APPENDICES

Appendix A - List of Supplemental Documents ........................................... A-1

Appendix B - Industrial Categories with Pretreatment Standards ............................. B-1

Appendix C - Pollutants Regulated by Categorical Pretreatment Standards ..................... C-1

Appendix D - Clean Water Act Priority Pollutants and the Federal Water Quality Criteria ......... D-1

Appendix E - Federal Sewage Sludge Standards .......................................... E-1

Appendix F - Toxicity Characteristic Leachate Procedure Limitations ......................... F-1

Appendix G - Literature Inhibition Values ............................................... G-1

Appendix H - Closed-cup Flashpoints for Select Organic Compounds ......................... H-1

Appendix I - Discharge Screening Levels and Henry’s Law Constants for Organic Compounds ..... I-1

Appendix J - OSHA, ACGIH and NIOSH Exposure Levels ................................. J-1

Appendix K - Landfill Leachate Loadings ............................................... K-1

Appendix L - Hauled Waste Loadings .................................................. L-1

Appendix M - Hazardous Waste Constituents - RCRA Appendix VIII ........................ M-1

Appendix N - Statistical Approach to Determining Sampling Frequency ....................... N-1

Appendix O - Minimizing Contamination in Samples ...................................... O-1

Appendix P - Methods for Calculating Removal Efficiency ................................. P-1

Appendix Q - Methods for Handling Data Below Detection Level ............................ Q-1

Appendix R - Priority Pollutant Removal Efficiencies ...................................... R-1

Appendix S - Specific Gravity of Sludge ................................................ S-1

Appendix T - Sludge AHL Equations Using Flow (in metric units) ........................... T-1

Appendix U - POTW Configurations ................................................... U-1

Appendix V - Domestic Pollutant Loadings .............................................. V-1

Appendix W - Best Management Practices Mini-Case Studies .............................. W-1

Appendix X - Region 1, Reassessment of Technically Based Industrial Discharge Limits Checklist . . X-1

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APPENDIX A -

LIST OF SUPPLEMENTAL DOCUMENTS

GENERAL GUIDANCE ON PRETREATMENT 

TITLE DATE EPA Number NTIS Number ERIC 

Number 

CERCLA Site Discharges to POTWs 

Guidance Manual 

August 1990 540-G-90-005 PB90-274531 W150 

Control Authority Pretreatment Audit 

Checklist and Instructions 

May 1992 

Control of Slug Loadings To POTWs: 

Guidance Manual 

February 1991 21W-4001 

Environmental Regulations and Technology: 

The National Pretreatment Program 

July 1986 625-10-86-005 PB90-246521 W350 

Guidance for Conducting a Pretreatment 

Compliance Inspection 

September 

1991 

300-R-92-009 PB94-120631 W273 

Guidance For Developing Control Authority 

Enforcement Response Plans 

September 

1989 

PB90-

185083/AS 

Guidance for Reporting and Evaluating 

POTW Noncompliance with Pretreatment 

Implementation Requirements 

September 

1987 

PB95-157764 W304 

Guidance Manual for POTW Pretreatment 

Program Development 

Guidance Manual for POTWs to Calculate 

the Economic Benefit of Noncompliance 

Guidance Manual for Preparation and 

Review of Removal Credit Applications 

Guidance Manual for Preventing 

Interference at POTWs 

Guidance Manual for the Control of Wastes 

Hauled to Publicly Owned Treatment Works 

Guidance Manual for the Identification of 

Hazardous Wastes Delivered to Publicly 

Owned Treatment Works by Truck, Rail, or 

Dedicated Pipe 

Guidance Manual for the Use of ProductionBased Pretreatment Standards and the 

Combined Wastestream Formula 

Guidance Manual on the Development and 

Implementation of Local Discharge 

Limitations Under the Pretreatment Program 

Guidance on Evaluation, Resolution, and 

Documentation of Analytical Problems 

Associated with Compliance Monitoring 

Guidance on the Privatization of Federally 

Funded Wastewater Treatment Works 

Guidance to Protect POTW Workers From 

Toxic And Reactive Gases And Vapors 

October 1983 PB93-186112 W639 

September 

1990 

833-B-93-007 

July 1985 833-B-85-200 

September 

1987 

833-B-87-201 PB92-117969 W106 

September 

1999 

833-B-98-003 

June 1987 PB92-149251 W202 

September 

1985 

833-B-85-201 PB92-232024 U095 

December 

1987 

833-B-87-202 PB92-129188 W107 

June 1993 821-B-93-001 

August 2000 832-B-00-002 

June 1992 812-B-92-001 PB92-173236 W115 

A-1
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GENERAL GUIDANCE ON PRETREATMENT 

TITLE DATE EPA Number NTIS Number ERIC 

Number 

Guides to Pollution Prevention: Municipal 

Pretreatment Programs 

Industrial User Inspection and Sampling 

Manual For POTWs 

Industrial User Permitting Guidance Manual 

Metals Translator: Guidance for Calculating 

a Total Recoverable Permit Limit from a 

Dissolved Criterion 

Model Pretreatment Ordinance 

Multijurisdictional Pretreatment Programs: 

Guidance Manual 

National Pretreatment Program: Report to 

Congress 

NPDES Compliance Inspection Manual 

Pollution Prevention (P2) Guidance Manual 

for the Pesticide Formulating, Packaging, 

and Repackaging Industry: Implementing 

the P2 Alternative 

POTW Sludge Sampling and Analysis 

Guidance Document 

Prelim User’s Guide, Documentation for the 

EPA Computer Program/Model for 

Developing Local Limits for Industrial 

Pretreatment Programs at Publicly Owned 

Treatment Works, Version 5.0 

Pretreatment Compliance Inspection and 

Audit Manual For Approval Authorities 

Pretreatment Compliance Monitoring and 

Enforcement Guidance and Software 

(Version 3.0) 

Procedures Manual for Reviewing a POTW 

Pretreatment Program Submission 

Procuring Analytical Services: Guidance for 

Industrial Pretreatment Programs 

Region III Guidance for Setting Local Limits 

for a Pollutant Where the Domestic Loading 

Exceeds the Maximum Allowable 

Headworks Loading 

Protecting the Nation's Waters Through 

Effective NPDES Permits: A Strategic Plan 

FY 2001 and Beyond 

RCRA Information on Hazardous Wastes for 

Publicly Owned Treatment Works 

Report to Congress on the Discharge of 

Hazardous Wastes to Publicly Owned 

Treatment Works 

October 1993 625-R-93-006 

April 1994 831-B-94-001 PB94-170271 W305 

September 

1989 

833-B-89-001 PB92-123017 W109 

June 1996 823-B-96-007 

June 1992 833-B-92-003 PB93-122414 W108 

June 1994 833-B-94-005 PB94-203544 W607 

July 1991 21-W-4004 PB91-228726 W694 

September 

1994 

300-B-94-014 

June 1998 821-B-98-017 

August 1989 833-B-89-100 

January 1997 

July 1986 833-B-86-100 PB90-183625 W277 

(Manual) 

September 

1986 

(Software) 

September 

1992 

(Software) 

831-F-92-001 

(Software) 

PB94-118577 

(Software) 

W269 

October 1983 833-B-83-200 PB93-209880 W137 

October 1998 833-B-98-004 

June 1994 

June 2001 833-R-01-001 

September 

1985 

833-B-85-202 PB92-114396 W351 

February 1986 530-SW-86-004 PB86-184017 & 

PB95-157228 

W922 & 

W692 

A-2
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GENERAL GUIDANCE ON PRETREATMENT 

TITLE DATE EPA Number NTIS Number ERIC 

Number 

Supplemental Manual On the Development 

And Implementation of Local Discharge 

Limitations Under The Pretreatment 

Program 

May 1991 21W-4002 PB93-209872 W113 

Source: Updated, originally part of U.S. EPA’s Introduction to the National Pretreatment Program, EPA-833-B-98-002,

February 1999, pp. 51-52

GUIDANCE ON INDUSTRY PRETREATMENT STANDARDS 

TITLE DATE EPA Number NTIS Number ERIC 

Number 

Aluminum, Copper, And Nonferrous Metals 

Forming And Metal Powders Pretreatment 

Standards: A Guidance Manual 

December 

1989 

800-B-89-001 PB91-145441 W119 

Guidance Manual For Battery Manufacturing 

Pretreatment Standards 

August 1987 440-1-87-014 PB92-117951 W195 

Guidance Manual for Electroplating and 

Metal Finishing Pretreatment Standard 

February 1984 440-1-84-091-G PB87-192597 W118 

Guidance Manual For Implementing Total 

Toxic Organics (TTO) Pretreatment 

Standards 

September 

1985 

440-1-85-009-T PB93-167005 W339 

Guidance Manual For Iron And Steel 

Manufacturing Pretreatment Standards 

September 

1985 

821-B-85-001 PB92-114388 W103 

Guidance Manual for Leather Tanning and 

Finishing Pretreatment Standards 

September 

1986 

800-R-86-001 PB92-232024 W117 

Guidance Manual for Pulp, Paper, and 

Paperboard and Builders’ Paper and Board 

Mills Pretreatment Standards 

July 1984 PB92-231638 W196 

Guidance Manual for the Use of ProductionBased Pretreatment Standards and the 

Combined Wastestream Formula 

September 

1985 

833-B-85-201 PB92-232024 U095 

Permit Guidance Document: Pulp, Paper, 

and Paperboard Manufacturing Point 

Source Category (40 CFR Section 430) 

May 2000 821-B-00-003 PB2002-

106590 

Permit Guidance Document: Transportation 

Equipment Cleaning Point Source Category 

(40 CFR 422) 

March 2001 821-R-01-021 

Small Entity Compliance Guide: Centralized 

Waste Treatment Guidelines and 

Pretreatment Standards (40 CFR 437) 

June 2001 821-B-01-003 

Source: Updated, originally part of U.S. EPA’s Introduction to the National Pretreatment Program, EPA-833-B-98-002,

February 1999, pp. 51-52

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A-4
APPENDIX B -

INDUSTRIAL CATEGORIES WITH PRETREATMENT STANDARDS

Source: U.S. EPA’s Introduction to the National Pretreatment Program, EPA-833-B-98-002, February 

1999, Figure 13, p. 14. (Updated) 

Category 

(SIC Codes)* 

[NAICS Codes]** 

40 CFR 

Part (Subparts) 

Type of

Standard*** Overview of Pretreatment Standards 

Aluminum Forming 

(3353, 3354, 3355, 3357, 

3363) 

[331315, 331316, 331319, 

331521] 

467(A-F) PSES 

PSNS 

Limits are production-based, daily maximums and 

monthly averages. 

from certain operations. 

Battery Manufacturing 

(3691, 3692) 

[335911, 335912] 

461(A-G) PSES 

PSNS 

Limits are production-based, daily maximums and 

monthly averages. ed from 

any process not specifically identified in the 

regulations. 

Carbon Black Manufacturing 

(2895) 

[325182] 

458 (A-D) PSNS Limits are for Oil & Grease only (no limit duration 

specified). 

Centralized Waste Treatment 

(4953) 

[562211, 562219 ] 

437 (A-D) PSES 

PSNS 

Limits are concentration-based, daily maximums and 

monthly averages. 

Coil Coating 

(3411, 3479, 3492) 

[332431, 332812] 

465 (A-D) PSES 

PSNS 

Limits are production-based, daily maximums and 

monthly averages. 

Commercial Hazardous Waste 

Combustors 

(4953, 2819, 2869, 3241, 

1422, 1429, 1459) 

[562213, 212312, 325188, 

325199, 327310] 

444 (A) PSES 

PSNS 

Limits are concentration-based daily maximums or 

maximum monthly averages. 

Concentrated Animal Feeding 

Operations 

(0211, 0213, 0214, 0241, 

0251, 0252, 0253, 0254, 0259, 

0272) 

[112112, 11221, 11241, 

11242, 112111, 11212, 11232, 

11231, 11233, 11234, 11239, 

11292] 

412 (B) PSNS Discharge of process wastewater is prohibited, 

except when there is an overflow resulting from a 

chronic or catastrophic rainfall event. 

Copper Forming 

(3351, 3357, 3463) 

[331421, 331422, 332112] 

468 (A) PSES 

PSNS 

Limits are production-based, daily maximums and 

monthly averages. 

Electrical and Electronic 

Components 

(3671, 3674, 3679) 

[334411, 334413, 334419] 

469 (A-D) PSES 

PSNS 

Limits are concentration-based, daily maximums and 

30-day averages or monthly averages (varies per 

subpart and pollutant parameter). 

allowed in lieu of monitoring for certain pollutants 

when a management plan is approved and 

implemented. 

Subpart C prohibits discharges 

No discharge is allow

Certification is 

B-1
Category 

(SIC Codes)* 

[NAICS Codes]** 

40 CFR 

Part (Subparts) 

Type of 

Standard*** Overview of Pretreatment Standards 

Electroplating 

(3471, 3672) 

[332813, 334412] 

413 (A-B, DH) 

PSES Limits are concentration-based (or alternative massbased equivalents), daily maximums and four 

consecutive monitoring days averages. wo sets of 

limits exist, depending on if facility discharges more 

or less than 10,000 gallons per day of process 

wastewater. on is allowed in lieu of 

monitoring for certain pollutants when a management 

plan is approved and implemented. 

Fertilizer Manufacturing 

(2873, 2874, 2875) 

[325311, 325312, 325314] 

418 (A-G) PSNS Limits may specify zero discharge of wastewater 

pollutants (Subpart A), production-based daily 

maximums and 30-day averages (Subparts B-E) or 

concentration-based (Subparts F-G) with no limit 

duration specified. 

Glass Manufacturing 

(3211, 3221, 3296) 

[327211, 327212, 327993] 

426 (H, KM) 

PSNS Limits are either concentration- or production-based, 

daily maximums and monthly averages. 

Grain Mills 

(2041, 2043, 2044, 2045, 

2046, 2047) 

[311111, 311211, 311212, 

311213, 311221, 311230] 

406 (A) PSNS Discharge of process wastewater is prohibited at a 

flow rate or mass loading rate which is excessive 

over any time period during the peak load at a 

POTW. 

Ink Formulating 

(2893) 

[325910] 

447 (A) PSNS Regulations specify no discharge of process 

wastewater pollutants to the POTW. 

Inorganic Chemicals 

Manufacturing 

(2812, 2813, 2816, 2819) 

[325120, 325131, 325181, 

325188] 

415 (A-BO) PSES 

PSNS 

Limits vary for each subpart with a majority of the 

limits concentration-based, daily maximums and 30-

day averages, or may specify no discharge of 

wastewater pollutants. Numerous subparts have no 

pretreatment standards. 

Iron and Steel Manufacturing 

(3312, 3315, 3316, 3317, 

3479) 

[331111, 331210, 331221, 

331222, 332812] 

420 (A-F, HJ, L, M) 

PSES 

PSNS 

Limits are production-based, daily maximums and 30 

day averages, or may specify no discharge of 

wastewater pollutants. 

Leather Tanning and Finishing 

(3111) 

[316110] 

425 (A-I) PSES 

PSNS 

Limits are concentration-based, daily maximums and 

monthly averages. 

volume dictates applicable pretreatment standards. 

Metal Finishing 

(Industry groups: 34, 35, 36, 

37, 38) 

[Industry Subsectors: 332, 

333, 334, 336] 

433 (A) PSES 

PSNS 

Limits are concentration-based, daily maximums and 

monthly averages. ion is allowed for certain 

pollutants where a management plan is approved 

and implemented. 

Metal Molding and Casting 

(3321, 3322, 3324, 3325, 

3365, 3366, 3369) 

[331511, 331512, 331513, 

331524, 331525, 331528] 

464 (A-D) PSES 

PSNS 

Limits are primarily production-based, daily 

maximums and monthly averages. 

certain processes are prohibited (Subparts A-C). 

Nonferrous Metals Forming 

and Metal Powders 

(3356, 3357, 3363, 3497, 

3499) 

[331491, 331422, 331521, 

332117, 332999] 

471 (A-J) PSES 

PSNS 

Limits are production-based, daily maximums and 

monthly averages. 

regulations prohibit the discharge of wastewater 

pollutants. 

T

Certificati

In certain instances, production 

Certificat

Discharges from 

In some instances, the 

B-2
Category 

(SIC Codes)* 

[NAICS Codes]** 

40 CFR 

Part (Subparts) 

Type of 

Standard*** Overview of Pretreatment Standards 

Nonferrous Metals 

Manufacturing 

(2819, 3331, 3334, 3339, 

3341) 

[331311, 331312, 331314, 

331411, 331419, 331423, 

331492] 

421 (B-AE) PSES 

PSNS 

Limits are production-based, daily maximums and 

monthly averages. he majority of the Subparts 

have both existing and new source limits, with others 

having solely new source requirements. 

instances, the regulations prohibit the discharge of 

wastewater pollutants. 

Oil and Gas Extraction 

(1311) 

[211111] 

435 (D) PSES 

PSNS 

Regulations specify no discharge of process 

wastewater (drilling fluieds, deck drainage, etc.) 

pollutants to the POTW. 

Organic Chemicals, Plastics, 

and Synthetic Fibers 

(2821, 2823, 2824, 2865, 

2869) 

[325211, 325221, 325222, 

32511, 325132, 325192, 

325188]] 

414 (B-H, K) PSES 

PSNS 

Limits are mass-based (concentration-based 

standards multiplied by process flow), daily 

maximums and monthly averages. 

metals and cyanide apply only to metal- or cyanidebearing wastestreams. 

Paint Formulating 

(2851) 

[325510] 

446 (A) PSNS Regulations specify no discharge of process 

wastewater pollutants to the POTW. 

Paving and Roofing Materials 

(Tars and Asphalt) 

(2951, 2952, 3996) 

[324121, 324122, 326192] 

443 (A-D) PSNS Limits are for Oil & Grease only (no limit duration 

specified). 

Pesticide Chemicals 

(2879) 

[325320] 

455 (A, C, 

E) 

PSES 

PSNS 

Limits are mass-based (concentration-based 

standards multiplied by process flow), daily 

maximums and monthly averages. 

specifies no discharge of process wastewater 

pollutants but provides for pollution prevention 

alternatives. 

process wastewater pollutants. 

Petroleum Refining 

(2911) 

[324110] 

419 (A-E) PSES 

PSNS 

Limits are concentration-based (or mass-based 

equivalent), daily maximums. 

Pharmaceutical Manufacturing 

(2833, 2834) 

[325411, 325412] 

439 (A-D) PSES 

PSNS 

Limits are concentration-based, daily maximums and 

monthly averages. 

certify they do not use or generate cyanide in lieu of 

performing monitoring to demonstrate compliance. 

Porcelain Enameling 

(3431, 3469, 3479, 3631, 

3632, 3633, 3639) 

[332116, 332812, 332998, 

335221, 335222, 335224, 

335228] 

466 (A-D) PSES 

PSNS 

Limits are concentration-based (or alternative 

production-based), daily maximums and monthly 

averages. 

operations. 

T

In some 

Standards for 

Subpart C 

Subpart E specifies no discharge of 

Subpart A and C facilities may 

Subpart B prohibits discharges certain 

Pulp, Paper, and Paperboard 

(2611, 2621, 2631) 

[322110, 322121, 322122, 

322130] 

430 (A-G, IL) 

PSES 

PSNS 

Limits are production-based or concentration-based 

(or alternative production-based) daily maximums 

and monthly averages. hese facilities may certify 

they do not use certain compounds in lieu of 

performing monitoring to demonstrate compliance. 

Facilities subject to Subparts B and E must also 

implement Best Management Practices as identified. 

Rubber Manufacturing 

(2822) 

[325212] 

428 (E-K) PSNS Limits are concentration- or production-based, daily 

maximums and monthly averages. 

T

B-3
Category 

(SIC Codes)* 

[NAICS Codes]** 

40 CFR 

Part (Subparts) 

Type of 

Standard*** Overview of Pretreatment Standards 

Soap and Detergent 

Manufacturing 

(2841) 

[325611] 

417 (O-R) PSNS Regulations specify no discharge of process 

wastewater pollutants to the POTW. 

Steam Electric Power 

Generating 

(4911) 

[221112] 

423 PSES 

PSNS 

Limits are either concentration-based, daily 

maximums, or “maximums for any time,” or 

compliance can be demonstrated through 

engineering calculations. 

regulations prohibit the discharge of wastewater 

pollutants. 

Timber Products Processing 

(2421, 2435, 2436, 2491, 

2493, 2499) 

[321114, 321219, 321211, 

321212] 

429 (F-H) PSES 

PSNS 

All PSNS (and PSES for Subpart F) prohibit the 

discharge of wastewater pollutants. 

Subparts G and H are concentration-based, daily 

maximums (with production-based alternatives). 

Transportation Equipment 

Cleaning 

(4491, 4499, 4741, 7699) 

[484230, 488320, 488390, 

488210] 

442 (A-C) PSES 

PSNS 

Limits are concentration-based daily maximums. 

Subpart A and B allow for a pollutant as an 

alternative to achieving PSES or PSNS. 

In some instances, the 

PSES for 

* SIC = Standard Industrial Classification, 1987 SIC Manual 

** NAICS = North American Industry Classification System, 1997 NAICS Manual. 

*** PSNS = Pretreatment Standard New Source; PSES = Pretreatment Standard Existing Source 

B-4
C-1

APPENDIX C -

POLLUTANTS REGULATED BY CATEGORICAL PRETREATMENT

STANDARDS Aluminum Forming Battery Manufacturing Carbon Black Manufacturing Centralized Waste Treatment

Coil Coating

Copper Forming

Electrical and Electronic Components

Electroplating

Feedlots

Fertilizer Manufacturing

Glass Manufacturing

Grain Mills

Ink Formulating

Inorganic Chemicals Manufacturing

Iron and Steel Manufacturing

Leather Tanning and Finishing

Metal Finishing

Metal Molding and Casting

Nonferrous Metals Form./Metal Powders

Nonferrous Metals Manufacturing

Oil and Gas

Organic Chems., Plastics, and Syn. 

Paint Formulating

Paving and Roofing Materials

Pesticide Chemicals

Petroleum Refining

Pharmaceutical Manufacturing

Porcelain Enameling

Pulp, Paper, and Paperboard

Rubber Manufacturing

Soap and Detergent Manufacturing

Steam Electric Power Generating

Timber Products Processing

Transportation Equip. Cleaning

Waste Combustors

Flow Restrictions

Only

X X X X

Ammonia (as N) X X X X X X

BOD X

COD X X

Fluoride X X X X X X

Nitrate (as N) X

Oil and Grease X X X X X X X X X

Oil (mineral) X

Organic Nitrogen

(as N) X

pH X X X

Phenols X X X

Phosphorus X X

Sulfide X

TSS X X

1,1-

Dichloroethane X X X X

1,1-

Dichloroethylene X X X X X X

1,1,1-

Trichloroethane XXXX X X X X X

1,1,2-

Trichloroethane X X X X X

1,1,2,2-Tetrachloroethane X X X

1,2-

Dichlorobenzene X X X X X X X

1,2-

Dichloroethane X X X X X X X

1,2-

Dichloropropane X X X X

1,2-Diphenylhydrazine X X X X

1,2-transDichloroethylene X X X X Fibers

X

X

X

X

X

X

X
Aluminum Forming

Battery Manufacturing

Carbon Black Manufacturing

Centralized Waste Treatment

Coil Coating

Copper Forming

Electrical and Electronic Components

Electroplating

Feedlots

Fertilizer Manufacturing

Glass Manufacturing

Grain Mills

Ink Formulating

Inorganic Chemicals Manufacturing

Iron and Steel Manufacturing

Leather Tanning and Finishing

Metal Finishing

Metal Molding and Casting

Nonferrous Metals Form./Metal Powders

Nonferrous Metals Manufacturing

Oil and Gas

Organic Chems., Plastics, and Syn. 

Paint Formulating

Paving and Roofing Materials

Pesticide Chemicals

Petroleum Refining

Pharmaceutical Manufacturing

Porcelain Enameling

Pulp, Paper, and Paperboard

Rubber Manufacturing

Soap and Detergent Manufacturing

Steam Electric Power Generating

Timber Products Processing

Transportation Equip. Cleaning

Waste Combustors

C-2

1,2,4-Trichlorobenzene X X

XXX

1,3-Dichlorobenzene X X

XXX

1,3-Dichloropropene 

XXXX

1,4-Dichlorobenzene X X

XXXX

2-Chloroethyl

vinyl ether

(mixed) 

XX

2-Chloronaphthalene 

XX

2-Chlorophenol XXXXX

2-Nitrophenol XXXX

2,3-Dichloroaniline

X

2,3,4,6-Tetrachlorophenol

X

2,4-

Dichlorophenol X X X X

X

2,4-Dimethyl-

phenol 

XXX

2,4-Dinitrophenol XX

2,4-Dinitrotoluene 

XXX

2,4,5-Trichlorophenol

X

2,4,6-Trichlorophenol 

XXXXXX

2,6-Dinitrotoluene 

XXX

3,3-Dichlorobenzidine 

XX

3,4,5-Trichlorocatechol

X

3,4,5-Trichloroguaiacol

X

3,4,6-Trichlorocatechol

X

3,4,6-Trichloroguaiacol

X

4-Bromophenyl

phenyl ether 

XX

Fibers

XXX

X

X

X

XX

X

X

XX
Aluminum Forming

Battery Manufacturing

Carbon Black Manufacturing

Centralized Waste Treatment

Coil Coating

Copper Forming

Electrical and Electronic Components

Electroplating

Feedlots

Fertilizer Manufacturing

Glass Manufacturing

Grain Mills

Ink Formulating

Inorganic Chemicals Manufacturing

Iron and Steel Manufacturing

Leather Tanning and Finishing

Metal Finishing

Metal Molding and Casting

Nonferrous Metals Form./Metal Powders

Nonferrous Metals Manufacturing

Oil and Gas

Organic Chems., Plastics, and Syn. 

Paint Formulating

Paving and Roofing Materials

Pesticide Chemicals

Petroleum Refining

Pharmaceutical Manufacturing

Porcelain Enameling

Pulp, Paper, and Paperboard

Rubber Manufacturing

Soap and Detergent Manufacturing

Steam Electric Power Generating

Timber Products Processing

Transportation Equip. Cleaning

Waste Combustors

C-3

4-Chlorophenyl

phenyl ether X X

4-Nitrophenol X X X X X

4,4-DDD X X X

4,4-DDE X X X

4,4-DDT X X

4,5,6-Trichloroquaiacol X

4,6-Dinitro-ocresol X X X

Acenaphthene X X X X X

Acenaphthylene X X X X

Acetone X

Acrolein X X

Acrylonitrile X X

Aldrin X X

Alpha-BHC X X

Alphaendosulfan X X

Anthracene X X X X X X X

Benzene X X X X X X X

Benzidine X X X

Benzo (b)

fluoranthene X X X X

Benzo (a)

anthracene X X X

Benzo (ghi)

perylene X X X

Benzo (a) pyrene X X X X X X

Benzo (k)

fluoranthene X X X

Beta-BHC X X X

Beta-endosulfan X X

Bis (2-chloroethoxy) methane X X

Bis (2-chloroisopropyl) ether X X

Bis (2-chloroethyl) ether X X X

Bis (2-ethylhexyl) phthalate X X X X X X X X

Bromoform X X X X Fibers

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X
Aluminum Forming

Battery Manufacturing

Carbon Black Manufacturing

Centralized Waste Treatment

Coil Coating

Copper Forming

Electrical and Electronic Components

Electroplating

Feedlots

Fertilizer Manufacturing

Glass Manufacturing

Grain Mills

Ink Formulating

Inorganic Chemicals Manufacturing

Iron and Steel Manufacturing

Leather Tanning and Finishing

Metal Finishing

Metal Molding and Casting

Nonferrous Metals Form./Metal Powders

Nonferrous Metals Manufacturing

Oil and Gas

Organic Chems., Plastics, and Syn. 

Paint Formulating

Paving and Roofing Materials

Pesticide Chemicals

Petroleum Refining

Pharmaceutical Manufacturing

Porcelain Enameling

Pulp, Paper, and Paperboard

Rubber Manufacturing

Soap and Detergent Manufacturing

Steam Electric Power Generating

Timber Products Processing

Transportation Equip. Cleaning

Waste Combustors

C-4

Butyl benzyl

phthalate X X X X X

Carbon

tetrachloride X X X X X X

Carbazole X

Chlordane (tech.

mix. &

metabolites) 

X X

Chlorobenzene X X X X X X X

Chlorodibromomethane X X X

Chloroethane X X X

Chloroform XXXX X X X X X X X

Chrysene X X X X

Cresol X

Delta-BHC X X X

Di-n-butyl

phthalate X X X X X X X

Di-n-octyl

phthalate X X

Dibenzo (a,h)

anthracene X X X

Dichlorobromomethane X X X X X

Dieldrin X X

Diethyl phthalate X X X X X X

Diethylamine X

Dimethyl

phthalate X X X X

Endosulfan

sulfate X X X

Endrin X X X

Endrin aldehyde X X X X

Ethyl acetate X

Ethylbenzene X X X X X X X

Fluoranthene X X X X X X X

Fluorene X X X X X

Gamma-BHC X X X

Heptachlor

epoxide X X

Heptachlor X X Fibers

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X
Aluminum Forming

Battery Manufacturing

Carbon Black Manufacturing

Centralized Waste Treatment

Coil Coating

Copper Forming

Electrical and Electronic Components

Electroplating

Feedlots

Fertilizer Manufacturing

Glass Manufacturing

Grain Mills

Ink Formulating

Inorganic Chemicals Manufacturing

Iron and Steel Manufacturing

Leather Tanning and Finishing

Metal Finishing

Metal Molding and Casting

Nonferrous Metals Form./Metal Powders

Nonferrous Metals Manufacturing

Oil and Gas

Organic Chems., Plastics, and Syn. 

Paint Formulating

Paving and Roofing Materials

Pesticide Chemicals

Petroleum Refining

Pharmaceutical Manufacturing

Porcelain Enameling

Pulp, Paper, and Paperboard

Rubber Manufacturing

Soap and Detergent Manufacturing

Steam Electric Power Generating

Timber Products Processing

Transportation Equip. Cleaning

Waste Combustors

C-5

Hexachlorobenzene X X X X

Hexachlorobutadiene X X

Hexachlorocyclo

pentadiene X X X

Hexachloroethane X X X

Indeno (1,2,3-

cd)pyrene X X X

Isobutylaldehyde X

Isophorone X X X X

Isopropyl acetate X

Isopropyl ether X

Methyl formate X

Methyl bromide X X X X

Methyl cellosolve X

Methyl Isobutyl

Ketone X

Methyl chloride X X X X X

Methylene

chloride XXXX X X X X X X

n-Amyl acetate X

n-Butyl acetate X

n-Decane X

n-Heptane X

n-Hexane X

N-nitrosodi-npropylamine X X X X

N-nitrosodimethylamine X X X

N-nitrosodiphenylamine X X X X X

n-Octadecane X

Naphthalene X X X X X X X X X

Nitrobenzene X X X

Non-polar

material (SGTHEM)X

Parachlorometacresol X X X X

PCB–1016 X X X X Fibers

X

X

X

X

X

X

X

X

X

X

X

X
Aluminum Forming

Battery Manufacturing

Carbon Black Manufacturing

Centralized Waste Treatment

Coil Coating

Copper Forming

Electrical and Electronic Components

Electroplating

Feedlots

Fertilizer Manufacturing

Glass Manufacturing

Grain Mills

Ink Formulating

Inorganic Chemicals Manufacturing

Iron and Steel Manufacturing

Leather Tanning and Finishing

Metal Finishing

Metal Molding and Casting

Nonferrous Metals Form./Metal Powders

Nonferrous Metals Manufacturing

Oil and Gas

Organic Chems., Plastics, and Syn. 

