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EPA
EPA Document# EPA-740-R1-8007
June 2019
United States Office of Chemical Safety and Pollution Prevention
Environmental Protection Agency
Draft Risk Evaluation for
1,4-Dioxane
CASRN: 123-91-1
June 2019
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TABLE OF CONTENTS
1 EXECUTIVE SUMMARY 18
2 INTRODUCTION 22
2.1 Physical and Chemical Properties 24
2.2 Uses and Production Volume 25
2.3 Regulatory and Assessment History 26
2.4 Scope of the Evaluation 28
2.4.1 Conditions of Use Included in the Risk Evaluation 28
2.4.2 Conceptual Models 32
2.5 Sy stemati c Revi ew 36
2.5.1 Data and Information Collection 36
2.5.2 Data Evaluation 42
2.5.3 Data Integration 42
3 EXPOSURES 43
3.1 Fate and Transport 43
3.2 Environmental Releases 46
3.3 Environmental Exposures 46
3.3.1 Environmental Exposures - Aquatic Pathway 46
3.4 Human Exposures 47
3.4.1 Occupational Exposures 47
3.4.1.1 Occupational Exposures Approach and Methodology 48
3.4.1.2 Manufacturing 54
3.4.1.3 Import and Repackaging 55
3.4.1.4 Recycling 57
3.4.1.5 Industrial Uses 58
3.4.1.6 Functional Fluids (Open System) 60
3.4.1.7 Functional Fluids (Closed System) 63
3.4.1.8 Laboratory Chemicals 63
3.4.1.9 Film Cement 65
3.4.1.10 Spray Foam Application 67
3.4.1.11 Printing Inks (3D) 70
3.4.1.12 Dry Film Lubricant 71
3.4.1.13 Disposal 73
3.4.1.14 Dermal Exposure Assessment 74
4 HAZARDS (EFFECTS) 79
4.1 Ecological Hazards 79
4.1.1 Approach and Methodology 79
4.1.2 Hazard Identification- Toxicity to Aquatic Organisms 80
4.2 Human Health Hazards 80
4.2.1 Approach and Methodology 80
4.2.2 Toxicokinetics 82
4.2.3 Hazard Identification 85
4.2.3.1 Non-Cancer Hazards 85
4.2.3.2 Genetic Toxicity and Cancer Hazards 92
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4.2.4 Potential Modes of Action for 1,4-Dioxane Toxicity 98
4.2.5 Evidence Integration and Evaluation of Human Health Hazards 105
4.2.6 Dose-Response Assessment 108
4.2.6.1 Potentially Exposed or Susceptible Subpopulations 108
4.2.6.2 Points of Departure for Human Health Hazard Endpoints 108
4.2.6.2.1 Acute/Short-term POD for Inhalation Exposures 109
4.2.6.2.2 Acute/Short-term POD for Dermal Exposures extrapolated from
Inhalation Studies 110
4.2.6.2.3 Chronic Non-Cancer POD for Inhalation Exposures Ill
4.2.6.2.4 Chronic Cancer Unit Risk for Inhalation Exposures i.e. Inhalation Unit
Risk (II R) 115
4.2.6.2.5 Chronic Non-Cancer POD for Dermal Exposures extrapolated from Chronic
Inhalation Studies 117
4.2.6.2.6 Chronic Non-Cancer POD for Dermal Exposures extrapolated from Chronic
Oral Studies 119
4.2.6.2.7 Chronic Cancer Unit Risk for Dermal Exposures i.e. Cancer Slope Factor (CSF)
extrapolated from Chronic Inhalation Studies 122
4.2.6.2.8 Chronic Cancer Unit Risk for Dermal Exposures i.e. Cancer Slope Factor (CSF)
extrapolated from Chronic Oral Studies 123
4.2.7 Summary of Human Health Hazards 128
5 RISK CHARACTERIZATION 130
5.1 Environmental Ri sk 130
5.1.1 Aquatic Pathways 130
5.2 Human Health Ri sk 131
5.2.1 Human Health Risk Estimation Approach 131
5.2.2 Risk Estimation for Effects Acute/Short-term Inhalation Exposures 135
5.2.3 Risk Estimation for Non-Cancer Effects Following Chronic Inhalation Exposures 136
5.2.4 Risk Estimation for Cancer Effects Following Chronic Inhalation Exposures 139
5.2.5 Risk Estimation for Non-Cancer Effects Following Acute/Short-term Dermal Exposures 142
5.2.6 Risk Estimation for Non-Cancer Effects Following Chronic Dermal Exposures 143
5.2.7 Risk Estimation for Cancer Effects Following Dermal Exposures 144
5.3 Assumptions and Key Sources of Uncertainty 145
5.3.1 Occupational Exposure Assumptions and Uncertainties 145
5.3.2 Environmental Hazard and Exposure Assumptions and Uncertainties 148
5.3.3 Human Health Hazard Assumptions and Uncertainties 148
5.3.4 Risk Characterization Assumptions and Uncertainties 150
5.4 Potentially Exposed or Susceptible Subpopulations 152
5.5 Aggregate and Sentinel Exposures 153
6 RISK DETERMINATION 151
6.1 Unreasonable Risk 152
6.1.1 Overview 152
6.1.2 Risks to Human Health 154
6.1.2.1 Determining Non-Cancer Risks 154
6.1.2.2 Determining Cancer Risks 154
6.1.3 Determining Environmental Risk 156
6.2 Risk Determination for 1,4-Dioxane 155
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7 REFERENCES 176
APPENDICES 190
Appendix A REGULATORY HISTORY 190
A. 1 Federal Laws and Regulations 190
A.2 State Laws and Regulations 195
A. 3 International Laws and Regulations 196
Appendix B EXPOSURE SCENARIO MAPPING TO COU 198
Appendix C LIST OF SUPPLEMENTAL DOCUMENTS 210
Appendix D FATE AND TRANSPORT 211
Appendix E ENVIRONMENTAL EXPOSURES 213
Appendix F ENVIRONMENTAL HAZARDS 221
F. 1 Systematic Review 221
F.2 Hazard Identification- Aquatic 222
F.3 Concentrations of Concern (COC) 223
F.3.1 COC for Acute Aquatic Toxicity 223
F.3.2 COC for Chronic Aquatic Toxicity 224
Appendix G OCCUPATIONAL EXPOSURES 224
G. 1 Systematic Review Summary Tables 224
G. 1.1 Evaluation of Inhalation Data Sources Specific to 1,4-Dioxane 224
G. 1.2 Evaluation of Cross-Cutting Data Sources 230
G.2 Equations for Calculating Acute and Chronic Inhalation Exposures 232
G.3 Sample Calculations for Calculating Acute and Chronic Inhalation Exposures 237
G.3.1 Example High-End ADC and LADC 238
G.3.2 Example Central Tendency ADC and LADC 238
G.4 Modeling Approach and Parameters for High-End and Central Tendency Inhalation Exposure
Estimates for Import and Repackaging, Functional Fluids (Open System), Spray Foam Application,
and Disposal 239
G.4.1 Model Design Equations 240
G.4.2 Model Parameters 242
G.4.3 Sample Monte Carlo Simulation Result 245
G.5 Approach for Estimating the Number of Workers 245
G.6 Occupational Exposure Scenario Grouping 251
G.6.1 Manufacturing 253
G.6.2 Import and Repackaging 257
G.6.3 Industrial Uses 260
G.6.4 Functional Fluids (Open System) 264
G.6.5 Laboratory Chemical Use 268
G.6.6 Film Cement 270
G.6.7 Spray Foam Application 272
G.6.8 Printing Inks (3D) 276
G.6.9 Dry Film Lubricant 277
G.6.10 Disposal 281
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G.7 Dermal Exposure Assessment Method ....288
G.7.1 Incorporating the Effects of Evaporation 288
G.7.2 Calculation of fabs 289
G.7.3 Potential for Occlusion 292
G.7.4 Incorporating Glove Protection 293
G.7.5 Proposed Dermal Dose Equation 294
Appendix H HUMAN HEALTH HAZARDS 295
H. 1 Hazard and Data Quality Summary Tables by study duration/endpoint.... ..295
H. 1.1 Hazard and Data Evaluation Summary for Human Studies 295
H. 1.2 Hazard and Data Quality Evaluation Summary for Acute and Short-Term Studies 296
H. 1.3 Hazard and Data Evaluation Summary for the Developmental Toxicity Study 298
H. 1.4 Hazard and Data Evaluation Summary for Subchronic and Chronic Non-Cancer Studies. .298
H. 1.5 Hazard and Data Evaluation Summary for Genotoxicity Studies 303
H. 1.6 Data Evaluation Summary for Chronic Cancer Studies 308
H. 1.7 Data Evaluation Summary for Mechanistic Studies 317
H.1.8 Hazard Data Tables 325
Appendix I BENCHMARK DOSE ANALYSIS 331
I.1 BMDS Summary of Centrilobular necrosis of the liver in male F344/DuCrj rats {Kasai, 2009,
193803}.... 335
1.2 BMDS Summary of Squamous cell metaplasia of respiratory epithelium in male F433/DuCrj
rats {Kasai, 2009, 193803} ' ..338
1.3 BMDS Summary of Squamous cell hyperplasia of respiratory epithelium in male F433/DuCrj
rats (Kasai, 2009, 193803} 340
1.4 Benchmark dose analysis of respiratory metaplasia of the olfactory epithelium in the nasal
cavity of male F344/DuCrj rats {Kasai, 2009, 193803} .....343
1.5 BMDS Summary of Hydropic change (lamina, propria) {Kasai, 2009, 193803} .351
1.6 BMDS Summary of Nasal cavity squamous cell carcinoma (male F344/DuCrj rats) {Kasai,
2009, 193803} 354
1.7 BMDS Summary of Zymbal gland adenoma (male F344/DuCrj rats) {Kasai, 2009, 193803}
356
1.8 MS-Combo portal of entry tumors 357
1.9 BMDS Summary of Hepatocellular adenoma or carcinoma (male F344/DuCij rats) {Kasai,
2009, 193803} 358
1.10 BMDS Summary of Renal cell carcinoma (male F344/DuCrj rats) {Kasai, 2009, 193803} ...361
1.11 BMDS Summary of Peritoneal mesothelioma (male F344/DuCrj rats) {Kasai, 2009, 193803}
363
1.12 BMDS Summary of Mammary gland fibroadenoma (male F344/DuCrj rats) {Kasai, 2009,
193803}. 365
1.13 BMDS Summary of Subcutis fibroma (male 1'344/DuCrj rats, high dose dropped) {Kasai,
2009, 193803} 367
1.14 MS-Combo Systemic (including liver) 368
1.15 MS-Combo Systemic (omitting liver) 369
1.16 MS-Combo portal of entry + systemic (including liver) ..370
1.17 MS-Combo portal of entry + systemic (omitting liver) 371
1.18 BMDS Summary of Hepatocellular mixed foci in male F344/DuCrj rats
{Kano, 2009, 594539} 371
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1.19 BMDS Summary of Cortical tubule degeneration in female OM rats {NCI, 1978, 62935} ....374
1.20 BMDS Summary of Nasal squamous cell carcinoma in Male F344/DuCrj rats (Kano, 2009,
594539}. 376
1.21 BMDS Summary of Peritoneum mesothelioma in Male F344/DuCrj rats {Kano, 2009, 594539}
378
1.22 BMDS Summary of Hepatocellular adenoma or carcinoma in Male F344/DuCrj rats {Kano,
2009, 594539} .....380
1.23 BMDS Summary of Subcutis fibroma in Male 1'344/DuCrj rats {Kano, 2009, 594539} 382
1.24 BMDS Summary of Nasal squamous cell carcinoma in female F344/DuCrj rats {Kano, 2009,
594539} 384
1.25 BMDS Summary of Mammary adenoma in female F344/DuCrj rats {Kano, 2009, 594539} .386
1.26 BMDS Summary of Hepatocellular adenomas or carcinomas female F344/'DuCrj rats {Kano,
2009, 594539} 388
1.27 BMDS Summary of Hepatocellular adenomas or carcinomas in male CrjBDFl mice {Kano,
2009, 594539}..... ..390
L28 BMDS Summary of Nasal cavity tumors in Sherman rats [Kociba, 1974,62929} .....392
1.29 BMDS Summary of Liver tumors in Sherman rats (male and female combined) {Kociba, 1974,
62929} ....394
1.30 BMDS Summary of Nasal squamous cell carcinomas in female OM rats (MS models) {NCI,
1978, 62935} 396
1.31 BMDS Summary of Hepatocellular adenoma in female OM rats {NCI, 1978, 62935} 398
1.32 BMDS Summary of Hepatocellular adenomas or carcinomas in male B6C3F1 mice {NCI,
1978, 62935} 400
1.33 BMDS Summary of Hepatocellular adenomas or carcinomas in female B6C3F1 mice {NCI,
1978, 62935} 402
1.34 MS-Combo Result {Kano, 2009, 594539}, Male F344/ DuCrj rats, excluding liver 404
1.35 MS-Combo Result {Kano, 2009, 594539}, Male F344/ DuCrj rats, including liver ....404
1.36 MS-Combo Result {Kano, 2009, 594539}, Female F344/ DuCrj rats, excluding liver ...........405
1.37 MS-Combo Result {Kano, 2009, 594539}, Female F344/ DuCrj rats, including liver............406
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LIST OF TABLES
Table 2-1. Physical and Chemical Properties of 1,4-Dioxane 24
Table 2-2. Production Volume of 1,4-Dioxane in Chemical Data Reporting (CDR) Reporting Period
(2012 to 2015) a 25
Table 2-3. Assessment History of 1,4-Dioxane 26
Table 2-4. Categories and Subcategories of Conditions of Use Included in the Scope of the Risk
Evaluation 30
Table 3-1. Environmental Fate Characteristics of 1,4-Dioxane 44
Table 3-2. Assigned Protection Factors for Respirators in OSHA Standard 29 CFR § 1910.132 53
Table 3-3. Manufacturing Worker Exposure Data Evaluation 54
Table 3-4. Acute and Chronic Inhalation Exposures of Worker for Manufacturing Based on Monitoring
Data 55
Table 3-5. Import and Repackaging Data Source Evaluation 56
Table 3-6. Acute and Chronic Inhalation Exposures of Worker for Import and Repackaging Based on
Modeling 57
Table 3-7. Industrial Uses Data Source Evaluation 59
Table 3-8. Acute and Chronic Inhalation Exposures of Worker for Industrial Uses Based on Monitoring
Data 60
Table 3-9. Functional Fluids (Open System) Data Evaluation 61
Table 3-10. Acute and Chronic Inhalation Exposures of Worker for Open System Functional Fluids
Based on Modeling 61
Table 3-11. Acute and Chronic ONU Inhalation Exposures for Open System Functional Fluids Based on
Monitoring Data 62
Table 3-12. Laboratory Chemicals Data Evaluation 64
Table 3-13. Acute and Chronic Inhalation Exposures of Worker for Laboratory Chemicals Based on
Monitoring Data 65
Table 3-14. Film Cement Data Evaluation 66
Table 3-15. Acute and Chronic Inhalation Exposures of Worker for the Use of Film Cement Based on
Monitoring Data 66
Table 3-16. Acute and Chronic ONU Inhalation Exposures for the Use of Film Cement Based on
Monitoring Data 67
Table 3-17. Spray Foam Application Data Source Evaluation 68
Table 3-18. Acute and Chronic Inhalation Exposures of Worker for Spray Application Based on
Modeling 69
Table 3-19. Acute and Chronic Non-Sprayer Workers Inhalation Exposures for Spray Applications
Based on Modeling 69
Table 3-20. Use of Printing Inks Data Evaluation 70
Table 3-21. Acute and Chronic Inhalation Exposures of Worker for Use of Printing Inks Based on
Monitoring Data 71
Table 3-22. Dry Film Lubricant Data Source Evaluation 72
Table 3-23. Acute and Chronic Inhalation Exposures of Workers for the Use of Dry Film Lubricant
Based on Exposure Data 72
Table 3-24. Disposal Data Source Evaluation 73
Table 3-25. Acute and Chronic Inhalation Exposures of Worker for Disposal Based on Modeling 74
Table 3-26. Glove Protection Factors for Different Dermal Protection Strategies 76
Table 3-27. Estimated Dermal Absorbed Dose1 (mg/day) for Workers in All Conditions of Use 79
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Table 4-1. Acceptable Studies Evaluated for Toxicity of 1,4-Dioxane Following Acute or Short-term
Exposure21 87
Table 4-2. Acceptable Studies Evaluated for Non-Cancer Subchronic or Chronic Toxicity of 1,4-
Dioxane Following Inhalation Exposure 88
Table 4-3. Acceptable Subchronic and Chronic Studies Evaluated for Non-Cancer Toxicity of 1,4-
Dioxane Following Oral Exposure 90
Table 4-4. Acceptable New Studies Evaluated for Genetic Toxicity of 1,4-Dioxane 93
Table 4-5. Studies Evaluated for Cancer Following Inhalation Exposure to 1,4-Dioxane 96
Table 4-6. Studies Evaluated for Cancer Following Oral and Inhalation Exposure to 1,4-Dioxane 97
Table 4-7A. Incidence of carcinogenic and non-carcinogenic lesions reported at each dose level in a two
year inhalation study in rats 102
Table 4-8. Model selection and duration-adjusted HEC estimates for BMCLs (from best fitting BMDS
models) or NOAECs/LOAECs from the 2-year inhalation study by Kasai et al. (2009) in
Male F344/DuCrj ratsa 114
Table 4-9. Dose-response modeling summary results for male rat tumors associated with inhalation
exposure to 1,4-dioxane for 2 years 116
Table 4-10. Dose-response modeling summary results for oral non-cancer liver, kidney, and nasal effects
and route-to-route extrapolated applied dermal HEDs 121
Table 4-11. Cancer slope factor for dermal exposures extrapolated from studies for male rat tumors
associated with inhalation exposure to 1,4-dioxane for 2 years 123
Table 4-12. Dose-response modeling summary results for oral CSFs and route-to-route extrapolated
dermal CSFs 126
Table 4-13. Summary of Hazard Identification and Dose-Response Values 128
Table 5-1. Concentrations of Concern (COCs) for Environmental Toxicity 130
Table 5-2. Calculated Risk Quotients (RQs) for 1,4-Dioxane 131
Table 5-3. Summary of Parameters for Risk Characterization 132
Table 5-4. MOE for Acute/Short-term Inhalation Exposures; Benchmark MOE = 300 136
Table 5-5. Chronic Inhalation Exposure Risk to Workers: Non-Cancer; benchmark MOE=30 137
