modelling of clogging in laboratory column experiments

275
Modelling of Clogging in Laboratory Column Experiments Conducted with Synthetic Land fdl Leachate by Andrew J. Cooke Faculty of Engineering Science Civil Engineering Submitted in partial fuifilment of the requirements for the degree of Master of Engineering Science Faculty of Graduate Studies The University of Western Ontario London, Ontario, Canada September 1997 OAndrew J. Cooke 1997

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Page 1: Modelling of Clogging in Laboratory Column Experiments

Modelling of Clogging in Laboratory Column Experiments Conducted with Synthetic Land fdl Leachate

by Andrew J. Cooke

Faculty of Engineering Science Civil Engineering

Submitted in partial fuifilment of the requirements for the degree of

Master of Engineering Science

Faculty of Graduate Studies The University of Western Ontario

London, Ontario, Canada September 1997

OAndrew J. Cooke 1997

Page 2: Modelling of Clogging in Laboratory Column Experiments

National Library I * m of Canada Bibliothèque nationale du Canada

Acquisitions and Acquisitions et Bibliographie Services services bibliographiques

395 Wellington Street 395. rue Wellington OttawaON K1AON4 OttawaON K1AON4 Canada Canada

Yow filn Votre reulsnce

Our hb Notre reYrem8

The author has granted a non- L'auteur a accordé une Licence non exclusive licence allowing the exclusive permettant à la National Library of Canada to Bibliothèque nationale du Canada de reproduce, loan, distribute or sell reproduire, prêter, distribuer ou copies of this thesis in microform, vendre des copies de cette thèse sous paper or electronic formats. la fome de microfiche/6ilm, de

reproduction sur papier ou sur format électronique.

The author retains ownership of the L'auteur conserve la propriété du copyright in this thesis. Neither the droit d'auteur qui protège cette thèse. thesis nor substantial extracts fiorn it Ni la thèse ni des extraits substantiels may be printed or otherwise de celle-ci ne doivent être imprimés reproduced without the author's ou autrement reproduits sans son permission. autorisation,

Page 3: Modelling of Clogging in Laboratory Column Experiments

ABSTRACT

A numericd model has been developed for predicting the rate of clogging in

column experiments conducted using synthetic landfi11 leachate as part of a broader study

of the clogging processes occurrïng in landfill leachate collection systems. Consideration

is given to biological growth and biochemically driven minerai precipitation. The model

represents the porous media flow system as a collection of elements in which each element

acts as a separate, fixed film reactor. By applying biological process and geotechnical

engineering concepts to the system, the model predicts the substrate utilization, growt h

and decay of biofilm, and accumulation of inert biomass and calcium carbonate on the

porous media at any tirne, or position, dong the length of the column. The model is

applied to two series of experiments and is show to be successfiil in predicting substrate

removal, biofilm thickness and porosity.

Keywords: Numerical modelling, Clogging in drainage systems, Synthetic leachate,

Porous mediq Biofilm, Mineral precipitation, Landfill.

Page 4: Modelling of Clogging in Laboratory Column Experiments

ACKNOWLEDGEMENTS

The author wishes to express his appreciation and gratitude to his supervisor, Dr.

R Kerry Rowe, who provided patient and continual guidance, advice and encouragement

throughout the duration of this research.

The author would also like to acknowledge Dr. Bruce E. Rittmann for his insight,

guidance, and encouragement.

Sincere appreciation is expressed to 1. Fleming, M. Armstrong, L. Hrapovic, Dr.

R. Cullimore, S. Millward, and J. vanGulck for their assistance and for perforrning the

laboratory column tests with synthetic leachate that are modelled in this thesis. In

addition, R. Brachman provided much advice and support, and the faculty, staff and

graduate students at the Geotechnical Research Centre were always available for

assistance when needed; their contributions are much appreciated.

This study was supported by the Natural Sciences and Engineering Research

Council of Canada under Collaborative Research Grant CPG 0 163097.

Finally, the author wishes to thank his family and fkiends for their love and support

throughout the course of this study.

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TABLE OF CONTENTS

CERTIFICATE OF EXAMINATION . . . . . . . . . . . . . . . . . . .

ACKNOWLEDGEMENTS . . a . .

TABLEOFCONTENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

LIST OF APPENDICES . . . . . . . . . . . . . . . . . . . .

NOMENCLATURE . . . . . . . . . . . . . . . . . . . . . . . . . xix . . . . . . .

CaAPTER 1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 LANDFILLING 1 1.2 DRAINAGE SYSTEM CLOGGINC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 COLUMN TESTS 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 O ~ C T M 5 1.5 THESIS OUTLINE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

CHAPTER 2 MODELLiNG TBE BIOLOGICAL CLOGGING IN COLUMN EXPERlMENTS FED SYNTHETTC LEACaATE . . . . . . . . . . 10 2.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2 B A ~ E R I U M . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.2.1 Dimensions and Classification . . . . . . . . . . . . . . . . . . . . . . . . 13 2.2.2 Growth 14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.3 FORMATION OF A BIOLOGICAL GROWTH ENVIRONMENT . . . . . . . . 15 2.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.3.2 Chernical and Biochemical Oxygen Demand . . . . . . . . . . . . . 16 2.3.3 Landfil1 Leachate and the L.C.S. Environment . . . . . . . . . . 16

2.3.3.1 Leachate Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3.3 -2 The L.C. S . Environment . . . . . . . . . . . . . . . . . . . . . . . . 17

2.3.4 Synthetic Leachate and the Column Test Environment . . . . 18 2.4 THE CLOGGING PROCESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

2.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.4.2 Biological Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

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3.4.7.5 Numencal Solution of Rhombic Model Shape for Volume and Surface Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

3.4.7.6 Corrective Model Solutions for Porosity and Specific . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Surface 53

3.4.8 Derivation of the Special Cap Mode1 Solution . . . . . . . . . . . 55 3.4.8.1 Porosity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.8.2 Specific Surface 56 3.4.9 Derivation of Final Corrected Equations . . . . . . . . . . . . . . . . 57

3.4.9.1 Base Equations . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.4.9.2 Corrected Equations for Cubic Packing . . . . . . . . . . . . . 58

. . . . . . 3.4.9.3 Corrected Equations for Orthorhombic Packing 58 3 -4.9.4 Corrected Equations for Tetragonai-Sphenoidal Packing

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 . . . . . . 3.4.9.5 Corrected Equations for Rhombohedral Packing 61

. . . . . . . . . . . . . . . . . . . . 3.4.10 Note Regarding Taylor et al . (1990) 62 3.5 FILM TH~CKNESS AT CLOGG~NG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

3.5.1 Pore Discontinuity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 S ~ Y 64

CHAPTER 4 . . . . . . . . . . . . . . . . . . . . . . . . . . CLOGGING MODEL: FORMULATION 81

4.1 ~NTRODUC~ION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.2 REPWSENTATION OF COLUMN FLOW . . . . . . . . . . . . . . . . . . . . . . . . 81

4.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 . . . . . . . . . . . . . . . . . . . 4.2.2 Representation of the Porous Media 82

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Boundary Conditions 83

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.4 Advection Algorithm 83 4.2.4.1 introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

. . . . . . . . . . . . 4.2.4.2 Caiculation of Fluid Travel Time Delays 84 . . . . 4.2.4.3 Management o f Calculated Effluent Concentrations 85

4.4 BIOLOGICAL PROCESSES WITHXN ELEMENT . . . . . . . . . . . . . . . . . . . . 88 4.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 4.4.2 Process Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.4.3 Biofilm Idealization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.4.4 Calculation of Substrate Flux . . . . . . . . . . . . . . . . . . . . . . . . . 90

. . . . . 4.4.5 Calculation of Biofilm and Mineral Growth and Loss 94 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.5.1 Introduction 94

. . . . . . . . . . . . 4.4.5.2 Non-Steady Growth and Loss of Biofilm 95 4.4.5.3 Minerai Precipitation and Inert Biomass Accumulation . 96

. . . . . . . . 4.4.6 Calculation of Porosity and Speeific Surface Area 99 4.4.7 Convergence to Revised Effluent Substrate Concentration

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4.4.7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4.4.7.2 Application of a Second Substrate . . . . . . . . . . . . . . . . 101 4.4.7.3 Mass Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IO1

vii

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LIST OF TABLES

Table

2.1

3.1

3.2

3 -3

3 -4

Description Page

Conditions afEecting rnethanogenesis in landfills (Farquhar. 1989) . . 18

Characteristics of Packing of Uniform Spheres . . . . . . . . . . . . . . . . . 38

Surnrnary of Critical Film Thicknesses in Terms of 2Lt / d, . . . . . . . 45

Corrective Models and Corresponding Film Thickness (2Lt / d, ) . . . 48

Surnrnary of Film Thicknesses at Pore Discontinuity in Tems of .. 2L,/dp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calculated variables for advection algorithm example . . . . . . . . . . . . 87

Porosity and Specific Surface Equation Summary . . . . . . . . . . . . . . 121

Summary of Convergence Routine Details . . . . . . . . . . . . . . . . . . . . 122

Experiment Flow Rates and Muent Substrate Concentration . . . . . 130

. . . . . . . . Given Mode1 Parameters (Rittmann and McCarty. 1980) 131

Assumed Mode1 Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132

Parameter Sensitivity Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

Directly Measured Input Parameters . . . . . . . . . . . . . . . . . . . . . . . . 147

Indirectly Measured Input Paramet ers . . . . . . . . . . . . . . . . . . . . . . . 150

Assumed Mode1 Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153

Variable Mode1 Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154

Composition of Synthetic Keele Valley Leachate (Millward. 1997) . . 163

Surnrnary of reported Monod kinetic constants for anaerobic degradation of propionic and acetic acids by various mixed cultures ' 164

Summary of Critical Film Thicknesses in Terms of 2Lt I d, . . . . . . . . 235

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LIST OF FIGURES

Figure Description Page

1.1 Typical two liner, two leachate collection system Iandfill. . . . . . . . . . 8

1.2 Granular leachate collection system drainage layer and, (Inset) unsaturated and saturated zones of the drainage path with dominant flow paths shown. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.1 Common idealization of biofilm structure (Characklis and Marshall, 1990). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

2.2 (a) Formation of iron sulphide on sulphate reducing bacteria, (b) Formation of carbonate on methane bacteria (Brune et al., 199 1). 3 5

3.1 The four stable, regular packing arrangements, illustrated as faces of the unit cell. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

3.2 Variation of porosity with film thickness using equations by Taylor et al. (1990). Symbols indicate mode1 breakdown due to the occurrence of volume overlaps. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

3.3 Variation of normalized specific surface area with film thickness using equations by Taylor et al. (1990). Symbols indicate model breakdown due to the occurrence of volume overlap. . . . . . . . . . . . . 68

3.4 Verification of length of radius of interface circle at any contact point . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

3.5 Verfication of film thickness at onset of spherical cap overlap for cubic packing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

3 -6 Verification of film thickness at complete occlusion of cubic packing. . . . . . . . . . Double hatched area indicates overlap of spherical caps. 71

3 -7 Verification of film thickness at occurrence of first overlap for orthorhombic packing. Hatched area indicates spherical cap at two contacts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

3.8 Overlap shapes used in corrective models. The shapes depicted, named according to the face in which they occur, are (a) Square, @) Rhombic, and (c) Special Rhombic Spherical Cap Overlap. . . . . . . . 73

3.9 Diagram of shapes for volume and surface area integration. . . . . . . . 74

3.10 Curve fit to normalized volume of overlap as a fùnction of d'Et for the square corrective model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

xii

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Curve fit to normdized surface area of overlap as a function of a/R . . . . . . . . . . . . . . . . . . . . . . . . . . . for the square correction model.

Curve fit to normalized volume of overlap as a function of aR for . . . . . . . . . . . . . . . . . . . . . . . . . . . . . the rhombic corrective model.

Curve fit to normalized surface area of overlap as a function of aR for the rhombic corrective model. . . . . . . . . . . . . . . . . . . . . . . . . .

Corrected variation of porosity with film thickness. Symbols indicate the beginning of corrective models, pore discontinuity and curve tennination. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Corrected variation of normalized specific surface with film thickness. Symbols indicate the beginning of corrective models, pore

. . . . . . . . . . . . . . . . . . . . . . . . discontinuity, and cuve termination.

(a) Column test apparatus, (b) flow field column test modelling, (c) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . one element (or "segment").

Method of retrievd of effluent concentrations for advection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . algonthm.

Flow diagram of processes performed for each element of the flow field during each tirnestep (optionai secondary substrate processes

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . omitted).

(a) Idealized biofilm and thicknesses, (b) substrate concentration . . . . . . . . . profiles (modified fiom Rittmann and McCarty, 1980a).

. . . . . . . . . . . . . . . . . Flow diagrarn of primary processes of model.

Effect of timestep length dt on predicted effluent Acetate . . . . . . . . . . . . . concentration for test BC 1 using mean pararneters.

Effect of timestep length dt on predicted effluent Acetate . . . . . . . . . . . . . concentration for test BC3 using mean parameters.

Effect of number of segments on predicted effluent Acetate . . . . . . . . . . . . . concentration for test BC 1 using mean pararneters.

Measured Acetate concentration profile dong the length of the column at steady-state and initiai predictions using mean pararneters for test BCl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measured Acetate concentration profile along the length of the colurnn at steady-state and initial predictions using mean pararneters fortestBC3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

S..

Xlll

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Measured Acetate concentration profile dong the length of the colurnn at steady-state and fined predictions using Ks = 4.48 mg/L

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . and b = 0.254 d" for test BCI.

Measured Acetate concentration profile dong the length of the column at steady-state and fitted predictions using Ks = 4.48 mglL

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . and b = 0.254 d" for test BC3.

Measured biofilm thickness profile dong the length of the column at steady-state and fitted predictions using Ks = 4.48 mgR. and b = 0.254 d" for test BC1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measured biofilm thickness profile along the length of the column at steady-state and fined predictions using Ks = 4.48 mg/L and b = 0.254 d" for test BC3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measured Acetate concentration profile along the length of the column at steady-state and effect of difision layer thickness LI on fitted predictions using Ks = 4.48 mgL and b = 0.254 d" at 28 days

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . for test BC3.

Measured Acetate concentration profile along the length of the column at steady-state and effea of diffusion layer thickness L, on fitted predictions using Ks = 4.48 mgL and b = 0.254 d" at 28 days for test BC3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measured Acetate concentration profile along the length of the column at steady-state and effect of diffusion coefficient D, on fitted predictions using Ks = 4.48 m g L and b = 0.254 d-' at 28 days for testBC3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measured Acetate concentration profile dong the length of the column at steady-state and effect of detachment method on fitted predictions using Ks = 4.48 mg/L and b = 0.254 d-' at 28 days for testBC3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measured calcium carbonate removed versus COD removed and calculation of calcium carbonate yield coefficient Y, by linear regression for colurnns fed synthetic leachate. . . . . . . . . . . . . . . . . .

Reported measured half-velocity coefficient, Ks, versus system temperature for bacterial growth in propionate and acetate (various sources, see Table 5.10). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Reported measured maximum specific substrate utilization rate, q, versus system temperature for bacterid growth in propionate and

. . . . . . . . . . . . . . . . . . . . acetate (various sources, see Table 5.10).

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Reported measured yield coefficient, Y, versus systern temperature for bacterid growth in propionate and acetate (various sources, see

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Table 5.10).

Reported measured decay coefficient, b, versus system temperature for bacterial growth in propionate and acetate (various sources, see

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Table S. 10).

Measured and initiaily predicted nomalized effluent concentration using q = 4 mgCOD1mgVS-d for propionic acid and q = 4 mgCOD/mgVS-d for acetic acid for colurnn tests fed synthetic

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . leachate.

Measured and initially predicted porosities using q = 4 mgCOD/mgVS-d for propionic acid and q = 4 mgCOD/mgVS-d for acetic acid after 220 and 270 days of operation of columns fed synthetic leachate. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measured normalized etnuent concentration and model prediction using q = 3 mgCOD/mgVS-d for propionic acid and q = 4 mgCOD/mgVS-d for acetic acid for column tests fed synthetic

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . leachate.

Measured porosities and model predictions using q = 3 mgCOD1mgVS-d for propionic acid and q = 4 mgCOD1mgVS-d for acetic acid after 220 and 270 days of operation of colums fed synthetic leachate. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measured normalized effluent concentration and the effect of timestep length dt on mode1 predictions using q = 3 mgCOD/rngVS-d for propionic acid and q = 4 mgCOD/mgVS-d for

. . . . . . . . . . . . . . acetic acid for column tests fed synthetic leachate.

Measured porosities and the effect of timestep length dt on model predictions using q = 3 mgCOD1mgVS-d for propionic acid and q =

4 mgCOD/mgVS-d for acetic acid after 220 and 270 days of . . . . . . . . . . . . . . . . . . operation of columns fed synthetic leachate.

Measured normalized effluent concentration and the effect of the number of segments on model predictions using q = 3 mgCODImgVS-d for propionic acid and q = 4 mgCOD1mgVS-d for

. . . . . . . . . . . . . . acetic acid for column tests fed synthetic leachate.

Measured porosities and the effect of the number of segments on model predictions using q = 3 mgCODIrngVS-d for propionic acid and q = 4 mgCOD/mgVS-d for acetic acid after 220 and 270 days of operation of columns fed synthetic leachate. . . . . . . . . . . . . . . . . . .

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Measured normalized effluent concentration and mode1 predictions using q = 3 mgCODImgVS-d for propionic acid and q = 3.9 mgCOD1mgVS-d for acetic acid for column tests fed synthetic

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . leachate.

Measured porosities and model predictions using q = 3 mgCOD/mgVS-d for propionic acid and q = 3.9 rngCOD1mgVS-d for acetic acid after 220 and 270 days of operation of columns fed

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . synthetic leachate.

(a) Measured porosities and model predictions using q = 3 mgCOD1mgVS-d for propionic acid and q = 3.9 mgCODlmgVS-d for acetic acid d e r 130 days of operation and @) porosity profiles at

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 day intervals.

Variance of predicted propionate degrader film thickness at specified . . . . . . . . . . . . . . . . . . . . . . . . . . . . column heights (Ht) over tirne.

Variance of predicted acetate degrader film thickness at specified . . . . . . . . . . . . . . . . . . . . . . . . . . . . column heights (Ht) over tirne.

Variance of predicted total inactive film thickness at specified . . . . . . . . . . . . . . . . . . . . . . . . . . . . column heights (Ht) over time.

Variance of predicted effluent COD concentrations of propionic . . . . . . . . . . . . . . . . . acid, acetic acid, and the total COD over time.

Predicted (a) propionate and @) acetate COD concentration profiles . . . . . . . . . . . . . . . . . . . . . . . . along the column at 50 day intervals.

Predicted (a) propionate and (b) acetate degrader film thickness . . . . . . . . . . . . . . . . . . profiles along the column at 50 day intervals.

Predicted propionate and acetate degrader film thickness profiles . . . . . . . . . . . . . along the column at (a) 220 days and (b) 270 days.

Variance of predicted detachment coefficient b' at specified column . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . heights (Ht) over time.

Predicted propionic, acetic and total COD profiles along the column . . . . . . . . . . . . . . . . . . . . . . . . . . . at (a) 220 days and @) 270 days.

Predicted inactive and total film thickness profiles dong the column . . . . . . . . . . . . . . . . . . . . . . . . . . . at (a) 220 days and (b) 270 days.

Variance of predicted total and inactive film thickness at the influent (Seg. 1) and effluent (Seg. 13) ends of the

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . column over time.

Page 17: Modelling of Clogging in Laboratory Column Experiments

5.41

5 -42

5 -43

5 -44

Al. 1

Al .2

A1 -3

A1.4

Variance of predicted total film thickness at specified column heights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . wt)overtime

Variance of predicted total active film thickness at specified column . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . heights (Ht) over time.

Variance of predicted detachment rates for propionate degraders at specified colurnn heights (Ht) over time. . . . . . . . . . . . . . . . . . . . . .

Variance of predicted detachment rates for acetate degraders at specified column heights (Ht) over time. . . . . . . . . . . . . . . . . . . . . .

Venfication of length of radius of interface circle at any contact point . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Verification of film thickness at onset of sphencal cap overlap for . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . cubic packing.

Verification of film thickness at complete occlusion of cubic packing. Double hatched area indicates overlap of spherical caps. . . . . . . . . .

Verification of film thickness at occurrence of first overlap for orthorhombic packirig. Hatched area indicates sphencal cap at two contacts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Verification of film thickness at occurrence of second overlap for orthorhombic packing. Double hatched area indicates overlap of

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . sphencal caps.

Verification of film thickness at pore space occlusion for . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . orthorhombic packing.

Verification of film thickness at onset of special sphencal cap overlap for tetragonal-sphenoidai packing.

Verification of film thickness at onset of complex overlaps for tetragonal-spheroidal packing. Special spherical cap shown in centre ofsection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Venfication of film thickness at pore occlusion for . . . . . . . . . . . . . . . . . . . . . . . . . . . . . tetragonal-sphenoidal packing.

Verification of film thickness at onset of complex overlaps for . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rhombohedral packing.

Verification of film thickness at onset of pore occlusion for . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . rhombohedral packing.

Page 18: Modelling of Clogging in Laboratory Column Experiments

LIST OF APPENDICES

Appendix Title Page

Al DETERMINATION OF CRITICAL FILM THICKNESSES OF THE POROSITY AND SPECIFIC SURFACE MODELS . , . . . 2 19

Page 19: Modelling of Clogging in Laboratory Column Experiments

NOMENCLATURE

Symbol Definition Dimension

Radial distance to overlap

Specific surface of porous media

Initiai, clean media specific surface

Specific surface calculated using Taylor et al. (1990)

Biornass decay coefficient

Total biornass loss coefficient

Biomass detachment coefficient

Diameter of porous media particle, Stone or sphere

Molecular diffision coefficient of the substrate in the Liquid

Molecular diffusion coefficient of substrate 1 in the liquid

Molecular difision coefficient of substrate 2 in the liquid

Dimensionless molecular difision coefficient of the substrate in the iiquid

Molecular difision coefficient of the substrate within the biofilm

Molecular diffusion coefficient of substrate 1 within the biofilm

Molecular diffision coefficient of substrate 2 within the biofilm

Dirnensionless moIecular difiùsion coefficient of the substrate within the biofilm

Fraction of biomass degradable due to decay

Flux of substrate into the biofilm

Flux of the substrate 2 (propionic acid) into the biofilm

Dimensionless flux of substrate into the biofilm

Segment number

Detachent coefficient

Page 20: Modelling of Clogging in Laboratory Column Experiments

Endogenous decay coefficient

Maintenance coefficient

Half - maximum rate substrate concentration

Half-maximum rate substrate concentration for substrate 1

Haif-maximum rate substrate concentration for substrate 2

Thickness of active biofilm

Dimensionless thickness of the active biofilrn

Revised active biofilm thickness

Active biofilm thickness caused by substrate 1

Active biofilm thickness caused by substrate 2

Revised active biofilm thickness caused by substrate 2

Critical film thickness

Thickness of inactive film layer

Revised inactive film thickness

Total initial active biofilrn thickness

Inactive biofilm thickness caused by substrate 1

Inactive biofilm thickness caused by substrate 2

Revised inactive film thickness caused by substrate 2

Thickness of diffusion layer

Dimensionless thickness of diffusion layer

Total film t hickness (L, = Lfa + L,J

Number of contact points

Porosity

Porosity calculated using Taylor et al. (1 990)

Number of time steps elapsed as fluid travels fiom beginning of column to the end of segment k

Number of segments

Portion of Ieachate which is substrate 2

Page 21: Modelling of Clogging in Laboratory Column Experiments

S b

S b *

S c

S c

s,, sC.2

Matrix colurnn number for advection routine

Maximum specific rate of substrate utilkation

Maximum specific rate of substrate utilization of substrate I

Maximum specific rate of substrate utilization of substrate 2

Substrate flow

Rate of endogenous decay of biomass

Biomass growth rate

Biomass loss rate

Rate of loss of substrate for ce11 maintenance

Net biofilm growth rate

Substrate utilization rate

Rate of bacterial growth

Radius of the surface of a sphere coated uniformiy with film

Reynolds number

Growth limiting substrate concentration

Substrate concentration of the bulk Buid

Dimensionless substrate concentration in the bulk liquid

Shmidt number

Effluent substrate concentration for a segment

Revised effluent substrate concentration

Effluent concentration of secondary substrate (pro pionic acid)

Substrate concentration within the active biofilm

Total influent substrate concentration

Infiltration substrate I concentration

Infiltration substrate 2 concentration

Refractory influent substrate concentration

Substrate concentration at the active biofilm surface

Page 22: Modelling of Clogging in Laboratory Column Experiments

DirnensionIess substrate concentration at the active biofilm surface

Substrate concentration at the base of the active biofiIm

Influent substrate concentration

Average time required for nuid to move from one end of a segment to the other

System temperature

Real number of time steps elapsed as fluid travels from beginning of colurnn to the end of segment k

Temperature of the reference parameter

Volume

Biomass concentration

Density of active biofilm

Density of inactive film layer

Maximum yield coefficient

Yield coefficient for calcium carbonate precipitation

Packing factor

Effectiveness factor

Interior angle of the overlap shape

Temperature factor for a parameter

Absolute viscosity

Time step length

Specific growth rate

Maximum specific growth rate

Standard biofilm depth dimension

Convergence tolerance factor

Page 23: Modelling of Clogging in Laboratory Column Experiments

CHAPTER 1

INTRODUCTION

The most cornrnon method of disposing of municipal and industrial wastes is by

landfilling. Of the approximately 10 million tonnes of municipal solid waste generated in

Ontario, 90% is disposed of in about 1,400 active landfills in Ontario (MOEE, 1992).

Water which percolates through the landNl leaches compounds fkom the decomposing

waste creating a contarninated fluid called leachate. The leachate which escapes fiorn

landfiils may have a negative impact on local groundwater and surface waters. Where

natural attenuation is not sufficient to assure protection of the environment, a barrier

system is conaructed pnor to landfilling to diminish the escape of leachate.

Municipal solid waste landfills typicaliy include a bamer systern consisting of a

leachate collection system or systems and either a natural or engineered liner (or liners)

(see Figure 1.1). A liner rnay be made of compacted clay, a geomernbrane, a geosynthetic

clay liner, or a combination of a geomembrane and either compacted clay or geosynthetic

clay liner. Due to the low hydraulic conductivity of the liner, leachate will build up over

the liner. To prevent this build up, a Ieachate collection system (L.C.S.) is constructed on

the liner. The L.C.S. typicdly consists of a senes of perforated pipes ( co~ec ted to

manholes to allow cleaning) in a granular layer (sand, grave1 or crushed stone). The

L.C.S. is expected to collect most (or ail) of the leachate generated and to controi the

Page 24: Modelling of Clogging in Laboratory Column Experiments

height of the leachate mound on the base of the landfill, thereby minimizing the potential

for contamination of ground water (by migration through the liner) or surface water (by

leachate seeps). The L.C.S. drains the leachate to one or more locations where it is

rernoved for treatment.

Failure of leachate collection systems, including pipes and surrounding drainage

matenal, may be caused by clogging (due to extreme sedimentation, chemical

precipitation, biochernical precipitation or biological growth) or pipe faiiure (eg. due to

separation, breakage or deterioration) (McBean et al, 1995). Clogging has been found to

be a very cornrnon cause of failure of the L.C.S. (Brune et al., 199 1). A L.C.S. is said to

have failed due to clogging when there is a physicai buildup of material in the collection

pipes, drainage layer or filter layer that causes the leachate head to exceed the design

value. Clogging due to sedimentation, and pipe failure, can be controlled by appropriate

design and, in the case of pipes, maintenance. This thesis, therefore, will focus on

clogging due to the presence of microorganisms causing biological growth and

biochernical precipitation. As indicated by Ramke (1989), the mechanisms of biological

clogging include slime growth, filamentous growth, biomass formation and femc

incrustations. Also attributed to biological processes were the bacterial production of

sulphide and carbonate precipitations.

Once a clogged L.C.S. can no longer control the height of the leachate mound

acting on the base of the landfill, the mound will increase and this will generally result in

Page 25: Modelling of Clogging in Laboratory Column Experiments

increased advective contaminant transport through the underlying banier. Clogging cm

also increase the incidence of leachate seeps ( lateral leakage of leachate to surface

waters), and in extreme cases, the stability of the landfill may be compromised. Since the

L.C.S. also removes contaminants fiom the base of the landfill, clogging may reduce its

ability to divert contarninants fiom the underlying hydrogeological system. The reliability

of the leachate collection system is of particular importance since excavation and

replacement are generally not feasible.

The time at which the collection system clogs and the magnitude of the leachate

mound at subsequent times may be critical in terms of assessing the potential impact of the

landfill on groundwater. If the L.C.S. operates without failure for long enough, the

concentration of contarninants in the landfill leachate will reduce and will have negligible

impact if released to the environment (see Rowe, 199 1, 1995 and Rowe et al., 199%).

However, if the collection system fails prematurely, the concentration of contarninants in

the leachate that is now transported through the liner system ma7 cause unacceptable

impact.

Contaminant transport models designed for landfills may incorporate the modelling

of the effect of failure of the leachate collection system on contaminant migration to

adjacent aquifers (Rowe and Booker, 1995, 1997a,b). The time at which this failure may

occur is an important input to these models, and current estimates are based on relatively

cmde caiculations (Rowe et al., 1994).

