United States
Environmental Protection
Agency
Effluent Guidefines Division
WH-552
Washington OC 20460
EPA 440/1^3/009-^
.ฃohOiar>1983**"
Development
Document for Effluent
Limitations Guidelines
and Standards for the
Organic Chemicals
and Plastics and
Synthetic Fibers
Point Source Category
Volume I (BPT)
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DEVELOPMENT DOCUMENT
for
PROPOSED EFFLUENT LIMITATIONS GUIDELINES
AND
NEW SOURCE PERFORMANCE STANDARDS
FOR THE
ORGANIC CHEMICALS AND PLASTICS AND SYNTHETIC
FIBERS INDUSTRY
VOLUME I
(BPT)
Anne M. Bur ford
Adminstrator
Frederic A. Eidsness, Jr.
Assistant Administrator For Water
Steven Schatzow, Director
Office of Water Regulations and Standards
Jeffery D. Denit, Director
Effluent Guidelines Division
Devereaux Barnes, Acting Branch Chief
Organic Chemicals Branch
Elwood H. Forsht
Project Officer
FEBRUARY 1983
EFFLUENT GUIDELINES DIVISION
OFFICE OF WATER REGULATIONS AND STANDARDS
U.S. ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, DC 20460
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notice MAR 31 1983
On February 28, 1983, EPA proposed effluent limitations guidelines and
standards for the organic chemicals and plastics and synthetic fibers (OCPSF)
point source category. The Federal Register notice of this proposal was printed
on March 21, 1983 (48 FR 11828 to 11867).
Information received by the Agency after proposal indicates that the total
OCPSF industry estimated annual discharges of toxic pollutants are too high.
The Agency will be reevaluating these estimates when additional information
becomes available prior to promulgation of a final regulation. In the interim,
the Agency advises that there should be no reliance on the annual total toxic
pollutant discharge estimates presented in the Federal Register notice, the
February 1983 OCPSF Development Document, and February 10, 1983 OCPSF Regulatory
Impact Analysis.
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TABLE OF CONTENTS
VOLUME I
SECTION PAGE
I INTRODUCTION 1
II SUMMARY AND CONCLUSIONS 5
III DESCRIPTION OF INDUSTRY 11
Introduction 11
Definition of the Industry 12
Product/Process Description 29
Data Base Profile 39
IV SUBCATEGORIZATION 61
Introduction 61
Statistical Methodology 61
Technical Methodology 62
Raw Wastewater Characteristics 63
Manufacturing Product/Processes 63
Facility Size 70
Geographical Location 72
Age of Facility and Equipment 83
Raw Materials 94
Treatability 95
Energy and Non-Water Quality Aspects 96
Summary-Subcategorization 97
V SELECTION OF POLLUTANT PARAMETERS 99
Wastewater Parameters 99
Conventional Pollutant Parameters 99
Non-Conventional Pollutant Parameters 102
VI WATER USE AND WASTEWATER CHARACTERIZATION 105
Water Use and Sources of Wastewater 105
Wastewater Characterization 108
VII CONTROL AND TREATMENT TECHNOLOGIES 119
General
In-Plant Source Controls
In-Plant Treatment
End-of-Pipe Treatment 1^1
0CPS Effluent Quality
Effluent Variability m
Wastewater Disposal
i
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TABLE OF CONTENTS (Continued)
VOLUME I (CONTINUED)
VIII ENGINEERING COSTS AND NON-WATER QUALITY ASPECTS 199
Introduction 199
Cost Development 199
CAPDET Modifications 199
Estimating Discrete Unit Costs 205
Bench Mark Analysis 235
Effluent Target Levels 235
Plant-by-Plant Cost Results 241
BPT Cost Estimates 241
CAPDET Reproducibility 268
Further Changes to CAPDET 268
Non-Water Quality Aspects 269
IX EFFLUENT REDUCTION ATTAINABLE THROUGH THE APPLICATION OF BEST
PRACTICABLE CONTROL TECHNOLOGY CURRENTLY AVAILABLE
General 277
Regulated Pollutants 277
Identification of the Best Practicable Control
Technology 277
Rationale for Selection of Best Practicable Control
Technology 278
BPT Effluent Limitations 279
Methodology Used for Development of BPT Effluent
Limitations 279
Cost of Application and Effluent Reduction Benefits 281
Non-Water Quality Environmental Impacts 283
Energy 283
Solid Waste 283
Air and Noise 283
X EFFLUENT REDUCTION ATTAINABLE THROUGH THE APPLICATION OF BEST
CONVENTIONAL POLLUTANT CONTROL TECHNOLOGY EFFLUENT LIMITATIONS
GUIDELINES
General 285
Regulated Pollutants 285
Identification of the Best Conventional Pollutant
Control Technology 285
BCT Effluent Limitations 285
Rationale for the Selection of Best Conventional
Pollutant Control Technology 287
Methodology Used for Development of BCT Effluent
Limitations < 287
Cost of Application and Effluent Reduction Benefits 287
Non-Water Quality Environmental Impacts 287
11
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TABLE OF CONTENTS (Continued)
VOLUME I (CONTINUED)
XI NEW SOURCE PERFORMANCE STANDARDS
General 289
Regulated Pollutants 289
Identification of the Technology Basis of NSPS 289
New Source Performance Standards 289
Rationale for the Selection of the Technology Basis
for NSPS 289
Methodology Used for Development of NSPS Effluent
Limitations 289
Cost of Application and Effluent Reduction Benefits 291
Non-Water Quality Environmental Impacts 291
XII ACKNOWLEDGMENTS 293
XIII
REFERENCES
295
APPENDIX A Product/Process Frequency Counts for 308 Summary Data Base
APPENDIX B BPT Development Document Statistics
APPENDIX C Glossary
APPENDIX D Rationale for Exclusion of Daily Data Base Plants From
Variability Analysis
APPENDIX E CAPDET Methodology
APPENDIX F Discrete Unit Cost Curves
APPENDIX G Waste Stream Data Listing
iii
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LIST OF TABLES
Page
2-1 BPT Effluent Limitations 9
3-1 Annual Production and Sales by SIC Code 14
3-2 Annual Production Volume of Organic Chemicals in "Top 50"
List 1980 15
3-3 Annual Production Volume of Plastics and Synthetic Fibers
1980 16
3-4 OCPS Plant Distribution by SIC Code 18
3-5 Plant Distribution by State 19
3-6 Plant Distribution by Employment Size 22
3-7 Plant Distribution by Sales Volume 24
3-8 Plant Distribution by Age 27
3-9 Generic Chemical Processes and Codes 37
3-10 Data Base Designation 41
3-11 Plants and Their Associated Streams 47
3-12 Number and Types of Plants and Streams in the Data Bases 53
3-13 Production Comparisons 55
3-14 Number and Type of Plants and Streams by Age 56
3-15 Number and Types of Plants and Streams by Product/Processes 58
3-16 Occurrences of Generic Processes 59
4-1 Expected 5-Day Biochemical Oxygen Demand by Generic
Process Group 68
4-2 Terry-Hoeffding Test for Not Plastics Only Plants 69
4-3 Terry Hoeffding Test for Subcategorization Based On COD
and TOC 71
4-4 (Direct Systems) Number of Streams Within Production
70
Rate Ranges 'J
iv
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LIST OF TABLES (Continued)
Paง,
4-5
Spearman Correlation Coefficients (R) for Raw Waste BOD
and TSS vs. Size
74
4-6
(Direct Systems) Number of Streams Per Age Group
84
4-7
Spearman Correlation Coefficients (R) For Raw Waste BOD
and TSS vs. Age
93
6-1
Effluent Flows by Subcategory (Direct Dischargers)
106
6-2
Influent Flows by Subcategory (Zero/Alternate Dischargers)
107
6-3
Raw Wastewater Characteristics - Plastics Only (Direct)
110
6-4
Raw Wastewater Characteristics - Plastics Only
(Zero/Alternate)
111
6-5
Raw Wastewater Characteristics - Type I with Oxidation
(Direct)
112
6-6
Raw Wastewater Characteristics - Type I with Oxidation
(Zero/Alternate)
113
6-7
Raw Wastewater Characteristics - Type I Without Oxidation
(Direct)
114
6-8
Raw Wastewater Characteristics - Type I Without Oxidation
(Zero/Alternate)
115
6-9
Raw Wastewater Characteristics - Not Type I (Direct)
116
6-10
Raw Wastewater Characteristics - Not Type I (Zero/Alternate)
117
7-1
Principal Treatment/Disposal Practices
120
7-2
Companies Reported to Have Activated Carbon Experience
124
7-3
Steam Stripping
130
7-4
Clarification
133
7-5
Precipitation, Coagulation, Filtration
134
7-6
Dissolved Air Flotation
136
7-7
Degree Days Vs. Effluent Quality
143
7-8
Aerated Lagoons
v
145
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LIST OF TABLES (Continued)
Page
7-9 Aerated Lagoons - Plastics Only 146
7-10 Aerated Lagoons - Type I and C 147
7-11 Aerated Lagoons - Type I NOT C 148
7-12 Aerated Lagoons - Not Type I 149
7-13 Aerobic Lagoons 150
7-14 Anaerobic Treatment 152
7-15 Activated Sludge 153
7-16 Activated Sludge - Plastics Only 154
7-17 Activated Sludge - Type I and C 155
7-18 Activated Sludge - Type I NOT C 156
7-19 Activated Sludge - Not Type I 157
7-20 UNOX Process 158
7-21 Trickling Filter 160
7-22 Rotating Biological Contactor 161
7-23 Activated Carbon 163
7-24 Biological Systems 169
7-25 Single Stage and Two Stage Biological Systems 171
7-26 Biological Systems With Polishing 172
7-27 Biological Systems With MMF 173
7-28 Biological Systems 174
7-29 Biological Systems, >95% Removal 175
7-30 Biological Systems, >95% or <50 mg/1 176
7-31 Biological Systems, >95% or <30 mg/1 178
7-32 Biological Systems, TSS Concentrations 180
7-33 Biological Sytems With Polishing, TSS Concentrations 181
7-34 Biological Systems With MMF, TSS Concentrations 182
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LIST OF TABLES (Continued)
Page
7-35 Biological Systems With Activated Carbon,
TSS Concentrations 183
7-36 Summary of Plant Screening 187
7-37 Summary of Engineering Analysis 190
7-38 Plastics Only Variability Factors 193
7-39 Not Plastics Only Variability Factors 194
8-1 Adjustments to CAPDET Default Data and Results 200
8-2 CAPDET Default Influent Waste Characteristics 203
8-3 Waste Characteristic Removal Default Values For CAPDET
Processes 204
8-4 Cost Summary, Flotation 207
8-5 Cost Summary, Clarification (Sedimentation) 208
8-6 Cost Summary, Activated Sludge 209
8-7 Cost Summary, Aerated Lagoon 210
8-8 Cost Summary, Multimedia Filtration 211
8-9 CAPDET Unit Process Replacement Schedule 213
8-10 Cost Summary, Polishing Ponds 230
8-11 Comparison of Polishing Pond and Multimedia Filter Costs 234
8-12 Bench Mark Comparisons 236
8-13 Effluent Target Levels ^37
8-14 Sample Plant-By-Plant Cost Analysis 238
8-15 Plant-By-Plant Suggested Treatment and Costs,
Non-Plastics ^42
8-16 Plant-By-Plant Suggested Treatment and Costs,
Plastics ^52
8-17 Potential BPT Effluent Limitations 258
8-18 Plant-By-Plant Cost Estimates 259
vii
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LIST OF TABLES (Continued)
Page
8-19 Total Costs, Plant-By-Plant Analysis 265
8-20 Percentage of Plants Requiring Additional Treatment For
BPT(l) 266
8-21 Percentage of Plants Requiring Additional Treatment For
BPT(II) 266
8-22 Percentage of Annual Costs by Subcategory 267
9-1 BPT Effluent Limitations 280
9-2 Effluent Reduction Benefits and Non Water Quality Impacts
For Each of the Proposed Subcategories 282
9-3 Case Study for Estimating Total Industry Direct Discharge
Loadings for BOD^ and TSS 284
10-1 BCT Effluent Limitations 286
10-2 BCT "Cost-Reasonableness" Test Results 288
11-1 NSPS Effluent Limitations 290
vlii
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LIST OF FIGURES
Page
3-1 Plant Distribution by Number of Employees 23
3-2 Plant Distribution by Sales Volume 26
3-3 Distribution by age of OCPS Plants 28
3-4 Some Products Derived From Methane 30
3-5 Some Products Derived From Ethylene 31
3-6 Some Products Derived From Propylene 32
3-7 Some Products Derived from and Higher Aliphatics 33
3-8 Some Products Derived From Aromatics 34
3-9 Data Overlaps 42
3-10 Data Base and Related Industry Guidelines Overlap 45
4-1 Probability Plot of Subcategory Influent BOD 64
4-2 Least Squares Fit of Figure 4-1 65
4-3 Rank Correlations - Direct Discharge Systems - Not Plastics
Only/Not Type I 75
4-4 Rank Correlations - Direct Discharge Systems - Not Plastics
Only/Type I and Not C 76
4-5 Rank Correlations - Direct Discharge Systems - Not Plastics
Only/Type I & C 77
4-6 Rank Correlations - Direct Discharge Systems -
Plastics Only 78
4-7 Rank Correlations - Direct Discharge Systems - Not Plastics
Only/Not Type I ^9
4-8 Rank Correlation - Direct Discharge Systems - Not Plastics
Only/Type I and Not C
4-9 Rank Correlation - Direct Discharge systems - Not Plastics
Only/Type I & C 81
4-10 Rank Correlation - Direct Discharge Systems -
Plastics Only
ix
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LIST OF FIGURES (Continued)
Pag
4-11 Rank Correlation - Direct Discharge Systems -
Plastics Only 85
4-12 Rank Correlation - Direct Discharge Systems - Not Plastics
Only/Type I & C 86
4-13 Rank Correlation - Direct Discharge Systems - Not Plastics
Only/Type I and Not C 87
4-14 Rank Correlation - Direct Discharge Systems - Not Plastics
Only/Not Type I 88
4-15 Rank Correlation - Direct Discharge Systems -
Plastics Only 89
4-16 Rank Correlation - Direct Discharge Systems - Not Plastics
Only/Type I & C 90
4-17 Rank Correlation - Direct Discharge System - Not Plastics
Only/Type I & Not C 91
4-18 Rank Correlation - Direct Discharge Systems - Not Plastics
Only/Not Type I 92
7-1 Biological Systems - Plastics Only 138
7-2 Biological Systems - Not Plastics Only 139
7-3 Temperature Effect of Effluent Quality 141
7-4 Effluent BOD vs. Gal/lb Product Water Discharged 179
7-5 Moving Summary Graph Type 185
7-6 Estimated 99 Percentile vs. Moving Time Intervals 186
8-1 Aerator Retention Time Sensitivity Analysis 206
8-2 Captital, Operating and Annual Costs, Dissolved Air
Flotation 215
8-3 Capital, Operating and Annual Costs, Sedimentation 217
8-4 Activated Sludge Process Considered for Cost Estimation 218
8-5 Capital Costs, Activated Sludge 220
8-6 Operating Costs, Activated Sludge 221
x
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LIST OF FIGURES (Continued)
Page
8-7 Annual Costs, Activated Sludge 222
8-8 Aerated Lagoon Process Considered for Cost Estimation 223
8-9 Capital Costs, Aerated Lagoons 224
8-10 Operating Costs, Aerated Lagoons 225
8-11 Annual costs, Aerated Lagoons 226
8-12 Multimedia Filtration Process 228
8-13 Capital, Operating and Annual Costs,
Multimedia Filtration 229
8-14 Sludge Production For Complete Mix Activated Sludge 271
8-15 Energy Requirements For Complete Mix Activated Sludge 273
8-16 Energy Requirements For Clarification 274
8-17 Energy Requirements For Dissolved Air Flotation 275
8-18 Energy Requirements For Multimedia Filtration 276
xi
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SECTION I
INTRODUCTION
PURPOSE AND LEGAL AUTHORITY
The Federal Water Pollution Control Act Amendments of 1972 established a
comprehensive program to restore and maintain the chemical, physical and
biological integrity of the nation's waters [Section 101(a) ]. by July 1,
1977 existing industrial direct dischargers were required to achieve ef-
fluent limitations requiring the application of the best practicable con-
trol technology currently available (BPT) [ Section 301(b)(1)(A) ]. By
July 1, 1983 these dischargers were required to achieve effluent limita-
tions requiring the application of the best available technology econom-
ically achievable (BAT), which will result in reasonable further progress
toward the national goal of eliminating the discharge of all pollutants
[ Section 301(b)(2)(A) ]. New industrial direct dischargers were required
to comply with Section 306 new source performance standards (NSPS) based on
best available demonstrated technology. New and existing dischargers to
publicly owned treatment works (POTW) were subject to pretreatment stan-
dards under Sections 307(b) and (c) of the Act. The requirements for di-
rect dischargers were to be incorporated into National Pollutant Discharge
Elimination System (NPDES) permits issued under Section 402 of the Act.
Pretreatment standards were made enforceable directly against dischargers
to P0TW8 (indirect dischargers).
Although Section 402(a)(1) of the 1972 Act authorized local authorities to
set requirements for direct dischargers on a case-by-case basis, Congress
intended that for the most part control requirements would be based on
regulations promulgated by the EPA Administrator. Section 304(b) of the
Act required the Administrator to promulgate regulatory guidelines for di-
rect discharger effluent limitations, setting forth the degree of effluent
reduction attainable through the application of best practicable control
technology (BPT). Moreover, Sections 304(c) and 306 of the Act required
promulgation of regulations for NSPS, and Sections 304(f), 307(b) and
307(c) required promulgation of regulations 'for pretreatment standards. In
addition to these regulations for designated industry categories, Section
307 (a) of the Act required the Administrator to promulgate effluent stan-
dards applicable to all dischargers of toxic pollutants. Finally, Section
501(a) of the Act authorized the Aministrator to prescribe any additional
regulations necessary to carry out his or her functions under the Act.
The EPA was unable to promulgate many of these regulations by the dates
contained in the Act. In 1976 EPA was sued by several environmental
groups. In settlement of this lawsuit, EPA and the plaintiffs executed a
settlement agreement which was approved by the Court. This agreement re-
quired EPA to develop a program and adhere to a schedule for promulgating,
for 21 major industries, BAT effluent limitations guidelines, pretreatment
standards and new source performance standards for 65 "toxic" pollutants
and classes of pollutants.
On December 2f, 1977 the President signed into law the Clean Water Act of
1977. Although this law makes several important changes in the federal
water pollution control program, its most significant feature is its
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incorporating into the Act several of the basic elements of the settlement
agreement program for toxic pollution control. Sections 301(b)(2)(A) and
301(b)(2)(C) of the Act now require the achievement by July 1, 1984 of
effluent limitations requiring application of BAT for toxic pollutants,
including the 65 priority pollutants and classes of pollutants which Con-
gress declared toxic under Section 307(a) of the Act. Likewise, EPA's
programs for new source performance standards and pretreatment standards
are now aimed principally at toxic pollutant controls. Moreover, to
strengthen the toxics control program, Congress added Section 304(e) to the
Act, authorizing the Administrator to prescribe best management practices
(BMPs) to prevent the release of toxic and hazardous pollutants from plant
site runoff, spillage or leaks, sludge or waste disposal, and drainage from
raw material storage associated with, or ancillary to, the manufacturing or
treatment process.
In keeping with its emphasis on toxic pollutants, the Clean Water Act of
1977 also revised the control program for "conventional" pollutants
(including biochemical oxygen demand, suspended solids, fecal coliform, oil
and grease, and pH) identified under Section 304(a)(4). Instead of BAT for
conventional pollutants, the new Section 301(b)(2)(E) requires by July 1,
1984 achievement of effluent limitations requiring the application of the
best conventional pollutant control technology (BCT). The factors consid-
ered in assessing BCT include the reasonableness of the relationship be-
tween the costs of attaining a reduction in effluents and the effluent re-
duction benefits derived, and the comparison of the cost and level of
reduction for an industrial discharge with the cost and level of reduction
of similar parameters for a typical POTW [ Section 304(b)(4)(B) ]. For
nontoxic, nonconventional pollutants, Sections 301(b)(2)(A) and
301(b)(2)(F) require achievement of BAT effluent limitations within three
years after their establishment or after July 1, 1984 (whichever is later),
but not later than July 1, 1897.
This document presents the technical bases for the application of revised
BPT, BCT and conventional pollutant new source performance standards (NSPS)
for the organic chemicals and plastics and synthetics (OCPS) manufacturing
point source category. The technical bases for toxic pollutant related
limitations are presented in the "BAT" Development Document which is being
published jointly with this report.
PRIOR EPA REGULATIONS
EPA promulgated effluent limitation guidelines and standards for the
Organic Chemicals Manufacturing Industry, in two phases, in 40 CFR Part
414. Phase I, covering 40 product/processes (a product that is manufac-
tured by the use of a particular processsome products may be produced by
any of several processes), was promulgated on April 25, 1974 (39 FR 12076).
Phase II, covering 27 additional product/processes, was promulgated on
January 5, 1976 (41 FR 902).
EPA also promulgated effluent limitation guidelines and standards for the
Plastics and Synthetics Industry, in two phases, in 40 CFR Part 416. Phase
I, covering 31 product/processes, was promulgated on April 5, 1974 (39 FR
12502). Phase II, covering 8 additional product/processes, was promulgated
on January 23, 1975 (40 FR 3718).
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Several industry members challenged the above regulations. On February 10,
1976 the Court, in Union Carbide v. Train, 541 F.2d 1171 (4th Cir. 1976),
granted the parties' motion to remand the Phase I Organic Chemicals regula-
tions. The Court also directed EPA to withdraw the Phase II Organic Chem-
ical regulations, which EPA did on April 1, 1976 (41 FR 13936). Pursuant
to an agreement with the industry petitioners, however, the regulations for
butadiene manufacture were left in place. The court in FMC Corp. v. Train,
539 F.2d 973 (4th Cir. 1976). remanded the Phase I Plastics and Synthetics
regulations. In response, EPA withdrew both the Phase I and Phase II regu-
lations on August 4, 1976 (41 FR 32587) except for the pH limitations,
which had not been addressed in the lawsuit.
Today, there are no promulgated regulations for the Organic Chemicals and
Plastics and Synthetics Industries, except for the butadiene and pH regu-
lations mentioned above.
This report prsents a summary of the data collected by the studies under-
taken since 1976, and the analyses used to support the proposed regula-
tions. Section II presents a summary of the findings presented in this
document, along with the proposed regulations. Sections III through VIII
present the technical data and the supporting analyses used as the bases
for the proposed regulations, and Sections IX through XI include the actual
numerical development of the national limitations. Detailed data displays
are included in Appendices A-G.
3
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SECTION II
SUMMARY AND CONCLUSIONS
SUMMARY
EPA is proposing effluent limitations guidelines basd on the application of
the best practicable technology (BPT), best conventional technology (BCT),
best available technology (BAT), new source performance standards (NSPS)
and pretreatment standards for existing and new sources (PSES and PSNS).
These proposed regulations apply to wastewater discharges resulting from
the manufacture of organic chemicals, plastics and synthetic fibers. The
organic chemicals industry is generally included within the U. S. Depart-
ment of Commerce, Bureau of the Census Standard Industrial Classification
(SIC) Major Groups 2865 and 2869. The plastic and synthetic fibers indus-
try is generally included in SIC Groups 2821, 23823, and 2824. Due to the
interdependence of these two industries, EPA studied them in combination
and is including both of them in a single set of proposed regulations.
When finally promulgated, these regulations will supersede the existing
regulations for butadiene manufacture and the pH limitation for the
manufacture of plastics and synthetic fibers.
Some plants have OCPS operations that are a minor portion of and ancillary
to their primary production. In some such cases, effluent guidelines for
the primary production category (e.g., the guidelines for the petroleum
refining, pesticides, and pharmaceuticals industries) include subcategories
for the discharge of combined wastewaters from the primary production and
the OCPS processes. In such cases, to avoid duplication and potential in-
consistencies, these OCPS discharges are excluded from coverage by the pro-
posed OCPS regulations and remain subject to the other applicable
regulations.
The proposed regulations also do not apply to discharges from the extrac-
tion of organic chemical compounds from natural materials. Natural mate-
rials used to make organic chemical compounds include a variety of parts of
plants (e.g., trees and seaweed) and animals. These proposed regulations
address the manufacture of organic chemicals via chemical synthesis.
Readers should note that extraction of chemical compounds from natural
materials is included in many other industrial categories, e.g., Adhesives
and Sealants, Pharmaceuticals, and Gum and Wood Chemicals. Readers should
also note that discharges from the synthesis of organic chmical compounds
that have been extracted from natural materials are covered by these pro-
posed regulations.
The OCPS industry is large and diverse, and many plants in the industry are
highly complex. The industry includes approximately 1,200 facilities which
manufacture their principal or primary product or group of products under
the OCPS SIC Groups. Some plants are secondary producers, with OCPS prod-
ucts ancillary to their primary manufacture. Various sources studied by
EPA indicate that the number of secondary OCPS plants is in the range of
5
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320 to approximately 900 plants. Thus, the total number of plants in the
OCPS industry may be as high as 2,100. This range is attributed to the
difficulties inherent in segregating the OCPS industry from other chemical
producing industries such as petroleum refining, inorganic chemicals, phar-
maceuticals and pesticides as well as chemical formulations industries such
as adhesives and sealants, paint and ink, and plastics molding and formu-
lating. Even though over 25,000 different organic chemicals, plastics and
synthetic fibers are manufactured, only 1,200 products are produced in
excess of 1,000 pounds per year. As mentioned above, except for certain
specified exceptions, all discharges from OCPS operations at these plants
are covered by these proposed regulations.
Some plants produce chemicals in large volumes, while others produce only
small volumes of "specialty" chemicals. Large-volume production tends
toward continuous processes, while small-volume production tends toward
batch processes. Continuous processes are generally more efficient than
batch processes minimizing water use and optimizing the consumption of raw
materials in the process.
Different products are made by varying the raw materials, chemical reaction
conditions and the chemical engineering unit processes. The products being
manufactured at a single large chemical plant can vary on a weekly or even
daily basis. Thus, a single plant may simultaneously produce many differ-
ent products in a variety of continuous and batch operations, and the
product mix may change frequently.
Total production of organic chemicals in 1980 was 291 billion pounds, with
sales of $54 billion. Production of plastics and synthetic fibers in 1980
was 60 billion pounds, with sales of $26 billion.
For the 1200 facilities whose principal production relates to the OCPS in-
dustry, approximately 40 percent are direct dischargers, approximately 36
percent are indirect dischargers (plants that discharge to publicly owned
treatment works), and the remaining facilities use zero or alternative dis-
charge methods. The estimated average daily flow per plant is 2.31 MGD
(millions of gallons per day) for direct dischargers and 0.80 MGD for
indirect dischargers. The remainder use dry processes, reuse their waste-
water, or dispose of their wastewater by deep well injection, incineration,
contract hauling, or evaporation or percolation ponds.
As a result of the wide variety and complexity of raw materials and proc-
esses used and of products manufactured in the OCPS industry, an excep-
tionally wide variety of pollutants are found in the wastewaters of this
industry. This includes conventional pollutants (pH, BOD, TSS and oil and
grease), toxic pollutants (both metals and organic compounds), and a large
number of organic compounds produced by the industry for sale).
To control the wide variety of pollutants discharged by the OCPS industry,
OCPS plants use a broad range of in-plant controls, process modifications
and end-of-pipe treatment techniques. Most plants have implemented pro-
grams that combine elements of both in-plant control and end-of-pipe waste-
water treatment. The configuration of controls and technologies differs
6
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from plant to plant, corresponding to the differing mixes of products man-
ufactured by different facilities. In general, direct dischargers treat
their wastes more extensively than indirect dischargers.
The predominant end-of-pipe control technology for direct dischargers in
the OCPS industry is biological treatment. The chief forms of biological
treatment are activatd sludge and aerated lagoons. Other systems, such as
extended aeration and trickling filters, are also used, but less extensive-
ly. All of these systems reduce BOD and TSS loadings and, in many instan-
ces, incidentally remove toxic and nonconventional pollutants. Biological
systems biodegrade some of the organic pollutants, remove bio-refractory
organics and metals by sorption into the sludge, and strip some volatile
organic compounds into the air.
Other end-of-pipe treatment technologies used in the OCPS industry include
neutralization, equalization, polishing ponds, filtration and carbon
adsorption. While most direct dischargers use these physical/chemical
technologies in conjunction with end-of-pipe biological treatment, at least
39 direct dischargers use only physical/chemical treatment.
In-plant control measures employed at OCPS plants include water reduction
and reuse techniques, chemical substitution and process changes. Tech-
niques to reduce water use include the elimination of water use where
practicable, and the reuse and recycling of certain streams, such as
reactor and floor washwater, surface runoff, scrubber effluent and vacuum
seal discharges. Chemical substitution is utilized to replace process
chemicals possessing highly toxic or refractory properties by others that
are less toxic or more amenable to treatment. Process changes include var-
ious measures that reduce water use, waste discharges, and/or waste load-
ings while improving process efficiency. Replacement of barometric con-
densers with surface condensers, replacement of steam jet ejectors with
vacuum pumps, recovery of product or by-product by steam stripping, dis-
tillation, solvent extraction or recycle, oil-water separation and carbon
adsorption, and the addition of spill control systems are examples of proc-
ess changes that have been successfully employed in the OCPS industry to
reduce pollutant loadings while improving process efficiencies.
Another type of control widely used in the OCPS industry is physical/
chemical in-plant control. This treatment technology is generally used
selectively on certain process wastewaters to recover products or process
solvents, to reduce loadings that may impair the operation of the biolog-
ical system or to remove certain pollutants that are not removed suffi-
ciently by the biological system. In-plant technologies widely used in the
OCPS industry include sedimentation/clarification, coagulation, floccula-
tion, equalization, neutralization, oil/water separation, steam stripping,
distillation and dissolved air flotation.
Many OCPS plants also use physical/chemical treatment after biological
treatment. Such treatment is used in the majority of situations to reduce
solids loadings that are discharged from biological treatment systems. The
most common post-biological treatment systems are polishing ponds and
multimedia filtration.
7
-------
At approximately 5 percent of the direct discharging plants surveyed, no
treatment is provided. At another 20 percent, only physical/chemical
treatment is provided. The remaining 75 percent utilize biological treat-
ment. Approximately 36 percent of biologically treated effluents are fur-
ther treated by polishing ponds, filtration or other forms of physical/
chemical control.
At approximately 52 percent of the indirect discharging plants surveyed, no
treatment is provided. At another 39 percent, some physical/chemical
treatment is provided. Nine percent have biological treatment.
CONCLUSIONS
BPT
Biological teatment has been identified as the best practicable control
technology currently available for each of the four proposed subcategories.
In general, the long-term median BPT final effluent BOD,, and TSS concentra-
tions were calculated for each subcategory by using the performance of
plants which attain 95% BOD, reduction or a final effluent BOD,, concentra-
tion less than or equal to 50 mg/1.
Maximum 30-day and daily maximum effluent limitations were determined by
multiplying long-term median effluent limitations by appropriate variabil-
ity factors which were calculated through statistical analysis of long-term
BOD,, and TSS daily data. This statistical analysis is described in detail
in Section VII.
Proposed BPT limitations are presented in Table 2-1.
BCT
The 1977 amendments added Section 301(b)(2)(E) to the Act, establishing
"best conventional pollutant control technology" (BCT) for discharges of
conventional pollutants from existing industrial point sources. Section 304
(a)(4) designated the following as conventional pollutants: BOD, TSS,
fecal coliform and pH. The Administrator designated oil and grease as
"conventional" on July 30, 1979, 44 FR 44501.
EPA has proposed a BCT cost-reasonableness test which provides that BCT is
cost-reasonable if: (1) the incremental cost per pound of conventional
pollutant removed in going from BPT to BCT is less than $.27 per pound in
1976 dollars, and (2) this same incremental cost per pound is less than
143% of the incremental cost per pound associated with achieving BPT.
All the incremental costs per pound ratios were found to fail this first
part of the BCT "cost-reasonableness" test ($0.33 per pound in 1979 dol-
lars). Therefore, EPA did not perform the second part of the BCT "cost-
reasonableness" test, and is proposing BCT effluent limitations which are
equal to the BPT effluent limitations for each of the proposed BPT
subcategories.
8
-------
TABLE 2-1
BPT EFFLUENT LIMITATIONS
(mg/1 or ppm)
LONG TERM MEDIAN
SUBCATEGORY
Plastics Only
bod5
14.5
TSS
24
MAXIMUM 30-DAY
BOD 5
22
TSS
36
MAXIMUM DAILY
BOD.
49
TSS
117
Oxidation
o High Water Use
o Low Water Use
26
36
62
89
42
58
84
120
106
146
246
353
Type I
24.5 34.5
40
47
100
137
Other Discharges 17
29
28
39
69
115
9
-------
NSPS
The basis for new source performance standards (NSPS) under Section 306 of
the Act is the best available demonstrated technology. At new plants, the
opportunity exists to design the best and most efficient production proc-
esses and wastewater treatment facilities. Therefore, Congress directed
EPA to consider the best demonstrated process change, in-plant controls and
end-of-pipe treatment technologies that reduce pollution to the maximum
extent feasible. It is encouraged that at new sources reductions in the
use of and/or discharge of wastewater be attained by application of
in-plant control measures.
The technologies employed to control conventional pollutants at existing
plants are fully applicable to new plants. In addition, no other technol-
ogies could be identified for new sources which were different from those
used to establish BPT effluent limitations. Thus, the technology basis for
NSPS is the same as that for BPT effluent limitations. For detailed infor-
mation on the technology basis for BPT effluent limitations, refer to
Section IX of this document.
Since the Agency could identify no additional generally applicable technol-
ogy for NSPS, and since the technology basis for NSPS is the same as that
identified for BPT effluent limitations, EPA has established NSPS effluent
limitations equal to the proposed BPT and BCT effluent limitations.
10
-------
SECTION III.
DESCRIPTION OF INDUSTRY
INTRODUCTION
The organic chemicals industry had very modest beginnings in the middle
of the 19th century. The production of coke, used both as fuel and a
reductant in blast furnaces for steel production, generated coal tar as
a by-product. Although these tars were initially regarded as wastes,
with the synthesis of the first coal tar dye (mauve) by Perkin in 1856,
chemists and engineers began to look for ways to recover and use all
industrial by-products.
With increasing numbers of chemical compounds possessing valuable prop-
erties being identified, commercial routes to these compounds became
necessary. Not surprisingly, the early products of the chemical indus-
try were those most desired by society: dyestuffs, explosives, and
pharmaceuticals. The economic incentive to find markets for industrial
wastes and by-products continued to be a driving force behind these in-
dustries. The chlorinated aromatic chemicals industry, for example,
developed mainly out of: (1) the need to use the large quantities of
chlorine formed as a by-product from caustic soda production, (2) the
availability of benzene derived from coal tar, and (3) the discovery
that such compounds could serve as useful intermediates for production
of other, more valuable materials, e.g., phenol and picric acid. In
time, specialty products such as surfactants, pesticides, and aerosol
propellants were also developed.
The plastics and synthetic fibers industry began only somewhat later.
The first commercial polymers, rayon and bakelite, were produced in the
early 1900s from feedstocks manufactured by the organic chemicals indus-
try. While the organic chemicals and plastics and synthetic fibers in-
dustries are regarded as separate, the latter is clearly an outgrowth of
the organic chemicals industry. The variety of plastic and synthetic
fiber products developed in the last decades and the diversity of mar-
kets and applications of these products have made the plastics and syn-
thetic fibers industry the largest consumer of organic chemicals on a
volume basis.
Coal derived chemicals were the principal feedstocks of the early indus-
try (though ethanol, derived from fermentation, served as a source of
some aliphatic compounds). The growth in the markets for organic chem-
icals and plastics and synthetic fibers led, in time, however to changes
in the source of feedstocks for the industry. By World War II, the mod-
ern organic chemicals and plastics and synthetic materials industry
based on petrochemicals was firmly established in the United States.
Today the industry is comprised of production facilities of two distinct
types: those facilities whose primary function is chemical synthesis
and plants that recover organic chemicals as a by-product from unrelated
manufacturing operations such as steel production. The bulk of the in-
dustry is comprised of plants in the former category: plants that
11
-------
process chemical raw materials into a wide variety of products that per-
meate virtually every industrial and consumer market. Approximately 90%
of the precursors, which are the primary feedstocks for all of the in-
dustry's thousands of products, are derived from petroleum and natural
gas. The remaining 10% is supplied by plants that recover organic chem-
icals from coal tar condensates generated by coke production.
The apparent complexity and diversity of the organic chemical manufac-
turing industry can be simplified by recognizing that approximately
2,500 distinct chemical products are synthesized from only seven parent
compoundsmethane, ethylene, propylene, butane/butenes, benzene, tol-
uene, and o,p-xylenes. These seven compounds are processed into deriva-
tives which in turn are marketed or used as feedstocks for the synthesis
of other derivatives. However, the product line of the industry is very
complex with approximately 1,200 products that are produced in excess of
one thousand pounds per year, and probably several thousand more that
are produced in lesser quantities. Because these products are produced
by one or more manufacturers using different synthetic routes, few
plants are exactly alike in terms of either product or processes.
The early chemical industry used an assortment of general purpose equip-
ment and operated very labor intensive batch processes that required
relatively little capital investment. As the demand grew, around the
time of World War II, the chemical production shifted to large scale
continuous processing units because of technological improvement and
also because of the economies of scale associated with large production
facilities. This changed the industry to a high-capital-intensive, low-
labor basis.
Although there is still a large number of small organics producers util-
izing batch processes, these producers are usually dedicated to the man-
ufacture of fairly small volumes of high-priced specialty products which
may contribute substantially to the total value of organic chemical pro-
duction, but is only a small portion of chemical production volume.
Since organic chemicals are produced both by large manufacturing com-
plexes made up of continuous major processing units and by smaller batch
process plants producing many different products, there is a wide varia-
bility of products and process units from one complex to another with
treatment facilities typically servicing the complex rather than the in-
dividual process units. Among the hundreds of products made by the in-
dustry, there are derivative and coproduct relationships that result in
groups of products commonly being made together.
DEFINITION OF THE INDUSTRY
It is difficult to profile the organic chemicals and plastics and syn-
thetic fibers industries due to their complexity and diversity. How-
ever, traditional profiles can provide useful descriptions of the chem-
ical industry. The following profile factors are discussed briefly in
the ensuing subsections:
12
-------
Standard Industrial Classification System (SIC)
Production and Sales
Geographic Location
Size of Plant
Age of Plant
Standard Industrial Classification System
One industrial profile commonly employed for collection of economic data
for manufacturing industries is the Standard Industrial Classification
(SIC) System. The organic chemicals and plastics and synthetic mater-
ials industrial categories are nominally described under SIC 2865 and
2869 for organic chemicals, and SIC 2821, 2823, and 282A for plastics
and synthetic materials. SIC codes as established by the U. S. Depart-
ment of Commerce are "classifications of establishments by type of
activity in which they are engaged." Each plant is "assigned an indus-
try code on the basis of its primary activity which is determined by its
principal product or group of products." However, as a practical mat-
ter, many plants can also have secondary, tertiary, or subsequent order
SIC codes assigned to classify those activities in which they engage be-
yond their primary activities. Thus the inclusion of establishments
with one of these SIC codes as primary, secondary, or subsequent classi-
fication would provide an all inclusive listing of establishments pro-
ducing organic chemicals including such operations as steel mills, which
are not intended to be controlled under the organic chemical industry
guidelines. This classification system is oriented towards the collec-
tion of economic data related to gross production, sales, number of
employees and geographic location.
Production and Sales
Estimates of the production volume and sales for the OCPS industry were
made using the 1981 U. S. Department of Commerce statistics and are
shown in Table 3-1. These estimates of production and sales include
secondary as well as primary production. Primary products are those
materials that comprise the largest portion of a facility's total pro-
duction. Secondary production involves those products manufactured in
smaller volumes as co-products, by-products or as raw materials for pri-
mary products. Therefore, these estimates reflect some double counting
since certain secondary products are derived from products also included
in the total (e.g., ethylene dichloride is included as well as the eth-
ylene from which it is produced). Furthermore, the ITC presents statis-
tics on products or groups of products within a specific use category.
These use categories can contain products from more than one SIC code.
Where possible, adjustments were made to exclude products not
applicable.
The production volumes of the 29 organic chemicals included in the Chem-
ical and Engineering News' 1980 Top 50 List of Chemicals are listed in
Table 3-2. The total volume of production for these 29 organic com-
pounds was 78.75 million kkg (173.66 billion lbs) or 60 percent of all
organic chemicals productions (as shown in Table 3-1). Table 3-3 gives
the production volumes of the "top" products in the plastics and syn-
thetic fibers categories.
13
-------
TABLE 3-1
ANNUAL PRODUCTION AND SALES BY SIC CODE
SIC Production Sales
CODE (million kkg) (billion dollars)
Organic
Chemicals
Plastics and
Synthetic
Materials
TOTAL
2865 132 11.0
2869 43.2
2821 27 16.1
2823 1.2
2824 8.7
159 80.2
SOURCE: U. S. Department of Commerce, 1981.
14
-------
TABLE 3-2
ANNUAL PRODUCTION VOLUME OF
ORGANIC CHEMICALS IN "TOP 50" LIST 1980
Production
Rank Chemical (million kkg)
6
Ethylene
12.50
13
Urea
6.51
14
Propylene
6.22
15
Toluene
5.12
16
Benzene
4.98
17
Ethylene dichloride
4.53
18
Ethylbenzene
3.45
20
Methanol
3.18
21
Styrene
3.13
22
Vinyl chloride
2.93
23
Xylene
2.91
24
Terephthalic acid
2.69
25
Formaldehyde
2.62
27
Ethylene oxide
2.25
28
Ethylene glycol
1.92
30
p-Xylene
1.74
31
Cumene
1.43
32
Butadiene (1,3-)
1.31
33
Acetic acid
1.28
36
Phenol
1.12
38
Acetone
0.96
39
Cyclohexane
0.89
41
Vinyl acetate
0.87
42
Acrylonitrile
0.83
43
Isopropyl alcohol
0.81
44
Propylene oxide
0.80
46
Acetic anhydride
0.67
49
Ethanol
0.55
50
Adipic acid
0.55
TOTAL
78.75
SOURCE: Chemical and Engineering News 1981
15
-------
TABLE 3-3
ANNUAL PRODUCTION VOLUME OF PLASTICS AND SYNTHETIC FIBERS
1980
Production
Thermosetting resins
Phenolic and other tar acid resins 0.68
Polyesters (unsaturated) 0.41
Urea resins 0.53
Expoxies (unmodified) 0.15
Melamine resins 0.08
Thermoplastic resins
Low-density polyethylene 3.31
Polyvinyl chloride and copolymers 2.48
Polystyrene and copolymers 2.06
High-density polyethylene 2.00
Polypropylene and copolymers 1.66
Cellulosics
Rayon 0.22
Acetate 0.15
Noncellulosics
Polyester 1.81
Nylon 1.07
Glass fiber 0.39
Acrylic 0.35
Olefin 0.34
TOTAL 17.69
SOURCE: Chemical and Engineering News 1981
16
-------
Manufacturing Sites and Geographic Distribution of Industry
The number of plants operating under each of the five primary SIC codes
and classifications and the total number of organics and plastics and
synthetic materials plants are shown in Table 3-4. Table 3-5 presents
the distribution of these plants by state. It is not surprising that
most organic chemical plants are located in the coastal regions near
sources of raw materials. The plastics and synthetic materials indus-
tries generally follow this trend to minimize transportation costs of
monomer feedstock. However, a significant number of plastic plants are
situated near end product markets (i.e., large population centers) for
the same reason.
The first column in Table 3-4 utilizes Economic Information System data
which are based mainly on U. S. Department of Commerce statistics from
the Bureau of Census on Manufacturers. These statistics concentrate on
primary production facilities and estimates are used to predict the num-
ber of smaller facilities below certain employee levels. The second
column represents an estimate of all OCPS facilities which attempt to
take into account secondary production facilities. In estimating these
plant counts, a number of information sources were used, including:
1. Permit listings supplied by NEIC-Denver and EPA's Office of
Water Enforcement
2. 308 Questionnaire plant listings
3. EGD Telephone Survey of Plastics and Synthetic Materials
facilities
4. Plant listings from the economic contractor
5. Economic Information Service (EIS) plant listings
6. Plant listings from EPA's Permit Compliance System (PCS)
7. Dunn & Bradstreet
8. TSCA inventories
In compiling plants from the above listings, the number of direct dis-
charge plants was first obtained by cross-checking each of the available
data sources. Non-direct discharge plants were projected utilizing
ratios of non-direct to direct discharge plants from the 308 Question-
naire plant listings and the direct discharge plants as determined
above. SIC code information as well as 308 Questionnaire and Telephone
Survey data were used to group all plants into three broad industry seg-
ments: (1) plants manufacturing only organic chemicals, (2) plants man-
ufacturing only plastics and synthetic materials, and (3) plants manu-
facturing both organic chemicals and plastics and synthetic materials in
the same facility.
Except for EIS (which utilizes Census of Manufacturers statistics), each
of these information sources is independent of the others and provides a
17
-------
TABLE 3-4
OCPS PLANT DISTRIBUTION BY SIC CODE
Number of Projected Estimate of
Industry SIC Code Plants* Number of Plants
Organic Chemicals 2865 195 1045
Only 2869 457
Plastics and 2821 484 879
Synthetic Materials 2823 19
Only 2824 62
Organic Chemicals &
Plastics and Synthetic 176
Materials (Combined)
TOTAL 1217 2100
* SOURCE: Economic Information Service (1981)
18
-------
TABLE 3-5
PLANT DISTRIBUTION BY STATE
Organics Chemicals Plastics and Synthetic
Industry Fibers Industry
2865
SIC CODE
2969
Total
2821
SIC
2323
CODE
2324
Total
STATE
Alabama
4
5
9
7
1
2
10
Alaska
0
1
1
0
0
0
0
Arizona
0
1
1
1
0
0
1
Arkansas
1
3
4
5
0
1
6
California
6
30
36
45
0
1
46
Colorado
1
4
5
3
0
0
3
Connecticut
0
8
8
11
0
3
14
Delaware
1
5
6
12
0
1
13
Florida
3
6
9
7
0
2
9
Georgia
1
6
7
7
1
5
13
Hawaii
0
0
0
0
0
0
0
Idaho
0
0
0
0
0
0
0
Illinois
12
32
44
28
1
1
30
Indiana
4
4
8
7
1
1
9
Iowa
0
2
2
4
0
0
4
Kansas
2
3
5
1
0
0
1
Kentucky
2
8
10
5
0
0
5
Louis iana
3
33
36
10
0
0
10
Maine
0
0
0
1
0
0
1
Maryland
0
4
4
3
1
1
5
Massachusetts
7
14
21
32
0
2
34
Michign
3
16
19
16
1
0
17
Minnesota
1
3
4
3
0
0
3
Missouri
1
7
8
8
0
0
8
Mississippi
3
1
4
6
0
1
7
Montana
0
1
1
1
0
0
1
North Carolina
12
11
23
12
0
11
23
North Dakota
0
0
0
0
1
0
1
Nebraska
0
2
2
0
0
0
0
New Hampshire
1
2
3
4
0
0
4
New Jersey
48
67
115
60
1
1
62
New Mexico
0
1
1
0
0
0
0
Nevada
0
2
2
1
0
0
1
New York
10
27
37
24
1
1
26
19
-------
TABLE 3-5 (Continued)
PLANT DISTRIBUTION BY STATE
Organic Chemicals
Plastics and Synthetic
Industry
Fibers Industry
SIC CODE
SIC CODE
2865 2869 Total
2821 2323 2324 Total
STATE
Ohio
18
19
37
43
2
1
46
Oklahoma
0
2
2
5
0
0
5
Oregon
0
4
4
4
0
0
4
Pennsylvania
12
21
33
31
2
0
33
Puerto Rico
3
9
12
4
0
3
7
Rhode Island
5
6
11
1
0
0
1
South Carolina
10
9
19
5
1
15
21
South Dakota
0
0
0
0
0
0
0
Tennessee
1
5
6
7
2
4
13
Texas
17
57
74
35
0
0
35
Utah
1
0
1
2
0
0
2
Virginia
1
4
5
5
2
7
14
Vermont
0
0
0
1
0
0
1
Washington
2
4
6
5
1
0
6
Wisconsin
0
6
6
9
0
0
9
West Virginia
1
11
12
7
0
1
8
Wyoming
J_
0
J_
0
0
0
0
TOTAL
198
466
664
488
19
65
572
SOURCE: Continental United States (EIS 1981); Puerto Rico
(Bureau of the Census 1977)
20
-------
fairly accurate estimate of both primary and secondary production
facilities.
Plant Size
Sales volume, number of employees, area of plant site, plant capacity
(design or "nameplate" capacity) and production rate are factors that
logically would be considered to define plant size. However, none of
these completely describes plant size in a manner satisfactory for all
purposes. Each of these definitions are discussed below.
Often, number of workers employed will be used as an indication of the
relative size of a facililty. However, continuous plants producing com-
modity (i.e., high volume) chemicals typically employ fewer workers per
unit of production than do plants producing specialty (i.e., relatively
low volume) chemicals. Also, the area of a plant site can be very mis-
leading when considering it for determining plant size. Some plants are
built on enormous lots of land but only take up a small portion of that
land, while other plants may utilize the entire lot. Sales volume does
not accurately define plant size since it is totally dependent on the
demand, for certain products or the demand for goods produced from those
chemical products. Demand may then be dependent on prices and the econ-
omy, with sales volume fluctuating because of outside variables, and
therefore not relating to a plant or its size.
Table 3-6 and Figure 3-1 present the plant distribution of the organic
chemicals and plastics and synthetic materials industries based upon
number of employees. Table 3-7 and Figure 3-2 present plant distribu-
tion based on sales volume.
For the purposes of this report, plant size cannot be sufficiently de-
fined based on plant or design capacity due to the often broad differ-
ences between a plant's design capacity or rate and its average produc-
tion rate per year. Therefore, plant size for this evaluation is best
described by the average production (lbs/day) while operating, as re-
ported in the 308 Questionnaire. Production data on an industry-wide
basis is not available. However, a summary and analysis of the 308 pro-
duction data is presented in Section IV.
Plant Age
Plant age within the organic chemicals and plastics and synthetic mate-
rials industries is difficult to define since such plants evolve over
extended periods of time by additions of product/processes, increases in
production rates or changes in technology for the existing product
lines. Because new products are continually being introduced by the
industry, process units are added to satisfy a growing product demand.
Plant age is problematic at such plants, i.e., which process should be
chosen to define plant age? Typically, the oldest process in current
operation is used to define plant age. Information concerning plant age
is not available in the literature and has been compiled from the 308
data base. Table 3-8 and Figure 3-3 illustrate the age (as defined
above) of manufacturing facilities within these industries.
21
-------
TABLE 3-6
PLANT DISTRIBUTION BY EMPLOYMENT SIZE
Number of Number of Plastics
Organic Chemicals and Synthetic
Plants Fibers Plants
Number of
Employees
SIC
2865
CODE
2869
2821
SIC CODE
2323
2824
20-49
77
181
184
4
7
50-99
45
96
107
4
6
100-249
38
79
101
0
9
250-499
23
53
45
1
8
500-999
9
28
30
5
7
1000-2499
3
14
16
3
17
2500-9999
0
6
1
2
8
SOURCE: EIS 1981
22
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PLANT DISTRIBUTION BY NUMBER OF EMPLOYEES
300 n
200-
Number
The Organic Chemicals Industry
Plants
100-
The Plastics/Synthetic
-.^Fibers Industry
100
Number of Employees
1000
10,000
FIGURE 3-1
23
-------
TABLE 3-7
PLANT DISTRIBUTION BY SALES VOLUME
Number of Plants
Sales (million dollars) Organic Plastics
1-10
217
287
10-20
137
86
20-30
76
53
30-40
42
29
40-50
28
14
50-60
17
13
60-70
20
8
70-80
19
5
80-90
11
6
90-100
9
6
100-110
7
5
110-120
8
4
120-130
5
4
130-140
9
4
140-150
2
3
150-160
2
2
160-170
4
3
2
1
3
170-180
4
180-190
3
190-200
2
200-210
1
210-220
1
220-230
2
_
230-240
1
1
240-250
2
4
250-260
1
260-270
3
1
270-280
-
2
280-290
-
2
290-300
1
2
300-310
-
310-320
2
2
320-330
2
330-340
1
-
340-350
1
350-360
1
1
360-370
-
2
370-380
-
-
380-390
1
-
390-400
-
-
24
-------
TABLE 3-7 (Continued)
PLANT DISTRIBUTION BY SALES VOLUME
Number of Plants
Sales (million dollars) Organic Plastics
400-410
1 1
410-420
1 3
450-460
1
470-480
1 -
480-490
1
580-590
1 -
640-650
1
670-680
1 -
690-700
1
730-740
1
780-790
1 -
920-930
1 -
1240-1250
1
1850-1860
1 -
25
-------
PLANT DISTRIBUTION BY SALES VOLUME
300-1
The Plastics/Synthetics Fibers Industry
Number
Plants
100-
The Organic Chemicals Industry
1
10
1000
100
Sales Volume (millions of dollars)
FIGURE 3-2
26
-------
TABLE 3-8
DISTRIBUTION BY AGE OF ORGANIC CHEMICALS
AND PLASTICS AND SYNTHETIC MATERIALS PLANTS
Age in Years Number of Plants
0-5 18
6-10 44
11-15 61
16-20 53
21-25 44
26-30 22
31-35 17
36-40 11
41-45 5
46-50 2
51-55 3
56-60 1
61-65 1
TOTAL 282
27
-------
DISTRIBUTION BY AGE OF ORGANIC CHEMICALS AND
PLASTICS/SYNTHETIC FIBERS PLANTS
Number
of
Plants
40-
30
20-
10-
i
10
20 30
Plant Age (years)
40
FIGURE 3-3
28
-------
PRODUCT/PROCESS DESCRIPTION
Synthetic organic chemicals are derived from petroleum, natural gas, and
coal by some type of chemical reaction (e.g., oxidation, hydrogenation,
halogenation, alkylation). The chemical process and its variations can
produce an enormous number of potential organic products from a simple
list of starting materials.
Petrochemicals are the major raw materials used to produce many organic
products. Five major sources (methane, ethylene, propylene, and higher
aliphatics and aromatics) are utilized in organic chemical produc-
tion.[3-1] This list is extended when such aromatics as benzene, tol-
uene, and xylenes used for manufacture are included. A small number of
these aromatics are derived from coal, but most raw materials evolve
from petroleum and natural gas. In fact, 90 percent (by weight) of all
organics are derived from these latter two sources.[3-2] Other raw ma-
terials are derived from coal and some naturally occurring renewable
sources, notably fats, oils, and carbohydrates. Obscure natural prod-
ucts used as raw materials contribute to specialty chemical production
within the organics industry.
Methane, one of the seven basic raw materials, is one of the least com-
plex of the organic chemicals. Even using this simple compound, how-
ever, a series of increasingly complex chemicals can be made (see Figure
3-4).
As the chemical complexity of a raw material increases, the variety and
number of potential products and chemical intermediates tend to increase
also (see Figures 3-5 through 3-8 for the products and intermediates
from the raw materials ethylene, propylene, hydrocarbons and higher
aliphatics, and the aromatics). Most of the organic chemicals and plas-
tics and synthetics produced in the U. S. are derived from relatively
few basic raw materials, which come almost entirely from petroleum and
natural gas.
Even though a portion of the raw materials is derived from other sources
(such as coal), these materials are subjected to similar chemical mani-
pulations and appear in the same series of intermediates and products.
Delineation between raw materials and products is difficult to determine
at best, since the product from one manufacturer can be the raw material
for another manufacturer. This lack of distinction is more pronounced
as the process series approaches the ultimate end product, which is nor-
mally the fabrication or consumer stage. Also, many products/intermedi-
ates can be made from more than one raw material (a specific example of
this is acetone which is produced from such raw materials as propylene,
C, hydrocarbons, and aromatics). Frequently, there are alternate proc-
esses by which a product can be made from the same basic raw material.
Another characteristic which makes profiling the OCPS industry by raw
material, process, or product difficult is the high degree of integra-
tion in the manufacturing units. Since the bulk of the basic raw ma-
terials are derived from petroleum or natural gas, many of the organic
chemical manufacturing plants are incorporated into petroleum refiner-
29
-------
METHANE
SYNTHESIS CAS
CHLORINATED
METHANES
HCN
ACETYLENE
AMMONIA OXO METHANOL ADIPONITRILE
CHEMICALS
AMMONIUM
SALTS
UREA
ACHYLONITRILE
ACETONE
CYANOHYORIN
METHYL
AMINES
OMT
fORMALOEHYOE
METHYL
CHLORIOE
METHYL
METHACRYLATES
U>
O
RESINS
SILICONES VINYL
CHLORIOE
CS2
CCI,
ELUOROCARBONS
CELLULOSE
FROOUCTS
VINYL
ACETATE
NEOPRENE
CHLORINATED
ETHYLENE
ACRYLIC
ACI04 ESTERS
FROM: Riegel's Handbook of Industrial Chemistry, Seventh Edition, by James A. Kent;
Copyright (c) 1974 by Van Nostrand Reinhold Company. Reprinted by permission of the
publisher.
FIGURE 3-4 - SOME PRODUCTS DERIVED FROM METHANE
-------
ETHYLENE
I
ETHANOL
I
ACETALOEHYOE
ETHYl
AMINES
ETHYL
BROMIDE
I
CHLORAL
ethyl
ETHER
ETHYL BENZENE
&
ETHYLTOLUENE
I
SEE AROMATICS
ETHYL
CHLORIOE
ETHYLENE
DIBROMIOE
ETHYLENE
OICHLORlOE
TETRAETHYL
LEAO
ETHYL
CELLULOSE
I
ACETALDOL
I ETHYL
HEXANOl
ACETIC ACIO
ป ANHYORIDE
PENTAERY-
TMRITOl
I
DOT
] BUTYIENE
GLYCOL
CROTON
AlOEHYOE
ACETATE
ESTERS
ACETYL
CHLORIDE
ACETANILIOE
VINYL
ACETATE
ASPIRIN
00
CELLULOSE
ACETATE
MISCELLANEOUS
DERIVATIVES
PERACETIC ACIO
PARALOEHYOE
PYAIOINE
TRIMETHYLOl
PROPANE
ETHYLENE
AMINES
VINYL
CHLORIOE
1.1.2 TRICHLORO
ETHANE
ETHANE
METHYL
CHLOROFORM
r-1
PENTACHLORO
ETHANE
I
PERCHLORO
ETHYLENE
TETRACHLORO
ETHANE
I
TRICHLORO
ETHYLENE
VINYLIOENE
CHLORIOE
I
methyl
CHLOROFORM
POLYVINYL
ALCOHOL
CHLOROACETIC
ACIOS
I
POLYETHYLENE
LOW
DENSITY
I
HIGH
OENSITY
PROPYLENE
I
COPOLYMERS
ETHYL
ACETATE
1
VINYL
ACETATE
PROPION ALOEHYOE
I
PROPIONIC ACIO
ETHYLENE OXIOE
ETHYLENE
GLYCOL
POIYETHYLENE
GLYCOLS
ETHOXYLATEO
SURFACTANTS
GLYCOL
ETHERS
I
ETHANOLAMINES
HYOROXY ETHYL
CELLULOSE
I
POLYESTERS
I
OIOXANE
ETHYLENE
CARBONATE
GLYOXAl
OIOXOLANES
FROM: Riegel's Handbook of Industrial Chemistry. Seventh Edition, by James A. Kent;
Copyright (c) 1974 by Van Nostrand Reinhold Company. Reprinted by permission of the
publisher.
FIGURE 3-5 - SOME PRODUCTS DERIVFD FROM ETHYLENE
-------
PROPYLENE
POLYPROPYLENE
ISOPROPANOL CUMENE
W
N5
NONYL
PHENOL
NONENE ACETONE PHENOL
ฆ
ISOOECYL
ALCOHOL
ACROLEIN ALLYL
CHLORIDE
OODECENE
ALLYL PROPYLENE
ALCOHOL OXIDE
GLYCERINE
ACRYLONITRILE
POLYMERS
GLYCOL
ETHERS
HEPTENE
BUTYRALDEHYOES
OOOECYL BUTANOL
BENZENE
ISO OCTYL
ALCOHOL
POLYGLYCOLS
ETHYL
HEXANOL
ALKANOLAMINES
FROM: Riegel's Handbook of Industrial Chemistry, Seventh Edition, by James A. Kent;
Copyright (c) 1974 by Van Nostrand Reinhold Company. Reprinted by permission of the
publisher.
FIGURE 3-6 -SOME PRODUCTS DERIVED FROM PROPYLENE
-------
PfTAOtiUM
ACflAlOCHYOE
SU SU1AN01
HYonopfiioxtoe
UK
MIX
NBA
I-IUTVI
AlCOHOl
PfNIAERYTHRITOL
EIMYlMEXANOl
ACEliC
fOKMMD(HYOC
CC11U LOSE
ACHAT!
rftOFROfHC AClO
POLYBUTAOlENt
MAlllC
ANHYDRIOE
AMYi
AlCOHOLS
ISOOCTYl
ALCOHOi
POLYBUTENES
iBUTYL
UTYLINE
OXIOE
lS06UlYtCซES
PARAFFIN WAXtS
Oxidation
LINEAR StCONOANY
HICHEN ALCOHOLS
am vi
ALCOHOLS
AMVl
CYCLO PEMTAOfENE
tMSICllCIOES
FROM: Riegel's Handbook of Industrial Chemistry, Seventh Edition, by James A. Kent;
Copyright (c) 1974 by Van Nostrand Reinhold Company. Reprinted by permission of the
publisher.
FIGURE 3-7 - SOME PRODUCTS DERIVED FROM C4 AND HIGHER ALIPHATICS
-------
Co
-ts
tlmi
KUlini
HAttlC
ANHlDRIOf
I
C (KMC
J
r
ACETONf
HtNc'tut
sui.ro.i4TC
Gt(.OKi'acit;EN(
J
OCTCKCCNT
ALKTLATC
ClClOHflANt
I
X*tfhฃ5
ISOPllfHAlIC
ACID
PhTHAIIC J-KAPuThOI
AWllOfilM
URCPhTMAUC
ACID
OiCHLOKOTIXUฃn(
PmฃnOl
l_
SALICYLIC
ACIO
ULCIl PltCNOlS
CYClOH(lAhOt
FROM: Riegel's Handbook of Industrial Chemistry, Seventh Edition, by James A. Kent;
Copyright (c) 1974 by Van Nostrand Reinhold Company. Reprinted by permission of the
publisher.
FIGURE 3-8 - SOME PRODUCTS DERIVED FROM AROMATICS
-------
ies, and may produce to almost any point in a process from any or all of
the basic raw materials. Normally, relatively few organic chemicals
manufacturing facilities are single product/process plants unless the
final product is near the fabrication or consumer product stage.
This generalized configuration, of which the bulk of the organics indus-
try is comprised, is commonly referred to as a petrochemical complex.
Processing arrangements within petrochemical complexes can be quite sim-
ilar on a worldwide basis since a variety of raw materials, intermedi-
ates or finished products is relatively common in the larger scale man-
ufacturing facilities. Furthermore, several processing units are char-
acteristically integrated in such a fashion that the relative amounts of
products can be varied as desired over wide ranges.
The capacity of individual plants can change over time. Plants are of-
ten modified to produce other products, increase capacity, or produce
the same product by a different synthesis route. Some plants or compa-
nies exhibit a pronounced degree of vertical integration, while other
plants or companies may only produce a limited number of products from
one basic chemical raw material. Plant capacities are highly variable
even among those plants that use the same unit process to produce the
same product.
Wastewater Generation
i iii r
Chemical and plastics manufacturing plants share an important character-
istic: chemical processes never convert 100 percent of the feed stocks
to the desired products, since the chemical reactions/processes never
proceed to total completion. Moreover, because there are generally a
variety of reaction pathways available to reactants, undesirable by-
products are often generated. This produces a mixture of unreacted raw
materials, products and by-products that must be separated and recovered
by operations that generate residues with little or no commercial value.
These losses appear in process wastewater, in air emissions, or directly
as chemical wastes. The specific chemicals that appear as losses are
determined by the feedstock and the process chemistry imposed upon it.
The different combinations of products and production processes distin-
guish the wastewater characteristics of one plant from that of another.
I
Plastic Plants vs. Non-Plastic Plants
In contrast to organic chemicals, plastics and synthetic fibers are pol-
ymeric products. Their manufacture directly utilizes only a small sub-
set of either the chemicals manufactured or processes used within the
Organic Chemical Industry. Such products are manufactured by polymeri-
zation processes in which organic chemicals (monomers) react to form
macromolecules or polymers, composed of thousands of monomer units.
Reaction conditions are designed to drive the polymerization as far to
completion as practical and to recover unreacted monomer. Unless a sol~
vent is used in the polymerization, by-products of polymeric product
manufactures are usually restricted to the monomer(s) or to oligomers (a
polymer consisting of only a few monomer units). Because the mild reac-
tion conditions generate few by-products, there is economic incentive to
recover the monomer(s) and oligomers for recycle. The principal yield
35
-------
loss is typically scrap polymer. Thus, smaller amounts of fewer organ-
ics chemical co-products (pollutants) are generated by the production of
polymeric plastics and synthetic fibers, than are generated by the manu-
facture of the monomers and other organic chemicals. A logical first
subcategorization step is to separate production of plastics from all
other production processes. The subcategorization of the remaining or-
ganics and mixed plastics-organics processes is evaluated below.
Generic Processes and Product/Processes
Despite the differences between individual chemical production plants,
all transform one chemical to another by chemical reactions and physical
processes. Though each transformation represents at least one chemical
reaction, production of virtually all the industry's products can be de-
scribed by one or more of 41 generalized chemical reactions/processes
shown in Table 3-9. Subjecting the basic feedstocks to sequences of
these 41 generic processes produces all the commercial organic chemicals
and plastics.
Each chemical product may be made by one or more combinations of raw
feedstock and generic process sequences. Specification of the sequence
of product synthesis by identification of the products and the generic
process by which it is produced is called a "product/process." There
are thousands of product/processes within these industries. Data gath-
ered on the nature and quantity of pollutants associated with the manu-
facture of specific products within the Organic Chemicals and Plastics/
Synthetic Fibers Industries have been indexed by product/process.
Thus, while the industry may be examined on the basis of a plant's capa-
city, age, size, location, or number of employees, it is the mixture of
products and the processes by which they are made that distinguishes the
wastewater characteristics of one plant from that of another. Product/
processes are a fundamental descriptor by which data concerning the na-
ture and quantity of pollutants associated with the manufacture of spe-
cific products have been gathered. There are, however, thousands of
industrial product/process combinations which would have to be evaluated
to define the pollutant discharge potential for the entire industry.
Evaluation of each for overall wastewater yield losses, to say nothing
of identifying the pollutant loadings in the plant effluent, is unneces-
sarily difficult and burdensome.
The premise of the generic approach is that a generic process once char-
acterized in one or more plants for generation of process wastes (yield
losses) can be extended to similar generic processes throughout the in-
dustry. Given that biological treatment is widely practiced by direct
dischargers (and ultimately by indirect dischargers as well), there is a
strong inference that pollutant loadings characteristic of generic pro-
cesses have similar treatabilities. The bulk of chemical processes em-
ployed commercially, moreover, can be limited to a number of generic
processes, and this procedure can serve as the basis for relatively sim-
ple characterization of the OCPS industry. The great advantage of a
generic approach, as applied to effluent regulation within the organic
chemicals and plastics and synthetic materials industries, is the struc
36
-------
TABLE 3-9
GENERIC CHEMICAL PROCESSES AND CODES
1. Oxidation (C)
26.
Sulfonation (M)
2. Peroxidation (8)
27.
Nitration (L)
3. Acid Cleavage (9)
28.
Hydrodealkylation (U)
4. Condensation (A)
29.
Pyrolysis (H)
5. Isomerization (22)
30.
Cracking (T)
6. Esterification (G)
31.
Distillation (2)
7. Hydroacetylation (13)
32.
Extractive Distillation (15)
8. Hydration (12)
33.
Extraction (16)
9. Alkoxylation (5)
34.
Crystallization/Distillation (17)
10. Hydrolysis (E)
35.
Fiber Production (23)
11. Carbonylation (0)
36.
Halogenation (B)
12. Hydrogenation (F)
37.
Oxyhalogenation (S)
13. Neutralization (24)
38.
Hydrohalogenation (P)
14. Amination (6)
39.
Dehydrohalogenation (R)
15. Ammonolysis (K)
40.
Chlorohydrination (20)
16. Oximation (10)
41.
Phosgenation (V)
17. Dehydration (Q)
18. Ammoxidation (N)
19. Electrohydrodimerization
(19)
20. Cyanation/Hydrocyanation
(7,18)
21. Epoxidation (21)
OTHER CLASSIFICATIONS
22. Etherification (14)
Non OCPS Product/Processes (3)
23. Polymerization (D)
Cannot Be Classified (2)
24. Alkylation (I)
25. Dehydrogenation (J)
37
-------
turing of existing data within a framework which allows extrapolation to
processes not explicitly evaluated.
The extent to which process yield losses can be correlated with generic
process types depends on the ability to evaluate the chemical reaction
system. The evaluation must include a full consideration of the process
chemistry with a wide range of feedstocks and reaction conditions. Some
of the fundamental concepts of this procedure are presented in the fol-
lowing discussion.
Manufacture of a chemical product necessarily consists of three steps:
(1) combination of reactants, under suitable conditions, to yield the
desired product, (2) separation of the product from the reaction matrix
(e.g., by-products, co-products, reaction solvent), and (3) final puri-
fication of the product. Among the basic concepts that can be employed
to limit the scope of pollutants expected from a plant are: (1) conser-
vation of mass, (2) principles of thermodynamics, and (3) kinetic or
mechanistic analyses.
In general, chemical species do not react via a single reaction pathway.
Depending on the nature of the reactive intermediate, there are a vari-
ety of pathways which lead to a series of reaction products. Often, and
certainly the case for reactions of industrial significance, one pathway
may be greatly favored over all others, but never to total exclusion.
Thus, by appropriate process design and proper control of reaction con-
ditions, product yield is maximized. There are two fundamental sources
of pollutants within a process: pollutants formed as the result of al-
ternate reaction pathways; and reaction, by either the main or alternate
reaction pathways, of impurities present in feedstocks. With regard to
the latter, it is important to realize that even though feedstock impur-
ities may be inert under a given set of reaction conditions, the direct
discharge of such impurities to the environment may still represent a
significant pollution potential.
Potentially, an extremely wide variety of compounds could form within a
given process. The formation of expected products from known reactants
is controlled thermodynamically while the rate at which such transfor-
mations occur depends upon the existence of suitable reaction pathways.
Detailed thermodynamic calculations are of limited value in predicting
the entire spectrum of products produced in a process. Both the iden-
tity of true reacting species and the assumption of equilibrium between
reacting species are often speculative. Also, kinetic data concerning
minor side reactions are generally unavailable. Thus, neither thermo-
dynamic nor kinetic analyses alone can be used for absolute prediction
of pollutant formation. However, these analyses do provide a framework
within which pollutant loadings may be considered and generalized.
The direction of reactions in a process sequence is controlled through
careful adjustment and maintenance of conditions in the reaction vessel.
The physical condition of species present (liquid, solid, or gaseous
phase), conditions of temperature and pressure, the presence of solvents
and catalysts, and the configuration of process equipment dictate the
kinetic pathway by which a particular reaction will proceed. From this
38
-------
knowledge it is possible to identify reactive intermediates and thus an-
ticipate species (potential pollutants) formed.
To produce a complete and valid descriptor using the generic methodol-
ogy, the initial feedstock and each generic process used to produce a
final product must be specified. For commodity chemicals, generally it
is sufficient to specify a feedstock and a single generic process. Ni-
tration of benzene to produce nitrobenzene, for example, is sufficient
description to predict composition of process wastewaters: nitrophenols
will be the principal process wastewater constituents. Other compounds,
however, may involve several chemical reactions and require a fuller
description. For example, acetic acid and its anhydride can be produced
by first manufacturing acetaldehyde by the hydration of acetelene, fol-
lowed by the oxidation of acetaldehyde to acetic acid and acetic
anhydride.
This example is relatively simple and manufacture of speciality chemi-
cals is more complex. Thus, as individual chemicals become further re-
moved from the basic feedstocks of the industry, fuller description is
required for unique specification of process wastewaters. Limited plant
data, however, were available by which to assign generic processes to a
product, and in many cases the product was specified while the feedstock
was not.
In such cases a generic process assignment was made on the basis of
process chemistry and engineering, i.e., judgment was made as to the
feedstock and chemistry employed at the plant. In no case, however, was
more than one generic process assigned to a given product within a pro-
duction line.
Appendix A presents the product/process frequency counts for the 308
Summary Data Base for direct dischargers, and zero dischargers and al-
ternative disposal plants by each of the 41 generic product/processes.
DATA BASE PROFILE
Introduction
Despite the wide range of plant sizes, the diversity of plant specific
product/processes, and the dynamic nature of technological innovations
and market conditions, the OCPS industry is characterized using the
latest available data from the industry and published sources.
Most of the data used for the engineering analysis in this report are
extracted from the industry responses to the 1976 BPT questionnaire and
the subsequent 1977 BAT questionnaire. The data from these question-
naires were transcribed on a plant-by-plant basis to a computer tape.
The transcribed data for each plant were then computer printed and the
individual data were submitted from December 1979 to January 1980 to the
plants for review and comments. Also, long-term daily pollutant raw
waste and final effluent data were collected and transcribed to the com-
puter at this time.
39
-------
Additionally, some qualitative information on the generation of waste-
water and mode of discharge at 301 plastics manufacturing facilities was
obtained by a supplemental telephone survey. It was also determined
whether these plants produced resins and polymers which should be in-
cluded in the data bases or whether the operations were limited to ex-
trusion and/or fabrication of plastics.
The data sources included in this analysis are as follows:
1. The Telephone Survey data from the 301 plastic manufacturing
plants, 251 of which were not covered in the 308 Data Base. This survey
consistently determined the mode of discharge (direct, indirect, zero),
location, and general product type. Thirty seven of the plants con-
tacted were identifiable as extruding or otherwise fabricating plastics
from purchased polymers. At the present time, the data from these 37
plants are included only in the mode of discharge portion of the data
bases.
2. The daily data from plants contained in the 308 Data Base. A
following subsection details the decisions involved in the selection of
the plants included in the long-term Daily Data Base.
3. The original 308 data tape was used as the basis for the cur-
rent specialized data bases. The following subsection describes the
changes made to the original data and the parameters and terms used to
profile the data.
The 308 Questionnaire was designed to collect information that would
adequately describe and characterize the OCPS industry. Requested
information related to such items as products manufactured, processes
used, production rates, age, size, water consumption, wastewater gen-
eration, treatment technologies employed, and influent and effluent
characteristics.
The responses varied in respect to completeness of response and detail
of information. Some plants misinterpreted the units requested, did not
give complete responses, provided data in units other than those re-
quested, or otherwise responded in a manner which required either recal-
culation of the data, follow-up contacts for clarification, or in some
cases rejection of the data. This may be explained in part by the fact
that some companies simply did not keep records of information as was
requested by the questionnaire, and consequently could not respond fully
on all items of interest.
The data acquired from the questionnaire were necessary to assure that
the industry was adequately described and to determine the need for sub-
categorization of the industry. Some specifics of the problems associ-
ated with the raw data and the corrective steps required for clarifica-
tion are discussed in the following sections of this report.
The names applied to the data bases used in this report and a brief
description of their contents are shown in Table 310 and Figure 39.
These data base names will be used where the data bases are referred to
in the text of this report.
40
-------
TABLE 3-10
DATA BASE DESIGNATION
Data Base File Name
Description
308 Data Base
Original data base containing
all data extracted from 308
Questionnaires
Dally Data Base
Contains long-term influent &
effluent data from 50 plants
Summary Data Base
Updated version of 308 data
base covering the 291 direct
& zero discharge plants
41
-------
(see note 1)
308
DATA
BASE
-(see note 2)
Hi
r-~* ST-'iKl..* - 'V T-- + * * ฆ
t-
:vsummary; *'>
-;-V DATA . ;-
:''?> 'ฆฆ- ป- r"'- J*
(see note 3)
Nc"*v. ;*
TELEPHONE
SURVEY
I
(see note 4)
NOTES:
(1) 308 Data Base contains Information on 566 plants
(2) Daily Data Base contains information on 50 plants
(3) Summary Data Base contains information of 291 plants
(4) Telephone Survey Data Base contains information on 301 plants
FIGURE 3-9 - DATA OVERLAPS
42
-------
In addition to the above data bases, there are numerous files of data
that have been generated and stored in the computer to allow segregation
and manipulation of special or selected data. These files contain such
data as plant numbers, product/processes and treatment systems for indi-
rect discharge plants, and plants rejected from the direct discharge and
zero discharge (Summary) data base ("gray" plants) because the majority
of each plant's production was not associated with the OCPS industry.
Final Data Base Development
The Summary Data Base is a corrected and updated version of the original
data found in the 308 Data Base. Since this report covers only zero and
direct dischargers, the 343 plants shown in the 308 Data Base as using
those discharge modes were used as the initial list of plants for the
Summary Data Base. A review of the information in the files of the re-
maining 223 indirect dischargers (including the responses from 1979
mailing to industry for data update) indicated that another 35 plants
could no longer be classified as indirect dischargers. This brought the
number of plants to be used in the Summary Data Base to 378. This left
188 plants marked as indirect dischargers in the 308 Data Base.
Data on product/processes, plant location and age, production, percent
operating capacity, mode of discharge, treatment unit operations, influ-
ent and effluent wastewater flow and concentrations, age, and period of
data collection were obtained from the original data printouts for each
of the 378 plants in the total direct/zero discharge data base. The
file for each plant was examined and the data were modified to reflect
any corrections to the original data and to incorporate the plant's re-
sponses to the 1979 mailing. After these final corrections, the data
were placed in a System 2000 Data Base Mangement System (DBMS) on EPA's
UNIVAC Computers.
Examination of these data, however, pointed out problems which led to
the deletion of 87 of the plants from the initial Summary Data Base.
Forty-two of the deleted plants were rejected from the Summary Data Base
because they were found to be indirect dischargers whose status had
changed from direct or zero dischargers; eight of these indirect dis-
charge plants also utilize some type of zero discharge technique.
Eleven additional plants had data which were not representative of this
industry. These included plants which have since been shut down, plants
which have been sold or no longer make the products described in the BAT
mailing, and one plant whose influent includes a large and unquantifi-
able amount of municipal sewage. Thirty-four plants were rejected be-
cause their products do not fall under the SIC codes being studied.
These plants were divided into two groups. One group consists of 23
plants which clearly are not primarily in the SIC codes under study
(e.g., refineries, paper mills, tall oil plants, welding gas plants, and
plastics extrusion and compounding plants which do not polymerize on
site). The other group consists of plants which make organics, but
which are primarily inorganic plants. These plants typically have only
one treatment system for all plant operations, with the wastewater from
organics processes accounting for less than 10 percent of the total
43
-------
plant flow. This group of 11 rejected plants ("gray" plants) is segre-
gated from the other group and may be studied separately or later with
the rest of the organics industry. The final Summary Data Base, which
after rejection of these 87 plants contains data from 291 plants, was
entered into a System 2000 DBMS on the UNIVAC Computer.
The final Summary Data Base contains detailed information on 291 plants
which are direct dischargers or zero discharge/alternate disposal facil-
ities. They were selected from the 566 plant data base (308 Data Base)
for the reasons given previously. In addition to the 566 plants, some
information is available on 243 plants from the EGD Telephone Survey,
giving a total of 809 plants which are represented in some way in the
data bases. This means that about 67 percent of approximately 1200
plants (or 40 percent of approximately 2100 plants estimated to be in-
cluded in the OCPS industry by EPA) are directly covered in the combined
data base.
SIC Code Applicability - As a result of the complexity of many plants in
the chemical industry, several unrelated SIC codes may be applicable to
a single plant. Consequently, the boundaries of the OCPS and related
industries may not be sharply defined using SIC codes.
As a result there exists an overlapping of SIC code coverage in the Sum-
mary Data Base. Although the data included in the Summary Data Base are
for the OCPS industries, some plants which manufacture primarily other
materials, but also produce organic chemicals or plastics (e.g., produc-
tion of alkyd or urethane resins in paint plants and formaldehyde pro-
duction in adhesive plants), have been included in the Summary Data Base
where the relevant development document specifically left such produc-
tion for limitation by the OCPS regulations.
Additionally, where a separate wastewater treatment system exists for
the OCPS portion of a mixed product (SIC code) plant, that plant's data
were included in the Summary Data Base. Plants that specifically inclu-
ded manufacture of OCPS products in their regulations (petroleum refin-
ing, production of rosin resins in gum and wood chemicals, and pharma-
ceuticals) have been excluded from the Summary Data Base since this pro-
duction is already covered by those regulations. Figure 3-10 presents
these data base and industry guideline overlaps.
Stream/Plant Distinctions - The 291 plants in the Summary Data Base ac-
tually represent 377 different wastewater streams. A wastewater stream
in this context is defined as a discrete disposal method used for the
disposition of some of a plant's wastewater; dry processing and recyc-
ling of wastewater count as a stream each. For example, if a plant had
two wastewater streams going to one activated sludge system, three to
deep well injection, two processes which discharge wastewater untreated,
and two dry processes (i.e., processes which neither use nor generate
process contact water), it would be defined as having four waste
streams: activated sludge, deep well, no treatment, and dry processing.
However, if the two wastewater streams going to one activated sludge
system were instead going to two separate activated sludge systems and
had separate influent and effluent data for each, data for five streams
would exist: two with activated sludge, one with deep well injection,
44
-------
Fertilizers
(See Note 2)-
-------
one with no treatment, and one with dry processing. Separation of the
plant processes in this manner allows each process to be linked with the
influent and effluent of the treatment system to which it goes, rather
than simply be considered as a contribution to an overall plant average
loading.
Of these 377 streams, 212 are direct, 162 are zero or alternate disposal
and three are of unknown disposition. The majority of plants (225) have
only one discharge. The remaining 66 plants account for the other 152
waste streams. The tallies of plants and the associated streams are
given in Table 3-11.
Some of the tables in this report are presented in terms of plants, some
are presented in terms of streams, and some are presented in terms of
both. It should be noted whether the word "plant" or the word "stream"
appears in the title or content of each table.
Stream Combining - Early emphasis on the data evaluation was put on the
determination of overall plant wastewater treatment efficiencies and
effluent qualities. Since, by inspection of the 308 data, it was evi-
dent that biological treatment, especially activated sludge, was the
most prevalent method of treatment, these plants were the first exam-
ined. Where more than one treatment system existed at a plant, the data
over the systems were combined by calculating a total, composite influent
load and a total composite effluent load, and then the overall removal
of a given pollutant parameter achieved by the plant was calculated.
In subsequent data evaluation efforts required to demonstrate the effi-
ciency of a particular treatment technology, it became apparent that
this procedure of combining streams to arrive at an overall influent and
effluent loading over multiple treatment systems (including the "no
treatment" discharges) was not suited for the study of individual treat-
ment system performance because it led to gross over or under estimation
of the efficiency of a specific technology. For example combining the
characteristics of the effluent from a well operated biological treat-
ment plant with an untreated stream could mask the effectiveness of the
biological treatment plant.
To avoid the potential misrepresentation of treatment efficiencies,
stream combination was abandoned except for five plants which utilize
either dual biological or non-biological treatment. Each of these
plants have multiple treatment systems for which the data presented were
not detailed enough to allow separation of the data to evaluate the in-
dividual treatment system's performance. However, since the treatment
technologies employed at each of the plants are similar within the mul-
tiple treatment installation at that plant, it is judged that no sub-
stantial data errors are generated by combining the streams and using
the resultant data. For example, the data from a biological treatment
system are not being combined with the results from a non-biological
treatment system.
Finally, streams have been combined where product/processes could be
specifically allocated to each stream. For example, if a plant sends
its wastewater to north and south wastewater sewers without specifying
46
-------
TABLE
For AH Plants
Total Number of Plants
Number of Plants with One Stream
Number of Plants with Multiple
Streams
Number of Plants with Zero
Discharge Streams
Number of Plants with Direct
Discharge Streams
Number of Plants with Unknown
Discharge Streams
For Plants Of Any Number Of Streams
Total Number of Streams
Number of Direct Discharge
Streams
Number of Zero Discharge
Streams
Number of Unknown Discharge
Streams
FOR PLANTS WITH MULTIPLE STREAMS
Total Number of Streams
Number of Direct Discharge
Streams
Number of Zero Discharge
Streams
Number of Unknown Discharge
Streams
3-11 - PLANTS AND THEIR ASSOCIATED STREAMS
All Direct Discharge Zero Discharge Unknown Discharge
291 19S 94 2
225 156 67 2
ฃ6 19 27
127 33 94
195 195
3 3
377 251 124
212 212
162 38 124
3 1 2
152 95 57
56 56
95 38 57
11 - -
-------
which process has its wastewater sent to which sewer, and if both
streams are treated with oil/water separation, it was assumed that those
two separators had been combined.
Cooling Water - Often, effluent data for a plant is gathered after non-
contact cooling water is mixed with the effluent from the treatment sys-
tem. This dilution will decrease the apparent effluent concentration
from the treatment processes. To factor out the effects of this dilu-
tion, each plant's effluent flow was reduced by the amount of the cool-
ing water. The necessary assumption is that the total pounds of pollu-
tant discharged are due to the effluent from the treatment system and no
pollutants were contributed by the noncontact cooling water. If data on
the cooling water were available, they were used for back calculation
instead of assuming the water to be uncontaminated. The practice of re-
porting the plant effluent on the basis of total discharge (i.e., in-
cluding commingled noncontact cooling water) is very common in this in-
dustry since most state regulatory agencies require the information on
discharges to be based on total discharges and the quality thereof.
Of all the plants in the Summary Data Base, a total of 49 plants had
cooling water commingled with the treatment plant discharge, thus re-
quiring calculation to eliminate the diluting effects of the cooling
water.
The assumption of uncontaminated cooling water will result in slight
underestimates of treatment efficiency since the cooling water will not
actually be completely free of contamination. It will also result in
conservative (i.e., slightly high) estimates of effluent concentrations
from the treatment facilities. However, it should be noted that cooling
water can contribute relatively high TSS loadings, especially to the
typically low strength plastics and synthetic materials wastewaters. If
a cooling water stream was combined at the influent of a treatment sys-
tem after the influent sample point, a composite influent stream was
also developed as described above.
Offsite Treatment - One of the more confusing issues concerning the des-
ignation of treatment facility type was offsite treatment. Offsite
treatment refers to that method used by a plant which discharges its
wastewater to a privately or jointly owned treatment work. This des-
ignation was a source of confusion since some plants employing "offsite"
treatment were originally regarded as indirect dischargers. Subsequent
analysis determined that a plant discharging to a treatment work not
owned by a governmental entity would not be covered by pretreatment
standards for existing sources or pretreatment standards for new
sources, and therefore would be covered by this study.
The offsite treatment plants were first differentiated from the 22
plants which use contract removal. Contract removal was considered to
be removal in drums or trucks. Offsite-treated wastewater is defined as
being wastewater piped directly to the treatment system handling the
wastewater. Two more plants were removed because they had been pur-
chased by the plant treating the wastewater. The product/processes and
all other parameters associated with the purchased plants were combined
with those from the parent plant.