Table 5-6. Inhalation Exposure Risk to Occupational Non-Users: Non-Cancer; Benchmark MOE = 30
138
Table 5-7. Inhalation Exposure Risk Estimates to Workers: Cancer; Benchmark Risk = 1 in 104 140
Table 5-8. Inhalation Exposures to Occupational Non-Users: Cancer; Benchmark Risk = 1 in 104 141
Table 5-9. Dermal Exposure Risk Estimates to Workers: for Acute/Short-term Exposures Non-Cancer;
Benchmark MOE = 300 142
Table 5-10. Dermal Exposure Risk Estimates to Workers: Non-Cancer; Benchmark MOE = 30 144
Table 5-11. Dermal Exposure Risk Estimates to Workers: Cancer 145
Table 6-1. Risk Determination by Conditions of Use 158
LIST OF FIGURES
Figure 2-1. 1,4-Dioxane Life Cycle Diagram 29
Figure 2-2. 1,4-Dioxane Conceptual Model for Industrial and Commercial Activities and Uses: Potential
Exposures and Hazards 34
Figure 2-3. 1,4-Dioxane Conceptual Model for Environmental Releases and Wastes: Potential
Exposures and Hazards 35
Figure 2-4. Literature Flow Diagram for Environmental Fate and Transport Data Sources 38
Figure 2-5. Literature Flow Diagram for Engineering Releases and Occupational Exposure Data
Sources 39
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Figure 2-6. Literature Flow Diagram for General Population, Consumer and Environmental Exposure
Data Sources 40
Figure 2-7. Literature Flow Diagram for Environmental Hazard Data Sources 41
Figure 2-8. Literature Flow Diagram for Human Health Hazard Data Sources 42
Figure 4-1. EPA Approach to Human Health Hazard Identification and Dose-Response for 1,4-Dioxane
81
Figure 4-2. 1,4-Dioxane Metabolism Pathways 84
LIST OF APPENDIX TABLES
Table A-l. Federal Laws and Regulations 190
Table A-2. State Laws and Regulations 195
Table A-3. Regulatory Actions by other Governments and Tribes 196
Table B-l. Industrial and Commercial Occupational Exposure Scenarios for 1,4-Dioxane 198
Table B-2. Environmental Releases and Wastes Exposure Scenarios for 1,4-Dioxane 208
Table E-l. Summary of 1,4-Dioxane TRI Releases to the Environment in 2015 (lbs) 214
Table E-2. Facility Selection Characterization 215
Table E-3. Summary of Modeled Surface Water Concentrations for DMR Facilities 217
Table E-4. Summary of Modeled Surface Water Concentrations for TRI Facilities 219
Table F-l. Acceptable acute aquatic toxicity studies that were evaluated for of 1,4-Dioxane 221
Table F-2. Acceptable chronic aquatic toxicity studies that were evaluated for of 1,4-Dioxane 223
Table G-l. Summary of Inhalation Monitoring Data Sources Specific to 1,4-Dioxane 226
Table G-2. Summary of Cross-Cutting Data Sources 230
Table G-3. Representative Worker Exposure Durations Considered for Risk Assessments 234
Table G-4. Overview of Average Worker Tenure from U.S. Census SIPP (Age Group 50+) 237
Table G-5. Median Years of Tenure with Current Employer by Age Group 237
Table G-6. Summary of Parameter Values and Distributions Used in the Inhalation Exposure Model 243
Table G-l. SOCs with Worker and ONU Designations for All Conditions of Use Except Dry Cleaning
246
Table G-8. SOCs with Worker and ONU Designations for Dry Cleaning Facilities 247
Table G-9. Estimated Number of Potentially Exposed Workers and ONUs under NAICS 812320 248
Table G-10. Occupational Exposure Scenario Groupings 251
Table G-l 1 2017 1,4-Dioxane Production Monitoring Data (BASF, 2017) 255
Table G-12. 2007-2011 1,4-Dioxane Production Monitoring Data (BASF, 2016) 255
Table G-13. 2016 CDR Data and Assumed Container Types for Repackaging 259
Table G-14. Number of Totes and Containers per Site 259
Table G-15. Industrial Use NAICS Codes 262
Table G-16. DoD and 2002 EU Risk Assessment Industrial Use Inhalation Exposure Data 263
Table G-17. 1997 NIOSH HHE PBZ and Area Sampling Data for Metalworking Fluids 266
Table G-18. 2011 ESD on Metalworking Fluids Inhalation Exposure Estimates 268
Table G-19. Monitoring Data for Laboratory Chemicals 270
Table G-20. NIOSH HHE PBZ and Area Samples for Film Cement Use 272
Table G-21. Values Used for Daily Site Use Rate for SPF Application 274
Table G-22. Estimated Activity Exposure Durations 275
Table G-23. PBZ Task and TWA Monitoring Data for Dry Film Lubricant Manufacture and Spray
Application at KCNSC 279
Table G-24. NAICS Codes with Workers and ONUs for Disposal 285
Table G-25. 2016 TRI Off-Site Transfers for 1,4-Dioxane 287
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Table G-26. Estimated Fraction Evaporated and Absorbed (fabs) using Equation G-20 291
Table G-27. Exposure Control Efficiencies and Protection Factors for Different Dermal Protection
Strategies from ECETOC TRA v3 293
Table H-l. Summary of Mechanistic Data for 1,4-Dioxane 317
Table H-2. Cancer Incidence for 1,4-Dioxane Studies with Acceptable Data Quality Ratings1 322
Table H-3. Incidences of non-neoplastic lesions in male F344 rats exposed to 1,4-dioxane via inhalation
for 2 years (6 hours/day, 5 days/week) (Kasai et al., 2009) 326
Table H-4. Altered hepatocellular foci data in F344/DuCrj rats exposed to 1,4-dioxane via drinking
water for 2 years (ad libitum) (Kano et al., 2009) 326
Table H-5. Incidence of cortical tubule degeneration in female Osborne-Mendel rats exposed to 1,4-
dioxane via drinking water for 2 years (ad libitum) (NCI, 1978) 326
Table H-6. Tumor incidence data in male F344 rats exposed to 1,4-dioxane via inhalation for 2 years (6
hours/day, 5 days/week) (Kasai et al., 2009) 327
Table H-7. Tumor Incidence data in male and female F344/DuCrj rats and Crj :BDF1 mice exposed to
1,4-dioxane via drinking water for 2 years (ad libitum) (Kano et al., 2009) 328
Table H-8. Tumor Incidence data in in male and female Sherman rats (combined) exposed to 1,4-
dioxane via drinking water for 2 years (ad libitum)(Kociba et al., 1974) 329
Table H-9. Tumor Incidence data in male and female B6C3F1 mice, and female Osborne-Mendel rats
exposed to 1,4-dioxane via drinking water for 2 years (ad libitum) (NCI, 1978) 329
Table 1-1. Summary of BMD Modeling Results for Centrilobular necrosis of the liver in male
F344/DuCrj rats (Kasai et al., 2009) 335
Table 1-2. Summary of BMD Modeling Results for Squamous cell metaplasia of respiratory epithelium
in male F433/DuCrj rats (Kasai et al., 2009) 338
Table 1-3. Summary of BMD Modeling Results for Squamous cell hyperplasia of respiratory epithelium
in male F433/DuCrj rats (Kasai et al., 2009) 340
Table 1-4. Summary of BMD Modeling Results for Hydropic change (lamina propria) (Kasai et al.,
2009) 351
Table 1-5. Summary of BMD Modeling Results for Nasal cavity squamous cell carcinoma (male
F344/DuCrj rats) (Kasai et al., 2009) 354
Table 1-6. Summary of BMD Modeling Results for Zymbal gland adenoma (male F344/DuCij rats)
(Kasai et al., 2009) 356
Table 1-7. Summary of BMD Modeling Results for Hepatocellular adenoma or carcinoma (male
F344/DuCrj rats) (Kasai et al., 2009) 358
Table 1-8. Summary of BMD Modeling Results for Renal cell carcinoma (male F344/DuCrj rats) (Kasai
et al., 2009) 361
Table 1-9. Summary of BMD Modeling Results for Peritoneal mesothelioma (male F344/DuCrj rats)
(Kasai et al., 2009) 363
Table I-10. Summary of BMD Modeling Results for Mammary gland fibroadenoma (male F344/DuCrj
rats) (Kasai et al., 2009) 365
Table 1-11. Summary of BMD Modeling Results for Subcutis fibroma (male F344/DuCrj rats, high dose
dropped) (Kasai et al., 2009) 367
Table 1-12. Summary of BMD Modeling Results for Hepatocellular mixed foci in male F344/DuCrj rats
(Kano et al., 2009) 371
Table 1-13. Summary of BMD Modeling Results for Cortical tubule degeneration in female OM rats
(NCI, 1978) 374
Table 1-14. Summary of BMD Modeling Results for Nasal squamous cell carcinoma in Male
F344/DuCrj rats (Kano et al., 2009) 376
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Table 1-15. Summary of BMD Modeling Results for Peritoneum mesothelioma in Male F344/DuCrj rats
(Kano et al., 2009) 378
Table 1-16. Summary of BMD Modeling Results for Hepatocellular adenoma or carcinoma in Male
F344/DuCrj rats (Kano et al., 2009) 380
Table 1-17. Summary of BMD Modeling Results for Subcutis fibroma in Male F344/DuCij rats (Kano et
al., 2009) 382
Table 1-18. Summary of BMD Modeling Results for Nasal squamous cell carcinoma in female
F344/DuCrj rats (Kano et al., 2009) 384
Table 1-19. Summary of BMD Modeling Results for Mammary adenoma in female F344/DuCrj rats
(Kano et al., 2009) 386
Table 1-20. Summary of BMD Modeling Results for Hepatocellular adenomas or carcinomas female
F344/DuCrj rats (Kano et al., 2009) 388
Table 1-21. Summary of BMD Modeling Results for Hepatocellular adenomas or carcinomas in male
CrjBDFl mice (Kano et al., 2009) 390
Table 1-22. Summary of BMD Modeling Results for Nasal cavity tumors in Sherman rats (Kociba et al.,
1974) 392
Table 1-23. Summary of BMD Modeling Results for Liver tumors in Sherman rats (male and female
combined) (Kociba et al., 1974) 394
Table 1-24. Summary of BMD Modeling Results for Nasal squamous cell carcinomas in female OM rats
(MS models) (NCI, 1978) 396
Table 1-25. Summary of BMD Modeling Results for Hepatocellular adenoma in female OM rats (NCI,
1978) 398
Table 1-26. Summary of BMD Modeling Results for Hepatocellular adenomas or carcinomas in male
B6C3F1 mice (NCI, 1978) 400
Table 1-27. Summary of BMD Modeling Results for Hepatocellular adenomas or carcinomas in female
B6C3F1 mice (NCI, 1978) 402
LIST OF APPENDIX FIGURES
Figure D 1. EPI Suite™ welcome screen set up for 1,4-dioxane model run 211
Figure G-l. Example of Monte Carlo Simulation results for the Disposal Scenario 245
Figure G-2. Generic Manufacturing Process Flow Diagram 253
Figure G-3. General Process Flow Diagram for Import and Repackaging 257
Figure G-4. Generic Industrial Use Process Flow Diagram 260
Figure G-5. Process Flow Diagram for Open System Functional Fluids 265
Figure G-6. General Laboratory Use Process Flow Diagram 269
Figure G-l. Process Flow Diagram for Film Cement Application 271
Figure G-8. Process Flow Diagram for Spray Application 273
Figure G-9. Process Flow Diagram for Printing Inks (3D) 276
Figure G-10. Process Flow Diagram for Dry Film Lubricant in Nuclear Weapon Applications 278
Figure G-l 1. Typical Waste Disposal Process 282
Figure G-12. Typical Industrial Incineration Process 283
Figure G-13. General Process Flow Diagram for Solvent Recovery Processes 285
Figure H-l. Literature Flow Diagram for Human Health Hazard 295
Figure 1-1. Plot of incidence rate by dose with fitted curve for the unrestricted LogProbit (left) and
restricted LogLogistic (right) models for Centrilobular necrosis of the liver in male
F344/DuCrj rats (Kasai et al., 2009); dose shown in ppm. Restricted LogLogistic has the
lowest AIC but exhibits higher residuals for all dose groups 336
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Figure 1-2. Plot of incidence rate by dose with fitted curve for LogProbit model for Squamous cell
metaplasia of respiratory epithelium in male F433/DuCrj rats (Kasai et al., 2009); dose
shown in ppm 338
Figure 1-3. Plot of incidence rate by dose with fitted curve for Quantal-Linear model for Squamous cell
hyperplasia of respiratory epithelium in male F433/DuCij rats; dose shown in ppm.... 341
Figure 1-4. Plot of incidence rate by dose with fitted curve for LogLogistic model for Hydropic change
(lamina propria) (Kasai et al., 2009); dose shown in ppm 352
Figure 1-5. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Nasal
cavity squamous cell carcinoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown
in ppm 354
Figure 1-6. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Zymbal
gland adenoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown in ppm 356
Figure 1-7. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenoma or carcinoma (male F344/DuCrj rats) (Kasai et al., 2009); dose
shown in ppm 359
Figure 1-8. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Renal cell
carcinoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown in ppm 361
Figure 1-9. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Peritoneal
mesothelioma (male F344/DuCij rats) (Kasai et al., 2009); dose shown in ppm 363
Figure I-10. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Mammary gland fibroadenoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown
in ppm 365
Figure 1-11. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Subcutis
fibroma (male F344/DuCrj rats, high dose dropped) (Kasai et al., 2009); dose shown in
ppm 367
Figure 1-12. Plot of incidence rate by dose with fitted curve for LogLogistic model for Hepatocellular
mixed foci in male F344/DuCrj rats (Kano et al., 2009); dose shown in mg/kg-d 372
Figure 1-13. Plot of incidence rate by dose with fitted curve for Weibull model for Cortical tubule
degeneration in female OM rats (NCI, 1978); dose shown in mg/kg-d 374
Figure 1-14. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for Nasal
squamous cell carcinoma in Male F344/DuCij rats (Kano et al., 2009); dose shown in
mg/kg-d 376
Figure 1-15. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for
Peritoneum mesothelioma in Male F344/DuCrj rats (Kano et al., 2009); dose shown in
mg/kg-d 378
Figure 1-16. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for
Hepatocellular adenoma or carcinoma in Male F344/DuCrj rats (Kano et al., 2009); dose
shown in mg/kg-d 380
Figure 1-17. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Subcutis
fibroma in Male F344/DuCij rats (Kano et al., 2009) ; dose shown in mg/kg-d 382
Figure 1-18. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Nasal
squamous cell carcinoma in female F344/DuCri rats (Kano et al., 2009); dose shown in
mg/kg-d 384
Figure 1-19. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Mammary adenoma in female F344/DuCij rats (Kano et al., 2009); dose shown in mg/kg-
d 386
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Figure 1-20. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for
Hepatocellular adenomas or carcinomas female F344/DuCrj rats (Kano et al., 2009); dose
shown in mg/kg-d 388
Figure 1-21. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenomas or carcinomas in male CrjBDFl mice (Kano et al., 2009); dose
shown in mg/kg-d 390
Figure 1-22. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for Nasal
cavity tumors in Sherman rats (Kociba et al., 1974); dose shown in mg/kg-d 392
Figure 1-23. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Liver
tumors in Sherman rats (male and female combined) (Kociba et al., 1974); dose shown in
mg/kg-d 394
Figure 1-24. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for Nasal
squamous cell carcinomas in female OM rats (MS models) (NCI, 1978); dose shown in
mg/kg-d 396
Figure 1-25. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenoma in female OM rats (NCI, 1978); dose shown in mg/kg-d 398
Figure 1-26. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenomas or carcinomas in male B6C3F1 mice (NCI, 1978); dose shown
in mg/kg-d 400
Figure 1-27. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenomas or carcinomas in female B6C3F1 mice (NCI, 1978); dose
shown in mg/kg-d 402
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ACKNOWLEDGEMENTS
This report was developed by the United States Environmental Protection Agency (U.S. EPA), Office of
Chemical Safety and Pollution Prevention (OCSPP), Office of Pollution Prevention and Toxics (OPPT)
with support from the Office of Research and Development (ORD).
