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 311983
On February 2B, 19R3, 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, 19R3 (4fl _FR 11R2R to 11B67).
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 1n the Federal Register notice, the
February 1983 OCPSF nevelopment Oocument, and February 10, 19R3 OCPSF Regulatory
Impact Analysis.
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CONTENTS
SECTION \ > PAGE
I INTRODUC 1
II SUMMARY AND CONCLU. 5
III DESCRIPTION OF INDU 11
Introduction 11
Definition of the 12
Product/Process 29
Data Base Profii 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
Siumnary-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 LOB
VII CONTROL AND TREATMENT TECHNOLOGIES 119
General 119
In-Plant Source Controls 119
In-Plant Treatment 122
End-of-Pipe Treatment 131
OCPS Effluent Quality 168
Effluent Variability 177
Wastewater Disposal 195
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
ii
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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
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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
Rate Ranges 73
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LIST OF TABLES (Continued)
Page
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) . Ill
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 145
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LIST OF TABLES (Continued)
lฃSฃ
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, >95X Removal 175
7-30 Biological Systems, >95% or <50 mg/l 176
7-31 Biological Systems, >95% or <30 mg/l 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 237
8-14 Sample Plant-By-Plant Cost Analysis 238
8-15 Plant-By-Plant Suggested Treatment and Costs,
Non-Plastics 242
8-16 Plant-By-Plant Suggested Treatment and Costs,
Plastics 252
8-17 Potential BPT Effluent Limitations 258
8-18 Plant-By-Plant Cost Estimates 259
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LIST OF TABLES (Continued)
Pag
8-19 Total Costs, Plant-By-Plant Analysis 265
8-20 Percentage of Plants Requiring Additional Treatment For
BPT(I) 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
viii
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LIST OF FIGURES
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 79
4-8 Rank Correlation - Direct Discharge Systems - Not Plastics
Only/Type I and Not C 80
4-9 Rank Correlation - Direct Discharge systems - Not Plastics
Only/Type I & C 81
4-10 Rank Correlation - Direct Discharge Systems -
Plastics Only 82
ix
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LIST OF FIGURES (Continued)
Page
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
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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
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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 be6t 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 pretreatraent 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 POTWs (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 27, 1977 the
1977. Although this law
water pollution control
President signed into law
makes several important
program, its most signi
1
the Clean Water Act of
changes in the federal
ficant 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 pretreatraent standards
are now aimed principally at toxic pollutant controls. Moreover, to
strengthen the toxics control program, Congress added Section 306(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 1 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.
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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
regulat ions.
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
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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 aeTated 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.
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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 me'dian effluent limitations by appropriate variabil-
ity factors which were calculated through statistical analysis of long-terra
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
.(rag/1 or ppra)
LONG TERM MEDIAN
MAXIMUM 30-DAY
MAXIMUM DAILY
SUBCATEGORY
Plastics Only
bqd5
14.5
TSS
24
B0D5
22
TSS
36
BOD.
49
TSS
117
Oxidat ion
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
-------
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 car 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 11, 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 volum^.
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 2824 for plastics
and synthetic materials. SIC codes as established by the U. S. Depart-
ment of Coranerce 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
Synthet ic
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
Butad iene (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
TOTAL
Adipic acid
0.55
78.75
SOURCE: Chemical and Engineering News 1981
15
-------
TABLE 3-3
ANNUAL PRODUCTION VOLUME OF PLASTICS AND SYNTHETIC FIBERS
1980
Production
Resin/Fiber (million kkg)
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
Cellulosic s
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
cake 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
Industry
Organic Chemicals
Only
Plastics and
Synthetic Materials
Only
Organic Chemicals &
Plastics and Synthetic
Materials (Combined)
TOTAL
Number of
SIC Code Plants*
2865 195
2869 457
2821
2823
2824
1217
Projected Estimate of
Number of PlantB
1045
176
2100
484 879
19
62
* SOURCE: Economic Information Service (1981)
18
-------
TABLE 3-5
PLANT DISTRIBUTION BY STATE
Organics Chemicals Plastics and Synthetic
Industry Fibers Industry
SIC CODE
SIC
CODE
2865
2969
Total
2821
2323
2324
Total
STATE
Alabama
4
5
9
7
1
2
10
Alaska
0
1
1
0
0
0
0
Ar izona
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
Connect icut
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
Massachuset t s
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
Mont ana
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
Tota
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
Tennessee
1
5
6
7
2
4
13
Texas
17
57
74
35
0
0
35
Ut ah
1
0
1
0
0
2
Virginia
1
4
5
5
2
7
14
Vermont
0
0
0
1
0
0
1
Wash ington
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
i_
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 Bite, 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
-------
PLANT DISTRIBUTION BY NUMBER OF EMPLOYEES
200-
Number
The Organic Chemicals Industry
Plants
100-
The Plastics/Synihenc
Fibers Industry
1000
10
100
10.000
Number of Employees
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
170-180
4
2
180-190
3
1
190-200
2
3
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
200
Number
of
Plants
100'
0_r
1
The Plastics/Synlhelics Fibers Industry
The Orgsn'c Chemicals Industry
1000
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
6-10
11-15
16-20
21-25
26-30
31-35
36-40
41-45
46-50
51-55
56-60
61-65
18
4
6
5
4
2
1
1
TOTAL
282
27
-------
DISTR!
BUTION BY AGE OF ORGANIC CHEMICALS AND
PLASTICS/SYNTHETIC FIBERS PLANTS
40i
Number
Plants
30-
20-
0
10
20
30
40
Plant Age (years)
FIGURE jo
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,
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
CHCOAINAIEO
METHANES
HCN
ACETYLENE
ammonia oxo methanol aoiponitrilE
CHEMICALS
ammonium
SALTS
UREA
ACRYLONlTRILE
ACETONE
CYANOHYORIN
methyl
AMINES
DMT
U)
O
FORMALDEHYDE
RESINS
methyl
chloride
methyl
METHACRYLATES
SILICONES VINYL
CHLORlOE
CCU
CELLULOSE
PRODUCTS
fLUOROCARBONS
VINYL
ACETATE
chlorinated
ethylene
neoprene
ACRYliC
AClO I 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
ETIIANOl
ACCTAIOEHYOE
ETMYl
AMINES
ETHYL
BHOMlOE
CHLORAL
ETHYL
ETHER
ethyl oenzene
6
ETHYL TOLUENE
I
SEE AAOMATICS
ETHYL
CHIORIOE
ETHYLENE
OISROMIOE
ethylene
OiCHiORlOE
acetalool
2 ETHYL
HEXANOL
ACETIC AC<0
& ANHYORlOE
PENTAERY
THRITOL
3BUTYLENE
GLYCOL
CROTON
ALOEHYDE
ACETATE
ESIC RS
ACETYL
CHLORIDE
VINYL
ACETATE
ACETANILIOE
ASPIRIN
CELLULOSE
ACETATE
tetraethyl
LEAO
ETHYL
CELLULOSE
I
OOT
MISCELLANEOUS
DERIVATIVES
pehacetic acio
paraloehyoe
PYRIOINE
trimethylol
PROPANE
ethylene
AMINES
VINYL
CHLORIOE
1.1? TRICHLORO
ethane
C thane
METHYL
CHLOROFORM
PENTACHLORO
ETHANE
perchloro
ethylene
tctrachloao
(THANE
TRICHLORO
ETHYLENE
vinylioene
CHlOfllOf
methyl
CHLOROFORM
POLYVINYL
ALCOHOL
CHLOROACETlC
ACIOS
I
polyethylene
I
LOW
OENSITY
1
HIGH
OENSITY
I
propylene
COPOLYMERS
ETHYL
ACETATE
VINYL
ACETATE
I
PROPIONALOEHYOC
I
PROPIONIC ACIO
I
ETHYLENE OXIOE
ethylene
GLYCOL
polyethylene
glycols
ethoxylateo
surfactants
glycol
ethers
ithanolauines
HYOROXY ETMYl
cellulose
POLYESTERS
I
OIOXANE
ethylene
carbonate
GLYOXAL
OIOXOLANES
FR0M: 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 - SOMF PRODUCTS DERIVFD FROM ETHYLENE
-------
PROPYLENE
POLYPROPYLENE
ISOPflOPANOL CUMENE
NONENE ACETONE PHENOL
JL
OJ
ro
NONYL
PHENOL
ISOOfCYL
ALCOHOL
ACROLEIN ALLYL
CHL0RI0E
OOOECENE
ALLYL PROPYLENE
ALCOHOL OXIOE
GLYCERINE
ACRYLONIiniLE
POLYMERS
GLYCOL
ETHERS
HEPTENfc
BUTYRALOEHYOES
IANOL j
OOOECYl BUIANOL I ISOOCTYI
BENZENE | ALCOHOL
POLYGLYCOLS
ITHYL
HEXANOL
ALKANOLAUINES
FROM: Riegel's Handbook of Industrial Chemistry, Seventh Edition, by James A. Kent;
Copyright (c) 1974 by Von Nostrand Reinhold Company. Reprinted by permission of the
publisher.
FIGURE 3-6 - SOME PRODUCTS DERIVED FROM PROPYLENE
-------
euiAirs |
eui'imnj
mOI
, I
itrntNf
CO^OiTMlD
lAlII
roiriui aohiI
i autri
Ai COfOt
I
ISOIuITKHI
LO
LO
uooctu
AICOMOI
MAlliC
ANHTOMIOI
AUTi
AlCOHOlS
lutrtlNl
Ol'Df
~~I
IHT
I0UITI
HtlNOlS
fOi*
ฆsot>ur i m(i
fOltlotlNlS
UITMACATIO
mitiii
OmSO
luiTiim
Itufvt
AlCOHOl
i i f-
k P( h t ANf ISO PI SlAltl PaIUHii
, -J I I
II I <
kHvl *OlปC>u0ซO lS0'ซ( Nl 01IITDRUGINAII
ClClOHNlANfi |
I J I .
*"*1 HNIIMi CTClOrihTAOKNf I HlCMlB AlCONOlt
PCAflAHl AlCONOti | -
ฆbS< C DC'OiS
(MIOAIOf
I lh f A A OlfflNl
(ฆAtxlORO | lINiARStCOMOAMT
HiCMt* aicqhOIS
FROM: Riegel's Hondbook of Industrial Chemistry, Seventh Edition, by James A. Kent;
Copyright (c) 1974 by Von Nostrund Keinhold Company. Reprinted by permission of the
publisher.
FIGURE 3-7 - SOME PRODUCTS DERIVED FROM C4 AMD HIGHER AUPHATICS
-------
L
MKIC
Ctft Hi
I
I
lu.vr.ii
summit
oaonojtfcUNf
J
MHtfCfnr
mmAit
H(b(f
t
fHlHtuli J-Wli'HOl
MiroBior
OICWOBO'Ol Utซf
41.111 PulMOll
nciMioi
FROM- Rieircl's Handbook of Industrial Chemistry, Seventh Edition, hy James A. Kent;
Copyrighlifc) 1974 by Van Noslrond Reinhold Company. Reprinted by permission of the
publisher.
PIG UII P. 3-8 - SOMlฃ PRODUCTS DERIVl-D FROM AROMATICS
-------
ies, and may produce Co 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 co 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
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 conmercial 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 o? products and production processes distin-
guish the wastewater characteristics of one plant from that of another.
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 nixed plastics-organics processes is evaluated below.
Generic Processes and Product/Processes
Despite the differences between individual chemical production planes,
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 6truc
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.
Crystallizat ion/Dist illation (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
-------
Curing 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
iB 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 specieB 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: nitrophenol6
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 terras used to
profile the data.
The 308 Questionnaire was designed to collect information that would
adequately describe and characterize the 0CPS 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 3-10 and Figure 3-9.
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)
ฑ
308
DATA
BASE
(see note Z)
(5ee note 3)
(see nste 4)
fvSUMMARY' !_:'"
DATA . - :
. -c -- ฆ. v. '
V" .A.'.*. *
1;
. " :> l>.\ฆฆ
TELEPHONE '
SURVEY
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
aftsr 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)
See Note 1)
Paint
Formulating
Alcohol Fuels
(see note 1)'
L
Adhesives
and Sealants
fsee note 2)
Coal
Gasification
(see note I)'
(see note 3)-
Tirrber Products
(see Note 1)
Numerous
Unrelated
Guidelines
Inorganic
Chemicals
><(see note 2)
:;ia
Plastics and.
' Synthetics-:!
Refineries
^(see note 3)
Gum and
Wood.
Chemicals
see Note 1)
Pharmaceuticals
Pesticides
N(see note 2)
Plastics
Molding aod
Forrnufatipq
(See Ilote 2)
see note 1)
Ink
Formulating
Pulp,
Paper,
Paperboard,
and Builders'
Paper and
Paperboard Mills
('see note I
NOTES:
(1) No identified direct discharge Data Base overlap with organic
chemicals and plastics and synthetic materials industries.
(2) Identified direct discharge Data Base overlap with organic
chemicals and plastics and synthetic materials industries.
(3) Overlapping plants excluded from Data Base because organic
chemical production is covered by categorical regulations
througn petrochemical and chemical synthesis subcategories
in the appropriate industries.
FIGURE 3-10 - DATA BASE AND RELATED INDUSTRY GUIDELINES OVERLAP
U5
-------
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 3-11 -
PLANTS AND THEIR ASSOCIATUD STKEAMS
For All PlanH
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
POR PLANTS WITH MULTIPLE STREAMS
Total Number of Streams
Number of Direct Discharge
Streams
Number of Zero Discharge
Streams
Number of Unknown Discharge
Streanu
Direct Discharge Zero Discharge Unknown Discharge
195 94 2
156 67 2
39 27
33 94
195
3
251 124
212
38 124
1 - 2
95 57
56 -
30 57
1
All
291
225
66
127
195
3
377
212
162
3
152
56
95
1
-------
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
which pumped their wastes either
treatment work. These six plants
treatment.
plants, there were still six plants
to a jointly or a privately owned
are described as utilizing offsite
Generic Processes - In addition to cataloging the products at each plant
byproduct/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 Bhown 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 cora-
pilation oฃ 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-terra 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 1
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
.
A11
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 noc
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-i
** 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 ia such a way as to make these numbers available
55
-------
TABLE 3-14 NUMBER AND TYPES OF PLANTS AND STREAMS BY ACE
Stream*
Planet
Dally
ACE
All
Dlr
Zer.
Unk.
All
Dlr ZS
4
2
2
-
4
3 1
-
-
27
4
4
-
4
4
-
1
23
5
4
1
-
5
4 1
-
1
29
5
I
3
-
5
2 3
-
-
3U
4
2
2
-
4
2 2
-
1
31
2
2
-
I
2
-
1
32
5
3
-
b
4 1
-
33
6
5
1
-
5 1
-
34
3
3
-
-
3
3
-
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
-
-
42
1
1
-
-
1
L
-
-
43
3
2
1
-
3
2 1
-
-
44
0
-
-
u
-
1
46
1
1
-
-
1
1
-
1
50
1
1
-
-
1
1 -
-
-
51
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
19 5 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, eyelohexanone 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 raechani.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 60 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/
Processes
All
Dir
Zer
Unk
All
Dlr
Zer
Unk.
Daily
Data
1
65
31
33
1
42
21
20
1
3
2
43
27
15
1
26
15
11
-
7
3
55
30
24
1
22
14
8
-
10
4
25
19
6
-
8
5
3
-
4
5
26
19
7
-
5
3
2
-
6
17
10
7
-
3
2
1
-
1
7
8
6
2
-
2
2
-
-
1
8
12
8
4
-
1
1
-
-
2
9
8
6
2
-
1
1
-
-
3
10
8
5
3
-
7
5
2
-
1
11
10
8
2
-
10
8
2
-
1
12
3
3
-
-
3
3
-
-
1
13
4
2
2
-
2
1
1
_
14
4
4
-
-
4
4
-
U
15
4
2
2
-
4
2
2
-
1
16
3
3
-
-
3
3
-
-
1
17
2
1
1
-
2
1
1
-
18
3
3
-
-
3
3
-
-
1
20
2
2
-
-
4
4
-
-
1
21
2
2
-
-
11
6
5
-
-
22
2
2
-
-
13
12
1
-
1
23
27
13
13
1
-
24
1
1
-
-
13
10
3
-
-
25
1
1
-
-
23
18
5
-
-
26
2
2
-
-
16
10
6
-
1
27
6
5
1
-
28
11
8
3
-
_
29
1
1
-
-
9
6
3
-
-
31
1
1
-
-
1
1
-
-
-
33
1
1
-
-
1
1
-
-
1
34
1
1
-
-
-
39
1
-
1
-
1
_
1
-
-
41
1
1
-
-
1
1
-
-
1
45
1
1
-
-
1
1
-
-
1
51
1
1
-
-
1
1
-
-
v'ot Reported
60
9
51
-
3
3
-
-
1
TOTALS 377 212 162 3 291 195 94 2 50
58
-------
TABLE 3-16
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
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
-
-
J 2
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
-
59
-------
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
St reams
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.
SllBCATEGORIZATION
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-
categorization 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
Bubcategorization 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
-------
On
10900-
1000-
B
0
D
P
P
n iB0-
leH
LOG-NORMAL PROBABILITY PLOT
SUBCATEGORY INFLUENT BOD
. r>
D1RZCT DISCHARGE STRฃAMS
.csฐฐ ^
-*++
V" A A
+ +ฆ t
ฐ ++ A'
J
-------
LOG-NORMAL PROBABILITY PLOT
SUBCATEGORY INFLUENT BOD
DIRECT DISCHARGE SYSTEMS
a*
4H
B
0
D
P
P
H 3H
1
H
L
0
G
1 z-i
0
U
H
1
T
5
/ /'/
Organics only -- &
/ Plasncs
/ v' Plastics only
/>
0.0
" ' " I'
.001
ฆ'' I'
.023
T-T-p-
.16
ฆ ฆ i '
.50
ฆ ' 4 "
.34
T'
.977
"J"
. 999
i
1.0
CUMULATIVE FREQUENCY
FIGURE h-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 a^id 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 biodegradabi1ity on theoretical grounds.
Table 4-1 summarizes expected 5-day biochemical oxygen demand by generic
process group.
Type 1 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 ฆ 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
Oxidat ion
Peroxidation
Acid Cleavage
Condensat ion
Isomerization (maleic >
fumaric acid)
Esterification
Hydroacetylation
Hydrat ion
Alkoxylation
Hydrolysis
Carbonylat ion
Hydrogenation (butyraldehyde >
n-butanol)
Neutralization
TYPE II - Intermediate 5-Day Biochemical Oxygen Demand
Aminat ion
Ammonolysis
Oximat ion
Dehydrat ion
Ammoximdation
Electrohydrodimerization
Cyanation/Hydrocyanation
Epoxidation (unsat'd esters)
Etherification (alkycellulose)
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 ^
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.)
Chlorohydrinat ion
Phosgenat ion
Extraction
68
-------
TABLE 4-2
TERRY-HOEFFDING TEST
FOR NOT PLASTICS ONLY PLANTS
Raw Waste BOD
SIGNIFICANCE
TYPES TEST STATISTIC SAMPLE SIZE LEVEL
TYPE I vs. NOT TYPE I T - 2.251 N - 74 P - .024
NOT TYPE I BUT TYPE II T - .710 N - 11 P - .478
vs. NOT TYPE I OR TYPE II
Raw Waste TSS
TYPE I vs. NOT TYPE I T = .784 N - 47 P - .433
NOT TYPE I BUT TYPE II T - .560 N - 13 P - .576
vs. NOT TYPE I OR TYPE II
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 ฆ 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
Oxidat ion).
3. Plants manufacturing organic chemicals only, organic chemicals
and plast ics 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 Sample Significance
Category Stat istics Size Level
Plastics vs. Not Plastics Only 3.516 107 0.000
Not Plastics Only
Type I vs. Not Type I 2.114 62 0.034
Type I and C vs. Type I
and Not C* 1.347 49 0.178
RAW WASTE TOC
Test Sample Significance
Category Statistics Size Level
Plastics vs. Not Plastics Only 0.738 48 0.461
Not Plastics Only
Type I vs. Not Type I 1.205 40 0.228
Type I and C V6. Type I
and Not C* 0.576 32 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 vill most
likely have higher strength wastes due to less efficient production
(lower yields) and much higher variability due to the campaign aspect of
it9 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, wherea9 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 itBelf 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
{if /day)
Size
All
Streams
Plastics
Only
Not Plastics
Type I & C*
Not Plastics
Type I Not O**
Not
Not
Plastics
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 Race)
All
Plants
Plastics
Only
Not
I w/oxidation
Plastics Only
I w/o oxidation|
No Group
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: Cป0) 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 ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/NOT TYPE I
BOD
12.5H
10.0
7.5-
2.5
5
8
2
3
4
6
7
9 10 11
0
1
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT = -0.31
-------
FIGURE 4-4
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT RUSTICS ONLY/TYPE I ft NOT C*
BOD
25 H
20 -
15 -
10 -
5 -
0 H
0 2 4 6
8 10 12 14 16 13 20
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT ป -0.02 CP ป .92, N - 21)
i
* Type I w/o oxidation
-------
FIGURE 4-5
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I ft C *
BOD
50 H
40 -
30 -
20 -
10 -
0 "I
lltlllllllllll
10
T
15
T
20
25
"I"
30
* ' I '
35
w w I "
40
SIZE (Pr oduction Rate)
SPEARMAN CORRELATION COEFFICIENT ซ -0.12
-------
FIGURE 4-6
RANK CORRELATION
FOR THE PLASTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
PLASTICS ONLY
BOD
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
SIZE (pr oduction Rate)
SPEARMAN CORRELATION COEFFICIENT ป .06
-------
FIGURE U-l
RANK CORRELATION
FOR THE PLASTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/NOT TYPE I
TSS
12 -
8
2
3
5
6
9 10
0
1
4
7
12
13
11
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT = -0.20 (P ป .52, N ป 13>
-------
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
0
6 7 8
VJVVIfMIMJi
9 10 11
HI|MIIIปH|
12 13
Wflll|
1
5
2
3
4
0
SI2E (Production Rate)
SPEARMAN CORRELATION COEFFICIENT ป 0.42
-------
FIGURE U-9
RANK CORRELATION
FOP THE PLASTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I * C*
TSS
20 H
15 -
4
8
12
14
8
6
16
18
20
2
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT ป -0.13
-------
FIGURE 4-10
RANK CORRELATION
FOR THE PLASTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
PLASTICS ONLY
TSS
50 H
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42
SIZE (Production Rate)
SPEARMAN CORRELATION COEFFICIENT ซ -0.00
82
-------
The effectB 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 y-ears 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 R= -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 =
0.5 and P = 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
50
46
20
19
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48
AGE
SPEARMAN CORRELATION COEFFICIENT ซ -0.19
-------
FIGURE 4-12
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I ft C*
BOD
58
48
38
28
5
15
25
35
18
28
38
48
8
AGE
SPEARMAN CORRELATION COEFFICIENT ซ -8.49
-------
FIGURE 4-13
RANK CORRELATION
FOR THE PUSTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
MOT PLASTICS ONLY/TYPE I ft NOT C*
BOD
20 H
15 -
10
5 -
0 1
o
0
^*JTTTTTT^^qTTTTTTTIT|TTTTTซlT,ป^rT*TTTTTT|TTTTTTTT*^
8 10 12 14 16 IS
AGE
SPEARHAN CORRELATION COEFFICIENT ป 0.01
-------
FIGURE 4- 14
RANK CORRELATION
FOR THE PLASTIC * ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/NOT TYPE I
BOD
12.5H
10.0-
7.5-
5.0-
2.5-
0.0-
6 7 8 9 10 11
3
2
5
4
0
AGE
SPEARMAN CORRELATION COEFFICIENT ซ 0.06
-------
FIGURE 4-15
RANK CORRELATION
FOR THE PLASTIC & ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
PLASTICS ONLY
TSS
40
30
28
0
20
30
0
5
10
15
25
35
40
AGE
SPEARMAN CORRELATION COEFFICIENT - -0.18 CP - .25, N ป 40)
-------
FIGURE I*-16
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/TYPE I ft C*
20 ~
0
2
4
6
10
8
12
14
16
18
20
AGE
SPEARMAN CORRELATION COEFFICIENT = -8.33 CP ซ .13, N = 20)
o
* Type I w/oxidation
-------
FIGURE 4-17
TSS
12.5H
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/TYPE I ft NOT C *
I I
0123456799 18
AGE
SPEARMAN CORRELATION COEFFICIENT -0.00 CP ซ' .00, N
ฆ?
ฆฆI i
11 12
12)
Type I w/o oxidation
-------
FIGURE 4-18
10
ho
TSS
15 H
12 -
9 "
6 -
3 -
0 -
RANK CORRELATION
FOR THE PLASTIC ft ORGANIC CHEMICAL INDUSTRIES
DIRECT DISCHARGE SYSTEMS
NOT PLASTICS ONLY/NOT TYPE I
~
6
O
o
0 1
6 7
AGE
8 9 18 11 12 13
SPEARMAN CORRELATION COEFFICIENT 0.12 (P * .69, H ฆ 13)
A
-------
TABLE 4-7
SPEARMAN CORRELATION COEFFICIENTS (R)
FOR RAW WASTE BOD AND TSS vs. AGE
All
Plants
Plastics
Only
Not Plastics Only
I w/oxldatlon | I w/o oxidation | No Group I
BOD
TSS
-0.19
(0.04)
-0.13
(N.S.)
-0.19
(N.S.)
-0.18
(N.S.)
-0.49
.00
-0. 35
(N.S.)
0.01
(N.S.)
-0.08
(N.S.)
0.06
(N.S.)
0.12
(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, halogenati-on 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
quent process.
Delineation between raw materials and products
since the product from one manufacturer can be
another manufacturer. This lack of distinction
the process approaches the ultimate end product,
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.
material for a subse-
ts nebulous at best,
the raw material for
is more pronounced as
which is normally the
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
st age.
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 span6.
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 iB affected by the presence
of inhibitory materials (toxics); availability of alternative disposal
methods; and pollutant concentrations in, and variability of, the RVL.
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's 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 95Z)
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 fTom 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
Esterification
Hydroacetylat ion
Hydration
Alkoxylat ion
Hydrolys is
Carbonylat ion
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 (A) 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 (0&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 BOD) 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
Preceding page blank
-------
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 wa9te.
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.
ฃH
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 that 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 rediasolve 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 Btill 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
BOD, 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 te6t 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 (COj) by catalytic combusion or by wet chemical oxida-
tion. The COj 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 CO^ 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: (1) 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 ae 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 jet6
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
.. - "\
Preceding page blank
-------
TABLE 6-1
EFFLUENT FLOWS FOR PROPOSED SUBCATEGORIES
DIRECT DISCHARGERS ONLY
HOT PLASTICS NOT PLASTICS
TYPE I u/ TYPE I w/o NOT PLASTICS
OXIDATION OXIDATION NOT
TYPE I
ฃF F
iff
iff
FLOW
F I. OW
F i 0 W
F LOrf
MGD
r.'GD
I.-C0
l.'GO
MAXIMUM
10.700
39 .000
32. 100
10.000
MEAN
1 .357
2.771
2 .164.
3.346
MINIMUM
0.034
0.000
0 ,020
0.007
MEDIAN
0.612
I .010
0,852
0.950
NUMOEf? OF
OBSEHVATIONS
74
C3
34
35
PLASTICS
ONLY
-------
TABLE 6-2
INFLUENT AND EFFLUENT FLOWS FOR PROPOSED SUDCATECORIES
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(1)
FLOW
A1CD
EFF
F LOW
MGD
INF (1) eff
FLOW FLOW
MGD MCD
INF (1) EFF
Flow Flow
MGD MGD
I N f( 1) EFF
Flow flow
MGD MGD
MAX!MUM
MEAN
MINIMUM
MEDIAN
NUMBER OF
OB5ERVATIONS
10.700 . S.329
0.530 . 1.009
0.000 . 0.000
0.012 . 0.271
29 20
4.030 . 2.600
0.475 . 0.500
0.000 . 0.001
0.152 . 0.118
14 14
(]) Since effluent flow for these plants Is by definition zero, Influent flows
are presented
-------
should be noted Chat Che number of streams does not correspond to the
number of plants due to the existence of multi-scream 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
U. 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 cend 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 9usceptability 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
biotnass 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 almOBt invariably higher than BOD values for the Bame 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
-------
TAHLE 6-3
RAW WASTEWATER CHARACTERISTICS - PLASTICS ONLY SUBCATEGORY
DIRECT DISCHARGERS ONLY
INF
1 N
INF
lNf
INF
inr
INF
INF
IMF
INF
bOD
BOO
US
TSS
CCD
CO
TCC
roc
0*G
0ฃG
MG/l
LB/OAY
MG/L
l 0,'DAY
MG/L
UI/DAY
MC/L
LG/OAY
V.G/ I
LB/OAY
MAX IMUM
3520 . 0
25262.0
209B . 0
IG0B2.3
0330.0
51392.G
2751 .0
5560.0
242.0
2355.7
MEAN
506.2
3603.1
394 . 4
2263.0
1101 .6
0315.9
705 . 4
1 720.7
02.3
710.0
MINIMUM
2.0
13.0
5.0
1 . 5
27.0
60 . 5
9.0
13.0
23.0
/ 2.9
MEDIAN
349.0
1905.8
00.0
003 . 3
857 . 0
40B9.5
362.0
943 . 9
32.0
207 . 3
NUMBEI1 OF
O0SERVATIONS
49
49
42
42
45
45
B
0
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
CIOO
MG/l
1 N F
000
LO/OAY
INF
r?s
MG/ L
1 H (
1 ss
L n/'JAY
1 NF
COO
.VC/L
1 \r
C 00
L li /OAY
INF
TOC
VC/L
1\F
TOC
LO/OAY
INF
OSG
f.'.G/U
INF
OSG
LO/OAY
MAXIMUM
12042.0
417 0.0
1055.0
3 fi 1 . t
10 5-19.0
G 1 7 3 . 1
1 930.0
201.6
MEAN
4 110.7
1232.3
317.7
1 05 . G
5303.1
2060.4
923.0
02 . 3
MIN 1 MUM
30(3 . 0
111.7
0.3
1 . 7
4U . 0
6 . 0
31.0
16.8
MED I AN
1370.0
327 .6
237 .0
29 . 1
1422.0
1 107 . 4
BOO . 0
SG.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
I 1-iF
000
MG/L
|.\F
000
LB/DAY
INI'
i :s
mg/l
IMF
T1S
LH/CAy
1 \'F
COO
MG / L
INF
COD
LO/OAY
INF
IOC
MG/L
INF
IOC
LG/DAY
INF
OSG
WG/l
INf
06 C
LG/OAr
MAX 1 MUM
S9GI .0
249714.3
4 110.0
34 1 95.2
21170.C
20270G.2
3202.0
1 15196.9
17.4
351 .0
MEAN
170?.1
25975.2
44 1 . G
3 9 '19 . 0
4414 . G
4 0 360 . 9
836. 4
24792.7
11.4
1 00 . 1
MINIMUM
43.0
939 . 7
9 . 0
19.0
53 . 0
1409.6
20.0
49. 9
0.0
42 . t
MEDIAN
1036.5
13209.5
72.0
G72 .9
3302.5
19714.5
SI 3 . 0
13334.0
16.0
146.4
NUM3ER OF
OBSERVATIONS
42
42
2 1
2 1
34
34
2 1
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 INF INT 1u r |NF |N r [ M F 1N F INf IMF
noo 000 TSS IS s COO COO TOC toc ocg o&c
f'G/L IB/DAY MG/l LB/DAY MG/l LU/OAY KG/L LB/DAY MC/L L0/OAY
MA/. I MUM 52551.0 37H00.5 '15'J.O 7901. G 670S5.0 592G50.2 1)000.0 20182G.6 539.0 5B29.0
MEAN 11532.1 7 1 520.G 207.7 1 1 50.1 2GH ' . i 117315.G 5716.0 05117.3 539.0 5029.0
MINIMUM 150.0 2506.9 Gl.O 050.0 960.0 7C71.0 202.0 2 1000.1 539.0 5029.0
MEOIAN 6022.0 20550.7 103.0 3796.0 23711.0 71623.0 5019.5 56977.2 539.0 5029.0
NUMBER OF
OBSERVATIONS 7733901111
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
INF
INF
ItJF
i NF
I flF
1 HF
1 NF
INF
INF
000
R09
T'jS
TSS
COO
COD
TOC
TOC
OSG
0,".G
MC/ l
L U/OA V
MG/ L
L U/OAY
MC / L
L 0/DAY
M C/L
LO/OAY
MC/l
IB/OAY
MAX 1 MUM
2725.0
30913.0
26GC.0
1G925.5
3207b.0
71000.Q
5226 . 0
31009.9
570.0
591.2
MEAN
783.6
9300.2
079. 7
2620 . 7
0702 . 5
11902.2
900 . 0
6303.8
335.0
365 . o
MINI MUM
9.0
6.0
1 . 0
0 . 7
23.0
10.6
66.0
302. 1
17.0
90 . 0
ME 01 AN
467 .0
5620.3
170.0
590 . 0
1022.0
6139.0
272.0
2109. 1
01 8.0
4 10.2
HUMOER OF
ODSERVATIONS
21
21
1 3
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 Dage 109.)
-------
TABLE 6-8
RAW WASTEWATER CHARACTERISTICS -
NOT PLASTICS TYPE I WITHOUT OXIDATION SUBCATEGORY
ZERO DISCHARGE/ALTERNATIVE DISPOSAL ONLY
INF |NF INF IMF [NF
900 000 TSS rS S COO
MG/l LO/OAY r.'G/l LD/DAY IL
|M f INF INF INF INF
CC10 TOO TOC O&G Of.G
LG/CAY MC/L LO/OAY MG/L LO/OAY
MAXIMUM 3001.0 7597.G 207.0 75^.3 11960.0 290G7.1 2G4.0 G63.2
MEAN 1019.0 2010.0 10G.3 397.2 3G00.5 072G.G 223.0 523.1
MINIMUM 42.0 29.7 32.0 G2.0 |1.0 9.9 130.0 411.0
MEOIAN 495.0 1007.1 63.0 375.G 1211.0 2510.G 175.0 495.0
NUMOER OF
OBSERVATIONS 4 4 4 4 0 4 33
Note: Each set of observations represents a separate data subset. Calculations which combine
subsets may not be meaningful. (See Jast paragraph page 109.)
-------
TABLE 6-9
RAW WASTEWATER CHARACTERISTICS -
NOT PLASTICS NOT TYPE I SUBCATEGORY
DIRECT DISCHARGERS ONLY
INF
UOO
MG/l
INF
000
LB/OAY
I "ic
TSS
MG/l
1 t
-------
TABLE 6-10
RAW WASTEWATER CHARACTERISTICS -
NOT PLASTICS NOT TYPE I SUBCATEGORY
ZERO DISCHARGE/ALTERNATIVE DISPOSAL
INF
DOO
MG/l
1 NF
000
10/OAY
I NF
ICS
MG/l.
1 .'IF
: SS
113 / 0 A Y
INF
CCD
MG/l
INF
CO?
iu/Day
INF
TOC
MG/l
I N F
TOC
10/OA Y
INF
O&G
MG/l
INF
Of.C
10/OAY
MAX 1 MUM
1139.0
5l>4G . 0
3 3 17 0.0
103003.
3
2707-> .0
150002.1
9592 .0
1197 . 1
286.0
6106.0
MEAN
63 1 . 0
1 997.5
10230.3
06790.
1
901)0 . 0
37921.0
4076.5
660. 2
206.0
6106.0
Ml'J I MUM
193.0
1 67 . 0
6 1.0
70 .
1
5-16.0
072.4
161.0
1 39. 3
206 . 0
6106 . 0
MEDIAN
261 .0
1 79.6
3031.0
1639.
5
2956.0
2607 . 0
4876.5
660. 2
206.0
6106.9
NUM9ER OF
OBSEHVATIONS
3
3
4
4
5
5
2
2
1
l
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 6tream. 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
Preceding page blank
-------
TABLF 7-1
PปTNClPLC TREATMENT/DISPOSAL PRACTICE
ho
O
1
1
NOT PL
8TIC8 1
i not plastics ii
NOT PLASTIC
1
ALL
HABTE
1
plast:
CS ONI7 1
TTPE
* C* 1
i type t
NOT C**l
not tvpc I
1
STREAMS
PI)- PRINCIPAL 1
i*
I|
*ฆฆ
i
>
l
i
i
i
P03AL OCMCMTION I
NO, OF
1 NO, OM
no. or
NO, OPI
1 NO. OP
NO, OFI1
no, or
NO.
on
no. or
i no. or
COOC 1
plants
' M3U 1
plants
HA3TC 1
1 PLANTS
MA8IE II
PLANTS
MAS
c i
plants
1 NASTC
1
STPEa-SI
STREAM)!
3TR(am9I1
TRC
MSI
ISTREANS
2CRO DlSCnAHGE I
1 1
1 1
6f>N INC1hf R A TI ON |
1
1 10 1
2
II 1
1 1
1 1
1 II
1
i
i
7
1 24
CON CONTRACT MAUI. I
ll
1 It 1
0
0 1
1 1
> II
J
i
19
1 22
OP* DffP WELL |
2
1 5 1
2
12 1
1 0
* 11
I
i
7
1 27
0ซT 0ซY PROCESS (REPORTED) |
12
1 19 1
1
II 1
I 4
4 1 1
1
i
20
1 19
EVP EVAPORATION 1
2
1 2 1
0
0 I
1
0 1 1
0
i
2
1 2
I*P IMPOUNDMENT 1
1
> T I
4
9 1
1 1
4 | |
2
i
12
1 IB
LAP LAND APPLICATION 1
1
' J >
0
0
1 0
0 1 1
0
i
J
1 S
on ofF-ant treatment i
1
1 1 1
2
i
1 0
8 1 1
1
i
4
1 4
RTf RECYCLE |
9
1 10 |
11
tl
1 2
2 1 I
2
i
24
1 2S
total. ZERO I
ซป
1 47 1
22
52
1 11
20 M
11
2
i
94
1 162
1
DIRECT DISCHARGE 1
1 1
1 1
1 1
i
i
ALA AFRaTCD LACOON |
1 6 1
9
9 1
1 4
1 1
4 1 1
S
i
i
24
1 27
ANL ANALH081C |
0
1 0 |
2
2 l
1 0
0 ||
0
i
2
1 2
A*L AfPOBIC LAGOON |
2
1 1 1
0
0 1
1 t
1 1 1
1
i
4
I 9
ASL ACTIVATED SLUDGE 1
40
1 40 1
40
42 1
1 14
19 II
1ฉ
1
1
i
104
1 |07
0* T UNO! |
0
1 0 |
0
0 1
1 2
2 II
i
J
1 S
RBC ROTATING BIOLOGICAL CONTaCTORi
4
I 4 1
0
0 1
1 0
II
0
ป
4
I 4
TRF TRICKLING f 1LTER 1
1
1 1 1
0
0 1
1 1
1 II
1
i
3
1 J
m m m m
1 ----- 1
ฆฆฆa |
1 ,
a a a
ซ
| ฆ
TOTAL BIOLOGICAL ป
55
1 54 1
91
9) 1
1 22
23 11
IB
1
i
146
1 191
1
ACR AC TIVATfD CARBUN |
0
1 1
1 0 1
1
1 1
1 2
11
1 II
s
i
i
6
1 7
CLP CLAftJfICAllON |
s
1 T 1
0
0 1
' 1
1 11
2
i
8
1 10
oaf oi33oLvco air Floatation i
0
1 0 1
0
0 1
1 0
0 1 1
1
i
1
1 1
ซULtl-MtOU r TL TRAf ION |
0
1 0 1
1
1 1
1 0
0 1 I
0
i
1
1 1
Nfu NCUTHAL WATIUN |
0
1 1 1
0
0 1
1 s
i 1 1
4
i
4
1 10
Olป 9 OtL SEPARATION 1
2
1 9 1
1
2 1
1 0
o 1 I
1
i
4
| 9
PCF PPT,tCOAGULATION(FlLTRATlON 1
1
I I *
0
0 1
1 2
2 II
0
i
s
1 J
33* SK JMHINC 1
)
1 5 1
0
0 1
1 1
1 11
0
i
4
I 4
3TR STEAM STRIPPING 1
0
1 0 1
1
1 i
1 0
0 1 I
2
i
s
1 )
I ----- 1
1
ฆ ฆ|
i
| m m mmm
total non-biological I
11
1 17 1
4
9 1
1 9
10 II
19
. 1
i
19
1 4B
NOT NO TREATMENT |
4
1 1
1 1
s
6 1
t 2
1 1
2 11
1
i
10
1 1)
UN* UNKNOHN |
2
1 i 1
0
1 1
1 0
0 II
0
i
2
I 1
GRAND TOTAL |
116
1 146 |
bo
11 T I
1 44
S5 1 |
49
9
i
291
1 177
* 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 coBts 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 unit6, 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 wacer 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
operat ions.
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
downst ream.
- 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 plasties 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 used to remove toxic mate-
rials (i.e., metals, cyanide, solvents, etc.), the 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
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.
c
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)
Crompton and Knovles Corp. Gibraltar, FA
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
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
Houston Chem. Div. of PPC Beaumont, TX
ICI Americas
Iowa Army Ammunition Plant
Joliet Army Ammunition Pit
Kansas Army Ammunition Pit
Goldsboro, NC
Burlington, IA
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,
ni trotoluene
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
Explos ives
125
-------
TABLE 7-2 (Continued)
Liquified Coal Development
Corp.
Captina, WV
Anthracene-der ived
solvents
Lone Star Army Ammunition
Plant
Texarkana, TX
Explosives
Louisiana Array Ammunition
Plant
Shreveport, LA
Explos ives
Matlack
Swedesboro, NJ
Tank truck washing
Mobay
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
Pest ic ides
Organic chemicals
Organic chemicals
Organic chemicals
Owens Corning
Anderson, SC
Plastics and resins
Palisades Industries
Peace Dale, RI
Textiles
Peanwait
Houston, TX
Organic chemicals
Pfizer Chemical
Terrahaute, IN
South Port, NC
Brooklyn, NY
Greensboro, NC
Pharmaceutical chems.
Citric acid
Organic chemicals
Organic chemicals
Proctor and Gamble
Chicago, IL
Baltimore, MD
Kansas City, KS
Dallas, TX
Fatty acids
Fatty acids
Fatty acid6, alcohols
Fatty acids
Reichhold Chemicals
Tuscaloosa, AL
Phenol,
pentaerythritol, resin
Republic Steel Cleveland, OH Coke
126
-------
Rhodia (Rhone-Poulenc)
TABLE 7-2 (Continued)
Freeport, TXC
Portland , OR
Rocky Mountain Arsenal Denver, CO
Rogers Corporation Manchester, CT
SCA Chemical Waste Services Lewiston, NY
Schenectady Chemical
Sherwin Williams Co.
Stauffer Chemical
Stepan Chemical
Stephen-Leedom Carpet
Schenectady, NY
Chicago, 1L
Bucks, AL^
Lemoyne, AL
Richmond, CA
Dominguez, CA
San J06e, CA
Delaware City, DE
Louisville, KY
d
Geismar, LA
Henderson, WV
Skaneateles Falls,NY
Galliopolis Ferry,WV
Green River, WY^
Fieldsboro, NJ
Southhampton, PA
Tooele Army Ammunition Pit Tooele, UT
TRA
Union Carbide
Irving, TX
Hahnville,dLAd
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 Textiles
Vicksburg, MS
Yorktovn 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)
Toxaphene , methyl
parathion
Explosives
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
k Location not given in data source.
Information incomplete,
c .
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 suimnarized 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
-------
TABI.F 7-3
9TฃAK liSlPPJNG, AIL ปAi1l JI Rf AM)
.1 '
Nu>ซBlR Of 3fN(AMS ซ(PQNtlซC THI9 UChnOlOCI At MAJOR -AJUซAUซ IR|A1m(N1I J
cff
0UO
ปuo
BOO
T 99
T 90
199
CUO
COO
coe
U16
OU
016
FLO"
INF
Iff
t
INf
IFF
I
INF
CFF
*
INF
CFF
S
MCU
MC/L
MC/L
RfO
ซC/L
mG/L
Reo
MC/L
MC/L
ซEO
MC/L
MC/L
ฆto
MAllMU*
0,546
210.0
206,0
4.
1196,0
1*0,0
~0,5
MEAN
o, W5
210,0
112.0
04,
*41.1
*1.)
04,0
ftlN|ปUซ
0,700
2J0.O
w.o
ป.
05.0
10,0
*9,4
MEDIAN
0.J00
2)a,t
i*.o
04*
*1.5
26.0
04,0
NUMBER OF
observations 1
1
1
1 *
1
I
0
0
0
0
0
STEAM STRIPPING, ALL WASTE
9TREAM9
NUMBER
or 9 T RC Aซ3 REPORTING
TM13
a
TECHNOLOGY AS MAJOR KA 9 TE rtA TtR
TmEAThENTI 1
IOC
IOC
TOC
phenol
PhE*0l
phenol
NH IN
NH SN
NH JN
cซ
CR
CR
1"'
if r
X
INF
Iff
X
1 Nf
eff
X
INF
EFF
t
Mt/L
MC/L
RtD
*C/L
MC/L
REO
MC/L
MC/L
Reo
HC/L
MC/L
REO
HAH MUM
fl*2
0
160,0
07,*
hCAN
49?
0
145,1
07,*
ซ
M J N|NUN
492
0
15,0
07,* ,
.
MEDIAN
492
0
61.0
07.6
,
NUMBER OF
OBSERVaTIONS 1)1000000000
a Thesr dala arc ft ?. ;i1aiiiซ that
was ! tiWfl t er l r eiurrc n t s\ st
i;se this t erhnu 1. y'v ^ primioai ^orpon.-til of their
-------
END-OF-PIPE TREATMENT
End-of-pipe treatment refers to those processes that treat a combined
plant waste 6tream 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 treacment system. The technologies available for tertiary
treatment vary, but normally relate to the removal of specific pollutant
parameters not effectively removed in secondary treacment. 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. Mo 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.
Prec ipitat ion/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
-------
TAR1.F 7- (*
C L A A 1 M C * I * UN ซ ALk. *AJTE JTAtAKj
NUMBER U' 91REA*9 DiPORllNO TM|9 UCHnQLOCT ซ5 MAJOR HA9T(hATIR IRlAfMCNTI |0
I'f
FlO*
"GO
BUO
1 Nf
C'L
BUO
Vf
"fi/l
BOO
t
*cฉ
199
iNf
ซC'L
191
Iff
ซC/L
T99
1
ฆto
COD
lNf
Mf/L
coo
Ff
*6/1
coo
I
"ED
ou
INf
N6/l
0t6
iff
ซC/L
OIK
t
ฆto
MAI(MUM
J.TOO
VJ,ป
119.0
ea.T
170.0
90.0
1119.0
55,0
62.7
1.4
#
MEAN
0.067
1*0,0
09.8
ซ.3
'*.9
Tl,5
169,4
28.4
1.0
M|h|HUM
1,0V
9.0
1,0
10.9
11.0
ป.o
7.2
2.0
2.0
0.0
0.0
"(DUN
0.1ซซ
69,9
17.0
*2.0
60*0
lซ.9
91,2
120.9
96,0
29.4
1.0
ซ
NUซซe* 0'
OBsERvAIIONf II
4
3
4
6
0
4
J
4
0
I
8
U>
U>
CL*RlMC*t ION, ALL HA31E 9TREAM9
HUH0CA 0' fiTRfAM) REP0ปUwC THJJ UCHNOLOCT AS HAJQlf ซA9U*ATA TREATmEnTI 10
toe
TOC
10c
PHฃJ,Ul
phenol
phenol
NHJN
NHlH
NHJN
CR
Cfl
CP
i ปr
Iff
X
In f
EFF
X
INF
EFF
I
INF
EFF
1
MC/L
MC/L
OEO
MC/L
MG/L
red
MC/L
MC/L
RED
HC/L
HC/L
RED
MAXIMUM
103.0
116.0
17,9
.
.
1.5
0.3
99.2
MC AN
76.0
6T,9
17.9
.
.
.
.
1.0
0.1
69.4
MlNJMUM
9,0
17,0
*7.9
0.5
0.0
00.0
MEDUN
76.0
47.9
17.5
t
1.0
o.o
69,6
KUMBER 0*
083tซVAIl0NB
i
2
t
0
0
9
0
0
0
2
3
2
ซ ntcnc ('o'.a .ire fro- plants that use this technology as the principal component of
ilirlr trcaircr.t cvstcn.
