Optimal Design and Operation of Wastewater Treatment Plants by

Optimal Design and Operation of Wastewater Treatment Plants
by
Prasanta K. Bhunia, Ph.D. and
Michael K. Stenstrom, Ph.D., P.E. 1986

TAB⁲E OF CONTENTS
⁲IST OF FIGURES ⁲IST OF TAB⁲ES ACKNOW⁲EDGMENTS VITA ABSTRACT I. INTRODUCTION II. ⁲ITERATURE REVIEW
A. Primary Clarifier B. Activated Sludge Process C. Secondary Clarifier D. Anaerobic Digestion
D-1 . Propionic and n-butyric acids D-2. Hydrogen Transfer Kinetics D-3 . Inhibition D-4. Process Design and Process Modeling E. Optimization ESimplified Mathematical Models E-2. Advanced Mathematical Model III. MODE⁲ DEVE⁲OPMENT A. Model Inputs B . Primary Clarifier C. Biological Reactor Model C-1 . Nitrification
111

Page
V Vii
viii ix x 1 7 7 10 16 2122 26 29 31 33r4d35 3 7 41' 41 42 48 54

C-2. Oxygen Utilization

57

D. Secondary Clarifier Model

59

E. Anaerobic Digestion

65

E-1 . Mathematical Development

'71

E-2. Carbonate System and pH

79

F. Optimization Description

84

IV. COST EQUATIONS FOR UNIT PROCESSES

94

V. RESU⁲TS AND DISCUSSION

106

A. Simulated Primary Sedimentation Basin Performance

106

B . Simulation of Activated Sludge Process

114

C. Dynamic Characteristics of Anaerobic Digestion

122

D. Optimization

127

VI. SUMMARY AND CONC⁲USIONS

137

A. Conclusions

139

B . Recommendations

REFERENCES

142

APPENDIX A

152

APPENDIX B

157

w

⁲IST OF FIGURES

Page

Fig . 1 .1 Process System Diagram

3

Fig. 3.1 Actual and Reconstructed Biochemical Oxygen Demand

43

Fig . 3.2 Magnitude Spectrum for Biochemical Oxygen Demand

44

Fig . 3 .3 Relationship Between Pollutant Concentrations

45

Fig. 3 .4 Schematic Structured Model

51

Fig. 3 .5 Summary of Mathematical Model and Information Flow

60

Diagram

Fig. 3.6 Flux Curves

,

63

Fig. 3.7 Solids Concentration Profiles

63

Fig. 3 .8 System Information Flow Diagram

66

Fig. 3 .9 Anaerobic Digestion of Organic Wastes (Old Concept)

68

Fig. 3.10 Anaerobic Digestion of Organic Wastes (New Concept)

69

Fig. 3.11 Summary of Mathematical Model and Information Flow

85

Fig. 3 .12 Information Flow Diagram for the ⁲east Cost Design and

89

Operation

Fig. 4.1 Cost Breakdown (Capital fixed operation and maintenance and 104 variable operation)

Fig. 5.1 Relationship Between Efficiency (%) and Settling

Velocity, W , cms/sec

107

Fig. 5.2 Relationship Between Efficiency (%) and Settling

Velocity, U, cms/sec

108

Fig. 5 .3 Relationship Between Removal Efficiency (%) and Depth,

109

cms (V,W : Constant)

Fig. 5.4 Relationship Between Removal Efficiency (%) and Depth,

111

v

cms (V,Q : Constant)

Fig. 5 .5 Relationship Between Effluent Concentration and Depth

112

with Time for Variable Flow Rate and Influent

Concentration

Fig. 5.6 Steajdy State Effluent Soluble Substrate Concentration

118

gm /m

Fig. 5.7 Steady State Mass Concentrations (RXA = 0.15, RH = 0.01,

119

RSD = 0.001, KT = 0.005, fs = 0.5)

Fig. 5.8 Steady State Effluent Ammonia Concentrations for

Variable Solids Retention Time (SRT), Days

120

Fig. 5.9 Steady State Effluent Concentrations (Biodegradable

Solid (BD) and Soluble Substrate (S)) for Variable

123

SRT, Days

Fig. 5.10 Steady State Volatile Solids Destruction, Gas Flow

Rate (QCH 4, QCO 2, and QH2), and

124

Specific Growth Rate of Methanogens for Variable SRT,

Days

Fig. 5.11 Steady State Un-ionized Acids Concentration (Acetic (HA),

Propionic (PA), and N-Butyric Acids Concentration),

and Bi-carbonate Concentration (HCO 3) for Variable

125

SRT, Days

Fig. 5.12 Steady State Gas Production/VSS Destroyed, Total Acids

Concentration, pH, and % CH4 for Variable SRT,

126

Days

Fig. 5.13 Optimal Design and Operating Parameters with Varying

Oxygen Transfer Costs

130

Fig. 5.14 Optimal Design and Operating Parameters with Varying

132

Sludge Disposal Costs

Fig. 5.15 Optimal Design and Operating Parameters with Varying

133

⁲abor Rate

Fig. 5.16 Influence of Oxygen Transfer Costs on Optimal Design and

Operating Parameters for Higher SRT Systems

134

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⁲IST OF TAB⁲ES

Page

Table 2.1 Methanogenic Interspecies H2 Transfer

24

Table 2.2 Role of methanogen on Interspecies H2 Transfer

27

Table 4.1 Cost Estimates for Unit Processes

102

Table 4.2 Designed Parameters and Unit Sizes of Activated Sludge

103

Treatment Plant

Table 5.1 Effluent Suspended Solids Model Parameters

113

Table 5.2 Parameters and Coefficients for Heterotrophic Bacteria

115

Table 5.3 Parameters and Coefficients for Nitrifying Bacteria

116

Table 5 .4 Steady State Results of Activated Sludge Process (CFSTR)

