WATER POLLUTION CONTROL RESEARCH SERIES
A GENERAL/ZED COMPUTER MODEL
FOR STEADY-STATE PERFORMANCE
OF THE ACTIVATED SLUDGE PROCESS
U.S. DEPARTMENT OF THE INTERIOR*FEDERAL WATER POLLUTION CONTROL ADMINISTRATION
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WATER POLLUTION CONTROL ADMINISTRATION
The Water Pollution Control Research Reports describe
the results and progress in the control and abatement
of pollution of our Nation's waters. They provide a
central source of information on the research, develop-
ment, and demonstration activities of the Federal Water
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should be sent to the Planning and Resources Office,
Office of Research and Development, Federal Water
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A GENERALIZED COMPUTER MODEL
FOR
STEADY-STATE PERFORMANCE OF THE ACTIVATED SLUDGE PROCESS
By
Robert Smith
and
Richard G. Eilers
Robert A. Taft Water Research Center
U. S. Department of the Interior
Federal Water Pollution Control Administration
Advanced Waste Treatment Branch, Division of Research
Cincinnati, Ohio
October, 1969
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FWPCA Review Notice
This report has been reviewed by the Federal
Water Pollution Control Administration and
approved for publication. Approval does not
signify that the contents necessarily reflect
the views and policies of the Federal Water
Pollution Control Administration, nor does
mention of trade names or commercial products
constitute endorsement or recommendation for
use .
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TABLE OF CONTENTS
INTRODUCTION
PHENOMENOLOGICAL BASES USED IN MODEL
1. What Mixing Model? 3
2. Time Rate of Synthesis 4
3. Yield Coefficient and Endogenous Respiration 12
4. Fate of Colloidal and Particulate Biodegradable Organics 17
5. Nitrification 21
6. Oxygen Requirements 22
7. Performance of Final Settler 24
8. Effect of Secondary Parameters 27
GRAPHICAL ANALYSIS OF DATA FROM ACTIVATED SLUDGE PROCESS 28
DESCRIPTION OF FILL AND DRAW ACTIVATED SLUDGE PROGRAM 32
DESCRIPTION OF CONTINUOUS STEADY STATE ACTIVATED SLUDGE PROGRAM 33
COMPARISON OF COMPUTED AND MEASURED DATA USING THE CSSAS PROGRAM 39
CONCLUSIONS AND RECOMMENDATIONS 45
DEFINITIONS AND TEXT SYMBOLS 47
BIBLIOGRAPHY 49
APPENDIX I Iteration Techniques Used
APPENDIX II Listing of Programs
APPENDIX III Measurements Used for Validation of Model
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INTRODUCTION
Mathematical models used to represent the activated sludge process
in the past have covered a bewilderingly wide range of forms. The
different forms correspond to differing sets of assumptions concerning
the hydraulic and biological relationships believed to be significant
in the particular biological system under study.
Because of the problems of measurement and the difficulty of
fitting data to complex models, researchers often use simplified
models which either omit or make some plausible assumption concerning
the role of various factors in the process.
In this way a multiplicity of models many of which are basically
different have been proposed and used in correlating measurements
made on the activated sludge process.
The purpose of this report is to examine the whole range of
models which have been used in the past and to investigate by means
of analysis and computation the differences and similarities between
them. Particular attention will be given to graphical or computational
methods which can be used to evaluate the characteristic parameters
of the process from the experimental data.
For this purpose two digital computer programs have been developed.
The first (CSSAS)* is a steady state model of the conventional activated
sludge process which is flexible enough to simulate any of the models
proposed. The second digital program (FADAS)** attempts to simulate
the biological activity in a fill and draw bench experiment in which
activated sludge is mixed with substrate in any proportions.
* Continuous Steady State Activated Sludge
** Fill and Draw Activated Sludge
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The researcher who wishes to select a mathematical model for the
activated sludge process has many choices. An almost unlimited number of
models can be synthesized by making selections from the various ideas pre-
sented in the literature relating to each of the following basic questions,
1. What mixing model best represents the flow regime in the
aerator?
2o What is the form of the equation expressing the time rate of
synthesis of substrate into new cells?
3. What factors control the yield coefficient, the death rate of
cells, the basal metabolism requirements, and the return to
solution of lysed cells? To what extent are non-biodegradable
metabolic end products produced?
4. What is the fate of colloidal and particulate biodegradable
matter in the aerator? How can the accumulation of non-
biodegradable particle in the system be expressed?
5. What factors control the nitrifying bacteria which convert
ammonia to nitrates?
6. How can the oxygen requirements of the system be computed?
7. How can the performance of the final settler be expressed
in terms of the efficiency for removing particulate from
the liquid phase and in terms of the sludge compaction
characteristics?
8. What is the effect of secondary parameters such as water
temperature, dissolved oxygen concentration, pH, toxic
substances, etc.?
The answers to these questions can be determined only by an objective
study of available data. The data in most instances is inadequate to
give satisfactory answers. These questions, however, should be con-
sidered, at least, in developing models for the activated sludge process.
The digital computer programs (CSSAS and FADAS) described in this report
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- 3 -
were designed to investigate the consequence of alternative assumptions
for the above questions and to act as a tool for analysis of measure-
ments made on the activated sludge process. A discussion of each
question listed on the previous page will be given first. Next, avail-
able graphical techniques are discussed. Finally, both programs will
be described fully and computed results together with measurements
from several bench scale and full-sized processes will be presented.
1. WHAT MIXING MODEL BEST REPRESENTS THE FLOW REGIME OF THE AERATOR?
The first place where dissimilarities develop in models for the
activated sludge process is in the hydraulic (mixing) assumptions.
The two limiting conditions for a single tank are completely mixed
(Figure la) and plug flow (Figure lb). The completely mixed assumption
is equivalent to assuming that each element of wastewater which enters
the tank is immediately dispersed uniformly throughout the volume of the
tank. The plug flow condition can be understood by visualizing the tank
as being made up of a number of completely mixed sub-volumes in series
and then allowing the number of sub-volumes to increase without limit.
The mixing regime which fits any particular process can then, hopefully,
be found somewhere between these two limits by assuming that the aerator
behaves like some number of completely mixed tanks in series. It has been
found that ten tanks are almost sufficient to adequately represent the plug
flow condition. The digital computer program (CSSAS) provides for setting
the number of tanks in series to any number between one and ten. Various
other more complicated mixing models including such ideas as "stagnant
zones" or "short-circuiting" have been proposed but other massive uncer-
tainties surrounding the activated sludge process make it very unlikely
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Control Volume "A1
a. Completely Mixed Reactor with Recycle
Control Volume "A1
r
20
|
1
1
1
1
1
L_
, / Vina
V
x^
17
I
15
b. Plug Flow Reactor with Recycle
Figure 1
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- 4 -
that anything more complex than some intermediate point between these
two limiting mixing models will be justified in models for the activated
sludge process. This intermediate point can hopefully be represented by
some number between one and ten of equal volume completely mixed sub-
aerators .
2. WHAT IS THE FORM OF THE RATE EQUATION EXPRESSING THE TIME RATE OF
SYNTHESIS OF BIODEGRADABLE MATTER INTO NEW CELLS?
All mathematical representations for the activated sludge process
are expressed in terms of mass balances with the emphasis on mass balances
around the aerator. For example, using Figure la, representing a single
completely mixed aerator, we can write the following mass balance around
the aerator for active cells.
V •— = Q0(X0 - X. ) + G - D /, x
dt 2V 2 I' e (1)
G = growth of cells in the aerator per unit time, (Ib/day)/8.33
D = death of cells in the aerator per unit time, (lb/day)/8.33
Since X and X are related through the recycle stream (17); the first
term on the right of equation (1) can be rewritten in a more convenient
form. Assuming that no significant amount of biological activity occurs
2
in the settler (shown by Reid ) the following mass balance relationships
can be written.
Xl Ql = Q14X14 + Q15X15 + Q17X17
Also, by assuming that stream (20) contains no significant amount of
active cells the following relationship follows:
X2Q2 = Q17X17
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— 5 —
Subtracting these two equations:
Equation (1) can, therefore, be rewritten as equation (2) below. This is
equivalent to writing the mass balance for active cells around control
volume "A".
= G - °e - (Q14X14 + QI
A similar mass balance can be written about the aerator for substrate
as follows.
dS
• V -G/Y
Y = yield coefficient, Ib cells synthesized/lb
substrate utilized
If we assume the substrate in stream (1) to be dissolved, S can be
^
related to S, in the following way.
Q2S2 = Q20S20 + Q17S1
Q1S1 = S1
therefore,
Q2S1
Again, writing a mass balance about the aerator is equivalent to writing
a mass balance about control volume "A".
An important consequence of this transformation is elimination of
the need for consideration of the recycle stream No. 17. Some authors
3 4
such as Ramanathan and Gaudy and Reynolds and Yang appear to believe
that the volume of the recycle stream is a significant parameter in con-
trolling the operation of the completely mixed activated sludge process.
This point will be reexamined later where it will be shown that Q must
be considered when more than two sub-aerators are used.
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- 6 -
Noting that the sum of Q and Q equals Q and the substrate at
J_ TT -L _5 ^ v_/
stations (I) and (14) has been assumed to be dissolved, equation (3) can
be rewritten as follows.
dS
V — = Q20(S20 - S14> * G/Y
The steady state solutions to equations (2) and (4) are easily obtained
by setting the left-hand term equal to zero. The following expression
for substrate removal in the activated sludge process is obtained from
the steady state solution of equation (4).
S14 = S20 - G/Y/Q20 <5)
This relationship can be used to effectively correlate data if the form
of G is known and the assumption that substrate is wholly dissolved at
station (1) is justified. With some notable exceptions, the growth (G)
and death (D) of microorganisms per unit of time is generally agreed to
be directly proportional to the number of microorganisms present, that is,
to the product of the aerator volume (V) and the concentration (X) of
microorganisms (expressed as dry weight per unit volume)„ Garrett and
Sawyer showed this to be true through experimentation with mixed cultures
and a synthetic dissolved substrate prepared to simulate natural sewage.
It is, therefore, more convenient to discuss the growth of microorganisms
in terms of the growth per pound of microorganisms present expressed as
G* = G/(VX). The units of G* are (lb/day)/lb or days" „ Similarly, it is
reasonable to express the death of microorganism as K = D /VX. Most of
the discussion found in the literature is concerned with finding the form
of the relationship between G* and the concentration of substrate (S) or
other growth limiting nutrient surrounding the bacteria. G* is known to
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_ 7 -
have a value of zero when (S) falls below some limiting value; usually
taken as zero concentration. It is also known that G* has some maximum
asymptotic value which is approached as the concentration of limiting
nutrient becomes very large. Various relationships have been proposed in
the literature to express these ideas quantitatively „
Penfold and Norris were among the first to observe that the doubling
time, T , for bacteria (B0 typhosis) varies inversely with the concen-
tration of limiting nutrient. This can be expressed as follows, k and
k are constants.
£
Td = k^l/S) + k2 (5a)
If we assume the concentration of limiting nutrient (S) to be fixed j the
growth of bacteria can be expressed as follows.
G* = a constant
G = G*(VX) = d(VX)/dt
dX/X = G* • dt
ln(X/X ) = G*«At
The time. At, for the weight of bacteria to double is then given as follows.
Td = ln(2)/G* (6)
Substituting this into equation 5a we obtain the following:
1/G* = k (1/S) + k4 Where kg = ^111(2) and k4 = k2ln(2) (7)
7
Monod found that G* could be related to the concentration of growth limit-
ing nutrient in the following way.
K S
G* =
Taking the inverse of both sides of this equation we obtain the following.
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- 8 -
= iri + ir
r r
Notice the similarity between equations (7) and (9). Relationships
proposed by Penfold and Norris and Monod are essentially the same.
Q
Schulae , working with Eschericia coli in a continuous flow reactor
found that measured values fit the following type of equation. This
g
form had apparently been suggested previously by Teissier .
G* = Kr(l - e"aS) (10)
K = maximum growth rate, day
a = a constant
It will be shown later that this form is almost equivalent to the Monod
relationship.
Garrett and Sawyer and Eckenfelder and McCabe have proposed a
two phase discontinuous relationship between G* and S as follows:
G* = K S for S < S* (11)
G* = Kr0 for S > S* (12)
Garrett and Sawyer noted that the disagreement between measurements and
this discontinuous function was greatest at the point of discontinuity.
Garrett and Sawyer also stated the opinion that this type of function fit
the measurements made by Monod better than the relationship proposed by
Monod (equation 8).
Rao, Gaudy} and Ramanathan investigated the form of the relationship
between G* and substrate concentration (S) using a synthetic substrate
containing a carbon source of 1000 mg/1 of glucose. They found the Monod
relationship allowed a better fit of the data than either the Schulze or
12
the following expression suggested by Moser .
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- 9 -
G* = Kr/(l + KsX S"X) (13)
Rao Gaudy and Ramanathan also found the relationship between G* and S to
depend on the detention time (V/Q). The rate of growth was generally
greater for the short detention time (3 hr.) and least for the longer
13 14
detention times up to 24 hr. Finally, McKinney and Smith , unlike
most other investigators, do not accept the hypothesis that the growth
of microorganisms in the aerator (G, Ib/day) is directly proportional to
the amount of microorganisms present. Indeed, Smith asserts that the
active solids can range from 6-250O mg/1 without affecting the growth rate
G. Since it was found by Frazier that active solids represented about
27% of the mixed liquor suspended solids, this corresponds to a range of
22-9250 mg/1 for mixed liquor suspended solids. McKinney's findings can
be summarized as follows:
G = k S for food/microorganism < 2.1 (14a)
G = k X for food/microorganism > 2.1 (14b)
Food is measured in terms of ultimate oxygen demand (mg/1) and micro-
organisms as dry weight of microorganisms per liter. Clearly, equation
(14a) applies to most practicable wastewater treatment applications.
Typical values for process constants taken from the literature are
given below for domestic sewage and pure substrates at 20 c. Downing
and Wheatland suggested the following values for use with the Monod
relationship for cell growth.
K =4.8 day"
K = 150 mg/1 (5-day BOD)
Y = O.5O Ib volatile suspended solids/lb 5-day BOD
The Monod relationship using these values is shown in
Figure 2.
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Ill
SPECIFIC GROWTH RATE
SUBSTRATE CONCENTRATION
Substrate Concentrationj•8/1
BOD or ammoni* nitrogeo
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- 10 -
Garrett and Sawyer found the break point for the two phase discon-
tinuous relationship (11) and (12) to occur at about 160 mg/1 (5-day
BOD). Garrett and Sawyer also found the maximum value for G* to be
1.92 day"1 at 10°C, 4.8 day"1 at 20°C and 7.2 day"1 at 30°C. Garrett
and Sawyer used a dissolved synthetic sewage. The Garrett and Sawyer
relationship for 2O C is shown in Figure 2.
Q
Schulze , using a pure culture of Escherichia coli, found a maxi-
mum value for G* of 18.2 day" and a value for the constant (a) of
(0.014). An equation of the form suggested by Schulze can be shown to
(Figure 2) fall very close to the Monod relationship if the following
constants are used.
G* = 4.6(1 - e"-°06S) (16)
Some of the best work with pure substrate and mixed cultures has been
reported by Gaudy, Ramanathan, and Rao . They found a range of values
from 9.35 day" to 13.1 day" for K in the Monod relationship. Values
found for K in the Monod relationship ranged from 35-138 mg/1 glucose.
The reactor temperature was 25°C. As mentioned previously, they found
a strong dependence of both K and K on detention time. Much additional
work has been performed using pure cultures and pure substrates but these
experimental values are of little usefulness in estimating the constants
for domestic sewage.
When the flow regime for the aerator is assumed to be plug flow as
shown in Figure Ib the computed aerator performance differs significantly
from the completely mixed case. The most important difference is greatly
increased synthesis for the same detention time using the plug flow aera-
tor. Recycle ratio (Q17/Qpn) also has an effect on performance in the
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plug flow aerator system. Recycle is determined, in part, by the com-
paction ratio (URSS = (X /X )). It should be emphasized that considera-
tion of the plug flow aerator is only of academic interest since most
real aerators more closely approximate one or two completely mixed tanks.
The performance of the plug flow aerator system shown in Figure Ib can be
solved in closed form if we make the following simplifying assumptions.
1. Endogenous respiration rate equals zero
2. Substrate completely dissolved
3. No loss of active cells from the system at
station 14
From assumption (1) above, the following relationship between substrate
and heterotrophs across the aerator can be written.
Xx - X2 = Y(S2 - S1) (17)
By combining (17) with the Monod expression for growth shown in equation
(8) a differential equation is found which when integrated takes the
following form.
(H + 1) loge(X2/X1) - H.loge(S2/S1) = -K^.1 (18)
where
+ YS1)
= V/(Q2Q(1 + p))
P = Q17/Q20
If we take X.. and S., as independent parameters, the following expressions
for p, (X /X ) and (S /Sn) can be computed from the following mass balance
J. ^ £ J-
expressions which relate to Figure Ib.
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- 12 -
1-Y
- URSS -
1 + p (20)
J20-SJX1
P= -
X2 _ p. URSS
+ p
/S1
/
Some sample computations have been made using equations (18), (19), (20),
and (21). The following values were used for the constants.
S2Q = 130 mg/1 5-day BOD
K =4.8 days'1
K =150 mg/1 5- day BOD
s
URSS = 5.0, 3.O, 2.0
Detention time is defined as the volume of the aerator divided by the vol-
ume flow at station (20). The computed detention time (days) for com-
binations of }C and S are shown in Figure 3. A value of (3.0) for URSS
was used in computing the data shown in Figure 3. The effect of different
values for URSS is shown in Figure 4. Changing the value of URSS from
(5.0) to (2.0) increases the required detention time about 20%. This is
not a major effect and since plug flow is not realizable in the real
world, it is probably more correct to say that performance is independent
of recycle than to consider recycle as a primary parameter.
3. WHAT FACTORS CONTROL THE YIELD COEFFICIENT. THE DEATH RATE OF CELLS.
THE BASAL METABOLISM REQUIREMENTS. AND THE RETURN TO SOLUTION OF LYSED
CELLS? TO WHAT EXTENT ARE NDN- BIODEGRADABLE METABOLIC END PRODUCTS
PRODUCED?
The stoichiometric factors to be considered in selecting a model for
the activated sludge process are illustrated in Figure 5. Substrate (5-day
BOD or ammonia nitrogen) is combined with dissolved oxygen to produce new
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GBNRRAL SOLUTION FOR PLUG FLOW AERATOR
Dissolved Substrate
No Endogenous Respiration Loss
No Loss of Cells over Settler Weirs
7 8 9tfo
Utoo
3 4567
fo9,tfoo
Concentration of Heterotrophs at Station No. 1, mg/1
FIGURE 3
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1.0 -^.ll.iilUI
GENERAL SOLUTION FOR PLUG FLOW AERATOR
Dissolved Substrate
No Endogenous Respiration Loss
No Loss of Cells over Settler Weirs
1OO 0.01 200
20*00
Concentration of Heterotrophs at Station No. 1, mg/1
FIGURE 4
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Debris (MLDSS)
Protoplasm
o
Cell Lysis
Metabolic
End Products
New Cells
(MLASS)
Basal Metabolism
STOICHIOMBTRIC PATHWAYS FOR
ACTIVATED SLUDGE
FIGURE 5
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cells, carbon dioxide and water, and non-biodegradable end products.
About % Ib of heterotrophs are produced per Ib of 5-day BOD utilized
while only about 5/10O Ib of Nitrosomonas are produced per Ib of ammonia
nitrogen utilized. The viable cells in the aerator use substrate and
dissolved oxygen for vital cellular activity, respiration, and locomotion.
This is referred to as basal metabolism or endogenous respiration.
Dissolved non-biodegradable end products are difficult to distinguish from
dissolved non-biodegradable organics entering the system in the feed stream.
Jenkins and Garrison estimate the dissolved non-biodegradable organics
in a well operated activated sludge process as 30-40 mg/1 COD. Eckhoff and
18
Jenkins measured the metabolic end products in a bench scale process
using synthetic substrate as 5.56% of the influent COD.
It is generally recognized that a certain portion of the viable
bacteria die and lyse each day and that a portion of the cell protoplasm
returns to solution as substrate while a portion becomes particulate non-
biodegradable material. The substrate requirement for endogenous respira-
tion can be related to the oxygen used over and above oxygen requirements
for synthesis. This is found to be about equal to the substrate released
19
to solution as a result of cell lysis. Bhatla, Stack and Weston in fill
and draw experiments with activated sludge and natural substrates found that
a kind of equilibrium is reached which they attribute to the rate of sub-
strate utilization for synthesis becoming equal to the rate at which new
substrate is supplied by cell lysis.
