Appendices to Regulatory Impact Analysis of EPA's Proposed 

Regulations for the Management of Hazardous Waste 

Pharmaceuticals at Healthcare Facilities 

June 2015 
i 

TABLE OF CONTENTS 

APPENDICES: 

Appendix A. Identification of Waste Streams in the 2009 Biennial Report Database that are not 

Hazardous Waste Pharmaceuticals A-1

Appendix B. Annual Generation of Hazardous Waste and Hazardous Waste Pharmaceuticals by Industry 

and Generator Status B-1 

Appendix C. Annual Cost Impacts by State C-1 

Appendix D. Annual Costs per Model Facility by Cost Type and Scenario D-1

Appendix E. Regression Based Approach for Estimating Hazardous Waste Generation for LQG 

Hospitals E-1

Appendix F. Occurrence of APIs in Finished Drinking Water F-1 
A-1 

APPENDIX A. IDENTIFICATION OF WASTE STREAMS IN THE 2009 BIENNIAL 

REPORT DATABASE THAT ARE NOT HAZARDOUS WASTE 

PHARMACEUTICALS 

As described in Chapter 2, this RIA relies on data from EPA’s 2009 Biennial Report (BR) database to 

estimate the annual generation of hazardous waste pharmaceuticals for both hospitals and reverse 

distributors. Because the BR database does not include a clear identifier for hazardous waste 

pharmaceuticals, such waste streams were identified based on other variables included in the BR 

database. As an initial step in this process, this RIA first identified several waste streams generated by 

hospitals and reverse distributors that most likely are not hazardous waste pharmaceuticals. The approach 

used in this RIA for identifying these waste streams and excluding them from the BR data is as follows: 

1. Exclude remediation wastes. Wastes are considered “remediation wastes” if they: 

 Have the word “remediation," “cleanup," “clean?up," “media," and/or “soil” in the waste 

description field; or 

 Have form code W301; or 

 Are represented by source codes G41 through G49, as shown below in Exhibit A-1. 

EXHIBIT A-1. SOURCE CODES FOR REMEDIATION WASTES

SOURCE CODE SOURCE CODE DESCRIPTION

G41 Closure of hazardous waste management unit under RCRA 

G42 Corrective action at a solid waste management unit under RCRA 

G43 Remedial action or emergency response under Superfund 

G44 State program or voluntary cleanup 

G45 Underground storage tank cleanup 

G49 Other remediation (specify in comments) 

2. Exclude construction wastes. Wastes are considered construction wastes if they have the word 

“construction,” and/or “demolition" in the waste description field. 

3. Exclude paint wastes. Wastes are considered paint wastes if they have Source Code G06, Form 

Code W209, Form Code W211, Form Code W604, or the waste description includes the word 

“paint”. 
A-2 

4. Exclude waste oil and battery wastes. Wastes are oil and battery wastes if they have Source 

Code G16, Form Code W206, Form Code W309, or the word “battery” or batteries” is in the 

waste description. 

5. Exclude pesticide wastes. Wastes are pesticide wastes if they have Form Code W401 or the word 

“pesticide” in the waste description. 

6. Exclude tank sludge wastes. Wastes are tank sludge wastes if they have Source Code G14. 

7. Exclude certain pollution control and waste management process residuals: 

 Source Code G21 – Air pollution control devices (baghouse dust or ash from stack 

scrubbers or precipitators; vapor collection, etc.) 

 Source Code G23 - Wastewater treatment (sludge, filter cake, etc., including wastes from 

treatment before discharge by NPDES or POTW or by UIC disposal) 

 Source Code G24 - Solvent or product distillation or recovery (sludge, waste solvent, 

bottoms, from recovery/recycling of used product) or waste descriptions containing the 

word “distillation”. 

 Source Code G26 - Leachate collection (from landfill operations or other land units) 

 Source Code G27 - Hazardous residual from treatment or recovery of universal waste 

8. Exclude mercury-containing equipment wastes. Wastes are mercury-containing equipment if 

they have Form Code W320 or the words “thermometer”, “sphygmomanometer”, “thermostat”, 

“fluorescent”, or “flourescent” in the waste description. 

9. Exclude lead-containing equipment wastes. Wastes are lead-containing equipment if they 

contain the words “lead apron’ or “lead shield” in the waste description or the combination of 

EPA Waste Code D008 and the words “apron”, “shield” or “electronic” in the waste description. 

10. Exclude silver wastes from X-rays and development of X-rays and photographs. Silver wastes 

include EPA Waste Code D011 and the words “x?ray”, “xray”, “developer”, photo”, “film”, or 

“fixer” in the waste description. 

11. Exclude solvent wastes. Wastes are solvent wastes if they include EPA Waste Codes F002, 

F003, or F005 or any of the following words in the waste description: “solvent”, “refrigerant”, 

“Chloroform”, “methanol”, “acetone”, “methylene chloride”, “xylene”, “ethanol”, “isopropanol”, 

“toluene”, or “acetonitrile”. Wastes containing the words “formaldehyde” or “formulin” were not 

excluded in this step. 

12. Exclude mixed infectious or radioactive wastes. Exclude wastes with the words “infectious” or 

“radioactive” in the waste description. 

13. Exclude formaldehyde and formal wastes – chemicals used to preserve specimens. Exclude all 

wastes with the words “formaldehyde” or “formalin” in the waste description. 
A-3 

14. Exclude laboratory analytical wastes – used chemicals from laboratory operations. Wastes are 

laboratory analytical wastes if they have Source Code G22. 

After completion of the steps above and review of waste descriptions, the following steps were 

added: 

15. Exclude additional mercury wastes. Waste streams were assumed to contain mercury if they 

include any of the following terms in the BR waste description: 

“mercury” AND “retort” 

“amalgam” 

“bulb” 

“mercury” AND “lamp” 

 “mercury” AND “gauge” 

“mercury” AND “guage” 

 “mercury” AND “drain” 

“mercury” AND Source Code G15 

“mercury” AND Source Code G19 

“mercury” AND “instrument” 

“mercury” AND “debris” 

“mercury” AND “dental” 

“waste elemental mercury” 

“waste liquid mercury” 

16. Exclude additional lead wastes. Waste streams were assumed to contain lead if they include any 

of the following terms in the BR waste description: 

“lead” AND “bite” 

“lead” AND “debris” 

“lead” AND “glass” 

“bullet” AND “floor sweeping” 

“lead” AND “floor sweeping” 

“lead contaminated” 

“water with lead” 

17. Exclude additional photographic/x-ray wastes. Waste streams were assumed to fall in this 

category if they include any of the following terms in the BR waste description: 

“film” 

“fixer” 

18. Exclude fuels. Waste streams with any of the following descriptors in the BR waste description 

were excluded: 

“fuel” 

“oil” 
A-4 

“gasoline” 

“diesel” 

“propane” 

“gas filter” 

19. Exclude other miscellaneous wastes. Wastes containing any of the following terms in the BR 

waste description field were also excluded. 

“incinerator ash” 

“radiation shield” 

“lab” AND “machine” 

“calibration” AND “gas” 

“maintenance” AND “gas” 

“PCB” 

 “tank sludge” 

“scale remover” 

“dental repair” 

“rubber rejuvenator” 

“blanket conditioner” 

 “pepper spray” 

 “roof tar” 

“anti-freeze” 

“still bottoms” 

“slag” 

“dross” 

“metal scale” 

20. Exclude cleaner wastes. Waste streams were assumed to fall in this category if they include any 

of the following terms in the BR waste description: 

“cleaner” 

“part washer” 

“laundry detergent” 

“cleaning solution” 

“cleaning product” 

“clean” AND “maintenance” 

“clean” AND “rinse water” 

“gun patch” 

The number of BR waste records and the associated hazardous waste tonnage removed by each step is 

presented in Exhibit A-2. 
A-5 

EXHIBIT A-2. NUMBER OF WASTE RECORDS AND HAZARDOUS WASTE TONNAGE REMOVED BY 

EACH EXCLUSION STEP 

EXCLUSION 

STEP EXCLUSION STEP DESCRIPTION

NUMBER OF WASTE 

STREAMS 

EXCLUDED 

HAZARDOUS WASTE 

EXCLUDED (TONS) 

1 Remediation Waste 55 436.7 

2 Construction Waste 4 45.3 

3 Paint Waste 382 8,620.4 

4 Waste Oil and Batteries 73 43.2 

5 Pesticides 11 74.7 

6 Tank Sludge 7 2,935.5 

7 Pollution Control and Waste Management 

Residuals 

46 67.3 

8 Mercury-containing Equipment 63 39.2 

9 Lead-containing Equipment 25 4.1 

10 Silver Waste 49 93.3 

11 Solvent Waste 1,717 2,702.6 

12 Infectious or Radioactive Waste 22 60.9 

13 Formaldehyde and Formalin Waste 98 270.9 

14 Laboratory Analytical Waste 1,442 721.0 

15 Additional Mercury Waste 67 7.3 

16 Additional Lead Waste 16 17.7 

17 Additional Photographic/X-Ray Waste 3 0.1 

18 Fuels 34 7.7 

19 Other Miscellaneous Waste 21 145.5 

20 Cleaners 21 4.4 

TOTAL EXCLUDED 4,156 16,298
B-1 

APPENDIX B. ANNUAL GENERATION OF HAZARDOUS WASTE AND HAZARDOUS 

WASTE PHARMACEUTICALS BY INDUSTRY AND GENERATOR 

STATUS 

To provide additional detail on the generation data included in Chapter 2, this appendix presents the 

estimated generation of hazardous waste and hazardous waste pharmaceuticals by industry and RCRA 

generator status for the universe of facilities affected by the rule. These data are presented in Exhibit B-1 

(hazardous waste in aggregate) and Exhibit B-2 (hazardous waste pharmaceuticals). 

