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Anaerobic digestion of cheese whey in an upflow anaerobic sludge blanket reactor Yan, Jing-Qing 1991

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A N A E R O B I C  DIGESTION  A N A E R O B I C  O F C H E E S E  S L U D G E  W H E Y  B L A N K E T  IN A N  R E A C T O R  By Jing-Qing Yan B. Eng. South-Central University of Technology, China M. Sc. Dalian Institute of Physical Chemistry, Chinese Academy of Sciences  A  T H E S I S  S U B M I T T E D  T H E  I N  P A R T I A L  R E Q U I R E M E N T S  D O C T O R  F O R  O F  T  H  F U L F I L L M E N T  E  D E G R E E  O F  P H I L O S O P H Y  in T H E  F A C U L T Y  O F  C H E M I C A L  G R A D U A T E  S T U D I E S  E N G I N E E R I N G  We accept this thesis as conforming to the required standard  T H E  U N I V E R S I T Y  O F  B R I T I S H  C O L U M B I A  March 1991 © Jing-Qing Yan, 1991  O F  U P F L O W  In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives.  It is understood that copying or publication of this thesis for  financial gain shall not be allowed without my written permission.  Chemical Engineering The University of British Columbia 2075 Wesbrook Place Vancouver, Canada V6T 1W5  Date:  Dedication  To my parents for their love, encouragement and sacrifice.  11  ABSTRACT  T h e anaerobic digestion of cheese whey was studied in an upfiow anaerobic sludge blanket reactor for its start-up characteristics, the effects of various process parameters, the effect of sulfate addition and the determination of optimal operating conditions. Start-up of an U A S B reactor treating cheese whey was extremely difficult due to its tendency to acidify. Various start-up strategies were tested to facilitate start-up and to ensure stable operation. Among the operating parameters, sludge loading rate was the most critical for proper start-up of the U A S B reactor.  The initial sludge loading rate  during start-up period should not exceed 0.25 g C O D / g V S S . The response of whey digestion to several process parameters was investigated. W i t h out pH-control, over 97% C O D removal was obtained for influent concentrations from 5 to 28.8 g C O D / 1 and H R T of 5 days. However, instability was observed when the influent concentration was increased to 38.1 g C O D / 1 . Gas production from whey is affected by organic loading rate ( O L R ) . A t an O L R less than 4 g C O D / l - d , higher influent strength resulted i n a higher methane production rate. W h e n the O L R was greater than 6, higher strength feed or shorter hydraulic retention time ( H R T ) produced less methane. From the profiles of substrate concentration measured at various levels above the bottom of the reactor, two reaction stages, acidogenesis and methanogenesis  were dis-  tinguished. It was experimentally illustrated that the rate of acidogenesis is much faster than the rate of methanogenesis in a whey anaerobic digestion system.  The accumu-  lation of V F A s in the first stage being faster than its assimilation in the second stage creates a distinct acidogenic phase in the bottom of the reactor. The instability caused  iii  by high influent concentration could be attributed to the accumulation of VFAs beyond the assimilative capacity of the methanogenic stage. A set of empirical models for accumulation and degradation of VFAs was developed using linear regression analysis. The requirement for maintaining this system in a dynamic balance was that the degradation capacity for VFA in the second stage be greater than the accumulation of VFA in the first stage. Based on this idea, the optimal influent concentration was given as between 25 to 30 g COD/1 for system stability. A hypothesis was proposed in this study that a proper amount of sulfate may be applied to moderate the detrimental influence of excess hydrogen on a stressed anaerobic reactor.  The effect of sulfate was tested to study the biochemical mechanism. The  permissible influent COD concentration was increased from 30 g COD/1 to 50 g COD/1 by using sulfate addition. The pH in the reactor was on the average 0.8 units higher and the concentration of butyric acid in the acidogenic phase much lower with added sulfate than without sulfate addition. The significant improvement of process stability and treatment efficiency made by the addition of sulfate clearly illustrated that sulfate acted like a stimulator which helped to maintain conditions favorable to methanogenesis. The mechanism of this stimulation is explained according to thermodynamics and hydrogen regulation which suggested that sulfate is able to promote the /3-oxidation of VFAs by consuming hydrogen. A two-stage inhibition mechanism was proposed to explain the inhibition of high VFA concentrations and the stimulation of sulfate. Higher hydrogen pressure is the cause of preliminary inhibition, resulting in the accumulation of VFAs, which subsequently inhibit the activity and growth of methanogens in the second inhibition stage. The mechanism of inhibition of methanogens from VFAs was interpreted as being caused by the acidification of the internal cytoplasm and destruction of the pH gradient by non-ionized acids based on the theory of bacterial membrane transport. A new control strategy for stabilization iv  of an anaerobic system is recommended. Under the optimal operating conditions based on the results in the first three steps, over 97% reduction of C O D was achieved when the influent C O D was 30 g / l using an H R T of 2 days, an O L R of 16.61 g C O D / l - d and sulfate concentration of 0.2 g/1.  v  Table of Contents  Dedication  ii  ABSTRACT  iii  List of Tables  xi  List of Figures  x  v  List of Abbreviations  xix  Acknowledgement  x x  1  2  INTRODUCTION  1  1.1  DISPOSAL/UTILIZATION OF CHEESE WHEY  1  1.2  ANAEROBIC METHANE FERMENTATION OF WHEY  2  1.3  PROBLEMS ASSOCIATED WITH T H E ANAEROBIC DIGESTION OF CHEESE WHEY  5  1.3.1  Inadequate Buffering Capacity  5  1.3.2  Micronutrient Deficiency  6  LITERATURE REVIEW 2.1  8  DEVELOPMENT OF REACTOR DESIGN TECHNOLOGY/UASB REACTOR  2.2  8  ANAEROBIC TREATMENT OF CHEESE WHEY IN DIFFERENT REACTOR CONFIGURATIONS  13 vi  2.3  2.4  E N V I R O N M E N T A L F A C T O R S IN A N A E R O B I C D I G E S T I O N  14  2.3.1  p H Control in the Anaerobic Process  14  2.3.2  Nutrient Requirement  16  2.3.3  Sulfate Effect  18  M I C R O B I O L O G Y OF A N A E R O B I C DIGESTION  25  2.4.1  Anaerobic Microorganisms  25  2.4.2  Microbial Interaction in Anaerobic Digestion  30  2.4.3  Hydrogen Regulations  36  3  RESEARCH OBJECTIVES  40  4  EXPERIMENTAL METHOD  43  4.1  R E A C T O R SET-UP  43  4.2  FEED SUBSTRATE  45  4.3  SEED SLUDGE  47  4.4  EXPERIMENT DESIGN  48  4.5  REACTOR OPERATION  50  4.6  ANALYSIS  51  5  START-UP A N D E F F E C T S OF PROCESS P A R A M E T E R S  52  5.1  INTRODUCTION  52  5.2  S T U D Y IN S T A R T - U P O F T H E R E A C T O R  53  5.2.1  Difficulties in Start-up  53  5.2.2  Start-up Performance  55  5.2.3  V F A Behavior in Reactor Start-up  66  5.3  STEADY STATE OPERATION  67  5.4  UNSTEADY-STATE PERFORMANCE  70  vii  5.5  6  70  5.5.1  The Effect of Influent Concentration  70  5.5.2  The Effect of Hydraulic Retention T i m e ( H R T )  76  5.5.3  The Effect of Organic Loading Rate ( O L R )  81  5.6  TREATMENT EFFICIENCY  85  5.7  SUMMARY  88  DISTRIBUTIONS O F S L U D G E A N D S U B S T R A T E S  90  6.1  INTRODUCTION  90  6.2  RESULTS  91  6.2.1  Distribution and Behaviour of the Sludge  91  6.2.2  Growth of Sludge  100  6.2.3  Profiles of C O D , V F A and p H  101  6.3  7  GAS PRODUCTION  SUMMARY  112  E F F E C T S OF S U L F A T E O N A N A E R O B I C D I G E S T I O N O F W H E Y 116 7.1  GENERAL REMARKS  116  7.2  HYPOTHESIS  117  7.3  RESULTS IN B A T C H E X P E R I M E N T S  121  7.4  R E S U L T S IN C O N T I N U O U S E X P E R I M E N T S  122  7.4.1  Effect of Sulfate on Reactor Operation: T i m e Profile  122  7.4.2  Effect of Sulfate on Steady State Performance  134  7.4.3  The Improvement of Reactor Stability  139  7.4.4  . The Effect of Sulfate on Buffer Capacity  141  7.4.5  The Improvement of Treatment Efficiency  141  7.4.6  The Effect of Sulfate on Profiles of p H , Sludge and V F A s  141  viii  7.5  M E C H A N I S M OF INHIBITION OF HIGH C O N C E N T R A T I O N OF VFAs AND LOW  P  H  154  7.6  M E C H A N I S M OF STIMULATION B Y SULFATE  158  7.7  SUMMARY  168  8  T R E A T M E N T E F F I C I E N C Y IN O P T I M A L O P E R A T I O N  170  9  CONCLUSIONS, CONTRIBUTIONS AND  174  RECOMMENDATIONS  9.1  CONTRIBUTIONS  AND CONCLUSIONS  9.2  RECOMMENDATIONS FOR FUTURE RESEARCH  174 178  Bibliography  180  Appendices  200  A  EMPIRICAL MODEL  200  A.l  T H E P R O G R A M OF MINITAB  200  A.2  ANALYSIS OF T H E A C C U M U L A T I O N OF ACETIC ACID  201  A.2.1  Determination of the Equation  201  A.2.2  Analysis of the Adequacy of the Equation  203  A.2.3  The Comparison between the Experimental Data and the M o d e l .  210  A. 3  B  S U M M A R Y OF EMPIRICAL MODELS  210  A.3.1  In the Absence of Sulfate  210  A.3.2  In the Presence of Sulfate  219  E F F E C T S OF  S U L F A T E IN B A T C H E X P E R I M E N T S  221  B. l  INTRODUCTION  221  B.2  PRELIMINARY E X P E R I M E N T A L DESIGN  222  B.3  B.4  B.2.1  Variables  222  B.2.2  Experimental Design  224  E X E C U T I O N OF T H E E X P E R I M E N T  225  B.3.1  Substrate  225  B.3.2  Seed Sludge (Bacteria)  225  B.3.3  Reactor Operation  225  B.3.4  Chemical Analyses  226  RESULTS AND DISCUSSION B.4.1  226  Effects of Sulfate (S), Feed Strength (Co) and Seed Sludge Amount (A) on the Methane Production (Cif %) 4  B.4.2  Effects of S, Co and A on pH of the System  B.5  CONCLUSIONS  B. 6  CRITIQUE OF T H E E X P E R I M E N T  2 2 6  234 240  AND F U T U R E P L A N  C T H E C A L C U L A T I O N OF NON-IONIZED ACID  240  243  Cl  THEORY  243  C. 2  C A L C U L A T I O N OF NON-IONIZED ACID  244  D STATISTICAL ANALYSIS OF pH  245  E  250  DATA TABLES  x  List of Tables  2.1  K i n e t i c Characteristics  of Sulfate Reducers and Methanogens  23  2.2  Stoichiometry and Change in Free Energy of Reaction  28  2.3  Methanogenic Substrates and Reactions  31  2.4  Partial Reaction for a Hypothetical Glucose Fermentation W i t h out and W i t h a Methanogen  34  4.1  Characteristics  46  4.2  Experimental Design  49  5.1  Sludge L o a d i n g in Start-up  54  5.2  Experimental Results in Steady State Performance  68  5.3  C O D Balance  71  5.4  Gas P r o d u c t i o n Rate and Composition for Different Influent  of Cheddar Cheese W h e y  Concentrations at 5 days H R T  73  5.5  M e t h a n e Production Rate at Influent of 20.5 g C O D / 1  78  5.6  M e t h a n e Production Rate at Influent of 41.1 g C O D / 1  79  5.7  V F A in the Reactor and Effluent at Different H R T s  82  5.8  Effects of Influent Concentration and H R T on Gas Production Rate for Similar O L R  84  6.1  Distribution of Sludge and Substrates  93  6.2  Relation between Sludge Distribution and Biogas  99  6.3  Sludge in the U A S B Reactor  102  6.4  Acetic A c i d ( A A )  7.1  Free E n e r g y  Changes  114 of Reactions  I n v o l v e d i n M e t a b o l i s m of  Some Organic Matter  120  7.2  E x p e r i m e n t a l Results in Steady State  135  7.3  S l u d g e i n the R e a c t o r  140  7.4  P r o f i l e s of the U A S B R e a c t o r w i t h S u l f a t e A d d i t i o n  150  7.5  C a l c u l a t e d C o n c e n t r a t i o n of N o n - i o n i z e d V F A s  155  8.1  R e s u l t s i n the O p t i m a l O p e r a t i o n  172  8.2  C o m p a r i s o n of A n a e r o b i c T r e a t m e n t  A.l  A c c u m u l a t i o n of A c e t i c A c i d  202  A.2  S t e p w i s e A n a l y s i s f o r A c c u m u l a t i o n of A c e t i c A c i d  203  A.3  S t e p w i s e A n a l y s i s f o r A c c u m u l a t i o n of A c e t i c A c i d  204  A.4  Stepwise A n a l y s i s for A c c u m u l a t i o n of A c e t i c A c i d  205  A.5  Stepwise A n a l y s i s for A c c u m u l a t i o n of A c e t i c A c i d  206  A.6  S t e p w i s e A n a l y s i s f o r A c c u m u l a t i o n of A c e t i c A c i d  207  A.7  S t e p w i s e A n a l y s i s f o r A c c u m u l a t i o n of A c e t i c A c i d  208  A.8  S t e p w i s e A n a l y s i s f o r A c c u m u l a t i o n of A c e t i c A c i d  209  A. 9  R e g r e s s i o n A n a l y s i s f o r D e g r a d a t i o n of A c e t i c A c i d  217  B. l  Independent Variables in B a t c h E x p e r i m e n t  222  B.2  E x p e r i m e n t a l D e s i g n of B a t c h R u n  223  B.3  Experimental Results  227  B.4  Yates Analysis  229  B.5  A N O V A Table  B.6  95% Confidence Interval  .  Processes for Cheese W h e y  173  233 235  xii  B.7  Experimental  Design Based on Steepest Ascent  D.l  C a l c u l a t i o n of Standard Deviations  247  D.2  t-test  248  D. 3  t-test  249  E. l  Sludge G r o w t h  251  E.2  T h e Propionic Acid (PA)  252  E.3  T h e Total Volatile Fatty A c i d ( T V F A )  253  E.4  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  254  E.5  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  255  E.6  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  256  E.7  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  257  E.8  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  258  E.9  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  259  E.10 A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  260  E . l l A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  261  E.12 A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  262  E.13 A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  263  E.1'4 A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  264  E.15 A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  265  E.16 A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  266  E.17 A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  267  E.18 A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  268  E.19 A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  269  E.20 A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  270  E.21 A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  271  xiii  241  E.22  A n a l y s i s for A c c u m u l a t i o n  and Degradation  of V F A  272  E.23  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  273  E.24  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of V F A  274  xiv  L i s t of F i g u r e s  2.1  M e t a b o l i c D i s t i n c t i o n of the M i c r o b i a l P o p u l a t i o n i n A n a e r o b i c Digestion  27  2.2  M e t a b o l i c P a t h w a y Inside A c i d - f o r m i n g B a c t e r i a  33  2.3  Graphical Representation  of the H y d r o g e n - d e p e n d e n t  d y n a m i c F a v o r a b i l i t y of A c e t o g e n i c  Thermo-  Oxidations and Inorgani  c  R e s p i r a t i o n s A s s o c i a t e d w i t h the A n a e r o b i c D e g r a d a t i o n of W a s t e O r ganics  39  4.1  Schematic  D i a g r a m of U A S B S y s t e m  5.1  O r g a n i c L o a d i n g R a t e versus T i m e  57  5.2  I n f l u e n t C O D versus T i m e  58  5.3  E f f l u e n t C O D versus T i m e  59  5.4  C O D R e m o v a l versus T i m e  60  5.5  M e t h a n e P r o d u c t i o n R a t e versus T i m e  61  5.6  B i o g a s C o m p o s i t i o n versus T i m e  62  5.7  Effluent Volatile F a t t y A c i d s versus T i m e  63  5.8  Volatile Suspended Solid ( V S S ) in the Effluent  64  5.9  C o m p a r i s o n of C O D , V F A a n d B i o g a s P r o d u c t i o n  65  5.10 Q u a l i t y of E f f l u e n t as a F u n c t i o n of I n f l u e n t C o n c e n t r a t i o n HRT =  5 days)  44  (at 69  5.11 E f f e c t of Influent C o n c e n t r a t i o n o n M e t h a n e P r o d u c t i o n  74  5.12 E f f e c t of I n f l u e n t C o n c e n t r a t i o n o n B i o g a s C o m p o s i t i o n  75  xv  5.13  Effect of H R T o n M e t h a n e P r o d u c t i o n  8 0  5.14  Effect of H R T o n M e t h a n e C o m p o s i t i o n  8 3  5.15  E f f e c t of O r g a n i c L o a d i n g R a t e o n M e t h a n e P r o d u c t i o n  8 6  5.16  Relation Between  8 7  6.1  P r o f i l e s of S l u d g e at D i f f e r e n t I n f l u e n t C o n c e n t r a t i o n s  9 4  6.2  Sludge D i s t r i b u t i o n in the U A S B  9 6  6.3  Sludge Concentration  6.4  Sludge D i s t r i b i t i o n versus G a s P r o d u c t i o n  6.5  Sludge G r o w t h  1 0 3  6.6  p H Profile  1 0 4  6.7  P r o f i l e of A c e t i c A c i d  1 0 5  6.8  P r o f i l e of P r o p i o n i c A c i d  1 0 6  6.9  P r o f i l e of C O D  1 0 7  6.10  P r o f i l e of C O D R e d u c t i o n  1 0 8  6.11  P r o f i l e s of p H a n d V F A s  1 1 3  6.12  A c c u m u l a t i o n a n d D e g r a d a t i o n of A c e t i c A c i d  1 1 5  7.1  M i c r o b i a l E c o l o g y for t h e A n a e r o b i c D i g e s t i o n P r o c e s s  1 1 9  7.2  C O D Concentration  1 2 3  7.3  O r g a n i c L o a d i n g R a t e versus T i m e  1 2 4  7.4  Effluent C O D versus T i m e  1 2 5  7.5  C O D R e m o v a l versus T i m e  1 2 6  7.6  Effluent Volatile Fatty A c i d Versus T i m e  1 2 7  7.7  Effluent p H versus T i m e  1 2 8  7.8  M e t h a n e P r o d u c t i o n R a t e versus T i m e  1 2 9  7.9  Biogas C o m p o s i t i o n versus T i m e  1 3 0  M e t h a n e P r o d u c t i o n and O L R  Reactor  i n the U A S B R e a c t o r  versus T i m e  xvi  9 7 9 8  7.10 V S S i n the E f f l u e n t versus T i m e 7.11 Effect  of Influent  131  Concentration  on  Methane  Production  and  Composition  136  7.12 Effect of O L R on M e t h a n e P r o d u c t i o n  137  7.13 Effect of Sulfate on p H P r o f i l e s  143  7.14 C o m p a r i s o n of p H w i t h o u t S u l f a t e a n d w i t h S u l f a t e  144  7.15 P r o f i l e of S l u d g e  145  7.16 P r o f i l e of p H  146  7.17 P r o f i l e of A c e t i c A c i d  147  7.18 P r o f i l e of P r o p i o n i c A c i d  148  7.19 P r o f i l e of C O D . .  149  7.20 Effect of Sulfate on the P r o f i l e of A c e t i c A c i d :  (A) W i t h o u t  S,  (B) W i t h S  151  7.21 Effect of Sulfate on t h e P r o f i l e of P r o p i o n i c A c i d :  (A)  Without  S, (B) W i t h S 7.22 Effect  of Sulfate o n B u t y r i c  152 Acid  Concentration  i n the  Acido-  genic P h a s e  153  7.23 Effect of Sulfate o n the A c c u m u l a t i o n ( A ) a n d t h e  Degradation  ( B ) of P r o p i o n i c A c i d  163  7.24 Effect of Sulfate on t h e P e r m i s s i b l e C o n c e n t r a t i o n  Determined  b y A c c u m u l a t i o n a n d the D e g r a d a t i o n o f P r o p i o n i c A c i d  .  (A)  i n the A b s e n c e of S u l f a t e ; ( B ) i n the P r e s e n c e of S u l f a t e 7.25 A c c u m u l a t i o n a n d D e g r a d a t i o n  of A c e t i c A c i d , P r o p i o n i c  16 4 Acid  a n d T o t a l V F A s i n the A b s e n c e of S u l f a t e 7.26 A c c u m u l a t i o n a n d D e g r a d a t i o n  of A c e t i c A c i d , P r o p i o n i c  a n d T o t a l V F A s i n the P r e s e n c e of S u l f a t e xvii  165 Acid 166  7.27  Two-Stage Inhibition M e c h a n i s m  169  A.l  F i t t e d V a l u e s versus the A c t u a l Values  211  A.2  A n a l y s i s of r e s i d u a l s  212  A.3  A n a l y s i s of residuals  213  A.4  A n a l y s i s of r e s i d u a l s  214  A.5  A n a l y s i s of residuals  215  A. 6  C o m p a r i s o n of E x p e r i m e n t a l D a t a w i t h M o d e l  216  B. l  E f f e c t of s u l f a t e o n B i o g a s C o m p o s i t i o n  228  B.2  E f f e c t of S u l f a t e o n t h e B i o g a s C o m p o s i t i o n  231  B.3  I n t e r a c t i o n E f f e c t s of S u l f a t e (S), I n f l u e n t C O D ( C ) , a n d S l u d g e ( A ) : (a) S a n d C , (b) S a n d A , (c) C a n d A  B.4  E f f e c t of S u l f a t e o n p H  B.5  I n t e r a c t i o n E f f e c t s of S u l f a t e (S), I n f l u e n t C O D ( C ) , a n d S l u d g e  232 236  ( A ) : (a) S a n d A , (b) S a n d C , (c) C a n d A  237  B.6  F i t t e d p H versus A c t u a l V a l u e  238  B.7  A n a l y s i s of R e s i d u a l s  239  xvm  L i s t of A b b r e v i a t i o n s  ATP  adenosine triphosphate  ADP  adenosine diphosphate  BOD  biochemical oxygen demand  COD  chemical oxygen demand  HOA  hydrogen oxidizing acetotrophs  HOM  hydrogen oxidizing methanogens  HRT  hydraulic retention time  MPB  methane producing bacteria  NAD  nictinamide adenine dinucleoticide  NHOA  non-hydrogen oxidizing acetotrophs  NRB  nitrogen reducing bacteria  OHPA  obligate hydrogen-producing acetogens  OLR  organic loading rate  Pi  phosphate  pmf  proton motive force  SLR  sludge loading rate  SRB  sulfate reducing bacteria  SRT  solids retention time  TSS  total suspended solid  UASB  upflow anaerobic sludge blanket reactor  VFAs  volatile fatty acids  VSS  volatile suspended solid  xix  Acknowledgement  T h e author would like to express her sincere gratitude and appreciation to her thesis committee members, D r . K . V . L o , D r . K . L . P i n d e r and D r . R . B r a n i o n , for their strong support, special guidance and valuable advice. Thanks should be given to the Universitj' of British Columbia and Canadian people for providing the award of University Graduate Fellowship in the second and third year of P h . D . program, and for their kindness that have made my study and life here possible and easier. T h e Author is also very grateful to many individuals in Department of Chemical and Department of Bio-Resource Engineering for their invaluable assistance and great deal of spiritual support. T h e author would like to thank D r . P . H . L i a o for his technical and laboratory advice, and to Adeline L a u for her assistance in laboratory analyses. Special thanks should be given to my dear husband and loving son, Tingwei Zhou and X i n g Zhou.  Without their sincere undersdanding, loving, moral and spiritual support,  the thesis would never been finished. Finally, the author would like to thank her friends, M s . Kathelly G u n n and M r . Richard Barrow for their caring and sincere friendship.  xx  Chapter 1  INTRODUCTION  1.1  DISPOSAL/UTILIZATION  OF CHEESE  WHEY  Cheese whey is a by-product of cheese production. Each pound of cheese produced results in five to ten pounds of fluid whey. In the U . S . A . , approximately 2 7 x l 0 tonnes of whey 9  are produced each year, while 2 million tonnes of whey are generated annually in Canada. W i t h the increasing cheese demand in N o r t h America, fluid whey production is tending to increase. Cheese whey contains about 5% lactose, 1% protein, 0.3% fat and 0.6% ash (Loehr,1977). The C O D of cheese whey ranges from 60,000 to 70,000 mg C O D / l i t e r , depending on the type of cheese process. Every 1000 gallons per day of raw whey discharged into a sewage treatment plant can impose a load equivalent to that from 1800 people.  Every  1000  gallons of raw whey discharged into a stream requires for its oxidation the dissolved oxygen in over 4,500,000 gallons of unpolluted water.  The high organic content of whey,  the trend towards increasing production of cheese whey and stricter pollution control standards have led to an expensive and difficult waste disposal problem for the cheese manufacturers. Cheese whey represents about 90% of the milk used in the cheese manufacturing process.  A number of solutions have been proposed to recover nutrients and reduce  the pollution level resulting from whey. These rely on converting the whey or various components of it to marketable products. Considering that whey has a high content of  1  Chapter 1.  2  INTRODUCTION  lactose and protein, several investigators have developed new schemes for whey treatment with an emphasis on product recovery and new product development (Castillo et al. 1982; Friend et al. 1982). These efforts include fermentation of whey to ethanol for beverage production (Palmer 1978, 1979) or gasohol production; drying of whey into powder which may be used as animal feed or as a supplement in human foods (Muller, 1979; Modler, 1980); separation of whey components by membrane technology (Teixeira, 1982) or fermentation of whey for protein production. Many of these schemes, however, are limited to larger producers due to economic constraints.  But even so, they don't  completely solve the final waste disposal problem of whey. Further treatment is needed to meet the requirement for waste discharge. Biological waste treatment systems, either aerobic, anaerobic or combinations of them can be used to treat a wide variety of waste streams and are capable of reducing the levels of pollutants to meet even the most stringent requirements.  However, the activated  sludge process, which is one of the most commonly applied methods in waste treatment, is unsuitable for the treatment of very high strength wastes such as whey due to its large energy consumption for aeration, which leads to high operating costs. In contrast, anaerobic systems have much lower operating due to the low yield of cells and low energy consumption (no aeration) and produce methane which can be used as an energy source.  1.2  ANAEROBIC  METHANE  FERMENTATION  OF WHEY  As a process to convert the organic materials contained in biomass into useful energy (methane) and to reduce the emission of pollutants from industrial and agricultural wastes, anaerobic fermentation has already exhibited its potential. The growing realization of the potential of anaerobic treatment is evident from the large number of the  Chapter 1.  INTRODUCTION  3  research reports published on this process each year.  Significant advances have been  made in extending this process for the treatment of a variety of wastes . W i t h regard to cheese whey treatment, these advantages are pronounced because cheese whey constitutes a high strength organic waste. Several studies have shown that anaerobic treatment can achieve an adequate removal of chemical and biological oxygen demand from cheese whey and that the methane production is close to the theoretical yield.  It has been estimated that 1 liter of whey can generate about 45 liters of gas  with a C i / 4 content of around 55%, given that an expected C O D removal efficiency of 80% is achievable. For every liter of whey, 20 liters of C i f equivalent to an energy production of 700 Btu's. are produced every year. This means 1.4 x 10  12  4  can be generated, which is  In C a n a d a , 2 x 10 tonnes of whey 6  Btu's of energy could be obtained by  anaerobic methanogenesis of whey. According to the results of a survey among cheese producers in New York state, up to 46% of the oil and gas needs of a cheese plant could be supplied by methane generated from whey (Switzenbaun, 1982). In spite of its present significance and its optimistic future potential, the anaerobic process has not had a favorable reputation because the conventional process usually suffers from a long start-up period, a slow digestion rate and unstable process performance, all largely due to the low growth rate of the anaerobic bacteria. These drawbacks have prevented the anaerobic process from having wide application. In the last decade, advances i n the microbiology and biochemistry of the anaerobic process, along with the advances in high-rate digestor technology have led to a great improvement in treatment efficiency and process control. One of the major advantages of anaerobic digestion is the relatively low yield of microbial cells (sludge) in comparison with the aerobic process. However, this becomes a disadvantage with respect to its longer period of start-up and its poor capability for tolerating load shock and other drastic changes in environmental conditions. It is now  Chapter 1.  INTRODUCTION  4  well understood that the efficiency of the anaerobic process is strongly dependent on the solid retention time (SRT). SRT requires considerably more attention in anaerobic digestion than in the aerobic process. Most of the new anaerobic reactor designs attempt to maximize S R T , and in turn the concentration of biomass in the reactor to permit a reduction in the required hydraulic retention time ( H R T ) . The anaerobic filter was the first design which allowed the S R T to be independent from H R T . Since then, a series of high-rate digestors haveeen developed. The development of novel high SRT designs for biological reactors has resulted i n many new anaerobic systems which are suitable for the treatment  of concentrated  organic  wastewaters. These new anaerobic digestors include the upflow and downflow anaerobic filter, the fluidized bed reactor,the expanded bed reactor and the sludge blanket reactor. T h e Upflow Anaerobic Sludge Blanket ( U A S B ) reactor is one of these innovative reactor designs (Lettinga et al.1980) . Two distinguishing features of the U A S B reactor are the installation of the 3-phase separator in the upper part of the reactor and the ability to cultivate sludge in granules. These two features permit the maintenance of a high concentration of biomass in the digestor. The U A S B reactor has been widely used to successfully treat a variety of wastewaters (Wang et al. 1985; Lettinga et al. 1985). However, little research has been done on the use of this reactor for treating cheese whey. Few studies on treating acidic substrates, such as monosodium glutamate wastewater and cheese whey, with an U A S B reactor are available so far (Wu and Zhang 1983; Samson et al. 1984). It has been suggested that the development of an anaerobic sludge with high activity and settleability is associated with the proper start-up procedures (Lettinga et al. 1979). Therefore, an assessment pf the technical feasibility of treating cheese whey i n an U A S B reactor, concentrating on the start-up procedures, is necessary.  Chapter 1.  1.3  INTRODUCTION  PROBLEMS OF CHEESE  T h e anaerobic  ASSOCIATED  5  WITH  T H E ANAEROBIC  DIGESTION  WHEY  digestion of cheese whey has been investigated  by using different di-  gestor configurations (Hakansson, 1977; Clanton et al., 1980; Boening and Larsen, 1982; Switzenbaun, 1979; Hickey and Owens, 1981; Sutton and L i , 1981). Treatment efficiency was affected by reactor type, experimental method, pH-control, nutritional supplement and waste strength.  Unlike the other substrates which are usually used as feed for anaer-  obic digestion, the treatment of cheese whey is much more difficult . Unsuccessful experiments have been reported, apparently due to its high organic strength and its tendency towards rapid acidification. A primary obstacle is a lack of fundamental understanding of the process. T h e problems encountered in this process can be attributed to inadequate buffering capacity and micronutrient deficiency. It was reported that stable operation of an anaerobic fermentation reactor with cheese whey could not be maintained unless p H control or additional nutrients (or mixture with manure) were applied.  1.3.1  Inadequate  Buffering Capacity  Examining the effects of medium and inoculum on the treatment of whey and cellulose in an anaerobic fixed-bed reactor, Nordstedt and Thomas (1984) found that the reactor could not achieve stable operation within 30 days without p H control.  Treating full  strength whey in a fixed-film reactor, Marshall and Timbers (1982) reported that addition of N a O H was needed to maintain stability. Dehaast et al. (1983) used dilute whey as feed substrate and neutralized the acids to avoid a rapid p H drop in their experiment.  In the  study conducted by Follmann and Mark! (1979), a pH-static process was used in which the p H value was the control signal for whey feed. When the p H increased beyond 7.0, a  Chapter 1.  INTRODUCTION  6  pump was automatically triggered to add substrate until the p H fell to 6.95. Wildenauer and Winter also used a pH-titrate control unit in their fixed-film system to treat high strength acidic whey. Using an expanded bed reactor Switzenbaum and Danskin (1982) found that when the influent strength was increased from 5 to 20 g C O D / l i t e r , the C O D removal decreased from 83% to 58%. It was suggested that the physiological balance between the methaneproducing organism and the hydrogen- and acid-producing organisms was more easily upset because of the great difference in the rates of acidogenesis and methanogenesis for an easily biodegradable carbon source, such as whey.  It seems that a certain level of  influent concentration represents a kind of inhibition to the system.  1.3.2  Micronutrient Deficiency  In their study of the effects of temperature  on an anaerobic film expanded bed reactor  ( A F E B ) treating cheese whey, Kelly and Switzenbaun (1984) noticed that in the absence of nutrient supplement, the C O D removal efficiency was much lower as compared with Switzenbaun and Danskin's results (1982) for the same loading rate and influent concentration.  It was assumed that the poor removal efficiency was due to nutritional limita-  tions. Some necessary nutrients, that were present in the tap water used by Switzenbaun and Dankin, were absent from the tap water used for dilution by Kelly and Switzenbaun. T h e results of experiments on nutrient requirements indicated that trace nutrients had a significant influence on reactor performance. after the addition of the nutrients.  Operation of the A F E B reactor improved  Gas production increased within 24 hrs.. C O D  removal efficiencies increased from 60.3% for the nutrient-limited experiment to 80% for the nutrient-supplied experiment.  The volatile organic acid ( V F A ) concentration in the  effluent of the nutrient-limited experiment was at least three times higher than the V F A  Chapter 1.  7  INTRODUCTION  concentration of the nutrient-supplied experiment. Based on the theoretical value of the C / N ratio, DeHaast et al.(1983) performed a study in a downflow-fixed film reactor treating deproteinated cheese whey with different C/N-ratios ranging from 7.5 to 73. T h e results indicated that no decrease in efficiency and stability occurred even at the highest C / N ratio.  It is known from the literature  (Henze 1982) that the nutrient requirement is a function of organic loading rate ( O L R ) . Since the O L R used by Haast and his co-workers was only 2.6 g C O D / l i t e r day, their conclusions could not be regarded as being universal. Treating both whole and diluted cheese whey in an anaerobic rotating biological contact reactor, L o and Liao(1986) noticed that the system could not be maintained at steady-state when the H R T was decreased  below 5 days.  However, a significant im-  provement in efficiency and stability was obtained by using a mixture of cheese whey and screened dairy manure instead of cheese whey alone as the feed substrate (Lo and Liao 1987). In this case, the reactor could be operated successfully at a H R T of only 2 days without the addition of buffering and nutritional reagents. This study showed that something which existed in the manure was necessary for maintaining the stability of the system. T h e question remains as to what nutrients contained in manure help to restore the system and maintain it's stability.  Chapter 2  LITERATURE  2.1  REVIEW  D E V E L O P M E N T O FR E A C T O R DESIGN T E C H N O L O G Y / U A S B R E ACTOR  In traditional anaerobic sludge treatment the solid retention time (SRT) and the hydraulic retention time ( H R T ) were almost identical. More recent studies have denned S R T as the crucial design and operational parameter because of the very low growth rate of anaerobic microbes.  Proper S R T control provides sufficient acclimation time to allow efficient  treatment. Young and McCarty (1969) were among the first to recognize this " S R T effect" when they introduced the concept of the anaerobic filter, in which the ratio of S R T and H R T could be increased to 100 (Henze 1982). T h e independence of S R T from H R T has proven to be a turning point in the study of the anaerobic process and has made anaerobic wastewater treatment economically interesting as compared to the aerobic process. Since then, the development of the anaerobic process has focused on the maintenance and accumulation of a high concentration of biomass in the reactor.  A variety of high-rate  reactors has been developed (Callander 1983). These high-rate, anaerobic reactors differ in the way in which biomass is retained. They can be broadly divided into two systems: attached growth system and suspended growth systems (Stronach  1986).  T h e former  includes upflow and downflow fixed-film reactors, expanded bed reactors and fluidized bed reactors, in which a high S R T is achieved by retaining the biomass as a film on the inert support media, packing material in a fixed-film reactor or particle material in  8  Chapter 2.  LITERATURE  REVIEW  9  fiuidized bed reactor. T h e latter is called an Upflow Anaerobic Sludge Blanket ( U A S B ) reactor in which high biomass levels are accumulated and retained in the digestor by means of an interior gas-liquid-solid separator  that relies for its effectiveness  on the  design of the separator as well as on sludge settleability. T h e U A S B reactor, which was initially developed by Lettinga and his co-workers, has already been recognized as one of the most promising methods for anaerobic treatment of organic waste (Lettinga et al 1984). Instead of using a packing material to support and concentrate biological growth, the upflow sludge blanket operates as a suspended growth system.  