRODUCTION
1. f Background
Knowledge of floc permeability is the basis for the study of mass tramfer in the floc. In an
activated sludge floc mass is transported by advection and diffusion (Li and Ganczarczyk, 1988:
Li and Ganczarczyk, 1992). Logan and Hunt (1988) used the following equation to descnbe
the steady-state transport of substrate inside a porous aggregate:
UC - D~ dc2/dzx = -ksC
Where
u - intrafloc liquid velocity [ d s ]
Equation 1
C - m a s concentration [mg&]
k, - mass uptake rate constant
x - distance over which diffusion occurs usually assumed to be the size of a floc [pl
D f- diffusion coefficient [mqs]
The advection term in Equation 1 requires estimation of the liquid velocity inside a floc. The
intra-aggregate liquid velocity is a function of floc permeability according to Darcy's law:
where
cihidl - hydraulic gradient
k - fioc permeability [m']
p - dynamic liquid viscosity @cg/m/s]
g - ww Ws21
p - liquid density @cg/m3]
Floc permeability affects sludge senling. Settling of sludge is described in ternis of solid
concentration and some parameten characteristic for the sludge (Ekama et al., 1997). For
activated sludge four concentration regions have been identified (Figure 1):
Region 1 - very low concentration region containhg non-senleable flocs
Region 2 - low concentration range where discrete sealing of individual tlocs is
usudly assumed
Region 3 - at this concentration range sludge settles independent of the concentration
Region 4 - settling rate of the sludge (Vzs) depends on the solid concentration (C). for
example:
Equation 3
Where ki, nl - constants characteristics for a particular sludge
Stokes law can describe settling of individual flocs (in region 2). The main difficulty in
applying Stokes' law stems from the problem in estimating the drag force acting on a porous
floc. Flow of Buid through the senling floc lowen the drag acting on tbe floc. Consequently,
highly permeable flocs settie faster than flocs with Iow permeability. In the zone settling
(region 4 on) the sludge is subjected to solid pressure lowered by the dynarnic pressure of fluid
draining kom the compacting sludge (Zheng and Bagley, 1999). Therefore, permeability and
dewatering properties of flocs detemine behaviour of sludges at the concentrations in the region
4. Although the physical properties of flocs are probably the most imporiant factors affecthg
sludge settling the exisMg secondary clarifier models do not recognize that importance.
Permeability of flocs is usually estimated using mathematicai models ( Table 1). Ail of
the expressions in Table 1 in are in the following form:
Equation 4
Where
h- diameter of primary particle in the floc aggregate [ml
Therefore, the porosity and the size of particles building the floc are required for estimation of an
aggregate's permeability. These parameters are determined by the structure of the specific type
of a floc. Considering the differences in chernical and biologicai fiocculation it is rather unlikely
that alum coagulation and activated sludge flocs have identical stnxctures. Yet permeability of
both inorganic and microbial aggregates were caicuiated assuming that the porosity and structure
of these flocs are the same.
Table 1 Floc permeability models (Lee et al., 1996)
-- - - -
Modef Primary particle shapc Pcnnea bilicy function Equation
Carman-Kozcny Spherc
Happe1 (or ceII rnodcl) Sphere
me symbol dF = primary particlc diametcr (m); 4 = -e = sotid fraction of flac; y = 4lJJ; So = spccific e a u ana of the primary particle = 6/dF ( rn- l ) ; Rc, = d,,pd/pe = the RcynoIds Number bascd on the primary partide and interna1 flow vclocity.
The concept of a multi-level floc structure has been presented in a nurnber of studies (Vold,
1 963 ; Lagvankar and Gemmell, 1 968; Forster and Dallas-Newton, 1 980; Eriksson and Hardin,
1984; Francois and Van Haute, 1985; Francois, 1987; Li and Ganczarczyk, 1990; Clark and
Flora, 199 1 ; Clark and Laine, 199 1 ; Eriksson and Ah, 199 1 ; Eriksson et al., 1992; Urbain et ai.,
1993; Jorand et al., 1995; Li and Logan, 1997). According to the multi-level mode1 of floc
formation in these studies, primary particles form compact flocculi. Flocculi, formed at the
highest shear, would be srnail, have a high resistance to shear and have small pores, fonned
between primary particles. Flocculi join themselves to form microflocs. These microflocs
would have a higher porosity than that of flocculi because of the possibility to form larger pores
(medium size pores) at the flocculi's boundary (illustrated in Figure 2). Microflocs then gather
together to form large, weak and highly porous floc aggregates containing small, medium, and
large pores. The large pores will be formed between the microflocs in the floc aggregate. The
three levels of aggregation structures (flocculi, microflocs and floc aggregates) wouid have a
different size, density, resistance to shear, and porosity. Although the porosity of flocs is clearly
non-homogeneous, most models for floc and biofilms assume that the porosity is constant
(Scuras et al.. 1998).
The porosity variations are especially important in relation to mass transfer, since any porosity
gradient will result in the rnass (substrate or oxygen) concentration gradients inside a floc.
The presence of three diflerent pore populations within a floc ma&, i.e. small, medium and
large pores. is a direct consequence of the muiti-level structure of a floc. Other floc
characteristics such as size or strength of floc cannot be used directly to indicate the multi-level
structure of aggregates. Several factors, besides structure, affect the size of flocs. For example,
the size of flocculi depends on the size and number of primary particles. Flocculi, microfiocs
and floc aggregates are formed at dBerent shear rates during the floccdation process. Floccuü
form during a fast mix, when the shear rate, defïned by liquid velocity gradient, is the highest,
whereas floc aggregates are present when the shear rate is low. The three different levels of
aggregation - flocculi, microflocs and floc aggregate have different resistance to shear or
strength. The strength of flocs c m be deterrnined from the relationship between the floc size and
the mixing energy input in the flocculatioa experiment. However, this energy input varies with
time and location within the floccuiation vesse1 and the local mixing enerw input which is the
factor controlling the size of flocs, is difficult to measure.
In this study, the porosity of a alum coagulation and activated sludge flocs was investigated.
The characteristic sizes of pores in these aggregates were anaiyzed to support conclusions
pertaining to the specific structure of the aggregates studied.
Figure 2 Multi-level mode1 of floc formation (Li and Logan, 1997).
1.2 Objectives
The objectives of this study were to determine the porosity of alum coagulation and
activated sludge flocs and investigate the possibility of using porosity as an indicator of structure
of these aggregates. To reach these objectives two issues needed to be addressed. First, an
experimental method for deteminhg the pomsity of flocs had to be developed. Second,
appropriate methods for analyzing data and cornparing the porosity of severai highly random floc
populations had to be identified. For clarity and consistency, the term floc in this thesis refers to
a particle aggregate both in alurn coagulation and an activated sludge process, unless othewise
indicated.
1.3 Rationale
The porosity of flocs caiculated using a simple mass balance equation is referred to as
mass porosity (E) in this thesis (Tambo and Hozumi, 1979; Klimpel and Hogg, 1986; Li and
Ganczarczyk, 1987; Wong, 1992; Ganczarczyk. 1995). The mass porosity (s) is calculated from
the density of flocs. This density is usually estimated by applying Stokes' law to descnbe the
senling of aggregates. Stokes' law cannot be applied directly to descnbe the settling of a floc
because the drag force acting on a floc is difficult to estimate. In early hidies the drag force
acting on a floc was described using an expression for drag on an impermeable sphere. Since
flocs are permeable and their shape is usually far fiom spherical, several corrective factors in the
expression for the drag force were proposed. In Chapter 2.1.1 a more detailed discussion of the
correction factors applied to Stokes' law is presented. Yet Stokes' law failed to predict the
settling velocity of flocs accurately even after these correction factors were applied (Johnson et
ai., 1995). All of the proposed correction factors for the drag require an estimate of floc
penneability. It is quite possible that the calculated corrections to Stokes' Law were inadequate
because of erroneous estimates of floc permeability. Consequently, the density of flocs
calculated according to Stokes' law was underestimated, thus the porosity calculated in this
method was overestimated.
The porosity of flocs was dsc? measured on thin sections of the aggregates (Li and
Ganczarczyk, 1990; Rizzi, 1993; Ganczarc y k and Rizzi, 1996; Guzowska, 1996; Lay, 1997;
Cousin, 1998). The porosity detemined microscopically is referred to as geometric porosity (P)
in this thesis. The geometric porosity (P) is calculated as the ratio of the area occupied by pores
in a floc section to the total cross-sectional area of the floc.
The geometric porosity (P) appears to be more realistic since it provides direct Somation about
the presence of the liquid phase in the biornass. Only microscopie analysis of the geometric
porosity (P) of flocs allows for an investigation of detailed characteristics of the pores, such as
their number. shape and size.
Determining the geometric porosity of flocs in experiments is difficult because of the
complexity of sampling and data analysis. Unlike the model aggregate, flocs are random
assemblages of flocculi, microflocs and floc aggregates. Because of this randomness, variable
porosity values for flocs of the same size cm be expected. Considering the multi-level modei of
a floc, it seems appropriate to assume that the porosity of a floc is non-homogeneous and varies
with the size of the aggregate. It is important to remember that the sizes of aggregates within the
population may Vary by a factor of 1000. Therefore, since so many factors affect the porosity of
flocs, it is naniral to expect significant random noise in experimental data descnbing such
porosity. Yet in spite of the natural randomness of floc characteristics almost all early reports
on geornetric porosity (P) were based on the measurements of either a single floc or no more
than five. The flocs were individ~ally handpicked for resin stabilization, and therefore oniy
large, easily visible aggregates were likely to be analyzed. Thus almost no information is
available on the geometnc porosity of small flocs (equivalent diameter <100 p), although these
smdl aggregates constitute a majority of the su~pended solids. Moreover, al1 previous studies
described porosity of a floc in terrns of a total average porosity of an aggregate oniy. It is
appropriate to use the average Dorosity to estimate floc permeability provided al1 pores within the
aggregate facilitate intemal flow. In cases where the flow occurs only through some pores in the
floc, permeability of an aggregate calculated based on the total average porosity will be
overestirnated.
1.4 Structure of the Thesis
To identi@ an experimental method with which the porosity of flocs' can be adequately
characterized a critical review of available methods and porosity data has been presented in
Chapter 2. A statinical design of sample size is presented in Chapter 3. In the same chapter the
experimental results detedning the porosity and structure of dum coagulation and activated
sludge flocs have been presented. In Chapter 4 the porosity and some other characteristics of
alum coagulation and activated sludge flocs were compared. Based on the experimentd results,
structural models were proposed for the two types of aggregates studied. In Chapter 5
conclusions fiom al1 analyses conducted in this thesis are summarized. Some ideas for future
studies on floc permeability are recommended and the engineering significance of the results is
emp hasized.
2. I Porosity and Structure of Alum Coagulation Flocs and Other lnorganic Aggregates
2.1.1 Mass Porosity (E)
Tambo and Watanabe (1979) detemillied the porosity of flocs obtained fiom alun
coagulation by using a simple mass balance equation:
Where Mf - mass of a floc
M, - mass of a solid material in the floc
M W - mass of water in the floc
Equation 5 cm be rewritten as:
E = (1 -(pf - pw)/(ps - pw)) x 100%
Equation 5
Equation 6
Where
E - m a s porosity of a floc
pf ,pw ,ps ,- density of a floc, water and dry solid respectively [g/m3].
The porosiy calculated with Equation 6 is referred to as mass porosity (sj. Clearly,
determination of mass porosity depends on the precise estimate of the density of a floc.
Various methods have been proposed for measuring floc density, such as linear-density stiatified
column (or isopycnic centrifugation) (Ozturgut and Lavelle, 1984; Dammel and Schroeder,
11
199 1 ; Knocke et al., 1993), interference microscopy (Andreadakis, 1 993) and the free settling
test. Of these methods, the fiee settling test has been the most widely cited method in literature.
In this test, the effective density (pf - h) of flocs is e h a t e d by applying modified Stokes' law
(Equation 7) to the settling velocity of individual particles. The floc settling velocity is
determined by measuring, fiorn photographs, the floc travelling distance during the course of
fiee senling and recordhg the correspondhg time (Figure 3).
where
v, - teminal settling velocity [m/s]
CD - drag coefficient exerted on an impermeable sp
g - gravitational acceleration [m/s2]
D- diameter of settiing particle [ml
pf - pw -effective density of a floc kg/m3]
R - drag force correction factor
Ksh - shape correction factor.
Equation 7
Tambo and Watanabe (1979) calculated the mass porosity of alum flocs by determinhg their
density in the settling test. The specific mass porosity values were not listed in the article.
The modified Stokes' Law does not adequately describe the settling of particle
aggregates, and this limitation stems primarily from the difficulty in estimating the drag force
acting on the floc. The drag force exerted on a floc can be stated as:
Mere
v - floc settling velocity [mls]
FD - drag force EN]
Equation 8
51 - ratio of drag resistance expenenced by a floc to that of an equivaient solid sphere
Under creeping flow conditions (Recl), CD for a nonporous sphere is govemed by the inversely
proportional relationship:
CD = 24Re Equation 9
Neale et al. (1 973) theoretically anaiyzed settling of highly porous spheres moving steadily
through an infinite medium. Brinkman's extension of Darcy's Law was used to describe flow
inside of a floc and Stokes' Law described velocity of fluid around the floc. A theoretical
equation for R was obtained by comparing calculated settling velocity of a permeable sphere to
that of an impermeable one:
Equation 10
Equation 11
k - floc permeability [m2]
For a porous sphere moving steadily through an infinite medium at R s l O , the corresponding
drag force would be less than that for a non-porous sphere. The velocity of the fluid (and the
h g ) 3t the porous floc surface will be smdler than the velocity at the surface of the solid
sphere. This is because the permeation velocity lowes the liquid velocity at the surface of a
porous floc.
Tne setiling velocities of porous particles made of steel wool (Matsumoto and Suganuma.
1977) and semi-rigid plastic (Masliyah and Polikar, 1980) were found to correlate well with the
theoretical predictions of Equztion 7,8 and 9. However, the settling rates of a variety of particle
aggregates could not be predicted with these equations.
Johnson et al. (1 995) studied the settiing properties of latex microspheres coagulated
with NaCl. The sedimentation rates of these aggregates were on average 4 to 8.3 times higher
than those predicted with the modified Stokes' Law. It was concluded that the estimate of a drag
force acting on a floc was incorrect.
While discussing the feasibility of using a fiee-settling test for estimating floc density, Lee et al.
(1996) concluded that the drag coeficient employed must be the most influentid factor that
affects floc settling. Lee and Wu (1 998) numencally evaluated the hydrodyiiamic h g force
exerted on individual flocs.
Huang (1993) studied the properties of drillhg mud flocs, consisting primarily of clay
(bentonite) and other mineral parficles. The density of flocs calculated incorporaMg factor R in
the Stokes' Law was 17 to 38% higher than that calculated without this correction. Higher
density resulted in lower rnass porosity as calculated with Equation 6.
Pattyjohn and Christiansen (1948 ) studied the effects of different shapes of particles on
their settling velocity. Hongwei (1992) and Namer and Ganczarczyk (1 993) included the shape
correction factor in the Stokes' Law to calculate the density of activated and digested sludge
Bocs. They reported that an increase of shape factor to 1 .O (spherical form) induces a decrease in
the projected diameter of a particle aggregate and simultaneously decreases its temiinal velocity.
Therefore, ignoring the shape factor (Ksh) may lead to an underprediction of the floc density
fkom Equation 7.
Gorczyca (1 991) reported that the density of alun coagulation flocs calculated with
unmodified Stokes' Law varied fiom 1 .O22 to 1.45 1 @cm3 (equivalent to mass porosity of 98-
82%). Applying a shape factor correction resulted in an hcrease of the calculated density by 2 -
24 %.
Application of Equation 6 for estimation of mass porosity of flocs (E) always results in
overestimation of a floc's interior porosity. This is because the available methods for the
determination of the density of particle aggregates are not precise. For example. in the settling
test method. the drag acting on the settling floc has to be evaluated before density can be
calculated. Therefore, until a reliable method for determinhg the density of flocs is found. the
mass porosity of flocs (E) cannot be used to estirnate the intenor porosity of an aggregate.