EXHIBIT B-1. ANNUAL GENERATION OF HAZARDOUS WASTE BY INDUSTRY AND RCRA GENERATOR 

STATUS (TONS)

NAICS FACILITY TYPE LQG SQG CESQG 

ALL 

GENERATORS 

44611 Pharmacies 5,320 5,650 1,470 12,400

54194 Veterinary Clinics 1,840 2,360 1,130 5,330

6211 Physicians’ Offices 20,500 18,400 8,610 47,500

6212 Dentists’ Offices 400 4,700 5,580 10,700

6213 Other Health Practitioners (e.g., 

chiropractors) 0 13,000 4,940 17,900

6214 Outpatient Care Centers 3,500 3,980 1,050 8,530

6219 Other Ambulatory Health Care 

Services 590 1,460 330 2,380

622 Hospitals 21,600 5,960 430 28,000

6231 Nursing Care Facilities 600 1,840 620 3,070

623311 Continuing Care Retirement 

Communities 81 230 260 570

Subset of 

92219 

Medical Examiners and Coroners' 

Offices 720 440 50 1,210

Various 

NAICS Reverse Distributors 1,270 17 4 1,290

TOTAL 56,500 58,000 24,500 139,000

Note: The values reported in this exhibit reflect all of the hazardous waste generated by facilities affected by the 

rule. These values include hazardous waste pharmaceuticals as well as other hazardous wastes generated by 

these facilities. 

 
B-2 

EXHIBIT B-2. ANNUAL GENERATION OF HAZARDOUS WASTE PHARMACEUTICALS BY INDUSTRY 

AND RCRA GENERATOR STATUS (TONS)

NAICS FACILITY TYPE LQG SQG CESQG 

ALL 

GENERATORS 

44611 Pharmacies 1,280 1,360 350 2,990

54194 Veterinary Clinics 440 570 270 1,280

6211 Physicians’ Offices 4,940 4,410 2,070 11,400

6212 Dentists’ Offices 95 1,130 1,340 2,570

6213 Other Health Practitioners (e.g., 

chiropractors) 0 3,120 1,190 4,300

6214 Outpatient Care Centers 840 960 250 2,050

6219 Other Ambulatory Health Care 

Services 140 350 78 570

622 Hospitals 6,680 1,840 130 8,650

6231 Nursing Care Facilities 150 440 150 740

623311 Continuing Care Retirement 

Communities 20 56 62 140

Subset of 

92219 

Medical Examiners and Coroners' 

Offices 170 110 12 290

Various 

NAICS Reverse Distributors 1,200 16 3 1,220

TOTAL 15,900 14,400 5,920 36,200
C-1 

APPENDIX C. ANNUAL COST IMPACTS BY STATE 

As a supplement to the cost impacts presented in Chapter 3, this appendix presents the incremental costs 

of each policy option by state. These estimates are presented in Exhibit C-1 using a discount rate of 7 

percent. 

EXHIBIT C-1. ANNUAL COSTS OF EACH POLICY OPTION INCREMENTAL TO THE BASELINE, 

7 PERCENT DISCOUNT RATE (MILLIONS OF 2011$)

STATE 

COSTS INCREMENTAL TO 

FULL COMPLIANCE BASELINE 

COSTS INCREMENTAL TO 

PARTIAL COMPLIANCE BASELINE 

MORE 

STRINGENT 

OPTION 

PREFERRED 

OPTION 

LESS 

STRINGENT 

OPTION 

MORE 

STRINGENT 

OPTION 

PREFERRED 

OPTION 

LESS 

STRINGENT 

OPTION 

Alabama $0.72 $0.59 $0.56 $2.45 $2.31 $2.29 

Alaska $0.11 $0.09 $0.09 $0.39 $0.37 $0.37 

Arizona $0.87 $0.69 $0.66 $2.92 $2.73 $2.69 

Arkansas $0.53 $0.43 $0.41 $1.77 $1.66 $1.64 

California $5.06 $4.03 $3.80 $17.03 $15.97 $15.73 

Colorado $0.77 $0.62 $0.58 $2.60 $2.44 $2.41 

Connecticut $0.51 $0.41 $0.38 $1.72 $1.61 $1.59 

Delaware $0.13 $0.10 $0.10 $0.44 $0.41 $0.40 

District of 

Columbia $0.09 $0.08 $0.07 $0.32 $0.30 $0.30 

Florida $3.14 $2.43 $2.30 $10.26 $9.52 $9.39 

Georgia $1.34 $1.07 $1.02 $4.48 $4.19 $4.14 

Hawaii $0.20 $0.16 $0.16 $0.69 $0.65 $0.64 

Idaho $0.27 $0.23 $0.22 $0.94 $0.89 $0.88 

Illinois $1.83 $1.42 $1.35 $6.02 $5.60 $5.52 

Indiana $0.95 $0.75 $0.71 $3.14 $2.93 $2.89 

Iowa $0.53 $0.43 $0.41 $1.79 $1.69 $1.67 

Kansas $0.54 $0.46 $0.44 $1.89 $1.80 $1.77 

Kentucky $0.72 $0.59 $0.56 $2.46 $2.33 $2.30 

Louisiana $0.84 $0.71 $0.68 $2.92 $2.77 $2.74 

Maine $0.23 $0.19 $0.18 $0.80 $0.76 $0.75 

Maryland $0.82 $0.65 $0.62 $2.75 $2.59 $2.55 

Massachusetts $0.90 $0.73 $0.69 $3.05 $2.86 $2.82 

Michigan $1.42 $1.14 $1.08 $4.80 $4.51 $4.45 
C-2 

EXHIBIT C-1. ANNUAL COSTS OF EACH POLICY OPTION INCREMENTAL TO THE BASELINE, 

7 PERCENT DISCOUNT RATE (MILLIONS OF 2011$)

STATE 

COSTS INCREMENTAL TO 

FULL COMPLIANCE BASELINE 

COSTS INCREMENTAL TO 

PARTIAL COMPLIANCE BASELINE 

MORE 

STRINGENT 

OPTION 

PREFERRED 

OPTION 

LESS 

STRINGENT 

OPTION 

MORE 

STRINGENT 

OPTION 

PREFERRED 

OPTION 

LESS 

STRINGENT 

OPTION 

Minnesota $0.70 $0.57 $0.54 $2.37 $2.23 $2.20 

Mississippi $0.46 $0.38 $0.36 $1.57 $1.49 $1.48 

Missouri $0.93 $0.74 $0.70 $3.08 $2.88 $2.84 

Montana $0.23 $0.19 $0.18 $0.79 $0.75 $0.74 

Nebraska $0.36 $0.30 $0.29 $1.25 $1.18 $1.17 

Nevada $0.36 $0.30 $0.28 $1.24 $1.17 $1.16 

New 

Hampshire $0.19 $0.15 $0.14 $0.64 $0.60 $0.60 

New Jersey $1.42 $1.13 $1.07 $4.77 $4.48 $4.41 

New Mexico $0.28 $0.23 $0.22 $0.95 $0.90 $0.89 

New York $3.03 $2.37 $2.24 $9.98 $9.30 $9.17 

North 

Carolina $1.21 $0.93 $0.88 $3.92 $3.62 $3.58 

North Dakota $0.16 $0.13 $0.13 $0.55 $0.53 $0.52 

Ohio $1.62 $1.30 $1.23 $5.46 $5.13 $5.06 

Oklahoma $0.68 $0.56 $0.54 $2.35 $2.22 $2.20 

Oregon $0.53 $0.42 $0.40 $1.79 $1.68 $1.66 

Pennsylvania $2.02 $1.61 $1.53 $6.74 $6.31 $6.23 

Rhode Island $0.17 $0.14 $0.13 $0.58 $0.54 $0.54 

South 

Carolina $0.57 $0.47 $0.44 $1.95 $1.84 $1.81 

South Dakota $0.19 $0.17 $0.16 $0.68 $0.65 $0.64 

Tennessee $0.98 $0.77 $0.73 $3.23 $3.01 $2.98 

Texas $3.47 $2.81 $2.67 $11.75 $11.05 $10.91 

Utah $0.41 $0.31 $0.29 $1.29 $1.18 $1.17 

Vermont $0.12 $0.10 $0.09 $0.41 $0.38 $0.38 

Virginia $0.97 $0.79 $0.74 $3.30 $3.10 $3.06 

Washington $0.90 $0.72 $0.68 $3.03 $2.83 $2.79 

West Virginia $0.32 $0.27 $0.26 $1.11 $1.05 $1.04 

Wisconsin $0.80 $0.63 $0.60 $2.65 $2.48 $2.45 

Wyoming $0.11 $0.09 $0.09 $0.39 $0.37 $0.36 

TOTAL $45.71 $36.56 $34.69 $153.45 $143.86 $141.96 
D-1 

APPENDIX D. ANNUAL COSTS PER MODEL FACILITY BY COST TYPE AND 

SCENARIO 

As a supplement to the cost results presented in Chapter 3 of this RIA, this appendix presents the annual 

costs of each of the waste management activities discussed in Chapter 3 by model facility and scenario 

using a 7 percent discount rate. These costs are presented in Exhibits D-1 through D-16. 
EXHIBIT D-1. ANNUAL NOTIFICATION COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 20

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator Status 

(under 2 and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) Mo

Stringe

Optio

Hospitals Small 836 CESQG CESQG $0.00 $0.00 $0.0Hospitals Large 1,719 CESQG CESQG $0.00 $0.00 $0.0Other Healthcare Facilities Small 123,957 CESQG CESQG $0.00 $0.00 $0.0Other Healthcare Facilities Large 18,874 CESQG CESQG $0.00 $0.00 $0.0Reverse Distributors Small 21 CESQG CESQG $0.00 $0.00 $5.0Hospitals Small 785 SQG SQG $0.00 $0.00 $5.0Hospitals Large 1,612 SQG SQG $0.00 $0.00 $2.8Other Healthcare Facilities Small 18,147 SQG SQG $0.00 $0.00 $2.8Other Healthcare Facilities Large 2,763 SQG SQG $0.00 $0.00 $2.9Reverse Distributors Small 7 SQG CESQG $0.00 $0.00 $2.9Other Healthcare Facilities Large 3,721 LQG LQG $0.00 $0.00 $2.9Reverse Distributors Large 28 LQG SQG $0.00 $0.00 $0.0Non-teaching Hospitals Large 421 LQG LQG $0.00 $0.00 $0.1Teaching Hospitals, less than 370 beds Large 570 LQG LQG $0.00 $0.00 $0.0Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $0.00 $0.00 $0.0Teaching Hospitals, 800 or more beds Large 82 LQG LQG $0.00 $0.00 $0.0
EXHIBIT D-2. ANNUAL TRAINING COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011$)

