c/EPA
United States
Environmental Protection
Agency
Municipal Environmental Research
Laboratory
Cincinnati OH 45268
EPA-600 2-79-014
March 1979
Research and Development
Performance
Evaluation of
Existing Aerated
Lagoon System at
Bixby, Oklahoma
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3, Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7. Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the ENVIRONMENTAL PROTECTION TECH-
NOLOGY series. This series describes research performed to develop and dem-
onstrate instrumentation, equipment, and methodology to repair or prevent en-
vironmental degradation from point and non-point sources of pollution. This work
provides the new or improved technology required for the control and treatment
of pollution sources to meet environmental quality standards.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/2-79-014
March 1979
PERFORMANCE EVALUATION OF
EXISTING AERATED LAGOON SYSTEM
AT BIXBY, OKLAHOMA
by
George W. Reid
Bureau of Water and Environmental Resources Research
and
Leale Streebin
School of Civil Engineering and Environmental Science
University of Oklahoma
Norman, Oklahoma 73019
Grant No. R803916
Project Officer
Ronald P. Lewis
Wastewater Research Division
Municipal Environmental Research Laboratory
Cincinnati, Ohio 45268
MUNICIPAL ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CINCINNATI, OHIO 45268
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DISCLAIMER
This report has been reviewed by the Municipal Environmental
Research Laboratory, U. S. Environmental Protection Agency, and
approved for publication. Approval does not signify that the con-
tents necessarily reflect the views and policies of the U. S. En-
vironmental Protection Agency, nor does mention of trade names or
commercial products constitute endorsement or recommendation for
use.
ii
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FOREWORD
The Environmental Protection Agency was created because of
increasing public and government concern about the dangers of
pollution to the health and welfare of the American people. The
complexity of the environment and the interplay between its com-
ponents require a concentrated and integrated attack on the pro-
blem.
Research and development is that necessary first step in
problem solution and it involves defining the problem, measuring
its impact, and searching for solutions. The Municipal Environ-
mental Research Laboratory develops new and improved technology
and systems for the prevention, treatment, and management of
wastewater and solid and hazardous waste pollutant discharges
from municipal and community sources, for the preservation and
treatment of public drinking water supplies, and to minimize the
adverse economic, social, health, and aesthetic effects of pollu-
tion. This publication is one of the products of that research;
a most vital communications link between the researcher and the
user community.
As part of these activities, this case history report was
prepared to make available to the sanitary engineering community
a full year of operating and measured performance data for a two-
celled, aerated wastewater treatment lagoon system.
Francis T. Mayo, Director
Municipal Environmental Research
Laboratory
111
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ABSTRACT
The University of Oklahoma School of Civil Engineering and
Environmental Science research group in collaboration with INCOG
& BIXBY, have studied a well designed, well operated two cell
aerated wastewater treatment lagoon system. The study involved
four seasons and nineteen study parameters. The data was treated
to statistical analysis, using a SPSS multiple regression, and
to normative analytical expression.
The lagoon exhibited an overall BODs removal efficiency of
92%, but was only totally in compliance for 7 months of the year.
The use of several kinetic models and regression models were not
very satisfactory though the temperature coefficient (9) were in
substantial agreement with Adams and Eckenfelder and other re-
puted values.
This report was submitted in fulfillment of Grant No. R803-
916 by the University of Oklahoma under the partial sponsorship
of the U.S. Environmental Protection Agency. This report covers
the Bixby lagoon operating period of January 1976 through Decem-
ber 1976.
iv
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CONTENTS
Disclaimer ii
Foreword iii
Abstract iv
Figures vi
Tables viii
Acknowledgements xi
1. introduction 1
Background 1
Significance of project 1
2. Conclusions 5
3. Recommendations 6
4. Approach 7
Primary objective 7
Secondary objective 7
Scope 8
5. project Description 10
Description of the city of Bixby and
its lagoon system ..... 10
Description of the experimental
investigation 12
Description of statistical analysis
techniques 15
6. Project Generated Data 17
Data generated on a year-round basis .... 17
Data generated on a seasonal basis 17
Data generated on a monthly basis 17
7. Project Data Evaluation and Analysis 44
Results and analysis 46
References . 56
Appendices
A. Summary of a Comparative Study of Parameters Used
for Measuring Waste Treatment Lagoon
Performance 58
B. Results of Regression Analysis 61
C. Operational Problems 92
D. Daily Data 93
v
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FIGURES
Number Page
1 Flow schematic of Bixby lagoon system 13
2 Seasonal mid-point water temperature change
at Bixby lagoon, 1976 21
3 Seasonal influent flow rate change at Bixby
lagoon, 1976 22
4 Seasonal influent BOD$ change at Bixby lagoon, 1976 . 23
5 Seasonal mid-point BOD5 change at Bixby lagoon,
1976 24
6 Seasonal effluent BOD5 change at Bixby lagoon, 1976 . 25
7 Seasonal change of mid-point volatile suspended
solids at Bixby lagoon, 1976 26
8 Seasonal change of effluent volatile suspended
solids at Bixby lagoon, 1976 27
9 Monthly average pH value at Bixby lagoon, 1976 ... 31
10 Monthly average water temperature at Bixby
lagoon, 1976 32
11 Monthly average alkalinity at Bixby lagoon, 1976 . . 33
12 Monthly average dissolved oxygen at Bixby
lagoon, 1976 34
13 Monthly average total BOD5 at Bixby lagoon, 1976 . . 35
14 Monthly average soluble BOD5 at Bixby lagoon, 1976 . 36
VI
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15 Monthly average total suspended solids at
Bixby lagoon, 1976 37
16 Monthly average volatile suspended solids
at Bixby lagoon, 1976 38
17 Monthly average total COD at Bixby lagoon, 1976 ... 39
18 Monthly average soluble COD at Bixby lagoon, 1976 . . 40
19 Monthly average total Kjeldahl nitrogen at
Bixby lagoon, 1976 41
20 Monthly average ammonia nitrogen at Bixby
lagoon, 1976 42
VI1
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TABLES
Number Page
1 Sampling and Analytical Guide 9
2 Process Data 11
3 Statistical Description of Influent Water Quality
at Bixby Lagoon, 1976 18
4 Statistical Description of Mid-Point water Quality
at Bixby Lagoon, 1976 18
5 Statistical Description of Effluent Water Quality
at Bixby Lagoon, 1976 19
6 Summary of Bixby Lagoon Efficiencies, 1976 19
7 Seasonal Average Influent, Mid-Point, and Effluent
Water Quality at Bixby Lagoon, 1976 20
8 Monthly Average Influent Water Quality at Bixby
Lagoon, 1976 28
9 Monthly Average Mid-Point Water Quality at Bixby
Lagoon, 1976 29
10 Monthly Average Effluent Water Quality at Bixby
Lagoon, 1976 30
11 Algal Genus Identified at Bixby Lagoon 43
12 Evaluation of Temperature Coefficient 53
13 Summary of Model Testing, Bixby Cell 1 55
14 Summary of model Testing, Bixby Cell 2 55
viii
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A-l Comparison of Parameters Measured at Five Lagoon
Systems '.. 59
A-2 Preliminary Identification of Tests Necessary for
the Performance Evaluation of Each Type of Lagoon . . 60
B-l Summary of Preliminary Regression Data,
Jan.-Dec. 1976 61
B-2 Results of Regression of Variables Selected after
Stepwise Regression, Jan.-Dec. 1976 62
B-3 Results of Regression of Variables Selected after
Stepwise Regression, Jan., Feb., Dec. 1976 63
B-4 Results of Regression of Variables Selected after
Stepwise Regression, March-May 1976 64
B-5 Results of Regression of Variables Selected after
Stepwise Regression, June-Aug. 1976 65
B-6 Results of Regression of Variables Selected after
Stepwise Regression, Sept.-Nov. 1976 66
B-7 Summary of Stepwise Regression Data, Jan.-Dec. 1976 . . 67
B-8 Results of Regression of Variables Selected after
Stepwise Regression, Jan.-Dec. 1976 69
B-9 Results of Regression of Variables Selected after
Stepwise Regression, Jan., Feb., Dec. 1976 71
B-10 Results of Regression of Variables Selected after
Stepwise Regression, March-May 1976 73
B-ll Results of Regression of Variables Selected after
Stepwise Regression, June-Aug. 1976 ......... 75
B-12 Results of Regression of Variables Selected after
Stepwise Regression, Sept.-Nov. 1976 77
B-13 Summary of Stepwise Regression Data, Jan.-Dec. 1976 . . 79
B-14 Results of Regression of Variables Selected after
Stepwise Regression, Jan.-Dec. 1976 80
ix
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B-15 Results of Regression of Variables Selected after
Stepwise Regression, Jan., Feb., Dec. 1976 81
B-16 Results of Regression of Variables Selected after
Stepwise Regression, March-May 1976 82
B-17 Results of Regression of Variables Selected after
Stepwise Regression, June-Aug. 1976 83
B-18 Results of Regression of Variables Selected after
Stepwise Regression, Sept.-Nov. 1976 84
B-19 Summary of Stepwise Regression Data, Jan.-Dec. 1976 . . 85
B-20 Results of Regression of Variables Selected after
Stepwise Regression, Jan.-Dec. 1976 87
B-21 Results of Regression of Variables Selected after
Stepwise Regression, Jan., Feb., Dec. 1976 88
B-22 Results of Regression of Variables Selected after
Stepwise Regression, March-May 1976 89
B-23 Results of Regression of Variables Selected after
Stepwise Regression, June-Aug. 1976 90
B-24 Results of Regression of Variables Selected after
Stepwise Regression, Sept.-Nov. 1976 91
D-l Influent Test Data of Bixby Lagoon, 1976 93
D-2 Mid-Point Test Data of Bixby Lagoon, ' 1976 97
D-3 Effluent Test Data of Bixby Lagoon, 1976 101
x
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ACKNOWLEDGEMENTS
The authors acknowledge with gratitude the following indivi-
duals for their contribution to this report.
Anil Mathur for his diligent and conscientious pursuit of
the data required to perform the analysis of the aerated lagoon
system.
Joseph L. Norton, Chief of Laboratory Services, Division of
the Tulsa City County Health Department, for his assistance in
reviewing the project plans and laboratory analysis performed in
his laboratory.
Jerry G. Cleveland, Chief of Planning & Research, Division
of the Tulsa City County Health Department, for his assistance in
reviewing the project plans.
Fred Keas, City of Bixby, Oklahoma, for his assistance in
sampling and analysis during his tenure as Superintendent of the
Water Pollution Control Facilities.
Bobby J Toilette, Superintendent of Water Pollution Control
Facilities, for his assistance in sampling and analysis.
Gene-Pai, Chou, for his assistance in graphical work.
Andy Law, Research Assistant, the Bureau of Water & Environ-
mental Resources Research, for his assistance in writing the
final report.
xi
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SECTION 1
INTRODUCTION
BACKGROUND
Biological waste treatment by means of waste stabilization
lagoon system can be considered as a major wastewater treatment
alternative for small communities (especially those with less
than 50,000 population) and rural areas and some industries.
Waste stabilization lagoon system are chosen not only for the
reason of low initial capital cost, but also because of their
relative stability and simplicity, as well as minimum cost of
operation and maintenance. The low initial capital cost is part-
icularly true in the rural areas where more openland is available
and at lower costs. For these reasons, today there are thousands
of wastewater treatment lagoons in use for domestic wastewater
treatment in the United States.
The use of lagoon systems to treat wastewater is wide-spread
and there are great variations in the design of these systems:
from simple anaerobic, facultative, aerobic and maturation lagoons
to modified lagoons of various designs (for example - the use of
aeration systems or devices to maintain aerobic conditions), from
single to multiple cell systems, and so forth. Although a large
number of these different systems of lagoons have been studied,
there is a common lack of carefully collected data in sufficient
depth in terms of realistic, long-term performance data which
would be indispensible for producing sound design criteria for
future use. Partly this is due to very little on-site capability
and facility to determine operational test results.
SIGNIFICANCE OF PROJECT
In the October of 1972, Congress passed the Federal Water
Pollution Control Act Amendments. The Act has three major targets:
(a) All municipal treatment facilities must achieve second-
ary treatment effluent limitations, and all industries
must implement the Best Practicable Treatment technology
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(BPT) for treatment of the wastewater discharged into
all surface waters. The Act requires that these efflu-
ent criteria be met by 1977 . The Environmental Protec-
tion Agency (EPA) has defined municipal secondary treat-
ment standards and also Best Practicable Treatment tech-
nology effluent standards for each category of industry
and type of manufacturing process used.
(b) By 1983, municipalities must achieve BPT in their treat-
ment facilities. (BPT has been defined by EPA as secon-
dary treatment for municipalities). Industries will
have to implement Best Available Technology (BAT), as
defined by EPA by 1983, for each kind of industry class,
(c) By 1985, all pollutional discharges must be eliminated
from the nation's waters.
The Congress mandated that these steps be taken to enable the
water quality goals of fishable and swimmable waters to be achiev-
ed by 1983. The spirit and overall purpose of the Act is to re-
store and maintain the chemical, physical and biological integrity
of the nation's waters.
The law also established the National Pollution Discharge
Elimination System (NPDES). Under NPDES, all point source (muni-
cipal and industrial) are issued permits specifyin the nature and
quality of pollution they may discharge. These permits, at a
minimum, reflect the appropriate technology based BPT or BAT
standards.
The secondary treatment effluent limitations or the minimum
performance requirements for publicly owned treatment works as
established in the Act of 1972 specify that the BOD5 and suspend-
ed solids arithmetic mean values of the effluent samples for 30
days consecutive sampling shall not exceed 30 milligrams per
liter or 45 milligrams per liter for samples collected in seven
consecutive days. They further specify that the arithmetic mean
values for the 30 day consecutive sampling shall not exceed 15%
of arithmetic mean of the influent samples collected at approxi-
mately the same time during the same period. Finally, they spe-
cify that the geometric mean of the fecal coliform bacteria and
the effluents shall not exceed 200 for the 30 day period or 400
for the seven consecutive day period.*
These regulations and EPA's definition of secondary treatment
seems to emphasize the installation of activated sludge units.
*This has been deleted. See new standards at end of this section.
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On the other hand, it is precisely because small communities can-
not afford the high costs involved in the construction, operation
and maintenance of activated sludge or other sophisticated units
that they had to resort to treatment by means of lagoons. There
also exists a strong possibility that many of the present operat-
ing lagoon will not meet EPA secondary treatment effluent stand-
ards without modifications. (2,3,4) Thus, in order to meet
treatment standards, many of the presently'operating lagoons
would have to be modified or upgraded.
Among the numerous alternatives for upgrading lagoon treat-
ment, functionally serialized lagoons (anaerobic, facultative and
maturation) present a possible solution. Other possible solutions
for upgrading the treatment are addition of air, recycling, con-
trolled discharge, possibility of final sedimentation, filtration,
and even the possibility of harvesting algae through natural met-
hods such as culturing carp or milk-fish, or passing through a
natural aquatic habitat. However, before a decision can be made
on what methods of upgrading are sufficient in improving effluent
quality to meet the standards, it becomes necessary to gather
additional pertinent data on existing lagoon systems. At the
present, there are very limited published data on performance of
lagoons on a seasonal basis for the most important water quality
parameters (including nutrients). It is most important to have
such data in order to do a rigorous performance evaluation.
Therefore, it is important to determine how an existing well-
designed aerated lagoon treats wastewater. Well designed, well
operated lagoon must have been operated sufficiently long and at
different climatic conditions to be able to ascertain their per-
formance in order to determine whether there are existing contin-
uous discharge aerated lagoons that can meet the 1977 secondary
treatment standards. This project will document and evaluate
carefully collected operating performance data from one such
lagoon system.
* Since the beginning of this project, the federal Secondary
Treatment Effluent Standards have been amended. As published in
the July 26, 1976 Federal Register, the limitations on fecal coli-
form bacteria were deleted in the 1976.revision of the standard.
It is now felt that it is environmentally sound to establish dis-
infection requirements for domestic wastewater discharges in ac-
cordance with water quality standards promulgated pursuant to
Section 302 and 303 of the Act and associated public health needs.
On October 7, 1977, suspended solids limitations were amended to
permit less stringent limitations for publicly owned wastewater
treatment ponds with a design capacity of two million gallons per
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day or less. Either the Regional EPA Adminstrator or the State
Director for Environmental Control, subjected to EPA approval,
may establish less stringent limitations based on the actual per-
formance of waste stabilization ponds in the geographic area
which are meeting effluent quality limitations for biochemical
oxygen demand.
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SECTION 2
CONCLUSIONS
Although the Bixby lagoon system exhibits an overall BOD5
removal efficiency of 92%, it is only in compliance with EPA's
BOD5 standard for about 7 months out of the year. Winter and
early Spring months are the non-complying months.
Total suspended solid levels in the effluent remained fairly
high for 11 months of the year. The average TSS level for those
months was 52 mg/1, which may be attributed to algal growth.
Fecal coliform density in the wastewater entering the Bixby
lagoon system was high, in the order of 10^/100 ml. Even if the
lagoon system had coliform removal efficiency as high as 98%, it
still would not be able to reduce the coliform bacteria to less
than 200/100 ml. Additional treatment would be necessary if
there were a bacterial limitation for the receiving stream.
The use of linear regressions to characterize the influent,
mid-point and effluent parameter and correlate lagoon efficien-
cies all fall short of being satisfactory. Additional parameters
not clear at the present will have to be included in the regress-
ion analysis for it to be meaninful.
The attempt to depict the performance of Bixby lagoon system
in terms of kinetic models was unsuccessful. The wide variations
in experimental data which were being fitted to the models could
not be satisfactorily explained. One possible explanation was
that it may be due to algal growths which affected the fraction
of the biologically active volatile suspended solids.
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SECTION 3
RECOMMENDATIONS
For the numerous small communities and rural areas, waste-
water treatment by means of lagoons is a significant and econo-
mically feasible alternative. However, few existing lagoons were
able to perform to more desirable treatment levels as that obtain-
ed from conventional secondary treatment systems. It is obvious
that lagoons as a viable means of wastewater treatment need to be
further studied and monitored so that from such actions meaning-
ful knowledge may be acquired and better design criteria may be
formulated.
At the present, lagoon effluent standards are less strigent
as a result of subsequent revisions of the 1972 Act. However,
should a need arise in the future for the improvement of the
Bixby lagoon system the addition of one or a combination of the
followings is recommended: anaerobic lagoon for pretreatment,
maturation lagoon for polishing and/or chlorination prior to dis-
charge. However, feasibility study should be conducted prior to
any such action.
The effect of the relative abundance of algae on the biolo-
gically active portion of the volatile suspended solids should be
investiga ted.
The retention time in each lagoon at Bixby based on plug
flow is 40 days. A method of accounting for this time lag in the
correlation and regression analysis should be developed.
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SECTION 4
APPROACH
PRIMARY OBJECTIVE
The primary objective of this project was to generate relia-
ble year round performance data for a typical multi-cell aerated
lagoon waste disposal system. Bixby, Oklahoma is a case in point.