2.1.2 Geornetric Porosity (P) of Alum Coagulation Flocs
Lay (1 997) detemiined the geometric porosity (P) of alun coagulation flocs by
examining the microtome sections of the aggregates. This geometric porosity (P) was calculated
as the ratio of the area occupied by the pores within the floc section to the total cross-sectiooal
area of the floc. In Table 2 the values for the average mass and geometnc porosity and size of
alum flocs are summarized. The average geometric porosity (P) for alum coagulation flocs was
reported to be about 40 %, which was approximately half of the mass porosity (E) of the same
flocs. The difference between the mass (e) and geometxic porosity (P) could be due to the
presence of aluminium hydroxide precipitate within the floc. The density of aluminium
hydroxide is much smaller than the density of the primary particles suspended in raw water.
Because of this low density of alun precipitates, when Equation 5 is used, the mass of
aluminium hydroxide is considered as mass of water.
Another problem encountered when comparing mass porosity (E) with geometric porosity
(P) is that the two types of porosity were measured for different floc sizes. Mass porosity (E)
was detexmined for fairly large flocs, whereas geometric porosity (P) was measured on much
smaller aggregates (Table 2). Also. many more data are available on the mass porosity of flocs
than for geometrk porosity of the aggregates. Because the experimental procedure was not
adequately developed, the average geometric porosity (P) of alum coagulation flocs reported in
the past was based on a total of about 5 measurements only. The average mass porosity value
was calculated based on measurements of about 60 flocs.
Table 2 Porosity of alum coagulation flues
SOURCE
flocs formed in coagulation of four di fferent niineral suspensions (Gorczyca, 199 1 )
measurement on four different ihin seciions (Lay, 1997)
EQUIVALENT DIAMETERS RANGE
(rneasured on flocs photographed during
settling )
N.A.
AVERAGE MASS POROSITY
(calculated h m settling velocity of flocs)
-
EQUIVALENT DIAMETERS RANGE
(measured on thin sections of Ilocs)
--
AVERAGE GEOMETRIC
POROSITY (measured on thin sections af flocs)
N.A.
EQUIVALENT DIAMETERS
RANCE- (measured on flocs embedded in agar)
N.A.
2.1 -3 Porosity and Structure of Alum and Other lnorganic Flocs
It is thought that alun coagulation flocs possess a multi-level structure (Francois and Van
Haute, 1985; Francois, 1987; Clark and Flora, 199 1 ; Clark and Laine, 199 1). Considering the
floc formation mode1 illustrated in Figure 2, it seems reasonable to asnune that the porosity of a
floc depends on its size. The relationship between the mass porosity (E) and the size of alum
and other inorganic flocs has been investigated before. Tambo and Watanabe (1 979) found that
an increase in mass porosity of alum coagulation floc was proportional to an increaçe in the
floc's diameter. Klimpel and Hogg (1 985) obtained the mass porosity (E)-size relationship for
polyacrylamide flocs and split the c w e into three regions 1, II and III. Region 1 represented
smdl. low-porosity flocs, perhaps flocculi. These small compact flocs would then act as the
basic unit for the subsequent growth of the larger flocs in Region II, perhaps rnicroflocs. Region
III was characterized by large (d>200 pm ), highly porous aggregates, perhaps floc aggregates .
Gorczyca ( 199 1) observed a similar relationship between an alun coagulation floc size and
porosity, but due to expenmental limitations. Region 1, which represented smail flocs, was not
O bserved (Figure 4).
The relationship between the geometnc porosity (P) and the size of flocs has never been
explored because of scarcity of data The existing geometric porosity data (Lay, 1997) for alun
coagulation flocs are hadequate to formulate a relationship (Table 2).
Figure 4 Relstionsliip behveen mass porosity and sizc of flues
O 0.2 0.4 0.6 0.8 1 1.2
EQUIVALENT CIRCULAR DIAMETER (mm)
ACTIVATIXI SLUDGE FLOCS (Li and Ganczarczyk, 1987)
L~I~--- 400 0.2 0.4 0.b 0.8 1 1.2 1.4
LONGEST DIMENSION (mm)
2.2 Porosity and Structure of Activated Sludge Flocs and Other Biologîcal Aggregafes
2.2.1 Mass Porosity (E) of Activated Sludge Flocs
Several researchers have determined the density of activated sludge flocs by applying
Stokes' Law to the settiing velocity of these agregates (Li and Ganczarczyk. 1987: Wong.
1992; Ganczarczyk, 1995; Ganczarczyk and Rizzi. 1996). Hongwei (1 992) calculated the
density of activated sludge flocs by using a modified version of Stokes' Law and reported that
the density varied fiom 1 .O9 to 1.002 g/m3. The average m a s porosity (c) for activated sludge
flocs caiculated fiom the floc's density by using Equation 6 ranged from 43 to 99%.
Alldredge and Gotschaik (1988) studied the settiing properties of marine snow
aggregates. These aggregates consist of diatorns. bacteria, faecai pellets. and nearly al1 types of
organic and inoqanic matter present in the ocean. Alldredge and Gotschalk (1988) also used a
m a s balance equation (Equation 12) to determine the porosity of aggregates:
porosity = 1 - W b f v
where
W - dry weight of an aggregate @cg]
Equation 13
p f - density of solid hydrated matter within the aggregate Fglrn']
V - volume of an aggregate [m3].
The floc density (pr) was caiculated by applying Stokes' Law to the sinking rates of zooplankton
faecal pellets. These pellets contain a representation of many of the types of particles found also
21
in marine snow. The porosity of marine snow aggregates calculated with Equation 12 were
higher than 99%.
By using Equation 13 , Logan and Wilkinson (1 99 1) calculated the porosity of the
aggregates of Zoogloeo ramigera and Succharomyces cerevisae:
Equation 1 1
Where
N - number of pnmary particles within an aggregate
Vo - volume of pnmary particles [mJ]
Flocs were dispersed enzymatically with cellulase to determine the number of primary particles
within individuai aggregates (N). The porosity of microbial aggregates in Logan and Wilkinson's
study varied from 97 to 99%.
2.2.2 Geometrk Porostty (P) of Activated Sludge Flocs and Biofilms
Severai researchers have measured the geometric porosity of activated sludge flocs (P)
(Li and Ganczarczyk. 1990; Rizzi, 1993; Ganczarc y k and Rizzi. 1996; Guzowska, 1996:
Cousin. 1998; Cousin and Ganczarczyk. 1998). The reported average geometric porosity of
activated sludge flocs varied fiom 9 to 60% (Table 3).
One of the reasons for the large difference between the mass porosity (E) and geometric porosity
(P) of the activated sludge flocs is the presence of extracellular polymers within the floc matrix.
The density of bacterial cells ranges fiom 1 -02 to 1.10 g/mL, but the density of extracellular
material may be only slightly higher than the density of the liquid phase of the wastewater. In
the mass porosity estimation (Equation 5 and Equation 6), the mass of extracellular polymer may
be considered entirely as a mass of liquid because of its low density. Yet extracellular polymer
may represent up to 30% of total sludge volume.
Equation I I , used I?y Logan and Wilkinson (1 991) to estimate the aggregates' porosip,
clearly does not consider the presence of extracellular matenal within floc. Moreover. the
equation is based on a precise determination of the number of primary particles within the
aggregate by floc dispersion. The two mechanisms of floc dispersion suggested in literature are
floc fragmentation and floc erosion. In the fragmentation process. flocs disperse into microflocs
and fiocculi before being dispeaed into primary particles. In the erosion process, the graduai
release of individual primary particles frorn the aggregate matrix occurs. Therefore. in either
floc breakup mechanism assumed - fragmentation or erosion. flocs do not immediately disperse
into pnmary particles. Therefore. the number of primary particles determined by floc dispersion
may be underestimated. thus resulting in an overestimation of porosity.
In Table 3. the information available on the porosity of activated sludge flocs is
summarized. It is important to note that the reported mass porosity averages were based on
rneasurements of 60-1 00 flocs. whereas the geometric porosity data. excepting the work by
Cousin and Ganczarczyk (1 998), are based on measurements of a single or up to maximum of
10 flocs. The reported geometric porosity of activated sludge flocs varied fiom 9 - 66 %.
Biofilrns and activated sludge flocs are similar foms of rnicrobiai aggregation
(Ganczarcyk, 1996). Since biofilms have received more detailed study than activated sludge
flocs more information regarding the porosity and intemal flow is available for biofilms in the
literature. The reported geometric porosity of biofilms was relatively low ranged fiom 4 - 32 %
(Zahid and Ganczarczyk, 1994) suggesting that biofilms form more compact structures than
activated sludge flocs.
Table 3 Porosity of activated sludgo flocs -- - -
EQUIVALENT DIAMETERS RANCE
(measured on fiocs photographed during
settling)
-- - .
AVERAGE MASS POROSITY
(calculated fram settling velocity of
flocs)
- -
EQUIVALENT DIAMETERS RANCE
(measured on thin section of flocs)
EQUIVALENT DIAMETERS
RANCE- (measured on fïocs embedded in agar)
P z ) 1Pl
SOURCE AVERACE CEOMETRIC
POROSITY (measured on lhin sections of flocs)
act ivated sludge flocs ficiin the laboratary scale reactor (Li and Ganczarczyk, 1987; Li and Ganczarczyk, IWO)
activated sludgc flocs from the laboratory scalc reactor ( Wong, 1 992)
activated sludge flocs conditioned with varioiis dosages of polymer: 0, O S , 1,2 mUL)
(tdangwei, 1992; R ia i , 1993; Ganczarczyk and Rizzi, 1996)
- - - -
150 - 1 O00 and up (longest dimension)
activated sludge flocs from the full scale plant (Guzowska, 1996)
N.A. N.A.
Activated sludge flocs
At differeni salinity levels
(Cousin, 1998)
N.A.
2.2.3 Porosity and Structure of Activated Sludge and Other Biological Çlocs
Biological flocs are believed to possess a three-level structure (Forster and Dallas-
Newton, 1980; Eriksson and Hardin, 1984; Li and Ganczarczyk, 1990; Eriksson and Alm, 199 1 ;
Eriksson et al., 1992; Urbain et al., 1993; Jorand et al.. 1995; Zartarian et al., 1995; Snidaro et
al., 1997) . Misraorganisms (~hûse size is approximately 1 pi) foiin niicrocolonies about 2 - 4
pn in diameter. Microcolonies form flocculi whose sizes range from 13 to 30 p. The flocculi
build rnicroflocs whose average size may range from 50 to 125 pm (Jorand et al.. 1995). The
structure of activated sludge flocs is non-uniforni, and primas, particles, flocculi. as well as
microflocs. are randornly distnbuted within floc aggregates (Li and Ganczarczyk. 1990).
(Ganczarczyk, 1996) demonstrated that both biological films and activated sludge floc possess a
discontinuous structure. Sloughing particles fkom biological films often resemble activated
sludge flocs. Beer and Stoodley (1995) estimated the size of ce11 clusten in biofilms to Vary
fiom 200 - 300 p. This size range corresponds to the size of activated sludge flocs.
Ganczarczyk (1 996) estimated the size of microbial clusters (representative of flocculi) in both
microbial flocs and biofilms to Vary from 6 - 12 pm.
The relationship between the mass porosity and the size of microbial flocs has been
investigated before. An increase in the mass porosity (E) of activated sludge flocs' corresponded
to an increase of the flocs' longest dimensions. This increase was large for flocs with longest
dimension less than 200 microns. For larger activated sludge flocs the porosity wa? hi& (>90%)
and did not Vary much with the floc size (Figure 4). Alldredp and Gotschalk (1 988) reported
the relationship between the size and mass porosity for marine mow flocs to be a straight line on
a log - log scale.
2.3 Penneability of Flocs
Knowledge of floc permeability is required to estimate the rate of flow through flocs.
Evaluation of floc permeability is usually based on permeability modeis in Table 1. For
example, Li and Ganczarczyk (1992) used the following form of the Carman-Kozeny equation
to estimate permeability of activated sludge flocs:
k = (& 1 1 0.6) (g31( 1 -E)' ) Equation 14
Where
a - diameter of wet particle inside a floc [ml
Lee et al. (1 996) reported that the two parameters - porosity and a size of wetted particle
inside a floc. required to estimate permeability of a floc. are not simultaneously available.
Depending on the mode1 used to relate porosity to penneability as well as the selection of
parameters related to floc structure. the permeability of flocs can Vary by two to three orders of
magnitude.
Wu et al. (1998) determined the permeability of activated sludge flocs by observing the
motion of an individual floc moving towards an impermeable plate. When a particle was
approaching the plate the hydrodynarnic drag would increase because the fluid in the gap
between the particle and the plane was repelled radially. Consequently as the particle
approaches the plate its settling velocity was reduced. For a porous floc such reduction in settling
velocity will be smaller than for impermeable particle, because of the possibility of flow of fluid
through the floc. The reduction in senling velocity of individual flocs can be related to the drag
correction R. Experimentally determhed R values were compared with analyticaily predicted C2
for the test conditions. From such comparisons, hydraulic diameter (P) and therefore,
permeability of activated sludge flocs was calculated. Wu et al. (1998) reported that the
permeability of activated sludge flocs varied fiom 0.7 - 5 * 10 -7 m2. It is important to note that
in this experimental determination of floc permeability none of the models presented in Table 1
was used. However, Wu et al. (1 998) reported that their experimental data could be fitted by the
Carrnan-Kozeny equation assuming the cluster diameter (3 of 20 pn and fioc porosity of 90%.
No literature data is available in the permeability of alum coagulation flocs.
2.4 Flow Through SetHing Flocs
According to Darcy's Law, the flow velocity through any porous medium is detemiined by
the permeability of that medium:
Where
u - intrafloc velocity [mls]
cih/dl - hydraulic gradient
Equation 15
Adler (198 1) developed the following equation to estirnate the flow velocity inside a settling
floc:
Where V - floc settling velocity [m/s]
D* - drainage radius
D* = @/2)(1-WB - c/p3) Os
Equation 16
Where
b = (315) ~'(l-tanh W B )
c = (- I /j)[pS+6 p3- (tanh(p)/p)(3 ps +6p3)]
J = 3p2+ 3 - 3 tanh (P)/p
P = D/(2(k) 0q5)
Flow rate (q) through a floc can be calculated as:
q=v * 2 n ( ~ * ) '
Logan and Hunt (1 987) used Davies permeability
Equation 18
mode1 (Table 1) and the above
equations to estimate the intrafloc velocity in microbial and organic flocs (Figure 5 ) .
Figure 5 Intra-aggregate fluid velocities for settling and sheared aggregates (Logan and Hunt, 1987)
FLOC
- - -
FLOC
. -
AGGREGATE RADIUS prn
2.5 Fractal Geometry and Porosity of Flocs
In actual turbulent suspensions, flocs form as a resuit of rmdom collisions of primary
particles, flocculi and microflocs. Therefore, unlike in the mode1 floc (illustrated in Figure 2) the
structure of a real floc is a random assembly of al1 levels of aggregation. Random processes tend
to create hc t a l objects. Several researchea demonstrated that particle aggregates. formed in
water and wastewater treaunenr, possess frac tai features (Li and Gmczarcq k i 9 89; Kzzi, 1 993 ;
Gorczyca and Ganczarczyk, 1995; Guzowska, 1996; Lee et al.. 1996; Bahrami, 1997; Lay, 1997:
Cousin, 1998; Cousin and Ganczarczyk, 1998; Lee and Wu, 1998; Gorczyca and Ganczarczyk,
1999). M e r organic and inorganic aggregates, such as marine snow, aggregates formed in pure
microbial cultures and flocs foxmed in coagulation of glas beads were also found to possess
hc ta l qualities (Jiang and Logan, 199 1 ; Logan and Wilkinson, 199 1 ; Kilps et al., 1994; Logan
and Kilps. 1995; Li and Logan, 1997).
Fractal objects are so irregular and disordered that it is often impossible to describe them
in the terms of classical mathematics. Spatially disordered systems, however, can be analyzed
using concepts of fiactal geometry (Mandelbrot, 1983). in the hc t a l theory, an irregular
geometric form is considered a transition between two Euclidean forms. For example, a rugged
curve can be descnbed as a form located somewhere between a smooth curve and a plane. The
hc ta l dimension (d) that lies between the two Euclidean dimensions characterizes this
transitional nature. This is similar to the concept that a line can be considered a geometric object
between a point and a plane. Its dimension possesses a value between those of a point
(Euclidean dimension of 0) and a plane (Euclidean dimension of 2). Fractal dimension extends
the traditional concepts of dimensions by including the Euclidean dimensions as a special case.