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator Status 

(under 2 and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) Mo

Stringe

Optio

Hospitals Small 836 CESQG CESQG $0 $0 $0 Hospitals Large 1,719 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Small 123,957 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Large 18,874 CESQG CESQG $0 $0 $0 Reverse Distributors Small 21 CESQG CESQG $0 $0 $2,23Hospitals Small 785 SQG SQG $6,197 $6,197 $6,19Hospitals Large 1,612 SQG SQG $7,211 $7,211 $7,21Other Healthcare Facilities Small 18,147 SQG SQG $981 $981 $1,02Other Healthcare Facilities Large 2,763 SQG SQG $1,659 $1,659 $1,72Reverse Distributors Small 7 SQG CESQG $1,022 $1,022 $2,23Other Healthcare Facilities Large 3,721 LQG LQG $3,876 $3,876 $4,02Reverse Distributors Large 28 LQG SQG $4,024 $4,024 $4,02Non-teaching Hospitals Large 421 LQG LQG $9,046 $9,046 $9,04Teaching Hospitals, less than 370 beds Large 570 LQG LQG $12,648 $12,648 $12,64Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $24,411 $24,411 $24,4Teaching Hospitals, 800 or more beds Large 82 LQG LQG $43,198 $43,198 $43,19
EXHIBIT D-3. ANNUAL MANIFEST TRAINING COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 201

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator Status 

(under 2 and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) Mor

Stringe

Option 

Hospitals Small 836 CESQG CESQG $0 $0 $0 Hospitals Large 1,719 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Small 123,957 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Large 18,874 CESQG CESQG $0 $0 $0 Reverse Distributors Small 21 CESQG CESQG $0 $0 $228 Hospitals Small 785 SQG SQG $228 $228 $228 Hospitals Large 1,612 SQG SQG $228 $228 $228 Other Healthcare Facilities Small 18,147 SQG SQG $219 $219 $228 Other Healthcare Facilities Large 2,763 SQG SQG $219 $219 $228 Reverse Distributors Small 7 SQG CESQG $228 $228 $228 Other Healthcare Facilities Large 3,721 LQG LQG $220 $220 $228 Reverse Distributors Large 28 LQG SQG $228 $228 $228 Non-teaching Hospitals Large 421 LQG LQG $228 $228 $228 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $228 $228 $228 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $228 $228 $228 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $228 $228 $228 
EXHIBIT D-4. ANNUAL CONTINGENCY PLAN UPDATING COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT 

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 

2 and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0 $0 $0 Hospitals Large 1,719 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Small 123,957 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Large 18,874 CESQG CESQG $0 $0 $0 Reverse Distributors Small 21 CESQG CESQG $0 $0 $950 Hospitals Small 785 SQG SQG $0 $0 $0 Hospitals Large 1,612 SQG SQG $0 $0 $0 Other Healthcare Facilities Small 18,147 SQG SQG $0 $0 $0 Other Healthcare Facilities Large 2,763 SQG SQG $0 $0 $0 Reverse Distributors Small 7 SQG CESQG $0 $0 $950 Other Healthcare Facilities Large 3,721 LQG LQG $915 $915 $950 Reverse Distributors Large 28 LQG SQG $950 $950 $950 Non-teaching Hospitals Large 421 LQG LQG $950 $950 $950 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $950 $950 $950 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $950 $950 $950 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $950 $950 $950 
EXHIBIT D-5. ANNUAL CONTAINER MANAGEMENT COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 2 

and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $86 $86 $86 Hospitals Large 1,719 CESQG CESQG $86 $86 $86 Other Healthcare Facilities Small 123,957 CESQG CESQG $86 $86 $86 Other Healthcare Facilities Large 18,874 CESQG CESQG $86 $86 $86 Reverse Distributors Small 21 CESQG CESQG $74 $74 $297 Hospitals Small 785 SQG SQG $491 $342 $502 Hospitals Large 1,612 SQG SQG $491 $342 $502 Other Healthcare Facilities Small 18,147 SQG SQG $331 $331 $491 Other Healthcare Facilities Large 2,763 SQG SQG $331 $331 $491 Reverse Distributors Small 7 SQG CESQG $594 $594 $594 Other Healthcare Facilities Large 3,721 LQG LQG $1,324 $1,005 $1,644 Reverse Distributors Large 28 LQG SQG $8,906 $8,906 $8,906 Non-teaching Hospitals Large 421 LQG LQG $673 $662 $982 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $1,324 $1,313 $1,655 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $3,345 $3,002 $4,018 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $5,696 $5,331 $7,020 
EXHIBIT D-6. ANNUAL LABELING COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011$)

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 2 

and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0.00 $0.00 $0.00 Hospitals Large 1,719 CESQG CESQG $0.00 $0.00 $0.00 Other Healthcare Facilities Small 123,957 CESQG CESQG $0.00 $0.00 $0.00 Other Healthcare Facilities Large 18,874 CESQG CESQG $0.00 $0.00 $0.00 Reverse Distributors Small 21 CESQG CESQG $0.00 $0.00 $24.48 Hospitals Small 785 SQG SQG $24.48 $4.90 $24.48 Hospitals Large 1,612 SQG SQG $24.48 $4.90 $24.48 Other Healthcare Facilities Small 18,147 SQG SQG $0.00 $0.00 $24.48 Other Healthcare Facilities Large 2,763 SQG SQG $0.00 $0.00 $24.48 Reverse Distributors Small 7 SQG CESQG $24.48 $24.48 $24.48 Other Healthcare Facilities Large 3,721 LQG LQG $70.76 $14.15 $73.45 Reverse Distributors Large 28 LQG SQG $73.45 $73.45 $73.45 Non-teaching Hospitals Large 421 LQG LQG $73.45 $14.69 $73.45 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $73.45 $14.69 $73.45 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $73.45 $14.69 $73.45 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $73.45 $14.69 $73.45 
EXHIBIT D-7. ANNUAL INSPECTION COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011$)

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 2 

and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0 $0 $0 Hospitals Large 1,719 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Small 123,957 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Large 18,874 CESQG CESQG $0 $0 $0 Reverse Distributors Small 21 CESQG CESQG $0 $0 $2,551 Hospitals Small 785 SQG SQG $2,546 $2,546 $2,546 Hospitals Large 1,612 SQG SQG $5,093 $5,093 $5,093 Other Healthcare Facilities Small 18,147 SQG SQG $2,445 $2,445 $2,546 Other Healthcare Facilities Large 2,763 SQG SQG $4,890 $4,890 $5,093 Reverse Distributors Small 7 SQG CESQG $2,546 $2,546 $2,551 Other Healthcare Facilities Large 3,721 LQG LQG $4,906 $4,906 $5,093 Reverse Distributors Large 28 LQG SQG $5,093 $5,093 $5,097 Non-teaching Hospitals Large 421 LQG LQG $5,093 $5,093 $5,093 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $5,093 $5,093 $5,093 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $5,093 $5,093 $5,093 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $5,093 $5,093 $5,093 
EXHIBIT D-8. ANNUAL SECURITY (WAREHOUSING) COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RAT

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 2 

and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0 $0 $0 Hospitals Large 1,719 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Small 123,957 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Large 18,874 CESQG CESQG $0 $0 $0 Reverse Distributors Small 21 CESQG CESQG $0 $0 $60 Hospitals Small 785 SQG SQG $0 $0 $0 Hospitals Large 1,612 SQG SQG $0 $0 $0 Other Healthcare Facilities Small 18,147 SQG SQG $0 $0 $0 Other Healthcare Facilities Large 2,763 SQG SQG $0 $0 $0 Reverse Distributors Small 7 SQG CESQG $0 $0 $60 Other Healthcare Facilities Large 3,721 LQG LQG $0 $0 $0 Reverse Distributors Large 28 LQG SQG $0 $0 $163 Non-teaching Hospitals Large 421 LQG LQG $0 $0 $0 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $0 $0 $0 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $0 $0 $0 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $0 $0 $0 
EXHIBIT D-9. ANNUAL CLOSURE COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011$)

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 2 

and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0 $0 $0 Hospitals Large 1,719 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Small 123,957 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Large 18,874 CESQG CESQG $0 $0 $0 Reverse Distributors Small 21 CESQG CESQG $0 $0 $843 Hospitals Small 785 SQG SQG $0 $0 $47 Hospitals Large 1,612 SQG SQG $0 $0 $47 Other Healthcare Facilities Small 18,147 SQG SQG $0 $0 $47 Other Healthcare Facilities Large 2,763 SQG SQG $0 $0 $47 Reverse Distributors Small 7 SQG CESQG $0 $0 $843 Other Healthcare Facilities Large 3,721 LQG LQG $827 $827 $859 Reverse Distributors Large 28 LQG SQG $1,252 $1,252 $1,252 Non-teaching Hospitals Large 421 LQG LQG $828 $828 $828 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $859 $859 $859 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $969 $969 $969 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $1,111 $1,111 $1,111 
EXHIBIT D-10. ANNUAL RCRA STORAGE PERMIT COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 2 

and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0 $0 $0 Hospitals Large 1,719 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Small 123,957 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Large 18,874 CESQG CESQG $0 $0 $0 Reverse Distributors Small 21 CESQG CESQG $0 $0 $12,100 Hospitals Small 785 SQG SQG $0 $0 $0 Hospitals Large 1,612 SQG SQG $0 $0 $0 Other Healthcare Facilities Small 18,147 SQG SQG $0 $0 $0 Other Healthcare Facilities Large 2,763 SQG SQG $0 $0 $0 Reverse Distributors Small 7 SQG CESQG $0 $0 $12,100 Other Healthcare Facilities Large 3,721 LQG LQG $0 $0 $0 Reverse Distributors Large 28 LQG SQG $0 $0 $12,100 Non-teaching Hospitals Large 421 LQG LQG $0 $0 $0 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $0 $0 $0 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $0 $0 $0 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $0 $0 $0 
EXHIBIT D-11. ANNUAL SORTING COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011$)

