United States       Industrial Technology    July 1985
Environmental Protection   Division (WH-5ci2)
Agency         Washington, DC 20460       OOOR85106

Water	^__^__^__^______________________^_______^___

Selected Summary of

Information in Support

of the
Organic Chemicals, Plastic
and Synthetic Fibers
Point Source Category
Notice of Availability of
New Information

-------
        SELECTED SUMMARY OF INFORMATION IN SUPPORT OF
        THE ORGANIC CHEMICALS, PLASTICS AND SYNTHETIC
            FIBERS POINT SOURCE CATEGORY NOTICE OF
               AVAILABILITY OF NEW INFORMATION
             U.S.  ENVIRONMENTAL PROTECTION AGENCY
                INDUSTRIAL TECHNOLOGY DIVISION
          OFFICE OF WATER REGULATIONS AND STANDARDS
                      401 M Street, S.W.
                   Washington, D.C.  20A60
                         July 1, 1985
U.S. Environmental  Protection  Agency
Region V, U''.~:v
230 Sojiii Dearborn Street   -"^
Chicago,  Illinois  60604

-------
                                 TABLE OF CONTENTS


   I.   DEFINITION AND SUBCATEGORIZATION OF THE ORGANIC CHEMICALS, PLASTICS,
        AND SYNTHETIC FIBERS POINT SOURCE CATEGORY

  II.   INDUSTRY SURVEY AND OVERVIEW

 III.   TECHNOLOGY BASIS FOR BPT OPTIONS AND DERIVATION OF EFFLUENT LIMITATIONS

  IV.   TECHNOLOGY BASIS AND DERIVATION OF BAT EFFLUENT LIMITATIONS

   V.   TECHNOLOGY BASIS AND DERIVATION OF PSES EFFLUENT LIMITATIONS

  VI.   EVALUATION OF THE VALIDITY OF USING FORM 2C DATA TO CHARACTERIZE PROCESS
        AND FINAL EFFLUENT WASTEWATER

 VII.   CALCULATION OF PRIORITY POLLUTANT WASTE LOADS

VIII.   COSTING DOCUMENTATION AND NOTICE OF NEW INFORMATION REPORT

  IX.   SUPPLEMENT TO COSTING DOCUMENTATION OF NOTICE OF NEW INFORMATION REPORT
                                           U,S. EnvIreRmenfaf Protection Agency

-------
I.  DEFINITION AND SUBCATEGORIZATION
      OF THE ORGANIC CHEMICALS,
   PLASTICS AND SYNTHETIC FIBERS
       POINT SOURCE CATEGORY

-------

-------
I.  DEFINITION AND SUBCATEGORIZATION OF THE ORGANIC CHEMICALS, PLASTICS
              AND SYNTHETIC FIBERS POINT SOURCE CATEGORY
                              TABLE OF CONTENTS
1.   DEFINITION OF THE ORGANIC CHEMICALS AND THE PLASTICS/                1
     SYNTHETIC FIBERS INDUSTRIES

2.   SUBCATEGORIZATION                 .                                  14
     2.1   INTRODUCTION                                                  14
     2.2   SUBCATEGORIZATION BASED ON PRODUCT GROUPS                     19
     2.3   PROCESSES EMPLOYED AND PROCESS CHANGES                        29
           2.3.1  Raw Materials                                          29
           2.3.2  Process Chemistry                                      31
           2.3.3  Product/Processes                                      33
     2.4   FACILITY SIZE                                                 34
     2.5   GEOGRAPHICAL LOCATION                                         37
     2.6   AGE OF EQUIPMENT AND FACILITY                                 38
     2.7   ENGINEERING ASPECTS OF CONTROL TECHNOLOGIES (TREATABILITY)    43
     2.8   FLOW '                        .                                 46
     2.9   COST OF ACHIEVIING EFFLUENT REDUCTION                         48
     2.10  ENERGY AND NONWATER QUALITY ENVIRONMENTAL
           IMPACTS                                                      '49

-------
I.  DEFINITION AND SUBCATEGORIZATION OF THE ORGANIC CHEMICALS, PLASTICS
              AND SYNTHETIC FIBERS POINT SOURCE CATEGORY
                                LIST OF TABLES
 1   SIC 2865"  CYCLIC (COAL TAR) CRUDES AND CYCLIC INTERMEDIATES,
     DYES, AND ORGANIC PIGMENTS (LAKES AND TONERS)
 2   SIC 2869:  INDUSTRIAL ORGANIC CHEMICALS NOT ELSEWHERE CLASSIFIED     5

 3   SIC 2821:  PLASTICS MATERIALS, SYNTHETIC RESINS,                     7
     AND NONVULCANIZABLE ELASTOMERS

 4   SIC 2823:  CELLULOSIC MAN-MADE FIBERS                                8

 5   SIC 2824:  SYNTHETIC ORGANIC FIBERS, EXCEPT                          9
     CELLULOSIC              .              -

 6   OCPSF CHEMICAL PRODUCTS LISTED AS SIC 29110582                      12
     PRODUCT CODES

 7   OCPSF CHEMICAL PRODUCTS LISTED AS SIC 29116324                      13
     PRODUCT CODES

 8   SIGNIFICANCE LEVELS FOR ANOVA FOR VARIOUS PRODUCTION CRITERIA       27
     VS. SELECTED DEPENDENT VARIABLES

 9   PERCENT PRODUCTION OF PRODUCT/PRODUCT-GROUPS BY SUBCATEGORY         28

10   SPEARMAN RANK CORRELATION COEFFICIENTS (R) FOR RAW WASTE BOD        36
     AND TSS VERSUS SIZE

11   SPEARMAN RANK CORRELATION COEFFICIENTS FOR DEGREE DAYS VERSUS       39
     EFFLUENT BOD AND EFFLUENT TSS

12   SPEARMAN RANK CORRELATION COEFFICIENTS FOR AGE OF PLANT             42
     VERSUS INFLUENT BOD AND TSS

13   SPEARMAN RANK CORRELATION COEFFICIENTS FOR INFLUENT FLOW VERSUS     47.
     VERSUS INFLUENT BOD AND INFLUENT TSS

-------
     1.   DEFINITION OF THE ORGANIC CHEMICALS AND THE PLASTICS/SYNTHETIC
                              FIBERS INDUSTRIES
     The Consent Decree requires that effluent limitations and guidelines,
including pretreatment standards, extend to 95% of the point sources within
the Organic Chemicals and Plastics/Synthetic Fibers (OCPSF) industries.   The
Consent Decree defines the OCPSF industries to comprise the following SIC1
codes:

     2865  Cyclic (Coal Tar> Crudes,  and Cyclic Intermediates, Dyes, and
           Organic Pigments (Lakes and Toners)
   •  2869  Industrial Organic Chemicals, Not Elsewhere Classified
     2821  Plastics Materials, Synthetic Resins,  and Nonvulcanizable Elastomers
     2823  Cellulosic Man-Made Fibers
     2824  Synthetic Organic Fibers,  Except Cellulosic.

     The Agency has defined the Organic Chemicals Manufacturing and Plastics/
Synthetic Materials Manufacturing industries (since combined into one indus-
try category because of their interdependence) to include all facilities
within specific SIC codes:  SIC 2865, Cyclic (Coal Tar)  Crudes, and Cyclic
Intermediates, Dyes, and Organic Pigments (Lakes  and Toners);  SIC 2869,  Indus-
trial Organic Chemicals, Not Elsewhere Classified;  and SIC 2911,  Liquified
Refinery Gases (including other aliphatics) made  from purchased refinery pro-
ducts and other Finished Petroleum Products (aromatics)  made from purchased
refinery products.

     The products that the SIC Manual includes in the industrial organic
chemical industry (SIC 286) are natural products  such as gum and wood chemi-
cals (SIC 2861), aromatic and other cyclic organic chemicals from the proces-
sing of coal tar and petroleum (SIC 2865),  and the aliphatic or acyclic
Standard Industrial Classification (SIC)  codes,  established  by  the  U.S.
 Department of Commerce,  are classifications of commercial and industrial
 establishments by type of activity in which they are  engaged.
                                     -1-

-------
organic chemicals (SIC 2869).  These chemicals are the raw materials for
products such as plastics, rubbers, fibers, protective coatings, and deter-
gents, but have few direct consumer uses.  Gum and Wood chemicals (SIC 2861)
are regulated under a separate Consent Degree industrial category, Gum and
Wood Chemicals Manufacturing.

     The Plastics/Synthetic Materials Manufacturing category as defined by
the Consent Decree comprises SIC 282, Plastic Materials and Synthetic Resins,
Synthetic and Other Man-Made Fibers, except Glass.  SIC 282, in turn, includes
the following four-digit SIC codes:

     2821  Plastics Materials, Synthetic Resins, and Nonvulcanizable Elastomers
     2822  Synthetic Rubber  (Vulcanizable Elastomers)
     2823  Cellulosic Man-Made Fibers              .            .
     2824' Synthetic Organic Fibers, Except Cellulosic.

     Of  these codes, SIC  2822 is covered specifically by another Consent
Decree industrial  category,  Rubber Processing.   Similarly, another SIC code
which might  be  considered  as part of the Plastics  industry, SIC 3079, the
miscellaneous plastics  products industry, is covered by the Consent Decree
industrial category Plastics Molding and Forming.  The Agency has defined
the Plastics/Synthetic  Fibers industry  to include  all facilities within SIC
codes  2821,  2823,  and 2824.

      Important  classes  of  chemicals of  the  Organic Chemicals Industry within
SIC 2865 include:   (1)  derivatives of benzene,  toluene, naphthalene, anthra-
cene,  pyridine, carbazole, and  other cyclic chemical products;  (2) synthetic
organic dyes;  (3)  synthetic organic pigments;  and  (4) cyclic (coal tar)
crudes,  such as light oils and  light oil products; coal tar acids; and pro-
ducts of medium and heavy oil such as creosote oil, naphthalene, anthracene
 (and  their high homologues), and  tar.   Important classes of chemicals of the
 Organic Chemicals industry within SIC 2869  include:   (1) noncyclic organic
                                      -2-

-------
chemicals such as acetic, chloroacetic, adipic, formic, oxalic and  tartaric
acids and their metallic salts; chloral, formaldehyde, and methylamine;
(2) solvents such as amyl, butyl, and ethyl alcohols; methanol; amyl, butyl,
and ethyl acetates; ethyl ether, ethylene glycol ether, and diethylene glycol
ether; acetone, carbon disulfide, and chlorinated solvents such as  carbon
tetrachloride, tetrachloroethene, and trichloroethene; (3) polyhydric alco-
hols such as ethylene glycol, sorbitol, pentaerythritol, synthetic  glycerin;
(4) synthetic perfume and flavoring materials such as coumarin, methyl sali-
cylate, saccharin, citral, cintroellal, synthetic geraniol, ionone, terpineol,
and synthetic vanillin; (5) rubber processing chemicals such as accelerators
and antioxidants, both cyclic and acyclic;  (6) plasticizers,  both cyclic and
acyclic, such as esters of phosphoric acid, phthalic anhydride, adipic acid,
lauric acid, oleic acid, sebacic acid, and stearic acid; (7) synthetic tan-
ning agents such as naphthalene sulfonic acid condensates;  (8) chemical
warfare gases; and (9) esters, amines, etc., of polyhydric alcohols and
fatty and other acids.  Tables 1 and 2 list specific products of SIC 2865
and 2869, respectively.

     Products produced by the Plastics/Synthetic Fibers industry are consider-
ably more difficult to define.  Within SIC 2821 important products include:
cellulose plastic materials; phenolic and other tar acid resins;  urea and
melamine resins; vinyl resins; styrene resins; alkyd resins;  acrylic resins;
polyethylene resins;  polypropylene resins;  rosin modified resins;  coumarone-
indene and petroleum polymer resins;  and miscellaneous resins including poly-
amide resins, silicones, polyisobutylenes,  polyesters, polycarbonate resins,
acetal resins, fluorohydrocarbon resins; and casein plastics.   Table 3 lists
important products of SIC 2821.  Important cellulosic man-made fibers (SIC
2823) include:  acetate fibers, cellulose acetate,  cellulose  rayon,  triacetate
fibers, and viscose fibers (see Table 4).  Important noncellulosic synthetic
organic fibers (SIC 2824) include:   acrylic, acrylonitrile, casein,  fluoro-
carbon, linear ester, modacrylic, nylon, olefin, polyester, polyvinyl, and
polyvinylidene fibers.  Table 5 lists important fiber products of  SIC 2824.
                                     -3-

-------
   TABLE 1.   SIC 2865: CYCLIC (COAL TAR) CRUDES, AND CYCLIC INTERMEDIATES,
                DYES, AND ORGANIC PIGMENTS (LAKES AND TONERS)
Acid dyes, synthetic
Acids, coal tar: derived from coal tar
  distillation
Alkylated diphenylandnes, mixed
Alkylated phenol, mixed
Aminoan thr a quinone
Aminozobenzene
Aminozotoluene
Aminophenol
Aniline
Aniline oil
Anthracene
Anthraquinone dyes
Azine dyes
Azo dyes
Azobenzene
Azoic dyes
Benzaldehyde
Benzene hexachloride (BHC)
Benzene,  product of coal tar
  distillation
Biological stains
Chemical  indicators
Chlorobenzene
Chloronaphthalene
Chlorophenol
Chlorotoluene
Coal  tar  crudes, derived from coal
  tar distillation
Coal  tar  distillates
Coal  tar  intermediates
Color lakes and toners
Color pigments, organic: except  animal
  black and bone black
Colors, dry: lakes, toners, or full
  strength organic  colors
Colors, extended (color lakes)
Cosmetic  dyes,  synthetic
Creosote  oil,  product  of  coal  tar
  distillation
Cresols,  product of coal  tar
  distillation
Cresylic  acid,  product  of  coal tar
  distillation
Cyclic  crudes,  coal tar:  product of
  coal  tar  distillation
Cyclic  intermediates
 Cyclohexane
Diphenylamine
 Drug dyes,  synthetic
 Dye (cyclic)  intermediates
 Dyes, food:  synthetic
 Dyes, synthetic organic
 Eosine  toners
 Ethylbenzene
Hydroquinone
Isocyanates
Lake red C toners
Leather dyes and stains, synthetic
Lithol rubine lakes and toners
Maleic anhydride
Methyl violet toners
Naphtha, solvent: product of coal
  tar distillation
Naphthalene chips and flakes
Naphthalene, product of coal tar
  distillation
Naphthol, alpha and beta
Nitro dyes
Nitroaniline
Nitrobenzene
Nitrophenol
Nitroso dyes
Oil, aniline
Oils: light, medium, and heavy-pro-
  duct of coal tar distillation
Organic pigments (lakes and toners)
Orthodichlorobenzene
Paint pigments, organic
Peacock blue lake
Pentachlorophenol
Persian orange lake
Phenol
Phloxine toners
Phosphomolybdic acid lakes and toners
Phosphotungstic acid lakes and toners
Phthalic anhydride
Phthalocyanine toners
Pigment scarlet lake
Pitch, product of coal tar distillation
Pulp colors, organic
Quinoline dyes
Resorcinol
Scarlet 2 R lake
Stains for leather
Stilbene dyes
Styrene
Styrene monomer
Tar, product of coal tar distillation
Toluene, product of coal tar distilla-
  tion
Toluidines
Toluol, product of coal tar distilla-
  tion
Vat  dyes, synthetic
Xylene, product of coal tar distilla-
    tion
Xylol, product of coal tar distilla-
  tion
                                      -4-

-------
 TABLE 2.  SIC 2869:  INDUSTRIAL ORGANIC CHEMICALS, NOT ELSEWHERE CLASSIFIED
Accelerators, rubber processing:
  cyclic and acyclic
Acetaldehyde
Acetates, except natural acetate
  of lime
Acetic acid, synthetic
Acetic anhydride
Acetin
Acetone, synthetic
Acid esters, amines, etc.
Acids, organic
Acrolein
Acrylonitrile
Adipic acid
Adipic acid esters
Adiponitrile
Alcohol, aromatic
Alcohol, fatty: powdered
Alcohol, methyl: synthetic (methanol)
Alcohols, industrial: denatured
  (nonbeverage)
Algin products
Amyl acetate and alcohol
Antioxidants, rubber processing:
  cyclic and acyclic
Bromochloromethane
Butadiene, from alcohol
Butyl acetate, alcohol, and propionate
Butyl ester solution of 2, 4-D
Calcium oxalate
Camphor, synthetic
Carbon bisulfide (disulfide)
Carbon tetrachloride
Casing fluids, for  curing fruits,
  spices, tobacco,  etc.
Cellulose acetate,  unplasticized
Chemical warfare gases
Chloral
Chlorinated solvents
Chloroacetic acid and metallic  salts
Chloroform
Chloropicrin
Citral
Citrates
Citric acid
Citronellal
Coumarin
Cream of tartar
Cyclopropane
DDT, technical
Decahydronaphthalene
Dichlorodifluoromethane
Diethylcyclohexane  (mixed isomers)
Diethylene glycol ether
Dimethyl divinyl acetylene
  (di-isopropenyl acetylene)
Dimethylhydrazine, unsymmetrical
Embalming fluids
Enzymes
Esters of phosphoric, adiplc,
  lauric, oleic, sebacic, and
  stearic acids
Esters of phthalic anhydride
Ethanol, industrial
Ether
Ethyl acetate, synthetic
Ethyl alcohol, industrial (non-
  beverage)
Ethyl butyrate
Ethyl cellulose, unplasticized
Ethyl -chloride
Ethyl ether
Ethyl formate
Ethyl nitrite
Ethyl perhydrophenanthrene
Ethylene
Ethylene glycol
Ethylene glycol ether
Ethylene glycol, inhibited
Ethylene oxide
Fatty acid esters, amines, etc.
Ferric ammonium oxalate
Flavors and flavoring materials,
  synthetic
Fluorinated hydrocarbon gases
Formaldehyde (formalin)
Formic acid and metallic salts
Freon
Fuel propellants, solid: organic
Fuels, high energy: organic
Geraniol, synthetic
Gylcerin, except from fats (synthetic)
Grain alcohol, industrial (non-
  beverage)
Hexame thylenedi amine
Hexamethylenetetramine
High purity grade chemicals, organic:
  refined from technical grades
Hydraulic fluids, synthetic base
Hydrazine
Industrial organic cyclic compounds
lonone
Isopropyl alcohol
Ketone, methyl ethyl
Ketone, methyl isobutyl
Laboratory chemicals, organic
                                     -5-

-------
 TABLE 2.  SIC 2869:
INDUSTRIAL ORGANIC CHEMICALS, NOT ELSEWHERE CLASSIFIED
           (Continued)
Laurie acid esters
Lime citrate
Malononitrile, technical grade
Metallic salts of acyclic organic
  chemicals
Metallic stearate
Methanol, synthetic (methyl alcohol)
Methyl chloride
Methyl perhydrofluorine
Methyl salicylate
Methylamine
Methylene chloride
Monochlorodifluoromethane
Monomethylparaminophenol sulfate
Monosodium glutamate
Mustard gas
Napthalene sulfonic acid condensates
Naphthenic acid  soaps
Normal hexyl  decalin
Nuclear fuels, organic
Oleic acid esters
Organic acid  esters
Organic chemicals, acyclic
Oxala.tes                           .
Oxalic acid and  metallic salts
Pentaerythritol
Perchloroethylene
Perfume materials, synthetic
Phosgene
Phthalates
Plasticizers, organic:  cyclic and
   acyclic
Polyhydric alcohol esters,  amines,  etc.
Polyhydric alcohols
Potassium  bitartrate
Propellants  for  missiles,  solid: organic
Propylene
Propylene  glycol
Quinuclidinol ester  of benzylic acid
Reagent  grade chemicals, organic:
   refined  from technical grades
Rocket  engine fuel,  organic
                     Rubber processing chemicals, organic:
                       accelerators and antioxidants
                     Saccharin
                     Sebacic acid
                     Sillcones
                     Soaps, naphthenic acid
                     Sodium acetate
                     Sodium alginate
                     Sodium benzoate
                     Sodium glutamate
                     Sodium pentachlorophenate
                     Sodium sulfoxalate formaldehyde
                     Solvents, organic
                     Sorbitol
                     Stearic acid salts
                     Sulfonated naphthalene
                     Tackifiers, organic
                     Tannic acid
                     Tanning agents, synthetic organic
                     Tartaric acid and metallic salts
                     Tartrates
                     Tear gas
                     Terpineol
                     Tert-butylated bis (p-phenoxyphenyl)
                       ether fluid
                     Tetrachloroethylene
                     Tetraethyl lead
                     Thioglycolic acid, for permanent wave
                       lotions
                     Trichloroethylene
                     Trichloroethylene stabilized,
                       degreasing
                     Trichlorophenoxyacetic acid
                     Trichlorotrifluoroethane tetrachlorodi-
                       fluoroethane isopropyl alcohol
                     Tricresyl phosphate
                     Tridecyl alcohol
                     Trimethyltrithiophosphite (rocket
                       propellants)
                     Triphenyl phosphate
                     Vanillin, synthetic
                     Vinyl acetate
                                      -6-

-------
          TABLE 3.  SIC 2821:  PLASTICS MATERIALS, SYNTHETIC RESINS,
                        AND NONVULCANIZABLE ELASTOMERS
Acetal resins
Acetate, Cellulose (plastics)
Acrylic resins
Acrylonitrile-butadiene-styrene resins
Alcohol resins, polyvinyl
Alkyd resins
Allyl resins
Butadiene copolymers, containing less
  than 50% butadiene
Carbohydrate plastics
Casein plastics
Cellulose nitrate resins
Cellulose propionate (plastics)
Coal tar resins
Condensation plastics
Coumarone-indene resins
Cresol-furfural resins
Cresol resins
Dicyandiamine resins
Diisocyanate resins
Elastomers, nonvulcanizable (plastics)
Epichlorohydrin bisphenol
Epichlorohydrin diphenol
Epoxy resins
Ester gum
Ethyl cellulose plastics
Ethylene-vinyl acetate resins
Fluorohydrocarbon resins
Ion exchange resins
lonomer resins
Isobutylene polymers
Lignin plastics
Melamlne resins
Methyl acrylate resins
Methyl cellulose plastics
Methyl methacrylate resins
Molding compounds, plastics
Nitrocellulose plastics (pyroxylin)
Nylon resins
Petroleum polymer resins
Phenol-furfural resins
Phenolic resins
Phenoxy resins
Phthalic aIkyd resins
Phthalic anhydride resins
Polyacrylonitrile resins
Polyamlde resins
Polycarbonate resins
Polyesters
Polyethylene resins
Polyhexamethylenedlamlne adipamide
  resins
Polyisobutylenes
Polymerization plastics, except fibers
Polypropylene resins
Polystyrene resins
Polyurethane resins
Polyvinyl chloride resins
Polyvinyl halide resins
Polyvinyl resins
Protein plastics
Pyroxylin
Resins, phenolic
Resins, synthetic: coal tar and
  non-coal tar
Rosin modified resins
Silicone fluid solution (fluid for
  sonar transducers)
Silicone resins
Soybean plastics
Styrene resins
Styrene-acrylonitrile resins
Tar acid resins
Urea resins
Vinyl resins
                                     -7-

-------
               TABLE A.   SIC 2823:   CELLULOSIC MAN-MADE FIBERS
Acetate fibers                            Rayon primary products: fibers,
Cellulose acetate monofilament, yarn,       straw, strips, and yarn
  staple, or tow                          Rayon yarn, made in chemical
Cellulose fibers, man-made                  plants (primary products)
Cigarette tow, 'cellulosic fiber           Regenerated cellulose fibers
Cuprammonium fibers                       Triacetate fibers
Fibers, cellulose man-made                Viscose fibers, bands, strips,
Fibers, rayon                               and yarn
Horsehair, artifical: rayon               Yarn, cellulosic: made in chemical
Nitrocellulose fibers                       plants (primary products)
                                     -8-

-------
       TABLE 5.  SIC 2824:  SYNTHETIC ORGANIC FIBERS, EXCEPT CELLULOSIC
Acrylic fibers
Acrylonitrile fibers
Anidex fibers
Casein fibers
Elastomeric fibers
Fibers, man-made: except cellulosic
Fluorocarbon fibers
Horsehair, artifical: nylon
Linear esters fibers
Modacrylic fibers
Nylon fibers and bristles
Olefin fibers
Organic fibers, synthetic:  except
  cellulosic
Polyester fibers
Polyvinyl ester fibers
Polyvinylidene chloride fibers
Protein fibers
Saran fibers
Soybean fibers (man-made textile
  materials)
Vinyl fibers
Vinylidene chloride fibers
Yarn, organic man-made fiber except
  cellulosic
Zein fibers
                                     -9-

-------
     SIC codes have been established to classify commercial and industrial
establishments by the type of activity in which they are engaged.  The SIC
code system is commonly employed for collection and organization of economic
data (e.g., gross production, sales, number of employees, and geographic
location) for U.S. industries;  establishments are economic units typically
engaged in a single or dominant type of economic activity for which an indus-
try code is applicable.

     A plant is assigned a primary SIC code corresponding to its primary
activity, which is the activity producing its primary product or group of
products.  The primary product is the product having the highest total annual
shipment value.  The secondary products of a plant are all products other
than the primary products.  Frequently in the chemical industry a plant may
produce large amounts of a low-cost chemical but be assigned another SIC code
because of lower-volume production of a high-priced specialty chemical.  Many
plants are also assigned secondary, tertiary, or lower order SIC codes corres-
ponding to plant activities beyond their primary activities.  The inclusion
of plants with a secondary or lower order SIC code produces a list of plants
manufacturing a given class of industrial products but also includes plants
that produced only minor (or in some cases insignificant) amounts of those
products.  While the latter plants are part of an industry economically,
their inclusion may seriously distort the description of the industry's
wastewater production and treatment, unless the wastewaters can be segregated
by SIC codes.

     For some petroleum refineries and pharmaceutical manufacturers, process
wastewater from some synthetic organic chemical products are specifically
regulated under the Petrochemical and Integrated Subcategories of the Petroleum
Refining Point Source Category (40 CFR 419, Subparts C and E) or the Chemical
Synthesis Products Subcategory of the Pharmaceuticals Manufacturing Point
Source Category (40 CFR 439, Subpart C).  The petroleum reftnefTes"and pharma-
ceutical manufacturers that produce organic chemical products that generate
                                     -10-

-------
process wastewaters treated in combinations with petroleum refinery or pharma-
ceutical manufacturing wastewaters, respectively, should consider any such
organic chemical products as non-OCPSF products.  However, if petroleum
refineries or pharmaceutical manufacturers produce organic chemical products
that generate process wastewaters that are treated in a separate wastewater
treatment system, these facilities should consider any such organic chemical
product as an OCPSF product.  Organic chemical compounds that are produced
solely by extraction from natural materials (e.g., plant and animal sources)
or by fermentation processes are not considered to be OCPSF products.   Thus,
ethanol derived from natural sources (SIC 28095112) is not considered to be
an OCPSF industry product; ethanol produced synthetically (hydration of
ethene) jls_ an OCPSF industry product.   Similarly, cellophane (SIC 3079)
which is produced by extrusion of viscose (chemically derived from the natural
polymer cellulose) is being considered by the Agency to be an OCPSF industry
product.  (Both rayon and cellophane are manufactured by similar processes,
differing only in the extruded form.)   Cellophane would be placed in the
Rayon subcategory.

     Certain products of SIC groups other than 2865, 2969, 2821, 2823, and
2824 are considered to be OCPSF products.  Benzene, toluene,  and mixed xylenes
manufactured from purchased refinery products in SIC 29110582 (in contrast to
benzene, toluene, and mixed xylenes manufactured in refineries—SIC 29110558)
are considered to be OCPSF products (see Table 6).   Similar considerations
apply to aliphatic hydrocarbons manufactured from purchased refinery products—
SIC 29116324 (see Table 7).
                                     -11-

-------
   TABLE 6.  OCPSF CHEMICAL PRODUCTS LISTED AS SIC 29110582 PRODUCT  CODES



                              Benzene

                              Cresylic acid

                              Cyclopentane

                              Naphthalene

                              Naphthenic Acid

                              Toluene

                              Xylenes, Mixed

                              C9  Aromatics
SOURCE:   1982 Census of Manufactures and Census  of  Mineral Industries.
         Numerical List of Manufactured and Mineral Products.   U.S.  Depart-
         ment of Commerce, Bureau of the Census, 1982.
                                     -12-

-------
    TABLE 7.  OCPSF CHEMICAL PRODUCTS LISTED AS SIC 29116324 PRODUCT CODES
C2 Hydrocarbons
Acetylene
Ethane
Ethylene
C3 Hydrocarbons
Propane
Propylene
C4 Hydrocarbons
Butadiene and butylene fractions
1,3-Butadiene, grade for rubber
n-Butane
Butanes, mixed
1-Butene
2-Butene
1-Butene and 2-butene, mixed
Hydrocarbons, C4, fraction
Hydrocarbons, C4, mixtures
I'sobutane (2-Methylpropane)
Isobutylene (2-Methylpropene)
C4 Hydrocarbons, all other
Amylenes•
Dib'utanized aromatic concentrate'
C5 Hydrocarbon, mixtures
Isopentane (2-Methylbutane)
Isoprene (2-Methyl-l,3-butadiene)
n-Pentane
1-Pentene
Pentenes, mixed
Piperylene (1,3-Pentadiene)
C5 Hydrocarbons, all other
C6 Hydrocarbons
Diisopropane
Hexane
Hexanes, mixed
Hydrocarbons, C5-C6, mixtures
Hydrocarbons, C5-C7, mixtures
Isohexane
Methylcyclopentadiene
Neohexane  (2,2-Dimethylbutane)
C6 Hydrocarbons, C6, all  other
n-Heptane
Heptenes,  mixed
 Isoheptanes
C7 Hydrocarbons
C8 Hydrocarbons
Diisobutylene (Diisobutene)
n-Octane
Octenes, mixed
2,2,4-Trimethylpentane (Isooctane)
C8 Hydrocarbons, all other
C9 and above Hydrocarbons
Dodecene
Eicosane
Nonene (Tripropylene)
Alpha Olefins
Alpha olefins, C6-C10
Alpha olefins, Cll and higher
n-Paraffins
n-Paraffins, C6-C9
n-Paraffins, C9-C15
n-Paraffins, C10-C14
n-Paraffins, C10-C16
n-Paraffins, C12-C18
n-Paraffins, C15-C17
n-Paraffins, other
Hydrocarbons, C5-C9, mixtures
Polybutene
Hydrocarbon Derivatives
n-Butyl mercaptan (1-Butanethiol)
sec-Butyl mercaptan (2-Butanethiol)
tert-Butyl mercaptan (2-Methyl-
   2-propanethiol)
Di-tert-butyl disulfide
Diethyl sulfide (Ethyl sulfide)
Dimethyl sulfide
Ethyl mercaptan (Ethanethiol)
Ethylthioethanol
n-Hexyl mercaptan (1-Hexanethiol)
Isopropyl mercaptan (2-Propanethiol)
Methyl ethyl sulfide
Methyl mercaptan (Methanethiol)
tert-Octyl mercaptan (2,4,4-Trimethyl-
   2-pentanethiol)
Octyl mercaptans
Thiophane (Tetrahydrothiophene)
Hydrocarbon derivatives:  all other
   hydrocarbon derivatives
Hydrocarbons, C9 and above, all other,
   including mixtures
 SOURCE:  1982 Census of Manufactures and Census  of Mineral  Industries.
          Numerical List of Manufactured and Mineral Products.  U.S. Depart-
          ment of Commerce, Bureau of the Census,  1982.
                                      -13-

-------
                            2.  SUBCATEGORIZATION

2.1  INTRODUCTION

     Sections 304(b)(l)(B),304(b)(2)(B),  and 304(b)(4)(B) of the Clean Water
Act require EPA to consider certain factors in establishing effluent limi-
tations guidelines based on the best practicable control technology (BPT),
best conventional pollutant control technology (BCT), and best available
technology (BAT).  Factors to be considered include:  the age of equipment and
facilities involved; the process employed; the engineering aspects of the
application of various types of control techniques; process changes; the cost
of achieving such effluent reduction; nan-warter quality environmental impact
(including energy requirements); and such other factors as the Administrator
deems appropriate.  The purpose of such consideration is to determine whether
these industries (or segments of these industries) exhibit unique wastewater
characteristics which support the development of separate national effluent
limitations guidelines.  Thus, major industry groups may require division into
smaller homogeneous groups that account for the individual characteristics of
different facilities.

     In order to consider subcategorization on the basis of the factors listed
above, it is necessary to demonstrate that significant differences among the
plant wastewater quality or differences in the treatability of plant
wastewaters exist.  The Organic Chemicals and Plastics/Synthetic Fibers
Industries (OCPSF) might be subcategorized into groups with significant
differences in terms of influent and effluent quality based on the following
factors:
                                     -14-

-------
     •  Products produced
     •  Processes employed and process changes
     •  Facility size (as measured by plant production
        and/or sales)
     •  Geographical location
     •  Age of equipment and facilities
     •  Engineering aspects of control technologies
     •  Flow
     •  Cost of achieving effluent reduction
     •  Non-water quality environmental impacts.

     Each of these factors have been evaluated to determine if subcate-
gorization is necessary or feasible.  The subcategories proposed for the
OCPSF industries are based primarily upon the concentrations of conventional
pollutants in effluent wastewaters.  Both engineering and statistical analyses
were performed to determine whether pollutant data supported subcategorization;
statistically significant test results implied that there were differences in
wastewater quality between groups of plants that suggested a need for
subcategorization.  These analyses are discussed in detail in the following
sections.

     On March 21, 1983,  the Agency proposed OCPSF effluent guidelines in
which the industry was subcategorized based on products produced:

     •  Plastics Only; and
     •  Not Plastics Only (includes organics plants and
        plants which manufacture plastics and organics).

     With the "Not Plastics Only" category, plants were subcategorized
based on generic process chemistry:
                                     -15-

-------
     •  Plants with oxidation processes
     •  Plants with one of the following generic processes
        (Type I)
        - Peroxidation
        - Acid Cleavage
        - Condensation
        - Isomerization
        - Esterification
        - Hydroacetylation
        - Hydration
        - Alkoxylation
        - Hydrolysis
        - Carbonylation
        - Hydrogenation
        - Neutralization,
     •  Plants with none of the above generic processes.

Plants we're further subdivided into normal and low flow plants, a factor
added for the determination of equitable effluent discharge levels.  Industry
provided comments on this subcategory scheme, which beyond stating general
displeasure with the proposed subcategories also discussed:  the complexity
and confusing nature of the subcategories; the relative size of between and
within subcategory variability; and the advantage of focusing attention on
effluent BOD.

     The Agency agrees that the proposed subcategories were complex and
confusing, not only to industry, but to permit writers as well.  In order to
solve this problem, the Agency has decided to focus its attention on OCPSF
products produced and not on generic processes.  By focusing on products
produced, the Agency hopes to emphasize the inherent economic structures of
the industry and the basic wastewater similarities of plants with similar
products.  It is clear, however, that the processes found at a plant are
dictated by the products produced by the facility.
                                     -16-

-------
     Industry comments also took exception to the statistical technique used
to analyze the data for subcategorization.  In particular, these comments
emphasized that the proposed subcategories had greater variability within a
subcategory than between subcategories, a trait which is indicative of a
poorly defined subcategory.  In order to remedy this problem, the Agency has
used both analysis of variance (ANOVA) and Spearman's Rank Correlation to
measure the efficacy of a subcategory scheme.

     Finally, industry comments discuss the value of effluent BOD as a
parameter of interest in determining subcategories.   In particular, page 38
of the Chemical Manufacturers Association's comments states:

     "a.  Between-Plant Variability Is Greater Than Between-Subcategory
          Variability	
          EPA...The Agency failed, however, to use this statistical approach
          (referring to Terry-Hoeffding test) with median effluent BOD levels
          for each group.  Since the establishment of effluent levels which
          are technically achievable by each plant in a subcategory is a
          legal requirement of the guideline development process, it is not
          appropriate for the Agency to ignore effluen-t levels in the
          subcategorization analysis."  (emphasis added)

The Agency agrees that effluent BOD quality is an important factor in
determining suitable OCPSF subcategories.

     Wastewater load (WL) was selected as  the dependent variable to be used
to evaluate the significance of all of the subcategorization factors discussed
in this section.   WL for the purposes of subcategorization is a measure of
BOD, flow, and size and was used as the basis for comparison to the other
eight subcategorization factors.

     Two major statistical techniques were used to determine an appropriate
subcategorization scheme for the OCPSF industry:   analysis of—variance (ANOVA)
(Appendix A) and the Spearman rank correlation (Appendix B).   The Spearman
rank correlation is nonparametrie, thus making the fewest assumptions about
the nature of the underlying data.  The ANOVA is  nonparametric in the
                                     -17-

-------
calculation of the variance but not in the use of underlying probabilities to
test the adequacy of a particular hypothesis.   This does not offer too much
of a problem since the test is typically robust (relatively insensitive to
modest deviations in the underlying distribution from normality); though the
probabilities might change, the probabilities still give a good picture of
the quality of the subcategorization.

     The Spearman rank correlation was used to determine the existence of any
relationships among the factors which must be considered for subcategorization
of the OCPSF industry.

     Nine factors were examined for technical significance in the development
of the proposed subcategorization scheme:

     •  Products produced
     •  Processes employed and process changes
     •  Facility size (as measured by plant production
        and/or sales)
     •  Geographical location
     •  Age of equipment and facilities
     •  Engineering aspects of control technologies
     •  Flow
     •  Cost of achieving effluent reduction
     •  Non-water quality environmental impacts.

In general, the proposed subcategorization is based primarily on significant
differences in wastewater characteristics, since many of the other eight factors
could not be examined in appropriate technical and statistical depth due to
lack of specific or appropriate data.   The ideal data base (for subcategorization
                                     -18-

-------
analysis) would include raw wastewater and final effluent pollutant data for
facilities which employ only one generic manufacturing process or multiple-
product plants which segregate and treat each process raw waste stream
separately.  In this manner, each factor could be evaluated independently.
Available information, however, consists of historical data collected by
individual companies, primarily for the purpose of monitoring the performance
of end-of-pipe wastewater treament technology and compliance with NPDES permit
limitations.  Variations in wastewater characteristics were therefore utilized
to evaluate the impact of the other eight factors on subcategorization.

     The OCPSF 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.  Each plant's overall raw wastewater characteristics are affected
by all of the production processes operating at the site at any given time.
The contribution of each production process to the raw wastewater characteristics
(e.g., BOD and toxic pollutant concentration) was not generally reported nor
could they be accurately separated from all of the other site-specific
processes that generate wastewaters.   To overcome this difficulty, a combination
of both technical and statistical methodologies was used to evaluate the
significance of each of the subcategorization factors;  that is,  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 subcategorization.
These technical/statistical evaluations of the nine factors are presented below.

2.2  SUBCATEGORIZATION BASED ON PRODUCT GROUPS

     The purpose of subcategorization is the division of the OCPSF industry
into smaller homogeneous groups that  account for the individual characteristics
of different facilities.  The OCPSF industry (as defined by EPA)  is  recognized
to comprise several industry groups:
                                     -19-

-------
     •  Organic Chemicals (SIC 2865/2869/2911)
     •  Plastic Materials and Synthetic Resins (SIC 2821)
     •  Cellulosic Man-made Fibers (SIC 2823).

Vertical integration of plants within these industries is common, however,
blurring distinctions between organic chemical plants and plastics/synthetic
fibers plants.  As a practical matter, the OCPSF industry is divided among
three types of plants:

     •  Plants manufacturing only organic chemicals
        (SIC 2865/2869/2911)
     •  Plants manufacturing only plastics and synthetic
        materials (SIC 2821/2823/2824)
     •  Integrated plants manufacturing both organic
        chemicals and plastics/synthetic materials
        (SIC 2865/2869/2911/2821/2823/2824).

Each type of plant is unique not only in terms of product type (e.g., plastics)
but also in terms of process chemistry and engineering.  Using raw materials
provided by organic chemical plants, plastic plants employ only a small subset
of the chemistry practiced by the OCPSF industry to produce a limited number
of products (approximately 200).  Product (reactant) recovery from process
wastewaters in plastic plants is, in general, possible, thus lowering raw BOD
loadings.  On the other hand, plants producing organic chemicals utilize a
much larger set of process chemistry and engineering to produce approximately
25,000 products; process wastewaters from these plants are (in general) not
as amenable to product recovery and are generally higher in raw BOD and
priority pollutant loadings.

     Further divisions are possible within these broad groupings.  Plastic
materials and synthetic resins manufacturers can be subdivided—tfito'thermo-
plastic materials (SIC 28213) producers and thermosetting resin (28214)

                                     -20-

-------
producers.  Rayon manufacturers and synthetic organic fiber manufacturers are
also both unique in terms of process chemistry and engineering.

     The Organic Chemicals industry produces many more products than does the
Plastics/Synthetic Fibers industry and is correspondingly more complex.  While
it is indeed possible to separate this industry into product groups, the
number of such product groups is large.  Moreover, with few exceptions, plants
produce organic chemicals from several product groups and thus limit the
utility of such a scheme.

     An alternative to a product-based scheme is a scheme based on the type
of manufacturing conducted at a plant.  Large plants producing primarily
commodity chemicals (the basic chemicals of the industry, e.g., ethylene,
propylene, benzene) comprise the first group- of plants.   A second tier of
plants comprises plants that produce high-volume intermediates (bulk chemicals),
Plants within this tier typically utilize the products of the commodity
chemical plants (first tier plants) to produce more structurally complex
chemicals.  Bulk chemical plants are generally smaller than those in the
first group but still may produce several hundred million pounds of chemicals
per year (e.g., aniline, methylene dianiline, toluene diisocyanate).   The
third group comprises those plants that are devoted primarily to manufacture
of specialty chemicals—chemicals intended for a particular end use (e.g.,
dyes and pigments).  Specialty chemical plants use the products of the
commodity and bulk chemical plants as raw materials.   Generally, specialty
chemicals are more complex structurally than either commodity or bulk chemicals.
Plants within this group tend to be much smaller,  producing tens of millions
of pounds of chemicals per year.

     The Agency has grouped the products of the OCPSF industries into seven
categories.  These product groups are:
                                     -21-

-------
     •  Rayon fibers (Census product code 2823)
     •  Other fibers (Census product codes 2823 and 2824)
     •  Thermosetting resins (Census product code 28214)
     •  Thermoplastic resins (Census product code 28214)
     •  Organic chemicals (Census product codes 2865, 2869, and 2911).

The organic chemicals group has been further divided into three groups of
chemicals or chemical groups depending upon the total 1980 production volume
of a chemical.   These subgroups are:

     •  Commodity Chemicals - organic chemicals produced in amounts greater
        than one billion pounds per year.  This list includes 37 products or
        product groups.
     •  Bulk Chemicals - organic chemicals produced in amounts less than one
        billion pounds per year but more, than 40 million pounds per year.
        This list comprises 221 products or product groups.
     •  Specialty Chemicals - all organic chemicals not defined as Commodity
        or Bulk Chemicals.

     Based on the information submitted to EPA as a result of the 1983 "308"
Questionnaire,  the Agency has compiled lists of chemicals and chemical groups
by the industry segments discussed above.  These industrial segments are
integral parts of establishing and defining subcategories.  Table I lists
rayon products.  Table II lists other fiber products.  Thermoplastic resin
products and thermoplastic resin groups are listed in Table III.  Thermosetting
resin products and thermosetting resin groups are listed in Table IV.  Table V
lists commodity organic chemicals and chemical groups.  Bulk organic chemicals
and chemical groups are listed in Table VI.  Table VII lists- specialty organic
chemicals and chemical groups.  Tables I - VII are in Appendix C.

     It should be emphasized that the placement of products and product groups
shown in Tables I - VII is not expected to be static:  specific chemicals and
chemical groups may (and are expected to) change classifications with time.
                                     -22-

-------
Furthermore, closely related chemical products may in some cases be in
different subcategories because of production volume.  Benzene, toluene, and
xylene, for example, are defined as commodity chemicals; BTX (a product which
is a mixture of benzene, toluene, and xylene) is defined as a bulk chemical
product.

     Based on these product groups, the Agency has identified eight subcategories.

     •  Rayon—plants that produce rayon products
     •  Fibers—plants that produce fiber products or
        plants which produce organics and fiber products
     •  Thermosets—plants which manufacture thermosets
        or those plants that produce organic and ther-
        moset products
     •  Thermoplastics—plants that make thermoplastic
        products
     •  Thermoplastics and Organics—plants that
        produce organics and thermoplastic products
     •  Commodity—plants producing predominantly
        commodity chemicals
     •  Specialty—plants producing predominantly
        specialty chemicals
     •  Bulk Organics—plants whose production is
        neither commodity nor specialty organic products.

Plants are assigned to a subcategory based on the percent of total  production
of a product group.  Plants that produce only organic chemicals or  groups of
organic chemicals are assigned to a subcategory based on the relative  amounts
of commodity, bulk, and specialty organic chemicals produced.   Because
relatively few OCPSF plants produce only one product group,  a variety  of pro-
duction criteria were considered for subcategorizatiou of OCPSF plants.
Within product categories rayon fibers,  other fibers, thermosetting resins,
thermoplastic resins, and thermoplastic resins and organic chemicals),
                                     -23-

-------
four production criteria for placement of a plant into a subcategory were
statistically evaluated using analysis of variance:
     100 percent production of a product category;
      95 percent production of a product category;
      90 percent production of a product category; and
      85 percent production of a product category.
For plants placed  in the organic chemicals product category, four production
criteria were also statistically evaluated for commodity and specialty
chemicals and chemical groups.   These criteria are:

      95 percent commodity (specialty) chemical production;
      75 percent commodity (specialty) chemical production;
      60 percent commodity (specialty) chemical production;  and
      50.percent commodity (specialty) chemical production.

To determine the best combination of production rules the Agency used Analysis
of Variance (ANOVA).

     Table 8 gives the results of an ANOVA to determine which of the hypothesized
subcategory combinations is adequate.  The analysis focuses  on four variables—
influent BOD, effluent BOD, flow, and total production (size).  A good
subcategory scheme would magnify the variance between groups relative to the
variance within groups.  A measure which helps interpret how much larger the
between variance is relative to the within variance is the probability that
the ratio is greater than 1, listed in Table 8.  Thus, the closer this
probability is to 1, usually greater than 0.95, the better the subcategori-
zation.

     BOD is a measure of the wastewater's organic content.  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.  Based on the ANOVA, influent BOD is not significant

                                     -24-

-------
as a variable for subcategorizing the OCPSF industry, since  the  ratio  of
between to within is less than 1 (Table 8).  However, effluent BOD is  a
significant variable for all combinations of productions less than 100%.

     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 contact steam.
Wastewater flow does not include storm water, noncontact 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.

     The subcategorization is very effective when flow is the variable of
interest (Table 8).   The probability that the ratio of. between-to within
variances is greater than 1 is nearly 1 in all cases.  However,  upon
examining the table, combinations with probability of significance greater
than 0.999 seem to cluster together.  These combinations are production groups
95% and 90%.  Thus,  the combinations chosen are optimal for flow discrimination
at OCPSF plants, a variable which relates to the size and construction costs
of a plant's wastewater treatment system.

     Production, in this analysis,  is measured in million pounds per year and
includes all OCPSF products.   A subcategorization that discriminates well on
production implies that size of plant has been successfully included as a
factor in the analysis.  Thus,  plants of similar economic viability are
grouped together.   The analysis index shows that the subcategories chosen
effectively group production into homogeneous groups relative to the inherent
variability of production throughout the industry (Table 8).   In fact,
production (size)  is the best variable in substantiating the subcategories.
The probability that the ratio of variances is significantly different from 1
is 0.9999+ for most  combinations.  All combinations do well with only groups
with percent commodity equal to 95% having a probability less than 0.9999+ for
                                     -25-

-------
most combinations.  All combinations do well with only groups with percent
commodity equal to 95% having a probability less than 0.9999+ (even here the
probability is 0.999+).  The combination with the greatest probability of
significance (underlined in Table 8) is 95% organic chemical production and
75% commodity chemical production.   OCPSF subcategories by product/product-
groups are shown in Table 9.
                                     -26-

-------
TABLE 8.  SIGNIFICANCE LEVELS FOR ANOVA FOR VARIOUS PRODUCTION
          CRITERIA vs. SELECTED DEPENDENT VARIABLES
PRODUCTION CRITERIA
% PRODUCT % COMMODITY
CATEGORY (SPECIALTY)
100 50
60
75
95
95 50
60
75
95
90 50
60
75
95
85 50
60
75
95
SIGNIFICANCE OF
INFLUENT
BOD
.63
.64
.77
.77
.38
.38
.53
.50
.46
.46
.46
.45
.52
.52
.57
.49
EFFLUENT
BOD
.84
.86
.87
.93
.96
. .97
.97
.98
.96
.97
.97
.98
.99
.99
.99
.99
DEPENDENT

FLOW
.999
.999
.999
.999
.9996
.9995
.9995
.9994
.9996
.9996
.9996
..9996
.9983
.9982
.998
.998
VARIABLES
TOTAL OCPSF
PRODUCTION
.9999
.9999
.9998
.9994
.9999
.9999
.9999
.9994
.9999
.9999
.9999
.9991
.9999
.9999
.9999
.9991
                             -27-

-------
8
cd
H
pa

en
CM

o
i
§
Sk
o
Q

s
Cu
Cd
O
w
OH
O\

Cd

so
25
o
M
H
O
§
CU
            Cd

            5

            Cd
>< en
H cj J
1 * ' rf**
M M <3
•5 z cj
H •< M
CJ CJ 33
Cd Od Cd
PH O 33
tn cj


en
CJ J
M 52
s*s z cj
i ^» wj
H^ ^j t-H
3 CJ S
5 2 Cd
0 33
CJ




s* en
H 0 J
M H <
-i
ae
o
CJ
u
<
CJ
cc

e7































i/






























































u-i
fl\
Wi
A|








m
V

1
V






















u










































in



I/
in
r~
s
-\
CN
V >>










V
m
en
Al


m

\







•>
u
/













i/
m
ON
A|








•^
en
m
V

1 u

•>
V  O\








A|/\|







in
m ON














M










4J
,_J
T^H
JJ i-4
Of** _
TO
B -H
O
>w eu
•H p.
en
\j
•A
>H W
3 O
pa c

M













co -o in
« G CN
T3 V
CU >,
1-1 w
m >4-i -H
r*. IH "O
CO O
A| we
1 « 0






•







iH O
CJ CJ




































in m
V V
m
in in v

V V

cr> , m m
>v t
/

m
r


"' N


cj\ m m
^1
• v
•
/ V




/






















^—


























t»s
-H -0
C C
O CO CO CO CO
>\ u u u
i-( T3 CO CO -H -H -H
C C CO 4J4JC0 U 4J C
O « O CO 0) CU O CO COCO
T-I u co co i-( to cg&o >>u u >-. o
CO CO C OIOOC iH rH U 4.1-H -H 4J-H
M U CO CO 8 B CO O. O.O -H C C rH C
CO CU CD 00 OV4U&0 OX O T3 CO CO CO CO
C UjajQb S 0) 0) lJ S rH a T3 O 60 00 -HOC
O CU-H-HO U j= j: O MC iJ C 8 )-> Ml* Ul-i
>-, JS PL, pt, ry ^, f_i CU O 0) CO SO rHO CU O
co -H j= j: j: o 3 a.
Olfa H HHCjoqcn
                                                  -28-

-------
2.3  PROCESSES EMPLOYED AND PROCESS CHANGES

     An important characteristic of the Organic Chemicals and Plastics/Syn-
thetic Fibers industry is the degree of vertical and horizontal  integration
between manufacturing units at individual plants.  Since the bulk of the
basic raw materials is derived from petroleum or natural gas, many of  the
commodity organic chemical manufacturing plants are either part  of or  contiguous
to petroleum refineries; most of these plants have the flexibility to  produce
a. wide variety of products.  Relatively few organic manufacturing facilities
are single product/process plants unles-s the final product is near the
fabrication or consumer product stage.  Additionally, many process units are
integrated in such a fashion that amounts of related products can be varied
as desired over wide ranges.  There can be a wide variation in the size
(production capacity) of the manufacturing complex as well as diversity of
products and processes.  In addition to the variations based on  the design
capacity and design product mix, economic and market conditions  of both the
products and raw materials can greatly influence the production  rate and
processes employed even on a relatively short-term basis.

2.3.1  Raw Materials

     Synthetic organic chemicals are derivatives of naturally-occurring
materials (petroleum, natural gas, and coal) which have undergone at least
one chemical reaction.   Given the large number of potential starting materials
and chemical reactions  available to the industry, many thousands of organic
chemicals are produced by a potentially large number of basic processes having
many variations.   Similar considerations also apply to the Plastics/Synthetic
Fibers industry although both the number of starting materials and processes
are more limited.  Both organic chemicals and plastics are commercially
produced from six major raw material classifications:   methane,  ethane,
propene, butanes/butenes, and higher aliphatic and aromatic compounds.   This
list can be expanded to eight by further defining the aromatic compounds to
include benzene,  toluene, and xylene.   These raw materials are derived from

                                     -29-

-------
natural gas and petroleum, although a small portion of the aromatic compounds
is derived from coal.

     Using these eight basic raw materials (feedstocks) derived from the
Petroleum Refining industry, process technologies used by the Organic Chemicals
and Plastics/Synthetic Fibers industries lead to the formation of a wide
variety of products and intermediates, many of which are produced from more
than one basic raw material either as a primary reaction product or as a co-
product.  Furthermore, the reaction product of one process is frequently used
as the raw material for a subsequent process.  The primary products of the
Organic Chemicals industry, for example, are the raw materials of the
Plastics/Synthetics industry.  Furthermore, the reaction products of one process
at a plant are frequently the reactants for other processes at the same plant,
leading to the categorization of a chemical as a product in one process and a
reactant in another.  This ambiguity continues until the manufacture of the
ultimate end product, normally the fabrication or consumer stage.  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.

     A second characteristic of the OCPSF industry which makes subcategorization
by raw material difficult is the high degree of integration in manufacturing
units.  Most OCPSF plants use several of the eight basic raw materials derived
from petroleum or natural gas to produce a single product.  The choice of
which raw material to choose as a basis for subcategorization is therefore
ambiguous.  Moreover, relatively few organic chemical manufacturing facilities
are single product/process plants unless the final product is near the
fabrication or consumer product stage.  Therefore, subcategorization based on
eight raw materials would necessitate the creation of 256 subcategories;
subcategorization based on six raw materials would necessitate creation of 64
subcategories.  Because of the integrated nature of the OCPSF indusry, it may
be concluded that subcategorization by raw materials is not feasible for the
following reasons:
                                     -30-

-------
     •  The OCPSF industry is made up primarily of
        chemical complexes of various sizes and complexity.
     •  Very little, if any, of the total production is repre-
        sented by single raw material plants.
     •  The raw materials used by a plant can be varied widely
        over short time spans.
     •  The conventional and nonconventional wastewater pollu-
        tant parameter data gathered for this study were not
        collected on a product/process basis, but rather
        represent the mixed end-of-pipe plant wastewaters.

2.3.2  Process Chemistry

     Chemical and plastics manufacturing plants share an important characteristic:
chemical processes never convert 100 percent of the feedstocks to the desired
products, since the chemical reactions/processes never proceed to 'total
completion.  Moreover, because there is generally a variety of reaction
pathways available to reactants, undesirable by-products are often generated.
This produces a mixture of unreacted raw materials, products, and by-products
that must be separated and recovered by operations that generate residues
with little or no commercial value.   These losses appear in process wastewater,
in air emissions, or directly as chemical wastes.  The specific chemicals
that appear as losses are determined by the feedstock and the process chemistry
imposed upon it.  The different combinations of products and production
processes distinguish the wastewater characteristics of one plant from those
of another.

     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 solvents);  and (3)  final purification of the
                                     -31-

-------
wastewaters:  pollutants arise from the first step as a result of alternate
reaction pathways; separation of reactants and products from a reaction
mixture is imperfect and both raw materials and products are typically found
in process wastewaters.

     Though there is strong economic incentive to recover both raw materials
and products, there is little incentive to recover the myriad of by-products
formed as the result of alternate reaction pathways.  An extremely wide
variety of compounds can form within a given process.  Typically, chemical
species do not react via a single reaction pathway; depending on the
nature of the reactive intermediate, there is a variety 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 neve.r to total exclusion.  The direction of reactions in a
process sequence is controlled through careful adjustment and maintenance of
conditions in the reaction vessel.  The physical condition of species present
(liquid, solid, or gaseous phase), conditions of temperature and pressure,
the presence of solvents and catalysts, and the configuration of process
equipment dictate the kinetic pathway by which a particular reaction will
proceed.

     Therefore, despite the differences between individual chemical production
plants, all transform one chemical to another by chemical reactions and
physical processes.  Though each transformation represents at least one
chemical reaction, production of virtually all the industry's products can be
described by one or more of 55 generalized chemical reactions/processes.
Subjecting the basic feedstocks to sequences of these 55 generic processes
produces most commercial organic chemicals and plastics.

     Pollutant formation is dependent upon both the raw material and process
chemistry, and broad generalizations regarding raw wasteater loads based solely
on process chemistry are difficult at best.  Additionally, OCPSF typically employs
unique combinations of generic processes to produce organic chemicals and
plastics/synthetic fibers that tend to blur any distinctions possible.

                                     -32-

-------
2.3.3  Product/Processes

     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 product and the generic process by
which it is produced is called a "product/process,"  There are, however,
thousands of product/processes within the OCPSF industries.  Data gathered
on the nature and quantity of pollutants associated with the manufacture of
specific products within the Organic Chemicals and Plastics/Synthetic Fibers
industries have been indexed for 176 product/processes.

     Organic chemical plants vary greatly as to the number of products
manufactured and processes employed, and may be either vertically or horizontally
integrated.   One representative complex which .is both vertically and horizontally
integrated may produce a total of 45 high volume products with an additional
300 lower volume products.  In contrast, a specialty chemicals plant may
produce a total of 1,000 different products with 70 to 100 of these being
produced on any given day.

     On the other hand, specialty chemicals may involve several chemical
reactions and require a fuller description.  For example,  preparation of
toluene diisocyate from toluene (a. commodity chemical) involves three
synthesis steps—nitration, hydrogenation, and phosgenation.   This example,
in fact, is relatively simple; manufacture of other specialty chemicals  is
more complex.   Thus, as individual chemicals become further removed from the
basic feedstocks of the industry, more processes are required to produce them.

     In contrast to organic chemicals, plastics and synthetic fibers  are
polymeric products.  Their manufacture directly utilizes only a small subset
of either the chemicals manufactured or processes used within the Organic
Chemicals industry.  Such products are manufactured by polymerization processes
in which organic chemicals (monomers) react to form macromolecules or polymers,
                                     -33-

-------
composed of thousands of monomers units.  Reaction conditions are designed to
drive the polymerization as far to completion as practical and to recover
unreacted monomer.  Unless a solvent is used in the polymerization, by-products
of polymeric product manufactures are usually restricted to the monomer(s) or
to oliomers (a polymer consisting of only a few monomer units).  Because the
mild reaction conditions generate few by-products, there is economic incentive
to recover the monomer(s) and oliomers for recycle; the principal yield loss
is typically scrap polymer.  Thus, smaller amounts of fewer organic chemical
co-products (pollutants) are generated by the production of polymeric plastics
and synthetic fibers than are generated by the manufacture of the monomers
and other organic chemicals.

     There are several ways by which the Organic Chemicals and Plastics/Synthetic
Fibers industry might be potentially subcategorized on the basis of process
chemistry.  For example, subcategorization could Se based upon the particular
combination of product/processes in use at individual plants.  Individual
plants within these industries, however, are unique in terms of the numbers
and types of product/processes employed and raw wastewater quality.  As plants
are made subject to effluent limitations or standards, pretreatment and treat-
ment trains are uniquely designed and operated to meet pollutant removal
criteria; although raw wastewater quality may differ greatly among plants,
similar removal efficiencies may be obtained.  Thus, a scheme that would
subcategorize plants based on raw wastewater quality alone would unnecessarily
separate plants that are appropriately covered by a single set of uniform re-
quirements.  Product/process is inappropriate as a basis for subcategorization.

2.4  FACILITY SIZE

     The Agency has chosen total OCPSF production to define facility size.
Sales volume, number of employees, area of plant site, plant capacity, and
production rate have been chosen by others as a measure of facility size.  In
exploring the suitability of using alternate measures, the Agency concluded
that none of the alternative definitions were appropriate to describe facility
size for the purposes of subcategorization analysis.  Total OCPSF production,
however, is adequately grouped by the proposed subcategories based on products
                                     -34-

-------
or product groups manufactured by facility (see Table 9).  Spearman rank
correlations are used to further search for possible secondary effects of
facility size within a subcategory.

     As discussed in Appendix B, the Spearman rank correlation is a nonparametric
statistical technique that measures the association between two variables,
i.e., total OCPSF production and influent BOD and TSS individually.  It should
be noted that the Spearman rank correlation is an overly sensitive technique
for determining association and that each correlation significantly greater
than zero may have no practical implications on the overall regulations.
Therefore, the Agency feels this technique will not miss any hidden relationships.

     Table 10 gives the Spearman rank correlation coefficients (rank) for size
when compared with influent BOD and influent TSS.  Beneath each rank is the
level of significance for the test, that is, whether the given rank is
significantly different from zero.   Also in this-table is the sample size, •
the number of plants where data existed for both variables (e.g.,  influent
BOD and size).  The Rayon row of Table 10 shows N/A (not applicable) beneath
both ranks.  In both cases, the sample size of two is insufficient to measure
significance, since for rank correlations a sample size of two yields a
correlation of either +1 or -1 as an artifact of the calculations.
                                     -35-

-------
             TABLE 10.  SPEARMAN RANK CORRELATION COEFFICIENTS  (R)
                    FOR RAW WASTE BOD AND TSS VERSUS SIZE
                           (5% Significance Level)
                             Influent BOD
             Influent TSS
Rayon


Other Fibers


Thermosets


Thermoplastics
Thermoplastics and
 Organics

Commodity Organics
Bulk Organics
Specialty Organics
(R)

 1.0
(N/A)

 0.77
(N.S.)

 0.4
(N.S.)

-0.311
(N.S.)

-0.147
(N.S.)

-0.036
(N.S.)

-0.193
(N.S.)

-0.309
(N.S.)
 n

 2
20
16
19
11
(R)

 1.0
(N/A)

 1.0
(0.0)

-0.4
(N.S.)

-0.355
(N.S.)

-0.269
(N.S.)

 0
(N.S.)

-0.011
(N.S.)

 0.151
(N.S.)
 n

 2
17


17
15
                                       -36-

-------
     The only significant correlation exists for influent TSS and size for
the Other Fibers subcategory, where R - 1.  Closer inspection of the data,
however, suggests that this correlation results from inclusion of data from a
poorly operated plant.  This conclusion is based on two observations:  first,
the range of production for this category is between 50 and 3,000 million
pounds per year, and the highest TSS is for a plant with only 400 million
pounds per year, a production level easily within the coverage of all the
data, while the largest production plant has the second lowest effluent TSS.
Thus, a bigger plant can do better.  Second, a rank correlation analysis based
on effluent TSS shows a correlation of R - 0.217 with no significance (N.S.).
Thus, wastewater characteristics do not seem to be correlated with production.
Therefore, total OCPSF production as a measure of facility size is not a
factor for further subcategorization.

2.5  GEOGRAPHICAL LOCATION

     Companies in the OCPSF industry usually locate their plants based on a
number of factors.  These include:

     •  Sources of raw materials
     •  Proximity of markets for products
     •  Availability of an adequate water supply
     •  Cheap sources of energy
     •  Proximity to proper modes of transportation
     •  Reasonably priced labor markets.

     In addition, a particular product/process may be located in an existing
facility based on availability of certain types of equipment or land for
expansion.  Companies also locate their facilities based on the type of
production involved.   For example,  specialty producers may be located closer
to their major markets, whereas bulk producers may be centralJLy-JrOcated to
service a wide variety of markets.   Also, a company may locate its plants
based on its planned method of wastewater disposal.   A company that has
committed itself to zero discharge  as its method of wastewater disposal has

                                     -37-

-------
the ability to locate anywhere, while direct dichargers must locate near
receiving waters, and indirect dischargers must locate in a city or town
which has an adequate POTW capacity to treat OCPSF wastewaters.

     Because of the complexity and interrelationships of the factors affecting
plant locations outlined above, no clear basis for subcategorization according
to plant location could be found.  Therefore, location is not a basis for
subcategorization of the OCPSF industry.

     In order to confirm that temperature, a surrogate for location, is not a
fdctor, the Agency calculated rank correlation by subcategory for BOD effluent
and TSS effluent versus heating degree days.  This measure is typically used by
power companies to estimate heating bills; as heating degree days increase, daily
temperature decrease.  The results of this analysis were consistent with the
assumption that temperature is not a factor (Table 11).  With the exception
of effluent'TSS for specialty chemicals, all calculated rank correlations are
not significant.  In the case of specialty chemicals the correlation is
positive, R - 54, and significant (.0064).  A positive correlation between TSS
and heating degree days implies that TSS increases as temperature decreases.

     From an engineering viewpoint, this result appears spurious, since one
would expect TSS to increase with temperature in biological systems.  Moreover,
all comments directed to the temperature effects support this belief, i.e.,
TSS increases with increasing temperature.  Therefore, the Agency believes
that temperature is not a factor.