Paint Formulating

Paving and Roofing Materials

Pesticide Chemicals

Petroleum Refining

Pharmaceutical Manufacturing

Porcelain Enameling

Pulp, Paper, and Paperboard

Rubber Manufacturing

Soap and Detergent Manufacturing

Steam Electric Power Generating

Timber Products Processing

Transportation Equip. Cleaning

Waste Combustors

C-6

PCB–1221 X X X

PCB–1232 X X X

PCB–1242 X X X X

PCB–1248 X X X X

PCB–1254 X X X

PCB–1260 X X X

Pentachlorophenol X X X X X

Phenanthrene X X X X X X X X

Phenol X X X X X

Pyrene X X X X X

TCDF X

Tetrachlorocatechol X

Tetrachloroethylene X X X X X X X X X

Tetrachloroguaiacol X

Tetrahydrofuran X

Toluene XXXX X X X X X X

Toxaphene X X

Trichloroethylene X XXX X X X X

Trichlorosyringol X

Triethylamine X

Vinyl chloride X X X X

Xylenes X

2,3,7,8-

tetrachlorodibenzo-p-dioxinX X X

Organic

Pesticide Active

Ingredients

X

Antimony X X X X X X

Arsenic X X X X X X

Asbestos X

Barium X

Beryllium X

Cadmium X X X X X X X X X X

Chromium, Total X X XXXXX XXXX X X X X X X X X X Fibers

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X
Aluminum Forming

Battery Manufacturing

Carbon Black Manufacturing

Centralized Waste Treatment

Coil Coating

Copper Forming

Electrical and Electronic Components

Electroplating

Feedlots

Fertilizer Manufacturing

Glass Manufacturing

Grain Mills

Ink Formulating

Inorganic Chemicals Manufacturing

Iron and Steel Manufacturing

Leather Tanning and Finishing

Metal Finishing

Metal Molding and Casting

Nonferrous Metals Form./Metal Powders

Nonferrous Metals Manufacturing

Oil and Gas

Organic Chems., Plastics, and Syn. 

Paint Formulating

Paving and Roofing Materials

Pesticide Chemicals

Petroleum Refining

Pharmaceutical Manufacturing

Porcelain Enameling

Pulp, Paper, and Paperboard

Rubber Manufacturing

Soap and Detergent Manufacturing

Steam Electric Power Generating

Timber Products Processing

Transportation Equip. Cleaning

Waste Combustors

C-7

Chromium,

Hexavalent X X

Cobalt X X X X

Copper X X X X X X X X X X X X X

Cyanide, Total X X X X X X X X X X X X X X

Cyanide,

Amenable X

Gold X

Indium X

Iron X X

Lead X X X X X X X X X X X X X X X X X X

Manganese X X

Mercury X X X X X X X

Molybdenum X X X

Nickel X X X X X X X

Palladium X

Platinum X

Selenium X X X

Silver X X X X X X X

Tantalum X

Thallium X

Tin X X

Titanium X X X

Tungsten X

Vanadium X

Zinc XX XXXXX X X XXX X X X X X X X X

Source: Updated from the 1991 National Pretreatment Program Report to Congress, pp. 5-6. Fibers

X

X

X X X X X

X

X X
This page intentionally left blank. 

C-8
APPENDIX D -

CLEAN WATER ACT PRIORITY POLLUTANTS AND THE FEDERAL

WATER QUALITY CRITERIA

The appendix below lists, in three tables, the National Recommended Water Quality Criteria for: 

• Specific chemical compounds that are identified by unique Chemical Abstract Service (CAS) 

registry numbers; 

• Priority pollutants in the form of the Criteria Maximum Concentration (CMC) and Criterion 

Continuous Concentration (CCC); 

• Non-priority pollutants in the form of the Criteria Maximum Concentration (CMC) and Criterion 

Continuous Concentration (CCC) for non-priority pollutants; 

• Organoleptic effects in the form of Organoleptic Effect Criteria. 

Please see page D-16 for further discussion and definitions of these criteria. 

D-1
D-2

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR PRIORITY POLLUTANTS

PriorityPollutant

CAS

Number

Freshwater Saltwater

Human Health For

Consumption of:

FR

Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

1 Antimony 7440360 14 B,Z 4300 B 57FR60848

2 Arsenic 7440382 340 A,D,K 150 A,D,K 69 A,D,bb 36 A,D,bb

0.018 C,M,S 0.14 C,M,S

62FR4216057FR60848

3 Beryllium 7440417 J,Z J 62FR42160

4 Cadmium 7440439 4.3 D,E,K 2.2 D,E,K 42 D,bb 9.3 D,bb J,Z J 62FR42160

5a Chromium III 16065831 570 D,E,K 74 D,E,K

J,Z Total J

EPA820/B-96

-001

62FR42160

5b Chromium VI 18540299 16 D,K 11 D,K 1,100 D,bb 50 D,bb J,Z Total J 62FR42160

6 Copper 7440508 13 D,E,K,cc 9.0 D,E,K,cc 4.8 D,cc,ff 3.1 D,cc,ff 1,300 U 62FR42160

7 Lead 7439921 65 D,E,bb,gg 2.5 D,E,bb,gg 210 D,bb 8.1 D,bb J J 62FR42160

8 Mercury 7439976 1.4 D,K,hh 0.77 D,K,hh 1.8 D,ee,hh 0.94 D,ee,hh 0.050 B 0.051 B 62FR421609 Nickel 7440020 470 D,E,K 52 D,E,K 74 D,bb 8.2 D,bb 610 B 4,600 B 62FR42160

10 Selenium 7782492 L,R,T 5.0 T 290 D,bb,dd 71 D,bb,dd

170Z 11,000

62FR42160

IRIS 09/01/91

11 Silver 7440224 3.4 D,E,G 1.9 D,G 62FR42160

12 Thallium 7440280 1.7 B 6.3 B 57FR60848

13 Zinc 7440666 120 D,E,K 120 D,E,K 90 D,bb 81 D,bb 9,100 U 69,000 U 62FR42160

IRIS 10/01/92
D-3

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR PRIORITY POLLUTANTS

Priority Pollutant

CAS

Number

Freshwater Saltwater

Human Health For

Consumption of:

FR Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

14 Cyanide 57125 22 K,Q 5.2 K,Q

1 Q,bb 1 Q,bb 700 B,Z 220,000 B,H

EPA820/B-96-001

57FR60848

15 Asbestos 1332214 7 million

fibers/L 

57FR60848

16 2,3,7,8-TCDD (Dioxin) 1746016 1.3E-8 C 1.4E-8 C 62FR42160

17 Acrolein 107028 320 780 57FR6084818 Acrylonitrile 107131 0.059 B,C 0.66 B,C 57FR60848

19 Benzene 71432 1.2 B,C 71 B,C 62FR42160

20 Bromoform 75252 4.3 B,C 360 B,C 62FR42160

21 Carbon Tetrachloride 56235 0.25 B,C 4.4 B,C 57FR60848

22 Chlorobenzene 108907 680 B,Z 21,000 B,H 57FR6084823 Chlorodibromomethane 124481 0.41 B,C 34 B,C 62FR42160

24 Chloroethane 7500325 2-Chloroethylvinyl Ether 11075826 Chloroform 67663 5.7 B,C 470 B,C 62FR42160

27 Dichlorobromomethane 75274 0.56 B,C 46 B,C 62FR42160

28 1,1-Dichloroethane 7534329 1,2-Dichloroethane 107062 0.38 B,C 99 B,C 57FR60848

30 1,1-Dichloroethylene 75354 0.057 B,C 3.2 B,C 57FR60848

I
D-4

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR PRIORITY POLLUTANTS

Priority Pollutant

CAS

Number

Freshwater Saltwater

Human Health For

Consumption of:

FR

Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

31 1,2-Dichloropropane 78875 0.52 B,C 39 B,C 62FR42160

32 1,3-Dichloropropene 542756 10 B 1,700 B 57FR60848

33 Ethylbenzene 100414 3,100 B,Z 29,000 B 62FR42160

34 Methyl Bromide 74839 48 B 4000 B 62FR42160

35 Methyl Chloride 74873 J J 62FR42160

36 Methylene Chloride 75092 4.7 B,C 1600 B,C 62FR42160

37 1,1,2,2-Tetrachloroethane 79345 0.17 B,C 11 B,C 57FR60848

38 Tetrachloroethylene 127184 0.8 C 8.85 C 57FR60848

39 Toluene 108883 6,800 B,Z 200,000 B 62FR42160

40 1,2-Trans-Dichloroethylene 156605 700 B,Z 140,000 B 62FR42160

41 1,1,1-Trichloroethane 71556 J,Z J 62FR42160

42 1,1,2-Trichloroethane 79005 0.60 B,C 42 B,C 57FR60848

43 Trichloroethylene 79016 2.7 C 81 C 57FR6084844 Vinyl Chloride 75014 2.0 C 525 C 57FR60848

45 2-Chlorophenol 95578 120 B,U 400 B,U 62FR42160

46 2,4-Dichlorophenol 120832 93 B,U 790 B,U 57FR60848

47 2,4-Dimethylphenol 105679 540 B,U 2,300 B,U 62FR42160

48 2-Methyl-4,6-Dinitrophenol 534521 13.4 765 57FR6084849 2,4-Dinitrophenol 51285 70 B 14,000 B 57FR60848

50 2-Nitrophenol 88755

51 4-Nitrophenol 10002752 3-Methyl-4-Chlorophenol 59507 U U
D-5

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR PRIORITY POLLUTANTS

Priority Pollutant

CAS

Number

Freshwater Saltwater

Human Health For

Consumption of:

FR

Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

53 Pentachlorophenol 87865 19F,K 15F,K 13bb 7.9bb 0.28 B,C 8.2 B,C,H 62FR42160

54 Phenol 108952 21,000 B,U 4,600,000

B,H,U

62FR4216057FR60848

55 2,4,6-Trichlorophenol 88062 2.1 B,C,U 6.5 B,C 62FR42160

56 Acenaphthene 83329 1,200 B,U 2,700 B,U 62FR42160

57 Acenaphthylene 20896858 Anthracene 120127 9,600 B 110,000 B 62FR42160

59 Benzidine 92875 0.00012 B,C 0.00054 B,C 57FR60848

60 Benzo (a) Anthracene 56553 0.0044 B,C 0.049 B,C 62FR42160

61 Benzo (a) Pyrene 50328 0.0044 B,C 0.049 B,C 62FR42160

62 Benzo (b) Fluoranthene 205992 0.0044 B,C 0.049 B,C 62FR42160

63 Benzo (ghi) Perylene 19124264 Benzo (k) Fluoranthene 207089 0.0044 B,C 0.049 B,C 62FR42160

65 Bis 2-Chloroethoxy Methane 11191166 Bis 2-Chloroethyl Ether 111444 0.031 B,C 1.4 B,C 57FR60848

67 Bis 2-Chloroisopropyl Ether 39638329 1,400 B 170,000 B 62FR42160

57FR60848

68 Bis 2-Ethylhexyl Phthalate X 117817 1.8 B,C 5.9 B,C 57FR60848

69 4-Bromophenyl Phenyl Ether 10155370 Butylbenzyl Phthalate W 85687 3,000 B 5,200 B 62FR42160

71 2-Chloronaphthalene 91587 1,700 B 4,300 B 62FR42160
D-6

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR PRIORITY POLLUTANTS

Priority Pollutant

CAS

Number

Freshwater Saltwater

Human Health For

Consumption of:

FR

Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

72 4-Chlorophenyl Phenyl Ether 700572373 Chrysene 218019 0.0044 B,C 0.049 B,C 62FR42160

74 Dibenzo (a,h) Anthracene 53703 0.0044 B,C 0.049 B,C 62FR42160

75 1,2-Dichlorobenzene 95501 2,700 B,Z 17,000 B 62FR42160

76 1,3-Dichlorobenzene 541731 400 2,600 62FR42160

77 1,4-Dichlorobenzene 106467 400 Z 2600 62FR42160

78 3,3'-Dichlorobenzidine 91941 0.04 B,C 0.077 B,C 57FR60848

79 Diethyl Phthalate W 84662 23,000 B 120,000 B 57FR60848

80 Dimethyl Phthalate W 131113 313,000 2,900,000 57FR60848

81 Di-n-Butyl Phthalate W 84742 2,700 B 12,000 B 57FR60848

82 2,4-Dinitrotoluene 121142 0.11 C 9.1 C 57FR60848

83 2,6-Dinitrotoluene 60620284 Di-n-Octyl Phthalate 11784085 1,2-Diphenylhydrazine 122667 0.040 B,C 0.54 B,C 57FR60848

86 Fluoranthene 206440 300 B 370 B 62FR4216087 Fluorene 86737 1,300 B 14,000 B 62FR42160

88 Hexachlorobenzene 118741 0.00075 B,C 0.00077 B,C 62FR42160

89 Hexachlorobutadiene 87683 0.44 B,C 50 B,C 57FR6084890 Hexachlorocyclopentadiene 77474 240 B,U,Z 17,000 B,H,U 57FR60848

91 Hexachloroethane 67721 1.9 B,C 8.9 B,C 57FR60848
D-7

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR PRIORITY POLLUTANTS

Priority Pollutant

CAS

Number

Freshwater Saltwater

Human Health For

Consumption of:

FR

Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

92 Indeno (1,2,3-cd) Pyrene 193395 0.0044 B,C 0.049 B,C 62FR42160

93 Isophorone 78591 36 B,C 2,600 B,C IRIS

11/01/97

94 Naphthalene 9120395 Nitrobenzene 98953 17 B 1,900 B,H,U 57FR60848

96 N-Nitrosodimethylamine 62759 0.00069 B,C 8.1 B,C 57FR60848

97 N-Nitrosodi-n-Propylamine 621647 0.005 B,C 1.4 B,C 62FR42160

98 N-Nitrosodiphenylamine 86306 5.0 B,C 16 B,C 57FR60848

99 Phenanthrene 85018100 Pyrene 129000 960 B 11,000 B 62FR42160

101 1,2,4-Trichlorobenzene 120821 260 Z 940 IRIS 11/01/96102 Aldrin 309002 3.0 G 1.3 G 0.00013 B,C 0.00014 B,C 62FR42160

103 alpha-BHC 319846 0.0039 B,C 0.013 B,C 62FR42160

104 beta-BHC 319857 0.014 B,C 0.046 B,C 62FR42160

105 gamma-BHC (Lindane) 58899 0.95 K 0.16 G 0.019 C 0.063 C 62FR42160

106 delta-BHC 319868

107 Chlordane 57749 2.4G 0.0043G,aa 0.09G 0.004G,aa

0.0021 B,C 0.0022 B,C

62FR42160

IRIS 02/07/98

108 4,4-DDT 50293 1.1G 0.001G,aa 0.13G 0.001G,aa 0.00059 B,C 0.00059 B,C 62FR42160

109 4,4-DDE 72559 0.00059 B,C 0.00059 B,C 62FR42160

110 4,4-DDD 72548 0.00083 B,C 0.00084 B,C 62FR42160
D-8

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR PRIORITY POLLUTANTS

Priority Pollutant

CAS

Number

Freshwater Saltwater

Human Health For

Consumption of:

FR

Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

111 Dieldrin 60571 0.24K 0.056K,O 0.71G 0.0019G,aa 0.00014 B,C 0.00014 B,C 62FR42160

112 alpha-Endosulfan 959988 0.22G,Y 0.056G,Y 0.034G,Y 0.0087G,Y 110 B 240 B 62FR42160

113 beta-Endosulfan 33213659 0.22G,Y 0.056G,Y 0.034G,Y 0.0087G,Y 110 B 240 B 62FR42160

114 Endosulfan Sulfate 1031078 110 B 240 B 62FR42160

115 Endrin 72208 0.086K 0.036K,O 0.037G 0.0023G,aa 0.76 B 0.81 B,H 62FR42160

116 Endrin Aldehyde 7421934 0.76 B 0.81 B,H 62FR42160

117 Heptachlor 76448 0.52G 0.0038G,aa 0.053G 0.0036G,aa 0.00021 B,C 0.00021 B,C 62FR42160

118 Heptachlor Epoxide 1024573 0.52G,V 0.0038G,V,

aa

0.053G,V 0.0036G,V,

aa

0.00010 B,C 0.00011 B,C 62FR42160

119 Polychlorinated Biphenyls

PCBs:

0.014 N,aa 0.03 N,aa

0.00017 B,C,P 0.00017 B,C,P

62FR4216063FR16182

120 Toxaphene 8001352 0.73 0.0002aa 0.21 0.0002aa 0.00073B,C 0.00075B,C 62FR42160

Footnotes:A This recommended water quality criterion was derived from data for arsenic (III), but is applied here to total arsenic, which might imply that arsenic (III)

and arsenic (V) are equally toxic to aquatic life and that their toxicities are additive. A 440/5-84-033, January 1985),Species Mean Acute Values are given for both arsenic (III) and arsenic (V) for five species and the ratios of the SMAVs for each species range from 0.6 to

1.7. hronic values are available for both arsenic (III) and arsenic (V) for one species; for the fathead minnow, the chronic value for arsenic (V) is 0.29

times the chronic value for arsenic (III). be available concerning whether the toxicities of the forms of arsenic to aquatic organisms

are additive.

B This criterion has been revised to reflect The Environmental Protection Agency’s q1* or RfD, as contained in the Integrated Risk Information System

(IRIS) as of April 8, 1998. factor (BCF) from the 1980 Ambient Water Quality Criteria document was retained in each

case.

C This criterion is based on carcinogenicity of 10-6 risk. k levels may be obtained by moving the decimal point (e.g., for a risk level of 10-5 ,

move the decimal point in the recommended criterion one place to the right).

D Freshwater and saltwater criteria for metals are expressed in terms of the dissolved metal in the water column. ed water quality criteria

value was calculated by using the previous 304(a) aquatic life criteria expressed in terms of total recoverable metal, and multiplying it by a conversion

factor (CF). onversion Factor" (CF) represents the recommended conversion factor for converting a metal criterion expressed as the totalrecoverable fraction in the water column to a criterion expressed as the dissolved fraction in the water column. onversion Factors for saltwater CCCs

are not currently available. ater CMCs have been used for both saltwater CMCs and CCCs). See "Office of Water

Policy 

In the arsenic criteria document (EP

C

No data are known to 

The fish tissue bioconcentration 

Alternate ris

The recommend

The term "C

(C

Conversion factors derived for saltw
hardness of 100 mg/L. Criteria values for other hardness may be calculated from the following: CMC (dissolved) = exp{mA [ln( hardness)]+ bA} (CF), 

or CCC (dissolved) = exp{mC [ln (hardness)]+ bC} (CF) and the parameters specified in Appendix B to the Preamble- Parameters for Calculating 

Freshwater Dissolved Metals Criteria That Are Hardness-Dependent. 

This recommended water quality criterion is expressed in terms of total recoverable metal in the water column. It is scientifically acceptable to use the 

This value was announced (61FR58444-58449, November 14, 1996) as a proposed GLI 303(c) aquatic life criterion. EPA is currently working on this 

440/5-80-019), Chlordane (EPA 440/5-80-027), DDT (EPA 440/5-80-038), Endosulfan (EPA 440/5-80-046), Endrin (EPA 440/5-80-047), Heptachlor (440/5-80-052), Hexachlorocyclohexane (EPA 440/5-80-054), Silver (EPA 440/5-80-071). The Minimum Data Requirements and derivation procedures were different in the 1980 Guidelines than in the 1985 Guidelines. For example, a “CMC” derived using the 1980 Guidelines was derived to be used as an instantaneous maximum. If assessment is to be done using an averaging period, the values given should be divided by 2 to obtain a value that is more comparable to a CMC derived using the 1985 Guidelines. 

No criterion for protection of human health from consumption of aquatic organisms excluding water was presented in the 1980 criteria document or in 

PCBs are a class of chemicals which include aroclors, 1242, 1254, 1221, 1232, 1248, 1260, and 1016, CAS numbers 53469219, 11097691, 11104282, 

This recommended criterion is based on a 304(a) aquatic life criterion that was issued in the 1995 Updates: Water Quality Criteria Documents for the 

The CMC = 1/[(f1/CMC1) + (f2/CMC2)] where f1 and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and 

Protection of Aquatic Life in Ambient Water, (EPA-820-B-96-001, September 1996). This value was derived using the GLI Guidelines 

(60FR15393-15399, March 23, 1995; 40CFR132 Appendix A); the difference between the 1985 Guidelines and the GLI Guidelines are explained on page iv of the 1995 Updates. None of the decisions concerning the derivation of this criterion were affected by any considerations that are specific to 

F

the Great Lakes. 

reshwater aquatic life values for pentachlorophenol are expressed as a function of pH, and are calculated as follows: CMC = exp(1.005(pH)-4.869); 

The derivation of the CCC for this pollutant did not consider exposure through the diet, which is probably important for aquatic life occupying upper 

Nevertheless, sufficient information was presented in the 1980 document to allow the calculation of a criterion, 

and Technical Guidance on Interpretation and Implementation of Aquatic Life Metals Criteria,” October 1, 1993, by Martha G. Prothro, Acting 

Assistant Administrator for Water, available from the Water Resource Center, USEPA, 401 M St., SW, mail code RC4100, Washington, DC 20460; 

and 40CFR§131.36(b)(1). Conversion Factors applied in the table can be found in Appendix A to the Preamble- Conversion Factors for Dissolved 

Metals. 

EPA has not calculated human health criterion for this contaminant. However, permit authorities should address this contaminant in NPDES permit 

EPA is currently reassessing the criteria for arsenic. Upon completion of the reassessment the Agency will publish revised criteria as appropriate. 

The freshwater criterion for this metal is expressed as a function of hardness (mg/L) in the water column. The value given here corresponds to a 

This Criterion is based on 304(a) aquatic life criterion issued in 1980, and was issued in one of the following documents: Aldrin/Dieldrin (EPA 

This criterion for asbestos is the Maximum Contaminant Level (MCL) developed under the Safe Drinking Water Act (SDWA). 

conversion factor of 0.922 that was used in the GLI to convert this to a value that is expressed in terms of dissolved metal. 

11141165, 12672296, 11096825 and 12674112 respectively. The aquatic life criteria apply to this set of PCBs. 

This criterion applies to total pcbs, i.e., the sum of all congener or all isomer analyses. This recommended water quality criterion is expressed as :g free cyanide (as CN)/L. 

CCC = exp(1.005(pH)-5.134). Values displayed in table correspond to a pH of 7.8. 

even though the results of such a calculation were not shown in the document. 

This recommended water quality criterion refers to the inorganic form only. 

CMC1 and CMC2 are 185.9 

criterion and so this value might change substantially in the near future. 

:g/L and 12.83 :g/L, respectively. 

the 

actions using the State's existing narrative criteria for toxics. 

1986 Quality Criteria for Water. 

trophic levels. 

E 

F G 

H 

I J 

K 

L 

M N O P Q R S T 

D-9
0.025 :g/L given on page 23 of the criteria document is based on the Final Residue Value procedure in the 1985 Guidelines. Since the publication of the Great 

This recommended water quality criterion was derived on page 43 of the mercury criteria document (EPA 440/5-84-026, January 1985). The saltwater CCC of 

Water Quality Criteria for the Protection of Aquatic Organisms and Their Uses, PB85-227049, January 1985) and was issued in one of the following criteria 

documents: Arsenic (EPA 440/5-84-033), Cadmium (EPA 440/5-84-032), Chromium (EPA 440/5-84-029), Copper (EPA 440/5-84-031), Cyanide (EPA 440/5-

84-028), Lead (EPA 440/5-84-027), Nickel (EPA 440/5-86-004), Pentachlorophenol (EPA 440/5-86-009), Toxaphene, (EPA 440/5-86-006), Zinc (EPA 

1995 (60FR15393-15399, March 23, 1995), the Agency no longer uses the 

440/5-87- 003). 

Final Residue Value procedure for deriving CCCs for new or revised 304(a) aquatic 

criteria. 

life criteria. 

It is anticipated that industry intends to publish in the peer reviewed literature draft aquatic life criteria generated in accordance with EPA Guidelines. 

EPA will review such criteria for possible issuance as national WQC. 

Although EPA has not published a final criteria document for this compound it is EPA’s understanding that sufficient data exist to allow calculation of aquatic 

This recommended water quality criterion was derived from data for inorganic mercury (II), but is applied here to total mercury. If a substantial portion of the 

This water quality criterion is based on a 304(a) aquatic life criterion that was derived using the 1985 Guidelines (Guidelines for Deriving Numerical National 

This CCC is based on the Final Residue Value procedure in the 1985 Guidelines. Since the publication of the Great Lakes Aquatic Life Criteria Guidelines in 

mercury in the water column is methylmercury, this criterion will probably be under protective. In addition, even though inorganic mercury is converted to methylmercury and methylmercury bioaccumulates to a great extent, this criterion does not account for uptake via the food chain because sufficient data were 

The selenium criteria document (EPA 440/5-87-

not available when the criterion was derived. 

006, September 1987) provides that if selenium is as toxic to saltwater fishes in the field as it is to freshwater 

fishes in the field, the status of the fish community should be monitored whenever the concentration of selenium exceeds 5.0 :g/L in salt water because the 

A more stringent MCL has been issued by EPA. Refer to drinking water regulations (40 CFR 141) or Safe Drinking Water Hotline (1-800-426-4791) for 

Lakes Aquatic Life Criteria Guidelines in 1995 (60FR15393-15399, March 23, 1995), the Agency no longer uses the Final Residue Value procedure for 

T

deriving CCCs for new or revised 304(a) aquatic life criteria. 

his value was derived from data for heptachlor and the criteria document provides insufficient data to estimate the relative toxicities of heptachlor and 

This recommended water quality criterion was derived in Ambient Water Quality Criteria Saltwater Copper Addendum (Draft, April 14, 1995) and was 

When the concentration of dissolved organic carbon is elevated, copper is substantially less toxic and use of Water-Effect Ratios might be appropriate. 

This value was derived from data for endosulfan and is most appropriately applied to the sum of alpha-endosulfan and beta-endosulfan. 

EPA is actively working on this criterion and so this recommended water quality criterion may change substantially in the near future. 

There is a full set of aquatic life toxicity data that show that DEHP is not toxic to aquatic organisms at or below its solubility limit. 

promulgated in the Interim final National Toxics Rule (60FR22228-222237, May 4, 1995). 

heptachlor epoxide. 

values. 

saltwater CCC does not take into account uptake via the food chain. 

V W X Y 

Z 

aa bb 

cc 

dd 

ee 

ff 

gg hh 

D-10
D-11

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR NON-PRIORITY POLLUTANTS

Priority Pollutant CAS Number

Freshwater Saltwater

Human Health For

Consumption of:

FR Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

1 Alkalinity -- * 20000 F * Gold Book

2 Aluminum pH 6.5 - 9.0 7429905 750 G,I 87 G,I,L * 53FR33178

3 Ammonia 7664417 FRESHWATER CRITERIA ARE pH DEPENDENT -- SEE DOCUMENT 

SALTWATER CRITERIA ARE pH AND TEMPERATURE DEPENDENT

EPA822-R-98-008

EPA440/5-88-004

4 Aesthetic Qualities -- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book5 Bacteria -- FOR PRIMARY RECREATION AND SHELLFISH USES -- SEE DOCUMENT Gold Book

6 Barium 7440393 1,000 A Gold Book

7 Boron -- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book

8 Chloride 16887006 860000 G 230000 G 53FR19028

9 Chlorine 7782505 19 11 13 7.5 C Gold Book

10 Chlorophenoxy Herbicide

2,4,5,-TP

93721 10 A Gold Book

11 Chlorophenoxy Herbicide

2,4-D

94757 100 A,C Gold Book

12 Chlorpyrifos 2921882 0.083 G 0.041 G 0.011 G 0.0056 G Gold Book

13 Color -- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book

14 Demeton 8065483 0.1 F 0.1 F Gold Book

15 Ether, Bis Chloromethyl 542881 0.00013 E 0.00078 E IRIS 01/01/91

16 Gases, Total Dissolved -- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book17 Guthion 86500 0.01 F 0.01 F Gold Book18 Hardness -- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book

* * ** * *

D

F

F
D-12

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR NON-PRIORITY POLLUTANTS

Priority Pollutant CAS Number

Freshwater Saltwater

Human Health For

Consumption of:

FR Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

19 Hexachlorocyclo-hexaneTechnical 319868 0.0123 0.0414 Gold Book

20 Iron 7439896 1000 F 300 A Gold Book

21 Malathion 121755 0.1 F 0.1 F Gold Book

22 Manganese 7439965 50 A 100 A Gold Book23 Methoxychlor 72435 0.03 F 0.03 F 100 A,C Gold Book24 Mirex 2385855 0.001 F 0.001 F Gold Book

25 Nitrates 14797558 10,000 A Gold Book

26 Nitrosamines -- 0.0008 1.2427 Dinitrophenols 25550587 70 14,000 Gold Book

28 Nitrosodibutylamine,N 924163 0.0064 A 0.587 A Gold Book

29 Nitrosodiethylamine,N 55185 0.0008 A 1.24 A Gold Book

30 Nitrosopyrrolidine,N 930552 0.016 91.9 Gold Book

31 Oil and Grease -- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book32 Oxygen, Dissolved 7782447 WARMWATER AND COLDWATER MATRIX -- SEE DOCUMENT Gold Book33 Parathion 56382 0.065 J 0.013 J Gold Book34 Pentachlorobenzene 608935 3.5 E 4.1 E IRIS 03/01/88

35 pH -- 6.5 - 9 F 6.5 - 8.5 F,K 5 - 9 Gold Book

36 Phosphorus Elemental 7723140 0.1 F,K Gold Book37 Phosphate Phosphorus -- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book

F

O
D-13

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR NON-PRIORITY POLLUTANTS

Priority Pollutant CAS Number

Freshwater Saltwater

Human Health For

Consumption of:

FR Cite/Source

CMC

(:g/L)

CCC

(:g/L)

CMC

(:g/L)

CCC

(:g/L)

Water +

Organism

(:g/L)

Organism

Only

(:g/L)

38 Solids Dissolved and

Salinity

-- 250,000 A Gold Book

39 Solids Suspended and

Turbidity

-- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book

40 Sulfide-Hydrogen Sulfide 7783064 2.0 F 2.0 F Gold Book

41 Tainting Substances -- NARRATIVE STATEMENT -- SEE DOCUMENT Gold Book42 Temperature -- SPECIES DEPENDENT CRITERIA -- SEE DOCUMENT Gold Book

43 Tetrachlorobenzene,1,2,4,5- 95943 2.3 E 2.9 E IRIS03/01/91

44 Tributyltin TBT -- 0.46 N 0.063 N 0.37 N 0.010 N 62FR42554

45 Trichlorophenol,2,4,5- 95954 2,600 B,E 9800 B,E IRIS 03/01/88

Footnotes:A This human health criterion is the same as originally published in the Red Book which predates the 1980 methodology and did not utilize the fish ingestion

BCF approach. lue is now published in the Gold Book.

B The organoleptic effect criterion is more stringent than the value presented in the non priority pollutants table.C A more stringent Maximum Contaminant Level (MCL) has been issued by EPA under the Safe Drinking Water Act. water regulations

40CFR141 or Safe Drinking Water Hotline (1-800-426-4791) for values.