The quantity of cells produced by synthesis and the quantity lost by
natural death or endogenous respiration has been estimated by many investi-
gators. It is believed that a part of the organic substrate utilized
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- 14 -
reappears in the form of new cells while the remaining part of the sub-
strate utilized is oxidized to supply the energy necessary for synthesis .
This is often expressed as follows:
COD^ . = COD + o
Food Cells
Dividing both sides by COD . gives :
FoOQ
1 = f + f (22)
s e v '
where f is the fraction of the substrate which reappears as viable cells
and f is the fraction of the substrate oxidized.
e
The quantity of substrate utilized has been measured as ODD, 5-day BOD,
or ultimate carbonaceous BOD. Ultimate BOD is believed to be equivalent to
about 90-100% of ODD. The ratio between 5-day BOD and ultimate carbonaceous
BOD varies with the value of the rate constant (k) in the following equation
which represents the dissolved oxygen measured in the BOD test as a function
of time.
y = L(l - e~kt)
The ratio of 5-day BOD to ultimate BOD is about 0.9 for primary effluent
and as low as 0.55 for secondary effluent. Cells produced by synthesis
are about 90% volatile. The COD of cells produced by synthesis has been
measured as 1.42 Ib COD per Ib of volatile solids.
The yield coefficient (Y) expressed as pounds of volatile suspended
solids produced per pound of substrate (COD) utilized can, therefore, be
found as follows :
YCOD = fs<1/:L-42> <23>
The fraction of substrate which reappears as cells has been estimated by
McKinney as 2/3. McCarty has summarized measurements for this fraction
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- 15 -
for various pure substrates and these values range from (0.63) to (O.28).
Thus, McKinney concluded that 0.47 Ib of volatile suspended solids are
produced by utilization of one pound of ultimate BOD. Yield is believed
to be independent of water temperature.
One of the first measurements of sludge production was made by
21
Heukelekian, Orford, and Manganelli . They found the following relation-
ship to express the production of volatile suspended solids in terms of
the 5-day BOD in the feed stream.
Ib VSS/day = 0.5(lb 5-day BOD fed/day) - 0.05S(lb VSS in aerator)
22
McCarty and Brodersen in an analysis of measurements made by others con-
cluded that the yield coefficient in terms of 5-day BOD removed was 0.65
Ib VSS per Ib 5-day BOD utilized. McCarty and Brodersen evaluated the
endogenous respiration constant as (0.18). The endogenous respiration
23
constant (K ) is temperature dependent. McCarty found the following
relationship to hold:
T ?ft
Ke =
McCarty and Brodersen concluded that about 82% of the lysed cell is con-
verted to CO + HO to meet endogenous respiration requirements while 18%
£* £
of the cell is particulate non-biodegradable debris (MLDSS).
24
Sawyer estimated the growth of volatile suspended solids in full-
sized plants as (0.5) Ib of volatile solids per Ib of 5-day BOD removed
from the influent stream. He also concluded that the yield coefficient
. s> -
is independent of water temperature.
25
Hetling, Washington, and Rao performed experiments with pure cultures
and pure synthetic substrates. They found the effective yield coefficient
was not a constant but varied significantly with the substrate, the type of
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- 16 -
organism, and with detention time. They found yield coefficients in
the range of (O.16) to (O.35) in terms of mg of cells per rag of sub-
strate COD. Measured values of K varied from 0.01 to 0.067.
e
Gaudy, Ramanathan, and Rao found that yield coefficients
measured in batch experiments were on the average, 45% smaller than
yield coefficients measured in continuous experiments.
n S"
Postgate and Hunter investigated the amount of substrate
returned to solution as a result of cell lysis and concluded that it
was negligable.
27
Klei has found an interesting effect of increased pressure on
the production of sludge in model activated sludge continuous experiments
without recycle. He found a marked decrease in the amount of waste
sludge formed when the pressure was greater than 60 psi gage.
To summarize, values for the yield coefficient vary over a con-
siderable range depending on the kind of experiment, on the precision
of measurements, and on the method used to evaluate the numerical value.
The yield coefficient cannot be inferred or computed but must be
evaluated from experimental data. The value of the yield coefficient
does not appear to depend on temperature. The temperature dependent
endogenous respiration coefficient is generally small and is sometimes
combined with the growth relationship (G*) to give an effective growth
rate. Substrate contributed by cell lysis is about equal to that required
for endogenous respiration. Activated sludge effluent normally contains
dissolved non-biodegradable GOD equal to about 15% of the influent ODD.
One researcher found the COD of metabolic end products to be equivalent
to about 5% of the influent COD.
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- 17 -
4. WHAT IS THE FATE OF COLLOIDAL AND PARTICULATE BIODEGRADABLE MATTER
IN THE AERATOR? HOW CAN THE ACCUMULATION OF SOLIDS IN THE AERATOR
BE EXPRESSED?
One of the most troublesome and complex problems associated with
selecting a model for the activated sludge process is representing
properly the character of the solids held in the aerator. Since new
cells (MLASS) are continually produced in the aerator; solids must
be removed continuously to hold the aerator solids at a stable value.
The rate of sludge wasting is determined by the rate of substrate
utilization and the yield coefficient. This required wasting rate
then determines the concentration of various classes of solids present
in the aerator. The six classes generally assumed to be present are
listed below:
1. Active heterotrophs, MLASS, mg/1 mass
2. Active nitrifying bacteria, mg/1 mass
3. Organic biodegradable solids, MLBSS, mg/1 mass
4. Organic non-biodegradable solids, MLNBSS, mg/1 mass
5. Organic debris solids, non-biodegradable, MLDSS, mg/1 mass
6. Inorganic solids, MLISS, mg/1 mass
It will be shown later that the inorganic solids in the aerator
(MLISS) are often largely attributable to precipitation of inorganic
salts and not to inorganic particulate entering the process. Since
the nature of this inorganic precipitation is not well known, we have
chosen to omit this phenomenon from the model and to deal only with
organic or volatile suspended solids. The total of all solids in the
aerator considered by the model will, therefore, be called mixed
liquor volatile suspended solids (MLVSS).
The small concentration of nitrifiers which is present when
conditions are correct is also omitted from the computed value for
MLVSS. This error is about 1-2% of the total MLVSS and, if necessary,
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-IS-
the program could be revised to account for this omission. The
yield coefficient for Nitrosomonas is about 0.05 cells/lb N oxidized.
The corresponding coefficient for Nitrobacter is 0.02 Ib cells/N
oxidized. The concentration of Nitrosomonas in the aerator is printed
out and this plus the corresponding concentration of Nitrobacter can
be added to MLVSS by hand if great precision is required. The
difficulty associated with making this computation in the program is
that the calculation assumes that sufficient air is supplied. If
this is not the case, then nitrification cannot occur. In order to
make the computation in the program, the air supplied and the transfer
efficiency would have to be known.
The concentration of active heterotrophs (MLASS) is inferred from
the computational scheme as that concentration which produces the best
agreement between computed and measured values around the process.
MLBSS is the concentration of organic solids in the aerator which are
available for synthesis. To compute MLBSS, it is necessary to make some
assumption about the relative biodegradability of dissolved and
particulate fractions of the influent BOD. The two limiting assumptions
are first, that only dissolved BOD is available for synthesis, and
second, that both dissolved and particulate fractions are equally
available. It will be shown later that the second of these assumptions
allows better agreement between computed and measured values. The
large variability of measured values and other uncertainties make
intermediate assumptions seem impractical.
-------
- 19 -
The particulate BOD over total BOD is called SFBOD in the program.
This can be measured at station 20 and called SFBOD . It is then
necessary to estimate SFBOD at station 1 in order to begin the
computation. SFBOD can be computed from SFBOD using the following
mass balance equations and the assumption that dissolved and particulate
BOD are equally available. Let station 2 be upstream of the aerator
and station 1 be downstream of the aerator.
S20Q20SFB°D20 + Q17S17SFB°D17 = S2 SFB°D2
s1? = SI(I-SFBODI) + s1 SFBODI URSS
S2Q2 = Q20S20 + Q17S17
SFBOD = SFBOD
£ .L
These equations can be combined to give the following relationship
for SFBOD^^ in terms of SFBOD2Q and other variables known or assumed
in the computational scheme.
B = URSS - 1
_
"
B - A + \j (A - B)2 + 4A-B,SFBOD /S
SFBOD = — X^° (25)
If the normal range of values are substituted in this equation it can be
shown that SFBOD is always near in value to SFBOD . The computation,
however, is made in the program. MLBSS is then computed as S(1,1)*SFBOD /O.8,
Using this assumption the contribution of MLBSS to BOD in the effluent
*
stream (14) is always small and the particulate fraction of BOD in the
effluent is almost wholly due to MLASS.
-------
- 20 -
One of the most critical elements of the model is to compute the
concentration of organic non-biodegradable solids in the aerator
(MLNBSS). If both total and dissolved BOD and COD are measured at
station 20 this can be approximated in the following way:
Biodegradable Volatile Suspended Solids
Total Volatile Suspended Solids
(26)
Ultimate Carbonaceous BOD of Particulate
COD of Particulate
To solve this equation for biodegradable volatile suspended solids it
is necessary to infer the ultimate carbonaceous BOD of the particulate
from the measured 5-day BOD of the particulate. This rate constant
has never been precisely determined but some measurements made by T.
Margolies are given in Table I. In analysis of data from the Hyperion
Plant the ratio of 5-day BOD to ultimate carbonaceous BOD was taken
as (0.9). The non-biodegradable volatile suspended solids (VIS20) is
then taken as total volatile suspended solids minus the biodegradable
volatile suspended solids. The accumulation of MLNBSS in the aerator
is then computed as follows:
Q VIS20
MLNBSS = 0?° XRSS + Q,, URSS (2?)
J. 4 JL J
If we assume that 18% of the cells which die remain as non-bio-
degradable debris, the following mass balance can be written around
control volume "A" for MLDSS:
Y(0.18)(S2Q - S^Q^ = (MLDSS + . 18MLASS) (XRSS.Q_14 + URSS.Q^) (28)
This equation can be solved for MLDSS.
-------
TABLE I
STUDY OF 'K' VALUES OF OWL'S HEAD*
INFLUENT AND EFFLUENT
Composite and grab samples taken for analysis - Total and filtrate.
Dilutions incubated at 2O°C for 1,2,3,4, and 5 days for the purpose
of determining reaction rates.
Days Incubated at 2O C
Date
3/16/53
3/23/53
4/6/53
4/21/53
4/13/53
Sample
Influent
Influent
Inf. Grab
9:00 AM
Inf. Grab
10:00 AM
Inf. Grab
1:00 PM
Influent
Effluent
Influent
Same-Dec
added
Decant
Effluent
Thickener
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
- Total
Filtrate
1
43
28
51
3O
45
27
84
47
5O
47
82
41
25
14
56
30
50
27
115
0
22
12
23
12
2
85
41
86
44
81
48
103
67
14O
85
118
54
44
27
76
46
75
37
185
0
39
23
48
25
3
101
47
130
63
109
67
122
85
217
115
147
67
54
37
92
53
97
45
275
70
47
30
55
32
4
122
51
150
71
132
76
138
100
295
134
170
70
59
41
104
55
105
52
350
95
56
34
61
36
_5
136
54
171
75
143
83
149
107
337
141
185
72
62
43
116
59
113
56
425
125
59
36
66
39
'K' Values
0.132
0.302
O.098
O.168
0.114
0.122
O.302
0.2OO
O.1O2
0.132
0.208
0.330
0.208
0.145
0.240
0.302
0.220
0.236
0.168
0.150
0.188
0.140
* Measurements by T. Margolies
-------
_ 21 _
5. WHAT FACTORS CONTROL THE NITRIFYING BACTERIA WHICH CONVERT AMMONIA
TO NITRATES?
Two species of autotrophic bacteria, Nitrosomonas and Nitrobacter
are believed to be responsible for nitrification of ammonia nitrogen in
the aerator. Nitrosomonas converts ammonia nitrogen to nitrite (NO~)
31
and Nitrobacter converts nitrite to nitrate (NO ). Downing, et al.
has shown first, that the growth rate of both species of bacteria can
be represented by the Monod relationship and second, that the growth
rate of Nitrobacter is much greater than the growth rate of Nitrosomonas.
It is generally true that the growth rate of Nitrobacter is sufficiently
greater than the growth rate of Nitrosomonas that only the growth of
Nitrosomonas need be considered in studying the nitrification of ammonia
in the aerator. The following Monod equation constants were measured by
Downing et al. for Nitrosomonas at 2O°C.
K =O.33 day"1
K =1.O mg/1 Nitrosomonas
s
Y = O.O5 Ib Nitrosomonas/lb NH - N
The principal environmental controls on Nitrosomonas are the water
temperature and the specific wasting rate (D ) which must be set to con-
trol the build-up of heterotrophic bacteria in the aerator. Since the
maximum growth rate for Nitrosomonas is less than 10% of the maximum
growth rate for heterotrophs (see Figure 2) the tendency is to waste
nitrifying bacteria at a greater rate than it is possible to replace them
by synthesis of new cells. The behavior of Nitrosomonas in the activated
sludge process can be evaluated if we assume that the same values for XRSS
-------
- 22 -
and URSS apply to both Nitrosomonas and heterotrophs . Then the same
value of (D ) must apply to both classes of bacteria. For lack of some-
thing better, this approach is usually taken in writing a mathematical
model. The details of how this assumption can be used to compute the
extent of nitrification will be given in the discussion of the CSSAS
program which appears later in this report .
6. HOW CAN THE OXYGEN REQUIREMENTS OF THE SYSTEM BE COMPUTED?
Oxygen must be supplied to the aerator for three purposes:
1. Synthesis of new heterotroph cells
2. Endogenous respiration of heterotrophs
3. Synthesis of Nitrosomonas and Nitrobacter
Oxygen used in synthesis of new cells is, theoretically, related to the
value used for the yield coefficient. The yield coefficient for heterotrophs
can be based on utilization of COD, ultimate carbonaceous BOD, or 5-day
BOD. Yield coefficient is defined as follows:
Y = (Ib VSS formed)/lb COD utilized
YBOD = (Ib VSS formed)/lb BOD utilized
[i H
YBOD = (Ib VSS formed)/lb BOD utilized
If the ultimate BOD is estimated as 90% of COD and the ratio of 5-day BOD/
ultimate BOD is taken as (0.9), the two ratios (5-day BOD/COD) and (Y ^
Y ) will have the value of (0.81). It was shown in equation (23) that
'
Y must be equal to (f /I. 42). f can, therefore, be calculated from
COD s s
the 5-day BOD yield coefficient as follows:
fs = YBOD5 (0.8
-------
- 23 -
Using the input yield coefficient for heterotrophs, f (lb 0 /lb COD
synthesized) can then be expressed as follows :
f = 1. - 1.15 CY(1)
Converting to pounds of oxygen per pound of 5-day BOD the following
final relationship is found:
lb 02/lb BOD5 used = 1.235 - 1.42 CY(1) (29)
It has been mentioned previously that the substrate utilized for
endogenous respiration is about equal to 82% of the lysed cells. The mass
of cells which lyse per day can be expressed as (K -MLASS-VAER.8.33). The
oxygen requirement for endogenous respiration of heterotrophs can, there-
fore, be expressed as follows;
lb 0 used/day = (1.42)(.82) K •MLASS-VABR-8.33 (30)
^ 6
28
In the work of Downing et al. the growth of nitrifying bacteria
was expressed as the effective growth so that no measurement was made of
(K ) for nitrifying bacteria. In computing oxygen requirements for nitrify-
ing bacteria Downing et al. gives the following stoichiometric relationship;
2NH* + 40 > 2ND" + 2H 0 + 4H+
4 ^ j &
Four moles of oxygen are, therefore, required to convert one mole of
ammonia nitrogen to nitrate. The yield coefficient for Nitrosomonas is
given as 0.05 lb of cells produced per lb of nitrogen converted. Thus, a
negligible amount (O.8%) of the nitrogen used as food is converted to cell
material. The pounds of oxygen required per pound of nitrogen converted
to nitrate is therefore, 64/14 or 4.57.
-------
- 24 -
7. HOW CAN THE PERFORMANCE OF THE FINAL SETTLER BE EXPRESSED?
The two principal performance parameters associated with the final
settler are XRSS the fraction of mixed liquor suspended solids which
escapes over the final weirs and URSS the compaction ratio. Both of
these parameters are known to depend on the physical characteristics of
the final settler and on the characteristics of the activated sludge-
Characteristics of activated sludge are determined, in part, by the design
and operating decisions adopted for the aerator.
40
Villiers made settling column measurements on sludge from bench scale
batch experiments. This work, which was performed at room temperature,
yielded the following empirical expression for XRSS where (GSS) equals the
settler overflow rate in gpd/sq ft, (MLSS) is the mixed liquor suspended
solids concentration, mg/1, and (TA) is the aerator detention time (V/Q )
£\J
in hours.
, .
\ J *- 1
-l op
(MLSS)1*82(TA)
The range of MLSS used by Villiers was 90O-380O mg/1. This relationship
expresses the fact that XRSS is not a constant but becomes smaller as MLSS
increases. The effect of water temperature is not shown and the expression
tends to predict better performance than is generally realized in full-
sized plants operating with MLSS in the range 300-5OO mg/1.
In a recent study sponsored by Federal Water Pollution Control
Administration (Contract No. 14-12-194) Rex Chainbelt Inc. attempted to
find empirical relationships between key design parameters and the
-------
- 25 -
efficiency (XRSS) and compaction ratio (URSS) for the final settler
in the activated sludge process. The following relationship between
BOD loading and Sludge Volume Index (SVI) was found:
SVI = 56.1 + 113. (lb BOD5/day/lb MLVSS)(1.05)T"2° (32)
where SVI _ Sludge volume Index
BOD = 5-day BOD, mg/1
MLVSS = mixed liquor volatile suspended solids in aerator, mg/1
T = water temperature, degrees Centrigrade
This empirical relationship was based on 41 observations and the
correlation coefficient was 0.78.
If we assume that the sludge concentration in the underflow stream
from the settler is equal to concentration of the sludge in the SVI
graduate cylinder after 30 minutes settling, the following mass balance
relationship first derived by Bloodgood can be written.
Q15 + Q16 _ SVI MLSS !__ (33)
Qi = io6 = URSS
By combining equations (32) and (33) a maximum value for URSS can be found
from the BOD loading on the process. Of course, URSS can be set at any
value below this maximum by increasing the pumping rate above that
required to return the sludge at the maximum concentration.
Rex Chainbelt Inc. also derived the following equation for XRSS:
vocc - 382. (overflow rate, gal./day/sq ft)°'12( BOD Loading)0'27 (34
XKijs - 1 3r -I cto
MLSS (Detention Time)
where EQD Loading . lb s^ay BOD/day/lb MLVSS
Detention Time = Aerator Volume, mg/Aerator effluent flow, mgd
-------
- 26 -
The correlation coefficient for this empirical relationship was only
0.63 indicating a poor correlation.
38
Pflanz of Federal Republic of Germany made measurements on the
efficiency of the settler with aerator suspended solids ranging from
3OOO-10,OOO mg/1. He found that a reasonably good relationship existed
between suspended solids in the effluent and the surface solids loading
rate expressed as kilograms/hr/ sq meter. He also observed a pronounced
effect of water temperature. For example, at a surface solids loading
rate of 2.O the suspended solids in the effluent was 19 mg/1 at 13-15°C
and about 42 mg/1 at a temperature of 2-3 Co
To summarize, no completely satisfactory method of estimating the
efficiency and compaction ratio of the final settler has yet been
presented. For this reason these two parameters were classified as
input to the program.
-------
- 27 -
8. WHAT IS THE EFFECT OF SECONDARY PARAMETERS SUCH AS WATER TEMPERATURES,
DISSOLVED OXYGEN CONCENTRATION, pH, TOXIC SUBSTANCES, ETC?
Synthesis rate constants, CR(I), and endogenous respiration con-
stants, CE(I), have both been shown to be temperature dependent. The
yield coefficient, however, is believed to be independent of temperature.
No temperature corrections are performed in the program. All synthesis
and endogenous respiration constants must be temperature corrected by
hand before being supplied to the program. Generally accepted relation-
ships for temperature corrections are shown below.