-------
TABLT 7- 5
PPT , ,COACUi.AT ICS,f ll 1 RAUUN, ALL ฆ A 31E
NUMBER Of MAEAm) REPOHTIwC Th|J UCmhOLOCT Al MAjUR
IFF
FlOซ
MCO
BUD
)N'
"C/L
BUO
EFF
MC/L
BOD
1
red
T33
INF
"C/L
T3)
EFF
MC/L
T33
ซ
Bฃ0
cuo
INF
MC/L
coo
crp
MC/L
CuD
%
red
Ult
INF
MC/L
0(6
EFF
OiC
1
MAXJHUM
12,100
6i. 0
*12.0
72.*
004,0
52J.0
M CAN
ii,ปn
62.0
124,5
y2>
40*, 0
521,0
MINIMUM
4,400
62.0
17.0
72.*
8.0
521,0
MCOJAN
5,240
62.0
124.5
72.*
406,0
521,0
number of
OBSERVATIONS )
1
2
1
B
2
0
0
1
0
0
0
0
MA 3 TI aA 7 E fl T RE A T ME N TI 1
PPT,,COaGULATION,FIlTRATJON, ALL **STE 31 PC AM)
a
NUMBER or STREAM) REPOHTInC TH]3 UChnOlOCT A3 mAjOR HASTEkATER TREAImENTI J
IOC 1UC TOc P*fcซOL PhCNOL PHINOL Nhjn nh3N NHJN Cซ CR CR
inf Err x lur err * \ht ฃ r f x inf Err i
MC/L MC/L RED MC/L HU/L RED MQ/L HC/^ fltD WQ/L Hli/L Rt0
MAXIMUM
276.0 , .0.1, , 782,0
O.B
MEAN
276.0 , 0,1 , 782.0
0.1
MJKIMUM
, *76,0 , 0,1 , 762,0
O.B
MEDIAN
276.0 , 0.1 . 702*0
O.B
NUMBER OF
OBSERVATIONS
0 I 0 0 I 0 0 I
0
0
t
0
a These data .ire from plants thai use this ttfrhnolop.y
'-npop*>nt of their wastewater tre.itnienf system.
as
the principal
-------
enhance the efficiency of the flotation units. Although flotation ia
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 a6 a mean6 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;iicvtO A*a flo*ta<ซc->ซ AuL ซou
.1
NUiBtR 0' JIhUhS RlP0M*UC Inฃ5 UChnOlOCT 4$ m*JOR ซA9llซ4TER IhCAImEnTI I
EFF
aoo
euo
BOD
TSS
199
199
COD
COD
COD
U1C
oic
ou
FlOn
INF
Iff
k
INF
Iff
1
INF
trr
1
INF
Iff
I
*qq
Ht/l
ซC/L
*EO
HC/L
"C/l
RfO
*C/L
"G'L
Rt0
MC/L
Mfi/L
RED
MAIIMU*
0, JJซ
122.
42,0
1*2.0
HEAtf
o.m
122.0
42,0
162,0
MjNjMUM
O.JH
122.0
.
2.0
162.0
MEDIAN
0.11ซ
122,0
ซ2.0
162,0
NUMBER 09
OBsCAvATION* 1
0
1
0
1
1
1
0
0
0
DJ350LVED AIR FLOATATION, ALL "A3TE STREAM)
NUMBER OF STREAM) REPQRIInC Ihjs TEChNOlOCT A3 MAJUR*\
-------
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-] and 7-2. These fig-
ures were prepared by plotting the lognorraal 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 BOD, concentrations up to 1000 mg/1, and a
median effluent BOD, of 44 rag/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 rag/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 costentrat ion. Waste
137
-------
FICUKr 7-1
SYSTEMS - PLASTICS ONLY
IbTLVENT ItCDSCl 000*- MC/l)
cc 9S/IO0 OR JQDbFr LT SO 1tC/L
N-7
BIOLOGICAL
0.34
lyFLUSfiT BQ05
-------
FIGURE 7-2
BIOLOGICAL SYSTEMS - HOT FUSTICS ONLY
.OJH
.01-]
INFLUENT BOBSftOQO* MC/L)
RIM Cr 35/lOO OR BODSFF LZ 60 Of/1
ff*19
*fl3i
.82i
:kc
23 48 6B W '.B0 128 143 tbft
0. 04
B. HI
JSFLUtyr B063(SQQ-i0SQ MC/L)
A/rf CS 9S/tC0 CR aODirF IF 60 CW/i
ffslf
2e 4e ฃ0 bb ies i ?9 iซe i c*
WFLl'tXT tOQS(200-SQO ifC/L)
Jtfif cฃ 9S/I0O OR BOOIFF Lt Cd/L
Hปti
'1 j
0- '
MFLV8NT BOOSf0-200 UC/1)
kฃV CC S6/1C0 OR BQDtFF Li 60 CM/l
.V=9
te is iat
ฃFFLtENl 800<ซ-'L>
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 changea 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.
Ic is generally accepted chat temperature affects the performance of the
biological treatment process since the biodegradation rate is tempera-
ture dependent. The relationship usually employed is:
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
0, a dimensionless coefficient.* A value of 9 equal to 1.00 would imply
that the reaction kinetics are unaffected by changes in temperature. As
the value of 0 increases above 1.0 the reaction becomes increasingly
sensitive to changes in operating temperature. The value of 0 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 ratio6 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.
[7-4] ...
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 (4-24 C)
occurred.
* which must be determined empirically
where
0 - temperature coefficient
140
-------
o
o
UJ
o:
<
q:
LlI
q.
UJ
I
F/M = 0.2
F/M = 0.4
F/M=0.3
I I
F/M=0.5
i
100 98
94 92 90 88 86
PERCENT BOD REMOVED
82 80
figure _Zii.TEMPERATURE EFFECT ON EFFLUENT
QUALITY
141
t
-------
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 rag/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 terra), 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
variations.
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, bioraass 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 sunlighc 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
kl*HtO LACOON, ALL STREAMS
a
NUMBER OF S?R|A*3 R|P0ซTlN0 1M|3 1ICm*OIOC* A3 MAJOR nASTIhAHR IREAlMENTi 27
IFF
BOO
bUD
bod
T S3
13S
tas
COD
COO
coo
Oftt
oic
oic
FLO*
INF
IFF
x
INF
CFF
X
INF
IFF
X
INF
IFF
&
MQO
MC/L
MC/L
Bed
"6/L
MC/L
RED
M6/L
MC/L
"ID
MC/L
MC/L
RID
MAXIMUM
19.900
1117.0
279.0
*8,ซ
1*5.0
98.7
21178
1170,0
98.0
570.0
112.0
80,0
MEAN
3.156
4Tf,l
*0,2
550.1
*2,6
51.2
4229.5
27*,
82.
570,0
SO.5
80,0
minimum
0,008
94.0
7.0
23.0
2.0
-56,5
120,0
30.0
66,5
570,0
1.0
80,0
HfOIAN
0,812
514,5
19.0
285.0
11,0
*1.1
1127.0
1)5.0
81,5
570.0
11.5
00.0
Nuh0(R OF
t
ObSERVaIJONS 26
10
21
10
II
22
II
II
19
10
1
0
L/i
AeRATCD LACOONi all HA9TE STREAMS
a
NUMBER or STREAMS ซEP0ซTING Thj9 TCCH*OlOCt AS major *A3T(MAlEfl TRCaTmeNTI 27
IOC
INF
MC/L
IOC
iff
"C/L
ioc
I
RID
phenol
INF
HG/L
Phenol
IFF
MC/L
PHENOL
X
RED
NMJN
INF
MC/L
NH 3N
Iff
MC/L
NHJN
X
RED
CR
INF
MC/L
CR
Iff
MC/L
CR
X
RED
MAllMUM
2056,0
133,0
86,1
2395,0
lซ,0
99,7
19.0
240.0
00.5
0,0
1.)
50.6
ME AN
503.7
08.|
61.0
05ซ,1
O.J
99.5
10,4
54,4
52,7
0,0
0.1
54.6
MINIMUM
20,0
U.O
25.0
2.5
0,0
99,2
1.8
I.I
22,2
0,0
0.1
50.6
*E0!AN
332.0
34.0
6J.9
709,5
0,8
99.6
10,4
3,7
54,0
0,0
0.2
54,6
NUMBER OF
objervat JONS
7
7
6
8
6
3
4
7
4
1
6
1
o These data are from plants that use this technology as the principal component
of their wastewater treatnent systen.
-------
TABLE 7-9
Km, tb/ L*OOCmป ''tAjlJCS 0*LT
J
HUM6IB Of JTRlAMj hCPOHTINO THIS TECm*OIOOv At MAJOR VAllCVATCN TREATMENTl |
Iff
BO0
BOO
BOD
TJJ
T5J
til
coo
COO
COO
O40
OAS
046
fLOtf
INF
err
%
I NF
err
t
|Nr
err
%
INF
err
%
MAO
M0/L
M0/L
Re o
MO/t
Mซ/L
PPp
MO/L
MO/L
Rto
MO/L
MO/L
REO
MlJHUM
1.990
44?,0
96.0
ซ0.4
449,0
'T.O
5)1,0
>34,0
4.0
t
14,0
MEAN
NZl*
220.0
10.1
9*0
*41,0
T.O
)ปi0
114,0
TT.f
T.f
minimum
O.UT
*.0
T.O
ฆa,*
443,0
11.0
T.O
1T9.0
30,0
TO,4
I.I
ME01AN
C.AM
ll*ซ0
15.0
oev)
441,0
|9ซ0
T.O
369,0
104,9
TT.f
T.l
numkck OF
OQieRVATIOMI $
3
T
i
1
4
1
I
4
ซ
0
t
0
AERATED LAC00Ni PLASTICS ONIT
nUnBCR
or STREAM) reporting
TMJ3 TEChsOLOCT AS mAJqr naSTCnaTER
trcatxEnti e
TOC
TOC
TOC
PHFNOL
PhEnOL
PHt NOL
NH JH
NhJN
NH IN
CR
CR
CR
|NP
Iff
X
InF
EFF
I
INF
IFF
I
INF
Iff
1
MC/l
MG/l
RED
MC/l
MC/L
RED
MC/L
MC/L
RED
mG/l
hq/L
RED
MAXIMUM
MEAN
mjnihun
MEDIAN
NUMbffi Of
OejCRVATIONJ
0.1
0.1
0.1
0.1
1
0.0
0,4
o.ซ
0.ซ
Thcoc data arc frorr p.or.-.s that uoc thfo trchr.o*, opv ac the principal component
of their w.i:;rov.iccr trcnincn- cysrcn.
-------
TABLE 7-10
AthAltO w.-UOg*, NOY Pl.MT|C* HTM I i Cป
*UM0E* 0' 1T0CAM) RCPOHTINO ThII HChnpluOOt A1 MAJOR WtlTfWATE" TREATMfNT| ซ
Iff
FLOW
MOO
000
INF
MO/L
*00
Iff
MO/L
BOD
%
nco
Tป1
INr
MO/l.
T*S
IFF
mO/L
TU
%
REp
COD
|Nf
MO/l
COD
Iff
MO/L
COO
%
REO
049
INF
MO/L
010
IFF
mO/l
010
%
RED
HillMUM
liiieo
an.o
151.0
90,*
649..0
399.0
41.1
(1170
1170.0
9ซ.I
9.0
mean
3.710
934,7
Tt.)
7,1
11*. *6
1*1.*
IM
9lJf,0
*11.9
0*.3
9.0
MINIMUM
0*001
199,0
T.O
63,1
VI..0
*0.0
94,0
1317.0
138.0
1.1
1
9.0
MtDMN
1.010
911.0
*1.0
97,4
73..0
41.0
7119,8
194.0
0I.T
NUMB!* Of
OBlflVATfONI 9
3
T
3
ป
ซ
9
A
T
4
I
0
AERATED L*r.COONซ NOT
PLASTICS (TYPE I & C)
NUM0CR
O' STREAMS REPQRTInC
1H J 3 IECHNC..OCT A 9 MAJOR WASTEWATER TREATmEnII 9
IOC
IMF
MC/C
TOC
Iff
MQ/L
TOC
1
RED
PHEKC..
INF
MC/L
PHENOL
fFF
MC/L
phenol
X
REO
NHJN
IN?
MC/L
NHJN
Iff
MO/L
NHJN
X
RED
CR
INF
NC/l
CR
EFF
MO/L
CR
I
REO
MAIIMUM
51 J.0
64,0
80.I
1.4
09,7
19,0
129,0
00.9
0.4
1.3
94.6
MEAN
288, 3
ซ6.7
60.6
7tf9.;i
0.7
99,7
15.9
34,0
63.3
0.4
0.4
90.6
MINIMUM
20,0
>5.0
25.0
0.0
99,7
t*.o
I.I
90.0
0.4
o.i
94.6
MEDIAN
332,0
6|,0
60.7
709.: s
0.7
99,7
19.9
ซ.a
69.3
o.ซ
0.1
94.6
NUMBER or
OBSERVAl10N3
s
J
1
i?
Z
1
2
4
2
1
9
1
* 1 Type I v/oxidation
a These data are from plants that us* this technology as the principal component of their
wastewater Treatment system.
-------
TABLE 7-11
k*vwi/li| -
-------
TABLE 7-12
AfAATCD IAOOOn. NOt PLAjTlC* INOT tTPC II
a
NUMBCR or PCPORTlNO THIS UChNOlOOy Aป MAJOR ซซSKซA1(N 1D(AtM(NTI *
191
BOO
"00
POO
Til
TSJ
TซS
coo
eoo
coo
04O
010
01*
now
jwr
IFF
%
INF
IFF
ซ
iwr
fFF
B
IN*
Iff
t
MOO
HO/L
MO/L
RED
M6/1
MO/l
'(0
ho/u
NO/U
PtO
HO/U
MQ/L
PtO
MAXIMUM
19,900
IT9.0
91.6
ni.o
)t,t
ฆ .1
<6.0
10*9.0
44,ป
44.0
MCAN
T.66S
99.0
9.T
91.4
6,0
16.5
4T.9
*46.0
>1.3
46.5
t
44.0
MINIMUM
0*601
9.0
1.0
1.6
S4.0
C.o
5.'
246.0
*0,0
66.9
44.0
NfOIAN
4.0*0
99.8
11.0
1.6
66.0
19.0
4*.9
*46.0
09.0
66,5
44.0
9
NUM0CN 0t
08SCBVAT10NJ 9
1
3
1
t
1
t
1
3
I
0
1
0
AERATED
IACOON
ซ NOT
PLA5TJC8
(NOT
TYPE I)
NUMBER or eTR[ซHJ REP0R11NG 1M] 9 UCHNOIOCy A3 MAJUlf nASTEhATER 1REATNENTI 6
10c 10c 10c PMtNOl Phenol PmEHOL NhlN SHIN NHJN [R CR CR
|NF EFF I INF EFF I INF EFF I INF EFT >
Ki/l MS/L RED mG/L Mb/l RED HC/L ซG/l RED NG/L "G/L RED
HjfrjMUM
*02,0
153.0
*3,9
2395,0
10,0
99.6
6,8
240,0
58,0
0.1
.
MฃAN
40|,7
61,0
21*5.0
10,0
99. ft
8.0
121,8
58,0
0.1
.
NlhlMUM
35.0
16,0
50.0
2395.0
10,0
99,6
8.8
3.T
58,0
0.1
.
MEDIAN
68.0
34.0
5o.J
2395.0
10,0
99,6
8,8
121,8
56,0
0.1
.
NUMBER OP
OBSERVATIONS
3
3
3
1
1
1
1
2
1
0 1
a T.icsc d.nta arc fror that use r.hie technology ac tho principal conooncnt of
tK/v
-------
TABLE 7-13
NUMBER OF SIRIAmS RlPQHTluG 1m|9 IICm0l0Cป A3 hAJOR1 ซA3llซAltR TREATmENTI J
CM
000
000
000
TSS
133
US
COO
coo
COO
U&C
QIC
ou
FLO"
INF
Iff
t
I
iff
1
1 Nf
Iff
x
INF
Iff
1
Mtu
*C/L
MC/L
"CO
ซc/l
MC/l
"ED
ซfc/L
*6'L
ซco
"6/1
ซga
RED
MAXIMUM
J. WO
78.0
*2.0
06.5
".0
iw.o
6.0
ซ
ปCAซ
1.479
76,0
17. 6
66.9
.
16,6
166,9
6.0
M|N|HUN
0,|99
76, #
7.0
66.1
.0
*
69,6
6.0
"tO UN
1.500
70,o
10,0
66.9
16,6
t
166,9
.
6.0
NumBLA OF
OBSERVATIONS
9
1
S
1
0
9
0
6
I
6
0
1
0
L/l
ฐ Af RDBIC L'COON, ALL N A 3 T E 3TREAMJ
a
NUMBER Of 3IRCAซ3 REPORTING IHU IECHnQlOGI A3 MAJOR ซA3TEnATER TREATMENT I 5
IOC TOC TOc PHENOL PmENOl PhENOL Nnjn NH1N NHIN CR CR CR
|NF Iff I INF Iff I INF Eff * INF EFF I
Mt/L MG/L REO mc/L MC/L RED mC/l MC/L REO MC/L "G/L RED
HA 11 MUM
66.0 46,0
n,i . o.*
0.0
0.1
0.3
99.1
*UN
66,0 31.9
M.2 0,0
0.ซ
0.1
o.I
99.1
M1N JMUH
66,0 19,0
71,2 . 0.1
*
0.*
0.1
0.0
59,1
MEOIAN
66.0 31,9
71.2 . 0,4
ซ
0.4
ซ
b.l
0.0
99.1
NUMBER OP
OBJtBVAlJONS
1 2
1 0 2
0 o
I
0
I
>
1
0
Thcor f'a'a nrr fron plnntc u~c
t^clr "*ot?v'0tpr treatment nvsttrr.
rHin r.cchnolory
an
the princln.i"
comoonont of
-------
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 i6 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 bioniass 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-aerat ion, 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
ANA(POo i C i ALL ปปปIl
a
MUHBtB OF 9TN(ซhs REROUTING Ihjs ICCm*OiO&| AS MAJOR WASTEWATER IREATNENTI 2
iff BOD HUO 800 TS8 TJ8 T3J CUD COO COD Ult 016 016
fLO* In? iff % jnf iff x inf iff t hf iff i
ซC0 *C'L ซ&/L ft(Q Mc/L Ht/I. Bto mc/L *C/L *CD "G/L Mg/L RED
MAXIMUM |j,209
9 70,0
22.0
*7.7
>b,0
2109,0
147.0
01. 1
MCAN 8,225
6Mt5
'0.5
*5.?
.
06,0
. H2I.0
7.5
70.2
H|fซ|HUN 4.250
319,0
iซ.o
4.0
06,0
51.0
20.0
7.2
MEDIAN 8.225
6*4.5
20.5
95.9
.
06.0
1121,0
7.5
70.2
*UMB(R OP
0BjtflปA!10NJ 2
2
2
2
1
2
2
2
0
ANACRQBic
ALU
HASTE STREAMS
a
*UWBฃป OF Sป*CamS REPORTING IMi# TECHNOLOGY A3 MAJOR *A 3 T Eha TC R TREATMENT! 2
TOC
IOC
T0C
PHfHOi.
PhEnOl
PnENOi.
NH JN
NH 3N
Nm JN
cซ
CR
CR
INF
Iff
t
INF
EFF
1
INF
IFF
I
INF
EFF
I
MG/U
ซC/L
RID
*G/L
"G/L
REO
"C/C
HC/U
RED
HC/i.
MC/L
RED
MAXIMUM
695,0
74,0
89,4
,
.
.
ซ
MEAN
411.5
51,0
ฆ1.7
.
.
.
.
.
minimum
128,0
28,0
78,1
.
.
ซ
.
ปEO!AN
411.5
51.0
0J.7
.
NUMBER OF
OBsERvATIONS
2
2
2
0
0
0
0
0
0
0
0
a These data arc from plantsthat use this technology as the principal component of
their wastewater Lreainerc svstcn.
-------
TABLE 7-15
ปctiปปico sluocc, 'll ซปjiฃ juca"*
number of simcamj ซepoซUng ihu iicmnolOUt aj ซปJoi? nซsifซปuป TheainCnti iot
Iff
BUD
000
BOD
T 93
(39
T 19
COO
CUD
COD
OtG
ou
Oi6
rtox
INF
Iff
1
INF
Iff
1
INF
IFF
ft
INF
ซpr
ft
mco
HC/l
MC/L
RgD
"G/L
*ซC/L
R[D
*ft/L
MC/L
"to
Mซ/L
Mc/L
ฆto
MAlfNUN
40,900
5941,0
roo.o
*0,7
0110,0
051.0
W.I
12474
11000
90.1
242,0
oo.o
90. F
MCปN
2.an
1214.4
5T.4
512,9
40.1
43.1
1000,6
059.2
0|.l
5ฎ, I
10.
S9.1
NJH1HUN
0,008
10.0
1.0
07.5
271,0
210.0
34,0
10.1
>ป.o
0,4
!ซ.*
Mซ01AN
I.0T0
754.0
24,0
95.4
114.0
45.0
62.9
1400.0
tao.o
eป.9
21.0
4.0
47.4
NUmOE* OF
0*3l*VAU0N$ |0T
IS
101
as
SO
90
SO
71
79
70
7
17
4
ACTIVATED SLUDGE, ALL "AJTt STRtAHS
0
number or streahj reporting tซiป UChnologt as major ปajteปaier treatmenti iot
TOC toe 10c phenol PHENOL PHENOL NHJH NH3N nm JN C* CR CR
INf err I INF EFF t INF IFF I INF Iff I
MG/L "C/L "to HG/L ปG/L RED MC/L HG/L RtD MG/L MS/L RED
MAXIMUM
5224,0
405.0
99.5
747.0
34,0
100.0
190,0
274,0
91.6
2.1
10.0
97.2
mean
1025,6
121.2
eo.T
145.4
2.3
92,2
75,1
11,4
10.9
0.4
0.*
-80.2
HJHJMUM
*'.0
7.0
lb.5
o.l
0,0
41,5
0.6
0.4
-107.4
0.0
0.0
1129
median
505,0
49.0
09.4
10.1
0.1
90,7
10.0
4.9
27.0
0.2
0.1
71.4
NUfBCS OF
Oft&CSVAUONS
29
29
24
IB
26
18
21
00
22
12
21
11
a These data are from plants that use this technology as the principal component of
their wast o'aLcr treatment system.
-------
TABLE 7-16
0' STftlAMl f)( POM T | NO THIS TlCHNr.L.OOT A1 HaJOR Ul31CVAT(H T*ปrATMfNl| 4ft
no*
MOO
jwr
MO/l
Iff
MO/i,
Boo
ซ
ซo
m
M0/L
TSS
Iff
MO/L
TH
1
eco
COO
INf
MO/l.
coo
Iff
MO/L
Coo
%
ftto
019
INf
MO/L
C ff
MO/L
010
%
ฆto
HAIIMUM |0.TOO
)SfO,B
*1,0
99.7
)lft, c
IM.O
*338.0
6*0.0
*ฆ,1
241,0
ฆo.o
TM
ปCAN
1**31
416.ฆ
17.ft
*3
SOJ.L
44,ft
91,1
1302.1
lia.i
H.I
lOt.O
|B.ft
ftM
MINIMUM
0,0)4
l*.ft
3.0
7#.l
fl.V
T.O
-41.5
>10,0
34,0
4ft,I
13,0
M
u,f
NfOI*N
0.*03
390,0
10,B
96,ft
101.X
30.0
46,0
900,0
7,0
*,0
41,0
T,0
4ft,3
numrir or
oiurvationi
40
39
31
3:
J*
31
33
34
SI
)
9
ACTIVATED ULUDCC, PL A 3 T IC 9
ONLY
NUH8ER
OF 9fflEA*s REPORTInC
THIS
TCCHmiilOCT *9
major haSTEhatcR TRCaTmCnTI
00
IOC
INf
H&/L
IOC
trr
MG/l
TOC
I
RED
pH[ NI'JL
i*r
MC/'l
P nENOl
EFT
NC/L
PhTNOU
X
HEO
NHJN
INF
Mt/L
NhJN
Iff
MC/L
NHJN
t
RED
cfi
INF
MC/L
CR
Iff
MC/L
CR
1
fieo
MAII HUM
2751 a 0
96,0
99.3
ซ2* .0
0.5
100,0
09.0
109,0
09,6
2.0
0,1
97.2
MEAN
1103.ซ
ซe.2
06,7
71.6
0,1
06.9
16,5
6
-27,0
0.6
0,1
51,5
MJN1HUM
2ซ0,0
15,0
0-1
0.0
61.5
0.ซ
197,4
o.t
0.0
-50.0
MEDIAN
460,0
ซ),9
90,5
0,1
0.0
92,0
6.0
6.0
23.0
0.2
0.0
01.4
nuhbcr or
OBSERVATION)
5
6
0
6
9
6
10
16
9
ft
7
ft
a These data are fiom plnntsthat use ihis technology as the principal component of
their uasv.rwaier troatne^t 6ys:em.
-------
TABLE 7-17
hy-lfH OF ITBtAN? RlR0ปTJMQ TH
* CI
9 TlCn'tOiOOv AS Majqb wAtT(ปATE* T*EATM(NT| 4t
Ln
Ln
IFF
BOD
BOO
BOO
tit
TSS
Til
coo
coo
coo
01*
Oift
0*9
no*
I*f
Iff
I NF
Iff
1
l*F
Iff
%
1"'
CFF
t
hod
MO/L
mo/l
P
0
MO'l
tp
h#/l
mo/l
BtO
Hfl/L
MO/L
MO
MAXIMUM
<000
mue
ซtl,t
9
.ft
*110,0
133.0
91.9
'zn.o
4079,0
98.1
IT.4
14,1
H.ft
Mt AN
1.659
19Tft.8
84.0
ฆ 0
*2l.ft
8*ปI
*ft.7
tftf.l
79,8
Ift.T
7.1
If.ft
MINIMUM
o.ooa
H3.0
*.0
4
ft
ia,o
-------
TABLE 7-18
ACiiVA.tJ iwOOftt, ซul id 17 ft * ..wi C) *'
a
NUMUCR OF 9TREAN9 REPOR||NC Thj9 UCmnOlOCT AS MAJOR ฆ aSTCwaUR 1REATMEMI 19
EFF
MOD
BOO
BOO
T 99
199
T99
coo
coo
COD
Olc
016
010
FLO"
INF
CFF
1
INF
CFF
1
INF
EFF
1
INF
CFF
1
NQO
HC/L
MC/L
RfO
*C/L
NC/L
RED
NC/L
NC/L
"CO
NC/L
ซC/L
"CO
HAIIMUH
4,510
2729,0
700.0
97.?
700,0
6)1,0
61,0
12476
11000
06.1
17.0
15.0
59.)
ฆCAN
1,551
1267,7
112,2
90,4
lis,2
156,1
41,2
6661,4
1611,9
2.5
17.0
15.0
js. y
M1NIMUN
0.020
66,0
u.o
70.ฎ
115,0
16,0
-9,1
111,0
40,0
66,1
17,0
u.o
M.l
HEDUN
1 .440
1015.9
28,0
92.7
177.0
71.0
00.1
1440,0
197,9
70.1
17.0
15.0
15.)
NUMBER OF
OBSERVATIONS
1 IS
10
IS
10
S
II
9
7
6
7
1
2
1
ACTIVATED 9LUDCE, NOT PLASTICS (T TPฃ I NOT C)
a
NUHBCR OF STREAMS REPORTING 7*13 TECH*3tOC* AS MAJOR hASTEhATER THEaTMENTI |5
IOc TOc 10c PซE*ปOl Phenol PmENOL NmJN NhJN nhJN Cr CR CR
INF Iff I J Hf e F F * 1hf IFF I INF EFF I
HC/L HC/L BED MC/L HC/L RED ซC/L mC/L RED mG/l HC/L REO
MAXIMUM 5226,0
S0| .0
ป7,5
16.0
1.0
99, 1
255,0
60,0 9),a
0.0
MEAN 1144,1
111,5
80.4
14,1
0.7
95,6
132,5
28,2 79,7
0.4
MINIMUM 67,0
7.0
ซ6,4
10.7
0.2
12.6
12,0
1,6 65.7
0.ซ
ME 01 AN 411,0
70,0
70.7
14.3
0.6
95,6
112.5
15,5 79,7 .
0.ซ
NUMBER of
OBSERVATION) T
6
T
2
1
2
2
4 2 0
1
* Type I v/o fixirfat ior.
a These data arc from
pl;ซptb
that i
isc
: t cc'~.
n3 e
nr' ".c: 1 z"
of r'-
rrca'.r:r.: system.
-------
TABLE 7-19
ACTIVATED SlUOoE# hot PlAjtlCi JhOT TTH |)
A
hu*Bฃซ OF 9TR(Am5 Bt^O^TjNO THIS TlC**OlOOr AS major WAlTf KATE" TRCAT*CNTl |0
fLOM
POn
poo
TiS
TJ1
Iff
ซ
INF
Iff
KO/L
RCO
M8/L
UO/L
ซ
TI* COO
ft J*f
ฆCo Hfl/l.
coo
Iff
HO/L
too
ซ
Pto
OiO
| Hf
H8/L
010
Iff
M9/t
old
%
PปCD
NAAtMUN
40*000
920.0
1T.0
97,0
1160.0
101*0
9T.3
5460,0
413.0
90,0
90a|
3.0
MEAN
9*991
in.t
15. ft
43?.0
AUK
33.t
IT0ป.3
159.2
Tf .ft
90.0
1.1
00.T
MINIMUM
0.315
10*.0
3.0
*1.5
1T.0
10*0
TO.4
*10.0
65.0
4.f
90ซ0
ซ.r
ซ.T
HfOfAN
1.445
314.0
]ซซ
~*.l
tri.o
lป.o
ซ.ป
ซซr.o
111.0
ri.t
JO.O
tl.T
ปU*0C Of
OBSfRVATIONS to
ft
i
9
9
9
1
s
I
L"
-sj
ACTIVATED 31UOCE, NOT PIAJT1C3 (NOT TTPC 1)
a
NUMBER or 91RCAHS REPOhUnC ?H]3 TECHNOLOGY A3 hAJQR "AJUmATLR IMEATmENTI 10
IOC IOC !Oc
INF err i
Ht/L MC/L RED
Phenol. PhEnOI Phenol NhJN NhJN NHJN CR CO CR
1Hf Iff 1 [NF IFf I INf IFF I
mc/L hC/L RED H&/L MC/L *EO *G/l *C/l RCO
MAllMUN
|9Q,0
01.0
4.0
0.2
96.9
65,6
64.1
2.1
O.T
10.0
90.5
MEAN
16a.5
ซl.O
2.2
0.1
95.9
33.2
22,4
-5,1
0,3
2.1
-396.0
minimum
1*5,0
1.0
o.J
0.0
95.0
0.0
0.9
-12.5
0.0
0,0
-1329
MEOIAN
I0oป5
1.0
2.2
0.1
95,9
33.2
2.2
5.1
0.2
0.1
50.0
NU^BJR or
OBSERVATION*
2
1
0 2
s
2
2
3
2
3
5
3
a These data 3rr from places that use this technology /is the principal component of their
wactcwarcr treatment systcn.
-------
TABLE 7-20
Kirr "x'^'rn Arrtvnted Slud>-c
AIL -.rฃAH>
a
NUM0C* or 91MCAN) Rt'OHlINQ TซI$ UChnUlO&| A9 MAJOR flABr(ซAl(R TRCATMfNTl 1
irr
L0ซ
MCO
BUD
|Nf
MC/L
BUD
Iff
MC/L
BOD
1
BfO
in
INF
MC/L
199
CFf
MC/L
T 99
I
"CO
coo
INF
MC/L
COO
err
MC/L
COP
1
"CO
oic
IHF
MC/L
OK
err
Mq/L
OIC
t
to
maximum
.160
ซ67,0
26.0
97.2
204,0
58,0
345,0
105.0
65,2
NtAN
,850
210,0
18.7
90aB
1)1,0
25.0
522,5
18.0
75,1
M|N|NUซ
,950
lซJ,0
il.o
ฎT.O
98.0
JO
500,0
51.0
65,0
MEDIAN
,580
200.0
I 7 #
ea.i
151.0
25.0
M.3
522,5
7B,0
75,1
NUmBC* 0'
UbSlRVAflON)
1
)
3
2
2
2
2
2
0
0
t
Purr Oxygen Actlvarod Sludge
ALL NAS1C 8Tfi[iM3
a
NUH6CA OF STซC*H3 NCPOHTInC IHJJ TEChnulOCT A3 MAJOR "MTEKATtR TREATnENTI 3
IOC IOC roc fHlhUi, PHENOL PHCNOL NhJN NHJN NH}N Cซ CR CN
|hr irr x isf cff t \nf iff i inf trf x
"C/L MC/L RtD mC/l mC/L REO MC/L ซC/L RIO MC/L' MC/L ซCD
MAXIMUM
15.0
26,0
65,5 8,1
0,fl
99,0 ,
.
mCAN
75,0
2ป,0
65,5 5.1
0.2
96,8
MJNJMUM
e
26,0
65,1 2,0
0,0
9ซ,T ,
MEDIAN
75,0
26,0
65.5 5.1
0,2
ซ6.a
nUmBCR OF
obscrvaiJONJ
1
1
1 2
2
2 0
0 0 0
0
J
These rfa!"
their was
n arc f
: cw.iicr
rom p]anปo:hat ui;r
ticarrcn: yystcci.
rhlo technology
as the principal
component
of
-------
can be single or two stage. The most suitable medium in both Che 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 721.
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 o^ 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 9haft 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 6ome 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 step9 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-
ment (PAC) refers tothe addition of powdered carbon to the aeration
159
-------
TABLE 7-21
NUMBER Of 9TRLAปS R|PORT1nฃ Thj I ILCm*ปJl06t A9 MAJOR aASIlNAKR TH(AfMENTl 1
Iff BOO BOO 800 193 (99 189 COO COO COO U&t 016 016
FLO" INF Iff I (Nf Uf \ INF Iff X INF Iff I
-CO hc/l HG/L RtO ซG/L MG/l ซtO MG/L MC/L *ED MG/L Hfi/L 8(0
maiinum J.5?o
ซai
0
31,0
1225,0
*5.*
1*79.0
250. 0
6T.8
M*N l.TJI
SIO
0
26.0
<0,0
WT.5
3a, 0
76,1
1021,7
1*1,0
79.1
MINIMUM 0#ซ1S
170
0
*3,0
30,0
13. 0
56.r
210,0
*3,0
70,0
MCOIAN 1.200
0
2ซ,0
fts.t
*3*. 5
34,0
76,0
1*6,0
7ป.ซ
NUMBER Of
observations J
1
1
1
2
2
a
1
1
1
0
IfljCKLlNC FRTtR, ALL "*9Tฃ SlREAMJ
<1
NUMBER OF 91RฃAป9 HEPONTING 1HJ9 ItCMNOlOGr AS MAJOR KASUkATER TREATmENTI 1
?0c 10c TOc PHENOL Phenol Phฃh0L NHJn NHjN NhJN CR CR CR
|NF iff 1 InF EFF t INF IFF I IN? Iff I
MG/L m^/L RED *C/l HC/L RED MG/L MG/L ซE0 MG/l HG/L ซED
mAkimuM
MEAN
M(N|MUM
MEDIAN
NUhBER op
observations
3,0
t.O
66,7
,
3.0
1,0
66,7 ,
3,0
1,0
66.7
3,0
1,0
66.7
1
1
1 0
0
0
no!ogv
a 3
the principal
conooncnt
of
t-icir wastewater trcaLncnt syotco.
-------
TABLE 7-22
6 !(" Cb < *k I I *kl
a
NUmBEr OF 3181**3 rLPomDnC 1HJ3 HChnOLO&T AS HAJOR ฆ*9TIha1Cb iRCATpENTI 4
Iff BUD BUD BOD MS 199 T99 CUO COO COD UlC olt Olt
no* INF iff l In F iff I INF IFF I INF Iff I
M&O ซC/L *G/L RfD "C'L NC/L RED Nft/L MC/L *ED MC/L MC/L "CD
MAXIMUM
2,lซ0
1200.0
W.t
1.0
25.0
2174.0
186.0
92.1
2
1
MEAN
0,904
l)ซ,0
)0.5
BO,A
Jซ.5
29.J
ta,ซ
659,8
99.0
71,5
2
J
M|N{MUM
0.0M
51.0
4.0
ซ!.
20.0
15.0
12. 2
'7.0
13,0
3l.i
2
3
MEDIAN
0,41 J
2ซ2.*
JJ.O
92,5
34.5
ป0.0
IB,4
ซM,0
96.5
65,A
2
1
number of
08 sER VA|(ON) 4
4
4
J
I
4
4
4
0
1
ROTATING 6I0L0GJCAI CONTiCTOH, ALL PASTE STREAM)
a
fclMSCft Of 9TREAM9 PCPOhTJnG THJS TECHNOIOCT A3 MAJOM "ASTEhaTER TmEATmENTI 4
10c 'UC TUc Phenol Ph[n0l Phenol NhjN nhJn nhJN C* cr c*
)NF EFF I ]UF iff I INF Iff X iNf Iff 1
HC/L MC/L ซE0 MC/L ซC/L RED MC/L mc/1 ปID mG/l hc/L REO
MAXIMUM too
0 71.0
29.0 .
".0
9.1
0.1
66.9
MEAN 100
0 Tl.O
29.0
*ป.o
0.1
0.1
66.9
MINIMUM 100
0 Tl.O
29,0 ,
ซ.e
0.1
0,0
66.9
MEDIAN 100
0 Tl.O
29.0
2ซ.0
o.l
0.1
66.9
number op
observations
1 1
1 o
0 0
0
1
0
1
2
1
a These data
arc fron.
plants that
use this technology
hb the
principal component
of t
vao town tcr
I rc.it :nci)t
cystcm.
-------
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 PAC 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 syscenis 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/Ultrafi1tration - 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
Nu^BlB OF 31h(.*"3 Rt ~'ON 11NC 1HI3 ICChnUlOCT AS Ma jQR A 31 I ซ A T I R TRfAtMENll 7
t FF BOO BUD BOO 13 3 133 t33 COO CUO COO Ult 016 016
FcOซ INF iff I INF IFF t iHf Iff I INF JFF S
MC0 H6/1 MC/l MC/t "G/J. ปtO "C/l MC/l *ฃฉ Hfi/l MQ/l ftฃp
NAXIMUM
0,114
|7ซ1.0
"2.9
55.*
6*7.0
".0
97.5
155*.0
1126.0
7B.0
1
MfAN
0, 13*
I2M.0
?06.?
0)1,0
21,D
51.
2606.0
aio.e
75.0
I
minimum
0,0lซ
801,0
B.O
5ซ,2
H.O
16.0
5.1
266.0
66,0
70. ซ
1
MEDIAN
0.12T
ป2'1.0
16.0
S4.9
31.0
19.5
SI ,9
297^,0
171,0
76.2
t
ปซUM8Cป OF
OBSERVATIONS 6tt22ซ2)6l020
Hป
LO
ACTIVATCO CARBON, ALL ซ*3Tf 3TPEA*3
NUMBER OF S1RCAM3 rEP0ปM1nC THIS IEChnqlqCT A3 M A JOR* ฆ * 3 1 E * A U H IrEATmCNTI 7
lOC
ปuc
1UC
PhCnOl
PHtNOL
PHENOL
Nh }N
KM JN
NHJN Cซ
CR
CR
INT
EFF
1
INF
EFF
X
INF
Iff
1 INF
Iff
I
MC/L
HG/t
RtO
MG/L
hC/L
RED
HC/L
MG/L
RED MC/L
MC/L
RED
MAXIMUM
la5S,0
115.0
7B,ซ
171,0
2.2
94,6
.
0.0
Ml An
7X1.5
111,0
7fl.ซ
127,0
1.0
99,0
o.o
M IN]MUM
92.0
2ซ,0
78,ซ
66,0
9T.5
0.0
MEDIAN
773.5
52.5
76.
120.0
0.6
99,7
ซ
0.0
number or
0B3(RVa1)0N6
2
ซ
1
1
3
3
0
0
0 0
1
0
J ~'-.c
r,c c.i'a ore frcr
o,1;; ;
\">r :hj
n t c-'-
f.o 1 (>p^f
nrinrlpal component
of r'irir
"woicr
ren
a y s "
om.
-------
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 profliction 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 pretreatraent
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
U. 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/l 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:
Before After
Upgrade Upgrade
Effluent BOD 510 mg/1 41 mg/1
Effluent TSS No Data No Data
166
-------
Plant 45 - This plant originally had an activated sludge system with
primary clarification. The plant wa6 upgraded by Che addition of a 3.5
million gallon equalization basin and mixed-media filtration. Addition-
al aeration capacity was installed and a second secondary clarifier wa6
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 unit6 were added downstream of the existing treatment plant. In
1977, additional blower (aeration) capacity wa6 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 Che activated sludge system,
additional instrument at ion, 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 in 1977. System improvements included the addition of an emer-
gency holding basin and a storrawater 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.
Effluent BOD
Effluent TSS
Before
Upgrade
15 rag/1
46 mg/1
After
Upgrade
11 mg/1
No Data
PCPS 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 3t3T[mJ
6009 CmutNl CO*C E N ? RA TIONS
1 BOOS 11
1 NOt Pli3MC3
11
NOT PLASTICS
f 1
NOI plasmcs I
1 ALL "ASIC 1
I IfFLUENT I I
irflur r ui 011 inu I i
PLA3TIC3
ONL* I
1 TTPฃ I
AMD C *
11
TfPC I
not c **
1 1
*0* tTPC
1 |
1 97HCAM9 |
1LU'tl^IPa1|Un11
1 1 <
MjNlHUMi
3.0 1
1 M|h|HUMซ
6.V
11
M J NI HUH*
'.o
1 1
M1N J HUH*
3.0 1
| MJNIHUM* 1,0 |
1 1 1
8b.0 1
1
466,0
11
HAฆiMUMa
760,0
1 1
maximum*
279.0 1
1 MAXIMUM* 760,0 1
1 1 1
hE AN
19,< 1
1 MEAN ฆ
81 ,S
11
HE AN ฆ
60,4
1 1
MEAN
1ซ,7 1
I MEAN *2.6 t
1 1 1
H. E 01 AN *
1ฐ,0 1
I MtDlAN ฆ
1.ฎ
11
MEDIAN ฆ
26,0
1 1
median
17,0 1
1 MEDIAN ฆ 21.0 I
1 1 1
N ฆ
Si 1
1 N ฆ
SO
11
N ฆ
21
1 1
N ฆ
IS 1
IN * 1)9 1
1 1 1
1
: i
1 1
1 1
ACTIVATCO SLUOCC ONLT
BODS E FF LUfNT CONCCnTRaTIONB
1 BODS 11
1 1
not PLA3T1CB
1 1
*0T PLASTICS 11
NOT KA8MC3
1 1
ALL "ASIC 1
1 CffcUtNT ||
plastics
ONL*
1 1
T 1 PC I
A I'D C *
1 1
ITPC 1
SOT C ** M
NOT TtPE
I
1 1
STREAMS |
1 1 1
HINlHUM*
3.0
1 1
minimum*
t.o
1 1
M]N(MUH*
11,0 II
MINIMUM*
3.0
1 1
MINIMUM* 1,0 I
1 1 1
M A 11 MUM*
36,0
1 1
MAlIM0M*
466,0
1 1
MAI IMyMp
760,0 1 1
MAXIMUMS
*J.o
1 1
MAXIMUM* 760,0 1
1 1 1
ME AN *
17,6
1 1
MEAN
86,0
1 1
MฃAN ฆ
!W,2 1 1
Mfc an
15.6
1 1
MEAN ฆ 57.ซ |
1 1 1
-EOJAn
10.S
1 1
Hฃ0J*N ฆ
SO.O
1 1
MEDIAN ฆ
26,0 II
MEDIAN
14.0
1 1
MEDIAN 26.0 1
1 1 1
N
36
1 1
N *
4 1
1 1
N *
13 1 1
N
9
1 1
N 101 1
1 1 1
1 1
1 1
1 1
1 1
BIOLOCIC&l 3v3TCm)( NOT AC'lVATEO SlUDGC
HODS EFFLUENT C0NCtHTH*T10NS
1 BOOS 11
1 NOT PLASTICS 4
1 1
NOT PLASTIC6 . .
1 1
NOT Pi A311CS |
1 ALL maSTC |
1 EfftUfNT ||
PLA 3 T1C 3
ONLY |
1 nPf 1
AND C
1 1
T TKE I
NOT C
1 1
not type | 1
I BTRLamS |
JC0HE"IซMtON| |
..........
........
1 1
f....ซ
11
I............---...I
1 1 1
MINIMUM*
ซ,0 1
1 minimum*
T.O
1 1
MINIMUM*
9.0
1 1
MINIMUM* 6,0 |
| MINIMUM* 6.0 1
1 11
fAXlMUM*
8b, 0 |
1 MAXIMUM*
2SI ,0
1 1
HA X I HUM*
60,0
1 1
MAXIMUM* 279,0 |
| MAXIMUM* 279,0 |
1 1 1
MEAN
2S.3 1
1 MEAN *
60 ,6
1 1
MฃAN *
26,6
1 1
MEAN 61.S 1
I MEAN * ซ0.S 1
1 1 1
MEDIAN *
20ซ0 1
1 MEDIAN *
22,0
1 1
HL DI AN *
19.S
1 1
MEDIAN ฆ 20.0 1
1 median ฆ io.s 1
1 1 1
1 1 1
H ป
IS
1 N *
1
9
1 1
1 1
H ฆ
6
1 1
1 l
N ฆ 6 1
IN 36 1
1 1
* Type 1 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 ha9 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 address 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 mg/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
3!*ClC STAGE BIOiOClCAl StSTCmb ONUf
bOOS t^LUENl CONCENTRATION#
eoos
EPFLUENf
COnCInTBaUON
11
1
1 NOT PLASTICS |
1 NOT PL
II PLMUC8
OnlT 1
1 ttpc I
anU C * I
1 TrPf |
1 {ปซป
11 MJNlHUHt
3,0 1
1
6,0 |
H IN Jhuna
1 1
06,0 1
1 HA I 1 rVJMB
066,0 |
KAXjFU*"
II MfAN ฆ
19.9 |
I *CAN ฆ
T8,l 1
Ht AN ฆ
11 "E 0 I AN
)ซซo t
1 -ED14N ฆ
1,0 1
*E01*N ฆ
1 1 N ฆ
1 1
53 I
1
1 M
A9 |
1
N
I I
I I
NOT FlMTlct
NOT TYP* J
9,0 || MJNtMUXa
?eo,o
60, *
38,0
21
t I
HUlHUMl
II A N
I I H|01 AN
I I N
I I
i
3ซ.f
IT.O
14
I ALL MA8TC
I 3tปtAซ8
it*ซซซ
I H|N|HUNฎ
I MAXJ HJH*
I MEAN
I HE 01 AN ฆ
1.0
766,0
*!.<
?).o
136
IwO STAGE BIOLOGICAL SYSTEMS ONLY
HOUb irfLOtNT CONCEN1RA1IONS
BOOS
EFFLUENT
CO"Ct nTuation
I II NO! PLASTICS
I PL AST ICS ONLY lป 1 * PE I ANQ c
I MlNlNiJfci.