T w o distinguishing features of the U A S B reactor permit it to maintain a high  concentration of biomass. These two features are a 3-phase separator and the quality of the cultivated granular sludge. T h e gas-liquid-solid separator (Lettinga et al 1980; V a n der Meer 1982) is mounted in the upper part of the reactor. This arrangement has the following advantages:  • T h e bottom plates of the settler can serve as gas separator. • No additional space is required. • T h e sludge separated in the settler can flow directly back into the reactor without any mechanical means, such as a pump or scrapers, being required. • T h e sludge is not exposed to "strange" conditions, it remains within the system.  In order to enhance the return of the sludge from the settler, the following conditions have to be fulfilled:  • Gas bubbles must be separated before the mixture of water and sludge enters the settling compartment.  Chapter 2.  LITERATURE  REVIEW  10  • To avoid gas production in the settling compartment,  the retention time of the  sludge in the settler must be short. • The inclined wall of the settler should be at an angle of approximately 5 0 ° . • The surface load on the settler should be kept below about 2 to 2.5 m / h r . • The sludge present at the liquid-gas interface in the gas collector should be kept well immersed.  The key to successful operation of the U A S B system is that the hydraulic loading rate and upflow velocities of fluid must not exceed the sludge particle settling rate. The second principal feature of the U A S B reactor is its ability to cultivate granular sludge with good settleability and high activity. T h e development of this granular sludge, in terms of both specific activity and settleability in the U A S B reactor, is associated with the composition of the wastewater, initial seeding and environmental conditions, including a temperature of 30 to 3 5 ° C and a p H of 6.5 to 7.2 (Wu 1985). Calcium ions play a positive effect on the flocculating ability of sludge, presumably due to the improvement of the mechanical strength of the floes (Lettinga 1980a; Hulshoff 1982  ).  It has been found, using yeast, sugar beet or potato waste as substrates, that granulation of sludge proceeded satisfactorily,  whereas problems arose with distillery, corn  starch and rendering wastes (Hulsoft pol et.al,1983).  Granule characteristics may be  detrimentally affected by significant amounts of suspended solid in the influent. T h e properties of the initial seed have an effect on sludge aggregation.  Lettinga et  al. (1985) suggested that thicker types of digested sewage sludge (approximately  60 kg  T S / m ) are preferred because the thicker sludge has better settleability, although it is 3  Chapter 2. LITERATURE  REVIEW  11  generally lower in specific methanogenic activity than thinner types of digested sewage sludge (i.e. 40 kg TS/m ). 3  The microorganisms themselves could function as a filtering medium (Lettinga 1981; Frostell 1981). To facilitate the filtration, the feed inlet system should introduce the influent wastewater homogeneously by using a distributor at the base of the reactor column. One of the most serious limitations of the UASB process is the considerable time (4-8 weeks or longer) for start-up. The washout of sludge during the initial phases of operation is significant. It has been noticed that the development of a sludge with high specific activity and settleability could be highly dependent on the start-up procedure. Both sludge loading rate and hydraulic loading rate are the most important factors which affect the properties of anaerobic sludge (Wu 1985). Considerable attention has already been paid to the start up procedure (De Zeeuw 1985; Hulshoff et al 1983, 1984; De Zeeuw and Lettinga 1980; Lettinga 1979, 1985; Dubourguier et al 1983; Ross 1983). It was indicated that the initial sludge loading should not exceed 0.2-0.4 kg COD/kg VSS day until the volatile fatty acids were well removed. Sludge granules formed rapidly only at loading rates in excess of 0.6 kg COD/kg VSS day (Lettinga et al. 1979). In the UASB system, agitation is provided by both hydraulic upflow and rising gas bubbles. A proper upflow velocity and the agitation due to rising gas bubbles are necessary for sludge aggregation.  Higher hydraulic loading rates, ranging between 0.25-  0.4m /m hr, are favorable to the granulation of sludge because at these higher loading 3  2  rates light floe sludge will move upward and be discharged from the reactor, whereas heavy granular sludge will move downward and grow quickly. The ability of the 3-phase separator to maintain a high concentration of biomass in the reactor makes the UASB reactor capable of attaining high rates of methane production, high rates of conversion for dilute and mostly soluble wastes, and of accepting organic and  Chapter 2.  LITERATURE  12  REVIEW  hydraulic shock loads and temperature fluctuations. Since there is no need for a recycle pump, mechanical mixer, nor support media, the U A S B reactor is simple in construction and operation, has low energy consumption and is cheap to run and to maintain. In order to mathematically describe and optimize the U A S B process, various kinetic and dynamic models have been proposed , which include the fluid-flow pattern  , the  kinetics of substrate conversion and bacterial growth and the sludge distribution and behavior (Bolle et al 1986a, 1986b; Buijs et al 1980, 1978,  1982;  Heertjes and Ven der Meer  1982,). A model based on a mass balance for the sludge in the blanket has been  developed and experimentally checked for the physical behavior of the sludge in the blanket.  Also, using stimulus response experiments with a L i  the fluid flow in a U A S B reactor were studied (Heertjes  +  tracer, the dynamics of  1978). From the model, three  distinct parts of the sludge could be distinguished. Both sludge bed and blanket can be described as perfectly mixed tank reactors with short-circuiting flows; the settler volume acts like a plug-flow region.  Bolle and his co-workers proposed a dynamic model of a  continuous working U A S B reactor which included the integration of the fluid flow pattern in the reactor, the kinetic behavior of the bacteria and the mass transport  phenomena  between different compartments and different phases. T h e mathematic equations are able to predict the various observable, nonobservable or difficult to observe state variables and were prepared for computation and simulation T h e wastewaters that have been treated include: sugar beet, potato starch, maize starch, alcohol, yeast, brewery, slaughter house, dairy, paper mill, distiller's grain supernatant, synthetic fatty acid, sewage and bean production wastes Although the application of the U A S B reactor to the treatment of industrial wastewater has been widely reported (Lettinga et al 1985;  Wang et al 1985), few studies on  treating acidic substrates so far are available. Using an U A S B reactor in the anaerobic treatment of monosodium glutamate wastewater with a p H of 2.0 and a chemical oxygen  Chapter 2. LITERATURE  REVIEW  13  demand (COD) concentration of 3 to 4.5 g/liter, Wu and Zhang (1983) reported a rapid decrease in pH in the reactor resulting in instability and a complete loss of bacterial activity.  Lettinga(1979) suggested that improper procedures used in a UASB start-  up period could lead to the development of sludge with low specific activity and poor settleability. Treating cheese factory effluent with an average strength of 2 g COD/liter, Samson et al (1984) found that the granular sludge in the UASB reactor tended to float, and a large amount of sludge was washed out. It might have occurred in the acidic environment because a massive growth of filamentous bacteria created a bulky sludge with poor settleability.  2.2  ANAEROBIC REACTOR  TREATMENT  OF CHEESE  WHEY  IN DIFFERENT  CONFIGURATIONS  The anaerobic digestion of cheese whey using different reactor configurations has been reported. These reports show that anaerobic treatment can achieve significant removal of chemical oxygen demand (COD) from whey. It is evident that treatment efficiency is affected by reactor type, waste strength and the experimental method used. Without the addition of nutrients and pH-control, a fixed-film reactor was able to treat higher strength substrates and had higher COD removal efficiency than a fluidized bed. However, a longer HRT was needed in the fixed-film reactor than in the fluidized bed. It was reported by several authors that at least 5 days of HRT were needed in the fixed-film reactor system (Hakansson 1977; Claton et al 1980; Boening and Larsen 1982; Switzenbaun 1979; Hickey and Owens 1981; Sutton and Li 1981); whereas the fluidized bed reactor could be operated at much shorter HRTs. In a study of the anaerobic digestion of high strength, acidic whey using a pH-controlled, up-fiow fixed-film loop reactor, Wildenauer and Winter  Chapter 2. LITERATURE  14  REVIEW  (1985) noticed that re-circulation of the reactor liquid helped to significantly improve the process efficiency. They suggested that the circulation of liquid was essential for fast gas expulsion. In addition, according to Monteith's studies (1981), liquid circulation could improve the mixing behavior of the reactor contents, in turn, reducing any dead volume and facilitating the contact between substrate and biomass . Furthermore, liquid circulation could minimize pH gradients along the reactor column and maintain a good pH environment for methane producing bacteria. These considerations help to explain why fluidized bed and expanded bed reactors are able to be operated at much lower HRT. Therefore, liquid circulation would be recommended to improve process operation in a stationary system.  2.3  ENVIRONMENTAL  2.3.1  FACTORS IN ANAEROBIC  DIGESTION  p H C o n t r o l i n the A n a e r o b i c Process  The successful control of the anaerobic treatment process depends upon a knowledge of the various environmental factors which affect the microorganisms responsible for waste degradation. Of the various control factors, pH is one of the most important. Under anaerobic conditions, pH is controlled by the interaction of the carbonic acid system and a net strong base, the latter being the net result of the activities of the VFAs, ammonia and any other strong acids and bases present. This control depends on the maintenance of an adequate bicarbonate buffer system to counteract any acidity due to the carbon dioxide and organic acids produced during the anaerobic treatment. Alkalinity is a measure of the buffering capacity of the digestor contents. It consists of bicarbonate, carbonate, ammonia and hydroxide components. VFA, hydrosulphuric and orthophosphoric acids should also be considered. McCarty (1964) indicated that a  Chapter 2. LITERATURE  REVIEW  15  bicarbonate alkalinity in the range of 2.5 to 5.0 g C a C O a / l i t e r (25 to 50 m M ) provided a safe buffering capacity for anaerobic treatment of waste. Hydrosulphuric and orthophosphoric acid systems under anaerobic conditions were reported to provide very limited buffering capacity as they existed in extremely low concentrations.  T h e dissociation con-  stants of acetic and propionic acids allow them to be considered as weak acids (Capri and Marnis,1975; Stronach et al. 1986). Between p H values of 6.0-7.7, the buffering function of ammonia and the V F A s could be negligible. In an anaerobic system with a substrate which has a rapid acidification rate, the accumulation of intermediate fatty acid products might reach a concentration that exceeds the system's buffering capacity (Mah 1969; Chynoweth and M a h 1977).  Cheese  whey is a substrate in which a majority of its contents are easily acidified. A n instability in the p H of an anaerobic system of cheese whey was often observed. V F A concentrations  Although high  with low p H values are particularly detrimental to methanogenic  activity through the toxic action of the unionized V F A (Andrews et al 1971; Kroeker 1979), a high cation concentration caused by neutralizing agents, added to restore the p H , may also inhibit methanogenic activity (McCarty 1964; Kugelman 1971). Therefore, neutralization by base addition is not the best way to control p H . Recent studies, based on thermodynamic considerations and the hydrogen regulation function, have suggested that the accumulation of intermediate organic acids, during periods of overloading or other process stress is, due to hydrogen sensitivities moderated by syntrophic associations between hydrogen-producing bacteria (acidogens) and hydrogen consuming bacteria (methanogens, sulfate reducing bacteria or S R B and nitrate reducing bacteria or N R B ) . Propionate, lactate and ethanol are produced when the accumulation of hydrogen is beyond the collective assimilative capacity of these hydrogenotrophs including methanogens, S R B and N R B . Since methanogens cannot use those end products directly as substrate, their accumulation leads to a depression in p H .  Chapter 2. LITERATURE  REVIEW  16  Considering that the group of acid and methane forming bacteria each display different requirements with respect to both environmental factors and nutrients for optimal growth, the concept of phase separation was proposed (Babbitt and Baumann 1958; Andrews and Pearson 1965; Pohland and Ghosh 1971; Fan et al. 1973). However, it should be realized that an one-phase anaerobic process can not be regarded simply as the sum of the acidogenic and the methanogenic phases of the two-phase process (Cohen 1980) because of the role of interspecies hydrogen transfer which is an important interaction that occurs between non-methanogens and methanogens in an anaerobic environment (Wolin 1974; Ianotti et al 1973; Hungate 1967; Scheifinger et al 1975; Mah et al 1977; Zeikus 1977; Patel and Roth 1978; Winfrey et al 1977). It might be argued that the physical separation of methanogens and acidogens (two-phase system) can not enhance the anaerobic byconversion rate for some wastes since the necessary interspecies hydrogen transfer function is disturbed  2.3.2  Nutrient Requirement  The anaerobic process is dependent on bacteria which require certain nutrients for growth. In addition to the fundamental requirements for macronutrients such as carbon and nitrogen, the inability of a great number of anaerobes to synthesise some essential vitamins or amino acids necessitates their supplementation with such micronutrients for growth and activity. Since municipal waste sludge normally contains a variety of these nutrients, it usually can provide an ideal environment for growth. However, industrial wastes are frequently more specific in composition, micronutrients must be added to optimize the process.  Chapter 2.  LITERATURE  REVIEW  17  Our lack of knowledge of the nutritional requirements of the methanogens has hindered the development of the anaerobic process.  One of the earliest studies of the nu-  tritional needs of the anaerobic process was conducted by Speece and M c C a r t y (1964). Since then, attention to nutritional requirements has been paid by only few researchers. Such research has indicated that the microbial regeneration time is a function of the nutrients present.  The rate of substrate metabolism may also be limited by nutrient  limitations. Specific substrate utilization rates can be increased several fold when all the required nutrients are in excess (Speece 1985). Generally, nitrogen is the major nutrient, other than an energy source, for microbial systems. Speece and McCarty (1964) determined that the nitrogen requirements for the anaerobic digestion of fatty acids, carbohydrates and protein obeyed the following growth equations:  for Glucose and Starch  0.088M  (2.1)  A = 0.054F -  0.03M  (2.2)  A = 0.076F -  0.014M  (2.3)  A = 0.46F for Amino and Fatty Acids  for Nutrient Broth  Where A=substrate  synthesized into biomass  F=substrate metabolized by biomass  Chapter 2. LITERATURE  REVIEW  18  M=mass of biomass in system  The nitrogen requirements for all substrates were equal to A/9.4.  It was noted that microbial synthesis and, thus the nitrogen requirement, for carbohydrate digestion is about six times greater than for proteins and fatty acids (Speece 1985). This has a significant impact on some nitrogen-deficient biomass feedstocks. Therefore, anaerobic conversion of high carbohydrate content feedstocks to methane gas deserves special consideration because of the relatively high ratio of microbial synthesis to substrate consumption. Speece (1964) also found that two stages exist in the anaerobic digestion of complex substrates, one in which the BOD remains constant and another in which the BOD is reduced due to production of methane. In the case of carbohydrates the major nutrient requirements and major biological solids accumulation result from the first or constant BOD stage of digestion.  2.3.3  Sulfate Effect  Among the nutrient studies, the function of sulfate has received much less attention than other nutritional compounds. Therefore, the sulfur requirement for methanogens has not been extensively documented. However, many industrial wastes contain sulfate, and the role of sulfate and the sulfate-reducing bacteria (SRB) in anaerobic digestion cannot be underestimated. Species of the genera Desulfovibrio and Desulfotomaculum are routinely isolated from digestors. The reason why this family of organisms must be considered in anaerobic digestion processes is shown by the examination of the similarity and complementary and competitive relationship between them and the other native groups of microorganisms, i.e.,  Chapter 2. LITERATURE  REVIEW  19  mainly acetogens and methanogens. It is known that methanogenesis and sulfate reduction are the two main terminal processes in the complete anaerobic mineralization of organic matter.  As all of the  methane-producing bacteria (MPB) are known to be able to couple the oxidation of molecular H2 with the reduction of its electron acceptor CO2 to yield the electron sink product CH , all of the SBR are capable of coupling the oxidation of molecular H 4  2  with the reduction of its electron acceptor SO^ to yield the electron sink product H S. 2  The electron donor in either of these cases may be supplied as a dissolved gas from an exogenous source or through a syntrophic association with an obligate proton reducing or hydrogen-producing acetogen (OHPA). Certain VFAs are metabolized by the SRB to acetate, CO2, and H in the presence of a methanogen, thus switching roles in mutualistic 2  pairing. This type of intimate association or mutualism, is an example of interspecies hydrogen transport and plays an important role in this fermentation (Postgate 1984). In anaerobic digestion, sulfate reduction is usually considered undesirable not only because of the very toxic and corrosive gas, H S, produced from the reduction of sulfate, 2  (therefore creating a problem with regarded its removal from the biogas) but also because of the inhibition of methanogenesis. This inhibition has been explained in terms of the level of sulfide produced and the resultant cytotoxicity. Very recently this inhibition has been subjected to reaction rate kinetics and thermodynamic analysis. Kristjanson (1982) found that methane formation is generally absent in marine sediments when the sulfate concentration is high. He.attributed the apparent inhibition of methane formation by sulfate to a variety of factors including hydrogen sulfide inhibition (Cappenberg, 1974), kinetic competition for substrate (Abram and Nedwell 1978 a,b; Bryant et al.1977; Mountfort 1980; Winfry and Zeikus 1977), and thermodynamic considerations (Zehnder 1978).  Chapter 2.  LITERATURE  REVIEW  20  O n theoretical grounds, the higher free energy change associated with sulfate reduction to H2S as compared to CO2 reduction to CH  4  cannot in principle explain the  inhibition of sulfide to methanogenesis (McCarty 1972; Thauer et al. 1977). energy change of sulfate reduction to H S 2  of CO2 reduction to CH^ with i f  2  T h e free  with H2 is 151 K J / m o l sulfate whereas that  is only 135 K J / m o l carbon dioxide. Therefore, the  most likely mechanism is probably competition for substrates. Inhibition caused by the activity of sulfate reducers has been attributed to competition for the common substrates, since in the presence of excess substrates both processes can take place (Mountfort et al. 1980; Oremland and Taylor 1978; Winfrey and Zeikus 1977). T h e competition between sulfate reducers and methanogens in sediments or mixed cultures for H2 and acetate has been investigated by several workers.  Qualitatively,  their data indicate that sulfate reducers effectively compete with methanogens for both substrates.  The fact that the addition of sulfate inhibits methanogenesis in anaerobic  digestion can be attributed to the finding that the coupled sulfate reducing reactions are thermodynamically more favorable than are the methanogenic reactions. Sulfate reducers have demonstrated a higher affinity for hydrogen than methanogens in marine sediments (Ormaland et al. 1978 and 1982, Martens et al.1974, A b r a m et al. 1978a, 1978b, Sorensen et al. 1981), freshwater sediments (Winfrey et al.1977, Strayer et al. 1978, Cappenberg 1974  and 1975)  1982).  and in pure or mixed culture with methanogens (Kristjiansson et al.  Schonheit et al.(1982) has shown that in the case of H  2  the Ks (affinity con-  stant) value of a typical sulfate reducer was found to be about 5-fold lower than that of a methanogen isolated from a similar habitat.  They also reported that the appar-  ent K s value of D.postgatei for acetate is lower than that of M . barkeri by a factor of 15.  T h e explanation for the sulfate-reducing bacteria in general having a lower Ks for  acetate than the methanogens might be the different mechanisms of acetate utilization. D.postgatei oxidizes acetate via the citric acid cycle (Thauer 1982) and Methanosarcina  Chapter 2.  LITERATURE  21  REVIEW  cleaves acetate by a still unknown mechanism (Zehnder and Brock 1979). straightforward explanation as to why S R B has a lower Ks for H  2  ent topology of the common hydrogenase enzyme system.  T h e most  might be the differ-  T h e hydrogenase reaction is  a specific control mechanism in strict and facultative anaerobes which governs the flow of electrons.  In the M P B , hydrogenase is free in the cytoplasm, while in the S R B it is  located within the periplasmic space (Kristjiansson et.  al 1983,  Stronach et al 1986).  Such a location presents less of an osmotic barrier. Another possibility is that thermodynamics indirectly puts a constraint on the kinetic parameters of the biological reactions involved. As mentioned previously, the free energy change of sulfate reduction is higher than that of C0  reduction. The Haldane equation (Fresht 1977) predicts that the Ks of  2  an enzyme is partly determined by the free energy change associated with the particular reaction. Their experimental results show that CH  A  production and sulfate reduction are  not mutually exclusive and in the presence of excess H When the H  2  2  they have no effect on each other.  supply becomes rate limiting, however, competition does take place. T h e  methanogenic bacteria are not inhibited by the activity of the sulfate reducing bacteria but have a lower affinity for the common substrate which results in suppression. In other words, the difference in substrate affinities accounts for the inhibition of methanogenesis from H  2  and C0  2  in sulfate rich environments where the H  2  concentration is well below  5 M. Complete conversion of organic waste is possible by S R B even with total methanogenic inhibition (Stephen, 1986). A comparison of the kinetics of hydrogen and acetate uptake by M P B and S R B (Table 2-1) suggests that higher organic waste conversion rates may be available through sulfate reduction than through methanogenesis. are not limited to one or two-carbon substrates,  as are methanogens.  Moreover, S R B T h i s approach  therefore may hold possibilities for reducing propionic acid and hydrogen in a stressed reactor, in order to reestablish equilibrium with the hydrogen removal system. However,  Chapter 2. LITERATURE  22  REVIEW  such an approach has major disadvantages, including the loss of energy available from methane and the production of sulfide. Limited references in recent literature do reveal that the sulfur requirement is part of a complex picture. Observations have shown that a special relationship exists between the H  2  utilizing methanogens and the sulfate reducing bacteria.  It has been suggested that  the sulfate reducing bacteria might help to maintain the anaerobic conditions required for the growth of methanogens (Stephen 1985). In addition, the methanogens are dependent on the production of sulfide for growth. Ronnow and Gunnersson (1981) reported that a thermophilic methanogenic terium has a specific sulfide requirement for methane production and growth.  bac-  Scherer  and Sahm (1981) stated that optimal growth of M . barkeri occurred on a defined medium containing methanol when 2.5 to 4.0 m M sodium sulfide was added. T h e y also reported that iron sulfide, zinc sulfide or L-methionine could also act as sulfur sources.  How-  ever, the addition of sodium sulfide to a sulfide depleted media failed to restore growth. Mountfort and Asher (1979) found that a part of the sulfide requirement for growth is used as a precursor of H S - C o M which is 40% sulfide by weight.  According to Ronnow  and Gunnarsson's studies, 2.6% of the cell mass of M . thermoautotrophicum is sulfur. A t sulfide levels below 0.1 m M , growth of M . thermoautotrophicum was poor and the methane production rate decreased. After injection of sulfide, a large increase in methane production was noted within 30 minutes. They noticed a linear relation between growth, methane production and sulfide concentration.  They also noted that sulfate or thiosulfate  could not replace the sulfide requirement. In subsequent work Ronnow and Gunnarsson (1982) noted that when sulfide was added in increments  of 20 mg/1, the methane production rate increased until sulfide  was completely depleted in the medium (as determined by sulfide analysis) and that the methane production rate then decreased. This observation provides further indication of a  Chapter 2.  LITERATURE  23  REVIEW  Table 2.1: K i n e t i c C h a r a c t e r i s t i c s o f S u l f a t e R e d u c e r s a n d M e t h a n o g e n s  Reference  Culture  Substrate  J  max (day ) 1  Y  Ks  (mg C O D / l ) ( g V S S / g C O D )  methane phase  acetate  0.49  4200  methane phase  acidified glucose  0.43  395  Methanosarcina barken  acetate  0.60  320  0.04  acetate  0.11  30  0.03  Huser  Methanothrix soehngenii Methanothrix soehngenii  acetate  0.16  45  0.02  Hungate  Rumen bacteria  H /C0  2  5.4  2*10-  Shea  digesting sludge  H /C0  2  1.1  0.75atm  Badziong  Desulfovibrio vulgaris  H /S0 =  3.6  0.09  Badziong  Desulfovibrio vulgaris  H /S0 =  5.0  0.15  Lake sediment  H /S0 =  Middleton  digester sludge  acetate/S0  4  Liu  Desulfovibrio vulgaris  lactate/S0  4  Schonheit  Desulfovibrio postgatei  acetate/SO^  Liu  Desulfovibrio oreintis  lactate/S0  Ghosh Massey  Smith Zhender  Lovley  2  2  2  2  2  4  4  4  O.OOlatm  4  4  =  8.3  0.05  0.12  =  =  13  0.04  Chapter 2. LITERATURE  REVIEW  24  sulfur compound requirement for high-rate methane formation rates. They further stated that although methanogenic bacteria contain large amounts of coenzyme M , between 0.3 to 16 fimole/g dry weight (Balch and Wolfe 1979), coenzyme M cannot account for a large part of the sulfur absorbed.  A large pool of sulfur compounds, possibly low molecular  weight compounds, still remains to be discovered.  Methionine and cysteine obviously  account for a large part of the sulfur. Zehnder (1980) noted the effects of various sulfide concentrations on the growth and specific methane production rate of M . arboriphilus at p H 7.0. Optimal growth and specific rate of methane production required the presence of between 10~ and 1 0 " M sulfide. A sulfur source of about 0.85 m M was found to be 6  3  essential for degradation of cellulose to methane (Khan and Trottier 1978). A t 9 m M , all inorganic sulfur compounds other than sulfate inhibited both cellulose degradation and methane formation. T h e inhibition increased in the following order: thiosulfate <C sulfite <C sulfide <C H . Sulfide was found to act as a sulfur source rather than a reducing agent 2  (Wellinger and Wuhrman 1977).  T h e optimum sulfide concentration  was found to be  1 0 ~ M , which coincides with the sulfide concentration in the rumen. In the absence of 4  sulfide, cysteine was the only compound which stimulated methanogenesis.According to Speece's  results,  the total sulfide requirement  for optimum anaerobic digestion is  essentially equivalent to the nitrogen requirement if a C S T R is used. Besides the nutritional effect, other beneficial effects of sulfate on anaerobic digestion include the prevention of the biotoxicity of heavy metals through precipitation.  Also,  there is a report in the literature that sulfate promotes the biodegradation of the normally recalcitrant  celluloses (Khan A . W . and Trottier 1978) through a shift in interspecies  hydrogen transport. It should be mentioned that the stimulation effect of sulfate on methanogenesis has not been studied. Since anaerobic (3 oxidation of long chain fatty acids is considered to be the rate-limiting step for the fermentation of soluble substrates,  there are reasons to  Chapter 2.  LITERATURE  REVIEW  25  suggest that the rate of this digestion can be enhanced through interspecies hydrogen transport caused by the presence of sulfate at a concentration below that which may be inhibitory to methanogenesis Finally, an interesting new technology has been developed that will permit an anaerobic digestor to be able to process higher sulfate wastes effectively while simultaneously enriching the off-gases in methane by passing them through a secondary, smaller anaerobic photobioreactor (Cork et al. 1982, Cork 1985, Maka and Cork 1988). In this process, driven by light photons, CO2 is converted to biomass, H S 2  is oxidized to economically  valuable elemental sulfur, and CH4 is free to pass through.  2.4  MICROBIOLOGY  2.4.1  OF ANAEROBIC  DIGESTION  Anaerobic Microorganisms  The anaerobic biological conversion of organic wastes to methane is a complex process involving directly and indirectly a number of microbial populations linked by their individual substrates and product specificities. Nine recognizable steps, each mediated by a specific group of microorganisms, can be identified (Stephen et al.1986). In general, four steps are considered to be essential (Figure 2.1).  T h e y are hydrolysis of carbohydrates,  proteins and fat, fermentation of sugar and amino acids, /3-oxidation of intermediate and long chain fatty acids, and methane formation from acetate CO2 and H . 2  For soluble  substrates the first step can be neglected. The bacteria which are responsible for the fermentation of pyruvic acid to a mixture of acetic, propionic and butyric acids are the acid forming bacteria. They are fast-growing bacteria (minimum doubling time .is around 30 mins) (Mosey 1983). The reactions involved in this step are:  26  Chapter 2. LITERATURE REVIEW  CH COCOOH  + H 0 = CH COOH  CH COCOOH  + 2H 0 = CH CH COOH  3  3  6CH COCOOH 3  2  + C0  3  2  3  + H  2  + C0  2  3  2  (2.5)  2  + AH 0 = ACH CH CH COOH 2  (2.4)  2  + 2C0  2  2  (2.6)  T h e preferable reaction is the first one, the conversion of pyruvate to acetic acid. T h e other reactions,  the fermentation of butyric and propionic acid are carried out by the  bacteria response for the accumulations of hydrogen during surge loads. T h e obligate hydrogen-producing acetogenic bacteria ( O H P A ) are those that convert propionic and butyric acids into acetate according to the equations:  CH CH COOH 3  2  + 2H 0 = CH COOH  CH CH CH COOH 3  2  3  2  3  + C0  + 2H 0 = 2CH COOH 2  3  2  + H  2  (2.7)  + 2H  2  (2.8)  These bacteria grow relatively slowly, even under optimum conditions of low concentration of dissolved hydrogen, with a minimum doubling time of from 1.5-4.0 days. Table 2.2 shows that these reactions are energetically very difficult and can easily be stopped by the accumulation of hydrogen. They can catabolize those substrates into acetate only when the hydrogen pressure is at an extremely  low level.  In other words, when they  are placed in syntrophic association with i7 -utilizing organisms, such as methanogens 2  and desulfovibrio, the reactions become energetically favorable enough to proceed (Table 2.2).  Chapter 2.  LITERATURE  REVIEW  C O M P L E X  27  O R G A N I C  /  M A T T E R  A  C A R B O H Y D R A T E  P R O T E I N  L I P I D  LONG-CHAIN F A T T Y  A M I N O A C I D S  A C I D S  (1) H Y D R O L Y T I C  O R G A N I C  A C I D S  &  N E U T R A L  BACTERIA  C O M P O U N D S  (2) REPRODUCING  A C E T A T E F O R M A T E M E T H A N O L  ACETOGENIC BACTERIA  M E T H Y L A M I N E  H ,C0 2  2  (3) HOMO ACETOGENIC BACTERIA, A C E T A T E  I  (4) METHANOGENIC BACTERIA  C H  Figure 2.1: Digestion  4  -f C 0  2  Metabolic Distinction of the Microbial Population in Anaerobic  Chapter 2. LITERATURE  REVIEW  28  Table 2.2: S t o i c h i o m e t r y a n d C h a n g e i n F r e e E n e r g y o f R e a c t i o n  A G°(Kcal)  REACTIONS A . Single culture of H -producing acetogenic bacteria : 2  C H C H C O O - + 3 H 0 —-> C H C O O ' + HCO3- + H + + 3 H 3  2  2  3  C H C H C H C O O - + 2 H 0 —-> 2CH3COO- + H + + 2 H 3  2  2  2  +11.5  2  2CH3CHOHCOO' + 4 H 0 —> 2CH3COO- +2HCO3- +2H++4H 2  C H C H O H + H 0— > CH COO" + H+ + 2H 3  2  2  3  +18.2  2  2  -1.9 +2.3  2  B . H2-utilizing methanogens and desulfovibrios : 4H  2  +HCO3- + H + -~-> 2 C H + 3 H 0 4  -32.4  2  C . Syntrophic association of coculture ( A + B ) : 4CH CH COO-+3H 0 —>4CH C00-+HC0 -+H +3CH 3  2  2  3  +  3  2CH CH CH COO-+HC0 +H 0—>4CH C00-+CH +H+ 3  2  2  3  2  3  4  2CH CHOHCOO-+H 0—>2CH C00-+HC0 -+H +CH 3  2  3  3  +  2CH CH OH+HC0 -—>2CH COO-+CH +H 0+H+ 3  2  3  3  4  2  4  4  -24.4 -9.4 -34.3 -27.3  Chapter 2. LITERATURE REVIEW  29  There is another group of bacteria, the homoacetogenic bacteria, which can ferment a very wide spectrum of multi or one carbon compounds (e.g. sugars, acids, CO2, CO, H , etc) to acetic acid (Yang, 1984). 2  As a consequence of consuming hydrogen rather  than producing it, homoacetogens may lower the hydrogen partial pressure during anaerobic digestion.  However, in a normal anaerobic digestion system, methanogens  to successfully out-compete  homoacetogenic  used for reducing C0  4  2  of homoacetogenic homoacetogens  to CH .  bacteria for hydrogen since H  2  appear  is mainly  So far, little is known about the functional importance  metabolism in anaerobic digestion or the metabolic interaction of  and methanogens (Zeikus 1981).  Acetate, C0  2  and H  are catabolized to the terminal products by methanogens (Fig-  2  ure 2.1). T h e methanogens are a unique but diverse group of organisms. Methanogenic bacteria isolated to date are limited to catabolism of one- and two carbon compounds (Table 2.3).  Most of them utilize hydrogen and one-carbon compounds such as carbon  monoxide, carbon dioxide, and formate as substrates for methane production. are two known genera of methanogens,  There  Methanosarcina and Methanothrix, which can  utilize the two-carbon compound, acetate.  Methanosarcina, which can utilize  H /C0 2  2  as well as acetate and other one-carbon compounds, are classified as hydrogen-oxidizingacetotrophs  ( H O A ) . Since methanothrix are unable to use hydrogen.in combination with  carbon dioxide, they are classified as non-hydrogen-oxidizing acetotrophs ( N H O A ) . Those which can utilize  H /C0 2  2  and other one- carbon compounds, but do not cleave acetate  are named hydrogen-oxidizing methanogens Acetoclastic methanogens  (HOM).  convert acetic acid into end productions: carbon dioxide  and methane according to the reaction  CH COOH = CH + C0 3  A  2  (2.9)  Chapter 2.  LITERATURE  30  REVIEW  T h e conversion of acetate accounts for 60% to 75% of the methane formed and is of critical importance in maintaining a relatively stable fermentation and in determining the maximum volatile solids loading rate at a given hydraulic retention time. However, up to date, only few microbes have been found which can produce C i f acid so far.  4  from acetic  Therefore they most likely do not play a major role in acetate utilization  in methanogenic  fermentations.  Perhaps, since they are difficult to isolate due to a  close symbiotic relationship with other bacteria, they grow slowly (minimum doubling time of 2-3 days), and they are extremely  sensitive to oxygen, the acetate utilizating  methanogenic bacteria of major important have not yet been isolated. T h e hydrogen-utilizing bacteria (hydrogen-oxidation  methanogens)  for removing almost all of the hydrogen from the system.  are responsible  They grow quite quickly  with minimum doubling times of around 6 hours and control the redox potential of the digestion process. The traces of hydrogen that they leave behind are believed to regulate both the total rates of acid production and acid oxidation. They are the autopilot of the anaerobic digestion process.  2.4.2  M i c r o b i a l Interaction  in A n a e r o b i c Digestion  A microbial ecological population distribution is determined when a fragile compromise is forged among the various species present and their environment; and it is this compromise, involving synergistic and antagonistic interrelationships, that makes anaerobic digestion both possible and limited. It has been accepted that sugar is fermented mainly via the Embden-Meyerhof-Parnas pathway to pyruvate, which is then further catabolized to fatty acids, alcohols, hydrogen and CO2- N A D H generated in glycosis must be reoxidized to N A D before the degradation  Chapter 2.  