48
-------
After removing these two types of plants, there were still six plants
which pumped their wastes either to a jointly or a privately owned
treatment work. These six plants are described as utilizing offsite
treatment.
Generic Processes - In addition to cataloging the products at each plant
by product/process numbers, data was also sorted using generic chemical
processes. For this effort, a list of 41 major generic processes was
examined. General categories were also established for inorganic opera-
tions on organic chemicals, items which are called chemical processes
but which really are not (cooling tower blowdown, etc.), products for
which insufficient data exist to characterize the process, and products
outside the SIC codes of interest to this report. A list of the generic
codes used in the industry is shown in Table 3-9.
Each of the product/processes was then examined to determine its appro-
priate generic unit process. Where more than one generic process was
required to characterize any particular product/process, engineering
judgment was exercised to assign the step in the overall process most
likely to generate wastewater.
Possible Sources of Inaccuracy - As is the case whenever a large com-
pilation of diverse types of data are accumulated from a large number of
varying sources, there are potential sources of error both in the data
accumulated and in the interpretation of the data. Errors can arise
because of questionnaire ambiguities and technical misinterpretation by
the respondees. Some examples of these possible errors are:
1. The assumption that MGD was interpreted as million gallons per
day, a commonly recognized term used by people in the wastewater field.
However, in many responses "M" was interpreted as the Roman numeral for
thousand, a practice also fairly common in many fields of engineering
including those of the chemical industry.
2. Misinterpretation of treatment technology definition. This was
most evident in the lack of consistency in referring to treatment proc-
esses which have subtle differences such as aerobic lagoon vs. aerated
lagoon, the several options of activated sludge processes, and the use
of colloquial or "house" names for such technologies as tertiary la-
goons, polishing ponds and similar installations.
3. Failure of the respondents to fill in the questionnaire com-
pletely, or the submittal of conflicting or contradictory information.
To alleviate the effect of the possible errors, engineering judgments
and calculations were made to determine reasonable values based on the
data supplied, or follow-up contacts were made to plant personnel to
clarify the data in question.
A source of inaccuracy in the data is the reporting of identical influ-
ent and effluent flows. This is a very common practice in industry
where the effluent values for flow are reported, and for control of the
49
-------
waste treatment system influent flow is equated. Although this proce-
dure may create errors by not accounting for slight amounts of water
removed in the sludge, evaporation or other miscellaneous losses, the
discrepancies introduced by equating influent and effluent flows are of
more theoretical than practical interest and would be meaningful only
for the most highly sophisticated material balance studies.
Another possible source of error is the reporting of net pollutant val-
ues. The NPDES permits at some plants allow them to offset the pollu-
tant concentration of intake waters and allow them to report only the
increase in pollution due to the plant. Many plants have this kind of
permit and, since the 308 Questionnaire asked for pounds per day rather
than concentration of pollutants, therefore reported the net increase in
lbs/day used for their NPDES Discharge Monitoring Reports (DMRs) rather
than the total amount of discharge. Unless specifically stated as such
in the questionnaire response, plants reporting net BOD (or other param-
eter) discharges could be detected only where negative discharge loads
were reported. Where detected, the values for net reporting were ad-
justed to the gross value prior to entry in the Summary Data Base. One
plant (113) reported a negative value and three plants indicated the use
of net values.
An additional potential error source could lie in the lack of differen-
tiation between the filtered (soluble) BOD and unfiltered (total) BOD
values. The customary practice in industry is to report total BOD since
practially all reporting is normally done for permit purposes concerned
with the total pollutant discharged. A review of the Summary and Daily
Data Base plants showed only four plants which specified the method of
reporting or analyzing for BOD: one plant specified unfiltered BOD re-
sults, another plant reported four months filtered and the remainder
unfiltered, and two plants reported total BOD.
Another possible source of error in BOD values is the use of chlorina-
tion by some plants before the effluent sample point. Although there
may be some reduction in BOD due to chlorination, the main effect of
chlorination can be interference with the BOD test procedure. Residual
chlorine in the wastewater sample can inhibit the growth of the bacter-
ial seed used in the BOD test. This results in a BOD value lower than
the true oxygen demand of the pollutants contained in the sample. How-
ever, since the effect of chlorine on BOD determinations is well known,
the laboratory procedures (Standard Methods) employed in practically all
wastewater laboratories provide methods for the removal of the chlorine
before the BOD analyses are carried out. Examination of the data indi-
cates that the respondents followed standard analytical procedures in
BOD determinations.
The values for COD and TOC used in the Summary Data Base were collected
from the data provided in the 308 Questionnaire responses. The values
furnished could have been derived from laboratory determination,
BOD/COD/TOC ratios, or values taken from literature. Since any source
other than laboratory determinations or a properly derived and applied
statistical correlation of parameter ratios may lead to erroneous con-
clusions, every effort was made to exclude COD and/or TOC values which
could not be verified as being derived from acceptable procedures. Only
50
-------
one plant mentioned an empirical relationship but furnished no COD
values.
These sources of error, if ignored, could seriously affect the quality
of the data bases. Since these sources of error can and do exist in the
accumulated raw data, a diligent review of the 308 Questionnaires and
supplemental information was made in an effort to identify and either
reject or correct discrepancies. Only after this review was data incor-
porated into the Summary Data Base.
Daily Data Base Development
One of the major purposes of this study is the development of long-term
daily pollutant data. These data are required to derive variability
factors which characterize wastewater treatment performance and provide
the basis for derivation of proposed effluent limitations guidelines and
standards. Hundreds of thousands of data points have been collected,
analyzed, and entered into the computer.
The first effort at gathering daily data involved the BPT and BAT mail-
ings. These questionnaires asked each plant for backup information to
support the long-term pollutant values reported. Many plants submitted
influent and effluent daily observations covering the time period of in-
terest in the BPT questionnaire (January 1, 1976 to September 30, 1976).
Additionally, there were some other conventional and nonconventional
pollutant daily data in the files from the period of verification sam-
pling. Some plants also submitted additional data with their responses
to the 1979 mailing. Data from these three sources were examined and
interpreted.
Approximately 50 plants were identified as those routinely taking influ-
ent and effluent daily observations of parameters of interest. These
plants were contacted, and in many cases visited. The contacts usually
resulted in accumulation of long-term (sometimes six years) influent and
effluent data and detailed information on plant operations. Other data
were obtained from various EPA offices which provided long term daily
data for a total of 56 plants. Data from fifty of the plants were
transcribed, keypunched, and loaded into the computer. Data from six of
the plants were never used due to deficiencies in data.
After the data from plants were available on the computer, further in-
vestigation resulted in the reconsideration of some of the plants and/or
data. However, the data from these flagged plants may be utilized in
some of the statistical evaluations. Reasons for flagging of the trans-
cribed daily data plants are:
1. Incomplete data (either influent or effluent data missing).
2. Major process changes during data collection period.
3. Dilution of effluent stream before sample point or influent
stream after sample point which causes some difficulty in
analyzing certain stream's data for each day.
51
-------
4. The existence of conditions which indicate poor operation of a
biological treatment system. Examples of these conditions in-
clude low MLSS for activated sludge plants, extreme carryover
of suspended solids, and unconventional design parameters such
as inadequate detention times.
A detailed acceptance/rejection analysis of Daily Data plants, for use
in development of variability factors, is presented in Section VII.
The final Daily Data Base consists of data from 50 plants. These data
are available in two forms on the UNIVAC computer. They are available
in the units in which they were measured at the plant (some in mass per
unit time and some in concentration) and in a file which has been pre-
processed to a consistent set of flow (million gallons per day) and con-
centration (milligrams per liter) units. Each day's data consists of
the plant number, the date and the influent and effluent parameters for
flow BOD, COD, TSS, TOC, ammonia, oil and grease, phenol, chromium, pH,
and temperature, where available.
Mode of Discharge
There are three basic discharge modes utilized by the industry: direct,
indirect and zero or alternative disposal/discharge. Direct dischargers
are plants which have a contaminated effluent, treated or untreated,
which is discharged directly into a surface water. Plants with only
noncontact cooling water or sanitary sewage effluents are not considered
to be direct dischargers for purposes of this report. Indirect dis-
chargers are plants which route their effluents to publicly owned treat-
ment works (POTWs) and are therefore subject to pretreament standards.
Discharge of wastewaters into the system of an adjoining manufacturing
facility or to a treatment system not owned by a government entity is
not considered indirect discharge, but is termed offsite treatment (see
Offsite Treatment). Indirect dischargers are outside the scope of this
report. Zero or alternative disposal/dischargers are plants which dis-
charge no wastewater to surface streams or to POTWs. For the purposes
of this report, these include plants which generate no wastewaters,
plants which recycle contaminated waters, and plants which use some kind
of alternate disposal technology (e.g., deep well injection, incinera-
tion or contractor removal).
Some plants with insufficient information to determine discharge mode
were termed unknown dischargers (see Table 3-12).
The final Summary Data Base contains 291 plants, 195 of which are direct
dischargers, 94 of which are zero or alternative disposal/dischargers,
and two of which are unknown. No indirect dischargers are included.
These 291 plants contain 377 waste streams, 212 of which are direct, 162
of which are zero or alternative disposal/dischargers, and three of
which are unknown. The 195 direct discharge plants include 33 plants
which also utilize zero or alternative disposal discharge techniques
(see Table 3-12).
52
-------
TABLE 3-12
NUMBER AND
TYPES OF PLANTS AND
IN THE DATA BASES
STREAMS
Summary Data Base
Number of
Plants
Number of
Streams
(291 Plants)
All
Dir
Zero
Unk
All Dir
Zero
All
291
195
94
2
377 212
162 3
Organic - Only
62
41
20
1
89 52
36 1
Plastic - Only
113
67
45
1
146 77
67 2
Organics/Plastics
116
87
29
-
142 83
59 -
Daily Data Base
All
50
50
-
-
-
-
Organic - Only
6
6
-
-
-
-
Plastic - Only
17
17
-
-
-
-
Organics/Plastics
27
27
-
-
-
-
Informal Telephone
Survey
All 301
Nonduplicated Plants 251
53
-------
Size
Although there are several possible ways to describe plant size, the 308
Questionnaire did not ask for sales, employment, or acreage data. There-
fore, the only possible remaining description for size in the 308 Data
Base is capacity and actual production. Since data available on the in-
dustry do not include capacity, and since one would not expect design
capacity to determine the pollutant load, those numbers were not includ-
ed in the Summary Data Base.
The Summary Data Base includes values for actual production as shown in
the 308 Questionnaire and for percent of operating capacity being used
in each plant. These data are presented on a stream basis as the total
production of all products made at the plant whose wastewaters are di-
rected to that stream and include production of all products contribu-
ting wastewater, including inorganics and other products not covered
under the SIC codes of interest to this study. Table 3-13 presents the
total production or organic chemicals and plastics in the 308 Data Base,
the total OCPS production for industry determined by the Bureau of Cen-
sus, and the Summary Data Base production values.
Age
Plant age could have an impact on pollutant loadings since water use,
process technology, waste treatment technology, and plant maintenance
techniques have vastly improved over the years since industry begin-
nings. Age was defined for purposes of this study as the year of in-
stallation of the oldest remaining unit at the plant. Table 3-14 pre-
sents the distribution of plant ages in the Summary and Daily Data Base.
Plant ages range from two to 64 years, with most plants between 9 and 24
years old.
Products
The OCPS industry may be described in terms of the number and variety of
products manufactured. This can be done by listing the manufactured
products in a broad categorization such as "organics" and "plastics and
synthetics" or by listing the separate products made at each plant.
The latter approach would provide useful information concerning the pre-
diction of the presence of toxic pollutants at each plant but would not
contribute significantly to the study of conventional and nonconvention-
al pollutant parameters found in end-of-pipe wastewater. Therefore, the
former method of using broad product categories was used for grouping
data. Many of the tables in this section have included information
based on plants which make only organic chemicals, plants which make
only plastics, and plants which make both.
The final Summary Data Base contains 62 plants which are organic only
producers 113 plants which are plastic-only manufacturers, and 116
plants which make both (see Table 3-12). Approximately 1200 products
exist in the 308 Data Base, while 31 percent (373) exist in the Summary
Data Base.
54
-------
TABLE 3-13
PRODUCTION COMPARISONS
Total U. S. *
Total 308
Data Base
All Products
(billion lb/yr)
350
198.4
(57%)
Plastics
(billion lb/yr)
60
44.6
(74%)
Organics
(billion lb/yr)
290
153.8
(53%)
Summary Data Base**
All Streams
Direct Streams
Zero Streams
230
190
40
N/A
N/A
N/A
N/A
N/A
N/A
* per Table 3-1
** These data include manufacture of all products contributing to waste-
water loading, including inorganics and other products not under study
here.
N/A Data not collected in such a way as to make these numbers available
55
-------
TABLE 3-14 NUMBER AND Tit PES OF PLANTS AND STREAMS BY AGE
Streams Plants
AGE
All
Dir
Zer.
Unk.
All
Dir
Zer.
Unk
Daily
Data
2
1
1
_
1
1
-
-
-
3
6
4
1
1
5
4
1
-
1
4
8
6
2
-
8
2
-
2
5
4
1
3
-
4
1
3
-
-
6
8
4
4
-
7
4
3
-
-
7
6
3
3
-
4
2
-
1
8
7
2
5
-
7
3
4
-
-
9
14
11
3
-
13
10
3
-
4
10
14
8
6
-
13
7
6
-
-
11
16
8
8
-
12
7
5
-
1
12
14
9
5
-
12
7
5
-
1
13
10
8
2
-
9
7
2
-
2
14
11
4
6
1
10
5
4
1
3
15
20
16
3
1
18
16
1
1
4
16
9
6
3
-
8
2
-
2
17
10
5
5
-
10
5
5
-
1
18
13
7
6
-
12
7
5
-
1
19
14
7
7
-
14
7
7
-
1
20
10
5
5
-
9
4
5
-
2
21
13
7
6
-
11
7
4
-
2
22
11
6
5
-
9
4
5
-
-
23
10
8
2
-
8
7
1
-
'i
24
10
7
3
-
9
7
2
-
1
25
7
5
2
-
7
5
2
-
-
26
4
2
2
-
4
3
1
-
-
27
4
4
-
-
4
4
-
-
1
28
5
4
1
-
5
4
1
-
1
29
5
2
3
-
5
2
3
-
-
30
4
2
2
-
4
2
2
-
1
31
2
-
2
-
2
2
-
1
32
8
5
3
-
5
4
1
-
1
33
6
5
1
-
6
5
1
-
1
34
3
3
-
-
3
3
-
-
1
35
1
1
-
-
1
1
-
-
-
36
2
2
-
-
2
-
-
-
39
4
4
-
-
4
4
-
-
2
40
6
5
1
-
5
5
-
-
1
41
1
1
-
-
1
1
-
-
-
42
1
1
-
-
1
1
-
-
-
43
3
2
1
-
3
2
1
-
-
44
0
0
-
-
0
-
-
1
46
1
1
-
-
1
1
-
-
1
50
1
1
-
-
1
1
-
-
-
51
2
2
-
-
2
2
-
-
2
52
1
1
-
-
1
1
-
-
-
56
1
1
-
-
1
1
-
-
-
64
1
-
1
-
1
1
-
-
0
65
15
50
-
9
7
2
-
4
TOTALS
377
212
162
3
291
195
94
2
50
56
-------
Processes
Another important way to describe the data bases is in terms of proc-
esses. Process is a more significant description than product because
one product may be made by numerous different processes, each of which
uses different raw materials and reaction conditions. Data on products
and on processes were taken in combinations which yield what are termed
product/processes. A product/process is one product made by a particu-
lar process. For example, cyclohexanone manufacture by oxidation of
cyclohexane is one product/process, and production of cyclohexanone (the
same product) by dehydrogenation of cyclohexanol is a different product/
process. Product/ process designations were given to all products and
processes found in the data bases, including products not in the SIC
codes of interest. There are approximately 2100 product/processes asso-
ciated with the 1200 products in the 308 Data Base. The Summary Data
Base contains 858 different product/processes. Attempting to relate
each individual product/ process with its associated pollutant loading
would be nearly impossible, not because the mechani.cs of such an effort
would be difficult, but because the results would be of little value.
This is true for two reasons. First, each product/process occurs an
average of 2.1 times in the data base. This means that conclusions
would have to be drawn on specific product/processes based on very lit-
tle data. Second, each plant in the data base utilized an average of
6.2 product/processes and each stream contains an average of 4.8
product/processes. The fact that the average plant in the data bases
makes so many products means that the end-of-pipe data collected on each
plant will be a combination of the pollutant loads from all product/
processes existing at that plant. Attempting to relate the end-of-pipe
data to any one of the processes present cannot be done since all of the
product/process data are for total end-of-pipe discharges.
Two methods have been used to make the study of processes more useful:
complexity and generic product/processes.
Complexity - Plant complexity is a description of the variety of prod-
ucts and processes represented at each plant. In the OCPS study, com-
plexity is defined as the number of product/processes available at each
plant. The distribution of plants and streams among the various numbers
of product/processes is indicated in Table 3-15. Plants range in com-
plexity from one to 51 product/processes. Seventy-three percent of the
streams have five or less product/processes going to each, while 45 per-
cent of the plants have between twenty and thirty product/processes.
Generic Processes - To make the process information more meaningful, da-
ta were developed for generic process groups as described in "Generic
Processes." Distributions of the streams among these generic groups are
presented in Table 3-16. All of the generic groups in Table 3-9 are re-
presented in the Summary Data Base.
57
-------
TABLE 3- 15 NUMBER AND TYPES OF PLANTS AND STREAMS BY PRODUCT/PROCESSES
Streams Plants
No. of Product/ Daily
Data
3
7
10
k
2
1
1
2
3
1
1
1
4
1
1
1
1
Processes
All
Dlr
Zer
Unk
All
Dir
Zer
Unk.
1
65
31
33
1
42
21
20
1
2
43
27
15
1
26
15
11
-
3
55
30
24
1
22
14
8
-
4
25
19
6
-
8
5
3
-
5
26
19
7
-
5
3
2
-
6
17
10
7
-
3
2
1
-
7
8
6
2
-
2
2
-
-
8
12
8
4
-
1
1
-
-
9
8
6
2
-
1
1
-
-
10
8
5
3
-
7
5
2
-
11
10
8
2
-
10
8
2
-
12
3
3
-
-
3
3
-
-
13
4
2
2
-
2
1
1
-
14
4
4
-
-
4
4
-
-
15
4
2
2
-
4
2
2
-
16
3
3
-
-
3
3
-
-
17
2
1
1
-
2
1
1
-
18
3
3
-
-
3
3
-
-
20
2
2
-
-
4
4
-
-
21
2
2
-
-
11
6
5
-
22
2
2
-
-
13
12
1
-
23
27
13
13
1
24
1
1
-
-
13
10
3
-
25
1
1
-
-
23
18
5
-
26
2
2
-
-
16
10
6
-
27
6
5
1
-
28
11
8
3
-
29
1
1
-
-
9
6
3
-
31
1
1
-
-
1
1
-
-
33
1
1
-
-
1
1
-
-
34
1
1
-
-
39
1
-
1
-
1
-
1
-
41
1
1
-
-
1
1
-
-
45
1
1
-
-
1
1
-
-
51
1
1
-
-
1
1
-
-
Not Reported
60
9
51
-
3
3
-
-
1
1
TOTALS 377 212 162 3 291 195 94 2 50
58
-------
TABLE 3-16
OCCURRENCES OF GENERIC PROCESSES
Occurrences
Occurrences i Occurrences in Occurrences in Unknown
Generic Class* in the ' Direct Discharge Zero Discharge Discharge
Codes Sura. Data Base Streams Streams Streams
A
63
48
15
-
B
99
85
14
-
C
139
102
37
-
D1
378
231
144
3
D2
140
121
19
-
E
51
46
5
-
F1
37
30
7
-
F2
16
14
2
-
G
117
92
25
-
H
71
57
14
-
I
6
5
1
-
11
3
3
-
-
12
17
17
-
-
J
2
2
-
-
J1
10
10
-
-
J2
19
15
4
-
K
26
22
4
-
L
24
24
-
-
M
35
32
3
-
N
5
3
2
-
0
42
32
10
-
P
35
33
2
Q
10
7
3
-
R
18
16
2
S
6
6
-
-
T
1
1
-
U
5
5
-
V
16
16
-
Z
6
6
-
12
20
17
3
13
1
-
1
14
9
9
-
15
27
23
4
16
6
3
3
17
8
8
-
18
4
3
1
~~
19
1
1
2
48
43
5
20
8
8
21
4
2
2
22
1
1
-
-
23
18
17
1
-
24
9
2
7
-
-------
TABLE 3-16 (Continued)
OCCURRENCES OF GENERIC PROCESSES
Occurrences
Occurrences
Occurrences in
Occurrences
in Unknown
Generic Class*
in the
Direct Discharge
Zero Discharge
Discharge
Codes
Sum. Data Base
Streams
Streams
Streams
3
203
150
52
1
4
12
6
6
-
5
63
54
9
-
6
20
16
4
-
7
2
2
-
-
8
4
4
-
-
9
1
1
TOTAL
1866
1451
411
4
* For description of codes see
Table 3-9.
60
-------
SECTION IV.
S UBCATEGORIZATION
INTRODUCTION
Sections 304(b)(1)(B) and 304(b)(4)(B) of the Clean Water Act require
EPA to assess certain factors in establishing effluent limitations
guidelines based on the best practicable control technology (BPT) and
best conventional pollutant control technology (BCT). These factors
include the age of equipment and facilities involved, the manufacturing
process employed, the engineering aspects of the application of recomm-
ended control technologies including process changes and in-plant con-
trols, non-water quality environmental impacts including energy require-
ments and other factors as determined by the Administrator.
To accommodate these factors, it may be necessary to divide a major in-
dustry into a number of unique and homogeneous groups or subcategories.
This allows the establishment of uniform national effluent limitations
guidelines and standards while at the same time accounting for the
individual characteristics of different groups of facilities.
The factors considered in the subcategorization of the Organic Chemicals
and Plastics and Synthetics Point Source Categories (OCPS) include:
1. Facility Size
2. Geographical Location
3. Age of Facility and Equipment
4. Raw Wastewater Characteristics
5. Treatability
6. Raw Materials
7. Manufacturing Product/Processes
8. Nonwater Quality Environmental Impacts
9. Energy Requirements
The impacts of these factors have been evaluated to determine if sub-
categorisation is necessary or feasible. These evaluations are discus-
sed in detail in the following sections.
STATISTICAL METHODOLOGY
Two major statistical techniques were used to determine an appropriate
subcategorization scheme for the OCPS industry: the Spearman Rank Cor-
relation [4-1] and the Terry-Hoeffding Test.[4-2] Both techniques are
non-parametric, thus making the fewest assumptions about the nature of
the underlying data.
The Spearman Rank Correlation was used to determine the existence of any
relationships among the factors which must be considered for subcategor-
ization of the OCPS industry. A detailed explanation of the Spearman
Rank Correlation technique and an example of its use are presented in
Appendix B.
61
-------
The Terry-Hoeffding test was used to test whether two populations of
plants differ in terms of median levels of a parameter of interest
(e.g., median influent BOD concentration). If the test indicates that
two groups of plants are different, then the groups could represent a
basis for subcategorization. A detailed explanation of the Terry-
Hoeffding test and an example of its use are presented in Appendix B.
TECHNICAL METHODOLOGY
All nine factors mentioned previously were examined for technical sig-
nificance in the development of the proposed subcategorization scheme.
However, in general, the proposed subcategorization is based primarily
on significant differences in raw waste characteristics, since many of
the other eight factors could not be examined in appropriate technical
and statistical depth due to the intricacies of the data base. There-
fore, variations in raw waste characteristics were utilized to evaluate
the impact of the other eight factors on subcategorization. For exam-
ple, the ideal data base for evaluating the need for subcategorization
and the development of individual subcategories would include raw waste-
water and final effluent pollutant data for facilities which employ only
one generic manufacturing process or multiple product plants which seg-
regate and treat each process raw waste stream separately. In this man-
ner, each factor could be evaluated independently. Specifically, to
evaluate the significance of facility size, the ideal data base would
contain fifty or more plants using only one generic process and all
varying in size (i.e., production rates of 10 kilograms per year to
1,000,000 kilograms per year). In addition, all 50 plants would be lo-
cated in one geographic region and be of the same age. In this manner,
the effects of size would not be masked or enhanced by the effects of
geographic location or plant age. Therefore, to evaluate each factor
ideally, the data base would need to contain plants that would allow
isolation of each of the factors as described above for size.
However, the available information consists of historical data collected
by individual companies primarily for the purpose of monitoring the per-
formance of end-of-pipe wastewater treatment technology and compliance
with NPDES permit limitations. The OCPS Industry is primarily comprised
of multi-product/process, integrated facilities. Wastewaters generated
from each product/process are collected in combined plant sewer systems
and treated in one main treatment facility. Therefore, each plant's
overall raw wastewater characteristics are affected by all of the pro-
duction processes occurring at the site at one time. The effects of
each production operation on the raw wastewater characteristics cannot
be isolated accurately from all of the other site specific factors.
Therefore, a combination of both technical and statistical methodologies
had to be used to evaluate the significance of each of the subcategori-
zation factors. In the methodology that was employed, the results of
the technical analysis were compared to the results of the statistical
efforts to determine the usefulness of each factor as a basis for sub-
categorization. The combined technical/statistical evaluations of the
nine factors are presented below.
62
-------
RAW WASTEWATER CHARACTERISTICS
Raw wastewater load (RWL) was selected as the dependent variable to be
used to evaluate the significance of all of the subcategorization fac-
tors discussed in this section. RWL for the purposes of subcategoriza-
tion is a measure of flow, BOD and TSS and was used as the basis for
comparison to the other eight subcategorization factors.
Flow, for the purpose of this report, is measured in million gallons per
day (MGD), and includes only process wastewater. This includes contact
cooling waters, vacuum jet waters, wash waters, reaction media and con-
tact steam. Wastewater flow does not include storm water, non-contact
cooling water and sanitary wastewaters. Wastewater flow can be affected
by facility size, efficiency of water use, methods of production (e.g.,
solvent or aqueous based) , methods of cooling and vacuum generation, as
well as other factors.
BOD is a measure of the wastewater's organic content (see Section V).
Plants that use highly soluble organic materials, or use contact waters
extensively, usually have higher BOD loadings than plants that use dry
process techniques or solvent based reactions.
TSS is a measure of both organic and inorganic solid materials (see
Section V). It is a measure of the insoluble phase of the wastewater.
Higher TSS values can be associated with precipitation products, wash
waters, contaminated storm water, as well as other sources.
MANUFACTURING PRODUCT/PROCESSES
Because this rulemaking involves the combination of two industries,
(Organic Chemicals and Plastics & Synthetic Materials), an initial
subcategorization involving the following broad industry segments was
selected:
1. Plants manufacturing only plastics and synthetic materials
2. Plants manufacturing only organic chemicals
3. Plants manufacturing both organic chemicals and plastic
and synthetic materials at the same facility.
Due to the nature of the raw materials and production processes, organic
chemicals plants would be expected to have higher raw waste loads than
plants manufacturing only plastics and synthetic materials, with com-
bined organics and plastics plants lying between these two groups. This
is confirmed in Figure 4-1, which shows the cumulative distribution of
raw waste BOD for the three initial industry segments: Plastics Only,
Organics Only, and Combined Plastics and Organics. Figure 4-2 presents
the least squares fit of the data shown in Figure 4-1. As shown in
these figures, the points generated from plotting the three cumulative
distributions on log probability scale show the Plastics Only plants
have considerably lower raw waste loads than the other two groups. This
is further substantiated by the application of the Terry-Hoeffding Test
for raw waste BOD for the groups Plastics Only and Not Plastics Only
(combined groups 2 and 3). The test statistic T = 3.765 for a sample
size of 123 yielded a probability level of zero. A level less than 0.05
63
-------
ON
4>
108G0-
1000H
B
0
D
P
P
H 180-
18H
LOG-NORMAL PROBABILITY PLOT
SUBCATEGORY INFLUENT BOD
DIRECT DISCHARGE STREAMS
S-0 j
-------
LOG-NORMAL PROBABILITY PLOT
SUBCATEGORY INFLUENT BOD
DIRECT DISCHARGE SYSTEMS
_ . . .* / /Orcanics &
Orgaixics only , sj*- . ฃ
/ f Plastics
/ / /
S / / Plastics only
/>X
ss /
X/
y/
V 1 I 4 .. n .... M i ................ n ......... r
.0 .001 .023 .16 .50 .34 .977 .999 1.0
CUMULATIVE FREQUENCY
FIGURE 4-2 - LEAST SQUARES FIT OF FIGURE 4-1
-------
is considered significant. Thus, Plastics Only is significantly differ-
ent from the other two groups in terms of BOD. (There was no signifi-
cant difference in the groups for TSS.)
The other two groups offer some statistical analysis problems. As shown
in Figures 4-1 and 4-2, the Organics Only and Plastics and Organics
groups yield cumulative curves which intersect, indicating an interrela-
tionship between the groupings' organics contributions. Unfortunately,
due to data deficiencies, it was not possible to proportion the individ-
ual organics and plastics raw waste contributions for combined organics
and plastics producers by flow or production. As a result, another
approach based on the product/process chemistry exhibited by plants in
the combined groups (Not Plastics Only) was examined.
As detailed in Section III, the OCPS industry produces thousands of or-
ganic chemical products and in many cases, one product can be produced
by a number of processes. Therefore, subcategorizing by specific pro-
duct would result in an unmanageable number of subcategories. However,
since BPT regulations will limit such broad based pollutant parameters
as BOD, TSS, and pH, subcategorizing by type of production process and
their tendencies to produce high or low quantities of these pollutants
can result in a manageable, yet appropriate method of subcategorization.
In general, certain production factors may affect the concentration of
BOD or TSS in the raw wastewater generated by an OCPS industry facility.
Factors that might contribute to a relatively higher BOD or TSS loading
include: the use of aqueous reaction media that may require subsequent
disposal, the general yield of the process (if a process does not retain
a high percentage of reaction products, and instead product and reactant
find their way to the waste stream, a relatively higher raw waste load
may be observed), the absence of toxic materials in the raw wastewater
that might inhibit the BOD test procedure, and the use of vacuum jet
water, steam ejector condensate or contact cooling waters and their dis-
charge to the process sewer.
Also contributing to relatively higher BOD or TSS raw waste characteris-
tics is the use of raw materials or the manufacture of products that
contain oxygen, nitrogen, or phosphorous. Generic processes which gen-
erate oxygenated by-products may be expected to produce wastewaters
which are more biodegradable, and thus exert a higher biological oxygen
demand than process wastewaters which do not. This is because enzymatic
catabolic pathways generally follow a sequence of hydroxylation and sub-
sequent oxidation to keto or carboxylic acid derivatives; and the great-
er the degree of oxidation (whether chemically or biologically induced)
the shorter the pathway to ultimate biodegradation as well as a greater
choice of existing catabolic enzymatic pathways. The generic process of
oxidation therefore would be expected to generate wastewaters that exert
a relatively high biochemical oxygen demand.
An intermediate 5-day biochemical oxygen demand may be expected for
chemical species which occupy an intermediate position in metabolic
pathways (i.e., compounds which require scission of bonds other than
carbon-hydrogen). Substituted amines and similar nitrogen containing
species, for example, are generally biodegradable, although at rates
somewhat less than those of oxygen containing species. Processes that
66
-------
generate wastewaters containing nitrogen in a reduced form (amines,
oximes, nitriles, etc.), or compounds that require scission of a
carbon-oxygen bond prior to oxidative degradation (ethers), are
predicted to exert an intermediate 5-day biochemical oxygen demand.
Other generic processes may be expected to generate wastewaters of re-
latively low biochemical oxygen demand for one of two reasons:
1. refractory chemical species predominate in the wastewater, or
2. relatively few chemical species are present in the wastewater
Generic processes such as nitration and sulfonation generate wastewaters
of a refractory nature and, therefore, exert a low 5-day biochemical ox-
ygen demand for the first reason. Other less refractory potential raw
materials apd products associated with the OCPS industry include aromat-
ics, primary aliphatics, PCBs and halo-ethers. Generic processes pro-
ducing high flow wastewaters that contain relatively few chemical spe-
cies (for example, most polymerization processes) may also be expected
to exert a low biochemical oxygen demand. Based on the presence or ab-
sence of species in industry wastewaters, and the generic process fac-
tors described above, it is reasonable to attempt to aggregate generic
process wastewaters by their biodegradability on theoretical grounds.
Table 4-1 summarizes expected 5-day biochemical oxygen demand by generic
process group.
Type I includes those generic manufacturing processes expected to have
high BOD values, whereas Type IV processes are expected to generate
wastewaters lower in BOD. Type II and III processes complete the range
of high to low BOD values.
The Terry-Hoeffding test was applied to the above product/process struc-
ture. As shown in Table 4-2, Type I vs. Not Type I was the only poten-
tial scheme which showed statistically signficant differences, with raw
waste BOD showing the greatest difference (T = 2.251, P = 0.024). This
suggested that the Not Plastics Only initial grouping be further divided
into two subgroups:
- Plants manufacturing organic chemicals only and organic chemicals
and plastics and synthetic materials in the same facility and
which employ Type I generic chemical processes whether or not
other Type processes are used at the facility (Not Plastics Only
- Type I)
- Plants manufacturing organic chemicals only and organic chemicals
and plastics and synthetic materials in the same facility and
which do not employ Type I generic chemical processes (Not Plas-
tics Only - Not Type I)
Upon further engineering analysis of the production process chemistry,
it was believed that the oxidation generic product/process segment,
which is part of Type I, contributed higher raw waste BOD loadings than
any of the other processes. Thus, it was decided to further subcategor-
ize by the presence or absence of the oxidation generic product/process.
This decision was statistically confirmed by applying the Terry-
67
-------
TABLE 4-1
EXPECTED 5-DAY BIOCHEMICAL OXYGEN DEMAND BY GENERIC PROCESS GROUP
TYPE I - High 5-Day Biochemical Oxygen Demand
Oxidation Hydration
Peroxidation Alkoxylation
Acid Cleavage Hydrolysis
Condensation Carbonylation
Isomerization (maleic > Hydrogenation (butyraldehyde >
fumaric acid) n-butanol)
Esterification Neutralization
Hydroacetylation
TYPE II - Intermediate 5-Day Biochemical Oxygen Demand
Amination Electrohydrodimerization
Ammonolysis Cyanation/Hydrocyanation
Oximation Epoxidation (unsat'd esters)
Dehydration Etherification (alkycellulose)
Ammoxiradation Polymerization (condensation)
TYPE III - Lower 5-Day Biochemical Oxygen Demand
Alkylation (phenol > Dehydrogenation (isobutanol >
nonyl phenol) acetone)
Hydrogenation Sulfonation
(nitrobenzene ^ aniline) Nitration
TYPE IV Lowest 5-Day Biochemical Oxygen Demand
Alkylation (phenol ป
nonyl phenol)
Hydrodealkylation
Isomerization
Pyrolysis (steam)
Cracking (catalytic)
Dehydrogenation (ethyl
benzene > styrene)
Distillation
Extractive distillation
Crystallization/Distillation
Polymerization (bulk & addition)
Fiber production
Halogenation
Oxyhalogenation
Hydrohalogenat ion
Dehydrohalogenation
(1,2-dicholorethane > vinyl CI.)
Chlorohydrination
Phosgenation
Extraction
68
-------
TABLE 4-2
TERRY-HOEFFDING TEST
FOR NOT PLASTICS ONLY PLANTS
Raw Waste BOD
TYPES
TEST STATISTIC
SAMPLE SIZE
SIGNIFICANCE
LEVEL
TYPE I vs. NOT TYPE I T - 2.251
NOT TYPE I BUT TYPE II T - .710
vs. NOT TYPE I OR TYPE II
N ป 74
N - 11
P - .024
P - .478
Raw Waste TSS
TYPE I vs. NOT TYPE I T - .784
NOT TYPE I BUT TYPE II T - .560
vs. NOT TYPE I OR TYPE II
N - 47
N - 13
P - .433
P - .576
Note: See Table 4-1 for definition of Type I and II
69
-------
Hoeffding Test to Type I With Oxidation versus Type I Without Oxidation.
The test statistic was T = 2.706, sample size n = 63 and the signifi-
cance level was P = 0.007. For TSS no significant differences were
found.
The Terry-Hoeffding test was also used to investigate the applicability
of the four subcategories to the parameters COD and TOC. The test re-
sults are shown in Table 4-3. For COD, significant differences were
found between Plastics Only and Not Plastics Only plants, and between
Type I and Not Type I plants in the Not Plastics Only group. For TOC,
no significant differences were found. Based on these results it
appears that the four subcategories are compatible with the COD and TOC
data, and prior to considering the other factors listed previously, the
initial subcategorization is:
1. Plants manufacturing only plastics and synthetic materials
(Plastics Only).
2. Plants manufacturing organic chemicals only, organic chemicals
and plastics and synthetic materials in the same facility, and
other SIC code products which commingle their wastewater with
the above OCPS wastewaters and employ Type I generic chemical
processes including oxidation (Not Plastics Only - Type I With
Oxidation).
3. Plants manufacturing organic chemicals only, organic chemicals
and plastics and synthetic materials in the same facility, and
other SIC code products which commingle their wastewater with
the above OCPS wastewaters and employ Type I generic chemical
processes, but do not include oxidation (Not Plastics Only -
Type I Without Oxidation).
4. Plants manufacturing organic chemicals only, organic chemicals
and plastic and synthetic materials in the same facility, and
other SIC code products which commingle their wastewaters with
the above OCPS wastewaters and employ Type II, III or IV generic
chemical processes (Not Plastics Only - Not Type I).
FACILITY SIZE
Although sales volume, number of employees, area of plant site, plant
capacity and production rate might logically be considered to define
facility size, none of these factors completely describes size in a sat-
isfactory manner. Section III discusses the elimination,^ each of
these factors as an adequate definition of facility size. Specifi-
cally, measuring a facility's size by using the sum of its production
quantities does not account for all characteristics encompassed in plant
size. For example, Plant A may have a relatively fixed market for a
given product and therefore manufactures this product with dedicated
equipment, 24 hours per day, 365 days per year. However, Plant B, which
lists its production rate as identical to Plant A, may manufacture the
same product on a specification basis in six to eight weekly campaigns
(*) See Section III, pp. 21 to 28.
70
-------
TABLE 4-3
TERRY-HOEFFDING TEST FOR SUBCATEGORIZATION
BASED ON COD AND TOC
RAW WASTE COD
Test
Statistics
Type I and C vs. Type I
and Not C*
3.516
Category
Plastics vs. Not Plastics Only
Not Plastics Only
Type I vs. Not Type I 2.114
Sample
Size
107
62
1.347
49
Significance
Level
0.000
0.034
0.178
RAW WASTE TOC
Test
Category Statistics
Plastics vs. Not Plastics Only 0.738
Not Plastics Only
Type I vs. Not Type I 1.205
Type I and C vs. Type I
and Not C* 0.576
Sample Significance
Size Level
48
40
32
0.461
0.228
0.564
* Type I w/oxidation vs. Type I w/o oxidation
71
-------
per year. In addition, Plant A has invested R&D funds in this produc-
tion process and has developed continuous production methods, while
Plant B still utilizes batch production techniques. Therefore, although
products are produced in the same annual quantities, Plant B will most
likely have higher strength wastes due to less efficient production
(lower yields) and much higher variability due to the campaign aspect of
its operation. A statistical evaluation of size as defined by produc-
tion also confirms that size is not a factor for subcategorization. In
the Summary Data Base, the only production data available is on an indi-
vidual waste stream basis. Table 4-4 presents the number of waste
streams per facility size or production rate grouping for each of the
initial subcategories. Table 4-5 and Figures 4-3 through 4-10 present
correlations ranging from -0.3 to +0.19 for raw waste BOD and TSS in the
initial subcategorization scheme. In all cases, the null hypothesis
(Ho) is accepted; that is, raw waste BOD and TSS is independent of size
as defined by production rate in pounds per day.
Therefore, there is no adequate method to define facility size, and it
cannot be used as a technical basis for subcategorization. In addition,
using production as an indication of facility size (because of data
availability), as defined by production, was not a statistically signif-
icant factor for subcategorization.
GEOGRAPHICAL LOCATION
Companies in the OCPS industry usually locate their plants based on a
number of factors. These include:
1. Sources of raw materials
2. Proximity of markets for products
3. Availability of an adequate water supply
4. Cheap sources of energy
5. Proximity to proper modes of transportation
6. Reasonably priced labor markets
In addition, a particular product/process may be located in an existing
facility based on availability of certain types of equipment or land for
expansion. Companies also locate their facilities based on the type of
production involved. For example, specialty producers may be located
closer to their major markets, whereas bulk producers may be centrally
located to service a wide variety of markets. Also, a company may lo-
cate its plants based on its planned method of wastewater disposal. A
company which has committed itself to zero discharge as its method of
wastewater disposal has the ability to locate anywhere, while direct
dischargers must locate near receiving waters, and indirect dischargers
must locate in a city or town which has an adequate POTW capacity to
treat OCPS wastewaters.
Because of the complexity and interrelationships of the factors outlined
above affecting plant locations, no clear basis for subcategorization
according to the plant location could be found. Therefore, location is
not a basis for subcategorization of the OCPS industry.
72
-------
TABLE 4-4
(DIRECT SYSTEMS) NUMBER OF WASTE STREAMS WITHIN PRODUCTION RATE RANGES
(#/day) All Plastics Not Plastics Not Plastics Not Plastics
Size Streams Only Type I & C* Type I Not C** Not Type I
1-9,999
1
0
0
1
0
10,000-49,999
5
2
0
2
1
50,000-99,999
7
5
1
1
0
100,000-249,999
21
15
2
1
3
250,000-449,999
27
16
5
3
3
450,000-599,999
20
8
7
2
3
600,000-999,999
28
14
7
4
3
1,000,000-1,999,999
33
12
7
6
8
2,000,000-4,999,999
29
1
13
8
7
Over 5,000,000
31
0
19
6
6
Missing
10
4
3
1
2
TOTAL
212
77
64
35
36
* Type I w/oxidation
** Type I w/o oxidation
-------
TABLE 4-5
SPEARMAN CORRELATION COEFFICIENTS (R)
FOR RAW WASTE BOD AND TSS vs. SIZE
(Production Rate)
All
Plants
Plastics
Only
Not Plastics Only
I w/oxidation I w/o oxidation|
No Group I
BOD
0.21
0.06
-0.12
-0.02
-0.31
(0.02)
(N.S.)
(N.S.)
(N.S.)
(N.S.)
TSS
0.02
-0.00
-0.13
-0.42
-0.20
(N.S.)
(N.S.)
(N.S.)
(N.S.)
(N.S.)
Note: Results of testing (Ho: C*0) are indicated as:
a) N.S. - Not significantly different from zero (P>.05)
b) <.01 - Significantly didfferent from zero (P<.01)
c) Actual probability (.01
-------
FIGURE 4-3
RANK CORRELATION
FOR THE RUSTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/NOT TYPE I
BOD
12.5H
10.0
7.5-
2.3-
0.0
iihiimhii'i mni|Miiimipimuini
I
0
9 10 11
8
2
5
7
3
4
6
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT ป -0.31
-------
FIGURE 4-4
RANK CORRELATION
FOR THE FUSTIC & ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I ft NOT C*
BOD
25 H
28 -
15 -
~
o
6
O
o
o
o
10 -
5 -
o
~
o
0 H
|IIIIIIIIHIIIHIIII[IIIIIIIII|IIHIIIII|I'" |IIIIIIIIHซ "| Illl|ป'l IIH|IIIU
0 2 4 6 8 10 12 14 16 13 20
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT ป -0.02
-------
FIGURE 4-5
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I ft C*
-J
BOD
50 H
48 -
30 -
20 -
10 -
0 -
I
0 5
T
10
fliiialfi
15
* ' i '
20
25
w * I "
30
35
r^p.
40
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT ซ -0.12
-------
FIGURE 4-6
RANK CORRELATION
FOR THE FUSTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
PLASTICS ONLY
BOD
58
40
38
28
ฎ 3 6 9 12 15 18 21 24 27 38 33 36 39 42 45 48
5J2E (Production Rate)
SPEARMAN CORRELATION COEFFICIENT * .86
-------
FIGURE 4-7
RANK CORRELATION
FOR THE PLASTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
HOT PUSTICS ONLY/NOT TYPE I
TSS
15
12
9
6
3
8
345678 9 18 11
12 13
2
1
8
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT * -8.28 CP * .52, N ซ 13>
A
-------
FIGURE 4-8
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
HOT PLASTICS ONLY/TYPE I ft NOT C*
TSS
15
12
9
6
3
8
VMIJIHHV9II|M
4 5
9 18 11 12 13
3
2
6
6
t
1
5I2E (Production Rate)
SPEARMAN CORRELATION COEFFICIENT * 8.42 (P * .15, N = 13>
i
* Type I w/o oxidation
-------
FIGURE 4-9
RANK CORRELATION
FOR THE PLASTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS ^
NOT PLASTICS ONLY/TYPE I * C
TSS
28 -i
|iunim|iriiiiiM|
18 20
16
14
18
12
6
8
4
8
2
SIZE (Production Rate)
SPEARHAN CORRELATION COEFFICIENT * -8.13
9
* Type I w/oxidation
-------
FIGURE 4-10
RANK CORRELATION
FOR THE PLASTIC & ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
PLASTICS ONLY
IS 3
50 H
40 -
30 -
o ~
~ ~
~ . ~
20 -
10 -
0 -
A ^
~ ~~
~ ~
~ O ~
|ii)ii|niii|iiiii|iiiii|iiiii|iiiii|iiiiiniiin
0 3 6 9 12 IS Id 21 24 27 30 33 36 39 42
SIZE (Production Rate)
SPEARllftN CORRELATION COEFFICIENT -0.00
-------
The effects of temperature, which is related to geographical location,
are discussed in detail in Section VII, Control and Treatment Technol-
ogy. It is concluded in Section VII that the effects of temperature are
inconclusive.
AGE OF FACILITY AND EQUIPMENT
The age of an OCPS plant is difficult to accurately define. This is
because production facilities are continually modified to meet produc-
tion goals and to accommodate new product lines. Therefore, actual
process equipment is generally modern (i.e., 0-15 years old). However,
major building structures and plant sewers are not generally upgraded
unless the plant expands significantly. Facility age, for the purposes
of this report, and as reported in the 308 Questionnaire, is defined as
the oldest process in operation at the site. Table 4-6 presents the
number of waste streams per age grouping for each of the initial subcat-
egories .
Older plants may use open sewers and drainage ditches to collect process
wastewater. In addition, cooling waters, steam condensates, wash
waters, and tank drainage waters are generally collected in these drains
due to their convenience and lack of other collection alternatives.
These ditches may run inside the process buildings as well as between
manufacturing centers. Therefore, older facilities are likely to exhib-
it higher wastewater discharge flow rates than newer facilities. In ad-
dition, since the higher flows may result from the inclusion of rela-
tively clean noncontact cooling waters and steam condensates as well as
infiltration/inflow, raw wastewater concentrations may be lower due to
dilution effects. Furthermore, recycle techniques and wastewater segre-
gation efforts normally cannot be accomplished with existing piping sys-
tems, and would require the installation of new collection lines as well
as the isolation of the existing collection ditches. However, due to
water conservation measures as well as ground contamination control,
many older plants are upgrading their collection systems. In addition,
the energy crisis of recent years has caused many plants to upgrade
their steam and cooling systems to make them more efficient.
Figures 4-11 through 4-18 present BOD and TSS raw waste rank correla-
tions versus facility age for each of the initial subcategories. All
rank correlations shown in Table 4-7 show no clear trend. The only
apparent correlation appears for the Not Plastics Only-Type I With Oxi-
dation group with a rank correlation of Rm -0.49 and P* <0.01 for raw
waste BOD and age. This negative correlation reinforces the argument
that higher raw waste levels in newer plants can be attributed to more
rigorous modern water conservation techniques. This is again supported
by raw waste flow versus age rank correlations for the Not Plastics
Only-Type I With Oxidation group, which shows a rank correlation of R ฆ
0.5 and P ฆ 0.0001. Thus, older plants within the same grouping tend to
have higher flows which dilute the strength of their raw wastewaters.
Therefore: (1) a plant's age for the purposes of regulation would be
difficult to accurately measure, and (2) the relationship between facil-
ity age and RWL characteristics is greatly affected by many external
factors, eliminating facility age as a feasible basis for subcategori-
83
-------
TABLE 4-6
(DIRECT SYSTEMS)
NUMBER OF STREAMS PER AGE GROUP
(Years)
Age
All
Streams
Plastics
Only
Not Plastics
Type I & C*
Not Plastics
**
Type I Not C
Not Plastics
Not Type I
1-5
12
9
1
1
1
6-9
20
7
10
0
3
10-12
25
7
9
5
4
13-15
28
8
8
6
6
16-18
18
5
4
6
3
19-20
12
6
2
1
3
21-23
21
7
10
2
2
24-30
26
10
5
4
7
31-40
25
8
10
3
4
41-0ver
10
4
2
2
2
Missing
15
6
3
5
1
TOTAL
212
77
64
35
36
* Type I w/Oxidation
II Type I w/o Oxidation
84
-------
FIGURE 4-11
RANK CORRELATION
FOR THE PLASTIC & ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
PLASTICS ONLY
BOD
58 H
48
38
28
8 3 6 9 12 15 18 21 24 27 38 33 36 39 42 45 48
AGE
SPEARMAN CORRELATION COEFFICIENT ซ -8.19
t
-------
FIGURE 4-12
RANK CORRELATION
FOR THE RUSTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I ft C*
BOD
58
48
38
28
35
18
28
25
38
5
15
48
8
AGE
SPEARMAN CORRELATION COEFFICIENT * -8.49
-------
FIGURE 4-13
oo
-j
RANK CORRELATION
FOR THE PLASTIC A ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT RUSTICS ONLY/TYPE I ft HOT C*
BOD
28 H
15 -
10 -
5 -
ฎ '|iiiimiHปปniniHiniiniHiminiHinimii|iinniii|iiinmi|ปiiiniii|ปninm|
8 2 4 8 10 12 14 16 13
AGE
SPEARHAN CORRELATION COEFFICIENT ป 8.81 CP ซ .96, N ซ 18>
f
* Type I w/o oxidation
-------
FIGURE 4-14
oo
00
BOD
12.5-
10.0-
7.5-
5.0-
2.5-
0.0-
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/NOT TYPE I
~
o
MiiiniHniimimnimmimininimiiiii|iiinim|iiiiinmmmiiniiiin
0123456789 10 11
AGE
SPEARMAN CORRELATION COEFFICIENT * 0.86
-------
FIGURE 4-15
RANK CORRELATION
FOR THE PLASTIC * ORGANIC CHEMICAL INDUSTRIES
OIRECT DISCHARGE SYSTEMS
PLASTICS ONLY
TSS
40
30
20
10
0
30
35
15
25
40
10
5
0
AGE
SPEARMAN CORRELATION COEFFICIENT - -0.18
-------
FIGURE 4-16
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I ft C*
TSS
28
15
10
5
0
14
10
12
16
20
6
8
18
4
0
2
AGE
SPEARMAN CORRELATION COEFFICIENT = -0.35 CP ป .13, N = 20)
o
* Type I w/oxidation
-------
FIGURE 4-17
RANK CORRELATION
FOR THE FUSTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I & NOT C *
TSS
12.5H
10.0J
7.5-
5.0-
2.5-
0.0-
0
2 3 4 5 6 ? 8 9 10 11 12
AGE
SPEARMAN CORRELATION COEFFICIENT * -0.06 CP ซ .80, N * 12)
"2
Type I w/o oxidation
-------
FIGURE 4-18
RANK CORRELATION
FOR THE PLASTIC & ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/NOT TYPE I
TSS
15
12
9
6
3
0
[in ปnniiiiiiiinininiii|iiiiiiiininiiiiininiiiiii|innnmiu
1 2 3 4 5
9 10
IIIJMIItllllJ'
11 12
0
6
7
8
AGE
SPEARMAN CORRELATION COEFFICIENT ซ 0.12
-------
TABLE 4-7
SPEARMAN CORRELATION COEFFICIENTS (R)
FOR RAW WASTE BOD AND TSS vs. AGE
All
Plants
Plastics
Only
I w/oxidation
Not Plastics Only
I w/o oxidation
| No Group
BOD
-0.19
-0.19
-0.49
0.01
0.06
(0.04)
(N.S.)
.00
(N.S.)
(N.S.)
TSS
"0.13
-0.18
-0.35
-0.08
0.12
(N.S.)
(N.S.)
(N.S.)
(N.S.)
(N.S.)
Note: Results of testing (Ho: C=0) are indicated as:
a) N.S. - Not significantly different from zero (P>.05)
b) <.01 - Significantly different from zero (P<.01)
c) Actual probability (.01
-------
zation. Nevertheless, because there is a negative correlation between
RWL and age in the Not Plastics Only - Type I With Oxidation group, age
and the subsequent impact of water usage may be important in this group.
Therefore, evaluation of this phenomenon to accommodate these statis-
tically significant factors based on water usage within this particular
subcategory, is appropriate and is discussed in detail in Section VII.
RAW MATERIALS
Synthetic organic chemicals can be defined as derivative products of
naturally occurring materials (petroleum, natural gas and coal) which
have undergone at least one chemical reaction such as oxidation, hydro-
genation, halogenation or alkylation. This definition, when applied to
the larger number of potential starting materials and the host of chem-
ical reactions which can be applied, leads to the possibility of many
thousands of organic chemical compounds being produced by a potentially
large number of basic processes having many variations. There are more
than 25,000 commercial organic chemical products derived principally
from petrochemical sources. These are produced from five major raw ma-
terial classifications: methane, ethylene, propylene, hydrocarbons,
and higher aliphatics and aromatics. This major raw materials list can
be expanded by further defining the aromatics to include benzene, tol-
uene and xylene. These raw materials are derived from natural gas and
petroleum, although a small portion of the aromatics are derived from
coal. Currently, approximately 90 percent by weight of the organic
chemicals used in the world are derived from petroleum or natural gas.
Other sources of raw materials are coal and some naturally-occuring re-
newable material of which fats, oils and carbohydrates are the most im-
portant. The third source also includes more obscure natural products
(consisting of small quantities of very specialized chemicals) which
contribute to highly specialized segments of the industry.
Regardless of the relatively limited number of basic raw materials util-
ized by the organic chemicals industry, process technologies lead to the
formation of a wide variety of products and intermediates, many of which
can be produced from more than one basic raw material either as a pri-
mary reaction product or as a by-product. Furthermore, primary reaction
products are frequently processed to other chemicals which categorize
the primary product from one process as the raw material for a subse-
quent process.
Delineation between raw materials and products is nebulous at best,
since the product from one manufacturer can be the raw material for
another manufacturer. This lack of distinction is more pronounced as
the process approaches the ultimate end product, which is normally the
fabrication or consumer stage. Also, many products/intermediates can be
made from more than one raw material. Frequently, there are alternate
processes by which a product can be made from the same basic raw
material.
Another characteristic of the OCPS industry which makes subcategoriza-
tion by raw material difficult is the high degree of integration in man-
ufacturing units. Since the bulk of the basic raw materials are derived
from petroleum or natural gas, many of the organic chemical manufactur-
94
-------
ing plants are either incorporated into or continguous to petroleum re-
fineries, and may formulate a product at almost any point in a process
from any or all of the basic raw materials. Normally, relatively few
organic manufacturing facilities are single product/process plants un-
less the final product is near the fabrication or consumer product
stage.
Because of the integrated complexity of the largest (by weight) single
segment of the organics industry (petrochemicals), it may be concluded
that subcategorization by raw materials is not feasible for the follow-
ing reasons:
1. The organic chemicals industry is made up primarily of chemical
complexes of various sizes and complexity.
2. Very little, if any, of the total production is represented by
single raw material plants.
3. The raw materials used by a plant can be varied widely over
short time spans.
4. The conventional and nonconventional wastewater pollutant par-
ameter data gathered for this study were not collected on a raw
materials orientation, but rather represent the mixed end-of-
pipe plant wastewaters.
TREATABILITY
Treatability of OCPS wastewaters is discussed in great detail in Section
VII. The treatability of a given wastewater is affected by the presence
of inhibitory materials (toxics); availability of alternative disposal
methods; and pollutant concentrations in, and variability of, the RWL.
However, all of these factors can be mitigated by sound waste manage-
ment, treatment technology design, and operating practices. Examples of
these are:
o The presence of toxic materials in the wastewater can be con-
trolled by in-plant treatment methods. Technologies such as
steam stripping, metals precipitation, activated carbon, reverse
osmosis, etc. can eliminate the presence of materials in a
plant'8 wastewater which may inhibit or upset biological treat-
ment systems.
o Although many plants utilize deep well injection for disposal of
highly toxic wastes to avoid treatment system upsets, other al-
ternative disposal techniques such as contract hauling and in-
cineration are available to facilities which cannot utilize deep
well disposal. In addition, stricter groundwater regulations
may eliminate the option of deep well disposal for some plants,
or make it uneconomical for others, forcing facilities to look
more closely at these other options.
o RWL variability can easily be controlled by the use of equaliza-
tion basins. In some plants, "at process" storage and equaliza-
95
-------
tion is used to meter specific process wastewaters, on a con-
trolled basis, into the plant's wastewater treatment system.
o Raw waste concentrations can be reduced with roughing biological
filters or with the use of two-stage biological treatment sys-
tems. These techniques are discussed in more detail in Section
VII.
OCPS wastewaters can be treated by either physical-chemical or biologi-
cal methods, depending on the pollutant to be removed. Also, depending
on the specific composition of the wastewater, any pollutant may be re-
moved to a greater or lesser degree by a technology not designed for
removal of this pollutant. For example, a physical-chemical treatment
system designed to remove suspended solids will also remove a portion of
the BOD of a wastewater if the solids removed are organic and biodegrad-
able. It is common in the OCPS industry to use a combination of tech-
nologies adapted to the individual wastewater stream to achieve desired
results. These concepts are discussed in detail in Section VII.
In general, the percent removals of BOD and TSS are consistent across
all initial subcategories. It is also possible for plants in all ini-
tial subcategories to achieve high percent removals (greater than 95%)
for both BOD and TSS (data supporting these removals are presented and
discussed in Section VII). Therefore, based on the consistency of these
removal data and the ability of plants in all initial subcategories to
achieve high removals of pollutants, it is concluded that subcategoriza-
tion based on treatability is not justified.
ENERGY AND NON-WATER QUALITY ASPECTS
Energy and non-water quality aspects include the following:
1. Sludge production
2. Air pollution derived from wastewater generation and treatment
3. Energy consumption due to wastewater generation and treatment
4. Noise from wastewater treatment
The basic treatment step, used by virtually all plants in all subcate-
gories that generate raw wastes containing basically BOD and TSS, is
biological treatment. Therefore, the generation of sludges, air pollu-
tion, noise and the consumption of energy will be homogeneous across the
industry. However, the levels of these factors will relate to the vol-
ume of wastewater treated and their associated pollutant loads. Since
the volumes of wastewater generated and the RWL from each pollutant were
considered in earlier sections, it is believed that all energy and non-
water quality aspects have been adequately addressed in the proposed
subcategorization scheme.
96
-------
SUMMARY - SUBCATEGORIZATION
Based on the preceding technical and statistical evaluation of the OCPS
industry, four subcategories have been established. These subcategories
are as follows:
Subcategory 1 - Plastics Only
Discharges resulting from the manufacture of plastics and synthetic
fibers only.
Subcategory 2 - Oxidation
Discharges resulting from the manufacture of organic chemicals only, or
both organic chemicals and plastics and synthetic fibers, that include
wastewater from the oxidation process.
Subcategory 3 - Type I
Discharges resulting from the manufacture of organic chemials only, or
both organic chemicals and plastics and synthetic fibers, that include
wastewater from any of the following generic processes (referred to in
the BPT Development document as "Type I" processes) but not from the
oxidation process:
Peroxidation
Acid Cleavage
Condensation
Isomerization
Gsterification
Hydroacetylation
Hydration
Alkoxylation
Hydrolysis
Carbonylation
Hydrogenation
Neutralization
Subcategory 4 - Other Discharges
All OCPS discharges not included in Subcategories 1-3.
97
-------
SECTION V.
SELECTION OF POLLUTANT PARAMETERS
WASTEWATER PARAMETERS
Specific conventional and nonconventional wastewater parameters were
determined to be significant in the Organic Chemicals and Plastics and
Synthetic Materials Industries and were selected for evaluation based
on: (1) an industry characterization, (2) data collected from sampling
efforts, (3) historical data collected from the literature, and (4) data
provided by industry questionnaires (308 Portfolio).
Conventional pollutant parameters chosen for evaluation include 5-day
biochemical oxygen demand (BOD^), total suspended solids (TSS), pH, and
oil and grease (O&G). Nonconventional pollutant parameters selected are
chemical oxygen demand (COD) and total organic carbon (TOC).
CONVENTIONAL POLLUTANT PARAMETERS
5-day Biochemical Oxygen Demand (BOD^)
The 5-day Biochemical Oxygen Demand (BOD^) test traditionally has been
used to determine the strength of domestic and industrial wastewaters.
It is a measure of the oxygen required by biological organisms to assim-
ilate the biodegradable portion of a waste under aerobic conditions.
[5-1] Substances that may contribute to the BOD include carbonaceous
materials usable as a food source by aerobic organisms; oxidizable
nitrogen derived from organic nitrogen compounds, ammonia and nitrites
that are oxidized by specific bacteria; and chemically oxidizable mater-
ials such as ferrous compounds, sulfides, sulfite, and similar reduced-
state inorganics that will react with dissolved oxygen or that are
metabolized by bacteria.
The BOD of a wastewater is a measure of the dissolved oxygen depletion
that might be caused by the discharge of that wastewater to a body of
water. This depletion reduces the oxygen available to fish, plant life,
and other aquatic species. Total exhaustion of the dissolved oxygen in
water results in anaerobic conditions, and the subsequent dominance of
anaerobic species that can produce undesirable gases such as hydrogen
sulfide and methanol. The reduction of dissolved oxygen can be detri-
mental to fish populations, fish growth rates, and organisms used as
fish food. A total lack of oxygen can result in the death of all aero-
bic aquatic inhabitants in the affected area.
The BOD. (5-day BdD) test is widely used to estimate the oxygen demand
of domestic and industrial wastes and to evaluate the performance of
waste treatment facilities. The test is widely used for measuring
potential pollution since no other test methods have been developed that
are as suitable or as widely accepted for evaluating the deoxygenation
effect of a waste on a receiving water body.
The BOD test measures the weight of dissolved oxygen utilized by micro-
organisms as they oxidize or transform the gross mixture of chemical
99
-------
compounds in the wastewater. The degree of biochemical reaction in-
volved in the oxidation of carbon compounds is related to the period of
incubation. When municipal sewage is tested, BOD^ normally measures
only 60 to 80 percent of the total carbonaceous biological oxygen demand
of the sample. When testing OCPS wastewaters, however, the fraction of
total carbonaceous oxygen demand measured can range from less than 10
percent to more than 80 percent. The actual percentage for a given
waste stream will depend on the degradation characteristics of the or-
ganic components present, the degree to which the seed is acclimated
to these components, and the degree to which toxic or inhibitory compo-
nents are present in the waste.
Total Suspended Solids TSS
Suspended solids can include both organic and inorganic materials. The
inorganic materials include sand, silt and clay and may include insol-
uble toxic metal compounds. The organic fraction includes such mater-
ials as grease, oils, animal and vegetable waste products, fibers,
microorganisms and many other dispersed insoluble organic compounds.
[5-2] These solids may settle rapidly and form bottom deposits that are
often a mixture of both organic and inorganic solids.
Solids may be suspended in water for a time and then settle to the bot-
tom of a stream or lake. They may be inert, slowly biodegradable mater-
ials, or they may be rapidly decomposable substances. While in suspen-
sion, they increase the turbidity of the water, reduce light penetra-
tion, and impair the photosynthetic activity of aquatic plants. After
settling to the stream or lake bed, the solids can form sludge banks,
which, if largely organic, create localized anaerobic and undesirable
benthic conditions. Aside from any toxic effect attributable to sub-
stances leached out by water, suspended solids may kill fish and shell-
fish by causing abrasive injuries, clogging gills and respiratory pas-
sages, screening light, and by promoting and maintaining noxious condi-
tions through oxygen depletion.
Suspended solids may also reduce the recreational value of a waterway
and can cause problems in water used for domestic purposes. Suspended
solids in intake water may interfere with many industrial processes, and
cause foaming in boilers, or encrustations on exposed equipment, espe-
cially at elevated temperatures.
Jfi
The term pH describes the hydrogen ion-hydroxyl ion equilibria in water.
Technically, pH is a measure of the hydrogen ion concentration or acti-
vity present in a given solution. A pH number is the negative logarithm
of the hydrogen ion concentration. A pH of 7.0 indicates neutrality or
a balance between free hydrogen and free hydroxyl ions. A pH above 7.0
indicates thft a solution is alkaline; a pH below 7.0 indicates that a
solution is acidic.
The pH of discharge water is of concern because of its potential impact
on the receiving body of water. Wastewater effluent, if not neutralized
before release, may alter the pH of the receiving water. The critical
100
-------
range suitable for the existence of most biological life is quite nar-
row, lying between pH 6 and pH 9.
Extremes of pH or rapid pH changes can harm or kill aquatic life. Even
moderate changes from acceptable pH limits can harm some species. A
change in the pH of water may increase or decrease the relative toxicity
of many materials to aquatic life. A drop of even 1.5 units, for exam-
ple, can increase the toxicity of metalocyanide complexes a thousand-
fold. The bactericidal effect of chlorine in most cases lessens as the
pH increases.
Waters with a pH below 6.0 corrode waterworks structures, distribution
lines, and household plumbing fixtures. This corrosion can add to drink
ing water such constituents as iron, copper, zinc, cadmium, and lead.
Low pH waters not only tend to dissolve metals from structures and fix-
tures, but also tend to redissolve or leach metals from sludges and bot-
tom sediments.
Normally, biological treatment systems are maintained at a pH between 6
and 9; however, once acclimated to a narrow pH range, sudden deviations
(even in the 6 to 9 range) can cause upsets in the treatment system with
a resultant decrease in treatment efficiency.
Oil and Grease (0 & G)
Oil and grease analyses do not actually measure the quantity of a spe-
cific substance, but measure groups of substances whose common charac-
teristic is their solubility in freon. Substances measured may include
hydrocarbons, fatty acids, soaps, fats, oils, wax and other materials
extracted by the solvent from an acidified sample and not volatilized by
the conditions of the test. As a result, the term oil and grease is
more properly defined by the conditions of the analysis rather than by a
specific compound or group of compounds. Additionally, the material
identified in the 0&G determination is not necessarily free floating.
It may be actually in solution but still extractable from water by the
solvent.[5-3]
Oils and greases of hydrocarbon derivative, even in small quantities,
cause troublesome taste and odor problems. Scum lines from these agents
are produced on water treatment basin walls and other containers. Fish
and water fowl are adversely affected by oils in their habitat. Oil
emulsions may cause the suffocation of fish by adhering to their gills
and may taint the flesh of fish when microorganisms exposed to waste oil
are eaten. Deposition of oil in the bottom sediments of natural waters
can serve to inhibit normal benthic growth. Oil and grease can also ex-
hibit an oxygen demand.
Levels of oil and grease that are toxic to aquatic organism vary greatly
depending on the oil and grease components and the susceptibility of the
species exposed to them. Crude oil in concentrations as low as 0.3 mg/1
can be extremely toxic to freshwater fish. Oil slicks prevent the full
aesthetic enjoyment of water. The presence of oil in water can also in
crease the toxicity of other substances being discharged into the re-
ceiving bodies of water. Municipalities frequently limit the quantity
101
-------
of oil and grease that can be discharged to their wastewater treatment
systems by industry, since large quantities of O&G can cause difficul-
ties in biological treatment systems.
There are several approved modifications of the analysis for oil and
grease. Each is designed to increase the accuracy or enhance the selec-
tivity of the analysis. Depending on the procedure and detection method
employed, the accuracy of the test can vary from 88 percent for the Sox-
hlet Extraction Method to 99 percent for the Partition-Infrared Method.
NONCONVENTIONAL POLLUTANT PARAMETERS
Chemical Oxygen Demand (COD)
COD is a chemical oxidation test devised as an alternate method of
estimating the oxygen demand of a wastewater. Since the method relies
on the oxidation-reduction system of a chemical reaction rather than a
biological reaction, it is more precise, accurate, and rapid than the
BODc test. The COD test is sometimes used to estimate the total oxygen
(ultimate rather than 5-day BOD) required to oxidize the compounds in a
wastewater. In the COD test strong chemical oxidizing agents under acid
conditions, with the assistance of certain inorganic catalysts, can oxi-
dize most organic compounds, including many that are not biodegradable.
[5-4]
The COD test measures organic components that may exert a biological
oxygen demand and may affect public health. It is a useful analytical
tool for pollution control activities. Most pollutants measured by the
BOD^ test will be measured by the COD test. In addition, pollutants
resistant to biochemical oxidation will also be measured as COD.
Compounds resistant to biochemical oxidation are of great concern be-
cause of their slow, continuous oxygen demand on the receiving water and
also, in some cases, because of their potential health effects on aqua-
tic life and humans. Many of these compounds result from industrial
discharges and some of the compounds have been found to have carcino-
genic, mutagenic, and similar adverse effects. Concern about these com-
pounds has increased as a result of demonstrations that their long life
in receiving water (the result of a low biochemical oxidation rate)
allows them to contaminate downstream water intakes. The commonly used
systems of water purification are not effective in removing these types
of materials and disinfection with chlorine may convert them into even
more objectionable materials.
It should be noted that the COD test may not measure the oxygen demand
of certain aromatic species such as benzene, toluene and pyridine.
Total Organic Carbon (TOC)
TOC measures all oxidizable organic material in a waste stream, in-
cluding the organic chemicals not oxidized (and therefore not detected)
in BOD and COD tests. TOC analysis is a rapid test for estimating the
total organic carbon in a wastestream.
102
-------
When testing for TOC, the organic carbon in a sample is converted to
carbon dioxide (CC^) by catalytic combusion or by wet chemical oxida-
tion. The CC>2 formed can be measured directly by an infrared detector
or it can be converted to methane (CH,) and measured by a flame ioniza-
tion detector. The amount of C0ฃ or CH^ is directly proportional to the
concentration of carbonaceous material in the sample. TOC tests are
usually performed on commercially available automatic TOC analyzers.
Inorganic carbons, including carbonates and bicarbonates, interfere with
these analyses and must be removed during sample preparation.[5-5]
103
-------
SECTION VI.
WATER USE AND WASTEWATER CHARACTERIZATION
WATER USE AND SOURCES OF WASTEWATER
Water use and wastewater generation occur at a number of points in OCPS
manufacturing processes and ancillary operations, including: (l) direct
and indirect process contact, (2) contact and noncontact cooling water,
(3) utilities, maintenance and housekeeping, and (4) air pollution con-
trol systems such as Venturi scrubbers.
An example of direct process contact water is the use of aqueous reac-
tion media. The use of water as a media for certain chemical processes
becomes a major high strength wastewater source after the primary reac-
tion has been completed and the final product has been separated from
the water media, leaving unwanted by-products formed during secondary
reactions in solution.
Indirect process contact waters, such as those discharged from vacuum
jets and steam ejectors, involve the recovery of solvents and volatile
organics from the chemical reaction kettle. In using vacuum jets, a
stream of water is used to create a vacuum, but also draws off volatil-
ized solvents and organics from the reaction kettle into solution.
Later, recoverable solvents are separated and reused while unwanted
volatile organics remain in solution in the vacuum water which is dis-
charged as wastewater. Steam ejector systems are similar to vacuum jets
with steam being substituted for water. The steam is then drawn off and
condensed to form a source of wastewater.
The major volume of water use in the OCPS industry is cooling water.
Cooling water may be contaminated, such as contact cooling water from
barometric condensers, or uncontaminated noncontact cooling water.
Frequently, large volumes of cooling water may be used on a once-through
basis and discharged with process wastewater. Many of the effluent val-
ues reported by plants in the data bases were based on flow volumes
which included their cooling water. An adjustment of the reported vol-
umes of the effluents was therefore required to arrive at performance of
treatment systems and other effluent characteristics. This adjustment
was made by eliminating the uncontaminated cooling water volume from the
total volume, to arrive at the contaminated wastewater flow. Concentra-
tions also were adjusted using the simplifying judgment that the uncon-
taminated cooling water did not contribute to the pollutant level. How-
ever, it should be noted that in some cases cooling water can contribute
relatively high TSS loading, especially to typically low strength plas-
tics and synthetic materials wastewaters.
Tables 6-1 and 6-2 present treated effluent wastewater and raw waste
flows reported by direct discharge plants and zero or alternative dis-
charge disposal plants, respectively, for each of the four proposed sub-
categories. The adjusted flows presented were calculated from all raw
and treated wastewater streams reported with the number of observations
corresponding to the total number of reported waste stream flows. It
105
-------
TABLE 6-1
EFFLUENT FLOWS FOR PROPOSED SUBCATEGORIES
DIRECT DISCHARGERS ONLY
NOT PLASTICS NOT PLASTICS
TYPE I w/ TYPE I w/o NOT PLASTICS
OXIDATION OXIDATION NOT
TYPE I
EFF
EFF
EFF
EFF
FLOW
FLOW
FLOW
F LO>V
MGO
f.'GO
'ฆ'GO
(ฆ'CD
MAXIMUM
10.700
29 .000
32.100
40 .000
MEAN
1 .357
2.771
2 .180
3.346
MINIMUM
0.034
0.008
0 . 020
0.007
MEDIAN
0.612
1.010
0 .852
0 .950
NUMBER OF
OBSERVATIONS
74
63
34
35
PLASTICS
ONLY
-------
TABLE 6-2
INFLUENT AND EFFLUENT FLOWS FOR PROPOSED SUBCATEGORIES
ZERO DISCHARGE/ALTERNATIVE DISPOSAL ONLY
PLASTICS
ONLY
NOT PLASTICS
TYPE I w/
OXIDATION
NOT PLASTICS
TYPE I w/o
OXIDATION
NOT PLASTICS
NOT
TYPE I
INF(l) EFF INf(1) EFF INF (1) EFF INF<1) ฃFF
FLOW FLOW FLOW FLOW FLOW FlOW FLOW FLOW
MGD MGO f.'iGD MGO f.'GO MGO MGO MGO
MAXIMUM 10.700
MEAN 0.530
MINIMUM 0.0 00
MEOIAN 0.012
NUMBER OF
OBSERVATIONS 29
S.329 . 4.
1.009 . 0.
0.000 . 0.
0.271 . 0.
20
030 . 2.600
175 . 0.500
000 . 0.001
152 . 0.119
14 14
(1) Since effluent flow for these plants is by definition zero, influent flows
are presented
-------
should be noted that the number of streams does not correspond to the
number of plants due to the existence of multi-stream plants.
WASTEWATER CHARACTERIZATION
A number of different pollutant parameters are used to characterize
wastewater discharged by OCPS facilities. These include:
1. Biochemical Oxygen Demand (BOD)
2. Suspended Solids (TSS)
3. pH
4. Chemical Oxygen Demand (COD)
5. Total Organic Carbon (TOC)
6. Oil and Grease (O&G)
BOD is one of the most important gauges of the pollution potential of a
wastewater and varies with the amount of biodegradable matter which can
be assimilated by biological organisms under aerobic conditions. Large,
complex facilities tend to discharge a higher BOD mass loading, although
concentrations are not necessarily different from smaller or less com-
plex plants. The nature of specific chemicals discharged into wastewa-
ter affects the BOD due to the differences in susceptability of differ-
ent molecular structures to microbiological degradation. Compounds with
lower susceptability to decomposition by microorganisms tend to exhibit
lower BOD values even though the total organic loading may be much
higher than compounds exhibiting substantially higher BOD values.
Raw wastewater TSS is a function of the products manufactured and their
processes, as well as the manner in which fine solids that may be re-
moved by a processing step are handled in the operations. It can also
be a function of a number of other external factors including stormwater
runoff, runoff from raw material storage areas, and landfill leachates
which may be diverted to the wastewater treatment system. Solids are
frequently washed into the plant sewer and removed at the wastewater
treatment plant. The solids may be organic, inorganic or a mixture of
both. Settleable portions of the suspended solids are usually removed
in a primary clarifier. Finer materials are carried through the system,
and in the case of an activated sludge system, become enmeshed with the
biomass where they are then removed with the sludge during secondary
clarification. Many of the manufacturing plants show an increase in TSS
after wastewater leaves the treatment plant. This characteristic is
usually associated with biological systems and indicates an inefficiency
of secondary clarification in the removal of secondary solids. However,
in plastics and synthetic materials wastewaters, formation of biological
solids within the treatment plant may cause this solids increase due to
the low strength nature of the waste.
Raw wastewater pH can be a function of the nature of the processes con-
tributing to the waste stream. This parameter can vary widely from
plant to plant and can also show extreme variations in a single plant's
raw wastewater, depending on such factors as waste concentration and the
portion of the process cycle discharging at the time of measurement.
Fluctuations in pH are readily reduced by equalization followed by a
neutralization system, if necessary. pH control is important regardless
108
-------
of the disposition of the wastewater stream (i.e, indirect discharge to
a POTW or direct discharge) to maintain favorable conditions for biolog-
ical treatment organisms.
COD is a measure of oxidizable material in a wastewater as determined by
subjecting the waste to a powerful chemical oxidizing agent (such as di-
chromate) under standardized conditions. Therefore, the COD test shows
the presence of organic materials that are not susceptable to attack by
biological microorganisms. As a result of this difference, COD values
are almost invariably higher than BOD values for the same sample. The
COD test cannot be substituted directly for the BOD test because the
COD/ BOD ratio is a factor which is extremely variable and is very de-
pendent on the specific chemical constituents in the wastewater. How-
ever, a COD/ BOD ratio for the wastewater from a single manufacturing
facility can be established. This ratio is applicable only to the
wastewater from which it was derived and cannot be utilized to estimate
the BOD of another plant's wastewater. It is often established by plant
personnel to monitor process and treatment plant performance with a min-
imum of analytical delay. As production rate and product mix changes,
however, the COD/BOD ratio must be revalidated for the new conditions.
Even if there are no changes in production, the ratio should be recon-
firmed periodically.
TOC measurement is another means of determining the pollution potential
of wastewater. This measurement shows the presence of organic compounds
not necessarily measured by either BOD or COD tests. TOC can also be
related to the BOD and COD by ratio, but it too is only applicable to
the specific wastewater for which the ratio is derived. TOC determina-
tion is also useful for day-to-day control of treatment operations.
Oil and grease determinations do not measure the quantity of a specific
substance but measure substances whose common characteristic is their
solubility in freon. Treatment of oil and grease involves dissolved air
flotation and skimming practices. If these procedures are implemented
and efficiently used and maintained, oil and grease values should be
substantially lowered. Therefore, plants discharging high oil and
grease values may reflect limited use of available treatment technol-
ogies and limited source controls for oil and grease abatement.
Tables 6-3 through 6-10 present raw wastewater characteristics for each
of the four proposed subcategories. Minimum, maximum, mean and median
concentration values as well as mass loading in pounds per day for all
pollutant parameters of interest (BOD, TSS, COD, TOC and 0&G) are pre-
sented for direct discharge plants and zero or alternative discharge/
disposal facilities.
Each set of observations shown in Tables 6-1 thru 6-10 should be consid-
ered a separate data subset, independent of other data subsets pre-
sented. Calculations which involve more than one data subset (i.e.,
determining BOd/COD ratios) may not be meaningful, since data subsets do
not reflect the same group of plants. Similarly, multiplying the median
concentration for some parameter by the mean flow will not correspond to
the median pounds for that parameter.
109
-------
TABLE 6-3
RAW WASTEWATER CHARACTERISTICS - PLASTICS ONLY SUBCATEGORY
DIRECT DISCHARGERS ONLY
INF
BOO
MG/l
1 Nf
BOO
LB/OAY
INF
TSS
tAG/1
INF
TSS
LB/DAY
INF
CCD
MG /1
IUF
cc.l
LLI/OAY
INF
TCC
MC/l
INF
TOC
IB/DAY
IMF
OSG
>V-G/ t
INF
0ฃG
L 0/OA Y
MAXIMUM
3520.0
25262.0
209B.0
16082.3
4338.0
51392.6
2751 .0
5560.8
242.0
2355. 7
MEAN
506.2
3693.4
394 . 4
2263.0
1101.6
03 1 5 . 9
705.4
1720.7
82.3
7 10.8
MINIMUM
2.0
13.0
5.0
1 .5
27.0
60.5
9.0
13.0
23.0
72.9
MEDIAN
349.0
1985.0
80.0
803.3
857 .0
4869.5
362.0
949.9
32.0
207.3
NUMBER OF
OBSERVATIONS
19
49
42
42
45
15
8
8
4
4
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See last paragraph page 109.)
-------
TABLE 6-4
RAW WASTEWATER CHARACTERISTICS - PLASTICS ONLY SUBCATEGORY
ZERO DISCHARGE/ALTERNATIVE DISPOSAL ONLY
INF
000
M G/ I
INF
000
LB/OAY
INF
TSS
mg/l
INF
TSS
LB/OAY
INF
COO
r.-G/l
l\F
COO
L 15/DAY
INF
TOC
VG/ L
INF
TOC
10/0AY
INF
OSG
f.'G/L
I NF
OSC
L0/DAY
maximum
12542.0
4 174.0
1055.0
35 1 . 1
1 8549.0
6173. 1
1930.0
201 .6
.
.
MEAN
4110.7
1232.3
317.7
105.G
5303.4
2060 . 4
923.0
02.3
MINIMUM
300 .0
111.7
0.3
1 . 7
40.0
6.0
31.0
16.0
MEDIAN
1370.0
327.6
237.0
29. 1
1422.0
1107.4
800.0
26. G
NUMBER OF
OBSERVATIONS
6
6
5
5
5
5
3
3
0
0
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See last paragraph page 109.)
-------
TABLE 6-5
RAW WASTEWATER CHARACTERISTICS -
TYPE I WITH OXIDATION SUBCATEGORY
DIRECT DISCHARGERS ONLY
INF
INF
I Nl-
INF
I\'F
I MF
INF
INF
INF
INF
BOD
BOO
T'jS
TSS
COD
COO
TOC
TOC
OSG
OfiG
MG/L
LB/OAY
MG/L
LB/DAY
MG / L
L D/OAY
MG/ L
LB/DAY
MG/L
LB/DAY
MAXIMUM
5961 . 0
249714.3
4110.0
34195.2
2 1 1 70 . C
202706.2
3202.0
115196. 9
17.4
351.8
MEAN
1702.1
25975.2
441.6
3949 . 8
4414.6
40363.9
836 . 4
24792.7
11.4
180.1
MINIMUM
43.0
939. 7
9.0
19.0
53 . 0
1409.6
20.0
49.9
O . 0
42 . 1
MEDIAN
1036.5
13289.5
72.0
672 .9
3302.5
19714.5
513.0
13334.0
16.0
146.4
NUM3ER OF
OBSERVATIONS
42
42
21
21
34
34
21
21
3
3
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See last paragraph page 109.)
-------
TABLE 6-6
RAW WASTEWATER CHARACTERISTICS -
NOT PLASTICS TYPE I WITH OXIDATION SUBCATEGORY
ZERO DISCHARGE/ALTERNATIVE DISPOSAL ONLY
INF
D00
r.'G/ L
INF
000
L0/DAY
INF
TSS
MG/L
I NF
TSS
LB/DAY
INF
COO
MG / L
INF
COO
'-B/0AY
I NF
TOC
(V.G / L
INF
TOC
LB/DAY
INF
oeG
MG / L
INF
0ฃG
LB/OAY
MAXIMUM
52551 . 0
3 7 4 100.5
<159.0
7994.6
67 0S5.0
592650.2
11006.0
20182G.6
539.0
5829.8
MEAN
14532.1
71520.6
207 . 7
4150. 1
264/) 1 . A
147305.G
5746 .0
05417.3
539 .0
5029.0
MINIMUM
450.0
2566.9
61.0
659.0
960 . 0
7474.0
202.0
21BQQ.1
539.0
5829.0
MEDIAN
6022.0
20550.7
103.0
3796.0
23744.0
74S23.0
5049.5
56977.2
539.0
5829.8
number OF
OBSERVATIONS
7
7
3
3
9
9
4
4
1
1
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See last paragraph page 109.)
-------
TABLE 6-7
RAW WASTEWATER CHARACTERISTICS -
NOT PLASTICS TYPE I WITHOUT OXIDATION SUBCATEGORY
DIRECT DISCHARGERS ONLY
INF
000
MG/l
INF
BOD
L13/ DA Y
INF
TSS
MG/ L
I NF
TSS
LO/OAY
INF
COO
MG /1
INF
COO
LQ/OAY
IMF
TOC
MG / I
INF
TOC
L0/OAY
INF
OSG
MG/ l
INF
OSG
18/0AY
i.'ftX I mum
2725.0
30913.0
2 666.0
16925.5
32476.0
71448.0
5226.0
31009.9
570 .0
591.2
MEAN
783.6
9384 . 2
17 9.7
2624 . 7
4782 . 5
11902.2
940.8
6343.8
335 .0
365.1
MINIMUM
9.0
6.0
1 .0
0.7
23.0
18.6
66.0
342 . 1
17.0
91 .8
MEDIAN
467 .0
5621.3
170.0
594 . 0
1022.0
6139.0
272 . 0
2109. 1
418.0
410.2
NUMBER OF
OBSERVATIONS
21
21
13
13
15
15
1 1
1 1
3
3
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See last paragraph page 109.)
-------
TABLE 6-8
RAW WASTEWATER CHARACTERISTICS -
NOT PLASTICS TYPE I WITHOUT OXIDATION SUBCATEGORY
ZERO DISCHARGE/ALTERNATIVE DISPOSAL ONLY
I HF
INF
INF
1 N F
INF
INF
INF
1 NF
INF
SOD
000
TSS
TSS
COD
coo
TOC
TOC
OSG
MG/L
LB/DAY
MG/ L
L13/DAY
,1'G / L
L0/DAY
MG/ L
LB/DAY
MG/L
MAXIMUM
3014.0
7597.0
267 . 0
7 5!3 . 3
1 1 966.0
29067.1
364 . 0
663 . 2
.
MEAN
1019.0
2110.0
106. 3
397 . 2
3600.5
0726.6
223.0
523. 1
MINIMUM
o
CN
<7
29.7
32.0
B2 .4
14.0
9.9
130.0
411.0
MEDIAN
195.0
1007.1
63.0
375.6
1211.0
2 514.6
1 75.0
495.0
NUMBER OF
OBSERVATIONS
4
4
4
4
4
4
3
3
0
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See last paragraph page 109.)
-------
TABLE 6-9
RAW WASTEWATER CHARACTERISTICS -
NOT PLASTICS NOT TYPE I SUBCATEGORY
DIRECT DISCHARGERS ONLY
INF
130D
AUG/I
1 N F
000
LG/DAY
IN^
TSS
RIG/I
IMF
TSS
10/DAY
I \r
cco
11
INF
cco
IP/OAY
1 wr
TCC
iV G / I
I N F
TOC
lB/DAY
INF
OSG
MG/L
INF
0ซC
10/OAY
MAXIMUM
1 743 . 0
59901.0
1 2G6.0
36940 . 6
549a
. 0
66653.0
1455.0
6 <) 5 6 3 . 2
420.0
6900 . B
MEAN
421.7
9035 . 4
456.5
7303.6
1 623
.5
15229.4
376.6
10759.9
235.0
3606.9
MINI MUM
95.0
435.4
17.0
14.9
2 I '3
. 0
223 .7
35.0
72 . 0
50.0
225 . 1
MEDIAN
310.0
3083.9
138.0
1 723.4
590
. 0
5099 . 1
104.5
1992.7
235 .0
3606.9
number of
OBSERVATIONS
1 1
1 1
13
1 2
1 3
13
0
8
2
2
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See last paragraph page 109.)