D According to the procedures described in the Guidelines for Deriving Numerical National Water Quality Criteria for the Protection of Aquatic Organisms and

Their Uses, except possibly where a very sensitive species is important at a site, freshwater aquatic life should be protected if both conditions specified in

Appendix C to the Preamble--Calculation of Freshwater Ammonia Criterion are satisfied.

E This criterion has been revised to reflect The Environmental Protection Agency’s q1* or RfD, as contained in the Integrated Risk Information System (IRIS) as

of April 8, 1998. used to derive the original criterion was retained in each case.

F The derivation of this value is presented in the Red Book (EPA 440/9-76-023, July, 1976).

G This value is based on a 304(a) aquatic life criterion that was derived using the 1985 Guidelines (Guidelines for Deriving Numerical National Water Quality

Criteria for the Protection of Aquatic Organisms and Their Uses, PB85-227049, January 1985) and was issued in one of the following criteria documents:Aluminum (EPA 440/5-86-008); Chloride (EPA 440/5-88-001); Chlorpyrifos (EPA 440/5-86-005).

I This value is expressed in terms of total recoverable metal in the water column.J This value is based on a 304(a) aquatic life criterion that was issued in the 1995 Updates: Water Quality Criteria Documents for the Protection of Aquatic Life

in Ambient Water (EPA-820-B-96-001). Guidelines (60FR15393-15399, March 23, 1995; 40CFR132 Appendix A); the

differences between the 1985 Guidelines and the GLI Guidelines are explained on page iv of the 1995 Updates. rning this criterion was

affected by any considerations that are specific to the Great Lakes.

F

M

This same criterion va

Refer to drinking 

The fish tissue bioconcentration factor (BCF) 

This value was derived using the GLI 

No decision conce
For open ocean waters where the depth is substantially greater than the euphotic zone, the pH should not be changed more than 0.2 units from the naturally 

occurring variation or any case outside the range of 6.5 to 8.5. For shallow, highly productive coastal and estuarine areas where naturally occurring pH 

variations approach the lethal limits of some species, changes in pH should be avoided but in any case should not exceed the limits established for fresh 

water, i.e., 6.5-9.0. 

This value was announced (62FR42554, August 7, 1997) as a proposed 304(a) aquatic life criterion. Although EPA has not responded to public comment, EPA 

bass in water with pH= 6.5-6.6 and hardness <10 mg/L. Data in “Aluminum Water-Effect Ratio for the 3M Plant Effluent Discharge, Middleway, West 

Virginia” (May 1994) indicate that aluminum is substantially less toxic at higher pH and hardness, but the effects of pH and hardness are not well quantified at 

this time. (2) In tests with the brook trout at low pH and hardness, effects increased with increasing concentrations of total aluminum even though the 

concentration of dissolved aluminum was constant, indicating that total recoverable is a more appropriate measurement than dissolved, at least when particulate 

aluminum is primarily aluminum hydroxide particles. In surface waters, however, the total recoverable procedure might measure aluminum associated with 

clay particles, which might be less toxic than aluminum associated with aluminum hydroxide. (3) EPA is aware of field data indicating that many high quality 

waters in the U.S. contain more than 87 :g aluminum/L, when either total recoverable or dissolved is measured. 

There are three major reasons why the use of Water-Effect Ratios might be appropriate. (1) The value of 87 :g/L is based on a toxicity test with the striped 

U.S. EPA. 1973. Water Quality Criteria 1972. EPA-R3-73-033. National Technical Information Service, Springfield, VA.; U.S. EPA. 1977. Temperature 

U.S. EPA. 1986. Ambient Water Quality Criteria for Dissolved Oxygen. EPA 440/5-86-003. National Technical Information Service, Springfield, VA. 

is publishing this as a 304(a) criterion in today’s notice as guidance for States and Tribes to consider when adopting water quality criteria. 

Criteria for Freshwater Fish: Protocol and Procedures. EPA-600/3-77-061. National Technical Information Service, Springfield, VA. 

According to page 181 of the Red Book: K 

L 

M 

N 

O 

D-14
D-15

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR ORGANOLEPTIC EFFECTS

Pollutant CAS Number

Organoleptic Effect Criteria

(:g/L) FR Cite/Source

1 Acenaphthene 83329 20 Gold Book

2 Monochlorobenzene 108907 20 Gold Book

3 3-Chlorophenol -- 0.1 Gold Book4 4-Chlorophenol 106489 0.1 Gold Book

5 2,3-Dichlorophenol -- 0.04 Gold Book

6 2,5-Dichlorophenol -- 0.5 Gold Book

7 2,6-Dichlorophenol -- 0.2 Gold Book

8 3,4-Dichlorophenol -- 0.3 Gold Book

9 2,4,5-Trichlorophenol 95954 1 Gold Book

10 2,4,6-Trichloropehnol 88062 2 Gold Book

11 2,3,4,6-Tetrachlorophenol -- 1 Gold Book12 2-Methyl-4-Chlorophenol -- 1800 Gold Book

13 3-Methyl-4-Chlorophenol 59507 3000 Gold Book

14 3-Methyl-6-Chlorophenol -- 20 Gold Book

15 2-Chlorophenol 95578 0.1 Gold Book

16 Copper 7440508 1000 Gold Book

17 2,4-Dichlorophenol 120832 0.3 Gold Book

18 2,4-Dimethylphenol 105679 400 Gold Book

19 Hexachlorocyclopentadiene 77474 1 Gold Book

20 Nitrobenzene 98953 30 Gold Book
be exposed briefly without resulting in an unacceptable effect. The Criterion Continuous Concentration (CCC) is an estimate of the highest concentration of a 

The CMC and CCC are just two of material in surface water to which an aquatic community can be exposed indefinitely without resulting in an unacceptable effect. 

the six parts of a aquatic life criterion; the other four parts are the acute averaging period, chronic averaging period, acute frequency of allowed exceedence, and 

chronic frequency of allowed exceedence. Because 304(a) aquatic life criteria are national guidance, they are intended to be protective of the vast majority of the aquatic communities in the United States. 

This compilation lists all priority toxic pollutants and some non priority toxic pollutants, and both human health effect and organoleptic effect criteria 

issued pursuant to CWA §304(a). Blank spaces indicate that EPA has no CWA §304(a) criteria recommendations. For a number of non-priority toxic pollutants not 

listed, CWA §304(a) “water + organism” human health criteria are not available, but, EPA has published MCLs under the SDWA that may be used in establishing 

water quality standards to protect water supply designated uses. Because of variations in chemical nomenclature systems, this listing of toxic pollutants does not duplicate the listing in Appendix A of 40 CFR Part 423. Also listed are the Chemical Abstracts Service CAS registry numbers, which provide a unique identification for each chemical. 

The Criteria Maximum Concentration (CMC) is an estimate of the highest concentration of a material in surface water to which an aquatic community can 

The human health criteria for the priority and non priority pollutants are based on carcinogenicity of 10 -6 risk. Alternate risk levels may be obtained by 

moving the decimal point (e.g., for a risk level of 10 -5 , move the decimal point in the recommended criterion one place to the right). 

Because of variations in chemical nomenclature systems, this listing of pollutants does 

not duplicate the listing in Appendix A of 40 CFR Part 423. Also listed are the Chemical Abstracts Service (CAS) registry numbers, which provide a 

unique identification for each chemical. 

NATIONAL RECOMMENDED WATER QUALITY CRITERIA 

FR Cite/Source 

NATIONAL RECOMMENDED WATER QUALITY CRITERIA FOR ORGANOLEPTIC EFFECTS 

Gold Book 

Gold Book 

45FR79341 

Organoleptic Effect Criteria 

CAS Number 

Criteria Recommendations for Priority Pollutants, Non Priority Pollutants and Organoleptic Effects 

(:g/L) 

30 

300 

5000 

Criteria Maximum Concentration and Criterion Continuous Concentration 

These criteria are based on organoleptic (taste and odor) effects. 

87865 

108952 

7440666 

Human Health Risk 

Pollutant 

Pentachlorophenol 

General Notes: 

Additional Notes: 

Phenol 

Zinc 

21 22 23 

1. 

1. 

2. 

3. 

D-16
The compilation contains 304(a) criteria for pollutants with toxicity-based criteria as well as non-toxicity based criteria. The basis for the non-toxicity based 

criteria are organoleptic effects (e.g., taste and odor) which would make water and edible aquatic life unpalatable but not toxic to humans. The table includes criteria 

for organoleptic effects for 23 pollutants. Pollutants with organoleptic effect criteria more stringent than the criteria based on toxicity (e.g., included in both the priority and non-priority pollutant tables) are footnoted as such. 

The Chemical Abstract Services number (CAS) for Bis(2-Chloroisopropyl) Ether, has been corrected in the table. The correct CAS number for this chemical is 

39638-32-9. Previous publications listed 108-60-1 as the CAS number for this chemical. 

In the 1980 Selenium document, a criterion for the protection of human health from consumption of water and organisms was calculated based on a BCF of 6.0 

L/kg and a maximum water-related contribution of 35 mg Se/day. Subsequently, the EPA Office of Health and Environmental Assessment issued an errata notice (February 23, 1982), revising the BCF for selenium to 4.8 L/kg. In 1988, EPA issued an addendum (ECAO-CIN-668) revising the human health criteria for selenium. Later in the final National Toxic Rule (NTR, 57 FR 60848), EPA withdrew previously published selenium human health criteria, pending Agency review 

of new epidemiological data. 

The 304(a) criteria for metals, shown as dissolved metals, are calculated in one of two ways. For freshwater metals criteria that are hardness-dependent, the 

dissolved metal criteria were calculated using a hardness of 100 mg/L as CaCO3 for illustrative purposes only. Saltwater and freshwater metals’ criteria that are not 

hardness-dependent are calculated by multiplying the total recoverable criteria before rounding by the appropriate conversion factors. The final dissolved metals’ 

criteria in the table are rounded to two significant figures. Information regarding the calculation of hardness dependent conversion factors are included in the 

footnotes. 

The compilation includes footnotes for pollutants with Maximum Contaminant Levels (MCLs) more stringent than the recommended water quality criteria in 

the compilation. MCLs for these pollutants are not included in the compilation, but can be found in the appropriate drinking water regulations (40 CFR 141.11-16 

Many of the values in the compilation were published in the proposed California Toxics Rule (CTR, 62FR42160). Although such values were published 

pursuant to Section 303(c) of the CWA, they represent the Agency’s most recent calculation of water quality criteria and thus are published today as the Agency’s 

304(a) criteria. Water quality criteria published in the proposed CTR may be revised when EPA takes final action on the CTR. 

In the 1980 criteria documents, certain recommended water quality criteria were published for categories of pollutants rather than for individual pollutants 

within that category. Subsequently, in a series of separate actions, the Agency derived criteria for specific pollutants within a category. Therefore, in this 

compilation EPA is replacing criteria representing categories with individual pollutant criteria (e.g., 1,3-dichlorobenzene, 1,4-dichlorobenzene and 

and 141.60-63), or can be accessed through the Safe Drinking Wat

1,2-dichlorobenzene). 

er Hotline (800-426-4791) or the Internet (http://www.epa.gov/ost/tools/dwstds-s.html). 

Water Quality Criteria published pursuant to Section 304(a) or Section 303(c) of the CWA 

Correction of Chemical Abstract Services Number 

Calculation of Dissolved Metals Criteria 

Maximum Contaminant Levels 

Specific Chemical Calculations 

Human Health 

Organoleptic Effects 

Category Criteria 

Selenium 

(1) 

A. 

4. 

5. 

6. 7. 

8. 9. 

10. 

D-17
This compilation includes human health criteria for selenium, calculated using a BCF of 4.8 L/kg along with the current IRIS RfD of 0.005 mg/kg/day. EPA 

included these recommended water quality criteria in the compilation because the data necessary for calculating a criteria in accordance with EPA’s 1980 human 

health methodology are available. 

Aquatic Life (2) 

This compilation contains aquatic life criteria for selenium that are the same as those published in the proposed CTR. In the CTR, EPA proposed an acute 

criterion for selenium based on the criterion proposed for selenium in the Water Quality Guidance for the Great Lakes System (61 FR 58444). The GLI and CTR 

proposals take into account data showing that selenium’s two most prevalent oxidation states, selenite and selenate, present differing potentials for aquatic toxicity, as well as new data indicating that various forms of selenium are additive. The new approach produces a different selenium acute criterion concentration, or CMC, 

depending upon the relative proportions of selenite, selenate, and other forms of selenium that are present. 

EPA notes it is currently undertaking a reassessment of selenium, and expects the 304(a) criteria for selenium will be revised based on the final reassessment 

(63FR26186). However, until such time as revised water quality criteria for selenium are published by the Agency, the recommended water quality criteria in this compilation are EPA’s current 304(a) criteria. 

1,2,4-Trichlorobenzene and Zinc B. 

Human health criteria for 1,2,4-trichlorobenzene and zinc have not been previously published. Sufficient information is now available for calculating water 

quality criteria for the protection of human health from the consumption of aquatic organisms and the consumption of aquatic organisms and water for both these 

compounds. Therefore, EPA is publishing criteria for these pollutants in this compilation. 

Chromium (III) C. 

The recommended aquatic life water quality criteria for chromium (III) included in the compilation are based on the values presented in the document titled: 

1995 Updates: Water Quality Criteria Documents for the Protection of Aquatic Life in Ambient Water, however, this document contains criteria based on the total recoverable fraction. The chromium (III) criteria in this compilation were calculated by applying the conversion factors used in the Final Water Quality Guidance 

for the Great Lakes System (60 FR 15366) to the 1995 Update document values. 

Ether, Bis (Chloromethyl), Pentachlorobenzene, Tetrachlorobenzene 1,2,4,5-, Trichlorphenol D. 

Human health criteria for these pollutants were last published in EPA’s Quality Criteria for Water 1986 or “Gold Book”. Some of these criteria were calculated 

using Acceptable Daily Intake (ADIs) rather than RfDs. Updated q1*s and RfDs are now available in IRIS for ether, bis (chloromethyl), pentachlorobenzene, tetrachlorobenzene 1,2,4,5-, and trichlorophenol, and were used to revise the water quality criteria for these compounds. The recommended water quality criteria for ether, bis (chloromethyl) were revised using an updated q1*, while criteria for pentachlorobenzene, and tetrachlorobenzene 1,2,4,5-, and trichlorophenol were 

derived using an updated RfD value. 

PCBs E. 

These criteria replace the In this compilation EPA is publishing aquatic life and human health criteria based on total PCBs rather than individual arochlors. 

previous criteria for the seven individual arochlors. Thus, there are criteria for a total of 102 of the 126 priority pollutants. 

D-18
-- --

-- --

-- --

Conversion Factors for Dissolved Metals 

Metal 

Conversion Factor 

freshwater CMC 

Conversion Factor 

freshwater CCC 

Conversion Factor 

saltwater CMC 

Conversion Factor 

saltwater CCC1 

Arsenic 1.000 1.000 1.000 1.000 

Cadmium 1.136672-[(ln 

hardness)(0.041838)] 

1.101672-[(ln 

hardness)(0.041838)] 

0.994 0.994 

Chromium III 0.316 0.860 

Chromium VI 0.982 0.962 0.993 0.993 

Copper 0.960 0.960 0.83 0.83 Lead 1.46203-[(ln 

hardness)(0.145712)] 

1.46203-[(ln 

hardness)(0.145712)] 

0.951 0.951 

Mercury 0.85 0.85 0.85 0.85 Nickel 0.998 0.997 0.990 0.990 

Selenium 0.998 0.998 Silver 0.85 0.85 Zinc 0.978 0.986 0.946 0.946 

D-19
-- -- --

 Parameters* for Calculating Freshwater Dissolved Metals Criteria That Are Hardness-Dependent 

Chemical mA bA mC bC 

Freshwater Conversion Factors (CF) 

Acute Chronic 

Cadmium 1.128 -3.6867 0.7852 -2.715 1.136672-[ln 

(hardness)(0.041838)] 

1.101672-[ln 

(hardness)(0.041838)] 

Chromium III 0.8190 3.7256 0.8190 0.6848 0.316 0.860 

Copper 0.9422 -1.700 0.8545 -1.702 0.960 0.960 

Lead 1.273 -1.460 1.273 -4.705 1.46203-[ln 

(hardness)(0.145712)] 

1.46203-[ln 

(hardness)(0.145712)] 

Nickel 0.8460 2.255 0.8460 0.0584 0.998 0.997 

Silver 1.72 -6.52 0.85 

Zinc 0.8473 0.884 0.8473 0.884 0.978 0.986 

* Where mA and bA are conversion factors to calculate CMC and mC and bC are 

conversion factors necessary to calculate CCC 

D-20
Appendix C - Calculation of Freshwater Ammonia Criterion 

1. The one-hour average concentration of total ammonia nitrogen (in mg N/L) does not exceed, more than once 

every three years on the average, the CMC calculated using the following equation: 

0.275 39.0

CMC = 

1 107.204− pH + 1 10pH − 7.204 + + 

In situations where salmonids do not occur, the CMC may be calculated using the following equation: 

0.411 58.4

CMC = 

1 107.204− pH + 1 10pH − 7.204 + + 

2. The thirty-day average concentration of total ammonia nitrogen (in mg N/L) does not exceed, more than once 

every three years on the average, the CCC calculated using the following equation: 

0.0858 3.70

CCC = 

1 107.688− pH + 1 10pH − 7.688 + + 

and the highest four-day average within the 30-day period does not exceed twice the CCC. 

Source: U.S. EPA’s National Recommended Water Quality Criteria-Correction, EPA-822-Z-99-001, 

April 1999, pp. 7-25; http://www.epa.gov/OST/standards/wqcriteria.html 

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D-22
APPENDIX E -

FEDERAL SEWAGE SLUDGE STANDARDS Pollutant Ceiling Concentration* Monthly Average Pollutant Concentration* Cumulative Pollutant Loading Rates* Annual Pollutant Loading Rate* (Table 1, 40 CFR 503.13) (Table 3, 40 CFR 503.13) (Table 2, 40 CFR 503.13) (Table 4, 40 CFR 503.13) mg/kg lbs/1000 lbs 

mg/kg lbs/1000 lbs kg/hectare lbs/acre** kg/hectare/ 365-day period lbs/acre/ 365-day period** 

Arsenic 75 75 41 41 41 37 2 1.8 

Cadmium 85 85 39 39 39 35 1.9 1.7 

Copper 4,300 4,300 1,500 1,500 1,500 1,338 75 67 

Lead 840 840 300 300 300 268 15 13 

Mercury 57 57 17 17 17 15 0.85 0.76 

Molybdenum 75 75 - - - - - -

Nickel 420 420 420 420 420 375 21 19 

Selenium 100 100 100 100 100 89 5 4.5 

Zinc 7,500 7,500 2,800 2,800 2,800 2,498 140 125 

Biosolids Land Application Limitations 

* ** Calculated using metric standards specified in 40 CFR 503.13 multiplied by the conversion factor of 0.8922. 

Dry weight. 

Source: 40 CFR §503.13, Tables 1-4, October 25, 1995 

E-1
Surface Disposal 

Distance from the Boundary of Active 

Biosolids Unit to Surface Disposal Site 

Property Line (meters) 

Pollutant Concentration* 

Arsenic 

(mg/kg) 

Chromium 

(mg/kg) 

Nickel 

(mg/kg) 

0 to less than 25 30 200 210 

25 to less than 50 34 220 240 

50 to less than 75 39 260 270 

75 to less than 100 46 300 320 

100 to less than 125 53 360 390 

125 to less than 150 62 450 420 

Equal to or greater than 150 73 600 420 

* Dry-weight.

Source: 40 CFR Part 503.23 Table 1 and 2.

Conversion Factors 

pounds per acre (lbs/ac) x 1.121 = kilograms per hectare (kg/ha)

kilograms per hectare (kg/ha) x 0.8922 = pounds per acre (lbs/ac)

pound (lb) = 0.4536 kilogram (kg)

kilogram (kg) = 2.205 pounds (lbs)

English ton = 0.9072 metric tonne

metric tonne = 1.102 English ton

E-2
APPENDIX F -

TOXICITY CHARACTERISTIC LEACHATE PROCEDURE

LIMITATIONS

EPA Hazardous 

Waste No. Contaminant CAS No. 

1 Regulatory Level (mg/L) 

D004 Arsenic 7440–38–2 5.0 

D005 Barium 7440–39–3 100.0 

D018 Benzene 71–43–2 0.5 

D006 Cadmium 7440–43–9 1.0 

D019 Carbon tetrachloride 56–23–5 0.5 

D020 Chlordane 57–74–9 0.03 

D021 Chlorobenzene 108–90–7 100.0 

D022 Chloroform 67–66–3 6.0 

D007 Chromium 7440–47–3 5.0 

D024 o-Cresol 95-48-7 200.0 2 

D024 m-Cresol 108–39–4 200.0 2 

D025 p-Cresol 106–44–5 200.0 2 

D026 Cresols 200.0 2 

D016 2,4-D 94–75–7 10.0 

D027 1,4-Dichlorobenzene 106–46–7 7.5 

D028 1,2-Dichloroethane 107–06–2 0.5 

D029 1,1-Dichloroethylene 75–35–4 0.7 

D030 2,4-Dinitrotoluene 121–14–2 0.13 3 

D012 Endrin 72–20–8 0.02 

D031 Heptachlor (and its 

epoxide) 

76–44–8 0.008 

D032 Hexachlorobenzene 118–74–1 0.13 3 

D033 Hexachlorobutadiene 87–68–3 0.5 

D034 Hexachloroethane 67–72–1 3.0 

D008 Lead 7439–92–1 5.0 

D013 Lindane 58–89–9 0.4 

D009 Mercury 7439–97–6 0.2 

D014 Methoxychlor 72–43–5 10.0 

D035 Methyl ethyl ketone 78–93–3 200.0 

D036 Nitrobenzene 98–95–3 2.0 

D037 Pentachlorophenol 87–86–5 100.0 

D038 ridine 110–86–1 5.0 3 

D010 Selenium 7782–49–2 1.0 

D011 Silver 7440–22–4 5.0 

D039 Tetrachloroethylene 127–18–4 0.7 

D015 Toxaphene 8001–35–2 0.5 

D040 Trichloroethylene 79–01–6 0.5 

Py

F-1
EPA Hazardous 

Waste No. Contaminant CAS No. 

1 Regulatory Level (mg/L) 

D041 2,4,5-Trichlorophenol 95–95–4 400.0 

D042 2,4,6-Trichlorophenol 88–06–2 2.0 

D017 2,4,5-TP (Silvex) 93–72–1 

D043 Vinyl chloride 75–01–4 

1.0 

0.2 

1 Chemical Abstracts Service number. 

2 If o-, m-, and p-Cresol concentrations cannot be differentiated, the total cresol (D026) 

concentration is used. The regulatory level of total cresol is 200 mg/L. 

3 Quantitation limit is greater than the calculated regulatory level. The quantitation limit 

therefore becomes the regulatory level. 

Source: 40 CFR 261.24 

F-2
APPENDIX G -

LITERATURE INHIBITION VALUES

Pollutant 

Reported Range of Activated Sludge 

Inhibition Threshold 

Levels, mg/L 

References* 

METALS/NONMETAL INORGANICS 

Ammonia 480 (4) 

Arsenic 0.1 (1), (2), (3) 

Cadmium 1 - 10 (2), (3) 

Chromium (VI) 1 (2), (3) 

Chromium (III) 10 - 50 (2), (3) 

Chromium (Total) 1 - 100 (1) 

Copper 1 (2), (1), (3) 

Cyanide 0.1 - 5 

5 

(1), (2), (3) 

(1) 

Iodine 10 (4) 

Lead 1.0 - 5.0 

10 - 100 

(3) 

(1) 

Mercury 0.1 - 1 

2.5 as 

(2), (3) 

(1) 

Nickel 1.0 - 2.5 

5 

(2), (3) 

(1) 

Sulfide 25 -30 (4) 

Zinc 0.3 - 5 

5 - 10 

(3) 

(1) 

Hg (II) 

ORGANICS 

Anthracene 500 (1) 

Benzene 100 - 500 

125 - 500 

(3) 

(1) 

2-Chlorophenol 5 

20 - 200 

(2) 

(3) 

1,2 Dichlorobenzene 5 (2) 

1,3 Dichlorobenzene 5 (2) 

1,4 Dichlorobenzene 5 (2) 

2,4-Dichlorophenol 64 (3) 

2,4 Dimethylphenol 40 - (3) 

2,4 Dinitrotoluene 5 (2) 

1,2-Diphenylhydrazine 5 (2) 

Ethylbenzene 200 (3) 

Hexachlorobenzene 5 (2) 

Naphthalene 500 

500 

500 

(1) 

(2) 

(3) 

Nitrobenzene 30 - 500 

500 

500 

(3) 

(1) 

(2) 

200 

G-1
Reported Range of Activated Sludge 

Pollutant Inhibition Threshold References* 

Levels, mg/L 

Pentachlorophenol 0.95 (2) 

50 (3) 

75 - 150 (1) 

500 (1) 

500 (2) 

50 - 200 (3) 

200 (2) 

200 (1) 

200 (3) 

50 - 100 (1) 

Surfactants 100 - 500 (4) 

Phenanthrene 

Phenol 

Toluene 

2,4,6 Trichlorophenol 

Pollutant Reported Range of Trickling Filter References* Inhibition Threshold Levels, mg/L 

Chromium (III) 3.5 - 67.6 (1) 

Cyanide 30 (1) 

Pollutant Reported Range of Nitrification 

Inhibition Threshold Levels, mg/L References* 

METALS/NONMETAL INORGANICS 

Arsenic 1.5 (2) 

Cadmium 5.2 (1), (2) 

Chloride 180 (4) 

Chromium (VI) 1 - 10 [as (CrO4 )

2-] (1) 

Chromium (T) 0.25 - 1.9 

1 - 100 

(trickling filter) 

(1), (2), (3) 

(1) 

Copper 0.05 - 0.48 (2), (3) 

Cyanide 0.34 - 0.5 (2), (3) 

Lead 0.5 (2), (3) 

Nickel 0.25 - 0.5 

5 

(2), (3) 

(1) 

Zinc 0.08 - 0.5 (2), (3) 

ORGANICS 

Chloroform 10 (2) 

2,4-Dichlorophenol 64 (3) 

2,4-Dinitrophenol 150 (2) 

Phenol 4 

4 - 10 

(2) 

(3) 

G-2
Pollutant 

Reported Range of Anaerobic 

Digestion Inhibition Threshold 

Levels, mg/L 

References* 

METALS/NONMETAL INORGANICS 

Ammonia 1500 - 8000 (4) 

Arsenic 1.6 (1) 

Cadmium 20 (3) 

Chromium (III) 130 (3) 

Chromium (VI) 110 (3) 

Copper 40 (3) 

Cyanide 4 - 100 

1 - 4 

(1) 

(2), (3) 

Lead 340 (3) 

Nickel 10 

136 

(2), (3) 

(1) 

Silver 13 - 65** (3) 

Sulfate 500 - 1000 (4) 

Sulfide 50 - 100 (4) 

Zinc 400 (3) 

ORGANICS 

Acrylonitrile 5 

5 

(3) 

(2) 

Carbon Tetrachloride 2.9 - 159.4 

10 - 20 

2.0 

(1) 

(3) 

(2) 

Chlorobenzene 0.96 - 3 

0.96 

(1) 

(2) 

Chloroform 1 

5 - 16 

10 - 16 

(2) 

(1) 

(3) 

1,2-Dichlorobenzene 0.23 - 3.8 

0.23 

(1) 

(2) 

1,4-Dichlorobenzene 1.4 - 5.3 

1.4 

(1) 

(2) 

Methyl chloride 3.3 - 536.4 

100 

(1) 

(2) 

Pentachlorophenol 0.2 

0.2 -

(2) 

(1) 

Tetrachloroethylene 20 (2) 

Trichloroethylene 1 - 20 

20 

20 

(1) 

(2) 

(3) 

Trichlorofluoromethane - (2) 

1.8 

* Total pollutant inhibition levels, unless otherwise indicated.

** Dissolved metal inhibition levels.

(1) Jenkins, D.I., and Associates. 1984. Impact of Toxics on Treatment Literature Review.

G-3
(2) Russell, L. L., C. B. Cain, and D.I. Jenkins. 1984. Impacts of Priority Pollutants on Publicly 

Owned Treated Works Processes: A Literature Review. 1984 Purdue Industrial Waste 

Conference. 

(3) Anthony, R. M., and L. H. Briemburst. 1981. Determining Maximum Influent Concentrations 

of Priority Pollutants for Treatment Plants. Journal Water Pollution Control Federation 

53(10):1457-1468. 

(4) U.S. EPA. 1986, Working Document; Interferences at Publicly Owned Treatment Works. 

September 1986. 

Source: EPA’s Guidance Manual on the Development and Implementation of Local Discharge 

Limitations Under the Pretreatment Program, December 1987, pp. 3-44 to 3-49. 

G-4
APPENDIX H -

CLOSED-CUP FLASHPOINTS FOR SELECT ORGANIC COMPOUNDS

Pollutant Closed Cup 

Flashpoint (/F) 

Acrolein -15 

Acrylonitrile 30 

Benzene 12 

Chlorobenzene 82 

Chloroethane (Ethyl chloride) -58 

1,1-Dichloroethane 2 

1,2-Dichloroethane (Ethylene dichloride) 56 

1,1-Dichloroethylene (Vinylidene chloride) -2 

Trans-1,2-Dichloroethylene, (1,2-Dichloroethylene) 36-39 

1,2-Dichloropropane (Propylene dichloride) 60 

Ethylbenzene 55 

Toluene 40 

Source: Online NIOSH Pocket Guide to Chemical Hazards at 

http://www.cdc.gov/niosh/npg/npg.html. 

H-1
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H-2
APPENDIX I -

DISCHARGE SCREENING LEVELS AND HENRY’S LAW CONSTANTS

FOR ORGANIC COMPOUNDS

Discharge Screening Levels Based on Explosivity 

Pollutant LELs(1) 

% volume / 

volume 

LELs 

(mol/m3

) 

Acrolein 2.8 1.15 

Acrylonitrile 

Benzene 

Chlorobenzene 1.3 

Chloroethane 3.8 

1,1-Dichloroethane 5.4 

1,2-Dichloroethane 6.2 

1,1-Dichloroethylene 6.5 

Trans-1,2-Dichloroethylene 5.6 

1,2-Dichloropropane 3.4 

Ethyl benzene 0.8 

Hydrogen Cyanide 5.6 

Hydrogen Sulfide 4.0 

Methyl bromide 10.0 

Methyl chloride 8.1 

Methylene Chloride 13.0 

Toluene 1.1 

1,1,2-Trichloroethane 6.0 

1,1,1-Trichloroethane 7.5 

3.0 

1.2 

Trichloroethylene 8.0 (F) 

Vinyl Chloride 3.6 

1.23 

0.49 

0.53 

1.55 

2.21 

2.54 

2.66 

2.29 

1.39 

0.33 

2.30 

1.64 

4.09 

3.31 

5.32 

0.45 

2.45 

3.07 

3.20 

1.47 

Henry's Law 

Constant 

(mol/m3

)/(mg/L) 

8.7E-05 

8.4E-05 

2.9E-03 

1.3E-03 

7.0E-03 

2.4E-03 

4.9E-04 

1.2E-02 

4.0E-03 

1.0E-03 

3.1E-03 

1.7E-4 

1.7E-2 

2.7E-03 

7.4E-03 

1.2E-03 

3.0E-03 

2.6E-04 

5.2E-03 

3.1E-03 

1.7E-02 

MW 

(g/mol) 

Discharge 

Screening 

Level (mg/L) 

56.1 13163 

53.1 14586 

78.1 169 

112.6 395 

65.5 222 

99 909 

99 5221 

97 215 

97 571 

113 1326 

106.2 106 

27 13529 

34 96 

95 1521 

50.5 450 

84.9 4307 

92.1 152 

133.4 9611 

133.4 591 

131.4 1029 

62.5 88 

Lower Explosive Limits (LELs) assumed for 25°C unless noted otherwise. 

