EPA-660/2-75-021
                                    JUNE  1975
OPTIMIZING A PETROCHEMICAL WASTE BIO-OXIDATION
            SYSTEM THROUGH  AUTOMATION
                   M.  A. Zeitoun
                  W.  F. Mcllhenny
                   N.  J. Biscan
                    J.  H. Gulp
                   H.  C. Behrens
              Grant No. S800  766
             Program Element  1BB036
             ROAP/Task No.  21  AZP-36
                    Project Officer

                     T. E. Short
      Robert S. Kerr Environmental Research Laboratory
          National  Environmental  Research  Center
                   Ada, Oklahoma 7^820
    NATIONAL ENVIRONMENTAL  RESEARCH CENTER
        OFFICE OF  RESEARCH &  DEVELOPMENT
      U. S. ENVIRONMENTAL  PROTECTION AGENCY
             CORVALLIS, OREGON  97330
           For sale by the Superintendent of Documents, U.S. Government
                Printing Office, Washington, D.C. 20402

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                         ABSTRACT

Instrumentation and control of an industrial, activated
sludge pilot plant was accomplished by development of
systems controlling the critical parameters of the
process to achieve reliable, high quality effluent.  Opti-
mization techniques based on the steady-state and transient
models of the activated sludge process were used to deter-
mine the minimum volume of the aeration basin required for
a specified effluent quality and to predict the transient
conditions as a result of step changes in loading.

A pH control system stopped plant operations for the dura-
tion of the upset, automatically restoring it when the feed
pH returned within operating limits.  An automated sampling
system, sampling feed and homogenized mixed liquor, monitored
the total carbon in both samples.  Nutrients, nitrogen and
phosphorus (N&P) were added in proportion to the total
carbon in the feed, thus maintaining low residual nutrients
in the effluent.  The sludge recycle flow rate was control-
led by a food to microorganisms (F/M) signal, measured as
the ratio of total carbon in the feed to that in the mixed
liquor.  Response time of the F/M control system to a step
increase in feed concentration was reduced by 50 to 70 per-
cent, as compared to the uncontrolled system, depending on
the amount of excess sludge available for recycle.  Chemical
flocculants were added in proportion to the turbidity of
the biosettler overflow, removing 85 to 98 percent of the
suspended solids.  Toxic or inhibitory effects of the feed
were measured by a Biological Inhibitor Detector, an instru-
ment which measures the oxygen uptake of standard solutions
before and after exposure of a bacteria sample to a feed
sample and calculates an activity ratio, that had an auto-
mated cycle of 60 minutes.  The use of the instrument as an
upstream sensing device was demonstrated as toxic substances
were added to the feed.
                             ii

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The developed on-line control systems are applicable to
municipal, industrial, or combined treatment plants.
Incorporation of control systems and predictive models in
future plants will greatly affect the optimum de-sign and
enable more efficient and economic operation.

This report was submitted in fulfillment of Grant S800 766,
by the Dow Chemical Company, Preeport, Texas, under the
partial sponsorship of the Environmental Protection Agency.
Work was completed as on July, 197^•
                            iii

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                          CONTENTS

                                                   Page
Sections
I      Conclusions                                  1

II     Recommendations                              5

III    Introduction                                 8

IV     Activated Sludge Miniplant                   14

V      Pood to Microorganisms (F/M) Control         29
       System

VI     Nutrients Addition Control System            16

VII    Chemical Flocculation Control System         84

VIII   Biological Inhibitor Detector                95

IX     Effluent Quality Monitoring and              138
       Instruments Evaluation

X      Process Design Considerations                148

XI     References                                   155

XII    List of Inventions                           160

XIII   Glossary                                     l6l

XIV    Appendices
                              iv

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                          FIGURES


No.                                                 Page

1      Activated Sludge Miniplant - Flow Diagram     11

2      Activated Sludge Control System               12

3      Activated Sludge Pilot Plant - Acid and pH    15
       Analyzer

4      Activated Sludge Pilot Plant - Total Carbon   16
       Analyzer for Nutrients Control and Sludge
       Recycle Control

5      Activated Sludge Pilot Plant - Flocculation   17
       Control and Effluent Quality Monitor

6      Activated Sludge Pilot Plant - Control Panel  18

7      Activated Sludge Pilot Plant - Plan View      19

8      Activated Sludge Pilot Plant - Side View      20

9      Influent Flow and pH Controls                 21

10     Activated Sludge Pilot Plant - Nutrients      30
       Control and F/M Control

11     F/M Control Sampling System                   32

12     Electrical Diagram of Aeration Controls       35

13     Nutrients and F/M Control - Block Diagram     37

14     Schematic of an Activated Sludge Process      41
       Completely Mixed Biological Reactor

15     Bio-Settler Steady-State Sludge Compaction    44
       Fresh Water Glycol Bacteria

16     Unsteady-State Variation of the Sludge        45
       Compaction Ratio

17     Sludge Growth Coefficients - Fresh Water      47
       Glycol Feed

18     Substrate Removal Coefficients - Fresh        48
       Water-Glycol Feed
                              v

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                    FIGURES (continued)
No.                                                 Page

19   F/M Blank Test - Bacteria Growth and F/M        51
     Response (Run A)

20   Relationship Between the Mixed Liquor           53
     Microorganisms, and Substrate Concentrations
     After a Step Increase in Loading - Blank Run
     A, Computer Simulation

21   Computed Initial Steady State for Run A         56

22a  F/M Control Test - Bacteria Growth and          57
     P/M Response, Run B

22b  F/M Control Test - Recycle and Waste            58
     Response, Run B

23a  F/M Control Test - Bacteria Growth and          59
     F/M Response, Run C

23b  F/M Control Test - Recycle and Waste            60
     Response, Run C

24a  F/M Control Test - Bacteria Growth and          62
     F/M Response, Run D

24b  F/M Control Test - Recycle and Waste            63
     Response, Run D

25a  F/M Control Test - Bacteria Growth and          64
     F/M Response, Run E

25b  F/M Control Test - Recycle and Waste            65
     Response, Run E

26   Sludge Settling as a Function of F/M            66
     (Grab Sample Data)

27   Sludge Settling as a Function of F/M            67
     (On-Line Control Data)

28   Response Characteristics With and Without       72
     F/M Control - Low Loading
                            vi

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                    FIGURES  (continued)
No.

29   Response Characteristics With and Without       73
     F/M Control - High Loading

30   Comparison of Aeration Basin Substrate          74
     Concentration With and Without F/M Control

31   Response Characteristics With and Without       75
     P/M Control (Salt Propylene Glycol System)

32   Response of Nutrients Control System            78

33   Ammonia Consumption by Microorganisms           80

34   Relationship Between Phosphorus and             81
     Ammonia Consumptions

35   Determination of Ammonia Requirement            83

36   Plocculation Controls                           85

37   Alum Flocculation Jar Tests                     88

38   Optimum Alum Dose as a Function of              89
     Initial Turbidity

39   Schematic of Oxygen Concentration During        103
     the Bio-Oxidation of a Degradable Carbon Source

40   Biological Inhibitor Detector - Schematic       109
     of Measurement Cycle with No Toxin in Feed

41   Biological Inhibitor Detector - Schematic       110
     of Measurement Cycle with Toxin in Feed

42   Effects of Inorganic Toxins on the Oxygen       112
     Uptake of Glycol-Acclimated Fresh Water Bacteria

43   Effects of Organic Toxins on the Oxygen         114
     Uptake of Glycol-Acclimated Fresh Water Bacteria

44   Biological Inhibitor Detector - Electronics     117
     and Read Outs

45   Biological Inhibitor Detector - Reactor         118
     and Sampling
                           vii

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                    FIGURES (continued)

No.                                                 Page

46   Biological Inhibitor Detector - Cam Time        119
     Program

47   Biological Inhibitor Detector - Schematic       120
     of Electrical Controls

48   Biological Inhibitor Detector - Signal          121
     Block Diagram

49   Effects of Inorganic Toxins on Activity         127
     of Glycol-Acclimated Fresh Water Bacteria

50   Effects of Inorganic Toxins on Activity         128
     of Glycol-Acclimated Salt Water Bacteria

51   Effects of Organic Toxins on Activity of        130
     Glycol-Acclimated Fresh Water Bacteria

52   Effects of Organic Toxins on Activity of        13i
     Glycol-Acclimated Salt Water Bacteria

53   Dynamic Toxicity Test A, Copper in Feed,        132
     6.6 mg/1

54   Dynamic Toxicity Test B, Copper in Feed,        133
     3.0 mg/1

55   Dynamic Toxicity Test B, Copper Accumulation    135
     in Aeration Basin Mixed Liquor

56   Reaction Order Kinetics of Copper Adsorption    137
     on Glycol-Salt Bacteria

57   Schematic of Effluent Quality Monitor           139

58   Precision Control Chart - TOD Analysis          l4l

59   Precision Control Chart - TC Analysis           144

60   Controlled Activity Sludge Treatment            149

61   Steady-State Design Relationships               153

62   Electrical Diagram of Automatic Shutdown        168
     System
                             viii

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                          TABLES


No.                                                 Page

1    Control Panel, Instrument Legend                24

2    Influent Plow and pH Controls, Instrument       25
     List

3    F/M Test Conditions                             54

4    Alum Flocculation System Performance,           92
     Glycol-Fresh Water System

5    Alum Flocculation System Performance,           93
     Glycol-Salt Water System

6    Exposure Time Effect of Inorganic Toxins        113
     on Glycol-Acclimated Fresh Water Bacteria

7    Exposure Time Effect of Organic Toxins          115
     on Glycol-Acclimated Fresh Water Bacteria

8    Legend for Signal Block Diagram for Figure 48   122

9    Dynamic Toxicity Test B - Material Balance on   134
     Copper (Basic 24 Hours)

10   Performance of the Total Oxygen Demand Analyzer 143

11   Performance of the Total Carbon Analyzer        145

12   Calculations of Plant Performance Data          17^
     Input Form

13   Computer Program for Calculations of            177
     Plant Performance

14   Summary of Plant Performance - Print Out        185

15   Transient-State Activated Sludge, Computer      191
     Program

16   Activated Sludge Transient Simulation -         195
     Print Out

17   Steady-State Activated Sludge Computer Program  198

18   Steady-State Activated Sludge Model - Print Out 200
                             ix

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                     ACKNOWLEDGEMENTS

The work reported was performed at the Texas Division of
The Dow Chemical Company, Freeport, Texas, by Dr.  M.  A.
Zeitoun, Project Director, N.  J. Biscan,  J. H. Gulp,
H. C. Behrens, W. D. Spears, and R. W. Murray.  W. F.
Mcllhenny was the Project Manager.

The project was partially supported by a  grant from the
Water Quality Office of the Environmental Protection
Agency.  Appreciation is expressed to the personnel of
Robert S. Kerr Environmental Research Laboratory,  Ada,
Oklahoma, and the Environmental Protection Agency,
Washington, DC, for their cooperation and assistance.

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                         SECTION I
                        CONCLUSIONS

An automated, activated sludge pilot plant was operated on
industrial waste to test previously developed control
systems in order to optimize the waste control process and
to produce a reliable effluent quality.  Both fresh water
and saline (8 to 10 percent NaCl) waste waters containing
glycol were examined as feeds to a completely mixed aera-
tion basin.

The following conclusions were drawn:

1.  Automation of an activated sludge system to the degree
    of sophistication expected of chemical systems control
    is practical and gives improved efficiency and relia-
    bility in operation.

2.  Automatic fail-safe operation of the plant was accomp-
    lished by the use of individual feedback control loops
    supervised by an overall shutdown system.  The pH
    control systems, which neutralized the feed within a
    preset pH control range, operated the feed control
    valve.  Upsets in the feed pH stopped the feed flow,
    all chemical additions, and sludge wastage for the
    duration of the upset only, automatically restoring
    operation when the feed pH returned within operating
    limits.

3.  A sampling system was devised to handle the continuous
    flow of the feed and take a batch sample from the di-
    luted and homogenized mixed liquor to be injected
    repetitively into a Total Carbon Analyzer.  Operation

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    of the automated (18-minute  cycle)  sampling  system was
    satisfactory except  for frequent  maintenance of the
    mechanical homogenizer.

4.  Nutrient addition proportional  to the  total  carbon in
    the feed was automated, exhibited a linear response,
    and performed reliably.  The nutrient  control system
    assured microbial viability  at  all  times,  and the
    concentrations of ammonia and phosphorus in  the effluent
    were maintained below 10 ppm and  2  ppm, respectively.

5.  On-line food to microorganism ratio (P/M)  control is
    Justifiable in activated sludge plants with  high yield
    coefficients where excess sludge  is available to in-
    crease the bacteria concentration in response to a
    step increase of organic concentration in  the feed.

    The organic loading, or F/M, was  measured  as the ratio
    of total carbon in the mixed liquor.  The  automated
    (F/M) signal proportionally  controlled the fraction of
    the recycle sludge to be wasted.

    For a fresh water feed, the  response time  of the F/M
    control system to a step change in  feed concentration
    was reduced by 65 to 70 percent as  compared  to
    the response time of the uncontrolled  system having
    fixed recycle and waste sludge  flow rates.

    For a highly saline waste water feed,  the  response time
    with F/M control was reduced by about  50 percent, but
    it was too long (33 hours) due  to the  low  yield of
    the halophilic bacteria resulting in much  less waste
    sludge available for additional recycle.

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6.  A Biological Inhibitor Detector was  built  and operated
    to monitor the toxic effects  of the  feed on the acti-
    vated sludge plant.   The automated measurement cycle
    (60 minutes) compared the oxygen uptake of two standard
    propylene glycol samples before and  after  the exposure
    of the bacteria to a feed sample.  Activity ratio as
    measured by the instrument had a precision of ±5
    percent of chart and the oxygen uptake measurement was
    linear for the range of 200 to 1,000 mg/1  of propylene
    glycol solutions.  Tests with toxic  substances added
    to the feed showed that the instrument can detect the
    presence of the toxin rapidly enough on a  repetitive
    basis to serve as an upstream sensing device in a feed-
    forward control system.

7.  A chemical flocculation control system, using a surface
    scatter turbidimeter, in a feed-forward mode of propor-
    tional control of the alum addition  resulted in a high
    quality effluent.  The system was stable,  removing 85
    to 98 percent of the suspended solids in the biosettler
    overflow and maintaining the  turbidity of  the final
    effluent below 3 Jackson Candle Units (JCU).

8.  Neither the Total Carbon Analyzer nor the  Total Oxygen
    Demand Analyzer used to monitor the  effluent quality
    were suitable for operation on highly saline samples.
    Better accuracy, more precision, and less  maintenance
    was experienced with the Total Carbon Analyzer.

9.  Computer programs were developed to  calculate plant
    performance and steady-state  and unsteady-state models
    of the activated sludge process.  The steady-state

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program was used to determine the  minimum volume of
the aeration basin required for a  specified treatment
efficiency at various recycle ratios and recycle sludge
concentrations.  The unsteady-state program predicted
the transient changes in bacteria  concentration, aeration
basin substrate concentration, and food to microorgan-
isms (F/M) ratio to step changes in loading.  The
results obtained by this transient model program agreed
well with the experimental results.

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                        SECTION II
                      RECOMMENDATIONS

The developed on-line control systems for the  activated
sludge process are applicable to sewage,  industrial,  or
combined treatment plants.   Based upon the operating
experience gained during this investigation, the  follow-
ing recommendations for further development of the  con-
trol systems and process design are  made:

1.  The nutrient addition and flocculation control  sys-
    tems could be modified to allow  for variations  in
    the feed flow rate by measuring  the flow and  changing
    the chemical addition by the multiple of flow times
    the measured control parameter.

2.  The feed-forward inhibition control system is necessary
    to maintain the viability of the acclimated  culture
    and the high performance of the  process.   This  system
    is comprised of an upstream biological activity sensing
    device, an equalization basin, a diversion basin, and
    pretreatment facilities.  The developed Biological
    Inhibitor Detector should be tested under  varying
    operating conditions as the upstream  sensing  device.
    The equalization basin, in addition to dampening  the
    fluctuations in substrate concentration in the  influent,
    provides a time delay together with dilution  of a
    possibly toxic feed during the biological  activity
    analysis period.  A diversion basin serves as a holding
    reservoir of a toxic influent as detected  by  the
    Biological Inhibitor Detector and diverted by a control
    valve or manually as an alarm system  is actuated.  After
    determination of the chemical nature  of the toxin, it

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    could be bled back Into the  process  or pretreated  by
    sorption to remove toxic organics, chelation  of  toxic
    metal ions, or other indicated process.

3.   The food to microorganisms  (F/M)  control  system, to
    maintain a constant loading  of the activated  sludge
    plant, could be modified to  include  flow  measurement.
    The control system should include an aerated  stabil-
    ization tank to supply  additional sludge  recycle in
    periods of high loading.  A  pilot-plant study of this
    concept to determine the best  location of the excess
    sludge tank is recommended.  For  equal-sized  stabili-
    zation tanks, the one located  in  the recycle  line
    would give shorter hydraulic residence time,  indicating
    a higher biota viability while the one located in  the
    sludge waste line would produce a more stabilized
    sludge, possibly improving the bio-flocculation  charac-
    teristics .

4.   Sampling the influent as it  enters the aeration  basin
    allows easy proportional control  of  the F/M ratio.
    It is recommended that  the sampling  of the influent
    before the equalization basin  be  studied  and  that  a
    minicomputer be included and programmed to calcuate
    the hydraulic effect of the  equalization  on the  feed
    flow and composition and the F/M  control  system. This
    could improve the F/M response time, increasing  the
    sludge recycle rate before the higher loadings affect
    the aerated biomass.

5-   Future plant design procedures will  have  to incorporate
    both control systems and predictive  mathematical models,
    These greatly affect the optimum  design and enable more
    efficient and economic  operation.

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6.   There is a need to improve the instruments  available
    to monitor organic concentrations.   More  reliable
    operation and reduced maintenance requirements  should
    be the goal,  especially when handling highly  saline
    waste water streams.

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                        SECTION III
                       INTRODUCTION

Aerobic microbial suspensions are used for the removal of a
large variety of soluble organic matter from petrochemical
waste waters.  Such suspensions may consist of dispersed
growths as in aerated lagoons or flocculated suspensions
of microorganisms, at relatively high concentration, as in
the activated sludge process.  The activated sludge process
is more amenable to control than the aerated lagoon system.
The emphasis on control and optimization to produce a reliable
effluent quality will continue to make the activated sludge
process the principal method of waste water treatment.

For the optimization of the activated sludge process, it is
necessary to adjust a number of parameters that are inter-
acting both independently and dependently.  The rate-deter-
mining steps of the process are:  the dissolution of oxygen
from the air into the waste liquid, the mass transfer of
nutrients from the substrate, and dissolved oxygen to the
bacterial cell surface, and the respiration and metabolism
of the aerobic bacterial cells.  The aggregation or floccula-
tion of the individual microorganisms into matrices to
achieve solid-liquid separation could be a controlling param-
eter for such applications as municipal sewage and food
industry waste water.

The metabolic reaction rate has been shown to be controlling
for petrochemical waste water treatment (Eckenfelder, 1970).
Once suitable conditions of pH, temperature, nutrients,
oxygen supply and adequate mixing are supplied, kinetic
reactions within the system proceed at rates defined by the

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nature of the organic matter in the waste water and the
activity of the biomass.  The controlling parameter of the
activated sludge process has always been recognized as the
enzymatic activity of the biomass.  The success or failure
of the activated sludge process is dependent on the
control of the food to microorganisms ratio (F/M) and the
absence of inhibitors or toxins that retard or destroy the
action of the biota.

The controlling parameters of the activated sludge process
are well understood.  The question is how shall we measure
and control these parameters.  The common practice of monitor-
ing plant operations with random daily or weekly analysis
is inaccurate and clearly inappropriate for control and opti-
mization.  Parameters to control the process must be measured
on a continuous basis or must be obtained rapidly enough on
a repetitive basis to provide updated data for use within
the time constant constraints of the process.  A real-time
response could be achieved when the analytical response time
is much less than the unit step detention time.

Valid computer modeling of the activated sludge process
exists (Smith and Eilers, 1969).  Hardware is available to
perform feedback, feed forward, adaptive and optimizing
control, in analog or digital execution or a combination
thereof.

The problems of automated control of activated sludge
plants lie in selecting parameters and developing sensors
for these parameters rather than in the analysis and presen-
tation of the accumulated data.

The objective of the reported study was to develop instru-
mentation to control an industrial activated sludge plant

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with the same degree of instrument sophistication that
controls a continuously operating chemical process.   For
this purpose, an existing,  skid-mounted minlplant was
utilized.  A simplified flow diagram of the plant is shown
in Figure 1.  This plant was successfully operated to
process a high salt (8 to 10 percent) industrial waste
containing polyhydric organics (sucn as glycol and glycerine),
extending the activated sludge process into salt concen-
trations not previously believed possible (Zeitoun,  et al.
1971).  Chemical flocculation following the bio-settler was
necessary to remove the turbidity produced by the halophilic
bacteria and was considered part of the process.

Control of the feed pH and manual control of the air supply
to the aeration basin were features of the existing plant.
The specific control systems developed during the reported
study are illustrated schematically in Figure 2 and include:

1.  Nutrients Addition Control
    Control of the nutrients addition by sensing the carbon
    in the feed and adding the nutrients in a ratio to the
    measured carbon was proposed.  The carbon in the feed was
    to be measured with an organic carbon analyzer.   The
    nutrient solution, containing fixed and known amounts
    of nitrogen and phosphorus, was to be added in a ratio
    to insure the bacterial viability and to regulate the
    amount of residual nitrogen and phosphorus in the
    effluent, improving both the quality of the effluent
    and the process economics.

2.  Food to Microorganisms (F/M) Ratio Control
    A real-time measure of the loading ratio would allow
    control of the biomass in the aeration basin and the
                            1C

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    amount of sludge to be wasted and returned to the
    process.  It was proposed to measure the concentra-
    tion of the bacteria in the overflow from the aeration
    basin and the concentration of substrate in the feed
    by a total carbon analyzer.  The measured values,
    as organic or total carbon, would be transmitted to a
    differential controller.   The output of the controller
    would actuate a control valve on the sludge return line
    to keep a constant loading ratio.

3-  Flocculation Control
    A measurement of turbidity in the effluent was proposed
    to control the amount of alum fed to the flocculator.
    The pH in the flocculator would be controlled by the
    addition of sodium hydroxide solution at a level cor-
    responding to the optimum pH for alum flocculation.

4.  Biological Inhibitor Detector
    An upstream sensing device was proposed to detect toxic
    loads in the feed in a feed-forward control system.  The
    sensing device, a respirometer or a biological reactor
    would measure the rate of the biological reaction of
    the acclimated culture and the feed at regular inter-
    vals.  When the presence of a toxin was sensed, it
    would either divert the toxic feed to a holding pond or
    actuate an alarm system.

It was also proposed to apply a total oxygen demand instru-
ment to monitor the effluent quality and to assess the per-
formance of the plant.  The evaluation of the automatic
control in increasing the plant efficiency to obtain reliable
high quality effluent would be made utilizing a simplified
mathematical model of the activated sludge bio-oxidation
process.
                            13

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                        SECTION IV
                ACTIVATED SLUDGE MINIPLANT

The activated sludge miniplant, designed,  constructed, and
built under Grant No. 12020 EEQ, similar to that described
by Mulbarger (1966), was designed for an average flow rate
of 0.5 gallons per minute.  This miniplant was  successfully
operated for more than a year on an equalized propylene
glycol waste water that contained a high salt concentration
(8 to 10 percent NaCl).  The results of this testing and
a description of the plant are contained in the Final Report
submitted in the previous grant (Dow, 1970). The operational
and design parameters determined from the  miniplant  operation
were verified in a 150-gallons-per-minute  pilot plant utiliz-
ing commercial size equipment.

For the present study, the existing plant  was renovated,
new electrical circuits for the instrumentation were added,
and the existing circuits modified for outdoor  operation.

PLANT DESCRIPTION
The skid-mounted miniplant was connected to an  equalization
tank and a cooling tower (if necessary).  Details of the
unit may be seen in Figures 3 through 9.  The major  components
of the plant, mounted on the skid are:

1.  An acid tank, feeding into the suction line of the recycle
    pump through a pH-controlled automatic valve (Figure 3)-

2.  A nutrient solution tank supplying nutrients to  the
    aeration basin through a metering pump.

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                                   21

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3.  A 280-gallon aerator tank (Figure 4)  made of Plexiglas
    with six removable partitions was operable as a plug
    flow reactor or a completely mixed tank.   Diffused air
    was introduced into seven points in the bottom of the
    tank and controlled by needle valves  at the  airflow
    rotameters.

4.  Two 50-gallon Plexiglas settlers, each with an adjust-
    able overflow weir and airlift or pump to remove the
    settled solids from the bottom.   The  bio-floe from the
    first settling tank was recycled to the aeration tank
    and part of  the flow wasted as excess sludge.  A
    Total Carbon Analyzer (Figure 4) measured the total
    carbon of the feed and the mixed liquor from the aera-
    tion basin.

5.  A flocculator consisting of a 10-gallon glass battery
    jar with a stirrer fed alum and caustic through con-
    trol valves  and placed between the two settling tanks
    (Figure 5).

6.  A Total Oxygen Demand Analyzer to monitor the total
    oxygen demand (TOD) of the influent and effluent before
    and after chemical flocculation.  The TOD analyzer was
    equipped with a five stream selector and sampling
    filters and  pumps.

7.  The control  panel (Figure 6) included instruments to
    indicate the major measured parameters of the process.
    The influent pH and its flow rate were chart recorded.
    The influent flow rate was set manually at the control
    board.  The  sludge recycle was recorded and was man-
    ually controllable at the board.  The alum flow rate
    and the turbidity of the final effluent were both
                             22

-------
    recorded and the flow of the alum solution was control-
    led at the board.  The pH of the final effluent was both
    recorded and indicated.

A plan view and a side view of the miniplant are shown in
Figures 7 and 8, respectively.  The control panel instru-
ment legend is described in Table 1.

The influent pH control system was designed for fast response
in a well mixed system.  By coupling the pH feedback loop
around the recycle feed pump, the loop capacity, mixing time
and measurement lags were kept to a minimum.  The pump also
served as the feed pump to the aeration tank and provided
the feed at the proper pH independent of the volume and pH
of the influent in the equalization tank.  The influent flow
and pH controls are shown in Figure 9 with the instrument
list given in Table 2.