Page 26: Modelling of Clogging in Laboratory Column Experiments

Exhumation of a portion of the L.C.S. at the Keele Valley Landfill (Rowe et al.,

1997a) has indicated that there are two zones in the collection system. A Iower saturated

zone where the clogging was greatest, and an overlying unsaturated zone where some @ut

less) clogging occurs (see Figure 1.2). It may be hypothesized that the lower portion of

the collection system will decrease in hydrauiic conductivity with tirne, due to clogging,

and that once this clogs the leachate will then be diverted higher up in the system creating

a new saturated zone in the previously unsaturated portion of the leachate collection

system. In order to understand and model the clogging of the leachate collection system,

it is first necessary to understand and model the clogging in the saturated portion of the

system. Furthemore, since the saturated system in real landfills contain many variables,

including variable grainsize of the granular material and variable leachate quality it would

be desirable to first test the model of any such system against tests where the grainsize and

leachate characteristics were controlled before testing it against real systems ( where

greater vanability and uncertainty is to be expected).

Several investigators have performed experiments simulating the passage of landfill

leachate through the saturated portion of the granular drainage layer using laboratory

colurnns packed with porous media fed actual or synthetic leachate (ie. Brune et al., 1991;

Paksy et al., 1995). It is also noted that numerous scientists in the field of wastewater

treatment have performed column expenments which, while not simulating the L.C.S., are

otherwise similar in many ways and provide penpheral contributions to the study and will

be referenced, where appropriate, through the thesis.

Page 27: Modelling of Clogging in Laboratory Column Experiments

To allow increased focus on the biological causes of clogging, a synthetic (man-

made) leachate may be substituted for actual leachate, thus providing relatively uniform

source substrate concentration. The substrate concentration is the concentration of the

nutrient which limits the rate of bacterial growth. It's considered that this type of

controlled column experiment provides the best way of collecting data for testing the

modelling of biological processes occurring in the L.C.S.

1.4 OBJECTIVE

The objective of this thesis is to develop, irnplement and test a numencal model to

predid the clogging of porous media in column experiments conducted using synthetic

landfill leachate as the first step towards predicting the rate of clogging in the drainage

blanket in a landfill leachate collection system. Specifically, the objectives (and original

contribution) of this thesis are to :

derive corrective formulas to allow use of a published geometric mode1 for

caiculation of porosity and specific surface area of film-coated porous media for

situations involving clogging of granular systems;

develop a numerical mode1 of clogging that incorporates:

a a novel relationship between bacterial activity and mineral precipitation so

as to allow simulation of the contribution of each to clogging;

the representation of bacterial utilization of both a primary and secondary

substrate;

a variable mass transfer resistance, advection, and temperature dependencies

of parameters;

Page 28: Modelling of Clogging in Laboratory Column Experiments

develop a method for expenmentally denving a yield coefficient for mineral

precipitation;

examine how well the model simulates the behaviour observed in well controlted

column tests performed by Rowe et ai. (199%);

illustrate the shift in system dominance over time fiom one of biofilm growth to

one of rnineral precipitation for a specific case.

THESIS OUTLIIW

Chapter One has defined the problem. In Chapter Two readers are given

background information regarding the growth of bactena, the formation of biofiirns, the

relationship between bacteria and mineral accumulation, and the proposed structure of the

ideaiized film used by the model. Since published geometric models for the porosity and

speci£ic surface of a porous media fail when there is a significant biofilm, Chapter Three

describes the development of a geometric model that allows the calculation of porosity

and specific surface area of granular media coated with thick film. The ciogging model is

described in Chapter Four, including the method by which the system is defined and

substrate transported, the biofilrn and rnineral film growth and loss routines, the iterative

procedures required to process each element, and the management of the system of

elements as the program marches forward in time. Chapter Five applies the mode1 to two

sets of published column test data: in one case a short duration experiment using a single

substrate and no inactive film growih; in the other case a long duration experiment in

which a synthetic leachate is represented by two substrates and inactive film accumulation

is simulated. The final chapter, Chapter Six, presents the conclusions of this work and

Page 29: Modelling of Clogging in Laboratory Column Experiments

recornmendations for future extension of this work towards the ultimate goal of prediction

of leachate collection system clogging.

Page 30: Modelling of Clogging in Laboratory Column Experiments

Figure 1 .1 : Typical h o liner, Mo leachate collection system landfill.

Primary Leachate

Cover 1

Leac Yion

Waste

Natural Soil

J . . . . . . ' Aquifer . ,

Page 31: Modelling of Clogging in Laboratory Column Experiments
Page 32: Modelling of Clogging in Laboratory Column Experiments

CHAPTER 2

MODELLING THE BIOLOGICAL CLOGGING IN COLUMN EXPERIMENTS FED SYNTHETIC LEACHATE

Landfill leachate collection systems have been found to clog by biological

processes in landfills (Bass, 1986; Brune et al, 1991; McBean et al, 1993; Rowe et al,

1995a,b ) and in expenments simulating landfill conditions (Brune et al. 199 1 ; Paksy et al,

1995).

A survey conducted by Arthur D. Little Inc. (Bass, 1986) found that of 23 U. S.

waste disposal facilities investigated, biological growth was a problem at four sites and

biochemical precipitation was a problem at one site. One site, for example, contained a

30m long biological growth mass which packed a leachate collection pipe. Bass concludes

that although few cases of biological or biochemical clogging of the drainage @ers of a

L.C.S. were found, the conditions beneath landfill facilities are such that these processes

cannot be mled out as possible clogging mechanisms.

A survey by Brune et al. (199 1) of 23 Geman sanitary landfills with Ieachate

collection systems (between 1987 and 1989) found that more than half of the cases

investigated had drainage pipes and drainage layers which contained consolidated,

insoluble deposits. Impairment of the drainage system ranged corn moderate deposits on

the pipe bottom to incrustation of the whole drainage layer. The formation of these

Page 33: Modelling of Clogging in Laboratory Column Experiments

incrustations were aîtributed to anaerobic bacteria. This conclusion was based on

experimental and in-field observations which showed that the anaerobic rnicroorganisms

(present in landfill leachate at high concentrations) easily colonize drainage system

surfaces and this is accompanied by the precipitation of inorganic deposits around the

bacteria. The aggregate of bacteria and inorganic deposit can accumulate to the degree

that clogging occurs. The deposits were found to mainly contain calcium and iron

combined with sulphur and carbonate. A significant arnount of organic material was found

in al1 deposits.

As indicated by Rowe et al. (199Sa), significant clogging has occurred in the

leachate collection system at the Keele Valley Landfll in Canada. The clog matenal

typically consisted of 21 to 27% calcium, 38 to 54% carbonate, 1 to 10% iron and 2 to

7% silica.

McBean et al. (1993) found that al1 the essential features required for rnicrobial

growth were present in leachate collection systems. They report the results of an

excavation of a landfill in Peterborough, Ontario, where biomass accumulation was found

to be the cause of leachate mounding and subsequent leachate seeps.

Paksy et al. (1995) performed a laboratory experiment in which synthetic leachate

was passed through a column modelling a landfill drainage system. It was concluded that

under simulated landfill drainage system conditions bacterial populations cm rapidly

develop on granular materials and due to this growth a gradua1 reduction in drainable pore

Page 34: Modelling of Clogging in Laboratory Column Experiments

volume with time will occur. It was found that the pore reduction leveled off, Ieading to

the conclusion that microbial growth may not continue indefinitely for the test condition

they examined.

Coiumn tests performed by Brune et ai. (1 99 l), using real landfill leachate and

drainage rnaterial (gravel), showed that a highly loaded leachate caused extensive clogging

corresponding to that observed in landfills. The chernical composition and microscopie

structure of the clog material formed was similar to that formed in landfill sites. Over the

approximately 10 to 15 month period of the tests, the permeability of coarse drainage

material (grain size 16 - 32 mm) showed no significant change, while finer drainage

material (grain size 8 - 16 mm) showed a significant reduction. Use of fine and well

graded material (2 - 4 mm and 1 - 32 mm respectively) resulted in considerable loss of

permeability.

These case histories demonstrate that biological clogging of the L.C.S. occurs and

that anaerobic bacterial activity is suspected to be the dominant process. Colurnn tests

have provided the opportunity to observe the processes under controlled conditions.

This chapter discusses clogging in colunin tests fed synthetic leachate by first

describing the bacterium involved, the processes of biological clogging, bacterial growth

models, and the groundwork for the proposed model. To aid in the understanding of the

processes of biological clogging, the structure and metabolic activity of bacterium are first

discussed. The means by which an environment favourable to biological growth cm be

Page 35: Modelling of Clogging in Laboratory Column Experiments

formed is then explored. Thirdly, bacterial adhesion and the clogging process are

discussed. Fourthy, bacterial growth models are addressed and kinetic parameters are

defined, and finally the basis for the distribution of the bacteria by the mode1 is discussed.

2.2 BACTERIUM

2.2.1 Dimensions and Classification

According to Brune et al. (1 99 l), anaerobic bacteria are the primary

microorganism involved in the biological clogging of landfill leachate collection systems.

Bacteria form various shapes and sizes, are unicellular, and most are bound by a rigid ceIl

wall (Charackiis and Marshall, 1990). Many have diameters in the 0.3 to 3 pm range and

Iengths in the 1 to 10 pm range (cocci, bacilli, vibnos) or up to 50 pm long (spinlla) or

greater than 100 pm long (filamentous forms) (Metcalf and Eddy, 199 1). The bacteria ce11

may secrete extracellular polymers which can fom an attached, highiy hydrated capsule or

create a fiee, viscous, soluble slime (Characklis and Marshall, 1990). The composition of

the bacterial ce11 has been found to be 80% water and 20% dry matenals, with 90% of the

dry materials being organic (Metcalf and Eddy, 1 99 1 ).

The dominating bactena in wastewater are usually classified as facultative

anaerobic chemo heterotrophs and obligate anaerobic chernoheterotrop hs, while

chemoautotrophs are also present (McBean et al, 1995). According to Metcalf and Eddy

(1991), a 'chemoautotroph' obtains energy fiom the oxidation of reduced inorgonic

compounds such as ammonia, nitrite and sulphide and carbon from carbon dioxide while a

'chemoheterotroph' usually denves energy and carbon from the oxidation of organzc

Page 36: Modelling of Clogging in Laboratory Column Experiments

compounds. OMigateiy anaerobic bacteria can oniy exist in an environment devoid of

oxygen whilefuczîltative anaerobic bacteria cm grow in the presence or absence of

oxygen.

2.2.2 Growth

The following description of biological growth is based on Characklis and Marshall

(1990), unless othenvise noted, and is provided as background for the reader.

Bioenergetics is the transformation of energy through cellular metabolism. The

process of metabolisrn must be maintained in order to conserve the structure and viability

of the bacteria. The metabolism of bacteria relies upon reactions of oxidation-reduction.

In the process, reduced energy donors (electron donors), are oxidized allowing some

available energy to be stored by the bacterium in a usefùl form. The bacteria of interest

have metabolisms which may utilize organic compounds or reduced inorganic compounds

as energy sources.

Bacterial growth may be defined as the increase in the number of cells or mass of

the entire collection of cells from the initial state. Reproduction is largely by binary

fission, but some bactena reproduce by budding or fragmentation of filamentous growths.

If al1 growth requirements are met a rapid increase in growth will occur.

Bacteria have nutntional and environmental requirements which must be met in

order for growth to occur. Nutntionally, the bacteria must have sources of energy,

Page 37: Modelling of Clogging in Laboratory Column Experiments

carbon, nutrients (ie. nitrogen, phosphorus) and may require organic nutrients for ce11

synthesis. With respect to the bacterial environrnent, the proper range of pH and

temperature among other factors must be met. Specific bacteria groups have fairly narrow

temperature ranges and diEering optimal temperatures. Bacteria have an optimum pH

range fYom 6.5 and 7.5 (Metcalf and Eddy, L 99 1).

2.3 FORMATION OF A BIOLOGICAL GROWTH ENVIRONMENT

2.3.1 Introduction

McBean et al. (1993) found that al1 the essential features required for rnicrobial

growth were present in leachate collection systems including microorganisms: organics as

food; nutrients such as nitrogen and phosphorus; an acidic (in the early stages) to slightly

basic (in the late stages) environment; and temperatures and rnoisture contents conducive

to growth. The establishment of an environment that is conducive to biological growth

and biochemicai precipitation begins with the decomposition of solid waste, coupled with

the percolation of infiltrating water creating a contaminated water called leachate. This

leachate percolates through and is collected by the leachate collection system for removal

from the landfill. The following sections define two rnethods of measuring the organic

content of wastewater, discuss the characteristics of Ieachate and the environmental

conditions created in the L.C.S., and discusses synthetic leachate and the column test

environment.

Page 38: Modelling of Clogging in Laboratory Column Experiments

2.3.2 Chemical and Biochemical Oxygen Demand

Chemical oxygen demand (COD) and biochernical oxygen demand (BOD) are both

parameters which measure the organic content of wastewaters. According to Metcalf and

Eddy (1991). COD is the measurement of the oxygen equivalent of the organic matter that

can be oxidized using a strong oxidizing agent in an acidic medium. BOD is the

measurement of the dissolved oxygen utilized by microorganisms in the biochemical

oxidation of organic matter. The ratio of B0D:COD is often used to show the

degradability of the organic matter in wastewater. Since the COD oxidizing process is

more efficient than the BOD process, which oxidizes only the readily biodegradable

organics, a high ratio of BOD to COD would indicate a highly degradable leachate. ORen

the concentration of organic constituents is considered the limiting factor in microbial

growth (ie. the substrate), and therefore the values of COD and BOD may be critical.

2.3.3 Landfill Leachate and the L.C.S. Environment

2.3 -3.1 Leachate Quality

Due to the heterogeneity of the waste, different phases of decomposition will likely

occur simultaneously in the landfill at different locations until closure, and after closure the

hydrolysis, acetogenic and methanogenic phases will continue simultaneously for several

years until hydrolysis and acid anaerobic phase decomposition is gradually diminished.

Leachate, therefore, may travel through or be produced by zones or layers in the waste of

varying decomposirg phases and so will not simply have the characteristics of one phase,

but be a mixture of the intermediate and end products of different phases and include

constituents of non-biological origin, and rnay include large concentrations of

Page 39: Modelling of Clogging in Laboratory Column Experiments

microorganisms (McBean et al., 1995).

Crawford (1985) stated that the leachate of a young landfill ( les than 2 to 4 years

after closure) is likely to contain high concentrations of organic acids, arnmonia and total

dissolved solids (TDS). The organic acids will rnostly be fatty acids of low molecular

weight, for example acetic acid, and some fùlvic or other more complex organic acids.

The young landfiil leachate's high COD/TOC value reflects the unoxidized state of organic

carbon in the leachate. Inorganic components such as dissolved saits may be present in

concentrations greater than 10,000 mg/l, and high concentrations of sodium, calcium,

chloride, sulphate and iron rnay be present. The pH will be in the low 6 to 7 range

(McBean et ai., 1995). The leachate contains large microbial populations with the

majonty being bacterial, but also including other pathogens such as vimses, protozoa and

helminths (Lu et al., 1985).

2.3.3.2 The L.C.S. Environment

From the previous sections it can be seen that the leachate which flows through the

drainage system will contain the elements conducive to biological growt h. Leachate,

especiaily young landfill leachate has been found on exiting the L.C. S. to contain the

bacteria responsible for decomposition and the organic substrates and nutnents required to

sustain them. Landfill conditions, though, may not be optimum for bacterial growth, as

shown in Table 2.1, compiled by Farquhar (1989) for representative southem Ontario

landfills.

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Table 2.1 : Conditions affecting methanogenesis in landfills (Farquhar, 1989)

Parameter - - - . - -

Optimal Representative ranges for Value southern Ontario landfills

Temperature (OC) 35 10-20 at depth > 2 m

PH 7.2 5.5 - 6.5 (young leachate)

Moisture content (% wet weight) Saturation 20 - 30 at placement

Oxidation reduction potential (mV) < - 330 > - 330 at placement

Nutrients Sufficient Phosphorous deficient

Toxicants None Ammonia and certain metais

It can be seen that landfill leachate, especially of southem Ontario landfills, does

not produce an environment which optimizes bacterial growth. It must be noted, though

that the majonty of these comparisons are for methanogenic bactena and that many other

varieties of bacteria exist in the landfill system, and each of them have differing optimum

values of environmental factors. It should also be noted that the comparison in Table 2.1

is an averaging of measured values, and therefore a specific landfill may produce more

favourable conditions. Likewise, more favourable conditions may occur at a particular

point in a landfill (eg. see Barone et al., 1997). To conclude it can be said that while the

conditions in leachate collection systems may not be optimal for bacterial growth, the

requirements exist, and growth is possible.

2.3.4 Synthetic Leachate and the Column Test Environment

Control of the composition of the synthetic leachate and other column test factors

d o w s a column test environment to simulate L.C.S. conditions which are average, or

optimal for bacterial growth. The pH of the synthetic leachate, or temperature of the

Page 41: Modelling of Clogging in Laboratory Column Experiments

system, for example, may be controlled such that microorganism growth is optirnized.

The porous media used in a colurnn test may be selected to relate closely to the L.C.S. by

using actual drainage layer material (such as Brune et al, 199 1) , or may be selected to

relate closely to a mode1 by using, for example, glas spheres (such as Millward, 1997,

Rowe et al., 199%). Synthetic leachate usually does not contain a significant number of

microorganisms, thus the porous media is often inoculated with actual landfill leachate

prior to testing. This provides a source of microorganisms available to consume substrate

frorn the synthetic leachate and multiply throughout the system.

2.4 THE CLOGGING PROCESS

2.4.1 Introduction

The previous section showed that the conditions required for rnicrobial growth

were present in landfill leachate and synthetic landfill Ieachate. It was shown that while

typical leachate does not provide optimum bacterial growth conditions, the potential for

biological growth and biological precipitation does exist, and that synthetic leachate may

be substituted and controlled to optimize this potential. This section discusses the two

biological clogging processes to be modelled: biological growth in the fom of biofilms,

and biochernically driven precipitation.

2.4.2 Biologieal Growth

2.4.2.1 Introduction

The primary cause of biological clogging is believed ( Bass, 1986; Brune et al.,

199 1; Paksy et al., 1995 ) to be the growth of bactena and the subsequent production of

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bioslime (extracellular polymers, or exopolymers) in the porous media. The majority of

bactena and bioslirne grow in the form of biofilms (Flemming, 1993), and therefore the

formation, structure and effects of biofilms in porous media will be discussed in detail.

2.4.2.2 Bacterial Attachent and Biofilm Formation

The following is a list of steps fiom bacterial transport to biofilm development

(derived from Cullirnore, 1993):

1) Bacteria are usually negatively charged and are attracted to positive surfaces.

Other causes of attachment may be of greater significance since positively charged

surfaces do not dominate the system.

2) The bactena ce11 becomes anchored to the surface by extending polymers (long

chained molecules) which make the primary attachent.

3) Cells reproduce and colonize the surface by "jumping" or "tumbling" or may

simply clump together. They spread rapidly on fnendly surfaces.

4) A biofilm is formed when the structures in which the various microorganism

species CO-exist are bound together with a water-retaining polyrneric matrix.

5 ) The biofilm extracts substrates and bioaccumulates fiom the passing water. The

bioaccumulates are not utilized, but accumulate within the biofilm. Some comrnon

accumulates are non-degradable organics and metallic ions (ie. iron, manganese,

copper, aluminum, and zinc).

6) The biofilm, initially a randomized mixture of rnicroorganisms, becomes more

organized over time. Due to competition and other factors some rnicroorganism

strains are elirninated, some become dormant, and some stratification occurs.

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Besides being sirnply attracted to surfaces, it has been thought that it is

advantageous for starved bactena to colonize on surfaces and it has been found that

starved bacteria are more adhesive than well-fed bacteria and some can utilize substrates

at the surface (Characklis and Marshall, 1990).

2.4.2.3 The Biofilm

Characklis and Marshall (1990) stated that "A biofilm consists of cells

irnrnobilized at a substratum and fkequently ernbedded in an organic polymer matnx of

microbial origin ... it is a surface accumulation, which is not necessarily uniform in time or

space.. . [and]. .may be composed of a significant fraction of inorganic or abiotic substances

held together by the biotic matrùc."

Biofilm Structure

The latest studies of biofilm structure have led to the belief (Costerton et ai, 1995)

that with adhesion, structural molecules of bactena change allowing the synthesis of

exopolysaccharides (bioslime). This synthesis, combined with ceIl division, leads to the

development of microcolonies encloseci in dense slime and attached to the colonized

surface.

Studies at the Centre for Biofilm Engineering in Montana, U.S.A. @ebeer et al.

1993; Debeer et al., 1994; Stoodley et ai., 1994) found that confocal scanning laser

rnicroscopy allowed detailed examination of live biofilms under flow conditions. These

works revealed the structure of biofilms to be heterogeneous and consisting of round ce11

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clusters separated by channels. It was shown that flow existed within the voids (channels)

while the interior of the ce11 clusters remained stagnant. Flow velocities within the biofilm

were found to be related to physical parameters such as the local structure and biofilm-to-

voids ratio. This fiow was found to travel around and over ceIl clusters, and even against

the direction of bulk flow. It is thought by Debeer et al. (1993) that due to convection

within the biofilm the mass transfer rate fiom the bulk liquid may be significantly higher

than previously believed.

Based on these observations Lewandowski et al. (1995) concluded that a new

conceptual mode1 of biofilm where microorganisms are organized in clusters separated by

interstitiai voids must be accepted. Liquid flow in the charnels was found to extend to

the substratum. Three microscopie methods were used by Stewart et a1 (1995) to provide

a p i a r e of the stmcture which was consistent between methods and previous studies

above, and which noted that patches of bare substratum could be seen even though the

biofilm was several hundred microns thick in places. It was found (Costerton et al, 1995)

that early clusters are cone-shaped while later clusters may develop mushroom shapes,

with water channels existing very near to the substratum. It was also noted that the

channels are wide enough to allow the passage of 0.3 pm latex beads.

The biofilm system, idealized by Charackiis and Marshall (1990), is made up of

five compartments (see Figure 2.1): the gas, the bulk liquid, the surface film, the base film,

and the substratum. The gas cornpartment, wbich may not be present in some biofilm

systems, provides for aeration and/or removal of gaseous products of the biofilm. The

Page 45: Modelling of Clogging in Laboratory Column Experiments

bulk liquid provides substrates to the biofilm. The surface film is the transition zone

between the bulk liquid and the base film and may extend to the substratum, or may not

exist at dl . In the surface film advective transport dominates. The base film consists of a

rather structured accumulation of microbiai cells where rnolecular diffusion transport

dominates. The film portion of the biofilm, composed of the base film and surface film, is

composed of two phases including a continuous liquid phase containing some dissolved

and suspended particulates and a solid phase composed of rnicroorganisms, extracellular

rnaterial or inorganic particles. The substratum is generally an impermeable, nonporous

material, in our case the stones of the L.C.S. or g las beads.

It is important to note that while this biofilm representation recognizes the

existence of a liquid phase within the biofilm little was known of the possible significance

of this Iiquid phase until very recently. The mode1 adopted for this research, based on this

representation, assumes a continuous solid phase bacterial growth on the substratum and

diffusion to be the only manner of mass transport within the biofilrn. Since the biofilm

may grow rapidly, it may expand into interstitial spaces forming a semi-permeable bamer

to flow. The biofilrn is deemed semi-permeable because of the existence of

interconnections between the biofilms. Due to hydraulic forces penodic sloughing of

biomass occurs and this matenal may colonize surfaces downstream.

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2.4.3 Biochemical Precipitation

2.4.3. l Introduction

It is accepted ( Bass, 1986; Paksy, et al., 1995) that the main cause of biological

clogging is formation of biomass, but in the long term, due to questionable permeability of

the biofilm and slime, it may be the build-up of biochemically produced precipitates that

cause zones of near impermeability. Biochemical precipitates are solid deposits formed

with the aid of the metabolic activity of bacteria. The following provides explanation of

biochemical precipitation formation in landfill systems.

2.4.3 -2 Precipitation Formation

Bass (1986) concluded that the principal biochernical precipitates are Fe(OH), and

FeS although manganese compounds may be also involved. The processes involved

depends primarily on the availability of dissolved ffee ions and on the presence of iron-

reducing bacteria. It was found that biochernical precipitate is generdly mixed with the

bioslime. Usually the precipitates formed by biological processes are different in fom and

structure than chernical precipitates, and Bass concludes that they are more effective in

clogging.

Brune et al. (1 99 1) postulate that the precipitation of incnistation material is

caused by:

(a) The formation of iron sulphide on sulphate reducing bacteria (Figure 2.2(a)). Fe3' is

reduced to ~ e " by iron reducing bactena while sulphate is reduced to sulphide by sulphate

reducing bacteria. Due to this bioreduction the region immediately around the bacteria

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becomes more alkaline and leads to precipitation of sulphur as an insoluble metal sulphide

(Le. iron sulphide).

(b) The formation of carbonate on methane bacteria (Figure 2.2(b)). Calcium and other

metals are first mobilized in the waste due to the acidity of the young leachate. Methane

and sulphate reducing bacteria, consurning hydrogen ions, cause a local increase in pH and

the disturbance results in hydrogen carbonate combining with the mobilized metals to

produce precipitates of calcium carbonate and other metal carbonates on the bacteria

surfaces.

Rittmann et al. (1996), utilizing data fî-om mesocosm studies using actual landfill

leachate and drainage materials, aiso concluded that COD removal by rnicroorganisms

allowed or accelerated the precipitation of calcium carbonate (CaCO,). Because most of

the COD removed was acetic acid, a moderate strength acid is converted to CO, with

about 50% dissolving as a weaker acid. It was concluded that the resulting increase in pH

and total carbonate allows or accelerates CaCO, precipitation.

2.5 BIOFILM GROWTH MODELLING

2.5.1 Bacterial Growth Models

The mode1 developed in this thesis was based upon the assumption that a unifonn

biofilm is formed on the media within which utilization of substrate and subsequent growth

and decay occur. According to Baveye and Valocchi (1989), two other types of

mathematical models have been adopted for predicting bactenal growth and biologically

reacting solute transport in saturated porous media. One other class of models assumes

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that the bacteria grow in small discrete colonies attached to the porous media and these

colonies either grow in size, or increase in number while another class of models makes no

assumption of rnicroscopic configuration and distribution in the porespaces. Growth and

decay of the biofilm are govemed by the kinetics of the substrate / biofilrn reactions,

discussed next .

2.5.2 Kinetics of Biofilm Growth

The following is based on Characklis and Marshall, 1990 (except where noted).

2.5.2.1 Introduction

Expressions of the rates of the fundamental biological processes including growth,

maintenance. decay and death are derived through the combination of rate expressions and

stoichiometnc ratios (ie. yields). Since the rates of these fundamental processes are

difficult to measure, observable rates such as specific substrate removal rate, specific

oxygen removal rate and specific biomass production rate must be used to arrive at an

expression. The form of a rate equation may be based on empincal curve fit or theoretical

analysis of a mechanistic model. Environmental factors are reflected in the rate

coefficient. The values of rate coefficients must be determined experimentally and

typically involves the study of the infiuence of concentration on the rate assuming al1 else

constant.

The most common expressions describe unstmctured kinetic models, with the

biotic component characterized by mass and/or cell numbers only, with little attention

given to state or species diversity. Balanced growth (ie. steady-state in an open system )

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and a single species are often assumed.

2.5.2.2 Growth Rate Equations

The required conditions for rnicrobial growth include a viable inoculum, an energy

source, nutrients for synthesis and a suitable physicochernical environment.

Two exarnples of growth rate equations are:

Exponential Growth

The rate of microbial growth is proportional to the biomass present:

rdy = CL^

where p = specific growth rate (t-')

& = biomass concentration (M LJ )

r, = rate of bacterial growth (M L-3 t-' )

This expression is usefùl as long as environmental conditions remain constant and the

constitution of the biomass remains constant (balanced growth). The specific growth rate,

p, is afFected by many environmental variables especially the substrate, but also the

temperature, pH, ionic strength and concentration of inhibiting substances.

Saturation Rate Eauation

The most widely used expression for describing the rate of microbial growth as a

function of nutnent concentration is aaributed to Monod. The equation, describing

specific growth rate lirnited by substrate concentration, descnbes a rectangular hyperbola:

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where Ks = rate (saturation) coefficient, aiso called the half velocity constant, the

substrate concentration at one-half the maximum growth rate (M L")

S = growth limiting substrate concentration (M L")

p, = the maximum specific growth rate (t")

The Monod equation (Monod, 1949) can be considered to provide a transition between

limiting cases for very low concentrations and very high concentrations:

High concentration, P = CL,, for S )) Ks

Low concentration,

At low concentrations the rate is first order with respect to substrate

concentration. The organisms still have significant reaction potential, therefore an

increase in substrate supply will cause an increase in growth rate. At high concentrations,

the rate is independent of concentration (zero order) because the cell can no longer

assimilate the substrate.