CR(1) = CR(1)2Q (1.047)T"2° (for Heterotrophs)
CE(1) = 0.1245 (1.047)T"2° (for Heterotrophs)
CR(2) = 0.33 (1.123)T"2° (for Nitrosomonas)
where CR(1) _ = maximum rate constant for synthesis for heterotrophs,
20 day-1
o
T = water temperature, C
No endogenous respiration constant is needed for Nitrosomonas because
the rate constant for synthesis represents the net growth rate.
Although it has been suggested that the rate of synthesis increases
with the dissolved oxygen concentration this has never been shown con-
clusively and no such relationship is included in the model.
Much work has been done on the effect of toxic substances but this
kind of information has not been incorporated into the model.
One important effect which should be included in the model is the
effect of adsorption in the contact stabilization process. The effect
could be evaluated by using the program if sufficiently complete
measurements were available. The contact tank should be a separate tank
and not the downstream portion of the aerator. This effect will be
evaluated when data becomes available.
-------
- 28 -
GRAPHICAL ANALYSIS OF DATA FROM ACTIVATED SLUDGE PROCESS
To find relationships suitable for describing the efficiency of
the activated sludge process as a whole we can substitute one of the
alternative expressions for G* into equation (5). The most generally
accepted forms of G* are the Monod expression (8) and the two phase
relationship proposed by Garrett and Sawyer (11) and (12). Sub-
stituting equation (11) into equation (5) gives the following three
equivalent forms:
A4 " 1/S20 " (Krl' -"—' (35j
S20 " S14 _ Krl'S14
X'T Y (36)
S20 * + KrlT X/Y *
L = loading, Ib 5-day BOD/day/lb active microorganisms
Q20S20/VX
T = detention time, days, V/Q,
'20
Substituting the Monod relationship (8) into equation (5) yields the
following expression for efficiency of substrate removal:
4 - 1/S20 ' V(Kr+ S14) (38,
Several problems are involved in using these equations to fit data
from full-sized plants treating wastewater containing both particulate
and dissolved biodegradable fractions. For example, the concentration of
active microorganisms in the aerator (X) is difficult to measure. A meas-
ure of MLSS or volatile suspended solids is often substituted for (X). The
implicit assumption is then made that active solids concentration is a fixed
-------
- 29 -
percentage of the total or volatile solids concentration over the range
of operating conditions studied. Second the assumption has been made
that remaining substrate at stations (1) and (14) is totally dissolved.
Actually, MLASS and MLBSS held in the aerator are known to exert a BOD
and some solids are almost always found in stream (14). Mancini and
32
Barnhart attempted to account for this by measuring S as dissolved
BOD only and then adding a term (2, day ) to the righthand side of
equation ( 36) to account for the BOD contributed by the particulate
matter in stream (14). Jenkins and Garrison have also recommended
measurement of dissolved ODD only at station (14) in attempting to
33
describe the efficiency of the activated sludge process. Eckenfelder
has used equation (36 ) successfully to fit data from several full-sized
plants.
Steady state expressions for the quantity of active solids produced
by the process per unit of time can be found by first, setting the left-
hand term of equations (2) and (4) equal to zero and second, solving for
G* in each case as follows:
r^ Q14X14 + Q15X15 + °e
G* - ^T£ + rrrr
(S - S )
2OV 20 14
(40)
The grouping on the right-hand side of equation (40) which is multiplied
by (Y) is known as the specific substrate removal rate (q), Ib substrate
utilized per Ib of active microorganisms present. The first term on the
right-hand side of equation (39) is called the specific waste rate (D ), Ib
of active solids wasted per day per Ib of active solids present in the
-------
- 30 -
system. The second term on the right-hand side of (35^ is the endogenous
respiration coefficient (K ), death rate of active solids, Ib/day per lb
of active solids in the system. Equations (39) and (4O) can be summarized
as follows :
Dc = qY ' Ke (41
When it is possible to measure the concentration of active cells in the
aerator and in streams 14 and 15, equation (41) can be used to evaluate
the yield coefficient (Y) and the endogenous respiration constant K
by plotting DC versus q on a linear scale. The slope then corresponds
to Y and the intercept to Kg. This is generally possible in bench scale
experiments where dissolved substrates are used.
This procedure presents some difficulty, however, when used to
analyze data from a full-sized activated sludge process in which a major
fraction of the solids held in the aerator are inert. It can be reason-
ably assumed that the ratio of (Xj^/X) equals the ratio (VSS /VSS )
and that the ratio (X15/)C) equals the ratio (VSS /VSS ) where VSS
represents the concentration of volatile suspended solids, mg/1. D can
c
therefore be seen to equal the following expression which can be measured.
Q14vss14 * Q15vss15
°c -- V(VSS1) - (42)
Since we cannot measure X., we cannot find a value for q directly. By
using VSS instead of X^ we can measure q* as follows;
, Q20(S20 - S14>
q* = — v(vss1) - <43)
q* = q(VSS1/X1)
Now
if we plot D versus q* the slope will be equal to Y(VSS_/X_ ) and the
intercept will be K
-------
- 31 -
Equation (35) which is a linear relationship between inverse loading
and the performance measure (1/BOD - 1/BOD. ) can be used to roughly
correlate plant data. Data from various plants and bench scale experiments
are shown plotted in this way in Figures 6-29.
As a management surveillance tool the slope of this linear relation-
ship might be plotted as a function of time. Such a plot which is similar
to a quality control chart would have the advantage of showing the overall
performance of the process with respect to time. Increasing values for
the slope indicate superior performance. Charts based on 24-hr composite
measurements for the Hyperion Plant in Los Angeles and the Whittier-Narrows
Plant near Los Angeles are shown in Figures 30 and 31 . A horizontal limit
line might be drawn on these charts such that points falling below the
limit line might signal an upset in the process, in Figure 3O the gradual
upward trend during the summer is probably due to increased sewage
temperature. A correction for temperature should logically be made.
During the winter months at Hyperion significant one month cycles can be
noted. The Whittier-Narrows data shows a great random variation but
some cycling seems to be present. The effluent BOD was total rather than
filtered.
-------
i
1
4-t
ffl;
±i.:t
—' I
i
ffi
±1-!
LI:
5-
-------
5-day BOD Removal Effectiveness
versus
Inverse 5-day BOO Loading
::: Data Reported by Haseltine (35)
slope - (Kr/Y)« 0.0147
std. error slope/slope - 0.0722
Inverse Loading (1.0/lb 5-day BOO per day per Ib MLSS)
-------
Substrate Removal Effectiveness
versus
Inverse Loading
ff composite slope - (K /Y)
r
-0.0236
0.0744
std. error slope/slope
O Pomona Daily Measureaents Based on COD
D Whittier Narrows Monthly Averages Based on 5-day BOD
.0/lb substrate per day per Ib MLVSS)
Inverse Loading
-------
5-day BOD Renewal Effectiveness
versus
Inverse 5-day BOD Loading
slope - 0.0173
std. error slope/slope *>0.127
mum
Hyperion Treatment Plant Monthly Averages
(1.0/lb 5-day BOD per day per Ib MLSS)
-------
5-day BOD Removal Effectiveness
versus
Inverse 5-day BOD Loading
slope - (K /Y
std. error slope/slope « 0.0675
Data Reported by Setter. Carpenter
and Winslow (31)
Inverse Loading (1.0/lb 5-day BOD
-------
^^^^ffl^^^H^^^P^P
EffiW™4:^^
:.. . .11.— u -jiimmTirmmTimTTTTr
;;: : ::::::; ::: :: : ::: ::::::: 5-day BOD RemOVJ
:;: : ._::::: ::: :r : :::.|{:::: VCD
::: : :::::: ::: ± ::::::::::: Inverse 5-day
---:: |n: Washington, D.C. Treatne
i i t i : ------ '- ~ -+5 "- -- j- std. error slope/
- t • - ~ » ; ; \.~.~. .......... : .:::::: ;::: :::: t; i£
: : : h : -H : - ;:;; -I;;:::; ; ;;::;:: ;:;: ;; ; : :
FT • m vx uU-U-J Ml
--• : :"" O: ::::::::::::::::::: I:::::::: ::::::::: :::::^::
- : :: - «-4 ... •£
- -i M •-• — ;:::: t::: ::::: .::::::::::::::::::::::::::;
nrm nTTTli * f ttttttHlttl 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 i 1 1 1
rnrmr TTrrf •" 111 1 1 1 [1 1 1 1 1 [I] [ 1 1 |i||ffel
t - - - -. - - . f _-. L_
: : : | Inverse Loading (1.0/lb Ji-day
^•piitfttfl^^
ll Effectiveness ::+::::::::: t ::: ±::: | gi:
BOD Loading r:::::::::: ::::: ': -t^^ :::
::::::::|:::::::::::::::::::|:::::|::::::: : :::gtt:::: :J
nt Plant Monthly Averages -• - - it^- -(-iff
Blope « 0.0810 ::r -- T-- -:- : " T :l : ::
-- -- - ___ _ _ 1(1 . _ _ . _. _ „ _ I _
-4---- -- _. _ -. _- jl -_ j_-
- - -'<- _ _ _ ^ _ _!T _. t . . _. _ . ._
1?, ____ __ _._
i : : : : : : : ; :± ffi ::
::::••-•"- ... .*.
:::::::::: : : :: : PICSlfeE "ll : : i
: : i » |M E ! E i h":::::::::::::: : : :
BOD per day p«r lb MLSSJ ttttil'litftltll'llllllitttltl
-------
std. error slope/slope « 0.156
Aerator Detention Tine - 1-1/2 hours
Inverse Loading, (1.0/lb 5-day BOD per day per Ib VSS)
5-day BOD Removal Effectiveness
versus
Inverse 5-day BOD Loading
Aerator Detention Time • 3 hours
Loading. (1.0/lb 5-day BOP per day per lb VSS)
FIGUSfe 12
Data froa D.A. Wallace N.S. Thetis (Univ. Iowa)
-------
5-day BOD Removal Effectiveness
versus
Inverse 5-day BOD Loading
slope - 0.0679
std. error alope/alope * 0.110
Aerator Detention Tint
Inverse Loading, (1.0/lb 5-day BOO per day per Ib VSS)
Data fnmD.A. Wallace M.S. Thesis (Univ. leva)
-------
slope » 4.871
_t; std. error slope/slope
Aerator Detention Time » 1-1/2 hours
Inverse Volumetric Loading,
(1.0/lb 5-day BOD per day per 1000 cu ft aerator)
iOD Removal
Effectiveness
Inverse Volumetric Loading
111ii111111111i-i-i-HM ;trrrppi-p
slope » 8.901
std. error slope/slope « 0.115
Aerator Detention Time • 3 hours
day BOO p«r day per 1000 cu ft aerator)
FIGURR 14
Data from D.A. Wallace M.S. Thesis (Onlv.
-------
BCD Removal Effectiveneaa
versus
Inverse Volwaetric Loading
slop* -7.503
•td. error slope Mope . 0.136
lerator Detention Tiae «• 3 noun
Inverse Volumetric Loading, (1.0/lb 5-day BOli
par 1000 e« ft a«x«tor)
Data from D.A. Wallace M.8
-------
COD Renoval Effectiveness
versus
Inverse COD Loading
Data Reported by Reynolds and Yang (4)
slope - (Kr/Y) » 0.1073
std. error slope/slope » 0.0381
iiu'iTHrnmTTminnnfrrnrrmii Mini HURT
Inverse Loading. (1.0/lb COD per
per Ib MLSS)
-------
s
1 • ' ' • ' * L • • ' i ' i ' • J i i i i : i i I i J I I I I, ^ i I I f i i I i I ! I i I i ! L i I M I 1 I 1 L I IT TTTTTTTT
ACTIVATED SLUDGE PLANT PERFORMANCE DATA
WASHINGTON, D. C.
Slope = .0294
Variance of Slope = .44 x 1O
t
APRIL, L967
t DAILY AVERAGES
-H-H-
-i£
en
FIGU1B 17
= Organic Loading, lb. 5-day BOWaay/lb. MLSS
= Influent Stream 5-day Total BOD Concentration, mg/1
a Bffluentstrc&ai 5-** T°tal BOD Concentration, mg/1
- , , ., , , _-.- . , -.. , ^.. -,.8^:,--^.,
-------
ACTIVATED SLUDGE PLANT PERFORMANCE DATA
WASHINGTON, D. C.
Slope = .1098 _3
_•-- Variance _of _ Slope =__•' ~
APRIL. 1967
DAILY AVERAGES
FIGURE 18
ilH^H^Wg
^lirmirrfniTT
S2JV
Organic Loading, Ib. 5-day BOD/day/lb. MLSS
Influent Stream 5-day Total BOD Concentration,
= Effluent Stream 5-day dissolved BOD Concentration, ! mg/j
1/L
-------
::::: | : : ::: |: :: + ::: ACTIVATM) SUJDGB &j
:::: ::: :::::::: :::::: : :: : : : t T::::: WARDS ISLANl
liUI Hi" niiW iTllll^^ SDNTHLY AVRI
:;;: *• o\\ ;; ;;; ; ;; ; ; ; ;; ; = ; PEE ;;f : ;; ; : :E:: :- :- - 3 : :::
:::: .:: c>l :: ::: . :: : : : ± t: :: ±::: ::-: ------ '--- •--- :::: " : : :::
EEiiiEEE ^ | :: ;;: : ;; ; ! iii! ;;; ;E;; |; ;;;;;; EEE: ;;;|;;;; ;;: E IE:
EEp d. I; ill ;: :li II III IE ElEhEIEEEEEEIEIIEEIIIEEIIIiliElf:
g:^3 1 1 EE; ; ;; :; : E; ; ; ; :: E IEJ : ; EEgiEEi i :±:: i EE;; ;:;: IEEE EE E E ;|
HH^ iliii^^
tt: ::: :H *-:! : :: :: f:: : : : :: : : f : :::: :::: :::::: ;::: t:: ::+ :: : : :
-4-- — — -- • • -- •-- • -L - ^ - - - - -^-- ---i — • -- • i — --f- - •
JiiMiiMiiiM
|i»|il|fifflf™
i^iffityifiifflstitjj^
f f j- ] : : :::::::::::::: : ::::::»:::: ::::::: :: : :
::H EE i : : : : : :...... -?___..__._.
p|iiH^P|i^||jp^
miSipifij^5M^^^^
lllllll!™^^
kMHB PERFORMANCB DATA [tl]! Ill |l|||l||||||||||l Illl Illll III II III 1 III l||||l| ||l||l
) 1948-1950 t [[[
3AGBS J £
::::::::::::::::::: :::| :::::::::::::! :::::::::::::::::::::::::::::;,:::::::: |::: :::::::::::::;
L = Organic Loading, Ib. 5-day BOD/day/lb. MLSS -
S— Kf -f 1 Han't- Qf- i*AAn S^f^Aw ROD rV>nr^j>ni'i"A'f"T nn wn/1 -
S = Influent Stream 5-day BOD Concentration, mg/1 !-:
nmnnri " -= = TnnTTirririTrmiTTTniTniirrmirniTT7rTnTirTiiiuii -— ---•
:::::: :::: ::• Slope = .O059 5 \- :;SE|:±|| :::|
jl II 1 11 II 1 Variance of Slope - .09 x 10 i[|| \\\ \\ \\\\ |!||||||
. _ . .- — --._ ~ -. — i — -1- --f - — — T -f--- -- T 3--- — - — — L i i- -Mi i-i-^- ---•
- - - -- J — - -- -J — I- 1--] — _- . — 1_ _L- .- 4-1- — 1- -t-J — 1- i 1 i . __ .
:fi- :: :::: :::: : :: :::± :::: ::: j :::: :±: :::: :: : :±: J+::::: :q:: EE: :::| :::: ::::
::: ;:|:|]] : 1:1 :H§ EWESE!:! E|:|:EE: 1 | ||E EE ||i
— --}- j-T-- --T — t- -T4- - - -+- - 4-(- - ~ Tf -«— T-T- — - - - t\T\ • -f- ^ ~r * - - f • ^- -
EEE EEI :EEE E EE EE EEEE EEEE EE E J |: :E:I IE : E: : : | : E:EEEEEEEl|E | :;;
|E::EEE EE; :EEE :EE:EEEEE:|E: E;:; E;;E;EEEE EEEE IE EEEE ; 1 E ; :EEE;;;:::::E:; E| E;;E
it I lit i 1 1 1 1 1 jJlJjriTnltiT'fl N m
: : : : : : : : E|:::|::: |: :|: ::E| ::E| ::::::: FIOJ8B 19^ | :
>-- _ - - + - - - - jX-t- .j...it----t----+j------- j- ---
-------
ACTIVATBD SLUDGE PLAMT PERFORMANCE DATA
HUNTS POINT 1952-1957
iniiLi iu-U-1-Lumimimiii-ii
Organic Loading, Ib.. 5-day BOD/day Ib. MLSS
Effluent Stream 5-day BOD. Concentration, rag/1
Influent Stream 5-day BOD Concentration, mg/1
Slope = .0421
Variance of Slo
MONTHLY AVERAGES
-------
ACTIVATED SUJBGB-FfcSNT PERFORMANCE DATA
BOWERY 1952-1954, 19'58
MONTHLY AVERAGES
FIGURE 21 *
iti^^itiitif r-n-4—»-I-
Slope = .0335
Variance of Slope = .45 x 10
i I hi I n-mtn \ 11 m H-
L = Organic Loading, Ib. 5-day BOD/day Ib. MLSS
S = Effluent Stream 5-day BOD Concentration, mg/1
S ~ = Influent Stream 5-day BOD Concentration, mg/1
-------
Pj::
ACTIVATED SLUDGE *>LANT PBRFORMANCE DATA
^ALLMANS .ISLAND .1952-1959
MONTHLY AVERAGES Ji!|
E
fl-
tnt
FIGURE
Slope = . O382
-
L =
S =
-; Variance of Slope = .16 x 10"
±ttLl 1 J_l-LlJ_LJa 1 I l l l * ; i i i : i ! i i i ii
Organic Loading, Ib. 5-day BOD/day/lb. MLSS
Effluent Stream 5-day BOD Concentration, mg/1
Influent Stream 5-day ,BOD Concentration, mg/1
2
-------
ACTIVATED SLUDGE PLANT PERFORMANCE DATA
^DWL'S HEAD 1952-1959
MONTHLY AVERAGES!
±H
1/L
Slope = .04O3
Variance of Slope = .23 x 10
-5 5^
H-H-t i i 1.1 II I i 1 i-H-H-H-r-j-1-H—r -
Organic Loading, Ib. 5-day BOD/day/lb. M^S
Effluent Stream 5-day BOD Concentration, mg/1
Influent Stream 5-day BOD Concentration, ag/1
-M-.-4- 4
rFtttt
FIGURE 23:
-------
fltf-
ACTIVATED SLUDGE. PEaNT PERFORMANCE DATA
JAMAICA 3,952-1959
3 MONTHLY AVERAGES U'4"
'ffflMtiiffflftffitfBi
: u+
±t.
L = Organic Loading, Ib. 5-day BOD/day Ib". MLSS
= Effluent Stream 5-day BOD Concentration, mg/1
= Influent .Stream 5-day BOD Concentration, mg/1
Slope = .O347
Variance of Slope = .21 x 10
-------
ACTIVATED SLUDGE PLANT PERFORMANCE DATA
ROCKAWAY 1953-1959
MONTHLY AVERAGES
L = Organic Loading, Ib. 5-day BOD/day/lb. MLSS
S = Effluent Stream 5-day BOD Concentration, rog/1
= Influent Stream 5-day BOD Concentration, mg/1
20
-*4-W-44-~l »4.;4-4(4 i-, »U4-;4-( I I :;n ! 14 Hi 14-U-.-I I I 1 I i i 1 l-i-li-l J 1 1 ,11
Slope = .0448
Variance of Slope = .42 x 10~
H-t+i-t-t •(-'-- -4 H-I-M ttl ! 1 i i I' i I I I I i ! i I1±:
FIGURE- 25
ttftl
-------
ffiffl
fell
ACTIVATED SLUDSB PLANT PERFORMANCE DATA
OAKWOOD. 1957-1959
tmit.LUttmitltiftIiU1itlU±l! U 1 1 ! 11 M
-
! f I i I !