MW = molecular weight 

Source: Updated in 2002 via the online NIOSH Pocket Guide to Chemical Hazards at 

http://www.cdc.gov/niosh/npg/npg.html 

I-1
Discharge Screening Levels Based upon Fume Toxicity 

Pollutant 

Exposure 

Limit* 

(mg/m3

) 

Henry's 

Law 

Constant 

(mg/m3

/ 

mg/L) 

Discharge 

Screening 

Level 

(mg/L) 

Acrolein 0.23 4.9 0.047 

Acrylonitrile 21.70 4.5 4.822 

Benzene 228.0 0.014 

Bromoform 5.17 22.8 0.227 

Carbon Tetrachloride 12.58 1185.0 0.011 

Chlorobenzene 345.75 151.0 2.290 

Chloroethane 2,640.00 449.0 5.880 

Chloroform 9.76 163.5 0.060 

Dichloroethane, 1,1- 405.00 240.4 1.685 

Dichloroethane,1,2- 8.10 48.1 0.168 

Dichloroethylene, 1,1- 19.80 1202.1 0.016 

Trans-Dichloroethylene,1,2- 794.00 389.3 2.040 

Dichloropropane,1,2 20 118.5 4.289 

Ethyl benzene 542.50 327.0 1.659 

Hydrogen Cyanide 5.17 4.5 1.149 

Hydrogen Sulfide 14.00 414.4 0.034 

Methyl bromide 77.80 255.5 0.305 

Methyl chloride 207.00 371.6 0.557 

Methylene Chloride 433.75 104.8 4.139 

Tetrachlorethane, 1,1,2,2- 34.35 18.6 1.847 

Tetrachloroethylene 678.00 717.1 0.945 

Toluene 565.50 272.5 2.075 

Trichloroethane, 1,1,2- 54.60 34.1 1.601 

Trichloroethane, 1,1,1 1,911.00 692.7 2.759 

Trichloroethylene 10.74 408.7 0.026 

Vinyl Chloride 12.80 1048.0 0.012 

3.19 

508.

Source 

TLV-STEL 

PEL-Ceiling, REL- Ceiling 

REL-STEL 

PEL-TWA, TLV-TWA, REL-TWA 

REL-STEL 

PEL-TWA 

PEL-TWA 

REL-STEL 

PEL-TWA, TLV-TWA, REL-TWA 

REL-STEL 

TLV-TWA 

PEL-TWA, TLV-TWA, REL-TWA 

TLV-STEL 

TLV-STEL, REL-STEL 

TLV-Ceiling, REL-STEL 

REL-Ceiling 

PEL-Ceiling 

TLV-STEL 

PEL-STEL 

PEL-TWA 

TLV-STEL 

REL-STEL 

PEL-TWA, TLV-TWA, REL-TWA 

REL-Ceiling 

REL-Ceiling 

PEL Ceiling 

*Exposure limits are lowest of acute toxicity data (NIOSH REL-STEL, ACGIH TLV-STEL, OSHA PELSTEL, NIOSH REL-Ceiling, ACGIH TLV-Ceiling, OSHA PEL-Ceiling) converted from ppm to mg/m3 

through conversion factor. If acute toxicity data were not available, the highest chronic exposure limit 

(NIOSH REL-TWA, ACGIH TLV-TWA, OSHA PEL-TWA) was used. See Appendix J of this manual 

for full list of acute and chronic exposure data. 

Discharge Screening Level = Exposure Limit / Henry’s Law Constant. 

I-2
Henry's Law Constants Expressed in Alternate Units 

Pollutant 

Henry's Law 

Constant(2) 

M/atm @ 298 K 

(25°C) 

Henry's Law 

Constant 

(atm m3

 / mol) 

Henry's Law 

Constant 

(mol/m3

 / mg/L) 

Henry's Law 

Constant 

(mg/m3

 / mg/L) 

Acrolein 8.2 0.00012 0.000087 4.9 

Acrylonitrile 0.00011 0.000084 4.5 

Benzene 0.0056 0.0029 228 

Bromoform 0.00056 0.000091 23 

Carbon Tetrachloride 0.029 0.0077 1185 

Chlorobenzene 0.27 0.0037 0.0013 151 

Chloroethane 0.089 0.011 0.007 449 

Chloroform 0.25 0.004 0.00137 164 

1,1-Dichloroethane 0.17 0.0059 0.0024 240 

1,2-Dichloroethane 0.85 0.0012 0.00049 48 

1,1-Dichloroethylene 0.034 0.029 0.012 1202 

Trans-1,2-Dichloroethylene 0.105 0.0095 0.004 389 

1,2-Dichloropropane 0.345 0.0029 0.001 119 

Ethyl benzene 0.125 0.008 0.0031 327 

Hydrogen Cyanide 9.3 0.00011 0.00017 4.5 

Hydrogen Sulfide 0.1 0.01 0.017 414.4 

Methyl bromide 0.16 0.0063 0.0027 256 

Methyl chloride 0.11 0.0091 0.0074 372 

Methylene Chloride 0.39 0.0026 0.0012 105 

1,1,2,2,-Tetrachlorethane 2.2 0.00045 0.00011 19 

Tetrachloroethylene 0.057 0.018 0.00432 717 

Toluene 0.15 0.0067 0.003 273 

1,1,2-Trichloroethane 1.2 0.00083 0.00026 34 

1,1,1-Trichloroethane 0.059 0.017 0.0052 693 

Trichloroethylene 0.1 0.01 0.0031 409 

Vinyl Chloride 0.039 0.026 0.017 1048 

9.15 

0.18 

1.8 

0.034 

Source: Compilation of Henry’s Law Constants for Inorganic and Organic Species of Potential 

Importance in Environmental Chemistry, R. Sanders 1999 (version 3). 

H (atm m3

/mol) = [986.9 * H (M/atm)]-1 

H (mg/m3

 / mg/L) = 40,893 * H(atm m3 / mol) 

H (mol/m3

 mg/L) = H (mg/m3 / mg/L) / (1000 * MW) 

MW = molecular weight in grams per mole 

I-3
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I-4
APPENDIX J -

OSHA, ACGIH AND NIOSH EXPOSURE LEVELS

EXPOSURE LIMITS FROM VARIOUS AGENCIES FOR VOLATILE ORGANIC PRIORITY 

POLLUTANTS 

OSHA Permissible 

Exposure Limits 

ACGIH Threshold 

Limit Values 

NIOSH 

Recommended 

Exposure Limits 

Volatile Organic 

Compounds 

mg/m3 

per ppm 

TWA 

ppm 

STEL 

ppm 

TVA 

ppm 

STEL 

ppm 

TWA 

ppm 

STEL 

ppm 

Acrolein 2.29 0.1 0.1 0.1 0.3 

Acrylonitrile 2.17 2 C 10 2 1 C 10 

Benzene 3.19 1 5 .5 2.5 0.1 1 

Bromoform 10.34 0.5 0.5 

Carbon Tetrachloride 6.29 10 C 25 5 10 2 

Chlorobenzene 4.61 75 

Chloroethane 

(Ethyl chloride) 2.64 1000 

Chloroform 4.88 C 50 10 2 

Dichloroethane, 1,1- 4.05 100 100 

Dichloroethane,1,2-

(Ethylene dichloride) 4.05 50 C 100 10 1 2 

Dichloroethylene, 1,1-

(Vinylidene chloride) 3.96 5 

transDichloroethylene,1,2-

(1,2-Dichloroethylene) 

3.97 200 200 200 

Dichloropropane,1,2-

(Propylene dichloride) 4.62 75 75 110 

Ethyl benzene 4.34 100 100 100 125 

Hydrogen Cyanide 1.10 10 C 4.7 4.7 

Hydrogen Sulfide 1.40 C 20 10 15 C 10 

Methyl bromide 3.89 C 20 1 

Methyl chloride 2.07 100 C 200 50 100 

Methylene Chloride 

(Dichloromethane) 3.47 25 125 50 

Tetrachlorethane, 

1,1,2,2- 6.87 5 

Tetrachloroethylene 

(Perchloroethylene) 6.78 100 C 200 25 100 

Toluene 3.77 200 C 300 50 100 150 

Trichloroethane, 1,1,2- 5.46 10 10 

Trichloroethane, 1,1,1 

(Methyl Chloroform) 5.46 350 350 450 350 

Trichloroethylene 5.37 100 C 200 50 100 25 C 2 

Vinyl Chloride 2.56 1 5 

C 

0.5 

10 

100 

100 

125 

1 

10 

C 

C 5 

J-1
Occupational Safety and Health Administration Permissible Exposure Limits (PELs) (29 CFR 1910.1000) 

PEL time-weighted average (TWA) concentrations must not be exceeded during any 8-hour workshift of 

a 40-hour workweek. PEL short-term exposure limit (STEL) must not be exceeded over a 15-minute 

period unless noted otherwise. PEL ceiling concentrations (designated by “C” preceding the value in the 

STEL column) must not be exceeded during any part of the workday; if instantaneous monitoring is not 

feasible, the ceiling must be assessed as a 15-minute TWA exposure. OSHA values were updated in 2002 

via the online NIOSH Pocket Guide to Chemical Hazards. http://www.cdc.gov/niosh/npg/npg.html. 

American Conference of Governmental Industrial Hygienists (ACGIH) Threshold Limit Values (TLVs) 

TLV Time-weighted average (TVA) concentrations are for a conventional 8-hour workday and a 40-hour 

workweek for which it is believed that nearly all workers may be repeatedly exposed, day after day, 

without adverse effect. TLV short-term exposure limit (STEL) concentrations are the 15-minute TWA 

exposure which should not be exceeded at any time during a workday even if the 8-hour TWA is within 

the TLV-TWA. TLV ceiling concentrations (designated by a “C” preceding the value in the STEL 

column) should not be exceeded during any part of the working exposure. ACGIH values found in the 

ACGIH 2002 TLVs and BEIs. 

National Institute for Occupational Safety and Health (NIOSH) Recommended Exposure Limits (RELs) 

REL time-weighted average (TWA) concentrations must not be exceeded over a 10-hour workday during 

a 40-hour workweek. REL short-term exposure limits (STELs) are a 15-minute TWA exposure that 

should not be exceeded at any time during a workday. A ceiling REL, designated by “C” preceding the 

value in the STEL column, should not be exceeded at any time. NIIOSH values updated in 2003 via the 

online NIOSH Pocket Guide to Chemical Hazards at http://www.cdc.gov/niosh/npg/npg.html. 

J-2
APPENDIX K -

LANDFILL LEACHATE LOADINGS

Landfill Leachate Monitoring Data* 

Maximum Pollutant Minimum Concentration 

(mg/L) 

Antimony

Arsenic

Barium

Cadmium

Chromium (T)

Copper

Cyanide

Iron

Lead

Manganese

Mercury

Nickel

Selenium

Silver

Zinc

Acetone

Benzene

Benzoic Acid

Chlorobenzene

Chloroethane

p-chloro-m-Cresol

1,4-Dichlorobenzene

1,1-Dichloroethane

1,2-Dichloroethane

Ethylbenzene

Methyl Butyl Ketone

Methyl Ethyl Ketone

4-Methylphenol

Naphthalene

N-Nitrosodiphenylamine

Pentachlorophenol

Phenol

Concentration (mg/L) 

INORGANICS 

0.008 

0.002 

<0.1 

< 0.001 

0.007 

0.007 

0.04 

1.5 

0.005 

0.63 

< 0002 

0.003 

< 002 

< 0.01 

< 01 

0.3 

0.13 

0.55 

1.25 

12.1 

10.87 

0.05 

4500 

9.8 

73.2 

0.002 

12.09 

0.02 

0.05 

58 

ORGANICS 

2.8 

< 0.002 

0.02 

0.011 

< 0.001 

0.018 

< 0.005 

< 0.001 

< 0.005 

0.017 

0.028 

5.3 

0.065 

< 0.01 

0.011 

0.016 

0.008 

2.8 

0.031 

< 0.4 

0.011 

< 0.1 

0.018 

< 0.4 

0.052 

6.8 

0.54 

0.16 

29 

0.065 

<0.4 

0.011 

0.016 

2.9 

Average Concentration 

(mg/L) 

0.142 

0.042 

0.201 

0.03 

0.633 

0.395 

0.029 

33.8 

0.156 

13.224 

0.002 

0.55 

0.01 

0.019 

12.006 

2.8 

0.025 

0.19 

0.011 

0.021 

0.018 

0.101 

0.002 

1.136 

0.171 

0.094 

13.633 

0.065 

0.113 

0.011 

0.016 

1.06 

K-1
Pollutant Minimum Concentration 

(mg/L) 

Toluene 

Trichloroethene 

1,1,1-Trichloroethane 

2,4-Dimethyl Phenol 

Diethyl Phthalate 

Dimethyl Phthalate 

Di-N-Butyl Phthalate 

Vinyl Acetate 

Vinyl Chloride 

0.0082 

< 0.001 

0.011 

0.005 

0.11 

0.0049 

0.0044 

0.25 

< 0.002 

Maximum 

Concentration (mg/L) 

1.6 

< 0.1 

0.022 

< 0.4 

0.11 

0.0049 

0.0044 

0.25 

0.21 

Average Concentration 

(mg/L) 

0.735 

0.025 

0.019 

0.107 

0.11 

0.0049 

0.0044 

0.25 

0.067 

* Number of detections/number of observations could not be determined from data provided. 

Source: U.S. EPA’s Supplemental Manual on the Development and Implementation of Local Discharge 

Limitations Under the Pretreatment Programs, May 1991, pp. 1-30 and 1-31. “Pollutant levels 

reported below specified detection limit were considered in the data analysis and, for the purpose 

of statistical analysis, were considered to be equal to the detection limit.” 

Most Common Landfill Leachates* 

Pollutant Concentration Range 

(parts per million) 

INORGANICS** 

Arsenic 0.0002 - 0.982 

Barium 0.11 - 5 

Cadmium 0.007 - 0.15 

Chloride 31 - 5,475 

Chromium (Total) 0.0005 - 1.9 

Copper 0.03 - 2.8 

Iron 0.22 - 2,280 

Lead 0.005 - 1.6 

Manganese 0.03 - 79 

Nickel 0.02 - 2.2 

Nitrate 0.01 - 51 

Sodium 12 - 2,574 

Sulfate 8 - 1,400 

ORGANICS*** 

1,1-Dichloroethane 0.004 - 44 

Trans-1,2-Dichloroethylene 0.002 - 4.8 

Ethylbenzene 0.006 - 4.9 

Methylene Chloride 0.002 - 220 

Phenol 0.007 - 28.8 

Toluene 0.006 - 18 

K-2
* Leachate data is compiled from a database of 70 MSWLFs [U.S. EPA 1988. Summary of Data on 

Municipal Solid Waste Landfill Leachate Characteristics-Criteria for Municipal Solid Waste 

Landfills (40 CFR Part 258) - Subtitle D of Resource Conservation and Recovery Act 

(Background Document)]. Washington, DC: Office of Solid Waste. 

** Leachate data from 62 landfills. 

*** Leachate data from 53 landfills. 

Source: U.S. EPA’s National Pretreatment Program Report to Congress, July 1991, p. 3-81. 

Contaminant Concentration Ranges in Municipal Leachate 

Pollutant 

Parameter 

George 

(1972) 

Chain

/DeWalle 

(1977) 

BOD 

pH 

TSS 

9 - 54,610 

3.7 - 8.5 

6 - 2,685 

Alkalinity 0 - 20,850 

Bicarbonate 

Chlorides 

COD 

Fluorides 

Hardness 0 - 22,800 

NH3-Nitrogen 0 - 1,106 

NO 

-Nitrogen 

34 - 2,800 

0 - 89,520 

Organic 

Nitrogen 

OrthoPhosphorus 

Sulfates 

Sulfide 

TOC 

TDS 

Total-KNitrogen 

Total 

Phosphorus 

Total Solids 

0 - 1,300 

1 - 1,826 

0 - 42,276 

0 - 1,416 

1 - 154 

Aluminum 

Arsenic 

Barium 

Beryllium 

81 - 33,360 2,200 -

720,000 

3.7 - 8.5 3.7 - 8.5 

10 - 700 13 - 26,500 

Metry/ 

Cross 

(1977) 

CONVENTIONAL 

Cameron 

(1978) 

Wisconsin 

Report 

(20 Sites) 

Sobotka 

Report 

(44 Sites) 

9 - 55,000 ND - 195,000 7 - 21,600 

3.7 - 8.5 5 - 8.9 5.4 - 8.0 

2 - 140,900 28 - 2,835 

NON-CONVENTIONAL 

0 - 20,850 310 - 9,500 0 - 20,900 ND - 15,050 0 - 7,375 

3,260 - 5,730 

4.7 - 2,467 47 - 2,350 34 - 2,800 2 - 11,375 120 - 5,475 

40 - 89,520 800 -

750,000 

0 - 9,000 6.6 - 97,900 440 - 50,450 

0 - 2.13 0 - 0.74 0.12 - 0.790 

0 - 22,800 35 - 8,700 0 - 22,800 52 - 225,000 0.8 - 9,380 

0 - 1,106 0.2 - 845 0 - 1,106 11.3 - 1,200 

0.2 - 1,0.29 4.5 - 18 0 - 5,0.95 

2.4 - 550 4.5 - 78.2 

6.5 - 85 0.3 - 136 0 - 154 

1 - 1,558 20 - 1,370 0 - 1,826 ND - 1,850 8 - 500 

0 - 0.13 

256 - 28,000 ND - 30,500 5 - 6,884 

584 - 44,900 100 - 51,000 0 - 42,300 584 - 50,430 1,400 -

16,120 

2 - 3,320 47.3 - 938 

0 - 130 ND - 234 

0 - 59,200 1,900 -

25,873 

METALS 

0 - 122 ND - 85 0.010 - 5.07 

0 - 11.6 ND - 70.2 0 - 0.08 

0 - 5.4 ND - 12.5 0.01 - 10 

0 - 0.3 ND - 0.36 0.001 - 0.01 

K-3
Pollutant 

Parameter 

George 

(1972) 

Chain 

/DeWalle 

(1977) 

Metry/ 

Cross 

(1977) 

Cameron 

(1978) 

Wisconsin 

Report 

(20 Sites) 

Sobotka 

Report 

(44 Sites) 

Boron 0.3 - 73 0.867 - 13 

Cadmium 0.03 - 17 0 - 0.19 ND - 0.04 0 - 0.1 

Calcium 5 - 4,080 60 - 7,200 240 - 2,570 5 - 4,000 200 - 2,500 95.5 - 2,100 

Total 

Chromium 

0 - 33.4 ND - 5.6 0.001 - 1.0 

Copper 0 - 9.9 0 - 9.9 0 - 10 ND - 4.06 0.003 - 0.32 

Cyanide 0 - 0.11 ND - 6 0 - 4.0 

Iron 0.2 - 5,500 0 - 2,820 0.12 - 1,700 0.2 - 5,500 ND - 1,500 0.22 - 1,400 

Lead 0 - 0.5 <0.10 - 2.0 0 - 5.0 0 - 14.2 0.001 - 1.11 

Magnesium 16.5 - 15,600 17 - 15,600 64 - 547 16.5 - 15,600 ND - 780 76 - 927 

Manganese 0.06 - 1,400 0.09 - 125 13 0.06 - 1,400 ND - 31.1 0.03 - 43 

Mercury 0 - 0.064 ND - 0.01 0 - 0.02 

Molybdenum 0 - 0.52 0.01 - 1.43 

Nickel 0.01 - 0.8 ND - 7.5 0.01 - 1.25 

Potassium 2.8 - 3,770 28 - 3,770 28 - 3,800 2.8 - 3,770 ND - 2,800 30 - 1,375 

Sodium 0 - 7,700 0 - 7,700 85 - 3,800 0 - 7,700 12 - 6,010 

Titanium 0 - 5.0 <0.01 

Vanadium 0 - 1.4 0.01 

Zinc 0 - 1,000 0 - 370 0.03 - 135 0 - 1,000 ND - 731 0.01 - 67 

All concentrations in mg/L, except pH (standard units). 

ND = Non-detect 

Source: U.S. EPA’s Technical Development Document for Proposed Effluent Limitations Guidelines and 

Standards for the Landfills Point Source Category, EPA 821-R-97-022, January 1998, Table 6-3. 

* Literature sources were: 

George, J. A., Sanitary Landfill-Gas and Leachate Control, the National Perspective, Office of Solid 

Waste Management Programs, U.S. EPA, 1972. 

Chian, E. S., and F. B. DeWalle, Evaluation of Leachate Treatment, Volume I, Characterization of 

Leachate, EPA-600/2-77-186a. 

Metry, A. A., and F. L. Cross, Leachate Control and Treatment, Volume 7, Environmental Monograph 

Series, Technomic Publishing Co., Westport, CT, 1977. 

Cameron, R. D., The Effect of Solid Waste Landfill Leachates on Receiving Waters, Journal AWWA, 

March 1978. 

McGinley, Paul M., and Peter Met. Formation, Characteristics, Treatment and Disposal of Leachate from 

Municipal Solid Waste Landfills, Wisconsin Department of Natural Resources Special Report, August 1, 

1984. 

Sobotka & Co., Inc., Case History Data Compiled and Reported to the U.S. Environmental Protection 

Agency Economic Analysis Branch, Office of Solid Waste, 1986. 

K-4
APPENDIX L -

HAULED WASTE LOADINGS

Septage Hauler Monitoring Data 

Pollutant Number of 

Detections 

Number of 

Samples 

Minimum 

Concentration 

(mg/L) 

Maximum 

Concentration 

(mg/L) 

Average

Concentration

(mg/L) 

INORGANICS 

144 145 0 3.5 0.141 

128 128 0.002 202 5.758 

825 1097 0.005 8.1 0.097 

931 1019 0.01 34 0.49 

16 32 < 0.003 3.45 0.406 

963 971 0.01 260.9 4.835 

575 577 0.001 1.53 0.469 

464 464 0.2 2740 39.287 

962 1067 < 0.025 118 1.21 

5 5 0.55 17.05 6.088 

582 703 0.0001 0.742 0.005 

813 1030 0.01 37 0.526 

237 272 < 0.003 5 0.099 

11 25 < 015 1 0.076 

959 967 < 0.001 444 9.971 

Arsenic

Barium

Cadmium

Chromium (T)

Cobalt

Copper

Cyanide

Iron

Lead

Manganese

Mercury

Nickel

Silver

Tin

Zinc

COD

Acetone

Benzene

Ethylbenzene

Isopropyl Alcohol

Methyl Alcohol

Methyl Ethyl Ketone

Methylene Chloride

Toluene 

Xylene 

NONCONVENTIONALS 

ORGANICS 

183 510 

118 

112 

115 

117 

117 

115 

115 

113 

87 

118 0 

112 0.005 

115 0.005 

117 1 

117 1 

115 1 

115 0.005 

113 0.005 

87 0.005 

183 117500 21247.951 

210 

3.1 

1.7 

391 

396 

240 

2.2 

1.95 

0.72 

10.588 

0.062 

0.067 

14.055 

15.84 

3.65 

0.101 

0.17 

0.051 

Source: U.S. EPA’s Supplemental Manual on the Development and Implementation of Local Discharge 

Limitations Under the Pretreatment Programs, 21W-4002, May 1991, pp. 1-27 and 1-28. 

“Pollutant levels reported below specified detection limit were considered in the data analysis 

and, for the purpose of statistical analysis, were considered equal to the detection limit.” 

L-1
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L-2
APPENDIX M -

HAZARDOUS WASTE CONSTITUENTS - RCRA APPENDIX VIII

Constituent CAS No. Hazardous 

Waste No. 

A2213 30558-43-1 U394 

Acetonitrile 75-05-8 U003 

Acetophenone 98-86-2 U004 

2-Acetylaminefluarone 53-96-3 U005 

Acetyl chloride 75-36-5 U006 

1-Acetyl-2-thiourea 591-08-2 P002 

Acrolein 107-02-8 P003 

Acrylamide 79-06-1 U007 

Acrylonitrile 107-13-1 U009 

Aflatoxins 1402-68-2 -

Aldicarb 116-06-3 P070 

Aldicarb sulfone 1646-88-4 P203 

Aldrin 309-00-2 P004 

Allyl alcohol 107-18-6 P005 

Allyl chloride 107-18-6 -

Aluminum phosphide 20859-73-8 P006 

4-Aminobiphenyl 92-67-1 -

5-(Aminomethyl)-3-isoxazolol 2763-96-4 P007 

4-Aminopyridine 504-24-5 P008 

Amitrole 61-82-5 U011 

Ammonium vanadate 7803-55-6 P119 

Aniline 62-53-3 U012 

Antimony 7440-36-0 -

Antimony compounds, N.O.S. - -

Aramite 140-57-8 -

Arsenic 7440-38-2 -

Arsenic compounds, N.O.S. - -

Arsenic acid 7778-39-4 P010 

Arsenic pentoxide 1303-28-2 P011 

Arsenic trioxide 1327-53-3 P012 

Auramine 492-80-8 U014 

Azaserine 115-02-6 U015 

Barban 101-27-9 U280 

Barium 7440-39-3 -

Barium compounds, N.O.S. - -

Barium cyanide 542-62-1 P013 

Bendiocarb 22781-23-3 U278 

Bendiocarb phenol 22961-82-6 U364 

Benomyl 17804-35-2 U271 

Benz[c]acridine 225-51-4 U016 

Benz[a]anthracene 56-55-3 U018 

Benzal chloride 98-87-3 U017 

Benzene 71-43-2 U019 

Benzenearsonic acid 98-05-5 -

Benzidine 92-87-5 U021 

Benzo[b]fluoranthene 205-99-2 -

Benzo[j]fluoranthene 205-82-3 -

Benzo(k)fluoranthene 207-08-9 -

Benzo[a]pyrene 50-32-8 U022 

p-Benzoquinone 106-51-4 U197 

Benzotrichloride 98-07-7 U023 

Benzyl chloride 100-44-7 P028 

Beryllium powder 7440-41-7 P015 

Beryllium compounds, not otherwise specified (NOS) - -

M-1
Constituent CAS No. Hazardous 

Waste No. 

Bis(pentamethylene)-thiuram tetrasulfide 120-54-7 -

Bromoacetone 598-31-2 P017 

Bromoform 75-25-2 U225 

4-Bromophenyl phenyl ether 101-55-3 U030 

Brucine 357-57-3 P018 

Butyl benzyl phthalate

Butylate

Cacodylic acid

Cadmium

85-68-7 -

2008-41-5 -

75-60-5 U136 

7440-43-9 -

Cadmium compounds, NOS 

Calcium chromate 

-

13765-19-0 

-

U032 

Carbofuran 

Carbofuran phenol 

Carbon disulfide 

Carbon oxyfluoride 

Carbon tetrachloride 

Carbosulfan 

Chloral 

Calcium cyanide 

Carbaryl 

Carbendazim 

592-01-8 P021 

63-25-2 U279 

10605-21-7 U372 

1563-66-2 P127 

1563-38-8 U367 

75-15-0 P022 

353-50-4 U033 

56-23-5 U211 

55285-14-8 P189 

75-87-6 U034 

305-03-3 U035 

57-74-9 U036 

Chlorambucil 

Chlordane 

Chlordane (alpha and gamma isomers) 

Chlorinated benzenes, NOS 

- U036 

- -

Chlorinated ethane, NOS 

Chlorinated fluorocarbons, NOS 

-

-

-

-

Chlorobenzene 

Chlorobenzilate 

p-Chloro-m-cresol

2-Chloroethyl vinyl ether

Chloroform

Chloromethyl methyl ether

beta-Chloronaphthalene

o-Chlorophenol

1-(o-Chlorophenyl)thiourea

Chloroprene

3-Chloropropionitrile

Chromium

Chromium compounds, NOS

Chrysene

Citrus red No. 2

Coal tar creosote

Copper cyanide

Copper dimethyldithiocarbamate

Creosote

Cresol (Cresylic acid)

Crotonaldehyde

m-Cumenyl methylcarbamate 

Cyanides (soluble salts and complexes), NOS - P030 

Cyanogen 460-19-5 P031 

Cyanogen bromide 506-68-3 U246 

Cyanogen chloride 506-77-4 P033 

Chlorinated naphthalene, NOS 

Chlorinated phenol, NOS 

Chlornaphazin 

Chloroacetaldehyde 

Chloroalkyl ethers, NOS 

p-Chloroaniline 

- -

- -

494-03-1 U026 

107-20-0 P023 

- -

106-47-8 P024 

108-90-7 U037 

510-15-6 U038 

59-50-7 U039 

110-75-8 U042 

67-66-3 U044 

107-30-2 U046 

91-58-7 U047 

95-57-8 U048 

5344-82-1 P026 

126-99-8 -

542-76-7 P027 

7440-47-3 -

- -

218-01-9 U050 

6358-53-8 -

8007-45-2 -

544-92-3 P029 

137-29-1 -

- U051 

1319-77-3 U052 

4170-30-3 U053 

64-00-6 P202 

M-2
Constituent CAS No. Hazardous 

Waste No. 

Cycasin 14901-08-7 -

1134-23-2 -

131-89-5 P034 

50-18-0 U058 

94-75-7 U240 

Cycloate

2-Cyclohexyl-4,6-dinitrophenol

Cyclophosphamide

2,4-D

2,4-D, salts, esters 

Daunomycin 

Dazomet 

- U240 

20830-81-3 U059 

533-74-4 -

72-54-8 U060 

72-55-9 -

50-29-3 U061 

2303-16-4 U062 

226-36-8 -

DDD 

DDE 

DDT 

Diallate 

Dibenz[a,h]acridine 

Dibenz[a,j]acridine 

Dibenz[a,h]anthracene 

7H-Dibenzo[c,g]carbazole 

Dibenzo[a,e]pyrene 

Dibenzo[a,h]pyrene 

Dibenzo[a,i]pyrene 

1,2-Dibromo-3-chloropropane 

Dibutyl phthalate 

224-42-0 -

53-70-3 U063 

194-59-2 -

192-65-4 -

189-64-0 -

189-55-9 U064 

96-12-8 U066 

84-74-2 U069 

95-50-1 U070 

541-73-1 U071 

o-Dichlorobenzene 

m-Dichlorobenzene 

p-Dichlorobenzene 

Dichlorobenzene, NOS 

106-46-7 U072 

25321-22-6 -

3,3’-Dichlorobenzidine 

1,4-Dichloro-2-butene 

91-94-1 U073 

764-41-0 U074 

Dichlorodifluoromethane 

Dichloroethylene, NOS 

1,1-Dichloroethylene 

1,2-Dichloroethylene 

Dichloroethyl ether 

Dichloroisopropyl ether 

Dichloromethoxy ethane 

Dichloromethyl ether 

2,4-Dichlorophenol 

2,6-Dichlorophenol 

Dichlorophenylarsine 

Dichloropropane, NOS 

Dichloropropanol, NOS 

Dichloropropene, NOS 

1,3-Dichloropropene 

Dieldrin 

75-71-8 U075 

25323-30-2 -

75-35-4 U078 

156-60-5 U079 

111-44-4 U025 

108-60-1 U027 

111-91-1 U024 

542-88-1 P016 

120-83-2 U081 

87-65-0 U082 

696-28-6 P036 

26638-19-7 -

26545-73-3 -

26952-23-8 -

542-75-6 U084 

60-57-1 P037 

1,2:3,4-Diepoxybutane

Diethylarsine

Diethylene glycol, dicarbamate

1,4-Diethyleneoxide

Diethylhexyl phthalate

N,N'-Diethylhydrazine

O,O-Diethyl S-methyl dithiophosphate

Diethyl-p-nitrophenyl phosphate

Diethyl phthalate

O,O-Diethyl O-pyrazinyl phosphoro- thioate

Diethylstilbesterol

Dihydrosafrole

Diisopropylfluorophosphate (DFP)

Dimethoate

1464-53-5 U085 

692-42-2 P038 

5952-26-1 U395 

123-91-1 U108 

117-81-7 U028 

1615-80-1 U086 

3288-58-2 U087 

311-45-5 P041 

84-66-2 U088 

297-97-2 P040 

56-53-1 U089 

94-58-6 U090 

55-91-4 P043 

60-51-5 P044 

3,3'-Dimethoxybenzidine 119-90-4 U091 

p-Dimethylaminoazobenzene 60-11-7 U093 

M-3
Constituent CAS No. Hazardous 

Waste No. 