I MA1|HUMซ
I MCAN
I hCOI*N
I N
I
9.0 I < MINIMUM* 7.0 I
*S.O II MAXIMUM* 468.0 I
?|tB II MEAN > 106.7 I
17.0 II MED I AN 4 1.01
1? II N ฆ 17 1
I I I
NOT PLASTICS
TtPE I NUl C
NOT PLASTICS
NOT TYPE I
I I
I I
ALL WASTE |
STREAMS I
M | N | MIJMW
MAI 1 MUM*
mean
ME 01 AN
N
13.0 II MINIMUM*
1B1.0 M MAXIMUMซ
87.7 I I MCAN ฆ
6J.5 I I kCOIAn
6 I I N
I I
3.0 II MINIMUM*
*2.0 II MAXIMUM*
I I MฃAN ฆ
II MEDIAN
I I N
I I
22.3
?2 0
3
3.0 I
*68.0 I
70.2 I
33.0 I
38 I
I
* Type I v/Oxldarion
** Type 1 v/o Oxidation
-------
TABLE 7-26
BIOLOGICAL SYSTEMS WITH POLISHING
BODS EFFLUENT CONCENTRAT IONS
1 ROP5 1
11 NOT P
AST ICS
II NOT PLASTICS 1
1 NOT PLASTICS
1 ALL
UASTF 1
1 FFTt UENT 1
1 PLASTICS
ONLY
II TYPE
AND C*
11 TYPE I
NOT C ** 1
1 NOT T YPfi I
1 STftFAMf* , 1
ICONCENTRATIONI
1 |
, |
1
I
1 < < = MG/l. ) 1
ICUM FRFOI
CUM X
1ICUM FREQ
CUM Z
1 ICUM FRFR 1
run x i
ICUM frf.oi nun X
ICUM FRr.R
CUM X 1
1 20 1
1 9 1
64.3
II 5
33.3
II 0 1
0.0 1
1 3 1 42.9
1 17
43.6 1
1 30 1
1 10 1
71.4
1 1 6
40.0
II 0 1
0.0 1
1 6 1 05.7
1 22
56.4 1
1 40 1
1 13 1
92.9
1 1 7
46.7
II 1 1
33.3 1
1 6 1 R5.7
1 27
69.2 1
1 SO 1
1 14 1
100.0
1 1 8
53.3
II 2 1
*6.7 1
1 7 1 100.0
1 3)
79.5 J
1 100 1
1 14 1
100.0
1 1 13
OA. 7
II 2 1
66.7 I
1 7 1 100.0
1 36
92.3 1
1 200 1
1 14 1
100.0
1 1 IS
100.0
II 3 1
100.0 1
1 7 1 100.0
1 3?
100.0 1
1 300 1
1 14 1
100.0
II 15
100.0
II 3 1
100.0 1
1 7 1 100.0
1 39
100.0 1
1 400 1
1 14 1
100.0
II 15
100.0
II 3 1
100.0 1
1 7 \ 100.0
1 39
100.0 1
1 300 1
1 14 1
100.0
1 1 13
100.0
II 3 1
100.0 1
1 7 1 100.0
1 39
100.0 1
1 600 1
1 14 1
100.0
II IS
100.0
II 3 1
100.0 I
1 7 1 100.0
1 39
100.0 1
1 700 1
1 14 1
100.0
1 1 15
100.0
II 1 1
100.0 1
1 7 1 100.0
1 39
100.0 1
1 BOO 1
1 14 1
100.0
II IS
100.0
II 3 1
100.0 1
1 7 1 100.0
1 39
100.0 1
SUMMARY STATISTICS
i ii hiNihun=
6.0 1
1 MINIMUM-
10.0 1
1 MINIMUM^
3 7.0
1 1
MINIMUM^
3.0 1
1 MINIMUM^
3.0 1
1 II MAXIMUM^
45.0 1
1 MAXIMUM-:
104.0 1
1 MAX 1 MUMJ
16B.0
1 1
MAX IMUM =
42.0 1
1 MAX IMUM =
168.0 1
1 11 MF AN
13.7 1
1 MF AN
4fl,5 1
1 MF AN
04.0
1 1
MFAN
19.1 1
1 MfTAN *
35.3 1
1 11 MEDIAN ฆ
10.0 1
1 MFDIAN ซ=
50.0 1
I MT nIAN =
47.0
1 1
MF-DIAN =
22.0 1
1 Mm I AN 3
23.0 1
1 1 \ N
1 1 1
14 1
S
1 N
15 1
1
1 N ซ
3
1 1
1 1
N
7 1
1 N
1
39 1
1
*
**
Type I w/Oxidation
Type I w/o/Oxidation
-------
TABLE 7-27
BIOLOGICAL SYP.TFMG WITH MMF
boos Grnur.NT cqnccntrations
1 DOD3 1
1 1
NOT PLASTICS.
NOT PLASTICS^, 1
MOT PLASTICS
11 ALL WASTE 1
1 FFFLUENT 1
1 PLASTICS
ONLY
1 1
TTPF 1
AND CK
1 1
TYPF I
NOT C*W 1
NOT TYPF. I
11 STRFAMS 1
1 CONCฃNTRATION 1
1 1
1
1 |
I
1 < <=MG/L ) 1
ICUh FRFOI
CUM X
II CUM FRFOI
CUM X
1 1 CUM FRFOI
CUM X 1
CUM FRFOI
CUM Z
1 1C11M FRFOI
ii .... - -1
CUM Z 1
1 20 1
1 2 1
A6.7
i i
1 1
2 1
50.0
i i
1 1
0 1
0.0 1
1 1
JOO.O
ii i
II 5 1
50.0 1
1 30 1
1 2 1
66.7
1 1
2 1
50.0
1 1
1 1
50.0 1
1 1
100.0
II 6 1
60.0 1
1 40 1
1 3 1
100.0
1 1
2 1
50.0
1 1
1 t
50.0 1
) 1
100.0
II 7 t
70.0 1
1 "50 1
1 3 1
too.o
1 1
2 1
50.0
1 1
1 1
50.0 1
1
100.0
II 7 1
70.0 1
1 100 1
1 3 1
100.0
1 1
3 1
75.0
1 1
7 1
100.0 1
1 1
100.0
II 9 1
90.0 1
1 200 1
1 3 1
100.0
1 1
4 1
100.0
1 1
?. 1
100.0 1
1
100.0
II to 1
100.0 1
1 300 1
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0 1
1 1
100.0
II 10 1
100.0 1
1 400 1
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0 1
1
too.o
II 10 1
100.0 1
1 500 I
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0 1
1
100.0
II 10 1
100.0 1
1 600 1
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0 1
1
100.0
II 10 1
100.0 1
1 700 1
1 3 1
100 . 0
1 1
4 1
100.0
1 1
2 1
too.o 1
1
100.0
II 10 1
100.0 1
1 800 1
1 3 1
100.0
1 1
4 1
100.0
1 1
2 1
100.0 1
1 1
100.0
II 10 1
100.0 1
SUMMARY
STATISTICS
1
1 MINIMUM =
3.0
1 1
MINIMUM-
i?.o
1 1
MINI MUM1
76.0 II MINIMUM=
17.0
II MINIMUM^
3.0 1
1
1 MAXIMUM-
37.0
1 1
MAXIMUM"
103.0
1 1
MAX IMUM3
00.0 II MAX IMUM =
17.0
II MAXIMUM^
103.0 1
1
1 MEAN -
15.3
1 1
MFAN =ฆ
51.5
1 1
MFAN
53.0 II MFAN
17.0
1 1 MFAN ฆ
37.5 1
1
1 MFDIAN =
6.0
1 1
MFDIAN ซ
45.5
1 1
MEDIAN =
S7>.0 II MFD I AN -
17.0
1 1 MCD1AN =
22.5 1
1
1 N
3
1 1
N ซ=
4
1 1
N
2 1
1 N -
t
1 1 N
10 1
1
1
1 1
1 1
1 1
1 1
1
*
**
Type I w/Oxidation
Type I w/o/Oxidation
-------
TABLE 7-28
blOLUGICAL SYSTEMS
oOUb ป hฃmUVAL
1 Munb i
11 NOT HLปSTICS
II NUT KLtSllcS
1 NOT
PL*STICS
1 1 ALU
ASTB 1
1 lFM.uf.nT 1
i Plastics
ONLY
11 TYPE I
AND C*
II TYKE I
NUT C **
1 NOT
TYPE J
II STREAMS 1
1 klbAI t flU 1
1 1 1 1
icu* fheui
CUM ซ
1 ICI'M FHtUI
CUM ซ
1IfUM fHFUl
CUM ft
ฆ CUM F*fui CUM ft
1IfUH FHf0
CUM ft I
1 40 1
1 0 1
0.0
II 0 1
0.0
II 0 1
0.0
1 0
1 0.0
1 1 0
0.0 1
1 bo 1
ฆ 1 i
2.3
i li
2.6
II 0 1
0.0
1 0
1 0.0
1 1 2
1.9 1
1 60 1
i 1 i
2.J
ii ii
2.6
II 0 1
0.0
1 0
1 0.0
11 e
1.9 1
1 TO 1
i 1 I
2*3
II 2 1
5.1
II 0 1
O.D
1 0
1 0.0
11 3
Z.B 1
1 BO 1
1 3 1
7.0
II 3 1
7.7
II 11
5.9
1 0
1 0.0
11 T
6.5 1
1 90 1
1 H 1
1H 6
II b 1
lb.*
II 7 1
<>1.2
1 1
1 11*1
1 1 22
20.~ 1
1 92 1
1 10 1
23.3
II 10 1
2b. 6
I 1 8 1
4T.I
1 3
1 33.3
1 1 31
28.7 1
1 9* 1
1 19 1
4ป.2
II 13 1
33.3
II 11 1
64,7
1 3
1 33.3
1 1 46
42.6 1
1 96 1
1 25 1
be. i
II 20 1
bl .3
II 12 1
70.6
1 6
1 66.7
1 1 63
SB.3 1
1 98 1
1 9b I
b3.T
II 2T 1
b"9. 2
II 16 1
9ป.l
1 9
I 100.0
1 1 60
81.b 1
1 100 1
1 *3 1
jor.r
II 39 1
100.0
II IT 1
100.0
1 9
1 10O.P
II 10b
100.0 1
SW'fAHr STUlSUCS
I 1 1 "J* lป-uซ*ป
*1 .b
11
1 N I MUMp
ป7,b
1 1
MlNJf.U^P
TO, 8 1
| KIN JMUMp
Bb.l
II MJNJKUMp
41.0 1
| II maaImom*
9V.7
11
ha*1mump
V9.6
1 1
~A* Irur *
96.0 1
1 rA*l"liMp
97.0
1| MAXIKUMP
99.T 1
I II *tปN
92.5
11
MtAN p
V2.7
I I
~"E4N ซ
91.0 1
1 mean p
94.2
II mean p
92.5 1
1 1 1 rEOJAfc p
94.7
11
MEDIAN p
96.7
1 1
MEDIAN p
92.0 1
1 MEDIAN P
95.4
11 MEDIAN p
95.2 I
1 1 1 N ฆ
1 II
43
11
11
N P
J9
1 1
1 1
N P
17 1
1 N P
9
1 1 N p
108 1
1
*
**
Type I w/Oxidation
Type I w/o/Oxidation
-------
TABLE 7-29
BIOLOGICAL SYSTEMS
B005 EFFLUENT CONCENTRATIONS
r. REMOVAL >- vs*
1 BODS 1
1 NUT PLA8T1C8 11
NOT PLASTICS
I NOT
PLASTICS
1 ALL
HASTE 1
1 EFFLUENT |
I PLASTICS
ONLT
1 TTPE I
AND C * II
T ฅPE I
NOT C**
1 NOT
TTPE I
i STREAMS |
IC0NCENTRAT10NI
1 ( <ปMC/L ) 1
ICUM FKEQI
CUM X
ICUM FREQI
CUM % ||
CUM FREQI
CUM X
ICUM FREQI
CUM x
ICUM FREOI
CUM x 1
1 20 1
1 15 1
7b. 0
1 6 1
26,1 II
2 1
33,3
1 4
1
66.7
1 27 1
49.1 1
1 JO |
1 1<> 1
80.0
1 11 1
17,8 ||
4 1
66,7
1 b
1
100,0
1 37 |
67.3 |
1 40 1
1 17 1
es.o
1 16 1
69,6 II
4 1
66,7
1 6
1
100.0
1 43 1
78.2 |
1 50 1
1 19 1
95,0
1 1? 1
73,9 II
5 1
63,3
1 6
1
100.0
1 47 1
65.5 1
1 100 1
1 20 1
100.0
1 21 1
91.1 II
6 1
100,0
1 6
1
100.0
1 53 1
96.4 I
1 200 1
1 20 1
100,0
1 ?3 1
100,0 II
6 1
100,0
1 6
1
100.0
1 55 1
100.0 1
1 300 1
1 20 1
ioo.o
1 2 J 1
100,0 II
6 1
100,0
1 6
1
100.0
1 55 1
100.0 I
1 400 1
1 20 1
100,0
1 21 1
100,0 II
6 1
100,0
1 6
1
100.0
1 55 1
100.0 1
1 500 1
1 20 1
100,0
1 2 J 1
100,0 II
6 1
100,0
1 6
1
100.0
1 55 1
100.0 I
< 600 1
1 20 1
100,0
1 23 1
100,0 II
6 1
100,0
1 b
1
100.0
1 55 1
100.0 1
700 1
1 20 1
100,0
1 23 1
100,0 II
b 1
100,0
1 6
1
100,0
1 55 1
100.0 1
l eoo i
1 20 1
100,0
1 23 1
100,0 II
b 1
100,0
1 6
1
100.0
1 55 1
100.0 |
SUMMARY
STATISTICS
1 1
I MINIMUM*
3,0
1 MINIMUM"
6,0 II
MINIMUM*
13,0
| MINIMUM*
5.0
I MINIMUM*
1.0 1
1 1
1 maximum*
52,0
1 MAXIMUM"
154.0 II
MAXIMUMa
82,0
I MAXIMUM*
24.0
1 maximum*
154.0 1
1 1
1 MEAN ฆ
lb.e
1 mean ฆ
43,1 II
MEAN ฆ
3ซ.3
1 mean
ฆ
14.0
1 mean ฆ
29.5 1
1 1
1 median ฆ
9.5
1 MEDIAN ฆ
13.0 ||
MEDIAN ฆ
25,5
I MEDIAN
ฆ
12.0
I MEDIAN
21.0 |
1 1
1 1
1 N ฆ
20
1 N ป
1
23 I 1
1 1
N ฆ
6
1 N
1
ฆ
6
1 N ฆ
1
55 '
1
* Type
** Type
I w/oxidation
I w/o/oxidation
-------
TABLE 7-30
BIOLOGICAL SYSTEMS
BOOS EFFLUENT CONCENTRATIONS
X REMOVAL >ฆ 95* OH EFFLUENT BOO <ซ 50 MG/l
1 BOD5 1
1 1 NUT PLASTICS
1 1 NOT PLASTICS
1 NOT
PLASIICS
1 1 ALL
HASTE 1
1 EFFLUENT I
1 plastics
ONLY
II TYPE I
AND C*
II TYPE I
NOT C**
I NOT
TYPE I
I | STREAMS I
iconcentrationi
1 ( <ซHG/L ) i
icum freqi
CUM X
1ICUM FREQI
CUM X
1ICUM FREQI
CUM X
ICUM FREQI CUM X
1 ICUM FREQ
CUM I |
1 20 1
1 35 I
68,6
II 12 1
36.4
II 7 1
43.8
1 8
1 57.1
1 1 b2
54.4 |
1 30 1
1 40 1
78.4
II 17 1
51.5
II 12 1
75,0
1 13
1 *2.9
1 1 62
71.9 |
I ao i
1 lb 1
<90.2
II 24 1
72.7
II 14 1
87.5
1 13
1 98.9
1 1 97
65,1 I
1 50 1
1 50 1
96,0
II 27 1
81,8
II 15 1
93.8
1 14
1 too.o
1 1 tOb
93.0 1
1 100 1
1 51 1
IU0.0
II 31 1
93,9
II lb 1
too.o
1 14
1 100.0
II 112
98,2 |
1 200 1
1 51 1
100,0
II 3 3 1
100,0
II lb 1
100.0
1 14
1 100.0
II 114
100.0 1
1 300 1
1 51 1
100,0
II 33 1
100,0
II lb 1
100.0
1 14
1 100*0
II 11 4
too.o 1
1 400 1
1 51 1
100.0
II 33 1
100.0
II lb 1
100.0
1 14
1 too.o
II 114
100.0 |
1 500 I
1 51 1
100,0
II 33 1
too.o
II lb 1
100.0
1 14
1 too.o
II 114
too.o 1
1 600 |
1 51 |
100.O
II 33 I
100.0
II lb I
100.0
1 14
1 100.0
II 114
100,0 1
1 700 1
1 51 1
100,0
II 33 1
1O0.0
II lb 1
100.0
1 14
1 too.o
II 114
10U.O I
1 000 I
1 51 1
100,0
II 33 1
too.o
II lb 1
100,0
1 14
1 too.o
II 114
tou.ft 1
SUMMAMT STATISTICS
1 I 1 MINIMUM*
3.0
1 1
MINIMUms
b,0
1,
MINIMUM"
9.0
1 1
MINI M'JMa
J.o
1 1
MINIMUM*
1.0 1
1 11 MAXIMUM-
52.0
1 1
maximum*
154.0
1 1
MAXIMUM!
82.0
1 1
MAXIMUMS
42.0
1 1
MAXIMUM*
154.0 1
1 II MEAN ฆ
W.9
1 1
MEAN ป
J7.2
1 1
MEAN a
2*.9
1 1
MEAN ฆ
17. 3
1 1
MEAN
24.5 1
1 II MEDIAN ฆ
12.0
1 1
median ฆ
30,0
1 |
MEDIAN ซ
2ซ.5
1 1
MEDIAN ฆ
15.5
1 1
MEDIAN ฆ
18.0 1
1 UN ฆ
51
1 1
N ฆ
33
1 1
N ฆ
lb
1 1
N ฆ
14
1 1
N ฆ
114 1
1 1 1
1 1
1 1
1 1
1 1
1
* Type I w/oxidatioa
** Type I w/o/oxidation
-------
made using the criceria 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 1-U. 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
-------
TAHLE 7-31
BIOLOGICAL SYSTEMS
BOOS EFFLUENT CONCENTRATIONS
i removal >ฆ 951 oh effluent dod <ฆ jo mg/l
1 8005 1
II hot PLA ST ICS
11 NUT PLASTICS
1 NUT PLASTICS
1 1 ALL
WASTE 1
i effluent i
1 plastics
Only
II TYPE 1
and c*
|| TYPE 1
NUT I**
1 NUT
TYPE I
II STREAMS I
ICONCENJRATIONI
1 ( OHC/L ) 1
1 CUM FHtni
CUI' X
1 1 CUH FREOI
CUM X
1 I CUM FRt'UI
CUH I
ICUM FflEO
1 CUM X
1 ICUM freb
CUM I |
1 20 1
1 35 I
7''. 5
II 12 1
U1.4
II 7 1
5U, 0
i a
1 61.5
1 1 62
62,0 1
1 30 1
1 a0 1
9(1.9
II 1 ' 1
56.6
II 1
8'j, 1
1 13
I loo.o
1 1 B2
82.0 |
1 UO 1
I U| I
9
II ? 2 1
75.9
II 12 1
85.7
1 13
1 100,0
1 1 88
88.0 1
1 50 1
1 <13 1
91.r
II i 3 1
79.3
II 13 1
91 .
1 13
1 100,0
1 1 92
92,0 1
1 100 1
I |
100.0
II i 7 1
'3.1
II 14 1
10 0,'.'
1 13
1 100,0
II 9#
98,0 |
1 200 1
1 4V 1
J 0') . 0
II 29 1
100,0
II PI 1
100,0
1 13
1 100.0
II 100
100,0 I
1 300 1
1 uii I
1 0 C . 0
II ?> 1
100.0
II lซ 1
100,0
1 13
1 100,0
II 100
100,0 I
1 UQQ 1
1 9 1
1 00,0
II 14 |
1 oo . 0
1 13
1 100,0
II 100
100.0 1
1 600 1
1 u" 1
i ou, o
II l'> 1
100,0
II 14 1
100 .c
1 13
1 100,0
II too
100,6 1
1 700 1
1 4U 1
IO0.)
II ซ;9 1
100,0
II 14 1
100. 3
1 13
1 100,0
II 100
1OU.0 1
1 800 1
1 44 1
100.0
II 29 1
100,0
II lซ 1
100,0
1 13
1 100.0
II 100
100.0 I
5UHHAHT 31 ATI3TICS
MINIMUM"
3.0 1
1 M | III HUMฎ
6,0 l|
MINIMUM-
. 0
I I
MINI MUMฆ
3.0
| |
MINIMUM"
3.0
MAXIHUM"
1
1 HMlWo
154.0 II
U,',K1MUMซ
. o
I I
M4X|HUMa
27.0
1 1
maximum*
154.0
HฃAN a
14.7 1
1 mean ป
36.1 I I
Mi; A.N =
-------
FIGURE 7-4
*7
TYPE 1 & C PLANTS WITH BJOKXMCAI. TREATMENT
EFFLUENT BOD VS. CAl./l.B 1'ROMICT WATER DISCHARGED
2.4
2.2
2.0
l.B
GAL
M LB lA
*vj
vo
1.2
20 40 60 80 100 120 140 160 180 200 220 240 260
EFFIXF.NT BOD, m*/l
-------
TABLE 7-32
BIOI.OGICAI SYSTEMS
rss rFriurNT roNcr.NT rat ions
BOD ZKFhnVAl > = 95* OR FTFLUFNT POD < = SOMO/l
1 TSS 1
1 NOT PLASTICS 11
NOT PLASTICS
1 NOT P
AST ICS
1 1
ALL
UASTE 1
1 EFFLUENT 1
1 PLASTICS
ONI Y
1 TYPE I
AND C 11
TYPE 1
NOT C
1 WOT
YPE I
1 1
STREAMS 1
1 CONCENTRAT ION 1
1
1
| |
1 -
1 1
I
1 ( <=MO/L ) 1
ICUh FRF.OI
cun z
1 CUM FRF.OI
CUM X 11
CUM FREOI
riiM z
1 CUM FREO
CUM Z
1 1
CUM TREOI
CUM Z 1
1 20 1
1 19 1
39.6
1 3 1
10.7 II
4 1
33.3
1 4
28.6
1 1
1 1
30 1
79.4 1
1 30 1
1 29 1
60*4
1 6 1
21.4 II
5 1
41.7
1 7
50.0
1 1
47 1
46. 1 1
1 40 1
1 34 1
70.8
1 10 1
35.7 II
7 1
58.3
1 10
71.4
1 1
61 1
59.8 1
1 50 1
1 34 1
75.0
1 12 1
47.9 1 1
? 1
75.0
1 It
78.6
1 1
68 1
66. 7 1
1 100 1
1 46 1
95.8
1 21 1
75.0 II
1 1 1
91.7
1 13
92.9
1 1
91 1
09.2 1
1 700 1
1 48 1
too.o
1 78 1
100.0 II
12 1
100 ,0
1 14
100.0
1 1
102 1
100.0 1
1 300 1
1 48 1
100.0
1 26 1
100.0 II
12 1
100.0
1 14
100.0
1 1
102 1
100.0 1
1 400 1
1 48 1
100.0
1 28 1
100.0 II
12 1
100.0
1 14
100.0
1 1
102 1
100.0 1
1 500 1
1 46 1
100.0
1 28 1
100.0 II
12 1
1 00 . 0
1 14
100.0
1 1
102 1
100.0 1
1 400 1
1 48 1
100.0
1 78 1
100*0 11
17 1
100.0
1 14
100.0
1 1
102 1
100.0 1
1 700 1
1 46 1
100.0
1 78 1
100.0 II
12 1
100.0
1 14
100.0
1 1
102 1
100.0 1
1 800 1
1 48 1
too.o
1 78 1
100.0 11
17 1
100.0
1 14
100.0
1 1
102 1
100.0 1
SUMMARY
STATISTICS
1 1
1 MINIhUh=
4.0 1
i minimumฎ
9.0 II
MINIMUM'
13.0 1
1 MINIMUM=
2.0
1 1
MINIMUMฎ
7.0 1
1 1
1 MAX I MUM =
177.0 1
1 MAXIM IJM =
189.0 II
ma:
-------
TABLE 7-33
Pioi.nniCAi. systems with rni isminh
TSS FhFI.UFNT CONCgN T ft A T I ONS
POD ZREMOVAL OR FFFl UFNT HOP <=50Mf>/L
1 TSS 1
1 1 NOT PI.AST ICS
1 1 NOT PI
astins
1 1 NOT PI.AST ICS
1 1 ALL
UASTF |
1 FFFLUENT 1
1 PLASTICS
ONLY
11 TYPE I
AND C
1 1 TYFF I
NOT r
1 1 NOT
TYPF I
1 1 f.TRFAMS 1
i i _.. ป . _
II. _
ii _ _ _
ICONCF.NTRATIONI
i | -
1 1
ii ~
1 < < =MG/l > 1
1 CUM FKFQI
CUM X
1 ICUh FFiFQ 1
CUM X
1 1 CUM FRFR
niiM x
liriJM FRFO
i nijM x
iir.tjh FRrn
nun z i
1 20 1
1 S 1
3P.5
II 2 1
25.0
1 1 0
0.0
11 ?
1 2R. ฃ
1 1 9
30.0 1
1 10 1
1 to 1
74.9
II 1 1
17. S
1 1 0
0.0
1 1 4
1 57.1
II 17
54.7 1
1 40 1
1 11 1
P4 .6
II 4 1
50 . 0
1 1 I
50.0
11 (,
1 R5.7
1 1 77
73.3 1
1 50 1
1 12 1
97.3
M ;> i
1 1 1
50.0
11 I
1 R5.7
1 1 24
ro.o 1
1 100 1
1 11 1
100.0
ii n i
too. 0
1 1 2
100.0
1 1 7
1 100.0
1 1 10
100.0 1
1 200
1 13 1
100*0
II B 1
100.0
1 1 2
1 00 . 0
1 1 7
1 100.0
1 1 30
100.0 1
1 100 1
1 13 1
too. 0
II 3 1
too. 0
1 1 7
100.0
1 1 7
1 100.0
1 1 10
100.0 1
1 400 1
1 13 1
100.0
ii p i
1 00 . 0
1 1 2
I c. 0 . o
1 1 7
1 100,0
1 1 30
100.0 1
1 500 1
i n i
too.o
11 9 1
100.0
1 1 2
t 00 . 0
1 1 7
1 100.0
1 1 30
100.0 1
1 600 1
1 13 1
100.0
II P 1
10C-.0
1 1 ?
1 00 . o
1 1 7
1 100.0
1 1 30
100.0 1
1 700 1
i n i
too.o
II 8 1
100.0
1 1 2
100.0
1 1 7
1 1.00,0
1 1 30
too.o 1
f GOO 1
1 13 1
100.0
II 8 1
100.0
1 1 ?
1 00 .0
1 1 7
1 100.0
1 1 70
JOO.O 1
SUMMARY STAUr-TirS
M
00
1 1 1 MINT hlJM =
9.0 1
1 MINT MIJM =
9.0 1
1 MINIMUM^
31.0 1
1 M T H T MI|M =
2.0 1
1 MINT MUM =
2.0 1
1 1 1 MAX 1MUM =
7A.0 1
1 MAX IMUM =
9r. .o i
1 MAX T MUM =
6 2.0 1
1 MAX J MIJM =
55.0 1
1 MAX IMUM =
95.0 1
1 1 1 MEAN
26.3 1
1 MF.AN
a 9. 5 i
1 MF AN
A (,. 5 1
1 MF AN
27,7 1
1 MEAN
34.2 1
I 1 1 hF.f'IAN =
23.0 1
1 MFPIAN =
4 2.0 1
1 MEDIAN =
4A.fi I
1 MrniAN -
2A.0 1
1 MFOIAN =
23. "5 1
1 (IN =
1 1 1
13 1
1
1 N
8 1
1 N
i |
1 N
1
7 1
1
1 N
1
30 1
1
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
TABLE 7-34
noinr.icAi syptfms with unr
TSS FTFLUFNT CONrrNTRAT IOHS
BOD ZRFMPVAL > = 952 OR EFFLUENT HOP <-r>OMR/l.
1 TSS 1
1 NOT PLASTICS I
1 NOT P
AST ICS
1 HOT PLASTICS
1 1 MX
UASTF.
1 EFFLUENT 1
1 PI AST ICS
ONLY
1 TYPE I
AND C t
1 TYFT
NOT C
1 NOT TYFF I
1 1 STRFAMS
ICC1NCFNTRATJ0NI
1
1
1
I -- -
1 - -
| |
1 ( < = MG/I. > 1
1 CUM FRF.OI
CUM X
1 CUM FRFOI
CUM Z 1
ICUM FRFQ
CUM X
ir.llrt FRFO 1 CUM X
1 1 CUM FRFO
CUM X
1 70 1
1 t 1
33.3
1 1 1
33.3 1
1 0
0.0
1 1 too.o
1 1 3
37.S
1 30 1
1 3 1
100.0
1 2 1
/,/>.?
1 0
0.0
1 1 100.0
1 1 6
7r,.o
1 40 1
1 3 1
100.0
1 2 1
66. 7 1
1 0
0.0
1 1 100.0
1 1 6
7S.0
1 50 1
1 3 1
100.0
1 ? 1
/A 7 1
1 1
100.0
1 1 100.0
1 1 7
R7.S
1 100 1
1 3 1
100.0
1 3 1
100.0 1
1 1
100.0
1 1 100.0
1 1 8
100.0
1 700 1
1 3 1
100.0
1 3 1
too.o
1 1
100.0
1 t 100.0
1 1 8
100.0
1 300 1
1 3 1
100.0
1 3 I
100.0 1
1 1
100.0
1 1 JOO.O
1 1 C
.1 00 . 0
1 400 1
1 3 1
100.0
1 3 1
100.0 1
1 I
100. 0
1 1 100.0
1 1 9
100. 0
1 SOO 1
1 3 1
100.0
1 V 1
100.0 1
1 1
100.0
1 1 100.0
1 1 R
100.0
1 400 1
1 1 1
100.0
1 3 1
100.0 1
1 1
too.o
1 t 100.0
11 n
too.o
1 700 1
1 3 1
100.0
1 3 1
100.0 1
1 1
too.o
1 1 100.0
11 n
100.0
1 800 1
1 3 1
100.0
1 1 1
100.0 1
1 1
too.o
1 1 too.o
1 I Q
too.o
(- SUMMARY STATISTICS
00
to
1 I 1 MINIMUM=
1Q.0 1
1 M IN TM1IM =
19.0 1
1 MTNTMllM =
1Q.0 I
I H T MT MUh=
13.0 1
1 MINIMUM-
12.0 1
1 1 1 MAXIMUM =
?4 . 0 1
1 KAXJHUM=
74.0 1
1 MAXIMIJM--
OR.O I
1 MAX J MIIM =
1?.0 1
1 MAXIMUM"
74.0 1
1 II MEAN
21.3 1
1 MF AN
40. 7 1
1 MF AN
<*8.0 I
1 HFf-.N =
J?.0 1
1 MF AN
30. B I
i 11 urniAN =
1
1 MFPIAN =
79.0 1
1 MEDIAN =
46.0 I
1 MFDI AN =
12.0 1
1 MEDIAN =
7.3.0 1
1 1 1 N
1 1 1
3 1
1
1 N
3 1
1 N
1 1
1 N =
1 1
1 N
8 1
1
* Type I w/Oxidation
** Type I w/o/Oxidation
-------
TABLE 7-35
Pioiomr.Ai. systems kith activatf! r.Ar.FiON
TS5 effiufnt concentrations
POO X3EM0VAL >ป?r>X OR EFFLUENT BOD O50M0/L
1 T SS 1
1 NOT PI.
AST ICS 1 1
NOT PI A
r,Tir.5 i
1 NOT PLASTICS 1
1 ALL
UASTE 1
1 EFTLUCNT 1
1 FIA5TICS
ONt Y
1 TYPF I
ANp C 11
TYPE I
NOT C * 1
1 NOT TYFE I 1
1 STREAMS 1
1CONCCNTRATION 1
1 ( 'ฆMG/L ) 1
1 CUM FRFOI
CUM X
1 CUM FRF01
hum x i i
CUM FRFOI
CUM Z 1
iruM rRrm cum x i
ir.UM FRFOI
CUM X 1
1 20 1
1 0 1
0.0
1 0 1
1 1
0 1
0.0 1
10 1 1
1 0 1
0.0 1
1 30 1
1 0 1
0.0
1 0 1
11
0 1
0.0 1
10 1 1
1 0 1
0.0 1
1 40 1
1 0 1
0.0
1 0 1
11
0 1
0.0 1
10 1 1
1 0 1
0.0 1
1 50 1
1 0 1
0.0
1 0 1
11
I 1
100.0 1
10 1 1
1 1 1
50.0 1
1 100 1
1 1 1
100.0
1 0 1
1 1
1 1
100.0 1
10 1 1
1 2 1
100.0 1
1 200 1
1 1 1
I no . 0
10 1
1 1
I 1
100.0 1
10 1 1
1 2 1
100.0 1
1 300 1
1 1 1
100.0
1 0 1
1 1
1 1
100.0 1
10 1 1
1 7 1
100.0 1
1 400 1
1 t 1
100.0
1 0 1
11
I 1
100.0 1
10 1 1
1 2 1
100.0 1
1 500 1
1 1 1
100.0
I 0 1
11
1 1
100.0 1
10 1 1
1 7 1
100.0 1
1 AOO 1
1 t 1
100.0
1 0 1
11
I 1
100.0 1
10 1 1
1 2 1
100.0 1
1 700 1
1 1 1
100.0
1 0 1
11
1 1
100.0 1
10 1 1
1 ? 1
100.0 1
1 800 1
1 I 1
100.0
1 0 1
11
1 1
100.0 1
10 1 1
1 2 1
100.0 1
SUMMARY
STATISTICS
1 1
1 HIHIMIIM-
76.0
1 MINIMUM-
1 1
MINIMUM =
40.0 1
1 MINIMUM- . 1
1 MINIMUM*
40.0 1
1 1
1 MAXIMUM-
76.0
1 MAX I MIJM"
. 1 1
MAXIMUM"
48.0 1
1 MAXIMUM- . 1
1 MAXIMUM-
76.0 1
1 1
1 MEAN
74. 0
1 MEAN -
1 1
mf.an ซ
40.0 1
1 MEAN ฆ . 1
1 MEAN ฆ
67.0 1
1 1
1 MF I' I AN -
76.0
1 MF.DIAN ป
1 1
MFMAN -
4 P . 0 1
1 MFniAN . 1
1 MF nI AN -
67.0 1
1 1
1 1
1 H ป
1
1 N *
1
0 1 1
1 1
H =
1 1
IN ป 0 1
1 1
1 N
1
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 co five years. The data base includes records for 50
plants. Although some records were a6 short as three months, m06t 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
c
ao- caca
185
-------
l'"3Lf 'PUWX ปtj . r 'OtliM Tt 111 1M II fซ
si *
~ u
II 3PJ1. ?ซ *"rnOJ
K S? 17 (I It 9
_!..._ . I_
J.... _ ! U . . _.l. I 1_
-iilTTiTnj 11T11 ia
.....i
i
ซ
d
a
\D
00
' wivif <;|rปWlJ
* JV,\h .I.IM iwrj OMlr.UU Bft 5!-**l I J ff'OHlM
-------
TABLE 7-36
SUMMARY OF PLANT SCREENING
BOD
'lant
Stream
Type
Begin Date
Data Gap
End Date
1
A01
I
01
02
75
09/29/76
1
A02
III
01
01
75
10/76 - 05/79
07/30/79
3
A01
III
01
04
77
09/76 - 12/76
05/29/80
9
A01
I
01
15
75
09/22/76
292
A01
I
01
01
78
12/29/78
15
A01
I
01
01
78
05/31/80
18
A01
II
07
02
75
09/20/76
293
A01
I
01
03
75
09/24/76
27
A01
III
04
04
78
05/78 - 08/78
08/21/80
28
A01
II
09
03
75
09/30/76
42
A01
II
01
17
79
07/17/80
44
AO 1
I
01
01
79
05/30/80
45
A01
II
01
02
79
06/26/80
53
A01
I
01
02
75
09/30/76
60
A01
II
01
01
78
04/30/80
61
AO 1
I
01
03
75
09/30/76
73
AO 1
II
05
02
75
06/25/76
75
A01
I
08
02
74
05/31/76
89
A01
II
05
01
74
09/30/76
90
A01
I
01
02
75
09/30/76
96
A01
I
01
01
75
09/27/76
106
A01
I
01
07
75
10/31/76
109
A01
I
05
01
74
09/30/76
no
A01
II
01
03
75
09/30/76
111
A01
I
01
04
77
12/29/77
113
A01
I
01
01
78
12/31/79
118
A01
I
01
01
79
12/31/79
120
A01
I
04
01
76
09/29/76
124
A01
II
01
01
75
09/28/76
126
A01
I
01
02
75
09/30/76
138
A01
I
01
05
79
12/30/79
146
A01
III
01
02
75
10/76 - 04/79
07/31/79
170
A01
II
06
04
78
05/29/80
175
A01
II
01
03
78
07/11/80
176
A01
I
08
01
78
10/31/78
220
A01
II
01
02
75
09/24/76
229
A01
I
09
01
74
09/30/76
234
A01
I
01
03
78
12/27/79
236
A01
III
05
01
78
03/79 - 05/79
06/25/80
245
A01
I
05
21
77
04/29/80
268
A01
II
01
01
79
07/31/80
269
A01
II
01
04
75
09/29/76
274
A01
I
01
01
75
06/30/80
281
AO 1
I
07
02
78
06/29/80
187
-------
TABLE 7-36 (Continued)
SUMMARY OF PLANT SCREENING
TSS
Plant
Stream
TyPe
Begin Date
Data Gap
End Date
1
AO 2
III
01/01/75
10/76 - 05/79
07/31/79
3
A01
II
01/01/77
05/29/80
9
A01
I
01/15/75
09/22/76
292
A01
I
01/01/78
12/30/78
18
A01
II
07/02/75
09/29/76
293
A01
I
01/03/75
09/24/76
27
A01
III
04/04/78
04/79 - 05/80
05/27/80
28
A01
II
09/02/75
09/30/76
44
A01
II
01/01/79
05/30/80
45
AO 1
I
01/01/79
06/30/80
53
A01
II
01/02/75
07/11/76
73
A01
II
05/05/75
06/25/76
89
A01
I
05/06/74
09/30/76
90
A01
I
01/01/75
09/30/76
96
A01
I
01/07/75
09/29/76
109
A01
I
06/18/74
07/26/74
110
A01
I
01/02/75
09/28/76
111
AO 1
I
01/01/77
12/31/77
113
A01
I
04/01/79
06/30/79
120
A01
I
04/01/76
09/29/76
123
A01
I
06/01/75
09/30/76
124
A01
I
01/01/75
09/28/76
126
A01
I
01/02/75
09/30/76
138
A01
I
01/01/70
12/31/79
146
A01
III
01/01/75
10/76 - 04/79
07/31/79
176
A01
I
08/01/78
10/31/78
220
A01
I
01/03/75
09/27/76
229
A01
I
09/01/74
09/30/76
236
A01
I
06/01/78
06/29/80
245
A01
I
06/21/77
04/29/80
274
A01
III
01/01/75
09/76 - 05/78
06/30/80
294
AO!
I
01/01/79
12/31/79
188
-------
treatment system daring 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 laBt 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(D) 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 6ince 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
PLANT
>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^nd 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
-------
TABLE 7-37 Continued
>95ZR EXCLUDED
or FROM
PLANT <50 mg/1 ANALYSIS
61 no yes
72 - yee
73 yes yes
74 - yes
75 yes yes
87 - yes
89 yes yes
90 yes yes
96 yes no
103 - yes
106 yeB 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 plant;^0^ filtration 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 70Z 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 OCPS waste-
water .
191
-------
TABLE 7-37 Continued
'LANT
>95ZR
or
<50 mg/1
EXCLUDED
FROM
ANALYSIS
ENGINEERING COMMENTS AND/OR
NATURE OF AND REASON FOR EXCLUSION
123
-
yes
Sample point downstream of stormwater dilu-
tion (no BOD data).
124
yes
yes
Sample point dovmstream of stormwater mixing
point.
126
yes
no
None
136
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 chree months of data available
220
yes
no
None
234
yes
no
None, daca 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
-
ye 8
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
o)
Poor performance is
defined as not achieving 95Z 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
III
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.
-------
lant
15
26
110
113
118
170
175
220
234
236
281
TABLE 7-39
ESTIMATES OF VARIABILITY FACTORS "NOT PLASTICS ONLY" PLANTS
Effluent BOD
N
P0.99 P0.95 VF(1) VF(30)*
363
160
247
332
365
103
361
55
157
162
205
16.88
17.55
5.91
17.47
12.17
33.90
39.09
55.13
11.58
32.19
8.44
63.55
68.26
21.82
75.06
61.34
145.75
181.49
291.35
41.60
93.17
26.73
22.80
26.69
8.37
28.95
25.25
74.51
69.66
16.74
39.75
11.62
AVG
3.77
3.89
3.69
4.30
5.04
4.30
4.64
5.28
3.59
2.89
3.17
1.35
1.52
1.42
1.66
2.07
2.20
1.78
1.45
1.23
1.38
4.05 1.61
Effluent TSS
P0.99 P0.95 VF(1) VF(30)
158 21.86 76.32 28.99 3.49 1.33
218 10.09 45.33 14.37 4.49 1.42
91 22.41 100.27 31.22 4.48 1.39
149 94.09 441.22
4.69
362 59.72 159.29 72.55 2.67 1.21
AVG 3.95 1.34
there was
insuf fic ient
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-
cerranean 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
che 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.
Inc inerat 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
-------
Evaporat ion
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 pretreatraent 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, heac
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 rag/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 thera. 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 ass imitated 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 BFT 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 ta industrial plant situations. Table 8-1 summar-
izes the quantitative bases and default valueB 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
-------
TAULE 8-1
ADJUSTMENTS TO CA I'DET DEFAULT
DATA AND RESULTS
PROCESS
CAPDET
VALUE
ADJUSTED
VALUE
DEI'AULT
on
it ESULT
ASL
ALA
k = 0.00135 1/mg/hr
k = 0.001 1/mg/lir
. 5 / day / 1
doy/24hr/So mg
H = 5 / do y / 1
day/24/hr/So mg
Where: DEFAULT
So = BOD Influent Concentralion
DEFAULT
PRIMARY
CLARIFIEIl
("IN" "ASL" AND "ALA"
TRAINS)
BOD % Removal
= 32%
BOD % Removal
= 10%
DEFAULT
DAF, CLAR
Land Result
Based on
SlOOO/ucre
Labora lory
Labor Based
on Flow
Land Result Based
on Dimensions of
Unit at ilO.OOO
per sere
Laboratory Labor
Dused on Prorotion
of J50,000/yr for 1
mnn per on entire waste
Treotment Plant
RESULT
RESULT
ALL UNITS
Administra live
Costs Based
on Flow
201 Planning
Indirect Cost
Equol TO 3.5%
of Construction Cost
ond Contingency
Equol to
Administrative
Costs Equal to
15 percent of
of/mnint. labor
Delete 201
Plonning ond
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
CAPDET'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 coramon
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 paramecer and the subjective opinion of the engineer. Builc 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 chan 500 mg/1 is:
t = (1-S /S ) / (S /S k X ) (1)
e o e o v
Where:
t
detention time, hours
s
e
-
effluent BOD concentration, mg/1
S
o
3
influent BOD concentration, mg/1
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 DEFAULT INFLUENT WASTE CHARACTERISTICS
TEMPERATURE 18.0 ฐC
SUSPENDED SOLIDS 200 mg/1
VOLATILE SOLIDS 60 % of SS
SETTLEABLE SOLIDS 15 mg/1
BOD5 250 mg/1
SBOD 75 mg/1
COD 500 mg/1
SCOD 400 mg/1
pH 7.6
CATIONS 160 mg/1
ANIONS 160 mg/1
P04 18 mg/1
TKN 45 mg/1
NH3 25 mg/1
NO2 0 mg/1
NO^ 0 mg/1
OIL AND GREASE 80 mg/1
203
-------
TABLE 8-3
WASTE CHARACTERISTIC REMOVAL DEFAULT
VALUES FOR CAPDF.T PROCESSES
WASTE CHARACTERISTIC REMOVALS
PROCESS
BODe
TSS
COD
OIL &
GREASE
TKN
PHOS
KH_
SETTLEABLE
SOLIDS
Dissolved Air
Flotation
30Z
80Z
30Z
10Z
Primary
Clarlficatlon
32Z
58Z
40Z
5Z
5Z
Ac C1vated
Sludge
USER INPUT
INFLUENT
AND EFFLUENT
USER INPUT
TO SECONDARY
CLARIFIER
1 .5 x BOD,
EFF
30Z 30Z
SET
EQUAL
TO TKN
Aerated
Lagoon
USER INPUT
INFLUENT
AND EFFLUENT
USER INPUT
TO SECONDARY
CLARIFIER
ASSUME
SAME AS ASL
Multl Media
Filtration
SET EFFLUENT
EQUAL TO
bodsoluble
INFLUENT
60Z
SF.T EFFLUENT
EQUAL TO
codsoluble
INFLUENT
PASS ON PASS ON PASS
THROUGH THROUGH THJtOUGH
-------
t - (24 S ) / (X (F/M)) (2)
o v
Where:
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 (l) 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
.jnt i3Ul>-
140
120
t- 100
ac
.u
60
40
20
So = Influent BOD Concentration (100 mg/1)
FIGURE 8-1 - AERATOR RETENTION TIME SENSITIVITY ANALYSIS
-------
lAULE 6-1-COST S lI I V\RY, HjOIATION
Unit
installed
Equip11 cnt
Cost
5
Anort.
Cost
S/YR
L^bor
Cose
S/YR
ft int.
L.-jjor
Cost
S/YR
Power
Cose
$/YR
$0.06/KWH
Material
Cost
$/YR
Chemical
Cose
5/YR
PlxiC
oy.
Cose
$/YR
flotation
Total
283,767
288,767
29,116
29,116
6,666
6,666
1,259
1,259
7,861
7,861
2,887
2,887
-0-
-0-
18,651
18,651
TOTAL CONSTRUCTION COST $
TOTAL 06M COST $/YR
DI R]_C
Installed Equipment
Contractor Oil fป Profit
Total Direct
.-ma
Misc. Non Construction
A/l Design Fee
Inspection
Tecnnical Costs
AciTun/Legal
Contingencies
288,767
63,528
352,295
1,000 (0.1 acres)
17.616
31.733 (9.017. Const.
7,065
7.065
7.065
60,513
Plant O&M Cost
Laboratory Cose
Administration
Total
Cost)
18,651
12,500
1.188
32,339
EQUIVALENT ANNUAL COST $/':
$t6,889/YR
PLANT DESIGN BASIS
FLOW 6.0 fCO
INT TSS 200 ng/1
EFF TSS 60 irg/1
Total Indirect
111.995
Total Direct and Indirect 666,290
-------
TABiX 8-5-OOST SiK-VMY, CLARIFICATION (Sฃi)dVJer.
Lsbor
Cose
5/YR
Maint.
Ljbor
Cost
$/YR
Power
Cose
S/YR
$0.04/KWH
Material
Cost
$/YR
Cnanical
Cost
$/YR
Plane
OU-I
Cost
$/YR
Prim Cia
Total
202,233
202.253
18,579
18,579
4,288
4,288
1,532
1,532
346
346
2,022
2,022
-0- 8,188
-0- 8,188
N>
O
00
TOTAL CONSTRUCTION POST $
TOTAL 06M COST $/YR
DIRECT
Installed Et;iiipT.e.-.c
Contractor Oil & Profit
Total Direct
INDIRECT
l.and
Misc. t.'on Construction
A/F. Design Fee
Inspection
Technical Costs
Adrian/Legal
Contingencies
Total Indirect
Total Direct & Indirect
202,253
44,495
246,748
2,000 (0.2 acre)
12,337
24,055 (9. 757. Const. Cost)
4.934
4,934
4 934
28,375
81,569
328,317
i'lant OvSM Cost
laboratory Cost
Administration
Total
8,188
12,500
873
21,561
EQUIVALENT ANNUAL POST $/YR
$60,100/YR
PLANT DESIGN BASIS
FLOW 4.0 t-CD
INF TSS 200 mg/1
EFF TSS 80 irซ/l
-------
TABLE 8-6 COST SUi'ARY.ACi IVATED SLUDGE
Insc/jiied Oper. iv*nnt Pli.it
E^uijincnC A.Tiort. Labor Labor Power (Material Chemical Q5iM
Uiit Cose Cost Cost Cose Cost Cost Cost Cost
$ $/YR $/YR $/YR 5/YR $/YR $/YR $/YR
$n.06/KWH
Prim Cia
107,816
9,906
2,566
1,206
299
1,078
-0-
5.129
Puling
92,868
9,926
3.200
2,170
2.679
650
-0-
8,699
S Sec CI
165,374
13,356
3,186
1,658
309
1.453
-0-
6,606
Comp Mix
1.630,337
168,006
36,063
17,526
321.666
6.637
-0-
379.892
Crav Ync
61,986
5,696
1,536
267
619
-0-
6,688
Dry Beds
152,996
17,970
19,216
7,958
-0-
1,376
-0-
28.55^
lloul & Lf
81,602
36,706
1,771
-0-
-0-
11,236
-0-
13,005
Total
2,072,777
261,563
66,271
31.855
325.855
23.050
-0-
666,367
TOTAL CONSTOLiCTI ONCOST $
iUi'AL 06M COST $/YR
DIRECT
Insraliea Equipment
Contractor OH & Profit
Totai Direct
INDIRECT
Land
Misc. Hon Construction
A/E Design Fee
Inspection
Technical Costs
Actain/i/egai
Contingencies
Total Indirect
2.072,777
_ซ6,0i0
2,328,787
9.685 (.95 acre)
126,639
169,82/ (6.727. Const. Cost)
50.575
50,575
50,575
390,809
868,285
Plant 06
-------
TABLE 8-7-C05T SIM'ARY, AERATED LAGOON
Installed
Oper.