This lagoon system, which consists of two cells in series using
an Air Aqua* system, is located in the town of Bixby, Oklahoma,
which is part of the INCOG Multi-County Planning System. This
aerated lagoon was selected for study by EPA with the concurrence
of others.
SECONDARY OBJECTIVE
The secondary objective was to utilize these data to evaluate
the effectiveness of the multi-cell lagoon system to perform in
accordance with its design criteria and its ability to meet the
secondary treatment standards as established by the Federal Water
Pollution Control Act Amendments of 1972.
Data generated and evaluated in this lagoon system were to
be similar to data from other types and locations of well-designed
well-operated multi-cell aerated or a combined aerated and facul-
tative lagoon system. These data could be used not only to assist
design engineers and regulatory officials, but also assist EPA in
its stated objective of defining lagoon capabilities and lagoon
grading needs. A great number of parameters were studied in con-
siderable depth. Out of the parameter study two significantly
useful things were sought: 1) the more meaningful parameters
conceivably could be used as routine operational tests, and 2)
the parameters could be interrelated to provide predictive equa-
tions for future design.
*Tradename of Hinde Engineering aeration system.
7
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SCOPE
From the existing Bixby lagoon system at Bixby, Oklahoma,
one full year of lagoon performance data were collected. Within
this period, data collection was divided into four temporal phases
coinciding with the four seasons: Spring, Summer, Fall and Winter.
In each period, data were collected daily for one month while
samples of one week (7 consecutive days) per month were taken du-
ring the remaining two months.
Sampling was done with a flow proportional type compositing
device, and sampling points were the influent (before entering the
lagoon system), the mid-point (exit of first cell) and the efflu-
ent (exit from the lagoon system). Nineteen parameters were at-
tempted: flow data, pH, temperature, dissolved oxygen, alkalinity,
total BOD5, soluble BOD5, total suspended solids, volatile suspen-
ded solids, total COD, soluble COD, phosphorus (dissolved ortho-
phosphate) , total Kjeldahl nitrogen, ammonia nitrogen, nitrate and
nitrite nitrogen, fecal and total coliform. Nitrate and nitrite
nitrogen tests were subsequently discarded after tests performed
at the start of project consistently showed near zero values.
The remaining parameters were measured in depth with the exception
of algal determination which was performed qualitatively only.
Table 1 is a sampling and analytical guide.
Four tests were performed at the site, namely: pH, tempera-
ture, alkalinity and dissolved oxygen. Total suspended solids,
volatile suspended solids, total and soluble COD, total and solu-
ble BOD5 tests were performed at the University of Oklahoma's
mobile laboratory parked by the lagoon. Remaining tests were con-
ducted by Laboratory Services, Division of the Tulsa City County
Health Department.
This report in addition to containing the tabulation of the
performance data, detailed information concerning the lagoon de-
sign, operational parameters, inlet and outlet configurations and
flow pattern, also included an interpretation of the data as to
its significance in relation to the objectives of the project.
Statistically, data were analysed in the form of correlation ma-
trices to assist in the identification of appropriate and redun-
dant tests, and hopefully to develop through regression analysis
technique and equations representing the performance of this type
of lagoon. These equations, if developed, would be useful in
design and evaluation of performance, including both efficiency
and cost of treatment.
8
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TABLE 1. SAMPLING AMD ANALYTICAL GUIDE
SAMPLING POINTS
PARAMETER INFLUENT MID-POINT EFFLUENT
WW Flow
PH
WW Temperature
Dissolved Oxygen
Alkalinity
Total BOD 5
Soluble BOD5
Total Suspended Solids
Volatile Suspended Solids
Total COD
Soluble COD
Phosphorus*
Total Kjeldahl Nitrogen
Ammonia Nitrogen
Nitrate Nitrogen
Nitrite Nitrogen
Fecal Coliform
Total Coliform
Algal Determination
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
*Actual test performed was dissolved ortho-phosphate. For con-
venience, dissolved ortho-phosphate was identified by phosphorus.
Nitrate and nitrite tests were discontinued after numerous tests
performed at the start of the project yield zero or near zero
values consistently.
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SECTION 5
PROJECT DESCRIPTION
DESCRIPTION OF THE CITY OF BIXBY AND ITS LAGOON SYSTEM
The site selected for this segment of the oxygen-supplied
multiple lagoon system was that of the city of Bixby, Oklahoma.
The city of Bixby is situated in the Indian Nation Council of
governments (INCOG) and is adjacent to south Tulsa City. The
current population of Bixby is 3,000 and is projected to grow to
6,000 in the year 2,000. The present population prodces an effl-
uent 6005 averaging 350 milligram per liter. Currently, Bixby
has no manufacturing or process industries discharging industrial
waste into the sanitary sewers. This greatly increased the desi-
rability of the Bixby lagoon system as a site for intensive study
because the wastewater concentration entering the lagoon system
will be relatively stable and practically free of toxic substances
which may disrupt treatment continuity. All variabilities in the
wastewater which enters the Bixby lagoon system can thus be attri-
buted to normal small town domestic and commercial sources.
Bixby Lagoon System
Bixby lagoon system is a dual-cell system, with total surface
area of 23.5xlO~3 km^, an average depth of 3.2 m, and an overall
volume of 5.6x10^ m^. Each cell is 167 m long and 38 m wide.
The cells are not cemented and are supported on the sides by a
dike of slope 3:1. It has 20 h.p., 9.8 m3/min., Hinde/Air-Aqua
system with 84 laterals in the primary and 48 laterals in the
secondary, designed to supply all the oxygen requirements for
loading of 276 kg of BOD5 per day, a population of 4,500 people
and o.4 MGD (1 GPD = o.oo3785 m3/<3) . The present plant is oper-
ating at about 90% efficiency, and a retention time of about 67.5
days. The flow is continuous, the inlet and outlet system is de-
signed against short-circuiting. The plant is well operated, and
is always acessible. It does not have final clarification nor
does it have chlorination, nor are there available long-term re-
cords. These data are summarized in Table 2 and a sketch of the
10
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TABLE 2. PROCESS DATA
Two Lagoons - 5.6x10^ m3 volume
23.5x10-3 km2 surface area
3.2 m depth
designed for either serial or parallel operation.
(See sketch, Figure 1)
Aeration -
Design -
Actual -
Operation -
Other -
20 h.p.- Air Aqua System/Hinde Engineering
84 laterals in primary
48 laterals in secondary
% oxygen demand supplied - 100%
Q = 0.45 MOD (1 GPD = 0.003785 m3/d)
Population = 4,500
BOD5/DAY = 335 kg
Retention Time = 31.6 days
BOD5/100 m3 = 0.6 kg
BOD5/HPH = 0.7 kg
BOD5/m2/DAY = 0.015 kg
Q = 0.21 ± 0.04 MGD (1 GPD = 0.003785 m3/d)
Population = 3,000
Influent BOD5 = 240 (200 - 350) mg/1
Effluent BOD5 = 11 rag/1
Efficiency = 90.5%
BOD5/m2/DAY = 0.008 kg
Retention Time =67.5 days
Continuous flow
Off set inlet, air lift, over under baffle
No C12
Effluent V notch weir
No cover, cell depth constant
Maintenance good, always acessible
Built in 1970
Engineering - HTD (Tulsa/Okla. City)
Operator - Fred Keas
11
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facility in Figure 1.
DESCRIPTION OF THE EXPERIMENTAL INVESTIGATION
Sampling was simplified with the use of automatic-samplers
which were setup at the lagoon influent, the mid-point and the
lagoon effluent. The sampler set at the mid-point allowed analy-
sis of each cell's performance individually.
Each sampler collected 50 ml of sample every fifteen minutes
and approximately 4 liters of sample was collected in a 24 hour
period.
The samples were stored in ice boxes at 4 degrees Celsius.
This inhibited biological activity in the composite samples. All
the experimental parameters used in the correlation were measured
within 1 day of sample collection. pH, temperature, dissolved
oxygen and alkalinity tests were conducted on-site immediately
after samples were collected.
In the experimental analysis, 462 samples were collected and
analyzed between January and December 1976. January, April, July
and November were months of intensive testing and approximately
75 samples were analyzed in each of these months. This close
study of the behavior of the lagoons was essential to get data to
predict the seasonal variation of the performance of the lagoons.
During each of the remaining months, testing was not equally
rigorous and about 21 daily samples were analyzed in each month.
DESCRIPTION OF EXPERIMENTAL ANALYSIS AND PROCEDURES
All analysis were performed in accord to either the 13th
Edition of Standard Methods for the Examination of Water and
Wastewater (7) or EPA's Manual of Methods for Chemical Analysis
of Water and Wastes (17). In the following, they will be abbre-
viated as Standard Method and EPA Manual respectively. The ana-
lytical procedures chosen for the parameters included in this
project are briefly outlined as follows:
Tests conducted on-site:
pH - direct measurement by pH meter.
Temperature - measured by thermometer in Celsius.
Dissolved Oxygen - measured by D.O. probe.
Aklalinity - titrimetrically determined by mixed bromcresol
green - methyl red double indicator method.
12
-------
PUMP 1
SCREEN
PUMP 2
LEGEND
I
E
A
D
E-
E2-
E°-
FM-
R -
*-&*
Influent
Effluent
Air
Drain
Plant Effluent
Lagoon 1 Effluent
Lagoon 2 Effluent
Overflow & Emergency Effluent
Plow Meter
Return Plow
I
>
BLOWE1
HOUSE
' i,
E:
j
A <
}
A <
>
2<
)
i
LAGOON 1
i /
) C
) <
' i
iAl
>A
:
I
(
R
1
-fih-
>
El
'
LAGOON 2
r
r
i
D
^
E°
I
D
,.
TO RIVER
Figure 1. Flow schematic of Bixby lagoon system.
-------
(Standard Method)
Tests conducted in laboratories*:
Phosphorus - determined in terms of dissolved ortho-phosphate
by direct colorimetric analysis procedure.
(EPA Manual, storet no. 00671)
Ammonia Nitrogen - determined by Automated Colorimetric Phe-
nate Method using Technicon Autoanalyser
Unit AAII. (EPA Manual, storet no. 00610)
Total Kjeldahl Nitrogen - determined by titration of ammonia
after distillation. (EPA Manual,
storet no. 00625)
Nitrate Nitrogen - measured by spectrophotometer. (EPA Manual,
storet no. 00630)
Nitrite Nitrogen - measured by spectrophotometer. (EPA Manual,
sotret no. 00615)
Total BOD5 - determined by Azide Modification of the Winkler
Method. (Standard Method)
Soluble BOD5 - samples were first filtered through 0.45 ^i
filter with subsequent determination by the
Azide Modification of the Winkler Method.
(Standard Method)
Total COD - determined by titrimetric method after reflux.
(EPA Manual, storet no. 00335, Low Level)
Soluble COD - samples were first filtered through 0.45 ^i fil-
ter with subsequent determination by titrimet-
ric method after reflux. (EPA Manual, storet
no. 00335, Low Level)
Total Suspended Solids - complete evaporation of the water
portion with residue dried at oven
temperature of 103 °C. Determined
by weight difference. (Standard
Method)
Volatile Suspended Solids - complete evaporation and ashed
at 550 °C. Determined by weight
difference. (Standard Method)
Total Coliform - determined by membrane filter technique.
(Standard Method)
Fecal Coliform - determined by membrane filter technique.
(Standard Method)
Flow Rate - determined by measurement of water level over
weir with a portable water level recorder.
'Algal determination - qualitatively determined.
*Six tests were performed in O.U. Mobile Laboratory. See page 8.
14
-------
DESCRIPTION OF STATISTICAL ANALYSIS TECHNIQUES
Because of the extremely large amount of performance data
collected over the project period, statistical analysis would be
impractical as well as not feasible without the use of high-speed
computers. All the analysis conducted in this project were done
with the use of a "canned" statistical analysis package -SPSS. (6)
SPSS is a highly flexible, user oriented tool with output data
printed out in very neat and readable manner.
Analysis of experimental data to obtain continuous variable
descriptive statistics such as maximum, minimum, mean values, and
standard deviation, etc. was executed with the use of a sub-pro-
gram in the SPSS.
For studies related to characterization of wastewater enter-
ing the facility, efficiency correlations and design method veri-
fication, the principal tool used was multiple regression analysis.
In all correlation work, where all the variable interdepen-
dencies are not immediately obvious, stepwise regression analysis
is probably the most useful and versatile tool (6).
Stepwise regression enables the identification of the most
significant variables, which "explain" a given dependent variable,
in the relative order of their importance. The initial task,
therefore, is to identify all possible independent variables which
may be related to a given dependent variable. The stepwise regre-
ssion procedure introduces each variable, in order of its impor-
tance, into the regression equation and shows the effect of this
introduction on the overall correlation coefficient (r2), the F
ratio, the standard error, and the beta weights for each variable
in the equation. No variables would be added to the regression
equation if the addition of a variable does not increase the r
value.
Once the pertinent variables are identified by the stepwise
regression, a very close examination of all the possible under-
lying theoretical explanations is necessary. This is simply to
avoid the problems caused by an exclusive reliance on statistical
analysis. There are, sometimes, unexpected indications of varia-
ble interdependencies. These need very careful substantiation.
Alternatively, variables thought to be extremely significant may
not appear in the final equation resulting from the stepwise pro-
cedure. This can happen easily especially when there is consi-
derable scatter in the original data for that variable because
15
-------
of low experimental reproducibility (7). This problem occurs
often in biochemical tests.
One common decision whenever this problem arises is to force
the excluded variable(s) into the regression equation by abandon-
ing the stepwise procedure. This also enables dropping of non-
significant variables from the equation with a corresponding in-
crease in the total number of valid cases. The final regression
then, shows the best relationship between the independent varia-
bles and the dependent variables.
The output from such a final regression includes a tabulation
of all regression parameters, a case by case listing of observed
versus predicted values for the dependent variable, and a plot
of the standardized error in predicted variable values. An ana-
lysis of such a plot can reveal whether or not there is reason to
suspect systematic violations of the assumption that the regre-
ssion is linear. In such cases, non-linear transformations of
the independent variables may be indicated and the entire regre-
ssion exercise repeated. However, the regression statistics pro-
duced after such variable transformations cannot be compared
against the original statistics except in a very general, quali-
tative way. This is especially true if logarithmic transforma-
tions are used.
The fitting of observed lagoon data to a general design equa-
tion can be done by rearrangement of the design equation, identi-
fication of "synthetic" new variables and regression of these va-
riables using least squares methods. Should it be necessary to
force such regressions through a fixed point (for theoretical
reasons), the usual unconstrained regression procedure is no lon-
ger useful. A similar situation would arise, for example, if a
particular regression coefficient were to be held fixed. Such
problems are best handled by a basic reformulation of the least
squares technique which forces such constraints to be met at the
beginning. Examples of such modifications are discussed later
in the report.
16
-------
SECTION 6
PROJECT GENERATED DATA
The primary objective of this report on Bixby lagoon system
was to generate the much needed performance data for a typical
multi-cell aerated lagoon waste disposal system on a year-round
basis. For this reason, Section 6 is entirely devoted to the
tabulation and presentation of data generated during the course
of this project. For clarity purpose, data are organized into
three levels: year-round, seasonal, and monthly.
DATA GENERATED ON A YEAR-ROUND BASIS
Data generated in this group is an attempt to create an over-
all view of the parameter characteristics measured at the Bixby
lagoon system. Tables 3 to 5 are statistical descriptions of the
water quality parameters at the influent, mid-point and effluent
of the Bixby lagoon system. Table 6 summarizes lagoon efficiency
of individual cells and the lagoon system as a whole.
DATA GENERATED ON A SEASONAL BASIS
Seasonal average water quality of wastewater at various
treatment stages of the Bixby lagoon are computed and tabulated
in Table 7. Data generated in this manner allow observation and
comparison of wastewater treatment efficiency on a seasonal basis.
Figure 2 to 8 are computer interpretations of parameter level vs
time (these parameters are the ones involved in the kinetic model-
ling.)
DATA GENERATED ON A MONTHLY BASIS
Tables 8 to 10 contain data computed to monthly averages.
Their significance lie in the fact that they revealed the trend
of parameter level variation throughout the year when data were
collected. Figure 9 to 20 are graphical presentations of data so
computed. These graphs besides visually showing trends of para-
meter variation, also permit comparison of treatment efficiencies
17
-------
TABLE 3. STATISTICAL DESCRIPTION OF INFLUENT WATER
QUALITY AT BIXBY LAGOON, 1976
TEST AVE. VALUE+ MIN. MAX. STD. DEV.
pH
Alkalinity*
Total BOD5
Soluble BOD 5
Total S.S.
Volatile S.S.
Total COD
Soluble COD
TKN
Ammonia -N
Flow, GPD**
154.0
368
154
268
201
641
262
45.7
29.3
1.4x105
4.3
94.0
210
53
92
40
233
115
21.0
9.0
617
7.6
198.0
740
350
772
631
1,148
545
115.0
48.9
17.6x105
18.9
90
56
138
116
147
69
11.8
6.7
l.SxlO5
+All values were computed from one year period data. Unless
indicated, all units are mg/1 except for pH.
*As CaC03
**1 GPD = 0.003785 m3/d
TABLE 4. STATISTICAL DESCRIPTION OF MID-POINT WATER
QUALITY AT BIXBY LAGOON, 1976
TEST AVE. VALUE+ MIN. MAX. STD. DEV.
PH
Alkalinity*
Tempera ture,°C
DO
Total BOD5
Soluble BOD5
Total S.S.
Volatile S.S.
Total COD
Soluble COD
85.7
17.8
, 7.6
84
25
90
70
195
71
5.5
26.0
1.0
2.2
26
3
19
12
88
17
8.0
194.0
30.0
13.6
183
132
232
196
498
246
41
8
2
37
28
46
39
67
35
.7
.6
.6
+A11 values were computed from one year period data. Unless
indicated, all units are mg/1 except for pH.
*As CaC03
18
-------
TABLE 5. STATISTICAL DESCRIPTION OF EFFLUENT WATER
QUALITY AT BIXBY LAGOON, 1976
TEST
AVE. VALUE+ MIN.
MAX.
STD. DEV.
PH
Alkalinity*
Tempera ture,°C
DO
Total BOD 5
Soluble BOD5
Total S.S.
Volatile S.S.
Total COD
Soluble COD
TKN
Ammonia -N
74.4
17.3
8.8
30
16
56
35
103
55
7.8
3.3
6.3
24.0
1.0
2.0
7
1
11
4
20
6
1.0
0.1
9.8
180.0
31.0
19.0
131
128
186
146
330
250
23.0
23.8
24.1
9.1
4.0
21
19
33
23
45
32
4.7
4.6
+A11 values were computed from one year period data
indicated, all units are mg/1 except for pH.
*As CaC03
Unless
TABLE 6. SUMMARY OF BIXBY LAGOON EFFICIENCIES, 1976
TEST
AVE. VALUE+ MIN.