If Equation 2.2 is substituted into Equation 2.1 for the value of p, the growth rate

can be expressed as:

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The quantity of new cells produced has been found to depend upon the

concentration of substrate, as implied by the yield coefficient Y, defined as the ratio of the

mass of cells formed to the mass of substrate consumed. The rate of the utilization of

substrate for ce1 growth is expressed as:

where r,u = substrate utilization rate (M L-3 V' )

Y = maximum yield coefficient (Mx M i 1 )

Often the term p, 1 Y in Equation 2.4 is replaced by the term ij which is defined as the

maximum rate of substrate utilization per unit mass of microorganisms:

If the term ij is substituted into Equation 2.4 the following expression is created:

2.5 -2.3 Maintenance Rate Equations

Microorganisms require energy to maintain existing structures and for process

such as movement, therefore maintenance rate reflects a diversion of substrate away from

synthesis or growth, therefore maintenance decreases the overall yield of the cells from

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substrate. The maintenance rate tenn is part of the substrate depletion term

where = maintenance coefficient (M M" t-')

Often the overall decrease in ceU mass due to maintenance, predation (destruction

by a second population) and death is combined and called endogenous decay. The

endogenous decay term is formulated as

rd = -kdXf rZe8]

where k, = endogenous decay coefficient (t-') (Metcalf and Eddy, 199 1).

2.6 IDEALIZATION OF BIOFILM STRUCTURE BY PROPOSED MODEL

2.6.1 Uniformity of Film Thickness

It was decided that the model's objective of predicting the degree of clogging of

the porous media would be best met by prediction of the porosity of the media. In order

to allow geometric calculation of porosity, the media is represented using simple,

repeating arrangements of spheres. The representation is discussed in Chapter 3. To

incorporate the change in porosity due to the accumulation of biomass, the biomass is

assumed to grow on the spheres at a uniform thickness throughout the subregion analysed.

The assumption of uniform (and tiius continuous) biofilm growth has been

assumed by several authors including Taylor et al. (1990) and Taylor and JaEe (1990a,b,c)

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and Cunningham et al. (1991). Other authors, such as Vandevivere and Bayveye

(1992a,b), McBean et al. (1993). Stewart et al. (1995) and Murga et al. (1995) assume the

growth is discontinuous and non-uniform. By analysis of the works of several of these

authors, Rittmann (1 993) concluded that the biofilms were continuous for highly loaded

surfaces, while discontinuous under situations of low loading. Since usuaiiy much of the

porous media of the collection system is subjected to a high substrate loading, it is

expected that the spheres would be covered in a continuous film. For the purposes of this

thesis, the thickness of the film is taken to be relatively uniform to examine how well

processes can be modelled based on this assumption.

2.6.2 Film Layering

The mode1 must simulate the accumulation of both biomass as biofilm and

biochemically driven precipitate. The proposed mode1 assumes that two distinct films are

formed. One film, called the active biofilm, is a uniform layer of active biomass in which

substrate travels by difision, substrate is utilized, and biomass growth and loss occurs. A

second film, called the inactive film is a layer consisting of non-degradable inert biomass

and precipitate (calcium carbonate). It is assumed that the inactive film adheres to the

porous media surface, and the active film adheres to the inactive film. It is assumed that

each film has a distinct thickness and spatially unifom density. The inactive film,

consisting predominately of calcium carbonate, will have a considerably greater density

than the active layer.

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Several researchen (tawrence et al., 199 1 ; Masuda et al., 199 1; Zhang and

Bishop, 1994; Ohashi and Harada, 1994 ) have found that the density of biofilm changes

with depth. Zhang and Bishop (1994) found that the density of bottom layers were 5 to

10 times greater than those in the top layers, and the ratio of living cells to total biomass

decreased significantly from the top layers to the bottom layers. These findings

substantiate the proposed model's separation of the two layers which places more dense

matter in a layer below the active layer. The distribution of living cells also provide some

substantiation for the incorporation of the inert biomass into the lower, inactive film layer.

2.6.3 Film Permeability

Several authors ( Taylor and J&e, 1990qb,c ; Taylor et al., 1990 ; Cunningham et

al., 199 1; Vandevivere and Baveye, 199îa,b ; Baveye et ai., 1992 ; McBean et al., 1993 ;

Wanner et al., 1995) have stressed the critical role that bacteria, in the form of biofilms,

play in reducing the permeability of porous media. Disagreements exist between authors

regarding the manner in which permeability is affected by biofilm growth.

Taylor et al. (1990) and Cunningham et al. (199 1) mode1 permeability reduction by

the decrease in pore diameter caused by biofilm accumulation (neglecting slime

production) on the pore walls. Overall biofilm thickness, therefore, is the critical factor.

Vandevivere and Baveye (1992a,b) and McBean et al. (1993) concluded that biofilm with

slime (exopolymers) accumulating at pore restrictions were the critical factor. Still others

believe permeability reduction is a function of the fiction factor attributed to the

accumulation of biofilm and slime at all points within the pore (Rittmann, 1993).

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The proposed model, in an effort to allow flexibility with regards to this issue,

would allow the active biofilm layer to be either permeable or impermeable, that is, the

thickness of the active layer could be chosen to not be used in caiculating changes in

porosity. The inactive film is assumed to be impermeable to flow, and therefore the film

thickness of this layer is always included in the calculation of porosity.

2.7 MODELLING BIOLOGICAL CLOGGING IN THE L.C.S.

This chapter has demonstrated though published case histories (Bass, 1986; Brune

et al, 199 1; McBean et al, 1993; Rowe et al, 1995a,b ) that biological clogging in the

leachate collection systems of landfills occurs, that the dominant process is suspected to be

the growth of anaerobic bacteria, and that column tests have been utilized to study the

phenornenon involved. Under favourable conditions, rapid growth of bacteria can occur.

The favourable conditions for microbial growth in the L.C.S. are established by the

percolation of leachate, containing the products of the decomposition of the waste above.

As indicated by McBean et al. (1 993). the L X . S. environment provides: microorganisms,

organics for consumption, nutrients, and pK temperature and moisture levels conducive

to growth. In a column test fed synthetic leachate the conditions for bacterial growth may

be met or optimized by controlling leachate composition and other system factors.

The majority of bacteria and bioslime grow in the form of biofilms (Flemming,

1993) which fix themselves to the granular media of the L.C.S. and may form a semi-

permeable barrier to leachate flow. Attributed to the growth of bacteria is the build-up of

biochernical precipitates, solid deposits fonned with the aid of the metabolic activity of

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bacteria. The growth of such deposits has been discussed by Brune et al. (1991) and

Rittmann et al. (1 996). An idealized biofiim structure was developed for the proposed

modei which incorporates an inactive layer consisting of non-degradable inert biomass and

the biochemical precipitate attached to the porous media, and an active layer of biomass

adhering to the surface of the inactive film. The formulas for calculating the porosity and

specific surface area of the porous media foiiowing film build-up are discussed in Chapter

3.

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Figure 2.1 : Cornmon idealkation of biofilm structure (Characklis and Marshall, 1 990).

Acidic Environment - - caf Acidic Environment

Figure 2.2(a,b): (a) Formation of iron sulphide on sulphate reducing bacteria, (b) Formation of carbonate on methane bacteria (Brune et al.. 1991).

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CHAPTER 3

POROSITY AND SPECIFIC SURFACE MODELS

A mode1 was required that could calculate the porosity and specific surface of a

volume of attachent media with various biofilm thicknesses. The model rnust ailow

varied initial porosities or packing of the clean attachent media. The model should have

the best possible accuracy within the eniire range of film thicknesses, including the film

thicknesses as the porosity and specific surface near zero.

3.2 ASSUMPTIONS

It was assumed that the attachment media could be idealized as perfect spheres of

equal diarneter with a repeating, consistent packing arrangement. The film is assumed to

be a single, impermeable layer of unifonn thickness in the derivation of the models.

3.3.1 Packing Arrangements

The mode1 assumes the structure of the porous media can be simulated by spheres

of equal diameter. Any manner of arranging solid spheres in which each sphere is held in

place by gravity and supported by tangent contact with neighbouring spheres is considered

itspacking. II will be assumed that the porous media can be represented by a regrrlm or

geometrically sysiematic packing arrangement, that is, the Iayers, or sets of rows of

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spheres repeats its arrangement in both directions within that plane.

Assurning that the structure of the porous media is represented by stable, regular

packing arrangements, it has been found that only four such arrangements exist for spheres

of equal diameter ( Graton and Fraser, 193 5 ). The four arrangements are cubic,

orthorhombic, tetragonal-sphenoidal and rhombohedral. These arrangements are named

&er the shape of the 3-dimensionai, 6 sided box formed by joining the centres of eight

spheres. This box is called the unit cell and is the smallest portion of a stack of layers of

spheres which completely represents the packing and distribution of voids throughout the

entire arrangement. The unit ce11 for each arrangement may be descnbed completely by

illustrating the three sides or faces of the ce11 as shown in Figure 3.1. The shapes of the

faces are called square, with a facial angle of 90°, rhombic, with a facial angle of 60" and

the third face shape is neither square nor rhombic and will be called a specid rhombic

face, with a facial angle of 75 O 3 1 '.

3.3.2. Packing Arrangement Characteristics

For each packing arrangement the spheres have a unique number of contact points

with neighbouring spheres, m, and the unit ce11 has a unique volume, see Table 3.1. By

summation of the fractions of the spheres in the corners of the unit ce11 it cm be proven

geometncally that each unit ce11 contains exactly the volume of one solid sphere (0.52 d:

where $ is the diameter of the sphere) with the remainder of the volume of the unit ce11

being pore space. The volume of the unit void space can thus be found by subtracting the

volume of one sphere fiom the volume of the unit cell. The porosity of each packing

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arrangement can be determined by dividing the volume of the unit void space by the

volume of the unit cell. The porosities are listing in Table 3.1. The packing factor, am , a

dimensioniess value characterizhg the packing arrangement and a required parameter for

further calculations of porosity and specific sudace, is calculated by dividing the volume of

the unit ce11 by d,) (Taylor, IWO).

Table 3.1 : Characteristics of Packing of Uniform Spheres

Packing

Cubic

Orthorhombic

Tetragonal- Sp henoidal

d, = diarneter of a sphere Graton and Fraser (1935), Cadle (1965), Taylor et al. (1 990).

Rhombo hedral

The mode1 assumes that the initial, clean media porosity for the simulation can be

measured or estimated. The initiai specific surface, k0, the surface area provided by the

porous media per unit volume (L" ) when clean, may be calculated from the initial

porosity and particle diarneter, assuming the porous media is represented by ideal spheres.

The specific surface is critical as a measurement of the surface area available for

attachment by biofilm. The initial specific surface for al1 elements of the flow field is

caiculated using (Taylor et al., 1990):

Nwnber of Contact points, m

6

8

10

12

Volume of Unit Ce11

4' n/ 2 43 0.75 d i

1 / J Z ~ '

Porosity, n (%)

- - - --

47.64

39.54

30.19

Packing Factor. am

1

d 7 / 2

O. 75

25.95 1 / a

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where d, is the particle diameter.

The fùnctions derived in this chapter calculate the porosity and specific surface of

the film-coated media for only the four possible regular packing arrangements. Each of

these two tùnctions requires the number of contact points, m. and packing factor, am, to

describe the packing arrangement. Lf the initial estimated porosity does not correspond to

one of the four regular packing arrangements, the porosity and specific surface may be

estimated by interpolating between values obtained for the packing arrangements that

bracket the estimated initial porosity.

3.4 DERIVATION OF POROSITY AND SPECIFIC SURFACE MODELS

3.4.1 Introduction

Of particular interest in this thesis, is the change in porosity and specific surface

assuming that a film of thickness L, grows on the surface of a sphere of diameter dp.

These properties of the media will be calculated geometrically based on an arbitrary film

thickness, that is, with no consideration of the growth requirements of the bacteria. Pore

discontinuity causing the isolation of pore space, for example, will have no effect on film

thickness in the isolated pore. It is also important to recognize that as the film grows on

each sphere, allowance must be made for the fact that, near the contact points there will be

'overlapping' of the film on adjacent spheres and one must avoid double counting in

assessing the actual porosity and surface area. The following sections will discuss the

existing models for porosity and specific surface (Taylor et al. 1990) and the authors

modifications to these models.

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3.4.2 Taylor et aL(1990) Mode1

Taylor's equations for caiculating porosity and specific surface are derived by

calculating the volume of the unit cell, the volume of solids in the unit cell, and the surface

area of the solids. The volume of the unit ce11 is a function of the packing factor and

sphere diameter,

as listed in Table 3.1. With the volume of the unit ce11 known, the calculation of porosity

requires calculation of the total volume of solids (sphere + film) in the unit cell, while the

calculation of the specific surface requires calculation of the surface area of the sphere and

film in the unit cell. Since the packing arrangements are geometrically systematic, the

volume and surface area of the 8 quarter hernispheres of spheres making up the unit ce11

are equal to an entire single sphere of equal size.

The total volume of solids in the unit ce11 is based on a calculation by Deb (1969)

which calculates the volume of a solid sphere and its film coating taking contact points

between spheres into account :

The first term of this equation is the total volume of a solid sphere and film coating

assurning uniform coverage and the second term is the sum of the volumes of each

Merical cap of film where accumulation cannot occur due to contact with neighbouring

Page 63: Modelling of Clogging in Laboratory Column Experiments

spheres and which is therefore subtracted fiom the total. A sirnilar equation is used to

calculate the sufiace area in each unit cell.

The following equations of Taylor et al. (1990) were used to calculate the variance

of porosity, n, and specific surface, A, , with film thickness:

The equations calculate porosity and specific surface as a function of the film thickness in

terms of non-dimensional 2 L j 4 , and account for the packing arrangement using the

packing factor q , and number of contact points, m. The equation results are plotted in

Figures 3.2 and 3.3 . In subsequent discussions the thickness of the film will be expressed

in normalized terms of 2Lt /d, for mathematical simplification.

3.4.3 Error in the Taylor et aL(1990) Model

Figure 3 -2 shows a plot of the effect of the film thickness on porosity for various

packing arrangements based on Equation 3.4. It can be seen that porosity decreases with

increasing film thickness to the equation's local minima, and after this thickness is reached

the equations calculate porosities to be increasing with increasing film thickness. This

does not make physical sense. From physical reasoning, it follows that there must be

Page 64: Modelling of Clogging in Laboratory Column Experiments

some film thickness at which the pore space is completely filled, and the porosity is equal

to zero. Since the porosities at each of the minima are greater than zero it may be

concluded that some error is inherent in the assumptions or denvation of the equations by

Taylor et al. (1990).

Figure 3.3 shows a plot of the eEect of film thickness on specific surface for

various packing arrangements. The specific surface decreases with increasing film

thickness until the specific surfaces become zero. Although the specific surface plots do

not indicate obvious error, some error is suspected due to the sirnilarities in the derivation

of the equations, as discussed Iater. Figure 3.3 illustrates that the specific surface becomes

zero, indicative of completely filled pores, while the porosity expression discounts

completely filled pores.

3.4.4 Source of Error in Taylor's Equations

A spherical cap is illustrated as the hatched area in Figure 3.4 for any contact

point. The sphencal cap has a circular base centred at and tangent to the contact point,

and a height equal to the film thickness, Lt. The line DB is the diameter of the circular

base of the cap. A spherical cap is a three dimensional volume of film which is subtracted

from the total volume of sphere plus film and the multiplier m represents the number of

contact points for a specific packing factor. The specific surface expression utilizes a

sirnilar equation in which the total surface area of a sphere covered by film is calculated

and the surface area of the sphencal cap (excluding the base) at each contact point is

subtracted.

Page 65: Modelling of Clogging in Laboratory Column Experiments

In the Plan view in Figure 3.5 the hatched area indicates two of the six sphencal

caps subtracted from each sphere's total volume for cubic packing. Figure 3.6 shows the

same spheres after further accumuiation. The double hatched area in this figure reveals an

overlapping of spherical caps. If Equation 3.5 is used when spherical caps have

overlapped the overlapped volume is subtracted from the total solid volume for each cap,

therefore subtracting the same space twice when it should be subtracted oniy once. The

simple calculation of Deb (1969), Equation 3 -3, therefore becomes inaccurate when the

film thickness increases to such an extent that the spherical caps overlap.

Figure 3.7 depicts the film thickness at the onset of overlap. On inspection it may

be mistakenly assumed that since this overlap coincides with pore discontinuity of the face

it is insignifiant, but, as section SS ' shows, the complete filling of ail of the void space

occurs only after greater accumulation has occurred. The inaccuracy of Equation 3.5 for

large thicknesses causes an underestimation of the total volume of the film covered sphere

in aii subsequent calculations. Similarly, an underestimation of surface area occurs. In

order to correct for the overlapping of volumes, the volume and surface area of the

overlapped space is to be calculated geometrically. The limitations of the equations by

Deb (1969) and Taylor et al. (1990) have not previously been noted in the literature other

than the erroneous argument by Taylor et al. (1990) that the solution breaks down due to

the isolation of the remaining pore space. Since the mode1 is geometnc (and does not

consider hydraulic conductivity) the question of whether pores are isolated (while an

important practical issue ) has no bearing on the breakdown of the solution.

Page 66: Modelling of Clogging in Laboratory Column Experiments

3.4.5 Determination of Critical Film Thickriesses

3.4.5.1 Introduction

Critical film thicknesses are thicknesses at which the geometrical basis of the

porosity or specific surface mode1 rnust change or complete filling of the pore space,

cdled pore occlusion, has occurred. The critical film thicknesses occur when (a) spherical

caps first overlap, (b) spherical caps overlap at a different region at a greater thickness, (c)

overlaps overlap, and (d) pore space is completely füled. As film thickness increases on an

initidy clean sphere, overlap will occur earliest in the face with the most contact points,

since as the number of contact points in the face increases, the closer the spherical caps are

to each other and the thinner the film thickness required for volumes to overlap. The face

with the most contact points is the cntical face. The critical face for the cubic packing

arrangement is the square face while the criticai face for the other three packing

arrangements is the rhombic face (see Figure 3.1 and imagine the packing arrangement of

each face repeating around a single sphere to sum the contact points for each face).

3.4.5.2 Critical Film Thickness Summary and Interpretation

As already illustrated for cubic packing in Figures 3.4 - 3.7, the critical film

thicknesses can be geometrically derived for al1 four packing arrangements (see Appendix

Al for the detailed geometric proof for the four arrangements ). A summary of these

cntical film thicknesses is given in Table 3.2:

Page 67: Modelling of Clogging in Laboratory Column Experiments

Table 3.2 - Summary of Critical Film Thicknesses in Terms of ZL, / d,

Packing Arrangement

Name

Cubic

Orthorhombic

At thicknesses greater than 2L& = 0.4 142 for cubic and ZLjd,, = 0.1547 for the other

packing arrangements the fist overlap occurs. For larger values of 2L&, the calculation

of the volume and surface area of a sphere covered with film is underestimated by

Equation 3.3 and the similar equation for surface area. Using the methods of Taylor et al.

(1 990) the porosity is overestimated and the specific surface underestimated. This point

of theoretical breakdown and thus beginning of inaccurate results is shown as the "first

occurrence of overlap" in Figures 3.1 and 3.2 for each packing arrangement. It may be

expected that by correcting for the overestimated porosity it will be possible to bring the

curves to zero porosity.

Number of Contact Points

(1)

6

Tetragonal- Sphenoidal

Rhombo hedral

The geometnc identification of the film thickness required to reach complete pore

occlusion can now be used to ver@ that there is also an error in the specific surface

equation by Taylor et al. (1 990) since the thicknesses at which the equation calculates a

specific surface of zero does not correspond to the geometricaily derived film thickness at

pore occlusion.

8

First Cap Overlaps

(2)

0.4132

10

12

O. 1547

Second Cap Overlaps

(3 1

-

0.1547

0.1547

0.4 142

Complex Cherlaps (4

0.732

0.5275 0.5275

0.2247

0.2247

CompIete Pore Occlusion

(5 1

0.732

0.2639

0.2247

0.3228

0.4 142

Page 68: Modelling of Clogging in Laboratory Column Experiments

3.4.6 Corrective Models Required

3.4.6.1 Introduction

In order to obtain the porosity and specific surface for a given film thickness it is

necessary to provide a correction to the solution of Taylor et al. (1990). The corrective

models and the corresponding film thicknesses at which they are to be used are

summarized in Table 3.3, and discussed in the following subsections.

3 A6.2 Square Model

The first cap overlap of the cubic arrangement and the second cap overlap of the

orthorhombic arrangement result in overlapped space with sirnilar shapes. The cross-

section of the centre of this shape is depicted in Figure 3.6 (Plan). The model used to

calculate the volume and specific surface of this shape will be called the Square model

since it occurs in the square face of the packing arrangement. Focussing only on the shape

of one overlap on one film coated sphere, it cm be seen in Figure 3.6 that the shape is a

section of a sphere created by perpendicular cuts tangent to the sphere. A three

dimensional depiction of this shape is given in Figure 3.8(a).

3 -4.6.3 Rhombic Model

The first cap overlap of the orthorhombic, tetragonal-sphenoidal, and

rhombohedral packing arrangements result in overlapped space which is similar in shape.

The cross-section of the centre of the shape is shown in Figure A I S (Plan). The

corrective mode1 for calculating the volume and specific surface area of this shape will be

called the Rhombic model because it occurs in the rhombic face of the sphere

Page 69: Modelling of Clogging in Laboratory Column Experiments

arrangement. It c m be seen in Figure A1 -5 and in the three dimensional drawing in

Figure 3.8(b) that this shape is sirnilar to the Square model shape, except that the cutting

planes intersect with an inside angle of 120°, but still lie tangent to the contact points.

3.4.6.4 Special Cap Model

The tetragonal-sphenoidd packing arrangement has, in addition to the rhombic

overlap corresponding to its rhornbic face, a special cap overlap corresponding to its

special rhombic face. The cross-section of the shape of this overlapped volume is shown

in Figure AL8 (Section) and is sïmilar to the regular spherical caps which occur at each

contact point. The simple model required to account for the volume and surface area of

this overlapped space is called the Special Cap model. A three-dimensional depiction of

this shape is given in Figure 3.8(c). The use of the Special Cap model differs frorn the

Square and Rhombic models because, in contrast to these models, the volume and surface

area of the shape is to be subtracted fiom the total, not added. This is because the overlap

creating a special cap is an overlap of actual film while the other overlap models are for

the overlap of contact point volumes which is already accounted for by the Deb (1 969)

equation. A special cap is essentially a contact point overlap like those which occur

between al1 spheres, but which occurs at a specific film thickness in the special rhombic

face of the tetragonal-sphenoidal racking arrangement.

3.4.6.5 Geometric Complexity

Geometric complexity of the cubic and orthorhombic packing arrangements either

did not occur or coincided with pore occlusion, thus there was no need for a corrective

Page 70: Modelling of Clogging in Laboratory Column Experiments

mode1 beyond that given in colurnn (4) of Table 3 -3. However, for the tetragonal-

sphenoidal and rhombohedral packing arrangements, for film thicknesses between those

given in colurnn (5) and (7) of Table 3.3 it was not possible to get an exact geometric

solution due to the geometric complexity of the overlaps for this range of film thickness.

Thus for the tetragonal-sphenoidai and rhombohedral packing arrangements it is assurned

that upon correction of the porosity and specific surface values using the above three

models, a iinear relationship may be employed for calculation within the region of

complexity to the known point of pore occlusion.

Table 3.3 - Corrective Models and Corresponding Film Thickness ( 2L, 1 d,)

Packing Arrangement

Name

Cubic

Orthorhombic

Tetragonal- Sphenoidal

3.4.7 Derivation of the Square and Rhombic Model Solutions

3.4.7.1 Introduction

In order to correct the porosity and specific surface equations, the volume and

surface area of the overlapped shape as a function of film thickness, sphere size, and

packing arrangement must be derived. The overlap shape is depicted at the top of Figure

3.9. Note that in this figure the sphere of radius R is the shape of the surface of the film

First Cap Overlaps

(1)

0.4142

O. 1547

0.1547

0.1547

Second cap

Overlaps

(3

- 0.4 152

0.2247

0.2247

Corrective Mode1

(2)

Square

Rhombic

Rhombic

Rhornbic

Corrective Mode1

(4

NA

Square

Special Cap

NA

Corrective Mode1

(6)

N A

NA

L inear

L inear

Geometric- all~

CompIex Overlaps

(5 )

0.732

0.5275

0.2649

0.2247

Complete Pore

Occlusion

(7)

0.732

0.5275

0.3228

0.4 142

Page 71: Modelling of Clogging in Laboratory Column Experiments

coating an ideal sphere (not shown) centred at the origin. Using symmetry about the y = O

plane, half of the shape is defined as the portion of the sphere of radius R formed by the

intersection of the y = O plane with a plane intersecting at y = 0, z = a, and interior angle

8. Due to symmetry about the y=O plane the interior angle 0 is half of the actual angle,

and the volume calculated is half the actual volume. Control of the intenor angle is

required because for the square model the angle is 90" while for the rhombic model the

angle is 120". This also would allow for calculation of other shapes if required.

3.4.7.2 Limits of Integration

The dotted lines in Figure 3.9 (Top) show the projection of the y > O side of the

shape on the z = O plane. This projection is an ellipse on the plane, and thus, in order to

calculate the limits of integration, the equation of the ellipse must be derived. The

diagram in the middle of Figure 3 -9 illustrates the cross-section at the x = O plane, the

bounds for z and the distance to the centre of the projected ellipse from the ongin. By

equating the equations of z, and knowing the location of the centre of the ellipse, the

equation of the ellipse on the z = O plane was solved. This allowed the calculation of the

length of the major and rninor axes of the ellipse, shown at the bottom of Figure 3.9, and

required for the limits of integration.

The integral of the volume was found to be

Page 72: Modelling of Clogging in Laboratory Column Experiments

where the lirnits are

b = <jsin29 (R' - a ' s in28) - a s i n û c o s û i'

and the integral of the surface area is

where lirnits b, and b, are the sarne as for the volume, a is the distance from the centre of

the sphere to the intersection of the cut with the y = O plane and R is the radius of the

sphere. The integrals could not be solved analytically and were evaluated numerically as

described below.

3.4.7.3 Numerical Analysis of Integrals

The integrals of Equations 3.6 and 3.8 were numerically evaluated using the

program MathCad. For a particular solution model, since 8 is constant, the volume or

surface area of the overlap shape depends only on radiai lengths a and R. It was

hypothesized (and subsequently verified) that if the volume is normaiized with respect to

R~, one function would describe the normalized volume as it varies with a/R for al1

applicable values of a and R. A sirnilar finding was applied to the surface area normalized

with respect to R ~ .

Page 73: Modelling of Clogging in Laboratory Column Experiments

In order to calculate the applicable range of a/R , it must be converted to terms of

2L,/dp. The applicable range of 2Ljdp for the square mode1 in exact terms is:

while for the rhombic model the range is

Geometrically it is known that R and a for the integration in terms of tL/d, are

and

a = - d p if square model, J2

Therefore the ratio d R in terms of 2L/dp is

Page 74: Modelling of Clogging in Laboratory Column Experiments

and the applicable range of the square model is

while the applicable range of the rhombic model is

3.4.7.4 Numerical Solution of Square Mode1 Shape for Volume and Surface Area

To solve the square model shape the angle 0 was set to d 4 (45"). To check for

the independence of the normalized volume or surface area of the length R, calculations

were performed for R values of 0.00 1, 0.01, 0.1, 1, 2, 5, and 10. A set of values of the

ratio a/R were selected from the applicable range. The length a was then calculated for

each value of R. The results of the numerical analysis evaluating the normalized volume of

the overlap shape used to correct the square model are s h o w in Figure 3.10. tt was

found that the normalized volume was independent of the value of R. To obtain a ciosed

Page 75: Modelling of Clogging in Laboratory Column Experiments

fom expression, a fourth order polynomial was fit to the results, and the coefficients are

given in Figure 3.10. The curve fit was impiemented using the cornputer program

SigrnaPlot which utilizes the Marquardt - Levenberg algorithm. The results of the

numerical analysis for the surface area of the shape are shown in Figure 3.1 1. Sirnilar to

the volume andysis, it was found that the normalized area was independent of the value of

R. A fourth order polynomial was fit to the results, and the coefficients are given in

Figure 3.1 1.

3 -4.7.5 Numerical Solution of Rhombic Model Shape for Volume and Surface Area

For the rhombic model shape, the angle was set to d 3 (60"). The values of R

were the same as those used in the square model shape analysis. A set of a/R values

within the applicable range for the rhombic model shape were selected. The normalized

volume results of the numerical integration are shown in Figure 3.12. The coefficients of

the fourth order polynomiaf fit to the data is given in Figure 3.12. The surface area

results are plotted the coefficients of the fourth order polynomial that provide a fit to the

results are given in Figure 3.13. Both the normalized volume and area were found to be

independent of the choice of R.

3 A7.6 Corrective Model Solutions for Porosity and Specific Surface

The volume and surface area of the overlap shape are descnbed by the following

equations:

Page 76: Modelling of Clogging in Laboratory Column Experiments

where Vol is volume, S is surface area, and b[#] represents the calculated coefficients.