The pH measurement was made with a glass electrode and a
solid-state reference electrode fitted in a polypropylene
holder of the flow-through type.  The electrodes were
easily removable for calibration in buffer solutions.  The
control system was composed of a Bell and Howell solid-state
pH-to-air converter, a Foxboro pneumatic recording control-
ler, and an Annin control valve with a special Kynar body
and trim and a flow coefficient (Cv) of 0.1 with linear
characteristic.  The sample flow taken from the pump dis-
charge passed through a ball valve that throttled the
sample flow so it was large enough for good mixing at the
acid injection point without subjecting the pH electrodes
to the excessive pressure of the pump discharge.  The
velocity distance lag time of the pH control system was
about two seconds.
                             23

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      Table 1.   CONTROL  PANEL,  INSTRUMENT  LEGEND
   Legend
         Description
P-l
P-2
pHRC-1
FIC-1
AIC-1
RRC-1
pHRC-2
AIC-2
AT-2
pHE-1
pHT-1
FV-1
FR-1
AR-1
AR-2
TOD
TCA
influent recycle pump
nutrients proportioning pump
influent pH control
influent flow control
nutrients flow control
sludge recycle control
effluent pH control
alum dosage control
turbidity transmitter
influent pH electrodes
influent pH transmitter
influent flow control valve
second pen of pHRC-1
second pen of pHRC-2
second pen of RRC-1
Total Oxygen Demand Analyzer
Total Carbon Analyzer

-------
Table 2.  INFLUENT FLOW AND pH CONTROLS, INSTRUMENT LIST
Tag No.
PT-l
FC-1
FV-1
FR-1
FI-1
PI-1
PLS-1
pHT-1
pHC-1
pHR-1
pHV-1
pHHS-1
pHLS-1
SV-F,
SV-pH-1
Description
Foxboro M13AM-MS 2, 0.159
I/O
Moore Products M 55A
Annin M1560, 3/4" NPT
(second pen of pHR-1)
Brooks, PVC body
Ashcroft 1279-S
Static-0-Ring #12N-K45
Bell & Howell Type 18-155
(integral to pHR-1)
Foxboro M 40R-A4-2
Annin Domotor w/Kynar body
and trim
Static-0-Ring #12N-K45
Static-0-Ring #12N-K45
Skinner 3-way solenoid valve
#V53 LB 2100, 1/4" NPT,
115V coil
Range
0-84" w.e.
0-1 GPM
Cv = .6
0-1 GPM

30"-0-30 PSI
0-16 PSI
2-12 pH
2-12 pH
2-12 pH
Cv = .1
0-16 PSI
0-16 PSI

Set Point

.5 GPM




4 PSI

7.7


pH 8.5
pH 6.5


-------
The pH control system had a high and low limit switch
that closed the feed valve if the pH got out of control
and opened the feed control valve as the control range
was regained.  The control points were set at any pH
limit for automatic control.

The influent flow rate to the aeration basin was controlled
with an integral orifice d/p transmitter providing the
flow measurement that was recorded on the second pen of the
pH recorder.

PLANT OPERATION
Automatic operation of the plant was accomplished with a
number of individual feedback control loops supervised by
an overall shutdown system.  Each individual control loop
functioned in its prescribed manner as long  as  the feed
stream pressure and pH were maintained.  The electrical
schematic of the shutdown system is given in Appendix A.

Operation of the process was initiated by a pushbutton to
start the feed pressure pump.  A short duration time-delay
relay allowed time for pump priming.  Once the feed pressure
was sufficient, the pH control system automatically added
acid to bring the feed pH within the control limits.  This
was automatically followed by the influent flow control
that throttled the feed to the aeration basin at the set
value.  All forward flows from the aerator and the subse-
quent equipment were regulated by gravity heads.

The loss of feed pressure caused all chemical additions and
sludge wastage to stop until the system was manually reset.
An upset in the feed pH stopped the same operations but
only for the duration of the upset.  Operation was automatical-
ly restored when the feed pH returned to operating limits.
                            26

-------
A pH bypass switch was provided to inhibit automatic shut-
down during periods of attended testing.  Two time-delay
relays protected this automatic shutdown system from false
operation due to electrical transients.

Inidividual feedback control loops were arranged for fail-
safe operation.  In case of power loss or air supply within
a loop, the control element closed.

Details of the start-up procedures, routine maintenance of
the instruments and controls systems, and the sampling
schedule during operation of the plant are given in Appendix
A.

CALCULATIONS OP PLANT PERFORMANCE
A computer program was developed to facilitate routine data
handling and to calculate parameters which described the
miniplant performance.  The output from the program aided
evaluation of the proposed control systems and operational
decision making.  The details for the program are presented
in Appendix B.

Data entered into the program represent daily averaged
values.  Included were Total Oxygen Demand (TOD), Total
Carbon (TC), Mixed Liquor Volatile Suspended Solids (MLVSS),
turbidity, temperature, pH, and flow data.

The height of waste sludge accumulated in a receiving barrel
was entered and converted into an average waste flow rate.
A 2^1-hour average recycle flow rate was calculated from flow
data from a one-minute grab sample of both waste and recycle,
The sum of the waste and recycle flow was a constant, and it
was necessary to calculate this flow since the individual
                            27

-------
recycle and waste flows were not constant because of the
F/M control action.

Among the data tabulated by the program were TOD removal
and the formulation of volatile suspended solids.  A micro-
organism balance on the aeration basin allowed calculation
of the specific substrate removal and the specific growth
rate parameters, which are necessary for the generation
of kinetic constants (see Section VI).

Carbon and oxygen material balances were also provided by
the program.  Insertion of program logic to evaluate oxygen
transfer efficiency was optional.

The mean cell residence time, commonly called the sludge
age, was a useful operational parameter.  It was calculated
on a daily basis as the average microbial mass (as MLVSS)
in the aeration basin divided by the total mass flow of
wasted microorganisms and biota lost through the bio-settler
overflow.

The program out put included calculation of the sludge volume
index (SVI) based on the measured, 30-minute, mixed liquor
settling time in a 1,000-ml graduated cylinder.

The performance of the control systems, presented in terms
of daily averaged values, included calculation of carbon-to-
nitrogen-to-phosphorus ratios for the nutrients control
system, alum usage for the flocculation control system, and
loadings for the F/M control system.
                            28

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                         SECTION V
        FOOD TO MICROORGANISMS (F/M) CONTROL SYSTEM

The most important parameter in optimum control of the
activated sludge process is the loading ratio, or the
food to microorganisms ratio.  Good F/M control will result
in a high quality effluent and a sludge with good settling
properties.

For a given hydraulic loading, F/M is determined by the
ratio of the concentrations of the feed stream and the
aerated bio-mass.  The method used in the pilot plant was
to make on-line total carbon analysis of each of the two
streams, convert these to stored values, and adjust the
recycle flow to the aeration basin by proportional F/M
control.

SYSTEM DESIGN
The food to microorganisms control system is shown schemat-
ically in Figure 10, together with the nutrients addition
control system.

An Ionics Model 1212 Total Carbon Analyzer was used to
analyze the feed and the mixed liquor samples.  Sample in-
jection was provided through a slide valve with a 40-
microliter sample volume alternated with a 100-microliter
distilled water wash.  A MSA Model 300 IR unit, sensitized
for carbon dioxide, was the sensor portion of the analyzer.
The recorder housed the analyzer time controls and the com-
busion tube controls.  The automatic zero circuitry was added
to the rear of the infra-red unit housing.

The analysis-cycle time was set by the speed of the program
cam timer which controlled the operation of the sample
                            29

-------
                  o
3C

-------
injection valve and the auto-zero circuitry.  Added to
this time was the control necessary to synchronize the
peak picker, peak transfer, and peak picker reset circuitry
with the analysis signal.  Also added to the timer was the
sample stream transfer controls.

Sample Handling System
The sample handling system of the Ionics Model 1212 Total
Carbon Analyzer was modified to accomodate two sample
streams, a continuous flow and a batch sample.  The filtra-
tion and bypass components of the original analyzer were
removed (Figure 11).

A continuous sample of feed passed through a 3-niicron Cuno
filter, through a valved rotameter, and through a two-way
manually-opened solenoid valve (A).  It then passed through
the Total Carbon Analyzer (TCA) sample injection slide
valve to a special three-way solenoid valve (B) and on to
drain.  The feed sample was blocked from three-way solenoid
valve (C).

The mixed liquor typically contained from 1,000 to 5,000 mil-
ligrams per liter of suspended bio-solids, whose random floe
size was too large to obtain a reproducible aliquot of the
40-microliter size needed for analysis.  Hence, homogeniza-
tion of a larger aliquot was performed in order to obtain a
representative sample.  A Virtis 45 homogenizer was used,
operating at about 10,000 rpm.

A 1:1 dilution of the mixed liquor sample aided in the homog-
enization step.  Two timers operated sequentially to first
operate pumps providing the aliquot and next operate the
                            31

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homogenizer.  Upon completion of the homogenization time,
another sample pump emptied the homogenizer contents Into
the stand-pipe above solenoid (B), which allowed deaeration
of the sample before analysis.  All three solenoid valves
were energized at that moment:  two-way solenoid valve (A)
was closed, and the drain connections of valves (B) and (C)
were closed.  The homogenized sample passing through the
stand-pipe above valve (B) flowed by gravity through the
sample injection slide valve and into the stand-pipe above
solenoid valve (C) until the stand-pipe levels approached
equilibrium.  Flow in this direction flushed the prior
feed sample from the injection valve.

Upon injection of the homogenized sample, all of the solenoid
valves were de-energized, restoring the flov; of the continuous
feed sample stream through the system.   Meanwhile, the batch
sample in both stand-pipes was drained.

Energizing the solenoid valves from a power source outside
the automatic stream-swtiching controls permitted the addi-
tion of a standard solution to the stand-pipes for calibra-
tion of the instrument.

Peak Picker and Signal Memory
The signal to the recorder of the Total Carbon Analyzer was
0 to 5 millivolts.  By adding a retransmitting slidewire
inside the recorder, a signal range of 0 to 5 volts was
obtained.  The simplest form of peak picker consisted of
a single diode and capacitor.  The charge on the capacitor
was proportional to the height of the peak signal applied.
Quick transfer of this charge to a sample and hold amplifier
provided storage of that signal value for extensive periods
of time.  Following transfer of the charge, a relay was
energized to discharge the capacitor, preparing it for the
                           33

-------
next peak to be applied.  To provide a high impedance
connection between the capacitor and the sample and hold
amplifier, a glass-encased Form A reed relay and high
voltage wiring were used.   To provide the separate stor-
age of two analyses, two sets of reed relays and sample
and hold amplifiers were used.

Selection of the proper anlaysis signal storage must be
synchronized with the last sample injected into the analyzer.
During automatic switching from one stream to the other,
selection of the correct reea relay was made through con-
tacts on the same relay that was next to be analyzed.  This
was accomplished through the use of a double-pole double-
throw ratchet relay (which reverses the sense of the relay
contacts only upon energizing).   If single stream operation
was desired, the sense of the reed relay selection contacts
were reverse and further operation of the ratchet relay
inhibited.  This was accomplished through a triple-pole
double-throw switch that opened the ratchet relay coil cir-
cuit as it reversed the reed relay coil circuits.  An
electrical schematic of the controls is shown in Figure 12.

The three-position toggle switch located on the side of
the peak picker and memory control enclosure provided three
modes of sample injection sequence.  Two indicator lights,
identified as stream 1 and 2, displayed which stream was
next to be analyzed.  Stream 1 was the feed stream; stream
2 was the homogenized aerator sample.  When the switch was
in the AUTOMATIC position, the controls caused alternate
injection and memory of the two samples.  In the MANUAL
position, only the feed stream was analyzed with its assoc-
iated memory updated.  In the STANDARD position, the memory
update function was inhibited so that analyzer calibration
procedures did not affect the stored analysis values for the
two streams.

-------
F/M Signal Conversion and Control
A block diagram of the food to microorganisms ratio control
equipment is shown in Figure 13 (the nutrients control
is also included in this diagram).

The output of each sample and hold  amplifier was converted
to a 1- to 5-ma. signal and then to a 3- to 15-psi pneumatic
signal.  Since the biota sample had been diluted 1:1, the
value of that signal was multiplied by two before division
into the signal for the food.  The  quotient of. the pneumatic
divider was the F/M ratio with a 0  to 1 range.  This signal
was fed to a pneumatic recorder-controller.  The controller
adjusted an output pneumatic signal proportional to the
offset between the desired and actual F/M value.  This
output signal controlled tne percent energized time of
a 60-second-cycle timer. The energized circuit operated a
one-half inch NPT normally closed solenoid valve that allowed
flow of the bio-settler underflow stream to waste.  This
stream was pumped at constant flow  and was normally re-
cycled to the aeration basin inlet.

The system also included a high signal selector and regulator
that can be set to designate a maximum waste flow rate
independent of the F/M controller.   This safety device pre-
vented cell washout in case of control system failure.

THEORETICAL BACKGROUND AND BASIS FOR UNSTEADY-STATE
COMPUTER SIMULATION
Unsteady-state material balances coupled with reaction
kinetics were the basis for the development of a computer
simulation of biological growth, substrate removal, and
the F/M control system dynamics.
                            36

-------
 Figure  13.   Nutrients  and  F/M  control—block diagram
Infl uent
Sample Stream
1

Total
Carbon
Analyzer
1 A
i i



Mixed Liquor
Sample Stream

i
Stream
Select
Valve
4
i
»-


1:
Dilu
i
1
tion

Homogenizer

      TCA
   Recorder
  Programmer
rn- ^_ ^^ __ ^^
           Stream
          Selector
         Peak Picker
                                            ±18 V PWR SUP
                             Sample & Hold
                               Amp!ifiers
        r
   MA-to-Air
   Converter
        Mul tip! ier
                             MA-to-Air
                             Converter
                        Di vi der
                                RRC-1
                            (Recycle  Ratio)
Air-to-% Recy .
   Converter
    Nutri ents
  Flow Control
                  f
                          Power
                          Relays
„.	j
                                                 1
                            Air-to-% Recy
                               Converter
                            Recycle Sludge
                             Flow  Control
                       —  Sample Stream
                          Electrical Signal
                          Pneumatic Signal
                         37

-------
Growth and Substrate Utilization Kinetics
The basic emperically developed kinetic relationship
generally used to describe the growth rate of micro-
organisms in a biological oxidation system is:
               §
where X  = concentration of microorganisms (mass/volume)
      j V
      -jr- = net growth rate of microorganisms (mass/volume-
           time)

      Y  = growth yield coefficient (mass of microorganisms
           produced/mass of substrate utilized)
      -TT- = rate of substrate utilization (mass/volume-time)

      k(j = microorganism decay coefficient (time"1)
Another emperical relationship, similar to that developed
by Monod (19^9)» can be used to describe the rate of sub-
strate utilization by microorganisms:
               dF  _  kXSj
               dt     K+S
where k  = maximum rate of substrate utilization per unit
           weight of microorganisms (time"1)
      Ks = half velocity coefficient, equal to the sub-
           strate concentration when (dF/dt)/X = (l/2)k
           (mass/volume)
      Si = concentration of substrate surrounding the micro-
           organisms (only that portion of the waste which
           is soluble and biodegradable) (mass/volume)
                            38

-------
Division of both sides of Equation (2)  by X gives
             dF/dt  _
               X
Hence, the removal of substrate per unit mass of micro
organisms on a finite time basis defined as (F/M)r is
given by.*
                                 (p/M)
where Xavg is the average biota concentration present in
the aeration basin during the chosen time interval.

The process loading ratio (F/M) is defined in terms  of
the efficiency of removal as:

             F/M   =  (F/M)r  x  100                   (5)
                         Jti

where E   = 100 (So-S^/So (percent efficiency)
      S0  = influent waste concentration (soluble substrate)
            (mass/volume)
Equations (4) and (5) implicitly illustrate an advantage of
F/M control.  If F/M is held constant for a designated
treatment efficiency, then the removal per unit mass (F/M)r,
is fixed.  By Equation (4), constant (F/M)r implied a con-
stant effluent soluble waste concentration, Si, since k and
Ks are constants.  In other words, if the amount of substrate
available to a unit mass of microorganisms remains constant
then the degradation by the biota is fixed.

Another parameter commonly calculated in the activated sludge
treatment is the sludge age.  Writing Equation (1) on a
                            39

-------
finite time basis after division by X yields

                           =  y(p/M)  _ k
                                    i    u
where y is the net specific growth rate of microorganisms.
The reciprocal of y is what is termed as the sludge age,
or mean cell residence time and is inversely proportional
to F/M.

Unsteady-State Modeling of the Activated Sludge Process
The Monod kinetic equations can be incorporated into
substrate and microorganism material balances around the
aeration basin (Figure 14) and provide a basis for mathe-
matical modeling of the activated sludge process.  The sub-
strate material balance is«
      QS0 + RSi  -  (Q+R)S1 -        =  V   i          (7)
or     Q(s..Sl)  .
and the microorganism material balance ist

             RX  + V (P^- - kdX)  -  (Q+R)X
               1      ^"r'-:)
                                                       (9)
where Q  = influent waste flow (volume/time)
      R  = recycle sludge flow (volume/time)
      W  = waste sludge flow (volume/time)
      V  = aeration basin (volume)
      Xr = bio-settler underflow sludge concentration
           (mass/volume)

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Implicit for this model is the assumption of complete
mixing in the aeration tank.  The model is conservative
in that substrate degradation is assumed to occur only
in the aerated reactor.

The scheme of F/M proportional control can easily be in-
serted into the activated sludge model.  The waste flow
is varied with F/M by:

              W  =  A(P/M) + B ,  0£¥
-------
where n is defined as the efficiency of settler operation.
This equation can be derived from a steady-state material
balance around the bio-settler, assuming that a negligible
mass of microorganisms leaves through the clarifier over-
flow (n = 100 percent).

Figure 15 shows the fit  of Equation (13) for steady-state
miniplant data, indicating a settling efficiency of 97
percent.

There were obvious limitations in using a constant ratio
to describe the non-steady-state performance of a biological
settler.  However, no better general model could be found
and this relationship was able to adequately allow predictions
of unsteady-state bacteria concentrations in the aeration
basin.   Figure 17 shows  that the sludge compaction ratio did
remain relatively constant during unsteady-state miniplant
operation.

It should be pointed out that having a constant sludge com-
paction ratio was specific for a particular settler geometry
and system.  This consideration was particularly important
in  scale-up design.  Tracey and Keinatch (1973) present a
dynamic model based on gravitational and bulk flow consid-
erations which does not  indicate a constant sludge compac-
tion ratio.  Their model predicts an increase in sludge
blanket height but no change in sludge underflow concentra-
tion for an increased solids input.

KINETIC CONSTANTS FOR PROPYLENE GLYCOL ACCLIMATED BIOTA
The four kinetic constants represented in Equations (1) and
(2) were determined from miniplant TOD and MLVSS data.  The
data were retrieved from aeration basin temperature at 30
±3° C.

-------
Figure 15.   Bio-settler steady-state compaction
            fresh water glycol  bacteria
Sludge
Compacti on
Ratio,
           5,Or
           3,0
           2,0
           1,0
           0,0
                       I
            Slope = 0.97
                 I
0,0     1,0    2,0     3,0     4,0

    Biosettler  Inflow           Q+R
    to  Underflow  Ratio,         R+W
                                                     5,0

-------
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The analysis for TOD feed data was done on a sample which
had been passed through a 3.0-micron filter.  TOD bio-
settler overflow data was used as the representation of
soluble substrate in the aeration basin, Si, and a sample
which had been passed through a 25-micron filter was
analyzed.

Figure 17 shows the determination of the sludge growth
coefficients for the fresh water propylene glycol biota.
The slope of the line is the yield coefficient (Y = 0.21
gm VSS formed/gm TOD removed) and the ordinate intercept
is the decay or endogenous coefficient (k
-------
   Figure  17.   Sludge  growth coefficients	
                fresh water-glycol. feed
CO
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                                        gm TODr

                                      = 0.06 day1
                         2,0
3,0
4,0
        Gms. TOD Removed  per  Day per Gm. MLVSS

                        (F/M)r

-------
   Figure 18.   Substrate  removal  coefficients	
               fresh water-glycol  feed
Specific
Substrate
Uti1ization,

(F/M)r


gm TODr/Day
gm MLVSS
5,0

4,0

3,0

2,0

1,0
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k  * 5.0 day1
Ks » 117 mg/1  TOD
  100
600
      1
    (F/MTr
              0,6
              0,5
0,1
              0,3
              0,2
                       i Substrate Concentration,
                             TOD, mg/1
                   0    25    50    75    100    125
                           x

-------
The kinetic constants were determined from data of a pre-
vious study on the treatment of the brine propylene glycol
waste water (Zeitoun, 197D as kf  = 0.0132 (mg/1 TOD)-1day-1,
Y = 0.1-3 gm VSS formed/gm TOD removed,  and kd = 0.02 day-1.

There has been much discussion in  the literature on the
limitations of using the Monod type kinetic equations to
describe the dynamics of cell growth and substrate removal
in a continuous flow biological oxidation system.   Assump-
tions of a constant yield and decay coefficient have been
criticized (Chiu, Fan, Kao and Erickson, 1972; Storer and
Gaudy, 1969; McLellan and Busch, 1969) and it has  been
suggested that Ks be considered dependent upon the degree
of mixing (Kornegay and Andrews, 1970).   Changes in viability
and physiological activity of the  microorganisms relate to
the difficulty in obtaining descriptive  kinetic coefficients.
However, a degree of success can be anticipated in using
this model to simulate the dynamics of the propylene glycol-
activated sludge miniplant because of four basic reasons:

1.  The Monod model was originally developed to describe
    behavior of pure cultures.  It was found that about
    80 percent of the microorganisms present in the fresh
    water glycol system were the one bacteria species,
    Pseudomonas.  No more than two to four different
    bacteria are present in the brine-activates sludge
    and about 90 percent are one bacterium (Zeitoun, et
    al. 1971).

2.  Si was in terms of a single, soluble substrate,
    propylene glycol.

3.  The carbon energy source was rate limiting.  Otherwise
    deficient nutrients were added by the nutrient control
    system.

-------
4.  The pH and temperature were regulated for the opti-
    mum rate of biological growth.

TESTING OP THE F/M CONTROL SYSTEM
In general, the miniplant test runs were started with the
F/M controller set on manual, i.e., constant recycle and
sludge waste flow rates were set.  The system was allowed
to approach a steady-state condition in terms of reactor
microorganism concentration, substrate removal efficiency,
and bio-settler characteristics such as sludge concentration
and sludge blanket height.  The system was then put on
automatic control and a step increase in the concentration
of the feed was made by adding an aliquote of industrial
grade propylene glycol to the equalization tank.   The
aeration basin temperature was held constant during each run.

An automatic, total carbon analysis was made every six
minutes during these runs, with alternate analysis of feed
sample and homogenized mixed liquor sample.  To reduce the
volume of data, each F and M concentration plotted in
this section is represented as the average of five total
carbon analyses.   Waste, recycle, and F/M data are also
hourly averaged values.

A blank F/M test in which no control was effected, that is,
the recycle and waste flow rates were kept constant through-
out the test, showed the dynamics of cell growth under
continuous flow conditions and was used as a basis for com-
parison for F/M control test system responses.

Fresh Water Propylene Glycol System
Figure 19 shows the mixed liquor and F/M response to a
47-percent increase in loading from Blank Run A.   The solid
                            50

-------
           Figure  19.   F/M  blank  test	
                       (Constant  Recycle  Flow,  Run A)
                        Feed Flow            1938 ml/min
                        Sludge Recycle Flow  1070 ml/min
                        Sludge Waste Flow      85 ml/min
   600
I 500
E- 400
o
" 300
   800
^ 700
E
J 600
" 500
   0,8
" 0,7
   0,6
                                Feed
CD
•r~
co
                                Mixed Li_quor^     °o
                                  oo   "  	^L
                            O »-oO-   "ll if"   O     O
                                   O  Experimental
                                   — Computed
                        oo
                           oo
       _  o
            I     I     I     I     I     i     I     I     I     I
5   10   15
                          20   25   30
                           Time, hours
                                         35   40   45   50
                         51

-------
lines are the predicted responses using the transient
state computer model (Appenix C).  A very good fit was
obtained for the increase in MLTC (mixed liquor total
carbon) but, because of a non-linear calibration of the
total carbon instrument above 50 percent of scale, data
for the F/M signal lay below the computer prediction of
F/M.  When the MLTC values reach the same non-linear range
as the feed values, the predicted curve agreed with the
data.

Analytical technique did not entail separate determination
of the microorganisms and substrate concentrations in
the aeration basin.  However, the concentration of sub-
strate in the reactor represented less than five percent
of the MLTC concentration under steady-state conditions.
The computer simulation shown in Figure 20 illustrates
the effect of the step increase in loading upon the
reactor substrate concentration during Blank Run A.  The
substrate concentration rapidly increased after the step
change but the dynamics of cellular growth caused the
food to microorganisms ratio to steadily decrease, thus
     i
causing the substrate concentration in the aeration basin
to gradually decrease to the original steady-state level.

In Table 3 and Figure 21 the F/M testing conditions for
Blank Test A and four F/M control tests are summarized.
The initial experimental conditions for Control Test B
(Figure 22) were similar to those for Blank Test A.
However, the initial mixed liquor concentration in Run B
was 120 mg/1 higher than that of Run A, even though the
initial feed concentration only differed by 25 mg/1.

Computer simulation verified that the bacteria concentration
in Run A had not yet reached a steady-state level at the
                            52

-------
  Figure 20.
        Relationship between  the mixed liquor,
        microorganisms,  and substrate concentrations
        after a step increase in loading	
        Blank Run A, computer simulation
TC
mg/1
TC
mg/1
TC
mg/1
900

800

700

600

800

700

600

500

 60

 50

 40

 30

 20
                                      Mixed Liquor
         Microorganisms
         0
              I
                  I
I
I
I
        5   10   15   20   25   30
                    Time, hours
              35
          47% Step Increase
          in Loading
                         53

-------
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-------
initial feed concentration.   About four days would have
been required to reach steady state (Figure 21).

The computer simulation fitted the data of Run B  (Figure 22,
a&b).   The drop in mixed liquor concentration from t=19
to t-28 hours was probably due to a plugged aeration basin
outlet, causing a dilution of reactor mixed liquor by the
feed stream.  A rapid buildup of bacteria concentration
occurred after the unit was  unplugged because of  an increased
recycle sludge concentration.