L = Organic Loading, Ib. 5-day BOD/day/lb. MLSS
S = Effluent Stream 5-day BOD Concentration, mg/1
S Q = Influent Stream 5-day BOD Concentration, mg/1
Slope = .O225
Variance of Slope = .23 x
mti i! 1
MONTHLY AVERAGES
FIOJRB 26
it-
-------
ACTIVATED SLUDGE 0LAHT PERFORMANCE DATA
26TH WARP 1952^1959
MDNTHLY AVERAGES
L =
Organic Loading, Ib, 5-day BOD/day/lb. MLSS
Effluent Stream 5-day BOD Concentration, mg/1
Influent Stream 5-day BOD Ctoncentration, mg/1
LnEinrninig
LjuiuiTttmttrrttif
Slope = .0361
Variance of Slope = .22 x 1O
-------
ACTIVATED SLUDGE PLANT PERFORMANCE DATA
WHTTTIER NARROWS MARCH 1964-APRIL 1965
.. T-]-|-T.T i • -v-ft ^'iTrniiiiniiiiiiiJiini i~n IT
MONTHLY AVERAGES
^rFIGURE 28
Slope = .0333
p Variance of Slope = .147 x 10
L = Organic Loading, Ib. 5-day BOD/day/lb. MLSS
= Effluent Stream 5-day BOD Concentration, mg/1
^
S2O = Influent Stream 5-day BOD Concentration, mg/1
-------
ACTIVATED SEUDGB PLANT PERFORMANCE DATA
HYPERION y JUNB 1967-MAY 1968
MDNTHLY AVERAGES
Slope = .0215
Variance of Slope = .60 x 10~
Organic Loading, Ib. 5-day BOD/day.Ib. MLSS
Effluent Stream 5-day BOD Concentration, mg/1
Influent Stream 5-day BOD Concentration, mg/1
-------
STATISTICAL QUALITY CONTROL CHART
BASED ON OVERALL RATE CONSTANT
HYPERION PLANT
DAILY AVERAGES
FTGURB 30
3 JUNE 196'
JULY 1967
SEPT 1967
NOV 1967
MAR 1968
-------
STATISTICAL QUALITY CONTROL CHART
BASED ON OVERALL RATE CONSTANT
WHITTIER-NARROWS PLANT
DAILY AVERAGES H
FIGURE 31
linn ,n
APR 1964
JUNE 1964
JULY 1964 :
SEPT 1964
: AUG 1964 ^
OCT 1964
FEE 1965
MAR 1965 APR 1965
-------
- 32 -
DESCRIPTION OF FILL AND DRAW ACTIVATED SLUDGE PROGRAM (FADAS)
The FADAS program uses the Runge-Kutta method of numerical integration
to compute the biological activity as a function of time in a batch
activated sludge experiment. Initial concentrations of substrate and
heterotrophic bacteria are supplied as input. The program then
computes the concentration of substrate and heterotrophs at any number
of time points separated by a specified time interval. The Monod
expression for synthesis is used in the program. It is assumed that
a fixed fraction (K ) of the bacteria are destroyed each day. The
rate of growth can then be expressed as follows;
K S X
19
Some investigators, for example, Bhatla, Stack and Weston believe
that a portion of the lysed cells return to solution to be reused as
22
substrate. Others, such as McCarty believe that only a non-biodegradable
fraction is returned to solution as a result of natural destruction of
cells. The rate of change of substrate with time is expressed in the
program as follows :
,_ R K X K S X
dS e r
dt ~ Y Y(Ks + S)
R is the coefficient which converts the lysed cell mass to substrate
returned to solution. If we assume that all of the cell protoplasm is
returned to solution, the value for I? should be about (0.84). If we
assume that the cell protoplasm is used for endogenous respiration, £
would have a value of zero. The form of the growth relationship can
be easily changed in the program. Typical computed results are shown
in Figures 32 and 33.
-------
COMPUTED RESULTS
FROM
FILL AND DRAW ACTIVATED SLUDGE
DIGITAL PROGRAM
Initial Active Cell Concentration = 2OO mg/1
Initial 5-day BOD Concentration = 5O mg/1
tf m i
FIGURE 32
Time, days
Detention
-------
COMPUTED RESULTS
FROM
FILL AND DRAW ACTIVATED SLUDGE
DIGITAL PROGRAM
Initial Active Cell Concentration = 4OO mg/1
Initial 5-day BOD Concentration = 1OO mg/1
-t fHft+i-H
tFIGURE 33
Detention Time, days
-------
- 33 -
DESCRIPTION OF CONTINUOUS STEADY STATE ACTIVATED SLUDGE PROGRAM (CSSAS)
The CSSAS program is a computational scheme programmed for the
digital computer which simultaneously solves all of the mass balance
and rate equations which describe the activated sludge process. The
computation is strictly for steady state conditions and the program is
arranged to simulate most, if not all, of the modifications of the acti-
vated sludge process. For example, conventional, high rate, extended
aeration, step aeration, and contact stabilization modifications can be
simulated with the program. The hydraulic flow diagram for the program
is shown in Figure 34. in addition to the modifications mentioned above,
the return sludge stream can be divided among the sub-aerators as shown
in the diagram.
The system shown in Figure 34 is solved first for heterotrophic
bacteria, then for nitrifying bacteria, and finally air requirements
for all sub-aerators are computed. A computational flow diagram for
the program is shown in Figure 35. The program provides for dividing
the total aerator volume (VABR) into any number of equal volume sub-
aerators between one and ten. This provision is for simulating the
mixing model for long slender aerators or for investigating the
performance of segmented aerators.
The Monod form of the growth equation is used for both heterotrophs
and Nitrosomonas. K , K , K and Y for both classes of bacteria must
™"^•* i S 6
be supplied as input to the program. Total aerator volume (VAER), the
number of equal volume sub-aerators (NTKS), and the compaction ratio
(URSS) for the final settler are also supplied as input. Characteristics
listed below of the influent stream (2O) are read into the program.
Q(20), S(l,20), S(2,20), SBOD(2O), VIS20
-------
CONTROL VOLUME "A"
2O 1
1
i:
i
n*J
1
1
1 i
r
i
( 20n
f
\
k
1 17n
1
1
+ 1 i 20n - 20d (
Y *
1 '
r 1 1
n _J_ J
1 1
1 1
V4
1
la
^ A
+ 1 4 17n 4 17d (
1 1
I 1
i
1 1
I 20c (
' 1
4
V.
3a
k >
|17c i
i 20b (
r i
3
V2
2a
^ ^
»17b ,
20a
t
2
S
V, 1 / FIN
\ SETT
^s^
i
>17a
^ 17
16
STARILTZATTOM ^
TANK
(
14
FIGURE 34
-------
FLOW DIAGRAM FOR CSSAS ACTIVATED SLUDGE PROGRAM
(A
it
u
Read Aerator Consts., SSOUT, URSS,
VAER, S(l,20), S(2,20), SFBOD,
AEFF, NTKS, VIS2O, X(l,l),
SBOD(20)
in
8
• H
(l,l) = .5»*S(i,20)
Q(17) = .5*3(20)
Solve for S
1»1
and X errors
Compute
MLVSS
XRSS =
SSOUT
MLVSS
Solve for S
2,1
and X . errors
4 j J.
Calculate Air
Requirements
Print Output
Readjust
Q17*S1,1
Readjust
X2,l & S2,l
FIGURE 35
-------
- 34 -
A value for efficiency of the aeration equipment (AEFF) is read into
the program. Since the performance of the final settler cannot be
expressed with any reliability in terms of the design parameters such
as overflow rate, detention time, or weir loading the computational
scheme is constrained to hold a set value (SSOUT) for volatile suspended
solids in stream No. 14
The volume of the stabilization tank (V.,_) is supplied as input.
If a value of zero is supplied the stream vector for station 17 is set
equal to the stream vector at station 16. The fractions (between 0
and 1.) of influent flow (PCTFL(I)) are supplied as input as well as
the fractions of return flow (PCTRN(I)). The integer (I) refers to
the station number just downstream of the entry point; thus PCTFL(l)
and PCTRN(l) are both always equal to zero.
The following mass balance relationships are used to compute
concentrations of 5-day BOD and mass of heterotrophs at stations (1)
through (NTKS + 1). (n) is the station number downstream of each sub-
aerator.
K S^ X DT
- S + r " "
~ n Y(Ks + SR) (46)
K S X DT
= Xn + Ke Xn OT ' K I s" <47>
s n
DT = V/(Q2() +Q1?) (48)
All iterations use the Bolzano or "halfing" technique. As shown
in the flow diagram (Figure 34) the first iteration solves the system
for heterotrophs. The concentration of heterotrophs (NLASS, or X, )
J- >1
is supplied as input. The independent variables for this two
-------
- 35 -
dimensional iteration are Q,7j the return sludge volume, and S ,
-L / J. j J.
the 5-day BOD of substrate at the effluent end of the sub-aerator
just upstream of the final settler. Beginning at station No. 1
the concentrations of heterotrophs and substrate are computed in a
direction opposite to the direction of flow across all sub-aerators
and back through the stabilization tank. The computed value for
MLASS must equal the input value within the set tolerance and the
value of S must equal the beginning value. The values for S
J., -L i, J.
and Q _ are readjusted in a systematic way until the tolerances are
satisfied.
After the iteration for heterotrophs has been completed, the
concentration of total volatile suspended solids at station No. 1 is
computed. XRSS is then recomputed as SSOUT/MLVSS and the iteration
for heterotrophs is recomputed two more times. It has been found
that this is usually sufficient to make XRSS equal to the ratio of
input value for SSOUT over the computed MLVSS.
The values for all stream volumes is now fixed and the next
iteration is designed to compute the concentration of ammonia and
Nitrosomonas at all stations. The independent variables for this
iteration,which is also of the Bolzano type, are the concentrations
of ammonia nitrogen at station No. 1 (S ) and the concentration of
2,1
Nitrosomonas at station No. 1 (X ,). The object of the iteration
2,1
is to find values for ammonia nitrogen and Nitrosomonas at station
No. 1 which will satisfy the system equations with all of the values
for flow fixed. The computational scheme used for heterotrophs is
used for Nitrosomonas except that the biological constants are
changed. The errors are taken as the difference between guess and
-------
- 36 -
computed values for ammonia nitrogen at station No. 1 and the
difference between the previously computed TEMPI and a new variable,
X2, computed after each iteration. The reasoning behind this
scheme can be seen by considering control volume "A" in Figure 34.
The net growth of heterotrophs within the control volume must equal
the net wasting rate from the control volume since it is assumed
that none enter at station No. 20. The mass of heterotrophs wasted
from the control volume can be expressed as 8.33*X(1,1)*(XRSS Q +
URSS Q,-) or 8.33*X(1,1)*TEMP1. The net growth within the control
volume can be equated to the wasting rate as follows:
i = n
Q17X17 ' Q16X16 + / QX - QiXi = X! TEMP1 (49)
i = 1
where: X = concentration of heterotrophs, mg/1
Q = volume flow, mgd
n = number of sub-volumes
Exactly the same reasoning can be applied to the growth of Nitrosomonas
within the control volume. We then have the following identity:
i = n
Q17Z17 - Q16Z16
i = 1
where: Z = concentration of Nitrosomonas, mg/1
The expression on the left of equation (50) is computed after each
iteration and if the answer does not agree with TEMPI within some
acceptable tolerance, the trial concentration of Nitrosomonas at
station No. 1 is readjusted by the Bolzano scheme and the system is
solved again. When both the computed concentration of ammonia at
station No. 1 and the computed value for X2 fall within the specified
-------
- 37 -
tolerances, the iteration is terminated. A detailed description of
the iterative scheme is given in Appendix I.
The initial guess for ammonia nitrogen is one half of the influent
value. The initial guess for Nitrosomonas is found by assuming that
half of the ammonia is converted to the oxidized form. The following
equation applies;
Q(20)*S(2,20)*Y(2) = X(2,1)*(Q(14)*XRSS + Q(15)*URSS)
Solving for Nitrosomonas concentration:
X(2,l) = Q(20)*S(1,20)*Y(2)/(Q(14)*XRSS + Q(15)*URSS) (51)
After this iteration has been completed the air requirement for each
subaerator is computed and these are summed to give the total air
requirement. Air requirements are expressed first as standard cubic
feet of air per gallon of water (AIRPG(I)) and as standard cubic feet per
minute (BSIZE).
In the extended aeration modification of the activated sludge
process there is no sludge wasting from the underflow of the final
settler; in other words the volume of stream No. 15 is zero. Since
sludge must be wasted to satisfy the mass balance equations, the
wasting must occur over the final settler weirs in stream No. 14.
The program can be readily adapted to simulate extended aeration by
setting IEA = 1 which automatically makes the following changes within
the program:
1. Q(15) = 0.0
2. XRSS = 1. - Q(17)*(URSS - l.)/Q(20)
-------
- 38 -
Any value for SSOUT can be used as input because the program
will never make use of the input value. The tolerance used in
the main iteration is normally set at 0.1 mg/1 BOD. For extended
aeration this should be reduced to 0.01 mg/1.
Some computed results using the CSSAS program are shown in Figures 36 and
37 and for one, two, and three sub-aerators. The performance curve for
plug flow was computed from the closed form equations 2O and 21.
-------
-r T- ~' ' I |- - ~
imtititl
4+£
-0.
-fit
rift
tnrt
ACTIVATED SLUDGE PERFORMANCE
WITH
PLUG FLOW AERATOR
AND
1, 2, AND 3 TANKS IN SERIES
tff
Jttr
m?
if
ittt
Dissolved Substrate
No Endogenous Respiration Loss
No Loss of Cells over Settler Weirs
Til T!t'":rT-1+r"^1'^^t"T'~T-n-r'-rtrttTi iTitrf
"t
URSS = 5, Total Detention Time = 4 hours
;.;;' Inverse Loading (1.0/lb 5-day BOD per day per lb MLASS)
r---r I T^— 1 "T^T: ; i • • 'i— I , I i , , , I , — I I , I , I • • • '•'••. ' • | i , , , , , ,
-------
ACTIVATED SLUDGE PERFORMANCE
WITH
PLUG FLOW AERATOR
AND
1, 2, AND 3 TANKS IN SERIES
rmft^lMmfmffiffitfitl
Dissolved Substrate
No Endogenous Respiration Loss
No Loss, of Cells over Settler Weirs
URSS = 2, Total Detention Time = 4 hours
(1,0/lb 5-day BOD per day per Ib MLASS
Inverse Loading
-------
- 39 -
COMPARISON OF COMPUTED AND MEASURED DATA USING THE CSSAS DIGITAL PROGRAM
Validation of the process model by comparing computed versus measured
values is an essential part of all modeling work. In this way the
strengths and weaknesses of the model are discovered and functional
relationships between model parameters necessary to make the computed
results approximate the measurements are found.
The CSSAS model was validated primarily with data gathered at the
Hyperion Plant in Los Angeles where the conventional activated sludge
process is used. Data gathered at the Washington, D.C. Blue Plains
Plant, which uses the high rate or modified modification of the activated
sludge process, was also used to validate the model. Extended aeration
data gathered at various Ohio plants by the University of Cincinnati
was also used. (See Appendix III)
Measurements used to validate the CSSAS model are shown in Table II
and III together with the corresponding variables computed with the
model. Table II shows computed variables assuming that both dissolved
and particulate fractions of 5-day BOD are equally available in the
process. Table III shows computed variables assuming that only the
dissolved 5-day BOD is available for synthesis. In Table IV other
measured and computed data are shown using the assumption that dissolved
and particulate BOD are equally available.
When the model was first written, it was believed that the inorganic
or non-volatile fraction of the mixed liquor suspended solids was due to
inorganic particulate entering the process at station No. 20 and
accumulating in the aerator. The Hyperion data, however, showed con-
clusively that this assumption was not consistent with observation and
it was concluded that inorganic precipitates formed in the process were
-------
SIMULATION OF ACTIVATED SLUDGE MEASUREMENTS USING
CSSAS DIGITAL PROGRAM
DISSOLVED AND PARTICULATE BOD AVAILABLE FOR SYNTHESIS
c
O CO
•H CO
* '&
d • £
K- M
o O zr H
2: < «!
c
•t-> • i -H rH
fl S S £ \
O O -H O W
H Z H 26
HYPERION DATA
1 6 2000
2 6 3000
3 5 3500
4 4 3000
5 4 1800
6 4 1600
7 4 10OO
8 6 1OOO
9 6 600
10 6 600
11 6 700
12 6 1500
O
O
•\
0>
M
3
f->
rf
M
M 0
CTj
•o
1
m
c
rH M
«J
•u Q
H OQ
140.=
155. £
163.3
164.3
157.7
158.4
163. C
130. C
153. £
136. €
151.1
170.1
>x
H S
O H
in
in O
•H Q
Q 55
34.6
38.7
28.6
47.3
49.6
51.4
41.9
35.8
58.8
58.2
49.8
58.7
Q) ..
rH
ft
ri
•0 rH
«J \
JH Ol
• c* E
-
4->
•O 3
iH
3 0
CO U)
• 4.4
5.5
12.6
11.6
22.8
12.2
16.3
12.8
17.3
22.4
17.1
12.6
CO
C CO
O £i
•H 3
T->
0 -
(0 O
CX-rl
e *->
SCO
a
2.86
2.46
2.24
2.54
3.20
3.39
3.59
3.55
4.55
5.36
4.73
3.35
in
X
-.?•-.
it) nJ
r^ TJ
!fi «
•M 4->
in C
0) rt
x: +j
•4-> in
C C
>>,Q
co O
4.8
4.0
3.3
4.8
5.6
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TABLE II
-------
SIMULATION OF ACTIVATED SLUDGE MEASUREMENTS USING
CSSAS DIGITAL PROGRAM
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EXTENDED AERATION DATA
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TABLE III
-------
COMPUTED AND MEASURED RESULTS USING HYPERION DATA
DISSOLVED AND PARTICULATE BOD EQUALLY AVAILABLE FOR SYNTHESIS
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1.68
1.66
0.84
0.74
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0.59
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2.73
2.13
2.27
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0.98
0.81
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2.19
1.29
1.30
1.36
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1.40
1.33
1.40
1.42
1.4O
1.40
1.4O
1.4O
873.
1245.
1074.
1460.
1150.
715.
474.
398.
290.
251.
312.
715.
0.96
0.87
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1.53
2.66
4.45
3.28
4.O4
6.07
6.24
3.65
2.33
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557.
157.
452.
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379.
198.
173.
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418.
110.
244.
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11.9
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18.8
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TABLE IV
-------
- 40 -
largely responsible for the non-volatile fraction of mixed liquor suspended
solids. Mass balances for non-volatile suspended solids for the first
four tests performed at the Hyperion Plant are shown in Table V. From
Table V it can be seen that the non-volatile suspended solids leaving
the process is two or three times that entering the process.
Since modeling of salt precipitation within the activated sludge
process is known to be far more complex than available simple theory
would suggest, it was decided to base the model on the behavior of
organic or volatile materials and to exclude consideration of inorganic
materials.
The model as it now stands is relatively flexible in that it can
be arranged to compute performance under various sets of assumptions.
For example, the availability of dissolved and particulate fractions
of substrate for heterotrophs can be arranged in two ways. First, it
can be assumed that only dissolved substrate is available for synthesis
and second, that both dissolved and particulate fractions are equally
available. When the first assumption is used, the particulate BOD
observed in stream 20 accumulates within the process and appears again
in the effluent stream as part of the inputed SSOUT. Under the second
assumption the particulate BOD not synthesized in the aerator also
exerts a BOD in the effluent stream; Under both assumptions, however,
the active solids which escape over the final weirs contribute to the
BOD of the effluent stream.
The model can be arranged to simulate conventional, modified,
extended aeration, or contact stabilization. In addition, the influent
stream can be split and distributed to the various sub-aerators and the
-------
TABLE V
MASS BALANCES FOR NON-VOLATILE SUSPENDED SOLIDS
Sta. 20
Sta. 14
Sta. 15
HYPERION PLANT - Test No. 1
Volume Flow, mgd
Suspended Solids, mg/1
Fraction Volatile
Non-Volatile Mass Flow, Ib/day
Percent Error in Mass Balance
HYPERION PLANT - Test No. 2
Volume Flow, mgd
Suspended Solids, mg/1
Fraction Volatile
Non-Volatile Mass Flow, Ib/day
Percent Error in Mass Balance
HYPERION PLANT - Test No. 3
Volume Flow, mgd
Suspended Solids, mg/1
Fraction Volatile
Non-Volatile Mass Flow, Ib/day
Percent Error in Mass Balance
HYPERION PLANT - Test No. 4
Volume Flow, mgd
Suspended Solids, mg/1
Fraction Volatile
Non-Volatile Mass Flow, Ib/day
Percent Error in Mass Balance
49.51
74.46
.832
619.33
191%
49.6
67.8
.843
527.97
193%
49.8
99.8
.868
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74%
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696.28
160%
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7408. 7.09
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1470.12 74.99
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7867. 14.
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1073.57 68.25
.88 49.14
7340. 15.2
• 747 . 764
1634.18 176.28
-------
- 41 -
concentrated sludge from the final settler underflow can be distributee
to the individual sub-aerators.