MAX.
STD. DEV.
BOD5 Cell 1
BODs Cell 2
BOD^ Overall
Total S.S. Cell 1
Total S.S. Cell 2
Total S.S. Overall
COD Cell 1
COD Cell 2
COD Overall
TKN Overall
77
61
92
61
16
76
69
45
84
83
48
-17*
68
-22
-392
29
18
-15
55
34
94
92
97
93
94
96
89
95
97
98
9
24
5
24
76
14
12
21
7
10
+A11 values were computed from one year period data.
removal efficiencies in percentages.
*Negative sign indicates increase in waste concentration.
Values are
19
-------
TABLE 7. SEASONAL AVERAGE INFLUENT, MID-POINT, AND EFFLUENT
WATER QUALITY AT BIXBY LAGOON, 1976
TESTS
PH
Alkalinity*
Temperature , °C
DO
Total 5005
Soluble BOD5
Total S.S.
Volatile S.S.
Total COD
Soluble COD
Phosphorus**
TKN
Ammonia-N
Fecal Coli.+
Total Coli.+
Flow, xlO3 gpd#
INF.
6.5
160
-
-
394
148
301
221
606
240
37.7
49.1
24.1
199
_
150
SPRING
MID.
6.8
109
19.3
6.6
88
24
79
61
206
77
44.0
-
-
147
303
-
SUMMER
EFF.
7.2
85
19.1
7.1
35
16
58
41
131
74
48.2
10.4
5.0
73
166
-
INF.
6.2
151
-
-
355
129
258
214
594
248
-
43.5
31.1
_
151
MID.
6.7
78
28.0
6.4
64
13
72
58
156
62
-
-
_
_
-
EFF.
6.8
72
28.4
5.2
20
9
66
33
84
49
38.0
4.7
C.8
_
«.
-
INF.
6.2
149
366
144
258
192
757
257
46.9
33.9
_
_
132
AUTUMN
MID.
6.2
71
12.7
8.2
111
7
133
108
263
67
-.
_
_
-
EFF.
7.6
60
11.8
11.6
25
10
52
35
102
47
_
5.3
0.1
_
-
INF.
6.7
157
_
_
357
199
253
178
630
302
36.9
43.6
29.8
118
WINTER
MID.
6.9
113
6.6
9.8
80
52
78
52
165
78
40.7
_
^
-
EFF.
7.9
79
5.7
13.2
40
28
46
28
94
46
32.0
10.1
6.1
-
Unless otherwise indicated, all units are mg/1 except for pH.
*Alkalinity as CaC03.
**Actual tests performed were dissolved ortho-phosphate. For convenience, dissolved
ortho-phosphate was identified as phosphorus.
"^Values are xlOO/lOOml.
#1 gpd = 0.003785
-------
30
25
20
0U
15
w
a,
10
« * *
*. *
*
*
*
XX
*
*
**
#J.
* « *
* * »**
* *
*t ***fc
»*
*.
«**««* r *
** * * % **
*
A* *
*
4* *
«.*
* * * *
** * *
** **.
* *
0
Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec,
Months
Figure 2. Seasonal mid-point water temperature change at Bixby
lagoon, 1976
-------
60
M
50
Q TJ
g
p LTI
rH CO
X r-
n
* o
W o
30
S
gp20
jj p j
ti O
10
A
* *
< *
*** »t *t
* ** **
* *
* *
*
X
it
4
* * * *
^ «**«*
* *
AC * *
*.**« #
*
* *
*
*
x « x
* *
* ** *
* ***. + * *
** «
* * *
*
it
X
* ** * * *
** * * *<
#* *
** *
*
Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec.
Months
Figure 3. Seasonal influent flow rate change at Bixby lagoon, 1976
-------
ro
U)
800
700
600
,500
in
Q
400
300
200
* * *
«
* *
**
*
*
* *
5***
«*
*
* *«
* * *
* **
**
*.«
*
** *
* *
* **
11 *
* * **
* * **
«* * « *
* * *
Jan. Feb. Mar. Apr. May June July Aug. Sep.
Months
Oct. Nov. Dec.
Figure 4. Seasonal influent BOD5 change at Bixby lagoon, 1976
-------
175
150
125
100
in
O
75
*
t
< C
f
*
* t*
*
*
* <
*
**
*
*
*
*
*
« *
*
ft
«
* *
** *
*
*
* *
*
* * t
* C
* *
*
It
* * *
*
A
*
*
*
*
* *
* *
*
*
*
t
t
* »
* *
* «*
« t
ff*
* «
* C
*
X
*
* *
*
*
* *
** *
* * *
*
* «
* *
*
*
*
*
*
50
25
Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec,
Months
Figure 5. Seasonal mid-point BOD5 change at Bixby lagoon, 1976
-------
150
to
125
IT)
Q
O
50
25
0
* «
*
4 *
*
*
*
* *
*
t *
****
<
*
*
*
** «
*
*
***
* * * *
*
*«* K t
* * * t
*
«
*
* **
* t< *
* « * *
* * * * *
« « *
* * *
* *
« *
* * *
« * * «
* s * « «
*f *
* *** *
Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec.
Months
Figure 6. Seasonal effluent BOD- change at Bixby lagoon, 1976
-------
to
175
150
125
CO
100
w
H
EH
g
75
50
25
0
i
*
«
* *
* * **
C *.
* «*
**
* < *
*
t * **
*
<
*
*
* t
* «
* *
*
* *
*
*
4
*
*
X
*
*
*
** *
*
* *
* * «
X X
*
*
*
*
«**
*
*
*k ft
* V
* *#
*
* r *
« i
^
*
Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec
Months
Figure 7. Seasonal change of mid-point volatile suspended solids
at Bixby lagoon, 1976
-------
150
125
100
75
CO
H
EH
S 50
*.
M- it
* *
* **
*
*
**
*
«*
*
*
lk
*
tr t
* t
* *
*
x *
* *
X
*
*
**«
*
*****
* **
* * *
f *
* *
* *
*
*
«** *
**
*
<*«t
* » *
* * *«
*
*
*
*
*
25
0
Jan. Feb. Mar. Apr. May June July Aug. Sep. Oct. Nov. Dec
Months
Figure 8. Seasonal change of effluent volatile suspended solids
at Bixby lagoon, 1976
-------
TABLE 8. MONTHLY AVERAGE INFLUENT WATER QUALITY AT BIXBY LAGOON, 1976
tO
00
TESTS
PH
Alkalinity*
Total BOD5
Soluble BOD5
Total S.S.
Volatile S.S.
Total COD
Soluble COD
Phosphorus**
TKN
Anunonia-w
Fecal Coli. ,
xlOO/100 ml
Flow,
xlO gpd#
Jan.
6.9
165
368
222
323
230
664
312
36.5
42.9
31.0
-
Ill
Feb.
_
-
422
244
228
177
523
368
-
44.4
27.9
-
109
Mar.
7.1
162
414
227
236
107
671
319
37.3
63.6
25.1
133
123
Apr.
6.7
169
430
132
347
288
619
225
-
42.3
24.7
225
168
May
6.5
159
379
136
271
207
552
240
-
40.2
24.4
-
141
June
6.5
157
413
122
230
187
606
267
-
40.8
26.5
-
Ill
July
6.1
152
355
140
253
200
594
254
-
47.5
36.3
-
124
Aug.
6.4
144
213
105
282
255
589
22.3
-
36.3
22.3
-
222
Sep.
6.2
142
330
142
213
82
646
259
-
44.2
33.5
-
140
Oct.
6.3
163
388
136
230
180
773
278
-
47.1
40.4
-
124
Nov.
6.5
154
383
156
289
229
815
262
-
50.2
32.6
-
148
Dec .
6.3
143
283
119
134
96
619
224
-
44.3
28.5
-
148
Unless otherwise indicated, all units are mg/1 except for pH.
*Alkalinity as CaCO3.
**Actual tests performed were dissolved ortho-phosphate. For convenience, dissolved
ortho-phosphate was identified as phosphorus.
#1 gpd = 0.003785 m3/d.
-------
TABLE 9. MONTHLY AVERAGE MID-POINT WATER QUALITY AT BIXBY LAGOON, 1976
to
vo
TESTS
PH
Alkalinity*
Temperature , °C
DO
Total BOD5
Soluble BOD5
Total S.S.
Volatile S.S.
Total COD
Soluble COD
Phosphorus**
Fecal Coli.,
xlOO/100 ml
Total Coli.,
xlOO/100 ml
Jan.
7.3
142
5.7
10.6
68
55
93
64
147
65
38.6
Feb.
-
-
-
-
150
87
63
40
186
133
-
-
-
Mar.
7.7
157
16.6
6.7
60
40
101
63
191
111
43.6
113
213
Apr.
6.8
111
19.3
7.3
99
37
73
59
216
84
-
162
328
May
6.6
72
21.0
4.4
71
9
80
74
183
64
-
-
-
June
6.5
71
25.9
3.5
87
13
61
53
175
104
-
-
-
July
6.6
81
28.7
6.9
56
14
66
50
139
53
-
-
Aug.
6.8
74
27.4
7.7
79
8
102
87
204
69
-
-
Sep.
6.7
52
25.0
7.1
87
5
109
78
185
68
-
-
Oct.
6.4
45
14.0
8.4
105
8
166
140
268
57
-
-
-
Nov.
6.6
38
9.5
8.4
110
9
120
98
248
68
-
-
Dec.
6.4
74
7.4
7.9
52
12
51
40
173
66
-
-
-
Unless otherwise indicated, all units are mg/1 except for pH.
*Alkalinity as CaCOo.
**Actual tests performed were dissolved ortho-phosphate. For convenience, dissolved
ortho-phosphate was identified as phosphorus.
-------
TABLE 10. MONTHLY AVERAGE EFFLUENT WATER QUALITY AT BIXBY LAGOON, 1976
OJ
o
TESTS
PH
Alkalinity*
Temperature , °C
DO
Total BOD5
Soluble BOD5
Total S.S.
Volatile S.S.
Total COD
Soluble COD
Phosphorus**
TKN
Ammonia -N
Fecal Coli. ,
xlOO/100 ml
Total Coli.,
xlOO/100 ml
Jan.
7.6
91
5.2
13.5
48
36
51
31
85
41
32.9
7.7
4.6
-
Feb. Mar.
9.2
149
16.0
9.0
41 39
32 36
59
43
154
107
39.9
19.2 22.2
13.9 14.8
53
129
Apr.
6.9
80
19.2
5.7
36
13
67
41
128
70
-
7.5
3.0
80
178
May
6.9
59
20.3
8.3
27
6
44
39
119
59
104
5.6
1.2
-
June
6.7
69
26.1
3.9
26
9
97
52
146
60
-
6.3
1.3
-
July
6.7
75
29.3
4.3
20
10
71
33
75
48
38
5.0
0.6
-
Aug.
7.1
69
28.2
6.4
14
5
38
25
60
44
-
2.7
0.5
-
Sep.
8,1
63
24.3
9.5
40
4
28
16
61
30
-
3.9
0.1
-
-
Oct.
7.7
62
12.8
10.6
19
6
51
34
85
39
-
4.3
0.2
-
-
Wov.
7.1
59
8.6
11.7
24
7
56
39
116
52
-
5.9
0.1
-
Dec.
6.7
49
6.6
11.5
21
5
36
21
110
55
8.4
1.0
-
Unless otherwise indicated, all units are mg/1 except for pH.
*Alkalinity as CaCO3.
**Actual tests performed were dissolved ortho-phosphate. For convenience, dissolved
ortho-phosphate was identified as phosphorus.
-------
W
3
EFFLUENT-
I
INFLUENT-
I
-MID-POINT
1 j
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 9. Monthly average pH value at Bixby lagoon, 1976.
31
-------
30
25
20
15
w
^
10
MID-POINT-
EFFLUENT-
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 10. Monthly average water temperature at Bixby lagoon, 1976
32
-------
180
160
tn
e
140
120
8 100
u
H
Hi
£
Hi
80
60
40
20
-INFLUENT
.MID-POINT
I I
EFFLUEN
r
!
I
~i
! I
I l
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 11. Monthly average alkalinity at Bixby lagoon, 1976.
33
-------
14
13
12
11
10
EFFLUENT,
MID-POINT
I .*.
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 12. Monthly average dissolved oxygen at Bixby lagoon, 1976.
34
-------
500
400
J 300
Q
O
m
200
100
I
-INFLUENT
-MID-POINT
r
i i
EFFLUENT 1 1
EFFLJJ
/
I
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 13. Monthly average total BOD5 at Bixby lagoon, 1976.
35
-------
250
200
H50
tn
g
m
Q
O
CQ
W
D100
50
I 1
! 1
I
i_
EFFLUENT.
MID-POINT
~]
L_
INFLUENT,
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 14. Monthly average soluble BOD5 at Bixby lagoon, 1976.
36
-------
400
350
300
\250
en
200
150
100
50
INFLUENT-
MID-POINT-
I I
I I
I I
r
i !
I
J
EFFLUENT-
I
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 15. Monthly average total suspended solids at Bixby
lagoon, 1976.
37
-------
300
250
200
CO
co'150
w
EH
a
100
50
INFLUENT.
MID-POINT-
I 1
l I
r
I 1
I I
I I
I
-EFFLUENT
|
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 16. Monthly average volatile suspended solids at Bixby
lagoon, 1976.
38
-------
900,
800
700
600
^500
Q
O
U
400
300
200
100
-INFLUENT
MID-POINT*
r
I
\
r
.VJ
I
I I
I I
EFFLUENT-
'ili
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 17. Monthly average total COD at Bixby lagoon, 1976.
39
-------
400
350
300
.250
Q
0200
rI
§
O
CO
150
100
50
.INFLUENT
I !
!
MID-POINT
~l
I I I
I
EFFLUENT
_i «_
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 18. Monthly average soluble COD at Bixby Lagoon, 1976.
40
-------
70
60
50
40
30
20
10
-INFLUENT
-EFFLUENT
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 19. Monthly average total Kjeldahl nitrogen at Bixby
lagoon, 1976
41
-------
45
40
35
30
r-l
\
e
INFLUENT
S20
o
15
10
.EFFLUENT
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sep. Oct. Nov. Dec.
MONTHS
Figure 20. Monthly average ammonia nitrogen at Bixby
lagoon, 1976.
42
-------
at any month of the year.
The analysis of algae was performed qualitatively only and
analysis was made to the genus level. Based on comparative ob-
servation, the population density of the different algae are re-
ferred to as very abundant (VA) or rare (R). Algal analysis
performed at the Bixby lagoon are tabulated in Table 11.
TABLE 11. ALGAL GENUS IDENTIFIED* AT BIXBY LAGOON
ALGAL GENUS POPULATION DENSITY
(From mid-point of lagoon system)
Ankistrodesmus VA
Euglena R
Golenkinia R
Oocystis R
Scenedesmas R
(From effluent of lagoon system)
Ankistrodesmus VA
Chlorella R
Euglena R
Golenkinia R
Pediastrum R
Identification was performed by Bill Cox, Pollution Control
Section, Tulsa City-County Health Dept., Tulsa, Oklahoma; on
single sample.
43
-------
SECTION 7
PROJECT DATA EVALUATION AND ANALYSIS
The stated secondary objective in the proposal is to utilize
the generated data to evaluate the effectiveness of the multi-
system lagoon to perform in accordance with its design criteria
and the ability to meet the secondary treatment standards as
established by the Federal Water Pollution Control Act Amendments
of 1972.
This section of the report will discuss, in relation to the
stated secondary objectives, the results of analysis of data co-
llected. However, before the discussion of the results, a brief
literature review will perhaps be helpful to readers who are un-
familiar with the modelling aspects of biological waste treatment.
BRIEF LITERATURE REVIEW IN BIOLOGICAL WASTE TREATMENT MODELLING
Literatures reviewed indicated that there exists a proli-
feration of design methods for biological treatment facilities.
There are, however, precious few articles on the analysis of
existing biological treatment facilities. A study of operational
parameters in facultative lagoons is essential if one is to com-
pare the performance efficiencies against design values.
Horsfall (8) points out that little is understood of the bio-
chemical reactions that take place in facultative lagoons. Enzy-
matic processes do not necessarily occur in the same environment
as the bulk of water. Also, if cells encounter food sources at
low concentration, they develop a mechanism for concentrating
food around the cell in a separate layer. These cells are thus
able to consume food that cannot be transported directly through
the cell walls. The cells excrete enzymes that break up the food,
thereby enabling transport across the cell wall.
A variety of life forms degrade organic wastes. It is impo-
ssible to predict which of the several steps these organisms use
to consume the waste is rate-controlling. The problem is compli-
44
-------
cated by the fact that domestic and industrial wastes are prac-
tically impossible to classify at a level of detail essential for
theoretical biochemical degradation studies. Horsfall suggests
that lagoon design procedures are simplistic and that the fact
that biochemical facilities operate efficiently is surprising in
view of the uncertainties in design methods.
Shastri, Fan and Erickson (9) have developed a non-linear
least squares method for estimating the parameters in a nine
parameter stream water quality model. However, as Brown and
Berthouex (10) have pointed out, the model is not convincing
because the fundamental premises on which the model is built are
themselves questionable. They argue that using highly non-linear
kinetic models for BOD removal studies is questionable if numerous
parameters are arbitrarily hypothesized as being revelant. In
fact, practically any data set could be forced to fit a nine-
parameter, non-linear model. Therefore, a mere parameter esti-
mation exercise does not validate the model per se. This is
simply because innumerable "counter-models" could be proposed and
shown to fit the same data equally well, regardless of the theore-
tical validity of the models themselves. This issue lies at the
heart of the question of model calibration versus model testing
and validation against observed data which was not included in
model calibration originally. As a result, complex models re-
quire very extensive field data collection. A corollary of this
statement would be that, in the absence of extensive field data,
models should be constructed to be as simple as possible. The
real problem therefore, is not the lack of theoretical models but
rather the shortage of consistent and reliable experimental data
drawn from long term water quality monitoring studies of opera-
ting facilities. In fact, an even more fundamental problem often
is the lack of good waste characterization studies.
Viraraghavan (11) attempted such a waste characterization
study between BOD5, COD and TOG for a raw sewage, septic tank
effluent and polluted groundwater. Viraraghavan made the fo-
llowing conclusions:
(a) For raw sewage the correlation coefficients be-
tween 6005, COD and soluble organic carbon were
not significant at the 5 percent level.
(b) For polluted groundwater the correlation coeffi-
cient between COD and soluble organic carbon was
significant at the 1 percent level.
However, these conclusions may be entirely premature since
45
-------
Viraraghavan used only ten raw sewage, 20 septic tank effluent
and 28 polluted groundwater samples in the statistical analysis.
Besides, other essential parameters such as suspended, dissolved,
settleable, and total solids as well as nutrients and their de-
gradation by-products were completely ignored in the characteri-
zation. A final point in such an exercise is simply that there
is no logical necessity for different waste waters and surface
or groundwaters to have similar statistical profiles for various
pollutants. It is obvious that each kind of wastewater has uni-
que characteristics and that any extrapolation to other kinds of
wastewater is not logical.