Acknowledgements
The OPPT Assessment Team gratefully acknowledges participation and/or input from Intra-agency
reviewers that included multiple offices within EPA, Inter-agency reviewers that included multiple
Federal agencies, and assistance from EPA contractors GDIT (Contract No. CIO-SP3,
HHSN316201200013W), ERG (Contract No. EP-W-12-006), Versar (Contract No. EP-W-17-006), ICF
(Contract No. EPC14001) and SRC (Contract No. EP-W-12-003).
Docket
Supporting information can be found in public docket: ] Q-QPPT-2016-0723.
Disclaimer
Reference herein to any specific commercial products, process or service by trade name, trademark,
manufacturer or otherwise does not constitute or imply its endorsement, recommendation or favoring by
the United States Government.
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ABBREVIATIONS
ACC
American Chemistry Council
°c
Degrees Celsius
atm
atmosphere(s)
AEC
Acute Exposure Concentration
AES
Alkyl Ethoxysulphates
AQS
Air Quality System
AT SDR
Agency for Toxic Substances and Disease Registries
BLS
Bureau of Labor Statistics
CAA
Clean Air Act
CASRN
Chemical Abstract Service Registry Number
CBI
Confidential Business Information
CCL
Candidate Contaminant List
CDR
Chemical Data Reporting
CNS
Central Nervous System
CSF
Cancer Slope Factor
DHHS
Department of Health and Human Services
DMR
Discharge Munitions Report
EC
European Commission
ECHA
European Chemicals Agency
E-FAST
Exposure and Fate Assessment Screening Tool
EPA
Environmental Protection Agency
ESD
Emission Scenario Document
EU
European Union
EUSES
European Union System for the Evaluation of Substances
FDA
Food and Drug Administration
HEAA
(3-Hydroxyethoxy Acetic Acid
HAP
Hazardous Air Pollutant
Hg
Mercury
HPV
High Production Volume
IARC
International Agency for Research on Cancer
ICSC
International Chemical Safety Cards
ILO
International Labor Organization
IRIS
Integrated Risk Information System
IUR
Inventory Update Reporting Rule; or Inhalation Unit Risk
kg
Kilogram(s)
Kow
Octanol: Water Partition Coefficient
LADC
Lifetime Average Daily Concentration
lb
Pound
LOAEC
Lowest Observed Adverse Effect Concentration
LOAEL
Lowest Observed Adverse Effect Level
Log Kow
Logarithmic Octanol:Water Partition Coefficient
MATC
Maximum Acceptable Toxicant Concentration
mg
Milligram(s)
Hg
Microgram(s)
MOE
Margin of Exposure
MRL
Minimal Risk Level
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NAICS
North American industrial Classification System
NAS
National Academies of Science
NATA
National Air-Toxics Assessment
NEI
National Emissions Inventory
NIOSH
National Institute of Occupational Safety and Health
NOEC
No Observed Effect Concentration
NOAEL
No Observed Adverse Effect Level
NPL
National Priorities List
NTP
National Toxicology Program
OAR
Office of Air and Radiation
OCF
One Component Foam
OCSPP
Office of Chemical Safety and Pollution Prevention
OECD
Organisation for Economic Co-operation and Development
OES
Occupational Exposure Scenario
OLEM
Office of Land and Emergency Management
ONU
Occupational non-user
OPPT
Office of Pollution Prevention and Toxics
OSHA
Occupational Safety and Health Administration
OSWER
Office of Solid Waste and Emergency Response
OW
Office of Water
PBPK
Physiologically Based Pharmacokinetic
PBT
Persistent, Bioaccumulative, Toxic
PBZ
Personal Breathing Zone
PDE
Permitted Daily Exposure
PEC
Predicted Environmental Concentration
PEL
Permissible Exposure Level
PFIA
Problem Formulation and Initial Assessment
POD
Point of Departure
ppb
Parts per Billion
ppm
Parts per Million
PV
Production Volume
PWS
Public Water System
RA
Risk Assessment
RAR
Risk Assessment Report
REACH
Registration, Evaluation, Authorisation and Restriction of Chemicals
REL
Recommended Exposure Level
RfC
Reference Concentration
RfD
Reference Dose
SDS
Safety Data Sheet
SPFs
Spray Polyurethane Foams
SUSB
Statistics of US Businesses
TCA
1,1,1 -Trichloroethane
TIAC
Time Integrated Air Concentration
TLV
Threshold Limit Value
TRI
Toxic Release Inventory
TSCA
Toxic Substances Control Act
TWA
Time Weighted Average
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UCMR Unregulated Contaminant Monitoring Rule
US United States
VCCEP Voluntary Children's Chemical Evaluation Program
WHO World Health Organisation
WWTP Wastewater Treatment Plant
Yr Year
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1 EXECUTIVE SUMMARY
This draft risk evaluation for 1,4-dioxane was performed in accordance with the Frank R. Lautenberg
Chemical Safety for the 21st Century Act and is being disseminated for public comment and peer
review. The Frank R. Lautenberg Chemical Safety for the 21st Century Act amended the Toxic
Substances Control Act, the Nation's primary chemicals management law, in June 2016. As per EPA's
final rule, Procedures for Chemical Risk Evaluation Under the Amended Toxic Substances Control Act
(I 16), EPA is taking comment on this draft, and will also obtain peer review on this draft risk
evaluation for 1,4-dioxane. All conclusions, findings, and determinations in this document are
preliminary and subject to comment. The final risk evaluation may change in response to public
comments received on the draft risk evaluation and/or in response to peer review, which itself may be
informed by public comments.
TSCA § 26(h) and (i) require EPA to use scientific information, technical procedures, measures,
methods, protocols, methodologies and models consistent with the best available science and to base its
decisions on the weight of the scientific evidence. To meet these TSCA § 26 science standards, EPA
used the TSCA systematic review process described in the Application of Systematic Review in TSCA
Risk Evaluations document ( 1018b). The process complements the risk evaluation process in
that the data collection, data evaluation and data integration stages of the systematic review process are
used to develop the exposure, fate and hazard assessments for risk evaluations.
1,4-Dioxane is a clear volatile liquid used primarily as a solvent and is subject to federal and state
regulations and reporting requirements. 1,4-Dioxane has been reportable to Toxics Release Inventory
(TRI) chemical under Section 313 of the Emergency Planning and Community Right-to-Know Act
(EPCRA) since 1987. It is designated a Hazardous Air Pollutant (HAP) under the Clean Air Act (CAA),
and is a hazardous substance under the Comprehensive Environmental Response, Compensation and
Liability Act (CERCLA). It was listed on the Safe Drinking Water (SDWA) Candidate Contaminant
List (CCL) and identified in the third Unregulated Contaminant Monitoring Rule (UCMR3).
1,4-Dioxane is currently manufactured, processed, distributed, and disposed of following use in
industrial processes with industrial and commercial conditions of use. Manufacturing sites produce 1,4-
dioxane in liquid form at concentrations greater or equal to 90% [EPA-HQ-OPPT-2016-0723-0012;
Of V\L .->\t;)] and 1,4-dioxane is also imported. EPA evaluated the following conditions of use:
manufacturing; processing; functional fluids in open and closed systems; laboratory chemicals;
adhesives and sealants (professional film cement); spray polyurethane foam; printing and printing
compositions; disposal of waste materials containing 1,4-dioxane; and dry film lubricant. The total
aggregate production volume is approximately 1 million pounds.
Approach
EPA used reasonably available information, defined in 40 CFR 702.33 as information that EPA
possesses, or can reasonably obtain and synthesize for use in risk evaluations, considering the deadlines
for completing the evaluation, in a fit-for-purpose approach, to develop a risk evaluation that relies on
the best available science and is based on the weight of the scientific evidence. EPA used previous
analyses as a starting point for identifying key and supporting studies to inform the exposure, fate and
hazard assessments. EPA also evaluated other studies that were published since these reviews. EPA
reviewed the information and evaluated the quality of the methods and reporting of results of the
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individual studies using the evaluation strategies described in Application of Systematic Review in
TSCA Risk Evaluations ( :018b).
In the problem formulation, EPA identified the conditions of use and presented two conceptual models
and an analysis plan for this draft risk evaluation. In this draft risk evaluation, EPA evaluated the risk to
workers and occupational non-users (ONUs) from inhalation and dermal exposures by comparing the
estimated occupational exposures to acute and chronic human health hazards. ONUs are workers at the
facility who neither directly perform activities near the 1,4-dioxane source area nor regularly handle 1,4-
dioxane. The job classifications for ONUs could be dependent on the conditions of use.
EPA utilized environmental fate parameters and physical-chemical properties, and modelling, to assess
ambient water exposure to aquatic organisms, sediments and land-applied biosolids. While 1,4-dioxane
is present in various environmental media such as groundwater, surface water, and air, EPA determined
during problem formulation that no further analysis beyond what was presented in the problem
formulation document would be done for those environmental exposure pathways in this draft risk
evaluation. However, risk determinations were not made as part of problem formulation; therefore, the
results from these analyses are presented in this draft risk evaluation and used to inform the risk
determination section. The exposure and environmental hazard analyses for the environmental release
pathways for ambient water exposure to aquatic organisms, sediments, and land-applied biosolids
conducted based on a qualitative assessment of the physical-chemical properties and fate of 1,4-dioxane
in the environment and a quantitative comparison of hazards and exposures for aquatic organisms are
presented in sections 3.1, 3.3 and 5.1.
EPA evaluated acute and chronic inhalation exposures to workers and ONUs in association with 1,4-
dioxane for the conditions of use identified. EPA used inhalation monitoring data that was from
literature sources where reasonably available and that met data evaluation criteria and modeling
approaches to estimate potential inhalation exposures. EPA also estimated dermal doses for workers in
these scenarios since dermal monitoring data was not reasonably available. These analyses are described
in section 3.4 of this draft risk evaluation.
In the human health hazards section, EPA evaluated reasonably available information and identified
hazard endpoints including acute/chronic toxicity, non-cancer effects, and cancer for inhalation and
dermal exposure for relevant chronic exposures. EPA used an approach based on the Framework for
Human Health Risk Assessment to Inform Decision Making (U.S. EPA. ^ ) to evaluate, extract and
integrate 1,4-dioxane's human health hazard and dose-response information. EPA reviewed key and
supporting information from previous hazard assessments [EPA IRIS Assessments (U.S. EPA. 2013c.
2010). an ATSDR Toxicological Profile ("ATSDR. 2012). a Canadian Screening Assessment (Health
Canada. 2010). a European Union (EU) Risk Assessment Report (ECJRC. 2002). and an Interim AEGL
(U.S. EPA.., 2005b)l. EPA also screened and evaluated new studies that were published since these
reviews (i.e. from 2013 - 2018).
EPA developed a hazard and dose-response analysis for inhalation and oral hazard endpoints identified
based on the weight of the scientific evidence considering EPA, National Research Council (NRC), and
European Chemicals Agency (ECHA) risk assessment guidance and selected the points of departure
(POD) for acute/chronic, non-cancer endpoints, and inhalation unit risk and cancer slope factors for
cancer risk estimates. Potential health effects of 1,4-dioxane exposure described in the literature include
effects on the liver, kidneys, respiratory system, neurological endpoints, and cancer. EPA identified
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acute PODs for inhalation and dermal exposures based on acute liver toxicity observed in rats (Mattie et
at.. 2012). The chronic POD for inhalation exposures are based on effects on nasal tissue in rats (Kasai
et at.. 2009). EPA provided chronic PODs for dermal exposure that extrapolated from effects on liver
following exposure through inhalation (Mattie et at.. 2012) and exposure through drinking water (Kama
et at.. 2009; NCI. 1978; Kociba et at... 1974). EPA also considered the current evidence for two potential
modes of action that would support either a threshold approach or a linear non-threshold approach for
estimating cancer risk. The risk evaluation ultimately calculated cancer risk with a linear model using
cancer slope factors based on evidence of increased risk of cancer in rats exposed to 1,4-dioxane through
air or drinking water (Kano et at.. 2009; Kasai et at.. 2009). The results of these analyses are described
in section 4.2.