LITERATURE  Table 2.3:  31  REVIEW  Methanogenic Substrates and  2  A G°(Kcal)  Reaction  Substrate 1. H - C 0 :  Reactions  2  H  2  - 32.4  +HCO3- + H + —> C H + 3 H 0 4  2  2. Formate: H C O O " + H 0 + H + —> C H + 3 H C 0 -  - 31.2  CH3COO- + H 0 — >  -7.4  2  4  3  3. Acetate: C H +HCO3-  2  4  4. Methanol: 4 C H O H —-> 3 C H 3  5. Methyl amines: 4CH  + HCO3- + H + + H 0  4  N H + + 3 H 0 —> 3 C H 3  3  2  4  2  2  2  4 ( C H ) N H + + 9 H 0 —> 9 C H 3  3  + HCO3- + 4 N H + + H +  -53.8  + HCO3- + 2 N H + + H +  -52.5  + 3HCO3- + 4NH ++3H+  -159.8  4  2 ( C H ) N H + + 3 H 0 —> 3 C H 3  -75.2  2  2  4  4  4  4  6. C O : 4CO + 2 H 0 — > C H 2  4  + 3C0  2  -43.1  Chapter 2.  LITERATURE  32  REVIEW  of organic matter can continue (Figure 2.2). In single-culture system, electrons ethanol, and H  from pyruvate are used for the production of  is not a significant product.  2  Regeneration of N A D for glycolysis is  dependent on ethanol formation. This is due to the fact that the evolution of H  2  from  reduced nicotinamide adenine dinucleoticide ( N A D H ) is thermodynamically unfavorable under standard conditions:  NADH  + H  +  = H  2  + NAD  (2.10)  +  A G ° = + 4 . 3 Kcals  When the H -utilizing 2  methanogens are cocultured with fermentative bacteria, the  metabolic activities of the latter are shifted to generate more oxidized end products, e.g. acetate. Wolin (1976) illustrated this phenomenon by a hypothetical, but not unrealistic, fermentation pathway for the formation of ethanol, acetate, C 0 (Table 2.4). W h e n the partial pressure of H increasingly negative.  2  2  and H  2  from glucose  is reduced, the free energy change becomes  Therefore, with methanogens, N A D is regenerated by formation  of H , which is removed by methanogens. 2  Thus electrons from N A D H are used for H  2  formation and methanogenesis i n the mixed system rather than for ethanol formation. Through the methanogenic H  2  removal, the cocultures not only alter the fermentation,  but also provide an additional mole of A T P per mole of glucose fermented (Table 2.4). The effect of the interspecies i / - t r a n s p o r t reaction on fermentation has been demon2  strated by several experiments (Zeikus 1982; W o l i n 1974; C h u n g 1976; Weimer 1977) The # -producing acetogenic bacteria catabolize the products of the hydrolysis stage, 2  mainly propionate, butyrate, long-chain fatty acids, alcohols, and probably aromatic and other organic acids to acetate, H  2  and C0 . 2  However, these organisms cannot catabolize  Chapter 2. LITERATURE  REVIEW  i  c a r b o h y d r a t e s  glucose  AOP ATP  glucose 6 phosphate  glucose  —ATP -*-ADP  2 [glyceraldehyde phosphate]  fructose 1:6 diphosphate  2(phcsphati  2NAD  2NA0H*2H«  1  211:3 diphosphoglycerafe] 2C0  l — 1.A0P  2 2HSGJA  • \ — 2 [pyruvic acid]  2[aeetyl CoAJL 2NA0-  2NA0H*2H  ®  H0-4—AATP  ® | 2 N NAO AI 2HSCoA  2 NAOH  1  ri  • UHAOH* 4H • • <tNAD'  2 2H.  2[acetic acid]  2H,  butyric acid  I  2 [propionic acid]  Figure 2.2: Metabolic Pathway Inside Acid-forming Bacteria  Chapter 2.  LITERATURE  34  REVIEW  Table 2.4: P a r t i a l R e a c t i o n for a H y p o t h e t i c a l G l u c o s e F e r m e n t a t i o n and  W i t h a Methanogen  Glucose + 2 ATP —> 2 Glyceraldehyde-3-p +2 ADP Glyceraldehyde-3-p + 2 NAD+ +4 ADP + 2 pi — > 2 Pyruvate + 2 NADH + 4 ATP + 2 H+ 2 Pyruvate + 2 CoASH — > 2 Acetyl-SCoA + 2 H + 2 C 0 2  2  A. Glucose-fermenting organism alone: Acetyl-SCoA + pi + ADP —> Acetate +CoASH + A T P Acetyl-SCoA + NADH + H+ —> Acetyldehyde + NAD+ + CoASH Acetyldehyde + NADH + H+ —> Ethanol + NAD+ Sum: Glucose + 3 ADP + 3 pi —> Ethanol + Acetate + 2 H + 2 C 0 + 3 ATP 2  2  B. Glucose-fermenting organic plus methanogen : 2 Acetyl-SCoA + 2 pi + 2 ADP —> 2 Acetate + 2 CoASH + 3 ATP 2 NADH + 2 H+ —> 2 NAD+ + 2 H  2  4 H + C 0 —> C H + 2 H 0 2  2  4  2  sum: Glucose + 4 ADP + 4 pi —> 2 Acetate + C H + C 0 + 4 A T P 4  2  Without  Chapter 2.  LITERATURE  35  REVIEW  these substrates to acetate when H2 in the environment is not at an extremely low level. As is illustrated in Table 2.2 , only when acetogenic bacteria are placed in syntrophic association with i/ -utilizing organisms, such as methanogens and desulfovibrio, do the 2  reactions become energetically favorable to proceed. (Mclnerney 1979). Although microbial interactions among diverse trophic groups of microbes in methane fermentation are not clear, methanogens have been considered as effective bio-regulators of anaerobic digestion through proton and electron exchange. By removing the metabolite of the acid-formers, acetate, methanogens provide a constantly favorable environment for the fermentative bacteria.  Otherwise most of them would be inhibited by  their own metabolite. Also, electron transfer (or H transfer) between methanogens and 2  iJ -producers creates favorable conditions for metabolism of certain metabolites. The 2  fermentation pathway of fermentative bacteria may be altered to gain more energy. On the other hand, the accumulation of intermediate organics, which are metabolites of acid-formers and have a detrimental effect on methanogenesis during periods of overloading or other process stress, is due to hydrogen sensitivity moderated by syntrophic associations between hydrogen-producing bacteria (acidogens) and hydrogen-consuming bacteria (methanogens, S R B , NRB). The physical separation of methanogenesis and acidogenesis (two-phase) in an attempt to optimize growth conditions for each group of bacteria theoretically cannot enhance anaerobic bioconversion rates since the necessary interspecies hydrogen transfer function is disturbed.  Chapter 2.  2.4.3  LITERATURE  36  REVIEW  H y d r o g e n Regulations  General  Perspective  Hydrogen in relatively low concentration appears to regulate the overall conversion process by throttling the acidogenic reactions at several points in the glucolytic pathway. Accumulation of hydrogen obviously needs an alternate method of electron disposal for N A D regeneration. This need drives the fermentation of pyruvate to propionate, lactate and ethanol and/or the fermentation of acetyl-CoA to butyrate. Since the methanogens cannot use these end products as substrates directly, their accumulation leads to a problematic depression in p H . The subsequent degradation of these acids to acetate is also hydrogen dependent and is mediated by obligate hydrogen producing acetogens ( O H P A ) linked to the various hydrogen oxidizers. In addition to their hydrogen sensitivities, the number of O H P A and associated  H O M (hydrogen oxidation methanogens)  bacteria existing in an anaerobic  process may vary, depending on its stability history. Under a process upset, the O H P A H O M must increase to accommodate the accumulated hydrogen and propionate. If a long period of stable operation ensues, the relative proportion of propionate may decrease, and the number of O H P A will decrease accordingly. T h i s dynamic balance is considered central to the overall stability and efficiency of many anaerobic processes and is regarded as the key to stabilizing and improving anaerobic In single-phase processes,  treatments.  the proportion of O H P A and methanogenic bacteria re-  sponds to the relatively uncontrolled production of acidogenic products, which may alternately reach inhibitory and substrate-limiting proportions. A number of researchers have also demonstrated that the environmental requirements of acidogenic and methanogenic enrichments are quite different from each other as reflected in terms of p H and O R P (Hammer et al. 1969, Dirasian 1963,  Niktin 1968,  Blanc 1973 ). T h e two-phase system  Chapter 2.  LITERATURE  REVIEW  37  was originally proposed to address these issues.  However, the role of hydrogen was not  emphasized as the primary control factor in earlier investigations.  Although the two-  phase process seems best suited for the treatment of soluble-type wastewaters, which present a high potential for volatile acids accumulation,(Ghosh et al. 1981, perior performance  has also been demonstrated  sewage sludge and agricultural wastes.  for particulate-type  1983a) su-  substrates such as  (Ghosh 1983b, Keenan 1976,  Normann et al.  1977). However, these studies failed to show definitive reasons for process improvements.  T h e r m o d y n a m i c Q u a n t i f i c a t i o n of H y d r o g e n  Effects  In view of the reported differences in hydrogen effects, and the traditional difficulties in adequately defining the redox nature of the wastewater substrate, at hydrogen levels of 10~  6  to 1 0  - 1 0  atm, the regulatory effects of hydrogen on O H P A and H O M have been  illustrated using thermodynamic models and equilibrium assumptions by several authors ( M c C a r t y 1971,1981, Mclnerney 1981, Gujer 1983). Thermodynamic calculations associated with those half reactions during anaerobic stabilization of organic wastes to methane indicated that propionic acid oxidation to acetate becomes favorable only at a hydrogen partial pressure below 1 0 below 1 0  - 3  -4  atm (Figure 2.3).  atm, while butyric acid oxidation becomes favorable at or Figure 2.3 provides insight into the product formation pat-  terns to be expected in a two-phase process. Evident from Figure 2.3 is the preference of sulfate reduction over bicarbonate respiration at all hydrogen partial pressures and the preference of acetate cleavage by S R B over methanogens.  Chapter 2.  The  LITERATURE  38  REVIEW  R o l e of H y d r o g e n i n R e g u l a t i o n of M e t h a n o g e n e s i s  Standard free energy levels associated with the methanation reaction, listed in Table 2.3, indicate that the favorability of acetate cleavage is an order of magnitude lower than H2/CO2 and methanol conversions (at standard state of 1 atm of H  2  in gaseous phase).  However, this high level of hydrogen is uncommon i n well-operating anaerobic wastewater treatment systems. At more realistic hydrogen concentrations, acetate cleavage competes more favorably with the methanogenic respiration of bicarbonate, as shown in Figure 2.3 In addition, hydrogen regulation i n an anaerobic reactor is a result of the integrated effects of the specific capabilities of O H P A , H O A , N O H A , and H O M , and may be dependent on the cultures selected by seeding, substrates and operational procedures. For example, species of Methanosarcina ( H O A ) which utilize both acetate and H2/CO2 as substrates  may be subject to catabolic repression of acetate cleavage by low levels of  hydrogen.  However, other investigators have reported a complete and rapid inhibition  of acetate cleavage in the presence of H2/CO2 (Baresi et al.). H2/CO2 is preferentially utilized over acetate in mixtures of these substrates by Methanosarcona species to the extent that acetate cleavage is inhibited until H is exhausted (Mclnerney 1981, Ferguson 2  1983, M a h 1978)  Chapter 2.  LITERATURE  REVIEW  39  Gibb's Free Energy Change (KJ/reactlon)  Figure 2.3: Graphical Representation of the Hydrogen-dependent Thermodynamic Favorability of Acetogenic Oxidations and Inorganic Respirations A s sociated with the Anaerobic Degradation of Waste Organics: 1 Propionic acid oxidation to acetic acid, 2 Butyric acid oxidation to acetic acid, 3 Ethanol to acetic acid, 4 Lactic acid to acetic acid, 5 Acetogenic respiration of bicarbonate ( C 0 ) , 6 Methanogenic 2  respiration of bicarbonate,  7 Respiration of sulfate to sulfite, 8 Respiration of sulfite to  sulfide, 9 Methanogenic cleavage of acetic acid, 10 SRB-mediated cleavage of acetic acid (from Harper, 1986)  Chapter 3  RESEARCH  OBJECTIVES  A considerable amount of research has been directed over the years at using different reactor configurations to establish the development of an industrial anaerobic digestor for cheese whey.  However, most of the previous studies were feasibility assessments  of the process and were generally preliminary in nature and incomplete.  Unsuccessful  fermentation experiments have often been reported apparently due to the high organic concentration  of cheese whey and its tendency toward rapid acidification.  droped and gas production and C O D reduction decreased.  p H quickly  However, surprisingly little  work has been done so far to explain the reason for this system instability. In addition, although the high organic strength of cheese whey can supply a useful source of energy for cheese manufacturers by means of the anaerobic fermentation, industrial applications have been very limited due to the unreliability of the process. It is therefore necessary to carry out a study to increase the fundamental understanding of the process, to find an explanation for its instability, to efficiently control such instability and to optimize the process. T h e special objectives include: (1) To assess the technical feasibility of treating cheese whey in a U A S B reactor, and to determine the effects of start-up procedures on reactor performance and treatment efficiency. (2) To determine the effects of influent concentration, H R T and O L R on the treatment efficiency, and to determine the inhibitory effects of influent concentration and organic  40  Chapter 3.  RESEARCH  OBJECTIVES  41  loading rate. Previous studies have shown that, when influent concentration was increased to a certain level, the system became unstable. This was attributed to an upset in the physiological balance between the methane-producers and hydrogen-and acid-producers because of the great difference in the rates of acidogenesis and methanogenesis.  This research  will explore the difference in the rates between these two stages, the threshold level of the influent concentration and will try to obtain the optimal influent concentration for the particular system. (3)To assess the effect of sulfate addition on the buffering capacity and stability of the anaerobic system, and to investigate the mechanisms of inhibition. As has been discussed in earlier sections, knowing the importance of the nutritional requirements of methanogens is important to the overall knowledge of an anaerobic processes. Among these required nutrients, sulfur should be given more attention for special substrates such as whey. A limited number of literature references, which were cited i n section 2 of the literature review, revealed that a sulfur requirement is part of a complex picture. O n one hand, sulfate reducing bacteria help to maintain the anaerobic conditions required for the growth of methanogens, while on the other hand the addition of sulfate inhibits methanogenesis because sulfate reducers have demonstrated a higher affinity for hydrogen than methanogens. Methanogens and sulfate reducers are not mutually exclusive. In the presence of excess hydrogen, they have no effect on each other. W h e n the hydrogen supply becomes rate limiting, competition does take place. From the point of view of thermodynamics and hydrogen regulation, the hydrogenotrophic association would help to maintain the reaction condition favorable for methanogenesis. It is expected that the results of this research will yield the proper sulfate concentration needed to moderate the detrimental influences of excess hydrogen on a stressed anaerobic reactor.  Chapter 3. RESEARCH  OBJECTIVES  42  Obviously, the practice of sulfate addition holds numerous potential challenges, including the control of the inhibitory and corrosive hydrogen sulfide gas. However, such a study might yield valuable information on the utility of manipulating hydrogen to control acidogenesis and methanogenesis. significant levels of sulfates.  Moreover, a number of industrial wastewaters contain  T h e successful anaerobic treatment of these wastewaters  requires an understanding of the competition for methanogenic precursors  by S R B as  well as of the associated microbiology and substrate conversion kinetics. (4)To explore maximum treatment efficiency by using optimal control parameters based on all the above studies .  Chapter 4  EXPERIMENTAL  4.1  REACTOR  METHOD  SET-UP  The flow sheet of the U A S B system is presented in Figure 4.1.  T h e reactor was made  of acrylic pipe with an inner diameter of 11.5 cm (4.5 in.) and a height of 168 cm (60 in.).  The total volume and working volume of the reactor were 17.5  respectively.  and 14.3  liters,  A series of sampling ports were fitted at intervals on one side of the reactor  to permit sampling for the analysis of the reactor contents.  T h e reactor was operated in  an upflow, continuous mode. A distinguishing feature of this U A S B reactor design is a conical three-phase separator located at the top of the reactor. T h e three phases refer to gas, liquid and solid (sludge). The basic principle of separation by the separator is explained as follows. Gas bubbles produced by the bacteria rise to the top of the reactor where they are first  separated  from the liquid and collected in the gas chamber between the column and the top cone. The biogas passes through a water seal column outside the reactor, which is used to regulate the liquid level in the separator, then goes to a wet gasmeter for measurement. The lower baffle, a small cone suspended below the larger,top cone is used to minimize the possibility of gas entering the separator by blocking the uprising gas bubbles from the open tip of the larger cone. The separation of sludge is accomplished by fluid dynamics. T h e floes of sludge with poorer settleability rise through buoyancy provided by rising gas bubbles, and travel with  43  Chapter 4.  EXPERIMENTAL  44  METHOD  BIOGAS  BIOGAS  =X*=10  9 T H R E E PHAS: SEPARATOR  WATER SEAL  s  M p L I  W E T GAS METER  N =x» G  A P S  TEMPERATURE CONTROLLER  HEATING TAPE  1  I-  VFEED TANK  FEED PUMP  Figure 4.1: Schematic D i a g r a m of U A S B System  Chapter 4.  EXPERIMENTAL  the liquid into the upper cone. sectional area increases.  METHOD  45  T h e upflow velocity of the fluid decreases as the cross  When the upflow velocity of fluid decreases to a value equal to  downflow velocity of the sludge, the rising particles slow down, drop and return back to the reactor.  This design was efficient in retaining a large percentage of the bacteria in  the reactor. T h e whey, stored in a refrigerator at 4 ° C , was introduced continuously into the bottom of the reactor by a peristaltic pump through a copper-alloy coil immersed in a water bath to bring the feed temperature to about 3 4 ° C . T h e effluent left the reactor from the top of the settlling chamber and was collected in a plastic container. Fermentation temperature was maintained at 33 ± 1° C using a feedback controller and a number of external electric heater pads wrapped around the reactor. In this set-up, there was no p H control system.  4.2  FEED SUBSTRATE  Cheddar cheese whey used in this study was obtained from the Fraser Valley Milk Producers Association's cheese producing plant at Abbotsford, British Columbia, Canada. Typical whey composition is presented in Table 4-1. T h e manufacture of cheese from either whole or skim milk produces, in addition to cheese itself, a greenish-yellow fluid known as whey.  Whole milk is used to produce  natural or processed cheeses such as cheddar, and the resulting whey has a p H in the range of 4.5 to 6. T h e lower p H is the result of the acid developed during coagulation. As indicated in Table 4.1, although the basic nutritional requirement of nitrogen in whey for bacterial growth seems to be adequate according to the criteria of C O D : N : P being 100:5:1, the extremely low ammonium nitrogen is perhaps the main cause of the  apter 4. EXPERIMENTAL  METHOD  46  Table 4.1: Characteristics of Chedder Cheese Whey  Total solid (TS)  5.66-5.88 %  Volatile solid (VS)  4.52-4.70 %  Total Chemical Oxygen Demand (TCOD) Soluble Chemical Oxygen Demand (SCOD)  64-67 g/1 62-65.5 g/1  SCOD as percent of TCOD  96-97 %  Biological Oxygen Demand (BOD)  60-62 g/1  BOD as percent of TCOD  95-96 %  Total Kjeldahl nitrogen (TKN) Ammonium Nitrogen Nitrate Total Phosphorus P  H  2.75-3.05 g/1 2.8-3.0 mg/1 0.45-0.70 mg/1 0.34-0.37 g/1 4-5.5  Chapter 4.  EXPERIMENTAL  METHOD  47  lower buffering capacity of whey. In addition, a shortage of phosphorus is apparent. Two characteristics  of raw whey are its unusually high S C O D to T C O D ratio and  extremely low p H . These can create difficulties during anaerobic processing. Fresh cheese whey was contained in 5 50-liter tanks and transported from the cheese plant to the large freezer of the bio-resource lab at U B C once every 3 months, and stored there at - 3 0 ° C . About one week before it was needed, a portion of the frozen whey was moved into a cold room at 4° C for defrosting. T h e n it was prepared to the desired C O D concentration by mixing with cool tap water, adjusted to a p H of about 7 by using 5% N a O H , and transferred to the small scale, feed tank, where it was kept refrigerated at 4° C and ready for use.  4.3  SEED  SLUDGE  T h e seed sludge was originally obtained from the effluent of an anaerobic rotating biological reactor ( A n R B C ) in the laboratory and had been stored in a plastic container in a cool room at 4° C for several months. T h e bacterial concentration in the effluent from the A n R B C was very low, even in the dense portion in the bottom. To obtain the necessary concentration and activity of seed sludge to ensure a successful start-up of a U A S B reactor, it had to be incubated.  First, the dense portion of the effluent in the  container bottom was moved to a glass jar at a room temperature of 2 2 ° C . T h e sludge was acclimated using 200 ml of raw cheese whey daily for more than 30 days before it was put into the reactor.  A t the time of seeding, the sludge concentration was 3% T S  and 2.1% V S , respectively. Four liters of this effluent were used as seed .  Chapter 4. EXPERIMENTAL  4.4  METHOD  48  E X P E R I M E N T DESIGN  It was the author's intention to attempt to achieve a high treatment efficiency initially by using a U A S B reactor without pH-control or nutritional addition, and to optimize the process through experimental investigations. This research was carried out in 18 months in 4 steps, in which a variety of influent concentrations and H R T s were used as shown in Table 4.2. For each step, the reactor was started using 4 liters of the seed sludge and 6 liters of diluted cheese whey of 5 g C O D J\. T h e remaining 7 liters (the digestor capacity ) were filled by continuously adding whey at the rate of 2.5 liters/day. T h e experiment was started with a very dilute influent concentration of about 5 g C O D / 1 in order to observe the effect of a wide range of substrate strengths on treatment efficiency and gas production. After 40 days of operation, the reactor was stabilized at a constant gas production and effluent properties, including C O D , V F A , T S S and p H . T h e n the influent concentration was increased stepwise from approximately 10 to 40 g C O D / 1 at a constant H R T of 5 days during the preliminary assessment of technical feasibility. T h e stepwise increase of feed strength not only allowed the microbes to gradually acclimate themselves to the new environment with a minimum negative impact, but also permitted a full view of the performance profile over the entire range of the operational settings with the objective of locating the optimum performance conditions. T h e tests on the effects of sulfate ions were first carried out in batch experiments to get a basic sense of sulfate behavior in the anaerobic process.  A 3-factor experimental  design was used in the batch experiment. The details are given in Appendix A . O n the basis of the results of the batch experiments, continuous flow experiments were designed to gain more accurate information about the sulfate effects. T w o reactors were operated simultaneously at the same temperature with the same seed, but with different operating  Chapter 4.  EXPERIMENTAL  49  METHOD  Table 4.2: Experimental Design  HRT (days)  Inf. Cone, (g COD/1)  Sulfate (g/1)  Start-up  5  5-9.9  0  Effect of Inf. Cone.  5  5-38  0  Effect, of HRT  24-5  20 40  oo  Experiment  Parameters  Effect of Sulfate  5  15-50  0.2 0.3 0.5  Optimal Operation  7.5 3.8 2.0  26-32  0.2 0.2 0.2  Chapter 4. EXPERIMENTAL  METHOD  50  conditions. Finally, an experiment was designed using the optimal operating conditions found from the previous experimental results to achieve the optimum treatment efficiency.  4.5  REACTOR  OPERATION  T h e reactors were continuously fed and operated at 3 3 ° C . T h e feed rate was monitored and recorded every 3 hours to ensure a constant daily feed. T h e production of biogas was measured daily. Samples were taken daily of the influent and effluent for analysis of C O D , V F A , T S S , V S S and p H . T h e analysis of the gas composition was also performed every day. During the time of changing loading rate, the biogas was sampled up to three or four times daily. W h e n the gas production rate and the effluent C O D were stationary again (3 to 5 days for gas production and 6 to 10 days for C O D ) the reactor was at steady state.  Samples of the mixture of liquid and  solid in amount of 200 to 300 ml (just enough for chemical analyses) were then taken from the 10 sampling ports mounted in the reactor wall for measurement of the sludge, C O D , butyric, propionic, acetic acids and p H for each operating condition. T h e amount of sample taken from each sample port was recorded for the calculation of sludge growth in the reactor. To obtain reliable results of reactor profiles, only one port was sampled every hour from sample port 10 (top) to port 1 (bottom).  For each subsequent increment  of influent concentration, an operating period of 2 to 3 H R T s was maintained to ensure stable operation.  Chapter 4.  4.6  EXPERIMENTAL  METHOD  51  ANALYSIS  Analyses conducted on the influent and effluent were as follows: total solids (TS), total suspended solids (TSS), volatile suspended solid (VSS) and ash according to the "standard methods" ( A P H A , 1975). Chemical oxygen demand ( C O D ) was determined by a colorimetric method using an optical fiber instrument (Knechtal 1978). Gas production was measured by a wet gas meter and then corrected to the standard temperature and pressure ( S T P ) . Both gas composition and volatile fatty acids ( V F A s ) were analyzed on a Hewlett Packard 5890a gas chromatograph, using an external standard. The G C was equipped with both a flame ionization detector and a thermal conductivity detector with separate columns; a Porapak column was used for gas analysis and a carbopack C column for V F A s .  Total Kjeldahl nitrogen ( T K N ) , and ammonia nitrogen (NH  3  — N)  were determined using a block digestor and a Technicon Auto Analyzer II (Schulmann et al 1973).  Chapter 5  START-UP  5.1  AND EFFECTS  OF PROCESS  PARAMETERS  INTRODUCTION  Cheese whey acidifies easily and frequently causes problems when treated biologically. Some frustrating, unsuccessful experiments  have led to the suggestion that the system  was hard to maintain stable without p H control. was also seriously considered.  T h e necessity of some micronutrients  In view of the obvious difficulties in start-up of a cheese  whey anaerobic system and maintenance  of its stability, this part of the  dissertation  centers on the feasability of anaerobic digestion of cheese whey by using a new reactor configuration, a U A S B reactor, in an effort to increase V S S concentration in the reactor. T h e other major differences of this experiment  from previous research are that no  p H control or nutriential addition were applied in order to find the mechanism of the reported inhibition. T h e U A S B process has been described in the literature  as one of the innovative  reactor designs which permits efficient and economical treatment because of its ability to retain higher V S S concentrations  in the reactor. However, the application of a U A S B  reactor to treat high strength acidic wastes has not been established. This could be due to improper start-up procedures and/or a poor understanding of the importance of the control parameters during the start-up period. This study included the following investigations:  1. Proper start-up procedures for a cheese whey U A S B system.  52  Chapter  5.  START-UP  AND  EFFECTS  OF PROCESS  53  PARAMETERS  2. Determination of the quality of effluent and treatment efficiency when the reactor was operated over a wide range of influent concentrations. Various operating parameters were to be used to assess the effectiveness of the process. 3. Effect of influent concentration on gas production and system performance.  5.2  STUDY  5.2.1  IN S T A R T - U P  OF T H E REACTOR  Difficulties in S t a r t - u p  Use of the U A S B process is dependent on good sludge floe formation.  T h e procedure  of start-up is important for the development of active sludge with both high specific activity and settleability. Considerable attention has been directed to the start-up of the U A S B reactor because of the very slow growth of anaerobic microbes. It was found in this experiment, that for cheese whey, the start-up of a U A S B reactor was even more arduous. This might be attributed to the inherent characteristic of the substrate of being extremely easily acidified. Various start-up strategies were tried. The parameters applied in the period of startup are presented in Table 5.1.  T h e results have shown that sludge loading rate was the  most critical parameter and must be carefully controlled. T h e reactor 1 which was fed with the lowest strength whey of 5 g C O D / 1 operated very well.  The other two (reactor 2 and reactor 3), which were started with higher  strength whey, experienced difficulties.  Over the first 3 days, reactor 2 was fed at a  rate of 2.7, 2.4 and 2.6 liters daily with an influent concentration of 30 g C O D / 1 .  The  methane content in the biogas was extremely low, only 19.8%  The  on the third day.  reactor finally failed to start-up because the sludge loading rate (SLR) reached 0.38  to  0.43 g C O D / g V S S . d . T h e n , 5 liters of seed sludge with a V S S of 24.2 g / l was added.  Chapter 5.  START-UP  AND EFFECTS  OF PROCESS  54  PARAMETERS  Table 5.1: S l u d g e L o a d i n g i n S t a r t - u p  Reactor  Influent (g C O D / 1 )  Feed (1/d)  Performance SLR (g C O D / g VS!|>)  5  2.8  0.162  stable  30  a  2.6  0.300  failure  28  b  2.6  0.490  failure  20  1.0  0.190  stable  R  63  1.0  0.214  stable  R/i  20  0.5  0.256  stable  Ri Rr  2  N o t e : In a & b , the reactor was seeded i n different a m o u n t of sludge  Chapter 5. START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  55  T h e total amount of V S S in the reactor was 121 g V S S . T h e daily feed of 2.1 liters of influent with a concentration of 28 g C O D / 1 caused the methane content to drop from 51.9% to 44.3%, and further to 25.2%, since the S L R was as high as 0.49 g C O D / g V S S . d at that point. A n attempt to recover the reactor was made by reducing the feed to 0.9 liters daily. Immediately, biogas composition rose to 44.1% methane by the next day. 2.2 1/d feed was tried again. However, the reactor was entirely unstable which was indicated by drastic drop in methane content of the biogas from 44% to 34%. A number of attempts to start-up the cheese whey U A S B reactor indicated that a successful start-up was strongly related to the S L R . Table 5.1 clearly shows this relationship between the performance of the reactor and S L R . No matter how strong the influent concentration, up to 63 g C O D / 1 for reactor 3, or how large the feed rate, up to 2.8 1/d for reactor 1, if the S L R was lower than 0.26 g C O D / g VSS~d, the reactors were able to start without any problem. T h e reactor start-up was destined to fail, on the other hand, if the S L R employed was beyond 0.26 to 0.3 g C O D / g V S S - d . From this study it can be concluded that S L R is the most important parameter to be controlled during the start-up of an U A S B reactor. T h e permissible S L R for a cheese whey anaerobic system was 0.25 g C O D / g V S S - d .  5.2.2  Start-up  Performance  This part of the study presents the behavior of the reactor which was initially fed the low strength of 5 g C O D / 1 at H R T of 5 days. T h e first 48 days were considered as the start-up period during which two influent concentrations (5 and 9.93 g C O D / 1 ) were used. T h e U A S B reactor performance during the start-up period is shown in Figures 5.1 to 5.8. Figure 5.3 shows the effluent C O D concentration vs time of reactor operation. T h e  Chapter 5.  START-UP  AND EFFECTS  OF PROCESS PARAMETERS  56  C O D concentration decreased significantly with the length of time of operation. O n day 40, in spite of high influent concentration from 1500 to 110 mg/1 (Figure 5.3).  of 17.7 g C O D / 1 , effluent C O D was reduced  T h e same trend of increasing efficiency in terms of  C O D removal and gas production was also observed, as shown in Figures 5.2 and 5.3. Within the first 40 days, the C O D removal efficiency increased from 70 to 97%.  In the  meantime, biogas composition increased from 48 to 57% methane and the gas production rate reached a value of 2.5 liters CHu per liter feed per day within 15 days and remained at approximately the same level under the same loading rate. Comparing C O D and V F A in the effluent and gas production, it could be noticed that the lowest effluent V F A , the highest methane content in the produced biogas and the highest C O D removal were reached after 40 days of operation. However, the highest gas production rate was reached much earlier at day 15 (Figure  5.9).  T h e effluent V S S concentrations  are shown in Figure 5.8.  Due to the poor settling  quality of the seed sludge, a large amount of sludge left the reactor at the beginning of the operation. After 15 days of operation, the amount of sludge remaining in the reactor was reduced from 86 to 60 g V S S . At day 15, 67.2 g V S S of seed sludge were added to the reactor to maintain the specific activity of the sludge. As a result of natural selection and sludge particle growth, the sludge settleability improved gradually. At day 30, the T S S content in the effluent was as low as 0.1 g/1. Many factors have been shown to be associated with the start-up of the U A S B reactor and its later performance.  Attention has also been directed to the use of different seed  sludge in order to shorten the start-up period.  Starting with a poor quality digested  sewage sludge, De Zeeuw (1985) was able to cultivate a highly active biomass (specific activity of 0.75 g C O D / g V S S d) within a period of 6 weeks (organic loading rate of 7.5 g C O D / 1 d). Compared to the sewage sludge used by De Zeeuw , the seed used in this study had a  Chapter 5.  START-UP  TJ  ~ Q O O o  0  1  AND EFFECTS  OF PROCESS PARAMETERS  57  1  8-  .vj  A  TJ <0 O _J  o c « a  6 a  •> ,  ,  1  10  1  20  '  1  30  •  1  40  ' ——1  Time (days)  Figure 5.1:  SO  '  1  eo  '  O r g a n i c L o a d i n g R a t e versus T i m e  1  70  '  80  Chapter 5. START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  58  32  28 H  24 H  S  20  Q O  CH^O-OO-C  c Cv-<><><X>0 O-CD  coi  10  20  30  40  50  eo  Time (days)  Figure 5.2: Influent C O D versus Time  70  80  Chapter 5.  START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  Time (days)  Figure 5.3: E f f l u e n t C O D v e r s u s T i m e  59  Chapter 5.  START-UP AND EFFECTS  OF PROCESS  PARAMETERS  T i m e (days)  Figure 5.4:  C O D R e m o v a l versus T i m e  Chapter 5.  START-UP AND EFFECTS  OF PROCESS  61  PARAMETERS  12  TJ © «  /  «  CC  u  TJ  o o c «  o 2  •)  -r~  10  -1—  20  -1— SO  40  Tim« (day8)  Figure 5.5:  —I—  60  eo  - r 70  M e t h a n e P r o d u c t i o n R a t e versus T i m e  -  eo  Chapter 5. START-UP  AND EFFECTS  OF PROCESS  62  PARAMETERS  60  ^  55 H  C O  co 50 O  •»v  a  E  o O <D C  45H  co  sz  o  2  AOA  35-  —r~ 10  ~20~  -r  30  -  60  60  versus  Time  40  Time (days)  Figure 5.6: B i o g a s C o m p o s i t i o n  -r  70  -  so  Chapter 5.  START-UP AND EFFECTS  OF PROCESS  PARAMETERS  tao  Tlm« (days)  Figure 5.7: E f f l u e n t V o l a t i l e F a t t y A c i d s v e r s u s T i m e  63  Chapter 5.  START-UP AND EFFECTS  OF PROCESS  PARAMETERS  2  CO CO  > -4-*  c o  JD H—  UJ  Time (days)  Figure 5.8:  Volatile Suspended Solid (VSS) in the Effluent  64  Chapters. START-UP AND EFFECTS OF PROCESS PARAMETERS  65  56  CQ0FB3UDCN  says was**  Z  O 90O D Q £ 80 Q O ° 70  U  A /  I  /  50 • •  A/  V  •  48  600  \  XI 25  «  V  I  P icnwcmouacN  I  O  fas  £  15 1  —1  0  1  T  1  1  V 20 30 40 50  4001  \  200  1  0  1  1  1  1  1  O 20 30 40 50  MM  Figure 5.9: C o m p a r i s o n of C O D , V F A a n d B i o g a s  Production  Chapter 5.  START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  66  lower V S S content and poorer settleability. This was demonstrated by the loss of a large amount of sludge (Figure 5.8), high V F A concentrations and low gas production at the beginning of the start-up. However, the seed was able to degrade acetate and propionate resulting in very low effluent V F A concentrations within a period of 40 days, reaching 0.71 g C O D / g V S S - d of specific activity after an operation period of 70 days.  5.2.3  V F A B e h a v i o r in Reactor  Start-up  Figure 5.7 shows the daily V F A s concentrations in the effluent of the reactor. It was found that V F A s were sensitive parameters performance.  