-------
TABLE 6-10
RAW WASTEWATER CHARACTERISTICS -
NOT PLASTICS NOT TYPE I SUBCATEGORY
ZERO DISCHARGE/ALTERNATIVE DISPOSAL
INF
INF
I NF
\ur
INF
INF
INF
INF
I NF
INF
BOD
000
T S 5
TSS
COO
COD
TOC
TOC
OSG
O/.G
MG/L
LB/DAY
MG/t.
LO/OAY
MG/L
10/DAY
MG/ L
L 0/OAY
MG/ I
10/OAY
MAXIMUM
113 9.0
5046.0
33170.0
183043.3
27872.0
154/142.1
9592.0
1 197. 1
286.0
6 106.0
ME AH
631 .0
1997.5
10230.3
46790.1
9 00 U . 0
37921.0
4076.5
660 . 2
206.0
6106.0
MINIMUM
193.0
1 67 . 0
81.0
70. 1
546.0
472.4
161.0
1 39. 3
286.0
6106.0
MEOIAN
261 .0
179.6
3031 .0
1639.5
2956.0
2607.0
4876.5
666 . 2
286.0
6186.8
NUMBER OF
OBSERVATIONS
3
3
4
4
5
5
2
2
1
1
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See last paragraph page 109.)
-------
SECTION VII.
CONTROL AND TREATMENT TECHNOLOGIES
GENERAL
This chapter addresses control and treatment technologies currently used
or available to the OCPS industries for BPT. The treatment methodol-
ogies presented in this section are divided into in-plant technologies,
including source control and in-plant treatment, and end-of-pipe (EOP)
technologies.
Wastewaters from the OCPS industries are disposed of by one of three
methods: (1) direct discharge, (2) indirect discharge, and (3) zero or
alternative discharge. Direct discharge refers to the release of treat-
ed or untreated wastewater to a receiving stream. Indirect dischargers
transport wastewater to a publicly owned treatment works (POTW). Zero
or alternate discharge refers to situations in which generated wastewa-
ter is either disposed of on plant property or transferred to an alter-
nate location where it is disposed of on-site or discharged after treat-
ment .
Table 7-1 lists the zero or alternate discharge practices and the prin-
cipal direct discharge end-of-pipe treatment technologies reflected by
the Summary Data Base. The principal disposal/treatment practices are
grouped by the number of waste streams and the number of plants for the
four potential subcategories discussed in Section IV.
A total of 71 plants are single stream zero or alternate dischargers,
and 23 plants are multiple stream zero or alternate dischargers. The
largest group of plants in the data base are the 157 single pipe direct
dischargers. Five other plants have multiple direct discharge streams.
An additional 33 plants have both zero or alternate and direct discharge
streams. The disposal method used at 2 plants could not be determined.
Although the Summary Data Base was only developed for direct and zero or
alternative discharge, six plants are currently indirect dischargers be-
cause they have diverted their effluents to a POTW. Data collected at
these plants while they were direct dischargers has been retained in the
Summary Data Base.
IN-PLANT SOURCE CONTROLS
In-plant source control refers to process or operating techniques used
to either reduce the quantity or improve the quality of a waste stream
within a plant. Some in-plant control methodologies are capable of
completely eliminating a waste stream, while others recover valuable
by-products of the manufacturing process.
In-plant controls provide several advantages. Beyond the potential for
recovery of saleable material, in-plant control may reduce EOP treatment
plant costs, which often offset the in-plant treatment costs. In-plant
control can also remove pollutants inhibitory or not amenable to EOP
treatment schemes.
119
-------
TABLE 7-1
PปTNCIPLE TREATMENT/DISPOSAL practice
1 1
1
NOT PL
STICS 1
NOT PLASTICS II
NOT PLASTICS 1
ALL
HASTE 1
1 1
ปDI3- PRINCIPAL 1
PLA3TIZ
9 ONLY 1
TVPE
I C* 1
type I
NOT C**l
NOT TYPE I 1
STREAMS 1
NO, OF I
IPOSaL designation t
NO, OF 1
NO. OF 1
NO. OF
NO, OF 1
NO. OF
NO. OF 11
NO, OF
NO, OF 1
NO, OF
ICOOE 1
PLANTS '
NaSTE I
PLANTS
WASTE 1
PLANTS
waste II
PLANTS
HASTE 1
PLANTS
maSTE 1
1 t
STREaMSI
STREAMSI
STREAMS!1
STREAMSI
STREAMSI
1 ZERO DISCHARGE 1
1
1
i
I 1
II
1
1
1 6RN INCINFRaTION I
3 t
10 1
2
11 1
1
1 II
1
2 1
T
24 I
1 CON CONTRACT HAUL 1
t! t
1* 1
0 1
1
3 11
3
3 i
15
22 |
1 OPm deep WELL 1
2 1
3 1
12 1
0
6 I I
3
4 1
7
27 I
1 DRY DRV PROCESS (REPORTED) |
12 1
15 1
1
11 1
4
4 1 1
3
S 1
20
35 I
1 EVP evaporation t
2 1
2 t
0
0 1
0
0 1 1
0
0 1
2
2 |
1 IMP IMPOUNDMENT 1
3 1
7 1
4
5 1
3
* 1 1
2
2 1
12
IB |
1 LAP LAND APPLICATION I
3 1
3 I
0 I
0
0 1 1
0
0 1
3
3 1
1 0F3 OFF-SITE TREATMENT |
t 1
t 1
2
2 1
0
0 11
1
3 1
4
4 I
i PTE RECYCLE 1
* 1
10 1
11
11 1
2
2 11
2
2 1
24
25 I
| |
* i
ป |
mmmmm
mmmmm
|
1 TOTAL ZERO 1
At 1
47 1
ฆ
22
52 1
ฆ
11
20 11
11
IS
23 1
i
94
162 1
1 DIRECT DISCHARGE I
l
1
i
1
i
ฆ i
11
11
i
1
1
1 ALA AERATED LAGOON 1
6 1
B 1
9
i
9 1
4
4 1 1
s
4 1
24
27 1
1 ANL ANAEROBIC 1
0 1
0 I
2
2 1
0
0 II
0
0 I
2
2 I
1 APL AEROBIC LAGOON |
2 1
3 1
0 1
1
1 II
1
1 1
4
5 1
1 A3L ACTIVATED SLUDGE 1
AO 1
40 1
40
42 1
14
IS 1 1
10 1
104
107 1
1 0*Y UNOX I
0 1
0 1
0
0 1
2
2 II
1
1 1
3
3 1
1 BBC ROTATING BIOLOGICAL CONTACTOR)
A |
4 |
0
0 I
0
0 II
0
0 I
4
* I
1 TRF TRICKLING FILTER 1
1 1
1 1
0
0 1
i
1 II
1
1 1
3
3 1
1 -ซปซ |
|
mmmmm
a |
||
mmmmm
mmm-m
_ |
1 TOTAL BIOLOGICAL 1
55 I
56 1
51
53 1
ฆ
22
21 II
ฆ 1
IB
14 1
ฆ
144
151 1
1 |
1 aCR ACTIVATED CARBON |
0 1
1
1
1
i
1 t
2
1 1
3 II
3
i
3 1
6
7 1
1 CLR CLARIFICATION |
5 t
7 1
0
0 i
1
1 II
2
2 1
6
to 1
i daf dissolved air Floatation ป
0 1
0 1
0
0 1
0
0 I 1
1
1 1
1
1 1
| mmp multi-media filtration |
0 1
0 1
1
1 1
0
0 II
0
0 1
1
1 1
1 NEU NEUTRALIZATION 1
0 1
1 1
0
0 1
3
3 II
4
6 1
4
10 1
1 ols oil ซATE* SEPARATION 1
2 1
5 1
2 1
0
0 I 1
1
2 1
4
9 I
1 PCF PPT.,COACULATION,FILTRITION |
1 1
1 1
0
0 1
2
2 II
0
0 1
3
3 1
1 S3* SKIMMING 1
3 1
3 1
0
0 1
1
1 II
0
0 1
4
4 1
1 sift STEam STRIPPING 1
0 1
0 ป
1
1 1
0
0 1 f
2
2 t
3
3 ป
1 1
**-- |
ฆ |
1 TOTAL NON-BIOLOGICAL I
II 1
17 1
4
5 I
9
10 | 1
15
39
48 1
1 NOT NO TREATMENT 1
0 1
4 1
3
* 1
2
2 1 1
1
1 1
10
13 1
1 UN* UNKNOWN I
2 1
2 1
0
1 1
0
0 I 1
0
0 1
2
3 1
I GRAND TOTAL 1
118 1
14* |
BO
117 1
44
55 11
49
59 1
201
377 1
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
Many of the newer chemical manufacturing plants are being designed with
a reduction in water use and consequent minimization of contamination as
part of the overall planning and plant design criteria. In addition,
improvements have been made in existing plants to control pollution from
their manufacturing processes and other activities, prior to discharge.
In-plant source controls that have been effective in reducing pollution
loads in the OCPS industries are described in the following paragraphs.
Process Modification
Older plants were sometimes designed without regard for raw material or
water conservation. As costs have increased and local environmental
regulations have become more stringent, some plants have modified their
manufacturing processes. For example, plants which once used batch
processes have gone to continuous operation. By doing so, wastewaters
containing spent solvents or caustic which are generated by between
batch cleanup are eliminated. As a consequence, production yields
increase and overall wastewater generation is reduced.
Instrumentation
An important source of pollutant loading in the OCPS industries is occa-
sional process upset resulting in discharge of products, raw materials
or by-product. For example, reaction kettles occasionally become over
pressurized, resulting in a burst rupture-disc and subsequent discharge.
The in-plant control best suited to eliminate these occurrences is the
installation of more sophisticated instrumentation. Alarms, pH and flow
sensors and similar devices are capable of early detection of process
upsets. Use of this type of instrumentation, coupled with added opera-
tor training, can measurably reduce pollutant loading.
Solvent Recovery
The recovery of waste solvents has become a common practice among plants
using solvents in their manufacturing processes. However, several
plants have instituted further measures to reduce the amount of waste
solvents discharged. Such measures include incineration of solvents
that cannot be recovered economically, incineration of bottoms from sol-
vent recovery units, and design and construction of better solvent re-
covery columns to strip solvents beyond the economical recovery point.
The economical recovery point has been reached when the cost of recover-
ing additional solvent (less the value of the recovered solvent) is
greater than the cost of treating or disposing of the remaining waste
solvent.
Water Reuse, Recovery, and Recycle
The use of barometric condensers can result in significant water contam-
ination, depending upon the nature of the materials entering the dis-
charge water streams. As an alternative, several plants use surface
condensers to reduce hydraulic or organic loads.
121
-------
Water-sealed vacuum pumps often create water pollution problems. Sev-
eral plants use a recirculation system as a means of greatly reducing
the amount of water being discharged.
Reduction of once-through cooling water by recycling through cooling
towers is a common industrial practice which results in a decreased
total discharge volume. Stormwater runoff from manufacturing areas can
contain significant quantities of pollutants. Separation of stormwater
from process wastewater has been practiced throughout the industry and
often facilitates the isolation and treatment of contaminated runoff.
Process modifications allowing for enhanced wastewater recycle have also
been applied within the OCPS industry. Twenty-four facilities in the
291 plant Summary Data Base indicate that, through wastewater recycle,
they achieve zero discharge.
IN-PLANT TREATMENT
Besides implementing source controls to reduce or eliminate the waste
loads generated within a manufacturing process, another alternative is
available. In-plant treatment is directed toward removing certain pol-
lutants before they are combined with the plant's overall wastewaters
and consequently diluted. In a general sense, in-plant treatment proc-
esses are designed to treat specific waste streams. Although in-plant
technologies can remove a variety of pollutants, they are usually de-
signed to treat toxic or priority pollutants.
Generally speaking, in-plant treatment is employed to avoid undesirable
impacts on a plant's end-of-pipe (EOP) treatment. Indirect dischargers
may utilize in-plant treatment to remove components which could detri-
mentally affect the POTW, or materials which could pass through a POTW
without receiving adequate treatment. In-plant treatment is also used
to take advantage of the more efficient treatment of low volume, con-
centrated and homogenous waste streams generated by specific unit
operations.
The basis for any decision to employ in-plant treatment is governed by
the presence of:
- Pollutants toxic to the biota of an EOP biological treatment
system.
- Biologically refractive pollutants.
- Highly concentrated pollutants.
- Pollutants that may offer an economic recovery potential
(solvent recovery).
- Pollutants that are hazardous if combined with other chemicals
downstream.
- Pollutants generated in small volumes in remote areas, precluding
conveyance to centralized treatment.
122
-------
- Corrosive pollutants that are difficult to transport.
- Pollutants that would contaminate EOP waste sludge, limiting
disposal options.
Many demonstrated technologies are available for the removal of specific
pollutants found in the wastewaters from organics and plastics manufac-
ture. The selection of a specified in-plant treatment scheme depends
both on the nature of the pollutant to be removed and on the engineering
and cost comparisons of the options available.
The following paragraphs provide brief summaries of technologies either
in use as in-plant treatment technology, or available to the OCPS indus-
try. In that in-plant treatment is primarily us^ed to remove toxic mate-
rials (i.e., metals, cyanide, solvents, etc.), tiie reader is referred to
the BAT Development Document for further details on these treatment
processes.
Activated Carbon Adsorption
Adsorption on granular activated carbon (GAC) is an effective, and more-
over, a commercially established means of removing dissolved organic
species from aqueous waste streams. Contaminants are removed from sol-
ution by a three-step process involving (1) transport to the exterior of
the carbon, (2) diffusion within the pores of the activated carbon, and
(3) adsorption on the interior surfaces bounding the pore and capillary
spaces of the activated carbon. Eventually the surface of the carbon is
saturated. When this occurs, replacement of the adsorber system with
fresh (i.e., virgin or reactivated) carbon is required.
Both powdered activated carbon (PAC) and GAC are capable of efficiently
removing many pollutants, including toxic and refractory organics. Pow-
dered carbon is most frequently added to biological treatment processes
and is not recovered.
Table 7-2 was taken from a recently published study ^ ^ of carbon
adsorption systems which have been in use in the chemical industry.
The table lists more than 100 examples of full scale activated carbon
adsorption systems.
Metals Removal
Heavy metals are of importance since their presence even at very low
levels can inhibit biological activity and thereby lower the efficiency
of the biological treatment system.
Technologies are well established for a number of metals removal meth-
ods. Hydroxide and sulfide precipitations, for example, are the most
common methods of metal ion removal used. Many metals ions form insol-
uble hydroxides and sulfides at a high pH when treated with either
caustic soda, lime, or soluble sulfides. The precipitates may be re-
moved from the waste stream by such methods as settling or filtration.
Other technologies applicable to metals removal are ion exchange and
123
-------
TABLE 7-2 (Continued)
Crompton and Knowles Corp. Gibraltar, PA
Diamond Shamrock
Dow Chemical
Du Pont
Houston, TX
Gales Ferry, CT
Plaquemine, LA
Midland, MI
Beaumont, TX
Richmond, Va
Belle, WV
EPA Emergency Response Unit Mobile Unit
Fike Chemical
Nitro, WV
First Chemical Corp.
FMC
General Electric
Georgia Pacific
Hardewicke chemical
Hercules, Inc.
Hooker
Houston Chem. Div. of PPC
Pascagoula, MS
Baltimore, MD
So. Charleston, WV
Nitro, WV
Middleport, NY
Bayport, TX
Pittsfield, MA ,
Fort Edwards, NY
Selkirk, NY
Conway, NC
Elgin, SC
Hattiesburg, MS
Hahnville, LA
Beaumont, TX
Goldsboro, NC
Burlington, 1A
Joliet, IL
Parsons, KS
Dyes
Pesticides
Plastics and resins
Organic chemicals
Phenol, acetic acid
Pharmaceutical chems.
Textile fibers
Organic chemicals
Chemical spill cleanup
Speciality organic
chemicals
Aniline, nitrobenzene,
nitrotoluene
Pesticides
Organic chemicals
Organic chemicals
Pesticides
Plasticizers, glycerin
Plasticss and resins
Plastics and resins
Phenolic resins
Specialty organic
chemicals
Terpen oils,
hydrocarbon resins
Ethylene glycol,
ethylene dibromide
Pesticide research
Explosives
Explosives
Explosives
ICI Americas
Iowa Army Ammunition Plant
Joliet Army Ammunition Pit
Kansas Army Ammunition Pit
125
-------
TABLE 7-2
COMPANIES REPORTED TO HAVE EXPERIENCE WITH FULL-SCALE
GRANULAR ACTIVATED CARBON SYSTEMS
[7-5]
Company
Alkcolac
Allied Chemical
Location
Sedalia, MO
Fairfield, AL
South Point, OH
Frankford, PA
Buffalo, NY
Syracuse, NY
Hopewell, VA
Moundsville, WV
Amerada Hess a
American Aniline a
American Color and Chemical Lockhaven, PA
American Cyanamid
Atlantic Richfield0
Atlantic Richfield/
Polymers, Inc.
BASF Wyandotte
Beckman Instrument Co.
Borden, Inc.
British Petroleum Corp.
C. M. Masland
Ciba Geigy
Bound Brook, NJ
Carson, CA
Monaca, PA
Geismar, LA
Washington, NJ
Porterville, CA
Bainbridge, NY
Marcus Hook, PA
Waskefield, RI
St. Gabriel, LA
124
Principal Product
Surface active agents
Creosote oils, tars,
pitches
Formaldehyde
Organic chemicals
Inorganic chemicals
Monochlorobenzene,
o-dichlorobenzene
Organic chemicals
Toluene diisocyanate,
methylene dianiline
Refinery products
b
Dyes
Organic chemicals
Refinery products
Diethylebenzene,
divinyl benzene
Chlorine, hydrogen,
sodium hydroxide
Polypropxy ethers,
polypropylene glycol
Plastics and resins
Refinery products
Textiles
Pesticides
-------
TABLE 7-2 (Continued)
Liquified Coal Development Captina, WV Anthracene-derived
Corp. solvents
Lone Star Army Ammunition Texarkana, TX Explosives
Plant
Louisiana Army Ammunition
Plant
Shreveport, LA
Explos ives
Matlack
Swedesboro, NJ
Tank truck washing
Mob ay
Cedar Bayou, TX
Organic chemicals
New Martinsville, WV
Isocyanates, polyols,
polyesters
Monsanto
Anniston, AL
Sauget, IL
St. Louis, MO
Alvin, TX
Texas City, TX
Luling, LA
Nitro, WV
Polynitrophenol
Organic chemicals
Organic chemicals
Organic chemicals
Organic chemicals
Cyclohexanol
Pesticides
Neville Chemical
Neville Island, PA
Plastics, resins
Olin Corp.
Mcintosh, AL
Bradenberg, KY
Rochester, NY
Ashtabula, OH
Pesticides
Organic chemicals
Organic chemicals
Organic chemicals
Owens Corning
Anderson, SC
Plastics and resins
Palisades Industries
Peace Dale, RI
Textiles
Pennwalt
Houston, TX
Organic chemicals
Pfizer Chemical
Terrahaute, IN
South Port, NC
Brooklyn, NY
Greensboro, NC
Pharamaceutical chems.
Citric acid
Organic chemicals
Organic chemicals
Proctor and Gamble
Chicago, IL
Baltimore, MD
Kansas City, KS
Dallas, TX
Fatty acids
Fatty acids
Fatty acids, alcohols
Fatty acids
Reichhold Chemicals
Tuscaloosa, AL
Phenol,
pentaerythritol, resins
Republic Steel
Cleveland, OH
126
Coke
-------
TABLE 7-2 (Continued)
Rhodia (Rhone-Poulenc)
Freeport, TX
Portland, OR
Rocky Mountain Arsenal Denver, CO
Rogers Corporation Manchester, CT
SCA Chemical Waste Services Lewiston, NY
Schenectady Chemical Schenectady, NY
Sherwin Williams Co.
Stauffer Chemical
Stepan Chemical
Stephen-Leedom Carpet
Tooele Array Ammunition Pit
TRA
Union Carbide
Chicago, 1L
Bucks, AL^
Lemoyne, AL
Richmond, CA
Dominguez, CA
San Jose, CA
Delaware City, DE
Louisville, KY
Geismar, LA^
Henderson, WV
Skaneateles Falls,NY
Galliopolis Ferry,WV
d
Green River, WY
Fieldsboro, NJ
Southhampton, PA
Tooele, UT
Irving, TX
Hahnville
Ponce, PR
Greenville, SC^
Woodbine, GA
Organic chemicals
Pesticides
Plastics and resins
Chemical waste disposal
Phenolic resins
Para-cresol
Sulfur
Pesticides
Inorganic chemicals
Flavor and fragrance
chemicals
Carbon disulfide
Organic chemicals
Organic chemicals
Detergents
Syn. lubricants,
plasticizers, esters
Detergent intermediates
Carpets
Explosives
b
Synthetic fibers
127
-------
Velvet Textile Co.
Vicksburg Chemical
TABLE 7-2 (Continued)
Blackstone, VA
Vicksburg, MS
Yorktown Naval Weapons Sta. Yorktown, VA
Unidentified (1)C
Unidentified (2)
Unidentified (3)
Unidentified (4)
Unidentified (5)
Unidentified (6)
Unidentified (7)
Unidentified (8)
Unidentified (9)
Unidentified (10)
Unidentified (11)
Unidentified (12)
Unidentified (13)
Text iles
Toxaphene, methyl
parathion
Explos ives
Pesticides
Organic chemcials
Explosives
Chlorobenzene,
dichlorobenzene
Toxaphne, DNBP,
cyanazine
Dalpon
2,4-D, 2,4-DB, MCPA
Parachloronitrobenzene,
terrazole
Dicofol
Trifluralin,
isopropanol,
ethalfluralin
DEET, piperonyl
butoxide, thanite
Carbofuran
Atrazine
a . ...
k Location not given in data source.
Information incomplete,
j Unit known to be shut down.
No plant listed at this location in 1979 Directory of Chemical
Producers.
e
Neither company nor location identified in data source.
128
-------
membrane processes such as reverse osmosis and ultrafiltration. These
technologies are normally employed by industry as in-plant treatment;
however, none were reported in the Summary Data Base.
Steam Stripping
Steam stripping is a variation of distillation whereby steam is used as
both the heating medium and the driving force for the removal of vola-
tile materials. For employment of steam stripping, steam is introduced
into the bottom of a tower. As it passes through the wastewater, the
steam vaporizes and removes volatile materials from the waste and then
exits via the top of the tower. Although most commonly employed as an
inplant technology for solvent recovery, steam stripping has been re-
ported as a wastewater treatment process. Data from three plants using
steam stripping as the primary treatment step are summarized in Table
7-3.
Liquid-Liquid Extraction
Liquid-liquid extraction (LLE) is a process that can separate certain
components from a solution by contacting the solution with an immiscible
liquid that has a higher solubility for the components of the solution
than it does for the solution contacted. LLE operating and capital ex-
penses involve the liquid-liquid contactor with its peripheral equipment
and the solvent regeneration equipment. Although liquid-liquid extrac-
tion is a common process operation, it is normally applied as an in-
plant treatment to utilize the highest available concentration gradient.
No data were available for LLE.
Oxidation
Oxidation as a treatment practice is accomplished by either wet or
chemical oxidation. Wet oxidation is a common process in which an
aqueous waste can be oxidized in a closed, high-temperature, high-
pressure vessel. Wet oxidation has been used to treat a variety of
wastes including pulping waste and acrylonitrile liquor. A percent
reduction in excess of 99.8 has been reported for some of the toxic
pollutants.[7-2] This process is applicable particularly as in-plant
and EOP treatments of wastes with a high organic content.
The application of chemical oxidation to industrial wastes is well
established for cyanides, sulfide, ammonia, and other such harmful sub-
stances in waste streams. Chemicals commonly used as oxidizing agents
include chlorine, hypochlorite, hydrogen peroxide, potassium permanga-
nate, ozone, and chlorine dioxide. Although several plants in the
Summary Data Base reported using chlorination as part of their EOP
treatment, it was used as a sterilizing medium rather than as a chemical
oxidation process.
No data were available for oxidation.
129
-------
TABLE 7-3
STEAK iTSJPPING, all H57E STREAMS
n
number of stkcams reporting this iechnoloc* as major wastehatcr trea tment 3
iff
flo *
MCO
0UO
INF
MG/L
BUD
EFF
MC/L
BOD
X
*ED
TS9
INF
MC/L
T 38
EPF
MC/L
133
X
Red
CUD
INF
M6/L
COO
EFF
MC/L
CUD
X
RED
UlG
INF
mg/l
016
Iff
MC/L
Olt
X
RE0
MAXIMUM
0.516
2)8,0
280.0
eซ.9
1190.0
140.0
98,5
.
ป
MEAN
0.375
2)6,0
112.0
ซซ,ซ
641,5
61.3
04,4
ซ
0,290
230,0
12.0
84.9
85,0
18.0
69.4
.
ฆ
.
MEDIAN
0.300
238.0
36.0
84.9
641.5
26.0
84.0
NUMBER of
OBSERVATIONS
3
1
1
1
2
3
2
0
0
0
0
O
0
STEAM
STRIPPING, all
WASTE
STREAMS
a
NUMBER OF STREAMS REPORTING THIS TECHNOLOGY as MAJOR WASTEWATER TREATMENTI 3
TOC
TOC
TOC
PhENOL
PHENQi.
PHENOL
Nhjn
NHJN
KH3N
CR
CR
CR
INF
EFF
I
INF
EFF
X
INF
EFF
X
INF
EFF
X
MG/L
MG/L
RED
MG/L
MG/L
RED
H5/L
MG/L
RE0
MG/L
HG/L
RED
MAM HUM
492,0
360,0
87,6
.
,
MEAN
492,0
145,3
87,6
ฆ
.
.
MINIMUM
492,0
15.0
87,6
.
.
.
MEDIAN
492,0
61.0
67.6
#
t
.
number of
OBSERVATIONS 131000000000
a These data a.e fi r. plants that use thi? technolr^v as the prirK-iDai corjv.nent of their
wastewater treatment system..
-------
END-OF-PIPE TREATMENT
End-of-pipe treatment refers to those processes that treat a combined
plant waste stream for pollutant removal prior to discharge. Adequately
designed, operated, and maintained EOP facilities allow manufacturers to
discharge their wastewater directly to a receiving body of water.
EOP technologies covered in this report are classified as primary, sec-
ondary and tertiary processes. Depending on the nature of the pollu-
tants to be removed and the degree of removal required, different com-
binations of the available treatment technologies may be used.
Primary treatment usually involves physical separation processes. These
technologies include clarifiers, oil skimmers, dissolved air flotation
and similar devices which may use flocculants to assist in the removals.
Depending on the nature of the suspended solids in the wastewater, this
treatment may remove a significant amount of the BOD attributable to
suspended solids or floating materials from industrial wastewaters.
Secondary treatment is utilized when the primary system cannot improve
the wastewater to a sufficient degree to permit discharge. Secondary
treatment usually consists of biological processes capable of removing
the soluble pollutant constituents. Biological processes are widely
used in industrial waste treatment and, as measured by BOD, are very
successful in removing biodegradable organics. Factors which influence
the design and operation of biological systems for industrial wastes
include the sensitivity of these systems to influent composition changes
and the potential inhibitory effects of certain industrial chemicals on
the microorganisms. Design techniques which accommodate such factors
are discussed in the section entitled "Design, Operation and Management
Practices."
Tertiary treatment refers to treatment following the biological or other
secondary treatment system. The technologies available for tertiary
treatment vary, but normally relate to the removal of specific pollutant
parameters not effectively removed in secondary treatment. Some ter-
tiary treatment unit processes are also applicable to in-plant or pri-
mary treatment schemes.
Primary Treatment
In the following paragraphs the primary treatment processes used by the
291 OCPS industry plants in the engineering data base are discussed.
Equalization - Equalization consists of a wastewater holding vessel or
pond large enough to dampen flow and/or pollutant concentration varia-
tion and permit a nearly constant discharge rate and wastewater quality.
The holding tank or pond capacity is determined by wastewater volume and
composition variability. The equalization basin may be agitated or may
utilize a baffle system to prevent short circuiting. Equalization is
employed prior to wastewater treatment processes that are sensitive to
fluctuations in waste composition or flow. No plants in the Summary
Data Base reported equalization as the only treatment technology used.
131
-------
However, 124 plants included equalization as a part of their total
treatment system.
Neutralization - Neutralization is practiced in industry to raise or
lower the pH of a wastewater stream. Alkaline wastewaters may be neu-
tralized with hydrochloric acid, carbon dioxide, sulfur dioxide, and,
most commonly, sulfuric acid. Acidic wastewaters may be neutralized
with limestone or lime slurries, soda ash, caustic soda, or anhydrous
ammonia. Often a suitable pH can be achieved through the mixing of
acidic and alkaline process wastewaters. Selection of neutralizing
agents is based on cost, availability, ease of use, reaction by-
products, reaction rates, and quantities of sludge formed.
Nine plants in the 291 plant Summary Data Base reported using neutral-
ization as their principal treatment method. In addition, 104 other
plants used neutralization as part of their treatment system.
Clarification - Clarification, in this context, may be defined as the
removal of solid particles from a wastewater through gravity settling.
The nature of the solids and their concentration are the major factors
affecting the settling properties.
Among plants in the Summary Data Base, eight employ clarification as the
principal component of their treatment system. Performance data for
these plants is presented in Table 7-4. In addition, 94 other plants
use some form of clarification as part of their treatment system, either
with or without the use of precipitation, coagulation or flocculation.
Precipitation/Coagulation/Flocculation - Gravity clarification may be
supplemented by precipitation, coagulation or flocculation providing en-
hanced suspended solids removal. Precipitation, coagulation or floccu-
lation may also be used as a primary treatment step to protect biologi-
cal secondary treatment processes from upset due to toxic metallic pol-
lutants .
Simple clarification is usually accomplished with standard sedimentation
tanks (either rectangular or circular). If additional solids removal,
removal of colloidal solids, or removal of dissolved metallic ions is
required, precipitation, coagulation or flocculation are added. Coagu-
lation is usually accomplished by adding an appropriate chemical (alum,
lime, etc.) followed by a rapid mix and finally a slow agitation to pro-
mote floe particle growth. A polymeric coagulant aid is sometimes used
in these systems.
A total of 3 plants in the Summary Data Base report using precipitation,
coagulation, or flocculation as the principal component of their treat-
ment system. Data reported for these systems is presented in Table 7-5.
A total of 15 plants use some form of coagulation as part of their
treatment system.
Flotation - Flotation is used to remove oils and other suspended sub-
stances with densities less than that of water or, in the case of dis-
solved air flotation, particles that may be slightly heavier than water.
As with conventional clarifiers, flocculants are frequently employed to
132
-------
TABLE 7- 4
CLA4iHCซ7iONt ALt milt SISfAMS
A
NUMBER U' 3TMEANS REPORTING THIS TECHsOLOST AS MAJOR KASUxATCR TREATmENTI 10
Iff SOD BOO ป00 TSS TSI TJS COD COD COO OIC OIC OIC
floซ inf ctr % [nr err t inr err t i*r trr t
"to "6/L Nc'l ปE0 "6/L Me/l Rfp "6/L Me/l "ED *6/1. Hj/L *ED
MAIIMUN
3.700
5H,ซ
lit.*
a.7
170.0
90.0
ซ.ป
1219.0
ซSS
a
42.7
l.t
MEAN
0.ปป7
1*0.ป
ซซ.ป
48.S
M.S
21.6
51.5
75.5
1*5
6
20.4
>.
MINIMUM
0.057
ซ.0
ซ.o
10.9
11.0
7.0
7.2
ซ2.o
ฆ 2
0
ซ.*
0.4
MEOJAN
0.144
89.5
17.
52.0
H.5
51.2
120.)
it
0
25.4
l.t
NUMBER OF
OBSERVATIONS I*
4
*
1
a
4
4
T
4
0
2
0
CO
U>
CLARIFICATION, ALL HASTE STREAMS
NUMBER or streams reporting thjs technoloc* AS MAJOl? xASTEhATER TREATmENTI 10
IOC
IOC
IOC PHENOL
phenol Phenol
nnjn
NHiN
NHJN CR
CR
CR
INF
eff
X INF
EFF X
INF
Iff
X INF
Iff
X
M6/L
HG/L
RED "C/l
HG/L Rฃ0
MG/L
HG/L
REO HG/L
MC/L
RED
maximum 1*3.0
115.0
17.5
,
. 1.5
0.3
99.2
MEAN 76.0
7.5
17.5
1.0
0.1
69.6
MINIMUM 9.0
17.0
17.5
t
0.5
0.0
40.0
MEDIAN 76.0
*7.5
17.5
ซ
1*0
0.0
69.6
NUMBER OF
OBSERVATIONS 2
2
1 0
0 0
0
0 0 2
3
2
a Those r'ata
arc fro
r. plants that use this technology
as
the principal
component of
inr-Ir
w.ijcr t.
rcacrcr.t cys
ten.
-------
TABLE 7- 5
FPT.iCOASUcATJGK.FILIRATIDI., ALL NA37E
a
NUMBER OF STREAKS REPORTINC THIS TECHNOIOCT AS MAJOR HASTEnATER TREATMENT! 3
iff
FlOซ
H6Q
BOD
INF
MS/L
BUD
tff
ms/l
BOD
I
Red
TSS TSS
INF EFF
M6/L *6/1
TSS
X
RED
COO
INF
Hfi/t
COO
EFF
MC/L
CUD
S
red
u&c
INF
MC/L
OtC
Iff
ซG/t
QIC
X
BED
maximum
12.100
62.0
~ 12.0
T2.ป
eoซ.o
S2J.0
mean
*2.0
J2ซ,5
Ti.t
. ซฐป.o
521.0
minimum
ซ,*00
ป2.ป
1T.0
72.*
523.0
MEDIAN
5.220
*2.0
124.J
72.*
. <06,C
523.0
number or
OBSERVATIONS 3
1
Z
I
2
0
0
1
0
0
0
0
fFT.,
COAGULATION,FILTRATION
ALL
hASTE
STREAM3
a
NUMBER OF STREAMS REPORTING THIS TECHNOLOGY A3 MAJOR ซปSTEnATER TRCATmENTI J
i i
i i
i i
i
i t
i i
t
ป t
i i
a i
i i
i ป
i
TOC IOC TOC PmEnOl PHENOL PHENOL
JNF IFF X INF EFF X
MC/L "C/L RฃD MC'L MC/l- RED
NM3N NH3N NH3N
INF EFF X
M&/L HG/L "ED
CW
INF
MG/
CH
EFF
HC/L
CR
X
RED
MAXIMUM
276.0 . 0,1
. 782.0
0.6
MEAN
276,0 . 0,1 .
762.0
0,6
mjkimum
ซ
276.0 . 0,1
. 782.0
0.8
MEDIAN
276*0 0*1
. 782.0
0.8
number of
OBSERVATIONS
0
t 0 0 I o
0 1 o
0 1
0
a These data are from plants that use this technology as
c?~pOPent of their wastewater treatnent svstem.
the
principal
-------
enhance the efficiency of the flotation units. Although flotation is
sometimes referred to in the context of dissolved air flotation, such
other technologies as oil/liquid skimming and solids skimming are also
flotation operations, and are sometimes an integral part of standard
clarification.
For the one OCPS industry plant having flotation as its primary method
of treatment, summary performance data is presented in Table 7-6. An
additional 6 plants use flotation as a part of their total treatment
system.
Secondary Treatment
Technologies classified as secondary treatment are generally biological
processes and serve the primary function of removing dissolved carbona-
ceous pollutants as represented by BOD, COD, and TOC measurements. Bio-
logical systems may also be designed to remove some nitrogenous pollu-
tants. Biological systems can remove limited amounts of heavy metals
and refractory organic toxic chemicals through adsorption, biomass up-
take and biodegradation, if properly acclimated to the waste. Neverthe-
less, these processes are usually designed to treat large quantities of
dissolved carbonaceous wastes and any other pollutant removal or treat-
ment is often incidental.
Biological Treatment - All biological treatment systems are designed to
expose wastewater containing biologically degradable organic compounds
to a suitable mixture of microorganisms, in a controlled environment
which contains sufficient essential nutrients for the biological reac-
tion to procede. Under these conditions the reduction of biologically
assimilable pollutants will take place in a reasonably predictable man-
ner. Biological treatment is based on the ability of mircoorganisms to
utilize organic carbon as a food source. The treatment is classified as
aerobic, anaerobic, or facultative. Aerobic treatment requires the
availability of free dissolved oxygen for the bio-oxidation of the
waste. Anaerobic treatment is intolerant of free dissolved oxygen and
can utilize "chemically bound" oxygen (such as sulfates) in breaking
down the organic material. Facultative organisms can function under
aerobic or anaerobic conditions as the oxygen availability dictates.
Although the definitions of the processes are distinct, in practice both
aerobic and anaerobic conditions may exist in the same treatment unit,
depending on degree of aeration, degree of mixing, effects of photosyn-
thesis, and other factors which contribute to the supply and distribu-
tion of oxygen to the treatment system. Facultative lagoons are de-
signed to utilize both aerobic and anaerobic mechanisms as a means of
reducing the net sludge production.
Biological treatment processes are widely used, and if properly designed
and operated, are capable of high BOD removal efficiencies. Such sys-
tems given sufficient reaction time, can reduce the concentration of any
degradable organic material to a very low concentration. Any organic
material which will respond to the standard BOD test procedure is by
definition a degradable substrate.
135
-------
TABLE 7^6
C;I5Cป.VL3 AiS FLOATAUC., A*.L XASiE _7f.ฃ- 3
NUMBER or B1REAMS REP0"THC 11IS TECHNOLOCT *1 MAJOR* ปปปIEซปTEซ TKEATMENTI 1
EFF
BOO
fiuo
BOD
T3S
TS9
TSS
COD
COD
COO
uic
016
oic
FlOซ
INF
tFF
X
INF
EFF
X
INF
EFF
X
INF
EFF
X
M CO
MS/L
*G/L
"ed
Mq/L
*C/l
Rฃ0
*C/L
mg/l
*ฃD
mc/l
M c/L
RED
MAXIMUM
8.15*
122.0
<2.0
162.0
ป
.
HE*N
O.IM
122,0
<2.0
162.0
.
*
MjWjMUM
0,3Jซ
122.0
.
2.0
.
162.0
.
MEDIAN
9.3H
122.0
<2.0
ฆ
ฆ
162.0
*
t
NUMBER or
OBSERVATIONS I010ซ|ซ0l000#
o->
ON
TOC
TOC
TOC
PHENOL
phenol
PHENOL
NHJN
NH3N
NMJN
CR
CR
CN
INF
EFF
I
INF
EPF
X
INF
EFF
X
INF
EFF
X
MG/l
HG/l
RED
MC/L
MC/L
RED
MG/L
MC/L
RED
MC/L
MC/L
RED
MAXIMUM
.
62.#
a
a
0.3
a
a
ป
.
2.0
.
mean
a
62.#
a
0.3
a
a
2.0
MINIMUM
62,
ฆ
a
ซ.3
*
a
.
.
a
2.0
.
MEDIAN
.
*2.*
0.3
ฆ
.
2.0
number of
OB3ERVATION3
ป
1
0
0
1
0
Q
0
0
0
1
0
a These data are from plants that use this technology as the principal component
of their wastewater treatment system.
DISSOLVED AIR FLOATATION, ALL HASTE STREAMS
NUH8ER or STREAMS REPORTING THJS TECHNOLOGY AS HAJORASTEWATER TREATMENTI 1
-------
It was previously noted in Section IV that properly designed and opera-
ted biological treatment systems will produce similar effluent BOD. con-
centrations even though influent BOD- concentrations may be significant-
ly different. This is illustrated by Figures 7-1 and 7-2. These fig-
ures were prepared by plotting the lognormal frequency distribution of
plants achieving various effluent BOD,, concentrations. The criteria, as
explained Later in this section, for establishing that a plant was well
designed and operated was defined by including data from only those
plants which achieved 95 percent BOD^ removal or which achieved effluent
BOD- concentrations of 50 mg/1 or less. Prior to graphing, the data was
sorted by influent BOD,, concentration into the four ranges shown in the
figure. The minimum, maximum, and median values for each set of data
are also shown. Figure 7-1 presents data from Plastics Only plants,
Figure 7-2 presents the data from all other plants for which influent
and effluent BOD^ concentrations were available, and which met the cri-
teria for being well designed and operated.
The figures illustrate that good effluent quality can be achieved over a
wide range of influent concentrations. For the Plastics Only plants,
median effluent BOD,, varies between 9 and 21 mg/1 although influents
range over two orders of magnitude. For OCPS plants producing products
other than Plastics Only, median effluent BOD- concentrations range from
10 to 20 mg/1 for influent B0D_ concentrations up to 1000 mg/1, and a
median effluent BOD- of 44 mg/l for influents greater than 1000 mg/1.
The higher median effluent obtained for influents greater than 1000 mg/1
does not necessarily indicate that high strength influents are any less
degradable than the lower strength influents previously presented. The
three lower plots in Figure 7-2 represent a relatively narrow range of
influent concentrations, specifically 0 to 1000 mg/1. The uppermost
plot presents data from 19 plants with influent BOD concentrations which
range from 1076 mg/1 to 5710 mg/1. Because of the signifcantly wider
range of influents in this group, the spread between minimum and maximum
effluent values does not necessarily contradict the theoretical assump-
tion that a similar limiting effluent concentration can be achieved.
Although the 19 plants with influent BOD concentrations greater than
1000 mg/1 generally achieve the highest percentage BOD removals, typi-
cally 96 to 98+ percent, they do not necessarily degrade the organic
material to the maximum degree possible. Without access to the design
basis for each of the 19 plants, it cannot be determined if the plant
was designed to achieve the maximum removal possible by a biological
system, or a specified level of treatment (i.e., some percentage of BOD
reduction) which was judged adequate for a specific site.
Although most biological systems can ultimately reduce effluent BOD to
similar limiting concentrations, the rate of reaction will depend on a
variety of design considerations. These considerations do limit the
direct transfer of design and operating conditions from one industrial
plant to another although the chemical product lines may be similar.
Techniques are available, however, to optimize design and operating
conditions to ensure adequate treatment for all industry wastes.
Biological systems operate most efficiently under so called "steady
state" conditions. Unfortunately, industrial wastewater is frequently
found to be extremely variable in composition and coiftentration. Waste
137
-------
FICURl'. 7- 1
BIOLOGICAL SYSTEMS - PLASTICS ONLY
1KFLUENT BQOS(1000+ UC/XS
cr as/) 00 Oft DODjiFP Lฃ 60 UG/L
N=7
MJniปu
HrdUn
WIVIHT BOD5(500-1000JtC/L)
ojy CS 95/100 OB BODSrr I* so XC/L
s-e
0.03
n.ix unu
0.00
INnVBNT B0D5(200-500 UC/L)
HlU CS 96/100 OH BODEFF IM 60 MG/l
N*14
H'di
9.62
Max lau
INFWBNT B006(0-200 UC/l)
K^diia A/JS CS 96/100 OF bODEFF IX 60 MC/l
N~t6
Hx* iikufl
20 38 40
EFFLUENT BOCKHG'L)
138
-------
FIGURE 7-2
BIOLOCICAL SYSTEMS - NOT PLASTICS ONLY
0.09-
F
P.08-
E
Q
0.07-
U
E
0.0o-
H
C
0.05"
Y
0.04-
F
U
0.03-
N
C
0.02-
T
1
0.01-
Q
k
0.00-
0.09-
F
0.09-
E
Q
0.0?-
U
E
8. 06-
H
C
0. 85-
V
0.04-
F
U
0.03-
M
C
0.02-
T
I
0.01-
0
J NFL US NT B0&5( JOOO+ MC/L)
RSU GS 96/100 OR BODSFF LE 60 GV/l
N*19
20 49 6B
120 140 168
INFLUSST B0D5(S00-100Q MC/L)
RSU CS 96/100 OR BODSFF LB 60 CU/L
N=t1
Hiuuniiป Hrdlftn
Minlao
i f
V.i* imu
0.09-
Median
0.07
0.86
0.05
0.04
0.03
0.02
0.01
0.00
Mซซ1muซ
mnVSNT B0D!(2O0-5GO MG/l)
RSU CS 96/tOO OR BODSFF LB CM/l
N*11
INFIUSNT BOD5(0-Z0Q VGA)
RSU Cฃ 96/100 OR BODSFF LE 60 Gii/L
0 00 100
CFFLUCNT BOD
139
-------
equalization is typically used prior to biological treatment to address
this consideration.
Toxic or inhibitory compounds frequently present in industrial wastes
can impair the biological process. Proper acclimatization can develop
strains of organisms which are tolerant to normally toxic substances.
However, once a specialized strain is established, care must be exer-
cised to avoid changes in concentration of the chemicals for which the
microorganisms have developed a tolerance. Increases or decreases in
concentration over a narrow range can result in a complete loss of the
specialized organisms and failure of the treatment process. Reestab-
lishment of a suitable microbial population can be a lengthy procedure.
It is generally accepted that temperature affects the performance of the
biological treatment process since the biodegradation rate is tempera-
ture dependent. The relationship usually employed is:
" k20ฐC ซ ฐ(T-20'
where: = kinetic rate at teragerature T (ฐC)
^20ฐ = kinetic rate at 20( C)
9 = temperature coefficient
It should be recognized that the temperature of significance is the tem-
perature in the reaction system, and a thermal balance must be computed
considering the ambient air temperature and influent wastewater tempera-
ture. The sensitivity of the reaction rate to temperature is defined by
9, a dimensionless coefficient.* A value of ฉ equal to 1.00 would imply
that the reaction kinetics are unaffected by changes in temperature. As
the value of 9 increases above 1.0 the reaction becomes increasingly
sensitive to changes in operating temperature. The value of 9 for sev-
eral organic-chemical wastewaters has been reported [7-3] to vary from
1.055 to 1.10. The effect of temperature on BOD removal in an organic
chemicals plant, as reported by Eckenfelder, et al., is shown in Figure
7-3. The figure shows that although treatment efficiency decreases with
decreasing temperature, a high degree of BOD removal can be achieved
even at very low temperatures if suitable food to microorganism ratios
are maintained. Lower F/M ratios than those shown in Figure 7-3 can be
used to obtain even higher BOD removals. Increasing MLSS concentrations
and optimizing sludge ages will also help in improving BOD removals.
Other references show conflicting results in evaluating the effects of
temperature on wastewater treatment plant performance.
17-4]
Berthouex, et al. developed linear and time series models relating
effluent BOD^ to influent BOD^, MLSS, temperature and hydraulic reten-
tion time based on three years of data compiled at the Madison Sewage
Treatment Plant (Wisconsin). They found no significant effect of tem-
perature on performance when gradual changes in temperature (4-24ฐC)
occurred.
* which must be determined empirically
140
-------
30
20
10
0
100 98 96 94 92 90 88 86 84 82 80
PERCENT BOD REMOVED
FIGURE 7-3 TEMPERATURE EFFECT ON EFFLUENT
QUALITY
141
0= 1.055
F/M=0.5
F/M = 0.4
F/M=0.2
F/M=0.3
-------
B.A. Sayigh [7-5] conducted activated-sludge laboratory studies with
continuous stirred-tank reactors and concluded that the effects of tem-
perature using domestic sewage, organic-chemicals wastewaters and petro-
chemical wastewaters depend on the specific type of wastewater being
treated. The author also found that the higher the sludge age, the less
the susceptibility of the process to variations in temperature.
Work done by Del Pino [7-6] using wastewaters from three organic chemi-
cal plants showed that low temperature operation did reduce treatment
efficiency, but this could generally be compensated for by operation at
higher MLSS concentrations.
Spearman correlation coefficients were used to statistically determine
if temperature, as measured by geographic location in degree-days, was
significant for biological effluents in the EGD Summary Data Base.
Table 7-7 presents a summary of this analysis for BOD, COD and TSS. In
all cases, effluent quality (measured as effluent mg/1) was found to be
statistically independent of location using degree-days as a surrogate
for temperature.
The principal difficulty encountered when evaluating the impact of tem-
perature on treatment system performance is that temperature is only one
of several characteristics which affect the operation of the system.
Changes in temperature (both seasonal and short term), raw waste load,
product mix, flow, food to microorganism ratio, dissolved solids and
suspended solids will all have some impact on treatment. In reviewing
full scale plant operating data, it is difficult to isolate temperature
effects from changes caused by variables other than temperature. This
problem can be overcome in laboratory scale studies where temperature
can be controlled and other variables held constant, but the usefulness
of applying temperature data collected in this manner to the operation
of a full scale system is questionable. This is particularly true in
the OCPS industry where raw waste load variability is significant due to
batch operations, frequent product mix changes, and raw materials
variat ions.
In summary, analysis of this data would generally confirm the observa-
tions which appear in the literature. Specifically, temperature can
have an impact on the treatment efficiency in some cases. However, tem-
perature is only one of several factors which impact treatment. Waste
load variations, biomass acclimation, flow variations, waste treatabil-
ity and temperature of the wastewater during treatment must all be taken
into consideration when developing a treatment sequence for a specific
industrial site. The interaction between these factors makes it diffi-
cult to isolate any one, such as temperature, separately. Thus, temper-
ature considerations must be viewed as specific to a given site, rather
than as specific to any given region or geographic area.
Regardless of the above restrictions and limitations on the applicabil-
ity of biological treatment systems, technologies and operating tech-
niques exist, which if properly applied, can overcome these limitations.
Just as two organic chemical plants producing the same product may have
different process chemistry which reflects differences in feedstocks,
treatment systems must be designed and operated to reflect the specific
142
-------
TABLE 7-7
DEGREE-DAYS VS. EFFLUENT QUALITY
SPEARMAN CORRELATION COEFFICIENTS FOR EFFLUENTS
Coefficient
Data Set BOD COD TSS
PLASTICS ONLY -0.13 0.10 0.04
ORGANICS ONLY -0.04 -0.03 -0.10
PLASTICS AND ORGANICS 0.07 0.12 -0.21
ALL PLANTS -0.06 0.03 -0.11
143
-------
characteristics of the wastewater they process. By considering each
wastewater stream to be treated individually, and judiciously selecting
the optimum combination of source control, pretreatment and treatment
technologies, treatment of OCPS wastewaters to very low effluent BOD
levels will be possible in all but the most extreme cases. Specific
means of mitigating temperature aspects are discussed later in this
chapter.
Aerated Lagoons
Aerated lagoons are stabilization basins to which air is added either
through diffusion or mechanical agitation. The air provides the oxygen
required for aerobic biodegradation of the organic waste. In some de-
signs the air addition will provide sufficient mixing to maintain the
biological solids in suspension so that they can be removed in a sec-
ondary sedimentation tank. After settling, sludge may be recycled to
the head of the lagoon. When operated in this manner, the aerated la-
goon is an activated sludge process. The viable biological solids level
in an aerated lagoon is normally low when compared to that of an acti-
vated sludge unit. The aerated lagoon relies primarily on detention
time for the breakdown and removal or organic matter. Aeration periods
of 3 to 8 days are common.
Twenty-seven of the 291 plants included in the Summary Data Base re-
ported using aerated lagoon treatment. A summary of the performance of
these plants is presented in Tables 7-8 thru 7-12.
Aerobic Lagoons
Aerobic lagoons are shallow ponds which contain bacteria and algae in
suspension, with aerobic conditions prevailing throughout the depth of
the basin. Waste is stabilized as a result of the symbiotic relation-
ship between aerobic bacteria and algae. Supplemental oxygen is pro-
vided through natural reaeration. Bacteria break down waste and gener-
ate carbon dioxide and nutrients (primarily nitrogen and phosphorus).
Algae in the presence of sunlight utilize the nutrients and inorganic
carbon and, in turn, supply oxygen that is utilized by aerobic bacteria.
Aerobic lagoons are usually less than 4-6 feet deep and can be period-
ically mixed to maintain their aerobic conditions. Algae do not settle
well using conventional clarification. In order to achieve effective
pollutant removals with aerobic lagoons, some means of removing algae
(coagulation, filtration, multiple-cell design) is sometimes necessary.
A total of four OCPS industry plants use aerobic lagoons as the princi-
pal component of their treatment system. A performance summary for
these four plants is presented as Table 7-13.
Anaerobic Lagoons
An anaerobic lagoon is deoxygenated throughout its depth and has the
advantages of low sludge production and operating costs. Treatment
results from a combination of precipitation and anaerobic decomposition
of organics, initially to organic acids and cell tissue, and ultimately
to carbon dioxide, methane and other gaseous end products. Anaerobic
144
-------
TABLE 7-8
AEKATlLt? LAGOON, ALL ซปSU STREAMS
a
MUMBEA OF 3TREA"3 REPORTING THJS IICHMOLOCr *3 MAJOR hASTEnATER TfiฃAlHฃHT| 27
fPf
BOD
DUO
BOD
TSS
ISS
TSS
COD
COO
COO
016
OIG
016
FLO"
INF
EFF
X
INF
EFF
X
INF
Iff
X
INF
EFF
t
"SO
X6/L
MC/k
Red
MC/L
MC/L
Red
MC/L
MC/L
RED
MC/L
MC/L
RED
MAXIMUM
1117.4
27*.*
2686,0
3*5.*
98.7
21178
1178,
<1,1
570.0
112.0
80.4
MEAN
J.IS#
479,8
sซ.ป
ซ0.2
550.
*2.*
>1.2
4229.5
276.4
2.4
570.0
30.5
80.ซ
minimum
l.ltl
M.I
7.ป
*5.ซ
21.0
2.0
16,1
Uป,ซ
30.0
*4,5
570.0
1.0
80.4
MEDIAN
*.12
su.s
U.O
285.e
33.0
61.1
1327.0
1)5.0
83.5
570.0
11.5
B0.4
number or
Observations 26
It
21
1*
11
22
it
11
19
10
1
6
1
Ln
AERATED LAGOON, all. HASTE STREAMS
MUMHEfi or 3TREAHS REPORTING ThzS TECHNOLOGY *3 MaJOR^ASTEwaTE* TRฃA**ฃNTI 27
TQC
INF
MC/L
T0C
EFF
MC/L
TOC
1
RED
PHENOL
INF
MG/L
PHENOL
EFF
Mfi/L
phenol
X
RED
NHJN
INF
MC/L
NHJN
EFF
MG/L
NHJN
I
RED
CR
INF
MG/L
CR
EFF
HG/L
CR
(
RED
MAXIMUM
2056.0
133.0
88.1
2345,0
U.O
99.7
19,0
240.0
80.5
0.4
1.3
54
6
MEAN
503.7
<8.1
61.9
954.1
4.3
99.5
10,4
54.4
52.7
0.4
0.3
54
6
MINIMUM
20,0
14.0
25.0
ซ.5
0.0
99,2
1.0
1.1
22.2
0.4
0.1
54
6
MEDIAN
332.0
34.0
63. ซ
709.5
0,8
99.6
10.4
3.7
54.0
0.4
0.2
54
6
NUMBER OF
observations
7
7
6
4
6
3
4
7
4
1
8
1
a These data are from plants that use this technology as the principal component
of their vastevater treatnent system.
-------
TABLE 7-9
LAOOCNt ^UAjliCS only
a
NUMBC* of ST*CAM$ RCP0RT1N0 THIS TECHNOLOGY AS MAJOR WASTEWATER TREATMENTI
EFF 000 BOD BOO TSS TSS TS* COO COO COO OlO 0Lซ
ftow iNf err % i*r trr % inf eff % inf err %
NflO HO/L KQ/L REO Ktt/t Mt/L ปEp MO/l Hfl/t peo MO/l MO/l KtD
MAXIMUM ง.950
44T.0
06.0
90.4
M3.0
SBiO
*T.O
531.0
334.0
04.0
14,0
MEAN 1*216
220*0
10.1
9.0
43.0
iaซป
T.O
358,0
U4.0
77,1
7.1
MINIMUM 0*147
4,0
T.O
ป!
*43,0
Uซo
7,0
179.0
30.0
70,4
1.1
median e*m
11'.0
15.C
85*3
*43.0
13.0
T.O
369.0
104.9
77, t
7.5
NUMBER or
observation* a
3
7
3
I
ft
1
2
*
I
0
2
AERATED LAGOON
, PLAST IC 3 ONLY
NUMBER Qf STREAKS REPOซT1nO
TMJS TECHNOLOGY
a
AS MAJOR HASTENATER
treatmenti e
TOC
TOC
TOC
phenol phenol
PHENOL
NHJN
NH3N
NHJN
CR
CR
INF
EFF
X
INF EPF
X
INF
EFF
X
INF
EFF
HG/l
MG/L
RED
HG/l MG/L
RED
HG/l
HG/L
RED
HG/L
HO/L
MAXIMUM
MEAN
MINIMUM
ME01AN
NUMBER OF
observations
O.J
0.1
0.1
0.1
1
o.ซ
0,4
0,4
0.4
i
These data arc froir plar*:s that use th?s trchro'opy as the principal coirooncnt
of their wastewater tr cat^er.*- syoten.
-------
TABLE 7-10
AthAUD w.-QOwn, NOT PLASTIC* ITYfi I 1 e>
Number of streams acportino this technpuooy as major wastewater treatmenti
Iff
BOO
too
SOD
TJ!
TSS
TIS
COB
coo
coo
01>
01#
018
FLOW
IT
Err
ซ
INr
err
ซ
Iซr
ITT
i*r
err
ซ
MOO
MO/l
MS/L
RED
MB/L
M0/L
REp
MB/L
MO/L
RED
MS/L
MO/L
RED
MAXIMUM
1 ft80 0
il.O
19J .0
tซ.ซ
66B..0
JfS.C
*1.1
tnre
I 1T8.0
ป.o
MEAN
J.110
9S4.T
T2.1
T,t
11*..6
ป!*
IT.I
ปuป.o
*11. ป
8*.3
*0
MINIMUM
0.00*
!**.t
T.O
M.8
M. .0
*0.0
M.l
IJIT.O
138.0
81.1
t
*.0
HtOIAN
1.0)0
stt.o
*1.0
ปT.*
TJ..0
6*.0
ts.t
llts.i
IS8.0
88,T
*ฆ0
.
NUMBER op
OMfWjlTIWI 1ST) I9S474I10
Iป AERATED LAf.COON, NOT PLASTICS (TYPE I I C)
a
NUMBER 0' STREAMS REPORTING THIS TECHhC^OCY AS MAJOR WASTEWATER TREATmENTI 9
TOC TOC TOC PMENC-. PHENOL PHENOL NHJN NHJN NHJN CR CR CR
INF Iff X INF Iff X IN? EFF X INF EPF X
MG/L MC/L RED "CfL MG/L RED MG/L MG/L RED *C/L MG/L RED
MAXIMUM
513.0
64.0
(8.1
ซTซ..:
1.8
90.7
19,0
125,0
80.5
0
ซ
1.3
54
6
MEAN
288. J
46.7
60.6
7oซ.
0.7
99.T
15,5
34,0
65.3
0
4
0.4
54
6
MINIMUM
20,8
15.0
25.0
is..:
0.0
99,7
12.0
1.1
50,0
0
4
0.1
54
6
MEDIAN
332.0
61.0
eo.T
709.:5
O.T
99.T
15.5
1.8
65.3
0
0.2
54
6
NUMBER or
observations
}
3
3
I?
2
1
2
4
2
1
5
1
* I Type I w/oxidatlon
a These data are from plants that use this technology as the principal^ component of their
wastewater treatment system.
-------
TABLE 7-11
C>*
n
NUMBER OP STREAMS REPORTING THIS TECHNOLOGY AS MAJOR NASTExATER TREATMENT! ซ
EFF BOD HOD BOO TSS TSS TSS COD COD COO Ota 01C 010
FLO" IMF Iff I INF EFF X INF EFF X INF tff X
MCO HC/L MC/L RfO ME/L Ms/L RED ซC/L MG/L RED Mo/L Mq/L RED
MAXIMUM
J,600
HIT.*
bo.o
98.0
2606
0
62.0
90.7
5546.0
154.0
96.5
570.0
112.0
BO.4
MEAN
l.ZM
#11,0
ST.6
*3.*
1390
3
31.0
2140,J
141.1
02.0
570.0
56.5
BO.4
MINIMUM
1,111
t*7,l
11.ฆ
07.6
494
0
13,0
ซT.4
120.0
30.0
66.7
570.0
1.0
BO.4
MEDIAN
0.762
655.0
JO. ป
95.ซ
991
0
24.5
98,7
1461.5
40.0
02.9
570.0
56.5
BO.4
NUMBER OF
observations
4
1
ซ
3
3
4
3
4
3
3
1
2
1
00
number or streams reporting this technology as majorWastewater treatwenti ซ
toc toc toc phenol phenol phenol nhjn nhjn nhjn cr cr cr
INF EFF x INF EFF X INF EFF X INF EFF X
MG/L MG/L RED mg/l MS/L RED MS/L "G/L red MG/V. MG/L red
MAXIMUM
2056.0
14.0
2.5
14,0
99.2
l.B
1.4
22.2
0.1
MEAN
2056.0
14.0
.
2.5
7.0
99.2
l.B
1.4
22.2
.
0.1
.
MINIMUM
2056.0
14.0
.
2.5
0.0
99.2
l.ป
1.4
22.2
0.1
.
MEDIAN
2056.0
14.0
,
2.5
7.0
99.2
l.B
1.4
22.2
0.1
.
number or
OBSERVATIONS 110121111010
These cata arc frcr plar.tc that uccthiG tcchr.olopv as the ?rinciT>al conpo^ent of
f?-leiT wastewater treatmciit systcn.
Type ] w'c Oxic^t. c-
-------
TABLE 7-12
ACRATCO LAOOONt NOT PliJTlCl INOT TYPE |l
a
NUHBC* or STREAMS HEP0MTIN8 THIS TECHNOLOGY AS MAJOR KAปTE*ATEซ TREATMENTI
err
r tow
MOO
000
INf
MO/L
"00
err
MO/L
*00 TSS TSS
i iNr err
RED MO/L MO/L
TSS COO COO
% jNr Err
RED MI/l mo/L
COQ
ft
RED
04*
iwr
MO/L
044
Err
MO/L
064
ft
no
MAXIMUM
19,900
99.0
m,p
*1.*
isa.e
ItiO
9.1
m.o
10*9.0
46.9
*4.0
MEAN
T,44S
95.0
*9.?
91.*
86.0
1*.9
*T.9
2*6.0
991.1
44.9
.
44,0
MINIMUM
o.ooo
Mifl
1.0
91.*
94.0
2.0
5.9
2*6.0
AO.O
44.5
44.0
MEDIAN
4.090
45.0
12.0
91.*
84.0
19,0
AT. 9
2*4.0
89.0
44.9
Aft.O
NUM3C* or
OBSERVATIONS s
1
9
1
I
9
t
1
3
1
0
1
0
aerated
LAGOON
i NOT
PLASTICS
(NOT TTPE I)
NUMBER OF STREAMS REPORT1NG THIS TECHNOLOGY AS MAJUfP KASTEKATER TREtTHENTl 6
T0C
inf
MG/L
ioc TOc phenol
EFF x INF
MG/L REO MG/L
phenol phenol
eff X
MG/L REO
NH3N nh3N NhJN cr CR CR
INF EPF X INF EFF X
MG/L MG/L RED MG/L *G/l R^D
MAXIMUM
502.0
133.0
T3.5 2395.0
10,0
99,b
8.6 240.0 50,0 , 0.1 ,
MEAN
201.7
*1.0
59,J 2395.0
10,0
99,4
8.8 121.8 58.0 . 0.1
MINIMUM
55.0
16.0
50.ซ 2395.0
10,0
99.*
8.8 3.T 58.0 . 0.1
MEDIAN
68,0
34.0
54.3 2395.0
10,0
99.6
8.8 121.8 58. . 0.1 .
number or
12 10 10
OBSERVATIONS
9
9
I 1
1
1
2
These data
arc from plarปrs that use
this technology ac the principal component of
tbni.r vaittcvaucr
treatment ays
t-CQ.
-------
TABLE 7-13
NUMBER OF STREAMS REPORTING THIS TECHNOLOGY AS MAJOlf HASTEnAUR TREATMENTS 5
iff eoo SOD BOD T3S TSS TSS COO COD COD OtC 016 OIC
FLO" INF EFF t INF EFF 1 INF iff t INF ฃFF X
"eo hc/c ซc/i ซto ms/l hg/l red "s/l "ซ/l "ed mg/l *e/L "to
MAXIMUM
).ป
78.0
2.0
6.5
17.0
252.0
0.0
HE AN
1ปซ79
70,0
17.4
08.5
16,0
160,5
0.0
MINIMUM
0,155
70.0
7.0
ee.5
05,0
. e.o
median
1.500
78.0
10.0
08.5
10,0
1*0,5
0.0
number OF
OBSERVATIONS
5
I
5
1
0
5
0
0
2
0
0 1
Ol
0 AEROBIC LซCOON( ALL HASTE STREAMS
a
number or STREAMS REPORTING THIS TECHNDLOCr AS MAJOR HASTEnATER TREATmENTI s
T0C
TUC
T0c
PHfSOL
PHENOL
PHENOL
NH3N
NHJK
NH3N
Cซ
CR
CR
INF
EFF
I
INF
EFF
X
INF
EFF
X
INF
EFF
X
MG/l
MG/l
RED
MC/L
MC/L
RED
MC/L
MC/L
RED
mc/l
MG/L
RED
HAftlMUH
60,0
40,0
7i,2
0,6
o.ซ
t
o.t
0.3
55
1
MEAN
00,0
33.5
71,2
o.ซ
ฆ
o.fl
0.1
0.1
55
1
MINIMUM
06,0
19.0
Tl.2
.
o.t
0.0
o.i
o.o
55
1
MEDIAN
06.0
33.5
7| ฆ 2
0,4
ฆ
0.0
b.l
o.o
55
1
number or
OBSERVATIONS 12102001013
a Thcar t'i'a arr fron piantx thai utc r.Hic tcchr.olof-y as thr Drincircal comnonent of
t^eir "astfvster treatment svster.
-------
lagoons are constructed with depths to 20 feet and steep side walls to
minimize surface area (relative to total volume) to allow a natural
organism cover (pellicle) to form and help retain heat, suppress odor,
and maintain anaerobic conditions. Wastewater enters near the bottom
and the discharge point is located opposite and below the pellicle.
Sludge recirculation is not necessary because gasification and the
inlet-outlet flow pattern provide adequate mixing. Anaerobic lagoons
are sometimes used to digest the waste sludge from an activated sludge
plant. Anaerobic lagoons as a principal wastewater treatment technology
are used at two plants in the 291 plant Summary Data Base. BOD removals
greater than 90 percent were reported by these plants. Additional per-
formance data is presented in Table 7-14.
Activated Sludge
Activated sludge is an aerobic biological process. Its basic processes
include an aerated biological reactor, a clarifier for separation of
biomass, and a piping arrangement to return separated biomass to the
biological reactor. Aeration provides the necessary oxygen for aerobic
biodegradation and mixing to maintain the biological solids in
suspension.
Activated sludge process modifications commonly in use include conven-
tional, step-aeration, tapered-aeration, modified-aeration, contact
stabilization, complete-mix, extended-aeration and oxygen activated
sludge. Activated sludge is the most common end-of-pipe treatment em-
ployed in the OCPS industry Summary Data Base. Of the 291 plants making
up the data base, a total of 104 use activated sludge, treating 107 sep-
arate waste streams. Tables 7-15 thru 7-19 summarize the performance of
these activated sludge plants by OCPS industry proposed subcategories.
Pure oxygen activated sludge was reported to be the principal treatment
technology at three plants. A performance summary of these plants is
presented in Table 7-20.
Attached Growth Biological Treatment
In attached growth biological systems the biomass adheres to the sur-
faces of rigid supporting media that contact the wastewater. Systems of
this type that are in common use in the OCPS industry include trickling
filters, packed towers and rotating biological contactors. While the
physical structures differ, the biological process is essentially the
same in all attached growth systems.
As wastewater contacts the supporting medium, a thin-film biological
slime develops and coats the surfaces. The film consists primarily of
bacteria, protozoa, and fungi that feed on the waste. As the slime
grows, it separates or sloughs off. The sloughed biomass is then re-
moved in a secondary clarifier.
Trickling filters are classified by hydraulic or organic loading as "low
rate" or "high rate." Low-rate filters generally have a depth of six to
ten feet and no recirculation. High-rate filters have a depth of three
to ten feet and a recirculation rate of 0.5 to 4.0. High-rate filters
151
-------
TABLE 7-14
ANAEROoiC, ALL KAME *1 REAMS
a
NUH&CR of STREAMS REPOHTINC THIS TECHNOlOG* *9 MAJOR mAMEmATER TREATMEMTl 2
CFF
BOD
BUD
BOO
TSB
TSS
TSS
CUO
COO
coo
OIC
016
OIG
FLOซ
INF
ฃFF
1
INF
EFF
X
INF
EFF
X
INF
EFF
X
MCO
MC/L
mc/L
re0
Mfi/L
mg/l
Reo
mg/l
MG/L
red
MG/L
mc/l
Reo
maximum
12.200
970.0
22. 0
*7.7
86.0
2109.0
147.0
ซ.3
MEAN
a.225
frซ4cS
20.5
ซ5.1
66,0
1121.0
87,5
70.2
MINIMUM
4.250
319.0
h.o
4.0
06.0
53.0
28.0
07.2
MEDIAN
0.225
4U.S
20.5
95.9
flfc.O
1121.0
07.5
70.2
number or
OBSERVATION) Z
2
2
2
0
1
2
2
2
0
0
0
ANAEROBIC
, ALL
hASTE
STREAMS
NUMBER
or STREAMS REPORTING
THIS
TECHNOLOGY AS
MAJOR
hastehater treatmenti
2
TOC
TOC
TOC
PHENOL
PHENOL
PHENOL NHJN
NH3N
NHJN
CR
CR
CR
INF
eff
X
INF
eff
X
INF
EFF
X
INF
EFF
X
MG/L
MC/L
RED
HG/L
MC/L
RED
MG/L
MG/L
RED
mg/l
MC/L
REO
MAXIMUM
695. 0
74.0
09,4
.
MEAN
411.5
51.0
B5.7
a
.
.
.
MINIMUM
128.0
28,0
78.1
median
411.5
51.0
83.7
ซ
NUMBER OF
OBSERVATIONS
2
2
2
0
0
0
0
0
a These data are from plantsthat use this technology as the principal component of
their wasrouatcr treatment systen.
-------
TABLE 7-15
ACTIVATED SLUDGE, ALL HASTE STREAM*
NUMBER or SIHEAMS REPORTING THIS TECMnOlOST AS mAJo# HASTEHAUR TREATMENT! 1ป7
EFF
flon
MGD
BUD
INF
MC/L
BOD
EFF
mg/l
OD
1
Red
TSS
INF
MG/L
TSS
EFF
MG/L
TSS
X
Red
COO
INF
MC/L
COO
EFF
MC/L
COD
X
Red
OIC
INF
MC/L
016
IFF
Mc/L
016
X
RED
HAH IMUM
40.*04
5**1.
78I.B
44.7
II*.
651.1
M.I
32476
1IIM
46.3
242.0
SO.O
46.7
mean
2,172
1216.6
37,4
'i.'
512.4
*1.1
10Sป,0
454.2
1.3
SB.l
10.0
34.3
MINIMUM
14.0
I.*
47.3
271,4
21#.#
34.0
14.0
#.*
12.*
MEDIAN
1.070
754.0
2*.#
45.4
Ilk.*
5.0
M.I
1666.4
166.4
4,4
23.0
4.0
47.4
number or
OBSERVATIONS tOT
S
101
s
so
40
34
71
74
70
7
17
4
Wn
W ACTIVATED SLUDGE, ALL HASTE STREAMS
a
nuhaer or streams reporting tซiป teCmmolog* as major kaste*ateซ treathฃnti 107
TOC TOC 10c PHENOL PHENOL PHENOL NHJN NHJN NHJN CR CR CR
INF EFF X INF iff I INF EFF X INF EFF *
WG/L HC/L RED *C/L MC/L RED MG/L MG/L RED MG/L MG/L RED
MAIIMUM
5226.0
665.0
44.5
747.0
16,0
100,4
340.0
274,0
43.6
2.3
10.0
47,2
MEAN
1025.8
121.2
BO.7
145.6
2.1
ซ2.2
75.1
31,4
10,4
0.6
0.6
60.2
MINIMUM
67.0
7.0
36.5
0.1
0.0
61.5
0.6
0.4
-347,4
0,0
0.0
-1324
MEDIAN
505.0
64.0
B4.6
14.J
0.1
44.7
10.0
6,4
27,0
0.2
0.1
71.6
NUMBER OF
OBSERVATIONS
24
24
24
IB
2B
16
21
40
22
12
21
11
a These data are from plants that use this technology as the principal component of
their wastewater treatment systcra.
-------
TABLE 7-16
Nuซ8ฃA or STREAMS RE*0ซTIN0 THIS TECMNfiL.OOY AS MAJOR* WOUWATCH TREATMENT! 40
trr
000
800
eoo t$s
TSS
TSS COO
COO
COO
019
040
01ฎ
FLOW
iwr
trr
ป INf
cff
% INF
trr
%
INF
EFF
%
MOO
Mfl/L
MO/L
RCO MO/L
MO/L
REO MQ/L
MO/L
RCO
MO/L
MO/L
RED
1
t
...
MAXIMUM 10*700
39*0,0
Si.O
99.7
2090,C
179,0
9ป. 1
4330,0
420.0
90.1
242*0
0,0
73.9
MEAN 1.690
414,0
IT.O
*4*3
903,.L
~ 4 . 6
9*.l
DOM
ltl.l
44.9
102*0
19.9
69,7
MINIMUM 0*0)4
t*ซ0
3*0
7ซ*l
ei,t
7,0
49,9
210.0
34.0
49.1
13.0
l.t
44,9
MEDIAN 0.463
3*0,0
io*ป
Hi9
101.X
30.0
64,0
900 , 0
9T.0
09.0
41*0
T.O
40,3
KUMRER OF
OBSERVATIONS 40
99
30
39
3:
39
31
39
34
31
3
0
3
Ui
4S
ACTIVATED ULUDGE, PLASTICS ONLY
a
NUMBER OF STREAMS REPORTING THIS TECHNOLOGY AS MAJOR WASTEWATER TREATmENTI #0
TOC TOC TOc PHEMI3L PHENOL PHENOL NHJN NHJN NM3N CR CR CR
I Hf IFF t INF EFF * INF EFF * INF EFF *
MG/L hg/L RED MC/L RED MG/L MG/L RED MG/L MG/L RED
MAXIMUM
2751.0
'6,0
ซ9.5
42b .0
0*5
100,0
49,0
109,0
69,6
2.0
0.3
'7.2
mean
1103,4
46,2
86,7
7l6
o.i
06,5
1*,5
22.fi
27.0
0.6
0.1
53,5
minimum
290,0
15.0
66.9
0-1
0,0
61.5
2*0
0,4
-347,4
0.1
0.0
0
1
median
464,0
43.5
90,3
0,1
0.0
92,4
0*0
6.0
25.0
0.2
0.0
03.4
number of
OBSERVATIONS
9
6
4
6
9
6
10
16
9
4
7
4
a These data are from plantsthat use this technology as the principal component of
their vasVjwater treatment system.
-------
TABLE 7-17
> 1 bw* r J |tC< > ' ซ 4 C)
A
NgMlฃft 0' ITOIAMS RCP0*TINS THIS TEChNOlOOT AS MftJOft *AปTEปMฃH TREATMENT I 42
CFF BOD
FLOW JNF
HOD M8/t
BOD
CFF
HB/L
BOO
%
RCO
Tt$
INF
MSfl
TSS
CFF
Mfl/L
TSS
%
*ep
coo
INF
Hซ/t
coo
CFF
MO/L
COD
ซ
BCD
Olป
IN*
N8/L
01(
err
m#/l
OK
*
MO
ซป.l
J7.6
is.t
11.4
Tป,ซ
14.7
T.I
11.4
lป.l
14.0
e.4
It.4
ป.ป
14.7
4.5
It.4
I*
t
ซ
1
MAXIMUM
MEAN
MINIMUM
MEDIAN
NUMSEJI OF
OBSERVATIONS
0*00t 1SSซ0
!ซUป ISHifl
At
3%
BO.O
*1
4T.B 11,0 -KTl.A Sซt,0 M.O
)*
11
ป
13
15
SB
Ln
ui
ACTIVATED SLUDGE, NOT PLASTICS (TYPE I I C)
a
NUMBER Of STREAMS REPORTING THIS TECHNOLOGY A3 MAJOR KA3TEHATEA TREAT*ENTl ซ*
TOC
TOC
TOC
PHENOL
PHENOL
phenol
NMJN
NH1N
NHJN
CR
CR
CR
INF
EFF
1
INF
EFF
i
INF
EFF
X
INF
EFF
X
MC/L
KG /L
RED
KC/t.
MC/L
RED
MS/L
M5/L
ซฃ0
MS/L
MC/L
RED
MAXIMUM
1202.0
665.0
97.7
747,<1
16.0
100.0
190.0
274.0
>1.1
2.1
0.5
80.0
MEAN
lost.*
156.0
7S.9
269,7
5.5
'ซ.6
117.1
06.6
17.1
o.ป
0.2
22.9
MINIMUM
260.0
21.0
16.5
I.*
0.0
60.0
2.ซ
l.ซ
.17.0
0.1
0.0
66,7
KEDUN
71'.0
>6.5
9.9
121.5
0.2
ป7.1
51.0
16.0
11.4
0.1
0.2
19.1
NUMBER OP
OBSERVATIONS
15
H
11
11
17
a These data are from plants that use this technology as the principal component of
their wastewater treatment systen.
Tvp? I w' Ox- rlatlc
-------
TABLE 7-18
ACiiVftici) 3i.O0Ct| ftuT tid [ T i r t . nui C) 'ฆ
a
number of streams reporting this technology as major ซastcnater treatmenti is
EFF ROD BOO BOO TSS TSS TSS COO COD COO OIC OIC 016
FLOW INF EFF t INF ฃ ff X INF EFF *
hco mg/l ซg/l RfD mg/c mg/l red "g/l mg/l Red mg/l mg/l red
MF EFF X
maximum
4.310
272S.0
780,0
r.T
780.ป
>51.0
85.0
32476
note
17.0
15.0
35.3
mean
1.533
1267,7
112,2
145,2
136.1
41.2
BOB],4
1613,5
2.5
17.0
1S.0
35.3
minimum
0.020
6k, a
>1.0
70,
131,0
ซ.ป
-9.1
333,0
40,0
66.1
17.0
11.ฎ
35.1
median
I ,ซ40
1015.5
20.0
*2.7
177.0
71,0
40.1
344*,0
357.5
79.1
17.0
13.0
35.3
NUMBER OF
OBSERVATIONS IS 10 1] 10 5 11 5 T T 1 2 I
m
activated sludge, not plastics (type i not c>
a
NUHBER of STREAMS REPORTING This technology AS major nASTEnATER TREATMENTI 15
TOC TOc 10c PnE^OL PHENOL PHENOL NHJN ShJH NHJN C" CR CR
IMF E^F X INF EFF I INF EfF X INF EFF X
HG/L MG/L RED MGA HG/L RED HG/L MG/L RED "G/t ซG/L RED
maximum
5226.0
501.0
97.5
ia.0
1.0
99.1
233,0 80,O 93,8
0.ซ
mean
Jlซ4,t
131.5
BO.4
14.3
O.T
95.8
132.5 28,2 79,7 ,
0.4
minimum
67,0
7,0
4B.ซ
10.7
0.2
"ป2.6
32.0 1.8 65.7 .
0.4
median
431.0
79.0
79.7
14.3
0,8
95.8
112.5 15.5 79.7 .
0.4
number of
OBSERVATIONS
7
a
7
2
3
2
2 4 2 0
1
* Type I v/
o i^xidatior.
a These dat
a are Irom
plants
that
use
fcc>,
olcg/
33 z:.c z~'
of
"reatr.or.:
system.
-------
TABLE 7-19
ACTIVATED SLUDSEl NOT PLASTIC* (NOT TYPE II
a
Nuxie* or STREAMS REPORTINO THIS TtCMNOLOOV AS MAJOR WASTEWATER TREATNENTI 10
-
-
--
.. , ,ฆ..
trr
000
f>on
POO
TSS TSJ COO
con too
04* Oil
01*
rto"
INF
EFF
1
INF EFF INF
EFF ซ
INF ฃff
I
*00
N0/L
MO/L
RED
NO/L MS/L *E0 mo/l
MO/L RED
MO/L M6/L
REO
MAXIMUM
*0.000
520.0
2T.0
07 .0
1366.0
101,0
rr.3
5416,0
413.0
9ป.0
50,0
3.0
90,7
MEAN
s.sปo
323. t
IS.4
ซ.s
4ST.0
41.1
S3.7
ITof.l
150.2
71.6
50.0
1.9
*0.7
MINIMUM
0.333
102.0
3.0
tl.9
17,0
iซ.o
TO.4
<18.0
3.0
ซ*,ซ
50.0
0.7
~.7
median
1.445
324.0
U,0
tป.l
1Z1.0
t*,0
3S.5
42.0
111.0
71,9
50.0
9
*9.7
number or
0ปSfซ*ATI0NS II
*
I
f
ซ
9
f
9
1
J
1
U1
^ ACTIVATED SLUDGE, NOT PLASTICS (NOT TYPE I)
a
NUMBER OF STREAM REPORTING THIS TECHNOLOGY AS MAJOR HtSTEHATER THEATKENTI 10
^ ^ ^ PHEXOL PHENOL PHENOL NHJN NH3N NHJN CR CR CR
Ittf Iff I lNf EFF I INF Iff I INF EFF *
MG/L MC/L red mc/l MG/L RED MG/L MG/L RED MG/L ซG/l RED
65*6 64,1 2*1 C.T 10.0 *0,5
JJ.2 22.4 -5.1 O.J 2.1 -396.0
0.6 0.9 *12.5 #.ซ 0.0 '1329
31.2 2.2 -5.1 0.2 0.1 50.0
2 3 2 1 5 3
a These data are from plants that i:se this technology as the principal conponert of their
wastewater treatment system.
maximum
1*4.0
*1.0
. *>
0.2
96,9
MEAN
184.5
41.0
2.2
0.1
95.9
minimum
175.0
1.0
0.0
95.0
MEDIAN
iซ#.5
41.0
2.2
0.1
95.9
NUMBER OF
OBSERVATIONS
2
1
0 2
5
2
-------
TABLE 7-20
Kire "x'^-cn A^Mvnted Sludge
ALL KASiZ - .rcAHfl
a
NUMBER OF 31 REAMS REPORTING T*I9 UCHHULOtl A9 MAJOR mAปTฃwATฃR TREATMENT! 1
tFf BOD 000 aoo T9S 183 T39 COO COO COP OtG OlC OIG
FLO" iNf iff * !Nf CFF % INF Iff X lNf iff X
MCO Mc/L MG/L ซC0 Mc/L MC/L Rฃ0 *G/L Mc/L ซE0 MG/L Mg/L *ED
MAKIHUH
7.160
str.o
26.0
*7.2
204,0
10,0
Jซ5.0
105,0
05.2
mean
J,810
270,0
>.7
9ซ.8
lll.O
25,0
tA.i
322.5
70,0
75,1
hinjhuh
ซ,ซซ
HJ.O
n.o
7.0
!ป.ป
ป*.ซ
100,0
5>.0
65,0
HEOUN
j.jeo
200.0
17.0
88.1
131,0
25,0
6ซ.l
322.5
70,0
75.1
NUH0EH OF
OBSERVATIONS 3333222222000
Ture Oxygen Activated Sludge
All WASTE STREAMS
a
NUMBER OP STREAMS REPORTING THIS TECHfcUlOGY AS MAJOR NASTEnATER TREATmENTI 3
TOC
IOC
TQC
phenol phenol phenol
NH5N
NH1N
NH JH
Cซ
CR
CR
INF
EFF
X
INF EfF X
INF
EFF
K
INF
EFF
{
ซG/l
MG/L
RfcD
MG/L HG/l RED
MG/L
MG/L
RED
ซG/Li
MG/L
ftED
MAXIMUM
75.0
26.0
*5.3 0.3
o.ซ
99.0 #
i
MEAN
75.0
2b.0
65.3 5.1
0.2
96,a ,
MJNIHUH
75.0
26,0
65.3 2.0
0,0
9ซt7
ซ
MEDIAN
75.Q
26.0
65.3 5.1
0.2
96,ft
number of
OBSERVATIONS
I
1
1 2
2
2 0
0
0 0
0
I
a
These data
are from plantsthat
use
this technology
as the
principal
component
o
their vast
cvatcr
trcatrent system.
-------
can be single or two stage. The most suitable medium in both the low
and high-rate filters is crushed rock.
In the OCPS 291 plant Summary Data Base three plants reported using
trickling filters as their principal technology for EOP treatment. A
performance summary for these three plants is presented as Table 7-21.
Packed towers are much like conventional trickling filters, but use a
manufactured medium instead of crushed rock or gravel. The manufactured
medium can be corrugated plastic packing oij r^ugh-sawn redwood slats.
These media have high specific surfaces (ft /ft ), a high percentage of
void volume, uniformity for better liquid distribution, chemical resis-
tance, light weight facilitating construction of deeper beds, and the
ability to handle high-strength and unsettled wastewaters. Packed tow-
ers are used in flow patterns similar to normal high-rate, natural-media
filter systems.
In rotating biological contactor systems a series of disks constructed
of corrugated plastic plate and mounted on a horizontal shaft are placed
in a contour-bottomed tank and immersed to approximately 40 percent of
the diameter. The disks rotate as wastewater passes through the tank
and a fixed-film biological growth similar to that on trickling filter
media adheres to the surface. Alternating exposure to the wastewater
and the oxygen in the air results in biological oxidation of the organ-
ics in the wastes. Biomass sloughs off (as in the trickling filter and
packed tower systems) and is carried out in the effluent for gravity
separation. Direct recirculation is not generally practiced with the
rotating biological disks.
Four plants in the OCPS Summary Data Base use rotating biological con-
tactors as their principal form of treatment. All four of these plants
are "plastics only" facilities. A summary of their performance is pre-
sented in Table 7-22.
Tertiary Treatment
In some instances, where secondary treatment does not produce a satis-
factory effluent, polishing or tertiary treatment is utilized. The
addition of a tertiary unit process does not always result in an efflu-
ent of higher quality than can be achieved with biological treatment.
Often tertiary treatment is used to compensate for inadequately designed
or improperly operated biological systems. Depending on the nature of
the pollutant to be removed and the degree of removal required, the pol-
ishing or tertiary treatment system can consist of a one unit operation
or multiple-unit operations in series. Some of the unit operations used
in tertiary treatment may also be used as in-plant treatment options.
Polishing Ponds - Polishing ponds serve as polishing steps following
other biological treatment processes. They primarily serve the purpose
of reducing suspended solids. Water depth generally is limited to two
or three feet. Polishing ponds are commonly used as a final process.