Maint.
Pi.mt
F.qui iinenc
Arort.
Labor
Labor
Power
Material
Chemical
O&M
Unit
Cost
Cost
Cose
Cost
Cost
Cost
Cost
Cost
$
S/YR
$/YR
$/YR
$/YR
$/YR
$/YR
$/YR
$0.04/KWH
Prim Tnnc
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
TVjo St I.
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
Crav 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
iloul & 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 ow cost s/yr
DIRECT
Installed Equipment
Contractor OH & Profit
Total Direct
INDIRECT
] -qnd
Misc. Non Construction
A/E Design Fee
Inspection
Teclinical Coses
Admin/Legal
Contingencies
1.360.458
299,301
1.659.759
22,000 (2.2 acres)
82,988
117,157 (7.06% Const. Cose)
33,195
33,195
33,195
190,871
Plant OSM Cost
Laboratory Cost
Adiumstration
Total
136,810
28,649
28,414
193,873
EQUIVALENT ANNUAL POST $/YR
$467,705
PLANT DESIGN BASIS
Total Indirect
512,601
Total Direct fa Indirect
2,172.360
-------
TABLE 8-8-COST SJ1-MY.MUL.7IM1DIA FILTRATION
Unit
Installed
Equi pinent
Cost
$
Amort,
Cost
$/YR
Oper.
Labor
Cose
$/YR
Maine.
Labor
Cost
$/YR
Power
Cost
5/YR
Material
Cose
$/YR
Cnemical
Cost
$/YR
Pl?->t
0^
Cost
$/YR
Tiltrati
Punping
Total
345,396
142,710
'ฆ88,107
40,570
15,256
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
30,910
TOTAL CONSTRUCTION COST $
TOTAL O&M POST $/YR
DIRECT
Installed Equipment
458,107
Contractor OH & Profit
107,373
Total Direct
595,490
Land
14,261
Misc. Non Construction
29,774
A/E Des;gn Fee
48,106 (8.087. Con:
Inspection
11,909
Technical Costs
11,909
Admin/Legal
11,909
Contingencies
68,481
Total Indirect
196,349
Plant O&M Cost
Laboratory Cost
Administration
Total
30,910
24,936
17,458
73,304
EQlfIVAi.ENT ANNUAL COST $/YR
$164,561/YR
PLANT DF.SIGN aASIS
7NF TSS 40 n\g/l
EF7 TSS 16 mg/1
AVG FLOW 4.0 MGD
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 8-4 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 rag/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 solidB 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 sol ids-1iquid 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 Unit6
Complete Mix
COMPLE
Mechanical Aerator
(RSSA)
20
Contact Stabilization
CONTAC
Dlffuser (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
Denitrif1cation
Nitrification
Oxidation Ditch
Pure Oxygen
Trickling Filter
Key word
Replacement
Schedule
Coat Item (years)
PRIMAR Mechanism (RSMS)
L PRIM Structural (RSST)
PUMPIN Pump (RSPS)
Structural (RSST)
CLARIF
A SECO
D SECO
N SECO
0 SECO
SECO
SECO
P
T
Mechanism (RSMS)
Structural (RSST)
40
40
25
40
40
40
214
-------
No Chemicals
With Chemicals
KZ3SOT
FLOW (MILLION GAL/DAY)
FIGURE 8-2 - CAPITAL, OPERATING AND ANOTAL 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 AO 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/l. [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/l (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 Qav(,
216
-------
No Chemicals
With Chemicals
gS=ป==
: (IG^/YR J
iOr$/TR>^-J 1 | ; ฆ j
gSfSMJSfT/'JW-T
FLOW (MILLION 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)c is never lees 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.
CAFDET 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 (j^l5 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 6et 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 - l.CCO ng/L BOD
ROW (MILLION GAL/DAT)
FIGURE 8^-5CAPITAL COSTS, ACTIVATED SLUDGE (1,000 mg/1)
220
-------
INFLUENT ป 1 ,000 (rg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE S-5-OPERAT1NG COSTS, ACTIVATED SLUDGE (1,000 mg/1)
221
-------
SOD INF1.UEN'
-f ' :JฆH
ll - _i-" ... | "1 , 1 1 , . , ' |
, h"
' ฆ 1
> | ( 1 . . I - 1. 1 ' ' > I . - I i 1 1 ' .1 . ซ i . |
. i - :- i > i" - > 11. !.! t i i . ซ . ฆ i i i i > I
,T 4| (4 > j| ซ T .ป J ,1 .ป .ซ J .T 1
FLOW (MILLION GAL/DAY) -ng/L
a
4
4 ซ T t ซ
FIGURE 8-7-ANNDAL COSTS, ACTIVATED SLUDGE (1,000 mg/1)
222
-------
INFLUENT
AERATED LAGOON
EFFLUENT
SLUDGE
GRAVITY
THICKENER
DRYING
HAULING AND
LANDFILL
SECONDARY
CLARIFIER
PRIMARY
CLARIFIER
FIGURE 8-8 - AERATED LAGOON PROCESS CONSIDERED FOR COST ESTIMATION
-------
INFLUENT = 1C00 mg/L BOD
n.ou (iill::n qal/dat)
FIGURE 8-&-C APITAL COSTS, AERATED LAGOONS (1,000 mg/1)
224
-------
INFLUENT ป 1000 mg/L SOD
FLOW(MILLION &AL/OAY)
FIGURE 8-10 - OPERATING COSTS, AERATED LAGOONS (1,000 mg/1)
225
-------
INFLUENT = 1000 sig/L 800
*
FLOW (MILLION GAL/DAY)
FIGURE 8-11ANNU AL 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
AND-DRACITE
SAND
FINE SAND
GRAVEL
SURFACE WASH
EFFLUENT
BACKWASH
EFFLUENT
SURGE TANK
FIGURE 8-12 - MULTIMEDIA FILTRATION PROCESS
-------
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 $/ft 3900 ft 2,100
Subtotal 8,100
Miscellaneous (15% of subtotal) 1,215
Subtotal 9,315
Engineering (15%)(5,000 min) 5,000
Contingencies (15%) 1,400
Total Installed Co6t 15,715
Land (2X pond) 10,000$/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%) 5,900
Sludge Disposal 7,600 S/yr MGD 6,540
Total Operating Cost 12,440
TOTAL ANNUAL COST 19,800
12.5% T.C.C. & T.O.C.
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 $/ft 55225 ft 29,820
Subtotal 46,940
Miscellaneous (15% of subtotal) 7,040
Subtotal 53,980
Engineering (15Z)(5,000 min) 8,100
Contingencies (15%) 8 ,100
Total Installed Cost 70,180
Land (2X pond) 10,000$/aere 2.6 acre 26,000
TOTAL CAPITAL COST 96,180
Operating Cost
Maintenance (10%)
Sludge Disposal 7,600
Total Operating Cost
TOTAL ANNUAL COST
12.5% T.C.C. & T.O.C,
9,620
$/yr MGD 10,940
20,560
32,600
232
-------
TABLE 8-10 (Continued)
COST SUMMARY, POLISHING PONDS
Plant: 60
Flow: 5.07 MGD
Subcategory: NOT PLASTICS/TYPE I WITH OXIDATION
Item
Unit Cost
Amount
Total Cost($)
Excavation
Earth Prep
Liner
1.20 $/yd"
0.54 $/ft"
Subtotal
25100 yd"
180625 ft
30,120
30,120
97,540
157.780
Miscellaneous (15% of subtotal)
Subtotal
23,670
181,450
Engineering (15%)(5,000 min)
Contingencies (15%)
Total Installed Cost
27 ,200
27,200
235,850
Land (2X pond) 10,000$/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. (x 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 estimates.
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 8-12-5ENQI KARK C0KT-AR1SGNS
Plant No., Treacment Type.
and Design Parameters
0146
ASL @ 0.8 MOD
DOD INF 720 ng/1
BOD EFF 20 ng/1
Reported
Costs
Capital,$ 2,421,000
Operating,$/YR 376,800
Eq. Annual,$/YR 661,600
CAPDLT
Costs
2,300,000
310,000
580,000
Difference
(CAPDET - Reported)
-121,000
- 66,800
- 81,600
*/. Difference
Compared to
Reported Cost
CAPDET IS
57. low
187. low
127. low
042
ASL 0 0.13 NOD
BOD INF 6,000 ng/1
BOD EFF 380 ng/1
Capital,?
Operacing, $/YR
Eq. Annual,$/YR
1,082,000
190,000
317,000
900,000
HO. 000
260,000
-182,000
- 50,000
- 57.000
177. low
267. low
187. low
#178
ASL @ 3.5 MCD
HOD IMF 1,000 mg/1
BOD EFF 50 n^/1
Capital,$
Operating,$/YR
Eq. Annual, $/YR
7,960,000
837,000
1,778,000
8,000,000
1,200,000
2.140.000
+ 40,000
+363,000
+362.000
0.57. high
437. high
207. high
Petroleum Refinery
ASL P 2.2 MCD
BOD INT 134 mg/1
BOD EFF 12 irg/1
Installed Equipment
Costs Only, 5 630,000 868.000
+238.000
387. high
CLAR @ 2.2 MCD
Installed Equiprnenc
Costs Only, $ 190,000 155,000
- 35,000
187. low
IV\F without Chemical Installed Equipment
Feed @ 2.2 MCD Costs Only. $ 155,000
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
flANT IV riANT COST ANAIYUS
KfQUlD WAUfWAUl OAU
1."_203 |MimwปCfP)i 0.(Ob
AmiNAiivi cons
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j. AlS/tCAt. IJUyxo Jli|,CQtt_ ^23^Dcij?
ri*l*fltal IGD7TH Capilol OpซMi[uf Am^oI
A||ซ|aปU< C Ml HI Cปป' CปH {\/f\
I. AH IJO'IO) fo UP I If J fllO
j. ALA (50/ioo} I yeo.no /ftI.A.P
100/1)1 *<]a/J0l
WIJi iji C p 11 I Opซซnlซg AmwoI
AM.I-Q4.I. Co,. 1)1 C..MI/,,! C.,.||/,.|
I. i no) 1 OM ?V.iTO <1/OD
J. MiCiO HO) < rvi-J 5*7 ftp
Sซ*g9 ป*rd lolซl Cfh.l Oj>ซ,ปฆ.ป.* Cซ.i 0) Cป.> H'V.l Cซ.I It/Y.)
QCQ. 7:frtY> /glrt'O
)./\la/maปP- l.Vb.OM I 2f.OiX>
Itifii HI
I.Vnj^'i'lOu/n* '' iซp71S|~
C*ปi it)
UpซiaUn9 "
C... ll/,.l
A" I
C..i|l/,.|
V.MJ.
1 *u co'joi s-tonrn FJccf /(/arm
i. A LA {10/1031 JQQJU'2i> 32QJ2UD
C ป.> I l/ri)
1. MM/
2. MiClO
l>0|
110}
25Q&Q 57.000
*25tynCU2 ISICjZO. sn.coo
TO
C*.. iw
C3pr
Co.I
irr.1
-ESZl
Co.. ll'Y.I
Xi^eQ. J$,0ql1_ lllฃ&6
2./LA|mปaP 11(,
-------
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 plant6 with BOD concentrations within Che 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-6olid 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 rag/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 rag/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 co6ts 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 6olids
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: (l) 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 B-L5 PI. ANT-BY-PLANT SUGGESTED TREATMENTS AND COSTS, NON-PLASTICS
TMCWKU/KI
i (30/301
"TARGET SI! (53/35)
n|
Sucgrilrd
Capital
Operating
Annuii
S-yjf i'ed
Cซplul
Opm 1 ln(
Annual
Sug gnted
Capital
Opซrtlln|
Annual
ฆ q.
Tfซ I rr inl
Costa
Com
CoiQ
U)
(l/yr)
1
ciAn
HI,000
U.OftO
5a.000
M M P
470,000
4C,ono
OS,000
MMP
470,000
40,000
B1.000
11
1*0 Til EAT
0
s
0
>0 TREAT
0
0
0
MM P
I21.0UO
7),000
170,000
Ift
aI.a/CLa A
S.1JO.OOO
491,000
I.JPQ.000
ala/mmF
J.HO,000
13T.00Q
1,570,000
A LA/MMP
3.810.000
SJ7.000
1 ,170,000
21
>ฆ0 Til CAT
0
0
0
NO THr.AT
0
0
0
NO TIIFAT
0
t
0
?l
NO T'l hAT
0
. 0
0
*0 7 HIM
c
0
0
ASL/M Mf
1.MD.D00
70,000
s:i,ooo
35
NO T;t 6aT
0
0
0
SO T'JI'AT
0
0
0
HO T n tAT
0
0
0
:*
ASI.
1:0,0:0
>&,cco
) )3,COG
ASL/MMI'
TซC'.:50
re.oo:
110,000
ASL/MMP
MO.OD
7S.D00
191,000
tc
C LA R
ICO.coo
I 7 ; 0 0 0
79.00C
v- M r
3!5,tS0
K .030
72,000
MMP
370,000
30,COO
72,000
17
SO T.I EAT
0
0
0
*0 Tn EAT
0
0
0
HO Tn EAT
0
0
0
1)
Clah
760 .000
70.000
is.003
A
>ป0 TU tAT
0
0
0
*1 MF
7.t:C,OIJO
I0VOOO
493,000
mmt
2,P QQ , 00 a
161,000
<90,000
10
K0 Til tAT
0
0
0
NO Tn EAT
0
0
0
SO TREAT
0
0
C
a>
CLAn
101,000
I),000
30.0C9
M P
3 < 0 .000
32 ,o:o
71,000
V M P
340.000
37.00a
71. COO
91
C LA II
1,100,000
<1.003
is:,oo5
M MF
s,-:;ri.03o
210,030
110,000
M MP
5,c:o,odo
no,000
110. iOC
9?
CI.A II
111,000
Ik.OOO
)1.Q0C
M MF
1Jj.0G3
47,030
103,000
M MP
179,000
42.000
ico.rjo
10)
HO Tf! EAT
0
0
0
MMf
"DO,000
e? .ooo
M0,000
M M F
1:0,000
62 , 000
149, COO
110
HO Tit KaT
0
0
0
hO TREAT
0
0
0
KO TREAT
0
0
0
Ml
M MP
100,001
<1,000
>1 .000
ASL
S30.000
91,000
210,000
ASL/M M F
1 ,00,000
IH.O00
307 , COO
in
NO T A EAT
0
0
fi
fcO Tn EAT
0
0
0
ASl/MM F
7,3:0.00:
*10 , P30
t,110,300
111
c la n
310,000
J?,ooo
m.o:o
y r
nr.030
"n.ooo
wo.oco
m k< r
no,coo
17 , CS-0
1 73,000
130
HO TR 0AT
, 0
0
0
HO TR EAT
0
0
0
MMP
], 100 . C DO
1 tc .coo
4 S3, OCO
m
ASL
1,200,000
115,000
710,000
ASL/M MP
1,7(0,300
1M .000
390,000
ASL/MMP
1,910,000
174 .COO
<20,000
-------
P 1 H
1
ie
16
21
28
35
36
50
52
53
57
59
60
62
64
76
80
85
94
97
102
110
112
113
Hi
120
127
TARCET IV (15/20)
Suggested
Treatment
Capltal
Costa
(S)
Ope ra tlog
Co 9 C S
<5/yr)
Annual
Costs
Jlhil.
MHF
HHP
ALA/KM?
No Treat
ASL/KMF
No Treat
ASL/KMF
KMF
No Treat
HKP
KMF
HKJ
XMf
ASL/MHF
No Treat
h.1f
No Treat
HKF
KMF
HMF
KM?
No Trtat
ASL/MHF
ASL/MMF
HMF
KMF
ASL/MMF
470,000
825,000
5,850,000
0
2,640,000
0
840,000
320,000
0
675,000
720,000
600,000
900,COO
1,750,COO
0
2,800,000
0
340,000
5,000,000
520,000
700,000
0
1,430.000
7,330,000
850,000
2,500,000
1,960,000
40,000
75,000
537,000
0
2B3.000
0
7 B.000
30,000
0
60,000
65,000
50,000
80,COO
168,000
0
165,000
0
32,000
250.000
42,000
62,000
0
136,000
780,000
77,000
150,000
174.000
95,000
170,0C0
1,270,000
0
605,000
0
195,000
72,000
0
135,000
150,000
120,000
190,000
375,000
0
490,000
0
75,000
850,000
100,000
140,000
0
307,000
1,550,000
170,000
450,000
420,000
243
-------
TABLE 8-15 (cont), NON-PlASTICS
7rปchr nwm
PlaM C^pllil Opmllnf Annual
Ho. TieMfncnl Com Com CtuU
(t) tt/yr) H/yr)
Ul
NO Tn EAT
0
0
0
no
hO TllEAT
0
0
0
i)i
ASL
100,00
10*.000
nr .ooo
hi
h O Tfl PAT
0
0
0
MS
ho thiat
0
0
0
160
ASL
no,ooo
tc .000
17},000
\U
K.-J Tfl EAT
0
1 0
0
111
ASL
i. roo. ooo
JOC.OOO
son,ooo
in
NO Tn eat
0
c
0
IIC
nO tucat
0
0
0
IM
S'O TUEAT
0
0
0
m
NO Til EAT
0
0
0
Ji i
ASi.
010,oco
0,000
103,000
718
CLAn
SS.000
16.000
27,030
no
OAK
71,000
11,000
33.000
:i7
ASI.
BCO.OOO
1IC ,000
130,COO
ni
ciAn
190,000
K.000
41,oco
Da
CLAfl
320,000
2 i.COO
CO.000
m
ASL
100,000
ISO.000
190,000
239
ho Tn eat
0
0
0
74 t
no Tn f.AT
0
0
0
7S&
NO TIIKAT
0
0
0
2S7
ASL
170,000
90,000
2 IC ,000
ho vntiAT
0
0
0
261
NO TUEAT
0
0
0
770
NO Tn EAT
0
0
0
371
ciAn
IBS.000
11.000
40,000
f
rAnctT n (30/iffT
SuggMlrd
Trc a imenl
Capital
Com
(ป
r;map.7Mmmr
Cap'lal Opcrallng
Coils Com
(I) O/vr)
Annual
Coin
(1/vr)
MMP
610,000
61,000
ISO,ooo
MMP
ISO,000
61,000
ISO,000
HO Tfl EAT
0
0
0
HO TREAT
0
0
0
ASL/MM F
r,370,000
Ml ,C0O
31S,000
ASL/MMP
1,<4),000
ISl,000
33S.OOO
M MP
140,000
47,000
100,000
M MP
S40.000
47, COO
100.030
M M P
100,000
so,coo
120,000
MMP
000,000
SO,000
173,000
ASL/MMF
1,110,000
lis.ooo
260,003
ASL/MMP
1,110,000
Ml. 000
2C3.000
mmF
000,000
SO.000
170,000
M MP
600,000
SO,ooo
i: o,ooo
ASL/M MP
3,700,000
363 . 000
640.000
asl/mmP
3,100,000
303.000
773,000
NO THFaT
0
0
0
NO TUEAT
0
0
0
kO Til i;at
0
0
0
NO TfldAT
0
0
0
M MF
t<0.000
<7,000
100,000
MMF
5 4 0,000
47,000
103,000
SO Tn EAT
0
0
0
MMP
710,000
74,000
ii,:co
ASL/M MF
,000
60,000
Ml .000
ASL/MMF
SOS,000
60,000
mi ,o:o
r. M F
730.000
20,000
41,000
M M F
730,000
:o,ooo
4 1,000
MMF
700,000
21.000
H.000
M MP
7SO.OOO
71,000
16,COO
asl/m m r
1,710,000
Mi.000
306,000
ASL/MMP
1,4)0,000
1S2.000
346,000
MMF
HO.000
40,000
110,000
M MF
SCO,000
40,000
110,090
M Ml'
7 SO. 000
7U.00O
100,000
M MP
ISO,000
70,000
1(0,000
ASL/MMF
1,120,000
MC.000
712,000
ASL/MMP
1 , 370,OCO
1S6.000
3)2.COO
M MF
ICS.000
i r.. n o o
3S.000
M MP
16S.O00
16,COO
31.030
no rnr.AT
0
0
0
MMP
771.000
61,030
110,030
M M |ป
770.000
2G .000
6 i .000
M MF
270 ,OCO
26,000
ft 4, COO
ASL/M M P
1,330,000
129,000
302,000
ASL/MMP
1,330,000
139,030
370 , 0P0
M MP
7n),000
17,000
41,000
ASL/MMP
60S,000
n ,000
MS,030
HO Tn CAT
c
0
0
MMP
1)0,000
S3,000
130,030
no Tn eat
0
0
0
NO TREAT
0
0
0
MMF
SCO ,000
44,000
110,000
MMF
560,000
44,000
110.000
-------
TAHCET IV (15/20)
Suggested
Treatment
Plant #
Capital
Costs
<ป
Operating
COS t B
(?/yr)
Annjal
Cove 9
(?/yr)
128
130
138
144
US
160
171
178
183
180
188
216
218
219
220
222
226
228
231
239
247
256
277
263
264
270
271
KMF
No Treat
ASL/MMF
HKP
KKP
ASL/HKF
MMF
ASL/MHF
No Treat
No Treat
MKF
MMF
ASL/MMMF
KMF
KMF
ASL/KMF
MMF
KMF
ASL/MMF
KMF
MMF
MMF
ASL/MMF
ASL/MMF
MMF
No Treat
MMF
650,000
0
1,445,000
540,000
600,000
1,180,000
600,000
3,100,000
0
0
540,000
250,000
565,000
230,000
250,000
1.450,000
560,000
750,000
1,270,000
165,000
725,000
270,000
1,330,000
605,000
630,000
0
560,000
68,000
0
151,000
4 2,000
50,000
116,000
50,000
303,000
0
0
42,000
24,000
60,000
20,000
25,000
152,000
46.COO
70,COO
156,000
16,000
65,000
26,000
129,000
57,000
53,000
O
44,000
150,000
0
335,000
100,000
120,000
260,000
120,000
720,000
0
0
100,000
55,000
141,000
48,000
56,000
346,000
110,000
160,000
332,000
35,000
150,000
64,000
320,000
146,000
130,000
0
110,000
245
-------
TABLE 8-15 (cent), NON-PLASTICS
tarcet i ปc;sci ~ Tirrcr.ET hup/jiit^ tahuut uiTTtryrJT
Min|
Si<|Mlซd
Capital
Operating
Annual
5uff filed
Capital
Operating
Annual Suggested
Capllal Opintlng
Annual
Hq.
TปCl Imrnl
Cซnll
Colli
Colli
Trea imfni
Colli
Colli
Co# i i Tr * ฆ imp^i
Colli
C9llป
Colli
IJ]
CWyr)
m
U/jrj
< 1/yr)
iil
HJit)
\lhd
HI
CLArt
:. c:o
AS ซ,/*' M P
T?0 .000
7 3,000
no.ooo
A5UซMP
HO,DOO
n.ooo
MS, 000
" 61
ASL
l.ป0,000
PO .CL'O
:-'^.CC-C
AS./VMP
2.7 7 a.D DO
330 ,C20
4l)t,f!00
aSl/m m p
j,;io,oco
130,000
411,000
II
cl.au
<13,000
31 , COO
?!ปrcno
MVP
1,Oi 0.000
as,o*o
uo.ooa
asl/mmp
3,800,000
430 .COO
no.oofl
* 10)
KO TA FAT
0
0
c
NO THEAT
0
0
0
KO Til EAT
0
0
111
HO TREAT
0
0
0
SO "AT
D
0
0
KO Til EAT
0
0
0
170
NO ~\\KAT
0
0
r
so r.ilAT
0
0
0
MMP
700,000
14,000
141,050
m
hO Tn eat
0
Q
0
sMซr
*70,000
4 4,000
91,000
MMP
WO, 000
44,000
61,000
in
NO Til EAT
0
0
D
hO THKAT
0
0
0
ho rn eat
1
0
0
nซ
hO TUKAT
0
c
0
no rn cat
0
0
0
NO Tn KAT
0
0
0
"
"
totals
73,113,000
j.zjg.ouo
000
47.7B7.ti00
4 ,1 lb,DOO
I0.0lfl.000
70,013,DOO
1,311,000
14,171,000
IHSUPriCIENT TSS OAT A,
-------
target iv (15/20)
Sugge6ted Capital Operating Annual
Treatment Costs Costa Costs
Plant I
(S)
($/yr)
(S/yr)
269
HHP
BOO,000
75,000
170,000
272
MMF
800,000
75,000
170,000
275
asl/hmf
800,000
84,000
195,000
15
MMF
670,000
60,000
135,000
20
AS1/KHF
740.000
74,000
180,000
42
ASL/KMF
810,000
75,000
185,000
61
ASL/MKJ
2,220,000
230,000
495,000
94
ASL/KMf
3,500,000
420,000
890,000
103
No Treat
0
0
0
118
No Treat
0
0
0
170
KMF
700,000
84,000
145,000
175
KM/
520,000
4 4,000
98,000
177
No Treat
0
0
0
234
No Treat
0
0
0
247
-------
TABLE 8-1* (cont). NON-PLASTICS
TAHCET I liCTffl
Ss^gMtcd
Capital
Ope't' Inf
Annua1
Sufc-gr sled
Trea imrnl
Coปiป
Cotii
Colts
Treซ Imcnl
III
ll/yr)
(S/yr)
Mli Slrctmi
Trปil STM.I
UM: NO.TRT
0
0
0
ASL/MMK
CLAU
1 IS ,000
11.000
40.000
MMP
ASL
410.000
44,000
IOC,000
asl/mmp
NO treat
0
0
0
mmP
Tr f a I S*l M |
M.i 1(11
ASL
I.IOC.000
ISO.000
300.000
A S w/ V M F
CLAR
lie.coo
16.000
44 ,000
CLAQ/mmF
A$L
1)0,000
3F ,000
190,000
ASL/M wr
NO TREAT
0
0
0
ASL/MMF
CLAR
300,000
II.000
43.000
M MF
NO TREAT
0
0
0
NO TREAT
h\ P
6)0.000
56,000
130.000
M m r
SO TfUAT
0
0
0
KO TRCAT
NO 'rn LAT
0
0
0
NO TR EAT
NO trkat
0
0
0
NO Til LAT
KO TR L AT
0
0
0
mmF
NO TRCAT
0
0
0
nO TRCAT
ASL
700.000
73.000
170,000
ASL/MMF
CLAR
110.000
1? .000
31,000
M MF
NO TREAT
0
0
0
NO TREAT
ASL
100,000
7?,000
1 TO ,000
ASL/MMF
CLAR
190,000
18.000
40,000
V. M F
NO TREAT
0
0
0
vmP
ASL
1,SCO.COO
no.000
363 ,000
ASl./MMp
DAf
7k. COO
IS.000
74,000
mmF
TA nC L~T II (3C/J0)
YAftCg'f ili(ป7flT
Capital
Opcrillnf
Annual
Sufi* "d
cซpiui
Opera llftf
Annual
Coปit
CotU
Colli
TVralmenl
COMtt
Coill
Coitl
II)
(S/yr)
(l/yf)
(1)
(Wyr)
U/yr)
TVซ#l STM.I
74J.000
?S,000
no,ooo
ASL/MMP
740,000
7S,000
179,000
sso.oeo
44,000
101,coo
MMP
SSO.OOO
44,000
101,cco
C2U .000
CI .000
Ml. COO
ASL/MMP
120.000
II ,000
I 4 I, C CO
(.40 , 000
47,000
100,000
M MT
Mil |ll|
S 40,000
43,000
too,cco
4,7ftC.P00
449,000
3 G 0,COO
ASL/M MP
4,700,000
449.000
960.000
110,000
66,900
ist,ooo
CLAfl/MMp
110,000
66,COO
IS9.C30
1.C9C.033
uc.coo
2CS.C00
ASL/MMP
1,770,000
176,000
7IS.C00
i.6co.c:o
167.000
370,000
ASL/MMP
1.(00.000
167,000
370,t::
i 90 .000
47.000
us.ooo
MMF
590.000
47 ,000
IIS,cco
0
0
0
NO TR F.AT
0
0
0
6s;ooo
Si, 000
130,000
ASL/M MP
6SO.OOO
S6.000
i;o,o:o
c
0
0
NO TRKAT
0
0
0
0
0
0
M MF
G3S.OOO
SI.000
140.000
0
0
0
NO TREAT
0
0
0
(SO.000
sc.000
130,000
MMF
(SO,000
S6.000
130,003
0
0
0
NO TREAT
0
0
0
1 .04S,000
104,000
24S.000
ASL/MMP
I.04S.000
104,000
Hi.OCO
370.000
34 .000
80.000
MMP
370,000
34.000
10,000
0
0
0
NO TREAT
0
0
0
t,c:o.ooo
106 ,000
iso.ono
ASL/MMF
1,000,000
106,000
iso.eo:
sro.coo
44,000
110,000
M MT
SG0.C00
44,COO
uo.cro
4*0.000
38.000
90,000
ASL/MMP
i .no.goo
177.COO
783,c:o
J, 1 ?S OCO
102,000
480,000
ASL/MMP
3.37S.OOO
j;: .ooo
S4C.(c:
7SO.OOO
2S.000
60.000
MMP
7S0.000
3S.000
60,o:o
-------
TARGET IV (15/20)
Plane t
Treatment
Capital $ Open
itlonal $
Annual $
8
ASL/MMF
740,000
75,000
179,000
31
HMF
550,000
44,000
108,000
32
ASL/KMF
620,000
61,000
148,000
49
HHP
Ml* I 6 II
540,000
42,000
100,000^
63
ASL/KMF
4,200,000
449,000
960,000
66
CUAR/MMF
810,000
66,000
159,000
81
ASL/KMF
1,220,000
126,000
285,000
86
ASL/KMF
1,660,000
167,000
370,000
88
ASL/MMF
1,150,000
120,000
260,000
92
No Treat
0
0
0
98
ASL/MKF
650,000
56,000
130,000
117
No Treat
0
0
0
119
MMF
62 5,003
52.0C0
140,000
121
No Treat
0
0
0
122
MMF
650,000
56,000
130,000
151
MKF
700,000
64,000
148,000
153
ASL/MMF
1,045,CC0
104,000
245,000
158
ASL/KMF
700,000
73,000
170,000
159
MMF
460,000
39,000
90,000
164
ASL/KMF
1,060,000
106.000
250,000
176
MMF
560,000
44,000
110,000
182
ASL/KMF
1,250,000
122,000
280,000
187
ASL/MKF
2,325,000
222,000
540,000
192
MMF
250,000
25,000
60,000
2 A 9
-------
TABLE 8-15 (cont), NON-PLASTICS
TAnccr i (so/>o) TAnccfinWii) taucct ilino/iO)
Plant
Soffriled
CapUal
Operating
Annul)
Sifinled
Capital
Operating
Annuซ!
Suggested
Capital
Opera llnf
Annual
He.
Trcftlmcnt
Colli
Coils
Com
Trea Iment
Coals
Coil!
Coils
Treatment
Coils
Coils
Colli
0.000
no.000
ASL/M MP
7CO.COO
71,000
187,000
ASL/MMP
790,000
70,COO
197,000
701
CLAR
30,000
M',000
11,coo
M MP
100,cco
11,030
34 .0C0
MMP
1C0,COO
11.OCO
34,030
706
C LA R
3->0,000
77,000
64,000
M Mf
850,000
71.COO
170.000
M MF
050,COO
71.000
170.COO
701
HO Tit EAT
0
0
0
WMF
400,000
3f..C00
ei.ooo
M M p
4:0,COO
36,000
01.COO
no
ASL
700,000
7 7.o6o
170.000
ASL/MMP
1. osc. oco
1P4 ,coo
7 < G.000
ASL/MMP
1,010,000
104,000
746.000
731
ASL
J.300.000
170.000
*60.000
ASL/MMP
3,700.000
310.COO
710,OCO
ASL/MMP
3,700,000
350,000
710 000
236
CLAR
330,000
77,000
C7.000
M M F
800,000
71,000
170,000
M MP
noo.ooo
11.000
170.000
NO Tn EAT
0
0
0
NO T/l CAT
0
0
NO treat
0
0
0
748
ASL
1.300,000
130,000
793,000
ASL/M MP
1.971,000
161.000
410,000
ASL/MMP
1,571,030
161.000
410,000
7<9
HO Tfl 6AT
0
0
C
NOT TIlf.AT
0
0
HO THF.AT
0
0
0
710
HO THEAT
0
0
0
ASL/MMP
110,000
19,000
136,000
ASL/M MP
110,000
19,000
138.000
i
ASL
MO.000
St.000
nc .000
ASL/MMF
711.000
81,000
16 7,000
ASL/M MP
011,000
63.000
194.000
II
ASL
>10.000
SB,000
no,000
ASL/MMF
7 > > , 000
II, COO
167,000
ASL/MMF
SH.OOO
63,000
194,000
HI
ASL
410.000
44,000
107,000
ASL/MMP
011.000
61.000
147 , 000
ASL/MMP
611,COO
61.000
141.000
~ 704
NO Tn EAT
0
0
0
NO TH LAT
0
0
0
MMP
770,000
16,000
67,000
719
no Tn EAT
0
0
0
NO TRLAT
0
0
0
HO Tn EAT
0
0
0
?CI
ASL
1,700,000
310.000
500,000
ASL/MMF
7.M0.000
310,000
770,000
ALA/MMP
3,100,000
310,000
140,000
711
HO Tn EAT
0
0
0
HO Til EAT
0
0
0
NO TUEAT
0
0
0
totals
17,2)3,000
1,973,000
4,779.000
31,483,000
3.607 .000
1.010,00
31,130,000 3,111.000
1,700,000
INSUFFICIENT TSS DATA.
-------
TARGET IV (15/20)
Plant 1
Treatocnt
Capital $
Operational $
Annual $
193
ASL/MMF
1,535,000
171,000
373,000
195
MOT
1,050.000
85,000
210,000
201
ASL/MMF
710,000
83,000
173,000
203
A5L/MMF
790.000
79,000
197,000
205
MM?
160,000
15,000
34,000
206
ASL/MMF
2,100,000
250,000
510,000
208
MKT
400,000
36,000
85,000
230
ASL/HMF
1,050,000
104,000
246,000
235
ASL/MMF
3.200.000
350,000
750,000
2 36
ASL/MMF
2,000,000
230,000
490,000
245
No Treat
0
0
0
248
ASL/MMF
1,925,000
181,000
410,000
249
No Treat
0
0
0
258
ASL/MMF
550,000
59,000
136,000
6
A5L/MMF
815,000
83,000
194,000
81
ASL/KMP
815,000
83,000
194,000
163
ASL/KMy
615,000
61,000
14 7,000
204
MMF
270,000
26.000
62.000
259
No Treat
0
0
0
263
ALA/MMP
3,883,000
350,000
840,000
281
MMF
540,000
42,500
100,000
TOTALS 44,170,000 4,401,500 10,013,000
251
-------
TABLE fi-16 PLANT-BY-PLANT SUGGESTEO TkEATKuNI AND COSTS, PLASTICS
ho
Ln
ho
TA!ปCIT 1 fW,Ci
TAflCCT II nO/JO>
fXllciT li
f:37:t"i
"
Plant
So^fcllrd
Ceplll
Annual
?-j^ rilfrt
Opt'* i tg
Anngal
<>tf il
Ceplil
OfWfil nj
ARnui1
No.
TreMmpn!
Com
Coปtป
Celt*
** i r d i
Ceป>i
Cei.a
Colli
Ttt* Ini ซnl
COHI
C0 TREAT
0
C
NO T.ICaT
0
0
0
KO T. ฃ AT
0
0
0
kO TfiBAT
0
0
i?
CLAfl
I2C.CC0
li.000
<6,030
v. r
L2S ,C30
i2,000
173,000
M P
629,030
11,000
t:o,cco
sc
NO TT 6aT
0
0
0
NO "llEAT
0
0
0
KO Tn EAT
G
0
i
c la n
; * c .coo
if .000
itt.CCO
v s-
1iD.OOO
1C.030
130,005
M M K
6!i0,C05
It,033
i:t.c:a
?:
OA P
re.coo
ii.co:
: <,: o c
Vfc-
no.too
tl .030
lO.DCD
H'MF
UO.OOO
U , 0 c c
(:,t'OP
tซ
hO-treat
c
c
5
C ""1 Cat
0
0
C
SO Tr\ EAT
5
c
c
i:!
"0 TJiEaT*
c
c
c
" m C at
c
0
C
SO 711 "AT
0
D
c
; <
C LA R
: 3 o .c:o
It.coo
45 , CC0
K
(00.000
5?.CC0
110 ,053
* MF
GOQ.OOO
i o. o: o
i::,:co
f n 11 i ;> il'firrl far opl'mf* annual coil.
-------
TARGET IVA ฃ10/201
Plant I
Teeataent
Capital $
Operational $
Annual $
J
3
9
10
17
19
2?
29
34
39
44
45
54
65
73
77
09
90
91
93
96
100
104
MHF
ASL/KHF
MNF
No Treat
ASL/M.1T
No Treat
ASL/MMT
HHP
ASi/MMF
No Treat
HMF
MMF
KMf
ASL/HKF
No Treat
No Treat
ASL/HHF
No Treat
MMF
KMF
No Treat
"Ho Triat
MMF
640,000
990,000
240.300
0
680,000
0
5,400,000
1,250,000
450,000
0
470,000
650,000
280,000
3,400,000
0
D
1,300,000
0
650,C00
260,000
0
0
600,000
54,000
99,000
2 2,000
0
67,000
0
683,000
95,000
49,000
0
40,000
56,000
28,003
410,000
0
0
140,COO
0
56,000
26,000
50,000
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
130,000
60,000
0
0
120,000
253
-------
vsz
z z z x z > z
o o o o o 2 o
> > > > >
-i -i -i -t -i
zzzzzzzzzzzzOOz
OOOOOOOOOCOOr-rO
,ti i> jtj re Tt. rr, ป. r. ft iT n N 0
*>>>>>>>>>>> >
H oe
2 A
3 2
u
e
. S -3
o
tnl
Z Z Z Z Z >
O O O C O "
J:;rz2i>zzr7>>z2
zz-sslsZ. s s 5 a = x 3 2 2 s
r" n .'o n * re ~ f. C* I ^ f-. f. n ฃ ฃ f.
>>>>-3-T,>
II
"C
> >>>>
H H H -! -!
H H -i H
z Z Z X
z
>
2
2
Z
z
2
z
>
2
2
z
2
>
>
o o o o
O
Lfl
c-
z
ฆ
*
C
2
O
u
r
S
2
ฉ
*
V'
c~
u
c-
H -J H H
H
_
ฆ9
H
H
3 S ;= J=
t
3
Ja
2
7>
2
Z
r% rปi re ,"r
r*i
s
__
re
X
ra
ฃ
S
> > > >
>
"B
>
>
>
*
-a
H H H H
H
-i
H
3 3
3:
= B'
:o?
' 8 3
-------
Plane I
105
107
109
111
124
125
126
132
146
147
150
152
157
174
179
184
1B9
194
196
202
210
217
TARGET -VA (10/20)
Treatment Capital $ Operational 5 Annual $
HM?
ASL/HMF
HMF
No Treat
ASL/HMF
ASL/MMF
HMF
ASL
MM?
HMF
ASL/HMF
No Treat
MM?
No Treat
MM?
Ml* I i 11
MM?
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
1,020,000
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
102,000
0
o
58,000
0
44,000
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
-------
TABLE 8- 16(cont), PLASTICS
TAflGrr I lijj/58) TAncTT-nr.tffHT TAI1GCT III iio/H)
Pi.M
S*CTฐitd
CfipllAl
Oprra Hn[
Aniui |
StClMlrd
Capital
OprtAllnff
Annual
S ufc ( e 11 r d
C.pl! ซ1
Opซrป I Inf
Annual
Ho.
TVeslrntnl
Coป>ป
Colli
Colli
Trcolmenl
Colli
Coili
Colli
TVralmtnl
Con
Coill
m
(l/yr)
lป;yr>
Hi
:j.ooo
K1. M r
(75.001
10.coo
1)5,000
:87
hO TH HaT
0
0
0
NO TR FAT
0
0
0
KG TREAT
0
0
0
75
hO Tn EAT
0
0
c
>0 Tnr.AT
0
0
0
M M P
390,000
35,000
B0,000
IDS
KO Til CAT
0
c
0
hO TRCAT
0
0
0
#<0 TflgAT
0
0
0
111
hO Trt F^T
0
0
0
M MF
4 SO,000
)S.000
co,ooo
MMf
450,000
19,000
90,000
TOTALS
3,716,600
1H ,000
009,000
11.S?S,GOO
1,515 ,000
i,2:a.ooo
15,09 5,000 2.131,000
S.113,000
MNSUPPlCltNT TSS DATA.
-------
Pla
223
224
229
246
25*
262
273
277
287
75
106
233
TOT/
TARCET IVA 110/20}
treatment Capital $ Operational $ Annual $
ASL
480,000
40,000
94,000
ASL/MMF
470,000
52,000
120,000
No Treat
0
0
0
ASL/KHF
1,190,000
121,000
275,000
MK?
510,000
41,000
96,000
ASL/MHF
660,000
68,000
160,000
ASL/MMF
200,000
230,000
480,000
MKT
675,000
60,000
135,000
No Treat
0
0
0
ASL/MMF
730,000
75,000
175,000
No Treat
0
0
0
ASL/MMF
830,000
85,000
190,000
36,175,000 3,752,000 8,325,000
257
-------
TABLE 8-17
POTENTIAL BPT EFFLUENT LIMITATIONS
BPT (I)
Subcategory BOD mg/1 TSS mg/1
Plastics 14.5 24
Not Plastics -Type I with Oxidation
High Flow 26.0 62
Low Flow 36.0 89
Not Plastics Type I w/o Oxidation 24,5 34.5
Not Plastics NOT Type I 17.0 29
BPT (II)
Subcategory BOD mg/1 TSS mg/1
Plastics 14.5 23
Not Plastics - Type I with Oxiation
High Flow 26.0 42
Low Flow 36.0 42
Not Plastics Type I w/o Oxidation 24.5 27
Not Plastics NOT Type I 17.0 26
258
-------
TABLE 8-18
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: PLASTICS ONLY
BPT (I)
1
BPT
(II)
Suggested
Capital
Operat ing
Annual |
Suggested
Capital
Operat ing
Annual
Plant
t Treatment
Cost ($)
Cost($/yr)
Cost($/yr) |
Treatment
Cost($/yr)
Co st($/yr)
Cost($/yr)
2
No Treat.
0
0
0 1
MMF
640,000
54,000
127,000
3
ASL/MMF
990,000
99,000
233,000 |
ASL/MMF
990,000
99,000
233,000
9
MMF
240,000
22,000
52,000 |
MMF
240,000
22,000
52,000
10
No Treat.
0
0
0 1
No Treat.
0
0
0
17
ASL/MMF
680,000
67,000
160,000 |
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
o 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
0 1
No Treat.
0
0
0
77
No Treat.
0
0
0 1
No Treat.
0
0
0
90
No Treat.
0
0
o 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
0 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
o 1
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 |
MMF
360,000
34,000
80,000
146
No Treat.
0
0
0 i
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 |
ASL/MMF
1,300,000
126,000
285,000
152
No Treat.
0
0
0 1
No Treat.
0
0
0
157
MMF
600,000
46,000
110,000 |
MMF
600,000
46,000
110,000
-------
TABLE 8-18 (Continued)
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: PLASTICS ONLY
BPT (I)
1
BPT
(II)
Suggested
Capital
Operat ing
Annual |
Suggested
Capital
Operat ing
Annual
Plant
# Treatment
Cost ($)
Cost($/yr)
Cost($/yr) I
Treatment
Cos t($/yr)
Cost($/yr)
Cost($/yr)
174
No Treat.
0
0
1
0 1
No Treat.
0
0
0
179
MMF
420,000
38,000
85,000 1
MMF
420,000
38,000
85,000
184
MMF
560,000
46,000
110,000 1
MMF
560,000
46,000
110,000
189
ASL/MMF
1,020,000
102,000
235,000 I
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 1
ASL/MMF
1 ,190,000
121,000
275,000
277
MMF
675,000
60,000
135,000 I
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 I
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 I
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 I
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 I
ASL/MMF
830,000
84,000
195,000
217
MMF
210,000
16,000
41,000 I
MMF
210,000
16,000
41,000
223
No Treat.
0
0
0 1
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 |
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 1
ASL/MMF
1,000,000
100,000
235,000
273
ASL/MMF
2,775,000
300,000
640,000 1
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
Opturat ing
Annual |
Suggested
Capital
Operat ing
Annual
Plant #
Treatment
Cost ($)
Co61($/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 I
ASL/MMF
840,000
78,000
195,000
49
No
Treat.
0
0
0 1
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 j
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 I
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 1
No Treat.
0
0
0
80
No
Treat.
0
0
0 1
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 1
No Treat.
0
0
0
103
No
Treat.
0
0
0 1
No Treat.
0
0
0
110
No
Treat.
0
0
0 1
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 1
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 I
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 I
ASL/MMF
1 ,535,000
171,000
373,000
195
No
Treat.
0
0
0 1
No. Treat.
0
0
0
216
No
Treat.
0
0
0 1
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 j
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 1
No Treat.
0
0
0
-------
TABLE 8-18 (Continued)
SUBCATEGORY:
PLANT-BY-PLANT COST ESTIMATES
TYPE I W/ OXIDATION - HIGH FLOW
Plant #
Suggested
Treatment
BPT (I)
Capital
Cost ($)
Operat ing
Cost($/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
1
560,000 I
ASL/MMF
3,200,000
350,000
750,000
248
ASL
1,300,000
130,000
290,000 |
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 |
ASL/MMF
1,330,000
129,000
302,000
272
CLR
340,000
22,000
62,000 |
MMF
800,000
75,000
170,000
88
ASL
1,150,000
120,000
260,000 |
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 |
MMF
850,000
75,000
170,000
236
MMF
800,000
75,000
170,000 |
MMF
800,000
75,000
170,000
SUBCATEGORY: TYPE I W/ OXIDATION - LOW FLOW
42
ASL
490,000
54,000
125,000
I ASL/MMF
720,000
73,000
170,000
50
No Treat.
0
0
0
j 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
1
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
1 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
0
I No Treat.
0
0
0
188
No Treat.
0
0
0
I No Treat.
0
0
0
218
ASL
380,000
43,000
103,000
1 ASL/MMF
565,000
60,000
141,000
219
CLR
55,000
16,000
22,000
| MMF
230,000
20,000
48,000
239
No Treat.
0
0
0
1 No Treat.
0
0
0
268
ASL 2
,200,000
320,000
580,000
I ASL/MMF
2,880,000
380,000
720,000
271
CLR
185,000
18,000
40,000
I MMF
560,000
44,000
110,000
-------
TABLE 8-18 (Continued)
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: Type I w/o Oxidation
BPT (I)
1
BPT
(II)
Suggested
Capital
Operat ing
Annual |
Suggested
Capital
Operat ing
Annual
Plant #
Treatment
Cost ($)
Cost($/yr)
Cost($/yr) I
Treatment
Cost($/yr)
Cost($/yr)
Cost($/yr)
1
ASL/MMF
1,330,000
178,000
1
295,000 |
ASL/MMF
1,330,000
178,000
295,000
15
No Treat.