Figure 22b demonstrates the  proportionality involved in
F/M control.  Because of the increased recycle flow at the
expense of sludge wastage, the F/M response of the control
test was faster than the response for the blank.

The conditions of Run C (Figure 23, a&b) compared closely
with those used in Blank Test A.  The reactor microorganism
concentration was initially  below its steady-state level
(Figure 23a) since the step  decrease in feed concentration
at t-27.5 hours, the original concentration, allowed the
biota to proceed toward a steady-state level.

The model prediction of the  increase in mixed liquor total
carbon (t=0 to t=2?.5 hours) fitted the data for Run C.
A good representation of the recycle and wastage  response
is obtained with a fast F/M response (Figure 23b).

The F/M signal data lay above the predicted F/M curve
for the first several hours  following the step change
because an average value for the feed concentration rather
than the individual data points, was used in the simulation.
                             55

-------
Figure 21.   Computed initial  steady state	
            for Run A
                Feed Concentration    385 mg/1 TC
                No Change in Loading
  "  800
      750
      700
  S-
  o
      650
      600
  5   550
         0
Experimental
Initial  State
                        1
                1
         2      3
        Time,  days
                        Computed
                       —
                        Steady state
                    56

-------
-»-> £
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  c
•o o
a* xi
O) J-
700


600


500


400
          Figure  22a.   F/M  control  test	
                       bacteria  growth  and F/M
                       response—Run  B
                        Feed Flow            1938 ml/mir

                        Initial  Recycle Ratio    0.55

                        «l              A  O _      O
          -O-
                         o  o
                                                 o  o
°e  1000

cr »
*f" ^
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  _a
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-------
        Figure 22b.   F/M  control  test---
                      recycle  and  waste response,
                      Run  B
>d

en

to
0,9


0,8

0,7

0,6

0,5
         — o
                              o  Experimental
                             — Computed
                          '00
                                             o   o
    1200i-
     200r-
°c  100
QJ ^
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ro
  0
        0         10
                             I	I
                      20         30
                    Time,  hours
                       58

-------
          Figure 23a
                       F/M control  test ---
                       bacteria growth  and F/M
                       response,  Run  C

                          Feed  Flow          1938 ml /mi n
                          Initial  Recycle Ratio  0.55
      600
-l-> E


°li 500
•o ta E
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      400
                                  U 0
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                                    '0 "~ wpO Q W(J 4,
      900
s- c
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-------
          Figure 23b.   F/M  control test	
                        recycle and waste  response,
                        Run  C

o
I—

-------
The prediction of the transient biological state after the
step decrease in feed concentration was not accurate
because of an inadequate representation of the bio-settler
dynamics.  However, the final steady-state computer pre-
diction (t > 50 hours) fitted the data.

Figures 24 a&b and 25 a&b show the results of two F/M
tests (Run D and E) having different feed flows and
recycle ratios.  Increases in mixed liquor total carbon
were well predicted by the mathematical model while the
subsequent decreases were not accurately predicted.  A
more rapid return to the F/M setpoint was experienced in
these runs because a greater mass flow of waste was avail-
able for additional recycle.  Although the volumetric
availability of waste was still 85 ml/min for Run E and
only 75 ml/min for Run D, much high'er concentrations of
sludge existed because of higher compaction ratios
(see Equation 13).

Figures 26 and 27 illustrate the effect that the F/M
control had upon sludge settling.  Figure 26 is plotted
from early propylene glycol and MLVSS data.  Abscissa
values in Figure 27 are from on-line F/M control data,
using the total carbon instrumentation.

A definite limited range of loading from 0.25 to 0.^5
(permissible for good sludge settling) is shown in Figure
26.  An optimum F/M of 0.35 gave a minimum SVI (sludge
volume index) of less than 100.  Operation at about 0.25
to 0.35 was desirable since a lower F/M also increased
process efficiency in terms of soluble substrate (TOD)
removal.
                             61

-------
      Figure 24a.   F/M  control  test	
                    bacteria  growth and F/M
                    response,  Run  D
                             Feed Flow    2325 ml/min
                             Initial  Recycle Ratio  0.30
to C7I
-i-> e
O
-o o
O) .O

-------
         Figure 24b.   F/M  control test	
                       recycle and waste response,
                       Run  0
to
c.
O)
3- E
OJ E
O -»->
O) (O
o; s-
  c
3-r-
O E

<*- r—
  E

-------
       Figure 25a.
                    F/M control test —
                    bacteria growth and
                    F/M response, Run E
tO CD
•*-> e
0
c
-b o
OJ .Q

-------
      Figure 25b.  F/M control test	
                   recycle and waste  response,
                   Run E
CO
c
01
 0,8


 0,7

 0,6
O
O)
o;
QJ '
•4-> i
to
1100


1000


 900


 200


 100


   0
                              •   Experimental
                              	 Computed
             -   I,,,, '••t«
                       I     i     I     i     I
            0         10        20        30
                       Time, hours
                    65

-------
                                         10 E
                                        CO
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-------
The on-line control data in Figure 27 indicated an increase
in the SVI at high loadings and an optimum F/M operating
range from 0.3 to 0.5 TCp/TC^.  With F/M, less than 0.3
increases in SVI were expected.

Saline Propylene-Glycol Waste Water System
The activated sludge miniplant was operated with the saline
propylene-glycol waste water as the miniplant feed for
about three weeks.  During this period, the F/M control
system did not result in a significant time reduction
of F/M response because only 20 to 40 ml/min of waste
sludge was available for additional recycle in the salt
system.  The growth rate of microorganisms was much smaller
than in the fresh water system, as can be seen by inspection
of the kinetic growth constants.

The waste water feed concentration upon start-up on the
saline system and was only 250 mg/1 total carbon.  The
initial biota concentration in the aeration basin was
about 1000 mg/1 MLVSS.  There was no significant waste
flow.  The feed flow was 1938 ml/min (0.5 gpm), and the
recycle ratio was about 0.6.  Because of the low feed con-
centration (hence a very small growth of microorganisms)
and the concentration loss of about 80 mg/1 VSS in the
bio-settler overflow stream, it was not possible to
maintain the microorganism concentration in the aeration
basin.

The feed concentration was gradually raised to about 450
mg/1 total carbon by adding batch aliquots of propylene
glycol to the equalization tank.  With the feed concentra-
tion at 450 mg/1, the aeration basin MLVSS increased from
1082 to 2104 mg/1 in three days (with no waste flow).  The
F/M control system served to maintain this level of biota
                            68

-------
concentration, but the response to increases in loading
were slew.

SYSTEM EVALUATION
In order to have a meaningful basis of comparison for the
F/M control tests, it was necessary to have a blank run
with identical initial conditions.  The initial steady
state had to be the same in terms of feed, recycle and
waste flow rates, substrate concentrations, re-actor and
bio-settler underflow microorganism concentration, temper-
ature, and physiological conditions of the biota.  Although
these conditions were difficult to achieve experimentally,
a valid comparison was made by using the mathematical model-
ing which predicted the transient accumulation of micro-
organisms.

The computer-simulated curves in Figures 28 and 29 show
the differences in response characteristics for the fresh
water propylene glycol system with F/M control versus the
system with no control.  The time-dependent simulations
were allowed to proceed until a true steady state was
reached before a 50-percent step increase in feed concen-
tration was made.

The response time for F/M to return to the set point
decreased markedly for the system with control.  An 8.5
hour hydraulic residence time with an initial recycle
ratio of 0.55 required 17 hours for the controlled system
F/M to return within 20 percent of the set point level
after the step increase in loading (Figure 28).  This
represented a 63-percent reduction in response time.

Figure 29 represents the system having a 6.95-hour
hydraulic residence time and an initial recycle ratio of
                             69

-------
0.3-  The F/M ratio returned to within 20 percent of the
set point in ten hours, less than a third of the time
required for the system without control.   The larger mass
of waste available for recycle (as with Runs D and E)
allowed a 69-percent reduction in response time.

Figure 30 shows the relationship between substrate con-
centration in the aeration basin for the blank and the
F/M control simulation of Figure 29.  The control enabled
a fast return to the desired effluent quality.

Figure 31 shows the simulation of an F/M blank test and an
F/M control test for the brine propylene glycol waste
water system.  Because only 40 ml/min of waste was avail-
able for additional recycle, the response time with F/M
control was 33 hours.  While this was 54 percent less than
the 72 hours it took for the blank system, on-line F/M
control for the salt system did not seem justifiable.
Manual adjustment of the recycle and waste flows were
adequate for loading control because of the long response
times involved.

The implication from the testing of the fresh water and
salt systems was that biota with faster growth character-
istics (i.e., a high yield coefficient) necessitated
relatively high waste rates to remove the cellular produc-
tion.  Because the F/M response time was limited only by the
amount of waste available for additional recycle, F/M
loadings in these high yield systems can be well controlled.
For example, a domestic waste was found (Benedek and
Horvath, 1967) to have a cell yield coefficient of 0.6?
mg VSS per mg COD removed (k, - 0.07 day"1).  This compares
with 0.21 mg VSS/mg TOD    for the fresh water-propylene
                       X cIII
                             70

-------
glycol system (k^ = 0.06 day1).   The specific  rate  of
sludge growth reported by Benedek and Horvath was  nearly
three times that of the glycol system.   The F/M ratio
response time for a controlled system such as this would
only be a few hours.

The problems associated with F/M control where  the micro-
bial population had slow growth characteristics were
readily overcome.  Use of an aerated sludge storage  or
stabilization tank supplied additional recycle  in  periods
of high loading.  Innovative schemes similar to those
used in contact stabilization could be designed for  opti-
mum loading control.  In existing facilities, biota  from
aerobic sludge digesters might be used for F/M  control
purposes.
                             71

-------
       Figure  28.   Response characteristics with
                   and  without F/M control	
                   low  loading
(O
     600
Sc-  500
11  400
Li. 
-------



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Figure 29. Response characteristics with
and without F/M control —
high loading
600 r-


500

400



	 Control Simulation
	 Blank Simulation



1000
f\ C\f\
900


800


700
600
1,0
0,9
0,8
0,7
Or
Feed Flow 2325 ml/min
r~ Initial Recycle Ratio 0.3
Initial Loading 2.1 gm TCp/gm TCM«day
^^-^•^
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900 r- 10 32,5

800
700



_
1 \^^_


1 1 1 1 1
0 10 20 30 40 50
Time Since Step Change, hours
73

-------
   Figure  30.   Comparison of aeration  basin
                substrate concentration  with
                and without F/M control
(O
c
1,0

0,9

0,8

0,7
0,6
                          Digital Computer Simulation
                             Feed Flow       2325 ml/min
                          Initial Recycle
                             Ratio           0.3
                          — •**.	       Blank
                              F/M Control
C
O
•r-
-H
 E
C O
 4->
cd O
i- +J
-»->
l/J
 70
 60

 50
 40
 30

 20

 10
  0
             I
                    Blank
          F/M  Control
I
I
I
I
              0       10      20      30
                Time Since Step Change,  hours
                                                50

-------
        Figure  31.   Response characteristics with
                    and  without F/M control
                    (salt-propylene glycol system)
tO C7>
•»-> £
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+->  •
  c.
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cu
  .
O r—
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1000

 800

 0,9

 0,8

 0,7

 0,6

 0,5

1200

1100

1000
    1  Control Simulation
	  Blank Simulation
                           Feed Flow
               Initial  Recycle Ratio
                     Initial  Loading
             1938 ml/min
             0.55
             1.5  gm TCp

             gm TCM«day
                      I
                              I
             I
                                         !
              0      20      40      60      80     100
                  Time Since Step Change, hours
                        75

-------
                        SECTION VI
             NUTRIENTS ADDITION CONTROL SYSTEM

An industrial waste stream to be treated by biological
oxidation may not have sufficient concentrations of
nitrogen and phosphorus to supply the amounts necessary
for cell production and respiration requirements.

Constant nutrients addition, based only on flow, will
occasionally result in excess or insufficient nutrients
addition.  Insufficient addition decreases bacterial
viability while excess nutrients addition, besides being
economically unsound, can cause downstream algae blooms
and subsequent pollution problems.  High nutrient resid-
ual may also prevent recycle of industrial treated
effluents.

The solution to all of these problems lies in providing
a varying flow of nutrients to the aeration basin based
upon a measurement of the soluble organic substrate
concentration in the feed.

SYSTEM DESIGN
The designed nutrients addition control system was operated
on the basis of the addition of an ammonia and a phosphoric
acid solution proportional to an analysis of total carbon
in the feed stream.  The feed sample was passed through
a 3-tf-icron Cuno filter and the total carbon content was
measured by an Ionics Model 1212 Total Carbon Analyzer
(TCA) operating on a six-minute analysis cycle.  The
recorder peak height was converted to an equivalent electric-
al signal of sufficient magnitude to match a peak picker
                             76

-------
sensor.  The output of this  sensor was  transferred  to a
sample and hold amplifier by a programmer synchronized
with the analyzer.  The electrical signal was converted
to a pneumatic signal which linearly adjusted the per-
cent energized time of a 30-second cycle timer that
powered a nutrients addition pump (see Figures 10 through
13).

The nutrients pump maintained a given flow until its con-
trols received an up-dated analysis signal.  If the
period between analyses extended to hours or days,  some
slow reduction in the pump rate was anticipated due to
decay in the sample and hold amplifier output.

Proportionality of nutrients addition was varied by
changing the influent flow, the carbon analyzer calibra-
tion, the full scale pumping rate, and the concentration
of the nutrients solution.  If required, additional varia-
tion in proportionality was available by altering the
calibration of various intermediate hardware components.

The same total carbon analysis (TCA) that was used for
F/M control (Section V) was also used for the nutrients
control system.  A flow chart and block diagram which
includes both the F/M and the nutrients control system
are given in Figure 10 and Figure 13, respectively.  An
electrical schematic of the controls is given in Figure 12,

SYSTEM TESTING AND PERFORMANCE
The time lag from the peak on the TCA to the air signal
operating the nutrient pump was less than 10 seconds and
the resulting linear response is shown in Figure 32.
The control system performed reliably during the nine
months of miniplant operation.
                             77

-------
Figure 32.  Response of nutrients control system
   25
   20
   15
CO


I  10
i.
    0
I    I    I    I    I    I    I    I    I
     0  10  20  30  40  50  60  70  80  90  100

         Total Carbon in Feed, % of scale
                    78

-------
Routine analyses for the ammonia and phosphorus concentra-
tions of the bio-settler overflow were made in order to
determine the best C:N:P ratio for the miniplant operation.
Ammonia and ammonium ion concentrations were determined by
the Kjeldahl Nitrogen method.   Total phosphorus concentra-
tion was determined by a molybdate colorimetric method,
after co-precipitation of the  phosphorus with iron.

Figure 33 shows the relationship between ammonia consump-
tion and microbial growth.   Data were calculated by  material
balance on a daily basis.  Although the experimental data
reflects the ammonia consumption for cellular growth plus
the ammonia consumed by adsorption onto the bio-floe, the
results compare closely with the theoretical ammonia con-
sumption for cellular grwoth only.  For a cell formula of
C5H702N, 0.15 grams of ammonia would be required for the
growth of one gram of new cells.  This compares with the
experimental value of 0.133 gm NH3/gm cells formed.

Figure 3^ shows that the phosphorus consumption is directly
proportional to the ammonia consumption.  The phosphorus
required is 0.06 gram per gram of ammonia.  This translates
to 0.008 gram of phosphorus required per gram of microbial
cells formed.

The linear curves of Figures 33 and 3^ illustrate the
theoretical basis for feed-forward nutrients control.
Because microorganism growth is directly proportional to
the incoming feed concentration and because the nutrients
consumption is directly proportional to the microorganism
growth (Figure 33), the nutrient utilization will vary
directly with the incoming feed concentration.
                             79

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 Figure 33.   Ammonia consumption by microorganisms
    0,7
    0,6
    0,5
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                                   Slope = 0.133
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       0,0    1,0     2,0     3,0     4,0      5,0
           Microorganism Growth, Ib vss/day
                      80

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     Figure 34.
             Relationship between phosphorous
             and ammonia consumptions
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               Ammonia Consumption, Ib/day
                                          1,0
                      81

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In order to determine the minimum nutrients requirement,
the ratio of nutrients addition to feed total carbon
concentration was progressively lowered until analysis
of the bio-settler overflow indicated a low concentration
of ammonia and phosphorus.  The results shown in Figure 35
indicate a large adsorptive capacity of the mixed liquor
bio-floe for values (nitrogen fed/carbon fed x 100)
greater than 20.  Material balance calculations show that
without any bio-adsorption, for every ten units increase
in the abscissa value above the minimum value, a 40 ppm
increase in the bio-settler overflow ammonia concentration
would have occurred.  Because of the high adsorption, if
the data of (NiC x 100) above 20 in Figure 35 were plotted
in Figure 33 they would lie considerably higher than the
linear curve presented.

The results in Figures 3^ and 35 indicate an optimum car-
bon-to-nitrogen ratio of 100 to 9 and an optimum carbon-
to-phosphorus ratio of 100 to 0.5^.  Using this propor-
tionality the nutrients control system assured microbial
viability and the effluent concentration was maintained
at less than 10 ppm ammonia and less than 2 ppm phosphorus.

This control system could be modified to allow variations
in influent flow rate by flow measurement and increased
nutrients addition corresponding to the multiple of the
flow times the feed total carbon analysis.
                            82

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                                83

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                        SECTION VII
           CHEMICAL PLOCCULATION CONTROL SYSTEM

The overflow of the bio-settler Is usually too turbid for
release without some additional clarification.  This is
especially true in the treatment of saline waste waters,
where overflow turbidities are unusually high.

In the pilot plant, a chemical flocculation control system
was used to remove suspended and colloidal matter from both
the fresh water and the saline biologically treated effluents

DESCRIPTION OF THE SYSTEM
The schematic in Figure 36 illustrates the flocculation
controls and process flows.  The proportional control was
based on a turbidity measurement.  Aluminum sulfate was
used as the flocculant, and the pH was controlled (propor-
tional-integral) at the level corresponding to the optimum
for alum flocculation.

Both feed-forward and feed-back modes of control were tested.
An Ecologic Model 204 Turbidimeter was used for feed-back
control but fouling of the sensor window surfaces was a
reoccurring problem.  A timer-operated water flushing sys-
tem was therefore installed to clean the probe every 100
minutes.  This somewhat improved the instrument operation,
but significant fouling still occurred.

The Ecological turbidimeter was replaced by a Hach Surface
Scatter No. 2^126 Turbidimeter in which there is no contact
between the sample and the optical surface.  In both feed-
back and feed-forward control the entire settler overflow
was passed through the instrument.

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                                     85

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The pH of the flocculator effluent was measured with
conventional glass electrodes and recorded on a pneumatic
recorder-controller.  The caustic added was a 2-percent
NaOH solution.  A high pH alarm automatically closed the
control valve at values above 8.3 and aided in control
recovery under high pH-upset conditions.

The pilot plant chemical flocculation control system was
operated at a constant overflow rate in the range of
1,800 to 2,200 ml/min.

OPTIMUM pH AND ALUM DOSAGE
The stability of bio-colloids is dependent upon the surface
charge density.  In general, the microorganisms carry a net
negative charge, within the pH-range of interest.  The
charge is acquired through acid-base interactions of func-
tional ionogenic groups and, thus, the biota surface charge
density is strongly pH dependent (Tenney and Stumm, 1965).

Flocculation is not a result of the aluminum ion Al (III)
but of its hydrolysis products (Stumm and Morgan,
1962j Stumm and O'Melia, 1968).  The solution pH is the most
important parameter in determining which particular polymeric
hydrolysis specie predominates.  This in turn influences the
polymer bridging characteristics which cause flocculation.

Jar Tests
The optimum pH for alum flocculation was determined by a
series of jar tests at various pH values.  A one-liter
sample of the bio-settler overflow was placed in a beaker
and 1M HC1 or NaOH was added to bring the sample to the
desired pH.  The pH was held constant by adding a predeter-
mined amount of caustic simultaneous with the alum dose
                             86

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during a one-minute, rapid-mixing phase.   After an additional
slow stirring at 30 rpm for 15 minutes, the sample was
allowed to settle for 20 minutes.  The supernatant was
then .siphoned and analyzed for turbidity.

To determine the optimum pH for flocculation, the tests
were performed on samples having the same initial turbidity.
There was an increase in the optimum alum dosage for floc-
culation above pH of 6 and below pH of 5.   Also, the height
of the settled floe subsidence line was much higher when the
pH was above 7 and when the alum doses were greater than
1 millimole per liter.

Optimum Alum Dose as a Function of Turbidity
The meaning of optimum alum dosage is illustrated in Figure
37.  If the dosage of alum is less than the optimum,
effluent quality will diminish, while doses above the opti-
mum are economically unsound.  Also, high alum doses were
found to cause light, fluffy floes, which sometimes resulted
in settler upsets because of poor settling and high sub-
sidence levels.  This would result in less compacted
sludge and necessitate increased sludge dewatering.

There exists a stoichiometric relationship between the
bio-settler overflow turbidity and the optimum alum  dose
for flocculation, at constant pH (Figure 38).

The effect that the physiological condition of the bacteria
has on the optimum alum dosage for flocculation is illustra-
ted  in Figure  38.   Data point  5  represents a series  of jar
tests on a sample  of bio-settler overflow with  an artificially
increased initial  turbidity.   The turbidity of  the  overflow
                            87

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      Figure 37.  Alum flocculation jar tests
   33

   30

   27


   24

   21
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15

12

 9
     0,0
Constant pH    6
Initial Turbidity  31
      Optimum
      Dose,  0.26
             1,0         2,0         3,0
             Alum Dose, mil 1imoles/1iter

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          Figure  38.   Optimum alum dose as a
                      function of initial turbidity
                                 pH   6
                                 Fresh Water Biota
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-------
sample was increased from 25 JCU to 44 JCU by adding
aeration basin mixed liquor to the sample.  Thus the sample
represents larger bio-colloids of older microorganisms.  On
the other hand, data point 6, where a higher optimum alum
dose was required, represents a case of finely dispersed
microorganisms.  Point 6 is taken from continuous flow
miniplant data.  Here the alum flow was increased just to
the level of good flocculation.  The high, bio-settler over-
flow turbidity was the result of a very high growth rate
of microorganisms in the aeration basin.

SYSTEM OPERATION AND PERFORMANCE
The Hach Surface Scatter Turbidimeter worked well in both
modes of control.  When operating in the feed-forward mode
it was necessary to drain the instrument every two to four
hours in order to flush a buildup of bacteria on the in-
side walls of the turbidimeter body cylinder.

Because of the lag time of several hours associated with the
flocculator and final settler, control stability was a
major problem in feedback control.

Since in feedback control an increase in the floe-settler
turbidity was necessary before the controller would increase
the alum flow, final settler upsets were not uncommon.  High
alum additions because of a slight settler upset would some-
times result in a fluffy, poor-settling floe which would
further upset the condition.  High alum doses sometimes
caused a milky white effluent, increasing the overflow
turbidity and causing total instability.

The feed-forward mode of proportional control resulted in a
high quality effluent.  Stability was not a problem.
                             90

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The feed-forward control was tested in both the propylene-
glycol fresh water system and the glycol-salt waste water
system.  Typical performance of the control system is
given in Table 4 and Table 5.

The calibration of the optimum alum dose versus overflow
turbidity shown in Figure 38 was used for the feed-forward
control for the fresh water system.  A ten-percent higher
calibration was necessary for the salt system.

Dosages of alum were sufficient to remove residual phosphate
(about 2 ppm phosphorus) due to excess nutrient addition.
Higher concentrations of phosphorus required additional alum
in stoichiometric proportions.

An average of 98 percent of the suspended solids were removed
by the flocculation step in the fresh water system and 85
percent were removed in the salt system.

The chemical flocculation control system increased process
efficiency in terms of TOD removal.  (TOD data was taken
from samples passed through a 25-micron Cuno filter.)  For
the fresh water system, an average of 25 percent of the
bio-settler TOD was removed in the flocculation step.  This
increased the overall process efficiency from 90.9-percent
TOD removal to 93-4 percent.  A 37-percent reduction in
effluent TOD resulted in an increase in the average, overall
process efficiency from 7^.5 percent to 85.4 percent for
the saline propylene glycol system.

The turbidity of the final fresh water effluent was reduced
to 2 to 3 Jackson Candle Turbidity Units (JCU); whereas,
the bio-settler overflow turbidity was typically 15 to 25 JCU.
                             91

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    Table 4.   ALUM FLOCCULATION  SYSTEM PERFORMANCE,'
              GLYCOL-FRESH  WATER SYSTEM
             Effluent  Before
          Chemical Flocculation
   Effluent After
Chemical Flocculatlon
Day of
Operation
1
2
3
4
5
6
7
8
9
10
MLSS,
mg/1
45
22
20
20
11
36
52
86
34
55
TOD Removal,
%
88.8
95.5
93.5
89.3
92.0
95-2
84.1
90.7
88.3
91.7
MLSS,
mg/1
4
0
0
0
0
1
0
0
0
0
TOD Removal,
%
89.7
96.0
95.8
93.0
93.9
95.4
87.7
94.9
94.0
93.9
a proportional  control with  optimum alum dosage  according
  to  Figure  38

  effluent turbidity maintained at 2 to 3 JCU
                          92

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 Table 5.   ALUM FLOCCULATION SYSTEM PERFORMANCE,'
           GLYCOL-SALT WATER SYSTEM
             Effluent Before
          Chemical Flocculation
   Effluent After
Chemical Flocculation
Day of
Operation
1
2
3
4
5
6
7
8
9
10
MLSS,
mg/1
91
164
52
43
23
214
66
43
52
40
TOD Removal,
%
76.2
78.9
63.2
66.6
90.3
75.8
71.5
69.0
75.4
78.4
MLSS,
mg/1
24
17
0
3
0
18
0
19
21
18
TOD Removal,
%
91.9
91.9
65.9
	
90.8
96.3
	
	
80.3
81.0
aalum dosage at optimum (10$ greater than doses in
 Figure 38)
                          93

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The bio-settler overflow turbidity for the saline system
was generally 35 to 80 JCU and the turbidity of the final
effluent was lowered in the same proportion as the suspended
solids removal, about 85 percent.

This control system could be modified to allow variations
in the flow rate by measuring the flow and increasing the
alum addition by the product of the flow times the turbidity.