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 2 

and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $24 $12 $37 Hospitals Large 1,719 CESQG CESQG $24 $12 $37 Other Healthcare Facilities Small 123,957 CESQG CESQG $24 $12 $24 Other Healthcare Facilities Large 18,874 CESQG CESQG $24 $12 $24 Reverse Distributors Small 21 CESQG CESQG $0 $0 $0 Hospitals Small 785 SQG SQG $649 $282 $759 Hospitals Large 1,612 SQG SQG $649 $282 $759 Other Healthcare Facilities Small 18,147 SQG SQG $465 $49 $588 Other Healthcare Facilities Large 2,763 SQG SQG $465 $49 $588 Reverse Distributors Small 7 SQG CESQG $0 $0 $0 Other Healthcare Facilities Large 3,721 LQG LQG $1,775 $539 $2,130 Reverse Distributors Large 28 LQG SQG $0 $0 $0 Non-teaching Hospitals Large 421 LQG LQG $1,224 $514 $1,420 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $2,204 $930 $2,583 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $6,146 $2,583 $7,186 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $10,798 $4,542 $12,610 
EXHIBIT D-12. ANNUALIZED BIENNIAL REPORTING COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RAT

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 2 

and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0 $0 $0 Hospitals Large 1,719 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Small 123,957 CESQG CESQG $0 $0 $0 Other Healthcare Facilities Large 18,874 CESQG CESQG $0 $0 $0 Reverse Distributors Small 21 CESQG CESQG $0 $0 $138 Hospitals Small 785 SQG SQG $0 $0 $138 Hospitals Large 1,612 SQG SQG $38 $35 $38 Other Healthcare Facilities Small 18,147 SQG SQG $38 $35 $38 Other Healthcare Facilities Large 2,763 SQG SQG $34 $31 $35 Reverse Distributors Small 7 SQG CESQG $34 $31 $35 Other Healthcare Facilities Large 3,721 LQG LQG $24 $19 $170 Reverse Distributors Large 28 LQG SQG $170 $136 $170 Non-teaching Hospitals Large 421 LQG LQG $245 $220 $254 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $761 $279 $761 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $328 $277 $328 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $328 $277 $328 
EXHIBIT D-13. ANNUAL RECORDKEEPING COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011$

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 

2 and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0.00 $0.00 $0.00 Hospitals Large 1,719 CESQG CESQG $0.00 $0.00 $0.00 Other Healthcare Facilities Small 123,957 CESQG CESQG $0.00 $0.00 $0.00 Other Healthcare Facilities Large 18,874 CESQG CESQG $0.00 $0.00 $0.00 Reverse Distributors Small 21 CESQG CESQG $0.00 $0.00 $5.30 Hospitals Small 785 SQG SQG $5.30 $5.30 $5.30 Hospitals Large 1,612 SQG SQG $5.30 $5.30 $5.30 Other Healthcare Facilities Small 18,147 SQG SQG $5.09 $5.09 $5.30 Other Healthcare Facilities Large 2,763 SQG SQG $5.09 $5.09 $5.30 Reverse Distributors Small 7 SQG CESQG $5.30 $5.30 $5.30 Other Healthcare Facilities Large 3,721 LQG LQG $5.11 $5.11 $5.30 Reverse Distributors Large 28 LQG SQG $5.30 $5.30 $5.30 Non-teaching Hospitals Large 421 LQG LQG $5.30 $5.30 $5.30 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $5.30 $5.30 $5.30 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $5.30 $5.30 $5.30 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $5.30 $5.30 $5.30 
EXHIBIT D-14. ANNUAL MANIFEST COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011$)

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status (under 

2 and 3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $0.00 $0.00 $0.00 Hospitals Large 1,719 CESQG CESQG $0.00 $0.00 $0.00 Other Healthcare Facilities Small 123,957 CESQG CESQG $0.00 $0.00 $0.00 Other Healthcare Facilities Large 18,874 CESQG CESQG $0.00 $0.00 $0.00 Reverse Distributors Small 21 CESQG CESQG $0.00 $0.00 $46.81 Hospitals Small 785 SQG SQG $25.06 $25.06 $59.34 Hospitals Large 1,612 SQG SQG $25.06 $25.06 $59.34 Other Healthcare Facilities Small 18,147 SQG SQG $25.06 $25.06 $59.34 Other Healthcare Facilities Large 2,763 SQG SQG $25.06 $25.06 $59.34 Reverse Distributors Small 7 SQG CESQG $25.06 $25.06 $59.34 Other Healthcare Facilities Large 3,721 LQG LQG $84.28 $84.28 $118.56 Reverse Distributors Large 28 LQG SQG $84.28 $84.28 $118.56 Non-teaching Hospitals Large 421 LQG LQG $84.28 $84.28 $118.56 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $84.28 $84.28 $118.56 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $84.28 $84.28 $118.56 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $84.28 $84.28 $118.56 
EXHIBIT D-15. ANNUAL TRANSPORTATION COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status 

(under 2 and 

3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $227 $203 $227 Hospitals Large 1,719 CESQG CESQG $227 $203 $227 Other Healthcare Facilities Small 123,957 CESQG CESQG $251 $226 $251 Other Healthcare Facilities Large 18,874 CESQG CESQG $251 $226 $251 Reverse Distributors Small 21 CESQG CESQG $316 $316 $316 Hospitals Small 785 SQG SQG $316 $316 $316 Hospitals Large 1,612 SQG SQG $927 $886 $967 Other Healthcare Facilities Small 18,147 SQG SQG $927 $886 $967 Other Healthcare Facilities Large 2,763 SQG SQG $820 $789 $922 Reverse Distributors Small 7 SQG CESQG $820 $789 $922 Other Healthcare Facilities Large 3,721 LQG LQG $1,930 $1,930 $1,969 Reverse Distributors Large 28 LQG SQG $1,930 $1,930 $1,969 Non-teaching Hospitals Large 421 LQG LQG $2,552 $2,453 $2,716 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $31,320 $31,320 $31,359 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $1,558 $1,590 $1,723 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $2,661 $2,571 $2,825 
EXHIBIT D-16. ANNUAL DISPOSAL COSTS PER MODEL FACILITY, BY SCENARIO (7 PERCENT DISCOUNT RATE, 2011$)

Facility Type 

Establishment 

Size Establishments 

Baseline 

Generator 

Status 

Regulatory 

Generator 

Status 

(under 2 and 

3) 

Baseline: 

Full 

compliance 

Baseline: 

Partial 

compliance 

1) More 

Stringent 

Option 

Hospitals Small 836 CESQG CESQG $612 $549 $624 Hospitals Large 1,719 CESQG CESQG $612 $549 $624 Other Healthcare Facilities Small 123,957 CESQG CESQG $630 $572 $640 Other Healthcare Facilities Large 18,874 CESQG CESQG $630 $572 $640 Reverse Distributors Small 21 CESQG CESQG $723 $723 $723 Hospitals Small 785 SQG SQG $10,072 $8,523 $10,531 Hospitals Large 1,612 SQG SQG $10,072 $8,523 $10,531 Other Healthcare Facilities Small 18,147 SQG SQG $10,018 $8,265 $10,548 Other Healthcare Facilities Large 2,763 SQG SQG $10,018 $8,265 $10,548 Reverse Distributors Small 7 SQG CESQG $10,544 $10,544 $10,544 Other Healthcare Facilities Large 3,721 LQG LQG $36,689 $31,561 $38,238 Reverse Distributors Large 28 LQG SQG $191,679 $191,679 $191,679 Non-teaching Hospitals Large 421 LQG LQG $18,953 $16,060 $19,842 Teaching Hospitals, less than 370 beds Large 570 LQG LQG $34,407 $29,136 $36,007 Teaching Hospitals, 370 to 799 beds Large 480 LQG LQG $95,841 $81,180 $100,299 Teaching Hospitals, 800 or more beds Large 82 LQG LQG $168,341 $142,590 $176,183 
E-1 

APPENDIX E. REGRESSION BASED APPROACH FOR ESTIMATING HAZARDOUS 

WASTE GENERATION FOR LQG HOSPITALS 

As described in Chapter 2, this RIA estimates waste quantities for a series of LQG model hospitals 

defined in terms of their teaching status and the number of beds at each hospital. The specification of 

these model hospitals was based in part on the American Hospital Directory data presented in Chapter 2, 

which included information on hospital revenues, discharges, patient days, beds, and teaching status. The 

statistical analysis presented in Chapter 2 showed that each of these variables has a statistically significant 

correlation with hospital hazardous waste generation (based on generation data in EPA’s 2009 Biennial 

Report database). Based on these correlations, we considered using a regression-based framework to 

estimate hazardous waste generation for LQG hospitals, using each of the hospital characteristics that are 

correlated with hazardous waste generation as an explanatory variable. More specifically, we assessed 

the feasibility of using a multivariate model to capture how the different variables outlined above interact 

and collectively explain variation in hazardous waste generation. All of the explanatory variables, 

however, are highly correlated with one another. This presents a significant challenge in multivariate 

regression analysis. Specifically, a regression model with a high degree of correlation among the 

explanatory variables—a phenomenon known as multicollinearity—may not give reliable estimates of the 

individual parameters or about which predictors are “more significant” with respect to others.1

 

Furthermore, multicollinearity can cause coefficient estimates to be highly sensitive to small changes in 

the model or the data. Recognizing these limitations, Exhibit E-1 reports the results of a multivariate 

regression model with the following explanatory variables: number of beds, revenue, and teaching status. 

Each of these explanatory variables has a positive impact on hazardous waste generation and the 

regression yields a fairly robust goodness-of-fit or “R-squared” value. 