To get an intuitive feeling for h c t a l dimension one can start with a standard object such as a
segment, square or cube. Such an object can be covered by N(r) reduced venions of itself,
where r is the contraction ratio, as illustrated in Figure 6 a). For these simple objects (Adler,
1992):
Equation 19
Where
N(r) - number of reduced versions of an object
l/r - cmtmction ratio
d - fracta1 dimension of an object
In Equation 19 (d) is the usual spatial dimension of an object:
d = ln??J(r) An( 1 /r) Equation 20
A Cantor set is an example of a hctal object. It is constnicted by dividing a segment into three
equai size segments and removing the middle portion of the segment (Figure 6 b). The fiactal
dimension for the Cantor set depicted in Figure 6 can be calculated as ln(2)/ln(3) ( Equation 20).
Equation 19 is equivalent to Equation 2 1, which has been widely used to determine the fractal
dimension of flocs:
Equation 2 1
Where
N(L) - number of primary particies within a floc
L - characteristic length of a floc
d - three-dimensional hc ta l dimension of the floc
The mass of a particle aggregate is proportional to the number of the primary particies building
that aggregate. Therefore, Equation 2 1 is equivalent to:
MdL) - L~ Equation 27
It should be noted here that the term mass in Equation 22 is used in a very loose sense, since it
may dso denote the length. surface or volume of an aggregate. For exarnple. Logan and
Wilkinson (1 99 1) proposed to use the floc area-length relationship to determine a two-
dimensional bct ; i l dimension:
Equation 23
Where
d2 - is a two-dimensional fractal dimension.
For classincation and cornparison of hc t a l dimensions, it is important to note the equation and
parameters used in their calcdations.
Porous media may exhibit fracta1 features in three different ways (Adler, 1992). The pore
space, the solid phase, or the solid-pore interface can al1 be fiactal. Pore spaces of various
sandstones were found to have Factal properties (Katz and Thompson, 1985). Bayles et al.,
(1987) found that the solid-pore interface of the coal cake was also hctal . In the fractal analysis
of many porous materials, it is convenient to adopt a mode1 of the Sierpinski carpet (Sierpinski.
19 16: Mandelbrot, 1983). Examples of ideal Sierpinski carpets constmcted with different
algorithms are presented in Figure 7.
Fractal dimensions of the Sierpinski carpet are calculated fiom plots of an individual pore
area (trema) against the solid fraction of the carpet (residual area) as illustrated in Figure 8.
A Sierpinski fiactal dimension is defmed as (Kaye, 1989):
Equation 24
Where
SF - Sierpinski Fractal dimension
m- slope of a relationship between normalized pore size and normalized
solid fraction on logarithmic scale
The Sierpinski fracta1 dimension indicates how the measured solid fraction (or porosity) of the
carpet changes with the change of the minimum visible size of pore (microscope resolution).
For the ideal carpet depicted in Figure 7. this rate is constant and a Sierpinski plot shows a single
straight line. The value of Sierpinski dimension (and dope of the data line on the plot) depends
on the method of construction of the carpet Figure 8. For a porous media built with two different
Sierpinski carpets there will be two data lines on the Sierpinski plot (Figure 8). The breakpoint
in the data line (transition pore - T.P.), indicates the size of pores dividing the two structures
building the porous materid.
Several researchen used the Sierpinski carpet mode1 to characterize pores present in
biofilms and activated sludge flocs (Rini, 1993; Zahid and Ganczarcqk, 1994; Guzowska,
1996; Bahrami, 1997; Lay, 1997; Cousin, 1998). For activated sludge flocs and biofilms,
Sierpinski plots indicate the presence of two distinctively different lines and therefore, two
Sierpinski fracta1 dimensions. The first line (Sierpinski hctal dimension - S.FI-) descnbes the
population of small pores. The other line (Sierpinski h c t a l dimension - S.F2.) refers to the
population of large pores. The transition pore area in Figure 9 corresponds to the equivalent
diarneter of pore equal to 25 p.
Fractal models have also been used to predict the permeability of porous media. Adler.
(1986) estimated the theoretical permeability of the Sierpinski carpet and found it similar to the
permeability calculated with semi-empincal Carman-Kozeny equation. Based on Adler's
fmdings, Li and Ganczarczyk (1992) estimated permeability of activated sludge flocs with the
Carman-Kozeny equation.
Experimental evidence shows that porous materials ofken possess a hctal structure. This
evidence has to be contrasted with the classical image of porous media, which is usually
considered to be homogenous. Fractal analysis can be especially useful for investigating
materials with the non-homogeneous porosity such as flocs.
Figure 9 Sierpinski plot for the biofilms formed in Rotating Biological Contacton (Zahid and Gaoczarczyk, 1994).
1 E-5 1 €04 1 E-3 0.01
Normaiized resolved trema
2.5.1 Peneability of Sierpinski Carpet
Adler (1986) used the Carman-Kozeny equation to calculate permeability of an ideai
square Sierpinski carpet depicted in Figure 7. He suggested the following form of the Carman-
Kozeny equation:
Equation 25
k* - dimensionless permeability k*= klII2
b' - number of subsquares in the carpet
1' - number of subsquares removed in the carpet
N - the construction stage
It is important to note that Equation 25 requires information on the geometry of the carpet only
and does not include the porosity tem.
2.6 The Pomsity of FIocs and Their Resistance to Shear
Flocs have to be dispersed into hgments built with lower Ievel of aggregation stnicntres
in order to snidy the non-homogeneity of the floc porosity. The presence of voids in a structure
lowers the strength of a matenal. It is reasonable, therefore, to expect a large highly porous floc
aggregate ro be less mistant to shear than a small microfloc with lower porosity. nius the
porosity, size and strength of a floc must be interrelated. Of these three floc properties, the size
can be determined rather easily.
On the other hand, the strength of a floc cannot be detemined directly, and other floc
characteristics (usually the size) are used to indicate the aggregates' strength.
In this chapter. theoretical and experimental equations obtained in studies determining the
strength of Bocs are reviewed. Special attention is given to those equations describing the
strength of flocs that include porosity and size of the aggregate as parameters.
The theory of the breakup of particles in a turbulent liquid flow is based on the
assumption of homogeneous and isotropic turbulence (Komolgorov, 1949; Levich. 1962). A
distinguishing feature of turbulent regime is the chaotic and unsteady nature of the motion of
fluid particles. Therefore, the theory of turbulent flow is statistical in nature. Turbulent eddies
are characterized by their velocities, and by the distances over which these velocities change.
These distances are also called scale of turbulence, or size of an eddy. In the turbulent
suspensions there are two types of eddy: large and small. Large eddies contain the main part of
the kinetic energy of turbulent motion and are responsible for distribution of this energy
throughout the vessel. The size range of these eddies is called inertial convection range. The
mal1 eddies dissipate energy, therefore are directly involved in floc breakup. The size range of
smdl eddies is called a viscous dissipation range. The Komolgorov microscale 5 divides these
two size ranges.
An aggregate would break up if the hydrodynamic stress acting on it exceeds the flocs'
strength. Floc strength is therefore defmed by the critenon for rupture:
Where
F - hydrodynamic force exerted on a floc N
p(D) - the difference in the dynamic pressure impressed on the opposite
sides of a floc of the diameter D w/rn2 1
S - floc surface area [m' ]
B - floc binding force IN]
The pressure difference acting on a floc is a function of the change of the liquid velocity
dong the distance equd to floc diameter:
Where
Kr - turbulent drag coefficient. Kf =1/2 CD
VI' v2 - liquid velocities at points separated fiom each other by distance D,
Le. floc diameter [ d s ]
Equation 27
The change in liquid velocity over a region of length D is defined as the eddy velocity vd.
According to the theory of turbulence the eddy velocity is described by the following formula:
Where
v- linernatic iiscosiv, Y = $p, [m' !SI
f - universal function such that:
f (D/h, )- (Dlh, )' if D<h,
(viscous range)
f @IL, )-(Dlh, )m if D>h,
(inertid convection range)
Equation 28
Equation 29
Equation 30
Equation 3 1
Where
Lo - scde of turbulence (size of eddy) [ml
E - energy dissipation rate, i.e. loss of energy per unit volume of liquid [ ~ l r n ~ ]
Mer incorporating Equation 29 - 30 into Equation 28, the following expressions for relative
liquid velocities could be obtained:
Equation 32
Equation 33
Equation 27 (after substituthg Equation 32 and 33) shows that floc diameter @ ) is a function
of the hydrodynamic pressure exerted on a floc, or floc binding strength (B). Therefore. the
strength of flocs is reflected by the size of aggregates that penist in a suspension.
Parker et al. (1972) used the theory of turbulence to derive a relationship for the
maximum stable diameter of a floc in turbulent suspensions:
Where
c - strength constant
n - floc size coefficient (n<O)
G - liquid velocity gradient [ I l s ] .
The liquid velocity gradient is defined as:
Equation 35
Where
p - liquid viscosity [kg/m/s]
P - power input [w V - flocculator volume [m3]
The relationship in Equation 34 has been confïrmed experimentally. Several researchers
reported that relationship on a loflog scale between the G value in the flocculator and the
average floc diameter in the suspension to be a h g h t line (Tomi and Bagster, 1975; Tomi and
Bagster, 1978; Levantaar and Rebhun, 1983).
44
Tambo and Hoc (1979) assumed the binding force of an aluminium hydroxide floc
(B) to be a product of the mean binding strength ((o) and the cross-sectional area of the floc - (A):
B=o A Equation 36
Where
A - cross-sectional area of the floc [m' ]
a - floc mean binding strength WlrnLI
For a floc diameter D and mass porosity (E), the floc volume can be estimated by:
V - D'( I -E)
From Equation 37 it follows:
Comparing Equation 27,32 and 33 with Equation 36 and 37 we obtain:
p (u~)D" - a ~ ' ( 1 - E ) ~ for Il<&-,
2 3 2 p (UpD) D - a ~ ~ ( 1 - s ) ~ for D>h,
Equation 37
Equation 38
Equation 39
Equation 40
It is important to note that the above equations contain the mass porosity (E) of a floc determined
£kom its effective density. The effective density when caiculated by applying Stokes' Law was
found to vary with the aggregate size, according to the following formula:
Equation 41
a Kp - floc density function constants.
The mass porosity (E) can be formulated in tems of effective density by incorporating Equation
41 into Equation 6. Then Equation 39 and 40 can be solved for the maximum floc size in a
suspension as a function of the energy dissipation rate:
D = c E ( J L ! ( ~ + K ~ P ' for D<h,
D = C E'-1 "1 for D>h,
Equation 42
Equation 43
Where
C - constant.
It is clear that Equation 42 and 43 resemble Equatîon 34. It is ais0 important to note that
Equation 43 and 43 contain parameter Kp. which is defined by the density of flocs. ïherefore.
the density of a floc (and mass porosiw) is expected to influence strength of the aggregate
(Bache et ai.. 1999).
Aluminium hydroxide flocs (diameter D) were ruptured by known velocity gradients.
The ruptured floc (diameter Dbrcakup) was allowed to re-grow again . The relationship on a
logflog scale between the G value in the flocculator and the average floc diameter in the
suspension was assumed to be a measure of floc strength (Francois and Van Haute, 1985;
Francois, 1987). An additional parameter related to floc strength was introduced:
strength factor = (D 1 Dbrdup )IO0 Equation 44
Where
D - initial diameter of flocs
Dbiealiup - diameter of flocs afkr breakup.
The strength factor was a measure of the sensitivity of a floc to an increase in the shear forces.
More than one strength factor was found for the same floc suspension. This indicated that the
structure of flocs was non-homogeneous, Francois (1 987) speculated, that different strength
values would be obtained, depending on the level of aggregation of the floc. The authors also
suggested that an alum floc aggregate had a four- level structure (primary particles - flocculi - rnicroflocs - floc aggregates).
Photographie observations of the disintegration of individual flocs upon interaction with
a turbulent jet were used to quanti& the binding force of kaolin-polymer and k a o l i n - ~ e ~ ~ ' ~
aggregates. The following experimental relationships between floc binding force (B) and size
@) were obtained by Glasgow and Hsu (1982) :
D = 0.33 B*.~* for kaolin-polymer flocs
D = 0.41 BO-"^ for kaolin-~e '"' flocs
Equation 45
Equation 46
The following relationships between floc size and the energy dissipation rate in a stined
tank were obtahed for activated sludge tlocs (Glasgow ec al.. 1983 j:
D-0.175 (E) O-*
D- 0.186 (E) ' . O 5
D-0.265
Equation 47
Equation 48
Equation 49
Direct observation of activated floc breakup indicated that biological flocs were typically
monger than clay-Fe -"' aggregates.
Acoustic energy can also be used to disperse flocs. In ultrasonic fields, acoustic energy is
converted into hydrodynamic energy. Since the disintegration of a particle in ultrasonic fields
occurs due to mechanical forces arising from liquid flows (Williams et al.. 1970; Doulah. 1977).
it was suspected that the particle breakup mechanisms might be similar to that in the mechanical
breakup.
King and Forster (1 990) r~ported the following conelation between the sonic power
level (Power) and the aggregate size for activated sludge flocs:
Equation 50
Where
Dso - floc diarneter such that 50% of aggregates population has diarneter
smaller than Dso [ml
Since the relationship behveen the size and sonic energy input is similar to the relationship
between the mechanicai energy input and tloc size, it was suggested thal the change of floc size
in sonication experiments could also be used to indicate the strength of flocs:
D = cs(Sonic Energy I n p ~ t ) ~ Equation 5 1
Where
CS. ns -strength parameters as detemined in sonication experiments.
By using Equation 5 1 . Morgan and Forster (1992) determined strength constants (CS) for
activated and digested sludge. It is important to note that below a certain acoustic energy input
(Emt) there was no significant change in the size of flocs observed (Morgan and Forster, 1997).
For example. Biggs and Lant (2000) reported that energy input of 36 k.Vg MLSS was required to
disperse activated sludge flocs into microcolonies. Sonication of activated sludge flocs not only
changed the size of these aggregates but also caused a release of polyrnenc material from the floc
(King and Forster. 1990: Q m b y and Forster. 1995).
Values for floc strength constants and size exponents obtained experimentally using
Equation 34 and 51 are presented in Table 4 and 5. It should be noted that the velocity gradient
(G) and sonic energy input. the main independent variables in Equation 34 and 51 have d.eren t
49
dimensions. Therefore, the strength parameters (c) obtained in mixing and sonication
experiments also have different dimensions and cannot be compared directly. To compare the
results, velocity gradients (G) have to be calculated fiom the power input in sonication
experiment. This c m only be done if sarnple volumes and viscosity of activated sludge used in
experiments are kno W.
Al1 the studies s m a r i z e d in this chapter indicate that the Hoc properties, namely
porosity, size and strength, are closely related. Therefore, white investigating porosity, attention
should be paid to changes in the size and resistance to shear of the aggregates studied.
Table 5 Strength parameters c and n for activated sludge flocs
INVESTIGATORS
(Parker et al., 1972) I
' Coniinuous flow activated sludge unit. Floc strength deiemined at di fferent sludge age:
1 1.9 days 9.9 days 3.2 days
(Glasgow and 1 !su, 1982) Continuous flow , laboratory activated sludge unit. Floc strength determined ai different nutrient regimes
(King and Forster, 1990) I Floc strength determined in sonication experiments laboratory scale activated
experiments; laboratory activated sludge unit. full scale plant
(Morgan and Forster, 1992)
STRENGTH PARAMETER
(4
sludge unit. Floc strength determined in sonication
STRENGTH PARAMETER
(JO
3. EXPERIMENTAL PROCEDURES AND ANALYTICAL METHODS
3.1 Outline of Experïments and Analysis Conducted
In this chapter the experimental determination of geornetric porosity alum coagulation
and activated sludge flocs is described. In order to study the non-homogeneous nature of the floc
porosity the aggregates were dispersed into smaller hgments that were cornposed
predominantly of the lower level structures (microflocs and flocculi). Mechanical and sonic
energy was used to break up the aggregates. The geometric porosity data were used to study
structures of alum coagulation and activated sludge fiocs. In Table 6 experiments and analysis
conducted in this chapter are presented.
lame O uurme OI expemnems ana anaiysis conaucrea ut rnis rnesis
Experirnents and analysis
+ Design of experiments to study geometric
porosity of flocs - - - -- - - -
4 Mechanical dispersion of alum i d activated
sludge fiocs
+ Sonic dispersion of activated sludge flocs
Outline
Statisticai design of floc sampling using preliminary
geometric porosity data set
4 Analysis of geomerric porosity and size of flocs
dispersed with increasing mixing intensities
4 Analysis of geornetnc porosity and size of flocs
dispersed with increasing sonic energy input
4 Cornparison of the effect of mechanical and sonic
dispersion on the sue and porosity of advated sIudge
floc
3.2 Design of Experiments to Study Geomefric Pomsity of Flocs
3.2.1 Description of the Project
The specific objective of this part of the study was to design floc sarnpling to examine the
geometric porosity of flocs. nie statistical design was based on a prelirninary data set that
consisted of the geometnc porosity (P) of 6 randomly selected activated sludge flocs. For each
floc, the porosity was determined on 5 randomly selected sections fkom the centre of that floc.