Thus, studies which report field data for the major water
quality constituents on a seasonal basis are useful. They make
it possible to confirm or deny the reliability of the design
procedure which was used to build the facility in the first place.
In a stream water quality modeling effort, field data would be
similarly essential to enable model calibration. Additional
data, not used in the model calibration, would be necessary for
model validation exercises.
This study shows in the succeeding sections that influent
characterization, treatment process efficiency correlations, and
effluent characterization and correlation against influent data
are all possible using simple multi-parameter linear models.
A final effort in the study addresses the important problem
of attempting to derive characteristic design parameters from
operational information. The complications caused by seasonal
temperature variations are, specifically, addressed in an attempt
to see how well the^standard lagoon design method formulas fit
observed performance data.
RESULTS AND ANALYSES
The discussion on results and analyses, will be divided
into seven sections as follows: (results from regression analysis
are summarized in Appendix B).
(i) Computing statistical averages and standard deviations.
(ii) Characterization of the wastewater entering the lagoon
system (influent).
(iii) Calculation of removal efficiencies for pollutants
listed on the NPDES permit and also for other parame-
ters. (These removal efficiencies were computed for
each cell as well as for the total system). Correla-
tion of pollutant removal efficiencies against influent
46
-------
properties and parameters for each cell and for the
total system.
(iv) Correlation of lagoon mid-point properties (between
cell 1 and cell 2) with influent properties.
(v) Correlation of effluent parameters with influent pa-
rameters .
(vi) Fitting the standard aerated lagoon design equations
to actual performance data for biochemical oxygen de-
mand (BOD), with temperature dependency of the reac-
tion rate constant included.
(vii) Fitting the CSTR and Plug Flow Models for different
rate mechanism to a set of data which has a constant
temperature.
(i) Computing statistical averages and standard deviations;
Descriptive statistics of the experimentally determined pa-
rameters are summarized in Tables 3-5. The statistics of the
parameters at the influent are presented in Table 3, the mid-
point and effluent statistics are presented in Tables 4 and 5,
respectively.
Examination of these tables indicate the wide variation of
the experimentally determined water quality data.
As shown in Table 3, the average value of the influent 8005
is 368 mg/1 and has a standard deviation of 90. The volatile
suspended solids have an average value of 201 mg/1 and a stan-
dard deviation of 116. At the outset, a close study of these
standard deviations indicates that a waste characterization
attempt would have dubious success. This hypothesis is confirmed
in subsequent sections.
Tables 4 and 5 indicate similar wide variations. For inst-
ance, the effluent BODs has an average value of 30 mg/1 and a
standard deviation of 21. An attempt to predict the mid-point
and effluent parameters was ambiguous at best. In the linear
regression equations the constant term was always high, indica-
ting that the correlating parameters only"partially "explain"
the dependent variable.
(ii) Characterization of wastewater entering the
lagoon system;
Raw wastewater properties dictate the lagoon performance.
Influent wastewater properties at a lagoon system can vary on
an hourly, daily, monthly and seasonal basis. Hourly fluctua-
tions can be very different because total flow and pollutant
47
-------
loadings are particularly high after morning and evening hours.
Mid-afternoon and night-time conditions are usually less severe.
In the Bixby study, it was decided to take, samples composited
throughout the day so that the effect of hourly fluctuations
could be smoothened out.
Despite such daily averaging, there remains a high degree of
variation in raw wastewater properties by season. This, along
with climatic considerations, causes the performance to vary con-
siderably between the seasons.
The federal NPDES permit does not specifically require raw
wastewater analysis. The apparent emphasis in the permit system
is on the quality of the treated wastewater. Due to this, some
communities do not feel that influent monitoring is necessary on
a routine basis. However, for design calculations, or for per-
formance grading studies, influent characteristics data are
equally important as those of the effluent.
An examination of Tables B-l to B-6 (in Appendix B) shows
the several significant correlations attempted between various
influent parameters for different seasons. Table B-l shows the
stepwise regression which led to the identification of signifi-
cant variables for explaining selected dependent variables. The
low correlation coefficients indicate that the regression equat-
ions are a poor substitute for experimental data, and most likely
are excluding significant parameters from variables considered in
the regression analysis.
(iii) Correlation of pollutant removal efficiencies;
As may be expected, the lagoon efficiencies for BOD removal
are consistently high except possibly during winter. From the
one year data period of this project, the overall BOD removal
efficiency averaged about 92%. This, in conjunction with the
annual average effluent BOD5 concentration of 29 mg/1, shows the
Bixby lagoon to be substantially in compliance with the federal
requirements of secondary treatment for BODg.
The overall removal efficiency for BOD was found to corre-
late primarily only with the temperature of the wastewater. on a
monthly basis, effluent BOD5 concentration was below 30 mg/1 in
seven months out of the year. Low BOD values seemed to coincide
with the warm temperature of summer months while lagging into the
late autumn months. Further explanation is difficult because of
the uncertainties involved in the experimental determination of
influent BOD caused by flocular dispersion of organic material.
48
-------
BOD removal efficiency correlation for cell 2 is quite good with
BOD at the end of cell 1. This reinforces the suspicion that raw
influent BOD fluctuations are quite large; the high standard
deviation of 89 mg/1 again pointe in the same direction.
Total suspended solids (TSS) removal efficiency averaged at
76%, while the average effluent TSS was 54 mg/1 on an annual
basis. This shows that the lagoon fails to meet federal second-
ary treatment limitations for suspended solids. Examination of
the monthly average effluent water quality (see Table 10) revealr-
ed that for TSS only one month out of the year did the effluent
TSS level meet the standard.
The fecal coliform density data of raw wastewater at the
Bixby lagoon system are in the range of 105/3.00 mi. with this
concentration of coliform bacteria in the wastewater, even a re-
duction efficiency as high as 98% may still result in an effluent
with fecal coliform exceeding the 200/100 ml secondary effluent
standard. Data of effluent total and fecal coliform collected at
Bixby are in the range of 104 and 103/100 ml respectively, indi-
cating non-compliance with the federal secondary treatment re-
quirement. In view of this inadequacy in bacteriological treat-
ment, it is suggested here that perhaps a maturation pond added
will greatly improve the bacterial removal efficiency of the
Bixby lagoon system or disinfection should be used if the water
quality standards required meeting effluent numbers less than
200/100 ml.
(iv) Correlation of lagoon mid-point properties;
At the mid-point of the lagoon (between cell 1 and cell 2)
system, the annual average 3005 and TSS were found to be 84 mg/1
and 89 mg/1 respectively. This shows that the bulk of the BOD
and TSS removal occurred in cell 1. This is in keeping with
theoretical considerations which predict a BOD removal rate pro-
portional to the average concentration of BOD in the cell. Simi-
larly, the bulk of the TSS in the influent settle down rather
quickly in cell 1. Cell 1 is also more vigorously aerated than
cell 2 and this surely complicated the analysis. Above all, the
growth of algae in cell 2 also contributed significantly to TSS.
(v) Correlation of effluent properties with influent
properties;
As discussed under (ii) above, the Bixby lagoon meets the
EPA criteria for BOD5 but not for TSS, or fecal coliform density.
49
-------
Correlations were attempted for total and soluble BODs and
COD, total and volatile suspended solids and total Kjeldahl nit-
rogen in the lagoon effluent. In general, it was not found fea-
sible to correlate effluent properties with influent data with
any high degree of reliability, for in cases where correlation
did exist, they were found to be erratic in nature. This is
perhaps partly because of the inscrutable random scattering in
the influent and effluent peoperties and the fact that the effect
of algae has not been considered.
A further complication is the fact that the lagoons' average
residence time (based on plug flow) is nearly eighty-two days.
This time lag is very significant and an attempt to correlate
influent and effluent properties has proved this to be true. On
the other hand, an attempt to correlate influent and effluent
data taken eighty-two days apart would ignore the effect of in-
tervening parameters like climatic and other cumulative factors
during those eighty-two days. It can be said, therefore, that
at this time there is no satisfactory method for correlating
effluent parameters with influent values for a high retention
time aerated lagoon unless during the entire retention period
all intervening factors could be controlled. This fact also
casts some doubt on ones ability to accurately compare the de-
sign calculations against actual operating data. Ignoring the
time lag or considering the average values seems to be the only
viable alternatives at the moment.
(vi) Curve-fitting of design equation to operating data;
The standard design equation for aerated lagoons (11) is:
(S0-Se)/(Xvt) = k Se (1)
So = influent BODc concentration, mg/1.
Se = effluent 6005 concentration, mg/1.
Xv = average or equilibrium concentration of volatile sblids
(active bio-mass) in lagoon, mg/1.
t = detention time = V/Q, days.
k = specific organic removal rate coefficient 1/mg-day.
In the above design equation it is a normal practice to plot
(S0-Se)/t versus Se. A linear regression is then carried out to
obtain the slope (kXy). The reason why k and X^ are lumped to-
gether in most studies is that prediction of Xy in an aerated
50
-------
lagoon which has zero recycle is often impossible. The inter-
cept from this plot (which theoretically should be zero) is
labeled as a "residual term". The alternative to having a
residual is forcing the line through the origin and decreasing
the degrees of freedom of the regression equation for y by 1.
The real problem with the above mentioned plot is that the
term, S , appears in the numerator of both the x and the y-axis
term. fhis, as discussed by Sherwood and Reed (12), is a cardi-
nal error since highly erroneous values of S would be disguised
under such a plot.
The correct procedure for plotting the design equation is
really:
(S0-Se)/Se = k Xyt (2)
and to do a least squares fit which forces the line to pass
through the origin. Such a plot of (S /S - 1) versus t would
show two independent variables on either axis and would not
suffer from the above mentioned deficiencies.
Before such a plot is made the temperature effect on the
specific organic removal rate constant must be considered. The
standard approach (9) is:
k = kQ 0CT-20) (3)
where
k = specific organic removal rate at 20°C; 1/mg-day.
0 = temperature coefficient (dimensionless)
T = temperature of the waste °c
Substituting (3) in (1) and taking logarithms yields In
(S -S )/S ) =
In (kQXv V) - 20(ln 0) + (T 2n § - fn Q) (4)
a plot of these synthesized variables In ((S -S )/S ) versus
(Tin 0 - In Q) should be forced through a sl8pee ofe1.0. The
intercept is then ln(k X V).
There is no really definitive recommendation in the litera-
ture as to whether or not one should treat X as an independent
design parameter in aerated lagoon design, ^or this reason, an
51
-------
attempt was made in this study to determine whether extensive
operating data gathered over a period of one year could be used
to elucidate the problem.
The methodology used to segregate the effect of Xv, assum-
ing it to be statistically significant, was to rewrite equation
(4) as:
ln((S0- Se)/S0) = In (k0 V) - 20 (In 9)
+ (T In 9 - In Q + In X ---------- (5)
where Xv has been combined with the synthetic independent vari-
able term.
It should be recognized that Xv reduced very rapidly from
the entrance to the first cell to the exit of the first cell.
The variation in the second cell is not so marked because of the
rapid growth of algae which interfere with the measurement of the
volatile suspended solids (VSS). In other words, the fraction of
the VSS which is biologically active, x, varies inversely with
the relative abundance of algae. There was no attempt to isolate
the value of x from the measured VSS value in this study. Such
a determination would have to be based on extensive pilot plant
experiments in which- all other operating conditions could be
carefully controlled. Such control was not possible in the Bixby
lagoon system.
The Xv term, as used in the above equations, therefore
should be thought to include the multiplier x. The net effect of
using Xv without x in the regression exercise would be to bias
the value of the intercept term (In kQV - 20 In 9) in equation (5)
If the basic data variables in equation (5) were "noisy",
this could easily conceal the true significance of x in the re-
gression. The Bixby study has shown that these data items do in
fact contain a great deal of random spread and hence the error
involved in ignoring x is probably not significant.
Equation (5) was regressed for two alternatives:
(a) Cell 1, with So measured at raw influent, Se» T, Xv
measured at cell 1 exit.
(b) Cell 2, with So measured at cell 1 exit, Se, T, Xv
measured at cell 2 exit (i.e. at lagoon system exit).
Eckenfelder reported the temperature coefficient, 0 for a
pulp and paper mill waste and for a board-mill waste to be
52
-------
varying from 1.07 to 1.09 for filtered and settled samples. (13)
Herman and Gloyna using municipal wastewater for a temperature
range of 25°C to 35°C found the optimum rate constant 1(35 to be
0.60, with e value equal to 1.085. (14) Mancini and Barnhart re-
ported that for aerated lagoons, e varies from 1.06 to 1.18. (15)
Because the value of the temperature coefficient 0 is not
known with certainty, it would have to be varied until the best
least squares lines could be obtained. Seventeen values of e be-
tween 1.0 and 1.2 were attempted in each of the two alternatives.
The value of 9 which gave the best fit in terms of the lowest re-
sidual sum of squares of the errors and/or the best correlation
coefficient (r) was chosen.
The regression exercise was repeated for equation (4) which,
as explained earlier, helped produce an average value for the
product k0Xv rather than ko alone.
Results of these regression exercises for both equation (4)
and (5) are tabulated in Table 12. All regressions were found to
have F values which were statistically insignificant at the con-
fidence level of 95%. Correlation coefficients were also found
to be rather low, probably due to noisy data and ignoring of the
effect of algae.
The most impressive result obtained from these regressions
was that the temperature coefficient values e were 1.01 and 1.035
for equation (4) and 1.05 and 1.035 for equation (5) for cell 1
and cell 2 reapectively. This is in strong agreement with Adams
and Eckenfelder's (16) reported general value of 1.035.
TABLE 12. EVALUATION OF TEMPERATURE COEFFICIENT
REACTOR Xv
CELL MODEL VARIABLE? SSr
1
1
1
2
2
2
CSTR
CSTR
Plug Flow
CSTR
CSTR
CSTR
Yes
No
No
Yes
No
No
49.42
16.74
6.02
130.70
76.20
38.20
SSy
22.4-
22.4
5.9
62.2
62.2
27.6
r2
0.062
0.269
0.239
0.068
0.072
0.062
VALID
CASES
72
72
72
75
75
75
e
1.050
1.035
1.020
1.035
1.010
1.000
53
-------
(vii) Fitting the CSTR and Plug Flow Models for different
rate mechanisms to a set of data which has a constant
temperature;
As can be observed from data tabulated previously, the temp-
erature of the wastewater remained fairly constant for the months
June through September. Average temperature was 28 °C, with a
standard deviation of 1.2. Since the average retention time in
each of the two cells is 40 days (based on plug flow), it is ne-
cessary to choose data for model fitting which has the same temp-
erature over an extended period of time. Accordingly, the data
for July to September were used in the following models.
The basic design equations for a plug flow reactor and a
CSTR under steady state conditions are respectively:
fV fSe
I dv/Q = ds/(-r) and Q(SO- Se)/V = -r
Jo JSQ
In the above equations: V = volume of reactor (m^)
0 = flow rate (m3/day)
S = concentration of BODj mg/1.
r = rate of reaction mg/l/day.
Both these design equations represent ideal extremes between
which .the lagoons perform. Different kinetic models for the rate
of reaction were substituted in these design equations. These
equations were simplifies and linearized by taking logarithms.
The possibility of treating the volatile suspended solids as a
variable was also considered.
Table 13 summarizes the results for cell 1 and Table 14 for
cell 2. In these tables the first column represents the reactor
model, the second column the rate equation that was used. The
third column, SSr, is the residual sum of the squares - a measure
of the deviation of the observed values from the values predicted
by the regression equation. Column 4, SSV, is a measure of the
deviation of the observed value from the average value of the
dependent variable.
An examination of Tables 13 & 14 show that none of the models
are "better" than just predicting an average value for the lagoon
performance, that is, none of the models explain the data suffic-
iently. This can be explained partly because the kinetic models
do not account for algae growth. Actually, the poor results in
this modeling exercise are in keeping with Horsfall's (8)
54
-------
contention that existing design equations are simplistic and do
not reflect the complexity of the biochemical reactions.
TABLE 13. SUMMARY OF MODEL TESTING, BIXBY CELL 1
REACTOR MODEL
Plug Flow
Plug Flow
Plug Flow
CSTR
CSTR
CSTR
CSTR
CSTR
CSTR
K = k Xv
25 DATA POINTS,
TABLE 14
REACTOR MODEL
Plug Flow
Plug Flow
Plug Flow
CSTR
CSTR
CSTR
CSTR
CSTR
CSTR
RATE EQUATION
r = K
r = K S
r = (K S)/S0
r = K
r = K S
r = (K S)/S0
r = V V
i /W -A*T
i ~" JX **\7 ^
r - (k ^ S)/S0
AVE. TEMP. = 28 °C,
. SUMMARY OF MODEL
RATE EQUATION
r = K
r = K S
r = (K S)/S0
r = K
r = K S
r = (K S)/S0
r = V Y
* IX ^*\7
r = k xv S
r = (k Xv S)/S0
ssr
2.14
2.18
3.30
2.14
3.95
4.08
6.41
12.55
13.20
STD. DEV
TESTING,
ssr
12.11
10.05
7.23
12.11
20.32
31.74
26.72
31.95
46.39
ssy
0.75
0.89
1.39
0.75
3.86
4.61
0.75
3.86
4.62
. = 1.8
BIXBY CELL 2
ssy
7.36
5.59
5.94
7.36
14.53
24.78
7.36
14.53
24.78
**
0.159
0.159
0.023
0.159
0.150
0.198
0.019
0.163
0.128
s
0.068
0.067
0.015
0.068
0.073
0.080
0.052
0.092
0.034
K = k
25 DATA POINTS, AVE. TEMP. = 28 °C, STD. DEV.
= 1.5
55
-------
REFERENCES
1. Marais, G. V. R. New Factors in the Design, Operation and
Performance of Waste Stabilization Ponds. Bull. Wld. Hlth.
Org., 34:737-763, 1966.
2. Barsom, G. M., and Rychman, D. W. Evaluation of Lagoon Per-
formance in Light of 1965 Water Quality Act. In: Second In-
ternational Symposium for Waste Treatment Lagoons, Kansas
City, Missouri, June 1970.
3. Barsom, George. Lagoon Performance and the State of Lagoon
Technology. U.S.E.P.A., Wash. D.C., June 1973.
4. Coleman, M. S., Henderson, J. P., Chichester, H. G., and
Carpenter, R. L. Agriculture as a Means to Achieve Effluent
Standards. Env. Prot. Tech. Series EPA-660/2-74-041.
5. Eckley, L. E., Canter, L., and Reid, G. Operation of Stabi-
lization Ponds in Tropical Area. U.S. Army Medical Research
and Development Command, Office of the Surgeon General, Wash.
D.C., 1974.
6. Nie, N. H., Hull, C. H., Jenkins, J. G., Steinbrenner, K.,
and Bent, D. H. Statistical Packet for the Social Sciences.