                                                            

1

 The multivariate model with multicollinearity would still provide unbiased estimates of waste generation. 
E-2 

EXHIBIT E-1. REGRESSION RESULTS FOR HOSPITAL HAZARDOUS WASTE GENERATION1

EXPLANATORY VARIABLE COEFFICIENT STANDARD ERROR2

Number of Beds 0.00032* 0.00019 

Natural Log of Revenue3 0.24817*** 0.06168 

Teaching Status 0.20519** 0.08826 

Constant -3.68544*** 1.19527 

Observations (Number of Hospitals) 

R-squared 

154 

0.44 

Notes: 

*** Significant at the 99% level, ** Significant at the 95% level, * Significant at the 90% level 

1. The dependent variable is transformed in order to achieve an approximate normal distribution and 

diminish the differences in outliers in the data. We use the fourth root of total hazardous 

pharmaceutical waste generation. This is the first nth root that does not reject the null hypothesis 

that the sample came from a normally distributed population using the Shapiro-Wilk test. The 

transformation of the data makes it more challenging to interpret the magnitude of the resultant 

coefficients, but improves the reliability and overall fit of the regression model. 

2. Standard errors represent a measure of uncertainty associated with the precision of the regression 

coefficients. Standard errors can be used to construct confidence intervals for the coefficients, which 

may vary depending on the level of significance desired. For example, a 95% confidence interval for 

the natural log of revenue is calculated as approximately 0.24817±1.96×0.06168 or 

[0.12629,0.37004]. 

3. We use the natural log of revenue in order to achieve an approximate normal distribution and 

diminish the differences in outliers in the data.

The R-squared value for the regression implies that the hospital characteristics in Exhibit E-1 explain a 

non-trivial proportion, but not all, of the variation in hazardous waste generation. While this approach to 

estimating total hazardous waste generation was promising, the results are considerably weaker for the 

generation of hazardous waste pharmaceuticals. This may be due to a significant number of hospitals 

generating zero or very low quantities of hazardous waste pharmaceuticals. Nearly a third of hospitals in 

the BR database report no hazardous pharmaceutical waste. In the regression, the R-squared value drops 

considerably when we use hazardous waste pharmaceuticals generation as the dependent variable. 

Considering the limitations of the regression-based approach, we instead use the series of “model 

hospitals” presented in Chapter 2 as the basis for estimating the generation of hazardous waste 

(pharmaceutical and total) among LQG hospitals.
F-1 

APPENDIX F. OCCURRENCE OF APIs IN FINISHED DRINKING WATER 

Exhibit F-1is reproduced from Daughton (2010), Table I. See notes for full citation. 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

AlimentaryTract &Metabolism

A01AB21 Chlortetracycline 57-62-5 ND (DL=5-150) (2) 

A02BA02 Ranitidine 66357-35-5 ND (DL=0.01) (3) 

A07AB03 Sulfaguanidine 57-67-0 ND (DL=5-75) (2) 

Cardiovascular System: C03 Diuretics; C04 Peripheral Vasodilators; C07 Beta Blocking Agents; C08 Calcium Channel Blockers; C10 

Lipid Modifying Agents 

C03AA03 Hydrochlorothiazide 58-93-5 0.8-117 [2.8] (RO DWTP) (4) 

2.6-330 [7.1] (NF DWTP) (4) 

C03CA01 Furosemide 54-31-9 ND (DL=4.30) (3) 

C04AD03 Pentoxifylline 6493-05-6 ND (DL=5-60) (2) 

ND (DL=1) (5) 

C07AA05 Propranolol 525-66-6 ND (DL=1.9; 3 tap 

water samples) 

(6) 

C07AB02 Metoprolol 37350-58-6 up to 13.5 [2.6] (RO/NF 

DWTP) 

 (4) 

14-26 [20] (2 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

C07AB03 Atenolol 29122-68-7 1.2 [18] (8 of 18 samples) 0.84 [0.47] 

(8 of 15 samples) 

(8) 

[2.8] max=26 (11 of 20 DWTPs) (9) 

ND (RL=0.25) (10) 

ND (DL=0.05) (3) 

C08CA05 Nifedipine 21829-25-4 ND (DL=15.5; 3 tap 

water samples) 

(6) 

C08CA05 

metabolite 

Dehydronifedipine 

(metabolite) 

67035-22-7 2-6 (2 of 12 samples) (11) 

4 (12) 

C08DB01 Diltiazem 42399-41-7 ND (DL=13.0; 3 tap 

water samples) 

(6) 

C09AA02 Enalapril 75847-73-3 ND (RL=0.25) (10) 

C10AA01 Simvastatin 79902-63-9 ND (RL=1.0) (10) 

C10AA01 

metabolite 

Simvastatin hydroxy 

acid 

12009-77-6 

(Na salt) 

ND (RL=0.25) (10) 

C10AA05 Atorvastatin 134523-03-8 ND (RL=0.25) (10) 

ND (MRL=0.25) (18 samples) <MRL 

(15 samples) 

(8) 

C10AA05 

metabolite 

o-Hydroxy atorvastatin 214217-86-6 ND (MRL=0.50) (18 samples) <MRL (18 samples) (8) 

C10AA05 

metabolite 

p-Hydroxy atorvastatin 214217-88-6 

(Ca-salt, acid 

form) 

ND (RL=0.50) (10) 

ND (MRL=0.50) (18 samples) <MRL (18 samples) (8) 

C10AB01 Clofibrate 637-07-0 ND (DL=55) (13) 

C10AB01 

metabolite 

Clofibric acid 882-09-7 up to 170 (12 of 14 DWTPs) (14) 

3.2-5.3 (1 of 3 DWTPs) 

(DL=1.50) 

 (3) 

up to 70 (16 of 30 samples) 

(DL=1) 

 (15) 
F-2 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

up to 70 (16 of 25 samples) 

(DL=1) 

 (16) 

270 (14) 

32 (17) 

0.9-1.1 (2 of 4 samples) (18) 

>50, <100 (2 of 22 samples) (19) 

13-136 [59] (3 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

10-165 (64 of 64 tap water 

samples from Berlin) 

 (1) 

ND (DL=130) (13) 

ND (DL=3-90) (2) 

C10AB02 Bezafibrate 41859-67-0 27 (1 of 25 samples) (DL=25) (16) 

up to 14 (20) 

[0.7] max=1.9 (21) 

13-20 [17] (2 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

ND (DL=0.05) (3) 

ND (DL=3-90) (2) 

C10AB04 Gemfibrozil 25812-30-0 ND (RL=0.25) (10) 

1.3-6.5 (5) 

70 (1 of 10 DWTPs) (DL=3-90) (2) 

2.4 (22) 

2.1 [0.48] (7 of 18 samples) 1.2 [0.43] (4 of 15 

samples) 

(8) 

0.6-10.6 (5 of 5 DWTPs) (23) 

up to 3.0 (20) 

[0.4] max=0.8 (21) 

[1.0] max=2.0 (6 of 20 DWTPs) (9) 

 >2.4, LOD (mean 3 

tap water samples)

(6) 

ND (LOD=0.1; 6 tap

water samples) 

(24) 

C10AB05 Fenofibrate 49562-28-9 14-21 [18] (2 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

C10AB05 

metabolite 

Fenofibric acid 42017-89-0 42 (1 of 30 samples) (DL=5) (15) 

Dermatologicals: D01 Antifungals; D06 Antibiotics & Chemotherapeutics; D08Antiseptics & Disinfectives 

D01AE12 

S01BC08 

Salicylic acid 

(also transformation 

product) 

69-72-7 10-122 [39] (13 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

 4.2 (mean 3 tap 

water samples) 

(6) 

D06AX02 

(multiple) 

Chloramphenicol 56-75-7 12-13 [13] (2 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

D08AE04 Triclosan 3380-34-5 734 (1 of 15 samples) (DL=125) (13) 

43 (1 of 20 locales) (5) 

1.2 (1 of 18 samples) <MRL (15 samples) (8) 

[1.1] max=1.2 (2 of 20 DWTPs) (9) 

ND (DL=1) (25) 

ND (RL=1.0) (10) 
F-3 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

ND (DL=2.4; 3 tap 

water samples) 

(6) 

D08 

(possible 

assignment) 

Triclocarban 

(Trichlorocarbanilide) 

101-20-2 

ND (DL= 10; 

samples from 12 

DWTPs) 

(26) 

Genito Urinary System & Sex Hormones: G03 Sex Hormones & Modulators of the Genital System 

G03AC01 Norethisterone 

(Norethindrone) 

68-22-4 ND (DL=10) (27) 

G03BA03 Testosterone 58-22-0 ND (DL=1) (5) 

ND (MRL=0.50) (18 samples) <MRL (15 samples) (8) 

G03CA01 17α-Ethynylestradiol 57-63-6 0.15-0.50 (28) 

ND (DL=5) (27) 

ND (DL=1) (5) 

ND (MRL=1.0) (18 samples) <MRL (15 samples) (8) 

<90 (below LOQ; 12

tap water samples 

over several 

months) 

(29) 

ND (DL=4.8; 3 tap 

water samples) 

(6) 

G03CA03 17α-Estradiol 57-91-0 0.3 (28) 

G03CA03 17β-Estradiol 50-28-2 0.20-2.1 (28) 

 >100 (below LOQ; 1

of 12 tap water 

samples over 

several months) 

(29) 

ND (DL=1) (5) 

ND (MRL=0.50) (18 samples) <MRL (15 samples) (8) 

G03CA07 Estrone 53-16-7 1.1-2.3 (5) 

0.2-0.6 (28) 

 1.7 (mean 3 tap 

water samples) 

(6) 

1 (1 of 5 DWTPs; but not in 

raw water) 

 (30) 

ND (MRL=0.20) (18 samples) <MRL (15 samples) (8) 

<70 (below LOQ; 2 

of 12 tap water 

samples over 

several months) 

(29) 

G03CA07 

metabolite 

Estrone-3-sulfate 481-97-0 0.22 (post ozonation, but ND 

after GAC) 