Powdered Activated Carbon Treatment - Powdered activated carbon treat-
raent ^PAC) refers to the addition of powdered carbon to the aeration
159
-------
TABLE 7-21
number of stream* reporting thu technology *o major nastekahr treatment| 3
EFF
BOP
BOO
BOD TSS
TSS
TSS
COD
coo
COO
Ulc
0*6
0&G
FLO*
INF
EFF
X INF
EFF
X
INF
EFF
X
INF
EFF
I
MCO
*6/1
MC/L
Red *g/l
MC/L
RED
mg/l
MC/L
RED
mg/l
Mfi/L
REO
ป
*
MAXIMUM
3,570
*ป!ซ0
31.0
*5.2
1225.0
5S.0
*5,3
1979,0
250.0
67.4
MEAN
1,731
310,9
26.0
*0.0
62T.5
30# 0
76,1
1021.7
163.0
79.1
.
minimum
0.*23
170,0
",0
30.0
13.0
56.7
210.0
63.0
70,0
,
MEDIAN
1.200
279.0
24.0
as.9
*27.5
3ซ,0
76,1
076,0
176.0
79,1
number of
observations
i 3
3
3
3
2
2
2
3
3
3
0
0
TRICKLING FILTERi ALU HASTE STREAMS
a
NUMBER Of STREAMS REPORTING THIS TECHNOLOGY AS MAJOR WASTEWATER TREATMENTl 3
toc toc TOc phenol phenol phenol nhsn nhjn nhjn cr cr cr
INF EFF X lNF Iff X INF EFF I INF Iff X
MC/L MG/L RED mc/L MG/L RED MC/L MC/L RED MC/l MC/L RED
i
i
i
i
i
i
i
i
MAXIMUM
. ฆ
3.0
1.0
66
7 . ซ
HEAN
. #
3.0
1.0
66
7 . .
MINIMUM
a
3.0
1.0
66
7 . . ป
MEDIAN
*
3.0
1.0
66
7 . .
NUMBER of
OBSERVATIONS
0 0 0
0 0
1
1
1 B 0 O
a
These
tiicir
data arc froir. nlar.ts
vastcvater treatment
that urปe
SVQtCB.
this technology
as
the
principal cormonent of
-------
TABLE 7-22
6 lUfeww ซ w Cii II A^L * * 4 *- ซ#trU.'"ปd
a
NUMBER of SIRCAMS REPORT IซC THIS tCCHNOLOCT AS MAJOR ซASTtซATE* TREATMENTI 4
IFF BUD BUD ftOD TSS MS T93 CUD COO COD OIC ' OlC OU
FLO* INF Iff t INF EFF * INF ฃF f X INF tff t
HCO *S /L Ht/L ซCo Me/L *C/L *C0 ปC/L HC/L ปED MC/L MC/l RED
MAXIMUM
2.7ซ0
woo.o
52.0
95.T
49.0
43,0
2S.0
2170,0
ISB.O
'2.1
2.1
MEAN
0.904
434,0
30.5
BO,4
H.J
29.3
IS.*
851.B
99.0
73,5
2.3
MJN1MUN
0.054
ซ.ซ
ซ1.0
20.0
15.0
12.2
97.0
15.0
31.2
2.3
MEDIAN
0.411
242,5
33.0
92.5
34.S
30,0
IB.*
403.0
94.5
05.4
2.3
NUMBER Or
OBSERVATION} 4
4
ซ
2
J
2
4
4
4
0
1
H1
ROTATING BIOLOGICAL CONTACTOR, ALL CASTE STREAMS
a
NUMBER OF STREAMS REPOHUnC IHJS TECHNOLOGY as MAJOR MASTEHATER THEATmENTI 4
ioc iuc toc phenol phenol phenol h*jn nhin nnjn cr cr cr
INF EFF X INF EFF X INF EFF ป INF IFF t
MG/L MC/L RED ซ6/L MC/L RED MG/L MS/L RED MG/L ms/L RED
MAXIMUM
100
0
71.0
29,0
29,0
0.1
0,1
BB.9
MEAN
too
0
71.0
24,0
ซ
29,0
0.1
0.1
BB.9
MINIMUM
100
0
Tl.o
29,0
1
2't0
0.1
0.0
ee.9
MEDIAN
1*0
0
Tl.0
29.0
29.0
ป.ป
0.1
BB.9
NUMBER Or
observations
1
1
1
0
0
0
0 1
0
1
2
1
a These data arc from plants that use this technology as the principal component of their
vaotewatcr treatment system.
-------
basin in the activated sludge process. It is a recently developed proc-
ess that has been shown to upgrade effluent quality in conventional
activated sludge plants. In the PA.C treatment process the carbon con-
centration in the mixed liquor is generally equal to or greater than the
volatile mixed liquor suspended solids level. The carbon and adsorbed
substances are removed as part of the waste biological sludge.
Activated Carbon Adsorption - The use of activated carbon adsorption can
be confined to the removal of specific compounds or classes of compounds
from wastewater streams, or for the removal of such parameters as COD,
BOD and color. Although more common as in-process treatment, it is also
used for tertiary treatment.
An aspect of granular carbon carbon columns that is currently receiving
attention is the role and possible benefits of biological growth on the
carbon surfaces. In some applications much of the removal has been
found to result from biodegredation rather than from adsorption.
Six plants in the Summary Data Base reported using activated carbon as
their principal EOP treatment. The performance of these systems is
summarized in Table 7-23.
Filtration - Filtration may be employed to polish an existing biological
effluent, to prepare wastewater for a subsequent advanced treatment
process, or to enable direct reuse of a discharge. Filtration of a sec-
ondary effluent will remove additional BOD and TSS, and reduce
turbidity.
Reverse Osmosis/Ultrafiltration - Reverse osmosis is a physical separa-
tion process that relies on applied pressure at a level greater than
osmotic pressure to force flow through a semi-permeable membrane. The
process is capable of removing suspended particles and substantial frac-
tions of dissolved impurities, including organic and inorganic mater-
ials. The process results in two effluents, one relatively pure and the
other containing the concentrated substances. Reverse osmosis systems
generally require extensive pretreatment (pH adjustment, filtration,
chemical precipitation, activated carbon adsorption) of the wastewater
stream to prevent rapid fouling or deterioration of the membrane
surface.
Ultrafiltration is similar to reverse osmosis and relies on a semiper-
meable membrane and an applied driving force to separate suspended and
dissolved materials from wastewater. The membranes used in ultrafiltra-
tion have pores large enough to eliminate osmotic pressure as a factor
and to allow operation at pressures as low as five to ten psi. Sieving
is the predominant mechanism of removal and the process is usually
applicable for the removal of materials that have a molecular weight
above 500 and that have very small osmotic pressures at a moderate con-
centration.
Combined Secondary and Tertiary Treatment System - In practice primary,
secondary and tertiary processes are often used in series to treat OCPS
industry wastewater. In fact, of the 146 plants employing biological
treatment in the Summary Data Base, 58 use a form of treatment after
162
-------
TABLE 7-23
Nuซ8tซ OF JIKEป"S REPORTING THIS TECHNOLOGY *3 MปJORaซ13Uซป T[R TREATMENT I T
EFF
SOD
BUD
BOO
T9S
T S3
193
COD
COO
COO
Ulfi
ou
Olfi
floซ
INF
EFF
X
INF
EFF
X
INF
EFF
X
iNf
EFF
X
MCO
MC/L
MC/L
Red
Hc/L
MC/L
RED
MC/L
MG/L
Red
HC/L
MC/L
REO
MAXIMUM
0.1)4
1743.0
772.0
55.7
M7.9
JT.O
97.5
1556.0
1126,0
76.0
1.5
MEAN
0,132
1271.0
20b.2
5ซ.ซ
Ji.a
23.0
51.4
2606,0
410,6
75.0
1.2
MINJMUM
0,014
601.0
ป.o
5ซ.2
16.0
5.1
206, 0
60.0
70.*
1.0
MEDIAN
0.127
1271.0
30.0
$ซ.ซ
31.1
19.5
51.4
2ป7fc.0
171.0
76.2
1.2
hUMBEซ OF
observations 6
2
*
2
2
4
2
1
6
1
0
2
0
activated carbon, all haste STREAMS
NUMBER
of streams reporting
this
iechnoloct ปs
MAJOR3 WASTEWATER TREATmEnTI
7
TQC
TOC
TOC
phenol
phenol
phenol
NH3N
KH5N
NH1N
CR
CR
CR
l*F
Iff
1
INF
iff
X
JNF
EFF
X
INF
EFF
X
MG/L
MC/L
red
H6/L
MC/L
RED
MC/L
MG/L
RED
MC/L
MC/L
RED
MAXIMUM 1455,0 115.0
78.4 171.0
2.2
99.B
o.o
MEAN 771,5 111.0
78,4 127,0
i.o
99,0
.
ป
0.0
MINIMUM *2,0 2a.ฎ
76.4 6B,0
o.z
97.5
0.0
MEDIAN 771,5 52.5
76.4 120.0
0.6
99.7
0.0
NUMBER OF
observations 2 *
1 1
1
1
0
0 9
0 1
a These da"a arc frcr
plaur.r. .he.
V-.0 this
rcc'
-elegy
as the principal
comn oner.
was*;^vater * reatrj-ปn
system.
-------
secondary. The most prevalent tertiary process in the industry Summary
Data Base is polishing ponds. A total of 34 plants reported using pol-
ishing ponds. Filtration and a combination of filtration and polishing
ponds are the next most common tertiary processes in use with 11 streams
utilizing this process.
Design, Operation and Management Practices
The need for good engineering design, good operating practices and con-
scientious waste management is as important in waste treatment as in
chemical manufacturing. The design of the system must be site specific
in that it must consider raw waste components, organic and hydraulic
load variations, manufacturing practices, waste temperature, operator
capabilities and other considerations which may be unique to the site.
Operating practices must be based on a thorough understanding of mech-
anisms at work and probable response to changes in operating conditions.
Waste management must be considered when planning for production cam-
paigns, prodution shutdowns and new product addition, and should also
include contingency planning for mechanical failures, inadvertent dis-
charges and treatment system upsets.
As previously stated, optimum treatment system performance is usually
obtained under so called "steady state conditions." This condition
could be approached in wastewater from a single product, continuous
process manufacturing operation. Such a situtation is unfortunately
uncommon in OCPS plants. Many OCPS plants produce a variety of prod-
ucts, often on a campaign basis, using production operations which may
be either continuous or batch. This frequently results in wastewater
which varies significantly in composition and quantity.
Equalization and storage is the primary design approach taken to mini-
mize this problem. It may be possible in some instances to modify pro-
duction schedules to avoid simultaneous multiple batch discharges or
cleanup operations to avoid excessive peak loads. Treatment plant oper-
ators should be advised of known or anticipated waste load changes so
that they may respond accordingly, i.e., increase aeration, divert and
hold accidental discharges, increase chemical feed rates, etc.
Plants operating in cold weather conditions should recognize that unnec-
essarily excessive storage prior to treatment may reduce the temperature
of the biotreatment system. Cold temperature operation may require in-
sulation of treatment units, covering of open tanks, and tracing of
chemical feed lines. Insulation of treatment units may include instal-
ling tanks inground rather than above ground, using soil around the
walls of above-ground units to prevent heat loss, or providing enclo-
sures around treatment units. Operators should recognize that during
colder periods it may be necessary to maintain higher MLSS concentra-
tions, which may in turn require greater operator attention to effluent
solids concentrations.
Plants operating in hot weather climates may be required to reduce waste
temperatures to maintain a suitable treatment environment. Natural or
mechanically induced evaporation may be used to reduce waste
temperatures.
164
-------
Control of toxic and inhibitory waste components may be required to
avoid treatment system upsets. This may be accomplished by separation
and segregation of the material at the point of waste generation, or
destruction or removal of the material through the use of a pretreatment
system. Waste components typically handled in this manner include cya-
nides, heavy metals and metallic sulfides. In the case of inhibitory
components, equalization and subsequent dilution may be sufficient to
eliminate the inhibition.
Upgrading Biological Treatment Systems
Many treatment systems in the OCPS industry have undergone one or more
major modifications to upgrade performance since the initial installa-
tion of the system. The four most common reasons for plant upgrading
are:
1. To accommodate changing environmental regulations
2. To accommodate higher loads from expanded production facilities
3. To accommodate wasteloads associated with the manufacture of
new products
4. To address inadequacies in the treatment system design
Because of the modular nature of most treatment systems, upgrading is
most commonly accomplished by adding additional modules. When the up-
grading is done to increase treatment system capacity, it is commonly
done by adding modules similar to those already installed, i.e., addi-
tional aeration basins or clarifiers. Upgrading to accommodate more
stringent treatment requirements usually involves adding new treatment
process unit operations to an existing treatment train, e.g., addition
of multi-media filtration following secondary clarification or addition
of a coagulant feed system to a primary clarifier.
The nature of this evaluation of treatment system capability is best
illustrated by use of an example. Consider a hypothetical chemical
plant whose treatment system initially consists of a simple aerobic
lagoon. The first level of upgrading could include providing aeration
to convert the aerobic lagoon to an aerated lagoon. The next level of
upgrading might include the addition of secondary clarification to re-
turn solids, thus converting the lagoon to an activated sludge system,
providing some initial equalization capacity, and providing an aerobic
digestor to stabilize waste secondary solids. The next level of upgrad-
ing could include the installation of a dissolved air flotation system
to reduce influent suspended solids or oils, addition of multi-media
filtration to reduce effluent solids, and the addition of solids
dewatering equipment to allow for landfill disposal of waste activated
sludge.
The OCPS industry provides several examples of similar upgrades:
165
-------
Plant 53 - This plant was upgraded in June 1977. Facilities originally
consisted of an equalization basin and aerated lagoon. The lagoon was
converted to activated sludge by the addition of two clarifiers and
additional aeration basin capacity. Solids handling equipment and an
aerobic solids disgestor were also added. Change in operating perform-
ance was as follows:
Before After
Upgrade Upgrade
Effluent BOD 316 mg/1 28 mg/1
Effluent TSS 63 mg/1 74 mg/1
Plant 292 - This plant was upgraded in late 1977. The existing acti-
vated sludge system was upgraded by adding multi-media filters followed
by granular activated carbon contactors. Other changes included an im-
proved solids handling system comprised of gravity thickening, vacuum
filtration and multiple hearth incineration.
Before After
Upgrade Upgrade
Effluent BOD 20 mg/1 12 mg/1
Effluent TSS 56 mg/1 34 mg/1
This plant, and plant 53, are somewhat unusual in that they exhibit
negative TSS removals. This will occur in any biological system where
the loss of biological solids from the secondary solids separation sys-
tem to the effluent is greater than the influent TSS received by the
biological system. When a treatment system is achieving good secondary
solids capture, typically 50 mg/1 or less effluent TSS, the occurrence
of a negative TSS removal percentage is not significant.
Plant 60 - This plant was upgraded in 1977. Treatment originally con-
sisted of equalization, neutralization, primary clarification, aerated
lagoon and final clarification. The system was converted to completely
mixed activated sludge. Aerobic digestion, gravity thickening, pressure
filtration and an onsite landfill were also provided. Change in opera-
ting performance was as follows:
Effluent BOD
Effluent TSS
Before
Upgrade
510 mg/1
No Data
After
Upgrade
41 mg/1
No Data
166
-------
Plant 45 - This plant originally had an activated sludge system with
primary clarification. The plant was upgraded by the addition of a 3.5
million gallon equalization basin and mixed-media filtration. Addition-
al aeration capacity was installed and a second secondary clarifier was
added. New sludge handling facilities consisting of two pressure fil-
ters were installed to accommodate increased solids production.
Before After
Upgrade Upgrade
Effluent BOD 46 mg/1 3 mg/1
Effluent TSS 91 mg/1 24 mg/1
Plant 109 - In 1976 this activated sludge system was upgraded through
the addition of an extended aeration basin and multi-media filtration.
Both units were added downstream of the existing treatment plant. In
1977, additional blower (aeration) capacity was added.
Before After
Upgrade Upgrade
Effluent BOD 12 mg/1 3 mg/1
Effluent TSS 83 mg/1 No Data
Plant 118 - This plant was originally operated as a single stage trick-
ling filter plant. In 1977 it was ugraded by the addition of a dis-
solved air flotation system to accomplish primary treatment, and added a
UNOX pure oxygen system as a second stage biological treatment unit.
Before After
Upgrade Upgrade
Effluent BOD 293 mg/1 13 mg/1
Effluent TSS No Data No Data
Plant 269 - This treatment facility originally consisted of clarifica-
tion, neutralization and activated sludge. In late 1977 it was upgraded
by the addition of increased primary sedimentation capacity, the addi-
tion of an equalization basin prior to the activated sludge system,
additional instrumentation, the addition of another secondary clarifier
and improvements to the sludge handling facilities.
Before After
Upgrade Upgrade
Effluent BOD 255 mg/1 66 mg/1
Effluent TSS No Data No Data
167
-------
Plant 281 - The original activated sludge system at this plant was up-
graded Tn 1977. System improvements included the addition of an emer-
gency holding basin and a stormwater holding basin, the addition of
equalization upstream of existing treatment units, chromium reduction on
a boiler blowdown stream and some in-plant flow reductions. An addi-
tional secondary clarifier was also added.
Before After
Upgrade Upgrade
Effluent BOD 15 mg/1 11 mg/1
Effluent TSS 46 mg/1 No Data
OCPS EFFLUENT QUALITY
Effluent quality in the OCPS industry, as defined by conventional pol-
lutant parameters, is determined by several factors. Those factors with
the greatest influence on effluent quality include: the origin of the
wastewater, the type of treatment system used, and the design and opera-
tion of the treatment system.
The origin of the wastewater, which takes into account the type of prod-
ucts manufactured and manufacturing processes used, has already been
discussed in Section IV. In that section a subcategorization scheme
based on wastewater origin was developed.
In determining the effluent quality achievable by OCPS plants, biologi-
cal treatment has been evaluated as the principal treatment practice
within the industry. Of the 185 plants for which treatment system in-
formation is available, 146 use some form of biological treatment.
Although nonbiological treatment systems are often used to produce high
quality effluents, only biological treatment has been sufficiently
applied to be considered as applicable across the broad spectrum of the
OCPS industry.
The various biological treatment technologies differ only in the mechan-
ical means by which the wastewater, biomass and essential nutrients are
brought together. Although an activated sludge system and rotating bio-
logical contactor appear very different, the biological processes are
similar. Therefore, it follows that all biological systems, including
air and pure oxygen activated sludge, trickling filters, aerobic and
aerated lagoons, and rotating biological contactors should, given suffi-
cient detention time, achieve essentially the same effluent BOD^ concen-
tration. This is illustrated by Table 7-24 which presents summary per-
formance data by subcategory for all biological systems, activated
sludge systems and all biological systems other than activated sludge.
Although some variations are apparent, particularly where the data base
in a given subcategory is limited, the data generally tend to support
the above statement. On this basis, biological treatment in general may
be considered the best technology for treatment of OCPS wastewaters.
The specific mechanical system used to accomplish biological treatment
will depend on cost, available space, climate and other site-specific
considerations.
168
-------
TABLE 7-24
BIOLOGICAL SYSTEMS
BODS EFfLUCNT CONCENTRATIONS
PLASTICS only
600* 11
EFFLUENT I I
CONCENTRATION!!
II MINIMUM*
|| MAXIMUMS
| | MEAN
It KEOIAN ฆ
UN
I I
I I
I I
NOV plastics
TYPE 1 AND C *
HOT PLASTICS ||
TYPE I NOT C ** I|
NOT PLASTICS
not TTPE 1
tl
11
ALL HASTE
streams
3.0 II minimum*
66.0 I I HAxIMoM*
19.9 || MEAN ฆ
I| mEOIAN ฆ
I I N ฆ
II
14.0
S3
6.V <1 M]NJHUHซ
4*6,0 I I MAXIMUM*
61.5 II MEAN *
41.0 (I MEOIAN
SO II N *
! I
9.0 II MINIMUM-
760.0 I I MAXIMUM*
60.4 I I MEAN *
ea.o ri median
21 II N *
II
3.0 II MINIMUM!
279.0 II MAXIMUM-
34.7 I I MEAN *
17,0 f| MEDIAN *
IS II N ฆ
I I
3.0 I
760.0 I
*2.6 I
23.0 I
139 I
I
ACTIVATED SLUDGE ONLY
BODS EFFLUENT CONCENTRATIONS
o*
vo
BODS
II
I I
not plastics
{I
EFFLUENT || PLASTICS ONLY II
CONCENTRATION I
I I MINIMUM*
|| MAXIMUMฎ
II MEAN ฆ
I I MEDIAN ฆ
UN *
I I
TYPE 1 AND C * II TYPE 1 SOT C ** I I
...LL.
NOT PLASTICS II NOT PLASTICS ||
NOT TYPE I
I I
ALL HASTE
STREAMS
I
3.0
56.0
MINIMUMฎ
MAXIMUM*
17.6 I| MEAN
10.5
36
MEDIAN
N
6.0 II MINIHJM*
466.0 I I MAXIMUM*
66.0 || MEAN
SO.O I I MEDIAN *
41 M N
I I
11.0 II MINIMUM*
760.0 I I MAXIMUM*
112.2 t| mฃaN *
26.0 I I MEDIAN *
13 II N
I I
3.0
MINIMUM*
27.0 II MAXIMUM*
15.6- I I MEAN
14.0 I I median
9 t I N
I I
3.0 I
760.0 I
57.4 I
26.0 I
101 I
I
BIOLOGICAL SYSTEMS, NOT ACTIVATED SLUDGE
60DS EFFLUENT CONCENTRATIONS
I 6005 11
I EFFLUENT (I
1C0*CฃNJซat1ON|1-
plastics ONLY
NOT PLASTICS
TYPE 1 AND C
NOT PLAST1C8 ||
TYPE I NOT C ||
NOT PLASTICS
NOT TYPE I
II
I I
ALL HASTE
STREAMS
II MINIMUM*
H MAXIMUM*
II MEAN *
I | MEDIAN *
I I N *
I I
4.0 tt MINIMUM*
7.0 tI MINIMUM*
66.0 || MAXIMUM* 251,0 || MAXIMUM*
25,3 II MEAN
20.0 II MEDIAN
IS II N
I I
60,6 tI MEAN
22,0 I I MEDIAN
9.0 I I MINIMUM*
60,0 l| MAXIMUM*
26.6 II MEAN *
19,5 I| MEDIAN *
6 I I N *
I I
6.0 I I MINIMUM*
279,0 |I MAXIMUM*
63.5 II MEAN
20.0
6
MEDIAN
N
4.0 I
279,0 |
40.5 I
*0.S I
36 I
I
* Type I w/Oxidaticn
** Type I w/o Oxidation
-------
The 146 plants in the Summary Data Base which use some form of biologi-
cal treatment, treat a total of 176 different waste streams. Single
stage biological systems are used to treat 138 waste streams. The re-
maining 38 waste streams are treated using two separate biological units
in series. Table 7-25 compares the performance of single and two stage
biological systems. It is apparent that plants using two stage biologi-
cal treatment do not achieve lower effluent concentrations than single
stage systems. In several subcategories, single stage systems produced
lower effluent BOD,, concentrations than two stage systems. This appar-
ent contradiction may have resulted from the fact that the second stage
of many two stage systems was added to upgrade a single stage system
which was either poorly designed, poorly operated or overloaded follow
ing installation. However, due to the absence of interstage monitoring
data, this assumption cannot be verified.
Use of biological treatment as the principal treatment practice will
produce high quality effluents as shown in the previous tables. An
evaluation was done to determine if additional treatment processes,
i.e., polishing ponds and filtration, would further improve effluent
quality. Tables 7-26 and 7-27 present summary data by subcategory which
illustrate effluent BOD^ concentrations from plants using biological
treatment with polishing ponds and filtration processes. A comparison
of the median concentrations in each category indicates that plants with
additional processes do not achieve significantly different effluent BOD
concentrations than plants with only biological treatment.
Although biological treatment has been demonstrated to achieve low ef-
fluent BOD^ concentrations, the median value obtained for all biological
systems in the industry is not considered to represent the best level of
treatment which could be achieved. While some plants in the data base
are well designed and operated, others are operating at less than opti-
mum performance. In order to segregate good performers from bad per-
formers, it was necessary to develop a statistical test to distinguish
the better plants from those operating less efficiently.
Table 7-28 presents a summary of the BOD percent removals for biological
systems in the Summary Data Base. The median for all systems (108
streams) is 95.2% BOD removal. The medians for all subcatgories are
also approximately 95%. Table 7-29 presents effluent data for those
plants achieving 95% removal. These show significantly better effluents
than for all biological systems shown in Table 7-23. Based on this
analysis, 95% BOD removal has been determined to represent well operated
systems.
It is also recognized that use of the 95% removal criteria eliminates
some plants which achieve lower effluent BOD^ concentrations, but by
virtue of having very low influent BOD. concentrations, do not achieve
95% removal. In addition, there are well operated plants that have not
reported percent removal data. In an attempt to addresg this potential
inconsistency, a new segment was evaluated which included all plants
which achieved 95% BOD,, reduction or which achieved an effluent
BOD concentration of 50 rag/1 or less. The resulting frequency distri-
bution of plants as a function of effluent BOD^ concentration and the
summary statistics are presented in Table 7-30. A second analysis was
170
-------
TABLE 7-25
SINGLE STAGE BIOLOGICAL SYSTEMS ONLY
ปOOS EFFLUENT CONCENTRATION!
1 BODS 1
1 EPflUCNT I
PLA3TJC9
1
ONLY I
1 NOT PLASTICS
i type i and c *
It
II
NOT PLASTICS
type i not C **
1 1
1 1
MOT PIUTICI
NOT TYPE I
11
11
ALL HASTE I
streams |
1 1
MINIMUMฎ
1
1 minimum*
6,0
II
MINJMUH*
ป.ซ
1 I
MINIMUM*
*!
11
MINIMUM!
1.0 1
1 1
HA X IHUM*
66,0 |
I MAKIMUMM
166,0
1 1
MAXIMUMฎ
7ซ0,0
1 1
MAXIMUM"
iT).t
11
MAXIMUM*
TftG.O 1
1 l
MEAN
1*.ซ 1
I ซEAN
T6.I
1 1
hEan ป
so,ซ
1 1
MEAN ฆ
31.f
11
MEAN ฆ
Sl.ซ 1
i f
MEDIA* ป
1ซ.0
1 *ฃPJAW
ซl,0
If
MEDIAN ซ
21,0
II
MEDIAN ฆ
17.0
11
MEDIAN ฆ
23.0 1
\ 1
N ฆ
51 I
1 M
61
I 1
M m
21
1 1
N ป
ii
11
N a
US 1
1 1
I
II
II
11
1
TWO STAGE BIOLOGICAL SYSTEMS ONLY
aoos effluent CONCENTRATIONS
BODS 1 I
EffLUENT M PLASTICS ONLY
CONCENT PAT I ON I I
I I MINIMUM*
I | MAX I MUM*
| t MEAN
I f MEDIAN ฆ
n n ฆ
II
11
11
.ปi - -
9.0
4S.0
21.8
17*0
12
NOT PLASTICS
TYPE I AND c
MINIMUM"
MAX I HUH a
HfAN *
median ฆ
N
7.0
468.0
106.7
41.0
17
NOT PLASTICS tt ALL WASTE I
TYPE I NOT C **|t NOT TYPE I II STREAMS I
NOT PLASTICS I I
**.
MINIMUM*
MAXIMUM*
MEAN *
MEDIAN
N ฆ
13.0
101.0
B7.7
63.5
6
MINIMUM*
maximum*
MEAN *
HEOIAN ฆ
N ฆ
MINIMUM*
MAX I HUH*
HEAN ฆ
I I HEOIAN
I I N ฆ
I I
3.0
466.0
70.2
33.0
38
* Type I v/Oxidation
** Type I v/o Oxidation
-------
TABLE 7-26
BIOLOGICAL SYSTEMS WITH POLISHING
B0D5 EFFLUENT CONCENTRATIONS
1 BODS
1
1
NOT PLASTICS
1 1
NOT PLASTICS
NOT PLA
f.TICS
1 ALL
WASTE 1
1 EFfl..UF.NT
1 PI.AST ICS
ONLY 1
TYPF. I
AND C*
1 1
TYPE I
NOT C **
NOT TYPE I
1 STREAMS 1
1 CONCENTRATION
|
1
1
1 < <=MG/L )
1 CUM FREGI
CUM X 1
CUM FRFQI
CUM X
1 1
CUM FREOI
CUM Z
CUM FRERI
CUM Z
1 CUM FRERI
CUM X 1
1 20
1 ? 1
64.3 1
S 1
33.3
1 1
0 1
0.0
3 1
42.9
1 17 1
43.6 1
1 30
1 10 1
71.4 1
6 1
40.0
1 1
0 1
0.0
6 1
05.7
1 22 1
56.4 1
1 40
1 13 1
92.? 1
7 1
46.7
1 1
1 1
37,. 3
6 1
85.7
1 27 1
69.2 1
1 SO
1 14 1
100.0 1
8 1
53.3
1 1
J> 1
66.7
7 1
100.0
1 31 1
79.5 1
1 100
1 14 1
100.0 1
13 1
86.7
1 1
2 1
A6.7
7 1
100.0
1 36 1
92.3 1
1 200
1 14 1
100.0 1
IS 1
100.0
1 1
3 1
100.0
7 1
100.0
1 39 1
100.0 1
1 300
1 14 1
100.0 1
15 1
100.0
1 1
3 I
100.0
7 1
too.o
1 39 1
100.0 1
1 400
1 14 1
100.0 1
15 1
100.0
1 1
3 1
100.0
7 1
100.0
1 39 1
100.0 1
1 500
1 14 1
100.0 1
IS 1
100.0
1 1
3 1
100.0
7 1
100.0
1 39 1
100.0 1
1 600
1 14 1
lOO.O 1
IS 1
100.0
I 1
3 1
100.0
7 1
100.0
1 39 1
100.0 1
1 700
1 14 1
100.0 1
15 1
100.0
1 1
3 1
100.0
7 1
100.0
1 39 1
100.0 1
1 800
1 14 1
100.0 1
1S 1
100.0
1 1
3 1
100.0
7 1
J 00.0
1 39 1
100.0 1
SUMMARY
STATISTICS
1
1 MINIMUM*
6.0 II MINIMUM*
10.0
1 1
MINIMUM*
37.0
1 1
MINIMUM*
.1.0 II MINIMUM*
3.0 1
1
I MAXIMUMฎ
45.0 1
MAXIHUM*
104.0
1 1
MAXIMUM*
1 68.0
I 1
MAXIMUM*
42.0 II MAXIMUM*
168.0 1
1
1 MT AN
13.? 1
MEAN
48.5
1 1
MEAN
34.0
1 1
MEAN
19.1 II MEAN
35.3 1
1
t MEDIAN *
10.0 1
MEDIAN *
50.0
1 1
MEDIAN =
47.0
1 1
MEDIAN =
22.0 II MEDIAN =
23.0 1
1
1 N
14 1
N
15
1 1
N
3
1 1
N
7 1 1 N
39 1
1
1
i
1 1
1 1
1 1
1
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
TABLE 7-27
BIOLOGICAL. SYf.TFHC WITH MMF
BODS EFFLUENT CONCENTRATIONS
1 BODS
1
1 1
NOT PI.A
fiTICS
1 1
NOT PLA
STtC5**
1 1
NOT PLASTICS
11
AI L UA
5TE 1
1 EFFLUENT
1 PLASTICS
ONLY
1 1
TYPF I
AND C*
1 1
TYPF I
NOT
1 1
NOT TYPE I
11
STREAMS 1
1 CONCENTRATION
1
11
1
1 < <=HG/l )
1 CUM FREOI
CUM X
1 1
run FREOI
CUM *
1 irilM FREOI
CUM X
1 IT.UM FRFOI
CUM X
1 ICUM FRFOI
CUM Z 1
1 20
1 2 1
66.7
1 1
2 1
50.0
1 1
0 1
0.0
1 1
1 1
100.0
11
5 1
50.0 1
1 30
1 2 1
66.7
1 1
2 1
50.0
1 1
1 1
50.0
1 1
1 1
too.o
11
6 1
60.0 1
1 40
1 3 1
100.0
1 1
2 1
50.0
1 1
1 1
50.0
1 1
1 1
100.0
11
7 1
70.0 1
1 50
1 3 1
too.o
1 1
2 1
50.0
1 1
1 1
50,0
1 1
I 1
too.o
11
7 1
70.0 1
f 100
1 3 1
100.0
1 1
3 1
75.0
1 1
2 1
100.0
1 1
1 1
100.0
11
9 1
90.0 1
1 200
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
too.o
1 1
1 1
too.o
11
10 1
100.0 1
1 300
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0
1 1
1 1
100.0
11
10 1
100.0 1
1 400
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0
1 1
1 1
100.0
11
10 1
100.0 1
1 SOO
1 3 1
100. O
1 1
4 1
100.0
1 1
2 1
JOO.O
1 I
1 1
100.0
11
10 1
100.0 1
1 600
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0
1 1
1 1
100.0
11
10 1
100.0 1
1 700
1 3 1
too.o
1 1
4 1
too.o
1 1
2 1
too.o
1 1
1 1
100.0
11
10 1
100.0 1
1 800
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0
1 1
1 1
100.0
11
10 1
100.0 1
SUMMARY
STATISTICS
1
I MINIMUH-
3.0
1 1
MINIMUM-
12.0
1 1
MINIMUM-
26.0
1 1
MINIMUM-
17.0
11
MINIMUM-
3.0 1
1
1 MAXIMUM=
37.0
1 1
MAXIMUMฎ
103.0
1 1
MAXIMUM-
30.0
1 1
MAXIMUM-
17.0
11
MAXIMUM-
103.0 1
1
1 MEAN *
15.3
1 1
MFAN
51.5
i i
MFAN
53.0
1 1
MFAN
17.0
11
MEAN ฆ
37.5 1
1
1 MEDIAN =
6.0
1 1
MEDIAN =
45.5
f 1
MEDIAN =
53.0
1 1
MFDIAN =
17.0
11
MEDIAN =
22.5 1
1
1 N
3
1 1
N =
4
11
N
2
1 1
N
I
11
N
10 1
1
1
1 1
11
1 (
11
1
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
TABLE 7-28
blOLUGJCAL SYSTEMS
oOU!> * WE^OVAL
1 MOOS
11
NOT Ht*STJCS
1 1
NU1 PLASTICS
1 1
HOT PLASTICS
1 ALL
XASTf 1
i fcfrt.ue.nT
i Plastics
ONLY
11
TYPE 1
AND C*
1 1
tyke
1
not c **
1 1
*ot Type x
1 STREAMS 1
lCOl*CtNT*ATION
1 I <"Mป/L )
icum FซEUI
CUM ซ
11
Ci'H FRtUI
cum t
1 1
CUM F KFU
1
CUM ft
1 I
CUM
CUM *
1 CUM F*EOI
CUM * I
) 40
1 0 1
0.0
11
0 1
0.0
1 1
0
1
0.0
1 1
0 1
0.0
1 0 1
0.0 1
1 bo
' I
2.3
11
I 1
2.b
1 1
0
1
0.0
1 1
0 1
0.0
1 2 1
1.9 1
1 60
i l i
2.3
11
1 t
2.6
1 1
0
t
0.0
1 1
0 1
o.o
1 2 1
1.9 t
1 TO
ฆ 1 i
2.3
11
2 1
5.1
1 1
0
1
0.0
1 1
0 1
0.0
1 3 1
2.B 1
1 BO
1 3 1
7.P
11
3 1
T,7
1 1
1
1
5.V
1 1
0 1
0.0
1 7 1
6.5 1
1 90
1 8 1
lS.fc
11
6 1
1ปป.4
1 t
7
1
41.2
1 t
1 i
11.1
1 22 1
20.4 1
1 92
1 10 1
23.3
11
10 1
25.6
1 1
a
1
4 7.1
1 1
3 1
33.3
1 31 1
2B.7 t
1 94
1 19 1
44.2
11
13 1
33.3
1 1
11
1
6 A ซ 7
1 1
3 1
33.3
1 *6 I
42.6 1
1 V6
i 25 1
i>e.J
11
20 t
bi .3
1 1
12
1
70.h
1 1
6 I
66.7
1 63 1
SB,3 1
1 90
1 36 1
b3.T
11
27 1
6<9.2
1 1
16
1
9ป.1
1 I
9 1
100.0
1 fe8 1
B1.5 t
1 100
1 A3 1
10P.P
11
39 1
100.0
1 1
17
1
100.0
1 1
9 1
100.C
1 10b t
lon.o I
SlJt'nAKT
STAT 1ST ICS
1 1
1 m jr ]fu>-ซ
41.0
11
"IN
*7,S
1 1
MlMfUr-*
70.6
1 1
mIMmUh*
B6.1
1 MJNJMUMs
*1.0 1
t l
1 MAปlMfc)M*
9V.7
1 1
MA*jMUrซ
ฅ9.6
1 1
KA*1PUH*
96.0
1 1
MA* 1 ML'MS
97,0
1 MAXIMUM*
99.7 1
1 I
1 MfcAN *
92.S
11
mean m
92.T
1 l
~Ean
ฆ
91.0
1 1
MEAN ฆ
94.2
1 mean m
92.5 1
1 1
1 fEOJAk, *
94,7
11
median ฆ
95.7
1 1
mEDIAn
n
92.0
1 1
MEDIAN
95. ซ
\ mฃ.01AN a
95.2 1
1 1
1 N ซ
43
f 1
H P
39
1 1
N
m
17
1 1
N P
9
1 N ฆ
108 1
1 1
1
(1
1 1
1 1
1
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
TABLE 7-29
BIOLOGICAL systems
BOD5 EFFLUENT CONCENTRATIONS
X REMOVAL >= 95*
1 80D5
1
1 1
NUT plastics
1 1
NOT PLASTICS
I NOT PLASTICS
1 1
ALL
HASTE 1
1 effluent
| PLASTICS
ONLY
1 1
TYPE 1
AND C *
1 1
TYPE I
NOT C**
| NOT TYPE I
1 1
STREAMS 1
irnurrutdittnw
1 ( <"MG/L )
1 CUM FREOI
CUM *
1 1
CUM FREQI
CUM I
1 ICUM FREQI
CUM X
ICUM FREQI
CUM X
1 1
CUM FREOI
CUM X |
1 20
1 15 1
75,0
1 1
6 1
26,1
1 1
2 1
33,3
1 4 1
66.7
1 1
27 1
49,1 1
1 30
t 16 I
80.0
1 1
11 1
47,6
1 1
4 i
66,7
1 6 |
100,0
1 1
37 |
67,3 |
1 40
t IT 1
as.o
1 1
16 1
69,6
1 1
4 1
66,7
1 6 1
100,0
1 1
43 1
78,2 |
1 50
1 19 1
95.0
1 1
17 1
71.9
1 1
5 1
83,3
1 6 1
100,0
1 1
47 1
65,5 1
1 100
1 20 1
100.0
1 1
21 1
"1.3
1 1
6 1
100,0
1 6 I
100,0
1 1
53 1
96.4 1
1 200
1 20 1
100,0
1 1
21 1
100,0
1 1
6 1
100,0
1 6 1
100.0
1 1
55 1
100.0 1
1 300
i 20 1
106,0
1 1
23 1
100,0
1 1
6 1
100,0
1 6 1
100,0
1 1
55 1
100.0 I
1 400
1 20 1
100.0
1 1
23 1
100,0
1 1
6 1
100,0
1 6 1
100,0
1 1
55 1
100.0 |
1 soo
1 20 1
100.0
1 1
23 1
100,0
1 1
6 1
100,0
1 6 1
100.0
1 1
55 1
100,0 |
600
1 20 1
100.0
1 1
23 1
100,0
1 1
6 1
100,0
1 6 1
100,0
1 1
55 1
100,6 1
ป 700
1 20 1
100,0
1 1
23 1
100,0
1 1
6 1
100,0
1 6 1
100,0
1 1
55 1
100.0 1
( 800
1 20 1
100,0
1 1
23 1
100,0
1 1
6 1
100.0
1 6 1
100.0
1 1
55 1
100,0 I
SUMMARY
statistics
1
1 MINIMUM"
3.0
1 1
MINIMUM"
6,0
t 1
MINIMUM"
13,0
I MINIMUM"
5.0
1 1
MINIMUM"
3.0 1
1
1 MAXIMUM"
52,0
1 1
MAXIMUM"
154,0
1 1
MAXIMUM"
62.0
t MAXIMUM"
24,0
1 1
MAXIMUM"
154,0 1
1
1 MEAN a
16,&
I 1
MEAN ฆ
13.3
1 1
MEAN "
34,3
1 MEAN a
14,0
1 1
MEAN ฆ
29.5 1
1
1 median ฆ
">.5
1 1
MEDIAN ซ
33.0
1 1
MEDIAN ฆ
25.5
1 MEDIAN "
12.0
1 1
MEDIAN
21.0 |
1
1 N ฆ
20
1 1
N ป
23
1 1
N ป
6
1 N
6
1 1
N "
55 <
1
1
I 1
11
1
t 1
1
* Type I w/oxidation.
** Type I w/o/oxidation
-------
TABLE 7-30
BIOLOGICAL SYSTEMS
B0D5 EFFLUENT CONCENTRATIONS
X REMOVAL > 95X Of< EFFLUENT BOD <* 50 MS/L
1 B0D5 1
1 1
NOT PLASTICS
1 1
NOT
PLASTICS
1 1
NOT PLASTICS
1 1
ALL
MA9TE 1
1 effluent |
1 PLASTICS
ONLY
1 1
TYPE I
AMD C*
1 |
TYPE
I
NOT C**
1 1
NOT TYPE I
1 1
STREAMS |
1 CONCENTRATIONt
1 ( <ซMG/L >
ICUM FRฃQ1
CUM *
1 ICUM freqi
CUM *
1ICUM FREQt
CUM X
1 ICUM FREQI
CUM X
1 1
CUM FREQI
CUM X 1
1 20 1
1 35 1
60,6
11
12 1
36.a
1 1
7
1
43.8
1 1
8 1
57.1
1 1
62 1
54.4 1
1 30 I
1 00 I
78. 4
11
17 1
51.5
1 1
12
1
75.0
1 1
13 |
92.9
1 1
62 |
71.9 |
1 Q0 1
1 4b 1
90.2
11
24 1
72.7
1 1
14
1
67,5
1 1
13 1
92.9
1 1
97 1
65.1 1
1 SO 1
1 SO 1
<>6,0
11
27 1
si. e
1 1
IS
I
93.8
t 1
14 |
100.0
1 1
106 1
93.0 1
1 too 1
1 51 t
100.0
11
31 1
93.9
1 1
16
1
100.0
1 1
14 I
100.0
1 1
112 1
96,J 1
1 200 1
1 51 1
100.0
11
53 1
100,0
1 1
16
1
100.0
1 1
14 1
100.0
1 1
114 1
100,0 1
1 300 1
1 51 1
lOO.U
11
33 1
100,0
1 1
16
1
100,0
1 1
14 I
100*0
1 1
114 1
100,0 1
1 400 1
1 51 1
100.0
11
33 1
100.0
1 1
16
1
100.0
1 1
14 1
100.0
1 1
114 1
100,0 I
1 S00 1
1 SI t
106,0
11
33 1
100.0
1 t
16
1
100,0
1 1
14 1
100.0
1 1
114 I
100.0 1
1 600 |
1 51 !
100.0
11
33 1
100.0
1 I
16
1
100.0
1 1
14 |
100,0
1 1
114 |
10U.0 |
1 700 1
1 51 1
10ซ,0
11
33 1
100.0
1 i
16
1
100.0
1 1
14 1
100.0
1 t
114 1
lOo.o |
1 800 1
1 51 1
100,0
11
33 1
100,0
1 t
16
1
100,0
' 1
14 I
100.0
1 1
114 1
lOu.i I
SUMM/kHY
STATISTICS
1 1
I MINIMUM*
3.0
1 (
MINIMUmb
6,0
1 1
MINIMUM*
'.0
1 1
MINIMUM*
3.0
1 1
MINIMUMฎ
3.0 1
1 1
1 MAXIMUM-
52.0
11
MAXIMUM*
154,0
1 1
MAXIMUM*
62. 0
1 1
MAXIMUM*
42.0
1 1
maximum*
154.0 1
1 1
1 mean ฆ
n.<ป
11
MEAN *
37,2
1 1
MEAN
a
25,9
1 1
MEAN ฆ
17.3
| |
MEAN ฆ
24.5 1
1 1
i median ฆ
12.0
11
median ฆ
30,0
1 1
MEDIAN
a
2ซ.S
1 1
median *
15.5
| |
MEDIAN
16.0 1
1 1
1 N ฆ
51
11
N ฆ
33
1 I
N
a
16
t I
N ฆ
14
| |
N ฆ
114 1
1 1
1
11
1 1
1 1
1 1
1
* Type I w/oxidation
** Type I w/o/oxidation
-------
made using the criteria of plants which achieve 95% BOD reduction or
which have an effluent BOD,, concentration of 30 mg/1 or less. The re-
sults of this analysis are presented in Table 7-31.
In reviewing the data, it appeared that well operated Type I and C
plants exhibited a wider range of effluent BOD values than the plants in
the other subcategories. Subsequent investigations showed that this
effect appeared to be related to the efficiency of water use by plants
in the Type I and C subcategory. Water use efficiency was defined as a
plant's daily water usage divided by its daily production level. The
resulting water use, in gallons per pound of production, was plotted as
a function of effluent BOD^ concentration for the plants in the subcate-
gory identified as achieving 95% removal or effluent BOD less than 50
mg/1. This plot is presented as Figure 7-4. The figure indicates that
plants with low water use, i.e., less than 0.2 gallons per pound, gener-
ally do not achieve effluent BOD^ concentrations as low as do plants
with higher water usage. A more detailed analysis showed this effect to
be limited to those plants in the first quartile of water use. This in-
cluded plants with water use equal to 0.165 gallons per pound or less.
This would suggest that the Not Plastics, Type I and C subcategory be
further divided into low flow (less than or equal to 0.165 gallons per
pound) and high flow (greater than 0.165 gallons per pound) subcategor-
ies. If this is accomplished, the resulting median effluent BOD- con-
centrations of plants with greater than 95% removal or 50 mg/1 effluent
BOD^ would be 26 mg/1 for high flow and 36 mg/1 for low flow plants.
It was previously shown that biological plants followed by additional
unit processes do not achieve significantly lower effluent BOD^ concen-
trations than biological systems alone. This is not the case for efflu-
ent TSS concentrations. Table 7-32 through 7-35 present a comparison of
summary statistics for effluent TSS concentrations based on biological
systems meeting the 95/50 criteria, and 95/50 biological systems follow-
ed by additional unit processes such as polishing ponds, multimedia fil-
ters and activated carbon. These tables show that systems which include
polishing ponds or filters achieve lower median effluent TSS concentra-
tions than those systems which do not. In addition, these data indicate
that polishing ponds and filters achieve comparable effluent TSS levels.
EFFLUENT VARIABILITY
It is well known that biological wastewater treatment systems produce an
effluent of varying quality, much of this attributable to the inherent
nature of the treatment process. The range of this variation is depend-
ent on many process characteristics. In some cases significant changes
in effluent quality may be associated with specific causes such as shock
loads, mechanical failures, poor design or operation, or errors in sam-
pling or analysis.
The term variability, as used in this context, is defined as the varia-
tion in the effluent quality from a properly designed and operated bio-
logical treatment system which is attributable to the basic nature of
the treatment process. Minimizing the impact of the cited specific
causes of variability through the use of proper design and management
techniques can reduce to a minimum the effluent variability which the
177
-------
TABLE 7-31
BIOLOGICAL 3Y3TEMS
BODS EFFLUENT CONCENTRATIONS
* removal >* ssx ok effluent boo < 30 mc/l
1 BOD5 1
1 effluent 1
iconcentrationi
1 ( <*MC/L ) 1
1 plastics
only
1 NOT plastics
1 type I and c*
11
11
nut plastic
TYPE I MOT
0
c**
1 NOT PLASTICS
1 not type I
1 I all waste 1
1 1 STREAMS 1
icum freoi
CU" X
icum freqi
CUM x
1 ICUM FRt'QI
CUM
I
ICUM FREQI
CUM X
1ICUM FREO
CUM X I
1 20 1
1 35 1
79.5
1 12 1
41,4
11
7 1
50
.0
1 a 1
01.5
1 1 62
62,0 I
1 30 |
1 10 1
9 0,9
1 1/ I
56,6
11
12 1
85
. r
1 13 |
100,0
1 1 62
62.0 |
1 40 1
1 41 1
9J.2
1 ?2 1
75. 9
11
12 1
6b
.7
1 13 1
100.0
1 1 66
66,0 1
t 50 1
1 4J 1
Vf.7
1 23 1
79.3
11
13 1
9?
1 13 1
100.0
1 1 92
92,g 1
1 100 1
I 44 I
100,0
1 27 1
'3.1
1 1
14 I
100
f '
1 13 1
100,0
1 1 96
98,0 1
t 20 0 1
1 44 t
100,0
1 2V I
100,0
11
1ซ 1
100
, s
1 13 1
100,0
II 100
100,0 |
1 300 1
1 44 I
100.0
1 ?9 I
100,0
11
1" 1
100
.0
1 13 1
100,0
II 100
100,0 1
1 400 i
1 44 I
100,0
1 29 1
100,0
11
1ซ 1
100
.0
1 13 1
100,0
II 100
100,0 1
1 500 1
1 44 1
100,0
1 ?v 1
100,0
11
14 1
100
,0
1 13 1
100,0
II 100
tofl.0 1
1 bOO )
1 40 I
100,0
I 2 9 1
100,0
i 1
14 1
100
1 13 1
100,0
II 100
100,0 1
1 700 1
1 44 1
100.)
1 av 1
100,0
11
1ซ 1
100
t *
1 13 1
100,0
II 100
1OU.0 t
1 000 1
1 44 1
100.0
1 29 I
100,0
11
14 i
100
,0
1 13 1
100,0
II 100
100.0 I
summary statistics
1 11 MINIMUM"
3,0 I
1 Ml 111 HUM"
6.0
1 1
MINIMUM"
'-.0 1
1 MINIMUM"
3,0
1 |
MINIMUM*
3.0 1
1 11 MAXIMUM"
52,0 1
1 maximum-
150.0
1 1
MAXIMUM"
t:.o 1
1 MAXIMUM"
27.0
1 1
MAXIMUM"
154.0 1
| || mean ฆ
14,7 I
1 MEAN ป
36,9
1 1
Hi; AN h
24,7 1
1 MEAN ฆ
15.a
1 1
mean
22.6 1
1 11 MEDIAN
10.0 1
1 median ป
24,0
11
MEDIAN "
20.0 1
1 MEDIAN "
14.0
1 |
MEDIAN ป
15.0 1
i II N "
1 1 1
<14 1
1 U "
1
2'
1 (
N ป
H 1
1 N ฆ
1
13
1 1
1 1
N
100 1
1
* Type I w/oxidation
** Type I w/o/oxidation
-------
FIGURE 7-4
>1
VO
GAL
LB
TYPE 1 & C PLANTS WITH BIOLOGICAL TREATMENT
effluent bod vs. gal/lb product water discharged
8. 3) (21.51 (18.1) _
2.4 i
2.2 1
2.0 1
1.1
1.6
1.4
1.2
1.0
.8
-n
i 1 1 ซ 1 1 1 r ฆ I 1 1 1 1
20 40 60 80 100 120 140 160 180 200 220 240 260
EFFLUENT BOD, mg/1
-V1
-------
TABLE 7-32
BIOI.PBir.At. SYSTF.MS
TSS EFFLUFNT CONCENTRATIONS
BOD ZREMOVAt. >=952 OR EFFLUENT B0ป <=50M(5/1.
1 TSS |
II NOT PLASTICS
1 1 NOT PLASTICS 1
NOT PLASTICS
1 1 ALL
HASTE 1
1 EFFLUENT 1
1 PLASTICS
ONl.Y
11 TYPE I
ANH C
11 TYPE I
NOT C 1
NOT TYPE I
11 STREAMS 1
1 CONCENTRATION 1
1
I |
1 (
1
- 1 1
1
f ( <=MG/L ) 1
1 CUM FREQI
CUM Z
1 1 CUM FREQI
CUM X
1 1 CUM FREOI
CUM X 1
CUM FRERI CUM X
1 1 CUM FREO
CUM I 1
1 20 1
1 19 1
39.6
II 3 1
JO.7
II 4 1
33.3 1
4 1 28. (
1 1 30
29.4 1
ป 30 1
1 29 1
60.4
II 6 1
21.4
II 5 1
4t #7 1
7 1 50.0
1 1 47
44.1 1
1 40 1
1 34 1
70.8
II 10 1
35.7
II 7 1
58.3 1
10 1 71.4
1 1 61
59.8 1
1 50 1
1 3A 1
75.0
II 12 1
42.9
II 9 1
75.0 1
11 1 78.A
1 1 A8
66.7 1
1 100 1
1 46 1
95.8
II 21 1
75.0
II 11 1
91.7 1
13 1 92.9
1 1 91
B9.2 1
1 200 1
1 48 1
100.0
II ?a 1
100.0
II 1? 1
100.0 1
14 1 100.0
1 1 102
100.0 1
1 300 1
1 48 1
100.0
II 28 1
100.0
II 12 1
100.0 1
14 1 100.0
1 1 102
100.0 1
1 400 1
1 48 1
100.0
II 28 1
100.0
II 12 1
100.0 1
14 1 100.0
1 1 102
100.0 1
1 500 1
1 48 1
100.0
II 78 1
100.0
II 12 1
100.0 1
14 1 100.0
1 1 102
100.0 1
1 400 1
t 48 1
100.0
II ?8 1
too.o
II 12 1
100.0 1
14 1 100.0
1 1 102
100.0 1
1 700 1
1 48 1
100.0
II 29 1
100.0
II 12 1
100.0 1
14 1 J 00.0
1 1 JO?
100.0 1
1 800 1
1 48 1
100.0
II 28 1
100.0
II 12 1
100.0 1
14 1 100.0
1 1 102
100.0 1
I-1
CO
O
SUMMARY STATISTICS
1 II MINIMUM=
4.0 1
1 MJNIMIIM =
9.0
1 1
MINIMUM-
13.0
1 1
MINIMUM=
2.0
1 II MAX IMUM=
127.0 1
1 MAX IMUM =
189.0
1 1
MAXIMIIM =
104.0
1 1
MAXIMUM-
JOt .0
1 11 MEAN =
36.1 1
1 MEAN =
71 .3
1 1
MEAN
40.P
1 1
MEAN
36.4
1 11 MEDIAN =
24.5 1
1 MEDIAN =
A3.5
1 1
MEDIAN -
34.5
1 1
MEDIAN =
30,5
1 1 1 N
1 1 1
48 1
1
1 N
?8
1 1
1 1
N =
1?
1 1
1 1
N
14
MJ.NIMUM=
MAXIMUM=
MEAN
MEDIAN =
N
7.0
189.0
4A.3
33.0
10?
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
TABLE 7-33
BIOLOGICAL. SYSTEMS WITH P 01 ISKINP
TSS EFFLUENT CONCENTRATIONS
BOD ZREMPVAL > = 95Z OR EFFI UFNT BOP <=50M6/L
1 TSS 1
1 NOT PLASTICS 1
1 NOT FLA
STICS
1 1 NOT PLASTICS
1 1 ALL
UASTE 1
1 EFFLUENT 1
1 PLASTICS
ONi.r i
1 TYPE I
AND C 1
1 TYPE I
NOT C
11 NOT TYPE I
11 STRFAMS 1
1 CONCENTRATION!
1
1
1
1
1 --
I |
| |
|
1 < <*MG/l ) 1
1 CUM FRFOI
CUM X 1
ICUh FREGI
CUM X 1
1 CUM FRERI
CUM X
1 ICLJM FRERI CUM X
1 1 CUM FRFO
CUM % 1
I 20 1
1 5 1
38.5 1
1 2 1
25.0 1
1 0 1
0.0
II ? 1 28.6
1 1 9
30.0 1
1 30 1
1 10 1
74.9 1
1 3 1
37.5 1
1 0 1
0.0
II 4 1 57.1
1 1 17
56.7 1
1 40 1
1 11 1
84.6 1
1 4 1
50.0 1
1 1 1
50.0
II 6 1 85.7
1 1 77
73.3 1
1 50 1
1 12 1
92.3 1
1 5 1
(ฆ7.5 1
1 1 1
50.0
II {ฆ 1 85.7
1 1 74
BO.O 1
1 100 1
1 13 1
100.0 1
1 8 1
100.0 1
1 2 1
100.0
II 7 1 100.0
1 1 30
100.0 1
1 200 1
1 13 1
100.0 1
1 8 1
100.0 1
1 7 1
100.0
II 7 1 100.0
1 1 30
100.0 1
1 300 1
1 13 1
100.0 1
1 8 1
100.0 1
1 2 1
100.0
II 7 1 100.0
1 1 30
100.0 1
I 400 1
1 13 1
100.0 1
1 8 1
100.0 1
1 7 1
100.0
II 7 1 100.0
1 1 30
100.0 1
1 500 1
1 13 I
100.0 1
1 8 1
100.0 1
1 2 1
100.0
II 7 1 100.0
1 1 30
100.0 1
1 600 1
I 13 1
100.0 1
1 8 1
100.0 1
1 ?. 1
100.0
II 7 1 100.0
1 1 30
100.0 1
1 700 1
1 1.3 1
100.0 1
1 8 1
100.0 1
1 2 1
100.0
II 7 1 100.0
1 1 30
100.0 1
1 800 1
1 13 1
100.0 1
1 8 1
100.0 1
1 2 1
100.0
II 7 1 100.0
1 1 30
100.0 1
SUMMARY STATISTICS
M
00
1 11 MINIMUMฎ
9.0
1 1
MINIMUM=
9.0
1 1
MINIMUMฎ
31.0 1
1 MINIMUMฎ
7.0 1
1 MINIHUMฎ
2.0 1
1 II MAXIMUMฎ
76.0
1 1
MAXIMUMฎ
95.0
1 1
MAXIMUMฎ
62.0 1
1 MAXIMUMฎ
55.0 1
1 MAXIMUMฎ
95.0 1
1 1 1 MEAN
26.3
1 1
MEAN
49.5
1 1
MEAN
A 5 1
1 MEAN
27.7 1
1 MEAN
34.7 1
1 11 MEDIAN =
23.0
1 1
MEDIAN =
42.0
1 1
MEDIAN =
4A.5 1
1 MEDIAN
26,0 1
1 MEDIAN =
73.5 1
1 1 1 N
1 1 1
13
1 1
1 1
N
8
1 1
1 1
N
2 1
1 N
1
7 1
1 N
30 1
1
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
TABLE 7-34
EIOI Of,ICAt SYPTFhS UITH MHF
TBS ETFLUFNT CON CENT F;ATIONS
BOIi ZRFMOVAL > = 95Z OR EFFLUENT POP <-T>0ftR/L
1 TSS 1
NOT PLASTICS 11
NOT PI. AST ICS
1 MOT PLASTICS
1 ALL
WASTE 1
1 EFFLUENT 1
1 PLASTICS
ONLY
TYPE I
AND C 11
TYF'F I
NOT C
1 NOT TYF'F I
1 STREAMS 1
tCONCENTRATION!
I
I |
1 ฆ -
- 1
1 < <=M6/L ) 1
ICIIM FREQI
CUM Z
CUM FREQI
CUM X 1t
CIJM FREQI
CUM X
ICUM FREQI
CUM X
ICUM FREQI
CUM % 1
1 20 1
1 I 1
33.3
1 1
33.3 II
_. | _
0 1
0.0
1 1 1
100. 0
1 3 1
37.5 1
1 30 1
t 3 1
100.0
2 1
66.7 II
0 1
0.0
1 1 1
100.0
1 6 1
75.0 1
1 40 1
1 3 1
100.0
2 1
66.7 II
0 1
0.0
1 1 1
100.0
1 & 1
75.0 1
1 SO 1
1 3 1
100.0
2 1
66<7 II
1 1
100.0
1 1 1
100.0
1 7 1
B7.P 1
1 100 1
1 3 1
100.0
3 1
100.0 1 1
1 1
100.0
1 1 1
100.0
1 B 1
100.0 1
1 200 1
1 3 1
100.0
3 1
100.0 11
1 1
too.o
1 1 1
100.0
1 8 1
100.0 1
1 300 1
1 3 1
100.0
3 1
100.0 II
1 1
100.0
1 1 1
K'0.0
i e i
J 00,0 1
1 400 1
1 3 1
100.0
3 1
100.0 11
1 1
100.0
1 1 1
100.0
1 8 1
100.0 1
1 300 1
1 3 1
100.0
3 1
100.0 II
1 1
100.0
1 1 1
3 00.0
1 B 1
)00.0 1
1 600 1
1 3 1
100.0
3 1
100.0 11
1 1
100.0
1 I 1
too.o
i n i
100.0 1
1 700 1
1 3 1
100.0
3 1
100.0 11
1 1
100.0
1 1 1
100.0
1 B 1
J 00.0 1
1 800 1
1 3 1
100.0
3 1
100.0 II
1 1
100.0
1 1 1
100.0
1 3 1
100.0 1
SUMMARY
STATISTICS
1 I
1 MINIMUM*
18.0
1 1
HINIMUM=
19.0 11
MINIMUK=
18.0
1 MINIMUMฎ
12.0
1 MINIMIJM"-
12.0 1
1 1
1 MAXIMUM*
24.0
1 I
MAXIMUMฎ
74.0 II
MAXIMUM"
43.0
1 MAXIMl!M=
1?.0
1 MAXIMl)M=
74.0 1
1 1
1 MEAN
21.3
1 1
MFAN
40.7 II
MFAN
48.0
1 MFAN =
17.0
1 MFAN
30.8 1
1 1
1 MEDIAN =
22.0
1 1
MEDIAN =
29.0 11
MED IAN =
48.0
1 MEDIAN =
12.0
1 MEDIAN =
23.0 1
1 1
1 1
1 N
1
3
1 1
1 1
N
3 1 1
1 1
N
1
1 N
1
1
1 N
1
8 1
1
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
TABLE ?-35
VIOlORjr.AI. SYSTEMS WITH ACTIVATED CARPON
TSS EFFLUFNT CPNCFNTRATIONS
BOO ZREMOVAL >*7f,Z OR EFFLUENT BOD <-SOMG/L
1 TSS
1
1 1
NOT PLASTICS^ II
NOT PI.AST ICS , 1
1 NOT PLASTICS 1
1 ALL
WASTE 1
1 EFFLUCNT
1 MASTICS
ONI Y
1 1
TYPF I
ANP C* II
TYPE I
NOT C **1
1 NOT TYPE I 1
1 STREAMS 1
1 CONCENTRATION
1
1 < <-MG/L )
ICUH FRFOI
CUM X
1 1
CUM FRF.QI
CUM X 11
CUM FREOI
CUM X
1 CUM rfiCR 1 CUM X 1
1 CUM FRF.QI
CUM Z 1
1 20
1 0 1
0.0
1 1
0 1
1 1
0 1
0.0 1
10 1 1
1 0 1
0.0 1
1 30
I 0 1
0.0
1 1
0 1
1 1
0 1
0.0 1
10 1 1
1 0 1
0.0 1
1 40
1 0 1
0.0
1 1
0 1
1 1
0 1
0.0 1
10 1 . 1
1 0 1
0.0 1
1 SO
1 0 1
0.0
1 1
0 1
1 1
1 1
100.0 1
10 1 1
1 1 1
50.0 1
1 100
1 1 1
100.0
I 1
0 1
1 1
1 1
100.0 1
10 1 1
1 2 1
100.0 1
1 200
1 1 1
100.0
1 1
0 1
1 1
I 1
100.0 1
10 1 1
i ^ i
1 4 '
100.0 1
1 300
1 1 1
100.0
1 1
0 1
1 1
1 1
100.0 1
10 1 1
1 7. 1
100.0 1
1 400
1 1 1
100.0
1 1
0 1
1 1
I 1
100.0 1
10 1 1
1 2 1
100.0 1
1 SOO
1 1 1
100.0
1 1
0 1
1 1
1 1
100.0 1
10 1 1
1 7 1
100.0 1
1 600
1 t 1
100.0
1 1
0 1
1 1
I 1
100.0 1
10 1 1
1 ? 1
100.0 1
1 700
1 1 1
100.0
1 I
0 1
. 1 1
1 1
100,0 1
10 1 1
1 7 1
100.0 1
1 800
1 t 1
100.0
1 1
0 1
1 1
1 1
100.0 1
10 1 1
1 2 1
100.0 1
SUMMARY
STATISTICS
1
1 MINIMUM-
76.0
1 1
MINIhUM-
1 1
MINIMUMฎ
40.0 1
1 MINIMUM- . 1
1 MINIMUM-
413.0 1
1
1 MAXIMUM"
76.0
1 1
MAXIMUM-
. 1 1
MAXIMUM-
4B.0 1
1 MAXIMUM- . 1
1 MAXIMUM-
76.0 1
1
I MEAN
76.0
1 1
MEAN -
. 1 1
MEAN *
48.0 1
1 MEAN - . 1
1 MEAN
62.0 1
1
1 MEDIAN ซ
76.0
1 1
MF.DIAN ป
1 1
MFHIAN -
48.0 1
1 MITniAH - . 1
1 MFHIAN -
A2.0 1
1
1
1 N
1
1
1 t
1 1
N -
0 1 1
1 1
H -
1 1
1
IN - 0 1
1 1
1 N -
2 1
1
* Type I w/ oxidation
** Type I w/o oxidation
-------
system can achieve. Simply stated, this level is the minimum variabil-
ity which can be practically obtained assuming proper system design,
management, operational control, sampling and measurement.
Effluent variability can be characterized by the statistical analysis of
daily data from well-operated treatment systems. The daily data compu-
ter file available for this analysis contains daily BOD, TSS, COD and
TOC influent and effluent measurements over variable periods of records
from three months to five years. The data base includes records for 50
plants. Although some records were as short as three months, most were
for a period of at least one year. Before performing the variability
analysis, however, it was necessary to screen the 50 plants to identify
those exhibiting acceptable treatment system performance and using prop-
er sampling procedures. This data screening involved the complementary
statistical and engineering analyses described below.
The statistical screening for each plant was based on summary statis-
tics, plots of daily concentrations versus time, and plots of moving
summary statistics. Examples of the plots produced are given in Figures
7-5 and 7-6. The most useful statistical screening tool was the plot of
the moving 12-month 99th percentile illustrated in Figure 7-6. The first
point represents the estimated 99th percentile of data from the first 12
months. Succeeding points represent estimated 99th percentiles of data
from months 2-13, 3-14, etc. This plot reflects changes in either the
mean or variance of effluent concentrations over time. Plots for both
BOD and TSS were produced for each plant based on the lognormal
distribution.
Three types of plots were identified in studying the moving 99th percen-
tile (Y0.99) plots:
Type I: Performance improved over time (there was a time after
which Y0.99 decreased).
Type II: Performance worsened over time (there was a time after
which Y0.99 increased).
Type III: There was a data gap due to modifications in the treat-
ment system (generally followed by improved
performance).
Table 7-36 shows the classification for each plant for BOD and TSS,
along with beginning and ending dates and dates of data gaps (if any).
Data from plants with Type I or III graphs for both BOD and TSS were
tentatively accepted for further engineering analysis. Data from plants
with Type II graphs were examined to determine if some cause for the
worsening performance could be identified.
An engineering analysis also was conducted on each of the 50 candidate
plants with daily data. The analysis consisted of a detailed review of
each plant diagram and other information relevant to plant operation and
performance. Specific points of interest included the relationship of
the effluent sampling site to mixing points for stormwater runoff, un-
treated process water and cooling water, as well as modifications to the
184
-------
FIGURE 7-5
MOVING SUMMARY GRAPH TYPES
185
-------
FIGURE 7-6 PLOT OF ESTIMATED 99th PKKCMJTI I.KS vs. MOVING TJMK INTKKV'AI.S
i\KLhn- i
411
00
as
B
0
0
ซ eซซ
f
F
A
1
III
. - J-lUlli I i 11 llULU JJJJ u.tJJLrLTX7.T_l.tmi.t
i i i i i i i r i i i r
* I is iซ M > 35 41 4( lii bb
noun* 12 ittHTM Tine inTKvml ii
I II HC III li (unlit*, i . nt Zftt-illH nonius. 11C...I
-------
Plant
1
1
3
9
292
15
18
293
27
28
42
44
45
53
60
61
73
75
89
90
96
106
109
110
111
113
118
120
124
126
138
146
170
175
176
220
229
234
236
245
268
269
274
281
TABLE 7-36
SUMMARY OF PLANT SCREENING
BOD
Stream Type Begin Date
A01
I
01
02
75
AO 2
III
01
01
75
A01
III
01
04
77
A01
I
01
15
75
A01
I
01
01
78
A01
I
01
01
78
A01
II
07
02
75
A01
I
01
03
75
A01
III
04
04
78
A01
II
09
03
75
A01
II
01
17
79
A01
I
01
01
79
A01
II
01
02
79
A01
I
01
02
75
A01
II
01
01
78
A01
I
01
03
75
A01
II
05
02
75
A01
I
08
02
74
A01
II
05
01
74
A01
I
01
02
75
A01
I
01
01
75
A01
I
01
07
75
A01
I
05
01
74
A01
II
01
03
75
A01
I
01
04
77
A01
I
01
01
78
A01
I
01
01
79
A01
I
04
01
76
A01
II
01
01
75
A01
I
01
02
75
A01
I
01
05
79
A01
III
01
02
75
A01
II
06
04
78
A01
II
01
03
78
A01
I
08
01
78
A01
II
01
02
75
A01
I
09
01
74
A01
I
01
03
78
A01
III
05
01
78
A01
I
05
21
77
A01
II
01
01
79
A01
.11
01
04
75
A01
I
01
01
75
A01
I
07
02
78
Data Gap
10/76 - 05/79
09/76 - 12/76
05/78 - 08/78
10/76 - 04/79
03/79 - 05/79
187
-------
lant
1
3
9
292
18
293
27
28
44
45
53
73
89
90
96
109
110
111
113
120
123
124
126
138
146
176
220
229
236
245
TABLE 7-36 (Continued)
SUMMARY OF PLANT SCREENING
TSS
Stream
Type
Begin Date
Data Gap
AO 2
III
01/01/75
10/76 - 05/79
A01
II
01/01/77
A01
I
01/15/75
A01
I
01/01/78
AOl
II
07/02/75
A01
I
01/03/75
AOl
III
04/04/78
04/79 - 05/80
AOl
II
09/02/75
AOl
II
01/01/79
AOl
I
01/01/79
AOl
II
01/02/75
AOl
II
05/05/75
AOl
I
05/06/74
AOl
I
01/01/75
AOl
I
01/07/75
AOl
I
06/18/74
AOl
I
01/02/75
AOl
I
01/01/77
AOl
I
04/01/79
AOl
I
04/01/76
AOl
I
06/01/75
AOl
I
01/01/75
AOl
I
01/02/75
AOl
I
01/01/70
AOl
III
01/01/75
10/76 - 04/79
AOl
I
08/01/78
AOl
I
01/03/75
AOl
I
09/01/74
AOl
I
06/01/78
AOl
I
06/21/77
AOl
III
01/01/75
09/76 - 05/78
AOl
I
01/01/79
188
-------
treatment system during or after the period of data collection. A sum-
mary of the engineering analysis is presented in Table 7-37. This table
provides the engineering comments and the nature of the reason for ex-
clusion, where applicable, for each of the 50 candidate plants. A poor
performer has been defined as a plant not achieving 95% BOD removal or
an effluent of 50 mg/1 BOD.
Based on the engineering and statistical analyses, 17 of the 50 plants
were retained for further analysis. Appendix D contains a description
of these plants and the reasons for exclusion. Because treatment system
performance generally improved over time in the selected plants, the
data retained in the final Daily Data Base for each plant were limited
to samples collected within 12 months of the last sampling date.
Having selected daily data representing the performance of well-operated
treatment systems, the next step was to find a statistical model to
characterize effluent variability. The distributional model most com-
monly employed for daily measurements of BOD and TSS is the lognormal
distribution. This model tends to be appropriate because distributions
of daily pollutant measurements have a lower bound of zero, are posi-
tively skewed, and have standard deviations proportional to their means.
To ensure that the lognormal model was appropriate for the data in the
Daily Data Base, distributions of daily data were plotted and goodness-
of-fit tests were run for each plant/pollutant data set. The goodness-
of-fit test employed is described in Appendix B. The results of these
analyses supported the use of the lognormal model.
Finally, effluent variability was characterized for BOD and TSS for each
plant in terms of the variability factorthe ratio of the 99th percen-
tile of the concentration to its long-term average for the daily maximum
and the ratio of the 95th percentile of the concentration to its long-
term median for the 30 day average. The methods used to estimate daily
and 30-day average variability factors are described in Appendix B. The
daily variability factors were based on the lognormal model, and the 30-
day variability factors on the Central Limit Theorem (taking day-to-day
correlation into account). The daily and 30-day variability factors
calculated for each parameter and plant-specific data set in the Daily
Data Base are presented in Tables 7-38 and 7-39. These summary tables
provide the number of observations (N) , the estimated mean, 99th per-
centile (P0.99), 95th percentile (P0.95), daily variability factor
(VF(1)) and 30 day variability factor (VF(30)).
The variability factors were summarized separately for two categories of
plants, Plastics Only and Not Plastics Only. The decision to use two
categories, rather than determine a single set of factors for the entire
OCPS industry, was based on the lower effluent BOD- levels achieved by
Plastics Only plants relative to the rest of the OCPS plants. Further
partitioning of the Not Plastics Only segment for the purpose of calcu-
lating variablity factors did not appear warranted since all plants use
biological treatment as the major treatment technology. In addition,
further partitioning would have effectively reduced the available data
base for each group.
189
-------
TABLE 7-37
SUMMARY OF ENGINEERING ANALYSIS
LANT
>95%R
or
<50 mg/1
EXCLUDED
FROM
ANALYSIS
ENGINEERING COMMENTS AND/OR
NATURE OF AND REASON FOR EXCLUSION
1
yes
yes
Treatment system upgraded during first data
collection period; second data period too
short for analysis.
3
yes
yes
Plant had upsets and bypasses continuously;
poor operation, system modification dur-
ing data period.
9
yes
no
None
292
-
yes
Receives significant amount of municipal
waste of unknown quantity.
15
yes
no
None, BOD only
18
yes
yes
Treatment system under construction during
period of performance, effluent data not
representative.
293
no
yes
Plant is a poor performer^0^ due to inade-
quate solids control (66% removal TSS)
20
-
yes
No effluent data on BOD, COD or TSS
24
-
yes
No effluent data on BOD, COD or TSS
27
-
no
None
28
yes
yes
Chlorination before trickling filter, no
longer manufactures organic chemicals.
42
no
yes
Poor performance plantpoor operating
practices, upset operations during data
period.
44
yes
no
Treatment system changed prior to 1/79.
45
yes
no
None
53
yes
yes
Treatment system inadequate for average
loadings, resulting in poor performance ฐ
and subsequent upgrade of system after data
period.
60
no
yes
BOD only
190
-------
TABLE 7-37 Continued
>95%R EXCLUDED
or FROM
PLANT <50 mg/1 ANALYSIS
61 no yes
72 - yes
73 yes yes
74 - yes
75 yes yes
87 - yes
89 yes yes
90 yes yes
96 yes no
103 - yes
106 yes yes
109 yes yes
110 yes no
111 yes no
113 yes no
118 yes no
120 yes yes
ENGINEERING COMMENTS AND/OR
NATURE OF AND REASON FOR EXCLUSION
Poor performance plantfiltration unit
added after period of performance in order
to improve solids removal.
No effluent data on BOD and TSS
Plant phased out a process during data per-
iod, resulting in drop of 70% BOD load dur-
ing period of record.
No effluent data on BOD, COD or TSS
Effluent sample point downstream of point
where stormwater and cooling water are mixed
with contaminated wastewater.
Sample point is downstream of nonbiotreated
effluent dilution, BOD and TSS data
unavailable.
Sample point downstream of untreated process
water dilution.
Sample point downstream of cooling water
dilution.
None
No effluent data on BOD or TSS
Sample point downstream of cooling water
dilution.
Effluent contains unquantified dilution from
a "consolidated" sump.
None
None
None
None
Treats refinery wastewater with 0CPS waste-
water .
191
-------
TABLE 7-37 Continued
>95%R EXCLUDED
or FROM ENGINEERING COMMENTS AND/OR
PLANT <50 mg/1 ANALYSIS NATURE OF AND REASON FOR EXCLUSION
123
"
yes
Sample point downstream of stormwater dilu-
tion (no BOD data).
124
yes
yes
Sample point downstream of stormwater mixing
point.
126
yes
no
None
138
no
yes
Poor performer^0^
146
yes
yes
Sample point downstream of stormwater
dilution.
170
yes
no
BOD data only
175
yes
no
None
176
yes
yes
Only three months of data available
220
yes
no
None
234
yes
no
None, data is for secondary system only.
236
yes
no
None
245
yes
yes
Non-biological treatment
268
no
yes
None
269
no
yes
Poor plant performance^0^ appears due to
plant being undersize; plant has upgraded
treatment since data period.
274
-
yes
Significant portion of wastewater treated is
sanitary flow.
294
yes
Poor performance^0^ is due to poor solids
control, especially for plant with sand
filtration.
281
yes
no
None
Poor performance is defined as not achieving 95% BOD removal or
50 mg/1 effluent BOD.
192
-------
TABLE 7-38
ESTIMATES OF VARIABILITY FACTORS "PLASTICS ONLY" PLANTS
Effluent
BOD
Effluent
TSS
Plant
N
X
P0.99
P0.95
VF( 1)
VF(30)*
N
X
P0.99
P0.95
VF( 1)
VF(30)
9
24
5.84
17.88
-
3.06
-
24
29.72
97.58
-
3.28
-
44
261
8.97
29.51
11.84
3.29
1.32
260
11.58
80.50
19.76
6.95
1.71
45
156
3.07
10.67
4.28
3.47
1.39
364
18.95
124.62
30.87
6.57
1.63
96
105
2.31
7.86
-
3.41
-
66
12.34
45.26
16.05
3.67
1.30
111
157
6.19
18.38
9.25
2.97
1.49
347
10.42
54.12
14.84
5.19
1.42
126
249
6.05
23.70
10.23
3.92
1.69
253
23.28
78.35
31.10
3.37
1.34
AVG
3.35
1.47
AVG
4.84
1.48
* Where there was insufficient data to estimate day-to-day correlation, no VF(30) value is given.
-------
TABLE 7-39
ESTIMATES OF VARIABILITY FACTORS "NOT PLASTICS ONLY" PLANTS
Effluent
BOD
1
1
Effluent TSS
Plant
N
X
P0.99
P0.95
VF( 1)
1
VF(30)* I
1
N
X
PO.99 P0.95
VF(1)
VF(30)
15
363
16.88
63.55
22.80
3.77
1
1.35 1
1
26
160
17.55
68.26
26.69
3.89
!
1.52 I
1
158
21.86
76.32 28.99
3.49
1.33
110
247
5.91
21.82
8.37
3.69
l
1.42 |
1
218
10.09
45.33 14.37
4.49
1.42
113
332
17.47
75.06
28.95
4.30
1
1.66 I
I
91
22.41
100.27 31.22
4.48
1.39
118
365
12.17
61.34
25.25
5.04
l
2.07 1
1
170
103
33.90
145.75
74.51
4.30
1
2.20 1
1
175
361
39.09
181.49
69.66
4.64
1
1.78 I
1
220
55
55.13
291.35
-
5.28
l
i
149
94.09
441.22
4.69
-
234
157
11.58
41.60
16.74
3.59
1
1.45 1
1
236
162
32.19
93.17
39.75
2.89
1
1.23 I
1
362
59.72
159.29 72.55
2.67
1.21
281
205
8.44
26.73
11.62
3.17
1
1.38 |
i
AVG
4.05
l
1.61 |
AVG
3.95
1.34
~Where
there
was insufficient
data to
estimate day-to-day
correlation
no VF(30) value is
given
-------
WASTEWATER DISPOSAL
The method of treatment for the direct dischargers was discussed under
the previous heading. Under this heading the treatment processes and
disposal methods associated with zero or alternate discharge in the OCPS
industry are described.
Zero or Alternate Discharge
Zero or alternate discharge is defined as no discharge at the OCPS plant
of contaminated process wastewater to either surface water bodies or to
POTWs. Means by which zero or alternate discharge may be achieved are
described in the following paragraphs.
Deep Well Disposal
Deep well injection is a method frequently used for disposal of highly
contaminated or very toxic wastes not easily treated or disposed of by
other methods. Deep well injection is limited geographically because of
the geological requirements of the system. There must be a substantial
and extensive impervious caprock strata overlying a porous strata which
has no utility as a water supply or other withdrawal.
Because of the potential hazard of contaminating useable aquifers, some
states prohibit the use of deep well disposal. Contamination of these
aquifers can occur: (1) from improperly sealed well casings which allow
the waste to flow up the bore hole, and (2) from unknown faults and fis-
sures in the caprock which allow the waste to escape into the useable
stratum. The latter is conceivable even though the fault may be miles
from the well and the migration of the waste material to the fault might
take many years. This problem could be enhanced by the increased sub-
terranean pressure created by the injection well and could be further
enhanced if a substantial withdrawal of water from the useable aquifer
were made in the vicinity of the caprock flow.
Deep wells are drilled through impervious caprock layers into such unus-
able strata as brine aquifers. The wells are usually more than 3,000 ft
deep and may reach levels over 15,000 ft. Pretreatment of the waste for
corrosion control and especially for the removal of of suspended solids
is normally required to avoid plugging of the receiving strata. Addi-
tional chemical conditioning could be required to prevent the waste and
the constituents of the receiving strata from reacting and causing plug-
ging of the well.
Because of the relatively high pressures required for injection and dis-
persion of the waste, high pumping costs for deep well disposal may be
incurred.
A total of 20 plants in the Summary Data Base practice deep well injec-
tion. The wastes disposed of in this manner are fairly concentrated
with mean BOD, TSS and COD of 3368 mg/1, 4301 mg/1 and 14,242 mg/1, re-
spectively.
195
-------
Contract Hauling
Another method of achieving zero discharge is contract removal and dis-
posal. This method involves paying a contract hauler/disposer to pick
up the wastes at the generation site and to haul them to another site
for treatment or disposal. The hauling may be accomplished by truck,
rail or barge.
Contract hauling is usually limited to low volume wastes, many of which
may require highly specialized treatment technologies for proper dis-
posal. Although plants utilizing this technology are defined as zero
dischargers, an impact on the environment may not be eliminated since
the wastes are relocated only from the generating site and may be treat-
ed and discharged elsewhere. Reported data regarding contract disposal
indicates that there are 15 plants using this disposal method in the
Summary Data Base.
Offsite Treatment
Offsite treatment refers to wastewater treatment at a cooperative or
privately owned centralized facility. Offsite treatment and disposal
are used by plants that do not choose to install and operate their own
treatment facilities. The rationale for utilization of offsite treat-
ment usually is economically oriented and governed by the accessibility
of suitable treatment facilities willing to treat the wastes (usually on
a toll basis). Sometimes adjacent plants find it more feasible to in-
stall a centralized facility to handle all wastes from their facilites.
The capital and operating costs usually are shared by the participants
on a pro-rata basis.
Depending on the nature of the waste and/or the restrictions imposed by
the receiving treatment plant, wastes sent for offsite treatment may re-
quire pretreatment at the generating plant. Four plants in the Summary
Data Base practice off-site treatment.
Incinerat ion
Incineration is a frequently used zero-discharge method in the OCPS
industry. Depending upon the heat value of the material being incin-
erated, incinerators may or may not require auxiliary fuel. The gaseous
combustion or composition products may require scrubbing, particulate
removal, or another treatment to capture materials that cannot be dis-
charged to the atmosphere. This treatment may generate a waste stream
that ultimately will require some degree of treatment. Residue left
after oxidation will also require some means of disposal.
Incineration is usually used for the disposal of flammable liquids,
tars, solids, and/or hazardous waste materials of low volume and not
amendable to the usual EOP treatment technologies. In all, seven plants
in the Summary Data Base employ incineration. Only three data points
were reported for incineration. The average of those data showed a
waste BOD of approximately 25,000 mg/1.
196
-------
Evaporation
Evaporation is used in the OCPS industry to reduce the volume of waste
water and thereby concentrate the organic content to render it more
suitable for incineration or disposal to landfill. This technology is
normally used as in-plant treatment or pretreatment for incineration or
landfill.
Evaporation equipment can range from simple open tanks to large, sophis-
ticated, multi-effect evaporators capable of handling large volumes of
liquid. Typically, steam or some other external heat source is required
to effect vaporization. Therefore, the major limitations to mechanical
evaporation is the amount of energy required.
Only two OCPS plants, both exclusively plastics, reported evaporation as
their principal disposal method.
Impoundment
Impoundment generally refers to wastewater storage in large ponds.
Alternate or zero discharge from these facilities relies on the natural
losses by evaporation, percolation into the ground, or a combination
thereof. Evaporation is generally feasible if precipitation, tempera-
ture, humidity and wind velocity combine to cause a net loss of liquid
in the pond. If a net loss does not exist, recirculating sprays, heat
or aeration can be used to enhance the evaporation rate to provide a net
loss. The rate of percolation of water into the ground is dependent on
the subsoil conditions of the area of pond construction. Since there is
a great potential for contamination of the shallow aquifer from percola-
tion, impoundment ponds are frequently lined or sealed to avoid percola-
tion and thereby make the basins into evaporation ponds. Solids which
accummulate over a period of time in these sealed ponds will eventually
require removal. Land area required for impoundment is a major factor
limiting the amount of flow disposed by this method.
Twelve plants in the Summary Data Base use impoundment for wastewater
disposal. The wastewaters handled in this way are relatively concen-
trated having average BOD, TSS and COD levels of about 2700, 2000 and
7500 mg/1, respectively.
Land Disposal
There are two basic types of land disposal: landfilling and land appli-
cation (or spray irrigation). Landfilling consists of dumping the
wastes into a pit and subsequently burying them. Land application re-
quires spraying the wastes over land. Both disposal methods require
care in selecting the site to avoid any possibility of contaminating
ground and surface water. The type of pollutant being disposed by land
application also must be considered. For instance, if the land is to be
used for growing crops at a later time, some of the pollutants present
197
-------
at the time of application may persist in the soil for long durations
and later may be assimilated by the crops and find their way into the
food chain.
Four plants in the Summary Data Base practice land disposal.
198
-------
SECTION VIII.
ENGINEERING COSTS AND NON-WATER QUALITY ASPECTS
INTRODUCTION
This section addresses the cost, energy requirements and non-water qual-
ity environmental impacts associated with meeting BPT effluent guide-
lines. The cost estimates represent incremental expenditures required
to supplement the control and treatment technology presently in place.
Cost estimates have been prepared using a modified version of the CAPDET
computer costing algorithm. Non-water quality aspects reviewed include
the potential for (a) air pollution, (b) solid waste generation, (C)
RCRA considerations, (d) noise pollution, and (e) energy requirements.
COST DEVELOPMENT
In order to estimate the industry expenditures required to meet alter-
native effluent targets, and as a partial basis for economic studies, a
plant-by-plant cost analysis has been made. Capital, operating and an-
nual costs were developed for each of the plants that supplied suffi-
cient information to the Summary Data Base. For each plant, the cost of
applying various treatment technology alternatives to meet selected tar-
get concentrations for BOD and TSS was conducted.