which responded to loading change and reactor  A t the very beginning of the reactor operation, V F A s in the effluent were  fairly high due to the lower activity and concentration of the sludge at that time. T h e n they were gradually decreased. A n increase in loading rate increased the V F A concentration. At day 30, the peak in acetic acid concentration was a response to the increase of influent concentration from 4.56  to 9.9 g C O D / 1 .  As long as the sludge was acclimated and had built up enough  concentration and achieved a high specific activity, the V F A in the effluent would decrease to a very low level. In this case, after 45 days from start, the total V F A in the effluent was as low as about 40. Although at days 45 and 60 when the influent concentration was increased from 10 to 18 g C O D / 1 and from 18 to 28 g C O D / 1 respectively, there was no peak observed. It is very important during the start-up of a U A S B reactor that the O L R be increased only after the majority of V F A is removed. At day 12, when an attempt was made to decrease the H R T from 5 days to 4, a sudden increase in V F A was detected. By using V F A concentration as a sensitive indicator while varying the start-up parameters it has been shown that 0.2-0.25 g C O D / g V S S would be recommended for start-up of the reactor.  Chapter 5. START-UP AND EFFECTS  5.3  S  T  E  A  D  Y  S  T  A  T  E  O  P  E  R  A  T  I  OF PROCESS  O  PARAMETERS  67  N  The steady-state performance of whey digestion as a function of influent concentration is summarized in Table 5.2.  A C O D removal efficiency of over 97% was maintained  after 45 days of reactor operation. A 98% C O D reduction with a gas production rate of 9.57 1 CH4 / l feed-d was achieved at a loading rate of 5.96 g C O D / 1 d and an influent concentration of 28.8 g C O D / 1 . Figure 5-10 illustrates the quality of effluent as a function of influent concentration. In spite of the high influent C O D concentration concentrations  of 28.8 g C O D / 1 ,  the effluent C O D  were between 400 and 500 mg/1. Effluent p H increased with an increase  in influent concentration.  V F A contents of the effluent were in the range of 76-16 mg/1.  A comparison of the behavior of a U A S B reactor with a fixed-film reactor for cheese whey treatment showed that the growth rate and bacterial activity were somewhat different for the suspended-growth system ( U A S B system) and the attached-growth  system  (fixed-film) (Lettinga et al 1979, Kelly and Switzenbaum 1984, Nordstedt and Thomas 1984, Wildenauer and Winter 1985, L O and Lioa 1986). Lower effluent V F A concentrations were reported for the U A S B reactor than for the fixed-film system. V F A concentration  T h e effluent  has proven to be a good indicator for the condition of an anaerobic  reactor. Such a comparison revealed that a higher activity of biomass was developed in the U A S B reactor than in the attached growth system with respect to the degradation of V F A . C O D balances were determined for the four experimental conditions. A mass balance of the system enables the sludge formed in the reactor to be calculated (Table 5.3). T h e observed yields calculated from the C O D balance over the whole experimental period were in the range of 0.098 to 0.166 g T S S formed/g C O D removed.  This appears to  be within a reasonable range for this type of waste which is primarily  carbohydrate  Chapter 5.  START-UP AND EFFECTS  Table 5.2:  Influent  OF PROCESS  PARAMETERS  E x p e r i m e n t a l Results in Steady State  OLR  COD  Effluent pH  VFA  COD removal  68  Performance  GAS  %  1 CH / 1 reactor d  l C f W g CODd  35  98  1.37  0.30  56.5  6.92  56  97  2.35  0.32  51.5  191  7.08  16  98  3.25  0.33  48.2  3.54  286  7.05  18  99  5.80  0.33  47.0  21.50  4.23  348  7.10  20  99  7.14  0.34  46.5  28.80  5.96  457  7.18  18  99  9.57  0.33  46.1  38.10  7.77  505  7.26  20  99  11.20  0.30  42.5  mg/1  g COD/1  g COD/1 d  4.56  0.91  120  6.75  7.30  1.36  215  9.93  1.97  17.70  mg/1  4  C H  4  %  Quality of Effluent as a Function of Influent Concentration  Figure 5.10:  The  (at  5 days)  HRT =  Chapter 5. START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  70  (Switzenbaum and Danskin 1982, Henze and Harremoes 1982).  5.4  UNSTEADY-STATE  PERFORMANCE  T h e process became unstable 14 days after the reactor was fed influent at a concentration of 38.1 g C O D / 1 . This was first noticed by a decrease in gas production from 70 to 61 1/d and an increase in effluent acetic acid and propionic acid concentrations to 80 and 64 mg/1, respectively, following an increase of effluent C O D from 500 to 643 mg/1. T h e influent concentration was decreased to 28.5 g C O D / 1 until steady-state was re-established in 20 days and then increased to 41.1 g C O D / 1 . A n instability appeared again and finally the reactor was entirely upset.  This apparently indicated that the system was overloaded  and the influent strength of about 38 g C O D / 1 appears to be a barrier or threshold for this system.  Similar findings were reported by Switzenbaum and Danskin (1982) when  they treated cheese whey by using an expanded bed reactor.  T h e C O D reduction was  decreased from 83% to 58 % and the process became unstable when they increased the influent concentration from 5 to 20 g C O D / 1 (Switzenbaum et al 1982). It was suggested that in treating high strength whey the physical balance between the methanogens and the hydrogen and acid-producing bacteria was more easily upset in this system. This will be the main topic of this thesis and will receive further consideration in a later chapter.  5.5  5.5.1  GAS PRODUCTION  T h e Effect of Influent C o n c e n t r a t i o n  In this part of the study, the reactor was operated at a constant H R T of 5 days, and the influent C O D concentration, and therefore O L R , was varied. Biogas production rate and  Table  5.3  C O D Balance  (/)  (2) Influent  Influent concentration  {mgCODd' ) 1  (mgCODr*) 4 780 9 934 17725 28 700  (3) Effluent concentration  W  Effluent {mgCODd-')  (5)  CH\ production {mgCODd'')  «$)  (7)  Ctf in effluent Total COD out (mgCODd' ) {mgCODd- ) t  1  1  (8) ,(9) Sludge formed Sludge accumulation factor (mgCODd- ) 1  (mgCODl-')  13623 28312 50515 81795  132 191 286 457  376 544 815 1304  The above parameters were calculated as follows: (2) = 2-85 * (1), 2-85(1 .d) is the amount of feed (4) = 2-85*(3) (5) 1 g COD = 395 ml C H * at 32°C (6) assume effluent is saturated with C H at 32-8ml C H . L (7) = (4)+ (5)+ (6) (8) = (2)-(7) (9) = (8)/[(2) - (4)]. Assume 10 mg solid = 1-42 mg COD 4  (mg VSSformed/ mg COD removed)  9885 23447 41848 69049  235 235 235 235  10496 24228 42898 70 587  3 127 4084 7618 17 208  0166 0104 0108 0098  .  Chapter 5. START-UP AND EFFECTS  OF PROCESS  PARAMETERS  72  methane composition are presented in Table 5.4. A plot of gas production rate in terms of liters of methane produced per gram C O D added per day as a function of the influent concentration is shown in Figure 5.11.  The  production rate of methane was increased with increasing influent C O D concentration up to a concentration of 28.8 g C O D / 1 , then the trend reversed.  T h e methane production  rates ranged between 0.219 and 0.313 1/g C O D d. Figure 5.12 position.  demonstrates  the effect of influent concentration on the methane com-  It has been believed that gas composition is a function of the nature of  the biodegradable portion of the feed.  It would be an interesting study to relate the  biodegradable portion of substrates to the methane composition. bohydrates yields C0  2  and CH  4  in equal quantities.  Degradation of car-  A higher proportion of CH4 is  generated from proteins and fatty substances, and this may reach a level as high as 75% methane and 25% carbon dioxide.  A high C 0  2  content in the gas phase in this sys-  tem (up to 45% and higher) indicates the domination of acidogenic fermentation over methanogenesis. In general, a lower influent C O D concentration yields a higher methane composition in the produced biogas. This implies that the dominance of acidogenesis over methanogenesis is enhanced by an increase in substrate strength in the cheese whey anaerobic process. Therefore, it could also be possible to develop a useful technique based on this phenomena for quickly determining stability or to monitor any stress in an anaerobic system from the spectrum of produced biogas composition since the methane composition is such a sensitive parameter which responds to any environmental change and reflects the reactor operation. T h e methane in the produced biogas rapidly diminished from 56% down to 48% with an increase in influent concentration up to a certain level (9.9 g C O D / 1 ) . There was little change in biogas methane composition with a further increase in influent concentration  Or  CO  Table 5.4  jjj  :  Gas Production Rate and Composition for Different Influent Concentration at 5 days H R T Influent concentration (g COD litre-')  Organic loading  Gas  rate (g COD litre' day-')  composition (CH %)  4-56  091  7-30 9.94  1-36 1-97 3-56 4-20 5-96 7-77 8-14  17-7 21-5 28-8 38-1 41-1  1  4  Gas production (litres biogas litre''  56-1 51-5 48-2 47-0 46-6 46-1 42-5 41-0  ^  day' )  2-45 4-60 6-73 12-4 15-3 20-8 265 23-9  1  (litres biogas g-' COD day' ) 1  0-537 0-630 0-677 0-647 0-714 0-721 0-705 0-581  g'  1  (litres CH, COD day' ) 1  0-282 0-302 0-304 0-305 0-310 0-311 0-3000-222  I o  O  I  co  ?  I  I8  Chapter 5.  START-UP AND EFFECTS  Figure 5.11:  OF PROCESS PARAMETERS  Effect of Influent Concentration on Methane Production  74  Chapter 5.  START-UP  Figure 5.12:  AND EFFECTS  OF PROCESS  PARAMETERS  Effect of Influent Concentration on Biogas Composition  Chapter 5. START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  76  to 28.8 g C O D / 1 . T h e methane composition decreased when the influent C O D was raised to more than 28.8 g C O D / 1 . It showed that no simple linear relationship exists between the gas composition and the influent concentration. The average methane production rate was about 0.32 compositions decreased after the influent concentration g C O D / 1 (loading rate great than 6 g C O D / l - d ) .  1/g C O D - d .  T h e methane  was raised to more than  28.8  A t this loading rate, instability was  observed. The highest methane production rate of 9.57 1 CH  4  / l feed d was obtained at  a loading rate of 6 g C O D / 1 d and an influent concentration of 28.8 g C O D / 1 .  5.5.2  T h e Effect of H y d r a u l i c R e t e n t i o n T i m e ( H R T )  In this part of the study, the U A S B reactor was first tested at an influent concentration of 20.5 g C O D / 1 , while the operating H R T was varied from 24.7 to 4.9 days. T h e experiment was then conducted over the same range of H R T s with a higher feed concentration  (41.1  g C O D / 1 ) . The methane production rates are summarized in Tables 5.5 and 5.6. The methane production rate was increased with increasing H R T , which agrees with previous research (Preffer, 1974). Figure 5.13 shows the relationship between methane production rate and H R T . This study gave almost the same results as were reported by Eckenfelder and Ford that at 22.5 days H R T , the methane production rate was almost twice that at 8.8 days H R T . A more interesting finding was that there is an interaction between H R T and feed strength.. In other words, the effect of H R T was related to influent concentration.  At  H R T s longer than 10 days, the methane production rate was similar for two influent concentrations as shown in Figure 5.13.  A t short H R T s , the effect of H R T on methane pro-  duction rate was more pronounced for the higher influent concentration (41.1 g C O D / 1 ) than for the lower influent concentration (20.5 g C O D / 1 ) . T h e methane production rate  Chapter 5.  START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  77  decreased slightly from 0.356 to 0.341 1 CH^/g C O D - d at an influent concentration of 20.5 g C O D / 1 when H R T was decreased from 10.1 to 6.8 days. However, under the same range of operating H R T , a sharp decrease in methane production rate from 0.376 to 0.249 1 CH /g A  C O D - d was observed for tests with the influent concentration of 41.1 g C O D / 1 .  T h e results also indicated that for a given H R T , a higher methane production rate (1 CH /g 4  C O D d) was obtained at a lower influent C O D concentration at H R T s  shorter  than 10 days. T h e effect of H R T on methane production rate can be represented by the slopes of the linear equations.  for Co=20.5 g C O D / 1 Gp = 0.0090 + 0.292  (5.1)  for Co=41.1 g C O D / 1 , 9 > 10 days Gp = 0.0100 + 0.286  (5.2)  for Co=41.1 g C O D / 1 , 9 < 10 days Gp = 0.0270 + 0.107  (5.3)  where $=hydraulic retention time, days Co=influent concentration, g C O D / 1 Gp=methane production rate, 1 CH /g 4  COD d  Equations (5.1) and (5.2) showed similar slopes and intercepts at H R T s longer than 10 days for both influent concentrations.  Equation (5.3) has a slope 2.7 times greater than  T a b l e 5.5 Methane Production Rate at an Influent Concentration of 20-5 g C O D litre"  HRT (days)  24-7 23-1 16-5 10-1 6-8 5-2  Influent concentration (gCOD litre'') 18-2 18-2 20-2 20-0 20-5 21-0  Organic loading rate (g COD litre-' day-') 0-74 0-79 1-23 1-98 3-01 4-08  Gas composition (CH %) 4  50-6 50-6 48-5 47-4 47-0 46-5  1  Gas production (litresgas litre-' feed day'') 190 19-2 18-4 15-9 160 154  (litres gas g~ (litres CH g-' COD day-') COD day-') 1  1-021 1-054 0-909 0-807 0-780 0-731  4  0-492 0-497 0-411 0-356 0-341 0-317  Table 5.6  Methane Production Rate at an Influent Concentration of 41-1 g C O D litre"  HRT (days)  23-9 10-8 7-1 6-0 5-0  Influent concentration (g,COD litre'') 41-1 4M 4M 41-1 41-1  Organic loading rate (g COD litre' day' ) 1  1-73 3-82 5-84 6-91 8-21  1  Gas composition (CH %) 4  49-7 46-5 44-7 43-2 41-0  •  1  Gas production (litresgas litre' feed day'')  1  43-3 34-5 27-1 25-2 23-9  (litres gas g' COD day'') 1-053 0-846 0-658 0-618 0-581  1  (litres CH g'' COD day' ) 4  1  0-490 0-367 0-274 0-249 0-222  Chapter 5. START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  Hydraulic Retention T i m * (days)  Figure 5.13: Effect of H R T on Methane Production  Chapter 5. START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  81  that of equation (5.2), and the methane production rates decreased rapidly when the reactor was fed with an influent concentration of 41.1 g C O D / 1 . This dramatic decrease in the methane production rate indicates some inhibition of the methanogenesis, a fact supported by the V F A s data in Table 5.7. T h e concentration of V F A s generally increases with a decrease in H R T or an increase in organic loading rate.  There was a surge of  propionic acid when the H R T was decreased from 10 to 7 days. As the H R T was further decreased, propionic acid concentration increased, followed by an increase in acetic acid. T h e effect of H R T on methane composition is presented in Figure 5.14.  As with  biogas production, the methane in the biogas decreased as the H R T decreased.  5.5.3  T h e E f f e c t of O r g a n i c L o a d i n g R a t e ( O L R )  Figure 5.15 shows that at a constant influent C O D concentration the methane production rate decreased with an increase in organic loading rate (a decrease of H R T ) . A t an O L R less than 4 g C O D / 1 d, a higher influent concentration resulted in a higher methane production rate. Longer HRTs led to higher methane production rates at a similar O L R (Table 5.8).  When the O L R was greater than 4 g C O D / 1 d, an increase in influent  concentration or a decrease in H R T resulted in a decrease in the methane production rate.  T h e observed effects of O L R on biogas production were in good agreement with  the findings of a number of investigators. experimental results.  For example, Varel et al had quite similar  Studying methane production from beef cattle waste, Varel et  al (1980) found that for a given V S loading rate, higher methane production rates are possible at higher influent V S concentrations and longer H R T up to an influent V S concentration of about 8%. At a constant H R T of 5 days, a change in influent concentration resulted i n a small change of methane production rate, which remained relatively constant up to an influent  Co  Table 5.7  V F A in the Reactor and Effluent at Differential H R T  Influent COD HRT VFA at 60 cm in the reactor (mg litre'') VFA in the effluent (mg litre'') COD Removal (g COD litre-') (days) (%) Acetic Propionic Iso-Butyric Butyric Acetic Propionic Iso-Butyric Butyric 20-5  41-1  j  23-8 .16-4 101 6-8 5-8  18 20 23 22 45  0 0 0 2 14  0 0 0 0 0  0 0 0 0 0  10 5 15 26 10  0 0 0 0 0  0 0 0 0 0  0 0 0 0 0  99 99 98 98 98  23-8 10-4 6-8 5-9 5-0  29 278 266 993 556  20 762 1204 1636 2231  4 0 0 168 76  0 0 0 809 158  10 6 54 398 208  3 0 838 1252 1793  0 0 0 111 57  0 0 0 0 0  99 95 92 86 81  § o o ^' o co CO  2  00  Chapter 5.  START-UP AND EFFECTS  OF PROCESS  PARAMETERS  55  •  influent 20.5 g COD I '  1  52-  o c o  49-  to  o a E  o O  46-  co co  (5  43-  O  40-  12  i 16  —r~ 20  -r~ 24  Hydraulic Retention Time (days)  Figure 5.14:  Effect of H R T o n  Biogas  Composition  83  •s T a b l e 5.8  to  ?  Effects of Influent Concentration and H R T on Gas Production Rate for Similar Organic Loading Rate Gas production  Organic loading rate (g COD litre-' day' )  Influent concentration (g COD litre' )  HRT (days)  0-90  4-56 18-2  5-0 23-0  7-30 20-2  5-0 16-4  9-85 200  5-0 10-1  41-1 21-0  23-9 5-1  46-5  1-053 0-731  41-1 28-1 411  10-8  46-6 46-1 44-7  1  0-79 1-36 1-23 1-92 1-97 1-73 4-08 3-82 5-96 5-84  1  Gas composition (CH %)  (litres gasg-' COD day-')  56-3  0-537  0-302  50-6 51-5 48-5 48-2 47-4 49-7  1-054 0-630 0-888 0-678 0-806  0-533 0-324  a  0-431 0-327 0-382 0-524  o  0-846  0-340 0-394  o  0-723 0-658  0-333 0-294  4  5-0 7-1  ^  §  (litres CH g ' 4  1  COD day '')  I  co  CO 2 2 El  oo  Chapter 5. START-UP AND EFFECTS  concentration  OF PROCESS PARAMETERS  of 28.8 g C O D / 1 , then decreased  (see Table 5.5 and Figure 5.16). T h e  highest methane production rate of 9.57 1 CH /\ feed-d (0.33 1 CH /g 4  85  4  C O D ) was obtained  at an O L R of 5.96 g C O D / l - d and influent concentration of 28.8 g C O D / 1 (Table 5.2). These results imply that the reactor can be operated at short H R T s , as long as the O L R does not exceed 6 g C O D / l - d . A simple linear relationship between O L R and methane production in terms of liters CH  4  5.6  per liter reactor per day was found in O L R range of 2 to 8 g C O D / l - d (Figure 5.16)  TREATMENT  EFFICIENCY  T h e highest C O D removal efficiency for raw whey treated in a chemostat (Clanton et al. 1985) was only 58% for a completely-mixed anaerobic reactor. Wildenauer and Winter (1985) achieved a C O D removal of 95%, close to the results of this study with the help of pH-control, which maintained the p H at about 6.7. Without p H control in the whey digestion process, lower organic loading rates were usually applied to the reactor and relatively lower C O D reductions were obtained as indicated in Table 8-2. In this study, the U A S B process accommodated fairly well to whey strength up to 28.8 g C O D / 1 and maintained a C O D reduction of over 97% . These results indicated that the U A S B reactor can tolerate a higher wastewater strength although this type reactor was supposed to be best for dilute wastes, typically under 20 g C O D / 1 and at moderate O L R .  Chapter 5.  START-UP AND EFFECTS  Figure 5.15:  OF PROCESS  PARAMETERS  86  Effect of Organic Loading Rate on Methane Production  Chapter 5.  START-UP AND EFFECTS  Figure 5.16:  OF PROCESS  PARAMETERS  Relation Between Methane Production and O L R  87  Chapter 5.  5.7 1.  START-UP AND EFFECTS  OF PROCESS  PARAMETERS  88  SUMMARY T h e performance of the U A S B reactor was evaluated in the range of 4.5 to 38.8 g  C O D / 1 of cheese whey influent concentrations results of the present experiments  at a 5 days hydraulic retention time. T h e  have shown that anaerobic digestion using a U A S B  reactor can be an efficient treatment method for diluted cheese whey. Over 97% C O D removal was achieved.  Without p H control and nutritional addition, the system could  treat cheese whey successfully up to a concentration of about 29 g C O D / 1 . 2. It is known that reactor performance strongly depends on the start-up procedure. Various start-up strategies were used to facilitate the start-up of an U A S B reactor and ensure stable operation.  Among the operating parameters, sludge loading rate was the  most important during start-up. In the very beginning, the initial sludge loading should not exceed 0.25 g C O D / g V S S d. 3. V F A s in the effluent were found to be a very useful indicator for primary adaptation of the sludge and for monitoring the system's stability. increased only after the V F A concentrations  T h e loading rate should be  are greatly reduced . Too rapid an increase  of O L R may result in the loss of activity of the sludge. 4.  T h e methane production rate increased with increasing H R T . At H R T s longer  than 10 days, the methane production rate was similar for two influent concentrations. At short H R T s , the effect of H R T on methane production rate was more pronounced for the higher influent concentration (41.1 g C O D / 1 ) than for the lower influent concentration (20.5  g COD/1).  For a given H R T , a higher methane production rate (1 CH /g 4  was obtained at a lower influent C O D concentration 10 days.  COD-d)  and at those H R T s shorter  than  From the point of view of fuel gas production, the organic loading rate was  a critical parameter.  At an O L R less than 4 g C O D / l - d , the reactor fed with a higher  influent concentration yielded a higher methane production rate. When O L R was greater  Chapter 5.  START-UP  AND EFFECTS  OF PROCESS  PARAMETERS  89  than 6 g C O D / l - d , the higher influent concentration or shorter H R T produced a lower methane production rate.  Therefore, the optimal O L R for this particular system with  regard to methane production would be between 4-6 g C O D / l - d .  For a H R T of 5 days,  the optimal influent concentration should be between 20-30 g C O D / 1 . 5.  W h e n the influent concentration was increased to 38 g C O D / 1 ,  observed.  instability was  For this system the influent concentration should be maintained below 30 g  C O D / 1 at H R T of 5 days. Further studies were emphasize a search for the reasons for the inhibition caused by high influent concentrations and to seek an efficient way to prevent instabilities.  Chapter 6  DISTRIBUTIONS O F S L U D G E A N D S U B S T R A T E S  6.1  INTRODUCTION  T h e U A S B process has been widely investigated since it was developed. A great number of research papers which have been published each year reveal that it is an effective process for anaerobic wastewater treatment.(Lettinga  et al.1985, 1984, 1983, 1979; Wang  et al.  T h e treatment  1985;  W u et al.  1985;  Sayed et al.1984).  of cheese whey in  a U A S B reactor has further demonstrated that the easily acidified substrates, such as cheese whey, can be treated by using an U A S B reactor, if the proper start-up procedure is used. Satisfactory treatment efficiencies have been obtained (Yan et al. 1989). In order to describe and optimize the U A S B process, various models have been proposed to explain the kinetics of anaerobic digestion in a U A S B reactor,  which include  the fluid flow pattern, the kinetics of substrate conversion and bacterial growth, and the sludge distribution and behavior in the reactor (Bolle et al.1986a, 1986b; Buijs et al.1982, 1980;  Heertjes et al.1978,1982; Ven der Meer et al. 1983). However, the substrate dis-  tributions in the reactor have not been reported, in spite of their obvious importance for better understanding and for optimizing the process. Such a procedure is time and effort consuming and can be tedious because of the huge number of experiments and analyses that must be performed to obtain the details of the profiles. This study was motivated by the surprising shortage of data about the substrate distribution which is needed for modelling and optimization.  90  Chapter 6. DISTRIBUTIONS OF SLUDGE AND SUBSTRATES  In this part of the research, therefore,  91  an extensive study of the profiles in a U A S B  reactor, i.e.the distribution of the sludge, C O D , V F A s and p H under a wide spectrum of operating conditions was conducted.  There were 5 different operating conditions, in  which the influent C O D was increased stepwise from 5 to 40 g C O D / 1 at a H R T of 5 days. For each operating condition, samples were taken from the influent, the corresponding effluent and 10 sampling ports mounted along the column of the reactor. This study was originally designed, as was stated above, to gain detailed information about the sludge and substrate distributions in the U A S B reactor and to serve as the basis of future modelling research, and to increase the understanding of the U A S B process.  It  was also expected to provide information about the cause of the instability of the process which can result in a rapid upset.  As these experiments  progressed, it was found that  the profiles of the substrates truly did provide much information about the instability mechanisms, which will be discussed in this chapter. in Table 6.1  have shown definitively that two reaction  methanogenesis  6.2 6.2.1  T h e results which' are summarized stages, i.e.  acidogenesis  and  could be distinguished in different regions in the same reactor.  RESULTS Distribution and Behaviour of the Sludge  The profiles of sludge concentration at different influent concentrations Figure 6.1.  are presented in  The curves show that two sludge regions exist in the reactor.  T h e dense  sludge phase was retained in the lowest part, below 30 cm from the bottom, constituting a sludge bed with VSS of 18 to 56 g/1. In this zone, the sludge concentration varied with the location.  For example, at 4 cm height, the sludge content was 35 g V S S / 1 for an  influent of 28.8 g C O D / 1 , while the sludge concentration was 25 g VSS/1 at 25 cm height at the same influent concentration.  Above 37 cm height (sampling port 4), there was  Chapter 6.  DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  92  a sludge blanket. The average V S S concentration in this area ranged from 2 to 10.g/1, depending on the loading rate. Unlike the sludge in the bed, the sludge concentration in the blanket was constant and quite homogeneously distributed. As indicated in Fig.6.1, the plots of sludge concentrations in the blanket (above 38 cm) vs. the reactor height were horizontal lines parallel to the x axis. The results indicated that, in the course of the experiment, the sludge in the blanket was completely mixed, but the sludge in the bed was not well mixed. The mixing, which was brought about by gas evolution, might be insufficient under these experimental conditions in the lower zone, although the biogas production was as high as 75 1/d which equals 0.30 m / m - h . 3  2  Generally, when the organic loading was increased, the sludge bed and blanket both expanded upward, as the result of gas lift and sludge settleability deterioration.  As  loading was being increased, more gas was produced, creating more flotation to lift the sludge upward.  At the lowest influent concentration of 4.5 g C O D / 1 , the sludge bed  occupied as little as one eighth of the total working volume of the reactor (below 13 cm from the bottom).  W i t h an increase i n the influent concentration, mainly as the result  of the increase in the gas production, the sludge bed extended to the upper part of the reactor. T h e sludge bed reached a height of 25 cm when the influent concentration was increased to 9.93 g C O D / 1 . W h e n the loading rate was increased to such an extent that it exceeded the sludge digestive capacity, the sludge would not be able to maintain its vitality. In effect, its settleability deteriorated.  Hereafter, poorly settled sludge tended  to be suspended. It was particularly true in the case of an influent concentration of 38.1 g C O D / 1 . A large amount of floating sludge was collected in the effluent at this time. It was common when the reactor was subjected to a new higher organic loading rate, that the increase of gas production was followed by a surge of sludge wash out due to the sudden increase in floatation. If the new operating conditions were within the capacity of the reactor, a new adaptation and stabilization would be re-established, resulting in a  Chapter 6.  THE DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  Table 6.1: the Distribution of Sludge and Substrates  Influent  Height VSS  g COD/I  cm  COD  g/1  mg/1  4.56  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  26.18 19.04 5.42 1.96 1.69 1.51 1.42 1.39  3390 800 570 410 400 370 370 330  9.93  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  35.92 18.18 14.38 5.23 3.96 3.16 2.76 2.65  7520 330 290 240 230 220 220 220  17.70  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  28.80  38.10  P  H  AA  PA  BA  COD  mg/1  mg/1  mg/l  Removal  382 152 162 50 45 48 120 112  92 60 100 56 52 56 60 44  480 58 0 0 0 0 0 0  0.26 0.82 0.88 0.91 0.91 0.92 0.92 0.93  4.52 6.40 6.48 6.68 6.65 6.69 6.68 6.66  688 96 60 194 96 338 82 30  134 1140 14 14 10 0 0 0 0 0 0 0 0 0 0 0  0.24 0.97 0.97 0.97 0.98 0.98 0.98 0.98  31.12 10940 20.50 560 18:55 590 6.19 350 4.96 380 4.74 400 4.73 370 4.59 340  4.40 6.50 6.54 6.72 6.72 6.70 6.71 6.68  876 20 22 32 20 24 16 18  290 1454 3 0 3 0 0 0 0 0 0 0 0 0 0 0  0.38 0.97 0.97 0.98 0.98 0.98 0.98 0.98  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  35.39 15300 32.11 970 25.07 700 7.62 520 9.35 500 7.77 480 7.60 480 7.87 440  4.50 6.90 7.05 7.10 7.10 7.10 7.10 7.15  1166 40 18 20 18 16 22 18  748 36 34 0 0 0 0 0  0.49 0.97 0.97 0.98 0.98 0.98 0.98 0.98  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  56.56 31500 38.20 35250 39.77 33240 31.43 2640 3.38 2760 4.84 2760 3.26 2790 2.69 2690  2.89 3.12 3.12 6.70 6.70 6.70 6.75 7.20  2685 231 2895 468 2883 537 702 1336 596 1192 396 846 376 722 262 694  243 255 495 108 160 44 2 20  0.17 0.07 0.13 0.93 0.93 0.93 0.91 0.91  93  Chapter 6.  THE DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  70  Figure 6.1: Profiles of Sludge at Different Influent Concentrations  94  Chapter 6.  DISTRIBUTIONS  OF  SLUDGE  AND  SUBSTRATES  95  new balance between sludge and substrates. Figures 6.2 and 6.3, which show the concentration of the sludge at each location for different influent concentrations, illustrate that the sludge moved upward with an increase in the influent concentration.  For example, the portion of sludge at 4 cm height decreased  from 41% for the influent concentration  of 4.56 g C O D / 1 to 29% for an influent C O D  of 28.8 g/1, which is different from the higher location of the reactor, at 25 cm height, rhere the sludge increased from 9% to 19% for the same range of influent concentration change. T h e relation between the sludge distribution and the gas production is shown in Figure 6.4.  and Table 6.2. T h e sludge concentration in the bed did not change significantly with  gas production, which is indicated by the V S S concentration at sampling ports 1 and 2 in Figure 6.4a, while the sludge concentration in the blanket varied with the gas production (Figure 6.4c).  T h e most significant effect of gas production on the sludge distribution  was observed in the area of sampling port 3, which is at the junction between the bed and the blanket.  G o o d linear relations between the sludge and gas production in the  blanket, which are shown in Figure 6-4c, were fitted with the following equations: for the area between the bed and the blanket (Figure  X = 8.710 + 5.30 for the blanket (Figure  6.4b)  (6.1)  6.4c)  X = 3.50 + 0.7  (6.2)  where X is the sludge. concentration in g V S S / 1 and 0 is the biogas production 1/d. T h e greater slope of equation 6.1 compared to equation 6.2 indicates the more significant  Chapter 6.  THE DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  4«-i  Reactor Height (cm)  Figure 6.2: Sludge Distribution in the U A S B Reactor  96  Chapter 6.  THE DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  40-i  Reactor Height (cm)  Figure 6.3: Sludge Concentration in the U A S B Reactor  97  Chapter  6.  THE DISTRIBUTIONS  OF SLUDGE  AND  SUBSTRATES  A: Sludge in Bed  </>  iS) >  3<H  o o  2 o  2<H  €>  TJ  •r  io  CO CO  •  somple port $1  O  somple port  #2  C: Sludge in the Blanket  >  c o  6H  o c c o  9  « ° ™ P * * port  ^)  s o m p l o port  #5  *  perl  #6  Port  #8  O  l  o  m  p  l  o>  ^7  »  3  ^  » o m p l * port  ^  o  10  20 30 40 Gas Production  o  m  P * *  50  #4  60  #10  70  (Id)  Figure 6.4:! Sludge Distribition versus the Gas Production  98  Table 6.2: Relation between Sludge Distribution and the Biogas  Input g COd/l,  Biogas l/d  '  1#  2#  SludgeConcentration g vss/i  3#  4#  5#  6#  8#  10#  8 1 I 3 O  §  4.56  6.96  26.18  19.40  5.43  1.96  1.69  1.51  1.42  1.39  9.93  19.11  35.92  18.18  14.38  5.23  3.96  3.16  2.75  2.65  17.73  35.10  34.58  20.50  18.55  6.19  4.96  4.74  4.73  4.59  Co  28.70  59.02  35.39  32.11  25.07  7.62  9.35  7.77  7.77  7.80  CO  to  Chapter 6. DISTRIBUTIONS  OF SLUDGE  100  AND SUBSTRATES  effect of gas flow rate on the sludge distribution in the area between the bed and the blanket than in the blanket.  6.2.2  G r o w t h of Sludge  T h e total amount of sludge in the reactor was determined by sludge profiles over the height of the reactor for each experimental condition. There was a net increase in V S S concentration  in the reactor with loading rate as is shown in Table 6.3.  The small  amount of biomass formation at the beginning was attributed to the low food/sludge ratio of 0.164 g C O D / g V S S d. A significant increase in V S S in the lower regions of the reactor took place only after the influent concentration was increased to 17.7 g C O D / 1 , corresponding to a sludge loading rate of 0.547 g C O D / g V S S . These results together with the process operating conditions, which are presented in Table 6.3, provided the possibility of calculating the biomass yield coefficient Y and the decay constant K d using the following model:  (6.3)  where Y i s the yield coefficient in terms of g V S S / g C O D , X is the sludge concentration in the reactor in term of g VSS/1 and K d is the decay constant of the biomass. A plot of ( d X / d t ) / X against ( d F / d t ) / X gave a straight line with Rsq of 0.8 (Figure 6.5), from which the yield coefficient Y and the decay constant K d can be derived (see Table E . l ) . They are 0.058 g V S S / g C O D and 0.02 d' , 1  respectively.  T h e observed yields calculated from the C O D balance (see chapter 5) over the whole  Chapter 6. DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  101  experimental period (0.098 to 0.166 g T S S formed/g C O D removed) agree quite well with the sludge growth yield of 0.058 g V S S / g C O D as estimated from the sludge growth kinetics.(The ratio of VSS to T S S is about 0.49).  6.2.3  P r o f i l e s of C O D , V F A a n d p H  C O D , V F A and p H were monitored at influent concentrations of 4.56, 9.93, 17.1, 28.8 and 38.1 g C O D / 1 , (pH was not measured at an influent concentration of 4.56 g C O D / 1 ) . T h e p H , acetic acid, propionic acid and C O D profiles are presented in Figures 6.6, 6.7, 6.8, 6.9 and 6.10, respectively. Each curve represents the effect of different influent concentration at steady state except for a concentration of 38.1 g C O D / 1 . Below- 4 cm, the p H was in the range for 4 to 5, V F A concentrations  were high (up  to 2895 mg/1 of acetic acid) and C O D reduction was between 17 to 49%, depending on the activity of the sludge and the influent concentration.  Above 12 cm, the p H increased  to 6.4 and the volatile fatty acid decreased to 100 mg/1 or less. More than 60% of total C O D reduction occurred between 4 cm and 12.5 cm above the reactor bottom except for an influent concentration of 38.1 g C O D / 1. T h e two completely different sets of p H C O D and V F A s values demonstrate that two separate reaction phases: acidogenesis and methanogenesis were established in the reactor. T h e acidogenic phase was in the bottom below 4 cm, which was indicated by lower p H , higher V F A and lower C O D reduction (Figure 6.11). Above 4 cm, methanogenesis took place. This was demonstrated by higher p H , lower V F A s and high C O D removal. So far, in anaerobic digestion studies, phase separation has been accomplished in two separate reactors by controlling the p H and dilution rate. It is believed that this is the first time that the two phases were reported in the same reactor. this would be true for all substrates in a plug flow reactor. using a U A S B reactor to treat baker's yeast wastewater  It was thought that  Interestingly enough, when  in the same lab, two distinct  Table 6.3: Sludge in the U A S B Reactor  OLR  Input  Sludge  Ratio  Sludge  Sludge Lost in Effluent  Sample  growth  g VSS  g C O D / g VSS  g VSS  g VSS  g VSS  5.00  86.5  0.164  -  -  -  0.91  4.56  133.6*  0.099  22.36  -  3.06  1.97  9.93  107.4  0.262  20.11  13.58  7.37  3.54  17.7  91.7  0.547  4.87  17.87  7.05  5.96  28.7  114.2  0.711  2.32  13.72  38.46  7.77  38.1  164.9  0.654  2.52  13.92  67.14  g COD/1 d g COD/1  * Add 67.23 g VSS of sludge to digester at day 15.  