2.6  AGE OF EQUIPMENT AND FACILITY

     Facility age can affect raw waste pollutant concentrations in several
ways.  Older plants may use open sewers and drainage ditches to collect
process wastewater.  These ditches may run inside the process buildings as
well as between manufacturing centers.  Because of their convenience and lack
of other collection alternatives, cooling waters, steam condensates, wash
                                     -38-

-------
      TABLE 11.  SPEARMAN RANK CORRELATION COEFFICIENTS FOR DEGREE DAYS
                     VERSUS EFFLUENT BOD AND EFFLUENT TSS
                           (5% Significance Level)
                            Effluent BOD
Effluent TSS
Rayon


Other Fibers


Thermosets


Thermoplastics
Thermoplastics and
 Organics

Commodity Organics
Bulk Organics
Specialty Organics
R
-0.50
(N.S.)
-0.11
(N.S.)
0.59
(N.S.)
-0.04
(N.S4)
-0.25
(N.S.)
0.08
(N.S.)
0.03
(N.S.)
0.24
(N.S.)
n
3
10
10
34
30
20
45
23
R
-0.50
(N.S.)
0.32
(N.S.)
0.35
(N.S.)
-0.13
(N.S.)
-0.20
(N.S.)
-0.17
(N.S.)
-0.05
(N.S.)
0.54
(0.0064)
n
3
9
10
33
31 .
18
50
24
                                      -39-

-------
waters, and tank drainage waters, as well as contact wastewaters, are generally
collected in these drains.  Older facilities, therefore, are likely to exhibit
higher wastewater discharge flow rates than newer facilities which typically
segregate process contact wastewaters from noncontact process wastewaters.
In addition, the inclusion of relatively clean waters (e.g., noncontact
cooling waters, steam condensates) dilutes raw wastewaters.  Older plants are
also less amenable to recycle techniques and wastewater segregation efforts;
both methods require the installation of new collection lines as well as the
isolation of the existing collection ditches and are difficult to accomplish
with existing piping systems.

     Facility age, for the purposes of this report and as reported in the
1983 "308 Questionnaire," is defined as the oldest process in operation at
the site.  Because most plants within the Organic Chemicals and Plastics/Synthetic
Fibers industries consist of more than one process, however, this definition
fails to reflect the true age of an OCPSF plant.  Moreover, production faci-
lities are continually modified to meet current production goals and to accom-
modate new product lines.  Actual process equipment is generally modern (i.e. ,
1-15 years old), while major building structures and plant sewers are not
generally upgraded when the plant expands significantly by new construction.
Because the age of plants within the Organic Chemicals and Plastics/Synthetic
Fibers industries cannot be accurately defined, plant age is inappropriate
for subcategorization.

     Process equipment common to the OCPSF industries can be divided into the
following general categories:  vessels in which the chemical reaction takes
place; equipment used to separate products from unwanted materials; equipment
used to control emissions from the process train; and vessels used to store
raw materials and products.  Process wastewaters may be generated in this
equipment as a reaction product, reaction solvent, working fluid, heat transfer
medium, and maintenance/cleaning operations.  Emission contiroJL^&qaipment such
as scrubbers may also generate wastewaters.
                                     -40-

-------
     The extent to which process wastewaters are contaminated with pollutants
depends mainly upon the degree of contact process water has with reactants/
products, the effectiveness of the separation train, and the physico-chemical
properties of those pollutants formed in the reaction.  Raw wastewater quality
is determined by the specific process design and chemistry.  For example,
water formed during a reaction, used to quench a reaction mixture, or used to
wash reaction products will contain greater amounts of pollutants than water
that does not come into direct contact with reactants or products.  The ef-
fectiveness of a separation train is determined by the process design and
the physico-chemical properties of those pollutants present (see Engineering
Aspects of Control Technologies).  While improvements are continually made
in the design and construction of process equipment, the basic design of
such equipment may be quite old.  Process equipment does however, deteriorate
during use and requires maintenance to ensure optimal performance.  When pro-
cess losses can no longer be effectively controlled by maintenance,  process
equipment is replaced.  The maintenance schedule and useful life associated
with each piece of equipment are in part determined by equipment age and pro-
cess conditions.   Equipment age, however, does not directly affect pollutant
concentrations in influent or effluent wastewaters and is therefore
inappropriate as  a basis for subcategorization.

     Table 12 gives the results of the Spearman rank correlations for age
versus influent BOD and influent TSS.   The only subcategory that was not
nonsignificant was Rayon, where the sample size was two,  thus guaranteeing a
significant result.  From a practical viewpoint, this result is not  signi-
ficant.  The age  and influent BOD for each plant are 44/175 and 32/163,
respectively, different as to ranks but not practically different.
                                     -41-

-------
              TABLE 12.  SPEARMAN RANK CORRELATION COEFFICIENTS
                 FOR AGE OF PLANT VERSUS INFLUENT BOD AND TSS
                           (5% Significance Level)
Rayon


Other Fibers


Thermosets


Thermoplastics
Thermoplastics and
 Organics

Commodity Organics
Bulk Organics
Specialty Organics
Influent BOD
 R        n

+1.0      2
(N/A)

 0.54     6
(N.S.)

-0.80     5
(N.S.)'

-0.363   20
(N.S1.)

-0.076   16
(N.S.)

-0.286    7
(N.S.)

-0.259   18
(N.S.)

 0.50    11
(N.S.)
                                                  Influent TSS
+ 1.0
(N/A)

 0.40
(N.S.)

  .00
(N.S.)

-0.182
(N.S.)

-0.289
(N.S.)

-0.80
(N.S.)
-0.207   15
(N.S.)

 0.02     9.
(N.S.)
17


17
                                    -42-

-------
2.7  ENGINEERING ASPECTS OF CONTROL TECHNOLOGIES (TREATABILITY)

     The selection of a treatment train for OCPSF industries wastewaters is
done on a plant-by-plant basis.  The selection is based on the desired effluent
quality and thermodynamic properties of the waste stream contaminants.  While
the different product/process mixes which exist at individual plants are
unique and result in process waste streams of widely varying quality,
conventional and toxic pollutant wasteloads are treatable by commonly employed
physical-chemical and biological unit operations.

     Typically, the treatability of a waste stream is described in terms of
its biodegradability, as biological treatment usually provides the most cost-
effective means of treating a high volume, high (organic) strength industrial
waste (i.e., minimum capital and operating costs).   Furthermore, biodegradability
s'erves as an important indicator of the toxic nature of the waste load upon
discharge to the environment.  Aerobic (oxygen-rich) biological treatment
processes achieve accelerated versions of the same type of biodegradation
that would occur much more slowly in the receiving water.  These treatment
processes accelerate biodegradation by aerating the wastewater to keep the
dissolved oxygen concentration high and recycling microorganisms to maintain
extremely high concentrations of bacteria, algae, fungi, and protozoa in the
treatment system.  Certain compounds which resist biological degradation in
natural waters may be readily oxidized by a microbial population adapted to
the waste.  As would occur in the natural environment, organic compounds may
be removed by volatization (e.g., aeration) and adsorption on solid materials
(e.g., sludge) during biological treatment.

     One of the primary limitations of biologial treatment of wastewater from
the Organic Chemicals and Plastics/Synthetic Fibers industries is the presence
of both refractory (difficult to treat) compounds as well as compounds which
are toxic or inhibitory to biological processes.   Compounds oxidized slowly
by microorganisms can generally be treated by subjecting the wastewater to
biological treatment for a longer time; thereby increasing the overall
                                     -43-

-------
conventional and toxic pollutant removals.  Lengthening the duration of
treatment, however, requires larger treatment tanks and more aeration, both
of which add to the expense of the treatment.  Alternatively, pollutants
that are refractory, toxic, or inhibitory to biological process can be removed
prior to biological treatment of wastewaters.  Removal of pollutants prior
to biological treatment is known as pretreatment.

     The successful treatment of wastewaters of the OCPSF industries primarily
depends on effective physical-chemical pretreatment of wastewater, the ability
to acclimate biological organisms .to the remaining pollutants in the waste
stream (as in activated sludge processes), the year-round operation of the
treatment system at an efficient removal rate, the resistance of the treatment
system to toxic or inhibitory concentrations of pollutants, and the stability
of the treatment system during variations in-the waste loading (i.e., changes
in product mixes).

     A primary limitation of biological treatment of OCPSF process wastewaters
is the great variability of toxic pollutant loadings.  While microbial
populations within a.biological treatment system gradually acclimate to
specific compounds in the waste streams from a given organic chemicals plant,
the composition of a waste stream may rapidly vary as different production
processes are operated.  The microbial population treating a complex waste
stream of widely varying composition will not be as well acclimated as a
microbial population treating a relatively constant waste stream.   Thus, in
order to maintain desired removal rates, physical-chemical pretreatment may
be required prior to the biological treatment train.

     Physical-chemical technologies are commonly used by industrial manufacturers
as in-process recovery and treatment steps, as a means of rendering wastewaters
more amenable to treatment by biological processes, and in certain cases, as
the sole end-of-pipe treatment of wastewaters where such streams are
ineffectively treated by biological processes (e.g., low in BOD and COD or
low in BOD and high in COD).  Such operations include:  equalization,
                                     -44-

-------
sedimentation, fltration, phase separation, solvent extraction, stripping,
aeration, adsorption on a synthetic resin or activated carbon, azeotropic or
extractive distillation, chemical precipitation, chemical coagulation, and
polishing ponds.  These techniques may be combined or repeated in sequence, as
required, to achieve the desired level of treatment of the waste effluent.

     Selection of the appropriate treatment train for a waste stream is almost
solely dependent on the desired performance characteristics.  Biological
systems are based on the required residence time to achieve the desired
effluent quality.  Where extended residence times are infeasible (e.g., space
limitations on reactor size), pretreatment upstream of the biological unit
may be employed to remove toxic pollutants which slow, prevent, or interfere
with the biological process.

     In selecting a physical-chemical treatment unit, the thermodynamics of
the operation dictate effluent quality.  Steam stripping, for example, is a
mass transfer operation that is used to remove volatile organic contaminants
from dilute solutions.   The practicality of using steam stripping to treat a
particular waste stream is dependent on the solubility, vapor pressure, and
the activity coefficients of pollutants to be treated.  These thermodynamic
properties dictate tray and steam requirements, and ultimately, column
efficiencies.  Excessive tray requirements to obtain the desired outlet
(effluent) concentration of organic pollutants would rule out steam stripping
as a desirable treatment operation.

     In summary, though the design of a treatment train can be unique to each
plant, by selection and proper operation of appropriate treatment technologies
it is possible for individual plants to meet common effluent limitations
regardless of raw wastewater quality.   Indeed, the percentage removals of BOD
and TSS are consistent across all subcategories.  It is also possible for
plants in all subcategories to achieve high percentage removals (greater
than 95%) for both BOD and TSS.  Therefore,  based on the consistency
                                     -45-

-------
of BOD and TSS removal data and the ability of plants in all subcategories
to achieve high removals of pollutants, the Agency concluded that subcate-
gorization based on treatability is not justified.

2.8  FLOW

     A variable of interest but not typically used in subcategorization is
flow.  In the last proposal (March 21,  1983) the Agency designated subcate-
gories which used flow as a factor.  Therefore,  the Agency has again decided,
for continuity of the analysis, to analyze whether flow is a significant
factor.  The results of Table 13 show that flow has been adequately incorporated
into the initial eight subcategories; based on the ANOVA analysis, .there was
a 0.9999 significance for flow.  A possibility remains that there is a
secondary effect for flow within the subcategpries specified.   Based on Table
13| it appears that there are no secondary effects possible with the exception
of the thermoset subcategory.  The Spearman rank correlation for thermosets
is -1 for TSS: i.e., TSS decreases with flow.  This result appears to be
spurious, since the two highest influents are 2,509 ppm and 740 ppm, while
their flows are 0.011 MGD versus 0.018  MGD.  Furthermore, the rank correlation
of effluent TSS is -0.02 and is not significant.   This result is based on a
sample size of 10 compared to 4 for influent.  Thus, flow is not a factor for
further subcategorization.
                                     -46-

-------
     TABLE 13.  SPEARMAN RANK CORRELATION COEFFICIENTS FOR INFLUENT FLOW
                     VERSUS INFLUENT BOD AND INFLUENT TSS
                           (5% Significance Level)
                            Influent BOD
Influent TSS
Rayon
Other Fibers
Thermosets
Thermoplastics
Thermoplastics and
 Organics

Commodity Organics
Bulk Organics
Specialty Organics
R
1.
(N.A.)
0.37
(N.S.)
-0.3
(N.S.)
-0.16
(N.S.)
-0.27
(N.S.)
-0.07
(N.S.)
-0.37'
(N.S.)
-0.44
(N.S.)
n
2
6
5
20
16 '
7
19
11
R
1.
(N.A.)
0.8
(N.S.)
-1.0
(0.0)
-0.38
(N.S.)
-0.39
(N.S.)
-0.37
.(N.S.)
-0.21
(N.S.)
0.317
(N.S.)
n
2
4
4
17
17
4
15
9
                                    -47-

-------
2.9  COST OF ACHIEVING EFFLUENT REDUCTION

     The waste treatment investment and operating costs for a specific chemical
plant depend on several factors:

     •   The ability to recycle process wastewaters
     •   The ability to recover products from process wastewaters
     •   The composition and quantity (e.g. flow) of waste streams
     •   The geographical area within which the wastes are generated and
         disposed of
     •   The existence of POTWs to accept waste streams
     •   The generation of solid waste
     •   The nature of- the chemical process
     •   The kind and purity of the raw materials.

The technology for pollution abatement consists mainly of the same physical
and chemical separations and reaction technologies used in chemical manufacture.
Wastewater streams such as process water, boiler blow-down, and runoff water
may be treated separately or collectively by appropriate operations in one or
more treatment stages.  Streams requiring different treatment methods are
segregated and subsequently combined at the point where treatment becomes
similar.  For example, runoff waters might be settled in a thickener; certain
process waters might be separated by dissolved air flotation, steam stripped,
and treated biologically; other process wastewaters might be neutralized and
filtered; and the sanitary sewer flow might either be treated biologically
or discharged to a POTW.  All streams might then be combined for a water
quality check, flow equalization, and discharge to an adjacent water body.
Each of these factors is considered in this section.  The composition of raw
wastewaters is largely a function of the products and processes by which
these products are made.  The treatability of these wastewaters (as discussed
earlier) is largely independent of the raw waste load; that is, by selection
and proper operation of appropriate treatment technologies, it is possible

                                     -48-

-------
for individual plants to meet common effluent limitations.  Accordingly,
treatment costs are inappropriate as a basis for subcategorization.  Industry-
wide costs of compliance with alternative effluent limitations are analyzed in
.a separate companion economic impact study.

2.10  ENERGY AND NONWATER QUALITY ENVIRONMENTAL IMPACTS

     Plants within the Organic Chemicals and Plastics/Synthetic Fibers
industry, in addition to producing process wastewaters requiring treatment,
may generate significant amounts of airborne pollutants and solid wastes.  Air
emissions are controlled by a wide variety of technologies including absorp-
tion, adsorption, filtration, condensation, and incineration.  Absorption tech-
nologies in controlling atmospheric emissions generate both solid and liquid
waste streams.  Solid wastes generated by OCPSF plants are treated by tech-  '
nologies including  coagulation, extraction, distillation, chemical reaction,
chemical fixation, and incineration.  Many of these technologies used to
treat solid wastes also generate wastewater streams.

     Generation of both airborne waste streams and solid waste streams is
subject to the same considerations as process wastewaters:  chemical manu-
facturing processes do not convert raw materials to products at 100 percent
efficiency; that is, a portion of the raw materials used in a manufacturing
process is inevitably converted into unwanted products.  These products may
potentially be discharged to the atmosphere, the aquatic environment, and
the terrestrial environment depending upon the specific manufacturing con-
figuration (e.g., use of an aqueous reaction medium, use of gaseous reactants).
Both the impacts of air and solid waste emissions parallel those of wastewater
and do not provide an alternate subcategorization system.

     Similarly, the energy consumption of wastewater treatment technologies
fails to provide meaningful subcategorization.  The high energy content of
raw materials and products of the OCPSF industry results in only a small
fraction of the total energy used for pollution control.  Specific energy
                                     -49-

-------
requirements are determined by the nature of the processes and by such unit
operations as thermal cracking, distillation, heating of reactors, and similar
processing steps.  In contrast, practically all wastewater treatment tech-
nologies require a modest energy input that is a small fraction of the total
plant energy requirements.  The energy requirements of the wastewater treat-
ment facility are small in comparison to the plant total.
                                     -50-

-------
     APPENDIX A




ANALYSIS OF VARIANCE

-------
                             ANALYSIS OF VARIANCE

     Analysis of Variance (ANOVA) is a statistical technique which can be
used to determine, for a particular variable (e.g., BOD), the relative con-
tribution of the variance between certain groupings of this variable to the
total variance of the variable.  As used by the Agency and recommended by
commmentors following proposal, ANOVA is used to test the hypothesis that
certain fixed groups (the subcategories) explain most of the variance for
variables the Agency considers as suitable measures of the adequacy of its
subcategorization and appropriate for ANOVA analysis.

     Typically, as explained below, there are two hypotheses: the null hy-
pothesis (HQ) and the alternative hypothesis (HI).  In our case the Agency
has tested the hypotheses that:
     HQ:  The subcategories determined by the Agency adequately account
        •  for all the factors which affect the variance of a variable (such
          as BOD concentration).
     HI:  The subcategories determined by the Agency do not account for all
          factors which affect the variance.

     The variables chosen by the Agency are Influent BOD, Effluent BOD, Total
Production, and Total Flow.  The statistical basis of the Agency's use of
ANOVA is discussed below.

     Suppose there exist k groups.  Let xn, x^2> •••» *in  ^e independent
observations from group i, i - 1, ..., k.  Let x^. be the sample mean for
group i, and let x.. be the sample mean for all of the observations.  That is,
                  1  ni
             . "-5— Z  Xjj  for  i*l,  ..., k, and
                  1 J-l
          _     1  k   ni                    k
          x..  »—— I   I x^ 4,   where    N * I
                 N i-1  =l                   i-1
                                  A-l

-------
        To test whether or not the null hypothesis can be rejected, the following
   analysis of variance table is constructed:


                             ANALYSIS OF VARIANCE TABLE
   SOURCE
Among Groups
Within Groups
  Total
DEGREES OF FREEDOM    SUMS OF SQUARES     MEAN SQUARES
     k - 1
     N-k
     N - 1
       — ~~     ^~   0
 Z nt (xt. - x..)    SS(Among)/(k -
1-1
                              MS,
 k   ni
 I   I
- xi.)2  SS(Within)/(N - k) = MSW
     ni       _
     E (xlf - x..)
          3
        An F statistic, MS^/MSyj, is compared with a critical value, as found in
   standard F tables  (see Neter and Wasserman (1974)).  This critical value is
   ^(k-1  N-k  1-a) wi^ degrees of freedom k-1 and N-k and a significance level
   a - 0.05.  If the  F statistic is larger than the critical value, the null
   hypothesis is rejected and  the alternative hypothesis  is accepted.  If the F
   statistic is smaller than the critical value, the null hypothesis is not rejected.
                                     Reference
    Neter, J.  and W.  Wasserman.   1974.   Applied  Linear  Statistical  Models.
    Homewbod,  111.:   Richard D.  Irwin,  Inc.,  pp.  807-13.
                                          A-2

-------
        APPENDIX B




SPEARMAN RANK CORRELATION

-------
                      SPEARMAN RANK CORRELATION TECHNIQUE

      Let (KI,  yj.),  (x2,  72)*  •••»  (xn»  vn) be a bivariate random sample of
 size n.   The rank of  x^, RCx^),  for 1=1, 2, ...,  n ,  as compared with other
 X values, is the position of  x^  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(xj) « n.   Similarly, the values  for  Y can be ranked for
 i - 1, 2, ..., n.  Once  ranked,  the data can be replaced with the rank pairs
'(R(XI),  R(yi)),  (R(x2),  R(y2))»  •••» (R(xn), R(yn)). The Spearman rank cor-
 relation coefficient  (r) is  calculated  as follows:
Z  R(xi)R(yi)
                                      - I0.5(nV I)]
                                  n(n2 -
                                      12
 Based on r, the rank correlation statistic, the following hypotheses can be
 tested:
      HQ:  The X and Y variables are independent (i.e.,  their correlation is
           zero)
      HI:  Either (a) there is a tendency for the larger (smaller) values of
           X to be paired with the larger (smaller) values of Y, or (b) there
           is a tendency for the smaller (larger) values of X to be paired wih
           the larger (smaller) values of Y.

 By using influent or effluent concentrations for the X's and subcategorization
 variables for the Y's, the above hypothesis becomes a statistical test for
 significant subcategorization factors.
                                    B-l

-------
     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.  The Spearman rank correlation coefficient is
used to identify a relationship between R(X) and R(Y), and development of the
relationship between X and Y requires additional statistical techniques.
                                        B-2

-------
              APPENDIX C




PRODUCT LISTINGS BY INDUSTRIAL SEGMENT

-------

-------
UJ

19
       £
       B
       (ft
       u
       CO
                                       a a o
                                       a. a a.
                                                               C-2

-------
Ul
(9

GL
  111

  ffl
                 * * *
                         * *  * *
                                      * * *
                                                            C-3

-------
58
o.
                                                                                                                             I
   ffi
8
ex
           tf)
           w
           o
           M
           IU
           p
           (a
           uj
           at

           u
                                                                                            IU
                                                                                            IU UJ

                                                                                            iu O
                                                                                            Z NJ
                                                                                            iu Z
                                                                                            -I IU
                                                                                            >• ca


                                                                                            II

                                                                                            £2
                                                                                                               gjgin
                                                                                                               	z
                                                                                                             JC M M M
                                                                                                             -i in in in
                                                                                                             M IU IU IU
                                                                                                             u. CE oe ae
                                                                                                                          w O
                                                                                                                          in
                                                                                                                          iu u
                                                                                                                          IU H
                                                                                                                          t- IU
                                                                                                                                        3

                                                                                                                                        r
a
iu
                                                                                                               >-    — — a. ^
                                                                                                               a -i iu iu <    x
                                                                                                               u >• a. a. a: x  uj
                                                                                                               < Z a a u <  i—
                                                                                                    >•>•       «  • • M in o:
                                                                                                    z-izzzzzzzo
                                                                                                    t— OWMtHMMMM-l
                                                                                                    lutLinminininininz
                                                                                                          UJ UJ UJ UJ UJ UJ U U
                                                                                                     i   i  a a tr ec a a: ac

                                                                                                 uj u iu u u iu u uj u uJ iu
                                                                                                 zzzzzzzzzzz
                                                                                                 U U UJ UJ UJ U UJ UJ UJ UJ U4
                                                                                                 zzzzzzxzzzz
                                                                                                 l-l-l-HH-t-t-t-KI-l-
                                                                                                 IU IU UJ U UJ IU IU IU IU UJ IU
                                                                                                                                             UJ UJIUUJ
                                                                                                                                          in -J zzz
                                                                                                                                          UJ >• UJUJUJ
                                                                                                                                          a a. aceac
                                                                                                                                          H o >->->-
                                                                                                                                          C ac t-i-i-
                                                                                                                                          M a. inmcn
                                                                                                                                        go o o o o
                                                                                                                                        a. a. a. a. a.
                                                                                                                               ggggg
******
                   *  *
                              *  * * *
           m
           a
           IU
                                                                                C-4

-------
in

Ul
(9

2
                                   tn
                                   ce
                in
   M

   IU


   S
in


a.
           ce
           iu
in
iu
ce
8
h- - H-
ceox,^__ —
O-
                                           ujucce
                                        oo      >- u
                                        IUIH-
                                                   -
                                                           -IUI
                                                           OQ
                                                                               u
                                                                               a
                                                                               M
                                                           xtj
                                                           iu
                                                           *--!
                                                           <>-
                                                           -iz
                                                   a
                                                   O
                                                 ceuuj
                                                 u
                                                 < u -
                                              in x H >- u
                                                            --  —
                                                           act>
                                                           uotni
                                                                 ui  LU
                                                                    z in
                                       >ui
                                         H-
tO      O <    < U -J       —I UJ LU
zz    -J   inxn>-iuuisK-zin
MM    xuzt--Jxaau-HMM   _i -j M in
UILU       ujuiECKujarcs-Jvvioz
o: cc     « _i uj    uioo>-a:xiiJM
     iu LU < ce  i  <«\j_i-JZ->-
     >->->->->--IZZ
                LU LU  < ce  i  <«\j_i-JZui-cEin
UJLUUJUJUJ—IQaZ          I  X X M < IU   LU
           KOMMI-JUJUJUJU(J>       UJ CE
           < x ce CE  CE < t— K t-       i   •«>
           h-oooiu£<«(-Lu
           u-JXXHOuiuiuiuiuiujujuj-
                                                              _l
                                                              o
                                                              o.
                                                              O
                                                              u
                                                              .
                                                              in
                                                              IU
                                                                                               ui
                                                                                               z
                                                                                               iu
                                                                                               M
                                                                                               a
                                                                                               <
                                                                                               H
                                                                                               3
                                                                                                 CE m
                                                                                                 a iu
                                                                                                    ce
                                                                                 Z
                                                                                 O O
                                                                                                 Mi-i>-iHM
                                                                                                    CE
                                                                                                 U iu i
                                                                                             >  Z
                                                                                             l  O
                                                                                                    E-I-JOQ
X
in in

55
-j m
— UJ

«"

Sz
in iu
ui NI
ce z
   LU
UJ CQ

ui —i
M v
o z
      in
      ce
      Ul

      >•
      _j

in in o.
Z ce ce
M ui ui
in E (-
ui >
ae -J ui
   O Z
CE a uj

SS3

S«g
O (-
Q. < -I
o: -J >-
uj > z
KgM

111 <
t- X •
< h- ui
_i UJ 2
>- C LU

U -I O
                                                                                            tntn-j-ieeacH-i-H-:
                      >>->>-V>->->->->->>->->»OOUJOUJM

                      ZZZZZZZZZZZZZZa-CLQCain
                                                                                                           .^ = 5
                                                                                                           I IU UJ CQ
in

M
in
LU
ce

ui
a
M
CE
a
>•



Iz
   M
u in
M LU
LU a
                                                                                    Ul Ul
                                                                                    Z IU
                                                                                    UJ >-


                                                                                    Es
                                                                                    -
      LU _j ce
   uj z >- u
   K ui CE <
in < M u -J
z -i a < >-

in CE i- t- 3
UJ O 3 LU CO
ce < CQ r  i
    I  I   I  Z
LU IU IU IU  I
Z Z Z Z HI
UJ LU UJ LU H
3 3 3 3 <
_i -l -l -l I-
O O O O '-il
I- H t- t- L)
                2££
                *
                        ooo
                      a o
                   a. a. a.

                   *   *
                            j— i_i__-j__i_j— i_i-j_-ju
                              ooaoaoaooaooo>
                            .aQ.aQ.Q.Q.aa.CL.CL.Q.Q.Q.a.
                                                                              >OOO-Ki
                                                                                                              ' ^ «•» Av d_
                                                                                                              • 3 Z W M
                                                                                                              i in 3 > >
                                                                                                                          Z  Z Z Z Z
                                                                                                                             M M M M
                                      ***
                                                      *  *  x * *
                                                                                                       *************
                                                                                                                                             *  *
           1
                                                                                C-5

-------
UJ
IS


O.
      m
      Q.

      O

      g
      u
      M
      r,
      IU
      n
      u
      M



      (9

      g
          3
u

u
H



I

g
          i
      UI

      >S
                    UJ
                    o
                            (0
                            UI
M a — uj
an   z

M < IUIX   UI

        a ui
o     ui z   _
•JOOZODUIX
-D.>--l
UJIUIUUIIXMH-U

miiz^
                    O IU
                    u a

                    JX
                    C9 O

                    ui ui
                    Z Z
ui
a -i
>- o

iu < .

3S!
                                    O
                                    u
 (9

 ui


 IU
 -i


 QL
 O

I Q.
I >-
: x
                                                  UI
                                                  o
                                                  X
                                                  o
                                                ZZ
                                                UJUJ
til HI

H O
< CC

K O


U X
< O
                              U U4 U UI U UB H4 i
                                                     1 Z N I

                                                      M  -

                                                     I > -i i
      O
      U
                                                           C-6

-------
r>.

ui
   u
   M

   IU

   g
   (9


   g


   U
   t-t




   O
                 Ul

                 5
      £UI
      ce
UJ    3
K ui a.
ui z C
h- uj M
                                 I ID
                                  z
                               So
                               in v>
                                        o
                                        H
                                        U
UJ    > uj Z Z    t-
Z UJ X O Ul Ul -I
ujzi--i-i-iox
KIUJUJ^-VVZL)

Ul
              rrrxxuit-
             J 5 M H-  I  I Z M
 (9

 ui

 m uj
 >- z
 -I UJ
 o ae
 cc >-

. O. tf> I

 *
                       Ul 3
                       a -i
                       UJ Q
 o
 Ul
 X
 M


  - Ul
I (A Z
: u ui
i z -i
I ui >


• x o

 X
                                                                                    C-7

-------
(9
<
Q.
   tn
   5
   U
   Ht

   U>
   g
         Ul
         a
         M

         g
   UJ
   u>

   3
                                                                     C-8

-------
(9

a
         - X -I -I
X < -I O >- >-
O Z Z X X X
HI t~ t- >- t- I-
o iu UJ uj uj u
-J -J    X
O O    h-
U U    Z
> >-    >
_i -j in in
(9 (9 O —
      M UJ
IU IU U Z
Z 2 < tH .
iu iu    o: <
_i -j >- iu
>• >- I- u

iE£SS
iu iu u. is
                                     8
                                     ex
                                     o
                                     •o
                                     U

                                     a.
                                     IU UJ
                                     x a
                                                                                                                                                                              >-   UJ
                                                                                                                                                                              0-IZ
                                                                                                                                                                     < ui
                                                                                                                                                                     X Z
                                                                                                                                                                     O <
                                                                                                                                                                     > X
                                                                                                                                                                     -J uj
                                                                                                                                                                     is x
tn i	
UJ COM—
Z 033

X QOO
uj >-i/itn
         U     t-
         M     <
         i     £
         (9     M

         s     3
                                                                                       C-9

-------
0.
  £
AND CHEMICAL Gf
2
u
M
Ul
g
U
(J
M
1
ce
O

u
w
t-
5 -
M
a «
< w Oe -i
U K UJ O
U X Ul OX
• H H Z MO
o in uj ui ui o u u u
MIUZHH Q < -I
Ul U O < -J Ul HI ' <
ui o i- < ui o o H. -J >• * a w -i u
QM--t- -1 UIQH-OHI 1-1
>• u H- u HI u u ii a 3 -i o ui uu a a >- < x H o
x < ui M « < < o a >• x H. H. >- M x H- o ui in H.
Ul ' U Z O -I < 1 h- O •«< < I U 2 UJ U U Ul M
30 < o >- 0 o >- x H. 3 ut-i-ui<-X
- a x z a. 10 KCEUI MZ-i_i_io:a:o:u.>->-oin a a
mQ.Q-Q.Q.ZUIXXXXXXX-J333333-XXUI
MMMHiM-Jcz:z:£sc££zzzzzzzzzzzzoe)a.

* * « *


in
UJ
<
a
u.
_4
3
-
O X
Ul >-
M 0
a. a.




_i
O
u
(9
UJ
UJ
_l
1
>-
X
0
2





UJ
o
X
UJ
O
_l
z a
2 a!
11






a
HI
2
U
o
o,
1




_l
0 °
"OK
-j -j <
(9 < E
Ul _J 0
Zw n
^ uu
Ul 1—
-J 5 E
a. i HI
O (J Q
a: ui o
a. in in




|
g
M
0 O
u
• —1
0 <
^ ^
O U 3
H> H CQ
t-i a i
03 < H>
cr ui a:
en in H





Ul
K
^?
M Ul
0 U
Ul <
ui Z
UJ Z ^ J
Z UJ H- >-
Ul H> 3 H>
H. Z ffl 3
3 ui l 03
m o. -
Z < X
< a. \-
X >• ui
ui l- E
X 3 w
CQ Of
-I _) t-
>• >- 1
X Z •*
h- H -
LU LU eg
i i *
C\J CsJ OJ




  £
                                                   C-10

-------
ui
10
  tn
  Q.
  o
  g
                                                                I— Ul
                                                                ui Z
  111
  • .


 tn HI ui < -i ui
< uj ui i: ui   CE UJ a Z —' >- 2
M Z -1 < Z   UZ   M>-XM
-	     M1UEXI	1
                                               >   Ul
                                               X UJ Z
                                               H Z IH
                                               UJ M £
                                                                               Hd I	 .•• T~l

                                                                              i Z ui M Z
                                                                              ; M -i tn 5
                                                                              I -I >• M M
                                                                              I M X 00 Q
                                                                             a -i
                                                                             Ul >-
                                   rxv,
                        I Ul UJ

                         *
ui   UJ o 3 K w _l _J
_I>.£:Q:-IC£>->-
>-K- M M < I

                                                      3 i  i  a
                                                      03 Z Z H
                                                     I
                                               >-  I  H
                                               -J u a
                                               o ui ui
                                               a. in H
> M Ul
' a z
I Ul M
> z a


 33
 o o
     UJ Z Z
     >. ui ui

     §^

    ig*.*.
    : >- ui ui
X?'
a. o I
 I  -
   M
                                                                      C-ll

-------
UJ

a
Q.
  I
  o:
  u>
  u
2

2
M

UI

5

u



i

(J
         O
         in
         UJ
         at
         o
         i
g
         u
         I
         -o
         UJ

         £
         X UJ
         H z
         UJ UJ
         c at
         !->•
         O _1
         IX V
         U
          I
               in ^

           •    ii

               §i
               - >• >• z

     222S
  3


  UJ

  UI
  «J
  «t

Z^
M X
Qt ^

S§

Si
§   2
U.   X
-I O -I
  31-1 >•
  U X
M < I-
Q   UI
UI O I
Z M «U
UJ O ^
N M
z z in
  UI

  UI
  u

  X ui


  s5

  32

  0 =
  I- a.

< uj -i

-J UI [

Z Z '
UJ UI
  £03 U
   l >- .
VI X t-

03 (Q CQ
               OT
               UI
                   En*
                   M
   b1

   §
   a-
   a.

 oc o:
I < <
                                       o o
                                       u u
       _l

       in u

       W5
   o   M -i
   ui a H- <
   x M < x
   M u 5 i-
   r < o x
       a: a.
 ui  - u <
 v- in 1-4   -i
• o -i a o >•
 in o 3 M t-
 o in z J a
 UJ UJ < U CO
 ot a >- >• M
 u u u u a
                                                        •< < <
                                                      UJ UI
                                                      X h-
                                                    Ul M <


                                                    *53
                                                               _
                                                               s
rz£
                                                             O UJ
       UI
.. _   >
u a.   -i
< M ui o
  o z in
(J UJ UJ «
                                                        a Q
H ui _

£3.,
  O >•   w M* «,  _
_i(-u-iMZ-J(n
>-OUJO-!UJ<<
XCEQOTM-IXX
»-h-l-IUlZ>-t-t-

E2?S??£cx
M M M I  UI UJ < <
OOQCCEZZ
to u
Z Z -I

KSi

5^S
m t- a.
O O _i

H K Z
M M O
Z Z Z
  ui
  a
  M
  ae
  a in
Q > ui

u z o
                                                                                               x
                                                                                               M
                                                                                       (0
                                                                                       UJ
                                                           -I < Q
                                                             §>- tH
                                                             U U
                                                           UI O <
                                                           x in
                                                           a. HI u
                                                                   ui

                                                                   o
                                                                                                      H- 3 D
                                                  -J U U
                                                    SW IH
                                                    -I -I


                                                  tt x x in
                                                  o i- (- os
                                                   I X X •«
             *  * *
                                                         31U -1

                                                         Z -J
                                                        I UI UI
                                                       (- 3 3T


                                                       UJ O O!



                                                         *
   -65

  ciee
-I -I M M
O < Z Z
in oe M M
ui H a a
K UJ I  I
U t- * 
-------
(9


O.
   (ft
   o.
          at
          o
   IU
          en
          a
          tu
                  iu
                  a
   o
   IH
   U
   (9


   g
             0
             IU IU

             23

             5JE
                   IU IU
                   o o
               g
IU IU I
Z Z '
iu iu ;
                                 in
          >•.
          Z :
            :_!>•;
tLiB^xxs
<•* < 0) U U U U
  I  Z u. ce (-
1 UJ  IU M O IU

 00000
    See ce ce ce
    o O q p
                  U U

                     *
                       O IU
                       z z
                       iu iu
                       z a:
                       SC a.
                       o o
                       a o:
                                 U U

                                 *
                                       a a:
                                       X X
                                       U U
                                       Z U
                                       (3 CE
                                    IU Z
                                    Z 11
                                    < ne
                                    a. a
                                    o >-
                                iu
                                a en
                                M z

                                  8
                               §
                     a -i
                     M o
                    i ce z
                    I O IU
                    i —1 x
                    : x EL
                    i u a
III
u u
O ce :
ce o i
o -J
-i x
x u :

S£i
Q UJ
                                                                     IU UJ
                                                                     z r
                                                                     IU O
                                                           iu


                                                      iu    <
                                                      Q IU X
                                                      M Z I-
                                                        S< UJ
                                                        X O IU
                                                                              - D£ X
                                                                                O O.
                                            iu u
                                            19 <
                                            - i   » i
z — -t 
-------
tu
10
   m
   Q.
   g
   (J
   IU
   u
    u
    u
    M

    IS
    g
.  t- 01 X
UJ iu o: <
h- 1- 3 3
                                                                       C-14

-------
                                                                                       UJ
                                                                                       o
uj
o
   >

   III
        in
        a.

        §

        s
        y
        IU
        5
->-
                                                                                                                                          Q O >• XXX
                                                                                                                                          z a. a h-t-t-
                                                                             C-15

-------
UJ
s
D.
  1
                                                  C-16

-------
IU
(9
   tn
   a.
g

-i

u
HI

IU
          ce
          U
          a
        OT
        o
  IU
O
s
s
§
          -i <
          vr
         i x CE
                  <
                  K
          in


       iu o
       I- CE
       < a
       CE >•

     O IU  I
     IU H- «M
                         IU I
                         z :
                         X^
                                1^

                                S5
                             i   CE a
                              UJ < CE

                             :ZU2

                              z^-.-,
                              u x >• o
                              a. u H z
                                             CE
                                             <
                                             UJ
                      ilU I
                      h-

                     • < .
>• >-

PS
UJ UJ
r r
             >•>->-

             5??
             IU UI UJ
             £ C£
   u

< u
_l _l
>- >•

PE
                         u u

                         u u
                           >- >-
                           X X

                      o -J o z

                      U u H a
>•>->->•
X X X X
                                UJUJUJUJ

                      u        <
                      a        at
                      H        <

                      §        Si
                      EX        m   z
                      iu             o
                      a        -J   M
                      o        o   t-
                      a        u   3 ui u -i
                      a        >-   -J t- o <
                      >-        ~l   O < X CE
                      x   o   (a   -
                       I    M           IU U t-
                      -Uh--Juias-!.J_i
                     !-u_>-i->-
                                        pg


                                        II

                                        s§
                                        u 
                                        O   IU
                                        H UJ I—
                                      -i x a <
                                      Z I- >- u.
                                       I H X -I
                                       i a uj r>
                                       i -i a in
                                                                                       ui
                           ae
                           UJ
                           £ CE i
                           < UJ .
                           as £ .	
                           I- H < > -I -I .
                         in uj CE
                                                                                       3i:ct:
                                                                                       fflo:3
z o
SB
80
                                                       )-aiu
                                                                       .
                                                                 X>-OZZZ
                                                                 »--J>>
   <>v>->.>-
CCECECE-J-I-J-I—I-J
 I  - uj uj uj
x -J -i z i: £ £ :

g f S- 5- P P P
                                                                                                      M
                                                                                                      in
     t-   a
     -I U) IU   IU

     - uj a
 i    < iu H- H x o. M
     u £ m N a o x
 :              CE CE o
   a  . .  . - uj a a
 ;HOooaa.>-uj

 :->• v
                                                                                                                        tn
                                                                                                                        uj
                                                                                                                             UJ
                                                                                                                             a
                                                                                                                             (H
                                                                                                                             X
                                                                                                                             o
                                                                                                                             a
                                                                                                                             >•
                                                                                                                         • n.
                                                                                                                          in
                                                                                                                          o
                                                                                                                          x
                                                                                                                          a.
                                                                                                                               Of
                                                                                                                             ex uj
                                                                                                                             UJ X
                                                                                                                             x t-
                                                                                                                             1- UJ
                                                                                                                             01
                                                                                                                               -i
                                                                                                                             -J >-
                                                                                                                             > x
                                                                                                                             xh-
                                                                                                                             H uj
                                                                                                                             uj o
                                               _ a. a. a. H M H
                                               o o a o a a a
                                               CE CE CE CE o o o
                                               a. a. a. a. in in ui
   CE ce CE CE CE  i  i
   <<<<• -I
It >•
< <

P5P
UJ IU
                                             >
                                             X IU
                                             h- O
                                             IU >-
                                             i: x
                                             >• ULl

                                             §3

                                             Sz
                                                                                                                             XHUZZz>-
 in o o o
 UJ U U U
 »->>•>-    _   .
 < _i _i _i uj moo
 CE to ID o z o
                                                                                                                        UJ-J


                                                                                                                        -H
                                                                                                                        a—ix
                                                                                                                                         W XUJUJ

                                                                                                                                           I O.ZZ
                                                                                                                             UJCE
!>>•>•>- m za-a.
 X X X X O UJOO
 t- H- H I- IO XCCCE
 iu iu iu iu H a. ctcu
 H H H H H MIHH
 CE CE CE CE CE QSCECE
 I- (- »- I- H- h-Kt-
   a

   o.
                                                                        C-17

-------
Ul

8
a.
en
a.
i
S


u
£
             Ul


             HI
X Ul
Q. I-   -I

ax   x
  £0. a i-
  in ui ui
  o t- z:
— X «< M
-I Q. U. DC
  2   £
       _ — 3 r
       ui —i m *
  ui
u

u
  u>
  cc
  o
a. -i 11 i
o >- o o
  £X   or
  t- ui a
  ui _i >-
   i  0 x
M CM < l-l

in M ui i

o: a ui -
H- t- > -«
SO
     -I Ul
     o r
  -J U l-l

ssss

2e»5

Sz-Z-S
a < ui x
v i- _i O
X 3 >- J
O CO K U

uj -j- m o
    o —
    M >•

    32

    o?

    CE V
-I -J < X
O O ui o
IH l-l I- X
a a - Ul
z z x r
UJ >- O I
K t a CM

 >. I
                               >• >- x •

                               o o z
                               X X H I
                               K- H UJ I
                                                   5
                                                   O
                                                   B
                                                   u
                                                   <
                                                   Ul
                                                   Z
                  >•
                  I  UJ

                  75
                  X X
                  UJ UJ
                •  z x

                  V ^

                  gg
                  o: a
                  ui ui
                  a. a.
                      ui
                  -i -J Z
                ui >• ^ ui

                5S55
             ui M A to ui
             a o i   i a.
             M < l- i	1
             XX'	>-
             O Ul M M I
            i oc x Q a i- i
             ui i  i   i iu
            : a. -^tn in r ;

                   1 CM '.
                                                                     Ul


                                                                     UJ
                                                                     Ul
                                                                     a
                                                                     o
                                                                     a:
                                                                     ui
                                                                     t-
                                                                     m
                                                                     ui

                                                                     -i
                                                                     >-


                                                                     ffl
                                                                       ui Z
                                                                     ui Z <
                                                                     z o u
                                 oox
                                 H-XH
                           to >  i
                           I  X CM
                               CJ3I— UJ-J
                               — auix:v
                          . CM  I

                           -< CM
Ul





II
a. x
Ul Ul

 I  I
«4 C4
                                                              i£
                                                 uia:
                                                 0.0.
   ': X Ul CM Oi
   I I- Z I   I
    UJ o -J —
   I M M >• V >- I


    §S?Z?7
   | z; fc u, uj g _J
>- >• IH Z S C L_
XXCUIIHIHIHX
l-H-1-ta.OQOt-
Ul Ul I  I  I   I  I  Ul
cxcM^inininx
 i  i  . .... i

CMCMCMCMCMCMCM^
.  Ul
Z IH
Ul Q
a.  i
I Ul
CM  -
I CM

>- O
x ce


is
i  i
2SJS

 I  I  I
CM IO >-
 I  I X
-J -J a

x x ui
H t- I
Ul Ul O

 I  I  -
Ul \t\ 9-
                                                          _    C-18

-------
UJ
(9
a.
  IU
  U
  M
  IU
  X
  U
  u
  w

  1
  §
  IU
  Q
  I
  IU
  M
-4-AMINCMDIAZENE
_j
1
IU
I

.PHENYL)
>•
i
~


in
o:
UJ
IU
8
u
1
in
IU UJ
Q O
ETAMIDI
ETANIU
ETANIL]
U CJ O
< < <
*
in
K
IU
IU
(9
a
u
i
in
IU
a
M
_i
M
Z
ETOACE1
<
*





IU UJ
RYLAMIC
LYLAMIh
< <



IU
H
•<
U.
_l
in
o
INOALCC
<


IU
M
E
<
rLETHANO
INOETHl
<



IU
a
. M
g
IYDROCHL
YLAMINE
ILINE K
55







M
o
M
CO
5

UJ
a
M
u
UJ
•Z iu
M a
N M
< a
M • o
0! - IU -1
t- ax
M U
iu H- r o
— Z -i < a
Siu < iu z a
ca in H- iu >-
HI — ' IU < U, X
CM - Z ttJ u. -J M
< 1- . M Z -J 30
J 01 CM 3 tfllUIIU
v — «t E in luziuz
x Q a < >- -JMZM
H M H-J X OSM-I
UJU UI O O IM < E M
C •< 1- Z X < lu < Z
OTM iu< I--IM-IZM<
oc a u zx >u uj o X>-MQO
UJIM luh- Z I Z t-NJriutn
ZZZ UJUiu M Z UJ O Z < Z O
IU -O Q IUZ>-M C X N! UJ _l UJ CC
§Z U. M ZMXQ! U< « Q. UJ ZCOV-lh-
— _j ij a uj M i; h- 1- zasiuinz iu X>M
u uj i 3 iu-iux>-i
SM i ZMUinz: M_J < i— tu Mh- as MM- uj i- < z ujujiua E E M M IIUM- <-Z DMIU-IZ-J UJIUMX UJ< >-O.MIV>-
UNZZiua-io.ZMXMiucora.3MM -i-izzuz-izxtux i ZCMXX
aaea M£CMCEXoaiujx-lUXOIJO-l-l>->-O-'-l-IMI-HVOCEXK>-£K-l5-l>->-O.E
r u r M i 	 1 i ->-xxa:>->->-x:ujuJXMu.ijujzoQ-i>xz--4'Q!OOOMOUXXMI-h-UUU-h->-ujujwujujujE<-h-ujx i i
>-ozzzzin-i-
UJ
X
a.
i
a
i
_i
>.
IU
x
0.
a
i
z
z



UJ
M
_l
M
1
O
IU tvl
a <
z:z>-

-------
13

Q.
   §
   g
IU

u
   u
   UJ
   u

   u
   g
   UJ
   a
   M
                  UJ
                  a
                    o u-
                       o
                    O M
                                 Sn   o
                                 Ul   UJ
                              HZ   i-

                              25   M
   uj -J   tn   en
uj z v uj    in iu
Q uj ^ z  - uj z
M -i -i M tn z o
£ >- < £ UJ M Q
M Z ^ < Z O M
-J I- X -I M M -I
•t UJ O >- O C O
x, >- >• a. M M a
v- -J -i o a a o:
xooa>->->-
                               a. a.
                                 * *
                                         a. o. a.

                                         * « *
                                                                                                   X
                                                                                                   O UJ
                                                                                                             a:
          >•   uj
          X   Z
          O U HI UJ
          a. -J a t-

          5 N a a
          x < >- t-
           i  M a. M

          f^^2
          O O >- UJ
                                                                                                                                              UJ
                                                                                                                                              a
                                                                                                                                            Q M
                                                                                                                             UJ
                                                                                                                                    O
                                                                                                                                    UJ
        O UJ
        IM a

      'ii
      :  £ M
      :W5
                                                                                                                                         UJ
                                              t OOUIOOOOO
xaazzzzzz
S3
E?
< - *
Z I  .
uj O
                                                                                                                                       UJ
                                                                                                                                       z z
                                                                                                                                       M <
                                                                                                                                           I UJ X
                                                                                                                                           i z a.
                                                                                                                                  >_J_J_1MH-—M
                                                                                                                              : uj :
                                                                                                                               £
                                                                                                                                  UJ UJ
                                                                                                                                  £ X
                                                                                                                                  i  a.
                                                                                                                                  •f M
                                                                                                                                  i  a
                                                                                                                                    o
   5Z <
   H ;
o uj:
a: £ i
                                                                                                                                         £ ne
                                                                                                                                         < u
                                                                                                                                         w
                                                                                                                                         a
                                                                                                                  Z  -I
                                                                                                                  OLUO
                                                                                                                  NJ-JZ
                                                                                                                  -
                                                                                                                                              3Q-Z
                                                                                                                                              -IOM
                                                                                                                                              OZUJ
UJMMX£££££MQ:
£zza.
-------
PAGE
U ^ND CHEMICAL GROUPS
<
u
M
r
u
X
u
u
HI
(9
8

UI
a
M
E
UI
Z
HOXY BENZENE SULFONAMIDE
t-
Ul
£
1
*
1
LAMINO
>-
a)
i
Z
1
m






UI
a
HI
_l
M
UI
U
<
i
HI
E
<
I
•f








ut
YLAMIN
Z
UI
£
M
to
1
-f



UI
Ht
_l
M
Z
<
o
tE
H
1
m
1
o

_l
u.
i
*



UI
HI
_!
V
Z
UI
£
POXYDI
O
a:
a.

M
i
*



YLANILINE) CARBINOL
X
1-
IU
r
M
Q
1
«k
z
1
V)
H
CO

*
•l
*



C-21

-------
N
CJ

ia

3
Q.
EMICAL GROUPS
CHEMICALS
  g
  O
                                                         aa
                                                         a
         iu

         UJ
IU
oa
 i


it
Ul H>

ii
a. Z
iu  i
             < < O -J
             z z H. >-
             IU UJ IU X
             u u u -i
             <<•<•<
r z zz
< < < <
< u   u

 -i
LU >- a. < M

^gsss
CE tsl I  UJ UJ
< < 03 03 CO
  UJ
a z
M UJ
U CE
< >•
  a
u  i
w •<
_i  i
M O
MM

UJ UJ
03 03
                    * *
to
a
IU

to in
UJZ

IU CE

555
000

32S
UJ UJ UJ
00 QQ GQ

* *
G
  UJ
  O
  M

IU O
z a
o iu
z a.
IU
x -i
a. >-
o o
                                                                        iu
                                                                        Q
                                                                        i
    UJ
u —i t-
H o <
< x o
I- O N
uj U Z
U -I UJ
< < ID -J

_J _J -I Z
    >- UJ
                                                  UJ UJ
                                                  CO 00
                                    !zz!
     UJ UJ UJ M
     oa oo aa 03
                                          o
                                          u
                                          >-
                                          _i»»
                                          tfi IU

                                          u§

                                          ^5

                                          2i

                                          > N Q
                                                                                   uj uj
                                                                                   )— f-
                                                                                        X
                                                                                   uj uj a
                                                                                   H- H 03
                                                                                   < < a:
                                                                                   _i _j <
                                                                                   < 4 U
                                                                §
                                                           Ul   M


                                                     .     i   i
                                                     H     X   UJ
                                                     _J     X UJ UJ
                                                     <     a. z z
                                                     X UJ UJ    UJ UJ
                                                     H> H- t— -J N IM
                                                                                        1-
                                                                                        <
                                                                                          UJ
                                                                                          a

                                                                                          x
                                                                                         1 O
                                                                                          a
                                                                                          UJ
                                                                                          a.
                                                                                          O
                                                                                          a:
                                                                                          o
                                                                                                                                in
                                                                                                                        8.
                                                                                                                        
                                                                                                                        o
                                                                                                                        HI
                                                                      LU
                                                                      H
                                                                      <
             ^"s
xffl —   O. D. X X >• >-
  £Z U     Q. I- X I— —I
  HI HI .» <7>   Z LU -

_i < >- u u -H C i  iz
>- £ - >•

H- K
UJ UJ

HI HI
a a
                    UJ
                    CCUULU
                     Bzz
                     UJLU
                    Hi MM
                    xzz
                    • UJLU
       in

>- a x z


LU O Q. —I


>•>->•>• >J^J—'

H* UJ LU UJ UJZCJ

^ E£ ££5S
M M M M tHMO
a Q o o aao
                                                                C-22

-------
Kl
CM
                                          -J UI
                                          < 1-
I
§
 UJ

 5
 _j
 _i
 <
  i
i >-
• X
                                             1-
                                            i x
                                          >• a.
5
g
  z

  (9
z o
UJ H-
  £UJ
  (J
-I <

U -I
UJ >

§z
Q UJ
     >-      O
     a   u x
         o o
     ->   >- u
     O   X -J
      •   Ul ^    UJ
—i    (j -J a   ui i-
O     I O -I -I Z •<
X     - Z < 5- Ul -J

S UJ  -XZZ-IU
JZcjO-uiuiow
< O  -   03 03 K -I
                                      _i -J o
                                      < < l
                                      z x
                                      P i-
                                      x x i
                                      Q. a.
                                        — — 3 X. -1
                                        _i _i i o. <
                               U
                               UJ X
                               O Ul
                               Z X

                               I  >
            -I -
            o fy rv
              3
                     Q- o o a
                     o z z z -J
                        £UI UJ UJ >-
                        X X X X
          <9txtzaaoa.a.cLt-
          3 3 3 >- z - —i
                     \— >-
                     a. x
                     UJ UJ
                     X X

                     z z
X >-
01 Z
x o
                                           i  a.
                                          N Ul
X X
UJ UJ
X X

z z
                                             -
                                             < ui
                                             x i—
                                             »— <
  ^   UJ

^=   5
V X   -J
u a. a < .
UJ    MX
Q _i u i-
 i >- < x
-4 O   P-
X UJ O
K Q M _1 _l
U  I  O >• O
o z z u z
 I    «< UJ UJ
-i -J H a x
>- >- Z   0.
X I- uj -J -i
ui u o. >• v
x a Q t- t-

       38
                                               Z Z Z i
     %<

  So?
  O M I-
-1 < O 3

iuSS
IU M UJ tO
X O CD H
0. M
>- Z -I -I
X UI >- >•
O CD t- X

-I X 03 UJ
>- O I  >

Sg£g
iu >- iu z
OJ X I- Ul
 III"
a. a. a.
                                                             miu
                                                                u
                                                             E <
                                                             3-1
                                                             M>-
                                                             -
                                                                  < X i
                                                                    UJ I
                                                                  (J O
                                                                  1-4 _l


                                                                  UJH
  in
  UI


  UI
  N


  UJ UJ

  03 Z
                                                                         X -I UI
                                                                         H- < 03
                                                                                -
                                                                                -J
                                                                                iu
                                                                                L)
                                                                    U
                                                                    <
                                                                    •
                                                                    u
                                                                  in M
                                                                  zo
                                                                  ui M
                                                                  a:z
                                                                 ' >• uj
                                                                                  a a
                                                                                  >- H
                                                                                  x u
                                                                                  UJ <
                                                                    ZZ
                                                                    iuuj
                              : >- z x
                              i o: uj HI
                               < 03 UJ
                                                                                  uiv>
                                                                                  z uj
                            tn >-
                            -i X
                            v o
                            X Q!
                     IU     H" W
                     H     IU 0.
                     <     z:
                     U-      I  Q£
                            < UI
                             I  t-
                   , ,,     uj in
              .-.-.zoaazuj
              ZDCUJMMtHUJ**J
              UJ-
                                                                                                 —
                                                                                                 >-
                                                                                                 x
                                                    h- >• IU -J
                                                    < X I- 3
                                                    O O < •'
                                                    SI 03
                                                                    lu
                                                                    o
                                                                    H
                                                                    a:
                                                                    a
                                                                                                                 <

                                                                                                                 u
                                                                                                               ui
                                                                                                               2
                                                                                                      11
                                                                                                      2£
                                                                                                      o o
                                                                                                      a: K
                                             in >-
                                             a u
                                      ui

                                   S5

                                   S1
                                   < UI

                                   iS

                                   zi
                                   < UJ
UJ

UI

Sui
a: Z

?s

§5
M 0}

5x
03 O
w X
a i-
                                                      o  z
                                                      M  IU
                                                      U  X

                                                      <  g

                                                      M  Z
                                                      -I  UJ
                                                      >-  CO
                                                      X  —
                                                                                                                                      o
                                                                                                                                      CD
-
MNJh-

cezu
I—UJO
UJCD—


5x-i-
NO I
                                                                        z ui uj _i _i                i: 3 >- v   :
                                                                        M_i2>->-EErz:uu->->-
a a. a.
                                      M  • • t-i  i MQ;
^_	              .    xaaaroina UIDQ
Z»HMi-it-iMMfflZH»-o:o;3a.    i   --i  -i>-
M_i_iaciaQQ:2Q:ii:H-t-—iMcvjcjwMto mj-x
3<
-------
13


Q.
             o
             Nl
  8

  _i


  u
  M

  IU


  U
   OT




   U
   M


   IU

   X

   u


   u
   M




   19
OPHE
OXY-BE
= <


•ffco1

xxS
00-1

§55
              I
             *
              I
             _l
             >-


             i
      a
       i
      in

      • >•
o a. -o x x
 ii-ii

* -f -f in •*•
il

^J§

xg
 i >•
in :
si


CMCMCMCMCMCtlCMtnOcb
              I
   <







   1
                                                               C-24

-------
m


I
at
                                                                                                       a o: os
                                                                                                       ai co a) muu
                                                                                                       M M M MMM
                                                                                                       o a a aoa
            * * *
                                                      C-25

-------
•o
OJ
01
(a
                                                                                                    I
    .
   i
   g
   IU

   5
   M

   LU

   5

   u
   M

   u>

   g
                                                          o Z M a. ui -J
                                                            §uj o O Z >•
                                                            N < -J < Q.
                                                                                                    O
                                                                                                    g
                                                                                                                •S-
                                                                                                                           in
                                                                                                                           a
                                                                                                                           UJ
                                                                                                                                   -i >•
aaaaoaa
                                                    LU UJ UJ	  _. ..
                                                  XXXXXXIHMI-I
 UJ              I
 Z             ro
 UI     IU      —
 N   iu a

 UI UJ UJ CX      tH IU
 CO Z N O IU   CE Q
 oiuz-JQujaM
 cx3iuxiHa>-Q:
 )--ICQU£MXO
 MOO   o o o -J
 ZI-CK-JBOCXX
 ~ ~ ~>-CQI-IOO
        —i      _i -j
        J—I —I -I X >•
        < >• >• u t-
ixxwxxxas
lOUQKI-t-ZCQ
  I  I   I UJ UJ UI O I
 Ecsrcrcz
                                                                                                        i a
                                                                                                        : uj
                                                                                                        11-
                                                                                                        i in
                                                                                                        : iu
                                                                                                        i    ui
                                                                                                        I -J Z
                                                                                                            M O >• 1
                                                                                                            -"per :
                                                                                                         55
                                                                                                       & a. a.
   01

S5
IU M
KJ Z
Z UJ
iu 01
CO O

gg
O -J
-J X
X U
U <
M I-
a Z
 I  IU
a. a
IU UJ    LU
Z O    X
UJ M    Q.
-J a UJ v-t
< o a a
X -J M
i- x a a
CL U O UJ
<   -it-

§^52
tx t-    1-1
O UJ -J CX
-J U >- O
X < O -J
O —1 —I X
< >- 1 U
H Z X >-
Z ui I	1
	          o
iu   Z     ujiu
X   w     t-O
a.   ex ui UJOH
H   a a i-za

i-   x it H-E-I
     O O UJOX
o ui ex -J UCEO
uj a o x -
Z O U O 0-"O
M -1      _lt-l-l
CK X UJ UI XO<
O U Z Z U  X
u   ui uj   Zl-
X -J -J -J E•>->• ^UJQ-
>- a. a. a. MCOUJ
-J o o O Q>-Q:
O ex CE ex o Ouj
o. a. o. r  	
   CD
   O
                                                                           C-26

-------
                                                                                                                                                     H
                                                                                                                                                     Ul
o

a.
         £M

         01
   a:
   to
   i
   ce
   o
                                                                                                                                                            ) <
                                                                                                                                                            r x
ui 3 u, >
Z CD M
M  I  Ce -I U I-
Q ro H- >- ce x
M  • I x O Q.
ce -« -r >- >- <
>•  I  I ui X Z
a. o o o o o
o ce ce a: ce C£
c o o o o o
O -i -I -I -I -1
ce x x x x x
ID U U U U U
 I   I  I  I   I   I
                                                                                                                                                                 OOQ
                                                                                                                                                                   ZM
                                                                                                                                                                  :a.a.
                                                                                                                                                                  3OO
XZZ
uuu
 I  I  I
NCUCVJ
   u
                                                                                    C-27

-------
(9

£
                           g
   OC.
   O


   -I


   (J
   u
   o
   M

   111

   u

   u
   M


   (9
   a
   o
cc
IU
                            IU
                 i  at i
                   h* '
                 i  i  i
                                  0!
                                  IU
                                           IU
                                        -

                                        O -I
            E!
     i at x
     : o u
      -J M
      -x.ee.
      u t-
      tH  I
      o -a
  i o in M o -J z >•
  : at  i  Q z >• iu z

xSvNxJuax

O X K- UJ O Q. Z
Q£ H IU (O D£    W J


X  I  O O X Z  I IU
UCvJO£*J(JIU
-------
                                                                                          01
                                                                                          I
                                                                                         u
Ul
  to
  O.
  in
  u
  g
  u
  1-1
  u
  o:
  O
  ex
  Ul
  5
a
M
U
g
U
U.
i
MWTHALENE
z
I
<

5
H
«•
Ul
a
H
on
o
< -
<
o
<

Ul
u.
_i
3
in
UJ
1
>•
x
_i
>
IU
§

<





L MERCAPTA
>-
<




a
IRANI LIC A
i-
<

u?
UJ
(J
CE
U
LSIFRJ
1A CHEMICA
0
<
*
0
I
3
o
Ul
Ul
_1
>- Ul
t- X H
-i £ <
s ₯ i
_l eo 0-
UJ 1 CD
U ' HI HH M £ L
M Ul N M Z h-
§Z Ul ^
ui 	 r -i
t-MOOUl M— >-
ZOKHO a Q- X
uj < < < IH i-m ui i-
a-HCCu. i3 uj H- ui
O O < < J — ui Z < >-
-J d 03 03 3 xU)H> UJ X X
a u o Z a or in *z< MO. o
(J UCJOXCJO'^ *HQH- ^O QUJ Ul
< M >- D o o -i uj - 3 uj >-( H x >- z a
CO U U, M M O Q -3- — ' 1- Z inUOLQ X MUJUIM
U XXZM — U<-XOUi<-3OD
ui-ii-i>>->-v tn _i -i ouua.Mza:M3xininin
Z3os>-un:o:ei;KxHO ui-JMujuji-iMOi-iHt-iQcain^^^^
•JUJM >*«J-J»JcOuJO2IZJ>->->->-
OZZJZXXXWI-I 1 SujEOLO£-l-IUJUJUj_l<«lN>>-XXXX
U UJ O >- 1 OUUQQO.W3;-OMZX3:i— h-h-h-
a.zzz)-inininininin-iz:Q:a!in-i-i_i-i-iuj<<<(iQujuizz:Es
ffi^tQ03COfOrt^fnf!r1lPCQL)^)Ot-JtJCJCJ<_fCLJtJtLJOQQQQOOQC?
* *

«,
a.
Q
«t
r
Kz
UJLU
UJZ
ZCD
UJOUJ
coinz
oo-<
CKCC-J
h-KO
zzo
QQQ
*
                                                                  C-29

-------
IU
is
  u
  M
  IU
  U
  I
  2
  u
  u
  ID
  CE
  O
                                                                                                              Z ZZZ
                                * *
  o
                                                         C-30

-------
u>
£
                                                                                                                a
                                                                                                                M
                                                                                                                U
a
iu
X
M
   in
   a
   u
   UJ
   s
   u
   M
   UJ
   5
   u
   M

   (9
   s
                                                  tn
                                                  C
                                                  K
                                                  O
                                                 UJ
                                                 0)
          in
        in 3
        cr M
                             5
                  UJ

                «n5
E O a. w    M
3 u. < Z    U
     S.J
     o >-
                                  §
                                  £
                                  o
§
 - a    <    -i
in M o  -    <
a u M -i         i

>   M *    UI f-
< u Z —'    ««   :
-i M < <       z
u. Z o:  i    ai iu
   OX  i o 3 uj ,
   u. h- in M —i ct

in 3 < z <
UJ in    M    H H !
c -i _i x u z z :
3 O >- Q. M ui UJ i
u. z z in a: S E
Of UJ UJ O O O O l
UJ X X X I-H W M
a. a. a. a. a. & & i

* *    x
   S1
   a
   UJ
   a.
   o :
   K I
   O <
   > •
   X •
     o   uj a
     UB   Q UJ
     -J UI M X
in «n 3 o u. t-
uj uj in w —j uj
        X 3 >-
     zO- >• M
Z Z
HH M
a. a.
                     Nl UI
                     < Nl
                     at <
                     UJ V
                     a. -J
                     M o
                     a. a.
: o o i
: NI N :
; < < i
 O M .
I H X '
! E H. :

 Nl N|
 Z Z
                                                            UJ UI <


                                                         z a a in
                                                         M W W O
                                                         in -j -J x
                                                         ui o o a.
                                                         o: a: a o
                                                            K cr at

                                                         Z Q. & a
                              *l
                              ui a
                              x >-
                              i- x
                              UJ  I

                              X?
                              Uj Q;
                              -J UJ
                              a. a.
                                                                                                                u
                                                                           i
                                                                           K
                                                                           O

                                                                           £
                                                                                                                iu

                                                                                                                tn
                                                                                                                UJ
                                                                                           §  3
                                                                                           t  5
                                                                                           UJ  O
                                                                                           x • uj
                                                                                           OUIln
                                                                         <
                                                                         (0 UJ
5                                                                           a in
                                                                           M a:
                                                                         u a uj
                                                                         o o t-
                                                                         w -J 01
                                                                         x x ui
                                                                         i- u
                                                                         M o a
                                                                         a a M
                                                                                                                                                     o >• ^ >•
     _1 -J _l _l

     £2S£
                 UJ Z

                 IE
                 _i .1
                 p o
                 Q- Q.
        a  -
        uj in
-j i:    NI ui iu
>- 3    w z i-
z M in z M <
M in uj a -i z
> in z ui o 1-1
>- < O i- z u,
-i K a < M u,
O O >- 3 3 <
a a. a. or or o:
-i u
O HI
Z -I

u u

§g
in in
UJ UJ
a ix
V   UJUJH3   O-IU
K   COHM   MM<
3   M M < Z   O tE
a   a N u. <   < h- u
M Z    <    Z      M M UJ
in x
 - u
in u
                                                            «         .-    —
                                                            W -i
                                                                                                                u. u
     _ujoa.l-3333
    iininininininminin
                                                                                                         I Q-—I
                                                                                                        _im>-
                                                                                                        >-ox
                                                                                                        zxv-
                                                                                                        UJQ.UJ
                                                                                                       l X  M
                                                                                                        Q.-IQ
                                                                                                        o>-^^
                                                                                                        El-tf)
                                                                                                        CE3M
             *  *
                                                                                    in in i

                                                                                    *
   i
                                                                            C-31

-------
CM
Kl
19
                                                                                 X
                                                                                 IU
                                                                                 a
                                                                                 IU
                                                                                 a.
  tn
  a.
  |
  UJ
  5
  3
  u
  M
  IU
  S
  u
  M

  S
PHONIUM SULFATE
s
£
j
>- Q
X M
1— U
IU ^1
5 u
§2
Q> Ul
a u
•^f UJ
m z
M U

2 O
UJ X
H H-






X
IU
a.
g
u
UJ

Q
M
X
H


IU
H

z
^
IISOC
a
i
CM
IU
55
a 3
M -I
X 0
1- H
CM X
CM
i a
IU H
a z u
u M iu in <
UJ >- U H N IU
. • z z < . -i z a u
IU UJ • • IU • < IU M M
x M -HO -J tntar-i
HO _J M O O «t >•
iu< «: z NI u NI x x
HH in o < z < o o
— Z-J X" M M 03 03
_i iu < go. x Miuoceo:
>- a. iu tn 3 en t- — i a < •<
§0 H MO O - O 0 0 U
-J < £ gx N UJNI-I
i- u- u z 5 o a. z a < x iu uj
< J >- O M V) M UJ tn M M U Z Z
5D O M 0 Q UJ UJ J UJ CO -J a X X i UJ UJ
in-iao " i zzoz to uio>-in-J-j
>- -I >- O U1 O — M M Z M IU — Z Z IOI <«C
U >• x a: iu M -J-UJMN• xx
O a.HO.»H U O->Z-rt- •< a. OQXZ<>->-O.>->-UJIO:Q omaiu<<
o iNZu.tn Mujh-- x z z
i z uj _i o in zxuaxi— — i_icMuj-j>-zi-ia:o xcoxa-i i
O — -< U 3 X Q: OMUJt-X>-VIQ_>-XHZMZU1 HOMOCMCMIU
- viu«na.-owinu.czuja.xzi-iozo-iiMujuj 011-11x0:1 -->-lu
ZMoa-i-iiui-uj3inaxzuJx>-zxHX i -J o. M o M p- i M x x -i
iuiucaca-J>->-3iuu)in-ii-iaa2:a.xiua.uia.a>-o_tzc3>-i- z o o o
ZX 1 Q£OCJh*-J OIUOttKCCMMOCC^MQfZXQEO^MO^MQSQIU-
ULio.in<>-iuoca-JxzzMai— a o i i aoo»-ih-t— uza: i - a a o -J
3 < Z (J O Q >- >- t— IU UJ N >• M 1 I-CJI l£ClUHMM>--- 1 >- >- 3

* * * * *


a
M
1

u
M
o
2
IU
EQ
O
K
1-
Z
a
i
"^
CI

IU
M
C
<
M
a
UJ
UJ
_)
s
UJ
£
1
O
O
t-
M
t
sT



IU
Z
£•
<
_l
>-
LU
X
a.
M
O
o
in
o
i—
M
Z
•»•






_l
UJ
£
§
a
f_4
z
*




IU
IU
LOHEX
u
u
1
1
z
M
1
*
ISULFONIC ACID
0
CM
CM
1
IU
IU
STILB
t
o
HI
§
M
a
i
•
*
*




_,
o
in
IU
a:
u
i
O
o
C£
H-
>H
M
a

•o
*


UJ
a
M
cc
o
UJ >-
_J x
o z
N <
a u
t-4 M
z a
M <
Nl Z
IU
Srf
a: x
t- t—
M U
Z E
i i
•a r~
  I
  s
                                                              C-32

-------
II.  INDUSTRY SURVEY AND OVERVIEW

-------
                      II.  INDUSTRIAL SURVEY AND OVERVIEW
                               Table of Contents
1.  Industry Section 308 Survey                                  1
2.  Industry Overview                                            3
                                 List of Tables


Table                                                          Page

  1     Mode of Discharge - Plant_Counts by Subcategory          8
        and Type of Questionnaire Response

  2     Median Subcategory - Annual Production by Mode  of         9
        Discharge and Type of Questionnaire Response

  3     Median Subcategory Flows by Mode of Discharge and        10
        Type of Questionnaire Response

  4A    Direct Discharge In-Place Treatment Plant Count         11

  4B    Indirect Discharge In-Place Treatment Plant Count        12

-------
                       II.  INDUSTRY SURVEY AND OVERVIEW

1.  INDUSTRY SECTION 308 SURVEY

     Since proposal, on extensive data gathering program has been conducted to
improve the coverage of all types of OCPSF manufacturers.  This effort included
mailing Section 308 surveys to all manufacturers of OCPSF products.