Uncertainties: 1,4-Dioxane is a multi-site carcinogen and may have more than one MOA. There was a
high degree of uncertainty in each of the MOA hypotheses considered in this evaluation (e.g., mutagenic
mode of action or threshold response to cytotoxicity and regenerative hyperplasia for liver tumors).
Chronic non-cancer risk estimates from inhalation exposures were based on portal of entry effects in the
respiratory tract. These effects are relevant to inhalation exposures and are more sensitive than the
observed systemic effects.
Dermal extrapolation and dermal absorption were also sources of uncertainty in the dermal risk
assessment for both dermal cancer and noncancer estimates of risk. Inhalation to dermal and oral to
dermal route-to-route extrapolations were compared for relevance to dermal exposures. Metabolism
occurs in both oral and dermal routes and portal of entry effects from inhalation are not as relevant to
dermal exposures.
Risk Characterization
For environmental risk, EPA estimated risks based on a qualitative assessment of the physical-chemical
properties and fate of 1,4-dioxane in the environment for sediment and land-applied biosolids, and a
quantitative comparison of hazards and exposures for aquatic organisms. EPA utilized a risk quotient
(RQ) to compare the environmental concentration to the effect level to characterize the risk to aquatic
organisms. Table 5-2 in this draft risk evaluation summarizes the RQs for acute and chronic risks of 1,4-
dioxane for aquatic organisms. EPA included a qualitive assessment describing 1,4-dioxane exposure in
sediments and land-applied biosolids. 1,4-Dioxane is not expected to accumulate in sediments and is
expected to be mobile in soil and to migrate to water or volatilize to air. The results of the risk
characterization are in section 5.1.
EPA used a Margin of Exposure (MOE) approach to identify potential non-cancer human health risks
and allow for a range of risk estimates. EPA estimated potential inhalation cancer risk from chronic
exposures to 1,4-dioxane by using a range of inhalation unit risk values multiplied by the chronic
exposure to workers and ONUs for each COU. For dermal cancer risk, EPA used the cancer slope factor
multiplied by the chronic exposure to workers and ONUs for each COU. In section 5.2, EPA presents 8
tables which describe risk estimates: for acute/short-term and chronic exposures via inhalation (non-
cancer) to workers and ONUs; chronic exposures via inhalation (cancer) to workers and ONUs; and
acute and chronic dermal exposure (non-cancer) and chronic dermal exposure (cancer) to workers. The
results of these analyses are presented in section 5.2.
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Potentially Exposed Susceptible Subpopulations
TSCA § 6(b)(4) requires that EPA conduct a risk evaluation to "determine whether a chemical
substance presents an unreasonable risk of injury to health or the environment, without consideration of
cost or other non-risk factors, including an unreasonable risk to a potentially exposed or susceptible
subpopulation identified as relevant to the risk evaluation by the Administrator, under the conditions of
use " TSCA § 3(12) states that "the term 'potentially exposed or susceptible subpopulation' means a
group of individuals within the general population identified by the Administrator who, due to either
greater susceptibility or greater exposure, may be at greater risk than the general population of adverse
health effects from exposure to a chemical substance or mixture, such as infants, children, pregnant
women, workers, or the elderly
In developing the risk evaluation, the EPA analyzed the reasonably available information to ascertain
whether some human receptor groups may have greater exposure or greater susceptibility than the
general population to the hazard posed by a chemical. The results of the available human health data for
all routes of exposure evaluated (i.e., dermal and inhalation) indicate that there is no evidence of
increased susceptibility for any single group relative to the general population. For consideration of the
most highly exposed groups, EPA considered 1,4-dioxane exposures to be higher amongst workers and
ONUs using 1,4-dioxane as compared to the general population.
Risk Determination
In each risk evaluation under TSCA section 6(b), EPA determines whether a chemical substance
presents an unreasonable risk of injury to health or the environment, under the conditions of use. In
making this determination, EPA considered relevant risk-related factors, including, but not limited to:
the effects of the chemical substance on health and human exposure to such substance under the
conditions of use (including cancer and non-cancer risks); the effects of the chemical substance on the
environment and environmental exposure under the conditions of use; the population exposed (including
any potentially exposed or susceptible subpopulations); the severity of hazard (including the nature of
the hazard, the irreversibility of the hazard); and the uncertainties. EPA considered the confidence in the
data used in the risk estimates and whether estimates might be overestimates or underestimates of risk.
The rationale for the risk determination is located in section 6.2.
Environmental Risks: For all conditions of use, EPA did not identify any exceedances of benchmarks to
aquatic vertebrates, aquatic invertebrates, and aquatic plants from exposures to 1,4-dioxane in surface
waters. Because the RQ values do not exceed 1, and because EPA used a conservative screening level
approach, these values indicate there are no risks of 1,4-dioxane to the aquatic pathways. As a result,
EPA does not find unreasonable risks to the environment for any of the conditions of use for 1,4-
dioxane.
Occupational Non-Users (ONUs): For all conditions of use, inhalation exposure scenarios for
occupational non-users resulted in calculated MOEs and cancer risk levels that did not indicate risk
relative to the respective benchmarks. As a result, EPA does not find unreasonable risks to the health of
occupational non-users from the conditions of use for 1,4-dioxane.
Workers: For the following conditions of use: manufacturing (domestic), processing, industrial use -
(intermediates, processing aids, laboratory chemicals, adhesives and sealants, professional film cement,
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printing and printing compositions), and disposal, EPA assessed inhalation and/or dermal exposure
scenarios that resulted in MOEs and/or cancer risk estimates that indicate risks relevant to the respective
benchmarks. EPA considered those risk estimates; confidence in the data used in the risk estimates and
uncertainties associated with the risk estimates; and relevant risk-related factors described above and has
preliminarily concluded that the aforementioned conditions of use present an unreasonable risk of injury
to health, as set forth in the risk determination section of this draft risk evaluation. This draft document's
preliminarily determination of unreasonable risk does not mean that this is EPA's final conclusion. EPA
will consider further input through scientific and public review.
For the following conditions of use: manufacturing (import), processing (repackaging), distribution, and
industrial use (functional fluids in open and closed systems, spray polyurethane foam, dry film
lubricant), EPA assessed inhalation and/or dermal exposure scenarios that resulted in MOEs and/or
cancer risk estimates that do not indicate risk relevant to the respective benchmarks. As a result, EPA
finds that the aforementioned conditions of use do not present an unreasonable risk of injury to health.
2 INTRODUCTION
This document presents for comment the draft risk evaluation for 1,4-dioxane under the Frank R.
Lautenberg Chemical Safety for the 21st Century Act. The Frank R. Lautenberg Chemical Safety for the
21st Century Act amended the Toxic Substances Control Act, the Nation's primary chemicals
management law, in June 2016.
The Agency published the Scope of the Risk Evaluation for 1,4-dioxane ( ) in June
2017, and the problem formulation in June, 2018 ( 018c). which represented the analytical
phase of risk evaluation in which "the purpose for the assessment is articulated, the problem is defined,
and a plan for analyzing and characterizing risk is determined' as described in Section 2.2 of the
Framework for Human Health Risk Assessment to Inform Decision Making. The EPA received
comments on the published problem formulation for 1,4-dioxane and has considered the comments
specific to 1,4-dioxane, as well as more general comments regarding the EPA's chemical risk evaluation
approach for developing the draft risk evaluations for the first 10 chemicals the EPA is evaluating.
The problem formulation identified the conditions of use and presented two conceptual models and an
analysis plan. In this risk evaluation, EPA evaluated the risk to workers from inhalation and dermal
exposures by comparing the estimated occupational exposures to acute and chronic human health
hazards. While 1,4-dioxane is present in various environmental media such as groundwater, surface
water, and air, EPA determined during problem formulation that no further analysis of the
environmental release pathways for ambient water exposure to aquatic organisms, sediments, and land-
applied biosolids needed to be conducted based on a qualitative assessment of the physical chemical
properties and fate of 1,4-dioxane in the environment and a quantitative comparison of hazards and
exposures for aquatic organisms. Risk determinations were not made as part of problem formulation;
therefore, the results from these analyses are presented in this risk evaluation and used to inform the risk
determination section of this draft risk evaluation.
EPA used reasonably available information consistent with best available science for physical and
chemical properties, environmental fate properties, occupational exposure, environmental hazard, and
human health hazard studies according to the systematic review process. For human exposure pathways,
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EPA evaluated inhalation exposures to vapors and mists for workers and occupational non-users and
dermal exposures for skin contact with liquids for workers. For environmental release pathways, EPA
characterized risks to ecological receptors from surface water, sediment, and land-applied biosolids in
the risk characterization section of this draft risk evaluation based on the analyses presented in the
problem formulation.
The document is structured such that Introduction, Section 2, presents the basic physical-chemical
properties of 1,4-dioxane, as well as a background on uses, regulatory history, conditions of use and
conceptual models, with emphasis on any changes since the publication of the problem formulation.
This section also includes a discussion of the systematic review process utilized in this draft risk
evaluation. Exposures, Section 3, provides a discussion and analysis of the exposures, both human and
environmental that can be expected based on the conditions of use for 1,4-dioxane. Hazards, Section 4,
discusses environmental and human health hazards of 1,4-dioxane. Risk characterization is in Section 5,
which integrates and assesses reasonably available information on human health and environmental
hazards and exposures, as required by TSCA (15 U.S.C 2605(b)(4)(F)). This section also includes a
discussion of any uncertainties and how they impact the risk evaluation. In Risk Determination, Section
5.4, the agency presents the determination of whether risk posed by the chemical substance is
unreasonable as required under TSCA 15 U.S.C. 2605(b)(4).
As per EPA's final rule, Procedures for Chemical Risk Evaluation Under the Amended Toxic
Substances Control Act (82 FR 33726). this draft risk evaluation is subject to both public comment and
peer review, which are distinct but related processes. EPA is providing 60 days for public comment on
this draft risk evaluation during the peer review meeting to inform the EPA Science Advisory
Committee on Chemicals (SACC) peer review process. The EPA seeks public comment on all aspects of
this draft risk evaluation. This is also an opportunity for the EPA to receive any additional information
that might be relevant to the science underlying the risk evaluation and the outcome of the systematic
review associated with 1,4-dioxane. This satisfies TSCA (15 U.S.C 2605(4)(H)), which requires the
EPA to provide public notice and an opportunity for comment on a draft risk evaluation prior to
publishing a final risk evaluation.
Peer review will be conducted in accordance with EPA's regulatory procedures for chemical risk
evaluations, including using the EPA. Peer Review Handbook and other methods consistent with section
26 of TSCA (See 40 CFR § 702.45). As explained in the Risk Evaluation Rule, the purpose of peer
review is for the independent review of the science underlying the risk assessment. Peer review will
therefore address aspects of the underlying science as outlined in the charge to the peer review panel
such as hazard assessment, assessment of dose-response, exposure assessment, and risk
characterization. Peer-review supports scientific rigor and enhances transparency in the risk evaluation
process.
As the EPA explained in the Risk Evaluation Rule, it is important for peer reviewers to consider how the
underlying risk evaluation analyses fit together to produce an integrated risk characterization, which will
form the basis of an unreasonable risk determination. The EPA believes peer reviewers will be most
effective in this role if they receive the benefit of public comments on draft risk evaluations prior to peer
review. For this reason, EPA is providing the opportunity for public comment before peer review on this
draft risk evaluation. The final risk evaluation may change in response to public comments received on
the draft risk evaluation and/or in response to peer review, which itself may be informed by public
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comments. The EPA will respond to public and peer review comments received on the draft risk
evaluation when it issues the final risk evaluation.
EPA solicited input on the first 10 chemicals, including 1,4-dioxane, as it developed use dossiers, scope
documents, and problem formulations. At each step, EPA received information and comments specific
to individual chemicals and of a more general nature relating to various aspects of the risk evaluation
process, technical issues, and the regulatory and statutory requirements. EPA has considered comments
and information received at each step in the process and factored in the information and comments as
the Agency deemed appropriate and relevant including comments on the published problem formulation
of 1,4-dioxane. Thus, in addition to any new comments on the draft risk evaluation, the public should re-
submit or clearly identify at this point any previously filed comments, modified as appropriate, that are
relevant to this risk evaluation and that the submitter believes have not been addressed. EPA does not
intend to further respond to comments submitted prior to the publication of this draft risk evaluation
unless they are clearly identified in comments on this draft risk evaluation.
2.1 Physical and Chemical Properties
1,4-Dioxane is a clear liquid at room temperature and has a cyclic structure with two oxygen molecules
attached at the first and fourth bonds, each with free electrons (U.S. EPA, 2.006b). 1,4-Dioxane is
expected to volatilize based on its high vapor pressure (40 mm Hg at 25 °C) (U.S. EPA. 2009). 1,4-
Dioxane has a Log Kow value of -0.27, indicating that this chemical is hydrophilic and readily miscible
in water (U.S. EPA. 2009). A summary of the physical and chemical properties of 1,4-dioxane are listed
in Table 2-1.
Table 2-1. Physical and Chemical Properties of 1,4-Dioxane
Properlv
Value"
References
Molecular formula
C4H8O2
Molecular weight
88.1 g/mole
(Howard. 1990)
Physical form
Clear liquid
(O'Neil et al. 2001)
Melting point
11.75°C
(Hayn.es et al., 2014)
Boiling point
101.1°C
(O'Neil et al.. 2006)
Density
1.0329 g/cm3 at 20°C
(O'Neil et al.. 2006)
Vapor pressure
40 mm Hg at 25°C
(Lewis. 2000)
Vapor density
Not readily available
Water solubility
>8.00 x 102 g/L at 25°C
(Yalkowskv et al..: )
Octanol:water partition
coefficient (Log Kow)
-0.27
(Hansch et al. 1995)
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Henry's Law constant
4.8 x 10"6 atm-m3/mole at 25°C
4.93 x 10"4 atm-m3/mole at 40°C
(Sander. 2017); (Howard.
1990);(Atkins. 1986)
Flash point
18.3°C (open cup)
(Lewis.: )
Autoflammability
180 °C at atmospheric pressure
CUSCG. 1999)
Viscosity
0.0120 cP at 25°C
(O'Neil. 2013)
Refractive index
1.4224 at 20°C
(Havnes et al. 2014)
Dielectric constant
2.209 Farad per meter
(Bruno and PDN, 2006)
a Measured unless otherwise noted
2.2 Uses and Production Volume
The EPA's Chemical Data Reporting (CDR) database (U.S. EPA. 2016a) reported that there were two
manufacturers producing or importing 1,059,980 pounds of 1,4-dioxane in the U.S. in 2015 (see Table
2-2). The total volume (in lbs.) of 1,4-dioxane manufactured (including imports) in the U.S. from 2012
to 2015 indicates that production has varied over that time. Historically, 90% of 1,4-dioxane production
was used as a stabilizer in chlorinated solvents such as 1,1,1-trichloroethane (TCA)(ATSDR. 2012);
however, use of 1,4-dioxane has decreased since TCA was phased out by the Montreal Protocol in 1995
(NTP. 2011; ECJRC. 2002). Based on the lack of information on reported uses (Sapphire Group. 2007).
EPA concludes that many other industrial, commercial and consumer uses were also stopped., 90% of
1,4-dioxane production was used as a stabilizer in chlorinated solvents such as 1,1,1-trichloroethane
(TCA)( DR. 2012); however, use of 1,4-dioxane has decreased since TCA was phased out by the
Montreal Protocol in 1995 (NTP. 2011; ECJRC. 2002). Based on the lack of information on reported
uses (Sapphire Group. 2007). EPA concludes that many other industrial, commercial and consumer uses
were also stopped.
Table 2-2. Production Volume of 1,4-Dioxane in Chemical Data Reporting (CDR) Reporting
Period (2012 to 2015) a
Reporting Year
2012
2013
2014
2015
Total Aggregate
Production Volume (lbs.)