Chapter 6. THE DISTRIBUTIONS  OF SLUDGE AND  0.8  Figure 6.5:  Sludge G r o w t h  SUBSTRATES  Chapter 6.  THE DISTRIBUTIONS  OF SLUDGE AND  Figure 6.6: p H Profile  SUBSTRATES  Chapter 6.  THE DISTRIBUTIONS  OF SLUDGE AND SUBSTRATES  105  Chapter 6.  THE DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  106  Influent O 4.56 o coo I" •  9.93 o COO  A  17.1 a COD  X V Eaocfor H*lgM (oO  Figure 6.8:  Profile of P r o p i o n i c  Acid  f  r  28.8 a COO l " 38.1  Q COO r  Chapter 6.  THE DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  Influent  O  4.56 o COD i"  •  8.93  g COD r' A t7.1 g COD I" X 28.8 g COO I'' V 38.1 g COD I''  —J— 20  —T— •40  —r60  —r80  R«actor Height (cm)  Figure 6.9:  • Profile of C O D  — I —  100  120  Chapter 6.  THE  DISTRIBUTIONS  Figure 6.10:  OF SLUDGE  AND  SUBSTRATES  Profile of C O D R e d u c t i o n  108  Chapter 6. DISTRIBUTIONS  phases were not observed. characteristics  OF SLUDGE  AND  SUBSTRATES  109  The different results could be due to the inherent chemical  of the substrates.  Anaerobic digestion is a biological process in which a  series of parallel and consecutive reactions take place.  From an oversimplified point of  view, it has been accepted that only two major steps, acidogenesis and methanogensis, are considered essential, and generally, the second one is extremely slow and therefore is the rate-controlling step. If the two major steps remain in balance, the intermediate products, i.e. V F A s , would not be detected.  Therefore, two phases wouldn't be seen in  one reactor. It is only possible to observe the two phases in cases in which the reaction rates of the two steps are very different. In other words, the observation of two phases in one reactor is only possible for some particular substrates, such as cheese whey which is easily converted into short chain acids by acidogenic bacteria. W h e n more fatty acids are formed than can be converted, V F A s accumulation occurs and the p H drops. The accumulation of V F A s in the first step being faster than the assimilative capacity in the second step creates a distinct acidogenic phase. T h e backer's yeast wastewater contained high concentrations of hard-to-degrade organic material that could not be easily acidified. In contrast, whey has a tendency of rapid acidification. T h e observation of two phases indicates that the anaerobic system using whey was not maintained in dynamic balance even at very low organic loading rates even though the overall system, from the effluent analyses, appears to be very stable at influent concentrations below 28 g C O D / 1 . W i t h an increase in influent concentration, the V F A s and C O D in the reactor gradually increased. T h e curves for C O D , acetic acid, propionic acid and p H distribution as a function of the height didn't change markedly until an influent concentration of 38.1 g C O D / 1 was applied . At this condition, the acidogenic as well as the methanogenic zones extended upward. Much higher C O D , acetic and propionic acid concentrations were accumulated at the bottom.  These high concentrations  also extended to a height of 37.5  cm above the reactor bottom. For example, the p H value remained around 3 at a height  Chapter 6. DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  110  of 37.5 cm. In particular, propionic acid concentrations remained high throughout the reactor (Figure 6.11). Low p H values (below 3.2) were also observed in this region. Consequently, the overall reactor performance was affected. T h e process became unstable 14 days after the reactor was initially fed at this loading. This was indicated by a decrease in gas production from 67 to 61 liters/ day, and an increase in effluent C O D from 55 to 643 mg C O D / 1 and also an increase in effluent acetic and propionic acid concentrations to 80 and 64 mg/1, respectively. T h e upward extension of the acidogenic as well as the methanogenic zones causes the intrusion of the acidogenic phase into the region previously occupied by methanogens. T h e methanogens, previously highly active, in this region could be rendered inactive under the acidic environment. Moreover, the methanogens could not be easily replenished in a newly established methanogenic phase to counteract the accumulation of V F A concentrations due to the very slow growth rate of the anaerobes.  It can be predicted that  the acidogenic region will extend into the upper portion of the reactor as the substrate loading is increased until the whole region is occupied by the acidogenic reaction and fermentation fails. This is the bottleneck of a suspended growth system. In general, the maximum influent concentration accepted in the U A S B process has been 30 g C O D / 1 to the best knowledge of author based on a literature search, even for those substrates which were not quickly acidified. W i t h an increase in influent concentration, V F A and C O D in the reactor increased. In other words, more of the V F A s produced in the first step accumulated.  This could  indicate that the rate of acidogenesis increased with the increase in influent C O D . Let the acetic acid concentration of sample port #  1 represent the accumulation of  V F A in the first phase. The difference in acetic acid between # the degradation capacity of V F A in the second phase (Table 6.4).  1 and #  2 represents  T h e requirement for  maintaining the anaerobic system in a dynamic balance is that the degradation capacity  Chapter 6.  DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  111  of V F A in the second phase is greater than the accumulation of V F A in the first phase. Based on this idea, the best influent concentration can be found with regard to the system stability. Using linear regression analysis, a set of empirical models for accumulation of acetic acid and propionic acid with increase of influent concentration has been developed which is the best fit to the experimental data (see Appendix A ) .  AA = - 0 . 2 7 + 0.183Co - 0.0102Co + 0.000197Co 2  PA  The  (6.4)  3  = 0.112 - 0.00893Co + 0.00108GV  (6.5)  accumulation and degradation of acetic acid are shown in Figure 6.12.  degradation rate first increased until the influent concentration  The  reached 20 g C O D / 1 ,  then declined. Between 15-28 g C O D / 1 , the degradation curve is above the accumulation curve , which means that in this region the degradation capacity exceeds the accumulation capacity.  Therefore, this would be the optimal influent concentration for a cheese whey  anaerobic fermentation system. This conclusion agrees with the experimental results. The experimental results indicated that the majority of the C O D was reduced below a height of 13 cm in the reactor (more than 80%).  T h e C O D concentration  decreased  from 3.4 g/1 at 4 cm to 0.8 g/1 at 13 cm for an influent C O D of 4.56 g/1, and from 15.3 g/1 to 0.97 g/1 for an influent C O D of 28.1 g/1. T h e rest of volume of the reactor functions as a settler so that the height of the reactor could effectively be reduced from 140 cm to 30 cm.  Chapter 6.  DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  112  From these results the suggested operating conditions and reactor size can be described as follows :  • T h e optimum influent concentration would be 25 to 30 g C O D / 1 • T h e reactor height should be reduced to 40 cm or less for the reactor with a diameter of 12 cm.  6.3  SUMMARY  Profiles of the sludge concentration  showed that two sludge regions, a sludge bed with  high density V S S and a sludge blanket, exist in the U A S B reactor. T h e distribution of the sludge was strongly dependent on the process conditions.  W i t h an increase of the  loading rate, the sludge bed expanded so that the sludge concentration  in the blanket  and also in the area between the bed and blanket, varied because of gas production. T h e two reaction stages: acidogenesis and methanogenesis  were distinguished in the  U A S B reactor by the profiles of the substrates, which indicated that cheese whey is very easily converted to short chain fatty acids and that the rate of the first step is much faster than the second step. T h e appearance of two stages in the same reactor was associated with either the nature of the substrate or process stress and could be attributed to the fact that the rate of V F A s production exceeded the rate of their utilization. T h e optimum influent concentration would be between 25-30 g C O D / 1 . T h e reactor height could be reduced to 40 cm or less. There is an upper influent concentration threshold of cheese whey for stable operation of the U A S B system. If the feed strength is in excess of this threshold value, such as 30 g C O D / 1 at H R T of 5 days, instability occurs because the accumulation of V F A s from the first phase exceeds the degradation capacity of the second phase.  Chapter 6.  THE DISTRIBUTIONS  Figure 6.11:  OF SLUDGE AND  SUBSTRATES  Profiles of p H and V F A s  113  Chapter 6. THE DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  114  Table 6.4: Acetic Acid (AA)  A A at 1#  A A at 2#  A A i -AAo  (g/1)  (g/1)  (g/D  4.56  0.382  0.152  0.23  9.93  0.688  0.096  0.59  17.7  0.876  0.02  0.856  28.8  1.166  0.04  1.126  38.1  2.895  2.553  0.342  Input  (g COD/1)  1# 2#  sample port 1 sample port 2  Chapter 6.  DISTRIBUTIONS  OF SLUDGE AND  SUBSTRATES  Influent concentration (g/IJ  Figure 6.12:  Accumulation and Degradation of Acetic Acid  115  Chapter 7  EFFECTS  7.1  O F SULFATE O NANAEROBIC  GENERAL  DIGESTION  OF W H E Y  REMARKS  High concentrations of sulfate have been thought to be inhibitory to methanogenic bacteria. T h e inhibition of the highly fastidious methane producing bacteria(MPB), due to the presence of sulfate, is usually interpreted in relation to the levels of sulfide produced via the S R B (Lawrence et al 1966 and 1965, Cappenberg 1974, Kroiss et al 1983, Speece et al 1983) . Previous studies have paid more attention to the inhibition caused by sulfate on the anaerobic digestion and several mechanisms have been proposed to explain the inhibitory effect. T h e kinetics of competition for the available electron donors between sulfate-reducing bacteria ( S R B ) and methane-producing bacteria ( M P B ) have received considerable attention,and it has been concluded that the S R B apparently have a higher affinity (lower Ks) for hydrogen and acetate, which are the major methane precursors relative to the M P B (Abrum et al 1978, Kristjiansson et al 1982, Schonheit et al 1982). T h e reason might be the periplasmic location of the hydrogenase of sulfate reducing bacteria (Badziong and Thauer 1980; Bell et al. 1974). Besides, the toxicity of sulfide or free H S produced by microbial reduction of sulfate is also thought to be a factor of primary 2  importance. On the other hand, from the point of view of thermodynamics and hydrogen regulation (Stephen et al 1986, Jack et al 1989), the presence of sulfate appears to help maintain the anaerobic conditions required for the growth of methanogens.  116  Surprising little research  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION OF WHEY 117  has been done on this aspect, but rather, to provide information which supports this idea theoretically.  Motivated by a need to explore the inhibition mechanism caused by high  substrate strength and a desire to improve the stability and efficiency of the system as well, an effort was made to examine the effect of sulfate on system performance.  The  sulfate function in the cheese whey anaerobic fermentation will be the subject in this chapter.  7.2  HYPOTHESIS  It is well known that high organic loading results in an inhibitory effect in the anaerobic digestion of cheese whey. As the preliminary results of Chapter 5 indicated, when influent concentration was increased to 38.1 g C O D / 1 system instability occurred.  The  distribution of substrates in the reactor given in Chapter 6 further provided evidence that the instability was the result of the ease of conversion of cheese whey into short chain V F A s . T h e two major steps, acidogenesis and methanogenesis in anaerobic fermentation of whey, have been shown to have very different rates of metabolism. W h e n the accumulation of V F A in the first step exceeds the capacity of the methanogenesis as influent C O D approaches a threshold, such as 38 g C O D / 1 , catabolism leads to the system failure. A n optimal influent concentration as being found in Chapter 6 can be chosen to avoid the problem. W h e n higher influent concentrations are desirable to achieve the satisfaction of treatment efficiency, however, the question then arises as to how to enhance and control the process stability. Theoretically, the system stability can be enhanced by increasing the activity or concentration of the methanogens, or by inhibiting acidogenic activity, or creating a microbial association which can help to degrade V F A s . p H control was chosen as a reliable method to neutralize acids for maintaining stability  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY 118  of an anaerobic reactor. However, the link between p H and system stability has not been clearly shown.  In addition, other possible strategies have not been explored for the  improvement of the stability of control. Recent studies have shown that molecular H  2  and interspecies  hydrogen  transport  play an important role in anaerobic digestion since anaerobic ,/3-oxidation of long chain fatty acids is considered to be the rate-limiting step for the digestion of soluble substrates (Figure 7.1, Stephen 1986). As previously described (in the literature review), the free energy changes of /3-oxidation are feasible only when the reaction can be " pulled" to the right by the continuous removal of H  2  (Table 7.1, Stephen 1986).  In terms of control  strategies, then it is apparent that operation of the anaerobic reactor at the lowest  H  2  pressure will minimize the accumulation of fatty acids. Inhibition of the M P B by the S R B has been recognized in relation to the value of Ks, which suggests a higher affinity of the S R B toward H  2  (Kristjiansson et al 1982, 1983).  The free energy change for the oxidation of reduced pyridine dinucleotides becomes ever more favorable as the H partial pressure diminishes. T h e H partial pressures 2  2  generated  by the O H P A (obligate hydrogen-producing acetogens) can be kept at a low enough value by associating them with a i ^ - u t i l i z i n g organism, either a M P B or a S R B . Therefore, a hypothesis was proposed that the rate-limiting step (for soluble substrates) for anaerobic digestion, /3-oxidation, or degradation of fatty acids can be enhanced through the presence of sulfate. In other words, a proper amount of sulfate may be applied to moderate the detrimental influence of excess H  2  on a stressed anaerobic  reactor. A study of the effect of sulfate ions (sodium sulfate) in anaerobic fermentation was conducted to determine whether or not they help maintain a favorable environment for methanogens  and how they effect the anaerobic digestion system in terms of methane  production, C O D reduction, p H , V F A and stability of the system.  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION  OF WHEY 119  ORGANIC MATTER carbohydrates proteins  v I ACID- FORMING BACTERIA acetic (o)  -p(B>-pyruvic  t  butyric  butyric acid  (<D propionic  propionic acid •  -s— acetic  acetic  V  ACETOGENIC BACTERIA  CHCOOH  w+ 2  cq  Acetoclastic METHANE BACTERIA  Hj-utilising METHANE BACTERIA  e.g. Hettunosarctna  e.g. Hethanospirillum  CH  bariceri  0 4 +  CO,  hungatei  CH + 2H.0 A  Figure 7.1: T h e M i c r o b i a l E c o l o g y for t h e A n a e r o b i c D i g e s t i o n P r o c e s s (Stephen  1986)  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY 120  Table 7.1: F r e e E n e r g y C h a n g e s o f R e a c t i o n s I n v o l v e d i n M e t a b o l i s m o f S o m e Organic Matter  (Stephen  1986)  A G°(Kcal)  REACTIONS 1. Single culture of H2-producing acetogenic bacteria : A . C H C H C O O - + 3H 0 —> C H C O C r + H C O 3 - + H + + 3 H 3  2  2  3  B . C H 3 C H 2 C H 2 C O O - + 2 H 0 — > 2 C H 3 C O O - + H+ + 2 H 2  C . 2 C H 3 C H O H C O O " + 4 H 0 —-> 3  2  2  2. H2-utilizing  +11.5  2  2CH3COO- +2HCO3- +2H++4H  2  D . C H C H O H + H 0 —>  +18.2  2  C H 3 C O O - + H+ + 2 H  2  -1.9 +2.3  2  methanogens and desulfovibrios :  E.4H + H C O 3 - + H+ —> 2CH + 3H 0  -32.4  F.4H + S 0 = + H+ —> HS; + 4H 0  -36.3  2  4  2  2  4  2  3. Acetate-utilizing methanogens G . 2 C H 3 C O O - + 2 H 0 —> 2  2CH  4  -14.8  +2HCO3-  4. Syntrophic association of coculture : (A+E) 4CH CH COO-+3H 0 —>4CH COO-+HC0 -+H +3CH 3  2  2  3  +  3  4  -24.4  (B+E) 2CH3CH CH COO-+HC0 +H 6—>4CH COO-+CH +H+  -9.4  (C+E) 2CH CHOHCOO--fH 0—>2CH COO-+HC0 -+H +CH  -34.3  2  2  3  3  3  2  2  4  3  +  3  4  (D+E) 2CH CH 0H+HC0 ---->2CH COO-+CH -l-H2O-|-H+  -27.4  (A+F)  -36.1  3  2  3  3  4  4CH CH COO-+3S0 =—>4CH COO-+4HC0 -+H+-l-3HS3  2  4  3  3  (B+F) 2CH CH CH COO-+S0 =—>4CH COO-+H++HS3  2  2  4  -13.3  3  (C+F) 2CH CHOHCOO-+S0 =—>2CH COO-+2HC0 -+H S  -38.2  (C+E+G)  -49.1  3  4  3  3  2CH CHOHCOO-+3H 0—>3CH +3HC03-+H+ 3  2  4  2  Chapter 7. EFFECTS  7.3  RESULTS  OF SULFATE  IN B A T C H  ON ANAEROBIC  DIGESTION OF WHEY  121  EXPERIMENTS  A preliminary experiment was first conducted in batch reactors. T h e details are presented in A p p e n d i x B . A n interesting finding was that the effect of sulfate on the gas composition was related to the feed strength.  At lower feed strengths,  the CH % 4  decreased when sulfate was  added. However, no difference in gas composition was observed at higher feed strengths for both continuous and batch experiments. It would seem that the S R B competed with methane bacteria more effectively at lower substrate concentration. No significant inhibition was observed even when the ratio of C O D to sulfate was as low as 5 and the sodium sulfate concentration was as high as 60 mM/1. This can be attributed to the fact that this substrate had higher solubility and higher feed strength than that used in the previous studies (compared to 0.5 - 1 g C O D / 1 ) .  Using higher  solubility substrates as feed, such as cheese whey, the inhibition threshold concentration might be higher than that of other substrates which have lower solubility since excess hydrogen exists in such systems. Therefore, the critical inhibition value of sulfate varies from one substrate to another. T h e effect of sulfate on p H is very significant. T h e p H was higher when sulfate was applied.  This implies that a proper concentration of sulfate might be able to increases  the p H stability of an anaerobic process by competition for hydrogen and fatty acids between the sulfate reducing bacteria and the methane bacteria, helping to maintain stable operation. Batch experiments could not indicate a meaningful relationships between sulfate concentration and other responses, such as C O D and V F A s concentration. experimental mode was therefore chosen to determine these effects.  A continuous  It turned out that  the effect of sulfate addition was far more noticeable in continuous operation than in  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION  OF WHEY 122  batch experiments.  7.4  RESULTS IN C O N T I N U O U S  7.4.1  EXPERIMENTS  E f f e c t of S u l f a t e o n R e a c t o r O p e r a t i o n : T i m e P r o f i l e  During the 300 days of operation, the loading rate of the reactor was increased through 7 steps from 1.2 (the sludge loading rate of 0.2 g C O D / g V S S - d ) . t o 10 g C O D / l - d . T h e first 3 load changes were accomplished by the reduction of the H R T from 15 to 5 days at a constant influent concentration of 15 g C O D / 1 with an addition of 0.2 g/1 sodium sulfate. Following that, the change of load was done by changing the influent concentration  at  a H R T of about 5 days.  an  For each subsequent increment of influent concentration,  operating period of 6 to 10 H R T s was maintained to ensure stable operation. The results are graphically presented in Figure 7.2 to 7.10.  Several stages could be  identified from the time profile of the reactor performance. T h e first 45 days could be considered the start-up period. T h e effluent concentration decreased from 1.95 to 0.35 g C O D / 1 , while C O D reduction increased from 87% to 98%. T h e reactor start-up was also indicated by other process parameters. Methane content in the biogas increased from 40% to 51%, then stabilized at about 48%.  p H of the effluent  increased from an average of 7.5 to a value of about 8.2.  T h e content of V F A in the  effluent significantly decreased during this period of time.  After 45 days operation, the  total V F A in the effluent was maintained below 0.3 g/1. Note that there was no difference between the results with sulfate addition and with no-addition, (in comparison with the results in Chapter 5). From day 46 to 134, in the first 4 increases of organic loading rate ( O L R ) of 1.2,  1.8,  2.8 and 4 g C O D / 1 d, the system was stable. T h e effluent C O D , V F A and gas composition  Chapter 7. EFFECTS  50 H  Q O O  3  OF SULFATE ON ANAEROBIC DIGESTION OF WHEY 123  Start S=0.2 g/1  40  Steady S=0.2 g/1  Transient Unsteady S=0.2 g/1! S=0.3g/1  O In • Out  S=0.3 g/1  C  o  VL CO  30  V_  *-> c CD O  o O  2  0  *•> 3  o 10  %rroq&3><x)ooc^ 0  40  80  120  160  200  Time (days)  Figure 7.2: C O D C o n c e n t r a t i o n  versus T i m e  240  280  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION  12  Time (days)  Figure 7.3: Organic Loading R a t e versus T i m e  OF WHEY  124  Chapter 7. EFFECTS  OH 0  .  OF SULFATE  r 40  1  •  1 80  ON ANAEROBIC  1 120  L  -'  1 160  DIGESTION  i  •  200  Time (days)  Figure 7.4:  Effluent C O D versus T i m e  h 240  OF WHEY  • 280  125  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION  OF WHEY  100-  ae-  _  82-  88-  Steady S=0.2 g / l  Start S=02g/l  Transient S=0.2 g/l  Uhsteady S=0.3g/1  S=0.3g/1  84-  80-  40  80  120  -i— 160  T —  200  Time (days)  Figure 7.5: C O D R e m o v a l v e r s u s T i m e  240  280  126  Chapter 7. EFFECTS OF SULFATE ON ANAEROBIC DIGESTION OF WHEY 127  1600-  Starl S=0.2 g/1  Steady S=0,2 g/1  Transient S=0Jg/1 S=0.2 g/l!  S=0.3 g/1  1200-  CO  o <  Acetic  800-  Propionic  eoo-  Load shock 2  Load Shock 1  300-  40  eo  120  160  240  Time (days)  Figure 7.6: E f f l u e n t V o l a t i l e F a t t y A c i d V e r s u s  Time  280  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION  OF WHEY  128  9.5 Sforf S=0.2g/1  Steady S=0.2 g / l  Transient S=0.2 g/l  Unsteady S=0.3g/1  S=0.3 g/1  a  Time (days)  Figure 7.7: E f f l u e n t p H v e r s u s T i m e  280  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION OF WHEY  40 Start S=0.2 g/l  Steady  S=0.2 g / l  Transient S=0.2 g/l  UrtsUo<fy S=0.3g/1  S=0.3 g/1  30-  \/  / 20-  10-  —r  40  I—  80  120  160  200  240  Time (days)  Figure 7.8: M e t h a n e P r o d u c t i o n R a t e v e r s u s T i m e  280  129  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY  60 Steady  Star! S=0.2g/1  °^ 50 C  o w o a E o O  Transient  S=0.2 g/l  S=0.2 g/l  / %  •  w\/\ Load _A Shock 1  © C  ©  "i  • shock 2  •1  •  11  30  20  S=0.3 g/l  •  •>  40  Unsteady S=0.3g>1  <  40  ——'  1  ao  '  1 —  120  160  Time (days)  200  ,—  Figure 7.9: B i o g a s C o m p o s i t i o n v e r s u s T i m e  i  240  1  260  130  Chapter 7. EFFECTS  OF SULFATE  Star! S=0.2g/1  ON ANAEROBIC  Steady S=0.2 g / l  DIGESTION  OF WHEY  Transient S=0.2 g/l  280  Time (days)  Figure 7.10: V S S in the Effluent versus Time  131  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION OF WHEY 132  were constant, which indicated that the reactor was in a very active and underloaded conditions without any stress up to an O L R of 4 g C O D / 1 d. T h e gas production, in terms of liters of methane per liter of feed per day, had not changed as the O R L increased stepwise to 4 g C O D / 1 d. From Figure7.2 we can see that the same influent C O D of 15 g/1 was applied for the first 3 steps. The O L R was changed by changing the H R T during this period of time. Independent evidence (Yan et al 1988), which showed that the effect of H R T on gas production was not significant for low influent concentrations, agrees with this result. Similar to the previous results without the addition of sulfate (Yan et al 1989), when an influent concentration of 30 g C O D / 1 ( O L R of 5.5 g C O D / 1 d) was applied on the 138th day, the system experienced a non-steady state condition. parameters,  Only the sensitive  such as V F A , p H and gas composition showed a respond to a "transient  state". Gas composition immediately declined to 40% methane. Four days after the new load was applied, V F A , especially propionic acid increased to 500 mg/1 and p H dropped to 7.3. T h e transient state returned to steady state within 1.5 H R T s . T h e results of this experiment demonstrated once again that an influent concentration of 40 g C O D / 1 is the threshold concentration for the stability of this system, as is shown for the case without sulfate addition. The instability of the system appeared on day 15 after the load change (day 200).  It was first detected by a drop in methane content in  the biogas from 47% to 30%, p H fell and V S S in the effluent rose.  A large amount of  sludge, up to 4.3 g VSS/1, left the reactor with the effluent. T h e total V F A in the effluent accumulated to 2000 mg/1. T h e ratio of propionic to acetic acid increased from 0.5-1  at  steady state to 1.5, and continued up to 2.5-5. T h e results,..under these conditions with the addition of sulfate, were less favorable than the author expected, based on the concept of interspecies hydrogen transfer and the functions of hydrogenotrophic association of S R B with M P B in the fermentation process.  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION OF WHEY 133  It was assumed that 0.2 g/1 sulfate was not enough to create a favorable environment for methane fermentation of high strength cheese whey up to 40 g C O D / 1 , which represents a ratio of C O D to sulfate of 200.  Further tests were then made with higher sulfate  concentration in the hope that this would enhance the activity of the S R B . It was first necessary to return the reactor operation to a stable steady state. Various strategies have been tried to bring the reactor back to normal operation.  Maintaining  the feed concentration at 40 g C O D / 1 , the O L R was decreased from 8.5 to 3 g C O D / 1 d (daily feed of 1.1 liters), then increased step wise, until it again reached 8 g C O D / 1 d. It took 30 days (day 204-233) to re-establish the full activity of the methane bacteria. Both acetic acid and propionic acid decreased well below 200 mg/1. V S S in the effluent decreased, remaining below 1-2 g/1. After day 235, a feed of 50 g C O D / 1 with 0.3 g/1 sulfate concentration was used. The reactor remained stable until day 262, 15 days later the influent concentration was increased to 50 g C O D / 1 . T h e gas composition suddenly dropped to 40% CH4 and further declined to 37% the next day. To avoid an entire upset of the reactor, more sulfate was added into the feed substrate to rise the sulfate concentration to 0.5 g/1 in the feed. However, the addition of sulfate was not able to immediately reverse the decline of reactor performance. Methane content in the biogas remained about 39% for a while (day 263-267). Both acetic and propionic acids kept increasing from day 265 to 272, which showed that the high concentration of cheese whey had already upset the reactor. 5 days later, the gas composition return to about 43% CH , and both acetic and propionic acids dropped below 0.2 g/1. A much 4  lower butyric acid concentration than found during the previous stressed period indicated that the bacteria were less severely inhibited this time. A high concentration cheese whey of 69 g C O D / 1 with 0.5 g/1 sulfate was used during the last stage from day 282 on. A low methane content of only 31.8% in biogas on the  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY 134  third day of the last stage indicated that the reactor was subjected to stress.  Further  addition of sulfate up to 1 g/1 no longer improved the reactor stability.  7.4.2  E f f e c t of S u l f a t e o n S t e a d y State  Performance  Steady state was denned as the condition in which the system parameters remained constant within ± 1 0 % over the period of operation. For each operating condition, at least two H R T s were needed to reach a new steady-state.  T h e results for whey digestion at  steady state as a function of influent concentration are summarized in Table 7.2. In comparison with no-sulfate addition, the results at steady state were quite similar in terms of gas production and C O D removal with the exception that with sulfate addition the reactor could treat a higher allowable influent concentration and organic loading rate, which shows that no inhibition occurred at these operating conditions. T h e results show little effect of sulfate on gas composition or methane production rate for continuous operation in the U A S B reactor (Figure 7.11 a and b). T h e presence of sulfate also appeared to have no influence on the relationship between methane production and organic loading (Figure 7.12). T h e addition of sulfate resulted in similar volumes of biogas produced in terms of 1 CH4 j\ reactor per day as those in the absence of sulfate. W i t h the increase of influent concentration, the percentage o(CH  4  in the produced biogas gradually diminished which  indicated that the domination of acidogenesis in the digestion of whey increased with an increase i n influent concentration. Gas production in terms of liters C / / per gram C O D 4  per day also declined when influent concentration was increased. O n the other hand, the presence of sulfate did affect the yield of methane in the batch experiments (Appendix B). T h e studies on the inhibitory effects of sulfate on the activity of methanogens led Isa et al (1986) to conclude that the competitive nature of S R B relative to M R B was dependent on the nature of the feed substrate.  T h e effect of  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC DIGESTION OF WHEY  Table 7.2: E x p e r i m e n t a l R e s u l t s i n S t e a d y S t a t e  Effluent. Influent OLR g COD/1 g COD/l.d  COD g/1  pH  Gas COD Removal% 1/1 d  CH % 4  2,03  0.33  7.95  97  5.2  47.25  3.13  0.28  7.87  98  5.5  47.41  20.96  4.21  0.32  7.73  98  7.2  45.50  30.50  5.58  0.63  7.56  98  9.1  43.92  41.30  7.52  0.68  7.56  98  10.9  41.07  50.91  11.41  1.16  7.77  97  13.9  40.10  15.50  135  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION OF WHEY  136  7.11: Effect of Influent Concentration on Methane Production and Composition  Figure  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC DIGESTION  OF WHEY  Figure 7.12: Effect of O L R on Methane Production  137  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION OF WHEY 138  sulfate on biogas composition can be attributed to the different substrate mix used in two experiments, basically the ratio of substrate to sulfate.  In the batch experiments,  the concentration of whey and sulfate were compatible, since the ratio of C O D to sulfate ranged between 5 to 10. Only small amounts of sulfate were employed in the continuous experiments, a range of ratios from 100 to 200. T h e substrate concentration used (0.5-5 g C O D / 1 ) by Isa was also much lower than those used in the continuous experiments of this study. In addition, the different types of substrate used in the two cases should be also taken into account.  Using acetate as a feed material for digestion, Isa found  that both specific methane production and CH^ increased as the feed concentration was increased. This was interpreted as meaning that the S R B became more competitive at lower substrate strengths.  Since acetate was the only carbon source and cleavage of  acetate therefore was the only major reaction involved in the digestor, it is reasonable to believe that the methanogenic cleavage of acetate was inhibited by S R B at a very low H partial pressure. W h e n whey, which mainly consists of lactose, was used as substrate 2  for anaerobic digestion, the reactions involved in interspecies H  2  transport  were more  complicated. H as an interspecies plays many roles in whey fermentation. In this case, 2  S R B could be competing for H  2  with i ^ - u s i n g methanogens  i ^ - u s i n g methanogens and acetoclastic  bacteria.  and could inhibit both  O n the other hand S R B might also  promote and stimulate the degradation of fatty acids by removing excess hydrogen. T h e final result would be the overall effect of these two opposing mechanism. The amount of sludge was monitored by measuring the V S S profile in the reactor and the V S S content in the effluent. These results are presented in Table 7.3. A plot of ( d X / d t ) / X vs ( d S / d t ) / d X provides the means for determining Y (yield coefficient ) and K  d  (decay coefficient), which were 0.053 g V S S / g C O D and 0.00047 day^.  T h e sludge  yield was the same, while the decay rate was much lower than in the process without sulfate.  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC DIGESTION OF WHEY 139  Despite the fact that methane production, effluent C O D and C O D reduction at steady state for the two cases (with sulfate addition and without sulfate addition) were virtually the same, several remarks can be made about the difference in the two operating conditions.  7.4.3  The Improvement of Reactor Stability  T h e impressive improvement in the reactor stability with the addition of sulfate was a significant result. shocks.  During the first 180 days, the reactor experienced a number of load  T h e first load shock appeared on day 106 when the reactor was fed 3.4  of cheese whey with a concentration the same concentration  of 20 g C O D / 1 daily.  1/d  Two days later, 5.4 1 of  were pumped into the reactor again.  Surprisingly, except for  gas production and gas composition, which drastically decreased then rapidly recovered, there was no other evidence that the reactor was becoming unstable.  This is seen by  considering the constant V F A s and C O D concentration in the effluent. T h e second load shock was applied on day 167.  3.9 1/d of 31 g C O D / 1 cheese whey was used.  At this  time, both the gas production and effluent V F A decreased immediately, then returned to their normal values shortly afterwards.  T h e reactor was so stable that it was expected  that an influent concentration of 40 g C O D / 1 could be applied. Although 0.2 g/1 of sodium sulfate concentration in the feed did improve the bacterial resistance to shock loads, it could not help with further increases in the loading rate. As in the earlier studies, the influent concentration  of 40 g C O D / 1 or O L R of about 8 g  C O D / l - d caused instability. Even though the V S S profiles show that the total amount of sludge was greater than that without sulfate, it could not help to improve the O L R , nor could the 0.2 g/1 of sulfate added. It was interesting to find that no H S 2  when only 0.2 g/1 sulfate was added to feed, while 0.3-0.6% H S 2  was detected  was observed for 0.3 g/1  sulfate addition. It could be explained that sulfate was first used as nutrient for M P B 139  Chapter  7.  EFFECTS  OF SULFATE  ON ANAEROBIC  Table 7.3: S l u d g e in the  Inf-COD  Sludge  g COD/l-dg COD/1  gVSS  OLR  F/S  DIGESTION  OF WHEY  140  reactor  Eff.  lost in Sample  Net Growth  gVSS  g VSS  -  -  • gVSS  128.95  0.250  14.4  142.21  0.254  -51.75  4.03  20.96  .206.13  0.254  64.26  14.48  142.66 •  5.50  3L24  253.34  0.308  115.83  33.59  185.53  7.56  41.36  152.52  198.24  24.1  9-11.  50.42  224.52  130.56  18.57  2.96-3.13  0.56  -  -  65.01  220.86  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC DIGESTION OF WHEY 141  and S R B rather than hydrogen utilizing reagent.  7.4.4  T h e E f f e c t o f S u l f a t e on B u f f e r C a p a c i t y  Figures 7.13  and 7.14  show the effect of sulfate on p H by comparing the results with  and without sulfate addition. A statistical analysis of the data using Minitab t-test is presented in Appendix D . It was evident that there was a substantial increase in p H with sulfate addition, an average of 0.6 (from 0.48 to 0.82) p H units higher than without sulfate.  7.4.5  T h e Improvement  of T r e a t m e n t E f f i c i e n c y  T h e improvement in the treatment efficiency can be seen from the higher allowable influent concentration with further sulfate addition of 0.3 - 0.5 g/1 (Table 7.2). 30-38 g C O D / 1 without sulfate (Table 5.2),  Instead of  the highest permissible feed concentration  reached 50 g C O D / 1 in the experiments with sulfate of 0.5 g/1. Accordingly, the organic loading rate rose to 11.41  g C O D / l - d , which is higher than without sulfate, 7 g C O D / 1  d.  7.4.6  T h e E f f e c t o f S u l f a t e o n P r o f i l e s of p H , S l u d g e a n d V F A s  Profiles of p H , sludge and V F A s as a function of influent concentration  are showed in  Figure 7.15 to 7.19 and Table 7.4. In general, it can be said that sulfate addition in the amount applied here did not change the shapes of the profiles. Two different stages were distinguished again for the first 4 operating conditions, as was noticed in earlier experiments.  