The experirnentd procedure for preparing floc sections is presented in Chapter 3.4.2. On each
of the sections, two rectangular measurement windows (window 1 and window 2) were drawn at
two different locations inside a floc section. The total geometric porosity (P) was determined for
each window as a ratio: area of pores to the measurement window area. In the preliminary data
set the size of flocs was not determined. To account for the possible effects of the fioc size on
the porosity each floc in the prelimlliary data set was assigned an identification number (floc id
number). The experimental data are listed in Appendix 1. The preliminary data set did not
contain the sizes of individual pores on the floc sections.
The primary dependent variable in this study was the average geometric porosity of a floc
(P). The primary independent variables were the floc id number, section number. measurement
window number. and measurement window area. The following questions needed to be
answered:
1) how many sections from a single floc have to be used for the porosity determination?
2) What is the optimum area of the measurement window?
3) How many flocs have to be analyzed to test if floc size and dispersion intensity have
statistically significant eEect on the porosity of the aggregate?
3.2.2 Statistical Analysis of Preliminary Data
To identifi the variables that had significant effects on the geometric porosity, an
analysis of the variance of the experimental data was conducted (Kuehl, 1994) (Appendix 2).
The following statistical model was proposed for the analysis of porosity data:
y -y4 - regression coefficients
It was found that the variable floc id number had a significant effect on porosity value.
whereas section number, window number and area of the window had non-significant effects on
the porosity of flocs. It was also found that 69% of the variance in the geometric porosity (P) of
flocs was due to the variable floc id number (Appendix 2). This variation was most likely due to
differences in the size of individual flocs. Therefore. it was decided to include size of floc in the
fume geometric porosity data sets. Only 3% of the variance was due to different sections of the
same floc being used for porosity determination (variable floc section number). Therefore, the
measurements of a single randomly selected section fiom the centre of that floc provided an
adequate description of the geometric porosity of that floc. It was observed that the porosity
variations within a single section were minimized when larger measurement windows were used.
The specific size of the measurement window is limited by the size of the floc on the section.
Overall the following statistical model was proposed for the analysis of porosity data:
porosity of a floc = y + yi(floc size) Equation 53
Sample Sire Determination
In the dispersion expenment an additional variable - dispenion energy input had to be
introduced to the statistical model:
floc porosity = y + y i(floc size) + yz(energy input) Equation 54
A sample variation method was used to choose the sample size (Brunner, 1996) to
statistically test the model in Equation 54. in this method, the floc dispenion (treatment) effect
size was detemined using the following equation:
Equation 55
Where
a - treatment (dispenion) effect size
R& is the proportion of variation explained by the reduced statistical model, (Le. the one containing only the variables for which we are controllkg (floc size) but not those for the effect of the variable of interest (dispenion energy input). The reduced statistical model is: porosity = y + y* (floc size)
R F ~ - is the proportion of variation explained by the full statistical model, i.e. the one containing both variables (floc size and dispenion energy input). The fui1 statistical model is: Porosity = y,+ y2 (floc size)+ y3 (dispersion energy input).
In Equation 55, &' represents the proportion of porosity variation, which is explained by the
effect of floc breakup. C oeficient (a) expresses Ilc2 as a proportion of the variation le ft
unexplained by the size of the flocs. The F statistic for testing the reduced against the fidl model
can be written as:
F = ((n - p)/s) (a/ ( 1 -a)) Equation 56
Where
p - number of regsession coefficients in the statistical model
s - number of independent variables tested
n - sarnple size to be determined.
The floc dispersion (treatrnent) effect size (a) was determined as follows. A new data set
(DATA 2) was created using the preliminary experimental data (DATA 1). Each floc in the new
data set had its geometric porosity (P) increased by some vaiue - x. DATA 2, therefore.
represented new population flocs. The analysis of variance using the full mode1 (two
independent variables: breakup energy input and floc size) was nui to detect if the difference
between DATA 1 and DATA 2 was significant. The value of x was increased until the difference
between these two porosity data sets was significant. The minimum value of x was determined
to be 2.5 %. For this value of x. R: was equal to 0.6971, and R~~ was equal to 0.6832. The
value of treatrnent effect size (a in Equation 55) was cdculated to be 0.04 by using these results.
By holding the effect size coefficient (a) constant, one can increase the sample size (n) in
Equation 56 until F is significant. The sample size (n) was increased until the F statinic
(calculated for p = 3 and s=l) and was significant at a 95% confidence level. The sample size
(n) of 150 flocs resulted in calculated F value of 3.06 and probability p = 0.049. Therefore,
minimum 150 of flocs need to be analyzed for porosity in order to detect if significant effects of
size and dispersion energy input on aggregates' porosity.
3.2.3 Statistical Experiment Design - Conclusions
The following conclusions were made fiom the preliminary statistical analysis:
1) the rneasurements of a single randomly selected section of a floc provided an adequate
description of the geometric porosity of that floc. The largest possible measurement window
should be used to minimize variations due to non-homogeneous nature of the porosity of flocs.
2) There was a significant variation in the porosity of the individual flocs. This variation was
m o a likely due to differences in the size of individual flocs. Therefore, the size of flocs has to
be included when determining the geometric porosity (P) of aggregates.
3) A sample of 150 flocs will be suficient to test if floc size and dispersion intensity have
significant effect on the georneûic porosity of aggregates.
3.3 Pomsity and Structure of Alum Coagulation Flocs
In this section the geometric porosity of alum coagulation flocs was anaiyzed. The flocs
were dispersed with mechanical energy increasing from O - 0.3 kJ/g SS. The porosity and the
size of flocs were measured at various mixing intensities.
3.3.1 Experimental Methods
Jar Tests. Turbid water (suspended soiids concentration of 75 mg& and nirbidity of 66 NTU)
was prepared by rnixing kaoiinite clay and tap water. Five rectangdar (2 litre) glas jars with
paddle type mixers (2.5 X 7.5 cm) were used. The jars were filled to 1-L volume, and the paddle
height was adjusted to the mid-depth of the liquid volume. Alun was used as a coagulant. Lay
(1997) determined the optimum dose of coagulant for the same tesr conditions to be 40 mgL.
The optimum dose of alun was introduced rapidly into the eye of the mixer, which operated at a
speed of 80 rpm for 30 seconds. The slow mix was continued for 20 minutes at 30 rpm. After
the alum coagulation flocs were formed, the agitation intensity was increased to 40,60,80, 100
and 140 rpm for 5 minutes to disperse the aggregates (Table 7).
Table 7 Jar coagulation test data
JAR #
1
2
2
3
4
5
FINAL MIX
SPEED IWMl
INITIAL TUR-
BIDITY WTUl
TURBI- 1 O I W TEMPERA-
TURE
["Cl
-- -
ALKALINITY
[m%L as Ca CO3 1
19
19
19
19
19
19
Initial
63
63
63
63
63
63
Final
52
52
52
52
52
52
settliag [NTUl
3.5
3 3
7.3
15.2
26.7
39.6
Initia1
7.5
7.5
7.5
7.5
7.5
7.5
Final
6.9
6.9
6.9
6.9
7.0
7 .O
Pre~aration of agar embedded floc sam~les. Immediately after final d g , a sample of flocs
(about 6 mL) was withdrawn with a wide mouth pipette f?om the bottom of the jar (Le. fiorn a
depth of about 10-cm). About 1 rnL of the sample was preserved in 9 mL of 4% agar mixed with
alizarin dye (the volume ratio of agar and the dye solution was 10: 1, with an alizarin soiution
concentration of 10 g/L). This sample was used for the meanirernents of the flocs' size, using
microscope and image analysis system. Detailed procedure is described in an earlier study
(Gorczyca and Ganczarczyk, 1995).
he~aration of resin embedded floc sarn~les. Another sample was prepared, using a larger
sample volume (about 5 mL) placed in 5 mL mixture of 4% agar and aiizarin. The larger
sample volume allowed for a fairly high concentration of aggregates in the volume of the gel.
Several small agar cubes (0.5 x 0.5 x 1 mm) were cut From this sample. Because of the high
concentration of flocs in the gel, each cube contained a number of alum flocs. Several of these
cubes were placed in the JB-4 infiltration solution (J.B.EM Services hc. Dorval, Quebec).
Approximately 1 mL of the alizarin dye was added again to 5 mL of the infiltration solution to
stain the almost translucent alun flocs. The agar cubes containing the floc samples were left in
the infiltration solution for 24 hours at 4 OC. The next day, the agar cubes (thoroughly
infiltrated) were removed IÏom the solution and transferred into BEEM embedding capsules.
Flocs were embedded in a J'E#dM Plus Ernbedding Kit (J.B.EM Senices Inc. Dorval, Quebec).
The composition and characteristics of JB-4 resin are very similar to the resin used previously
for embedding biofilms (Ganczarczyk et al., 1992). Thin sections (2 p thick) were cut fiom the
blocs containing embedded aggregates using microtome. The sections were stained with
toluidine blue for better contras. The porosity and size of flocs were determined by examining
the sections with microscope and a Global Lab Image analysis system (Transduction Limited,
Ontario, Canada). For most rneasurements 200 X magnifîcation was used Figure 10 shows a
typical digitued image of a thin section of alum coagulation floc. In the process of porosity
61
measurement with the image analysis system, the researcher manually selects the pixels that
belong to the solid phase on the image of the floc in order to separate them from those pixels that
indicate liquid phase on the image. The selected pixels became bnght (white). This procedure is
called a threshold selection. A cornparison between the initiai video image of the floc and the
brightened one (threshold image) ensures the accuracy of the measurement.
3.3.2 Data Processing
The Global Lab image analysis data were used to determine:
DIMETER i j = rquivaieni circular diameter of coagulation flocs -s d e t e d e d on
thin sections (Figure 10);
DIAMETER 2 (D2) = equivaient circulas diameter of alun coagulation flocs as determined on
agar embedded samples;
POROSITY 1 (PI) = hole ratio = total area of pores /floc area ratio as detexmined by Global Lab
Image software ; in this measurement the hole ratio of the entire cross-sectional area of a floc is
determined as opposed to the porosity of the measurement window only (POROSITY 2);
POROSITY 2 (Pz) = porosity of a rectangular window placed within floc section (Figure 10).
The maximum possible window site that cm be fitted inside a floc section was used to minirnize
the porosity variations. The geometric porosity was calculated as the ratio of the total area
occupied by the pores in the window to the area of that window.
POROSITY 3 (P,) was determined like Porosity 2, but pores larger than 10 pn' in a cross-
sectional area were excluded;
POROSITY 4 (Pa) was determined like Porosity 2, but pores smaller than 10 pn' in a cross-
sectional area were excluded.
The reason for reporting the floc porosity in several different ways was justified by
several factors. First, Porosity 2 was detemiined for the purpose of comparing the data with
64
those reported earlier (Li and Ganczarc yk, 1990; Ganczarczyk and Rim, 1996; Guzowska,
1996; Cousin and Ganczarczyk, 1998). Second, the earlier studies indicated the presence of two
populations of pores in microbial systems: a population of very mal1 pores (usuaily smaller that
10 pn2) and a population of large pores (usually larger than 10 pn2). The Porosity 3 and 4 were
detennined to detect the possible effects of floc dispersion on these two pore populations. Basic
statistics and analysis of variance of dl data were perfomed using SAS software (SAS Institute
Inc., Cary, North Carolina).
3.3.3 Results
Effects of mechanicd dimersion on size and porositv of dum coadation flocs. A cross-
sectional area of about 100 flocs embedded in agar was determined before dispersion, and after
every final mixing. The sizes of flocs were log-normally distributed, similar to the observation
reported carlier by several researches (Kavanugh and Leckie, 1980; Gorczyca, 199 1 ). The
initiai distribution of equivalent diameter of aium coagulation flocs is presented in Figure 24.
The logarithmic means of the equivalent circular dimetes of flocs (DIAMETER 2) afier
dispersion are listed in Table 8. With the increased mixing intensity, the size of flocs decreased.
and this was observed for both agar and resin-stabilized samples (DIAMETER 1 and
DIAMETER 2 on Figure 12). The analysis of variance indicated that the applied rnixing intensity
had significant effect on the size of the flocs (Appendix 3).
The size of alum flocs as detennined on the microtome sections was somewhat smaller
than that measured on the agar-embedded samples. This could be due to either the breakup of
flocs during the infiltration procedure, or to some shrinkage durhg polymerization of the
embedding resi.. This phenornenon was aiso observed in earlier studies (Bahrami, 1997; Lay.
1997).
The porosity of 150 randomly selected flocs was determined. The average geometric
porosities (P ,. Pl. P3 and P4) are reported in Table 9 through 12. In Figure 1 1, the distributions
of porosity of a lun flocs sampled at increasing rnixing speeds are shown. For low rnixing
speeds (up to SO rpm), the porosity values were distributed normally. At hi& mixing speeds (i.e.
at 100 and 140 rprn). the distribution of porosity data changed to log-normal (Figure 1 1 e and f) .
Table 8 Effects of minng speed on size (D2) of alum conplation f loa - -
FINAL MIXING SPEED r
Table 9 Effect of mirring speed on geometric porosity (Pl) and size (Di) of alum
DIAMETER 2 @2
Log.Mean
[vml
coagulation flocs
FINAL MIXING SPEED
STD. DEV.
[ P l
AVERAGE POROSITY I
(Pl)
STD. DEV.
DIAMETER OF T m
SMALLEST FLOC Ilrm l
DIAMETER OF THE
LARC;EST FLOC [ P l
Table 10 Effects of mixing speed on geometric porosity (Pz) of alum coagulation flocs
1 FINAL 1 AVERAGE 1 STD.DEV. 1 AVERAGEPORE M n w G SPEED
W M l 30
POROSITY 2 (Pz)
["hl
9
[%1
7
SIZE
[ P 2 1
9
Table 11 Effects of miUng speed on geometric porosity (P3) of alum coagulation flocs
AVERAGE PORE SIZE [PZ 1
-.
FINAL MMING SPEED
W M l
AVERAGE NUMBER OF
SMALL PORES (within one
section)
AVERAGE POROSITY 3 (P3)
[%1
Table 12 Effects of rnuing speed on geometric porosity (P4) of alum coagulation flocs
- -
AVERAGE NUMBER OF LARGE PORES
(within one section)
1 MIXING SPEED 1 AVERAGE ( AVERAGE PORE POROSITY 4 (Pr)
[%1
SIZE
bm21
Figure 11 Distribution of geometric porosity (Pi) of alum coagulation flocs at an increasing mking speed
Figure 12 shows a relationship between the POROSITY 2, d n g energy input (E) and size of
alum flocs. The average energy dissipation per unit volume was calculated by using the method
of Comwell and Bishop (1983). This average energy dissipation rate varies with the location in
the flocculation vesse1 (Tomi and Bagster, 1978). To account for the higher local energy input in
the impeller tip zone (where flocs were sampled) the average energy dissipation was multiplied
by a factor of 50. It was assumed that within the short penod of time between Nming off the
mixer and floc embedding in aga (severai seconds) significant reflocculation of aggregates did
not occur.