7,12-Dimethylbenz[a]anthracene 57-97-6 U094 

119-93-7 U095 

79-44-7 U097 

57-14-7 U098 

540-73-8 U099 

122-09-8 P046 

105-67-9 U101 

3,3'-Dimethylbenzidine

Dimethylcarbamoyl chloride

1,1-Dimethylhydrazine

1,2-Dimethylhydrazine

alpha,alpha-Dimethylphenethylamine

2,4-Dimethylphenol

Dimethyl phthalate

Dimethyl sulfate

131-11-3 U102 

77-78-1 U103 

644-64-4 P191 

25154-54-5 -

Dimetilan 

Dinitrobenzene, NOS 

4,6-Dinitro-o-cresol 

4,6-Dinitro-o-cresol salts 

534-52-1 P047 

- P047 

2,4-Dinitrophenol 

2,4-Dinitrotoluene 

51-28-5 P048 

121-14-2 U105 

2,6-Dinitrotoluene 

Dinoseb 

606-20-2 

88-85-7 

U106 

P020 

Di-n-octyl phthalate 

Diphenylamine 

1,2-Diphenylhydrazine 

Di-n-propylnitrosamine 

Disulfiram 

117-84-0 U017 

122-39-4 -

122-66-7 U109 

621-64-7 U111 

97-77-8 -

298-04-4 P039 

541-53-7 P049 

115-29-7 P050 

145-73-3 P088 

72-20-8 P051 

- P051 

106-89-8 U041 

Disulfoton 

Dithiobiuret 

Endosulfan 

Endothall 

Endrin 

Endrin metabolites 

Epichlorohydrin 

Epinephrine 

EPTC 

51-43-4 P042 

759-94-4 -

Fluoroacetic acid, sodium salt

Formaldehyde

Formetanate hydrochloride

Formic acid

Formparanate

Glycidylaldehyde

U238 

P101 

-

U114 

U114 

U067 

U077 

U359 

P054 

U115 

U116 

U076 

U118 

U119 

P097 

-

206-44-0 U120 

7782-41-4 P056 

640-19-7 P057 

62-74-8 P058 

50-00-0 U122 

23422-53-9 P198 

64-18-6 U123 

17702-57-7 P197 

765-34-4 U126 

Ethyl carbamate (urethane)

Ethyl cyanide

Ethyl Ziram

Ethylenebisdithiocarbamic acid

Ethylenebisdithiocarbamic acid, salts and esters

Ethylene dibromide

Ethylene dichloride

Ethylene glycol monoethyl ether

Ethyleneimine

Ethylene oxide

Ethylenethiourea

Ethylidene dichloride

Ethyl methacrylate

Ethyl methanesulfonate

Famphur

Ferbam

51-79-6 

107-12-0 

14324-55-1 

111-54-6 

-

106-93-4 

107-06-2 

110-80-5 

151-56-4 

75-21-8 

96-45-7 

75-34-3 

97-63-2 

62-50-0 

52-85-7 

14484-64-1 

Fluoranthene 

Fluorine 

Fluoroacetamide 

M-4
Constituent CAS No. Hazardous 

Waste No. 

Halomethanes, NOS - -

Heptachlor

Heptachlor epoxide

Heptachlor epoxide (alpha, beta, and gamma isomers)

Heptachlorodibenzofurans

Heptachlorodibenzo-p-dioxins

Hexachlorobenzene

76-44-8 P059 

1024-57-3 -

- -

- -

- -

118-74-1 U127 

Hexachlorobutadiene 

Hexachlorocyclopentadiene 

Hexachlorodibenzo-p-dioxins 

Hexachlorodibenzofurans 

87-68-3 U128 

77-47-4 U130 

- -

- -

Hexachloroethane 

Hexachlorophene

Hexachloropropene

Hexaethyl tetraphosphate

Hydrazine

Hydrogen cyanide

Hydrogen fluoride

Hydrogen sulfide

Indeno[1,2,3-cd]pyrene

3-Iodo-2-propynyl n-butylcarbamate

Isobutyl alcohol

Isodrin

67-72-1 U131 

70-30-4 U132 

1888-71-7 U243 

757-58-4 P062 

302-01-2 U133 

74-90-8 P063 

7664-39-3 U134 

7783-06-4 U135 

193-39-5 U137 

55406-53-6 -

78-83-1 U140 

465-73-6 P060 

119-38-0 P192 

120-58-1 U141 

Isolan 

Isosafrole 

Kepone 

Lasiocarpine 

Lead 

143-50-0 U142 

303-34-1 U143 

7439-92-1 -

- -

301-04-2 U144 

7446-27-7 U145 

1335-32-6 U146 

58-89-9 U129 

Lead compounds, NOS 

Lead acetate 

Lead phosphate 

Lead subacetate 

Lindane 

Maleic anhydride 

Maleic hydrazide 

Malononitrile 

108-31-6 U147 

123-33-1 U148 

109-77-3 U149 

Manganese dimethyldithiocarbamate 15339-36-3 P196

Melphalan

Mercury

Mercury compounds, NOS

Mercury fulminate

Metam Sodium

148-82-3 U150 

7439-97-6 U151 

- -

628-86-4 P065 

137-42-8 -

Methacrylonitrile 126-98-7 U152

Methapyrilene 

Methiocarb 

91-80-5 U155 

2032-65-7 P199 

Methomyl 

Methoxychlor 

Methyl bromide 74-83-9 U029 

Methyl chloride 74-87-3 U045 

Methyl chlorocarbonate 79-22-1 U156 

Methyl chloroform 71-55-6 U226 

3-Methylcholanthrene 56-49-5 U157 

4,4’-Methylenebis(2-chloroaniline) 101-14-4 U158 

Methylene bromide 74-95-3 U068 

Methylene chloride 75-09-2 U080 

Methyl ethyl ketone (MEK) 78-93-3 U159 

Methyl ethyl ketone peroxide 1338-23-4 U160 

Methyl hydrazine 60-34-4 P068 

Methyl iodide 74-88-4 U138 

16752-77-5 P066 

72-43-5 U247 

M-5
Constituent CAS No. Hazardous 

Waste No. 

Methyl isocyanate 624-83-9 P064 

75-86-5 P069 

80-62-6 U162 

66-27-3 -

298-00-0 P071 

56-04-2 U164 

1129-41-5 P190 

2-Methyllactonitrile 

Methyl methacrylate 

Methyl methanesulfonate 

Methyl parathion 

Methylthiouracil 

Metolcarb 

Mitomycin C 

MNNG 

315-18-4 P128 

50-07-7 U010 

70-25-7 U163 

2212-67-1 -

Mexacarbate 

Molinate 

Mustard gas 

Naphthalene 

1,4-Naphthoquinone 

alpha-Naphthylamine 

beta-Naphthylamine 

alpha-Naphthylthiourea 

Nickel 

505-60-2 -

91-20-3 U165 

130-15-4 U166 

134-32-7 U167 

91-59-8 U168 

86-88-4 P072 

7440-02-0 -

Nickel compounds, NOS - -

Nickel carbonyl

Nickel cyanide

Nicotine

13463-39-3 P073 

557-19-7 P074 

54-11-5 P075 

- P075 

10102-43-9 P076 

100-01-6 P077 

98-95-3 U169 

10102-44-0 P078 

Nicotine salts 

Nitric oxide 

p-Nitroaniline 

Nitrobenzene 

Nitrogen dioxide

Nitrogen mustard

Nitrogen mustard, hydrochloride salt

Nitrogen mustard N-oxide

Nitrogen mustard, N-oxide, hydro- chloride salt

Nitroglycerin

p-Nitrophenol

2-Nitropropane

Nitrosamines, NOS

51-75-2 -

- -

126-85-2 -

- -

55-63-0 P081 

100-02-7 U170 

79-46-9 U171 

35576-91-1D -

N-Nitrosodi-n-butylamine 

N-Nitrosodiethanolamine 

924-16-3 

1116-54-7 

U172 

U173 

N-Nitrosodiethylamine 

N-Nitrosodimethylamine 

N-Nitroso-N-ethylurea 

N-Nitrosomethylethylamine 

N-Nitroso-N-methylurea 

N-Nitroso-N-methylurethane 

N-Nitrosomethylvinylamine 

N-Nitrosomorpholine 

N-Nitrosonornicotine 

55-18-5 U174 

62-75-9 P082 

759-73-9 U176 

10595-95-6 -

684-93-5 U177 

615-53-2 U178 

4549-40-0 P084 

59-89-2 -

16543-55-8 -

N-Nitrosopiperidine 100-75-4 U179

N-Nitrosopyrrolidine 

N-Nitrososarcosine 

930-55-2 U180 

13256-22-9 -

Octamethylpyrophosphoramide 

Osmium tetroxide 

99-55-8 U181 

152-16-9 P085 

20816-12-0 P087 

23135-22-0 P194 

5-Nitro-o-toluidine 

Oxamyl 

Paraldehyde 

Parathion 

123-63-7 U182 

56-38-2 P089 

Pebulate 

Pentachlorobenzene 

1114-71-2 -

608-93-5 U183 

- -

- -

Pentachlorodibenzo-p-dioxins 

Pentachlorodibenzofurans 

M-6
Constituent CAS No. Hazardous 

Waste No. 

Pentachloroethane 76-01-7 U184 

Pentachloronitrobenzene (PCNB)

Pentachlorophenol

Phenacetin

82-68-8 U185 

87-86-5 F027 

62-44-2 U187 

Phenol 108-95-2 U188

Phenylenediamine

Phenylmercury acetate

Phenylthiourea

Phosgene

Phosphine

Phorate

25265-76-3 -

62-38-4 P092 

103-85-5 P093 

75-44-5 P095 

7803-51-2 P096 

298-02-2 P094 

Phthalic acid esters, NOS 

Phthalic anhydride 

Physostigmine 

Physostigmine salicylate 

2-Picoline 

- -

85-44-9 U190 

57-47-6 P204 

57-64-7 P188 

109-06-8 U191 

Polychlorinated biphenyls, NOS -

Potassium cyanide

Potassium dimethyldithiocarbamate

Potassium n-hydroxymethyl-n-methyl-dithiocarbamate

Potassium n-methyldithiocarbamate

151-50-8 P098 

128-03-0 -

51026-28-9 -

137-41-7 -

7778736 -

506-61-6 P099 

2631-37-0 P201 

23950-58-5 U192 

Potassium pentachlorophenate 

Potassium silver cyanide 

Promecarb 

Pronamide 

1,3-Propane sultone

n-Propylamine

Propargyl alcohol

Propham

Propoxur

Propylene dichloride

1,2-Propylenimine

Propylthiouracil

Prosulfocarb

1120-71-4 U193 

107-10-8 U194 

107-19-7 P102 

122-42-9 U373 

114-26-1 U411 

78-87-5 U083 

75-55-8 P067 

51-52-5 -

52888-80-9 U387 

Pyridine 110-86-1 U196

Reserpine 

Resorcinol 

50-55-5 U200 

108-46-3 U201 

Selenium compounds, NOS 

Selenium dioxide 

81-07-2 U202 

- U202 

94-59-7 U203 

7782-49-2 -

- -

7783-00-8 U204 

7488-56-4 U205 

144-34-3 -

630-10-4 P103 

7440-22-4 -

- -

506-64-9 P104 

Saccharin 

Saccharin salts 

Safrole 

Selenium 

Selenium sulfide 

Selenium, tetrakis(dimethyl-dithiocarbamate) 

Selenourea 

Silver 

Silver compounds, NOS

Silver cyanide

Silvex (2,4,5-TP)

Sodium cyanide

Sodium dibutyldithiocarbamate

Sodium diethyldithiocarbamate

Sodium dimethyldithiocarbamate

Sodium pentachlorophenate

Streptozotocin

Strychnine

93-72-1 F027 

143-33-9 P106 

136-30-1 -

148-18-5 -

128-04-1 -

131522 None 

18883-66-4 U206 

57-24-9 P108 

- P108 

95-06-7 -

Strychnine salts 

Sulfallate 

M-7
Constituent CAS No. Hazardous 

Waste No. 

TCDD 1746-01-6 -

Tetrabutylthiuram disulfide 

1,2,4,5-Tetrachlorobenzene 

1634-02-2 -

95-94-3 U207 

Tetrachlorodibenzo-p-dioxins 

Tetrachlorodibenzofurans 

-

-

-

-

Tetrachloroethane, NOS 

1,1,1,2-Tetrachloroethane 

25322-20-7 -

630-20-6 U208 

2,3,4,6-Tetrachlorophenol

2,3,4,6-tetrachlorophenol, potassium salt

2,3,4,6-tetrachlorophenol, sodium salt

Tetraethyldithiopyrophosphate

Tetraethyl lead

Tetraethyl pyrophosphate

Tetramethylthiuram monosulfide

Tetranitromethane

79-34-5 U209 

127-18-4 U210 

58-90-2 F027 

53535276 -

25567559 -

3689-24-5 P109 

78-00-2 P110 

107-49-3 P111 

97-74-5 -

509-14-8 P112 

7440-28-0 -

- -

1314-32-5 P113 

563-68-8 U214 

1,1,2,2-Tetrachloroethane 

Tetrachloroethylene 

Thallium 

Thallium compounds, NOS 

Thallic oxide 

Thallium(I) acetate 

Thallium(I) carbonate 

Thallium(I) chloride 

Thallium(I) nitrate 

Thallium selenite 

6533-73-9 U215 

7791-12-0 U216 

10102-45-1 U217 

12039-52-0 P114 

Thallium(I) sulfate 

Thioacetamide 

7446-18-6 

62-55-5 

P115 

U218 

59669-26-0 U410 

39196-18-4 P045 

74-93-1 U153 

23564-05-8 U409 

Thiodicarb 

Thiofanox 

Thiomethanol 

Thiophanate-methyl 

Thiophenol 

Thiosemicarbazide 

108-98-5 P014 

79-19-6 P116 

Thiourea 62-56-6 U219 

Thiram 137-26-8 U244 

Tirpate 26419-73-8 P185 

Toluene 108-88-3 U220 

Toluenediamine 25376-45-8 U221 

Toluene-2,4-diamine 95-80-7 -

Toluene-2,6-diamine 823-40-5 -

Toluene-3,4-diamine 496-72-0 -

Toluene diisocyanate 26471-62-5 U223 

o-Toluidine 95-53-4 U328 

o-Toluidine hydrochloride 636-21-5 U222 

p-Toluidine 106-49-0 U353 

Toxaphene 8001-35-2 P123 

Triallate 2303-17-5 U389 

2,4,6-Tribromophenol 118-79-6 U408 

1,2,4-Trichlorobenzene 120-82-1 -

1,1,2-Trichloroethane 79-00-5 U227 

Trichloroethylene 79-01-6 U228 

Trichloromethanethiol 75-70-7 P118 

Trichloromonofluoromethane 75-69-4 U121 

2,4,5-Trichlorophenol 95-95-4 F027 

2,4,6-Trichlorophenol 88-06-2 F027 

2,4,5-T 93-76-5 F027 

M-8
Constituent CAS No. Hazardous 

Waste No. 

Trichloropropane, NOS 25735-29-9 -

1,2,3-Trichloropropane 96-18-4 -

Triethylamine 121-44-8 U404 

O,O,O-Triethyl phosphorothioate 126-68-1 -

1,3,5-Trinitrobenzene 99-35-4 U234 

Tris(1-aziridinyl)phosphine sulfide 52-24-4 -

Tris(2,3-dibromopropyl) phosphate 126-72-7 U235 

Trypan blue 72-57-1 U236 

Uracil mustard 66-75-1 U237 

Vanadium pentoxide 1314-62-1 P120 

Vernolate 1929-77-7 -

Vinyl chloride 75-01-4 U043 

Warfarin, concentrations less than 0.3% 81-81-2 U248 

Warfarin, concentrations greater than 0.3% 81-81-2 P001 

Warfarin salts, when present at concentrations 

less than 0.3%. - U248 

Warfarin salts, when present at concentrations greater 

than 0.3%. - P001 

Zinc cyanide 557-21-1 P121 

Zinc phosphide, when present at concentrations greater 

than 10%. 1314-84-7 P122 

Zinc phosphide, when present at concentrations of 10% 

or less. 1314-84-7 U249 

Ziram 137-30-4 P205 

Source: 40 CFR Part 261, Subpart D and Appendix VIII - Hazardous Constituents. 

M-9
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M-10
APPENDIX N -

STATISTICAL APPROACH TO DETERMINING SAMPLING

FREQUENCY

The use of statistical analyses can help establish an acceptable minimum number of samples needed to 

adequately represent a population of pollutants influent and effluent at an acceptable confidence level. 

The procedure for establishing an acceptable minimum number of samples is calculated using the 

technique described in: Statistical Methods for Environmental Pollution Monitoring (Gilbert, 1987). This 

text is frequently cited in environmentally related statistical work. The method utilizes Equation 1 to 

calculate the sample size required to estimate the true mean of a population, based on the coefficient of 

variation, a confidence level, and a relative error. The method assumes a normal distribution of samples. 

n = (Z1-"/20/dr)

2 

Where:

n = Sample size required for estimating the true mean, :

Z1-"/2 = Normal deviate of desired confidence level

0 = Coefficient of variation

dr = Relative error

The coefficient of variation is determined by Equation 2. 

0 = s /0

Where: 

s = Standard deviation

0 = Mean

The sample standard deviation is determined by Equation 3. 

Eq. 1 

Eq. 2 

Eq. 3 

The mean and standard deviation used above should be taken from an acceptable past available sample. Both 

an acceptable confidence level and an acceptable relative error must be selected, each of which will vary 

depending on the type of pollutant being measured. Selection of both levels should be determined by the 

POTW based on the situation. The confidence level expresses the certainty of the estimated mean while the 

relative error indicates the accuracy of the estimated mean compared to the true mean. 

Table 1-1 is an example matrix which applies Equation 1 to calculate sample size. 

N-1
Table 1-1. 

Confidence 

Level 

(1-") 

0.80 

(Z0.90 = 1.28) 

Relative 

Error 

Sample Sizes Required for Estimating the True Mean 

Coefficient of Variation (0) 

0.10 0.30 0.50 1.00 1.50 2.00 

2 15 41 164 369 656 

0.90 

(Z0.975 = 1.645) 

1083 

7 

11 

(dr) 

0.10 

0.25 - 3 7 27 59 105 

0.50 - 1 2 7 15 27 

1 - - - 2 4 

0.10 3 25 68 271 609 

0.25 - 4 11 44 98 174 

0.50 - 1 3 11 25 44 

1 - - 1 3 7 

As shown in Table 1-1, establishing the number of samples needed to estimate the true mean is critically 

dependent on a data set’s coefficient of variation (CV). 

For example, a past, reliable sample produced a data set with standard deviation of 2 mg/L and a mean of 2 

mg/L, resulting in CV equal to one. If a confidence level of 0.80 (with a corresponding Z1-"/2 = 1.28) and a 

relative error of 0.25 are determined to be adequate, then Equation 1 is used as follows: 

n = (1.28 * 1 / .25)2

 = 26.21 

The sample size must then be rounded to the next whole number, in this case, 27. The 27 samples may be 

taken throughout the year if desired, or as determined by the POTW. In the case of taking the samples 

throughout the year, the POTW might take two samples per month and an additional three samples at random 

times during the year. One sample may be evaluated for multiple contaminants; however, each location 

would need to be sampled independently. 

Under these conditions, there would be 80% confidence that the estimated mean from 27 samples (as 

illustrated in Table 1-1) would be within + 25% of the true mean. Therefore, if the estimated mean is 4 mg/L, 

there would be 80% confidence that the true mean is within the interval of 3 to 5 (i.e., 4 + 1). If a confidence 

level of 0.90 and relative error of 0.10 were desired, the number of samples would increase substantially. 

Under these conditions, there would be 90% confidence that the estimated mean from 271 samples (as 

illustrated in Table 1-1) would be within + 10% of the true mean. Therefore, if the estimated mean was 2 

mg/L, there would be 90% confidence that the true mean was within the interval of 1.8 to 2.2 (i.e., 2 + 0.2). 

Source: SAIC. 1998. POTW Metals Analysis Project, Task 3 Deliverable to U.S. EPA Region VIII, EPA, 

Contract No. 68-C4-0068; Work Assignment Number PS-3-1, SAIC Project Number 01-0833-08-

2696-800, August 25, 1998. 

N-2
APPENDIX O -

MINIMIZING CONTAMINATION IN SAMPLES

Some of the data reported as below the detection level (BDL) may be the result of the POTW sampling 

techniques and chosen analytical methods. With the need to accurately detect trace levels of pollutants, 

POTWs should thoroughly examine potential sources of gross and trace contamination and select analytical 

methods that can detect very low levels of pollutants. EPA has established new performance based1

 sampling 

and analysis methods (1600 series) for measuring 13 toxic metals in the low ppt to ppb range. While these 

methods were developed for ambient water quality monitoring, POTWs may apply some of the concepts in 

Method 1669, Sampling Ambient Water for Determination of Metals at EPA Water Quality Criteria Levels, 

to improve the reliability of data collected, potentially even utilizing analytical methods 1631, 1632, 1636-40. 

Excerpts from Section 4.2.2 of Method 1669 are provided below. 

Minimizing Contamination: Sampling Location, Sampling Equipment and Materials, and Chemicals: 

C Where possible, limit exposure of the sample and equipment in areas of higher contamination, e.g., 

downwind from the sludge beds. 

C Minimize contact with airborne dust, dirt, particulate matter, or vapors from automobile exhaust; 

cigarette smoke; nearby corroded or rusted bridges, pipes, poles, or wires; nearby roads; and even 

human breath. Areas where nearby soil is bare and subject to wind erosion should be avoided. 

C Clean the sampling equipment and minimize the time between cleaning of equipment and use. 

C Use metal-free equipment, i.e., equipment should be nonmetallic and free of material that may 

contain metals of interest. When it is not possible to obtain equipment that is completely free of the 

metal(s) of interest, the sample should not come into direct contact with the equipment. 

C Do not use sampling equipment where there are indications that it may not be clean, e.g., sampler 

tubing or collection bottle is stained, has not been changed out in some time, was used to collected 

a sample of a slug load that hit the WWTP, etc. 

C Avoid contamination by carryover. Contamination may occur when a sample containing low 

concentrations of metals is processed immediately after a sample containing relatively high 

concentrations of these metals. 

C Where possible, do not collect, process, or ship samples containing high concentrations of metals 

(e.g., untreated effluents, in-process waters, landfill leachates) at the same time as samples being 

collected for trace metals determinations. 

C Wear clean, non-talc dusted gloves during all operations involving handling of equipment, samples, 

and blanks. Change gloves once they have become contaminated. 

1

An alternate procedure or technique may be used so long as neither samples nor blanks are contaminated when 

following alternate procedures. 

O-1
C Fluoropolymer (FEP, PTFE), 

conventional or linear 

polyethylene, polycarbonate, 

polysulfone, polypropylene, or 

ultrapure quartz are the 

preferred materials for coming 

in contact with samples. 

Fluoropolymer or glass 

containers are preferred for 

samples that will be analyzed 

for mercury because mercury 

vapors can diffuse in or out of 

other materials, resulting either 

in contamination or low-biased 

results. 

Lot Analyses of Metals in Different Grades of Nitric Acid 

(SOURCE-FISHER-INTERNET) 

Highest Grade Higher Grade High Grade 

Antimony <0.01 ppb <0.1 ppb 

Arsenic <0.1 ppb <0.3 ppb #4 ppb 

Cadmium <0.005 ppb <0.1 ppb 

Chromium <0.03 ppb #9 ppb #100 ppb 

Copper #0.05 ppb <1 ppb #50 ppb 

Lead #0.01 ppb <0.3 ppb #100 ppb 

Mercury <0.1 ppb <0.5 ppb 

Nickel #0.1 ppb <1 ppb #50 ppb 

Selenium <0.5 ppb 

Silver <0.005 ppb <0.1 ppb 

C The following materials have been found to contain trace metals: Pyrex, Kimax, methacrylate, 

polyvinyl chloride, nylon, Vycor, highly colored plastics, paper cap liners, pigments used to mark 

increments on plastics, and rubber. It is recommended that these materials not be used to hold 

liquids that come in contact with the sample or must not contact the sample. 

C Use an appropriate grade of chemicals when prepping equipment/materials and chemically 

preserving samples. 

Quality Control: 

C Serial numbers should be indelibly marked or etched on each piece of Apparatus so that 

contamination can be traced, and logbooks should be maintained to track the sample from the 

container through the sampling process to shipment to the laboratory. Chain-of-custody procedures 

should be used so that contamination can be traced to particular handling procedures or lab 

personnel. 

C Equipment blanks should be periodically generated and analyzed to identify contamination that may 

result from improper preparation or handling of sampling equipment and bottles in the laboratory. 

Equipment blanks include processing reagent water (i.e., water known not to contain pollutants at 

detectable levels) through sampling equipment and sample bottle(s) prior to taking the equipment 

or bottle(s) to the field. 

C A trip blank should be periodically generated and analyzed to identify incidental contamination that 

may occur to sampling equipment/bottles while in transit to and from the sampling location. 

Essential, reagent water is place in a sample bottle prior to going to the field. 

C Field blanks should be periodically generated and analyzed to identify contamination that may occur 

to sampling equipment/bottles while in the field. Like equipment blanks, it involves process reagent 

water through the sampling equipment/bottle. 

O-2
APPENDIX P -

METHODS FOR CALCULATING REMOVAL EFFICIENCY

There are three methods of calculating removal efficiencies: average daily removal efficiency (ADRE) 

method, mean removal efficiency (MRE) method, and the decile approach. 

ADRE across a plant is defined as: 

Where: 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

I n = POTW g/L 

Epotw, n = POTW 

n = Paired observations, numbered 1 to N 

As defined in Equation 5.2, the MRE across a plant is defined as: 

Where: 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

Ir = POTW g/L 

Epotw, t = POTW g/L 

t = Plant effluent samples, numbered 1 to T 

r = Plant influent samples, numbered 1 to R 

It is important to realize that the portion of the pollutant removed through a treatment process is transferred 

to another wastestream, typically the sludge. For conservative pollutants, such as metals, all the pollutant 

from the influent ends up in either the effluent or the sludge. ple, a 93% overall plant removal 

means that 93% of the cadmium in the influent is transferred to the sludge, while 7% remains in the effluent 

wastewater. 

1. REVIEW OF THE DATA SET AND EXCLUSION OF CERTAIN DATA 

A good first step in determining removal efficiencies is to review the data set. identify any 

data values that are extremely high or low. e isolated extreme values, there are formal statistical 

procedures that can be applied to evaluate whether a value can be classified as an “outlier” relative to the rest 

of the data set. ethods most widely used to make this determination are described in the following two 

paragraphs. 

If the data is known to closely follow a normal distribution, then any data point that lies more than two 

standard deviations from the mean is considered an outlier. Consider, for example, the DRE data values 

As defined in Equation 5.1, the 

influent pollutant concentration at headworks , m

effluent pollutant concentration 

influent pollutant concentration at headworks, m

effluent pollutant concentration, m

For exam

This review can 

If there ar

Two m

P-1
located in Table 1 of this appendix, and assume that this data is from a normal distribution. The 15 

observations have a mean of 52.69 and a standard deviation of 34.65. Using this method, any data point that 

lies outside of the range -16.61 to 121.99, or 52.69 ± 2*34.65, can be considered an outlier. In this case, one 

value, -20.25, falls outside of the range and can be determined to be an outlier. 

However, the DRE data values do not approximate a “bell-shaped” normal distribution. In this case, outliers 

can be determined based on the interquartile range (IQR) of the data set. First, order the data from smallest 

to largest and locate the data points that fall at the 25th percentile (also referred to as the first quartile or Q1), 

and the 75th percentile (also referred to as the third quartile or Q3). The IQR is equal to the value of the 

observation at Q3 minus the value of the observation at Q1. Any data point that lies more than 1.5 times this 

IQR below Q1, or above Q3, is considered an outlier. Again, consider the data in Table 1, but now make no 

assumptions about the distribution of the population from which the sample was taken. The Q1 and Q3 of 

this data set are located at 38.04 and 78.5 respectively. Based on these values, the IQR is equal to 40.46 (78.5 

- 38.04). Any value that falls below -22.65 (38.04 - 1.5*40.46), or above 139.19 (78.5 + 1.5*40.46), can be 

considered an outlier. In this case, there are no values that fall outside of the range and, consequently, no 

values should be determined to be outliers. 

Both of these methods are meant to determine any values that may be candidates for exclusion from the data 

set. Data exclusion should be performed only if technical justification exists to support such action (e.g., poor 

removals due to temporary maintenance or operational problems or known sampling problems). For 

example, if an examination of the data set shows that an unusually high influent value is from the same 

sampling day/event as an unusually high effluent value, this occurrence of corresponding extreme values 

should be investigated to determine if the data values can be explained by technical or operational problems 

not related to treatment system performance (e.g., maintenance, repair, or sampling problems). If this is the 

case, dropping the data pair from the data set may be appropriate. 

Review of the data may also show patterns such as increasing effluent values over time. If a similar pattern 

is not observed for the influent values, this will generate a pattern of decreasing DREs over time. A graph 

or plot of DRE against sampling day/event (in order from first to most recent sample) can help identify such 

trends. This may alert the POTW to operational problems that should be investigated. A plot can also 

highlight unusually low DREs that call for further review, such as checking laboratory quality control samples 

to determine if blank or duplicate samples indicate anything out of the ordinary. If abnormalities are found 

in laboratory QA/QC (quality assurance/quality control) data, the POTW may consider excluding the affected 

values from the data set. 

Table 1 contains an example data set of 15 influent and effluent sample pairs for zinc. The influent and 

effluent concentrations have been converted to loadings using the POTW flows for the sample days. The 

influent and effluent concentrations may be used instead of converting to loadings. Whether loadings or 

concentrations are used will likely have little impact on the results of the ADRE and decile approaches. 