0
0
0 1
No Treat.
0
0
0
16
ALA/MMF
5,850,000
537,000 1
,270,000 I
ALA/MMF
5,850,000
537,000
1,270,000
28
MMF
740,000
68,000
155,000 I
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 1
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 1
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 1
No Treat.
0
0
0
118
No Treat.
0
0
0 1
No Treat.
0
0
0
128
No Treat.
0
0
0 1
MMF
650,000
68,000
150,000
130
No Treat.
0
0
0 1
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 I
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 1
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 1
No Treat.
0
0
0
230
ASL/MMF
1,050,000
104,000
246,000 I
ASL/MMF
1,050,000
104,000
246,000
256
No Treat.
0
0
0 1
MMF
270,000
26,000
64,000
259
No Treat.
0
0
0 1
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 1
No Treat.
0
0
0
269
ASL/MMF
2,900,000
315,000
670,000 I
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 1
No Treat.
0
0
0
281
No Treat.
0
0
0 1
No Treat.
0
0
0
-------
TABLE 8-18 (Continued)
PLANT-BY-PLANT COST ESTIMATES
SUBCATEGORY: NOT TYPE I
BPT (I)
BPT
(II)
Suggested
Capital
Operat ing
Annual |
Suggested
Capital
Operat ing
Annual
Plant #
Treatment
Cost ($)
Cost($/yr)
Cost($/yr) |
Treatment
Cost($/yr)
Cost($/yr)
Cost($/yr)
6
ASL/MMF
815,000
83,000
194,000 |
ASL/MMF
815,000
83,000
194,000
8
ASL/MMF
890,000
90,000
208,000 |
ASL/MMF
890,000
90,000
208,000
18
No Treat.
0
0
o 1
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 |
MMF
600,000
50,000
120,000
66
MMF
810,000
66,000
159,000 |
MMF
810,000
66,000
159,000
86
ASL/MMF
1,660,000
167,000
370,000 |
ASL/MMF
1,660,000
167,000
370,000
92
No Treat.
0
0
0 I
No Treat.
0
0
0
94
MMF
5,000,000
250,000
850,000 |
MMF
5,000,000
250,000
850,000
97
MMF
520,000
42,000
100,000 I
MMF
520,000
42,000
10,000
120
No Treat.
0
0
o 1
MMF
2,500,000
150,000
450,000
121
No Treat.
0
0
0 1
No Treat.
0
0
0
122
MMF
650,000
56,000
130,000 |
ASL/MMF
1,700,000
166,000
370,000
144
MMF
540,000
42,000
100,000 |
ASL/MMF
1,020,000
94,000
220,000
145
ASL/MMF
1,800,000
180,000
400,000 |
ASL/MMF
1,800,000
180,000
400,000
153
ASL/MMF
1,045,000
104,000
245,000 |
ASL/MMF
1,045,000
104,000
245,000
182
ASL/MMF
1,250,000
122,000
280,000 |
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 |
MMF
160,000
15,000
34,000
208
MMF
400,000
36,000
85,000 |
ASL/MMF
830,000
81,000
195,000
226
MMF
560,000
46,000
110,000 |
MMF
560,000
46,000
110,000
231
ASL/MMF
1 ,270,000
156,000
332,000 |
ASL/MMF
1 ,270,000
156,000
332,000
245
No Treat.
0
0
0 |
No Treat.
0
0
0
247
No Treat.
0
0
o 1
No Treat.
0
0
0
258
ASL/MMF
550,000
59,000
136,000 |
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 |
MMF
700,000
64,000
148,000
-------
TABLE 8-19
TOTAL COSTS, PLANT-BY-PLANT ANALYSIS
Capital
Co6t ($)
BPT (I)
Operating
Cost ($/Yr)
Annual
Cost ($/Yr)
I Capital
1 Co6t ($)
BPT (II)
Operating
Co61 ($/Yr)
Annual
Cost ($/Yr)
PLASTICS
33,045,000
3,215,000
7,388,000
1 41,875,000
4,265,000
9,665,000
TYPE I W/ OXID.
-High Flow
-Low Flow
31,025,000
6,540,000
3,281,000
824,000
7,205,000
1,702,000
1 43,565,000
1 10,145,000
4,363,000
1,128,000
9,682,000
2,436,000
TYPE I W/O OXID.
21,470,000
2,141,000
5,335,000
1 22,390,000
2,235,000
5,549,000
NOT TYPE I
19,220,000
1,628,000
4,001,000
I 23,680,000
1,985,000
4,921,000
TOTAL
111,300,000
11,089,000
25,631,000
1 141,290,000
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
W10 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 ASL/MMF MMF ASL CLAR
Plastics Only 31 36 33 0 0
Not Plastics - Type I
W/Oxidat ion
-High Flow 28 49 23 0 0
-Low Flow 23 54 23 0 0
Not Plastics -Type I
W/O Oxidation 40 30 27 0 0
Not Plastics NOT Type I 30 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
(8ฃ 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 Che 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 documencation 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 coated 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 SI.07 million for
the revised CAPDET versus 3.69 MG vessel costing SI.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 co 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 1. in
"Comments on Selected Aspects of Activated Sludge Treatment Technology
Based on Recent Union Carbide Experience".
268
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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 oils 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
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nologies, biological sludge from biological treatment plants, spent
activated 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 E0P 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
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'(3
o
g
E
500
400
30D U7LLENT
300
100
FIGURE 8-14 - SLUDGE PRODUCTION FOR COMPLETE MIX
ACTIVATED SLUDGE
271
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Energy Requirements
Due Co 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
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"0 20 40 50 SO 100 120 UO L60 ISO 200 220 240 260
c CHR)
FIGURE 8-15 - ENERGY REQUIREMENTS FOR COMPLETE MIX
ACTIVATED SLUDGE
-------
}m 3 .a .A .ซ .1 4 I .1 |ฃ 1 4
FLOW - MILLION GAL/DAY
FIGURE 8-16 - ENERGY REQUIREMENTS FOR CLARIFICATION
274
-------
LICN GALLONS/DAY
figure 8-17 - energy requirements for dissolved air flotation
275
-------
' M t.O
FlOU - MILLION HAL/DAT
FIGURE 8-18 - ENERGY REQUIREMENTS FOR MULTIMEDIA FILTRATION
276
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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 transAx
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 143 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 BOD^ data which
had no corresponding influent value.
278
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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 u6e 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 terra 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 rag/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 concentrat ion 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 perform 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 terra 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
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TABLE 9-1
BPT EFFLUENT LIMITATIONS
(mg/i or ppra)
LONG TERM MEDIAN
SUBCATEGORY
Plastics Only
bod5
14.5
TSS
24
MAXIMUM 30-DAY
BOD5
22
TSS
36
MAXIMUM DAILY
BOD.
49
TSS
117
Oxidat ion
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 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 plantB 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
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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
Million lbs/yr
Removed
BOD TSS
1.75
o High Water Use 6.50
o Low Water Use 2.72
TYPE I 9.68
OTHER DISCHARGERS 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
Addit ional
Solid Waste
(Tons/yr)
3,311
3,307
800
7,239
5 ,203
TOTALS
21.58
32.17
156,995
19,860
282
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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 Sunmary 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
(19,860 tons/yr) of wastewater treatment solids
mary Data Base. Table 9-2 presents the amount of
erated by subcategory.
AIR AND NOISE
Attainment of BPT will have no measurable impact on air or noise
pollution.
18.02 thousand kkg/yr
for plants in the Sum-
additional solids gen-
283
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TABLE 9-3
CASE STUDY FOR ESTIMATING TOTAL INDUSTRY
DIRECT DISCHARGE LOADINGS FOR
BODj AND TSS
3
mg/I million lbs/year
bod5
Mean raw waste^ 945 3,1.53.9
Current effluent^ 63 208.3
BPT effluent2 18 59.5
TSS
A 148.8
Mean raw waste^ 427 1,401.7
Current effluent^ 63 208.3
BPT effluent2 32 105.8
A 102.5
mean of all plants in Summary Data Base
median value of all biological systems with BOD removal >_ 95% or
effluent BOD^ ฃ 50 mg/1
based On 330 operating days per year, 2.31 MGD per plant, and 520
direct discharge plants
284
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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 Amer ican 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
(rag/I or ppm)
LONG TERM MEDIAN
MAXIMUM 30-DAY
MAXIMUM DAILY
SUBCATEGORY
Plastics Only
bod5
14.5
TSS
24
BOD 5
22
TSS
36
BOD,
49
TSS
117
Oxidat ion
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 limitacions 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
111 - " ฆ J
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 LO-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 Cose Per Pound of
Cost
(1979 $/yr.)
2,277,000
2,477,000
734,000
214,000
920,000
BOD, and TSS Removed
(1979 $/yr.)
$ 14.09/lb.
$ 1.13/lb.
$ 1.77/lb.
$ 0.46/lb.-
$ L.52/lb.
-------
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: BOD5, 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
BOD 5
22
TSS
36
BOD.
49
TSS
117
Oxidat ion
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 times
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 As sociates Contract 68016701
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
Perspect ive, Part 1, New York, John Wiley & Sons, 1980, p. 40.
4-1 Conover, W. J., Pract ical Nonparamet ric Statistics, 1st Edition,
New York, John Wiley & Sons, 1971, pp. 245-249.
4-2 Kendall, H. G. and Stuart, A., The Advanced Theory of Statistics,
Volume 2, Inference and Relationship, New York, Hafner Pub-lushing
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. a
Barton, D. A., "Survey of Indus-
trial Applications of Aqueous--Phase Activaced--Carbon Adsorption
for Control of Pollutant Compounds from Manufacture of Organic
Compounds," Env i rose ierice 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 Wasce 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.
8-8 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 (CAPDETTI Office of Water and Waste
Management, U. S. Environmental Protection Agency, Washington, DC,
1980.
E-2 Peters, M.S. and Timraerhaus, 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 Construetion 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 Synchetic 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, 19B0.
297
-------
Sidwick, J.M., "The Treacment of an Industrial EffLuent From the
Manufacture of Organic Chemicals for Process Reuse," Prog. Water
Tech. , Vol. 10, 1978.
Sittig, M., Pollution Control in the Organic Chemical Industry,
Park Ridge, NJ, Noyes Data Corp., 1974, pp.34-38.
298
-------
APPENDIX A
GENERIC PROCESS CODES WITH FREQUENCY OF OCCURRENCE
-------
FREQUENCY or OCCURRENCE FOR EACH PRODUCT PROCESS *
PP..CODE OtN^COOf OIR ZERO
UNK
PP"TE*T
0005*01
0005*02
0005-03
0005-90
0010-90
0012*01
0030*02
0030*06
00)0*07
0070*00
ooro*of
0070*0*
0070-05
ooro-or
0070*08
0070*09
0070*12
0070*13
0070*14
0070*15
0070*1*
0075*00
0075*99
0080*01
0080*02
0090*01
0090*03
0090*00
0090*11
0100*01
0110*01
0110*02
0120*01
0130*01
0130*02
0130*03
01*0*01
0150*01
0153*01
0155-01
0155*02
0155-03
0155*06
*Note:
01
01
01
3
1
01
C
E
01
01
01
01
"1
APS RESIN/EHULS10N POLYMERIZATION
AซS RESJN/MASS POLVMER!Z*TiON
ASS RESIN/SUSPENS10M POLYMERIZATION
AflS RESIN/FINiSMifiO PROCESS
ABS/SAN/FINISHINQ PROCESS
ACENAPhThEnE/BY-PROOUCT 0' PROPANE PyROLYSIS
ACETAlOEhyde/oKIOATIOn or ETHYLENE with CUCL2 CATALYST
ACETซLOEmvde/RY*PROOUCT OP ACROLEIN BY propylene OXIO
ACET*LOEMYOE/CAT*LYTIC OEHYOROOENATION or EThANOL
ACETIC *CI0/
ACETIC ACI0/CATAL*TIC OXIOATION or BUTANE
acetic acio/oiioation or acetaloehyde
ACETIC ACIO/CAR0ONYLATION OF METHANOL WITH CO AND H*
acetic acio/by-product or p*a"inopmenol "y acid clv
ACETIC ACID/BY-PRODUCT OE OIATRIZOIC ACIO
ACETIC ACIO/TRANSESTERlriCATION-MCTHYLACETATEirORMICACID
ACETIC ACID/BY-PRODUCT POLYVINYL rORMAL
ACETIC ACID/BY-PRODUCT or POLYVINYL AlCOMOL(MYOROLVSIS Of POLWInlE ACETATE}
ACETIC ACIO/RECOVERY PRO" POLYOL PROCESS
ACETIC ACIO/RECOVERY rROM SULriTE PULP WASTEWATER
ACETIC ACID/COPROOUCT OF TPA BY OXIOAT OF ACETALOEMYOE
acetic acid salts/ acetic acid ~ metal o*ide or hydroxide
ACETIC ACID SALTS (TOTAL)/ ACETIC ACIO * METAL OXIDE (HYDROXIDE)
ACETIC ANMYORIOE/THER^AL CRacซINo OF ACETIC ACIO
ACETIC AmhvORIDE/FRom ACETIC By ACIO kETCnE PROCESS
ACETONE/CUMENE PEROXIDATION and ACIO CLEAVAOE
aCeTONe/oEhYDROOENATiOn of ISOPROPANOL
ACETONE/vAPOR-PHASE OXIDATION OF RUTANE/PROPANE
ACETONE/BYPROOUCT OF H202 BY OXIDATION OF ISOPROPANOL
ACETOWE CYANOhYORIN/RXN OF ACETONE WITH HYDROCYANIC ACID
ACETOnITRIlE/ NH3 ~ ACETIC ACIOtOEHYORATION OF ACETAmIDE
ACETONITRILE/RY-PROOUCT OF ACRYLONITRILE BY AMMOXIDATI0N OF PROPYLENE
acCTOPmEmonE/ปY*PRODUCT Phenol by CUmenE PEROXIDATION and ACfO CLEAVAqE
ACETYLENE/PARTIAL OxIOATION of methane
ACETYLENE/FROM CALCIUM CARBIDE
ACETylEnE/BY-PRODUCT OF BY PROPANE PYR0LYSIS
ACROLEIN/OXIOATION OF PROPYLENE
ACRYLAHIDE/CATALYTIC HYDRATION OF ACRYLONITRILE
ACRYLIC LATEX/EMULSION POLYMERIZATION
ACRYLIC RESINS/EMULSION POLYMERIZATION
ACRYLIC RESINS/SUSPeNSION POLYMERIZATION
ACRYLIC RESINS/SOLUTION POLYMERIZATION
ACRYLIC RESINS/RULK POLYMERIZATION
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.
-------
frequency or occurence roR each product process
PP_CODE ซEN_CODE OJB ZERO UN* PP TEXT
0155-10 01 1 .
0155-11 01 1 ,
0155*1* 01 1 .
0\*5-99 01 1 .
0156-01 01 2 ,
0156-02 01 2 ,
0160*03 0 1
0160*04 C 1
0160-80 C 2 1
0165-01 0 3 2
0165*0* 0 1 .
0165*05 0 1 ,
0165*06 0 1
0165*07 0 1 .
0165*09 0 1 ,
0165*10 0 2 .
0165-11 0 1 .
0165-12 0 1 .
0169*13 0 1 ,
0165-1* 0 1
0165*15 0 1 .
0170-00 * , 1
0170-01 N 3 1
0175*01 9 1 .
0176*01 6 1 .
0177*01 0 1
0179*01 0 1 1
0180-01 C . 1
0180*02 E 1 .
0180-03 C . 2
0180*80 C 1
0185-01 B , 1
0185-03 18 1 .
0185*04 K , 1
0185*05 19 1 ,
0186-01 5 1 ,
0189-00 01 . 1
0189-01 01 5 15
0191-01 ]2 2 ,
0192-01 F1 , 1
0192*03 K 1 ,
0192-0* 1 1 ,
0195-01 11 1 .
ACYL1C
ACRYLIC
ACRYLIC
ACRYLIC
ACRYLIC
ACRYLIC
ACYL1C
ACRYLIC
ACHYLIC
ACRYLIC
ACฐYLIC
ACHYLIC
ACRYLIC
ACRYLIC
ACPYLIC
ACRYLIC
ACHYLIC
ACRYLIC
ACYLTC
ACRYLIC
ACRYLIC
ACYLONITRILf/
ACRYLOHlTRILF/PHOPYLCNE AMMO*IDATION
AOIPIC ACIDiOI<2ปrTMYLMe*rL)eSTER/pSTe*IFIC OF AOIPIC AC
AOIPIC ACIOiOI-ISQDECYL ESTER/FSTERlFICATION OF ADIPIC A
AOIPIC ACIO.OI*TRIOCYL ESTf.R/ESTERIF I CAT ION OF AOIPIC A
AOJPIC ACID eSTEปS/ESTCRFICATION Or AOIPIC ACIO
AOIPIC ACIO/OXIOATION OF CYCLOHEXANOL
AOIPIC ACIO/DEPOLYMCRIZ4TION OF NYLON 6
AOIPIC ACIO/OXIOATION OF CYCIOHCxanOL'OnE MIX
AOIPIC ACIO/ OXIDATION OF CYCLONEXANE VIA OL/ONe
AOIPONJTRILE/CHLORINATION ซ CYANATfON Or BUTAOICNf
AOlPON1TRILE/ DIRECT HyOROCYANATION OF BUTADIENE
AOIPONITRILE/AMMONOLYSIS OF AOfPlC ACIDDEHYORATION Of 0IAMIDE
ADIPONITRILE/ELECTRONYOROOIMERIZATION OF ACRYLONITB1LE
ALKOXy ALKANOLS/ ALKOXV ALKANOLS from alkylene OXIDE AN
ALKYO RESINS/
ALKYO RESJN/CONOENSATION POLYMERIZATION
ALKYL ปENZrNrS/*LKYLATION or BENZENE "ITM ALPMA-OLEF1NS
ALKVL AMINES/HV0ป00EN*TI0N OF FATTY NITrILE
ALXYL Aป"INES/AMlN*TION OF ALCOHOLS
ALKVL AMINFS/C-13*C19 FROM OLEFIN I hcn II H2
AL*YL PMENOLS/NONvL-OCTvL ALKYLATION Or PHENOL
RESINS/BULK POLYMERIZATION TO CAST SHEET
RESINS/E-ULSION OR SOLUTION POLYM, TO COATINOS
RESINS/POLVACRyLAMIDE BY SOLUTION POLYMERIZATION
RESINS/PROCESS IN REVIEW
riHEn<85ซ POLYACRYLONITPILEI/SUSP poly.wet spinn
FIBER (85* POLYACRYLONITRILEISUSP POLY.DปY SPINN
ACJO/FROM ACETYLENE(CARBON MONOXIDE AND WATER
ACIO/OXIOATION OF ACROLEIN
ACIO/OXIOATION OF PROPYLENE VIA ACROLEIN
ACIO ESTERS/ACRYLIC ACIO ESTERTF OF MISC ALCOHOL
ACID ESTFRS/HYDROXY alkyl acrylate by acrylic AL
ACIO ESTERS/ETHL 2*CYANO ACRLATE FROM FOPMALOtET
ACIO ESTERS/METHL 2*CYaNO ACRLATE FROM FORMaLOซE
ACIO ESTERS/ALLYL 2-CYANO ACRLATE FROM rORMALOtE
ACIO ESTERS/N.BUTYL ACRYLATE-ACRY ACIDซNsBUTANOL
ACIO esters/ethyl ACRYLATE-ACRY ACIO ~ ETHANOL
ACID ESTFRS/ETHYLHFXYL ACRYLATE*ACRV ACID.FTmhE*
ACIO ESTERS/ISOBUTVL ACRYLATE-ACRY ACID*ISORUTAN
ACID esters/ethyl acrylate-moptficd rerpe procfs
ACIO ESTERS/metmv ACPYLATE-MOOIFIEO RePPE PROCES
ACIO ESTERS/BUTYL ACRYLATC-MOOIFIEO REPPE PROCES
-------
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS
3
PP.CODE
OEN.COOE
DIP
zeป o
UNK
PP_TEXT
01*5.02
11
2
ALKVt PHENOLS/MIXED ALKVUTJON OF PHENOL
0200*01
I
1
ALLYL AlCOWOL/PEOOK OF ACROLEIN AND SEC*0UTANOL(REDUCTION BY ALUMINUM BUTOX10E)
0*00.03
r
1
#
AtL*L AlCOMOL'HVDROLYSIS OF allyl chloride
0210*01
*
ALLYL CHLOR1DE/CHLORINATION OF PROPYLENE
0230-01
5
amxnoetmyleThanolamine/RXN of ethyleneoiamine ป eTm,0*!0
0238*03
7
P-AMINOPHENOL/REOuCTION of NItR0BEN?ENE*ac!0 REARRANGE
0240*01
AMYL ACETaTES/RXN of ACETIC ACID ซ. AMYL ALCOHOLS
0300*03
F2
ANILINE/BY*PR0DUCT OF P-AMlNOPHENOL
0300*0*
F2
ANILINE/NITRORENZENE HYDROOENATION
0320*01
11
ซ
ซ
ANiSlOlNE/METHYLATlON and REDUCTION
0320*99
ANISIOINE/PROCESS UNDER REVIEW
0335*01
2
1
*NTHRปCENE/CO*L Tar OISTILLATION
0390*99
C
1
ANTHRAOUINONE/ OXIDATION OF ANTHRACENE
0358-00
3
ABPIHTN/OENfRAL
0350*01
3
ซ
ASPIRIN/ACETYLATION OF SALICYLIC ACID
0350*99
1
ASPIRlN/ACETYLATION OF SALICYLIC ACID
0)60-03
C
1
ป
BENZALOEHYDE/OX IDAT ION OF TOLUENE
0300-00
H
1
BENZENE/ STEAM PYROLYSIS OF LPQ
0300*01
BCN7ENE/MYnPODEAL"YLI2ATION OF TOLUENE AND/OR XYLENE
3=> 0300-02
2
BENZENE/DIST OF BTX EXTRACT,CAT, REFORMATS
^ 0300-04
H
BEN7ENE/OIST. OF BTX EXTRACT-COAL TAR LIGHT OIL
0300-08
c
1
BENZENE/BY*PRODUCT OF PmenOL*Hfo BY CUMENE OXIDATION (RECOVERED RAM MATERIAL)
0300*09
>
BEN7ENC/OIST OF BTX EXTRACT*PYROLYS!S OASOLINE
0300*11
2
1
BENZENt/nv.PRODUCT OF SILICONE MANUFACTURE
0300*12
1
BEN7ENE/HY-PPOOUCT OF STYRfNE BY ETHYLBENZ nCHYDROOENATI
0300*13
1
benzene/by-product of acrylate MANUFACTURE
-------
FREQUENCY OF OCCURRENCE. FOR EACH PRODUCT PROCESS
PP.COOE
OEN_COOt
0]R
zeRo
UNK
PRETEXT
0640*01
ri
1
n.RUTVL ALCOHOL/BY PRODUCT OF 1ป3*BUTYLENC GLYCOL BY HVO
06*0-02
f i
6
i
N.9UTYL ALCOMOL/HYOROQEMATION OF N*BUTYRALOEHYOE OXO PR
0640*0%
12
1
n.BuTyL ALCOhOL/OISTILLATION OF DILUTE AOUEOUS BUTANOL
0650.01
12
3
SEC*BUTVL ALCOHOL/IN01RECT mYoRATJON OF BUTENES
0660-99
12
1
TERT-BUTYl ALCOmOL/FROm ISOBUTYLENE
0710ซ01
F1
2
1.3 BUTYLENE 0LYC0L/MY0R0GE*ATI0N or acetalool
0720*01
15
5
BUTYLENES/BY EXTRACTIVE OISTlLLATION OF C4 PYROLVZATES
0720*99
15
BUTyLENES/ FRO* PYROLYZATE BY EXTRACTIVE DISTILLATION
07)0*99
I
9
tert*butylphenol/ alkylation of phenol ซitm isohutylene
0750*01
0
2
NvBUTYRALOEhyOE/hyOHOFORHyLATION OF PROPYLENEiOxO proces
0760*01
C
1
N*BUTYRIC ACIO/OXIOATION of BUTYRALOEHYQE
0760*02
C
n.HUTYRIC ACI0/C0*PR00UCT of BUTANE OXIDATION
0780*99
6
1
N*PUTyRONITR1LE/ BUTANOL ~ NH3, DEHYDRATION
0785*00
4
t
CAPROLACTAH/
0785-06
z
CAPROLACTAM/FROM PHENOL VIA CYCLOHEXANONE OXIME/
0785*07
z
CaPROLaCTaM/OEPOLYMERXZATION NYLON 6
0785*09
c
2
CAPROLACTAM/FROM CYCLOHEXANE VIA CYCLOHEXANONE AND OXIME
0790*99
3
1
f
CARBON 01SULFIDE/PROCESS UNDER REVIEM
0810*01
8
t
t
CARBON TETRACHLORlOE/CHLORINATION OF MfTMANE
0810*02
8
)
Carbon TETRaChLORIOE/ChLOR, OF methyl CHLORIDE (FROM MVOROCHLORINATION OF METHANOL)
0810*0)
B
CARBON TETRaCHLORIDE'CmLORINATION of CARBON disulfide
0810*04
a
4
CAPBON TETRACHLORlOE/CO*PROOUCTION OF TETRACHLOROETHYLeN
0810*05
H
1
CARBON TETRACHLORIOE/BY-PROOUCT OF PHOSOENE MANUFACTURE
0814*01
01
CAPBOXMETHYL CElLULOSE/fTHERIFICATION of CELLULOSE
0815*00
E
9
CASTOR OIL (INCLUOINO USP)/
0815*99
4
CASTOR OIL (INCLUOINO uSP) PROCESS UNDER REVIE*
0816*01
0
3
CELLOPHANE/VISCOSE PROCESS
0R20*01
23
5
f
CELLULOSE ACETATES FIBEPS/SPINNINO FROM ACETYLATEO CELLU
0820*03
01
5
CELLULOSE ACETATES RESIN/ACETYLATION OF CCLLI'IOSC
0821*01
0
1
CELLULOSE ACETATE/BUTYPATES
0823*01
0
1
CELLULOSE ACETATES/PROPIONATES/ESTERIFICATN OF CELLULOSE
0824*01
L
1
CELLULOSE NITRATE/NITRATION OF CELLULOSE
0825*01
G
1
CELLULOSE SPONOE/VISCOSE PROCESS
0840*99
B
t
$
CMLOROACETIC ACIO/ CHLOHINATION OF ACETIC ACIO
0890*01
B
2
CHLOROBENZENE/CHLOHINATION OF BENZENE
0890*99
4
9
chlororewzeme/
0921.01
P
1
9
ChlOROOIFLUOHOMETHAnE/hyDROFLUORINATION OF CHLOROFORM
0930*01
B
3
CHLOROFORm/CHLORINaTIOn or METHYLCHLORIOE (FROM MYOROCHLORINATION OF METHANOL)
09)0*02
B
2
$
CHLOROFORM/CHLORINaTION OF methane
09)0*03
b
9
CHLOROFOPM/BY*PROOUCT OF CARHON TETRACHLORIDE PROOUCTION
0930*04
C
1
CHLOROFORM/ 8YซPR00UCT OF ACETALDEHYDE PRODUCTION
0949*01
B
1
MbCHLOROnITROUEnZEnE/ChlOHINATION or NITROBENZENE
0950*99
L
0*CHLORONITROBENZENE/ NITRATION Or CHLOROBENZENE
-------
FREQUENCY OF OCCURRENCE FOB EACH PRODUCT PROCESS
5
i
<_n
PPCODE
OEN_C
0951.99
L
0961-01
8
0963-01
8
0993-00
6
0993-01
6
0993-99
4
099499
3
0997-01
H
099B-99
3
1005-01
2
1007-01
H
1010-01
H
1021-01
2
1030-01
2
1060-01
12
1080-99
7
1100-99
3
1120-02
F2
1122-01
F2
1130-02
F2
11)5-01
C
1140-01
c
1140-02
F2
1140-03
C
11*0-04
J1
1170-99
D2
1171-01
15
1190-01
A
1215-01
1216-01
1216-02
V
1220-01
1221-01
P
1229-02
P
1236-00
B
1244-01
B
1244.02
B
1244.03
S
1257.01
B
1265.01
8
1271.01
B
1281-99
20
1300-01
5
DIR ZERO UMK PP.TExT
P-CMLORONITROBEN7ENE/ NITRATION OF CHLOROBFNzENE
2-CHLOBOPHENOL/CHLORINATlON OF PMfNOl
~ChLOROPHEnVL PHENYL ETmep/CMLOR OF PHENYL PHENYL ETHER
CHOLINE CHLORIDE/ ETHYLENE OXIOE TRImeThyLamine ซ MCL
choline chloride/ ethylene chlorohyorin trjmethyl amine
CHOLINE CHLORIOE/PROCESS UNOEM REVIEW
ChPohiUmjT0T4L/PROCESS UNnER REVIEW
COซL TAR/COKINO OF COAL
COPPER I TOTAL)-PROCESS UNDER REVIEW
CO*L TAP PRODUCTS (hISC.I/COAl TAR DISTILLATION
CREOSOTE/DIST, OF COAL TAR LIOMT OIL
nซCRESOL/REFINlNfl OF mixeo CBESOLS
CRESซLS.MIMED/TAR ACID RECOVERY AND PEFInInO
CRESYLIC ACIO/TaR ACID RECOVERY REFININfl
CUHfNE/ALKYLATION OF BENZENE BY PROPYLENE
CVANOACETIC ACID/ CHLOROACETIC ACID ~ NACN
CYANIJPIC ACID/ HEAT UREA
CYCLOHE*ANE/MYORO0ENATION OF BENZENE
CYCLOHEXANE niMETHANOL/HYOROOENATION OF DIMETHYL TERAPHT
CYCLOHEXANOL/HYDROflENATION OF PhENOL"DISTIL
CYCLOHEXANOL/ONE(MIxEOI/OlIDATION OF CCYCLOHEXANE
CTCLOHEXANONf/OXIOATION OF cyclohe*anc
CYCLOHEXANONE/HYOROOENATION OF PHENOL-DISTIL
CYCLOHEXANONE/OXIO or CYCLOhexanE-DISTIL-OEHYDROO of ol
CYCLOHEXANONE/OEHYOROOENATION of CYCLOhExanol
cyclooctadiene/ oimerization of butadiene inickle cat,)
CYCLOPENTaDIENE DINER/EXTR DIST C5 PYROLYZaTeS ~ 01her 11
DIACETONE ALCOHOL/ALDOL CONDENSATION OF ACETONE
M-DICHLORORENZENE/CHLORJNATION or BENZENE
O-OIChlOROREnZEnE/CHlOPInATIon oF BENZENE
O-OICHLOPOOENZENE/BY-PROdUCT of POLYMfPtc MDI OR TOJ MANUFACTURE CPhOSOENaTION SOLVENT)
p-DiChLOROHENZENE/ChLORINATIOn or BENZENE
DICHLORODIFLuOROHETHANE/HYDROFLuOPINATION or CARBON TETRACHLO
ltl OICHLOROETMANE/REACT or HCL I VINYL CHLORIDE
I2-TRAnS-OICHLOROETHYLEnE/ CHLORINATION or ETHYLENE
1 ?ซOICMLORDETHANe/OIRECT CHLORINATION Or ETHYLENE
li2 OICHLOROETHANE/ CHLORINATION Or ETHYLENE
1 i?-DICHLOPOETHANE/OXYCHLORlNATION or ETHYLENE
DICMLORON1TROBENZENE/CHLORINATION OF NITROBENZENE
ZปaซOIChlOROPHENOL/CHLORInaTIOn of phenol
1 ป2-0IChl0R0PR0PEnE/BY.PDCT OF ALLVL CHLORIDE HAnUFACTUR
DICHLOROPROPANE/ BY PRODUCT CHLOPOHyDRINATION OF PROPYLENE
OIETHYLENE GLYCOL/COPRODUCT OF ETHYLENE OLYCOL FROM fTHY
-------
frequency of occurrence for each proouct process
6
PPCODE
OEN_CODE
Of
ZERO
UNK
pp.tekt
1300-04
5
2
oiethvlene olycol (refining of distil t*ilsป / ethylene glycol ~ f.o
1300-05
C
OIETMVLENE ซL*COL/CO-PROO OF HYDROLYSIS -ETHYLENE 0*IDE
1365-01
6
1
DIETHYLENE TRI4HINE/ETHYLENE diamine * EOC nhs
1*40-99
0*
1
t
DIISOBUTYLENE/PROCESS UNOER REVIE"
1442-01
12
1
OMSOPPOPYL BENZENE/HY-PBOO OF CIJMENE
1450-01
A
2
t
OIKFTENE/OIMERIZATION OF KETENE-ACETIC acio
1465-99
5
2ซOImETHYL*HINOFTHAnOL/ ETHOXYLATION OF DIHETHYLAMINE
14*0-01
A
N.N-DIMETHYLANILINE/CATALYTIC CONDENSATION OF ANILINE
1460-99
A
1
9
DIMETHYL ETHEB/OEHYDPATION OF METHANOL
1490-00
K
1
N,N-DIMETHYLF0BH4HirปE/ DIHETHYLAMINE FORMALDEHYDE
1490-99
K
1
NNpIMCTHVLFOBMiHjoe/ D1mEThYLaminc ~ FORMIC ACIO
1500-99
1
DIMETHYL SULFATE/ METHANOL SULFURIC ACID
1510-99
14
1
mfTHYL SULFIDE/ K MjThyl sulfate *kzs
1530-01
5
OImETHYl TEHEPHTHAlATE/ESTEBIFICATION OF TPA^hETHANOL
1530-0?
c
t
DIheTwyL TERCPHThalaTE/OKIOATION OF P-XYLENF methyl estc
1535-99
L
1
ฆ
0INlTB08ENZENE(H(0fP)/ NITBATIOM of BENZENE
1550-01
L
4
OINITROTOLUENE (MIxEO)/NITRATION OF TOLUENE
1551-01
L
1
2t4 DINITBOTOLUENE/NITRaTION OF TOLUENE
1552-01
L
1
2*6 01NIT BO TOLUENE/** ITBAT 1 ON OF TOLUENE
1560-01
4
1
OIPHENVLAMINE/CATALYTIC condensation OF aniline
1590-99
4
OIPHENYL ETHER /CHLORO0ENZENE SODIUH PHfNOLATE
1610-01
5
t
OIPBOPVLENE GLYCOL/R*N OF PBOP, GLYCOL PBOPY OK IDE
1610-02
E
OIPBOPVLENE GLYCOL/CO-PROD OF H*oปOLYSIS-PBOPYLENE OXIDE
1612-99
A
2t2-DITHIoBISBEnZOTHIAZOLE/ OXIDATION OF 2-mERCAPTORENZOTRIAZOLE
1634-01
4
DOOECYLOUANIOINC ACETATE/CONDENSATION OF DODECYLAHINf *c
1635-99
M
1
DODEC*LMEBCAPTAn/ DODECENE ~ H2S
1641.99
L
1
OYES^OvE INTERMEDIATES/WAT DyESi A20 dyes
1650-01
20
3
EPICHLOROHYDBIN/FROM 4LLYL ChLOBIPE wta nIchlorohvdrIN
1653-01
21
2
EPO*10IZEn ESTErSiTOTAl/EpOXIOATIon OF unsatupateo esteb
1656-00
01
EPOXY BESINS/ EPICHLOROHYDBIN ~ BISPHENOLA
1656-01
01
3
EPOXY PESins/EPiChLOROhYDRiN RiSPhEnOL A
1656-02
01
1
EPOXY RESINS/FROH polyols ~ EPICHLOBOHyDRIN
1656-03
01
1
EPOXY PESINS/EpICHLOBOhYdRIN ปNd nOVOLA* BfSINS
1656-04
D
EP0*V BESINS/EPOKIOATION OF POLYMERS
1656-OT
01
ซ
EPOXY RESINS/PURCHSD EPOXY(EPI-BIS)RESIN BISPHENOL A
1656-08
01
1
EPOXY RESINS/PUBCHSD EPXY BESINS.RISPHENOL AปFATTY ACID
1656-09
01
1
EPOXY RESINS/MOnIFIED EPOXVESTEB
1656-10
01
EPOXY beSINS/PURCHaSED FPOXY(EPI-RIS)BESIN*DIETHaNOLamIN
1659-01
H
1
ETHAnE/CRACK 1 kiG OF NAPHTA
1659-02
2
1
ETHANE / NATURAL gas by-product
1659-03
3
ฆ
ETHANE/REFINEBY BY-PBODUCT
1660-01
12
3
2
ETHANOL/OIBECT hvORatION OF ETHYLENE
1660-0?