     For the purposes of the survey, the OCPSF industry was defined generally
as all establishments that manufacture:  (1) organic chemical products included
within the U.S. Department of Commerce Bureau of the Census Standard Industrial
Classification (SIC) major groups 2865 and 2869 and/or (2) plastics and synthetic
fibers products includ'ed in SIC major groups 2821,  2823, and 2824.'  However,
organic chemical compounds that are produced solely by extraction from natural
materials, such as parts of plants and animals, or by fermentation processes
are not included in this definition of the OCPSF industry even if classified in
one of the OCPSF SIC classifications.  Thus, any such products were considered
non-OCPSF products for the purposes of the survey.

     The questionnaire mailing list was compiled from many references that
identify manufacturers of OCPSF products.  These sources included the Economic
Information Service, SRI Directory, Dun and Bradstreet, Moody's Industrial
Manual, Standard and Poor's Index, Thomas Register, and Plastics Red Book as
well as internal Agency sources such as the NPDES Permit Compliance System and
the TSCA Inventory.

     In October 1983, EPA sent the General Questionnaire' to 2,829 facilities to
obtain information regarding individual plant characteristics, wastewater
treatment efficiency, and the statutory factors expected to vary from plant to
plant.  The General Questionnaire consisted of three parts:  Part A (General
Profile), Part B (Detailed Production Information), and Part C (Wastewater
Treatment Technology, Disposal Techniques, and Analytical Data Summaries).

-------
     Some plants that received the questionnaire had OCPSF operations that were
a minor portion of their principal production activities and related wastewater
streams.  The data collected from these facilities allows the Agency to
characterize properly the impacts of ancillary (secondary) OCPSF production.
Generally, if a plant's 1982 OCPSF production was less than 50 percent of the
total facility production (secondary manufacturer),  then only Part A of the
questionnaire was completed.

     Part A identified the plant, determined whether the plant conducted
activities relevant to the survey, and solicited general data (plant age,
ownership, operating status, permit numbers, etc.).   General OCPSF and non-
OCPSF production and flow information was collected for all plant manufacturing
         *
activities.  This part also requested economic information including, data on
shipments and sales by product groups, as well as data on plant employment and
capital expenditures.

     Part A determined whether a respondent needed to complete Parts B and C
(i.e. whether the plant is a primary or secondary producer of OCPSF products,
whether the plant discharges wastewater, and, for secondary producers, whether
the plant segregates OCPSF process wastewaters).  For those plants returning
only the General Profile, Part A identified the amounts of process wastewater
generated, in-place wastewater treatment technology, wastewater characteristics,
and disposal techniques.  Part B, requested detailed 1980 production information
for 249 specific OCPSF products, 99 specific OCPSF product groups, and any
OCPSF product that constituted more than one percent of total plant production.
Less detailed information was requested for the facility's remaining OCPSF and
non-OCPSF production.  Part B also requested information on the use and known
presence of the priority pollutants for each OCPSF product/process or product
group.  Part C requested detailed information on plant wastewater sources and
flows, treatment technology installed, treatment system performance and disposal
techniques.

-------
     Responses to economic and sales items in Part A pertain to calendar year
1982, which were readily available since the plants were required to submit
detailed 1982 information to the Bureau of the Census.  This reduced the
paperwork burden for responding plants.  The rest of the questionnaire, however,
requested data for 1980 — a more representative production year.  The Agency
believed that treatment performance in 1982 would be unrepresentative of
treatment during more typical production periods.  This is because decreased
production normally results in decreased wastewater generation.  With lower
volumes of wastewater being treated, plants in the industry might be achieving
levels of effluent quality that they could not attain during periods of higher
production.  The year 1980 was selected in consultation with industry as
representative of operations during more normal production periods but recent
enough to identify most new treatment installed by the industry since 1977.
The industry representatives did not assert that significant new treatment had
been installed since 1980.

     The 2,829 Section 308 questionnaires were mailed in October 1983.  In
February 1984, Section 308 follow-up letters were sent to 914 nonrespondents.

     A total of 981 OCPSF manufacturers were used in the analysis; 1,529
responses were from facilities not dovered by the regulation (sales offices,
warehouses, chemical formulators, etc.); 162 were returned by the Post Office;
and 159 did not respond.  A follow-up telephone survey of 52 nonrespondents
concluded that less than 10 percent would be covered by the OCPSF regulations.

2.  INDUSTRY OVERVIEW

     The OCPSF Industry is large and diverse, and many plants in the industry
are highly complex.  The industry includes approximately 1000 facilities which
generally manufacture products under the OCPSF SIC Groups - SICs 2821, 2823,
2824, 2865, and 2869.                                        —-—~

     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 in
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 different
products in a variety of continuous and batch operations, and the product mix
may change frequently.

     For the 981 facilities in the OCPSF industry data base, approximtely 76
percent of the facilities are designated as primary OCPSF manufacturers (over
50 percent of their total plant production includes OCPSF products) and
approximately 24 percent of the facilities are secondary OCPSF manufacturers.
Approximately 32 percent of the plants are direct dischargers, approximately 42
percent are indirect dischargers (plants that discharge to a publicly owned
treatment works) and the remaining facilities use zero or alternative discharge
methods.  The estimated average daily process wastewater flow per plant is 1.22
MGD (millions of gallons per day) for direct dischargers and 0.24 MGD for
indirect dischargers.  The remainder use dry processes, reuse their wastewater,
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
processes used and of products manufactured in the OCPSF industry, an exceptionally
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
nonconventional pollutants (including the organic compounds produced by the
industry for sale).

-------
     To control the wide variety of pollutants discharged by the OCPSF industry,
OCPSF plants use a broad range of in-plant controls, process modifications and
end-of-pipe treatment techniques.  Most plants have implemented programs that
combine elements of both in-plant control and end-of-pipe wastewater treatment.
The configuration of controls and technologies differs from plant to plant,
corresponding to the differing mixes of products manufactured by different
facilities.  In general, direct dischargers treat their waste more extensively
than indirect dischargers.

     The predominant end-of-pipe control technology for direct dischargers in
the OCPSF industry is biological treatment.  The chief forms of biological
treatment are activated sludge and aerated lagoons.  Other systems, such as
extended aeration and trickling filters, are also used, but less extensively.
All of these systems reduce BOD and TSS loadings, and, in many instances,
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 OCPSF 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, some direct dischargers use
only physical/chemical treatment.

     In-plant control measures employed at OCPSF plants include water reduction
and reuse techniques, chemical substitution and process changes.  Techniques 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 amendable to
treatment.  Process changes include various measures that reduce water use,

                                       5

-------
waste discharges, and/or waste loadings while improving process efficiency.
Replacement of barometric condensers with surface condensers; replacement of
steam jet ejectors with vacuum pumps; recovery of product or by-product by
steam stripping, distillation, solvent extraction or recycle, oil-water separation
and carbon adsorption; and the addition of spill control systems are examples
of process changes that have been successfully employed in the OCPSF industry
to reduce pollutant loadings while improving process efficiencies.

     Another type of control widely used in the OCPSF 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 biological system or to remove
certain pollutants that are not removed sufficiently by the biological system.
In-plant technologies widely used in the OCPSF. industry include sedimentation/
clarification, coagulation, flocculation, equalization, neutralization, oil/water
separation, steam stripping, distillation, and dissolved air flotation.

     Many OCPSF plants also use physical/chemical treatmnt 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.

     At approximately 9 percent of the direct discharging plants surveyed,
either no treatment or no treatment beyond equalization and neutralization is
provided.  At another 14 percent, only physical/chemical treatment is provided.
The remaining 77 percent utilize biological treatment.  Approximately 42 percent
of biologically treated effluents are further treated by post biological controls
such as polishing ponds, filtration, or activated carbon.

     At approximately 39 percent of the indirect discharging plants surveyed,
either no treatment or no treatment beyond equalization and neutralization is
provided.  At another 47 percent, some physical/chemical treatment is provided.
The remaining 14 percent utilize biological treatment.

-------
     The mode of discharge counts by type of questionnaire response are shown
in Table 1 for each subcategory or category.  As noted before, full responses
were returned by primary producers of OCPSF products as well as secondary
producers with dedicated OCPSF wastewater treatment systems (25 percent or less
dilution of OCPSF wastewater).  Part A responses were returned by zero discharge
and alternative disposal plants as well as other secoadary manufacturers of
OCPSF products.  The "mixed category" includes those plants that cannot be
assigned uniquely to one subcategory.  The "secondary organics and zero discharge
primary organics category" includes those Part A-only-response plants whose
total production is 95 percent or more organic chemicals (SICs 2865, 2869,
29110582, and 29116324); however, the Part A information is insufficient for
assigning plants to a commodity, bulk, or speciality organic chemical subcategory.
Subcategory and category median annual OCPSF production figures, .median process
wastewater flows, and in-place treatment by mode of discharge and type of
questionnaire response are shown in Tables 2, 3, 'and 4, respectively.

-------













-























-*
Ed
J
09
H





























































Ed
CO
z
o
o<
CO
Ed
2
Ed
BS
1— 1
<
O
M
CQ
VJ
• Ed
3
cr
Ed
U Ex.
at! o
«S
S Ed
S a.
CO >*
1-1 H
Q
0
Si
Ed S-
Q a!
0 0
z o
Ed
E->
5
CJ
aa
r>
CO

><
CO

CO
!



E-
z
cu

























z
Q
j2










o
a:
Ed
M











H
U
EL
ae
^

2
H






H
O
Ed
at:
M
f}
Z
M
••^
H
O
Ed
as
i— i
d








H
U
Ed
as
M
o




J
£
O
H
Cd
CO
-3 Z
J O
3 0.
i. en
S
JM
£5!
< O
a.
<
<
H
O
H
Ed
CO
•J Z
J O
£O4
CO
Cd
S
>•
f- J
a: z
< O
o.
<
j
^
0
H
Ed
to
J Z
i-] O
£0.
CO
Ed
od

H 3
as z
< o
0.
<
J
<
s
H

Cd
to
J Z
-3 O
3 0.
CK CO
Ed
5

>i
S^
< 0
a.
<
-;
S
H
Cd
to
-J Z
J O
£0.
CO
Ci
fi£
n2
2=: z
<: o
a.
<
IIICM 1 Illsocn -m vom
o en ^ao m
CM




Illen— iien-nl loo




ip^.tncM m l-Hlaoin ^OPX
\o tn -ff * -?
CM

1 r^ ejN in O — 
CM



llOmen i||-.-4 IO
CM i-i CM m — •
•«.


Ili^en en lencncM'H -HI>.






IIMCM CM lenencMl — -3-
^H
^ .
*~


lll-H—i llll-H In




eno^^oo ^o p^encjNinr^. ^HO
-^eM^-rn cMincMcncs a>
CM




enor»r-i 
i— i'Hj'fn cMmcMcM • >
a: X.
O C
o o
Cd Cd
55
U U
so
3 t*
CO O
U | 1
n> to < >> ^
^(yrtp^rHOU U u >» "*
CljWCi.CCU'^^-t ^H C0*^5^ C CO
OOOOiOC'W ra t! ea 3 e^
CUES E_i u a uuao E Jai <-> n oaoii^ao c ran
>, ^ V OI-H 0) •-! 1- 6 —i CJ X UUiCUUUi ^ U
r9 u j= £u f>UQ O 3 Q- — ' 4IONCLO C OZ
as O E- E^ H oOJCOZtn 3 H ^^

-------
















































CM

Cd
»J
CO
^J
H












































































^
04
0
c
w
H

CJ
CO

cn

*y.
^
M
a
Cd





































*
Cd
CO
z
o
a.
cn
cd
04
cc
04
M
<
Z
z
o
M
H
cn

3
o-

Cb
o
Cd
a,
H
o
z
4*

Cd
CJ
O4
^
X
CJ
cn
M '
a

Cb
o

Cd
Q
O
£ •

«

^S
to
z
8
H
OS
O
Z
cn

0
o
o^
r-t
x^
Z
O
M
H
CJ
a
o
as
a,
J
«C
3
Z
Z
<



-
5
o
z
§2
9





»J
g
Cb



EH
28
ex













Q

Cd
M







J
J
3
Cb




g-l
OS
^
O4









H
CJ
CO
OS
M
Q
Z
M





J
J

Cb




H
04
•<
a-








e
Cd
04
M
a
z
i— i
"H
CJ
Cd

M
O

j
r_^
S
C*H


H

^
ftrf







H
O
04

O




J
J
£



H
^
p t




Cd
cn
Z
o
(X
cn
Cd
OS
SM
,J
Z
O

••C



1





1








Cd
cn
z
o
04

Cd
OS

^4
^

Q

^J



1







1







Cd
cn
z
o
04
cn
Cd
OS

^
>J
Z
o

^



1



.



1










Cd
Z
o
04
cn
Cd
j^
,j
J2
Q

^


1






1





cn
z
o
a-
1

><

Q

^

m
•
00




1





I        I       I       I
I        I       I
        I       I
              oo
                                                        oo
                                                          •
                                                        oo
                                 (M
                                   •

                                 CM
                                                                        00
                                                                       —•      c^
               in
                                                               cn

                                                               \o
oo


vO
                                                                               in
                                                                               CM
 c
 o
•H   cfl
4J   4-1
 O   «
 3  T3
X)
O   C
M   O
a. -H
     u
•a   o
0)   3
w  -a
l-i   O
o   tj
a.  o.

en   o
c   a.
O   01
a.  )j
ca
a>   en
cc;   ai
     en
>^  C
•-^   o
c   a
O   tn
     0)
<  04
                                                                                                              (0  3
                                                                                                             Cu Cb
                                                                                                             CM
                                                                                                             CM
       0)
       .a
jj
01
CO
01
CO
^1
Ol

H
1
cn
i— i i— i
a c
0 O
U U
Ol -H
f^ ^ i
H
moplas-
^4
01
Si
H
.
0
T-l
4_l

anics
oc

O

4J
•H
•o
o
s

o
CJ

V
rH
3
CQ
S^
i— t
(0
•<-i -a
o oi
0) X
Ck> *^
cn S
u
S3
•o
C
O
y
cu
cn
M,
M
u
O

u
o s

01 W
N 0-

•
M
^4
O

                                                                                                              0)   0)
                                                                                                             M-l U-l
                                                                                                              O  O

                                                                                                             a\ in
                                                                                                             -c in
                                                                                                             en in
                                                                                                             •K

-------































en

W
pj
"
H




























































*
W
to
z
o
ft.
CO
u


u
0*
M
O Z
o z
•5 2
to 'to
3 Cd
Cb
Cb
>- O.
OS
O M
U ft.
Cd JM

^j
U P
so z
3 •<
to
cd
z u
< OS
M <
a x
u u
£ CO
M
a

Cb
o

Cx3
o
o


«






























o
*
w
N



cd
CO
1-3 Z
d °
3 ft.
Cb tO
M
2

^4
H J
3§
ft.

es •*
r-4 i-* O
ON O O
• • •
O O 0



F-H
00 O
1 O O
o o










G
W
M
O
Z
M


W
to
J Z
J 0
3 a.
Cb CO
u

^4
H -J
OS Z
< O
ft.
<

m «M
CM -> £.
c£ C E-1


vH
^^
0
*
0



^v|
0
o
o







ff*
^'
o
•
o


\o
o
0
•
o






f>
^»
\Q
•
o




vO
fsj
*
^H








* c -o
e n o
i- cj oo E
01 -H M S
J= u O O
H 0


^ o
O — i
o — <
• •
o o





1 1








m
"^ ^O
0 0
• •
0 0



i i







O 00
r~ in
m o
• •
0 0






1 1









CO ^^
OO f^»
CN CN
• •
O 0





1 1








^
u
^
m
•H
Ji! O
i-t 01
3 0.
oa to


en
p-4
0 1 1
•
o



en ^
O en
O O 1
• •
0 0







00 CM
en O
0 1 —
t •
0 0


vO CN
O en
0 0 1
• •
0 0






vO • O
*^ *^
O 1 O
0 0





en
1 • 1









ON r*»
— o
ON 1 0
• •
0 0



CN
en -*
O en I
• •
0 0






^
S-i X

•o nj 3
•a c • o e • a
01 O 60 !•< i"l 00 C
X u U 01 U M X.
•H- 	 -«^O"!Sl'ft. O C
S CO 3




































CS
u .
CO
t3
S
O
1-1 cr
U-l

•a
01
4-1 3
»- c
O —
p i^ .
01
>-i -a
01
Cfl U
01 U
«1 O
c c.
O OJ
C. b
CO
01 U
a: 01
en
^ c
1-1 O
c e.
o en
O)
^ Q^
U F— .
l-> —
« 3
ft. &
CM ON
CN in
^ LP

0) SJ

U L.

U-l U_
O C

00 r-
CN in
10

-------
oa
         o
         a
         at
         (U
         CO
         c
         c
         o
         en
         at
         3
         ai
         a
        •o
         c
         CO
         o
         tsc
         a>
         4J
         CO
         U
         J2
         3
         en
 C
 3
 O
O
         c
         CO
         C
         01

         u
         CO
         01
         0)
         y
         CB
        I— I
        a.
         i
        *
         01
         60
         U
         CO
        .e
         o
         en
         y
         01
         iu

t"*
Q <
Z O
3 M
o
i-3 O
< J
UJK
O
1— > 1— 1
O CO
O 1

o en
M O
pa a.


K-I

O
o
s
0
03



j
^
^
g
U
X

J
CJ
M
en

s


£— <
J2
Cx3
£
6"^
 Ol — ( Ol -^ — l




1 1 1 -1 1 1 1 1 <• <*,





• -- 1 eo -• m vooi.^---!
^





I 1 -N 04 01 1 1 1 -i ST






1 *-^ CO P^ Ol 1 *^ CO ^^ 1






1. 1 01 01 1 1 1 1 —1 01

^-i -a w tn
C c y y
O CO i-( i-l >s
ecu
en en co co co
y y 60 en 60 -a
en -H 1-1 u y u c
(J 4J iJ O -H O O
01 en w en e y
•O j»j cc co ^t co ^*i CD
f^0i^i~^en4->6ow cnen
J*T , (J3 Q. Q^ ^J (f^ ^J ^^ (^
O O O i^ ^3 fO CO ^^ "^
C IJ S E 6 C O iH*O C
o oi u u u ft £ j£ y eu uco
>,^I Ol 01 0>60£rH 01 X U 60
cOujz^^S>i O 3 a.i-1 03 l-i
aSOHHHOUo3enz;a,o



vD
r^N






CO
Ol




^^
01




,^
p-1




CO
CO





o
*-4





i»H
01
f




f*



en
^^
CO
4-1
O
4J
J3
3
en

c
s
3
rH
O
a





^N
s~s
CT^ CO
•>»x










in s-s
i— i >^-
^









/^
^
-3- iH













OO S^S
01 c\





en
i— i
CO
4J
O
H

u ^^
c in
01 O
E ro x-s

co II b
Ol O
U Z —1
p-^ ^-X s^1
                                                                                                                                                                      C
                                                                                                                                                                      CO
                                                                                                                                                              c.

                                                                                                                                                              0>
                                                                                                                                                              U
                                                                                                                                                              X
 o
 cu
 14
iH
•c
 c
                                                                                                                                                             T3


                                                                                                                                                             T!
                                                                                                                                                              01
                                                                                                                                                              C
                                                                                                                                                                      O
                                                                                                                                                                      y
                                                                                                                                                              c
                                                                                                                                                              •3
                                                                                                                                                              O
                                                                                                                                                              y

                                                                                                                                                              tn
                                                                                                                                                              01
                                                                                                                                                             T3
                                                                                                                                                              3
                                                                                                                                                             i—I
                                                                                                                                                              y
                                                                                                                                                              c
                                                                                   11

-------
•a
 =•
 e
e
o
CO
-c
H
        o oc
cu  -I 1 1 CN 1 I







1 1 1 1 1 1 t I «N 1





1 I O vO CN CN 0-1 CN CN 1




| | CN — — I 1 ' 1 1 rO




,
1 ^ o^ oo vO on u^ r**« ^^ |
C*4 C*J fO C^4

1 1 O r». I | | | ao -tf
— n





linoonoo vomr^cNl
t-H 0^ «i-4 m i-^



I I co i^ CN i | | _ 1
co co to to to
U U SO 03 SO T3
CO -H iH U O l-l C
U i-i u O — * O O
01 en co en c u
o 4J to to >*» CO ^ 0)
^^^^^icousou ooco
£b CO CU C- O «H V4 '•H CJ
O O O *H "O O *0 ^ "^
c u s £ 6 c o •H'O c
O 01 iJ t-i 1-iCQ E ^ U 01 \ sz oi 01 oiaoS1"1 oi x PSO
co*jj=j:j=>-i o 3 a. -H cou
oiOHHHOcja3ooso«o



C7N







CN





fO




r~-





O


Q^
in
*




^.
*^
"™*


fsj
«^



CO
_j

u
o
4-1
,G
3
W

C
E
3
p—H
o
0






*~4 3^5
— i fO
>^









s^
<• — i
^^






•

oo f*^
v— '









VO P
C






CO
^
to
jj
o
s-

U /" N
C O
O) O
s <• ^

to u b
01 O
1- Z —
H ^ ^
                                                                                  12

-------
III.  TECHNOLOGY BASIS FOR BPT OPTIONS AND
       DERIVATION OF EFFLUENT LIMITATIONS

-------

-------
III.  TECHNOLOGY BASIS FOR BPT OPTIONS AND DERIVATION OF EFFLUENT LIMITATIONS

                               TABLE OF CONTENTS
                                                                     Page
1,  BPT TECHNOLOGY BASIS	    1
2.  DERIVATION OF LIMITATIONS	    2
    2.1  LONG-TERM SUBCATEGORY BOD AND TSS AVERAGE	    2
3.  DERIVATION OF BOD AND TSS VARIABILITY FACTORS	    5
4.  BPT EFFLUENT LIMITATIONS	    9


                                  APPENDICES
APPENDIX A:  BPT STATISTICAL METHODOLOGY
APPENDIX B:  HYPOTHESIS TESTING             •   .

-------
III.  TECHNOLOGY BASIS FOR BPT OPTIONS AND DERIVATION OF EFFLUENT LIMITATIONS


                                LIST OF TABLES

Table                                                                Page

1.  RANGE OF PERCENT DILUTION FOR DIRECT-DISCHARGE, FULL-RESPONSE
    PLANTS                                                             3

2.  SUBCATEGORY LONG-TERM MEDIAN CONCENTRATION VALUES VS.
    TECHNOLOGY AND PERFORMANCE EDITS                                   6

3.  RATIONALE FOR EXCLUSION OF DAILY DATA PLANTS FROM DATABASE         9

4.  BOD VARIABILITY FACTORS FOR BIOLOGICAL SYSTEMS                    11

5.  TSS VARIABILITY FACTORS FOR BIOLOGICAL SYSTEMS                    12

6.  OPTION I BPT LIMITATIONS BASED ON BIOLOGICAL TREATMENT WITHOUT
    POST-BIOLOGICAL CONTROLS                                   .       13

7.  OPTION II BPT LIMITATIONS BASED ON BIOLOGICAL TREATMENT WITH
    AND WITHOUT POLISHING PONDS   .               '     -            '    13-

8.  LONG-TERM TSS VALUES FOR BIOLOGICAL SYSTEMS                  '     15

9.  OPTION III BPT LIMITATIONS BASED ON BIOLOGICAL TREATMENT WITH
    FILTRATION AND BIOLOGICAL TREATMENT WITH POLISHING AND FILTRATION 17

-------

-------
                    III.  TECHNOLOGY BASIS FOR BPT OPTIONS
                    AND DERIVATION OF EFFLUENT LIMITATIONS
BPT TECHNOLOGY BASIS
     Three technology options are being considered for BPT.  These options
focus on the primary end-of-pipe technologies used in the industry.  These
technologies are widely used in the industry to control conventional pol-
lutants.  To varying extents, these technologies also remove toxic and non-
conventional pollutants.  However, it is not possible to calculate consistent
removals of specific toxic and nonconventional pollutants across the industry
without carefully considering a variety of process controls and in-plant
treatment technologies that are more appropriately considered to be BAT
controls and technologies.  Therefore, the selected BPT technologies are end-
of-pipe technologies that are designed primarily to address the conventional
pollutants BOD and TSS, supplemented by those in-plant controls and tech-
nologies that are commonly used to assure the proper and efficient operation
of the 'end-of-pipe technologies.

     Option I:  The first BPT technology option is based on biological
treatment preceded by the necessary controls to protect the biota and other-
wise assure that the biological system functions effectively and consistently.
Activated sludge and aerated lagoons are the primary examples of such biolog-
ical treatment.  Other biological systems, such as aerobic lagoons, rotating
biological contractors, and trickling filters, are also used effectively at a
few plants, and data from such plants were also used to develop BPT
limitations based on this option.

     Option II:  The second BPT technology option includes, in addition to
Option I technology, biological systems followed by polishing ponds.  In some
cases, plants originally installed biological systems that had inadequate
retention times or were otherwise not designed and operated to optimally treat
conventional pollutants.  When these plants were required in the late 1970s to
upgrade to meet BPT permit limits (established by permit writers_J,fl^4.ha-
absence of guidelines on a case-by-case basis, using their best engineering
judgment), some chose to add polishing ponds rather than to enlarge or
otherwise improve their existing biological systems.
                                     -1-

-------
     Option III:  The third BPT technology option is based on multimedia
filtration as a basis for additional TSS control after biological  treatment.

2.  DERIVATION OF LIMITATIONS
     The BPT technology assessment and derivation of limitations focussed on
the 253 direct-discharge, full-response plants with sufficient production data
to establish subcategory assignments.

     Since the limitations apply to process wastewater only, the relative
contributions of process and nonprocess wastewater were determined at the
effluent sample sites.  These data were used to calculate plant-by-plant
"dilution factors" for use in adjusting'pollutant concentrations at effluent
sampling locations.  For example, if BOD was reported as 28 mg/1 at the final
effluent sampling location with 1 MGD of process wastewater flow and 9 MGD of
noncontaminated nonprocess cooling water flow, then the BOD concentration in
the process wastewater was actually 280 mg/1.

     Sufficient information was.available for 224 direct discharge plants to
assess process wastewater dilution.  Of these, 111 plants diluted  the process
wastewater before effluent sampling sites.  The remaining plants either did
not dilute or provided insufficient information to make a determination.
Table  1 relates the number of direct-discharge, full-response plants in their
assessment to the range of dilution at the NPDES monitoring sites.

2.1  Long-Term Subcategory BOD and TSS Average
     After selecting  technology options, associated limitations were developed
based  on the "average-of-the-best" plants that use these technologies.  A
statistical criterion was developed to segregate the better designed and
operated plants from  the poorer performers.  This was done to assure that the
plant  data relied upon to develop BPT limitations reflected the average of the
best existing performers.  Since the database Includes many plants which are
poor performers, it is necessary to develop appropriate crirfeeTta'foT: differen-
tiating poor plant performance  from good plant performance.  The criterion
                                      -2-

-------
                    TABLE 1
                x
         RANGE OF PERCENT DILUTION FOR
    DIRECT-DISCHARGE, FULL-RESPONSE PLANTS
  No. of Plants             Range of Dilution
in Assessment (%)              in Percent	
    113  (51%)                       0

     39  (17Z)             .     >0 to 25

     35  (16Z)                  >25 to 100

     23  (10*)                  MOO to 500

     14   (6Z)                  >500 to 17,400

    224 (100%)
                     -3-

-------
selected was to Include in the database any plant with a biological treatment
system that, on the average (1) discharged 50 mg/1 or less BOD after treat-
ment, or (2) removed 95 percent or more of the BOD that entered the end-of-
pipe treatment system.  This criterion reflects the performance level  that is
generally achieved by well-operated plants in the OCPSF industry that  use the
recommended BPT technologies.

     These are the same performance criteria utilized at proposal.  Many
industry comments suggested that EPA unreasonably screened the database for
establishing "average of the best" BPT technology and suggested that a more
liberal indicator of performance, such as 85 percent removal, should be used.

     To assess this recommendation, BOD  data was evaluated from the 163
Section 308 questionnaire full-response plants in the direct discharge
database with biological treatment systems.  After adjusting the data  for
nonprocess wastewater dilution, the median BOD- percent removal for all
facilities is 95.4 percent, and the median effluent concentration  is 28 mg/1.

     The more liberal editing rule suggested by industry was considered for
excluding plants with poorly operated or inadequate biological treatment
systems.  Using the industry's suggestion, plants would be retained for
analysis if at least biological treatment was in place and if, on  the  average,
the  treatment system removed 85 percent or more of the BOD, after  treatment.
These criteria would retain 87 percent of all the biological treatment systems
reporting BOD. data.

     The "95 percent or more BOD. removal or 50 mg/1 or less BOD,
concentration after treatment" performance editing criteria retains 76 percent
of all  the biological  treatment systems reporting BOD  data.  The  subcategory
BOD  and TSS median values were calculated for both performance editing rules.
Using the 95 percent/50 mg/1 performance edit reduces  the average  subcategory
BOD  and TSS median values for Option  I treatment technology approximately  10
and  16  percent, respectively, below those obtained using the 85 percent/100
mg/1 edit.  Similarly,  the average median values for Option II treatment
technology  are reduced  approximately  11 and 4 percent, respectively.   The
                                      -4-

-------
median BOD. percent removal for all facilities is 95.4 percent  and  the median
effluent BOD. concentration is 28 mg/1.  Based upon all these facts,  the  "95
percent/50 mg/1 BOD," performance editing criteria is believed  to provide a
reasonable determination of "average of the best" BPT performance.

     The long-term BOD- and TSS averages for each subcategory are shown in
Table 2 for several technology and performance edits.  The technology edits
include all biological systems, biological systems without post-biological
solids control, biological systems with and without polishing ponds,  and  all
direct dischargers with data (no editing rules).  The performance edits
include no edits, "85 percent/100 mg/1 BOD5," and "95 percent/50 mg/1 BOD5."
The last column in the table, identified as "(Mixed)," lists the median values
for the 28 plants that are not uniquely covered by one subcategory.   The
selected BPT technology and performance edits are labled as "(Option  I) and
(Option II)" in the table.
3.  DERIVATION OF BOD AND TSS VARIABILITY FACTORS
     To establish maximum 30-day average and daily maximum BODe an<* TSS
effluent limitations for each technology option, variability factors were
determined for biological treatment systems.

     The OCPSF database contains daily data from 69 plants.  The daily data,
including flow, BOD, and TSS, were automated along with sampling site identi-
fication treatment codes.  The treatment codes provided specific identifica-
tion of the sampling site within the treatment plant.  For example, effluent
data were identified as sampled after the secondary clarifier, after a
polishing pond, or after tertiary filtration.

     After the database was established, the data at each sampling site were
compared with the treatment system diagrams obtained in the Section 308
survey.  The comparison served to verify that the data corresponded to the
sampling sites indicated on the diagrams and to determine if the_data,_w,e.r.e
representative of the performance of OCPSF wastewater treatment systems.
Nonrepresentative data were those data from (1) effluent sampling sites where
the treatment plant effluent was diluted (>25 percent) with nonprocess
                                     -5-

-------
o
M



I



Cd




1




M
Q
06


1
 cn












1

cn













^»
^3
«
I
«4
>«
5 5
u S
• «
« « «
•
^ ^
»« e
•2
S °
X
w •
*« u
•o —
i!
r. a u
N U o
1
•
• ^ •
— e u
a • —
• . S
U 0 «
"* f " o
1
• X
1M
8 .
« Si
* £-
•
«
«
• !
u :
5 i
M •*
2 °*
e
e
•
M

BPT TECHNOLOGY EDITS


vi
n
1
«
a
a
S
m
r"
Q
^
in
M
H
n
s
M
W)
*•
o
£
 5

«•*
8 *
—
m
9
•» o«
•49
M ^
S *
rfS
N
^
M
* (S
M
«
.ft
F4
<**
r»4
. *•
a>
•>
o
•»
r«
O»

•
I
«
w
•
X
M *5
e «N
M
2 «
«
*•
f^
M
M S
«4
«
o r4
-O
— "*
O
' * */"\
M
« S
M
>/•»
d
*> M
M
*O
•*
*»
„ S
*n
IN
f*
O
*
o
*

•
^
• e
I
2
•
•4
"3
a.
0
*J
^
*
Blologl*
^
*» n
*v
« «n
M
— *
MI
••
<*»
M
r*
f4
?*
• N
*>
9* S
r. S
^
p^

O
—
- s
, s
<4f
,. "
•ft
« "
>• ""
o
M *
9>

•M
a
U
W
J
•
fl
^

N
tn
e 

w^
«
At
4
I
M
0
M«
?
S
:§' 1
a w
2 «
X
— V)
* —
«
•• «M
s 1
• 2
a. •
e —
2 5
u
al
(•i
•> w
: 5
o S
—
••
M
M
M
M
• £


~ g
N
«
N
t^
M
«
"* «^
M
«
« *
* S
^
r^
f*k
O
O
»
"
•
a
a.
«
e
•*
ji
•
••
£
a
"5
^
•4
•
|
a
a
.«
* <^
i S
. 2
^

>«
•~
„
••
V. S


w
« m
9>
—
tn
—
i^ e*«
«
•£
^
<
("4
*
*\
P4
tfl
X
O
•»
M
9>
**
«l
e
M
*4
•
•fl
«•
a
 IN
(S
0 *1
0 S

<*
f«
p*.
«M
»
m» fa*
**
M «
f^
t/) 
««
O
•»
ft
f


• ~
•
- ?
n a
a. •
e «M
"3 3
M
«
at
rt
• 1-1
_ e
• r<
. 2

• «
a
•> 

i/ » w)o Pollahing Pond* (BPT Option II)
•
a*
a
a
Z
«o
•» 
•
« S

l<1
—
»
•• 9>
»
«•• 
- *
o
— »rt
c*
o
« •*
^

•^
O
O
^
•
>
V
»













«rf
1
w
«
a.
9
«
£
w
e
•
^
a
c
J
I-
«
^
e
w
V)
"S
rcct-dl*charge, f ull-(e«pon*e plant* with pr<
pldnl-couiua with BOD and TSS data.
^ u
u
^Include* 2S
corner* arc
                                          -6-

-------
wastewater just prior to sampling, (2) treatment systems where  a.  significant
portion of the treated wastewater (>25 percent) was nonprocess  wastewater,  (3)
treatment systems where side streams of wastewater entered midway through  the
treatment system and no data were available for these wastestreams,  and  (4)
treatment systems where the influent sampling site did not include all
wastewaters entering the head of the treatment systems (example:   data for  a
single process wastestream rather than all of the influent wastestreams).

     Examination of the data available for each plant and the treatment  system
diagrams provided the basis for exclusion of some of the plants from further
analysis.  The criteria used were:

     •  Data do not reflect or account for OCPSF process wastewater  treatment
        system performance as listed in items 1 through 4 above
     •  Insufficient data due to infrequent sampling (less than once a week
        while operating) or omission of one or more parameters  from  testing
        (BOD, TSS, or flow)         .            '
     •  Treatment plant performance far below expected performance.

Of the plants excluded from the database, most were excluded for  two or  more
reasons.  The exclusion criteria most commonly applied were nonrepresentative
data and insufficient data.

     Plots of concentration versus time and statistical analysis  of  the  data
revealed that most observations clustered around the mean with excursions far
above or below the mean.  In the case of influent data, the excursions were
believed related to production factors such as processing unit  startups  and
shutdowns or accidental spills.  Effluent excursions, particularly those of
Several days duration were believed to be related to upsets of  the treatment
system, production factors, and uncorrected seasonal trends.  Verification of
the cause of the excursions and of the apparent outliers in each  plant
database was deemed necessary in order to supplement the statistical analysis
of the data with engineering judgment and plant performance information.  Each
plant was contacted and asked to respond to a series of questions  regarding
their treatment system, its performance, and the data submitted.   Plant
contacts were asked about possible seasonal effects on the treatment system
                                     -7-

-------
performance and operational adjustments made to compensate, winter and summer
NPDES permit limits, operation problems (slug loads, sludge bulking, plant
upsets, etc.), production changes, and time of operation, plant shutdowns, and
flow metering locations.  Data observations which were two standard deviations
above or below the mean were identified and the plants were asked to provide
the cause of each excursion.

     The plant contacts and analysis of the data revealed some of the
strengths and weaknesses of the database.  Daily data over at least a year of
operation show operational trends and problems, plant upsets, and uncorrected
seasonal trends which would not be apparent for plants sampled less fre-
quently.  The OCPSF industry, regardless of plant subcategory, experiences
common treatment system problems.  Equilization and diversion basins are
commonly used to reduce the effects of slug loads on the treatment system and
to prevent upsets.  Influent data obtained before equilization or diversion
will show high strength'wastes but the effluent may not as a result of
equilization and diversion.  Seasonal effects tend to be more pronounced in
southern climates, perhaps because original treatment systems designs and
current operations do not accommodate necessary weather adjustments.

     While common operational problems are observed across the industry,
specific treatment systems design and operation adjustments were not always
readily available or documented.  Treatment systems incorporating the same
unit process produced significantly different effluent quality.  The reasons
include strength and type of raw wastes, capacity of the treatment system
(under or overloaded), knowledge and skill of operating personnel and design
factors.  While the raw waste type can be categorized by dividing the OCPSF
industry into subcategories, the degree to which the other factors affect
plant performance may not be readily apparent in the data.  For instance, the
daily data may not show seasonal trends because of plant design or operational
adjustments which adequately compensate for cold weather.

     The 46 plants deleted  from the variabilty factor calculations are listed
in Table 3  along with the criteria that provide the basis for each plant edit.
(Some of these edits will be reassessed before promulgation.  For example,
                                      -8-

-------







UJ
I/I
i
o
x
LL.
 S
:lfi
^ a •« w
t
s •£ J
sJaS
•i
•^ -*
c e •
s t .
« -* »»
i s 5 5
'.-! S
O 7 •
1 1 1 g- i

1 =
l{|Il
Isii S
-1^%
2 S ? "C S
JE k *» « V
t L. MM
Mi s ^
*• • * *-
5
• »°
If;

i -1 §
c «• ; —
8 5- "
s Is s

ii

M
MM M




M .MM MM MMMMK



MM M


MM M

M M M c
O
O
0
^~ 1-
-» - MMMMMMM *
C
C
11

—
** MM M _ ,
C


c
3>
^'<*t^i*"*««*^*₯'i*^^'*No^i*y*4S^>*2!!22I2^I^C'-2!SS22S8^*»S9S5 'o
*E^*i*3*^**s"™'*^^*s'^kaSSSS£SSStI"*«?!S'*^S*1^*^'*''^ ^ w
-9-

-------
only activated sludge and aerated lagoons were retained for variability  factor
calculations since they are the most representative biological  treatment
systems in the industry.)

     After these edits, data from 23 biological treatment systems were
retained to calculate variability factors using the statistical methodology
developed in Appendix A.  The statistical methods developed in  Appendix  A
assume a lognormal distribution, and hypothesis tests investigating  this
assumption are discussed in Appendix B.  Individual plant variability factors
grouped by subcategory or category are listed in Tables 4 and 5 for  BOD  and
TSS, respectively.  As shown in the tables, the average BOD  maximum 30-day
average and daily maximum variability factors are 1.41 and 3.91, respectively.
The average TSS maximum 30-day average and daily maximum variability.factors
are 1.45 and 4.74, respectively.

4.  BPT EFFLUENT LIMITATIONS
     The BPT effluent limitations for Options I and II are presented in  Table
6 and 7, respectively.  The industry average BOD and TSS variability factors
derived above for biological systems only are utilized for BPT  Options I and
II.

     An assessment of the long-term BOD and TSS averages in Table 6  and  7
indicates that subcategory effluent quality does not necessarily improve when
plants with biological treatment and polishing ponds are included in the
subcategory averages.  As noted above, these plants may have merely  added
polishing ponds to an inadequately designed or operated biological treatment
system rather than, enlarge or otherwise improve their existing  biological
treatment systems.  The performance edits were utilized to segregate the
better designed and operated plants from the poorer performers  based on  BOD
performance only.  The Agency has not yet conducted a performance edit based
on TSS control but intends to assess TSS performance for all plants  prior  to
promulgation.

     For example, in  the case of the commodity organic chemicals subcategory,
the long-term TSS values are 99 mg/1 in both Tables 6 and 7.  The 11 commodity
                                      -10-

-------

/— *
o
CO

—
£
in
e
o
O 4J
m

o i-
z o>
in
.Q
O

U-l
U-l
W
e, ^H
•<-* be
•a E
0) >«/
m c
Q 0
§ °
U-l *-*
U-l i_4
w ^-.
bO
c s
cfl -^
0)
e
in o
0 CJ
O
03
94 CO
m o
Q S
O Ol
S3 f£
P M
O O
bO bO
01 . O

o" o a


~*

00

CO


CO
o
CM









vO






00








in
ON


00

(U
CD
O
E

N in
4-1 CJ
T- -H
•a c
o «
S bo
e i-
o o



ao
-a-
-M
IW4
CJ

co ^f in r**
CM ••tf \O CN

O> O O 00
00 ON in -^
CM CO ^ *^


CO ^ >«O CO
\o in m -a1
w* ^* ~* ^*«









-< CM r-N. \O
CO — I-. -,





CM \o oo ON
CO ~- ON *-•*







1 1 sO 1
ON


X
O
C
•H
Cfl
00
M
0

^
(-4
3
03

-* -* O
^3" ^^ ^O f*^
in •—> oo ^o
— « — -m CM
CJ CJ CJ CJ

CM — i
CM vO

\Q C
p^ co
_


00 ON
>3- m
CO









CM CO
— ' —•





CO — i
-« CM







P^ 00
ON ON



>N in
u u
— 1 — H
•-I C
(0 (0
•H 6C
U U
01 O
a
en

P<"
^o >n
0 0
CO CM
CJ CJ

00 CO CM
-3- sr P^

P*1* OO -*3
ON ro  ^N &\






T3
01
X
•^
y



f^ ^p
<• ON CO
CM p>. in
ON CM CM
0 CJ 0


•*


0\
CO

03
Cb
S*

1

ir\
^


fl!
01
^






































-11-

-------
J
0-

z
h*
<
   ul
CO

M  <
H  >
CO  O
>-  S
co  u
    as
c
—  Cb
CO  M

as  as
o  o
    6
OS
o
H
O O
< m
u.
M  Q
J  O
h-  93
ce
<  E-
M  Z
Of!  U
•<  3
>  J
    CL.
 I

in

o
CO
Cb
>

-«
*~*
Cb
>
CO
c
o
^4 ^"4
O 4-1
CO
• >
o u
Z 0)
CO
^
•fcj
o
•
<4-l
IU *^
W -(

C W
re e
•H -^/
T3
01 •
S c
o
CO U
CO
H
•
IU '-V
Hi -rf
w ^
tt
Ce
C
CO v— '

o
v* e
CO 0)
H as
^ >
>j i-
O O
QC M
01 01
4-1 4J
to eg
3"
a u
co o

•
o
Z

4-1
c
re
_^
cu
CO

(8
OS



sO
ON
CO
CM
CJ

ON — i O
co co sr

ON in o
P-» CO 00
CM CO >y




CO sO — •
vo so m
CO CO —







sO r<« vo
CM CO






OfifH fff.
OW C^l
en in








1 1 CN
CO



CO
U
U 01
41 .O
£ fl
4-> (b
o



^o o
r>. m ~*
O r» o

U U U

O
co

r-
CJV
-*




i/l
m
»-4







in
CM







CO








1



CO
4-1
01
CO
o
6
t-i
0)
H



r»
-3-
CM
0

CM in vo
\o — m

•
o. ^
o c
e o
U
0)
—
H

r» -i
o> in
in <• oo
CM CM in
U U CJ

o\ cy\ o m -tf-
CM — • CM rO O
— i — — . — CM
in CM o ro oc
p^ in co CJN ^
•31 CM CM CO 00




cjs oo m \o <•
c^ in in \o m
_ — i fO —







— ' O — > vO ON
CO CM P~ — i







^O CO *^ GO ^D
-3- CM P^ —• CM








00 1 1 ON 1
OO ON


CO
U
-r4
4-1
CO CO
re u
1-1 -^ i-i
a. c e
o re re
e sc
)-> M
01 O
£
H

P*. — ON 00
vO m r^ <•
^3" ^4O ^ P1^ 00
ON —• CM CM — '
U CJ O U U

vO
-*
•

o
00
«3-




\B
vO
CO







vO







^^









CM
ON



CO
>% o
4J ft
•H e
•o re
O M
s u
E 0
o
U

oo
-3-

*<^
0

— — 0 O
CM CO CM CO
— • — i CM —
I** oo co P-.
\O C3N -31 00
CM - -- vO
\o m in -31
CO _• CM — •







NjO O CJ> CJN
m CM -*







O *^ ON ^3"
V4O CM CO —
***







1 1 1 p^
ON


ca
o
•H
C
re
(90
u
o
_*:
^H
3
oa

vr ^r o
^ o •-o o
in — < oo o
— . — m CM
CJ CJ CJ CJ

m -it
CO OO

vO CO
vO «3"
in p^




00 sO
-31 sO
CO







CO OO
— ' CM







oo ^^
— 00








CN 
f f\
V J
CO
H
41
BC
re
P
4)
>
<


































                                                                       -12-

-------
                       TABLE 6

          OPTION I BPT LIMITATIONS BASED ON
BIOLOGICAL TREATMENT WITHOUT POST-BIOLOGICAL CONTROLS
               BOD
TSS (mg/1)
Subcategory
Rayon
Other Fibers
Thermosets
Thermoplastics Only
Thermoplastics &
Organics
Commodity Organics
Bulk Organics
Specialty Organics
Long-Term
Avg
19
11
14
18

28
28
25
35
30-Day
Avg
27
16
20
25

39
39
35
49
Daily
Max
74
43
55
70

109
109
98
137
Long-Term
Avg
40
25
46
34

52
99
40
62
30-Day
Avg
58
37
67
50

76
145
58
91
Daily
Max
190
119
218
161

246
469
190
294
                •   '    TABLE 7

          OPTION II BPT LIMITATIONS BASED-ON
BIOLOGICAL TREATMENT WITH AND WITHOUT POLISHING PONDS
               BOD
TSS (mg/1)
Subcategory
Rayon
Other Fibers
Thermosets
Thermoplastics Only
Thermoplastics &
Organics
Commodity Organics
Bulk Organics
Specialty Organics
Long-Term
Avg
19
10
24
18

25
28
27
35
30-Day
Avg
27
14
34
25

35
39
38
49
Daily
Max
74
39
94
70

98
109
106
137
Long-Term
Avg
40
25
46
29

40
99
46
62
30-Day
Avg
58
37
67
42
_
58
145
67
91
Daily
Max
190
119
218
137

190
469
218
294
                         -13-

-------
organic chemical plants that utilize biological treatment (9 without polishing
ponds and 2 with polishing) and that reported effluent data are located in
North Carolina, Louisiana, and Texas.  Application of the performance edit
deletes the North Carolina plant and one Texas plant.  Therefore, 9 Louisiana
and Texas facilities (7 without polishing and 2 with polishing) provide the
basis for the subcategory averages.  Many of these high TSS plant averages are
believed to be due to periods of high ambient temperatures that may cause
algae blooms in holding or polishing ponds.  Many industry comments discuss
this TSS control problem.

     Apparently, a well-operated biological treatment system (based on BOD)
even with polishing ponds does not necessarily ensure adequate solids control.
In those cases where biological treatment provides inadequate TSS control,
additional treatment such as filtration systems should provide the basis for
effluent TSS limitations.  Filtration has been a well-established technology
for many years in both the OCPSF industry and many other industries.

     Approximately 11 percent of the plants in the direct discharge database
utilize filtration in combination with either biological treatment or bio-
logical treatment and polishing ponds.  If this technology provides the basis
for final TSS standards, those biological systems that are not followed by
adequate physical/chemical solids control systems would be deleting from the
database, for TSS purposes.  Based upon the present database on the perfor-
mance of such biological/tertiary solids control systems, this approach would
result in the TSS long-term averages shown in Table 8.  Since the BOD perfor-
mance edit (95 percent/50 mg/1) retains only 16 facilities with tertiary
solids control, TSS data for some subcategories would be pooled.

     The TSS filtration data was pooled for the plastics subcategories —
rayon, other fibers, theraosets, and thermoplastics-only.  The TSS filtration
data was separately pooled for the three organic chemical subcategories.  The
data for the thermoplastics and organics subcategory was not pooled because it
had TSS  filtration data from five plants in that subcategory.  The prefiltra-
tion (i.e., Option II) TSS levels for plants within each of these broad
groupings are believed to  be within  a sufficiently similar range to support
pooling  the filtration effluent data.
                                      -14-

-------
                      TABLE 8

LONG-TERM TSS VALUES (MG/L) FOR BIOLOGICAL SYSTEMS
 (WITH OR WITHOUT POLISHING PONDS) WITH FILTRATION
      (RETAIN PLANT IF EFFLUENT BOD <50 MG/L
             OR IF BOD Z REMOVAL >95%)
Subcategory
or Category

1.  Rayon

2.  Other Fibers

3,  Thermosets

4.  Thermoplastics Only

5.  Thermoplastics and
    Organics

6.  Commodity Organics

7.  Bulk Organics

8*  Speciality Organics


Pooled Groups 1, 2, 3, 4

Pooled Groups 6, 7, 8
No. of Plants
with Data
2
1
2
5
3
2
1
5
6
Median TSS
(mg/1)
27.
50
22.
37
46
29.
9
27
40
5

5


5



                          -15-

-------
      The BPT Option II TSS maximum 30-day average and daily maximum standards
listed in Table 9 were calculated using the TSS variability factors
established for BPT Options I and II.
                                      -16-

-------
                         TABLE 9
     OPTION III TSS BPT LIMITATIONS (MG/L) BASED ON
          BIOLOGICAL TREATMENT WITH FILTRATION
 AND BIOLOGICAL TREATMENT WITH POLISHING AND FILTRATION
                         Long-Term      3-Day      Daily
Subcategory                 Avg          Avg        Max

Rayon                        27           39        128

Other Fibers                 27           39        128

Thermosets                   27           39        128

Thermoplastics Only          27           39        128

Thermoplastics & Organics    37           54        175

Commodity Organics           40           58        190

Bulk Organics                40           58        190

Specialty Organics       -40      '  •   58        190
                              -17-

-------
        APPENDIX A




BPT STATISTICAL METHODOLOGY

-------
        VARIABILITY  FACTOR DEVELOPMENT FOR BOD AND TSS CONCENTRATIONS

1.  DAILY VARIABILITY FACTORS

     Assuming that the distribution of concentration values X is lognorraal,
then Y * log(X) is normally distributed with mean u and variance a  (Aitchison
and Brown (1957)).  Thus the 99th percentile on the natural log (base e) scale is

                           u + 2.3260,

and the 99th percentile on the concentration scale is

                     P99 - exp(Y99) - exp(y + 2.326o).                      (1)

The expected value, E(X), and variance, V(X), on the concentration scale are:

                     E(X) - exp(y + 0.5o2)                                  (2)

and                  V(X) - exp(2u + 
-------
2.  30-DAY MEAN VARIABILITY FACTORS

     Variability factors for 30-day average concentrations, VF(30), are based
on the distribution of an average of values drawn from the distribution of
daily values and take day-to-day correlation into account.  Positive auto-
correlation between concentrations measured on consecutive days means  that
such concentrations tend to be similar.  An average of positively correlated
concentration measurements is more variable than an average of independent
concentrations.  The following formulas incorporate the autocorrelation
between concentration values measured on adjacent days.

     Using the first-order autoregressive model commonly found to be appro-
priate in water pollution modeling, the mean and variance of an average of n
daily values, where this average is denoted by XQ, are approximated by:
                           - E(X) - exp(y + 0.5
-------
                     P95 - E(X30) + 1.645n/V(X30)                           (10)

and                  VF(30)
                                  1.645[(exp(o2) - I)f30(p)/30]             (11)
where E^Q) and V(X3Q) are calculated by setting n - 30 in equations (7) and
(8), using 0 and o2 as defined in (5) and (6), and defining p as the Pearson
product-moment correlation coefficient between the logarithm of adjacent
days' measurements (i.e., the estimated .lag-1 autocorrelation).
                                 A-3

-------

-------
            APPENDIX B




DISTRIBUTIONAL HYPOTHESIS TESTING

-------

-------
                          GOODNESS-OF-FIT PROCEDURES

     The Studentized range test was used to test the assumption that concen-
tration values follow a lognormal distribution (i.e., the natural logarithm
of the concentration values follows a normal distribution).  This test was
used for all plant-pollutant combinations for which variability factors were
developed.  The pollutants included both priority pollutants and conventional
pollutants (BOD and TSS).  To conduct this test, let x^, X2, ..., TK^ be a set
of n nonzero concentration values for a particular plant-pollutant combina-
tion, and let y^ (i • 1, ..., n) be the natural logarithm of these concentrations
(i.e., y^ - log(xi), i - 1, ..., n).  The Studentized range test is based on
the test statistic U - R/S, where

     R • 7(n) ~ y(l)»   where y(n) is the natural logarithm of the largest
                        concentration value, and y(\) is the natural
                        logarithm of the smallest concentration value,
and  S
            I
           n-1 i-1
y)
                              1/2
                                                     71
where y
An upper tail test was used to guard against alternative distributions with
heavier tails than the lognormal distribution, and a significance level of
a • 0.01 was employed for each test.

     Critical values for the hypothesis test involving the U statistic are
given in David, et al. (1954), and selected values are shown below (in
particular, upper percentage points for a « 0.01).
                                        E-l

-------
17
18
19
20
30
40
50
60
80
100
150
200
500
1000
4.59
4.66
4.73
4.79
5.25
5.54
5.77
5.93
6.18-
6.36
6.64
6.85
7.42
7.80
           N          U0.99
            3         2.000
            4         2.445
            5         2.803
            6         3.095
            7         3.338
            8         3.543
            9         3.720
           10         3.875
           11         4.012
           12         4.134
           13         4.244
           14       •  4.34
           15         4.43
           16         4.51
     When the hypothesis of a lognormal distribution is tested (at a signifi-
cance level of a - O.OD for the various plant-pollutant distributions of
detected priority pollutant concentration values used for variability factor
analysis, only one hypothesis test (out of 68 plant-pollutant combinations
investigated) shows a significant result (Copper (120), Plant P225; n - 5;
U - 2.813; p value < 0.005; used for PSES standards based on physical-chemical
controls).  The remaining 67 distributions corresponding to the various plant-
pollutant combinations used in variability factor analyses are nonsignificant
at the a - 0.01 significance level.  Results of hypothesis tests of the
lognormality of the distributions of conventional pollutant (BOD and TSS)
concentrations (for the plants used for variability factor analyses) are
given in the subsequent tables.

                                  Reference
David, H.A., H.O. Hartley, and E.S. Pearson.  1954.  The Distribution of  the
Ratio, in a Single Normal Sample, of Range to Standard Deviation.  Biometrika
41:482-93.
                                    B-2

-------
              GOODNESS-OF-FIT TESTS  FOR BOD DAILY DATA -
              NULL HYPOTHESIS OF LOGNORMAL DISTRIBUTION
Plant
C58
C94
C107
C247
C306
C586
C924
CIO 10
C1104
C1148
C1544
C1667
C1756
C1848
C2057
C2396
C2451
C2536
C2597
C2600
C2651
C2779
C2790
Test
Statistic*
3.85
4.94
6.49
4.79
4.68
5.85
4.36
6.01
6.36
7.75 • .
7.29
5.75
5.93
5.36
6.48
5.23
4.63
7.34
5.87
6.26
6.02
5.75
4.62
ji
124
96
157
203
48
156
157
162
154
366
163
157
357
153
359
160
84
347
262
143
144
363
210
Significance*
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
. <0.005 '
<0.005
'N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
<0.005
N.S.
N.S.
N.S.
N.S.
N.S.
 *Test Statistic U » R/S (see discussion of  Studentized  range  test)

**N.S. indicates nonsignificant at a - 0.01  level  of  significance;
  when results are significant at the a - 0.01 level,  an approximate
  p-value is given.
                                  E-3

-------
             GOODNESS-OF-FIT TESTS FOR TSS DAILY DATA -
             NULL HYPOTHESIS OF LOGNORMAL DISTRIBUTION
Plant
C58
C94
C107
C247
C306
C586
C924
CIO 10
C1104
C1148
C1544
C1667
C1756
C1848
C2057
C2396
C2451
C2536
C2597
C2600
C2651
C2779
C2790
Test
Statistic*
6.08
4.87
6.35
4.77
4.99
5.00
5.69
6.11
6.71 .
4'. 2 3
6.42
5.84
5.86
4.35
6.77
6.02
5.34
8.39
6.00
5.56
5.91
6.38
7.33
n
366
99
363
155
48
251
347
151
*
159
' 366
363
158
366
154
366
158
130
365
261
146
155
366
362
Significance**
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
<0.01 .
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
N.S.
<0.005
N.S.
N.S.
N.S.
N.S.
<0.01
 *Test Statistic U » R/S (see discussion of Studentized range test)


**N.S. indicates nonsignificant at a - 0.01 level of significance;
  when results are significant at the a = 0.01 level,  an approximate
  p-value is given.
                              3-4

-------
IV.  TECHNOLOGY BASIS AND DERIVATION OF BAT EFFLUENT LIMITATIONS

-------

-------
IV.  TECHNOLOGY BASIS AND DERIVATION OF BAT EFFLUENT LIMITATIONS
                               TABLE OF CONTENTS
                                                                     Page
1.  INTRODUCTION	     1
2.  CONCENTRATION VERSUS MASS-BASED LIMITATIONS	     2
3.  TECHNOLOGY OPTIONS	     5
4.  CALCULATION OF CONCENTRATION-BASED BAT END-OF-PIPE EFFLUENT
    LIMITATIONS	     8
5.  BAT DATA BASE EDITING	     9
6.  CALCULATION OF THE MEDIAN OF LONG-TERM MEANS	   22
7.  CALCULATION OF DAILY MAXIMUM AND FOUR DAY VARIABILITY FACTORS...   23
8.  CALCULATION OF BAT EFFLUENT LIMITATIONS	   29
9.  DEVELOPMENT OF IN-PLANT PRE-BIOLOGICAL BAT LIMITATIONS	•	' 30

                                  APPENDICES
APPENDIX A - BAT STATISTICAL METHODOLOGY
APPENDIX B - DOCUMENTATION FOR TOXIC POLLUTANT AIR EMISSION RATE ESTIMATES
             FROM WASTEWATER'TREATMENT SYSTEMS

-------
IV.  TECHNOLOGY BASIS AND DERIVATION OF BAT EFFFLUENT LIMITATIONS


                                LIST OF TABLES


Table                                                                Page

 1.  CATEGORY ASSIGNMENTS                                              10

 2.  PLANT-POLLUTANT DATA COMBINATIONS REMOVED BASED ON TECHNICAL
     EDITS                                                             20

 3.  DATA DELETIONS BASED ON ONLY ONE PLANT-POLLUTANT COMBINATION      24

 4.  PRIORITY POLLUTANT GROUPS                            •             25

 5.  OPTION I BAT EFFLUENT LIMITATIONS                                 31

 6.  OPTION II BAT EFFLUENT LIMITATIONS                                34

 7.  OPTION III BAT EFFLUENT LIMITATIONS                               38

 8.  VOLATILE AND SEMI-VOLATILE POLLUTANTS AND AIR STRIPPING
     ESTIMATES THROUGH OPEN BIOLOGICAL TREATMENT SYSTEMS               42

 9.  HENRY'S CONSTANT STRIPPABILITY GROUPS WITH AVERAGE STEAM
     STRIPPING EFFLUENT VALUES                                         44

10.  BAT IN-PLANT LIMITATIONS FOR OPTIONS II AND III                   45

-------
       IV.  TECHNOLOGY BASIS AND DERIVATION OF BAT EFFLUENT LIMITATIONS

1.  INTRODUCTION
     Due to the diversity of priority pollutants in the OCPSF industry, a
variety of treatment technologies are employed by OCPSF plants to control
priority pollutants as well as nonconventional pollutant discharges.  Conse-
quently, the selection of a particular set of BAT treatment technologies is
plant-specific since the OCPSF industry is not amenable to any single BAT
technology.

     The range of technologies used to control priority pollutant discharges
encompasses virtually the entire range of industrial wastewater treatment
technology.  Generally, this technology consists of a combination of in-plant
control or treatment of specific vastest-reams (sometimes from several dif-
ferent product/processes) by any of a variety of physical/chemical methods,
biological treatment of.combined wastestreams, and post-biological treatment.

     In-plant controls frequently used by OCPSF plants for treatment of
individual wastestreams include steam stripping (or distillation), carbon
adsorption, chemical precipitation, solvent extraction and chemical oxidation.
Biological treatment generally consists of some form of activated sludge
(i.e., extended aeration, complete mix, pure oxygen) individually or in
combination with other types of biological treatment, such as aerated lagoons,
trickling filters, and aerobic and anerobic lagoons.  Post-biological treat-
ment for priority pollutants (and nonconventionals) is generally limited to
granular activated carbon and multimedia filtration.