The porosity of flocs showed some initial increase when the mixing speed reached 80 rprn (0.05
kJ/g SS). This could be a consequence of a more intensive liquid flow through flocs at a higher
mixing intensity. At the mixing speeds higher than 80 rpm, the porosity decreased somewhat,
but this change was rather srnail.
nie anaiysis of variance (using the mode1 in Equation 53) indicated that the floc size had
a significant effect on the porosity (Appendix 4 and Table 13). Figure 13 shows a plot of the sue
against the average geometric porosity of alun coagulation flocs. A linear relationship fitted to
the data had low correlation coefficient. That was quite expected because of the natural
variability of the floc porosity discussed earlier in the Introduction section. Because of the large
scatter of the data, the average geometric porosity data could be related to neither size of flocs
nor their resistance to shear. Yet such a relationship was expected based on the multi-level
mode1 of alun floc formation. It was concluded, therefore. that the average geornetnc porosity
alone cannot indicate the possible differences in the structure of flocculi. microflocs and floc
aggregates. Therefore, fractal analysis of the entire pore distributions in the individual flocs was
conducted.
Table 13 Effects of mixing speed and the floc size on the geometric porosity - results of the analysis of variance
VARIABLES
POROSITY I
POROSITY 2
POROSITY 3
POROSITY 4
- - - - -- -
NOT-S IGNEICANT I
SIGhi iCAiT
p = 0.2494 p = 0.0003
EFFECT OF INCRFiASING MUUNG SPEED
SIGNIFICANT
p = 0.0065
EFFECT OF FLOC SIZE
- --
SIGNIFIC ANT
p = 0.0001
NOT-SIGNlFIC ANT
p = 0.1731
S IGNIFIC ANT
p = 0.0884
NOT-SIGNTFIC ANT
p = 0.6424
NOT-SIGNIFIC ANT
p = 0.5349
Figure 13 Average geometric porosity vs. size of alum flocs
EQUIVALENT CIRCULAR DIAMETER (Dl) [MICRONS]
3.3.4 Sierpinski Fractal Dimensions for Alum Coagulation Flocs
A Sierpinski plot allows for the analysis of the entire distribution of pores on a floc
section. Sierpinski plots were constructed following the procedure developed by Kaye (1 989).
For each floc section. the solid fraction of the floc (residual area R,) was ploaed against the area
of the smallest pore visible at magnification X (nomalized by the size of the measurement
window):
Nonnalized area of pore (A3 = Area of smallest pore visible at mamificatior! X Equation 57 Area of a measurement window
ResiduaI Area (Rd = 1 - Porosity measured at magnification X Equation 58
In this procedure we assume that initiaily when looking at the floc section the microscope is
adjusted to such a loa magnification (Xi) that only the largest pore of size Axl can be seen
clearly. Assuming that at particular magnification Xi we cannot see pores smaller than Axi we
calculate the residual area RXI= 1 - AxJarea of measurement window. When magnification is
increased to Xz the residual area RG= 1 - ( h l + Axz )I area of measurement window
Generally for the magnification X,, , R, = 1 - (Axi +. . . . . .+ Ax,)/ area of measurement window.
Figure 14 shows an example of a Sierpinski plot for a single alum coagulation floc. The slope
(m) of the best-fit line between the pore area and the residual area was used to calculate the
Sierpinski fractal dimension (Equation 24). For most of alun flocs analyzed in this study. three
lines fit the data. Therefore, three different Sierpinski Fractal dimensions: S.Fo. , S.FI. and S.F2.
described the distribution of pores in an alum coagulation floc.
The sizes of transition pores were detemiined by visual inspection of 150 Sierpinski plots (Table
14). Flocs collected at higher dispersion intensities were predominatly small with smaller pores.
Therefore, the Sierpinski plots for small flocs (at 1 00 and 1 40 rpm) had many more data points
in the smdl pore sizes (Le. smaller than 10 pn2). A large number of data in the small pore size
region allowed for the observation of the additional line and the m i t i o n point in the srnall
pores region.
Generaily the pores in alum coagulation flocs could be divided into the following groups: small
pores with a size < 2.5 pn' (described by S.Fo. ), medium size pores with sizes ranging fiom 2.5
- 10 pm2 (described by S.FI.), and large pores > 10 pn' (S.F2). Smail pores would be present
primarily in flocculi, while medium and large size pores would occur in microflocs and floc
aggregates respectively. Clearly, the presence of three different pore populations within the
aiun coagulation floc matrix confmed previous theoretical and experimental investigations that
argued for the multilevel floc structure.
On most of the Sierpinski plots. a discontinuity in the data descnbing medium and large
pores was observed (Figure 14). This means that the largest pore in the Sierpinski carpet
describing microfloc (S.FI .) does not automatically become the smallest pore in the Sierpinski
carpet describing floc aggregate(S.F2.) (Figure 15). This may suggest the size of the flocculi
(medium pores) must be significantiy different that the size of microflocs (large pores).
Sierpinski fracta1 dimensions of flocs determined at each rapid mix speed are listed in
Table 15. As expected, the firictal dimensions decreased mostly in the following order: S.Fo.>
S.FI. > S.F2.
The results of aoaiysis of variance (Appendi 5) showed that the ciifferences between the d w e
Sierpinski fiactai dimensions are significant at the 95% confidence level.
Table 14 Sue of transition pores on Sierpinski plots for alum coagulation flocs
1 30 1 10.20 1 Not available 1
Final Muing Speed h m ]
1 140 ( Not available 1 1 .O2 1
Table 15 Sierpinski fractal dimension of alum coagulation flocs after miring
Average Size of the Transition
Pore on Sierpinski Plot
-
MIXING SPEED Line 1 on the Sierpinski Line 2 on the 1 Line 3 on the r plot (Figure 14) Sierpinski plot 1 Sierpinski plot
Average Size of the Transition
Pore on Sierpinski Plot
I 1 Siope 1 SJO. Slope 1 S.FI. 1 Slope 1 S.Fr
3.3.5 Discussion
The porosity of alun flocs determined in this study was compared to other data available
in the literature (Table 16). The geometnc porosip of alun coagulation flocs determined in this
study ~ 3 s somewhat lower that what has been reported earlier. In this study the geometric
porosity of a representative sample containhg both small and large flocs was analyzed. The
resuits of the earlier studies are based on analysis of a few large flocs only, and the porosity of
large flocs is expected to be higher than the porosity of small flocs. Also, the process of
determining geometric porosity with an image analyzer depends largely on die selection of
threshold (as described in Chapter 3.3.1 ). The selection of range of pixels that belong to the
solid phase of the section depends to some extent on the persona1 judgement of the researcher.
Therefore, when comparing geometric porosity values the ben results are obtained when the
values that have been measured by the sarne researcher are used.
In the second column of Table 16. the average geometric porosity (Pi & Pz) is listed. in
The data in Table 16 clearly indicate that the exact numben for descnbing the porosity of alun
flocs are still diflicult to establish. However, the following conclusions can be made at this
point:
1. The average geornetric porosity (Pz) of alum coagulation flocs determined in this study varied
from 9 - 17%. which is lower than the values reported earlier (Table 2). This may be due to the
srnailer ske of flocs analyzed in this study. DifFerent threshold value (grey colour of pore and
solid hc t ion on the section) may also be the reason for the dinerences between the results of
this study and the values reported by other researchers. The m a s porosity of dum flocs was
always about 10 tirnes higher than their geometric porosity.
2. No clear trend between the average geornetric porosity and the size or the resistance to shear
of alum flocs could be determined. Yet the multi-level models of floc formation suggested that
smaller and stronger flocs should have lower porosity than large, weak aggregates.
3. The Sierpinski plots for dum coagulation flocs indicate that at least three distinctive pore
populations exist within an alun coagulation floc. Three difFerent pore populations indicate the
presence of the three different levels of aggregation, i.e. flocculi, microflocs and floc aggregates.
Therefore, ody when porosity data were anaiyzed using concepts of hc t a i geometry was the
multi-level structure of a l u n fiocs reveded. The results of fractai anaiysis indicated that the
mal1 pores in aium coagulation flocs are smaller than 3 pm2 , medium pores ranged from 3 -10
pm2 and large pores are larger than 10 pn'.
Table 16 Porosity of alum coaguiation flocs - summary
ALUM COAGULATION FLOC AVERAGE )FLOCS 1 PoRosrrv pq
- -
This study
( calcite suspension * 1 ~ = 8 1 1
(Lay, 1997) L
formed in coagulation of
Pz =25 - 50
I fomed in coagulation of clinoptilolite suspension* E = 89
- -
formed in coagulation of montomorillonite suspension*
~ = 9 8
I formed in coagulation of illite suspension*
* (Gorczyca, 199 1)
E = 94
I formed in coagulation of silt suspension* ~ = 9 1
The objective of this part of the study was to examine the geomemc porosity of activated
sludge flocs. The flocs were dispersed using mechanical and sonic energy so that the non-
homogeneous nature of the porosity of aggregates could be studied.
3.4.1 Experimental Methods
Activated sludge (2L) was collected from the aeration tank at the Peterborough
wastewater treatment plant. It is a conventional activated sludge plant. The sewage flow is
divided into two treatment trains: train 1 and 2. The flow coming into train 2 is divided equally
into two additional trains: 3 and 4. The plant processes municipal and industrial wastewater (45-
50,000 m3/day of average BOD quai to 176 rnglL). The treatment parameten monitored during
the time of experiments are listed in Table 17. The temperature of the mixed liquor was 21 O C
(MLSS of 2610 mg/L). Activated sludge flocs were dispersed by a mixing energy that increased
fiom O - 1.40 kl/ g MLSS in a cylindrical, steel vessel (height = 30 cm and diameter = 10 cm).
The mixed liquor depth was 26 cm (Figure 16). The geometry of the rnixing vessel used in the
experiments with activated sludge flocs was slightly different than that of the jars used for the
dispersion of alum coagulation tlocs. This was because the vessel used in the experiments with
activated sludge flocs had an AME transducer artached to it, and this transducer was used later in
sonication experiments. A cornparison of floc properties d e r mechanical and sonic dispersion
was one of the objectives of the conducted experiments.
Table 17 Operation data for the Peterborough Wastewater Treatment Plant
1 AVERAGE FOR JULY 1996 (based on 4 -3 1 samples) 1 TRAIN 3
( Qw - Wastage Rate [rn3/day] 1 277
1 Va - Volume of Aeration Tanks [m3] 1 2546
1 BODs (prirnary effluent) [rng/L] I 94 1 Suspended Solids (prirnary effluent) [rng/L] 1 80 1 Volatile SS (in mixed liquor) [%] 1 75.2
- -- 1 30 min Sertling Test, % 1
1 Final Effluent Suspended Solids [mg&] 1 4.1
1 pH influent 1 7.3
Sludge Age, (calculated for volume of aeration tanks only) [days] 3.9
F:M (BOD applied/MLVSS present per day) 0.26
Figure 16 Experimental apparatus used in experiments with the activated sludge flocs
1 - TIP OF TRE SONICATOR
2 - CYLINDRICAL VESSEL
3 - PADDLE MUCER
4 - GMIE TRANSDUCER
3.4.2 Mechanical Dispersion of Activated Sludge Flocs
The sludge was continuously agitated with a paddle mixer operathg at a speed of 40
rpm. Severai breakup mixing speeds, ranging nom 3 15 - 990 rpm, were applied for 5 minutes.
The higher mixing speeds used in the experùnents with activated sludge flocs as compared to
those applied in the dispersion of alun coagulation flocs are explained as follows. First,
activated sludge flocs are known to be more resistant to shear than alum coagulation flocs. Also,
the cylindncai mixing vesse1 used in the dispersion of activated sludge flocs had no baffles.
Therefore, in spite of the hi& speeds, the actual energy input would have been lower than that in
the rectangular jars used in the dispersion of alun flocs. To avoid excessive vortexing during
mixing, an axial flow propeller (diameter of 5 cm) was used instead of the paddle mixer. Mer
each rapid mix penod, the sludge was slowly agitated (40 rpm) with the paddle mixer to dlow
the flocs to reflocculate. The activated sludge fiocs were assumed to reflocculate completely
during this 5 minutes of slow mixing. The time required for refloccdation was determined in the
following experiment. The activated sludge (1 L) was mixed vigorously (350 rpm) in the
standard jar test apparatus as described earlier. The impeller zone power input in this experiment
was approximately equal to 0.2 Wlg MLSS. Following the breakup, the activated sludge flocs
were ailowed to reflocculate. The average floc size (D2) was detennined after 5, 15, 30,45 and
60 minutes during the reflocculation (Figure 17). Within 5 minutes of reflocculation, the size of
the Bocs reached the initial value of 67 pm.
Possible effects of reflocculation on the structure of activated sludge flocs were considered as
follows. Reflocculated activated shdge floc might have k e n more compact and resistant to
shear due to the rearrangement of flocculi and microflocs within the aggregate (Figure 18).
However, both the original floc and the reflocculated aggregate would disperse into Mcroflocs
or flocculi, and it is the porosity of these dispersed structures (not the reflocculated aggregate)
that was assessed in this study.
Figure 18 Breakup and re-growth of a floc
Primary Floc Floc dispersed Reflocculated particles to microflocs fl O c
The embeddhg procedure used for activated sludge flocs was different h m the one applied for
alurn coagulation aggregates. Activated sludge flocs contain microorganisms that had to be
preserved in a life-like state with specific Exatives.
Preoaration of aear embedded floc sam~les. M e r each dispersion period, a sample of sludge
(about 6 mL) was withdrawn from the vessel. Al1 samples were taken fiom a depth of about 10
cm. About I mL of the sample was preserved in 9 mL of 4% agar. This sample was used for the
analysis of the flocs' size.
Preoaration of resin embedded floc sam~les. The remaining floc sample (about 5 mL) was fixed
in 2% glutharaldehyde in O. 1M cacodylate buffer (about 5mL) and 0.1 5% nitheniun red stain
(IrnL). Flocs were s h e d with nithenium red for possible identification of the amount of
extracellular material within in the floc (Luft. 1971). This sample was furiher processed using
the procedure drscribed by Ganczarczyk et al. (1 992). SrnaIl samples of activated sludge flocs
were embedded in BEEM capsules with the ~ l 3 - 4 ~ ~ P l u Embedding Kit, (J.B.EM Services Inc.,
Quebec, Canada). Two-micron thick sections were cut with microtome fiom the blocs
containing the embedded aggregates. The sections were stained with toluidine blue to provide a
better contrast between the biomass and pores. The geornetric porosity (P) and size were
determined from the sections of flocs by using a BIOQUANT IV image Analysis System (R&M
Biometrics. USA).
3.4.2.1 Data Processing
The Bioquant N image analysis measurement data were used to determine DIAMETER
1 (Di). DLAMETER 2 (D2), POROSITY 2 (Pz), POROSITY 3 (P3) and POROSITY 4 (Pa).
Defdtions of these parameters have been presented earlier (Chapter 3.3.2). Most of the floc
rneasurernents presented in this thesis were performed with BIOQUANT N image analysis
system. During the experiments with alurn coagulation flocs the BIOQUANT IV system failed
and another image analysis software (the Global Lab Image) had to be used. POROSITY 1 (Pi -
hole ratio) could not be determined with the Bioquant IV image analysis system because the
sohare does not hclude the hole ratio calculation option. Measurements were done using 100
X and 200 X magnifications. Basic statistic and the analysis of variance of al1 data were
conducted with SAS software.
Effects of mechanical dispersion on the size and ~orosity of activated sludge flocs. The
lognomal distributions of activated sludge floc size have been presented numerous times in the
literature (Li and Ganczarczyk, 1986; Hongwei, 1992; Wong, 1992: Cousin, 1998). The initial
distribution of the equivalent diameter of activated sludge flocs is shown in Figure 24. The
logarithmic means of the equivaient diameter of floc after dispersion are presented in Table 18.
With the increased mixing intensity, the size of flocs decreased. This was observed for both agar
and resin-stabilized sarnples (Figure 20). The analysis of variance indicated that the differences
in floc size were statistically significant at a 95% confidence level (Appendix 6). The energy
input in the experiment was calculated using the method described previously in Chapter 3.3.3.
The sizes of activated sludge flocs as detennined from thin section (Di) were quite similar to
those measured on the agar-embedded sample (Dz). Therefore, in contmt to aiun flocs, the size
of microbid aggregate was not af5ected by the embedding procedure.
The average geometric porosity (P2) varied fiom 3 - 8 %. Averages for al1 different types
of porosity detemiined are listed in Table 19- 22. The distributions of the floc porosity for each
applied mixing speed are presented in Figure 19. Analysis of variance indicated that floc
dispersion had a significant effect on the geometric porosity of flocs (Table 22 and Appendix 7).
Table 18 Effects of rnixing speed on size (D2) of activated sludge flocs
MIXING SPEED
P M I
- -
DIAMETER 2 ' @2)
Logmean.