Influent and effluent flows are probably similar (if not the same) for a data pair and therefore will have little 

effect on the relative size of the influent and effluent values, so DREs will change little. However, converting 

to loadings may have a noticeable impact on the MRE method if a POTW has high variability in its flows. 

Because influent and effluent loadings for high flow days will increase more relative to influent and effluent 

loadings for low flow days, the net effect is to give greater weight to the removal rates on those days with 

high flows. If the POTW has high variability in its flows, it should evaluate whether its removal rates tend 

to go up and down in relation to flow. If so, the POTW should consider calculating an MRE using both 

concentrations and loadings and evaluating which is more appropriate. 

P-2
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Table 1. Removal Efficiency Example 

Sample 

Day Date 

Influent Load 

(lbs/day) 

Effluent Load 

(lbs/day) 

DRE 

(%) 

3/4/99 518.22 111.41 78.50 

3/5/99 163.98 173.99 -6.10 

3/6/99 110.15 97.64 11.36 

3/7/99 1739.93 474.41 72.73 

3/8/99 266.48 320.45 -20.25 

4/15/99 170.48 105.15 38.32 

5/11/99 473.16 132.67 71.96 

5/12/99 314.19 148.96 52.59 

5/13/99 306.68 132.69 56.73 

5/14/99 232.57 92.63 60.17 

5/15/99 226.52 72.60 67.95 

6/15/99 533.25 98.87 81.46 

7/1/99 141.43 87.63 38.04 

7/15/99 1166.77 103.90 91.10 

8/1/99 2301.00 97.88 95.75 

Average 577.65 150.06 52.69 

Review of the data shows that: 

C The data set does not require removal of outliers. 

C The three particularly high influent values (sample days 4, 14, and 15) all have 

DREs of more than 70%, so the high influent values do not appear to make the data 

candidates for elimination. 

C There are two effluent values (sample days 4 and 5) that are significantly higher than 

the others. For one, the corresponding influent value is also high and the DRE is 

73%. For the other day, the DRE is negative (-20%) because the influent value is 

relatively low. These results are from samples taken on two consecutive days 

(March 7 and March 8), which may indicate that the POTW treatment system was 

experiencing some operational difficulties or interference at the time. The POTW 

should investigate the matter to determine if there are valid reasons for dropping 

these data from the removal calculations data set. 

C There are two negative DREs (one for March 8) calculated from the influent and 

effluent data pairs. They occurred three days apart and may indicate temporary 

operational problems, so the POTW should investigate the matter (as noted above). 

A plot of the data may help the POTW identify any data concerns that should be investigated. Based on the 

review of data for this example, it was determined that no justification exists for excluding any of the data 

from the data set. 

2. CALCULATION OF REMOVAL EFFICIENCIES 

Once the data set has been reviewed, the POTW can proceed to calculating removal efficiencies. The 

following sections describe each of the methods for calculating removal efficiencies and perform the 

calculations using the example data set in Table 1. 

P-3
2.1 Average Daily Removal Efficiency (ADRE) 

The ADRE is calculated by first calculating a DRE for each pair of influent and effluent values (i.e., an 

influent value and an effluent value from the same sampling day/event are used to calculate a DRE). This 

set of DREs is then averaged to determine the ADRE for a pollutant. Use of the ADRE method requires that 

a POTW only use data for the sampling days/events for which it has both an influent and an effluent value, 

and the influent value is greater than zero. 

Example 

For the example data set in Table 1, the ADRE is calculated as: 

ADRE = [78.5+(-6.1)+11.36+72.73+(-20.25)+38.32+71.96+52.59+56.73+60.17+67.95+81.46+38.04 

+91.10+95.75)]/15 = 52.69% 

2.2 Mean Removal Efficiency (MRE) 

The MRE is calculated by using the same formula as for the DRE (shown at the beginning of the Appendix), 

but instead of using individual influent and effluent values from sampling days/events, the set of influent 

values is first averaged to determine the average influent value and the same is done for the set of effluent 

values (either concentrations or loadings). These average values are then used in the DRE equation to result 

in the MRE for a pollutant. Unlike the ADRE method, the MRE method does not require paired influent and 

effluent values from the same sampling days/events. The MRE can be based on influent and effluent sample 

values that are not always paired (e.g., one effluent sample is lost or destroyed, so the influent average is 

based on one more value than the effluent average). However, the POTW should use caution in building the 

data sets for calculating influent and effluent averages because if too many unpaired values are used the 

removal efficiencies may be meaningless because the influent data and effluent data may represent different 

time periods, and treatment plant conditions do vary over time. 

Example 

For the example data set in Table 1, the MRE is calculated as: 

Average of the influent values = 577.65 lbs/day 

Average of the effluent values = 150.06 lbs/day 

MRE = 100*(577.65-150.06)/577.65 = 74.02% 

2.3 Comparison of Results from ADRE and MRE Methods 

Note that the MRE (74.02%) is higher than the ADRE (52.69%). The three days with the highest influent 

loadings have relatively high DREs and the two negative DREs (Day 2 and Day 5) occur on days with values 

that are not significantly greater than the other days. In the ADRE calculation, each day/DRE is given the 

same weight as the others, while the MRE method gives greater weight to the days with greater loadings. 

This means that the high removals on the days with high influent loadings affect the MRE more than the other 

days do, leading to a higher MRE, while the negative values do not have as great an impact because they 

occur on days with less elevated influent and effluent values If each DRE were to be weighted by its 

proportion of the total loading, the result would be the same as with the MRE method. 

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Usually, the MRE and ADRE are slightly different from each other, and can be quite different (as in the 

example presented here). The POTW can calculate both and decide if one of the estimates is the most 

appropriate for use in AHL calculations. The POTW can also use the decile approach to determine 

representative removal efficiencies. 

2.4 Decile Approach 

The decile approach, unlike the above methods, considers how often the actual DRE will be above or below 

a specified removal rate, thereby taking into account the variability of POTW removal efficiencies over time. 

The decile approach involves putting the set of DREs (calculated using the formula presented at the beginning 

of this appendix) in order from least to greatest and then determining nine decile values. Each decile is the 

value below which a certain percentage of the DREs fall. For example, the first decile is the value below 

which 10% of the DREs fall. Similarly, the second decile is the value below which 20% of the DREs fall, 

on up to the ninth decile, which is the value below which 90% of the DREs fall. The fifth decile is the median 

and half of the DREs fall below this number. To apply the decile approach, a minimum of nine DREs are 

required. If exactly nine DREs are available, the nine estimated deciles are simply the nine DREs. If more 

then nine DREs are used, the POTW needs to calculate the nine decile estimates. 

Tables 2 and 3 below illustrate use of the decile approach for the example zinc data set. The steps are: 

C Step 1: Take the set of DREs and put the values in order from smallest to largest (see Table 2). 

C Step 2: The entries for Column 1 are obtained by performing the two calculations. First, define the 

location for the first decile and then calculate the next eight multiples of that location value to 

determine the location for the second through ninth deciles. The first location is determined by the 

equation: (N+1)/10, where N = the number of data pairs/DREs used. For the example data set, N=15, 

so the location for the first decile is (15+1)/10 = 1.6. The location for the second decile is 2 x 1.6 = 

3.2, the location for the third decile is 3 x 1.6 = 4.8, and so on up to the ninth decile of 9 x 1.6 = 14.4. 

(Column 1 in Table 3) 

C Step 3: For each decile, take the whole number part of the value in Column 1 and place it in Column 

2 (e.g., the first decile is 1.6, so the whole number part is 1; the fourth decile is 6.4, so the whole 

number part is 6). 

C Step 4: The entries in Column 3 of Table 3 are taken from the ordered list of DREs in Table 2. The 

whole number values in Column 2 correspond to the entry in the ordered list in Table 2 [e.g., the 

whole number part for the first decile is 1, so entry 1 (-20.25%) from Table 2 is the correct value and 

is placed in Column 3 of Table 3; similarly, the fourth decile whole number part is 6, so value 6 

(52.59%) is placed in Column 3 of Table 3 for the fourth decile]. 

C Step 5: Following a similar procedure as in Step 4, values for Column 4 are taken from Table 2 and 

place in Table 3, except that this time the values taken from Table 2 are the ones that immediately 

follow the Column 3 entries [e.g., for the first decile, the value placed in Column 4 is -6.10, which 

is value 2 (the value immediately after value 1) from Table 2; for the fourth decile, the value placed 

in Column 4 is 56.73, which is value 7 from Table 2]. 

C Step 6: Fill in Column 5 by subtracting Column 3 from Column 4 and entering the result. 

C Step 7: Similar to the process for filling Column 2 (explained in Step 3) of Table 3, place the decimal 

part of the Column 1 entries in Column 6 of Table 3 (e.g., for the first decile, use 0.6; for the fourth 

decile, use 0.4). 

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C Step 8: Fill in Column 7 by multiplying the values in Column 5 by the values in Column 6 and 

entering the result. 

C Step 9: Add Column 3 and Column 7 and enter the result in Column 8 of Table 3. These values are 

the estimated deciles. 

Table 2. Set of DREs Sorted in Ascending Order 

1 3 10 11 12 13 14 15 

-20.25 -6.1 11.36 38.04 38.32 52.59 56.73 60.17 67.95 71.96 72.73 78.50 81.46 91.10 95.75 

2 4 5 6 7 8 9 

Table 3. Decile Approach for Zinc Example 

Deciles Column 1 Column 2 Column 3 Column 4 Column 5 Column 6 Column 7 Column 8 

1st 1.6 1 -20.25 -6.10 14.15 0.6 8.490 -11.76 

2nd 3.2 3 11.36 38.04 26.68 0.2 5.336 16.70 

3rd 4.8 4 38.04 38.32 0.28 0.8 0.224 38.26 

4th 6.4 6 52.59 56.73 4.14 0.4 1.656 54.25 

5th 8.0 8 60.17 67.95 7.78 0 0.000 60.17 

6th 9.6 9 67.95 71.96 4.01 0.6 2.406 70.36 

7th 11.2 11 72.73 78.50 5.77 0.2 1.154 73.88 

8th 12.8 12 78.50 81.46 2.96 0.8 2.368 80.87 

9th 14.4 14 91.10 95.75 4.65 0.4 1.860 92.96 

The main value of the decile approach is that it provides an estimate of how often a POTW is expected to 

exceed certain removal values, such as the ADRE and MRE. For the example, the ADRE is 53% and the 

MRE is calculated as 74%. If the POTW uses either one of these values, what amount of the time will its 

removal efficiency exceed those values? This can be estimated using the decile approach. The ADRE of 

53% falls between the third and fourth deciles (38.26% and 54.25%, respectively), meaning that the actual 

removal efficiency is estimated to exceed the ADRE 60% to 70% of the time [(e.g., the third decile means 

that 30% of the time values will fall below that value (38.26% in this case)]. The MRE of 74% lies between 

the seventh and eight deciles (73.88% and 80.87%, respectively), so the POTW is estimated to exceed the 

MRE 20% to 30% of the time. 

In developing local limits, appropriate removal efficiencies must be selected for calculation of AHLs for each 

pollutant. POTWs have often selected a pollutant’s ADRE for local limits calculations. EPA recommends 

that POTWs consider using the decile approach or the MRE method because they better account for 

variabilities in removal efficiencies over time. For example, because a higher removal efficiency means more 

pollutant is removed to the sludge, if the POTW used the ADRE from the above example (which is likely 

exceeded 60% to 70% of the time) to calculate an AHL to protect sludge quality, the resulting AHL may not 

be adequately protective. More pollutant will likely be removed to the sludge 60% to 70% of the time, so 

loadings in the sludge will higher than was estimated in the AHL calculations and may lead to exceedances 

of sludge disposal standards. 

A different approach that may address this concern is to use one decile for AHL calculations to protect sludge 

quality (for sludge disposal and for sludge digester inhibition for conservative pollutants) and a different 

decile for AHL calculations for protection against Pass Through concerns (e.g., NPDES permit limits). For 

example, a POTW can base its sludge quality-based AHLs on the seventh decile removal which means that 

greater removals to sludge and hence greater sludge loadings would be estimated to occur 30% of the time. 

P-6
Similarly, the POTW can use the third decile for calculating its water quality-based AHLs because lower 

removals (and hence higher effluent loadings) would be estimated to occur about 30% of the time. 

use of these deciles estimates that AHLs would be exceeded 30% of the time, in reality this is not highly 

likely. If the entire AHL is allocated to IUs, all IUs would have to discharge at their maximum allowed level 

to reach the AHL. the removal achieved is greater than the seventh decile, more loading would go 

to the sludge than is provided for with the AHL. me IUs discharge at below their allocated loadings, 

which is very likely at any given time, the likelihood of exceeding the allowed loading to the sludge is much 

lower. 

3. NON-CONSERVATIVE POLLUTANTS 

The above discussion of removal efficiency calculations applies to conservative pollutants (e.g., metals). 

However removal efficiencies for non-conservative pollutants can be used to calculate AHLs based on Pass 

Through criteria (e.g., biological process inhibition data, NPDES permit limits) and the guidance above can 

be used for non-conservative pollutants only in these cases. Conservative pollutant removal efficiencies are 

determined by pollutant concentrations in the POTW influent and effluent streams. ption applied 

to conservative pollutants (that removed pollutants are exclusively transferred to the POTW’s sludge streams) 

cannot be extended to non-conservative pollutants because losses through degradation and volatilization do 

not contribute to pollutant loadings in sludge. efore, non-conservative pollutant removal efficiencies 

cannot be used in deriving AHLs from criteria/standards applicable to the POTW’s sludge streams (e.g., 

digester inhibition, sludge disposal). 

Equation 5.13, -conservative pollutants, based on criteria for sludge digester 

inhibition, is: 

Where: 

AHLdgstr = AHL based on sludge digestion inhibition, lb/day 

Linfl = POTW influent loading, lb/day 

Cdgstinhib = Sludge digester inhibition criterion, mg/L 

Cdgstr = Existing pollutant level in sludge, mg/L 

The equation can be rewritten as: 

Where the factor Cdgstr/Linfl is a partitioning factor that relates the pollutant level in the POTW sludge, Cdgstr, 

to the headworks loading of the pollutant, Linfl. ation of an allowable 

loading based upon sludge digestion inhibition, AHLdgstr, from a sludge digester inhibition criteria, Cdgstinhib, 

for a non-conservative pollutant. ine the partitioning factor for a particular pollutant, the POTW’s 

influent and sludge must be routinely sampled for that pollutant. 

Although 

Then if 

If so

The presum

Ther

for calculating AHLs for non

The partitioning factor enables calcul

To determ

P-7
The factor Cdgstr/Linfl expresses non-conservative pollutant removals to sludge. Non-conservative pollutant 

removals to sludge are highly variable, and are dependent on such factors as wastewater temperature, ambient 

air temperature, biodegradation rates (which are temperature dependent), aeration rates, and POTW influent 

flow. Because non-conservative pollutant removals to sludge are highly variable, the variability in nonconservative pollutant sludge partitioning factors should be addressed in the local limits development process. 

The procedures and recommendations presented in this manual for addressing removal efficiency variability 

for conservative pollutants (e.g., the calculation of mean removals and the decile approach) can be extended 

to addressing variability in non-conservative pollutant sludge partitioning factors. In calculating sludge 

AHLs, the sludge partitioning factor should be used in place of the removal efficiency for non-conservative 

pollutants. 

P-8
APPENDIX Q -

METHODS FOR HANDLING DATA BELOW DETECTION LEVEL

The occurrence of values below the detection limit (DL) in environmental data sets is a major statistical 

complication. Uncertainty about the actual wastewater treatment plant influent and effluent values below the 

DL can bias subsequent statistical analyses to determine the removal efficiencies. 

The various approaches to handling below detection level (BDL) data can be broken into three main 

categories: 

C Regression order statistic (ROS) and probability plotting (MR) methods 

C Maximum likelihood estimation (MLE) methods 

C Simple replacement of a single value (e.g., detection limit or one half detection limit). 

Although this discussion focuses on handling data below the detection limit, the same techniques can be 

applied to those data below the minimum level of quantitation (ML) as well. These methods can be applied 

by those without a background in statistics. However, EPA strongly recommends a statistician perform these 

data manipulations. 

REGRESSION ORDER STATISTIC (ROS) AND PROBABILITY PLOTTING (MR) METHODS 

Both the original ROS and the MR methods are based on ordered statistics of observed data and the 

assumption that data come from a normal or log-normal distribution. If Y is from a normal distribution with 

mean : and standard deviation F (Y ~ N(:,F)) and Z is from a normal distribution with mean 0 and standard 

deviation 1 (Z ~ N(0, 1)), statistical theories show that Y = :+ F Z when Y and Z are at the same percentiles 

in their respective distributions. For a given observation (sampling result) Y that is above the detection limit, 

we can calculate the “order statistic”, i.e., the proportion of observations that are less than Y. This order 

statistic of Y is an estimate of the percentile. The corresponding Z value is available by either using existing 

computer program or checking the normal distribution table. In other words, we have a list of observations 

that are above the detection limit (Y1, Y2, ..., Ym) and a list of Z values (Z1, Z2, ..., Zm) that are of the same 

percentiles as the respective Y values. By performing a regression analysis of Y against Z, the resulting 

intercept and slope are estimates of the mean and standard deviation of the distribution of Y. 

When the data are from a log-normal

2 distribution, a log transformation is needed before the regression. The 

estimated mean and standard deviation is for the log-transformed variable. To convert the estimates to the 

original metric, the standard log-normal distribution results should be used. For example, if Y is from a lognormal distribution, and estimated mean and variance for log(Y) are : and F, the mean of Y is and the 

+  variance of Y is e2μ σ2 



 e

σ2 

− 1

 .  

Alternatively, one may use the regression equation to “fill in” the missing (BDL) values. This is possible 

because we can calculate the order statistics for all BDL values. For example, suppose we have 20 out of 100 

observations are BDL. The order statistics for the 20 BDL values are 0.01, 0.02, ..., 0.20. Using these order 

statistics, we can get the corresponding Z values Z1, Z2, ..., Z20. Substitute these Z values into the regression 

model, we have the 20 fill-in Y values. 

2

 Log-normal distributions are probability distributions which are closely related to normal distributions: if X is a 

normally distributed random variable, then exp(X) has a log-normal distribution. In other words: the natural logarithm of a 

log-normally distributed variable is normally distributed. 

Q-1 
To recap, we first define the variables used in this method: 

n = Total number of observations 

k = Number of BDL observations 

Yi

= Value of the ith ranked observation 

To utilize the ROS method, data are first ranked from smallest to largest so that Yn is the largest data value 

and Y1 through Yk are the unknown BDL values. If an approximately normal distribution is expected, each 

Yi

 is plotted on the y-axis against the expected normal order statistic Zi for each rank i. The following linear 

regression is used to obtain : and F, using only the points above the DL (i.e., i = k+1,...,n). 

Yi = :+ F Zi 

One may use the estimated intercept and slope as the mean and standard deviation. Alternatively, one may 

use the above equation to obtain appropriate “fill-in” values for each of the k BDLs using the Z-statistic. The 

mean and standard deviation are then calculated using traditional formulas applied to both the observed and 

filled-in data. Thus, the estimated data are based on the assumption of normality, while the observed data 

are used directly with no assumption about their distribution. This method is relatively robust to departures 

from normality or lognormality (Gilliom and Helsel 1986). 

If a distribution is expected to be skewed, then log(Yi

) is plotted against Zi and the fitted data and the observed 

data are transformed back to original units from which the mean and standard deviation are calculated 

(Gilliom and Helsel 1986). Transformation of the data, rather than the summary statistics, avoids inherent 

transformation bias (Helsel 1990). 

MR METHOD 

The MR method, an extension of the ROS method, accounts for multiple detection limits. When there is only 

one detection limit, the k-BDL values are assigned order statistics of 1 through k. When there are multiple 

detection limits, it is not obvious how to assign the order statistic for some of the data, both below or above 

some detection limits. For example, suppose we have the following five observations: <100, 110, <200, 250, 

and 300. It is obvious that the two largest observations, 250 and 300 should receive order statistics of 4 and 

5. But the rest is not clear, because the value labeled as <200 can be 199 or 9. Helsel and Cohn (1988) 

developed a plotting position method for assigning order statistics when there are multiple detection limits. 

The idea is that although we don’t know exactly where the value, say <200, should fall, we can lay out all 

possible positions for this particular value and take the average rank of all possible ranks. For example, the 

value labeled as <200 can be the smallest (rank 1), the second smallest (rank 2), or the third smallest (rank 

3), the average rank is (1+2+3)/3 = 2. The value 110 can be the second smallest or the third smallest, 

therefore a rank of (2+3)/2 = 2.5. Finally, the observation <100 receives a rank of (1+2)/2=1.5. Once the 

order statistics are assigned, one may use the same regression analysis method in the ROS method. When 

there is only one detection limit, the MR method is the same as the ROS method. 

Helsel and Cohn (1988) found that if a single estimating method for several descriptive statistics is desired 

and the sampling distribution of a data set is unknown, the MR method should be utilized. The actual plotting 

procedure for the MR method is detailed in Appendix B of Estimation of Descriptive Statistics for Multiple 

Censored Water Quality Data (Helsel and Cohn, 1988). 

Q-2
MAXIMUM LIKELIHOOD ESTIMATION (MLE) METHOD 

The MLE method is based on a specific probabilistic assumption about the observations. For example, 

suppose the data we observed (Y1, Y2, ..., Yn) are from a normal distribution with unknown mean and standard 

deviation. The likelihood of observing a specific value, say Yi

, is calculated by the normal distribution density 

function: 

(Yi −μ )

2 

( ) = 

2πσ 

1 

e 

− 2σ2

L Yi 

The likelihood for a BDL value is: 

  2 

e 

− 1 

2

2 2 

πσ 

σ

 X − μ 



DL

L Y( ) = ∫ dX k −∞ 

The likelihood of observing all the data (Y1, Y2, ..., Yn), both below and above the detection limit is the product 

of all individual likelihoods. The likelihood of observing all data is a very complicated function of : and F. 

A different set of : and F values will lead to a different likelihood value. The maximum likelihood estimator 

is the pair of : and F values that maximize the likelihood function. Because the likelihood function is often 

very complicated, computation of the MLE method is difficult. 

Gilliom and Helsel (1986) found that the ROS and the MR methods appear to be more robust to departures 

from distributional assumptions. 

MLE methods have been shown to have the smallest mean-squared error (i.e., higher accuracy) of available 

techniques when the data distribution is exactly normal or lognormal (Harter and Moore 1966). However, 

simulation results indicate that ROS and MR methods are superior when distribution shape population is 

unknown (Gilliom and Helsel 1986). 

In a simulation study by Newman et al. (1989) comparing mean and standard deviation estimates between 

MLE and ROS, the results were similar. However, the MLE method provided slightly more accurate results 

when BDL values comprised less than 30 percent of the data set, while ROS methods provided slightly more 

accurate results when BDL values represented 30 percent or more. 

SIMPLE SUBSTITUTION METHODS 

Simple substitution methods simply replace the below detection value with another value, such as zero, the 

detection limit, or one-half the detection limit. Both ROS and MLE methods offer substantial advantages 

over most simple replacement methods (Gilbert 1987, Gleit 1985, Helsel and Gilliom 1986, Newman et 

al.1989). 

In general, replacement methods result in a greater bias when calculating the mean or standard deviation. 

Additionally, their relative performance worsens as the proportion of BDLs increases (Gilliom and Helsel 

1986). Helsel (1989) reasons that because large differences may occur in the resulting estimates for any given 

population, and because the choice of the replacement value is essentially arbitrary without some knowledge 

of instrument readings below the reporting limit, estimates resulting from simple substitution are not 

defensible. 

Q-3
CONCLUSION 

The MR method is most applicable for use in local limits development because of the data set’s multiple 

detection limits and unknown parent distribution. Additionally, the MR method is recommended when the 

data set contains a relatively high percentage of BDL values. 

Further information on statistical methods can be found in the literature listed below. 

LITERATURE REVIEW LIST/REFERENCES 

Gilliom and Helsel 1986. Estimation of distribution parameters for censored trace level water quality data: 

1 Estimation techniques. Water Resources Research 22:135-146. 

Gleit 1985. Estimation for small normal data sets with detection limits. Environmental Science Technology 

19:1201-1206. 

Harter and Moore 1966. Local-Maximum-Likelihood estimation of the parameters of three-parameter 

lognormal populations from complete and censored samples. Journal of American Statistical Association 

61:842-851. 

Helsel, D. R. 1990. Less Than Obvious: Statistical treatment of data below the detection limit. 

Environmental Science and Technology 24:1766-1774. 

Helsel and Cohn 1988. Estimation of Descriptive Statistics for Multiple Censored Water Quality Data. 

Water Resources Research 24:1997-2004. 

Newman, Dixon, Looney, and Pinder 1989. Estimating the mean and variance for environmental samples 

with below detection limit observations. Water Resources Bulletin 25:905-916. 

Porter, Ward, and Bell 1988. The Detection Limit: Water quality monitoring data are plagued with levels 

of chemicals that are too low to be measured precisely. Environmental Science Technology Vol. 22, No. 8. 

Travis and Land. 1990. Estimating the Mean of Data Sets with Nondetectable Values. Environmental 

Science Technology Vol. 24, No. 7. 

Q-4
ATTACHMENT - DESCRIPTION OF THE MR METHOD 

Method: 

(1) If an analytical result is reported as ND (to be referred to as a nondetect), set the result ci

 = 1. 

Annotate the result with a “<” and consider this observation to be “< a detection limit.” 

(2) Divide the observations into two groups: Nondetects, those observations annotated with a “<” sign, 

and detects. 

(3) Let m = number of distinct detection limits. 

(4) Let Aj

 = number of detected observations at or above the jth detection limit (j = 1,...,m) and below 

the next highest detection limit. 

(5) Let Bj

 = number of detected and nondetected observations below the jth detection limit (j = 1,...,m). 

(6) Let pe,j = pe,j+1 + (Aj

/[Aj + Bj])(1 - pe,j+1), and solve iteratively for j = m,m-1,...,2,1. By convention, 

pe,m+1 = 0. 

(7) Determine plotting positions, p(i), for detected observations as: 

p(i) = (1 - pe,j) + (pe,j - pe,j+1)@r/(Aj

 + 1), where r is the rank of the ith observation above the jth 

detection limit. If detected observations are “tied,” arbitrarily order the “tied” observations before 

assigning ranks. Whether the “tied” observations are arbitrarily ordered or assigned the same midrank (average of the corresponding ranks) is expected to be of negligible importance. If detected 

observations are present below the lowest detection limit, assume the “0th detection limit” is 0, and 

consequently pe,0 = 1. 

(8) Assign plotting positions, pc(i), for nondetected observations as: 

pc(i) = (1- pe,j)@r/(Cj

 + 1), r = 1,...,Cj. Cj is the number of nondetected values known only to be less 

than the jth detection limit (j = 1,...m). The formula for Cj

 is: Cj = Bj - (Aj-1 + Bj-1), where A0 = B0 

= 0. Plotting positions are therefore assigned separately within the j groups of nondetects (j=1,...,m). 

(9) Perform a simple linear regression using only the detected observations. The natural logarithm of 

the detected observations (zi

 = ln(yi)) is the dependent variable, and the normal quantile associated 

with the corresponding plotting position (M-1(p(i))) is the independent variable, where M-1(@) is the 

normal quantile. 

^ ^ ^ (10) Use the estimated regression line (zi

 = b0 + b1@M-1(pc(i))) to “fill in” (using the terminology of Helsel 

and Cohn) estimated natural logarithm values for nondetected observations, based on the normal 

quantile associated with the calculated plotting position (pc(i)). 

(11) Calculate a natural log mean (:^) and log standard deviation (F^) of the detected and “filled in” 

observations using the formulas below. Assume zi

 = ln(yi), where zi represents the natural logarithm 

of detected observations where available, and "filled in" estimated natural logarithm values where 

nondetects were observed. 

Q-5
(1)

(2) 

(12) Use the values of :

^ and F^ to estimate a 90th percentile using a lognormal distribution: 90 = exp (:^ 

+ 1.282@F

^ ). 

An example of the MR method is given below. 

Comments: 

Although the algorithm for determining plotting positions when multiple detection limits are present 

appears rather cumbersome, as described in the 12-step process above, the process of fitting a regression line 

to order statistics is well-established as a method for determining parameters of a distribution. 

method utilizes plotting positions to “spread” nondetected observations along a continuum, rather than simply 

substituting an arbitrary value for each nondetected measurement. 

values to be “spread out” rather than all fixed at a single point, as would be the case with simple substitution 

methods. 

The MR method described above directly mimics the methods of Helsel and Cohn. 

article by Helsel and Cohn contains an inaccurate formula for Cj

, which has been revised above. 

the article did not address ties in detected observations and detected observations below the lowest detection 

limit. 

At least two detected observations are necessary to estimate a regression line. , this 

procedure is not useful when 0 or only 1 detected observation is present. 

Software which utilizes the MR method to compute summary statistics is available. The feasibility 

of utilizing the software available at this site for implementation among numerous POTWs must be explored 

further. For example, the software is restrictive in some ways, such as the format of data which can be 

processed. 

Reference: 

Helsel, D.R., and T.A. Cohn. Estimation of Descriptive Statistics for Multiple Censored Water Quality 

Data. Water Resources Research 24:1997-2004. 

P

The ROS 

In practice, one would expect nondetected 

However, the 

In addition, 

These questions have been addressed in Steps 7 and 9 above. 

Consequently

1988. 

Q-6
EXAMPLE OF THE MR METHOD 

Suppose we have a set of data from multiple sources with varying detection limits. When combined, the data 

set is ordered as follow: 

Data Summary 

<50 <200 <400 100 300 500 

<50 <200 <400 100 300 500 

<50 <200 <400 700 

1000 

1200 

In order to provide estimates of the mean and standard deviation, it is necessary to fill-in the non-detected 

values. Once the non-detected values are filled-in, sample mean and standard deviation can be estimated. The 

following are the MR steps for filling in the nondetected values. 