The basic calculation tool used to develop alternative engineering costs
(with the exception of RBC costs) is the computer program, CAPDET
(Computer Assisted Procedure For the Design and Evaluation of Wastewater
Treatment Facilities). The CAPDET computer model was developed jointly
by the Corps of Engineers' Waterway Experiment Station, Vicksburg, Mis-
sissippi and the EPA Office of Water and Waste Management. The major
purpose of the CAPDET model is to provide for the rapid design, cost
estimating and ranking by cost of municipal sewage treatment plant al-
ternatives for the EPA Construction Grants Program. The model may be
used for the design of industrial wastewater treatment systems by modi-
fying selected computer program default values. A detailed discussion
of the design and application of the CAPDET program is presented in
Appendix E.
CAPDET MODIFICATIONS
Development of the specific costs applicable to this study requires
adaptation of many of the factors in the program from their default val-
ues for municipal systems to values more appropriate to chemical indus-
trial wastewater and to industrial plant situations. Table 8-1 summar-
izes the quantitative bases and default values employed, reflecting
those adjustments considered necessary for an industrial wastewater
system.
Because of the varying complexity and biodegradability, as well as the
generally lower biodegradability of industrial wastewaters as opposed to
the essentially constant treatability of domestic wastewater, reaction
rate coefficients must be adjusted from CAPDET default values. A
199
-------
TABLE 6-1
PROCESS
ADJUSTMENTS TO CAPDET DEFAULT
DATA AND RESULTS
CAPDET
VALUE
ADJUSTED
VALUE
DEFAULT
OR
RESULT
ASL
ALA
k = 0.00135 1/mg/hr
k = 0.001 1/mg/hr
5 ! dfly/ 1 Where: DEFAULT
doy/24hr/So mg So = BOD Influent Concentration
k =
5 / day/ 1
day/24/hr/So mg
DEFAULT
PRIMARY
CLARIF1 Ell
("IN" "ASL" AND "ALA"
TRAINS)
BOD 96 Removal
= 32%
BOD % Removal
= 1096
DEFAULT
DAF, CLAR
Land Result
Based on
$1000/acre
Laboratory
Labor Based
on Flow
Land Result Based
on Dimensions of
Unit al $10,000
per acre
Laboratory Labor
3ased or, Prorotion
of $50,000/yr for 1
r^nn per an entire waste
Treatment Plant
RESULT
RESULT
ALL UNITS
Administrative
Costs Based
on Flow
201 Planning
indirect Cost
Equal TO 3.5%
of Construction Cost
and Cont ingency
Equal to 896
Administrative
Costs Equal to
15 percent of
of/maint. labor
Delete 201
Planning and
Adjust Contingency
to 11.5% of
Construction
Costs
RESULT
-------
reaction rate coefficient of 5.0 days is used to represent organic
chemical wastewater. In the primary clarification segment of the acti-
vated sludge process the percent BOD reduction is taken as 10 percent,
rather than the default value of 32 percent. These changes adapt
CAPDET1 s approach to the design of organic chemical industrial waste-
waters. Alternative cost factors were needed for certain limited scope
treatments to avoid the flow-loaded factors applicable to complete sys-
tems. Administrative costs for clarification and dissolved air flota-
tion were set at 15 percent of the operating and maintenance labor
costs.
Laboratory labor was also adjusted to reflect discrete unit manpower
requirements for clarification and dissolved air flotation processes.
Laboratory charges are based on the use of one full-time individual for
an entire waste treatment system. The approximate annual cost is
$50,000. Costs are prorated over the various treatments and assumed
constant, whether the flow volume treated was high or low. The hourly
laboratory charges include analyst's base pay plus overtime, fringe ben-
efits, lab equipment and materials and miscellaneous overhead burdens.
The availability of land and its valuation varies markedly with site
specific conditions. If land is available on the site, its potential
future use and opportunity cost should be considered. If land is not
available, purchase of the necessary acreage must be considered. The
CAPDET default value of $1000 per acre is judged to be substantially on
the low side, possibly several times too low. Where appropriate, if
land costs were a factor in the technology costs, both acreage and cost
per acre were separately estimated and inserted to override in the pro-
gram. In these cases estimated acreage costs of $10,000 per acre were
used to represent the industrial value of land.
In developing the cost analysis, the cost of upgrading an existing
treatment facility is assumed to be approximated by the cost of second
stage treatment as an addition to the existing facilities. This repre-
sents a conservative approach to cost development in that it reflects
the maximum cost of upgrading an existing system. In many cases, less
expensive treatment system modifications, improved operating practices,
or application of in-plant source control techniques may achieve equal
or better results at a lower cost. However, in the absence of extensive
plant-by-plant design details, second stage or add-on treatment was used
as the cost basis. True costs will depend significantly on factors site
specific for each plant.
Other considerations when applying CAPDET to industrial treatment esti-
mates are as follows:
1. Unless changed by the user, CAPDET uses default values for
conventional pollutant concentrations and other stream characteristics.
Also, for each treatment process, specific relationships exist for the
removal of the conventional pollutants. For example, the long term mean
(LTM) TSS in the activated sludge model is reported at the raw waste-
water influent as 200 mg/1 (LTM) and at the final clarifier effluent as
20 mg/1 (LTM). For industrial wastewaters, a final effluent of 20 mg/1
201
-------
(LTM) may be optimistic and is more likely to be in the range of 30 to
50 mg/1 (LTM) unless flocculants or other settling aids are used. Some
of the CAPDET values were found to be suitable for industrial wastewater
treatment calculations and consequently were not revised. The influent
and effluent values for the other characteristics (COD, 0&G, TOC, etc.)
are reported as noted in Tables 8-2 and 8-3; however, these values do
not affect the cost estimates and are included in CAPDET primarily for
municipal planning purposes.
2. The cost estimates are generated for average flows. A common
engineering design practice is to determine the flow and other parameter
variability, and design on a basis of an 80 to 95 percentile value. The
exact design value chosen is determined by the range of variability of
the parameter and the subjective opinion of the engineer. Built into
the evaluation is a long range corporate objective or plan pertaining to
future expansions, changes in product lines and similar factors which
might affect the various parameters associated with the design. Since
these factors were not available, the average flow values were used as a
basis for the cost estimates. However, since the cost curves show
ranges of parameter values, costs for any flow can be derived for any
individual plant. Furthermore, CAPDET has built-in Excess Capacity Fac-
tor equations which allow for peak flow vs. average flow performance in
calculating the detention times and other design factors of the
technologies.
3. The cost generated by CAPDET for activated sludge and aerated
lagoons appear to be insensitive to changes in target effluent BOD
concentrations when the influent concentration is less than 500 mg/1.
This phenomenon is created by the fact that the CAPDET model introduces
a second equation for aeration detention time calculation at the 500
mg/1 influent concentration and selects the larger value of the two.
The formula used for the detention time calculations when the influent
BOD concentration is greater than 500 mg/1 is:
t = (1-S /S ) / (S /S k X ) (1)
e o e o v
Where:
t = detention time, hours
Sg ฎ effluent BOD concentration, mg/1
S = influent BOD concentration, mg/1
o
k = reaction rate constant 1/mg hr
Xv = mixed liquor volatile suspended solids, mg/1
When the specific influent BOD concentration is below 500 mg/liter, the
following equation is added, the retention time calculated by both meth-
ods, and the greater time is reported:
202
-------
TABLE 8-2
CAPDET
TEMPERATURE
SUSPENDED SOLIDS
VOLATILE SOLIDS
SETTLEABLE SOLIDS
bod5
SBOD
COD
SCOD
pH
CATIONS
ANIONS
Pฐ4
TKN
nh3
N02
no3
OIL AND GREASE
DEFAULT INFLUENT WASTE CHARACTERISTICS
18.0 ฐC
200 mg/1
60 % of SS
15 mg/1
250 mg/1
75 mg/1
500 mg/1
400 mg/1
7.6
160 mg/1
160 mg/1
18 mg/1
45 mg/1
25 mg/1
0 mg/1
0 mg/1
80 mg/1
203
-------
TABLE 8-3
WASTE CHARACTERISTIC REMOVAL DEFAULT
VALUES FOR CAPDET PROCESSES
WASTE CHARACTERISTIC REMOVALS
PROCESS
BODc
TSS
COD
OIL &
GREASE
TKN
PHOS
NH,
SETTLEABLE
SOLIDS
Dissolved Air
Flotation
302
80Z
30Z
101
N3
O
Primary
Clarification
Activated
Sludge
32*
USER INPUT
INFLUENT
AND EFFLUENT
58Z
USER INPUT
TO SECONDARY
CLARIFIER
AO*
1.5 x BOD,
EFF
5X
30Z
5*
30Z
SET
EQUAL
TO TKN
Aerated
Lagoon
USER INPUT
INFLUENT
AND EFFLUENT
USER INPUT
TO SECONDARY
CLARIFIER
ASSUME
SAME AS ASL
Multi Media
Filtration
SET EFFLUENT
EQUAL TO
BODSOLUBLE
60Z
SET EFFLUENT
EQUAL TO
CODSOLUBLE
PASS ON
THROUGH
PASS ON
THROUGH
PASS
THROUGH
INFLUENT
INFLUENT
-------
t = (24 S ) / (X (F/M))
o v
Where:
(2)
t = detention time, hours
Sq = influent BOD concentration, mg/1
= mixed liquor volatile suspended solids, mg/1
F/M = food to microorganism ratio, lbs/day/lb
usually 0.3-0.6
In comparing equations (1) and (2) it should be noted that the detention
time (t) in equation (1) is influenced by influent and effluent sub-
strate concentrations, the reaction rate "k," and the reactor MLVSS.
The detention time determined by equation (2) is a function of the in-
fluent substrate concentration, MLVSS and the F/M ratio. Since the de-
tention time determined by equation (2) is theoretically independent of
the effluent concentration, a single cost is determined for all effluent
target levels considered.
Figure 8-1 compares the calcuated detention time determined by the two
methods. The solid lines represent the result of applying equation (1)
at various target levels. The dashed line presents the results of equa-
tion (2) with the same applied influent concentration. Note that the
time curves from both equations merge as the influent BOD decreases in
concentration. Since the CAPDET program uses the greater of the two
values calculated for detention time, cost estimates for aerators will
be slightly overestimated for wastewaters with influent BOD concentra-
tions less than 500 mg/1 (LTM) and effluent concentrations of 50 mg/1
(LTM).
ESTIMATING DISCRETE UNIT COSTS
Engineering cost estimates are presented for the following wastewater
treatment processes:
1. Dissolved air flotation
2. Clarification
3. Activated sludge
4. Aerated lagoon
5. Multimedia filtration
The cost estimates were prepared using the CAPDET model which was mod-
ified as previously indicated to reflect industrial rather than munici-
pal treatment costs.
An example of the engineering costs determined by CAPDET for a typical
treatment application are shown for each of the above unit processes in
Tables 8-4 through 8-8. The installed cost of the machinery is shown by
unit, in the second column, followed by the amortization cost for the
individual equipment pieces. Because the life expectancy of different
205
-------
200
180
160
140
120
H 100
ID
80!
60
40
So = Influent BOD Concentration (100 mg/1)
FIGURE 8-1 - AERATOR RETENTION TIME SENSITIVITY ANALYSIS
-------
TABLE 6-4-C3ST S'^rARY, RjJIATION
Unit
Installed
Equipment
Cose
$
Arrort.
Cose
$/YR
Oper.
Labor
Cost
$/YR
>'iainc.
Labor
Cost
$/VR
Power
Cose
$/YR
$0.04/KWH
Material
Cose
$/YR
Cne^acai
Cose
$/YR
Plar.c
0:J<
Cost
$/YR
Flocacion
Total
283,767
288,767
29,114
29,114
6,664
6,664
1,259
1,259
7,841
7,841
2,857
2,887
-0- 18,651
-0- 18,651
TOTAL CONSTRUCTION COST $
DIRtoi
Installed Equipment
Contractor OH & Profit
Total Direct
i'Zcr
lAIO
Misc. Non Construction
A/E Design Fee
Inspection
Technical Costs
Acmin/Legal
Contingencies
Total Indirect
288,767
63,528
352,295
1,000 (0.1 acres)
17,614
31,733 (9.017. Const. Cost)
7,045
7,045
7,045
40,513
111.995
TOTAL O&M COST $/YR
Plant Cost 18,651
Laboratory Cose 12,500
Administration 1,188
Total 32,339
EQUIVALENT ANNUAL COST $/\
$ฃc,889/YR
PLANT DESICN BASIS
FLOW 4.0 MTD
INF TSS 200 rrg/1
EFF TSS 40 rag/1
Total Direct and Indirect 464,290
-------
TABLE 8-5-COST Sii-;-V\i
-------
TABLE 8-6 COST SLH'ARY. ACTIVATED SLUDGE
Installed Oper. Mam: Pli-t
Equi-j^renC Anort. Labor Labor Power Material Chemical G5ซM
Uhic Cose Cose Cose Cost Cose Cose Cose Cose
$ $/YR $/YR 5/YR $/YR $/YR $/YR $/YR
$0.04/KWH
Prim Cla
107,816
9.904
2.546
1,206
299
1,078
-0-
5,129
PuTiping
92,668
9,926
3,200
2,170
2,679
650
-0-
8,699
S Sec CI
145,374
13,354
3,184
1,458
309
1,453
-0-
6,404
Cornp Mix
1,430,337
165,006
34,063
17,526
321,666
6.637
-0-
379.892
Grav 'ltic
61,984
5,694
2,288
1,534
247
619
-0-
4,688
Dry Beds
152,994
17,970
19,216
7.958
-0-
1,376
-0-
28,550
lioul & Lf
81,402
36,706
1,771
-0-
-0-
11,234
-0-
13,005
Total
2,072,777
261.563
66.271
31,855
325,855
23,050
-0-
446,367
TOTAL CONSTRUCTION COST $
TOTAL O&M COST $/YR
DIRECT
Installed E^uipmsnc
Contractor OH & Profit
Total Direct
INDIRECT
Land
Misc. Hon Construction
A/E Design Fee
Inspection
Technical Costs
Admin/Legal
Contingencies
2,072,777
456,010
2,528,787
126,439
169,827 (6.727. Const. Cost)
50,575
50,575
50,575
390,809
Plarit OtSM Cost
Laboratory Cost
Administration
Total
446,367
19,149
6,911
472,427
EQUIVALENT AK~JAL COST S/YP.
$875,296/YR
PLANT DESICN BASIS
INF BOD
1000
mg/1
EFF BOD
30
mg/1
FLOW
1
MSD
(. 95 acre)
EFF TSS
50
mg/1
Total Indirect
848,285
Total Direct & Indirect 3,377,072
-------
TABLE 8-7-COST SIM-WRY, AEPvATED LAGOON
Installed
Oper.
Ma int.
Piant
Equipment
Ainort.
Labor
Labor
Power
Material
Cnemical
O&M
Unit
Cost
Cost
Cost
Cost
Cost
Cost
Cost
Cost
$
$/YR
$/YR
$/YR
$/YR
$/YR
$/YR
$/YR
$0.04/KWH
Prim Tnnt
170,064
16,098
13,915
5,741
1,859
4.251
-0-
25,766
Aer Lago
211,090
31,646
3,965
587
42,888
3,099
-0-
50,539
L Prm CI
107,817
9,904
2,546
1,202
300
1,078
-0-
5,126
TVra St L
556,842
65,406
-0-
16,129
-0-
1,824
-0-
17,953
L Prm CI
107,817
9,904
2,546
1,202
300
1,078
-0-
5,126
Grav Tnc
47,850
4,395
1,596
1,140
210
478
-0-
3.424
Dry Beds
90,568
10.638
11,181
4,616
-0-
815
-0-
16,612
lioul & Lf
68,410
30,847
1,030
-0-
-0-
11,234
-0-
12,264
Total
1,360,458
178,838
36,779
30,617
45,551
23,857
-0-
136,810
TOTAL CONSTRUCTION POST $
TOTAL OM COST $/YR
DIRECT
Installed Equipment
Contractor OH & Profit
Total Direct
INDIRECT
Land
Misc. Non Construction
A/E Design Fee
Inspection
Technical Costs
Admin/Legal
Contingencies
Total Indirect
1,360,458
299,301
1,659,759
22,000 (2.2 acres)
82,988
117,157 (7.06% Const. Cost)
33,195
33,195
33,195
190,871
512,601
Plant O&M Cost
Laboratory Cost
A&ninistration
Total
136,810
28,649
28,414
193,873
EQUIVALENT ANNUAL COST $/YR
$467,705
PLANT DESIGN BASIS
Total Direct & Indirect 2,172,360
-------
TABLE 8-8-COST SUVARY,MULTIMEDIA FILTRATION
Unit
Installed
Equipment
Cost
$
Anort,
Cost
$/YR
Labor
Cost
$/YR
Maint.
Labor
Cost
$/VR
Power
Cost
$/YR
Material
Cost
$/YR
Cnemical
Cost
$/YR
Plait
O&M
Cost
$/YR
Filtrati
Pimping
Total
345.396
142,710
488,107
40.570
15.254
55,824
1.292
3,825
5,117
605
2,202
2,808
1,264
10,684
11,948
10,040
998
11,039
-0-
-0-
-0-
13.201
17,709
ฆ30.910
TOTAL CONSTRUCTION POST $
DIRECT
Installed Equipment
Contractor OH & Profit
Total Direct
Land
Misc. Non Construction
A/E Design Fee
Inspection
Technical Costs
Admin/Legal
Contingencies
458,107
107,373
595,490
14,261
29,774
48,106 <8.087. Const. Cost)
11,909
11,909
11,909
68,481
TOTAL O&M COST $/YR
Plant OSM Cost 30,910
Laboratory Cost 24,936
Administration 17,458
Total 73,304
EQUIVALENT ANN'UAL COST $/YR
S164.561/YR
PLANT DESIGN BASIS
INF TSS 40 nig/1
ErF TSS 16 mg/1
AVG FLOW 4.0 MGD
Total Indirect
196,349
Total Direct & Indirect
791,839
-------
pieces of equipment varies quite widely, CAPDET uses different amortiza-
tion periods for different equipment. For example, the operating life
expectancy of a pump may be 2 to 10 years, but a concrete structure such
as a clarifier may have a life expectancy of 50 years. A listing of the
life expectancy used by CAPDET for various treatment system components
is presented in Table 8-9. This table also serves to define the unit
process keywords shown in Tables 84 thru 8-8.
The lower part of the tables summarize the construction costs (direct
and indirect), the operation and maintenance costs and the equivalent
annual costs. Also included is the basis of the unit process design.
Discrete unit cost curves for all treatment processes evaluated are in
Appendix F.
Dissolved Air Flotation
In wastewater treatment, dissolved air flotation (DAF) is used as a
clarification process to remove suspended solids, or oil and grease. It
may also be used as a thickening process to concentrate various types of
flotable sludges or scums.
The principal components of this system are a pressurizing pump, chemi-
cal mix tanks, air injection facilities, a retention tank, a backpres-
sure regulating device and a flotation unit. The influent data used for
the model includes wastewater flow and suspended solids concentration in
the feed. Variations in both flow and concentration occur in industrial
situations and consequently are considered in most designs; however, the
governing parameter in the design of flotation units is the flow rate.
Except in extreme cases, the solids concentration does not influence the
size or operating cost of the unit.
CAPDET approximates BOD and COD removals in primary clarification and
flotation at 30 percent each, with default influent values of 250 mg/1
and 500 mg/1, respectively. These values are for estimation purposes
for municipalities only and do not affect the costs of dissolved air
flotation, which are primarily a function of flow rate.
Costs for polymer addition are included in this exercise as an option.
The suggested usage of dissolved air flotation for solids removal is
limited to effluent values of 50 mg/1 (LTM) TSS. CAPDET assumes 80 per-
cent removal of TSS and 30 percent removal of BOD. In practice, the
reduction of suspended solids ranges from 70 to 95 percent with inci-
dental BOD removal ranging from 10 to 50 percent. Table 8-4 is an
example summary sheet for cost data at 4 MGD, and Figure 8-2 presents
the cost versus flow curves from dissolved air flotation. Figure 8-2
presents costs with and without chemical addition.
Clarification
Clarification (sedimentation) is a solids-liquid process designed to re-
move suspended particles that are heavier than water. Primary clari-
fiers are normally used in conjunction with biological wastewater treat-
ment systems to remove the settleable solids and a fraction of the BOD
212
-------
TABLE 8-9
CAPDET UNIT PROCESS REPLACEMENT SCHEDULE
Replacement
Schedule
Unit Processes Key word Cost Item (years)
Activated Sludge Units
Complete Mix
COMPLE
Mechanical Aerator
(RSSA)
20
Contact Stabilization
CONTAC
Diffuser (RSPD)
30
Extended Aeration
EXTEND
Swing Arm Diffuser
(RSPH)
30
High Rate
HIGH R
Pump (RSPS)
25
Plug Flow
PLUG F
Structural (RSST)
40
Air Flotation
AIR FL
Air Flotation Unit
(RSFS)
30
Structural (RSST)
40
Aerated Lagoon
AERATE
Mechanical Aerator
(RSSA)
15
Liner (RSLL)
15
Structural (RSST)
40
Chemical Feed Systems
None
Alum System
40
(Service life cannot
Iron Salts System
40
be changed)
Lime System
40
Polymer System
40
Drying Beds
DRYING
4-in. Pipe (RSCP)
20
6-in. Pipe (RSCP)
20
8-in. Pipe (RSCP)
20
Structural (RSST)
40
Equalization
EQUALI
Floating Aerator (RSSA)
15
Liner (RSLL)
15
Structural (RSST)
40
Filtration
FILTRA
Filter Unit (RSSF)
20
Pump (RSPS)
25
Package Filter Unit
(RSSF)
20
Structural (RSST)
40
Gravity Thickening
GRAVIT
Thickener (RSTS)
40
Structural (RSSt)
40
Sludge Hauling and
HAULIN
Vehicle (RSSV)
6
Land Filling
Structural (RSST)
40
Lagoon
LAGOON
Steel Pipe (RSSP)
20
Butterfly Valve (RSSV)
20
Liner (RSLL)
15
Structural (RSST)
40
Microscreening
MICROS
Microscreen (RSSM)
15
Structural (RSST)
40
213
-------
TABLE 8-9 (Continued)
Unit Processes
Primary Clarification
Primary
Two-Stage Lime
Pumping
Secondary Clarification
General
Activated Sludge
Denitrification
Nitrification
Oxidation Ditch
Pure Oxygen
Trickling Filter
Key word
PRIMAR
L PRIM
PUMPIN
CLARIF
A SECO
D SECO
N SECO
0 SECO
P SECO
T SECO
Replacement
Schedule
Cost Item (years)
Mechanism (RSMS)
Structural (RSST)
Pump (RSPS)
Structural (RSST)
Mechanism (RSMS)
Structural (RSST)
40
AO
25
40
40
40
214
-------
No Chemicals
With Chemicals
CArl-T AEtOSTS-
YR*
tป,jB ,1
FLOW (MILLION GAL/DAY)
FIGURE 8-2 - CAPITAL, OPERATING AND ANNUAL COSTS
DISSOLVED AIR FLOTATION
215
-------
and thereby reduce the load on the biological systems. Secondary clari-
fiers are used after the biological system to remove the biomass for
disposal or recycle.
Clarifier costs are related to wastewater flow, since the overall cost
of a clarification unit is not greatly affected by influent and effluent
TSS levels. Suspended solids removal through sedimentation typically
ranges from 60 to 90 percent, with incidental BOD removal ranging from
10 to 40 percent.[8-1] As previously indicated, CAPDET has been modi-
fied to use a constant 10% BOD removal through primary clarification.
Clarification with floculation can producet TSS levels as low as 30
mg/1. [8-2] The cost of polymer addition is included as an option.
Secondary clarification units following biological treatment systems
represented in the summary data base achieve an effluent TSS concentra-
tion of about 35 to 60 mg/1 (LTM). The cost of clarification for var-
ious flow rates is presented in Figure 8-3. A cost summary example for
a 4 MGD waste stream is listed in Table 8-5. CAPDET uses a circular
clarifier in developing a process design.
Complete Mix Activated Sludge
Activated sludge is the most commonly used biological treatment process
for removing soluble and colloidal contaminants from process wastewa-
ters. [8-3] One of several possible unit process sequences for complete
mix activated sludge treatment of industrial wastewater is shown in Fig-
ure 8-4. This typical design includes a complete mix activated sludge
unit with primary and secondary clarification, sludge recycle, gravity
thickening, sludge drying and hauling, and landfilling.
The input data required by CAPDET for this technology includes influent
BOD, flow and a target effluent BOD. Average values are considered and
the flow is assumed to be constant. A detailed calculation procedure is
employed by CAPDET using coefficients and constants, adjusted as neces-
sary for industrial application, as shown in Table 8-1.
The use of average input values is judged to provide cost estimates of
sufficient accuracy to provide the basis for an economic impact evalua-
tion. Although in actual site specific design practice the variability
in flow and raw wastewater characteristics would be considered, the ex-
cess capacity included in the design calculations depends upon a de-
tailed statistical study of the variability of all parameters. Once
this is made, the design basis is influenced by the intuitive and sub-
jective evaluation of the design engineer, and in some cases by corpor-
ate policy.
As an alternative to exhaustive site specific analysis, CAPDET provides
an Excess Capacity Factor which automatically oversizes the activated
sludge plant by the equation:
(ECF)t = 1.3 - 0.002 Qavg>
216
-------
No Chemicals
With Chemicals
^^SG/^IHT^3fflCi=q5I5}(I0:VTR>.
FLOW (MILL ION GAL/DAY)
FIGURE 8-3 - CAPITAL, OPERATING AND ANNUAL COSTS, SEDIMENTATION
217
-------
EFFLUENT
>
INFLUENT
RECYCLE
SLUDGE
SLUDGE
DRYING
GRAVITY
THICKENER
HAULING
AND
LANDFILL
PRIMARY
CLARIFIER
ACTIVATED
SLUDGE
SECONDARY
CLARIFIER
FIGURE 8-4- ACTIVATED SLUDGE PROCESS CONSIDERED FOR COST ESTIMATION
-------
Where:
(ECF)t = excess capacity factor for tank volume of aerator
= average daily wastewater flow MGD
(ECF)t is never less than 1.1
In similar calculations other components of the system also have excess
capacity built in to calculations to accommodate peak demands and emer-
gencies. Thus, without the rigorous variability analysis of the param-
eters, it is judged that peak demands are adequately addressed by the
Excess Capacity Factor term in the model.
CAPDET predicts costs for BOD effluent levels less than 10 mg/1 (LTM).
However, considering the complex nature of industrial waste water and
the relative accuracy of the test for BOD (+15 percent), it is reason-
able to limit the general use of these costs to a minimum effluent
target of 10 mg/1.
Several sample sets of curves are presented in Figures 8-5 through 8-7.
Each set of curves lists capital, operating, or annual costs for a var-
iety of effluent BOD concentrations and a fixed influent concentration.
An example cost summary sheet used to plot one set of data points is
presented in Table 8-6.
Aerated Lagoons
Aerated lagoons can provide a cost effective alternative to activated
sludge treatment where sufficient land area is available. Because aer-
ated lagoons utilize much longer detention times with lower biological
solids concentrations they are less sensitive to variations in organic
loading and flow.
The aerated lagoon system can approach or equal the organic removal ca-
pability of an activated sludge process, provided the unit is properly
designed and operated. As indicated in Section VII, 26 plants in the
Summary Data Base report using aerated lagoons as the major wastewater
treatment process. Median effluent BOD and TSS for these plants are 15
mg/1 and 33 mg/1, respectively.
Figure 8-8 shows the aerated lagoon system process diagram used for cost
estimation. Table 8-7 shows a sample cost summary sheet, and Figures
8-9 through 8-11 graphically present a set of capital, operating and
equivalent annual cost curves for aerated lagoons.
Multimedia Filtration
Removing finely divided suspended materials from wastewater (effluent
polishing) is a growing technology of modern wastewater treatment. Two
common methods are multimedia filtration and microstraining.[8-4] The
design of filters depends on influent wastewater characteristics, proc-
ess hydraulic loadings, method and intensity of cleaning; nature, size
and depth of the filtering material, and the required quality of the
219
-------
INFLUENT ป 1,000 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 8-5-CAPITAL COSTS, ACTIVATED SLUDGE (1,000 mg/1)
220
-------
INFLUENT - 1,000 mg/L BOD
O
<
z
<
C3
a
ซ
f
a
f* .-m
19
,\
.X
.J
FLOW (MILLION GAL/DAY)
FIGURE 8-6-OPERATING COSTS, ACTIVATED SLUDGE (1,000 mgA)
221
-------
BOD INFLUENT - 1.000 mg/L
ta a % .ป .ป
* ซ > *j
FLOW (MILLION GAL/OAV) mg/L
FIGURE 8-7-ANNUAL COSTS, ACTIVATED SLODGE(1,000 mg/1)
222
-------
INFLUENT
AERATED LAGOON
EFFLUENT
SLUDGE
DRYING
GRAVITY
THICKENER
HAULING AND
LANDFILL
SECONDARY
CLARIFIER
PRIMARY
CLARIFIER
FIGURE 8-8 - AERATED LAGOON PROCESS CONSIDERED FOR COST ESTIMATION
-------
INFLUENT = 1000 mg/L BOD
f '
o
V
o
u
<
h-
50y<}Q ;--c n ckl C- irig/L
FLOW (MILLION GAL/DAT)
FIGURE 8-9-CAPITAL COSTS, AERATED LAGOONS (1,000 mg/1)
224
-------
INFLUENT = 1000 mg/L BOD
FLOW(MILLION GAL/DAY)
FIGURE 8-10 - OPERATING COSTS, AERATED LAGOONS (1,000 mg/1)
225
-------
INFLUENT = 1000 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 8-11ANNUAL COSTS, AERATED LAGOONS (1,000 mg/1)
226
-------
final effluent. However, the costs of filtration are primarily depend-
ent on flow rate. In general, multimedia filters are more effective
than most filters and are easier and less expensive to operate for the
treatment of wastewaters. Typically, either multimedia or dual-media
filtration will reduce suspended solids to about 5 to 19 mg/1 (LTM).
Multimedia filtration has been shown to reduce TSS levels by 55 to 99
percent in various cases.[8-5] In addition to suspended solids re-
moval, resulting incidental BOD removals ranging from 40 to 90 percent
have been accomplished using multimedia filtration.[8-5]
The design considered for cost estimation of multimedia filtration in-
cludes a layered filter with anthracite, sand, garnet sand and gravel.
Pumps are used to provide pressure backwash. Surge tanks are provided
to control the return of waste filter backwash water to treatment units.
Surface sprayers and air blowers are included (see Figure 8-12).
Table 8-8 lists a sample cost summary sheet. The capital, operating and
annual costs are plotted versus flow in Figure 8-13.
Polishing Ponds
Where sufficient land is available, polishing ponds may present an econ-
omically attractive alternative to multimedia filtration or microscreen-
ing as a means of reducing effluent TSS. It was determined that CAPDET
could not be conveniently used to estimate polishing pond costs. There-
fore, a manual estimating procedure similar to that used by CAPDET was
used to determine the cost of applying polishing pond technology to four
OCPS plants. The four plants which were selected represented a wide
range of flow conditions. In addition, the four selected plants includ-
ed one from each of the four proposed subcategories. Table 8-10 pre-
sents a cost summary for the application of polishing ponds at each of
the four plants. Table 8-11 shows a comparison of the capital, operat-
ing and annual costs for polishing ponds with those costs generated by
CAPDET for multimedia filtration. As indicated in the table, polishing
pond costs are significantly lower. There are some minor differences in
the cost estimating methods used, for example, polishing pond estimates
do not include laboratory, administrative or inspection costs. These
costs are, however, not significant in relation to the total cost of
applying the technology. Inclusion of these additional cost items will
still result in polishing pond technology being more cost effective than
either multimedia filtration or microscreening.
Multimedia filtration, although more costly, is a more universally ap-
plicable technology. The significantly smaller land requirement may
make filtration more attractive to plants where space is limited.
Since polishing ponds may not represent an implementable option at all
OCPS manufacturing plants, multimedia filtration was used in preparing
the plant-by-plant cost estimates. As indicated in Table 8-11, this
represents a very conservative engineering approach in developing in-
dustry costs. Therefore, many of the OCPS industry plants will be able
to provide solids control at a lower cost than that reflected by the
plant-by-plant cost estimates.
227
-------
INFLUENT
~
BACKWASH COLLECTION
t-o
N3
oo
ANTHRACITE
SAND
FINE SAND
GRAVEL
SURFACE WASH
EFFLUENT
BACKWASH
EFFLUENT
SURGE TANK
FIGURE 8-12 - MULTIMEDIA FILTRATION PROCESS
-------
3
CAP ITAL tCOSTSjU lofs)
o
"EQUIVALENT ANNUAL-COSTS-(IQ7S/TR}
I C35A L'lT EiiAilC i
FLOW (MILLION GAL/DAY)
FIGURE 8-13 - CAPITAL, OPERATING AND ANNUAL COSTS,
MULTIMEDIA FILTRATION
229
-------
TABLE 8-10
COST SUMMARY, POLISHING PONDS
Plant: 9
Flow: 0.7 MGD
Subcategory: PLASTICS
Item Unit Cost Amount Total Cost($)
3 3
Excavation (3,000 min) 1.20 $/yd 346 yd 3,000
Earth Prep (3,000 min) . 3,000
Liner 0.54 $/ft 3900 ft 2,100
Subtotal 8,100
Miscellaneous (15% of subtotal) 1,215
Subtotal 9,315
Engineering (15%)(5,000 min) 5,000
Contingencies (15%) 1,400
Total Installed Cost 15,715
Land (2X pond) 10,000$/acre 0.18 acre 1,800
TOTAL CAPITAL COST 17,515
Operating Cost
Maintenance (10%)
Sludge Disposal 7,600
Total Operating Cost
TOTAL ANNUAL COST
12.5% T.C.C. & T.O.C.
1,750
$/yr MGD 530
2,280
4,470
230
-------
TABLE 8-10 (Continued)
COST SUMMARY, POLISHING PONDS
Plant: 97
Flow: 0.86 MGD
Subcategory: NOT PLASTICS/NOT TYPE I
Item Unit Cost Amount Total Cost($)
Excavation 1.20 $/yd"* 4258 yd"* 5,100
Earth Prep 2 5,100
Liner 0.54 $/ft 34225 ft 18,480
Subtotal 28,680
Miscellaneous (15% of subtotal) 4,300
Subtotal 32,980
Engineering (15%)(5,000 min) 5,000
Contingencies (15%) 4,950
Total Installed Cost 42,930
Land (2X pond) 10,000$/acre 1.6 acre 16,000
TOTAL CAPITAL COST 58,930
Operating Cost
Maintenance (10%)
Sludge Disposal 7,600
Total Operating Cost
TOTAL ANNUAL COST
12.5% T.C.C. & T.O.C.
5,900
$/yr MGD 6,540
12,440
19,800
231
-------
TABLE 8-10 (Continued)
COST SUMMARY, POLISHING PONDS
Plant: 171
Flow: 1.44 MGD
Subcategory: NOT PLASTICS/TYPE I W/O OXIDATION
Item Unit Cost Amount Total Cost($)
Excavation 1.20 $/yd^ 7130 yd"^ 8,560
Earth Prep 8,560
Liner 0.54 $/ft 55225 ft 29,820
Subtotal 46,940
Miscellaneous (15% of subtotal) 7,040
Subtotal 53,980
Engineering (15%)(5,000 rain) 8,100
Contingencies (15%) 8 ,100
Total Installed Cost 70,180
Land (2X pond) 10,000$/acre 2.6 acre 26,000
TOTAL CAPITAL COST 96,180
Operating Cost
Maintenance (10%) 9,620
Sludge Disposal 7,600 $/yr MGD 10,940
Total Operating Cost 20,560
TOTAL ANNUAL COST 32,600
12.5% T.C.C. & T.O.C.
232
-------
TABLE 8-10 (Continued)
COST SUMMARY, POLISHING PONDS
Plant: 60
Flow: 5.07 MGD
Subcategory: NOT PLASTICS/TYPE I WITH OXIDATION
Item
Excavation
Earth Prep
Liner
Unit Cost
1.20 $/yd~
0.54 $/ft"
Amount
25100 yd"
180625 ft
Subtotal
Total Cost($)
30,120
30,120
97,540
157,780
Miscellaneous (15% of subtotal)
Subtotal
23,670
181,450
Engineering (15%)(5,000 min)
Contingencies (15%)
Total Installed Cost
27,200
27,200
235,850
Land (2X pond) 10,000$/acre
TOTAL CAPITAL COST
8.4 acre
84,000
319,850
Operating Cost
Maintenance (10%)
Sludge Disposal
Total Operating Cost
TOTAL ANNUAL COST
12.5% T.C.C. & T.O.C.
7,600 $/yr MGD
31,985
38,530
70,515
110,500
233
-------
TABLE 8-11
COMPARISON OF POLISHING POND AND MULTIMEDIA FILTER COSTS
MULTIMEDIA FILTRATION
Plant Capital Cost Operating Cost Annual Cost
9 240,000 22,000 52,000
60 900,000 80,000 190,000
97 520,000 42,000 100,000
171 600,000 50,000 120,000
POLISHING PONDS
9 17,515 2,280 4,470
60 319,850 70,515 110,500
97 58,930 12,440 19,800
171 96,180 20,560 32,600
234
-------
BENCH MARK ANALYSIS
A bench mark analysis was performed to compare the wastewater treatment
technology cost estimates generated by CAPDET to actual industry exper-
ience. The objective of such an analysis is to determine the reason-
ableness of relying on the modified CAPDET costing model to estimate
OCPS industry wastewater treatment costs.
Appropriate cost data were available from a total of four facilities,
three from the organic chemicals and plastics and synthetics resins
industry, and one from the petroleum refining industry. The data tab-
ulated from these facilities, shown in Table 8-12, were selected because
of their similarity to treatment system configurations utilized in the
CAPDET est imat e s.
In all cases the costs were adjusted to the same cost year dollars to
avoid distortions caused by changes in the construction cost index.
Although there are differences in the cost comparisons between the
CAPDET plants and the industry plants, there is no definitive pattern to
the differences in either magnitude or direction.
It is judged that cost differences may be due to variations in the cost
accounting and cost estimating procedures which vary from one company to
another.
In reference to the capital cost differences, the variations between the
CAPDET estimates and the industry actuals are within the range normally
associated in industrial practice with the preliminary engineering cost
(+30%). To obtain more precise values requires substantially more de-
tailed information than is available from the industrial costs studied.
It is therefore judged that CAPDET is a useful model with sufficient
accuracy in cost estimating to permit an economic impact analysis to be
made, providing that the industrial factors are used in the model as
required.
EFFLUENT TARGET LEVELS
During the initial phases of the regulatory development, a series of
effluent target levels for the OCPS industries were defined based on the
performances demonstrated by the plants represented in the data base.
Targets were selected to range from the minimum treatment level judged
necessary to avoid serious potential adverse impacts on receiving wa-
ters, to the maximum degree of treatment shown to be achievable by well
designed and operated plants within the industry group.
The least stringent BOD target concentration has been defined as 50
mg/1 (LTM). Of the direct discharge plants in the data base, 74 percent
have effluent BOD concentrations equal to or less than this value. For
Plastics Only plants the most stringent target considered for BOD is 10
mg/1 (LTM). This corresponds to an effluent BOD concentration slightly
below the median obtained for well run Plastics Only plants (see Table
7-27). For Not Plastics Plants, the lowest effluent BOD target has been
235
-------
TABLE 8-12-30^
Plane No., Treatment Type,
and Design Paraneters
#146
ASL @ 0.8 MOD
BOD INF 720 ng/1
BOD EFF 20 rrg/1
#42
ASL @ 0.13 MSD
BOD INF 6,000 ng/1
BOD EFF 380 ng/1
#178
ASL @ 3.5 MGD
BOD INF 1,000 mg/1
BOD EFF 50 mg/i
Petroleum Refinery
ASL P 2.2 MGD
BOD iNT 134 mg/I
BOD EFF 12 ng/1
CLAR @ 2.2 MGD
a\F without Chemical
Feed @ 2.2 MGD
Reported
Costs
2,421,000
376,800
661,600
1,082,000
190,000
317,000
7,960,000
837,000
1,778,000
Installed Equipment
Costs Only, $ 630,000
Installed Equipment
Costs Only, $ 190,000
Installed Equipment
Costs Only, $ 155,000
Capital,?
Operating,?/YR
Eq. Annual,$/YR
Capital,?
Operating,S/YR
Eg. Annual,?/YR
Capital,?
Operating,?/YR
Eq. Annual,?/YR
OKf-ARISCNS
7. Difference
CAPDET Difference Coirpared to
Costs (CAPDET - Reported) Reported Cost
CAPDET IS
2,300,000
310,000
580,000
-121,000
- 66,800
- 81,600
57. low
187. low
127. low
900,000
140,000
260,000
-182,000
- 50,000
- 57,000
177. low
267. low
187, low
8,000.000
1,200,000
2,140,000
+ 40,000
+363,000
+362,000
0.57. high
437. high
207, high
868,000 +238,000 387. high
155,000 - 35,000 187. low
205,000
+ 50,000
327. high
-------
defined as 15 mg/1 (LTM). This represents the median value obtained by
the "Not Type I" segment of the Not Plastics Plants.
Three suspended solids targets were evaluated for engineering cost esti-
mations. The highest effluent TSS target considered was 50 mg/1 (LTM),
which represents the level generally achievable using conventional clar-
ification. Sixty-six percent of direct dischargers in the data base
reported effluent TSS concentrations equal to or less than this value.
The minimum target concentration considered is 20 mg/1 (LTM), which is
judged to be attainable using multimedia filtration or microscreening
technology.
Based on these considerations, a series of target concentrations for BOD
and TSS were defined. These targets, and the plants to which they are
applied are presented in Table 8-13.
TABLE 8-13
EFFLUENT TARGET LEVELS
Target Level (BOD/TSS)mg/l Applied to
I (50/50) All Plants
II (30/30) All Plants
III (20/20) All Plants
IVa (10/20) Plastics Plants
IVb (15/20) Not Plastics Plants
For the plant-by-plant analysis, a tabulation of costs was prepared for
each plant listing the treatment technology alternatives and correspond-
ing estimated costs required to meet the four proposed effluent target
levels for BOD and TSS. An example cost summary sheet for achieving
Targets I, II and III for plant 203 is presented in Table 8-14. This
example provides a reference for the following discussion.
The treatment alternatives considered for this plant-by-plant analysis
include clarification, dissolved air flotation, activated sludge, aera-
ted lagoons and multimedia filtration.
Based on an anlysis of the data available for engineering cost analysis,
there are plants that will require (a) biological treatment for the re-
moval of BOD and/or TSS, and/or (b) solids removal treatment for the re-
duction of TSS and/or BOD levels, or (c) no further treatment.
To achieve further BOD removal, the following criteria based on the gen-
erally attainable treatment levels (see Section VII) are established for
the plant-by-plant analysis:
1. For plants with BOD concentrations greater than the targets and
with reported solids less than the targets, biological systems
are required except in the case of Criterion 3.
237
-------
TABLE 8-14 SAMPLE PLANT-BY-PLANT COST ANALYSIS
ho
oj
00
IUQMIQ *
Cปu (1/yซl
Ifllvtnl Tatyat It
ruinu.r1 ioD7t rr
Cftpilol
Cmi tn
ซJllng
C#ซi ll'ri)
Anrtwol
Cปu {!/,.)
TS5 [UK**!
(ฆ<~1)1 /V7
Kiperlid
100/1 SI - OO/iO)
isj Copiioi ~
All*lnublซ Ceil (H
I. Ml tlO/JOl tT/AfYO SO CCO U&Qdi) 1. ClAl
I. AlA IJO'IOO) /.>JCC CCO /OO.CXO 100.0(0 I. OA f
3. MMf
ng A rwc I
Co.MUr.) Co..(l/r)
^wgjuicJ Toi!
riant Ttป
Copltฎ'
Co. I m
Opซfollng A^rwoJ
Co.t (1'Yi) O.i (1/Yil
(5C)
00)
(20)
A
2i^92. LiJ&e_ Zxccq
<&ฃฃฃฃ& &U\ฃt
i-AS l- x> t\i.QQC>
AL*/cux [jUitfp jui,Qafi__ 323
100/Til >-(10/301
-ปr cepti
Anซlfkoti|ซ Coil
in
Cq.i l\/r>)
' ll/r'l
StปQ9ฐ> -2^02.
JfW-1 5"? nrr?
./u/mmf ik^cai
J. rtLA/MAtp- I.L^oor.O l If.otX) 3S3,QCLL>
r.(ฆ< Itllni Tf l III IOD/TSS (JO/JOI
ir.TijrtTTIUU/ilS CipTl"! OpiTolTSj ปWI >ปIIJ| Hi Copiioi ฆ u^TSl", Ann^i 1 !ป9ซ.iซj 17771 Co,.li J <37^ |7] JCi^l
All.iwlll. cปll III C.llll/,.) C..lH/,i) AlHln.1,1. Crnl 111 Cป.l(l/r.| Cป.'ll/ri) fl.., l,.lป,,v C.,1 111 Co.l 0 Y, 1 Co.l ll 'Y.l
i. Ail iป/w s-igrcn ฃi(&> m^ap ' MW/ <"> ?ฃฐ,ck
-------
2. For plants with BOD concentrations greater than the targets (but
not exceeding the targets by an amount equal to 60 percent of
the target concentration) and with TSS concentrations greater
than the targets, BOD reduction can be achieved with solids
removal.
3. For plants with BOD concentrations within the 60 percent range
of targets specified in Criterion 2 and with TSS concentrations
less than the targets, BOD reduction by solids removal may be
achieved if the amount of BOD to be removed is less than or
equal to 75 percent of the TSS available for removal. This
assumes 75 percent of the solids removed are biological and
thus contribute to effluent BOD. Multimedia filters have been
shown to reach effluent solids concentration of 5 to 19 mg/1
(LTM).
4. For plants requiring the addition of biological systems, the
solids leaving the proposed secondary clarifiers are assumed to
meet the TSS Target of 50 mg/1 for activated sludge systems.
However, for aerated lagoons some form of secondary solids
separation will be required to achieve the 50 mg/1 TSS Target.
Additional solids treatment beyond conventional secondary clar-
ification is required for all biological systems to achieve
Targets II and III. The exception to this rule includes cases
where a biological system is added to a reported biological sys-
tem of the same type which produce solids concentrations that
meet the proposed targets. For example, an activated sludge
system added to a reported activated sludge system with exces-
sive BOD and sufficiently low TSS is assumed to produce solids
with similar settling characteristics and equivalent effluent
TSS levels.
5. For each target, three biological alternatives are presented for
the cases requiring BOD reduction by means of biological treat-
ment. If solids removal alternatives are also presented, there
are several possible combinations of bio-solid treatment alter-
natives. For example, an aerated lagooon system may be combined
with additional clarification, dissolved air flotation, or mul-
timedia filtration. There is no specific combination intended
by placement of biological and solids alternatives on the same
line of the cost sheet for each plant.
To achieve further TSS removal the following criteria are
established:
1. For plants with TSS concentrations greater than the targets and
also requiring biological treatment, the achievable TSS effluent
concentrations are determined by the biological system (activa-
ted sludge: 50 mg/1 (LTM), aerated lagoon: 100 mg/1 (LTM). For
Target I, additional solids removal alternatives are required
for aerated lagoons, but not for activated sludge systems.
Additional solids removal alternatives are required for all
biological systems for Targets II and III except as noted.
Clarification and dissolved air flotation are suitable alter-
239
-------
natives to achieve Target I, but for Targets II and III, multi-
media filtration or microscreening is necessary.
2. For plants with TSS concentrations above the proposed target
levels and without additional biological system requirements,
further solids removal can be achieved to reach Target I by
clarification or dissolved air flotation, or for Targets II and
III by multimedia filtration or microscreening.
3. For plants with TSS concentrations exceeding 200 mg/1 (LTM) ,
clarification or dissolved air flotation should precede multi-
media filtration (or microscreening).
4. For plants with insufficient TSS data, but sufficient BOD data,
costs based on a few additional assumptions are provided. The
costs for plants with high BOD levels are not affected since the
solids effluent is based on the biological treatment chosen.
For plants with BOD levels within 60 percent of the proposed
target, it is assumed that BOD reduction via solids removal is
appropriate. This type case exists frequently among plants with
sufficient BOD and TSS data. For plants meeting BOD targets,
solids targets are assumed also to be within the target limits.
These assumptions are considered reasonable based on the cases
existing in the plants with sufficient data.
There are five plants with flows greater than 10 MGD (the maximum flow
on the cost curves) and with concentrations above the targets. The flow
rates are 10.7, 15.8, 16.7, 19.9, and 40 MGD. Costs for these plants
were obtained from the graphs through a simple extrapolation of the
curve.
The accuracy of the extension for the plant with a flow of 40 MGD is
questionable; however, the only costs for this plant are for the in-
stallation of multimedia filtration. The modular nature of filtration
systems suggests that simple extrapolation of costs will tend to over-
estimate rather than underestimate the cost of the system. In any case,
the possible error which could result from this approach is small in
relation to the total estimated cost for that portion of the industry
requiring additional treatment.
The treatment codes used in the plant-by-plant analysis, as illustrated
in Table 8-14, are defined as follows:
1. ASL refers to activated sludge
2. ALA refers to aerated lagoons
3. CLAR refers to clarification
4. DAF refers to dissolved air flotation
5. MMF refers to multimedia filtration
6. MICRO refers to microscreening
For plants with multiple streams, the costs are reviewed for treating
each stream both individually and mixed. The least annual cost is con-
sidered the suggested alternative for each target. It is assumed for
estimating purposes that mixing is a viable alternative even though mix-
240
-------
ing possibly would be difficult for some plants (e.g., a plant where
inadequate piping between streams exists) .
PLANT-BY-PLANT COST RESULTS
Costs for the preliminary plant-by-plant analysis are summarized in
Table 8-15 and 8-16.
A review of the total costs indicates that for a 170 plant data base,
the annual costs are $10,346,000 per year for Target I, $21,887,000 per
year for Target II, $28,963,000 per year for Target III and $33,131,000
per year for Target IVi
BPT COST ESTIMATES
A second group of plant-by-plant cost estimates were prepared to deter-
mine the cost of complying with two sets of effluent limitations which
could potentially be applied to the OCPS industry. These targets,
identified as BPT (I) and BPT (II), have been developed separately for
each proposed subcategory. Limitations are based on the effluent con-
centrations achieved by well designed and operated plants in the Summary
Data Base. A more detailed explanation of the rationale for these po-
tential limitations is presented in Sections IX and X.
The proposed effluent limitations used to develop these cost estimates
are shown in Table 8-17. As the table indicates, the BPT (I) and BPT
(II) differ in the level of effluent TSS control required. The costing
methodology used for preparing the cost estimates was identical to that
used earlier (see pages 235 thru 240). As previously explained, multi-
media filters were costed as the technology used for effluent solids
control. Use of polishing ponds, although not applicable to every OCPS
plant, would result in significantly lower costs.
The plant-by-plant cost analysis to achieve BPT (I) and BPT (II) is pre-
sented in Table 8-18. Plant-by-plant costs are listed by subcategory.
Table 8-19 presents a summary of the total costs for additional treat-
ment to meet the two sets of potential guidelines. Plant costs are pre-
sented by subcategory.
Table 8-20 indicates the percentage of plants in the Summary Data Base
which require additional treatment to achieve BPT (I) limits. Table
8-21 presents the same information for BPT (II).
Table 8-22 presents the percentage of annual costs by subcategory to
meet BPT (I) and BPT (11). Also shown for each target is the percentage
of the total etimated annual cost attributable to each subcategory.
It should be noted that the plant counts in the earlier cost estimates
do not agree with counts in the "BPT" costing exercise. This is due to
the following factors: (1) the project data base has been updated
since the earlier efforts, changing the count of direct dischargers, and
(2) when the plants were re-subcategorized into 5 subcategories streams
from multi-stream plants were evaluated differently.
241
-------
TABLE 8-15 PLANT-BY-PLANT SUGGESTED TREATMENTS AND COSTS, NON-PLASTICS
"TAhGET I (50/50)
1*A k qET li (30/30)
Plant
No.
NJ
->
to
Suggested
CapHa)
Operating
Annua)
5'jested
CapHal
Opera ting
Annual
Suggested
Capita)
Operating
Annual
Trealrrenl
Costs
Costs
CosU
Treซ 1 mcnl
Cosls
Cosls
CoJli
Tren I mm I
Cost!
Cซt>
Cotts
m
U/yr)
!ii
tt/yr)
U/yr)
m
iifjt)
U/yr)
CLAfl
MS,000
11.000
30,000
MMP
470,000
40,000
95,000
MMP
4? 0,000
40,000
95,000
NO TREAT
0
0
0
NO TREAT
0
0
0
MMP
825,000
75,000
170,000
ALA/CIA R
5, 530,000
493,000
1.200,000
ALA/MVf
5, f50,000
537,000
1,270,000
AlA/MMP
5 , E50,0 00
537,000
1 ,370,000
NO TR HAT
0
0
0
NO treat
0
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
N O T R L A T
c
0
0
ASL/M MF
2,640,D C 0
2 JD ,000
635,000
NO Til EAT
0
0
0
no t:u:at
0
0
0
NO TREAT
0
0
0
ASL
500.000
56, 0C0
no,000
asl/mm p
7 4 0 ,CD0
76,000
110,000
ASL/MMP
140,00
76,000
195,000
CLAR
1 00 .coo
17,0 0 0
29,000
MF
: 2 0, c: 0
3C.000
72,000
MMP
320,000
30,000
72,000
NO TREAT
0
0
0
NO TREAT
0
0
0
NO TnEAT
0
0
0
CLAn
260.000
20.000
10,000
MM P
CT5.CD0
60,000
135,000
M MF
675,000
so,000
135.000
clar
290,000
71,000
56,030
MMP
7 20 ,COO
65.oao
150,000
MMF
720 ,000
65 , COO
i 50 . CCO
NO TREAT
0
0
0
^'0 treat
0
0
0
M MP
SCO,cco
50,000
120,000
CLAfl
370,000
2D.0C0
55.CD0
mmt
e:c,oco
60,:co
190,COO
MMP
ฃ*0,000
80,COO
ISO,CCO
ASL
1,150,000
120,000
2 CO, COO
ASL/MMP
1,750,0:0
1 Gฃ.OOC
375,000
ASL/MMP
I ,750.000
166,000
375 , 000
NO TREAT
0
0
0
no trlat
0
0
Q
NO TREAT
0
0
0
NO TH EAT
0
0
0
M MP
2,too,000
165.000
490,000
MMF
2,f 00,00 0
165,000
^50,000
NO Til EAT
0
0
0
no treat
0
0
0
NO TREAT
0
0
0
CLAn
105,000
17,000
30,000
M M P
3^0,000
32,000
75 ,000
V MP
340,000
33,000
75,000
CLAll
1,500,000
45,000
250.000
M M F
5,0,10 ,C00
2*0,000
ISO.OGO
M M P
5,c:o,ooo
250,000
I5C.G0C
c la n
165,000
IS.000
37,000
M MF
52C.0C3
42.000
100,000
M MP
520,000
42,000
t CO,soo
NO TREAT
0
0
0
MMF
700,000
62,000
140,000
M M F
7 20,000
62,000
140,000
NO TH EAT
0
0
0
so treat
0
0
0
NO TREAT
0
0
0
M MP
500,000
<1.000
97,000
ASL
*30,000
95,000
210,000
ASL/M MF
1 ,<3Q ,000
136 .000
3C7 , C0Q
NO TREAT
0
0
0
ko treat
0
0
0
ASL/MMF
7,:c:-,ooo
76C,COO
1,550,0:0
CLAR
350,000
22,000
64,000
MMP
(50,000
77.000
170,000
M MF
650,000
77,0:0
1 7 C , 0 0 0
NO TREAT
0
0
0
NO TREAT
0
0
0
MMP
1,500,000
150,000
450,CCO
ASL
1 ,'700 ,000
115,000
260,000
ASL/MMF
1,7&0,000
159.000
390,000
ASL/MMP
1,960,000
174 .000
420 .000
-------
1
18
16
21
28
35
36
50
52
53
57
59
60
62
64
76
80
85
94
97
102
110
112
113
114
120
127
TARGET IV (15/20)
Suggested
Treatment
Capltal
Coats
($)
Operating
Costs
(S/yr)
Annual
Costs
(S/yr)
MMF
470,000
40,000
95,000
MMF
825,000
75,000
170,000
ALA/MMF
5,850,000
537,000
1,270,000
No Treat
0
0
0
ASL/MMF
2,640,000
283,000
605,000
No Treat
0
0
0
ASL/MMF
840,000
78,000
195,000
MMF
320,000
30,000
72,000
No Treat
0
0
0
MMF
675,000
60,000
135,000
MMF
720,000
65,000
150,000
MMF
600,000
50,000
120,000
MMF
900,000
80,000
190,000
ASL/MMF
1,750,000
168,000
375,000
No Treat
0
0
0
MMF
2,800,000
165,000
490,000
No Treat
0
0
0
MMF
340,000
32,000
75,000
MMF
5,000,000
250,000
850,000
MMF
520,000
42,000
100,000
MMF
700,000
62,000
140,000
No Treat
0
0
0
ASL/MMF
1,430,000
136,000
307,000
ASL/MMF
7,300,000
780,000
1,550,000
MMF
850,000
77,000
170,000
MMF
2,500,000
150,000
450,000
ASL/MMF
1,960,000
174,000
420,000
243
-------
TABLE 8-15 (cont), NON-PlASTICS
7 A HO ITT I (50/50)
Plant Si^Tferted Capital Opfatlnj Annual
No. Treatment Costs Costs Coats
(J) (J/vr) (J/yr)
i:b
NO TREAT
0
c
0
no
NO TREAT
C
0
0
138
ASL
6 00,00
105.000
23r ,000
144
NO TRCAT
0
0
0
145
NO TREAT
0
0
0
160
ASLป
780,000
FC ,000
175,000
nt
no TR EAT
0
1 -0
0
na
ASL
2,f00,000
200,000
50C ,000
163
n0 TREAT
c
c
0
!8G
NO Til CAT
0
c
0
i n6
N O Til EAT
0
0
0
:: 6
NO Til BAT
0
0
0
7; 8
ASi.
:bo,oco
o.ccc
ic: ,000
719
ClAn
55.CCD
i6.::c
22, COO
::o
OAI:
7 g,000
15, crc
2 3 i r. 0
222
ASI.
800.COO
151,C ?0
2:0 ,tcc
176
C LA R
150,C00
11,000
4j,cc:
m
CLAR
320,000
2;,coo
DO.000
?:i
ASL
6 00.ceo
15C.OC0
190,000
239
NO TREAT
0
0
0
241
NO TREAT
0
0
0
?S6
NO Til BAT
0
c
0
257
ASL
no,ooo
90,000
21c,000
253
NO TREAT
0
0
0
264
NO TREAT
0
0
0
270
NO TREAT
0
0
0
27 I
CLA R
165,000
18,000
40 ,000
'ARCt-7 li (jQ/30)
7A it Gr,7 Hi {TZ7W
Suf jested
Capital
Opera 1 Inj
Annual
Swelled
Capital
Opera 1 Inp
Annual
Trca tment
Costs
Costs
Costs
Ttco tment
Coili
Cosls
Coils
Li!
HM
m
U/yr)
U/yrj
MMF
650,000
68,000
150,000
WMF
650,000
61,000
150,000
NO TREAT
0
0
0
NO TREAT
0
0
0
ASL/MMF
l', 2 20 , 000
HI t 000
315,000
ASL/M MP
1,4<5,000
151 ,000
335,000
M MP
5 40 ,D00
47,0:0
100,000
MMP
540,000
41,COS
ICO.OOO
M V P
GOO,000
50, CC0
120.0C0
M M F
GOO,COO
5C.000
1:0,COO
ASL/MMF
1,180,000
11?,CCD
2CC.0C3
ASL/M MP
1,150,CC0
111,000
2c?,c:o
V.MF
GQC ,000
50.CCG
i:c,coo
S< V' p
6:3, OCO
SC ,000
;::,coo
ASL/M MP
2,-00,000
203 ,000
640,COO
ASL/M MP
3,100,000
303,000
723,000
NO 'MEAT
0
0
0
NO TREAT
0
0
0
NO theat
0
0
0
NO TREAT
0
0
0
MMF
540,000
42,000
100,000
MMF
540,000
4 2,000
1:3.COO
^0 TR eat
0
0
0
M M P
JSO.CC'O
24 ,cec
5 5 , : 0 0
ASL/M MF
555,CC0
60,000
Ml ,005
ASL/MMF
505,000
60, CC 0
Ml ,0:0
v v F
220.000
20,0CC
48,COO
M M F
2 3 0,: c 0
2 0,000
<5,::c
MMF
J5C , DD0
25.000
5G,000
M M F
250.CD0
25,COO
55,CCD
ASL/MMF
1,210,000
142,000
30G,000
ASL/MMP
1 , 4 5 0 ,CC 0
152 ,0:0
3
-------
TAKUET IV (15/20)
Suggested Capital Operating Annual
Treatment Costs Costs Costs
Plant #
($)
(S/yr)
(S/yr)
128
MMF
650,000
68,000
150,000
130
No Treat
0
0
0
138
ASL/MMF
1,445,000
151,000
335,000
144
MMF
540,000
42,000
100,000
145
MMF
600,000
50,000
120,000
160
ASL/MMF
1,180,000
118,000
260,000
171
MMF
600,000
50,000
120,000
178
ASL/MMF
3,100,000
303,000
720,000
183
No Treat
0
0
0
180
No Treat
0
0
0
188
MMF
540,000
42,000
100,000
216
MMF
250,000
24,000
55,000
218
ASL/MMMF
565,000
60,000
141,000
219
MMF
230,000
20,000
48,000
220
MMF
250,000
2 5,000
56,000
222
ASL/MMF
1,450,000
152,000
346,000
226
MMF
560,000
46,000
110,000
228
MMF
750,000
70,000
160,000
231
ASL/MMF
1,270,000
156,000
332,000
239
MMF
165,000
16,000
35,000
247
MMF
725,000
65,000
150,000
256
MMF
270,000
26,000
64,000
277
ASL/MMF
1,330,000
129,000
320,000
263
ASL/MMF
605,000
57,000
146,000
264
MMF
630,000
53,000
130,000
270
No Treat
0
0
0
271
MMF
560,000
44,000
110,000
245
-------
TABLE 8-15 (cont), NON-PLASTICS
K>
On
Plint
No.
Sweated
Tree tmซnt
rARCET K5C/50J
Cupliat
Costs
(f)
"TAitCrr li (33/30)
Annual
Costs
(Vyr)
Suggested
Trea trrienl
Capital
Costs
m
Opera tlnj
Costs
(J/jrr)
TARGET ni ;:u7W
Su^geited Capital Ofxritlnf Annual
Tremmrnt Costa Costs Costs
(I) (S/vr) (l/yr)
289
clar
340,000
32,000
62,000
MVP
600,000
75,000
170,000
M M P
f 0 9,CO 0
75,000
170,000
273
ClAR
340,000
ป71,000
G2.CQC
M V P
rOO.COO
75,000
170,000
MMP
800,000
75,000
170,000
275
ASL
540 , OOC
50,000
135 , TOO
ASL.'VMF
830,000
84,000
195,000
ASL/MMP
100,000
84,CC0
iss.coo
15
NO TREAT
0
0
0
SO TREAT
0
0
0
M M F
670,000
6 0 , C C 0
135,000
20
ASL
460,000
48,COO
;:?,c:o
A5L/v MP
7 20,000
70,COO
170,000
ASL/MMP
740,000
7< ,CC0
jso.cco
<2
ASL
490,000
54,000
125,0:0
AS _/V M P
:;o.oco
73,000
17 0 , C'OO
ASL/VMP
610,000
75,000
165,0*0
fil
ASL
1,550,000
no,coo
35 0,000
ASป,".:MP
2,220,000
230,000
455 , C00
ASL/MMP
2,220,CC0
230,COO
49 5 , CCO
' 14
CLAR
430,000
25,000
75,000
m vr
1,050,000
85,000
210,000
ASL/M MP
3,000,000
420,CCO
190,000
103
NO TREAT
0
0
0
NC TREAT
0
0
0
NO TREAT
0
0
0
111
NO TREAT
0
0
0
SO ฐ.at
c
0
0
NO TREAT
0
0
0
170
no treat
0
0
0
so Til CAT
0
0
0
MMP
700,000
M,000
145,000
175
NO TR EAT
0
0
c
v v p
5*2 0,000
44,000
96 , 000
MMP
530,000
44,COO
5S , 000
177
NO TREAT
0
0
0
NO TREAT
0
0
0
NO TREAT
0
C
0
234
NO TREAT
0
__0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
TOTALS
23,773,000
7,226,000
s.m.ooc
47,287.000
4,185,000
10,018,000
70,015,000
8,286,000
14,879,000
INSUPPICIENT TS3 DATA.
-------
TARGET IV (15/20)
Suggested Capital Operating Annual
Treatment Costs Costs Costs
Plant I
($)
(S/yr)
(S/yr)
269
MMF
800,000
75,000
170,000
272
MMF
800,000
75,000
170,000
275
ASL/MMF
800,000
84,000
195,000
15
MMF
670,000
60,000
135,000
20
AS1/MMF
740,000
74,000
180,000
42
ASL/MMF
810,000
75,000
185,000
61
ASL/MMF
2,220,000
230,000
495,000
84
ASL/MMF
3,900,000
420,000
890,000
103
No Treat
0
0
0
118
No Treat
0
0
0
170
MMF
700,000
84,000
145,000
175
MMF
520,000
44,000
98,000
177
No Treat
0
0
0
234
No Treat
0
0
0
247
-------
TABLE 8-15 (cont), NON-PLASTICS
ntitet\ turn
Imt
Stiff esttl
Capital
Operating
Annuo1
Wo.
Treatment
Costs
Costa
Costs
(t)
U/yr>
tl/yr)
Mli Slruma
It 11: NO.TRT
1
0
9
31
CLAR
11),Oil
11,000
40,000
32
ASL
411,000
44,000
106,001
49
NO TREAT
I
0
0
Treat STMl
S3
ASL
1,100.000
110,000
300,000
II
CLAR
210,COO
11.000
44,000
II
ASL
750,000
3?,000
190,000
II
HO TREAT
0
9
0
II
CLAR
200,009
11.009
43.000
91
NO TREAT
0
0
0
91
MMF
59,000
51,009
130,000
11?
SO TREAT
9
9
0
i 19
WO TREAT
0
9
0
121
HO TREAT
0
9
0
m
KO TREAT
1
9
0
151
KO TREAT
0
9
0
153
ASt
700,009
72,000
120,000
151
CLAR
110,000
12.000
31,000
159
HO TREAT
9
9
0
111
ASL
289,009
72,000
170,000
Ul
CLAR
199,000
11.000
40,000
111
MO TREAT
0
9
0
111
ASL
1,500,000
150,000
319,009
192
OA#
21,000
15,900
24,000
TXnCEi'HUt7WT
YAftCETrti OH/lll)
Suggested Capital Operatlnf Annual Suggested Capital Operatlnf Annual
Treatment Cosis Costs Costs Treatment CoaIs Costs Costs
It) It/yr) (t/yr) (t) (t/jr) (t/yr)
Treat STM.I
Treat 5TM.I
ASL/MMP
740 (
,000
75,
,000
179,
,000
asl/mmp
740,
,000
,000
179,
,000
MMP
550,
,000
44,
,000
101,
,000
MMP
550
,000
44,
,000
101,
, cco
ASL/MMP
I2G,
.000
61,
,000
HI
.000
asl/mmp
120,
,000
1,
,000
141,
,000
MMP
640,
t000
,000
100
,000
MMP
540,
,000
42,
,000
100,
, cco
M ii llll
Mix mi
ASL/UMF
4
,2?:
,090
449,
,000
960
,000
ASL/MMP
4,
,200
,090
449,
,000
960,
,000
Clar/m.mf
810
,000
6,
,000
15S
,000
CLAR/MMP
110
,000
66,
,000
159,
, C30
ASL/MMF
1,
,C9C
.003
120,
,000
265
.coo
ASL/MMP
1,
,220,
.000
116,
,000
21$,
, coo
ASL/MMF
1
,<60,
,c:o
167,
,000
370,
,000
ASL/MMP
1(
,cco,
,000
167,
,000
370,
,c:-3
MMP
590,
,000
47,
,000
H5,
,000
MMF
590
.000
47,
,000
115,
,GC0
NO TREAT
0
0
0
NO TREAT
0
0
0
MMF
6 5; 000
56,
,000
130
,000
ASL/MMP
650,
,000
56,
,000
i:0,
, oco
KO TREAT
G
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
MMF
625,
,000
52,
,000
14 0,
, coo
NO TREAT
0
0
0
NO TREAT
0
0
0
MMF
ฃ50,
,000
56,
,000
130,
,000
MMP
650,
,000
56,
,000
133,
,009
NO TREAT
0
0
0
NO TREAT
0
0
0
ASL/MMF
V
.045,
,000
104,
,000
245
.009
ASL/MMP
1,
,045.
.000
104,
,000
3<5,
, occ
MMF
370,
,000
34.
,000
10,
,000
MMP
370,
,000
34,
,000
to,
,0:0
NO TREAT
0
0
0
NO TREAT
0
0
0
ASL/MMF
I,
,c:o,
,oco
106,
,000
250,
,000
ASL/MMF
1,
,060,
,000
106,
,000
JS0,
, COS
MMF
5(0,
,030
44,
,000
HO,
,000
MMF
560,
,coo
44,
,C00
110,
,c:o
MMP
450,
,000
39,
000
90,
,000
ASL/MMP
1.
.250,
,C90
132,
,000
283,
,c:o
ASl*/MMP
2,
125.
oco
202.
000
410,
,000
ASL/MMP
2,
,325,
,090
222,
000
5<0,
,cc:
MMF
250,
,000
25.
000
SO,
,000
MMP
250,
,000
25,
000
60,
,030
-------
TARGET IV
(15/20)
Plant 1
Treatnent
Capital $
Operational $
Annual $
8
ASL/MMF
740,000
75,000
179,000
31
MMF
550,000
44,000
108,000
32
ASL/MMF
620,000
61,000
148,000
49
MMF
Mix I 4 II
540,000
42,000
100,000
63
ASL/MMF
4,200,000
449,000
960,000
66
ClAR/MMF
810,000
66,000
159,000
81
ASL/MMF
1,220,000
126,000
285,000
86
ASL/MMF
1,660,000
167,000
370,000
88
ASL/MMF
1,150,000
120,000
260,000
92
Ho Treat
0
0
0
98
ASL/MMF
650,000
56,000
130,000
117
No Treat
0
0
0
119
MMF
625,000
52,000
140,000
121
No Treat
0
0
0
122
MMF
650,000
56,000
130,000
151
MMF
700,000
64,000
148,000
153
ASL/MMF
1,045,000
104,000
245,000
158
ASL/MMF
700,000
73,000
170,000
159
MMF
460,000
39,000
90,000
164
ASL/MMF
i,oซo,ooo;
106,000
250,000
176
HHP
560,000
44,000
110,000
182
ASti/WF
1,250,000
122,000
280,000
187
ASL/MMF
2,325,000
222,000
540,000
192
MMF ..
250,000i
25,000
60,000
249
-------
TABLE 8-15 (cont), NON-PLASTICS
TAnCET I (SO/SO)
Plant
Capital
Operating
Annual
No.
Treatment
Costs
Coils
Costs
<$)
Ct/yrl
(t/yr)
193
ASL
ISO,000
110,000
220,000
m
HO TREAT
0
0
0
201
ASL
410,000
57,000
170,000
703
ASL
510,090
50,000
130,000
205
CLAR
30,000
14', 000
18,000
201
CLAR
350,000
32.000
64,000
201
NO TREAT
0
0 .
0
230
ASL
700,000
72,000
170,000
235
ASL
2,300.000
270,000
560,000
236
CLAR
330,000
32,000
62,000
245
HO TREAT
0
0
0
241
ASL
1,300,000
130,000
290,000
249
NO TREAT
0
0
0
2SI
HO TREAT
0
0
0
6
ASL
510,000
50,000
130,000
~ II
ASL
510,000
58,000
130,000
163
ASL
410,000
44,000
107,000
204
NO TREAT
0
0
0
259
NO TREAT
0
0
0
2GI
ASL
1,200,000
320,000
580,000
211
NO TREAT
0
0
0
TOTALS
17,253,000
1,973,000
4,229,000
insufficient tss data.
TAHCET II (30/30)
TARGET III (Will)
Sugfcsled
Capital
Operating
Annual
Sugfcsled
Capllil
Operating
Annual
Treatment
Coats
Costs
Costs
Treatment
Cosls
Costs
Costs
U)
(t/yr)
tt/yr)
(tj
(l/yr)
(l/yr)
ASL/MMF
1,235,000
HI,000
303.000
ASL/MMF
1,535,000
171,000
373,000
MMP
1,050,000
85,000
210,000
MMP
1,050,000
15,000
210,000
ASL/MMF
511,000
72,000
139,000
ASL/MMP
710,000
-83 ,000
173,000
ASL/MMP
no,ooo
7 S .000
187,000
ASL/MMP
790,000
7 P,COO
197,000
MMP
160,090
15,090
34.0C0
MMF
1GC.C00
15,000
34,000
MMF
850,000
75.000
170,000
MMF
850,COO
75,000
170,003
WMF
400,000
36,000
85,000
MMP
420, COO
38,000
85. COO
ASL/MMP
1,050,000
104,COO
246.COO
ASL/MMP
1,050,000
104,000
248,000
ASL/MMP
3,700,000
350,GOO
750,000
ASL/MMP
3,700,000
350,000
750,000
MMF
800,000
75,000
170,000
MM K
800,000
75,000
170,000
NO TREAT
0
0
NO Tfl EAT
0
0
0
ASL/MMP
1,925,000
181,000
410,000
ASL/MMP
1,525,000
181,000
410,000
NOT THEAT
0
0
NO TREAT
0
0
0
ASL/MMP
550,000
59,000
130,000
ASL/MMP
550,000
50,000
138,000
ASL/MMF
755,000
81,000
182,000
ASL/MMP
815,000
83,000
194,000
ASL/MMF
755,000
81,COO
182,000
ASL/MMF
815.000
83,000
194,000
ASL/MMP
615.000
61.000
147,000
ASL/MMP
615,090
61,000
147,000
NO TnI*AT
0
0
0
MMF
270,000
20,000
62,000
NO TREAT
0
0
0
NO TREAT
0
0
0
ASL/MMF
2,810,000
380,000
720,000
ALA/MMP
3,880,000
350,000
840,000
NO TaEAT
0
0
0
NO TREAT
0
0
0
55,411 J. 000
1,607,000 1,050,00
39,130,000 3,115,000 1,710,000
-------
193
195
201
203
205
206
208
230
235
236
245
248
249
258
6
81
163
204
259
268
281
TARGET IV (15/20)
Treatment
Capital $
Operational $
Annual $
ASL/MMF
1,535,000
171,000
373,000
MMF
1,050,000
85,000
210,000
ASL/MMF
710,000
83,000
173,000
ASL/MMF
790,000
79,000
197,000
MMF
160,000
15,000
34,000
ASL/MMF
2,100,000
250,000
510,000
MMF
400,000
36,000
85,000
ASL/MMF
1,050,000
104,000
246,000
ASL/MMF
3,200,000
350,000
750,000
ASL/MMF
2,000,000
230,000
490,000
No Treat
0
0
0
ASL/MMF
1,925,000
181,000
410,000
No Treat
0
0
0
ASL/MMF
550,000
59,000
136,000
ASL/MMF
815,000
83,000
194,000
ASL/MMF
815,000
83,000
194,000
ASL/MMF
615,000
61,000
147,000
MMF
270,000
26,000
62,000
No Treat
0
0
0
ALA/MKF
3,880,000
350,000
840,000
HMF
540,000
42,500
100,000
44,170,000 4,401.500 10,013,000
251
-------
TABLE 8-16 PlANT-BY-PLANT SUGGESTED TREATMENT ANO COSTS, PLASTICS
TARGET I liS/iCl TARGET H U0/3D) TARGET iil UiS/IC)
int
Suggested
Cep'ttl
Operating
Annual
Suj^estetl
Capital
Operating
Annual
Smelted
Capital
Ofxri | ir^
Annual
'o.
Treatment
Costs
Costs
Costs
Treatment
Costs
Ccsls
Costs
Trentment
Coals
Costs
Coil s
W
2
NO TREAT
e
0
D
KO TREAT
0
0
0
MMP
640,000
5<,C?0
1ST,000
:
so trhat
0
0
0
ASL/mmP
690,000
99,000
723,000
ASL/MMP
*90,000
99 ,030
233,COO
$
HO TUf.AT
c
C
0
NO TREAT
0
0
0
M M P
240,0C0
23.CGC
t:,oso
i:
NO 7:tt'AT
0
0
c
no tji Cat
0
0
0
NO TREAT
0
0
0
V
NO T,tฃAT
c
c
0
asl/vmp
too ,000
67 ,000
HO,COO
ASL/MMP
f.JO.OCO
67,000
i. :,cco
is
SO TuฃA7
0
c
c
N'D 7KJฃAT
0
0
c
NO TREAT
0
0
:
;7
NO TRtAT
c
0
9
NO *~fl EAT
0
0
0
M MP
1 ,750,CC0
120,000
:i
CLAR
415,000
75.pOO
53,000
M V!'
1,250,000
95,000
2
-------
TARGET XV* (10/20)
Plane f
2
3
9
10
17
19
27
29
34
39
44
45
54
65
73
77
89
90
91
ซ
96
100
104
Tceatment
MMP
ASL/MMF
MMP
No Treat
ASL/MMF
No Treat
ASL/MMF
MMP
ASL/MMF
No Treat
MMP
MMP
MMP
ASL/MMF
No Treat
No Treat
ASL/MMF
No Treat
MMP
MMP
No Treat
No Treat
MMP
Capital $
640,000
990,000
240,000
0
680,000
0
5,400,000
1,250,000
450,000
0
470,000
650,000
280,000
3,400,000
0
0
1,300,000
0
650,000
260,000
0
0
600,000
Operational $
54,000
99,000
22,000
0
67,000
0
680,000
95,000
49,000
0
40,000
56,000
28,000
410,000
0
0
140,000
0
56,000
26,000
0
0
50,000
Annual $
127,000
233,000
52,000
0
160,000
0
1,400,000
245,000
115,000
0
92,000
130,000
68,000
830,000
0
0
300,000
0
110,000
60,000
0
0
120,000
253
-------
TABLE 8-16 (cont), PLASTICS
Went
No.
Suggested
Tree (men!
'TAKCEf
TARGET II (30/30)
Cepilil
Costs
(I)
Operetlnf
Costs
(l/yr)
Annuel
Costs
t*/yr)
Suggested
Tteelmeflt
Cepltel
Coals
(I)
Operetlnf
Costs
(l/yr)
Annuel
Costs
U/yr)
TAhocT lunmr
Sufgcsted
Treatment
Cepitel Operetlnf
Coals Coats
(I) U/yr)
Annuel
Costs
(i/yr)
05
NO Til BAT
0
0
MMF
940,000
32,000
75,000
MMF
340,000
32,000
75,000
0?
CLAR
370.000
30,000
33,000
MMP
700,000
12,000
140,000
M MP
700,000
62,000
140,000
99
CLAR
230,000
19.000
<5,000
MMP
600,000
50,000
120,000
MMP
600,000
50,000
130,000
11
NO TREAT
0
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
34
NO Til RAT
0
0
0
ASL/MMF
070,000
106.000
248,000
ASL/MMP
1,070,000
108,000
248.000
3S
NO TR EAT
0
0
0
asl/mmp
1
210,000
116,000
270,000
ASL/MMP
1,210,000
116,000
270,000
Jt
NO TREAT
0
0
0
NO TREAT
0
0
0
M M P
360,000
34,000
80,000
32
NO TR EAT
0
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
41
NO Til EAT
0
0
0
NO TUEAT
0
0
0
MMF
360,000
34,000
10,000
47
NO Tn EAT
0
0
0
NO TRP.AT
0
0
0
MMP
330,000
31,000
73,000
SO
NO TR EAT
0
0
0
ASL/MMF
1
300,000
126,000
28S.000
ASL/MMP
1,300,000
126,00
285,000
S3
NO TREAT
0
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
ST
NO Tit EAT
6
0
0
MMF
600,000
40,000
110,000
MMP
600,000
46.000
% 110,000
14
NO TREAT
0
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
19
NO TREAT
0
0
0
MMF
Mix Mil
420,000
38,000
85,000
MMP
Mix 1 ~ II
420,000
36,000
85,000
14
NO TnEAT
0
0
0
NO TREAT
0
0
0
MMP
560,000
46,000
110,000
19
ASL
610,000
70.000
HO. 000
asl/mmf
1
.030,000
102,000
255,000
ASL/MMP
1,020,000
102,000
235,000
94
NO TR EAT
0
0
0
NO TREAT
0
0
0
NO Tn EAT
0
0
0
96
NO TREAT
0
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
03
NO TREAT
t
0
0
NO TUEAT
0
0
0
NO TREAT
0
0
0
to
NO TREAT
ซ
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
17
NO Tn EAT
0
0
0
NO TUEAT
0
0
0
NO TREAT
0
0
0
-------
107
109
111
124
125
126
132
146
147
150
152
157
174
179
184
189
194
196
202
210
217
TARGET IVA (10/20)
Treatment Capital $ Operational $
MMF
ASL/MMF
MMF
No Treat
ASL/MMF
ASL/MMF
MMF
ASL
MMF
MMF
ASL/MMF
No Treat
MMF
No Treat
MMF
Mix I 4 II
MMF
ASL/MMF
No Treat
No Treat
ASL
No Treat
ASL
340,000
1,600,000
600,000
0
1,070,000
1,210,000
360,000
640,000
360,000
330,000
1,300,000
0
600,000
0
420,000
560,000
t,02Q,000
0
0
540,000
0
420,000
32,000
175,000
50,000
0
108,000
118,000
34,000
66,000
34,000
31,000
126,000
0
46,000
0
38,000
46,000
02,000
0
0
58,000
0
44,000
Annual $
75,000
370,000
120,000
0
248,000
270,000
80,000
155,000
80,000
73,000
285,000
0
110,000
0
85,000
110,000
235,000
0
0
135,000
0
107,000
255
-------
TABU 8- 16(cont), PLASTICS
TARGET I ISO/SO) TARGET II (30/30) TAllCET III M/lt)
Plant Supgestad Capital Operating Annual Suggested Capital Operating Annual Suggested Capital Operating Annual
No. TYeaiment Costs Coals Costs Treatment Costs Costs Costs Treatment Costs Conti Costs
^ ซป) <ป/*'> <*/y> (f) <ป/yr) (t/yr) (I) (J/yr) (J/yr)
Ln
On _
273
NO TREAT
0
0
e
NO TREAT
0
0
0
NO TREAT
0
0
0
714
DAP
7ป,00ป
14,000
23,000
MMF
250,000
23,000
52,000
MMP
250,000
23,000
52,000
an
NO TREAT
0
9
0
NO TREAT
0
0
0
NO TREAT
0
0
0
7U
ASU
710,600
14,000
190,000
A9L/MMF
1,190,000
121,000
375,000
ASL/MMP
1,190,000
171,000
275,000
2S4
NO TREAT
0
o
0
NO TREAT
0
0
0
NO TREAT
0
0
0
767
CLAH
105,000
17,000
30,000
MMP
340,000
37,000
75,000
MMP
340,000
37,000
75,000
m
CLAH
330,000
22,000
61,000
MMF
775,000
70.000
160,000
MMP
775,000
70,000
160,000
777
NO TREAT
0
0
0
MMF
675,000
60,000
135.000
MMP
(75.000
60,000
135,000
717
NO TREAT
0
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
a
NO TREAT
0
0
0
NO TREAT
0
0
0
MMP
390,000
35,000
10,000
* 101
NO TREAT
0
0
0
NO TREAT
0
0
0
NO TREAT
0
0
0
* 233
NO TREAT
0
0
0
MMF
450,000
39.000
90,000
MMP
450.000
39.000
90,000
TOTALS
a.Tis.ooo
344,000
809,000
17.575,000
1,595,000
3,736.000
25,685,000 2,337,000
5.413,000
INSUFFICIENT TSS DATA.
-------
TARGET IVA (10/20)
Plant #
Treatment
Capital $
Operational $
Annual $
223
224
229
246
254
262
273
277
287
75
106
233
ASL
ASL/MMF
No Treat
ASL/MMP
MM?
ASL/MMF
ASL/MMP
MMF
No Treat
ASL/MMF
No Treat
ASL/MMF
480,000
470,000
0
1,190,000
510,000
660,000
200,000
675,000
0
730,000
0
830,000
40,000
52,000
0
121,000
41,000
68,000
230,000
60,000
0
75,000
0
85,000
94,000
120,000
0
275,000
96,000
160,000
480,000
135,000
0
175,000
0
190,000
TOTALS
36,175,000
3,732.660
8,325,000
257
-------
TABLE 8-17
POTENTIAL BPT EFFLUENT LIMITATIONS
BPT (I)
Subcategory BOD mg/1
Plastics 14.5
Not Plastics -Type I with Oxidation
High Flow 26.0
Low Flow 36.0
Not Plastics Type I w/o Oxidation 24.5
Not Plastics NOT Type I 17.0
TSS mg/1
24
62
89
34.5
29
BPT (II)
Subcategory
Plastics
Not Plastics - Type I with Oxiation
High Flow
Low Flow
Not Plastics Type I w/o Oxidation
Not Plastics NOT Type I
BOD mg/1
14.5
26.0
36.0
24.5
17.0
TSS mg/1
23
42
42
27
26
258
-------
TABLE 8-18
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: PLASTICS ONLY
BPT (I)
1
BPT
(II)
Suggested
Capital
Operating
Annual I
Suggested
Capital
Operating
Annual
Plant #
Treatment
Cost ($)
Cost($/yr)
Cost($/yr) |
Treatment
Cost($/yr)
Cost($/yr)
Cost($/yr)
2
No Treat.
0
0
1
0 1
MMF
640,000
54,000
127,000
3
ASL/MMF
990,000
99,000
233,000 I
ASL/MMF
990,000
99,000
233,000
9
MMF
240,000
22,000
52,000 I
MMF
240,000
22,000
52,000
10
No Treat.
0
0
o 1
No Treat.
0
0
0
17
ASL/MMF
680,000
67,000
160,000 I
ASL/MMF
680,000
67,000
160,000
19
No Treat.
0
0
o 1
No Treat.
0
0
0
29
MMF
1
,250,000
95,000
245,000 |
MMF
1,250,000
95,000
245,000
39
No Treat.
0
0
0 1
No Treat.
0
0
0
45
No Treat.
0
0
0 1
No Treat.
0
0
0
54
ASL/MMF
880,000
88,000
218,000 |
ASL/MMF
880,000
88,000
218,000
73
No Treat.
0
0
o 1
No Treat.
0
0
0
77
No Treat.
0
0
o 1
No Treat.
0
0
0
90
No Treat.
0
0
0 1
No Treat.
0
0
0
91
MMF
650,000
56,000
130,000 |
MMF
650,000
56,000
130,000
93
MMF
260,000
26,000
60,000 |
MMF
260,000
26,000
60,000
96
No Treat.
0
0
0 1
No Treat.
0
0
0
100
No Treat.
0
0
o 1
No Treat.
0
0
0
104
MMF
600,000
50,000
120,000 |
MMF
600,000
50,000
120,000
105
MMF
340,000
32,000
75,000 |
MMF
340,000
32,000
75,000
109
MMF
600,000
50,000
120,000 |
MMF
600,000
50,000
120,000
111
No Treat.
0
0
0 I
No Treat.