C
1
ETHAN0L/COPR0DUCT OF butane OXIDATION
-------
12
14
5
0
c
n
02
C
c
*
14
02
C
C
K
c
3
FREQUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS
OIR 2ER0 UNK PP_TCKT
4 . . ETHaNOLAMINES/AMMINOLYSIS or ETHYLENE 0*I0E
4 . , ETwOXYLATES/FROM AlkYLENE 0*I0t AND ALKANOL
2 F.TH0*YL*TSป (HlSO/ALKYLPHtNOL-PHE^OL i ETHYLENE 0*101
2 1 ETH0KYL*TtS/CllปCl?ปLINE4R ALCOHOLS AND ETHYLENE OXIDE
1 2 . ETHYL ACETATE/ESTERIF OF ACETIC ACID WITH ETHANOL
1 ETHYL ACETATE/COPRODUCT OF BUTANE OXIDATION
. . . ETmyl ACETATE/FROM POLYVINYL ACETATE ANO ETmANOL
1 ฆ ETHyL ACFIOACFTATE/ ACETALOEMYDE CONDENSATION
1 . , ETHYLAHINC /AMM0N0LVS1S OF EThaNOL
9 . ETHYL8EN7ENE/BEN7ENE ALKyLATION
3 ETHYLBENZCNC/SEPARATION prom bt* extract
1 1 ETHYLBENZENE / ALKYLATION OF BENZENE WITH ETHYLENE
1 ETHYL9EN7ENE/0ISTILLATI0N FROM COAL TAR
1 EThyl CELLULOSE/CELLULOSE ~ ETHYL CHLORIDE
t ethyl chloride/hydrochlorination OF ETHYLENE
1 . ETHYLCYANOACETATE/ ETHANOL ester of CYANOACETIC acid
11 A . ETHYLENE/PYROLYSIS OF EThANC/PBOPANC/BUTANE/LPO
5 1 ETHYLENE/PYROLYSIS OF naphtha anoซOR OAS OIL
2 . . ETHYLENE/PYROLYSIS OF EThaNE
2 ป ETHYLENE/PYPOLYSIS OF NAPHTHA(PROPANEtETMANE(BUTANE
1 ETHYLENE/FRACTIONATION OF REFINERY LIGHT E*OS
2 1 . ETHYLENE DIAMINE/AMJNATION OF ETHYLENE OICHLORIOE
i . ETHYLENE DIBROMIDE/ ETHYLENE ~ BROMINE*
11 1 ETHYLENE QLYCOL/hyOROLYSIS OF ETHYLENE OXIDE
2 1 ETHYLENE 6LYCOL/HYDROLYSIS OF ETHLENE OXIDE
1 ETHYLENE GLYCOL "ONOEThyl EThER ACETATE ETHANOL ~ ETHYLENE OXIOE ACETIC ANHYORIOE
ETHYLENE GLYCOL M0N0HETHYL ETHER/ HETHANOL ~ ETHYLENEOXIDE
1 ETHYLENE GLYCOL monomctmyl ETHER/ETHOXYLATION OF ALCHOLS
2 ETHYLENE GLYCOL monomEThyl ETHER/ METHANOL ~ ETHYLENE OXIDC
1 ETHYLENE GLYCOL MONOMETHYL ETHER ACETATE/ METHANOL E.O, ACETIC ANHYDRIDE
11 2 ETHYLENE oxioe/direct OXIDATION OF ethylene
1 ( ซ ETHYLENE OXIOE/VIA ETHYLENE CHLOROHYORIN process
8 1 , POLYETHYLENE & POLYVINYL ACETATE COPOLYMERS/ \
1 *2 ETHYL HEXANOIC ACID/OXIDATION OF 2.ETHYLHEXALOEHYDE (FROM ALOOL CONO OF N.RUTYRALDEHYOE)
2>ETHYLHEXAN0IC ACID/OXIDATION OF 2>ETHYLHEXALOEHYDE
4 . 2ซethyl hexanol/aldol CONDENSATION-MYDROG OF N*BUTALDEHY
1 EThyL ORTHOFORMATE/ CHLOROFORM NAETHANOLATE
3 ป . FLUOปOCARBON RESINS/POLYHERUaTION of FLUORINATED OLEFINS
11 * . FORMALOEHYDE/OXIDATION OF METHANOL-SILVER CATAlYST
T 9 . FORMALOEHYOE/OXIOATXON OF mEThan0LซmeTAL OXIDE PROCESS
1 . FORMAMJOE/ FORMIC ACIO ~ AMMONIA
#2 FORMIC ACID/RY-PROOUCT OF BUTANE OXIOATION
. FOฐmic ACID/RECOVERY FROM SULFITE PULP WASTEWATER
-------
FREQUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS
a
pp.cooe
oEN.cooe
DIR
ZERO
UNK
PPTEKT
2070
01
22
1
FUMARIC ACID/ISOMERJZATION OF MALEIC ACIO
2080
00
24
GLUTAMIC ACIOt MONOSODJUM SALT/
>080
01
24
GLUTAMIC ACIOt MONOSODIUM SALT/OLUTAMIC ACIO ~ NAOH
2080
99
1
t
GLUTAMIC ACIOt MONOSOOIUM SAlT/NfUT OF SLUT ACIO BY NAOH
2090
01
12
1
GLYCERINE (SYNTHETIC)/HYDROXYLATION OF ALLYL ALCOHOL
goto
03
e
GLYCERINEซSYNJ/myoROL OF EPICMLOROMY VIA ALLYL CHLORIDE
2120
99
OLYOXAL/ OZONATION OF BENZENE
2136
01
H
t
HEPTANE/BTX SOLVENT EXTRACTION AND ADSORPTION
21*5
01
8
1
HEXACMLOROBENZENE'CHLORINATION of benzene
2145
02
A
HEXACHL0R08ENZENE/BY PRODUCT OF TETRACHLOROETHYLENE (CHLORINATION
2145
03
8
1
hEXACmL0R0BENZEnE/BYปPR0DUCT OF CHLOROSILANfS
2150
01
8
1
HEXACHLOROETHANE/ETHANE CHlORINATION
2165
01
K
1
HEXAMETHvLENEOIAMINE/AMmonolySIS OF 1-6 MEXANfDlOL
2165
02
ri
hcXAMEThYLE*EOIAMINE/HYDROGENATIO*< OF ADIPONITRILE
2165
03
c
1
t
HEXAHETHVLENEOIAMINE/OEPOLYMERIZATTON OF nylon 66
2166
99
A
1
HEXYLENF OLYCOL/ ALDOL CINQENSaTION OF ACETONE
21 TO
99
ri
1
MEXAMFTMYLENE GLYCOL UiA.HEkaNEDIOL)/
2180
99
A
*
mEXAMEThyLENETETRAMINE / FORMALDEHYDE NH3
2181
01
HEXANE/RTX SOLVENT EXTRACTION ANO AOSORPTION
2181
02
3
ซ
HEXANE / REFINERY BYซPROOUCT
2185
99
3
1
ซ
HYDRAZINฃ SOLUTIONS/PROCESS UNDER REVIE*
2190
99
1
HYDROGEN CYANIDE / PROCESS UNOER REVIEW
2200
01
C
1
hYOROOUINONE/OXIDATIOn OF ANILINE VIA OUINONE
2212
01
1
HYOROXYETHYL CELLULOSE/ETHOXYLATION of ALKALI cellulose
2215
99
3
1
hydROXYLAMINE/PROCESS under REVIEW
2216
01
01
mYDROXYPROPYL CELLULOSE/EThERIFTCATION of cellulose
2225
99
A
t
1
ImtnOOI-ACETIC ACIO/ NH3 ~ FORMALDEHYDE ~ NACN
2240
99
15
1
ISOAMYLENE / EXTRACTIVE DISTILLATION OF BTX RaFFINaTE
2250
01
F1
1
ISOBUTANOL/HYOROfl of IS0BUTYRALDEHV0Eซ0X0 PROCESS
2250
02
A
1
ISORUTANOL/FROM IS0*8UTYRAL0EHY0E by ALDOL CONDENSATION
2250
03
A
1
t
ISOHUTANOL/ crude ISOBUTANOL by AlOOL CONDENSATION/ HYOR
2260
99
0
1
1
IS0ซUTyL ACETATE/ISOBUTANOL ~ ACETIC ANMYORIDE
2265
01
IS
ฆ
1SOBUTYLENE/EXTRACT FROM C4 pyrolyzate
2265
02
e
1
ISOfluTYLENE/DEHyORATlON OF PuRCHAjEO TERT-BuTANOL
2266
01
02
1
ISOPUTYLENE POLYMERS/POLYMERIZATION OF ISOBUTYLENE
2270
01
0
1
ISOBUTYRALDEHYDE/HYDROFORMYLATION of propylene-oxo proce
2280
01
c
1
ISOPUTYRIC ACID/ ปIR OXIOATION OF ISORUTYRaLDEHYDE
2300
99
0
1
ISODECANOL/ CARBONYLATIOn of OLEFIN oligomers ป M2
P320
99
0
1
I500CTYL ALCOHOL/CARBONYLATION OF OLEFIN OLIGOMERS ~ HJ
2321
99
2
ISOPENTANE/ DISTILLATION rROM CA/C5 HYOROCARBON MIX
2330
01
A
1
ISOPHORONF/CATALYTIC OAS PHASE RXN OF ACETONE
2340
99
c
1
ISOPHTMALIC ACIO/ OXIOATION OF MปXYLENF
2350
02
15
2
ISOPRFNE/EXTRACTIWE DIST C5 PYROLYZATE
-------
FREQUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS
PPCODE
OEN_COOE
2360.01
12
2360*02
M
2360-0}
12
2370-99
0
2415-99
3
2*20-00
12
2*30-01
C
2*30-02
C
2**1-01
A
2**2-99
3
2**3-01
01
2*50-01
A
2*45-99
ft
2*60-01
IB
2*70-02
0
2*70-03
0
2*70-0*
0
2*70-09
0
2*70-06
0
2*70-07
0
2*70-08
0
2500-01
0
2500-02
0
2500-03
F1
2500-0*
Fl
2300-06
F
2500-07
Dl
2300-09
C
2500-10
I
2330-00
6
2330-01
K
25*5-01
P
2355-01
1*
2360-00
16
2360-01
P
2360-03
B
2560-03
C
2620-01
B
2620-02
B
2620-03
C
2630-01
A
2631-00
A
2633-01
V
OIR ZERO UNK PRETEXT
3 1 . ISOPฎOPANOL/HYORATIONS OF PROPYLENE
ISOPROPANOL/CATaLYTIC MYOROOENATION OF ACETONE
ISOPROPANOL/SOLVENT-WATER AZEOTROP1C OISTILLATION
ISOPROPyL ACETATE/ISOPROPANOL ~ ACETIC ANWyORJOE
LEAOITOTaD/PROCESS UNOER REVIEW
halic acio/ hydration of maleic acid
MALEIC ANhyoRIOE/RENZCNE OXIDATION
-AtEIC ANHYDRIOE/BY-PRoOUCT OF PHTHALIC anhyorioe by oil
HELAMINE/TRIMERI7ATION OF urea
mELA"INE CRYSTAL/ CONDENSATION OF UREA
MELAMINE RESTNS/POLYCONOFNSATION of MELAMINE HUM formal
MESITYL OHIDE/OEHYnRATION OF DIACETONE ALCOHOL
METANILIC ACID/ HYDROOEnATION OF 3-nITROBEnZENE SULFONIC ACIO
MCTHACRYLIC ACID/ACETONE CYANOHYORIN PROCESS
NtTHACRYLIC ACID ESTERS/BUTYLMCTMACRYLATES-ESTERIFIC OFM
METHACRYLIC ACID ESTERS/ETHYL METHACRYLATE งY METHACRT A
METMACRYLIC acid ESTERS/2-ETHYL HEXYL HEThaCRLTE BY Mfa
METHACRYLIC ACID ESTERS/HIOHER METHACRYLATES BY METM ACI
METHACRYLIC ACIO ESTER/2-ACETOACETOIYETML METhacRLTE EปM
METHACRYLIC ACID ESTER/methacRYlIC ACID ESTERIFCTN OF NO
METHACRYLIC ACID ESTERS/BUTYL metmacRyLATE BY ACN I MEOL
WETHANOL/H.P* SYNTHESIS FROM NaT OAS via SYN OAS
mETHAnOL/LซP> SYTHESIS From NAT OAS VIA SYN OAS
METHANOL/HYOROOENATION OF CARBON MONOXIDE
methAnOL/hYOROOE^ATION OF BUTYNfOlOL
METMANOL/CATALYTIC HYDROOENATION OF ALDEHYDES
-ethanol/by product polyester
METHANOL/BUTANE OXIDATION
METMAMOL/RY.PRODUCT OF ALKYLOLAMJOES
METHYLAMINES/ METHANOL * AMMONIA
METHYLAHINES(TOTAL)/CONDENSATION OF METHANOL AND AMMONIA
METhYL BROMiDE/hYDROhALOoENATjON OF meTmANOL
METHYL CELLULOSE/CELLULOSE ~ METHYL CHLORIDE
METHYL C"LORIOE/ PROBABLY USED AS SOLBENT
METHYL CHLORIDE/MYDROCHLORINATION of METHANOL
methyl CMLORIDE/CHLORINATION OF methane
methyl CHLORIOE /BYPRODUCT OF ETHYLENE oxide iซbo-oi
methylene CHLORIDE/CHLORINATION of met HVLCMLORIDE IFROM MYDROCHLORINATION of METHANOL)
methylene CHLORIDE/CHLORINATION OF methane
methylene CHLORIOE/ BY-PROOUCT ETHYEnE OXIDE 1980-61
METHYLENE OIANILINE/REACTION OF formaloehype aniline
*,ซi.meThvlENEDIANILINE/ (MOD aniline ~ FORMaldf.hYoE
METHYLENE OIPHENYL DIISOCYANATE/PMOSOENATION of MOA
-------
frequency of occurrence for each proouct process
10
PP.CODE
OEN.COOE
D|R
ZERO
UNK
pp_Te*T
2640*01
J1
2
METHYL ETHYl KtTONE/DEMYOPOGENATION 0P SECaBUTANOL
2640*06
C
2
METHYL ETHYl KET0NE/RY"P*00UCT Or HUTANE OXIDATION
2640*07
Jl
1
methyl ethyl ketone/redo*ปof acrolein ft scoautanol
2640*08
J1
1
METHYL ethyl KETONE/ OEhYOPOOENATlON Or SEC-RUTANOL
2645*99
0
1
METHYL rOBMATE/ rOPMALDEMYOE ~ CAUSTIC (CANNIZaPO)
2650*99
*
1
METHYL ISOBUTYL CARBInOL / ALDOL CINOENSATION OF ACETONE
2660*01
Ft
METHYL XSOPUTYL KETONE/NYOPOGENATION or MESITYL OXIOE
2665*02
0
METHYL METMACPYLATE/mEThANOLTSIS or ACETONE CVANOHYDPIN
2665*03
0
t
#
METHYL METmACPYLaTE/meTmaCPYLIC ACI0 ~ METHANOL
2665*04
M
METHYL METhACPYLATE/POLVMEP CROCKING 1
2680*01
0
METHYL SALICYLATE/ESTEPTPICATION or SALICYLIC ACID
2690*01
c
#
A-mETMyLSTyPENE/RV-PROD Or ACETONEftPMENOL BY CUMENE OIIO
2690*02
J2
t
ALPHAvMETHYLSTYPENE/nEHYDPOOENATTON Or CUMENE
2691*01
01
MODACRYLIC RCSIN/PESINปP0LYACปYL0NITPILE ft COMONOMEP
2691*07
0
MOOACpYLlC PESIN/PESIN^POLYACPYLONITPILE ft COmONO*eP
2691*11
01
1
MOOACPYLIC PESIN/ri9EPปP0LYACPYL0NlTPILE ft COMONOMEP
2695*99
6
2ป(HOPPHOLINOปTHIO)*AENZOTHIAZOLE/ NOPPHOLNE 2*mEPCAPT0BEN70THIa70LE
2701*01
2
1
NAPHTHALENE/SEPAPATION rPOM COAL tap DISTILLATE
2701-02
2
NAPHTHALENE/DISTILLATION rPOM PYROLYSIS gas
2750*01
1
NEOPENTANOlC ACID/rPOM ISOBUTYLENE VIA OXO PROCESS AND OHOATlON
2756*01
K
1
PปNITPOANILINE/AMMONOLYSIS OP PARAปNITROCHLORORENZENE
2757*01
K
1
PปNITP0ANILINE/AMM0N0LYSIS Or PAPAปNlTปOCHLOBORENZENE
2770*01
L
#
nitrobenzene/nitration or benzene
2770*10
4
NITROBENZENE/
2792*00
L
1
tปNlTPOPHฃNOL/ NITRATION OP PHENOL
2792*99
4
tซNITPOPHENOL/PPOCESS UNDER REVIEW
2793*99
L
1
pปnitrophenol ft sonjum salt/ nitpation or phenol
2000*01
I
t
NITrOTOLUENE/NITqATION or TOLUENE
2805*99
C
nปnitposooiphenyla*jNg/ oiphenylamine ~ nitrous oxioe
2824*01
Z
NYLON SAlT/AOIPIC ACID ft MmOAvAQMEOUS SOLUTION
2024*02
z
1
NYLON SALT/ADIPIC ACID ft HMDAซMEThaNOL SOLUTION
2825*00
4
NYLON/
2825*01
01
2
NYLON 6/PESIN by POLYCONDENSATION rROM CAPROLACTAM
2825-02
01
7
1
nylon 6/PIRER BY POLYCONOENSATIOn rROM CAPROLACTAM
2825*03
01
1
nylon 66/RESlN BY POLYCONDEnSATI ON rROM NYlON SALT
2825-04
01
1
nylon 66/ribep by polycondensation rROM nylon salt
2825*05
01
1
i
NYLON 612/PESIN* POLYCONDENSATION rROM hmOA ft ClSOIACIDS
2825*08
01
1
NYLON 6 ft 66 COPOLY/POLYCOND OP NYLON SALT ft CAPROLACTAM
2825*09
01
1
t
NYLON/MISCELLANEOUS NYLON PRODUCTS-RESINS
2825*10
01
NYLON/nYLON rOPMALDEMYDE RESIN
2825*11
01
NYLON COATING SOLUTION/
2825-22
23
1
NYLON 6 rIRER/EKTPUSION
2825*90
23
3
t
nylon/nylon finishing processes
-------
FREQUENCY or OCCURRENCE for EACH PRODUCT PROCESS
11
>
I
PP.CODE
OEn.COOE
OIR
2031
01
0
4
2631
02
0
2031
05
0
2031
07
0
1
2031
00
0
2032
01
H
2041
01
0
1
2043
01
e
1
2043
99
9
ซ
2050
01
A
3
20S3
01
3
2096
01
02
3
20S7
01
c
1
2050
01
0
2
2059
01
0
2
2060
01
0
2062
01
0
2063
01
0
1
2065
01
0
2
206T
01
0
ฆ
2060
01
0
2070
01
0
1
207|
01
0
1
2072
01
0
2073
01
0
1
2074
01
0
1
2075
01
0
1
2076
01
0
1
2077
01
0
1
2070
01
0
1
2079
01
0
1
2000
01
0
t
2003
01
0
2
2004
01
0
2005
01
0
3
2006
01
0
1
2905
01
01
14
2910
02
c
6
2910
03
c
1
2910
05
H
1
2910
00
c
1
2910
09
16
2910
10
16
1
ZERO
24
UNK PP_TE*T
0*0 AL0EHV0ES.4LC0H0LS/MI5C AuOeHVOES
0*0 ALDE"Y0ESซ*LC0M0LS/*MVL ALCOHOL
0*0 AL0EHV0FSปA|.C0M0LS/C11-C1A ALC FROM C10-C-C13 OLEFIN
0*0 ALOEHvOES/ALCOMOLS/NFOPENjANOL from ISORUTVLENC
0*0 ALOEMVOES-4LCOMOLS/AMYL aldehydeIm1*En>
OCTANE/RT* SOLVENT EXTRACTION ANO ADSORPTION
PENTAChLOROBENZENE/BVซPROnUCT OF RENZENE CHLORINaTION
PENTACHLOPOPMENOL/CHLORINATION of phenol
PENTACMLOROPHENOL/ CHLORINATION of PMJNOL
PE^TacRVThRITOL/ALOOL C0N0.0F ACETALOEhVOE i FORMALOtHVO
PENTANE/REFINCPY BVwPROOUCT
PETROLEUM MYOPOCAR0ON RESINS/FROM C9-C0 UNSATURATES
PERACETIC ACIO/PEPO*IOATION or ACFTALDEHYDE
PHTHALIC ESTER/PMTMALIC ACIO AKO ALCOHOL ESTCRIFICATION
RIS 2-EThYLhEXYL PhTMALATF ESTfB/2960 ซ ALCOHOL ESTERirI
RUTYLOCTYL PHTHALATE ESTEP/2960 t ALCOHOL ESTERIFICATION
C7ปC10 PHTHALATF ESTER/2960 ANO ALCOHOL ESTERIFICATION
Cll-CM PHTHALATE ESTER/2960 K ALCOHOL ESTERIFICATION
OIRUTyL PHTHALATE ESTER/2960 ALCOHOL ESTERirICATION
OI-OEC*L PHTHALATE ESTER/2960 ANO ALCOHOL ESTERIFICATION
DI-N.hEXYL PHTHALATE FSTEP/2960 AND ALCOHOL ESTEQIFICATI
OT*ISOOECYL PHTHALATE ESTER/2960 d ALCOHOL ESTERIFICAT10
OI-ISOOCTYL PHTHALATE ESTER/2960 K ALCOHOL ESTERIFICAT10
OIPHENyL PHTHALATE ESTER/PHENOHPhthalyL CHLORIDE ESTEปI
DI-TRIDECYL PHTHALATE ESTFR/2960 I ALCOHOL ESTEPIFICATIO
N-HEPTYLNONYLUNOECYL PHTHALATE ESTER/2960 I ALCOHOL ESTE
N-MEXYL-2ปETHYLHE*YLIS00ECYL PHTHALATE ESTER/2960 1 ALCO
NซHE*YLป2"ETHY|.ME*YL PHATHALATE/2960 H ALCOHOL ESTERIFIC
N.hexyLHEPTyLNOnyLUNOECYL PHTHALATE ESTER/2960 & ALCOHOL
N-HEXVLOCTYLOfCYL PHTHALATE ESTfR/2960 6 ALCOHOL ESTERir
MIXED ALCOHOL PHTHALATE ESTER/2960 A, ALCOHOL ESTERFICATI
OCTYLDECYL PhThaLATe FSTER/2960 t ALCOHOL ESTERiriCATION
OI-ETHYL PHTHALATE ESTfP/2960 AND ALCOHOL ESTERIFICATION
DI-N.OCTYL PHTHALATE FSTER/2960 AND ALCOHOL ESTERirICATI
DIMETHYL PHTHALATE ESTFR/2960 AND ALCOHOL ESTERIFICATION
0UTYLRENJYL PHTIHALATE ESTER/2960 ~ 0UTANOL ~ BENZYL ICORIOE
phenolic rcsins/polycondensation of phenol with formaldehyde
PHENOL/CUMENE PEROXIDATION AND ACIO CLEAVAGE
PHENOL/OKIOATION OF TOLUENE
PMENOL/BENZFNE SULrONATI0NซhY0R0Lysis
PHENOL/LIQUID PHASE OXIDATION Or BENZOIC ACID
phenol/tar ACIO RECOVERY REriNlNQ
PHENOL/RECOVERY FRO* pyrOLYSIS oasoline
-------
frequency or occurrence ro* each product process
12
ppcooe
QtN_COOC
DIP
ZERO
UWC
PRETEXT
2910
12
4
1
PhEN0L/BY-PIป00UCT op OIPHCNVL oxide
2910
13
I
1
PmENOL/BYปPAOOUCT OP ISOCyANATES ('ROM NjTORENfENE AND DINlTROTOLUfNE
2950
00
3
$
phosgene/ chlorine * carbon monoxtoe
2990
01
m
6
PHOSGENE/CHLORINATIO* of CARBON MONOXIDE
2951
01
0
1
ซ
PHOSPHATE ESTHERS/PHOSPHORUS oxychlorioe AND PHENOL/ALC
2951
02
0
1
t
PHOSPHATE ESTERS /DIPHENYLISOOECYL P0CL3lPHfMOLilSOOEC
2960
01
c
1
pmtmalic anhydride/oxidation or naphthalene
2960
02
c
2
PhThALIC ANMYORlDE/OXtOATlO* Of 0ปXYLE*E
29ซl
01
H
PITCH tar RESIDUE/SEP.PROm COAL tar LIGHT oil oistillate
2990
99
01
1
t
POLYCETaL RESINS/PROCESS under REVIEW
2992
99
02
POLY.ALPHA.mETHYL STYRENE/PROCESS UNDER review
2996
01
01
POLYAMIOES PROM ETHYLENE AMINES AND PATTY ACIDS
2996
02
01
NYLOMS/PROM ADIPIC ACIDvOIETHYLENETRIAHINEvEPICHLOROHYOR
2996
04
01
1
P0LYAHI0ESซALS0 SEE NyLONS/PROM DIBASIC ACI0 AND AMINES
2996
99
01
1
POLYAMI0ES/ OICARBOXYLIC ACIO ~ DIAMINE
3000
99
02
I
POLYBUTENES/ SOLUTION PPYMERIฃATIflN OP BUTYLENES
3004
00
V
1
polycarronates/oeneral
3004
99
V
2
POLYCARBONATES/PROCESS under review
3006
OS
3
POLYESTER/PIBER MELT SPINNING FROM PURCHASED RESIN
3006
20
01
2
POLYESTfR/RESlN BY POLYCONO# PROM 0*T 4 1*4-CYCL0HEXAN0L
3006
21
01
*
POLYESTER/RESIN BY POLYCONO. PROM TPA 1 ETHYLENE GLYCOL
3006
22
01
1
POLVESTER/RESIN by POLYCOWO. pROM PhTHALIC and ANHYDR*
3006
23
01
7
POLVESTER/RESIN BY POLYCONO. PROM DMT 4 ETHYLENE GLYCOL
3006
26
01
1
POLYESTER/RESIN BY P0LYC0N, FROM TPA OR DMT i ETHYLGLYC*
3006
28
01
2
POLYESTER/RESIN BY POLYCON, PROM DMT ANO BUTANEDIOL
3006
29
01
3
POLYESTER/RESIN BY POLYCONO* PROM VARIOUS ACID 4 *LC,
3006
30
01
1
0
POLYESTER/PIBER BY MELT SPINNING PROM OMT and 1#4
3006
31
01
4
POLYESTER/PIBER By MELT SPINNING PROM TPA and ethy qlycl
3006
33
01
10
POLYESTCR/PIBER BY MELT SPINNING PROM OMT ANO EThy GLYCL
3006
3*
01
1
POLYESTER/PIBER BY mElT Spinning PROm TPA OR DMTAEThygly
3006
35
23
4
POLYESTER/PIBER by melt SPINNING PROM PuRCMASEO RESIN
3006
3T
01
1
ROLYESTfB/riBER
3006
40
01
1
POLYESTER/PILH PRO* OMT AnO lป4 CYCLOHEXANE DfMETHANOL
3006
90
3
4
POLYESTER/FINISHING RROCESS
3006
99
01
POLYESTER/
3000
01
02
9
POLYETHYLENE RESINS/SOLUTION POLYMERIZATION(mdPEI
300H
03
02
5
polyethylene RESI^/SUSPENSIDN POLVm(PaRTICLE PORMjjHOPEI
300b
04
02
15
POLYETHYLENE RESINS/HIGH PRESSUปE P0LYHFPIJATI0N (LOPE)
3008
09
02
2
POLYETnyLENC RESINS/GAS PmaSF POLYMfRI7aTION (HOPE)
3008
90
3
I
POLYETHYLENE/PINISHING process
3008
99
02
POLYETMYLFNE/PROCESS UNDER REVIEW
3009
00
02
2
POLYETHYLENE COPOLYMERS/
3010*00
5
1
POLYOXYETHYLENE OLYCOL/ETHOXYLATION OP ETHYLENE glycol
-------
FREQUENCY or OCCURRENCE FOR EACH PRODUCT PROCESS
13
PP.COOC
OCN.CODE
01R
ZERO
unk pp_text
3010-01
5
2
. polyethylene gycol/ ethylene oxide
3011*01
6
2
. POLYETmylene P0LY*ซ1NES/ETHYLENE 01AMJNE ~ EDC ~ NH3
3013-01
01
2
. POLYMERIC methylene OMNIlINE/REACTION op anil 1 PORmAlh
3015-01
*
2
. POLYMERIC methylene 01PHENYL 01ISOCYANATE/FROM POLY METM
3015-02
*
1
. POLYMฃP|C METHYLENE OIPHENYL 01ISOCYANATE/MfTHVLENE DIAN
3015-B0
A
1
POLYMERIC METHYLENE OIPMENyL DIISOCyANATE/RxN OF FORM*AN
3020-01
29
3
, POLYPROPYLENE /FIBER by melt SPJNNINS FROM PURCMAS RESjN
3020-03
02
5
. POLYPROPYLENE/RESIN by SOLUTION POLYMERIZATION
3020-0*
3
, POLYPPOPYLENE/POLYMER EMRUSION
3020-05
02
2
, polypropylene/resin BY SUSPENSION polymerization
3020-06
02
1
, POLYPROPYLENE/GAS PHASE POLYMERIZATION
3020-90
3
ป
, POLYPROPYLENE/FINISHING PROCESS
3025-01
5
*
. POLYOXYPROPYLENE OvCOL/ REACT OF PROPYLENE OYCOL 1 PROPYLENE OXIDE
3025-02
5
2
. POLYOXYPROPYLENE GLYCOL/PซOPOXYLATION OF GLYCERINE
3030-02
01
5
, POLYSTYRENE COPOLYmERS/SUSP POLYMERIZATION ป-0 RUBBER
3030-03
02
6
, POLYSTYRENE I COPOLYMERS/HULK POLYMERIZATION WITH RUBBER
3030-04
02
*
, POLYSTYRFNE ~ COซปOLYMERS/BULK POLYMERIZATION M-O rubber
3030-06
02
POLYSTYRENE AND COPOLYMERS/
3030-90
3
1
. POLYSTYRENE ~ COPOLYMERS/FINISHINO PROCESS
3031-01
02
. POLYSTYRENE.EXPANDED/POLYMERIZATION of POLYSTYRENE
30 33-99
Dl
1
ฆ
. POLYSULFONE RESINS/FROM SODIUM BISPHENOLATE
3036-00
01
1
. POL.YURETMANE PFS1NS/ POLYOLS 01 1SOCYANATE
3036-01
01
17
. P0LYURETH4NE PESINS/ POLYOL ~ Dl]SOCYANATES
3036-02
9
1
ซ POLYURETmANE RESINS/COmPOUNOING
30*0-01
01
2
POLYVINYL ACETATE PES INS/EMULSION POLYMERIZATION
30*0-03
01
1
. POLYVINYL ACEUTE "ESINS/SOLUTION POLYMERIZATION
30*2-01
(
polyvinyl alcohol/hydrolysis of polyvinyl acetate
30*2-0B
01
1
. POLYVINYL ALCOHOL/PESIN-SOLUTION POLYH (METHANOL) OF VJNYL ACETATE, HYDROLYSIS OF POLYMER
30*2-80
D
. POLYVINYL ALCOMOL/RESIN-SOLN POLYMCMEThanolIOf VINYLACET
30*3-01
01
1
POLYVINyLACETATE*ACRyLIC COPOLYmERป/LATEX-EMuLSION POLyK
30**-03
01
. POLYVINYL BUTVRAL/POLYVINYL ACETATE AND BUTYRaLOEHYOE
30**-99
01
1
POLYVINYL BUTYRAL/PROCESS UNDER REVIEW
30*5-01
01
. POLYVINYL ACETATE I PVC COPOLYMERS/SUSPEN POLYMERIZATION
30*5-02
Dl
, POLYVINYL acetate i PVC COPOLYMERS/SOLUTION POlYMERIZATI
30*5-03
01
1
POLYVINYL ACETATE 4 PVC COPOLYMERS/EMULSION POLVmERIZAtI
30*5-0*
01
1
, polyvinyl acetate t PVC C0P0LYMERS/ST4PLE FIBER FROM res
30*7-01
Dl
1
COPOLYMERS OF POLYVINYL ACETATE/EMULSION POLYMERIZATION
30*7-02
01
1
. POLYVINYL ACETATE COPOLYMERS/SOLPOLY wt vin PYROLLIOINON
30*7-03
Dl
1
, COPOLYMERS of polyvinyl ACETATf/COPOLYMER WJTm EThYLENj
30*8-01
02
7
, POLYVINYL CHLORIOE/EMuLSION POLYMERIZATION
30*8-02
D2
16
. POLYVINYL CHLORIOE/SUSPENSION POLYMERIZATION
30*8-0*
02
3
ป
POLYVINYL CHLORIDE/BULK POLYMERIZATION
30*8-11
3
t
. POLYVINYL CHLOHIOE/FRM OR FIBE" BY CALENDERING
-------
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS 14
PP.COOE
OEN_CO0E
OJR
ZERO
UNK
PRETEXT
3040*90
3
4
POLYVINYL CHLORIOE/riNlSHjNO PROCESS
3050-01
0
1
1
$
PROPIONALOEHYOE/HYOROFORMYLATlON OF EThylENE-OXO PROCESS
3052*01
02
1
POLYVINYL CHLORIDE COPOLYMERS/SUSPENSION POLYMERIZATION
3055*99
01
J
POLYVINYL PYRROLIOONE'POLYMERIZATION OF vinyl PYRROLIOONE
30*0*01
02
1
POLYVINYLIOENE CHLORIDE/EMULSION POLYMERIZATION
3060*99
02
1
POLYVJNYLIOENE CMLORIOES/PROCESS UNOE* REVIEW
3063*01
propane/refinery by-product
3063*02
I
2
PROPANE/NATURAL OAS BY-PRODUCT
3063*03
ฆ
PROPANE/BUTANE PYROLYSIS
3066*01
C
1
1
PROPIONIC ACIO/AIR OXIDATION OP PROPIONALDEMVDE
3066*02
c
PROPIONIC ACID/CO*RROOUCT OF BUTANE OXIDATION
3066*04
1
PROPIONIC ACIO/BYซPROOUCT OF NlTPOPARAFFlNS
3068*01
8
1
1
NPROPYL ACETATE/REACTION OF ACETIC ACIO 1 N*PROP*NOL
3070*01
n
2
1
Npropyl ALCOHOL/HYOROOENATION OF PROPIONALOEHYOE*OXO PR
3090*02
H
10
PROPYLENE/PYROLYSlS OF ETMANE/PROPANE/HUTANE/LPO
3090*06
M
5
1
PROPYLENE/PYROLYSIS OF naphtha and OR OAS OIL
3090*00
2
1
PROPYLENE/FRACTIONATION OF REFINERY LlซMT ENDS
3090*11
H
2
PROPYLENE/*YROLYSIS OF NAPhTmaปPR0PanE.ETHANEป8UTaNE
3100*01
20
1
PROPYLENE CHlOROHYDRIn/INTERmEOIATE IN CHLOROHYDRIN PROC
3110*01
20
1
PROPYLENE OICMLORIOE/CHLOROHydRINATION of ALLYL CHLORIDE
3110*02
20
1
PROPYLENE OICMLORIOE/BY-POCT OF PROPY OXIOE BY CHLOROHYO
3111*01
E
3
ฆ
PROPYLENE OLYCOL/MYOROLYSIS of PROPYLENE OXIOE
3120*02
R
3
PROPYLENE OXIDE/FROM PROPYLENE VIA CHLOROHVORIN
3135*01
1
PYROLYSIS OASOLINE/CRACKINO ETHANEปPROpANE(BUTANE ปLPQ
3135*03
H
1
PyROLYSlS OASOLINE/CRACKINO ETHANE/PROPANE/BUTANC and na
3145*01
E
5
RaYON/VISCOSF PROCESS
3170*01
A
SALICYLIC ACIO/CARBoxYlATIon of ory sodium PHEnATE
3170*99
c
1
SALICYLIC ACIO/CARBONOIYLATION OF PMENOLATE
3172*01
01
4
San PESIN/SUSPENSION POLYMERIZATION
3172*02
01
1
1
SAN RESIN/MASS POLYMERIZATION
3175*01
3
SILICONES/SILICONE MONOMERS(CHLOROSILANES1 CMLORINATION of SILICON DIOXIDE
3175*02
E
4
SILICONES/SILICONE FLUIDS (HYDROLYSIS Aluft CYCLIZATION)
3175*03
E
1
1
SILICONES/SILICONE RESINS
3175*04
E
4
silicones/ silicone RUrbERS
3175*05
E
SILICONES/ELASTOMER PRODUCTION
3175*06
E
2
SILICONES/ SILICONE SPECIALTIES (OREaSEiOISPERSION AOENT
3101*01
Z
1
SOOIUh BFNZOATE/NEUTRALIZATION OF BENZOIC ACID
3200-99
3
SODIUM F0RM4TE/ FORMIC ACID ~ CAUSTIC
3230*01
J2
7
STYRCNE/OEMYnROOENATION OF EThYLBENZENE
3230-02
2
1
STYPFnE/SEPARATION FROM PYROLSIS GASOLINE
3235*01
02
5
1
STYRENE-HUTADIENE RESIN/ EMULSION PROCESS
3236-01
01
1
STYPENE malEIC ANHYORIDE RESINS/COPOLYMERIZATION OF STYRENfcMAL.ANH.
3237*01
02
1
STYRENE-METHVL METhACRYLATE COPOLYMERS/SUSPENSION PROCES
-------
PP.CODE
OEN.CODE
01
3251-01
M
3260-99
16
i
3280-01
C
6
3260-03
E
1
3286-01
B
1
3287-01
1
3288-01
R
1
3291-01
1
3295-01
3295-02
R
%
3295-0*
B
2
3300-01
B
1
3307-01
6
3310-01
t2
4
3312-01
P
i
3315-99
F1
i
3325-01
5
i
3325-02
5
3338-01
It
3
3349-00
H
1
3349-01
e
3
3349-02
Z
3349-04
J2
4
3349-07
2
6
3350-01
F2
4
3351-01
'2
1
3354-01
V
3
3355-01
V
4
3360-99
6
3380-99
M
33B1-01
F2
1
3390-01
1
3392-01
B
1
3393-00
4
3393-01
1
3393-02
R
3394-01
n
1
3395-01
1
3395-03
1
3395-04
p
1
3400-01 ฆ
2
3400-02
n
3400-03
p
FREQUENCY
ZEffO UNK
or OCCURRENCE for EACH product process
PP_TE*T
SULF4NJLIC ACIO/SULFON*TJON OF ANILINE
SULFOL*NE/ butane SULFUR
TEREPMTHALIC *CID/C*T*LVTIC OXIDATION OF p-XYLENE
TEREPHTMALIC ACID/MVOROLVSIS OF DIMETHYL TtREpMTMAL*TE
1234-TETRACHlOROBEnZEnE/BY-PRODUCT BENZENE CHLORINATION
l?*5*TETRACHLORO0EN7ENE/ev-PROOUCT BEN/ENE CHLORINATION
U35ปTfTRACML0ป0BEN7ENE/B*-PR00UCT BENZENE CMLORINATION
lปlป2.2-TETRACHLOROETHANE/CMLORINATION of ethylene
TeTRaChLOROETMYLENE/ OXYCHLORINATION OF HYDROCARBONS
TETPACHLOROETHYLENE/CHLORINATION of edc t OTHER CHLOR mc
TETRACHLOROETHYLENE/CHLORINATION OF MYOROCARBONS
TeTRAChLOROPmTHซLIC ANMYORIDE/CMLORINATN of PHTHALIC anhydride
TETRAETHVLENE PENTAMINE/ETMYLENE OIAMINE EOC ~ NM3
TETRaEThyl LCAD/ALKYL HALIDE ~ SOOIUM-LEAf) ALLOY
TETRAFLUOROOICHLOROETHANE/HYOPOFLUORIN OF TETRACHLOROCTHYLENE
TETRAHYOROFURAN/ HYDROOENATION of HALEIC ANHYDRIDE
TETRAETHYLENE OLVCOL/COROCT of ETHY GLYCOL from ETHYLENE
TETRAETHVLENE GLYCOL/FROM ETHYLENE OLYCOL STILL BOTTOHS
TETRameTmyl LEAO/ALKYL MALIDE ~ SOOIUH-LEAO alloy
TOLUENE/ STEAM PVROLYSIS OF LPO
TOLUENE/DIST OF BTX EXTRACT-CAT REFORMATS
TOLUENE/DIST, OF BTX EXTRACT-COAL TAR LIOHT OIL
toluene/by-productof styrfne mfo
TOLUENE/OIST OF BTX E*T-PYROLYSIS OaSOLINe
2i4-ToLUENE DIAMINE/CATALYTIC hyOroOENATIoN OF DINITROTOIUENE
TOLUENE DIAMINE *"TRICHLORORENjENE/CHLORINATION OF 1ปA-OICHLOROBENj,
124-TRIChLORORENZfne/RYPROdUcT OF BEN7ENE ChLORINaTION
13S-TRICHLOROBENZENE/RY-PROOUCT OF BENZENE CHLORINATION
111 TRICHLOROEThanE/ CHLORINATION OF ETHYLENE DieHLORO
ltltlซTRICHLOETMANE/CHLOR!NATION of ETHANE
1tli1-TRICmLOROETHANE/MyDROChLORINATION OF WINvL CHLORIDE
1ป1ป2-TRICHLOROETMANE/CHLORINATION of VIN*l CMLORIOE
lซlt2ซTPICHLOROETHANC/CHLORINATION OF ETHYLENE OICHLORIR
ltlt2ปTRICHLOPOETMANE/BYPDCT, OF VINvl CMLORIOE MaNUFACT
-------
FREQUENCY OP OCCURRENCE FOR EACH PRODUCT PROCESS
PP.COOE
OEN^COOE
OIR
ZERO
UNK
PP_TEXT
3410-02
S
TPICHLOROETHYLENE/OXYCHLOPINATION or HYDROCARBONS
3410-03
R
2
TปlC*LOPOfTMVLEfcE/CMLOP.OF EOC AND OTHER CHLORINATED MC
3411-01
P
4
1
TPICMLOPOFLUOPOMETHANE/FLUOPINATION OF CARBON TETPACHLOR
3415-01
R
1
?ป4ป6ซTPICmL0R0PnEN0L/CML0RTN#TI0N or PHENOL
3430-01
P
1
)i)ซ2-TPICHLOROปlt2ซ2*TR!rLUOROFTHANE/COPROO or 3312*01
3460-00
5
1
TRIETHYLENE GLYCOL/ETHYLENE glycol ~ E.o.
34*0-01
5
8
1
TP1ETMYLENE GLYCOL/COPR.OF ETHYLENE GLYCOL FROM ETm 0"0ป
3460-02
E
tpietmylene glycol/coproo or hydrolysisปetmylene oxide
3460-03
5
1
TPJfTMYLENE OLVcOL/rROM ETHYLENE GLYCOL STILL BOTTOMS
34 79-01
K
1
a
TRIETMYLC*ETETRAM1NE/AmINATI0N or ETHYLENE OICHLOPIOE
3477-01
P
1
TPirLUOPODlCHLOPOETHANE/HYOROFLUOPINAT or TETRACHLOROETHYLE*E
3487-01
5
1
TP1PPOPYLENE OLYCOL/PXN or PROPY OLVCOL ~ PROPY OXIOE
3488-00
1
2i2f4-TPI*RTHYLปlO*PENTANEDI0L/ alool CONDENSATION I$0*UTyRALOEHYOE
3500-99
3
UPEA/ NH3 ~ C02
3501-00
0
UNSATURATED POLYESTER RESINS/
3501-01
01
3
12
UNSATURATED POLYESTER RESIN/REACT MALEIC/PHTHALIC/GLYCOL
3503-99
m
1
URETHANE PPEPOLYmERS/PROCESS under REVIEM
3506-00
02
UREA PES INS/GENERAL
3506-01
01
13
22
UPEA PESINS/POLVCONOENSATION OF UREA WITH FORMALDEHYDE
3510-01
0
1
1
VINYL ACETATE/LIQUID PHASE ETHYLENE 1 ACETIC ACID
3510-03
13
1
VINYL ACETATE/ACETYLENE ~ ACETIC ACID
3510-05
0
1
VINYL ACETATE/VAPOR PHASE PX Or fTHYLENE ft. ACETIC ACID
3520-03
R
6
1
vinyl chloride/thermal cracking or ethylene oichloride
3520-80
R
2
VINYL CHLOPlDE/rROH ETHYLENE via EOC ซY ChLORปOXY CHLOR
3530-02
R
2
VINYLIOENE CHLORIOE/OEHYOPOCHLORซ OF TRICHLOPOETHANE
3540-01
02
t
1
t
VINYL TOLUENE/POLYMERIZATION
3541.01
17
2
XYLENESปHlXED/BOTTOM BTX EXT*PYPOLVSIS GASOLINE
3541-03
17
2
XYLCNEStMIXEO/tiOTTOM BTX EXTRACT-CAT RErORHATE
3541-04
H
XYLENESปmiXEO/BOTTOM BTX EXTRACTซCOAL TAP LIGHT OIL
3541-08
17
1
XYLENEStNlXEO/MfPfซXYLENES^BOTTON$ XYLENE SEPARATION
3541-09
7
ง
XYLENESปMlXED/CPUDE PปXYLENE BY ISOHERIZATION or C89S
3550-02
m.xylene tIMPURE)/fractionation or hiked xylenes
3560-01
2
3
a
O.XYLCNE/DISTILLATION from MIXED XYLENE
3570-01
17
1
P^XVLENE/CRYSTALIZATION EPOM MIXED XYLENE
3570-02
17
2
P-KYLENE/ISOMEPIZAT-CPYSTALLIZAT or MIKED XYLENES
3570-05
2
2
ง
MIXEO XYLENES/ FROM BTX EXTRACT
3580-01
H
XYLENOL#MIXED/TAR AC10 RECOVERY AND REFINING
3587-00
M
1
XYLENESULFONIC ACIOt SODIUM SALT/
3587.99
M
2
XYLENESULFONIC ACIOf SOOIUM salt/ fULFONATION OF XYLENE
3600-99
3
ZINC(T0TAL)/PP0CESS UNOEP REVIEW
9601-00
3
ammonium chloride/
9601-01
3
ammonium BICARBONATE/
9603-00
M
1
CVCLOHEXYL MERCAPTan/ OOOECENCNE ~ H2S
-------
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS
1?
>
i
PP.CODE
OEN_CODE
9604*00
01
9604*0|
16
9608-00
M
9608>01
M
9612-00
M
9619*00
1
9616-00
01
9616-01
3
9619-00
3
9619-01
3
9619-02
3
9619-03
3
9619-04
E
9619-OS
3
9626-00
4
9801-01
H
9801-02
3
9001-04
H
9801-0$
DI
9801-06
0
9B01ซ09
16
9801-11
6
9801-12
3
9801-13
I
9801-14
6
9001-14
6
9801-1*
01
9801-18
s
9801-19
6
9801-21
I
9B01-23
H
9801-24
H
9801-25
6
9801-26
I
9801-2T
3
OJR ZERO UNK PRETEXT
oh - 501 rayon qrade/
2ป4-0ImETHYL PHENOL/ EXTRACTION) DISTILLATION OP REFINERY SPENT CRESYLATES
n-mmaoECYL MERCAPTAN/ OLEFIN ซH?S
n-he*YL mercaPTan/ OLEFIN ~ M|5
0ซLIป0NENE OIMERCAPTAN/ OLEFIN H?S
p-tert-octyl phenol/
POLVAhJDE RESINS/
PHOSPHORIC ACID/
sodium nitrate/
SOniUM BICARBONATE/
SODIUM MVOROSULFIDE/
SODIUM SULFIDE/
SOOIUM SULFATE/RECOVERY AS PART OF VISCOSE PROCESS
SODIUM TETRASULFJOE/
ZEREMBA/
ACETYIENICS/ steam pyrolysis
AOPICULTURe CHEMICALS/
aromatic concentrate/ steam ptrolysis of crude oil cuts* or lpo
ACRYLAMJOE RESINS/
OlycolS* MIXED/ OLEFIN 0LI00MERS ~ 0>0* HVDROOENATJON
aromatic SOLVENTS/ 8TX EXTRACTION FROM PYROLYSIS GASOLINE
ANTIOXIDANTS/
ASRHALT/REFINERy PRODUCT
ALIPHATIC SOLVENTS/ DISTILLATION FROM PYROLYSIS BaSOLINe
ACCELERATORS(TRAOE NAME)/ MERCAPTOBENJOTMIAZOLES
ANTI0Z0NANTS/
ACFTAL RFSIn (CElCON)/
MISCELLANEOUS ALKOXYLATES/
MISCELLANEOUS AMJDES/ FATTY ACIDS *L*ANOLAMJNES
ANT I KNOCK BLENDS/ LEAn ALKyLSt ETHYLENE OICHLORIOE
aR0MซTIc TaR/ STEAM PYROLYSIS RESIoUaLS
AROMATIC oistillates/ btx
amines /methanol nhj
ALUMINUM ALRYLS/ OLEFIN ALUMINUM hyorooen
ADHESIVES/
-------
FREQUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS
18
PPcoot
OEN.CODE
OIP ZERO U*K PP.TEXT
9(101
29
F2
. 1 MISC. ALKAMCS/
9801
30
1 * ALK6NYL succinic ANHYDRIDES/
9001
31
9
. ALKATEROE(TRAOE NAMF)/ ETHOXVLATION of ALKYL PHENOL
9801
34
A
t amantadine hydrochloride/
9B01
ป
D1
t 1 . ALKVO HOLOINO COMPOUND (TRADE NAME)/
9801
36
4
ALPHA 84] PRODUCTS (TPADE NAME)/
9801
*0
A
1 A"1*0 ALCOHOLS/ ALDOL CONDENSATION Of NJTROPARAFFINS UJTH FORMALDEHYDE REDUCTION
9801
42
3
. 1 . ACRVLONITR1LC CATALYST/ BISMUTH PHOSPHOMOLYBDATE. SB.U20T.SILICA OEL
9801
*3
6
1 ALKYLOLAMIDES/ FATTY ACIDS * ALKANOLAMINES
9801
4T
3
. ANTIBIOTICS/
9801
48
01
f ACETONE FORMALDEHYDE resins/
9801
*9
4
. . . A00IT| 3 > ISOXAZOLIOINONE)
-------
FREQUENCY OF OCCURRENCE FOR E*CH PROOUCT PROCESS 19
PP.COOE
GEN_CODE
01R
ZERO
UNK
PRETEXT
9809
19
6
CHOLINE BICARBONATE/ CHOLINE * SOOIUM BICARBONATE
9009
22
B
cmlorin*ted ***/
9803
25
3
COtTINOS/
9803
26
3
C*LCIUM PROPIONATE/
9009
tr
A
CHELATINO AGENTS/ EOT* ฆ ETHVLENFOIAMJNC ~ FORMALDEHYDE NซCN
9803
28
K
cleaning compounds/ vegetable oil sulfonates! ethokvlatesi ouats
9803
39
F1
CROTON OIL ALCOHOL/ hyOROGENAT ION OF CROTONALOEHvDE
9803
*2
15
C-5 UNSATURATES/ FROM PYปOLYZaTฃ 0Y EXTRACTIVE OISTjULATION
9803
*9
1*
CHFmical COTTON/ CELLULOSE ETHYLENE CHLOROHvORlN
9803
*6
1
corpent/ pentaerytmritol derivative
9803
53
3
coal ASH/
980*
02
6
1
01AM J NO OIPHENYL methane/ aniline FORMALOEHVOE
980*
0*
6
N.N.DIIS0PR0PYL-2 BENZOThiA20LE/OI1SOPROPYL AMjNp ซ ZaMERCAPTOBgNZOTHIAZOLE
980*
06
*
DISTILLATE! LJOHTปN-BUTANE DEHYDRO./RECOV,
980*
08
3
DIESEL FUEL/
980*
10
3
1
DIURON(TRADE NAME)/
980*
12
K
1
OIMETHYLACETAMJOE/ OIMETHYLAMJNE acetjc ACIO
980*
1J
A
DImer acids/ From pine ROSIN
lo
980*
1*
6
DIAMINES/
ฆL
9804
15
1
DIETHYL aniline/ ANILINE ~ ETHANOL ~ H2S0*
m
980*
17
*
1
OACA/
980*
19
19
DIATRIZOIC ACID/
980*
20
1
DIETHYL maLOnaTE/ ETHANOL ester of malonic ACIO
980*
21
1
DIMETHYL MALONATE/ METHANOL FSTER OF MALONIC ACIO
900*
22
12
OENATUREO ALCOHOL/
980*
2*
1
t
DYEING ASSISTANTS/ POLYESTERS
980*
25
K
1
DETEROENTS AND SCOURS/ VEGETABLE OIL SULFONATES, ETHOIYLATM, OUATS
980*
27
01
ฆ
1
01ALLYLPHTHALATE HOLOING COMPOUND/
900*
29
M
1
N.nECYL MERCAPTAN/ OLEFIN ~ M?S
980*
30
M
1
NซTRIปDECYL mercaPTan/ OLEFIN HIS
980*
31
2*
DISODIUMETHYLENEOlAMINETETRAACETATE/ NEUTRALIZATION OF EOTA
900*
36
M
1
DirHLOปOOIPHENYL 8ULF0NE/803 ซTHI0NYL CL ~ CMLOROBENZENE
980*
*7
9
1
OIMETHYLRENZYL ALCOHOL/ ACIO CLEAVAOE OF CUMENE HYDROPEROXIDE
900*
*0
01
1
OICYANOOIAMINE RESIN/
980*
*9
M
OODECYLBENZENE SULFONIC ACIO SALTS/ IULFONaTION OF DOOEC*IBENZENE
940*
52
OI0UTYLPHENVL PHOSPHATE/ BUTANOL ~ PHENOL POCL3
9P0*
59
6
t
?ซ6ซDIETHYL-Nป(METH0XYMETMYL)-2-CML0R0AceTANILI0F/
900*
5*
6
2ซ6wDIETHYLPHENYL AZOMETHANE/
980*
57
1
DINONENE/ FROM TERPINENE By OEALKyLATION
980*
50
5
1
OIETmanol ammonium LAURYL SULFATE/ LAUPYLA*INE ~ ETHYLENE OXIOE
9P05
03
6
N*ETHYL ANILINE/ ETHANOL ANILINE
9A05
0*
*
?ปETHYL HEXVL CHLORIDE/
9805
05
6
2
MISCELLANEOUS ESTERS (POSSIBLY AOIPATES) / AOIPtC ACIO ซ 2-ETMYLMEXANOL
-------
fBCouencY or occubbinci ro* each product process
PPjCOOt
OEN.COOe
010
ZERO
UNK
pp^te*t
qซosป08
01
1
E*ST0ซONDS (TRADE fcAMfl/ POYSTYRENES AND CELLULOSICS (ADHESIVE* FOR POLVOLE?INS)
980S-09
2*
1
ETMYLENEOIAHINE D!HVOft0!0O!DC/ HI ~ fTN*LfNEDfAMINf
9805-12
01
1
f
ELAS?0MฃR L**E*/
980ซ>*1*
01
I
emulsion polymers/
980i*l7
M
1
*
ซ
ETHYL "E&CA*TAN/ OLEFIN ~ Hit
9805-18
14
1
OI.ETMVL sulfide/ K ETMYLSULMTE ~ K2S (AO)
9809*19
A
1
ETMVLENEO!A*INETETRAACETIC *CI0/ ETMYLENEOUMJNE ~ EOปNALOEHYOE ~ NACN
980S.22
5
1
NONQETMYL OL*COL ETHER/
980S*29
1*
1
ETHYLENE CYANONYORIN/ acetaloemyde ~ HCN
980Sป31
i
1
ETHYLENE UReA/ ETHYLENE DIAHiNf * CM
980S*36
01
2
ALlCYOtPMENOLlCt POLYESTER. POLYURETNANE RESINS
9606-01
3
2
fuel oaS h* and cha iwroi/
9806-02
*
FUEL ADDITIVES/
9806-03
3
ฆ
t
FLOUR ADDITIVES/
9806-04
e
I
i
FATTY ACIDS 4 DERIVATIVES/ HYDROLYSIS OF OLYCERIOES
90 06-05
0
1
fatty NITRILES/ DEHYDRATION of FATTY AHIOES
9806-06
3
NUMrer 2 FUEL oil/
9806*08
P
1
FREON (GENERAL)/HYDRDFLUORINATION
9806-09
01
t
FLEXTAL/ *L*YD RESINS
9806-11
P
1
ซ
FLU0R0CAR80N BLENDS/ HF * CHLORINATED METHANE
9806*12
3
furazolidone/ reduction of nitrofurantoin
9806-13
4
FL0WC0 FAMjLY/
9806-1*
01
FURFURAL OESIN (INC. FURANJ/
9806*13
01
ฆ
foam resins (POLYURETHANES)
9806-17
01
1
fome-cor/
9806*19
3
I
1
FUNOICIDE AND INSECTICIDE/
9807*61
*
SENfROL 100 EXTRACTION/
9807*02
3
*
OENEBOL 105 FLAKlMl/
980?*04
7
1
OLYCOLONITRILE/ ETHYLENE CHLOROWYORIN ~ NACN
9807-08
3
oasoline/
9887*07
16
1
OASOLINE RLEND STOCK/ FROM PyROLYIATE BY EXTRACTIVE DISTILLATION
9807*08
PI
1
QANTREI AN/ POLYMERIZATION OF VINYL ETNฃR AND ACRYLONlTRlLE
9807*09
0
I
QAfcTRf* ES/ESTERIEICATION PROPAOyL ALCOHOL * ACID
9807-12
02
1
POLYMffl qasoline/by.proouct isoautylenc
9807*13
5
1
OYCOLSrMJSCil/ ALCHOHOL. OLYCOL ~ ETHYLENE OIIOE
9808*02
6
t
HFXAMETMVLENEDIAHINE / 1*6 HEXANEDIOL ~ AHMONIA (NICKLE CAT.)
9808*09
3
1
.
hydbooen sulfide/
9808*08
12
I
HVOROIYACCTIC ACID/ CMLOROACETIC ACIO ~ CAUSTIC
9808*09
02
1
HYPOLOMTRAOE NAHEi/ CMLOROSULFONATEO POLYETHYLENE RUBBER
9808-10
02
1
MYDAN (TRADE NAME)/
9ซnซ-H
e
MYO*OLYZEO VEGETABLE PROTEIN/
9808-12
3
HLป/
9808-16
0
HY0R0IY STEARIC ACID AND DERIVATIVES/
-------
FREQUENCY OF OCCURRENCE FOR EACH PBOOUCT PROCESS
21
PP.COOE OEN..COOE OJR ZERO UNK PP_TEXT
9000
17
3
9808
IS
3
9809
28
H
9908
31
M
9809
01
A
9809
03
Dl
9809
0*
3
9809
07
0
9809
U
V
9809
19
F1
9610
01
3
9811
01
8
9811
02
3
9811
03
Dl
9811
0*
01
9812
0*
01
9812
OS
3
9812
07
3
9812
oe
3
1
ro
9812
09
A
1
9812
10
3
981?
12
B
9812
13
B
9812
14
a
9812
19
3
9812
16
01
9813
01
10
9813
02
0
9813
04
24
9813
OS
24
9813
06
A
9813
07
12
9813
08
3
9813
09
2
9813
10
3
9813
11
3
9813
12
A
9813
13
3
9813
14
3
9813
16
01
9813
20
Dl
9813
22
0
9813
23
14
myoROXYLAMmonjum ACIO SULFATE/
hydroxylahmonium sulfate/
LIOHT HYDROCARBONS/
MVnROTPOPf/ SULF0N4TJON OF ALKYL BENZENES (ALKYbMETMYi |TMYLJS0PR0P*L>
ISOPNOPYL ETHYTHIONO CARBAMATE/ ALPHA.METHYL PROPJONANIOE ~ SOniUM ETHVLNfRCATIOE
ton exchange resins (probably acrylic resins)
ISOMERASE/
ISOPHTHALATE ESTER/ESTERIFICATION
MISCELLANEOUS TSOCYANATES/ PhOSOFNTATION of ANILINE'FORMALOEHVDC OERIV.