2nd. Edition, McGraw-Hill, Inc., 1975.
7. Standard Methods for the Examination of Water and Wastewater.
13th. Edition. American Public Health Association, American
Water Works Association and Water Pollution Control Federation.
1971.
8. Horsfall, F. L., III. Biochemical Augmentation of Wastewater
Treatment. Water Pollution Control Federation Highlights, 14
(2), February 1977.
9. Shastry, J. S., Fan, L. T., and Erickson, L. E. Nonlinear
Parameter Estimation in Water Quality Modeling. Journal of
the Environmental Engineering Division, ASCE, 99(EE3):315-331,
June 1973.
56
-------
10. Brown, L. C., and Berthouex, P. M. Discussion on Nonlinear
Parameter Estimation in Water Quality Modeling. Journal of
the Environmental Engineering Division, ASCE, 100(##1):226-
227, February 1974.
11. viraraghavan, T. Correlation of BOD, COD, and Soluble Org-
anic Carbons. Jour. Water Poll. Con. Fed., 48:2213-2214,
Sept. 1976.
12. Sherwood, T. K., and Reed, C. E. Applied Mathematics in
Chemical Engineering. 1st. Edition. McGraw-Hill Book Co.,
Inc., 1939. pp. 295-299.
13. Eckenfelder, W. W., Jr. Industrial Water Pollution Control.
McGraw-Hill, New York.
14. Herman, E. R., and Gloyna, E. F. Waste Stabilization Ponds.
I. Experimental investigations. II. Field practices. III.
Formulation of design equations. Sewage Ind. Wastes, pp.
30, 511, 646, 963.
15. Mancini, J. L., and Barnhart, E. L. Industrial Waste Treat-
ment in Aerated Lagoons. Advances in Water Quality Improve-
ment, (Ed. by Gloyna, E. F., and Eckenfelder, W. W., Jr.)
University of Texas Press, Austin, Texas, 1968.
16. Adams, C. E., Jr., and Eckenfelder, W. W., Jr. Process De-
sign Techniques for Industrial Waste Treatment. 1974. pp.181.
17. Methods for Chemical Analysis of Water and Wastes. Methods
Development and Quality Assurance Research Laboratory, U.S.
E.P.A., Wash. D.C., EPA-625/6-74-003.
18. Aguire, J., and Gloyna, E. F. Design Guides for Biological
Wastewater Treatment Process: Waste Stabilization Pond Per-
formance. University of Texas, Austin, Texas, 1970.
19. Neel, J. D., McDermott, J. H., and Monday, C. A. Experimen-
tal Lagooning of Raw Sewage at Fayette, Missouri. Jour, of
Water Poll. Cont. Fed., 33(6):603-641, 1961.
20. Sewage Stabilization Ponds in the Dakota: An evaluation of
the use of stabilization ponds as a method of sewage disposal
in cold climates. Vol. 1&2, Joint Report: N & S Dakotas
Dept. of Health, Robert A. Taft Sanitary Engineering Center,
Cincinnati, Ohio, 1975.
57
-------
APPENDIX A
SUMMARY OF A COMPARATIVE STUDY OF PARAMETERS
USED FOR MEASURING WASTE TREATMENT LAGOON PERFORMANCE
Appendix A is a summary of the determination of meaningful
parameters that the author proposed to be used as routine operat-
ional tests. Table A-l is a tabulation of the parameters that
were measured at five lagoon systems. Panama Lagoons are U.S.
Army lagoons in the Canal Zone. (5) Austin Lagoons are experimen-
tal lagoons. (18) Fayette and South Dakota lagoons are both muni-
cipal lagoons. (19, 20)
Table A-2 is the result of determination of tests necessary
for the evaluation of performance of the various type of lagoons.
This table is developed as a result of information gathered from
other lagoon studies and this project. In Table A-2, the most
important test as indicated are also the tests proposed to be used
as routine operational tests. These tests are important to both
design'evaluation and routine operational control. The second
group of tests, rated as important are pertinent to design evalua-
tion considerations. The third group or the less important tests
are the ones that are not apparent in their effect on design eva-
luation, but their overall important should not be entirely negl-
ected.
In Table A-2, the noticeable absence of the nutrient tests
among the important tests is due to the fact that in waste treat-
ment lagoons treating primarily domestic waste, nutrients are not
limiting factors in regard to lagoon performance. The exclusion
of the dissolved oxygen test from the most important test group is
that dissolved oxygen is usually at a reasonably high level and
therefore it is not necessary to test it routinely.
58
-------
TABLE A-l. COMPARISON OF PARAMETERS MEASURED AT FIVE LAGOON
SYSTEMS
PARAMETERS BIXBY
LAGOON
PH
Acidity
Alkalinity
Temperature
DO
Total BOD5
Soluble BOD5
Total S.S.
Volatile S.S.
Settleable S.
Total COD
Soluble COD
Phosphorus
TKN
Anrmonia-N
Nitrate-N
Nitrite-N
Organic-N
Algal Count
Fecal Coli.
Total Coli.
Flow, Influent
Flow, Effluent
Other
X
X
X
X
X
X
X
X
X
X
X
X
X
X*
X*
X
X
X
a
PANAMA AUSTIN
LAGOON LAGOON
X X
X*
X
X X
X X
X X
X* X
X*
X*
X X
X
X
X
X*
X
X
X X
X X
TOC
FAYETTE
LAGOON
X
X
X
X
X
X
X
X
X
X
X
b
SO. DAKOTA
LAGOON
X
X
X
X
X
X
X
X
X
X
X
C
*Tests were discontinued later.
a - Algal determination.
b - Chloride, detergent.
c - Turbidity, chloride, sulfide.
59
-------
TABLE A-2. PRELIMINARY IDENTIFICATION OF TESTS NECESSARY FOR THE
PERFORMANCE EVALUATION OF EACH TYPE OF LAGOON.
TESTS
NON-AERATED LAGOONS
ANAEROBIC AEROBIC FACULTATIVE MATURATION
pH X
Acidity *
Alkalinity
Temperature X
DO, Effluent
Total BOD5 X
Soluble BOD5 X
Total S.S. *
Volatile S.S. *
Total COD
Soluble COD
Phosphorus
Ammonia -N
TKN
Nitrate-N
Nitrite-N
TOC
Sulfide X
Turbidity
Algal Count
Fecal Coli.
Total Coli.
Flow
Odor X
X
*
*
X
X
X
X
X
X
X
X
X
*
X
X
X X
*
*
X X
X *
X X
X X
X X
X
X
X
X
*
* *
X
* *
X X
X X
AERATED LAGOONS
AEROBIC FACULTATIVE
X
*
*
X
*
X
X
X
X
X
X
X
*
X
X
X
*
*
X
*
X
X
X
X
X
X
X
*
X
X
EXT-AERATION
X
*
*
X
*
X
X
X
X
X
X
X
*
X
X
Unless indicated, tests should be per-formed at both influent and effluent points.
X - Most important tests. X - Important tests. * - Less important tests.
-------
APPENDIX B
RESULTS OF REGRESSION ANALYSIS
TABLE B-l. SUMMARY OF PRELIMINARY REGRESSION PAIR. JAN.-DEC. 1976
Characterization of Waste
Dependent
Variable
V011, COD IN
en
K1
V013 TSS IN
V014 VSS IN
voo7 T:
-------
TABLE B-2. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JAN.-DEC. 1976.
to
Characterization
Dependent
Variables
V011 TOTAL COD IN
V013 TSS IN
VC11 TOTAL COD IN
VC07 TKN
V014 VSS IN
V007 TXS IN
V010 SOL BOD IN
VOI2 SOL COD IN
of Waste
Independent
Variables
V007 TKN -IN
7009 TOTAL BOD IN
V013 TSS IN
V007 TKN IN
V009 TOTAL BOD IN
V015 FLOW GPD
V013 TSS .IN
7006 AMMONIA IN
V009 TOTAL BOD IN
V011 TOTAL COD IS
Coefficient In
Regression
Equation
2.371184
0.2984597
0.3044201
356.9379
2.750073
143.9223
0.2992710
545.3842
-7.6671401E-05
56.53597
0.7334903
-2.483477
0.4309353.
33.3799
0.24G3666
63.27534
0.1438168
166.5253
Confidence
Level
99.99
98,18
95.65
99.98
99.99
99.37
99.99
99.97
2
r
0.204
0.046
0.033
0.102
0.777
0.061
0.155
0.094
Standard
Error
125.70
139.34
140.23
11.5
55.45
11.97
52.04
67.02
-------
TABLE B-3. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JAN., FEB., DEC. 1976
en
OJ
Characterization
Dependent
Variables
V011 TOTAL COD IN
V013 TSS IN
V011 TQTA1, COD TM
VC07 TKJT TX
V014 VSS IN
VC07 r/QI IN
V010 SOL BOD IN
V012 SOL COD IN
of Waste
Independent
Variables
V007 TKN IN
V009 TOTAL BOD IN
V013 TSS IN
V007 TKN IN
VO09 TOTAI. BOD TH
VO15 FT OW* RPT)
V013 TSS IN
V006 AMMONIA IN
V009 TOTAL BOD IN
V011 TOTAL COD IN
Coefficient In
Regression
Equation
2.493559
3.613323E-02
0.5352311
388.1805
1.719844
178.1662
0.7976157
-21.15965
0.3753874
32.51137
0.2987844
91.34779
7.9981E-02
253.0131
Confidence 2 Standard
Level r Error
64.02 0.145 144.99
32.51 0.006 131.1
rtyRTfrr ATTOM ----
rfyRTJTT /ITTOM -
99,99 0.888 37.88
85.24 0.061 5.97
99.74 0.280 55.67
68.73 0.03 71.74
-------
TABLE B-4. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, MARCH-MAY 1976.
Characterization
Dependent
Variables
V011 TOTAL COD IN
V013 TSS IN
YOU TOTAL COD IN
V007 TXN IN
V014 VSS IN
V007 TKN IN
V010 SOL BOD IN
V012 SOL COD IN
of Waste
Independent
Variables
V007 TKN IN
V009 TOTAL BOD IN
V013 TSS IN
V007 TKN IN
V009 TOTAL BOD IN
V015 FLOW;GPD
V013 TSS IN
V006 AMMONIA IN
V009 TOTAL BOD IN
V011 TOTAL COD IN
Coefficient In
Regression
Equation
0.3534145
-1.9700766E-02
0.4801225
46~9.S646
2.106279
210.7788
-0.5635178
852.4
-1.1796518E-04
67.06766
0.6834089
0.8095333
0.9821723
25.34194
0.2342563
59.14523
0.2247983
102.9625
Confidence
Level
97.3
86.7
92.83
98.6
99.99
90.2
91.32
98.78
2
r
0.361
0.076
0.104
0.162
0.666
0.083
0.098
0.162
Standard
Error
100.21
136.1
119.5
18.1
68.9
19.66
50.09
72.63
-------
TABLE B-5. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JUNE-AUG. 1976.
Characterization
Dependent
Variables
V011 TOTAL COD IN
V013 TSS IN
7011 TOTAL COD IN
VC07 TKN IN
V014 VSS IN
V007 TKN IN
V010 SOL BOD IN
V012 SOL COD IN
of Waste
Independent
Variables
V007 TKN IN
V009 TOTAL BOD IN
V013 TSS IN
V007 TKN IN
V009 TOTAL BOD IN
V015 FLOW;GPD
V013 TSS IN
V006 AMMONIA IN
V009 TOTAL BOD IN
V011 TOTAL COD IN
Coefficient In
Regression
Equation
-0.2361691
0.6596316
0.1671231
334.56
-1.534388
323.6429
0.7103718
349.699
-8.72784E-05
57.06159.
0.8745831
-30.27953
0.8588041
17.36009
0.2835594
28.11254
0.3404716
45.43303
Confidence
Level
99.29
34.9
99.97
99.96
99.99
99.98
99.97
99.92
2
r
0.377
0.007
.0.351
0.352
0.884
0.465
0.327
0.284
Standard
Error
80.53
149.37
85.23
6.63
46.43
6.37
39.76
55.62
-------
TABLE B-6. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, SEPT.-NOV. 1976.
Characterization
Dependent
Variables
V011 TOTAL COD IN
V013 TSS IN
V011 TOTAL COD IN
V007 TKN IN
V014 VSS IN
V007 TXN IN
V010 SOL BOD IN
V012 SOL COD IN
of Waste
Independent
Variables
V007 TKN IN
V009 TOTAL BOD IN
V013 TSS IN
V007 TKN IN
V009 TOTAL BOD IN
V015 FLOW;GPD
V013 TSS IN
V005 AMMONIA IN
V009 TOTAL BOD IN
V011 TOTAL COD IN
Coefficient In
Regression
Eauation
10.23053
0.5929619
0.2321051
10.07123
13.85392
-398.6944
1.698052
147.4821
-9.51804E-05
59.70244
0.5878145
40.49858
0.6176733
26.20884
9.628862E-02
109.1254
9.641165E-02
Confidence
Level
99.99
99.91
99.99
91.53
99.99
99.87
77.85
95.31
2
r
0.778
0.376
0.573
0.114
0.674
0.355
0.055
0.144
Standard
Error
72.21
119.2
92.1
6.45
57.96
5.59
28.07
30.22
184.2956
-------
TABLE B-7. SUMMARY OF STEPWISE REGRESSION DATA, JAN.-DEC. 1976
Lagoon Efficiensies
Variables
Dependent Attempted
'Variable In Regression
Variables
Selected
In Regression
Confidence Standard
1 2 F.value Level Error
VC45 BOD
EFFIECIENCY
CELL 1
V047 BOD
EFFICIENCY
CELL 2
V048 BOD
EFFICIENCY
TOTAL
V049 COD
EFFICIENCY
CELL 1
V050 COD
EFFICIENCY
CELL 2
V019 TEMP HP
V009 TOTAL BOD IN
V013 TSS IN
V025 TSS MP
V031 TEMP EFT
V023 TOTAL COD MP
V021 TOTAL BOD MP
V009 TOTAL BOD IN
V019 TEMP M?
V011 TOTAL COD
V031 TEMP EFF ,
V011 TOTAL COD IN
V009 TOTAL BOD IN
V019 TEMP MP
V013 TSS IN
V025 TSS MP
V023 TOTAL COD MP
V031 TEMP EFF
V021 TOTAL BOD MP
V019 TEMP MP
V009 TOTAL BOD IN
7011 TOTAL COD IN
V025 TSS MP
V031 TEMP EFF
V023 TOTAL COD MP
V021 TOTAL BOD MP
V031 TEMP EFF
V011 TOTAL COD IN
V009 TOTAL BOD IN
V011 TOTAL COD IN
V025 TSS MP
V023 TOTAL COD M?
3 64 3.61696 98.2
4 63 9.81592 99.99
3 64 3.05528 96.53
1 66 2.54154 88.43
2 65 7.23842 99.85
8.1
20.45
5.05
10.35
20.11
-------
TABLE B-7. Cont'd.
Lagoon Efficiencies
Variables
Dependent Atterapted
Variable In Regression
Variables
Selected
In Regression
Confidence
2 F.value Level
Standard
Error
Ol
00
V051 COD
EFFICIENCY
TOTAL
V052 TSS
EFFICIENCY
CELL 1
V053 TSS
EFFICIENCY
CELL 2
VC54 TSS
EFFICIENCY
TOTAL
V035 TKN
EFFICIENCY
TOTAL
V013 TSS IN
V011 TOTAL COD IN
V019 TEMP foP
V031 TEMP EFF
V009 TOTAL BOD IN
V013 TSS IN
V011 TOTAL COD IN
V009 TOTAL BOD IN
V019 TEMP MP
V025 TSS MP
V031 TEMP EFF
V023 TOTAL COD MP
V021 TOTAL BOD MP
V013 TSS IN
V031 TEMP EFF
V011 TOTAL COD IN
V019 TEMP MP
VOC9 TOTAL BOD IN
V019 TEMP MP
V011 TOTAL COD IN
V009 TOTAL BOD IN
V013 TSS IN
V007 TKN IN
V013 TSS IN
1 66 1.19143 72.09
V009 TOTAL BOD IN 3 64 15.01452 99.99
V011 TOTAL COD IN
V013 TSS IN
V023 TOTAL COD M?
V031 TEMP EFF
V025-TSS MP
V013 TSS IN
V031 TEMP EFF
V011 TOTAL COD IN
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V019 TEMP MP
3 64 13.09213 99.99
3 64 9.39776 99.99
4 63 4.97705 99.85
7.C4
18.66
69.67
11.76
5.31
-------
10
TABLE B-8. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JAN.-DEC. 1976.
Lagoon Efficiencies
Dependent
Variables
V046 BOD
EFFICIENCY
CELL 1
V047 BOD
EFFICIENCY
CELL 2
V048 BOD
EFFICIENCY
Independent-
Variables
V019 TEMP MP
V057 AMT. BOD IN
V031 TEMP EFF
V063 AKT BOD MP
V067 AMT TSS MP
V031 TEMP EFF
Coefficient In
Regression
Equation
0.3096749
-6.367396E-08
75.04213
0.3956547
4.723639E-07
1.0786696E-06
37.13798
0.1714976
89.1727
Confidence
Level
98.94
99.96
99.79
2 Standard
r Error
0.085 9.04
0.192 21.77
0.089 4.93
TOTAL
V050 COD
EFFICIENCY
CELL 2
V052 TSS
"EFFICIENCY
CELL 1
V065 AMT COD MP
V067 AMT TSS MP
V031 TEMP EFF
V057 AMT BOD IN
V061 AMT TSS IN
V019 TEMP MP
V053 TSS V065 AMT COD IN
EFFICIENCY V067 AKT TSS MP
CELL 2 V031 TEMP EFF
6.239130E-07 99.99
2.380387E-07
0.23101231
22.23239
-2.123962E-07 99.99
4.116586E-07
0.6153472
44.33618
3.19013E-08 99.99
5.131307E-06
-2.895973
-0.4622752
0.198 19.40
0.235 21.90
0.366 64.41
-------
TABLE B-8. Cont'd.
Lagoon Efficiencies
Dependent
Independent
Variables Variables
Coefficient In
Regression
Eci u
-------
TABLE B-9. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JAN., FEB., DEC. 1976
Lagoon Efficiencies
Dependent
Variables
V046 BOD EFFICIENCY
CELL 1
V047 BCD EFFICIENCY
CELL 2
V048 BOD EFFICIENCY
TOTAL
Independent
Variables
V019 TEMP MP
V057 AMT BOD IN
V031 TEMP EFF
V063 AMT BOD MP
V067 AMT TSS MP
V031 TEMP EFF
Coefficient In
Regression
Eqv.atlon
1.804974
1.1025123E-07
63.10404
14.01739
3.0296144E-06
9.103946E-07
-66.25088
0.5952108
85.31143
Confidence
Level
87.93
96.44
69.36
2 Standard
r Error
0.232 8.05
0.560 18.83
0.055 7.40
V050 COD EFFICIENCY
CELL 2
V052 TSS EFFICIENCY
CELL 1
V053 TSS EFFICIENCY
CELL 2
V054 TSS EFFICIENCY
TOTAL
V065 AMT COD MP
V067 AMT TSS MP
V031 TEMP EFF
V057 AMT BOD IN
V06I AMT TSS IN
V019 TEMP MP
V065 AMT COD MP
V031 TEMP EFF
V061 AMT TSS IN
V059 AMT COD IN
97.57 0.456
8.2201986E-07
1.1222128E-06
-1.238537
19.16636
-2.28154E-07
5.0686795E-07
-3.336686
81.92313
----------------- NO CORRELATION-
70.41
-.6839095
3.565298E-07
-5.35SSS6E-08
75.07638
97.7
0.483
9.91
0.324 14.76
7.88
-------
TABLE B-9. Cont'd.