0
0
0
124
ASL/MMF
1
,070,000
108,000
248,000 |
ASL/MMF
1,070,000
108,000
248,000
125
ASL/MMF
1
,210,000
118,000
270,000 |
ASL/MMF
1,210,000
118,000
270,000
126
MMF
360,000
34,000
80,000 I
MMF
360,000
34,000
80,000
146
No Treat.
0
0
0 1
No Treat.
0
0
0
147
MMF
330,000
31,000
73,000 |
MMF
330,000
31,000
73,000
150
ASL/MMF
1
,300,000
126,000
285,000 I
ASL/MMF
1,300,000
126,000
285,000
152
No Treat.
0
0
0 I
No Treat.
0
0
0
157
MMF
600,000
46,000
110,000 1
MMF
600,000
46,000
110,000
-------
TABLE 8-18 (Continued)
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: PLASTICS ONLY
Plant
Suggested
^ Treatment
BPT (I)
Capital
Cost ($)
Operating
Cost($/yr)
1
Annual |
Cost($/yr) j
Suggested
Treatment
BPT
Capital
Cost($/yr)
(II)
Operating
Cost($/yr)
Annual
Cost($/yr)
174
No Treat.
0
0
1
0 1
No Treat.
0
0
0
179
MMF
420,000
38,000
85,000 |
MMF
420,000
38,000
85,000
184
MMF
560,000
46,000
110,000 |
MMF
560,000
46,000
110,000
189
ASL/MMF
1,020,000
102,000
235,000 j
ASL/MMF
1,020,000
102,000
235,000
196
ASL/MMF
2,640,000
290,000
615,000 |
ASL/MMF
2,640,000
290,000
615,000
210
No Treat.
0
0
0 1
No Treat.
0
0
0
229
No Treat.
0
0
0 1
No Treat.
0
0
0
246
ASL/MMF
1,190,000
121,000
275,000 |
ASL/MMF
1,190,000
121,000
275,000
277
MMF
675,000
60,000
135,000 |
MMF
675,000
60,000
135,000
287
No Treat.
0
0
0 1
No Treat.
0
0
0
27
MMF
1,750,000
120,000
300,000 |
ASL/MMF
7,150,000
800,000
1,700,000
34
ASL/MMF
690,000
64,000
165,000 |
ASL/MMF
690,000
64,000
165,000
44
No Treat.
0
0
0 1
No Treat.
0
0
0
52
No Treat.
0
0
0 1
No Treat.
0
0
0
65
MMF
1,250,000
95,000
245,000 |
MMF
1,250,000
95,000
245,000
75
ASL/MMF
1,120,000
110,000
255,000 |
ASL/MMF
1,120,000
110,000
255,000
89
ASL/MMF
1,925,000
192,000
420,000 |
ASL/MMF
1,925,000
192,000
420,000
107
ASL/MMF
1,900,000
237,000
510,000 |
ASL/MMF
1,900,000
237,000
510,000
119
No Treat.
0
0
0 1
MMF
125,000
52,000
140,000
134
MMF
320,000
31,000
71,000 |
ASL/MMF
960,000
97,000
226,000
192
MMF
250,000
25,000
60,000 I
ASL/MMF
750,000
78,000
190,000
202
MMF
290,000
26,000
60,000 |
ASL/MMF
830,000
84,000
195,000
217
MMF
210,000
16,000
41,000 |
MMF
210,000
16,000
41,000
223
No Treat.
0
0
0 |
MMF
480,000
40,000
94,000
224
ASL/MMF
720,000
75,000
172,000 |
ASL/MMF
720,000
75,000
172,000
233
ASL/MMF
980,000
119,000
280,000 I
ASL/MMF
980,000
119,000
280,000
254
No Treat.
0
0
0 1
MMF
510,000
47,000
96,000
262
ASL/MMF
1,000,000
100,000
235,000 I
ASL/MMF
1,000,000
100,000
235,000
273
ASL/MMF
2,775,000
300,000
640,000 j
ASL/MMF
2,775,000
300,000
640,000
-------
TABLE 8-18 (Continued)
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: TYPE I W/ OXIDATION - HIGH FLOW
BPT (I)
BPT
(II)
Suggested
Capital
Operating
Annual
Suggested
Capital
Operating
Annual
Plant #
Treatment
Cost ($)
Cost($/yr)
Cost($/yr)
Treatment
Cost($/yr)
Cost($/yr)
Cost($/yr)
20
ASL
500,000
52,000
130,000
ASL/MMF
740,000
74,000
180,000
31
CLR
185,000
18,000
40,000
MMF
550,000
44,000
108,000
36
ASL
600,000
58,000
145,000
ASL/MMF
840,000
78,000
195,000
49
No
Treat.
0
0
0
No Treat.
0
0
0
57
MMF
720,000
65,000
150,000
MMF
720,000
65,000
150,000
60
MMF
900,000
80,000
190,000
MMF
900,000
80,000
190,000
61
ASL
1,550,000
170,000
360,000
ASL/MMF
2,220,000
230,000
495,000
62
ASL
1,150,000
120,000
260,000
ASL/MMF
1,750,000
168,000
375,000
63
ASL
3,100,000
360,000
740,000
ASL/MMF
4,200,000
449,000
960,000
76
No
Treat.
0
0
0
No Treat.
0
0
0
80
No
Treat.
0
0
0
No Treat.
0
0
0
84
ASL
2,850,000
335,000
680,000
ASL/MMF
3,900,000
420,000
890,000
98
ASL
1,400,000
150,000
330,000
ASL/MMF
2,050,000
206,000
460,000
102
No
Treat.
0
0
0
No Treat.
0
0
0
103
No
Treat.
0
0
0
No Treat.
0
0
0
110
No
Treat.
0
0
0
No Treat.
0
0
0
112
ASL
930,000
95,000
210,000
ASL/MMF
1,430,000
136,000
307,000
113
No
Treat.
0
0
0
No Treat.
0
0
0
114
No
Treat.
0
0
0
MMF
850,000
77,000
170,000
127
ASL
1,400,000
130,000
310,000
ASL/MMF
1,960,000
174,000
420,000
175
MMF
520,000
44,000
98,000
MMF
520,000
44,000
98,000
176
MMF
560,000
44,000
110,000
MMF
560,000
44,000
110,000
187
ASL
1,700,000
170,000
420,000
ASL/MMF
2,325,000
222,000
540,000
193
ASL
1,200,000
140,000
300,000
ASL/MMF
1,535,000
171,000
373,000
195
No
Treat -
0
0
0
No. Treat.
0
0
0
216
No
Treat.
0
0
0
No Treat.
0
0
0
220
ASL
450,000
55,000
120,000
ASL/MMF
700,000
80,000
176,000
222
ASL
1,100,000
120,000
270,000
ASL/MMF
1,450,000
152,000
346,000
228
ASL
1,900,000
220,000
450,000
ASL/MMF
2,650,000
290,000
610,000
234
No
Treat.
0
0
0
No Treat.
0
0
0
-------
TABLE 8-18 (Continued)
SUBCATEGORY: TYPE
PLANT-BY-PLANT COST ESTIMATES
I W/ OXIDATION - HIGH FLOW
N3
On
N3
Plant #
BPT (I)
Suggested Capital
Treatment Cost ($)
Operating
Cost($/yr)
1
Annual |
Cost($/yr) |
Suggested
Treatment
BPT
Capital
Cost($/yr)
(II)
Operating
Cost($/yr)
Annual
Cost($/yr
235
ASL
2,300,000
270,000
560,000 I
ASL/MMF
3,200,000
350,000
750,000
248
ASL
1,300,000
130,000
290,000 I
ASL/MMF
1,925,000
181,000
410,000
249
No Treat.
0
0
0 1
No Treat.
0
0
0
257
ASL
870,000
90,000
210,000 I
ASL/MMF
1,330,000
129,000
302,000
272
CLR
340,000
22,000
62,000 I
MMF
800,000
75,000
170,000
88
ASL
1,150,000
120,000
260,000 I
ASL/MMF
1,740,000
167,000
375,000
158
ASL
700,000
73,000
170,000 |
ASL/MMF
1,070,000
107,000
250,000
206
MMF
850,000
75,000
170,000 j
MMF
850,000
75,000
170,000
236
MMF
800,000
75,000
170,000 I
MMF
800,000
75,000
170,000
SUBCATEGORY: TYPE I
W/ OXIDATION - LOW FLOW
42
ASL
490,000
54,000
125,000 |
ASL/MMF
720,000
73,000
170,000
50
No Treat.
0
0
o 1
MMF
320,000
30,000
72,000
81
ASL
750,000
88,000
190,000 I
ASL/MMF
1,090,000
120,000
265,000
81
ASL
510,000
56,000
130,000 I
ASL/MMF
765,000
81,000
188,000
81 (total
2 streams)
1
1,260,000
144,000
320,000 I
1,855,000
201,000
453,000
138
ASL
800,000
105,000
230,000 1
ASL/MMF
1,220,000
141,000
315,000
160
ASL
760,000
80,000
175,000 I
ASL/MMF
1,180,000
118,000
260,000
163
ASL
410,000
44,000
107,000 |
ASL/MMF
615,000
61,000
147,000
177
No Treat.
0
0
o 1
No Treat.
0
0
0
188
No Treat.
0
0
0 1
No Treat.
0
0
0
218
ASL
380,000
43,000
103,000 j
ASL/MMF
565,000
60,000
141,000
219
CLR
55,000
16,000
22,000 I
MMF
230,000
20,000
48,000
239
No Treat.
0
0
o 1
No Treat.
0
0
0
268
ASL
2,200,000
320,000
580,000 |
ASL/MMF
2,880,000
380,000
720,000
271
CLR
185,000
18,000
40,000 |
MMF
560,000
44,000
110,000
-------
TABLE 8-18 (Continued)
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: Type I w/o Oxidation
Plant #
BPT (I)
Suggested Capital
Treatment Cost ($)
Operating
Cost($/yr)
Annual
Cost($/yr)
Suggested
Treatment
BPT
Capital
Cost($/yr)
(II)
Operating
Cost($/yr)
Annual
Cost($/yr)
1
ASL/MMF
1,330,000
178,000
295,000
ASL/MMF
1,330,000
178,000
295,000
15
No Treat.
0
0
0
No Treat.
0
0
0
16
ALA/MMF
5,850,000
537,000 1
,270,000
ALA/MMF
5,850,000
537,000
1,270,000
28
MMF
740,000
68,000
155,000
MMF
740,000
68,000
155,000
32
ASL/MMF
620,000
61,000
148,000
ASL/MMF
620,000
61,000
148,000
35
No Treat.
0
0
0
No Treat.
0
0
0
53
MMF
675,000
60,000
135,000
MMF
675,000
60,000
135,000
64
No Treat.
0
0
0
No Treat.
0
0
0
85
MMF
340,000
32,000
75,000
MMF
340,000
32,000
75,000
117
No Treat.
0
0
0
No Treat.
0
0
0
118
No Treat.
0
0
0
No Treat.
0
0
0
128
No Treat.
0
0
0
MMF
650,000
68,000
150,000
130
No Treat.
0
0
0
No Treat.
0
0
0
164
ASL/MMF
1,060,000
106,000
750,000
ASL/MMF
1,060,000
106,000
750,000
171
MMF
600,000
50,000
120,000
MMF
600,000
50,000
120,000
170
MMF
700,000
64,000
145,000
MMF
700,000
64,000
145,000
178
ASL/MMF
3,100,000
303,000
720,000
ASL/MMF
3,100,000
303,000
720,000
183
No Treat.
0
0
0
No Treat.
0
0
0
201
ASL/MMF
710,000
83,000
173,000
ASL/MMF
710,000
83,000
173,000
203
ASL/MMF
790,000
79,000
197,000
ASL/MMF
790,000
79,000
197,000
204
No Treat.
0
0
0
No Treat.
0
0
0
230
ASL/MMF
1,050,000
104,000
246,000
ASL/MMF
1,050,000
104,000
246,000
256
No Treat.
0
0
0
MMF
270,000
26,000
64,000
259
No Treat.
0
0
0
No Treat.
0
0
0
263
MMF
205,000
17,000
41,000
MMF
205,000
17,000
41,000
264
No Treat.
0
0
0
No Treat.
0
0
0
269
ASL/MMF
2,900,000
315,000
670,000
ASL/MMF
2,900,000
315,000
670,000
275
ASL/MMF
800,000
84,000
195,000
ASL/MMF
800,000
84,000
195,000
159
No Treat.
0
0
0
No Treat.
0
0
0
281
No Treat.
0
0
0
No Treat.
0
0
0
-------
TABLE 8-18 (Continued)
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: NOT TYPE I
BPT (I)
1
BPT
(11)
Suggested
Capital
Operating
Annual I
Suggested
Capital
Operating
Annual
Plant #
Treatment
Cost ($)
Cost($/yr)
Cost($/yr) j
Treatment
Cost($/yr)
Cost($/yr)
Cost($/yr)
6
ASL/MMF
815,000
83,000
1
194,000 |
ASL/MMF
815,000
83,000
194,000
8
ASL/MMF
890,000
90,000
208,000 I
ASL/MMF
890,000
90,000
208,000
18
No Treat
0
0
0 |
No Treat.
0
0
0
21
No Treat.
0
0
o 1
No Treat.
0
0
0
59
MMF
600,000
50,000
120,000 1
MMF
600,000
50,000
120,000
66
MMF
810,000
66,000
159,000 1
MMF
810,000
66,000
159,000
86
ASL/MMF
1
,660,000
167,000
370,000 I
ASL/MMF
1,660,000
167,000
370,000
92
No Treat.
0
0
0 1
No Treat.
0
0
0
94
MMF
5
,000,000
250,000
850,000 I
MMF
5,000,000
250,000
850,000
97
MMF
520,000
42,000
100,000 1
MMF
520,000
42,000
10,000
120
No Treat.
0
0
0 I
MMF
2,500,000
150,000
450,000
121
No Treat.
0
0
o 1
No Treat.
0
0
0
122
MMF
650,000
56,000
130,000 1
ASL/MMF
1,700,000
166,000
370,000
144
MMF
540,000
42,000
100,000 1
ASL/MMF
1,020,000
94,000
220,000
145
ASL/MMF
1
,800,000
180,000
400,000 1
ASL/MMF
1,800,000
180,000
400,000
153
ASL/MMF
1
,045,000
104,000
245,000 1
ASL/MMF
1,045,000
104,000
245,000
182
ASL/MMF
1
,250,000
122,000
280,000 1
ASL/MMF
1,250,000
122,000
280,000
186
No Treat.
0
0
o 1
No Treat.
0
0
0
205
MMF
160,000
15,000
34,000 1
MMF
160,000
15,000
34,000
208
MMF
400,000
36,000
85,000 I
ASL/MMF
830,000
81,000
195,000
226
MMF
560,000
46,000
110,000 1
MMF
560,000
46,000
110,000
231
ASL/MMF
1
,270,000
156,000
332,000 1
ASL/MMF
1,270,000
156,000
332,000
245
No Treat.
0
0
0 1
No Treat.
0
0
0
247
No Treat.
0
0
0 1
No Treat.
0
0
0
258
ASL/MMF
550,000
59,000
136,000 I
ASL/MMF
550,000
59,000
136,000
270
No Treat.
0
0
0 1
No Treat.
0
0
0
151
MMF
700,000
64,000
148,000 I
MMF
700,000
64,000
148,000
-------
TABLE 8-19
TOTAL COSTS, PLANT-BY-PLANT ANALYSIS
BPT (I)
BPT (II)
Capital
Operating
Annual
Capital
Operating
Annual
Cost ($)
Cost ($/Yr)
Cost ($/Yr)
Cost ($)
Cost ($/Yr)
Cost ($/Yr)
PLASTICS
33,045,000
3,215,000
7,388,000
41,875,000
4,265,000
9,665,000
TYPE I W/ OXID.
-High Flow
31,025,000
3,281,000
7,205,000
43,565,000
4,363,000
9,682,000
-Low Flow
6,540,000
824,000
1,702,000
10,145,000
1,128,000
2,436,000
TYPE I W/O OXID.
21,470,000
2,141,000
5,335,000
22,390,000
2,235,000
5,549,000
NOT TYPE I
19,220,000
1,628,000
4,001,000
23,680,000
1,985,000
4,921,000
I
TOTAL 111,300,000 11,089,000 25,631,000 I 141,290,000 13,950,000 32,253,000
-------
TABLE 8-20
PERCENTAGE OF PLANTS REQUIRING ADDITIONAL TREATMENT
FOR BPT (I)
No Additional
Subcategory Treatment ASL/MMF MMF ASL CLAR
plastics Only 38 29 33 0 0
Not Plastics - Type I
W/ Oxidation
-High Flow 31 0 15 49 5
-Low Flow 31 0 0 54 15
Not Plastics -Type I
W/0 Oxidation 47 30 20 0 0
Not Plastics NOT Type I 33 30 37 0 0
3% require ALA/MMF (Not Plastics - Type I W/O Oxidation)
TABLE 8-21
PERCENTAGE OF PLANTS REQUIRING ADDITIONAL TREATMENT
FOR BPT (II)
No Additional
Subcategory Treatment
Plastics Only 31
Not Plastics - Type I
W/Oxidation
-High Flow 28
-Low Flow 23
Not Plastics -Type I
W/O Oxidation 40
Not Plastics NOT Type I 30
ASL/MMF MMF ASL CLAR
36 33 0 0
49 23 0 0
54 23 0 0
30 27 0 0
40 30 0 0
3% require ALA/MMF (Not Plastics - Type I W/O Oxidation)
266
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TABLE 8-22
PERCENTAGE OF ANNUAL COSTS BY SUBCATEGORY
Subcategory BPT (I) BPT (II)
PLASTICS
58 Plants
(35% of data base) 29 30
NOT PLASTICS - TYPE I W/ OXIDATION
-High Flow
39 Plants
(23% of data base) 28 30
-Low Flow
13 Plants
(8% of data base) 7 8
NOT PLASTICS - TYPE I W/0 OXIDATION
30 Plants
(18% of data base) 21 17
NOT PLASTICS - NOT TYPE I
27 Plants
(16% of data base) 15 15
167 Total Plants (100%) 100% ' 100%
267
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CAPDET REPRODUCIBILITY
Following completion of the cost estimates used to prepare this report,
an attempt was made to verify the reproducibility of the CAPDET program.
In conducting this evaluation it was determined that the CAPDET program
had been revised since the original cost analyses. Neither the EPA nor
the Corps of Engineers has available documentation of the earlier ver-
sion of CAPDET from which the costs were generated.
*
To determine the extent of the revisions, a set of activated sludge sys-
tem costs were run using input values identical to those used in an ear-
lier run for which printouts were available. The technologies designed
and costed included primary clarification, complete mix activated sludge
(with secondary clarifier), gravity thickening, sludge drying and con-
tract hauling.
Both series of runs using the old and revised CAPDET showed identical
designs and costs for primary and secondary clarifier, gravity thick-
ener, drying beds and similar costs for hauling. However, the designs
and costs for the complete mix activated sludge system were different.
Comparing a 1000 mg/1 BOD influent at 0.2 MGD and a 20 mg/1 (LTM)
effluent target, the sizing of the reactor by the revised version was
larger, but cost less. A 4.86 MG vessel with costs of $1.07 million for
the revised CAPDET versus 3.69 MG vessel costing $1.31 million for the
older version.
FURTHER CHANGES TO CAPDET
Following this analysis some further revisions were made to CAPDET. The
major difference in the design of OCPS industry wastewater treatment
systems, compared with domestic or sanitary wastewater treatment sys-
tems, is the slower rate at which biological oxidation reactions pro-
ceed. Typically, the kinetic rate for the BOD degradation of OCPS
wastewater is one-half to one-fifth the rate for domestic wastewater.
In addition, the influent BOD concentration for a domestic wastewater
treatment system usually falls within a relatively narrow range, typi-
cally from 200 to 350 mg/1. Influent BOD concentrations for OCPS indus-
try treatment systems can range from less than one hundred to several
thousand mg/1. On this basis, the kinetic model used by CAPDET was mod-
ified as shown in Table 8-1. As an alternative to the use of this mod-
el, the necessary programming changes were made to incorporate a kinetic
model specifically intended for industrial wastewater.
Research, provided by Gloyna, Grau, and any others in the industrial
waste field has found the Grau kinetic model more closely simulates ac-
tual biochemical removal or organics.[8-8] Union Carbide has completed
extensive study on the use of Grau kinetics to model its chemical
plants. The resulting conclusion is that BOD removal has been determin-
ed to be first order as a function of soluble BOD and volatile solids
but inversely proportionate to the influent soluble BOD concentration.
The work is described in an article by Cyron T. Lawson, et_ a_l. in
"Comments on Selected Aspects of Activated Sludge Treatment Technology
Based on Recent Union Carbide Experience".
268
-------
The use of soluble, rather than total, influent BOD concentrations re-
presents a constraint when applying the Grau model to develop industry-
wide treatment costs. Very few plants in the OCPS data base reported
soluble influent BOD characteristics. To apply the Grau model to plants
which reported only total influent BOD data, some relationship between
total and soluble BOD would have to be assumed. Errors in this assump-
tion may offset the benefits of using a more accurate kinetic modeling
technique.
NON WATER QUALITY ASPECTS
The use of wastewater treatment systems to alleviate water pollution
problems may result in adverse impacts in other environmental areas.
Elements of other environmental concerns that must be considered
include:
1. Air pollution
2. Solid waste generation
3. RCRA considerations
4. Noise pollution
5. Energy requirements
Air Pollution
If solvents or other volatile hydrocarbons are subjected to an evapor-
ative process (such as an evaporation pond) where vapor condensation is
impractical, volatile materials will be lost to the atmosphere. Vola-
tile materials can be lost to a lesser extent through aeration, dis-
solved air flotation and other treatment operations. The extent of the
pollution potential depends on the nature and concentration of the vol-
atile components and on the weather conditions at the site of disposal
or treatment, as well as the treatment technology itself.
Landfilling is a fairly common method of disposing of settled solids,
floating oil,s and biological sludges. If the landfill is not properly
designed and maintained, volatile components in the nonwater wastes can
evaporate and contribute to air pollution.
Incineration is another commonly employed method for the disposal of
nonaqueous wastes. Improperly designed or operated incinerators can
discharge particulates, hydrocarbons or noxious gases to the atmosphere.
Most of these emissions can be controlled by the use of scrubbers.
These scrubbers will, however, create an additional source of contam-
inated wastewater.
Solid Waste Generation
Solid wastes, for the purposes of this report, include the solids and
skimmings produced by the treatment technologies involved in the pri-
mary, secondary and tertiary end-of-pipe treatment of the OCPS indus-
try's wastewater.
The solids include such materials as grit and solids from primary clar-
ifiers, sludges and skimmings generated by the various separation tech-
269
-------
oologies, biological sludge from biological treatment plants, spent
3ctiv3t6d carbon and residues from incineration. Most of the above sol-*
ids generated cannot be quantified without a specific on-site evalua-
tion; either by the individual plant records, if available, or by a
study to determine the quantity of solid waste generated.
The major quantity of solid waste generated, however, is the excess bio-
logical sludge. This material can be approximtely quantified because,
in biological treatment, the excess sludge is directly related to the
BOD removed. CAPDET used 0.73 pounds of sludge generated per pound of
BOD removed. Figure 8-14 shows the sludge production as a function of
the change in BOD concentration.
RCRA Considerations
Processing operations and treatment facilities in OCPS plants generate
solid and liquid wastes which in some cases may be classified as "haz-
ardous wastes" by the definition and characteristics outlined in Section
3001 of the Resource Conservation and Recovery Act (RCRA). Storage,
transport, treatment and disposal methods for these wastes are regulated
by RCRA interim status standards.
OCPS hazardous waste generators using contract removal, offsite disposal
and sales must comply with the transportation guidelines for hazardous
waste. The guidelines include standards for manifest, labels, contain-
ers, marking and placarding of wastes before removal. The receiver of
the wastes would then be responsible for meeting treatment, storage and
disposal requirements.
Onsite treatment of hazardous waste by OCPS generators does not have to
comply with transportation guidelines for hazardous wastes. They must,
however, meet standards for treatment, storage and disposal of these
wastes (RCRA Section 3004) and must obtain a permit (RCRA Section 2005).
OCPS generators treating onsite include EOP systems and zero discharge
performers using deep wells, incineration followed by scrubbing, evapor-
ation ponds and land disposal.
Noise Generation
None of the alternate technologies presented in this report are judged
to be generators of excessive noise levels. Most industrial installa-
tions, including the OCPS plants, do generate a background noise level
which, if excessive, must be accommodated under OSHA regulations. Fur-
thermore, practically all machinery of recent manufacture is constructed
or installed to comply with OSHA noise level requirements.
None of the technologies proposed, nor the equipment associated with the
technologies, are unique or radically different from other industrial
machinery in respect to noise generation.
On this basis it is judged that noise pollution does not pose a poten-
tial problem with the implementation of the suggested technologies.
270
-------
100
200 300 400 500
BOD EffLUErr - 30D EF7LL2OT Cffig/1)
FIGURE 8-1A - SLUDGE PRODUCTION FOR COMPLETE MIX
ACTIVATED SLUDGE
271
-------
Energy Requirements
Due to the importance of today's need for energy conservation and the
inceasing costs arising from energy shortages, energy usage must be
considered before implementing treatment technologies.
In-plant technologies may require high energy consumptions. Activated
carbon adsorption requires a large energy utilization (3,000 BTU/lb of
carbon) to regenerate spent carbon. [8-9] Membrane technologies require
energy for use in producing pressure to force liquid wastes through the
film. Steam stripping utilizes energy to produce and move the steam.
Wet oxidation requires large energy amounts for generating high pres-
sures and for fueling the operation to promote extreme temperatures un-
less the organic content of the wastewater is high enough to sustain
auto-oxidation.
Energy requirements for EOP treatments using aerators range from 0.6 to
1.15 hp/1000 ft .[8-10] Energy requirements for complete^mix activated
sludge calculated for an average value of 0.88 hp/1000 ft are shown in
Figure 8-15 as a function of flow and residence time. These costs also
include pumping requirements in addition to aeration and mixing. The
residence time can be obtained from Figure 8-1 discussed previously.
Other energy requirements are needed for clarifier operation, some types
of filtration requiring pressure, dissolved air flotation and activated
carbon regeneration. Ultimate treatment of sludge, residues, scums and
liquid wastes by incineration would require additional energy. Figures
8-16 through 8-18 list the energy requirements utilized by CAPDET for
clarification, dissolved air flotatation and multimedia filtration.
Energy requirements for zero discharge treatment, except incineration,
are mainly for pumping liquids or for operating and transporting vehi-
cles. Recycling may require additional energy to return the recycled
wastes to the process. Incineration would rely on energy to heat and
oxidize wastes. Energy used to maintain evaporation process equipment
must also be considered.
272
-------
0 20 40 60 80 100 120 140 160 180 200 220
c
-------
FLOW - MILLION GAL/DAY
FIGURE 8-16 - ENERGY REQUIREMENTS FOR CLARIFICATION
274
-------
ROW - MILLION GALLONS/OAT
FIGURE 8-17 - ENERGY REQUIREMENTS FOR DISSOLVED AIR FLOTATION
275
-------
FLOW - MILLION GAL/DAY
FIGURE 8-18 - ENERGY REQUIREMENTS FOR MULTIMEDIA FILTRATION
276
-------
SECTION IX.
EFFLUENT REDUCTION ATTAINABLE THROUGH THE APPLICATION OF
BEST PRACTICABLE CONTROL TECHNOLOGY CURRENTLY AVAILABLE
GENERAL
The effluent limitations which were required to be achieved by July 1,
1977, are based on the degree of effluent reduction attainable through
the application of the best practicable control technology currently
available (BPT). The best practicable control technology currently
available generally is based upon the average of the best existing per-
formance, in terms of treated effluent discharged, by plants of various
sizes, ages, and unit processes within an industry or subcategory^
Where existing performance is uniformly inadequate, BPT may be trans-\
ferred from a different subcategory or category. Limitations based on
transfer technology must be supported by a conclusion that the technol-
ogy is, indeed, transferable and a reasonable prediction that it will be
capable of achieving the prescribed effluent limits (see Tanners
Council of America v. Train, 540 F. 2d 1188 (4th Cir. 1976)). While
best practicable control technology currently available focuses on end-
of-pipe treatment technology rather than process changes or internal
controls, it can include process changes or internal controls when the
changes or controls are normal practice with an industry.
BPT considers the total cost of the application of technology in rela-
tion to the effluent reduction benefits to be achieved from the technol-
ogies. The cost/benefit inquiry for BPT is a limited balancing, which
does not require the Agency to quantify benefits in monetary terms (see,
e.g., American Iron and Steel v. EPA, 526 F 2d 1027 (3rd Cir. 1975)).
In balancing costs in relation to effluent reduction benefits, EPA con-
siders the volume and nature of existing discharges, the volume and na-
ture of discharges expected after application of BPT, the general envi-
ronmental effects of the pollutants, and the costs and economic impacts
of the required pollution control level. The Act does not require or
permit consideration of water quality problems attributable to partic-
ular point sources or industries, or water quality improvements in par-
ticular water bodies (see Weyerhaeuser Company v. Costle, 11 ERC 2149
(D.C. Cir. 1978)).
REGULATED POLLUTANTS
Pollutants proposed for regulation under BPT are BOD^, TSS and pH.
IDENTIFICATION OF THE BEST PRACTICABLE CONTROL TECHNOLOGY
In determining the best practicable control technology, biological
treatment has been evaluated as the principal treatment practice within
the OCPS industry. Of the 185 plants for which treatment system infor-
mation is available, 146 use some form of biological treatment. Al-
though nonbiological treatment systems are often used to produce high
quality effluents, only biological treatment has been sufficiently ap-
plied to be considered across the broad spectrum of the OCPS industry.
On this basis, biological treatment, in general, may be considered the
277
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best technology for treatment of OCPS wastewaters and is, therefore,
chosen as best practicable control technology.
RATIONALE FOR SELECTION OF THE BEST PRACTICABLE CONTROL TECHNOLOGY
Use of biological treatment as the best practicable control technology
will produce high quality effluents as shown in Section VII. Evalua-
tions to determine if the addition of tertiary treatment processes such
as polishing ponds, filtration, carbon adsorption, etc., would improve
effluent quality indicated that plants with tertiary processes do not
achieve lower effluent BOD,, concentrations than plants utilizing only
biological systems. This apparent contradiction may have resulted from
the fact that, because the data base is limited to performance data for
entire treatment systems, performance data are not available for indi-
vidual unit treatment processes. This tends to mask the effect of
plants which install additional end-of-pipe treatment technologies to
compensate for poorly designed or poorly operated existing treatment
systems. Therefore, it was determined that the evaluation of levels of
performance by the treatment technology utilized by OCPS plants was not
appropriate.
Of the 145 plants in the Summary Data Base which employ biological
treatment and have effluent BOD,, data, only 65 plants, or 46%, comply
with applicable BOD- effluent limitations, while the remaining 78
plants, or 55%, were not in compliance. In addition, of the 129 plants
in the Summary Data Base which employ biological treatment and have ef-
fluent TSS data, only 60 plants, or 47%, comply with applicable TSS ef-
fluent limitations, while the remaining 69 plants, or 53%, were not in
compliance. This is an indication that, while biological treatment has
been demonstrated to achieve low effluent concentrations, the median
values obtained for all biological systems in the industry are not con-
sidered to be representative of the average level of treatment which can
be achieved. While some plants in the data base are well designed and
operated to the maximum potential, others are operating at less than op-
timum performance. In order to segregate good performers from bad per-
formers, it was necessary to develop a test to distinguish the better
plants from those operating less efficiently.
The first test used to define the well operated plants was to consider
only those plants which achieved BOD- removals equal to or greater than
95%. As presented in Section VII, plants which meet this test criteria
achieve lower median values than do all plants with biological systems.
However, it was also recognized that use of the 95% removal criteria
eliminates some plants which achieve lower effluent BOD,, concentrations,
but by virtue of having very low influent BOD^ concentrations, do not
achieve 95% removal.
In an attempt to address this potential inconsistency, a new segment was
evaluated which included all plants which achieved 95% BOD^ reduction or
which achieved a final effluent BOD- concentration of less than or equal
to 50 mg/1. This also allowed the inclusion of effluent BOD5 data which
had no corresponding influent value.
278
-------
In addition, while reviewing the data for this segment, it appeared that
well operated plants in the Not Plastics Only-Type I with Oxidation sub-
category had a wide range of effluent values. Subsequent investigations
showed that this effect appeared to be related to the efficiency of wa-
ter use by plants in this subcategory. Water use efficiency was defined
as a plant's daily water usage divided by its daily production level.
As described in detail in Section VII, a further analysis showed this
effect to be limited to those plants in the first quartrile of water
use. This included plants with water use less than or equal to 0.2 gal-
lons per pound of product. This suggested that the Not Plastics Only -
Type I with Oxidation subcategory be further divided into low water use
(less than 0.2 gallons per pound) and high water use (greater than 0.2
gallons per pound) subcategories. When this was done, the resulting
long term median final effluent BOD- and TSS concentrations for plants
with at least 95% BOD^ removal or 50 mg/1 final effluent BOD^ concentra-
tions were 26 mg/1 ana 62 mg/1 for high water use facilities and 36 mg/1
and 89 mg/1 for low water use facilities.
After the calculation of long term median effluent concentration for
each proposed subcategory, EPA grouped for analysis all plants which
performed better than the subcategory long term median and all plants
which performed worse. This analysis was performed to determine if
certain plant characteristics would cause plants to perforin better or
worse than the subcategory long term median. The results showed that
both groups have similar mixes and numbers of generic processes, similar
ranges in the number of specific product processes, similar raw waste
concentration distributions, similar contributions from secondary pro-
duction of non-OCPS products and geographical mix (as a measure of
temperature effects). Therefore, it can be concluded that different
types of plants were not improperly combined within a subcategory.
The implementation of additional end-of-pipe treatment technologies can
require additional land. In addition, spatial relationships and the
physical characteristics of available land can affect construction
costs. However, as detailed in Section VIII, the cost of land acquisi-
tion has been included in cost estimates, where appropriate. In addi-
tion, the impact of plant-by-plant variations has been lessened by cost-
ing least land intensive options available (i.e., activated sludge ver-
sus aerated lagoons).
BPT EFFLUENT LIMITATIONS
BPT effluent limitations are presented in Table 9-1.
METHODOLOGY USED FOR DEVELOPMENT OF BPT EFFLUENT LIMITATIONS
Biological treatment has been identified as the best practicable control
technology currently available for each of the four proposed subcategor-
ies. The long term median BPT final effluent BOD^ and TSS concentra-
tions were calculated for each subcategory by using the performance of
plants which attain 95% BOD, reduction or a final effluent BOD^ concen-
tration less than or equal to 50 mg/1. In addition, after a review of
data and information submitted by the industry, it was determined that
four plants which met the above BOD criteria had installed more advanced
279
-------
TABLE 9-1
BPT EFFLUENT LIMITATIONS
(mg/1 or ppm)
LONG TERM MEDIAN MAXIMUM 30-DAY MAXIMUM DAILY
SUBCATEGORY BOD^ TSS BOP5 TSS BOD5 TSS
Plastics Only 14.5 24 22 36 49 117
Oxidation
o High Water Use 26 62 42 84 106 246
o Low Water Use 36 89 58 120 146 353
Type I 24.5 34.5 40 47 100 137
Other Discharges 17 29 28 39 69 115
pH - All subcategories - Within a range of 6.0 to 9.0 at all times
280
-------
wastewater treatment technology in order to meet permit conditions based
on water quality standards. It was determined that the performance of
these four plants (three plants in the Plastics Only subcategory and one
plant in the Other Discharges subcategory) was not representative of
this technology-based regulation and therefore, were removed from the
calculation of effluent limitations. Remaining plants were determined
to achieve the best existing performance.
Maximum 30-day and daily maximum effluent limitations were determined by
multiplying long-term median effluent concentrations by appropriate var-
iability factors which were calculated through statistical analysis of
long term BOD,, and TSS daily data. This statistical analysis is de-
scribed in detail in Section VII.
COST OF APPLICATION AND EFFLUENT REDUCTION BENEFITS
Summary Data Base
The total cost (1979 dollars) of attainment of BPT effluent limitations
for the 130 direct discharging plants in the Summary Data Base which do
not meet these limitations has been estimated to be about 111.30 million
dollars in capital cost with associated total annual cost of about 25.63
million dollars per year.
Conventional pollutant removals from current discharge loadings associ-
ated with Summary Data Base plants have been estimated to be about 9.79
million kg/yr (21.58 million lbs/yr) of BOD^ and 14.59 million kg/yr
(32.17 million lbs/yr) of TSS. These removals represent a cost per
pound of BOD and TSS removed of about $0.48/lb. of BOD and TSS removed.
Percent removals of BOD and TSS from current raw waste loads are esti-
mated to be about 94.8 percent and 74.6 percent, respectively. Table
9-2 presents the annual pounds removed figures for each proposed sub-
category.
Total Industry
The total cost of attainment of BPT effluent limitations for all direct
discharging plants in the OCPS industry has been projected to be about
316 million dollars in capital costs with associated total annual costs
of about 105 million dollars per year. These projections were made for
use in the Economic Impact Analysis (EIA) and are documented in the EIA
document.
As discussed in previous sections of this document, many different est-
imates have been made on the number of plants in the OCPS industry.
Estimates range from about 1200 plants to as many as 2100 plants. Due
to the many estimates of the number of direct discharging plants in the
OCPS industry, a direct projection of the Summary Data Base to the en-
tire industry was not possible and a general analysis was utilized to
project the conventional pollutant removals to the entire OCPS industry.
Weighted averages of current BOD, and TSS concentrations and current
flows for each subcategory were utilized to calculate current total
industry BOD and TSS loadings. Using the same weighted average for cur-
rent flows, total industry BOD and TSS loadings were calculated using
281
-------
TABLE 9-2
EFFLUENT REDUCTION BENEFITS AND NON WATER QUALITY IMPACTS
FOR SUMMARY DATA BASE PLANTS
IN EACH OF THE PROPOSED SUBCATEGORIES
PLASTICS ONLY
OXIDATION
o High Water Use
o Low Water Use
TYPE I
OTHER DISCHARGERS
Million lbs/yr
Removed
BOD TSS
1.75
6.50
2.72
9.68
0.93
6.01
4.34
0.65
11.09
10.08
Energy
Requirements
(Barrels/yr)
29,455
84,137
6,771
24,188
12,444
Additional
Solid Waste
(Tons/yr)
3,311
3,307
800
7 ,239
5,203
TOTALS
21.58
32.17
156,995
19,860
282
-------
the proposed effluent limitations. The difference in these two total
industry loadings was used as the total BOD and TSS removals from cur-
rent discharge levels. A summary of this case study is shown in Table
9-3. As can be seen in Table 9-3, conventional pollutant removals from
current discharge levels based on attainment of BPT effluent limitations
have been projected to be about 67.59 million kg/yr (149 million pounds)
of BOD and 46.27 million kg/yr (102 million pounds) of TSS. These re-
movals represent a cost per pound of BOD and TSS removed of about
$0.42/lb. of BOD and TSS removed. Percent removals of BOD and TSS from
current raw waste loads are similar to those for the Summary Data Base.
NON-WATER QUALITY ENVIRONMENTAL IMPACTS
Non-water quality environmental impacts have also been considered in
Section VIII. The impacts associated with attainment of BPT effluent
limitations by Summary Data Base plants are discussed below. Non-water
quality impacts based on total industry attainment of the BPT effluent
Imitations are not discussed below due to difficulties associated with
projecting Summary Data Base impacts. However, general conclusions on
impacts can be drawn from the Summary Data Base statistics.
ENERGY
Attainment of BPT will require the use of the equivalent of approximate-
ly 32.69 million liters (157 thousand barrels) of residual fuel oil per
year for Summary Data Base plants. Table 9-2 presents a breakdown of
the energy requirement by subcategory.
SOLID WASTE
Attainment of BPT will result in an additional 18.02 thousand kkg/yr
(19,860 tons/yr) of wastewater treatment solids for plants in the Sum-
mary Data Base. Table 9-2 presents the amount of additional solids gen-
erated by subcategory.
AIR AND NOISE
Attainment of BPT will have no measurable impact on air or noise
pollution.
283
-------
TABLE 9-3
CASE STUDY FOR ESTIMATING TOTAL INDUSTRY
DIRECT DISCHARGE LOADINGS FOR
BOD5 AND TSS
bod5
TSS
m
3
g/1 million lbs/year
Mean raw waste1 945 3,153.9
Current effluent^" 63 208.3
2 ~\ A 148.8
BPT effluent 18 59.5 |
Mean raw waste^ 427 1,401.7
Current effluent^ 63 208.3
2 ~l A 102.5
BPT effluent 32 105.8 I
mean of all plants in Summary Data Base
median value of all biological systems with BOD, removal > 95% or
effluent BOD^ 50 mg/1 ~~
based on 330 operating days per year, 2.31 MGD per plant, and 520
direct discharge plants
284
-------
SECTION X
EFFLUENT REDUCTION ATTAINABLE THROUGH THE APPLICATION OF
BEST CONVENTIONAL POLLUTANT CONTROL TECHNOLOGY
EFFLUENT LIMITATIONS GUIDELINES
GENERAL
The 1977 amendments added Section 301(b)(2)(E) to the Act, establishing
"best conventional pollutant control technology" (BCT) for discharges of
conventional pollutants from existing industrial point sources. Section
304(a)(4) designated the following as conventional pollutants: BOD, TSS,
fecal coliform and pH. The Administrator designated oil and grease as
"conventional" on July 30, 1979, 44 FR 44501.
BCT is not an additional limitation, but replaces BAT for the control of
conventional pollutants. In addition to other factors specified in Section
304(b)(4)(b), the Act requires that BCT limitations be assessed in light of
a two-part "cost-reasonableness" test. EPA published a methodology for
determining BCT on August 29, 1979 (44 FR 50732). In American Paper
Institute v. EPA, 660 F. 2nd 954 (4th Cir. 1981), EPA was ordered to revise
the cost test.
The court held that EPA must apply a two-part test. The first test com-
pares the cost for private industry to reduce its conventional pollutants
with the costs for Publicly Owned Treatment Works to attain similar reduc-
tions in their discharge of these pollutants. The second test examines the
cost-effectiveness of additional industrial treatment beyond BPT. EPA must
find that limitations are "reasonable" under both tests before establishing
them as BCT. In no case may BCT be less stringent than BPT.
In response to the court order, EPA has proposed a revised BCT cost-
reasonableness test at 47 FR 49176 (October 29, 1982). The proposed test
provides that BCT is cost-reasonable if: (1) the incremental cost per
pound of conventional pollutant removed in going from BPT to BCT is less
than $.27 per pound in 1976 dollars, and (2) this same incremental cost per
pound is less than 143% of the incremental cost per pound associated with
achieving BPT.
REGULATED POLLUTANTS
Pollutants proposed for regulation under BCT are BOD^, TSS and pH.
IDENTIFICATION OF THE BEST CONVENTIONAL POLLUTANT CONTROL TECHNOLOGY
The Agency has considered an incremental technology level of conventional
pollutant control beyond BPT. The technology, additional solids control
such as polishing ponds and filtration, is already practiced by approxi-
mately one third of the plants in the industry.
BCT EFFLUENT LIMITATIONS
BCT effluent limitations are presented in Table 10-1.
285
-------
TABLE 10-1
BCT EFFLUENT LIMITATIONS
(mg/1 or ppm)
LONG TERM MEDIAN
SUBCATEGORY
Plastics Only
bod5
14.5
TSS
24
MAXIMUM 30-DAY
BOD 5
22
TSS
36
MAXIMUM DAILY
BODr
49
TSS
117
Oxidation
o High Water Use 26
o Low Water Use 36
62
89
42
58
84
120
106
146
246
353
Type I
24.5 34.5
40
47
100
137
Other Discharges 17
29
28
39
69
115
286
-------
RATIONALE FOR THE SELECTION OF BEST CONVENTIONAL POLLUTANT CONTROL
TECHNOLOGY
The Agency performed the first part of the BCT "cost-reasonableness" test
which compares the cost for private industry to reduce conventional pollu-
tants with the costs for Publicly Owned Treatment Works to attain similar
reductions in their discharge of conventional pollutants. To perform this
first test, EPA calculated the incremental conventional pollutant removals
beyond BPT and the incremental costs associated with the installation of
the BCT technology. Based on this information, cost per pound of BOD and
TSS removed ratios were calculated for each of the four BPT subcategories.
The results of this analysis are presented in Table 10-2.
All the incremental costs per pound ratios were found to fail this first
part of the BCT "cost-reasonableness" test ($0.33 per pound in 1979
dollars). Therefore, EPA did not perform the second part of the BCT "cost
reasonableness" test, and is proposing BCT effluent limitations which are
equal to the BPT effluent limitations for each of the proposed BPT sub-
categories .
METHODOLOGY USED FOR DEVELOPMENT OF BCT EFFLUENT LIMITATIONS
The methodology used for development of BCT effluent limitations is the
same as that used in the development of BPT effluent limitations since BCT
effluent limitations are equal to the BPT effluent limitations. For a de-
tailed description of this methodology, refer to Section IX of this
document.
COST OF APPLICATION AND EFFLUENT REDUCTION BENEFITS
There are no incremental costs or effluent reduction benefits associated
with the attainment of BCT effluent Imitations since BCT effluent limita-
tions are equal to the BPT effluent limitations. For detailed information
on the costs and effluent reduction benefits associated with the BPT efflu-
ent limitations, refer to Section IX of this document.
NON-WATER QUALITY ENVIRONMENTAL IMPACTS
Incremental non-water quality environmental impacts are associated with the
attainment of BCT effluent limitations since BCT effluent limitations are
equal to the BPT effluent limitations. For detailed information on the
non-water quality impacts associated with the BPT effluent limitations,
refer to Section IX.
287
-------
TABLE 10-2
BCT "COST-REASONABLENESS" TEST RESULTS
Subcategory
PLASTICS ONLY
OXIDATION
o High Water Use
o Low Water Use
TYPE I
OTHER DISCHARGES
Incremental BOD
and TSS Removed
(pounds/year)
161,600
2,199,000
414,000
461,000
604,286
Incremental Cost Per Pound of
Cost
(1979 $/yr.)
BOD^ and TSS Removed
2,277,000
2,477,000
734,000
214,000
920,000
<1979 $/yr.)
$14.09/lb.
$ 1.13/lb.
$ 1.77/lb.
$ 0.46/lb.
$ L.52/lb.
288
-------
SECTION XI
NEW SOURCE PERFORMANCE STANDARDS
GENERAL
The basis for new source performance standards (NSPS) under section 306 of
the Act is the best available demonstrated technology. At new plants, the
opportunity exists to design the best and most efficient production proc-
esses and wastewater treatment facilities. Therefore, Congress directed
EPA to consider the best demonstrated process change, in-plant controls and
end-of-pipe treatment technologies that reduce pollution to the maximum
extent feasible. It is encouraged that at new sources, reductions in the
use of and/or discharge of wastewater be attained by application of in-
plant control measures.
REGULATED POLLUTANTS
Conventional Pollutants
Conventional pollutants proposed for regulation under NSPS are the same as
for BPT: B0D5, TSS and pH.
IDENTIFICATION OF THE TECHNOLOGY BASIS OF NSPS
The technologies employed to control conventional pollutants at existing
plants are fully applicable to new plants. In addition, no other technol-
ogies could be identified for new sources which were different from those
used to establish BPT effluent limitations. Thus, the technology basis for
NSPS is the same as that for BPT effluent limitations. For detailed infor-
mation on the technology basis for BPT effluent limitations, refer to
Section IX of this document.
NEW SOURCE PERFORMANCE STANDARDS
New source performance standards for conventional pollutants are presented
in Table 11-1.
RATIONALE FOR THE SELECTION OF THE TECHNOLOGY BASIS FOR NSPS
Since the Agency could identify no additional generally applicable technol-
ogy for NSPS and since the technology basis for NSPS is the same as that
identified for BPT effluent limitations, EPA has established NSPS effluent
limitations equal to the proposed BPT and BCT effluent limitations.
METHODOLOGY USED FOR DEVELOPMENT OF NSPS EFFLUENT LIMITATIONS
The methodology used for the development of NSPS effluent limitations is
the same as that used for the development of BPT effluent limitations. For
detailed information on the methodology used to develop the BPT effluent
limitations, refer to Section IX of this document.
289
-------
TABLE 11-1
NSPS EFFLUENT LIMITATIONS
(mg/1 or ppm)
LONG TERM MEDIAN MAXIMUM 30-DAY MAXIMUM DAILY
SUBCATEGORY
Plastics Only
bod5
14.5
TSS
24
B0D5
22
TSS
36
BOD
49
TSS
117
Oxidation
o High Water Use 26
o Low Water Use 36
62
89
42
58
84
120
106
146
246
353
Type I
24. 5 34.5
40
47
100
137
Other Discharges 17
29
28
39
69
115
pH - All Subcategories - Within a range of 6.0 to 9.0 at all t
lines
290
-------
COST OF APPLICATION AND EFFLUENT REDUCTION BENEFITS
There are no incremental costs or effluent reduction benefits associated
with the attainment of NSPS since NSPS effluent limitations are equal to
the BPT effluent limitations. For detailed information on the costs and
effluent reduction benefits associated with the attainment of BPT effluent
limitations, refer to Section IX of this document.
NON-WATER QUALITY ENVIRONMENTAL IMPACTS
No incremental non-water quality environmental impacts are associated with
attainment of NSPS since NSPS effluent Imitations are equal to the BPT ef-
fluent limitations. For detailed information on the non-water quality im-
pacts associated with the attainment of BPT effluent Imitations, refer to
Section IX of this document.
291
-------
SECTION XII.
ACKNOWLEDGMENTS
The Environmental Protection Agency wishes to thank the following con-
tractors whose work formed the basis for this document:
JRB Associates Contract 68-01-6701
Environ Contract 68-01-6701
Clement Associates Contract 68-01-6024
Walk, Haydel & Associates Contract 68-01-6024
Catalytic, Inc. Contract 68-01-5011
The EPA would also like to thank the members of the Organic Chemicals
Plastics and Synthetic Fibers Industries and their plants who provided
data relative to this study.
293
-------
SECTION XIII.
REFERENCES
3-1 Riegel's Handbook of Ind. Chem., 3rd Edition, Ed. James A. Kent,
New York, Van Nostrand Reinhold Company, 1974, p. 772.
3-2 Wittcuff, H. A. and Reuben, B* G., Ind. Organic Chemistry in
Perspective, Part 1, New York, John Wiley & Sons, 1980, p. 40.
4-1 Conover, W. J., Practical Nonparametric Statistics, 1st Edition,
New York, John Wiley & Sons, 1971, pp. 245-249.
4-2 Kendall, M. G. and Stuart, A., The Advanced Theory of Statistics,
Volume 2, Inference and Relationship, New York, Hafner Publishing
Company, 1973, pp. 498-502.
5-1 APHA, AWWA and WPCR, Standard Methods for the Examination of Water
and Wastewater, 4th Edition, Washington, DC, APHA, 19076, p. 549.
5-2 Ibid., p. 94.
5-3 Ibid. , pp. 516, 517, 519, 521.
5-4 Ibid., p. 554.
5-5 Ibid. , p. 534.
7-1 Troxler, W.L., Parmele, C.S. and Barton, D. A., "Survey of Indus-
trial Applications of Aqueous-Phase ActivatedCarbon Adsorption
for Control of Pollutant Compounds from Manufacture of Organic
Compounds," Enviroscience Corp., Knoxville, TN.
7-2 Knopp, P.V. and Randall, T. L., "Detoxification of Specific Organic
Substances by Wet Oxidation," The 51st Annual Conference of Water
Pollution Control Federation, 1978.
7-3 Eckenfelder, W.W. and McMullen, E. D., "Factors Affecting the
Design and Operation of Activated Sludge Plants Treating Organic
Chemicals Wastewaters," Progress in Water Technology, Vol. 8, 1976.
7-4 Berthouex, P.M., Hunter, W.G., Pallesen, L. and Shih, C.Y., "The
Use of Stochastic Models in the Interpretation of Historical Data
From Sewage Treatment Plants," Water Research, 10, 1976, p.
689-698.
7-5 Sayigh, B.A., "Temperature Effects on the Activated Sludge
Process," Ph.D thesis presented in May 1977, University of Texas at
Austin, TX.
7-6 Del Pino, M.P. and Zirk, W.E., "Temperature Effects on Biological
Treatment of Petrochemical Wastewaters," Environmental Progress,
Vol. 1, No. 2, May 1982.
295
-------
8-1 Eckenfelder, W.W., Water Quality Engineering for Practicing
Engineers, New York, Barnes & Noble, 1970, p. 97, Table 5-16.
8-2 Kovalcik, R.N. , "Single Waste Treatment Vessel Both Flocculates and
Clarifies," Chemical Engineering, Vol. 85, June 19, 1978, pp.
117-120.
8-3 Thibault, G.T. and Tracy, K.D., "Controlling and Monitoring
Activated Sludge Units," Chemical Engineering, vol. 85, September
11, 1978, pp. 155-160.
8-4 Arora, M.L. and Montgomery, J., "Wastewater Treatment in the United
States.
8-5 Kenpling, J.D. and Eng. J., "Performance of Dual-Media Filters2,"
Chemical Engineering Progress, Vol. 76, April 1977.
8-6 op cit, 8-4.
8-7 op cit, 8-4.
Grau, P. and Dohanyos, M., "Kinetics of Substrate Removal by
Activated Sludge." Vod. Hospod., B20.20 (1970) (Czech.).
8-9 Water Pollution Control Federation and American Society of Civil
Engineers, "Wastewater Treatment Plant Design," Manual of Practice
No. 8, Lancaster, PA, Lancaster Press, 1977.
8-10 Metcalf and Eddy, Inc., Wastewater Engineering Treatment Disposal
Reuse, 2nd Edition, New York, McGraw-Hill, 1979.
E-l Computer Assisted Procedure for the Design and Evaluation of
Wastewater Treatment Systems (CAPDET), Office of Water and Waste
Management, U. S. Environmental Protection Agency, Washington, DC,
1980.
E-2 Peters, M.S. and Timmerhaus, K.D., Plant Design and Economics for
Chemical Engineers, 2nd Edition, New York, McGraw-hill, 1968, p.
850.
E-3 Brigham, Eugene F., Fundamentals of Financial Management, Hinsdale,
IL, Dryden Press, 1978. '
E-4 Construction of Municipal Wastewater Treatment Plant: 1973-1977,
Washington, DC, Office of Water Program Operation, 1978.
E-5 Department of the Army, Corps of Engineers, Design of Wastewater
Treatment Facilities, Major Systems, Part 1, Washington, DC, Office
of Chief of Engineers, 1978.
296
-------
OTHER REFERENCES
Scherm, M. and Lawson, C.T., "Activated Carbon Adsorption of
Organic Chemical Manufacturing Wastewaters After Extensive
Biological Treatment," Union Carbide Corp., S. Charleston, WV.
Wise, H.E. and Fahrenthold, P.D., "Predicting Priority Pollutants
From Petrochemical Processes," Environmental Science & Technology,
November, 1981.
Conway, R.A., Hougous, J.C. and Macauley, D.C., "Predicting
Achievable Effluent Quality and Variability in the Organic Chemical
Industry," Progress in Water Technology, Vol. 8, Pergamon Press,
1976.
Campbell, H.J. and Rocheleau, R.F., "Waste Treatment at a Complex
Plastics Manufacturing Plant," Journal WPCF, February 1976.
Ellis, K. V., "The Biological Treatment of Organic Industrial
Wastewaters," Effluent and Water Treatment Journal, May 1979.
Minor, P.S., "Organic Chemical Industry's Wastewaters,"
Environmental Science & Technology, July 1974.
Adams, C.E. and Davis, G.M., "Biological Treatment for World's
Largest Acrylate Plant to Achieve BATEA on Houston Ship Channel,"
30th Annual Purdue Ind. Waste Conference, 1975.
Sachs, E.F, Jennett, J.C. and Rand, M.C., "Anaerobic Treatment of
Synthesized Organic Chemical Pharmaceutical Wastes."
Sidwick, J.M. , "The Treatment of Liquid Waste From the Manufacture
of Organic ChemicalsTwo Case Histories," Prog. Wat. Tech., Vol.
8, 1976.
Housden, A.J., "Operational Experiences in the Effective Treatment
of Effluents from Synthetic Resin Manufacture," Water Pollution
Control, 1981.
Lawson, C.T. and Bryner, B.J., "Wastewater Renovation and Reuse in
an Organic Chemicals PlantA Pilot-Scale Study," Union Carbide
Corp.
Koon, J.H. and Adams, E. E., "Biological and Physical-Chemical
Treatment of Waste From a Diversified Organic Chemical Plant,"
30th Annual Purdue Ind. Waste Conference, 1975.
Chian, E.S.K., Chang, Y. , Dewalle, F.B. and Rose, W.B., "Combined
Treatment of an Organic Chemical Water by Activated Sludge Followed
by Activated Carbon," Perdue Ind. Waste Conf., 1975.
Ford, D.L. and Eckenfelder, W.W., "Design and Economics of Powdered
Activated Carbon in the Activated Sludge Process," Prog. Water
Tech., Vol. 12, 1980.
297
-------
Sidwick, J.M., "The Treatment of an Industrial Effluent From the
Manufacture of Organic Chemicals for Process Reuse," Prog. Water
Tech., Vol. 10, 1978. i
Sittig, M. , Pollution Control in the Organic Chemical Industry
Park Ridge, NJ, Noyes Data Corp., 1974, pp^^^S^
298
-------
APPENDIX A
GENERIC PROCESS CODES WITH FREQUENCY OF OCCURRENCE
-------
FREQUENCY or OCCURRENCE for each PRODUCT PROCESS *
PP_COOE
CN.CODC
or*
7Eป0
UNK
pp-text
0005*01
01
6
IPS RESIN/EMULSION POLYMERIZATION
0005.0*
01
1
ซ
ARS RESIN/MASS POLYMERIZATION
0009*09
01
2
ASS RESIN/SUSPฃN$10N POLYMERIZATION
0005*90
3
3
AflS RESIN/FINTSHINQ PROCESS
0010*90
1
ป
ABS/SAN/FINISHIN* PROCESS
0012*01
z
1
*
ACNAPHTHE*IE/9Y*Pป00UCT OF PROPANE pyrolvsis
0030*02
c
1
ACETALOEHYOE/OXIOATION OF ETHYLENE WITH CUCL2 CATALYST
0030*0*
c
1
ACETALOEHVOe/RY-PROOUCT of acrolein by PROPYLENE onto
0030*07
J1
1
ป
ACETALOEmYOE/CATALTTIC OEHYOROOENATION of etwanol
0070*00
4
*
ACETIC
ACIO/
0070*01
c
*
ACETIC
ACIO/CATALYTie OXIDATION OF butane
0070*04
c
1
2
ACETIC
ACIO/OXIOATION OF ACETALOEHYOE
0070*09
0
2
ACETIC
ACIO/CARbONYLATION of METHANOL WITH CO AND h*
0070*07
z
ACETIC
ACI0/งY*PR00UCT OF P*AMIN0PHEN0L BY ACIO C(.V
0070*08
13
ACETIC
ACIO/BY-PROOUCT OF DIATRIZOIC ACIO
0070*09
0
ACETIC
ACI0/rRANSESTERIFlCATI0N*HETHYLACETArE4F0RMICACI0
0070*1*
01
ACETIC
ACIO/BY-PRODUCT POLYVINYL FORMAL
0070*13
E
1
ACETIC
acid/by*ppoduct of polyvinyl alcoholihydrolysis of polyvinlE acetate)
0070*14
3
ACETIC
ACIO/RECOVERY from POLVOL PROCESS
0070*19
3
*
ซ
ACETIC
ACID/RECOVERY FROM SULFITE PULP WASTEWATER
0070*1*
C
1
ACETIC
ACID/COPROOUCT OF TPA BY 0X1OAT OF ACETALOEHYOE
0075*00
14
acetic
ACIO SALTS/ ACETIC ACIO ~ METaL OXIDE OR HYdRO*IDE
0075*99
24
1
1
ACETIC
ACIO SALTS (TOTAL*/ ACETIC ACID ~ METAL OXIDE (HYDROXIDE)
0080*01
a
2
1
ACETIC
ANHYDRIDE/THERMAL CRACKINo OF ACETIC ACIO
ooao*ot
0
2
1
ACETIC
AซHVOft!DE/FROM ACETIC 9V ACIO kETEnE PROCESS
0090*01
C
ซ
ACETONE/CUMENE PEROXIDATION AN0 acio cleavaoe
0090*03
Ji
4
ACETONE/OEHYDftOBENATlON OF ISOPROPANOL
0090*06
C
ACETONE/VAP0RปPMASE OXIOATION OF RUTANE/PROPANE
0090*11
C
a
ACETONE/BYPRODUCT OF H202 8Y OXIDATION OF ISOPROPANOl
0100*01
z
1
ACETONE cyanohydRIn/rxn of acetone with hydrocyanic ACIO
0110*01
K
1
ฆ
ACETONITRILE/ NHS ~ ACETIC ACIOtDEHVORATION OF ACETAmIDE
0110*02
N
ACET0N1TRILE/BY-PRO0UCT OF ACRYLONITRILE BY AHMOXIOATION OF PROPYLENE
0120*01
C
1
acetophEnone/by*product phenol by cuซene peroxidation and actd cleavaqe
0130*01
02
3
ACET*LENE>PARTIAL 0XI0ATI0N of methane
0130*02
E
ACETYLENE/FRON CALCIUM CARBIDE
0130*03
H
3
ACETylEmE/BYซPROOUCT OF BY PROPANE PYBOLYSIS
0140*01
C
2
ACROLEIN/OXIDAT10N OF PROPYLENE
0150*01
e
I
ACRYLAHIDE/CATALYTIC HYDRATION OF ACRYLONITRILE
0193*01
01
4
3
ACRYLIC LATEX/EMULSION POLYMERIZATION
0159*01
01
2
2
ACRYLIC RESINS/EMULSION POLYMERIZATION
0155*02
01
2
1
achylic pesins/suspension polymerization
0159*03
01
5
3
ACRYLIC RESINS/SOLUTION POLYMERIZATION
0155*06
01
1
2
ACRYLIC resins/rulk polymerization
*Note: Frequency counts reflect only the Summary Data Base which includes 195 Direct Dischargers,
94 Zero Dischargers and 2 unknowns. Product/Processes without frequency counts are from
indirect dischargers.
-------
rRtoutNCv or
PP_CODE 8CN_C00t OIR ZERO UNK
0155-10 01 1 . .
01SS.11 01 1 . .
0155-14 01 1 . .
0155-99 Dl 1 , ,
0156-01 01 2 .
0156*02 Dl 2 . .
0160*03 0 1 .
0160*04 C 1 * *
0160-80 C 2 1,
0165-01 8 3 2 .
0165-0* 0 1 .
0165*05 6 1ซ#
0165-06 0 1 ฆ .
0165-07 0 1 , ,
0165-09 0 1 , ,
0165-10 0 2 .
0165-11 0 1 . ,
0165-12 0 1 .
0165-13 0 1 . .
0165-16 0 1 .
0165-15 0 1 . .
0170-00 * , 1 ,
0170-01 N 3 1.
0175-01 1 . .
0176-01 8 1 . .
0177-01 0 1 .
0179-01 (S 11.
0180-01 C . 1 ,
0100-02 E I .
0180-03 C . 2 .
0180-80 C 1 . .
0185-01 B . 1 .
0185-03 18 1 . .
0185-06 K . 1
0185-05 19 1 , .
0186-01 5 1 .
0189-90 01 1
0189-01 01 5 15 1
0191-01 J2 2 . .
0192-01 PI . 1 .
0192-03 K 1 * .
0192-0* Z 1 . .
0195-01 II 1 .
OCCURRENCE for each PRODUCT PROCESS
PP.TEXT
ACRYLIC RESINS/BULK POLYMERIZATION TO CAST SHEET
ACRYLIC RESINS/EMULSION OR SOLUTION ROLYM, TO COATINGS
ACRYLIC RESINS/POLYACRVLAMIOE BY SOLUTION POLYMERIZATION
ACRYLIC RESINS/PPOCESS IN REVIEW
ACRYLIC FIBER<85* POLYACRYLONJTPILE)/SUSP POLY-WET SPINN
ACRYLIC FIBER (85S POLYACRYLONITRILEISUSP POLY-DRY SPI*N
ACYLIC ACID/FROM ACETYLENEtCARBON MONOXIDE ANO WATER
ACRYLIC ACIO/OXIOATION OF ACROLEIN
ACRYLIC ACID/OXIDATION OF PROPYLENE VIA ACROLEIN
ACRYLIC ACID ESTERS/ACRYLIC ACID ESTERTF OF MISC ALCOHOL
ACปYLIC ACID ESTERS/HYDROXY alkyl acrylate by acrylic AL
ACRYLIC ACID ESTERS/ETHL 2-CYANO ACRLATE FROM FOPMALO.ET
ACRYLIC ACIO ESTERS/MfTHL 2-CYaNO ACRLATE FROM FORMALDปE
ACRYLIC ACIO ESTtRS/AUYL 2-CYaNO ACRLATE FROM FORMALOfE
ACRYLIC ACIO ESTERS/N-BUTYL ACRYLATE-ACRY ACIOซN-BUTANOL
ACRYLIC ACID ESTERS/ETHYL ACRYLATE-ACRY ACIO ~ ETHANOL
ACRYLIC ACID ESTERS/ETHYLHFXYL ACRYLATE-ACRY AClO*fTMHEX
ACRYLIC ACIO ESTERS/ISOBUTYL ACRYLATE-ACRY ACI0ปISOBUTAN
ACRYLIC ACIO ESTERS/ETHYL ACRYLATE-MOOIFIED REPPE PROCFS
ACRYLIC ACIO ESTERS/MfTHV ACRYLATE-MOOIFIED REPPE PROCES
ACRYLIC ACIO ESTERS/BUTYL ACRYLATE-MOOIFIED REPPE PROCES
ACRYLONJTRILf/
acrylonitrile/ppopylene AMMOXIDATION
ADIPIC ACID.0I<2-ETMYLME*YLJESTER/ESTERIF!C of aoipic AC
ADIPIC ACIOtOI-ISQ0ECYL ESTER/FSTERIFICATION OF ADIPIC A
AOIPIC ACIOtOI-TRIOECYL ESTER/ESTERIF JCATION OF AOIPIC A
adipic acio esters/estcrfication OF ADIPIC ACIO
AOIPIC ACIO/OXIOATION OF CYCLOHEXANOL
ADIPIC acio/depolymerization Or nylon 6
AOIPIC ACIO/OXIOATION OF CYCLOHCXAnOL'ONE MIX
ADIPIC ACIO/ OXIDATION OF CYCLOHEXANE VIA OL/ONE
ADIPONITRILE/CHLORINATION ~ CYANATTON OF BUTADIENE
aoiponitrile/ direct hvorocyanation of butadiene
ADIPONITRILE/AMMONOLYSIS OF AOIPIC ACID.OEHYDRaTION of OlAMIOE
ADIPONITRILE/ELECTROHYOROOIMERIZATION of ACRYLONITRILE
ALKOXY ALKANOLS/ ALK0XY ALKAN0LS FROM ALKYLENE OXIDE AN
ALKYD RESINS/
ALKYD RESIN/CONOENSATION POLYMERIZATION
ALKYL PENZfNES/ALKYLATION OF BENZENE *ITH ALPHA-OLEFINS
ALKYL AMINES/HYDROGENATION OF FATTY NJTRILE
ALKYL AMINES/AMINATION OF ALCOHOLS
alkyl amines/c-13-ci9 rROM OLEriM * hcn * h?
alkyl phenols/nqnyl-octyl alkylation or phfnol
-------
FREQUENCY OF OCCURRENCE FOR EACH PROOUCT PROCESS 3
PP.CODE
8EN.C00E
OIR
ZERO
UNK
pp_text
01*5-02
11
2
ALKYL PHENOLS/MIXED ALKVLATION OP PHENOL
0200*01
I
I
ALLVL ALCOHOL/REDOX OF ACROLEIN ANO SECปBUTANOL(REDUCTION BY ALUMINUM BUTOXIOE)
0200*03
1
*LL*L alcohol/hydrolysis or ALLVL CHLORIDE
0210*01
n
ALLYL CHLORIDi/CHLORINATION or PROPYLENE
0230*01
5
AM|N0CTMYLCTHAN0LAMINE/RXN or ETMYLENEDIAMINE ~ ETH.OXJO
0238*05
r
t
PoAMSNOPHENOL/REDuCtION or NItROBENZENEปACIO REARRANGE
02*0*01
8
ANYL ACETaTES/RXN Or ACETIC ACID ft AMYL ALCOHOLS
0900*03
F2
ANILINE/BY-PRODUCT Or P-AMlNOPHENOL
0300*04
F2
ANILINE/NITROBENZENE HY0R06ENATI0N
0320*01
11
t
ANjSlOlNE/MfTHYLATtON ANO REDUCTION
0320*99
4
ANISIOINE/PROCESS UNDER REVIEW
0335*01
2
1
anthracene/coal tar OISTILLATION
0350*99
1
ANTMRAQUINONE/ oxidation or ANTHRACENE
0350*00
3
ASPIRIN/GENERAL
0350*01
3
i
aspirjn/acetylation or salicylic acid
0358*99
1
aspirin/acetylation or salicylic acid
0)60*03
e
1
benzaldehyde/oxidation or TOLUENE
0380*00
M
1
BENZENE/ STEAM PYR0LYS1S Of LPO
0380*01
BCNZENE/HYORODEALKYLIZATION or toluene and/or xylene
y> 0380*02
2
BENZENE/DIST Or BTX EXTRACT.CAT, RErORNATE
' 0380*04
M
ซ
benzene/oist. or rtx extract-coal tar light oil
0380*08
1
benzcne/by-proouct or phenol-m^o by cumene oxidation (recovered raw material)
0380*09
2
BEnZENE/OIST or btx extract-pyrolysis GASOLINE
0380*11
2
1
BENZENE/BY-PRODUCT or SILICONE maNUEACTURE
0380*12
1
BENZENE/BYwRRODUCT or STYRENE BY ETMYLBENZ DEMYOROGENATI
0380*13
1
BENZENE/BY-PRODUCT or ACRYLATE MANUrACTURE (REPPE)
0381*01
2
1
8TXซbENZENEปTOLUENEปXYLENE
-------
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS *
PP.CODE
ฉCN.CODE
DIR
ZERO
UNK
PP.TEXT
0640*01
fl
1
N.BUTYL ALCOHOL/BY PRODUCT OF lt3*BUTYLE"E GLYCOL BY HYO
0640*02
Fl
6
1
N*8UTYt alcohol/hydrogenation OF N*BUTYRAL0EHY0Eป 0X0 PR
06*0-05
12
1
N*BUTVIป ALCOHOL/DISTILLATION of DILUTE AQUEOUS BUTANOL
0650.01
12
3
SEC*0UTVL ALCOHOL/INDIRECT HYDRATION OF 0UTENES
0660.99
12
1
TEซT*8UTYL ALCOHOL/FROM ISOBUTYLENE
0710*01
Fl
2
9
9
1*3 8UTYLENE eLYCOL/MYOROGENATION OF ACETALDOL
0720*01
15
5
9
BUTYLENES/BY EXTRACTIVE OISTlLLATION OF C4 PYROLVZATES
0720-99
15
BUTYLENES/ FROM PYROLYZATE BY EXTRACTIVE DISTILLATION
0730*99
1
9
tert*butylphem>l/ alkylation of phenol with isobutylene
0750*01
0
2
N*BUTYRALOEHYDE/HYDROFORMYLATION of PROPYLENEiOxO PROCES
0760*01
c
1
N.8UTYRIC ACI0/0*10ATION OF BUTYRaLDEHYOE
0760*02
c
n*BUTYRXC ACIO/CO.PROOUCT OF BUTANE OXIDATION
0700*99
6
1
t
N.PUTyRONJTRILE/ BUTANOL NH3, DEHYDRATION
0785*00
*
CAPROLACTAH/
0785*06
2
CAPROLACTAH/FROM PHENOL VIA CYCLOHEXANONE OXIME/
0765*07
2
t
CaPROLACTAM/OEPOLVMERIZATION NYLON 6
0785*09
C
2
CAPROLACTAM/FROM CYCLOHEXAnE VIA CYCLOHEXANONE AND OXIME
0790*99
3
1
CARBON DISULFIDE/PPOCESS UNDER REVIEW
0010*01
e
2
CARBON TETRACHLOPIOE/CHLOHINATION OF METHANE
0010*02
a
3
9
CARBON TETRACHLORIDE/CHLOR, OF METHYL CHLORIDE (FROM HYDROCHLORINATION OF METHANOL)
0010*0}
b
9
CARBON TETRACHLORIDE/CHLORINATION OF CARBON DISULFIDE
0010*04
a
4
9
CAPBON tetrachlorioe/co-production OF tetrachloroethylen
0010*05
H
1
9
CARBON TETRACHL0RIDE/BY*PR0DUCT OF PHOSGENE MANUFACTURE
0016*01
01
9
CARBOXMETHYL CEUULOSE/ETHCPIFICATION of CELLULOSE
0015*00
c
0
CASTOR OIL (INCLU0IN0 USP)/
0015*99
4
CASTOR OIL (INCLUDING USP) PROCESS UNDER REVIEW
0016*01
a
3
f
CELLOPHANE/VISCOSE PROCESS
0020*01
23
5
cellulose ACETATES FIBERS/SPINNING from acetylateo cellu
0020*03
01
5
CELLULOSE ACETATES RESIN/ACETYLATION OF CELLULOSE
0021*01
0
I
CELLULOSE ACETATE/BUTYRATES
0023*01
1
t
CELLULOSE ACETATEI/PROPIONATES/ESTEPIFICATN OF CELLULOSE
0626*01
I
1
t
CELLULOSE NITRATE/NITRATION OF CELLULOSE
0025*01
0
1
9
CELLULOSE SPONGE/VISCOSE PROCESS
0060*99
B
ป
9
CHLOROACETIC ACID/ CHLORINATION OF ACETIC ACID
0090*01
0
2
9
9
CHLOROBENZENE/CHLORINATION OF BENZENE
0090*99
4
9
CHLOROBENZENE/
0921*01
P
1
9
CHLOROOIFLUOROMETHANE/HYDROFLUORINATION OF CHLOROFORM
0030*01
0
3
9
CHLOROFORM/CHLORINaTION of METHYLCHLORIOE (FROM HYOROCHLORINATION OF METHANOL)
0930*02
0
2
9
9
ChLOROFORM/ChLORINaTION OF methane
0930*03
u
CHLOROFOPM/BY*PROOUCT OF CARBON TETRACHLORtQE PRODUCTION
0930*0#
C
1
CHLOROFORM/ BY*PR0OUCT OF ACETALOEHYDE PRODUCTION
0949*01
0
1
i
M*CHL0R0NITR08ENZENE/CHL0RINATI0N OF NITROBENZENE
0950*99
L
O.CHLORONITROBENZENE/ NITRATION OF CHLOROBENZENE
-------
L
B
8
6
6
*
3
H
3
2
H
M
2
2
12
7
3
ft
ft
fZ
c
C
rz
c
ji
02
IS
A
e
8
V
8
P
P
8
B
B
S
8
8
B
20
5
TREOUENCY OP OCCURRENCE E0R EACH PROOUCT PROCESS 5
OJR ZERO UNK PP.TEXT
1 ซ . P-CHUORONITROBENZENE/ NITRATION or CHtOROBfNzENE
i , . 2*cmloปophenol/chlorin*tion nr phenol
i . . a-chlorophenyl phenyl etmer/chlor or phenyl phenyl ether
. . CHOLINE CHLORIDE/ ETHYLENE OKIOE ~ TRIMETHYLAMiNf ซ HCL
1 , , CHOLINE CHLORJDE/ ETHYLENE CHLOROHYORIN ป TRTHETHYL amine
* . CHOLINE CHLORIOE/PROCESS UNOCR review
, , , CHROMIUMCTOTAL)/PROCESS UNDER REVIEW
. 1 . COAL TAR/COKINS or COAL
1 . , COPPER (TOTAL)-PROCESS UNDER REVIEW
2 I . COAL TAP PRODUCTS
-------
FREQUENCY OF OCCURRENCE FOR each PRODUCT PROCESS
PP.COQE
0EN_C0DE
OIR
ZERO
UNK
PPmTfXT
1300-04
5
2
OICTHYLCNt OLYCOL (REFININQ OF DISTIL TAILS! / ETHYLENE GLYCOL ~ E.O
1300-05
E
#
METHYLENE QLYCOL'CO-PROO of HYOROLvS|S -ETHYLENE OMOE
1365-01
6
1
DIETMyLENE TRIAMINE/ETHyLENE OIAMINE ~ EOC ~ NH3
1440-99
0*
1
OllSOdUTYLENE/PROCESS UNDER REVIE"
1442*01
12
1
01IS0PR0PYL BENZENE/RY-PROO of CUHENE
1450*01
A
2
0
OIKETENE/OIMERIZATION of *ETE*E-ACETIC acio
1465.99
5
t
2-OImETHYLAmInOFTHAnOL/ ETHOXYLATION of OIHETHYLAMJHE
1470*01
A
NปNป01METHYLANILINE/CATALYTIC CONDENSATION OF ANILINE
1480-99
A
1
DIMETHYL ETHER/OEHYDRATION OF METHANOL
1490-00
K
1
NปNป0IMETHYL^0RM4MinE/ DIMETHYLAMINE ~ FORMALDEHYDE
1490-99
K
1
N.N-OIMETHYLFORmaMJoE/ OImEThYLAMJNE ~ FORMIC ACIO
1500-99
0
1
DIMETHYL SULFATE/ METHANOL ~ SULFURIC ACID
1510-99
14
1
METHYL SULFIDE/ K METHYL SULFATE *K2S
1530-01
0
5
DIMETHYL TEREPHTHAI.ATE/ESTERIFICATION Or TPA*METHANOL
1530-02
c
2
OIMETHYL TEREPHTHALATE/OXIOATION OF P-XYLFNF METHYL ESTE
1535-99
L
1
0INITR0BEN2ENE(Mป0ปP)/ NJTRATION OP BENZENE
1550*01
L
4
t
OINITROTOLUENE (MIXED)/NITRATION OF TOLUENE
1551-01
L
1
2.4 OINTTROTOLUENE/NJTRATION OF TOLUENE
1552*01
L
1
2t6 OINITROTOLUENE/NITRATION OF toluene
1560-01
4
1
0IPHENYLAMINE/C4TALYTIC CONDENSATION OF ANILINE
1590*99
A
01PHENYL ETHER /CHLORO0ENZENE ~ SODIUM PHENOLATE
1610*01
5
*
01PROPYLENE 0LYCOL/RXN OF PROP. OLYCOL ~ PROPY OXIDE
1610*02
E
oipropylene olycol/co*prod of hyorolysis-propylene oxide
1612-99
A
2ซ2*OITHIOSIS0EnZOTHIAZOLE/ OXIDATION of 2-MERCAPTO0ENZOTRIAZOLE
1634-01
A
OOOECVLOUANIOINE ACETATE/CONDENSATION OF PODECYLAMlNt AC
1635-99
M
i
OOOECYLMERCAPTAN/ DOOECENE ~ H2S
1641*99
L
1
OYCSWyE INtERMEDIAtES/VAt OYESt A20 DYES
1650*01
20
3
EPICHLOROHYDRIN/FROM ALLYL CHLORIDE VTA DICHLOROHYDRIN
1653*01
21
?
EPO*IOIZEO ESTErSปT0TAl/EP0*I0ATI0N of unsaturated ester
1656-00
01
EPOXY RESINS/ EP1CHL0R0HY0RIN ซ 0ISPHENOLA
1656-01
01
3
EPOXY RESiNS/EPiChLOROhYORIN ซ RiSPMENOL A
1656-02
01
I
EPOXY RESINS/FROM P0LY0LS EPICHLOROHYORIN
1656*03
01
1
epoxy reSins/epichlorohydRin and novolak resins
1656-04
0
EPOXV RESINS/EP0XI0AT10N OF POLYMERS
1656*07
01
EPOXY RESINS/PURCHSO EPOXY(EPI-RIS)RESIN * SISPHENOL A
1656*00
01
1
t
EPOXY RESINS/PURCHSO EPXY RESINS.RISPMENOL A.FATTY ACID
1656*09
01
1
EPOXY RESINS/MOOIFIEO EPOXYESTER
1656-10
01
t
EPOXY RESINS/PURCHASEO EPOXY(EPI-RIS)RESIN^QIETHaNOLAMIN
1659-01
H
1
ETHANC/CRACKInO OF NAPHTA
1659*02
2
1
ETHANE / NATURAL OAS BY-PRODUCT
1659*03
3
ETHANE/REFINERY BY-PRODUCT
1660-01
12
3
2
ETHANOL/DIRECT HYDRATION OF ETHYLENE
1660-02
C
1
ethanol/coproouct of butane OXIDATION
-------
rREQUENCY or OCCURRENCE rOR EACH PRODUCT PROCESS
PP.COOE
6EN.C00E
OIR
1661*01
K
*
1664*01
5
4
1666-01
5
2
1666*03
5
2
1670*01
8
1
1670*02
C
1670*03
E
1670*06
4
1
1700*01
K
1
1710*01
12
5
1710*02
H
3
1710*03
I
1
1710*0*
2
1
1730*01
1*
1
1740*01
P
7
1760"ซซ
e
1
1770*01
H
11
1770*02
H
5
1770*03
H
2
1770*06
H
2
> 1770*05
2
1
1000*01
K
2
1810*99
t
1830*01
c
11
1830*02
c
2
1920*99
8
1
1930*01
A
1930*02
5
1
1930*99
5
2
1940*99
8
1
19B0*01
C
11
1960*02
R
1
1985*01
02
8
1995*01
C
1
1995*02
c
2000*01
A
*
2010*99
1*
1
2035*01
02
3
20*0*01
C
11
2040*03
C
7
2050*99
K
1
2060*01
c
2060*02
3
ZERO UNK PRETEXT
ETHANOLAMINCS/AMMfNOLYSIS or ETHYLENE oxide
ETHOXVLATeS/rROM ALKVIFNE OXIOE AND ALKANOL
ETHOXYUATESซ
-------
FREQUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS
ฆ
CO
PP.COOE
8EN_C00C
ฃ070*01
22
2080*00
24
2080*01
2*
2080*99
1
2090*01
12
2090*03
E
2120*99
C
2136*01
M
21A5*01
8
21*5*02
A
2165*03
8
2150*01
8
2165*01
K
2165*02
F1
2165*03
E
2166*99
A
21T0-99
ri
2180*99
A
2181*01
H
2181*02
3
2185*99
3
2190*99
3
2200*01
C
2212*01
5
2215*99
3
2216*01
01
2225*99
A
2260*99
15
2250*01
F1
2250*02
A
2250*03
A
2260*99
0
2265*01
15
2265*02
e
2266*01
02
2270*01
0
2280*01
C
2300*99
0
2320*99
0
2321*99
2
2330*01
A
2360*99
C
2350*02
15
OJR ZERO UNK PRETEXT
fumaric acio/isomerjzation OF MALE1C ACIO
GLUTAMIC ACIO# MONOSOOIUM SALT/
GLUTAMIC ACIO* MONOSOOIUM SALT/SLUTAMie ACIO * NAOH
OLUTAMIC ACIOt MONOSOOIUM SALT/NfUT OF OLUT ACIO BY NAOH
GLYCERINE ปSYNTMETICI/HYDป*OXYLATlON OF ALLYL ALCOHOL
ฎLYCERINEJSYN)/HYoROL OF CPICHLOROHY VI* ALLYL CHLORIOE
LYOXAL/ OZONATION OF BENZENE
HEPTANE/BTX SOLVENT EXTRACTION ANO ADSORPTION
hfxacmlorobcnzene/chlorination OF BEN??"?