1. Summary statistics: 

n = 18

m = 3 (1st detection limit = 50, 2nd detection limit = 200, 3rd detection limit = 400)

A1 = 2 (2 detects $50 but <200)

A2 = 2 (2 detects $200 but <400)

A3 = 5 (5 detects $400)

B1 = 3 (3 nondetects <50)

B2 = 8 (3 nondetects <50, 3 nondetects <200, and 2 detects <200)

B3 = 13 (3 nondetects <50, 3 nondetects <200, 3 nondetects <400, 2 detects <200, and 2 detects <400)

C1 = 3 (3 nondetects <50)

C2 = 3 (3 nondetects <200)

C3 = 3 (3 nondetects <400)

pe,3 = pe,4 + (A3/[A3 + B3])(1 - pe,4) = 0 + (5/[5+13])@1 = 0.278

pe,2 = pe,3 + (A2/[A2 + B2])(1 - pe,3) = 0.278 + (2/[2+8])@(1-0.278) = 0.422

pe,1 = pe,2 + (A1/[A1 + B1])(1 - pe,2) = 0.422 + (2/[2+3])@(1 - 0.422) = 0.653

Q-7
-----------------------------------------------------------------------------------------------------------------

------------------------------------------------------------------------------------------------------------------

-----------------------------------------------------------------------------------

 2. Determination of plotting positions: 

Nondetected observations: 

Plotting Position 

xi j r pe,j Cj pc(i) = (1- pe,j)@r/(Cj + 1) 

<50 1 1 0.653 3 0.087 

<50 1 2 0.653 3 0.173 

<50 1 3 0.653 3 0.260 

<200 2 1 0.422 3 0.144 

<200 2 2 0.422 3 0.289 

<200 2 3 0.422 3 0.433 

<400 3 1 0.278 3 0.181 

<400 3 2 0.278 3 0.361 

<400 3 3 0.278 3 0.542 

Detected observations: 

Plotting Position 

xi j r pe,j pe,j+1 Aj p(i) = (1 - pe,j) + (pe,j - pe,j+1)@r/(Aj

 + 1) 

100 1 1 0.653 0.422 2 0.424 

100 1 2 0.653 0.422 2 0.500 

300 2 1 0.422 0.278 2 0.626 

300 2 2 0.422 0.278 2 0.674 

500 3 1 0.278 0 5 0.769 

500 3 2 0.278 0 5 0.815 

700 3 3 0.278 0 5 0.861 

1000 3 4 0.278 0 5 0.907 

1200 3 5 0.278 0 5 0.954 

3. Linear regression 

A simple linear regression is then performed using the following detected observations and their 

associated plotting points. The regression is based on zi as the dependent variable and p(i) as the independent 

variable. 

xi zi

 = ln(xi) p(i) M-1(p(i)) 

100 4.605 

100 4.605 

300 5.704 

300 5.704 

500 6.215 

500 6.215 

700 6.551 

1000 6.908 

1200 7.090 

0.424 -0.192 

0.500 0.000 

0.626 0.321 

0.674 0.451 

0.769 0.736 

0.815 0.896 

0.861 1.085 

0.907 1.323 

0.954 1.685 

Q-8
------------------------------------------------------------------------

The regression equation based on these nine detected observations is: 

^ zi

 = 4.9614 + 1.4186@M-1(p(i)) 

4. Fill-in 

This equation is used to “fill in” estimated nondetect values for the nine nondetects above. The results of the 

calculation are shown below: 

^ pc(i) M-1(pc(i)) zi 

<50 0.087 

<50 0.173 

<50 0.260 

<200 0.144 

<200 0.289 

<200 0.433 

<400 0.181 

<400 0.361 

<400 0.542 

-1.360 3.032 

-0.942 3.625 

-0.643 4.049 

-1.063 3.453 

-0.556 4.173 

-0.169 4.722 

-0.912 3.668 

-0.356 4.456 

0.106 5.112 

^ The z ^ 2 are shown below: 

4.605 5.704 6.551 3.032 3.453 3.668 

4.605 6.215 6.908 3.625 4.173 4.456 

5.704 6.215 7.090 4.049 4.722 5.112 

i

 and the zi from the two tables above are then combined to estimate a natural log mean and a log ^ standard deviation. The data and calculated values for : and F

^ : = 4.9937 ^ F

^ 2 = 1.5632 (F = 1.2503) 

^ ^ The calculated values for : and F can then be used for estimating the arithmetic mean of the sample: m = exp( 

^

: + 0.5 F

^ 2) = 322.241 and sample standard deviation s = m eσ$2 

− 1 = 626.168. In some instances, one may ^ be interested in the 90th percentile of the data, which can be estimated as P90 = exp (: + 1.282@F

^ ) = 732.585. 

It is worthwhile to note that these calculations are based on the assumption that the data follow a log-normal 

distribution. For most water quality related variables, such as BOD concentration, the log-normal distribution 

is appropriate. However, when percent removal is the variable of concern, log-normal is no longer an 

appropriate probability distribution. Instead, one may apply the MR method to the concentration variables 

first and calculate the percent removal after the non-detected concentration values have been filled-in. 

Q-9

xi 
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Q-10
APPENDIX R -

PRIORITY POLLUTANT REMOVAL EFFICIENCIES

Priority Pollutant Removal Efficiencies (%) Through Primary Treatment* 

Priority Pollutant Median Number of POTWs with 

Removal Data** 

METAL/NONMETAL INORGANICS 

Cadmium 15 6 of 40 

Chromium 27 12 of 40 

Copper 22 12 of 40 

Cyanide 27 12 of 40 

Lead 57 1 of 40 

Mercury 10 8 of 40 

Nickel 14 9 of 40 

Silver 20 4 of 40 

Zinc 27 12 of 40 

ORGANICS 

Benzene 25 8 of 40 

Chloroform 14 11 of 40 

1,2-trans-Dichloroethylene 36 9 of 40 

Ethylbenzene 13 12 of 40 

Naphthalene 44 4 of 40 

Phenol 8 11 of 40 

Butyl benzyl phthalate 62 4 of 40 

Di-n-butyl phthalate 36 3 of 40 

Diethyl phthalate 56 1 of 40 

Tetrachloroethylene 4 12 of 40 

1,1,1-Trichloroethane 40 10 of 40 

Trichloroethylene 20 12 of 40 

* Pollutant removals between POTW influent and primary effluent. From Fate of Priority Pollutants 

in Publicly Owned Treatment Works, Volume I (EPA 440/1-82/303), U.S. Environmental Protection 

Agency, Washington, D.C., September 1982, p. 61. 

** Median removal efficiencies from a data base of removal efficiencies for 40 POTWs. Only POTWs 

with average influent concentrations exceeding three times each pollutant’s detection limit were 

considered. 

Source: U.S. EPA’s Guidance Manual on the Development and Implementation of Local Discharger 

Limitations Under the Pretreatment Program, December 1987, p. 3-55. 

R-1
Priority Pollutant Percent Removal Efficiencies (%) Through Activated Sludge Treatment* 

Priority Pollutant Range 

METALS/NONMETAL INORGANICS** 

Arsenic 11-78 

Cadmium 25-99 

Chromium 25-97 

Copper 2-99 

Cyanide 3-99 

Lead 1-92 

Mercury 1-95 

Nickel 2-99 

Selenium 25-89 

Silver 17-95 

Zinc 23-99 

31 

33 

68 

67 

41 

39 

50 

25 

33 

50 

64 

ORGANICS** 

44 

50 

50 

50 

67 

36 

40 

37 

75 

47 

50 

39 

39 

76 

50 

80 

75 

75 

67 91 

80 96 

67 83 

67 91 

86 97 

62 77 

78 90 

68 86 

90 98 

72 87 

67 92 

64 87 

62 90 

86 95 

80 93 

93 98 

85 94 

89 98 

Anthracene 29-99 

Benzene 25-99 

Chloroform 17-99 

1,2-trans-Dichloroethylene 17-99 

Ethylbenzene 25-99 

Methylene chloride 2-99 

Naphthalene 25-98 

Phenanthrene 29-99 

Phenol 3-99 

Bis (2-ethylhexyl) phthalate 17-99 

Butyl benzyl phthalate 25-99 

Di-n-butyl phthalate 11-97 

Diethyl phthalate 17-98 

Pyrene 73-95 

Tetrachloroethylene 15-99 

Toluene 25-99 

1,1,1-Trichloroethane 18-99 

Trichloroethylene 20-99 

Second 

Decile Median Eight 

Decile 

Number of POTWs 

with Removal Data 

45 53 5 of 26 

67 91 19 of 26 

82 91 25 of 26 

86 95 26 of 26 

69 84 25 of 26 

61 76 23 of 26 

60 79 20 of 26 

42 62 23 of 26 

50 67 4 of 26 

75 88 24 of 26 

79 88 26 of 26 

5 of 26

18 of 26

24 of 26

17 of 26

25 of 26

26 of 26

16 of 26

6 of 26

19 of 26

25 of 26

16 of 26

19 of 26

15 of 26

2 of 26

26 of 26

26 of 26

23 of 26 

25 of 26 

* Pollutant removals between POTW influent and secondary effluent (including secondary clarification).

Based on a computer analysis of POTW removal efficiency data (derived from actual POTW influent and 

effluent sampling data) provided in U.S. EPA’s Fate of Priority Pollutants in Publicly Owned Treatment

Works, Volume II (EPA 440/1-82/303), September 1982. 

** For the purpose of deriving removal efficiencies, effluent levels reported as below detection were set equal

to the reported detection limits. All secondary activated sludge treatment plants sampled as part of the 

study were considered. 

Source: U.S. EPA’s Guidance Manual on the Development and Implementation of Local Discharger Limitations 

Under the Pretreatment Program, December 1987, p. 3-56. 

R-2
Priority Pollutant Removal Efficiencies (%) Through Trickling Filter Treatment* 

Priority Pollutant 

Cadmium

Chromium

Copper

Cyanide

Lead

Mercury

Nickel

Silver

Zinc

Benzene

Chloroform

1,2-trans-Dichloroethylene

Ethylbenzene

Methylene chloride

Naphthalene

Phenol

Bis (2-ethylhexyl) phthalate

Butyl benzyl phthalate

Di-n-butyl phthalate

Diethyl phthalate

Tetrachloroethylene

Toluene

1,1,1-Trichloroethane 

Trichloroethylene 

Range Second 

Decile Median Eighth 

Decile 

Number of POTWs 

with Removal Data 

METALS/NONMETAL INORGANICS** 

93 6 of 11 

71 9 of 11 

89 9 of 11 

79 8 of 11 

70 6 of 11 

62 9 of 11 

7 9 f 1 o 1

86 8 of 11 

81 9 of 11 

5

33-96 

5-92 

12-97 

7-88 

4-84 

14-80 

7-72 

11-93 

14-90 

33 68 

34 55 

32 61 

33 59 

25 55 

33 50 

1 9 

38 66 

34 67 

1 2

ORGANICS** 

5-98 

21-94 

14-99 

45-97 

5-98 

33-93 

50-99 

4-98 

25-90 

29-97 

17-75 

26-99 

17-99 

23-99 

50-99 

50 75 

50 73 

50 50 

50 80 

28 70 

40 71 

75 84 

21 58 

37 60 

41 60 

40 57 

53 80 

80 93 

75 89 

67 94 

93 7 of 11 

84 9 of 11 

96 7 of 11 

91 10 of 11 

85 10 of 11 

87 6 of 11 

96 8 of 11 

81 10 of 11 

77 9 of 11 

82 10 of 11 

67 8 of 11 

93 10 of 11 

97 10 of 11 

97 10 of 11 

98 10 of 11 

* Pollutant removals between POTW influent and secondary effluent (including secondary clarification). 

Based on a computer analysis of POTW removal efficiency data (derived from actual POTW influent and 

effluent sampling data) provided in U.S EPA’s Fate of Priority Pollutants in Publicly Owned Treatment 

Works, Volume II, (EPA 440/182/303), September 1982. 

** For the purpose of deriving removal efficiencies, effluent levels reported as below detection were set 

equal to the reported detection limits. All secondary trickling filter plants sampled as part of the study 

were considered. 

Source: U.S. EPA’s Guidance Manual on the Development and Implementation of Local Discharger 

Limitations Under the Pretreatment Program, December 1987, p. 3-57. 

R-3
Priority Pollutant Removal Efficiencies (%) Through Tertiary Treatment* 

Priority Pollutant Range 

METALS/NONMETAL INORGANICS** 

Cadmium 33-81 

Chromium 22-93 

Copper 8-99 

Cyanide 20-93 

Lead 4-86 

Mercury 33-79 

Nickel 4-78 

Silver 27-87 

Zinc 1-90 

Second 

Decile Median Eighth 

Decile 

50 50 

62 72 

58 85 

32 66 

9 52 

43 67 

7 7 

55 62 

50 78 

1 1

ORGANICS** 

40 50 

32 53 

50 83 

80 89 

31 57 

33 73 

80 88 

59 76 

50 63 

27 50 

29 38 

80 91 

83 94 

79 94 

62 93 

54 2 of 4 

64 3 of 4 

93 2 of 4 

94 3 of 4 

78 4 of 4 

86 3 of 4 

96 4 of 4 

94 4 of 4 

85 4 of 4 

70 4 of 4 

50 3 of 4 

97 4 of 4 

97 4 of 4 

97 4 of 4 

98 4 of 4 

Benzene 5-67 

Chloroform 16-75 

1,2-trans-Dichloroethylene 50-96 

Ethylbenzene 65-95 

Methylene Chloride 11-96 

Naphthalene 25-94 

Phenol 33-98 

Bis (2-ethylhexyl) phthalate 45-98 

Butyl benzyl phthalate 25-94 

Di-n-butyl phthalate 14-84 

Diethyl phthalate 20-57 

Tetrachloroethylene 67-98 

Toluene 50-99 

1,1,1-Trichloroethane 50-98 

Trichloroethylene 50-99 

Number of POTWs 

with Removal Data 

73 3 of 4 

89 4 of 4 

98 4 of 4 

83 4 of 4 

77 3 of 4 

75 4 of 4 

7 3 f o 4 

82 3 of 4 

88 4 of 4 

5

* Pollutant removals between POTW influent and tertiary effluent (including final clarification). Based 

on a computer analysis of POTW removal efficiency data (derived from actual POTW influent and 

effluent sampling data) provided in U.S. EPA’s Fate of Priority Pollutants in Publicly Owned Treatment 

Works, Volume II (EPA 440/1-82/303), September 1982. Tertiary treatment was taken to include POTWs 

with effluent microscreening, mixed media filtration, post aeration, and/or nitrification/denitrification. 

** For the purpose of deriving removal efficiencies, effluent levels reported as below detection were set 

equal to the reported detection limits. All tertiary treatment plants sampled as part of the study were 

considered. 

Source: U.S. EPA’s Guidance Manual on the Development and Implementation of Local Discharger 

Limitations Under the Pretreatment Program, December 1987, p. 3-58. 

R-4
APPENDIX S -

SPECIFIC GRAVITY OF SLUDGE

Equation to determine specific gravity of wet sludge 

The allowable headworks loading (AHL) equations presented in Chapter 5 for sewage sludge disposal contain 

a factor for the specific gravity of sludge (sludge density). This factor accounts for differences in the density 

of sludge based on the percent solids of sludge to disposal. e unit conversion factor (8.34) in the same 

equations converts the overall units into pounds per day (lbs/day), using a specific gravity or density of sludge 

equal to 1 kg/L, which assumes that sludge has the same density as water. sludge density 

is different from the density of water, the unit conversion factor is not fully accurate. 

of a sludge increases, the density of the sludge increases and therefore the error introduced by the inaccurate 

unit conversion factor increases. inaccuracy, the numerator of the AHL equation should be 

multiplied by the specific gravity of the dewatered sludge (as noted in Chapter 6). 

dewatered before disposal, the inaccuracy produced by using the unit conversion factor (8.34) without a 

specific gravity factor would probably not be significant. 

The POTW can determine the specific gravity (density) of its sludge prior to disposal through a simple 

laboratory measurement. The POTW should take this measurement as part of its local limits monitoring 

program and average the resulting data set (e.g., 7-10 data points) to determine a representative sludge 

specific gravity (density) factor for use in local limits calculations. ate the specific 

gravity of its sludge using the equations below and information on the percent solids. 

For a typical wet sludge at 10% solids, the approximate density is 1.03 kg/L. For a typical dewatered sludge 

at 30% solids, the approximate density is 1.11 kg/L. ay reach a density of 1.2 to 

1.3 kg/L, which would result in a 20% to 30% conservative error in the calculation of an AHL if a specific 

gravity factor is not used. ount of volatile solids in the sludge in 

comparison with the amount of fixed mineral solids, which vary with percent solids, and the densities of each 

of these types of solids. 

Where: 

MWS = Mass of wet sludge (kg) 

SWS = Specific gravity of wet sludge (kg/L) 

MS = Mass of dry sludge solids (kg) 

SS = Specific gravity of sludge solids (kg/L) 

MW = Mass of water (kg) 

SW = Specific gravity of water (kg/L) 

Th

If the dewatered 

As the percent solids 

To correct this 

If a sludge is not 

The POTW can also estim

A sludge at 50% solids m

All of these values depend on the am

Equation to determine specific gravity of dry sludge solids 

S-1
Where: 

MF = Mass of fixed solids (kg) 

SF = Specific gravity of fixed solids (kg/L) 

MV = Mass of volatile solids (kg) 

SV = Specific gravity of volatile solids (kg/L) 

The result from the second equation is used in the first equation. 

Example 

Sludge is 10% solids: 

Assume solids consist of 33% fixed mineral solids with a specific gravity of 2.5 kg/L and 67% volatile solids 

with a specific gravity of 1.2 kg/L. 

To determine the specific gravity of the dry sludge solids, use the second equation: 

which results in Ss = 1.45 kg/L. 

yields SWS = 1.03 kg/L. 

Using this value in the first equation: 

S-2
APPENDIX T -

SLUDGE AHL EQUATIONS USING FLOW (IN METRIC UNITS) 

Some POTWs may have sludge flow data available in dry metric tons per day, rather than MGD. The AHL 

equations for sludge disposal in Chapter 6 can be converted to use sludge flow data in these units. e of 

the equations in Chapter 6 are presented below using flows in dry metric tons per day. Use of these “dry 

flows” eliminates the need for the specific gravity factor in the equations. 

GENERAL SLUDGE EQUATION FOR CONSERVATIVE POLLUTANTS 

Where: 

LINFL = Allowable influent loading, lbs/day 

CCRIT = Sludge criteria, mg/kg dry sludge 

QSLDG = Total sludge flow to disposal, dry metric tons per day 

RPOTW = Removal efficiency across POTW (as decimal) 

0.0022 = Unit conversion factor 

LAND APPLICATION 

As explained in Chapter 6, determining the land application sludge criteria for use in the general sludge 

equation requires that the POTW first convert 40 CFR §503 Table 2 and Table 4 sludge criteria into values 

in mg/kg of dry sludge units. Table 4 criteria are in metric units (kg/ha), they must be 

converted into English units (lbs/acre) so that they can be used with the equations in Chapter 6 which use 

other English units (e.g., flow in MGD, area in acres). provided in both 

metric and English units in Appendix E. 

Another option is for POTWs to use the land application criteria equations in metric units (e.g., area in 

hectares, flow in dry metric tons per day), thus eliminating the need to convert Table 2 and Table 4 values 

to English units. These equations are provided below. These equations avoid the need for a specific gravity 

factor because they use also use a “dry flow” for sludge. 

Where: 

CCRIT = Sludge criteria, mg/kg dry sludge 

CCUM = Federal (Table 2 of 40 CFR 503.13) or State land application cumulative pollutant loading 

rate, kg/ha 

SA = Site area, hectares 

SL = Site life, years 

QLA = Sludge flow to bulk land application at an agricultural, forest, public contact, or reclamation 

site, dry metric tons per day 

0.365 = Unit conversion factor 

Som

Because Table 2 and 

Table 2 and Table 4 criteria are 

T-1
Arsenic, Cadmium, 

Chromium, Nickel 

Lead 

Beryllium, Mercury, 

pollutants with State limits 

Where: 

CCRIT = Sludge criteria, mg/kg dry sludge 

CANN = Federal (Table 4 of 40 CFR 503.13) or State land application annual pollutant loading rate, 

kg/ha 

AWSAR = Annual whole sludge application rate, metric tons per hectare per year dry weight basis 

0.001 = Unit conversion factor 

INCINERATION 

Sludge standards for maximum pollutant concentrations in sludge feed to the incinerator need to be in mg/kg 

dry sludge to be used in the equations at the beginning of Section 6.2.3 to calculate AHLs. 

disposing of sludge through incineration may already have sludge standards in mg/kg dry sludge, such as 

through a waste disposal agreement with the operator of a sludge incincerator. in Chapter 6, if no 

sludge standards have been calculated for the sludge feed to the incinerator, POTWs should use the Part 503 

equations (provided below) to determine the maximum pollutant concentrations for the incinerator feed. 

These maximum concentrations are then used in the equations at the beginning of Section 6.2.3 to calculate 

AHLs. 

Where: 

CCRIT = Sludge criteria, mg/kg dry sludge 

NESHAP = National emission standard for beryllium or mercury from 40 CFR Part 61, g/day 

NAAQS = National Ambient Air Quality Standard for lead, ug/m3 

RSC = Federal risk specific concentration limit for arsenic, cadmium, chromium, or nickel 

from 40 CFR 503.43, ug/m3 

CE = Control efficiency (removal efficiency) for sewage sludge incinerator for the given 

pollutant (as a decimal) 

QINC = Sludge flow to incinerator (i.e., sewage sludge feed rate), dry metric tons per day 

DF = Dispersion factor, ug/m3

/g/sec 

0.1 and 86,400 = Unit conversion factors 

For pollutants with State incinerator emissions standards, limits should be entered in g/day in place of the 

NESHAPs limits in the first equation above. 

A POTW 

As noted 

T-2
APPENDIX U -

POTW CONFIGURATIONS

The diagrams and discussions below demonstrate sampling locations to develop allowable headworks 

loadings (AHLs). For illustrative purposes, in this appendix all three plants must determine the AHLs based 

upon effluent limitations, secondary treatment inhibition, sludge digester inhibition, and sludge land 

application. Three different plants, with very different secondary treatment trains, are diagramed below along 

with sampling points for the AHL calculations. 

Diagram A 

Raw Wastewater 

Bar 

Screen 

and Grit 

Chamber 

Effluent 

Land 

Application 

Primary 

Clarifier 

Secondary 

Clarifier 

High Rate 

Sludge 

Digester 

Gravity 

Thickener 

Belt Filter 

Press 

Secondary 

Clarifier 

Trickling 

Filter 

Sludge 

Degritter 

Aeration 

Basin 

Chlorine 

Contact 

Chambers 

X

X 

X 

X 

A

B

C D

E

X 

AHL FOR SECONDARY TREATMENT INHIBITION 

At this POTW a trickling filter and an activated sludge system (aeration basin) operated in parallel provide 

secondary treatment of the raw wastewater. The concentration of a pollutant that could cause inhibition at 

the trickling filter may be different than the pollutant concentration that causes inhibition (known as the 

inhibition threshold level) at the aeration basin. The plant must determine a headworks loading protective 

of these two secondary treatment units. Using Equation 5.10, an AHL based on secondary treatment 

inhibition can be calculated. 

U-1
Trickling Filter 

Aeration Basin 

Where: 

AHLinhab = AHL based on aeration basin inhibition, lbs/day 

AHLinhtf = AHL based on trickling filter inhibition, lbs/day 

Cinhab = Inhibition criteria for aeration basin, mg/L 

Cinhtf = Inhibition criteria for trickling filter, mg/L 

Qpotw = Total POTW flow, MGD 

Rprim = Removal efficiency from headworks to primary treatment effluent as a decimal (See 

Section 5.1.1 for calculating removal efficiencies) 

8.34 = Unit conversion factor 

The equations to calculate the AHL based on trickling filter and aeration basin inhibition includes an 

inhibition criteria for the trickling filter, Cinhtf, and aeration basin, Cinhab, respectively. Both equations use the 

same removal rate, Rprim, from the headworks to the primary treatment effluent. Rprim can be determined by 

sampling loading at point “A,” the headworks, and point “B,” primary clarifier effluent (See Section 5.1 for 

these calculations). Qpotw can be determined through flow sampling at point “A” as well. AHLab and the AHLtf 

would be calculated, pared and the more stringent selected. 

AHL FOR SLUDGE DIGESTER INHIBITION 

This plant must determine a headworks loading protecting the high-rate sludge digester from inhibition. 

Using Equation 5.12, an AHL based on sludge digester inhibition can be calculated. 

Where: 

AHLinhhrsd = AHL based on high-rate sludge digester inhibition, lbs/day 

Cinbhrsd = High-rate sludge digester inhibition criteria, mg/L 

Qhrsd = Sludge flow to high-rate sludge digester, MGD 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

8.34 = Unit conversion factor 

The equation to calculate the AHL based on high-rate sludge digester inhibition includes an inhibition criteria 

for the digester, Cinbhrsd, sludge flow to the digester, Qhrsd , and an overall plant removal rate from headworks 

to plant effluent, Rpotw. Qhrsd can be determined sampling flow at point “C,” the sludge wastestream from 

gravity thickener to digester. Rpotw can be determined by sampling at point “A,” headworks before the 

bar screen and grit chamber, and at point “E,” the effluent after the chlorine contact chambers. 

com

by

the 

U-2
AHL FOR EFFLUENT LIMITS 

The plant must determine headworks loading that would lead to effluent from its chlorine contact chambers 

(CCC) comply with NPDES Permit limits. Using Equation 5.5, the AHL based on NPDES Permit limit can 

be calculated. 

Where: 

AHLeffccc = AHL based on CCC effluent compliance with NPDES, lbs/day 

Cnpdes = NPDES permit limit, mg/L 

Qpotw = POTW 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

8.34 = Conversion factor 

The equation to calculate the AHL based on CCC effluent compliance with NPDES includes the NPDES 

permit limit, Cnpdes, total POTW flow, Qpotw, and an overall plant removal rate from headworks to plant 

effluent, Rpotw. Rpotw can be determined by sampling loading at point “A,” 

screen and grit chamber, and at point “E,” the effluent after the chlorine contact chambers. Qpotw can be 

determined through sampling flow at point “A” as well. 

AHL FOR SLUDGE APPLICATION 

The plant must determine a headworks that would lead to sludge from the belt filter press suitable for land 

application. on sludge land application can be calculated. 

Where: 

AHLsabfp = AHL based on compliance with sludge application standards, lbs/day 

Cslgstd = Sludge standard, mg/kg dry sludge 

PS = Percent solids of sludge leading to belt filter press 

Qbfp = Total sludge flow to belt filter press, MGD 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

Gsldg = Specific gravity of sludge leading to filter press, kg/L 

8.34 = Unit conversion factor 

The equation to calculate the AHL based on belt filter press sludge compliance with sludge standards includes 

the sludge limit, Cslgstd ; the flow, percent solids and specific gravity of sludge leading press, 

Qbfp, PS, and Gsldg, respectively; and the overall plant removal rate from headworks to plant effluent, Rpotw. 

Rpotw can be determined by sampling loading at point “A,” the headworks before the bar screen and grit 

chamber, and at point “E,” the effluent after the chlorine contact chambers. Qbfp, PS, and Gsldg, can be 

determined through sampling point “D” the sludge waste stream to the belt filter press. 

flow, average, MGD 

the headworks before the bar 

Using equation 5.9 an AHL based

to the belt filter 

U-3
AHL FOR SECONDARY TREATMENT INHIBITION 

At this POTW a standard rate trickling filter, a high rate trickling filter, and rotating biological contactors 

(RBCs) operated in parallel provide secondary treatment of the raw wastewater. Each of these biological 

units is preceded by a different primary clarifier. An AHL (to prevent inhibition) should be determined for 

each of these biological unit processes because: 

Diagram B 

Raw Wastewater Effluent 

A

Chlorine 

Contact 

Chamber 

Gravity 

Thickener 

X 

X 

H

Land 

Application 

RBCs 

Bar 

Screen 

Grit 

Chamber 

Primary 

Clarifier #1 

Std. Rate 

Trickling 

Filter 

Secondary 

Clarifier #1 

High Rate 

Trickling 

Filter 

Primary 

Digester 

Secondary 

Digester 

Primary 

Clarifier #2 

Primary 

Clarifier #3 

Secondary 

Clarifier #2 

Secondary 

Clarifier #3 

Wet

Well

Vacuum 

Filter 

X 

X 

X 

X 

X 

X 

B

C

D

E

F

G

C The concentration of a pollutant that could cause inhibition at the standard rate trickling filter, high rate 

trickling filter, and RBCs are different. 

C The design and operational loadings to each of the secondary treatment units are different and therefore 

loading is different. 

C The primary clarifiers may have different removal efficiencies and therefore the pollutant concentrations 

to each of the secondary treatment unit may be different. 

The three equations listed below can be used to calculate secondary treatment inhibition. 

U-4
Standard Trickling Filter 

High-Rate Trickling Filter 

RBCs 

Where: 

AHLinhstf = AHL based on standard trickling filter inhibition, lbs/day 

AHLinhhrtf = AHL based on high-rate trickling filter inhibition, lbs/day 

AHLinhrbc = AHL based on RBC inhibition, lbs/day 

Cinhstf = Inhibition criteria for standard trickling filter, mg/L 

Cinhhrtf = Inhibition criteria for high-rate trickling filter, mg/L 

Cinhrbc = Inhibition criteria for RBC, mg/L 

Qpotw = Total POTW flow, MGD 

Rprim1 = Removal efficiency from headworks to primary clarifier #1 effluent as a decimal (See 

Section 5.1.1 for calculating removal efficiencies) 

Rprim2 = Removal efficiency from headworks to primary clarifier #2 effluent as a decimal 

Rprim3 = Removal efficiency from headworks to primary clarifier #3 effluent as a decimal 

8.34 = Unit conversion factor 

Each of the AHL equations has an inhibition criteria for each secondary treatment unit, Cinhstf , Cinhhrtf,, and 

Cinhrbc and removal rates from the headworks to corresponding primary clarifier unit effluent, Rprim1, Rprim2, 

and Rprim3. sampling locations “A” and “B” is used to calculate the removal efficiency from 

headworks to the primary clarifier #1 effluent, Rprim1. sampling locations “C” is used to 

calculate the removal efficiency from headworks to primary clarifier #2 effluent, Rprim2. sampling 

locations “A” and “D” is used to calculate the removal efficiency from headworks to primary clarifier #3 

effluent, Rprim3. Qpotw can be determined at sampling point “A.” The AHLinhstf, AHLinhhrtf, and AHLinhrbc should 

be calculated, compared, and the most stringent (smallest) selected. 

AHL FOR SLUDGE DIGESTER INHIBITION 

This plant must determine a headworks loading protecting both the primary and secondary sludge digesters 

from inhibition. on sludge digester inhibition can be calculated. 

Primary Digester 

Data from

Data from “A”and 

Data from

Using Equation 5.12, an AHL based 

U-5
Secondary Digester 

Where: 

AHLinbpd = AHL based on primary digester inhibition, lbs/day 

AHLinbsd = AHL based on secondary digester inhibition, lbs/day 

Cinbpd = Primary digester inhibition criteria, mg/L 

Cinbsd = Primary digester inhibition criteria, mg/L 

Qpd = Sludge flow to primary digester, MGD 

Qsd = Sludge flow to secondary digester, MGD 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

8.34 = Unit conversion factor 

The equations to calculate the AHL based on sludge digester inhibition include primary and secondary 

inhibition criteria, Cinbpd and Cinbsd, sludge flow to the primary and secondary digesters, Qpd and Qsd, and an 

overall plant removal rate from headworks to plant effluent, Rpotw. Qpd can be determined sampling flow 

at point “E,” the sludge wastestream to the primary digester. Qsd can be determined sampling flow at 

point “F,” the sludge wastestream from the primary digester to the secondary digester. Rpotw can be 

determined by sampling loading at point “A,” the headworks before the bar screen and grit chamber, and at 

point “H,” the effluent after the chlorine contact chambers. AHLinbpd and AHLinbsd should be calculated, 

compared and the more stringent selected. 

AHL FOR EFFLUENT LIMITS 

The plant must determine headworks loading that would lead to effluent from its chlorine contact chambers 

(CCC) comply with NPDES Permit limits. it limit can 

be calculated. 