894,505
1,043,627
474,331
1,059,980
" The CDR data for the 2016 reoortine period is available via ChemView (httDs://iava.eDa.gov/chemview) (IIS. EPA.
2014a). Because of an onsoins CBI substantiation process required bv amended TSCA. the CDR data available in the draft
risk evaluation document is more specific than currently in ChemView.
1,4-Dioxane is currently manufactured, processed, distributed and used in industrial processes and for
industrial and commercial uses. Manufacturing sites produce 1,4-dioxane in liquid form at
concentrations greater or equal to 90% [EPA-HQ-OPPT-2016-0723-0012; (BASF. 2017)1 and 1,4-
dioxane is also imported. Industrial processing includes: 1) Processing as a reactant or intermediate, 2)
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Non-incorporative processing, 3) Repackaging, and 4) Recycling. Disposal of waste materials
containing 1,4-dioxane is also a condition of use.
The primary conditions of use identified for 1,4-dioxane are:
• Processing aids (not otherwise listed) (270,000 lbs.)
• Functional fluids in open and closed systems (<150,000 lbs.)
• Laboratory chemicals (<150,000 lbs.)
• Adhesives and sealants (professional film cement)
• Spray polyurethane foam
• Printing and printing compositions
• Disposal of waste materials containing 1,4-dioxane
• Dry film lubricant
2.3 Regulatory and Assessment History
EPA conducted a search of existing domestic and international laws, regulations and assessments
pertaining to 1,4-dioxane. EPA compiled this summary from data available from federal, state,
international and other government sources, as cited in 7Appendix A.
Federal Laws and Regulations
1,4-Dioxane is subject to federal statutes or regulations, other than TSCA, that are implemented by other
offices within EPA and/or other federal agencies/departments. A summary of federal laws, regulations
and implementing authorities is provided in Appendix A.l.
State Laws and Regulations
1,4-Dioxane is subject to state statutes or regulations. A summary of state laws, regulations and
implementing authorities is provided in Appendix A.2.
Laws and Regulations in Other Countries and International Treaties or Agreements
1,4-Dioxane is subject to statutes or regulations in countries other than the United States and/or
international treaties and/or agreements. A summary of these laws, regulations, treaties and/or
agreements is provided in Appendix A.3.
EPA identified numerous previous assessments conducted within EPA and by other organizations (see
Table 2-3.). Depending on the source, these assessments may include information on conditions of use,
hazards, exposures and potentially exposed or susceptible subpopulations.
Table 2-3. Assessment History of 1,4-Dioxane
Authoring Organization
Assessment
EPA assessments
EPA, Office of Chemical Safety and Pollution
Prevention (OCSPP), Office of Pollution
Prevention and Toxics (OPPT)
TSCA. Work Plan Chemic; I em Formulation
and Initial Assessment: 1,4-Dioxe N
( )
EPA, National Center for Environmental
Assessment (NCEA)
Toxicological Review of 1.4-Dioxane (With.
Inhalation Uod* (2013c)
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Authoring Organization
Assessment
EPA, NCEA
Toxicoloeical review of 1.4-Dioxane (CAS No.
12 i - h (2010")
EPA, Office of Water (OW)
Drinking Water Health Advisory (2012a)
Other U.S.-based organizations
National Toxicology Program (NTP)
Report on Carcinogens. Fourteenth Edition. 1.4-
Dioxane(2016)
Agency for Toxic Substances and Disease Registry
(AT SDR)
Toxicological Profile for 1.4-Dioxane (2012.)
National Advisory Committee for Acute Exposure
Guideline Levels for Hazardous
Substances (NAC/AEGL Committee)
Interim Acute Exposure Guideline Level
fc-i 1 4 niutane (CAS Reg. No 1)
(2005b)
International
International Cooperation on Cosmetics Regulation
Report of the ICCR Working Group:
Considerations on Acceptable Trace Level o
Dioxane in Cosmet ucts (2017)
International Agency for Research on Cancer
(IARC)
IARC Monographs on the Evaluation of
Carcinogenic Risks to Humans Volume 71 (1999)
Government of Canada, Environment Canada,
Health Canada
Screening Assessment for the Challenge. 1.4-
Dioxane i V l 2 1 (2010)
Research Center for Chemical Risk Management,
National Institute of Advanced Industrial Science
and Technology, Japan
Estimating Health Risk from Exposui
Dioxane in Jaeaa (2006)
World Health Organisation (WHO)
cane in Drinking-water (2005)
Employment, Social Affairs, and Inclusion,
European Commission (EC)
Recommendation from the Scientific Committee
on Occupational Exposure Limits for )xane
(2004)
European Chemicals Bureau, Institute for Health
and Consumer Protection
European Union Risk Assessment Repor
dioxane. No: 204-
661-8. (2002)
National Industrial Chemicals Notification and
Assessment Scheme (NICNAS), Australian
Government
1 1-Dioxane Vrx n ttv Existing Chemical No. 7.
Full Public Report (1998)
Organisation for Economic Co-operation and
Development (OECD), Screening Information
Data Set (SIDS)
fane. SIDS initial assessment profile
( 9)
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Scope of the Evaluation
2.4.1 Conditions of Use Included in the Risk Evaluation
TSCA (15 U.S.C. § 2602(4)) defines the conditions of use as "the circumstances, as determined by the
Administrator, under which a chemical substance is intended, known, or reasonably foreseen to be
manufactured, processed, distributed in commerce, used, or disposed of" The conditions of use are
described below in Table 2-4.
Information on an additional use was submitted to EPA during the public comment period for the
problem formulation. Specifically, EPA received information indicating that the Department of Energy's
Kansas City National Security Campus uses 1,4-dioxane as a constituent of a dry film lubricant in the
manufacture of components for weapons systems. Although not reflected in the problem formulation,
this condition of use is included in this risk evaluation. The updated life cycle diagram is presented in
Figure.
No further evaluation of distribution of 1,4-dioxane was included in this risk evaluation because
chemicals are packaged in closed-system containers during distribution in commerce and no exposures
are expected.
Consumer uses were not considered within scope of this risk evaluation per the problem formulation,
which states that such activities will be considered in the scope of the risk evaluation for ethoxylated
chemicals. EPA believes that its regulatory tools under TSCA section 6(a) are better suited to addressing
any unreasonable risks that might arise from these activities through regulation of the activities that
generate 1,4-dioxane as an impurity or cause it to be present as a contaminant than addressing them
through direct regulation of 1,4-dioxane (U.S. EPA. 2018c).
As described in the Problem Formulation, general population exposures were not evaluated based on
EPA's determination that the existing regulatory programs and associated analytical processes have
addressed or are in the process of addressing potential risks of 1,4-dioxane that may be present in
various media pathways (e.g., air, water, land) for the general population (L Js ;_0jSc).
Closed system functional fluid precludes exposure as the transfer device could prohibit the escape of
chemicals outside the system. Due to the lack of evidence supporting its intended use in closed system
functional fluids, occupational exposures for functional fluid (closed system) of 1,4-dioxane were not
assessed.
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MFG/IMPORT
PROCESSING
INDUSTRIAL and COMMERCIAL USES3
RELEASES and WASTE DISPOSAL
Manufacture
(Includes Import)
(1 million lbs.)
Processing as a
Reactant/lntermediate
(Not reported in 2016 CDR)
Repackaging
(270,000 lbs.)
Non-lncorporative
Activities
(270,000 lbs.)
Recycling
Processing Aids, Not Otherwise
Listed
(270,000 lbs.)
e.g., wood pulping, pharmaceutical
manufacture, etching of fluoropolymers
Functional Fluids
(Open and Closed Systems)
(<150,000 lbs.)
e.g., hydraulicfluid
Laboratory Chemicals
(<150,000 lbs.)
e.g., laboratory reagent
Adhesivesand Sealants
e.g., film cement
Other Uses
Spray Polyurethane Foam; Printing and
Printing Compositions, Dry Film
Lubricant
Disposal
See Figure 2-3 for Environmental
Releases and Wastes
I I Manufacture (Includes Import) l l Processing ~ Industrial uses of 1,4-dioxane.
~ Industrial and/or commercial uses of 1,4-dioxane
Figure 2-1. 1,4-Dioxane Life Cycle Diagram
The life cycle diagram depicts the conditions of use that are within the scope of the risk evaluation during various life cycle stages including
manufacturing, processing, use (industrial or commercial) and disposal. The production volumes shown are for reporting year 2015 from the
2016 CDR reporting period (U.S. EPA. 2016a).
a See Table 2-4 for additional uses not mentioned specifically in this diagram.
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Table 2-4. Categories and Subcategories of Conditions of Use Included in the Scope of the
Risk Evaluation
Life Cycle Stage
Category 11
Subcategory h
References
Manufacture
Domestic
manufacture
Domestic
manufacture
Use document. 0-
OPPT-2016-0723 -0003;
Public Comment, EPA-H0-
OPPT-2016-0723-0012
Import
Import
Use document. O-
OPPT-2016-0723-0003
Repackaging
Public Comment. EPA-HO-
OPPT-2016-0723 -00! 2
Processing
Processing as a
reactant
Pharmaceutical
intermediate
Use document. O-
OPPT-2016-0723-0003
Polymerization
catalyst
Use document. O-
OPPT-2016-0723-0003
Non-incorporative
Pharmaceutical and
medicine
manufacturing
(process solvent)
Public Comment. EPA-HO-
OPPT-2016-07:
Basic organic
chemical
manufacturing
(process solvent)
Public Comment. EPA-HO-
OPPT-2016-07:
Recycling
Recycling
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l.ife Cycle Stage
Category 11
Subcategory h
References
\Vcllinu and
dispersing agent in
textile processing
I 'so document.
OPPT-2016-0723-0003
Polymerization
catalyst
Use document. EPA-HO-OPPT-
2016-0723-0003
Purification of
pharmaceuticals
Use document. EPA-HO-OPPT-
2016-0723-0003
Etching of
fluoropolymers
Public Comment, EPA-HO-
OPPT-2016-0723-0012
Functional fluids
(open and closed
system)
Polyalkylene glycol
lubricant
Use document, O-
OPPT-2016-0723-0003
Synthetic
metalworking fluid
Use document. : " A HO-
OPP' 23-0003
Cutting and tapping
fluid
Use document, O-
OPPT-2016-0723-0003
Hydraulic fluid
Use document. O-
OPPT-2016-0723-0003
Industrial use,
potential commercial
use
Laboratory
chemicals
Chemical reagent
Use document, O-
OPPT-2016-0723-0003:
Public Comment, EPA-HO-
OPP' 23-0009
Reference material
Use document, O-
OPPT-2016-0723-0003
Spectroscopic and
photometric
measurement
Use document, O-
OPPT-2016-0723-0003:
Public Comment, EPA-HO-
OPPT-2016-0723-0009
Liquid scintillation
counting medium
Use document, l'P \ HO-
OPP' 23-0003
Stable reaction
medium
Use document, O-
OPPT-2016-0723-0003
Cryoscopic solvent
for molecular mass
determinations
Use document, O-
OPPT-2016-0723-0003
Preparation of
histological sections
for microscopic
examination
Use document, O-
OPPT-2016-0723-0003
Adhesives and
sealants
Film cement
Use document. : " A HO-
OPPT-2016-0723-0003;
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l.ife Cycle Stage
Category 11
Subcategory h
References
Public Comment.
OPPT-2016-0723-002 i
Other uses
Spray polyurethane
foam
Printing and
printing
compositions,
including 3D
printing
Dry film lubricant
Use document 0-
OPPT-2016-0723-0003:
Public Comment, EPA-HO-
OPPT-2016-0723-0012
Disposal
Disposal
Industrial pre-
treatment
Industrial
wastewater
treatment
Publicly owned
treatment works
(POTW)
Underground
injection
Municipal landfill
Hazardous landfill
Other land disposal
Municipal waste
incinerator
Hazardous waste
incinerator
Off-site waste
transfer
a These categories of conditions of use appear in the initial life cycle diagram, reflect CDR codes and broadly
represent conditions of use for 1,4-dioxane in industrial and/or commercial settings.
b These subcategories reflect more specific uses of 1,4-dioxane.
2.4.2 Conceptual Models
The conceptual models for this risk evaluation are shown in Figures 2-2 and 2-3. EPA considered
the potential for hazards to workers and occupational non-users (ONUs) from inhalation,
workers dermal exposure and hazards to the environment resulting from exposure to aquatic
species as shown in the preliminary conceptual models and analysis plan of the 1,4-dioxane
scope document ( 317d). Workers, ONUs, and bystanders and certain other groups of
individuals who may experience greater exposures than the general population due to proximity
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to conditions of use to be potentially exposed or susceptible subpopulations. Workers and ONUs
could be exposed via pathways that are distinct from the general population due to unique
characteristics (e.g., life stage, behaviors, activities, duration) that increase exposure, and
whether groups of individuals have heightened susceptibility.
The conceptual models indicate the exposure pathways and exposure routes of 1,4-dioxane to
workers from industrial and commercial activities, and environmental releases and wastes. The
problem formulation documents refined the initial conceptual models and analysis plans that
were provided in the scope documents (U.S. EPA. 2018c). EPA has included the mapping tables
that described all possible scenarios and whether they would be further evaluated. This was
developed during problem formulation and is presented in Appendix B. The environmental
characterization for the pathways included in the risk evaluation is described in Section 5.1.
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INDUSTRIAL AND COMMERCIAL EXPOSURE PATHWAY EXPOSURE ROUTE RECEPTORSd HAZARDS
ACTIVITIES / USES*
Manufacture
(Including Import)
Hazards Potentially Associated
with Acute and/or Chronic
Exposures
Liquid Contact
Dermal
Workers®
Processing:
• Processing as a
reactant/intermediate
• Repackaging
• Non-incorporative
Occupational
Vapor/ Mist
Fugitive
Emissions''
Recycling
Processing Aids, Not
Otherwise Listed
Functional Fluids
(Open and Closed Systems)
La boratory Chem i ca Is
Other Industrial or
Commercial Uses
Waste Handling,
Treatment and
Disposal
Wastewater, Liquid Wastes, Solid Wastes
Figure 2-2.1,4-Dioxane Conceptual Model for Industrial and Commercial Activities and Uses: Potential Exposures and
Hazards
The conceptual model presents the exposure pathways, exposure routes and hazards to human receptors from industrial and
commercial activities and uses of 1,4-dioxane that EPA analyzed in this draft risk evaluation.
a Additional uses of 1,4-dioxane are included in Table 2-4.
b Fugitive air emissions are those that are not stack emissions (emissions that occur through stacks, confined vents, ducts, pipes or other confined air streams),
and include fugitive equipment leaks from valves, pump seals, flanges, compressors, sampling connections, open-ended lines; evaporative losses from surface
impoundment and spills; and releases from building ventilation systems.
0 Based on physical chemical properties, 1,4-dioxane in mists that deposit in the upper respiratory tract will likely be rapidly absorbed in the respiratory tract or
evaporate and were considered in the inhalation exposure assessment.
d Receptors include potentially exposed or susceptible subpopulations.
e EPA also considered the effect that engineering controls and/or personal protective equipment (PPE) have on occupational exposure levels.