ISOBUTVRONITRILE/ FROM ALPHAaMETHACRYLONITRILE BV MYDROQENATION
JET FUEL JP-4/
KETONE PEROXIDE (OIACETONE ALCOHOL PEROXIOE) / PEROXIDATION OF 01 ACETONE ALCOHOL
KEROSENE/
KETONE RESINS/
KEVLAP IARAHIO PEtIN ANO FIBER)/ISOPHTHALOYL CHLORIDE ~ 1t3*0IANILINE (TYPICAL) AN AROMATIC NYLON
LAMINATING RESINS/ CRESYLIC aCID-PmENOI ป FORMALDEHYDE
LINUP0N(hER8ICI0E)/
LOROX/
LACOHgR(SCNERALI/
LAUROYL SAPCOSINATE (30 PERCENT SODIUM SALT)/ SARCOSINE LAURALOEMYOE
LUBRICANTS / OPOANIC PERIOXioESf PEROXYCARRONaTES* ETC
LUPERSOL (TRADE NAME) / OROANIC PEpIOXIQES. PEROKYCArBONATES. ETC
LUPEBCO (TRADE NAME) / ORGANIC PERlOXIDESt PEROXYCaPBOnaTESt ETC
LUPEROX (TRADE NAME)/
LIOHT OILS/
LaTฃX(UNKNOWN TYPE)/ POLYVINYLACETaTE
METHYLETHYL KETOXIME/METHYLETMYL KETONE ~ HYDROXYLAMINE _(NH20H)?ปM?SO*
MALETC ACIO ESTERS/ESTERIFICATION
?ซmERCAPT0BEnZ0THIA70lE* ZINC SAi T/ ZINC OXIDE 2*mEACAPTBEnZ0THIAZOlE
2 MERCAPTO^ENZOTMlAZOLEt SODIUM SALT/ CAUSTIC * ?ปmeRCซPTRENZOTHIaZOLE
2i2* METhYLENEBIS(6>TปBUTVL>*>EhTVlPhEN0L)/ 4ปETmYL-6*Tป0UTYYLPhENOL FORMALDEHYDE
METHYL FORMCEL/ SOLUTION OF FORMALDEHYDE IN METHANOL
MOTOR GASOLINE/
MIXED C4 COMPOUNDS/ DISTILLATION FROM BTX RAFFINATE
MOTOR MIX 1/
MOTOR MIX/
METHYL MERCAPTAN/ METHYL CHL0RI0E * SOOIOM HYOROSULFIOE
meThOMYL/
MANEB (FUNGICIDE)/
MOLDING COMPOUNOS/ (POLYACRYLIC RESINS)
misc.plastic resins,shapesiChemical/
methyl CYANOACETATf/ methanol ester OF CYANOACETIC acid
methyl ORTmOFORMATE/ CHLOROFORM NAMEThANOLATE
-------
frequency or occurrence eac* proouct process
P
P
?
0
E
N
7
Z
P
P
T
0
0
D
E
u
E
0
0
I
R
N
X
E
E
R
0
K
T
981)
14
6
MOftPHOLINC DERIVATIVES Of NJTPO ALCOHOLS/
9813
25
02
1
miCPOThCNE (POWDERED PLOYETHYLE*E RESIN)
9813
28
2
1
METHANE/ ,
9813
28
0
1
CASTOR OIL DERIVATIVES/ IfSTEM)
9813
29
0
1
trihellitate ESTER/ESTERIF ICAT ION
9813
30
A
1
N-METHYL GLYCINE (SARCOSlNf) / METHYLAMINj ~ FORMALDEHYDE ~ NAC*
9813
31
0
1
MALEANUfO OIL/ OIL ~ MALEIC ANmYqRIOE
9813
39
0
1
i
TEXANOL BENZOATE/ ESTERIFICATION OF BENZOIC ACID
9813
41
a
1
METNOXYETmYL CARBAMATE/ 2*WETh0*YETmAN0L ~ CARBAMOYL CHLORIOE (HCL*UREA)
9813
43
e
MA^EATEO OILS/ mAlEIC ANHDPIDRIOE ~ OILS WITH HYOROXYl. GROUPS
9813
49
6
1
N-METHYL-2-PYRR0LID0NE/ 3ปBUTYROLACTONE ~ METHYLAMINE
9813
46
*
METHYL AMYL ALCOHOL/ ALOOL CONDENSATION OF ACETONE
9813
48
3
1
metallic carbonyls (MISC.)/
9813
49
A
METMYLENEBIS<6-TปHUTYLปPปCRES0L>/
3="
9813
50
A
1
METH0XY DlHYDROPYRAN/
ro
981*
01
A
1
NJTRILOTRIACETaTE/ NM3 ~ FORMALDEHYDE ~ NaC*
ro
981*
02
14
1
naphtha o*10E OILS/ sodium PHENOLATE * CHLORORENZENE
981*
03
A
4ซNITR0-0RTh0ซXYLENE DIETHYL KETONE BLEND/ MI* OP 2 PROOUCTS
981*
08
01
1
PARAFORMALDEHYDE/ POLYMERIZATION OF FORMALDEHYDE (ALGOL CANNIZARO)
9814
or
02
1
NOROEL (TRADE name)/ETHYLENE ซ PROPYLENE COPOLYMERS
9814
08
3
1
NYLON YaR"/PROm PURchaSEO resin
9814
U
I
1
S*NITr0ซ0*T0LUENE SULFONIC ACID/ SULFONATION of TOLUENE* NlTRATtON
9814
13
L
1
t
1*NITR0O*4*D!ChL0R08EnZENE/ NITRATION OF 0*0ICHL0R0flENZENE
9814
IS
D1
1
NAmEX (ARAhID RESlNtFIBER AND SHEET)/ ISOPHTHAlOYL CH0ปI0E ~ 1ป3ป0IAnIl!nE (TYplCAi.) An AROMATIC NYlON
9814
1ป
3
NR0*47/
9814
IT
01
1
t
NYLON/OACRON COSPUN fiber/(OACRON POLYESTER)
9814
18
02
NEOPR^NF/ OปCHL0RD-lV3*BUTADIENE)
9814
19
A
*
NlTRO AND AMINO ALCOHOL/ ALDO CONDENSATION OF NITROPaRaFFINS WITH FORMALDEHYDE
9814
21
3
NITROFURANTOIN/ 1*AMIN0MYDANT0INSULFATE * *0.NITrOFURALDEHyDE DIACET TE
9814
22
V
1
1*NAPhTHYLNปM^THYLCARBAMATESEVIN / METHYL amine ~ PHOSGENE ~ 1ปNAPMTH0L
9814
24
M
1
NONYL MfRCAPTAN/ ALPhAซ*0LEFINS ~ H2S
9814
25
I
NITROPARAFFINS/ NITRATION OF METHANE ETHANE PROPANE (HIOM TEMP9 VAP PHASE)
9814
26
A
NITROALCOHOLS/ ALDOL CONDENSATION OF NITROPARAFFINS wITh FORMALDEHYDE
9814
2T
3
i
NUSOL/EXTRACTION from SULFITE PULP HILL WASTEWATER
9814
28
3
1
NITROGEN FERTILIZER SOLUTIONS/
9814
31
14
PvNITROPHENCTOLE/ P'NITROPhENOLATE ~ ETHYL CHLORIDE
-------
frequency or occurrence for each product process 23
PP.COOE
GEN^COOE
OTR
J Eป0
UNK
PRETEXT
814-32
0
nonylicuhvl phenyl oiphenyl phosphate/ alkyl phenolsป phenol ~ pocl3
9B14-3A
2
SOLVENT nAPmTmA/ distillation FRO1"" COALTAP CONDENSATE
9814-39
L
1
NITROCMLOROBENjENf/ NITRATION OF CHLORORENjenE
9815-01
3
MISC. REFINERY OILS/
9815-02
11
OCTYL*TED OJPHENYLAMINE/ALKYLATION
9815-03
0
ORGANIC PEROKIDE/
9815-00
02
OLEFINS hIIEO/ ETHYLENE OLIGOMERS E
*815-09
01
OXAMAXES/ RESIDUES FROM OXA?OLTQINES PRODUCTION
9815-10
3
OXAZOLIOINES/
9815-12
E
OCTADECADIENOIC ACID Mix/
9815-14
M
1
T-OCTyl meRCAPTan/ alpha-OLEFINS H2S
9815-15
M
1
N-OCTYL MERCAPTAN/ ALPHA^oLEFINS ป H2S
9819-16
*
MISC. OROANICS/
9815-19
c
ORGANIC ACIDS (MlXEOt/ OXIDATION OF PROPIONALDEHYDE CONDENSATES
9815-22
10
OXIMES.MJSC./ CARBONYL CMPO ~ HYDRXYL AMINE
9816-01
01
1
~
POLY "ETHYLENE OIPHfNYL 01iSOCYANATf/(POLYMERIC MDI1
9616-03
02
t
ATACTIC P0LYPR0PYLENE/BYPR0OUCT OF 3020-03
9816-05
0
PfROXY ESTERS JT-bUTYL ESTERS OF PERREN70ICซ PEROCTANOIC# PERACETlC ACIDS
9816-07
6
~
POLYAMINES/
>
9016-00
02
POLYBUTADJENE RESINS/
1
r\3
9016-09
D1
polyrutylene TEREPHTMALATE IP*T>/
CO
9016-11
23
1
POLYESTER YARN/
9816-13
3
PIOMENTeO finishes/
9816-1*
3
1
ฆ
paraffins/
9816-15
D
POLYETHYLENE foam/
9816-16
01
POLYESTER IMIOE
-------
FREQUENCY Or OCCURRENCE FOR EACH PRODUCT PROCESS 24
PP.COOE
OEN.COOC
OIR
2E"0
UNK
PP.TEXT
9616*49
24
1
i
PENTASODIUM DIETHYLCnEDIAMINE PENTAACETATE / COPA CAUSTIC
9816*50
3
PnENOLIC coated papers/
9816*51
3
POLYESTER COATED PAPERS/
9816-54
1
PC**000 OVERLAYS/
9816-56
3
paper GENERAL/
9616-58
5
polvether/ propoxylation or propylene glycol
9816-69
01
1
poly DIEThyLE*E GLYCOL ADIPATE (POLYESTER!
9816-71
5
1
ETMOXYLATEO PซEnOLS/PHENOLS ~ ETHYLENE oxide
9816-72
3
ซ
PENICILLIN/
9816-75
ซ
1
PCASTTCI7ERS (PATHALATESt AOIPATESi SEBACATES) / PhTHALIC ANHYD. ~ ALCOHOL
9816-77
01
POLYVINYL FORMAL/
9816-80
3
PARATHIONS/
9816-83
01
1
POLYETHER POLYOL RESINS/
9816-87
K
1
t
2ซPYRROLIOONE/3ซBUTYROtACTONE ~ NHJ
9816-93
POLYปN (TRADE NAME)/ ORGANO-UREA POLYMER
9816-97
3
polyethylene compounds/compoundINO
9816-98
3
PLASTIC COMPONENT/
9816-99
3
1
plastic battery separators/
9817-01
6
1
QUATERNARY AMINES/ ALKYL CHL0RI0E ~ FATTY AMINE
ฆ>
9818-01
02
1
t
RESIN PR/STILL BOTTOMS FROM STEAM PYROLYSIS OF NaPTHA/ OAS OIL
ro
9818-02
H
1
RESIN OIL l*ROMATIC)/STEAM PYROLYSIS OF OAS OIL
9818-05
M
1
REACTIVE DISTILLATES FROM STREAM CRACKInq/
9818-06
6
*
resins solutions/
9818-07
3
ROSINS and DERIVATIVES/
9818-08
01
1
ROSIN DERIVATIVE RESINS/
9818-09
3
1
PEAOSORBER OFFปOASES/
9818-10
E
RICINOLEIC ACIO/FROm CASTOR OIL BY HYDROLYSIS
9818-11
0
RICINOLEATES and DERIVATIVES/ RICINOLEIC ACID ~ ALCOHOL
9818-14
16
RAFFINATE/ BTX EXTRACT OF COAL TAR COWOENSATE
9818-15
01
ฆ
1
RUBBER RESINS(P0LYURETHANE ELASTOMERS)
9818-16
1
98 1 8-17
01
1
i
RUBBERปCYCLIZC0/
9818-19
01
1
RESINS (GENERAL)/
9819-01
0
1
SURFACTANTS/ SUL'OSUCCINIC ACID ESTERS ฆ SUCCINIC ACIO ~ ALCOHOL SODIUM BISULMTE
9819-02
3
t
SULFAMETHAZINE/ CONDENSATION OF SULFAGUANIDINE AND ACETYLACETONE ~ SODIUM BISULFITE
9819-04
3
1
SOLVENT BLENDSi MISCELLANEOUS/
9819-09
5
1
SODIUM METMYLATE/METHANOL ~ SODIUM
9819-10
01
1
1
SPANOEX FIBERS (85% SEGMENTED POLYURETMANE) / POLYOL ~ D11S0CYANATES
9819-11
M
1
SODIUM LAURYL SULFATE/ SULFONATION OF LAURYL ALCOHOL
9819-14
M
1
t
SODIUM STYRENE SULFONATE/ SULF0n*TION OF STYRENE
9819-15
4
1
specialty lubricants/
9819-17
24
S001UM PROPIONATE/ PROPIONIC ACIO ~ CAUSTrC
9819-18
4
1
2
TEXTILE SOFTENERS/ UREA ซ FORMALOEHYOE ~ GLYOXAL
-------
FREQUENCY OF OCCURRENCE FOR EACH PRQOUCT PROCESS
RP_COOE
eEN_coot
OJR
ZfRO
UNK
PP_TEXT
9819-19
0
MISCELLANEOUS STEARATES/ STEARIC ACTO * ALCOHOL
9019-22
0
SYNTHETIC LUBRICANTS/
9819.26
M
1
fatty ESTER SULFONATES/ SULFONATION OF fatty ACIOf
9819-27
M
1
LAURYL SULFONATES/ SULFONATlON OF OOOCCENE
9919.20
M
1
linear alkylate sulfonate/ sulfonation of alkylbenzenes
9819-35
3
SOLVENT HASE COATING/ ?
9819.36
02
1
SYNTHETIC SPECIALTY P0LYMEPS (POLYSTYRENE)
9819.38
4
'
SOLUTIONS (MISCELLANEOUS*/
9819.39
M
1
SOOIUM LINEAP ALKYL BEN2ENE SULFONATE/ SULFON*TION OF ALKYLBEN7ENE
9819.40
24
SODIUM NITP0PEN2ENESULF0NIC ACID/
9819-42
02
1
STYPOFOAM/ EKTPUDEO EXPANDED POLYSTYRENE
9819.43
3
1
SPECIALITY PAPERS/
9819-45
L
1
SUBSTITUTED PHENOLS(MISC.)/NITRATION
9820-03
C
1
TRIMELLITIC ANHYDRIDE/ OXIDATION Or PSEUOOCUMfNE (1#2ป4ปTPtMETHYL BENZENE)
9820.04
4
1
TRIMFTHYLOLPROPANt/ N BUTYRALOEHYDE ~ FORMALOEMyDE (*LDOL# CANNIZARO)
9820-05
A
1
TRIOXANE/ FORMALDEHYDE TRIMEP
9820.06
3
TETRAHIX (TRAOE NAME)/
9820*07
M
?ป3.St6ปTETRACHL0R0^A-(METMYL SULFONyL) PYRIDINE/
9820.06
M
ZปJ#5ปTRICHLOR0ป4ป
-------
FREQUENCY OF OCCURRENCE FOR E*CM PRODUCT PROCESS
PP_CODE
aEN_COOE
DIR
ZERO
UNK
PP.TEXT
9820
96
01
1
TฃR*TE RESINS/ POLYESTER
9020
57
5
1
TRICTmANOL AMMONIUM lAURYl SULFATE/ LAURYL AMINE ~ ETHYLENE OX IDE
9820
58
H
1
t
TRISODIUM SULFO SUCCINATE/ MALEIC ANHyoRI0E ~ SODIUM BISULFITE
9820
59
5
1
TRICTM4N0LAMINC LINEAR ALKYLBENZENE SULFONATE/ EThOXYLATION
9820
60
8
TAhol 1 TRADE NAME) (POSSIBLY EPOXIOUEO SOYA OILS!
9820
62
F 1
1
1ซ2ซ3t6 TETRAMYDROBENZALDEHVOE/ HyoROOENATION OF BENZALDEHYDE
9821
01
6
URAn (TRADE NAME)/ UREA OERIVATIVE
9821
04
4
URETHANE (MISC)/ ISOCYANATE POLYOL
9822
01
0
I
t
VA7O(A7O0ISISOBUTYปONITRILE)/ metwacrylonitrile ~ HYDRAZINE DEHYOROOENaTION
9822
02
01
VARNISH RESIN (ROSIN AND ROSIN ESTERS)
9822
04
A
VOซMTrS (TRADE name) (URETmane PRfROLYMERS)
9822
07
3
VULCANIZED FIBRE/
9822
08
E
I
VEGETABLE oils-oeneral/
9822
09
3
I
prinTImO Ink varnishes/
9822
11
Q
I
NซwiNtLป2ซPYHR0LID0NE/ 3*BUTYR0LACT0NE ~ ETMaNOLAMINE, DEHYORATION
9822
12
01
I
VpitL^ACPYLIC SHEET/
9823
01
01
MAX EMULSIONS/ FORMULATED FROM CAPTIVE FORMALOEHYOE PHENOL* uREAt ETC RESINS
9823
02
3
I
waTEPrORne COATInq/
9823
03
3
I
woodflour/
9823
05
4
$
1
WATER REPELLENT/
9824
01
I
XANTHATES of C2ปCS ALCOHOLS/ ALCOHOLIC KOm CS2
9825
01
3
SPUN YARN DRV PROCESS/
9886
01
A
I
ZINC ammonium VERSENaTE/ ETHYLENE 01AMINE ~ CMLOROacETIC ACID
9826
02
3
ZERANOL/
9826
04
24
ZINC ijndECYLENaTe/ UNQECYLENIC ACIO ~ ZINCOXIDE
9826
05
24
I
ZINC and calcium stearate/
9826
07
24
I
ZINC DISODIUM ETMYLENEOIAMINC triacetate/
9901
01
3
AmmONIa/
9901
04
3
I
AMMONIUM NITRATE/
9901
05
3
Ammonjum SULFATE/ i.
9901
07
3
ammonia ANHVDROUS/RXN NJtROOEN HVDROSEN
9901
OB
3
aluminum sulfate/
9901
09
X
I
ammonium salts-fatty r-om ether sulfate/
9901
10
3
ALUMINUM FLUORIDE/
9902
02
3
1
RROMINE/
9903
02
3
I
catalyst/
9903
03
3
CHLORINE>CAUSTIC/
9903
05
3
CURIno ArtCNTS/
9903
09
3
CMLOROSULFONIC acid/
9903
11
3
chlorinated ORY bleach/
9903
12
3
4
1
CARBON MONOXIDE/
9903
13
3
2
2
$
CAUSTIC sooa/
9903
14
3
I
CELLULOSE BATTERY separators/
-------
FREQUENCY Of OCCURRENCE TOR EACH PROOUcT PROCESS
PP.COOE OEN_COOE
DIP ZERO ' UNK PPTC*T
I . CALCIUM CMLORIOE/
CALCIU" CARBIDE/
CARBON DJOXIOE/
CALCIUM HYDROXIDE/
DIAmmONIUM PHOSPHATE/
FLUORSPAR/
HYOBOCHLORIC ACID/
HYOPOGEN/
mydROFLOUPIC ACID salts/
HYOPOOEn PEROXIDE/
MY0R09EN SULFIDE/
HYOPOOEN CHLORIDE/
HYOROOEN CYANIDE/
INDUSTRIAL GASES-HYDROOEN NITROOEN/
IODINE/
LUDOX>SILICA/
MIXEO ACIOS (NITRIC 1 SULFURIC)/
MURIATIC ACIO (LOW SHADE MYOROChlORIC ACID)/
NITRIC ACID/
NON-PIOMENTEO PRODUCT/
NITROOEN/
OXYOEN/
PHOSPHOROUS ACID/
POLYSTYRENE (OPS) SHEET/
POTASSIUM ACID PHTHALATE/
PHOSPHOROUS PENTaSULFIDE/
POTASSIUM CARBONATE (POTASH)/"YPROO OF MSO
-------
FREQUENCY OF OCCURRENCE FOR EACH PRODUCT PROCESS
PP.COOE 8EN_C0DE
OtR
ZERO
UNK
PPTEXT
9919*32
9920-01
9923*01
9926-02
SULFUR ANHYDRIDE/
TITANIUM OJOXIOE/
WIRE ANO CARLE/
ZINC SULFATE/
-------
APPENDIX B
BPT STATISTICS
13-i
-------
3PT 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)
_ N
(2) Mean - arithmetic average: X = Z X^/N
i*=l
N
(3) Variance - standard unbiased estimate: S = i I (X- - X)
N - 1 i=l 1
(The standard deviation is S ฆ V S^. )
(A) Minimum - the smallest value in a set of N observations
(5) Maximum - the largest value in a 6et 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 statistic,
C(k). If N is even (N = 2k), the median is
1/2[C(k) + C(k + 1)].
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 Xi, ..., Xfl 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 i x i+1
n i = 1
and
n
S2
L c T^TT ifi (Xt"i+1 ' Xt) '
where t > n.
If the distribution of X is lognormal (so loge(X) is normal with parameters li
and 0^), then the 99th percentile of X is
P99 = gV + 2.326cJ
B-2
-------
The moving estimate of P99 at time t based on the lognorraal model, therefore,
IE
xt ~ 2.326St
P99t - e
2
with Xt and defined above.
Moving estimates of the 99th percentiles, of effluent concentrations were
plotted over tine 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).
GOODNTSS-OF-FIT TESTS
The statistical model used to describe effluent data assumes that y ป 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 BiometriVa 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 lognonnal distri-
bution; the lognormal model would tend to underestimate the 99th percentile
if such alternatives were appropriate.
A significance level of a = 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 testa. 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 nonparaoetric 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)I ฆ $_1[r/(n ~ l)],
where 4>~^(-) 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
N?
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 Che studentized range test (upper tail, a = 0.01) are
u.99
5.06
5.77
6.01
6.27
6.36
6.64
6.84
7.42
N.S. = Not significant (U value below critical level).
Reference: Biometrika Tables for Statisticians, Vol. 1, page 200.
25
50
65
90
100
150
200
500
B-5
-------
BQ[>
lcoe-
PROBABILITY PLOT
FLANT-9
1&6-
10-
1-1
-3
-1
ฆ1 " i ฆ ฆ ฆ
8
PPOBIT
T
4
eor-
1CซSS-
169-
10-
F1CURI B-l. PROBAB1 L1TY PLCT FOR SOD
PR03WILITY PLOT
FIJl.NT-15
ฆ ' ฆ I 1 ' '
e
P30PJ T
-4
71 CURE B-2. PROBABILITY PLOT FOS BOD
B-6
-------
eot.
16S8H
168-
16-
PKOEABlLlTV FLOl
PlAHt-2?
A AC
*ฃr~
tfi"
ฆ" I-' 1 " " " ' ' I- '
-2-1 0 1
PROSIT
ฆ r ฆ ฆ"ฆ'ฆr
2 3
BOD
C'OEH
160-
16-
ntam. b-3. pbobabiiitv plot fob bod
FKOtASlLin FLOT
P1AK7-U
,4 4
-2-10 1
rSOB IT
"T
3
~T
4
ncaRฃ B-4.
PROBABILITY PUTT FOR BOD
-------
PROBABILITY PLOT
SOD
ieou-
100
10"
PLA.VT-45
1 I " ' I
-1 0 I
PROSIT
riCURฃ B-i. PROBABILITY PLOT FOR BOD
BOD
!Gฃ)E>-
160-
16-
PF.OSABILITY PLOT
PLANT-96
I " '
0
F^GBIT
-4
-3
FICJFX B-6. PROBABILITY PLOT FOR BOD
B-8
-------
eop
1 t'OOH
iee-
le-
TRDBABILITY PLOT
PLAKT-110
-2
-4
EdD
)U00-
iaa-
i ฆ
o
FPC'B 1 t
riCUXI B-7. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLAHT-111
16*
*
&
1 -L
T
ฆ1 0 1
fROB IT
FIGURE 1-8. PROBABILITY PLOT FOR BOD
B-9
-------
PROBABILITY PLOT
EOD
lOuO-
PLANT-113
100-
10-
A A
1-L
-3 -2 -I
0
PkoBIT
BOD
!giiJ0-
FICDRI B-9. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLAKT-118
160-
18-
T"
-2
T
T
-i e i
fRDBIT
T
1
FIGURE BJO. PROBABILITY PLOT FOR BOD
B-10
-------
PROBABILITY PLOT
PUIKI-126
BOD
100a-
1G6-
FICURE B-ll. PROBABILITY PLCT FOR BOD
BOD
lCufl-
100-
FR3BAฃlLin FLOT
PLJJiT-170
,4'
s
i. - A
ฆr-. I I , . t-. rri-r, , i . . ( , i T
-4-2-2-1 6 1 2 3 4
PROSIT
F1CIRI B-12. PROBABILITY PLOT FOR BOD
B-ll
-------
PROBABILITY PLOT
plu;t-17J
FICURI B-13. PROBABILITY PLOT FOR BOD
1
FROBABILITV PLOT
PLUtT-220
A
*
A ^
A
y
I I I I I I J..
t -3 -2 -1 a 1 2 3 4
psosrt
nCJRE B-14. PROBABILITY PLOT FOR BOD
B-12
-------
PROBABILITY PLOT
POD
lOuO-
PLANT-234
100-
10-
A-i
A A
ฆn I" "
-3-2-1 0 1 2 3
pfcD&lT
EOP
1OP0-
FIGURI B-15. PROBABILITY PLOT FOR BOD
PROBABILITY PLOT
PLANT- 23 6
100"
10-
it
T*
-2
-1
r""
0
?SOB IT
FIGURE B-16. PROBABILITY PLOT FOX BOD
B-13
-------
probability plot
PLAKT-2B1
EOD
10"
l-l
T
-3 -2-i e i
FftOBIT
FIGURE B-17. PR0BA3IL1TY TLOT FOR BOD
PROBABILITY plot
PLANT" 9
K
A A
L ฃ>
-4
-2
-1
e
PROBIT
F] CURE B-18. PROBABILITY PLOT POR TSS
B-14
-------
PROBABILITY PLOT
TSS
11ซ&0-
100-
10-
PLANT-27
&
H
T
-4
Tr
-2
-1
'
0
PRGEIT
FIGURE B-19. PRQE'ilLm' PLOT FOR TSS
TSS
ieoo={
P30BAJILIT"* PLOT
PLAOT-44
100-
16-
y
T1
T*
-4
-1 0
PROSIT
riami B-20. probabilitj plot for tss
B-15
-------
FRCBABILI TY PLOT
TSS
loeoH
ia-
PI_ANT-45
10OH .Aa A
t.
X"
L
A
I I , i i ... i i i
-4 -i -2-i e l
PROBIT
FIGURE B-21. PROBABILITY PLOT FOR TSS
TSS
1000H
PROBABILITY PLOT
PLANT-96
jee-
1B-
t.
, A A
l-L
"'"I1"
0
PR09IT
FICURI B-22. PROBAฃILir* PLOT FOS TSS
B-16
-------
PROBABILITY PLOT
TSS
1&00-
PLAKT-llO
ซB0-
16-
tfi
A A
4'
T"
-4
r-p
T
-1 0 1
PROSIT
FIGURE B-23. probability plot FOR TSS
PROBABILITY PLOT
TSS.
1606-
PLANT-111
iee-
16-
-2-1 6 1
PROSIT
FIGURE B-24. PROBABILITY PLOT FOR TSS
B-17
-------
PROBABILITY PLOT
PLAKT-I13
A
h
A
A
A
1
-------
PROBABILITY PLOT
TSS
leea-
PLA.VT-220
100-
10-
J ' ฆ "
e
PSOBIT
-1
nCURI B-27. PROBABILITY PLOT FOR TSS
TSJ
1 iDGO-j
PS05ASILITY FLOT
PUlNT-236
1&0-
18"
1-^
-A
-2
i i i ฆ
1 0 1
PPOBJT
FJCITRI B-28. PROBABILITY PLOT FOR TSS
B-19
-------
VARIABILITY FACTORS
Assuming that the distribution of the concentration c is lognormal, then
y = log(c) is normally distributed with mean u and variance o2 (Aitchison
and Brown, pages 8-9). Thus the 99th percentile on the natural log scale is
y0.99 * V + 2.326 o ,
and Che 99th percentile on the concentration scale is
c0.99 s exp(y0<99) c e V 2-326 ฐ ฆ
The mean and variance on the concentration scale are:
V + 1/2 o2
and
_ 2 y + o2 o2
oc = e (e - 1),
Hence, the daily variability factor under the lognormal model is:
c0.99 2.326 a - 1/2 o2
VF( 1) - = e (2)
^c
Estimates of any of the above quantities are calculated by substituting the
mean and variance of natural logs of the observations for p and (J2, 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-6pecific
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 Che first-order autoregressive model
commonly found to be appropriate in water pollution modeling, the mean and
variance of an n-day average were approxiniated by:
VJ ~ 1/2 o2
e (3)
and
o2
fn( p) (4)
n
with
fn( p) - 1 4 P - 2 P (1 ~ p") .
1 ~ p n(l - p)2
It can be seen in (4) that 0^ equals the variance of an average of
n uncorrelated observations, c^/n, times a factor fnCp) 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
V 1
apart is p o* under the first-order autoregressive model. Since
-------
n-1
= [n (J2 + 2 Z (n - k) pk a2]
n2 C k=l C
n-1
- _ [1 I (n - k) p* - 1].
n n k=0
The expression in brackets reduces to fn(p) with the help of the summation
formula for arithmetico-geometric progressions:
n-1 a - [a + (n - l)r]qn rq(l - qn-^)
I (a + kr)qk * + ,
k=0 1 " (1 - q)2
taking a = n, r ฆ -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
cQ 95 ซ= p- + 1.645 o- (5)
and
VF(30) - c0-95/p-
2
- 1 + 1.645[(ec - l)f30(p)/30]1/2 (6)
with p- and o^f defined by equations (3) and (4). Estimates of Cq or
VF(30) are calculated by substituting estimates of y, o2, and p into the
formulas above.
B-22
-------
t
SPEARMAN RANK CORRELATION TECHNIQUE
Let (X^, Y^), CX2,Y2(X^,Yn) be a bivariate random sample of size n.
The rank of X^, RtX^), as compared with the other X values, for i ฆ 1,2 n
is the position of Xj as the X values are ordered from smallest to largest.
Thus, if X^ is the smallest X value, R(X^) = 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 + l)]2
i=l
n(n^ - 1)
12
Based on R the following hypothesis can be tested:
R0: The X^ and Y^ are mutually independent (i.e., their correlation is zero)
: Either (a) theTe 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'e, the above hypothesis becomes a statistical test
for significant subcategorization factors. Throughout this chapter the tern
"null hypothesis" refers to the hypothesis H0: the Xฃ 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
r = L (Xi - X)^
i
- Y)/[ Z (Xฃ - X)2 Z (Yj - Y)2]1/2
1
3
x = A i xi
Y = 1 I
while the nonparametrie 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 (RfX^), R(Y^)). 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, Hj. For ease of interpretation,
Figures B-29 through B-33 show the theoretical lines for a sample size of 50
and Spearman 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 EXA>flPLE OF VARIABLES WITH A NONLINEAR RELATIONSHIP
X Y R(X) R(Y)
1 1 I
10 1.5 2
20 2 3
25 A U
30 10 5
35 50 6
50 70 7
100 90 8
200 95 9
600 100 10
1
2
3
4
5
6
7
8
9
10
B-25
-------
SPUWJU1
BANK CORRELATION (Rl)
N= 50
9-
35-
30-
26
IB'
15
58
5
26
25
30
35
<0
X
FIGURE 8-2S. REGRESSION LIME FOR RANK CORRELATION OF -i
S?EAXMAK
HANK CORRELATION (R = -.5)
N = 56
5-
a-
35-
30
25
IS
25
3B
40
45
SB
18
0
V/
rป
FIGURE B-30. REGRESSION LINE FOR RANK CORRELATION OF -0.5
B-26
-------
SFEAKHUJ
RANK CORRELATION (R-0)
ii=Zi
11 1' ' 1 1 1 i '' ' "I j... I... rr s , ,
16 15 20 25 3D 35 40 45 50
rlG'JKL B-31. REGRESSION LlffE FOR RANK CORRELATION OF 0
SPEAJRKAK
RANK CORRELATION (R=.5)
H=5B
e-
20
e
45
FIGURE B-31. FF.GRI55I0H LIKE FOR RANK CORRELATION OF 0.5
B-27
-------
SFEAXMAN
RANK CORRELATION (R = l)
!i=50
<5
3B-
25-
0-
5-
eH
e
5
10
15
20
25
30
35
53
X
FICUSฃ B-33. REGRESSION LIHE FOR RANK CORRELATION OF 1
B-28
-------
that as R(Y) increases, R(X) increases. It should be noted that the Spearman
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 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 y^(i = l,...,n^) and fcj/i m l,...,n2)
represent the sample observations from the two populations. Then Student's t
statistic is
rank coefficient only indicates a dependent relationship between R(X) and
(7)
where
n = n^ + n2
B-29
-------
is the pooled sample size,
and
n2 i = l
= J_
are Che sample means, and
1 -1 ni _ 9 n2 _ 7
s2 - (n-2) M I (yj - y)2 ซฆ I (Zj_ - z)2]
is the pooled sample variance. The observed value of the t statistic is
compared to tabled critical values of Che t distribution with n-2 degrees of
freedom to determine whether to reject the null hypothesis of equal population
means.
The t cest assumes that the population values are normally distributed
with equal variances. When either of these assumptions fails to hold, conclu-
sions of the test nay 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 co avoid incorrecc conclusions that could be caused
B-30
-------
by failing Co satisfy the assumptions behind the t test, a different test
based on less restrictive assumptions was used.
The Terry-Hoeffding test corresponds cloeely to the two-sample t test,
but it assumes only that observations are drawn randomly from two continuous
population distributions. For large samples, the TerryHoeffding 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 d 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): $-1[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 nonparaaetric 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 ป V n-2 S/
n. n
ฃ1 l E(r,n)2 -
n r-1
1/2
(9)
where S is the sum 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
-------
n-1
nln2
1/2
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 value6 of S to
tabled critical values. Bradley (pages 327-330) gives critical values of S
for pooled sample sizes up to n ฆ 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 plant6 (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
-------
-3
AN
1
2
3
4
5
6
7
e
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
ti
EXAMPLE OF SAMPLE DATA FOR THE TERRY-HOEFFDING TEST
(r) BOD SOURCE* NORMAL SCORE (E(rtn))
150
P
-1.751
170
P
-1.405
190
P
-1.175
210
P
-0.994
230
P
-0.842
250
P
-0.706
270
P
-0.583
320
NP
-0.468
370
NP
-0.358
420
P
-0.253
470
P
-0.151
520
NP
-0.050
550
P
0.050
590
NP
0.151
610
NP
0.253
630
NP
0.358
680
NP
0.468
730
NP
0.583
780
NP
0.706
800
NP
0.842
810
NP
0.994
870
NP
1.175
930
NP
1.405
990
NP
1.751
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 ฆ 0.05 for a two-tailed test, we reject the null hypothesis at this a-
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, N J, 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). Bipnietrika 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.
C-l
-------
APPENDIX D
Rationale for Exclusion of Daily Data Base
Plants From Variability Analysis
J)-I
-------
APPENDIX D
Rationale For Exclusion of Daily Data Base Plants
From Variability Analysis
Plant No. 1: The plant upgraded its treatment 6ystem 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 3 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 rag/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/1).
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 che 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 6tream.
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
actual treatment plant performance
stormwater dilution.
this plant are not representative of
Available effluent data include
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
rag/1) and BOD removal below 953! (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 coated 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.
-------
After the treatment process alternatives to be considered have been sel-
ected and inpuc 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 designs 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 cose data are i.ontainvd 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
mechanis- ) 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), [E-3]
5. Design constants based on a statistical analysis of the mun-
icipal wastewater treatment industry as well as on literature
publications.[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
-------
TABLE E-l-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
0.06
$/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
Ad min/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
coses 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. Foj: a single unit, these costs have a much greater
effect.
E-5
-------
TABLEB-2
CAPDET DEFAULT INFLUENT WASTE
CHARACTERISTICS
TEMPERATURE
SUSPENDED SOLIDS
VOLATILE SOLIDS
SETTLEABLE SOLIDS
bฐd5
SBOD
COD
SCOD
pH
CATIONS
ANIONS
P04
TKN
nh3
no2
no3
OIL AND'GREASE
18 ฐC
200
60
15
250
75
500
400
7.6
160
160
18
45
25
0
0
80
JV1G/L
96 O F SS
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
E-6
-------
TABLE t-3
WASTE CHARACTERISTIC REMOVAL DEFAULT
VALUES POR CAPDET PROCESSES
WASTE CHARACTERISTIC REMOVALS
POll
OIL & Settle
PROCESS DO Dj TSS COD GREASE TKN PIIOS Nll^ SOL1C
Dissolved 30% 80% 30% - 10%
Ai r
Flotation
Clarifica- 32% 58% 40% - 5% 5% -
tion
Activated USER INPUT USER INPUT 1.5 x BOD 0 30% 30% SET
Sludge INFLUENT TOSECODARY Ll-t' EQUAL
AND EFFLUENT CLARIFIEll TO Tl< N
Aerated USER INPUT USER INPUT ASSUME SAM E AS ASL
Lagoon INFLUENT TO SECONDARY
' AND EFFLUENT CLARIFIER
Mul timedia
Fi 1 tra tion
SET EFFLUENT
EQUAL TO
DODSOLUI3LE
INFLUENT
60%
SET EFFLUENT
EQUAL TO
CODSOLU0LE
INFLUENT
PASS ON PASS ON PASS
THROUGH THROUGH THROUGH
-------
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 (mg/1) 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$, 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
removal 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.
-------
M
^ remVAl fNT'-AilifJAL' COSTS: (JO/IE
. a a .e ^ tf a* ^
% %
FLOW (MILLION GAL/DAY)
FIGURE 1DISSOLVED AIR FLOTATION ANNUAL, CAPITAL AND OPERATING COSTS
F-3
-------
FLOW (MILLION GAl/DAY)
2SEDIMENTATION ANNUAL, CAPITAL AND OPERATING COSTS
-------
INFLUENT ซ 85 rrg/l BOD
FLOW (MILLION GAL/DAY)
FIGURES 3ACTIVATED SLDDGE ANNUAL (8Smg/l)
F-5
-------
INFLUENT =ฆ 35 mg/L BOO
o
53^-307 onrf-UQ. ag/l~
FLOW (MILLION GAL/DAY)
FIGURE 4ACTIVATED SLUDGE CAPITAL COSTS (85 mg/0
F-6
-------
INFLUENT = 85 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 5ACTIVATED SLDDGE OPERATING COSTS (85 mg/1)
F-7
-------
INFLUENT ซ 100 rrg/L BOD
ฆeg*
! i i [T1
50y 30r-qnd-l0 ng/L
?
I.
m
T
ซo
ฆ
l m
ฆ
ป
FLOW (MILLION GAL/DAY)
FIGURE 6ACTIVATED SLUDGE ANNUAL COSTS (100 mg/1)
F-a
-------
INFLUENT - 100 mg/L BOO
! K50r30rnnd1.0 ms/L +3
aOW (MILLION GAL/DAY)
FIGURE 7ACTIVATED SLDDGE CAPITAL COSTS (100 mg/1)
F-9
-------
INFLUENT = 100 rcg/l BOD
aOW (MILLION WL/OAY)
FIGURE 8ACTIVATED SLUDGE OPERATING COSTS (100 mg/U
F-10
-------
INFLUENT = 150 mg/L BOD
FLOW (MILLION GAL/DAY)
FIGURE 9ACTIVATED SLDDGE ANNUAL COSTS (150 mg/1)
F-ll
-------
INFLUENT a 150 iป9/l 800
5Q"gnd-30~"ig/L I IT
FLOW (MILLION GAL/QAr)
FIGURE 10ACTIVATED SLUDGE CAPITAL COSTS (150 mg/1)
F-12
-------
INFLUENT - '50 ng/L BOD
' < m Br-Vvv^..V!
FU3W (MILLION GAL/DAY)
FIGURE 11ACTIVATED SLUDGE OPERATING COSTS (150 mg/1)
F-13
-------
INFLUENT - 250 mg/L BOD
f?'ui-"aTpi"
us p j i--=tsj
fOrcnrfSO sg/L
FLOW (MILLION GAL/DAY)
FIGURE 12ACTIVATED SLUDGE ANNUAL COSTS (250 mg/D
F-14
-------
INFLUENT ฆ 250 mg/L BOD
50 ond-^P1"^^
3
a
tx
T ซ
FT.0W (MILLION GAL/DAY)
FIGURE 13ACTIVATED SLUDGE CAPITAL COSTS (250 mg/1)
F-15
-------
INFLUENT = 250 mg/l BOD
O
U
-I
5
T
Z
<
<
>
5
o
p=ric
FLOW (MILLION GAL/DAT)
FIGURE 14ACTIVATED SLUDGE OPERATING COSTS (250 mg/l)
F-16
-------
INFLUENT = 400 mg/L BOD
rro mg/L
aond-iOng/L
rtij
a *
FLOW (MILLION GAL/OAY)
FIGUEE 15
ACTIVATED SLUDGE ANNUAL COSTS (400 mg/1)
F-17
-------
INFLUENT ป 400 irg/L BOD
'-afiir: t.r
j-r mg/Us=
ฆ:-i-u.i.:;;i.ii;:..r:|-. - i ฆi.TiK.k
J L.
FLOW (MILLION GAL/DAY)
i-iGURE 16ACTIVATED SLUDGE CAPITAL COSTS (400 mg/1)
F18
-------
INFLUENT = -WO mg/L BOD
FLOW (MILLION HAL/DAT)
FIGURE 17ACTIVATED SLODGE OPERATING COSTS (400 mg/1)
F-19
-------
INRUENT ป 500 mg/l BOO
F10U (MILLION GAL/DAY)
FIGURE 18ACTIVATED SLUDGE ANNUAL COSTS (500 mg/1)
F-20
-------
INFLUENT - 500 irg/L BOO
KrMiMT.
J. r'--:2"r
FLOW (MILLION SAL/DAY)
FIGURE 19ACTIVATED SLUDGE CAPITAL COSTS (500 mg/1)
F-21
-------
INFLUENT - 500 mg/L SOD
ปt .m J a ป .* . ,*i *
FT.OV (MILLION GAL/DAY)
FIGURE 20ACTIVATED SLUDGE OPERATING COSTS (500 mg/1)
F-22
-------
BOD INFLUENT - 1,000 mg/l
if ปa .ป ^ rป ^ 4 ,ซ , .+ * .7 M * t 9 9 4 # T v
aOW (MILLION GAL/DAY) mq/L
FIGURE 21ACTIVATED SLUDGE ANNUAL COSTS (1000 mg/1)
F - 23
-------
INFLUEMT - 1.000 *g/L BOO
ggggg
- wrrrr i > - -.rj^n "
^{igiec|g#ป6Rage!*fM
ซ t i#
aOW (MILLION GAL/DAr)
FIGURE 22ACTIVATED SLDDGE CAPITAL COSTS (1000 mg/1)
F-24
-------
INFLUENT - 1,000 mg/l BOD
FLOW (MILLION GAL/DAY)
FIGURE 23ACTIVATED SLUDGE OPERATING COSTS (1000 mg/l)
F-25
-------
INFLUENT " 1.500 mg/L BOO
liiiai
v'i :sA
FLOW (MILLION GAL/DAY)
FIGURE 24 ACTIVATED SLUDGE ANNUAL COSTS (1500 mgA)
F-26
-------
INFLUENT - 1500 mg/L BOD
smy.
-*w.
ฆ >ซ4 4 w .em *-t m * J
wป A +
FLOW (MILLION GAL/DAY)
FIGURE 25ACTIVATED SLDDGE CAPITAL COSTS (1500 mg/1)
F-27
-------
INFLUENT - 1500 ng/L BOO
ec
FLOW (MILLION GAL/DAY)
FIGURE 26ACTIVATED SLUDGE OPERATING COSTS (1500 mg/1)
F-28
-------
INFLUENT =ฆ 2000 mg/L BOD
F10W {MILLION GAL/DAV)
FIGURE 27ACTIVATED SLUDGE ANNUAL COSTS (2000 mg/1)
F-29
-------
INFLUENT ป 2000 mg/L BOO
FLOW (MILLION GAL/DAY)
FIGURE 28ACTIVATED SLDDGE CAPITAL COSTS (2000 rng/1)
F-30
-------
influent =ป 2000 mg/L bod
J i_L_U I I I
aOW (MILLION GAl/DAY)
FIGURE 29ACTIVATED SLUDGE OPERATING COSTS (2000 mg/1)
F-31
-------
INFLUENT - 100 mg/L BOD
10ring/L r
FLOW (MILLION GAL/DAY)
FIGURE 30AERATED LAGOONS ANNUAL COSTS (100 mg/l)
F-32
-------
INFLUENT m 100 mg/l BOO
m
FLOW (MILLION GAL/DAY)
FIGURE 31AERATED LAGOONS CAPITAL COSTS (100 mg/l)
F33
-------
INFLUENT - 100 >ng/L SOD
aCW (MILLION GAL/DAY)
FIGURE 32AERATED LAGOONS OPERATING COSTS (100 mg/1)
F-34
-------
INFLUENT = 200 mg/L BOO
.V ^-4*1
U *F"
FLOW [MILLION GAL/DAY)
FIGURE 33
AERATED LAGOONS ANNUAL COSTS (200 mg/ti
F-35
-------
INFLUENT = 200 mg/L 800
ROW (MILLION GAL/OAT)
FIGURE 34AERATED LAGOONS CAPITAL COSTS (200 mg/i)
F-36
-------
INFLUENT * 200mj/L BOD
Z-tT^J
5(t3Dj-nrid ~)0" mg / L
i J : I ' 1 'l I; I
Kp. S.kAjrJIB.J-.'Jiry!
ha vjEป-- I1-.
FLOW (MILLION 1AL/DAY)
FIGURE 35AERATED LAGOONS OPERATING COSTS (200 mg/1)
F-37
-------
INFLUENT ป 500 mg/L BOD
T ฆ
FLOW (MILLION GAL/OAY)
FIGURE 36AERATED LAGOONS ANNUAL COSTS (500 mg/1)
F-38
-------
INFLUENT = 500 rog/L BOD
50"."3Pr~qid=io mg/L
FLOW (MILLION GAL/DAT)
FIGURE 37AERATED LAGOONS CAPITAL COSTS (500 mg/1)
F-39
-------
INFLUENT = 500 mg/L BOD
FLOW {MILLION SAL/DAY)
FIGURE 38AERATED LAGOONS OPERATING COSTS (500 mg/l)
F-40
-------
INFLUENT =* 1000 mg/L BOD
FLOW (MILLION GAL/DAT)
FIGURE 39AERATED LAGOONS ANNUAL COSTS (1000 mg/1)
F-41
-------
INFLUENT =ฆ 1000 ng/L BOD
ROW (MILLION GAL/OAT)
FIGURE 40AERATED LAGOONS CAPITAL COSTS (1000 mg/1)
F-42
-------
INFLUENT-1000 mg/L BOD
aow (MILLION GAL/DAY)
FIGURE 41AERATED LAGOONS OPERATING COSTS (1000 mg/l)
F-43
-------
1ฆ
;,
_,_
i ฆ i i j
1 . ! .1 1
. . .ฆ I ; ! ; 1 1
I 1 - - ฆ ! .-1,-M'H! i l I- ซ u. SI i ' i 1,1 ;.r- ..1 I,
. : 1 -.I" . . . .1 " , II: ~
a a
FLOW {MTLLION GAL/DAT)
FIGURE 42ROTATING BIOLOGICAL CONTACTORS ANNUAL COSTS
F-44
-------
) .t, . 1 . f1 1
M-H r 1; -1 : |. i ' 1 1
1 1 ' 1 i ฆ i i
U ฆ 1 ฆ 1 1 ฆ M 1 1
-III = 1 .'111 !" ! 1 1 ฆ
1 I . < 1 1 | ' i | -| - 1 i 1 ! I l . I '
tm "ju "ฆ 1, -u IJ ฆ ฆ 1 ' ''ฆ-I 'M "ll f >*' ป:'ฆ 11 ฆฆ -FM -"-W",
ปฃ. m . * " .'ij '
-3=^1 =i^rti=v jy
*
f i * I.