 (31) 

G03DA04 Progesterone 57-83-0 1.1 (2 of 20 locales) (5) 

0.57 (1 of 18 samples) <MRL (15 samples) (8) 
F-4 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

G03 Estrogens: 

Estradiol (E2) 

Estriol (E3) 

Estrone (E1)

Estradiol-17-glucuronide 

Estrone-3-sulfate 

Estradiol-17-acetate

Ethynylestradiol (EE2) 

Diethylstilbestrol (DES)

ND (< LOQs): 

<0.59 

<1.02 

<0.18 

<1.02 

<0.02 

<0.23 

<0.83 

<0.21

(31) 

Antiinfectives for Systemic Use: J01 Antibacterials 

J01AA02 Doxycycline 564-25-0 ND (DL=50-150) (2) 

J01AA06 Oxytetracycline 79-57-2 ND (DL=50-150) (2) 

J01AA07 

(multiple) 

Tetracycline 60-54-8 ND (DL=50-150) (2) 

J01DD04 Ceftriaxone 73384-59-5 ND (DL=1.80) (3) 

J01EA01 Trimethoprim 738-70-5 1.3 (1 of 20 locales) (5) 

ND (RL=0.25) (10) 

ND (DL=5-60) (2) 

ND (MRL=0.25) (18 samples) <MRL (15 samples) (8) 

J01EB02 

(multiple) 

Sulfamethizole 144-82-1 9 (1 of 8 bottled waters) (32) 

ND (DL=5-75) (2) 

J01EB03 Sulfamethazine 

(Sulfadimidine) 

57-68-1 ND (DL=5-75) (2) 

J01EB04 Sulfapyridine 144-83-2 ND (DL=5-75) (2) 

J01EB05 

S01AB02 

Sulfisoxazole 

(Sulfafurazole) 

127-69-5 ND (DL=5-75) (2) 

J01EB07 

D06BA02 

Sulfathiazole 72-14-0 ND (DL=5-75) (2) 

J01EB Sulfabenzamide 127-71-9 ND (DL=5-75) (2) 

J01EC01 Sulfamethoxazole 723-46-6 3.0-3.4 (2 of 3 DWTPs) (33) 

13-80 (2 of 8 bottled waters) (32) 

2 (after carbon sorption) (34) 

14 (17) 

20 (1 of 20 locales) (5) 

3.0 [0.39] (4 of 18 samples) 0.32 (1 of 15 

samples) 

(8) 

0.3-0.5 (2 of 4 samples) (18) 

2.0-5.0 (1 of 5 DWTPs) (23) 

[0.39] max=3.0 (3 of 20 

DWTPs) 

 (9) 

<25 (2 of 22 samples) (19) 

19-25 [22] (4 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

ND (RL=0.25) (10) 

ND (DL=5-75) (2) 

ND (DL=10) (11) 

J01EC02 Sulfadiazine 68-35-9 ND (DL=5-75) (2) 

J01EC03 Sulfamoxole 729-99-7 ND (DL=5-75) (2) 
F-5 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

J01ED01 Sulfadimethoxine 122-11-2 11 (1 of 8 bottled waters) (32) 

7.0 (1 of 5 DWTPs) (23) 

ND (DL=5-75) (2) 

ND (DL=10) (11) 

J01ED04 Sulfameter 

(Sulfametoxydiazine) 

651-06-9 ND (DL=5-75) (2) 

J01ED05 Sulfamethoxypyridazine 80-35-3 ND (DL=5-75) (2) 

J01ED07 

D06BA06 

Sulfamerazine 127-79-7 ND (DL=5-75) (2) 

J01FA01 

(multiple) 

Erythromycin 114-07-8 1.3 (5) 

4.9 (1 of 3 DWTPs) (33) 

ND (DL=10) (11) 

ND (DL=0.03) (3) 

J01FA01 

metabolite 

Erythromycin-H20 114-07-8? ND (DL=10) (11) 

J01FA02 Spiramycin 8025-81-8 ND (DL=0.75) (3) 

J01FA05 Oleandomycin 3922-90-5 ND (DL=0.02) (3) 

J01FA06 Roxithromycin 80214-83-1 1.4 (1 of 3 DWTPs) (33) 

ND (DL=10-150) (2) 

J01FF02 Lincomycin 154-21-2 ND (DL=0.02) (3) 

ND (DL=10) (11) 

J01MA01 Ofloxacin 82419-36-1 0.7-1.6 (2 of 4 samples) (18) 

ND (DL=20-100) (2) 

J01MA06 Norfloxacin 70458-96-7 ND (DL=20-100) (2) 

J01MB04 Pipemidic acid 51940-44-4 ND (DL=20-100) (2) 

J01MB05 Oxolinic acid 14698-29-4 2.9-4 (2 of 3 DWTPs) (33) 

ND (DL=20-100) (2) 

J01MB07 Flumequine 42835-25-6 1.2-2.5 (3 of 3 DWTPs) (33) 

J01 Novobiocin 303-81-1 ND (DL=10-150) (2) 

J01 (misc) Sulfonamides (misc)c: 

p-Toluenesulfonamide 

o-Toluenesulfonamide 

Benzenesulfonamide 

70-55-3 

88-19-7 

98-10-2 

up to (95-percentile): 240 

160 

60 

 (35) 

Antibiotics Absence of 18 of 24 in three DWTPs (with all 

LODs 3 ng/L or lower, except for minocycline 

[LOD=6ng/L]). 

 (33) 

Survey of 28 antibiotics in Australia showed 

frequent occurrence in all waters (up to 64 

μg/L in sewage influent) but absence of all 

28 in drinking waters from 20 different sites 

(with LODs for 21 of the analytes being 20 

ng/L or lower). 

(36) 

L01 

Antineo plastic

Agents 

L01AA01 Cyclophosphamide 50-18-0 ND (DL=0.02) (3) 

ND (DL=5-60) (2) 
F-6 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

Musculo-skeletal System: M01 Antiinflammatory & Antirheumatic Products 

M01AB01 Indometacin 

(Indomethacin) 

53-86-1 ND (DL=3-90) (2) 

M01AB05 

(multiple) 

Diclofenac 15307-86-5 up to 6 (8 of 30 samples) 

(DL=1) 

 (15) 

up to 6 (8 of 25 samples) 

(DL=1) 

 (16) 

 up to 2.5 (6 tap 

water samples) 

(24) 

14-18 [16] (2 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

ND (RL=0.25) (10) 

ND (MRL=0.25) (18 

samples) 

ND (MRL=0.25) (15 

samples) 

(8) 

ND (DL=1) (5) 

ND (DL=3-90) (2) 

ND (DL=1.2; 3 tap 

water samples) 

(6) 

M01AE01 Ibuprofen 15687-27-1 510-1,350 [930] (2 of 15 

samples) (MDL=280) 

 (13) 

18-23 (37) 

up to 8.5 (38) 

up to 3 (3 of 30 samples) 

(DL=1) 

 (15) 

up to 3 (3 of 25 samples) 

(DL=1) 

 (16) 

2.7 (22) 

1-32 (5) 

up to 39 (20) 

up to 112 (25) 

2.2-3.0 (39) 

up to 0.6 (6 tap water

samples) 

 (24) 

28 (1 of 44 samples; 22 

DWTPs over 2 years) 

 (7) 

3.4 (mean 3 tap water 

samples) 

 (6) 

ND (DL=0.50) (3) 

ND (DL=3-90) (2) 

M01AE01 

metabolite 

Ibuprofen methyl ester 81576-55-8 4,950 

(1 of 15 samples) (MDL=110) 

 (13) 

M01AE02 

M02AA12 

Naproxen 22204-53-1 up to 7.5 (38) 

8 (5) 

3.0 (1 of 5 DWTPs) (23) 

up to 1 (25) 

up to 0.2 (6 tap water

samples) 

 (24) 

ND (DL=0.4) (40) 

ND (RL=0.50) (10) 

ND (MRL=0.50) (18 

samples) 

<MRL (15 samples) (8) 
F-7 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

ND (DL=2.1; 3 tap 

water samples) 

(6) 

M01AE03 Ketoprofen 22071-15-4 up to 3.0 (6 tap 

water samples) 

(24) 

ND (DL=3-90) (2) 

ND (DL=8) (38) 

M01AE04 Fenoprofen 31879-05-7 ND (DL=3-90) (2) 

M01AG01 Mefenamic acid 61-68-7 up to 19.8 [0.9] (RO DWTP) (4) 

up to 19.9 [1.9] (NF DWTP) (4) 

Nervous System: N02 Analgesics; N03 Antiepileptics; N05 Psycholeptics; N06 Psychoanaleptics; N07 Other Nervous System Drugs 

N02BA01 

A01AD05 

Acetylsalicylic acid 50-78-2 >50 (17) 

>50, <100 (2 of 22 samples) (19) 

N02BB01 Phenazone (Antipyrine) 60-80-0 50 (1 of 12 samples) (DL=10) (15) 

400 (41) 

250 (42) 

11-29 [21] (8 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

N02BB04 Propyphenazone 

(Isopropyl-antipyrine ) 

479-92-5 120 (41) 

80 (42) 

N02BE01 Acetaminophen 

(Paracetamol) 

103-90-2 0.3-3 (2 of 12 samples) (11) 

1.1-1.3 [3 of 10 brands of 

bottled water] 

 (43) 

 up to 210.1 (6 tap 

water samples) 

(24) 

33 (1 of 44 samples; 22 

DWTPs over 2 years) 

 (7) 

N03AA03 Primidone (2-

Deoxypheno­ barbital) 

125-33-7 up to 16 (44) 

0.7-1.3 (4 of 4 samples) (45) 

N03AB02 Dilantin (Phenytoin) 57-41-0 1.1-1.2 (22) 

[1.3] (10) 

1.6-13 (5) 

19 [6.2] (10 of 18 samples) 16 [3.6] (10 of 15 

samples) 

(8) 

[9.4] max=32 (15 of 20 

DWTPs) 

 (9) 

1-2 (3 of 4 samples) (45) 