The equations for correcting the volume and specific surface equations for the two models

were denved by substituting Equation 3.13 for a/R and the coefficients for each model

shape and by division by the ce11 volume, a&,'. The square mode1 correction equation for

each overlap for porosity is

and the square model correction equation for each overlap for specific surface is

The rhombic mode1 correction equation for each overlap for porosity is

and the rhombic model correction equation for specific surface is

Page 77: Modelling of Clogging in Laboratory Column Experiments

It should be noted that V, and VR are not volumes, but dirnensionless terms (one overlap

volume correction divided by unit ce11 volume). S, and SR are corrections to the specific

surface with dimension CL-'].

3.4.8 Derivation of the Special Cap Model Solution

3.4.8.1 Porosity

The Special Cap Modei required a calculation of the porosity contribution

(correction value) for the special cap. The volume, V, of a spherical cap is calculated

using

where R is the radius of the sphere plus film thickness, and h is the height of the cap. For

this analysis,

and

Page 78: Modelling of Clogging in Laboratory Column Experiments

where on the right side of Equation 3.24, the term in the brackets is the radius of the

sphere plus film, and the subtracted tenn is the length to the midpoint between the two

spheres in this direction, see Figure A1.8 (Section). Substitution of Equations 3 -23 and

3.24 into Equation 3.22, and division by the volume of the unit cell, a,%', results in the

correction factor to be applied to the porosity equations:

where V,, is not a volume, but a dimensionless term of solid (ie sphere and film) volume

divided by total unit ce11 volume.

3 A.8.2 Specific Surface

The Special Cap Mode1 required a simple calculation of the specific surface

contribution of the special cap. The basis is the surface area, S, of a spherical cap,

where R and h are previously defined in the porosity derivation, and where the surface

area excludes the surface area of the circular base of the cap. Substitution of Equations

3.23 and 3.24 and division of the surface area by the unit volume, a,,,d,', results in the

specific surface contribution of this shape given by this equation:

Page 79: Modelling of Clogging in Laboratory Column Experiments

3.4.9 Derivation of Final Corrected Equations

3.4.9.1 Base Equations

For al1 four packing arrangements the underlying porosity equation (Taylor, 1990)

i s

and underlying specific surface equation is

where the calculated maximum film thickness under which the equations may be applied, is

and where n,, is the porosity and 4,, the specific surface for this range of film

thicknesses using Taylor's equations, a, is the packing factor, m is the number of contact

points, L, is the total thickness of film presumed to be impermeable and d, is the average

Stone diameter. The packing arrangement corresponding to each m value is listed in

column 1 of Table 3.

Page 80: Modelling of Clogging in Laboratory Column Experiments

3.4.9.2 Corrected Equations for Cubic Packing

For the cubic packing arrangement (m = 6) with film thicknesses greater than the

specified lirnit stated in Equation 3 -30 the porosity and specific surface equations and

applicable range are

where V, and S, are calculated using Equations 3.18 and 3.1 9.

The corrected variation of porosity with film thickness using Equation 3.28 and

3.3 1 is illustrated in Figure 3.14. The corrected variation of specific surface with film

thickness using equations 3.29 and 3.3 1 is illustrated in Figure 3.1 5. A symbol is used to

indicate the point at which a critical thickness is reached, and the equation is changed. It

can be observed that the equations converge to porosities and specific surfaces of zero at

the same film t hickness t hat was geometrically calculated.

3 -4.9.3 Corrected Equations for Orthorhombic Packing

The porosity and specific surface equations and applicable film thickness range for

the orthorhombic packing arrangement (m = 8) for film thicknesses greater than the

specified lirnit stated in Equation 3.30 are

- As - As, Tay + 6 % J

-

Page 81: Modelling of Clogging in Laboratory Column Experiments

and

where n is the corrected porosity and A, is the corrected specific surface area for the film

thickness range given, and V, ,V, , SR and S, are calculated using Equations 3.20, 3.18,

3 -2 1 and 3.19 respectively.

A plot of the corrected porosity results using Equations 3.28, 3 .32 and 3.33 are

shown in Figure 3.14. The corrected specific surface results are shown in Figure 3.15.

Two symbols dong the curve indicate the critical points at which the equations employed

were changed from Equation 3.28 or 3.29 to 3.32 and fiom Equation 3.32 to 3.33.

Similar to the Cubic curves, the corrected equations reach porosities and specific surfaces

of zero at the same film thickness as was calculated geometncally.

3 -4.9.4 Corrected Equations for Tetragonai-Sphenoidal Packing

For Tetragonai-Sphenoidai packing the equations describing porosity and specific

surface for film thicknesses greater than the limits given for m=10 in Equation 3.30 are

and

Page 82: Modelling of Clogging in Laboratory Column Experiments

where n is the corrected porosity and A, is the corrected specific surface area for the given

film thickness range, and V, ,SR , V,, , and S,, are caiculated using Equations 3.20, 3.21.

3.25 and 3.27.

A plot of the corrected porosity results using Equations 3.28, 3 -34 and 3.35 are

show in Figure 3.14. The corrected specific surface results, using equations 3.29, 3.34

and 3 -3 5 are shown in Figure 3.15. The first two symbois along the curve indicate the

criticai points at which the equations employed were changed from Equation 3.28 or 3.29

to 3.34 and fiom Equation 3.34 to 3.3 5 . On the curves for both porosity and specific

surface an open triangle filled with a dot indicates the limit of special cap corrective

model. It can be seen that this limit occurs at low values of porosity and specific surface,

and are close to, but not quite at, the film thickness at which pore occlusion occurs.

A linear relationship estimating the remaining values of porosity and specific

surface to pore occlusion may be applied since this portion of the curve is not very

significant. The majority of any clogging calculation will be for lesser film thicknesses.

Using the calculated porosity and specific surface at the limit of Equation 3.3 5, and the

film thickness at which pore occlusion occurs, the equations estimating the remaining

portion of the curves are:

Page 83: Modelling of Clogging in Laboratory Column Experiments

The linear completion of the curve is show in Figures 3.14 and 3.15.

3.4.9.5 Corrected Equations for Rhombohedral Packing

For rhornbohedral packing the equations calculating porosity and specific surface

with film thicknesses greater then the limits stated in Equation 3.30 are

where n is the corrected porosity, and A, is the corrected specific surfaces for the given

film thickness range, and V, , and SR are calculated using Equations 3.20 and 3.2 1 .

The corrected porosity results of Equations 3.28 and 3.37 are plotted in Figure

3.14, and the corrected specific surface values of Equations 3 -29 and 3.37 are plotted in

Figure 3.15. An open triangle indicates the beginning of the corrected curve and a dotted

open triangle indicates its limit. The limit occurs at Io w values of porosity and specific

surface, and close to, but not at, the point of pore occlusion. Using the same reasoning as

with the tetragonal-sphenoidd curves, a linear estimation was applied. Using the

calculated porosity and specific surface at the limit of Equation 3.37, and the film

thickness at which pore occlusion occurs, the equations estimating the remaining portion

Page 84: Modelling of Clogging in Laboratory Column Experiments

of the curves are given by:

The linear completion of this curve is s h o w in Figures 3.14 and 3.15.

3.4.10 Note Regarding Taylor et al. (1990)

In the work by Taylor et al. (1990) fiom which the porosity and specific surface

expressions are taken the break down of the theory is amibuted to the filling of the narrow

passageways between the spheres and the isolation of enclosed pore space, and not to the

geometric complexity caused by the overlapping of film volumes at the contact points. In

the case of the cubic and rhombohedral packing arrangements these film thicknesses

coincide, that is, the film thickness at which pores become isolated equals the film

thickness at which film becomes overlapped. With the other two packing arrangements,

pore discontinuity occurs after the first occurrence of film overlap at the contact points. It

is true, therefore, that for two of the four packing arrangements the mode1 by Taylor et al.

breaks down at the film thickness that the pore spaces become isolated, but it does not

break down because of this action, and in the other packing arrangements it breaks down

at smaller thicknesses than pore discontinuity. Taylor et al. determined the film

thicknesses of pore discontinuity to be the sarne as the averages listed in Table 3.2 except

the orthorhombic arrangement was given a value to 0.24. It is suggested that the authors

erroneously averaged one square layer and two rhombic layers instead of two square

Page 85: Modelling of Clogging in Laboratory Column Experiments

layers and one rhombic layer in calculating this Nm thickness.

3.5 FILM THICKNESS AT CLOGGING

3.5.1 Pore Discontinuity

Pore discontinuity is the obstruction to flow within the openings between the

granular media. The first occurrence of pore discontinuity will occur where the pore

space is at its minimum, which occurs in the faces of each amangement. The film

thickness at which the void space in the plane of each face becomes filled is equal to the

critical film thickness at which the overlap of film occurs in the face as calculated

geometricaily in Appendix Al . The film thicknesses are summarized in Table 3.4, column

1, for each face of each packing arrangement.

Table 3.4 - Summary of Film Thicknesses at Pore Discontinuity in Terms of ZL, I d,

Name 1 Pore Discontinuity 1

Cubic

Orthorhombic

Since flow in the model is in only one direction in each element, and since the faces

0.5 142

I

in each packing arrangement have no directional representation in the model, it can not be

0.4 142

Rhombo hedral 1 O. 1547

determined whether having one or even two faces filled obstructs flow. Since each face

0.4 142

0.1547 1 0.1547 1 O. 1547

0.4 142

Note : the values 0.4 14 and 0.155 are from fi - 1 and 2 lJf respectively.

0.4 142 O. 4 142

O. 1547 0.3277

Page 86: Modelling of Clogging in Laboratory Column Experiments

separately may not be used to determine total pore discontinuity, it may be assumed that

the film thickness at which the average void space of the faces is filled rnay represent the

occurrence of pore discontinuity for a particular packing arrangement. The average film

thicknesses are listed in Table 3.4, column 2.

Mathernatically, using the average film thickness to represent pore discontinuity

may result in two faces of the unit ce11 being open, as in the case of the orthorhombic

packing arrangement. It must be emphasized, therefore, that the different packing

arrangements are used simply to represent the porosity and specific surface of the granular

media. For al1 packing arrangements the average film thickness at which pore

discontinuity occurs will be the limiting, or highest film thickness reached before the layer

is deemed a clogged or discontinuous layer and normal flow through is discontinued. The

point of pore discontinuity is illustrated in Figures 3.14 and 3.15 using small filled circles.

The cntical film thickness used in the model is found by interpolating between the cntical

film thicknesses of the two packing arrangements bounding the estimated initiai porosity.

The porosity and specific surface area of a porous media afler the accumulation of

a known thickness of film may be calculated using equations based on a model in which

the media is represented by regularly packed spheres of equal diameter. The porosity and

specific surface model is based on the work of Taylor et aL(1990). Film thicknesses were

geometrically detemiined above which Taylor's equations calculated erroneous volumes

and surface areas, and thus erroneous porosity and specific surface values. For sorne

Page 87: Modelling of Clogging in Laboratory Column Experiments

packing arrangements a significant region of error could be found between the maximum

applicable film thickness and the geornetrically calculated thickness at which the porosity

and specific surface becomes zero. The errors were found to be caused by the double

counting of overlapping volumes and surface areas. Equations were derived to be used

within the region oferror for each of the four packing arrangements by deriving equations

calculating the erroneous volumes and sunace areas as a function of the packing

arrangement, sphere size and film thickness.

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Cubic I Orthorhombic Three Square Faces Two Square Faces One Rhomblc Face

Tetragonal-Sphenoidal One Speclal Rhombic Face Two Rhombic Faces

Rhombohedral Three Rhombic Faces

1

:igure 3.1 : The four stable, regular pocking arrangements, illustateci as foces of the unit cell.

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Packing First Volume Overlap Arrangement Occurence - Cubic O Square - - Orthorhombic Cl Rhombic -- Tetragonal-Sphenoidal A Rhombic

1 Rhombohedral v Rhombic 1

Film Thickness, 2LJdd,

Figure 3.2 : Variation of porosity with film thickness using equations by Taylor et al. (1990). Symbols indicate modal breakdown due to the occurrence of volume overlaps.

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Packing First Volume Overlap Arrangement Occurence

Cubic Orthorhombic Tetragonal-Sphenoidal Rhombohedral

Square Rhombic Rhombic

v Rhombic 1

Film Thickness, 24d,

Figure 3.3 : Variation of nonnalized specific surface area with film thickness using equations by Taylor et al. (1990). Symbols indicate model breakdown due to the occurrence of volume overlap.

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Figure 3.4 : Verification of length of radius of interface circle at any contact point.

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SECTION

- - - - -

Figure 3.5 : Verification of film fhickness at onset of spherical cap overkip for cubic packing.

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CTI

Figure 3.6 : Verification of film thickness at complete occlusion of cubic packing. Double hatched area indicotes overiop of spherical caps.

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Figure 3.7 : Verifkation of film thickness at occurrence of first overlap for orthorhom bic packing. Hatched area indicates spherical cap at two contacts.

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Figure 3.9 : Diagram of shapes for volume and surface area integrdion.

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Square Model(8 = rr/4 )

1 I 1 Numerical solution with R=0.001,0.01,0.1,1,2, 5, 10

- Cuwe fit to R = 1 -

-- Calculated Coefficients

I bO = -0.491 757 bl = 5.002605 b2 = -1 1.7991 81 b3 = 10.554990 b4 = -3.266650

Figure 3.10 : Cuwe fit to normalized volume of overiap as a function of a/R for the square corrective model.

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Numerical solution wi R = 0.001, 0.01, O. 1, Curve fit to R = 1

Square Model ( e = 1

Calculated Coefficients

I bO = 50.31 5497 b l = -220.075399 b2 = 370.982948 b3 = -282.654845 b4 = 81.431 397

Figure 3.1 1 : Curve fit to normalized surface area of overiap as a function of alR for the square correction model.

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R = 0.001, 0.01, 0.1, 1, Curve fit to R = 1

I 1 l Rhombic Model (e = r1/3 )

I Calculated Coefficients

I

- bO = 0.01 51603 b l = 4.098545 b2 = -1 1.8408021 b3 = 11.3171685 b4 = -3.590046

Figure 3.12 : Cuwe fit to normal for the rhombic corrective mod

zed volume of overiap as a function of a 1 R $1.

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Numerical solution with R = 0.001, 0.01,0.1, 1, 2, 5, I O Curve fit to R = 1

I I I

Rhombic Model ( e = n13 ) I

Calculated coefficients

I

Figure 3.1 3 : Cunre fit to normalize a/R for the rhombic corrective moc

d surface area of overlap as a function of Iel.

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Packing

\ Corrective Model Curve

Arrangement Rhombic Square S. Cap Linear End

Pore Discontinuity

- - Orthorhombic O El -- Tetragonal -

Sphenoidal A ....... Rhombohedral v

Film Thickness, 24d,

Figure 3.14 : Corrected variation of porosity with film thickness. Symbols indicate the beginning of corrective models, pore discontinuity and curve termination.

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Packing Corrective Model Curve Arrangement Rhombic Square S. Cap Linear End

Cubic O a - - Orthorhombic O m -- Tetragonal -

Sphenoidal A A ....... Rhornbohedral v

Pore Discontinuity

Film Thickness, 24d,

Figure 3.15 : Corrected variation of normalized specific surface with film thickness. Symbols indicate the beginning of corrective models, pore discontinuity, and curve termination.

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CHAPTER 4

CLOGGING MODEL: FORMULATION

The objective of this chapter is to develop and implement model for predicting the

rate of clogging in laboratory column experiments. The model combines concepts

associated with transient anaerobic, fixed film biologicai processes (such as those used in

wastewater treatment) with concepts of geotechnical engineering involving fluid flow

through saturated porous media. The model uses a time marching algorithm to mode1 the

evolution of the infiuent and efnuent organic concentration, biofilm thickness, inert biofilm

plus mineral film thickness and porosity at any position or time.

4.2 REPRESENTATION OF COLUMN FLOW

4.2.1 Introduction

The model assumes a column test is an experiment in which landfill leachate (or a

synthetic leachate) is passed through a cylinder packed with granular media, entenng the

column fiom a single port at one end and exiting from a single port at the other (see

Figure 4.1 a). The column is discretized into a nurnber of elements (also called segments

hereafter). The manner in which the system is subdivided into elements is theflowfield

controlling fluid flow in the system. The column test flow field is rnodelled as 'one

dimensional' advective flow, that is, fiow is fiom the infiuent end of the column through a

single line of segments along the length of the colurnn as illustrated schematically in Figure

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Each segment, or "element" is assumed to act as a separate, fixed film reactor.

Acting as a reactor, each element reduces the concentration of substrate in the fluid as the

chemicai energy is converted partially into bacteria ceIl mass. This growth of biomass

foms an active film layer on the porous media. The bactenal activity aids in the formation

of a second film, an inactive film which consists of inert biomass and solid precipitate. The

modelling of these processes are detailed in Section 4.4. The active film grows on the

outer-most surface, whether that be the media or inactive film, and the inactive film is

assumed to fom directly on the porous media. The idealization of the biofilrn is described

in fiil1 in Section 4.4.3.

The influent substrate concentration to a segment (except the first segment) is

equal to the emuent substrate concentration of the previous segment in the series, as

s h o w in Figure 4.1 c. The transport of substrate fiom one segment to the next is purely

by advection. Saturated flow conditions are assumed for al1 segments. Flow through this

system is controlled by the segment with the greatest clogging; once a critical film

thickness is reached in the segment the flow stops (this corresponds to what is actually

observed in these experiments, Armstrong (pers. corn.)).

4.2.2 Representation of the Porous Media

The porous media of the flow system is represented using a volume of ideal

spheres of equal diameter. The diameter of the spheres is assumed to be equal to the

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average diameter of the media while the packing arrangement of the spheres is related to

the initial porosity of the media. This idealization of the porous media allows geometric

calculation of the porosity and specific surface as a function of the film thickness on the

porous media. Details are given in Chapter 3.

4.2.3 Boundary Conditions

The boundary conditions involve a specified initial influent flow rate and

concentration. The effluent flow rate must (for reasons of continuity) be the same as the

idluent however the effluent concentration is calculated by the mode1 (and not

prescribed). The initial condition is zero substrate and a specified thickness of biofilm in

each segment (as discussed in Section 4.4.5.2). The leachate is assumed to provide the

substrate for biofilm growth, but not bacteria.

4.2.4 Advection Algorithm

4.2.4.1 Introduction

Flow (and hence substrate) is transferred from one segment to another over time

using a time stepping process described below. As noted above, the influent concentration

of substrate to the first segment is a boundary condition (which could vary with time). For

each subsequent segment, the effluent concentration of the neighbouring upstream

segment is the concentration of the influent to this segment. To simulate the movernent of

the treated flow through the column segments consideration is given to the time required

for the flow to move fiom the influent end of the column to the effluent end of each

segment.

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4.2.4.2 Calculation of Ruid Travel Tirne Delays

The average tirne required for fluid to move from one end of a segment k to the

other end is given by

where V is the volume of the segment, n is the clean media porosity of the element, and Q

is the flow. If tirne steps are of length At, the total number of t h e steps elapsed as fluid

travels @y advection) fiom the beginning of the colurnn to the end of a segment k is T,

(the time delay in fiactions of timesteps) where

where p is the number of segments. and where T, = O.

It is assumed that the biomass growth and treatment of leachate in the segment

does not occur until the siug of leachate that entered the segment reaches the end of the

segment and hence these values are rounded up to the nearest whole number to arrive at

the number of tirnesteps required to pass through the column to the effluent end of

segment k, called Nk . Rounding the total time delay to the effluent end of each segment,

instead of rounding the time delay within each segment minimires the accumulation of

round-off error along the length of the column. Nk is rounded up using

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As an example, Table 4.1 gives the calculated values of T, and N, for a 65 cm long column

divided into 13 segments, and n = 0.382, V = 10 1.53 cm3, At = 0.2 d, Q = 1 120 cm3/d .

This is the column to be modelled in Section 5.3.

4.2.4.3 Management of Calculated Effluent Concentrations

Figure 4.2 illustrates how the advection algorithm manages the effluent

concentrations over time. in this figure, Sc indicates a calculated effluent concentration

for a segment, and the arrows indicate the timestep from which the influent is retrieved.

The figure shows the effluent history for the column up to the completion of timestep 5

(1 .O days). In the figure it can be seen that on timestep 1 the first 5 segments calculate an

effluent concentration, as indicated by each having an S. value, and this calculation is

based the effluent concentration received from each upstream segment as s h o w by the

arrows. The remaining segments have fluid travel time delays of greater than 1 timestep,

therefore the first slug of leachate does not reach these segments during timestep 1, and

thus retum zero effluent values. On timestep 2 the first 5 segments treat a new slug of

leachate, while segments 6 to 1 1 treat the slug from the previous timestep since during this

timestep the slug travels past the end of segment 11. The diagonal arrow in the row

between segments 5 and 6 illustrates that between timestep 1 and 2 the slug of leachate

h m segment 5 passes through segment 6 and then segments 7 through 1 1.

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The program keeps record of the required effluent concentrations of the previous

timestep for use in the current timestep. The bracketed matrix illustrates the values which

must be stored in order to calculate the effluents for timestep 5 for this example. The

columns of stored effluent concentrations in this matrix are numbered fiom 0, and in this

case the algorithm calculates a required storage of 2 columns of data, numbered O and 1.

The column on the far right of this matrk (in this case colurnn number 1 of the matrix)

contains the calculated effluent values of the current timestep, timestep 5, while al1 other

columns in the matrix contain the recorded effluents of previous timesteps (in this case

only column O of the matrix, timestep 4, is required).

In order to retrieve the correct recorded effluent concentration fiom the matrix, its

location must be calculated. Since each effluent concentration in the matrix is defined by

row (equal to segment number) and colurnn, and the segment number for retrieval of an

influent to a segment is always the previous segment number, only the column number

must be calculated. The delay values N, are used to calculate the column number location

in the matrix of recorded concentrations corresponding to each segment. This column

number, P, is calculated using:

The P, values for the column test example are given in Table 4.1. By inspection of Figure

4.2 and Table 4.1 it can be seen that in the current timestep (tirnestep S ) , the values of P,

indicate the matnx colurnn number fiom which each segment retrieves an infiuent value,

either O or 1, where a O indicates the slug concentration was calculated during the

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previous timestep, and a 1 indicates the slug concentration was calculated dunng the

current timestep. For example, segment 5 receives the effluent of segment 4 from column

P, = 1 (which is the previously calculated effluent fkorn this timestep), while segment 6

receives the effluent of segment 5 from column P, = O (which was calculated in the

previous timestep).

Table 4.1 : Calculated variables for advection aigorithm example.

1 1 Segment Number 1

This advection algorithm allows the location of each segment's influent to be

precalculated so that repetitive computations cm be ornitted. Once a timestep is

complete, the record shifis its columns by one timestep to the right, thus making the just

completed timestep the previous timestep. This algorithm allows for future expansion, for

example, the influent concentration may be made variable and retrieved from the

concentration record, or the fiow may be distributed along the length of the series of

segments like a drainage layer. If the total length of the flow field is short andfor the flow

is high and the time step length is sufficiently long, there may be no delay applied.

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4.4 BIOLOGICAL PROCESSES WITHIN ELEMENT

4.4.1 Introduction

The application of synthetic landfill leachate to each element of the flow field

encourages biological processes within the element. The model assumes that the supply of

organic compounds in the synthetic leachate provides a substrate for biological growth

and the formation of biofilm on the granular media. The substrate is considered to be the

single required nutrient which is not available in excess, and therefore limits the rate of

biofilm growth. This section deals with the processes occumng within a single element

dunng a single time step only. The routines required to impiement each element's

processes within the structure of the system's flow field and with respect to time, are

covered in Section 4.5.

The rate of biofilm and mineral film growth in a layer will depend on the bio-

kinetic parameters, influent COD concentrations, amount of flow, fluid mass density, the

physical dimensions of the flow field, the average diameter of the granular media, the

choice of packing arrangement, the system temperature and film properties such as

densities and mineral accumulation yield rate.

This section outlines the idealization of the films, and then, following the model

procedure, discusses the calculation of substrate flux, biofilm and mineral growth and loss,

and the new porosity and specific surface area. The iterative routine incorporating the

previous 3 topics to denve the revised effluent concentration is discussed next, and is

followed by a second iterative routine utilizing repeated calculations of the revised effluent

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concentration to converge on a total loss coefficient. Lastly, the section discusses the

convergence critena and routines used.

4.4.2 Process Description

A non-steady state biofilm has a thickness that changes with time. Growth of ce11

matter is proportional to the flux of substrate into the biofilm, while losses occur due to

bacterial detachment and respiration decay. Non-steady biofilm growth and loss due to a

single substrate can be modelled using an algorithm modified fiom Rittmann and McCarty

(198 1) and Rittmann and Brunner (1984). The non-steady state growth and loss

algorithm is combined with equations to model the change in porosity and specific surface

are% mass balance equations, and detachment equations. Due to non-linearity, two

coupled iterative procedures are required to derive each layer's effluent COD

concentration, film thickness, porosity, and specific surface area at each time increment.

A simplified flow diagram of the procedures incorporated to model the biological

processes in one element during one time step is illustrated in Figure 4.3.

4.4.3 Biofilm Idealization

For model simplification, the biofilm is idealized as shown in Figure 4.4(a). The

active portion of biofilm is assumed to have a unifonn thickness of L, (L where L is units

of length), and a uniform density of X, (Mx L~~ where Mx is mass of bactena). A liquid

diffision layer of thickness L, (L) represents a theoretical unifonn layer of stagnant liquid

adjacent to the biofilm which is void of microorganisms and offers substrate mass

transport resistance between the bulk liquid and the biofilm surface. The bulk liquid is

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assumed to be perfectly mked. The inactive film lies between the active film and the

attachment media and is assumed to have a uniform thickness of L, (L), and a unifonn

density of X, (M,L-~ where MT is total mass of solids).

Figure 4.4(b) depicts the substrate concentration profile through the biofilm.

Syrnbols Sb, S,, S, and S, in Figure 4.4@) represent the substrate concentrations in the

bulk liquid, at the outer surface of the biofilm, within the biofilm, and at the inactive film,

respectively (ail have units of Ms L - ~ where Ms is the mass of substrate). It is assumed

that the substrate concentration within the biofilm, S , only varies in the z direction, the

direction normal to the surface of the biofilm. It is also assumed that the substrate neither

difises into, or is utilized by, the inactive film and attachment media.

The biofilm growth and loss mode1 will include five processes occumng

simultaneously. The five processes are: mass transport of the substrate across the

difision layer, difision of the substrate in the biofilm, the utilization of the substrate for

ce11 growth, the growth of active cells due to this utilization, and the loss of biomass due

to detachment and decay of ce11 matter.

4.4.4 Calculation of Substrate Flux

The third step indicated on the flow diagram, Figure 4.3, is the calculation of the

flux of substrate into the biofilm. By considering substrate utilization kinetics similar to

Monod kinetics and molecular difision, Atkinson and Davies (1974) developed

approximate solutions for flux, J, into a biofilm, as a function of biofilm constants and

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thickness, L, and surface substrate concentration S, :

where J is the substrate flux into the biofilm (Ms L" T'), (î is the maximum specific rate of

substrate utilization (Ms MyL TI), Ks is the half-maximum rate substrate concentration

(Ms LJ), and q is an effectiveness factor relating the ratio of actual flux to the flux if the

film were entirely penetrated at concentration S,. In dimensionless ternis (Rittmann and

McCarty, 198 1),

where the new dimensionless variables are defined as folIows:

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and where z is the standard bioflm depth dimension in which

where D is the molecular diffusion coefficient of the substrate in the liquid (L2 T-l) and D,

is the molecular diffusion coefficient of the substrate within the biofilm (L* TI).

The effectiveness factor, q, was found (Atkinson and Davies, 1974) to be related

to S, and L, and the relationship, in dimensionless terms (Rittrnam and McCarty, 198 1)

was

where

Due to rnass transfer resistance, the substrate concentration at the biofilm surface,

S,, is not equal to the bulk substrate concentration, Sb. While the bulk substrate

concentration is assumed to be a known value at each iteration containing this routine, the

surface concentration is unknown. Mass transfer resistance is expressed in the mode1 by

Page 115: Modelling of Clogging in Laboratory Column Experiments

employing an effective diffusion layer where it is assumed mass transport resistance

between the bulk Liquid and the biofilm surface occurs in its entirety. Assurning a one

dimensional diffision layer, Fick's first law gives

which may be converted to dirnensionless terms and combined with Equation 4.6a to yield

where the new dimensionless terrns are defined

A quadratic expression may be denved fiom Equation 4.94 and the quadratic formula

solution according to Rittmann and McCarty (198 1) is

An iterative procedure can be used with Equations 4.10 and 4.7a to calculate an

acceptable effectiveness factor, q, and dirnensionless expression of the surface substrate

concentration, s,' . Equations 4.6a and 4.6b rnay then be used to calculate the flux into

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the biofilm. The steps taken were:

1. Convert inputs D, L, Sb and L, into dimensionless f o m using Equations 4.6c,

4.6d, 4.9b and 4 . 9 ~ .

2. Initialize the effectiveness factor q by setting the first estimate using

3. Calculate initial guess of S,' using Equation 4.10.

4. Calculate q' using Equations 4.7a and 4.7b.

5 . Check for convergence of q with q' to the given tolerance.