D W T E R OF THE
LARGEST FLOCS
STANDARD 1 DIAMETER
1. Logarithmic mean based on 200 samples.
DEVIATION OF THE SMALLEST
FLOCS
Table 19 Effects of miring speed on geometric porosity (Pd and size (Di) of activated sludge flocs
I I
2. Average based on 25 samples
Table 20 Effects of miring speed on geometric porosity (P3) of activated sludge flocs
DIAMETER 12 (Di) Logmean.
l P l 1 07
MIXING SPEED POROSITY 3 AVERAGE TOTAL NUMBER (P3) SIZE OF OF SMALL PORES
PORES
STANDARD DEVIATION
1%1 4
MIXING SPEED
IRPMl
30
POROSITY 2 ' (P2)
I"/.1 3
Table 21 Effects of mUhg speed on geometric porosity (Pd) of activated sludge flocs
Table 22 Efîects of mixing speed and the size of flocs on the geometric porosity - results of the analysis of variance
VARIABLES
TOTAL NUMBER OF LARGE f ORES
46
85
70
62
69
59
SPEED 1 IcFFECT SIZE oF
AVERAGE SIZE OF PORES
b 2 1 36
36
52
45
53
32
MIXING SPEED
I MM1
30
315
483
652
820
989
POROSITY 4 (Pd
[%1 4
S
4
4
6
6
POROSITY 1
POROSITY 2
POROSITY 3
I
POROSITY 4
not availabie
SIGNIFIC ANT
p = 0.0035
not available
NOT-SIGNIFIC ANT
p = 0.0753
SIGNIFICANT
p = 0.0001
NOT-SIGNIFIC ANT
p=0.1119
NOT-SIGNIFICANT
p = 0.4680
NOT-SIGNIFICANT
p = 0.0600
Figure 19 Distribution of geometric porosity (Pz) of activated sludge floa at an increasing miring speed.
Ylxlng s m - 30 rpm
Mlxfng sped - 989 rpm
Figure 20 shows the relationship (on log-log scale) between the energy-input (E), size
@ 1 and D2) and geometnc porosity (Pz) for activated sludge flocs. The geometnc porosity of
flocs showed some initial increase. This could be the consequence of a more intensive liquid
flow through flocs at a higher rnixing intensity. M e r the mixing speed reached 3 15 rpm (0.05
kT/g SS), the geometric porosity decreased somewhat.
Atternpts to relate the average geometric pros* to the size or resistance to shear of
activated sludge flocs were unsuccessfil. The effect of the size of floc on their average geometric
porosity was not significant and the eff'ect of the dispersion on the porosity of flocs was significant
(Appendix 7). This clearly suggests that the average geometric porosity alone cannot be used to
study non-homogeneous structure of flocs. Therefore. hctal analysis using the Sierpinski carpet
mode1 was applied to study distribution of pores within the activated sludge flocs.
3.4.2.3 Sierpinski Fractal Dimension for Activated Sludge Flocs
Figure 21 shows an example of a Sierpinski plot for a single activated sludge floc. As in
the plots for alum coagulation flocs, three lines were found to fit the expenmental data. The
transition pore sizes between these lines were determined by eye. These points indicated a
transition €tom a small to medium to large pore population and. consequently, a transition h m
flocculi to microfloc to floc aggregate. Therefore, the results of fracta1 analysis confirmed that
activated sludge flocs possess a multilevel structure.
The average sizes of the transition pores for activated sludge flocs are listed in Table 23.
Based on the transition pore sizes determined in this study and the results of previous work
(Table 24) the pores in activated sludge flocs were be divided into three groups: < 3 p'. 3 - 15
pn' and > 20 pm2. The fracta1 dimensions decreased in the following order: S.Fo. > S.FI. > S.F2
(Table 25).
Figure 21 Sierpinski plot for an activatcd sludge floc
Log(Pore Area)
-0.045 1
Transition Pore Area (T.P.) 3.6
Table 23 Size of transition pores on Sierpinski plot for activated sludge flocs in this sîudy
Final Mixing Speed I v m l
Average Sue of the Transition Pore on Sierpinski Plot
Average Size of the Transition Pore on Sierpinski Plot
T.PI ( p d
Table 24 Size of transition pores on Sierpinski plot for activated sludge fïocs in earlier studies
Sou rce Average Size of the Transition Pore on Sierpinski Plot
T. P2 (pm2)
I Activated sludge flocs (Riru', 1993)
I Activated sludge flocs (Cousin, 1998)
Table 25 Sierpinski fractal dimensions for activated sludge fiocs
MIXING SPEED [RPMI
O
315
Line 1 on the Sierpinski plot
Slope
0.0028
0.0076
Line 2 on the Sierpinski plot
SJo.
1.9972
1.9924
Line 3 on the Sierpinski plot
Slope
0.0 1 07
0.020 1
Slope
0.03 14
0.023 1
S-Ft.
1.9893
1.9799
S.Ft
1.9686
1.9769
3.4.2.4 Discussion
The porosity of activated sludge flocs determined in this study was compared with the
data available in literature (Table 26). Generally, the geometric porosity (Pz) determined in this
study was somewhat lower than the values reported earlier. This is most likely explained by the
sizes of flocs analyzed in this study: in the floc dispersion experiments many small aggregates
were created and their porosity was likely smaller than that of the large flocs used in earlier
studies. At this point the following conclusions can be made:
1. The average geornetric porosity of activated sludge flocs as determined in this study
varied from 3 - 28%.
2. The relationship between the average geometric porosity and size or resistance to shear of
activated sludge flocs was dificult to determine. Therefore, the non-homogeneous nature of
the porosity of flocs could not be assessed using a classical approach.
3. Sierpinski plots for activated sludge fiocs indicated that at l e s t three distinctive pore
populations exist within microbial aggregates. i.e. small pores had cross-sectionai area less
than 3 pn2, medium pores were smaller than 20 pn2, and large pores were larger than 20
pn'. Fractal analysis of porosity data revealed the multi- level Structure of activated sludge
flocs.
Table 26 Ceometrie porosity of activated sludge flocs - summary . -
AVERAGE POROSITY 2
(Pz)
- - -
NUMBER OF FLOCS ANALYZED
(sample size)
DIAMETER 1 (Dl 1
RANGE
SAMPLE SOURCE REFERENCE
Sample from the full- scak reactar (North
Toronto)
(Li and Ganczarczyk, 1 990)
Activated sludge flocs conditioned with various
dosages o f polynier
Activated sludge from the Main Treaiment
Plant (Toronto).
Activated sludge from the Main Treaiment
Plant (Toronto).
(Cousin, 1998)
Activated sludge froni Peterborough ' k a t nient
Plant
This siudy
3.4.3 Sonic Dispersion of Activated Sludge Flocs
In this experiment activated sludge fl ocs were dispersed with increasing arnounts of sonic
energy (fiom O - 0.9 k l l g MLSS). The effects of increasing sonic energy input on the porosity
and size of aggregates were studied. Both sonic and mechanical floc dispersion experiments
w r e nui on rhe same d ~ y . -' k s h s q ! e of acrivated sludge (2 L) was poured into the
cylindrical vessel used in the mechanical dispersion experiments (Figure 16). In order to prevent
the flocs fiom settling the sludge was agitated continuously with a paddle mixer operating at the
speed of 40 rpm. Mixed liquor samples were subjected to sonication using a Branson Soniner
(Heat Systems - Ultrasonic Inc., USA). The instrument operated at a power output of 50 Watts
and a fiequency of 20 kHz. The tip (diameter of 12.5 mm) was immersed into the mixed liquor to
a depth of approximately 10 cm (Figure 16). The activated sludge was sonicated for 10.30.60
and 90 seconds, with approximately a 5 minute interval between each sonication period. In
benveen the sonication penods, the mixed liquor was gently agitated. It was expected that during
the 5 minute slow mix the dispersed aggregates wouid have completely reflocculated to their
original size. The AME transducer attached to the side of the vessel (Figure 16) measured the
average amplitude (arnp) of activated sludge oscillation decay recorded between 0.6 and lms
after the initial stimulus (Milltronics, Peterborough, Canada). Cherek and Bleszynski (1996)
found this amplitude proportional to the suspended solid concentration of various sludges.
Pre~aration of floc sam~les. After every sonication penod a sample of sludge (about 6 ml) was
withdrawn h m the vessel. Al1 the samples were taken fiom a depth of about 10 cm. The
samples were processed as described earlier in Chapter 3.4.2.
3.4.3.1 Data Processing
The Bioquant IV image analysis system was used to measure DIAMETER 1 (Di),
DIAMETER 2 (DI), POROSITY 2 (Pl), POROSITY 3 (P3) and POROSITY 4 (Pd). Basic
statistic and analysis of variance of al1 data were conducted using SAS.
Effects of sonication on size and ~orositv of activated sludae flocs. The cross-sectionai
areas of about 200 flocs were measured before and after every sonication period with the
Bioquant N image analysis system. The sizes of flocs were log-normally distributed. The
logarithmic mean diameters of floc (D2 ) are Iisted in Table 27. Appendix 8 contains the results
of analysis of variance for floc sizes. Although a small decrease in the circular diarneter (D ?)
was observed after a sonication period of 60 seconds, the differences in floc size were not
significant. It seemed that sonication dispened the largest flocs ody. For example. the largest
flocs after 60 s of sonication were about 100 pm smaller than those in the initial sample. It is
possible that the breakup of smaller (and stronger) fiocs was not observed due to the low acoustic
energy levels applied.
The average geometric porosity (Pz) of 150 activated sludge flocs analyzed in this
experiment varied fiom 7 -28 % (Table 28). After the sludge was sonicated for 30 to 60
seconds, the porosity of flocs increased 2.5 times. It is important to note that the actual porosity
increase could have been smaller because the same sludge sample was used in d l sonication
experiments. The analysis of the POROSITY 3 (P3 - descnbing small pores) and POROSITY 4
(P4 - describing large pores) indicated that the increased sonication time had a significant effect
on the size of both large and small pores. However, the rapid increase of the average geornetric
porosity of activated sludge flocs was mainly due to the size increase of large pores (Table 29
and Table 30). After 90 seconds of sonication, the porosity decreased and the size of flocs
increased. During the subsequent reflocculation period, the size and the geomeeic porosity of
flocs did not change significantly. It was suspected, therefore, that after 90 seconds of
sonication, the flocs m u t have rapidly refiocculated during sampling, preventing the observation
of the size and the porosity changes (this hypothesis was M e r substantiated by the continuous
decrease of the oscillation amplitude of the insonified sludge discussed later in this chapter).
The analysis of variance indicated that the porosity of flocs changed significantly after sonication
(Appendix 9 and Table 34).
Table 27 Size @3 of activated sludge flocs after sonication
TIME OF SONICATION r DIAMETER 2
@z) Log. mean
STANDARD DEWATION
DIAMETER OF THE SMALLEST
FLOCS
DIAMETER OF THE LARGEST
FLOCS
Table 28 Geometric porosity (Pz) and size (Di ) of activated sludge flocs after sonica tion
Ab'ERAGE POROSITY 2
(PI 1
STANDARD OEVIATION
DIAMETER 1
~ @ I I Log.mean
Table 29 Geometric porosity (P3) of activated sludge flocs after sonication
TOTAL NUMBER OF SMALL PORES
524
277
476
1556
726
67 1
TIME OF SONICATION
[secl
O
10 1
30
60
90
after reflocculation
AVERAGE POROSITY 3
(P3
I%I
5
6
5
6
5
7
AVERAGE SIZE OF PORES
1pm7
3
2
3
3
3
- 7
Table 30 Geometric porosity (PI) of activated sludge flocs after sonication
TIME OF SONKATION LARGE PORES
ls-1
after refloccuiation 5
AVERAGE
Table 31 Oscillation decay and BO& of activated sludge mixed Liquor supernatant
AVERAGE TOTAL NUMBER OF POROSITY 4
Cpd [*hl
SIZE OF PORES
[lim21
B0D5 of MIXED LIQUOR
SUPERNATANT
afier sonication . TIME OF SONICATION
[s=l
O
1 O
30
60
90
AVERAGE AMPLITUDE OF DECAY
0.1 184
0.1 1 12
0.1 100
0.0900
0.0871
STANDARD DEVIATION
0.0171
0.0 150
0.0266
0.0 133
0.0072
Figure 22 shows the relationship between the size and porosity of activated sludge flocs, and the
acoustic energy input in the experiments. By increasing the sonication time up to 60 seconds, the
geometnc porosity more than doubled. This significant increase in the porosity of flocs, without
an apparent change in the floc size, m u t have been accompanied with the significant change in
the natural structure of the aggregates. Previous reports indicated that the sonication of activated
sludge flocs release extracellular polymen into the surroundhg liquid phase (King and Forster,
1990; Quarmby and Forster, 1995). It is unlikely that the ceil membranes were ruptured at the
0.9 kJ/g SS, i.e. the maximum sonic energy input applied in this experiment since about 36 kJ/g
SS was required to disperse activated sludge floc into microcolonies (Biggs and Lant, 2000). To
investigate m e r the effects of sonication on activated sludge flocs, the response signal of the
insonified mixed liquor was measured immediately f i e r each experiment.
3.4.3.3 Effects of Sonication on Response Oscillation of the Activated Sludge
The AME transducer attached to the vesse1 containing the activated sludge recorded the
average amplitude of the mixed liquor response signal. This signal decreased with the increasing
time of sonication (Table 3 l), and the change was statistically significant (Appendix 10). Since
the intensity of this signal is proportionai to sludge concentration, the results suggested that with
longer sonication penods the mixed liquor became less concentrated. ui the batch experiment
this couid only be explained by the dissolution of some material (most likely extracellular
polymers) from the aggregates' matrix into supernatant. To m e r nibstantiate this hypothesis,
the Biochemicai Oxygen Demand (BOD5) of the insonified mixed liquor supernatant was
determined (Table 3 1). To separate the flocs from the supernatant, samples of mixed liquor were
111
cenhifuged (2000 rpm, equivalent to 487 g, for 10 minutes) after each sonication period. As
expected. the BODs of the activated sludge supernatant increased with longer sonication penods.
This change indicated an increase in the biodegradable content of the supernatant, possibly due
to the release of extracellular polymers frorn the activated sludge floc ma&. It is important to
note that a mass balance of the carbohydrate and protein content in the flocs and the supernatant
would have provided definite proof of this hypothesis. However, because of the cornplex
chernical composition of extracellular polymer material, such a calculation would require
analysis beyond the scope of this study. It is important to note that release of polymenc matenal
&oom the floc matrix could have resulted in clogging of mal1 pores inside a floc, yet the decrease
in the size of small pores was not observed.
Bien et al. (1997) reported that the poiymen used to condition sludge prior to dewatenng
stretched and becarne less branched &er an ultrasound application. Long, metched polymer
chains fomed more open floc structures, containing very large pores. Similarly. the extracellular
polymer fibnls might have stretched in the insonified activated sludge floc. This stretching of
the polyrner chains would have caused enlargement of the existing pores and formation of new
very large pores. If such a mechanism of changes to the floc structure were accepted neither
extracellular polymer release nor small pore clogging would be observed.
Figure 22 Average geometric porosity and size of flocs vs. ucoustie energy input - activated sludge flocs
-1 -40 -1 -20 -1 .O0 -0.80 -0.60 -0.40 -0.20 Keflocculatcd
Log(Sonic energy input [kJIg SS]) Flocs
3.4.3.4 EfTects of Sonication on Sierpinski Fractal Dimensions of Activated Sludge Flocs
Figure 23 shows an example of a Sierpinski plot for a single activated sludge floc.
Multiple transition points in the data line on these plots, again, indicate the presence of srnall,
medium, and large pores within a floc. Also. many plots showed the presence of additional pore
populations - very large pores with the cross-sectional area usually about 30 gmL (SF,) but quite
ofien larger than 50 pm' . This new population of extra large pores was not observed during the
reflocculation penod, therefore, the formation of these pores m u t have been a direct result of
sonication. The observed transition points indicated the approximate size of pores in activated
sludge flocs after sonication: srna11 pores <3 pn2. medium pores approxirnately 3 - 17 pn' ,
large pores < 30 pm2 and extra large pores > 30 pn' (Table 32).