COD or TOC could be used as substrate for heterotrophs by changing
the Monod relationship constants. This, however, has not been attempted.
It should be pointed out that the model has not been adequately
tested on the contact stabilization process and, therefore, the adsorption
process which is believed to be important has not been evaluated.
In the first attempt to make the CSSAS program simulate measurements
the Hyperion conventional activated sludge data was used. Since no
tracer studies were available, it was assumed that the aerator could be
simulated best by two equal volume completely mixed tanks in series.
The input was prepared as described on page 20. The CSSAS program was
then used to compute all process variables using various values for
MLASS as input. MLASS was adjusted by trial and error until the computed
MLVSS at the aerator exit (Station No. 1) equalled the measured value
within some reasonable tolerance. To test the simulation, computed
values for effluent dissolved BOD, effluent total BOD, and volume of
waste activated sludge stream were compared to the measured values. If
the comparison between computed and measured variables was not adequate,
the maximum rate constant for synthesis, (K ) and the yield coefficient
(Y) were adjusted by trial and error until the best agreement between
all computed and measured variables was achieved. The saturation
constant (K ) was found to have little independent effect at the low
substrate concentrations characteristics of municipal sewerage. The
value used for Kg was 150 mg/1 5-day BOD on all computations.
-------
- 42 -
The final comparison between computed and measured variables using
the assumption that dissolved and particulate 5-day BOD are equally
available is shown in Table II. Similar comparisons for the modified
activated sludge data from the Washington, D.C. plant and the extended
aeration plant with no deliberate sludge wasting are also shown in
Table II. It can be seen that the agreement between computed and
measured variables is quite acceptable provided the proper values for
K and Y are used. The yield coefficient required to make the com-
puted results agree with measured results varied between 0.4O and
0.75 with no apparent relationship to process design and operating
parameters. For example, the yield coefficient for heterotrophs is
shown plotted versus inverse loading in Figure 38. NO relationship
is evident. The maximum rate constant for synthesis (K ), on the
other hand, varied as a fairly definite exponential function of
inverse loading as shown in Figure 39.
As shown in Table IV, the computed and measured volumes of the
return stream agree well. The measured value for URSS was supplied
as input to the program because no reliable relationship between URSS
and process design parameters is known. The amount of waste activated
sludge, however, was accurately predicted by the program. The com-
puted air usage rate is in agreement with the measured values provided
nitrification does not occur as in Test Nos. 5-11. The program
predicted nitrification in Test Nos 1-4 and 12. The measurements
showed, however, that no nitrification occurred in all twelve tests.
This discrepancy is probably due to the lack of available air as shown
by the computed requirements which are always greater than the amount
supplied.
-------
- 43 -
A similar analysis was made based on the assumption that only
dissolved BOD is available for synthesis. The results of this study
is shown in Table III and Figure 40- Again, no definite relationship
was observed for yield coefficient but a reasonable relationship was
found for all points except the extended aeration point. For extended
aeration the data were simply not compatible with the assumption that
only dissolved BOD is used for synthesis. The rate constants found
by trial and error are also significantly higher than those found under
the first assumption.
Probably neither assumption is strictly correct but it appears
from this work that the first assumption is closer to the truth. If
the rate constant for synthesis is read from Figure 39 corresponding
to the input value for MLASS, there is every reason to expect that
the program will yield performance estimates which are nearly correct
for domestic sewage. Estimating the performance of the final settler
in terms of the physical characteristics of the settler and the
character of the influent activated sludge remains the most signifi-
cant unsolved problem in the process design technology for the
activated sludge process.
Finally, the CSSAS program was used to compute performance charts
based on the assumption that both dissolved and particulate fractions
are available and the empirical relationship between rate constant and
inverse loading. This computer data using average Hyperion influent
data are shown in Figures 41 - 43. The lines shown in Figure 41 are
straight for most of the useful range but do not intersect the origin.
This tends to, justify further the use of this kind of plot for inter-
pretation of data provided the line is not constrained to pass through
the origin and provided the effluent is either filtered or contains a
-------
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-—f ^-Hnttijhii
O> VJ QO (O O
TT T
TT T
it* ' t 1 1
It t "
i i i H i i i
m i it u uJEiJ1^
i j l! i ' [|
:ion
ington, D.C. |
ided Aeration
! | 1 H i J |i i, H i Jli
i ' 1 1 ' ' • 1 " H W
1 i i h l| ii!
T M : ; • Ijl l MJ W i
40*ALOG(1./L) :
L.. .... .. iU [ . 1. .. |
• '1 ii i
t _TT 1 f M J I L
r i w\ [1 J]] FJi j
i j n | ij i]! iii
t IF ' r i
.... --- - - f} ' 4 '
r 1 1 i n i
r r n l
i '
I Tl ' 1
T i {j
}-- -4 - -
i,( .... • • + • • •
ii .
j-flf -j ! it .0
-tirf" J ['•
IGURB 39'
llllllnJllliliillllIlllllMjIIIHI
-------
_ u ^
— . ____-- -J-r- f ; | Ulllli
- K-- H — r "yTTT T ' _^ J IN
" ~ 1; ; , i , r "f f
T 2 L = Wa^
T ft
i 11
± r it
_ n
. CR_ = 5.89O - 5.<
1
Ii ' iil1 ii ' '' I i i i ' ' li!;l'l i I I '
'i \\ i I t M ! |!| '!!;,: ! i ••
ill Kill ill I it K\.. . I.-lLl- -H.il Li T
: |1 0 , T: I ; L 44 .- 4 , r
i • ! I • IT! ll ! ' 1 ^ M 1 | I t
j II iiii ' ii.i j' 111 I'l I i 1
n,j . iii b 1 1 .i 1 TI L
n J i C 1 J 4- -; ' " ' " L "
B ffi J — L "I V" ""
: ;" M 'n f ^ " T
• ' i 1 ' 1 !! IP L , I
['l , "! i ,1 ]|)j Lil| 1 1 4-4---
j t 'i 1 I I i Ii lli T
.i..4:'Ji2 !* LUi it __i:: ::::::!: ~~
1 U T 1 1 T t ; M r 4 ^ [ I H
1 , . j _. _... . J .__4-
!
t- f 1-t- - -f- 4- +
i i • i '4
f-itnt t
T r
t"~ " T
1 — u-- • j-- •-•
~T~ I ' " "" t
.
. | i -H -t - - •+- -- - _-.-..
-4 *. - - -• . t • ^* -t-4--4-+-i~ " .:i.:i- ift 4
r T I s ^* T4 T^ ri T
' j i " 11 1 ss _~ "::v:::it_ -;— - -- :"|::: rj^LL !
i ' • ! ' ^"^ ' L
" | "t 1 ' ;ii | i fi r ss~* - t -t |- - T^-
i .! "*•» ' _U t- ^ 4-
, I I II **
t ' ] %, T ... • .... . .. I
i M *V
! 1 V
i 1 L % 4-.
....... Ill rft1 - >s .-I-..I i
TTT - r "! i i ;
- • L " t r i ~ ~ \ I' '• .cr : i
1 1 -L
jrse Loading, 1.0/(lb. BOD/day/lb. VLASi
;\ .
*/
![|
II
1
|
TTMII.. I EniilEI [ I I
LO- Ji* -li-.l- ;i*^alJi oi: illi
} . , A • t" +£ rjT' 2
: ! . ! r j | i ' ;i!!
1 1 i< r ES
I .. ^ .. n pE
I.lLE IE. .. ||
i.nini .luifi .11
Q 710 n •
hinciton. D.C. JH
)! n iiinnnifiFii u 3
19
: ir'JEm'm a J
liU llillLlilu M 1 M J
>96*ALOG(1./L) i|
i 11 ill]
1 It i D It fl
II i H i 3
4-4- H I! ii I
III H K D
it 1 H Hi
i j i n|
1 U tt
" ' I i ! it
^" ILL
t ; t ! O
4- IK
t tHlttl
t i ti t it| j
] ; I ll 1
i • ] [Hi 1
i ii lI'lEilH
T t 1 jftj
i [iiii I
f 1 tJ tul
' IE 1
1 1 it i
i 1 11
. i Hit HiHI
|l i
In nnj
i ' III II
ft fllll
i- mi
t K 1 11
f t it] i
i j BIB
lit IS 4 I
j|] r| |
1 n] 1 1 .
i K] I!- u
' i 1 If 11
1 III, l.liil
; I IjMiUil n
j I 1 |||PUfj)|«O
i 1 ' 1' rilfil
i [ill { !| J[|
L 'ill ill Illlllillil
)jj Jill lj'f-lulvir 'Hi ID)
. . -F1UU^([j™||||
III IllilllllllllillJI 1 ll llNllnlJIB
-------
COMPUTED RESULTS FOR ACTIVATED SLUDGE
USING AVERAGE HYPERION INFLUENT STREAM
VAER = 11.7
l./L, Inverse Loading, Ib BOD fed/day/lb MLVSS
-------
COMPUTED RESULTS FOR ACTIVATED SLUDGE
USING AVERAGE HYPERION INFLUENT STREAM
VAER = 11.7
i SSOUT = 5.0
SSOUT = 10.0
SSOUT = 14.0 (average)}
SSOUT = 20.0
-------
1444 U444141 t-t-IU
COMPUTED SLUDGE PRODUCTION USING AVERAGED
INPUT DATA FROM 12 HYPERION DATA
MLASS varies 400-2400 mg/llrl
SSOUT = 5
removed/day/lbjMLVSS in aerator
QQ. Substrate Removal Rate, Ib BOD
FIGURE 43 !
-------
- 44 -
fixed concentration of organic suspended solids. The importance of
SSOUT can be seen clearly in Figure 41. Figure 42 is a similar plot
except that inverse loading is based on active solids rather than
total volatile suspended solids. The lines in this diagram are
clearly less linear.
Finally, Figure 43 shows computed results where net growth rate
is plotted as a function of substrate removal rate and SSOUT. Notice,
first, that SSOUT has a minimal effect on the plot. Using the
simplified theory described on pages 28 - 31, this plot is predicted
to be linear as shown by equation (41). According to the simple
theory, the slope of the line should equal the yield coefficient, and
the intercept should equal the negative of the endogenous respiration
constant (K )= Using the computer program, the slope of the lines are
0.50 for the SSOUT = 5. line and 0.57 for the SSOUT = 30. line. The
yield coefficient used in the program was the average for the Hyperion
data which had a value of 0.517. The extrapolated intercept of the
two lines have values of O.07 and O.085. The actual value used for
the endogenous respiration constant (K ) was 0.18. This shows the
limitations inherent in over simplified representations of the process
and helps to explain the range of values reported in the literature
for process biokinetic constants.
-------
- 45 -
CONCLUSIONS AND RECOMMENDATIONS
A computing tool (CSSAS program) has been developed to aid in
understanding the relationships which govern the quasi-steady-state
performance of the activated sludge process. A start has been made
towards fitting the model to measurements made on full-sized plants.
The FADAS program which has not been validated will be useful in
interpretation of bench scale fill-and-draw experiments.
The observed variation of the maximum rate constant for synthesis
(K ) with inverse loading is important for quasi-steady-state process
design and will also be useful for time-dependent models of the
process. The assumption that both dissolved and particulate 5-day
BOD are equally available for synthesis appears to be more consistent
with observation than the assumption that only dissolved 5-day BOD is
available. Some sort of intermediate assumption would probably improve
the correspondence between measured and computed results. The lack
of a relationship between the yield coefficient and some process
design parameters was disappointing and further study is needed to
resolve this question. Precision of measurement might be a
significant factor.
Additional work is needed to better understand the effect of mixing
in the aerator. Measurements are needed on aerators deliberately
divided into completely mixed sub-aerators.
The adsorption mechanism believed to be important in the contact
stabilization process should be investigated. A separate sludge
stabilization tank will be necessary if meaningful data are to be obtained.
That is, using the downstream portion of the aerator as the stabilization
zone yields confusing data because of the backmixing.
-------
- 46 -
The model has not been properly tested for nitrification because
an adequate supply of air was not available at the Hyperion Plant.
Additional measurements are needed to validate the model for the
computation of nitrification performance.
No adequate relationship between the efficiency (XRSS) and sludge
compaction (URSS) in the final settler and process design parameters
is known. The fraction of volatile solids which escape over the
final settler weirs is an important factor in effective design and
operation of the process. The compacting characteristics, on the
other hand, is less important.
To summarize, the CSSAS program represents the most complete
state-of-the-art computational procedure for quasi-steady-state
performance of the activated sludge process but some important
questions relating to design and operation of the process remain
unresolved. The program, however, will serve as a focal point for
any new information developed through experimentation and should
ultimately represent a thoroughly reliable design tool.
-------
- 47 -
DEFINITIONS OF TEXT SYMBOLS
Text
Symbols
NTKS
V
VAER
Q
X or X. T
Nominal
Value Definitions and Comments
Number of equal volume sub-aerators
Volume of each sub-aerator, mg
Total volume of all sub-aerators, V-NTKS,
mg
Volume flow, mgd
Concentration of heterotrophs , mg/1 at
S or S (see footnote)
i, J
K or CR(I) (see footnote)
K or CS(I)
S* 160 mg/1
URSS
MLASS
COD
food
cells
COD
O
L
K or CE(I)
e
station J
Concentration of substrate, 5-day BOD,
mg/1
Yield coefficient, Ib cells synthesized
per Ib of substrate utilized
Maximum rate constant for synthesis,
day-1
Saturation constant, mg/1 of substrate
Point on substrate scale where
discontinuity falls (5-day BOD)
Final settler compaction ratio
Concentration of heterotrophs, mg/1
Chemical oxygen demand of substrate
used, mg/1
Chemical oxygen demand of cells formed,
mg/1
Oxygen used in synthesis, mg/1
Total carbonaceous BOD, mg/1
Endogenous respiration constant, fraction
of viable cells which lyse per day, Ib
cells/day
-------
- 48 -
DEFINITIONS OF TEXT SYMBOLS
Text
Symbols
Nominal
Value
Definitions and Comments
VIS20
XRSS
SBOD(20)
SSOUT
Concentration of non-biodegradable
volatile suspended solids at station
20, mg/1
Final settler efficiency, volatile
suspended solids at station 14/volatile
suspended solids at station 1
Specific wasting rate, Ib MLASS wasted
per day/lb MLASS in aerator
Specific substrate removal rate, Ib
substrate removed per day/lb active
solids in aerator
Concentration of particulate 5-day
BOD at station 20, mg/1
Concentration of volatile suspended
solids at station 14, mg/1 (input to
program)
NOTE:
1=1 for heterotrophs or 5-day BOD
1=2 for nitrosomonas or ammonia nitrogen
J = station number
-------
- 49 -
BIBLIOGRAPHY
1. Grieves, R0 B., Milbury, W. F., and Pipes, w. O., Jr. "A Mixing
Model for Activated Sludge," .Journal Water Pollution Control
Federation, Vol. 36, 1964, pp7 619-635.
2. Reid, Raymond. "Studies of Reaction Time and Rate at Constant
Loading in a Completely Mixed Activated Sludge System," Unpublished
M.S. Thesis, University of Iowa, Iowa City, Iowa (1965).
3. Ramanathan, M. and Gaudy, A. F., Jr. "Effect of High Substrate
Concentration and Cell Feedback on Kinetic Behavior of Heterogeneous
Populations in Completely Mixed Systems," WP-OO325 Progress Report
FWPCA-USDI, "Kinetics and Mechanism in Activated Sludge Processes,"
May, 1968.
4. Reynolds, T. D. and Yang, J = T. "Model of the Completely-Mixed
Activated Sludge Process," Proc. 21st Industrial Waste Conf.
Purdue University (1966), pp. 696-713.
5. Garrett, M. T., Jr. and Sawyer, C. N. "Kinetics of Removal of
Soluble BOD by Activated Sludge," Proc. 7th Industrial Waste
Conf. Purdue University ( ), pp. 51-77.
6. Penfold, W. J. and Morris, D. "The Relation of Concentration of
Food Supply to the Generation Time of Bacteria," Jour. Hyg^,
Vol. 12 (1912), p. 527.
7. Monod, J. "Recherches Sur La Croissance Des Cultures Bacteriennes,"
Paris: Hermann and Cie, 1942.
8. Schulze, K. L. "A Mathematical Model of the Activated Sludge
Process," Developments in Industrial Microbiology, Soc. Ind.
Microbiology (1964), pp. 258-266.
9. Teissier, G. "Les Lois Quantitatives da la Croissance," Anna.
Physiol. Physicochim. Biol., Vol. 12 (1936), pp. 527-586.
10. Eckenfelder, W. W. and McCabe, J. "Process Design of Biological
Oxidation Systems for Industrial Waste Treatment," Proc. 2nd
Symposium on Treatment of Waste Waters, Pergamon Press, New York
(I960), pp. 156-187.
11. Gaudy, A. F., Jr., Ramanathan, M., and Rao, B. S. "Kinetic
Behavior of Heterogeneous Populations in Completely Mixed Reactors,"
Biotechnology and Bioengineering, Vol. IX (1967), pp. 387-411.
12. Moser, H. "The Dynamics of Bacterial Populations Maintained in
the Chemostat," Carnegie Inst. Wash. Publ. No. 614 (1958).
13. McKinney, R. E. "Mathematics of Complete Mixing Activated Sludge,"
Jour. Sanitary Engineering Div. A.S.C.E.. Vol. 88, No. SA3, May
1962, pp. 87-113.
14. Smith, H. S. "Homogeneous Activated Sludge/1," Water and Wastes
Engineering, Vol. 4, July 1967, pp. 46-5O. '
-------
- 50 -
15. Frazier, G.J. "A Study of Active Mass in a Homogeneous Activated Sludge
System" Unpublished M.S. Thesis, University of Iowa, Iowa City, Iowa (1966)
16. Downing, A.L. and Wheatland, A.B. "Fundamental Considerations in
Biological Treatment of Effluents" Trans. Institution of Chemical
Engineers Vol. 4O, No. 2 (1962) pp 91-103."
17. Jenkins, D. and Garrison, W. E. "Control of Activated Sludge by Mean
Cell Residence Time" Unpublished Paper 35 pages
18. Eckhoff, D.W. and Jenkins, D. "Activated Sludge Systems-Kinetics of the
Steady and Transient States" Sanitary Engineering Research Laboratory,
College of Engineering and School of Public Health, University of
California, Berkeley SERL Report No. 67-12.
19. Bhatla, M. N. Stack, V.T., Jr. and Weston, R. F. "Design of Wastewater
Treatment Plants from Laboratory Data" Journal Water Pollution Control
Federation, Vol. 38, No. 4 (1966) pp 6O1-613.
20. McCarty, P. L. "Thermodynamics of Biological Synthesis and Growth" Pro-
ceedings of Second International Water Pollution Research Conference
Tokyo, 1964 Pergamon Press, New York (1965).
21. Heukelekian, H., Orford, H.E. and Manganelli, R., "Factors Affecting
the Quantity of Sludge Production in the Activated Sludge Process,"
Sewage and Industrial Wastes Vol. 23, 1951, pp 945-957.
22. McCarty, P.L. and Brodersen, C.F. "Theory of Extended Aeration Activated
Sludge" Journal Water Pollution Control Federation, Vol. 34, 1962,
pp 1095-1103.
23. McCarty, P.L. "Review of Mathematical Model Devised by R. Smith,"
Nov. 15, 1966.
24. Sawyer, C.N. "Bacterial Nutrition and Synthesis" Biological Treatment
of Sewage and Industrial Wastes, Vol. I, pp 3-17, Reinhold Publishing
Corp. New York (1956)
25. Hetling, L. J., Washington, D.R. and Rao, S.S. "Kinetics of the Steady-
State Bacterial Culture - II Variation in the Rate of Synthesis" Division
of Environmental Engineering, Rensselaer Polytechnic Institute, Troy,
New York.
26. Postgate, T.R. and Hunter, T.R. "The Survival of Stored Bacteria"
J. Gen. Microbiol. Vol 29 (1962) pp 233-263.
27. Klei, H.E. "Progress Report to FWPCA under Demo. Grant No. WPD-175-Q1-67
School of Engineering, University of Connecticut, Storrs, Connecticut.
28. Smallwood, C., Jr. "Adsorption and Assimilation in Activated Sludge"
Journal of the Sanitary Engineering Division A.S.C.E.. SA4, August, 1957
pp. 1334-1 1334-12. '
-------
- 51 -
29. Maier, Wo J. "Model Study of Colloid Removal" Journal Water Pollution
Control Federation, Vol. 40, No. 3, Part 1 (1968) pp 478-491.