6. If convergence has not occurred, set q = q' and repeat steps 3 to 6.

7. Upon convergence, calculate J' using Equation 4.6a and J using Equation 4.6b.

A routine has thus been outlined which determines the substrate flux into the biofilm given

the kinetic constants, a known bulk substrate concentration and a known biofilm

thickness.

4.4.5 Calculation of Biofilm and Mineral Growth and Loss

4.4.5.1 Introduction

The calculation of change in thickness of the active biofilm and change in thickness

of the mineral and inen film, which added together f o m the inactive film, for the current

time step is step four as indicated in the flow diagram in Figure 4.3.

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4.4.5.2 Non-Steady Growth and Loss of Biofilm

The expression of non-steady growth and loss of biofilm developed by Rittmam

and Brunner (1984) differs fi-om other non-steady models due to the fact that it

distinguishes between decay Losses and shearing losses.

The biomass growth rate, r, (M, L3 T-'), was expressed by

where Y is the tme yield coefficient (M, M i 1 ) , and the biomass loss rate, r,, (Mx L" T-')

was expressed by

where b' is the first-order biofilm loss coefficient (TI). The growth and loss of biofilm

routine may be derived by first combining Equations 4.12 and 4.13 so that for an

increment of time,

where r,, is the net biofilm growth rate. This equation may be simplified to become

(fittmann and McCarty, l98Oa, Rittmann and Brunner, 1984)

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where t is time (T) and which may be integrated with respect to time, and if the tirne

incrernent, A t is small, J and b' do not change significantly, and Equation 4.15 becomes

Equation 4.16 can be used to calculate changes in biofilrn thickness for finite time steps.

By irnplementing Equation 4.16, the calculation of the new active film thickness in the

model is found using:

where the flux, I, used in the equation is calculated as outlined in Section 4.4.4 and the

biofilm thickness, L, , is the thickness calculated in the previous time step for this element.

The solution for L, is marched fonvard in time by incrernents of At. A very small initial

estimation of L, is required for the first time step since the calculation of substrate flux, J,

in Equation 4.17 requires that a non-zero thickness of biofilm exists. The initial film

thickness suggested by Rittmam and Bmmer (1984) and used throughout this thesis is

0.05 pm, which according to Rittmann and Brumer (1984) represents about 5% surface

coverage for a monolayer of bacteria.

4.4.5.3 Mineral Precipitation and Inert Biomass Accumulation

The composition of the inorganic portion of clog material has been found (Brune

et al. (1991) , Rowe et al. (1995a)) to be predorninately calcium carbonate, CaCO,.

Rittmann et al. (1996), reported that there is a relationship between the rnicrobial

Page 119: Modelling of Clogging in Laboratory Column Experiments

oxidation of COD to inorganic carbon to the mass of calcium carbonate precipitated out

of landfill leachate. Laboratory experiments perforrned using landfill leachate collection

Stone infiltrated with landfill leachate fiom the KVL indicated that the removal of COD

(mostly acetic acid), and its partial substitution with H2C03 (bicarbonate), resulted in

major increases in pH and total carbonate, which together caused a large increase in CO,"

concentration, allowing or accelerating CaCO, precipitation. From data obtained from

Rowe et al. (1995a) a linear relationship between COD removal aiid CaCO, precipitation

may be derived and a yield coefficient, Y,, may be calculated (Rowe et al, 1995a; Fleming,

pers. comm.).

Calculation of Y, requires reguiar measurement of influent and effluent COD and

CaCO, concentrations. The concentration of CaCO, is calculated by measurement of total

hardness and expressing it as an equivalent mass of calcium carbonate. The COD removal

is calculated by subtracting the mass of effluent COD from the mass of infiuent COD, and

similady, the CaCO, precipitated is calculated by subtracting the CaCO, in the effluent

from the CaCO, in the influent. The COD removed and CaCO, precipitated Vary as the

colurnn operates. The value of Y, for the column test is detemined by plotting the COD

removed versus the CaCO, precipitated. The dope of a straight line passing through the

plotted experimental data points and the origin is equal to Y,. If the plotted data is not

linear, but becomes asymptotic to some maximum CaCO, concentration, the system may

be calcium deficient, and the yield coefficient may oniy be applicable to the COD removal

that fdls within the linear portion of the plotted data.

Page 120: Modelling of Clogging in Laboratory Column Experiments

Utilizing the calculated yield coefficient for the specific system and substrate the

rate of mineral precipitation of CaCO, is given by

where J is the flux of COD into the active biofilm.

The accumulation of inert biomass rnay be found by assuming a fraction of the

active biornass, f,, is degradable due to decay. The remaining fraction, (1 - fJ, is not

degradable. The decay coefficient b represents the fraction of the biomass which dies off,

and therefore the portion (1 - fJb dies off, but does not degrade, and is thus assumed to

become inert. The rate of accumutation of inert biomass is

where b is the decay coefficient of the active biofilm.

The new thickness of the inactive film is found by the addition of the new mineral

and inert film accumulations as calculated in Equations 4.18 and 4.19 and implemented in

the mode1 using:

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where X, is the total density of the biofilm.

4.4.6 Calculation of Porosity and Specific Surîace Area

The calculation of new d u e s of porosity and specific surface area are the fifth

step in the flow diagram in Figure 4.3. The new porosity n, and specific surface A, d e r

the accumulation of biofilm, is calculated using equations based on the sphere model

representing the porous media as previously described in detail in Chapter 3.

The porosity and specific surface model is based on the work of Taylor, 1990. In

Chapter 3 film thicknesses were geometncally determined above which Taylor's equations

calculated erroneous volumes and surface areas, and thus erroneous porosity and specific

surface values. For some packing arrangements a significant region of error could be

found between the maximum applicable film thickness and the geometncally calculated

thickness at which the porosity and specific surface becomes zero. By calculating the

erroneous volumes and surface areas, equations were derived to be used within the region

of error for each of the four packing arrangements. The derivation of the limits,

modification equations, and final corrected equations are discussed in detail in Chapter 3

and Appendix Ai.

The porosity and specific surface can be calculated assuming the active biofilm is

permeable or impermeable. If the active biofilm is considered permeable, the porosity

depends upon only the inactive (inert plus minerai) film thickness, while if the active

biofilm is considered impermeable, the porosity depends upon the inactive film thickness

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plus the active biofilm thickness. The film thickness L, is the total thickness of the film on

the sp heres assuming t hese considerations

For each of the four packing arrangements Table 4.2 (page 12 1) sumrnarizes the

corrected equations used to calculate the porosity and specific surface and the film

thickness bounds in which they must be used. Interpolation between these functions is

used to derive porosities and specific surface areas for packing arrangements which do not

correspond to one of the four known fùnctions.

4.4.7 Convergence to Revised Effluent Substrate Concentration

4.4.7.1 Introduction

By making an initial guess of Sc and considenng the non-steady growth and loss of

biofilm equation, the change in porosity and specific surface, and mass balance, the revised

effluent substrate concentration S, can be calculated using an iterative procedure. This

process is illustrated in Figure 4.3 by steps 2 through 7 which begins with an initial

estirnate of S, and ends when the estimated value of the current iteration converges with

the calculated value. Convergence of the effluent concentrations indicates the balancing of

the flux of biomass and mineral ont0 the porous media, the surface area available, total

biomass losses, and substrate removal from the system. This section discusses this

iterative routine.

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4.4.7.2 Application of a Second Substrate

Leachate may include a number of potential substrates, however the dominant

substrates will usually be acetic and propionic acid. The model, therefore, was designed

to not only model a single substrate, but also a mixture of these two acids. The utilization

of each acid is considered separately, and thus the convergence routine outlined in this

section is repeated to caiculate the effluent concentration corresponding to the second

substrate. The schematic in Figure 4.3 omits this repetition.

Each substrate has its own set of kinetic parameters, but shares a single decay

coefficient, b, which, in the absence of contrary information, is used as the first

approximation of the decay coefficient for the biofilm as a whole. The detachment part of

the total loss coefficient is assumed to be proportional to the relative arnounts of each

substrate. Each substrate contributes to separate active and inactive film thicknesses, but

a single value of porosity and specific surface is calculated fiom the sum of the thicknesses

of the films. Besides input parameters, the only difference between the processing of two

substrates occurs in the mass balance used to calculate the effluent concentration of each

substrate, discussed next.

4.4.7.3 Mass Balance

In order to consider changes in substrate flux and specific surface area which occur

due to film growth, the effluent concentration is recalculated using a mass balance. The

mass balance for calculating the effluent concentration of a single substrate, or for the

propionic acid in a mixture of acetic and propionic acid is

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JVA, Swm = s, - -

Q

where S, is the iduent concentration of the specific substrate, J is the flux of the specific

substrate, 4 is the specific surface area, V is the volume of the element and Q is the flow

t hrough the element .

For the acetic acid in a mixture of acetic and propionic acid a different mass

balance equation is required to incorporate the degradation of propionic acid to acetic

acid. Since a product of the utilization of propionic acid is acetic acid, this acetic acid is

available for consumption, and thus must be incorporated into the acetic acid mass

balance. The addition of acetic acid to the mass balance is performed through the use of

the calculated substrate flux from propionic acid calculated in the previous step (step 2 in

the procedure in Section 4.4.8.4). The value 0.5714 is the ratio of the mass ( in COD) of

acetic acid created per mass of propionic acid degraded (Fùttmann, pers. comm.). The new

effluent substrate concentration for acetic acid, S,,, is calculated using :

J V A , JVA, Se+, = S, + 0.5714-0- - -

Q P

On the nght side of this equation the subtracted term is the concentration of the substrate

removed fiom the flow by substrate flux into the acetate degrader biofilm and the middle

term is the additional substrate concentration acquired ffom the degradation of propionate

into acetic acid @y the propionate degraders).

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4.4.7.4 Approximation of the Buik Substrate Concentration

The calculation of the substrate flux and thus rate of growth or loss of biofilm

described in the previous sections requires the bulk substrate concentration as input. The

bulk substrate concentration is the substrate concentration applied to the biofilm uniformly

throughout a segment. It is assumed that the bulk substrate concentration is equal to the

log-mean of the infiuent and effluent substrate concentration of the element. This

calculation is shown in Equation 4.23 in step 2 in Section 4.4.7.5. According to Wang et

al. (1986), the log-mean concentration represents the equivalent average reactor

concentration when a first-order reaction takes place in a plug-flow reactor. As shown by

the rapid removal of substrate over a relatively short distance from the inlet, the colurnn

tests modelled in this thesis undergo zero order reactions only in the segments nearest the

inlet, and first order substrate removal dominates the remaining length. The log-mean

concentration has also been used to model colurnn tests by Rittmann et al. (1986) and

Wirtel et al. (1992). The application of the log-mean will require further study, but is used

in the model as a first approximation of the bulk substrate concentration.

The substrate concentration applied to al1 regions of the element is equal to this

bulk substrate concentration. The assumption is valid so long as the difference between

the influent and effluent concentrations remain relatively small. This assurnption may be

met by making elements small, and increasing the number of elements, thus reducing the

removal by each element.

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i o a

4.4.7.5 Convergence on Revised Effluent Substrate Concentration

The concentration of the effluent of an element can only be established by adopting

an iterative process. The iterative steps are:

1. Initialize effluent substrate concentration variables Se- , Se,, for convergence,

and set the initial estimate of the effluent concentration using:

Se = So Time step = 1

se = se.,- 1 Time step > 1

where S,,, is the effluent concentration of this element from the previous time

step.

2. Calculate the bulk substrate concentration

3. Invoke substrate flux routine (Section 4.4.4) to calculate J fiom kinetic constants

and L, and Sb.

4. Calculate the new active and inactive film thicknesses using Equations 4.17 and

4.20.

5 . Invoke the porosity and specific surface mode1 desctibed in Chapter 3 and

calculate the new values of porosity and specific surface fiom the new active and

inactive film thicknesses. See Table 4.2 for a sumrnary of the modified porosity

and specific surface equations.

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6 . Mass balance. Calculate the efnuent concentration S, using Equation 4.2 1 if the

current substrate is a single substrate or the propionic acid portion of a mixture.

Calculate using Equation 4.22 if the current substrate is acetic acid as part of a

mixture.

7. Check for convergence of Se within given tolerance. Convergence is discussed in

detail in Section 4.4.9.

8. If Se has not converged, and the number of iterations is less than 10, set S, = S,,,

and repeat steps 2 to 8.

9. If Se has not converged, then recalculate Se using a binary chop algorithm and

repeat steps 2 to 8.

The resetting of S, to S,,, in step 8 allows quick convergence which occurs when

the initial estimate of S, is close to the final value of Sc. Slow converging solutions which

occur when Se is not close to the final value of S. converge faster using a binary chop

aigonthm (Step 9) implemented if 10 or more iterations are required. This is discussed in

detail in Section 4.4.9. Given the biofilm properties, influent substrate concentration S,,

total Ioss coefficient, b', and values of La, L,, n, A,, and Se from the previous time step for

a given segment, new values of L, ,L,, J, n, 4, and S, can then be calculated (specific to

the substrate if two are modelled).

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4.4.8 Convergence on the Biofilm Total Loss CoefFicient

4.4.8.1 Introduction

It is necessary to establish the biofilm total loss coefficient for each segment, at

each tirne step (see Figure 4.3, noting that the optional second substrate is ornitted). The

initiai estimate of the total loss coefficient, b', and diffusion layer thickness, L, (if

considered variable), are calculated based on the properties of the element in the previous

time step. The effluent concentration (for each substrate, if required) can then be

calculated using these parameters and the steps outlined in Section 4.4.7. The model

recalculates b' and L, based on the new properties of the element for this time step, and

the process is repeated until b' converges. The calculation of the parameters L, and b',

and convergence routine follow.

4.4.8.2 Calculation of the Diffision Layer Thickness L,

Introduction

The diffusion layer is a stagnant layer of Iiquid which is assumed to be void of

microorganisms and through which substrate is transported by molecular diffusion. The

model allows the difision layer thickness to be recalculated each iteration, or a fixed

value rnay be used.

The Difision Layer Thickness

The difision layer thickness may be estimated fiom principles of mass and

momentum transfer according to Skelland (1 974), by utilizing the equation

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where j, is the Colbum j factor for mass and momentum transfer, S, is the Shenvood

number, & is the Reynold's number, S, is the Shmidt number, and v is the empty bed

(superficial) velocity. A correlation developed by Wilson and Geankoplis (Skelland.

1974) for caiculating the j factor for mass transfer between liquids and deep beds of

packed spheres is

for 0.00016 i q s 55, 165 s Sc 70,600 ,0.35 3 n i 0.75. From equations 4.24 and

4.25 an equation for the thickness of the boundary layer can be derived :

This equation has been applied by Liu et al. (1991) and Suidan (1986) to calculate L, in

modelling column tests using light aggregate and packed spheres, respectively, as biofilm

attachent media.

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Variability of L,, with Clogging

The calculation of the Reynold's nurnber or Shenvood number does not account

for the effects of film buiidup on a bed of packed spheres therefore Equation 4.26 is

suspected to become Iess accurate as the element nears clogging.

Umealistic Values of L,

At low fluid velocities and large particle sizes such as those used in colurnn tests

modelling leachate collection systems, Equation 4.26 ofien results in unrealistically high

values of thickness L,,, such as thicknesses larger than the critical film thickness (which

would mean that at this thickness the stagnant difision layers could cause pore

discontinuity). The unrealistically high thicknesses may be due to the fact that the mass

and momentum transfer relationships have been derived from laboratory expenments using

small particles and very high fluid velocities relative to the values required for columns

representing leachate drainage systems. While coupling large particle size with small fluid

velocities such as those of this research results in Reynold's numbers which fa11 into the

allowable range for the relationships, it may do so due to the particle size, and when these

values are substituted into Equation 4.26 the result is a high value of L, . Due to the

possibility of unrealistic values of 4, computer implementation of the mode1 interface

calculates an estimate of L, using Equation 4.26 based on the known problrtm parameters

but then allows the user to choose to use either this calculated value or use a specified

fixed value.

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4.4.8.3 Calculation of the Total Loss Coefficient b'

Introduction

The calculation of the decay coefficient b', or total loss rate coefficient, is

performed assuming it includes losses due to ce11 decay or maintenance, b, and detachrnent

by any measurable means, b,:

The value of b can be obtained from the literature, while the loss due to detachment, b, is

often a calculated value based on the ceIl removal process believed to be responsible in

this system under analysis. A number of expressions have been developed to calculate b,

for specific applications, but few may be applied to a wide range of conditions. For this

reason two methods of calculating b, have been considered.

Shear-Stress Model

The theory behind the first method of caiculating b, is that shear-stress is the

primary mechanism of biofilm detachrnent. A relationship between shear stresses and

biofilm detachrnent was derived by Rittmam (1 982) based on data collected by Trulear

and Characklis fiom experiments measuring the rate of biofilrn loss within an amular

reactor rotated at different speeds. The expression denved for detachrnent due to shearing

for L, > 0.003 cm was

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where a is the shear stress, and for L, s 0.003 cm

b, = 8 . 4 2 ~ 1 0 -' O O - ' ~

where the shear stress o is

in which u is the superficial velocity (cdday). The shear stress calculation is applicable

for

Growth Rate Mode1

A second theory proposed that detachment rate is directly related to biofilm

growth rate in terms of its substrate utilization rate, yield, and biofilm thickness (Peyton

and Characklis, 1993). Monopopulation and rnixed-population biofilm data fiom the

study was combined with other experimental observations with the same cultures of

bacteria in order to correlate the expression. The relationship denved for the detachment

rate, &, was

where k, is the detachment rate coefficient, A,, is the biofilm surface area, Si is the influent

Page 133: Modelling of Clogging in Laboratory Column Experiments

substrate concentration and S, is the bulk substrate concentration. From this expression

the detachment coefficient b, may be found to be

where k, should be found experimentally. For the model the data compiled by Peyton and

Characklis (1993) was used to calculate detachment rate coefficients of 454 cm-' and 63

cm-' for single and mixed population bacteria cultures respectively. If this method is

selected, the model assumes that the bacteria culture is a mixed population and thus k, is

set to 63 cm".

4.4.8.4 Steps to the Satise Biofilm Total Loss Coefficient

The procedures required to obtain the biofilm total loss coefficient (with o v e ~ e w

given in Figure 4.3) are as follows:

1. Calculate the total biofilm loss coefficient, b', and diffusion layer thickness, L,,

based on previous values of n, As and L, and flow characteristics.

2. Solve the effluent concentration for substrate 1 (Section 4.4.7). Use the kinetic

pararneters for substrate 1. Calculates J, L, ,,,. L,,, n, 4 and Sc.

3 . Solve the effluent concentration for substrate 2 (optional) (Section 4.4.7). Use the

kinetic pararneters for substrate 2. Calculates I, , LBLn- LS.Lnm, n, 4 and S,,.

The flux of substrate 1 (propionic acid) is required to include the degradation of

propionic acid to acetic acid in the mass balance.

4. Recalculate b ', and b.

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Check for convergence of b' and b', (see Section 4.4.9 regarding convergence).

If b 'and bt2 do not meet convergence criterion, set b ' = bI2 and repeat steps 2 to 6.

Check for clogging of the element by checking that the total impermeable film

thickness is less than L,,, and A, is greater than zero.

Segment calculation is complete, go to next segment in line.

Convergence

4.4.9.1 Introduction

In the preceding sections, discussion of convergence has been greatly simplified to

allow attention on other processes. This section discusses aspects of the convergence

methods not described in detail. The parameters solved by convergence are:

the total loss coefficient of a layer, b', (Section 4.4.8),

effluent concentration of a layer, Se, (Section 4.4.7),

I effectiveness factor of the substrate flux, q, (Section 4.4.4)

Each convergence routine follows the same pattern. Maximum and minimum limits are

placed on the dependent pararneter, and an initial estimate of this parameter is made.

Using this estimated parameter as input to various equations, the parameter is

recalculated. If the estimated and calculated versions of the pararneter meet specific

convergence critena, the solution has been found and the convergence routine ends. If the

criteria were not met, adjustments are made to the limits such as increasing the minimum,

or decreasing the maximum (as listed in column 6 of Table 4.3, page 122) such that upon

Page 135: Modelling of Clogging in Laboratory Column Experiments

further iteration, the lirnits converge. A new estimation of the parameter is made either

dependent on the limits or the previously calculated parameter. The routine repeats. The

details of each convergence routine are given in Table 4.3.

4.4.9.2 Maximum Number of Iterations

The procedures have been simplified by assuming that the routines eventually

converge on a solution. In actuality, under certain conditions convergence criterion may

never be met or the solution may converge at a very slow rate. In order to allow

automatic or manual adjustments to be made to the convergence conditions a Iimit must

be placed on the maximum number of iterations so that the particular convergence routine

cm be halted. If the maximum number of iterations is reached, the mode1 terminates.

4.4.9.3 Convergence Criterion

The convergence criterion for each routine is basically the same. The parameter is

assumed to have converged when the relative change in the parameter is less than some

given tolerance. The condition for the convergence of the effectiveness factor, q, for

example, is

where q, is the previous estimate of the effectiveness factor, and e, is the convergence

tolerance for the effectiveness factor.

Page 136: Modelling of Clogging in Laboratory Column Experiments

4.4.9.4 Rapid versus Stable Convergence

Using the calculated parameter fiom one iteration as the estimate to the next

iteration is the fastest method of convergence, but this method may cause various

instabilities. The more stable, but slower converging method of revising the initial

estimate of the parameter is to use the calculated average of the limits of the parameter,

where the limits converge (as descnbed in Section 4.4.9.1). The convergence routines for

the total loss coefficient and effluent concentration are designed to change from a rapid to

a stable method if specific conditions are met which indicate instability.

For convergence of the total loss coefficient, an instability occurs when oscillating,

or recursive results are calculated. For example, a cyclical sequence can develop where

input (a) gives output (b) which then gives output (a) and the process repeats without

convergence. The mode1 has been programrned to detect non-converging cyclical

sequences and change from using the rapid convergence aigorithm to the less problernatic

algorithm involving averaging of the parameter limits, see Table 4.3, Column 7.

When using the effluent concentration calculated fi-om one iteration as the estimate

of actual effluent concentration, convergence to the final value may, under certain

conditions, be extremely slow. Under these conditions the rate of change of the estimated

effluent concentration is so small that the maximum number of iterations is reached before

the convergence criteria is met. The routine is prograrnrned to allow only 10 iterations

using the so called 'rapid convergence algorithrn' and if convergence is not reached after

10 iterations the convergence routine changes to the more stable averaging method.

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These convergence problems generally only occur when the input parameters do

not well represent the physical system.

4.5 COMPLETE MODEL PROCEDURE

4.5.1 Procedure

The complete procedure of the mode1 accepts the necessary input, initializes

variables and arrays of variables according to the values entered, and repeats the

caiculations of each segment dong the flow field for each time step analysed.

The algorithm adopted is illustrated schematically in Figure 4.5 and involves:

Entry of input parameters.

Variable Precalculations: temperature dependent variables, fluid absolute viscosity,

coefficients of substrate difision in the biofilm variables dependent on the

packing arrangement, element dimensions, influent flow and substrate

concentration and biofilm growth constants. Details are given in Section 4.5.2.

Initiaikation of Arrays: Set a11 elements (segments) to have the same initial

porosity, specific surface and initial biofilm thickness, and precalculate the arrays

for simulating advection. Details are given in Section 4.5.3.

Time step = 1.

Segment number: k = 1.

Perform calculations for segment k. The influent concentration is govemed by the

advective routine.

Repeat step 6 for each segment (k = k + 1).

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8. For advective flow algorithm. shift columns of values in the record of effluent

concentrations (see Section 4.2.4.3).

9. Repeat steps 6 through 8 for each time step.

4.5.2 Variable Precalculations

4.5.2.1 Temperature Dependency

Calculate temperature dependent pararneters fiom reference parameters and

temperatures if required. Temperature dependent pararneters calculated are K,,, K,,, 4,.

q2, Do,ir Da2 , and b. Temperature dependency is calculated using the expression (Metcalf

and Eddy, 199 1):

where T is the system temperature in OC, TT is the temperature the reference parameter

was measured at, in OC, PT is the parameter at temperature T T . P, is the parameter at

the reference temperature T r a c and h is the temperature factor for the parameter.

4.5.2.2 Absolute Viscosity

The absolute viscosity of the fluid can be specified or calculated assuming the

viscosity of the fluid to be that of water. A formula for calculating absolute viscosity

variance with temperature was derived using regression and published data (Metcalf and

Eddy, 199 1). Using this denvation, viscosity variance due to temperature is accounted for

b y :

Page 139: Modelling of Clogging in Laboratory Column Experiments

where T is temperature in O C , and y is the absolute viscosity (mg cm-' d-'). The absolute

viscosity is required in the caiculation of the diffision layer thickness and detachment

coefficient if the shear-stress mode1 is applied.

4.5.2.3 Substrate Difision in the Biofilm

The molecular diffision coefficient for the substrates in the active biofilm, D,,, and

D,, , may be obtained from published values or calculated fiom the diffision coefficient of

the substrates in the free liquid, Do,, and Do,Z. When D, is calculated, D, is assumed to be

80% of the coefficient of difision of the substrate in the fiee solution.

4.5.2.4 Packing Arrangement Dependencies

The initial specific surface area, k0, is calculated from the particle diarneter and

initial porosity using Equation 3.1. The number of contact points, m, and packing factor,

a,, corresponding to the packing arrangements bounding the initial porosity are set. The

number of contact points and packing factor corresponding to the initial porosity for the

four regular packing arrangements are given in Table 3.1. The critical film thickness, Lt&,

is calculated by interpolation of the critical film thicknesses of the bounding packing

arrangements. The critical film thickness is the film thickness at which the element

analysed is considered clogged. Derivation of this parameter is discussed in Section 3.5.

The critical film thicknesses are listed for each packing arrangement in Table 3.4, colurnn

Page 140: Modelling of Clogging in Laboratory Column Experiments

4.5 -2.5 Conversion to Mode1 Units and Miscellaneous Calculations

The segment length (cm) is calculated from the column length (cm) and the

nurnber of segments. The cross-sectionai area of flow (cm2) is calculated fkom the column

diameter. The half-velocity constants of the two substrates, K,, and K,, , entered in (mg

L-') are converted to (mg cm"). The standard biofilm depth dimensions for each substrate

(cm) are calculated using Equation 4.6E

4.5 -2.6 Substrate Flow and Concentration

The infiltration flow (cm3 d") is converted from units of (L d-'). The infiltration

substrate concentration (mg cm3) for substrates 1 and 2, SwI and S,, respectively, are

calculated using:

and

where P is the portion (%) of the leachate which is substrate 2, S , is the total substrate

concentration of the infiuent leachate (mg L-') , and SR,, is the concentration of refractory

substrate in the leachate (mg L-'). If any substrate concentration is calculated to be a

negative value, it is assumed to be zero.

Page 141: Modelling of Clogging in Laboratory Column Experiments

4.5.3 Initialbation of Arrays

4.5.3.1 Element Properties

The mode1 requires that the granular media of each element begins with a relatively

thin active biofilm thickness for each substrate, L,, and L,, so that initial utilization of

substrate and subsequent biomass accumulation c m occur (see Section 4.452). This

initialization is performed using

and

where L,, is the total initial active biofilm thickness (cm). The initial film thickness for

each substrate is calculated to have the same proportions as the substrates cornprising the

total concentration of substrate. If only one substrate is considered, P is zero and

therefore L,,, for each element is zero. The initial inactive film thicknesses, L,, and LP2 of

each element are set to zero. The initial specific surface area of the elements are set to the

value calculated using Equation 3.1.

4.5.3 -2 Advection Arrays

The precalculated arrays required for storage of effluent concentrations and

retrieval of influent concentrations to simulate advection through the segments are

outlined in Section 4.2.4.

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4.6 CHAPTERSUMMARY

A mode1 was developed for the prediction of the change in porosity in colurnn test

experiments. The porous media system was represented by a senes of segments in which

each segment was assumed to act as an anaerobic fixed-film reactor. An advection

algorithm was developed to retrieve influent concentration values fiom previous timesteps,

thus simulating time delay. Biofilm and mineral growth equations are derived, and are

implernented within an iterative routine for convergence on an effluent concentration.

This routine is implemented into a second iterative routine for convergence upon the total

loss coefficient. This routine is repeated for each segment and each timestep, with the

effluent of each segment being the influent to the next downstream segment (after some

time delay).

Page 143: Modelling of Clogging in Laboratory Column Experiments

Table 4.2 : Porosity and Specific Surface equation summary

b

Packing Arrangement -

(ml

Cubic (6 )

Film Thickness (2L/d,) 1 Porosity Equation -

Lower Bound Bound

Specific Surface Equation

Page 144: Modelling of Clogging in Laboratory Column Experiments

Table 4.3 : Summary of Convergence Routine Details

Convergence Routine

Total loss coefficient

Efïïuen! concentration

Initial Settings and Estimate of

Parameter

b' = calculated

Sc,, = calculated

q = calculated

Critical Parameter

1 s' Iteration

Condition

Convergence Cri terion Adjusimcnl of Liinits Revision of Initial Gucss

Jb', - b'I / b' < q,, I b' = bIl 1 ;bl, c b') and (b' < b1,,,3 then b',, = b'

if IbfmU- btm,( I bl,< 0.01(tbP) if

if oscillating, b' = 0.5 (bl,+ b',,)

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Start Element Anaiysis

1 1

Initial Estimate of Total Los Coefficient

- - -

l&i Estimate of ~ff&nt Concentration 1

Calculate Substrate Flux

l Calculate Porosdy ond Specific Surface

I . Calculate Revised Effluent Concentration

from Substrate Mass Balance I

\ NO

Concentration ?