Lagoon Efficiencies
Dependent
Variables
V055 TKN EFFICIENCY
Independent
Variables
V019 TEMP MP
Coefficient In
Regression
Eauation
-0.721412
Confidence
Level
93.6
2 Standard
r Error
0.395 5.44
TOTAL
V057 AMI BOD IN
V056 Al-lT TXN IN
4.394689E-08
-1.449E-06
91.88497
10
-------
TABLE B-10. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, MARCH-MAY 1976.
Lagoon Efficiencies
Dependent
Variables
V046 BOD EFFICIENCY
CELL 1
V047 BOD EFFICIENCY
CELL 2
V048 BOD EFFICIENCY
TOTAL
Independent
Variables
V019 TEMP MP
V057 AMT BOD IN
V031 TEMP EFF
V063 AMT BOD MP
V067 AMT TSS MP
V031 TEMP EFF
Coefficient In
Regression
Equation
-1.521782
-1.42388E-07
115.2151
4.286493
3.7664E-07
2.14375E-06
-52.31941
1.388996
65.21324
Confidence 2
Level r
99.16 0.289
99.10 0.377
98.99 0.221
Standard
Error
6.08
21.95
3.87
V050 COD'EFFICIENCY
CELL 2
V052 TSS EFFICIENCY
CELL 1
V053 TSS EFFICIENCY
CELL 2
V065 AMT COD MP
V067 AMT TSS MP
V031 TEMP EFF
V057 AMT BOD IN
V061 AMT TSS IN
V019 TEMP MP
V065 AMT COD MP
V067 AMT TSS MP
V031 TEMP EFF
7.691299E-07 51.28
-5.05891E-07
-0.239462
25.29951
-3.86296E-07 99.62
4.993186E-07
2.306771
26.59583
-2.403267E-07 76.68
1.53379E-06
2.756489
-11.34721
0.098
0.267
22.22
0.450 13.66
14.49
-------
TABLE B-10. Cont'd.
Lagoon Efficiencies
Dependent
Variables
V054 TSS EFFICIENCY
Independent
Variables
V031 TEMP EFF
Coefficient In
Regression
Equation
0.931586
Confidence
Level
88.01
2
r
0.205
Standard
Error
13.97
V055 TXN EFFICIENCY
TOTAL
V061 AMT TSS IN
V059 AMT COD IN
V019 TEMP MP
V057 AMT BOD IN
V056 AMT TXN IN
2.738169E-07
-5.50S731E-09
48,461
3.829024
-1.2462157E-07
1.154839E-06 '
3.138585
99.99
0.553
6.59
-------
Ul
TABLE B-ll. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JUNE-AUG. 1976.
Lagoon Efficiencies
Dependent
Variable
VC4S SOD EFFICIENCY
CZLL 1
V047 BOD EFFICIENCY
CELL 2
V048 BOD EFFICIENCY
TOTAL
Independent
Variables
V019 TEMP HP
V057 AMI BOD IN
V031 TEMP EFF
V063 AMT BOD MP
V067 AMT TSS MP
V031 TEMP EFF
Coefficient In
Regression
Eauation
3.088944
-5.1052676E-08
-3.332165
2.961521
1.561813E-06
-30.45803
0.2634126
86.67577
Confidence 2
Level r
98.21 0.250
94.7 0.301
69.51 0.038
Standard
Error
6.83
11.86
1.99
V050 COD EFFICIENCY
CELL 2
V052 TSS EFFICIENCY
CELL 1
V053 TSS EFFICIENT?
CELL 2
V065 AMT COD MP
V067 AMT TSS MP
V031 TEMP EFF
V057 AMT BOD IN
V061 AMT TSS IN
V019 TEMP MP
V065 AMT COD MP
V067 AMT TSS KP
V031 TEMP BFF
8.776925E-07 98.17
-1.046776S-07
3.98633
-85.51623
-4.82136E-08 62.11
1.803818E-07
-3.558946
165.5479
-3.37S21E-07 99.47
2.252324E-06
-18.84411
549.2112
0.348
17.5
0.128 20.47
0.741 17.61
-------
TABLE B-ll. Cont'd.
Lagoon Efficiencies
Dependent Independent
Variable
Variables
Coefficient In
Regression
Equation
Confidence
Level
Standard
Error
-j
a\
V054 TSS EFFICIENCY
TOTAL
V055 TKN EFFICIENCY
TOTAL
V031 TEMP EFF
V061 AMT TSS IN
V059 AMT COD IN
V019 TEMP MP
V057 AMT BOD IN
V056 AMT TKN IN
-2.323927 96.80
7.7S934E-08
1.476333E-07
123.4936
0.3588631 96.21
7.952106E-09
6.06&973E-07
75.50454
0.336 13.54
0.232 1.88
-------
TABLE B-12. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, SEPT.-NOV. 1976.
Lagoon Efficiencies
Dependent
Variables
Y046 BOD EFFICIENCY
CELL 1
V047 BOD EFFICIENCY
CELL 2
7043 300 EFFICIENCY
TOTAL
V050 COD EFFICIENCY
>
Independent
Variables
V019 TEMP MP
V057 AMT BOD IN
V031 TEMP EFF
V063 AMT BOD MP
3067 AMT TSS MP
V031 TEMP EFF
V065 AMT COD MP
Coefficient In
Regression
Ecuation
0.2872387
2.56492E-07
52.57227
-0.3122703
96.53475
5.844505E-07
Confidence 2
Level r
84.0 0.160
NO POPPFT ATTfTKT __
88.93 0.107
99.99 0.709
Standard
Error
8.85
4.85
7.54
CELL. 2
V052 TSS EFFICIENCY
CELL 1
V053 TSS EFFICIENCY
CELL 2
V067 AMT TSS M?
V031 TEMP EFF
V051 AMT BOD IN
V061 AMT TSS IN
V019 TEMP MP
V065 AMT COD MP
V067 AMT TSS MP
V031 TEMP EFF
-4.5638265E-07
1.262185
31.74012
-1.007704E-06
9.188986E-07
-0.4569783
63.36416
8.667412E-08
6.22611IE-07
0.7175017
37.84197
99.62
0.517 16.39
82.81
0.226 15.60
-------
TABLE B-12. Cont'd.
Laqoon Efficiencies
Dependent
Variables
V054 TSS EFFICIENCY
Independent
Variables
V031 TEMP EFF
Coefficient In
Regression
Equation
9.849385E-03
Confidence 2
Level r
99.96 0.623
Standard
Error
6.84
TOTAL
V055 TXN EFFICIENCY
TOTAL
V061 AMT TSS IN
V059 AMT COD IN
V019 TEMP MP
V057 AMT BOD IN
V056 AMT TKN IN
vj
00
5.643183E-07
-4.011315E-07
98.28307
0.1740435
-1.292232E-08
3.34404E-07
84.82043
68.45
0.183
2.40
-------
-J
vo
TABLE B-13. SUMMARY OF STEPWISE REGRESSION DATA, JAN.-DEC. 1976
Predicting Mid-Point Properties
Dependent
Variable
V021 TOTAL BOD
KP
V023 TOTAL COD
HP
V025 TSS HP
V022 SOL BOD
M?
V024 SOL COD
M?
Variables
Attempted
In Regression
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V019 TEMP MP
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V019 TEMP MP
VC09 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V019 TEMP MP
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V014 VSS IN
V019 TEMP MP
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V014 VSS IN
V019 TEMP MP
Variables
Selected
JCn Regression
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V011 TOTAL COD IN
V011 TOTAL COD IN
V019 TEMP MP
V009 TOTAL BOD IN
V011 TOTAL COD IN
V019 TEMP MP
V013 TSS IN
V009 TOTAL BOD IN
58
58
Confidence Standard
F. value Level Error
56 8.18624 99.98
4.56314 96.31
57 6.60485 99.73
55 12.84829 99.99
1.11408 70.44
30.35
73.07
43.74
18.89
41.3
-------
00
o
TABLE B-14. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JAN.-DEC. 1976.
Predicting Mid-point.Properties
Dependent Independent
Variables
Variables
Coefficient In
Regression
Equation
V021 TOTAL BOD MP V061 AMT TSS IN
V057 AMT BOD IN
V019 TEMP MP
V023 TOTAL COD MP
V025 TSS MP
V022 SOL BOD MP
V024 SOL COD MP
V061 AMT TSS IN
V059 AMT COD IN
V019 TEMP MP
V059 AMT COD IN
V058 AMT SOL BOD IN
V061 AMT TSS IN
V019 TEMP MP
V058 AMT SOL BOD IN
V060 AMT SOL COD IN
Confidence
Level
-2.431649E-07 99.99
9.5585035E-07
-1.479171
69.74439
-4.88751E-07 98.70
7.7177165E-07
149.7909
-2.177494 99.96
4.6S1205E-07
-9.369269E-07
6.6979104E-08
101.0664
-0.7011226 99.99
1.55455E-06
2.16999
4.882489E-07 90.89
51.99619
0.305
0.073
0.220
0.308
0.024
Standard
Error
29.67
67.46
41.47
20.67
33.61
-------
TABLE B-15. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JAN., FEB., DEC. 1976.
Predicting Mid-point Properties
Dependent
Variables
V021 TOTAL BOD KP
« V023 TOTAL COD MP
V025 TSS MP
Independent
Vnriableo
V061 AMT TSS IN
V057 AMT BOD IN
V019 TEMP KP
V061 AMT TSS IN
V059 AMT COD IN
V019 TEMP MP
Coefficient In
Regression
Ecuation
-9.40834E-07
6.278336E-07
-11.27744
149.7123
5.253647
Confidence
Level
99.5
?JO fOTJTJPT ATTi
** Mw V
-------
TABLE B-16. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, MARCH-MAY 1976.
a,
10
Predicting Mid-point properties
Dependent
Variables
V021 TOTAL BOD MP
V023 TOTAL COD MP
V025 TSS MP
V022 SOL BOD MP
V024 SOL COD MP
Independent
Variables
V061 AMT TSS IN
V057 AMT BOD IN
V019 TEMP MP
V061 AMT TSS IN
V059 AMT COD IN
V019 TEMP MP
V059 AMT COD IN
V058 A-S-'T SOL BOD IN
V061 AMT TSS IN
V019 TEMP MP
V058 AMT SOL BOD IN
V060 AMT SOL 'COD IN
Coefficient In
Regression Confidence 2
Eauation Level r
-2.679179E-07 99.54 0.426
9.S079974E-07
7.244122
-96.22798
-4.1396E-07 23.3 0.025
4.450183E-07
139.0472
«. MO rnpHTJT ATTOM __.»
-3.470565 97.74 0.253
8.7329E-07
73.15219
NO rORP.F.T,ATTf1\T
Standard
Error
25.23
59.60
16.01
-------
TABLE B-17. RESULTS OF REGRESSION VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JUNE-AUG. 1976.
Predicting Mid-point Properties
Dependent Independent
Variable Variables
V&21 TOTAL EOD MP V061 AMT TSS IN
V057 AMT BOD IN
V019 TEMP MP
Coefficient In
Regression
Eauation
Confidence 2
Level r
Standard.
Error
CD
U)
7023 TOTAL COD MP
V025 TSS M?
V022 SOL BOD MP
V024 SOL COD MP
V061 AMT TSS IN
V059 AMT COD IN
V019 TEMP MP
V059 AMT COD IN
V058 AMT SOL BOD IN
V061 AMT TSS IN
V019 TEMP MP
V058 AMT SOL BOD IN
V060 AMT SOL COD IN
-8.S67321E-08 99.68
4.688706E-07
-10.35434
333.7117
-6.804419E-08 99.04
6.89286E-07
96.34911
2.851196 77.87
5.24489E-08
9.819212E-07
2.515837E-07
-48.87567
0.3077798 73.74
5.2027359E-07
-5.515419
4.8975877E-07 99.26
38.53497
0.419
0.291
0.229
0.105
0.229
20.C6
38.7
31.39
11.69
12.87
-------
CO
TABLE B-18. RESULTS OF REGRESSION VARIABLES SELECTED
AFTER STEPWISE REGRESSION, SEPT.-NOV. 1976.
Predicting Mid-point Properties
Dependent
Variables
V021 TOTAL BOD MP
V023 TOTAL COD KP
V025 TSS MP
V022 SOL BOD KP
V09A SOT. ron MP
Independent'
Variables
V061 AMT TSS IN
VOS7 AMT ROT) TM
V019 TEMP MP
V061 AMT TSS IN
V059 AMT COT) IN
V019 TEMP MP
V059 AMT COD IN
V058 AMT SOL BOD IN
V051 AMT TSS IN
V019 TEMP MP
V058 AMT SOL BOD IN
vnfin AMT snr. rrm TM
Coefficient In
Regression Confidence 2
Equation Level r
1.121863 99.21 0.592
1.386452E-06
-4.707157E-06
9.352955E-07
45.16838
4.5705377E-02 67.33 0.130
2.30846E-07
0.8363860
Nfl mTJPFT.ATTnM
Standard
Error
33.28
3.31
-------
TABLE B-19. SUMMARY OF STEPWISE REGRESSION DATA, JAN.-DEC. 1976.
Predicting Effluent Properties
Dependent
Variable
Variables
Attempted
In Regression
Variables
Selected
In
Confidence Standard
1 2 F. value Level Error
21.49
CD
U1
V037 TOTAL BOD
EFF
V038 SOL BOD
SFF
V039 TOTAL COD
EFF
V040 SOL COD
EPF
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V019 TEMP MP
V031 TEMP EFF
V010 SOL BOD IN
V012 SOL COD IN
V014 VSS IN
V019 TEMP MP
V031 TEMP EFF
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V019 TEMP MP
V031 TEMP EFF
V010 SOL BOD IN
V012 SOL COD IN
V014 VSS IN
V019 TEMP M?
V031 TEMP EFF
V009 TOTAL BOD IN
V019 TEMP MP
2 48 8.96151 99.95
V010 SOL BOD IN
1 49 27.85733 99.99
V011 TOTAL COD IN 1 49 2.75074 89.64
V010 SOL BOD IN
V012 SOL COD IN
V019 TEMP MP
V031 TEMP EFF
46 4.39372
99.15
19.83
48.62
28.57
-------
TABLE B-19. Cont'd.
Predicting Effluent Properties
Variables
Dependent Attempted
Variable In Regression
Variables
Selected
In Regression
Confidence Standard
F. velue Level Error
V041 TSS EFF
V042 VSS EFT
00
V035 TXX EFF
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
voi9 Tna» HP
V031 TEMP EFF
VC09 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V014 VSS II?
voo? ran is
V009 TOTAL BOD IN
V011 TOTAL COD IN
V013 TSS IN
V019 TEM? K?
V031 TEMP EFF
V013 TSS IN
V011 TOTAL COD IN
VQ14 VSS IN
V007 TKN IM
V009 TOTAL BOD IN
V011 TOTAL COD IN
V019 TEKP MP
48
5.69229 27.91
6.57962 99.7
8.34508 99.99
29.55
15.93
2.58
-------
TABLE B-20. RESULTS OP REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JAN.-DEC. 1976.
Predicting Effluent Properties
Dependent independent
Variables Variables
Coefficient In
Regression
Equation
Confidence
Level
2 Standard
r Error
00
V037 TOTAL BOD
EFFLUENT
V038 SOL. BOD
EFFLUENT
V041 TSS EFFLUENT
V019 TEMP MP
V057 AMI BOD IN
V061 ANT TSS IN
V019 TEMP MP
V058 AKT SOL BOD IN
V062 AMT VSS IN
V019 TEMP MP
V057 AMT BOD IN
V061 AMT TSS IN
-0.6373126 98.36
3.0022921E-07
-1.0223558E-08
27.60717
-0.1601284 99.99
1.4907674E-06
-1.5S52SE-07
-8.426982
0.2934921 99.35
-6.75198E-07
3.69532E-07
69.96406
0.113 20.3
0.274 18.03
0.137 29.97
NO CONFIDENCE IN PREDICTING EFFLUENT COD'S AND VSS.
-------
00
00
TABLE B-21. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JAN., FEB., DEC. 1976.
Predicting Effluent Properties
Dependent
Variables
VC37 TOTAL BOD
EFFLUENT
V038 SOL BOD
EFFLUENT
V040 SOL COD
EFFLUENT
Independent
Variables
V019 TEMP MP
V057 AMI BOD IN
V061 AMI TSS IN
V019 TEMP MP
V058 AMI SOL BOD
V062 AMT VSS IN
V031 TEMP EFF
V060 AMT SOL COD
V062 AMT VSS IN
Coefficient In
Recension Confidence 2 Standard
Equation Level r Error
-15.19848 99.85 0.772 20.89
-3.177845E-08
6.432184E-08
147.6917
-9.064955 99.99 0.869 16.44
IN 2.341592E-06
-2.0301668E-07
44.96168
IN NO CORRELATION
V041 TSS EFFLUENT
V042 VSS EFFLUENT
V035 TKN EFFLUENT
V019 TEH? MP
V057 AMT BOD IN
V061 AMT TSS IN
V062 AMT VSS IN
V059 AMT COD IN
V019 TEMP MP
V056 AMT TKN IN
V061 AMT TSS IN
-1.733782 49.98
-7.007306E-07
5.268625E-07
74.12917
2.4052816E-07 60.38
1.098939E-07
14.66022
0.4897082 99.95
9.46846E-07
3.23272E-03
-1.645129
0.221
0.098
0.685
21.37
15.53
1.83
-------
oo
vo
TABLE B-22. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, MARCH-MAY 1976.