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                       SECTION VIII
               BIOLOGICAL INHIBITOR DETECTOR

The kinetic reactions within a biological oxidation system
proceed at rates defined by the nature of the chemical con-
stituents in the waste water and the activity of the biomass.
A real-time measure of enzyme activity to detect the presence
of inhibitors or toxins in the feed to an activated sludge
plant is required for optimization of the process.

The main objective of this study was to develop an  upstream
sensing device for toxic loads to an activated sludge process,
Such a feed-forward control system is essential in  an indus-
trial or combined plants to prevent the loss or inhibition of
the acclimated biomass.  If the presence of a toxin in the
feed to the plant can be detected rapidly enough on a
repetitive basis, the feed could be diverted to a holding
pond until the toxin is identified and eliminated.

BACKGROUND INFORMATION
Microbiological activity is a dynamic concept that  expresses
the ability of the microorganisms to interact with  their
environment.  Inhibition of the activity of an acclimated
culture may result from an adverse effect on the enzyme
catalytic ability, the cell membrane permeability,  or a
general systemic effect by destroying the cellular  integrity.
Toxic, heavy metal ions affect enzymes by binding reversibly
or irreversibly at the enzyme-active site or by causing
conformational changes in the enzyme.  Some organic inhibit-
ors alter the cell membrane permeability, preventing the
organisms from maintaining an environment favorable for
proper metabolic activity.  Heat and chlorine have  a general
systemic effect through denaturation of protein and other
cellular components.
                             95

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The enzyme theory of Mlchaelis and Menten (1913), used by
biochemists to adequately describe the toxic effects on
purified enzymes, was applied to describe the inhibition
of activated sludge (Hartmann and Laubenberger, 1968).
The application of enzyme inhibition equations to a mixed
culture represents the overall kinetics of the biomass
since it is not known if the toxicity effects are identical
or different for various species of organisms.  An inhibitor
at a certain concentration may be toxic to some species but
may stimulate the growth of others.  The varying composition
of the feed to an activated sludge plant adds to the problem
in the study of toxicity.  Some components may be syner-
gistic or antagonistic effects with the toxin being studied
(Poon and Bhayani, 1971).

The determination of different types of inhibitions of
enzyme-catalyzed reactions with more than one substrate
and product involves kinetic equations that are considerably
more complex than the basic Michaelis-Menten equation
(Cleland, 1963).  Three types of inhibition patterns are
commonly recognized from the kinetic analyses of experi-
mental data:

1.  Competitive inhibition results when inhibitor and sub-
    strate compete directly for the same enzyme site.  Thus
    increased substrate concentration would reduce the
    effect of the inhibitor.
2.  Uncompetitive inhibition is reaction of the inhibitor
    with the enzyme which can still undergo another reaction
    with the substrate.  This type results in decrease of
    reaction velocity with increased inhibitor concentration
    since there is no direct competition between inhibitor
    and substrate for the free enzymes.
                             96

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3.  A mixed or noncompetitive inhibition is a mixture of
    the two mechanisms and is what  takes place in a mixed
    culture such as the activated sludge.

The biological effects of toxic wastes  have been convention-
ally evaluated by standard sanitary tests that measure the
unit operation efficiency (BOD and  COD  reduction), biological
population density (MLVSS and SVI), and biological oxidation
capacities (sludge age, sludge yield, and rate of BOD exer-
tion) .

These measurements have been used by many investigators to
assess the effects of toxic substances  on the gross unit
efficiency of an activated sludge system (Barth, et al.,
1965; Banerji, et al., 1968; Ghosh and  Zugger, 1973;
Salatta, et al., 1964; Busch and Kalinske, 1956; Patterson,
et al., 1969; Stack, 1956; Hermann, 1959; Smith, 1953).

None of these tests are appropriate for monitoring the
activity of biomass in a treatment  unit because of the
time required to conduct any of these tests and the slow
response of parameters to a reduction in the activity of
the biomass caused by a toxic slug introduced into the treat-
ment unit.

Biological waste treatment processes can be monitored through
selective biochemical tests.  Cells may exist in either of
two metabolic states, the presence of utilizable substrate
or in the absence of substrate.  The endogenous metabolic
level is indicative of the microbial population while the
metabolic activity in the presence of  substrate represents
the oxidative activity of the biomass.
                             97

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The microbial concentration if deoxyribonucleic acid (DNA)
has been shown to be invariant with the physiological
state and fairly constant among bacterial species
(Genetelli, 1967).  The concentration of DNA does not indi-
cate the activity of a biomass and thus cannot be used as
a measurement of toxic effects.

The hydrolysis of adenosine triphosphate (ATP), common to
all cellular metabolism, is the basis of a method of measur-
ing the physiological state of microbial cultures.  The
endogenous ATP concentration represents a relative measure
of biomass while the rate of increase, or peak ATP concen-
tration after substrate addition, reflects the biomass
activity (Forrest, 1965 and Patterson, et al., 1969).  Assay
procedures for ATP are based on its bioluminescent reaction
with luciferin and luciferase  enzyme extracted from  firefjy
lanterns.  Briefly, ATP analysis requires rapid killing of
the cells and extraction of ATP into aqueous solution.
Many investigators utilize conventional liquid scintillation
counters for measurement of luminscence.  Others have
developed their own light-measuring devices, and one company
(E. I.  DuPont) is now marketing a special instrument for
ATP analysis.   Concentration of ATP seems an attractive
parameter to study the response of cells to their environment.
Few attempts have been made to apply it to heterogenous
systems such as an activated sludge, and its application as
a continuous monitor does not seem practical.

The dehydrogenase activity test uses an electron acceptor
dye 2,3,5-Triphenyl tetrazolium chloride (TTC), which is
reduced to an insoluble red precipitate, formazan.  The
drhydrogenase activity is reported as micrograms of formazan
produced during the incubation period per mg of cell material
(Lenhard, 1965).  The results of this test are greatly
                             98

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affected by incubation time, temperature,  mixing rate, and
the presence of oxygen (Patterson,  et al., 19&9).

Measurement of dehydrogenase activity in sludges was used
to assess the oxidative capacity of activated sludge units
(Ford, et al., 1965).   The measurement was found to respond
to significant changes in plant loading and sludge age,
although no correlation between BOD removal efficiency and
average dehydrogenase  activity was  found.

Many of the disadvantages of the dehydrogenase activity
method are obviated by the direct measurement of the oxygen
uptake, a measurement  of the natural terminal electron
acceptor without interrupting the normal biochemical processes,

Traditionally, the Warburg respirometer has been used in
both biochemical and sanitary engineering research to
measure the oxygen uptake rate of microorganisms.  The
Warburg technique requires special  equipment and skilled
technicians and is inappropriate for routine plant monitor-
ing.  Other manometric respirometers have been developed
for waste treatment application (Arthur, 1964; Tool, 1967).
The Arthur respirometer recycles the waste culture and air
counter-currently through a large,  closed, reaction chamber.
The air-stream is passed through a  sodium hydroxide solution
to absorb carbon dioxide.  As oxygen is utilized by the cul-
ture, the partial pressure of oxygen decreases within the
aeration chamber, which is monitored by an oil manometer,
and a pressure transducer.  The AC  signal from the trans-
former is then rectified and recorded as the change in
partial pressure in the aeration chamber withtime, which
represents the oxygen demand curve.
                             99

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Continuous manometric respirometers have been developed for
BOD monitoring (Clark, 1961; Pipen, 1973).  In these
devices, the oxygen uptake of a large, biological sample
is continuously replaced by a manometrically triggered
electrolysis reaction.  The amount of electrical energy
required to generate the required oxygen is recorded with
time and is a measurement of the oxygen demand of the sample.

Since the development of membrane electrode systems to
measure dissolved oxygen, such devices have been used to
measure the oxygen uptake rate replacing the manometric
methods.

The Simcar Respirometer (Abson, 35 al., 196?) utilizes a
galvanic cell oxygen electrode to obtain a continuous record
of dissolved oxygen concentration in an aerated culture to
obtain the oxygen uptake of large samples over a period of
10 to 18 hours.

An automated respirometer (Wallace and Tierman, 1968)
measures the oxygen uptake in a biological sample with an
inlet probe and an outlet probe as the sample is pumped
from one to the other in a predetermined transit time.  The
differential output of the two probes is representative of
the oxygen uptake rate of the sample flowing through the
device.  A plot of the oxygen uptake rate versus time is
then produced and the area under the curve represents the
BOD of the sample tested.  Results could be obtained within
four hours for each test.

Oxygen uptake rates, both Warburg and oxygen electrodes,
have been used to measure the effect of toxins and inhibitors
on activated sludge (Ayers, et al., 1965; Ghosh and Zugger,
1971; Sato, 1971; Hartmann and Laubenberger, 1968).
                             100

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The oxygen utilization rate shows more relative inhibition
than the ATP or the dehydrogenase activity measurements,
and it better approximates the actual activated sludge
process (Patterson, et al., 1969).  The oxygen utilization
rate response rapidly to induced disruption of metabolic
activity.  It is sensitive, reliable, and can be easily
automated with oxygen electrodes.  A quantitative evaluation
of commercially available oxygen probes has been recently
published (Pijanowski, 1971).

OXYGEN UPTAKE MEASUREMENT CYCLE
Laboratory tests were conducted to determine an oxygen uptake
measurement cycle that would be sensitive to the presence
of a toxic substance in the feed to an activated sludge plant
and that could be automated to rapidly detect the toxic
effect on a repetitive basis.

A New Brunswick Scientific Chemostat Model C-30 was used
as a batch reactor in which the temperature, mixing speed,
and rate of aeration were controlled.  It was also equipped
with an analyzer and recorder to follow the dissolved oxygen
(DO) level in the liquid phase in the reactor.  A procedure
was followed to measure the oxygen uptake rate and total oxy-
gen utilized when a sample of a degradable carbon source was
added to an acclimated and stabilized bacteria sample ob-
tained from the activated sludge pilot plant:

    About 500 ml of the activated sludge was introduced in
    the reaction vessel and aerated to reach an equilibrium
    DO level that represented the endogenous equilibrium
    oxygen concentration.  A 10-ml sample of a standard
    propylene glycol solution or a test sample containing a
    toxic substance was introduced in the reaction vessel
                             101

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    and the airflow turned off at the same moment.   The
    initial slope of the decrease in DO concentration was
    the oxygen uptake rate due to the oxidation of the
    organic substrate plus the endogenous uptake rate.
    If a low airflow was maintained as the sample was
    introduced in the reactor, the oxygen concentration
    followed a curve as shown in Figure 39.  The area under
    this curve was a measure of the oxygen consumed in the
    oxidation of the organic substrate in the sample added.

The volume of the test sample of 10 ml had negligible dilu-
tion effect on the DO concentration in the reaction vessel,
and for a 1000-mg/l propylene glycol sample, complete degra-
dation time was less than 15 minutes.

The oxygen uptake rate and the total oxygen consumed by
propylene glycol standard solutions containing various con-
centrations of toxic substances were compared to the measure-
ment obtained in the absence of the toxin.  The sensitivity
and reproducibility of the total oxygen consumed, as deter-
mined from the area under the oxygen uptake curve,  was
superior to that of the oxygen uptake rate, as determined
from the initial slope of the oxygen concentration curve
when the aeration was cut off.  The rate of oxygen uptake
was more dependent on the concentration of viable biomass
than the total oxygen consumed.  The automation of a measure-
ment cycle utilizing the area under an oxygen uptake curve
was simpler since it did not require cutting of the air
every time a test sample was added.

For these reasons, the total oxygen consumed by a test
sample added to an aerated sludge under controlled conditions
was selected as the parameter to monitor toxic and inhibitory
effects of the feed to an activated sludge process.
                             102

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Figure 39.
Schematic of oxygen  concentration
during the bio-oxidation of a
degradable carbon source
                         6      8
                   Time, minutes
                          10
12
                  103

-------
Mathematical Model of the Oxygen Uptake Curve (Figure 39)
When a sample of a degradable carbon source was added to a
stabilized and aerated sludge, the dissolved oxygen
decreased rapidly due to the oxygen consumed by the bacteria
to oxidize and metabolize the substrate added.   The DO
continued to decrease as long as the oxygen uptake was
greater than the oxygen transferred to the solution by the
controlled aeration.  The time required to reach the minimum
oxygen level depended upon the concentration and activity
of the biomass, the organic loading, the rate of aeration,
and the oxygen transfer characteristics.  As most of the
substrate was degraded and the rate of oxygen uptake became
less than the oxygen supply, the DO started increasing till
it leveled off at the original endogenous respiration
equilibrium concentration.

The concentration of dissolved oxygen in the liquid phase,
C, at any time is given by:

                 ||  =  KLa (Cs - C) - rr              (16)

where KLS = mass transfer rate of oxygen, min-1
      Cs  = saturation DO concentration, mg/1
      rr  = oxygen uptake rate by the microorganisms,
            mg/l«min

Before the addition of the test sample containing the degrad-
able substrate, the oxygen uptake by the microorganisms is
the endogenous uptake and is proportional to the biomass
concentration, X.

                 T£  =  KLa (Cs - C) - KeX             (17)
dt
            104

-------
At equilibrium -rr = 0 and therefore
               U. 0
               C  = Cs -
where Ke = endogenous reaction rate constant, min"1
      X  = concentration of the biomass, mg/1

When a substrate is added to the biomass, the oxygen uptake
will be the sum of the endogenous uptake and the uptake due
to the substrate degradation.  In a system that is not oxy-
gen limited, the substrate utilization can be represented
as a first order reaction by:

               || = -k'XS                              (19)

where k1 = substrate biodegradation rate constant,
           min-1 (mg/1)-1
      S  = substrate concentration in oxygen equivalent
           units, mg/1

Assuming the biomass concentration, X, to be constant during
the degradation of a small sample of a substrate, Equation
(19) can be integrated toi

                s = S0 e-k'XS                          (20)

The DO concentration after the addition of the substrate is
given by:

               |§ = KLa (Cs - C) - KeX - k'XS          (21)

Substituting Equations (18) and  (20) in (21) and rearranging!
                            105

-------
        If + KLaC = KLaCo - k'XSo e~k'xt               (22)

This differential equation is readily solved using an inte-
grating factor, exp. -/KLa^t and the initial condition of
Equation (18) to obtain the following expression for the DO
concentration as a function of time:

                C = °o + k'X-KLa (e-k'Xt _ e-KLat)     (23)

The area of the oxygen uptake curve of Figure 39 is given by:
             Area = /  (Co - C)dt
                    t=0
                               ce-k'Xt _ e-KLat )dt     (24)
                            -J.-Q
Performing this integration yields

             Area =  °-                                (25)
The area of the oxygen uptake curve can be used to determine
the biological oxygen demand (So) of the test sample if the
oxygen mass transfer coefficient KLE is known.   The value of
KLa depends on the rate of aeration and mixing and the
characteristics of the stabilized culture used in the test.

Development of the Measurement Cycle
In order to utilize the area under the oxygen uptake curve to
monitor the toxic effects of a feed to an activated sludge
plant, it is required to be able to distinguish between the
changes due to the varying concentrations of the substrate in
the feed and the presence of toxic substances.   The oxygen
uptake of a feed sample could be calculated per unit total
                             106

-------
organic carbon in the sample to eliminate  the change  due to
varying substrate concentration, but this  requires  the use
of another instrument to monitor the total organic  carbon in
the feed and a complicated,  synchronized,  electronic  system.

A comparison of the oxygen uptakes  of two  standard  propylene
glycol samples before and after the exposure of the bacteria
to a feed sample was a measure of the toxic effects of the
feed to the activated sludge process.  The oxygen uptake
of the first standard established a reference activity
of the bacteria sample, which was then exposed to the
feed to the process for long enough time to degrade the sub-
strate in the feed.  Then the same  bacteria sample  received
an equal volume of the standard and its oxygen uptake, com-
pared to that of the first sample,  was a meausre of any change
of activity due to the feed sample.

The procedure developed for the automated  biological  inhibitor
detector was as followsi

1.  About 500 ml of the mixed liquor was withdrawn  from the
    aeration basin to the reaction vessel  of the instrument.

2.  The bacteria sample was aerated at an  adjusted  rate of
    mixing and aeration for 16 minutes to  reach an  equilibrium
    endogenous respiration level.

3.  A 10-ml sample of a 600 mg/1 propylene glycol solution
    was introduced in the reaction vessel.  During  a  period
    of 12 minutes, the oxygen uptake curve was recorded and
    its area, AI, was determined and stored.

4.  A 10-ml sample of the feed was  then introduced  to the
    reaction vessel and the DO level recorded over  a  period
                             107

-------
    of 18 minutes, enough to degrade feed sample containing
    substrates equivalent to about 1000 mg/1 of propylene
    glycol.

5.  Step 3 was repeated and the Area, A2, of the oxygen
    uptake curve of this second standard solution was deter-
    mined and stored.

6.  The ratio of A2 to Ai was the activity ratio and was a
    measure of the toxic effects of the feed sample.

7.  At the end of the cycle, the bacteria sample was drained
    from the reaction vessel and within two minutes a second
    cycle started.  The total cycle time was 60 minutes.

Figure 40 is a schematic illustration of the measurement cycle
when the feed contained no toxic substance.  The activity ratio
would be approximately equal to 1.0.

Figure Ul illustrates the measurement cycle when the feed
contained a toxic substance.  The activity ratio would be
much less than 1.0.

LABORATORY TOXICITY TESTS
The developed method for the measurement of an activity ratio
was used to study the effects of concentration and time of
exposure of various toxic substances on a propylene glycol-
acclimated fresh water bacteria.  The purpose of the laboratory
batch testing was to determine the response of the activity
ratio measurement to the inhibitory effects of heavy metal
ions and toxic organic substances that may be present in a
petrochemical waste water treatment plant.
                             108

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The bacterial culture, obtained from the activated sludge
miniplant operating on a fresh water, propylene glycol
feed, had a mixed liquor volatile suspended solids (MLVSS)
of 1700 rr.g/1 to 2800 mg/1 during these tests.   Direct
plating of the acclimated culture indicated a microorganism
composition of 77 percent Pseudomonas, 13 percent Bacillus
subtilis, and 7 percent Alcaligenes as the main species.

The laboratory procedure was similar to the procedure
developed for the monitoring instrument, in whifch the feed
sample was a synthetic 600 mg/1 propylene glycol containing
varying concentrations of the toxic substance.  The oxygen
uptake of the second standard was measured at different
time intervals after the exposure of the bacteria sample
to the test solution to determine the accumulative toxic
effects or if the bacteria recovers with time.

The oxygen uptake, calculated per unit MLVSS, for some
selected inorganic toxins is plotted versus the concen-
tration of the toxin in the test sample in Figure ^2.
The activity ratios for the same toxins are given in Table  6
for one concentration at varying exposure time.  Mercury  was
the most toxic of the inorganic toxins tested, reducing the
oxygen uptake to less than half at 3 ml/1 and to nearly
zero at 16 mg/1 concentration.  At an intermediate concen-
tration of 8 mg/1, mercury exhibited an immediate reduction
of the activity ratio to 0.27 that was further reduced with
longer exposure times.  The same chronic toxicity effect
of the other inorganic toxins tested is illustrated in
Table 6.

The oxygen uptake for samples containing varying concentra-
tions of phenol and dichloroisopropyl ether is shown in
Figure ^3 and the effect of the exposure time on the activity
ratio of the two substances is given in Table 7.  Phenol was

                             111

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Figure 42.  Effects of inorganic toxins
            on the oxygen uptake of
            qlycol-acclimated fresh
            water bacteria
                  X Cadmium
                  A Sodium cyanide
                  © Sodium hypochlorite
                  O Copper
                  • Mercury
0
10      20     30      40      50
  Concentration  of Toxin, mg/1
                 112

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   Table  6.   EXPOSURE  TIME  EFFECT  OF  INORGANIC  TOXINS  ON
             GLYCOL-ACCLIMATED  FRESH  WATER  BACTERIA
      Toxin
Concentration
    mg/1
Exposure
  Time
 minutes
Activity
 Ratio
(A2/Ai)
Mercury
Copper
Sodium Cyanide
      8
     25
      3.0
Sodium Hypochlorite
Cadmium
     60
     50
immediate
   16
   48

immediate
   19
   64

immediate
   20
   40
   50

immediate
   12
   25

immediate
   14
   24
  0.27
  0.20
  0.12?

  0.31
  0.206
  0.204

  0.607
  0.502
  0.353
  0.316

  0.294
  0.187
  0.102

  0.70
  0.337
  0.276
                             113

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Figure 43.
  Effects of organic toxins on the
  oxygen uptake of glycol-acclimated
  fresh water bacteria
              •  Dichloroisopropyl  ether

              0  Phenol
   0
20      40      60      80     100
  Concentration  of Toxin, mg/1

-------
      Table 7.  EXPOSURE TIME EFFECT OF ORGANIC TOXINS ON
                GLYCOL-ACCLIMATED FRESH WATER BACTERIA
                                       Exposure   Activity
                      Concentration      Time      Ratio
	Toxin	       mg/1	     minutes   (A2/Ai)


Dichloroisopropyl
Ether                     100.0        immediate    0.498
                                           20       0.649
                                           40       0.649
                                           60       0.628

Phenol                    111.5        immediate    0.394
                                           13       0.438
                                           27       0.417
                                           39       0.410
                             115

-------
slightly more toxic to this culture than the ether,  which
occurred in low concentrations in the waste water from the
production of propylene glycol.   Also the recovery of the
bacteria, as indicated by an increase of the activity
ratio with time of exposure, was better for the ether than
for the phenol.  The immediate reduction of activity could
have been due to a shock loading effect, followed by accli-
mated and, thus, recovery of the biomass.

DESIGN AND OPERATION OF THE AUTOMATED INSTRUMENT
The measurement cycle, developed and tested in the laboratory
on standard solutions containing various toxic substances,
was used as the basis for the design of the automated instru-
ment.

The compact table top model, as  built, is shown in the
photographs of Figure 44 and Figure 45.  The bacteria sample
entered from the bottom connection to the reaction vessel
and drained through the same connection.  The reaction
vessel was placed on a variable  speed magnetic stirrer and
an air sparger, sample lines, the oxygen probe, and  a ther-
mometer were introduced through  the stopper.  The air supply
was controlled and measured by a rotameter while the exact
volumes of the standard solution and feed samples were intro-
duced through a calibrated, volumetric syphon system.  A
tracing of the measurement cycle as operated by a 10-cam timer
is shown in Figure 46.  A schematic of the electrical controls
for the instrument is shown in Figure 47.  A block diagram,
Figure 48, traces the path of the measurement signal through
the various electronic components.  The recorder may be
connected to any of six points indicated by the numbers in
parenthesis in Figure 48 and listed in Table 8, the  legend.
                             116

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  Figure 47.   Biological  inhibitor  detpctnr	
              schematic  of electrical  controls
CAM TIMER FOR
115 VOLTAGE AC
  MC-1
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Relay, P-B KRP-11AG

Timer, ATC 305, 0-15 seconds
 MX A  Mixer,  magnetic,  600 rpm
                     MC    Timer,  10  Cam,  ITC  MC-7
                          Solenoid  valve,  115  V  AC  coil
                     INT)  Integrator,  Bell  &  Howell
                          19-407A

                    [S-H)  Sample &  Hold,  Bell  &  Howell
                          20-419
                     120

-------
  Figure  48.   Biological  inhibitor  detector-
              signal  block  diagram
  Dissol ved
   Oxygen
  Analyzer
     I
    MV/V
Pre-Amplifier
        tor
I
         (2)
 Integrator
         (3)
Sample & Hold
      3
 Comparator
         (6)
    Relay
                      Sample & Hold
                            1
                            Sample & Hold
I
                                 (4)
                        Coefficient
                          (0-1.0)
                         Legend in Table 8
                     121

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Table 8.  LEGEND FOR SIGNAL BLOCK DIAGRAM OF FIGURE 48
     Position of
     Selector Switch           Recorded Parameter
          1                dissolved oxygen

          2                endogenous equilibrium
                           dissolved oxygen

          3                integration of oxygen uptake
                           curves of standard 1 and 2

          *J                area of oxygen uptake curve
                           of standard 1 (Ax)

          5                area of oxygen uptake curve
                           of standard 2 (A2)

          6                [(Ax)(coefficient) - A2]
                           comparator output
                           signal recorded is AI (coefficient)
                           122

-------
The operation of the automated cycle is as follows:

    Cam 1 activated a 0- to 15-second timer which opened
    a solenoid valve for a preset time interval to intro-
    duce 500 ml of the bacteria into the reaction vessel.
    Cam 6 switched on the mixer 15 seconds after filling
    the reaction vessel.  The bacterial sample was aerated
    to an airflow rate of 36 ml/min and mixed at a rate of
    200 to *JOO rpm for a period of 16 minutes.  This  was
    enough time for the DO level to reach equilibrium at
    80 to 90 percent of saturation, representing the  con-
    stant endogenous oxygen uptake in equilibrium with the
    oxygen transfer from the air supply.  The rate of mixing
    and airflow were kept constant throughout the measurement
    cycle.  At this point, Cam 2 activated a three-way
    solenoid valve allowing 10 ml of the standard propylene
    glycol solution (600 mg/1) into the reaction vessel.
    It also activated a relay to start the integrator and
    caused sample and hold unit No. 1 to store the endogenous
    DO value.  Cam 9 activated sample and hold unit No. 2
    to sample the integrator 11 minutes after the standard
    sample was introduced.  At the end of 12 minutes, Cam
    3 opened a three-way solenoid valve on the feed sample
    line allowing 10 ml of the waste vmter feed into  the
    reaction vessel.  The feed was continuously flowing
    through the solenoid valve into a stand pipe which
    held 10 ml to the overflow level.  After 18 minutes of
    exposure time (enough to degrade the feed samples),
    Cam 4 closed and repeated the operation of Cam 2  by
    adding another sample of the standard propylene glycol
    solution.  Cam 10 activated sample and hold unit  No. 3
    to sample the integrator 11 minutes after the second
    standard sample was introduced.  At the end of 12 minutes
                             123

-------
    Cam 5 opened the solenoid valve on the bacteria line
    to dump the contents of the reaction vessel, while
    Cam 6 turned off the mixer during the two-minute
    period that the reaction vessel was empty so that the
    mixer did not lose its magnetic coupling.  The total
    cycle time was 60 minutes and the cam timer ;\ras a
    continuous mechanism by which the same cycle was
    repeated every 60 minutes.