30. Voshel, D. and Sak, J. G. "Effect of Primary Effluent Suspended Solids
and BOD on Activated Sludge Production" Journal Water Pollution Control
Federation, Vol. 4O, Part 2, No. 5 pp R203-R212 (1968).
31. Downing, A.L., Painter, H.A. and Knowles, 3.A. "Nitrification in the
Activated Sludge Process" Journal Institute of Sewage Purification,
Part 2, 1964, pp. 130-157.
32. Mancini, J.L. and Barnhart, E.L. "Design of Aerated Systems for Indus-
trial Waste Treatment" Journal Water Pollution Control Federation, Vol. 39
No. 6, (1967) pp 978-986.
33. Eckenfelder, W.Wo "Comparative Biological Waste Treatment Design" Journal
of the Sanitary Engineering Division, A0S.C.E0 SA6, Dec.1967, pp 157-170.
34. Von Der Emde, W., "Aspects of the High Rate Activated Sludge Process,"
Proceedings of the 3rd Conference on Biological Waste Treatment, 1960,
pp. 299-317.
35. Haseltine, T.R. "A Rational Approach to the Design of Activated Sludge
Plants" Biological Treatment of Sewage and Industrial Wastes, Vol. I,
Reinhold Publ. Corp., New York 1956.
36. Setter, L.R., Carpenter, W. T. and Winslow, G.C. "Practical Applications
of Principles of Modified Sewage Aeration" Sewage Works Journal, Vol. 17
No. 4 (1945) pp 669-691.
37. Wallace, D.A. "The Effect of Mixed Liquor Suspended Solids Concentrations
on the Performance of a Completely Mixed Activated Sludge System with
Variable Reaction Times" Unpublished M.S. Thesis, University of Iowa,
Iowa City, Iowa (1968).
38. Pflanz, P. "The Sedimentation of Activated Sludge in Final Settling
Tanks" Jour. International Association of Water Pollution Research,
Vol. 2, No. 1 Jan. 1968 pp 80-86.
39. Symons, J. M. "Uses of Pure Oxygen and High Dissolved Oxygen Concentra-
tions in the Activated Sludge Process - A Literature Review" Internal
FWPCA Report, August, 1967.
40. Villiers, R. V. "Removal of Organic Carbon from Domestic Wastewater,"
M.S. Thesis, University of Cincinnati, June 1967.
41. Bloodgood, D. E. "Application of Sludge Index Test to Plant Operation"
Water and Sewage Works, Vol. 91, No. 6, p. 222, (June, 1944).
-------
APPENDIX I
DETAILS OF ITERATION SCHEMES USED IN CSSAS PROGRAM
-------
1-1
ITERATION FOR HETEROTROPH5, X(l,l)
A double "halfing" iteration is performed on contours of 5(1,1)
(concentration of BOD at station 1, mg/1) and Q(17) (return flow, mgd)
to find the values for S(l,l) and Q(17) that satisfy the governing
mass balance within a tolerance of .01 mg/1 and rate equations for
the system. SI and XI must agree with S(l,l) and X(l,l) within a
tolerance of 0.01 mg/1;
S(l,l) = SI = S(1,16)/(SFBOD*(URSS-1.)+l.)
X(l,l) = XI = X(1,16)/URSS
where X(l,l) is the concentration of active solids at station 1.
The program computes initial estimates for the iteration of
S(l,l) = .5*5(1,20) and Q(17) = .5*Q(2O), since it is known that
0. < S(l,l) < S(l,20) and O. < Q(17) < Q(2O). A value SI is computed
based on the initial estimates of S(l,l) and Q(17). If the absolute
value of (S(1,1)-SI) does not satisfy the tolerance and S(l,l) > SI,
then a larger value of 5(1,1) is needed to satisfy the system, i.e.
.5*5(1,20) < 5(1,1) < S(l,20), so the next estimate for 5(1,1) is \
of this remaining interval. If 5(1,1) < 51, then a smaller value of
5(1,1) is needed, i.e. O. < 5(1,1) < .5*5(1,20), so the next estimate
for 5(1,1) would be % of this remaining interval. This type of
iteration, taking ^ of the remaining valid interval for each successive
estimate, is performed on 5(1,1) until the tolerance is satified or
until 20 passes are completed. Once a satisfactory 5(1,1) has been
found for the initial Q(17) estimate, the absolute value of (X(1,1)-X1)
is tested against the tolerance. If the tolerance is not satisfied,
and X(l,l) > XI, then a smaller value of Q(17) is needed to satisfy
the system, i.e. 0.
-------
1-2
is ^ of this remaining interval. If X(l,l) < XI, then a larger value
of Q(17) is needed, i.e. .5*Q(20) < Q(17) < Q(20), so the next
estimate of Q(17) is ^ of this remaining interval. After the new
estimate of Q(17) is calculated for the system, the program re-
iterates on S(l,l) in the same manner as previously described. This
process continues until both tolerances are satisfied, or until Q(17)
has been iterated on 20 times. When both tolerances are satisfied,
the value of S(l,l) which satisfies the system has been found. If the
iteration has not converged after 20 passes on Q(17), an error comment
is printed, and the program proceeds to execute the next case.
-------
1-3
ITERATION FOR NITROSOMONAS, X(2,l)
A double "halfing" iteration is performed on contours of S(2,l)
(concentration of ammonia at station 1, mg/1) and X(2,l) (concentration
of nitrosomonas at station 1, mg/1) to find the values of S(2,l) and
X(2,l) that satisfy the governing mass balance and rate equations of
the system for nitrosomonas. S2 and X2 must agree with S(2,l) and
TEMPI within a tolerance of O.01.
S(2,l) = S2 = S(2,16)
TEMPI = X2 = (refer to page 36 )
where TEMPI = Q( 14)*XRSS-K3(15)*URSS.
The program computes initial estimates for the iteration of
S(2,l) = .5*5(2,20) and X(2,l) = XE = CT(2)*Q(2O)*S(2,20)/(DC*VAER),
since it is known that 0. < S(2,l) < S(2,2O) and O < X(2,l) < 2*XE.
A value S2 is computed based on the initial estimates of S(2,l) and
X(2,l). If the absolute value of (S(2,1)-S2) does not satisfy the
tolerance and S(2,l) > S2, then a larger value of S(2,l) is needed to
satisfy the system, i.e. .5*5(2,20) X2, then a smaller value of X(2,l) is
-------
1-4
needed to satisfy the system, i.e. 0. < X(2,l) < XE, so the next
estimate for X(2,l) is % of this remaining interval. If X(2,l) < X2,
then a larger value of X(2,l) is needed, i.e. XE < X(2,l) 2*XE, so
the next estimate of X(2,l) is \ of this remaining interval. After
the new estimate of X(2,l) is calculated for the system, the program
re-iterates on S(2,l) in the same manner as previously described.
This process continues until both tolerances are satisfied, or until
X(2,l) has been iterated on 2O times. When both tolerances are
satisfied, the values of S(2,l) and X(2,l) which satisfy the system
have been found. If the iteration has not converged after 20 passes
on X(2,l), an error comment is printed, and the program proceeds to
execute the next case.
-------
APPENDIX. II
LISTING AND OPERATING INSTRUCTION FOR
CSSAS AND FADAS DIGITAL COMPUTER PROGRAMS
-------
II-l
Input Data for the CSSAS Program
Input Card 1: FORMAT (4110)
NCASE, MULT, IEA, IDIS
Input Card 2: FORMAT (5F8.3,F8.4,4F8.3)
CR(1), CS(1), CE(1), CY(1), URSS, XRSS, SBOD(20),
VIS20, DNBC, Q(20)
Input Card 3: FORMAT (10F8.3)
CR(2), CS(2), CE(2), CY(2), VAER, V17, S(l,20),
S(2,20), AEFF, SSOUT
Input Card 4: FORMAT (11F5.3,23X,12)
(PCTFL(I),I= 1,11), NTKS
Input Card 5: FORMAT (11F5.3)
(PCTRN(I),I = 1,11)
Input Card 6: FORMAT (F10.3)
Input Card 7: If MULT = 1, start over with Input Card 2-
If MULT = 0, continue on with (NCASE-1) additional
cards like Input Card 6.
Figure II-l gives examples of both card input forms to the CSSAS
program.
Figure II-2 gives definitions of the FORTRAN variables used by
the CSSAS program.
Figure II-3 gives the FORTRAN listing of the CSSAS program.
Figure II-4 gives a sample printout from the CSSAS program.
-------
II-2
n f! 1
0. f:. !V I"., p
• . t'.i". 1 , fi. , io 1 f. 5 0. J :;ci. I;-,.--:9 i 9 r A3 . fi43 S. S6
5.3? 1=^. .166 .65 ,-'.4* . fifi?6 3P.67
49.6
fi r M . ' r i"j . !"' . i" . fi . fi- . fi . fi . fi .
fi. fi. } . fi. fi. fi. fi. fi • fi. fi'. fi. p
.707 1, " f-." ^.05 !?.?. " fi. " I40T5 18.1 .05 4.43
f.5? 'ISO. .171 .65 P.ftf, .fifi£9 3^.6 33.3 11. R5 So.
1? 1 fi fi
Input Form With MULT = 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 D 0 B 0 0 0 ,~ 0 0 0 0 0 0 0 0 0 ',' 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Q 0 0 0 O 0 0 0
» 1 } 4 5 6 ) B S 10 H I? 13 II 15 Ib 17 II 19 20 21 22 23 24 25 26 21 21 29 30 31 37 33 34 35 36 37 JB 39 4» 41 42 43 44 IS 46 47 41 49 50 51 52 53 Si 55 58 57 51 59 60 61 S2 63 6< 65 66 67 61 69 70 II 7! 7J 14 75 I6 n n „ ,„
II I 1 I I M, 1 I I 1 1 I I 1 1 I, 1 1 1 1 1 I 1 1 I I 1 1 1 1 1 1 1 1 1 1 1 1 I 1 I 1 1 1 1 1 I M 1 1 1 M 1 1 1 1 I 1 1 1 M I 1 M 1 I I M 11 I
222 22 22?22 2 2 2 22J 2 22 2 22 22 222 2 222 72222 2222 2 2 22 22222222222 22222 22 22222 222222222 2 22?
33333333333333333333333333333333333333333333333333333333333333333333333333333333'
555 55 55 5 5 5 5 5 5 5 5 55 5 S 5 5 5 55 55 5 5 5 55 55 5 55 5 5 5 5 5 5 5 5 5 55 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 b 5 5 5 5 5 55 5 5 555
666666666666666 66 66666 666666666 66 666666 66 66 666666566666 666666G6 6666 6B6666 666 6861
7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7/7 7 7 7 7 7 7 7 7 7 7 7 7 H 7 7 7 ? 7 7 7 7 77 7 7 7 7 7 7 7 M 7 7 77 7 7 7 7 7 7 7 7 7 f 7 7 7 7 7 7
8 8 8 8 8 88 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 88 8 8 8 08 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 B B 8 8 8 8 8 8 8 8 8 8 B 8 8 8 8 8 8 8 8 8 8 8 8 8 8 J U
9999999999999999999999999999999999999999999599999999999999999999999955999:99990,
I 7 3 4 b 6 .• B 9 10 II 12 13 II 15 IE 17 IB 13 20 II !J 73 24 25 II 21 21 29 30 31 32 33 34 35 36 31 31 3> 41 41 47 13 41 45 <6 17 4B 49 50 51 52 53 54 55 56 57 5B 5« 60 SI 62 63 61 65 66 67 U S< 10 II 77 '1 ,"i n
f.nal ocf * 'b I* 17 IB IJ IB
'-'•• v' IT. ,
.17!
Input Form With MULT = o
0 0 0 0 0 0 0 0 0 0 0 O 0 0 0 0 0 0 0,' 0 0 0 0 0 0 0 0 0 L' 0 0 0 0 0 0 0 0 0,' 0 0 0 O 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 B 0 0 0 0 0 D 0 D 0 0 0 D 0
« ! 3 4 b b 1 « 9 10 II 17 >1 14 15 >b I) II 13 20 21 22 11 24 25 26 27 !l 29 30 II 32 13 14 35 36 37 M 39 40 41 4? 43 44 45 46 47 41 49 50 51 5? 13 51 55 5t 57 51 59 SO 61 52 (3 64 fib IS 61 6B 69 70 II ;? 13 H n ,. ,
1 1 11 I 1 1 1 j I 1 I 1 I I 1 I 1 1 I I 1 1 1 1 I M 1 I 11 11 1 I 1 1 I I 11 1 I 1 I 1 1 1 1 i 1 1 II 1 1 1 1 1 1 1 I 1 I] I 1 I 1 I 1 | i | | ',",'"?
2 22 22 22 22, 1 22 2 22222?11 2222 2 2 222 22 2 22222 22 2222222222222222222 22 22222 222222222 22 2?
3 33 33 33 333 333 3 3 333 33 33 33 33 3 3333 33 33333 3 3333 333333333 3 3333 3 33 33 3 3333 33333 333 3 3 3 ,3
4444444 444444 4444444444444U44U44444444444 444144M444444 444 44 4444444444 « 4444444
5 55 5 5 55 555 555 55 b5 5 55 55 55 555 555 5 5 5 555 55555 55 555 5 5555555555 555 5 55 5555 S555 5 5 5555555
S666666666666 6666666 66 66 666 666S66 66666 6666666666666666S66 66 6666 6666 ISt666 6666S6S
777777777?77777777777M777777 1111111111 77777M777777777 J7 111 17 1 J777 77/7777777jj?
888888888888888888888888888888 I 88888811 888888888888888888888888881818888888881 eg
999999999999999999 99999399999 99 99 99999999 99 9999 99999999 999 9 9 9 99 9999 999999"Q9,« ..
I ) ) < 5 6 .' B 9 10 II II 13 14 15 IB II It 19 20 21 ?7 7J 24 25 21 27 it 29 30 Jl 32 3J 34 J5 16 37 3B ]• 40 41 4! 43 44 45 46 47 4B 49 50 51 52 53 54 55 St 51 5« 59 10 II 62 S3 64 65 66 tl H 69 10 II 71 n l". n. " " "
'081 BSC ™ " " '« II *>
FIGURE II-l
-------
II-3
FIGURE II-2
DEFINITIONS OF FORTRAN SYMBOLS
CSSAS PROGRAM
Compute r
Symbol
Definitions and Comments
AEFF
AIRPG(I)
BOD14
BSIZE(I)
CR(I)
CS(I)
CE(I)
CY(I)
D
DBOD
DC
DNBC
DT
IDIS
IEA
Efficiency of diffusers in aerator
Air requirements for sub-aerators, scf/gallon
Total 5-day BOD at station 14, mg/1 oxygen
Required size of blower for supplying air to aerator,
scf/min.
Maximum rate constant for synthesis, day1: 1 = 1 for
heterotrophs, 1=2 for nitrosomonas
Saturation constant, mg/1 of substrate
Endogenous respiration constant, fraction of viable
cells which lyse per day
Yield coefficient, Ibs cells synthesized per Ib of
substrate utilized
Ratio of volume xlow to total aerator volume, days
Dissolved 5-day BOD at station 14, mg/1 oxygen
Specific wasting rate, Ib MLASS wasted per day/lb
MLASS in aerator
Concentration of dissolved non-biodegradable carbon
at station 20, mg/1 carbon
Detention time for sub-aerators, V(I)/Q(I+1) days
Program control: set equal to 0 to allow both
dissolved and particulate BOD to be available for
synthesis; set equal to 1 to allow only dissolved
BOD to be available for synthesis
Program control: set equal to 0 to run regular
aeration data; set equal to 1 to run extended
aeration data
-------
II-4
DEFINITIONS OF FORTRAN SYMBOLS
CSSAS PROGRAM
Computer
Symbol
Definitions and Comments
MLASS
MLBSS
MLDSS
MLNBS
MLVSS
MULT
NCASE
NTKS
PCTFL(I)
PCTRN(I)
QQ
Concentration of active solids held in aerator, mg/1
mass
Concentration of unmetabolized biodegradable solids
held in aerator, mg/1 mass
Concentration of non-biodegradable solids in the
aerator caused by destruction of active solids by
natural causes, mg/1 mass
Concentration of inert organic solids in aerator
caused by inert organic solids in influent, mg/1
mass
Concentration of volatile suspended solids held in
aerator, mg/1 mass
Program control: set equal to 0 to run several cases
varying MLASS with one set of input; set equal to 1
to run several cases each with a different set of
input
Program control: number of cases to be executed by
the program
Number of equal volume sub-aerators
Fraction of influent flow at station I downstream of
entry point
Fraction of return flow at station I downstream of
entry point
Volume flow at station I, mgd
Specific substrate removal rate, Ib substrate removed
per day/lb active solids in aerator
-------
II-5
DEFINITIONS OF FORTRAN SYMBOLS
CSSAS PROGRAM
Computer
Symbol
Definitions and Comments
SBOD(I)
SFBOD
SSOUT
URSS
VI7
VAER
VIS20
WAS ( I )
WDN(I)
WFOOD(I)
Concentration of substrate at station I, mg/1: J = 1
for 5-day BOD, J = 2 for ammonia
Concentration of particulate 5-day BOD at station I,
mg/1 oxygen
Solid fraction of BOD at station 20
Concentration of volatile suspended solids at station
14, mg/1
Final settler compaction ratio
Volume of the stabilization tank, millions of gallons
Volume of individual sub-aerators, millions of gallons
Total volume of aerator, millions of gallons
Concentration of non-biodegradable volatile suspended
solids at station 20, mg/1
Ib heterotrophs in the Ith sub-aerator
Ib ammonia nitrogen used per day in the Ith sub-
aerator
Ib 5-day BOD used per day in Ith sub-aerator
XL
XRSS
XS
Concentration of micro-organisms at station I, mg/1:
J = 1 for heterotrophs, J = 2 for nitrosomonas
5-day BOD loading, Ib 5-day BOD per day per 1 Ib MLVSS
Final settler efficiency, VSS at station 14/VSS at
station 1
5-day BOD removal effectiveness, BOD14/S(1,20)
-------
II-6
DEFINITIONS OF FORTRAN SYMBOLS
CSSAS PROGRAM
Computer
Symbol Definitions and Comments
XXL Inverse 5-day BOD loading, l./lb 5-day BOD per day
per 1 Ib MLVSS
XXS 5-day BOD removal effectiveness, 1./BOD14 - l./S(l,2O)
-------
IJ-7
FIGURE II-3
t 2 STEADY STATE MATHEMATICAL MODEL FOR ACTIVATED SLUDGt
REAL MLVSS,MLASSfMLBSS,MLNBS,MLDSS
DIMENSION 513,20) ,X(3,20),CR(3),CS(3),CE(3),CY(3),0(20),SBOD(20 ) ,
. WFOOD(10),WAS(10)„WON(10),BSIZE{10),AIRPG(10),V(10),
. PCTFL (11) ,PCTRN(11),BTEMP(11),ATEMP(ll),BUSER(li),AUSER(11)
IN = 2
10=5
ISET=1
3 FORMAT!1H1,///,55X,'INPUT' ,/)
4 FORMA TdX,'CRd)',t)X,'CSd)',5X,'CEd)',5X,«CYd)',6X,'URSS',
. 5X,'XRSS' ,4X,'SBOD(20)' ,4X,'V IS20•,7X,'DNBC',4X,'Q(20)•,//IX,
. 'CR(2)',5X,'CS(2)',5X,'CF<2)',5Xt'CY(2)',6X,'VAER' ,5X,'V(17)*,3X ,
. «S(1,20)•,4X,'S(2,20) ',6X,'AEFF',4X,'SSOUT«,//IX,'PCTFL(I)',//IX,
. 'PCTRN!I ) ' ,/// )
11 FORMAT!55X,'OUTPUT',//)
12 FORMAT!IX,'X!1,1)•,4X,•X(1,NTKS+1)•,2Xt«S(l,l)',2X,*S(L,NTKS+1)',
. 3X,'NTKS',6X,'y!14)',5X,'Q(15)',4X,'Q(i7)',3X,'OBOD14',5X,'BOD14'
. ,7X,'XRSS',6X,'DT',//lX,'MLVSS',8X,'MLASS',6Xt'MLBSS',5X,'MLNBSS'
. ,5X,'MLDSS',4X,IX(1,L6)',3X,'X(1,17)',2X,IS(1,16)I,2X,«S(1,17)1,
. 4X,'SFBOD',9X,'D',7X,'DC',/)
14 FORMAT!IX,«X(2,1)',5X,'X(2,NTKS+I)«,2X,'S(2,1)•,2X,'S(2,NTKS+1)',
. 4X,'L' ,8X, ' 1/L1 ,7X,'S/S',4X,
. «V( I
WRITE
WRITE
WRITE
WRITE
WR ITE
10,3)
10,4)
10,11)
10,12)
10,14)
r NCASE IS THE NUMBER OF CASES TO BE EXECUTED.
c MULT=0 ONE SET OF INPUT FOR ALL POINTS.
r MULT=1 SEPARATE INPUT FOR EACH POINT.
c IEA=1 SETS THE DECK UP TO RUN EXTENDED AERATION DATA
c IDIS=1 SETS THE DECK UP TO RUN WITH ONLY DISSOLVED BOD AVAILABLE.