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RELEASES AND WASTES FROM EXPOSURE PATHWAY RECEPTORS HAZARDS
INDUSTRIAL / COMMERCIAL USES
Direct
Discharge
Water/
Sediment
Indirect
Discharge
Biosolids
Soil
POTW
Industrial WWT
Industrial Pre-
Aquatic
Species
Hazards Potentially Associated with Acute
and/or Chronic Exposures:
Figure 2-3.1,4-Dioxane Conceptual Model for Environmental Releases and Wastes: Potential Exposures and Hazards
The conceptual model presents the exposure pathways, exposure routes and hazards to human and environmental receptors from
environmental releases and wastes of 1,4-dioxane that EPA analyzed in problem formulation. Analyses were conducted using physical
and chemical properties, fate information and surface water modeling during problem formulation. EPA has included the results of the
analyses in Section 3.3.1, Appendix D, and Appendix E) and risk characterizations based on these analyses are included in the risk
characterization (Section 5.1).
a Industrial wastewater or liquid wastes may be treated on-site and then released to surface water (direct discharge), or pre-treated and released to POTW (indirect
discharge).
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2.5 Systematic Review
TSCA requires EPA to use scientific information, technical procedures, measures, methods,
protocols, methodologies and models consistent with the best available science and base
decisions on the weight of the scientific evidence. Within the TSCA risk evaluation context, the
weight of the scientific evidence is defined as "a systematic review method, applied in a manner
suited to the nature of the evidence or decision, that uses a pre-established protocol to
comprehensively, objectively, transparently, and consistently identify and evaluate each stream
of evidence, including strengths, limitations, and relevance of each study and to integrate
evidence as necessary and appropriate based upon strengths, limitations, and relevance" (40
C.F.R. 702.33).
To meet the TSCA § 26(h) science standards, EPA used the TSCA systematic review process
described in the Application of Systematic Review in TSCA Risk Evaluations document (U.S.
EPA. 2.018b). The process complements the risk evaluation process in that the data collection,
data evaluation and data integration stages of the systematic review process are used to develop
the exposure and hazard assessments based on reasonably available information. EPA defines
"reasonably available information" to mean information that EPA possesses, or can reasonably
obtain and synthesize for use in risk evaluations, considering the deadlines for completing the
evaluation (Citation to Final Rule).
EPA is implementing systematic review methods and approaches within the regulatory context
of the amended TSCA. Although EPA will make an effort to adopt as many best practices as
practicable from the systematic review community, EPA expects modifications to the process to
ensure that the identification, screening, evaluation and integration of data and information can
support timely regulatory decision making under the aggressive timelines of the statute.
2.5.1 Data and Information Collection
EPA planned and conducted a comprehensive literature search based on key words related to the
different discipline-specific evidence supporting the risk evaluation (e.g., environmental fate and
transport; engineering releases and occupational exposure; exposure to general population,
consumers and environmental exposure; and environmental and human health hazard). EPA then
developed and applied inclusion and exclusion criteria during the title and abstract screening to
identify information potentially relevant for the risk evaluation process. The literature and
screening strategy as specifically applied to 1,4-dioxane is described in the Strategy for
Conducting Literature Searches for 1,4-Dioxane: Supplemental File for the TSCA Scope
Document and the results of the title and abstract screening process were published in the 1, 4-
Dioxane (CASRN123-91-1) Bibliography: Supplemental File for the TSCA Scope Document;
0 v < < \ 2017j).
For studies determined to be on-topic (or relevant) after title and abstract screening, EPA
conducted a full text screening to further exclude references that were not relevant to the risk
evaluation. Screening decisions were made based on eligibility criteria documented in the form
of the populations, exposures, comparators, and outcomes (PECO) framework or a modified
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framework1. Data sources that met the criteria were carried forward to the data evaluation stage.
The inclusion and exclusion criteria for full text screening for 1,4-dioxane are available in
Appendix F of the Problem Formulation of the Risk Evaluation for 1,4-Dioxane (U.S. EPA.
2018c).
Although EPA conducted a comprehensive search and screening process as described above,
EPA made the decision to leverage the literature published in previous assessments2 when
identifying relevant key and supporting data3 and information for developing the 1,4-dioxane
risk evaluation. This is discussed in the Strategy for Conducting Literature Searches for 1,4-
Dioxane: Supplemental Document to the ISC A. Scope Document. In general, many of the key
and supporting data sources were identified in the comprehensive 1.4-Dioxar -91-1)
Bibliography: Supplemental File for the TSCA Scope Document (U.S. EPA. ). However,
there were instances that EPA missed relevant references that were not captured in the initial
categorization of the on-topic references. EPA found additional relevant data and information
using backward reference searching, which was a technique that will be included in future search
strategies. This issue was discussed in Section 4 of the Application of Systematic Review for
TSCA Risk Evaluations. Other relevant key and supporting references were identified through
targeted supplemental searches to support the analytical approaches and methods in the 1,4-
dioxane risk evaluation (e.g., to locate specific information for exposure modeling) or to identify
new data and information published after the date limits of the initial search.
EPA used previous chemical assessments to quickly identify relevant key and supporting
information as a pragmatic approach to expedite the quality evaluation of the data sources, but
many of those data sources were already captured in the comprehensive literature as explained
above. EPA also considered newer information not taken into account by previous chemical
assessments as described in the Strategy for Conducting Literature Searches for 1,4-Dioxane:
Supplemental Document to the TSCA. Scope Document. EPA then evaluated the confidence of the
key and supporting data sources as well as newer information instead of evaluating the
confidence of all the underlying evidence ever published on a chemical substance's fate and
transport, environmental releases, environmental and human exposure and hazards. Such
comprehensive evaluation of all of the data and information ever published for a chemical
substance would be extremely labor intensive and could not be achieved under the TSCA
statutory deadlines for most chemical substances especially those that have a data rich database.
Furthermore, EPA evaluated how EPA's evaluation of the key and supporting data and
1 A PESO statement was used during the Ml text screening of environmental fate and transport data sources. PESO
stands for Pathways and Processes, Exposure, Setting or Scenario, and Outcomes. A RESO statement was used
during the full text screening of the engineering and occupational exposure literature. RESO stands for Receptors,
Exposure, Setting or Scenario, and Outcomes.
2 Examples of existing assessments are EPA's chemical assessments (e.g. previous work plan risk assessments,
problem formulation documents), ATSDR's Toxicological Profiles, EPA's IRIS assessments and ECHA's dossiers.
This is described in more detail in the Strategy for Conducting Literature Searches for 1,4-Dioxane: Supplemental
File for the TSCA Scope Document (https://www.epa.gov/sites/production/files/2017-06/documents/14-
dioxane lit search strategy 053017.pdf).
3 Key and supporting data and information are those that support key analyses, arguments, and/or conclusions in the
risk evaluation.
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information and newer information would change the previous conclusions presented in the
previous assessments.
Using this pragmatic approach, EPA evaluated the confidence of the key and supporting data
sources as well as newer information instead of evaluating the confidence of all the underlying
evidence ever published on 1,4-dioxane's fate and transport, environmental releases,
environmental and human exposure and hazards. This allowed EPA to maximize the scientific
and analytical efforts of other regulatory and non-regulatory agencies by accepting for the most
part the relevant scientific knowledge gathered and analyzed by others except for influential
information sources that may have an impact on the weight of the scientific evidence and
ultimately the risk findings. The influential information (i.e., key/supporting) came from a
smaller pool of sources subject to the rigor of the TSCA systematic review process to ensure that
the risk evaluation uses the best available science and the weight of the scientific evidence.
Figures 2-4, 2-5, 2-6, 2-7, and 2-8 depict the literature flow diagrams illustrating the results of
this process for each scientific discipline-specific evidence supporting the draft risk evaluation.
Each diagram provides the total number of references at the start of each systematic review stage
(i.e., data search, data screening, data evaluation, data extraction/data integration) and those
excluded based on criteria guiding the screening and data quality evaluation decisions.
EPA made the decision to bypass the data screening step for data sources that were highly
relevant to the draft risk evaluation as described above. These data sources are depicted as
"key/supporting data sources" in the literature flow diagrams. Note that the number of
"key/supporting data sources" were excluded from the total count during the data screening stage
and added, for the most part, to the data evaluation stage depending on the discipline-specific
evidence. The exception was the engineering releases and occupational exposure data sources
that were subject to a combined data extraction and evaluation step (Figure 2-5).
Excluded References (n=2,939)
*Key/supporting
data sources (n=l)
Excluded: Ref that are
unacceptable based on the
evaluation criteria (n=0)
Data Extraction/Data Integration (n=l)
Data Search Results (n= 2,940)
Data Screening (n=2,939)
Data Evaluation (n=l)
Figure 2-4. Literature Flow Diagram for Environmental Fate and Transport Data Sources
Note: Following data screening, EPA determined during problem formulation that no environmental pathways would
be further analyzed ("U.S. EPA. 2018c). EPA evaluated a biodegradation study that was a key source in a previous EPA
assessment (U.S. EPA. 2015) and is discussed in Section 3.1.
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* These are key and supporting studies from existing assessments (e.g., I\1 'A IRIS assessments, ATSDR assessments,
ECHA dossiers) that were considered highly relevant for the TSCA risk evaluation. These studies bypassed the data
screening step and moved directly to the data evaluation step.
Key/supporting
data sources
(n=14)
Excluded References (n=2883';
Data Sources that were not
integrated (n=44)
Data Search Results (n=2981 )
Excluded: Ref that are
unacceptable based on
evaluation criteria (n=38)
Data Integration (n=16)
Data Extraction.i'Data Evaluation (n =98}
Data Screening (n=2967)
*The quality of data in these sources (n=44) were acceptable for risk assessment purposes, but they were ultimately
excluded from further consideration based on EPA's integration approach for environmental release and occupational
exposure data/information. EPA's approach uses a hierarchy of preferences that guide decisions about what types of
data,'information are included for further analysis, synthesis and integration into the environmental release and
occupational exposure assessments. EPA prefers using data with the highest rated quality among those in the higher
level of the hierarchy of preferences (i.e.. data > modeling > occupational exposure limits orreiease limits). If warranted.
EPA may use data/information of lower rated quality as supportive evidence in the environmental release and
occupational exposure assessments.
Figure 2-5. Literature Flow Diagram for Engineering Releases and Occupational Exposure
Data Sources.
Note: Key and supporting studies (n=14) were identified from existing assessments (e.g., EPA IRIS assessments, ATSDR
assessments, ECHA dossiers) and were considered highly relevant for the TSCA risk evaluation. These studies bypassed the
data screening step and moved directly to the data evaluation step. EPA conducted a literature search to determine relevant
references for assessing engineering releases and occupational exposures for 1,4-dioxane within the scope of the risk
evaluation. This search identified 2,981 references, including relevant supplemental documents. Of these, 2,967 were
forwarded for screening of the title, abstract, and/or full text for an inclusion/exclusion (RESO) screening process for
relevancy and quality. Of these, 98 references were recommended for data evaluation across up to four major study types,
each with their respective evaluation metrics. Sixteen of these were forwarded for further extraction and data integration.
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"Key/supporting
data sources (n= 0)
Excluded References (n=272)
Data Search Results (n= 272)
Excluded: Ref that are
unacceptable based on
evaluation criteria (n=0)
Data Extraction;Data Integration (n=0)
Data Evaluation (n= 0)
Data Screening (n=272 )
Figure 2-6. Literature Flow Diagram for General Population, Consumer and
Environmental Exposure Data Sources
Note: EPA's problem formulation laid out the scope of the evaluation and used reasonably available sources of
information to evaluate potential exposures to environmental receptors (aquatic) pathways from 1,4-dioxane. The
confidence of these data sources was considered acceptable for risk evaluation purposes and thus they were used to
support the analyses during scoping and problem formulation. EPA determined during problem formulation that
environmental pathways were within scope but would not be further analyzed based on quantitative and qualitative
analyses covering ecological pathways (U.S. EPA. 2018c). These analyses were made ahead of the data screening stage
for these data sources, and therefore, all exposure references were excluded, as they did not meet the risk evaluation
1'1'C'O statement.
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Excluded References due to
ECOTOX Criteria
(n = 42)
Excluded References due to
ECOTOX Criteria
(n = 3239)
Data Extraction I Data Integration (n = 9)
Data Evaluation (n = 14)
Full Text Screening (n = 56)
Excluded References
that are out of scope
(n = 5)
Data Search Results (n = 3302)
Title/Abstract Screening (n = 3295)
Figure 2-7. Literature Flow Diagram for Environmental Hazard Data Sources
Note: The environmental hazard data sources were identified through literature searches and screening strategies using
the ECOTOX Standing Operating Procedures. Additional details about the process can be found in the Strategy for
Conducting Literature Searches for 1,4-Dioxane: Supplemental File for the TSCA Scope Document, EPA-HQ-OPPT-
2016-0723. During problem formulation, EPA made refinements to the conceptual models resulting in the elimination
of the terrestrial exposure pathway from further analysis. Thus, environmental hazard data sources on terrestrial
organisms were considered out of scope and excluded from data quality evaluation.
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1=7
Keyftupporting data
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2.5.3 Data Integration
Data integration includes analysis, synthesis and integration of information for the risk
evaluation. During data integration, EPA considers quality, consistency, relevancy, coherence
and biological plausibility to make final conclusions regarding the weight of the scientific
evidence. As stated in the Application of Systematic Review in TSCA Risk Evaluations (U.S.
EPA, 2018b), data integration involves transparently discussing the significant issues, strengths,
and limitations as well as the uncertainties of the reasonably available information and the major
points of interpretation (U.S. EPA. 2018d). EPA defines "reasonably available information" to
mean information that EPA possesses, or can reasonably obtain and synthesize for use in risk
evaluations, considering the deadlines for completing the evaluation (Procedures for Chemical
Risk Evaluation Under the Amended Toxic Substances Control Act (82 FR 33726)).
EPA used previous assessments (see Table 2-3) to identify key and supporting information and
then analyzed and synthesized available evidence regarding 1,4-dioxane's chemical properties,
environmental fate and transport properties and its potential for exposure and hazard. EPA's
analysis also considered recent data sources that were not considered in the previous assessments
(Section 0) as well as reasonably available information on potentially exposed or susceptible
subpopulations.
The exposures and hazards sections describe EPA's analysis of the influential information (i.e.,
key and supporting data) that were found acceptable based on the data quality reviews as well as
discussion of other scientific knowledge using the approach described in Section 0. The exposure
section also describes whether aggregate or sentinel exposures to a chemical substance were
considered under the conditions of use within the scope of the risk evaluation, and the basis for
that consideration
3 EXPOSURES
3.1 Fate and Transport
EPA gathered and evaluated environmental fate information according to the process described
in the Application of Systematic Review in TSCA Risk Evaluations (U.S. EPA. 2018b).
Reasonably available environmental fate data were selected for use in the current evaluation.
Furthermore, EPA used previous regulatory and non-regulatory 1,4-dioxane assessments to
inform the environmental fate and transport information discussed in this section and Appendix
D. EPA had confidence in the information used in the previous assessments of 1,4-dioxane (see
Table 2-3) to describe the environmental fate and transport of 1,4-dioxane and thus used it to
make scoping decisions.
Because EPA determined during problem formulation that no environmental pathways would be
further analyzed, EPA limited data extraction and evaluation to key data sources used in previous
assessments (see Table 2-3), as described in Section 2.5.2. Thus, EPA assessed the quality of a
• Risk Evaluation for 1,4-Dioxane, Systematic Review Supplemental File: Data Quality Evaluation of Human Health Hazard
Studies, Animal and In Vitro Studies
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microcosm study on soil biodegradation (Kellev et al. 2001) based on the data quality criteria
described in the Application of Systematic Review in TSCA Risk Evaluations (U.S. EPA. 2018b)
and the study was rated 'high' confidence. The data evaluation tables describing review of the
sources used in this assessment can be found in the supplemental document, Data Quality
Evaluation of Environmental Fate and Transport Studies {U.S. EPA, 2019, HERO ID}.