    The integrated area of the oxygen uptake curve of the
    first standard sample, which was stored in sample and
    hold unit No. 2, was multiplied by a preset fraction,
    usually 0.5, and compared to the integrated area due
    to the second standard sample, which was stored in
    sample and hold unit No. 3.  The comparator operated
    a relay that set off an alarm or diverted the feed to
    a holding pond when the oxygen uptake of the second
    standard was less than 0.5 times the oxygen uptake of
    the first standard.

The instrument was designed for flexible operation and had
many features for easy trouble shooting and maintenance.
A recorder-selector switch located in front of the instru-
ment allowed recording of any of six different outputs
that are shown in Figures 48 and its legend (Table 8) .  A
dump button on the front of the instrument actuated the
solenoid valve on the bacteria sample line to drain the con-
tents of the reaction vessel at any time for the purpose
of routine cleaning of the reaction vessel or resetting the
measurement cycle.

The electrical controls were quite versatile.  The total
measurement cycle time was varied by simply changing a
gear in the 10-cam timer, and each cam switch was adjustable
for duration and phasing.

                             124

-------
The electronic components were also very versatile since
the gain of each component was adjustable.

INSTRUMENT TESTING ON MINIPLANT OPERATION
The automated biological inhibitor detector was installed
at the activated sludge miniplant to test its  operation
both under normal conditions and withtoxic  substances
addded to the feed to the plant.

The bacteria sample to the instrument was obtained from
the aeration basin mixed liquor or the sludge  recycle
stream from the biosettler.  The higher concentration of
the biomass in the sludge recycle gave a higher initial
slope of oxygen uptake, but the time required  for recording
the oxygen uptake curve was not significantly  different
from that obtained with the lower concentration of biomass
in the aeration basin liquor.  The sludge recycle sample
was deficient in DO and required a much longer time of
aeration to reach the equilibrium endogenous level, as com-
pared with the aeration basin liquor.  The  biomass concen-
tration in the aeration basin did not vary  as  much as that
of the sludge recycle, and more reproducible oxygen uptake
data were obtained with bacteria samples from the aeration
basin.

Continuous operation of the instrument to monitor the oxygen
uptake of fresh water bacteria under normal operating condi-
tions for a period of three months showed a measurement pre-
cision of ±5 percent.  The area of the oxygen uptake curve
as integrated by the instrument was linear for the range
of 200 to 1000 mg/1 standard propylene glycol solutions.  For
the same concentration of viable biomass in the bacteria
sample, the sensitivity of the oxygen uptake signal was
dependent on the rate of mixing, airflow rate, and other
                             125

-------
factors that affect the overall oxygen transfer coefficient
KL&.  Sensitivity was varied by controlling the airflow
rate and. adjusting the gain of the electronic parts of
the instrument.

The instrument was tested for the detection of toxic sub-
stances in the feed while it was continuously monitoring
the activity ratio (A^/Ai) of the activated sludge miniplant.
Batch tests were conducted by adding varying concentrations
of the toxic substance to the feed sample entering the re-
action vessel of the instrument.  Continuous feeding of a
selected toxin in the feed was the basis of dynamic tests
to evaluate the effects of accumulation of the toxin in the
bacteria.

Batch Toxicity Tests
The same inorganic and organic toxic substances tested in
the laboratory were used for testing the instrument while the
miniplant was operated on fresh water-glycol feed and the
high salt waste water from the glycol production plant.

The activity ratio, as recorded by the instrument, is plotted
as a function of toxin concentration in Figures 49 through
Figure 52.  The effects of the inorganic toxins on the fresh
water bacteria,  Figure 49, were very similar to the resutls
obtained in the laboratory tests, Figure 42, in which the
order of toxicity was Hg > CN > CIO > Cu > Cd.  In the case of
the glycol-acclimated salt bacteria, Figure 50, the order
of toxicity was CN> Cu>Hg> Cd.  The less toxic effect of
copper and its leveling off at concentrations higher than 10
mg/1 in case of the fresh water bacteria may have been due
tp the multiplicity of the species as compared to the salt
water acclimated bacteria, where one major species predominated,
                             126

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Figure 49.   Effects  of inorganic toxins  on
            activity of alvcol-acclimated
            fresh water bacteria
                                /\ Cadmium
                                X Copper
D                                   Sodium
                                   Hypocnlorite
                                O Sodium Cyanide
                                   Mercury
  0
                                               Cd
10      20      30      40      50
   Concentration  of  Toxin,  mg/1
60
                  127

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Figure 50.   Effects  of inorganic  toxins  on
            activity of qlycol-acclimated
            salt water bacteria
                                   Cadmium
                                 O Mercury

                                 X Copper

                                 O Sodium Cyanide
    0
10      20      30
   Concentration of Toxin, mg/1
60
                      128

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Both phenol and dlchloroisopropyl ether were quite toxic to
the fresh water bacteria, Figure 51,  while the ether had
negligible effect on the salt water bacteria, Figure 52.
This was clearly due to the presence  of the ether in the
waste water feed to the salt water bacteria, which was
acclimated to concentrations of less  than 100 mg/1 of the
ether.

Continuous Toxicity Tests
Dynamic toxicity tests were conducted by adding copper to
the glycol waste water feed in the activated sludge mini-
plant.  The copper was added as cupric chloride to the
equalization tank and fed continuously to the salt water
bacteria.  The area of oxygen uptake  curve for a standard
propylene glycol solution (Ai) was determined before the
copper addition.  The same area (A2)  was recorded by the ins-
instrument once an hour after the addition of copper for
a period of 24 hours.  The activity ratio (A2/Ai) for the
test runs with 6.6 mg/1 copper and 3*0 mg/1 copper are
shown in Figure 53 and Figure 5^, respectively.  The data
scattering of Figure 53 was due to the malfunction of the
stirring mechanism of the instrument; that was corrected
during the second test.

Both tests showed no, or slight, reduction of activity for
a period of six to nine hours followed by a sharp decline
of the activity and reached a nil value after 16 hours and
21 hours for the 6.6 mg/1 copper and 3.0 mg/1 copper,
respectively.  A material balance of the copper during
test B is shown in Table 9, and the concentration of copper
in the bacteria and the liquid of the aeration basin are
plotted as a function of time in Figure 55.  During the 24
hours of feeding 3 mg/1 of copper to the activated sludge
                             129

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        Figure 51.
         Effects of organic toxins on
         activity of glycol-acclimated
         fresh water bacteria
  1,0
  0,9-
  0,8-
 - 0,7-
to
GC.
  0,6
O
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  0,4-
  0.3
                                 Q-Phenol

                                 n-Dichloroisopropyl
                                 ^ Ether
I
I
     0    10    20    30    40    50     60    70    80
               Concentration of Toxin, rng/1
                         130

-------
Figure 52.
               Effects of organic toxins on
               activity of glycol-acclimated
               salt water bacteria
                    ODichloroisopropyl Ether
                    X Phenol
   1,0
   0,9
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       0     10    20    30    40    50   60
                Concentration of Toxin, mg/1
                                             70    80
                       131

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                                        132

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      Figure 54.
Dynamic  toxldty test B,
continuous  feed of copper
to glycol -accl imated
salt water  bacteria
(copper concentration  in feed
bacteria concentration in feed
                                               3.0 mg/1
                                                1855 mg/1
                                               MLVSS)
  1,0
  0,8
o" 0,6
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              Table 9.   DYNAMIC  TOXICITY  TEST B —
                        MATERIAL BALANCE  ON COPPER
                        (BASIS 24 HOURS)
                  Copper ,
                    mg

Copper In         10,044

Copper Out

Overflow, liquid   2,253

Overflow, bacteria   956

Wasted, Bacteria   1,043

Total Out          4,252

In-Out             5,792
Copper
Accumulation

In Liquid

In Bacteria

Total
Accumulation
                    Copper.
                      mg
  848

5*048


5,896
                              134

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          Figure  55.
Dynamic toxicity test B,
copper accumulation in
aeration basin mixed liquor
0  3000
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miniplant, about 5800 mg of copper were accumulated In
the bacteria, resulting in an increase of copper concen-
tration from 656 to more than 4000 mg of copper per Kg
of dry bacteria.  The copper uptake rate by the bacteria
was very rapid during the first eight hours, reaching a
level of 3000 mg per Kg of dry bacteria.  A plot of the
rate of copper uptake versus the amount of copper adsorbed
by the bacteria (Figure 56) indicates a second order
reaction.  This shows that the reaction with copper was
controlled by the amount of respiratory enzyme available,
which was large at the start of the test, showing no
reduction in activity, then, at a point where most of the
enzyme sites were complexed with copper, sharply decreased
in activity.
                          136

-------
      Figure 56.
   Reaction order kinetics of copper
   adsorption on glycol-salt bacteria
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                        SECTION IX
  EFFLUENT QUALITY MONITORING AND INSTRUMENTS EVALUATION

An Ionics Model 225 Total Oxygen Demand (TOD) Analyzer and
a multiple stream selector were used to monitor the feed
to the activated sludge miniplant and the effluent before
and after chemical flocculation.

A schematic of the monitoring system is shown in Figure 57-
The five-stream selector was equipped with a four-stream
manifold for the three streams to be monitored and for a
standard solution used to calibrate the instrument response
once a day.  The feed stream was diluated 1:3 with distilled
water using a cassette peristaltic pump.  Gravity flow of the
effluent samples to the instrument resulted in plugging the
sample valves.  Filters were added in the sample lines and
pumping at a rate of 20 ml/min was necessary to maintain
the sample flow to the instrument.  The instrument was
calibrated daily with a 700 mg/1 TOD standard solution and
the gain adjusted for a 70-percent full-scale response.
The response that included the diluted feed and the effluent
samples concentrations was linear in the range of 100 to
700 mg/1.  The linear range of the calibration curve was
checked once a week.

The Total Oxygen Demand Analyzer and the Total Carbon
Analyzer, used for the control of nutrients addition and
F/M control, were quantitatively evaluated for their per-
formance during the periods of monitoring both fresh water
and salt water streams (8 to 10 percent NaCl).
                             138

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                               139

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PERFORMANCE OP THE TOTAL OXYGEN DEMAND ANALYZER
The instrument was operated in the laboratory for several
months before being installed in the miniplant.  The
precision of measurement of standard solutions was ±4 per-
cent in the linear range of 0 to 500 mg/1 TOD.  The rotary
sampling valve required frequent adjustments to prevent
leakage around the injection port and the drive gears for
the motor turning the valve failed early during the second
month of operation.  The gears were replaced under warranty
by the manufacturer at a cost of four hours labor and four
days downtime.

The instrument and the multiple stream selector were installed
in the miniplant and operated on fresh water samples for a
period of four months and on salt water samples for one month.
During the second week of operation, the printed circuit
card in the stream selector, containing a stepping switch,
failed and was replaced under warranty, resulting in three
days downtime and four hours labor.  This was followed by
several problems with the instrument, a failure of a control
card (two days of downtime), a failure of a power relay in
the combustion heater circuit (two days downtime), and a
failure of the balancing motor of the recorder (four days
downtime).  Numerous, short-duration downtimes occurred
for cleaning the rotary sample valve and adjusting its 0-ring
injection seal.  The oxygen sensor required adjustment of
electrolyte level (that affects sensitivity) as frequently
as twice a week and was disassembled for electrode cleaning
once a month.

A precision chart and a record of the time out of control,
downtime, and hours of maintenance labor were kept during
the continuous operation of the instrument.  A sample of
the precision control chart is shown in Figure 58 and a summary
                             140

-------
         Figure  58.
Precision control
TOD analysis
chart	
       Range - 45-65% Scale
       * = 0.05 0 =  0.05
        Full Scale = 1034 mg/1  TOD
        S  = 1.90% Scale
CM
-o
   -50
                  23456
               Day of Duplicate Sample, M

-------
of the performance of the instrument is given in Table 10
for the fresh water and salt water sampling.  The last month
of operation on salt water (8 to 10 percent NaCl) samples
proved to be very difficult.  The combustion tube was coated
with a salt glaze and carbon precipitated in the lines
between the tube and the oxygen sensor, plugging the sample
passage in less than four days of operation.  The combustion
tube was then slowly cooled to prevent its rupture and
replaced every four days.

PERFORMANCE OF THE TOTAL CARBON ANALYZER
The instrument was operated in the laboratory for a period
of three months, without incident.  The precision of measure-
ment of standard solutions was ±1 percent of the range of 0
to 300 mg/1 organic carbon.

Operated on the miniplant feed stream was once interrupted
by the failure of a heater element around the combustion
tube that was replaced under warranty.  For the purpose of
monitoring the total carbon of a homogenized sample from the
aeration basin, several controls were added to the analyzer.
The added controls included a sampling switching circuit, a
memory control, and a signal retransmission circuit.  Oper-
ation of the analyzer on the homogenized bacterial samples
caused frequent plugging of the injection valve until the
sample handling system was improved to include a backwashing
with the continuous feed sample.  Replacement of the injec-
tion tube below the slide valve with one of larger bore
resulted in significant loss of sensitivity.

A sample of the precision control chart is shown in Figure 59,
and a summary of the instrument performance is given in
Table 11 for the fresh water and salt water operation.
During the four months operation on fresh water sampling one
                             142

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Table 10.  PERFORMANCE OF THE TOTAL OXYGEN DEMAND ANALYZER
           (Ionics Model  225-Serial No.  357)
                              Fresh Water
                              4-mon. Per.
             Salt Water
             1-mon. Per,
Time in Control, %
Time Out of Control, %
Down Time, %
Maintenance Labor, hrs
62.5
35.4
 4.1
95
52.6
41.6
 5.8
20
                            143

-------
         Figure 59.  Precision control chart	
                     TC analysis
         Range - 44-55% Scale  Full Scale  = 690  mg/1  TC
         <* = 0.05  6 = 0.05    Sd = ±  3.67% Scale
CM
"O
1X1
  - 50-
  -100-
      0   1
23456789  10  11
  Day  of  Duplicate  Sample,  M
                          144

-------
   Table 11.   PERFORMANCE  OF  THE  TOTAL  CARBON  ANALYZER
              (Ionics  Model  1212-Serial  No.  1196-12)
                              Fresh Water
                              4-mon. Per.
            Salt Water
            1-mon. Per,
Time In Control, %

Time Out of Control, %

Down Time, %


Maintenance Labor, hrs.
82.2

14.3

 3.5


60
97.5

 2.0

 0.5
                           145

-------
Incident resulted in most of the downtime and 50 hours of
maintenance labor.  The loss of sensitivity and the mal-
functioning of the automatic zero electronic unit attached
to the infrared detector resulted in a need to overhaul
many parts of the instrument, including the infrared unit
adjustment to restore its optical balance.  Satisfactory
operation was restored only after replacement of the com-
bustion tube.  Apparently, the catalyst inside the tube had
fallen below the high temperature region and was the main
cause of the erratic results.

Operation on the high salt (8 to 10 percent NaCl) sampled
at 18-minute intervals was excellent for a period of three
weeks followed by a slow loss of sensitivity to the end of
the one-month operation.  This was due to accumulation of
salt within the combustion tube.

The slide injection valve was smoothed by grinding twice
during the one-year operation of the instrument.  Electrical
maintenance was limited to replacement of one wire in the
infrared unit, while the recorder and associated signal
conditioning circuitry required no maintenance during the
entire operating period.

Comparing the performance of the two analyzers, it was con-
cluded that;

1.  The slide injection valve of the TCA was more reproducible
    and required less maintenance to prevent leaking than
    the rotary valve of the TOD analyzer.

2.  The infrared unit of the TCA was far more accurate and
    precise than the oxygen sensor of the TOD analyzer.
                             146

-------
3-   The Hastelloy combustion tube of the TCA was  not sub-
    ject to thermal fracture as was  the  case with the
    quartz combustion tube of the TOD analyzer.

4.   Samples containing salt were difficult  for both analyzers
    to handle.   Somewhat better service  was expected with
    the TCA.
                             147

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                         SECTION X
               PROCESS DESIGN CONSIDERATIONS

The development of on-line control systems for the activated
sludge treatment process opens up many possibilities for
flexible and innovative process design.

The two most important automatic control systems that
could be incorporated in new plant designs are the biological
inhibition detection (BID) system and the F/M control system.
This is especially true for the design of facilities for the
treatment of combined domestic and industrial wastes, where
variations in the loading and the chemical composition of the
waste stream may be very large.  A typical domestic waste
may have daily variations in BOD from 10 to 250 percent of
the average value and flow rates may vary from 50 to 150
percent (Andrews, 1971).  When combined with the possibility
of slugs (or continuous flow) of industrial wastes where a
toxin to the activated sludge biota may be present, the need
for an inhibition detection system and an F/M control system
becomes readily apparent.

Figure 60 illustrates a conceptual design of an activated
sludge treatment system using these controls,

Equalization of the feed is very helpful for F/M control
and is a necessary part of the plant design.  Equalization
dampens fluctuations in the organic content, in flow, in pH
and in order physical-chemical characteristics of the feed
to the aerated basin.

As illustrated in Figure 60, the equalization tank is also
part of the feed-forward inhibition detection control system.
Equalization provides a time delay, together with dilution
of a possibly toxic feed during the biological activity
analysis period.

-------
 c
 O)
 E
•M
 
 o
 s-
-M
 C
 O
o
 QJ
 C7>

-------
A toxic feed would ordinarily be diverted to a holding basin
by the BID control system.  After determination of the chem-
ical nature of the toxin it could either be bled back into
the system or treated by other means.   Pre-treatment could
include chelation of toxic metals and  sorption of toxic
organics.

The F/M control system would include measurement of
flow and measurement of soluble organic concentration.  The
control system includes an aerated waste stabilization tank
which supplies additional microorganism recycle in periods
of high loading.  The stabilization tank may be located as
shown in Figure 60 or it may be located in the sludge re-
cycle line.  A pilot study would be useful in determining
which site is more adequate in terms of microorganism viability
and the effect on bio-flocculation in  the aeration basin.
For equal-sized stabilization tanks, a tank in the recycle
line would give the shorter hydraulic  residence time, which
would indicate a higher biota viability.  Having the tank
located in the waste line would produce a more stabilized
sludge, possibly aiding in bio-flocculation.

If the post-treatment step of chemical flocculation is used,
another alternative in F/M control is  possible.  If the sludge
from the floe-settler is viable, it may be used as the source
of additional recycle in periods of high loadings.  It has
also been shown that both the treatment efficiency and the
compactability of bulking sludge are improved significantly
with the addition of aluminum hydroxide to the mixed liquor
(Hsu and Pipes, 1973).
                             150

-------
Two possible sources of the feed sample to be used for
F/M control are shown in Figure 60.   The location used
for the experimental work in this study was in the feed
line to the aeration basin (see Section V).  Sampling from
this location allowed easy proportional control.

If the feed sample for F/M control is taken before the
equalization tank, F/M control will be more anticipatory
in nature with very short F/M response times.  The control
system could then include a mini-computer which would be
programmed to calculate the hydraulic effect that the equal-
ization tank will have on the feed flow and composition and
would affect F/M control on this anticipatory basis.  Hence,
extra sludge recycle could begin before the higher loadings
affect the aerated biomass.

Another available control system that needs to be incorporated.
into the plant design is an aeration-basin oxygenation sys-
tem.  Besides optimizing oxygen allocations, the system should
assure that proper agitation and micro-turbulence occurs so
that the various mass transfer processes can be optimized
(Kalinske, 1971).  The supply of oxygen to the stabilization
tank would also be controlled.

Nutrients and pH control would be provided for those processes
requiring them.  Tertiary treatment is necessary for
colloidal and suspended solids removal from the effluent.
Turbidity control would be provided for designs that employ
flocculation as the tertiary treatment.

OPTIMUM DESIGN OF AN AUTOMATED ACTIVATED SLUDGE PLANT
The design of the aeration basin volume needed for a specified
treatment efficiency is greatly affected by the incorporation
of the F/M control system.
                             151

-------
The choice of a steady-state model and the determination of
the kinetic coefficients and other parameters pertinent to
the chosen model are necessary in determining the aeration
basin volume.  A continuous pilot system is recommended for
determining this data.

The steady-state model may then be used to calculate the
required volume of the aeration basin as a function of other
design variables.  For examples a computer program using
the Monod model steady-state calculations (completely mixed
reactor) is presented in Appendix D and some of the design
relationships for the fresh water, propylene glycol system
are illustrated in Figure 61.  The sludge compaction data
(SVI) and the assumed recycle sudge concentration (Xr) are
obtained from the pilot study.  The treatment must be at an
F/M within acceptable SVI limits.  The aeration basin volume
(the hydraulic residence time multiplied by the influent flow
rate) is then a function of the recycle ratio.

The steady-state program also predicts the concentration of
microorganisms in the aeration basin and the cell production
rate, which at steady state is set equal to the wastage rate.

The aerated basin design should include evaluation of a
transient-state model of the system to determine the effects
that the suspected operational variations in loading will
have on the process.  The transient model permits optimum
design of the F/M control system, both in terms of control
action and stabilization tank volume.  System response times
can be determined to evaluate the adequacy of a given design.

The design  should incorporate mixing and dispersion parameters
obtained from actual equipment in order to insure that the
residence time distribution in the constructed system will be
                            152

-------
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to
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•t->
OO
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S-
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CD
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CD
LO
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                                Ts
           001
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                             Bouapisay
                          153

-------
the same as was assumed for the designed system (Irvine,
et al., 1973).  This may entail further transient-state
modeling to consider the possibility of a combination of
two or more biological reactors.

The final design of the aeration basin volume is dependent
on an economic evaluation of the alternative systems.  Items
to be considered include the reactor capital cost,  recycle
pumping costs, aeration and mixing costs, and control systems
costs.  The F/M ratio control costs include the stabilization
tank capital and the cost of aeration.  Benefits of stabiliza-
tion, such as decreased sludge handling costs because of
sludge digestion, must be taken into account.  The  benefits
of increased process removals must also be weighed.

It is clear that the availability of developed control systems
and of sufficiently accurate predictive modules will enable
more efficient, more economic, and more controllable activated
sludge systems to be built and to be operated at more closely
regulated effluent limits.  Sophisticated plants will require
more sophisticated operation.

Future plant designs will have to incorporate the best avail-
able technology.  Future plant operation will have  to reflect
the increased level of technology.  Both design and operation
depend upon the availability of sensors and the instrumenta-
tion necessary to use the sensed data to control the processes,

-------
                        SECTION XI

                        REFERENCES


Abson, J. W., C. D. Furness, and C.  Howe.   1967.   Development
of the Simcar Respirometer and Its Application to Waste Treat-
ment.  J. Inst. Water Poll. Cont. (British) 6:607-621.

Andrews, John F.  1971.  Kinetic Models of Biological Waste
Treatment Processes.  Biotechnol. and Bioenp;., 2:5-33•

American Public Health Association.   1971.  Standard Methods
for the Examination of Water and Waste Water, 13th Ed.   APHA,
New York.

Arthur, R. M.  1964.  An Automated BOD Respirometer.  Purdue
Univ. Eng. Exten. Series, Eng. Bull. 117:628-637.

Ayers, K. C. , K. S. Shumate, and G.  P. Hanna.  1965.  Toxicity
of Copper to Activated Sludge.  In:   Proc. 20th Indust. Waste
Conf., Purdue Univ., Lafayette, Indiana.

Banerji, S. K., B. D. Bracken, and B. M. Garg.  1968.  Effect
of Boron on Aerobic Biological Waste Treatment.  Purdue Univ.
Eng. Exten. Series, Eng. Bull. 132:956-965.

Earth, E. P., M. B. Ettinger, B. V.  Salotto, and G. N.  McDermott
1965.  Summary Report on the Effects of Heavy Metals on the Bio-
logical Treatment Processes.  JWPCF 37:86-96.

Benedek, P. and I. Horvath.  1967.  A Practical Approach to
Activated Sludge Kinetics. Water Res. 1:10.

Bisogni, James J. and Alonzo VI. Lawrence.   1971.   Relationships
Between Biological Solids Retention Time and Settling Character-
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Black, A. P., G. P. Singley, G. P. Whittle, and J. S. Maulding
1963.  Stoichiometry of the Coagulation of Color-Causing Organic
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Busch, A. W., and A. A. Kalinske.  1956.  The Utilization of the
Kinetics of Activated Sludge in Process and Equipment Design.
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Reinhold Publishing Company, New York.

Chen, Gilbert K., L. T. Fan, and Larry E.  Erickson.  1972.
Computer Software in Waste Water Treatment Plant Design.
JWPCF 44(5) :746-762.


                            155

-------
Chiu, S. Y., L. T. Fan, I. C. Kao, and L. E. Erickson.  1972.
Kinetic Behavior or Mixed Populations of Activated Sludge.
Biotechn. and Bioeng. 14:179-199.

Clark, J. W.  1961.  BOD for Plant Operation.  Water and
Sewage Works 108(2): 61.

Cleland, W. W.  1963.  The Kinetics of Enzyme-Catalyzed
Reactions with Two or More Substrates or Products.  In:
Inhibition:  Nomenclature and Theory.  Biochem. Biophys.
Acta 67:173-187.

DeVillaret, Foulques and David M. Himmelblau.  1973.  Kinetic
Modeling of Aeration Basins.  JWPCF 45. (2):292-302.

Eckenfelder, W. W., and D. L. Ford.  1970.  Water Pollution
Control.  Jenkins Publishing Company, New York.

Erickson, Larry E., and L. T. Fan.  1971.  Optimization of the
Hydraulic Regime of Activated Sludge Systems.  JWPCF 40(3):
345-362.

Fan, L. T., L. E. Erickson, P. S. Shah, and B. I. Tsai.  1970.
Effect of Mixing on the Washout and Steady-State Performance
of Continuous Cultures.  Biotech, and Bioeng.  12:1019-1068.

Ford, D. L., J. T. Yong, and W. W. Eckenfelder.  1966.  De-
hydrogenase Enzyme as a Parameter of Activated Sludge Activities
Purdue Univ. Eng. Exten. Series., Eng. Bull. 121:53^-5^3.

Forrest. W. W.  1965.  Adenosine Triphosphate Pool During the
Growth Cycle in Streptococcus faecalis.  J. Bacteriol. 90:1013-
18.

Forster, C. F., and N.  M. Choudhry.  1972.  Physico-Chemical
Studies on Activated Sludge Bioflocculation.  Effl. and Water
Tmnt. J. 3:127-131.

Gaudy, J., M. Ramanathan, and B. S. Rao.  1967-  Kinetic
Behavior of Heterogeneous Populations in Completely Mixed
Reactors.  Biotechn. and Biceng. 9:387-411.