     It should be noted that although some of the controls or technologies
preceding the biological segment of the treatment system are installed for
product recovery or to reduce priority pollutants, others are expressly
designed into the treatment system to assure compliance with BPT effluent
limitations by protecting the biological segment of the system from shock
loadings and other forms of interference.  Sampling results show that some
plants remove certain toxic pollutants very effectively from the wastewater
through in-plant control technologies.  In these cases, the end-of-pipe
                                     -1-

-------
 systems  are  designed  primarily  for  BODS  and TSS removal.   However, other
 complete treatment  systems  have integrated both biological and post-biological
 components with  in-plant  components to control priority pollutants by uti-
 lizing the in-plant technologies as "roughing" controls to reduce toxic
 pollutant loadings  to levels  which  can be handled by biological and post-
 biological technologies.   It  is thus  inappropriate to specify any particular
 technology as  a  BAT technology  in the OCPSF industry.  Rather, each plant
 required to  control priority  pollutant discharges will employ a combination of
 in-plant controls and end-of-pipe treatment technologies  that result in the
 desired  effluent quality  with respect to a wide variety of pollutant
 parameters of  interest.

      Based upon  these considerations, a  particular set.of treatment technolo-
 gies  has not been specified as  the  basis for BAT.  Rather, priority pollutant
 control  will be  based on  removals achieved at OCPSF plants using different
 treatment configuration^.  Unlike the BAT editing rules used in the proposed
.rulemaking,  a  technology-based  editing rule has been used to retain-plant data
 in calculating BAT  limitations  rather than a performance  editing rule utiliz-
 ing BPT  effluent parameters.  These rules are discussed in detail in the BAT
 effluent limitations  portion  of this  report.

 2.  CONCENTRATION VERSUS  MASS-BASED LIMITATIONS
      Two general approaches were considered for developing BAT effluent
 limitations.  The first approach was  concentration-based  limitations (with
 appropriate  requirements  to prevent the  substitution of dilution for treat-
 ment) based  on end-of-pipe data (supported by performance data for selected
 in-plant control technologies)  that reflect total treatment system perform-
 ance. The second approach would set mass-based limitations based primarily on
 an evaluation  of the  treatability of  individual product/process streams by
 in-plant process controls, physical/chemical treatment and biological treat-
 ment.

      Serious consideration was  given to  the mass-based product process
 approach throughout the development of both the proposed regulations and those
 contained in the Notice of Availability.  This approach would have relied
                                      -2-

-------
primarily on the data gathered in the verification program for  the  176
product/processes and their treatability and also on the physical/chemical
treatability data base.  Based on these data, mass-based limitations could  be
determined based on the use of in-plant controls.

     Under this approach, each product/process would have been  considered a
separate subcategory, and the regulation would have contained separate
mass-based limitations for each such subcategory.  Monitoring would have been
separately required for each product/process effluent.  However, credit could
have been provided for removals by an end-of-pipe (usually biological)
treatment system if sampling before and after that system demonstrated a
percent reduction through the biological segment of the system.

     This approach, if supported by sufficient technical information, provides
some potential advantages over an end-of-pipe-based regulation:

     a.  By setting limits on individual product/processes, this approach
would assure treatment prior to the commingling of different process waste-
waters.  Thus, the dilution of one process wastewater containing only pollut-
ants A-E by another process wastewater containing only pollutants F-J could
not be used as a partial substitute for treatment.

     b.  This approach could be expected, in practice, to result in an
emphasis on process controls and in-plant physical/chemical treatment, thereby
promoting the recycling and reuse of wastewater and by-prodcuts.  Sueh an
emphasis would result in a reduction of the overall pollutant release through
various environmental media that might otherwise occur through a heavier
reliance on end-of-pipe biological treatment.  For example, biological
treatment, in many instances, causes the transfer of volatile and semivolatile
organic pollutants from the wastewater to the air, and the adsoprtion of some
other organic pollutants, as well as metals, to the biological sludge, which
is then disposed of through methods which may affect other media.  While some
in-plant physical/chemical controls may similarly transfer pollutants to other
media (e.g., precipitation of metals often results in the transfer of metals
                                     -3-

-------
from wastewater to other media), other in-plant controls and treatments  return
at least some pollutants to the process, thereby minimizing total environ-
mental releases.

     Despite these advantages, this approach has been determined to be both
technically and administratively infeasible.  The difficulties with this
approach are outlined below:

     a.  Data were collected characterizing 176 specific product/process
effluents.  This covers all of the high-volume products in the industry, and
represents approximately 40 percent of the industry wastewater flow and
approximaely 65 percent of its production.  Despite this extensive coverage,
thousands of minor individual product/processes are left unaddressed.  In
implementing BAT regulations to issue a permit under this option, a permit
writer would typically be faced with the arduous task of characterizing and
developing effluent limitations for those product/processes at each plant that
are not explicitly addressed by the regulation.  It is thus likely that  this
approach would substantially delay the issuance of permits to, and the
installation and operation of BAT controls by, OCPSF plants.

     b.  Calculating mass limits requires that for each product/process, an
F/P (flow divided by production volume) ratio must be calculated that is
representative of good industry practice.  (Multiplying F/P by concentration
yields a mass pollutant loading per unit of production.)  For 146 of the 176
product/processes, F/P data with corresponding final effluent data exists at
only one plant.  Moreover, where data exists from two or three plants, wide
variation in F/P ratios often occur.  (In one case the variation is a factor
of 74).  Causes for these disparities could be a variety of differing process
controls.  To establish a BAT F/P ratio, design and operating practices would
have to be set for each product/process in the industry.  This is far beyond
the reasonable scope of the BAT project.

      c.  Plants often combine the raw wastewater from several product/
processes prior to in-plant treatment. The piping configurations often make it
impossible to sample the isolated wastewater streams before they are combined.
                                     -4-

-------
Undetermined mixes of several product/process effluents would  confound
attempts to attribute F/P ratios, raw waste loads or treatabilities  to
particular product/process effluents.  This problem would similarly  confront
plants attempting to monitor individual product/process effluents  in order  to
comply with permits implementing this option.

     d.  Monitoring for compliance with individual product/process limitations
would be enormously expensive.  Sampling and analysis for organic  pollutants,
unlike analysis for conventional pollutants and metals, is very expensive.
Monitoring on a routine basis for organic pollutants at many different points
within the plant would be exceptionally expensive.  For example, if  a large
plant monitored 15 sample points for priority pollutants once  a week, the
annual cost of monitoring alone could be as high as $663,000.

     Based on the discussion above, the concentration-based limitations
approach was selected to develop BAT effluent limitations.
                                                                 i
3. " TECHNOLOGY OPTIONS
     Throughout this project, various sources of toxic pollutant data have
been used in the calculation of BAT effluent limitations for both  the proposed
regulations and this Notice of Availability and the collection of  each of
these data sets was aimed at gathering certain performance information for
certain pollutants.  The overall scope of each data gathering  episode has
greatly influenced the selection of BAT technology options due to  the type of
performance data each episode sought to collect.  For example, plants sampled
during the verification and CMA/EPA 5-plant sampling study focused on a
selected set of pollutants at each plant and only sampling of  the  influent and
effluent of the end-of-pipe treatment system (mostly biological) was per-
formed.  The in-plant controls at these plants were usually documented but
seldom sampled.  In addition, plants were selected for the current 12 plant
sampling study based on their ability fo fill gaps in the existing toxic
pollutant data base and to provide performance data for such treatment
technologies as steam stripping, activated carbon, chemical precipitstl-cm and
chemical oxidation as well as additional performance data for  activated sludge
systems.
                                     -5-

-------
     This combined toxic pollutant data base yielded performance data on the
following types of treament systems:

     a.  Biological treatment systems which consist primarily of activated
sludge and aerated lagoons.

     b.  In-plant controls such as steam stripping and chemical precipitation
individually and in combination with biological treatment systems.

     c.  Toxic pollutant polishing treatment technologies such as carbon
adsorption and filtration individually and in combination with biological
treatment systems.

     Based cm the types of performance data collected in the three data
gathering efforts, the following end-of-pipe BAT technology options were
selected:

     Option I—Concentration-based BAT effluent limitations based on the
performance of only the biological treatment component, which is usually equal
to the priority pollutant limitations attained when in compliance with BPT
effluent limitations.

     Option II—Concentration-based BAT effluent limitations based on the
performance of the biological treatment component plus in-plant control
technologies which remove priority pollutants prior to discharge to the
end-of-pipe treatment system.  These in-plant technologies include steam
stripping to remove volatile and semivolatile priority pollutants, activated
carbon for various base/neutral priority pollutants, chemical precipitation
for metals and cyanide and possibly multistage biological treatment for
removal of polynuclear aromatic (PNA) priority pollutants.

     Option III—Concentration-based BAT effluent limitations based on the
performance of biological treatment, in-plant controls and post
activated carbon adsorption  for the remaining toxic pollutants.
                                     -6-

-------
     Option I is a low cost option which reduces some toxic pollutants
utilizing the technology installed for BPT—biological treatment.  However,
some OCPSF facilities can comply with the BPT limitations for BOD5 and TSS
without the installation of biological treatment.  These facilities can comply
with Option I BAT effluent limitations only by installing the in-plant
controls recommended in Option II.  However, this technology in some cases
includes in-plant controls which have been installed to remove toxic pol-
lutants which would interfere with or inhibit the biological treatment
system's removal of BODS and TSS.  The need for such controls for BPT purposes
is likely to vary; thus some BPT plants may not be able to achieve BAT Option
I without additional technology at additional cost.

     Option II controls reduce large amounts of toxic pollutants from waste-
water prior to discharge to surface waters.  Furthermore, the installation of
in-plant controls under Option II would be particularly effective in reducing
the levels of volatile and semi-volatile organic toxic pollutants -in all
environmental media.  A large portion of volatile and semivolatile organic
toxic pollutants are emitted by biological systems into the surrounding air.
Thus, while removing them from the wastewater, the typical biological system
does not remove these pollutants from the environment but rather transfers a
large portion of them to another environmental medium.  The in-plant treatment
of such pollutants by methods such as steam stripping reduces or eliminates
the air emissions that otherwise would occur by the air stripping of the
organic toxic pollutants in the biological system.  Moreover, the installation
of in-plant controls would also reduce the levels of certain priority pollut-
ants which are not air stripped or otherwise removed from OCPSF wastewaters
using only biologi-cal treatment.  For example, the Agency's data base shows
that bis(Z-chloroisopropyl) ether, 2,4,6-trichlorophenol, and pentachloro-
phenol are not adequately removed by biological treatment systems.  However,
bis(Z-chloroisopropyl) ether, a base/neutral compound, may be controlled
through in-plant steam stripping.  Similarly, 2,4,6-trichlorophenol and
pentachlorophenol, acid compounds, may be controlled through in-plant absorp-
tion systems.
                                     -7-

-------
     Option III provides slightly higher removals for a limited number of
organic toxic pollutants such as 2,4-dimethyl phenol, naphthalene, and phenol.

4.  CALCULATION OF CONCENTRATION-BASED BAT END-OF-PIPE EFFLUENT LIMITATIONS
     For each of the technology options, end-of-pipe concentration-based BAT
limitations for the entire industry will be calculated based upon end-of-pipe
data that reflect the best available technology.  Depending on the option
selected, the BAT technology used as the basis for limitations includes
combinations of process controls, in-plant physical/chemical treatment and
end-of-pipe treatment.  The data base includes verification plants, CMA/EPA
5-plant study plants, and recent sampling study plants; the data has been
edited both technically and analytically.

     Prior to calculating concentration-based limitations, consideration was
given to whether the industry should be subcategorized for BAT purposes.  By
evaluating the same subcategorization factors which were considered for BPT,
it was decided to promulgate a single set of BAT limitations which would: be
applicable to all OCPSF facilities.  However, permits would tailor these
requirements somewhat to account for the fact that most OCPSF plants routinely
discharge only a subset of the pollutants covered by the BAT regulation.  The
available data for BAT show that plants in differing BPT subcategories can
achieve similar low toxic pollutant effluent concentrations by installing the
best available treatment components.  Since all plants can achieve compliance
with the same BAT limitations through some combination of demonstrated
technology, the predominant issue relates to the cost of the required,treat-
ment technology, which has been addressed in the cost estimation methodologies
and procedures used to generate BAT costs.

     Having concluded that in general only one set of BAT limitations for all
OCPSF facilities should be developed, BAT effluent limitations were calculated
for each technology option using data collected from different combinations of
BAT treatment systems during the verification, CMA/EPA 5-plant study, and
current  sampling program efforts as follows:
                                     -8-

-------
     Option I—BAT effluent limitations will be calculated using sampling  data
from plants that have been determined to have well-operated biological
treatment for the priority pollutants to be regulated.  These plants may
include in-plant toxic pollutant controls which were installed to ensure the
performance of the biological treatment system.

     Option II—BAT effluent limitations will be calculated using sampling
data from plants included in Option I for certain priority pollutants.  For
pollutants not adequately controlled by BPT technology, limitations will be
based on data from plants that have biological treatment plus in-plant
controls and plants that have physical/chemical control technology applied at
the end-of-pipe for the remaining priority pollutants to be regulated.

     Option III—BAT effluent limitations will be calculated using sampling
data from plants included in Options I and II for some pollutants plus, for
certain other pollutants, plants that have been identified as having biologi-
cal treatment , in-plant controls and post-biological activated carbon adsorp-
tion polishing.

     The following sections discuss the procedures used to calculate the
components necessary for the development of BAT effluent limitations.

5.  BAT DATA BASE EDITING
     Certain editing rules were utilized in preparing the data base prior  to
calculation of individual plant long-term averages (LTA) and industry long-
term medians (LTM).  First, all verification, CMA/EPA 5-plant study and
current 12 plant sampling study facilities were examined to determine if they
fit into the three BAT technology options.  Each plant-pollutant combination
was assigned to a technology category as shown in Table 1, based on their
in-place treatment technologies and the pollutants that were present.  Plant-
pollutant combinations used for BAT Options I, II, and III calculations are
listed in Table 1 as Categories I; I and II; and I, II, and II, respectively.
Depending on plant-specific wastewater treatment configurations,_di££erent
pollutants at a plant could be assigned to different plant-pollutant cate-
gories.  A total of seven verification plants were eliminated because they did
                                     -9-

-------
Ul
h-   -I

<   <

U   U
    M


 •   Ul


-   s
  tu tu
•  z z
  U Ul

  3z
  Ul Ul

£88.
Ul « OC

323!
ui x x :
01 U U I
O M l-l I
  go o
   I  I


5 25
                 oe
                 o
o o
ZZ
UIUI
i z
Q.E
oo
    2



    £



i   5
Ul   Ul

£   2
a   >-

?   r
               -iO^-t-QQ —
    M Z   ui ui u o
    zfi   z z zS_i
    •IX   UJ lu uj SI O
      8£   si si si z 2
      O   Z Z Z ui ui
    aCE-JUJUIUjmZ

    slsssggl
    XSUIOEKQEOp:
    (JUXQOO-IO
    MMOL-1-J-JZJ
    Socotoxxxux
    H->-auuu>-"U

ujr-*-a-iQQo i a
3 O  - - X i  i  i -  i
UIO£
ZZO
uiuiot
IM x o
zi-i
uJOz
                                                        Z
                                                      uiui

                                                      z er
                                                 i i- < o:

                                                   MKX
                                         C ui
                                         o a. o
                                             <
                                                            IS
                                                            u u
    i
    Ul

    £

  Z^gui

  ^5^5
  ** Ul I- -J
    £r z <
    11 < -
  < a oc
u z i  o
z ui  o
                                                                                  55u,
u. u. z Z
^ ^ h- Ul Ul
a x x u z
— — C < u
o o < at ai
si si z x a
Z Z ui t- 3
Ul UJ CJ Z «J
O O < < u.
I   03

Z UJ H4 ^4
C

uri
                                           < z z r 5
                                           Z lu uj O u _
                                           ui oc <*> a: oc z i
                                                                                    =
                                                                                  ui 5
                                                                         iSSu
                                                                          5=   °
                                                                          o u u z
                                                                          ~' ~; Z uj

                                                                             !5£
                                                                                                             ui
                                                                                                         z M a
        XUJ

        O.Z

UJ E >•*   ^UJ

3 O Z UZSl

-i O: •< Zuz

O Z >• ^^ ouj
h- U U SI <<0
~

s
          r^inh»«r«^-«o>Ki«4»«x-»in«N«-«e«-rep^iA
                                                              e w eo —
                                                          —i •- W CM CM   I
                                                                  r«.aDO — ^UI^KI

                                                                 i ^ r^ CQ ex) co ** "^ CM
                                                                                                     cvj ^ 
-------
     o
                                         >-               iu

                                                                                     Q
                                                                                                                      3
                                                                                                                      O

                                                                                                                      o
                                         *               Z                          UJ
M            ^                          U              _                          . .       _	
m            o                          out            >-                          42"               iu z z            -i
M            Z                       — OS Z — — —    UJ                 — —    O       2       Z — ~ —       M IU UJ            Q
                                      -I O UJ -J -J -J    O       w         -l J    -i       ui       ui w -i -J       Z 9 2 ui         Z
                           £iu         < _l _l •« •« <    gc       z         < •<    s    -I z       _ ,  _  ^	
                           Z         >_ x v h- t- >-    O       <         *- >-    u    Q£       >. i- h- ^-    iufflOO<
              _l !U uj      u         O U Z O O O    -I    tux         O O    <    Z O       Z O O O    Z  O 1- I- Z UJ
              ^ Z Z uj    _J         (- x K *— *— H-    X    Z>*>uJ      Hi-    oc    ujqe       K h- H- t-    ujoeOOKZ
                      -                  ---            U C M u Z      --    H-rxp       UJ---.    NOBBtBUJlU
              _J Ul UJ Z    >•         — a UJ — — —    U C uj uj Z      ——    h-CXO
ui            >- KJ, z uj    z            -       c
              C iu z <    xz   uj uj •< a 5    uj  iu h- u. uj qc <    iu 3    iu   U.KU    iu o  3       uiauzzqcuioaz    iuzuc3
              >iB-<5mp:acM.JZOM3»
u    u
              o-JptHO-zj;uji-iuj — aw-jK-giuS    ujootJopiuzc       uia:aoQ-JOH^-QOujcZMC IUM
              i >-Szzzouj3z  i  UOO.ZN  >o>>xzZ3OUNa)9x <  zauaauKio  i   i   >  XKMM i z 3 « uj r o a. zo
              ^x5iuiuJDoL-J-iQ!tL-o>--o:ro>-ui-zt->izoixxuji-iujx*--i-ii-ii   i   >xozo;-uj
      u       ojuiu.z£
-------
   u
1


U)
0   s
 •   IU
-   5
•< < <
555
 §
 IU
 £
. 2S
          3   WC
         -J M   Z M
               x uj:

               u Z i
                 en o z a
                           o
                     I
                                       o o o i
                                            H- U Z IU X
                                                 gs,
                             IU O O
                                     Uli
I UJ M IU « >—
: in N a  S M I
                                                                      ^x'SglSg
                                                                        u -i u. •< a _i
                                                                      Z M X O OC O X
                                                                              IS-'
                                                                              iSi
     -
 >UXXI
— zuu
XIU»II
uzoi
 2£ooIS5ul?-
    - u uuu U I r«o> oo-o " _j ^0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.10.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0. aaa. -12-

-------
      i
3    S
      (J OC
                                              Soo-»-r**-T>r~T'T*-r-r*-»-»l*-»'-t-»'0-o«oooooooommmmr«KiKiK>K>WK»rti«K»ioi'iKi^1r-T-r*^'»**^*^**sr-T^^-
               «MNN«lC>JNMCVIN<>lCgNC4AINNNAJNNNNI\4e>J(>lrJNJN>VI N<\MVI
                                                                                         -13-

-------
     .          *-H.H-iuiu     z
            §OQO   ZOKUIOO^^-SiUQpIL   M                ZOOtluOO^^XiuOOQ.    M              O           OUl uiui
            >-»-»-   iu a »- z at at o o u z 2 z o   «                iu a K z a ac a a u z 2 z o    a:              z           gc z z-i
            «_„   Moui-xxi-t>->zz£cL«    xc           £         o x z»-—vu
x   <     5      luaucniuuuzziuiuoozuiuS          uiauMuiuuzziuuiaazuiuS        tuo    uiuiu-uiuz xu
u   u     MQC   zaM*aMMMM_jd)acaeMZ    >-" at   J   zoM-OHMMM^acKOEMZ   «   J   zoe-JZZOMoa< a.<
     H     ciu   iugea—i—as"-i5   iu   lut-aiuiuaea-' CKCT
     r     o a. o M o  i  • o i   i  i   ixati-ii-ii3>oa,QatyNOi   -01  >   i  ixoti-ci-ii3>-OQ^oN«-z3Moi>- oxz
     iu     oeazz-icsi — -JRj-r^^>->-zz-TJZQ:a.3uzz-iM — -'«j-r-T«>->-zz-J'-iZQ:»UIMI   I  >O>-IXOUJMI-ltUX*-X****UIMI  I   oOMXIUMMIUIXOlUX**- -JUZ
     u     uoMaiu-"-<"-"j^Bj^>ooJZN4aiu — — o-'-"««tvcztJ-ruJ Z^KJ a«yi&^-oiu-*HJ u-«
                                                                                                                                        i in eO
                                                                                                                                        I cvi to
                                                                          -14-

-------
U
                                                                 fAtAtt
                                                                                            NC
                                             -15-

-------
                                                      32
                                                      « IU

<       iu J      ppppxpujj  izP  *   "*  ~    PPppoi       POP  J3 5 p 0 i
-a:a:gco:>-iiJ  o
                                                                — — —  at >• — — o o o o r 2  gc
         . _ X -I Z w «   eM£QZM- o <
                                                                                             >•





   x    h-i-iaxoxouji-i'-ixuijiu >^MXIUXUZX^OIXX^UJIU >XOI-IMXM>-IUUXXIU - — - •  >«««f>f^'~'O«3«3a3'O«3'O coaa
                                                             <>jrilAJJN«IJ<>l«lJ
-------
    u
m
tn
2   2
      o o o a
  "~ *•
  g uj
S53
S£g
u 3   iu

z£2S

in a: a. <
ee x O >•
•« u u u
  Z 5   ^

311   8
< h- a:   M
K iu o   o
o o -t   at
h- K X   O
^ O O Z J
  -i «- a x
  x a o u
  u t- u, i
  M I  O CM
  Q -o a: —
u  i -o


N •• oj u 01
a -i
M g
  S2
  IU


M

S3

SSu
^ < iu
55s*!

r a. z i
                                        x
                                        a.
                                        a
                                                  tu
                                                  2
                                    11
                                    if
                                      o^
                                      H- x
.S
!3,
                                            g
                                            z
                                                        ?
                                                        O
            iu
            5 o j
            z£S
            IU X IU
            §o-£
            SS§
                                                  HH-OCUU
                                                       i o a <
                                                       : i  i H
                                                    x
                                                    iu

                                                  IU -t
                                                  z >•
        •<
        )- IU
        O -i
                                                                 IU X ~ OS
                                                      oxx-J  MZU   «
                                            t--JK(-•

S^
    0.
    o

    £

    8
    M
    o

    I

    u
    -j —11

    BI:
    5£;
                                                                                        S
                                                                                        IU

                                                                                        £
                                                                                        o
                                                                                        K
7i7
     < < <  3      a

    :x^-g  2 iu ~" o  ' 12
   p- X H- •—  O Z Z Z  « w
     £O. _ ..  KIUIUIU^O:
            ^ *J X X  I h-
     -J S    >H z E Q. -J «
   -l >- 5  iuZiuOO>>Z
   >• x >i a. z «^a-o: a: x O -i



   MMXOUJ**^!  I  I(JX
iaaauuajNZo-"'n
    Zffl   «4 •« « -• -
-------
not have an effluent sampling point, they were indirect dischargers  with  only
their discharge points being sampled, no combined raw waste  sampling point  was
available or they were zero dischargers with only their discharge  points  being
sampled.

     Next, analytically suspect data were either removed from  the  data  base
completely or returned to the analytical laboratories for confirmation  or
correction.  This involved the deletion of all organic priority pollutant data
from five verification plants because the analyses were performed  using the
GC-CD/blind spike analytical method without GC-MS confirmation of  the results.
Also, one of the current 12 plant sampling study facilities  had all  organic
priority pollutant data eliminated from the data base because  the  analytical
laboratory did not adhere to the analytical protocols.

     If influent plant-pollutant concentrations were reported  as nondetect
then both the influent and corresponding effluent data pair  were eliminated
from the analysis.

     The current 12-plant sampling priority pollutant analytical data were
edited based on the following  criteria:

     •  End-of-pipe influent and effluent data for both organic and  heavy
        metal priority pollutants were edited and returned to  the  analytical
        laboratories for confirmation or correction if the detection limits
        were greater than 100 ppb and 50 ppb in Che Influent and effluent,
        respectively.
     •  In-plant control technology influent and effluent data were  edited  and
        returned to the analytical laboratories for confirmation or  correction
        if the detection limits were greater than 1,000 ppb  and 100  ppb in  the
        respective influents and effluents for steam stripping; greater than
        20 ppb in both the influents and effluents for carbon  adsorption; and
        greater than 100 ppb and 50 ppb in the respective influents  and
        effluents for chemical precipitation.
     •  Sampling point duplicates with widely divergent results were both
        removed from the data base and returned to the analytical  laboratories
        for confirmation or correction.
     After analytical editing of the data was performed, the remaining
effluent data points with duplicate sampling dates were matched and  averaged
                                      -18-

-------
to provide a single value for the date.  Then, influent and effluent  data  were
matched by sample date and nonmatching influent and effluent data  points were
excluded from the analysis.  Influent-effluent matching pairs were examined
and pairs with negative percent removals were excluded, too.  However,  it
should be noted that there are a number of reasons for the presence of
non-matching influent-effluent pairs and the occurrence of negative percent
removals including analytical laboratory problems, analytical editing of the
data and treatment system retention time lags between sampling points which
may allow the inclusion of some of these data in the analysis prior to
promulgation if the analytical laboratories can confirm or correct these data
and if treatment system retention time can be accommodated.

     After these general edits were performed, a more detailed point-by-point
technical edit was performed.  Table 2 presents the data points which were
removed based on technical considerations and the reason for each edit.  In
general, data points were removed if treatment system upset conditions existed
at a plant for any period of time, if single data points of high concentration
appeared during a long sampling period with no other reappearance or  if
certain pollutants were determined to be present at a certain plant because of
misidentification or analytical laboratory problems based on that plant's
product mix.

     It should be noted that certain plants have been sampled in more than one
of the BAT sampling programs previously mentioned.  For the purposes of
calculating plant LTAs and industry LTMs, each sampling program at a particu-
lar plant was treated separately and had individual LTAs which are included in
the calculation of the LTM for each pollutant (i.e., it is possible that LTAs
have been calculated for both the verification and CMA sampling programs for a
particular pollutant at a certain plant).  This decision was made due to
difference in time periods of each sampling program, the different analytical
procedures employed, the possibility of changes in product mix and processes
utilized during each time period and the fact that different sets of priority
pollutants may have been analyzed for the same plant during different-sampling
program efforts.
                                     -19-

-------
                                    TABLE 2

      PLANT-POLLUTANT DATA COMBINATIONS REMOVED BASED ON TECHNICAL EDITS
PLANT    POLLUTANT(S)
                                         REASON
P246A
   56
P206
P230
P202


P297



P297



P263
P253

P227
    4
    7
   10
   23
   86
   13
   20
   35
   37
   68
   70

   62
   56
(4/01/84)
   59
(3/25/84)
   10

   88
Aniline spill at the plant left residual quantities of
nitrobenzene in the carbon columns which leached out
during the sampling period.  All nitrobenzene data for
the sampling period deleted.

Malfunction of in-plant chemical oxidation units
caused elevated levels of these pollutants in the raw
waste to the end-of-pipe biological system which
passed through to the final effluent.  All data for
these pollutants for the entire sampling period were
deleted.

These pollutants were determined to be present at this
plant because pf misidenpification or analytical
laboratory problems, since the product/processes' at
this plant would not.produce these pollutants.  All
data for these pollutants were deleted.
This pollutant was misidentified and later confirmed
as acetone.  All data for this pollutant were deleted.

This data point was deleted because it was two orders
of magnitude higher than all other effluent data
points.

Only effluent value above the detect limit (20 ppb).
Since it was two orders of magnitude above all other
values, it was deleted.

Treatment efficiency for this pollutant was much  lower
than other pollutants at this plant which should  treat
similarly.  All data for this pollutant were deleted
pending closer exaimination of the field sampling
logs.

Same as preceeding.

Same reason as for above two plants and _pol_iu,taacs.
                                         -20-

-------
                                    TABLE 2

      PLANT-POLLUTANT DATA COMBINATIONS REMOVED BASED ON TECHNICAL EDITS
                                  (CONCLUDED)
PLANT    POLLUTANT(S)                              REASON
P217         21         Only two influent-effluent pairs for this plant show
                        100% removal and 3.7% removal.  Since these results
                        were so divergent, both pairs were deleted from the
                        analysis.

P297      114-128       Since the treatment system consists of only steam
                        stripping and activated carbon, metals removals were
                        considered to be misleading, so all metals data were
                        deleted.

P248      114-128       Same as for preceeding entry.
                                         -21-

-------
6.  CALCULATION OF THE MEDIAN OF LONG-TERM MEANS
     For each pollutant at each plant in each of the sampling efforts men-
tioned above, a long-term weighted average (LTA) effluent concentration was
calculated using only effluent data points whose corresponding end-of-pipe
influent data were greater than or equal to 20 ppb or to 100 ppb depending on
the type of technology used to remove a pollutant at a particular plant.  For
plants using in-plant controls prior to discharge to the end-of-pipe treatment
system, the 20 ppb level was selected for the treated pollutants; for other
pollutants, the 100 ppb level was used.  These edits were designed to retain
in the calculation of the limit for that pollutant only those plants that had
treatable levels of a pollutant in the raw waste.  The nondetected values at
the plant were assigned a nominal detection limit value using detection limits
associated with EPA analytical methods 1624 and 1625.  The long-term weighted
average was computed by a weighting scheme, which assumed that nondetected
values should be assigned a relative weight in accordance with the frequency
with which"nondetected-values for the pollutant generally were found in the
daily-data plants.  Long-term weighted averages are calculated for each
plant-pollutant combination from the previous five-plant long-term study, the
recent twelve-plant sampling study, and the verification sampling study.  The
long-term weighted average, m, for a plant-pollutant combination is as
follows:
                                      n
                     m - pD -i- (1-
where D is the nominal analytical method detection limit, n is  the number of
values that XI is detected, and p is then the proportion of nondetect values
reported from the daily data base.  That is, p equals  the total number of
reported nondetect values from all daily data plants for a particular pol-
lutant divided by the total number of values reported  from all  daily data
plants for a particular pollutant.  For plant-pollutant combinations with all
nondetected values, the long-term average, m, equals the nominal analytical
method detection limit.  For plant-pollutant combinations where all values are
detected, the long-term average is the arithemetic mean of all  values.
                                     -22-

-------
     Then, the median of the plants' long-term weighted averages was
calculated for each pollutant.  Because data were limited for certain  pol-
lutants, pollutant medians were retained for further analysis only if  at  least
one plant-pollutant combination had three or more influent/effluent data
pairs.  Table 3 lists the pollutants which were eliminated based on this
criterion.

7.  CALCULATION OF DAILY MAXIMUM AND FOUR DAY VARIABILITY FACTORS
     After developing long-term medians for each pollutant, EPA proceeded to
develop two variability factors for each pollutant—a daily maximum variabil-
ity factor (VF1) and a four-day variability factor (VF4).  These were  devel-
oped by fitting a statistical distribution to the daily data for each
pollutant at each plant; deriving a 99th percentile and a mean of the  daily
data distributions for each pollutant at each plant; deriving a 95th per-
centile and a mean of the distribution of 4-day averages for each pollutant at
each plant; dividing the 99th- and 95th percentiles by the respective means of
daily and 4-day average distributions to derive plant-specific.variability
factors for each pollutant; and averaging these plant-specific variability
factors across all plants to derive VF1 and VF4 for each pollutant.

     For certain pollutants, the amount of daily data was limited.  For such
pollutants, variability factors were interpolated from the variability factors
for groups of pollutants expected to exhibit comparable treatment variability
based upon comparison of chemical structure and characteristics.  Table 4
presents these groups and the pollutants contained in each group.  'Each
pollutant in each chemical group was then assigned a VF1 and VF4 equal to the
average of the VFls and VF4s of any pollutants in the same group.

     In response to comments on the statistical aspects of the proposed
limitations development, several statistical techniques were investigated for
deriving limitations.  This investigation found that a modification of the
delta-lognormal procedures provides a reasonable approximation of the under-
lying empirical toxic pollutant data.  The delta-lognormal distribution
assumes that data are a mixture of positive lognormally distributed values and
                                     -23-

-------
                           TABLE 3




DATA DELETIONS BASED ON ONLY ONE PLANT-POLLUTANT COMBINATION
PLANT
P276
P257
P253
P259
P257
P259
P253.
P246A
P280
. P234
P234
P208
P255
P225
POLLUTANT
2
13
13
13
15
15
15
15
18
• 46 . • .
. 54
75
118
118
                               -24-

-------
                                    TABLE 4

                           PRIORITY POLLUTANT GROUPS
1.  Halogenated Methanes (Cl's)

     46  Methyl bromide
     45  Methyl chloride
     44  Methylene chloride (dichloromethane)
     47  Bromoform (tribromomethane)
     23  Chloroform (trichloromethane)
     48  Bromodichlororaethane
     51  Dibromochloromethane
     50  Dichlorodifluoromethane
     49  Trichlorofluororaethane
      6  Carbon tetrachloride (tetrachlororaethane)

2.  Chlorinated C2's

     16  Chloroethane (ethyl chloride)
     88  Chloroethylene (vinyl chloride)
     10  1,2-Dichloroethane (ethylene dichloride)
     13  1,1-Dichloroethane
     30  1,2-trans-Dichloroethyiene '         .
     29  1,1-Dichloroethylene (vinylidene chloride)
     14  1,1,2-Trichloroethane
     11  1,1,1-Trichloroethane (methyl chloroform)
     87  Trichloroethylene
     85  Tetrachloroethylene
     15  1,1,2,2-Tetrachloroethane
     12  Hexachloroethane

3.  Chlorinated C3's

     32  1,2-Dichloropropane
     33  1,3-Dichloropropylene

4.  Chlorinated C4

     52  Hexachlorobutadiene

5.  Chlorinated C5

     53  Hexachlorocylopentadiene
NOTES: (1) Numbers refer to a published alphabetical listing of the priority
           pollutants.
REFERENCE: Wise, H.E., and P.O. Fahrenthold (1981).  Occurrence
           Predictability of Priority Pollutants in Waatewaters of the Organic
           Chemicals and Plastics/Synthetic Fibers Industrial Categories,
           USEPA, 1981.
                                      -25-

-------
                                    TABLE 4

                           PRIORITY POLLUTANT GROUPS
                                  (Continued)
6.  Chloroalkyl Ethers

     17  bis(chloromethyl)ether
     18  bis(2-chloroethyl)ether
     42  bis(2-chloroisopropyl)ether
     19  2-chloroethylvinyl ether
     43  bis(2-chloroethoxy) methane

7.  Metals

    114  Antimony
    115  Arsenic
    117  Beryllium
    118  Cadmium
    119  Chromium
    120  Copper
    122  Lead
    123  Mercury
    124  Nickel      .  .
    125  Selenium
    126  Silver
    127  Thallium
    128  Zinc

8.  Pesticides

     89  Aldrin
     90  Dieldrin
     91  Chlordane
     95  alpha-Endosulfan
     98  Endrin
     99  Endrin aldehyde
    100  Heptachlor
    101  Heptachlor epoxide
    102  alpha-BHC
    103  beta-BHC
    104  gamma-BHC (Llndane)
    105  delta-BHC
     92  4,4'-DDT
     93  4,4'-DDE (p,p'-DDx)
     94  4,4'-DDD (p,p'-TDE)
    113  Toxaphene

9.  Nitrosamines

     61  N-Nitrosodimethyl amine
     62  N-Nitrosodiphenyl amine
     63  N-Nitrosodi-n-propyl amine
                                         -26-

-------
                                    TABLE 4

                           PRIORITY POLLUTANT GROUPS
                                  (Continued)
10.  Miscellaneous

      2  Acrolein
      3  Acrylonitrile
     54  Isophorone
    121  Cyanide

11.  Aromatics

      4  Benzene
     86  Toluene
     38  Ethylbenzene

12.  Polyaromatics

     55  Naphthalene
      1  Acenaphthene
     77  Acenaphthylene
     78  Anthracene
     72  Benzo(a)anthracerie (1,2-benzanthracene)
     73  Benzo(a)pyrene («,4-benzopyrene)
     74  3,4-Benzofluoranthene
     75  Benzo(k)fluoranthene (11,12-benzofluoranthene)
     79  Benzo(ghi)perylene (1,12-benzoperylene)
     76  Chrysene
     82  Dibenzo(a,h)anthracene (1,2,5,6-dibenzanthracene)
     80  Fluorene
     39  Fluoranthene
     83  Indeno(1,2,3-cd)pyrene (2,3-o-Phenylene pyrene)
     81  Phenanthrene
     84  Pyrene

13.  Chloroaromatics

      7  Chlorobenzene
     25  o-Dichlofobenzene
     27  p-Dichlorobenzene
     26  m-Dichlorobenzene
      8  1,2,4-Trichlorobenzene
      9  Hexachlorobenzene

14.  Chlorinated Polyaromatic

     20  2-Chloronaphthalene

15.  Polychlorinated Biphenyls

    106-112  Seven listed
                                        -27-

-------
                                    TABLE 4

                           PRIORITY POLLUTANT GROUPS
                                  (Concluded)
16.  Phthalate Esters

     66  bis(2-Ethylhexyl)
     67  Butylbenzyl
     68  Di-n-butyl
     69  Dl-n-octyl
     70  Diethyl
     71  Dimethyl

17.  Nitroaromatics

     56  Nitrobenzene
     35  2,4-Dinitrotoluene
     36  2,6-Dinitrotoluene

18.  Benzidines

      8  Benzidine
     28  3,3'-Dichlorobenzidine
     37  1,2-Diphenylhydrazine

19.  Phenols

     65  Phenol
     34  2,4-Dimethylphenol

20.  Nitrophenols

     57  2-Nitrophenol
     58  4-Nitrophenol
     59  2,4-Dinitrophenol
     60  4,6-Dinitro-o-cresol

21.  Chlorophenols

     24  2-Chlorophenol
     22  4-Chloro-m-cresol
     31  2,4-Dichlorophenol
     21  2,4,6-Trichlorophenol
     64  Pentachlorophenol

22.  144 TCDD (2,3,7,8-Tetrachloro-dibenzo-p-dioxin)

23.  Haloaryl Ethers

     40  4-Chlorophenylphenyl ether
     41  4-Bromophynylphynyl ether
                                         -28-

-------
zero values that occur with a. definite probability.  Consequently, zero
concentration values are modeled by a point distribution, positive concentra-
tion values follow a lognormal distribution, and the mixture of these values
forms the delta-lognormal distribution.  The statistical metholodgy used for
testing the assumption of lognonnality is found in Appendix B of the BPT
Section, and the results of these hypothesis tests are also included in this
Appendix.

     This method provides a reasonable approach for combining quantitative
concentration values with information expressed only as a nondetect, which is
more qualitative in nature.  For the determination of variability factors, the
delta-lognormal procedure was modified by placing the point distribution at
the nominal detection limit.  This approach is somewhat conservative since
values reported as nondetect may actually be any value between zero and the
detection limit.  The detection limits used for each pollutant was the nominal
detection limit in EPA Analytical Methods 1624 and'1625.  Assigning a nominal
detection limit to non-detected values in calculating both variability factors
and long-term medians for this data base tends to result in slightly higher
limitations than would be derived if lower values were assumed.

8.  CALCULATION OF BAT EFFLUENT LIMITATIONS
     Daily maximum and four day monthly average BAT effluent limitations were
calculated for each pollutant by multiplying its long-term median value by
each of its two corresponding variability factors.  If a pollutant had its own
pair of variability factors, these were utilized rather than the pollutant
group variability factors.  With the exception of mercury, all priority
pollutant four-day monthly average and daily maximum limitations were rounded
up to the nearest 5 parts per billion.  Mercury was rounded up to the nearest
one-half part per billion.  After rounding, if the four-day monthly average
equaled the daily maximum value, then only the daily maximum limitation was
listed.  It should be noted that for the volatile priority pollutant bis(2-
chloroisopropyl)ether, data were not available for an appropriate Option II
and III treatment system.  Therefore, a treatability level for bis(2-
chloroisopropyl)ether of 10 ppb was selected based on the performance of steam
stripping.  The treatability level was determined using the methodology
described later in this report for establishing in-plant, pre-biological
limitations.
                                     -29-

-------
     Since insufficient data were available to determine BAT Option  I  Chlori-
nated Cl, C2, and C4 pollutant variability factors, the Chloroalkyl  Ether
variability factor was applied to these pollutants.  For BAT Option  II,  the
average of the variability factors for the Chlorinated Cl and C2  pollutant
groups was applied to the Chlorinated C3, CA, and Chloroalkyl Ether  pollutant
groups.  For BAT Option III, the average variability factors for  the Chlori-
nated Cl, C2, and C3 pollutant groups was applied to Chlorinated  C4  and
Chloroalkyl Ether groups as well.  Since insufficient data were available to
determine variability factors for acrylonitrile (miscellaneous pollutant
group) the average of all organic pollutant groups for each option was applied
to acrylonitrile.

     The BAT effluent limitations for Options I, II, and III are  presented in
Tables 5 through 7, respectively.  Derivation of the BAT statistical
methodology is presented in Appendix A.

9.  DEVELOPMENT OF IN-PLANT PRE-BIOLOGICAL BAT LIMITATIONS
     In addition to the end-of-pipe limitations set forth above,  in-plant
           I
prebiological limitations are being considered for a set of 20 volatile  and
semivolatile organic pollutants.  The purpose of these supplementary limita-
tions would be to assure that these pollutants are not simply transferred to
the air rather than treated by the wastewater treatment system.   Table 8 lists
the pollutants selected for in-plant control along with their estimated  air
emission rates (percent air stripped) through open biological treatment
systems.  Supporting information and data for the determination of these air
stripping figures are listed in Appendix B and available in the public record.
     BAT effluent limitations would  be established  prior  to  biological
treatment and would  require  that control  authorities  require compliance
monitoring  prior to  the  biological system.   These in-plant  limitations would
be based upon the available  in-plant  stream  stripping performance  data.   For
the  steam stripping  assessment, the  organic  priority  pollutants  were divided
into three  groups (high, medium, and  low) based  on  their  Henry's Law
Constants.   For aqueous  mixtures, the distribution  of a pollutant  between the
                                      -30-

-------
                                    TABLE  5

                    OPTION I BAT EFFLUENT  LIMITATIONS  (ppb)
Pollutant or Pollutant Property
by Priority Pollutant Classes
                               Median of
                               Long-Terra
                               Weighted
                               Means
          Four Day
          Monthly
          Average
                          Daily
                          Maximum
Halogenated Methanes (Cl's)

 6.  Carbon tetrachloride
23.  Chloroform
44.  Methylene chloride
47.  Bromoform

Chlorinated C2's

10.  1,2-Dichloroethane
12.  Hexachloroethane
16.  Chloroethane
30.  1,2-trans-Dichloroethylene
85.  Tetrachloroethylene

Chlorinated C4's

52.  Hexachlorobutadiene

Chloroalkyl Ethers

42.  bis(2-chloroisopropyl)ether

Metals
114.
115.
119.
120.
122.
123.
124.
125.
128.
Antimony
Arsenic
Chromium
Copper
Lead
Mercury
Nickel
Selenium
Zinc
                                  10
                                  10
                                  11.1
                                  10
                                 10.3
                                 10
                                 50
                                 77.5
                                 118.9
                                 10
                              1,463
,7
,3
 65
 17
 86,
 21,
329
  0.2
145
 12
 52.5
             20
             20
             25
             20
             25
             20
            100
            155
            235
             20
          2,860
 85
 30
120
 35
860

235
 20
 90
                              50
                              50
                              55
                              50
                              50
                              50
                             245
                            '375
                             575
                              50
                           7,035
  US'
   60
  195
   75
2,585
    0.
  495
   45
  190

-------
                                    TABLE 5

                    OPTION I BAT EFFLUENT LIMITATIONS  (ppb)
                                  (Continued)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Median of
Long-Term
Weighted
Means
Four Day
Monthly
Average
Daily
Maximum
Miscellaneous

  3.  Acrylonitrile
121.  Cyanide

Aromatics

 4.  Benzene
38.  Ethylbenzene
86.  Toluene
  50
  64.9
  27.1
  10
  10
  105
  120
   80
   35
   40
   270
   275
   245
   125
   155
Polyaromatics

 1.  Acenaphthene
39.  Fluoranthene
55.  Naphthalene
72.  Benzo(a)anthracene
73.  Benzo(a)pyrene
74.  3,4-Benzofluoranthene
76.  Chrysene
77.  Acenaphthylene
78.  Anthracene
80.  Fluorene
81.  Phenanthrene
84.  Pyrene

Chloroaromatics

 7.  Chlorobenzene
 8.  l,2»4-Trichlorobenzene
 9.  Hexachlorobenzene
25.  o-Dichlorobenzene
26.  m-Dichlorobenzene
27.  p-Dichlorobenzene

Phthalate Esters
 66.  bis(2-Ethylhexyl)phthalate
 68.  Di-n-butyl  phthalate
 70.  Diethyl  phthalate
 71.  Dimethyl  phthalate
  10
  13.2
  10
  10
  10
  10
  10
  10
  10
  10
  10
  12.6
  23-. 1
  42.8
  10
  23.9
  21.3
  10
   19.6
   22.2
   44.4
   10
   35
   45
   35
   35
   35
   35
   35
   35
   35
   35
   35
   40
   65
   70
   20
   40
   25
   20
   45
   40
   90
   20
   105
   140
   105
   105
   105
   105
   105
   105
   105
   105
   105
   135
   185
   140
    40
    75
    35
    40
    130
    80
    215
    50
                                          -32-

-------
                                    TABLE 5

                    OPTION I BAT EFFLUENT LIMITATIONS  (ppb)
                                  (Concluded)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Median of
Long-Term
Weighted
Means
Four Day
Monthly
Average
Daily
Maximum
Nitroaromatics

35.  2,4-Dinitrotoluene
36.  2,6-Dinitrotoluene
56.  Nitrobenzene

Benzidines

28.  3,3'-Dichlorobenzidine

Phenols

34.  2,4-Dimethylphenol
65.  Phenol

Nitrophenols

57.  2-Nitrophenol
58.  4-Nitrophenol
59.  2,4-dinitrophenol

Chlorophenols

21.  2,4,6-Trichlorophenol
24,  2-chlorophenol
31.  2,4-Dichlorophenol
64.  Pentachlorophenol
 952
 327
 351
 262
  10
  10
  40.7
  50
 102
  65.9
  10
  16.9
  50
1,360
  445
  950
  320
   20
   20
   '60
   75
  150
  115
   35
   45
   65
 2,450
   730
 2,965
   450
    35
    35
    95
   125
   260
   260
   125
   130
   100
                                          -33-

-------
                                    TABLE 6

                   OPTION II BAT EFFLUENT LIMITATIONS  (ppb)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Median of
Long-Term
Weighted
Means
Four Day
Monthly
Average
Daily
Maximum
Halogenated Methanes (Cl's)

 6.  Carbon tetrachloride              10
23.  Chloroform                        10
44.  Methylene chloride                10
45.  Methyl chloride     .              50
47.  Bromoform                         10
48.  B'romodichloromethane              10

Chlorinated C2's

10.  1,2-Dichloroethane                13:4
11.  1,1,1-Trichloroethane       .      10
12.  Hexachloroethane     •           '  10
14.  1,1,2-Trichloroethane             10
16.  Chloroethane                      50
29.  1,1-Dichloroethylene              10
30.  1,2-trans-Dichloroethylene        10
85.  Tetrachloroethylene               10.7
87.  Trichloroethylene                 10
88.  Vinyl chloride                    10

Chlorinated C3's

32.  1,2-Dichloropropane               59.4
33.  1,3-Dichloropropylene             36.9

Chlorinated C4's

52.  Hexachl°orobutadiene              10

Chloroalkyl Ethers

42.  bis(2-chloroisopropyl)ether       10
                  15
                  20
                  15
                  75
                  15
                  15
                 35
                 25
                 25
                 25
                 115
                 25
                 25
                 25
                 25
                 25
                 110
                 70
                 20
                 20
                 30
                 40
                 20
                130
                 30
                 30
                 95
                 65
                 65
                 65
                315
                 65
                 65
                 65
                 65
                 65
                265
                165
                 45
                 45
                                           -34-

-------
                 TABLE 6

OPTION II BAT EFFLUENT LIMITATIONS (ppb)
               (Continued)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Metals
114. Antimony
115. Arsenic
119. Chromium
120. Copper
122. Lead
123. Mercury
124. Nickel
125. Selenium
128. Zinc
Miscellaneous
3. Acrylonitrile .
121. Cyanide
Aromatics
4. Benzene
38. Ethylbenzene
86. Toluene
Polyaromatics
1 . Acenaphthene
39. Fluoranthene
55. Naphthalene
72. Benzo(a)anthracene
73. Benzo(a)pyrene
74. 3,4-Benzofluoranthene
76. Chrysene
77. Acenaphthylene
78. Anthracene
80. Fluorene
81. Phenanthrene
84, Pyrene
Median of
Long-Term
Weighted
Means

158
25.1
64.5
27.7
100
2.03
166
12
69.5

50
64.9

10
10
10

10
13.2
10
10
10
10
10
10
10
10
10
12.6
Four Day
Monthly
Average

200
50
90
45
265
2.5
195
20
105

100
120

30
30
35

35
45
35
35
35
35
35
35
35
35
35
40
Daily
Maximum

305
115
150
90
785
3.0
255
40
190

250
275

85
100
115

105
140
105
105
105
105
105
105
105
105
105
135
                     -35-

-------
                                    TABLE 6

                   OPTION II BAT EFFLUENT LIMITATIONS (ppb)
                                  (Continued)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Chloroaromatics
7. Chlorobenzene
8. 1,2,4-Trichlorobenzene
9 . Hexachlorobenzene
25. o-Dichlorobenzene
26. m-Dichlorobenzene
27. p-Dichlorobenzene
Phthalate Esters
66. bis(2-Ethylhexyl)phthalate
68. Di-n-butyl phthalate '
70. Diethyl phthalate
71. Dimethyl phthalate
Nitroaroraatics
35. 2,4-Dinitrotoluene
36. 2,6-Dinitrotoluene
56. Nitrobenzene
Median of
Long-Term
Weighted
Means

15.9
26.4
10
52.3
21.3
10

19.6
22.2
44.4
10

219
255
206
Four Day
Monthly
Average

40
45
20
80
25
20

45 .
40
90
20

310
340
285
Daily
Maximum

115
90
40
145
35
40

• 130
80 '
215
50

540
555
480
Benzidines

28.  3,3'-Dichlorobenzidine

Phenols

34.  2,4-Dimethylphenol
65.  Phenol

Nitrophenols

57.  2-Nitrophenol
58.  4-Nitrophenol
59.  2,4-dinitrophenol
60.  4,6-Dinitro-o-cresol
262
 10.6
 10
 24.0
 50
 50
 20
320
 20
 20
 35
 70
 75
 30
450
 35
 35
 55
120
130
 50
                                           -36-

-------
                                    TABLE 6

                   OPTION II BAT EFFLUENT LIMITATIONS (ppb)
                                  (Concluded)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Median of
Long-Term
Weighted
Means
Four Day
Monthly
Average
Daily
Maximum
Chlorophenols

21.  2,4,6-Trichlorophenol
24.  2-chlorophenol
31.  2,4-Dichlorophenol
64.  Pentachlorophenol
  65.9
  10
  16.9
  50 •
  115
   35
   45
   65
   260
   125
   130
   100
                                        -37-

-------
                                    TABLE 7

                   OPTION III BAT EFFLUENT LIMITATIONS  (ppb)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Median of
Long-Term
Weighted
Means
Four Day
Monthly
Average
Daily
Maximum
Halogenated Methanes (Cl's)

 6.  Carbon tetrachloride              10
23.  Chloroform                        10
44.  Methylene chloride                10
45.  Methyl chloride                   50
47.  Bromoform                 .        10
48.  Bromodichloromethane              10

Chlorinated C2's

10.  1,2-Dichloroethane                13
11.  1,1,1-Trichloroethane             10
12.  Hexachloroethane                  10
14.  1,1,2-Trichloroethane             10
16.  Chloroethane                      50
29.  1,1-Dichloroethylene              10
30.  1,2-trans-Dichloroethylene        10
85.  Tetrachloroethylene               10.2
87.  Trichloroethylene                 10
88.  Vinyl chloride                    10

Chlorinated C3's

32.  1,2-Dichloropropane               36.1
33.  1,3-Dichloropropylene             36.9

Chlorinated C4's

52.  Hexachlorobutadiene               10

Chloroalkyl Ethers

42.  bis(2-chloroisopropyl)ether       10
                  15
                  20
                  15
                  75
                  15
                  15
                 30
                 25
                 25
                 25
                 115
                 25
                 25
                 25
                 25
                 25
                 50
                 50
                  20
                  20
                 30
                 40
                 20
                 130
                 30
                 30
                 85
                 65
                 65
                 65
                315
                 65
                 65
                 65
                 65
                 65
                 70
                 70
                 40
                 40
                                       -38-

-------
                 TABLE 7

OPTION III BAT EFFLUENT LIMITATIONS (ppb)
               (Continued)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Metals
114. Antimony
115. Arsenic
119. Chromium
120. .Copper
122. Lead
123. Mercury
124. Nickel
125. Selenium
128. Zinc . .
Miscellaneous
3. Acrylonitrile
121. Cyanide
Aromatics
4. Benzene
38. Ethylbenzene
86. Toluene
Polyaromatics
1 . Acenaphthene
39. Fluoranthene
55. Naphthalene
72. Benzo(a)anthracene
73. Benzo(a)pyrene
74. 3,4-Benzofluoranthene
76. Chrysene
77. Acenaphthylene
78. Anthracene
80. Fluorene
8 1 . Phenanthrene
84. Pyrene
Median of
Long-Tera
Weighted
Means

158
25
57.6
27.7
86.7
2.03'
145
12
66.1

50
64.9

10
10
10

10
13.2
10
10
10
10
10
10
10
10
10
12.6
Four Day
Monthly
Average

200
40
80
45
230
2.5
170
20
100 *

95
120

25
30
30

35
45
35
35
35
35
35
35
35
35
35
40
Daily
Maximum

305
80
130
90
680
3.0
225
40
190

235
275

80
90
100

105
140
105
105
105
105
105
105
105
105
105
135
                       -39-

-------
                                    TABLE 7

                   OPTION III BAT EFFLUENT LIMITATIONS (ppb)
                                  (Continued)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Chloroaromatics
7. Chlorobenzene
8. 1,2,4-Trichlorobenzene
9. Hexachlorobenzene
25. p-Dichlorobenzene
26. m-Dichlorobenzene
27. p-Dichlorobenzene
Phthalate Esters
66. bis(2-Ethylhexyl)phthalate
68. Di-n-butyl phthalate
70. Diethyl phthalate
71. Dimethyl phthalate
Nitroaromatics
35. 2,4-Dinitrotoluene
36. 2,6-Dinitrotoluene
56. Nitrobenzene
Median of
Long-Term
Weighted
Means
11.3
26.4
10
23.8
21.3
10
*
19.6
22.2
44.4
10
108
217
206
Four Day
Monthly
Average
25
45
20
40
25
20
45
40
90
20
150
285
285
Daily
Maximum
70
90
35
70
35
35
130 '
80
215
50
255
455
480
Benzidines

28.  3,3'-Dichlorobenzidine

Phenols

34.  2,4-Dimethylphenol
65.  Phenol

Nitrophenols

57.  2-Nitrophenol
58.  4-Nitrophenol
59.  2,4-dinitrophenol
60.  4,6-Dinitro-o-cresol
262
 11.1
 10
 22.6
 50
 50
 20
320
 20
 20
 30
 70
 75
 30
450
 40
 35
 50
120
130
 50
                                         -40-

-------
                                    TABLE 7

                   OPTION III BAT EFFLUENT LIMITATIONS (ppb)
                                  (Concluded)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Median of
Long-Terra
Weighted
Means
Four Day
Monthly
Average
Daily
Maximum
Chlorophenols

21.  2,4,6-Trichlorophenol
24.  2-chlorophenol
31.  2,4-Dichlorophenol
&4.  Pentachlorophenol
  65.9
  10
  16.9
  50
  115
   35
   45
   65
   260
   125
   130
   100
                                          -41-

-------
                             TABLE 8
VOLATILE AND SEMI-VOLATILE POLLUTANTS AND AIR STRIPPING ESTIMATES
       (PERCENT) THROUGH OPEN BIOLOGICAL TREATMENT SYSTEMS
       Benzene                                 85
       Carbon tetrachloride                    60
       Chlorobenzene                           80
       1,1,1-Trichloroethane                   95
       Chloroform                              35
       Toluene                                 85
       1,1-Dichloroethylene                    45
       1,2-Trans-Dichloroethylene              70
       Trichloroethylene                       40
       Tetrachloroethylene                     95
       Hexachloroethane                        25
       1,3-Dichlorobenzene                    - 20
       1,4-Dichlorobenzene                     20
       1,2-Dichloroethane                      35
       1,1,2-Trichloroethane                   40
       Methylene Chloride                      55
       1,2-Dichloropropane                     90
       1,2-.Dichlorobenzene                     20
       Hexachlorobenzene                       25
       Vinyl chloride                          75
                                  -42-

-------
vapor phase and water can be expressed by Henry's Law.  Compounds with high
vapor pressures (high Henry's Law constants) are easily stripped.  By assuming
that compounds in each group behave similarly, group median effluent values
were calculated—a median of 11.7 ppb represents the high stripping group;
nondetect represents the medium stripping group; and 1417.5 ppb, for the low
stripping group.  Table 9 presents the pollutants that are contained in each
of these groups and the average steam stripping effluent values for the
pollutants with data are noted.

     The BAT in-plant limitations for Options II and III are listed in Table
10.
                                      -43-

-------
                                    TABLE 9

                     HENRY'S CONSTANT STRIPPABILITY GROUPS
               WITH AVERAGE STEAM STRIPPING EFFLUENT VALUES (ppb)
(3 x
  HIGH

102 to
   10-')
    MEDIUM

(10"2 to 10~3)
     LOW

(10~4 to 10~8)
Benzene - 16.1
Carbon Tetrachloride
Chlorobenzene
1,1,1-Trichloroethane
Chloroethane - ND
1,1-Dichloroethane
Chloroform - ND
Methyl Chloride - ND
Toluene
Vinyl Chloride -76
1,1-Diohloroethene- ND
1,2-Trans-Dichloroethene
     14.36
Trichloroethylene-13.4
Tetrachloroethylene
Hexachloro-1,3-Butadiene
Hexachlorocyclopentadiene
Bromomethane
Bromodichloromethane
Dichlorodifluoromethane
Trichlorofluoromethane
1,3-Dichlorobenzene
1,4-Dichlorobenzene
Ethylbenzene
                     Acenaphthene
                     Acrolein
                     Acrylonitrile
                     1,2-Dichloroethane - 12
                     Hexachloroethane
                     1,1,2-Trichloroethane-ND
                     1,1,2,2-Tetrachloroethane
                     Methylene Chloride - ND
                     1,2-Dichloropropane
                     1,3-Dichloropropene
                     Dibromochloromethane
                     Tribromomethane
                     •Bis(2-Chloromethyl)Ether
                     Bis(2-Chloroisopropyl)
                          Ether
                     4-Chlorophenyl Phenyl
                          Ether
                     4-Bromophenyl Phenyl
                          Ether
                     1,2-Dichlorobenzene
                     1,2,4-Trichlorobenzene
                     Hexachlorobenzene
                     4-Nitrophenol
                     4,6-Dinitro-o-Cresol
                     Acenaphthylene
                     Anthracene
                     Benzo(k)Fluoranthene
                     Fluorene
                     Naphthalene
                     Phenanthrene
                     Dimethyl Nitrosoamine
                     Diphenyl Nitrosoamine

                     Group
                     Median = ND
                                   3     3
Henry's Law constant units are mg/m /mg/m
Group
Median
11.7 ppb
                         Bis(2-Chloroethyl)Ether
                         2-Chloroethyl Vinyl Ether
                         Bis(2-Chloroethoxy)Methane
                         Nitrobenzene
                         2,4-Dinitrotoluene
                         2,6-Dinitrotoluene
                         Phenol
                         2-Chlorophenol
                         2,4-Dichlorophenol
                         2,4,6-Trichlorophenol-1051
                         Pentachlorophenol - 1784
                         2-Nitrophenol
                         2,4-Dinitrophenol
                         2,4-Dimethylphenol
                         p-Chloro-m-Cresol
                         Dimethyl Phthalate
                         Diethyl Phthalate
                         Di-n-Butyl Phthalate
                         Di-n-Octyl Phthalate
                         Bis(2-Ethylhexyl)Phthalate
                         Butyl Benzyl Phthalate
                         Benzo(a)Anthracene
                         Benzo(b)Fluoranthene
                         Benzo(ghi)Perylene
                         Benzo(a)Pyrene
                         Chrysene
                         Fluoranthene
                         Indeno(1,2,3-cd)Pyrene
                         Pyrene
                         Di-n-Propyl Nitrosoamine
                         Benzidine
                         3,3-Dichlorobenzidine
                         1,2-Diphenylhydrazine
                         Dibenzo(a,h)Anthracene
                                                    Group
                                                    Median
                                                        1417.5 ppb
                                       -44-

-------
                                   TABLE  10

             BAT IN-PLANT LIMITATIONS  FOR OPTIONS II AND III (ppb)
Pollutant or Pollutant Property
by Priority Pollutant Classes
Median of
Long-Term
Weighted
Means
Four Day
Monthly
Average
Daily
Maximum
Halogenated Methanes (Cl's)

 6.  Carbon tetrachloride
23.  Chloroform
44.  Methylene chloride

Chlorinated C2's
10.  1,2-Dichloroethane
11.  1,1,1-Trichloroethane
12.  Hexachloroethane
14.  1,1,2-Trichloroeth'ane
29.  1,1-Dichloroethylene
30.  1,2-trans-Dichloroethylene
85.  Tetrachloroethylene
87.  Trichloroethylene
88.  Vinyl chloride

Chlorinated C3's

32.  1,2-Dichloropropane

Aromatics

 4.  Benzene
86. Toluene

Chloroaromatics

 7.  Chlorobenzene
 9.  Hexachlorobenzene
25.  o-Dichlorobenzene
26.  m-Dichlorobenzene
27.  p-Dichlorobenzene
  11.7
  11.7
  •10
  10
  11,
  10
  10
  11,
  11,
  11,
  11,
  11.7
  10
  11.7
  11.7
  11.7
  10
  10
  11.7
  11.7
   25
   25
   20
   20
   25
   20
   20
   25
   25
   25
   25
   25
   20
   25
   25
   25
   20
   20
   25
   25
    55
    55
    45
    45
    55
    45
    45
    55
    55
    55
    55
    55
    45
    50
    50
    50
    40
    40
    50
    50
                                        -45-

-------
         APPENDIX A




BAT STATISTICAL METHODOLOGY

-------

-------
                        VARIABILITY FACTOR DEVELOPMENT

     In the process of developing limitations for effluent  concentrations,
EPA used a modification of the estimation procedure for the delta-lognormal
distribution for determining variability factors.  The delta-lognormal
distribution (discussed in Aitchison and Brown (1957)) can  be expressed  as
a mixture of the lognormal distribution for concentration values greater
than zero, and a point distribution for concentration values of zero.  That
is, the delta-lognormal distribution for concentration values x can be
expressed as:

     f(x) - « I(x ) + (1 - 6) g(x)
           where 0 £ 6 <_ 1,
          ' X(x0) - 1 for XQ = 0  _
                 * 0 elsewhere,
        and g(x) = (2TT02)"1/2 exp
                                   -(log x - y)2
                                      for x > 0
                                                          elsewhere.
     The 99th percentile of this distribution is Pgg - exp(u + z*a), where
b-1
          0.99 - 6
,  where *""*• represents the inverse of the standard normal
            1 - 5
cumulative distribution function.
     The mean or expected value, E(X), and the variance, V(X), of the delta-
lognormal distribution, are as follows:
     E(X) = (1 - 
-------
     Consider now a modification o'f the estimation procedure for this distri-
bution where a certain proportion of values are assumed to be at a nonnegative
value D.  This modification is used for a combination of positive concentration
values and observations which can only be quantified as nondetect (ND) at a
detection limit, D.  All nondetects will be incorporated at this point D.
That is:
f(x) - 5
                          - 6) g(x)
              where 0 ^ 5 <_ 1,
              I(x ) = 1  for XQ = D (for nondetected values)
                   = 0  elsewhere,
                                -(log x -
     and g(x) = (2n.o2)~1/2 exp
                                                   for x > 0
                                                         elsewhere.
     The 99th percentile is:
          Pgg = max (D, exp(y + z*o)),
and the mean and variance are:
          E(X) = 6 D + (1 - 5) exp(u + 0.5a2)
          V(X) - (1 - 6) exp(2u + a2) (exp(a2) - (1 - 6)) +
                 6 (1 - 6) D (D - 2 exp(y + 0.5a2)).
                                         A-2

-------
     In the following sections, details on variability factor development for
this method, as well as other methodologies investigated, are presented.  The
other methodologies are based on different distributional assumptions and are
organized as follows:
     Section A:  Modification of the estimation procedure
                 for the delta-lognormal distribution
     Section B:  Lognormal distribution' with censoring
     Section C:  Delta-lognormal distribution for shifted
                 concentration values
     Section D:  Combination of the lognormal distribution
                 and delta-lognorraal distribution for shifted
                 concentration values.
For each of these methodologies, procedures for the development of 99th
percentile daily variability factors and 95th percentile 4-day mean variability
factors are presented.  Daily variability factors are derived by taking the
ratio of the estimated 99th percentile of the distribution of concentration
values to the estimated mean of the distribution.  4-day mean variability
factors are found by taking the ratio of the estimated 95th percentile of
the distribution of 4-day means to the estimated mean of this distribution.