Predicting Effluent Properties
Dependent
Variables
V037 TOTAL BOD
EFFLUENT
Independent
Variables
V019 TEMP HP
V057 AMI BOD IN
Coefficient In
Regression
Equation
-5.0066
-1.44Q0566E-07
Cofindence 2
Level r
71.1 0.160
Standard
Error
17.67
V033 SOL BOD
EFFLUENT
V040 SOL COD
EFFLUENT
V041 TSS EFFLUENT
V042 VSS EFFLUENT
V035 TXN EFFLUENT
V061 AMT TSS IN
V019 TEMP HP
V058 AMT SOL BOD IN
V062 AMT VSS IN
V031 TEMP EFF
V060 AMT SOL COD IN
V062 ANT VSS IN
V019 TEMP MP
V057 AMT BOD IN
V061 AMI TSS IN
V062 AMT VSS IN
V059 AMT COD IN
V019 TEM? MP
V056 AMT TKN IN
V061 AMI TSS IN
8.4209674E-08
134.0367
-5.571941 99.62
1.045395E-08
-6.901865E-08
125.1794
-3.680056 75.48
1.41637E-06
-6.485565E-07
126.06
-4.181593 90.06
-1.08493E-06
5.7175E-07
176.1793
6.708066E-07 70.86
-4.754626E-07
68.58951
-2.640331 99.99
7.37957E-07
-3.9730322E-08
58.C3446
0.515
0.223
0.234
0.135
0.734
8.78
41.74
34.8
30.62
2.80
-------
TABLE B-23. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, JUNE-AUG. 1976.
vo
o
Predicting Effluent Properties
Dependent
Variable
V037 TOTAL BOD
Independent
Variables
V019 TEMP HP
Coefficient In
Regression
Equation
-1.129164
Condifence
Level
53.55
2
r
0.103
Standard
Error
9.S6
EFFLUENT
V038 SOL BOD
EFFLUENT
V040 SOL COD
EFFLUENT
V041 TSS EFFLUENT
V042 VSS EFFLUENT
V035 TKN EFFLUE!JT
V057 AMT BOD IN
V061 AMT TSS IN
V019 TEMP MP
V058 AMT SOL BOD IN
V062 AMT VSS IN
V031 TEMP EFF
V060 AMT SOL COD IN
V062 AMT VSS IN
V019 TEMP MP
V057 AMT BOD IN
V061 AMT TSS IN
V062 AMI VSS IN
V059 AMT COD IN
V019 TEMP MP
V056 AMT TXN IN
V061 AMT TSS IN
7.621SSSE-08
-8.121767E-08
51.02319
-0.9311389 88.43
5.251931E-07
-1.1085798E-07
29.93009
-4.839794 57.06
2.76011E-07
-2.149446E-07
188.377
3.524894 86.99
-9.85267E-07
2.857604E-07
-2.686C6
-2.1265245E-07 70.4
3.6231892E-07
6.616256
0.15C057 95.79
-1.292S168E-07
-1.15S428E-08
1.25442
0.251
0.146
0.222
0.120
0.275
8.82
24.43
34.65
26.38
1.031
-------
TABLE B-24. RESULTS OF REGRESSION OF VARIABLES SELECTED
AFTER STEPWISE REGRESSION, SEPT.-NOV. 1976.
predicting Effluent Properties
Dependent Independent
Variable Variables
Coefficient In
Rcgrccaion
Equation
Confidence 2 Standard
Level r Error
V037 TOTAL 30D
EFFLUENT
V038 SOL BOD
EFFLUENT
V040 SOL COD
EFFLUENT
V041 TSS EFFLUENT
V042 VSS EFFLUENT
V035 TKN EFFLUENT
V019 TEMP MP
V057 AMT BOD IN
V061 AMI TSS IN
V019 TEMP MP
V058 AMT SOL BOD IN
V062 AMT VSS IN
V031 TEMP EFF
V060 AMT SOL COD IN
V062 AMT VSS IN
V019 TEMP MP
V057 AMT BOD IN
V061 AMT TSS IN
V062 AMT VSS IN
V059 AMT COD IN
V019 TEMP MP
7056 AMT TKN IN
V061 AMT TSS IN
1.170972 91.7
-4.832518E-08
-4.97633E-07
26.07699
2.003566 98.52
1.55971E-06
-4.129796E-07
-37.4667
-1.03349 75.28
-1.098727E-07
3.1701628E-07
55.64379
-1.S36766 99.22
3.67628E-07
2.345345E-07
46.46516
0.290
0.472
0.183
0.475
14.32
13.72
16.92
15.66
-.133172
1.035E-07
-4.2646E-09
6.564393
NO CORRELATION
98.70 0.442
1.00
-------
APPENDIX C
OPERATIONAL PROBLEMS
During the study, several operational problems became evident.
The two major problems associated with the lagoon system itself
were loss of one of the dikes due to burrowing by muskrats and
plugging of the air diffuser system. In one month muskrats com-
pletely drained cell number two and one other time the cell level
was dropped significantly by someone who inadvertently turned on
the irrigation pump used for applying the effluent to adjacent
lands. The aerators were not functioning properly for a signifi-
cant portion of the time. Based on periodic site visits approxi-
mately twenty-five percent of the system was not functioning pro-
perly about fifty percent of the time. The problems were usually
associated with plugging of the aeration tubes.
Other problems associated with the project include:
a) Freezing of the samplers.
b) Loss of power to the mobile laboratory and con-
comitant freezing and breaking of important
glassware and loss of chemicals.
92
-------
APPENDIX D
DAILY DATA
TABLE D-l. INFLUENT TEST DATA OF BIXBY LAGOON, 1976.
vo
OJ
s^
-AOI
AOa
A03
A0»
-A05
AOtr
AC7
A'wM
-ACS
A1C
All
A13
'*\5
A16
A17
. AlB
A IK
A2C
A21
' A23
A2*
A25
6U1
b&2
603
604
6O7
C»l
C03
C04"
COS
CCt
C07
0
YR
76
76
76
7fc
76
76
?8
76
76
76
76
.76
?6
7b
76
"76
?6
7b
7b
76
76
7ft
76
7t
7fc
7b
76
76
76.
76
DATA
MO DT
1 6
1 7
1 8
1 9
1 1C-
1 11
: 12
1 13
i IS
i .5
1 19
1 fcO
1 21
23
2i
. 25
1 2S
1 29
2 22
2 23
III
1. 26
2 27
2 28
3 22
3 2,4
3 25
3 26
3 27
- 3 28
3 29
p« .ALKALINITY
7-5 "*
6>5
0
b">
6«8
6*5
6'h
7-6
-«Q .
.0
0
-6«9
7. a
0
0
7.3
6>5
6«9
0>ti
.0
197
15S
163
1 f". ft _ ...
11C
J/L5
53
O
181
0
"i
1«0
S
0
146
I8i
156
3
«o o
o o
.0 0
.3 3
*0 0
0 0
?.; lap
7«2
7.3
6*9
«,
16*
192
IS*
f,
0
, TOTAL
PHOSPHOROUS
37
31
3S
JS
3U
35
3s
Si
12
*S
3*
J
0
C
0
3
0
36
38
25
30
AMMONIA
NJTROC.SA
32-3
30-0
-i 1 a n
3U«l
33 3
§3«U
S:S
.0
0
0
2i *2
2 o
23«9
27-2
3tO
26'6
23«1
27*7
24.7
>3
23-1
g«- 1 g
£4«9
KJELDMAL
/ NtTROCEH
44)5
*3>0
3b 1
' 37.9
39. i>
.0
.0
.0
33.7
33.7
30.7
.0
46*8
42-9
11*8
32.0
4?.0
5l'C
Sl'U
97-0
5S*S
C,
56*0
5t«0
BOO BOD
TOTAL SOL
..0 0
0 U
740 232
337 253
0 U
35V Una
*?0 ||3
310 170
270 265
2*a 175
i-77 173
. ..300 !*»<
0 0
U U
0 U
3«0 23S
£<>i) 156
blp 1S9
0 U
44S 232
315 237
'j92 IBS
. 0 0
' "363 255
397 262
0 0
390 273
40b 245
540 £95
293 224
155 165
100 Ibl
too
TOTAL
.. . SS2
374
046
set
6S2
... IH
Hi
. 632
SSb
m
... 637
8
0
S16
512
B3C
£67
.... 542
61&
500
736
£16
636
617
7 IK
0
7CC
coo TOTAL
SOU* SUSPEN
SOLI
348 - 694
305 iHl
439 392
239 0
in 1 n
308
211
' '271 *
311
302
. 332
0
0
0
313
333
450
357
314
339
275....
302
tbb
197
323
328
234
157
301
190
380
357
104
120
3«7
... 185
8
0
285
275
328
0
336
210
232
156
0
0
357
_. 119
273
293
2«0
-180
190
VOLATILE
JED SUSPENDED
35 SOLIDS
631
1S7
278
0
Q
176
121
24*
90
2Ug
159
278
30*
265
121
0
0
0
230
190
220
If2
20B
13t>
0
a
0
BO
... . 90
140
170
160
90
120
FLO* F
RATE c
GPO
120400
125600
140500
76300
123600
133IJOO
1C5000
105000
IgllOO
I32b30
61700
110400
133200
11 j&CO
1C3000
13.4100
65600
106&CO
96900
10(»bOO
9
-------
TABLE D-l. Cont'd.
vo
V "Alt lUk.1
._??2200_
126700 ;
vocATTCEFCDW
SUSPENDED RATE
SOLIDS
262
49§
.. 0
232
378
230
530
352
13950
10960
»000.
81000
._ i
o637C-
331500
21^800
1S6600
17IJCJ
11C200
141500
^3gg
11-.900
116700
11M700
1K900
ISBCO
6C4CO
22 |SO
453C3
0_
18000
15000
21033
0 -
0
16000
P?8§§.
470CO
15000
36030
21000
8-
139300
143*00
142100
131600
1622C3
i^g§
30000
o
27003
FOl 76
F02 76
.reS76
FG* It,
F05 76
F06 76
-F07-76
263 146200 0_
3ZO 135700 0
0
0
123300
0-
-------
TABLE D-l. Cont'd.
S«NO DATA PM ALKALINITY TOT»L AMMONIA KJELDHAL
fft r.O OT PHOSPHOROUS fiTfite* NITPOU6N
501 '* * R *« «»k f. «B.n if.r.
G02
003
GO*
306
007
iff
.K3
Gil
CIS
-G17
G18
S19
020
.G21
£22
G23
02*
.G2t
set
H02
-*°l
hO5
"7oi
102
103
-10*
76
76
76
76
76
76
8
76
?s
-74
76-
76
76
76
76
.- 76
76
76
76
76
76
76
76
if,
76
76
76
7 6
7 7
7 8
7 Id
/ 13
7 1«
7 19
7 £0
7 21
7 VP
7 2*
7 ga
7 26
7 37
7 28
7 30
tf Z
ft ..3. .
8 »
211
i 24
a 26
b 27
h 23
* £C
9 21
9 22
9 23
6*1
b'l
5'S
6*0
6'w
tj . S
O'i
6*1
6'2
6.1
5.7
6-4
6*3
b-2
t:S
0
.0
6«G. .
60
b*2
6O
O.fa
0-3
6-7
6>b
60
15J
140
160
i 3*1
**»**
iii
IfcO
IS*
152
IfcO
ISO
0
L.
159
152
IfcH
133
1*6
130
100
132
1*0
0
a
0
0
0
0
u
a
c
0
8
f!
0
0
0
n
0
C
0
0
0
0
0
c
c
0
0
0
0
3
34*5
0
0
0
0
0
2R-8
*2'0
33.0
3tt«0
JUO
36*0
Q
0
36>0
33*0
27.0
0
£7.4
C-*.6
23'9
23-7
P7 1
31'6
35-0
3 8 . 1 -
»0.b
3B*3
*0.5
"55 u
57lo
61. U
0
540
.0
36*0
3H*J
33!-)
32.4
3U-C
36.1
3S* 3
40.4
bOC BOD
TOTAL SOL
3so i yo
430 140
500 170
6*0 -3QO
3*0 90
3*0 1*0
390 140
3JO lip
330 130
260 120
340 130
2iiO ISO
37U 110
JOO 130
200 140
330 110
0 0
0 0
330 120
210 BO
260 'JO
. 260 130
J^O 90
0 0
360 100
JlO 10U
350 120
293 120
330 90
Q [)
U 0
3*0 1*0
3*0 170
310 li!>.
ccc
TOTAL
A 7C
6S5
8*8
539
510
S5S
111
Mft
617
£19
0
439
614
... 686 .
6Ci?
- .4*5
7C7
tC3
£70
7C3
COD
SOL*
1 fejt
222
208
5*5
250
270
2b7
tyft
2*3
la*
264
2*b
264
. 230
236
239
0
0
26J
139
188
... 220
iSa
223
2*2
233
252
21*
2*2
- 232
226
0
309
241 -
TOTAL VOLATILE FLOW FECAL
SUSPENDED SUSPENDED RATE COLI
SOLIDS SOLIDS GPO
216
196
0
95
132
*6*
3f 8
107
18*
I13
23*
20B
280
0
0
332
160
215
2*0
304
.... 772
'J<>S
2?*
96
156
u*
92
120
0
0
0
532
216
316
168
*u
0
124
220
200
"S
0
160
*12
l&a
116
215
16S
296
638
32
- 2*
100
60
- 120
123000
140200
126700
115900
10:900
123100
127700
107iOO
12-J500
1161 00
671CO
lOClOO
IPliiOO
227700
15SPOO
12*000
ZliloO
2467QO
2*7500
asc^oo
25*300
126920
163300
126100
§
0
§
9
n
Q
5
0
0
0
o
0
§
0
0
0
0
o
0
1
Q
0
0
a
0
0
0
Q
-------
TABLE D-l. Cont'd.
S*NQ DATA
YK rO OT
~jol 76 10 I*
J03 76 1C 25
jOi 76 10 26
_iOS ?" in 5*
*yj
K03
Kb*
*CS
K07
K06
K39
-KIS
Kll
K12
K13
K15
Kit
K17
,K18
K15
-X22
K23
LOI
-LS2
LU3
LOS
-LOfc
L07
7g 16 |8
Vc, 1C 29
7fc 11 *
7fc }1 5
7b 11 S
7t 11 11
7t Jl 1?
7t 11 13
7o 11 16
76 11 17
_7b 11 18
76 11 19
7G 11 20
76 11 £1
_Zb-ll_2a.
7t 11 23
7o 11 c»
76 11 25
. 7o 11 £(»
7t 11 i«T
76 11 29
76 11 30
3&-IZ..- 2.
76 12 3
76 12 5
76 12 16
76 12 18
76 12 19
76 U 30
76-12 21-
76 12 2
tt~
t-Z
6*2
f».3
b*S
6*2
6* 1
t
6«*
b'l
*«2
h'O
fc
6*2
b'l
£»0-
s'e
t-c
6*1
5*8
k. i
t-0
b*0
b'&
6-2
6'*
6*1
6.3-
b«*
0
162
ISb
n »>
175
ISO
178
If*
153
131
162
156
3
0
91
110
ISb
it*.
IfcC
I'll
168
l >«.
15*
ItS
136
lib
136
ISO
- C
C
5
0
8
0
c
0
c
0
0
o
b
0
0
n
0
0
U
0
0
b
o
5
0
0
0
0
0
0
36*1
0
37«3
3h 8
"IB
0
a-*.?
1 1 * 6
in.?
1S> 0
30-7
30.5
.0
27-5
26«7
29-1
31-1
23> i
... 25-7 ._
<.0'9
31«0
'Jti'l
ff,.f
0
27-7
32-8
27-0
?( -H
15.7
11.4
U
.0
39. b
17.*
11. b
SO. H
51.1
**!
15. J
V
13. i;
*5O
11 *Cl
bd'b
< 'J
*l.il
Jtt'1
13.9
ib.'J
il.b
»tj.3
bCC
TOTAL
4 1 O
370
383
350
360
535
390
391)
303
130
270
3*0
330
230
310
360
U
110
350
319
- 280
350
310
380
a
310
0
- ^'J0
310
BOD
SOL.
170
115
!SE
150
>3?
1*0
HO
110
120
160"
150
130
150
140
150
0
170
HO
180
160
lyo
0
no
210
no
HO
0
135
lo
230
80
T§?SL
635
771
79c
m
m
b '
789
et*
ttt
772
... 1C3H
72*
758
662
1C*0
7CC
11*8
. 651
867
13C
t33
50V
0
tl*
COO T
SOL* SU
9 A A
260
§7*
07
PI
169
223
221
idi
260
269
220 .. .
^36
2*1
238
§67
0
260
31*
232
207
236
.... £33
207
19*
223
, ^06 - --
OTAL
3PENC
SOLIC
0
280
fP
177
160
116
170
186
197
258
327
18*
272
13*
0
36*
631
lid
12*
119
130
163
118
206
13?.
7*
VOLATILE F.LOrf FECAL
IEO SUSPENDED RATE coui
IS SOLIDS GPO
234
93
il!
i*3?
12t
117
152
132
206
. . 257
161
230
113
0
156
3**
321
_. as
112
83
88
88
161
88
2o
118800
1 23500
137100
! 28500
32930
22130
39000
1*2600
133100
150930
1*6600
1*8700
136800
1*8730
152100
153200
108300
757CO
150*30
1*5130
16J330
. 1**100
92700
72000
151600
.. . 131800 _
1*1000
132700
73300
171900
259900
131.500
0
8
\
0
0
8
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o .
0
0
0
-------
TABLE D-2. MID-POINT TEST DATA OF BIXBY LAGOON. 1976.
(Effluent Cell 1)
S'KO DATE ALKALlNltV PM fEip. OISS>
1S> OT DEO C OXYGEN
A01 76 66 6
A02 76 66 7
A33 76 66 8
-A04 76-66 it
A05 76 66 19
A06 76 66 11
»07 76 66 12
«09 76 66 14
«19 76 bt> 15
All 76 66 16
-413 --7fc Zfc it
«io 7t it, la
AIS 7£. t6 19
A16 76 &6 23
.A17 74 k6 21
Aid 7e 66 2il
\O A19 76 66 23
J A2C 76 66 24
-A21_7a 66 25
A22 76 66 26
*23 76 66 27
A2« 76 66 29
A25 _.7i 66 2*.
B92 76 66 Z£
§02 76 66 23 '
803 76 66 2*
604 _/6. 66 23
8C5- 76 66 26
806 76 66 £7
g07 76 66 2S
01.76.66 £2
C02 76 66 24
C03 76 66 £d
C04 76 !,* 26
COS 76 66 27... ,
C06 16 66 2b
C07 76 66 29
132 6.7 2.Q
132 7.0 1.0
132 .0 1.0
129 . 6.3 . 3.Q
132 6. B 2.0
i32 6'^ 4.0
136 7.3 SO
J36 /.« 7.0
1?5 7.0 jr. 3
137 /.3 6.0
6 « .9
1*0 7.2- 1C. 3
0 «0 IX
154 /.4 e.o
1»6 70 £.0
0 7.7 9.0
0 « .0
o .0 .a
153 **U B.Q
IS* 7.7 8.0
164 7.8 9.0
o *o .Q
0 .0 ,0
0 »0 .0
- ...0 .0 ... .0..
a >o .9
0 «O ,c
C >0 .0
-J.C ? a , o
:s« /.s 17.3
194 7.6 13.0
172 7.6 17.Q
0 «U 17.0
O «U .(}
1&.7
13.6
12.8
11>1
12*2
- a £
1C. 4
10. 3 -
11. »
10.4
0
£0
ic
0
C
0
.0.