Genetelli, E. J.  1967.  DMA ana Nitrogen Relationships in
Bulking Activated Sludge.  JWPCF 39:R37.

Gill, S.  1951.  A Process for the Step-by-Step Integration
of Differential Equations in an Automatic Digital Computing
Machine.  Proc. Cambridge Phil. Soc. 47:96.

Ghosh, M. M., and P. D. Zugger.  1973.  Toxicity Effects of
Mercury on the Activated Sludge Process.  JWPCF 45:425-433.
                            156

-------
Grieves, Robert B., William Milburg, J.  K.  Pipes,  and 0.
Wesley.  1964.  A Mixing Model for Activated Sludge.   JWPCP
36:5.

Hartmann, L., and G. Laubenberger.   1968.   Toxicity Measure-
ments in Activated Sludge.  J. ASCHE San Div. 94:247-256.

Hattingh, W. H. J.  1963.  Influence of Nutrition  on the
Respiratory Rate of the Mocroorganisms.   Water and Waste
Tmnt. 9(9) :424-426.

Hattingh, W. H. J.  1963.  The Nitrogen and Phosphorus
Requirements of the Microorganisms.  Water and Waste Tmnt.
8(8):380-386.

Herman, E. R.  1959.  A toxicity Index for Industrial Wastes.
Ind. and Eng. Chem. 51:84A-87A.

Hsu, Deh Y., J. K. Pipes, and 0. Wesley.  1973.  Aluminum
Hydroxide Effects on Waste Water Treatment Processes.  JWPCF
45(4):68l-697.

Irvine, Robert L., Robert T. Keegan, William D. Langley,
and Ronald C. Catchings.  1973.  Specific Removal  Patterns
in Activated Sludge System Design.  JWPCF 45(8):1771-1782.

Jones, P. H., and D. Prasad.  1969.  The Use of Tetrazolium
Salts as a Measure of Sludge Activity.  JWPCF 4l:R44l-449.

Kalinske, A. A.  1971.  Effect of Dissolved Oxygen and Sub-
strate Concentration on the Uptake Rate of Microbial Suspen-
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Kornegay, B. H., and J. F. Andrews.  1970.  Characteristics
and Kinetics of Biologically Fixed Film Reactors.   Env. Syst.
Eng. Dept., Clemson Univ., Clemson, S.C.

Lenhard, G.  1965.  Dehydrogenase Activity as Criterion for
the Determination of Toxic Effects on Biological Purification
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McLellan, J. C., and A. W. Busch.  1969-  Proc. 24th Ind.
Waste Conf., Purdue Univ., Lafayette, Indiana.

Monod, J.  1949.  The Growth of Bacterial Cultures.  Annual
Review of Microbiology, Vol. III.

Mulbarger, M. C., and J. A. Castelli.  1966.  A Versatile
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Operation.  Purdue Univ., Lafayette, Indiana.  Exten. Series
No. 121:322-337.
                              157

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Ottengraf, S. P. P., and K. Rietema.  1969.  The Influence of
Mixing on the Activated Sludge Process in Industrial Aeration
Basins.  JWPCF 41(8):R282-293.

Patterson, J. W., P. L.  Brezonik,  and H.  D.  Putnam.   1969.
Sludge Activity Parameters and Their Application to Toxicity
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Pippen, D. L.,  and G.  R. Kramer.   1973.   Metal Toxicity to
Sewage Organisms.  JASCE San Div.   97:161-169.

Ramanathan, M., and A.  P.  Gaudy,  Jr.  1969.  Effect  of High
Substrate Concentration and Cell  Feedback on Kinetic Behavior
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Ramanathan, M., and A.  F.  Gaudy,  Jr.  1971.  Steady-State Model
for Activated Sludge with Constant Recycle Sludge Concentration.
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Salotto,  B. V., E.  F.  Earth, W. E. Tolliner, and M.  B.  Ettinger.
1964.  Organic  Load and the Toxicity of Copper to the Activated
Sludge Process.  Purdue Univ.  Eng. Exten.  Series, Eng.  Bull.
117:1025-1034.

Sato, T.   1971.  The Toxicity of  Metallic  Ionics on  the Activated
Sludge and the  Detoxication Effect of EDTA.  Gifu Yakka Daigau
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Sawyer, C. N.,  and M.  S. Nicholes.  1939.   Activated Sludge
Oxidations.  I. Effect of Sludge  Concentration and Temperature
upon Oxygen Utilization.  Sew. Works. J.  11:51-59.

Schaezler, D. J., W. H. McHarg, and A. W.  Busch.  1971.  Effect
of the Growth Rate on the Transient Responses  of Batch and
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Sherrard, Joseph H., and Edward D. Schroeder.   1972.  Importance
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                             158

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Stack, V. T., Jr.  1957.   Toxicity of Alpha, Beta-Unsaturated
Carbonyl Compounds to Microorganisms.  Ind. and Eng. Chem.
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Storer, F. F., and A. F.  Gaudy, Jr.  1969-  Computational
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Stumm, Werner, and Charles R. D'Melia.  1968.  Stoichiometry
of Coagulation.   JAWWA 60:514.

Tenney, Mark W., and Werner Stumm.  1965.  Chemical Flocculation
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Tool, H. R.  1967.  Manometric Measurement of the Biochemical
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Tracy, Kenneth D., and Thomas Keinath.  1973.  Dynamic Model
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Wellens, V. H.,  and R. Zahn.  1971.  Untersuchungen iiber die
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Cont. Res. Series 12020.
                             159

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                       SECTION XII
                   LIST OF INVENTIONS

The following inventions are disclosed herein to the United
States Government.

1.   Biological Inhibitor Detector
The invention concerns the design and automation of a measure-
ment cycle to detect the presence of toxic or inhibitory mater-
ials in waste water fed to a biological process.  The measure-
ment cycle is based on measuring the dissolved oxygen in a
controlled biological reactor as a standard sample, a waste
water feed sample, and another standard sample are consecu-
tively added to the reactor.  A toxicity index or activity
ratio is calculated by comparing the oxygen uptake of the two
standard samples before and after the bacteria sample has been
exposed to the test sample.  The invented measurement cycle is
automated for repetitive monitoring of streams fed to a bio-
logical exidation process and can be used as a feed-forward
control to divert a toxic feed before the loss or inhibition
of the acclimated biomass.

2.  Sampling System for a Homogenizable Solid-Liquid Mixture
Solid-liquid mixtures, such as an acclimated bacteria in an
activated sludge aeration tank containing 2000 to 4000 mg/1
suspended solids, are diluted as necessary and homogenized
with a high-speed mixer.  The homogenized sample then enters
a stand pipe to be de-aerated, then flows by gravity to the
sample injection valve of a monitoring instrument, and into
the second leg of the U-shaped stand pipe.  This flow flushes
the sample valve, and upon injection of the homogenized sample
all of the solenoid valves on the U-shaped stand pipe are
de-energized to drain the excess sample.  This restores the
flow of a cobinuous sample of a clear waste water, e.g.
the feed through the system, thus cleaning the lines from
any residual from the batch sample.
                           160

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                        SECTION XIII
                          GLOSSARY

ABBREVIATIONS
COD     chemical oxygen demand
DO      dissolved oxygen
JCU     Jackson candle turbidity units
MLTC    mixed liquor total carbon
MLVSS   mixed liquor volatile suspended solids
N:C     nitrogen to carbon ratio
SVI     sludge volume index
TC      total carbon
TCp     total carbon of the feed
TC]y[     total carbon of the mixed liquor
TCA     total carbon analyzer
TOD     total oxygen demand
TODr    total oxygen demand removed
VSS     volatile suspended solids

MATHEMATICAL SYMBOLS
A       waste calibration constant in equation 10
B       waste calibration constant in equation 10
C       concentration of DO in a bacteria sample, mass/volume
Cs      saturation DO concentration in a bacteria sample,
        mass/volume
E       percent efficiency of substrate removal, 100 (S0-Si)/
        So
F       food concentration, mass/volume
F/M     food to microorganisms ratio or loading
(F/M)r  F/M "removed" or (S0-Si)/Xavg
k       substrate utilization kinetic constant—maximum
        rate of substrate utilization per unit weight of
        microorganisms, time"1
                              161

-------
kr      combined substrate biodegradation rate constant,
        volume/mas s • time
        microorganism decay coefficient, time"1
Ke      endogenous reaction rate constant , time"1
KLa     oxygen mass transfer coefficient,  time"1
Ks      half velocity coefficient, equal to the substrate
        concentration when the specific substrate utiliza-
        tion equals (1/2 )k, mass/volume
M       microorganism concentration, mass/volume
n       bio-settler efficiency, percent
Q       influent waste flow rate,  volume/time
R       recycle sludge flow rate,  volume/time
rr      oxygen uptake rate by microorganisms, mass/volume* time
S0      feed soluble organic substrate concentration,
        mass/volume
Si      soluble organic substrate  concentration in aeration
        basin, mass/volume
T       total bio-settler underflow rate,  volume/time
t       time
V       aeration basin volume
W       waste sludge flow rate, volume/time
Wmax    maximum waste flow rate, volume/time
X       concentration of microorganisms in aeration basin,
        mass/volume
Xavg    average microorganism concentration in aeration basin
        over a chosen time interval, mass/volume
Xe      effluent microorganism concentration, mass/volume
Xr      recycle microorganism concentration, mass/volume
X       growth yield kinetic coefficient,  mass microorganisms
        produced per mass of substrate utilized
Y       growth yield kinetic coefficient,  mass microorganisms
        produced per mass of substrate utilized
                             162

-------
                             SECTION XIV

                             APPENDICES


Appendix                                                    Page


A     Operation and Maintenance Manuals                     165

B     Calculations of Plant Performance                     175

C     Transient State Activated Sludge Computer
      Simulation                                            190

D     Steady-State Activated Sludge Computer Model          196
                                 163

-------
                         APPENDIX A
              OPERATION AND MAINTENANCE MANUALS

The automated activated sludge miniplant is operated
unattended but the instrumentation and control systems re-
quire certain routine maintenance and trouble shooting
practices that are detailed in this appendix.  The operational
procedures include some sampling collection and laboratory
analyses to check the control systems and assess the overall
performance of the process.

The details of the control systems applied to the operation
of the aeration basin are shown in Figure 12.  The automatic
shutdown system is detailed in Figure 62.  Operation and
maintenance of these systems are described under the approp-
riate subsection of this appendix.

START-UP PROCEDURE
The influent flow to the equalization tank was started a
day or two before plant start-up depending on the volume
and residence time in the equalization tank.   The stepwise
start-up procedurewas as follows:

1.  Prepare the required concentration of chemicals and fill
    the alum, caustic, acid, and nutrients tanks.  Turn the
    pov/er on to heat the furnaces of the total carbon and
    total oxygen demand analyzers.

2.  Add enough sludge to the aeration basin to obtain the
    desired mixed liquor suspended solids (MLSS) concentra-
    tion when the basin is full.  The source  of the sludge
    could be from the sludge recycle of a sewage treatment
    plant or a batch-acclimated culture previously prepared

-------
 2.   Adjusting the  set points  for  the  alum  and  caustic  flow
     rates
 3.   Checking the liquid level of  the  alum  and  caustic  tanks

 The surface scatter turbidimeter  required  infrequent replace-
 ment of the electrical fuse,  the  lamp,  and the meter relay
 lamp.

 The Total Oxygen Demand Analyzer, monitoring the  TOD in  the
 feed and effluents required the following  routine maintenance:

 1.   Changing filters to sampling  system once a week
 2.   Checking rubber tubing in the peristaltic  pumps
 3.   Checking leaks or plugging in sampling lines
 4.   Checking the rotary sampling  valve  for leaks  or plugging
 5.   Checking the stream  selector for proper operation sequence
 6.   Adjusting the  nitrogen flow and electrolyte level  in
     the oxygen detector of the instrument
 7-   Adjusting the  level in the instrument  scrubber, the
     detector current, and the automatic zero of the recorder
     for proper range of the signal
 8.   Replacing the  scrubbing and detector cell  solutions  once
     a week
 9-   Adjusting sample valve 0-ring clearance as necessary
10.   Replacing furnace tube with freshly prepared  catalyst
     at intervals found necessary  by the operation
11.   Changing the nitrogen cylinder when empty
12.   Replacing burned out light bulbs
                                165

-------
in drums by a fill-and-draw procedure.  Open the air
supply valve and adjust the air rotaraeters to the re-
quired flow so as to maintain 2 to 3 mg/1 dissolved
oxygen in the aeration basin.  A yellow springs oxygen
meter is used to measure the DO in the aeration basin.

When the head in the equalization tank is enough to
prime the feed-recycle pump, open all valves in the
recycle loop.  Turn the pH control on bypass and press
the start switch.  When recycle has started, set the pH
at the control point midway between the upper and lower
shutdown limits.  Slowly close the ball valve on the
pump suction until five inches of mercury vacuum is
shown on the gauge.   Open the acid valve and turn the
pH controller to automatic to start the acid flow.
Observe the rotameter to check the acid flow and when
the pH, as recorded, is in control, turn the pH bypass
off.

Start the feed to the aeration basin by turning the
set point on the pneumatic proportional controller at
the panel.  This controller is calibrated for maximum
flow of one gpm and is usually started at 0.5 gpm
depending on the concentrations of the influent and
MLSS in the aeration basin.

Check the temperature of the influent in the feed line as
it enters the aeration basin.  Control the temperature by
turning on one or several of the electrical heaters around
the feed line or diverting the feed through the cooling
tower to maintain the temperature required for the test
being conducted.
                        167

-------
As the overflow from the aeration basin fills about half
of the biosettler, start the sludge recycle pump.
The variable drive on the pump is adjusted to the desired
recycle flow rate.  The rate is checked at the inlet
to the aeration basin using a stopwatch and a one-liter
graduated cylinder.

Observe the biosettler as it overflows to the flocculator
and the last settling tank.  Control the overflow weirs
in the two settling tanks and remove the air trapped in
the lines to obtain a smooth gravity flow through the
flocculator and the last settling tank.  The total over-
flow from the biosettler is directed through the Hach
Surface Scattering Turbidimeter to the flocculator.

Put the Total Carbon Analyzer in service by turning on
the recorder switch, the timer switch, and the stream
selector switch.  Keep the stream selector switch on
Stream I (the feed) for a one cycle, then observe the
instrument and the sampling system operation through a
complete cycle.  The sampling system includes Stream II
(the bacteria sample) that is diluted, homogenized, and
pumped through to the instrument slide valve.

Check the nutrient pump for proper operation and flow.
The required flow rate of the nutrients  to obtain the
right ratio of organic carbon in the feed to the
nitrogen and phosphorus  in the nutrient solution  is
controlled by two variables.  One is the speed of the
nutrients pump that is adjusted manually.  The other is
the fraction of a  (30 seconds) cycle that the pump is
on.  This is automatically controlled by the feed total
carbon signal from the analyzer.
                          168

-------
10. Operate the plant with total recycle and no sludge waste,
    bypassing the F/M control system,  till the required
    steady-state concentration of MLVSS is reached.   Adjust
    the controller, at the panel, that receives the  F/M
    signal from the total carbon analyzer  to obtain the
    required flow rate of sludge waste.  This signal operates
    a three-way solenoid valve on the  sludge recycle line
    and opens it to the waste line for a fraction of a 60-
    second cycle.  The sludge waste flow rate is measured
    in a graduated cylinder at the wasted sludge drum.  The
    maximum flow of wasted sludge is controlled by a limit
    switch that should be set so the sludge wasted during
    a 24-hour period would not exceed  a precalculated
    maximum value.  This limit  switch guards against a
    washout of the bacteria in the event that the F/M
    control system fails.

11. Put the Hach Surface Scatter Turbidimeter in service by
    switching it on  and setting the range to record the
    turbidity of the biosettler overflow.  Open the  manual
    valves on the alum and caustic tanks, and start  the
    flocculator stirrer.  The flow of  the alum solution is
    controlled at the panel by adjusting the set point
    depending on the optimum dosage found by experiment.  The
    flow of the caustic  solution is controlled by setting
    the pH control system at the predetermined optimum pH
    (about 6.5).

12. Calibrate the Total Oxygen Demand  Analyzer using standard
    solutions setting the instrument zero at 5-0 on  the
    sensitivity dial.  Put the stream  selector in service by
    starting the sampling pumps and adjusting the stream
                             169

-------
    selector switches 1, 2, and 3.   Check the flow of all
    samples and the signals en the  recorder through one
    complete cycle.  Readjust the sensitivity of the instru-
    ment to obtain a feed TOD signal around 75 percent of
    chart.

PLANT OPERATION, SAMPLING, AND ANALYSES
The operation of the automated miniplant was limited to
daily and weekly routine checks of  the control systems.
The extent  of sampling and analyses depended on the experi-
mental design and the data required.  The objective of the
fresh water and salt water glycol feed tests was to evaluate
the control systems.  Accordingly,  data collection was limited
to those data necessary for this evaluation.

The influent pH-controller had a limit switch on high and
low pH that closed the feed valve to the aeration basin if
the pH got  out of control and opened it when the pH control
was regained.  The control points were set at 5.5 and 9.0
with the set point at an intermediate value of 7.8-  The
pH electrodes were checked with buffer solutions as frequently
as needed.   A twice weekly check was found to be sufficient.

The nutrient control system was checked by running daily
analysis of ammonia in the final effluent from the plant.
The dial setting on the nutrient pump was then readjusted
to minimize the residual ammonia in the effluent.  A daily
check of the amount of nutrients used was made by reading
the calibrated sight glass on the nutrients tank, where
each 3 mm was equal to one liter of solution.  Using a
nutrient solution of 1 percent ammonia and 0.1 percent phos-
phoric acid, normal operation of the plant consumed one tank
of 55 gallons every two weeks of operation.
                             170

-------
The food to microorganisms (F/M) control system required
daily attention and service.   The wasted sludge, collected
in a 55 gallon drum, was measured and samples for analysis
every 24 hours of operation.   The sludge recycle rate was
measured manually every day to check the performance of
the recycle pump and to verify the recycle and waste sludge
flow rates.  The sampling system to the total carbon analyzer
was cleaned daily to prevent  any solids accumulation in the
lines that could result in irregular analyses or even plug-
ging of the sample flow.

The flocculation control system required very little
attention.  If the turbidity  readings were recorded, the
24-hour results were obtained; otherwise, the indicator of
the instrument should be read and entered in the data book
daily.

The Total Oxygen Demand Analyzer, monitoring the feed and
effluents, had no controls that affected plant operation.
Calibration curves for this instrument and the Total Carbon
Analyzer were run once a week.  Daily, one standard was run
to check of the two instruments, and the span control was
reset if necessary.

Laboratory analyses were made daily as follows:

1.  Feed grab sample:  propylene glycol by VPC
2.  Aeration basin mixed liquor:  sludge volume index (SVI),
    Mixed liquor suspended solids (MLSS), and volatile
    suspended solids (MLVSS)
3.  Biosettler overflow composite:  MLSS, MLVSS, TOC,
    and ammonia
                             171

-------
4.  Final settler overflow composite:   MLSS,  MLVSS,  and
    TOC
5.  Sludge waste:  MLSS and MLVSS

A plant data sheet was posted daily showing the data
recorded by the instruments and the results of the labora-
tory analyses.

MAINTENANCE OF  INSTRUMENTS AND CONTROLS
The instruments used for control and monitoring the  oper-
ating parameters of the activated sludge miniplant required
strict routine  maintenance for good operation.  Sample
preparation and pretreatment was emphasized to minimize
downtime for non-routine maintenance.   Regular routine
maintenance practices for recorders and support equipment
are not covered in this text.

The influent pH-control system required the following routine
and non-routine maintenance:

1.  Inspecting and cleaning the pH-electrodes (once  a week)
2.  Calibration against high and low pH-buffer solutions
    (once a week)
3.  Checking the acid line and rotameter for any leaks (daily)
4.  Replacing defective electrodes (when necessary)
5.  Cleaning acid flow rotameter (once a month)

The Total Carbon Analyzer (Ionics Model 1212) used to
measure the TC in the feed and mixed liquor of the aeration
basin required daily checking of the sampling system besides
the following routine maintenance:
                             172

-------
1.  Checking the liquid level of the liquid gas separator
2.  Checking the gas flov; to the infrared analyzer
3.  Adjusting wattmeter for correct operating wattage
    (185 watts)
4.  Inspecting reaction chamber for oven heat
5.  Checking the sample slide valve for leaks
6.  Adjusting zero on the infrared analyzer
7.  Back-flushing of sample flow to analyzer (once every
    two days)
8.  Calibrating with one or two standards (daily)
9.  Running all of the calibration curve (once a week)
10. Replacing nitrogen cylinder when empty
11. Replacing distilled water for water rinse (once a week)

In cases of out-of-control instrument response the main
defective parts to check are:

1.  Sample injection valve - which may have to be dis-
    assembled, cleaned, and reground to prevent leaking.

2.  Reaction tube - which may have to be removed, and the
    catalyst and the injection tube cleaned.

3.  Infrared detector - which may require removal and clean-
    ing of the sample cell.

The flocculatlon control system, comprising the turbidimeter
and the alum and caustic addition, required very little
special maintenance:

1.  Draining the turbidimeter once a day to clean the solids
    accumulated at the surface.
                             173

-------
                         APPENDIX B

              CALCULATIONS OP PLANT PERFORMANCE

A computer program was developed to facilitate routine
data handling and to calculate parameters which describe
the miniplant performance.  The program was written in
Fortran IV language and a Xerox Sigma 5 batch time-sharing
monitor was used.

A sample data input form (#12) and the resulting computer
printout displaying the summary of plant performance are
presented.  The logic of the program is also given (#13 and
Definitions of symbols in the program can easily be related to
the data input sheet and the corresponding READ statements
and to the output printout and the corresponding WRITE state-
ments.  Material balances and parameters calculated have been
described in the literature (Zeitoun, et. al., 1971).

-------
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-------
                    TABLE  13.   COMPUTER PROGRAM FOR
                   CALCULATIONS OF PLANT PERFORMANCE
  1.000   1070  FORMAT<2X,*ECHO CHECK  ON  INPUT DATA'/)
  2.000  " 990  FORMAT<65X,'PAGE 3* //26X, • **SYSTEMS PERFORMANCE**'///
  3.000      Cl IX, 'LOADING ',14X,' REMOVAL' /,28X, 'THRU CLARIFIER* ,9X,
  4.000      C'THRU FLOCCULATOR' )
  5.000 _ 989   FQRMAT< 7X, » LBS/DAY  LBS/DAY    LBS/DAY  LBS/DAY',
  STOOU      C~»~~Wr  CFS7T5SY   DBS /DAY  %W*1           ~"
  7.000    988  FORMAT ( 1 5X, • /LBMLVSS' , 1 2X, • /LBMLVSS* , 16X, • /LBMLVSS' /1X,
  8TOOO      C»TC^73X7l^.273X7F5.3T5XTfT727^X7F5T3y2XyFSVl71X7F7.27
  9.000      CF5.3,2X,F5.1 >
  10.000   ~987  FORMAT* 30X, 'CARBON BALANCE1 /28X, 'ON AERATION I BASIN'/
  i 1.000      C16X, 'CARBON IN    CARBON  OUT  CARBON TO C02*>
~ T2 .uou — sus — FTjRMsrrnrxTTnra^yiJffY --- -LBSTDHY ------ CBSTTFAY— wr^Ti 7x7
  13.000      CF7.2,5X,F7.2,4X,F7.2,2X,F4.1/)
  14.000    985^ FORMAT(1X/,27X,' AERATOR PERFORMANCE' /34X7' AND* A
  15.000      C22Xj 'AERATION BASIN OXYGEN BALANCE' //I IX, • 02 SUPPLIED*,
  16.000      C8X,'02 TRANSFERED       EFFICIENCY' / 11X,'CFM    LB/HR»T"~"
  17.000      C7X,'KLA  CS*  LB/HR           %')   _ _      _
"~T8VODa    9aT4""FORMATT9X7F5".27T
  19.000    983  FORMAT<9X, '02 CONSUMED' ,25X, ' 02 CONSUMED'/
  20.000      C2X, 'BASED ON CARBON BALANCE         BASED ON 02=',
  21.000      C'A(L3S TOD REM/DAY) +3(VSS) ' 2X, • LBS/DAY   LBS/LB TC ' ,
  22.000      C'  REM', I 5X, • LBS/DAY     LBS/LB TC"REM'")
  23.000    982  FORMAT(2X,F5.2,9X,F5.2)
                                           * F ST
 25.000    949  FORMAT(6X,'FLOW   LBS/HR' ,4X,F8. 1 , 1 9X,F8 . 1 /1^2X,
 26.000       C'Gf9M',10X,F6.2,21X,F6.2)
 27.000    948  FORMAT<6X,'PH',18X,F4.1,23X,F4.1/6X, «TOC    PPM',
 23.000       C10X,F5. 1/22X,F5. 1/1 2X,' LBS/DAY' 5X,F6. 1,21 X,F6.1)
 29.000    946 FORMAT<65X,'PAGE  2' //23X, ' EQUILIZATION BASIN CONTENTS'//
 30YIKKJ - C^OX7^TE^P^Y5X7~'i:raTJTiy~I^^
 31.000       C4X,'DEG C ', 1 OX, ' GALLONS' , 1 OX, 'HRS ')
 32.000    945 FORMAT< 12X,F4.1,4X,F5.179X,F7.1,10X,F5.1//>
 33.000    899 FORMAT <29X,'PH  CONTROL SYSTEM* //4X, • EQUILI ZATION  BAS',
 34.000       C« IN' Y5X, 'AERATION BASIN INFLUENT     HCL ADDITION'/
 35,000       C12X,'PH', 13X,'HIGH PH   LOW PH  AVG PH ' ,9X, 'ML/MIN' /
 3Gr. 0 00       rrOX77^TT7r4X7F^VlV6X7F^VT7^X7F^VrV9^7F^71 775          ~~
 37.000    848 FORMATC26X, 'NUTRIENT ADDITION SYSTEM' //, IX,
 33.000       C 'FLOW FROM         CARBON' ,9X, • NUTRIENT ' ,14X, 'RATIOS' /
 39.000       C1X,'EQUILIZATION    FROM EQUILZ .', 3X, 'FLOW    COMPOSITION
 40.000       C'N'/1X,'    LB/HR'J9X,'LB/HR',6X,'LB/HR',3X,*%NH3»,4X,
 4^1 . 000 _ C_' %P',5X, 'C:N*,9X,* C t P* /3X,F7.2,5X, F8 . 3 ,6X,F5«3,2 X , F 5j^2^
 42"70(JG       C~3X,F4.2,2X,' 100": ',F4. l,4X7"*TOO: *,F47T77)
 43.000    8^5 FORMAT<23X,'F/M CONTROL SYSTEM* //2X, 'WASTE FROM EQUIL',
 44.000       C'IZATION    AERATION BASIN    RECYCLE  SLUDGE
 45.000       C/7X,' CONCENTRATION          MLVSS    TC