4 T I lO
aow (MILLION &AL/DAT)
FIGURE 43ROTATING BIOLOGICAL CONTACTORS CAPITAL COSTS
F-45
-------
9 <0
R.CV(MrLLION ML/DAY)
FIGURE 44ROTATING BIOLOGICAL CONTACTORS OPERATING COSTS
F-46
-------
a
s
EQUIVALENT ANNUAL COSTS-( 10t5/TK>
EMTI MifcARDItiA I NT
t=TnSTg(llfe/YR^
FLOW (MILLION GAL/DAY)
FIGURE 45
MULTI-MEDIA FILTRATION ANNUAL, CAPITAL AND OPERATING COSTS
F-47
-------
APPENDIX G
Wastestream Data Listing
Q.' I
-------
WASTE stream
DATA II8TING - 8UBCATEC0RIZATI0N FILE
t
plant
NUMBER *
0 pp
L0"INF
FLOซEFF
800INF
SUBCaTbPL
bodeff
ASTICS ONLY ซ
CODINF
codeff
T8SINF
T83EFF
HUD)
(HOC)
(PPN)
(PPM)
(PPH)
(PPM)
(PPH)
(PPM)
9
ป
a
""""""
mm mmm
W
1.83
ป.ซ3
3,00
10.00
27.00
0.2ซ
0,30
1394,00
45.00
2000,00
113.00
22
00
32.00
0.07
237
00
0.04
12542,00
16549,00
.
1055
00
0.07
0.07
iia.oo
6,00
.
28
00
31,00
0.71
0,76
7.00
30.00
14,00
.
o.so
0,20
ซ
.
.
2.00
.
0.00
.
0.05
0.05
1200.00
52.00
2376.00
188,00
30.00
.
3.ซ0
3,80
237.00
7.00
470.00
.
15,00
0.17
0.16
9,00
t
42.00
42.00
31
00
12,00
10.60
10.70
131,00
23.00
258.00
120.00
38
00
25,00
a.70
a.70
114,00
7.00
210.00
115.00
86
00
114,00
0.04
.
.
5.24
5.22
.
.
0.08
0,06
666,00
35.00
1669.00
194.00
23,00
0.70
388.00
416.00
.
0
30
0.39
0.39
6.00
.
.
9,00
0.67
0.67
754,00
9,00
1234.00
83.00
2898
00
22,00
2.22
2.22
390,00
1,00
639.00
57.00
285
00
24,00
.
.
t
.
.
t
.
.
.
.
0.86
0,86
104,00
6,00
.
67.00
13,00
0.20
0.22
424,00
30,00
857.00
118.00
49
00
43,00
0.01
1861,00
t
6082.00
.
280
00
V
.
.
0.00
.
.
a.70
a.70
349.00
16,00
710.00
110.00
153
00
52,00
.
.
ฆ
ป
.
.
.
0.25
0.25
14.00
3,00
473.00
3a.oo
1359
00
11,00
*Note: Each line entry represents a separate waste
plants with multiple waste streams.
tocinf
(PPM)
46a
St
1936
00
00
00
TOCEFF
(PPM)
42
74
00
00
17
00
00
stream. Plant code numbers are repeated for
-------
2
4
I
2
1
1
1
4
2
2
I
1
I
I
7
ฆ
1
b
I
3
I
1
2
2
2
3
3
1
I
2
U8TE STREAM
DATA imiNt - 8UBCATEG0RIZATI0N FILE
flominf
FLOMCFF
BOD INF
8UBCATซPLA
BODEFF
8T1CB only <
C0D1NF
CODEFF
T881NF
T8SEFF
(HGD)
(hGD)
(PPH)
(PPซ)
(PPM)
(PPM)
(PPM)
IPPH)
0,42
0.42
170.00
24,00
876,00
176,00
ฆ
0,94
0.94
2.00
2.00
27,00
27,00
10.00
10.00
0,01
.
895.00
.
46,00
9
16.00
.
.
.
.
.
.
.
0.03
.
m
.
.
ฆ
.
m
.
.
ฆ
i
.
ฆ
0.14
0,14
ฆ
.
0.66
0.68
.
.
1.71
1.71
979.00
40.00
1900,00
620,00
101,00
76,00
2.74
2.74
51.00
4,00
97,00
15,00
20,00
15,00
2.0b
2.06
174.00
10,00
329.00
69,00
79,00
84,00
0.47
ฆ
ฆ
.
.
.
i
0.12
0.12
80.00
15.00
504.00
146.00
205,00
78,00
3.00
3.00
128.00
3.00
.
.
24,00
19,00
1.00
1 ,00
424.00
15.00
607.00
96,00
106,00
37,00
0 .85
0.05
10,00
.
4,00
1.54
1.54
1082.00
11.00
1557.00
115.00
62,00
60,00
0.10
ฆ
ฆ
.
.
ฆ
ฆ
ฆ
.
.
ฆ
ฆ
.
.
0.30
0.30
1847,00
6,00
2689,00
131,00
41.00
35.00
5.95
5.95
94,00
11.00
179.00
53.00
ฆ
2.16
2.55
215,00
47.00
403.00
172,00
142.00
127.00
1.57
1.57
427,00
12,00
864,00
.
151.00
83.00
0.93
0,93
95.00
6.00
272,00
37.00
43. 00
10.00
1.65
1 .65
12,00
10.00
73,00
58,00
36.00
26.00
0,20
0,20
ป
807,00
96.00
ai.oo
18,00
0.30
0.30
568.00
37.00
874.00
61,00
63.00
22.00
0.S2
0,52
1764,00
45.00
3173.00
205,00
167.00
30,00
0.33
0,35
1021,00
8,00
2292.00
102,00
561.00
28,00
ฆ
.
.
.
.
0.00
.
.
.
0.28
0.28
.
21,00
110.00
ง
11,00
.
.
.
.
.
.
.
0.35
0.35
187.00
6,00
1681,00
45,00
2547.00
23,00
TOCINF
(PPM J
04
290
25
-------
,AN
iHai
47
as
5o
52
52
54
55
55
55
56
57
61
67
60
73
7
-------
pp
I
1
2
1
1
9
2
1
3
1
1
1
I
3
1
1
1
I
4
3
2
3
3
2
3
3
2
1
4
HASTE STREAM
DAT* LISTING SUBCATE60RIZATI0N PILE
SUBCATbPLASTICS only
FLOMINF
(MGO)
FLOWEFF
(MGO)
BODINF
(PPM)
BODEFF
(PPM)
CODINF
(PPM)
CODEFF
(PPM)
TSSINF
(PPM)
TSSEFF
(PPM)
TOCINF
(PPM)
TOCEFF
(PPM)
0.00
0.74
0,74
15
00
16
00
0.07
0,07
400
00
32
00
520
00
64
00
2076
00
64
00
0,17
0.17
0.09
f
478
00
1422
00
1.17
1.17
204
00
6
00
405
00
77
00
74
00
16
00
o|b0
o!bO
61
00
36
00
109
00
75
00
0.70
0.70
0.00
0.10
0.10
oloo
.
0*46
o!ซ8
572
00
99
00
1219
00
455
00
97
00
90
00
0.03
0.04
4
00
16
00
6
00
0.03
0,03
5
00
5
00
o|ae
o|e8
119
00
14
00
531
00
65
00
643
00
19
00
0.31
0.31
06
00
56
00
3060
00
323
00
2713
00
179
00
0.00
97
3.9ฎ
3.96
470
00
34
00
900
00
353
00
69
00
00
2.ซ7
2.30
2'1
00
16
00
1693
00
94
00
407
00
45
00
0.00
.
i|so
U50
7
00
6
00
o.so
.
.
.
100
00
71
00
-------
I PI
>
11
li
i i
11
i*
51
25
II
26
21
1ซ
11
41
45
HA3TE STREAM
DAT* LISTING SUBCaTESORIZATION FILE
SUBCATinOT P, TYPE IiCป naTCRUSE >.1*5 CAL/LB
FLOHINF
fioซeff
BODlNF
BOOEFF
CODINF
CODEFF
T88INF
TSSEFF
TOCInF
TDCEFF
(MGO)
(MtD)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPH)
(PPM)
ซ
1
1
1
1
1
1
ฆ
1
a
1
1
1
1
a
0.72
0.72
2113,00
190.00
5370.00
725.00
ซ
1110
1110
997) 00
22)00
2404)oo
294)00
62
00
71
00
0.06
0.06
2527,00
393.00
5629.00
t
2440.00
1946
00
148
00
0.99
ป
27632)00
459
00
11006
00
0.*90
6022)oo
10037)00
3613
00
3.11
3.10
1365,00
36.00
1466.00
201.00
116
00
5.OS
5.07
501.00
41.00
66
00
469
00
159.00
2.43
2.43
362.00
61,00
662.00
169,00
266
00
135.00
2.13
1.35
199.00
68.00
27
00
20
00
2.34
2.34
ฆ
.
.
473
00
23.00
16^36
tslao
582)oO
15)00
I327)oo
162^00
23
00
36
00
332
00
64)00
29.70
29.00
153,00
10,00
9
00
0.55
0.55
.
0.27
0.27
.
ฆ
ฆ
.
a
ง
6.67
6.66
299.00
54.00
0.27
0.27
1.33
>.33
1407,00
64.00
2454,00
142
00
1205
00
116.00
2lll
2)00
793)00
53)00
>
562)oo
351)00
50
00
,!n
65Cl)oO
.
15)00
39
00
S05
00
34)00
12.20
12.20
319.00
19.00
53,00
26.00
126
00
26,00
2.60
2.04
2.04
1506,00
6.00
2663.00
55.00
57
00
13
00
0.62
0.62
1177,00
53,00
72
00
26
00
665
00
69.00
17.46
16.70
1719.00
28,00
36
00
21
00
793
00
61.00
3.92
4.BO
623.00
13,00
135.00
73
00
62
00
513
00
61.00
-------
27
34
34
35
35
36
36
37
37
39
39
41
41
42
42
43
43
56
60
75
76
ao
eo
87
90
93
95
06
15
:i6
116
120
22
128
!34
35
136
!36
WASTE STHEAH
DATA LISTING 6UBCATEG0RIZATI0N FILE
SUBCATaftOT P# TYPE UC, NATERU8E >.165 SAL/LB
floซinf
(HGO)
FLOWEFF
(MGD)
BOOINF
(PPH)
BOOEFF
(PPM)
CODINF
(PPH)
CODEFF
(PPM)
T8SINF
(PPM)
TSSEFF
(PPM)
TOC1NF
(PPM)
1.13
1.13
6a4.00
127.00
653.00
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
0
40
0.37
61.00
4329
00
590
00
68.00
0
55
0.49
5710
00
as.oo
6757
00
220
00
28
00
104.00
0
a9
o.a9
443
00
40.00
993
00
322
00
.
1
07
1.07
2507
00
40.00
860
00
189,00
3
00
U9aa
00
.
23744
00
.
1
66
1 ฆ 66
2629
00
127)00
4016
00
523
00
170*00
0
26
0.26
9
00
9.00
0
30
0,30
537
00
537.00
1577
00
1577
00
9
00
9,00
6
50
6.50
559
00
24.00
98
00
42,00
4
47
4.47
41.00
334
00
53.00
0
09
0. 09
2400
00
19^00
29)00
0
09
o)o9
>741
00
5o)oO
6178
00
368
00
344
00
9s)oO
0
48
0.33
803
00
368.00
2976
00
654
00
16.00
3
75
3.75
63.00
364
00
78.00
7
95
7.91
546
00
12.00
1354
00
199
00
5
10
5.10
89.00
2605
00
367
00
428
00
235.00
4
oa
4.08
37.00
193
00
65,00
535.00
43.00
46.00
.
8086
23
336
00
00
00
3112
719
334
00
00
00
-------
NUHbl
210
248
219
257
2*0
272
274
27o
HASTE 8TREAH
DATA LISTING SUBCATEGOR1ZATION FILE
7
SUBCATahOT P, TYPE HC, HATERU8E >.165 GAL/LB
ซ PP
floninf
(MGO)
floncff
(MGO)
BODINF
(PpM)
BOOEFF
(PPH)
codinf
(PPH)
COOEFF
(PPH)
TSSlNF
(PPM)
T88EFF
(PPM)
TOCIHF
(PPM)
TOCEFF
(PPM)
2.01
0.6B
0.62
0.27
3.99
ซ.3J
0.95
1.60
0.66
0.62
)ปป
0)95
4490.00
1211 loo
97o)oO
450.00
72.00
12.00
103.00
22|00
8334.00
5141.00
2169.00
1122.00
217.00
120.00
147.00
25b)oO
86
103
00
00
74.00
19.00
66,00
8b)oo
132I00
3202
695
262
00
00
00
73
74
00
00
-------
HASTE STREAM
DATA LISTING - SUBCATE60RI2ATI0N FILE
6
SUKCATbnOT P, TYPE ItCf NATERUSE<ป,165 cal/lb
CD
I
00
PLANT
FLOป|NF
flo*eff
BODINF
BODEFF
CODINF
COOEFF
TS8INF
TS3EFF
NUMBER
PP
(MCP)
(MOD)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPH)
9
1
1
mmmmm
t
1
1
t
a
a
a
a
a
a
a
a
a
a
a
a
a
a
a
37
4
0.02
ป
SB
8
1.30
.
670.00
960.00
61.00
40
5
0.01
0,01
<2
3
0.05
0.05
5961.00
380.00
1681.00
541.00
ซ9
1.01
1.01
7.00
34,00
50
21
0.36
0.2S
3913.00
33.00
278.00
74.00
SO
0.12
.
SI
10
0.66
.
51
0.07
t
63
0.0|
ฆ
194*00
63
10
0.56
0.56
691.00
468.00
5496.00
4079.00
63
6.74
6.74
43.00
43.00
271.00
271.00
12.00
12.00
63
0.27
.
SI
2
0.12
0.11
104.00
14o|oO
SI
3
0.26
0.30
288.00
SI
I
0.00
.
64
4
0.12
0.12
136
10
0.49
0.49
251.00
3091.00
563.00
250.00
160
0.05
.
52554.00
t
67095.00
163
5
0.03
0.03
3977.00
154.00
6237.00
638.00
177
31
2.22
2.22
268.00
16.00
.
177
0.26
20000.00
.
177
1.23
25000.00
.
IBS
20
1.00
1.00
1076.00
36.00
9229.00
240.00
4110.00
45.00
193
.
0.01
21425.00
62383.00
.
395)00
218
2
0.02
0.02
111.00
11360.00
1178.00
665.00
219
3
0.05
0.05
2514.00
30.00
3514.00
545.00
105.00
239
3
0.01
0.01
9.00
60.00
37.00
267
9
0.35
5618.00
.
266
26
2.50
2.50
4847.00
248.00
6060.00
1069.00
271
1ซ
1.72
1.12
3015.00
39.00
5842.00
222.00
150.00
276
o.u
.
279
3
0.01
0.01
21176.00
249.00
265.00
111.00
TOCINF
( PPH )
TOCEFF
(PPM)
20
1079
1199
1475
00
00
00
00
IS
665
417
360
00
00
00
00
6S
00
-------
WASTE STREAM
DATA LISTING - SUBCATEGORYATION FILE
9
SUBCATbNOT P, type iinot c
plant
MUHBER
FLOซINF
FLO&EFF
SODINF
BODEFF
C0D1NF
pp
("CD)
(HGD)
(PPM)
( PPM )
CPPM)
......
m m m m m m
......
......
ป
9
O.BB
0.66
1137.00
47.00
2073.00
9
2.44
2,44
609.00
23.00
1622.00
6
4.60
4.60
.
632.00
ป
2
0.84
t
ฆ
11
2.ซ
2.49
0.22
.
761.00
1810.00
k
4.03
.
ซ
3.57
3.57
279.00
31.00
21O.00
9
0.02
0,03
647.00
60,00
5546.00
3
O.OB
0.08
9,00
4,00
26.00
3
2.26
2.2#
1201.00
26,00
3
0.66
0,6b
655.00
13.00
654,00
3
17
ฆ
.
$
4
0.31
0.30
30.00
$
a
0.84
0.64
o.os
ป
*
t
11
3.60
3.60
11.00
120,00
16
7.16
7.16
467.00
13,00
.
9
3.36
3.36
200.00
26.00
300.00
.
.
a
32.05
32.10
62.00
17,00
.
IS
0.30
.
3044.00
11966.00
1
0.64 ,
0.64
16.00
.
3
0.06
.
42.00
14.00
12
0.36
0.36
2436.00
82,00
3449.00
IS
0.00
.
*
ซ
22
2.90
2.90
349.00
26.00
.
16
1.44
1.44
26.00
7
2.60
2,7k
1327.00
166,00
3067.00
11
3.10
3.32
76.00
9,00
2
0.3B
.
.
11
0.22
0.22
12.00
.
6
0.00
.
s
0.02
0.02
2666.00
760.00
32476.00
ซ
O.U
0.11
2725.00
161,00
7957.00
2ซ
0.16
0.16
25,00
.
CODEFF
(PPM)
354.00
390.00
523.00
63.00
26^00
117,00
30.00
816.00
,
40 loo
IO5io0
$
$
m
335*00
713*00
11000.00
1697.00
99.00
T9SINF
(PPM)
T8SEFF
(PPM)
TOCINF
CPPM)
TOCEFF
CPPM)
494
93
30
26Bป
1
991
56
33
ITT
32
760
164
00
00
00
00
00
00
00
00
00
00
00
00
62
B04
00
00
16
00
175
00
36
00
364
00
13
00
36
00
2056
00
1
00
74
00
13
00
67
00
*31
00
42
00
lซl
00
13
00
14
00
36
00
75
00
26
00
6
00
22
00
106
00
ซ6
00
46
00
272
00
60
00
76
00
971
00
501
00
19
00
66
00
19
00
ISO
00
46
00
651
00
147
00
-------
HASTE STREAM
DATA LISTING - SUBCATEGORIZATION FILE
10
SUBCATซNOT P, TYPE ItNQT C
plant
PLOMlNP
FLOWEFF
BODINF
B0DEFF
CODINF
CODEFF
TS3INF
TSSEFF
TOCINF
TOCEFF
nuhbeR
PP
(MGO)
(HCD)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
9
1
213
3
0.00
213
3
230
3
0.42
0.32
129
00
115.00
423
00
165,00
170
00
13.00
143
00
116.00
230
S
0.34
209
00
612
00
267
00
*
175
00
256
4
0.17
0.17
20.00
100,00
36,00
254
0.00
259
12
0.03
0,03
13.00
75.00
24.00
263
IS
0.01
0.03
37.00
13080
00
226*00
31,00
5226
00
132.00
264
6
1,80
1.60
266
00
17.00
333
00
40.00
133
00
27.00
67
00
7.00
266
5
0.40
*
.
269
20
4.31
4.31
S30
00
66.00
472
00
71.00
667
00
176.00
275
11
0.1ซ
0.14
116
00
116.00
SO
00
60,00
281
12
1.00
1.00
66
00
11.00
CD
2S3
4
.
1
284
9
0.33
0.33
.
2960.00
16,00
O
266
6
0.00
.
.
2S6
3
.
-------
NASTE stream
DATA LISTING > SU8CATEG0RIZAT10N FILE
11
SUSCATaNOT Pf NOT TYPE I
PP
FLOMINF
FLOmEFF
BODlNF
BODEFF
COOINF
COUEFF
T58INF
TS9EFF
TOCINF
toceff
(MCO)
(HGO)
(PPซ>
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
B
1
1
------
.....
ฆ
1
1
1
$
1
0.37
0.37
43,00
7
00
17,00
0.01
0,01
279,00
1045,00
O.OB
0,08
104,00
241,00
37
00
0 ! 14
0 * la
!7|00
22)00
19
00
9
a.39
4,39
330,00
10,00
590
00
65,00
17,00
29
00
4.09
4,09
12,00
40,00
2
00
0.51
9
0.43
0,43
9
9
502
00
133,00
1.46
1,46
520,00
24,00
5486
00
110,00
9
24
00
1.35
1,40
12,00
75,00
9
442
00
21,00
Uซ3
U43
9
218
00
liiloo
1.26
1,28
50,00
13
00
4.36
4,38
4,00
39,00
10
00
9,00
0.04
40.00
40,00
180,00
6,00
111.00
101
00
194
00
0.66
0,66
429,00
1ซ,00
694
00
276,00
121.00
76
00
9
7.50
7,50
0.13
9
0.74
13.90
13,90
9
136,00
15
00
35
00
16,00
19.16
19,90
95,00
8,00
266
00
69,00
34.00
32
00
68
00
34,00
0.09
0,09
6,00
286
00
66,00
19,00
18
00
92
00
2?00
2)00
27)oO
6^00
.
51
00
6^00
o)oo
9
.
.
0.95
0.95
27,00
744
00
413,00
1266.00
34
00
1.57
1.57
42,00
252,00
37
00
46,00
3.00
3,00
22,00
102,00
16
00
41,00
o!33
01 S3
122I00
162)*0
42
00
62*00
0.01
9
.
0.01
.
2.60
261,00
1364
00
108.00
0.01
1439,00
9
17166
00
-
7554,00
9592
00
-------
XA8TE 8TREAH
DAT* LISTING - 8UBCATC60RIZATI0N FILE
12
subc*tปnot pป NOT TYPE I
PLANT
FLO'INF
FLOMCFF
BODINF
BODEFF
CODINF
CODEFF
TSSINF
T33CFF
TQCXNP
Tocerr
NUMBER
a PP
(MGD)
(NGO)
(PPM)
(PPM)
(PPM)
(PPM)
(PPM)
(PPH)
(PPM)
(PPM)
ฆ
ฆ
1
1
1
0
1
1
1
1
1
181
1
.
.
ซ
.
162
1
0.53
0.55
236.00
36.00
.
65.00
26.00
492.00
61.00
166
5
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
.
.
.
.
226
10
I .36
1.20
461.00
23.00
1979.00
250.00
1225.00
55.00
.
.
231
2
0.15
0.16
1745.00
772.00
4556.00
1326.00
647.00
21.00
1455.00
315.00
24$
15
m
0.26
12.00
1196.00
16.00
.
11.00
247
10
3,10
3.10
3.00
260.00
69.00
26.00
.
.
252
10
o.u
2956.00
.
.
.
252
0.24
.
.
.
.
252
I
0.67
27672.00
.
33176.00
.
.
.
255
8
0.40
0.40
31.00
.
16.00
256
5
0.01
0.01
51.00
2*3.00
.
37.00
70.00
261
2
0.10
0.10
.
270
ซ
0.97
0.95
143.00
17.00
345.00
51.00
204.00
12.00
.
276
a
.
.
265
9
1.60
.
.
.
290
3
0.10
193.00
546.00
61.00
.
ui.oo
.
291
1
.
ซ
ซ
.
-------
hASTE STREAM
DATA IISTINC 8UBCATE60RIZATI0N FILE
13
8UBCATaPLA3TIC8 ONLY
PLANT 0R6AMIC PLASTIC
NUMBER PP PP OTHER HTF DISCHARGE
0 2 0 S3K DIM
0 2 0 ASL DIR
0 2 1 DP" ZERO
0 2 0 LAP ZERO
0 2 0 ASL DIR
0 3 0 ALA DIR
0 1 0 URN ZERO
0 0 0 CLR DIR
0 1 0 BRN ZERO
0 2 0 RTE ZERO
0 3 0 CON ZERO
0 3 0 RBC DIR
0 0 0 CON ZERO
0 5 3 ASL DIR
0 1 0 CLR DIR
0 3 2 ASL DIR
0 1 1 ASL DIR
0 2 1 CON ZERO
0 1 0 PCF DIR
0 1 0 ASL DIR
0 1 0 BRN ZERO
0 4 0 ASL DIR
0 1 0 ASL DIR
0 2 0 ASL DIR
0 2 0 RTE ZERO
0 5 0 BRN ZERO
0 0 0 CON ZERO
0 1 0 RTE ZERO
0 2 0 ASL DIR
0 1 0 RbC DIR
0 I 0 IMP ZERO
0 1 0 RTE ZERO
0 1 0 IMP ZERO
0 2 1 ASL DIR
0 10 DRY ZERO
0 2 0 DRY ZERO
0 2 0 DRY ZERO
0 2 1 ASL DIR
-------
HASTE STREAM
DATA LISTING - SUBCATEGORIZATION FILE
SUSCATaPLA$TIC8 ONLY
ORGANIC PLASTIC
PP PP OTHER NT? DISCHARGE
mmmmm
0
2
0
TRF
DIR
0
4
0
NOT
OIR
0
0
0
IHP
ZERO
0
0
0
OLS
DIR
0
t
0
EVP
ZERO
0
2
0
OPm
ZERO
0
J
0
6RN
ZERO
0
5
0
DRV
ZERO
0
1
0
CLR
DIR
0
1
0
OLS
DIR
0
4
0
ASL
DIR
0
2
0
RBC
DIR
0
2
0
ASL
OIR
0
0
0
IMP
ZERO
0
t
0
ASL
DIR
0
t
0
ASL
OIR
0
2
0
ASL
DIR
0
0
0
ARL
DIR
0
7
0
ASL
DIR
0
0
0
DP*
ZERO
0
0
0
IHP
ZERO
0
0
0
NEU
DIR
0
1
0
ASL
OIR
0
s
i
ALA
DIR
0
1
0
ASL
OIR
0
s
0
ASL
DIR
0
t
0
ASL
DIR
0
t
0
OLS
OIR
0
1
1
ASL
DIR
0
2
0
ASL
DIR
0
2
0
ASL
DIR
0
S
0
ASL
DIR
0
1
0
CON
ZERO
0
1
0
CON
ZERO
0
t
0
ALA
OIR
0
2
0
DRY
ZERO
0
0
0
RTE
ZERO
0
4
1
ASL
DIR
-------
MA8TE STHtAH
DAT* LISTING - SUBCATECORIZATION FILE
8U8CATปPLA8TIC8 ONLY
PLANT ORGANIC PLASTIC
NUMBER PP PP OTHER HTF
117
0
2
1
A8L
(48
0
1
0
DRY
ISO
0
3
3
ALA
152
0
1
0
CLR
152
0
1
0
clr
154
0
2
1
CON
155
0
4
2
DRY
155
0
0
0
RTE
155
0
0
0
CON
156
0
2
0
88K
157
0
1
0
A8L
1*1
0
2
0
DRY
167
0
1
0
CON
168
0
1
0
UNK
173
0
4
1
CON
17ซ
0
4
3
ASL
179
0
2
1
ASL
184
0
4
0
88K
185
0
1
0
CON
189
0
1
0
ALA
192
0
2
i
ASL
194
0
1
t
NOT
196
0
1
0
CLR
197
0
3
0
RTE
197
0
1
0
BRN
198
0
1
0
ORV
199
0
3
0
RTE
199
0
1
0
RTE
200
0
1
0
BRN
200
0
0
0
IMP
202
0
1
0
ARL
207
0
2
0
DRY
209
0
1
0
BRN
210
0
8
0
ASL
210
0
0
0
BRN
211
0
1
0
LAP
212
0
*
0
LAP
217
0
2
0
ASL
DISCHARGE
DIM
ZERO
OIR
DIR
OIR
ZERO
ZERO
ZERO
ZERO
DIR
OIH
ZERO
ZERO
UNK
ZERO
OIR
DIR
OIR
ZERO
DIR
DIR
OIR
OIR
ZERO
ZERO
ZERO
ZERO
ZERO
ZERO
ZERO
DIR
ZERO
ZERO
OIR
ZERO
ZERO
ZERO
DIR
-------
HASTE STREAM
DATA LISTING . SUBCATEGORY AT ION FILE
SUSCAT0PLASTIC9 ONLY
PLANT ORGANIC PLASTIC
NUMBER PP PP OTHER WTF
221
0
1
0
DRY
ill
0
0
0
CON
m
0
1
0
ALA
22<
0
2
0
A8L
as
0
1
0
ALA
iif
0
1
0
OFS
229
0
i
1
asl
212
0
s
0
not
231
0
2
0
R8C
21?
0
1
0
ASL
2*0
0
2
1
EVP
241
0
I
0
OLS
2*2
0
1
0
CON
2ซ)
0
1
0
CON
244
0
1
0
ORY
244
0
0
0
IMP
2ซ*
0
s
0
CLR
249
0
I
0
OLS
210
0
1
0
NOT
251
0
1
Q
OR*
253
0
1
0
0RN
254
0
1
0
AL*
242
0
1
0
ASL
265
0
2
0
CON
275
0
X
0
ASL
iff
0
)
0
ASL
280
0
2
0
RTE
262
0
2
0
UN*
267
0
I
0
ARL
28ฎ
0
2
0
CON
286
0
0
1
DRY
2 99
0
1
1
ORY
1ft
mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmwm
DISCHARGE
ZEHO
ZERO
DIR
OIK
DIR
ZERO
DIR
DIR
DIR
DIR
ZERO
OIR
ZERO
ZERO
ZEHO
ZERO
DIR
DIR
OIR
ZERO
ZERO
DIR
OIR
ZERO
DIR
OIR
ZERO
UNK
DIR
ZERO
ZERO
ZERO
-------
HASTE STREAM
DATA LISTING - SUBCATEGORYATION FILE
SUBCATbnOT 9, TYPE HCป NATERUSE >,1*5 GAL/LB
ORGANIC PLASTIC
PP PP OTHER MTP DISCHARGE
1
2
0
A3L
DIR
0
0
0
URN
ZERO
s
0
3
ASL
DIR
1
5
0
ASL
DIR
1
2
0
l)RV
ZERO
0
0
0
IMP
ZERO
1
2
0
ORY
ZERO
0
0
0
IMP
ZERO
11
0
2
OPM
ZERO
0
0
0
ORY
ZERO
11
0
0
1HP
ZERO
3
2
0
ASL
DIR
3
1
0
ASL
DIR
9
2
0
ASL
DIR
1
3
0
ALA
DIR
12
1
1
ASL
DIR
0
0
0
BRN
ZERO
0
0
0
OPM
ZERO
4a
7
1
ALA
DIR
IS
5
5
ASL
OIR
a
0
0
OLS
OIR
5
0
0
NOT
DIR
2
0
0
UNK
UNK
11
1
0
ASL
DIR
4
0
0
NOT
DIR
23
0
3
A8L
DIR
1
0
0
BRN
ZERO
11
0
a
ASL
DIR
1
1
0
OPm
ZERO
0
0
0
BRn
ZERO
1
0
1
8RN
ZERO
2
2
1
ASL
DIR
e
3
3
ANL
DIR
5
2
4
l)P*
ZERO
2
1
0
ASL
DIR
2
1
ASL
DIR
29
12
0
ASL
DIR
39
S
1
ALA
DIR
-------
27
34
34
19
35
36
36
37
37
39
39
41
41
42
42
43
43
sa
60
75
76
ao
ao
87
90
93
95
06
(15
16
16
20
22
28
34
35
36
36
NASTE STREAM
DATA LISTING > SUBCATIGORIZATION FILE
IS
SUBCATbnOT P# type lie, MATERUgE >,165 CAL/LB
organic plastic
PP PP OTHER NTF 01JCHARGC
14
0
A8L
DIN
1
0
OR*
ZERO
0
0
RTE
ZERO
1
0
DRY
ZERO
0
0
RTE
ZERO
2
1
DRY
ZERO
0
0
RTE
ZERO
1
0
DRY
ZERO
0
0
RTC
ZERO
2
1
DRY
ZERO
0
0
HTE
ZERO
1
0
DRY
ZERO
0
0
RTE
ZERO
1
0
DRY
ZERO
0
0
RTE
ZERO
2
1
DRV
ZERO
0
0
RTE
ZERO
4
2
ASL
DIR
4
0
ASL
OIR
2
1
ASL
DIR
6
1
ASL
DIR
3
2
UP*
ZERO
0
0
OLS
DIM
1
1
ASL
DIR
2
0
NOT
DIR
3
0
NOT
DIR
16
0
ASL
DIR
S
0
ALA
DIR
1
0
RTE
ZERO
1
0
ASL
DIR
0
0
URN
ZERO
1
0
ASL
OIR
3
0
ACR
DIR
21
7
ASL
OIR
31
1
ASL
DIR
B
0
ASL
OIR
15
3
ASL
OIR
0
0
DPN
ZERO
-------
HASTE STREAM
DATA LISTING SUBCATEGORIZATION FILE
SUBCATinOT P, TYPE UCซ HATERUSE >.165 GAL/LB
PLANT
organic
PLASTIC
NUMBER
pp
PP
OTHER
NTF
DISCHARGE
mmmmm
ซป
238
t
2
0
KTE
ZERO
24B
2
0
0
ASL
DIR
249
s
0
0
ASL
DIR
257
4
2
0
ASL
DIR
2*0
3
0
2
ors
ZERO
272
12
3
0
anl
DIR
274
36
3
0
OFS
ZERO
276
S
1
0
ALA
DIR
-------
MASTE STREAM
DATA LISTING - SUBCATEGORIZATION FILE
20
9UBCATbnOT P, TYPE IIC# NATERUSE<ซ.165 GAL/LB
PtANT
ORGANIC
PLASTIC
NUMBER
PR
PP
OTHER
KTP
DISCHARGE
t
l
I
1
37
2
2
0
MTE
ZERO
38
6
0
2
DPri
ZERO
40
1
3
1
HHP
DIR
>2
1
2
0
ASL
DIR
49
0
0
0
ALA
DIR
SO
18
3
0
ASL
DIR
SO
0
0
0
IHP
ZERO
SI
10
0
0
DPm
ZERO
51
0
0
0
BRN
ZERO
63
0
0
0
BAN
ZERO
63
6
0
a
ASL
DIR
63
0
0
0
NOT
DIR
63
0
0
DPM
ZERO
01
2
0
0
ASL
DIR
at
3
0
0
STR
DIR
CD
61
1
0
0
bRN
ZERO
l
ro
a
S
0
0
NOT
DIR
o
138
6
1
3
ALA
DIR
160
0
0
0
BRN
ZERO
163
S
0
0
ASL
DIR
177
29
2
0
ASL
DIR
177
0
0
DPN
ZERO
177
0
0
0
DPป
ZERO
188
IS
2
3
ASL
DIR
193
1
2
0
URN
ZERO
218
1
1
0
ALA
DIR
219
1
2
0
ASL
DIR
259
1
2
0
ASL
DIR
267
8
0
1
JHP
ZERO
268
26
0
0
A6L
DIR
271
IS
3
0
ASL
DIR
276
0
0
0
DP*
ZERO
279
1
2
0
ALA
OIR
-------
MASTE STREAM
DAT* LISTING - 8UBCATEG0RIZATI0N FILE
21
3UBCATBNOT p, type unot c
plant organic plastic
number pp pp other htf discharge
12 b 1 ALA DIH
15 1 SO ASL DIR
lb 3 12 PCF DIR
16 1 0 1 DPN ZERO
22 9 2 0 ASL DIR
22 0 0 0 DPN ZERO
2* 6 0 0 RTE ZERO
26 1 2 1 TRF DIR
32 9 0 0 ALA DIR
35 2 1 0 NOT DIR
53 1 2 0 ASL DIR
64 1 11 ALA DIR
69 2 1 0 DRY ZERO
S3 11 1 5 RTE ZERO
65 2 2 0 NEU DIR
S7 4 11 ASL DIR
-------
HASTE STREAM
oata listing - subcategoryation file
............. SUBCATsNOT P, TYPE ItNOT C
NT ORGANIC PLASTIC
BER PP PP OTHER WTF
ซฆ ซซ
3 1 2 0 CON
3 0 J 0 DRY
0] 0 0 CLR
0 7 |0 OPm
6 1 3 0 SSK
6 0 0 0 IMP
9 12 0 0 ACR
3 17 10 ASL
4 2 1 ) ASL
6 4 1 0 IMP
9 15 2 S ASL
5 5 6 0 NOT
1 II 0 1 ASL
S3 1 0 DRY
4 6 0 1 NEU
6 2 4 0 CON
6 0 2 t ORY
DISCHARGE
ZERO
ZERO
DIR
ZERO
DIR
ZERO
DIR
DIR
OIR
ZERO
DIR
DIR
DIR
ZERO
DIR
ZERO
ZERO
-------
NASTE STREAM
DATA LISTING - 8UBCATCG0RIZATI0N FILE
BUBCATaNOT P# NOT TYPE I
plant
NUMBER
ORGANIC
pp
PLASTIC
PP
CD
I
ro
oo
OTHER
NTP
1
3
CLR
0
0
ALA
0
0
OLS
0
0
OFS
0
0
nEU
1
1
ASL
2
0
ALA
0
0
KTE
3
0
ALA
3
0
ASL
0
0
NEU
0
1
ORT
3
1
ASL
0
3
CLR
0
0
NEU
0
0
DP"
1
2
ASL
1
0
ASL
3
I
NEU
0
0
DP"
2
2
DPn
2
3
ALA
3
3
ALA
0
0
ACR
0
0
DRV
0
0
OLS
0
0
URN
0
0
IMP
5
0
CON
2
0
ASL
1
t
ARL
0
0
ASL
1
0
ALA
0
0
DAF
0
0
CON
0
1
RTE
0
0
CON
3
1
IMP
DISCHARGE
DIR
DIR
DIR
ZERO
DIR
DIR
DIR
ZERO
DIR
DIR
DIR
ZERO
DIR
DIR
DIR
ZERO
DIR
DIR
DIR
ZERO
ZERO
DIR
DIR
DIR
ZERO
DIR
ZERO
ZERO
ZERO
DIR
DIR
DIR
DIR
DIR
ZERO
ZERO
ZERO
ZERO
-------
HA9TE stream
DATA LISTING - 8UBCATEC0HIZAT10N FILE
PLANT
NUMBER
ORGANIC
PP
SUBCATbnOT 9, NOT TYPE I
PLASTIC
PP OTHER MTF
CD
i
r\j
tat
1*2
166
205
20a
214
226
231
245
2ซT
252
252
252
255
298
261
270
276
285
290
291
0
1
1
2
10
1
1
1
14
5
2
0
1
6
5
1
1
2
5
2
1
I
0
4
0
0
5
S
1
0
4
0
1
0
0
0
1
i
5
0
1
0
DRV
STH
ASL
NEU
ASL
DRV
TRF
ACS
STR
ASL
OFB
OF6
OP"
NEU
ACR
NOT
OXV
OKY
OPn
DPn
BRN
/
DISCHARGE
ZERO
OIR
01R
DIR
OIR
ZERO
DIR
OIR
OIR
DIR
ZERO
ZERO
ZERO
DIR
OIR
DIR
DIR
ZERO
ZERO
ZERO
ZERO
-------
HA3TE stream
DATA LISTING - SUBCATEGORYATION FILE
25
SUBCATaPLASTICS ONLY
PLANT
NUMttER
OtGINF
(PPM)
OtGEff
(PPM)
PHENOLINF
(PPM)
PHENOLEFF
(PPM)
NH3NINF
(PPM)
NM3NEFF
(PPM)
CHROMIUHINP
(PPM)
CHROMIUMEFF
(PPM)
CD
I
ro
(_n
41.00
4.00
13.00
0.1ซ
0.03
00
13
7.60
00
00
00
34.00
29
0
35
6
00
60
60
00
00
00
0.11
46
09
0.50
0.03
01
02
02
01
-------
WASTE STREAM
DATA LISTING . SUBCATECORIZATION FILE
26
SUBCATsPLASTJCS only
PL
NO
NT
SER
OtGINF
(PPM)
OlGEFF
(PPM)
phenolinp
(PPM)
PMENOLEFF
(PPH)
nhjnInf
(PPM)
nmjneff
(PPM)
CHROMIUMINF
(PPM)
CHROHIUMEFF
(PPM)
2,00
49
00
es
00
CD
I
ro
cn
20
10
09
01
Ot
00
20
50
46
40
47
46
36
23
23
00
00
00
00
00
19
30
00
20
00
20
00
30
05
-------
HASTE STREAM
DATA LISTING - SUBCATEGORIZATION FILE
27
SUBCATiPLASTICS ONLY
NT
8ER
OICINr
(PPH)
OtGEFF
(PPM)
PHENOLINF
(PPM)
PHENOLEFr
(PPM)
NMJNINF
(PPM)
NM3NEFF
(PPM)
CHROMIUMINF CHROMIUMEFF
(PPM) (PPM)
3.10
0.04
0.01
14
00
IS
00
ao
oo
to
26
ซ26
00
00
OS
11
00
109
11
00
00
67
SS
SV
02
-------
221
221
223
224
225
227
224
212
233
237
2ซ0
241
2ซ2
243
244
244
246
249
290
2S1
253
254
262
265
273
277
280
262
287
286
288
289
HA3TE STREAM
OATA LISTING ซ 6UBCATC60RIZATI0N FILE
26
6UBCaTปPLA8TIC# ONLY
01CINF
(PPM)
oigeff
(PPM)
PHENOLINF
(PPM)
PHENOLEFF
(PPH)
NHJNINF
(PPM)
NMJNEFF
(PPM)
CHROMIUMINF
(PPM)
CHROMIUMEFF
(PPM)
00
80
2
00
30
14
00
10
13
05
39
00
50
00
00
09
-------
HASTE STREAM
DATA LISTING - 8UBCATEG0RIZATI0N FILE
SUBCATaNOT P, TVPe lie, NATERUaE >.165 GAL/LB
PHENOUINF PHENOLEFF NMJnINF NH3NEFF
(PPh) (PPซ) (PPh) (PPM)
00
56
60
00
Ot
04
0ซ
12
6
56
ST
40
00
50
00
00
-------
HASTE stream
DATA LISTIN6 SUBCATECORIZATION PILE
SUBCATaNOT P, TYPE IปC* HATERUSE >,165 6AL/LB
PHENOLINF
(PPM)
PMENOLEFF
(PPM)
NH3NINP
(PPM)
nhsnefp
(PPM)
le.oo
3.60
303.00
eo
80
01
390
29
00
00
00
00
04
*0
-------
WASTE stream
DAT* LISTING - 6UBCATEG0RIZATI0N FILE
SUBCATsnOT P, TYPE IICป NATEKUSE >.165 SAL/LB
PLANT
number
016INF
(PPM)
otcerr
(PPM)
PHENOLINF
( PPM )
PHENOLEFF
(PPM)
NHJNINF
(PPh)
nhsneff
(PPM)
CHROMIUNINF
(PPM)
CHROHIUHEFF
(PPM)
2IB
248
249
257
260
272
274
276
00
9,00
42
t
00
ao
0.30
-------
USTE stream
D*TA LISTING - SUBCaTEGORJZATIOn FILE
80BC*Tซn0T Pซ TYPE UCf MATERUSE
-------
HASTE stream
DATA LISTING SU0CATCGOR1ZATION FILE
ss
PLANT
NUMBER
OtGINf
(PPM)
OtGCFF
(PPM)
SUBCATBNOT P, TYPE ItNOT c
phenolinf
(PPM)
PMENOLEFF
(PPM)
NH3N1NF
(PPM)
NH3NEFF
(PPM)
CHROMIUMINF
(PPM)
CHROMIUHEFF
(PPM)
762
00
es
570
00
112
00
50
02
00
60
00
40
CD
I
CO
CO
00
00
14
0
0
00
02
06
32
00
294
00
00
07
oa
00
11
15
00
00
16
00
17
00
29
00
20
2C
10
70
79
09
04
36
-------
HASTE stream 34
DATA LISTINS SUBCATECORIZATION FILE
SUBCATsNOT P, TYPE KNOT C
ANT OftGINF OIGeFP PHENOLZNF PhENOLEFF NHJnInF NHJNEFF CHROHJUHINF CHROHIUNEFF
*6ER (PPM) (PPM) (PPM) (PPM) (PPM) (PPM) (PPM) (PPM)
ซiS
00
23
I
00
00
15
15
25)
22
00
70
1
SO
22
60
00
70
50
01
SO
01
-------
MASTE STREAM
DATA LISTINC BUBCATCGORIZATION FILE
ss
BUBCATaNOT P, NOT TYPE I
plant
NUMBER
OIGINF
(PPN)
OtGCFF
(PPH)
PHENOLINP
(PPH)
PHENOlEFf
(PPH)
NHJNINF
(PPM)
NH3NEFF
(PPH)
CHROHIUHJNP
(PPH)
CHROMIUHEFF
(PPH)
o
I
CO
cn
420
2B6
00
0,42
46.00
00 1
00
*0
00
2J4S
120
21
00
00
00
00
10
15
00
00
12
10
20
20
65
02
SO
65
B0
00
240
4
60 64
B0
00
50
10
70
20
00
21
74
0.02
10
00
10
05
02
OS
29
23
00
-------
lal
1ซ2
16b
205
20ป
214
226
211
2*5
247
252
252
252
255
256
261
270
276
2ป5
290
291
otcinr
(PPM)
0ปGEFF
(PPM)
HASTE STREAM
DATA LISTING - 8UBCATCCORIZATION FILE
SUBCATaNOT 9, NOT TYPE I
PHENOLINF
CPPM)
PMENOLEFF
(PPซ)
nhInINF
(PPm)
nhsneff
(PPH)
CHROHIUHINP
(PPM)
CHROHIUHEFF
(PPM)
16
so
oo
67
77
00
46
ea
32
00
10
06
01
20
04
44
189
5111
SO
00
00
70
90
70
10
00
oa
44
OS
-------
1_
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing,
1. REPORT NO.
EPA 440/1-83/009b
2.
3 --^oiFMT'SAr.rceeiA*ป..ป
PB8 3-205633 K
4. title and subtitle
development Document for Effluent Limitations Guide-
lines and Standards for the Organic Chemicals and
Plastics and Synthetic Fibers Point Source Category
5. REPORT DATE
Februarv 19R3 prpparatinn
6. PERFORMING ORGANIZATION CODE
7. author(S) vol 1,(BPT)
E. H. Forsht
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANISATION NAVE ANO ADDRESS I
Effluent Guidelines Division WH-552
U.S. Environmental Protection Agency
401 M.St. S.W.
Washington, D.C. 20460
10. PROGRAM ฃLEMENT NO.
546B2B
1T. CONTRACT/GRANT NO.
68-01-6701
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
401 P St. S.W.
Washington, P.C. 20460
13. TYPE OF REPORT AND PERIOD COVERED
Proposed Development Pocumpnt.
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
i 16. ABSTRACT
This document presents the findings of studies of the organic chemicals and plastics
and synthetic fibers manufacturina point source category for the purpose of. developim
effluent limitations guidelines for existing point sources. Effluent limitations
quidelines proposed herein are for "best practicable technology", "best conventional
technology", and "best available technolooy", new source performance standards and
pretreatment standards, as renuired under Sections 301, 304, 306, 307, and 501 of the
Clean Water Act (the Federal Water Pollution Control Act Amendments of 1972, 33 U.S.C
1251 et sen., as amended by the Clean Water Act of 1977, P.I. 9F-217 (the "Act")),
and as required under the Settlement Aareement in 'Natural Resources Pefense Council.
Inc. v. Train,-8..EPC 2120 (D.D.C. 1976), modified 12 ERC 1833 (D.D.C. 1979), and
modified again by'order of the court dated October 26, 1982.
This document contains the supporting data and rationale for development of the
effluent limitations and guidelines includinq subcategorization schemes, wastewater
characteristics, treatment technologies and costs.
17. KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS
b. IDENTIFIERS/OPEN ENDEDTERMS
c. COS ATI Field/Group
Wastewater, Treatment, EPA, Peculations,
BPT, BAT, NSPS, PSES, PSNS, Orqanic
Chemicals, Plastics, Synthetic Fibers
18. DISTRIBUTION STATEMENT ~
Release Unlimited
19. SECURITY CLASS (This Report J
21. NO. OF PAGES
20. SECURITY CLASS (This page)
22. P
EPA Form 2220-1 19*73)
------- |