1 Calculate Revised Total Loss Coefficient 1

NO

Los Coefficient ?

Go to Next Element

Figure 4.3 : Flow diagram of processes performed for each element of the flow field during each timestep (optional secondary substrate processes ornitteci).

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Input o f Variables s 1

Precalculations, Conversion of Variables to Model Units

lnitialization of Arrays

Segment Anaiysis

/

YES Additional Segments ?

NO

YES Additional Timesteps ?

NO

stop

Figure 4.5 : Flow diagram of primary processes of model.

Page 150: Modelling of Clogging in Laboratory Column Experiments

CHAPTER 5

APPLICATION OF MODEL

5.1 INTRODUCTION

This chapter outlines two applications of the model. The first is to a fully

documented, short term colurnn reactor expenment reported by Rittmann and McCarty

(1980). In this test, a single substrate which does not contribute to mineral precipitation

was used, and kinetic coefficients were denved experimentally. Predicted and measured

acetate concentrations and biofilrn thicknesses are presented. Since a single substrate

which does not form mineral precipitate is examined, it is possible to test, and if necessary

isolate any problems with the core biokinetic components of the complete model, before

examining the complex case of biofilrn growth and minera1 precipitation examined in the

second application discussed below.

The second application of the model is to a saturated column test conducted using

synthetic leachate (Millward, 1997; J. vançiulck, pers. comrn.). The synthetic leachate is

represented by two substrates, and inciudes significant quantities of dissolved rninerals

which have the potential for mineral precipitation. This application of the model provides

comparison of predicted and measured effluent concentrations over time and porosity

profiles dong the column measured at specific times.

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5.2 APPLICATION TO RITTMANN AND MCCARTY (1980) DATA

5.2.1 Introduction

The rnodel was first applied to the results of colurnn experiments reported by

Eüttmann and McCarty (1980). This work was chosen because the experiments are well

documented for modelling purposes, and test only the core components of the clogging

model. The experiments were ideal for modelling purposes since

a. they were intended to veriQ a sirnilar biofilm growth mode1 and therefore the work

includes most of the required modelling parameters and significant results,

b. many of these parameters were determined by R i t t m a ~ and McCarty using

independent experirnents,

c. since glass beads were used, the media was well represented by the model,

d. the choice of influent allows representation by a single substrate (sodium acetate),

e. there is negligible inactive film growth over the shon duration of the test.

5.2.2 Experiments

The column reactor tests of R i t t m a ~ and McCarty (1980) were performed using a

glass column which was 12 cm in length, and 2.5 cm in diameter. The column was

designed with sampling ports at 1, 2,4,6, 8, and 10 cm fiorn the influent port. Glass

beads, 0.3 cm in diameter, were packed into the column at an initial porosity of 34%. The

colurnn tests were operated in upflow mode. Before each expenment, the reactor was

inoculated uniformly with about 10 mg C of e~chment culture, bacteria cultivated from

primary sewage. The rate-limiting substrate thereafter was carbon labeled sodium acetate.

The biofilm cultures, named BC1 and BC3 by Rittmann and McCarty, were developed at

Page 152: Modelling of Clogging in Laboratory Column Experiments

the flow rates and acetate concentrations listed in Table 5.1.

Table 5.1 : Experiment Flow Rates and Influent Substrate Concentration

- -

Parameter BC 1 BC3 Units

Q 1.58 6.676 Iitre 1 day

S, 7.2 3 -6 mg 1 litre

This continuous feeding was maintained until steady-state occurred, as indicated

by stable substrate removal with time. According to Rittmam and McCarfy (1 980), and

Rittmann (pers. co rn . ) deve!opment of steady-state required about 3 to 4 weeks of

reactor operation. Once at steady-state, each test was terminated and sarnples were then

taken by syringe and by removal of beads f?om various locations along the column. The

bacteria was sheared off of the beads and the resulting water was assayed for organic

carbon. Organic carbon was determined using a hybnd Oceanography International -

Dohrrnann instrument. Bacterial carbon was measured as non-soluble organic carbon. In

this marner the profiles through the column of measured acetate concentration and biofilrn

thickness at steady-state were developed.

5.2.3 Mode1 Parameters

Table 5.2 lists the parameten denved by Rittmann and McCarty (1980) to be used

to mode1 the column tests. These parameters will not be challenged. These parameters

include the dimensions of the reactor and the experimentally rneasured bio-kinetic

Page 153: Modelling of Clogging in Laboratory Column Experiments

properties. Due to the multiple evaluations performed, the kinetic constants include

standard deviations. The parameters for calculating the temperature dependence of kinetic

constants and diffusion coefficients were not required in this application of the model.

Table 5.2 : Given Mode1 Parameters (Rittmann and McCarty, 1980)

pp - -- -

Parameter Value Units -- - - -- - -

Length of column 12 cm

Diameter of colurnn 2.5 cm

Particle diameter 0.3 cm

Initial porosity 0.34

Ks 3.9 * 0.58 mg / litre

4 20 4.4 mg / mg C-day

b 0.204 * 0.049 day -' Y 0.07 1 0.007 m g C l m g

% 2.5 mg C / cm3

Do 1 .O9 cm' / day

Table 5.3 lists parameters required by the cornputer model which were not

published, but could be given an assumed value. It was assumed that the reactor

temperature is close to room temperature, at approxirnately 20" C (Rittmann, pers.

comm.). Selection of the system temperature has little significance since the kinetic

constants were experimentally denved at the system temperature. This eliminates the need

for recalculation of parameters using temperature dependency factors, and the oniy other

temperature dependent variable is the viscosity of the fluid. The refractory concentration

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is assumed to be zero since there is no significant non-degradable substrate. The calcium

carbonate yield coefficient was taken to be zero since there was insufficient calcium to

allow CaCO, precipitation. Since no inactive film buildup is expected, the inactive film

density was taken to be a large, arbitrary value so that, coupled with a calcium carbonate

yield rate of zero, the accumulated thickness of inactive film would be sufficiently close to

zero.

Table 5.3 : Assumed Mode1 Parameters

Parameter Value Units

Temperature 20 OC

Refiactory concentration O mg / litre

y, O mg 1 mg

10000 mg / cm3

Table 5.4 Iists the input parameters which were varied. Parameters such as the

number and length of timesteps, and number of segments were initially estimated, and then

the optimum value was established as discussed later. The sensitivity to the choice of

parameters such as permeability, diffusion layer thickness, intemal diffusion coefficient and

detachment method was examined. According to current theory it was assumed that in its

initial stages the active biofilm may be considered permeable. The diffusion layer

thickness, L, , is calculated by the model using a slightly different equation than used by

the model proposed by Rittmam and McCarty (1980) as discussed shortly.

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Table 5.4 : Parameter Sensitivity Study

Parameter Predorninately Unit s Assumed Value

- - - - --

Number of timesteps 1000

Length of timestep 0.04 day

Pemeability of biofilm Penneable

Number of segments 24

b Equation 4.26 cm

D , 0.87 cm2 I day

Detachment mode1 Shear

5.2.4 Defining the Required Number of Timesteps and Segments

5.2.4.1 Tirnesteps

The length of the timestep used in the model is a numencal parameter which can

infiuence the calculated results. Lf a smdl enough tirnestep is used then the active film

thickness of the previous timestep provides a reasonable basis for calculating the film

growth of the current timestep. The smaller the timestep is, the smaller the change in film

thickness between timesteps, and the greater the accuracy until the solution converges to

values that cease to be dependent on the timestep size. Using timesteps that are too long

will result in an overestimation of effluent concentration. The optimum timestep length is

the largest value below which further decreases no longer produce a significant change in

results, since this provides the required accuracy while rninirnizing the number of timesteps

required and thus shortenhg run-time.

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The mode1 was run for experirnents BC 1 and BC3 using the parameters listed in

Tables 5.1 - 5.4 above for various timestep lengths and for a test duration of 40 days. For

pararneters where Rittmann and McCarty provide a mean and standard deviations, the

mean values were used. Figures 5.1 and 5.2 show the effect of the timestep length on the

plot of effluent concentration versus time for BC 1 and BC3 respectively for the timestep

lengths of 1 .O, 0.2.0.04, and 0.008 days. For both experiments, a reduction in timestep

length fiom 1 .O to 0.2 days caused a significant shift in the calculated effluent acetate

concentration versus time plot to the left by approxirnately 2.5 days. Further reduction in

timestep length fiom 0.2 to 0.04 days resulted in plots that were shified to the lefi by a

significantly smaller amount (0.5 days), and a further decrease in timestep length fiom

0.04 to 0.008 days had little effect. Thus, a timestep length of 0.04 days (approx. I hour)

was found to be adequate for subsequent modelling.

While Rittmam and McCarty (1980) assumed that steady-state had been reached

after about three weeks of operation and had terminated the tests between 3 to 4 weeks,

Figure 5.1 shows that for this set of input pararneters, the mode1 predicts a gradua1

increase in effluent concentration afier the initial drop in effluent concentration, and tme

steady-state conditions are not reached within the 40 day period of analysis. Steady-state

was assumed to have been reached when there was no significant change in substrate

removal (Rittmann, pers. cornrn.). If these predictions are accurate, it shows that

experiment termination may have been prernature, but also that the rate of change of

effluent concentration after 3 or 4 weeks may have been small enough that changes in

effluent concentration were insignificant.

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5.2.4.2 Number of Segments

The properties of each segment (or element) of the column are assumed to be the

same throughout the segment. The bulk substrate concentration providing nutnent to the

biofilm in each segment is taken as the log mean of the influent and effluent substrate

concentrations as suggested by Wang et al. (1986) and as descnbed in Section 4.4.7.4.

This approximation is valid so long as the dserence between the influent and effluent

concentrations (ie. the substrate concentration removed), remains relatively small. In

order to improve model accuracy by reducing the substrate concentration removed by

each segment, the nurnber of segments must be increased and length of segment reduced.

This ailows approximation of the bulk substrate concentration.

The optimum segments length is selected in a manner sirnilar to the optimum

timestep length by decreasing the segment length until there is an insignificant change in

results for any additional reduction. It is important that in assessing the convergence on

the required segment length (and hence number of segments) that the model be mn for the

entire duration of the test being modelled. This is because at early times in the expenment

there is Little difference in the growth of biofilm between segments, and therefore little

removal. As the elapsed time increases, there is an increase in the difference between the

thickness of the biofilm in each segment and hence greater removal by each segment, thus

requiring smaller segments. The number of segments may be selected such that values are

caiculated at specific locations dong the colurnn, but the selected number of segments

must be greater than the optimum number of segments as defined above.

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The mode1 was run for test BC 1 using the parameters listed in the tables above for

various other numbers of segments for a test duration of 40 days using rnean parameters.

Figure 5.3 illustrates the effect of the number of segments on the effluent concentration

versus tirne. The figure shows the results for 1,2,4,6, 12 and 24 segments and it c m be

seen that there is no significant difference between the results obtained using 12 segments

and 24 segments and as few as 6 segments would have provided acceptable results. The

results for 1, 2 and 4 segments were accurate at early times, but become inaccurate after

about 10 days.

5.2.5 Results and Discussion

5 -2.5.1 Predicted Concentration Profiles Using Mean Parameter Values

Figure 5.4 shows the measured and predicted substrate concentration through the

column after three weeks for test BC 1. The leveling off of the rneasured acetate

concentration indicates that substrate removal predominately occurs in the first 4 cm of

the reactor. The remainder of the column has a substrate concentration so low that there

is no significant biofilm activity, and thus, since no further substrate is removed, the

concentration remains constant. The predicted acetate concentrations along the column

obtained using the mean parameter values are shown for 21 and 28 elapsed days. Two

times were exarnined because there is some uncertainty regarding the elapsed time at

which the measurements were made ( "about 3 weeks of operation" as reported, and

Rittmam (pers. comrn.) has indicated that it was 3 - 4 weeks). The elapsed operation time

before termination and sarnpling also rnay have differed between colurnns BC L and BC3.

There is no significant difference between the predicted profiles at 2 1 and 28 days for

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BC 1. The predicted concentration profile obtained using the mean parameters

overestirnates the acetate concentration in the first-in-line segments of the first 1.5 cm,

then underestimates the acetate concentration of the remaining portion of the reactor. The

predicted results become relatively constant with length along the reactor.

Figure 5.5 shows the rneasured substrate concentration at steady-state and the

predicted concentrations through the column after 2 1 and 28 days for test BC3. The

measured substrate concentrations from this expenment do not become constant within

the 12 cm of the reactor. This is due to the greater flow rate which decreased the

detention tirne in each segment, thus decreasing the rernoval by the early-in-line segments,

and allowing substrate to be transported to segments further from the source. The

predicted concentration profiles for 2 1 and 28 days are very close together, and correctly

predict that the test does not reach a constant minimum concentration. Using the mean

parameters the mode1 overestimates the first 2 cm, and underestimates the remaining 10

cm.

5 -2.5.2 Final Fitted Predicted Concentration Profiles

By slightly adjusting the kinetic constants within the range defined by the standard

deviation of each parameter, the predicted profile of test BC3 was fit to the measured data

using K, = 4.48 mgAitre and b = 0.254 dayeL . These kinetic constants were then used to

mode1 test BC 1. Figure 5.6 shows the concentration profiles for 2 1 and 28 days using the

revised input parameters. It was observed that the predictions for 21 and 28 days remains

close, and the first 1.5 cm is still overestimated, but the revised concentration profile

Page 160: Modelling of Clogging in Laboratory Column Experiments

provides a better fit to the measured data. The mode1 correctly predicts the occurrence of

a constant minimum concentration.

Figure 5.7 shows the predicted concentration profiles using the kinetic constants

denved for test BC3. The predicted results for 2 1 and 28 days separate by a maximum of

about 0.3 mg/litre. Through the first 2 cm of the reactor, the measured data is

overestimated at both 2 1 and 28 days, but the remaining measured concentrations lie

between the 2 1 and 28 day profiles.

5.2.5.3 Predicted Biofilm Thickness Profiles

The measured biofilm thicknesses at steady-state and predicted biofilm thicknesses

at 21 and 28 days for test BCI are shown in Figure 5.8. By cornparison of the measured

values in Figures 5.8 and 5.6 it can be seen that where significant removal of substrate

occurs, in the first 2 cm, there is very thick biofilrn. This biofilm thickness rapidly

decreases over the remaining 10 cm. The predicted biofilm thicknesses, calculated using

the revised kinetic constants, also show this rapid decline. There is little difference

between the predicted biofilm thicknesses after 21 and 28 days. The biofilm thicknesses

are overestimated over the first I cm, and are underestimated over the range 2 to 12 cm.

Figure 5.9 shows the measured steady-state biofilm thicknesses and predicted

biofilm thicknesses after 21 and 28 days for test BC3. By inspection of the measured

substrate concentrations for test BC3 in Figure 5.7, it can be seen that the gradua1 increase

in substrate removal which occurred throughout the reactor is matched with a measured

Page 161: Modelling of Clogging in Laboratory Column Experiments

gradud decline in biofilm thickness indicating utilization of substrate along the entire

length of the column. The predicted biofilrn thicknesses provides a good fit to the

measured values. There is a great difference between the predicted thicknesses at 2 1 and

28 days in the first 2 cm, which is followed by very similar predicted results from 2 to 12

cm length. This indicates the rîpid growth occurring in the early-in-line segments. The

measured data fa11 between the predicted profües at 21 and 28 days in the first 2 cm and

remain very close from 2 to 12 cm. This suggests that the measurements may have been

taken between 21 and 28 days.

5 -2.5 -4 Parameter Significance

Figure 5.10 shows the sensitivity of the model to the permeability of the active

biofilm for test BC3. The figure shows the effect of assuming the active biofilm is either

impermeable or permeable (that is, whether the active film should, or should not, be used

in the calculation of porosity). The predicted results for 28 days show a slight increase in

removal throughout the reactor, but indicate that for this model run, the permeability of

the active biofilm is insignificant.

Figure S. 1 1 illustrates the effect of using different rnethods of calculating the

difision layer thickness. If not set to a fixed thickness, the model applies the difision

layer thickness calculation (Suidan, 1986 and Lui et al., 1991) discussed in Section

4.4.8.2. The model discussed by Rittmann and McCarty, 198 1, uses a similar equation to

calculate a fixed layer thickness. This equation gives a fixed difision layer thickness of

0.0 1 58 cm, as compared to the model denved initial thickness of 0.0 129. The use of the

Page 162: Modelling of Clogging in Laboratory Column Experiments

fixed (siightly greater) difision layer thickness results in an increase in the predicted

substrate concentrations (a decrease in removal), which is expected since an increase in

the diffusion layer thickness causes a decrease in the substrate concentration available for

utilization by the biofilm.

In order to calculate the difision coefficient of the substrate within the biofilm,

Rittmann and McCarty, as well as many other modellers, suggest the use of a DJD0 ratio

of 0.8, meaning that the difision of substrate into the biofilrn, D,, is 80% that of the

diffusion of the substrate in fiee water, Do- The 0.8 ratio was determined by Williamson

and McCarty (1 976) for nitri@ng aerobic biofilms. Recent work (Yu and Pinder, 1994,

Pavlostathis and Giraldo-Gomez, 1991) has suggested much Iower D& ratios for the

difision of acetate in biofilms. A Df/Do ratio of 0.3 1 reported by Yu and Pinder was used

to obtain the results shown in Figure 5.12 for D, = 0.338 cm2/d and a ratio of 0.8 to obtain

the results shown for D, = 0.872 cm2/d. For this case it cm be seen that the choice of

diffusion coefficient has negligible effect over the range examined.

The sensitivity of the model to the method of calculation of the detachment

coefficient, b, was studied. The previous predictions were performed using the shear-

stress method, discussed in Section 4.4.8.3. Prediction using the growth rate method of

calculating b, ( also in Section 4.4.8.3) were also obtained and the results are compared in

Figure 5.13 and it can be seen that the growth rate method results in higher predicted

substrate concentrations (a decrease in removal). For this test, the choice of detachment

model did not significantly affect the results.

Page 163: Modelling of Clogging in Laboratory Column Experiments

5.2.5.5 Hydrodynamic Dispersion

According to Golla and Overcarnp (1 WO), the small disagreement between the

measured and predicted results shown in Figures 5.6, 5.7, 5.8 and 5.9 may be due in part

to the neglect of dispersion by the model. Golla and Overcamp (1990), also working with

test BC1 data, concluded that in comparing a plug flow rnodel and a model which included

longitudinal dispersion, the model which included longitudinal dispersion showed good

agreement while the plug flow model overpredicted the concentration and biofilm

thickness at the inlet of the reactor and underpredicted these variables downstream.

As s h o w in Figures 5.6 and 5.8 , this was the case for the plug flow mode1

developed in this thesis for test BC 1, but, as indicated in Figures 5 .7 and 5.9, not the case

for test BC3. According to dispersive theory, the effects of mechanical dispersion should

be more pronounced in test BC3 because of the substantially higher flow, leading to the

conclusion that dispersion may not be the cause of the overpredicted concentration and

biofilm thickness at the iniet of the reactor and underpredicted values downstream.

Instead, this phenomenon is likely caused by omission of some other modelling factor or

(less likely) expenmental error, such as neglecting biological activity O C C U ~ ~ ~ in the

influent tubing between the point of influent concentration measurement and the first

measurement location within the reactor. Such biological activity would result in an

overestimated influent concentration to the reactor, and cause the phenomenon described

above. It is unknown whether regular cleaning of the tubing was performed, or what

effect regular cleaning would have on substrate removal within the tubing. Modelling the

Page 164: Modelling of Clogging in Laboratory Column Experiments

growth of bacteria within the tubing of the apparatus may correct this situation, and

improve the accuracy of the results.

5.2.6 Conclusions for Rittmann and McCarty (1980) Experimenb

The model predictions of the concentrations and biofilm thicknesses were found to

provide a reasonably good fit to the experimental data for the two different flow rates and

initial concentrations. The effect of the choice of parameters where there was some

uncertainty was generally found to be insignificant. A better comparison may have been

possible had a more precise elapsed time to test termination been published. Neglect of

biofilm growth in the influent tubing to the reactors by the model may cause some

disagreement between measured and predicted results. In summary, the model was found

to provide a reasonable simulation of the acetate removal and biofilm growth for a short

duration expenment using a single substrate for which inactive film build-up may be

neglected.

5.3 APPLICATION TO SYNTHETIC LEACHATE COLUMN EXPERIMENTS

5.3.1 Introduction

Column experiments conducted using glass beads and synthetic leachate provide

the next level of complexity against which the proposed model can be tested. Like the

Rittmann and McCarty experiments (discussed in the previous section), the synthetic

leachate column tests (Millward, 1997, vanGulck, pers. cornrn.) simplify modelling

because the media (glass beads) are well represented by the sphere rnodel. However in

this case the leachate is more complex involving two primary substrates (propionic and

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acetic acid) and significant concentrations of C a and so that mineral precipitation

may be expected.

As compared to actual raw leachate, synthetic leachate provides an idluent with a

relatively constant value of COD, pH, Eh, and VFA ratio and substantiaily less particulate

matter (which may provide additional clogging due to particles attaching to the biofilm).

In the absence of experimentally derived kinetic constants for the leachates at the test

temperatures, the applicability of the mode1 will be studied by estimating the kinetic

constants fiorn reported values indicated in literature.

5.3.2 Experiments

The leachate reactor (column) tests were performed using columns constructed

from 5.08 cm intemal diameter, 76.0 cm long PVC pipe. Influent and effluent valves were

attached to the columns at 2.0 and 66.5 cm from the base respectively. The columns were

designed to allow gas escape and piezometric readings at various elevations. The colurnns

were packed from the influent valve to effluent valve with 0.6 cm diameter glass beads.

The experiment was nin in triplicate using 3 identical columns.

The composition of the prepared synthetic leachate was based on samples taken

from Keele Valley Landfill between June and August 1993. The composition of the

mixture is described in Table 5.9 (page 163) fiom Millward (1997). Synthetic leachate

provides the substrate for bacteria, but, unlike actud leachate, does not contain a

significant population of bacteria. Thus it was necessq to seed the column with a

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bacterial population at the oiitset of the experiment. This inoculation process was

performed by initially operating the columns using a mixture of KVL and synthetic

leachate, and then gradually increasing the proportion of synthetic leachate until the

mixture was 1 00% synthetic after approximately 12 days.

The column tests were inoculated and operated in an upflow direction with a target

continuous flow rate of 1 .O L/d ; controlled by a peristalic pump. The average fluid and

column temperature (infiuent and effluent) was 22 * 1 O C . Influent and effluent samples

were regularly taken for water quality measurements which included COD, calcium

hardness, biological activity reaction test ( B A R F ) , temperature, pH and Eh. Drained

porosity was measured at various times. At the tirne of modelling? these column

experiments had not been terminated and therefore autopsies had not been performed.

5.3.3 Modelling the System

The synthetic leachate contains acetic, propionic and butyric acids as organic

substrates in a known ratio of 75: 1 (intended concentrations of 7000 mg& 5000 mg/L

and 1000 mg/L respectively). Since the portions of acetic and propionic acids were

similar, and significantly greater than the concentration of butyric acid, it was assumed that

no one substrate would dominate in the system. For this reason, the system was modelled

using the two substrate option, with acetic acid as one substrate, and the mixture of

propionic acid and butyric acid to act as the second substrate (simulated as propionic

acid). This mode1 simulates the breakdown of propionic acid to acetic acid.

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5.3.4 Measured Input Parameters

5.3.4.1 Introduction

The basic, fixed mode1 pararneters are Iisted in Table 5.5. Details regarding the

measurement of these pararneters are given below.

5.3 -4.2 Fluid Temperature, Reactor Length, Diameter, Particle Size, Initial Porosity

The average temperature of the fluid was measured fiom the influent and effluent

temperatures taken prior to each water quality measurement. The reactor length is the

length dong which attachent of biofilm occurs. This length was taken as the length from

the Muent port to effluent port (approximately 65 cm). The reactor diameter was the

average measured inside diameter of the colurnn, and the particle sire was the measured

average diameter of the clean glass beads. The initiai clean bead porosity was measured

before testing using multiple measurements of the volume of water drained (the "drained"

porosity).

5.3.4.3 Flow Rate and Influent Concentration

For modelling purposes the flow rate was taken to be the average of the flows

obtained by regularly measuring the accumulated effluent volume and dividing by the

elapsed time. The influent concentration was taken as the average measured COD

concentration.

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5.3.4.4 Calcium Carbonate Yield Coefficient, Y,

As discussed in Section 4.4.5.3, a calcium carbonate yield coefficient may be

calculated from the COD rernoval and CaCO, precipitated for a particular set of

conditions. The infiuent and effluent COD concentrations and infiuent and efluent

calcium hardness were measured regularly. This data was used to calculate the COD

removed and CaCO, precipitated for each sampling time. The COD removed was plotted

against the CaCO, precipitated as shown in Figure 5.14. The slope of the straight line

passing through the experimental data and the ongin was to be the yield coefficient, Y,. A

single yield coefficient was derived fiom the data fiom the three sirnilar experiments.

5.3.4.5 Percent Acetic Acid

The average concentrations of acetic, propionic and butyric acids in the synthetic

leachate (approx. 7000 mg acetic 1 L ; 5000 mg propionic 1 L ; 1000 mg butyric / L )

were converted to concentration in terms of COD per litre (approx. acetic: 7399

mgCODL; propionic: 7565 mgCoDa; butyic: 18 18 mgCODL). The total calculated

COD concentration fi-orn these sources was approximately 16,782 mgCOD/L, which

compares well with the measured average infiuent concentration of 17,070 mgCODL.

The portion of the COD fiom the acetic acid source was caiculated to be approximately

44%.

Page 169: Modelling of Clogging in Laboratory Column Experiments

Table 5.5 : Directly Measured Input Parameters

-

Pararneter Value Units

Temperature 23i1 OC

Reactor length 65 cm

Colurnn diameter 5.08 cm

Bead diameter 0.6 cm

Porosity 0.382 - Flow (avg.) 1.12 L / day

[niluent concentration (avg.) 17070 mgCOD / L

Calcium carbonate yield rate, Y, 0.2 1 mgCaCo, / mgCOD

Percent acetic 44 YO

5.3.5 Indirectly Measured Input Parameters

5 -3.5.1 Refiactory Concentration

The refractory concentration, or non-degradable influent concentration, was

measured from batch tests to be no greater than approximately 500 mgCOD/L for actual

landfill leachate. To account for the significantly lower expected mass of non-degradable

organics in synthetic leachate, the value was estimated as 200 mgCODL

5.3 -5.2 Density of the Active and Inactive films, qct, and Xci

The active density is required to calculate the thickness of the active film, as shown

in Equation 4.17 (Section 4.4.5.2) and the inactive density is required to calculate the

thickness of the inactive film, as shown in Equation 4.20 (Section 4.4.5.3). The active

density is the mass of volatile solids (volatile solids are presumed to be ceIl matter) per

Page 170: Modelling of Clogging in Laboratory Column Experiments

cubic centimetre of active film. The inactive density is the mass of non-volatile solids per

cubic centimetre of inactive film. The data required to calculate the film densities along

the length of each column can be measured during the autopsy performed immediately

after the terrnination of each test.

Since at the tirne of this anaiysis the synthetic leachate columns had not been

terminated and autopsied, the autopsy results of a sirnilar column experirnent run using

actual landfiii leachate was used (Armstrong, pers. comm.). The "sirnilar" column

experiment was performed in duplicate at approximately the same temperature, flow rate

and organic loading. The autopsy process determines, at regularly spaced heights along

the column, the mass of water, non-volatile solids and volatile solids per bead using

modified Hach DiU2000 Spectrophotometer Handbook procedures (Hach, 1993). Also

determined, by specific gravity tests, are the bulk density of the film, the dry density of the

film material (volatile and non-volatile), and the dry density of the non-volatile solids (eg.

ash). From this data, film thichesses and densities may be estimated. To the time of

writing, the autopsy procedure could not isolate the properties of the active film fiom the

inactive film. Thus, for the purposes of density measurement, the structure of the film was

idealized as two films: an active film consisting of ail of the volatile solids and water, and

an inactive film consisting of the non-volatile solids.

Idealizing the films in this marner aliows the active biofilrn thickness and density to

be calculated using published methods, such as those of Rittmann et al. (1 986) as

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described in the following. Using this method the biofiim is assumed to be approximately

99% water by weight, the active film thickness Lt, cm be calculated using

where W, is the mass of evaporated water per bead, p is the density of water at 2 1 OC, and

A is the surface area of one bead. The active film density, was calculated using

where B, is the mass of volatile solids per bead.

The active film density used for modelling purposes was taken as the average

active f lm density in the two KVL leachate columns autopsied, where the active film

density in a column was calculated as the average of three samples taken From the top (or

outlet) half of the column, from 30cm to 65 cm from column base. This value was used

because it was hypothesized that the top portion of the column contained samples which

better represented the active biofilm density. Near the inlet the decreased water content

(indicating a decrease in active film) and increased volatile content means it is less likely

that the volatile solids are only contained in the active film, and therefore less accurately fit

the idealized active film. The lower active film densities measured at the top of the

column also better represent the active densities during the duration of the test. The

measured active density input parameter is given in Table 5.6.