Acetic acid, propionic  acid and C O D were well reduced below a height of 12 cm, and the border between the two stages appeared clearly. Also, two sludge regions, a sludge bed and sludge blanket,  Chapter 7. EFFECTS  OF SULFATE  were observed as shown in Figure 7.15.  ON ANAEROBIC  DIGESTION OF WHEY 142  However, the sludge was darker and thicker in  the reactor with sulfate addition than without sulfate. The profiles of the V F A s showed a change when the influent concentration was increased to 50 g C O D / 1 , presumably due to the fact that the organic loading rate of the reactor approached its upper limit. Under this circumstance, concentrations of acetic acid and propionic acid drastically increased and the acidogenic stage extended upward. At a height of 50 cm, 1100 mg/1 of acetic acid and 1400 mg/1 of propionic acid were detected. Acetic acid concentration was essentially zero at a height of 80 cm, while propionic acid maintained a high concentration of 1600-2000 mg/1. In spite of the high propionic acid concentration in the reactor, the system was fairly stable. The establishment of biomass activity and the fermenter performance can largely be interpreted by its V F A values.  Total V F A concentrations  greater than 2000 mg/1, or  acetic acid alone being greater than 800 mg/1 and a P / A ratio greater than 1.4 are the predictions of anaerobic process failure, as suggested in the literature (Hill et al,1987). The extremely high propionic acid concentration observed in the reactor with faily stable operation showed that the reactor performance was superior due to the sulfate addition. Figures 20 and 21 show the difference in acetic and propionic acids in the reactor for the absence and presence of sulfate. W h e n the influent concentration was increased to 38.1 g C O D / 1 without the addition of sulfate, acetic acid and propionic acid were as high as 3000 and 1000 mg/1, respectively. However, acetic acid and propionic acid were only 30 and 100 mg/1 at the influent concentration of 40 g C O D / 1 / when sulfate was added. A substantial decrease in butyric acid concentration in the acidogenic stage caused by sulfate addition was observed. Figure 7.22 shows this effect. In the absence of sulfate, a considerable concentration of butyric acid was accumulated in the first stage (acidogenesis), but was hardly detectable in the presence of sulfate.  Chapter 7. EFFECTS OF SULFATE ON ANAEROBIC DIGESTION OF WHEY 143  Without Sulfate x-  -X  X-  x  — = •  •  Influent 4.45flCOO 4-  -V  V  I'  1  «  9.93 g C O P »"  A  17.1 g C O D  X  28.8 g C O D  I''  V  38.1 g C O D  I'  I"  1  With Sulfate 7Influent 6-  O 15 g C O P r* 20 g COD  I'  A 30 g C O P  I'*  •  5-  1  X 40 g COD l' V SO g COD 0  20  40  —r— 60  I  80  %  I'  1  100  R e a c t o r Height (cm)  Figure 7.13: Effect o f S u l f a t e o n p H P r o f i l e s  120  7. EFFECTS  OF SULFATE  8  ON ANAEROBIC  • Without Sulfate  ^e-  With Sulfate  o  DIGESTION OF WHEY  °  or  2 I 0  '  T  1  10  r I  I 20 1  1 1  1  i—'.  30  I  1-  AO  Influent ConcentrationCg C O D I" ) 1  Figure 7.14:  C o m p a r i s o n of p H w i t h o u t Sulfate a n d w i t h Sulfate  144  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  Figure 7.15:  Profile of S l u d g e  DIGESTION  OF WHEY  145  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  6-  DIGESTION  OF WHEY 146  Influent O 15 fl COD I'  1  • 5-  20 g COD I"  A 30 g COD I" X 40 g COD I'  1  V 50 g COD I'  1  20  —r— 40  —r— 60  -r  Reactor Height (cm)  Figure 7.16: P r o f i l e o f p H  -  80  100  120  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY  Influent O  15  •  20flC O D  Reactor Hlght (cm)  Figure 7.17: P r o f i l e o f A c e t i c  Acid  o COD r I  147  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  Figure 7.18:  DIGESTION  P r o f i l e of P r o p i o n i c  Acid  OF WHEY  148  Chapter 7. EFFECTS  OF SULFATE  Figure 7.19:  ON ANAEROBIC  DIGESTION  Profile of C O D  OF WHEY  149  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION  Table 7.4: P r o f i l e s o f t h e U A S B R e a c t o r w i t h Sulfate  Influent g COD/1  " Height. VSS cm g/1  COD mg/1  pH  AA mg/1  PA mg/1  BA mg/1  OF WHEY  Addition  IBA COD mg/1 Removal  • 14.40 15.11  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  39.42 10478 31.72 1071 22.63 696 21.42 456 10.84 437 4.11 430 3.85 363 2.98 388  5.05 6.64 6.60 6.79 6.82 6.81 6.81 6.78  1038 103 44 45 45 54 43 51  297 64 34 34 40 12 8 26  36 20 0 0 0 0 0 0  941 0 0 0 0 0 0 0  0.31 0.93 0.95 0.97 0.97 0.97 0.98 0.97  18.51 20.96  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  47.25 12835 37.05 1339 36.26 739 28.16 308 8.52 398 9.82 289 8.28 399 7.77 407  5.56 6.87 6.89 6.89 6.91 6.92 7.07 6.93  1163 43 38 44 18 32 28 27  399 35 22 8 9 0 0 3  63 4 1 1 2 3 0 . 0  687 14 0 0 0 0 0 0  0.36 0.94 0.96 0.99 0.98 0.99 0.98 0.98  30.08 31.24 28.73  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  38.47 15985 40.77 1232 34.92 842 33.01 654 34.36 556 9.77 590 8.86 479 11.70 455  6.05 6.96 6.92 6.90 6.90 6.96 7.02 6.93  1413 73 67 62 57 61 63 62  901 21 17 14 14 8 13 8  75 1 1 2 1 1 2 2  364 0 0 0 0 0 0 0  0.47 0.96 0.97 0.98 0.98 0.98 0.98 0.98  40.48  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  32.82 18422 31.50 1848 12.94 1466 12.17 880 13.24 919 11.10 910 9.21 929 8.02 980  6.64 6.89 7.00 7.01 6.99 6.98 6.96 6.89  1600 1050 57 40 20 105 20 96 21 71 21 56 20 30 20 51  50.91 47.05  4.0 12.5 25.0 37.5 50.0 62.5 87.5 112.5  43.98 21449 39.38 8067 29.64 4836 18.40 4869 14.94 4834 12.74 4821 12.70 4690 12.82 4692  6.85 7.08 7.05 7.16 7.28 7.31 7.38 7.40  2127 1731 1154 1109 935 941 81 95  2377 2268 1685 1815 1586 1268 1902 1700  0.55 0.95 0.96 0.98 0.98 0.98 0.98 0.98 163 349 123 119 193 99 131 125  421 0.57 173 0.84 145 0.91 73 0.90 50 0.91 46 0.91 41 0.91 41 0.91  150  Chapter 7. EFFECTS OF SULFATE ON ANAEROBIC DIGESTION OF WHEY 151  7.20: Effect of Sulfate on the Profile of Acetic Acid: (A) Without S, (B) With S  Figure  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY  152  10000  o> \ooo4  Influent  -TO u 100^ < o c O  Q. O i_ CL  O  4.4S  •  9 . 9 3 q C O D I"  n C O D I"  A  17.1 g C O D I"  X  28.8 g C O D I"  V  38.1 g C O D I"  10000  O) 1000 E  "o  <  In fluent O  100  o c  15 q C O D 1"  •  20 q C O D 1"'  A  30 fl C O D . I "  o  X  40 fl C O D 1"  o i_  V  50 q C O D 1*'  Reactor Height (cm)  Figure 7.21: Effect of Sulfate on the Profile of Propionic Acid: (A) Without S, (B) W i t h S  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION OF WHEY  153  Figure 7.22: Effect of Sulfate on Butyric Acid Concentration in the Acidogenic Phase  Chapter 7. EFFECTS  7.5  MECHANISM  OF SULFATE  ON ANAEROBIC  O F INHIBITION  DIGESTION  OF WHEY 154  OF HIGH CONCENTRATION OF  VFAs A N DL O W pH Inhibition and toxicity in anaerobic digestion are subjects which have received considerable attention due to the important role they play in digester failure and also because they must be allowed for in the correct design and operation of reactors. M u c h information can be found about the effects of various chemicals and environmental factors on anaerobic digestion, but the data tend to be dispersed and without any basic unifying theory. W i t h highly soluble carbohydrate substrates, anaerobic digestion systems are always found to be easily upset. Under loading stress or impending failure conditions, low pHs and high V F A s concentrations are commonly observed, particularly for whey anaerobic digestion systems. p H control has been demonstrated to be crucial for maintaining stability. Inhibition modeling of digestors has been mainly restricted to the apparent effects of high concentrations of V F A s on methanogenic bacteria (Andrews 1968). However, the inhibition mechanism is not fully understood. It has been accepted that non-ionized V F A s are inhibitors for methanogens and suggested that the methanogenic bacteria are inhibited either by hydrogen ions or. by their substrate, the volatile acid (Andrews 1965, 1968)). T h e relationship between non-ionized V F A s and p H is that when p H decreases,  the non-ionized V F A s increase.  Calculated  concentrations of non-ionized V F A s (Appendix D ) for cases with and without sulfate are presented in Table 7.5, which shows how p H affects the concentration of non-ionized acid. A dramatic decrease in the concentration of non-ionized acids was obtained due to the increase in p H when sulfate was added. A theoretical explanation for why non-ionized acid acts as inhibitors can be given, combining bacterial membrane transport and the Mitchell chemiosmotic hypothesis. T h e  Chapter 7. EFFECTS  Table 7.5:  CH % 4  OF SULFATE  Calculated  pH  ON ANAEROBIC  DIGESTION  C o n c e n t r a t i o n of N o n - i o n i z e d  Non-ionized Acids AA(mg/l)  OF WHEY  VFAs  PA(mg/l)  Without Sulfate 56 51 48 45 39  4.0 4.2 4.4 4.5 3.9  324 510 612 753 2355  78 105 202 483 1336  W i t h Sulfate 47 46 44 41 40  5.05 5.56 6.05 6.64 6.85  263 155 69 21 17  100 55 44 14 19  155  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION  OF WHEY 156  accumulation of non-ionized acids leads to the acidification of the internal cytoplasmic p H and destruction of the p H gradient which is necessary for A T P synthesis. Bacteria have a cytoplasmic membrane that acts as a permeability barrier for hydrophilic and charged molecules. A peptidoglycan layer, that surrounds the cytoplasmic membrane, confers rigidity and shape on the bacteria.  In gram-negative  bacteria, an  additional outer membrane serves as a barrier to large hydrophilic and to hydrophobic molecules (Hancock 1984). Three different kinds of bacterial membrane transport:  pas-  sive diffusion, facilitated diffusion and active transport, were elucidated by Harold and Brock et al (Harold 1977, Brock 1984).  Passive diffusion is a transport mechanism by  which neutral molecules tend to equilibrate across the membrane. T h e driving force for transport is a concentration gradient. Water, oxygen and carbon dioxide are transported by passive diffusion across the cytoplasmic membrane. In the case of facilitated diffusion, the permeating molecule combines with a membrane carrier and is transported inside the cell along its concentration gradient. For active transport, a specific carrier is generally required for each solute.  Three categories of active transport:  ATP-dependent, group  translocation and transport coupled to the pmf (proton motive force), are recognized. T h e pmf is a chemiosmotic gradient across the bacterial cytoplasmic membrane that can be considered to have two distinct components: an electrical potential (interior negative) and a p H gradient (interior alkaline). Translocation of protons outside the cell membrane thus increases both components of the pmf. Major roles of the pmf are in the production of A T P by the membrane-bound A T P a s e enzyme complex, and for the transport of substrates.  In ATP-dependent transport,  the hydrolysis of A T P drives the internal  accumulation of solutes such as negatively charged amino acids. In group translocation, the solute is modified during its transport (e.g. sugars by phosphoenol pyruvate).  In  transport coupled to the pmf, cations, anions or neutral molecules can be co-transported with protons or other cations such that the molecule is neutral or carries a net positive  Chapter 7. EFFECTS  OF SULFATE  charge when it crosses the membrane.  ON ANAEROBIC  DIGESTION OF WHEY 157  For neutral molecules, such as sugars or amino  acids, the carrier proteins effectively transfer a positively charged molecule where protons are bound to the carrier for its activation. According to the Mitchell chemiosmotic hypothesis (Mitchell 1966), a trans-membrane p H gradient is generated between electron transport and phosphorylation of A D P . Electron transport  causes H  +  ions to be pumped outward across the bacterial membrane.  This proton expulsion leads to an increase in the p H gradient and the membrane potential, and concomitantly an increase in the proton motive force. This p H gradient (interior more alkaline) is the high-energy intermediate required for A T P synthesis. W h e n the p H of the medium decreases, the non-ionized V F A s consequently accumulated. T h e acetic, propionic and butyric acids in their non-ionized form will penetrat the bacterial membrane without any resistance based on the principle of the passive diffusion of neutral compounds across the bacterial membrane. A dissociation of the acids inside the cytoplasm is then provoked by the higher cytoplasmic internal p H . Thereby, protons are released and the cytoplasm is acidified, leading to the p H gradient dissipation. As a consequence, less energy will be available for the synthesis of bacteria and the attainable growth rate will be lowered. T h e acetic and propionic acids act as uncoupling agents for p H gradient destruction and potential membrane modification. Hence, the undissociated forms of V F A s are the inhibitors. Different bacteria have different systems and capacity to maintain their p H gradient. Aerobic neutrophilic bacteria, like E . C o l i , are capable of maintaining an internal p H near 7.6 for an external p H range of 5.5 to 8.5 (Padan et al., 1981). Some anaerobic bacteria, such as Clostridium pasteurian and Closdium thermoaceticum also show a similar system of p H gradient. However, methanogenic bacteria have only a limited capacity to maintain a constant internal p H . It has been explained that the i / - A T P a s e system, combined with +  an antiport cation, could be responsible for the maintenance of a high p H gradient at a  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY 158  low external p H (Kobayashi et al 1982). Not  all researchers share in the same belief that high V F A concentration  are the  inhibitors which cause failure. A n argument has existed for years that accumulation of V F A s are the result of unfavorable conditions for anaerobic process rather than the cause of inhibition. A further discussion on this topic will be given in next section.  7.6  MECHANISM OF STIMULATION  BY  SULFATE.  Microbial sulfate reduction is a process in which certain bacteria use sulfate as the electron acceptor during metabolism of organic matter.  T h e kinetics of competition for  available electron donors (acetate and hydrogen) by M P B and S R B have received attention in the literature.  Although acetate oxidizing S R B have been isolated and identified  (Desulfobacter postgatei), they do not seem to be found among digester bioflora (Hocks et al 1984,  Mulder 1984).  lithotrophic reduction pf  As previously mentioned, all S R B are able to perform the SO^ : 2  4tf + H 2  +  + SO~  Therefore, this common modality for H  2  2  .= HS-  + 4H 0 2  (7.6)  utilization sets up a situation of competition  between the M P B and the S R B . Molecular H  2  is generated in two distinct steps of the anaerobic digestion process,  i.e. fermentation and /3 oxidation. T h e fermentation of the hydrolytic products - amino acid and glucose - is performed by a number of acidogenic Clostridial species native to anaerobic reactors. Hydrogen gas is evolved when pyruvate, the end product of glycolysis, is decarboxylated and dehydrogenated to acetate via the phosphoroclastic reaction. H  2  is also generated in the anaerobic oxidation of volatile and long chain acids.  This  is performed by a number of native obligate syntrophic bacteria (usually referred to as  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION OF WHEY 159  obligate proton reducing or hydrogen-producing acetogen [OHPA]). In this process acetate units are split off endwise from the chain with molecular H for electrons.  2  being the main sink  T h e stoichiometry is as follows (Gujer and Zehnder 1983):  (~CH CH -) 2  2  + 2H 0 = CH C0 H 2  3  2  + 2H  2  (7.7)  This reaction, mediated by pyridine dinucleotides, is believed to be inhibited by increasing partial pressure of H , 2  electrode.  as its O R P , -0.32 V , is higher than the standard hydrogen  Oxidation of fatty acids is feasible only when the reaction can be "pulled" to  the right by the continuous removal of H . 2  The argument is, therefore, whether or not the fermentation of pyruvate to acetate is i? -sensitive. It was thought that this reaction seemed not be inhibited by increasing par2  tial pressures of H  2  (Gottschalk 1986, Cohen 1979), considering its oxidation/reduction  potential ( O R P ) of -0.68 tential of -0.42  V , which is lower than the standard hydrogen electrode po-  V . O n the other hand, it has been long believed that fermentation of  acetic, propionic and butyric acids from sugar via the E M P pathway is regulated by the availability of H . 2  Figure 2.2 (from Mosey) provides the main route - the Embden  Meyerholf pathway for conversion of sugar to organic acid. T h e acid-forming bacteria use this pathway to obtain energy from the oxidation of glucose to acetate. During the course of this oxidation, hydrogen atoms removed from the glucose are transferred first to the carrier molecule NAZ)  +  , converting it to N A D H + H  +  and then released into so-  lution as dissolved hydrogen gas. In order for catabolism to proceed continuously, given a constant pool of N A D , the N A D H produced during substrate-level phosphorylation of glyceraldehyde-3-phosphate  and the oxidative decarboxylation of pyruvic acid to acetyl-  CoA  This function is accomplished by the reduction of protons  must be regenerated.  to form hydrogen gas, which is subsequently removed by the hydrogenotrophs such as  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  methanogens, S R B and N R B through interspecies hydrogen transfer.  OF WHEY 160  Accumulations of  hydrogen need an alternate method of electron disposal for N A D H regeneration.  This  need is fulfilled by the fermentation of pyruvic to propionate, lactate, and ethanol and/or by the fermentation of acetyl-CoA to butyric acid. Accumulation of H  2  during the formation of acetic acid from pyruvate pushes the  reaction in the directions which will release the stress from a high pressure of H  2  (see  line D in Figure 2.3) by oxidation of acetic acid to butyric acid. Further accumulation of H  would shift the fermentation of pyruvate from producing acetic acid to butyric  2  and propionic acids.  T h e evidence that the concentrations  of butyric acid as well as  propionic acid decreased due to the presence of sulfate led to a new interpretation of hydrogen regulation of the overall conversion process by throttling the acidogenic reaction at several points in the glycolytic pathway. First, S R B , which have the capacity to utilize H  2  might be able to maintain the H  pressure low enough (say well below 10~  2  4  atm),  allowing the fermentation of pyruvate to continue going to acetate. Secondly, as can be seen from Figure 7-1, the removal of H  2  can move the metabolism to that of an O H P A .  T h e oxidation of butyric acid can be motivated when H  2  pressure drops to below 10~  3  atm according to thermodynamic calculations, so can be the oxidation of propionic acid at H  pressure below 1 0 ( F i g u r e 2.3). _4  2  No matter what the fate of butyric and propionic  acids might be, the results indicated that fermentation is H  2  by H  2  sensitive and is regulated  pressure.  A question remains whether S R B are able to change the pathway or promote (3oxidation by providing a H  2  a closer look at Figure 7.21  sink under the conditions of the present study. (also Tables 6.1 and 7.4)  Taking  it was easy to notice that the  concentrations of propionic acid in the acidogenic stage ( sample port 1) were the same for two experiments  (in the presence of sulfate and in the absence of sulfate), while in  the methanogenic stage (sample port 2) the propionic concentrations  were much lower  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  with the addition of sulfate than without sulfate addition.  OF WHEY  161  A possible explanation for  this observation is that pyruvic originally was fermented to propionic and butyric acids, perhaps acetic acid as well. Then propionic acid was further broken down to acetic acid. T h e lower the H  2  concentration  pressure, the more propionic acid was oxidized, thus the lower the  of propionic acid would be.  The results from these experiment  that S R B are more likely to promote /5-oxidation by providing a H of H  2  suggest  sink, due to the level  pressure to which the sulfate could reduce.  2  A reason for the decrease of butyric acid being far more noticeable  than that of  propionic acid after the addition of sulfate can be explained by the effect of the different H  2  partial pressure. T h e regulatory  effects of hydrogen on acetogenic and methanogenic  bacteria  have  been conveniently illustrated using thermodynamic models and equilibrium assumptions by several authors (Zhender et al.1980, Gujer 1983)). Thermodynamic calculations Figure 2.3)  indicate that a partial pressure of hydrogen of 1 0  - 3  atm would favor the  oxidation of butyric acid, while propionic acid oxidation to acetate becomes only at H  2  partial pressure below 1 0  -4  atm. If H  2  (see  favorable  is maintained at sufficiently low levels  (10~ atm), the production of propionic acid needs never occur. 4  T h e high concentration  of butyric acid in the experiment  without sulfate addition  indicated that the hydrogen pressure must have been greater than 1 0 inhibited the oxidation of butyric acid.  The decline of H  2  - 3  atm, which  pressure to below 1 0  -3  by  S R B due to the addition of sulfate then promoted the further oxidation of butyric acid to acetic acid.  However, the level of H  2  pressure must be higher than 10~  the addition of sulfate since the concentration  4  even with  of propionic acid remained very high in  acidogenic stage. More evidence were found to support the stimulation function of sulfate from Figures 7.23  to 7.26.  T h e y were made based on the equations developed in Appendix A , which  Chapter 7. EFFECTS  OF SULFATE  ON ANAEROBIC  DIGESTION OF WHEY 162  were statistically fitted to the experimental data. Figure 7.23B shows that the degradation of propionic acid in the absence of sulfate was much lower than that with sulfate, although the accumulation of propionic acid was similar for both experiments  (Figure 7.23A). These results indicate that oxidation  of propionic acid in the absence of sulfate was inhibited.  Supporting evidence was also  found that the permissible concentration determined by utilization of propionic acid was much lower in the absence of sulfate (Figure 7.24). Figure 7.25 shows the accumulation and degradation of acetic acid, propionic acid and total V F A s in the absence of sulfate. Figure 7.26 is for the case when sulfate addition was applied. It is interesting to note that in the absence of sulfate, the permissible influent concentration determined by propionic acid concentration was 22 g C O D / 1 , which was much lower than the value given by acetic acid and total V F A s . These were 28 and 30 g C O D / 1 respectively. concentration  T h e permissible concentration was defined as the highest influent  at which the degradation of V F A s was greater than their accumulation  (as described in Chapter 6). W i t h sulfate added, the permissible influent concentration calculated from propionic acid was 39 g C O D / 1 , V F A s , 35 g C O D / 1 (Figure 7.26).  higher than the one determined by  These results show that in the absence of sulfate,  degradation of propionic acid is the rate-limiting step. When sulfate was applied to the feed stream, oxidation of propionic acid was no longer the controlling step for the overall process due to the stimulation function of the S R B ' s consumption of hydrogen. No single parameters could be identified as being responsible for the control of the overall process in the presence of sulfate. It is postulated that the' rate-limiting step of the complicated reactions involved in anaerobic fermentation can be changed and that hydrogen pressure plays a central role in causing the shift between those different controlling steps. Acetoclastic activity could be the limiting steps at hydrogen pressures smaller than 10~ atm. Once the hydrogen 4  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY 163  1.6 -  1  1.2-  Without Sulfate 0.8-  *c o  0.4-  Prop!  Aci  CO <—'  B: D«g of PA With and Without Sulfate  ^  With Sulfate  0  10  20  30  40  50  Influent Concentration (cj C O D I ') Effect of Sulfate on the Accumulation(A) and the Degradation (B) of Propionic Acid  Figure 7.23:  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY  164  Figure 7.24: Effect of Sulfate on the Permissible Concentration Determined by Accumulation and the Degradation of Propionic Acid. (A) in the Absence of Sulfate; (B) in the Presence of Sulfate  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  0  5  10  15  20  25  30  DIGESTION  35  AO  OF WHEY  45  165  50  Influent Concentration (g C O D I ') Accumulation and Degradation of Acetic Acid, Propionic Acid and total V F A s in the Absence of Sulfate - - - •Figure 7.25:  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  DIGESTION  OF WHEY  166  A: Acc and Deg of AA  2-  Acc of A A  CD  1.5  Deg of AA  <  S  o-  5  < i—'—i—•—i—•—i—•—r  B: A c c and Deg of PA 1.5A c c of PA  "o < o  1  Deg_of_j^A  "c o o  l_ Q .  0  -T  1  1  1  1  1  1  1  1  J  1  1  1  J  1  J  f-  I  5-  C: Acc and Deg of Total VFAs  4CO  < >  .o  Acc of VFAs  3H 2-  H  0  5  10  i— —r 15 20 1  i  25  30  •  I  35  •  i  40  •  r  45  50  Influent Concentration (g C O D I ') Figure 7.26: Accumulation and Degradation of Acetic A c i d , Propionic A c i d and total V F A s in the Presence of Sulfate  Chapter 7. EFFECTS  OF SULFATE ON ANAEROBIC  pressure is greater than 1 0 , -4  DIGESTION  OF WHEY 167  the overall reaction rate might be determined by the rate  of oxidation of propionic acid as well as butyric acid. T h e similarity in the shape of the acetic acid accumulation curves for the two experiments (with sulfate and without sulfate) implies that S R B and M P B do not appear to compete for acetic acid. As a result of the above discussion, a new inhibition scheme, two-stage inhibition in anaerobic fermentation can be suggested, which could answer the question of whether V F A s are the inhibitor or the results of inhibition (Figure 7.27). Inhibition of an anaerobic system occurs in the following two stages.  First, high hydrogen pressure drives the  pyruvate fermentation to produce propionic and butyric acids rather than acetate, which is called preliminary inhibition. In this preliminary inhibition, higher hydrogen pressure is the cause and the accumulation of V F A s is the result. T h e accumulation of V F A s in the system subsequently predominates and the consequence of this accumulation causes the direct inhibition of the activity of methane bacteria in the second inhibition stage. High V F A concentrations  are the result of unfavorable conditions for the anaerobic  process,  and also the cause of failure due to the second inhibition. Once a high concentration of V F A s or a low p H is detected, the system has already suffered the second inhibition. Obviously, there is a more effective way to control the process prior to the observation of an apparent accumulation of V F A s , which is to maintain the hydrogen pressure low enough by using hydrogenotrophic association. T h e advantage of the new control strategy over the old p H control system is that it prevents the system from the first inhibition at the very beginning.  Moreover, hydrogenotrophic association is able to promote j3-  oxidation of butyric and propionic acids, in turn, to increase the conversion of acetate. Theoretically, it would increase the production of methane.  Chapter  7.7  7.  EFFECTS  OF  SULFATE  ON ANAEROBIC  DIGESTION  OF  WHEY  168  SUMMARY  T h e significant improvement in process stability and treatment efficiency made by adding sulfate has clearly illustrated that sulfate acts like a stimulator which helps to maintain a favorable condition for methanogenesis.  The mechanism of the stimulation can be  explained according to thermodynamics and hydrogen regulation.  It is that sulfate is  able to promote the /3-oxidation of V F A s by consuming hydrogen. T h e results showing the profiles of p H and substrate concentrations elucidated the fact that the rate-limiting step of the complicated reactions involved in anaerobic fermentation is changed and interspecies hydrogen transfer plays a central role. T h e significant decrease of butyric acid in the first stage indicated that sulfate serves as a hydrogen sink. T h e conversion of pyruvate to acetic acid offers a solution for the removal of excess hydrogen, improving the overall stability. A two-stage inhibition mechanism in anaerobic fermentation was proposed. Higher hydrogen pressure is the cause of preliminary inhibition, resulting in the accumulation of V F A s which subsequently inhibited the activity and growth of methanogens in the second inhibition stage.  T h e mechanism of inhibition of methanogens from V F A s was  interpreted as being caused by the acidification of the internal cytoplasmic p H and the destruction of p H gradient by non-ionized acids based on the theory of bacteria membrane transport.  A new control strategy for anaerobic system stability was recommended. T h a t  is to maintain the hydrogen presure at low level through hydrogenotrophic association.  Chapter 7. EFFECTS  OF SULFATE  H  ON ANAEROBIC  DIGESTION  OF WHEY 169  2  PYRUVIC  H*  He ACETIC  BUTYRIC  <4r H  FIRST  SECOND  PROPIONIC  2  ffigh  H pressure 2  INHIBITOR  VFAs  RESULTS  VFAs  INHIBITOR  Figure 7.27: Two-Stage Inhibition  Mechanism  Chapter 8  T R E A T M E N T E F F I C I E N C Y IN O P T I M A L  OPERATION  A n experiment was conducted in a 3.04 1 U A S B reactor under optimal operating conditions. T h e reactor configuration was the same as before except that the reactor height was reduced from 168 cm to 30 cm. The optimal operating conditions were selected from the results found in the first three sets of experiments and gave highest treatment efficiency and reliable system stability. These conditions included optimal influent concentration of about 30 g C O D / 1 , reactor height of 30 to 40 cm (for the same diameter) and amount of sulfate addition of 0.2 g/1. T h e reactor was seeded with 1.5 1 of sludge with a V S S concentration of 35.48 g/1. T h e total amount of V S S in the reactor was 53.12  g/1.  The start-up procedure strictly followed the recommendations from the start-up  ex-  periment, being certain that the sludge loading was less than 0.25 g C O D / g V S S . In the first 2 weeks the reactor was fed 0.4 1 of whey daily, which corresponds to a specific sludge loading of 0.22 g C O D / g V S S . The daily feed was increased to 0.8 1 after the 3rd week. T h e gradual increase in feed rate was continued until it finally reached 1.5 1/d after a month. T h e influent concentrations were in the range from 26 to 32 g C O D / 1 and sulfate was added at a concentration of 0.2 g/1. T h e experimental results are presented in Table 8-1. A very high treatment efficiency was obtained in this study.  Over 97% C O D reduction was achieved with an influent  concentration of 32.6 g C O D / 1 , H R T of 2 days and an organic loading rate of 16.61 C O D / 1 d.  170  g  Chapter 8.  TREATMENT  EFFICIENCY  IN OPTIMAL  OPERATION  171  By comparing the results from this work to other treatment systems given in Table 8-2, it can be seen that the highest C O D reduction for high values of organic loading were obtained using the U A S B reactor.  Chapter 8. TREATMENT EFFICIENCY IN OPTIMAL OPERATION  172  Table 8.1: R e s u l t s i n the O p t i m a l O p e r a t i o n  Gas 1/d  CH %  Reduction COD %  0.70  14.07  42.51  97  7.79  0.69  18.12  46.09  97  13.65  7.96  0.63  20.59  43.67  98  1.47  15.96  7.74  0.80  20.36  42.38  97  1.53  16.61  7.69  0.80  21.42  42.44  97  Input g COD/1  Feed 1  OLR g COD/1 d  pH  29.46  0.84  8.05  8.09  1.16  11.39  1.39 32.59  Output g COD / l  Influent Concentration: 29-32 g C O D / 1 Volume O f Reactor: 3 littres Sulfate Concentration: 0.2 g/1  4  Table 8.2: Comparison of Anaerobic Treatment Process for Cheese Whey  Waste  HRT  CMRj  raw  14-70  38  7.5  69  -  18-58  Fixed  sour  5 days  35  6.7  79  14.0  95  film  whey  Boening (1982)  whey  8.9-27hrs  28-31  No  10  8.9-27  77-93  Switzenbaum (1982)  powder  14-16hrs  35  5-15  8.2-22  61-92  raw  5 days  35  64  10.2  76  61-70  6.3-10  82-93  AAFEB  AnRBC  2  3  whey UASB  4  ; raw whey  Temp H (°C) control  Raw Waste Loading Removal g COD/1 g COD/1 d %  Reactor  P  6-11 days •  .No  35  OMR AAFEB AnRBC UASB  Wildcnauer (1985)  Lo & Liao (1986)  5 days  -: 33  No  5-28.7  0.91-6  97-99  this  5 days  33  No  41  7.9-8.2  81-86  study  32.6  16.61  96-98  2 days 1 2 3. 4.  Reference  completely mixed reactor. Anaerobic attached film expanded reactor. Anaerobic rotating biological reactor. Upflow anaerobic sludge blanket reactor.  Chapter 9  CONCLUSIONS,  9.1  CONTRIBUTIONS  CONTRIBUTIONS  Cheese manufacture,  A N D RECOMMENDATIONS  A N D CONCLUSIONS  one of the biggest food industries in North Americans facing the  challenge of a difficult waste disposal problem. Despite the fact that a number of studies on the anaerobic treatment of cheese whey during last decade have proved that anaerobic fermentation  of cheese whey could be an alternative  solution for waste disposal, the  system was suspect due to many unsuccessful experiments and the difficulties frequently encountered in maintaining a stable operation. This study attempted to overcome these difficulties by solving some of the major problems which existed in previous studies by increasing the basic knowledge of this process;  to in turn, facilitate the operation  of  anaerobic reactors and to lead to its better application by industries. Concentration profiles of various parameters in a U A S B reactor are necessary for the development of a dynamic model for the process which can be used for its optimization. From the measurement of these profiles, several interesting conclusions have been drawn. It is believed that this study is the first to show in anaerobic fermentation studies that the two stages, acidogenesis and methanogenesis,  occur separately in the same reactor.  T h e significance of this observation is the realization that two major steps in the whey anaerobic fermentation  process are not necessarily in dynamic balance since the two  reaction rates are very different.  This explains why this system is easily upset.  This  observation also gave a better understanding of how to efficiently control the system's  174  Chapter 9.  CONCLUSIONS,  CONTRIBUTIONS  AND RECOMMENDATIONS  stability by preventing the accumulation of the products in the first stage, e.g.  175  VFAs.  This in turn has led to the experimental study of sulfate effects. Sulfate ions have long been believed to be toxic to anaerobic bacteria.  T h e previ-  ous studies on the effect of sulfate have been limited to its inhibition effects.  These  experimental tests first illustrated the stimulation function of sulfate ions, which greatly supported the fundamental concept of a hydrogen regulation theory.  As a result of the  stimulation, a significant improvement in process stability and treatment efficiency was achieved. T h e knowledge gained from the study on sulfate stimulation provided a better understanding of the inhibition mechanism of anaerobic digestion and had significant implications for the handling of other high strength soluble carbohydrate wastes. Based on this experimental work, the major conclusions are summarized as follows. 1.  T h e results from the preliminary feasibility assessment experiments  have shown  that the anaerobic digestion of cheese whey using a U A S B reactor can be an efficient treatment method for diluted cheese whey. Without p H control and nutrient addition, the system could successfully treat cheese whey up to a concentration  of about 29 g  C O D / 1 . Over 97% C O D removal was achieved. 2. T h e start-up procedure is very important for successful reactor performance. ious start-up strategies were tested in the present  Var-  studies to facilitate start-up of the  U A S B reactor and to ensure stable operation. Among the operating parameters, sludge loading rate was the most critical for proper start-up of the U A S B reactor. T h e initial sludge loading during the start-up period should not exceed 0.25 g C O D / g V S S - d . 3. V F A s were found to be a very useful indicator for primary adaptation of sludge and for monitoring the system stability. T h e loading rate could be increased only after the V F A concentrations in the reactor were at a low value. A rapid increase of O L R may result in the loss of activity of the sludge. 4.  T h e methane production rate was a function of O L R . At an O L R less than 4 g  Chapter 9.  CONCLUSIONS,  CONTRIBUTIONS  AND RECOMMENDATIONS  176  C O D / l - d , the reactor fed with a higher influent concentration yielded a higher methane production rate. When the O L R was greater than 6 g C O D / l - d , a higher influent concentration or shorter H R T led to a lower methane production rate. for this particular system was between 4-6 g C O D / l - d .  T h e optimal O L R  If we choose a H R T of 5 days,  the optimal influent concentration should be between 20-30 g C O D / 1 . 5.  T h e profile of the sludge showed that two sludge regions, sludge bed with high  density V S S and sludge blanket, existed in the U A S B reactor.  