Other fate estimates were based on modeling results from EPI Suite™ ( 012c). a
predictive tool for physical/chemical and environmental fate properties
(https://www.epa.gov/tsca-screenine4ools/epi-siiitetm-estimation-program4nteiface). The inputs
and setup of EPI Suite™ runs for 1,4-dioxane are described in Appendix D. EPI Suite™ was
reviewed by the EPA Science Advisory Board
(http://YOsemite.epa.gOv/sab/sabprodiict.nsf/02ad90bl36fc21ef85256eba00436459/CCF982BA.9
F9CFCFA8525735200739805/$File/i f) and the individual models have been peer-
reviewed in numerous articles published in technical journals. Citations for such articles are
available in the EPI Suite™ help files.
The 1,4-dioxane environmental fate characteristics and physical-chemical properties used in fate
assessment are presented in Table 3-1. EPA used EPI Suite™ estimations and reasonably
available fate data to characterize the environmental fate and transport of 1,4-dioxane. As part of
problem formulation, EPA also analyzed the sediment and land-applied biosolids pathways. The
results of the analyses are described in the 2018 problem formulation for 1,4-dioxane (
2018c) and presented again in Appendix D. Please note that this section and Appendix D may
also cite other data sources as part of the reasonably available information on the fate and
transport properties of 1,4-dioxane. EPA did not subject these other data sources to the later
phases of the systematic review process (i.e., data evaluation and integration) based on the
approach explained above.
Table 3-1. Environmental Fate Characteristics of 1,4-Dioxane
Property or
K ml point
Value"
References
Data Quality
Rating
Direct
photodegradati on
Not expected to undergo direct
photolysisb
(ToxNet Hazardous
Substances Data
Ban! S
EPA. 2015)
Not applicable
Indirect
photodegradati on
4.6 hours (estimated for
atmospheric degradation)0
0 4 ; 2^1 %
2012c)
High
Hydrolysis half-life
Does not undergo hydrolysisb
0 s nn. _yu\
Wilbur et al.. 2012)
Not applicable
Biodegradation
0% in 120 days, 60% in 300
days (aerobic in soil
microcosm)
(
Kellev et al.. 2001)
High
Bioconcentration
factor (BCF)
3 (estimated via linear
regression from Log Kow)c
(! ? * J- \ iO 1 lc)
High
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Property or
K ml point
Value"
References
l):il;i Quality
Rating
0.9 (estimated via Arnot-Gobas
quantitative structure-activity
relationship [QSAR])C
Bioaccumulation
factor (BAF)
0.9 (estimated via Arnot-Gobas
QSAR)C
(! ? * J- \ iO 15,
2012c)
High
Organic carbon:water
partition coefficient
(log Koc)
0.4 (estimated)0
0 s nn. _yu\
2012c)
High
a Measured unless otherwise noted.
b 1,4-Dioxane lacks functional groups susceptible to the degradation mechanism
Information was estimated using EPI Suite™ (U.S. EPA. 2012c)
The EPI Suite™ module that estimates chemical removal in sewage treatment plants (STPWIN)
was run using default settings (details available in the STPWIN help file in EPI Suite™) and
estimated that 0.3% of 1,4-dioxane in wastewater will be removed by volatilization while < 2%
of 1,4-dioxane will be removed by adsorption. The organic carbon-water partition coefficient,
log Koc, reported in previous assessments of 1,4-dioxane were in the range of 0.4 - 1.23 (
t V \ .v '13c; AT SDR, * I _ / * M' \ 2010: ECJRC. 2002; NICNAS. 19981 and log Koc
values within this range are associated with low sorption to soil, sediment, and suspended solids.
Aerobic biodegradation of 1,4-dioxane is slow or negligible (U.S. EPA. 2015; AT SDR. 1:01 J;
NTP. 2.011; Health Canada. 2.010; ECJRC. 2002.; NICNAS. 1998) and will not contribute
significantly to removal of 1,4-dioxane in wastewater treatment. Thus, concentrations of 1,4-
dioxane in biosolids will be essentially equal to concentrations in the overlying wastewater, and
the 1,4-dioxane contained in biosolids will almost all be in the aqueous phase rather than
adsorbed to particles. Similarly, 1,4-dioxane concentrations in sediment are expected to be nearly
equal to concentrations in overlying water, with 1,4-dioxane almost exclusively in the aqueous
phase of sediment samples.
Due to its water solubility (>800 g/L; Table 2-1) and Henry's Law constant (4.8 x 10"6 atm-
m3/mole at 25°C; Table 2-1), 1,4-dioxane is expected to demonstrate limited volatility from
water surfaces, moist soil, and other moist surfaces such as land-applied biosolids. Once it enters
the environment, 1,4-dioxane is not expected to significantly adsorb to suspended solids and
sediment based on its log Koc and is therefore expected to migrate to surface waters and
groundwater.
1,4-Dioxane is expected to volatilize from dry surfaces and dry soil due to its vapor pressure (40
mm Hg at 25°C). In the atmosphere, it is expected to react with hydroxyl radicals with an
indirect photolysis half-life on the order of hours (U.S. EPA. 2012c).
The estimated bioconcentration and bioaccumulation factors are 3 or below (Table 3-1) and
measured bioconcentration factors for 1,4-dioxane are 0.7 or below (ECJRC. 2002). Therefore,
1,4-dioxane has low bioaccumulation potential.
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Overall, 1,4-dioxane is not likely to accumulate in wastewater biosolids, sediment, soil, or biota,
and is expected to largely remain in aqueous phases where it will slowly biodegrade or volatilize
and then degrade by indirect photolysis.
3.2 Environmental Releases
Releases to the environment from conditions of use (e.g., industrial and commercial processes)
are one component of potential exposure and may be derived from reported data that are
obtained through direct measurement, calculations based on empirical data and/or assumptions
and models.
Under the Emergency Planning and Community Right-to-Know Act (EPCRA) Section 313, 1,4-
dioxane has been a Toxics Release Inventory (TRI)-reportable substance since 1987. The TRI
database includes information on disposal and other releases of 1,4-dioxane to air, water, and
land, in addition to how it is being managed through recycling, treatment, and burning for energy
recovery. Based on 2015 TRI reporting, an estimated 35,402 lbs. of 1,4-dioxane was released to
surface water from industrial sources. See Table E-l in Appendix E for a TRI summary table and
further details on recent releases of 1,4-dioxane to various media.
3.3 Environmental Exposures
In the problem formulation, EPA presented an analysis on environmental exposures to aquatic
species based on releases to surface water. No additional information was received or identified
by the EPA following the publication of the problem formulation that would alter the analysis
and interpretations presented in the problem formulation. As reviewed during problem
formulation, 1,4-dioxane is present in environmental media such as groundwater, surface water,
and air. EPA conducted analysis of the environmental release pathways based on a qualitative
assessment of the physical-chemical properties and fate of 1,4-dioxane in the environment
(described in Section 3.1), and a quantitative comparison of hazards and exposures for aquatic
organisms as described in Section 4.1.2 of the problem formulation ( tOl 8c).
3.3.1 Environmental Exposures - Aquatic Pathway
As described in the problem formulation ( ;), an aquatic exposure assessment was
conducted using TRI and DMR release information to model predicted surface water
concentrations near discharging facilities. To examine whether near-facility surface water
concentrations could approach 1,4-dioxane's concentrations of concern, EPA employed a
conservative approach, using available modeling tools and data to estimate near-facility surface
water concentrations resulting from reported releases of 1,4-dioxane to surface water. High-end
surface water concentrations (i.e., those obtained assuming low receiving water body stream
flows) from all E-FA.ST 2.0 M (l ' \ C X _^14c) runs ranged from 0.006 |ig/L to 11,500 |ig/L.
National-scale monitoring data from EPA's STOrage and RETreival (STORET) and National
Water Information System (NWIS) for the past ten years, shows that 1,4-dioxane is detected in
surface water. The data points show a detection rate of approximately 6% for this media, with
detections ranging from 0.568 to 100 |ig/L. The E-FAST results and monitoring data were
compared to the acute and chronic aquatic concentrations of concern of 247,200 |ig/L and 14,500
|ig/L, respectively (see section 4.1). This aquatic exposure analysis and additional details about
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the approach and results are presented in and Appendix E. The analysis and determination of risk
are presented in the risk characterization and risk determination sections, respectively.
3.4 Human Exposures
3.4.1 Occupational Exposures
Occupational exposures could be direct or indirect and the magnitude of exposure for an
occupational worker could be a function of timeframe of exposures. The timeframes of exposure,
which depend on occupational mobility, could vary for different population groups. ONUs are
workers at the facility who are neither directly perform activities near the 1,4-dioxane source
area not regularly handle 1,4-dioxane. The job classifications for ONUs could be dependent on
the conditions of use. For example, ONUs for manufacturing include supervisors, managers, and
tradesmen that may be in the manufacturing area, but do not perform tasks that result in the same
level of exposures as production workers. It could be challenging to characterize direct and
indirect exposures to contaminants since it is not uncommon for employees at certain facility to
perform multiple types of tasks throughout the work day. The workers could perform activities
that bring them into direct contact with 1,4-dioxane and they could also perform additional tasks
as ONUs. The groupings of employees are not necessarily distinct as workers perform a variety
of tasks over the course of the day that could result in direct exposure and indirect exposure
throughout the day. Indirect exposures of employees working near contaminants could be
difficult to separate due to overlapping tasks that makes it difficult to delineate exposures of
workers and ONUs.
EPA evaluated acute and chronic inhalation exposures to workers and ONUs in association with
1,4-dioxane manufacturing, import and repackaging, its use in industrial applications, open
system functional fluids, spray polyurethane foam insulation, laboratory chemicals, film cement,
printing inks (3D), dry film lubricant, and disposal. Appendix G.6 provides additional detail on
the mapping of the conditions of use to the Occupational Exposure Scenario (OES) groups used
in this risk evaluation. EPA used inhalation monitoring data from literature sources where
available and that met data evaluation criteria (see Section 2.5); and modeling approaches to
estimate potential inhalation exposures where inhalation monitoring data were not available.
EPA modeled inhalation exposures using the following models: the EPA AP-42 Loading Model,
the EPA Mass Balance Inhalation Model, and the EPA Total PNOR PEL-Limiting Model. More
information about these models may be found in Section 3.4.1.1. EPA also estimated dermal
doses for workers in these scenarios since dermal monitoring data was not reasonably available.
EPA modeled dermal doses using the EPA Dermal Exposure to Volatile Liquids Model which
improves upon the existing EPA 2-HandDermal Exposure model by accounting for the effect of
evaporation on dermal absorption for volatile chemicals and the potential exposure reduction due
to glove use. More information about this model and how it was used may be found in Section
3.4.1.14 and Appendix G.7. EPA does not expect dermal exposures for occupational non-users
due to no direct contact with the chemical.
Components of the Occupational Exposure Assessment
The occupational exposure assessment for each condition of use comprises the following
components:
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• Process Description of the condition of use, including the role of the chemical in the use;
process vessels, equipment, and tools used during the condition of use; and descriptions
of the worker activities, including an assessment for potential points of worker exposure.
• Number of Sites that use the chemical for the given condition of use.
• Number of Workers and ONUs potentially exposed to the chemical for the given
condition of use. CDR data to identify the number of sites where exposure may occur and
approximate workers who may be exposed to the chemicals. Unless mentioned otherwise
in this report, the total number of workers and ONUs are number of personnel per site per
day. The details on estimation of the number of workers and ONUs are discussed in
Sections 3.4.1.1 and each conditions of use, and Appendix G.5.
• Central tendency and high-end estimates of inhalation exposure to workers and
occupational non-users. See Section 3.4.1.1 for a discussion of EPA's statistical analysis
approach for assessing inhalation exposure.
• Dermal Exposure estimates for multiple scenarios, accounting for simultaneous
absorption and evaporation, and different protection factors of glove use. The OSHA
Personal Protective Equipment Standard, 29 CFR § 1910.132, requires that employers
provide personal protective equipment such as hard hats, goggles, gloves, and respirators
to protect employees from hazardous exposures. The OSHA recommends employers
utilize the hierarchy of controls for reducing or removing hazardous exposures. The most
effective controls are elimination, substitution, or engineering controls. 29 CFR §
1910.134(a)(1) establishes OSHA's hierarchy of controls by requiring the use of feasible
engineering controls as the primary means to control air contaminants. Respirators are
required when effective engineering controls are not feasible. Gloves and other PPE are
the last means of worker protection in the hierarchy of controls. When effective
engineering and administrative controls are not feasible to adequately protect the health
of workers and maintain compliance with other OSHA statutory and regulatory
requirements under 29 CFR § 1910.1000, employers could provide PPE to protect
employees (29 CFR § 1910.134(a)(1)).
• Users include female and male adult workers (>16 years old) exposed to 1,4-dioxane for
8-hour exposure
• ONUs include female and male adult workers (>16 years old) exposed to 1,4-dioxane
indirectly by being in the same work area of the building.
3.4.1.1 Occupational Exposures Approach and Methodology
EPA performed a literature search to find descriptions of processes involving 1,4-dioxane and
worker activities that could potentially result in occupational exposures. The on-topic sources
were then screened against inclusion criteria in the RESO (Receptors, Exposures,
Setting/Scenario, Outcomes) statement and the relevant sources were further evaluated using the
data quality criteria in the Application of Systematic Review in TSCA Risk Evaluations (U.S.
EPA. 2018b). EPA identified 98 potentially useful sources based on literature search, of which
65 sources were determined to have potentially useful exposure information (see Figure 2-5).
Sources with an overall confidence score of less than 4 were considered acceptable in the
systematic review. Of these 65 sources, 27 were deemed to be acceptable. Sixteen of the
acceptable sources were determined to have exposure data relevant to the conditions of use and
were therefore used in this evaluation. A summary of the data quality evaluation results for the
1,4-dioxane occupational exposure sources are presented in Appendix G.l ("Systematic Review
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Supplemental File for the TSCA Risk Evaluation: Data Quality Evaluation for Occupational
Exposure and Release Data").
For the integration of occupational exposure data/information, EPA considered any relevant data
that it determined to be acceptable for use. The hierarchy found later in this section under
"General Inhalation Exposures Approach and Methodology" presents the preferences among the
primary types of data/information to be analyzed, synthesized and integrated for the occupational
exposure assessments in this risk evaluation.
Additional Data Sources
EPA used a variety of sources to supplement the data found through the Systematic Review
process. The additional sources included relevant NIOSH Health Hazard Evaluations, Generic
Scenarios, and Emission Scenario Documents. These sources were sometimes used to provide
process descriptions of the conditions of use as well as estimates for the number of sites and
worker counts.
CDR data was also used to provide a basis to estimate the numbers of sites, workers, and ONUs.
EPA supplemented the available CDR data with U.S. economic data using the following
methods:
1. Identification of the North American Industry Classification System (NAICS) codes for
the industry sectors associated with these uses.
2. Estimation of total employment by industry/occupation combination using the Bureau of
Labor Statistics" Occupational Employment Statistics (OES) data (BLS. ^ ).
3. Refinement of the OES estimates where they are not sufficiently detailed by using the
U.S. Census' Statistics of US Businesses (SUSB) ( nsus Bureau. 2016a) data on
total employment by 6-digit NAICS.
4. Use market penetration data (where available) to estimate the percentage of employees
likely to be using 1,4-dioxane instead of other chemicals.
5. Combine the data generated in Steps 1 through 4 to produce an estimate of the number of
establishments and employees using 1,4-dioxane in each industry/occupation
combination, and sum these to arrive at a total estimate of the number of employees with
exposure.
Market penetration data for 1,4-dioxane were not available for any condition of use. Without
these data, it is unknown what portion of a given set of sites use 1,4-dioxane. Absent this
information, EPA generally assumes that all sites involve 1,4-dioxane. Therefore, site, worker,
and ONU numbers considered could be overestimated.