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Since it was assumed that al1 the non-volatile solids were located in the inactive

film, the inactive film density was measured by performing a specific gravity test on the

oven-dried ash remaining after the volatization of the film material. The measured inactive

density input parameter is given in Table 5.6.

Table 5.6 : Indirectly Measured input Parameten

Parameter Value Units

Refractory concentration, S, 200 mgCOD 1 L

Active film density, Xf, 70 mgVS 1 cm3

Inactive film density, xi 2700 mgTS 1 cm3

5.3.6 Assumed Mode1 Parameters

5.3.6.1 Introduction

The assumed model parameters are listed in Table 5.7. These parameters were

determined f?om research of published data and application to the particular system

modelled. The parameters are discussed in greater detail next.

5.3.6.2 Permeability

Due to the high active biofilm density measured, and the high precipitate

accumulation (especially at later times), the active biomass is considered impermeable.

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5.3 -6.3 Kinetic Constants Ks, Y, and b

The kinetic constants Ks, 4, Y, and b were not directly measured. A summary of

reported values for kinetic constants corresponding to anaerobic degradation of acetic and

propionic acid by a variety bacteria is given in Table 5.10 (page 164). These values are

also plotted in Figures 5.15, 5.16, S. 17 and 5.18. Cornparison of kinetic values is made

difficult due to the variability in the environmentai and operational conditions (eg. pH,

organic loading), the mode of operation (eg. batch vs. continuous) and the lack of

advanced instrumentation in older studies (Pavlostathis and Giraldo-Gornez, 199 1). In the

absence of experimentally derived kinetic constants specific to the system modelled,

average kinetic values will be utilized, but only to show the applicability of the model

within reasonable ranges of kinetic constants.

The substrate type and temperature will be used to select kinetic constant values

for input to the model. Lawrence and McCarty (1969) found that fiom conversion of

volatile fatty acids the maximum specific substrate utilization rate, q, and half-velocity

coefficient, Ks, varied with temperature while the yield coefficient, Y, and decay

coefficient, b. were relatively unaffected. Lin et al. (1 987) found that for a VFA mixture,

there was a slight decrease of Y with temperature. Figure 5.15 illustrates the decrease in

the half-velocity coefficient with increasing temperature. The increase in 4 with increasing

temperature reported by Lawrence and McCarty ( 1969) is not clear in Figure 5.16. The

yield rate and decay coefficient show little evidence of variance with temperature in

Figures 5.17 and 5.18.

Page 174: Modelling of Clogging in Laboratory Column Experiments

Since the half-velocity coefficient Ks has an established temperature variance,

separate acetic and propionic coefficients were estirnated for 22 O fluid temperatures from

the reported measured values. These values are listed in Table 5.7. The maximum

specific substrate utilization rate 4 was varied to fit the predicted data to the measured

data, providing 4 remained within estimated, reasonable temperature dependent limits,

assumed to be 1.5 to 8 mgCOD/mgVSS-d at 22'. The yield and decay coefficients, Y and

b, were fixed values calculated using the averages of the population of reported values for

each coefficient (see Table 5.7).

5 -3 -6.4 Coefficients of Difision

The coefficients of diasion for the substrates in fiee solution and within the

biofilm were obtained fi-om literature. The intemal difision coefficient, D, and diffusion

ratio DF,, , published by Yu and Pinder (1993) for acetate and propionate were used to

establish the free difision coefficient for each substrate. The interna1 difision

coefficients arid fiee solution dif'fiision coefficients for the substrates modelled are Iisted in

Table 5.7. In the absence of temperature dependence factors for diffusion coefficients, the

values, measured at 35 OC, were applied without modification. Note that these values

correspond to DdD, ratios of 4 1 % and 3 1%, which , as discussed previously in Section

5.2.5.4, are significantly lower than the ratio of 80% suggested by Williamson and

McCarty (1 976).

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Table 5.7 : Assumed Model Parameters

Pararnet er Value Units

Penneability of biofilm

Ks (Propionic)

Y (Propionic)

K, (Acetic)

Y (Acetic)

b (Substrate mixture)

Do (Propionic)

D, (Propionic)

Do (Acetic)

Df ( Acetic)

Detachment model

Impermeable

2800

0.042

1700

0.03 8

0.066

1.27

0.52

1.5

0.47

Growth

- mgCOD / L

mgVS I mgCOD

mgCOD / L

mgVS / mgCOD

d- ' cm2 / d

cm2 / d

cm2 / d

cm2 / d

-

5.3.7 Variable Model Parameters

5.3.7.1 Introduction

A number of numerical parameters wiil be varied to optimize the accuracy of the

model fit while the value of 4 will also be varied over a reasonable range t o examine its

effect on model fit. Table 5.8 lists the initial estimate of these parameters and the value

used in the final analysis.

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5.3.7.2 Timesteps and Segments

The number of timesteps, length of timesteps, and number of segments were

established using the same approach as described in Section 5.2.4.1 for the Rittmann and

McCarty data. The optimization will be discussed in Section 5.3 -6.

5.3 -7.3 Maximum Specific Substrate Utilization Rate, 4

The initial estimates of the maximum specific substrate utilization rates were based

on temperature dependence, as discussed in Section 5.3 -6.3.

Table 5.8 : Variable Mode1 Parameters

Parameter Initially Optimum or Units Estimated Best Fit

Value Value

Number of timesteps 300 1500

Length of timestep 1 0.2 day

Number of segments 13 13

4 (Acetic) 4 3.9 mpCOD 1 rngVS-d

5.3.8 Predicted Results Based on Initial Parameter Estimates

The predicted and measured variation in the normalized effluent COD

concentration (ie effluent COD 1 influent COD) with time were compared as shown in

Figure 5.19. It can be seen in Figure 5.19 that the measured effluent concentrations of the

3 column tests were nearly identical. The results show an initial penod of approximately

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100 days of negligible removal (a "lag" phase), followed by an approximately 60 day drop

in effluent concentration and then a relatively steady period of between 0.45 to 0.65

normalized COD. In addition, the predicted and measured drained porosity along the

length of the column afler 220 and 270 days of operation were compared as shown in

Figure 5.20. Figure 5.20 (a) and (b) show that the porosity at the column inlet (near the

bottom of the column) decreased more rapidly than at the outlet (near the top).

In non-linear modelling of the form being conducted here the numerical parameters

(timestep and segment length) can oniy be optimized if the physical parameter altered

provide a reasonable approximation to the measured normalized COD concentrations.

The fit shown in Figure 5.19 is reasonable for the first 120 days, but gives a poor

prediction between 120 and 270 days. To aid in understanding why this situation occurred

the maximum specific substrate utilization rate, 4, was varied. Based on experience

modelling aceticlpropionic acid mixtures, it was known that the initial lag period is

strongly dependent on the acetic acid kinetics, while the steady state portion was strongly

dependent on the propionic acid kinetics. Since the initial lag penod was well predicted by

the model, but the COD removal of the measured steady-state portion was overestimated

by the model (see Figure 5.19), it was expected that the maximum specific substrate

utilization rate of the acetic acid was reasonable but that the value for propionic acid was

too high. To examine this the value for acetic acid was held constant while that for

propionic acid was decreased fiorn 4 to 3 mgVS/mgCOD-d. The revised predictions are

shown in Figure 5.2 1 and Figure 5.22. Since the predicted effluent concentration now fit

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the measured values reasonably well, the number of timesteps and segments could be

optimized.

5.3.9 Defining the Required Number of Timesteps and Segments

5.3 -9.1 Timesteps

As discussed previously in Section 5.2.4.1, the optimum timestep length must be

found such that funher decreases in timestep length gave an insignificant change in the

results. The input parameters used to predict the curves plotted in Figures 5.21 and 5.22

were used with timestep Iengths of 1 .O, 0.2 and 0.04 days to produce the results shown in

Figures 5.23 and 5.24. The reduction in the timestep from 1 -0 to 0.2 days reduced the

predicted lag time before the steep concentration drop, but has no effect on the predicted

effluent concentration during the lag time or steady state periods. Reducing the timestep

From 0.2 to 0.04 days gave an insignificant change in predicted effluent concentration.

Similarly, the predicted porosity decreased due to a decrease in timestep from 1.0 to 0.2

days, but did not change significantly when the timestep is reduced from 0.2 to 0.04 days.

The predicted decrease in porosity is greatest at the inlet end of the column at the earlier

time of 220 days. It was concluded that 0.2 day tirnesteps provide reasonable predictions

of effluent concentration and porosity.

5.3.9.2 Number of Segments

The previous model runs were perfonned assurning the column could be modelled

using 13 segments, each 5 cm in length. As discussed in Section 5.2.4.2, model accuracy

is improved by minimiung the volume of the segments. In order test the sensitivity of the

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predicted results to the number of segments an analysis was performed using 26 segments

each 2.5 cm in length with a timestep of 0.2 days. The predicted effluent concentration

and porosities at 220 and 270 days are show in Figures 5.25 and 5.26 and it can be seen

that there was no significant difference in effluent concentration or porosity. It was

concluded that a timestep of 0.2 days and a segment length of 5.0 cm (13 segments) were

reasonable for the purpose of predicting the behaviour of the columns.

5.3.10 Results and Discussion

5.3.10.1 Prediction of Measured Data

Inspection of the measured and predicted porosities s h o w in Figure 5.26 indicates

that using the current input parameters, porosities at the inlet are underestimated at 220

days, but otherwise the predicted values provide a reasonable fit to the data at both 220

and 270 days. To improve the predicted porosities, the maximum specific substrate

utilization rate of the acetic acid portion of the mixture was decreased fiom 4 to 3 -9

mgVS/mgCOD-d. Figures 5.27 and 5.28 show the predicted and rneasured effluent

concentrations as they Vary with time and porosities at 220 and 270 days using the new

utilization rate. There was an insignificant effect on effluent concentration and a small

increase in porosity. The predicted effluent concentrations (Figure 5.27) fit very well to

the measured data. The predicted porosities (in Figure 5.28) fit reasonably well to both

the measured porosities at both 220 days and 270 days.

At earlier times, in particular 130 days, the porosity is not as well predicted (Figure

5.29a). The average measured drainable porosity ranges between approximately 0.35 at

Page 180: Modelling of Clogging in Laboratory Column Experiments

the efnuent port to 0.30 at the influent port while the mode1 predicts a porosity of about

0.36 which is relatively constant along the length of the column.

5.3.10.2 Predicted Chronological Ecology of the Synthetic Leachate Column System

O - 50 davs : Acetate and propionate degrader lae phase

In the period up to 50 days there was negligible growth of the biofilm due to

propionate and acetate degraders as s h o w in Figures 5.30 and 5.3 1 and inactive film as

show in Figure 5.32. This period of negligible growth is known as a "lag" phase. This

resulted in negligible decreases in propionic and acetic COD through the column (see

Figures 5.33 and 5.34).

50 - 100 davs : Propimate lu acetate degrader ~ o w t h b a

In this period the lag phase of the propionate degraders continued and there was

nedigible inactive film accumulation as show in Figures 5.30 and 5.32. Acetate

degraders began to grow as shown in Figure 5.3 1, giving a relatively constant biofilm

thickness throughout the length of the column (see Figure 5.35b). This uniform growth of

acetate degraders resulted in a linear decline in acetate COD concentration along the

column, and a slight decrease in effluent acetate COD concentration as shown in Figures

5.33 and 5.34b.

100 - 150 davs : Prooionate d e d e r Iw acetate degrader erowth

The lag phase of the propionate degraders continued and little inactive film

accumulated (see Figures 5.30 and 5.32). The growth rate of acetate degraders increased

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substantiaily along the column (see Figure 5.3 I), but remauied relatively unifonn, with

only slightly more growth at the inlet end of the column (see Figure 5.35b). A large

decline in acetate COD along the column could be seen in Figure 5.34b, nearly constant

removal occurring along the length of the column. The result was a steep decline in

effluent acetate COD, and a deciine in etnuent total COD, as shown in Figure 5.33.

150 - 300 d a ~ s - Propionate degrader growth. acetate demader growth and decline

(a) 150 - 225 days - Decline of acetate degraders near outlet, rapid growth of

acetate degraders at inlet

Over the period of 150 to 225 days a decline in acetate degraders occurred

between 20 and 65 cm fiom the rniddle of the co1umn to the outlet end, as shown

in Figure 5.3 1, and Figure 5.35b by cornparison of 150 and 200 day profiles. The

decline was likely due to acetate deficiency caused by the great accumulation of

acetate degraders near the inlet dunng this period, as shown in Figures 5.3 1 and

5.35b. The acetate deficiency near the outlet is indicated by the relatively constant

acetate COD concentration (zero removal) at 200 days above 30 cm in Figure

5.34b.

@) 175 - 300 days - Propionate degrader growth phase near outlet

At approximately 175 days the growth phase of the propionate degraders

began as shown in Figure 5 -30. It can be seen in Figures 5.35a and 5.36 that the

growth occurred mostly in the latter 20 - 65 cm of the column. The restriction of

propionate degraders fiom near the inlet was likely due to Ioss rate control, as the

Page 182: Modelling of Clogging in Laboratory Column Experiments

high rate of growth of acetate degraders near the inlet (discussed in part (a),

above) caused great detachment of both acetate and propionate degraders, as

illustrated in Figure 5.37. The propionate growth phase results in a decrease in

propionate COD dong the column, as shown in Figure 5.34% and in effluent

propionate COD in Figure 5.33. The degradation of the propionic acid resulted in

production of acetic acid (see Figure 5.38) where the total COD concentration in

the effluent remained relatively constant in a range of about 9000 to 9500

mgCOD/L (see Figure 5.33).

(c) 250 - 300 days - Second phase of acetate degrader growth at outlet

A second penod of growth of acetate degraders began near the outlet as

shown in Figure 5.3 1 and Figure 5.35b after about 250 days. This new growth is

caused by the acetate production by the late growth of propionate degraders near

the outlet while most of the acetate From the influent has been utilized before

reaching this part of the column (see Figures 5.34b and 5.38).

(d) Film accumulation

Inactive film growth occurred at a nearly linear rate (see Figure 5.32) and

with most accumulating near the inlet (see Figures 5.32, 5.39 and 5.40). Inactive

film growth is dependent on the flux of substrate into the active film, not on the

thickness of the active film, therefore the linear rate of the inactive film growth

(see Figure 5.40) indicates an increasing flux, even afler the acetate degraders

have plateaued (in segment 1 in Figure 5.3 1, for example).

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The variation in total film and active film thickness with time are s h o w in

Figures 5.4 1 and 5.42 respectively. Near the influent port there is rapid active film

growth from 125 to 200 days and slower growth d e r that. In contrast the total

film thickness increased (from 125 days) almost linearly with time until clogging

occurred. The rate of total film growth is much slower elsewhere indicating that

there is significant biofilm growth occumng near the influent pon.

5.3.10.3 Biomass Detachment

In developing the model it was assumed that suspended biomass in the influent

could be neglected, and that the re-attachent of detached biomass could be neglected.

The first assumption was tested by measuring the biomass content of the influent, which

resulted in negligible biomass since the influent was synthetic. The second assumption is

difficult to test, since while detached biomass in the effluent may be measured, the arnount

which re-attached within the column is unknown. Figures 5.43 and 5.44 show the

predicted rate of ce11 detachrnent in mass of volatile solids per day for the separate

degraders in the system (note the scale change). Since detachrnent and film thickness are

dependent on the substrate flux, the predicted trends of these two properties are nearly

identical, as indicated by cornparison of Figures 5.43 and 5 -44 to Figures 5.30 and 5.3 1.

Upon review of these figures it was concluded that fbrther research may be required on

this subject as it seemed that detached biomass becomes sigruficant at times of clogging,

and may re-attach downstream.

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5.3.11 Conclusions for the Synthetic Leachate Experiments

The model provided quite good predictions of effluent COD and column porosity

for the synthetic leachate experiments examined. For this analysis, the film densities

measured from similar autopsied column expenments, difision coefficients from

Literature, and kinetic coefficients taking into account substrate type and system

temperature, provided adequate input parameters. From cornparison of Figures 5.19 to

5.22 it was observed that the mode1 may be sensitive to some input parameters (in this

case <î). The parameters adopted al1 lie within the typical range based on published values.

Dunng penods of rapid growth, it may be difficult to predict porosity as shown in Figure

5.29(a) and 5.29(b).

The model provides a logical history of the ecologj of the system incorporating

bacterial growth and minerai accumulation, and the interaction between two bacterial

populations. A more detailed synthetic leachate column test study in which the separate

COD concentrations of the two substrates were measured, effluent biomass was rneasured

and autopsies were performed would allow many of the predicted phenornenon to be

compared to that observed in the laboratory.

Page 185: Modelling of Clogging in Laboratory Column Experiments

Table 5.9 Composition of Synthetic Keele Valley Leachate (MilIward,1997)

COMPONENT CONCENTRATION (mg/L)

Acetic (Ethanoic) Acid 7000

Propionic (Pmpanoic) Acid 5000

Butyric (Butanoic) Acid 1000

NaNO, 50

NaHCO, 3012

CaCI 2882

M&12 x 6H20 3114

MgSO4 156

NtI,HC03 243 9

co(NH32 695

Na$ x 9H,O (Eh adjusiment & reducing medium preparation)

Trace metal solution (TSM) 1 ml per 1L of synthetic leachate

Trace Metal Solution

FeSO, 2000

H3BQ 50

ZNSO, x 7H,O 50

CuSO, x 5H,O JO

MnSO, x 7H,O 500

96% concentrated H,SO, (An&) 1 ml

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Table 5.10 Summary of reported Monod kinetic constants for anaerobic degradation of propionic and acetic acids by various mixed cultures '

Reference Process ' T Ks Y 9 b " C mgCOD/L mgVSS/ mgCOD/ d-'

mgCOD me;VSS-d Propionic A cid O'Rotuke, J.T.. 1968

Lawrence and McCarty, 1969 Lawrence and McCarty, 1969 Chang et al., 1983 t Gujer and Zehnder, 1983 t Heyes, RH., and Hall,RJ., 1983

Heyes, RH., and Hal1,RJ.. 1983

Whitmore et al., 1985 t Siegrist et al., 1993 t

Acetic A cid

ORourke, J.T.. 1968

Lawrence and McCarty, 1969 Lawrence and McCarty, 1969 Lawrence and McCarty, 1969 Kugelrnan and Chin, 197 1 t Cappenberg, T. E., 1975

van den Berg, 1977

van den Berg, 1977

van den Berg, 1977

Massey and Pohland, 1978 Smith, M.R and Mah, RA., 1978 Zehnder, A.J.B. et al., 1980 Wandrey,C. and Aivasidis,A., 1983 Chang et al., 1983 t Noike,T., et al., 1985 Noike,T., et ai., 1985

Noike,T,, et ai.. 1985

Siegrist et al., 1993 pt al 1994h t W S f f 1813

' Compiled from summaries by Pavlostathis and Giraldo-Gomez (199 1) and Vavilin and Lokshina (1996).

t referenoes listed by Vavilin and Lokshina (1996). al1 others listed by Pavlostathis and Giraldo-Gomez (1 99 1).

C = chemostat data, B = batch data, N = , C/S = simulation mode1 used with chemostat data. average value.

* 4 calcuiated fiom =

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Predicted, dt = 1 .O d .,....... Predicted, dt = 0.2 d --. Predicted, dt = 0.04 d -..- Predicted, dt = 0.008 d

20

Elapsed Time (days) Figure 5.2 : Effect of timestep length dt on predicted effluent Acetate concentration for test BC3 using mean parameters.

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1 Segment 2 Segments

-- 4 Segments - - 6 Segments - 12 Segments - - 24 Segments

20

Elapsed Tirne (days)

Figure 5.3 : Effect of number of segments on predicted effluent Acetate concentration for test BC1 using mean parameters.

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Measured - Predicted at 21 days .... . Predicted at 28 days

4 6 8

Length Along Column (cm)

Figure 5.5 : Measured Acetate concentration profile along the length of the column at steady-state and initial predictions using mean parameters for test BC3.

Page 192: Modelling of Clogging in Laboratory Column Experiments

I 1

Measured - Fitted prediction at 21 days - ..... Fitted prediction at 28 days

L

I

I

4 6 8

Length Along Column (cm)

Figure 5.6 : Measured Acetate concentration profile along the length of the column at steady-state and fitted predictions using Ks = 4.48 mglL and b = 0.254 d-' for test BCI.

Page 193: Modelling of Clogging in Laboratory Column Experiments

Measured - F itted prediction at 21 days ..... Fitted prediction at 28 days

Length Along Column (cm) Figure 5.7 : Measured Acetate concentration profile along the length of the column at steady-state and fitted predictions using Ks = 4.48 mglL and b = 0.254 d-' for test BC3.

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Length Along Column (cm) Figure 5.9 : Measured biofilm thickness profile along the length of the colurnn at steady-state and fitted predictions using Ks = 4.48 mglL and b = 0.254 d" for test BC3.

Page 196: Modelling of Clogging in Laboratory Column Experiments

Measured - Biofilm permeable . . . . . Biofi lm impermeable

I

Length Along Column (cm) Figure 5.10 : Measured Acetate concentration profile along the length of the column at steady-state and effect of biofilm permeabitity on fitted predictions using K, = 4.48 mglL and b = 0.254 d" at 28 days for test BC3.

Page 197: Modelling of Clogging in Laboratory Column Experiments

Measured - LI variable (L, = 0.0129 cm initially)

. . L, fixed (LI = 0.0158 cm)

4 6 8

Length Along Column (cm) Figure 5.11 : Measured Acetate concentration profile along the length of the column at steady-state and effect of diffusion layer thickness LI on fitted predictions using K, = 4.48 mglL and b = 0.254 d" at 28 days for test BC3.

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" Il Il -

f e o

Page 199: Modelling of Clogging in Laboratory Column Experiments

Measured - Shear detachment ..... Growth detachment

Length Along Column (cm) Figure 5.13 : Measured Acetate concentration profile along the length of the column at steady-state and effect of detachment method on fitted predictions using Ks = 4.48 mglL and b = 0.254 d-' at 28 days for test BC3.

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26 28 30

Temperature (OC) Figure 5.15 : Reported measured half-velocity coefficient, KSI versus system temperature for bacterial growth in propionate and acetate (various sources, see Table 5.10).

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P Propionate A Acetate

26 28 30

Temperature (OC) Figure 5.17 : Reported measured yield coefficient, Y, versus system temperature for bacterial growth in propionate and acetate (various sources, see Table 5.10).

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! 1 Column SOI L 0 Column S02 r Column S03 - Predicted

150

Time (days) Figure 5.19 : Measured and initially predicted normalized effluent concentration using q = 4 mgCODlmgVS-d for propionic acid and q = 4 rngCOD/mgVS-d for acetic acid for column tests fed synthetic leachate.

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I

Column S01 - 0 Column S02 v Column S03 - Predicted

150

Time (days) Figure 5.21 : Measured norrnalized effluent concentration and model prediction using q = 3 mgCODImgVS-d for propionic acid and q = 4 mgCOD1mgVS-d for acetic acid for column tests fed synthetic leachate.

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Column SOI 0 Colurnn S02 r Column S03 - Predicted, 13 Segments

-- Predicted, 26 Segments

O 50 100 150 200 250

Time (days) Figure 5.25 : Measured normalized effluent concentration and the effect of the number of segments on mode using q = 3 mgCODlmgVS-d for propionic acid and q = 4 mgCODlmgVS-d for acetic acid for column tests fed leachate.

I predict ions synthetic

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H Column SOI 0 Column S02 t v Column S03 1 1 - Predicted (Fitted) 1

Elapsed tim = 220 days "Pr

0. O O. 1 O. 2 0.3 0.4

Drained Porosity

Column SOI v O O Column S02 O r a r Column S03 1 - Predicted (Fitted) 1 1

O. 0 O. 1 O. 2 O. 3 0.4

Drained Porosity Figure 5.28 : Measured porosities and model predictions using q = 3 mgCODlmgVS-d for propionic acid and q = 3.9 mgCODlmgVS-d for acetic acid after 220 and 270 days of operation of columns fed synthetic leachate.

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Propionate ~eiraders

- Ht = 2.5 cm (Seg. 1) - Ht = 12.5 cm (Seg. 3) -- Ht = 22.5 cm (Seg. 5) -- Ht = 32.5 cm (Seg. 7) . . . . Ht = 42.5 cm (Seg. 9) - - Ht = 52.5 cm (Seg. 11) - .- Ht = 62.5 cm (Seg. 13)

150

Time (days)

Figure 5.30 : Variance of predicted propionate degrader film thickness at specified column heights (Ht) over tirne.

Page 217: Modelling of Clogging in Laboratory Column Experiments

Acetate ~ e ~ r a j e r s 1

Ht = 2.5 cm (Seg. 1) - Ht = 12.5 cm (Seg. 3) -- Ht = 22.5 cm (Seg. 5) -- Ht = 32.5 cm (Seg. 7) . . Ht = 42.5 cm (Seg. 9) - - Ht = 52.5 cm (Seg. 11) - . - Ht = 62.5 cm (Seg. 13)

150

Time (days)

Figure 5.31 : Variance of predicted acetate degrader film thickness at specified column heights (Ht) over time.

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150

Time (days)

Detachment Cc efficient, b'

Figure 5.37 : Variance of predicted detachment coefficient b' at specified column heights (Ht) over time.

-

Ht = 2.5 cm (Seg. 1) - - Ht = 12.5 cm (Seg. 3)

-- Ht = 22.5 cm (Seg. 5) -- Ht = 32.5 cm (Seg. 7) . . Hl = 42.5 cm (Seg. 9)

- - Ht = 52.5 cm (Seg. 11)

I - - Ht = 62.5 cm (Seg. 13) I I /

Page 224: Modelling of Clogging in Laboratory Column Experiments

Propionic COD . . . . * Acetic COD Total COD

O 4000 8000 12000 16000

COD Concentration (mgCOD/L)

O 4000 8000 12000 16000

COD Concentration (mgCODIL)

Figure 5.38 : Predicted propionic, acetic and total COD profiles along the column at (a) 220 days and (b) 270 days.

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I - Ht = 2.5 cm (Seg. 1) Total - -- Ht = 2.5 cm (Seg. 1) Inactive -.. Ht = 62.5 cm (Seg. 13) Total

- . . . . . . . Ht = 62.5 cm (Seg. 13) Inactive

150

Time (days) Figure 5.40 : Variance of predicted total and inactive film thickness at the influent (Seg. 1 ) and effluent (Seg. 1 3) ends of the column over time.

Page 227: Modelling of Clogging in Laboratory Column Experiments

Total Film -

Ht = 2.5 cm (Seg. 1) - Ht = 12.5 cm (Seg. 3)

- -- Ht = 22.5 cm (Seg. 5) -- Ht = 32.5 cm (Seg. 7)

. , Ht = 42.5 cm (Seg. 9) - - - Ht = 52.5 cm (Seg. il) - . - Ht = 62.5 cm (Seg. 13)

*

---- - .- . 7

150

Time (days) Figure 5.41 : Variance of predicted total film thickness at specified column heights (Ht) over time.

Page 228: Modelling of Clogging in Laboratory Column Experiments

Total Active Filh

Ht = 2.5 cm (Seg. 1) - Ht = 12.5 cm (Seg. 3) -- Ht = 22.5 cm (Seg. 5) -- Ht 32.5 cm (Seg. 7)

, . . Ht = 42.5 cm (Seg. 9) - . - Ht = 52.5 cm (Seg. Il) - . - Ht = 62.5 cm (Seg. 13)

150

Time (days)

Figure 5.42 : Variance of predicted total active film thickness at specified column heights (Ht) over time.

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Acetate Degraders

-- Ht = 2.5 cm (Seg. 1) - Ht = 12.5 cm (Seg. 3) -- Ht = 22.5 cm (Seg. 5) - -- t i t = 32.5 cm (Seg. 7) . . . Ht = 42.5 cm (Seg. 9) - - - Ht = 52.5 cm (Seg. 11) - . . - Ht = 62.5 cm (Seg. 13)

/'

/ / -----

150

Time (days)

Figure 5.44 : Variance of predicted detachment rates for acetate degraders at specified colurnn heights (Ht) over time.

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CHAPTER 6

CONCLUSIONS AND RECOMMENDATIONS

6.1 INTRODUCTION

This chapter provides a sumrnary and the conclusions of the work presented in this

thesis, and provides recornmendations for further model development.

6.2 SUMMARY AND CONCLUSIONS

The key processes involved in the clogging in othenvise well maintained Iandfill

leachate collection systems may be simulated under controlled laboratory conditions using

synthetic leachate and columns packed with porous media. A model was designed to be

applicable to the saturated laboratory experiments as a first step towards modelling the

clogging in a complete leachate collection systems. The model focused on the prediction

of clogging due to biological growth and biologically driven mineral precipitation since

with current design and maintenance practices most other causes of clogging can be

controlled in the L.C. S. or laboratory experiment .