121

Table 5.5 Economic Parameters Used for Optimal Design and Operation 129

Table 5.6 Comparison of Optimization Cases

135

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ACKNOW⁲EDGMENTS I would like to express my gratitude to Professor M .K. Stenstrom for his encouragement, guidance, and friendship during my graduate studies at UC⁲A and also for serving as my graduate advisor and doctoral committee chairman . I also wish to thank the other members of my doctoral committee, Professors R .G. ⁲indberg, R.A. Mah, J.B . Neethling, and W.W-G. Yeh. I would like to thank fellow students and office mates Sami A . Fam, Adam S. Ng, Gail K . Masutani, Hamid Vazirinejad, Hyung J . Hwang, Hoa G. Tran, Kevin M . Reagan, Stephen Song, Seth D . Abramson, Sam Beadles, and ⁲ynne Cardinal for their help in clarifying topics of mutual interest . Thanks are also due to Debby Haines who typed and retyped the seemingly endless draft with patience and care .
viii

VITA

1976 1976-1977 1977-1979 1979-1981
1981-1982 1982-1984
1983 1984-1985 1985-1986

B .E. (Civil Engineering), Calcutta University, India
Simplex Concrete Piles ⁲td ., India M. Tech., Indian Institute of Technology, Kanpur, India Post Graduate Research Engineer, University of California, ⁲os Angeles Teaching Associate Post Graduate Research Engineer, University of California ⁲os Angeles The Degree of Engineer, University of California, ⁲os Angeles Post Doctoral Research Engineer, University of Wisconsin Project Engineer, Applied Modeling Incorporated

PUB⁲ICATIONS AND PRESENTATIONS
E.R. Christensen and P.K. Bhunia, "Modeling Radiotracers in Sediments : Comparison with Observations in ⁲ake Huron and ⁲ake Michigan ." J. of Geophysical Research, AGU (In Press).
E.R. Christensen, P.K. Bhunia and M.H. Hermanson, "Forward and Inverse Problems Regarding the Deposition of Heavy Metals in Aquatic Sediments. Presented in the International Conference on Heavy Metals, Athens, Greece, 1985 .
Bhunia, P. and E .R. Christensen, "Advection-Diffusion Equation for Modeling Radionuclides in Sediments ." Paper presented at the Midwest Water Chemistry Workshop, 1984 .
Stenstrom, M.K., Ng, A.S ., Bhunia, P., and S . Abramson, "Anaerobic Digestion of Municipal Solid Waste ." J. Env. Eng. Div., ASCE, Vol . 106, No . 5, Oct . 1983.
Stenstrom, M.K., Ng, A.S., Bhunia, P., and S . Abramson, "Anaerobic Digestion of Classified Municipal Solid Waste ." Report prepared for the Southern California Edison Company and Cal Recovery Systems, Inc ., UC⁲A-ENG-81-42, Oct . 1981 .

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ABSTRACT OF THE DISSERTATION
Optimal Design and Operation of Wastewater Treatment Plants
by
Prasanta Kumar Bhunia Doctor of Philosophy in Engineering University of California, ⁲os Angeles, 1986
Professor M. K. Stenstrom, Chair
Traditional design procedures for wastewater treatment systems attempt to minimize total capital cost by considering steady state concepts for unit processes and design guidelines . Recent work has minimized capital as well as operation and maintenance costs using a single objective function and steady state models which are flawed because plant inputs vary as much as seven fold during a 24-hour period . Previous work using dynamic models for optimal design does not simultaneously consider both fixed and variable costs in a single objective function .
The objective of this dissertation was to develop a computer-based methodology which considers the dynamic interactions of unit processes and includes capital, operations and maintenance costs in a single objective function . This methodology can aid designers by selecting optimal design and operating parameters for the unit processes in order to produce the minimum, total discounted costs, while satisfying all design and operational constraints .
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The treatment plant model includes primary clarification, aeration, secondary clarification, gravity thickening and anaerobic digestion . The dynamic model of a primary clarifier includes a non-steady state advection-diffusion equation which considers turbulence and deposit resuspension . From this an optimal depth to maximize efficiency was obtained . The activated sludge process model distinguishes between particulate and soluble substrates, and calculates oxygen requirements and sludge production from transient inputs and varying operating strategies . These form the basis of the variable operating costs .
The goal of the anaerobic digestion model was to predict gas flow rates and purities, volatile solids destruction, total and un-ionized volatile acids, and pH, for different solids retention times and organic loading rates . Methane gas production is based upon kinetics and stoichiometry which consider interspecies hydrogen transfer, the decomposition of propionate and butyrate to acetate, and aceticlastic methanogenesis . The revenues from methane production was subtracted from the variable operating costs .
The dynamic models of unit processes were interfaced with an optimization technique to determine optimal, independent design and operating parameters conforming to the EPA effluent quality standards . The models and optimization technique can be used to predict optimal design and operating parameters for future wastewater treatment plants, as well as minimizing the operating costs of existing plants .
It is concluded that the overall lifetime treatment plant cost is minimized if capital, operation, and maintenance costs are considered in a single objective function . It is demonstrated that this procedure produces a lower overall cost than stepwise procedures, which may provide a least-capital cost design, but
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