     The delta-lognormal distribution and the estimation procedure- used for
determining variability factors are described above.  For reference in the
subsequent sections, the following distributions and their mathematical
formulations are described below:

     Lognormal:
                o
     g(x) = (2TT02)     exp
'-(log x -
       2V
          = 0
for x > 0
                      elsewhere
                                       A-3

-------
     Delta-Lognormal for Shifted Concentration Values:




     f(x) - 5 I(x ) + (1 - 6) g(x - D)



          where 0 <_ 5 <_ 1,




          *(XQ) • 1   for XQ = D



                » 0   elsewhere,



and g(x - D) is the lognormal distribution for shifted concentration values;

that is,
                   , -1/2
    g(x - D) - (2ita2)     exp
-(log(x - D) - u)
                 21
                                                    (x - D)
for (x - D) > 0
         - 0
                           elsewhere.
                                A-A

-------
                 A.  MODIFICATION OF THE ESTIMATION PROCEDURE
                     FOR THE DELTA-LOGNORMAL DISTRIBUTION
A.I  DAILY VARIABILITY FACTORS

     The 99th percentile of daily values was estimated by substituting the
sample logmean and logvariance of concentration values and the sample propor-
tion of nondetects into the mathematical formula for the 99th percentile of
the modification of the estimation procedure for the delta-lognormal distri-
bution described previously.  The expectation of the daily values was estimated
by substituting the sample logmean and logvariance of concentration values and
the sample proportion of nondetects into the formula for the mean of this
distribution.

     Let xi, X£, ••«, xr, xr+i  ..., xn be a random sample of size n, with r
observations recorded as nondetects, and n - r observations recorded as
concentration values.  Assume these n - r observations come from a lognorraal
distribution, and let y and a2 be the sample mean and variance, respectively,
of log(X).  Let 6 be the sample proportion of nondetects.  Then the estimate
of the mean of this distribution, based upon the modification to the estima-
tion procedure for the delta-lognormal distribution, is:
     E(X) = 6 D + (1 - 6) exp(y + 0.5a2)                                    (A-l)
            n
      A     I  log Xi
where y = i=r+l	   (calculated for r < n),                             (A-2)
             n - r
            I  (log xt - $)2
     a* * i=r+l	        (calculated for r < n - 1),           (A-3)
               n " r ~ 1                                      _~~—
      A
and   5 = 1..                                                               (A-A)
          n
                                        A-5

-------
     The log(*) notation presented above represents the natural logarithm
(base e), and this notation will be used in subsequent formulas.  The estimate
of the 99th percentile is:
              D                      6 > 0.99
                                        .
     P99 =  \              A                                                 (A-5)
              max (D, exp(n + z*a))  elsewhere
                    0.99 - 6
     where z*
                          A
                      1-6
Using expressions (A-l) and (A-5) the 99th percentile daily variability factor,
VF(1), is:
     VF(1) =  "    .
             E(X)

A.2  VARIABILITY FACTOR OF 4-DAY MEANS

     The procedure for estimating the 95th percentile of 4-day means was first
to substitute the sample logmean, sample logvariance, and sample proportion
of nondetects into the mathematical formulas of the logmean and the logvariance
of 4-day means of values, where the modification of the estimation procedure
for the delta-lognormal distribution, as described previously, was used.  The
logmean and the logvariance of 4-day means, in turn, were used to estimate
the 95th percentile of the distribution of 4-day means, based on this modifi-
cation.  The estimate of the expectation of 4-day means is the same as the
estimate of the expectation of daily values, assuming this modification of the
estimation procedure for the delta-lognormal distribution (as in section A.I),
where values of the sample logmean, sample logvariance, and sample proportion
of nondetects are incorporated.  The 95th percentile 4-day mean variability
factor was derived as the ratio of this estimate of the 95th percentile of
4-day means to this estimate of the expectation.
                                        A-6

-------
     The mean of the distribution of concentration values, based  on  this
modification, is

          E(X) = 6 D + (1 - 6) exp(y + 0.5o2)
                                                                        (A-6)
Making the assumption that the approximating distribution  of X^,  the  sample
mean for a random sample of four independent concentrations, is also  a  derived
from this modification of the estimation procedure for  the delta-lognorraal
distribution, with the same mean as the distribution of concentration values,
and with variance proportional to the variance of the distribution  of concen-
tration values (Barakat (1976)), it follows that  the mean  of this distribution
is:
E(X4)
                       - <54) .exp(u4 + 0.5a4)
     Using (A-7), it can be seeti'that
           log
            E(X4) - 640
              1 - 64
- 0.5a/.
Since E(X) = E(X4) and 64 =
          log
                E(X) - 6V
                        - 0.5a/.
                             i_
To derive an expression for 04, we use the following relationships;

     V(X) = (1 - 6) exp(2y + a2)  [exp(a2) - (1 - 6)]  +
              5 (1 - 6) D [D - 2  exp(u + 0.5a2)]
V(X4)
                - 64) exp(2u4 + a4)
                          D  [D - 2 exp(u4 + 0.5a4)]
                                             (A-7.)
(A-8)
                                             (A-9)
                                                                        (A-10)
                                             (A-ll)
                                       A-7

-------
Using. (A-7) and (A-ll) it  follows  that
     a4 -  log
                 -  64)
                             -  54)[V(X4)  - 64(1 - 54)D[D - 2exp(y4 + 0.5a4)]]
                                            [E(X4)  - 64D]
(A-
From  (A-7),  by  rearranging  terms,
                   2     E(X4) -  <54D
     exp(u4 + 0.5a4)
                         U -  64)
using  (A-12)  and  (A-13),
                                                                              (A-I:
       log  {  (1 -  64)
                              v(x4)
                                                - «4)D       2 64D
                                               	 + 	
                           [E(X4)  - 54D]2   [E(X4) - 64I
                                                              •4) ~ 54DJ
                                                                              (A-14
      Since V(X)  = V(X4)/4,  E(X)  = E(X4),  and 64 = 5k,  expression (A-14)

 can  be  rewritten as:
o2  - log / (1 -
V(X)
1 +
4[E(X) - 8kl
6l+(l-5l+)D:
)]2 (E(X) - 6U1
+
D]2 E(X) - 6^
                                                                             •  (A-15
                                       A-8

-------
                     A                                     A
     Using values of 6 (sample proportion of nondetects),  y  (sample  logmean
of the concentrations), and  a2 (sample logvariance), defined in  (A-2)  through
(A-4) as estimates of 6, p,  and  a2, respectively, in expressions  (A-9)  and
                                   rt                      9
(A-15) yields estimates of y^ and  a^, denoted by  u^ and  o^,  respectively.

     Using these estimates of 114,  04, and 61* ,  the estimate  of the 95th
percentile of X  is
     P95
                                         61* > 0.95
              max(D,exp(y^ + z^a^))     elsewhere
(A-16)
       .    -1 ' °'95 -
where z/. * *
               1  1 -

     Using (A-16) and (A-l), since E(X) = £(£4), the 95th percentile  4-day  mean
variability factor is
     VF(l) =
             E(X)
                                     A-9

-------
                  B.  LOGNORMAL DISTRIBUTION WITH CENSORING

B.I  DAILY VARIABILITY FACTORS

     Cohen's maximum likelihood estimate of the logvariance in the case of
Type I censoring (fixed censoring point) was substituted into the daily
variability factor, assuming a lognormal distribution.  The detection limit
was taken to be the censoring point.  This approach assumes that concentration
values which are recorded as nondetect exist, but are below the detection
limit.  Values falling below the detection limit (D) are considered Type I
censored observations.

     Assume y^_ ~ N(u, o2), i * 1, 2, ..., r, r + 1, ..... n, where y =
log(concentration value) and r nondetects are present in a sample of size n.
Let yo * log D and let y^, i « r + 1, ... n, be the logarithm of the
detected concentrations.

     Letting Y - s2/(7 - y0)2,
            1     n
where y » —=—   Z   y., , and
          n - r i-r+1
      •>     i     n        — •>
     s2 -—^-   Z  (y± - y)2,
          n - r 1-rH

and h = (n - r)/n allows one to obtain a value for X from Cohen's Table 2
(Cohen (1961)) to be used in the estimate of  a2.  This estimate for  a2 is

      a2 - s2 + X(7- y0)2-                                                  (B-l)
                                     A-10

-------
     The 99th percentile daily variability factor, VF(1), is calculated
assuming a lognormal distribution of concentration values.  That is,

     VF(1) = exp(2.326o - 0.5a"2),                                           (B-2)

where $2 is Cohen's maximum likelihood estimate assuming censoring, as found
in (B-l).

B.2  VARIABILITY FACTORS OF 4-DAY MEANS

     The mathematical formulation of the variability factor of 4-day means
of lognormally distributed values was derived in terms of the logvariance of
4-day means, which, in turn, was formulated in terms of the logvariance of
daily values.  The 4-day mean variability factor was estimated by substi-
tuting Cohen's maximum likelihood estimate of•the logvariance for the case
of Type I censoring into the resulting mathematical formulation.  The detection
limit was taken to be the censoring point.

     The 4-day mean variability factor, assuming lognormality and independence
of the observations, is derived from the following formulas, assuming X has a
lognormal distribution with parameters y and a2:
     E[X] =• exp(u + 0.5o2)                                                  (B-3)

     E[X4] = exp(u4 + 0.504)                                                (B-4)

     V[X] = exp(2y + a2)(exp(a2) - 1), and                                  (B-5)

     V[X4] - exp(2y4 + a4)(exp(a4) -1).                                    (B-6)

     Since E[X] = E[X4], by using (B-3) and (B-4), it follows that
                         2
      P4 - u -I- 0.5U2 - a4) .                                               (B-7)
                                     A-ll

-------
Since V[X4l = V[X]/4, by using (B-5), (B-6), and (B-7), the following expres-
sion results:

     oj = log((exp(a2) -*- 3)/4).                                              (B-8)

     Finally, the 95th percentile 4-day mean variability factor, VF(4), can
be expressed as

     VF(4) = exp(1.645 a4 - O.SaJ)                                           (B-9)
       f)
where OA is found by substituting Cohen's estimate of  a2 assuming censoring,
as given in (B-l), into expression (B-8).
                                   A-12

-------
       C.  DELTA-LOGNORMAL DISTRIBUTION ON SHIFTED CONCENTRATION VALUES

C.I  DAILY VARIABILITY FACTORS

     The 99th percentile of daily values was estimated by substituting the
sample logmean and logvariance of shifted concentration values and the esti-
mated proportion of nondetects into the mathematical formula for the 99th
percentile of a delta-lognormal distribution (i.e., a delta-lognormal
distribution with origin D).  The expectation of the daily values was esti-
mated by the Aitchison and Brown maximum likelihood equivalent method involv-
ing the Bessel function.  The daily variability factor was determined as
the ratio of this estimate of the 99th percentile to this estimate of the
expectation.
     Let X]_, X2, ..., xr, Xj+i, ..., xn be a random sample of size n from a
delta-lognormal distribution with origin D and r (r _<_ n) observations being
at D.  These r observations are those observations which were recorded as
nondetect and placed at the detection limit D.  Also, let u and a2 be the
sample mean and variance, respectively, of log(x - D), where x > D, and
let 6 be the sample proportion of nondetects.

     For D = 0, it can be shown that

           (1 - 5) exp(u) t(n_r)(o2/2) , r <. n - 2
E[X0] = \  xi/n                        , r - n - 1                          (C-l)
           0                           , r - n

is a minimum variance, unbiased estimate of E[X],  For the general case,
where D _> 0,

     E[XD] = E[X0] + D.                                                     (C-2)

     In expression (C-l),
              E uj(a, t),                                                   (03)
             j-o
                                    A-13

-------
where
u.j(a, t) =<
             (a - 1) t
             f   (a - 1)     t] u-i-
           ^  ja(a + 2j - 3)
      , J - o
      , j -1

i, t)  , j .> 2,
                                               (C-4)
Also, t|;a(t) is assumed to have converged  if
               (a - 1)
            ja(a + 2j - 3)
<_ 0.0001 for j >_ 2.
                                       (C-5)
     The 99th percentile of  this delta-lognormal  distribution with origin D is:
                               ,  5  V0.99
where
                           „
              D + exp(y +  z a) , elsewhere,
              /0.99 -  8\
              \ 1 - 6   /
                                                                             (C-6)
with  *~^ defined  as  the  inverse  of  the  standard  normal cumulative distribu-
tion  function.  An estimate  of  the  above  99th percentile can be calculated by
substituting estimates for  6,  y,  and  a  into  expression (C-6).   Here,  the
estimate of 5  equals r/n, and  the estimates  of y and a^ are the sample logmean
and logvariance,  respectively,  of the shifted (x - D)  concentrations.  This
                                              X*v
estimate for the  99th percentile, denoted by Pgg,  is used to develop  the 99th
percentile daily  variability factor,
     VF(1)
                                               (C-7)
              E[XD]
 where  E(XD)  is  defined in (C-2),
                                    A-14

-------
C.2  VARIABILITY FACTORS OF 4-DAY MEANS

     The procedure for estimating the 95th percentile of 4-day means was
first to substitute the sample logmean and sample logvariance into the
mathematical formulas of the logmean and the logvariance of 4-day means of
values distributed as a delta-lognormal distribution with origin D.  The
logmean and the logvariance of 4-day means, in turn, were used to estimate
the 95th percentile from the delta-lognormal distribution of 4-day means of
shifted concentration values.  The estimate of the expectation of 4-day means
is the same as the estimate of the expectation of daily values, assuming a
delta-lognormal distribution with origin D (as in section C.I), where the
Aitchison and Brown estimation method involving the Bessel function is utilized.
The 4-day mean variability factor was derived as the ratio of this estimate
of the 95th percentile of 4-day means to this estimate of the expectation.
                                                                             %
     Let X^ be the sample mean for a random sample of four independent
concentrations.  The distribution of X^ is also approximated by a delta- .
lognormal distribution of shifted concentration values, with origin D and
parameters 114, 04, and 64.

     The mean of this distribution is

     E[XD] = D + (1 - 6) exp(u + 0.5o2).                                    (C-8)

It follows that the mean of X4*s approximating distribution is

     E[X4] - D + (1 - 54) exp(ji4 + 0.504)-                                  (c'9)

Since E[XD] = £[£4] and 64 = 5\ by using (C-8) and (C-9), it can be seen that

      y4 = log(1 " 5lf) + u + 0.5(a2 - 04).                                  (C-10)
                                     A-15

-------
     Since V[XD]  = V[X4]/4 and <54 - 54, by using the relationships


     V[XD] - (1 - 6)(exp(p +'0.5a2))2(exp(a2) - (1 - 6)) and                (C-ll)


     V[X4] - (1 - 54)(exp(y4 + 0.5o-4))2(exp(a4) - (1 - S4)),                (C-12)


it follows that


     oj - log[[(l - 6t*)/4][(exp(a2)/(l - 5)) + 3]].                         (C-13)


     Modifying (C-6), the estimate of the 95th percentile of X4 is


     x-x    ( D                 ,  & > 0.95

     P95'ln      ,*     **\   i   „                                  '   (C
           / D + exp(p4 + z4<:4),  elsewhere


where                         "   •              '                       .
               1 -

The estimates of u4 and o4 are found by substituting u (the sample logmean of

the shifted concentrations), Aa2 (the sample logvariance of the shifted  concen-

trations), and S into expressions (C-10) and (C-13).

     Finally, the 95th percentile 4-day mean variability factor is
     VF(4) -   95   ,

             E[XD]


       •^^
where E[XD] is given in (C-2) and ?95 is given in (C-14)
                                        A-16

-------
    D.  COMBINATION OF SHIFTED LOGNORMAL AND DELTA-LOGNORMAL DISTRIBUTIONS

D.I  DAILY VARIABILITY FACTORS

     The methodology for estimating daily variability factors used in the
Development Document was also applied to the new data base.  The procedure
is the same as that of section C except that a combination of the lognormal
and the delta-lognormal distribution of shifted concentration values was
employed to derive the mathematical formulation of the 99th percentile and
the expectation of daily values; that is, the formulation is similar to that
for the delta-lognormal distribution of shifted concentration values (with
shift D), except that estimation of the expectation is based only on detected
values.
     The mean of XQ, where XQ has a lognormal distribution, is

     E[X0] = exp(y + 0.5o2) .                                            (D-l)

     The mean of XQ, where Xp is a lognormal distribution with origin D, is

     E(XD) = D + exp(u + 0.5o2) .        -                                (D-2)

     An estimate of E(X0) is computed by substituting p and a2, the sample
mean and logvariance, respectively, of ln(x - D),  into expression (D-2).
                                                /"•**
Substituting this estimate of E(XQ), denoted by E(XQ), into (C-7) yields the
99th percentile daily variability factor for this  methodology.  This vari-
ability factor is
      XX
where Pgg is the same quantity as used in (C-7).
                                    A-17

-------
D.2  ESTIMATION OF VARIABILITY FACTOR OF 4-DAY MEANS

     This procedure is the same as that of section C.2 except that a combina-
tion of the lognormal distribution and the delta-lognormal distribution of
shifted concentration values was employed to derive the mathematical formula-
tion of the 95th percentile and the expectation of the distribution of
4-day means.  The formulation is similar to that for the delta-lognormal
distribution of shifted concentration values, except that estimation of the
expectation is based only on detected values.  However, the formulation'of
the variance of a 4-day mean was adjusted for the random number of each set
of four values that may fall above the detection limit.  This adjustment was
based on binomial probabilities.

     A formula for the 4-day mean variability factor is found when the mean
of X4, assuming a lognormal distribution with origin D, is

     E["X4] = D -I- exp(u4 -I- 0.5o4) .                                         (D-3)

Since E[XQ] = E[X"4], by using (D-2) and (D-3), it follows that
                   2
U4 = v + 0.5(a2 - a4).                                                     (D-4)

Also, for this distribution,

     V(XD) = exp(2w + a2)(exp(a2) - 1)                                     (D-5)

                        2       2
and  V[X4] » exp(2u4 + a4)(exp(a4) - 1).                                   (D-6)
                                     A-18

-------
      With the presence of detected and nondetected observations, between zero

 and four values can be detected in any group of four observations.  In parti-

 cular,  assume M out of four values are greater than D (M = 1, 2, 3, 4).

 Then,


                          V[X4] = V[XD]/M,                                   (D-7)


 where M is a random variable with a binomial probability density function

 and parameter (1-6).  In other words,



      Pr[M = m] = (m) (1 - S)m 64~m, m = 0, 1 , 2, 3, 4, 0 < 6 < 1.           (13-8)



 Using (D-7) and (D-8) to calculate an expression for V(X4),



      V[X4] = f(5)V[XD]    .              .    -                  '.



            = f(6) exp(2u + a2) (exp(a2) - 1),                               (D-9)



                         4

 where f(6) = (1 - 54)"1 I Pr[M = m]/m, 0 < 5 < 1 , and
                        m=l


       f(6) = 1/4 for 6 * 0.


              2
 Solving for 
-------
A      A2                                2
U4 and 04 are these estimates of 114 and 04.  Finally, the 95th percentile
4-day mean variability factor, VF(4), is given as:
              ***,
              P95
     VF(4) =  ...                                                                (D-
             E[XD]
where §95 is shown in (D-ll), and E[XQ] is found by substituting estimates  of
U and a, the sample logmean and logvariance of the shifted concentrations,  into
(D-2).
     Using the methodology described in section A, daily and 4-day mean varia-
bility factors were calculated for plant-pollutant combinations  in the CMA/EPA
5-plant study and the recent 12-plant sampling study which have  at least  three .
single-day averages for which concentration values are recorded.  Average
daily and 4-day mean variability factors for each pollutant were calculated
by averaging plant-pollutant variability factors across all plants for each
pollutant for which variability factor information was present.   For  some
pollutants, variability information was limited.  For these pollutants,
variability factors were  extrapolated from the variability factors for groups
of pollutants with related chemical structure and thus comparable treatment
variability.  This extrapolation involved using the average variability factor
of all existing pollutant variability factors in the group.
                                     A-20

-------
                       LONG-TERM MEANS AND LIMITATIONS

     To calculate long-term means for each plant-pollutant  combination  in  the
CMA/EPA 5-plant study, the recent 12-plant sampling study,  and  the Verification
study, the Agency has calculated long-term means (m) as follows:
         A         A,
     m = 6D + (1 - 6)
where x^, i = 1, ..., n]_, denotes the n^ detected observations, D is  the
                                        A
po-llutant-specific detection limit, and 6 is an estimate of the proportion
of nondetects.  For those plant-pollutant combinations for which all  non-
detects are present, m » D, and for those combinations for which all  detects
are present, m is the arithmetic.average of these observations.  The  Agency
believes that the value of 6, derived from the proportion of nondetects
present in the daily data, is the best estimate of the percent of nondetect
values reported.  That is, <5, the best estimate of the proportion of  non-
detect values, is
                  total number of reported nondetect values
                          from all daily data plants
                  	for a particular pollutant	
                   total number of values reported from all
                  daily data plants for a particular pollutant
After calculating plant-pollutant long-term means in this fashion, the median
value of plant means for a given pollutant is determined, and this median  of
long-term means is multiplied by the average pollutant daily variability
factor to determine daily limitations for each pollutant.   The average 4-day
mean variability factor is multiplied by this median to determine 4-day mean
limitations for each pollutant.
                                    A-21

-------
                                REFERENCES


Aitchison, J., and J.A.C.  Brown.   1957.   The  Lognormal  Distribution.  London:
Cambridge University Press,  pp.  95-6.

Barakat, R.  1976.  Sums of  Independent  Lognormally Distributed Random Variables,
Journal Optical Society of America 66:211-16.

Cohen, A.C.  1961.  Tables for Maximum Likelihood Estimates  Singly Truncated and
Singly Censored Samples.  Technometrics  3:535-41.
                                  A-22

-------
                         APPENDIX B

DOCUMENTATION FOR TOXIC POLLUTANT AIR EMISSION RATE ESTIMATES
              FROM WASTEWATER TREATMENT SYSTEMS

-------
                                   TABLE Bl

                        ESTIMATES  OF AIR EMISSIONS  FROM
            WASTEWATER TREATMENT UNIT OPERATIONS (PERCENT STRIPPED)

KINCANNON
NON-BIO
VOLATILES AERATOR
4
6
7
10
11
14
15.
23
29
30
32
44
85
86
87
88
benzene 99
carbon tetrachloride
chlorobenzene
1,2-dichloroethane 96
1,1,1-trichloroethane 100
1,1, 2-trichlorethane
1,1,2, 2-tet rachloroethane
chloroform
1 , 1-dichloroethylene
1 , 2-trans-dichloroethylene
1,2-dichloropropane 99
methylene chloride 99
tetrachloroethylene
toluene
trichlorethylene
vinylchloride
& GAUDY
BIO
CLOSED
REACTOR
16


(97.5X99)
(99X100)

(100)'



89
7
95



IEC
(DRAFT)
BIO
15
59
5
35
62
25
27
34
43
72
32
54
27
20
41

HWANG
OPEN
BIO
100

100
100



79


99
12

100

75
STRIER
OPEN
BIO
85
80
80 .


40






50
85


See Table B3 for cites.
                                        B-l

-------
                                   TABLE B2
               CORRELATION OF PERCENT REMOVAL BY VOLATILIZATION
              AND HENRY'S LAW CONSTANT DURING SECONDARY TREATMENT
     Compound
Percent Removal
by Volatization
at Activated
Sludge Tank
      H
(ATM-ni/mole)
PCE, Tetrachlorethane
1,1, 2-Trichlorethane
Bromodichloromethane
Dibromochlorome thane
Dichloropropane
Methylene Chloride
Chloroform
Chlorobenzene
1 , 1 , 1-Trichloroe thane
Benzene
Toluene
Ethylbenzene
Trichloroethylene
Dichloroethene
Carbon Tetrachloride
82.5
75.7
98.4
86.3
95.7
94.8
94.7
92.2
96.6
96.5
93.7
86.3
93.9
98.1
98.5
0.38
0.74
2.12
2.12
2.8
3.19
3.93
3. '9 3
4.92
5.55
5.93
6.44
11.7
15
30.2
Source:  Petrasek et al. (1983).
From:  Versar, Inc. Memo, Dixon & Bremen to Reinhardt, October 11, 1984,
                                       B-2

-------
                                   TABLE B3
Selected Public Record Documentation

Reports

1.  Gaudy, A.F., Jr., Kincannon, D.F. and Manickam, T.C.  November  1982.
        Treatment Compatability of Municipal Waste and Biologically Hazardous
        Industrial Components.  Project Summary Rep. No. EPA-660/S2-82-075.
        Robert S. Kerr Environmental Laboratory.  Ada, Oklahoma.

2.  Industrial Economics, Inc. (lEc).  June 15, 1985.  Effects from Current
        Effluent Discharges From the Organic Chemicals, Plastics, and
        Synthetic Fibers Industry.  Prepared for U.S. Environmental Protection
        Agency, Office of Policy Analysis by lEc, Cambridge, Massachusetts.

3.  Hwang, S.T.  1980a.  Treatability and Pathways of Priority Pollutants in
        Biological Wastewater Treatment (Draft).  For Presentation in the
        AICHE Meeting, Chicago.  Organic Chemicals Branch., Effluent Guidelines
        Division, U.S. Environmental Protection Agency, Washington, D.C.

4.  Strier, M.P.  May 1985.  Treatability of Organic Priority Pollutants.
        Part F - Supplement I:  The Removal and Fate of Organic Priority
        Pollutants by Activated Sludge Treatment:  Estimated Percentage
        Removal Pathways.  Draft Report.  U.S. Environmental Protection
        Agency, Office of Analysis and Support, Washington, D.C.

5.  Petrasek, Albert C., Kugelman, Irwin, J., Austern, Barry M., Pressley,
        Thomas A., Winslow, Lawrence A., Wise, Robert H.  "Fate of Toxic
        Organic Compounds in Wastewater Treatment Plants."  Journal WPCF,
        Vol. 55, Number 10.  October 1983.

6.  Petresek, Albert., et. al.  "Removal and Partitioning of Volatile Organic
        Priority Pollutants in Wastewater Treatment."  Paper Presented at
        Ninth U.S.-Japan Conference on Sewage Treatment Technology, Tokyo,
        Japan.  September 13-29, 1983.


Correspondence

1.  October 11, 1984.  Gina Dixon and Bill Bremen, Versar Inc. to Forest
        Reinhart, Versar Inc.,  Memorandum Re:  Technical Background and
        Estimation Methods for Assessing Air Releases from Sewage Treatment
        Plants.

2.  December 10, 1984.  Gordon Lewandowski, New Jersey Institute of Technology
        to Murray P. Strier, EPA.  Letter Re Attachment:  Report Titles
        "Kinetics of Biodegradation of Toxic Organic Compounds."

3.  May 7, 1985.  Murray P. Strier, EPA to the Record.  Memorandum Re:
        Consequences of Telephone Conversation with Dr. Kincannon on Bench-
        Scale Activated Sludge Reactor Studies.
                                           B-3

-------
                                   TABLE B3
                                  (Concluded)
4.  May 17, 1985.  Murray P. Strier, EPA to The Record.  Memorandum Re:
        Response to Comments From Chemical Manufacturers Association on
        Proposed Effluent Limitations for OCPSF.

5.  May 24, 1985.  Murray P. Strier, EPA to The Record.  Memorandum Re:
        Evidence That Air Stripping Rates of Toluence Exceeds its Biological
        Oxidation Rates in Aeration Basins.
                                        B-4

-------
V.  TECHNOLOGY BASIS AND DERIVATION OF PSES EFFLUENT LIMITATIONS

-------
V.  TECHNOLOGY BASIS AND DERIVATION OF PSES EFFLUENT LIMITATIONS


                               TABLE OF CONTENTS

                                                                     Page

1.  INTRODUCTION	     1

2.  CONCENTRATION VERSUS MASS-BASED LIMITATIONS AND PSES
    SUBCATEGORIZATION	     1

3.  TECHNOLOGY OPTIONS	     2

4.  PSES PASS-THROUGH ANALYSIS	     2

5.  CORRECTION TO PSES COST ESTIMATES AND ECONOMIC IMPACT	     3



APPENDIX A:  SELECTED SUMMARY SHEETS FROM THE EPA TREATABILITY MANUAL

-------
V.  TECHNOLOGY BASIS AND DERIVATION OF PSES EFFLUENT LIMITATIONS


                                LIST OF TABLES

Table                                                                Page
1.  RESULTS OF PASS-THROUGH ANALYSIS COMPARISON OF BAT AND POTW
    PERCENT REMOVALS                                                    4

2.  PSES OPTION I LIMITATIONS FOR POLLUTANTS SELECTED BASED ON
    5 PERCENT PASS-THROUGH CRITERIA AND THE USE OF BAT OPTION II
    LIMITATIONS                                                        10

3.  POLLUTANTS CONTROLLED BY PSES OPTION II ON THE BASIS OF POTW
    INTERFERENCE                                                       13

4,  TOXIC POLLUTANTS WITHOUT OCPSF PHYSICAL/CHEMICAL TECHNOLOGY
    PERFORMANCE DATA OR OCPSF PHYSICAL/CHEMICAL CONTROL HIGHER
    THAN BAT                                                           15

5.  TECHNOLOGIES COSTED FOR PSES 30 PLANT INDIRECT DISCHARGER COST
    CORRECTIONS                                               .16

6.  COSTS. FOR PSES 30 PLANT INDIRECT DISCHARGER COST CORRECTIONS       17

7.  PRIORITY POLLUTANTS GROUPED ACCORDING TO IN-PLANT TREATMENT
    CARBON USAGE RATES WITH AVERAGE CARBON ADSORPTION EFFLUENT VALUES  19

8.  PSES OPTION III LIMITATIONS THAT WOULD APPLY TO POLLUTANTS
    WITH HIGHER PHYSICAL/CHEMICAL EFFLUENTS THAN BAT                   21

-------
       V.  TECHNOLOGY BASIS AND DERIVATION OF PSES EFFLUENT LIMITATIONS

1.  INTRODUCTION
     As discussed in the previous sections for the BAT effluent limitations,
the selection of a particular set of PSES treatment technologies is also
plant-specific for indirect dischargers in the OCPSF industry.  As with the
direct dischargers subject to BAT effluent limitations, treatment technologies
applicable to indirect dischargers subject to PSES can consist of in-plant
control or treatment of specific (or combined) wastestreams by a number of
physical/chemical methods sometimes in combination with biological treatment
of combined wastestreams where effluent levels from in-plant control  tech-
nologies still pass through, interfere with or inhibit publicly-owned treat-
ment works.  In-plant control and biological treatment technologies utilized
by indirect dischargers are the same as those employed by direct dischargers
as discussed in the previous sections.

     Prior to proposal, sufficient priority pollutant removal data for
in-plant control technologies which could be utilized to calculate PSES
limitations for indirect discharges were not available since previous sampling
efforts focused on complete end-of-pipe treatment systems rather than on
individual technology components.  A new sampling program was initiated after
proposal at 12 OCPSF facilities to collect toxic pollutant removal data for
selected in-plant control technologies as well as end-of-pipe technologies
which could be applied to indirect discharges.  Data are available for certain
in-plant controls as well as applicable end-of-pipe technologies for EPA to
establish PSES limitations for certain toxic pollutants which pass through the
POTW or interfere with the POTW operation.

2.  CONCENTRATION VERSUS MASS-BASED LIMITATIONS AND PSES SUBCATEGORIZATION
     As in the case of the BAT effluent limitations, both concentration-based
and mass-based PSES effluent limitations were considered and for the same
reasons mentioned previously, concentration-based PSES effluent-liattatlons
were established.
                                     -1-

-------
     Similarly, subcategorization of the industry for PSES purposes was
considered and, for the same reasons described for BAT, one set of PSES
limitations which are applicable to all plants was established.

3.  TECHNOLOGY OPTIONS
     As in the proposed regulations, it was decided that limitations would be
equal to BAT effluent limitations and would differ only in the set of toxic
pollutants regulated.  Therefore, PSES limitations can span the entire range
of BAT Options I through III.

     Two major PSES options are being considered for selection of pollutants
to be regulated:

     •  PSES Option I—Establish PSES limitations for pollutants failing EPA's
        standard pass-through analysis
     •  PSES"Option II—Add to Option I a set of volatile and semi-volatile
        organic toxic pollutants based on POTW interference'as well as pass-
        through.

A.  PSES PASS-THROUGH ANALYSIS
     The general methodology for performing a pass-through analysis for
pretreatment standard setting purposes is to compare, on a pollutant-by-
pollutant basis, the percentage of a pollutant removed by well-operated POTWs
(those meeting secondary treatment requirements) with the percentage removed
by direct dischargers complying with BAT.  If BAT removes more than POTWs,the
pollutant is deemed to pass through POTWs and a PSES limitation is established
for the pollutant.

     At proposal, this was modified for assessing pass through.  Cognizant of
the analytical variability typical of organic toxic pollutants in POTWs and
OCPSF plants, pass-through was determined to occur only if BAT removes at
least 5 percent more than a well-operated POTW removes.  This approach is
additionally supported by the fact that POTW influent organic toxic pollutant
concentrations are typically much lower than industry treatment system
influent concentrations; many POTW effluent samples are below detection,
                                     -2-

-------
precluding a complete accounting of all pollutants removed by the POTW.  This
approach has been retained for the Notice of Availability.  Table 1 lists  all
pollutants which had BAT percent removals along with their associated POTW and
BAT percent removals.

     Table 2 presents the PSES Option I limitations for the pollutants which
pass through based on the 5 percent criteria that would apply if BAT Option II
were adopted.  However, it should be noted that if a different BAT option  were
selected, PSES limitations would be revised accordingly.

     Under PSES Option II, EPA would additionally regulate the volatile and
semivolatile organic toxic pollutants listed in Table 3.  (This table also
lists the PSES limitations that would apply if BAT Option II were adopted).
These polluants interfere with the normal operation of POTWs by presenting
safety hazards due to volatilization of toxic organics in POTW's headworks.
While the severity of such hazards may depend on a variety of factors, -the
potential for harm is considerable.  For example, one state that has a large
number of OCPSF plants submitted comments on the proposal that attributed  POTW
employee deaths to the volatilization in POTW sewers of organic pollutants
discharged by industrial contributors.  In addition, these pollutants are
believed to pass through POTWs.  As discussed in the BAT section, these
polluants volatilize to the atmosphere from biological treatment systems.
Since POTWs are biological systems, large proportions of volatile and semi-
volatile pollutants are removed from wastewaters entering POTWs by air
stripping rather than treatment.  Thus, the standard pass-through analysis
comparing POTW and BAT removals is inappropriate for these pollutants.
Therefore, for the same reason that in-plant BAT effluent limitations are
being considered, control of these pollutants under PSES Option II is being
considered to ensure that pollutants not adequately treated by biological
treatment are properly pretreated.  Thus PSES Option II is supported by
considerations of pass-through as well as interference.

5.  CORRECTION TO PSES COST ESTIMATES AND ECONOMIC IMPACTS
     In the initial cost estimation activities for PSES for the notice, PSES
costs were based on the installation of only in-plant control technologies
                                     -3-

-------
                             TABLE 1

         RESULTS  OF  PASS-THROUGH ANALYSIS  COMPARISON OF
                  BAT AND POTW PERCENT REMOVALS
POLLUTANT
NUMBER
1
2
3
4
5
. 6
7
8
9
10
11
12
13
14
15
16
17
BAT
% REMOVAL
98.9
—
99.8
99.3
—
96.5
. 95.8
86.4
97.1
98.6
93.5
97.1
—
59.7
—
95.2
—
POTW
% REMOVAL + DIFFERENCE REMARKS
95.0 +3.9
— — Not regulated
for BAT
— — PSES required
97.6 +1.7 —
— — Not regulated
for BAT
91.4 +5.1 PSES required
98.4 -2.6 —
»
93.0 -6.6 —
— — PSES required
87.8 +10.8 PSES required
90.9 +2.6 —
— — PSES required
— — Not regulated
for BAT
88.9 -29.2 --
— — Not regulated
for BAT
— — PSES required
— — No longer a
18
priority pollutant

Not regulated
for BAT
                                 -4-

-------
                                TABLE 1

             RESULTS OF PASS-THROUGH ANALYSIS COMPARISON OF
                      BAT AND POTW PERCENT REMOVALS
                               (Continued)
POLLUTANT
 NUMBER
   BAT
% REMOVAL
  POTW
% REMOVAL
+ DIFFERENCE
REMARKS
    19
    20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
57.3
—
94.8
97.7
91.1
91.0
92.2
86.4
89.0
81.5
98.7
97.5
92.9
98.9
88.1
64.7
_—
—
—
82.7
—
93.1
100.0
83.3
—
84.4
94.9
60.7
94.3
99.0
53.3
—
—
_
— —
—
+ 12.1
—
-2.0
-9.0
+8.9
—
+4.6
-13.4
+38.0
+3.2
-6.1
+45.6
—
—
__
                                          Not regulated
                                          for BAT

                                          Not regulated
                                          for BAT

                                          PSES required

                                          Not regulated
                                          for BAT

                                          PSES required

                                          PSES required
                                                        PSES required

                                                        PSES required
                                                        PSES  required
                                                        PSES required

                                                        PSES required

                                                        PSES required

                                                        Not regulated
                                                        for BAT
                                      -5-

-------
                            TABLE  1

         RESULTS  OF  PASS-THROUGH ANALYSIS  COMPARISON OF
                  BAT AND  POTW PERCENT REMOVALS
                           (Continued)
POLLUTANT BAT
NUMBER % REMOVAL
38 98.4
39 97.7
40
41
42 76.2
43 — '
44 85.3
45 60.4
46
47 60.5
48 86.5
49
50
51
52 96,3
53 —
POTW
% REMOVAL _+ DIFFERENCE
REMARKS
95.0 +3.4 —
73.0 +24.7 PSES required
Not regulated
for BAT
— Not regulated
for BAT
— — PSES required
— — Not regulated
for BAT
70.9 +14.4 PSES required.
89.6 -29.2 --
— — Not regulated
for BAT
90.5 -30.0
71.4 +15.1 PSES required
— — No longer a
priority pollutant
— — No longer a
priority pollutant
— — Not regulated
for BAT
— — PSES required
— — Not regulated
                                                    for BAT
54
Not regulated
for BAT
                                 -6-

-------
                   TABLE 1

RESULTS OF PASS-THROUGH ANALYSIS COMPARISON OF
         BAT AND POTW PERCENT REMOVALS
                  (Continued)
POLLUTANT
NUMBER
55
56
57
58
59
60
'61
62
63
64
65
66
67
68
69
70
71
72
BAT
% REMOVAL
98.8
96.8
95.3
85.0
83.8
99. a
—
—
—
59.2
98.6
93.5
—
97.4
—
94.2
92.0
96.8
POTW
% REMOVAL +_ DIFFERENCE REMARKS
89.7 +9 -I PSES required
— — PSES required
— — PSES required
PSES required
— — PSES required
PSES required
— — Not regulated
for BAT
— — Not regulated
for BAT
— — Not regulated
for BAT
45.0 +14.2 PSES required
97,8 +0.8 —
76.2 +17.3 PSES required
— — Not regulated
for BAT
89.9 +7.5 PSES required
— — Not regulated
for BAT
88.7 +5.5 PSES required
55.9 +36.1 PSES required
— — PSES required
                        -7-

-------
                   TABLE 1

RESULTS OF PASS-THROUGH ANALYSIS COMPARISON OF
         BAT AND POTW PERCENT REMOVALS
                  (Continued)
POLLUTANT
NUMBER
73
74
75
76
77
. 78
79
80
81
82
83
84
85
86
87
88
89 - 113
114
115
BAT
% REMOVAL
95.4
96.0
—
99.3
97.9
97.8
—
94.0
99.6
—
—
96.4
98.4
99.6
92.9
99.8
—
52.6
82.4
POTW
% REMOVAL _+ DIFFERENCE REMARKS
— PSES required
— — PSES required
— — Not regulated
for BAT
— PSES required
PSES required
90.4 +7.4 PSES required
— — Not regulated
for BAT
— — PSES required
— — PSES required
— — Not regulated
for BAT
— — Not regulated
for BAT
80.0 +16.4 PSES required
89.8 +8.6 PSES required
96.5 +3.1 -- —
95.0 -2.1 —
89.0 +10.8 PSES required
— — Not regulated
for BAT
66.2 -13.6 —
38.9 +43.5 PSES required
                       -8-

-------
                                TABLE 1

             RESULTS OF PASS-THROUGH ANALYSIS COMPARISON OF
                      BAT AND POTW PERCENT REMOVALS
                               (Concluded)
POLLUTANT
 NUMBER
   BAT
% REMOVAL
  POTW
% REMOVAL
+ DIFFERENCE
REMARKS
   116
   117
   118
119
120
121
122
123
124
125
126
127
128
129
79.5
. 83.2
79.9
69.9
92.1
35.1
94.0
—
—
84.8
mtmm
77.8
85.0
68.6
58.6
60.0
45.5
—
—
—
76.0
_!_
+1.7
-1.8
+11.3
+11.3
+32,1
-10,4
—
—
—
+8.8
_.
                                          Not regulated
                                          for BAT

                                          Not regulated
                                          for BAT

                                          Not regulated
                                          for BAT
                                                        PSES required

                                                        PSES required

                                                        PSES required



                                                        PSES required

                                                        Not regulated
                                                        for BAT  ,_

                                                        Not regulated
                                                        for BAT

                                                        PSES required

                                                        Not regulated
                                                        for BAT
                                  -9-

-------
                                    TABLE 2

                   PSES OPTION I LIMITATIONS FOR POLLUTANTS
                 SELECTED BASED ON THE 5 PERCENT PASS-THROUGH
               CRITERIA AND THE USE OF BAT OPTION II LIMITATIONS
                                       Four Day
Pollutant or Pollutant Property        Monthly             Daily
by Priority Pollutant Classes          Average             Maximum
                                       (ppb)               (ppb)
Halogenated Methanes (Cl's)

 6.  Carbon tetrachloride                 15                    30
23.  Chloroform                           20                    40
44.  Methylene chloride                   15                    20
48.  Bromodichloromethane                 t5                    30

Chlorinated C2's                   ...

10.  1,2-Dichloroethane                   35                    95
12.  Hexachloroethane                     25                    65
16.  Chloroethane               .         115                   315
85.  Tetrachloroethylene                  25                    65
88.  Vinyl chloride                       25                    65

Chlorinated C4's

52.  Hexachlorobutadiene                  20                    45

Chloroalkyl Ethers

42.  bis(2-chloroisopropyl)ether          20                    45

Metals

115.  Arsenic                             50                   115
122.  Lead                               265                   785
123.  Mercury                              2.5                   3.0
125.  Selenium                            20                    40
128.  Zinc                               105                   190
                                        -10-

-------
                                    TABLE 2

                   PSES OPTION I LIMITATIONS FOR POLLUTANTS
                 SELECTED BASED ON THE 5 PERCENT PASS-THROUGH
               CRITERIA AND THE USE OF BAT OPTION II LIMITATIONS
                                  (Continued)
                                       Four Day
Pollutant or Pollutant Property        Monthly             Daily
by Priority Pollutant Classes          Average             Maximum
                                       (ppb) -              (ppb)
Miscellaneous

  3.  Acrylonitrile                      100                   250
121.  Cyanide                            120                   275

Polyaromatics

39.  Fluoranthene                        45                   140
55.  Naphthalene                         35   .                105
72.  Benzo(a)anthracene                  35                   105
73.  -Benzo(a)                           . 35-                   105
74.  3,4-Benzofluoranthene               35                   105
76.  Chrysene                            35                   105
77.  Acenaphthylene                      35                   105
78.  Anthrcene                           35                   105
80.  Fluorene                            35                   105
81.  Phenanthrene                        35                   105
84.  Pyrene                              40                   135

Chloroaromatics
 9.  Hexachlorobenzene                   20                    40
27.  p-Dichlorobenzene                   20                    40

Phthalate Esters

66.  bis(2-Ethylhexyl)phthalate          45                   130
68.  Di-n-butyl phthalate                40                    80
70.  Diethyl phthalate                   90                   215
71.  Dimethyl phthalate                  20                    50

Nitroaromatics

35.  2,4-Dinitrotoluene                 310                   54CT"
36.  2,6-Dinitrotoluene                 340                   555
56.  Nitrobenzene                       285                   480
                                         -11-

-------
                                     TABLE 2

                    PSES  OPTION  I  LIMITATIONS FOR POLLUTANTS
                  SELECTED  BASED ON THE 5  PERCENT PASS-THROUGH
                CRITERIA  AND  THE USE OF BAT OPTION II LIMITATIONS
                                   (Concluded)
                                        Four Day
 Pollutant or  Pollutant  Property         Monthly             Daily
 by  Priority Pollutant Classes           Average             Maximum
                                        (ppb)               (ppb)
 Benzidines

 28.   3,3'-Dichlorobenzidine             320                  450

 Phenols

 34.   2,4-Dimethylphenol                   20                   35

.Nitrophenols .            .                         •  .

 57.   2-Nitrophenol               .         35                   55
 58.   4-Nitrophenol                        70                  120
 59.   2,4-dinitrophenol                    75                  130
 60.   4,6-Dinitro-o-cresol                 30                   50

 Chlorophenols

 21.   2,4,6-Trichlorophenol              115                  260
 24.   2-chlorophenol                       35                  125
 31.   2,4-Dichlorophenol                   45                  130
 64.   Pentachlorophenol                    65                  100
                                         -12-

-------
                                    TABLE 3   -

                    POLLUTANTS CONTROLLED BY  PSES OPTION  II
                       ON THE BASIS OF POTW INTERFERENCE
Pollutant or Pollutant Property
by Priority Pollutant Classes
Four Day
Monthly
Average
(ppb)
Daily
Maximum
(ppb)
Halogenated Methanes (Cl's)

 6.  Carbon tetrachloride
23.  Chloroform
44.  Methylene chloride

Chlorinated C2's
10.  1,2-Dichloroethane
11.  1,1,1-Trichloroethane
14.  1,1,2-Trichloroethatie
29.  1,1-Dichloroethylene
30.  1,2-trans-Dichloroethylene
85.  Tetrachloroethylene
87.  Trichloroethylene
88.  Vinyl chloride

Chlorinated C3's

32.•  1,2-Dichloropropane

Aromatics

 4.  Benzene
86.  Toluene

Chloroaromatics

 7.  Chlorobenzene
 9.  Hexachlorobenzene
25.  o-Dichlorobenzene
26.  m-Dichlorobenzene
27.  p-Dichlorobenzene
  15
  20
  15
  35
  25
  25
  25
  25
  25
  25
  25
 110
  30
  35
  40
  20
  80
  25
  20
   30
   40
   20
   95
   65
   65
   65
   65
   65
   65
   65
  265
   85
  115
  115
   40
  145
   35
   40
                                      -13-

-------
such as steam stripping, activated carbon, and chemical precipitation.   This
was done based on the receipt of preliminary sampling data which indicated
that pollutant removals for in-plant controls approximated pollutant  removals
obtained by BAT treatment systems.  However, upon receipt of  the entire  toxic
pollutant data base, it became apparent that for 13 of the 58 PSES  Option II
priority pollutants, demonstrated physical/chemical effluent  concentrations
were essentially higher than BAT treatment effluent concentrations.   Table 4
lists the 13 pollutants and their respective BAT and PSES effluent  concen-
trations.  Because of this incorrect assumption, additional treatment would be
required (and costed) to achieve BAT level PSES for these 13  pollutants.

     In an attempt to estimate the actual costs which will be incurred  for
compliance with the PSES effluent limitations and the associated economic
impacts, a random sample of 30 indirect dischargers was selected and  each
plant's estimated raw waste toxic pollutant loading was examined to determine
the pollutants which would require additional treatment because the. plant's
effluent levels were greatet than the PSES Option II effluent limitations.
Since PSES Option II regulates more pollutants than PSES Option I,  the  use of
PSES Option II provides the most conservative approach which  would  yield the
highest potential costs and impacts.  The costing scenario included in-plant
treatment costs as well as costs for certain additional treatment technologies
for the 13 pollutants—eight organic toxic pollutants, four toxic pollutant
heavy metals and cyanide.  Table 5 lists the treatment technologies which were
costed to estimate the increase in costs due to these 13 pollutants.  For 5 of
the 30 plants, biological treatment (activated sludge) was costed in  addition
to the appropriate in-plant controls because at least one of  the eight  organic
toxic pollutants or. cyanide appeared in the plant's effluent  at greater than
BAT effluent levels.  Multimedia filtration was costed in addition  to chemical
precipitation for 19 plants because at least one of the four  toxic  pollutant
heavy metals appeared above the BAT effluent levels.  Table 6 presents  the
costs generated which were used to estimate the increase due  to these 13
pollutants.  The average cost  increases in adding the technolgies for the 13
pollutants across the 30 plant sample are 226 percent for land costs, 56
percent for capital equipment, and 11 percent for operation and maintenance
costs.  Sludge costs were not  projected to increase.  These increases were
                                      -14-

-------
                                 TABLE 4
       TOXIC POLLUTANTS WITHOUT OCPSF PHYSICAL/CHEMICAL TECHNOLOGY
   PERFORMANCE DATA OR OCPSF PHYSICAL/CHEMICAL CONTROL HIGHER THAN BAT
                                 BAT LONG-TERM          PSES LONG-TERM
      POLLUTANTS                 MEDIAN (PPB)            MEDIAN (PPB)
 24.   2-Chlorophenol                  10.0                     175
 34.   2,4-Dimethyphenol               10.6                     175
 59.   2,4-Dinitrophenol               50.0                     175
 72.   Benzo(a)anthracene              10.0                   1,418
 73.   Benzo(a)pyrene                  10.0                     175
 74.   3,4-Benzofluoranthene           10.0                     175
 76.   Chrysene                        10.0                   1,418
 84.   Pyrene                          12.6                   1,418
121.   Cyanide                         64.9
122.   Lead                  -         100.0    '     .             —
123.   Mercury                          1.03  •                   —
125.   Selenium                        12                        —
128.   Zinc                            69.5                     107
                                    -15-

-------
                                   TABLE  5
                    TECHNOLOGIES COSTED FOR  PSES  30 PLANT
                    INDIRECT DISCHARGER COST CORRECTIONS
    PLANT
ORIGINAL PHYSICAL/CHEMICAL
TREATMENT COSTED FOR PSES
        OPTION II
REVISED TREATMENT SYSTEM
COSTED FOR PSES OPTION II
NOTE:
71
423
749
797
830
845
862
997
1126
1181
1188
1219
1237
1322
1426
1528
1534
1621
1773
1861
2070
2129
2300
2346
2411
2609
2635
2679
2714
2776
: SS
CP
AC
F
BIO
SS,
CP
SS,
CP,
SS
CP
SS,
SS
SS,
SS,
NO
SS,
SS,
SS,
SS,
SS
SS,
CP
SS,
CP
SS,
SS,
SS,
CP
CP
CP
SS,
CP
CP
SS,
CP, AC

AC, CP
SS, AC


CP

AC, CP
AC, CP
COSTS
AC, CP
AC
AC
AC, CP

CP

CP

AC, CP
AC, CP
CP



AC


AC, CP
SS,
CP,
SS,
CP,
SS
CP,
SS,
SS
SS,
SS,
NO
SS,
SS,
SS,
SS,
SS
SS,
CP,
SS,
CP,
SS,
SS,
SS,
CP,
CP,
CP,
SS,
CP
CP
SS,
CP, AC, F
F
AC, CP, F
SS, AC, BIO

F
CP, F

AC, CP, + BIO
AC.-CP, F
COSTS
AC, CP, F
AC
AC
AC, CP, + (BIO)

CP, F
F
CP, F
F
AC, CP, F
AC, CP, + BIO
CP, F
F
F
F
AC
+ F
+ F _---•---
AC, CP, + BIO
- STEAM STRIPPING
- CHEMICAL PRECIPITATION
- ACTIVATED CARBON
- MULTIMEDIA FILTRATION
- ACTIVATED SLUDGE
                                     -16-

-------
              at at
              M V>
              Z s^
              O
              5
     So
     oo
eM   o
O
oo
o
                                     O
                                     -»
                                                     O   O
                                                     00   -»
                                                     o   eM
                                    o   o   o
                                    00   CO   00
                                    O   O   O
                         o
                         -»
                         eN
                              s  §
                              (M  O
o   o
•V   00
eM   O
o   o
CD   -a1
O   eM
                     o
                     OO
                     O
ooo
000000
ooo
oo
0000
oo
                                                             oo
                                                             0000
                                                             oo
              u v."

              Q en
                 Se-
                 en
              en o
                 u
              z en

              22
                 U]
                 NO   O   O   O
                 in   in   CM   00
                    o   CM
-   O   en
NO   r*.   O
                                                                 O      in
                                                                                      in   eM   en
                                                                                      --   eM
                                                  o
                                                  m
                                              I    m
                                              I      *
                                                  o
                                                                      o
                                                                      •a-
                                                                      o
Ed
at
at
en
B
X
U
en
en
H
e/5

8

a
&i
en
hi
as
                           O   OO   ON    O
                           •*   r»   -»    m
                           •»       •»
                                —   —   in
                                               "^   Px   00
                    O   p1*   o   NO   *a*   en
                         —   P»   co   oo   m
                         ON   in   NO   NO   NO
                                                                                                            —   vO
                                                                                                            to   m
                                                                                                                           in   P^   o   •**
                                                                                                                                m   en   r~
                                                                                                                              NO
                                                                                                                              o>
                                                                                                                              in
                                                          m
                                                          O
                                                          -T
                                                                  en   oo

                                                                  §   E
                                             •*   en   oo
                                             -«   m   CM
                                             —.   co   cr>
                                                                                                                                     •a-
                                                                                                                                     -»
                         eM   —   oo   eM   oo   ON

                         O   NO   eM   eN   en   oo
                                                                                                               00   ~T
                                                                                                               —   «M
                                                                                                               00   -C
                           -a-   m
                           a   2
O   O   -»    —   -T   —
m   oo   oo    o   en   en
i"»   O   eM    o   r»   f.
          o
          —
          CM
                                                          oo   \a
                                                             o  o   •*
                                     O   -»  oo   •»
                                     «   eN
                         -0   O
                         oo   «n
                                                                                      >e   en   o
                                                                                      o   —   —
                                                                                      •a   oo   •»
                                                                      Pv   CM   P*»   P"»   O   ^*   M3   00
                                                                      minoooooo   —   p-
en
Ed
CO
Ou

Qd
O
8
^

N^«
§
5
en -^
H a:
en >•
8 ~

•J
< r
s s
*-»
a;
0

^f

•j
<
H
t~t
Cu
<
U
rNi eM
IN NO
-* ejN
QN NO


•* -»
ON NO
en oo
O> p^
NO in
^Nl



00 O
ON -»
00 CM
NO -T
en o
in *a*



00 0
O m
NO 0
2 2


eM -T
00 NO
m NO
§_ 4
Q
CM -4



p>. en
in eM
00 P-
S NO
in en



-»• -»
in en
pv oo
oo


^* \o
O 00

en NO
.*




-» 00
en o
P* ON
oo co
O —
PS ^



^ r* co r*
* * • *
•» oo oo NO
-• p>. en


in ^ NO NO o
— • co ON en
m oo eM ON
en ^ -* o
en en ON •*
— • ON -"



O — en en O
-• NO — P»
CM 00 00 00
•3* — ON NO
— * «a- -a* oo
-a1 CM ON -a1

en

— « p^
. .
CM P^
ON ON


-» O
NO —
CO CM
en en
oo -a-
m



CM —
00 00
CM ON
in o
— ' ON
PN* CM
.
CM

oo oo m
• . m
CM ON


m O r^
O m ON
O CM CM
— •» m
CM en
^



en en NO
 NO CM


NO ON en
o in CM
r- en m
m m oo
co en — «




— p» CM
NO NO ON
— ON ON
O oo en
P» CM CM



S 00
0< CM
09


o •«•
NO CM
ON O
O -a-
CM 00
m



NO -
— r*N«
00 ON
00 P^
-» o
-• NO
.
CM

m P^ NO
in ON P^


ON "3" ^
-» oo en
o oo in
NO *T CM
CO — O
en in — •
CM


NO •» en
CM NO OO
-a* en p*.
P* OO ON
NO m p»

•*

3 S 3
en -* ON
— NO


m p» CJN
en CM —
en ON en
oo oo en
NO — CM
K4
-


— -» NO
en o r^
— NO CM
f*» en o
-^ ^ p^

en

S 5 S
00 00


O O NO

ON O CJN
en CM m
-» •»
-a1



-a* NO in
CM oo m
in oo — «
CO -T CO
en Pv



                                                                                                                                                                                       •o

                                                                                                                                                                                        to
                                                                                                                                                                                        60
                                                                                                                                                                                        c


CM m
en p»
O en



O
-»
O



0
o

-»
p*
§
o


,•*
p*.
en
0



O
0


m
en
O



o
in



m
CM
O



in
NO
O



en
in
en

CM
O
O
0

ta-
in P»
CM en
NO O
— o

«*
CM
o
o



o
o



o
m
—



•T
o
o


p*.
m
o



0
NO
CM



ON
-a1
o



NO
en
ON
CM




if*


-.
m


ON
NO in
^a* en
0 ON



in
CM

en
p*
§
o


_M
oo
in
O

       J
       a.
                                en
                                fM
                                -I
                                          m
                                          -a-
                                          oo
                               CM   P~
                               NO   ON
                               oa   ON
               •<•   OO   ON   r^
               oo   oo   —•   
-------
applied for all plants.  The projected economic impacts are presented in  the
appropriate supporting documents.

     For the organic toxic pollutants and cyanide, biological treatment plus
in-plant controls forms the principal technology basis for BAT Option II  and
therefore, should accurately reflect the costs necessary to attain PSES.  The
addition of multimedia filtration after chemical precipitation is a proven
method of reducing heavy metals concentrations in the metal finishing,
inorganic chemicals and other industries which generate heavy metals in their
raw wastewaters.  Data from the metal finishing industry show incremental
percent removals with the addition of filtration of 44 percent for total
chromium, 55 percent- for total copper, 32 percent for total lead, 42 percent
for total nickel and 55 percent for total zinc.  Therefore, the costing of
filtration is felt to be an adequate cost estimation technology which can
lower the in-plant control effluent values for chemical precipitation to
within an acceptable range of the BAT effluent levels.

     For all other pollutants, as noted, the costing procedures assumed that
in-plant treatment would be sufficient to achieve compliance with the PSES
limitations.  The treatment capability of steam stripping has already been
discussed with respect to BAT.  For the activated carbon assessment, the
organic priority pollutants were divided into three groups (high, medium, and
low) based on their in-plant carbon usage rates—pounds of pollutant adsorbed
per pound of carbon.  Table 7 presents the pollutants that are contained  in
each of these groups and the average carbon adsorption effluent values for the
pollutants with data are noted.  By assuming that compounds in each group
behave similarly, group median effluent vaues were calculated for costing
purposes—a median of nondetect represents both the high and medium adsorption
groups since data was available for the medium group only and a median of 175
ppb represents the low adsorption group.

     For the 52 organic toxic pollutants regulated at PSES Option II, the
steam stripping and activated carbon assessment demonstrates that these
controls can achieve the same or lower long-term concentrations for 33
organics, essentially the same concentrations (within 2 ppb) for  11 others
                                      -18-

-------
                                    TABLE 7

       PRIORITY POLLUTANTS GROUPED ACCORDING TO IN-PLANT TREATMENT CARBON
        USAGE RATES WITH AVERAGE CARBON ADSORPTION EFFLUENT VALUES (PPB)
    High
(11.3 to 0.2)
                      Medium
                 (0.19 to 0.091)
                                  Low
                           (0.090 to 0.00059)
Bis (2-EthyIhexyl)
  Phthalate
Butyl Benzyl Phthalate
Fluoranthene
Hexachlorobenzene
Anthracene
Fluorene
3,3-Dichlorobenzidine
2-Chloronaphthalene
Hexachlorobutadiene
Benzidine Dihydrochloride
N-Butyl Phthalate
N-Nitrosodiphenylamine
Phenanthrene
Group
Median
Assumed Not
  Detect Based on
  Median of Medium
  Group
Acenapthene
  4,4' Methylene-Bis
  (2-Choroaniline)
Benzo (k) Fluoranthene
4,6-Dinitro-0-Cresol~ND
2,4-Dichlorophenol
1,2,4-Trichlorobenzene
2,4,6-Trichlorophenol
Pentachlorophenol
2,4-Dinit rotoluene-ND
2,6-Dini trotoluene-ND
4-Bromophenyl Phenyl Ether
Naphthalene
1,2-Dichloroberizene
1,4-Dichlorobenzene
1,3-Dichlorobenzene
Acenaphthylene
Diethyl Phthalate
4-Chiorophenyl Phenyl
  Ether
2-Nitrophenol-ND
Dimethyl Phthalate
Hexachloroethane
Chlorobenzene
                          Group
                          Median
                          Not Detect
2,4-Dimethylphenpol
4-Nitrophenol-50
Dibenzo (a,h) Anthracene
Nitrobenzene-175
3,4-Benzo Fluoranthene
Ethylbenzene
2-Chlorophenol
Tetrachloroethene
Benzo (a) Pyrene
2,4-Dinitrophenol-611
Isophorone
Trichloroethene
Toluene •
N-Nitrosodi-N-Propylamine
Bis (2-Chloroisopropyl)
  Ether
Phenol
Benzo (a) Anthracene
Bromoform
Carbon Tetrachloride
Bis (2-Chloroethoxy)
  Methane
Benzo (ghi) Perylene
1,1,2,2-Tetrachloroethane
Dichlorobromomethane
1,2-Dichloroprop'ahe
1,1,2-Trichloroethane
1,1-Dichloroethylene
2-Chloroethyl Vinyl Ether
1,2-Dichloroethane
1,2-Trans-Dichloroethene
Chloroform
1,1,1-Trichloroethane
1,1-Dichloroethane
Acrylonitrile
Methylene Chloride
Acrolein
Benzene
Chloroethane
Carton usage rate units are
Ibs of pollutant adsorbed per
Ib  of carbon
                                            Group
                                            Median
                                    175 ppb
                                        -19-

-------
(benzene, carbon tetrachloride, 1,1,1-trichloroethane, chloroform,  1,1-
dichloroethylene, 1-2-trans-dichloroethylene, dichlorobromomethane, tetra-
chloroethylene, toluene, trichloroethylene, and vinyl chloride) and higher
concentrations (ranging from 125 to 1,418 pbb) for the remaining 8 organics
(2,4-dimethylphenol, 2-chlorophenol, 2,4-dinitrophenol, and 5 polyaromatics—
benzo(a)anthracene, benzo(a)pyrene, 3,4-benzofluoranthene, chrysene, and
pyrene).  In the case of the polyaromatics, biological treatment may provide
more cost-effective control than steam stripping or activated carbon (depend-
ing on the specific compound or combination of compounds in the wastewater)—
at least one indirect discharge facility for which toxic pollutant data exist,
has installed biological treatment to achieve long-term effluent concentra-
tions at or near the analytical method detection levels.

     For cyanide and the 5 toxic pollutant metals regulated at PSES Option II,
OCPSF physical/chemical performance data is available only for arsenic and
zinc.  Data for chemical precipitation demonstrates that physical/chemical
treatment alone can achieve lower concentrations for arsenic than BAT control;
however, for zinc, chemical precipitation performance is 38 ppb higher than
the BAT long-term average.

     A third PSES option which may be employed if PSES Option II proves to be
economically unachievable is to set PSES at levels achievable by physical/
chemical treatment alone.  Under this option, PSES would equal BAT  for most
pollutants but would be higher (less stringent) for the 13 priority pollutants
discussed above.  Table 8 presents the PSES Option III limitations  that would
apply to these 13 pollutants.

     The long-term averages for benzo(a)anthracene, chrysene and pyrene in
Table 8 are based on the steam stripping median value for the low Henry's Law
constant pollutant group.  For benzo(a)pyrene, 3,4-benzofluoranthene, 2,4-
dimethylphenol, 2,4-dinitrophenol and 2-chlorophenol, the long-term averages
are based on the in-plant carbon adsorption median value for the low carbon
usage rate pollutant group.  The zinc long-term average is based on the OCPSF
industry chemical precipitation data.  The long-term averages for lead,
mercury, selenium and cyanide are based on chemical precipitation performance
                                     -20-

-------
                                    TABLE 8

                PSES OPTION III LIMITATIONS THAT WOULD APPLY TO
          POLLUTANTS WITH HIGHER PHYSICAL/CHEMICAL EFFLUENTS THAN  BAT
Pollutant or Pollutant Property      Long-Term
by Priority Pollutant Classes        Average
              Four-Day
              Monthly
              Average
             Daily
            Maximum
Polyaromatics

72.  Benzo(a)anthracene
73.  Benzo(a)pyrene
74.  3,4-Benzofluoranthene
76.  Chrysene
84.  Pyrene

Phenols

34.  2,4-Dimethylphenol

Nitrophenols

59.  2,4-Dinitrophenol

Chlorophenols

24.  2-Chlorophenol

Metals

122.  Lead
123.  Mercury
125.  Selenium
128.  Zinc

Miscellaneous

121.  Cyanide
1,418
  175
  175
1,418
1,418
  175
  175
  175
1,795
  300
  300
1,795
1,795
  300
  300
  300
2,710
  570
  570
2,710
2,710
  570
  570
  570
122
1
162
107
215
2
285
180
495
4.5
660
380
   46
   85
  190
                                         -21-

-------
information from the inorganic chemicals, paint and ink, and steam electric
power generating industries.  These values were obtained by comparing OCPSF
median raw waste levels of these pollutants to other industries looking for
similar raw waste levels in industries which were comparable in wastewater
matrices to the OCPSF industry.  Appendix A contains the summary sheets from
the EPA Treatability Manual which most favorably compare to OCPSF raw waste
levels.  The corresponding variability factors for the stream stripping
systems are averages transferred from 2,4,6-trichlorophenol and pentachloro-
phenol.  The carbon adsorption variability factors are transferred from
nitrobenzene.  The OCPSF industry zinc chemical precipitation variability
factors were used for zinc, while averages for arsenic, chromium, copper and
zinc were transferred to lead, mercury, selenium, and cyanide.
                                      -22-

-------
           APPENDIX A

     SELECTED SUMMARY SHEETS
FROM THE EPA TREATABILITY MANUAL
  EPA 600/8-80-042e, JULY 1980

-------
TREATMENT TECHNOLOGY:  Sedimentation with Chemical Addition  (Alum, Lime)
Data source:  Effluent Guidelines

Point source category:  Paint manufacturing
Sub category:
Plant:  4
References:  A4,.Appendix G

Use in system:  Primary
Pretreatment of influent:  None

DESIGN OR OPERATING PARAMETERS

Unit configuration:
Wastewater flow:
Chemical dosage(s):
Mix detention time^
Mixing intensity  (G):
Flocculation  (GCt):
pH in clarifier:
Clarifier detention time:
      Data source status:

        Engineering estimate
        Bench scale
        Pilot scale
        Pull scale
Hydraulic loading:
Weir loading:
Sludge underflow:
Percent solids
  in sludge:
Scum overflow:
                                 REMOVAL DATA
Concentration,* •
Pollutant/parameter
Conventional pollutants, mg/Li
BOO*
COO
TOC
TSS '
Oil and grease
Total phenol
Toxic pollutants, U9/X>>
Copper
—Cyanide
— alellj
Mercury
Zinc
Di-n-butyl phthalate
Phenol
Benzene
Ethylbensen*
Toluene
naphthalene
Carbon tetzaehloride
Chloroform
1 ,2-Oichloropropane
Methylene chloride
1 ,1 .2 ,2-Tetrachloroethane
Tetrachloroethylene
Influent

3,300
147,000
13,000
14,000
830
1.1

500
ISO
370
7
170.000
6,500
1,300
92
1,230
1.900
54
12
16
968
2.300
SO
270
Effluent

3.900
7,970
2,300
480
<16
1.3

60
30
<200
2
1,100
HJ
47
46
22
72
16
ND
74
400
2,000
35
13
Percent
removal

(18)
95
82
97
>98
(18)

88
80
SO
71
>99
'V'lOO
96
50
98
96
70
•M.OO
(363)
59
13
30
95
                  Average of several samples.