C
READ(IN,1) NCASE,MULT,IEA,IDIS
I FORMAT(4I10)
WRITE(IO,13) NCASE,MULT,IEA,IDIS
13 FORMAT!IX,'NCASE=',I 3,3X,'MULT=',I 3,3X,'IEA=•,I 3,3X,•101S*•,I3///)
C
c THIS LOOP PERFORMS A COMPLETE SET OF CALCULATIONS FOR EACH CASE.
C
DO 200 J=l,NCASE
IF(ISET) 81,84,81
£ READ IN AND PRINT OUT ALL OF THE INPUT DATA.
C
81 READ(IN,5) CR(1),CS(1),CE(I),CY(1),URSS,XRSS,SBOD(20 ) ,
. VIS20,DNBC,Q(20)
READ(IN,6) CR(2),CS(2),CE(2),CY(2),VAER,V17,S(1,20),S(2,20),
. AEFF,SSOUT
READ( IN,76) (PCTFL!I),I = 1,11),NTKS,(PCTRN( I ),! = !,11)
76 FORMAT(11F5.3,23X,I2/11F5.3)
WRITE! 10,7) CRd) ,CS(1) ,CEd) ,CY( 1 ), URSS , XRSS , SBOD ( 20 ) ,
. VIS20,DNBC,Q(20)
WRITE(10,8) CR(2),CS(2),CE(2),CY(2),VAER,VI7,S(1,20),S(2,20),
. AEFF,SSOUT
KK=NTKS+1
-------
II-8
PAGE 3 STEADY STATE MATHEMATICAL MODEL FOR ACTIVATED SLUDGE
WRITE(10,192) (PCTFL(I), 1=1,KK)
WRITE(10,194)
WRITE(10,192) 3
b3 SFBOD=0.
bb UO 19 IJ=1,NTKS
19 V( IJ)=VAER/!MTKS
V17=0.
IF(V17) 72,73,72
73 S<1,1)=.5»S(1,20)
S(1,17)=S(1,1)*SFBOD*URSS+S
-------
II-9
PAGE 4 STEADY STATE MATHEMATICAL MODEL FOR ACTIVATED SLUDGE
DT = V(I1/FLOWA
S(ltI+l)=S(LtI)+CR(l)*S(LtI)*X(lfI)»DT/(CY(l)*(CS(l>+SUtI)»
X(1,I+1)=X(1,I)+CE(1)*DT*X(1, I)-(CR< 1)*S(1,I )»X( 1,1 )*DT)/(CS(1) +
. S(l, I ) )
BTEMP(1+1) = S(19I+l)
BUSER(I+1)=X(1,1*1)
IF(NTKS-Kl) 63,64,63
63 S(IfI + l)«(S(ltI+l)*FLOWA-S(1,20)*Q(20)*PCTFL( H-1)-S(1,17)»Q(17)*
. PCTRNI1+1))/FLOW6
X(l,I-H)=(X(l,I-H )*FLOWA-X( 1, 17)*Q(17)*PCTRN(1 + 1) )/FLOWS
64 CONTINUE
S(1,17) = (S( 1VNTKS+1)»(0(20)*PCTFL(NTKS+1)+Q( 17 ) *PCTRN ( NTKS-H ) )-
. S(1,20)*Q(20)*PCTFL(NTKS-H) ) / ( Q( 17 ) «PCTRN ( NTKS + 1 ) )
X( 1,17) = (X( 1,IMTKS-H)*(Q(20)»PCTFL(NTKS-H)+Q(17)»PCTRN(NTKS-H) ) )/
. (Q(L7)»PCTRN(NTKS+1))
X(l,16)=X(l,17)+CE(l)»DT17*X(l,17)-(CR(l)*S(l,17)*X(l,17)*DT17)/
. (CS( 1)+S(1 ,17) )
IF(V17) 68,66,68
66 S(1,16)=S(1,17)
68 S1 = S(1,16 )/(SFBOD*(URSS-i.)*l.)
DSl=S(l,l)-Sl
IF(ABS(DS1)-.01) 29,29,22
22 IF(IS-20) 24,29,29
24 IF(OSl) 27,27,25
25 SLOW=S(1,1)
S(l, 1) = S( 1, l)+.b*(SUP-SLOW)
IS=IS-H
GO TO 15
27 SUP=S(1,1)
S(1,1)=S(1,1)-.5*(SUP-SLOW)
IS=IS+1
GO TO 15
29 X1=X(1,16)/URSS
DX1=X(1,1)-Xl
IF(ABS(DX1)- .1) 50,50,30
30 IFUX-20) 31,40,40
31 IF(DXl) 37,37,35
35 QUP=Q(17)
Q(17)=0(17)-.5*(QUP-QLOW)
GO TO 10
37 QLOW=Q(17)
U(17)=0(17)+.5*(QUP-QLOW)
IQ=IQ+1
GO TO 10
40 WRITE(10,45) X( 1,1)
45 FORMAT(//,5X,'BOD ITERATION DOES NOT CONVERGE«,5X,'XI1,1)=•,
. F10.3,//)
GO TO 200
C
C THIS THE FINAL COMPUTED S(l,l).
C
50 SF1=S(1,1)
DBOD=S(1,!)•(!.-SFBOD)
Q(15)=(Q(20)»(1.-XRSS)-U(17)»(URSS-1.))/(URSS-XRSS)
-------
11-10
PAGE 5 STEADY STATE MATHEMATICAL MODEL FOR ACTIVATED SLUDGE
IF(IEA) 52,54,52
52 Q(15)=0.
54 Q(14)=«(20)-Q(15)
D=Q(20)/VAER
TEMP1=Q(14)*XRSS+Q(15)*URSS
MLASS=X(1,1)
MLBSS=S( 1,1)»SFBOD/.8
IF(IDIS) 58,59,58
58 MLBSS=SBOD(20)*Q(20)/.8/TEMPl
59 MLNBS=VIS20*Q(20)/TEMP1
MLDSS=. 18»CY(1)*(S(1,20)-S(1,1))*Q(20)/TEMP 1-.L8»MLASS
IF(MLDSS) 74,74,75
74 MLDSS=0.
75 MLVSS=MLASS+MLBSS+MLNBS+MLDSS
IFUJ-3) 70,71,70
70 XRSS=SSOUT/MLVSS
IF(IEA) 92,71,92
92 XKSS=1.-Q(17)«(URSS-1.)/Q(20)
71 BOD14=(.84*MLASS+.80*MLBSS)*XRSS+S(1,1)»(1.-SFBOD)
X(1,14)=XRSS»X( 1,1 )
X(I,15)=URSS»X( 1,1)
DC=(0(14)*X(1,14)+Q(15)*X(1,15))/(VAER»MLVSS)
XL=Q(20)«S<1,20)/(VAER*MLVSS)
XS=BOD14/S(1,20)
XXL=1./XL
XXS=1./BOD14-1./S(1,20)
0(J = 0(20)*(S(1,20)-BOD14)/(VAER»MLVSS)
WRITE(10,80) X(l,l),X(l,NTKS+i),S(1,1),S(1,NTKS* I),NTKS,Q(14),
. Q(15),Q(17),DBOD,BOD14,XRSS,DT
80 FORMAT(4F10.3,I10,F10.3,F10.6,3F10.3,FL0.5,F10.3,/)
WRITE( 10,90) MLVSS,MLASS,MLBSS,MLNBS,MLDSS,X( l,16),X(l,17),
. S(l,16) ,S(1,17) ,SFBOD,0,DC
90 FORMATt12F10.3,/)
C
C A DOUBLE HALFING ITERATION IS PERFORMED ON S(2,l) AND X(2,l).
C S(2,l) AND X(2,l) ARE BOTH ITERATED ON FOR 20 PASSES EACH.
C
X(2,l)=CY(2)*a(20)*S(2,20)/(DC»VAER)
IF(X(2tl)) 101,101,217
C
C IF X(2,l) IS NEGATIVE GOING IN, THERE ARE NO NITRIFICATION CALCULATIONS
C
101 WRITE(10,102) X( 1,1),X(2,l)
102 FORMATl///,5X,43HNO NITRIFICATION OUTPUT SINCE X(2,l) IS NEGATIVE,
. 5X,7HX(1,1)=,F10.3,5X,7HX(2,1)=,F10.3,///)
GO TO 200
217 XLOW=0.
XUP=2.*X(2,1)
IX = 0
210 S(2,1)=.5*S(2,20)
SLOW=0.
SUP=S(2,20)
IS=0
DT17=V17/Q{17)
IF(V17) 272,273,272
273 S(2,17)-S(2,1)
GO TO 278
-------
11-11
PAGE 6 STEADY STATE MATHEMATICAL MODEL FOR ACTIVATED SLUDGE
272 S(2,17)*.5*S(2,1)
216 X(2,17)=URSS*X(2,1)
215 Kl=0
ATEMP(1)*S(2V 1)
AUSER( 1)=X(2,1)
DO 264 I=1,NTKS
FLOWA=Q(20)+0(17)
Kl=Ki+l
DO 262 K=1,K1
FLOWA=FLOWA- *DT/ (CY( 2 ) • ( CS ( 2 )+S ( 2, I ) ) )
X(2tI+l)*X(2fI)+CE(2)*DT»X(2,I)-(CR(2)»S(2,I)*X(2 , I)»DT)/(CS(2 ) +
. S(2, I ) )
ATEMP(I+l)«S(2«I+l)
AUSER(I+l)eX(2tI+L)
IF(NTKS-Kl) 263,264,263
263 S(2,H-1)=(S(2,H-1)*FLOWA-S(2,20)*Q(20)*PCTFL( I+l)-S(2tl7)*Q(L7)»
. PCTRN(1+1))/FLGWB
X(2,I + 1) = (X(2,H-1)*FLOWA-X(2,17)»Q( 17)»PCTRN( 1 + 1) )/FLOWB
264 CONTINUE
S(2t17)«(S(2tNTKS+il«(Q(20)»PCTFL(NTKS+i)+Q(17)«PCTRN(NTKS+l))-
. S(2,20)*U(20)*PCTFL(NTKS-H) ) / ( Q( 17 ) *PCTRN( NTKS^-1) )
X(2,17) = (X(2,NTKS-H)*(Q(20)»PCTFL(NTKS-H)+Q(17)«PCTRN(NTKS-H) ) )/
. (Q( 17)*PCTRN(NTKS-H) )
S(2tl6)»S(2tl7)+CR(2)«S(2tl7)«X(2fl7)«DT17/(CY(2)*(CS(2»+S(2tl7))1
X(2f16)»X(2tl7)+CE(2)*DT17«X(2f17)-(CR(2)«S(2tl7)*X(2fl7)»DT17)/
. (CS(2)+S(2,17i )
IFW17) 268,266,268
266 S(2,16)=S(2,17)
X(2,16)=X(2,17)
268 S2»S(2,16)
DS2=S(2,1)-S2
IF«ABS(DS2)-.01) 229,229,222
222 IFUS-20) 224,229,229
224 IFJDS2) 227,227,225
225 SLOW=S(2,1)
S(2,1 ) =S(2,l)+.5»(SUP-SLOW)
IS=IS-H
GU TO 215
227 SUP=S(2,1)
S(2, 1) = S(2,1)-.5*(SUP-SLOW)
IS=IS+1
GO TO 215
229 Xl=0.
X2 = 0.
DO 251 I=1,NTKS
X1-X1+(Q(20)-Q(20)»PCTFL(I)+Q(17)-Q(17)»PCTRN(I))*AUSER(I)
251 X2 = X2+(Q(20)-U(20)*PCTFL(I)+Q(17)-Q(17)*PCTRN(I))«XI 2,1 + 1)
X2=(X1-X2)/X(2,1)
DX2=TEMPi-X2
IF(ABS(DX2)- .1) 250,250,230
230 IF(X(2,1)-.001) 250,250,232
232 IF(IX-20) 231,240,240
231 IF(DX2) 237,237,235
235 XUP=X(2,1)
-------
11-12
PAGE 7 STEADY STATE MATHEMATICAL MODEL FOR ACTIVATED SLUDGE
X(2,1)=X<2,1)-.5*(XUP-XLOW)
IX=IX+1
GO TO 210
237 XLOW=X(2tl)
X(2, 1)=X(2,1)+.5*(XUP-XLOW)
IX=IX+1
GO TO 210
240 WRITE(10,245) X(lfl)
245 FORMAT(//,5X,'NH3 ITERATION DOES NOT CONVERGE',5X,'X(1,1)=•,
. F10.3,//)
GO TO 200
C
C THIS IS THE FINAL COMPUTED X(2,l) AND S(2,l).
C
250 SF2=S(2,1)
XF2=X(2,1)
01=Q(20)+Q(17)
TSIZE=0.
FPG=0.
DO 185 I=1,NTKS
HFOOD(I)=Q1*(BTEMP(H-i)-S(l,I))*8.33
WAS(I)=X(1,I)*V(I)*8.33
WDN( I)=Ql»(ATbMP(I+l)-S(2,l))*8.33
BSIZE( I )=(.577*WFOOD(I)-H . 16»CE(1)»WAS(I)+4.6*WDN(I))/
. (AEFF».232*.075*1440.)
AIRPG(I)=BSIZE(I)*1440./(Q(20)*1000000.)
TSIZE=TSIZE+BSIZE(I)
TPG=TPG+AIRPG(I)
Ib5 Q1=Q1-Q(20)*PCTFL(I)-Q(17)*PCTRN(I)
WRITEt10, 190) XI2,1),X(2,NTKS + 1),S(2,i),S(2,NTKS + l),XL,XXL,
. XS,XXS,OQ
190 FORMAT(9F10.3,/)
WRITEl10,192) (V(I),I=l,NTKS),VAER
WRIFE(10,194)
WRITE(10,193) (BSIZEU),I=1,NTKS),TSIZE
WRITE(10,194)
WRITE(10,192) (AIRPG(I),I=1,NTKS),TPG
WRITE<10,196)
192 FORMATt11F10.3)
193 FORMAT(llFlO.l)
194 F(JRMAT( )
1^6 FORMAT!////)
200 CONTINUE
CALL EXIT
ENO
-------
11-13
INPUT
CR(1)
CR(2)
PCTFL(I)
PCTRN(I)
Xll.l)
MLVSS
csm
CS(2)
XU.NTKS+1
HLASS
CEU) CY(l) URSS XRSS SBODI20) VIS20 DNBC 0(20)
CE(2) CY(2I VAER V(17) S(l,20) S«2,20) AEFF SSOUT
OUTPUT
1 S(ltl) S(1,NTKS+1J NTKS 0(14) 0(15) Q(17) DB0014 BOD14 XRSS OT
MLBSS HLNBSS MLDSS X41.16) X(l,17) S(1,16I SU.17) SFBOD 0 DC
X(2,i) X(2,NTKS+1) S(2,l) S(2,NTKS+1> L 1/L S/S 1/S-l/S QO
V( I )
ftSIZEUI
AIRPGIII
NCASE- 12
6.550
0.707
0.000
0.000
873.000
1371.801
14.782
6.250
14772.1
0.425
MULT- 1
150.000
1.000
0.000
0.000
838.175
873.000
14.184
6.250
57047.8
1.642
IEA* 0 IOIS- 0
0.171 0.650 2.860 0.0029 34.600 23.300 11.650 50.000
0.000 0.050 12.500 0.000 140.500 18.100 0.050 4.430
1.000
1.000
3.058 94.840 2 49.004 0.995810 25.265 2.293 4.663 0.00322 0.083
0.956 387.529 110.316 2496.912 2496.912 4.481 4.481 0.250 4.000 0.153
0.091 12.054 0.409 2.440 0.033 0.207 0.396
12.500
71819.9
2.068
FIGURE II-4
-------
11-14
Input Data for the FADAS Program
Input Card 1: FORMAT (13)
NCASE
Input Card 2: FORMAT (8F8.2,F8.3,18)
XO, SO, XM, XKS, XKE, Y, R, TEST, H, NINC
Input Card 3: Continue on with (NCASE-1) additional cards
like Input Card 2
Figure II-5 gives an example of the card input form to the FADAS
program.
Figure II-6 gives definitions of the FORTRAN variables used by
the FADAS program.
Figure I1-7 gives the FORTRAN listing of the FADAS program.
Figure II-8 gives a sample printout from the FADAS program.
-------
11-15
Of'
JfiO. ?iVi. 4.P 150. .1 .!
ii an a a Q.
4 >''•*„ 400. 4.S 150. .1
400.
150.
f.55 .fifi?
.
0 00 00 0 0000 0 00 00 0 0 00 0 0 0 HO 00 00 0 0 0 0000 0 0 00 0 00 0 00 00 0 00 0000 00 00 000 0 0 0 tO 00 00 0
00 0 0
< 1 1 I 5 t 1 I 9 10 n i; i] il IS Ib II i! 19 20 21 11 li » Ii » !l » !S 30 31 1! a V Si X 17 u JS 40 41 47 <3 4< *0 «t 4? 43 4« 45 4fi *I 48 49 50 51 5Z 53 54 55 56 57 *R W SO Gl G2 63 64 65 66 67 68 S3 '0 M f? " '4 '5 76 H 18 '9 10
r
-------
11-16
FIGURE II-6
DEFINITIONS OF FORTRAN SYMBOLS
FADAS PROGRAM
Computer
Symbol
Definitions and Comments
FACTO
FACTX
H
I
NINC
SDOT
SO
SS
TEST
XDOT
XKE
XKS
XM
XD
XX
Y
Current concentration of substrate/initial concentration
of substrate
Current concentration of heterotrophs/initial concen-
tration of heterotrophs
Time interval for numerical integration, days
Number of time increment
Total number of time intervals the program is to
calculate
Coefficient which converts the lysed cell mass to
substrate returned to solution
Rate of change of 5-day BOD with time, mg/1 day
Initial concentration of 5-day BOD, mg/1
Current value for substrate, 5-day BOD, mg/1
Desired effluent concentration of 5-day BOD, mg/1
Rate of change of XX with time, mg/1 day
Endogenous respiration rate, day"
Saturation constant, 5-day BOD, mg/1
Maximum rate constant for synthesis, day
Initial concentration of heterotrophic bacteria, mg/1
Current value for concentration of heterotrophs, mg/1
Yield coefficient, Ib cells/lb substrate
-------
FIGURE II-7 H-17
PAGE 2 FADAS
FUNC1 (XXtSStXM,XKS,XKE)=XX»(XM*SS/(XKS+SS)-XKE)
FUNC2(XX,SS,XM, XKS, XKE , R , Y ) =XX/Y» ( R*XKE-XM*SS/ ( XKS+SS ) )
IN = 2
10 = 5
700 FORMAT! 13)
702 FORM AT ( lOX.'NSlOX.'X'.lAXt'X/XO'tlBX, • XDOT • , 14X, 'SDOT1 , 13X,
. *S/SO' ,14X,'S* )
703 FORMAT(7XtI5, 5X»El0.4v7Xt E10.4* 7XtE10.4t7X,EL1.4t7X,El0.4f
. 7XfE10.4)
704 FORMAT( 1H1, SOX, ' INPUT DATA ',//, IOX ,» CASE NO.1, 13)
READUN,700) NCASE
DO 200 N*1,NCASE
WRITE(IO,704) N
R6AD( IN, 701 ) XO,SO,XM,XKS,XKE,Y,R,TEST,H,NINC
701 FORMAT(8F8.2,F8.3,I8)
WRITEU0.706)
706 FORMAT(/,16X, • XO ' , 8X , • SO • ,9X, ' XM« , 6X, «XKS' , 8X , • XKE ' , 8X, «Y' ,9X,'R«,
. 7Xt*TESTlf8Xt*H*,BXt*NINC* )
WRITE (1 0,705) XO,SO,XM,XKS,XKE,Y,R,TEST,H,NINC
705 FORMAT(/,10X,9F10.3,I10,//J
WRITE( 10,702)
XX=XO
FXO=XO
SS = SO
FSO=SO
DO 100 I=1,NINC
SO=SS
XO = XX
XK1=FUNC1(XX,SS,XM,XKS,XKE)
XL1=FUNC2(XX,SS,XM,XKS,XKE,R,Y)
XDOT=XK1
SDOT^XLl
XK1=XK1*H
XL1=XL1*H
XX=XO+XKl/2
SS = SO-i-XLl/2
XK2=FUNC1(XX,SS,XM,XKS,XKE)
XL2=FUNC2(XX,SS,XM,XKS,XKE,R,Y)
XL2=XL2*H
XK2=XK2*H
XX=XO+XK2/2.