Table 33 contains the Sierpinski hctal dimension for activated sludge flocs after
sonication. Excepting the 90 seconds sonication, the fkctal dimensions decreased with the increase
in the intensity of sonication, which indicates that ail four pore populations increased their sizes.
The rate of the decrease in hctal dimensions was the highea for large (S.F2.) and extra large pores
(S.F3.). For 90 seconds sonication the h c t a l dimensions were quite similar to those before
sonication (at O seconds sonication). This again confirms the hypothesis that the possible changes to
the floc structure after 90 seconds of sonication reversed back to the initiai condition.
Discussion
Sonication at very low power levels significantly increased the geometric porosity of
activated sludge flocs without chmghg their size. This most Iikely cesulted fiom the formation
of very large pores (> 30 pn2 ) created either by the release or stretching of the extracellular
polymers in the aggregates' matrk. Therefore, low energy sonication significantly changed the
naturd structure of activated sludge flocs. This was not observed when the activated sludge
flocs were subjected to mechanical dispersion. Ln conclusion, the two floc breakup procedures
investigated - sonication and mixing - had different effects on activated sludge flocs. When
activated sludge flocs are dispersed mechanically they break into lower level structures. i.e.
microflocs and flocculi. Such fragmenting did not produce a significant change in the natural
structure of the floc. In sonication. the n a d structure of microflocs and floc aggregates was
changed (Table 35). Therefore, the results of sonication experiments were not used to study the
narural porosity structure of flocs. However, low level sonication may be considered for the
purpose of changing the structure of activated sludge flocs
Table 32 ~ O C S
Size of transition pores on Sierpinski plots for fionicated activated sludge
Sonic Energy Input Average Size of the Transition
Pore on Sierpinski Plot
T.PI (1im4
Average Size of the Transition
Pore on Sierpinski Plot
T.P2 (~im'
Average Size of the Transition
Pore on Sierpinski Plot
T.P3 (P')
Not available
Not available
Table 33 Sierpinski fractal dimension for activated sludge flocs after sonication
0.86
Refiocculation
1.98
2.75
Sonication time
[secl O
10
30
60
90
7.14
16.75
Re- NO^
3 1.60
Not available
Line 1 on the Sierpinski plot
Slope
0.0095
0.0245
0.01 55
0.0 160
0.0135
S.&
1
1.9855
1.9845
1,9840
1.9865
Line 2 on the Sierpinski plot
Slope
0.0356
0.023 1
0.0426
0.0394
0.0378
S.Fi.
1.9644
1 .9769
1.9574
1.9606
1.9622
Line 3 on the Sierpinski plot
Slope
0.0426
0.0384
0.0534
Line 4 on the Sierpinski plot
S.Fz
1.9574
1.961 6
1.9466
Slope
0.0379
0.0427
S.F3=
1.9621
1.9573
0.0892
0.0359
0.0412
0.1249 1.9 1 08
1.9641
1 .9588
1.875 1
Not available
Table 34 Effec& of sonication time and the size of flocs on the geometric porosity and
B
anaiysis of variance
EFFECT OF FLOC SUE
not available
NOT-SIGNIFICANT
p = 0.4278
SfGNIFICANT
p = 0.00 12
SIGNlFlCANT
0.0014
Not tested
Nor tested
Not tested
Not tested
Sierpioski fractal
VARIABLES
POROSITY 1
POROSITY 2
POROSITY 3
POROSITY 4
SFo
SF I
SF2
SF3
?
dimensions - results of the
EFFECT OF TIME OF SONICATION
nor available
SIGNIFICANT
p = 0.000 1
SIGNIFICANT
p = 0.0033
SIGNIFICANT
0.000 1
SIGNIFICANT
p = 0.3347
SIGNIFICANT
p = 0.0006
SIGNIFICANT
p = 0,0068
SIGNlFlCANT
p = 0.000 1
Table 35 Size of pores in activated sludge flocs
1 PORES 1 ACTWATED SLUDGE FLOCS 1
LARGE >20
SMALL
MEDrUM
1 EXTRA LARGE 1 Not present 1 >30 1
PORE AREA IN MECHANICAL DISPERSION
[Pm2 1 < 3
3 -20
PORE AREA IN SONICATION EXPERIMENT
[Pl2 1
<3
3 - 1 7
4. COMPARISON OF SOME PROPERTIES OF ALUM COAGULATION AND ACTIVATED SLUDGE FLOCS
In this chapter the geomeûic porosity and other properties of alum coagulation and
activated sludge flocs are compare& Based on the size of the pores, structural modrls for both
types of flocs are proposed. The specific structure of a floc determines its hydrodynamic
behaviour. Observed settiing behaviour of alun coagulation and activated sludge flocs support
the models proposed for these aggregates.
4.1 Cornpanson of the Sizes of Alum Coagulation and Activafed Sludge Flocs
Figure 24 shows the typical size distributions for aium coagulation and activated sludge
flocs. Generally. alurn flocs, with an average diarneter (D2) of about 94 p. were smaller than
activated sludge flocs, with an average diameter of approximately 1 19 p.
Also the distribution of aium flocs indicated a narrower range of sizes than those of the
rnicrobial aggregates. For exarnple. the smallest alun flocs were 10 times larger than the
srnailest activated sludge flocs.
Figure 24 'I'ypieal floc sizc distril~uiions for alum coligulrtion and rctivuted sliidge flocs
ALUM COAGULATION FLOC SlZE DISTRIBUTION
O 1 O0 200 300 400 500
Equivalent Circular Diameter [microns]
ACTIVATED SLUDGE FLOC SlZE DISTRIBUTION
O 3 00 200 300 400 500
Equivalent Circular Diameter [microns]
4.2 Cornpanson of the Average Geometric Pomity of Alum Coagulation and Activated Sludge Flocs
POROSITY 2 (Pz) varied fiom 9 - 17 % for alum coagulation flocs, and from 3 - 8% for
activated sludge flocs. During the analysis of alum coagulation flocs the BIOQUANT IV system
failed, therefore, two different image analysis systems were used to determine the geometric
porosity of flocs; BIOQUANT IV was used for measuring activated sludge flocs and GLOBAL
LAB IMAGE, for alum coagulation flocs. Because it was suspected that the measured porosity
value depended on the image analysis system used, the results produced by the two versions of
the software were compared. The geometric porosity of 15 randomly selected alum coagulation
and activated sludge flocs was determined with both image analyzers (Table 36) As expected.
the results differed significantly depending on the software used (Appendix 1 1). Overall, the
geometric porosity measured with BIOQUANT IV was always about 5% lower than that
measured with Global Lab Image. This difference was mainly due to different estimations of the
area of large pores (POROSITY 4 in Table 36).
In Table 37 the average values of the geometric porosity of alun coagulation and
activated sludge flocs are surnmarized. The measured geornetric porosity of alun coagulation
flocs was always higher than that of activated sludge flocs. However, after correcting for the
different image analysis systems used for the measurements, the average porosity of both types
of flocs was found to be very similar. The size of the primary particles in these aggregates is also
sirnilar. The size of kaolin clay particles (a primary particle in the alun coagulation floc in this
study) is approximatel y 3 pn (Craig, 1 987) and the approximate size of microorganisms in the
activated sludge floc is similar about 2.5 p (Jorand et al., 1995). Therefore according to
Equation 14 permeability of alum coagulation and activated sludge flocs should be similar.
Table 36 Comparison of geometric porosity determined with different image analysis
SYSTEM
systems
IMAGE ANALYSIS 1 POROSITY 2
Table 37 Comparison of the geometric porosity of alum coagulation and activated
POROSITY 3 POROSITY 4
--
Global Lab Image
Bioquant TV
sludge flocs
TYPE OF FLOC
s = standard deviation (baseci on i 5 measurernents j
21.0
(s = 9.3) 14.2
(s = 7.8)
-
Alum Coagulation
Flocs (Global Lab
Image)
Activated
4.5
(s = 1.9) 4.3
(s = 2.1)
Sludge Flocs (Bioquant IV)
16.7
(s = 9.4) 12.5
(s = 7.8)
GEOMETRiC GEOMETRIC ENERGY POROSITY 3 POROSITY 4
INPUT (PSI (Pd
0.162 1 Not available 1 5 1 2 1 4
--
0.003
0.045
0.401 1 Not available 1 5 1 1 1 4
0.779 1 Not available 1 6 1 1 1 6
1.392 1 Not available 1 6 1 2 1 6
- - -
4 Not available
Not available
3 1
8 4 5
4.3 Cornparison of the Dmg Acting on SeMng AIum Coagulation and Activated Sludge Flocs
The drag force correction (a) acting on a settling floc depends on the size and
permeability of that floc (Equation 7. 8 ,9 and 10). Shilar permeability of alun coagulation
and activaied sludge flocs suggests the sertling ntes of these aggregates would depend only on
the size and density of these flocs. The size, effective density and settling velocities of alum
coagulation and activated sludge flocs as determined in the free settling tests are show in Table
3 8.
Table 38 Settling Rates of Alum Coagulation and Activated Sludge Flocs
FLOC CHARACTERISTIC 1 ALUM COAGULATION ( ACTIVATED SLUDCE
SlZE (D3)
According to the Stokes' Law, the activated sludge flocs in Table 38 should sertle three times
quicker than alun flocs. The experimental obsewations indicate that the activated sludge flocs
settle five times faster than alum flocs. This can only be possible if the drag force acting on the
alum flocs is higher than that acting on the activated sludge floc.
SETTLINC RATE
Icds 1
(Gorczyca, i 99 1 )
339
(Ganczarczyk 1995)
700
0.07 0.38
The hydrodynamic drag force acting on an aggregate is one of the factors that detemine the
extent of the deformation or change in the shape of a floc during its settling. The shape of a floc
can be described by a shape factor:
Shape faftor = 4nA/p2 Equation 59
A - cross-sectional area of a floc section
p - perimeter of a floc section.
The shape factor for a circle is 1, and for a Iine is O. The shapes of alum coagulation and
activated sludge flocs were measured on aggregates in their stable position (agar embedded) and
during their settling. The cross-sectional area and perimeter of flocs were determined from the
digitized photographs of the settling aggregates (Figure 3) with the BIOQUANT IV image
analysis system. The aggregates changed their shapes during settling, and this was represented
by a new se~iing shape factor (Figure 25 and Figure 26). The settling shape factors for aium
coagulation flocs were sometirnes 6 times larger than those measured for the same aggregates in
their stable position (agar-embedded). The high values of the settiing shape factors for alum
flocs suggests that these flocs changed their shapes from discs (for the flocs in stable position) to
more sphericai foms (during the sealing of flocs). For the activated sludge flocs. the increase in
the shape factor during senling was also observed, but this increase was much smaller than that
for alum coagulation flocs. The extent of the deformation of an aggregate is related to the
magnitude of the drag force exerted on the floc, a force that in turn depends on the permeability
of the aggregate. Since the deformation of alum coagulation flocs was larger than that for
activated sludge flocs, it suggested that the drag force exerted on aium flocs during settling was
also higher. The higher drag force indicates a relatively low flow through alum flocs. Since the
drag on activated sludge floc is low, activated sludge flocs m u t be more permeable than alun
flocs. Yet the average porosity of alum coagulation and activated sludge flocs were determined
to be almost the same. Two aggregates with the same porosity can have different permeability
only if the flow through the aggregates does not occur in al1 pores. In other words, only certain
groups of pores are capable of conductirrg liquids. These pores are referred to as water chunnels.
Figure 25 Shape factors vs. floc size for alurn coagulation flocs
Settllng shape
Stable condit ion shape
10 105 175 245 315 385 4 5 5
Equivalent circular diameter [ microns]
Alum floc in s table position
c>
D u r i n g settling
H i g h d r a g
L o w flow
4.4 Companson of the Pore Sizes in Alum Coagulation, Activated Sludge Flocs and Biofilms
Both types of flocs indicated the presence of at least three populations of pores: small,
medium and large. The approximate cross-sectional area of these pores for alun coagulation,
activated sludge flocs and biofilms are listed in Table 39. Medium pores in activated sludge
flocs are twice the size of the medium pores in alun flocs. Since observation of senling of flocs
suggested that more flow pass through activated sludge floc than through alun flocs, only
medium and large pores would be capable to form channels for advective lnmsport of fiuid in
these flocs.
Table 39 Pore cross-sectional area for alum, activated sludge flocs and biofilms
Pore population Approximate cross-sectional area [pnL]
Extra large pores 1 Not available 1 Not available
Smail pores
Medium pores
(Zahid and Ganczarczyk 1 994)
(Beer and Stoodley, 1995)
<3
IO <
The approximate pore areas reported for biofilms are also listed in the Table 39. Because
biofilms have more compact structures (Ganczarczyk, 1996) the pores in biofilms are expected to
be smaller than pores in activated sludge flocs.
Beer and Stoodley (1995) measured the flow inside the biofilms by observing rnovements
of beads injected in the biornass. Pores varying h m 4,000 - 8,000 pn2 in cross-sectional area
(extra large pores) conducted significant amount of intemal fiow in biofilms. No advective flow
129
<3
20 <
was reported b i d e of a biofilms clusters with the estunated pore area of less than 0.1 p
(small pores). The role of medium and large pores in the advective transport in biofilms was not
addressed in the paper.
4.5 Estimation of Relative Permeability and Flow Rate through Alum Coagulation and Activated Sludge Flocs
4.5.1 PermeabMy of Flocs.
The size of medium pores was different in alum and activated sludge flocs. The size of
medium pores is detennined by the size of flocculi, therefore, it is the size of the flocculi and not
the primary particle that determines aggregate's permeability. Since the medium pores in
activated sludge flocs are twice the size of the medium pores in alum coagulation flocs, the
flocculi in activated sludge floc m u t also be about two t h e s larger than the flocculi in alum
flocs. Based on the relative estimate of the size of flocculi, the permeability of activated sludge
flocs would be approximately two times higher than the permeability of alurn flocs.
4.5.2 Intra-floc Flow Rates
Intmfioc flow velocity and flow rate for a settling aggregate cm be estimated using the
Equation 16 - 18 . Table 40 shows intrafloc flow velocities caiculated using floc size and
senling velocity from Table 38 and the average value of activated sludge floc permeability
estimated by Wu et al. (1 987). Their experiments were described earlier in Chapter 2.3.
Table 40 Estîmated internal flow velocities and rates for flocs and biofilms
Intrafloc Flow Velocity
i I
Permeability - k [m'] 318
(this study) 2500
(this study) (Beer and I S t d l e y , 1995)
Alum Coagulation Floc
1,425 * 1 O "
1 Flow Rate Thmugh Flocr [ W ~ ~ S I
Activated Siudge Floc
2.850 * 10 -'
Intrafloc Flow Velocity (Logan and Hunt, 1987)
10 (this study)
Biofilms
5 * 1 0 7 (this study)
300 (Logan and Hunt,
1987)
The measured flow velocities in the biofilms at the distance of about 100 pn fiom
substratum compare well with the intrafloc velocities calculated in this thesis for activated sludge
flocs. The internal flow velocities measured for biofilms are higher most likely due to higher
velocity of the extemal flow (3.4 cm/s) as compared to the settling velocity of activated sludge
flocs (0.3 8 cm/s).
0.7 (Logan and Hunt,
1987)
The velocities inside activated sludge fiocs were significantly higher than the velocities in
microbial flocs caiculated by Logan and Hunt (1987) shown in Figure 5. Logan and Hunt (1987)
used Davies permeability model (Table 1) assuming porosity of flocs of 99.5% and size of
primary particle of 1 m. The estimates made in this study are based predominantly on
experimental results without assurning any floc permeability model.
4.5.3 Floc Penneability Model
Equation 25 representing a version of the Carman-Kozeny pemeability model that does
not include the floc porosity was used to match the experimental results of this study. The
reasons for using the above fom of the permeability rnodel are as follows:
1) the exact value descnbing floc porosity is still unknown
2) the Carman-Kozeny equation is very sensitive to the porosity estimates in the high porosity
range
The simplest square Sierpinski carpet with b=3,1=1 and N=l was assumed to represent a floc
(Figure 27). The average cross-sectional areas of activated sludge and alum coagulation flocs
detemined in the settling tests (Table 38) were assumed to be equal to the area of the carpet.
ui Table 41 permeability, pore area and cluster sizes calcuiated for the carpet depicted in Figure
27 are presented. Measured pore areas are also show in this table. The pore sizes and flow
rates calculated based on the assumed pemeability model compare quite well with the
experimental results. Any differences between the modelled and experimental resdts m u t be
due to the following simpli8ing assumptions made in the calculations:
1) Ideal Sierpinski carpets was used to describe floc aggregate and clusters. In reaiity these are
random carpets.