Note:  Blanks indicate information not specified.

Date:  6/8/79
                                  III.4.3-21

From  the EPA Treatability Manual,  EPA 600/8-80-042e, July, 1980.

                                      A-l

-------
TREATMENT TECHNOLOGY:  Sedimentation with Chemical  Addition (Ferrous~~sulfate,
                       lime)

Data source:  Effluent Guidelines                Data  source  status:
Point source category:  Steam electric power        Engineering  estimate   	
                        generating
Subcategory:                                        Bench scale            	
Plant: 5409                                         Pilot scale              x
References:  A2, p. 24 (Appendix)                   Full  scale            	

Use in system:  Secondary
Pretreatment of influent:  Ash pond

DESIGN OR OPERATING PARAMETERS

Unit configuration:
Wastewater flow:
Chemical dosage{s):                         Hydraulic loading:
Mix detention time_:_                         Weir loading:
'Mixing intensity  (G):                       Sludge  underflow:
Flocculation  (Get):                         Percent solids
pH in clarifier:  11.5                        in sludge:
Clarifier detention time:                   Scum overflow:

                                REMOVAL DATA

             Sampling period;	  	  	
                                   Concentration, ug/L   Percent
             Pollutant/parameter   Influent   Effluent   removal
Toxic pollutants:
Antimony
Arsenic
Copper
Nickel
— Selenium
Silver
Thallium
Zinc

5.0
74
26
2.5
42
1.0
9.0
11

3.5
<1
18
2.0
32
1.1
7.0
<2.0

30
>99
31
20
24
oa
22
>82

              Actual data indicate negative removal.
 Note:   Blanks  indicate information was not specified.


Date:   10/29/79               III.4.3-81

                                    A-2

-------
TREATMENT TECHNOLOGY:  Sedimentation with Chemical Addition (Lime)

Data source:  Effluent Guidelines                 Data source status:
Point source category:  Inorganic chemicals         Engineering estimate
Subcategory:  Hydrofluoric acid                     Bench scale
Plant:  167                                         Pilot scale
References:  A29, p. 227                            Full scale

Use in system:  Primary
Pretreatment of influent:

DESIGN OR OPERATING PARAMETERS

Unit configuration:  47% of effluent is recycled
Wastewater flow:  127 m3/kkga
Chemical dosage(s):                         Hydraulic loading:
Mix detention timej_          .               Weir loading:
Mixing intensity  (G):                       Sludge underflow:
Flocculation  (GCt):                         Percent solids
pH in clarifier:                              in sludge:
Clarifier detention time:                   Scum overflow:
 value is for total raw waste from HP only.

                                 REMOVAL DATA
Sampling period: Three 24-hr composite samples

Pollutant/parameter
Toxic pollutants:
Antimony
Arsenic
Cadmium
Chromium
Copper
Lead
—Mercury
Nickel
Selenium
Thallium
Zinc
Cone entr a t ion
»* ug/L
Influent Effluent

46
150
-
470
120
87
27
1,100
63
-
240

<200
<24
<2.4
250
79
37
<1.2
610
87
7.9
180
Percent
removal
b
0°
>84
-
47
34
57
>96
45
0
-
25

              values are combined for wastes from HF and
              Concentration data is calculated from pollutant flow
              in m3/kkg and pollutant loading in kg/kkg.

              Actual data indicate negative removal.
Note:  Blanks indicate information was not specified.


Date:   8/30/79                 III.4.3-59

                                      A-3

-------
VI.    EVALUATION OF THE VALIDITY OF USING FORM 2C DATA
     TO CHARACTERIZE PROCESS AND FINAL EFFLUENT WASTEWATER

-------
                      FINAL
            EVALUATION  OF  THE  VALIDITY
             OF USING FORM 2C  DATA TO
CHARACTERIZE PROCESS  AND FINAL EFFLUENT WASTEWATER
                  PREPARED FOR:

        The Industrial Technology Division
       U.S Environmental Protection Agency
                401  M Street, .S.W.
             Washington, D.C.   20460
                       By:

               SAIC/JRB Associates
                 One Sears  Drive
            Paramus, New Jersey  07652
                  June 17,  1985
           EPA Contract No.  68-01-6947
       SAIC/JRB Project No.  2-835-07-688-01

-------
VI.  EVALUATION OF THE VALIDITY OF USING FORM 2C DATA TO CHARACTERIZE
     PROCESS AND FINAL EFFLUENT WASTEWATER
                            Table of Contents
                                                                        Page
1.  Introduction                                                          1
    I.I  Background                                                       1
    1.2  Summary and Conclusions                                          1
    1.3  Selection of Plants with Form 2C Application and
         308 Questionnaire Data                                           3
    1.4  Selection of Industrial Facilities                               4

2.  Methodology, Calculations and Data Analysis                           5
    2.1  General Methodology          •                                    5
    2.2  Data Analysis                                                    8
Appendix A:  Pollutants Reported at/or Below Levels of Detection         50

Appendix B:  Limits of Detection for Priority Pollutants                 51

Appendix C:  List of 129 Priority Toxic Pollutants                     .  54

-------
VI.  EVALUATION OF THE VALIDITY OF USING FORM 2C DATA TO CHARACTERIZE
     PROCESS AND FINAL EFFLUENT WASTEWATER
                                 List of Tables


Table                                                                     Page

  1    Miscellaneous Wastewater Generation                                 11

  2    Direct Dischargers Submitting Full 308 Questionnaire Responses       13

  3    Plants Without Dilution                                             15

  4    Plants With 2C Data                                                 16

  5    2C Data Plants With Dilution                                        17'

  6    Plants With Only Questionnaire Data                                 19

  7    Questionnaire Data Plants With Dilution                             20
                                           »       4
  8    Plants With Dilution That Did Not Submit Toxics  Data               .21

  9    Plant Totals                                                        22

 10    Percent of Total Plants Submitting Data                             23

 11    Table of 2C Data Plants With Dilution  (As Percent)                   24

 12    Table of Questionnaire Data Plants With Dilution (As Percent)        25

 13    Table of Questionnaire Data Plants With Dilution of
       Conventional Pollutants (As Percent)                                 26

 14    Raw Water Quality Parameters, Dilution Factor and Adjusted
       Water Quality Parameters                                            30

 15    Plant A                                                             36

 16    Plant A                                                             37

 17    Discharge Monitoring Report (DMR) Data - Plant A                    38

 18    Plant B                                                             39

 19    Plant C                                                             40

 20    Plant D - Final and Intermediate Wastewater Data                    41

 21    308 Questionnaire Data - Plant E                                    42

 22    308 Questionnaire Data - Plant F                                    43

-------
Table
                             List of  Tables  (Cont.)


                                                                          Page
 23    308 Questionnaire Data - Plant G                                    44


 24    308 Questionnaire Data - Plant H                                    45


 25    308 Questionnaire Data - Plant I                                    46


 26    308 Questionnaire Data - Plant J                                    47


 27    308 Questionnaire Data - Plant K

                                                                           AQ
 28    308 Questionnaire Data - Plant L

-------
VI.  EVALUATION OF THE VALIDITY OF USING FORM 2C DATA TO CHARACTERIZE
     PROCESS AND FINAL EFFLUENT WASTEWATER
                                 List of Graphs


Graph                                                                     Page


 1     2C Data Plants                                                      27

 2     Questionnaire Data Plants                                           28

 3     Questionnaire Data Plants With Dilution of Conventional             29
       Pollutants Only

-------
                               1.0  INTRODUCTION




1.1  BACKGROUND




     Industry comments on the March 21, 1983, proposed OCPSF regulations stated




that the toxic pollutant loadings were overestimated and suggested that the Agen-




cy rely on the NPDES permit application Form 2C toxic pollutant data for determin-




ing toxic pollutant loadings.  Industry representatives also questioned the need




to establish BAT Limitations on a wide range of toxic pollutants.  They maintain




that available NPDES Permit application Form 2C data constitute the most appropri-




ate and extensive data base for predicting the extent of occurrence of priority




pollutants in the OCPSF industry.  They argue that NPDES Form 2C data submitted




by OCPSF manufacturers indicate that only a few priority pollutants are detected




in treated discharges and conclude that existing treatment systems, installed prin-




cipally for the control of conventional pollutants, do an excellent job of control-




ling priority pollutant discharges.






     The purpose of this report is to evaluate the validity of the industry's in-




terpretation of effluent data in general and NPDES Form 2C toxic pollutant data




in particular.






1.2  SUMMARY AND CONCLUSIONS




     Since the OCPSF regulations apply to process wastewater only, the Agency de-



termined the relative contributions of process and nonprocess wastewater at the




effluent sample sites.  This data was used to calculate plant-by-plant "dilution




factors" for use in adjusting or assessing analytical data at effluent sampling




locations.  This information was used to determine if reported Section 308 and




Form 2C final effluent concentration data could be used to adequately character-




ize actual process wastewater pollutant parameter concentrations.  For example,




if a pollutant was reported as 30 ppb at the final effluent sampling location

-------
with 1 MGD of process wastewater flow and 9 MGD of noncontaminated nonprocess

cooling water flow,  then the concentration of the pollutant in the process waste-

water was actually 300 ppb.  Similarly, if the same plant reported that another

pollutant was" not detected at the same sampling location and the analytical

method detection limit was 10 ppb, then the other pollutant concentration in

the process wastewater could be as high as 90 ppb without being detected in the

diluted final effluent.


     One hundred-six plants reported Form 2C toxic pollutant data in the 1983

Section 308 Questionnaire.  Of these, 70 plants diluted the process wastewater

before the effluent Form 2C sampling point.  The following table relates the

number of plants with Form 2C data to the range of dilution at the effluent

sampling point.


                   No. of Plants                 Range of Dilution
               with Form 2C Data (Z)                 in Percent

                      36 (34Z)                           0
                      20 (19Z)                       >0 to 25
                      20 (19Z)                       >25 to 100
                      17 (16Z)                       MOO to 500
                      13 (12Z)                       >500 to 6,054


     The Agency was also able to identify 12 facilities that reported measured

toxic  pollutant concentrations of treated process wastewater both before and

after  dilution with nonprocess wastewater.  In general, analyzing the diluted

effluents yielded underestimated or undetected values for organic toxic pollut-

ants  that were measured in the undiluted process wastewater.  However, this was

not  generally the case for toxic pollutants metals such as cadmium, chromium,

lead,  and cyanide.  These metals are commonly found in cooling water additives

that may  be  utilized  to inhibit biological growth or the formation of rust and

scale  in  cooling equipment.  Therefore, the presence of a portion of these

metals in the diluted effluent seems to be caused by the nonprocess cooling

-------
water.  Therefore, the assumption that the nonprocess dilution wastewater is




relatively clean seems to apply to the organic toxic pollutants but not nec-




essarily to all of the toxic metal parameters.






     In conclusion, the use of unqualified plant effluent data which includes




dilution with nonprocess wastewater, does not provide an adequate assessment




of process wastewater pollutant constituents and concentrations.  The use of




unqualified industry supplied Form 2C data tends to underestimate organic toxic




pollutant constituents and concentrations in process wastewater and may actually




overestimate metal toxic pollutant constituents and concentrations.  Furthermore,




keeping these constraints in mind, process wastewater pollutant concentrations




can be predicted on a case-by-case basis (especially for conventional pollutant




parameters) using a dilution factor and the overall plant effluent quality.






1.3  SELECTION OF PLANTS WITH FORM 2C APPLICATION AND 308 QUESTIONNAIRE DATA




     308 Questionnaires were reviewed and all direct discharging plants (249)




submitting full responses were separated from all other types of plants (in-




directs, zeros).  One hundred and thirteen (113) of these plants did not dilute




their process wastewaters at all, while 70 plants that submitted Form 2C appli-




cation data and 66 plants that submitted questionnaire data had some form of




dilution.






     There were 100 plants that did not submit toxic pollutant data, (only




conventional pollutants) but had their process wastewaters diluted.  Conventional




pollutants for these plants were adjusted to reflect the changes resulting from




dilution.

-------
1.4  SELECTION OF INDUSTRIAL FACILITIES




     Industrial facilities were selected for inclusion in this study if data




were available for both final effluent (Form 2C),  and intermediate process




streams.  The availability of both sets of data for a facility made it possible




to compare overall effluent quality and process effluent  quality.   In addition




facilities showing substantial additions of nonprocess wastewater to process




effluents immediately upstream of monitoring points were  also included for




consideration.  These facilities proved useful in demonstrating the effect of




nonprocess waters upon the characterization of process effluents.






     Facilities meeting the preceding criteria were obtained by reviewing 308




Questionnaire data submitted by organic chemical manufacturers, and Draft




Engineering Reports prepared by JRB for the development of BAT and BPT permit




limitations for industrial facilities in New Jersey.   A total of thirteen




industrial facilities were obtained for use in this study.  Four of the




facilities included are from JRB's permit development files,  and the remaining




nine are from the OCPSF 308 Questionnaire data.

-------
                2.0  METHODOLOGY CALCULATIONS AND DATA ANALYSIS






2.1  GENERAL METHODOLOGY




2.1.1  Sampling Data




     The approach used in determining the viability of using overall plant ef-




fluent quality to characterize process wastewater discharges was to compare data




for process effluents only and total discharges for each facility.  In this man-




ner it was possible to discern whether data obtained at a final outfall truly re-




flected the contribution and strength of process wastewater flow.  The compari-




son was of particular importance if the overall effluent showed a pollutant to be




below the level of detection, while the process effluent reported higher levels.






2.1.2  .Dilution Factor:  Definition and Calculations




     In order.to collect data that would most accurately characterize process




effluents in the absence of actual data, a term called the dilution factor was




developed.  It is equal to the quotient of the nonprocess flow divided by the




process flow.  The dilution factor (plus one) for each facility multiplied by




the corresponding reported final effluent concentration, generated an adjusted




concentration which was considered to characterize, in an approximate manner,




the process effluent before the addition of other flows.  This assumed no




contamination of the nonprocess wastewaters or minimal background of pollutants.




Other minor contaminated nonprocess wastewaters, such as boiler blowdown, were




not considered appropriate for inclusion because of their unknown quality.




Table 1 presents the miscellaneous wastewaters that were considered process and




nonprocess wastewaters for the purposes of calculating the dilution factor.

-------
2.1.3  Plants with Dilution of their Process Wastewaters




     Two hundred and forty-nine (249) plants in the OCPSF industry that sub-




mitted full responses (parts A, B, and C) to the 308 questionnaires are direct




dischargers.  These plants are presented in Table 2.  The purpose of this study




was to determine what plants diluted their process wastewaters with nonprocess




waters as defined in Table 1.  A total of 113 facilities either did not dilute




their process wastewaters or did not provide accurate treatment system informa-




tion to determine if dilution was occurring.






     A review of the 308 questionnaires indicates that certain plants submit-




ted Form 2C application data (for toxic pollutants) in questions C13 to C16




of the questionnaire (Table 4).  Seventy of these plants diluted their process




wastewaters with nonp'rocess water (Table 5).






     Other plants submitted only questionnaire toxic pollutant data for ques-




tions C13 to C16 (Table 6).  Sixty-six of these plants diluted their process




wastewater streams, they are presented in Table 7.






     As mentioned earlier, some plants did not report toxic pollutant data




when they submitted their 308 Questionnaires, but were found to have diluted




their process wastewater streams.  There are 100 plants with conventional pol-




lutant data; these are presented in Table 8.






     There were 106 plants that submitted Form 2C toxic pollutant data of




which 70 diluted their process wastewaters.  This represents 66% of all plants




that submitted Form 2C data.  Likewise 109 plants submitted questionnaire tox-




ics data but only 66 plants with dilution.  This represents 61% of all plants




that submitted questionnaire data (Tables 9 and 10).

-------
     Bar graphs are presented to illustrate the range of percent dilution for




the Form 2C, questionnaire,  and conventional pollutant data discussed earlier




(Bar graphs 1,2, and 3 and Tables 11 to 13).  This data indicates that 29 to




35X of all plants are diluted in the range 0-25 while 33 to 482 of all plants




are diluted greater than 100Z.






     Table 14 presents dilution factors developed from 308 questionnaire data




covering a variety of OCPSF product/processes for the parameters TOG, COD,




TSS, and 8005.  Dilution factors range from 0.00031 to 2,519;  and the adjusted




pollutant concentrations are affected accordingly.  This table also shows the




variability in concentrations between the adjusted and reported conventional




pollutant parameters.                •                    •






   .  These results indicate that -there can be considerable differences between'




the reported and actual pollutant concentrations submitted by  OCPSF plants,




and that there is considerable dilution of process wastewaters with nonprocess




waters by plants that submitted priority pollutant, and conventional pollutant




data.  Approximately 55Z of all plants that submitted toxic data were found  to




have dilated their process wastewaters with nonprocess water.






2.1.4  Draft Engineering Permit Report Data




     Intermediate and final discharge data were obtained for four industrial




facilites from JRB's files.  The facilities are listed below:




          1.  Plant number A - An Oil Refinery Facility




          2.  Plant number B - A Bulk Organics Facility




          3.  Plant number C - A Pharmaceuticals Facility




          4.  Plant number D - A Speciality Organics Plant

-------
     Data for these facilities are presented in Tables 15 through 20.  In gen-




eral, the data present for the facilities show that concentrations of pollutant




parameters measured at combined outfalls which include nonprocess flow are mark-




edly lower th'an the levels measured directly at process outfalls.  This is a




good indication that pollutant data obtained from a final outfall is not truly




indicative of the effluent quality of a process discharge.






     Data presented in Tables 16 and 18, are of particular importance because




several pollutant parameters which were reported in the final outfalls at




concentration levels below those of detection were present at concentration




levels above detection at isolated process discharge points.  Nominal detec-




tion levels for pollutant parameters are presented in Appendix B.  These occurr-




ences are especially meaningful because they indicate that analyses of combined




outfall effluents do not necessarily provide a true characterization of process




wastewater quality.






2.1.5  308 Questionnaire Data




     308 Questionnaire Data was reviewed to obtain facilities with available




intermediate and final effluent data.  These facilities are presented in Tables




21 through 28.  As mentioned before, facilities were selected on the basis of




their process flows undergoing dilution with nonprocess flows immediately pre-




ceding sampling sites.  The data tabulated includes pollutant levels reported




at final outfalls, and calculated adjusted concentrations which represent iso-




lated process flows.






2.2  DATA ANALYSIS




2.2.1  Analysis of OCPSF Section 308 Information




     Plant data from the 1983 Section 308 Questionnaires were analyzed by com-




paring total facility effluent quality with process effluent quality before

-------
mixing.  Tables 15 through 26 present the data obtained.  Examination and  com-




parison of the data for each plant indicates that the final facility effluent




quality is not truly indicative of process effluent quality.  Final discharge




concentrations are noticeably lower than concentrations in undiluted process




streams.  In those cases where total effluent concentrations are below detection




limits, virtually no indication of process quality is provided.  This is illus-




trated in Table 18.  Chloroform,  ethylbenzene, and 1,4-dichlorobenzene were all




reported to be undetected in the overall facility effluent, but were reported




in varying quantities in the process effluent.  In this case, the overall




effluent- quality is not indicative of the process effluent quality.  Addition-




ally the variations in the concentrations of the three pollutants in the process




discharge indicate that the application of a dilution factor based on process




and total flows, to project process effluent quality, is not totally accurate




for this particular facility.  It is also true for Plant A whose datat were pre-




sented in Table 15.  Concentrations reported at Plant A's treatment plant, repre-




sentative of process effluent, were greater than those reported at the main out-




fall forBODs, TSS, phenols, oil & grease, and zinc.  However,  calculation of a




dilution factor, based on reported concentrations, yields values ranging from




3.12 to 7.39.  The actual dilution factor calculated for the faci-Ilty,  based on




flow data, is 17.875.  For those pollutants reported at higher concentrations in




the main outfall than in the treatment plant effluent, it is no longer reason-




able to speak about dilution with respect to the process effluent.   For these




pollutants, which include cadmium, chromium, lead, and cyanide,  it  is  actually




the cooling water that is being diluted with process effluent.   Table 15 also




indicates that pollutant loadings may be primarily caused by contributions from




nonprocess sources.  The loading attributable to the noncontact cooling water,




which mixes with the treatment plant effluent prior to the main outfall  samp-




ling point, was calculated using the appropriate flow based dilution factor.

-------
     Therefore, the strict use of a dilution factor to project process effluent


quality is not reliable in all cases and its limitations should be known on a


plant-by-plant basis.  It also may not be advisable to assume that noncontact



cooling water is devoid of pollutants in all cases.




2.2.2  308 Questionnaire Data Analysis


     Data from those industrial facilities obtained from a review of 308 Ques-



tionnaire information, were analyzed by projecting adjusted concentrations


based on reported concentrations and appropriate dilution factors.  Although


the dilution factor is not considered rigorously applicable to the accurate


calculation of process pollutant concentrations, as discussed in Section 2.2.1,


it was deemed reasonable to use it to estimate such concentrations, lacking


additional data, and keeping in mind its limitations.  Comparison of reported


and adjusted concentrations for the nine industrial facilities presented in


Tables 21 through 28 shows adjusted concentrations with the degree of difference
                                                                   •

being dependent upon the associated dilution factor.  Large dilution factors


resulted in larger adjusted concentrations than smaller dilution factors, given


equal reported concentrations.  Dilution factors for the facilities that submitte


toxic pollutant data ranged from 0.748 to 60.54.
                                     10

-------
                                           TABLE 1

                                Miscellaneous Wastevater Generation
                   Process
           Non-Process (Dilution)
1         Mr Pollution Control Vastewater
2         Sanitary (receiving biological  trt.)
3         Boiler blowdown
4         Sanitary (indirect discharge)
5         Steam Condensate
6         Vacuum Pump Seal Water
7         Wastewater Stripper Discharge
8         Blol. from Vertac
9         Boiler Peedwater Line
10        Softener Blowdown
11        Contaminated Water Offsite
12        Condensate
13        Storage, Labs, Shops
14        Laboratory Waste
IS        Steam Jet Condensate
16        Water Softener Backwashing
17        Misc. Lab Wastewater
18        Raw Water Clarification
19        Landfill Leachate
20        Water Treatment
21        Technical Center
22        Scrubber Water
23        Utility Streams
24        Washdown N-P Equipment
25        Contact Cooling Water
26        Vacuum Steam Jet Blowdown
27        Densator Blowdown
28        Bottom Ash-Quench Water
29        Demineralizer Washwater
30        Water Softening Backwash
31        Lab Drains
32        Closed Loop Equipment Overflow
33        HVAC Blowdown
34        Pilter Backwash
35        Demineralizer Wastewater
36        Laboratory Offices
37        Demineralizer Blowdown
38        Utility Clarifier Blowdown
39        Steam Generation
40        RO Rejection Water
Non-Contact Cooling Water (one  pass)
Sanitary (no biological  trt., direct  disch
Cooling Tower Blowdown
Stormwater Site Runoff
Deionized Water Regeneration
Miscellaneous Wastewater (conditional)
Softening Regeneration
Ion Exchange Regeneration
River Water Intake
Make-up Water
Pi re Water Make-up
Tank Dike Water
Demineralizer Regenerant
Dilution Water
Condensate Losses
Shipping Drains
Water Treatment Blowdown
Cooling Tower Overflow
Chilled Water Sump Overflow
Air Compressor and Conditioning Blowdown
Firewall Dralnlngs
Other Non-Contact Cooling
Misc. Leaks and Drains
Boiler House Softeners .
Pi re Pond Overflow
Boiler Regeneration Backwash
Groundwater (Purge)
Firewater Discharge
Freeze Protection Water
H2 and CO Generation
Demineralizer Spent Regenerants
Lime Softening of Process
Miscellaneous Service  Water
Recirculating Cooling  System
                                             11

-------
                                        TABLE 1 (Cont.)

                               Miscellaneous Wastevater Generation
 I_	Process	Non-Process (Dilution)

41        Power Bouse Slowdown
42        Inert Gas Gen.  Slowdown
43        Contaminated Groundwater
44        Potable Water Treatment
45        Unit Washes
46        Non-Contact Floor Cleaning
47        Slop Water from Disc.  Facilities
48        Laboratory and  Vacuum  Truck
49        Ion Bed Regeneration
50        Tankcar Washing (HCN)
51        Film Wastewater
52        Generator Slowdown
53        Ash Sluice Water
54        Research and Development
55        Quality Control
56        Steam Desuperheating
57        Pilot Plant
58        Other DuPont Off-site  Waste
59        Ion Exchange Resin Rinse
60        Iron Filter Backwash
61        Area Washdown             .                         .         •
62        Vacuum Pump Wastewa'ter
63        Garment Laundry
64        Hydraulic Leaks
65.       Grinder Lubricant
66        Utility Area Process
67        Contact Rainwater
                                               12

-------
                                      TABLE 2
           DIRECT DISCHARGERS SUBMITTING  FULL  308  QUESTIONNAIRE  RESPONSES
PLANT NUMBER
1
1
61
e."t
o j
83
W J
87
O /
101
A W i
102
4 W to
114
A A ~
154
155
X •* V
159
± J *
177
A * *
180
183
±\J J
225
to A>^
227
*• to *
250
to W W
254
260
267
to W *
269
284
to w~
294
to J ~
.296
• to ^ W
352
w ^ to
373
J / •/
384


387
^w *
392
394
399
412
415
443
444
447
481
486
500
502
523
525
536
569
580
602
608
626
633
657
659
662
663
664
669


682
683
695
709
727
741
758
775
802
811
819
825
844
851
859
866
871
876
883
' 888
908
909
913
915
938
942
948
970


984
990
991
1012
1020
1038
1059
1061
1062
1067
1133
1137
1139
1148
1149
1157
1203
1241
1267
1299
1319
1323
1327
1340
1343
1389
1407
1409


1414
1438
1439
1446
1464
1494
1520
1522
1532
1569
1572
1593
1609
1616
1618
1624
1643
1647
1650
1656
1684
1688
1695
1698
1714
1717
1753
1766

'
1767
1774
1776
1802
1839
1869
1881
1890.1
1890.2
1905
19,11.1
1911.2
1928
1943
1973
1977
1986
2009
2020
2026
2049
2055
2062
2073
2090
2110
2148
2181
2198

2206
2221
2222
2227
2228
2236
2241
2242
2254
2268
2272
2296
2307
2313
2315
2328.1
2328.2
2345
2353
2360
2364 .
2365
2368
2376
2390
2394
2399
2400
2430
2445
2447
2450
2461
2471.1
2471.2
2474
2527
2528
2531
2533
2536
2541
2551
2556
2573
2590
2592
2606
2626
2631
2633
2668
2673
2678
2680
2692
2693
2695


                                           13

-------
                              TABLE 2 (continued)
2701
2711
2735
2763
2764
2767
2770
2771
2786
2795
2816
2818
3033
4002
4010
4017
4021
4037
4040
4051
4055
                                           14

-------
                                      TABLE  3
                              PLANTS  WITHOUT DILUTION
fLANT NUMBER
1
101
102
180
227
254
260
267
296
373
392
412
415
444
481
502
523
536
569
608
626
633
659
662
663.1
663.2
664
669
683
709
741
758
775
825
851
888
942
970
991
1059
1133
1139
1148
1157
1203
1267
1299
1327
1343
1349
1407
1414
1438
1446
1464
1520
1522
1572
1593

1624
1643
1647
1650
1656
1684
1714
1753
1769
1774
1776
1881
1905
1928
1973
1977
1986
2020
2049
2055 .
2073
2198
2206
2221
2236
2254
2272
2296


2307
2345
2364
2365
2394
2400
2447
2461
2471.1
2471.2
2527
2541
2551
2556
2573
2590
2592
2606
2631
2701
'2770
2816
3033
4002
4021
4037
4055



                                           15

-------
                  TABLE 4

            PLANTS  WITH 2C DATA
  !              844            1656             2450
 63              859            1688             2461
 83              876            1717             2474
102              883            1753             2531
U4              887            1853             2551
154              909            1869             2556
159              913            1881             2573
183              942            1891             2590
269              984            1943             2626
294              990            2009             2633
296             992            2026             2635
352             1012            2055             2668
373            1020            2073             2673
387             1069            2090             2680
394            1137            2148             2692
399            1149            2228             2693
415    '        1241            2268             2701
500            1319            2272             2711
536            1407            2300             2735
601            1532            2315             2786
657  -           1569            2328            2795'
669            1572            2353             2818
717             1616            2364            3033
722             1617            2390            4010
727             1618            2430            4021
811             1643            2445            4040
                1647                            4051
                       16

-------
                            TABLE 5

                  2C DATA PLANTS WITH DILUTION


Plant t                          Dilution Factor

  63                                     .16308
  83 "                                    .0720
 102                                     .02792
 114                                     .74803
 154                                     .5480
 159                                     .3477
 183                                    3.1667
 269                                     .4440
 294                                    5.61905
 352                                     .31071
 373                                     .730
 387                                     .00091
 394                                     .0011
 399                                     .01590
 500                                    3.9113
 657                                     .2254
 727                                   14.46667
 811                                     .6273
 844                                     .6288
. 859                                .    6.27
 876                    "                2.791 .
 883                                     .3462
 909                                    2.087
 913                                     .2632
 942                                    3.0
 984                                     .3595
 990                                     .3113
 1012                                   4.6139
 1020                                     .88268
 1137                                    .05932
 1149                                     .02664
 1241                                    2.35163
 1319                                   9.5652
 1532                                  10.00
 1569                                   1.0
 1616                                    .45045
 1618                                    .2210
 1688                                   1.3514
 1717                                   1.346
 1869                                    .0977
 1943                                    .58594
 2009                                    .1111
 2090                                    .2495
 2148                                    .05106
 2228                                   5.298
 2268                                   14.5143
 2315                                   3.62
 2328                                   2.36318/2.35714
 2353                                   2.37
 2390                                    .02812
 2430                                    .28351
 2445                                    .60737
 2450                                   16.7129
 2474                                   52.94

-------
                      TABLE 5  (continued}

                  2C DATA PLANTS  WITH DILUTION


Plant t                           Dilution Factor

 2531                                  11.0651
 2626                                    .1963
 2633                                    .150
 2668                                  33.6515
 2673                                   1.4074
 2680                                    .375
 2692                                   1.0833
 2693                                    .2069
 2711                                  60.5439
 2735                                    .1478
 2786                                    .53127
 2795                  •                  .1455
 2818                                   1.184
 4010                                   9.9867
 4040                          •         2.00
 4051                                   3.30
             Note:  In addition to 2C data all of the above plants
                    have questionnaire data except:    114
                                                      913
                                                     2711
                                                     4010
                               18

-------
                               TABLE  6

                  PLANTS  WITH ONLY QUESTIONNAIRE DATA
 ,,                682             1323              2026                2678
 If                683             1327              2049                2695
 07                695             1340              2062                2763
,55                709             1343              2110                2764
\j7                775             1389              2181                2767
225                802             1409              2222                2770
227                819             1414              2227                2771
250                825             1439              2236                2816
254                851             1446              2241                4017
259                866             1464              2242
267                871             1494              2313
284                908             1522              2360
384                915             1593              2368
417                938             1609              2376
443           '     948             1695              2399
447                970             1698              2447
486                976             1766              2527
502            '   1038             1769              2528
523               1061             1774              2533
525               1062             1802              2536
580               1067             1839              2541
602               1133             1877              2554
608               1139             1890              2592
659               1203             1911              2631
662               1299             1928              2647
                                  19

-------
                TABLE 7

QUESTIONNAIRE DATA PLANTS WITH DILUTION
      Plant *

         12
         61
         87
        155
        177
        225
        250
        284
        384
        443
        447
        486
        525
        580
        602
        682
        695
        802
        81.9
        866
        871
        908
        915
        938
        948
        1038
        1061
        1062
        1067
        1323
        1340
        1389
        1409
        1439
        1494
        1609
      .  1695
        1698
        1766
        1802
        1839
        1890
        1911
  Dilution
  Factor

   7.147
  10.0
   0.308
   1.215
   3.67
   0.530
   1.190
   0.2868
   1.2123
  48.571
  84.8165
 250.0
   0.0912
    .00047
   9.000
   6.4393
   0.012
   0.933
   0.0591
   0.8406
   1.910
   0.0016
   0.0645
   5.5069
   0.0164
   1.0564
   0.0113
   1.6573
  15.90
   2.1177
   0.1720
   0.10337
   2.3516
  69.333
   0.2638
   0.0727
   0.1543
   1.0909
   0.6084
   1.290
2518.9
   1.480/.5174
   4.1667
                   20

-------
                                      TABLE 8

                PLANTS WITH DILUTION THAT DID NOT SUBMIT TOXICS DATA
PLANT NUMBER
   30        888      1936      2507
   94        944      1977      2556
  199        962      1986      2573
  .203        990      1993      2578
  2U       1053      2055      2590
  220       1059      2073      2609
  249       1086      2108      2631
  254       1117      2177      2635
  259       1139      2221      2679
  260       1188      2243      2736
  303       1237      2254      2756
  312       1238      2261      2776
  392       1432      2288      2793
  444       1437      2293      3033
  449       1438      2296      4002
  481       1504      2307      4007
  494       1539      2328      4008
  543       1579      2345      4017
  614       1621      2365      4023
  663       1624      2394      4037
  669       1643      2400      4040
  683       1657      2402      4051
  709       1714      2436
  717       1740      2447
   720        1764       2471
  771       1776      2485
  851        1838       2487
  887        1891   '    2495
                                           21

-------
                                   TABLE 9

                                PLANT TOTALS


                                                      Total Number
                                                       of Plants

                                                          249
1.   Direct Dischargers


2.   Plants Submitting Form 2C Data                          106


3.   Plants Submitting Only Questionnaire
     Data                                                  10
4.  Plants With 2C Data and Questionnaire
     Data               •                                    65
                                      22

-------
                                   TABLE 10

                   PERCENT OF TOTAL PLANTS SUBMITTING DATA



                                              Total Number
                                               of Plants         As Percent

1.  Form 2C Plants  With Dilution                    70               661


2.  Questionnaire Data  Plants With Dilution         66               60.62
3.  Plants Submitting Only  Conventional
     Pollutant Data                               100
   As percent of total  plants  submitting Form 2C toxics data.

   As percent ot total  plants  submitting questionnaire data.
                                     23

-------
               TABLE 11
TABLE OF 2C DATA PLANTS WITH DILUTION
             (AS PERCENT)
0-25Z
Plant 1
63
83
102
387
394
399
657
1137
1149
1618
1869
2009
2090
2148
2390
2626
2633
2693
2735
2795

Z
16
7
3
.09
.11
16
23
6
3
22
10
11
25
5
3
20
15
21
15
15
' 25-50
Plant #
159
269
352
883
913
984
990
1616
2430
2680

Z
35
44
31
35
26
36
31
45
28
38
          50-75
        Plant I  Z
          114
          154
          373
          811
          844
         1943
         2445
         2786
75
55
73
63
63
59
61
53
  75-100
Plant I  Z

  1020   88
  1569  100
                      100-500
                    Plant #  Z
 183
 500
 876
 909
 942
1012
1241
1688
1717
2315
2328
2353
2673
2692
2818
4040
4051
317
391
279
209
300
461
235
135
135
362
236
237
141
108
118
200
330
  >500
Plant *

  294
  727  1
  859
 1319
 1532  1
 2228
 2268  1
 2450  1
 2474  5
 2531  1
 2668  3
 2711  6
 4010
                  24

-------
                    TABLE 12
TABLE OF QUESTIONNAIRE DATA PLANTS WITH DILUTION
                  (AS PERCENT)
0-25%
Plant
525
580
695
819
908
915
948
1061
1340
1389
1609
1695
2026
2181
2227
2241
2313
2528
2536
2695
2771
4016
1 Z
9.1
.047
1.2
5.9
.16
6.45
1.64
1.1
17.2
10.3
7.27
15.4
1.4
3.95
2.51
12.3
19.37
6.86
.031
4.66
8.33
15.06
25-50 50-75 75-100 100-500
Plant # Z Plant # X Plant * Z Plant
87 308 225 53.0 802 933 155
284 28.7 1766 60.8 866 84.1 177
1494 26.4 1890.2 51.7 2062 81.8 250
2242 25.5 2368 54.6 384
2763 28.95 2376 50.8 871
1038
1062
1323
1409
1698
1802
1890
1911
2110
2360
2399
2533
2764
2767



* Z
120.15
367
119.0
121.2
191.0
105.6
165.7
211.8
235.2
109.1
129.0
.1 148
416.7
186.1
194.4
188
108.0
118.2
159.0



>500
Plant
12
61
443
447
486
602
682
938
1067
1439
1839
2222
2678









# Z
714.7
1000
4857
8481.6
25000
900
643.9
550.7
1590
6933
251900
1446.7
1156.5









                        25

-------
                                    TABLE  13

   Table of Questionnaire  Data Plants  with  Dilution of Conventional Pollutants
                                   (as percent)
0 - 257.
25 - 50
50 - 75%
75 - 100%
100 - 500%
>500%
30
199
199
220
254
312
449
683
717
720
990.1
1053
1059
1086
1139
1188
1237
1432
1504
1579
1764
1977
1993
2055.1
2221
2261
2402
2436
2485
2487
2495
2507
2736
2756
3033
4007
4008
4017
4023
6
00
4
9
0
20
11
19
23
7
0
5
.2
14
1
8
2
6
20
17
7
8
12
7
.5
18
.4
14
20
10
21
5
3
2
5
.1
24
15
.2
203
214

494
663.1
663.2
771
851
990.2
1238
1539
1621
1657
1714
1740
1891
1936
2073
2293
2471.1
2471.2
2573
2609
















27
30

49
34
34
33
26
31
33
41
29
37
27
33
33
42
40
35
25
39
42
43
















162 74 614 80 249
260 66 2177 83 303
444 50 2345 80 392
962 66 543
2296 50 887
2394 55 888
2590 58 1117
2631 64 1437
2679 50 1438
4073 60 1643
1838
2108
2243
2254
2288
2328
2365
2556
2635
2793
4002
4040
4051
















109
426
186
108
140
163
150
140
164
331
217
192
335
112
200
236
100
212
119
325
167
200
330
















259
481
669
709
944
1624
1776
1986
2055.2
2307
2400
2447
2578
2776

























17405
3000
916
1532
715
8929
1167
6063
2552
2170
2250
17400
654


























                                      26

-------
30
                                      GRAPH 1




                                   2C Data Plants
20
     28.6Z
10
               14.3Z
     11.4Z
                                   2.9Z
                                            24.3Z
                                                       18.5Z
            25
50
75
100
500
6100
                                  PERCENT DILUTION
                                         27

-------
                                     GRAPH 2




                            Questionnaire Data Plants
30
20
    32.8Z
10
               7.5Z
7.5Z
                                  4.5Z
                                           28.4Z
                                                      19.3%
           25       50        75        100       500        252,000
                                 PERCENT DILUTION
                                       28

-------
                                   GRAPH 3




    Questionnaire Data Plants with Dilution of Conventional  Pollutants Only
30
20
10
35.1Z
                  19.82
25
                               92
                                         2.72
                                                     20.72
50          75         100
                               Percent Dilution
                                                                12.62
                                                     500
                                                                         750,000
                                     29

-------
                 *«       3 •
                                                                                                                                                       „! P-- *•* O
                             -o 3O)uiaoou*)o
•3"
rH


 0)
r-l       Z
^3       I
 (Q       je

H       E
                                                                                                 ^  i     i  *   i
                  _
          s       «
                                                                                        30

-------
                        UJ	


                        OlO     -Oi^4r^p«.i-orx^f*»i   I   i   i   i  in  i  f»  i   t   i   i   r-  t   i
                                                                                                                                                                                      .*•) -3  3  3
                                                      ,n     —.— —  i«i    r*.     -•     —CN     _-.<>    ^j r>.  K) fi  <-•         fii        eN     ••     — — 3 pn     CNiiT
                                                                 •*                                                ^> I'O                      r^»                            (^           ••
              OC        U4
                                                                                                  C4              r<
                                                                                                                                                                                             "
 O
^3"
f—t

 d)
cj   .     «(J     j —  t>-*^>  — ^O»^-— — —
«cn     a a     f^i_inoi'-»
-------
•s
H



ft uuAiirv
UJ
O
Ul
'ft
O
Z
Mitejjii»e«iiii^ii
•3 O O O O O O 3* OOOOOOOOOO^OOOOOOlBO 3 O) O O O O 3 3OOOO9OO 3 O O 3 -3
* O* CN »
^ -T404 r*— —

                                                    32

-------
*J     ^*

§     s
u
 -
^

«
3
a
oc



Ui
U1
3
5

Z
—  0
a *-
a
U*
VI U1
3. •—
O

U1 O
3 U



Q
U4

3 0
0

Z O
— CJ
u- -*
-J

« u
3 a
u


.j
3 Wl
t— tn
«
_i
^a
i- 0
(-1 U
-J
«
^
2 ' ' ' ' ' ' S - ' ' '»'1-!1 '±5'-° 	 ^^^^.o, , , r. . 3 _ .0 , ,»,.-..
o-N--ooo»---*-«-r.«,1B*««o^oor,M,«,««,*<,<«^.~o,^.-1n
2 § ^ Z " ' ' i»»^^-^"~i52^-''-"j^'^«»i'-;o'g»-'"^j;-i>-"^1''-' »•"::" 2r?!




C4 (N K»





" in— P-1IN C-4 «C-40<
«00-->floa>J.r-t00-00~CMOIO-00300l>03f%or.'=a>»»3»0«0-4 D(S—-.O 3 3 O — 30003000000300000300
STTTTTrS^rrr^T^Tr^STSTrrTTrTro-S^^rrTSrS^^Tr^r^r





•*•" •• — — — -• -.»*. — —

+ ***~**-ez~*»*o + -~- + *«-~*~»* + -a>±**-.***;- + <*f: + s*-~n'>*

« ..

s"5S3SS3ss2-:-2~s?:ssssas^s?:ss^«K^sss5Sss?;2;s23^u
                                                                     33

-------
                                                                                                                   — oooo  300  3  o  a- «•» o — o  o vi ui o  30-00



                                                                                                                                i   i   i   I   i   in r>4  I  3)  I   I  ^ •
                      tn o     iinc
                                                                                                                                                                         f*  — i-i in
I
«       »«     o  »• o
             «        M.  a                 fi  n psi
             ?        LJ  4                 r*     -*
             o        «
             :       !
             «       a.
                                                                                                       34

-------
a
o
a
       . r- 3 -O


       i » m -o
•3
H
           II
      O O O 3



-------
c
o
f4

to —»
u •"*•.
S I3
V ^
y
e
o
u

-»

r*. co -T O

00 1 -» -< O 1






co r*
CM O
0 -«

1 1 1 O O







o
ts

1 O 1






(^ -T

•-> o

1 1 O O





              -a- O
              ^ oo
                                 en I  o  i   i  i  o->


a
o
*-t
4J
« -^
U ^"t
u -^
§ a
e ^
3




o
o o ->
o o o —
— X  r- O •<
m z oo — z





§iiissiill3s
oooooooooooo

-J 9
9 £
^t »**












o
0
o
06

u
VI
S


^^
-J
a.
g
z

TJ '^
« X
o a

a oo
a .*
S^
c
o
4-1
CQ x^
U ^H
4J *-*K

0 i
1
§ JnS5 So2of^§2S?n?!S3
-^ 1 r^u"»s
(0
^
-^
00
^
Xtfl'
00
irt
» 1
^
^ . « §! g 3
•1 ll^ll


HOfl»H^J^ 3 4) C ^— ' "*^


i ni x z crt t4 O

-------
                  OOOOOOOOOOOOOO^iri^-QOOO

            CO    V V V  V  V V V    V V V  V        V       •-•,-•
ffs                  •

•^     ^^^1,-tV—tVVVV
<£     V V V V    V
                                                        ZSKZO Z Z
            cs    vvvvv     v       vvv
            i^.    O    OOOO-4-- — OHHHt-H
  .
O
                                                        Ht-HOHH
                                                        ZZZOZZ
                                                                       OO
                           vvvvvvvv


fi
0
*o
g

h
oa
«
c
41
N
C
1
w
o
r^
£
(J
omomethane
u
^
u
0

e

s
o
o
o
i-H
£
u
omomethane
u
o
o
J^
u
a
hlorophenol
u

C 1
3 -

O -
Ihexyl) phtha:
thalate

.c &, e
u O
1 ^ O
'*~s u CL

S 5 «


?B §
a -3 a 5
vH S O &

5 5 6 o


1
V 01 ^
•Q ^ > 
-------
                         C  00
                         v  a
                                  Ut ^ -^ O —I '

                                  O ^ irt tA O I
                                                   .  r*»  o\  m  rt u^ o

                                                   •  r^  r*  r-.  00 ff* O
       B
       u

       3
w     ao


-«    t'
H     O
9


O.
                          B  »
                          «  F

                          C

                         .
                          o  a
                         J •«
                            •
                          B



                         I
                                   I
                                   igggggg
                                   Cf-HHHt-HHHHHH
                                   00
                                   u
                                   o
                                   CX CO 00

                                   ff> — -I I
                           38

-------
                                   TABLE 18

                                    Plant B
                             Wastewater Treatment Plant       Outfall 001
Parameter                      Effluent Stream (ug/1)         (ug/1)

Bromoform                             100.0                      19.0
Chloroform                             51.0                       ND
Ethylbenzene                            6.5                       ND
Methylene Chloride                     18.0                       7.6
Toluene                                 4.1                       2.2
1,4-dichlorobenzene                   470.0                       ND
Phenol                                 17.7               •        1.4
ND - Not Detected; Limit of Detection is 5 ppb.
                                         39

-------
         -

         a go
         a jt
o i  t— -a i  oo o *
     t/i tn   CM MS i
       W
       U
          si

          c
          o
         u
                 oooooooooooo
u


 e
          I
          IQ
 OOOOOOOOOOOO


 OOOOOOOOOOOO
                                                  O


                                                  O
             «
             B
             «
             b

             s.
   QOQQOOQOaOQ
   ooooooooooo
   uuouuuuuooo
o
u
            o
            00
            a>
                                    .n u   U
                                          a
                                          i*
                                          u
                                          0)
                                          Ul
              40

-------
                     cn
                      CO
                      s-
    >1
    CO
                          60
                         .J*
           VO


           O
                      60
 O

8

•o
4J
 CO
    60
    B
                                 CM
                                 en
                      cfl
                      O
            09
            CO
O
CM

W
        c
        «
       -H
       PH
            (U
            4-1
            c
                      CM
                      C
                      v
M-l
W
 CO
 c
                          >%
                          a
                         •a
                         •v»
                          60
                  cn
                    •

                  en
                                 CM
                                 00
           ul
                                               CM
           •o
            a
            c
                          60
                                        in
                                        CO
                                        CM
                                        sr
                         in
                         CM
                      W
                       e
                       CO
C
V
B

CO
01
M
H
                                        CJV
                                        vO
60
B
                                 vO
SO

cn
                                                                     m
                                                                     O
                                                                     m
                                                                     r-
                                        D  Q
                                        &-  a,  u
                                        cj  o
                                                h
                                        
-------
                                   TABLE 21

                            308 Questionnaire Data
                                    Plant E

                             Reported                    Actual
Pollutant               Concentration (ug/1)      Concentration  (ug/l)(l)

Aluminum                        140                        245
Boron                           ND                           16
Barium                           70                        122
BOD                           8,600                      15,033
Cobalt                          ND                           16
COD                          31,000                      54,188
Iron                            570                        996
Magnesium                     5,300                      9,264
Manganese                        40                          70
Molybdenum                      ND                           16
Nitrogen, Ammonia                70                        122
Nitrogen, Nitrate               850                      1,486
Oil & Grease                  2,600                      4,545
Phenols                         ND                           '0.80.
Tin                             140                        245
Ti                           -10                          18
Organic Nitrogen     •           430                        -752
TSS                          51,000                      89,148

Antimony                         28                          49
Arsenic                          60                        105
Cadmium                           8                          14
Chromium (Total)                  5                           9
Copper                           65                        114
Lead                              6                          11
Nickel                           27                          47 r,
Selenium                          7                          12
Thallium                          3                           5
Zinc                             78                        136
Toluene                          15                          26
Vinyl Chloride                   19                          33

Priority Pollutants  reported
  as ND (2)                     ND                            1.6-399.3

(1) Adjusted concentrations were generated  through a mass  balance,  using  the
    reported concentrations for combined process and dilution waters; and
    calculating an actual  process water concentration  through the use of  a
    term designated  as  the dilution factor.  The dilution  factor was calcula-
    ted by dividing  dilution water flow by  the process  flow.  The equation
    developed is as  follows:  Actual Concentration * Reported Concentration  (1
    + Dilution Factor)

        The dilution factor for this plant  is 0.748

(2) Priority pollutants reported as ND are  presented in Appendix A.  Detection
    levels are presented in Appendix B.


                                       42

-------
                                   TABLE 22

                            308 Questionnaire Data
                                    Plant F
                             Reported                    Actual
Pollutant               Concentration (ug/1)     Concentration (ug/l)(l)

BOD                            25,000                      165,475
COD                            55,000                      364,045
Oil & Grease                    1,000                        6,619
TOC                             9,700                       64,204
TSS                            29,000                      191,951

Antimony                           11                           73
Arsenic                            36                          238
Beryllium                           3.8                         25
Cadmium                             7.4                         49
Chromium (Total)             •      74                          490
Copper                             37                          245
Lead            .                   28           .           .185
Mercury                             3                           20
Nickel                             21   •                       139
Selenium                           28                          185
Silver                              8                           53
Thallium                           72                          477
(1) Adjusted concentrations were generated through a mass balance, using the
    reported concentrations for combined process and dilution waters; and
    calculating an actual process water concentration through the use of a
    term designated as the dilution factor.  The dilution factor was calcula-
    ted by dividing dilution water flow by the process flow.  The equation
    developed is as follows:  Actual Concentration « Reported Concentration (1
    + Dilution Factor)

        The dilution factor for this facility is 5.619
                                       43

-------
                                   TABLE 23

                            308 Questionnaire Data
                                    Plant G
                             Reported                    Actual
Pollutant               Concentration (ug/1)     Concentration (ug/l)(l)

Mercury                           0.20                        1.45

Zinc                            190                       1,378

Acrylonitrile                49,000                     355,250

Ethylbenzene                    640                       4,640

Benzene                          54                         392

Bis(2-ethylhexyl)phthalate       12                          87

Toluene                         270                       1,958
(1) Adjusted concentrations were generated through a mass balance, using the
    reported concentrations for combined process and dilution waters; and
    calculating an actual process water concentration through the use of a
    term designated as the dilution factor.  The dilution factor was calcul-
    ated by dividing dilution water flow by the process flow.  The equation
    developed is as follows:  Actual Concentration - Reported Concentration (1
    + Dilution Factor)

        The dilution factor for this facility is 6.27
                                       44

-------
                                   TABLE 24

                            308 Questionnaire Data
                                    Plant H
                             Reported                    Actual
Pollutant               Concentration (ug/1)     Concentration (ug/l)(l)

Mercury                          0.4                        2.1

Ethylbenzene                    10                         56

Bis(2-ethylhexyl)phthalate      36                        202
(1) Adjusted concentrations were generated through a mass balance, using the
    reported concentrations for combined process and dilution waters; and
    calculating an actual process water concentration through the use of a
    term designated as the dilution factor.  The dilution factor was calcula-
    ted by dividing dilution water flow by the process flow.  The equation
    developed is as follows:  Actual Concentration » Reported Concentration (1
    + Dilution Factor)

        The dilution factor for this facility is 4.6139
                                       45

-------
                                   TABLE 25

                            308 Questionnaire Data
                                    Plant I
                              Reported                   Actual
Pollutant               Concentration (ug/1)     Concentration (ug/l)(l)

Arsenic                             10                      46

Cadmium                              3                      14

Chromium (Total)                   340                   1,571

Copper                              70                     323

Nickel                              50                     231

Selenium                       .     12                      55

Silver            .                  40                     18.5

TCDD(2)                             26                     120
(1) Adjusted concentrations were generated through a mass balance, using the
    reported concentrations for combined process and dilution waters; and
    calculating an actual process water concentration through the use of a
    term designated as the dilution factor.  The dilution factor was calcula-
    ted by dividing dilution water flow by the process flow.  The equation
    developed is as follows:  Actual Concentration - Reported Concentration (1
    + Dilution Factor)

        The dilution factor for this facility is 3.620

(2) 2,3,7,8-Tetrachlorodibenzo-p-dioxin
                                       46

-------
                                   TABLE 26

                            308 Questionnaire Data
                                    Plant J
                             Reported                    Actual
Pollutant               Concentration (ug/1)     Concentration (ug/1)  (1)

Cyanide (Total)                  366                         4,416
Mercury                          300                         3,620
Selenium                         100                         1,207
Thallium                         400                         4,826
Antimony                        <110                         1,328
Beryllium                       <110                         1,328
Cadmium                         <110                         1,328
Chromium                        <110                         1,328
Copper                          <110                         1,328
Lead                            <110                         1,328
Nickel                          <110                         1,328
Silver                          <100                         1,207
Zinc    .                        <110       .                  1,328
2,4-Dinitrophenol   .          • <250                 .        3,016
4,6-Dinitro-o-cresol         •   <250                         3,016
Priority Pollutant Organics(2)   <10                           121
Priority Pollutant Organics(3)   <25                           302
(1) Adjusted concentrations were generated through a mass balance, using the
    reported concentrations for combined process and dilution waters; and
    calculating an actual process water concentration through the use of a
    term designated as the dilution factor.  The dilution factor was calcula-
    ted by dividing dilution water flow by the process flow.  The equation
    developed is as follows:  Actual Concentration » Reported Concentration (1
    + Dilution Factor)

        The dilution factor for this facility is 11.065

(2) Pollutants are presented in Appendix A.

(3) Pollutants are presented in Appendix A.
                                       47

-------
                                   TABLE 27

                            308 Questionnaire Data
                                    Plant K
                             Reported                    Actual
Pollutant               Concentration (ug/1)     Concentration (ug/l)(l)

Barium                             100                        3,465
Iron                               580                        20,998
Magnesium                          520                        18,019
Manganese                           50                        1,733
NO  as N                           100                        3,465
NOl: as N                           900                        31,186
Oil & Grease                     1,400                        48,512
Phosphorous                        280                        9,702
SO,                             29,000                     1,004,894
Total Kjeldahl Nitrogen          1,200                        41,582
TOG                             23,000                       796,985
1,1,1-Trichloroethane                9                           312
Cadmium                              0.9    .                      31
Chromium (Total)                     1.1        '                  38
Copper    .                           6.5                         225
Benzene                              9                           312
N-nitrosodiphenylamine               1                            35
Phenol                               8                           277
Bis(2-ethylhexyl)phthalate           4                           139
Diethyl phthalate                    0.1                           4
(1) Adjusted concentrations were generated through  a mass  balance,  using  the
    reported concentrations for combined process and dilution waters;  and
    calculating an actual  process water concentration  through the use  of  a
    term designated  as  the dilution  factor.  The dilution  factor was calcula-
    ted by dividing  dilution water flow by the process flow.   The equation
    developed  is  as  follows:   Actual Concentration  - Reported Concentration (1
    + Dilution Factor)

        The dilution factor for this facility is 33.6515
                                        48

-------
                                   TABLE 28

                            308 Questionnaire Data
                                    Plant L
                             Reported                    Actual
Pollutant               Concentration (ug/1)     Concentration (ug/l)(l)

BOD5                            16,000                    984,640

COD                             25,000                  1,538,500

TSS                             12,000                    738,480

Phenol                              15                        923
(1) Adjusted concentrations were generated through a mass balance, using the
    reported concentrations for combined process and dilution waters; and
    calculating an actual process water concentration through the use of a
    term designated as the dilution factor.  The dilution factor was calcula-
    ted by dividing dilution water flow by the process flow.  The equation
    developed is as follows:  Actual Concentration = Reported Concentration (1
    + Dilution Factor)

        The dilution factor for this facility is 60.54
                                        49

-------
                                 APPENDIX A

              Pollutants  Reported at  or  below Levels  of  Detection
    Industrial  Facility                          Pollutants'1)

    Plant E                            1-8;  10-16;  18-26;  28-49;  51-85;  87;
                                       89-113;  117;  121;  123;  126
    Plant J                            1;  4;  5;  7-30;  32;  33;  35-56;  61-63;
     Reported as  <10  ug/1              66-78;  80;  81;  84-113

     Reported as  <25  ug/1              31; 34;  57;  58;  64;  65;  79; 82;  83
(1) Pollutants are presented by number in Appendix C
                                    50

-------
                                   APPENDIX B

                  Limits of Detection for Priority Pollutants
                                                        Detection Limit (ug/1)
                                                                Plant
Code No^              Pollutants                             114     2531

   1      Acenaphthene                                        10      <10
   2      Acrolein                                           100
   3      Acrylonitrile                                      100
   4      Benzene                                             10      <10
   5      Benzidene                                           10      <10

   6      Carbon tetrachloride (tetrachloromethane)           10.
   7      Chlorobenzene                                       10      <10
   8      1,2,4-trichlorobenzene                              10      <10
   9      Hexachlorobenzene                                   -       <10
  10      1,2-dichloroethane                                  10      <10
  11      1,1,1-trichloroethane                               10      <10
  12      Hexachloroethane     *                              10      <10
  13      1,1-dichloroethane                                  10      <10
  14      1,1,2-trichloroethane                               10      <10
  15      1,1,2,2-tetrachloroethane                           10      <10
  16      Chloroethane                                        10      <10
  17*     bi*-4ehierometh7i-)-ether                             -      <10
  18      Bis (2-chloroethyl) ether                           10      <10
  19      2-chloroethyl vinyl ether (mixed)                   20      <10
  20      2-chloronaphthalene                                 10      <10
  21      2,4,6-trichlorophenol                               25      <10
  22      Para-chloro meta-cresol                             25      <10
  23      Chloroform (trichloromethane)                       10      <10
  24      2-chlorophenol                                      25      <10
  25      1,2-dichlorobenzene                                 10      <10
  26      1,3-dichlorobenzene                                 10      <10
  27      1,4-dichlorobenzene                                 -       <10
  28      3,3'-dichlorobenzidine                              10      <10
  29      1,1-dichloroethylene                                10      <10
  30      1,2-trans-dichloroethylene                          10      <10
  31      2,4-dichlorophenol                                  25      <25
  32      1,2-dichloropropane                                 10      <10
  33      1,3-dichloropropylene (1,3-dichloropropene)         10      <10
  34      2,4-dimethylphenol                                  25      <25
  35      2,4-dinitrotoluene                                  10      <10
  36      2,6-dinitrotoluene                                  10      <10
  37      1,2-diphenylhydrazine	^-10-    <10
  38      Ethylbenzene                                        10      <10
  39      Fluoranthene                                        10      <10
  40      4-chlorophenyl phenyl ether                         10      <10
  41      4-bromophenyl phenyl ether                          10      <10
  42      Bis (2-chloroisopropyl)  ether                       10      <10
  43      Bis (2-chloroethoxy) methane                        10      <10
  44      Methylene chloride (dichloromethane)                10      <10


 * Delisted  46 FR 10723

-------
                              APPENDIX B (Cont.)
                                                        Detection Limit (ug/1)
                                                                Plant
Code No.              Pollutants                             114     2531

  45      Methyl chloride (chloromethane)                     10      <10
  46      methyl bromide (bromomethane)                       10      <10
  47      Bromoform (tribromemethane)                         10      <10
  48      Dichlorobromomethane                                10      <10
 49**     Trichlorofluoromethane                              10      <10

 50**     Dichlorodifluoromethane                             -       <10
  51      Chlorodibromomethane                                10      <10
  52      Hexachlorobutadiene                                 10      <10
  53      Hexachlorocyclopentadiene                           10      <10
  54      Isophorone                                          10      <10
  55      Naphthalene                                         10      <10
  56      Nitrobenzene                                        10      <10
  57      2-nitrophenol                                       25      <25
  58      4-nitrophenol                                       25      <25
  59      2,4-dinitrophenol                                   25
  60      4,6-dinitro-o-cresol                               250
  61      N-nitrosodimethylamine                              10      <10
  62      N-nitrosodiphenylamine                              10      <10
  63      N-nitrosodi-n-propylamine                           10      <10
  64      Pentachlorophenol                                   25      <25
  65      Phenol                                              25      <25
  66      Bis (2-ethylhexyl) phthalate                        10      <10
  67      Butyl benzyl phthalate                              10      <10
  68      Di-n-butyl phthalate                                10      <10
  69      Di-n-octyl phthalate                                10      <10
  70      Diethyl phthalate                                   10,     <10
  71      Dimethyl phthalate                                  10      <10
  72      Benzo (a)anthracene (1,2-benzanthracene)            10      <10
  73      Benzo (a)pyrene (3,4-benzopyrene)                   10      <10
  74      3,4-benzofluoranthene                               10      <10
  75      Benzo(k)fluoranthene  (11,12-benzofluoranthene)      10      <10
  76      Chrysene                                            10      <10
  77      Acenaphthylene                          .            10      <10
  78      Anthracene                                          10      <10
  79      Benzo(ghi)perylene (1,12-benzoperylene)             25      <25
  80      Fluorene                                            10      <10
  81      Phenanthrene                                        10      <10
  82      Dibenzo  (a,h)anthracene
             (1,2,5,6-dibenzanthracene)                        25      <25
  *83      Indeno (1,2,3-cd)pyrene  (2,3-o-phenylenepyrene)     25      <25
  84      Pyrene                                              10      <10
  85      Tetrachloroethylene                                 10      <10
  86      Toluene                                             -       <10
  87      Trichloroethylene                                   10      <10
  88      Vinyl chloride  (chloroethylene)                      -      <10
  89      Aldrin                                              10      <10


 **  Delisted  46  FR  2266              52

-------
                              APPENDIX B (Cont.)
Code No.              Pollutants                             	

 90       Dieldrin                                            10
 91       Chlorodane (technical mixture and metabolities)     10
 92       4,4'-DDT                                            10
 93       4,4'-DDE (p.p'DDX)                                  10
 94       4,4'-DDD (p.p'TDE)                                  10
 95       A-endosulfan-Alpha                                  10
 96       A-endosulfan-Beta                                   10
 97       Endosulfan sulfate                                  10
 98       Endrin                                              10
 99       Endrin aldehyde                                     10
 100      Heptachlor                                          10
 101      Reptachlor epoxide                                  10
 102      A-BHC-Alpha         .                                10
 103      B-BHC-Beta                                          10
 104      R-BHC (lindane)-Gamma                               10*.
 105      G-BHC-Delta                                         10
 106      PCB-1242 (Arochlor 1242)                            10
 107      PCB-1254 (Arochlor 1254)                            10
 108      PCB-1221 (Arochlor 1221)                            10
 109      PCB-1232 (Arochlor 1232)                            10
 110      PCB-1248 (Arochlor 1248)                            10
 111      PCB-1260 (Arochlor 1260)                            10
 112      PCB-1016 (Arochlor 1016)                            10
 113      Toxaphene                                           10
 114      Antimony
 115      Arsenic
 116      Asbestos (Fibrous)
 117      Beryllium                                            1
 118      Cadmium
 119      Chromium (Total)
 120      Copper
 121      Cyanide (Total)                                     50
 122      Lead
 123      Mercury                                              5
 124      Nickel
 125      Selenium
 126      Silver                                               1
 127      Thallium
 128      Zinc
 129      2,3,7,8-tetrachlorodibenzo-p-dioxirv(TCDD)
Detection Limit (ug/1)
        Plant
     114     2531
                                     53

-------
                                 APPENDIX C

                    List of 129 Priority Toxic Pollutants
   Code No.