6>0
6>4
B. -a
S.B
0
aoo
TOTAL
c
0
13)1
95.
110
0
135
40
29
93
48
1
-.26
31
ii
0
. 0.. _
5a
35
174
_.. 3.
166
133
61
55
7 1
63
BOO COO
SOLUBLE TCTAL
0
0
132
.- 83_
ea
0
115
31
1!
Q
0 ..
41
23
14
27 .
0
112 _
117
104
72
0.
4?
62
41
}>&
17
47
150^
164
190
. 128
143
..ICg . _
161
117
142
13M
147
0
0
a
Erio
Iff
Hi
148
142
208
.1/6
its
5?!
174
CCD TO
SOLUBLE SUSP
SOI
36 63
ta 69
, , 75 "
75
95
65
11
!l
62
76
0
0
a
58" '
79
99
. . 60
-.124 .
"I
IPS
0 '
130
0
65
a
0
97
38
0
60
96
HI
124
66
0
0
O
140
HS
12fc
0
140
32
42
bfc
42
64
62
146
78
127
53
TAL VOLATILE
ENDED SUSPENDED
LIDS SOLIDS
79
il
0
0
63
34
38
68
si - --
142
106
54
0
a
72
58
68
a
80
\l
' ' '5 ' '
0
60
40
60
70
70
50
90
to
PHO
40
42
12
11
10
39
10
40
41
41
41
Si
43
42
43
37
39
39
39
39
0
0
0
0
0
0
0
0
46
44
47
40
44
36
44
SPHONOUS Cl
0
0
0
0
0
0
0
0
j
o
§
a
§
30OO
liooo
10000
19000
19000
11000
6000
:AL TOT;
ail COL;
a
0
0
a
0
0
0
ooooooooooooooooc
0
0
0
o
8
0
81000
30000
25000
0-
22000
14000
-------
TABLE D-2. Conf d.
S*NO OATE ALKALINITY
TR TO OT
PH
vo
oo
-------
TABLE D-2. Cont'd.
S.NO DATE ALKALINITY
TR 10 OT
PM
TEV.P.
DEO C
oiss.
OXYGEN
BOD
TOTAL
COU
SOLUBLE TLTAU
BOD
vo
vo
001 76
G02 76
G03 76
-034 76-
005 76
J06 76
07 76
08-76-
CCD TOTAL VO
SOLUBLE SUSPENDED SUSPENDED
SOLIDS S
1SO
61
- 0
32
19
65
"2"
51
. . 45 .
40
HO
200
0
102
62
64
46
126
64
138
96
"180
66
70
.. 70
230
ILE
3EO
DS
TOTAL
PHOSPHOROUS
0
0
0
0
0
0
0
Q
0
8
FETAL
COLI
0
0
0
Q
0
8
0
0
8
TOTAL
COLI
0
0
0
o
0
0
8
8 8 8-
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
TABLE D-2. Cont'd..
o
o
S'NO
JOI 74
J02 76
J03 76
~J05 76
J05 76
J07 7s
K32 7t
«03 7«,
KOi 7s
_K02.. 76
K06 76
K07 76
K03 76
_*09 7B
(00 76
Kll 76
K12 76
-K13 -.76
Kll 76
K15 76
Kit 76
...-U7 7i
K18 76
K19 76
K26 76
.K£l_.7&
K22 76
K23 76
<2l 76
-LOI _ 76
L02 76
L03 76
LOi 76
L06 ~76
L07 76
DATE ALKALINITY
^0 OT
66
66
66
66
66
66
~66
£6
66
60
66
66
66
66
60
66
66
!!
66
66
66
66
S6
46
66
66
-66
66
66
6a
66
6»
23
2i
25
fi
11
12
13
N
n
22
23
!5_
11
30
3
i
\fi .
17
18
19
i?
22
3
18
12
4
i!
12
9
33
34
11
11
0
32
-if
33
30
16
36
10
7?
70
70
72
74
83
76
PH
0
O
6.1
6- J
6.1
6.3
.6i1
6*b
Si.*
5.6
6« J
6'6
b > a
6.1
6.3
6. J
6. J
TEilP.
oca c
o
o
HO
10
HO,
12O
HO
s.o
O
ISO
9O
BO _
ICO
o
no
. .10.0
9:8
10.0
...100..
11.5
7.0
70
6.J
70
70
BO
8.0
90
70
10O
ft m fi
70
SO
UISS- BOO BOO COO
OXYGEN TOTAL SOLUBLE TOTAL
0
0
6*8
8.9
9.7
7.2
.... 9 , H
11. 1
9.7
8.8
8*6
O
7.2
7-2
£>6
8*8
O
7.2
BO
8.1
c'2
1.6
fc.5
11*8
1C-S
6.3
90
t <9
7-2
7 .Q
»>8
ICa
111
oe
11
105
86
1 -ji
163
99
HI
75
111
117
102
99
117
75
.. C ...
123
111
C
.. Hi
H7
69
129
117 .
la
126
0
33
0
3h
63
36
57
11
11
A
I
0
3
3
6
3
6
0
_ . 12
3
. .20
6
U
0
U
261
310
299
tSa
2§2
Po
*K1
S3J
fi*
£>&
2li
ell
£17
£63
f*3
2>9
230
30'J
£36
U3
191
IflO
186
eUl
H5
171
; £29
ltd
170
1C7
ccc TOTAL VOLATILE TOTAL
SOLUBLE SUSPENDED SUSPENDED PHOSPHOROUS
SOLIDS SOLIDS
El
65
67
31
US
62
_ 63
59
61
S3
. - 12 ..
56
52
56
71 .
16
57
65
70
70
. . 73 .
70
63
15
BO
67
63
138
232
1BO
1 J*»
108
£00
1H3
ioi
1J7
111
1*6
16
Hi
111
113
1-J1
1*7
113
111
109
HO
60
68
21U
92
61
60
61
6rt
19
0
0
33
S3
110
1S6
160
130
ij?
95
13
101
130
103
58
116
81
100
106
80
130
0
0
96
0
59
51
18
0
32
0
13
28
18
0
0
0
Q
U
§
Q
I
0
0
0
0
0
0
0
8
0
0
§
0
0
0
0
0
0
0
n
u
0
FECAL TOtAl.
COLI COLl
0
0
0
8
0
8
n
0
0
8
0
0
0
0
8
0
c
0
0
0
8
0
0
o
0
0
0
0
0
0
0
0
5
8
0
0
0
8
0
8
0
0
0
0
0
0
0
0
0
0
o
0
0
0
Q
0
0
-------
TABLE D-3. EFFLUENT TEST DATA OF BIXBY LAGOON,
(Effluent Cell 2)
1976.
»- *m n
TR
A01 7£
A02 76
A03 76
A04 76
A°5 76
A06 76
A97 76
ACS 76
AlO 76
Ail 7«
A13 76
Alt 76
A15 76
Alfc 7b
A17 7b
A1B 76
A19 /b
A20 76
A21 76
A aa 7 j_
A23 7o
A2« '6
A« 76
6oi 76
604 7e
06 /o
en *t
C02 'B
CO? 76
C04 /6
COS 7b
.C06 _76_
C07 76
TT PH
MU or
1 6 6.7
1 7 6*6
1 K >0
1 9 7.3
1 JO 7.1
1 11 7'f
1 12 B>2
1 13 7>|
l"l5 k'Z
i it. .8
1 17 8«0
1 1ft .(1
1 19 *C
1 20 8*S
1 21 «C
1 22 .£'6
1 J3 9*C
1 24 .0
1 25 «C
1 ?£ 9«P
1 27 9*3
1 28 9*4
1 29 9*8
£ 23. >0
2 £1 >C
2 23 *b
if 27 iC
«J l§ '$
J 22 «c
J £4 3-1,
3 25 9.3
3 2b 9.1
3 gr A. 9
_3 23 «0.
3 29 -0
TFf*0 -
oto c
2.4
1*0
1*0
2*0
. a«o_
2-0
3o
6«a_
3*0
.0
.0
>o
7.0
0
&. a
8.0
0
>0
7.C
7.0
7.0
0
>0
.0
0
:8
17* 0
17*0
Ifc-O
.a
0
1 t/A| «*
milt
y'f
11
79
los
110
0
0
lOfr
108
11*
lid
Q
C
0
e
5
0
0
o
146
160
0
0
11 DI3£*
OXYUEN
IS
14
11
15
13
0
14
Q
0
0
0
1 1
13
14
13
0
0
0
8
7
1U
0
fiTRobev
v.O
11*3
2*4
2*6
5.S
3.8
3.9
5*2
4!?
4.3
6*5.
.0
.0
* p
«, .5
5. 8
S*3
>u
13 " c
1**1
13^5
13J5
14.7
11*6
11-9
ui hnrt
i^nn rnr\
r r-rt
NITROGEN TCTAL SOL* TOTAL SCL SLSPENpED SUSPENClD
SOL: Os SOLIDS
6.4 0 0 83 E? 59 45
0.9
b.4
7!^
7.8
7.3
110
7*8
7-1
if' a
0
>0
.0
ft-4
9.0
7.1
0
ac.9
20*7
26.7
a >o
,. -J f . A
j[ t O
23. U
22*3
"*
20.7
131
76
0
115
31
15
Z
g
2C
21
IB
27
...... 35
32
41
44
..... 47
b
5$
u
0
128
50
58
23
15
24
34
23
27
13
0
0
0
15
13
10
14
41
0
-- 38
34
. 0
, 23
42
-..12
18
98
lij
2i
75
93
44
. -93
0
0
0
111
111
0
.- . o
8
.. 134
-I1
- 129
0
t|
49 ..
78
i)
IS
2C
44
^ r
si
.36
C
C
36
64
e?
32
r
C
c
L
J
11C .
91
lie
C
I,
39
33
0
o
II
45
42
J
68
/4
66
0
0
0
104
42
57
0
0
0
c
ft
8
8
... 63
0
67
60
.. 70
37
" 1*
13
if
29
5
2"$
49
37
75
37
19
22
0
0
0
36
18
32
0
38
30
SO
60
50
SO
4C
32
33
!?
5?
32
11
jy
ii
il
33
34
3«
?«
30
30
31
30
28
2l
n
0
8
8..
42
. _ .. 44
43
45
ft -
37
8 -8
3008 11008
6000 14000
iooo isooo
3000 0000
8000 1BOOO
7000 16000
2000 fcOOO
-------
TABLE D-3. Cont'd.
TR
OT
etc c INKY
01 SS *
-AMHONIA-KJEt-DAHLBCD- BOO-
NITHOOEN TCTAL bCL«
.COO CCC TOTAL VOLATILE
TOTAL SCL SLSPLNDED ~ "
SOLIDS
I
Ibu
90
120
. /B
112
b3
39
IB
-ft
24
33
. 63
II
26
P
bo
PHOSPHOROU*TECAL-TOTAL-
COLl coul
20
27
36
6?
100
eo
64
0
91
. 66
36
SO
. 39
0
31
..ll
29
. 14
25
18
8
37
23
0
0
7
0
20
- 23
146
"8
. 30
50
76
0
.. 0
5
0
.._ 8
0
0
0
0
0
8
0
0
0
0
o
8
0
. 0
§
0
0
0
0
0
Q
8
Q
10i
8
0
0
0
0
0
4000
7000
_... 8888
2000
2000
3000
0
6000
9030
10000
19000
170CO
16000
noso
7050
1 60CO
5000
7000
4000
2000
3000
27000
0
C
0
Q
8
Q
0
8
0
o
0
57000
1888
7000
7000
7000
0 .
8033
11000
21000
30000 ,
2SOOO
26COO
0
29000 .
17000
26000
13000
8000 .
9000
19000
54QOO
27000
0
0
0
0 -
0
8
o
g
0
0
0
0
o _,
-------
1ABLE D-3. Cont'd.
n»T
TR MO OT
_EH_I£3R._ALKAU
u^a c I-JIT
«STG^«M^^
H
o
-KWJ-
003 76
GO* 76
_G05_/6.
(iOfe 76
607 76
UJS 76
_GJ» 76 7
610 7ft 7
Gil 76 7
012 76 7
Ul3-.7e _J
lil* 7» 7
CIS 76 7
G16 76 7
_G17 7o 7
018 76 7
G19 76 7
020 76 7
-G21--76 7
G22 '6 7
023 76 7
G2* 76 8
G2b~It,a
026 76
fil 76
_3.-6.JL7 _
6 6«S JJj.O
7 6>4 2f'0
8 6*6 -'9.0
9 6.»_29«0.
10 t>>6 290
12 6«5 29*0
6*7
!.lQ_.100_
«0
14 S.t_30«0.
15 6*7 28*0
16 6-7 28.0
-" 6'4 2B«5
6>to-29*0 :
6'» «O !
17
1«
20 6>6 29-0 ._
21 6*3 30'U 80
.22 6>6_29«&12*
24 7.5 «U 70
25 6*5 30-0 72
£6 7.3 31.0 78
27 7.131*0 70
21 6*8 31*0 72
30 6*7 31*0 82
2 "C 29>0 62
3 6-a 39«0 76
4 6.7 2S>0 68
22 V.I 25.6 70
23 ?>H 29'0 70
:* 7.J -2f«0 --66
!6 7>« 27.0 79
>7 7*3 23«O 68
18 7.3 27.8 /O
13. 7i3_J«'fl 2i
8«* 20 6*
.. 7.7 24.0 6*
22 B'O 25*0 62
23-Hi 2
-------
TABLE D-3. Cont'd.
i* no OT
joi 7fc \a
:tl!*>_-AU.KAus DlaSiAWMONlA-KjEWDAHl
0 C I'U"Y OXYOEN v,r -
bCO_bOD_COD CCC TOTAL... VOLATILE -PHOSPHOROUS.
TOTAL SUL« IUTAL SCL SLSPENDED SUSPENDED
bOLius SOLIDS
TOTAL-
COLI COLI
.O
JOJ
J'Jt
J07
KJ1
"«03
KOS
76 10 2* >C -O
76 li) 23 7<5 13-3
76 10 2b 7«b" 13*0
ltf.27.7'5 13«_0_
't. 10 28 7-0 13.0
/6 10 29 7.7 12.0
It, 11 » 7.7 :2«0
7o .11. .5. 7«6_ il«C
'a 11 a 7.7 12>O
'6 11 9 7*7 12*0
76 11 11 8«a
KOS
_?o 11 12. .O
11 13 7.2
>l
'6
'a li
-iCiB.'ii 11
Kll 'o 11
K1Z '6 11
K13 76 11
16 7>0
. 0.
fO_.
l!o
!t>0
u
6*
6»
60
,6*
TO
12"
bb
o
6*
>0 >0
7.3 10-0
. - .. ... 7«2 8 « 0
..-76 11 22 7.« 7«0
K15 '6 11 23 7'f 10-0
76 11 2* 7.6 10«0
K16
.sU-Ji-
11 25 7.1 8«S
11 4$ 7.3 11.0.
" 5«0
6>0
'6 11 a,
'& 11 i»
7.1
..1
K23
76 li ja 7.S
_'6 IS .2 7«S
12
3 7-a
L01 >o 12 16 7*3
.L3|._76 12 17.7M.
L03 "" ------
/6 12 18"7.1
20 ?'e
/6 .-
76 12
fi'O
Jla.
6*0
9*b'
7*0
LO
. /6 U HI ,.7«1_7!0 !
/3 12 22 7*4 S«0
u
0
oO
-Ol -
30
s«
"SS"
jo
-If-
Sb
J6
L«»tt _
16
50 _
0
10
10
U.
11
.2
.2
. 4
-1-
2
.0
-:?
.1
.1
i.
.o
.1
.._.!.
1
.0
.0
- ti-
ll
.0
.0
o
.0
.0
... -0
.0
.U
.*
-'S
c
.9
l.C
il2
0
J 10S _ 2t
17
16
18
15
7
9
_ 5 _
0
3
8
go
86
98
12
11
t3
<*6
5«2 IS
<»6 2b
i>6 i!t
<» 17
9-1 32
ff.b 25
0«9 21
9.6 a?
b*2 25
S>9 0
- fc.7 i1*
b.<* 30
*» Jl
»«b £3
S.g So
7.3 27
s*a n
7.1 0
"~~ S.«t 12
7.1 2V
-?:s fr
1J:8 2?:
8.2 _ 11
B.I 3b
11
S
9a
3_»15
1 113 " 63
8 118 b7
2 121 7l
9._ 131 . El
123 1C
ICit 18
10s 51
It7 17
110 t6
120 19
109 76
125 -- 19
116 ||
5 130 £9
It 133 -- 16 ..-
8
0
68
6G
93
to
bb
t?
52
»6
?*
6b
0.
0
25
31
17
23
its
25
30
15
62
38
37
26 0
38
o
38
58
8 8
3
0
16
o '
2
2
0
2 '-
103 .
106
13Q
116
120
B9
l&H
127
110
SZ
H
*S
?i
51
t2
0
36
- 5j
2 6
to
30
2*
27
1
0
0
10
6
2t
0 J
0
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/2-79-014
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
PERFORMANCE EVALUATION OF EXISTING AERATED
LAGOON SYSTEM AT BIXBY, OKLAHOMA
5. REPORT DATE
March 1979 [Issuing Date)
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
George W. Reid, Leale Streebin
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
University of Oklahoma
Bureau of Water and Environmental Resources
Norman, Oklahoma 73019
10. PROGRAM ELEMENT NO.
1BC822 SOS #3 Task D-l/26
Research
11. CONTRACT/GRANT NO.
R-803916
12. SPONSORING AGENCY NAME AND ADDRESS
Municipal Environmental Research Laboratory--Cin.,OH
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, Ohio 45268
13. TYPE OF REPORT AND PERIOD COVERED
Final 1/6/76-12/22/76
14. SPONSORING AGENCY CODE
EPA/600/14
15. SUPPLEMENTARY NOTES
Project Officer: Ronald F. Lewis, (513) 684-7644
16. ABSTRACT
The University of Oklahoma School of Civil Engineering and Environmental Science
research group in collaboration with INCOG 5 BIXBY, have studied a well designed,
well operated two cell aerated wastewater treatment lagoon system. The study involved
four seasons and nineteen study parameters. The data was treated to statistical
analysis, using a SPSS multiple regression, and to normative analytical expression.
This report covers the BIXBY lagoon system operation period of January 1976 through
December 1976.
The lagoon exhibited an overall BOD,, removal efficiency of 92%, but was only
totally in compliance for 7 months of the year. The use of several kinetic models
and regression models were not very satisfactory though the temperature coefficient
were in substantial agreement with Adams and Eckenfelders and other reputed values.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
Waste treatment
*Lagoons (ponds)
*Performance evaluation
*Design criteria
Chemical analysis
Physical tests
Aerated
13B
18. DISTRIBUTION STATEMENT
Release to Public
INSECURITY CLASS (ThisReport)
Unclassified
21. NO. OF PAGES
117
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
105
* U.S. MYUWMWt niMTMeornCb 1971 -657-06071606
------- |