N03AF01 Carbamazepine 298-46-4 0.3-2.0 (46) 

258 max (12) 

5.3-7.5 (37) 

6.5-24 (3 of 10 DWTPs) (2) 

up to 20 ng/L (44) 

2 (after ozonation) (34) 

1.1-5.7 (5) 

[29] max=140 (12 of 12 

samples) 

 (11) 

23 (17) 

18 [6.0] (8 of 18 samples) 10 [6.8] (6 of 15 

samples) 

(8) 

0.8-135 (2 of 4 samples) (18) 

2.0-7.0 (3 of 5 DWTPs) (23) 

2.9-721 (20) 
F-8 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

[5.0] max=9.1 (21) 

up to 1.8 [1.2] (RO DWTP) (4) 

0.5-5.7 [1.0] (NF DWTP) (4) 

[5.4] max=18 (12 of 20 

DWTPs) 

 (9) 

 up to 43.2 (6 tap 

water samples) 

(24) 

10-25 [17] (4 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

 >0.7, LOD (3 tap 

water samples) 

(6) 

ND (RL=0.50) (10) 

30 (1 of 12 samples) (DL=10) (15) 

<25 (1 of 22 samples) (19) 

N03AF01 

metabolite 

10,11-Dihydroxy­ 10,11-

dihydro­ carbamazepine

125-28-0 up to 13 (44) 

N05AX08 Risperidone 106266-06-2 ND (MRL=2.5) (18 samples) 2.9 (1 of 15 

samples) 

(8) 

 ND (RL=0.25) (10) 

N05BA01 Diazepam 439-14-5 0.33 [0.33] (1 of 18 samples) <MRL (15 samples) (8) 

19.3-23.5 (1 of 3 DWTPs) 

(DL=0.02) 

 (3) 

ND (RL=0.25) (10) 

ND (DL=1) (5) 

ND (LOD=0.4; 6 tap

water samples) 

(24) 

N05BA16 Nordazepam 1088-11-5 ND (LOD=0.4; 6 tap

water samples) 

(24) 

N05BC01 Meprobamate 

(also a metabolite of 

the prodrug 

carisoprodol) 

57-53-4 1.6-13 (5) 

[5.9] (10) 

6.5-8 (22) 

42 [5.7] (14 of 18 samples) 40 [5.2] (11 of 15 

samples) 

(8) 

[9.2] max=43 (17 of 20 

DWTPs) 

 (9) 

6.3-9.4 (4 of 4 samples) (45) 

N06AA02 Imipramine 50-49-7 ND (LOD=0.7; 6 tap

water samples) 

(24) 

N06AA09 Amitriptyline 50-48-6 up to 1.4 (6 tap 

water samples) 

(24) 

N06AA12 Doxepin 1668-19-5 ND (LOD=0.7; 6 tap

water samples) 

(24) 

N06AB03 Fluoxetine 54910-89-3 0.82 [0.71] (2 of 18 samples) 0.64 (1 of 15 

samples) 

(8) 

1.0 (1 of 5 DWTPs) (23) 

10 (1 of 44 samples; 22 

DWTPs over 2 years) 

 (7) 

ND (DL=1) (5) 

ND (DL=14) (11) 

ND (DL=5-60) (2) 
F-9 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

ND (RL=0.50) (10) 

N06AB03 

metabolite 

Norfluoxetine 56161-73-0 ND (RL=0.50) (10) 

ND (DL=5-60) (2) 

ND (MRL=0.50) (18 

samples) 

0.77 (1 of 15 

samples) 

(8) 

N07BC02 Methadone 76-99-3 0.1-2.6 (47) 

N07BC02 

metabolite 

EDDP 

(methadone metabolite)

[2-Ethylidene-1,5­

dimethyl-3,3­

diphenylpyrrolidine] 

30223-73-5 1.7-4.7 (47) 

Veterinary: QJ01 Antibacterials for Systemic Use; QP51 Antiprotozoals 

QJ01EQ08 Sulfaphenazole 526-08-9 ND (DL=5-75) (2) 

QJ01EQ12 Sulfachlorpyridazine 80-32-0 ND (DL=5-75) (2) 

QJ01FA90 Tylosin 1401-69-0 0.6-1.7 (1 of 3 DWTPs) 

(DL=0.25) 

 (3) 

4.2 (1 of 3 DWTPs) (33) 

QJ01FA91 Tilmicosin 108050-54-0 ND (DL=0.75) (3) 

QP51AG03 Sulfaquinoxaline 59-40-5 ND (DL=5-75) (2) 

QP51AH03 Monensin 17090-79-8 0.1-2.8 (3 of 5 DWTPs) (23) 

Respiratory System: R03 Obstructive Airway Diseases 

R03AC02 Albuterol (Salbutamol) 18559-94-9 ND (DL=0.02) (3) 

ND (6 tap water samples) (24) 

R03AC03 Terbutaline 23031-25-6 ND (6 tap water samples) (24) 

R03AC14 

R03AC13 

Clenbuterol ND (LOD=0.6; 6 tap 

water samples) 

(24) 

Sensory Organs: S01 Ophthalmologicals 

S01AB04 Sulfacetamine 

(Sulfacetamide) 

144-80-9 ND (DL=5-75) (33) (2) 

Various: V08 Contrast Media 

V08AA01 

Diatrizoate (Diatrizoic 

acid; Amidotrizoic acid)

117-96-4 85 max [21] (5 of 10 samples) 

(DL=10) 

 (15) 

32 (34) 

60 (48) 

18-100 (3 of 3 DWTPs) (30) 

129-149 (49) 

V08AA04 Iotalamic acid 

(Iothalamic acid) 

2276-90-6 10 (48) 

ND (DL=4) (34) 

V08AA05 Ioxitalamic acid 28179-44-4 12 (34) 

ND (4 of 4 DWTPs) (DL=25) (30) 

V08AB02 Iohexol 66108-95-0 57 (1 of 44 samples; 22 DWTPs

over 2 years) 

 (7) 

38-40 (49) 

Iohexol 

transformation

product 

83 (50) 

V08AB04 Iopamidol 60166-93-0 

62883-00-5 

244 (50) 

up to 79 (4 of 10 samples) (15) 
F-10 

EXHIBIT F-1. COMPILATION OF PUBLISHED POSITIVE OCCURRENCE DATA FOR APIs IN FINISHED DRINKING WATER (AND SELECT DATA ON 

NEGATIVE OCCURRENCE – INDICATED BY SHADED CELLS) 

ATC NAMEa ATC CODEa API (SYNONYM) CAS RN 

FINISHED DRINKING WATER, 

NG/L [MEDIAN]b

DISTRIBUTION 

WATER (NG/L) REFERENCE 

(DL=10) 

60 (34) 

70 (48) 

180 (1 of 4 DWTPs) (DL=25) (30) 

72-98 (49) 

Iopamidol

transformation

product 

57 (50) 

V08AB05 Iopromide 73334-07-3 up to 177 (37) 

86 (1 of 10 samples) (DL=10) (15) 

1.1-31 (5) 

4.6 (22) 

40 (48) 

33-36 [35] (2 of 44 samples; 

22 DWTPs over 2 years) 

 (7) 

29 (1 of 4 DWTPs) (DL=10) (30) 

69-77 (49) 

ND (DL=4) (34) 

V08AB10 Iomeprol 78649-41-9 11 (34) 

81-92 (49) 

12 (1 of 4 DWTPs) (DL=10) (30) 

Iomeprol 

transformation

product 

18 and 289 (50) 

Schedule I & II ControlledSubstances 

illicit (also: 

N01BC01) 

(multiple)

Cocaine 50-36-2 ND (after ozonation & GAC) 

(LOD <80 pg/L) 

(51) 

illicit (also: 

N01BC01) 

(metabolite)

Benzoylecgonine 

(primary metabolite of 

cocaine) 

519-09-5 [45] with max of 130 (22 of 

24 samples 

 (51) 

illicit MDMA (ecstasy: 3,4­

methylenedioxymethamphetamine) 

69610-10-2 2-10 (after ozonation & GAC) 

ND (after post-chlorination) 

 (51) 

Notes: 

a. ATC/DDD Index (Anatomical Therapeutic Chemical) classification system: http://www.whocc.no/atcddd/; AT vet Index: 

http://www.whocc.no/atcvet/database/index.php. 

b. DL: detection limit; GAC: granular activated carbon; LOD: limit of quantitation; max: maximum value in range; NF: nanofiltration; ND: not 

detected (less than DL or RL); (M)RL: (method) reporting limit; RO: reverse osmosis. 

c. Richter et al. (67) provide an overview of the work done in Germany since the 1990s on a series of sulfonamides [p­ toluenesulfonamide (pTSA), o-toluenesulfonamide (o-TSA), and benzenesulfonamide (BSA)], which have had a steady presence in certain areas such as Berlin, which 

rely on ground waters recharged by rivers; their concentrations in ground waters reach up into the low μg/L range. The sources of these 

sulfonamides in the environment are not solely from antimicrobials (e.g., p-TSA is the primary degradation product of the disinfectant 

chloramine-T), as they also have a wide variety of other non- pharmaceutical uses. Richter et al. (67) provide some of the only data on finished

drinking water for p-TSA, o-TSA, and BSA, which are detected at ng/L concentrations (95th percentile) up to 240, 160, and 60, respectively. 

Source: Daughton CG "Pharmaceutical Ingredients in Drinking Water: Overview of Occurrence and Significance of Human Exposure," In: 

Contaminants of Emerging Concern in the Environment: Ecological and Human Health Considerations, Rolf Halden (Ed.), ACS Symposium Series 

1048, American Chemical Society: Washington, D.C., Chapter 2, p 9-68, 2 November 2010; DOI: 10.1021/bk-2010-1048.ch002; pre-publication 

version: http://www.epa.gov/esd/bios/daughton/ACS-SS1048-2010.pdf. 
F-11 

REFERENCES 

(1) Stan, H. J.; Heberer, T.; Linkerhägner, M. Vom Wasser 1994, 83, 57-68. 