       1
       2
       3
       4
       5
       6
       7
       8
       9
      10
      11
      12
      13
      14
      15
      16
      17*
      18
      19
      20
      21
      22
      23
      24
      25
      26
      27
      28
      29
      30
      31
      32
      33
      34
      35
      36
      37
      38
      39
      40
      41
      42
      43
      44
      45
      46
          Pollutant

Acenaphthene
Acrolein
Acrylonitrile
Benzene
Benzidene
Carbon tetrachloride ( tetrachloromethane)
Chlorobenzene
1 ,2,4-trichlorobenzene
Hexachlorobenzene
1 ,2-dichloroethane
1 ,1 ,1-trichloroethane
Hexachloroe thane
1 ,1-dichloroethane
1 ,1 ,2-trichloroethane
1,1,2,2-tetrachloroethane
Chloroethane
Bis (2-chloroethyl) ether
2-chloroethyl vinyl ether  (mixed)
2-chloronaphthalene
2 ,4 ,6-tr ichlorophenol
Para-chloro meta-cresol
Chloroform (trichloromethane)
2-chlorophenol
1 ,2-dichlorobenzene
1 ,3-dichlorobenzene
1 ,4-dichlorobenzene
3,3' -dichlorobenzidine
1 ,1-dichloroethylene
1 ,2-trans-dichloroethylene
2 ,4-dichlorophenol
1 ,2-dichloropropane
1 ,3-dichloropropylene  (1 ,3-dichloropropene)
2, 4-dimethyl phenol
2 ,4-dinitrotoluene
2 , 6-dinitrotoluene
1 ,2-diphenylhydrazine
Ethylbenzene
Fluoranthene
4-chlorophenyl  phenyl  ether     — ._^~—---
4-bromopffenyl phenyl ether
Bis (2-chloroisopropyl)  ether
Bis (2-chloroethoxy) methane
Methylene chloride  (dichloromethane)
Methyl chloride (chloromethane)
methyl bromide  (bromome thane)
* Delisted 46 FR 10723
                                     54

-------
                                APPENDIX C (Cont.)


    Code  No.                    Pollutant

      47            Bromoform (tribrometnethane)
      48            Dichlorobromomethane
      49**           Trichlorofluoromethane
      50**           Dichlorodifluoromethane
      51            Chlorodibromomethane
      52            Hexachlorobutadiene
      53            Hexachlorocyclopentadiene
      54            Isophorone
      55            Naphthalene
      56            Nitrobenzene
      57            2-nitrophenol
      58            4-nitrophenol
      59            2,4-dinitrophenol
      60            4,6-dinitro-o-cresol
      61            N-nitrosodimethylamine
      62            N-nitrosodiphenylamine
      63            N-nitrosodi-n-propylamine -                 •
      64            Pentachlorophenol
      65            Phenol
      66            Bis (2-ethylhexyl) phthalate
      67            Butyl benzyl phthalate
      68            Di-n-butyl phthalate
      69            Di-n-octyl phthalate
      70            Diethyl phthalate
      71            Dimethyl phthalate
      72            Benzo (a)anthracene (1,2-benzanthracene)
      73            Benzo (a)pyrene (3,4-benzopyrene)
      74            3,4-benzofluoranthene
      75            Benzo(k)fluoranthene (11,12-benzofluoranthene)
      76            Chrysene
      77            Acenaphthylene
      78            Anthracene
      79            Benzo(ghi)perylene (1,12-benzoperylene)
      80            Fluorene
      81            Phenanthrene
      82            Dibenzo (a,h)anthracene (1,2,5,6-dibenzanthracene)
      83            Indeno (1,2,3-cd)pyrene (2,3-o-phenylenepyrene)
      84            Pyrene
      85            Tetrachloroethylene
      86            Toluene
      87            Trichloroethylene
      88            Vinyl chloride (chloroethylene)
      89            Aldrin
      90            Dieldrin
      91            Chlorodane (technical mixture  and metabolities)
** Delisted 46 FR 2266
                                     55

-------
                          APPENDIX C (Cont.)


Code No.                   Pollutant

   92            4,4'-DDT
   93            4,4'-DDE (p.p'DDX)
   94            4,4'-DDD (p.p'TDE)
   95            A-endosulfan-Alpha
   96            A-endosulfan-Beta
   97            Endosulfan sulfate
   98            Endrin
   99            Endrin aldehyde
  100            Heptachlor
  101            Heptachlor epoxide
  102     -       A-BHC-Alpha
  103            B-BHC-Beta
  104            R-BHC (lindane)-Gamma
  105            G-BHC-Delta
  106            PCB-1242 (Arochlor 1242)
  107            PCB-1254 (Arochlor 1254)
  108          •  PCB-1221 (Arochlor 1221)
  109            PCB-1232 (Arochlor 1232)
  110            PCB-1248 (Arochlor 1248)
  111            PCB-1260 (Arochlor 1260)
  112            PCB-1016 (Arochlor 1016)
  113            Toxaphene
  114            Antimony
  115            Arsenic
  116            Asbestos (Fibrous)
  117            Beryllium
  118            Cadmium
  119            Chromium (Total)
  120            Copper
  121            Cyanide  (Total)
  122            Lead
  123            Mercury
  124            Nickel
  125            Selenium
  126            Silver
  127            Thallium
  128            Zinc
  129            2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)
                                 56

-------
VII.  CALCULATION OF PRIORITY POLLUTANT WASTE LOADS

-------
         VII.  CALCULATION OF PRIORITY POLLUTANT WASTE LOADS
                          Table of Contents
1.    Introduction                                                    1
2.    Methodology for Waste Load Calculation                          2
3.    Pollutant Concentration Data                                   13
3.1      308 Questionnaire Data                                      15
3.2      Screening Phase I                                           17
3.3      Screening Phase II                                          19
3.4      Verification Program                                        19
4.    Flow Data                                                      26
5.    Waste Load Calculation                                         27
5.1      BTP, BAT, and Current Waste Load Calculations               29
5.2      PSES Waste Load Calculations                                32
5.3      Annualized Waste Load                                       32
6.    Raw Waste Load Validation                                      34
      Appendix A: . Summary Loading Tables

-------
             VII.  CALCULATION OF PRIORITY POLLUTANT WASTE LOADS
                                List of Tables



Table                                                                   Page

1        Major Products by Process of the Organic Chemicals  Industry     4

2        Major Products by Process of the Plastics/Synthetic Fibers
         Industry                                                       11

3        Generic Chemical Processes                                     14

4        Overview of Wastewater Studies Included  in BAT Raw
         Wastestream Data Base                                          16

5        Phase II Screening - Product/Process  and Other Waste
         Streams Sampled at Each Plant                            '     20

6        Selection Criteria for Testing Priority  Pollutants  in
         Verification Samples                                           24

-------
             VII.   CALCULATION OF  PRIORITY POLLUTANT WASTE LOADS









                               List  of Exhibits









Exhibit                                                                Page






1        Raw Waste Load Calculation  Logic Flow                           30




2        BPT, BAT, and Current Waste Load Calculation Logic Flow         31




3        PSES Waste Load Calculation                                    33

-------
             VII.  CALCULATION OF PRIORITY POLLUTANT WASTE LOADS

1.  INTRODUCTION

     Plants within the Organic Chemical and Plastics/Synthetic Fibers indus-
tries use water for a wide variety of purposes:  direct process contact uses
(e.g., waste streams from reactors, raw material recovery, solvent recovery,
product separation and refining); indirect process contact uses (e.g., in
pumps, seals, and vacuum jet and steam ejector systems); maintenance, equip-
ment cleaning, work area washdowns; air pollution control; waste transport;
noncontact cooling; and noncontact ancilliary uses (e.g., boilers and
utilities).  With the exception of noncontact waters, wastewater from these
industries is potentially contaminated to a greater or lesser degree with
priority pollutants.  Because the Organic Chemicals and Plastics/Synthetic
Fibers (OCPSF) industry use large amounts of water in the manufacture of
products (~ 17 percent of the total water consumed by all manufacturing
establishments in 1978) these industries generate raw wastewaters that
contain significant concentrations of priority pollutants.

     Most of this wastewater receives some treatment to reduce pollutant con-
centrations prior to environmental discharge, either as an individual process
wastestream or in a wastewater treatment plant serving combined wastestreams
from the entire facility.  To determine what pollutants merit regulation, as
well as determining the costs and benefits of removing regulated priority
pollutants, the Agency has acquired extensive analytical data on priority
pollutant concentrations in industry wastewaters.

     In principle, there are a variety of ways by which priority pollutant
loads may be estimated.  Previously, the Agency had estimated raw, current,
projected BPT effluent, projected PSES effluent and projected BAT effluent
priority pollutant waste loadings for the entire OCPSF industrial category
using data developed as part of the Regulatory Impact Analysis of these
proposed regulations.  These data are presented in the February 18,  1983,
draft report from EPA's Office of Water Regulations and Standards, Monitoring
and Data Support Division (MDSD), entitled "Summary of Priority Pollutant
Loadings for the Organic Chemicals, Plastics, and Synthetics Industry."
                                     -1-

-------
     The MDSD draft report estimated raw, current, projected BPT, projected
PSES and projected BAT effluent waste loadings for the OCPSF industry based
on 176 product/processes that account for ~ 60% of the industry production.
The Agency then extrapolated these loadings by flow to cover all the product/
processes comprising OCPSF production, as follows:  the MDSD flow estimates
for the 176 product/processes were 222.4 MGD for direct dischargers and 96.6
MGD for indirect dischargers.  Assuming 520 direct dischargers at 2.31 MGD
each, total industry direct discharge flow is 1,201.2 MGD.  Assuming 468
indirect dischargers at 0.80 MGD each, total industry indirect discharge
flow is 374.4 MGD.  The direct waste loads for the total industry were esti-
mated by multiplying the MDSD waste loads for the 176 product/processes by
1,201.2/222.4 = 5.40.  The indirect waste loads for the total industry were
estimated by multiplying the MDSD waste loads for the 176 product/processes
by 374.4/96.6 = 3.88.

     This analysis was shown to overestimate annual toxic pollutant discharges
based upon information received by the Agency after proposal.  Upon the
receipt of 1983 "308" questionnaire data, the Agency determined that calcula-
tion of plant-specific toxic pollutant waste loads was practicable.

     The Agency has estimated raw, current, projected BPT effluent, projected
PSES effluent, and projected BAT effluent priority pollutant waste loadings
for the OCPSF industries.  These loadings have been calculated on a plant-by-
plant basis using both industry generated data (i.e., 1983 "308" questionnaire
data) as well as analytical data acquired by the Agency in various sampling
studies.  OCPSF industry waste loadings are presented in Appendix A.  The
following sections briefly describe the methodology used to calculate waste
loads from the OCPSF industries.

2.  METHODOLOGY FOR WASTE LOAD CALCULATION	r~~~-

     This section presents the approach taken by  the Agency for waste load
calculations.  A general methodology is presented first.  Analytical data for
                                     -2-

-------
toxic pollutants are discussed next.  Flow data and the assumptions used  to
calculate product/process flow are presented.  Plant specific waste load
calculations are presented last.

     There are four distinct levels at which toxic pollutant waste loads  from
a plant can be calculated.  The first level is at an aggregated product/process
level (or plant level) where wastestreams from several processes are combined.
If toxic pollutant concentration and flow are known for the aggregate raw
wastestream (i.e., prior to any treatment that may affect toxic pollutant
removal) and the final wastestream (after the current treatment system),
then both raw and current waste loads may be calculated as:
     RWLt =

     CWLe = [Pe]Fe

where RWL^ * raw' waste load for a pollutant
      CWLe = current waste load for a pollutant
      [P^] * concentration of a pollutant in raw wastewater
      [Pe] = concentration of a pollutant in final discharge
        F^ = raw wastewater flow
        Fe = final discharge wastewater flow.

If more than one aggregated wastewater stream exists at a plant, toxic pollu-
tant loadings are summed to determine the total waste load.

     The second level at which toxic pollutant waste loads from a plant can
be calculated is at a product/process or production unit level.   The Agency
has sampled the raw wastewaters of 176 product/processes employed by the
OCPSF industries to produce high production volume organic chemicals, plastics,
and synthetic fibers.  These processes (see Tables 1 and 2) comprise approxi-
mately 60% of the OCPSF industries'  total production.  This collection of
product/process data is known as the Master Process File (MPF) (see Appendix B)
                                     -3-

-------
    TABLE 1.   MAJOR PRODUCTS BY PROCESS OF THE ORGANIC CHEMICALS INDUSTRY
  PRODUCT
         PROCESS (FEEDSTOCK)
Acetaldehyde


Acetic Acid
Acetic Anhydride

Acetone


Acetonitrile

Acetylene



Acrolein

Acrylamide
Acrylic Acid Esters

   Ethyl Acrylate

   Ethylhexyl Acrylate

   Isobutyl Acrylate

   n-Butyl Acrylate

Acrylonitrile

Adipic Acid



Adiponitrile



Alkyl Amines
By-product (Acrolein/Propene/Oxidation)
Oxidation (Ethene)

By-product (Polyvinyl Alcohol)
Carbonylation (Methanol)
Co-product (Terephthalic Acid)
Oxidation (Acetaldehyde)
Oxidation (Butane)

Addition (Acetic Acid/Ketene)

Oxidation (Isopropanol/H202)
Peroxidation/Acid Cleavage (Cumene)

By-product (Acrylonitrile/Ammoxidation/Propene)

By-product (Propane Pyrolysis)
Hydrolysis (Calcium Carbide)
Oxidation (Methane)            .

Oxidation (Propene)

Hydration (Acrylonitrile)
Formlyation/Hydration (Acetylene/Carbon
   Monoxide/Water)
Oxidation (Acrolein)
Oxidation (Propene)

Esterification (Miscellaneous Alcohols)

Esterification (Acrylic Acid/Ethanol)

Esterification (Acrylic Acid/2-Ethylhexanol)

Esterification (Acrylic Acid/Isobutanol)

Esterification (Acrylic Acid/n-Butanol)

Ammoxidation (Propene)

Oxidation (Cyclohexane)
Oxidation (Cyclohexanol)
Oxidation (Cyclohexanone)

Ammonolysis/Dehydration (Adipic Acid)
Chlorination/Cyanation (Butadiene)
Electrohydrodimerization (Acrylonitrile)

Hydrogenation (Fatty Nitriles)
                                      -4-

-------
    TABLE 1.  MAJOR PRODUCTS BY PROCESS OF THE ORGANIC CHEMICALS INDUSTRY
                                 (Continued)
  PRODUCT
          PROCESS  (FEEDSTOCK)
Alkyi Phenols

Allyl Alcohol

Amyl Acetates

Aniline

Benzene
Benzoic Acid

Benzyl Alcohol

Benzyl Chloride

Bisphenol-A

BTX

1,3-Butadiene

Butenes

n-Butyl Alcohol

sec-Butyl Alcohol

Caprolactam

Carbon Tetrachloride
Cellulose Butyrates

Cellulose Acetate/Propionate

Chlorobenzene

Chlorodifluoromethane

Chloroform


3-Chloronitrobenzene
 Alkylation (Phenol)

 Reduction  (Acrolein/Aluminum Butoxide)

 Esterification (Acetic  Acid/Amyl Alcohols)

 Hydrogenation  (Nitrobenzene)

 Distillation (BTX Extract  Cat Reforraate)
 Distillation (BTX Extract  -  Coal Tar  Light  Oil)
 Distillation (BTX Extract  -  Pyrolysis Gasoline)
 Hydrodealkylization  (Toluene/Xylene)

 Oxidation  (Toluene)

 Hydrolysis (Benzyl Chloride)

 Chlorination (Toluene)

.Condensation' (Acetone/Phenol)           •   -   •

 Pyrolysis  (Gasoline)

 Extractive Distillation (C-4  Pyrolyzates)

 Extractive Distillation (C4  Pyrolyzates)

 Hydrogenation  (n-Butyraldehyde/Oxo Process)

 Hydration  (Butenes)

 Rearrangement  (Cyclohexanone  Oxirae)

 Chlorination (Carbon  Disulfide)
 Chlorination (Methane)
 Chlorination (Methyl  Chloride)
 Co-product (Tetrachloroethene)

 Esterification (Cellulose)

 Esterification (Cellulose)

 Chlorination (Benzene)

 Hydrofluorination (Chloroform)

 Chlorination (Methane)
 Chlorination (Methyl  Chloride)

 Chlorination (Nitrobenzene)
                                     -5-

-------
    TABLE 1.   MAJOR PRODUCTS BY PROCESS OF THE ORGANIC CHEMICALS INDUSTRY
                                 (Continued)
  PRODUCT
         PROCESS (FEEDSTOCK)
Coal Tar

Creosote

Cumene

Cyclohexane

Cyclohexanol/One (Mixed)

Cyclopentadiene Dimer

1,2-Dichlorobenzene

1,4-Dichlorobenzene

Dichlorodifluoromethane

1,2-Dichloroethane


Diethylene Glycol

Diisopropyl Benzene

Diketene

Dimethyl Terephthalate


Dinitrotoluene (Mixed)

Dyes and Dye Intermediates

Epichlorohydrin

Ethanol

Ethoxylates, Alkylphenol

Ethoxylates, Alkyl

Ethylamine

Ethylbenzene


Ethene
Coking (Coal)

Distillation (Coal Tar Light Oil)

Alkylation (Benzene/Propene)

Hydrogenation (Benzene)

Oxidation (Cyclohexane)

Extractive Distillation (C5 Pyrolyzates)

Chlorination (Benzene)

Chlorination (Benzene)

Hydrofluorination (Carbon Tetrachloride)

Direct Chlorination- (Ethene)
Oxychlorination (Ethene)

Co-product (Ethylene Glycol)

Alkylation of Benzene (Cumene)

Dimerization (Ketene/Acetic Acid)

Esterification (Terphthallic Acid)
Oxidation/Esterification (P-Xylene)

Nitration (Toluene)
Epoxidation  (Allyl Chloride/Chlorohydrination)

Hydration (Ethene)

Etherification  (Phenol/Ethylene Oxide)

Etherification  (Linear Alcohols/Ethlene Oxide)

Ammonolysis  (Ethanol)

Alkylation (Benzene)
Distillation (BTX Extract)

Pyrolysis (Ethane/Propane/Butane/LPG)
Pyrolysis (Naphtha/Gas Oil)
Pyrolysis (Ethane/Propane/Butane/Naphtha)
                                     -6-

-------
    TABLE 1.  MAJOR PRODUCTS BY PROCESS OF THE ORGANIC CHEMICALS INDUSTRY
                                 (Continued)
  PRODUCT
           PROCESS (FEEDSTOCK)
Ethylene Diamine

Ethylene Glycol

Ethylene Oxide


2-Ethylhexanol

Formaldehyde

Formic Acid

Glycerine (Synthetic)


Hexaraethylenediamine


Hydroquinone

Hydroxyethyl Cellulose

Hydroxypropyl Cellulose

Isobutanol

Isobutylene


Isoprene

Isopropanol

Maleic Anhydride

Methacrylic Acid

Methacrylic Acid Esters

Methanol
Methyl Chloride
Methyl Ethyl Ketone
  Amination (1,2-Dichloroethane)

  Hydrolysis (Ethylene Oxide)

  Epoxidation (Ethylene Chlorohydrin)
  Oxidation (Ethene)

  Condensation/Hydrogenation (n-Butaldehyde)

  Oxidation (Methanol-Silver Catalyst)

  By-product (Butane  Oxidation)

  Hydration (Allyl Alcohol)
  Hydrolysis (Epichlorohydrin)

  Depolymerization (Nylon 66)
  Hydrogenation (Adiponitrile)

•  Oxidation (Aniline)

  Etherification (Cellulose)

  Etherification (Cellulose)

  Hydrogenation (Isobutyraldehyde-Oxo  Process)

  Dehydration (tert-Butanol)
  Extraction (C4 Pyrolyzate)

  Extractive Distillation (C5  Pyrolyzate)

  Hydration (Propene)

  Oxidation (Benzene)

  Hydrolysis (Acetone Cyanohydrin)

  Esterification (Methacrylic  Acid/Alcohols)

  Oxidation (H.P. Synthesis  Natural Gas/Synthetic
     Gas)
  Oxidation (L.P. Synthesis  Natural Gas/Synthetic
     Gas)

  Chlorination (Methane)
  Hydrochlorination (Methanol)

  Reduction (Acrolein/Aluminum Butoxide)
                                     -7-

-------
    TABLE 1.  MAJOR PRODUCTS BY PROCESS OF THE ORGANIC CHEMICALS INDUSTRY
                                 (Continued)
  PRODUCT
         PROCESS (FEEDSTOCK)
Methyl Isobutyl Carb'inol

Methyl Isobutyl Ketone

Methyl Methacrylate

Methyl Salicylate

Methylamines

Methylene Chloride


Methylstyrene

Naphthalene


Neopentanbic Acid .

Nitrobenzene

4-Nitrophenol & Sodium Salt

Nonyl Phenol

Nylon Salt

"Oxo Aldehydes/Alcohols

Pentachlorophenol

Phenol

Phosphate Esters
Phthalate Ester, Bis
   2-Ethylhexyl

   Butylbenzyl
   C11-C14

   Diethyl

   Diphenyl
Condensation (Acetone)

Hydrogenation (Mesityl Oxide)

Methanolysis (Acetone Cyanohydrin)

Esterification (Salicylic Acid)

Ammination (MethanoI/Ammonia)

Chlorination (Methane)
Chlorination (Methyl Chloride)

By-product (Acetone/Phenol by Curaene Oxidation)

Distillation (Pyrolysis Gas)
Separation (Coal Tar Distillate)

Oxidation (Isobutylene Via Oxo Process)

Nitration (Benzene)

Nitration (Phenol)

Alkylation (Phenol)

Condensation (Adipic Acid/Hexamethylene Diamine)

Oxidation (Hydrocarbons - Oxo Process)

Chlorination (Phenol)

Peroxidation/Acid Cleavage (Curaene)

Phosgenation (Phosphoryl Chloride/Phenol/
   Isodecanol)

Alcoholysis (Phthalic Anhydride/2-Ethylhexanol)


Alcoholysis (Phthalic Anhydride/Butanol/
   Benzylchloride)

Alcoholysis (Phthalic Anhydride/Cll-C14 Alcohols)

Alcoholysis (Phthalic Anhydride/Ethanol)

Esterification (Phenol/Phthalyl Chloride)
                                     -8-

-------
    TABLE L.  MAJOR PRODUCTS BY PROCESS OF THE ORGANIC CHEMICALS INDUSTRY
                                 (Continued)
  PRODUCT	PROCESS (FEEDSTOCK)	

Phthalic Anhydride .            Oxidation (Naphthalene)
                               Oxidation (o-Xylene)

Pitch Tar Residue              Separation (Coal Tar Light Oil distillate)

Polyethylene Glycol            Polymerization (Ethylene Oxide)

Polyethylene Polyamines        Amination (Ethylene Diamine/2,3-Dichloroethane/
                                  NH3)

Polymeric Methylene Dianiline  Condensation (Aniline/Formaldehyde)

Polymeric Methylene Diphenyl   Phosgenation (Polymethylene Dianiline)
   Diisocyanate

Polyoxyethylene Glycol         Condensation (Propylene Glycol/Propylene Oxide)

Polyoxypropylene Glycol        Propoxylation (Glycerine)

Propene                      '  Pyrolysis (Ethane/Propane/Butane/LPG)
                               Pyrolysis (Naphtha and/or Gas Oil)
                               Pyrolysis (Naphtha, Propane, Ethane, Butane)

Propionaldehyde                Hydroformylation (Ethene-Oxo Process)

Propionic Acid                 Oxidation (Propionaldehyde)

n-Propyl Acetate               Esterification (Acetic Acid/Propanol)

n-Propyl Alcohol               Hydrogenation (Propionaldehyde)

Propylene Oxide                Epoxidation (Propene via Chlorohydrin)

Salicylic Acid                 Carboxylation (Sodium Phenolate)

Styrene                        Dehydrogenation (Ethylbenzene)

Terephthalic Acid    '          Catalytic Oxidation (p-Xylene)

Tetrachloroathene              Chlorination (1,2-Dichloroethane/Other
                                  Chlorinated Hydrocarbons)
                               Chlorination (Acetylene)
                               Chlorination (Hydrocarbons)

Tetrachlorophthalic Anhydride  Chlorination (Phthalic Anhydride)

Tetraethlene Glycol            Co-product (Ethylene Glycol)

Tetraethyl Lead                Alkylation (Ethyl Chloride/Sodium-Lead Alloy)
                                     -9-

-------
    TABLE 1.  MAJOR PRODUCTS BY PROCESS OF THE ORGANIC CHEMICALS INDUSTRY
                                 (Continued)
  PRODUCT
         PROCESS (FEEDSTOCK)
Tetramethyl Lead

Toluene



Toluenediamine (Mixture)

2,4-Toluenediamine

Toluene Diisocyanates
   (Mixture)

2,4-Toluene Diisocyanate

Trichloroethene



Trichlorofluoromethane

Triethylene Glycol


Vinyl Acetate
Vinyl Chloride



Vinylidene Chloride

Xylenes, Mixed




m-Xylene

o-Xylene

p-Xylene
Alkylation (Methyl Chloride/Sodium-Lead Alloy)

Distillation (BTX Extract - Cat Reformate)
Distillation (BTX Extract - Coal Tar Light Oil)
Distillation (BTX Extract - Pyrolysis Gasoline)

Hydrogenation (Dinitrotoluenes)

Hydrogenation (Dinitrotoluene)

Phosgenation (Toluenediamines)


Phosgenation (2,4-Toluenediamine)

Chlorination (1 ,.2-Dichloroethane/Other
   Hydrocarbons)
Chlorination (Acetylene)

Hydrofluorination (Carbon Tetrachloride)

Co-product (Ethylene Glycol/Ethylene Oxide)
Recovery from Ethylene Glycol Still Bottoms

Esterification (Acetylene/Acetic Acid
Esterification (Ethene/Acetic Acid.Gas Phase)
Esterification (Ethene/Acetic Acid Liquid
   Phase)

Dehydrochlorination (1,2-Dichloroethane)
Dehydrochlorination (1,2-Dichloroethane -
   Balanced Process)

Dehydrochlorination (Trichloroethane)

Extraction (Cat Reformate)
Extraction (Coal Tar Light Oil)
Extraction (Pyrolysis Gasoline)
Separation (Xylene Bottoms)

Fractionation (Mixed Xylenes)

Distillation (Mixed Xylenes)

Isomerization/Crystallization (Mixed Xylenes)
                                     -10-

-------
TABLE 2.  MAJOR PRODUCTS BY PROCESS OF THE PLASTICS/SYNTHETIC FIBERS  INDUSTRY
  PRODUCT
         PROCESS (FEEDSTOCK)
ABS Resin

ABS/San Resin

Acrylic Fiber
   (85% Polyacrylonitrile)

Acrylic Latex

Acrylic Resins

Alkyd Resins

Cellulose Acetate Fibers

Cellulose Acetate Resin

Epoxy Resins
Melamine Resins

Modacrylic Fiber

Nylon 6 Resin

Nylon 66 Resin

Petroleum Hydrocarbon Resins

Phenolic Resins

Polycarbonates

Polyester Fibers


Polyester Resins


Polyethylene Resins


Polypropylene Resin
Emulsion Polymerization

Emulsion/Suspension Polymerization

Suspension Polymerization - Wet Spinning


Emulstion Polymerization

Solution Polymerization

Condensation/Polymerization

Spinning from Acetylated Cellulose

Acetylation (Cellulose)

Condensation (Epichlorohydrin/Novolak Resins)
Condensation (Epichlorohydrin/Bisphenol A)
Condensation (Polyols/Epichlorohydrin)
Epoxidation (Polymers)

Condensation (Melamine/Formaldehyde)

Spinning

Condensation (Caprolactam)

Condensation (Nylon Salt)

Condensation (C5-C8 Unsaturates)

Condensation (Phenol/Formaldehyde)
Melt Spinning (DMT/Ethylene Glycol)
Melt Spinning (TPA/Ethylene Glycol)

Condensation (TPA/Ethylene Glycol)
Condensation (DMT/Ethylene Glycol)

High Pressure Polymerization (LDPE)
Solution Polymerization (HOPE)

Solution Polymerization
                                     -11-

-------
TABLE 2.  MAJOR PRODUCTS BY PROCESS OF THE PLASTICS/SYNTHETIC FIBERS INDUSTRY
                                 (Continued)
  PRODUCT-
         PROCESS (FEEDSTOCK)
Polystyrene and Copolyraers

Polyvinyl Acetate Resins

Polyvinyl Alcohol Resin



Polyvinyl Chloride



Rayon

San Resins

SiliconeS

  Silicone Fluids

  Silicone Resins

  Silicone Rubbers

Styrene-Butadiene Resin

Unsaturated Polyester Resin


Urea Resins
Bulk Polymerization

Emulsion Polymerization

Hydrolysis (Polyvinyl Acetate)
Solution Polymerization (Vinyl Acetate/
Hydrolysis of Polymer)

Bulk Polymerization
Emulsion Polymerization
Suspension Polymerization

Viscose Process

Suspension Polymerrization '

Hydrolysis (Chlorosilanes)

Hydrolysis/Cyclization (Chlorosilanes)

Hydrolysis/Cyclization (Chlorosilanes)

Hydrolysis/Cyclization (Chlorosilanes)

Emulsion Polymerization

Condensation (Maleic and Phthalic Anhydrides/
   Glycols)

Condensation (Urea/Formaldehyde)
                                      -12-

-------
     Given toxic pollutant concentrations for a given production process and
using wastewater flow specific to that product/process, toxic pollutant waste
load can be calculated as before.  The total waste load from a plant is the
sum of the individual product/process waste loads generated at an OCPSF plant.

     A third level at which toxic pollutant waste loads from a plant can be
calculated is at the product level.  This approach entails averaging toxic
pollutant concentrations from the MPF by product rather than product/process.
One hundred and twenty-one specific products are covered by the MPF com-
prising   86 percent of the OCPSF industries' total production.  Using toxic
pollutant concentration for a specific product and using wastewater flow
specific to that product, product specific waste loads can be calculated as
before.  Again, the total waste load from a plant is calculated as the sum
of individual product waste loads.

     The last and most general level at which plant specific waste loads can
be calculated is at the generic process level.  This approach entails averaging
toxic pollutant concentrations from- the MPF by generic process rather than by
product/process; each product/process reported by the OCPSF industries has
been assigned a generic chemical process.  Table 3 lists the generic chemical
processes employed by the OCPSF industry.  Ninety-eight percent of all products
produced by the OCPSF industries are covered by generic chemical process
calculations.   Using generic process toxic pollutant concentrations for a
specific product and using wastewater flow specific to that product,  product
specific waste loads are calculated as before.  Again, the total waste load
from a plant is calculated as the sum of individual product waste loads.

3.  POLLUTANT CONCENTRATION DATA

     A variety of studies has been undertaken by EPA to collect toxic pollu-
tant concentrations in the OCPSF industries' wastewaters.   Studies which
have produced significant data on raw and current wastewater characteristics
include the 1983 "308" Survey, the Screening Studies (Phases I and II),  the
                                     -13-

-------
                     TABLE 3.  GENERIC CHEMICAL PROCESSES
Acid Cleavage
Acylation"  -
Addition
Alcoholysis
Alkoxylation
Amination
Ammoxidation

Bromination

Carbonylation
Chlorination
Chlorohydrination
Condensation
Crystallization/Distillation
Cyanation

Decarboxylation
Dehydration
Dehydrogenation
Dehydrohalogenation
Depolyraerization
Oiazotization
Dimerization
Distillation

Electrohydrodiraerization
Epoxidation
Esterification
Etherification
Extraction
Extractive Distillation
Fiber Production
Fluorination

Hydration
Hydroacetylation
Hydrocyanation
Hydrogenation
Hydrohalogenation
Hydrolysis
Hydroxylation

lodination
Isomerization

Neutralization
Nitration
Nitrosation
Oxidation
Oxidation/Reduction
Oxiraation
Oxyhalogenation

Peroxidation
Phosgenation
Phosphonation
Polymerization
Pyrolysis

Re ar r ang eraen t

Sulfation
Sulfonation

Transesterification
                                     -14-

-------
Verification Study, and the CMA Five-Plant Study.  Toxic and conventional
pollutant data collected at the product/process level from these studies
make up the Master Process File.  These studies are summarized in Table 4
and discussed below.  Toxic pollutant concentration data used for calculation
of raw waste loads are listed in Appendix C.

3.1  308 Questionnaire Data

     In September, 1983, the Agency requested new information on current
manufacturing processes and wastewater control/treatment practices related to
the production of organic chemicals and/or plastics and synthetic fibers.
Data were collected at two levels:   primary Organic Chemical and Plastics/
Synthetic Fibers plants (plants whose manufacture of OCPSF products was more
than 50 percent of total plant production in 1982;  plants whose OCPSF waste-
waters were segregated; plants whose OCPSF process  wastewaters represented
75 percent or more of total process wastewater flow treated in a treatment
facility) provided a general profile of the plant,  detailed production data,
detailed wastewater treatment data, detailed disposal techniques, and.analy-
tical data summaries.  Secondary OCPSF plants (plants not meeting the above
criteria) provided only general profile data.

     With regard to toxic pollutant data,  the Agency requested 1980 average
priority pollutant concentration data from primary  organic and plastics
producers for the following sample points:

     o  Influent and effluent data for in-plant wastewater
        control or treatment unit operations;
     o  Influent to the main (end-of-pipe) wastewater treatment
        system;
     o  Intermediate sampling points within the main (end-of-
        pipe) wastewater treatment system;
     o  The effluent sampling point from the main (end-of-pipe)
        wastewater treatment system;  and
     o  The effluent sampling point if the wastewater is dis-
        charged without treatment.
                                     -15-

-------
e/3


BO
Cd
os
H
en
Cd
H
en
<


•3-
Q
Cd
a
3

CJ
z
a

H
en
Cd
Cd
 O
 §
 Cd

 93
\ 1
\

(



J2

^4
t-
5
o
r-l
Cb
i_4
S
w
^



i

1
i I
i
1 1
i

1
i
i


M
) >_4
^
0 Cd
3 en
H <
cn S
ex
t
t i i
i i
i i
• Irj.
!z
M
' '2
i~
cd
•'«
• — *
U
1 lc/i
i i
i
i i
1 1
i I

1
! p-1
i
Cd
'<
I i2
(0u
i 1^
1 !
< !

1
1 1
i 1
I t 1
i 1 1








H
j z

\ C3
! Cd
3
Cd


1
t
1
1
I
1
1









_

Cx O U*l CN
o <*> . -^ r-i CM
cr>
r-i
(-1
UJ
XI
e
01
y •
O)
Q


oo
r*.
ej>
r-l

r«
y
u
cfl .
S

0 rH 1 1 1
4-1 m
r-l
r*.
r**
C3>
r— 1

4J
•J3
3
6C
<:


03
^
en eu
•a— u 60 en
0) IH IH
DO CO 01
en n £ M
4-1 co y u
C J". en co
co y TJ .e
r-i en Q y
Bu 1-1 en
C 4-1 -J
u y a
O 4-1 4)
y IH u
u 0) ft eu
en cu M -a .c
eu A -H c 4J
4.) e a M o
co 3
a z

(0
ij
c
eu •
3 U
r* r- eu
a- 
0) T3 y 3
y c -H co
O BJ 4J Oi
u en
O. en co
"•»• 4J r- 4 •
jj c ft y
y 01 i-i
3 3 «T> C
T3 rH CN CO
O UH 6C
IH e c »H
ft. -H ft O











•
I— 1

eu
en
CO
js
IX
en
CO

0)

CO
cn





•
4J 4-1
c e en
01 01 en
€30)
4J rH y
CO U-l O
o> UH IH
IH oi a
H --.
73 4J
c u
• CO 3 •
i-i >a en
0) 4J O 4J
4-> e i-i c
CO 01 O- cu
33 3
~4 0) r*
3 u-i e u-i
CO C O u-i
c£ 1-1 en 01






en
c
o
1-1
4_l
CO
y
o
_j

60
C
i-l
rH
O.
s
CO
en
e
o
u
U-l

en
4J
C ^v
CO 4J
4J y
3 3
r^ t3
r-l Q
0 U
a a.
en
y y 01
t-i i-l 03
03 uj u-i en
x 1-1 -H eu
co y y y
•O 0) 0) O
a a. u
m en en p.












r- 1

eu
03
CO
' £
cx
V3
«
>%
CO 01 ..
•a s
' (0
r-i en




03
4-1
e
CO
44
3
—4
r-l
o
a
•
x en
4-1 O
•^4 4J
u en
O eu
•r< .C
u en
>> a. eg
CO
T3 r-l 4J
—I 3
rM < JQ



>*^
CO
«^

e T3
o eu
1-1 4J
4J CO
co eu
r< H
3
a 03
4-1
60 e
c co
•H 4-1
rH 3
O. rH
S rH
cfl O
en a*
•
X CO
u eu
0 -H
4_i a.
> c
rH Cfl
CO SO
C U
•< o
i

rH '
etJ „-;
S 4->
3 «
• £. O 0) •
01 y en 4J ^-<
C u 3 en
>-. CO UH U .C
TJ eU rH T4 CO
o en 3 4J j
u eu a en
i-l Oi C 03
> • M r-,
C 4-1 01 CX
W en 4-j j= v-' 1
eu 3 y
3 4J u en x
•• .C -H CO J2 01
en 4J 4J eu C u
^ 3 cn co y 3
co o C eu co y
j cn M a: "-3 <
I
i
i

 60
C C
Cd Cd


•
• *> x^
> M
rH at
r
* x^
rH 4U
> en eu
eu 4-1
• 3 3
I-H -^ 4J
rH -H vH
^^tn
en • c
e eu rH
O C
iH Ss f.
bo -a y
eu o u
06 IH CO
•H eu
<: > cn
OH C 01
Cd Cd Oi






60
C
•r4
4-1
CO
a
-r4
y _.__
iH ^ — "^^
4-1
IH
CO
CX
ca
J3
CO
_]








>>
rH
rH
CO
U
eu
c
cu
6C
cu
u
eu
3

en
y
e
CO
6C
U
0

eu
rH
1-1
4J
CO
i— 1
O
>
•o
c
CO

tn
rH
O
c
01
£.
a.
M
01
•o
•r*
c
CO
X
y

• M
en
eu .
4J en
— eu
cn r-
o a
£• s
e «
o en
y
_£
u aj
3 u
0 3C
1 ,£
| '4-
i s:
I eu eu
U iH
1 eu u
3 U
y>
en
CU TJ
i-^
a u
s o
CO
en M
01
* rJ
>% ex
-J C
rH C3
to en
>H
01 -O
C CO
eu u
CJ 5C

t
I/--N
CO
*>~s
                                                           -16-

-------
Average concentrations for toxic pollutant parameters were to be calculated
as follows:
     o  All not detected (ND), trace (TR), and less than (LT)
        the detection limit values were not be included in
        the calculation of average concentrations;
     o  All greater than (GT) the detection limit values were
        included in the calculation of average concentrations
        as the detection limit; and
     o  All "ND," "TR," and "LT the detection limit" values
        were counted in the "Number of Observations Below
        the Detection Limit".
     It is important to realize that no new analytical data were to be gene-
rated by this data request; additionally, data generated for design analysis
or similar purposes were not to be reported.  Of the five hundred and forty-
five plants requested to submit analytical data, forty plants submitted data
useful for the calculation of raw waste loads.

3.2  Screening Phase I.

     The wastewater quality data reported in the 1976 308 Questionnaires
were the result of monitoring and analyses by each of the individual plants
and their contract laboratories.  To expand its priority pollutant data base
and improve data quality by minimizing the discrepancies among sampling and
analysis procedures, EPA in 1977 and 1978 performed its Phase I Screening
Study.  The Agency and its contractors sampled at 131 plants, chosen because
they operated product/processes that produce the highest volume organic
chemicals and plastics/synthetic fibers.

     Samples were taken of the raw plant water, some product/process influents
and effluents, and influents and effluents at the plant wastewater treatment
facilities.  Samples were analyzed for all priority pollutants except asbestos,
and for several conventional and nonconventional pollutants.   Screening
                                     -17-

-------
samples were collected in accordance with procedures described in an EPA
Screening Procedures Manual (EPA 1977).  Samples for liquid-liquid extraction
(all organic pollutants except the volatile fraction) and for metals analyses
were collected in glass compositing bottles over a 24-hour period, using an
automatic sampler generally set for a constant aliquot volume and constant
time, although flow- or time-proportional sampling was allowed.  For metals
analysis, an aliquot of the final composite sample was poured into a clean
bottle.  Some samples were preserved by acid addition in the field, in accord-
ance with the 1977 manual; acid was added to the remaining samples when they
atrived at the laboratory.

     For purge and trap (volatile organic) analysis, wastewater samples were
collected in 40- or 125-ml vials, filled to overflowing, and sealed with
Teflon-faced rubber septa.  Where dechlorination of the samples was required,
sodium thiosulfate or sodium bisulfite was used.

     Cyanide samples were collected in 1-liter plastic bottles as separate
grab samples.  These samples were checked for chlorine by using potassium-
iodide starch test-paper strips, treated with ascorbic acid to eliminate the
chlorine, then preserved with 2 ml of ION sodium hydroxide/liter of sample
(pH 12).

     Samples for total (4AAP) phenol colorimetric analysis were collected in
glass bottles as separate grab samples.  These samples were acidified with
phosphoric or sulfuric acid to pH 4, then sealed.

     All samples were maintained at 4°C for transport and storage during
analysis.  Where sufficient data were available, other sample preservation
requirements (e.g., those for cyanide, phenol, and VOAs by purge and trap as
described above) were deleted as appropriate (e.g., if chlorine was known to
be absent).  No analysis was performed for asbestos during the screening and
verification efforts..  A separate program was subsequently undertaken for
determination of asbestos.
                                      1 Q_

-------
3.3  Screening Phase II.

     In December, 1979, samples were collected from an additional 40 plants
(known as Phase II facilities) manufacturing products such as dyes, flame
retardants, coal tar distillates, photographic chemicals, flavors, surface
active agents, aerosols, petroleum additives, chelating agents, microcrystalling
waxes, and other low volume specialty chemicals.  As in the Phase I Screening
study, samples were analyzed for all the priority pollutants except asbestos.
The 1977 EPA Screening Procedures Manual was followed in analyzing priority
pollutants.  As in Screening Phase I, some samples for metals analysis were
preserved by addition of acid in the field (in accordance with the 1977
Manual) and acid was added to the remaining samples when they arrived at the
laboratory.  In addition, the organic compounds producing peaks not attributable
to priority pollutants with a magnitude of at least one percent of the
total ion current were identified by computer matching.

     Intake, raw influent, and effluent samples were collected for nearly
every facility sampled.  In .addition, product/process wastewaters which could
be isolated at a facility were also sampled, as were influents and effluents
from some treatment technologies in place.  Fourteen direct dischargers, 24
indirect dischargers, and 2 plants discharging to deep wells were sampled.
Table 5 lists the product/process and other waste streams sampled at each
plant.

3.4  Verification Program.

     The Verification Program was designed to verify the occurrence of specific
priority pollutants in waste streams from individual product/processes.
Product/processes to be sampled were chosen to maximize coverage of the
product/processes used to manufacture major organic chemicals and plastics.
The priority pollutants selected for analysis in the waste stream from each
product/process were chosen to meet either of two criteria:
                                     -19-

-------
         TABLE 5.  PHASE II SCREENING - PRODUCT/PROCESS AND OTHER
                   WASTE STREAMS SAMPLED AT EACH PLANT
Plant
Number	Waste Streams Sampled	

  1                      Combined raw waste (fluorocarbon)

  2                      Anthracene
                         Coal tar pitch

  3                      Combined raw wastes (dyes)

  4                      Combined raw wastes (coal tar)

  5                      Combined raw wastes (dyes)

  6                      Oxide
                         Polymer

  7                      Freon

  8                      Freon

  9                      Ethoxylation

 10            '          Nonlube oil Additives
                         Lube oil Additives

 11                      Combined raw wastes (dyes)

 12                      Combined raw wastes (flavors)

 13                      Combined raw wastes (speciality  chemicals)

 14                      Combined raw wastes (flavors)

 15                      Hydroquinone

 16                      Esters
                         Polyethylene
                         Sorbitan monosterate

 17                      Dyes

 18                      Combined raw wastes (surface active  agents)

 19                      Fatty acids
                                    -20-

-------
                                                                        0 b , j f  1 J
         TABLE 5.  PHASE II SCREENING - PRODUCT/PROCESS AND OTHER
             WASTE STREAMS SAMPLED AT EACH PLANT (Continued)
Plant
Number	Waste Streams Sampled	

 20                      Organic pigments
                         Salicylic acid
                         Fluorescent brightening agent

 21                      Surfactants

 22                      Dyes

 23                      Combined raw wastes (flavors)

 24                      Chlorination of paraffin

 25                      Phthalic anhydride

 26              •        Combined raw waste (unspecified)

 27                      Dicyclohexyl phthalate

 28                      Plasticizers
                         Resins

 29                      Combined raw waste (unspecified)

 30                      Polybutyl phenol
                         Zinc Dialkyldithiophosphate
                         Calcium phenate
                         Mannich condensation product
                         Oxidized co-polymers

 31                      Tris (S-chloroethyl) phosphate

 32                      Ether sulfate sodium salt
                         Lauryl sulfate sodium salt
                         Xylene distillation

 33        "              Dyes

 34                      Maleic anhydride
                         Formox formaldehyde
                         Phosphate ester
                         Hexamethylenetetraraine
                                   -21-

-------
                                                                            " 4
                                                                            < -i
         TABLE 5.  PHASE II SCREENING - PRODUCT/PROCESS AND OTHER
             WASTE STREAMS SAMPLED AT EACH PLANT (Continued)
Plant
Number	 	Waste Streams Sampled	

 35                      Acetic acid

 36                      Combined raw waste (coal tar)

 37                      "680" Brorainated fire retardants
                         Tetrabromophthalic anhydride
                         Hexabromocyclododecane

 38                      Hexabromocyclododecane

 39                      Fatty acid amine ester
                         Calcium sulfonate in solvent (alcohol)
                         Oil field deemulsifier blend
                          . (aromatic solvent)
                         Oxylakylated phenol—formaldehyde resin
                         Ethoxylated monyl phenol
                         Ethoxylated phenol—formaldehyde resin

 40                      Combined raw waste (surface active agents)
                                   -22-

-------
                                                                         oi.;,j
    (1)  They were believed to be raw materials, precursors, or  products  in
         the "product/process, according to the process chemistry employed by
         the plant; or
    (2)  They had been detected in the grab samples taken several weeks before
         the three-day Verification exercise (see below) at concentrations
         exceeding the threshold concentrations listed in Table  6.
     The threshold concentrations listed in Table 6 were selected as follows.
The concentrations for pesticides, PCBs, and other organics are approximate
quantitative detection limits.  The concentration for arsenic, cadmium,
chromium, lead, and mercury are one half the national Drinking Water Standard
(Federal Register, Vol. 40, No. 248, December 24, 1975, pp. 59566-74).

     The Agency sampled at six integrated manufacturing facilities for the
pilot program to develop the "Verification Protocol."  Thirty-seven plants
were eventually involved in the Verification effort.  Samples were taken
from the effluents of 147 product/processes manufacturing organic chemicals
and 29 product/processes manufacturing plastics/synthetic fibers, as well as
from treatment system influents and effluents at each facility.

     Each plant was visited about four weeks before the three-day verifica-
tion sampling to discuss the sampling program with plant personnel, to deter-
mine in-plant sampling locations and to take a grab sample at each designated
sampling site.  These samples were analyzed to develop the analytical methods
used at each plant for the three-day verification exercise and to develop the
target list of pollutants described above for analyses at each site during
the three-day sampling.  Some pollutants that had been put on the list for
verificatio«=-sirBce they were believed to be raw materials, precursors, or
coproducts were not detected in the verification program grab samples.  If
such a pollutant was also not detected in the sample from the first day of
the three-day verification sampling, it was dropped from the analysis list
for that sample location.  Other compounds were added to the analysis list
since they were found in the Verification grab sample at a concentration
                                     -23-

-------
         TA&LE 6.  SELECTION CRITERIA FOR TESTING PRIORITY POLLUTANTS
                           IN VERIFICATION SAMPLES
	Parameter	Criterion (yg/1)

Pesticides and PCBs                                     0.1
Other Organics                                         10
Total Metals:
   Antimony                                           100
   Arsenic                                             25
   Beryllium                                           50
   Cadmium                                              5
   Chromium                                            25
   Copper                                              20
   Lead                                                25
   Mercury                                              1
   Nickel                                             500
   Selenium                                            10
   Silver                       '                        5
   Thallium                                            50
   Zinc            •                                 1,000
Total Cyanides                                         20
                                     -24-

-------
exceeding the threshold criteria in Table 6.  Priority pollutants known by
plant personnel to be present in the plant's wastewater were also added to
the Verification list.

     At each plant, Verification samples generally included:  Process water
supply; product/process effluents; and treatment facility influent and efflu-
ent.  Water being supplied to the process was sampled to establish the back-
ground concentration of priority pollutants.  The product/process effluent
waste loads were later corrected for these influent waste loadings.  Product/
process samples were taken at locations that would best provide representa-
tives samples.  At various plants, samples were taken at the influent to
and effluent from both "in-process" and "end-of-pipe" wastewater treatment
systems.

     Samples-were taken on each of three days during the Verification exercise.
As in Phase I and II Screening studies, 24-hour composite samples for extract-
able organic compounds and metals were taken with automatic sampling equipment.
Where automatic sampling equipment would violate plant safety codes requiring
explosion-proof motors, equal volumes of sample were collected every two hours
over an 8-hour day and manually composited in a glass (2.5-gallon) container.
Raw water supply samples were typically collected as daily grab samples
because of the low variability of these waters.

     Samples for cyanides analysis were collected in plastic bottles (either
as a single grab sample each day or as an equal-volume, 8-hour composite) and
were preserved as in the screening program.  Samples for analysis of volatile
organic compounds were also collected and preserved as in the screening
program, in headspace-free sealed vials; where headspace analysis of volatile
organic compounds was planned, sample bottles were filled half way.  No 4-AAP
phenol analyses were run during verification.

     The temperature and pH of the sample, the measured or estimated waste-
water flow at the time of sampling, and the process production levels were
                                     -25-

-------
all recorded.  Weather and plant operating conditions during the  sampling
period were also recorded, particularly in connection with operational upsets
(in the production units or wastewater treatment facilities) that could yield
a sample not of typical operation.

     Analytical methods for cyanides were the same as those used  in Phases I
and II of Screening.  Analytical methods for heavy metals conformed to the
1977 Manual; all samples were preserved by addition of acid in the field.
For organic compounds, however, gas chromatography with conventional detectors
was used instead of the GC/MS that was used in the Screening program.  GC/MS
analysis was used on about ten percent of the samples to confirm  the presence
or absence of pollutants whose GC peaks overlapped other peaks.   The analytical
.methods.finally developed were.usually applicable (with minor modifications)
to all sampling sites at any given plant.

     Because GC/MS was used only on samples whose GC peaks overlapped other
peaks, industry has questioned the extent of false positive values reported in
these data.  As part of the Master Process File validation, individual product/
processes in the MPF were reviewed as to the likelihood of the presence or
absence to reported toxic pollutants on the basis of process chemistry.  This
effort resulted in  the inclusion/exclusion of toxic pollutants in the MPF
(see Appendix D); generally the concentrations of pollutants eliminated were
_<_ 100 ppb.  At no time were toxic pollutant concentrations changed in the
Master Process File.

4.  FLOW DATA

     Flow data are  derived exclusively from the 1983 "308" Questionnaire
responses.  Wastewater flow data from primary organic chemical and plastics
facilities are provided for individual product/process by wastewater source
(e.g., an aqueous waste stream resulting from quenching of a reaction product,
washdown of process equipment); for product groups at in-plant, preliminary,
secondary, and tertiary treatment processes (i.e., wastewater effluent flows
                                     -26-

-------
through these treatment processes); for miscellaneous wastewaters entering
the main treatment system; and for final effluent discharge.  These data
allow waste loads to be calculated for individual product/processes, product
groups, or total plant effluent for primary organic chemical and plastics
producers provided that corresponding toxic pollutant data are available (see
Appendix A).

     In some instances, primary organic chemical and plastic plants reported
data for combined product/processes; moreover certain plants did not provide
product/process specific data.  In such cases, product/processes flows were
estimated by production in weighting either product group flow, if available,
or total waste flow, if product group flow was unavailable.  For plants that
did not provide production data, total process flow was apportioned equally
between product/ptocesses.  Product/process flow data are shown.in Appendix E.

     Secondary OCPSF plants provided only general data regarding plant opera-
tions.  These data include 1982 production data by eight-digit Census product
code, OCPSF process and nonprocess wastewater flow, total plant wastewater
flow, OCPSF process wastewater disposal methods, treatment technologies, and
pollutant summaries.  Wastewater flow was not reported by product/process
for secondary plants.  Total OCPSF wastewater flow for secondary plants is
shown in Appendix A.

5.  WASTE LOAD CALCULATION

     It is obvious from the preceding discussion that primary OCPSF plant
specific waste loads can be calculated in more than one way depending on the
availability of toxic pollutant concentration data and flow data.   For primary
plants that have provided 1983 "308" toxic pollutant data, waste loads for
individual pollutant may be estimated using these data.   Waste loads can be
calculated for a given plant on the basis of either product/process employed
by that plant or the products manufactured by that plant.   Waste loads can
also be calculated on the basis of the generic processes employed by a plant.
                                     -27-

-------
Secondary OCPSF plant toxic pollutant waste loads must be calculated in a

fundamentally different way and extrapolated from primary OCPSF plant toxic

pollutant waste loads.


     There are limitations to each waste load calculation approach.  Although

waste load calculations using plant specific toxic pollutant concentrations

(either from 1983 "308" data or screening data) are likely to be most accurate,

such data are available for relatively few plants.  Waste load calculation

using Master Process File toxic pollutant concentrations can be made for all

plants employing product/process contained in the MPF.  The MPF can be general-

ized to products allowing even greater coverage of the OCPSF industry.  Most

generally waste loads may be generated on the basis of-the generic process

chemistry employed by a plant.


     Rather than select any one method for waste load calculation, the Agency

determined all waste load calculation methods would be used when appropriate,

thus providing maximum coverage of the industry with the greatest accuracy

possible.  The following hierarchy of data sources was established:


     1.  Where "308" toxic pollutant data were available, these data would
         be used to calculate raw waste loads for those toxic pollutants.

     2.  Where the combined raw wastewaters of a plant had been sampled in
         either Phase I or Phase II Screening studies, these toxic pollutant
         concentration data would be used to calculate the raw waste loads
         from these plants.

     3.  Raw waste loads would next be calculated using Master Process File
         toxic pollutant concentration data for product/process covered by
         the MPF.  Where product/process waste load could not be calculated
         at a plant, product specific waste laods were calculated using the
         "Product Averaged Master Process File."

     4.  For plants producing products that could not be calculated by the
         above methods, generic process raw waste loads were calculated using
         the "Generic Process Averaged Master Process File."  Because the
         Generic Process method necessarily generated extraneous pollutants
         for any given product, raw waste loads from these plants were exten-
         sively reviewed; those pollutants believed to be inconsistent with


                                     -28-

-------
         process chemistry practiced at a plant were deleted from the raw
         waste load file.  Pollutants deleted from the generic process averaged
         waste load are shown in Appendix F.
Exhibit 1 summarizes the methodology used to calculate raw waste loads.


     Waste loads for secondary OCPSF plants were extrapolated from the waste

loads calculated for primary OCPSF plants in the following way:
     1.  Flow weighted toxic pollutant concentrations were calculated for
         each subcategory using data from primary OCPSF plants:
         _        n

                 j-1     '"'  3=1  "


         where C^ ^ = the mean toxic pollutant concentration of pollutant i
                      for subcategory k

           RWLj^j^ = the raw waste load for pollutant i at plant j of
                      subcategory k

               FJ k = the total process flow for plant j of subcategory k.


     2.  Plant specific raw waste loads are calculated from mean subcategory
         toxic pollutant concentration and the OCPSF process flow at a plant:


         RWL-i .; t = d k.(Fi' )
            -"-•J     -"-j^J


         where RWL^ j» = the raw waste load for toxic pollutant i at plant j'
                         (where ' denotes a secondary OCPSF plant)

                   FJ' = the total OCPSF process at plant j'.


5.1  BPT, BAT, and Current Waste Load Calculations


     BPT, BAT, and current waste load of individual plants were calculated for

those toxic pollutants found in the raw waste load as follows (See Exhibit 2):
                                     -29-

-------
                                                                                                                                   , >  i  .3
                                                                                               xrr ruurr
                                                                                               rCLLUTAXT
                                                                                               1.0*01 «J
EXHII1T 1   UK .ASTI LOAD CALO.LATIOK LOCK C-OL
                                                               -30-

-------
s

CALCULATE
BOD
ACTUAL
1 *°l>SIIICATEr.O«V




CAI CUI.ATE
ADJUSTED RPT
IOX 1 C POI LUTANT
CONCENTRATION
-31-

-------
     1.   Average toxic pollutant concentrations were calculated using the
         sampling data base (i.e.,  verification data, CMA 5-plant, and new
         sampling data).  Separate toxic pollutant concentrations were
         calculated by subcategory for both BPT and BAT plants (i.e., those
         plants currently meeting proposed BPT and BAT criteria respectively),

     2.   Pollutant concentrations were adjusted for those plants which
         incurred BPT costs by the ratio of actual BOD to the target BOD for
         that subcategory (20 mg/1 for rayon, other fibers,  thermoset, and
         thermoplastics only; 45 mg/1 for thermoplastics and organics, com-
         modity, bulk, and specialty organics).  Plants that did not incur
         BPT costs were assigned BPT toxic pollutant concentrations by sub-
         category.  Plants that did not incur either BPT or BAT costs were
         assigned BAT toxic pollutant concentrations.

     3.   Effluent concentrations of toxic pollutants as derived above were
         multiplied by total process flow to calculate current waste loads.
5.2 PSES Waste Load Calculations


     PSES waste loads were calculated in a manner analogous to current waste
loads.  If a plant was costed for PSES treatment, then toxic pollutant con-

centrations were considered to be equal to raw waste toxic pollutant concen-
trations.  If a plant was not costed for PSES, then toxic pollutant concen-
trations were assumed to be equal to "Current" toxic pollutant concentrations.

Effluent concentrations of toxic pollutants as derived above were multiplied
by total process flow to calculate PSES load.  Because "Current" toxic pollu-
tant concentrations are industry averages by subcategory in some cases "Cur-
rent" toxic pollutant concentrations exceeded those in the raw waste.  In such
cases, (_<_ x percent of the PSES waste load calculated by individual pollutant)
the toxic pollutant load was deleted from the PSES waste load file.  Exhibit 3
summarizes the methodology used to calculate PSES wasteloads.


5.3  Annualized Waste Load


     Product/process flow data provided by primary OCPSF plants in the 1983
"308" questionnaire are reported in millions of gallons per day when operating.
Primary plants have also provided total annual production data and operating
                                     -32-

-------
                      308 DATA BASE
                           DID
                          PLAHT
                       INCUR PSES
                          COSTS
PSES WASTE LOAD

 RAW WASTE LOAD
 PSES WASTE LOAD
        •         !
CURRENT WASTE LOAD
                                               CURREN
                                            TOXIC POLLU-
                                           TANT WASTE  LOAD
                                          > RAW TOXIC  POLLU
                                             TANT WASTE
                                                LOAD
                               DELETE POLLUTANT
PSES
WASTE LOAD
          EXHIBIT 3.   PSES WASTE LOAD CALCULATION
                              -33-

-------
rate data by product/process.   The Agency has calculated operating days for
each product/process at each primary OCPSF plant by dividing the annual
product/process production by the product/process operating rate.  Multipli-
cation of daily product/process waste load by product/process operating days
yields annualized product/process waste loads.  Toxic pollutant waste loads
from individual product/processes at a plant are then summed by pollutant to
yield total waste load for individual plants.  Appendix G lists product/process
operating days.

     Product/process production data are unavailable for secondary OCPSF
producers and annual waste loads cannot be calculated in a manner analogous
to those estimated for primary OQPSF plants.  Annual waste loadings from
secondary OCPSF plants were estimated from daily waste loads by assuming that
OCPSF product/processes generating wastewaters operated four days per week
or 208 days per year.