                                    176

-------
     Table 13 (continued)  .  COMPUTER PROGRAM FOR CALCULATIONS OP
                            PLANT  PEEFORMANCE -     -          -
 46.000      C'FLOW    MLVSS     FLOW'/3X,'GPM   PPM PG   PPM TC•,
 47.000      C'        PPM     PPM        GPM    PPM',6X,'GPM*/2X,
 48.000      CF4.2,3X,F6.1,4X,F5.1,6X,F6. 1 ,2X,F6.i /4X,F4 72*2X.F6'.Ij
 49.000      CF4.2/)
 50.000844"FORMAT<22X,'FOOD/MICROORGANISM RATIO (LOADING)'/~
 51.000      CIX,'FEED PG/',6X,•FEED TC/',6X,'LBS TC/DAY/»,5X,
 52.000      C »LBS TC/DAY/LB MLVSS»/rX7'AER~MLVSS•,5X,'AER TC*78X,
 53.000      C'LBS MLVSS',4X,'BASED ON MLVSS=»TC BUGS( 1 1 3/60) */1X,F4. 2,
"54TOaO	CTOX,F4.2,10X,F4.2,16X,F4.2//J
 55.000   795 FORMAT<26X,'AERATION BASIN CONTENTS'//1X,'TEMP  PH*,6X,

 57.000      C' AGE*/1X,*DEG C*,10X,*LBS*,6X,'GALLS    PPM    LBS',
 5870OO	CT»	PPM     LHS      DAYS1^~~
 59.000   794 |.-QRMATC1X,F5.1,1X,F4.1,3X,F8.1,2X,F7.I,2X,F6.I,
 £* /\"*"rtrt rt "" * **" "-1""™ ~^ f~f v1 J' i? £ ' yy"""«9l'r f«i^IA^r3»A^ OA > r O • c* ^
 61.000  _193_ F/jRMAT_( l x* ^x *x*f RECYCL?_   _   ^^RPf _J?_ME BASE^_ °J1* *	
 627660C9X,'SLUDGE   TC REM RATE  TOD R.R.'/2X>'RATIO      IN',      ^
 63.000   	C'FLUENT     INFLUENT* RECYCLED	VOLUME   CONSTANT  __C^_*_  __
 64.000      C' ONSTANT*~)                                                   E
 65.000   792 FORMAT<4X,*%',9X,'HRS»,14X,'HRS',9X,'INDEX*,6X,*1/MRS*,
67.000    791  FORMAT<_IX>F5. 1 *6X,F5. 2, 1 2X,
68.1000^       C//)
69.000    745 FORMAT <30X,» SETTLER DATA'//
70VOOO       C20X, TOVERFLOW» , IOX, » INFLOW
71.000       C • RATE ' , IPX* 'HOLDUP  T I ME
                                             .2>9X>F5.
                                                BOTTOMS
                                                            SLUDGE~r722X
                                            RATE • *6Xj,* DEPTH * / 1 5X,
 T2TTJOD
 73.000
 75.000
 76 .000
 77.000
          695 FORMATUX,•BIO-SETTLER',5X,F6.1,5X,F4.2,5X,F6.2,9X,F4.2,

             CF4.2,6X,F5.1///)
          696 FORMATT25X, »FLOCCULATI ON CONTROT. "SYSTEM* /7T7X7
             C'CAUSTIC     PH         ALUM',I OX,'OVERFLOW*/18X,
 78.UOO      C"'USUAaE*,I4X,fUSUAGE*,«X,i TURBIDITY*/I 9X7
 79.000      C'LB/HR',1 OX,•LB/HR',2X,•ML/MIN* *8X,•JCU*/I8X,F6.4,4X,
 80.000CF4.1,rX,F6«4,F6.1,9X/F4.17)
 81.000 	697_FORMAT<_1 IX,'FLOCCULATOR INFLUENT     FLOC-SETTLER OVER',
 82.000      C'FLOW      %  REMOVED•/18X7* LB/DAY* ,20X,* LB/DAY'76X7*TC»7"~
 83.000      C11X,F5.3,21X,F5.3,14X,F5.1/6X,*TOD*,10X,F5.3,21X,F5.3,
85.000
86.000
87.000
88.000
89 .00
             Cl4X,F5.1/>                                       ~
          645 FORMAT C1X,^/,27X, 'MICROORGANISM BAJLANCE ' /29X,
             C'ON AERATION BASIN' /)
          644 FORMATCIX, 'AVERAGE', 14X, 'VOLATILE SOLIDS FORMEp*,,
             C12X, 'RATIOS' /2X,IMLVSS',7X,» IN  BASIN  WASTAGE*,
             C   CLAR  QVERF LW   TOTAL     LBS  VSS/DAY/' /I X, 'PPM
90.000
91 •000^
92.000"
93*000_
947660"
95.000
               __             __                                 ____
             C ' S • , 3X, ' LBS/DAY' , 3X, • LBS/DAY' , 5X, • LBS/DAY ' ,4X, *LBS>DAY« ,
              3X,'MLVSS  TOC REM* )
          643 FORMAT
-------
      Table 13 (continued).  COMPUTER  PROGRAM FOR CALCULATIONS OF
                            PLANT  PERFORMANCE
   96.000   300 FORMAT < 65X7* PAGE" 1V/7T5X,
   97.000      C'GLYCOL WASTE TREATMENT MINIPLANT A-1656'///
   98.000      C14X, 'SUMMARY OF PLANT*,
   99.000      C'  PERFORMANCE FOR », 12, IX, 12, IX, I2///25X, • STREAM' ,
  100.000      C*  CHARACTERISTICS'/)
  lOi.QOO   299 FORMAT (13X, 'WASTE TO BASIN ___ 81 0_-SETTLE_R RECYCLE __ WASTE
  102.000      C ' -SETTLER' /14X, 'BASIN   EFFLUENT  OVERFLOW     SLU ' ,
  103.000      C'DGE   SLUDGE OVERFLOW'/)
  104.000   298 FORMAT (IX, 'FLOW  LB/HR • ,F7. 1 , IX, F8. 1 , 1X,F8, I ,2X,FJ3 . 1 ,
  105.000       C1X,F7.1,2X,F8.1)
  106.000   297 FORMAT(9X,'GPM    ',F5.2,3X>F6.2,3X,F6.2,4X,F6.2,2X,
  107.000       CF6.2,4X,F6.2)
  108.000   296 FORMAT UX, ' TC      PPM    • j LF5 . !_*_! 3X,F5 .1
  T697000~ 295"FOWMAtC6X,iLB/DAY •,F8.2,
  110.000   294  FORMAT < IX, 'REMOVAL  % • ,22X,F5. 1 ,23X,F5. 1 )
  IT 1 . 0<30~   293  FORMAT < 1 X, • TOD     PPM  '/F 7.1 * 1 2X, F6 . 1 , 22X, F6 . I )
  112.000   292  FORMAT <6X,'LB/DAY * ,F8.2> 1 OX,F8 .2,20X,F8.2)
  113.000   290  FORMAT<1X,'PH'.,13X,F4.1.»42X,F4.1)
  114.000   291  FORMAT C IX ^ '.REMOVAL  X ' ,22X,F5. 1 j.23X>F5 . U
  11 5.000   289  FORMAT < : 1 X> • TEMP  DEG C V, 3X, F5 . 1 ,4X,F5 . lV~4X* F5 • I * 23X,
  U6.000 _   CF5.D  __^        _  _            ___
  1 17.000   288  FORMAT < 1X/'PG',6X> 'PPM' >3X,F5. i74X,F5. U4X,F5. 1 *23X>
  118.000 __ ^P"5*1^  _______________            __
  TT9700Cr~~2~g7  F>JRMAT( 1 X, «~MLSS    PPM' > \ IX, F6. I ,3X,Fr6TT73X,F7. 1,TX,
         ____           __^
  121 .000    286  FORMAT<6X, 'LB/DAY' , 1 2X,F6.2, 3X,F6.2,3X,F7.2, iX,F7.2,
2  122.000      C3X,F6.1)
  123.000    285  FORMATOX,'MLVS    PPM' , 11X,F6. I ,3X,F6 . 1 , 3X,F7. 1 , IX,
  124.000      CF7.1,4X,F6.1)
  125.000    284  FORMATC6X,'LB/DAY',12X,F6.2,3X,F6.2,3X,F7.2,IX,F7.2,3X,
  126^000	CF6. \2	   			
  127.000    283  FORMATCIX,'RES     MRS',4X,F5.2,4X,F5.2,4X,F5.2,23X,
  128.000      CF5.2)                          		        _____
  1297000    282  FORMAT<1X,'NACL     %•,5X,F4.1)
  130.000    281  FORMAT<1X,'NAOH     %',5X,F5.2)
  131.000    278~TORMAT(IX,'ALUM  LB/HR' , SIX, F5. 3)
  132.000    277  FORMATC1X, 'BASE  LB/HR' , SIX, F5^j3)
  133.1300    276  FORMAT
                                   178

-------
     Table  13 (continued).   COMPUTER PROGRAM FOR CALCULATIONS  OF
                            PLANT PERFORMANCE
 143.000   494 FORMATX6F)
 144.00^   44J3 FORMATOrF)              		
 145.000   447 FORMAT POND  FROM POND*)
 146.000	446^ FORh!ATUX,«TOD',2X,F7.2,3X,F5.3,5X.sF7.2,3X,F5.3,2X,F5.1,
 147.000      C3X,F5.2,4XVF5.3,2X,F5.1///)
 148.000   442 FORMATOX,' SLUDGE AQEt * >F6.2> 'MRS. '/) 	
 149.000       READ<1,502>MTH,IDAY,
 1 50.000       READ< 1 >500)HEWFLV>yOLCP.»DENSj ,TOC1 *OH1 *CHL1 ,PH1 *TCP2	
 T5UOOO       REXDCPWFLW.» TINBAS*TOC2,DENS2, PJi2^HA8H,PHABL>TAB,
 TSTTOTOO"CSMETEH
 154.000       READC1,497)VOLAB,SS4,VSS4^PDVSS4>TOC^>DENS4,PHAB
 T55.000	READ(l,496>TOC5>SS5,VSS5,DENS5>SLDEPii,SLDEPF>TCL*PH5
 156.000       READ<1,495)FALUM,FNAOH,PHFL*TURBT2,TOC7,DENS7.,SS7,VSS71,
 1577000
 158.000       READ
 188.000       ABVFLW=CPVFLW+CSVFLW
 190.000       RX=RR/100.0  __


                                   179

-------
    Table 13 (continued ).
                           COMPUTER PROGRAM FOR CALCULATIONS OP
                           PLANT  PERFORMANCE
 191.000
 192.000^
 193.000
 194.000
 195.000
 196.000
T97.00O
 198.000
 I99TUOO"
 200.000
 2017000
 202.000
                      	            (1.0+RX)
               TOCFI=ABWFLW*TOCI*24.O/1.OE6
               CODI = (COD2-KRX*COD4))/( 1 .0+RX)
               CODFI=ABWFLW*CODI*24.071.OE6
               WSS6=
               V5STB= CW55TB* F • OE6 57 CABWFl.W*Z4VO )
               CVFLWa
204.000
205VOOTJ
206 . 000
2077000
2 08.000
                                       . OE6
               WVSS4=(CWFLW*VSS4*24.0)/1 .OE6
               RSTAB=< VOT-AB/ < ABVFLW*60 . 0 >T
               RSTABS»< VOLAB/ < CPVFLW*60 . 0 ) )
               WTAB=WLAB^*8 . 34*DENS4~762.~5
               S S A B a(WTAB*S S4)/l . OE6
 210.000
 211.606 C
 212.000
 213.000
 214. OOP
~2 1 5701TO
               AIRFLW=j/6^J  _  ____ ___ ___________
 2 27.000     "~~RSTC=50 . / < CVFLW*60T)
 228.000_      TOCRC=TOCF2-TOCF5                           __
 229.000       TOCPRC=(TOCRC/TOCF2)*100.0
 230.000       BOTFLV^CSVFjLW+CVSLUG
 235.000 C     FLOCCULATOR
 232 .pj)0_j; __ CHANGE ML/MIN TO LB/HR USING ALUM DENSITY 4Q.»OOOMG/LITER
 233.000       FALUMW"=FALUM
 234.000 ________ FALUM=FALyM*60.*40./(454.*1000. ) ____________ ________________      __
 235.000       TEWFLW=»FWFLW
 236.000 _____ TEVFLWa'TEWFLWjtt62.5/<8.34*DENS7*60.0)         ______
 237.000  ~ ~ ~  toCFT=(fEWFLW*TOC7*24. )7l.OE6
 238.000       WSS7=(TEWFLW*SS7*24.0)/1 .OE6
                                   180

-------
    Table  13 (continued).   COMPUTER PROGRAM FOR CALCULATIONS  OP
    	~    PLANT PERFORMANCE
 239.000       WSS7=*/1 . OE6
 240.000 	    FVSLUQ=(FWSLUG*62.5)/<8.34*DENS8*60.>
 241.000       FOVFLW3/1.0E6
 249.000       CWVSS»WSVSS6+WVSS5
 250.000       DWVSS»
 251.000       AVWVSSs/1.0E6
 252.000^       SLDAGE=AVWVSS/(WVSS5+WSVSS6)
 253.000       TOC2L=TOCF2/AVWVSS
 254^000 ____ RTOCCa
 258.000       RSLUG 1 =DWVSS/AVWVSS
 259.00"0       RSLUG2=DWSS7*1 00.~ ~
278.000	REMVTDaC 500)HEVFLW,VOLCP*DENS1,TOC1*OH1,CHL1*PH1,TCP2
283.00CT       WRITEX: 3^4991 SV3/PERNH37PERPHO>FO^01THCLFLWyTUR8TI
284.000       WRITE(3,498)CPVFLW,TINBAS>TOC2,DENS2>PH2>PHABH>PHABL*
                                   181

-------
    Table  13 (continued).
                           COMPUTER PROGRAM FOR  CALCULATIONS OF
                           PLANT PERFORMANCE
 285.000
 286.000
             CTA8,SMETER
              V/RITE<3*497WOLAB*SS4,VSS4,PDVSS4,TOC4,DENS4,,PHAB
 288.000
 289.000
 290.000
~29iVOOO
 292.000
              WRITEC 3*^195 >FALUMW,FNAOH,PHFL*TURBT2>TOC7*DENS7,SS7,
             CVSS7,TFL~
              VRITE< 3 , 494) SCSVFL, SCVSLU, SS6^VSS6,DENS6> WFLV
              WRIT EC 3T4W>COD2^'J^
              CALL PA6E<3>
293.000
294.000
               WRITE<3,300)MTH,1DAY^IYR
               WRITEC3,299>
 295.000
 296.000
 297.000
 298.000
              WRITE<3,298)CPWFLW,ABWFLW,FWFLV,CSWFLW,CWSLUG,TEWFLW
              WRlfE(3*296)tOC2,tOC5,tOC7
              WRITE<3,295)TQCF2*TOCF5jTOCF7
 300.000
 302.000
 303.000
 304.000
~3 057000
 306.000
 307.000
 308.000
"3097OOO
 310.000
              WRITE<3*293)COD2>COD4,COD6       ___
              WRITEr3,292)CODF2VCODF4,CODF6          ~"~
              WRITE<3^291 )CODPRC,CODPRF
              WRITEDENS2,D£NS4,DENS5,D£NS6>DENS67DEN57
              WRITE<3>290)PH2,PHFL
 31 1 .OOO
 312.000
 314.000
 31T. 000
 316.000
 317. ODD"
 318.000
 31 9. 000
 320.000
 3 21. 000
 322.000
 323.000
 324.000
 325.~000
 326.000
 327.000
 328.000
 329. OOO
 330.000
              WRITE< 3*289 )TINBAS>TAB,TCL*TFL
              WRITEC3,288)PG2*PGAB,PG47PG6
              WRITE(3>287)SS4,SS5,SS6,SS6,SS7
              WRITET3T256)^S54; WSS57V5S6TW 55^6^557
              WRITE<3*285)VSS4>VSS5>VSS6,VSS6,VSS7
              WRlTEr37^84)WV554,WVS55*WVS567W5VS
              WRITEC3,283)RSTABS>RSTAB,RSTC*RSTF           ___
              WRITE<37282)CHL1
              WRITE<3*28l>OHl
              WRir£(3V278)FALUM
              WRITE<3,277)FNAOH _          _
              flH rTET3T276~TSinpr
              WRITE(3,275)SV3
              WRITE<3*745)
              yRITE<3,695>COVFLW,FWLW,RSTC,BOTFLV,SLDEPB,FOVFLW,
             CTEVFLWjrTlSTF^                    "~"    ~
              CALL PAGE<3)
              WRITEO,^^
             _WRITE<3J,945^
              WRITE (3, 795 >
              WRITE (3,794) TAB ^PHAB,WTAB,VOLAB,SS4,SSAB>VSS4,VSSAB,
             CSLDAGE
              WRITE<3,793)
              WRITEC3,792)                    ~~
              WRITEC3,791)RRJRSTABS,RSTAB,SVI4,RTOC,RCOD
                                  182

-------
      Table  13  (continued) .   COMPUTER PROGRAM FOR CALCULATIONS OP
                            PLANT PERFORMANCE

 331.000       WRITEC3,987>
 332.000       WRITE(3^986>CIN,COUT,DELTAC,PCC02
 333.000WRITEC37985)
 334.000	VRITE(3,984)AIRFLV
 335. OODWRTT£T37913r3>~
 336.000       WRITEC3*982)RATE02*R02TOC   	
 337.000       WRITE<3>645~)
 338.000       WRITE<3,644)
 339.000       WRI TEC 3*643 >AVVSS,AVWVSS,ABVSS,WSVSS6,WSS5,DWVSS,
 340.000 _ CRSLUG1*RSLU62
"341.000       CALL PAGE<3>
 342.000       WRITE(3,990)          _    _
               WRITET3>959~)         "
 344.000       WRITE(3^988^TOCF2>TOC2L*TOCRC>RTOCC>TOCPRC*TOCRF,RTOCF>
 346.000       WRITE<3,446>CODF2,COD2L>CODRC,RCODC,CODPRC,CODRF,RCODF,
 348.000 _   WRITERS, 899 )PH I, PHABH,PHABLjLPH2*HCLFLW
 349. 000"     "~WRITE< 3,848yCPWFLW,tOCF2H*PDNOT*PERNH37PERPHO, CN,CP
 350.000       WRITE<3,845 >CPVFLW,PG2,TOC2*VS^^TOC4^,CSVFLW^VSS6
 351.000       WRITE<3V844)RPGVS4yFDARTC,TOC2L,TOC2LC :~"
 352. 000 _ WR I TE ( 3,696)FNAOH
-------
  Table  14.   SUMMARY  OF PLANT PERFORMANCE	
              June  18,  1973
              Glycol Waste Treatment MIniplant
              A-1656

            STREAM CHARACTERISTICS
WASTE TO BASIN   BIO-SETTLER
 RECYCLE  WASTE  FLOC-SETTLER
""SLUDGE	SUJETGEr WERFLTW	
FLOW LB/HR
GPM
TC PPM
LB/DAY
REMOVAL X
TOD PPM 1
LB/DAY
REMOVAL %
DENS LB/FT3
PH
TURB JCU
TEMP DEG C
PG PPM
MLSS PPM
LB/DAY
MLVS PPM
LB/DAY
RES HRS
NACL Z
NAOH 2
ALUM LB/HR
BASE LB/HR
SVI
SV MLS-30MINS
249.9
.50
473.0
2.84
511.0
9.06
62.4
6.5
30.0
680.0

8.33
.0
.00


370.0
.74



62.4
30.0
.0
2188.0
19.43
2044.0
i^7T5~~
5.63


146.3
320.0
240.8 120.1 9.1
.48 .24 .02
41.0
.24
91.6
93.0
.54
94.1
62.4 62.4 62.4
30.0
.0
.0
15.0 5889.0 5889.0
.09 16.98 1.29
13.0 5818.0 5818.0
.08 16.77 1.27
1.13



24078
.48
19.0
.11
96.1
85.0
.49
94.6
62.4
6.5
2.0
.0
.0
.0
.0
.0
.0
1.73

.062
.000

                  SETTLER DATA


BIO-SETTLER
FLOC-SETTLER
OVERFLOW
RATE
GAL/FT2/DAY
1 13.8
1 13.8

GPM
.48
.48
INFLOW
HOLDUP TIME
DAYS
1.13
1.73
BOTTOMS
RATE
GPM
.26
.00
SLUDGE
DEPTH
INCHES
14.0
30.5
                     184

-------
     Table  14 (continued).   SUMMARY OP PLANT  PERFORMANCE	June 18,  1973
                        EQUILIZATION BASIN CONTENTS
             PH
             6.5
             TEMP      LIQUID INVENTORY HOLDUP TIME
            DEC  CGALLONS           MRS
                .0           2580.0            86.0
 TEMP
 DEC C
  307TT
PH~
                           AERAT1ON BAS1N CONTEMTS
 AERATED" LIQUID
 LBS      GALLS
_2UHJ_7
                                     MLSS
                                   PPM    LBS
                                      ~.U2tT5
MLVSS
                                                   LBS
            SLUDGE AGE
                DAYS
 RECYCLE
""RATIO
    %
~~4~8~.~l
      ^lOLDUP
    TNFLUENT
      HRS
     8.33
                           BASED ON      ___ SLUDGE
                         INFLUENT+RECYCLE   VOLUME
                                MRS      __ INDE.X_
                               5.63         146.3
7C REM_RATE_
 CONSTANT
  I . 264
             TOD R.R.
            "CTlNSTANT
             1/HRS	
            T7830
                               CARBON BALANCE
                          	ON AERATION BASIN	
                CARBON  IN"   CARBON OUT  CARBON TO C02
                 LBS/DAY      LBS/DAY    LBS/DAY   %WT
                                  ^^        r^   ^T-^



                            AERATOR PERFORMANCE
                                   mD-                            .       .

                      AERATION BASIN OXYGEN BALANCE	

           02 SUPPLIED         02 TRANSFERED        EFFICIENCY
           ^...^   LB/HR        KtA- - CS*~ LB/HR           %


         02 CONSUMED                          02  CONSUMED
  BATS ED ON~CSnRBOW~BArffNCE	BASED ON~Tj2=A(LBb TOU HKM/UAY>-fB< VSS;	
 LBS/DAY   LBS/LB TC REM                LBS/DAY     LBS/LB TC	
   5.672.18                    """


   	MICROORGANISM BALANCE	
                             "OFTAElWriON BA^IN

 AVERAGE              VOLATTLE~~SOLTDS" FORMED             RATIOB
  MLVSS       IN BASIN  WASTAGE  CLAR OVERFLW    TOTAL    LBS VSS/DAY/
-DPM    tB^   LBS7DAY   LBS/DAY     LBS7DAY~   LBS/DAY"   MLVSS TOC~REM
 1910.0 4.0    .56      1.27         .08         1.91      .48   .73
                                   185

-------
    Table 14 (continued)
                          SUMMARY  OP  PLANT  PERFORMANCE-—June 18, 1973

                          **SYSTEMS PERFORMANCE**
TC
TOD
      LBS/DAY  LBS/DAY
              /LBMLVSS
        2.84     .714
        9.06   2.279
                             "REMOVAL
                         THRU CLARIFIER
                        LBS/DAY   LBS/DAY  %WT
                                 /LBMLVSS
                          2.60     .654    91.6
                          8.52    2.144    94.1
                      THRU FLOCCULATOR
                     LBS/DAY   LBS/DAY  *WT
                               /LBMLVSS
                     ~ 2.73.68696.1
                       8.57     2.156   94.6
   EfiUILIZATION BASIN
  	PH       ~
          6.5
                             PH  CONTROL SYSTEM
                          AERATION  BASIN INFLUENT
                          HTefl"PH~   Lw~pir~~svsrnp!
                             7.1        6.1     6.5
                                                     HCL ADDITION
                                                    	HU7MTNT-
                                                             .0
                         NUTRIENT  ADDITION SYSTEM
FLOW FROM
EQUILJZATION
   LB/HR
   249.90
               CARBON     "    NUTRIENT
             FROM EQUILZ.   FLOW    COMPOSITION	
               LB/HR      LB/HR    %NH3    %P     C:N
                 .118      1.576     .53    .07  100: 5.8
                                                       RATIOS
                                                                C:P
                                                               100:   .9
 WASTE FROM EQ U I L I ZAT ION
GPM
.50
        PPM PG
         680.0
                  PPM  TC
                   473.0
AERATION BASIN
 MLVSS	TC	
  PPM"     PPM
 2044.0   836.0
RECYCLE SLUDGE
 FLOW   MLVSS_
  GPM"   PPM
  .24  5818.0
                                                                 WASTAGE"
GPM
 .02
FEED PG/
AER MLVSS
 .36
                     FOOD/MICROORGANISM RATIO (LOADING)               	
              FEED  TC/LBS TC/DAY/     LBS TC/DAY/LB MLVSS
              ASR TC         LBS MLVSS   _?ASEiD ON MLVSS=TC J3UGS( U ^/6jD>
                ."57            .71                  .87
                         FLOCCULATION CONTROL SYSTEM
CAUSTIC
USUAGE
LB/HR
.0000
PH

6.5
FLOCCULATOR INFLUENT
LB/DAY
TC .237
TOD .537

ALUM
USUAGE
LB/HR ML/MIN
.0624 11.3
OVERFLOW
TURBIDITY
JCU
2.0
FLOC-SETTLER OVERFLOW % REMOVED
LB/DAY
.1 10
.491
8.6
                                 186

-------
The intput data needed for the execution of this program
are:
CARD NO. 1
V       -
Q       -
SPEED   -
SFEED2  -

RECY    -
W       -
XR      -
KSUBS   -
YIELD   -

KENDOG  -
           aeration basin volume (gallons)
           influent feed flow rate (gpm)
           initial influent feed concentration, (mg/1 TOD)
           influent feed concentration after step change
           (mg/1 TOD)
           recycle flow rate (ml/min)
           waste flow rate (ml/min)
           return sludge concentration (mg/1 MLVSS)
           half velocity coefficient (mg/1 TOD)
           growth yield coefficient (Ib VSS formed/lb TOD
           removed)
           microorganism decay coefficient (day-x)
CARD NO. 2
XSTEP   -  time at which feed concentration is changed
           (hours)
XF      -  time at which simulation ends (hours)
H       -  stepsize (hours)
INT     -  frequency of data output desired (real-time data
           output every H*INT hours)

CARD NO. 3
Y(l)    -  initial substrate concentration in aeration basin
           (mg/1 TOD)
Y(2)    -  initial microorganism concentration in aeration
           basin (mg/1 MLVSS)
CARD NO.
FACTOD  -
FACVSS  -
           conversion factor (mg TC/mg TOD)
           conversion factor (mg TC/mg MLVSS)
                              18?