As indicated in Chapter 2, current research has s h o w that under favourable

conditions rapid growth of bactena in the form of biofilms, and mineral deposits formed in

association with bacterial activity occur on the granular media of the L.C. S., and that this

phenornenon may be simulated using laboratory colurnn expenments. An idealized film

Page 232: Modelling of Clogging in Laboratory Column Experiments

structure consisting of an outer active layer of biomass and an inner inactive layer of inert

biomass and biochernical precipitate was developed.

In Chapter 3 a geometric model developed by Taylor et al. (1990) was modified to

ailow accurate calculation of porosity and specific surface area for granular media coated

with a known thickness of film. The mode1 assumes that the granular media cm be

represented by a regularly packed ideal spheres of equal diameter. Under these conditions

only four stable packing arrangements exist, each with a unique clean sphere porosity.

The fûnctions used for calculation of porosity and specific surface area are interpolated

f?om the four known functions given the initiai clean stone porosity and current film

thickness.

The model is described in Chapter 4. The fiow system is discretized into

subregions where each subregion, or element, is assumed to act as a separate, k e d film

reactor. Within each element organic substrate is converted by bacteria into additional ce11

mass, with the remaining substrate being the infiuent to the next element. The column test

consists of a single series of saturated elements with a single influent source at one end,

and a single efnuent port at the other. The system initially contains zero substrate and a

specified uniform layer of inoculum biofiim. An innuent flow rate and substrate

concentration is applied to the first segment of the system. An advective transport

algonthrn using a time stepping process is applied to mode1 the movement of substrate

dong the length of the colurnn.

Page 233: Modelling of Clogging in Laboratory Column Experiments

B i o f h growth and loss due to a single substrate was modelled using an algorithm

modified fiom Rittmann and McCarty (1981) and Rittmann and Brumer (1984). An

additional substrate was modelied by repeating these algorithms for a second substrate

with its own growth parameters and concentration, and allowing each substrate to

contnbute to a separate active and inactive film thickness. The growth and loss algorithm

is combined with equations to model the change in porosity and specific surface area. mass

balance equations, and detachment equations. Due to non-linearity, two coupled iterative

procedures were required to derive the effluent COD concentration, film thickness,

porosity, and specific surface area at for an element at a tirnestep. These calculations were

repeated for each element, fiom the influent to efnuent end of the column, and each series

of element calculations was repeated each timestep.

In Chapter 5 two applications of the model are addressed. In the first case the

model is applied to the published data of Rittmann and McCarty (1 980). In this

expenment a single substrate (acetate) was used, and kinetic parameters were derived in

independent experiments. Using the same kinetic parameters for the two sets of data for

experiments at dEerent flow rates and influent concentrations provided a reasonable fit to

both measured acetate concentrations and biofilrn thicknesses dong the length of the

column. Due to the chernistry of the infiuent and the short duration of the experirnent, it

was not necessary for the model to simulate the effects of inactive film growth, clogging,

or an additiond substrate.

Page 234: Modelling of Clogging in Laboratory Column Experiments

In the second case the model was applied to a colurnn fed synthetic landfill

leachate performed by Millward (1997), Armstrong (pers. comm.) and J. vanGulck (pers.

comm.). The experiments were nin to a high degree of clogging, were expected to

contain considerable mineral precipitation, and the kinetic coefficients had to be obtained

from published reports. Two substrates (acetic and propionic acid) were used to represent

the synthetic Ieachate. Using estimated kinetic parameters the model predicted effluent

COD concentrations and porosity profiles dong the length of the columns which fit

reasonably well to experimental data. The model was found to be sensitive to the kinetic

parameters used to fit the data, the maximum specific substrate utilization rate 4.

Additional research is required to derive kinetic parameters for landfill leachate, synthetic

leachate, propionic acid and acetic acid under the temperatures and loadings expected

within the L.C. S.. The model provides a Iogical history of the ecology of the system

incorporating bacterial growth and mineral accumulation, and the interaction between two

bacterial populations.

6.3 RECOMMENDATIONS

6.3.1 Introduction

The clogging of leachate colIection systems is a serious concern and any

improvements which can be made to increase the accuracy of predictions should be

pursued. This thesis described a model for simulation of saturated colurnn experiments

conducted using synthetic Ieachate with negligible suspended soiid content and was

intended as the first step towards developing a complete model for leachate collection

systems. Further work, therefore, should be focused on both predicting the clogging in

Page 235: Modelling of Clogging in Laboratory Column Experiments

laboratory column expenrnents conducted with real leachate (which contains bacterial

loading and suspended solids), and on extending the model towards the clogging of

granular drainage layers. The recommendat ions, t herefore, are broken into groups:

Drainage Layer Model Changes, for extending the model to represent leachate collection

systems, General Model Changes, for better prediction of clogging of any porous system,

and Additional Research suggests aspects of the current topic requiring improvement.

6.3.2 Drainage Layer Model Changes

The mode1 could be extended to simulate the clogging of the leachate collection

system by :

(a) modelling one drainage path from the top of the dope to the pipe using a senes

of segments, with each segment containhg multiple elements,

@) distributing the flow so that the upper unsaturated element in each segment

receives flow, and after treatment delivers it to horizontal flow elements, with this

flow from the segment entering the horizontal flow element of the downstrearn

segment where it is mixed with the downward flow from this segment, and so on,

(c) aliowing the upper, unsaturated portion of the drainage layer to be represented

by elements within which biofilm growth and loss is given special consideration

and flow is downward,

(d) allowing the number of saturated elements dong the length of the siope to be

chosen so that the height of saturation corresponds to the arnount of flow through

the zone. The use of variable heights of saturation will require further research.

Page 236: Modelling of Clogging in Laboratory Column Experiments

(e) upon clogging of a saturated element in this scenario, flow could be stopped

within the element, and diverted over it by adding saturated elements within the

unsaturated zone

6.3.3 General Model Changes

6.3 -3.1 Spatial Variation of Particular Parameters

The model could be altered to allow elements to be given specific initial porosity

and particle (or stone) diameter, as opposed to a single porosity and particle diameter for

ail elements. This alteration could be applied to either a column or drainage layer flow

field. This would ailow the modelling of clogging of systems of varying stone sizes, such

as clear stone underlain by sand, a design used at KVL. Such a change would also require

changes to the present advection algo rithm.

Specific to the drainage layer flow field, the downward influent flow rate and

substrate concentration could Vary from segment to segment. This would allow modeliing

of a drainage layer which is, for example, covered with an unequal height of waste, thus

producing unequal flow rates and substrate concentrations dong the length of the slope.

6.3.3.2 Temporal Variation of Particular Parameters

Typicaily, measured influent flow rates, substrate concentrations and temperatures

from experiments or field studies do not remain constant. For these situations the model

could be altered to allow entry of data files containing the variance of the parameter with

time, or the choice of a time dependent fiinction which describes the variance. Penods of

Page 237: Modelling of Clogging in Laboratory Column Experiments

low or high flow or concentration cm have a great impact on the system, and this impact

is not represented when a fixed average value is used. Allowing the influent flow rates or

substrate concentrations to change with tirne will require changes to the present advection

algorithm.

6.3 -3.3 Bactend Transport

The model could simulate bacterial transport and attachment within the system.

Presently bacterial transport is neglected, but should be modelled if significant biomass is

measured in the influent to the system, or significant biomass is detaching fiom the porous

media.

6.3.3.4 Advection Algorithm

The current advection algorithm could be changed so that the substrate delay is not

precalculated, but instead recalculated based on changes in the porosity of the elements.

Many of the other model changes listed would require changes to the advection algorithm.

6.3.3.5 Representation of Additional Systems

The model could be expanded to represent systems with different geometry, flow

directions or attachrnent media. For example, by sirnpiifjmg the model the clogging of a

leachate collection pipe transporting leachate could be simulated, and with additional

modification the clogging of the pipe perforations could be modelled. The addition of

other attachrnent media such as geotextiles in drainage layers or metal screens in column

tests could be represented by solving the geometry of the film accumulation.

Page 238: Modelling of Clogging in Laboratory Column Experiments

6.3.4 Further Research

6.3.4.1 Colurnn Expenments

The verification of the modelling of acetic and propionic acid could be improved

using a column test similar to that of Millward and vanGuluck, but in which only acetic

and propionic acids are used (ie. no butyric acid), the COD of each acid should be

measured instead of only the total COD, and concentrations could be measured along the

length of the column over tirne. The autopsy of such a test should involve differentiation

of the bacterial populations to verify the predicted spatial distribution of the propionate

degraders and acetate degraders if possible.

6.3.4.2 Kinetic Constants

Considerable research is required in the area of the growth kinetics of landfill

leachate and landfill leachate constituents such as acetic and propionic acids. To date the

study of growth kinetics has been for use in wastewater treatment at high temperatures,

and therefore little is known of growth kinetics in the temperature range of leachate

collection systems (approx. O to 20 O C ) . The model may be sensitive to growth kinetics,

even within reasonable ranges as provided fiom literature. An expenmental method

should be developed for determination of these input parameters, and the dependence of

the kinetic constants to temperature and substrate loading should be determined.

6.3.4.3 Field Studies

Verification of the model with regards to leachate collection system clogging in

actual field conditions would require many parameters which are currently difficult to

Page 239: Modelling of Clogging in Laboratory Column Experiments

ohtain for a specific case (such as infiuent concentrations and flow rates). An exhumation

of a clogged L.C.S. rnay yield critical information. Modelling a more controlled system

representing a L.C.S., such the mesocosm studies of Rowe et al. (1995a) is also

suggested.

6.3 -4.4 Idealization of Films

The idealization of the film requires further study. In particular, the density and

distribution of cells and mineral deposits on the porous media over time grown frorn amal

and synthetic leachate should be studied. The relationship between these hdings and the

utilization of substrate and detachment of film matter rnay provide an improved simulation

of the processes at work.

6.3 -4.5 Additional Parameter Uncertainties

The following parameters require fbrther research: (a) the permeability of the

biofilm, (b) the moisture content and dependencies in an unsaturated zone if a drainage

layer model is developed, and (c) the effective difision layer thickness for large media

under low flow conditions such as those of a L.C.S..

6.4 OVERALL CONCLUSION

A model for prediction of biologically induced clogging in column expenments fed

synthetic leachate has been developed as a first step toward developing a model for

predicting clogging in landfill leachate collection systerns. Full verification of the model

will require further research however the cornparison of experimental and predicted

Page 240: Modelling of Clogging in Laboratory Column Experiments

behaviour presented in this thesis provides encouragement that the portion of the mode1

that deals with saturated flow as presented herein represents a substantial step fonvard.

Page 241: Modelling of Clogging in Laboratory Column Experiments

DETERMINATION OF CRITICAL FILM THICKWESSES OF THE POROSITY AND SPECIFIC SURFACE MODELS

A1.1 Introduction

Al . 1 . 1 Critical Film Thicknesses

Critical film thicknesses are thicknesses at which filling of the porespace has

occurred, or the geometrical basis of the porosity or specific surfhce mode1 must change.

The cntical film thicknesses occur when (a) spherical caps first overlap, (b) spherical caps

overlap at a diEerent region at a greater thickness, called a spherical overlap, (c) overlaps

overlap, and (d) at the thickness at which pore occlusion occurs. As film thickness

increases on an initially clean sphere, overlap will occur earliest in the face (or plane) of

the packing arrangement with the most contact points, since as the number of contact

points in the face increases, the closer the spherical caps are to each other and the thimer

the biofilm thickness required for volumes to overlap. The face with the most contact

points is the critical face. The critical face for the cubic packing arrangement is the square

face while the critical face for the other three packing arrangements is the rhombic face

(see Figure 3.1 and imagine the packing arrangement of each face repeating around a

single sphere to sum the contact points for each face).

Al . 1.2 The Contact Interface Radius, C R

To simplify the calculation of the critical film thicknesses, the radius of the contact

interface should be predetermined. The contact interface is the division between a

Page 242: Modelling of Clogging in Laboratory Column Experiments

sphere's film and a neighbouring sphere's f lm coinciding with the base of the spherical

cap, in the shape of a circle centred at the contact point between the spheres. Figure

Al. 1 shows a cross section of the spherical cap and the contact interface, DB. The C R

varies only with sphere size and film thickness, therefore the equation is consistent for al1

packing arrangements. The CIR is determined using :

- C o n t a c t interface R a d i u s = C I R = AB

AB = J - Z F

C I R = d(2 + - ( + j 2

CIR = JL;'-+ d F L c

where points 4 B, and C are points on Figure A l . I .

AL2 Cubic Packing Arrangement

A1.2.1 First Overlap, Cubic Packing Arrangement

The film thickness at which the first overlap of spherical caps occurs in the cubic

packing arrangement may be determined geometrically, Figure A1.2 depicts the spheres,

film, and film interface at the onset of spherical cap overlap. Using this figure it can be

seen that for a particular sphere, the onset of cap overlap occurs when the sphencal caps

meet at the intersection of the lines tangent to two neighbouring contact points. The

critical film thickness, in tems of 2Ld4 , can be determined as the thickness at which the

contact interface radius reaches the radius of the sphere, thus:

Page 243: Modelling of Clogging in Laboratory Column Experiments

C I R = Sphere radi us

L L c = fl - 1 P o s i t i v e r o o t : - d,

The normalized film thickness at which spherical caps overlap, and errors in the original

equations begin for the cubic packing arrangement, is 0.4142. The number of overlaps

requinng correction is 12.

A 1.2.2 Pore Occlusion, Cubic Packing

The film thickness at which the pore space becomes completely filled with film

may also be determined geornetrically. The onset of this state, also known as pore

occlz~sion, is s h o w in Figure A1.3. Section SS' in Figure A1.3 depicts the contact

interfaces of the eight spheres at this film thickness as diagonally hatched circles. On

inspection of Section SS ' it can be determined that pore occlusion occurs when the

contact interfaces meet at the centre of the square created by joining the contact points of

the eight spheres. The critical film thickness can be found by equating the contact

interface radius to the distance to the centre of square formed by the four contact points:

Page 244: Modelling of Clogging in Laboratory Column Experiments

CIR = Distance t o centre of

contact point square

L l i t =JS - 1 P o s i t i v e m o t :

Thus at a normalized film thickness of 0.732, pore occlusion occurs and hence the

porosity and specific surface go to zero. No other critical thicknesses occur between the

In overlap and pore occlusion, although it can be proven that the overlapped volumes

overlap with one another (tip of horizontal overlap with tip of vertical overlap) at exactly

the sarne thickness as pore occlusion occurs.

AL3 First Overlap, Non-cubic Packing Arrangements

Each of the three remaining packing arrangements, orthorhombic, tetragonal-

sphenoidal, and rhombohedral, have a rhombic face. In the following discussion and

figures for each of these packing arrangements the rhombic face is considered to be the

horizontal face, show in the Plan view of each figure. As discussed in section Al . 1.1 it is

in this face that the first overlap of spherical caps occurs for these packing arrangements.

Page 245: Modelling of Clogging in Laboratory Column Experiments

Figure A1 -4 (Plan) shows the rhombic face of the orthorhombic packing

arrangement at the onset of spherical cap overlap and Figure A1.5 plan) shows the same

spheres after overlap has occurred. The doubled hatched area in Figure A 1.7 (Plan)

indicates the cross-section of the overlapped volume. By comparison of Figure A1 -4 with

Figure A1.2 of the square face of the cubic arrangement, and with the understanding that

the spheres are of equal diarneter and are accurately illustrateci, it can be observed that the

film thickness at which overlap occurs in the rhombic face is significantly less than that of

the square face. By comparing the Plan views of Figures A 1 -3 and A 1.5 it may also be

observed that the cross-section of the overlapped space (the doubled hatched area) is a

diferent shape due to the difference in the geometry of the face. This difference is

discussed in Chapter 3.

Using Figure A1.4 (Plan) it c m be determined that for a particular sphere in a

packing arrangement containing a rhombic face the onset of the first sphencal cap overlap

occurs when the caps meet at the intersection of the lines tangent to two neighbouring

contact points. This intersection occurs at the centre of the equilateral triangle fonned by

joining the centres of the three spheres in the face. Since the spherical caps overlap when

the contact interface radii meet at this centre, the critical film thickness is determined by

equating :

Page 246: Modelling of Clogging in Laboratory Column Experiments

CIR =

2 L t - Posi t i ve r o o t : - -

d,

Distance from contact p o i n t

to t r i a n g l e centre

Therefore the nomalized film thickness at which the first overlap of sphencal caps occurs

for the non-cubic packing arrangements is 0.1547.

A1.4 Orthorhombic Parking Arrangement

A1 -4.1 Second Overlap, Orthorhombic Packing

Figure A1 -4 illustrates the rhombic face (Plan) and one square face (Section) of the

orthorhombic packing arrangement at the onset of overlap in the rhombic face. The six

spherical caps around the circumference of the sphere in the rhombic face will overlap (2

are shown in the Plan view), while the two remaining sphericai caps at the top and boaom

are not at the onset of overlap. One of the caps is depicted in the Section. Figure A 1.5

(Section) illustrates the same sections at the onset of overlap in the square face. This

event is considered the second overlap for this packing arrangement since it occurs

between spherical caps of different contact points than the first overlap. Since the

Page 247: Modelling of Clogging in Laboratory Column Experiments

geometry of this face is exactly the same as that of the 3 square faces of the cubic

arrangement, it cm be proven that this cntical film thickness occurs at the same film

thickness as proven in Section Al .2.l. The nomalized cntical film thickness, therefore,

at which the second overlap occurs in the orthorhombic packing arrangement is 0.4142.

12 overlaps must be replaced.

A 1.4.2 Pore Occlusion, Orthorhombic Packing

It was detemined that the onset of pore occlusion is best depicted by a section

perpendicular to the rhombic face, tangent to the spheres of the rhombic face at the

contact points of the spheres as illustrated in Section SS ' of Figure A 1.6. Grap hically,

pore occlusion in this section occurs when the film thickness of the two spheres on the left

intersect with the contact interfaces of the spheres on the nght. Assurning this intersection

occurs at d42 above the centre of the spheres in the Plan, the critical thickness is that at

which the sum of the lengths from points A to B and B to C equal the total distance from

points A to C. From the Plan view, the length AC can be found to be 6 / 2 d, , the length

AB is the contact interface radius, and the length BC can be calculated from the known

sides of the right triangle BCD, where BD equals CR. The film thickness is found by

equating :

Page 248: Modelling of Clogging in Laboratory Column Experiments

d2

After manipulation, L-' + d p L c - = O 3

Pos i t ive root: - -

Thus the normalized film thickness at which pore occlusion of the orthorhombic packing

arrangement occurs is 0.5275.

A1.5 TetragonaCSphenoidal Packing Arrangement

A 1.5.1 First Overlaps, Tetragonal-Sphenoidal Packing

The first film overlaps in the tetragonal-sphenoidal packing arrangement occur at

the sarne critical film thickness as the first film overlaps of the orthorhombic packing

arrangement since both arrangements contain a rhombic face as its critical face. The first

overlaps occur at a normalized film thickness of 0.1547. The tetragonal-sphenoidd

arrangement includes 2 rhombic faces, each contributing 6 overlaps for a total of 12

overlaps.

Page 249: Modelling of Clogging in Laboratory Column Experiments

A 1.5.2 Second Overlap, Tetragonai-Sphenoidal Packing

Figure A1.7 illustrates the tetragonai-sphenoidai packing arrangement at the film

thickness at which a second overlap occurs. The second overlap is the result of the

growth of film on the non-contacting spheres between the closest corners of the special

rhombic face, depicted in the top left and bottom right spheres in the section shown in

Figure A1 -7. The section in Figure A1 -8 shows the shape of the overlap after fiirther

growth as a cap-shaped hatched area. The overlap is a volume similar in shape to the

spherical caps at the contact points, but originating at a tangent plane which is not in

contact with the sphere, but at the midway point between the spheres. It is therefore

called a special sphericai cap. Using the section shown in Figure AIS, it can be seen that

this second overlap begins when the film thickness passes this rnidway distance. The

critical film thickness at which this second film overlap occurs may be determined,

therefore, by equating the sphere and film radius with the rnidway point of the short

diagonal, see Figure A 1.8 (Section). :

R a d i u s of sphere + f i l m = Midway p o i n t of d i a g o n a l

Page 250: Modelling of Clogging in Laboratory Column Experiments

The normalked thickness at which the second overlap of the tetragonal-sphenoidal

packing arrangement occurs is 0.2247. Four of these special overlaps occur for each unit

cell.

A 1.5 -3 Complex Overlaps, Tetragonal-Sphenoidal Packing

As the radius of the special spherical cap increases with film growth it eventually

rneets and overlaps with the regular spherical caps. The onset of this event is depicted in

the section in Figure A1 -8. The volumes of the complex shapes created by the overlap of

the special and regular sphetical caps could not be determined by simple methods. The

film thickness at which they occur is required so that the remaining porosities and specific

surfaces of larger film thicknesses can be simplified. In Figure A1.8 (Section) the length

AB represents the radius of the sphere plus film thickness, the length BC represents the

radius of the base of the special sphencal cap (sirnilar to C R the contact interface radius

of the regular spherical caps) and lengths AC and CD are geometrically known lengths for

this packing arrangement. The radius of the specid spherical cap can be determined using:

Radius of special

spherical cap, =

The complex overlaps occur when the radius of the sphere plus film thickness of the

bottom left sphere intersects with the radius of the special spherical cap, BC, on Iine AC.

Page 251: Modelling of Clogging in Laboratory Column Experiments

The critical thickness is the film thickness at which the sum of the radius of the special

spherical cap and the radius of the sphere plus film equals the known length AC. The

verification is as follows:

( R a d i u s of sphere + f i l m ) +

Radius of s p e c i a l cap = Half l e n g t h of d i a g o n a l

2L t After m a n i p u l a t i o n , -

dP

Thus at a normalized film thickness of 0.2649 the tetragonal-sphenoidal packing

arrangement becomes too cornplex to mode1 exactly. Frorn this thickness to pore

occlusion the porosity and specific surface will be assurned to vary linearly with film

thickness.

A 1.5.4 Pore Occlusion, Tetragonal-Sphenoidal Packing

In order to find the film thickness at which pore occlusion occurs a cross-section

of the packing arrangement clearly showing the largest pore space is given in Section BB

of Figure A1.9. Note that Section BB is of Section AA in Figure A1 -9, and Section AA

is indicated in the Plan in Figure A1 .a. The shaded circle in the centre of Section BB is

the base of the speciai spherical caps of spheres on opposite sides of the cross-section (ie.

Imagine a sphere out of plane, sitting in the 'hopper' created by the 4 spheres shown).

Due to the symrnetry of the arrangement, the spheres responsible for the special spherical

Page 252: Modelling of Clogging in Laboratory Column Experiments

caps out of plane are the sarne distance apart as those non-contacting pairs on the left and

right in the section shown. Due to this fact, the filling in of the pore space dong the

horizontal centre line, AB fiom the centre, A to radius B. is equal to that ftom the centre

of the spherical caps on either side, filling from C to B. The onset of pore occlusion can

be determined by solving for the film thickness at which the sum of the radius of the centre

sphencal cap base, AB, and the radius of the side spherical cap, BC, where AB equals BC,

equals half the diameter of the sphere.

2 x S p e c i a l sphere cap r a d i u s = Sphere r a d i u s

P o s i t i v e r o o t :

Pore occlusion of the tetragonal-sphenoidal packing arrangement occurs at a nonnalized

film thickness of 0.3229.

A1.6 Rhombohedral Packing Arrangement

A 1.6.1 First Overlap, Rhombohedral Packing

The cntical face of the rhombohedral packing arrangement is the rhombic face, and

therefore, similar to the orthorhombic and tetragonal-sphenoidai arrangements the cntical

thickness at which the first film overlap occurs is 0.1547. Since the rhombohedral

Page 253: Modelling of Clogging in Laboratory Column Experiments

packing arrangement has 3 rhombic faces, al1 contact interfaces have 4 overlaps each, each

beginning at the critical thickness. A total of 24 overlap volumes must be accounted for.

A 1 -6.2 Complex Overlaps, Ethornbohedral Packing

As film thickness increases in the rhombohedral packing arrangement a critical

thickness is met at which multiple overlaps of various shapes, including overlaps of

overlaps, occurs. The film thickness at which these complex overlaps occur is the critical

thickness at which exact porosity and specific surface calculation will terminate, and a

linear relationship to pore occlusion will begin. By inspection of Figure Al . 10, Section

SS ', the occurrence of a complex overlap is illustrated as the sphencal cap on the bottom

left sphere (hatch filled) intersects with the vertical plane through the centre of the sphere

at point A. At this thickness the remaining 2 spherical caps at the top of this sphere (out

of section) also converge at the 'peak', point A. An increase in film thickness will cause

overlapping and create complex volumes to be corrected for. The overlap of the contact

interface circle at the top of the section with the film of the bottom left sphere is a cross-

section of the intersection of the outsf-section sphencal cap overlaps. The radius of the

sphencal cap at which the intersection occurs cm be geometrically denved as illustrated in

the section in Figure Al. 10. The cntical film thickness may be found by equating:

Page 254: Modelling of Clogging in Laboratory Column Experiments

Jz Spherical cap r a d i u s , C I R = ? d p

P o s i t i v e r o o t : F

The normalized critical film thickness at which complex overlaps occur begin is 0.2247.

A 1 -6.3 Pore Occlusion, Rhombohedral Packing

In order to calculate the critical film thickness at which pore occlusion occurred

the thickness of the film at points along the line joining the contact points in section SS

were studied. It was assurned that pore occlusion occurred at the film thickness at which

the radius of the spherical cap intersected with the film thickness between the non-

contacting spheres in the section. Since it was assumed that the critical thickness rnay

cause an overlap between the non-contacting spheres, the length fiom the centre along the

line joining the contact points was caiculated as the radius of a special spherical cap

between the non-contacting spheres:

Page 255: Modelling of Clogging in Laboratory Column Experiments

R a d i u s of s p e c i a l

spheri cal cap, == ,/-

It was assumed that pore occlusion, therefore, happened when dong the line joining the

contact points D and E, the addition of the radius of the regular sphencal cap, EB to the

radius of the special sphericd cap, EB, equalled the known length of the line joining the

contact point to the midpoint. Thus:

CIR + Radius of special cap = Midway point of diagonal

2 4 Positive Root: - = fi - 1 dP

The nomalized cnticai film thickness at which pore occlusion occurs, therefore, is 0.4142.

By inspection of Figure Al. 1 1 and mathematical verification, it is noted that the critical

film thickness results in a film intersection coinciding with the intersection of the lines

joining the contact points and the spheres, and therefore there is no overlap of the film

Page 256: Modelling of Clogging in Laboratory Column Experiments

between the non-contacting spheres, and the special cap radius is zero at the critical film

thickness.

A1.7 Critical Film Thickness Summary and Interpretation

Table Al. 1 surnmarizes the critical fiim thicknesses cdculated in this appendix. It

can be seen fkom Table Al. 1 that at thicknesses greater than 2L/d, = 0.4142 for cubic and

2 L j 4 = 0.1547 for the other packing arrangements, the first overlap occurs and the

calculation of the volume and surface area of a sphere covered with film becomes

underestirnated using the base volume and surface area calculation methods of Taylor et

al. (1990). This causes the porosity to be overestimated and the specific surface

underestimated at these thicknesses. These points of first theoretical breakdown and thus

beginning of inaccurate results are indicated by a syrnbol for each packing arrangement for

each curve in Figures 3.1 and 3.2. Each additional cntical film thickness corresponds to a

change in the equation required to calculate the volume or surface area until the cntical

film thickness at which pore occlusion occurs is reached. These equations are derived in

Chapter 3.

Page 257: Modelling of Clogging in Laboratory Column Experiments

Table AL1 - Summary of Critical Film Thicknesses in Terms of TL, / d,

Packing Arrangement

Name

Cubic

Orthorhombic

Tetragonai- Sphenoidal

Rhombohedral

Nurnber of Contact Points

(1)

6

8

10

12

First Cap Overlaps

(2)

0.4 142

O. 1547

O. 1547

O. 1547

Second Cap Overlaps

(3 )

0.4 142

0.2247

0.2247

Complex Overlaps

(4)

0.732

0,5275

0.2649

0.2247

Complete Pore Occlusion

( 5 )

0.732

0.5275

0.3228

0.4 142

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Figure A l .1 : Verification of length of radius of interface circle at any contact point.

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SECTION

-- ~~~~~~

Figure A1.2 : Verifkation of film thickness at onset of spherical cap overlap for cubic packing.

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Figure A1.3 : Verification of film thickness at cornplete occlusion of cubic packing. Double hatched a r a indicates overlap of spherical caps.

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orthorhombic packhg. Hatched area indicates spherical cap at h o contacts.

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orthorhombic packing. Double hatched area indicates overlap of spherical caps,

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Figure A l .6 : Verifkation of film thickness at pore space occlusion for orfhorhombic packing .

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overlap for tefragonal-sphenoida packing.

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Figure A l .8 : Verification of film thickness at onset of complex overkps for tetragonal-spheroidal packing. Special spherical cap shown in centre of section.

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sphenoidal packing.

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SECTION S S'

Figure A l . 10 : Verification of film thickness at onset of complex overlaps for rhombohedral packing.

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Figure A l . 1 1 : Verification of film fhickness at onset of pore occlusion for rhombohedral packing.

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