SS=SO+XL2/2.
XK3=FUNC1(XX,SS,XM, XKS,XKE)
XL3*FUNC2(XX,SS,XM,XKS,XKE,R,Y)
XK3=XK3»H
XL3=XL3»H
XX=XO+XK3
XKA=FUNC1(XX,SS,XM,XKS,XKE)
XLA=FUNC2(XX,SS,XM,XKS,XKE,R,Y)
DX=.1667»(XKH-2.*XK2+2.*XK3+XK^)
XX=XO+DX
SS=SO+DS
FACTX*XX/FXO
-------
11-18
PAGE 3 FADAS
FACTO=SS/FSO
WRITE!10,703) I ,XX,FACTX,XDOT,SDOT,FACTO,SS
IF(SS-TEST) 200t200,100
100 CONTINUE
200 CONTINUE
CALL EXIT
END
-------
11-19
INPUT DATA
CASE NO. 1
XO SO
400.000 100.000
N
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
0.4014E 03
0.4028E 03
0.4042E 03
0.4056E 03
0.4069E 03
0.4083E 03
0.4096E 03
0.4109E 03
0.4121E 03
0.4133E 03
0.4145E 03
0.4157E 03
0.4169E 03
0.4180E 03
0.4191E 03
0.4202E 03
0.4212E 03
0.4222E 03
0.4232E 03
0.4242E 03
0.4251E 03
0.4260E 03
0.4269E 03
0.4277E 03
0.4286E 03
.4294E 03
.4301E 03
0.4309E 03
0.4316E 03
0.4323E 03
0.4330E 03
0.4336E 03
0.4343E 03
0.4349E 03
0.4354E 03
0.4360E 03
0.4365E 03
0.4370E 03
0.4375E 03
0.4380E 03
0.4385E 03
0.4389E 03
0.4393E 03
0.
0.
XM XKS
4.800 150.000
X/XO
0.1003E 01
0.1007E 01
0.1010E 01
0.1014E 01
0.1017E 01
0.1020E 01
0.1024E 01
0.1027E 01
0.1030E 01
0.1033E 01
0.1036E 01
0.1039E 01
0.1042E 01
0.1045E 01
0.1047E 01
0.1050E 01
0.1053E 01
0.1055E 01
0.1058E 01
0.1060E 01
0.1062E 01
0.1065E 01
0.1067E 01
0.1069E 01
0.1071E 01
0.1073E 01
0.1075E 01
0.1077E 01
0.1079E 01
0.1080E 01
0.1082E 01
0.1084E 01
0.1085E 01
0.1087E 01
0.1088E 01
0.1090E 01
0.1091E 01
0.1092E 01
0.1093E 01
0.1095E 01
0.1096E 01
0.1097E 01
0.1098E 01
XKE
0.100
XDOT
0.7280E 03
0.7169E 03
0.7056E 03
0.6941E 03
0.6823E 03
0.6703E 03
0.6581E 03
0.6457E 03
0.6332E 03
0.6204E 03
0.6075E 03
0.5945E 03
0.5813E 03
0.5680E 03
0.5547E 03
0.5412E 03
0.5277E 03
0.5142E 03
0.5006E 03
0.4870E 03
0.4735E 03
0.4600E 03
0.4465E 03
0.4331E 03
0.4198E 03
0.4066E 03
0.3935E 03
0.3806E 03
0.3678E 03
0.3552E 03
0.3427E 03
0.3305E 03
0.3184E 03
0.3066E 03
0.2950E 03
0.2837E 03
0.2726E 03
0.2617E 03
0.2511E 03
0.2408E 03
0.2308E 03
0.2210E 03
0.2115E 03
Y
0.500
R
0.800
SDOT
-0.1472E 04
-0.1449E 04
-0.1427E 04
-0.1404E 04
-0.1380E 04
-0.1357E 04
-0.1332E 04
-0.1307E 04
-0.1282E 04
-0.1257E 04
-0.1231E 04
-0.1205E 04
-0.1179E 04
-0.1152E 04
-0.1126E 04
-0.1099E 04
-0.1072E 04
-0.1045E 04
-0.1018E 04
-0.9911E 03
-0.9640E 03
-0.9370E 03
-0.9101E 03
-0.8834E 03
-0.8568E 03
-0.8304E 03
-0.8043E 03
-0.7784E 03
-0.7529E 03
-0.7277E 03
-0.7028E 03
-0.6783E 03
-0.6543E 03
-0.6307E 03
-0.6075E 03
-0.5848E 03
-0.5627E 03
-0.5410E 03
-0.5198E 03
-0.4992E 03
-0.4791E 03
-0.4596E 03
-0.4406E 03
TEST
20.000
H
0.002
S/SO
0.9707E 00
0.9419E 00
0.9136E 00
0.8858E 00
0.8584E 00
0.8315E 00
0.8051E 00
0.7791E 00
0.7537E 00
0.7288E 00
0.7045E 00
0.6806E 00
0.6573E 00
0.6345E 00
0.6122E 00
0.5905E 00
0.5693E 00
0.5487E 00
0.5286E 00
0.5090E 00
0.4900E 00
0.4715E 00
0.4536E 00
0.4362E 00
0.4193E 00
0.4030E 00
0.3871E 00
0.3718E 00
0.3570E 00
0.3427E 00
0.3289E 00
0.3156E 00
0.3027E 00
0.2903E 00
0.2784E 00
0.2669E 00
0.2559E 00
0.2453E 00
0.2351E 00
0.2253E 00
0.2159E 00
0.2069E 00
0.1983E 00
NINC
100
0.9707E 02
0.9419E 02
0.9136E 02
0.8858E 02
0.8584E 02
0.8315E 02
0.8051E 02
0.7791E 02
0.7537E 02
0.7288E 02
0.7045E 02
0.6806E 02
0.6573E 02
0.6345E 02
0.6122E 02
0.5905E 02
.5693E 02
.5487E 02
0.5286E 02
0.5090E 02
0.4900E 02
0.4715E 02
0.4536E 02
0.4362E 02
0.4193E 02
0.4030E 02
0.3871E 02
0.3718E 02
0.3570E 02
0.3427E 02
0.3289E 02
0.3156E 02
0.3027E 02
0.2903E 02
0.2784E 02
0.2669E 02
0.2559E 02
0.2453E 02
0.2351E 02
0.2253E 02
0.2159E 02
0.2069E 02
0.1983E 02
0,
0.
FIGURE II-8
-------
APPENDIX III
EXPERIMENTAL DATA USED TO VALIDATE THE CSSAS MODEL
-------
III-l
BLUE PLAINS PLANT, WASHINGTON. D.C. - April 17-30, 1969
Primary Effluent:
1.
2.
3.
4.
5.
6.
7.
8.
9.
Temperature, C
Flow volume, mgd
Suspended solids, mg/1
% Volatile SS
TOC, uf, mg/1
5-day BOD, uf.
5-day BOD, f,
Ammonia as N,
mg/1
mg/1
mg/1 ,
Water temperature, F
Aerator :
1. Mixed liquor SS, mg/1
2. Mixed liquor volatile SS
3. Aerator volume, mg
Return and Waste Streams:
1. Return flow, mgd
2. Waste flow, mgd
3. Volatile SS, return, mg/1
4. Volatile SS, waste, mg/1
Secondary Effluent:
1. Volatile suspended solids, mg/1
2. 5-day BOD, uf, mg/1
3. 5-day BOD, f, mg/1
4. TOC, uf, mg/1
18.2
230.7
111.8
71.
69.1
114.8
40.4
14.7
61.
457.0
346.0
24.8
29.1
.921
2960.
15255.
28.9
45.4
18.4
32.1
EXTENDED AERATION. UNIVERSITY OF CINCINNATI DATA, Plant 2-B, Nov. 1965
Raw Influent Stream:
1. Flow volume, gpd
2. 5-day BOD, uf, mg/1
3. COD, uf, mg/1
4. Volatile SS, mg/1
Aerator:
1. Volume, gallons
2. Mixed liquor SS, mg/1
3. Volatile SS, mg/1
4. Air supplied, scf/gal.
Effluent Stream:
1. Suspended solids, mg/1
2. Volatile SS, mg/1
3. 5-day BOD, mg/1
4. COD, uf, mg/1
5. COD, f, mg/1
6. Final setter overflow,
gpd/sq ft
Waste Stream:
1. Flow volume, gpd
31,700.
195.
516.8
213.
4O,OOO.
4340.
3101.
6.1
176.
114.
35.6
169.6
43.6
331.
0.0
-------
III-2
HYPERION TEST NO.
Primary Effluent Flow Volume, mgd
Return Sludge Flow Volume, mgd
Waste Sludge Flow Volume, mgd
Aerator Volume, mg
Final Settler Surface Area, sq. ft.
Air Supplied, scf/gallon
HYPERION TEST NO.
Primary Effluent Flow Volume, mgd
Return Sludge Flow Volume, mgd
Waste Sludge Flow Volume, mgd
Aerator Volume, mg
Final Settler Surface Area, sq. ft.
Air Supplied, scf/gallon
HYPERION TEST NO.
Primary Effluent Flow Volume, mgd
Return Sludge Flow Volume, mgd
Waste Sludge Flow Volume, mgd
Aerator Volume, mg
Final Settler Surface Area, sq. ft
Air Supplied, scf/gallon
49.50
23.81
.950
12.50
95000.
1.29
49.60
29.07
.633
12.50
950OO.
1.30
49.83
33.98
.520
10.42
95000.
1.36
50.01
30.83
o877
8.33
95000.
1.40
10
11
8
49.68
20.14
1.160
8.33
95000.
1.40
49.11
17.09
1.100
8.33
950OO.
1.33
49.18
17.60
1.402
8.33
95000.
1.40
49.28
18.13
1.270
12.50
95000.
1.42
12
50.11
11.48
1.850
12.50
95OOO.
1.40
49.33
9.35
1.44O
12.50
95OOO.
1.4O
49.22
12.82
1.240
12.50
95000.
1.40
5O.18
19.19
.779
12.50
9500O.
1.4O
Note: In the Hyperion experiments the flow rate into the activated sludge process was fixed
at approximately 50 mgd and did not vary significantly with time
-------
III-3
HYPERION TEST NO.
Primary Effluent:
1. Water Temp. °F
2. COD, uf, mg/1
3. COD, f, mg/l
4. NH3 as N, mg/l
5. TKN, uf, mg/1
6. TKN, f, mg/l
7. P, uf, mg/1
8. P, f, mg/l
9. SS, mg/1
1O. % volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
Aerator Effluent:
1. COD, uf, mg/1
2. COD, f, mg/l
3. NH3 as N, mg/l
4. NO3 as N, mg/l
5. TKN, uf, mg/l
6. TKN, f, mg/l
7. P, uf, mg/l
8. P, f, mg/l
9. SS, mg/l
10. % volatile
11. BOD5, uf, mg/l
12. BOD5, f, mg/l
Return Sludge Stream:
1. COD, uf, mg/l
2. COD, f, mg/l
3. NH3 as N, mg/l
4. NO3 as N, mg/l
5. TKN, uf, mg/l
6. TKN, f, mg/l
7. P, uf, mg/l
8. P, f, mg/l
9. SS, mg/l
10. % volatile
11. BOD5, uf, mg/l
12. BOD5, f, mg/l
Final Effluent:
1. COD, uf, mg/l
2. COD, f, mg/l
3. NH3 as N, mg/l
4. NO3 as N, mg/l
5. TKN, uf, mg/l
6. TKN, f, mg/l
7. P, uf, mg/l
8. P, f, mg/l
9. SS, mg/l
10. % volatile
11. BOD5, uf, mg/l
12. BOD5, f, mg/l
80.3
280.2
219.1
22.0
29.3
27.8
14.8
14.0
76.9
83.2
140.3
106.5
1959.4
35.8
16.2
0.4
176.6
18.0
155.0
17.6
1996.9
68.9
613.1
23.2
5190.8
71.7
18.3
0.3
435.7
23.1
393.2
83.4
5696.9
68.0
1620. O
41.2
28.9
26.1
15.5
0.4
16.7
16.5
4.7
4.2
5.5
77.8
4.5
2.7
79.2
295.7
245.5
19.6
28.5
25.9
14.1
13.5
67.8
84.3
155.5
116.3
3358.0
39.2
17.6
0.1
243.3
19.1
201.0
17.8
3010.8
67.0
727.5
17.7
7471.5
75.1
19.9
0.1
562.8
23.9
474.0
60.1
7407.6
68.5
1753 . 7
18.6
33.3
27.4
16.5
0.1
17.8
17.7
7.1
7.1
9.1
79.2
4.9
3.6
75.8
320.1
245.6
17. "8
26.5
23.7
12.7
11.5
99.2
89.4
157.1
129.2
4016.0
36.5
16.2
0.1
277.1
18.0
146.2
14.4
3436.4
75.1
842.2
6.4
8593.6
57.4
19.0
0.1
625.3
22.9
338.9
49.7
7866.6
75.5
1627.8
16.6
39.9
27.5
14.9
0.2
17.0
16.1
6.9
5.8
14.0
90.1
8.0
4.1
-------
III-4
HYPERION TEST NO.
Primary Effluent:
1. Water Temp. °F
2. ODD, uf, rag/1
3. COD, f, mg/1
4. NH3 as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
1O. % volatile
11. BOD5, uf, ing/I
12. BOD5, f, mg/1
Aerator Effluent:
1. COD, uf, mg/1
2. COD, f, mg/1
3. NH3 as N. mg/1
4. NO3 as N, mg/1
5, TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
10. % volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
Return Sludge Stream;
1. COD, uf, mg/1
2. COD, f, rag/1
3. NH3 as N, mg/1
4. NO3 as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
10. % volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
Final Effluent r
1. COD, uf, mg/1
2. COD, f, mg/1
3. NHa as N, mg/1
4. NO3 as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
10. % volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
73.9
317.9
237.0
17.5
26.1
23.3
12.5
11.3
97.5
86.0
163.0
118.4
3004.4
36.3
12.0
0.3
227.2
14.1
157.3
12.3
2756.0
73.1
9C-2.7
6.8
7307.0
52.2
15.1
0.2
522.1
18.4
423.8
46.5
7310.9
73.8
1778.0
12.4
39.5
30.5
10.9
0.4
13.0
12.5
2.6
2.2
15.1
77.0
9.2
4.7
70.9
301.1
235.5
18.3
27.4
24.3
12.6
11.5
96.3
91.3
147.9
104.9
2009 . 1
46. 7
11.8
0.5
161.4
14.2
98.4
10.4
1935.4
75.5
772.3
8.2
6084.3
76.4
13.4
0.3
461.6
19.0
308.7
38.1
5543 . 6
75.4
1725.8
22.4
100.1
40.8
10.7
0.6
13.3
13.6
2.9
2.3
24.8
88.7
13.1
4.1
66.9
346.5
245 .,1
18. '6
28.4
24.7
12.2
11.1
106.0
84.6
158.4
107.0
1859.1
52.0
14.8
0.4
146.0
17.4
92.1
10.0
1597.1
75.1
647.5
7.8
6619.4
96.8
16.9
0.2
455.9
22.5
285.6
39.2
5624.3
72.4
1913.3
22.3
76.5
48.6
14.5
O.4
16.7
16.2
2.8
2.4
15.6
78.2
10.9
4.8
-------
HYPERION TEST NO.
Primary Effluent:
1. Water Temp. °F
2. ODD, uf, mg/.l
3. COD, f, mg/1
4.' NH3 as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, rag/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/.l
1O. % volatile
11. BOD5, uf, ing/1
12. BOD5, f, mg/1
Aerator Effluent:
1. COD, uf, mg/1
2. COD, f, mg/1
3. NHs as N, mg/1
4. N03 as N, mg/1
5. TKN, uf,.mg/l
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
1O. % volatile
11. EOD5, uf, mg/1
12. BOD5, f, mg/1
Return Sludge Stream:
1. COD, uf, mg/1
2. COD, f, mg/1
3. NH3 as N, mg/1
4. NO3 as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
10. % volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
Final Effluent:
1. COD, uf, mg/1
2. COD, f, mg/1
3. NH3 as N, mg/1
4. N03 as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
1O. % volatile
11. BODs, uf, mg/1
12. BOD5, f, mg/1
III-5
7
66.2
331.6
228.2
18.5
28.0
24.7
12.0
11.1
97.4
82.3
163.0
121.1
1298.2
75.3
15.3
0.2
99.2
18.5
35.4
12.4
105O.O
79.0
488.2
9.3
4254.5
108.5
16.6
0.1
337.4
23.4
101.2
31.6
3770.0
81.9
1690.0
31.8
97.5
49.8
14.4
0.2
17.2
16.6
8.2
7.5
19.0
86.4
13.5
4.6
8
GJ . 5
286.8
1«81.2
13.6
22.9
20.0
9.8
9.0
87.0
78.5
13O..O
94.2
1215.0
52.2
10.7
1.0
91.4
13.8
22.6
9.8
999.2
79.8
532.5
13.8
3872.5
86.5
12.3
0.2
280.4
18.4
47.6
15.9
3546.2
77.8
1605.0
24.2
56.6
43.3
10.0
0.9
13.0
12.0
8.1
7.5
17.0
75.0
11.2
5.2
9
64.o
349.8
217.0
16/5
25.8
21.3
10.4
9.2
109.0
71.7
.153.8
95.0
894.0
49.0
12.8
0.3
66.2
15.6
16.7
8.8
628.3
79.6
282.5
8.3
3876.0
89.0
14.2
0.1
243.2
20.4
38.0
10.9
2858.0
81.0
1315.0
28.0
66.0
45.0
12.7
0.2
16.2
14.7
8.8
8.2
17.3
79.6
17.2
5.2
-------
III-6
HYPERION TEST NO.
Primary Effluent:
1. Water Temp. °F
2. ODD, uf, mg/1
3. COD, f, mg/1
4. NH3 as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
10. % volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
Aerator Effluent:
1. COD, uf, mg/1
2. COD, f, mg/1
3. NH3 as N, mg/1
4. NO3 as N, mg/1
5.. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
1O. ?5 volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
Return Sludge Stream:
1. COD, uf, mg/1
2. COD, f, mg/1
3. NH3 as N, rug/1
4. NOa as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
g. SS, mg/1
10. % volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
Final Effluent:
1. COD, uf, mg/1
2. COD, f, mg/1
3. NH3 as N, mg/1
4. NO3 as N, mg/1
5. TKN, uf, mg/1
6. TKN, f, mg/1
7. P, uf, mg/1
8. P, f, mg/1
9. SS, mg/1
10. % volatile
11. BOD5, uf, mg/1
12. BOD5, f, mg/1
10
11
12
63.7
290.3
170.5
14.7
23.1
20.2
9.6
8.4
100.6
77.2
136.6
78.5
736.7
52.5
12.8
.4
61.0
15.8
13.6
8.1
57O.O
76.2
262.0
8.3
3629. O
105. 0
14.9
.1
238.8
22.5
28.5
10.4
29OO.O
80.3
1347.0
33.0
84.5
54.0
12.4
.3
16.5
14.8
8.2
7.7
28.9
77.5
18.7
4.0
67.7
318.1
209.2
16.8
25.4
22.0
10.4
9.5
97.1
79.8
151.1
101.3
1037.4
60.0
13.8
.2
79.7
16.4
16.4
8.8
706.8
80.3
298.3
7.4
4259.8
102.8
16.0
0.0
288.9
23.5
42.2
11.6
33O9 . 2
81.2
1438.8
35.1
76.2
46.6
13.2
.1
17.5
15.3
9.1
8.2
22.1
69.5
19.0
3.8
71.2
324.8
221.2
17."7
26.6
23.2
11.5
10.2
100.3
80.1
170.1
111.4
1933.0
53.8
14.1
.4
133.6
16.7
35.0
11.1
1485.5
80.3
606.7
9.4
6OO6 . O
101.7
16.1
.1
406.8
21.9
74.5
20.3
5O10.9
79.7
1911.0
32.8
58.3
44.3
14.5
.2
17.3
16.3
8.9
8.3
16.0
78.6
11.2
3.6
------- |