Where: 

AHLeffccc = AHL based on CCC effluent compliance with NPDES, lbs/day 

Cnpdes = NPDES permit limit, mg/L 

Qpotw = POTW 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

8.34 = Conversion factor 

The equation to calculate the AHL based on CCC effluent compliance with NPDES includes the NPDES 

permit limit, Cnpdes, total POTW flow, Qpotw, and an overall plant removal rate from headworks to plant 

effluent, Rpotw. Rpotw can be determined by sampling at point “A,” the headworks before the bar screen and 

grit chamber, and at point “H,” the effluent after the chlorine contact chambers. Qpotw can be determined 

through sampling flow at point “A” as well. 

by

by

Using Equation 5.5, the AHL based on NPDES Perm

flow, average, MGD 

U-6
AHL FOR SLUDGE APPLICATION 

The plant must determine a headworks that would lead to sludge from the vacuum filter suitable for land 

application. Using equation 5.9 an AHL based on sludge land application can be calculated. 

Where:

AHLsavf = AHL based on compliance with sludge application standards, lbs/day

Cslgstd = Sludge standard, mg/kg dry sludge

PS = Percent solids of sludge leading to vacuum filter

Qvf = Total sludge flow to vacuum filter, MGD

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal)

Gsldg = Specific gravity of sludge leading to vacuum filter, kg/L

8.34 = Unit conversion factor

The equation to calculate the AHL based on vacuum filter sludge compliance with sludge standards includes

the sludge limit, Cslgstd ; the flow, percent solids and specific gravity of sludge leading to the belt filter press,

Qvf, PS, and Gsldg, respectively; and the overall plant removal rate from headworks to plant effluent, Rpotw.

Rpotw can be determined by sampling at point “A,” the headworks before the bar screen and grit chamber, and

at point “H,” the effluent after the chlorine contact chambers. Qvf, PS, and Gsldg, can be determined through

sampling at point “G” the sludge waste stream to the vacuum filter.

Diagram C 

Raw Wastewater Effluent 

Landfill 

X 

A

E F G

2nd Stage 

Aeration 

Basin 

3rd Stage 

Aeration 

Basin 

1st Stage 

Clarifier 

2nd Stage 

Clarifier 

Final 

Clarifier 

Ozone 

Treatment 

Air 

Flotation 

Thickener 

Primary 

Clarifier 

1st Stage 

Aeration 

Basin 

Gravity 

Thickener 

Plate and 

Frame 

Press 

Sludge 

Digester X X

X 

X X

X 

X 

B C D

H

U-7
1st Stage Aeration Basin 

2nd Stage Aeration Basin 

3rd Stage Aeration Basin 

AHL FOR SECONDARY TREATMENT INHIBITION 

At this POTW three activated sludge units (aeration basins) operated in series provide secondary treatment 

of the raw wastewater. a pollutant entering the First Stage Aeration Basin would be 

different from the concentration of that pollutant entering the Second Stage Aeration Basin and the Third 

Stage Aeration Basin because of the removal occurring in each unit. 

be determined for each of these secondary treatment units. 

Where: 

AHLinhab1 = AHL based on 1st Stage Aeration Basin inhibition, lbs/day 

AHLinhab2 = AHL based on 2nd Stage Aeration Basin inhibition, lbs/day 

AHLinhab3 = AHL based on 3rd Stage Aeration Basin inhibition, lbs/day 

Cinhab1 = Inhibition criteria for 1st Stage Aeration Basin, mg/L 

Cinhab2 = Inhibition criteria for 2nd Stage Aeration Basin, mg/L 

Cinhab3 = Inhibition criteria for 3rd Stage Aeration Basin, mg/L 

Qpotw = Total POTW flow, MGD 

Rprim = Removal efficiency from headworks to primary treatment effluent as a decimal (See Section 

5.1.1 for calculating removal efficiencies) 

Rab1 = Removal efficiency from headworks to 1st Stage Aeration Basin effluent as a decimal 

Rab2 = Removal efficiency from headworks to 2nd Stage Aeration Basin effluent as a decimal 

8.34 = Unit conversion factor 

Each of the equations to calculate AHLs for secondary treatment has it own inhibition criteria for each basin, 

Cinhab1, Cinhab2, and Cinhab3 and corresponding removal rate, Rprim, Rab1, and Rab2, respectively, for the 1st, 2nd , 

and 3rd stage aeration basins. sampling locations “A” and “B” is used to determine the removal 

efficiency from headworks to primary clarifier effluent, Rprim. Data from sampling locations “A” and “C” is 

used to determine the removal efficiency from headworks to 1st stage clarifier effluent, Rab1. Data from 

sampling locations “A” and to determine the removal efficiency from headworks to 2nd stage 

clarifier effluent, Rab2. Qpotw can be determined by sampling at location “A.” The AHLinhab1, AHLinhab2 , and 

AHLinhab3 should be calculated, compared, and the most stringent (smallest) selected. 

The concentration of 

An AHL (to prevent inhibition) should 

Data from

“D” is used 

U-8
AHL FOR SLUDGE DIGESTER INHIBITION 

This plant must determine a headworks loading protecting the sludge digester from inhibition. Using 

Equation 5.12, an AHL based on sludge digester inhibition can be calculated. 

Where: 

AHLinhsd = AHL based on sludge digester inhibition, lbs/day 

Cinhsd = Sludge digester inhibition criteria, mg/L 

Qsd = Sludge flow to sludge digester, MGD 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

8.34 = Unit conversion factor 

The equation to calculate the AHL based on high-rate sludge digester inhibition includes an inhibition criteria 

for the digester, Cinhsd, sludge flow to the digester, Qsd , and an overall plant removal rate from headworks to 

plant effluent, Rpotw. Qsd can be determined sampling flow at point “E,” the sludge wastestream from air 

flotation thickener to the digester. Rpotw can be determined by sampling loading at point “A,” the headworks 

before the bar screen and grit chamber, and at point “H,” the effluent after the ozone treatment unit. 

AHL FOR EFFLUENT LIMITS 

The plant must determine headworks loading that would lead to effluent from its ozone treatment unit (OTU) 

comply with NPDES Permit limits. it limit can be 

calculated. 

Where: 

AHLeffotu = AHL based on OTU effluent compliance with NPDES, lbs/day 

Cnpdes = NPDES permit limit, mg/L 

Qpotw = POTW 

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal) 

8.34 = Conversion factor 

The equation to calculate the AHL based on OTU effluent compliance with NPDES includes the NPDES 

permit limit, Cnpdes, total POTW flow, Qpotw, and an overall plant removal rate from headworks to plant 

effluent, Rpotw. Rpotw can be determined by sampling loading at point “A,” 

screen and grit chamber, and at point “H,” the effluent after the OTU. Qpotw can be determined through 

sampling flow at point “A” as well. 

by

Using Equation 5.5, the AHL based on NPDES Perm

flow, average, MGD 

the headworks before the bar 

U-9
AHL FOR SLUDGE APPLICATION 

The plant must determine a headworks that would lead to sludge from the plate and frame press (PFP) suitable 

for land application. Using equation 5.9 an AHL based on sludge land application can be calculated. 

Where:

AHLsapfp = AHL based on compliance with sludge application standards, lbs/day

Cslgstd = Sludge standard, mg/kg dry sludge

PS = Percent solids of sludge leading to PFP

Qpfp = Total sludge flow to PFP, MGD

Rpotw = Plant removal efficiency from headworks to plant effluent (as decimal)

Gsldg = Specific gravity of sludge leading to PFP, kg/L

8.34 = Unit conversion factor

The equation to calculate the AHL based on PFP sludge compliance with sludge standards includes the sludge

limit, Cslgstd ; the flow, percent solids and specific gravity of sludge leading to the PFP, Qpfp, PS, and Gsldg,

respectively; and the overall plant removal rate from headworks to plant effluent, Rpotw. Rpotw can be

determined by sampling loading at point “A,” the headworks before the bar screen and grit chamber, and at

point “H,” the effluent after the OTU. Qpfp, PS, and Gsldg, can be determined through sampling flow at point

“E” the sludge waste stream to the PFP. 

U-10
APPENDIX V -

DOMESTIC POLLUTANT LOADINGS

Residential/Commercial Trunkline Monitoring Data 

Pollutant Number of 

Detections 

Minimum Number of Concentration Samples 

Maximum 

Concentration 

(mg/L) 

Average 

Concentration 

(mg/L) 

0.088 0.007 

0.216 

0.42 

0.11 0.008 

0.007 0.006 

1.2 0.034 

0.74 0.14 

0.37 0.082 

0.27 

3.4 

2.04 0.058 

0.031 0.031 

0.161 0.087 

0.054 0.002 

1.6 0.047 

30.2 

0.7 0.7 

1.052 0.019 

1.28 0.231 

0.115 

0.3 

0.255 

0.989 

28.8 

Arsenic

Barium

Boron

Cadmium

Chromium (III)

Chromium (T)

Copper

Cyanide

Fluoride

Iron

Lead

Lithium

Manganese

Mercury

Nickel

Phosphate

Total Phosphorous

Silver

Zinc

Chloroform

1,1-Dichloroethene

1,1-Dichloroethane

Trans-1,2-Dichloroethene

Fluoranthene

Methylene Chloride

Phenols

Bis (2-ethylhexyl) Phthalate

Pyrene

Tetrachloroethene

1,2,4-Trichlorobenzene

Total BHC

4,4-DDD 

Total Endosulfan 

(mg/L) 

INORGANICS 

140 

3 

4 

361 

1 

311 

603 

7 

2 

18 

433 

2 

3 

218 

313 

2 

1 

181 

636 

205 0.0004 

3 0.04 

4 0.1 

538 0.00076 

2 < 0.005 

522 < 0.001 

607 0.005 

7 0.01 

2 0.24 

18 0.0002 

540 0.001 

2 0.03 

3 0.04 

235 < 0.0001 

540 < 0.001 

2 27.4 

1 0.7 

224 0.0007 

638 0.01 

ORGANICS 

21 

2 

1 

1 

2 

7 

2 

5 

2 

5 

1 

30 <0.002 

29 0.005 

28 0.026 

28 0.013 

5 0.00001 

30 0.00008 

2 0.00002 

5 0.00002 

3 0.00001 

29 0.00001 

3 <0.002 

PESTICIDES 

3 

3 

3 

3 0.001 

3 0.00026 

3 0.002 

0.069 

0.008 

0.026 

0.013 

<0.001 

0.055 

0.00003 

0.022 

<0.005 

0.037 

0.035 

0.009 

0.007 

0.026 

0.013 

0.001 

0.027 

0.000025 

0.006 

0.0002 

0.014 

0.013 

0.001 0.001 

0.0004 0.0003 

0.002 0.002 

V-1
Source: U.S. EPA’s Supplemental Manual on the Development and Implementation of Local Discharge 

Limitations Under the Pretreatment Programs, May 1991. “Pollutant levels reported below specified 

detection limit were considered in the data analysis and, for the purpose of statistical analysis, were 

considered equal to the detection limit.” 

V-2
APPENDIX W -

BEST MANAGEMENT PRACTICES MINI-CASE STUDIES

POTWs can implement best management practice (BMP) programs to gain control over wastewater 

discharges from commercial sources. By developing a less formal source control program with emphasis 

on source control, education, BMPs, as-needed inspections, and individual or “general” permits, POTWs can 

gain additional control over uncontrolled wastewater discharges from commercial sources. Source control 

programs should place emphasis on certain specific pollutants of concern. For example, silver and mercury 

are often of great concern to POTWs because of NPDES permit requirements. 

The commercial sources of wastewater that are addressed by BMP-based source control tend to have lower 

pollutant concentrations and loadings than other more traditional industrial facilities regulated by the 

traditional pretreatment program. Taken as a group, however, numerous uncontrolled commercial 

establishments may represent a significant source control opportunity that can lead to measurable 

improvement in environmental quality. Several pretreatment programs have documented pollutant 

reductions after the implementation of BMP and source reduction programs. 

Several BMP/source control programs implemented at several POTWs are summarized in the following 

paragraphs to illustrate a variety of approaches that have been taken to utilize BMPs for the control of 

commercial sources of wastewater. Programs reviewed include: East Bay Municipal Utility District 

(EBMUD) in Oakland, California; Metropolitan Wastewater in San Diego, California; Seattle 

Metropolitan/King County in Washington State; Western Lake Superior Sanitary District, Duluth, Minnesota; 

and the Connecticut Department of Environmental Protection (CT DEP), Hartford, Connecticut. 

EAST BAY MUNICIPAL DISTRICT (EBMUD), OAKLAND, CA 

EBMUD has been issuing pollution prevention permits (PPPs) since 1988. EBMUD began their PPP 

program in response to tighter air emission standards and more stringent NPDES permit requirements. As 

a result, EBMUD had to augment headworks sampling and analysis programs for the development and local 

limits. Based on attentive tracking of regulatory requirements over the past 10 years, EBMUD has 

sequentially identified POCs, identified commercial users contributing those pollutants, and developed PPPs 

with best management practice requirements. 

When EBMUD recognizes a pollutant of concern, they follow step-wise procedures. First, information on 

businesses and commercial activities that may be contributing the targeted POC is collected and refined. 

Next, EBMUD engages in an outreach program and works with the businesses to define BMPs. Finally, 

EBMUD issues the PPP and evaluates compliance. Generally, there is one sector of business activity that 

is responsible for the specific pollutant. For example, silver is linked to the photo finishers. EBMUD works 

with representatives of the commercial sector to research and develop BMPs that will effectively minimize 

the pollutant in effluent wastewater. 

EBMUD believes that the most important aspect of a successful PPP program is education, outreach, and user 

awareness combined with an enforceable permit. When conducting outreach, EBMUD gets in touch with 

each user to confirm the nature of their business and the processes they use at the business that can contribute 

wastewater and pollutants of concern. The establishment is asked to participate in educational workshops 

to review EBMUD's concerns, review and refine preliminary methods to prevent pollutant releases and lay 

the groundwork for successful communications and understanding of the problem and the solution. Users 

are introduced to the permitting and enforcement process in a non-threatening forum. EBMUD’s inventory 

of users is based on water supply account information. Whenever a user opens a water account, it is 

W-1
automatically characterized for wastewater and source control purposes. A revenue collection system ($3.25 

per commercial account per month) assures adequate funding for the PPP program. 

EBMUD staff researches ideas for generalized BMPs through discussions with the business sector and State 

trade group associations. Each of the EBMUD staff tracks one or more business sectors and are responsible 

for knowing current pollution control measures and trends. During the research phase of BMP development, 

each user that is a potential contributor of a POC is sent a letter to notify them that EBMUD is working on 

a PPP and reviewing the anticipated time frame for permit issuance. 

The PPP includes similar BMPs for each permittee. Some examples include silver recovery canisters 

connected in series to optimize removal of silver with a required logging procedure that assures canisters are 

changed at the appropriate frequency to eliminate break through. EBMUD PPPs vary in length from two to 

8 pages and are issued in industry group batches for a duration of 5 years. In the administration of their PPP 

program, EBMUD conducts visits/inspections of the permittees, provides follow up education, distributes fact 

sheets, procedures and posters illustrating acceptable waste and wastewater disposal procedures. During the 

life of a 5-year permit, EBMUD tries to inspect the permittee at least once or twice. Based on the findings 

of the initial visit, and the degree to which the permittee is implementing the prescribed BMPs, the follow 

up frequency is set. When EBMUD fails to get cooperation from businesses, they initiate enforcement 

actions. As an example, EBMUD sought and obtained a $27,000 penalty from a dry cleaner. 

A partial list of the businesses for which EBMUD has developed BMPs and PPP permits includes: 

• Photofinishers 

• Boat ards Y

• Dry Cleaners 

• Auto Repairs 

• Print Shop 

• Radiator Repair Shops 

• Furniture Stripping 

METROPOLITAN WASTEWATER, SAN DIEGO, CA 

Metropolitan Wastewater issues sector-specific BMP discharge authorizations to commercial customers. 

These authorizations require: 

• Specific pollution prevention measures. 

• An initial certification of compliance. 

• On-going semi-annual “reminder” certifications for businesses to demonstrate familiarity 

with their pollution prevention measures. 

Metropolitan Wastewater covers a variety of sectors with this program. General permits are issued to film 

processing and dry cleaners. The photo processing BMPs are based on the Code of Management Practice for 

Silver Dischargers (AMSA 1996) developed by the Silver Council in concert with the Association of 

Metropolitan Sewerage Agencies and EPA. Metropolitan Wastewater conducted workshops to review silver 

control BMPs with their users. Boat repair yards or dry docks are required to submit their own customized 

BMPs which are incorporated into a permit. Food establishment discharge permits are also issued and require 

grease removal equipment, operation and maintenance, and compliance with general and specific discharge 

prohibitions. Auto repair shops that have steam-cleaning operations are required to have a sump for all O&G 

W-2
wastewater from steam cleaning operations. San Diego has initiated a more aggressive program to enforce 

grease trap cleaning particularly at food establishments. They have discovered that excessive amounts of 

grease buildup contribute to dry weather flows into San Diego and Mission Bay. Analytical/Research Labs 

are required to implement a solvent certification program that is very similar to the total toxic organic (TTO) 

certification program for metal finishers and electroplaters. 

San Diego has a 301(h) waiver for their wastewater treatment facility, allowing conditional discharge of 

wastewater without full secondary treatment. One condition of the waiver requires the City to reexamine their 

local limits every year and reassess loadings from all sources (domestic, SIU, and non-SIU contributions). 

The IU is considered a "contributor" of a pollutant of concern (presently one of six heavy metals) if the user 

has one of the six metals in its effluent at a concentration that is two standard deviations above the average 

domestic concentration. Once the IU is deemed to be a “contributor” of a pollutant of concern, wastewater 

flow is evaluated to determine whether the load is significant enough to be assigned to the “allocated” versus 

“non-allocated” load for their local limits accounting procedures. When the load is significant, the user is 

included in the allocated portion of headworks load calculations and the user is required to comply with local 

limits. Users with minor concentrations or loadings of pollutants of concern are not required to comply with 

local limits. However, they may still be required to comply with BMPs and general permit requirements. 

SEATTLE METROPOLITAN/KING COUNTY, WASHINGTON 

Seattle Metropolitan /King County (Seattle Metro) has a very large and active pollution prevention program 

that has acquired a great deal of information on dental mercury source control. Dental facilities in the Seattle 

Metro collection system are subject to the mercury local limits. After strong lobbying by the Dental 

Association against mandatory BMPs, dental facilities currently have latitude in controlling mercury through 

BMPs. Seattle Metro has developed a variety of tools to control mercury, including: 

• A certified list of the vendors and technologies that are able to achieve a 90% reduction in metals. 

• Videotape on mercury and silver source control from dental offices entitled “Amalgam Waste 

Conference.” 

• A dental facility waste management poster and a booklet entitled, “Waste Management Guidelines 

for Dental Facilities.” 

• Records on the amount of amalgam that is being reclaimed by recyclers as a means of tracking the 

success of their education efforts. 

• Voucher program that gives $500 to dental offices to obtain one of the approved metal removal units 

identified in the list above. 

• Educational materials (posters, videos, booklets). 

WESTERN LAKE SUPERIOR SANITARY DISTRICT (WLSSD), DULUTH, MINNESOTA 

With support from the Great Lakes Protection Fund, the WLSSD conducted a two-year Mercury Zero 

Discharge Project to examine the sources of mercury to its wastewater treatment plant and to determine how 

to reduce or eliminate those sources. This project included cooperative initiatives with industries known to 

be discharging mercury, programs aimed at specific uses of mercury, a monitoring program to identify 

additional sources and a public awareness campaign. In addition to these external programs, WLSSD also 

examined its own facilities and practices. 

W-3
WLSSD has authored the Blueprint for Mercury Elimination, Mercury Reduction Project Guidance for 

Wastewater Treatment Plants, March, 1997. Selected for an AMSA National Environmental Achievement 

Award for excellence in Public Information & Education, the document examines sources of mercury in the 

environment, reviews contributions to the wastewater collection system, and gives examples of success stories 

on mercury source reduction. Appendices to the document provide useful "how to" references for 

implementing a source reduction program, such as a sample news release for a mercury reduction project, 

sample letters to mercury contributors, telephone survey forms to interview possible contributors, survey 

forms for hospitals and dental offices. 

CONNECTICUT DEPARTMENT OF ENVIRONMENTAL PROTECTION (CT DEP), HARTFORD, CONNECTICUT 

In 1992, CT DEP began a Statewide general permit program. The program established requirements for 

industries that were not SIUs, regulated by CT DEP’s State-run pretreatment permitting program, but were 

a potential source of concern for POTWs. The general permitting program is “self implementing” and 

expects commercial establishments to be made aware of general permit program requirements by the local 

Town officials, the State, or through consultants. Thus, the general permitting program avoids the resource 

intensive individual permitting of traditional programs. 

The program works in the following manner. An IU assesses their eligibility for a general permit (versus a 

traditional pretreatment permit). CT DEP encourages industries to determine eligibility for a general permit, 

as the permitting process is quicker and less costly for the IU and CT DEP. Each general permit identifies 

BMPs that must be followed by each permit holder. CT DEP conducts selective auditing and enforcement 

of general permit holders, and facilities that may have failed to register for a general permit. By publicizing 

the enforcement actions and penalties, industries are made aware of their duties to have a permit and comply 

with the BMPs, record keeping, monitoring, and where applicable, effluent limits. General permits 

developed by CT DEP include the following sectors: 

1. Constructions and Operation of Certain Recycling Facilities 

2. Car Wash Wastewater 

3. Domestic Sewage of 50,000 gallons per day or 5% of the POTW Design Flow 

4. Groundwater Contamination Recovery Systems 

5. Hydrostatic Pressure Testing 

6. Minor Boiler Blowdown 

7. Minor Non-Contact Cooling Water 

8. Minor Photographic Processing 

9. Minor Tumbling and Cleaning of Parts Wastewater 

10. Storm Water Associated with Industrial Activities 

11. Storm Water and Dewatering Wastewaters - Construction Activities 

12. Vehicle Service Floor Drain and Car Wash Wastewater 

13. Storm Water Associated with Commercial Activities 

14. Minor Printing and Publishing Wastewater 

15. Water Treatment Wastewater - Commercial 

16. Food Processing Wastewater 

17. Public Swimming Pool Backwash 

18. Water Softening/Treatment Unit Wastewater-Individual Homes (under development) 

W-4
APPENDIX X -

REGION 1, REASSESSMENT OF TECHNICALLY BASED INDUSTRIAL

DISCHARGE LIMITS CHECKLIST

Attachment A. 

EPA - New England 

Reassessment of Technically Based Industrial Discharge Limits 

Under 40 CFR 122.21(j)(4), all Publicly Owned Treatment Works (POTWs) with approved Industrial 

Pretreatment Programs (IPPs) shall provide the following information to the Director: a written evaluation 

of the need to revise local industrial discharge limits under 40 CFR 403.5(c)(1). 

Below is a form designed by the U.S. Environmental Protection Agency (EPA - New England) to assist 

POTWs with approved IPPs in evaluating whether their existing Technically Based Local Limits 

(TBLLs) need to be recalculated. The form allows the permittee and EPA to evaluate and compare 

pertinent information used in previous TBLLs calculations against present conditions at the POTW. 

Please read direction below before filling out form. 

ITEM I. 

* In Column (1), list what your POTW’s influent flow rate was when your existing TBLLs were 

calculated. In Column (2), list your POTW’s present influent flow rate. Your current flow rate 

should be calculated using the POTW's average daily flow rate from the previous 12 months. 

* In Column (1) list what your POTW’s SIU flow rate was when your existing TBLLs were 

calculated. In Column (2), list your POTW’s present SIU flow rate. 

* In Column (1), list what dilution ratio and/or 7Q10 value was used in your old/expired NPDES 

permit. In Column (2), list what dilution ratio and/or 7Q10 value is presently being used in your 

new/reissued NPDES permit. 

The 7Q10 value is the lowest seven day average flow rate, in the river, over a ten-year period. 

The 7Q10 value and/or dilution ratio used by EPA in your new NPDES permit can be found in 

your NPDES permit “Fact Sheet.” 

* In Column (1), list the safety factor, if any, that was used when your existing TBLLs were 

calculated. 

* In Column (1), note how your biosolids were managed when your existing TBLLs were 

calculated. In Column (2), note how your POTW is presently disposing of its biosolids and how 

your POTW will be disposing of its biosolids in the future. 

ITEM II. 

* List what your existing TBLLs are - as they appear in your current Sewer Use Ordinance (SUO). 

X-1
ITEM III. 

* Identify how your existing TBLLs are allocated out to your industrial community. Some 

pollutants may be allocated differently than others, if so please explain. 

ITEM IV. 

* Since your existing TBLLs were calculated, identify the following in detail: 

(1) if your POTW has experienced any upsets, inhibition, interference or pass-through as a 

result of an industrial discharge. 

(2) if your POTW is presently violating any of its current NPDES permit limitations -

include toxicity. 

ITEM V. 

* Using current sampling data, list in Column (1) the average and maximum amount of pollutants 

(in pounds per day) received in the POTW's influent. Current sampling data is defined as data 

obtained over the last 24 month period. 

All influent data collected and analyzed must be in accordance with 40 CFR 136. Sampling data 

collected should be analyzed using the lowest possible detection method(s), e.g., graphite furnace. 

* Based on your existing TBLLs, as presented in Item II., list in Column (2), for each pollutant the 

Maximum Allowable Industrial Headwork Loading (MAIHL) values derived from an applicable 

environmental criteria or standard, e.g., water quality, sludge, NPDES, inhibition, etc. For each 

pollutant, the MAIHL equals the calculated Maximum Allowable Headwork Loading (MAHL) 

minus the POTW's domestic loading source(s). For more information, please see p. 3-28 in 

EPA’s Guidance Manual on the Development and Implementation of Local Limits Under the 

Pretreatment Program, 12/87. 

ITEM VI. 

* Using current sampling data, list in Column (1) the average and maximum amount of pollutants 

(in micrograms per liter) present in your POTW’s effluent. Current sampling data is defined as 

data obtained during the last 24-month period. 

All effluent data collected and analyzed must be in accordance with 40 CFR 136. Sampling data 

collected should be analyzed using the lowest possible detection method(s), e.g., graphite furnace. 

* List in Column (2A) what the Water Quality Standards (WQS) were (in micrograms per liter) 

when your TBLLs were calculated, please note what hardness value was used at that time. 

Hardness should be expressed in milligram per liter of calcium carbonate. 

List in Column (2B) the current WQSs or “Chronic Gold Book” values for each pollutant 

multiplied by the dilution ratio used in your new/reissued NPDES permit. For example, with a 

dilution ratio of 25:1 at a hardness of 25 mg/L - calcium carbonate (copper’s chronic WQS equals 

6.54 ug/L) the chronic NPDES permit limit for copper would equal 156.25 ug/L. 

X-2
ITEM VII.

* In Column (1), list all pollutants (in micrograms per liter) limited in your new/reissued NPDES 

permit. In Column (2), list all pollutants limited in your old/expired NPDES permit. 

ITEM VIII. 

* Using current sampling data, list in Column (1) the average and maximum amount of pollutants 

in your POTW's biosolids. Current data is defined as data obtained during the last 24 month 

period. Results are to be expressed as total dry weight. 

All biosolids data collected and analyzed must be in accordance with 40 CFR 136. 

In Column (2A), list current State and/or Federal sludge standards that your facility’s biosolids 

must comply with. Also note how your POTW currently manages the disposal of its biosolids. If 

your POTW is planing on managing its biosolids differently, list in Column (2B) what your new 

biosolids criteria will be and method of disposal. 

In general, please be sure the units reported are correct and all pertinent information is included in your 

evaluation. If you have any questions, please contact your pretreatment representative at EPA - New 

England. 

X-3
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REASSESSMENT OF TECHNICALLY BASED LOCAL LIMITS


(TBLLs)


POTW Name & Address :


_____________________________________________


NPDES PERMIT # :


_________________________________________________


Date EPA approved current TBLLs :


________________________________


Date EPA approved current Sewer Use Ordinance :


__________________


ITEM I.


In Column (1), list the conditions that existed when your current


TBLLs were calculated. In Column (2), list current conditions or


expected conditions at your POTW.


Column (1) Column (2)


EXISTING TBLLs


POTW Flow (MGD)


SIU Flow (MGD)


Dilution Ratio or


7Q10 (from NPDES Permit)


Safety Factor 


Biosolids Disposal


Method(s)


POLLUTANT


PRESENT CONDITIONS


N/A


NUMERICAL


LIMIT


(mg/L) or (lb/day)


ITEM II.


EXISTING TBLLs 


NUMERICAL LIMIT 


(mg/L) or (lb/day)


POLLUTANT


X-4
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ITEM III.


Note how your existing TBLLs, listed in Item II., are allocated


to your Significant Industrial Users (SIUs), i.e., uniform


concentration, contributory flow, mass proportioning, other. 


Please specify by circling. 


ITEM IV.


Has your POTW experienced any upsets, inhibition, interference or


pass-through from industrial sources since your existing TBLLs


were calculated?


If yes, explain.


_________________________________________________________________


____________________________________________________


Has your POTW violated any of its NPDES permit limits and/or


toxicity test requirements?


If yes, explain.


_________________________________________________________________


____________________________________________________


ITEM V.


Using current POTW influent sampling data fill in Column (1). In


Column (2), list your Maximum Allowable Headwork Loading (MAHL)


values used to derive your TBLLs listed in Item II. In addition,


please note the Environmental Criteria for which each MAHL value


was established, i.e., water quality, sludge, NPDES, etc.


Column (1) Column (2)


Pollutant Influent Data Analyses MAHL Values Criteria


Maximum Average


(lb/day) (lb/day) (lb/day)


Arsenic ------------------


Cadmium ------------------


Chromium ------------------


Copper ------------------


Cyanide ------------------


Lead ------------------


Mercury ------------------


Nickel ------------------


Silver ------------------


Zinc ------------------


Other (List)


------------------


------------------


------------------


X-5
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ITEM VI.


Using current POTW effluent sampling data, fill in Column (1). 


In Column (2A) list what the Water Quality Standards (Gold Book


Criteria) were at the time your existing TBLLs were developed. 


List in Column (2B) current Gold Book values multiplied by the


dilution ratio used in your new/reissued NPDES permit.


Columns


Column (1) (2A) (2B)


Pollutant Effluent Data Analyses Water Quality Criteria


Maximum Average (Gold Book)


From TBLLsToday


(ug/L) (ug/L) (ug/L) (ug/L)


Arsenic


*Cadmium


*Chromium -------------------


*Copper


Cyanide


*Lead


Mercury


*Nickel


Silver


*Zinc


Other (List)


---------


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---------


---------


---------


---------


---------


---------


---------


---------


---------


---------


*Hardness Dependent (mg/L - CaCO3)


ITEM VII.


In Column (1), identify all pollutants limited in your


new/reissued NPDES permit. In Column (2), identify all


pollutants that were limited in your old/expired NPDES permit.


Column (1)


NEW PERMIT


PollutantsLimitations


(ug/L)


Column (2)


OLD PERMIT


PollutantsLimitations


(ug/L)


X-6
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ITEM VIII.


Using current POTW biosolids data, fill in Column (1). In Column


(2A), list the biosolids criteria that was used at the time your


existing TBLLs were calculated. If your POTW is planing on


managing its biosolids differently, list in Column (2B) what your


new biosolids criteria would be and method of disposal.


Columns


Column (1) (2A) (2B)


Pollutant Biosolids Data Analyses Biosolids Criteria


Arsenic


Cadmium


Chromium


Copper


Cyanide


Lead


Mercury


Nickel


Silver


Zinc


Molybdenum


Selenium


Other (List)


Average


(mg/kg)


From TBLLs New


(mg/kg)


---------


---------


---------


---------


---------


---------


--------­


(mg/kg)


X-7