3) Sierpinski carpets describing al1 clusters were constnicted with the same algorithm.
Therefore. the same fracta1 dimension describes ail these clusters. The experimental data
showed that clusten building the floc represent different carpets.
Based on the assumed pemeability model, the flocculi would have diameter of 4 pm in
dum floc and 9 p in activated sludge floc.
Table 41 Permeabüity, pore area and cluster sizes for a square Sierpinski carpet
& =78 p k = 2.0890 * 10'" rn' a = 528 p' large pores measmd 20 - 1285 pm'
Floc aggregate
Cluster 3
(MICROFLOC)
activated sludge floc
d,=700 pn k = 1.6912 10" m'
4 '26 pn k = 3.3151 10-Il m' a = 58 Pm' medium pores measured 3- 69 p'
I a=42139w'
Cluster 4 (FLOCCULI)
d, = 8.6 prn k = 2.5526 10'" m2 a = 6.5 smail pores measured 0.1 - 6 pm'
Cluster 5 (MICROCOLONY)
aIum coaguiation floc
Flow rate through the settling carpet composed of cluters 1-4 [pm3/s]
d, = 38pm k = 4.8975* 10'"m' a = 124 pm2 large pores measured 10 - 578 pm'
0.7 * 10
d,=l3 pn k = 5.4446 * I 0"'m2 a = 14p.m' medium pores measured 3 - 18 pn2
&=4w k = 6.0592* 1 ~ ' ~ r n ' a = 1.5 small pores measured 0.1- 3 pmf
4.6 Cornparison of the Structures of Alum Coagulation and Activated Sludge FIocs
Figure 28 shows structural models proposed for alum coagulation and activated sludge
ilocs. As opposed to chemicd flocculation, bioflocculation is uader genetic control. This is
moa likely one of the reasons why the structures of alum coagulation and activated sludge flocs
are different. There are several benefits of microbial growth in aggregates. First, the aggregate
may form a microhabitat dlowing interactions between microorganisms. Second, growth within
an aggregate may provide protection from some predators. A third advantage of growth within
an aggregate may be that large, quickly settling aggregates will be recycled back into the reactor.
Therefore, the residence tirne of an aggregate in the bioreactor will be greater than that of a
dispersed cell. The fourth advantage of bioflocculation is that it can increase nutrient uptake
through attachent to organic materials, increased availability of organic materials at surfaces.
and improved mass transfer (Logan and Hunt. 1987). Bioflocculation has been consistently
observed to occur when substrate nears depletion. It has been shown that porosity of biofilms
decreases with depth of the biofilms due to changes in substrate availability (Zahid and
Ganczarcyk, 1994). Also pores and channels may remah open due to some form of growth
control signais between microorganisms. Clearly microorganisms are able adjust themselves to
different environmental conditions which cannot be said for inorganic particles.
The different sue of flocculi in alun and activated sludge flocs could be also attributed to
the different properties of the substance binding primary particles. Very Little information is
available on the size of arnorphous aluminium hydroxide precipitate formed during the alun
coagulation process. For the pinpose of modelling the alun coagulation process, Dente1 (1988)
assumed the maximum diameter of a1ulTilniu.m hydroxide particle to be 28 nm. On the other
hand the diametes of extracellula. fibrils in activated sludge flocs were in the range from 4 - 6
nm (Liss et al., 1996), but most irnportantly, the extracellula. fibrils cm have significant Iength
(up to seveml p) which increases their ability to entrap more primary particles.
5. CONCLUSIONS, RECOMMENDATIONS AND ENGINEERING SlGNlFlCANCE
5. f Conclusions
Based on the observations and analyses made in this thesis, the following conclusions can be
drawn:
The average mass porosity (e) of alum coagulation flocs ranged fiom 82-98%, whereas the
geometric porosity (P) of the same flocs ranged only fiom 9-1 7%. The average mas
porosity (E) of activated sludge flocs ranged from 43-99%, whereas the geometric porosity
(P) of the sarne flocs ranged only fiom 3.28%. Therefore, the exact value describing
porosity of flocs is difficult to determine. The geometric porosity data provide direct
information about the liquid phase in the floc, therefore, are more realistic than the mass
porosity data. Also, the geometric porosity data are not affected by the assumptions made
when using Stokes' Law to describe floc settling.
2. The average geometnc porosity was 9% for alum flocs and about 8% for activated sludge
flocs. The similar average porosity and size of primary particle of these aggregates
incorrectly suggested that the pemeability of these flocs is similar. Yet the direct
observations of settling rates and shapes of flocs indicated that the permeability of activated
sludge floc is higher than the permeability of alum coagulation aggregate. This suggested
that floc permeability cannot be adequately estimated based on the average floc porosity.
3. When the geometric porosity data were analyzed using a Sierpinski carpet model, three pore
populations were identified within alum coagulation and activated sludge flocs: mall,
medium and large. S m d pores had a cross-sectional area usually smaller than 3 pn2 for
both flocs. Medium pores were smaller than 10 ~II? for alun coagulation flocs, and smaller
than 20 pn2 for activated sludge flocs. The difference in the permeability of alum
coagulation and activated sludge flocs could only be explained by the difference in the size
of medium and large pores. Activated sludge flocs are more permeable than alun
coagulation flocs because the medium and large pores are larger than the same pores in dum
flocs. This difference in the pore size could not be detected with the classical analysis of the
porosity data.
4. The three pore populations - small, medium and large - identified in the hc ta l analysis of the
porosity data, indicated the presence of three structures representing - flocculi, microfloc and
floc aggregate - thus confîrming multilevel structure of flocs.
5. Based on the approximate size of small, medium, and large pores, permeability and nnictural
models were proposed for the two types of flocs studied. In these models. flocculi in
activated sludge fioc were larger than the flocculi in alum coagulation aggregates.
6. Sonication at low energy levels increased the average geometric porosity of activated sludge
flocs fiom 11% to 28 % without changing the floc size. Sonication. even at a very low
energy level, significantly changed the natural porosity and structure of activated sludge
flocs. Sonication, therefore. may be considered for the purpose of modifymg the structure of
activated sludge floc.
5.2 Recommendations
This thesis developed and applied experimental techniques to study both the porosity and the
structure of particle aggregates. The following suggests some ideas for M e r studies on particle
aggregates:
1. Knowledge of the floc permeability is the basis for the study of mass transfer in the floc.
Porosity (E) and size of unit particles building the aggregate are basic parameters required to
estimate the floc permeability (Table 1). The exact values descnbing the porosity of flocs are
difficult to determine due to experimental limitations. The size of pamcies building the
aggregate depends on the structure of that floc. It is recomrnended. therefore. to estimate
permeability of flocs using only the information on the aggregate structure. such as size of
floc and flocculi.
2. Based on the new estirnate of floc permeability the mass uptake rates for microbial flocs
should be re-calculated. An improved estimation of the floc permeability should lead to
better estimation of the drag force acting on a settling floc. The corrective factors in the
Stokes Law can be improved, making this law more applicable to predicting settling rates of
individual flocs.
5.3 Engineering SignMcance of this Study
Results of this study cm be applied to model activated sludge process based on the
substrate and oxygen utilization inside individual flocs. Another potential application includes
modelling of sludge senling.
5.3.1 Modelling of Activated Sludge Process
Hi& pemeability and flow rates through flocs estimated in Chapter 4.5 suggest that the
advective flow is the dominant mode of mass transfer inside a floc aggregate. D i f i i ve
transport would occur ody in the lower levels of aggregation structures of the flocs, that is
flocculi. microcolonies and individual cells. The size of the flocculi, rather than the size of the
entire floc aggregate, determines the diffusion path (value of x in Equation 1). With the
estvnated radius of activated sludge flocculi of less than 10 pn presence of the oxygen limited
zones in the centre of the floc (as predicted by models assuming the diffusive transport in the
floc only (Abbassi et al., 1999)) is unlikely. This explains why experiments attempting to detect
anoxic zones in activated sludge flocs were unsuccessful (Schrarnm et al., 1999).
5.3.2 Modelling of Secondary Settling
Zheng and Bagley (1999) simulated batch senting process incorporating both zone and
compression setthg. In the model, the unit volume of sludge is subjected to effective stress (P,)
141
that is equal to the difference between the shdge weight and the dynamic pressure of the fluid
flowing out fiom the dewatering sludge:
Equation 60
H- height of the solid liquid mixture undergoing compression
K2 - coefficient
Clearly, the sludge concentration and floc permeability only should determine the degree of
compression (dWH), therefore:
Equation 6 1
Zheng and Bagley (1 999) proposed the following equation expression for the coefficient Kz:
where
n2, kz - coefficients
Table 42 shows the parameten k2 and nz used to calibrate mode1 for alum and activated sludge
and properties (or combination of properties) of individual flocs as determined in this snidy.
Parameter n2 is in pretty good agreement with the inverse of the density dry sludge. Product of
the floc effective density, intrafloc velocity and floc permeability (Table 38 and 4 1) and the
value of the parameter k2 tumed out to be are quite similar. Since the intratloc velocity is a
function of floc pemeability we can assume that effective density and permeability of floc
142
determine the parameter kz. Combining Equation 62 with the expressions proposed for
coefficient k2 and nz in Table 42 we h d that the parameter K2 is indeed the function of sludge
concentration and floc permeability as suggested by Equation 61.
The cornparison of floc properties and sludge senling model parameters can provide
physical meaning to the empirical constants used in modelling of secondary clarifiers.
Table 42 Parameters used in the batch settiing models and properties of individual flocs
L
Activated Sludge Flocs
9.95 * 10"
3.62 * 10' (Zheng and Bagley. 1999)
0.71
(Li and Ganczarczyk, 1 987)
0.64
(Zheng and Bagley, 1999)
Parameter
(pf-pw) k
0<g/m4/h) Batch settling mode1 parameter k2
0<g/m4W 1/ ps
( m 3 W
Batch settling mode1 parameter n2
( m 3 W
Alum Coagulation Flocs
2 . ~ * 105
3.61 * 10'
(Zheng and Bagley, 1999)
0,4
(Gorczyca, 199 1 )
0.5
(Zheng and Bagley, 1999)
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APPENDICES
Appendix 1 Statistical design of experiments - data set
AREA OF PORES IN THE WINDOW
[pm21
5842
6384
3108
321 O
4017
471 1
4113
4283
4107
4101
400 ,
1229
WINDOW AREA
bm21 15970
20746
11102
11 102
i!Î02
11102
1 1099
1 1099
1 1099
1 1099
3832
3832
WINDOW NUMBER
1
2
1
2
1
2
1
2
1
2
1
2
FLOC ID NUMBER
1
1
1
1
1
1 w
1
1
1
1
2
2
SECTION NUMBER
1
1
2
2
3
3
4
4
5
5
1
1
Appendix 2 Statistical design of floc sampling - results of analysis of variance -. .. . . - - -
General Linear Models Procedure
1 Dependent Variable : Porosity (Pd
I Source
Floc id number
Floc section number
Window number
W indow area
-- --
Degrees of Freedom
R- square
0.7838
Sum of Squares
--
Mean Square F Value
Coefficient of Vanition
Type I Sum of Squares
0.46 1 O
0.0 1 O8
0.0 150
0.0346
Root Mean Square Eror
Mean Square F Value
I The SAS System
Nested Random Effects Analysis of Variance for Variable Porosity
1 Dependent Variable : Porosity (Pz)
Variance Source
Total
Floc id number
Floc section number
Error
I Variance Source
Total
Floc id number
Section number
Mean Square
0.01 13
0 .O922
0.0043
0.0034
Sum of Squares
Variance Component
F Value
Percent of Total
Pro ba bility>F
Appendix 3 Effects of mixing intensity on the size of alum coagulation flocs - results of
analysis of variance
The SAS System
General Linear Modeis Procedure
Dependent Variable : log@2)
I Source Degrees of Sum of / ireedam / Squares
Mode1 1 E r r a
Source Type 1 Sum of
Corrected Total
Mean Square
Root Mean Square Error
599
R- square
0.24 15
F Value Pro ba bilitpF
26.6634
Coefficient of Variation
10.1 184
Mean Square F Value Probability >F
Appendk 4 Effects of floc sue and miUng energy input on the geometric porosity of alum
coagulation flocs - results of analysis of variance
1 The SAS System 1 1 General Linear Models Procedure 1
Pro ba bility>F
0.0007
Mean (Pz)
0.0665
Dependent Variable : Porosity (PI)
l Mixing energy input (E)
Floc diameter (DI)
(E) x (Di)
F Value
33
DF
5
t
5
Source
Mode1
Enor
Corrected Total
Sum of Squares
0.0638
03503
0.3 141
Coefficient of Variation
64.0 1
Degrees of Freedom
@O
1 1
138
149
R- square
02033
Type 1 Sum of Squares
0.0121
0.025 1
0.0265
Mean Square
0.0058
0.00 18
Root Mean Square Error
0.0425
Mean Square
0.0024
0.025 1
0.0053
F Value
1.34
13.84
2.93
Pro ba bility >F
0.2494
0.0003
0.0151
Appendix 5 Sierpinski fractal dimensions (S.Fa., SoFio and S.F2.) for alum coagulation f l o ~
- results of analysis of variance .- - - - - -
General Linear Models Procedure
Dependent Variable : Log(Sierpinski Fractal Dimension)
I Sierpinski fi-act.1 dimension subscript
Degrees of Freedom
R- square
Sum of Squares
Mean Square
Coefficient of Root Mean Variation Square Error
F Value Proba bility>F
Type t II Sum / M a n Square of Squares I Va'ue Probability >F
Appendix 6 Effects of rnWg intensity on the size of activated sludge flocs - results of
analysis of variance
The SAS System
1 Ceneml Linear Models Procedure
( Dependent Variable : log(D2)
Degreesof Surnof Mean Square Freedom Squares
-
F Value
1249 10 1.8068
R- square Coefficient of Root Mean Mean log(D1) Variation Square Error
DF Type 1 Sum of Mean Square F Value Probability >F Squares
Appendix 7 EEects of floc size and miring energy input on the geometric porosity of
activated sludge fiocs - results of analysis of variance
The SAS System
General Linear Models Procedure
- -
Mean Square F Value Pro ba bi l i tpF I Source Degrees of Freedom
Mode1
Error
Corrected Total
Source
Sum of Squares
R- square
03425
l
Coefficient of Variation
Root Mean Square Error
Mean Square T F Value Type 1 Sum of Squares
Proba bility >F
Mixing energy input (E)
Floc diameter (DI )
(El x (DI)
Appendix 8 Effects of sonic energy input on the size of activated sludge flocs - results of
analysis of variance
l The SAS System
General Linear Models Procedure 1 Dependent Variable : Ii
Sonic energy input
R- square
0.0066
Coefficient of Root Mean Variation Square Error
Pro babilitpF Sum of Mean Square Squares
F Value
- - - - - -
Type 1 Sum of Mean Square Squares
0.7943 O. 1985
-
F Value
1.69
- - -
Proba bility >F
O. 1504
Appendix 9 Effects of floc size and sonic energy input on the geometric porosity of
activated sludge flocs - results of analysis of variance
The SAS System
General Linear Models Procedure
Dependent Variable : Porosity (Pr)
l Source Degrees of Freedom
R- square
0.53 17
' (DF)
I Source
Mode1
Enor
Corrected Total
1 Sonic mergy input (E) I
1 1
138
149
Coefficient of Root Mean Variation Square Error
Squares
Squares Probability >F
F Value Proba bility>F
Appendir 10 Effects of the sonic energy input on the oscillation amplitude of the activated
siudge - results of anaîysis of variance
1 The SAS System
Dependent Variable : Amplitude
Corrected Total
Source 1 Degrees of 1 Sum of M a n Square F Value
- -
-
Proba bility>F
- - -
Variation Square Enor Mean Amplitude
O. 1025
Appendix 11 Effects of image analysis software (Global Lab Image vs. Bioquant Iv) on the
value of the geometric porosity - results of analysis of variance
r The SAS System
General Linear Models Procedure
Source
R- square
0.1383
Sum of Squares
Coefficient of Variation
Mean Square F Value
Square Error
Proba bility>F
Mean Porosity 2
O, 1 724