-------
CARD NO. 5
LOPT    -  simulation option:    enter 0 for no F/M control
           enter 1 for F/M control
AA      -  constant for waste  calibration (see Equation. 10)
BB      -  constant for waste  calibration (see Equation 10)
WMAX    -  maximum waste flow  rate allowable,  (ml/mln)

Mini-plant kinetic data was obtained in terms  of MLVSS  and
TOD.  Since the F/M control action was in terms of total
carbon, it was necessary to have conversion factors FACTOD
and FACVSS.  The theoretical FACTOD conversion factor for
propylene glycol is 0.28.  However, the number entered  into
this program should be the actual conversion factor based on
the operation of the TC and TOC instruments.  Similarly,
FACVSS should be the conversion factor from MLVSS to MLTC
using values from on-line total carbon analysis (FACVSS is
theoretically equal to 0.53 for cellular formula CSH702N.)

The program and a sample printout are given in Tables 15 and
16, respectively.
                              188

-------
                         APPENDIX C
                 TRANSIENT STATE ACTIVATED
                 SLUDGE COMPUTER SIMULATION
A computer program was developed in order to predict
transient changes in microorganism concentration, P/M
and aeration basin substrate concentration to step changes
in loading.  The program logic uses the Monod type kinetic
equations which are incorporated into the unsteady-state
material balance equations (Equations 8 and 9).  The
P/M control is included in the program logic.

The computer program consists of the main program SIMUL,
the logical function RKG, and the subroutine PXY.

The main program includes all the input (READ) and output
(WRITE) statements.  It also includes a calculation of
the initial steady-state microorganisms concentration (XSTST)
and the initial aeration basin substrate concentration (SONE)
by using Monod kinetics.  When inputting plant data, this
calculation shows how close the process is to the theoretical
steady state.  The equations used are discussed in the litera-
ture (Lawrence and McCarty, 1970).

The material balance differential equations are solved in
logical function RKG by using a fourth-order Runge-Kutta
method with Gill's coefficients (Gill, 1951).  The actual
derivative evaluations are done in subroutine PXY.  Function
RKG also includes the P/M control logic.  Counter ICNT in
function RKG permits transfer to the main program for data
output.
                              189

-------
               TABLE 15.  TRANSIENT-STATE ACTIVATED SLUDGE,
                         COMPUTER PROGRAM
1.000 C
2.00O~C
3.000 C
4.OOO
5.000
6.000
7.000
8.000
9.000
10.000
11.000
12.000
13.000
14.000
15.000
16.000
17.000
18.OOO
19.000
20.000
21.000
22.000
23.000
24.OOO
25.000
26.000
27.000
28.000
29.000
30.000
31.000
32.000
33.000
34.000
35.000
36.UUU
37.000
38.000
39.000
PROGRAM SIMUL
TRANSIENT STATE ACTIVATED SLUDGE SIMULATION
DIMENSION Y(2),F(2)
REAL K,KSUBS, KENDOG
COMMON V, 6, SFEED,R,XR,K,KSUBS, YIELD, KENDOG, COMPAC
5 FORMAT(HF)
6 FORMAT<25X,'F/M CONTROL TEST SIMULATION'//)
7 FORMAT <22X,' BLANK SIMULATION - NO F/M CONTROL'//)
LOGICAL RKG,LOGRKG
8 FORMAT(27X, 'KINETIC MODEL CONSTANTS' /14X, 'K,l /DAY',
1' KSUBS,MG/L TOD YIELD KENDOG, I /DAY'/
2l5X,F4.1,7X,F6.1,llX,F4.2,5X,F5.3//)
9 FORMAT( IX, 'INPUT VALUES* V6X, 'AERATION BASIN VOLUME',
1' =', Ell. 4,' GALLONSV6X,' INFLUENT FLOW RATE = ',
2E11.4,' GPM'/6X, 'BIO-SETTLER UNDERFLOW »',E11.4,
3' ML/MIN' /6X, 'INITIAL RECYCLE FLOW a',Ell.4,
4' ML/MIN (RECYCLE RATIO =»' ,F6. 3, ')' //4X, * INITIAL *,
5'CONDITIONSt'/6X, 'AERATION BACTERIA =',F8.1,
6« MG/L MLVSS (*,F7.1,» MG/L TO '/6X7* SLUDGE BACTERIA',
7' =',F8.1,» MG/L MLVSS C,F7.1,' MG/L TO'/
86X,'BIO-SETL OVERFLOW TOD =',F8.l,' MG/L TOD (AER*,
9'ATION SUBSTRATE CONG) '/6X, • INFLUENT WASTE CONC. =»',
1FS.1,' ML/L TOD C,F6.l,' MG/L TO'//
16X,' SLUDGE COMPACTION RATIO =',F5.2,' MG/L SLUDGE PER'
2,' MG/L BACTERIA' /6X,'TC CONVERSION FACTOR = *,
3F5.2,' TC/MLVSS'/6X,'TC CONVERSION FACTOR »',F5.2,
4' FEED TC/FEED TOD' //6X, • INITIAL F/M LOADING »',
5F5.3,' TC/TC'///' INITIAL STEADY STATE VALUES AS CAL',
6*CULAT£D BY THE KlNETtC MODELt »/lX, 'MIXED LtGUoR SUB»,
7'STRATE CONCENTRATIONt',F6.l,' MG/L TOD OR',F7.1,
8' MG/L TC'/IX, 'MIXED LIQUOR BACTERIA CONCENTRATION* ',
9F7.1,' MG/L VSS OR',F7.1, ' MG/L TC'////6X, 'TIME AT',
" 1* WHICH LOADING IS CHANGED J *,F8.1, • HOURS »/6X,
2'NEW (T»',F4.1,') INFLUENT WASTE CONC«',F8.1,
3» MG/L tOD <*,F5.G,' MG/L TO'//)
10 FORMAT(4G)
15 FORMAT (2F)
16 FORMAT (20X,« ACTIVATED SLUDGE TRANSIENT SIMULATION'//)
 41.000
 42.000
 43.000
Tl4.OOO-
 45.000
 46.000
 47.000
 rrTORMArc2F>
 18 FORMAT(4G)
 19 FOHMAT<*TlM£   BACTERiA,MU/L.  i>UH5»l hATE  MlXt.U
   1'LIQ F/M  RECYCLE  WASTE    WSUM'/'HOURS  M',
  2rLV5S   TC     TOD,  MG/t   MG/L TC  TC/TC^T
  3'   ML/MIN  ML/MIN  GM VSS')
"20 FORMAT(F5. 1 ,F8. 1 ,F7TrnxVT8TT73X,Fffi 1,
   1F8.3,1X,F7.1,F8.1,1X,F7.1)
                                 190

-------
     Table  15  (continued).   TRANSIENT-STATE ACTIVATED SLUDGE
                           COMPUTER PROGRAM
  49.000
 -507000
  51.000
  52.000
  53.000
  b4.0UU C
  55.000
READV,Q,SFEED,SFEED2,RECY>W,XR,K>KSUBS,YIELD*KENDOG
READTITTO T) X5TE*, 'XFTK. INT
READCU15>YU>,Y<2)
READ<1.»18>LOPT.,AA,BB<»WMAX
  56.OOO
  57.000
  bS.UUO
  59.000
  60T001T
  61 .000
  527000"
  63.000
 -54700IT
  65.000
RsRECY/	
  7T).000       SONE»-1.)
~T^700D       XSTSTa < Yl ELD* C 5FEW-3WE5 vriiETA5">7"
	73.000      1 «1.+KENDOG*THETAC)*THETA)	    	
^T47000       SOTjETC>SONE*F~ACtOD
  75.000       XSTSTC=XSTST*FACVSS   	      	
-"757000       ^TCB^?r2T*FACVS"S
  77.000  	TCF=SFEED*FACTQD      	
  78.000XRTC=XR*FSCV53
  79.000 C	         		
  807000WRITE<3*T6)
  81.000       IF~
  85.000    26 K=K*24.               	
~B 67000       KENDOiG=kENDOG*24 .
  87.000	WRITE<3,8)K*KSUBS*Y1ELD,KENDOG
  88.000K=K/24.
  89.000	KENDOG»KENDQG/24.	         	
"90.000       9^5760^  ~    ~~  ~~   ~                        ~
  9J^±000	WRITE<3*9)V,Q*T,RECY,Rj,YC2)*TCB*XR,XRTC*YCl >_,SFEED*TCF»
  92.000     lCOI^ACVFACVSSVFACTOO«FMLOAb'
 J93.000	2XSTEP,XSTEP, SFEED2,FEED2C
  94.000       Q=Q*60.
  95.000       WRITE<3,19>
                                 191

-------
      Table 15 Continued).
TRANSIENT-STATE ACTIVATED SLUDGE,
COMPUTER PROGRAM
  96.000"    30 CONTINUE                      "                    "	
  97.000	    LOGRKG=RKG(N*X,XSTEP>SFE^D*SFEED2,Y,XF>H,INT>
  98.000      fTCB*FACVSS,FACTOD*FMLOAD7LOPt7AA7BB*W7RECYiWSUM*tHETA*t7
  99.000	    2WMAX,R,VJ,XR,TCMIX>
 100.000       WRITE<3*20)X,Y<2y,TCB,Y
 101.000	IF(.NOT.LOGRKG)GO TO  30
 10270015       STTjP
 103^,000	END^
 104.000 C            "               ~
 105.000 C	
 r06.000       LOGICAL FUNCTION
 107>000	ITCB;>FACySS,FACTO
 103.000      2WMAX.,R,V.,XR,TCMIX>
 109.000	REAL K(2)_                    _     	
 110.000       DIMENSION a<2),Y(2)\»FC2~)                   ~~
 11 1.000	DATA AI , A2» A3 *A4, AS* A6/V29 2893218813A5,0 .5^ 5 7864 376269O,
 112.000      10.12132034355964*1.70710678118655,3.41421356237310,
 113.000	14.12132034355964/	
 114.000       DATA 1CNT/0/
 115.000 j;   _ FUNCTION RKG SOLVES A SYSTEM OF N SIMULTANEOUS FJRST
 116.000 C     ORDER ORDINARY DIFFERENTIAL" EQUATIONS USING THE FOURTH
 117.000 C	   ORDER RUN6£-KUTTA_ METHOD J^ITH GILL^S COEFFJ[CIE^NTS.	
 118.000    40 CONTINUE
 1 1 9 .000	^F ( X.GE.XSTEP) SFEEDaSFEED2	^___	
nr2TJ".F>
 1_2UOOO	DO 50 I = 1>N	  	   	   	
 122.000       KtI>=F(I)*H
 1 23.000	Y( I ) =YUy*K( I ) * . 5     	     	
 124.000    50 Q(I)=iK(I)
 125.000 C
 126.000       X=X+.5*H
 127.000	CALL FXYCXjYjFV)	
 128.000       DO 51 I = UN
 129.000       K>
 137.000    52 Q=A5*K	
 T38TOOO C
 139.000       X=X+.5*H
 140 VOO'CT       CALlTFXYrXTYVF )
 141.000       DO 53 I=1>N
 1427^00       RCTy^FTIT*ff
 143.000    53 Y(I)=.YCI)*KCl)/6.-Q(I)/3.
                                     192

-------
     Table  15 (continued).
               TRANSIENT-STATE ACTIVATED  SLUDGE,
               COMPUTER PROGRAM
 145.000  C
 146.000
 147.000
   DO F/M CONTROL  OF  RECYCLE AND WASTE IF OPTION LOPT»1
   TCB=YT2)*FACVS5
   TCF=SFEED*FACTOD
 149.000
 TbU.OOO
 151.000
 1527000
 153.000
   FMLOAD=TCF/TCMIX
   IFCLOPT.NE.15GO  TO  56
   W=BB-AA*FMLOAD
   IFQ,SFEED,R*XR,K,KSUBS, YIELD, KENDOG*COMPAC
                       <1 ) )-K*Y< 1 )*YC2)/ * ( R*XR- (1 . +R > *Y ( 2 )T+YiELD*K* YTl )"*YC 2 >
  1/
-------
            Table 16.  ACTIVATED  SLUDGE  TRANSIENT SIMULATION
                      F/M  CONTROL TEST SIMULATION
                5.0
                      KINETIC  MODEL CONSTANTS
                  ~KSUBS*Md7L  TOD	TTEtD	KKNDOGiT/DAT"
                      117.0             .21      .060
 TNPUT~VALUE5:
      AERATION BASIN VOLUME
      INFLUENT FLOW RATE
 _ BIO-SETTLER UNDERFLOW
      INITIAL RE^YCLE^FLOW
    I N I T I AU~C OND I T I ON Si
      AERATION BACTERIA
                          .2500E 03 GALLONS
                          .6000E 00 GPM
                          .7850E 03 ML/MIN
                          .7000E  03 ML/MIN (RECYCLE RATIO =*  .301)
                                                736.4 MG/L TO
      BIO-SETL OVERFLOW TOD
      INFLUENT" W A STE^CONC.
 1938.0  MG/L  MLVSS  (
"75TO.O  MG/L  MLVSS  T
  116.0  MG/L  TOD (AERATION SUBSTRATE CONG)
 1556.0  ML/L  TOD ( 404.6MG/L TO"
SLUDGE COMPACTION  RATIO
TC CONVERSION FACTOR
TC~C~
                                3.88 MG/L SLUDGE  PER MG/L"BACTERIA
                                 '3J? IC/MLVSS	
                                 -~   ~"^~   TOD
      INITIAL F/M LOADING = .528 TC/TC
INITIAL STEADY STATE VALUES AS CALCULATED BY THE  KINETIC  MODEL:	
 MIXED LIQUOR SUBSTRATE" CONCENTRATIONi  116.7 MG/L TOD   OR   30.3 MG/L TC
 MIXED LIQUOR BACTERIA CONCENTRATION: 1992.0 MG/L VSS   OR  757.0 MG/L TC
      TIME AT WHICH LOADING IS CHANGED:
                                       9.0 HOURS
      NEW 
-------
                         APPENDIX D
         STEADY-STATE ACTIVATED SLUDGE COMPUTER MODEL

A computer program was developed to determine the minimum
volume of aeration basin required under steady-state conditions
for a specified treatment efficiency.  Several treatment ef-
ficiencies may be specified and the results tabulated according
to recycle ratio and recycle sludge concentration.  The basis
for the calculations is the Monod kinetic model.  A good dis-
cussion of the development of the model equations is presented
by Lawrence and McCartly, 1970.

The input data needed for the execution of this program are:

CARD NO. 1

Q      -  influent feed flow rate (gpm)
SPEED  -  influent feed concentration (mg/1 TOD)
K      -  substrate utilization coefficient (day""1)
KSUBS  -  half velocity coefficient (mg/1 TOD)
YIELD  -  growth yield coefficient (1 Ib VSS formed/lb TOD
           removed)
KENDOG -  microorganism decay coefficient (day ~ )

CARD NO. 2
NI     -  number of efficiencies specified
NJ     -  number of sludge concentrations specified
NL     -  number of recycle ratios specified

CARD NO. 3
EFF(I) -  efficiency of substrate removal (S0-Si)/S0.
          I = 1, NI
                             195

-------
CARD NO. 4

XR(J)   -  recycle sludge concentration (mg/1 MLVSS)
           J = 1, NJ
CARD NO. 5

R(L)    -  volumetric recycle ratio.  L = 1, ML


The computer program and a sample printout are given

in  Tables 17 and  18 respectively.
                              196

-------
        Table 17.   STEADY STATE ACTIVATED SLUDGE COMPUTER PROGRAM
   1 .000 C
   2.00O~C~
   3.000 C
   4 .OHO
   5.000
         c
    PROGRAM BACT
    MONOD~ MODEL" STEADY- ST ATET C ALCULAT I ON S
    REAL K,KSUBS,KENDOG
   7.000
   8TOTJO
   9.000
T070O0
  11.000
 10 FORMAT <6F)
"T5~FJJRMATC///iaX, 'STEADY  STATE
   123X, 'KINETIC MODEL CONSTANTS* /I 2X, «K, i /DAY
            TTECD
                                                   KSUBS,*,
   3F4.2,7X,F5.3/)
  12.000
  J3._000
  _.___. ^

  15.000
 20 FORMAT ( 10X7^1 NFLUENT^FLOW, GPM     lNFLUENTWA5TEf,
   I' CONCENTRATION,  MG/L T^D'/I SX^Fl 0^2,20X^8. 1/)
 25» FORMATT3I)
  17.000
  18.0015
  19.000
  20.000^
  21 .000
  22.00(
  23.000
  24.000
  25.000
  26TOOTT"
  27.000
 __                        		
 35~FORMATCTX77TX, 'CASE1 7l3*^ • r/8X7liEFFICIENCY^~OF*T
   I* WASTE REMOVAL  =* jrFS.U'X    C*^ F5 >l>* MG/L EFFLUENT •»
   2~*TOD>'/8X, • RECYCLE KLUDGE CONCENTRATION  ='*
	 3F6.0,* MG/L MLVSSf//5X> •REQUIREMENTTS TO  MEET THE DESIRE
   4 «ED REMOVAL: *78X,•BIOLOGICAL MASSV~XV =  V»E1674,
   5' LBS.VSX, «F/M  LOADING J^H^Ji''^-^^  LB  TOD/*,
   6'LBHL^S^-DAY'/SX^'F/M "REMOVAL RATIO =»,F67S7*
   7'LB MLVSS-DAY«/3X,'SLUDGE AGE REQUIRED =',F5.2,» DA',
   B^YSVHX,'WA~5HOUT  SLTTDUS AGE =1
  29.000
  y o.ooo
  31.000
                                       f DAYS
 9'  W =',£!
> FORMAT OX
 1'RECYCLE
 2' AEEATIT/N   TIYDRAUL 1C r 725G"' RAri7T~    FLO W7GPM   *
 3'  FLOW,  GPM      MLVSS,MG/L   VOL, GAL.  RET*N,*,
RECYCLE
                           WASTE SLUDGE
                                            BACTERIA
 33.)00
  35.000
 40 FORMAT<1X,F5.2,4X,E10.4,3X,E10.4,6X,F6.0,3X,E10.4,
~ T3X,F6.2)
 45 FORMATC 1X///20X, f *************#*5Me**********#**»/)
^48 FORMAT ( //// • CASE f ,1 3, •    RECYCLE SLUDGE "CONCENTRAT I ON * ,
   !•  =«,F6.0//>
36.000 C
37.000
38.000
39.000
40.000
41.000
42.000 C
43.000
44.000
45.000
READC 1,10) Q,SFEED,K, KSUBS, YIELD,KENDOG
READC1,25) NI,NJ,NL
R£AD<1,30) 
-------
    Table 17 (continued).
                          STEADY-STATE ACTIVATED SLUDGE
                          COMPUTER PROGRAM
  46.000
  47.000
~~4~87TFOO~
  49.000
  5~OiOOQT"
  51.000
  527000"
  53.000
           47 CONTINUE
              R=D
               1 = 1    	
           ~5ZT M*M+1
           51  SAER»SFEED-SFEED*EFF(I)/100.
  54.UUU
  55.000
 56.000
 57.000
~5BT001T
 59.000
 60~70~OlF
 JJI-OOO
 62.000
 63.000
 64.000
 65.000
n&6TOTTO"
 67.000
 68YOOO
 69.000
 TO". 000
 71.000
-72.UOO
 73.000
 74.00(
 75.000
 76.OOO
_77_»000
"T8VOTKT
 79j.OOO^
"80700"0"
 81.000
 82.000
 83^000
~B470~00"
 85.000
 86 ."000
    AERVOL»< 1440 . *Q*THETAC* ( 1 . +RC L> »/
    IFCL.NE.l)
    IFFMREM*THETAC>
~ 1AGE«1N>WMAX
 55 WRITE<3J36>
 36" WRTTET3"^40)«CO*RECY(L),t^AERX:,AER\70L7HRT
               ~1 ¥ ( L .nCETNLTUOTTT ^5T~
               L=l
               J=J+I
               IF45)
               GO  TO 50
               GO  TO 47
           140 WRITE<3*48)M,XRCJ)
               GO  TO 55
           150
               "END
                                   198

-------
             Table 18.   STEADY-STATE ACTIVATED SLUDGE MODEL
                       KINETIC MODEL CONSTANTS
            K,T/DAYKSUBS7MG/L   YIELD   KENDOG,1/DAY"
             5.0         117.0      .21        .060
          INFLUENT FLOW,  GPM
    INFLUENT WASTE CONCENTRATION*  MG/L TOD
                    rscr
CASE   1.
        EFFICIENCY OF  WASTE REMOVAL =
        RECYCLE SLUDGE CONCENTRATION
         80.OX   (400.0 MG/L  EFFLUENT TOD)
         * 5000. MG/L MLVS~S
    REQUIREMENTS TO MEET THE DESIRED REMOVAL*
       BIOLOGICAL MASS,  XV »  .2542E 01 LBS.
       F/M LOADING  RATIO
       F/M REMOVAL  RATIO
4 . 84 LB TOD/LB MLVSS— DAY
3.87 LB TOD/LB MLVSS -DAY
        5LUDGEAGEREQUIRED
        WASHOUT  SLUDGE AGE =
 1.07 DAYS  (MAX W »  .3855E-01  GPM)
RECYCLE
RATIO
.10
.20
.30
.40
.50
RECYCLE
FLOW, GPM
.5000E-01
.1000E 00
. 1500E 00
.2000E 00
.2500E 00
WASTE SLUDGE
FLOW, GPM
•3112E-01
•31 12E-01
.31 12E-01
.31 12E-01
.3112E-01
BACTERIA AERATION
MLVSS,MG/L VOL, GAL.
737. .4038E 03
1093. .2725E 03
1393. .2137E 03
1651. .1804E 03
1874. . 1589E 03
HYDRAULIC
HETW* TSSYS"
.56
.38
.30
.25
.22
IASE  2    RECYCLE SLUDGE CONCENTRATION = 7500.
RECYCLE
RATIO
.10
.20
.30
.40
.50
RECYCLE
FLOW, GPM
.5000E-01
.1000E 00
.1500E 00
.2000E 00
.2500E 00
WASTE SLUDGE
FLOW, GPM
.2075E-01
.2075E-01
.2075E-01
.2075E-01
.2075E-01
BACTERIA AERATION
MLVSS,MG/L VOL, GAL.
965. .3087E 03
1509. .1973E 03
1970. .1512E 03
2365. .1259E 03
2707. .UOOE 03
HYDRAULIC
RET*N, DAYS
.43
.27
.21
.17
.15
                                   199

-------
    Table  18 (continued).   STEADY-STATE ACTIVATED SLUDGE MODEL
CASE  "3V
       EFFICIENCY OF WASTE REMOVAL
       RECYCLE SLUDGE CONCENTRATION
                                       <200.0  MG/L EFFLUENT TOD)
                                5000. MG/L "MLVSS"
    REQUrREHEFTS~^rrn«EET THE "DE SI RED~~REMOVAL~i
        BIOLOGICAL MASS* XV a  .3507E  01  LBS.
        FVM LOADrNG RATIO =
                      3.51  LB Tt
F/M REMOVAL RATIO  =  3.15  LB TOD/LB M^SJ5-DAY	

WASHOUT SLUDGE  AGE »  1.07 DAYS  (MAX W  •  .5318E-O1 GPM)
RECYCLE
RATIO
.10
.20
.30
.40
.50
RECYCLE
.5000E-01
. TOOOE 00
.1500E 00
.2000E 00
•2500E 00
WASTE SLUDGE
TLOW, GPM ~
.3438E-01
.3438E-01
.3438E-01
.3438E-01
.3438E-01
BACTERIA
MLV5S,MG7L
767.
I12CT.
1418.
1674.
1896.
AERATION
VOL, GAL.
•5356E 03
.3669E 03
.2897E 03
.2454E 03
.2167E 03
HYDRAULIC
RET*N, D~AT5~
.74
.51
.40
.34
.30

RECYCLE
"RATTTl
    10
    RECYCLE
   •5000E-01
WASTE SLUDGE
 LW7~GPM
 .2292E-01
 BACTERIA   AERATION
MLVSS7MG7L" VOUT^GAL
   994.     .4132E  03
HYDRAULIC
RET*NTr DAYS
   .57
,2U
.30
,^»TJ
.50
.10UUE 00
.1500E 00
.2000E DO
.2500E 00
.yyyyE-oi
.2292E-01
" ~.2292ET-01
.2292E-01
Ib36.
1995.
"-- 12388.
2729.
.2674E 03
.2059E 03
.1720E 03"
•1505E 03
.37
.29
.24
.21
                                  200

-------
                             TECHNICAL REPORT DATA
                       (I'li-ase read Ittaruclioim on the reverse before completing)
 I Ml I'tlll I NO.

  EPA-660/2-75-021
e> fesffrtff*?z ^K •? rtf. 1
                           KEY WORDS AND DOCUMENT ANALYSIS
               DESCRIPTORS
Waste  Water Treatment
Industrial Waste Treatment
Petrochemical Waste Treatment
Pilot  Treatment Facility
                                       b. IDENTIFIERS/OPEN ENDED TERMS  C.  COS AT I Field/Group
                                        Activated Sludge
                                        Automation  and
                                          Control Systems
                                        Biological  Activity
                                          Monitor
                                        Nutrients Addition
                                        Sludge Recycle Con'
                                                              Cont.
                                                              rol
          N STATfcMENT

  Release Unlimited
                                     19. SECURITY CLASS (This Report)
21. NO. OF PAGES
    200
                                       20. SECURITY CLASS (Thispage)
                                                              22. PRICE
CPA form 2220-1 (»-73)
                         ft U 5 GOVERNMENT PRINTING OFFICE 1975-698-908 /3 REGION 10

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