T h e distribution of the  sludge was dependent on the process parameters. W i t h an increase in the loading rate the sludge bed expanded, mainly due to the gas production, so that the sludge concentration in the blanket, especially in the area between the bed and blanket, varied with gas flow rate. 6. For highly soluble and easily acidified substrates, such as cheese whey, difficulties existed in maintaining stable operation.  T h e results from this study provided a better  understanding of the cause of the instability. T h e observation that two reaction stages, acidogenesis and methanogenesis,  were distinguished in the U A S B reactor clearly indi-  cated that cheese whey is very easily converted to short chain fatty acids and that the rate of the first step is much higher than that of the second step. T h e appearance of two stages in the same reactor was caused by the excessive accumulation of V F A s from the acidogenesis stage which was the result of either the nature of the substrates or process stress. 7. There is a threshold of influent concentration of cheese whey at a given H R T for stable operation of a U A S B system. If the feed strength exceeds this threshold, instability occurs.  For this system the influent concentration  C O D / 1 at a H R T of 5 days.  should be maintained below 30 g  The optimum influent concentration  would be 25 to 30 g  C O D / 1 based on the finding that system stability can be maintained if the degradation capacity for V F A s is greater than their accumulation.  Chapter 9. CONCLUSIONS,  CONTRIBUTIONS  AND RECOMMENDATIONS  177  8. A l l measured substrate profiles at different operating conditions showed that more than 80% of the C O D reduction took place below a height of 12 cm in the reactor and the sludge concentration was as low as 5 to 10 g VSS/1 above a height of 30 cm. It is therefore recommended that the reactor height should be reduced to 40 cm or less for this reactor with a diameter of 12 cm. 9. T h e significant improvement of process stability and treatment efficiency made by the addition of sulfate clearly illustrated that sulfate acted like a stimulator which helps to maintain favorable conditions for methanogenesis.  The  mechanism of this stimulation is explained according to thermodynamics and hydrogen regulation which suggested that sulfate is able to promote the /3-oxidation of V F A s by consuming hydrogen. 10.  A two-stage inhibition mechanism in anaerobic fermentation  was proposed.  Higher hydrogen pressure is the cause of preliminary inhibition, resulting in the accumulation of V F A s which subsequently inhibit the activity and growth of methanogens in the second inhibition stage. T h e mechanism of inhibition of methanogens from V F A s was interpreted as being caused by the acidification of the internal cytoplasmic p H and destruction of the p H gradient by non-ionized acids based on the theory of bacterial membrane transport.  A new control strategy for anaerobic system stability by using  hydrogenotrophic association was recommended. 11.  Under the optimal operating conditions, over 97%  C O D reduction has been  achieved at an influent concentration of 32.6 g C O D / 1 , an H R T of 2 days and an organic loading of 16.61 g C O D / 1 d. T h i s is much higher than what has previously been reported in the literature.  Chapter 9. CONCLUSIONS,  9.2  CONTRIBUTIONS  R E C O M M E N D A T I O N S  AND RECOMMENDATIONS  F O R F U T U R E  178  R E S E A R C H  The following areas are recommended for future investigation based on the findings made in this research: 1.  It would be instructive to conduct research on the quantitative  relationship be-  tween hydrogen pressure and the concentration or accumulation rate of each volatile fatty acids using different substrates as well as different amounts of sulfate or other hydrogen utilizating reagents.  It is known that the conversion of pyruvate to butyric, propionic  and acetic acids is regulated by hydrogen pressure.  T h e significant reduction of butyric  acid shown by profiles of the V F A s indicated that sulfate serves as a hydrogen sink. The conversion of pyruvate to acetic acid offers a solution for the removal of excess hydrogen, improving the overall stability and the process efficiency. A quantitative relationship is definitely needed for the development of a mathematical model to describe and predict the possible products and their concentrations on system stability.  in the acidogenic step and their effect  These models would be very useful for further development of a  more efficient control strategy for the anaerobic fermentation processes. T h e y would be based on hydrogen partial pressure control as it is especially important according to the two-stage inhibition mechanism. 2.  It is recommended that an extensive study on inhibition kinetics in anaerobic  processes could be made following the two-stage inhibition mechanism proposed in this dissertation.  T h e discovery of new inhibition kinetics could be made on the  concept  that unexpected high hydrogen pressure is the inhibitor for preliminary inhibition and V F A s are both the result of preliminary inhibition and the inhibitor for the secondary inhibition. 3. This research provided the information on the concentration profiles in the U A S B reactor, which has extended our understanding of the anaerobic process and the causes  Chapter 9.  CONCLUSIONS,  of instability.  CONTRIBUTIONS  AND RECOMMENDATIONS  However, information about the substrate concentrations  179  between sam-  ple port 1 and 2 is lacking. Interesting information, related to inhibition and instability, might be presented if there were more sample ports located between port 1 and 2. A n extensive spectrum of substrate concentrations along the reactor column could be attained by constructing the column with a smaller diameter and a larger number of sampling ports. 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Y . pp.23-35  Appendix A  EMPIRICAL M O D E L  In such circumstances  when the mechanism underlying a process is not understood suffi-  ciently well, or is too complicated to allow an exact model to be postulated from theory, an empirical model may be useful. Particularly if it is desired to approximate the response only over limited ranges of the variables.  A.l  T H E P R O G R A M OF MINITAB  Minitab's regression is used to investigate the relationship among variables, particularly those relationships that enable the experimenter to predict a variable from one or more others. Minitab's regression has three features: 1. It applies simple linear regression to investigate the form of a linear relationship between two variables 2.  Multiple regression is for the investigation of the form of the linear relationship  between one variable and several other variables 3. Stepwise regression allows one to explore the relative importance of various predictor variables. T o invoke the regression command, the necessary information, including the dependent variable and its location (column number where it is stored) and independent variables as well as their locations, must be provided. After performing a simple linear regression by R E G R E S S , M I N I T A B first gives the default output.  T h e first fine is the estimated regression equation. 200  T h e second fine is  Appendix A. EMPIRICAL  MODEL  201  the estimate for each of the regression coefficients, their estimated standard deviations, the t-statistics and p-values for testing whether the coefficient is different from zero. T h e third line is the the estimated standard deviation of the regression, the R -squared value, or coefficient of determination and the adjusted R-squared. The final part of the output is the significance test for the regression in an A N O V A form, with a F-statistic and p-value as before. A n additional output can be got by issuing the " B R I E F L E V E L 3" Command in conjunction with the " R E G R E S S " C O M M A N D as show in Table A-6. Additional information is the independent value, the dependent (response) value, the fitted or predicted value (the estimated mean value of the dependent variable from the independent value and the regression equation), the standard error of the fitted value, the residual and the standardized residual. Use of S T E P W I S E command allows one to select from a large set of candidates  the  independent variables that best predict the dependent variable.  A.2 A.2.1  ANALYSIS O F T H E A C C U M U L A T I O N O F A C E T I C A C I D Determination of the Equation  Using the data in Table A - l and running the program of Minitab's regression, we have following results: Due to the shortage of data from the original experimental design, we can not completely go through the Stepwise procedure, as shows in Table A.2.  B u t , through step  by step of addition of each parameter, it was found that the inclusion of the squared terms increased the value of R-squared and decreased the S value. Here S is called "the standard deviation of y about the regression fine" or "the standard error of estimate". T h e value S can be thought of as a measure of how much the observed y values differ  Appendix A. EMPIRICAL  MODEL  202  Table A . l : A c c u m u l a t i o n o f A c e t i c  Acid  In the Absence of Sulfate Influent (g C O D / 1 )  AA at 1#  4.56  AA at 2#  AAi-AAo  • (g/1)  (g/1)  0.382  0.152  0.23  9.93  0.688  0.096  0.59  17.7  0.876  0.02  0.856  28.8  1.166  0.04  1.126  38.1  2.895  2.553  0.342  Influent (g GOD/1)  AA at 1# (g/1)  AA at 2 # (g/1)  AAi-AAo  15  1.038  0.103  0.935  20  1.163  0.043  1.120  30  1.403  0.073  1.330  40  1.600  0.057  1.543  50  2.127  1.714  0.413  1# 2#  (g/1)  sample port 1 sample port 2  In the presence of Sulfate  (g/D  Appendix A. EMPIRICAL  203  MODEL  Table A.2: S t e p w i s e A n a l y s i s f o r A c c u m u l a t i o n of A c e t i c  MTB MTB  > >  stepwise  STEPWISE STEP CONSTANT Co**3 T-RATIO S R-SQ MORE? SUBO SUBO  y  i n c2,  REGRESSION  OF  x  in c l  c3-c6  AA  ON  5  PREDICTORS,  Acid  WITH  N =  5  1 0.5143 0.00004 8.50  0.207 96.01 ( Y E S , N O , SUBCOMMAND,  OR H E L P )  j;uu<:>  from the corresponding average y value If a cubic term was included, the R-squared value went further up to 96 and the S value went down. It was obvious that the best equation was one which included influent concentration, its square and cubic terms as follow:  AA = - 0 . 2 7 + 0.183Co - 0.0102Co + 0.000197Co 2  A.2.2  3  (A.l)  A n a l y s i s of t h e A d e q u a c y o f t h e E q u a t i o n  T h e evaluation of the residuals and fitted values can be used to examine the model adequacy. Residual is the difference between the observation and the fitted value determined by regression equation. T h u s residuals tell us how the model missed in fitting the data.  Appendix A. EMPIRICAL  204  MODEL  Table A.3: S t e p w i s e A n a l y s i s for A c c u m u l a t i o n of A c e t i c  Acid  The r e g r e s s i o n equation i s AA = - 0.032 + 0.0601 Co < Predictor Constant Co  Coef  Stdev  -0.0317 0.06010  s = 0.4185  0.3560 0.01528  R-sq = 83.8%  t-ratio  -0.09 3.93  P  0 .935 0.029  R-sq(adj) == 78.3%  A n a l y s i s of Variance 1  SOURCE Regression Error Total Obs.  1 2 3 4 5  DF  1 3 4  Co  4.6 9.9 17.7 28.8 38.1  SS  MS  2.7089 0 .5255 3.2344 AA  0.382 0.688 0.876 1.166 2.685  Fit  0.242 0.565 1.032 1.699 2.258  F  2.7089 0.1752  15. 47  Stdev.Fit  Residual  0.299 0.241 0.190 0.232 0.336  0 .140 0.123 -0.156 -0.533 0.427  P  0.029  St .Resic  0. 48 0.36 -0. 42 - 1 . 53 1. 71  Appendix  A. EMPIRICAL  MODEL  205  Table A.4: S t e p w i s e A n a l y s i s for A c c u m u l a t i o n o f A c e t i c  Acid  MTB > MTB > regr c l 2 c2 c6 The r e g r e s s i o n equation i s AA = - 0.058 + 0.0597 Co + 0.171 Co**1.5 Predictor Constant Co Co**1.5  Coef -0.0577 0.05969 0.1711  s = 0.4388  Stdev 0.3745 0.01603 0.2004  R-sq = 88.1%  t-ratio -0.15 3.72 0.85  P 0.892 0.065 0. 483  R-sq(adj) = 76.2%  A n a l y s i s of V a r i a n c e SOURCE Regression Error Total  DF 2 2 4  SS 2.8494 0.3850 3.2344  SOURCE Co Co**1.5  DF 1 1  SEQ SS 2.7089 0.1405  MS 1.4247 0.1925  F 7.40  P 0. 119  CONTINUE? Obs. 1 2 3 4 5  Co 4.6 9.9 17.7 28.8 38.1  AA 0.382 0.688 0.876 1.166 2.685  F i t Stdev.Fit 0.386 0.355 0.364 0.345 1.170 0.256 1.490 0.345 2.387 0.384  Residual -0.004 0.324 -0.294 -0.324 0.298  St.Resid -0.01 1.20 -0.83 -1.20 1.40  Appendix A. EMPIRICAL  MODEL  206  Table A.5: Stepwise Analysis for Accumulation of Acetic Acid  MTB > r e g r c l 2 c2 c5 The r e g r e s s i o n equation i s AA = 1.87 + 0.180 Co - 1.02 Co**0.5 Predictor Constant Co Co**0.5  Coef 1 .870 0. 1799 -1. 0164  s = 0.4025  Stdev 1.739 0.1084 0.9113  R-sq = 90.0%  t-ratio 1.08 1.66 -1.12  P 0.395 0.239 0.381  R-sq(adj) == 80.0%  A n a l y s i s of Variance SOURCE Regression Error Total  DF 2 2 4  SS 2.9104 0. 3240 3.2344  SOURCE Co Co**0.5  DF 1 1  SEQ SS 2.7089 0. 2015  MS 1.4552 0.1620  F 8.98  P 0.100  CONTINUE?  Obs. 1 2 3  4 5  Co 4.( 9.9 17.7 28.8 38.1  AA 0.382 0.688 0.876 1.166 2.685  F i t Stdev.Fit 0.380 0.520 0.453 0.252 0.778 0.292 1.596 0.242 0.366 2.450  Residual -0.138 0.235 0.098 -0.430 0.235  St.Resid -1.04 0.75 0.35' -1.34 1.41  Appendix A. EMPIRICAL  207  MODEL  Table A.6: S t e p w i s e A n a l y s i s for A c c u m u l a t i o n of A c e t i c A c i d  MTB > b r i e f output l e v e l 3 MTB > regr c l 2 c2 c3 The r e g r e s s i o n equation i s AA = 0.666 - 0.0381 Co + 0.00230 Co**2 Predictor Constant Co Co**2  Coef 0.6665 -0.03808 0.002299  s = 0.3128  Stdev 0.4642 0.05469 0.001252  R-sq = 93.9%  t-ratio 1.44 -0.70 1.84 R-sq(adj)  p 0.288 0.558 0.208 = 87.9%  A n a l y s i s of Variance SOURCE Regression Error Total  DF 2 2 4  SS 3.0387 0.1957 3.2344  SOURCE Co Co**2  DF 1 1  SEQ SS 2.7089 0.3298  MS 1.5193 0.0979  F 15.53  p 0.061  CONTINUE? Obs. 1 2 .3 4 5  Co 4.6 9.9 17.7 28.8 38.1  AA 0.382 0.688 0.876 1.166 2.685  F i t Stdev.Fit 0.541 0.276 0.515 0.182 0.713 0.225 1.476 0.212 0.298 2.552  Residual -0.159 0.173 0.163 -0.310 0.133  St.Resid -1.08 0.68 0.75 -1.35 1.40  Appendix A. EMPIRICAL  208  MODEL  Table A . 7 : S t e p w i s e A n a l y s i s f o r A c c u m u l a t i o n of A c e t i c A c i d  MTB MTB  > b r i e f output l e v e l > r e g r c l 2 c2 c4  3  The r e g r e s s i o n e q u a t i o n i s AA = 0.540 - 0.0026 Co +0.000039 Predictor Constant Co Co**3 s  Coef 0.5400 -0.00260 0.00003910  = 0.2541  Analysis  Stdev 0.3161 0.02695 0.00001578  R-sq = 96.0%  Co**3 t-ratio 1.71 -0.10 2. 4 8 R-sq(adj)  P 0.230 0.932 0.132 = 92.0%  of Variance  SOURCE Regression Error Total  DF 2 2 4  SS 3.1053 0.1291 3.2344  SOURCE Co Co**3  DF 1 1  SEQ SS 2.7089 0.3964  MS 1.5526 0.0646  F 24.05  P 0.040  CONTINUE?  CONTINUE? Obs. Co 1 4.6 2 9.9 3 17.7 4 28.8 5 38.1  AA 0.382 0.688 0.876 1-166 2.685  Fit Stdev.Fit 0.532 0.216 0.552 0.146 0.711 0.174 1.399 0.186 2.603 0.247  Residual -0.150 0.136 0.165 -0.233 0.082  St.Resid -1.12 0.65 0.89 -1.34 1.39  Appendix A . EMPIRICAL  209  MODEL  Table A.8: S t e p w i s e A n a l y s i s f o r A c c u m u l a t i o n of A c e t i c  MTB > b r i e f o u t p u t l e v e l 3 MTB > r e g r c l 3 c2-c4 * NOTE * Co i s h i g h l y c o r r e l a t e d w i t h o t h e r * NOTE * Co**2 Is h i g h l y c o r r e l a t e d w i t h o t h e r * NOTE * Co**3 i s h i g h l y c o r r e l a t e d w i t h o t h e r The AA  Predictor Constant  +  0.1449 0.02967 0.001609 0 .00002496  0.18258 -0.010247 0.00019653  Co  **2 Co**3  R-sq = 99.9%  = 0.05573  Analysis  Stdev  Coef -0.2703  C o  s  equation is 0 . 1 8 3 Co - 0 . 0 1 0 2 C o * * 2  regression  = — 0.270  Acid  predictor predictor predictor  variables variables variables  +0.000197 Co**3  t-ratio -1.87  P  0.313 0 .103 0.099 0.080  6.15  -6.37 7.88  R - s q ( a d j ) = 99.6%  of Variance  SOURCE Regression Error Total  DF 3 1 4  SS  MS  3 . 2313 0 . 0031 3 . 2344  1.0771 0.0031  F 346.81  0 .039  P  CONTINUE? SOURCE Co  ' DF  Co**2 Co**3  Obs. 1 2 3 4 5  SEQ  i 1 1  Co  4.6 9.9 17.7 28.8 38.1  SS '  2 . 7089 0 . 3298 0 . 1926  AA  0.3820 0.6880 0.8760 1.1660. 2.6850  X d e n o t e s an obs.  Pit  0.3678 0.7247 0.8408 1.1832 2.6805  Stdev.Fit  0.0539 0.0419 0.0432 0.0530 0.0555  whose X v a l u e g i v e s  Residual  0.0142 -0.0367 0.0352 -0.0172 0.0045  i tlarge  St.Resid  influence.  1. -1. 1. -1. 1.  00 00 00 00 00 X  Appendix A. EMPIRICAL  MODEL  210  Figure A - l is a plot of the fitted values vs the actual values.  T h i s plot shows a ver3  r  good fit between the model and the data. In addition, plots of the residuals vs fit, actual values and independent variables were all made (Figures A-2 to A-5).  Strong pattern or  tendency in the residual plot indicates that we probably have a poor model. If the model is serious wrong, the residuals would tend to more positive for some parts of x values, and more negtive for others. However, none of them showed up any problem regarding the model adequacy.  A.2.3  The Comparison between the Experimental Data and the Model  Figure A - 6 presents the experimental data (points) and the model (curve).  It shows a  good fit.  A.3  S U M M A R Y OF EMPIRICAL MODELS  Following exactly the same procedure as described in the above section, the models for degradation of acetic acid and models for accumulation and degradation of propionic acid and total V F A s i n both the absence and presence of sulfate were developed as fo  A.3.1  In the Absence of Sulfate  Accumulation of AA (acetic acid)  AA = -0.27 + 0.183Co + -0.0102Co + 0.000197Co 2  Degradation of A A R a (Table A.9)  3  '  (A.2)  Appendix A. EMPIRICAL  211  MODEL  MTB > MTB > plot c31 c l _  *  2.40 + fit 1.60 + _  *  0.80+ _  *  *  * +  0.50  +  1.00  — - - -  +  1.50  +-  +  2.00  2.50  Figure A . l : Fitted Values versus the Actual Values  :  AA  Appendix A. EMPIRICAL  MTB  > print  ROW  212  c l c31 c22  AA 0. 382 0. 688 0. 876 1. 166 2 .685  1 2 3 4 5  MODEL  fit 0. 3678 0. 7247 0. 8408 1. 1832 2. 6805  residual 0 .0141891 -0 .0367000 0 .0352088 -0 .0172389 0 .0045412  MTB > MTB > •II  MTB  >  > plot  c22 C31  -  *  0.025+ residual-  *  0.000+  *  -  *  -0.025+  -  * +  0.50  +  1.00  +  1.50  +  2.00  MTB > MTB >  Figure A.2: A n a l y s i s o f r e s i d u a l s  +  2.50  f  i t  Appendix A.  MTB > MTB > p l o t  EMPIRICAL  213  MODEL  c22 c l  0.025+ residual-  *  0.000+  -0.025+  +-  0.50  1.00  1.50  2.00  MTB >  Figure A.3: A n a l y s i s o f r e s i d u a l s  2.50  -AA  Appendix A. EMPIRICAL  MODEL  214  MTB > p l o t cc22 c2  0.025+ residual-  ' *  0.000+  -0.025+  7  -°  + 14-0  + 21.0  + 28.0  MTB > MTB >  Figure A.4: Analysis of residuals  + 35.0  Co  Appendix A. EMPIRICAL  215  MODEL  MTB > MTB > p l o t c22 c3  0.025+ residual-  *  0.000+ *  —  -0.025+  +0  300  +600  + 900  + 1200  MTB >  Figure A.5: Analysis of residuals  + 1500  Co**2  Appendix A. EMPIRICAL  0  x  216  MODEL  10  20  30  40  hfijent Concentjation (g CCD/ft  Figure A.6: Comparison of Experimental Data with Model  50  Appendix A. EMPIRICAL  217  MODEL  Table A.9: Regression Analysis for Degradation of Acetic Acid MTB > p r i n t c l 2 - c l 5 ROW 1 2 3 4 5  l/r  C  C**2  C**(-2)  4 .34783 1 .68919 1 .16822 0 .88810 2 .92398  4 .56 9 .93 17 .70 28 .80 38 .10  20.79 98.60 313.29 829.44 1451.61  0 .0480917 0 .0101415 0 .0031919 0 .0012056 0 .0006889  MTB > The regression equation i s l / r = 3.68 - 0.293 C + 0.00707 C**2 + 38.1 C**(-2) Predictor Constant C C**2 C**(-2)  Coef 3.682 -0.2927 0.007075 38.14  s = 0.4739  Stdev 1.993 0.1703 .003305 30.45  R-sq = 97.3%  t-ratio 1.85 -1.72 2.14 1.25  P 0.316 0.335 0.278 0.429  R-sq(adj) = 89.0%  Analysis of Variance SOURCE Regression Error Total  DF 3 1 4  SS 7.9592 0.2246 8.1838  SOURCE C C**2 C**(-2)  DF 1 1 1  SEQ SS 0.7734 6.8336 0.3523  MS 2.6531 0.2246  F 11.81  P 0.210  CONTINUE? Obs. 1 2 3 4 5  C 4.6 9.9 17.7 28.8 38.1  l/r 4.348 1.689 1.168 0.888 2.924  F i t Stdev.Fit 4.328 0.474 1.859 0.442 0.839 0.341 1.166 0.384 2.825 0.464  Residual 0.020 -0.170 0.329 -0.277 0.099  St.Resid 1.00 X -1.00 1.00 -1.00 1.00  X denotes an obs. whose X value gives i t large influence.  Appendix A. EMPIRICAL  Ra  MODEL  218  = 3.68 - 0.293Co + 0.00707GV + 38.lCo~  2  (A.3)  Accumulation of propionic acid (PA)  PA = 0.112 - 0.00893Co + 0.00108GV  (A.4)  Degradation of PA Rp  -J- = -18.3 + 0.488Co + 216CO-  Rp  (A.5)  1  Accumulation of V F A  VFA  = 2.12 - 0.0325Co - 5.76Co  (A.6)  _1  Degradation of V F A Rv  — = -0.648 + 0.0288Co + 9.02CO" Rv  1  (A.7)  Appendix A. EMPIRICAL  A.3.2  MODEL  In the Presence of Sulfate  Accumulation of A A  AAs = 0.504 + 0.0590Co - 0.00172CV + 0.000024Co  = 15.6 - 0.63Co + 0 . 0 0 8 1 5 C V - 1 0 4 C o Rs Accumulation of P A  PAs = 0.603 - 0.039lCo + 0.001416V  4- = 11-0 - 0.54Co -f 0.00715GV Rs  Accumulation of V F A  VFA  Degradation of V F A  = 1.77 - 0.0552Co + 0.00215CV  _1  Appendix A. EMPIRICAL  MODEL  - j - = 3.36 - 0.213Co + 0.00367GV  Rs  220  (A.13)  Appendix B  E F F E C T S O F S U L F A T E IN B A T C H E X P E R I M E N T S  B.l  INTRODUCTION  When wastewater is subjected to anaerobic digestion, a high concentration of sulfate has been thought to be toxic for methanogenic bacteria (see literature review).  Recent  research has greatly increase the knowledge about the function of sulfate in the anaerobic process. It is known that the sulfate requirement of methanogens in anaerobic digestion is a complex function.  O n one hand, sulfate reducing bacteria help to maintain -the  anaerobic condition required for the growth of methanogens. Sulfur, which is the reduced product of sulfate in the anaerobic process, is also a nutrient necessary for methanogens. O n the other hand, the addition of sulfate inhibits methanogenesis. T h e inhibition from sulfate is attributed to that methanogens and sulfate reducing bacteria competing for the common substrates, acetic acid and hydrogen. In the presence of excess hydrogen, they have no effects on each other. W h e n the substrates supply becomes rate hmiting, however, competition does take place. A s described in earlier chapters, unsuccessful experiments on anaerobic digestion of cheese whey have been reported by a number of researchers. has been done so far to solve or to explain these failures.  Little research, however, T h e problems encountered  in previous studies has been generally attributed to inadequate buffering capacity and micronutrient deficiency of cheese whey.  According to the mechanisms considered in  Chapter 7, it can be assumed that sulfate, in the proper concentration, may be applied  221  Appendix  B.  EFFECTS  OF SULFATE  IN BATCH  222  EXPERIMENTS  Table B . l : Independent V a r i a b l e s in B a t c h E x p e r i m e n t  Levels  Variables  +  .  -  0.6  0  C h e e s e W h e y C o n c e n t r a t i o n (g C O D / 1 )  6  3  Sludge C o n c e n t r a t i o n  1.5  0.75  Sulfate  (g/1)  (g/1)  to moderate the detrimental influences of excess hydrogen on a stressed anaerobic reactor. The practical question is what sulfate concentration in an industrial wastewater of a given composition, such as cheese whey, makes anaerobic digestion possible and successful. This preliminary experiment, therefore, was carried out to find how sulfate affects the anaerobic digestion system  B.2  PRELIMINARY EXPERIMENTAL  B.2.1  DESIGN  Variables  The independent variables are presented in Table B - l . The concentration of cheese whey was chosen based on consideration of the possible organic loading rate during the start-up period for successful treatment.  According to  previous studies for a cheese whey anaerobic process, the organic loading rate cannot  Appendix  B.  EFFECTS  OF SULFATE  IN BATCH  Table B.2: E x p e r i m e n t a l  223  EXPERIMENTS  D e s i g n of B a t c h  Run  Table B-2 Experimental Design of Batch R u n Run  S  1 2 3 4 5 6 7 8  _  • -+ ++-  Co  A  -  -  + +-  - .  + +  -  + + + +  Appendix B. EFFECTS  OF SULFATE IN BATCH  EXPERIMENTS  224  exceed 0.3 g C O D / g VSS at the start-up. T h e maximum concentration of sludge available in the lab is about 20 g VSS/1. Therefore, the upper limit of cheese whey concentration was 6 g C O D / 1 .  A 3 g C O D / 1 difference would make the response variables, such as  gas composition and treatment efficiencj', different. So 3 g C O D / 1 was the lower limit. The possible lower limit of sludge concentration  might be 10 g/1 based on the same  consideration of organic loading rate. The concentration of sulfate was chosen based on the literature review.  T h e toxic  levels of sulfate for methanogens varied from one study to another. Generally, the optimal concentration of sulfate for methanogens growth in the anaerobic process was reported in the range of 0.1-1 m M , which is equal to 0.014-0.14 g Na S0 /\. 2  4  Based on the  mechanism of competition of both methanogens and sulfate reducing bacteria for common substrates, it would be reasonable to consider the ratio of C O D concentration and sulfate in the experiment. The only information that could be had from literature indicated that when the ratio of C O D to sulfate decreased below 10, sulfate reduction would occur and methanogenesis would be inhibited. T h e upper limit concentration of sulfate was set in such a way that the lowest ratio of C O D / N a S 0 2  4  concentration should be 0.6 g/1 at its upper limit.  was about 5. Therefore, the sulfate T h e lower Hmit was set at zero to  maximize the difference.  B.2.2  Experimental Design  A full 2  3  factorial design with duplicates was used i n this experiment.  shown in Table B-2  T h e layout is  Appendix B. EFFECTS  B.3 B.3.1  EXECUTION  OF SULFATE IN BATCH  EXPERIMENTS  225  OF T H E EXPERIMENT  Substrate  Cheddar cheese whey was used in this study.  T h e C O D concentration  of the original  substrate was as high as 65 g C O D / 1 and p H as low as 4. T h e cheese whey was dilute to the desired concentrations,  6 g C O D / 1 and 3 g C O D / 1 .  Then potassium hydroxide was  used to adjust the p H to 7  B.3.2  Seed Sludge (Bacteria)  T h e seed sludge was obtained from the effluent of a laboratory-scale,  upflow anaerobic  sludge blanket ( U A S B ) reactor and had a concentration of about 20 g V S S / 1 .  B.3.3  Reactor Operation  16 flasks with volume of 250 ml were used to as the batch reactors in this experiment. Each flask was seeded 75 m l sludge with two different V S S concentrations  as desired in  experimental design. They were sampled and fed once a week. In the first week each of flasks was fed 100 ml substrate liquid containing different concentrations  of sulfate and  cheese whey according to the experimental design. In the subsequent week, from each of them was drawn a 60 ml sample for analysis and fed 60 m l of the substrates which ware exactly the same composition as the first time. A l l the flasks were randomly located in the incubator under a constant temperature of 3 5 ° C .  Appendix B. EFFECTS  B.3.4  OF SULFATE IN BATCH  EXPERIMENTS  226  Chemical Analyses  Gas production was collected daily for each reactor. Gas composition was analyzed every other day. The liquid in the flasks was withdrawn once a week for analysis of C O D (Chemical Oxygen Demand), V F A (Volatile Fatty Acids), p H and residual sulfate. Both gas composition and V F A were analyzed on a Hewlett Packard 5890A gas chromatograph}'. C O D was determined by a colorimetric method. Sulfate analysis was conducted according to the "standard methods".  B.4  B.4.1  RESULTS A N D DISCUSSION  E f f e c t s of Sulfate (S), F e e d S t r e n g t h  (Co) and Seed Sludge A m o u n t  ( A ) on the M e t h a n e P r o d u c t i o n  4  (CH %)  A n anaerobic process is considered to be a step-wise process which proceeds in different successive stages. Anaerobic conversion of the acid products into methane and carbon dioxide, also called "methanogenesis", is the terminal and rate-limiting step of the whole sequence. Methane formation is accomplished by the methane bacteria. Methane content in the produced gas is one of the indicators of activity of the methane bacteria as well as of the system's performance. T h e experimental results are summarized in Table B-3. Subscripts a, b and c stand for sampling time, the first, the third and the fourth week from the start of the experiment respectively. Using the J A S S program, the main effects of S, C o and A and their interactions were estimated, which are presented in Table B-4. During the first week of the experiment, the effect of C o was the most significant one. As we can see from the cube plots (Figure B - l ) and the data analysis, CH % 4  increased  an average of about 7.4 units when the influent concentration decreased from 6 g C O D / 1 to 3 g C O D / 1 .  In comparison with the effect of C o , the effects of S and A were less  Appendix B. EFFECTS  OF SULFATE IN BATCH  EXPERIMENTS  227  Table B.3: E x p e r i m e n t a l R e s u l t s  Row 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  SulfateCODSludgeCH4%-aCH %-bCH %-c 4  -1 1 -1 1 -1 1 -1 1 -1 1 -1 . 1 -1 1 -1 1  1 -1 -1 1 1 -1 -1 1 1 -1 -1 1 1 -1 -1 1  -1 -1 -1 -1 1 1 1 1 -1 -1 -1 -1 1 1 1 1  60.15 59.29 52.99 52.09 60.30 57.70 52.25 50.11 61.13 59.66 54.82 51.75 60.10 58.62 51.92 51.55  47.65 45.26 49.30 49.25 48.06 47.08 46.61 46.92 48.12 44.74 50.06 49.70 53.36 49.05 47.00 47.19  4  48.48 48.41 45.47 46.81 49.88 46.65 54.02 48.12 49.00 46.48 44.84 47.12 51.48 47.56 47.28 46.87  pH 6.500 6.725 6.445 6.615 6.770 6.805 6.500 6.750 6.500 6.715 6.430 6.605 6.785 6.830 6.490 6.740  significant during the first week. T h e less significant effect of S might be attributed to two reasons. O n one hand, sulfate reducing bacteria (SRB) might not have built up and less competitive in the first week. It could also be due to the fact that growth of S R B was limited by the low concentration of sulfate in the culture. A higher concentration of sulfate addition might have led to a statistically significant effect of sulfate on the gas composition. A s time passed, it became clear that the effect of S on the gas composition was somehow related to the feed strength. Look at the upper surface (higher strength) and the lower surface (lower strength) of the cube plot (Figure B-2, C r 7 % in the third week). 4  For lower feed strength of 3 g C O D / 1 , the C r 7 % in the generated gas changed from 47.9% 4  in the absence of sulfate to 45% in the present of sulfate, or from 50.7% to 48.1%. While  Appendix  B. EFFECTS  OF SULFATE  IN BATCH  EXPERIMENTS  228  CH4I-a - 50.8 /  52.1 /  /  / : / : / : 1  / 51.9  53.9  - 58.2  60.2 /  / -1  /  /  / /  /  1 e  9 d  / «  £0.6  59.5  1  s  -1  CH4I-b  self -1 .  4S.8 /  1  - 47.1 /  / : / : / ! 1  / /  49.5  49.7  50.7 /  - 48.1 / e  /  /  / -1  47.9 sulf  1  Figure B . l : E f f e c t of sulfate on B i o g a s  g  / d / o 45.0 1 -1 s  Composition  1  Appendix B. EFFECTS OF SULFATE IN BATCH EXPERIMENTS  229  Table B.4: Y a t e s A n a l y s i s  CH %-a  CH %-b  CH %-c  55.90 -1.61 -7.43 -1.12 -0.01 -0.04 -0.29 0.40  48.08 -1.37 0.33 0.15 1.39 0.17 -2.80 0.05  48.03 -1.55 -0.92 1.91 0.88 -1.18 1.16 -0.67  4  Average Co A SCo SA CoA GoAS  4  4  pH 6.64 0.17 -0.13 0.14 0.04 -0.03 -0.05 0.06  Appendix B. EFFECTS  CH % 4  OF SULFATE IN BATCH  EXPERIMENTS  230  was almost the same for both cases of absence and presence of sulfate when higher  C O D concentration was applied. This result demonstrated that the S R B competed more effectively at lower substrate level. In contrast to sulfate, the effects of C o became less significant after 3 weeks running. This is because the microbes in the reactor had been acclimatized and their concentration increased. T h e interaction effects of S and C o , Co and A were not negligible compared to the main effect of S although they didn't cause inhibition.  The interaction plot of  CH % 4  (Figure B-3) shows that the interactions between sulfate and feed strength (the ratio of C O D / N a S 0 ) , and feed strength and sludge concentration (sludge loading) are more 4  significant than the interaction of sulfate and sludge concentration. It has been reported that the inhibition of sulfate on the activity of methanogens is related to the ratio of feed strength and sulfate concentration in terms of GOT)/Na S0 . 2  4  W h e n the ratio is  smaller than 10, inhibition could occur. In this study, the ratio was even as low as 5, but no inhibition was noticed. We would suggest that the critical value of sulfate causing inhibition to an anaerobic process may vary with substrates.  For a highly soluble feed,  such as cheese whey, a higher sulfate concentration can be tolerated since excess hydrogen and fatty acid exist in this system. A n unusual observation was made that the effect of sludge on the gas composition was negative in the first week.  T h a t meant that the more sludge in the reactor, the  less methane that was produced in the experiment.  Generally, a higher concentration  of sludge should result, in higher methane production since the sludge loading is lower. T h e only explanation for this observation was that the lower concentration of sludge was made in such a way that 35 m l sludge was mixed with 35 ml of effluent from an anaerobic digester, which contained bacteria and a higher p H (about 8.0), which might have increased the buffer capacity of the system. Therefore, in spite of a low concentration of sludge, it could have higher activity and buffer capacity than that of the original sludge.  Appendix B. EFFECTS  OF SULFATE IN BATCH EXPERIMENTS  231  CH4%-b 1  50.7 s  1 d g  I j I i  I I I  e  1  I  u  -1  48.1  i  47.9  45.0 sulf  .  -1  1 Co=  -1 CH4%-b 46.8  47.1  I  I  49.7  49.5 sulf  -1  1 co=  Figure B.2: Effect o f S u l f a t e on t h e B i o g a s  1  Composition  Appendix B.  EFFECTS  OF SULFATE IN BATCH  EXPERIMENTS  232  OM-b 52  52 *  -  C-„  4S * C+  +C  4  8  +  1  _  +  f T >  111  It!  44  f  » H « » I I I  111 f f i : f . f ] _P  44 *  t  -1  sulf  sulf  t«ol> t«ol> tvol>  twol> twol> twol> intplot Cl CH4I-b  52 +  48 +  »"t  tii  u r n  nun  in  nt  44 •  Co  Interaction Effects of Sulfate (S), Influent C O D (C), and Sludge (A): (a) S and C , (b) S and A , (c) C and A  Figure B.3:  Appendix B. EFFECTS  OF SULFATE IN BATCH  EXPERIMENTS  233  Table B.5: A N O V A Table  Fcrit  SS  MS  F  2  656.49  328.25  42.07  2.80  Treat  15  149.54  9.97  1.28  1.88  Exp.E  30  234.09  7.80  Total  47  1040.12  Source  DF  Block  Where DF=degreee of freedom, SS=sum square.  of square, MS=raean  The unusual phenomenon disappeared and the effect of sludge on the methane production could be ignored in subsequent weeks experiments because the sludge in both cases was acclimatized. It was noticed in this experiment that there was a time effect in batch culture. Considering time effect as the block effect (the first week and the third week), we constructed the ANOVA table (Table B-5) to find how significant the block effect was. From the F values in Table B-5 we can see that the block effect was very significant. This indicated that the effects of feed strength and sludge concentration changed with time. None of the main effects was clearly statistically significant from this experiment except the feed strength in the first week based on the calculation of a 95 % confidence  Appendix B. EFFECTS  interval.  OF SULFATE IN BATCH  EXPERIMENTS  234  Therefore, the scales of the factors should be made larger to increase the dis-  crimination, especially the sulfate concentration. T h e upper limit of sulfate concentration was based on the previous studies, but it still didn't cause any significant effects, which also revealed that the critical inhibition value of sulfate on cheese whey is higher than that of other substrates which have lower solubility.  B.4.2  Effects o f S , C o a n d A o n p H of t h e S y s t e m  p H is one of the important parameters for an anaerobic system.  T h e optimum p H for  methanogenesis is between 7.0.to 8.0 units. Below 6.0, methanogenesis will be inhibited. Therefore, p H value could be an indicator of the system stability and its performance. T h e higher the p H , the more stable the system is. From the results of yates analysis we can see that the effect of sulfate on p H was very significant.  B y using feed containing sulfate, pHs averaged 0.2 units higher than using  feed without sulfate. This indicated that, at these experimental conditions, the addition of sulfate helped to maintain the stability of the system since it can increase the buffer capacity of a cheese whey anaerobic digestion system. T h e effects of C o and A were also significant. p H decreased with the increase of feed strength and increased with the increase of the amount of the seed sludge. There was no unusual observation as i n the case of methane production since the p H data were taken after 3 weeks operation. T h e effects on p H had an estimated standard deviation of 0.0096 with 8 degree of freedom. T o determine the confidence interval from the N=16-run  ts  2.306 x 0.0096  N 4  2  + 0.011  (B.l)  Appendix B. EFFECTS OF SULFATE IN BATCH  235  EXPERIMENTS  Table B.6: 95% C o n f i d e n c e I n t e r v a l  to  0 .16  to  - 0 .14  0.15  to  0 .13  0.05  to  0 .03  0.18  0.17+0.01  or  -0.13+0.01  or  A  0.14+0.01  or  SCO  0.04+0.01  d'r  SA  -0.03+0.01  or  -0.02  to  -0  COA  -0.05+0.01  or  -0.04  to  -0 .06  0.06+0.01  or  0.07  to  0 .05  s Co  SCO A  -0.12  04  T h e 95% confidence intervals are shown in Table B-6. Since none of these effects include zero in the confidence interval, it can be stated that all of these effects are significant at the 95% confidence level. However, the intplot of Fig.B-5 shows that the interactions are not important in. these operating conditions. The  predominant effects are basically the first order terms.  