(2) Tauber, R. Quantitative analysis of pharmaceuticals in drinking water from ten Canadian cities, 2003, 

Enviro-Test Laboratories/Xenos Division, Ontario, Canada, pp 1-6, 

http://www.ctv.ca/servlet/ArticleNews/story/CTVNews/20030209/drugs_water030209/. 

(3) Zuccato, E.; Calamari, D.; Natangelo, M.; Fanelli, R. The Lancet 2000, 355, 1789-1790. 

(4) Radjenovic, J.; Petrovic, M.; Ventura, F.; Barceló, D. Water Res. 2008, 42, 3601-3610. 

(5) Snyder, S. A.; Lei, H.; Wert, E. C. In Fate of Pharmaceuticals in the Environment and in Water Treatment 

Systems; Aga, D. S., Ed.; CRC Press: Boca Raton, FL, 2007, p 229-260. 

(6) Yu, Z.; Peldszus, S.; Huck, P. M. J. Chromatogr. A 2007, 1148, 65-77. 

(7) Versteegh, J. F. M.; van der Aa, N. G. F. M.; Dijkman, E. Geneesmiddelen in drinkwater en 

drinkwaterbronnnen: Resultaten van het meetprogramma 2005/2006 [Pharmaceuticals in drinking water 

and resources for drinking water: Results of the measurement program 2005/2006], 2007, RIVM report 

703719016/2007, Rijksinstituut voor Volksgezondheid en Milieu RIVM, Bilthoven, The Netherlands, pp 53, 

http://hdl.handle.net/10029/16416 or http://www.rivm.nl/bibliotheek/rapporten/703719016.html. 

(8) Benotti, M. J.; Trenholm, R. A.; Vanderford, B. J.; Holady, J. C.; Stanford, B. D.; Snyder, S. A. Environ. Sci. 

Technol. 2009, 43, 597-603. 

(9) Snyder, S. A. Ozone: Sci. Eng. 2008, 30, 65-69. 

(10) Vanderford, B. J.; Snyder, S. A. Environ. Sci. Technol. 2006, 40, 7312-7320. 

(11) Stackelberg, P. E.; Gibs, J.; Furlong, E. T.; Meyer, M. T.; Zaugg, S. D.; Lippincott, R. L. Sci. Total Environ. 

2007, 377, 255-272. 

(12) Stackelberg, P. E.; Furlong, E. T.; Meyer, M. T.; Zaugg, S. D.; Henderson, A. K.; Reissman, D. B. Sci. Total 

Environ. 2004, 329, 99-113. 

(13) Loraine, G. A.; Pettigrove, M. E. Environ. Sci. Technol. 2006, 40, 687-695. 

(14) Heberer, T.; Stan, H. J. Int. J. Environ. Anal. Chem. 1997, 67, 113-124. 

(15) Ternes, T. In Pharmaceuticals and personal care products in the environment: Scientific and regulatory 

issues; Daughton, C. G., Jones-Lepp, T. L., Eds.; American Chemical Society: Washington, DC, 2001, p 39-

54. 

(16) Stumpf, M.; Ternes, T. A.; Haberer, K.; Seel, P.; Baumann, W. Vom Wasser 1996, 86, 291-303. 

(17) Versteegh, J. F. M.; Stolker, A. A. M.; Niesing, W.; Muller, J. J. A. Geneesmiddelen in drinkwater en 

drinkwaterbronnen [Pharmaceuticals in drinking water and sources for drinking water], 2003, RIVM 

rapport 703719004, pp 45, http://www.rivm.nl/bibliotheek/rapporten/703719004.html. 

(18) Chen, M.; Ohman, K.; Metcalfe, C.; Ikonomou, M. G.; Amatya, P. L.; Wilson, J. Water Qual. Res. J. Can. 

2006, 41, 351-364. 

(19) Stolker, A. A. M.; Niesing, W.; Hogendoorn, E. A.; Versteegh, J. F. M.; Fuchs, R.; Brinkman, U. A. T. Anal. 

Bioanal. Chem. 2004, 378, 955-963. 

(20) Kormos, J. L. Masters dissertation, University of Waterloo, Waterloo, Ontario, Canada, 2007, 

http://uwspace.uwaterloo.ca/bitstream/10012/2774/1/MSc%20Thesis%20JKormos%20Fin al.pdf. 

(21) Loos, R.; Wollgast, J.; Huber, T.; Hanke, G. Anal. Bioanal. Chem. 2007, 387, 1469-78. 

(22) Trenholm, R. A.; Vanderford, B. J.; Holady, J. C.; Rexing, D. J.; Snyder, S. A Chemosphere 2006, 65, 1990-

1998. 

(23) Illinois EPA Report on Pharmaceuticals and Personal Care Products in Illinois Drinking Water Bureau of 

Water, Illinois EPA, June 2008, 2008, Bureau of Water, Illinois,

http://www.epa.state.il.us/water/pharmaceuticals-in-drinking-water.pdf. 

(24) Togola, A.; Budzinski, H. J. Chromatogr. A 2008, 1177, 150-158. 

(25) Servos, M. R.; Smith, M.; McInnis, R.; Burnison, K.; Lee, B.-H.; Seto, P.; Backus, S. Water Qual. Res. J. 

Can. 2007, 42, 130-137. 

(26) TCC Consortium IUCLID Data Set: Triclocarban (International Uniform Chemical Information Database), 

2002, Soap and Detergent Association, New York, NY, pp 44, 

http://www.epa.gov/chemrtk/pubs/summaries/tricloca/c14186rs.pdf. 

(27) Aherne, G. W.; Briggs, R. J. Pharm. Pharmacol. 1989, 41, 735-736. 

(28) Kuch, H. M.; Ballschmiter, K. Environ. Sci. Technol. 2001, 35, 3201-3206. 
F-12 

(29) Sodré, F.; Locatelli, M.; Jardim, W. Water, Air, Soil Pollut. 2010, 206, 57-67. 

(30) Wenzel, A.; Müller, J.; Ternes, T. Study of endocrine disrupters in drinking water, 2003, Final Report 

ENV.D.1/ETU/2000/0083, Fraunhofer Institute for Molecular Biology and Applied Ecology, Schmallenberg, 

Germany, http://ec.europa.eu/research/endocrine/pdf/drinking_water_en.pdf. 

(31) Rodriguez-Mozaz, S.; de Alda, M. J. L.; Barcelo, D. Anal. Chem. 2004, 76, 6998-7006. 

(32) Perret, D.; Gentili, A.; Marchese, S.; Greco, A.; Curini, R. Chromatographia 2006, 63, 225-232. 

(33) Ye, Z.; Weinberg, H. S.; Meyer, M. T. Anal. Chem. 2007, 79, 1135-1144. 

(34) Bruchet, A.; Hochereau, C.; Picard, C.; Decottignies, V.; Rodrigues, J. M.; Janex-Habibi, M. L. Water Sci. 

Technol. 2005, 52, 53-61. 

(35) Richter, D.; Massmann, G.; Dünnbier, U. Water Res. 2008, 42, 1369-1378. 

(36) Watkinson, A. J.; Murby, E. J.; Kolpin, D. W.; Costanzo, S. D. Sci. Total Environ. 2009, 407, 2711-2723. 

(37) Kim, S. D.; Cho, J.; Kim, I. S.; Vanderford, B. J.; Snyder, S. A. Water Res. 2007, 41, 1013-1021. 

(38) Vieno, N. M.; Tuhkanen, T.; Kronberg, L. Environ. Sci. Technol. 2005, 39, 8220-8226. 

(39) Skadsen, J. M.; Rice, B. L.; Meyering, D. J. The Occurrence and Fate of Pharmaceuticals, Personal Care 

Products and Endocrine Disrupting Compounds in a Municipal Water Use Cycle: A Case Study in the City 

of Ann Arbor, 2004, City of Ann Arbor, Water Utilities, Fleis & VandenBrink Engineering, Inc., pp 22, 

http://www.a2gov.org/government/publicservices/water_treatment/Documents/EndocrineDisruptors.pdf

(40) Boyd, G. R.; Reemtsma, H.; Grimm, D. A.; Mitra, S. Sci. Total Environ. 2003, 311, 135- 149. 

(41) Reddersen, K.; Heberer, T.; Dunnbier, U. Chemosphere 2002, 49, 539-544. 

(42) Zuhlke, S.; Dunnbier, U.; Heberer, T. J. Chromatogr. A 2004, 1050, 201-209. 

(43) Naidenko, O.; Leiba, N.; Sharp, R.; Houlihan, J. EWG Research: Bottled Water Quality Investigation: 10 

Major Brands, 38 Pollutants. Bottled water contains disinfection byproducts, fertilizer residue, and pain 

medication, 2009, pp 33, http://www.ewg.org/reports/bottledwater, http://www.ewg.org/node/27011. 

(44) Hummel, D.; Loffler, D.; Fink, G.; Ternes, T. A. Environ. Sci. Technol. 2006, 40, 7321- 7328. 

(45) Trenholm, R. A.; Vanderford, B. J.; Snyder, S. A. Talanta 2009, 79, 1425-1432. 

(46) Hua, W.; Bennett, E. R.; Letcher, R. J. Water Res. 2006, 40, 2259-2266. 

(47) Boleda, M. R.; Galceran, M. T.; Ventura, F. Water Res. 2009, 43, 1126-1136. 

(48) Hirsch, R.; Ternes, T. A.; Lindart, A.; Haberer, K.; Wilken, R. D. Fresenius' J. Anal. Chem. 2000, 366, 835-

841. 

(49) Seitz, W.; Jiang, J. Q.; Weber, W. H.; Lloyd, B. J.; Maier, M.; Maier, D. Environ. Chem. 2006, 3, 35-39. 

(50) Kormos, J. L.; Schulz, M.; Wagner, M.; Ternes, T. A. Anal. Chem. 2009, 81, 9216-9224. 

(51) Huerta-Fontela, M.; Galceran, M. T.; Ventura, F. Environ. Sci. Technol. 2008, 42, 6809- 6816.