HEXACHLORO0ENZENE/8Y PRODUCT OF TETRACHLOROETHYLENE (CHLORINATION OF EOC)
HEXACHLOROBEMZENE/BYvPROOUCT OF CHLOROSILANES
HEXACHLOROETHAnE/ETMANE CHLORINATION
HEXAMCTHYLENEOIAMINE/AMMONOLYS1S OF 1-6 hexaneoiol
MEXAMCTMYLENEOIAMine/HYOROOENATIOW OF ADIPONITRILE
HEXAMETHYLENEOIAMINE/OEROLYMERIZATION OF NVLON 66
MEXYLENE OLYCOL/ ALOOL CINOENSATION OF ACETONE
HEXAMFTHYLENE GLYCOL(1ป6ปMEXANE0I0L)/
hexametmylenetetramine / FORMALDEHYDE ~ NH3
HEXANE/BTX SOLVENT EXTRACTION ANO ADSORPTION
HEXANE / REFINERY by-product
HYDRAZINE SOLUTIONS/PROCESS UNDER REV!EH
HYDROOEN CYANIDE / PROCESS UNDER REVIEW
HYOROQUINONE/OXIDATIOn OF ANILINE VIA OUINONE
HYORO*YETMYL CELLULOSE/ETHOXYLATION of ALKALI CELLULOSE
HYOROXVLAMINE/PROCESS UNOER REVIEW
HYOPOXYPROPYL CELLULOSE/EThERIFTCATION OF CELLULOSE
IMINODIACETIC ACIO/ NH3 * FORMALDEHYDE ~ NACN
isoamylene / extractive distillation OF BTX rซffinate
isobutanol/hyoroo of isobutyraldehyde*oxo process
ISOBUTANOL/FROM ISO.BUTYRALOEHYOE BY ALDOL CONDENSATION
ISOflUTANOL/ CRUDE ISOBUTANOL BY ALDOL CONDENSATION/ HYDR
ISOซUTYL ACETATE/ISOBUTANOL ~ ACETIC ANHYDRIDE
ISOBUTYLENE'EXTRACT FROM C4 PYROLYZATE
isobutylene/oehyoration of purchased tert*butanol
1SOBUTYLENE POLYMERS/POLYMERIZATION OF ISOBUTYLENE
ISOBUTYRALOEHYOE/HYOROFORMYLATION of PROPYLEnEปOXO proce
ISOBUTYRIC ACID/ MR OXIDATION OF ISORUTYRaLDEHYQE
ISOOECANOL/ CARBONYLATION OF OLEFIN OLIGOMERS ~ H2
ISOOCTYL ALCOHOL/CARBONYLATION OF OLEFIN OLISOMERS ~ *2
ISOPENTANE/ DISTILLATION PROM Cซ/C5 HYOPOCARBON MIX
ISOPHOBONE/CATALYTIC OAS PHASE RXN OF ACETONE
ISOPHTHALIC ACIO/ OXIDATION OF M.*YLE*E
ISOPRFNE/EXTRACTIVE OIST C5 PYROLYZATE
-------
FREQUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS
3ป
i
vo
PP.COOE
0EN.COOE
2360*01
12
2360*02
F1
2360*03
12
2370*99
8
2*15*99
3
2420*00
12
2430*01
C
2430*02
C
2441*01
A
2442*99
3
2443*01
01
2450*01
A
2455*99
ft
2460*01
IB
2470*02
2470*03
0
2470*04
2470*05
0
2470*06
0
2470*07
0
2470*06
0
2500*01
0
2500*02
0
2500*03
F1
2500*04
F1
2500*06
F
2500*07
01
2500*09
C
2500*10
I
2530*00
6
2530*01
K
2545*01
P
2555*01
14
2560*00
16
2560*01
P
2560*03
B
2560*05
C
2620*01
B
2620*02
B
2620*03
C
2630*01
A
2631*00
A
2635*01
V
OIR ZERO UW PP.TEXT
1 !SOP*OPANOL/HYDRATIONS OF propylene
ISOPROPANOL/CATALYTIC HYOROGENATION OF ACETONE
i$opropanol/solvent**ater azeotropjc distillation
ISOPROPyL ACETATE/ISOPROPANOL * ACETIC ANMyORTOE
LEAOtTOTAL)/PROCESS UNDER REVIEW
MALIC ACIO/ HYDRATION OF MALE1C ACID
MALEIC ANHYDRIOE/BENZfNf OXIDATION
maleic anhyoride/by*proouct OF PHTHALIC ANHYDRIDE BY Oil
MELAMINE/TRIMERI7ATI0N OF UREA
"ELA^INE CRYSTAL/ CONDENSATION OF UREA
MELAMINE RESINS/POLYCONDFNSATION OF MELAMINE MlTH FORMAL
MESITYL OXIDE/OEHYDRATION OF DIACETONE ALCOHOL
METAN1L1C ACID/ HYOROOENATION OF 3*nITR0BEnKNE SULFONIC ACID
METHACRYLIC ACID/ACETONE CYANOHYORIN PROCESS
METHACปYLIC ACIO ESTERS/BUTYLHETHACRYLATES-ESTERIFIC ofm
METHACRYLIC ACID ESTERS/ETHYL METHACRYLATE BY METHACRT A
METHACRYLIC ACIO ESTERS/*.fTHYL MEXYL METHACRLTE BY MEA
METHACRYLIC ACID ESTERS/HIGHER METHACRYLATES BY HETH ACI
METHACRYLIC ACID ESTER/2-ACET0ACET0XYETHL METHACRLTE FRN
METHACRYLIC ACID ESTER/METHACRYLIC ACID ESTERIFCTN OF NO
METHACRYLIC ACIO CSTERS/RUTYL MfTHACRYLATE BY ACN 1 HEOL
MCTHANOL/H.P, SYNTHESIS FROM NAT OAS VIA SYN QAS
mETHAnOL/L.P. SYTHESIS From NAT 6AS VIA SYN 0AS
METHANOL/HYDROOENATION of carbon MONOXIDE
METHANOL/HYOROOENATION Of BUTYNfOIOL
METHANOL/CATALYTie MYOROOENATION OF ALDEHYDES
METHANOL/BY PRODUCT POLYESTER
METHANOL/BUTANE OXIDATION
HCTHANOL/RY*PRODUCT OF ALKYLOLAMIOES
METHYLAMINES/ METHANOL ~ AMMONIA
METHYLAMINES(TOTAL)/CONDENSATION OF METHANOL AND AMMONIA
methyl BROMiDE/HYDROhALOoENATiON OF methanol
METHYL CELLULOSE/CELLULOSE ~ METHYL CHLORIDE
METHYL CHLORI0E/ probably used as SOLBENT
methyl CHLORIOE/MYOROCHLORINATION OF METHANOL
METHYL CHLORIDE/CMLORINATION OF METHANE
METHYL CHLORIDE /BYPROOUCT OF ETHYLENE OXIOE 19B0*01
METHYLENE CHLORIDE/CHLORINATION OF MET HYLCHLORIDE (FROM HYOROCHLORINATION of METHANOL)
METHYLENE CHLORIDE/CHLORINATION OF METHANE
METHYLENE CHLORIOE/ BY-PRODUCT ETHYENE OXIDE 1960*01
METHYLENE OIANILINE/REACTION OF FORMALDEHYDE ~ANJLJNE
4ป4ปปmeThYLENE0IANILINE/ (mod ANILINE ~ FORMALDEHYDE
METHYLENE D1PHENYL DllSOCYANATE/PHOSOENATlON OF MOA
-------
frequency op occurrence for each product process
10
I
PP.COOE
OEN.COOE
26*0.01
J1
2640*06
C
2640*07
Jl
2640*08
J1
2645*99
0
2650.99
A
2660*01
F1
2669*02
0
2669*03
0
2665*04
H
2680*01
0
2690*01
C
2690*02
J2
2691*01
01
2691*07
0
2691*11
D1
2695*99
6
2701*01
2
2701*02
2
2750*01
0
2756*01
K
2757*01
K
2770*01
L
2770*10
4
2792*00
L
2792*99
4
2793*99
L
2800.01
L
2805*99
C
2824*01
z
2824*02
z
2825*00
4
2825*01
01
2825*02
01
2825*03
01
2825*04
01
2825*05
01
2825*08
01
2825*09
01
2825*10
01
2825*11
01
2825*22
23
2825*90
23
OIR ZERO UNK PP.TEXT
2 METHYL ETHYL KETONE/DEHVORO0ENATION OF SEC.BUTANOL
2 . HETmvl ETHYL KETONE/BY*PROOUCT OF RUTANE oxioation
METHYL ETmYL KETONE/REOO*ปOF acrolein *. SEC-BUTANOL
METHYL ethyl KETONE/ OEHYOROGENATION OF SEC*RUTANOl
METHYL formate/ PORMaloehYDE ~ CAUSTIC (CANNJZaRO)
METHYL ISOBUTYL CAR8IN0L / ALDOL CINOENJATION OF ACETONE
METHYL ISOBUTYL KETONE/MYOROGENATION op MfSITYL OXIOE
METHYL METHACRYLATE/METHANOLYSIS OP ACETONE CYAWJHYORIN
METHYL METHACRYLATE/METHACRYLIC ACIO ~ METHANOL
METHYL METMACRYLATE/POLYMER CRACKING
METHYL SALICYLATE/ESTERIF|CATION OF SALICYLIC ACIO
AซMETHYLSTYRENE/BYปPROO OF ACETONEซ.PHฃNOL BY CUMENE ok id
AlPMAปMfTMYLSTYRENE/r>EMYOROOENATlON OF CUMENE
MOOACRYLIC RESIN/RES!NปPOLYACRYLON!tRILE a comonomer
MOOACYLIC ซESIN/ReSinปPOLYacRYLONiTซILE 4 C0M0N0MER
M00ACRYL1C RESIN/FIBERปP0LYACRYL0N!TRILE 4 COMONOMER
8ซ
-------
PP.COOE
8EN_C0DE
DIR
2031*01
0
6
2831*02
0
2831*05
0
2831*07
0
1
2831*08
0
2832*01
H
2861*01
B
1
2843*01
8
1
28*3*99
B
2850*01
A
3
2853*01
3
2856*01
02
3
2857*01
C
1
2858*01
8
2
2859*01
8
2
2860*01
8
2862*01
8
t
2863*01
8
1
2865*01
8
2
2867*01
8
2868*01
8
2870*01
8
1
2871*01
8
1
2872*01
8
2873*01
8
1
2876-01
8
1
2875*01
8
1
2876*01
8
1
2877*01
8
1
2878*01
8
1
2879*01
0
1
2880*01
8
2883*01
8
2
2886*01
9
2885*01
e
3
2886*01
6
1
2905*01
01
16
2910*02
C
6
2910*03
C
1
2910*05
M
1
2910*08
c
1
2910*09
16
2910*10
16
1
occurrence for each product PROCESS
PRETEXT
OXO ALOEMVDES.ALCOHOLS/MISC AlOEHYOES
0X0 ALOEHYOCSvALCOHOLS/AMvL ALCOHOL
0X0 ALOEHYOeSซALCOHOLS/CnซCl* ALC FROM C10-C-C13 OLEFIN
0X0 ALOEMYOES/ALCOHOLS/NtOPENTANOL FROM IsOBUTYLENE
0X0 ALOEMYOESปALCOmOLS/AMYL ALDEHYDE
-------
3
9
0
0
c
c
M
01
02
01
01
01
01
02
V
V
3
01
01
01
01
01
01
01
01
01
01
01
23
01
01
3
01
02
02
02
02
3
02
02
S
FREQUENCY or OCCURRENCE FOR EACH PRODUCT PROCESS
12
01R ZERO UNK PP_TEXT
RhENOL/BY-RROOUCT OF 01PHENYL OXIDE
R*EN0L/BYปRซ00UCT OF XSOCYANATES (PROM nJTOBENZENE and OINITROTOLUEME PRCURSORS)
phosgene/ chlorine ~ carbon monoxide
PHOSOENE/CHLORINATION OF carbon MONOXIDE
PHOSPHATE ESTHERS/PHOSPHORUS OXYCHLORIOE AND PHENOL/ALC
PHOSPHATE ESTERS /OIPHENYLISOOECVL POCLHPHENOLHSOOEC
PHTHALIC ANHYORIOC/OXIOATION OF N*PHTHปLENE
PHTHALIC ANMYORIOE/OX10 A T jON OF 0ปXYLENf
PITCH TAR RESIDUE/SEP.FROM COAL TAR LIGHT OIL DISTILLATE
POLYCETAL RESINS/PROCESS UNDER REVJE*
poly-alphaปmethyl styrene/process UNDER REVIEW
POLYAHJDES FROM ETHYLENE amines and fatty ACIOS
NYLONS/FROM adipic acid#dietmvlenetriamjneปepichlobomybr
1 . P0LYAMI0ESซALS0 see nylons/from dibasic acio and amines
1 , POLYAMIDES/ DICARBOXYLIC ACIO ~ DIAMINE
1 . POLYBUTENES/ SOLUTION POYHERIZATION OF BUTYLENES
POLYCARRONATES/OENERAL
POLYCARBONATES/PROCESS UNDER REVIEW
POLYESTER/FIBER MELT SPINNING FROM PURCHASEO RESIN
POLYESTER/RESIN BY POLYCONO. FROM 0ซT * 1ป4ซCYCL0WCXAN0L
POLYESTER/RESIN Br POLYCONO. FROM tPA I ETHYLENE OLYCOL
POLYESTER/RESIN BY POLYCONO. FROM PHTHALIC AND ANHYDR.
POLYESTER/RESIN BY POLYCONO* FROM DMT 1 ETHYLENE OLYCOL
POLYESTER/RESIN BY POLYCON, FROM TPA OR OMT 1 ETHYLBLYC.
POLYESTER/RESIN BY POLYCON, FROM DMT AND BUTANEOIOL
POLYESTER/RESIN By POLYCONO. FROM VARIOUS ACIO I ALC.
POLYESTER/FIBER BY melt SPINNING FROM OMT AND It*
POLYESTER/FIBER BY MELT SPINNINO FROM TPA AND ETHY GLYCL
polyester/fiber BY MELT SPINNING FROM OMT ANO ETHY OLYCL
POLYESTER/FIBER BY MfLT SPINNING FROM TPA OR DMT4ETHYGLY
POLYESTER/FIBER BY MELT SPINNING FROM PuRCHASEO RESIN
polyester/fiber
POLYESTER/FILM FROM OMT ANO 1ป* CYCLOHEXANE OIMETHANOL
4 . polyester/finishing PROCESS
. 1 POLYESTER/
9 i . POLYETHYLENE RESINS/SOLUTION POLYMfPjjปTI0N(H0PE)
9 , , polyethylene resin/suspension P0LYMJP*RTICLE FORM)(HOPE)
15 3 . POLYETHYLENE RESInS/migh PRESSURE POLYMERIZATION (LOPE)
2 , , polyethylene resin$/gซs phase polymerization
1 . . POLYETHYLENE/FINISHING process
. , , POLYETHYLENE/PROCESS under REVIEW
2 , . POLYETHYLENE COPOLYMERS/
1 , , POLYOXYETHYLENE BLYCOL/ETHOXVLATION OF ETHYLENE glycol
-------
s
6
01
A
A
*
23
02
3
02
02
3
5
9
01
02
02
02
3
02
01
01
01
3
01
01
t
01
0
01
01
01
01
01
01
01
01
01
ol
02
02
02
3
FREQUENCY Of OCCURRENCE FOR EACH PROOUCT PROCESS
13
01R ZERO UNK PP.TEXr
IT
1
2
polystyrene
POLYSTYRENE
POLYETHYLENE GYCOL/ ETHYLENE oxioe
POLYETHYLENE POLYAMJNes/EThvlENE OMปJNE ~ CDC * nh3
POLYMERIC METHYLENE 01 ANIlINE/REACT ION OP AMI 1 PORMALH
POLYMERIC "ETHYLENE 01PHENYL 01ISOCYANATE/FROM POLY HETH
polymeric methylene oipncnyl oiisocyanate/mfthylene dian
POLYMERIC METHYLENE OIPHENyL 01ISOCYANATE/RXN OF FORM*AN
POLYPROPYLENE /FIBER BY MELT SP1NNINB FROM PURCHAS RESIN
polypropylene/resin by solution polymerization
POLYPROPVLENE/POLYMCR EXTRUSION
POLYPROPYLENE/RESIN BY SUSPENSION POLYMERIZATION
POLYPROPYLENE/OAS PHASE POLYMERIZATION
polypropylcne/finishinb PROCESS
POLYOXYPROPYLENE QYCOL/ REACT OF PROPYLENE 8YC0L ft PROPYLENE OX IDE
POLYOXYPROPYLENE OLYCOL/PROPOXYLATION OF flLYCERINE
POLYSTYRENE ~ COROLVMERS/SUSP POLYMERIZATION wป0 RUBBER
1 COPOLYMERS/BULK POLYMERIZATION WITH RUBBER
~ COPOLYNERS/BULK POLYMERIZATION Wซ0 RUBBER
POLYSTYRENE AND COPOLYMERS/
POLYSTYRENE * copolymers/finishinb PROCESS
POLYSTYRENC.EXPANOEO/ROLYMERIZATION of polystyrene
POLYSULFONC RESINS/FROM sodium bisphenolate
POLYURETHANE RFS1NS/ POL VOLS ~ OUSOCYANATE
POLYURETHANE RESINS/ POLYOL ซ PUSOCYANATES
POLYURETHANE RESINS/COMPOUNDING
POLYVINYL ACET*TE resINS/EMULSION polymerization
POLYVINYL ACETaTE RESINS/SOLUTION POLYMERIZATION
POLYVINYL ALCOHOL/HYDROLYSIS OF POLYVINYL ACETATE
POLYVINYL ALCOHOL/RESIN-SOLUTION POLYM OF VINYL ACETATE, HYDROLYSIS OF POLYMER
POLYVINYL ALCOHOL/RESIN-SOLN POLVMCMEThANOLIOF VjNYLACET
P0LYV1NvLACETATEซACRyL1C COPOLyMERS/LATEX-EMuLSION POLyN
POLYVINYL BUTYRAL/POLWINYL ACETATE ANO SUTYRALDCHYDE
POLYVINYL BUTYRAL/PROCeSS UNOCR REVIEW
POLYVINYL ACETATE fc PVC COPOLYHERS/SUSPEN POLYMERIZATION
ACETATE * PVC COPOLYMgRS/SOLUTlON POIYmeRIZATI
ft PVC COPOLYMERS/EMULSION P0LYMER1ZATI
4 Pve COPOLYMERS/STAPLE FIRER from RES
COPOLYMERS OF POLYVINYL ACETATE/EMULSION POLYMERIZATION
POLYVINYL ACETATE COPOLYMERS/SOLPOLY *ปt vin pyrollioinon
COPOLYMERS OF POLYVINYL ACETATE/COPOLYMER with ETHYLENE
POLYVINYL CHLORIDE/EMULSION POLYMERIZATION
POLYVINYL CHLORIDE/SUSPENSION POLYMERIZATION
POLYVINYL CHLORIOE/BULK POLYMERIZATION
polyvinyl CHLOHIOE/FILH OR FIBER BY CALENDERING
POLYVINYL
POLYVINYL acetate
polyvinyl acetate
-------
PP^COOE
OEN_CODE
DIR
3048-90
3
A
3050-01
0
1
3052-01
D2
1
3033-99
01
1
30*0-01
02
f
3060*99
02
1
3063-01
3
f
3063-02
2
2
3063-03
H
ง
3066-01
C
1
3066-02
c
3066-06
C
3068-01
8
1
3070-01
Fl
2
3090-02
H
10
3090-06
H
5
3090-08
2
1
3090-11
H
2
3100-01
20
1
3110*01
20
1
3110-02
20
1
3111-01
E
3
3120-02
R
3
3139-01
H
3139-03
H
1
3149-01
E
5
3170-01
A
t
3170*99
C
1
3172*01
01
A
3172*02
01
I
3179*01
8
3
3179*02
E
4
3179-03
E
1
3179*0*
E
4
3179*09
E
3179*06
E
2
3181*01
Z
1
3200*99
0
3
3230*01
J2
7
3230*02
2
1
3239*01
02
9
3236*01
01
1
3237*01
02
1
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS
ZERO UNK PPTEXT
POLYVINYL CHLORIOt/flNISHlNO PROCESS
PROP10N*LOEHVDE/HYOROrORMVL*T|OW OF EThYLENE"0*O PROCESS
POLYVINYL CHLORIDE COPOLYMERS/SUSPENSION POLYMERIZATION
POLYVINYL PYRROLIDONC/POLYNERIZATION OP VINYL PYRROLIOONE
POLYV1NYLIOENC CHLORIOE/EMU(.SION POLYMERIZATION
POLYVJNYLIOENC CMIORIOES/PROCESS UNOC* REVIEW
PROPANE/REFINERY BY-PRODUCT
PROPANE/NATURAL OAS BY-PRODUCT
PROPANE/BUTANE PYROLYSIS
PROPIONIC ACID/AIR OXIDATION OP PROPIONALDEMYDE
PROPIONIC ACIO/CO-PROOUCT OF 8UTANE OXIDATION
PROPIONIC ACID/SYaPROOUCT OF NITROPARAPFINS
NPROPYL ACETATE/REACTION OF ACETIC ACIO 4 N-PROPANOL
N-PROPYL ALCOHOL/MYDROflENATlON OF PROPIONALOEHYOE-OXO PR
PROPYLENE/PYROLYSlS OF ETHANE/PROPANE/BUTANE/LPO
PROPYLENE/PYROLYSIS OF naphtha AND or OAS OIL
PROPYLENE/FRACTIONATION OF REFINERY LI8HT ENDS
PROPYLENE/PYROLYSlS of NAPHTHA(PROPANE*rTHANe,BUTANE
PROPYLENE CHLOROHYDRIN/INTERMEDIATE IK CHLOROHYORIN proc
PROPYLENE OICMLORIDE/CHLOROHYORINATION of allyl CHLORIDE
PROPYLENE 0ICHL0RI0E/8YปPDCT OF PROPY OXIDE BY CHLOROHYO
PROPYLENE OLYCOL/HYOROLYSIS OF PROPYLENE OXIOE
PROPYLENE OXIDE/FROM PROPYLENE VIA CMLOROHYDRIN
PVR0LYปIS 6ASOLINE/CRACKINO ETHANE*PROPANEปBUTANEปLPO
PyROLYSIS OASOLINE/CRACKIN0 ETHANE/PROPANE/BUTANC AND NA
RAYON/VISCOSE PROCESS
SALICYLIC ACIO/CARBOXYLATION OF DRY SOOJUM PHENATE
SALICYLIC ACIO/CARBONOXYLATION OF PHE*OLATE
SAN RESIN/SUSPENSION POLYMERIZATION
SAN RESIN/MASS POLYMERIZATION
SILICONES/SILICONE MONOMERS(CHLOROSILANeS) CHLORINATION of SILICON dioxioe
SILICONES/SILICONE FLUIDS (HYDROLYSIS AND CYCLIZATION)
SILICONES/SILICONE RESINS
SILICONES/ SILICONE RUBBERS
SILICONES/ELASTOMER PRODUCTION
SILICONES/ SILICONE SPECIALTIES C8REASE.DISPERS10N AGENT
SOOIUM BFNZOATE/NEUTRALIZATION OF BENZOIC ACID
SODIUM FORMATE/ FORMIC ACIO CAUSTIC
STYRENE/OEWYOR08ENATION OF ETHYLBfNZENE
STYRENE/SEPAPATION FROM PYROLSIS GASOLINE
STYRENE-BUTADIENE RESIN/ EMULSION PROCESS
STYPENE MALEIC ANHYDRIDE RESINS/COPOLTMERIZATION OF STYREN4MAL.ANH.
STYRENE-METHYL HETHACRYLATE COPOLYMERS/SUSPENSION proces
-------
FREQUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS 15
PP_COOE
OEN.COOE
DIR
zero
UNK
PP.TEXT
3291-01
M
t
SUtrANJLIC ACXO/SUIFONATXON or ANILINE
3260*99
16
1
ง
sulfolane/ butane ~ sulfur
3280*01
C
6
TCHCPHTHALJC ACIO/CATALVTIC oxioation OF P.XYLENE
3280*03
E
1
TCRCPWTMALIC ACIO/MYOROLVSIS OF OIMCTHYL TEปC*MTMALATe
3286*01
8
1
1234ปTETRACHlOROBENZEnE/BYปPRODUCT BENZENE CHLORINATION
3287*01
B
1
124SปTETRACHLOROBENzENE/BYปPRODUCT BENZENE CHLORINATION
3288*01
n
1
]f35ปTETRACMLOROaENZEซE/8V-RRODUCT BENZENE CHLORINATION
32*1-01
e
1
t
lปlป2t2ปTETRACHL0R0ETHANE/CML0PT*ATI0N OF ETHYLENE
3295*01
s
TETRACHIOROETHYIENE/ OXYCHLORINaTION or HYDROCARBONS
3295*02
8
5
i
TETRACHLOROETHYlENE/CHlORINATION or EDC I OTHER CHLOR HC
3295*0*
8
2
TETRACHtOROETHYLENE/CHlORINATION or HYDROCARBONS
3300*01
8
1
t
TETRACHtORORHTHALIC ANhYDRJDe/CmLORINATN or RmTHALIC ANHYDRIDE
3307*01
6
TETRAETHYLENE RENTANINE/ETHYLENE DIAMINE ~ EOC ~ NH3
3310*01
12
4
TETRAETHYL LEAO/ALKYL HALIDE ~ S00!UM*LEAD ALLOY
3312*01
P
i
t
TETRArtUOROOICHLOROETHANE/HVOPOrtUORIN or TETRACMLOROETHYLENE
3315*99
F1
i
TETRAHYOROrURAN/ HYOROOENATION OF CALCIC ANHYDRIDE
3325*01
5
i
TETRAETHYLtNE GlYCOL/COPDCT or ETHY GLYCOL PRO* ETHYLENE
3325*02
5
TETRAETHYLENE GLYCOL/rROM ETHYLENE GLYCOL STILL BOTTOHS
3336*01
It
3
TETRAHETHVL LEAO/ALKVL haLIDE ~ SOOIUH-LEAD ALLOY
3349*00
H
1
TOtUENE/ STEAM PYR0LYS1S Of LP6
3349*01
2
3
TOLUENE/DIST OF GTX fXTRACT*CAT REFORMATS
3349*02
2
TOLUENE/DIST, OF BTX EXTRACTปCO*l TAR LIGHT OIL
3349*04
J2
4
i
toluene/by-proouctof styrene HFG
3349*07
2
*
i
TOLUENE/DIST OF 0TX E*TปPYR0LYSIS GASOLINE
3390*01
A
2*4ฎTOLUENE DIAMINE/CATALYT1C HYDROOENATION OP OINITROTOLUE^E
3391-01
*2
1
TOLUENE 01AMINE fMJXTURE)/CATALYTIC HYDROOENATION OF DINITROTOLUENE
3394-01
V
3
2#4ซtoluene oiisocyamate/phosgenatn of zป4ปtoluene diami
3395*01
V
4
TOLUENE DIISOCYANATES(MIXTURE)/PHOSGfNATION OF TOLUOIAHS
3360-99
6
toluenesulfonamioe/ toluene sulfonylchloride *nh3
3380-99
M
TOLUENESULPONYL CHLORIOE/ TOLUENE SULPONIC ACID ~ CHLOROSULFONIC ACID
3381*01
F2
1
9
TOLUIDINES/CATALYTIC REOUCTION OF O-NITROTOLUENE
3390-01
B
1
9
TRICHL0R0REn2ENE/BYปPR00UCT of BENZENE CHLORINATION
3392-01
8
1
123ฎTRICHL0R0BCNZEN/BY*PR00UCT OF BENZENE CHLORINATION
3393-00
4
ซ
iซ2*4ซTRXCHL0R0GENZENE/
3393-01
B
1
i92*4*TRICHLOROBENZENE/CHLORINATtON OF 1ซ4*DICHL0R06ENZซ
3393*02
8
%
i?4*trichlorobenzene/byproouct of benzene cwlorination
3394-01
8
1
13SซTRlCHL0R0BtNZENE/RYปPR00UCT OF BENZENE CHLORINATION
3395*01
8
1
1ซ1ซ1 TR1CHL0R0ETHANE/ CHLORINATION OP ETHYLENE OieHLORD
3395*03
8
1
ltltl*TRICHLOETHANE/CHLORlNATION OF ETHANE
3395-04
P
1
Itltl-TRICNLOROETHANE/HYDROCHLORINATION OF VlNyL CHLORIDE
3400*01
P
2
ltlt2ปTRlCHLOROETHANE/CHLORINATlON OF VINYL CHLORIDE
3400*02
8
ง
iซi*?ปtrichloroethanc/chlorination OF ethylene dichlorid
3400*03
9
ฆ
ltl*2-TปICHL0R0ETHANE/BYR0CT# OF VINyL CHLORIDE HANUFACT
-------
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS
pp.cooe
tN.COOE
DIP
ZERO
UNK
PP_TEXT
3*10-02
S
TPICHLOROCTHYLENC/QKYCMLOPINATION OF HYDROCARBONS
3410*03
ft
2
TOlCwL0*0ETHYLCN:/CHtOซ,0r ZOC AND OTHER CHLORINATED HC
3411*01
P
*
1
TPlCMLOROfLUOROMETHANC/FLUORINATlON Or CARBON TETRACHLOP
3415*01
R
1
2t*t6ซTffICHLOROPMENOl/CMLOR|NATlOM Or PHENOL
3*30-01
P
1
lปlซ2ปTR!CHLOROปl*2ซ2*TRlFLUOPOtTHANr/COPROO OF 3312*01
3460*00
5
1
triethylene glycol/ethylene glycol ~ E.O.
3*60*01
5
1
TPIETMYLENE GLYC0L/C0PR90F ETHYLENE glycol from eth 0*0.
3*60-02
E
TPICTHYLENE GLYC0L/C0PR6D or HYOPOLYSIS-ETMYLCNE OXIDE
3460*03
5
1
TPJETHYLENC GLYCOL/rROM ETHYLENE GLYCOL STILL BOTTOMS
3*75-01
K
1
TPIETHYLCNETETfrAMlNE/AMjNATION or ethylene dicnlorioe
3*77*01
P
1
TRirLUOPOOlCHLOROETHANE/HYDPOrLUOPINAT Or TETRACHLOROETHYLENE
3497*01
5
1
TPJPPOPYLENE GLYCOL/PXN or PPOPY GLvCOL ~ PPOPY oxIDE
3488*00
A
1
2v2t*ปTPI"tTHYLปlซ3ซPENTANE010L/ ALGOL CONDENSATION ISOBUTyPALOEHYDE
3500*99
3
2
UREA/ NH3 ~ C02
3501-00
0
UNSATURATED POLYESTER RESINS/
3501*01
01
12
UNSATURATED POLYESTER PESIN/REACT MALEIC/PHTHALIC/GLYCOL
3503*99
01
ง
1
uretmane prepolvmers/process under review
3506-00
02
UREA PESINS/GENEBAL
3506*01
01
13
22
UPEA PESINS/POLYCONOENSATION Of UREA WITH rORMALDEHYDE
3510*01
0
1
1
VINYL ACETATE/L10UI0 PHASE ETHYLENE I ACETIC ACID
3510*03
13
ซ
1
VINYL ACETATE/ACETYLENE ~ ACETIC ACID
3510-05
G
1
2
VINYL ACETATE/VAPOP PHASE R* Or ETHYLENE fc ACETIC ACID
3520-03
R
6
1
vinyl CHLORIDE/THERMAL cracking or ETHYLENE DICHLORIDE
3520-80
R
2
VINYL CHLORlDE/rPOH ETHYLENE VIA EOC RY CHLOR-OXY CHLOP
3530*02
R
2
0
VINYLIDENE CHLORlDE/DEHYDPOCHLORi OF TPICHLOPOETHANE
35*0-01
02
VINYL TOLUENE/POLYMERIZATION
35*1*01
17
2
xylenesปmixed/bottom btx extซpyrolysis gasoline
3541*03
17
2
XYLENESฎMlXEO/BOTTOM BTX EXTRACT-CAT REFORMATS
3S*1*0*
H
xylenesซmixeo/bottom btx extractซcoal tap light OIL
35*1*08
17
1
XYLENESiMIXED/MfPfปXYLENES**งOTTOMS XYLENE SEPARATION
3541*09
Z
XYLENESfMiXED/CRUOE PปXYLENE BY ISOMfRIZATION or C8ซS
3550*02
2
M.XVLENE <1MPURE)/rPACTI0NATION Or MIXEO XYLENES
3560-01
2
3
O-XYLENE/OISTILLATION rROM MIXED xylene
3570-01
17
1
PปXYLENE/CPYSTAL12ATI0N rPOM MIXEO XYLENE
3570-02
17
2
ฆ
PปXYLENE/lSOMEPlZATปCRYSTALLIZAT or MIXED XYLENES
3570*05
2
2
0
MIXED XYLENES/ FROM BTX EXTRACT
3580-01
H
XYLENOLtMIXED/TAR ACID RECOVERY AND REFINING
3507-00
M
1
0
XYLEปESULFONIC ACIOi SODIUM SALT/
3587-99
M
2
0
xylenesuleonic acid, sodium salt/ sulfonation op xylene
3600-99
3
0
ZINCITOTAD/PROCESS under REVIEW
9601-00
3
AMMONIUM CHLORIDE/
9601-01
3
AMMONIUM BICARBONATE/
9603-00
M
1
CYCLOHEXYL MERCAPTAN/ OODECENCNE ~ H2S
-------
PP_COOE
8EN.COOE
01
960#*01
16
MtHOt
M
*608*01
M
U1MI
M
9615*00
616*00
01
*616*01
3
*619*00
3
*619*01
3
9619*02
3
9619*03
3
9619*06
E
9619*OS
3
9626*00
4
3>
9001*01
t
ROI*02
3
ป~J
9801*04
M
9801*0f
01
9801*06
9801*09
16
9801-11
6
9801-lt
9801*13
2
9801*16
6
9801*1S
6
9801*16
01
9801*18
5
9801*19
6
9801-21
9801*23
9801*26
M
9801*25
6
9801*26
I
9801-2T
3
oift
ZERO
FREOUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS
UNK pr_te*t
OH SO* RAYON 0RAOE/
2ป6*0IMETHYL PHENOL/ EXTRACTION* DISTILLATION OF REFINERY SPENT CRESYLATES
NwHFIADECYL RERCAPTAN/ OLEFIN *H2S
N-ME*YL MERCAPTAN/ OLEFIN ~ MfS
OaLIHONCNE OINERCAPTAN/ OLEFIN ซ H2S
p*tert*octyl Phenol/
POLYAHIDE RESINS/
PHOSPHORIC acio/
SOOIUM NITRATE/
SODIUH BICARBONATE/
SOOIUN HVDROSULFIOE/
sodium solFI"E/
SOOIUM SULFATE/RFCOVERV AS PART OF VISCOSE PROCESS
SOOIUM TETRASULFIOE/
ZCREH8A/
ACETYLENICS/ STEAN PYROLYSTS
AOปICULTURE CHENICALS/
aromatic CONCENTRATE/ STEAM PYROLYSIS OF CRUDE OIL CUTS* OR LP8
ACRYLAHIOE RESINS/
SLYCOLS* MIKED/ OLEFIN OLIOOMCRS ~ 0*0 HY0R09ENATI0N
AROMATIC SOLVENTS/ 8TX EXTRACTION FROM PYROLYSIS 8AS0LINE
ANTIOXIDANTS/
ASPHALT/REFINERY PRODUCT
alirhatic solvents/ oistillation from PYROLYSIS OaSOLINE
ACCELERATORS(Trade NAME)/ MERCAPTOBENZOTHIAZOLES
ANTIOZONANTS/
ACETAL RESIN (CELCON)/
MISCELLANEOUS ALKOXYLATES/
MISCELLANEOUS AMIDES/ FATTY ACIOS ~ ALKANOLAMiNES
ANT I KNOCK BLENOS/ LEAH ALKyLS* ETHYLENE OICHLORIOE
AROMnTIC TaR/ STEAN PYROLYSIS RESIOUปLS
AROMATIC DISTILLATES/ BTX
AMINES /METHANOL ~ NM3
ALUMINUM ALKYLS/ OLEFIN ~ ALUMINUM ~ HYOROOEN
AOHESIVfS/
IT
-------
FREQUENCY OF OCCURRENCE FOR EACH PROOUCT PROCESS
IB
PP.COOg QEN^COOE OIB ZERO UN* PRETEXT
9901*29
9801-30
9001*31
9001-J*
9001-35
9001*36
9801*40
9001**2
9001*43
9001*47
9001*48
9001*49
9001-51
9001*53
9001*58
9002*04
9002*05
9002-11
9002-12
9002-13
9002-14
9002-15
9002-17
9002*18
9002-21
9002-22
9002-23
9002*24
9002*36
9002-37
9002-30
9002-39
9003-02
9003-04
9003-05
9803*06
9003-11
9003-13
9003-14
9803*15
9003*16
9003*17
9003*10
1
R
0
0
6
3
MISC. ALKANES/
ALKENYL SUCCINIC ANHY0ซlDES/
#LK*TERGE(TRA0E N*mF)/ ETHQXYlATION OF ALKYL PHENOL
amantadine hydrochloride/
AlKYD MOLDINO COMPOUND (TRADE NAME)/
ALPHA 041 PRODUCTS I TRADE NAME)/
AMINO ALCOHOLS/ ALOOL CONDENSATION OF NITROPARAFFINS WJTh FORMaLOEHYOEi REDUCTION
ACRVLONITRILE CATALYST/ BISMUTH PHOSPHOMOLVBDATEซ S0-U2O7-SILICA GEL
ALKYLOLAMIOES/ FATTY ACIOS ALKANOLAMIweS
ANTI0IOTICS/
ACETONE FORMALDEHYDE REStNS/
ADOITIVES MISCELLANEOUS/
ALKYL VIMYL ETHERS/ ACETYLENE ~ ALCOHOL
AME* (TRAOE Name)/
ACETYL P.AMINOPHENOL IP*MYDR0XYACETAN|LI0E) / NITRATION, HYOROOENATION ACETYHTION OF PHENOL
n-butyl formccl/ SOLUTION OF forhaldehyoe IN butanol
BUnkER C fuel/
ปROHACIL*DIURON COMPLEX (HERBICIDE)/
ROMACIL(HERBICIDE)/
0ENOMYL/
benlate/
BIS*PAR**AMtNOCYCLOHEXYL*HETHANE/ ANILINE ~ FORMALDEHYOEป HYOROOENATION
BACITRACIN PRODUCTS/
butyl lactate/ butanol ~ lactic acio
N*BUTYL MERCAPTan/ OLEFIN ~ H2S
SEC*BUTYL MERCAPTAN/ OLEFIN ~ H2S
T-BUTYL MERCAPTAN/ OLEFIN H2S
bare* RESIN (POLYACRYLONITRILE BARRIER RESIN)
BUTYNEDIOL/ ACETIYLENE ~ FOrMALOCMYDE
1i4 0UTANEOIOL/ CONDENSATION ACETYLENE WITH FORMALDEHYDE* FOLLOWED BY HYOROOENATION
3-BUTYRDL*CT0nE/ OEHYDROOENATION OF 1*4*BUTANEDI0L (COPPER CAT)
2-BUTENE*l,4*DI0L/ HYOROOENATION OF BUTYNEDIOL
CELLULOSE BASEO OR0ANIC
-------
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS )9
PP.COOE
0EN_COOC
OIR
ZERO
unk
PP.TEXT
9803*19
6
CHOLINE BICAR0ONATE/ CHOLINE * SODIUM BICARBONATE
9I0S*ป
1
chlorinated WAX/
9S0IซZ5
3
COATINGS/
9803*26
3
CALCIUH PROPIONATE/
9003*27
A
CHCLATINO AGENTS/ EOTA ETHYLENE01AMJNE ~ FORHALDEHYOE N*CN
9803*28
cleaning compounos/ vegetable oil sulfonates* ethoxylates. ouats
9803-39
fi
croton OIL ALCOHOL/ HYOROGENATION of CROTONALOEHYOE
9103*42
15
C*5 UNSATURATES/ from PYROLYZaTE by EXTRACTIVE DISTILLATION
9803-49
14
CHEMICAL COTTON/ CELLULOSE ~ ETHYLENE CHLOROHvORIN
9003*46
8
1
CORPENT/ PENTAERYThRITOL oerivative
9903*53
3
t
COAL ash/
9004*02
6
1
01AMINO DIPHENYL METHANE/ ANILINE FORMALOEHYOE
9004*04
6
NปN*DIIS0PR0PYL*2 BENZOTHIAZOLE/OUSOPROPYL amine ~ 2*MERCAPTO0ENZOTHIAZOLE
9004*06
4
DISTILLATE* LI0HT*N*BUTANE DEHVDRO./RECOV.
9004*00
3
t
DIESEL fuel/
9004*10
3
1
OIUROMTRAOE NAME)/
9004*12
K
1
OIHETHVLACETAMIDE/ OIHETHYLAMINE ~ ACETIC ACID
9004*13
A
ฆ
ง
OlMgR ACIDS/ FROM PINE ROSIN
9804*14
6
DIAMINES/
t
9004*15
1
DIETHYL ANILINE/ ANILINE * ETHANOL ~ H2S04
vo
9004*17
*
1
OACA/
9004*19
13
OIATPIZOIC ACIO/
9904*20
1
OIETHYL M4L0NATE/ ETHANOL ESTER OF MaLONIC ACID
9004*21
1
DIMETHYL MALONATE/ METHANOL ESTER OF MALONIC ACID
9004*22
12
OENATUREO ALCOHOL/
9004*24
1
DYEING ASSISTANTS/ POLYESTERS
9004*25
K
ง
1
DETERGENTS AND SCOURS/ VEGETABLE OIL SULFONATESป ETHOKYLATES. OUATS
9004*27
01
1
OIALLYLPHTHALATE MOLDING COMPOUNO/
9004*29
M
1
N*OECYL MERCAPTAN/ OLEFIN H2S
9004*30
M
1
f
N*TRI*DECYL MERCAPTAN/ OLEFIN ซ H*S
9004*31
24
DISODIUMETHYLENEDIAMINETETRAACETATE/ NEUTRALIZATION of EOTA
9004*36
M
1
OICHLOPODIPHENYL SULF0NE/S03 *THIONYL CL * CHLOROBENZENe
9004*47
9
1
DIMETHYLRENZYL ALCOHOL/ ACIO CLEAVAGE OF CUMENE HYDROPEROXIDE
9004*40
01
1
#
DICYANOOIAMJNE RESIN/
9004*49
M
DODECYLBENZENE SULFONIC ACID SALTS/ SULFONaTION OF OOOCC^LBENZENE
9004*52
OIBUTYLPHENYL PHOSPHATE/ 0UTANOL ~ PHENOL ~ POCL3
9004*53
6
2*6*OieTHYL-N*tMETHOXYMETMYL)-2*CHLOROซCETANILIDE/
9004*54
6
2ป6*OIETHYLPHENYL AZOMETHANE/
9004*57
1
DINONENE/ FROM TERPINENE BY DEALKYLATION
9804*58
5
1
OIETHANOL AMMONIUM LAUPYL SULFATE/ LAUPYLAMINE ~ ETHYLENE OXIDE
9805*03
6
N.ETHYL ANILINE/ ETHANOL ~ ANILINE
9805*04
4
?*ETMYL HEXYL CHLORIOE/
9005*05
ft
2
MISCELLANEOUS ESTERS (POSSIBLY ADIPATESI / AOIPIC ACIO 2-ETHYLHEXANOL
-------
FREQUENCY Or OCCURRENCE FOR EACH PROOUCT PROCESS
PP.COOE
GENCOOe
OIR
ZERO
IJNK
PP_TE*T
ซ80%ปoa
01
1
EASTOBONDS (TRADE NAME)/ POYSTYRENES ANO CELLULOSICS (A0HES1VES rOR POLYOLEFlNS)
9805ซ09
24
ETHYLENEDIAMINE DIHVDROIOOIDE/ HI ~ ETHYLENEDIAMINE
9805-12
D1
1
t
t
elastomer late*/
9805-14
01
EMULSION POLYMERS/
9805*17
M
1
ETHYL meRCAPTAN/ OLEFIN ~ H2S
9005-18
14
1
DIaETHYL SULFIDE/ K ETMVLSULFATE ~ K2S (AQ)
9805*19
A
t
EYHYLENEOIAMINETETRAACETIC ACID/ ETHYLENEDIAMINE ~ FORMALDEHYDE ~ nacn
9805*22
5
1
MONOEtHVL SLYCOL ether/
9805*29
18
ETHYLENE cyanohyorin/ ACETALDEHYDE ~ HCN
9805*31
A
1
ETHYLENE urea/ ETHYLENE diamine ~ C02
9805*36
01
ALKY0ซPHEN0LICป POLYESTER* POLYURETHANE RESINS
9808*01
3
t
FUEL OAS H2 and CH4 (MFO)/
9806*02
4
t
FUEL ADDITIVES/
9806*03
3
t
FLOUR ADDITIVES/
9806*04
E
1
fatty ACIDS 4 derivatives/ hyorolysis of olycerides
9806*05
0
FATTY NITPILES/ DEHYDRATION OF FATTY AMIDES
*806*06
3
NUMBER 2 FUEL OIL/
9806*08
P
1
FQEON (OENERALI/HYOROFLUORINATION
9806*09
01
FLEXTAL/ ALKYO RESINS
9806*11
P
1
FLUOROCARBON BLENDS/ HF ~ CHLORINATED METHANE
9806*12
3
FURAZOLIDONE/ REOUCTION OF NITROFURANTOIN
9806*13
4
t
FLOWCO FAMILY/
9806*14
01
FURFURAL RESIN (INC. FURAN)/
9806*15
01
FOAM RESINS (POLYURETHANES)
9806*17
01
1
9
fome*cor/
9806*19
3
1
FUNGICIDE AND INSECTICIDE/
9807*01
4
$
0
8ENEROL 100 EXTRACTION/
9807*02
3
*
t
0ENER0L 105 FLAKING/
9807*04
7
1
01YC0L0NITRILE/ ETHYLENE CHLOROHYDRIN ~ N*CN
9807*06
3
3
oasoline/
9807*07
1*
t
GASOLINE BLEND STOCK/ FROM PYROLYZATE BY EXTRACTIVE OISTIILATION
9807*08
01
1
0ANTRE2 AN/ POLYMERIZATION Or VINYL ETHER AND ACRYLONITRILE
9807*09
0
1
OANTREZ ES/CSTERiriCATlON PROPAGYL ALCOHOL ซ ACID
9807*12
02
1
POLYMfR gasoline/by-product isobutylene
9807*13
5
1
OVCOLS(HISCt)/ ALCHOHOL* glycol ~ ETHYLENE OXIDE
9808*02
6
HEXAMETHYLENEDIAMINE / 1)6 * HEXANEOIOL ~ AMMONIA (NICKLE CAT,)
9808*05
3
1
t
HYDROGEN SULFIDE/
9808*08
12
1
hvdROXVACCTIC ACID/ CHLOROACETIC ACIO ~ CAUSTIC
9808*09
02
1
m
HYPOLON(TPAOE NAME)/ CHLOROSULrONATEO POLYETHYLENE RUBBER
9808*10
02
1
HYOAN (TRADE NAME)/
9808*11
E
t
hydrolyzeo vegetable protein/
9808*12
3
HLR/
9808-16
0
hydroxy stearic acid and DERIVATIVES/
-------
imr*
3
3
H
*
A
01
1
0
V
f\
3
3
01
01
01
3
3
3
A
3
3
01
10
a
2*
2*
A
12
3
2
3
3
A
3
3
01
01
0
1*
FREQUENCY OF OCCURRENCE FOR EACH PROOUCT PROCESS
21
01* ZERO UN* PP..TEXT
, I . MYOROXYLAMMONJUM ACIO SULFATE/
, 1 , MYDROXYLAMMONIUM sulfate/
f . LIGHT HYDROCARBONS/
1 HYOROTROPE/ SULF0NAT10N OF ALKYL BENZENES (ALKYiMCTHYt ETHYL*ISOPROPYL)
1 ISOPROPYL ETHYTHIONO CARBAMATE/ ALPHAปMฃthYL PROPIONaMIOE ~ SODIUM ETHVLMERCATIOE
1 . .ION EXCHANGE RESINS IPROSABLY ACRYLIC RESINS)
TSOMERASE/
a I t ISOPHTHALATC ESTER/CSTERIFICATION
2 MISCELLANEOUS ISOCYANATES/ PHOSBENTATION OF AN|LINEป*ORMALDEMYDE OERIV.
11 IS0BUTYR0NITR1LE/ FROM ALPMAซMETHACRYLONITRILE BY HY0R06ENATI0N
. .JET FUEL jp-*/
KETONE PEROXIDE (DIACETONE ALCOHOL PEROXIOE) / PEROXIDATION OF 01ACETONE ALCOHOL
. KEROSENE/
, . KETONE RESINS/
1 KEVLAR (ARAMIO RESIN ANO FI0ERI/1SOPMTHALOYL CHLORIDE ~ 1.3*01ANILINE (TYPICAL) AN APOMATIC NYLON
LAMINATING RESINS/ CRESYL1C ACI0*PhEN0L ~ FORMALOEHYOE
1 . LINURON(HERBICIOE)/
. LOROX/
1 . L ACQtlER (BENERAL) /
1 LAUROYL SARCOSINATE (30 PERCENT SODIUM SALT)/ SARCOSINE * L*URALDEHyDE
. LUBRICANTS / ORGANIC PERIOXJOES* PEROXYCARBONATESt ETC
1 LUPERSOL (TRAOE NAME) / OROANJC PERlOXlOESt PEROXYCARBONATESt ETC
1 ฆ LUPERCO (TRADE NAME) / ORGANIC PERlOXlOESt PEROXYCARBONATESt ETC
1 LUPEROX (TRADE NAmE)/
1 LIBHT OILS/
1 LATE*(UNKNOWN TYPE)/ POLYVINYLACETaTE
. METHYLETHYL KETOXIME/METMYLETHYL KETONE ~ HYOROXVLAMINE .(NH20H)2ซH2S0Aซ
. 1 -ALEIC ACIO ESTERS/ESTERIFICATION
, . ป 2ซmERCAPT0BEnZ0THIA70lC* ZXnC SAi T/ ZInC 0*IOE 2ปmERCAPTBEnZ0THIAZOlE
. .2 MERCAPT09ENZ0TMIAZOLE* SOOIUm SALT/ CAUSTIC ~ ?ปMERC*PT8ENZ0TMIAZOLE
, , , 2(21 METhYLENEBIS(6ปT-BUTYLป**EhTYLPhEN0LI/ A*EThVL*6*TซBUTVYLPhEN0L FORMALDEHYDE
1 ป . METHYL FORMCEL/ SOLUTION OF FORMALOEHYOE in methanol
. ป MOTOR GASOLINE/
1 MIXED C* COMPOUNDS/ DISTILLATION FROM BTX RAFFINATE
| , , MOTOR MIX 1/
1 . MOTOR MIX/
1 1 . METHYL MERCAPTAN/ METHYL CHLORIDE ~ SOOIOM HYOROSULFIOE
1 , . meTnOMYL/
1 ป MAKES (FUNGICIDE)/
, 2 MOLOINB COMPOUNOS/ (POLYACRYLIC RESINS)
1 * . MISC.PLASTIC RES1nS*SHAPES>CHEmICA|,/
1 . METHYL CYANOACETATE/ METHANOL ESTER OF CYANOACETIC ACIO
I . . METHYL ORThOFORMATE/ CHLOROFORM * NAMETHANOLATE
-------
frequency of occurence for each product process
0
t
N
7
Z
P
P
T
0
D
c
u
E
0
I
R
N
X
E
R
0
K
T
6
MORPHOLINE DERIVATIVES OF NITRO ALCOHOLS/
ox
1
MICป0THENE CPOwDEAtD RLOYETHYLENE RESIN)
2
1
METHANE/
8
ฆ
1
CASTOR OIL DERIVATIVES/
8
ฆ
1
TRIMELLITATE ESTER/ESTERIFICATION
A
1
NซMETHYL GLYCINE (SARCOSINE) / METHYLAMINE ~ FORMALDEHYDE * NACN
a
1
MALEANHeo ฐ1L/ ฐ1L ~ *ALEIC ANnYdRIOE
e
1
t
TEXANOL BENZOATE/ ESTERIFICATION OF BENZOIC ACID
8
1
METMOXYEThYL CARBAMATE/ 2-METH0XYETHAN0L ~ CARBAMOYL CHLORIDE (HCL*UREA)
8
1
MAiEATED OILS/ MALEIC ANMDRIORIOE ~ OILS WITH hyoro*yl groups
6
1
NปMCTHYL-2*-PYRR0LI00NE/ 3ปBUTYR0LACT0NE ~ MCTHYLAMINC
A
METHYL AMYL ALCOHOL/ ALOOL CONDENSATION OF ACETONE
3
1
METALLIC CARBONYLS IMISC.)/
A
MeTHYLENCBlS<6ปT*RUTYL^PซCRES0L)/
A
1
METHOXY DIHYORORYRAN/
A
1
nitrrotriacetate/ whs ~ formaldehyde ~ nac*
1*
1
NAPHTHA OXIDE OILS/ SODIUM PHENOLATE * CHLOROREnZENE
A
4tNlTR0ซ0RTH0ซiXYLENE DIETHYL KETONE BLEW)/ Mix OF Z RR00UCTS
01
1
PARAFORMALDEHYDE/ POLYMERIZATION OF FORMALDEHYDE (ALOOL* CANNIZARO)
02
1
NOROEL (TRADE NAME)/ETHYLENE PROPYLENE COPOLYMERS
3
1
nylon yarn/from purchased *csin
L
1
S^NIToO.O.TOLUENE SULFONIC ACIO/ SULFONATION OF TOLUENE* NITRATION
I
1
1*NITROOซ4*DICHLOR06ENZENE/ NITRATION OF 0ปOICHLOROBENZENE
01
1
NAmEX (ARAmID RESINซFIBER AND SHEET)/ ISOPHTHALOYL CHQRIDE ~ 1#3*0IAnIlINE (TYPIC*Uป AN AROMATIC NYLON
3
1
NRD**?/
01
1
NYLON/DACRON COSPUN FIBER/(OACRON POLYESTER)
02
NEORRENE/ (3-CHLORD-Iป3*BuTADIENE)
A
NITRO AND AMINO ALCOHOL/ ALOO CONOENSaTION OF NITROPARAFFINS WITH FORMaLDEHYOE
3
NITROFURANTOIN/ UAMINOHYDANTOINSULFATE * ZOปNITROFURALDEHYDE DIACET TE
V
1
IซNAPHTHYLNปMETHYLCAR9AMATESEVIN / METHYL AMINE * PHOSGENE ~ 1*NAPHTH0L
M
1
NONYL MfRCARTAN/ ,ALpHA*OLEFINS ~ H2S
I
1
NITROPARAFFINS/ NITRATION OF METHANE# ETHANE* PROPANE (HIOH TEMP, VAP PHASE)
A
1
NITROALCOHOLS/ ALDOL CONDENSATION OF NITROPARAFFINS WITH FORMALDEHYDE
3
NUSOL/E*TRACTION FROM SULFITE PUL* MILL WASTEWATER
3
1
1
nitpooen fertilizer SOLUTIONS/
14
PซNITR0RHENET0LE/ PปNITROPHENOLATE ~ ETHYL CHLORIDE
-------
0
i
L
3
U
8
02
01
3
E
H
M
A
c
10
01
02
0
*
02
01
23
3
3
0
01
3
02
6
3
3
3
02
02
02
01
02
02
12
A
M
M
frequency or occurrence for each product process
dip ZERO UNK PRETEXT
t , , N0NN.4CUMYL PHENYL OIPHENVL PHOSPHATE/ AL*YL PHENOLS# PHENOL ~ P0CL3
. , , SOLVENT NAPhThA/ oistILLATION from coaltap condensate
1 MTPOCHLOPOBCNJENE/ NITRATION Of CHLORORENZENE
. 3 NJSC. REFINER* OILS/
. . . OCTYLATED OIPHENYLAMINE/ALKYHTION
* ORGANIC PEROXIOE/
4 . . OLEFINS mIKEO/ ethylene oligomers E
. 1 . OXAWAXES/ RESIDUES FROM oxazolioines PRODUCTION
. . . OXAZOLIOINCS/
. . OCTAOECADIENOIC ACIO MIX/
1 , . T-OCTYL MFRCAPTAN/ ALPHA-0LEF1NS * H2S
1 N-oCTYL MฃปCAPTAN/ ALPHA^oLEFINS ~ H2S
2 , . MjSC* OROANICS/
, ORGANIC ACIDS (MIXED!/ oxidation OF PROPIONALDEHYOE conoensates
OXIMEStMISC./ CARBONYL CMPO * HYORXYL AMINE
1 , , POLY METHYLENE DIPMfNYL OIISOCYAKATE/(POLVMEIปIC MOH
2 ป < ATACTIC POLVRROPYLENE/BYPROfiUCT OF 3020-03
, , PEROXY ESTERS (T-gUTYL ESTERS OF PERBENZOIC* PEROCTANOIC# PERACETIC ACIDS
ซ POLYAMINES/
2 , . POLYBUTAOIENC RESINS/
2 . POLVaUTYLENE TEREPMTHALATE ซP*T)/
1 , . POLYESTER YARN/
. 1 . PlOMENTfO FINISHES/
1 , * PARAFFINS/
. . . polyethylene FOAM/
. 2 . POLYESTER IMIDE itmh/
i . . POLYPROPYLENE FILM/
. , . ROLYELECTROLYTE/ POLYACRYLAMIOE
1 , . PHENYL 0LYCINE/AN1LINE * CHLOROACETTC ACIO
, . PROTEIN slue/
2 ซ PAINT-GENERAL/
1 . polyethylene OXIDE/
. PICCOYAP RESIN/
. . . PICCO 6100 RESIN/
. . . PICCOMER/
1 1 . PHENOLIC M0L0IN6 COMPOUND/
. . . POLYETHYLENE XYLENE MIXTURE/
. . . POLYETHYLENE TOLUENE MIXTUPE/
1 . POLYOLS/ ALK0XYLAT10N OF FATTY ALCOHOLS, PROPYLENE GLYCOL AND OLYCfPOL
l , . phenylethylphenyl methane/
1 . . N.PROPYL MERCAPTAN/ ALPHA-OLEFINS * M2$
1 . ( I-PROPYL "ERCAPTAN/ ALPHA-OLEFINS ป M2S
1 , ( o-phenyl phenol/ FROM OIBENZOFUBAN
-------
24
3
3
3
3
S
01
5
3
0
01
3
01
K
6
3
3
3
6
02
H
H
ft
3
01
3
E
0
lft
01
01
01
a
3
3
S
01
M
M
4
24
4
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS 2*
DIR ZERO UNK PP_TEKT
1 . PENTASOOIUM DIETHYLENEDIAMINE PENTAACETATC / EDPA CAUSTIC
PHENOLIC COATEO PAPERS/
POLYESTER COATED PAPERS/
PLYWOOD OVERLAYS/
paper beneral/
POLYETHER/ PROPOXYLATION OF PROPYLENE GLYCOL
POLY OIETHVLENE GLYCOL AOJPATE PYRROL!00"E/3ซBUTYROLACT0NE * NH3
POLY-N (TRADE NAME)/ ORflANO-UREA POLYMER
POLYETHYLENE COMPOUNDS/COMPOUNDING
PLASTIC COMPONENT/
PLASTIC BATTERY SEPARATORS/
QUATERNARY AMINES/ ALKYL CHLORIDE 4 FATTY AMINE
RESIN PR/STILL BOTTOMS FROM STEAM PYROLYSIS OF NAPTHA/ OAS OIL
RESIN OIL (AROMATICJ/STEAM PYROLYSIS OF GAS OIL
REACTIVE DISTILLATES FROM STREAM CRACKING/
RESINS SOLUTIONS/
ROSINS AND DERIVATIVES/
ROSIN DERIVATIVE RESINS/
REAOSORBER OFF.GASES/
RICINOLEIC ACID/FROM CASTOR OIL BY HYDROLYSIS
RICINOLEATES AND DERIVATIVES/ RICINOLEIC ACID * ALCOHOL
RAFFINATE/ 9TX EXTRACT OF COAL TAR COWOENSATE
RU8RCR RESINS(POLVURETHANE ELASTOMERS)
rubber*cyclizeo/
RESINS (GENERAL)/
SURFACTANTS/ SULFOSUCCINIC ACID ESTERS SUCCINIC ACID ~ ALCOHOL SODIUM BISULFITE
SULFAMETHAZINE/ CONDENSATION OF SULFAGUANfDINE AND ACETYLACETONE * SOOIUM BISULFITE
SOLVENT BLENOS* MISCELLANEOUS/
SODIUM MfTHYLATE/METHANOL ~ SODIUM
SPANOEX FIBERS ซesป SEGMENTED POLYURETHANE) / POLYOL ~ OllSOCYANATES
SODIUM LAURYL SULFATE/ SULPONATION OF LAURYL ALCOHOL
SODIUM STYRE*ปE SULFONATE/ SULFONATION OF STYRfNE
SPECIALTY lubricants/
SODIUM PROPIONATE/ PROPIONIC ACIO ~ CAUSTIC
textile softeners/ urea ~ formaloehyoe glvoxal
-------
FREQUENCY Or OCCURRENCE FOR EACH PROOUCT PROCESS
25
3ป
I
ro
en
pp.code ecN.cooc djr zero
*819*19
ง819*22
9819*26
9819*27
9819*28
9819*35
9819*36
9819*38
9819*39
9819*40
9819**2
9819.43
9819*45
9820*03
9820*04
9820*05
9820*06
9820*07
9820*00
9820*10
9820*11
9820*12
9820*)3
9820*14
9820*16
9820*17
9820*18
9820*19
9820*20
9820*26
9820*27
9820*30
9820*31
9920-32
9820*33
9"20*34
9820*35
9820-36
9820*37
9ft20*39
9820*45 0
9820*51 R
9820*55 T
UNK PRETEXT
MISCELLANEOUS STEARATES/ STEARIC ACIO ~ ALCOHOL
SYNTHETIC LUBRICANTS/
FATTY ester sulfonates/ sulfonation of fatty ACIOS
LAURYL SULFONATES/ SULFONaTION OF OOOECENE
LINEAR ALKYLATE sulfonate/ sulfonation OF ALKYLBENZENES
SOLVENT BASE COATING/
SYNTHETIC SPECIALTY POLYMERS (POLYSTYRENE)
SOLUTIONS (MISCELLANEOUS)/
SODIUM linear alkyl benzene sulfonate/ sulfonation OF alkylbenzenc
SODIUM N1TROBENZENESULFONIC ACIO/
STYPOFOAM/ EXTRUDED EXPANQEO POLYSTYRfNf
SPECIALITY PAPERS/
SUBSTITUTEO PHENOLS(MISC*)/NITRATION
TRIMELLITIC ANHYDRIDE/ OXIDATION or PSEUOOCUMENE (1ป2ป4*TPIMfTHYL BENZENEI
TRIMETHYLOLPROPANE/ N 8UTYRALDEHYDE ~ rORMALDEHYDE (ALDOLt CANNIZARO)
TRIOXANC/ formaldehyde trimer
TETRAMIX ITRAOE NAME)/
2*3ซ5ป6*TETRaCHL0R0ป4*(METHYL SULFONvL) PYRIDINE/
Zป3ป5*TRICHL0R0*4*(N*PR0PYL SULrONYL) PYRIDINE/
TETRAMETMYL THIURAM MONOSULrtOE/
THIPAM(INSECTICIDE.VULCANIZER)/
TERBAC1L/
TRIAZ1NE DIONE/CONDESATION OF UREA* DEHYDR08ENATI0N
TETRAETHVL THIURAM OISULFIDE/
TH!MNฃR/
TYVEK (SPUNBONDED POLYOLEriN)/ HD POLYETHYLENE SHEET
TIRPENE/
TOTAL oils/
TPIMETHYLOLETHANE/ PROPIONALOEHYDE ซ FORMALOEHYDE (AL00L* CANNIZARO)
TRIMETHO*Y8ENZOIC ACID/ TRI8R0ซ09CNZ0IC ACIO ~ OIMETHVLSULrATf
TEO BOTTOMS/
ThioPHENE/ BUTANE * SULFUR
TETRAMYoROThjOPHENe/ THIOPHENE ~ HYnROOEN
NปTETRAOECYL MERCAPTAN/ ALPHA.OLEFIN *H2S
T1TRAS00IUM ETHYLENEDIAMINE TETRAACETATE/ EOTA
TRISODIUm NITRIL0TRIACETATEปH0N0MYDRATE/ NHS ~
TRISODIUM NITRILOTRIACETATE SOLUTION/
TRISODIUM N.HYROXYfTMYLETHYLENEOIAMiNE TRIACETATE/
TETRASOOIUM ethylenediamine TETRAACETATE/
TRIAMINO CRYSTALS/
TPI-oCTYL TRImEllITATE/ ESTERIPICAT Ion of TRImEllITIC AnHYORIOE
TRICHLOROPROPENE/ CHLORINATION OEHYDROCHLORINATION OF PROPYLENE
terphcnyls/ benzene thru hot ture
CAUSTIC
FORMALOEHYDE ~ NACN
-------
A
e
01
A
3
E
3
Q
01
01
3
3
4
6
3
*
3
2<
2*
2*
3
3
3
3
3
K
3
3
3
3
3
3
3
3
3
3
FREOUENCY or OCCURRENCE for EACH product process
26
OJR ZERO UNK PRETEXT
TIRATE RESINS/ POLYESTER
TPIETHANOt AMMONIUM L*URYL fULFATE/ LAURYL AMINE ~ ETHYLENE OXIDE
TRIS001UM SULFO SUCCINATE/ MALEIC ANHYDRIDE ~ SODIUM BISULFITE
TRIETHANOLAMINE LINEAR ALKTL8ENZENE SULFONATE/ ETHOXYLATION
TAMOL ITPAOE NAME) (POSSIBLY EPOXIOIZEO SOYA OILS)
1*2*3*6 TETRAMYOROBENZALDEHYDE/ HVDROGENATION OF BENZALDEHYOE
URAn (TRADE NAME)/ UREA DERIVATIVE
URETMANE (MISC)/ ISOCYANATE ~ POLYOL
VAZO(AZOilSISOBUTYRONITRJLE)/ METHACRVLONITRILE ~ HYDRAZINE* DEHYOROOENATION
VARNISH RESIN (ROSIN AND ROSIN ESTERS)
VORITES (TRADE name) (UReThaNE PRfPOLYmeRSJ
VULCANIZEO FIBRE/
VEGETABLE OILSซ0ENERAL/
PRInTInO INK VARNISHES/
NซVINVLปfซPYRROLIOONE/ J.BUTYROLACTONE ~ ETHANOLAMINE, DEHYDRATION
vinylปacpylic sheet/
WAX EMULSIONS/ FORMULATED FROM CAPTIVE FORMALOEHYOE PHENOL# UREA. ETC RESITS
HATEPPORNE COATIno/
"OODFlOOP/
WATER REPELLENT/
XANTHATES of C2*C5 ALCOHOLS/ ALCOHOLIC kOh ~ CSS
SPUN YARN DRY PROCESS/
ZINC ปMซONIUM VERSENaTE/ ETHYLENE 0IA*INE ~ CHLOROACETIC ACID
ZERANOL/
ZINC UNDECVLENATE/ UNOCCYLENIC ACIO ~ ZINCOXTOE
ZINC ANO CALCIUM STEARATE/
zinc DISODIUM ETMYLENEDIAMINE TRIACETATE/
Ammonia/
ammonium NITRATE/
AMMONJUM SULFATE/
AMMONIA ANHYDROUS/RXN NJtROOEN HYDROGEN
ALUMINUM SULFATE/
ammonium salts-fatty r-oh ether sulfate/
ALUMINUM FLUORIDE/
BROMINE/
catalyst/
CHLORINEปCAUSTIC/
CURING AGENTS/
CHLOROSULFONIC ACID/
CHLORINATED dry BLEACH/
A
2
1
CARBON MONOXIDE/
CAUSTIC SODA/
CELLULOSE BATTERY SEPARATORS/
-------
FREQUENCY Of OCCURRENCE FOR EACH PRODUCT PROCESS
PP.CODE ปEN^COOE
9903-19
9903-16
9903*18
9903*19
9904*01
9906*01
9908-02
9908*03
9908*04
9908*0T
9908*08
9908*09
9908*10
9909*02
9909*03
9912*01
9913*01
9913-03
991ซ*02
9914*04
9914*09
9915*01
9916*05
9916*08
9916*12
9916*20
9916*21
9917-01
9919*02
9919*04
9919*09
9919*06
9919*08
9919*10
9919*11
9919*12
9919*19
9919*16
9919*1r
9919*22
9919*29
9919*26
9919*31
3
3
OfR ZERO UNK PP_Tt*T
2 . CALCIUM CHLORIDE/
CALCIUM CARBIDE/
CARBON DIOXIDE/
CALCIUM HYDROXIDE/
diammonium phosphate/
FLUORSPAR/
HVOROCHLORIC ACID/
HVOROOEN/
MYOROPLOURIC ACIO SALTS/
HYDROOEN PEROXIOE/
HY0R08EN SULFIDE/
HYDROOEN CHLORIDE/
HYOROOEN cyanide/
INDUSTRIAL QASES*HYORO0EN NITROOEN/
IODINE/
LUDOX*SILICA/
MIXEO ACIOS (NITRIC t SULFURIC)/
MURIATIC ACID (LOM 8RADE HYDROCHLORIC ACID)/
WITRIC ACID/
NON*PIOMENTED PRODUCT/
NITROOEN/
0XY8EN/
PHOSPHOROUS 4CI0/
POLYSTYRENE (OPS) SHEET/
POTASSIUM ACIO PHTHALATE/
PHOSPHOROUS PENTASULPIDE/
POTASSIUM CARBONATE (POTASM)/RYpROO OP MSQ (2080*99)
OUARTERNARY AMMONIUM CHLORIOES/OUANTERNI2ED PIMER DIAMINES#TETRAM1NES
SODIUm CHROMATE/
S001U* SULFATE/
SULFURIC ACID/
SODIUM NITRITE/
SOOIU* CHLORATE/
SOOIUM SILICATE/
SYNTHESIS OAS/
SOOIUM metal/
SOOIUM CARBONATE (NAOH FLUE OAS)/
SULFUR M0N0CHL0R1DE/
SODIUM CHLORIDE/
SOOIU* HYPOCHLORATE/
SULFUR (CPYSTEX)/
SOOIUM SALTS*FATTY ALCH ETHER SULFATE/
SOOIUM ferrocyanide/
-------
FREQUENCY 0* OCCURENCE FOR EACH PRODUCT PROCESS
PP.COOE OEN.COOE Ot*
ZERO
UNK
PRETEXT
9919-32
9920-01
9923*01
992602
SULFUR ANMYDRIOE/
TITANIUM DIOXIDE/
mire and cable/
ZINC SULFATE/
-------
APPENDIX B
BPT STATISTICS
-------
BPT Statistical Appendix
DESCRIPTIVE STATISTICS
Some of the more commonly employed descriptive statistics are defined as
follows:
(1) N - number of valid observations used in a particular analysis (e.g.,
the total number of effluent samples at a particular plant for a parti-
cular pollutant)
(4) Minimum - the smallest value in a set of N observations
(5) Maximum - the largest value in a set of N observations
(6) Range - the minimum subtracted from the maximum
(7) Median - the middle value in a set of N observations. If N is odd
(N * 2k 1 for some integer k), the median is the kth order stati
C(k). If N is even (N ป 2k), the median is
l/2[C(k) + C(k + 1)].
_ N
(2) Mean - arithmetic average: X ฆ Z Xj/N
i=l
(3) Variance - standard unbiased estimate
(The standard deviation
)
B-l
-------
MOVING STATISTICAL MEASURES
Over a year's data were available for some plants. The question of
whether treatment system performance at those plants was consistent over
time was investigated by examining moving statistical measures of perform-
ance. Let Xlt .XN denote the N daily observations available from a
plant listed in the order they were obtained. Then the moving mean and
variance on day t based on observations for the latest n < N days are
defined as
xt " i j
n 1=1
and
S? " T^TT ฃ * x<)2'
where t > n.
If the distribution of X is lognormal (so loge(X) is normal with parameters V
and o^)t then the 99th percentile of X is
P99 s eP + 2.326o
B-2
-------
The moving estimate of P99 at time t based on the lognormal model, therefore,
is
Xt + 2.326St
P99t - e
with and defined above.
Moving estimates of the 99th percentiles of effluent concentrations were
plotted over time for each plant to evaluate the consistency of its treatment
performance (see Appendix D). Note that the moving 99th percentile will reflect
changes in both average effluent levels (through ) and day-to-day effluent
variation (through St).
GOODNESS-OF-FIT TESTS
The statistical model used to describe effluent data assumes that y ฆ log(C)
is normally distributed, where C is the daily effluent BOD or TSS concentration.
Goodness-of-fit tests for this model were run using the studentized range
test based on the statistic
U - R/S,
with the range (R) and standard deviation (S) defined above. Critical values
of the U-test are given in Biometrika Tables for Statisticians, Vol. 1, page
200, for selected sample sizes (N). An upper tail test was used to guard
against alternative distributions with heavier tails than the lognormal distri-
bution; the lognormal model would tend to underestimate the 99th percentile
if such alternatives were appropriate.
A significance level of a ฆ 0.01 was employed in each test. Since there
were a total of 28 data sets tested (17 for BOD and 11 for TSS), this choice
of a ensured that the overall probability of rejecting the lognormal model,
when it was appropriate, was reasonably small.
B-3
-------
Table B-l shows the results of the goodness-of-fit tests. The model was
rejected for only two out of twenty-eight data sets (BOD for plant 236 and
TSS for plant 27). The impact on the 99th percentile estimate for the two
rejected cases was evaluated by comparing model-based estimates with nonpara-
metric estimates; namely, the next to largest of the 162 BOD observations and
the next to the largest of the 158 TSS observations. For BOD at plant 236,
the model gave P99 = 93 versus the nonparametric estimate of P99 = 70. For
TSS at plant 27, the model gave P99 = 76 compared to the nonparametric esti-
mate of P99 = 80. In neither case was the lognormal estimate substantially
lower than the nonparametric estimate.
The goodness-of-fit of the lognormal model also was checked through a
graphical procedure called a probability plot. Let Xj, .. ., Xn denote the n
observed daily values of the parameter of interest (the BOD or TSS measure-
ments from a given plant). Denote the rth largest of the n values by X(r) ,
and define a corresponding score called the "probit" by
Probit[X(r)] = $-1[r/(n + 1)],
where ~"^(O is the inverse of the standard normal cumulative distribution
function. The probit score is the normal deviation (z-value) equivalent to
the value X(r). Probit scores are useful because plots of X values versus
corresponding probit scores tend to be straight lines when X is normally
distributed; this fact is the basis for probability plots. If X has a log-
normal distribution, a log-scale plot of X values versus probit scores tends
to be a straight line. Daniel and Wood (1971) give simulated examples of
probability plots to indicate the degree of random departure from a straight
line to expect for different sample sizes when X is normally distributed.
Probability plots for BOD and TSS are presented in Figures B-l to B-28.
Based on the results of the studentized range test and the probability
plots, it was concluded that the lognormal distribution could be used to
model the data.
B-4
-------
TABLE B-l. GOODNESS-OF-FIT TESTS FOR BOD AND TSS
LOGe OF DAILY DATA
PLANT
TYPE
BOD
TSS
N
U
P*
N
U
P*
9
P
24
4.84
N.S.
24
3.73
N.S.
15
NP
363
6.97
N.S.
0
-
-
27
NP
160
5.77
N.S.
158
7.36
<0.01
44
P
261
5.86
N.S.
260
6.00
N.S.
45
P
156
4.03
N.S.
364
3.86
N.S.
96
P
105
3.96
N.S.
66
4.83
N.S.
110
NP
247
4.73
N.S.
218
4.70
N.S.
111
P
157
4.36
N.S.
347
5.69
N.S.
113
NP
332
5.77
N.S.
91
4.45
N.S.
118
NP
365
4.52
N.S.
0
126
P
249
5.09
N.S.
253
5.49
N.S.
170
NP
103
3.21
N.S.
0
175
NP
361
4.98
N.S.
0
220
NP
55
3.92
N.S.
149
5.22
N.S.
234
NP
157
5.71
N.S.
0
-
236
NP
162
7.28
<0.01
362
6.43
N.S.
281
NP
203
5.22
N.S.
0
* Critical values for the studentized range test (upper tail, a * 0.01) are
N U.99
25
5.06
50
5.77
65
6.01
90
6.27
100
6.36
150
6.64
200
6.84
500
7.42
N.S. * Not significant (U value below critical level).
Reference: Biometrika Tables for Statisticians, Vol. 1, page 200.
B-5
-------
PROBABILITY PLOT
PLANT-9
2 -1 0
PJJOBTT
FIGURE B-l. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLAMT-15
ฆ [ ฆ ฆ i ฆ ฆ i . i| 11 i ฆ i ฆ ฆ ฆ | i ฆ ฆ ' ฆ ฆ ฆ ฆ 11 . ฆ ฆ
-2-1 0 1 2 3 4
PSOBIT
FIGURE B-2. PROBABILITY PLOT F05 BOD
B-6
-------
eoD-
16y0H
3 00-
10-
1-1
PROBABILITY PLOT
PLANT-27
*
T
-4
_-j
-2
-1 0 1
PROS IT
T
4
FIGURE B-3. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
EOD
1600-d
100-
16"
H
r
-4
~rv
-3
-vr-pr
-2
PLANT-44
A
'1 ' ' ฆ I T
0 1
P&G8IT
T
T
4
FIGURE B-4. PROBABILITY PLOT FOS BOD
B-7
-------
PROBABILITY PLOT
BOD
1606-
188-
10-
PLAKT-45
H
j i ii i rri I t j r-i i j ) i ni p r~i
* -3 -2
-1
6
PROBIT
T
4
BOD
1000-
i sa-
le-
ns
-4
-3
FIGURE B-5. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLANT-96
"T*
-2
ฆ i i ฆ
0 1
F.^OBIT
FIGURE B-6. PROBABILITY PLOT TOR BOD
Tr
t.
T
4
B-8
-------
EOD
leoo-
PROBABILITY PLOT
PLANT-110
100-
10"
T
4
BOD
10O0-
100-
T'
_*?
*"T*
-2
FROBIT
FIGURE B-7. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLANT-111
10"
.A *
A
. ^
1
T
-4
TT
0
TP
T*
3
T
-3
T*
T
-2-1 0 1
PROBIT
FICUIE B-8. PROBABILITY PLOT FOR BOD
B-9
-------
PROBABILITY PLOT
BOD
ioeo-
PLAKT-113
iee-
10-
A A
14.
-4
" I I 11 ฆ ฆ 11 ฆ ฆฆ' 11
-2-1 0 1 2
PROSIT
BOD
1888-
FIGDRE B-9. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLANT-118
100-
10"
-------
PROBABILITY PLOT
BOD
1869-
106-
10-
BOO
1G00H
100-
10-
H
PLANT-126
A A A
A
tJ*
*
H, , ฆฆฆฆปฆ" ป '
-4 -3 -2 -1 0 1 2 3 4
PR06IT
FIGURE B-ll. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLANT-170
... * i
y
A
Tป ป i i i i i i i | rป nrrn i | rrป rป rr i"i ninup
-4-3-2-1 0 l 2 3
PSOBIT
I 1 1 1 1 ฆ ฆ I I | ป I
4
FIGURE B-12. PROBABILITY PLOT FOR BOD
B-ll
-------
BOO
1606-
100-
10-
H
a 4
PROBABILITY PLOT
PLANT-175
A A
-4
T
-7
-1
' ' ' I ฆ ' '
0
PF:GB1T
FIGURE B-13. PROBABILITY PLOT FOR BOD
BOD
1000'
100-
10-
H
T
4
T
-3
PROBABILITY PLOT
PLANT-220
A A
J*
A
T
-2
-1
" " ฆ i ฆ"
0
FROBIT
-r-prr-
3
T
4
FIGURE B-l*. PROBABILITY PLOT FOR BOD
B-12
-------
BOD .
10U0H
probability plot
PLANT-234
100-
10"
*
.A-4
A A
1-L
"T1
-3
i-rp-i
-2
T*
"rTr
0
T"
-1 0 1
PRCIBIT
FIGURE B-15. PSOBABILITY PLOT FOR BOD
BOD
1600-
PnOBABILITY PLOT
PLANT"236
100-
10-
A A
-4
-3
-2
ฆ" 1" ฆ
0
PRC'S IT
"T*
2
3
~
4
FIGURE B-16.
B-13
PROBABILITY PLOT FOR BOD
-------
PROBABILITY PLOT
T"
-4
PLANT-281
"T
-2
-1
PROBIT
"T
4
FIGURE B-17. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLANT-9
ft A A. A
A
A A A A
I I | I I I I I I'l I ป J I I I
-4 -3 -2 -1 0
PROBIT
FIGURE B-18. PROBABILITY PLOT FOR TSS
B-14
-------
probability plot
TSS
1000-
100-
10-
PLANT-27
A ^
KtP
A
**
A
1 *lj I I | I ' ฆ ' | I I I I | I I I I , I ฆ ฆ ฆ , t |
-4-3-2-1 0 1 2 3 4
PROBIT
TSS
1600H
103*
10^
1H
FIGURE B-19. PROBABILITY PLOT FOR TSS
PROBABILITY PLOT
PLAVT-44
A
A
V'
ฆ ,, ,
-4-3-2 -1 0 1 2 3 4
PROBIT
FIGURE B-20. PROBABILITY PLOT FOR TSS
B-15
-------
TSS
1000H
PROBABILITY PLOT
PLANT-4 5
IBM A - A A
A^
iei aa
a
A
A
^ I " ' ' ฆฆ 1 ' | ''''''' " | * .i ii ii ii |
-4 -3 -2 -1 e
PROBIT
FIGURE B-21. PROBABILITY PLOT FOR TSS
TSS
leeeH
H
PROBABILITY PLOT
PLANT-96
106-
A *
18i
ฃ> A
A
A
A
11 i 11 11111 i j 111 ฆ i f ฆ i ' i i i i; '' ' i ฆ ' ฆ ' ฆ I i | j ฆ i i 111 i 11 j iป 111ปiป111
-4-3-2-1 0 1 2 3
PROBIT
FIGURE B-22. PROBABILITY PLOT FOS TSS
B-16
-------
PROBABILITY PLOT
TSS -
1300
10-
lH
-4
1 ' j " 1 J1
-7. -?
PLANT-110
A A
A
A
T I I 1
0 1
PROBIT
FIGURE B-23. PROBABILITY PLOT FOR TSS
PROBABILITY PLOT
T
4
TSS
1000H
100-
10"
1H
-4
PLANT-lll
ฆ' i ฆ ฆ ฆ r* ""!ฆ
-2-1 8 1
PROBIT
"T1
2
^T1
-3
T*
3
T
4
FIGURE B-24. PROBABILITY PLOT FOR TSS
B-17
-------
TSS
iceed
100-
le-
l-L
PROBABILITY PLOT
PLANT-113
A
A
,4^
A
A
A
. aAA
^AA
I ' I I 4 I I I |
"4 -3-2-1 0 1 ฃ 3 4
P.ROB IT
FIGURE B-25. PROBABILITY PLOT FOR TSS
PROBABILITY PLOT
PLANT-126
aa
A^
lA A
I I'l'JItll
2
-3 -2
e
PROBIT
"T
4
FIGURE B-26. PROBABILITY PLOT FOR TSS
B-18
-------
PROBABILITY PLOT
TSS
1000H
100"
10-
PLANT-220
A A
l-L
-rp-
7
t
2
ฆ 1 1
T
T
-1 S 1
PROBIT
FIGURE B-27. PROBABILITY PLOT FOR TSS
PROBABILITY PLOT
TSS
1000-
PLANT-236
160-
10-
A A
I"
-4
-3
-1 0
PROBIT
T
2
T1
3
T
4
FIGURE B-28. PROBABILITY PLOT FOR TSS
B-19
-------
VARIABILITY FACTORS
Assuming that the distribution of the concentration c is lognormal, then
y = logCc) is normally distributed with mean y and variance o2 (Aitchison
and Brown, pages 8-9). Thus the 99th percentile on the natural log scale is
yo.99 * v + 2.326 a ,
and the 99th percentile on the concentration scale is
c0.99 = exP(yo.99) = e u + 2-326 c . (1)
The mean and variance on the concentration scale are:
p + 1/2 o2
and
= e (e - 1).
2 y + o
2 2
Hence, the daily variability factor under the lognormal model is:
c0.99 2.326 o - 1/2 o2
VF(1) - - e (2)
Estimates of any of the above quantities are calculated by substituting the
mean and variance of natural logs of the observations for y and a2, respectively.
To determine the variability factor for 30-day average concentrations,
VF(30), it was necessary to take day-to-day correlation into account. Positive
autocorrelation between concentrations measured on consecutive days means
that such concentrations tend to be similar. The medians of plant-specific
autocorrelations for one-day-apart concentrations were about 0.7 and 0.4 for
BOD and TSS, respectively. An average of positively correlated concentration
measurements is more variable than an average of independent concentrations.
B-20
-------
A rigorous time series analysis to model the autocorrelation structure
of each data set was not possible because of the many missing days' data in
most data sets. Therefore, the correlation (p) between consecutive days'
measurements (i.e., the lag-1 autocorrelation) was estimated for each plant
using the available data. Then using the first-order autoregressive model
commonly found to be appropriate in water pollution modeling, the mean and
variance of an n-day average were approximated by:
p + 1/2 o2
y~ = e
and
c
(3)
cj2 ฆ fn( p)
n
with
fn( p) ฆ 1 * p - 2 p (1 - p ) t
1 ~ P n(l - P)2
It can be seen in (4) that equals the variance of an average of
n uncorrelated observations, 0c/n, times a factor fn(p) that adjusts for
the presence of autocorrelation. The correlation-adjustment factor is derived
as follows using the fact that the covariance between concentrations k days
apart is under the first-order autoregressive model. Since
_ n
c - I I cL,
n
0 1
j* ซ _ Z E cov(c-, cซ)
c i-1 3-1 J
B-21
-------
n-1
- [ri o? + 2 Z (n - k) o^]
n2 C k-1
at. n-1
[2l ฃ (n - k) pk - 1],
n n k=0
The expression in brackets reduces to fn(p) with the help of the summation
formula for arithmeticogeometric progressions:
n~l a - [a + (n - l)r]qn rq(l - q11-^)
I (a + kr)qk = + ,
k=0 1 " q (1 _ q)2
taking a = n, r = -1, and q = p (Gradshteyn and Ryzhik, page 1).
Finally, since c is approximately normally distributed by the Central
Limit Theorem, the 95th percentile and variability factor of a 30-day average
are approximately
c0.95 = VZ + 1>645 ฐc <5)
and
VFC30) - E0.95/vj
1 + 1.645[(e - l)f30(p)/30]1/2 (6)
with y- and defined by equations (3) and (A). Estimates of Cq.95 or
VF(30) are calculated by substituting estimates of u, o2, and p into the
formulas above.
B-22
-------
SPEARMAN RANK CORRELATION TECHNIQUE
Let (XL, Yi), (X2,Y2),...,(Xn,Yn) be a bivariate random sample of size n.
The rank of X^, R(X^), as compared with the other X values, for i ฆ l,2,...,n
is the position of X^ as the X values are ordered from smallest to largest.
Thus, if Xk is the smallest X value, RCX^) = 1 and if Xj is the largest X
value, R(X^) = n. Similarly the values for Y can be ranked for i ป l,2,...n.
Once ranked, the data can be replaced with the rank pairs (R(X^),R(Yi)), (R(X2),
R(Y2)),...,(R(Xn),R(Yn)). The Spearman rank correlation coefficient is cal-
culated as follows:
n ?
I R(Xi)R(Yi) - [1/2 (n + 1)]^
i-1
R ป
n(n^ - 1)
12
Based on R the following hypothesis can be tested:
H0: The X^ and Y^ are mutually independent (i.e., their correlation is zero)
: Either (a) there is a tendency for the larger values of X to be paired
with the larger values of Y, or (b) there is a tendency for the smaller
values of X to be paired with the larger values of Y.
By using influent or effluent concentrations for the X's and subcategoriza-
tion variables for the Y's, the above hypothesis becomes a statistical test
for significant subcategorization factors. Throughout this chapter the term
"null hypothesis" refers to the hypothesis Hq: the X{ and Y^ are mutually
independent.
Aside from the fact that a rank correlation statistically tests whether
two variables are independent, it also does not assume a linear relationship
B-23
-------
between the variables. Consider Table B-2, where X and Y are two variables
that exhibit a nonlinear relationship. The Pearson correlation coefficient,
r, which assumes a linear relation between X and Y, is 0.6, where
Y - I I Y-
n i 1
while the nonparametric Spearman Rank Correlation coefficient, R between R(X)
and R(Y), is 1. Correlation coefficients are numbers which range between -1
and +1. Values of +_1 indicate perfect associations or correlations, while a
value of zero indicates no relationship.
For each of the rank correlation coefficients calculated, a graph has
been attached which plots the rank pairs (R(Xi), R(Yi)). A least squares
line has been superimposed on the plot of the rank pairs to indicate graphi-
cally the degree of correlation. Each graph is labeled with the appropriate
industry subcategory (e.g., Plastics Only).
At the bottom of each figure is the Spearman rank correlation coefficient,
the sample size N, and the probability, p, that the null hypothesis, H0, is
true. Values of p of less than 0.05 indicate that a relationship exists, as
specified in the alternative hypothesis, H]_. For ease of interpretation,
Figures B-29 through B-33 show the theoretical lines for a sample size of 50
and Spearraan rank correlations of -1, -0.5, 0, 0.5, and 1, respectively. As
can be seen from these graphs, correlations of -1 and -0.5 indicate that as
R(Y) decreases, R(X) increases; a correlation of 0 indicates that no relation-
ship exists between R(X) and R(Y); and correlations of 0.5 and 1 indicate
B-2 4
-------
TABLE B-2. AN EXAMPLE OF VARIABLES WITH A NONLINEAR RELATIONSHIP
X Y R(X) R(Y)
1
1
1
1
10
1.5
2
2
20
2
3
3
25
4
4
4
30
10
5
5
35
50
6
6
50
70
7
7
100
90
8
8
200
95
9
9
600
100
10
10
B-25
-------
SPEARMAN
RANK CORRELATION (R=-l)
N=5B
e-
35-
30-
25-
15-
eH
16
15
20
v
25
30
40
35
45
50
X
FIGURE B-29. REGRESSION LINE FOR RANK CORRELATION OF -1
SPEARMAN
RANK CORRELATION (R=-.5)
H=56
48-
35-
20-
10-
fiH
20
40
50
15
25
30
45
C
x
FIGURE B-30. REGRESSION LINE FOR RANK CORRELATION OF -0.5
B-26
-------
5PEARMAN
RANK CORRELATION (R=0)
li=50
ฆ"If I " "I 11 HI I. ..-.1 U"1" ฆ " " 'I
10 15 20 25 3D 35 40 45 50
X
FIGURE B-31. REGRESSION LINE FOR RANK CORRELATION OF 0
SPEARMAN
RANK CORRELATION (R=.5)
H=50
45-
0-
35-
eH
so
45
40
35
20
25
30
15
FIGURE B-32. REGRESSION LINE FOR RANK CORRELATION OF 0.5
B-27
-------
SPEARMAN
RANK CORRELATION (R=l)
1-1=50
50-
46-
25-
38-
25-
5-
35
38
15
20
25
45
5
53
0
X
FIGURE B-33. REGRESSION LINE FOR RANK CORRELATION OF 1
B-28
-------
that as R(Y) increases, R(X) increases. It should be noted that the Spearman
rank coefficient only indicates a dependent relationship between R(X) and
R(Y). Derivation of the functional relationship between X and Y requires
additional statistical techniques.