Figure B-6 is the plot of  fitted value vs the actual p H value with a linear model. Note the fit is fairly good. So the interaction effects on p H can be negligible. This allows one to use the method of steepest ascent i n the next experimental step.  T h e different results between the two responses,  % C i ? 4 and p H , show that p H is more sensitive to the process parameters than % C i ? 4 . As a general procedure, the residuals were plotted. anything unusual. Figure B-7 demonstrates  None of those plots appeared  that residuals basically center at zero.  Appendix B.  EFFECTS  OF SULFATE  IN BATCH  EXPERIMENTS  two!) twol) e f f e c t s Effect  Std Error Effect  t-Ratio  Effects ! . S  Average  £.63781  .00240 -27653E+4  i  1  < •  salf (S) .17063 Co <C) -.13188 sludge (1) .14188 SC .04062 SI -.02SS3 C! -.04563 SCI  .06438  S = .00960 with  .00430 .00460 .00480 .00490 .00480 .00480  35.54180 -27.47010 23.55300 8.46230 -5.33778 -9.50334 .00480 13.40360  8 d.f.  .1 + t  : . sci ; . sc <  .0 +  : . si  ] . Cl  -.1 + twol> t«ol> cube  ' '  PH .495  .745  /  / / .438  1  /:  /  /:  :  / :  !  / .610  ! !  I I  C o  ! : :  -1  /  H:  '  i s subtracted Read .438 as 6.438  t <  .778 /  i i  P  fi  !-- .818 ': " / e .  J .500  ! :  1  g d I o .720 1 -1 /  /  s  suit -I  1  Figure B.4:  Effect of S u l f a t e o n p H  *  I  Appendix B. EFFECTS  OF SULFATE IN BATCH  EXPERIMENTS  237  pH 6.8 +  6.8 + a  "  ii  "  il  ,,"  II  ii  it  i  II  6.6  II  M  in  II  , *C  ||"  "  |~1  1+"  D  .  • II  I!  6.6 +  ,,-C  L  .  + C-"  ,,"  .  .  II  .  ii  i  II  II  "  II  - I-  - C+'  1  6.4 +  6.4 +  1  ;alf  -1  suit  tvo!> t«ol> intplot Cl pH £.8  + -  1*  tl  ri  c 11 11 i n  6.6 + l - ,  ii  f f f  M i l l  n  "+!  lift  III I.J 6.4 +  -1 Co  B.5: Interaction Effects of Sulfate (S), Influent C O D (C), and Sludge (a) S and A , (b) S and C , (c) C and A  Figure  (A):  Appendix B. EFFECTS OF SULFATE IN BATCH EXPERIMENTS  tvol> plot fitted pH  5.75 +  fitted «3  /  6.50 +  + 6.4  6.5  +-  1  6.6  6.7  +-^6.8  pH  Figure B.6: F i t t e d p H versus A c t u a l V a l u e  Appendix B.  EFFECTS  OF SULFATE  IN BATCH  EXPERIMENTS  .10 +  .05 +  residual  t*  t  .00 +  t  .05 +  *  i  +  1  0  5  i  1  10  15  OBSERVATION  Figure B.7: A n a l y s i s of  Residuals  239  Appendix B. EFFECTS  B.5  OF SULFATE IN BATCH  EXPERIMENTS  240  CONCLUSIONS  1. A n interesting finding is that the effects of sulfate on the gas composition was related to the feed strength.  At lower feed strength, V0CH4  decreased when sulfate was used.  However, no difference in gas composition between sulfate used and the control case was observed for higher feed strength.  This illustrated that S R B competed with methane  bacteria more effectively at lower substrate levels. 2.  Contrary to reports in the literature,  no inhibition was observed even when the  ratio of C O D and sulfate was as low as 5 and the sulfate concentration  was as high  as 60 m.M/1. This can be attributed contributed to cheese whey characteristics of high solubility , and high feed strength (compared to 0.5 -1 g C O D / 1 in the previous studies). Therefore, the critical inhibition value of sulfate varies from one substrate to another. Using higher solubility substrates as feed, such as cheese whey, the inhibition value of sulfate is higher than that of other substrates which have lower solubility since excess hydrogen exists in such a system. 3. T h e effect of sulfate on p H is significant. p H is higher when sulfate was applied. This indicates that a proper concentration of sulfate can help to maintain stability since sulfate in a proper concentration increases the buffering capacity of an anaerobic process by competing for excess hydrogen and fatty acids with methane bacteria. 4.  p H significantly decreased with the increase of feed strength and increased with  the increase of sludge amount.  B.6  CRITIQUE OF T H E E X P E R I M E N T A N D F U T U R E P L A N  T h e upper limitation of sulfate was set based on a literature review. This sulfate concentration could cause inhibition in some anaerobic treatment of wastewaters, but it seemed too low to produce a significant effect on the gas composition for cheese whey.  Much  Appendix B. EFFECTS  OF SULFATE IN BATCH  EXPERIMENTS  Table B.7: E x p e r i m e n t a l D e s i g n B a s e d o n S t e e p e s t  Co COD/1  S g/i Coding  Coefficients  o f coded  Coefficients  of o r i g i n a l  Design  coefficients  centre  Possible  point  steepest  -  path  unit  Ascent  A g  VSS  0.5  1.5  0 .3  increment  Adjusting  g  241  0 ,085  -0.066  0.071  0 .0255  -0.099  0.036  0 .25  -1  0.36  0 .3  4.5  1.13  0 .55  3.5  1.5  0 .8  2.5  1 .05  1.5  2.22  1 .3  0.5  2.56  "  1.86  more sulfate should be used i n order to obtain a possibly significant effect.  So far, we  don't know what the possible inhibition value of sulfate for a cheese whey anaerobic process is because we believe that the value varies with the substrates.  Since a linear  relationship was observed between p H and the operation variables (no interactions),  it  would be useful to use a steepest ascent strategy to search optimum operating conditions. Table B - 7 below shows values for the three operating variables along the direction of steepest ascent. It was originally proposed to test more response behaviors, such as C O D , volatile fatty acids and so on. However, these responses could not give meaningful information, perhaps due to the disadvantages of batch experimentation for a biological process.  and the short period used  A continuous experimental mode will be set up to gain more  Appendix B. EFFECTS  OF SULFATE IN BATCH  EXPERIMENTS  242  accurate determination of these effects. One may choose 6 different levels of sulfate ranging between 0.5 to 10 g/1 for two levels of 5 and 20 g C O D / 1 cheese whey feed. For a long run, the initial seed amount is not a very important parameter.  So, a 6 x 2 experimental design will be carried out.  Hence the interaction effects may have some effects even though they didn't play significant roles in the effects on the CH  A  interpret the interaction effects  %.  Future studies would be necessary  to  Appendix C  T H E C A L C U L A T I O N O F NON-IONIZED A C I D  Cl  THEORY  A weak acid or base is a weak electrolyte, which is only partially ionized in an aqueous solution, and as a result equilibrium is established between the ionized and unionized chemical forms. According to the Bronsted theory, an acid is a proton donor, whereas a base is a proton acceptor. A chemical equation representing the ionization of a weak monoprotic acid may written as  HA—>H +A~ +  (Cl)  the equilibrium constant expression for equation C - l has the form  KA  ~ ~\HAY  • (C  2)  Where K a represents the thermodynamic equilibrium constant for the acid reaction. B y introducing the definition of p H and p K a , this equation becomes  243  Appendix C. THE CALCULATION  OF NON-IONIZED ACID  H = Ka + Log^-t  P  P  244  (C.3)  This equation is known as the Henderson-Hasselbalch equation and is useful in calculation of pH of a solution. C.2  C A L C U L A T I O N O F NON-IONIZED ACID  Let X represent the fraction of the initial acid concentration which is ionized, from equation (C-l)  HA = H  +  Co-X  X  + A~  (C.4)  X  where Co is termed the initial concentration of the weak acid, Co-X represents the non-ionized acid. Substituting x for A~ and Co-X fo HA, we have the results in Table  Appendix D  STATISTICAL A N A L Y S I S O F p H  Comparison of p H in the absence and presence of sulfate was carried out by using a statistical program Minitab. Minitab is a general purpose statistical computing system which can be used to solve various statistical problems. Before carrying out any statistical test, some assumptions should be made, ie the error is independent, identically and normally distributed ( U N D (0.0)) and the samples are representive. T o compare two sets of independent data , the standard deviations and other statistics are calculated.  Independent data means the members of the two sets are not related,  thus two groups of p H measurements are not linked to the same influent concentration, even though the substrate and operation temperature are the same. T h e results are given in Table D - l . T h e important difference between the two sets of p H data can be seen clearly from the dotplot. T h e p H in the absence of sulfate is much lower than that observed in the presence of sulfate. T h e p H in the absence of sulfate ranges from 6.75 to 7.18, giving a average of 7.037. T h e p H in the presence of sulfate has a range of 7.55 to 7.87, resulting in a mean value of 7.687. Next we need to know how much difference there is between these two means. T h a t can be done by the t-test using the T W O S A M P L E command as shown in Table D-2. T h e 95% confidence interval means that if these 7 p H values were a random sample from a large population of p H sampling, then a 95% confidence interval for the average change  245  Appendix D. STATISTICAL  ANALYSIS OF pH  246  due to the addition of sulfate in that population would be 0.485 to 0.815. Thus, we would be fairly certain that p H is increased, on the average, by at least 0.48 and maybe by as much as 0.82 p H units. As shows in Table D-2, the confidence interval is from 0.485 to 0.815, which does not include zero, thus it can be stated that the p H without sulfate is significantly different from the p H with sulfate. It should be mentioned that if the two populations have the same standard deviation, a subcommand of P O O L E D can follow T W O S A M P L E , allowing one to get smaller confidence interval and slightly more likelihood to reject a true null hypothesis. T h e P O O L E D means the standard deviation from the two samples are pooled to get an estimate of the common standard deviation. This difference essentially disappears with moderately large sample size. It was recommended that it's better not to use the P O O L E D subcommand. If the standard deviations are equal, you have lost little as shows in Table D-3. T h e use of P O O L E D did not make very much difference. If they are unequal, you may have gained a lot. If you use the pooled procedure when it is not appropriate,  such as, when the  standard deviation of the two population are not equal, you could be seriously misled. For example, you might falsely claim to have evidence that the two populations differ when they really do not. A t-test can be further made to test the statistic significance. T=8.68 > t(0.025, 12)= 2.179 here 0.025=a/2, a=0.05 and 1 2 = ^ -f n -2=7+7-2 2  T h e critical T for 95% confidence and 12 degrees of freedom is 2.179 which is smaller than the calculated t=8.68. The conclusion is that the p H of the effluent was significantly increased by adding sulfate.  Appendix D. STATISTICAL  ANALYSIS OF H  247  P  Table D . l : C a l c u l a t i o n of S t a n d a r d D e v i a t i o n s  MTB > p r i n t c l ROW 1 2 3 4 5 6• 7  c2  pH  pH-S  6.75 6.92 7.08 7.05 7.10 7.18 7.18  7.75 7.87 7.73 7.58 7.56 7.55 7.77  MTB > MTB > MTU > MTB  > d o t p l o t c l c2;  S U B O same.  -+-pH  +-  7.00  6.75  +7.25  +7.50  +7.75  MTB >  MTB > d e s c r i b e c l c2 pH pH-S PH pH-S  N  MEAN  MEDIAN  TRMEAN  MAX  Ql 6.9200 7.5600  Q3. 7.1800 7.7700  7 7  7.0371 7.6871  MIN 6.7500 7.5500  7.1800 7.8700  7.0800 7.7300  7.0371 7.6871  STDEV  0.1543 0.1242  SEMEAN  +•-pH-S  8.00  0.0583 0.0469  Appendix  D. STATISTICAL  ANALYSIS  OF pH  248  Table D.2: t-test  MTB > twosample c2 c l TWOSAMPLE T FOR pH-S VS pH N MEAN STDEV pH-S 7 7.687 0.124 pH 7 7.037 0.154  SE MEAN 0.047 0.058  95 PCT CI FOR MU pH-S - MU pH: (0.485, 0.815) TTEST MU pH-S = MU pH (VS NE): T= 8.68 MTB >  P=0.0000  DF=  11  Appendix D. STATISTICAL  249  ANALYSIS OF pH  Table D.3: t-test  MTB > MTB > tvosaraple c l c 2 ; SUBO pooled. TWOSAMPLE T FOR pH VS pH-S N MEAN STDEV pH 7 7.037 0.154 pH-S 7 7.687 0.124  SE MEAN 0.058 0.047  95 PCT C I FOR MU pH - MU pH-S: (-0.813, -0.487) T T E S T MU pH = MU pH-S (VS NE) : T= -8.68 POOLED STDEV =  0.140  P = 0.0000  DF=  12  Appendix  DATA  E  TABLES  250  Appendix E.  DATA  TABLES  Table E . l : S l u d g e  KINETICS ANALYSIS SI IN. COD LOADIG EFF.COD g/i g/i g/1 d .5...Q00 0.132 0.910 4.560 0.191 1.970 9.930 0.286 3.540 17.700 5.960 0.457 28.000 :*8-.100 7.770 4.877  251  Growth  (dX/dt)/X dX dt (dF/dt)/X X SLUDGE RATIO OF F/S g VSS day g VSS g/g d £6.540 0.0013 ,097 3.060 17.000 133.600 0.0023 .263 7.370 30.000 107.400 0.0077 .548 91.700 7.050 10.000 0.696 38.46.0 ' 12J)00 0.0281 114.200 164.900 0.0254 0.656 67.140 16.000  FOR (dX/dt)/X=Y*(dF/dt)/X-Kd Regression Output: Constant Kd=-0.015742 Std-Err of Y Est 0.007 R Squared 0.799 No. of Observations 4.000 Degrees of Freedom 2.000 X Coefficient(s) Y=0.0584564447 Std E r r of Coef. 0.0208  Appendix E. DATA  TABLES  Table E.2: T h e P r o p i o n i c A c i d ( P A )  In the Absence of Sulfate P A at 1#  P A at 2#  (g/1)  (g/1)  (g/1)  4.56  0.092  0.060  0.032  9.93  0.134  0.014  0.120  17.7  0.290  0.330  -0.040  28.8  0.748  0.036  0.712  38.1  1.336  1.192  0.144  P A at 1#  P A at 2#  PAi-PAo  (g/1)  (g/1)  (g/1)  15  0.279  0.064  0.215  20  0.399  0.035  0.364  30  0.901  0.021  0.880  40  1.050  0.040  1.010  50  2.268  1.685  0.583  Influent  (g COD/1)  PA PA r  9  In the Presence of Sulfate Influent  (g COD/1)  Appendix E. DATA  TABLES  253  Table E.3: T h e T o t a l V o l a t i l e F a t t y A c i d  (TVFA)  In the Absence of Sulfate Influent (g C O D / 1 )  T V F A at 1#  T V F A at 2#  TVFA TVFA  (g/1)  (g/1)  (g/D  4.56  0.958  0.274  0.684  9.93  1.962  0.124  1.838  17.7  2.624  0.023  2.601  28.8  2.174  0.076  2.09S  38.1  3.585  2.148  1.437  Influent (g C O D / 1 )  A A at 1#  A A at 2#  AA1-AA9  (g/1)  (g/1)  (g/D "*  15  1.335  0167  1.168  20"  1.562  0.078  . 1.484  30  2.314  0.094  2.220  40  2.650  0.097  2.553  50  4.504  3.999  0.505  r  In the Presence of Sulfate  9  Appendix E.  DATA  TABLES  254  Table E.4: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n of V F A AAs  Co  Co**2  Co** 3  Co**0.5  1 .103 1 .136 1 .413 1 .600 2 .127  15 20 30 40 50  225 400 900 1600 2500  3375 8000 27000 64000 125000  3.87298 4.47214 5.47723 6.32456 7.07107  ROW 1 2 3 4 5 >  MTU  Co**0.5 i s h i g h l y c o r r e l a t e d w i t h other X v a r i a b l e s Co**0.5 has been removed from the e q u a t i o n Co i s h i g h l y c o r r e l a t e d w i t h Co**2 i s h i g h l y c o r r e l a t e d with Co**3 i s h i g h l y c o r r e l a t e d w i t h  * NOTE * * NOTE * * NOTE *  other other other  The r e g r e s s i o n e q u a t i o n i s AAs = 0.504 + 0.0590 Co - 0.00172 Co**2 +0.000024 Predictor Constant Co Co**2 Co**3  s = 0.07773 Analysis  R-sq = 99.1%  t-ratio 0.55 0.60 -0.54 0.73  variables variables variables  Co**3  P 0.677 0.656 0.687 0.599  R - s q ( a d j ) = 96.5%  of Variance  SOURCE Regress ion Error CONTINUE?  DF .3 1  CONTINUE? Total SOURCE Co Co**2 Co**3 Obs. 1 2 3 4 5  Stdev 0.9074 0.09825 0.003221 0.00003267  Coef 0.5036 0.05899 -0.001724 0.00002382  predictor predictor predictor  MS 0.23061 0.00604  F 38.16  P 0.118  0.69787 DF 1 1 1  Co 15.0 20.0 30.0 40.0 50.0  SS 0.69183 0.00604  SEQ SS 0.65956 0.02906 0.00321 AAs 1.1030 1.1360 1.4130 1.6000 2.1270  F i t Stdev.Fit 1.0809 0.0745 1.1843 0.0609 1.3647 0.0609 1.6290 0.0721 2.1201 0.0774  Residual 0.0221 -0.0483 0.0483 -0.0290 0.0069  X d e n o t e s an obs. whose X v a l u e g i v e s i t l a r g e  St.Resid 1.00 -1.00 1.00 -1.00 1.00 X  influence.  Appendix E. DATA  TABLES  255  Table E.5: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n o f V F A  Al  A2  1/Rs  C  C**2  C**(-l)  C**0.5  1. 038 1. 163 1. 403 1. 600 2. 127  0 .103 0 .043 0 .073 0 .057 1 .714  1. 06952 0. 89286 0. 75188 0. 64809 2. 42131  15 20 30 40 50  225 400 900 1600 2500  0 .0666667 0 .0500000 0 .0333333 0 .0250000 0 .0200000  3.87298 4.47214 5.47723 6.32456 7.07107  ROW 1 2 3 4 5 MTU  >  * *  C**0.5 i s h i g h l y c o r r e l a t e d w i t h o t h e r X v a r i a b l e s C**0.5 has been removed from t h e e q u a t i o n  * NOTE * * NOTE * * NOTE *  C i s h i g h l y c o r r e l a t e d with other C**2 i s h i g h l y c o r r e l a t e d w i t h o t h e r C * * ( - l ) i s highly c o r r e l a t e d with other  The r e g r e s s i o n e q u a t i o n i s 1/Rs = 15.6 - 0.630 C + 0.00815 C**2 - 104 Predictor Constant C C**2 C**(-l)  Coef 15.569 -0.6297 0.008148 -104.01  s = 0.3100 Analysis  R-sq = 95.4%  DF 3 1  Total  MTU  DF 1 1 1 C 15.0 20.0 30.0 40.0 50.0  >  C**(-l) P 0.358 0.317 0.270 0. 436  R - s q ( a d j ) = 81.7%  SS 2.00290 0.09611  MS 0.66763 0.09611  F 6.95  P 0.270  2.09901  SOURCE C C**2 C**(-l)  MTB >  t-ratio 1.59 -1.84 2.22 -1.22  variables variables variables  of Variance  SOURCE Regression Error CONTINUE?  Obs. 1 2 3 4 5  Stdev 9 .801 0.3424 0.003674 84.95  predictor predictor predictor  SEQ SS 0.71137 1.14746 0.14408 1/Rs 1.070 0.893 0.752 0.648 2.421  F i t Stdev.Fit 1.022 0.306 1.032 0.277 0.543 0.229 0.816 0.261 2.371 0.306  Residual 0.048 -0.140 0.209 -0.167 0.050  St.Res i d 1.00 -1.00 1. 00 -1.00 1.00  Appendix E. DATA  TABLES  256  Table E.6: A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n o f V F A ROW 1 2 3 4 5  Co  PA1  PA2  4 .56 9 .93 17 .70 28 .80 38 .10  0 .092 0 .134 0 .290 0 .748 1 . 336  0 .060 0 .014 0 .003 0 .036 1 .192  Co**2  Co**3  20.79 98.60 313.29 829.44 1451.61  94.8 979.1 5545.2 23887.9 55306.3  1/r 31 .2500 8 .3333 3 .4843 1 . 4045 6 .9444  Co**(-l) -1.00000 1.00000 -1.00000 1.00002 -1.00014  MTB >  MTII >  MTB > MTB > r e g r * NOTE * * NOTE * * NOTE *  c2 4 c Co Co**2 Co**3  l c5-c8 i s highly c o r r e l a t e d with other i s h i g h l y c o r r e l a t e d with other i s highly c o r r e l a t e d with other  predictor predictor predictor  variables variables variables  The r e g r e s s i o n e q u a t i o n i s PA1 = 0.108 - 0.00749 Co +0.000984 Co**2 +0.000002 Co**3 + 0.00213 Co**( Predictor Coef Constant 0.107665 Co -0.00748717 Co**2 0.00098372 Co**3 0.00000159 Co**(-l) 0.00212939 s = * Analysis  Stdev 0.000000 0.00000000 0.00000000 0.00000000 0.00000000  t-ratio  P *  *  *  *  of Variance  SOURCE Regress ion Error Total  DF 4 0 4  SS 1.102920  DF 1 1 1 1  SEQ SS 1.030516 0.072380 0.000007 0.000017  MS 0.275730 *  F  P  1.102920  CONTINUE? SOURCE Co Co**2 Co**3 Co**(-l) Obs. 1 2 3 4 5 MTB > MTB >  Co 4.6 9.9 17.7 28.8 38.1  PA1 0.09200 0.13400 0.29000 0.74800 1.33600  F i t Stdev.Fit 0.09200 * 0.13400 * 0.29000 * 0.74800 * 1.33600 *  Residual 0.00000 0.00000 0.00000 0.00000 0.00000  St.Resid * * * * *  Appendix E.  DATA  257  TABLES  Table E.7: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n o f V F A  MTB > s t e p w i s e y i n c 2 x i n c l c 5 c 6 c 7 * ERROR * ARGUMENT IS A CONSTANT OR M A T R I X , MTB > s t e p w i s e *  ERROR  c2  4 c l c5 c6 c7  STEPWISE  c2  4 cl  c5-c7  REGRESSION OF  STEP CONSTANT  1 0.04401  2 0.11244  Co**2 T-RAT10  0.00088 35.41  0.00108 76.93  S R-SQ MORE? SUBO SUBO  c8  * I L L E G A L ARGUMENT  MTB > s t e p w i s e  Co T-RATIO  BUT A COLUMN WAS E X P E C T E D  PA1  ON  -0.00893 -14.60 0.0296 0.00350 99.76 100.00 ( Y E S , N O , SUBCOMMAND, OR H E L P )  4 PREDICTORS,  WITH N =  5  Appendix E. DATA TABLES  258  Table E.8: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n o f V F A MTB > s t e p w i s e  c2 4 c l c5-c7  STEPWISE REGRESSION OF  PAl  STEP CONSTANT  1 0.04401  2 0.11244  Co**2 T-RATIO  0.00088 35.41  0.00108 76.93  Co T-RATIO  ON  4 PREDICTORS, WITH N =  -0.00893 -14.60  S 0.0296 0.00350 R-SQ 99.76 100.00 MORE? (YES, NO, SUBCOMMAND, OR HELP) SUBO :;mt MTB > r e g r c2 2 c l c5 The r e g r e s s i o n e q u a t i o n i s P A l = 0.112 - 0.00893 Co + 0.00108 Co**2 Predictor Constant Co Co**2  Coef 0.112443 -0.0089276 0.00107690  s = 0.003497  Stdev 0.005189 0.0006114 0.00001400  R-sq  100.0%  t-ratio 21.67 -14.60 76.93 R-sq(adj)  p 0.002 0.005 0.000  = 100.0%  A n a l y s i s of Variance SOURCE Regression Error Total  DF 2 2 4  SS 1.10290 0.00002 1.10292  SOURCE Co Co**2  DF 1 1  SEQ SS 1.03052 0.07238  MS 0.55145 0.00001  F 45084.95  P 0.000  CONTINUE? Obs . 1 2 3 4 5  Co 4.6 9.9 17.7 28.8 38.1  PAl ,09200 ,13400 .29000 .74800 1.33600  F i t Stdev.Fit 0.09413 0.00309 0.12998 0.00203 0.29181 0.00251 0.74855 0.00237 1.33554 0.00333  Residual -0.00213 0.00402 -0.00181 -0.00055 0.00046  St.Resid -1. 30 1.41 -0.74 -0.21 0.44  Appendix E. DATA TABLES  259  Table E.9: A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n Co  PAl  PA2  1/r  Co**2  4 .56 9 .93 17 .70 28 .80 38 .10  0 .092 0.134 0 .290 0.748 1 .336  0 .060 0 .014 0 .003 0 .036 1 .192  31 .2500 8 .3333 3 .4843 1 .4045 6 .9444  20.79 98.60 313.29 829.44 1451.61  ROW 1 2 3 4 5 MTB  > stepwise  of V F A  Co**3  Co**(-l)  94.8 979.1 5545.2 23887.9 55306 . 3  0.219298 0.100705 0.056497 0.034722 0.026247  c4 4 c l c5-c7  STEPWISE REGRESSION OF  1/r  STEP CONSTANT  1 -2.369  2 -9 .280  Co**(-l) T-RATIO  145 5.30  184 17.67  ON  4 PREDICTORS,  WITH N  0.00020 5.80  Co**3 T-RATIO  1.25 S 4.32 99.46 R-SQ 90.35 MORE? (YES, NO, SUBCOMMAND, OR HELP) SUBO MTB > r e g r c4 4 c l c5-c7 * NOTE * Co i s h i g h l y c o r r e l a t e d w i t h o t h e r  * The 1/r  predictor  Co**2 i s h i g h l y c o r r e l a t e d w i t h o t h e r X v a r i a b l e s Co**2 has been removed from t h e e q u a t i o n r e g r e s s i o n equation i s = - 11.4 + 0.112 Co +0.000160 Co**3 + 192 C o * * ( - l )  Predictor Constant Co Co**3 Co**(-l)  Coef -11.438 0.1119 0.0001597 191.59  s = 1.717  Stdev 8.721 0.4396 0.0001797 34.37  R-sq = 99.5%  t-ratio -1.31 0.25 0.89 5.57 R-sq(adj)  P 0.415 0.841 0.537 0.113 = 98.0%  A n a l y s i s of Variance SOURCE Regress ion Error Total CONTINUE?  DF 3 1 4  SS 576.66 2.95 579.61  MS 192.22 2.95  F  65.19  P 0.091  variables  Appendix E. DATA  TABLES  Table E.10: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  SOURCE Co Co**3 Co**(-l) Obs. 1 2 3 4 5  DF 1 1 1 Co 4.6 9.9 17.7 28.8 38.1  SEQ SS 243. 14 241. 92 91. 61 1/r 31 .250 8 . 333 3 .484 1 .404 6 .944  F i t Stdev.Fit 31 .101 1.711 9 .123 1.525 2 .252 1.196 2 .252 1. 493 6 .688 1.698  X d e n o t e s an obs. whose X v a l u e MTB MTB  > >  of V F A  gives  Res i d u a l 0.149 -0.789 1.232 -0.848 0.256  i t large  St.Resid 1.00 X -1.00 1.00 -1.00 1.00  influence.  Appendix E.  DATA  TABLES  Table E . l l : Analysis for Accumulation and Degradation of V F A  MTB > MTB > r e g r c4 2 c l c7 The l/r  r e g r e s s i o n equation i s = - 18.3 + 0.488 Co + 216 C o * * ( - l )  Predictor Constant Co Co**(-1)  Stdev 3. 819 0.1115 19 .30  Coef -18 .311 0. 4884 216.:L8 R-sq  s = 1.625  t-ratio -4.79 4.38 11.20  P 0.041 0.048 0.008  = 99 .1%  R - s q ( a d j ) = 98.2%  MS 287.17 2.64  A n a l y s i s o f Var i a n c e SOURCE Regress i o n Error Total  DF 2 2 4  SS 574 .33 5. 28 579 .61  SOURCE Co Co**(-l)  DF 1 1  SEQ SS 243. 14 331. 20  F 108.80  P 0 . 009  C O N T 1 NI1K?  Obs. 1 2 3 4 5 MTU  Co 4.6 9.9 17.7 28.8 38.1 >  l/r 31 .250 8 .333 3 .484 1 .404 6 .944  F i t Stdev.Fit 1.601 31. 324 1.154 8. 310 2. 548 1.087 0.917 3. 262 1. 414 5. 972  Residual -0.074 0.024 0.936 -1.858 0.972  St.Resid -0. 27 0 .02 0.78 -1.39 1.22  Appendix E. DATA  TABLES  Table E.12: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n  of  The r e g r e s s i o n e q u a t i o n i s 1/r = - 2.37 +- 145 C o * * ( - l ) Predictor Constant Co**(-l) s  Stdev 3.070 27.28  Coef -2.369 144.61  = 4.317  R-sq = 90.4%  t-ratio -0.77 5.30 R-sq(adj)  P 0.497 0.013 = 87.1%  A n a l y s i s of Variance SOURCE Regress i o n Error Total Obs. C o * * ( - l ) 1 0.219 2 0.101 3 0.056 4 0.035 5 0.026 MTB >  DF 1 3 4  SS 523.70 55.91 579.61 1/r 31.25 8.33 3. 48 1.40 6.94  MS 523.70 18.64 F i t Stdev.Fit 4.08 29.34 1.96 12.19 5.80 2.11 2.41 2.65 1.43 2.55  F 28.10  Residual 1.91 -3.86 -2.32 -1.25 5. 52  P 0.013  St.Resid 1.35 -1.00 -0.61 -0.35 1.59  Appendix  E. DATA  TABLES  263  Table E.13: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n of V F A  The r e g r e s s i o n e q u a t i o n i s P A s l = 0.275 - 0.0160 Cso +• 0.00105 Cso**2 4- 0.117 1/Cos Predictor Constant Cso Cso**2 1/Cos  Stdev 0.8816 0.06160 .0009478 0.1202  Coef 0.2746 -0.01595 0.0010453 0.1168  s = 0.2411  R-sq = 97.7%  t-ratio 0.31 -0.26 1.10 0.97 R-sq(adj)  P 0.808 0.839 0.469 0.509 = 90.7%  A n a l y s i s of Variance SOURCE Regress ion Error Total  DF 3 1 4  SS 2.44093 0.05811 2.49904  SOURCE Cso Cso**2 1/Cos  DF 1 1 1  SEQ SS 2.23270 0.15334 0.05489  MS 0.81364 0.05811  F 14.. 00  P 0.193  CONTINUE? CONTINUE? Obs. Cso 1 15.0 2 20.0 3 30.0 4 40.0 5 50.0  f  PAsl 0.279 0.399 0.901 1.050 2.268  F i t Stdev.Fit 0.387 0.215 0.257 0.195 0.854 0.236 1.192 0.195 2.207 0.233  Residual -0.108 0.142 0.047 -0.142 0.061  St.Resid -1.00 1.00 1.00 -1.00 1.00  Appendix E. DATA  TABLES  264  Table E.14: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n o f V F A  MTB MTB  > r e g r c22 2 c21 c25  The r e g r e s s i o n e q u a t i o n i s P A s l = 0.603 - 0.0391 Cso + 0.00141 Cso**2 Predictor Constant Cso Cso**2  Coef 0.6026 -0.03910 0.0014122  s = 0.2377  Stdev 0.8030 0.05602 0.0008572  R-sq = 95.5%  t-ratio 0.75 -0 .70 1.65 R-sq(adj)  P  0.531 0.557 0.241 = 91.0%  A n a l y s i s of V a r i a n c e SOURCE Regress ion Error Total  DF 2 2 4  SS 2.3860 0.1130 2.4990  SOURCE Cso Cso**2  DF 1 1  SEQ SS 2.2327 0.1533  Obs. 1 2 3 4 5  Cso 15.0 20.0 30.0 40.0 50.0  MTB > MTB > MTU  >  PAsl 0.279 0.399 0.901 1.050 2.268  MS  1.1930 0.0565  F i t Stdev.Fit 0.205 0.334 0.141 0.386 0.701 0.174 0.159 1.298 2.178 0.228  F 21.11  Residual -0.055 0.013 0.200 -0.248 0.090  P 0.045  St.Resid -0.46 0.07 1.24 -1. 40 1.34  Appendix E. DATA  TABLES  Table E.15: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n of V F A  MTB > MTB > r e g r  cl2 2 e l l cl5  The r e g r e s s i o n e q u a t i o n i s C12 = 1.77 - 0.0552 Cso + 0.00215 Cso**2 Predictor Constant Cso Cso**2 s  = 0.3299  Analysis  Stdev 1.115 0.07776 0.001190  Coef 1.768 -0.05523 0.002148  of  R-sq = 96.5%  t-ratio 1.59 -0.71 1.81  P  0.254 0. 551 0.213  R - s q ( a d j ) = 93.1%  Variance  SOURCE Regression Error Total  DF 2 2 4  SS 6.0888 0.2177 6.3065  SOURCE Cso Cso**2  DF 1 1  SEQ SS 5.7340 0.3549  MS 3.0444 0.1089  F 27.97  P  0.035  CONTINUE? Obs. 1 2 3 4 5 MTB > MTB >  Cso 15.0 20.0 30.0 40.0 50.0  C12 .335 .562 .314 .650 .504  F i t Stdev.Fit 1.423 0.285 1.523 0.195 2.045 0.241 2.996 0.221 4.378 0.317  Residual -0.088 0.039 0.269 -0.346 0.126  St.Resid -0.53 0.15 1.20 -1.41 1.36  Appendix E. DATA  TABLES  266  Table E.16: A n a l y s i s f o r A c c u m u l a t i o n a n d D e g r a d a t i o n o f V F A  MTB > p r i n t  c21-c28  )W  Cso  PAsl  PAs2  1/rs  Cso**2  Cso**3  1 2 3 4 5  15 20 30 40 50  0.279 0.399 0.901 1.050 2.268  0.064 0.035 0.021 0.040 1.685  4 .65116 2 .74725 1 .13636 0 .99010 1 .71527  225 400 900 1600 2500  3375 8000 27000 64000 125000  P s l -Ps2 0 . 215 0 .364 0 .880 1 .010 0 .583  MTB > s t e p w i s e c24 4 c21 c25 c26 c28 STEPWISE REGRESSION STEP CONSTANT 1/Cos T-RATIO Cso**3 T-RATIO  OF  -0.5539  1  2 -3.4673  71.84 3.89  120.65 129.91  1/rs  ON  4 PREDICTORS,  0.00002 62.83  S 0.709 0.0196 R-SQ 83.46 99.99 MORE? (YES, NO, SUBCOMMAND, OR HELP)  WITH N  Appendix E. DATA  TABLES  267  Table E.17: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n o f V F A  MTB > r e g r  c24 2 c21 c25  The r e g r e s s i o n e q u a t i o n i s 1/rs = 11.0 - 0.540 Cso + 0.00715 Cso**2 Pred i c t o r Constant Cso Cso**2 s = 0.2830 Analysis  Stdev 0.9559 0.06669 0.001020  Coef 10.9582 -0.54036 0.007148  of  R-sq = 98.2%  t-ratio 11.46 -8.10 7.00  P 0.008 0.015 0.020  R - s q ( a d j ) = 96.5%  Variance  SOURCE Regress ion Error Total  DF 2 2 4  SS 8.9662 0.1601 9.1263  SOURCE Cso Cso**2  DF 1 1  SEQ SS 5.0380 3.9282  MS 4.4831 0.0801  F 56.00  P 0.018  CONTINUE? Obs . 1 2 3 4 5  MTI  Cso 15.0 20 30 40 50  1/rs 4.651 2.747 1.136 0.990 1.715  F i t Stdev.Fit 4.461 0.244 3.010 0.167 1.180 0.207 0.780 0.189 1.809 0.272  Residual 0.190 -0.263 -0.044 0.210 -0.094  St.Resid 1.33 -1.15 -0.23 1.00 -1.18  Appendix E. DATA  TABLES  268  Table E.18: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n of V F A MTB  > print Co  VFA1  VFA 2  4 .56 9 .93 17 .70 28 .80 38 .10  0.958 1.962 2.624 2.174 3.585  0.274 0.124 0.023 0.076 2.148  ROW 1 2 3 4 5  cl-c8 co**2  1/Co  20.79 98.60 313.29 829.44 1451.61  0. 219298 0. 100705 0. 056497 0. 034722 0. 026247  1/rr 1 .46199 0 .54407 0 .38447 0 .47664 0 .69589  MTB > MTB > MTU  * *  >  Co**0.5 i s h i g h l y c o r r e l a t e d with o t h e r X v a r i a b l e s Co**0.5 has been removed from the e q u a t i o n  * NOTE *  Co i s h i g h l y c o r r e l a t e d  The  equation i s  regression  with other  VFA1 = 5.91 - 0.236 Co + 0.00484 co**2 - 18.3 C Po rn e ds it ca tn otr Co co**2 1/Co s  4. 018 Stdev 0.2704 0.004825 14 .32  5Coef .908 -0. 2357 0 .004839 -18.32  Analysis  0.380 p 0.544 0.499 0. 422  t - r a1.47 tio -0.87 1.00 -1.28  R - s q ( a d j ) = 62.9%  DF 3 1 4  SS 3. 3382 0. 3413 3. 6795  MS 1.1127 0.3413  DF 1 1 1  SEQ SS 2. 7596 0. 0197 0. 5589  R-sq  variables  1/Co  = 90.7%  = 0.5842  predictor  of V a r i a n c e  SOURCE Regression Error Total  F 3.26  P 0 . 382  CONTINUE? SOURCE Co co**2 1/Co Obs. 1 2 3 4 5 X  Co 4 .6 9 .9 17. 7 28. 8 38. 1  dftnotfts  an  VFA1 0.958 1.962 2.624 2.174 3.585 o b s .  uhosft  F i t Stdev.Fit 0. 916 0.583 2. 200 0.534 2. 217 0.420 2. 498 0 .486 3. 472 0.573 X  v a l u e  q i v « s  i t  Residual 0.042 -0.238 0. 407 -0.324 0.113  l a r g f ;  St. Resid 1. 00 •1. 00 1. 00 •1. 00 1. 00  i n f 1 iiftncft.  Appendix E. DATA  TABLES  269  Table E.19: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n of V F A  MTB  > regr  c2 2 c l c6  The r e g r e s s i o n e q u a t i o n i s VFA1 = 2.12 + 0.0325 Co - 5.76 1/Co Predictor Constant Co 1/Co s  Coef 2 .121 0.03246 -5 .762  = 0.5851  R-sq  Stdev 1.375 0.04016 6.950  t-ratio 1.54 0.81 -0.83  P 0.263 0.504 0.494  = 81.4%  R - s q ( a d j ) == 62.8%  MS 1 . 4974 0 .3423  A n a l y s i s of Variance SOURCE Regression Error Total  DF 2 2 4  SS 2. 9949 0. 6846 3. 6795  SOURCE Co 1/Co  DF 1 1  SEQ SS 2 .7596 0. 2353  F 4.37  P 0.186  CONTINUE? Obs. 1 2 3 4 5  Co 4.6 9.9 17.7 28.8 38.1  VFA1 0.958 1.962 2.624 2.174 3.585  F i t Stdev,Fit 1.006 0.577 1.863 0.416 2.370 0.391 2.856 0.330 3.207 0.509  Residual -0.048 0.099 0.254 -0.682 0.378  St.Res i d . -0.48 0. 24 0. 58 -1. 41 1. 31  Appendix E. DATA  270  TABLES  Table E.20: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n of V F A  *  Co**0.5 i s h i g h l y c o r r e l a t e d w i t h o t h e r X v a r i a b l e s Co**0.5 has been removed from t h e e q u a t i o n Co i s h i g h l y c o r r e l a t e d  * NOTE *  with other  The r e g r e s s i o n e q u a t i o n i s 1 / r r = - 0.579 + 0.0239 Co +0.000088 co**2 + 8.79 Predictor Constant Co co**2 1/Co s = 0.02197 Analysis  Stdev 0.1511 0.01017 0.0001814 0.5385  Coef -0.5789 0.02394 0.0000880 8.7929 R-sq  99.9%  t-ratio -3.83 2.35 0.48 16. 33  predictor  variables  1/Co  P 0.163 0.256 0.713 0.039  R - s q ( a d j ) = 99.7%  of Variance  SOURCE Regression Error Total  DF 3 1 4  SS 0.75313 0.00048 0.75361  DF 1 1 1  SEQ SS 0.17626 0.44817 0.12869  MS 0.25104 0.00048  F 520.17  P 032  CONTINUE? SOURCE CO . CO**2 1/Co Obs. 1 2 3 4 5  Co 4.6 9.9 17.7 28.8 38.1  1/rr 1 .46199 0 .54407 0 .38447 0 .47664 0 .69589  F i t Stdev.Fit 1. 46040 0.02191 0. 55301 0.02007 0. 36918 0.01577 0. 48883 0.01828 0. 69165 0.02155  Res i d u a l 0.00159 -0.00894 0.01529 -0.01218 0.00424  St.Resid 1.00 X -1.00 1.00 -1.00 1.00  Appendix E. DATA  TABLES  Table E.21: Analysis for Accumulation and Degradation of V F A  MTB > MTB > r e g r c4 2 c l c6 The r e g r e s s i o n e q u a t i o n i s 1 / r r = - 0.648 + 0.0288 Co + 9.02 Predictor Constant Co 1/Co  Coef -0.64769 0.028812 9.0212  s = 0.01726 Analysis  of  Stdev 0.04058 0.001185 0.2051  99.9%  R-sq  1/Co t-ratio -15.96 24.31 43.99  P 0.004 0.002 0.001  R - s q ( a d j ) = 99.8%  Variance  SOURCE Regress ion Error Total  DF 2 2  4  SS 0.75301 0.00060 0.75361  SOURCE Co 1/Co  DF 1 1  SEQ SS 0.17626 0.57675  MS 0.37651 0.00030  F 1263.40  P 0.001  CONTINUE? Obs. 1 2 3 4 5  MTII  Co 4.6 9.9 17.7 28.8 38.1  1/rr .46199 .54407 .38447 .47664 .69589  F i t Stdev.Fit 1.46204 0.01701 0.54690 0.01227 0.37196 0.01155 0.49534 0.00974 0.68683 0.01503  Residual -0.00005 -0.00283 0.01251 -0.01869 0.00906  St.Resid -0.02 -0. .23 0..97 -1. .31 1..07  Appendix E. DATA TABLES  Table E.22: ROW  Cso  1 2 3 4 5  15 20 30 40 50  272  A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n of V F A C12  C13  1 . 335 1 .562 2 .314 2 .650 4 .504  0 . 167 0 .078 0 .094 0 . 097 3 .999  1/Rs  Cso**2  tf 1-tf 2  1/Cos  0. 85616 0. 67385 0. 45045 0. 39170 1. 98020  225 400 900 1600 2500  1 .168 1 .484 2 .220 2 .553 0 .505  0 .0666667 0 .0500000 0 .0333333 0 .0250000 0 .0200000  MTB > 1 >  SUBO n MTB > r e g r c l 2 3 e * NOTE * Cso * NOTE * Cso**2 * NOTE * 1/Cos  ll is is is  cl5 cl7 highly correlated highly correlated highly correlated  with with with  other other other  predictor predictor predictor  The r e g r e s s i o n e q u a t i o n i s C12 = 11.2 - 0.378 Cso + 0.00553 Cso**2 - 82.0  1/Cos  Predictor Constant Cso Cso**2 1/Cos  P 0. 504 0 . 514 0.417 0 . 557  Coef 11.17 -0.3781 0.005526 -82.00  s = 0.3580 Analysis  Stdev 11.32 0.3953 0.004243 98.10  R-sq = 98.0%  t-ratio 0.99 -0.96 1.30 -0.84  variables variables variables  R - s q ( a d j ) = 91.9%  of Variance  SOURCE Regression Error Total  DP 3 1 4  SS 6.1784 0.1282 6.3065  DF 1 1 1 .  SEQ SS 5.7340 0.3549 0.0895  MS 2.0595 0.1282  F 16.07  P 0.181  CONTINUE? SOURCE Cso Cso**2 1/Cos Obs. 1 2 3 4 5  Cso 15.0 20.0 30.0 40.0 50.0  C12 1.335 1.562 2.314 2.650 4.504  F i t Stdev. F i t 1.280 0. 354 1.723 0. 320 2.072 0. 264 2.843 0 .301 4.446 0. 353  Residual 0.055 -0.161 0.242 -0.193 0.058  St.Res i d 1.00 -1.00 1.00 -1.00 • 1.00  Appendix E. DATA TABLES  273  Table E.23: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n of V F A  MTB > MTB > r e g r * NOTE * * NOTE * * NOTE *  cl4 3 e Cso Cso**2 1/Cos  l l cl5 cl7 i s highly correlated i s highly correlated i s highly correlated  with with with  other other other  predictor predictor predictor  variables variables variables  The r e g r e s s i o n e q u a t i o n i s 1/Rs = 14.0 - 0.577 Cso + 0.00748 Cso**2 - 92.4 1/Cos Predictor Constant Cso Cso**2 1/Cos s = 0.2397 Analysis  Stdev 7.578 0.2647 0.002841 65.69  Coef 13.958 -0.5773 0.007480 -92.42  •  R-sq = 96.6%  t-rat io 1.84 -2.18 2.63 -1.41  P 0.317 0.274 0.231 0 . 393  R - s q ( a d j ) = 86.3%  of Variance  SOURCE Regression Error Total  DF 3 1 4  SS 1.61853 0.05747 1.67600  DF 1 1 1  SEQ SS 0.46789 1.03689 0.11375  MS 0.53951 0.05747  F 9.39  P 0.234  CONTINUE? SOURCE Cso Cso**2 1/Cos Obs. 1 2 3 4 5  Cso 15.0 20.0 30.0 40.0 50.0  MTB > MTU  >  1/Rs 0.856 0.674 0.450 0.392 1.980  F i t Stdev.Fit 0.819 0.237 0.782 0.214 0.289 0.177 0.521 0.202 1.942 0.237  Residual 0.037 -0.108 0.162 -0.129 0.039  St.Resid 1.00 -1.00 1.00 -1.00 1.00  Appendix E. DATA  TABLES  274  Table E.24: A n a l y s i s for A c c u m u l a t i o n a n d D e g r a d a t i o n o f V F A  MTB  > regr c l 4 2 e l l c l 5  The r e g r e s s i o n e q u a t i o n i s 1/Rs = 3.3G - 0.213 Cso + 0.00367 Cso**2 Pred i c t o r Constant Cso Cso**2 s  Coef 3.3566 -0.21347 0.003672  = 0.2926  Stdev 0.9884 0.06896 0.001055  R-sq = 89.8%  t - r a t io 3.40 -3.10 3.48  P 0. 077 0.090 0.074  R - s q ( a d j ) = 79.6%  A n a l y s i s of Variance SOURCE Regression Error Total  DF 2 2 4  SS 1.50479 0.17121 1.67600  SOURCE Cso Cso**2  DF 1 1  SEQ SS 0.46789 1.03689  MS 0.75239 0.08561  F 8.79  P 0.102  CONTINUE? Obs. 1 2 3 4 5 MTB >  Cso 15.0 20 30 40 50  1/Rs 0.856 0.674 0.450 0.392 1.980  F i t Stdev.Fit 0.981 0.253 0.556 0.173 0.258 0.214 0.694 0.196 1.864 0.281  Residual -0.125 0.118 0.193 -0.302 0.116  St.Resid -0.8 5 0.50 0.97 -1.39 1.41  Appendix 1  PUBLICATIONS  1990  Yan J.Q., Lioa P.H. & Lo K.V., Anaerobic Digestion of Cheese Whey Using an Upflow Anaerobic Sludge Blanket Reactor 3.Sludge and Substrate Profiles , Biomass (21) 257-271.  1989  Yan J.Q.,Lo K.V.& Pinder K.L., Anaerobic Digestion of Whey in UASB Reactor (Treatment Efficiency), Paper No.89-6570, Winter Meeting of ASAE, New Orleans.  1989  Yan J.Q.,Lioa P.H. & Lo K.V., Methane Production from Cheese Whey, Biomass (17) 185-202 .  1989  Yan J.Q.,Liao P.H. & Lo K.V., Anaerobic Digestion of Cheese Whey Using Up-flow Anaerobic Sludge Blanket reactor (Start-up), Biological  1987  Waste,(21) 289-305.  Yan J.Q., Advances in Nitrification and Denitrification Processes. Environmental  1986  Science and Technology, No.l.(Chinese)  Yan J.Q., Denitrification of Photosensitive Emulphor Wastewater, Environmental  No.4.(Chinese)  Science and Technology,  1986  Zhou T.W. & Yan J.Q., The Bifurcation Behavior of the Steady States of Continuous Stirred Tank reactor. Journal of Engineering Mathematics. Vol.3, No.2. (Chinese)  1985  Yan J.Q. The Studies of Anaerobic Expanded Bed, paper in Guangzhou Institute of Energy Conversion .Chinese Academic of Sciences.  1983  Yan J.Q>. Studies in Solar Energy Storage Using Adsorption and Desorption. Energy Conversion No.l .(Chinese)  1981  Yan J;Q.. Studies in the Pulse reaction Kinetics, Master's thesis, Dalian Institute of Chemical Physics, Chinese Academy of Sciences.  1980  Yan J.Q., Discrimination of The Kinetic Models of Catalytic Pulse Reaction. The Paper presented in the 1st Conference of Catalysis and Kinetics, Chinese Chemical Society, Chengdou. China, July.  1980  Yan J.Q. & Jiang B.N., The Determination of adsorption Parameters under the Pulse reaction Conditions, The paper presented in the 1st Conference of Catalysis and Kinetics, Chinese Chemical Society, Chengdou. China, July .  

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