6.  RAW WASTE LOAD VALIDATION

     Where Organic Chemicals and Plastics/Synthetic Fibers plants have provided
toxic pollutant data (i.e., 1983 "308" analytical data summaries) or OCPSF
plants were sampled during the Phase I or Phase II screening studies, it has
been possible to compare these toxic pollutants raw waste loads with those
calculated using the Master Process File.  Differences between toxic pollutant
waste loads calculated from 1983 "308" toxic pollutant concentrations were
calculated and then compared statistically using the t-Test (see Appendix H).
Raw waste loads calculated from Screening data were similarly compared to
raw waste loads calculated using the Master Process File (see Appendix I).
In neither case were significant differences found between calculation methods.
                                     -34-

-------
      APPENDIX A




SUMMARY LOADING TABLES

-------
                                  TABLE A-l
                               Direct Discharge
                      Annual Priority Pollutant Loadings
                             (1,000 pounds/year)
                VOLATILES
              SEMIVOLATILES
               METALS & CN
                                  TABLE A-2
                              Indirect Discharge
                      Annual Priority Pollutant Loadings
                             (1,000 pounds/year)
                    TOTAL
Raw Waste
Current
BPT/BAT-I
BAT-II
BAT-III
82,746
248
218
59
56
39,079
208
180
80
62
35,491
730
628
104
102
157,316
1,186
1,026
243
220
                VOLATILES
              SEMIVOLATILES
               METAL & CN
                    TOTAL
Raw Waste

Current

PSES-II
12,655

 4,313

   133
192,316

 96,180

     44
28,796

 6,309

   588
233,767

106,802

    765
                                    A-l

-------
                                 TABLE A-3
              DEFINITION OF CODES USED IN THE FOLLOWING TABLES
Fractions
                     A   =   Acid Fraction
                     B   =   Base/Neutral Fraction
                     M   =   Metals and Cyanide
                     V   =   Volatile Fraction
                     T   =   A + B + V
                     G   =   A+B + V + M
Column Headings (Direct Dischargers)

               YBATEFF1   =   BAT Option II, yearly effluent load (Ib/year)

               YBATEFF2   =   BAT Option III, yearly effluent load (Ib/year)

               YARWLOAD   =   Yearly raw waste load (Ib/year)

               YCURREFF   =   Yearly current effluent load (Ib/year)

               YBPTEFF    =   Yearly BPT effluent load (Ib/year)

               ARWLOAD    =   Daily raw waste load (Ib/day)

               TOTFLOW    =   Total flow (MGD)

               AVGCONC    =   Average effluent concentration (ppm)


Column Headings (Indirect Dischargers)

                YRAWASTE   =   Yearly raw waste load (Ib/year)

                YCURREFF   =   Yearly current effluent load (Ib/year)

                YPSESEFF   =   Yearly PSES effluent load (Ib/year)

                RAWLOAD    =   Daily raw waste load (Ib/day)

                TOTFLOW    =   Total flow (MGD)
                                    A-2

-------
in
e
o
        g    S:
        t-    o CM co 
                                                                                  •» in •* KI CM



                                                                                 ' * * 2 KI CM
                                                                                                       in
                                                                                                       a
                                                                                                       e>
        O    CM o o o- — CM CM    o> co •» <0 KI    m.
        _i    r. o •* CM co «       —i    •»         —
        3      CM in KI •« CO
        K         CM    CM •"
                                                            O •«    —i KI CO •« CM    «0 U) KI O
                                                            —       « CM KI KI o    -o KI KI KI
                                                                                                          IU
                                                                                                                  i
                                                                                                                     in e> >o KI o CM
                                                                                                                     m «o —i -o CM in
                                                                                                                     -» e> MJ •• t> *
                                                                                                                     N » in * ** K»

                                                                                                                     K o> * in « r*
     Ik
     Ik    O- i
     IU    •* I
                                                                                   i «o o r» -o
                                                                                   • o> o o> ••
                                                                                   i co o e -o
                                                                                                                       to « « «o rs r»
                                                                                                                       ^ in  r- o
                                                                                                                       co •» co r» eo -o
                                                                                                                       (x oo o- o> 0 r-
                                                                                                                       <*i » co 10 co ^
                                                                                                                       CJ         «4 OJ
   in
   a
   O
        o.   ~> in CM o -« .
        CO         CM -« -<
                                                                 <><
                                           ir>    c-^3- U
                                                                                                       -I IU
                                                                                                       Z a
                                                                                                       O M
                                                                                                          O
                                                                                                                                -O
                                                                                                                                9>
<    CM O •« •• U> KI
£Q    tO ^ "4 9* *f C\J

>•    *T    eg   KI tt CM
                                                                                                                       CM -4 in CM in in
                                                                                                                       «       _|    CM
                                                                                                                       •• CM o- r~ o a
                                                                                                                       o in  CM CM
                                                                                                                     *> KI -o  r*.
                                                                                                                                KI ut
        u
                                              tntncntnenintntncotncncn
                                              uuuuuuuuuuuu
                                              MMMMMMMMMMMM
                                              HK*-^HHHHHH*->~
                                              inintnmtnincnvicDincnintncncnintncn
                                                 3<<«'<<<<<<<
              MMi-iMtHMintntntntntnoo
              (9(9C9t9U)(9
                                                                                                                     *- < co r > u
                                                                                                                                  in -o
        §   -
                                                                            A-3

-------
S
        §    Si
               O «  CO
              t KI CM  m
               x Kl
                O CM Kl
                                                                                M M «
                                                                                                             5
                                                                                                           in « r» r* o~ -o
                                                                                                           o •& -f t* t* •o
                                                                                                            ^
                                                                                                                  «rw           -«^
               -* in CM CM >«
                                                                                                                «o r> h  o m o>.
                                                                                                                a> m KI oo CM i^.
                                                                                                                00 CM * CM CM «
                                                                                                                >H      M p« ro
m
a:
iu
10
   u
>- iu
-i a
        IU
        a
                                                                                                        in
                                                                                                        a
                                                                                                        UJ
                                                                                                        19
                                                                                                        in
                                                                                                        M
                                                                                                        O
                                                                                                u
                                                                                                UJ
                                                                                                           r-. CM MS o oo -o
                                                                                                           CM j- -. in -o oo
                                                                                                           00 — O M !»• —
                                                                                                           CM -« J- 00 -O —
                                                                                                           MM]   —! ,T f»l

                                                                                                           9-00   M    O
                                                                                                     gS   £   2
                                                                                                           in    o o co -• o ->
                                                                                                                oo r» -. in * m
                                                                                                                in    KI •f -« o
                                                                                                                        in -«r»
                                                                                                     «< M
                                                                                                             IU
                                                                                                             Se KrS -• *
                                                                                                             m  oo
                                                                                                           eg r» -< po in in
                                                                                                           e in •»•<«• o •>•
        P

        ^
        a
                                                           m «n  — co — oo
                                                                                                     p    in -« CM KI — o
                                                                                                     •<    o> -o in M] « «n
                                                                                                     O    r» ^ co oo f» 4)
                                                                                                     -I    MJ -H CM — CM «
                                                                                                     3    • -a-

                                                                                                     tt    oa r»   CM   —i
                                                                                                     >.    « _        CM
                                                           (9 (9 (9 O (0 (9
                                                           gggggg
                                            (JUUUUUUUUUUU
                                                                                                             U

                                                                                                             o:
                                                                                                                  t- <
                                                                                                                             > «
     in m in in in eo
     u u u u u u

     iisiiii
     CD  IS (9 U (9 :

                                 I U W UJ 	    	              	 	 	 	 	 	 	 	
                                 ;xxxxuJuiwiuuluuuwujujuujujiDiui
                                                                                                                             in -o
        en
        s
                                                     iCJOJcucucMOJcvjcgcgcjKi
                                                                           A-4

-------
                                                 FULL RESPONSE
                                      SUMMATION FOR ALL DIRECT DISCHARGERS
                                                           11:46 THURSDAY, JUNE 13,  1985
CNEUCAT
FRACTION    YRAMASTE    YCURREFF    YBPTEFF    YBATEFFl    YBATEFFZ    RAHLOAD    TOTFLOW
1

3
*
[
6
7
8
9
0
1
Z
3
4
!
6
7
S
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
a
9
0
1
2
3
4
5
6
7
a
9
0
1
2
3
BULK ORQANICS ~
BULK OR6ANICS
BULK OR6ANICS
BULK OR6ANIC3
BULK ORGANICS
BULK ORGANICS
CELLULOSIC3
CELLULOSIC3
CELLUL03ICS
CELLULOSIC3.
CELLULOSICS
COMMODITY OR6ANICS
COMMODITY OR5ANIC3
COMMODITY ORGANICS
COMMODITY ORGANICS
COMMODITY ORGANICS
COMMODITY ORGANICS
FIBERS
FIBERS
FIBERS
FIBERS
FIBERS
FIBERS
OTHER
OTHER
OTHER
OTHER
OTHER
OTHER
SPECIALTY ORGANICS
SPECIALTY ORGANICS
SPECIALTY ORGANICS
SPECIALTY ORGANICS
SPECIALTY ORGANICS
SPECIALTY ORGANICS
THERMOPLASTICS
THERMOPLASTICS
THERMOPLASTICS
THERMOPLASTICS
THERMOPLASTICS
THERMOPLASTICS
THERMOPLASTICS ORGANICS
THERMOPLASTICS ORGANICS
THERMOPLASTICS ORGANICS
THERMOPLASTICS ORGANICS
THERMOPLASTICS ORGANICS
THERMOPLASTICS ORGANICS
THERMOSETS
THERMOSETS
THERMOSETS
THERMOSETS
THERMOSETS
THERMOSETS
A
B
G
M
T
V
A
6
M
T
V
A
B
G
M
T
V
A
B
G
M
T
V
A
B
G
M
T
V
A
B
G
M
T
V
A
B
G
M
T
V
A
B
G
M
T
V
A
B
G
M
T
V
4332462
2497432
14903061
2798589
12104473
5274578
7572
10157572
10149327
8245
673
427100
2028532
25679325
756621
24922703
22467071
311660
109
1427090
600070
827020
515251
1353983
101430
10480551
6395119
4085432
2630019
205389
60284
3148510
15S0952
1597558
1331886
713272
8163
1612217
72412
1539805
818370
1557096
675288
14359452
3429827
10929626
8697242
14808924
9453
1780757?
1473238
16334341
1515964
13350
36286
190671
75347
115324
65687
1326
249310
247580
1730
404
3279
11521
52971
14116
38855
24055
719
28
7446
5279
2168
1421
6465
15400
138039
90079
47960
26095
583
3241
36782
29132
7650
3826
1000
1749
15270
9035
6235
3486
6512
18340
168283
88854
79430
54578
1882
1186
32684
23823
8861
5793
12043
32818
156687
52121
104565
59704
1233
232940
231370
1570
336
3139
10858
49405
12771
36634
22637
273
28
6664
5079
1585
1285
4921
8778
120760
86701
34059
20360
427
2579
23936
17697
6240
3234
571
1468
10636
5897
4739
2700
6207
18079
162429
85265
77164
52878
350
1094
10092
7420
2672
1228
5709.5
5078.6
39555.8
16646.4
22909.4
12121.2
822.2
10784.4
9625.9
1158.5
336.3
1775.4
7169.9
20448.7
4786.6
15662.2
6716.9
181.8
28.0
2864.0
2219.8
644.2
434.5
2532.3
4089.7
21892.5
10167.7
11724.8
5102.8
161.9
840.8
5382.6
3265.0
2117.7
1114.9
387.6
1084.7
5344.6
2660.4
2684.2
1212.0
4497.6
16703.1
60515.7
23414.7
37101.0
15900.4
253.9
135.0
3321.1
2262.9
1058.2
669.4
3217.4
4453.2
35909.6
16485.8
19423.8
11753.2
753.7
10690.0
9625.9
1064.1
310.4
1607.5
5483.8
18436.1
4782.7
13653.5
6562.2
166.6
28.0
2848.9
2219.8
629.1
434.5
2231.2
3647.2
20924.2
10167.7
10756.6
4878.2
154.0
518.1
4924.0
3148.7-
1775.3
1103.1
355.3
813.8
5033.1
2652.1
2381.0
1212.0
4289.9
13838.9
56901.3
23323.8
33577.5
15448.7
232.7
135.0
3224.6
2190.5
1034.1
666.4
16471.5
10110.3
59418.4
11431.4
47987.0
21405.2
20.8
27949.2
27926.6
22.7
1.9
1686.9
8684.2
94913.3
2663.1
92250.2
81879.1
911.6
0.4
3979.9
1641.9
2337.9
1425.9
6441.7
371.2
34643.5
17620.0
17023.5
10210.5
574.8
244.3
12239.2
6179.1
6060.2
5241.1
1961.2
29.3
4765.6
217.0
4548.6
2558.1
4714.2
2038.9
66721.4
18397.6
48323.8
41570.7
48451.9
28.6
57885.6
5004.1
52881.5
4401.0
182.91
281.28
1243.49
237.27
1006.22
542.02
22.58
91.68
60.56
31.12
8.54
58.97
206.82
509.29
40.87
468.42
202.63
5.47
1.18
38.04
16.53
21.51
14.86
80.55
79.28
405.15
83.76
321.40
161.58
5.79
18.67
98.60
39.17
59.43
34.97
12.16
14.76
89.63
24.66
64.97
38.05
134.44
481.87
1443.75
262.69
1181.06
564.76
9.56
5.20
62.01
23.29
38.72
23.96
  OBS
         FRACTION
                     YRAUASTE
                                                 FULL RESPONSE
                                      SUMMATION  FOA ALL DIRECT DISCHARGERS
                                 YCURREFF    YBPTEFF
                                                       YBATEFFl
                                                                                       11:46 THURSDAY. JUNE 13, 1985
                                                                   YBATEFF2
                                                                               RAHLOAD    TOTFLOW
                                                                                                     AV6CONC
1
2
3
4
5
6

A
B
n
T
V
99575358
23717457
5380691
27226155
72349203
43251055
891457
35115
87752
583246
308211
185344
773549
29165
75702
504320
269229
164362
170110
16322
35130
75049
95060
43608
158892
13008
28918
74597
84295
42369
362516
81235
21507
91081
271435
168693
3981.65
512.43
1069.06
788.80
3192.85
1591.36
10.9103
18.9967
2.3665
13.8363
10.1874
12.7029
                                                         A-5

-------
                                            FULL RESPONSE
                                SUMMATION FOR ALL INDIRECT DISCHARGERS
                                                           11:26 THURSDAY,  JUNE  13,
DBS    CNEMCAT

  1    BULK ORGATWCS
  2    BULK ORGANICS
  3    BULK ORSANICS   .
  4    BULK ORSANICS
  5    BULK ORGANICS
  6    BULK ORGANICS
  7    COMMODITY ORGANICS
  8    COMMODITY ORGANICS
  9    COMMODITY ORGANICS
 10    COMMODITY ORGANICS
 11 '   COMMODITY ORGANICS
 12    COMMODITY ORGANICS
 13    FIBERS
 14    FIBERS
 15    FIBERS
 16    FIBERS
 17    FIBERS
 18    FIBERS
 19    OTHER
 20    OTHER
 21    OTHER
 22    OTHER
 23.    OTHER
 24    OTHER
 25    SPECIALTY ORGANICS
 26    SPECIALTY ORGANICS
 27    SPECIALTY ORGANICS
 28    SPECIALTY ORGANICS
 29    SPECIALTY ORGANICS
 30    SPECIALTY ORGANICS
 31    THERMOPLASTICS
 32    THERMOPLASTICS
 33    THERMOPLASTICS
 34    THERMOPLASTICS
 35    THERMOPLASTICS
 36    THERMOPLASTICS
 37    THERMOPLASTICS
 38    THERMOPLASTICS
 39    THERMOPLASTICS
 40    THERMOPLASTICS
 41    THERMOPLASTICS
 42    THERMOPLASTICS
 43    THERMOSETS
 44    THERMOSETS
 45    THERMOSETS
 46    THERMOSETS
 47    THERMOSETS
 48    THERMOSETS
ORGANICS
ORGANICS
OR6ANICS
ORGANICS
ORGANICS
ORGANICS
            FRACTION
YRAWASTE    YCURREFF
YPSESEFF
RAWLOAO
                       TOTFLOW
A
B
6
M
T
V
A
B
G
M
T
V
A
B
C
M
T
V
A
B
6
M
T
V
A
B
6
M
T
V
A
B
6
M'
T '
V
A
B
G
M
T
V
A
B
G
M
T
V
1969467
83432
3020903
446685
2574218
521319
14845
30206
2295124
745049
1550075
1505025
24905
762
50873
20654
30220
4553
1009679
9003
1482817
17846
1464971
446289
4514692
46753
7603649
2816370
4787279
225834
3120 .
1020
94527
18960
75567
71427
6142
398
63000
14390
48611
42071
4458542
2613
4668575
96695
4571880
110725
1717894
83253
2750850
444615
2306235
505088
12216
18447
2197540
746671
1450868
1420205
25078
762
51039
20649
30389
4550
982022
7589
1432816
17355
1415461
425850
4011568
49132
7016537
2712080
4304457
243757
2883
830
103416
17356
86059
82346
5889
62
60781
14431
46350
40399
4349591
2518
4545069
122095
4422974
70864
518.9
1230.0
14676.1
11103.5
3572.6
1823.6
247.9
656.9
13159.6
6655.9
6503.8
5599.0
9.4
61.6
1076.9
863.7
213.2
142.2
181.5
160.8
4007.9
1979.6
2028.3
1686.0
163.4
1803.2
15712.1
10547.0
5165.1
3198.5
125.9
378.2
5572.8
3628.4
1944.4
1440.3
23.8
54.3
6042.3
5768.4
274.0
195.8
87.7
46.2
2836.8
2426 . 0
410.8
276.9
5893.5
280.6
9573.0
1682.2
7890.8
1716.7
49.0
89.6
7371.8
2437.3
4934.5
4795.8
82.9
2.1
157.3
58.7
98.5
13.5
3195.3
37.5
4837.3
54.8
4782.5
1549.7
17730.6
229.0
31517.9
12473.8
19044.1
1084.5
9.5
4.3
405.0
55.7
349.3
335.5
30.5
1.8
227.5
50.6
176.9
144.6
18257.9
23.2
19720.8
1000.9
18719.9
438.7
11.6401
6.6653
69.8616
25.1888
44.6728
26.3674
6.8646
27.2012
92.6593
18.5949
74.0644
39.9986
0.1862
0.1126
3.5733
1.8822
1.6911
1.3923
4.1078
3.4913
38.3999
7.8089
30.5910
22.9919
5.0339
15.3255
79.8125
25.0642
54.7483
34.3889
2.6237
3.8481
34.9356
9.1762
25.7594
19.2876
0.5879
0.3860
19.8780
16.1473
3.7307
2.7568
4.8054
4.6979
38.6181
14.6025
23.8156
14.3123
                                            FULL RESPONSE
                                SUMMATION FOR ALL INDIRECT DISCHARGERS
         DBS
                FRACTION    YRAWASTE    YCURREFF
                                                    YPSESEFF
                                        RAMLOAD
                                                                                   11:26 THURSDAY, JUNE 13,
                                                                           TOTFLOM    AVGCONC
1
2
3
4
5
6
T
A
B
M
V
G
15102820
12001391
174186
4176648
2927243
19279469
14062793
11107142
162593
4095254
2793058
18158047
20112.2
1358.5
4391.3
42972.3
14362.3
63084.5
55996. 5
45249.1
668.2
17814.1
10079.2
73810.6
259.073
35.850
61.728
118.665
161.496
377.738
25.901
151.251
1.297
17.989
7.479
23.415
                                                    A-6

-------
APPENDIX B          See Public Record Pages 004080 - 004257




APPENDIX C          See Public Record Pages 004258 - 004273




APPENDIX D          See Public Record Pages 004274 - 004307




APPENDIX E          See Public Record Pages 004308 - 004419




APPENDIX F          See Public Record Pages 004420 - 004446




APPENDIX G          See Public Record Pages 004447 - 004557




APPENDIX H          See Public Record Pages 004558 - 004559




APPENDIX I          See Public Record Pages 004560 - 004564

-------
VIII. COSTING DOCUMENTATION AND NOTICE OF NEW INFORMATION REPORT
        Note:  Table of Contents, List of Tables, and
               Section 2  (New Costing Methodology)
               follow; entire report is included in
               the public record.

-------
                FINAL
        COSTING DOCUMENTATION
                 AND
  NOTICE OF NEW INFORMATION REPORT
            PREPARED FOR:

 The Industrial Technology Division
U.S. Environmental Protection Agency
         301 M. Street, S.W.
       Washington, D.C.  20460
                 By:

         SAIC/JRB Associates
           One Sears Drive
     Paramus, New Jersey  07652
            June 12, 1985
     EPA Contract No. 68-01-6947
   JRB Project No. 2-835-07-688-01

-------
                               TABLE OF CONTENTS                      Pages


1.0  INTRODUCTION	  1-1

     1.1   Historical Prospective	  1-1

          1.1.1  The Catalytic Model	  1-2
          1.1.2  The CAPDET  Model	  1-6

     1.2   In-Depth Analysis  of the  Catalytic Model	  1-8

          1.2.1  Detailed Design Comments  on Catalytic Model	  1-15

     1.3   Development of  the New Costing Approach	  1-19

2.0  NEW COSTING METHODOLOGY	  2-1

     2.1   Introduction and Overview	  2-1

     2.2   Technologies Available  to the OCPSF Industry	  2-2

          2.2.1   In-Plant Controls	  2-2
          2.2.2  End-of-Pipe Treatment	  2-4
          2.2.3   Secondary Effluent Polishing Techniques	'..  2-7
          2.2.4   Zero or  Alternate  Discharge	  2-8

     2.3   Current  Treatment  Practices in the OCPSF Industry	  2-12

     2.4   Technology Options and Cost Curve Development	  2-16

          2.4.1  Technology  Options	  2-16
          2.4.2   Cost Curve  Development	  2-16

     2.5   Detailed Costing Procedures OCPSF Industry	  2-18

          2.5.1   Introduction	  2-18
          2.5.2   Data Needs	  2-18
          2.5.3   Technology  Assessment Analysis	  2-19

                2.5.3.1  BPT	  2-19
                2.5.3.2  BAT	  2-24
                2.5.3.3  PSES	  2-25

          2.5.4   Additional  Cost Factors	  2-25

                2.5.4.1  Temperature  (Biological Treatment Processes).  2-25
                2.5.4.2  Land Cost	  2-28
                2.5.4.3  RCRA Baseline Costs for Surface Improvements.  2-29

3.0  TECHNOLOGY COST DATA	  3-1

     3.1  Activated Sludge	  3-2

          3.1.1   CAPDET	  3-2

-------
           3.1.1.1  The CAPDET  Computer Model	  3-2
           3.1.1.2  Sensitivity Analysis	  3-7
           3.1.1.3  Benchmark Analysis	  3-11

3.2  Activated Sludge System Upgrades	  3-22

     3.2.1  Activated Sludge System Upgrades Cost Estimates	  3-23

3.3  Steam Stripping	  3-47

     3.3.1  Data Collection and Review	  3-47
     3.3.2  Steam Stripping Cost  Estimates	  3-51
     3.3.3  Steam Stripping Design Analysis	  3-53

3.4  Activated Carbon Systems	  3-65

     3.4.1  Large Activated Carbon Systems Cost Estimates	  3-65
     3.4.2  Small Activated Carbon Systems Cost Estimates	  3-88

3.5  Coagulation/Flocculation/Clarification Systems	  3-106

     3.5.1  Coagulation/Flocculation/Clarification Systems
             Cost Estimates.	  3-96
     3.5.2  Benchmark Analysis	,	  3-106

3.6  Chemically Assisted Clarification	  3-109

     3.6.1  Chemically Assisted Clarification  Systems  Cost
             Estimates	  3-109
     3.6.2  Benchmark Analysis	  3-117

3.7  Filtration Systems	  3-121

     3.7.1  Filtration Systems  Cost Estimates	  3-122
     3.7.2  Benchmark Analysis	  3-135

3.8  Polishing Ponds	-*-...  3-138

     3.8.1  Polishing Ponds Cost  Estimates	  3-138
     3.8.2  Benchmark Analysis	  3-146

3.9  Contract Hauling	  3-152

     3.9.1  Contract Hauling Cost Estimates	  3-152

3.10 Monitoring Costs	  3-155

     3.10.1  Monitoring Cost Estimaes	  3-155
     3.10.2  Benchmark Analysis	  3-158

3.11 Sludge Disposal (Incineration)	  3-166

       3.11.1  Sludge Dewatering	  3-166

           3.11.1.1  Sludge Dewatering Cost Estimates	  3-167

-------
           3.11.2   Sludge Disposal	  3-170

                3.11.2.1  Sludge Disposal Cost Estimates	  3-178

            3.11.3   Annualizing Sludge Disposal Costs	  3-183

     3.12.1  RCRA Baseline  Costs	  3-188

            3.12.1   Introduction	  3-188
            3.12.2   RCRA Cost Estimates	  3-189


4.0  USER MANUAL FOR THE COMPUTERIZED COSTING PROCEDURE FOR THE
      OCPSF INDUSTRY	  4-1

     4.1  Introduction	  4-1

     4.2  Costing Procedures	  4-1

          4.2.1 Part A Only Submissions	  4-1
          4.2.2 Part B and C Submissions	  4-2

     4.3  Procedure for Costing BPT	  4-3

     4.4  Procedure For Costing BAT	  4-3

     4 .5  Procedure For Costing PSES	  4-3

     4.6  BPT, BAT, and PSES Computer Program	  4-3

          4.6.1  Introduction	  4-3
          4.6.2 BPT, BAT & PSES Worksheets	  4-4

     4.7  BPT Linear Database	  4-7

     4.8  BAT Spreadsheet	  4-8

          4.8.1 BAT Linear Database	  4-9
          4.8.2 Transferring Data Between BAT Spreadsheet
                  and Database	  4-9

     4.9  PSES Spreadsheet  and Linear Database	  4-9

     4 .10 MACROS	  4-10

     4.11 Advanced File and Data Manipulation	  4-11

          4.11.1  Developing A Values Only Database	  4-11
          4.11.2  Creating  A Values Only File	  4-11

     4.12  Database Management	  4-12


APPENDICES

  A ~ State Land Factors
  B - Equations for Computerized Cost Curves and Equations for Computerized
       Land Requirements  Curves
  C - Summary of Costing  Approach used for Biological Upgrades

-------

-------
                          2.0 NEW COSTING METHODOLOGY



2.1  INTRODUCTION AND OVERVIEW

     The development of effluent guidelines limitations involves the following

elements:

     o  Identification of technologies available for reducing the pollutant
        loads in industry effluents.

     o  Quantifications of the pollutant reduction attainable by each technology
        or groups of technologies.

     o  Identification of the costs associated with the application of each
        technology or group of technologies.

     A hypothetical summary of this analysis  would be as follows:


                                BAT options for Pollutant X
Effluent •
Quality
Pollutant X
Technology Option ug/1
1 1,000
2 100
3 10
Industry
Pollutant
Reduction
Attainable,
Pounds per year
1,000
10,000
100,000
Industry
Costs,
$/yr
300,000
800,000
2,000,000
     The results of these analyses are then used to determine which option

should be chosen as the basis for the regulation.


     The discussions presented below summarize the technologies available to

the OCPSF industry for reducing conventional,  non-conventional, and toxic

pollutants.  Detailed assessments of these technologies will be presented in

other reports and ultimately in the Control and Treatment Technology section of

the Development Document.
                                      2-1

-------
     After a review of the available technologies, technology-based regulatory

options for BPT,  BAT,  and PSES are presented.   A costing methodology is then

included which can be used for determining the cost for meeting each regulatory

option on a plant-by-plant basis.


2.2  TECHNOLOGIES AVAILABLE TO THE OCPSF INDUSTRY

     The following discussions outline the technologies available to the OCPSF

industry, the pollutants removed by each, and the number of plants that current1

use each technology.


2.2.1  In-Plant Controls


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 solvent recovery units, and design

and construction of better solvent recovery columns to strip solvents beyond

the economical recovery point.  The economical recovery point has been reached

when the cost of recovering additional solvent (less the value of the recovered

solvent) is greater than the cost of treating or disposing of the remaining wast

solvent.

       o  Pollutants Treated - Solvents such as Benzene, Toluene, Methylene
                               Chloride, etc.


Activated Carbon Adsorption

       Adsorption on granular activated carbon (GAG) is an effective and,

moreover, a commercially established means of removing dissolved organic specie;

from aqueous waste  streams.  Contaminants are removed from solution by a three-
                                      2-2

-------
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.  Even-




tually the surface of the carbon is saturated and when this occurs, replacement




of the adsorber system with fresh (i.e., virgin or reactivated) carbon is required.






       Both powdered activated carbon (PAC) and GAG are capable of efficiently




removing many pollutants, including toxic and refractory organics.  Powdered




carbon is most frequently added to biological treatment processes and is not




recovered.




       o  Pollutants Treated - BOD, COD, TOG, and all organic priority pollutants.






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 volatile




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 commonly employed as an in-plant technology for solvent




recovery, steam stripping is also used as a wastewater treatment'process.




       o  Pollutants Treated - All volatile organic pollutants.




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 pumping waste




and acrylonitrile liquor.  This process is applicable particularly as in-plant
                                      2-3

-------
and end-of-pipe treatments of wastes with a high organic content.  Chemicals con

used as oxidizing agents include chlorine,  hypochlorite, hydrogen peroxide,

potassium permanganate, ozone, and chlorine dioxide.

       o  Pollutants Treated - cyanide,  sulfide,  ammonia, and most organic
          compounds.


Precipitation/Coagulation/Flocculation

       Gravity clarification may be supplemented by precipitation, coagulation

or flocculation which provides enhanced heavy metals and suspended solids remova

Precipitation, coagulation or flocculation may also be used as a primary treatme

step to protect biological secondary treatment processes from upset caused by

toxic metallic pollutants.

     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 is added.  Coagulation is usually

accomplished by adding an appropriate chemical (alum, lime, etc.) followed by a

rapid mix and finally a slow agitation to promote floe particle growth.

A polymeric coagulant aid is sometimes used in these systems.

       o  Pollutants Removed - Suspended solids and any other pollutants in
          suspension.


2.2.2  End-of-Pipe Treatment


Equalization

       Equalization consists of a wastewater holding vessel or a pond large enot

to dampen flow and/or pollutant concentration variation which provides 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
                                      2-4

-------
short circuiting.  Equalization is employed prior to wastewater treatment

processes that are sensitive to fluctuations in waste composition or flow.

       o  Pollutants Treated - Improves the treatment efficiencies of down-
          stream technologies.


Neutralization

       Neutralization is practiced in industry to raise or lower the pH of a

wastewater stream.  Alkaline wastewater may be neutralized 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.

       o  Pollutants Treated - pH.


Clarification

       Clarification, in this context, is 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.

       o  Pollutants Removed - Suspended solids and any other pollutants in
          suspension.


Flotation

       Flotation is used to remove oils and other suspended substances with

densities less than that of water or, in the case of dissolved air flotation,

particles that may be slightly heavier than water.  As with conventional

clarifiers, flocculants are frequently employed to enhance the efficiency of

the flotation units.  Although flotation is often referred to in the context

of dissolved air flotation, other technologies such as oil/liquid skimming and
                                      2-5

-------
solids skimming are also flotation operations, and are sometimes an integral

part of standard clarification.

       o  Pollutants Treated - Suspended solids, oil and grease, and any other
          pollutants in suspension.


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 reaction to proceed.   Under these conditions the

reduction of biologically assimilable pollutants will take place in a reasonably

predictable manner.  Biological treatment is based on the ability of microorgani

to utilize organic carbon as a food source.  The treatment is classified as eith

aerobic,'anaerobic, or facultative.  Aerobic treatment requires the availability

of free dissolved oxygen for the bio-oxidation of the waste.  Anaerobic treatmen

is intolerant of free dissolved oxygen and utilizes "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 degeneration, degree of mixing, effects of photosynthesis, and other

factors which contribute to the supply and distribution of oxygen to the

treatment system.  Facultative lagoons are designed to utilize both aerobic

and anaerobic mechanisms as a means of reducing the net sludge production.


     Biological treatment processes are widely used and, if properly designed

and operated, are capable of high BOD removal efficiencies.  Such systems given
                                      2-6

-------
                                                                                 ' t
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.






     o  Pollutants Treated - BOD, TSS, COD,  TOG, and certain priority pollutants.






2.2.3  Secondary Effluent Polishing Technologies




     In some instances, where secondary treatment does not produce a satisfactory




effluent, polishing processes are utilized.   Depending on the nature of the




pollutant to be removed and the degree of removal required, the polishing




treatment system can consist of a one unit operation or multiple-unit operations




in series.






Polishing Ponds   .                                                         •    •




       Polishing ponds can be used 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.




       o  Pollutants Treated - TSS and any other pollutant in suspension.






Powdered Activated Carbon Treatment




       Powdered activated carbon treatment (PAC) refers to the  addition of powdered




carbon to the aeration basin in the activated sludge process.  It is a recently




developed process that has been shown to upgrade effluent quality in conventional




activated sludge plants.  In the PAC treatment process the carbon concentration




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.




       o  Pollutants Treated - BOD, COD,  TOG, and certain priority pollutants.
                                      2-7

-------
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 as a polishing treatment technology.






     An aspect of granular 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 bio-




degradation rather than from adsorption.




     o  Pollutants Treated - BOD, COD, TOC, and certain priority pollutants.






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.




       o  Pollutants Treated - TSS and any other pollutants in suspension.






2.2.4  Zero or Alternate Discharge






     Zero or alternate discharge is defined as no discharge at the OCPSF 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 geologic;




requirements of the system.  There must be a substantial and extensive impervioi
                                      2-8

-------
caprock strata overlying a porous strata which is not used as a water supply




or for other withdrawal purposes.






     Because of the potential hazard of contaminating usable 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 fissures in the




caprock which allow the waste to escape into the usable 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




intensified by the increased subterranean pressure created by the injection well




and could be further intensified if a substantial withdrawal of water from the




usable aquifer were made in the vicinity of 'the eaprock flow.






       Deep wells are drilled through impervious caprock layers into such




unusable 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 suspended solids is normally




required to avoid plugging of the receiving strata.  Additional chemical




conditioning could be required to prevent the waste and the constituents of the



receiving strata from reacting and causing plugging of the well.






       Because of the relatively high pressures required for injection and




dispersion of the waste, high pumping costs for deep well disposal may be




incurred.






Contract Hauling                                 ^






       Another method of achieving zero discharge is contract removal and
                                      2-9

-------
disposal.  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 treat-




ment 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 disposal.




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 treated and discharged elsewhere.






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 treatment 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 install a centralized facility to




handle all wastes from their facilities.  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 restrictions imposed by the




receiving treatment plant, wastes sent for offsite treatment may require




pretreatment at  the generating plant.






Incineration




       Incineration is a frequently useli zero-discharge method in the OCPSF




industry.  Depending upon the heat value of the material being incinerated,




incinerators may or may not require auxiliary fuel.  The gaseous combustion or
                                      2-10

-------
composition products may require scrubbing, particulate removal, or another




treatment to capture materials that cannot be discharged 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 which are not




amenable to the usual EOF treatment technologies.






Evaporation




       Evaporation is used in the OCPSF industry to reduce the volume of waste




water and thereby concentrate the organic content to render it more suitable




fbr incineration or disposal to landfill.  This technology is normally used as




in-plant treatment or pretreatment for incineration or landfill.






       Evaporation equipment can range from simple open tanks to large,




sophisticated, 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 limitation to mechanical evaporation




is the amount of energy required.






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,  temperature, humidity and




wind velocity combine to cause a net loss of liquid in the pond.  If a net loss




does not exist, recirculating sprays,  heat or aeration can be used to enhance
                                      2-11

-------
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 con-




struction.  Since there is a great potential for contamination of the shallow




aquifer from percolation, impoundment ponds are frequently lined or sealed.




Solids which accumulate 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.






Land Disposal




       There are two basic types of land disposal:   landfilling and land




application (or spray irrigation).  Landfilling consists of dumping the wastes




into a pit and subsequently burying them.  Land application requires 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 at the time of application may persist in the soil for




long durations and later may be assimilated by the crops and find their way int




the food chain.






2.3  CURRENT TREATMENT PRACTICES IN THE OCPSF INDUSTRY




     All of the Treatment Technologies discussed above are in use in the OCPSF




industry.  Table 2.1 presents a summary of treatment practices identified in th




new 308 data base, Table 2.2 presents the technologies included in the daily da




plants, and Table 2.3 presents the technologies associated with the 12 new toxi




field sampling plants.
                                      2-12

-------
                                   TABLE 2.1

              TECHNOLOGIES  USED  BY  PLANTS IN THE NEW  308 DATA BASE
Technology                                           Number of Plants

Steam Stripping                                          75

Flocculator                                              49

In-plant Carbon Adsorption                               16

All Other In-plant Controls                             260

Biological Treatment                                    122

One or more In-plant Controls plus                       55
 Biological Treatment

Biological Treatment plus Filtration                     77

Biological Treatment plus Polishing .Ponds                 34

Biological Treatment plus Activated Carbons               24

Zero or Alternative Discharge Technoiogies               331
                                      2-13

-------
                                   TABLE  2.2




     TECHNOLOGIES  USED  BY  THE  DAILY DATA  PLANTS FROM NEW  308 QUESTIONNAIRE
Technology                                            Number  of  Plants




Activated Carbon without Biological Treatment               2




Metals Removal                                            14




Ion Exchange                                               2




Steam Stripping                                           21




Solvent Extraction                                         5




Biological Treatment                                      48




Biological Treatment plus Polishing Ponds                   4




Biological Treatment plus Activated Carbons •               4   .




Zero or Alternative Discharge Technologies                11
                                      2-14

-------
                                   TABLE 2.3




               TOXIC SAMPLING DATA FROM NEW FIELD  SAMPLING EFFORT
Technology                                            Number  of Plants




Activated Carbon                                           1




Steam Stripping                                            4




Metals Removed                                             2




Biological Treatment                                       10




Biological Treatment plus Polishing Ponds                   1




Biological Treatment plus Filtration                       3




Biological Treatment plus Activated Carbon                 2
                                      2-15

-------
2.4  TECHNOLOGY OPTIONS AND COST CURVE DEVELOPMENT

2.4.1  Technology Options

     A minimum of three technology options have been identified for each regulat

Table 2.4 presents a summary of these options.  Each technology option must be

considered and separately evaluated for each subcategory in the industry.  For

example, the final BAT regulations can be based on Option 1 for one subcategory,

Option 3 for another, and Option 4 (contract hauling) for subcategories with

low flow rates or hard to treat effluents.


2.4.2  Cost Curve Development

     In order to derive costs associated with the technology options, cost

curves for the following technologies were developed:

   •  o  Activated Sludge (CAPDET)
     o  Biological Treatment Upgrade
     o  Steam Stripping
     o  In-plant and End-of-Pipe Carbon Adsorption
     o  Coagulation Flocculation
     o  Chemically Assisted Clarification
     o  Filtration
     o  Polishing Ponds
     o  Contract Hauling
     o  Monitoring
     o  Sludge Disposal (Incineration)

     Chapter 3 presents the detailed development of the costs for each of

these technologies; however, the following list presents the general approach

used:

     o  All costs are derived in 1982 dollars.  Where data were collected for
        other years, they were corrected to 1982 dollars using the ENR index.

     o  Actual plant cost data were used, where possible, to derive the cost
        curves.  Where they were not sufficient, the data that was available
        was used to benchmark the cost curves derived.

     o  CAPDET was used to derive costs or cost curves for biological
        treatment, upgrade activated sludge, activated carbon and filtration.
        The resultant cost curves were benchmarked with actual plant data.

     o  The design bases for filtration were based upon industry practice.
                                      2-16

-------
4J
C oo
i «
4J >
03 0)
0) fl
H
C
O
^H ^^
u be
a. o
O *H
O
e
u
0)
H



4J
C
a; 09
S ft
4J CD
CO >
01 0)
0 Id J
H
e
o
•H
4-J PS
a u
O 0
0
c
£
en u
Z 0)
0 H
M
H
0-
O
9- . e
8 § 03
i-J 4J iH
O CO O>

x id 01
CJ CM H fl
U
H C
O
h. ft
en *J >•,
a- o. be
0 O 0
O "•»
0
J3
CJ
01
H




4J
C
O) CO
e fi
4J Q)
CO >
01 01
h _j
-H H

C
O
•u >,
a OG
o o

o
c
j=
u
01
H





C
o
•H
4.J
CO

3
be
Q>
ft!























4C



c
o
v,
iH ffl
CO O
U
i-l 13
bO 09 01
0 3 *->
•H fl CO
o a. >
fi t-i
CO 4j
CJ
•<

•

. *





ca
^j
c
fl O
CO Ou C
CJ O
IH bO fi
bO en C 4-1
O 3 1-1 t-t co
I-H fl .n O M
O O. 09 4-1
•H fl ft
(O fl fl
a.






^e





u
fl ••-.
CO ^ p •
u e
ft O> .
bo e >
O 4J ft
rd CO 3
O 01 CJ"
•H ^l 0)

^4
0
^^








H
Q-
eo


o







4-1
cj bo
CO C
^4 *H

C 3
O CO
CJ B







•K







es TJ
01
c *-> e
O 00 CO O
•H 3 > jO
*J fl 1-1 Id
O. O. 4J <0
O CJ CJ'
•<



* c
0
•H
4-1
CO 4-1
fl C

60 C O g
e o cj w
•H ja o co
G. - i-H 01
a co b id
•H CJ "^ H
u c
u T: o fi
en 01 -H co co
u 4J 3 o
E « cfl i-t i-l
co > <-> o. M
QJ -H 3 O
4J 4J 5c i-i
en u co o
< O -H
CJ to



«





CJ

« 4-1 a-
u c
•H 01 «
be e >
O *-> -H
fl CO 3
o oi a-
•H Id 0)
PO H

0
•*-*








H



O





















*








4J

bo co -^
CO 0) 4-1
O 4-1 0
cj en <




•K











en
w
en
a*

O
Z







en
M
en
DO Pu







.





09
01
n
_j
CO
c
CO

J=
4J

Ud
O

c
0
1-1
4J
o>
ft
81
o
CJ

e
o
a
3

01
^^

CO
iH
•H
co
>
03

QJ
J3

iH
fl
i-l
S

e
o
id
4-1 •
a co
0 4J
CO
^"* ^3
O bO
^ C
O «H
C fl
•S &
0) CO
4-1 CO

cj o)
CO C
01
T3
0 io
14-1
CO
CO U
fl CO
01 -^)
>
01 >s
fl fl
•H
4J CO
C T3

E 0)
01
Id fl
4J fl
CO
01
f. >4d
eo H O
01
4J «
O
Z
2-17

-------
                                                                           3
     o  The design bases for activated carbon were based on industry practice,
        and included actual priority  pollutant removal data.

     o  Polishing ponds, coagulation/flocculation, chemically assisted
        clarification,  contract  hauling,  sludge disposal (incineration)
        and monitoring costs were based on actual manufacturer quotations.

     o  Steam stripping costs are based on actual plant data.


2.5  DETAILED COSTING PROCEDURES OCPSF INDUSTRY


2.5.1  Introduction

     The purpose of this procedure is to provide the basis for the determinatioi

of costs for meeting various regulatory options applicable to the OCPSF Industry

The methodology outlined below will allow for the calculation of capital and

operating costs on a plant-by-plant basis using actual plant  operating conditioi

The costs developed in this analysis are in 1982 dollars.  Section.2.5.2 outlini

the data that must be collected before the plant-by-plant analysis can begin,

and Section 2.5.3 presents the Technology Assessment Analysis for determining

which technology options can be costed for achieving each regulatory option.


2.5.2  Data Needs

     Prior to starting the costing estimates, the following data must be

collected for each OCPSF Facility:

     1)  Production Characteristics       a)  All product processes
                                          b)  Plant subcategory
                                          c)  Plant costing cell

     2)  Flow Data                        a)  Effluent flow
                                          b)  Total influent flow
                                          c)  Flow rates by product process
                                          d)  Flow rates for all in-plant contrc

     3)  Treatment Technology in place:   a)  In-plant
                                          b)  End-of-Pipe

     4)  Current  (1980) Performance Data  a)  Effluent data for BOD and TSS.
                                              If there are no BOD or TSS data, t
                                              assessment of the treatment in
                                              place must be undertaken.
                                      2-18

-------
                                          b)  Effluent  data  for  toxics.
                                             If  there  are no toxic data  for
                                             the plant,  the predictions  for  the
                                             presence  of priority pollutants
                                             must be obtained.
     Table 2.5 presents  a Cost  Worksheet  that  should be used with each plant-by-

plant analysis.


2.5.3  Technology Assessment Analysis

     The following presents  the methodology  for  costing BPT and BAT:

2.5.3.1  BPT

Regulatory Options 1  and 2:

I.  ACTIVATED SLUDGE  IN  PLACE
    A. A  BOD 0-3 mg/1 and;

        1.  A  TSS 0-3 mg/1

        2.  A  TSS > 3 and Target TSS >  20


        3.  A  TSS > 3 and Target TSS _<  20



    B. A  BOD > 3-15 mg/1 and,

        1.  £±  TSS 0-3 mg/1

        2.  A,  TSS > 3 and Target TSS >  20



        3.  A  TSS > 3 and Targe TSS _< 20




    C. A  BOD > 15-25 mg/1 and;

        1.  A  TSS 0-3 mg/1
                                                SYSTEM TO COST
   0 COSTS

Tertiary Clarifier (Filter/
Polishing Pond* if T.C. in place)

Tertiary Clarifier and Filter/
Polishing Pond*(if T.C. in place
cost only Filter/Polishing Pond)
Improved Operating Procedures

Imp. Op. Procedures and Tertiary
Clarifier (Filter/Polishing Pond*
if T.C. in place)

Imp. Op. Procedures, Tertiary
Clarifier and Filter/Polishing
Pond* (if T.C. in place cost only
Filter/Polishing Pond)
Imp. Op. Procedures and Tertiary
Clarifier (Filter/Polishing Pond*
if T.C. in place)
                                      2-19

-------
                                               SYSTEM TO COST

        2.  A  TSS > 3 and Target TSS > 20      Imp. Op. Procedures and Tertiar1
                                               Clarifier (Filter/Polishing Pon<
                                               if T.C. in place)

        3.  A  TSS > 3 and Target TSS £ 20      Imp. Op. Procedures, Tertiary C!
                                               and Filter/Polishing Pond* (if '
                                               in place cost only Filter/Polis
                                               Pond)

    D. A  BOD >  25 mg/1  and;

        1.  A TSS 0-3 mg/1                     Second stage biological

        2.  A TSS > 3 and Target TSS > 20      Second stage biological

        3.  A TSS > 3 and Target TSS £ 20      Second stage biological and Fil
                                               Polishing Pond (if filter is in
                                               place cost only Secondary Bio-
                                               logical)

II.  ACTIVATED SLUDGE NOT IN-PLACE

    A. A .BOD 0-3 mg/1  and;

        1.  A TSS 0-3 mg/1                     0 COSTS

        2.  A TSS > 3 and Target TSS > 20      Tertiary Clarifier (Filter/
                                               Polishing Pond* if T.C. in plac

        3.  A TSS > 3 and Target TSS <_ 20      Tertiary Clarifier and Filter/
                                               Polishing Pond* (if T.C. in pla
                                               cost only Filter/Polishing Pond

    B. A  BOD >  3-15 mg/1  and,

        1.  A TSS 0-3 mg/1                     Tertiary Clarifier (Filter/
                                               Polishing Pond* if T.C. in plac

        2.  £* TSS > 3 and Target TSS > 20      Tertiary Clarifier (Filter/
                                               Polishing Pond* if T.C. in plac

        3.  A TSS >  3 and Target £ 20          Tertiary Clarifier and Filter/
                                               Polishing Pond* (if T.C. in pla
                                               cost only Filter/Polishing Pond

    C. A  BOD >  15 mg/1 and;

        1.   A TSS 0-3 mg/1                     Activated Sludge

        2.   A TSS > 3 and Target TSS > 20      Activated Sludge

        3.  A  TSS >  3 and Target TSS < 20      Activated Sludge and Filter/Pol
                                               Pond (if a filter is in place
                                               cost only Activated Sludge)

*  If  the maximum monthly average temperature  is greater than 25°C add a filter,
   otherwise add a polishing pond.


                                     2-20

-------
                                       TABLE 2.5

                              COST WORKSHEET INFORMATION
  I  PRODUCT GROUP NAME   PROCESS NAME
     PVC Resin
     Polyvinyl Acetate
     Vinyl Acetate-
     Acrylic Resins
Susp. Polymer of
Vinyl Chloride

Emulsion Polymer
of Vinyl Acetate

Emulsion Polymer
of Vinyl Acetate &
N-Butyl Acrylate
TYPE AND
NUMBER OF
PROCESS
WASTEWATER
Al la
A2 Ib
Al 2a
TREATMENT
WASTE STREAM
CODE
001
002
FLOW (MGD)
.327
.040
Al 3a
 .ANT CONTROLS TREATMENT

 SATMENT WASTE STREAM CODE

     001

     002     . ,

 3F-PIPE TREATMENT

 ELIMINARY TREATMENT
 ASTE STREAM CODE

     001

     002

     003
          TYPE OF TECHNOLOGY

                C5a

                C5a
          TYPE OF TECHNOLOGY


        Dla, D2a, Dlla, D9a, D12a,

        Dlb, D2b

        Dla, D2a, Dlla, D9a, D12a
003
0.14
              AVG. PROCESS WASTEWATER(MG

                        .06
                        .131
              AVG. PROCESS WASTEWATER(MG


                        .06

                        .130

                        .192
CONDARY TREATMENT
ASTE STREAM CODE

     001, 003

     002
          TYPE OF TECHNOLOGY


        El, Ella, Ellb

        Ellb
              AVG.  PROCESS WASTEWATER(MG


                        .252

                        .131
IRTIATY TREATMENT
ASTE STREAM CODE

001, 002, 003
          TYPE OF TECHNOLOGY
        Fla
              AVG.  PROCESS WASTEWATER(MG
                        .382
                                        2-21

-------
                                    TABLE 2.5 (cont.)
  MISC. WASTEWATER CODE
LOCATION AT WHICH WASTEWATER
ENTERS MAIN TREATMENT SYSTEM
VOLUME OF MISC.
WASTEWATER (MGD
B2
B5
DATA
IN-PLANT CONTROL
POLLUTANTS
2
BODs
TSS
BOD 5
TSS
2
3
4
86
TOC
114
117
127
121
Dla
Dlb, Ela

TREATMENT
TREATMENT TECHNOLOGY INFLUENT CONCENTRATION
C5 400 ppm
Ela 372 ppm
Ela . 17 ppm
Hla
HI a
Hla
Hla
Hla
Hla
Hla
Hla
Hla
Hla
Hla
.09
.026


EFFLUENT CONCE
1.0 p pm


7 ppm
15.4 ppm
.03 ppm
.03 ppm
2.0 ppb
50.0 ppb
28.0 ppm
.01 ppm
.01 ppm
.01 ppm
.01 ppm
EFFLUENT TARGETS (REGULATORY OPTION)
                                            2-22

-------
                                TABLE  2.5  (cont.)
                                                                           I-  i .  ' ;H)


'ERENCE BETWEEN  ACTUAL  PERFORMANCE  AND  EFFLUENT  TARGETS


   BPT (BOD and  TSS)

)   a)  BAT or

   b)  Pollutants  to  be Treated Based  on Product/Process  Evaluation

1NOLOGY REQUIRED BASED  ON  FLOW, POLLUTANT, ETC.


)   BPT

)   BAT


DESIGN CRITERIA USED FOR  COSTING  (By  Technology):

   1)  Flow

   2)  Other

TREATMENT COSTS (By  Technology):

   1)  Capital Costs

   2)  Operating Costs

TOTAL TREATMENT COSTS

   1)  Capital Costs

   2)  Operating Costs


Note:  The following represents the definitions of  the various wastestream and
        treatment  codes used  in this example of  the  cost  worksheet:

Al  - Aqueous wastestream from reactors,  raw material recovery and solvent recovery
A2  - Non-aqueous wastestream from reactors, raw material  recovery and solvent recovery
C5  - Steam Stripping
D2  - Neutralization
Dl  - Equalization
HI  - Direct Discharge
B2  - Cooling Tower  Slowdown
Dll  - Flocculation
D9  - Primary Clarification
D12  - Nutrient  Addition
El  - Activated Sludge
Ell  - Secondary Clarification
Fl  - Polishing Pond
B5  - Air Pollution  Control  Wastewater
                                         2-23

-------
Regulatory Option 3:
         A.  In addition to the costs determined in 2.5.3.1, an end-of-pipe
             activated carbon system should be coated for each facility, if
            "there is not one already present.

         B.  As an alternative, the costs for contract hauling should also be
             determined.
2.5.3.2  BAT


Regulatory Option 1:

         No additional costs to those calculated in 2.5.3.1.

Regulatory Option 2:

         A.  Alternative 1

             In addition to the costs calculated in 2.5.3.1, the following
             additional costs should be determined:

             a)  For plants with metals in their RWL, coagulation/flocculation
                 should be costed (only if this technology is not already in
                 place).

             b)  For plants with volatile organic pollutants in their RWL,
                 steam stripping should be costed (only if this technology is
                 not already in place).

             c)  For plants with base-neutral or acid priority pollutants, in-
                 plant activated carbon should be costed (only if this technolo
                 is not already in place).

         B.  Alternative 2

             As an alternative, the costs for contract hauling should also be
             determined.

Regulatory Option 3:

         A.  Alternative 1

             The costs for this Regulatory Option are the summation of the
             costs determined for BPT options 1 and 3, and BAT option 2.

         B.  Alternative 2

             As an alternative, the costs for contract hauling should also be
             determined.
                                      2-24

-------
Regulatory Option 4:

         A.  Contract hauling should be costed for all facilites.


2.5.3.3  PSES'


Regulatory Option 1:

         There are no costs associated with this Regulatory Option.


Regulatory Option 2:

         A.  Alternative 1

             a)  For plants with metals in their RWL, coagulation/flocculation
                 should be costed (only if this technology is not already in
                 place).

             b)  For plants with volatile organic pollutants in their RWL,
                 steam stripping should be costed (only if this technology is
                 not already in place).

             c)  For plants with base-neutral or acid priority pollutants, in-
                 plant activated carbon should be costed (only if this technology
                 is not already in place).

         B.  Alternative 2

             As an alternative, the costs for contract hauling should also be
             determined.

Regulatory Option 4:

         Contract hauling should be costed for all facilities.

2.5.4  Additional Cost Factors

2.5.4.1  Temperature (Biological Treatment Processes)

     In order to take into account the affect of temperature, the following

factor has been derived:

       Temperature      /    \ 0.7
       Correction     !
         Factor
                                      2-25

-------
     where kB - Base Line k
          kS - k  rate  estalished  for  each  State
          0.7 - Cost Scale Factor

     The ratio  ^B  is derived  from the  following general equation:


                        (TS-TB)
          ks - kB x 0

     where   0  -1.07
       and TB - 208C

     Therefore,

          fcs  - 1.07
     Thus, the temperature correction factor is:
     Table 2.6 presents Ts  and the corresponding cost factor for each State.


     These values are based upon the state's actual minimum monthly average

ambient temperature.   In order to account  for the fact that wastewater only

approaches ambient temperature but never actually reaches ambient conditions,

a 5°C differential was used to calculate Ts, with 5°C being the lowest water

temperature attainable.  It should be noted that some plant's wastewater are

actually hot 12 months per year.  20°C will be the highest T established.


     Table 2.6 also presents each state's  average monthly maximum ambient

temperature.  Warm temperatures can cause  algae blooms in polishing ponds;

therefore, plants in states with average maximum ambient  temperatures over 25°C

will have filtration systems rather than polishing ponds.


     The T values shown in Table 2.6 will  be used when running CAPDET for activ,

sludge.  The cost factors shown on Table 2.6 will be used to adjust the biologii

upgrade costs.
                                      2-26

-------
                                         TABLE 2.6

-

State
Alabama
Alaska
Arltona
Arkansas
California
Colorado
Conn* ctl cut
Dtlawar*
Florida
Georgia
Hawaii
Idaho
Illlnoli
Indiana
I ova
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Mlnneaota
Mississippi
Missouri
Montana
Nebraaka
Nevada •
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Puerto Rico
Rhode Island
South Carolina
South Dakota
Tennessee
Texaa
Utah
Veramnt
Virginia
Washington
West Virginia
Wlaconain
Wyoming
Source of Data:
Minimum
Monthly Average
Temperature
CO (1)
8
-13
6
4
8
-6
-2
0
16
7
22
-2
-4
-6
-7
-2
0
10
-12 .
1
-3
-5
-13 '
8
-1
-8
-6
-1
-6
0
2
-3
6
-1*
-3
3
2
-2
2*
-1
8
-9
4
8
-3
-8
3
-3
0
-8
-6
National Oceanic and
United Stated through 1979(thirty yea:
                                               Maximum
                                           Monthly Average
                                            Temperature
                                             CO (1)

                                                  27
                                                  12
                                                  28
                                                  28
                                                  21
                                                  23
                                                  23
                                                  24
                                                  28
                                                  27
                                                  26
                                                  23
                                                  24
                                                  24
                                                  23
                                                  26
                                                  25
                                                  28
                                                  23
                                                  25
                                                  22
                                                  21
                                                  20
                                                  27
                                                  26
                                                  21
                                                  24
                                                  25
                                                  21
                                                  24
                                                  25
                                                  23
                                                  25
                                                  21
                                                  23   '
                                                  28
                                                  19
                                                  23
                                                  27
                                                  21
                                                  27
                                                  23
                                                  27
                                                  28
                                                  24
                                                  23
                                                  25
                                                  21
                                                  23
                                                  21
                                                  21
T
i!£l
13
5
11
9
13
5
5
5
20
12
20
5
5
5
5
5
5
IS
5
6
5
S
5
13
5
5
5
5
5
5
7
5
11
5
5
8
7
5
20
5
13
5
9
13
5
5
8
5
5
5
5
Comparison
Cost
factor
1.4
2.0
1.5
1.7
1.4
2.0
2.0
2.0
1.0
1.5
1.0
2.0
2.0
2.0
2.0
2.0
2.0
1.3
2.0
1.9
2.0
2.0
2.0
1.4
2.0
2.0
2.0
2.0
2.0
2.0
1.8
2.0
1.5
2.0
2.0
1.8
1.8
2.0
1.0
2.0
1.4
2.0
1.7
1.4
2.0
2.0
1.8
2.0
2.0
2.0
2.0
Climatic Data for the
As hevllie,  North Carolina
                                            2-27

-------
2.5.4.2  Land Cost




     Due to continuing urbanization, the cost of land available for wastewater




treatment plant sites has increased substantially in recent years,  and can be




a signifacant part of the initial plant cost.






     The area required for the plant site depends upon plant capacity, type of




treatment, treatment components, site topography and requirements for antici-




pated plant expansions.  The area of land actually purcahsed may also be in-




fluenced by the size of tracts available at the selected plant location.






     Since land costs may vary widely from place to place, it is difficult to




obtain a nationwide average figure.  However, based on an industrial real estat




market survey report (prepared by the Society of Industrial Realtors in 1983),




average land costs for suburban sites of each state can be obtained.  The




results are presented in Table 2.5.1 and 2.5.2.






     Table 2.5.1 shows the estimated unit land prices for the unimproved suburb




sites of major cities and the average for each state.  The unimproved sites are




also in the top 25 percent of overall desirability of the existing inventory




and zoned for industrial use.  Streets and utilities may not yet-be installed




but are reasonably close and available.  Rail serice may, or may not be




available.  Table 2.5.2 is a summary of the estimated land prices for each




state.  For those states that have no land prices available, the regional




average figures were used.  For example, in the Northeast region, no land price




are available for the states of Maine, Rhode Island and Virginia, therefore the




regional average figure of $24,700 was used for these states.  Table 2.5.2 also




indicates that, in general, the average land price for the North Central region




is the least expensive one with an average of approximately $20,600.  The
                                      2-28

-------
Northeast and South regions have average land prices of $24,700 and $27,000,

respectively.  The averge land prices for the West region seems to be the most

expensive, ranging from $19,600 to $190,400 with an average of $72,600.


2.5.4.3  RCRA Baseline Costs for Surface Improvements

     In November, 1984, the RCRA Reauthorization bill was signed.  As a result,

costs must be determined for upgrading surface impoundments to comply with this

law.  Facilities that have "aggressive biological treatment processes" are

exempt from the requirements.  Aggressive Biological Treatment Facility means

a system if surface impoundment in which the initial impoundment of the secondary

treatment segment of the facility utilizes intense mechanical Aeration to

enhance biological activity to degrade wastewater pollutants and:

     1..  The hydraulic retention time in such initial impoundment is no longer
         than five days under normal operating conditions on an annual average
         basis;

     2.  The hydraulic retention time in such an initial impoundment is no
         longer than 30 days under normal operating conditions on an annual
         average basis, provided that the sludge in such an impoundment does
         not constitute a hazardous waste as identified by the extraction
         procedure toxicity characteristic in effect on the date of enactment
         of the hazardous and solid waste amendments of 1984;  or

     3.  Such a system utilizes activated sludge treatment in the first portion
         of secondary treatment.


     This includes all activated sludge and aerated lagoon systems.  Therefore,

RCRA baseline costs will only have to be determined for facilities with aerobic

lagoons, facultative lagoons, and anaerobic lagoons.


     Section 3.12 describes the procedure used in developing baseline costs for

the above mentioned facilities.
                                      2-29

-------
. 9
3
:s -
•SS
e .
at
M 9
iw
1 1



5 5 u 3 £ «d 2
OH • ,3
• n ^j b
CM £ g ^g «
a s~ ^S s
3 -8 S~
H =- ^3

j
i
sa §!

• xw ' i ii S OO
- * 3 u ^1 *"

Ifi
?!
3£

! i
i i

^«4 p» «n o
•Ml >4 • CM
^ U «l CM ...
B M Ml « O O O

:


e


e • 9
•* A U
• b •
<* 9 b

J M ?

^^ CM 0
•M| M9 -4
*O U **l CM • •
B M IMI « " O
• b 
iJ Q. 4»J ^

•o
•^

2

V
•4
8 ?
w ««
b
tM b «1
""I
**



CM O
•""!




s



g
*
M>




V
5u5
°°8
o
o"
CM



2

• o -»
° I
*
*4
«»•





8
•
b •*
S b il St
O °^
8- 1
s s
5

i 1
3*5 a

-------
                          •H
                  »-4      r« ••  U
                           ^ C Tl
                           :
                           S22S
                           o ooo
                   8
                                           §8
                                           i
    b

N b3
                                        °  I

                                            O
                                             2-31
                  •o u
                  B ««
                  sz*
                                                             M 
                                                                       s
                                                                        •
                                                                       O
                                                             U U  CM
                                                             
-------

ls|

-

^r3
J£H

*
iJTs
•J b •»•»
J ft, u>
a X
-. l
in a u
• O M
«M •*
3 I
H ,
O
X

^N
«N
IS U W
e »< »•
• b -»
J ft. 0>
*•*
B

^*


3
»ft ** «-* O O
f»* r> «*> »A 00
00 *-i O *-« Q O
9^
•••1
?,!!
V -1
3 >
J§ S
b^l-sl
•g-SSo-S
«0
fsi «n
CO O O
r*
O
« b
33
b «
5S
O 
5
s
b
• O -— v u u
o Q a ^ j — | t-«
e
o
a*
s i
• •
in b *J V*l .O O ^J
• o "^ ^ u **l M| tf*i »n b *^.
o «| b ^.1 ex ^ — o
«o J ft, <»j — i| n
J» in"
a
e
u
ill
2-32

-------
                        O b U
                        •004

                        O   O
       I
       W
       £

5






si
« h
^ *-






5

M
a
V
£
a.



<-O v>
1 1 f*
£ «
^
i2|






3







o o
^ o
vO N

*-*
^/^
W »v
C •
w
• 3 -g
?5 S

S53







S§5






8
u

1
       3


       3
                         *>   4
                         -» u -3

                                                       " O "s.
                                                      -   §
                                             2-33

-------
                                  TABLE 2.5.2

                  Summary of Land Costs in the United  States
Region

Northeast
State

Connecticut
*Maine
Massachusetts
New Hampshire
New Jersey
New York
Pennsylvania
*Rhode Island
*Virginia
AVERAGE
    Estimated
Land Price ($/Acre)

      20,000
      24,700
      39,200
      16,600
      44,400
      16,600
      11,800
      24,700
      24,700
                                                            $24,700
North Central
Illinois
Indiana
Iowa
Kansas
Michigan
Minnesota
Missouri
*New Mexico
Ohio
Nebraska
*North Dakota
*South Dakota
Wisconsin
AVERAGE
      32,700
      11,800
       7,400
       4,360
      10,500
      21,800
      32,700
      20,600
      15,200
      30,500
      20,600
      20,600
      39.200
     $20,600
South
Alabama
Arkansas
Delaware
Florida
Georgia
*Kentucky
Louisianna
Maryland
*Mississippi
North Carolina
Oklahoma
South Carolina
Tennessee
Texas
Virginia
Washington D.C.
*West Virginia
AVERAGE
       6,500
      21,800
      15,700
      36,600
      43,600
      27,000
      43,600
      19,600
      27,000
      16,600
      21,300
      11,800
      15,200
      47,000
      19,600
      65,300
      27,000
      $27,000
                                       2-34

-------
                              TABLE 2.5.2 (Cont.)


                                                          Estimated
Region       "          State                         Land Price ($/Acre)

West                    *Alaska                             72,600
                        Arizona                             65,300
                        California                         190,400
                        Colorado                            38,300
                        *Hawaii                             72,600
                        *Idaho                              72,600
                        *Montana                            72,600
                        Nevada                              34,800
                        New Mexico                          19,600
                        Oregon                              72,700
                        *Utah                               72,600
                        Washington                          87,100
                        Wyoming                             72,600
                        AVERAGE                            $72,600.
* Obtained from Regional Average Price

-------
IX.  SUPPLEMENT TO COSTING DOCUMENTATION AND NOTICE OF NEW INFORMATION REPORT
           Note:  Table of Contents and List of Tables follow;
                  entire Supplement is included in the Public Record

-------
               FINAL
             SUPPLEMENT
                 TO
        COSTING DOCUMENTATION
                 AND
  NOTICE OF NEW INFORMATION REPORT
            PREPARED FOR:

 The Industrial Technology Division
U.S. Environmental Protection Agency
         301 M. Street, S.W.
       Washington, D.C.  20460
                 By:

         SAIC/JRB Associates
           One Sears Drive
     Paramus, New Jersey  07652
            June 17, 1985
     EPA Contract No. 68-01-6947
   JRB Project No. 2-835-07-688-01

-------
                     FINAL SUPPLEMENT TO COSTING DOCUMENT
                     AND NOTICE OF NEW INFORMATION REPORT

                              TABLE OF CONTENTS
             Summary and Conclusions

        1.0  Introduction

        2.0  Subcategorization

        3.0  BPT Procedure

        4.0  BAT Costing Document

        5.0  PSES Costing Procedure

        6.0  Conventional Pollutant Parameter Loadings
Page

3453-3454

3455

3456-3457

3458-3459

3460-3461

3462

3463
                                  APPENDICES


Appendix A -'Summary of BPT Costs Generated

Appendix B - Summary of BAT Costs Generated

Appendix C - Summary of PSES Costs Generated
18015-18026

18027-18032

18033-18040

-------
                                LIST OF TABLES


Table 1  - Product/Process Codes And Names By Subcategory       3464-3499
           And Cost Group

Table 2  - Direct Discharger Only                               3500

Table 3  - BOD5 And TSS Targets For BPT Costing                 3501

Table 4  - Median Effluent 8005 and TSS Values By Subcategory   3502

Table 5  - BPT Costing Rules                                    3503-3505

Table 6  - Plastics BPT Spreadsheet                             3506

Table 6A - Organics BPT Spreadsheet                             3507

Table 7  - Comparison Of Factors For Large And Small Facilities 3508

Table 8  - K-Rates'And. MLVSS"Value For Organics'Plants  .        3509

Table 9  - K-Rates And MLVSS Values for Plastics                3510

Table 10 - Miscellaneous Wastewater Generation                  3511-3512

Table 11 - Raw Water Quality Parameters, Dilution Factors and   3513-3518
           Adjusted Water Quality Parameters

Table 12 - Average Influent Concentrations                      3519-3520

Table 13 - Raw Waste Load Concentrations For The Subcategory -  3521
           Cellulosics

Table 14 - Raw Waste Load Concentrations For The Subcategory -  3522
           Fibers

Table 15 - Raw Waste Load Concentrations For The Subcategory -  3523-3524
           Thermoplastics

Table 16 - Raw Waste Load Concentrations For The Subcategory -  3525-3527
           Thermosets

Table 17A- Raw Waste Load Concentrations For The Subcategory -  3528-3529
           Bulk Group - Aliphatics

Table 17B- Raw Waste Load Concentrations For The Subcategory -  3530
           Bulk Group - Amides/Amines

Table 17C- Raw Waste Load Concentrations For The Subcategory -  3531
           Bulk Group - Arotnatics

-------
                          LIST OF TABLES (Continued)
Table 17D- Raw Waste Load Concentrations For The Subcategory -   3533
           Bulk Group - Halogens

Table 17E- Raw Waste Load Concentrations For The Subcategory -   3534
           Bulk Group - Others

Table ISA- Raw Waste Load Concentrations For The Subcategory -   3535-3537
           Commodity Group - Aliphatics

Table 18B- Raw Waste Load Concentrations For The Subcategory -   3538-3540
           Commodity Group - Aromatics

Table 18C- Raw Waste Load Concentrations For The Subcategory -   3541-3543
           Commodity Group - Halogens

Table 19A- Raw Waste Load Concentrations For The Subcategory -   3544
           Speciali-ty Group - Aliphatics

Table 19B- Raw Waste Load Concentrations For The Subcategory -   3545
           Specialty Group - Amides/Amines

Table 19C- Raw Waste Load Concentrations For The Subcategory -   3546
           Specialty Group - Aromatics

Table 19D- Raw Waste Load Concentrations For The Subcategory -   3547
           Specialty Group - Halogens

Table 19E- Raw Waste Load Concentrations For The Subcategory -   3548
           Specialty Group - Others

Table 20 - Average Raw Waste Concentration Data For The     -    3549-3553
           Subcategory - Cellulosics

Table 21 - Average Raw Waste Concentration Data For The     -    3554-3559
           Subcategory - Fibers

Table 22 - Average Raw Waste Concentration Data For The     -    3560-3576
           Subcategory - Thermoplastics

Table 23 - Average Raw Waste Concentration Data For The     -    3577-3579
           Subcategory - Thermosets

Table 24A- Average Raw Waste Concentration Data For The     -    3580-3606
           For The Subcategory - Bulk Group - Aliphatics

-------
                          LIST OF TABLES (Continued)
Table 24B- Average Raw Waste Concentration Data For The
           For The Subcategory - Bulk Group - Aromatics

Table 24C- Average Raw Waste Concentration Data For The
           Subcategory - Bulk Group - Amides

Table 24D- Average Raw Waste Concentration Data For The
           Subcategory - Bulk Group - Halogens

Table 24E- Average Raw Waste Concentration Data For The
           Subcategory - Bulk Group - Others

Table 25A- Average Raw Waste Concentration Data For The
           Subcategory - Commodity Group - Aliphatics

Table 25B- Average Raw Waste Concentration Data For The
           Subcategory - Commodity Group - Aromatics

Table 25C- Average Raw Waste Concentration Data For The
           Subcategory - Commodity Group - Halogens

Table 26A- Average Raw Waste Concentration Data For The
           Subcategory - Specialty Group - Aliphatics

Table 26B- Average Raw Waste Concentration Data For The
           Subcategory - Specialty Group - Aromatics

Table 26C- Average Raw Waste Concentration Data For The
           Subcategory - Specialty Group - Amides

Table 26D- Average Raw Waste Concentration Data For The
           Subcategory - Specialty Group - Halogens

Table 26E- Average Raw Waste Concentration Data For The
           Subcategory - Specialty Group - Others

Table 27 - Carbon Capacity For Priority Pollutants (In-
           Plant Treatment) Lbs. of Pollutant Absorbed/
           Lb. of Carbon

Table 28 - Strippability of Priority Pollutants (Steam
           Stripping)

Table 29 - BPT Loadings For Organics Plants
    3607-3620


    3621-3627


-   3628-3640


-   3641-3645


    3646-3665


    3666-3676


- '  3677-3678


    3679-3690


    3691-3700


    3701-3702


-   3J03-3708


    3709-3718


-   3719



-   3720


    3721-3727

-------
U.S.  Environmental Protection AgeifC^j
Region V, ! •   . •/
230  Sojth Goaroc'T!  "
Chicago,  Illinois  60604

-------