TERRY-HOEFFDING TEST
A common problem in statistics is the "two-sample problem" in which two
populations are compared based on random samples of observations from each.
This is precisely the problem one faces when trying to determine subcategories
for a guideline: if two populations are different, then they represent differ-
ent subcategories. For example, a statistical test which shows that Plastic
plants' influent BOD levels are different from those of Not Plastic plants
demonstrates the need for separately analyzing Plastic and Not Plastic plants.
In statistical terms, the problem is to test the null hypothesis that
two population distributions have the same mean or median value of a property
of interest. Random samples of sizes nj and n2 are taken from the populations,
a test statistic is computed from the sample data, and the value of the test
statistic is used to decide whether the null hypothesis of identical population
distributions should be rejected.
The most commonly used test for differences between population means is
the two-sample Student's t test. Let yฃ(i ฆ 1 n^) and zj(i - l,...,n2)
represent the sample observations from the two populations. Then Student's t
statistic is
t - (y - z)/s V" n/n^n2, (7)
where
n ฆ nj_ + n2
B-29
-------
is the pooled sample size,
- 1 ni
y - 1 yฃ
ni i=i
and
- 1 n2
z = i- I z.
n2 i-1 1
are Che sample means, and
-l nl - 9 n2 _ 0
- (n-2) 1[ I (yL - y)2 + E (z. - z)2]
i=l i=l
is the pooled sample variance. The observed value of the t statistic is
compared to tabled critical values of the t distribution with n-2 degrees of
freedom to determine whether to reject the null hypothesis of equal population
means.
The t test assumes that the population values are normally distributed
with equal variances. When either of these assumptions fails to hold, conclu-
sions of the test may be invalidated. One problem that may result is that
the null hypothesis may be rejected with higher probability than assumed when
it actually is true (i.e., the probability of a Type 1 error (a) may exceed
the nominal a-level). Another possible problem is that the t test may fail
to detect existing population differences as well as it would if the assump-
tions held (i.e., its statistical power may be reduced). Either of these
problems would have unfortunate consequences in subcategorization: false
rejection of the null hypothesis could lead to unnecessary subcategories;
failure to detect differences could result in failure to recognize needed
subcategories. In order to avoid incorrect conclusions that could be caused
B-30
-------
by failing to satisfy the assumptions behind the t test, a different test
based on less restrictive assumptions was used.
The Terry-Hoeffding test corresponds closely to the two-sample t test,
but it assumes only that observations are drawn randomly from two continuous
population distributions. For large samples, the Terry-Hoeffding test can be
thought of as a two-sample t test based on "normal scores" rather than on the
original observations. That is, before performing the t test, one replaces
the rth largest observation in the pooled sample of n observations with the
expected value of the rth largest observation from a random sample of size n
from a standard normal distribution (E(r, n)). For large n, it is convenient
to approximate normal scores by
E(r, n)s [r/(n + 1)], (8)
since the inverse of the cumulative normal distribution function, ~"!(*),
is readily available in computer systems. For small n, values of E(r, n) are
tabled in nonparametric statistics books (e.g., Bradley, page 326). The intui-
tive idea of the Terry-Hoeffding test is that replacing original observations
(which may not be normally distributed) with normal scores leads to a more
robust test (one whose validity is not as limited by underlying assumptions).
Because the sum of normal scores for the pooled sample is zero, the t
statistic based on normal scores simplifies to
t - Vn-2 S/ [ "i"2 E E(r,n)2 - S2] 1/2 , (9)
L n r-1 J
where S is the 6um of normal scores for the sample with fewer observations
(Bradley, page 152). The observed value of t is compared to critical values
of the t distribution with n-2 degrees of freedom (just like the classical t
test). A simpler approximation to this test for large samples is based on
comparing
B-31
-------
T =
h^l1/2 s
.nln2 J
(10)
to critical values of the standard normal distribution (the mathematical
justification for this approximation is given in Kendall and Stuart). For
small samples, the Terry-Hoeffding test compares observed values of S to
tabled critical values. Bradley (pages 327-330) gives critical values of S
for pooled sample sizes up to n = 20.
The Terry-Hoeffding test has several advantages over the classical t
test:
It is distribution-free; i.e., one need not be con-
cerned that violations of distributional assumptions
will affect the probability of a Type I error.
Its large-sample power is better except when the nor-
mality assumption holds (then, it is equivalent to the
t in large sample power)
It is less sensitive to extreme observations (outliers)
than the t. For example, the actual value of the largest
observation in the pooled sample doesn't affect the Terry
Hoeffding test, but can have a great impact on the classical
t test.
Kendall and Stuart (page 520) note that it is "difficult to make a case for
the customary routine use of Student's test" in comparing two populations
when the sample numbers are reasonably large.
To illustrate the application of the Terry-Hoeffding test, the hypothe-
tical influent BOD data from Plastics and Not Plastics plants in Table B-3
will be used. The table gives original observations and normal scores for
ten Plastics plants and fourteen Not Plastics plants (the normal scores were
calculated using formula (8)). The null hypothesis is that Plastics and
Not Plastics plants do not differ in median influent BOD. The sum of normal
scores for plastics plants is
B-32
-------
TABLE B-3. EXAMPLE OF SAMPLE DATA FOR THE TERRY-HOEFFDING TEST
RANK (r) BOD SOURCE* NORMAL SCORE (E(r,n))
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
*P " Plastics
NP " Not plastics
P -1.751
P -1.405
P -1.175
P -0.994
P -0.842
P -0.706
P -0.583
NP -0.468
NP -0.358
P -0.253
P -0.151
NP -0.050
P 0.050
NP 0.151
NP 0.253
NP 0.358
NP 0.468
NP 0.583
NP 0.706
NP 0.842
NP 0.994
NP 1.175
NP 1.405
NP 1.751
150
170
190
210
230
250
270
320
370
420
470
520
550
590
610
630
680
730
780
800
810
870
930
990
B-33
-------
s = -7.81,
so the test statistic based on formula (10) is
T = -3.71.
Since this is less than -1.96, the critical value for the normal distribution
with a - 0.05 for a two-tailed test, we reject the null hypothesis at this o-
level. That is, we conclude that Plastics plants are different from Not
Plastics plants in.the example. Note in Table B-3 that observed BOD values
(and normal scores) for Plastics tend to be lower than values for Not Plastics.
B-34
-------
REFERENCES
Aitchison, J,, and J.A.C. Brown (1957). The Lognormal Distribution, Cambridge
University Press, London, 8-9.
Bradley, J.V. (1968). Distribution-Free Statistical Tests, Prentice-Hall,
Englewood Cliffs, NJ, 149-154, 326-330.
Daniel, C., and F.S. Wood (1971). Fitting Equations to Data, Wiley, New
York, 34-43. ~
Gradshteyn, I.S., and I.W. Ryzhik (1965). Tables of Integrals, Series and
Products, Academic Press, New York, 1.
Kendall, M.G., and A. Stuart (1973). The Advanced Theory of Statistics,
Vol. 2, 3rd Edition, Hafner, New York, 516-520.
Pearson, E.S., and H.O. Hartley (1969). Bioroetrika Tables for Statisticians,
Vol. 1, 3rd Edition, Cambridge University Press, London, 200. ""
B-35
-------
APPENDIX C
See Chapter 13 of the BAT Volume of this report for the glossary.
-------
APPENDIX D
Rationale For Exclusion of Daily Data Base Plants
From Variability Analysis
Plant No. 1: The plant upgraded its treatment system significantly dur-
ing the first data period and since the second data collection period,
and no data are available for the upgraded plant. The aerated lagoons
were converted to activated sludge in 1980. In addition, the effluent
daily data for both periods included unqualified cooling water dilution.
Plant personnel expressed doubts as to available data's validity.
Plant No. 3: The treatment system for this plant was upgraded signifi-
cantly during the data collection period. The aerated lagoons were
replaced by activated sludge units after August 1976. In addition, the
plant had operational problems from July 1978 to February 1980, includ-
ing clarifier shutdowns, clarifier floodings and difficulties with the
equalization basins, which make the data unrepresentative of a steady-
state operation.
Plant No. 292: This plant is not considered representative of Organic
Chemical Industry plants due to the inclusion of municipal effluent in
its influent. The municipal flow may be as much as 25 percent of the
total influent, and therefore is considered a significant, and atypical,
influent stream.
Plant No. 18: During the data collection period, this plant underwent
major expansion and modification. Screening, equalization, increased
capacity, chlorination facilities and sludge handling facilities were
implemented in 1976. Available data are, therefore, not considered to
be from ? steady-state system. Also, the effluent sample point is
upstream of the final clarifiers, and therefore not representative of
actual plant performance.
Plant No, 293: This plant is a poor performer (BOD removal 89%,
effluent BOD 87 mg/1). Available information indicates poor solids con-
trol may be the cause of poor performance (TSS removal 66%).
Plant No. 20: No BOD, COD or TSS effluent data are available for this
plant.
Plant No. 24: No BOD, COD, or TSS data are available for this plant.
Plant No. 28: The treatment system of this plant does not conform to
accepted engineering practice. In particular, the use of chlorination
before trickling filters is noted as being extremely unusual, and not in
accordance with accepted wastewater treatment methodology.
Plant No. 42: The poor performance by this plant seems to be related to
poor operational procedures. Flow is reported to be alternated between
two equalization lagoons, with the switch between the two noted as a
cause for high effluent BOD. Steady-state operation is also reported to
be interrupted by periodic sludge wasting from the anaerobic lagoon.
D-l
-------
The treatment train used at this plant (anaerobic lagoon followed by
activated sludge) is unorthodox. Plant was zero discharge until 1978.
The data period is therefore shortly after startup and may not represent
steady-state operations.
Plant No. 53: The treatment system for this plant has been upgraded and
no data are available for the upgraded system. Plant had aerated
lagoons, but they were inadequate for loadings received. The plant was
converted to activated sludge in 1977 in order to improve solids control
(effluent TSS 74 mg/1).
Plant No. 60: This plant achieved poor treatment levels (BOD removal
88%, effluent BOD 54 mg/l).
Plant No. 61: This plant has upgraded its treatment system due to poor
performance, and no data are available for the upgraded system. In-
creased pretreatment, neutralization and dual media filters were added
in 1977 in order to improve poor (BOD removal 79%, effluent BOD 81 mg/1)
plant performance. (Available information indicates that insufficient
air supply to aeration basins and poor solids control may have been re-
sponsible for the poor performance noted during the data period.)
Plant No. 72: There are no continuous data for this plant available at
present.
Plant No. 73: This plant phased out a major production unit during col-
lection period, which resulted in an estimated 70 percent reduction in
influent BOD load from 12/75 through 12/76. Thus, the available data
are not for a system operating under steady state conditions.
Plant No. 74: The data available for this plant are not representative
of actual treatment system performance. The available effluent daily
data include an unquantified stormwater stream. In addition, no BOD,
TSS or COD data are available; only TOC and flow data were reported.
Plant No. 75: The data available for this plant are not representative
of actual treatment system performance. The available effluent daily
data include an unqualified waste stream which consists of untreated
boiler blowdown, stormwater runoff and cooling water. No daily data are
available for this stream.
Plant No. 87: For this plant, the effluent sampling site was downstream
from a mixing point of biological and nonbiological effluents (i.e.,
effluent is diluted) . Also, no BOD or TSS data are available for this
plant.
Plant No. 89: The data available for this plant do not accurately
represent actual treatment plant performance. The effluent daily data
include an unquantified stream which consists of untreated process water
and stormwater runoff. No daily data are available for this stream.
Plant No. 90: The data available for this plant are not representative
of actual treatment plant performance. Available effluent daily data
D-2
-------
include an unquantified stream consisting of untreated cooling water.
No daily data are available for the cooling water stream.
Plant No. 103: No effluent BOD, COD or TSS data are available for this
plant.
Plant No. 106: Effluent data for this plant contain cooling water dilu-
tion. This data is therefore not representative of actual treatment
plant performance.
Plant No. 109: Data available for this plant are not representative of
actual treatment plant performance. Effluent data contain dilution by
an unqualified wastestream for which only estimated average BOD is
reported.
Plant No. 120: This plant treats petroleum refinery wastewater as well
as organic chemical wastewater, and is therefore not representative of
treatment plants in the OCPS data base.
Plant No. 123: Data available for this plant are not representative of
actual treatment plant performance. Available effluent data include
stormwater dilution.
Plant No. 124: The data avilable for this plant are not representative
of actual treatment plant performance. The available effluent data
include an unquantified stream consisting of untreated stormwater. No
daily data are available for the stormwater stream.
Plant No. 138: This plant achieved poor removals during the period for
which data are available. (Effluent BOD 251 mg/1.) This appears to be
caused by inadequate treatment system design. In particular, the lack
of final clarification is noted.
Plant No. 146: Data available for this plant are not representative of
actual treatment plant performance. Available effluent data include
stormwater dilution.
Plant No. 176: There are only three months of data available for this
plant.
Plant No. 245: This plant has been rejected due to the use of a
nonbiological (air stripping) treatment system.
Plant No. 268: This plant was found to have high effluent BOD (248
mg/1) and BOD removal below 95% (93% BOD removal).
Plant No. 269: The treatment system of the plant has been upgraded and
no data are available for the upgraded system. Additions to the plant
in 10/77 included primary settling, equalization, increased secondary
clarification capacity and sludge handling modifications. Prior to
these modifications plant performance was poor (BOD removal 83%, efflu-
ent BOD 66 mg/1).
D-3
-------
Plant No. 274; A significant portion of flow treated by this plant is
sanitary wastewater.
Plant No. 294: Plant performance (effluent TSS 95 mg/1) is poor con-
sidering the level of treatment technology employed (activated sludge
followed by sand filtration).
D-4
-------
APPENDIX E
CAPDET Methodology
-------
appendix e
METHODOLOGY
The basic calculation tool used to develop alternative engineering costs
(with the exception of RBC costs) is the computer program, CAPDET (Com-
puter Assisted Procedure For The Design and Evaluation of Wastewater
Treatment Facilities).[E-l] The CAPDET computer model was developed
jointly by the Corps of Engineers Waterway Experiment Station, Vicks-
burg, Mississipi and the EPA Office of Water and Waste Management.
The major purpose of the CAPDET model is to provide for the rapid de-
sign, cost estimating and ranking by cost -of wastewater treatment plant
alternatives. The model can be applied to industrial wastewater treat-
ment system design, as well as Publicly Owned Treatment Works (POTWs),
with modifications of selected computer program default values.
The CAPDET model provides flexibility and accuracy while maintaining
ease of operation. The algorithm contains default values applicable to
all wastewater parameters. These default values enable complete waste-
water treatment design and costing by stipulating only average flow and
a list of the treatment schemes to be considered. Any value in the
CAPDET model (chemical data, cost data, unit operations parameters,
etc.) can be varied, however, to reflect more current information, more
localized cost data or specific waste treatment parameters applicable to
industrial wastewater treatment.
The CAPDET model is not designed to select and sequence unit operations
into a treatment system. The user must input a series of up to 20
"blocks" or waste treatment process functions into the model. Thus, the
user inputs the basic treatment scheme to be costed into the model.
In each treatment block, up to ten different treatment alternatives can
be considered. For example, a block containing complete mix activated
sludge could also contain conventional activated sludge, extended aera-
tion activated sludge, pure oxygen activated sludge and six other alter-
natives. The model will then design, estimate costs, and rank from
cheapest to most expensive all possible combinations. Further, the
model can also consider four separate treatment trains per run.
Another characteristic of the CAPDET model is its ability to consider up
to three modifications of each treatment process. The model contains
the process treatment parameters necessary to solve the unit process
equations, namely chemical default data for certain wastewaters and such
typical physical criteria as removal efficiency, overflow rate and aver-
age temperature. The CAPDET model allows the user direct access to any
of these parameters. In fact, the user can run three different versions
of any treatment process as alternatives in the same block or in differ-
ent blocks. An example would be checking in one run the impact on ef-
fluent quality and plant costs of changing the overflow rate of a clari-
fier. CAPDET, then, is able to consider many different alternative
treatment schemes, including multiple variants on one unit process.
E-l
-------
After the treatment process alternatives to be considered have been sel-
ected and input into the model, each possible alternative treatment
train is designed. The CAPDET model contains in its treatment catalog
64 large facility (>.5 MGD) and 23 small facility (<.5 MGD) unit proces-
ses, including sludge handling processes. Certain common industrial
processes (API oil separation, steam stripping etc.) were not included
in CAPDET because of CAPDET's original sanitary waste orientation. The
writers of CAPDET, however, have included as part of the model a process
known as the "dummy" process. To use this procedure, one calculates the
percentage reduction for any parameters affected by the applicable unit
process, plus any increase or decrease in effluent flow rate and sludges
due to the process. These numbers are entered in the model and the dum-
my process is treated as if it were a process in the CAPDET treatment
catalog. Like any other unit process, different modifications of the
dummy processes can be considered as treatment alternatives. This flex-
ibility enables the CAPDET model to simulate unit processes not in its
treatment process file.
As the CAPDET model lesigns all possible alternative treatment systems,
it determines the cost of each system. As with the design data, a com-
plete set of default unit construction, operation and maintenance cost
data are contained in the model. Thus, the cost of the treatment system
can be calculated. For each treatment process, secondary design calcu-
lations are performed by the computer to determine the specific amounts
of materials required: foundations, tanks, basins, walls and many other
items which are individually designed by the model to arrive at values
for such construction items as concrete, sand and gravel, size and
length of pipe, chemical use, number of valves and pounds of steel
plate. These items are then totaled for the specific treatment train
being considered and the construction coits are computed. Equipment
costs are calculated parametrically, with an attempt to optimize accu-
racy. The equipment cost data were provided by vendors of treatment
equipment. The parameter was chosen which best represented the cost of
that equipment as a straight line on a log-log plot (clarifier diameter
being a more appropriate parameter than total clarifier flow rate for
costing a clarifier mechanism). The total capital cost of the treatment
system is, therefore, a hybrid of construction design calculations and
parametric cost estimates.
Default values for all cost data are contained in the CAPDET model. As
with all other data in the model, however, the user has the option of
altering or updating the costs for nearly anything in the model. These
changes can be made in the following ways:
1. Equipment and construction default data are based on first quarter
1977 costs. The model updates these cost data to the present.
2. Equipment costs, operating costs, operating manhours per year and
construction material costs are all user selectable. Thus, if a
user knows that standard blower costs are lower or highter than the
default value in a particular area, then correct costs can be input.
If parametric cost curves are to be updated, the user inputs the
local cost for the standard sized unit (i.e., 90-foot clarifier
mechania- ) used in the model. The cost curve then will-be adjusted
E-2
-------
up or down, with the slope remaining unchanged. If local or current
data are input, they will not be updated again by one of the cost
indices.
3. Some costs are given as percentages of the total facility costs
(e.g., administrative costs and inspection costs). These percent-
ages can be changed depending on the judgment of the user or on
local conditions.
4. Other costs are also accessible to the user. CAPDET calculates
labor rates based on ratios with an Operator II rate. While these
ratios are not user selectable, the default Operation II rate is
alterable. Thus, the CAPDET model can account for variations in
labor costs.
The CAPDET model also has some optional cost items which can be included
as appropriate (i.e., special foundations, mobilization, site electrical
costs, lab and administration buildings, etc.).
The CAPDET model compares treatment alternatives rather than adding unit
operations until the effluent is below the desired efflent level. The
model calculates the expected effluent from each alternative train and
compares it with the desired effluent level. The model rejects those
alternatives that do not meet the desired effluent quality and ranks
(from the least expensive to the most expensive) the least expensive
hundred alternatives that meet the criteria.
The general design bases for the CAPDET model were:
1. Costs expressed as first quarter 1979 dollars.
2. Capital costs representing total equipment costs (installed),
contractor's overhead/profit, administration/legal expenses,
architectural/engineering design fees, inspection fees, con-
tingencies, technical costs and land costs.
3. Operating costs equal to the sum of costs for operating and
maintenance labor, power, materials, chemicals, and admini-
stration and laboratory expenses.
4. Equivalent annual costs representing the amortization of the
capital costs (capital*recovery plus interest) at 10 percent and
twenty years plus the annual operating costs.[E-2],[E3]
5. Design constants based on a statistical analysis of the mun-
icipal wastewater treatment industry as well as on literature
publicationฎ.[E-4]
6. Cost equations taken from correlations developed from data based
on municipally owned treatment plants.[E-5]
Unit price input data and details of the direct nonconstruction costs
are shown in Table E-l. Default waste characteristics present in the
E-3
-------
TABLE E -1-COST INPUT PARAMETERS (10 PERCENT, 20 YEARS)
COST INDEXES UNIT PRICES
Building
48.00
$/sq ft
Excavation
1.20
$/cu yd
Wall concrete (reinforced, in-place)
207.00
$/cu yd
Slab concrete (reinforced, in-place)
91.00
$/cu yd
Marshall and Swift Index (equipment cost)
577.00
Crane rental
67.00
$/hr
EPA Construction Cost Index
132.00
Canopy roof
15.75
$/sq ft
Labor rate (equipment installation)
13.40
$/hr
Operator Class II
7.50
$/hr
Electricity
0.04
$/kw hr
Chemical Cost
Lime
0.03
$/lb
Alum
0.04
$/lb
Iron salts
o.os
$/lb
Polymer
1.62
$/lb
Engineering News Record Cost Index
2886.00
Handrail, (in-place)
25.20
$/ft
Pipe Cost Index
295.20
Pipe installation labor rate
14.70
$/hr
Eight-inch pipe
9.08
$/ft
Eight-inch pipe bend
86.82
$/unit
Eight-inch pipe tee
128.49
$/unit
Eight-inch pipe valve
1346.16
$/unit
INDIRECT NON-CONSTRUCTION COSTS (AS % OF CONSTRUCTION COST)
Miscellaneous non-construction cost
Admin/legal
Inspection
Contingencies
Profit and overhead (contractor's)
Technical cost
5.0%
2.0%
2.0%
11.5%
22.0%
2.0%
E-4
-------
CAPDET model are summarized in Table E-2. Table E-3 lists removal
efficiencies of pollutants built into the program.
An evaluation of CAPDET suggests the following limitations:
1. CAPDET was originally designed for municipal wastewater plants and
therefore requires certain adjustments for industrial applications.
The characteristics of municipal raw wastewaters are normally more
consistent among different locations than those of industrial waste-
water, and the parameters relating to the treatability are more
applicable among the different locations than are the treatment
parameters of industrial wastewaters.
This permits the use of CAPDET for the POTW cost estimating without
changes in the default values. The use of CAPDET for evaluations
based on industrial wastewaters requires changes in the default val-
ues, particularly in the reaction rate constant, influent BOD con-
centrations, influent TSS, nutrient balances and other factors which
differentiate the composition of industrial wastewaters from muni-
cipal wastewaters.
2. The costs generated by CAPDET reflected grass roots installations.
This version of CAPDET is not capable of directly generating upgrade
costs for modifications or replacements of existing equipment. Many
OCPS plants may require only minor adjustments to current facilities
or management practices to reach proposed effluent targets. Al-
though these engineering options may be available to specific plants
to achieve the target effluent concentrations, CAPDET, as used in
this study, is limited to estimating the designs and costs for en-
tire wastewater treatment unit process additions (second stage
treatment).
3. Land requirements and administrative and laboratory costs calculated
by CAPDET are related to plant capacity rather than to discrete unit
operations. The relationship of costs to flow rate limits CAPDET in
the estimation of discrete (singular) units as opposed to entire
plant facilities. As a result, CAPDET predicts similar land costs
for clarification and an entire activated sludge unit for the same
flow rate. As a percentage of the total costs, land, administrative
and laboratory costs represent a small portion of an entire facility
estimate. For a single unit, these costs have a much greater
effect.
E-5
-------
TABLEE-2
CAPDET DEFAULT INFLUENT WASTE
CHARACTERISTICS
TEMPERATURE
18 ฐC
SUSPENDED SOLIDS
200
.MG/L
VOLATILE SOLIDS
60
% OF SS
SETTLEABLE SOLIDS
15
MG/L
B0D5
250
MG/L
SBOD
75
MG/L
COD
500
MG/L
SCOD
400
MG/L
PH
7,6
CATIONS
160
MG/L
ANIONS
160
MG/L
P04
18
MG/L
TKN
45
MG/L
nh3
25
MG/L
no2
0
MG/L
no3
0
MG/L
OIL AND GREASE
80
MG/L
E-6
-------
TABLE ฃ-3
WASTE CHARACTERISTIC REMOVAL DEFAULT
VALUES FOR CAPDET PROCESSES
WASTE CHARACTERISTIC REMOVALS
POR
OtL & Settle
PIIOCESS DOOj TSS COD GREASE TKN PHOS KHj SOLiC
Dissolved
Air
Flotation
Clarifica-
tion
Activated
Sludge
30%
32%
USER INPUT
INFLUENT
AND EFFLUENT
80%
58%
USER INPUT
TO SECODARY
CLAR1FIER
30%
40%
1.5 x BOD
EFF
10%
5%
30%
5%
30%
SET
EQUAL
TO TKN
Aerated
Lagoon
USER INPUT
INFLUENT
AND EFFLUENT
USER INPUT
TO SECONDARY
CLARIFfER
ASSUME
SAME AS ASL
Multimedia
Filtration
SET EFFLUENT
EQUAL TO
OODSOLUBLE
INFLUENT
60%
SET EFFLUENT
EQUAL TO
COฐSOLUBLE
INFLUENT
PASS ON
THROUGH
PASS ON PASS
THROUGH THROUGH
-------
APPENDIX F
Discrete Unit Cost Curves
-------
APPENDIX F - DISCRETE UNIT COST CURVES
1 GENERAL
This appendix supplements the engineering cost section of this report
(Section 8) with a detailed presentation of the discrete unit cost curves discussed in
Paragraph 8.2.3.
The curves presented contain costs for the treatment technology alterna-
tives considered in the plant-by-plant analysis for various influent and effluent
concentrations (mgA) and flow rates (MGD). The terms frequently listed on the
curves are defined as follows:
(1) Capital Costs are the costs representing the total installed equipment
costs, contractor's overhead/profit, administration/legal expenses, A/E design fees,
inspection fees, contingencies, technical costs, and land costs.
(2) Operating Costs are the costs equal to the sum of costs for operating and
maintenance labor, power, materials, chemicals, and administration and laboratory
expenses.
(3) Equivalent Annual Costs (Annual Costs) are those costs representing the
amortization of the capital costs (capital recovery plus interest) at 10 percent and
twenty years, plus the annual operating costs.
(4) M$t M$/yr are costs expressed as first quarter 1979 million dollars (per
year for operating and equivalent annual costs).
The procedure for obtaining the costs used for the plant-by-plant analysis,
is as follows:
F-l
-------
(1)
Locate the set of curves for the technology being considered.
(2) Look for the influent concentration (reported effluent) for BOD in the
upper right hand corner of the page among the various graphs. Note that solids
removed technologies are directly related to flow and that concentration levels are
only limiting conditions of the treatment alternative. The influent concentrations
are not listed on the graphs for solids removals alternatives.
(3) Select the capital cost (left axis) corresponding to the flow (bottom axis)
and effluent concentration (curve) from the capital, operating, and annual cost
pages. One cost should be obtained from each page for a given flow, influent BOD
and effluent BOD. The costs for solid removal are flow related and all three costs
can be obtained from one page for each technology alternative.
(4) Repeat this procedure for each target and continue for any plant being
considered.
(5) For influent concentrations, assume a 15 percent accuracy range. Occa-
sionally interpretation between two sets of costs may be required. This estimation
technique is within the accuracy of the costs.
The cost curves are presented for a variety of effluent BOD concentra-
tions for each biological alternative. Given a relative accuracy of 15 percent for
the BOD reported value, the cost curves are basically equivalent for BOD targets
with the same range. For example, the costs for a target of 50 mg/1 BOD are
approximately equivalent for targets ranging from 40 to 60 mg/1. The range for 30
mg/1 is 25 to 35 mg/1. For estimating purposes, the curves for 10 mg/1 represent
the 20 mg/1 target. In many cases, there is a lack of sensitivity in the costs for
changes in effluent targets at lower influent concentrations and flows. A
discussions of the sensitivities of the costs are provided in Section 8. The design
bases and cost model limitations are also discussed in Section 8.
From the information and bases presented in this appendix, additional
analysis of the plants may be pursued.
F-2
-------
FQttTVAIjEHTpMBE
Mi
FLOW (MILLION SAL/DAY)
FIGURE 1DISSOLVED AIR FLOTATION ANNUAL, CAPITAL AND OPERATING COSTS
F-3
-------
(WS/YR)
FLOW (MILLION GAL/DAY)
FIGURE 2SEDIMENTATION ANNUAL, CAPITAL AND OPERATING COSTS
F-4
-------
INFLUENT - 85 mg/L BOD
fSGjr^OrlanddO: mg/L p
FLOW (MILLION GAL/DAY)
FIGU RES 3ACTIVATED SLUDGE ANNUAL (85mg/l)
F-5
-------
INFLUENT = 85 mg/L BOO
50:^3^BfKt:40^ag;i"
FLOW (MILLION GAL/DAY)
FIGURE 4ACTIVATED SLUDGE CAPITAL COSTS (85 mg/D
F-6
-------
INFLUENT =85 mg/l SOD
FLOW (MILLION GAL/DAY)
FIGURE 5ACTIVATED SLUDGE OPERATING COSTS (85 mg/l)
F-7
-------
INFLUENT = 100 mg/L BOO
-50> 30,qnd10 "ig/L
FLOW (MILLION GAL/DAY)
FIGURE 6ACTIVATED SLUDGE ANNUAL COSTS (100 mg/l)
F-8
-------
INFLUENT * 100 mg/L BOO
,1 ฆ fl ซ ซ
FLOW (MILLION GAL/DAY)
FIGURE 7ACTIVATED SLUDGE CAPITAL COSTS (100 mg/1)
F-9
-------
INFLUENT - 100 mg/L BOD
;50^3d,-ar^]0_mg/l
FLOW (MILLION GAL/DAY)
FIGURE 8 ACTIVATED SLUDGE OPERATING COSTS (100 mg/1)
F-10
-------
INFLUENT" 150 mg/l BOD
:SCESnd3(Ji mg/L"
FLOW (MILLION GAL/DAY)
FIGURE 9ACTIVATED SLUDGE ANNUAL COSTS (150 mg/I)
F-ll
-------
INFLUENT a 150 mg/L BOD
U"omii30~ H19/L
FLOW (MILLION GAL/OAY)
FIGURE 10ACTIVATED SLUDGE CAPITAL COSTS (150 mg/1)
F-12
-------
INFLUENT = 150 mg/L BOD
50.gnd.3diins/L"
FLOW (MILLION GAL/DAY)
FIGURE 11ACTIVATED SLUDGE OPERATING COSTS (150 mg/1)
F-13
-------
INFLUENT ป 250 mg/L BOD
iQ~andr30 rag/L
ITl-
R.0W (MILLION GAL/DAY)
FIGURE 12ACTIVATED SLDDGE ANNUAL COSTS (250 mg/D
F-14
-------
INFLUENT = 250 mg/L BOD
iOTand'-SP"^/^:
FLOW (MILLION GAL/DAY)
FIGURE 13ACTIVATED SLUDGE CAPITAL COSTS (250 mg/D
F-15
-------
INFLUENT 3 250 mg/l BOD
50 /'
FLOW (MILLION GAL/DAY)
FIGURE 14ACTIVATED SLODGE OPERATING COSTS (250 mg/l)
F-16
-------
INFLUENT = 400 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 15
ACTIVATED SLUDGE ANNUAL COSTS (400 mg/1)
F-17
-------
INFLUENT = 400 mg/L BOO
5Oan
-------
INFLUENT = 400 mg/L BOD
-5Q_pnd-3,0. mg/L'
a ซ 7 i,
aOW (MILLION GAL/DAT)
FIGURE 17ACTIVATED SLUDGE OPERATING COSTS (400 mg/1)
F-19
-------
INFLUENT - 500 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 18ACTIVATED SLUDGE ANNUAL COSTS (500 mg/1)
F-20
-------
INFLUENT - 500 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 19ACTIVATED SLUDGE CAPITAL COSTS (500 mg/1)
F-21
-------
INFLUENT ฆ 500 mg/l BOO
FLOW (MILLION GAL/DAY)
FIGURE 20ACTIVATED SLUDGE OPERATING COSTS (500 mg/l)
F-22
-------
BOO INFLUENT - 1,000 mg/L
I7 Iซ* * 4 * ซ
FLOW (MILLION 6AL/0AY) mg/L
FIGURE 21ACTIVATED SLUDGE ANNUAL COSTS (1000 mg/1)
F-23
-------
INFLUENT - 1,000 mg/L BOO
ev J-~' ~ i=rr-=--
ja 14 i* n <: ft jmj* j
FLOW (MILLION GAL/DAY)
14*
FIGURE 22ACTIVATED SLUDGE CAPITAL COSTS (1000 mg/1)
F-24
-------
INFLUENT - 1,000 mg/L BOO
FLOW (MILLION GAL/DAY)
FIGURE 23ACTIVATED SLUDGE OPERATING COSTS (1000 mg/1)
F-25
-------
INaUENT - 1.500 mg/l BOD
FLOW (MILLION GAL/DAY)
FIGURE 24 ACTIVATED SLDDGE ANNUAL COSTS (1500 mg/l)
F-26
-------
INFLUENT- 1500 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 25ACTIVATED SLUDGE CAPITAL COSTS (1500 mg/D
F-27
-------
INFLUENT - 1500 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 26ACTIVATED SLUDGE OPERATING COSTS (1500 mg/1)
F-28
-------
INFLUENT - 2000 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 27ACTIVATED SLUDGE ANNUAL COSTS (2000 mg/l)
F-29
-------
INFLUENT =ป 2000 mg/L BOD
1 J .ป , .7
FLOW (MILLION GAL/DAY)
FIGURE 28ACTIVATED SLUDGE CAPITAL COSTS (2000 mg/1)
F-30
-------
INFLUENT = 2000 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 29ACTIVATED SLUDGE OPERATING COSTS (2000 mg/1)
F-31
-------
INFLUENT = 100 mg/L BOD
y, yO^.and7" 1 (X rng/L
ซ ซ ? to
FLOW (MILLION GAL/DAY)
FIGURE 30AERATED LAGOONS ANNUAL COSTS (100 mg/1)
F-32
-------
INFLUENT * 100 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 31AERATED LAGOONS CAPITAL COSTS (100 mg/1)
F-33
-------
INFLUENT - 100 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 32 AERATED LAGOONS OPERATING COSTS (100 mg/1)
F-34
-------
INFLUENT = 200 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 33
AERATED LAGOONS ANNUAL COSTS (200 mg/1)
F-35
-------
INFLUENT =ป 200 mg/L BOO
FLOW (MILLION GAL/DAY)
FIGURE 34AERATED LAGOONS CAPITAL COSTS (200 mg/1)
F-36
-------
INFLUENT = 200 mg/L BOD
a
50r"30r?nii"t
-------
INFLUENT = 500 mg/L BOD
J m id
FLOW (MILLION GAL/DAY)
FIGURE 36AERATED LAGOONS ANNUAL COSTS (500 mg/1)
F-38
-------
INFLUENT = 500 mg/L BOD
50y mg/L
FLOW (MILLION GAL/DAY)
FIGURE 37AERATED LAGOONS CAPITAL COSTS (500 mg/D
F-39
-------
INFLUENT = 500 mg/L BOO
5U "'9/'-
FLOW (MILLION GAL/DAY)
FIGURE 38AERATED LAGOONS OPERATING COSTS (500 mg/1)
F-40
-------
INFLUENT = 1000 mg/L BOD
* ป *!.
FLOW (MILLION GAL/DAT)
FIGURE 39AERATED LAGOONS ANNUAL COSTS (1000 mg/D
F-41
-------
INFLUENT ป 1000 mg/L BOD
3^ 50?36^ncfc4O: ng/L
FLOW (MILLION GAL/DAT)
FIGURE 40AERATED LAGOONS CAPITAL COSTS (1000 mg/1)
F-42
-------
INFLUENT = 1000 mg/L BOO
5rฎEtihtiฃ^ngK: z
FLOW (MILLION GAL/OAY)
FIGURE 41AERATED LAGOONS OPERATING COSTS (1000 mg/1)
F-43
-------
FLOW (MILLION GAL/DAY)
FIGURE 42ROTATING BIOLOGICAL CONTACTORS ANNUAL COSTS
F-44
-------
FLOW (MILLION GAL/DAY)
FIGURE 43ROTATING BIOLOGICAL CONTACTORS CAPITAL COSTS
F-45
-------
aOW (MILLION GAL/DAY)
FIGURE 44ROTATING BIOLOGICAL CONTACTORS OPERATING COSTS
F-46
-------
CAPLIAL_CDSTฃ.J (liฃs)
EQUIVALENT ANNUAL COSTS-(lOWTR)
ฆ^QEERftT I USSAMfliMA IMT
.^TOSISEtllfeflR
,$+ J* i?
T
FlOW (MILLION GAL/DAY)
FIGURE 45
MULTI-MEDIA FILTRATION ANNUAL, CAPITAL AND OPERATING COSTS
F-47
-------
APPENDIX G
Wastestream Data Listing
-------
WASTE STREAM
DATA LUTING - 8UBCATE60RIZATI0N FILE
1
SUeCATaPLASTlCS ONL*
I
plant
FLOMINF
FLOHEPF
BOOINF
BOOEFF
COOINF
CODEFF
T83INF
TS3EFF
number*
# PP
(NfiO)
(H60)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
mmmmm
ซ
ซ
c
ซ
1
ซ
2
2
1.83
1.83
3.00
10.00
27,00
3
0.29
0,30
1394.00
45.00
2000.00
113.00
22.00
32.00
4
3
0.07
237.00
7
2
0.04
12542.00
16549.00
1055.00
9
2
0.07
0.07
116.00
6,00
26.00
31.00
10
3
0.71
0.76
7.00
30.00
14.00
11
1
11
0.50
0.20
t
12
1
.
*
13
2
2.00
.
14
3
0.00
.
17
3
0.05
0.05
1200*00
52.00
2376.00
166.00
30.00
17
3
.
.
19
s.ao
3.80
237.00
7.00
470,00
15.00
25
4
0.17
0.16
9.00
42,00
42.00
31.00
12.00
27
10.60
10.70
131.00
23.00
258,00
120.00
38,00
25.00
29
2
8.70
8.70
114.00
7.00
210.00
115.00
66,00
114.00
30
3
0.04
.
ซ
33
1
5.24
5.22
34
1
0.06
0.06
666.00
35.00
1669.00
194.00
23.00
3S
1
0.70
366.00
416.00
0,30
39
4
0.39
0.39
6.00
ซ
9.00
44
1
0.67
0,67
754.00
9.00
1234.00
63.00
2696.00
22.00
45
2
2.22
2.22
390.00
3.00
639.00
57.00
285,00
24.00
46
2
t
V
47
5
ซ
47
.
t
46
1
52
0.86
0.86
104.00
6.00
67.00
t
13.00
54
1
0.20
0.22
424.00
30.00
657.00
116.00
49,00
43.00
56
1
0.01
1661.00
6062.00
260,00
56
1
62
0.00
65
3
6.70
8.70
369.00
16.00
710.00
110.00
153,00
52.00
67
1
t
66
2
70
2
73
3
0.25
0.25
14.00
3.00
473.00
o
o
<0
1359,00
11.00
TOCINF
(PPM)
TOCEPF
(PPM)
464
3!
1936
00
00
42
74
00
00
00
17
00
00
*Note: Each line entry represents a separate waste stream. Plant code numbers are repeated for
plants with multiple waste streams.
-------
HASTE STREAM
DATA LISTING - SUBCATEGORYATI ON FILE
2
SUBCATซPU3TIC8 ONLY
PLANT
FLONINF
floweff
BOOINF
BOOEFF
CODINF
CODEFF
TSSINF
TSSEFF
TOCINF
TUCEFF
NUMBER
ซ PP
(HGO)
(HGO)
(PPH)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPH)
ฆฆป
ซ
VMM
ป
MM
*ซ
75
2
0.42
0.42
170.00
24.00
876.00
176.00
77
4
0.94
0.94
2.00
2.00
27.00
27.00
10.00
10,00
77
*
0.01
.
095.00
40.00
16.00
t
77
.
.
78
1
.
.
79
2
0.03
.
.
0
0
8?
3
.
.
82
.
.
t
84
1
0.14
0.14
.
84
1
0.68
0.60
.
t
9
89
4
1.71
1.71
979.00
40.00
1908.00
620,00
101.00
76,00
t
ซ0
2
2.74
2.74
51.00
4.00
97.00
15,00
20.00
IS,00
91
2
2.06
2.06
174.00
10.00
329.00
69.00
79.00
84,00
91
0.47
.
.
.
.
*
93
1
0.12
0.12
80.00
15.00
504.00
146.00
205.00
78,00
96
1
3.00
3.00
120.00
3.00
.
.
24.00
19,00
too
1
1.00
1.00
424.00
15.00
607.00
90.00
106.00
37,00
100
1
0.85
0.B5
.
10,00
.
.
.
4,00
104
7
i.5ซ
1.54
1002.00
11.00
1557.00
115.00
62.00
60,00
434.00
5,00
104
0.10
.
.
.
.
,
.
104
.
.
.
.
*
.
104
.
.
.
*
.
105
1
0.30
0.30
1047.00
6.00
2689.00
131,00
61.00
35,00
10b
6
5.95
5.95
94.00
11.00
179.00
53,00
.
,
107
1
2.16
2.55
215.00
47.00
403.00
172.00
142,00
127,00
.
109
3
1.57
1.57
427.00
12.00
864.00
151.00
63.00
290,00
96,00
111
1
0.93
0.93
95.00
6.00
272.00
37,00
43,00
10.00
,
119
1
l.*5
1.65
12.00
10.00
73.00
58,00
36,00
26.00
25,00
19,00
123
2
0.20
0.20
807.00
96,00
81.00
16.00
.
124
2
0.36
0.30
560.00
37.00
874.00
61,00
83,00
22.00
.
125
2
0.52
0.52
1764.00
45.00
3173.00
205,00
187,00
30.00
126
3
0.35
0.35
1021.00
0.00
2292.00
102,00
561,00
26,00
.
129
3
.
131
1
0.00
.
132
1
0.20
0.20
21.00
130,00
11.00
140
2
.
140
.
t
146
5
0.35
0.35
107.00
6.00
1681.00
45,00
2547,00
23.00
-------
NASTE STREAM
data listing - SUBCATEGORIZATION file
3
SUBCATaPLASTICS ONLY
PLANT
NUMBER
# PP
FLOHINP floheff bodinf bodeff cooinf cooeff tssinf tsseff tocinf toceff
(M6D) (HGD) (PPM) (PPH) (PPH) (PPM) (PPH) (PPH) (PPM) (PPH)
ฃ75
I
CO
147
146
150
152
152
151
155
155
155
156
157
161
167
168
ITS
17ft
179
184
185
164
192
194
196
197
197
198
199
199
200
200
202
207
209
210
210
211
212
217
0.30
0.29
1000
00
9.00
2152
00
80
00
868
00
29.00
.
.
0.S8
0.63
447
00
43.00
124
00
11.00
1.96
1.96
7.00
58
00
21.00
0.06
0.06
4.00
49
00
16.00
0.07
0
10.70
0.50
0
1.06
0.06
14
00
0
1.72
1.31
18.00
37
00
52.00
*
0.00
.
.
.
0.00
.
8500
00
.
0.09
0.09
372
00
9.00
1178
00
62
00
14.00
0.48
0.48
378
00
10.00
1195
00
190
00
78
00
37.00
1.02
1.02
16.00
65
00
26.00
0.32
0.32
86^00
334
00
seloo
0.13
0.11
883
00
21.00
1686
00
186
00
90.00
0.39
0.39
7
00
7.00
10
00
10.00
3.70
.
t
3.70
50
00
24.00
218
00
127
00
31
00
17.00
.
.
.
.
o!oo
0.00
#
t
0.15
0,15
20.00
85
00
16.00
oloo
A
36
00
1.27
.
1.27
9.00
0
8.00
otoo
83
28
0.03
o|o3
3520
00
20.00
4338
00
00
00
7.00
800
1578
2751
00
00
00 15
00
-------
pp
1
1
2
t
I
5
2
1
3
I
t
1
1
0
3
1
!
1
1
4
3
2
3
3
2
3
3
2
I
4
WASTE STREAM
DAT* LISTING SUBCATC6ORIZATI0N FILE
SUBCATaPLASTlCS ONLY
FIOWINF
(HGD)
FLOWCFF
(M60)
80DINF
(PPH)
BODEFF
(PPM)
CODINF
(PPH)
COOEFF
(PPH)
TS8INF
(PPM)
TSSEFF
(PPM)
mmmmmm
mm
mmm
mmm
"
mmm
oloo
o.7a
0.74
IS
00
16
00
0.07
0,07
400,00
32
00
520
00
64
00
207
00
64
00
0.17
0.17
0.09
478.00
1422
00
t.ป7
I.IT
204.00
6
00
405
00
77
00
00
ie
00
olbo
0?*0
*1 loo
36
00
109
00
75
00
0.70
0.70
0.00
0.10
0.10
0.00
0.46
0.40
572.00
99
00
1219
00
455
00
00
90
00
0.03
0.04
4
oo
16
00
8
00
0.03
0.03
00
5
00
oles
o',*ป
11ซป loo
14
00
531
00
85
00
64
00
19
00
0.31
0.31
608.00
56
00
3060
00
323
00
271
00
179
00
0.00
3.ซe
3.9ฎ
470,00
34
00
900
00
353
00
6
00
97
00
2.ซ7
2.30
291.00
16
00
1693
00
94
00
40
00
45
00
0.00
1.50
1,50
7
00
6
00
O.SO
TOCINF
(PPM)
TOCEFF
(PPM)
100
00
71
00
-------
haste stream
DATA LISTING - SUBCaTEGORIZATION FILE
5
PLANT
FL0ซINF
FLOMEFF
NUMBER
(M60)
(MfiD)
20
0.72
0.72
20
.
31
1.10
1.10
36
0.06
0.06
41
.
41
.
43
.
43
.
49
0.99
.
51
.
55
0.90
.
57
3.11
3.10
60
5.03
5.07
61
2.43
2.43
T 62
2.13
1.35
tn 74
2.34
2.34
74
.
74
76
18.36
15.80
80
29.70
29.00
84
0.55
0.55
84
0.27
0.27
84
t
84
6.67
6.66
84
0.27
0.27
88
1.33
1.33
95
.
98
2.11
2)00
98
98
.
99
.ฆ
102
2.75
2.75
103
12.20
12.20
108
2.80
#
no
2.04
2,04
112
0.82
0.82
113
17.46
16.70
114
3.92
4.80
SUBCATaNOT P, TYPE UC# KATERUSE >.165 6AL/LB
BOOIMF
BODEFF
CODINF
(PPM)
(PPM)
(PPM)
2113.00
190.00
5370
00
997)00
22)00
2404
00
2527.00
393.00
5629
00
27632
00
6022*00
10037
00
1385.00
38.00
1488
00
501.00
41.00
3B2.00
81.00
862
00
199.00
68.00
.
582*00
.
15)00
1327
00
153.00
10.00
.
299*00
.
54)00
1407^00
64)00
2454
00
793^00
53)00
.
562
00
850)00
.
15)00
53
319.00
19.00
00
1506.00
1177.00
1719.00
B23.00
6.00
53.00
28.00
IS.00
2883
00
COOEFF
(PPM)
725
294
2448
201
189
162
351
28
55
135
00
00
00
00
00
00
00
00
00
00
TSSlNF
( PPM)
62
1946
459
27
23
57
72
36
73
00
00
00
00
00
00
00
00
00
TSSEFF
(PPM)
TOCINF
(PPM)
TOCEFF
(PPM)
71
00
148
00
11006
00
3613
00
118
00
88
00
469
00
159
00
268
00
135
00
20
00
473
00
23
00
36
00
332
00
64
00
9
00
142
00
1205
00
118
00
50
00
39
00
505
00
34
00
128
00
28
00
13
00
26
00
685
00
69
00
21
00
793
00
61
)0
62
00
513
00
61
00
-------
WASTE STREAM
DATA LI8TING - SUBCATEG0RIZAT10N FILE
0
1
PLANT
NUMBER
127
134
134
135
135
136
136
137
137
139
13 9
141
141
142
142
143
cr> i4j
156
160
175
176
160
160
167
190
193
195
206
215
216
216
220
222
226
234
235
236
236
SUBCATiKOT P# TYPE Itc# HATERUSE >.165 6AL/LB
FLOWJNF
(1G0)
FLOWEPF
(MCD)
60DINF
(PPH)
B00EFF
CPPH)
COOINF
(PPH)
COOEFF
CPPH)
T88XNF
(PPM)
T35EFF
(PPH)
T0CINF
(PPM)
1.13
1.13
664
00
127.00
653
00
535.00
43
00
46.00
ฆ
.
t
.
t
ซ
.
.
.
.
*
.
.
.
t
t
.
0.40
0.37
61.00
4329
00
590.00
66.00
0.55
0.49
5710
00
65.00
6757
00
220,00
26
00
104,00
0.69
0.69
443
00
40.00
993
00
322.00
1.07
1.07
2507
00
40.00
660
00
169,00
3.00
t
14960
00
23744
00
8066
00
1.66
1.66
2629
00
127.00
4016
00
523.00
170,00
0.26
0.26
9
00
9,00
23
00
0.30
0.30
537
00
537.00
1577
00
1577.00
9
00
9,00
6.50
6.50
559
00
24.00
96
00
42,00
336
00
4.47
4,47
41.00
334.00
S3,00
.
0.09
0.09
2400
00
19.00
.
29,00
t
.
.
0.09
0.09
3741
00
50.00
6176
00
366.00
344
00
95,00
0 ,46
0.33
603
00
366.00
2976
00
654.00
16,00
3.75
3.75
63.00
364.00
76,00
3112
00
7.95
7.91
546
00
12.00
1354
00
199.00
5.10
5.10
69.00
2605
00
367.00
426
00
235,00
719
00
4.06
4.06
37.00
193.00
65,00
334
00
.
T0CEFF
(PPM)
196,00
23
100
00
00
53
00
-------
WASTE STREAM
DATA IIBTIN6 SliBCATCCORIZATION FILE
7
SUBCATiNOT P, TYPE I1Cซ MATERU8E >.165 SAL/LB
PLANT
number
pp
FLO*INF
(MGO)
FLOWEFF
(MGO)
BOOINF
(PPM)
BODEFF
(PPM)
codinf
(PPH)
CODEFF
(PPM)
TSSINF
(PPM)
TSSEFF
(PPM)
TOCINF
(PPM)
TOCEFF
(PPH)
248
2
2.01
1.60
4490.00
72.00
6334.00
217.00
66
00
74.00
3202
00
73
00
249
5
0.66
0,66
12.00
5141.00
120.00
19.00
257
6
0.62
0.62
1211.00
103.00
.
.
66.00
260
6
0.27
.
.
272
IS
3.99
(.25
970.00
22.00
2169.00
147.00
66,00
695
00
74
00
274
3ซ
~.M
450.00
1122.00
.
103
00
262
00
276
6
0.95
0.95
.
.
.
256.00
132.00
-------
pp
>ซ
4
6
S
3
21
10
10
2
3
1
ซ
10
5
31
20
2
3
3
9
2*
1ป
3
HASTE STREAM
DAT* LISTING - SUBCATEG0RI2ATI0N FILE
SUBCATBhOT P, TYPE ItC# WATERU8E<ซ. 165 GAL/LB
FLONINF
FL0ซEFF
BOO INF
BOOEFF
CODINF
codeff
TSSINF
T33EFF
(mgd)
(hgd)
(PPM)
(PPH)
(PPM)
(PPM)
(PPM)
(PPM)
9
I
1
1
fl
I
1
WWW
a
i
i
i
0.02
9
ง
1.30
670.00
960.00
61.00
0.01
0,01
.
0.05
0,05
5961.00
360.00
3663.00
541.00
I.01
1,01
7.00
34.00
0.38
0.25
3913.00
33.00
276.00
74.00
0.12
0.66
t
t
0.07
0.01
0.56
0.56
891.00
466.00
5496.00
4079.00
194,00
6.74
6.74
43.00
43.00
271.00
271.00
12.00
12.00
0.27
.
.
0.12
0.11
104.00
.
0.26
0.30
268.00
.
140,00
0.00
0.12
0.12
.
0.49
0.49
251.00
3091.00
583.00
250.00
0.05
52554.00
67095.00
.
0.03
0.03
3977.00
154.00
8237.00
638.00
2.22
2.22
208.00
16.00
.
.
0.26
*
20000.00
.
1.23
.
25000.00
.
1.00
1.00
1076.00
36.00
9229.00
240.00
*110.00
45.00
0.01
21425.00
.
62383.00
.
0.02
0.02
111.00
11360.00
1176.00
665,00
395.00
0.05
0.05
2514.00
30.00
3514.00
545.00
105.00
0.01
0.01
t
9.00
.
60.00
37,00
0.35
.
5618.00
.
m
2.50
2.50
4647.00
246.00
8060.00
1069.00
1.72
1.12
3015.00
39.00
5842.00
222.00
150.00
0.11
.
.
.
0.01
0.01
.
21176.00
249.00
265,00
111.00
-------
HASTE STREAM
DATA LISTING 8UBCATESORIZATION FILE
9
SUBCATbNOT P# TYRE ISNOT C
plant
FL0*I*IF
floheff
B0DINF
BODEFF
C0DINF
CODEFF
T36XNF
TSSEFF
T0CINF
TOCEFF
number
ซ PP
(M60)
(M6D)
(PPM)
(PPM)
(PPM)
(PPH)
(PPH)
(PPM)
(PPH)
(PPM)
mmmmm
mmmmmm
mmmmmm
mmmmmm
1
9
0.66
0,66
1137,00
47,00
2073,00
354,00
494,00
62.00
IS
9
2.44
2.44
609.00
23.00
1622.00
360,00
16
6
4.60
4.60
632.00
523,00
604,00
276,00
16
2
0.64
.
93,00
22
11
2.49
2.49
.
16.00
175.00
36,00
22
0.22
761.00
.
1810,00
0
364,00
26
6
4.03
.
26
4
3.57
3.57
279.00
31.00
210,00
63,00
30,00
13,00
32
9
0.02
0.03
647,00
60.00
5546,00
2666,00
36,00
2056,00
35
3
0.06
0,06
9,00
9,00
26,00
26,00
1.00
1,00
53
3
2.26
2.26
1201,00
26,00
117,00
74,00
64
3
0.66
0,66
655,00
13.00
654,00
30,00
991,00
13,00
69
3
.
.
f
t
03
17
.
.
5
4
0.31
0.30
30.00
616,00
67,00
67
6
0.64
0.04
*
#
431,00
42.00
67
0.05
*
141,00
67
.
117
11
3.60
3.60
11.00
120,00
40,00
13,00
t
14,00
116
16
7.16
7.16
467.00
13.00
126
5
3.36
3.36
200.00
26.00
300,00
105,00
56,00
36,00
75.00
26,00
126
*
130
6
32.05
32.10
62.00
17.00
6,00
149
15
0.30
t
3044.00
*
11966,00
33,00
159
1
0.64
0.64
16.00
.
t
22,00
162
3
0.06
42,00
.
14.00
164
12
0.36
0,36
2436,00
62,00
3449,00
335,00
177,00
106,00
96,00
165
15
0.00
.
t
170
22
2.90
2,90
349,00
26.00
t
171
16
1.46
i.44
26,00
46,00
272,00
60,00
176
7
2.60
2.76
1327.00
166.00
3067,00
713,00
76,00
971.00
501,00
183
11
3.10
3.32
76,00
9,00
v
t
32^00
19,00
66.00
19,00
163
0.36
t
130.00
164
11
0.22
0.22
12.00
46,00
.
191
6
0.00
76o)oO
,
201
0.02
0.02
2666.00
760.00
32476,00
11000,00
651,00
203
4
0.11
0.11
2725,00
161,00
7957,00
1697,00
164,00
147,00
204
24
0.16
0,16
25.00
99,00
35,00
-------
WASTE STREAM
DATA LISTIN6 8UBCATEG0RIZATI0N FILE
10
SUBCATaNOT P, TYPE IปN0T C
plant
ซ PP
FlOnINF
FLOWEFF
600INF
80DEFF
CODINF
CODEFF
TSSINF
T8SEFF
T0CINF
TOCIff
number
(M60)
CGP)
(PPH)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPH)
CPPH)
mmmmm
-----
mmm
m
mmmmmm
a
213
3
0.00
9
213
3
ฆ
230
3
0.42
0.32
129
00
115,00
423
00
365,00
170
00
13.00
143.00
116.00
230
6
0.34
209
00
612
00
267
00
175.00
256
4
0.17
0.17
20,00
100,00
36,00
256
0.00
#
259
12
0.03
0,03
13.00
75,00
24,00
263
16
0.01
0,03
37.00
13060
00
226,00
31,00
5226.00
132.00
264
6
1.60
1,60
266
00
17.00
333
00
40,00
133
00
27.00
67.00
7.00
266
S
0.40
.
269
20
4.31
ซ.3l
630
00
66,00
472
00
71.00
667,00
176,00
275
11
0.14
0,14
116
00
116,00
60
00
60.00
261
12
1.00
1,00
66
00
11,00
ง
CD
263
4
.
ง
#
* .
264
9
0.33
0.33
2960,00
16,00
O
266
6
0.00
266
3
.
-------
NASTE STREAM
data LISTING SU0CATE6ORIZATION FILE
11
cn
i
PLANT
floซinf
FLOhEFF
BODlNP
8UBCATaN0T
60DEFF
NUM6ER
PP
(MCD)
(M6D)
(PPH)
(PPM)
mmmmm
5
5
0,37
0.37
6
1
0.01
0.01
279,00
6
2
0.06
0,06
104,00
6
6
1
0,14
0,14
17,00
16
3
4,39
4,39
330,00
10,00
21
5
4,09
4,09
12.00
23
3
0.54
24
4
0.43
0,43
59
7
1.46
l.ซ6
520,00
24.00
66
2
1.35
1.40
12.00
71
4
72
6
1.43
l.ซ3
66
6
1.26
1.26
50.00
92
5
4.36
4.36
4,00
92
0.04
94
22
40.00
40.00
160,00
a.oo
97
2
0.66
0.66
429.00
14.00
101
10
7.50
7.50
101
10
0.13
.
115
13
0.74
.
116
14
13.90
13.90
120
1ซ
19.16
19.90
95,00
6,00
121
4
0.09
0,09
6,00
121
122
3
2.00
2,00
27,00
129
131
0.00
133
6
.
144
5
0.95
0,95
27,00
145
*
1.57
1.57
42.00
151
2
3.00
3.00
22,00
151
4
a
153
3
0.33
0.33
122,00
166
1
0.01
t
169
5
0.01
26l|oO
172
6
2.60
161
6
0.01
1439.00
CODINF
(PPN)
590
5466
216
694
266
266
744
1364
17186
00
00
00
00
00
00
00
COUEFF
(PPM)
43.00
1045,00
241,00
22,00
65,00
40.00
110*00
75.00
UUOO
39.00
276*00
89*00
66,00
6^00
413,00
252,00
102,00
162^00
T3SINF
(PPM)
17
111
121
136
34
19
1266
00
00
106
7554
00
00
00
00
00
00
00
TSSEFF
(PPM)
7,00
37100
19^00
29,00
2,00
24,00
442,00
13,00
10,00
101I00
76,00
15.00
32,00
16,00
51^00
34,00
37,00
16,00
42^00
TOCINF
(PPM)
502
194
35
66
92
00
00
9592
00
00
00
00
00
TOCEFF
(PPM)
17,00
133
21
16
34
46
41
62
00
-------
NASTE STREAM
DATA LISTING - SUBCATEGORIZATION FILE
12
SUBCATsNOT P, NOT TYPE I
plant
FLOWINF
flokeff
B0DINF
bodeff
C0DINF
CODEFF
TS3IHF
TS3EFF
TOCINF
number
PP
(MGO)
(MGO)
(PPM)
(PPM)
(PP H)
(PPM)
CPPM)
(PPM)
(PPM)
mm9mm
------
161
1
.
.
162
0.53
0.55
236.00
36.00
65,00
26,00
492.00
166
0.32
0,33
162.00
5.00
5224.00
146.00
670.00
20.00
205
3
0.00
0.01
.
14.00
159,00
154,00
206
11
0.54
0.45
316.00
27,00
456.00
139,00
41.00
175.00
214
7
t
ฆ
226
10
1.36
1.20
461.00
23.00
1979,00
250.00
1225.00
55.00
231
2
0.1S
0.16
1743,00
772,00
4556.00
1326,00
647,00
21.00
1455.00
245
15
0.26
12.00
1196,00
16,00
247
10
3.10
3.10
3.00
260,00
69,00
26,00
252
10
o.u
2956,00
252
0.24
252
0.67
27672,00
33176.00
0
255
8
0.40
0.40
31.00
16,00
t
0
1
256
5
0.01
0.01
ft
51.00
243.00
37,00
261
2
0.10
0.10
.
t
t
ro
270
4
0.97
0.95
143.00
17.00
345,00
51.00
204.00
12.00
276
6
t
285
9
1.60
t
290
3
0.10
193.00
546,00
61.00
161,00
291
1
.
t
TOCEFF
(PPM)
61
SIS
IS
70
00
00
00
00
-------
2
3
4
T
9
10
II
11
12
13
14
17
17
19
25
27
29
so
33
34
35
39
44
45
46
47
47
48
52
54
56
58
62
65
67
68
70
73
toASTE STREAM
DATA LISTING - SUBCATEGORIZATION FILE
........ SUBCATbPLASTICS only ซซ
ORGANIC
PLASTIC
PP
pp
OTHER
NTF
1
I
1
1
I
0
2
0
8SK
0
2
0
ASL
0
2
1
OP"
0
2
0
LAP
0
2
0
ASL
0
3
0
ALA
0
1
0
BAN
0
0
0
CLR
0
1
0
BRN
0
2
0
RTE
0
3
0
CON
0
3
0
RBC
0
0
0
CON
0
5
3
ASL
0
1
0
CLR
0
3
2
ASL
0
1
1
ASL
0
2
1
CON
0
1
0
PCF
0
1
0
ASL
0
1
0
BRN
0
4
0
ASL
0
1
0
ASL
0
2
0
ASL
0
2
0
RTE
0
5
0
BRN
0
0
0
CON
0
1
0
RTE
0
2
0
ASL
0
1
0
RbC
0
1
0
IMP
0
1
0
RTE
0
1
0
IMP
0
2
I
ASL
0
1
0
DRY
0
2
0
DRY
0
2
0
DRY
0
2
1
ASL
-------
I
75
77
77
77
78
79
62
62
eซ
64
69
90
ซ1
91
93
96
100
100
104
104
104
104
105
106
107
109
111
119
123
124
125
126
120
151
1)2
1 AO
140
146
WASTE stream
DATA LISTIN6 8UBCATEGORIZATION FILE
SU8CATปPLA8TIC8 ONLY
ORGANIC PLASTIC
pp
OTHER
WTP
DI8CHA
mmmm
mmmmm
0
2
0
TRF
DIR
0
4
0
NOT
OIR
0
0
0
I HP
ZERO
0
0
0
0L8
OIR
0
1
0
EVP
ZERO
0
0
OPw
ZERO
0
3
0
6RN
ZERO
0
3
0
DRY
ZERO
0
1
0
CLR
OIR
0
1
0
OLS
DIR
0
4
0
ASL
OIR
0
2
0
RBC
OIR
0
2
0
ASL
OIR
0
0
I HP
ZERO
0
1
0
ASL
DIR
0
1
0
ASL
DIR
0
2
0
ASL
OIR
0
0
0
ARL
OIR
0
7
0
A6L
OIR
0
0
0
DP*
ZERO
0
0
0
IHP
ZERO
0
0
0
NEU
DIR
0
0
ASL
OIR
0
1
ALA
OIR
0
1
0
ASL
OIR
0
3
0
A8L
OIR
0
1
0
ASL
DIN
0
0
OLS
OIR
0
1
1
ASL
DIR
0
2
0
ASL
OIR
0
2
0
ASL
DIR
0
3
0
ASL
DIR
0
3
0
CON
ZERO
0
1
0
CON
ZERO
0
1
0
ALA
DIR
0
2
0
ORY
ZERO
0
0
0
RTE
ZERO
0
4
1
ASL
DIR
-------
WASTE STREAM
DATA LISTING - SUBCATEGORYATION FILE
SUBCATaPUASTICS ONLY
PLANT
ORGANIC
PLASTIC
number
PP
pp
OTHER
ntf
DISCHARGE
mmmmm
a
1
147
0
2
1
ASL
DIR
146
0
1
0
DRY
ZERO
ISO
0
J
I
ALA
DIR
152
0
1
0
CLR
DIR
152
0
1
0
CLR
DIR
154
0
1
CON
ZERO
155
0
2
DRY
ZERO
155
0
0
0
RTE
ZERO
155
0
0
0
CON
ZERO
156
0
0
8SK
DIR
157
0
1
0
ASL
DIR
1*1
0
0
DRY
ZERO
167
0
1
0
CON
ZERO
160
0
1
0
UNK
UNK
173
0
1
CON
ZERO
174
0
4
3
ASL
DIR
17*
0
1
ASL
DIR
104
0
4
0
SSK
DIR
165
0
1
0
CON
ZERO
IS9
0
1
0
ALA
DIR
192
0
1
ASL
DIR
194
0
1
1
NOT
DIR
196
0
1
0
CLR
DIR
197
0
0
RTE
ZERO
197
0
1
0
BRN
ZERO
198
0
1
0
DRY
ZERO
199
0
0
RTE
ZERO
199
0
1
0
RTE
ZERO
200
0
1
0
BRN
ZERO
200
0
0
0
IMP
ZERO
202
0
1
0
ARL
DIR
207
0
0
DRY
ZERO
209
0
1
0
BRN
ZERO
210
0
0
ASL
DIR
210
0
0
0
BRN
ZERO
211
0
1
0
LAP
ZERO
212
0
4
0
LAP
ZERO
217
0
2
0
ASL
DIR
-------
WASTE STREAM
DATA LISTING - SUSCATEGORIZATION FILE
16
SUeCATซPLASTlC8 ONLY
plant
ORGANIC
PLASTIC
number
PP
pp
OTHER
NTP
DISCHARGE
mmmmm
ซ
1
221
0
1
0
DRY
ZERO
221
0
0
0
CON
ZERO
223
0
1
0
ALA
DIR
224
0
2
0
ASL
DIR
225
0
1
0
ALA
DIR
227
0
1
0
OFS
ZERO
229
0
5
1
ASL
DIR
232
0
5
0
NOT
DIR
233
0
2
0
RBC
DIR
23?
0
1
0
ASL
DIR
2ซ0
0
2
1
EVP
ZERO
241
0
1
0
OLS
DIR
242
0
1
0
CON
ZERO
243
0
1
0
CON
ZERO
244
0
1
0
DRY
ZERO
244
0
0
0
IMP
ZERO
246
0
3
0
CLR
DIR
249
0
1
0
OLS
DIR
250
0
1
0
NOT
DIR
251
0
1
0
DRY
ZERO
253
0
1
0
8RN
ZERO
254
0
5
0
ALA
DIR
262
0
3
0
ASL
OIR
265
0
2
0
CON
ZERO
273
0
3
0
ASL
DIR
277
0
3
0
ASL
DIR
280
0
2
0
RTE
ZERO
262
0
2
0
UN*
UNK
207
0
3
0
ARL
OIR
268
0
2
0
CON
ZERO
268
0
0
1
ORY
ZERO
269
0
3
1
ORY
ZERO
-------
HASTE STREAM
DAT* LISTING 8UBCATE60RIZATI0N FILE
17
SUBCATbnOT Pป TYPE I1C# MATERUSE >,1*5 SAL/LB
PLANT
ORGANIC
PLASTIC
NUMBER
PP
PP
OTHER
*TF
DISCHARGE
ฆป
1
I
1
ซ
ฆฆฆฆK
20
1
2
0
ASL
DIR
20
0
0
0
BRN
ZERO
SI
6
0
3
ASL
DIR
36
1
5
0
ASL
DIR
41
1
2
0
DRV
ZERO
1
0
0
0
IMP
ZERO
ซ1
1
2
0
DRY
ZERO
43
0
0
0
IMP
ZERO
49
11
0
2
DP*
ZERO
SI
0
0
0
ORY
ZERO
55
11
0
0
IMP
ZERO
57
3
2
0
ASL
DIR
60
3
1
0
ASL
DIR
*1
9
2
0
ASL
DIR
62
1
3
0
ALA
DIR
74
12
1
1
ASL
DIR
74
0
0
0
BRN
ZERO
7a
0
0
0
OP*
ZERO
76
44
7
1
ALA
DIR
80
15
5
5
ASL
OIR
64
4
0
0
OLS
DIR
B4
5
0
0
NOT
OIR
64
2
0
0
UNK
UNK
84
11
1
0
ASL
OIR
64
4
0
0
NOT
DIR
68
23
3
ASL
OIR
95
1
0
BRN
ZERO
98
11
0
8
ASL
DIR
96
1
1
0
DP*
ZERO
96
0
0
0
BRN
ZERO
99
1
0
1
BRN
ZERO
102
2
2
1
ASL
DIR
103
6
3
3
ANL
OIR
106
5
2
4
DP*
ZERO
110
2
1
0
ASL
DIR
112
2
1
ASL
OIR
113
29
12
0
ASL
OIR
114
39
5
1
ALA
OIR
-------
WASTE STREAM
DATA LISTING - SUBCATEGORIZATION FILE
SUBCATahOT P# TYPE UCป NATEftUSE >.165 GAL/LB
plant
NUMBER
organic
PR
PLASTIC
PP
2
I
B
15
0
OTHER
WTF
discharge
1
1
1
1
4
0
A8L
DIR
2
0
OR*
ZERO
0
0
RTE
ZERO
2
0
DRY
ZERO
0
0
RTE
ZERO
2
1
DRY
ZERO
0
0
RTE
ZERO
2
0
DRY
ZERO
0
0
RTE
ZERO
2
1
DRY
ZERO
0
0
RTE
ZERO
2
0
DRY
ZERO
0
0
RTE
ZERO
2
0
ORY
ZERO
0
0
RTE
ZERO
2
1
DRY
ZERO
0
0
RTE
ZERO
0
2
ASL
OIR
t
0
ASL
OIR
6
1
ASL
DIR
0
1
ASL
OIR
2
2
OPW
ZERO
0
0
OLS
OIN
0
1
ASL
DIR
0
0
NOT
DIR
3
0
NOT
OIR
0
0
ASL
DIR
1
0
ALA
DIR
0
0
RTE
ZERO
s
0
ASL
DIR
0
0
BRN
ZERO
2
0
ASL
DIR
ซ
0
ACft
DIR
I
7
ASL
DIR
1
1
ASL
DIR
0
0
ASL
OIR
0
J
ASL
DIR
0
0
DPtf
ZERO
-------
waste stream
DATA LISTING - 8UBCATE60RJZATJON FILE
SUBCATซNOT P, TYPE UCป HATERUSE >.165 CAL/LB
plant
organic
PLASTIC
number
pp
PP
OTHER
WTF
DISCHARGE
23a
t
2
0
RTE
ZERO
2ซt
2
0
0
ASL
DIR
249
5
0
0
ASL
OIR
257
4
2
0
ASL
01ft
2*0
3
0
2
OFS
ZERO
272
12
3
0
ANL
DIR
274
36
3
0
OFS
ZERO
276
S
1
0
ALA
DIR
-------
haste STREAM
DATA LISTING - SUBCATEGORIZATION FILE
20
SUBCATahOT P, TYPE ItC, NATERUSE<ซ.165 GAL/LB
plant
ORGANIC
PLASTIC
NUMBER
PP
PP
other
KTf
DISCHARGE
a
t
ซป>
1
1
mmmmm
a
a
a
a
a
a
a
a
a
57
2
2
0
RTE
ZERO
56
6
0
2
DP*
ZERO
40
1
3
1
MMF
DIR
42
1
2
0
ASL
OIR
44
0
0
0
ALA
DIR
50
16
3
0
ASL
DIR
SO
0
0
0
IMP
ZERO
51
10
0
0
DP"
ZERO
51
0
0
0
BRN
ZERO
63
0
0
0
BRN
ZERO
63
6
0
4
ASL
DIR
63
0
0
0
NOT
DIR
63
0
0
0
DPW
ZERO
St
2
0
0
ASL
DIR
61
3
0
0
STR
DIR
61
1
0
0
BRN
ZERO
64
5
0
0
NOT
DIR
136
6
1
3
ALA
OIR
160
0
0
0
BRN
ZERO
163
5
0
0
ASL
DIR
177
29
2
0
ASL
DIR
177
0
0
0
DP*
ZERO
177
0
0
0
OP"
ZERO
166
IS
2
3
ASL
DIR
193
1
2
0
BRN
ZERO
216
1
1
0
ALA
DIR
219
1
2
0
A8L
OIR
239
1
2
0
ASL
OIR
267
8
0
l
IMP
ZERO
266
26
0
0
ASL
DIR
271
IS
3
0
ASL
DIR
276
0
0
0
DP*
ZERO
279
1
2
0
ALA
DIR
-------
WASTE STREAM
DATA LISTING SUBCATEGORIZATION FILE
plant
ORGANIC
SUBCATbnOT Pf
PLASTIC
TYPE ItNOT
C
NUMBER
PP
PP
OTHER
NTF
1
1
mmmmm
1
l
2
6
1
ALA
15
1
6
0
ASL
1*
3
1
2
PCF
16
1
0
1
DPN
22
9
2
0
ASL
22
0
0
0
DP*
26
6
0
0
RTE
26
1
2
1
TRF
32
9
0
0
ALA
35
2
1
0
NOT
53
1
2
0
ASL
64
1
1
1
ALA
69
1
0
DRV
61
11
1
5
RTE
65
2
2
0
NEU
67
4
1
1
ASL
67
0
0
0
DP*
67
2
0
0
ACR
117
6
0
2
ALA
116
14
1
1
OXY
128
2
1
OXY
126
0
0
0
DP*
ISO
4
3
1
PCF
1*ป
13
0
2
IMP
159
1
0
0
NEU
162
3
0
0
IMP
164
11
0
1
ASL
165
7
5
3
CON
170
14
3
S
ASL
171
8
2
6
ASL
178
2
5
0
ASL
163
7
2
2
ARL
163
1
1
1
UP"
164
1
0
0
ASL
191
1
0
BRN
201
3
0
2
ASL
203
4
0
0
A8L
204
22
0
2
ACR
21
DISCHARGE
OIR
DIR
OIR
ZERO
DIR
ZERO
ZERO
DIR
OIR
OIR
OIR
DIR
ZERO
ZERO
DIR
OIR
ZERO
OIR
OIR
OIR
OIR
ZERO
DIR
ZERO
OIR
ZERO
DIR
ZERO
DIR
DIR
DIR
DIR
ZERO
DIR
ZERO
DIR
DIR
OIR
-------
213
2U
230
230
256
256
259
263
264
266
269
275
291
263
264
266
266
MASTE STREAM
OAT* LISTING SU6CATEGORIZATION FILE
..... SUBCATaNOT P, TYPE ItNOT C
organic
PLASTIC
pp
PP
OTHER
MTF
DISCHARGE
ซ
a
I
ซ
ฆ
1
2
0
CON
ZERO
0
3
0
DRY
ZERO
3
0
0
CLS
DIR
7
1
0
OPN
ZERO
1
3
0
SSK
DIR
0
0
0
IMP
ZERO
12
0
0
ACR
DIR
17
1
0
ASL
DIR
2
1
3
ASL
OIR
4
1
0
IMP
ZERO
15
2
3
ASL
DIR
5
6
0
NOT
DIR
11
0
1
ASL
DIR
3
1
0
DRY
ZERO
6
0
1
NEU
DIR
i
4
0
CON
ZERO
0
2
1
DRY
ZERO
-------
5
6
A
8
a
18
21
23
24
59
6*
71
72
It
92
92
94
9T
101
10!
IIS
116
120
121
121
122
129
131
133
144
145
151
151
153
166
169
172
161
WASTE STREAM
DATA LISTING - 8UBCATEGORIZATION FILE
SUBCATปNOT P. NOT TYPE I
ORGANIC PLASTIC
pp
PP
OTHER
WTF
DISCHARGE
1
I
1
1
1
3
CLR
DIR
1
0
0
ALA
DIR
2
0
0
OLS
OIR
0
0
0
ors
ZERO
1
0
0
nEU
DIR
1
1
1
ASL
DIR
3
2
0
ALA
DIR
3
0
0
RTE
ZERO
1
3
0
ALA
DIR
u
3
0
ASL
OIR
2
0
0
NEU
OIR
3
0
1
DRT
ZERO
4
3
1
ASL
DIR
5
0
3
CLR
OIR
5
0
0
NEU
OIR
0
0
0
OPm
ZERO
19
1
2
ASL
DIR
1
1
0
ASL
DIR
6
3
1
NEU
DIR
0
0
0
0Pซ
ZERO
9
2
2
DPN
ZERO
9
2
3
ALA
DIR
8
3
3
ALA
DIR
4
0
0
ACR
DIR
0
0
0
DRV
ZERO
3
0
0
OLS
OIR
0
0
0
BRN
ZERO
0
0
0
IMP
ZERO
1
5
0
CON
ZERO
3
2
0
ASL
DIR
4
1
1
ARL
DIR
2
0
0
ASL
DIR
3
1
0
ALA
OIR
3
0
0
DAF
OIR
1
0
0
CON
ZERO
ซ
0
1
RTE
ZERO
6
0
0
CON
ZERO
1
3
1
IMP
ZERO
-------
NASTE STREAM
DATA LISTING - SUBCATE60KIZATION FILE
8UBCATซN0T 9, NOT TYPE I
PLANT
ORGANIC
PLASTIC
NUMBER
PP
PP
OTHER
MTF
DISCHARGE
.....
c
1
I
a
1
1
ป
1
1
1
1
1
I
I
iei
0
1
0
DRV
ZERO
1ซ2
l
0
0
8TR
OIR
1A6
l
4
0
ASL
01ft
205
2
0
1
NEU
DIR
208
10
0
1
ASL
OIR
214
1
3
3
DRY
ZERO
22*
1
8
1
TRF
DIR
231
1
1
0
ACR
OIR
245
14
0
1
STR
OIR
247
5
4
1
ASL
OIR
252
2
0
7
0F8
ZERO
252
0
1
0
0F6
ZERO
252
1
0
0
OP*
ZERO
255
6
0
2
NEU
DIR
258
5
0
0
ACR
OIR
261
1
1
0
NOT
OIR
270
1
3
0
OXY
DIR
278
2
5
1
DRY
ZERO
205
5
0
4
DP"
ZERO
290
2
1
0
OPm
ZERO
2ซ1
1
0
0
8RN
ZERO
-------
2
3
4
7
9
10
11
11
12
IS
14
17
17
19
25
27
29
SO
ss
S4
SS
S9
44
45
46
47
47
48
52
54
56
56
62
65
67
68
70
WASTE STREAM
DATA LI8TINS 8UBCATE6ORI2ATI0N FILE
25
SUBCATaPLASTICS ONLY
OtCINF
(PPM)
0I6EFF
(PPH)
PHENOLINF
(PPN J
PMENOLEFF
(PPH)
NHJNlNF
(PPM)
nmjneff
(PPM)
CHROM1UMINF
(PPM)
CHROM1UMEFF
(PPM)
ซ1.00
4.00
IS.00
0.14
0.0S
00
IS
7.60
00
00
00
S4.00
29
0
0
6
35
6
00
60
80
00
00
00
0,11
46
09
0.50
0.0S
01
02
02
01
-------
mmm
75
77
77
77
78
79
02
62
64
84
69
90
91
91
93
96
100
100
104
104
104
104
105
106
107
109
111
119
123
124
125
126
129
131
132
140
140
146
MASTE STREAM
OAT* LISTING - SUBCATEGORYAT10H FILE
26
SUeCATaPUSTICS ONLY
OtGINF
(PPM)
oteerr
(PPM)
phenolinf
(PPM)
PHENOLEFF
(PPM)
NH3NINF
(PPM)
NH3NEFF
(PPM)
CHR0MIUMINF
(PPM)
CHR0MIUMEFF
(PPM)
2.00
49.
00
83,
00
.20
,10
>09
01
01
00
20
.50
46
40
47
,48
>36
,00
!oo
00
00
,00
,19
30,
00
20,
00
,20
!oo
30
05
-------
PLANT
NUMBER
0I61NF
(PPM)
OtCEFF
(PPM)
HASTE stream
DATA IJ8TIN6 - SUBCATECORIZATION FILE
SUBCATaPLASTICS ONLY
PHENOLINF
CPPMJ
phenoleff NMJnINF nhjneff CHROMIUMINF CHROMIUMEFF
(PPM) (PPM) (PPM) CPPh) (PPM)
CD
I
ro
I
147
iซe
ISO
152
192
154
155
155
155
156
157
1*1
1*7
i*6
173
174
179
164
165
1M
192
194
19*
197
1ซ7
196
199
|99
200
200
202
207
209
210
210
211
212
217
3.10
0.09
0.01
14
00
13
00
00
10
20
2*
426
00
00
11
00
109
11
00
00
*7
36
03
39
02
-------
PLANT
NUMBER
221
221
223
22a
225
227
229
232
233
237
240
241
242
243
244
244
246
249
250
251
253
254
262
265
273
277
280
262
2ฎ7
268
288
289
-------
NASTE STREAM
DATA LISTING - SUBCATEGORYATION FILE
SUBCATaNOT Pt TYPE I&C* WATERUSE >.165 GAL/LB
plant
number
OIGINF
CPPMI
OtCCFF
(PPM)
PHENOLIW
(PPM)
PHENOLEFF
(PPM)
NH3NINF
(PPM)
nhjneff
(PPM)
CHROMIUMINF
(PPM)
CHROM1UMEFF
(PPM)
20
16
00
420
00
00
05
56
01
IT
40
15
20
40
60
60
18
00
30
-------
127
134
1M
135
1J5
lib
156
137
1ST
13*
lป
141
141
142
142
143
143
156
160
175
176
ISO
iao
187
190
193
195
206
215
216
216
220
222
226
23ซ
OtftINF
(PPM)
oigeff
(pp*)
HASTE STREAM
DATA LISTING - 8USCATEC0RIZATI0N FILE
ฎU8CATปN0T P, TrPE UC, WATERUsE >,165 fiAL/LB
PHENOLINF
(PPM)
phenoleff
(PPM)
NH3NINF
CPPHJ
NH5NEFF
(PPM)
CHROHIUKINF
(PPH)
cmromiumeff
(PPM)
la
oo
3.60
303.00
80,00
20
7
00
80
SO
60
01
390
29
00
00
271
29
00
00
10
10
09
00
23
173
00
00
04
60
55
00
-------
Pt*NT
number
ฆ
236
248
249
257
2*0
272
274
27*
WASTE STREAM
DATA LISTING - 8UBCATEGORIZATION FILE
UBCATbnOT P, TYPE l&Ct tUTERUsC >,165 6AL/LB
OtCINF
(PPH)
0&6EPP
(PPM)
PHENOLINF
(PPM)
PHENOLEFF
(PPM)
NH3NINF
(PPm)
nhjneff
(PPM)
CHROMIUMINF
(PPM)
cmromiumeff
(PPM)
00
42
I
00
60
00
0.30
-------
<
37
36
40
42
<19
SO
50
SI
SI
63
63
63
63
01
1
8}
6ซ
136
160
163
177
177
177
166
193
216
219
239
267
266
271
haste stream
DATA LISTING SUBCATECORIZATION FILE
SUBCaTปNOT P, TYPE IIC, HATERU8E<ซ,165 CAL/LB
OtGINF
(PPM)
016EFP
(PPM)
PHENOLINF
(PPM)
PHENOLEFF
(PPM)
NHJnINF
(PPM)
NMJNEFF
(PPM)
539
00
747
00
36
0
00
02
292
00
75
00
75
146
00
16
00
53
3
00
20
62
3
445
705
00
00
40
21
360
00
146
40
5
125
95
974
00
00
57
19
00
2
3
-------
PLANT
NUMBER
OICINF
(PPM)
0I.6EFP
(PPM)
PHENOLINF
(PPH)
CD
I
co
oo
1
15
16
16
22
22
26
26
32
35
53
64
69
63
65
67
7
67
117
118
126
126
130
!ซ
15ซ
162
16#
165
170
171
176
163
1ป3
166
lซl
201
203
204
570
00
112
00
50
00
00
17
00
11
15
00
00
16
00
10
70
-------
213
213
230
230
296
256
259
263
264
266
2*9
2*5
281
283
204
206
206
HASTE STREAM 34
DATA LISTING SUBCATECORIZATION FILE
SUBCATbNOT P, TYPE KNOT C
OtGINF OtCEFF PHENOLINF PHENOLEFF NHjNlNF NHJNEFF CHROMIUMINF CHROMIUMEFF
(PPM) (PPM) (PPH) (PPM) (PPM) (PPM) (PPM) (PPM)
4|0
00
23
1
00
00
15
15
233
22
00
70
1
SO
22
80
00
70
50
01
30
01
-------
ซ
5
6
e
8
la
21
23
24
59
66
71
72
I*
42
42
94
7
101
101
IIS
11*
120
121
121
122
124
131
133
144
145
151
151
153
WASTE STREAM
DATA LISTING SUBCATECORIZATXON FILE
SUBCATaNOT P, NOT TYPE I
OiSIMF
(PPM)
086EFF
(PPM)
phenolinf
(PPM)
PHENOLEFF
(PPซ)
NHJNINF
(PPM)
NH3NEFF
(PPM)
CHROMIUMINF
(PPM)
CHROMIUMEFF
(PPM)
420
00
286
00
0.42
46.00
00
*0
00
2345
120
23
00
00
00
00
10
15
00
00
12
10
20
20
65
02
30
65
80
00
240
4
60 64
80
00
50
10
70
20
00
21
74
0.02
10
00
10
05
02
03
24
23
00
-------
HASTE STREAM
DATA LISTING - SUBCATEGORYATION FILE
36
SUBCATaNOT P, NOT TYPE I
CD
I
CO
PLANT
NUMfaER
101
iซ2
166
205
aoe
214
226
231
2ซ5
207
292
252
252
255
250
261
270
27ซ
2ป5
290
2*1
OtCINp
CPPH)
50,
00
OtGEFF
(PPH)
mmmmw
.67
,77
00
46
PMENOLINF
tPPM)
0
It
.32
!oo
.30
PHENOUFF
CPPH)
08
01
.20
,04
NH3NINF
CPPM)
NH3NEFF
(PPM)
CHROMIUHINF CHROMIUHEFF
(PPH) {PPH)
189,
5331!
.80
00
00
,70
,90
,70
10,
00
,06
44
05
-------
|