General Dermal Exposures Approach and Methodology
EPA estimated dermal exposures using the EPA Dermal Exposure to Volatile Liquids Model.
This model accounts for evaporation, and glove usage which may provide a more refined
estimate of exposure than the existing EPA 2-HandDermal Exposure model. Additional details
about how this model was used is in Section 3.4.1.14.
General Inhalation Exposures Approach and Methodology
EPA developed occupational exposure values representative of central tendency conditions and
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high-end conditions. A central tendency was assumed to be representative of occupational
exposures in the center of the distribution for a given condition of use. EPA used the 50th
percentile (median), mean (arithmetic or geometric), or mode of a distribution as representative
of the central tendency scenario. EPA's preference was to provide the 50th percentile of the
distribution. However, if the full distribution was not known, EPA assumed that the mean, mode,
or midpoint of the distribution represented the central tendency depending on the statistics
available for the distribution (U.S. EPA. 1992).
A high-end exposure estimate was defined to be representative of occupational exposures that
occur at probabilities above the 90th percentile but below the 99.9th percentile, the exposure of
the individual with the highest exposure ( 32). EPA considered high-end results at
the 95th percentile. If the 95th percentile was not available, EPA used a different percentile
greater than or equal to the 90th percentile but less than or equal to the 99.9th percentile,
depending on the statistics available for the distribution. If the full distribution was not known
and the preferred statistics were not available, EPA estimated a maximum or bounding estimate
in lieu of the high-end occupational exposure estimates. In each case, EPA makes clear the actual
percentile that was used.
For occupational exposures, EPA used measured or modeled air concentrations to calculate
exposure concentration metrics essential for risk assessment. These exposures are presented as 8-
hour time weighted averages (TWAs) and used to calculate acute exposure concentrations
(AECs), average daily concentrations (ADCs), and lifetime average daily concentrations
(LADCs). The ADC is used to estimate chronic, non-cancer risks and the LADC is used to
estimate chronic, cancer risks. These calculations required additional parameter inputs, such as
years of exposure, exposure duration and frequency, and lifetime years. See Appendix G.2 for
more information about parameters and equations used to calculate acute and chronic exposures.
For the final exposure result metrics, each of the input parameters (e.g., air concentrations,
working years, exposure frequency, lifetime years) were point estimates (i.e., a single descriptor
or statistic, such as central tendency or high-end). EPA estimated a central tendency and high-
end for each final exposure result metric using deterministic calculations and combinations of
point estimates of each parameter. EPA documented the method and rationale for selecting
parametric combinations to be representative of central tendency and high-end. A probabilistic
approach was generally not used in cases where monitoring-based data was available, but models
for that condition of use were not.
EPA followed the hierarchy below in selecting data and approaches for assessing inhalation
exposures. In the hierarchy, monitoring data is preferred over modeling approaches and
occupational exposure limits are least preferred. Within each of the three categories, the sources
are listed in a descending order of preference. For example, la is preferred over lb. Once a
satisfactory source of information is identified in this list, sources below that point are not used,
although they can provide useful information for other purposes of this evaluation. For example,
if la satisfies the data needs, no other sources of data in this hierarchy are typically used for
purposes of assessing inhalation exposures. However, if the quality of data is deemed too low or
uncertain, EPA will not use those data and will provide justification.
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1) Monitoring data:
a) Personal samples from directly applicable scenarios (e.g. personal breathing zone,
PBZ, non-CBI data from BASF for the Manufacturing Scenario)
b) Area samples from directly applicable scenarios (e.g. area data from a NIOSH
HHE for the Film Cement Scenario)
c) Personal samples from potentially applicable or similar scenarios (e.g. PBZ data
from a manufacturing site that makes a chemical with physical properties similar
to 1,4-dioxane)
d) Area samples from potentially applicable or similar scenarios (e.g. area data from a
site that processes a chemical with physical properties similar to 1,4-dioxane)
2) Modeling approaches:
a) Surrogate monitoring data from chemicals with similar properties. Surrogate data
was used to estimate the inhalation exposure from the thickness verification step in
the Spray Foam Application condition of use. Appendix G.6.7 provides more
details on this use of surrogate data.
b) Fundamental modeling approaches (e.g. modeling of the Spray Foam Application
Scenario)
c) Statistical regression modeling approaches
3) Occupational exposure limits:
a) Company-specific OELs (for site-specific exposure assessments, e.g., there is only
one manufacturer who provides to EPA their internal OEL but does not provide
monitoring data)
b) OSHA PEL
c) Other occupational exposure limits (ACGIH TLV, NIOSH REL, Occupational
Alliance for Risk Science (OARS) workplace environmental exposure level
(WEEL) [formerly by AIHA])
EPA reviewed workplace inhalation monitoring data collected by government agencies such as
OSHA and NIOSH, and monitoring data found in published literature (i.e., personal exposure
monitoring data and area monitoring data). Studies were evaluated using the evaluation strategies
laid out in the Application of Systematic Review in TSCA Risk Evaluations ( ,018b).
The supplemental file provides details of the data evaluations, including scores for each metric
and the overall study score for each information source.
Exposure values were calculated from the datasets provided in the sources depending on the size
of the dataset. For datasets with six or more data points (Hawkins et at... 1992 ; U.S. EPA. 1994).
central tendency and high-end exposures were estimated using the 50th percentile and 95th
percentile. For datasets with three to five data points, central tendency exposure was calculated
using the 50th percentile and the maximum was presented as the high-end exposure estimate.
These data sets are considered to have relatively more uncertainty than datasets with more
datapoints. For datasets with two data points, the midpoint was presented as a midpoint value
and the higher of the two values was presented as a higher value. These data sets are generally
considered to have high uncertainty. Finally, data sets with only one data point are considered
indicating appropriate rationale, but EPA cannot determine the statistical representativeness of
the values given the small sample size. Existing data collected on workers and at locations with a
greater-than-average potential for high exposures, under certain conditions, could have
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performed using a work/research plan as monitoring is generally performed when there are
questions concerning compliance with industrial hygiene standards. As such these data sets are
considered to have extremely high uncertainty associated with them. Specific details related to
each condition of use can be found in Sections 3.4.1.2 - 3.4.1.13. For each condition of use, these
values were used to calculate chronic (non-cancer and cancer) exposures. Equations and sample
calculations for chronic exposures can be found in Appendix G.3.
EPA estimated exposures using the following models when exposure monitoring data were
unavailable:
• EPA AP-42 Loading Model estimates vapor releases that occur when vapor is displaced
by liquid during container loading. It calculates a vapor generation rate (G) using the
physio-chemical properties of the chemical (U.S. EPA. 2013 b).
• EPA Mass Balance Inhalation Model estimates occupational inhalation exposures
assuming the air immediately around the source of exposure behaves as a well-mixed
zone. EPA used the vapor generation rate (G), calculated using the EPA AP-42 Loading
Model, in conjunction with this model to develop estimates of inhalation exposure (U.S.
EPA. 2.013b).
• EPA Total PNOR PEL-LimitinsModel estimates occupational inhalation exposures to
particulates containing the chemical. The estimate assumes that the worker exposure is
equal to the OSHA Permissible Exposure Limit (PEL) for Particulates, Not Otherwise
Regulated (PNOR), total particulate (U.S. EPA, 2013b).
Specific descriptions of the use of these models for each condition of use can be found in
Sections 3.4.1.2-3.4.1.13.
Respiratory Protection
OSHA's Respiratory Protection Standard (29 CFR § 1910.132) provides a summary of respirator
types by their assigned protection factor (APF). OSHA defines the APF to mean: the workplace
level of respiratory protection that a respirator or class of respirators is expected to provide to
employees when the employer implements a continuing, effective respiratory protection program
according to the requirements of the OSHA Respiratory Protection Standard. OSHA
recommends employers utilize the hierarchy of controls for reducing or removing hazardous
exposures. The most effective controls are elimination, substitution, or engineering controls.
Respirators, and any other personal protective equipment, are the last means of worker protection
in the hierarchy of controls and should only be considered when process design and engineering
controls cannot reduce workplace exposure to an acceptable level.
Exposure to 1,4-dioxane can cause irritation and is likely carcinogenic ( PR. 2012: Wilbur et
at... 2012). The United States has several regulatory and non-regulatory exposure limits for 1,4-
dioxane: an OSHA PEL of 100 ppm 8-hour TWA (360 mg/m3) with a skin notation, a NIOSH
Recommended Exposure Limit (REL) of 1 ppm (3.6 mg/m3) as a 30-minute ceiling and an
American Conference of Government Industrial Hygienists (ACGIH) Threshold Limit Value
(TLV) of 20 ppm TWA (72 mg/m3) (OSHA. 2005). If respirators are necessary in atmospheres
that are not immediately dangerous to life or health, workers must use NIOSH-certified air-
purifying respirators or NIOSH-approved supplied-air respirators with the appropriate APF.
Respirators that meet these criteria include air-purifying respirators with organic vapor
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cartridges. Respirators must meet or exceed the required level of protection listed in Table 3-2 to
meet NIOSH recommended a 1 ppm (3.6 mg/m3, 30 minute) ceiling because 1,4-dioxane is a
potential human carcinogen (29 CFR § 1990).
The respirators should be used when effective engineering controls are not feasible as per
OSHA's 29 CFR § 1910.132. The knowledge of the range of respirator APFs is intended to assist
employers in selecting the appropriate type of respirator that could provide a level of protection
needed for a specific exposure scenario. Table 3-2 lists the range of APFs for respirators. The
complexity and burden of wearing respirators increases with increasing APF. The APFs are not
to be assumed to be interchangeable for any conditions of use, any workplace, or any worker or
ONU. The use of a respirator not necessarily would resolve inhalation exposures since it cannot
be assumed that employers have or will implement comprehensive respiratory protection
programs for their employees.
Table 3-2. Assigned Protection Factors for Respirators in OSHA Standard 29 CFR S
1910.132
Type of Respirator
Quarter
Mask
llair
Mask
I-Mil
l-'acepiece
llelinel/
Mood
1 .oose-
I'iUiii"
Kacepiece
1. Air-Purifying Respirator
5
10
50
2. Power Air-Purifying
Respirator (PAPR)
50
1,000
25/1,000
25
3. Supplied-Air Respirator (SAR) or Airline Respirator
• Demand mode
10
50
• Continuous flow mode
50
1,000
25/1,000
25
• Pressure-demand or other
positive-pressure mode
50
1,000
4. Self-Contained Breathing Apparatus (SCBA)
• Demand mode
10
50
50
• Pressure-demand or other
positive-pressure mode
(e.g., open/closed circuit)
10,000
10,000
Source: 29 CFR § 1910.132
Estimating the Number of Workers and Occupational Non-Users (ONUs)
EPA used a method consisting of the following steps to estimate the number of workers and
ONUs who may be potentially exposed to 1,4-dioxane in each condition of use:
1. Identify the North American Industry Classification System (NAICS) codes for the
industry sectors associated with each condition of use.
2. Estimate total employment by industry/occupation combination using the Bureau of
Labor Statistics' Occupational Employment Statistics (OES) data (BLS. 2016).
3. Refine the OES estimates where they are not sufficiently granular by using the U.S.
Census" (2016b) Statistics of U.S. Businesses (SUSB) data on total employment by 6-
digit NAICS.
4. Estimate the percentage of employees likely to be using 1,4-dioxane instead of other
chemicals (i.e., the market penetration of 1,4-dioxane in the condition of use).
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5. Estimate the number of sites and number of potentially exposed employees per site.
6. Estimate the number of potentially exposed employees within the condition of use.
See Appendix G.5 for more information about the approach used to estimate potentially exposed
workers and ONUs.
3.4.1.2 Manufacturing
1,4-Dioxane is commercially manufactured by the acid-catalyzed dehydration of diethylene
glycol, which in turn is obtained from the hydrolysis of ethylene oxide. The information and data
quality evaluation to assess occupational exposures during manufacturing is listed in Table 3-3.
See Appendix G.l for additional details.
Table 3-3. Manufacturing Worker Exposure Data Evaluation
Worker Aiii\ il> or
Siiinplinvi Locution
Diilii Tjpe
Number of
Siimples
Diilii Qu;ilil\ Killing
Source Reference
1 IlkllOW II
1*1 >/. MiilllUil'IIIU
:x
1 huh
( i
Routine duties,
neutralization,
evaporator dump
PBZ Monitoring
4
High
(BASF. 2017)
N/A
CDR Data - Number of sites
and workers
N/A
High
(U.S. EPA. 2016a)
Occupational exposures to 1,4-dioxane during manufacturing were estimated by evaluating full-
shift, personal breathing zone (PBZ) monitoring data obtained by BASF during internal
industrial hygiene (IH) studies. BASF monitoring data was selected as it is more relevant and
recent compared to the manufacturing data cited in other sources [such as (ECJRC. 2002)1 and
lack of availability of monitoring data from other U.S. manufacturer. For example, the data cited
in the 2002 EU Risk Assessment ranges from 1976 to 1998 while the data provided by BASF
ranged from 2006 to 2017 (BASF. 2017. 2.016; ECJRC. 2002). There was a lack of available
monitoring data from the other known U.S. manufacturer. The BASF data had limitations
including lack of descriptions of worker tasks, exposure sources, and possible engineering
controls. The BASF (2016) workplace monitoring data appeared to be real-time PBZ exposure
measurements. The data were assumed to be relevant to worker activities and were 8-hour TWA
measurements. EPA estimated the total number of workers who could be potentially exposed as
78 and the number occupational non-users as 36 (U.S. EPA. 2016a).
Acute and chronic occupational inhalation exposures during manufacturing of 1,4-dioxane are
summarized in Table 3-4. EPA calculated the 95th percentile and 50th percentile of the available
30 data points for inhalation exposure monitoring data to assess the high-end and central
tendency exposures, respectively. Using these 8-hour TWA exposure concentrations, EPA
calculated the ADC and LADC using the equations in Appendix G.2. Additional information
regarding the calculations is provided in Appendix G.6.1.
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Table 3-4. Acute and Chronic Inhalation Exposures of Worker for Manufacturing Based
on Monitoring Data
Exposure Type
Central Tendency
(50th percentile)
(mg/m3)
High-end
(95th Percentile)
(mg/m3)
Data Quality Rating
of Associated Sourcea
15-minute TWA (Evaporator Dump)
N/A
137*
High
8-hour TWA Exposure Concentrations
0.42
7.7
High
8-hour TWA Acute Exposure
Concentration (AEC)
0.42
7.7
High
Average Daily Concentration (ADC)
0.40
7.4
High
Lifetime Average Daily Concentration
(LADC)
0.16
3.8
High
N/A = not applicable. *: The higher of the two reported (BASF. 2017) 15-minute short-term exposures values (137
mg/m3 from the evaporator dump step), considered as high-end, short-term exposure.
a See Table 3-3 for corresponding references.
EPA estimated that 78 workers and 36 ONUs could be exposed at sites that manufacture 1,4-
dioxane in the U.S. EPA used worker number estimates reported in CDR and refined them using
BLS and SUSB data for the applicable NAICS codes. Additional information about the steps
used to estimate the number of potentially exposed workers and ONUs are available in Appendix
G.5. Exposure data for ONUs were not available. ONUs include employees that work at the site
where 1,4-dioxane is manufactured, but unlike workers, they do not directly handle the chemical
and are not near the chemical release source of the manufacturing process. Thus, ONUs are
likely to have lower exposures than workers. ONUs for manufacturing include supervisors,
managers, and tradesmen that may be in the manufacturing area, but do not perform tasks that
result in the same level of exposures as production workers.
Key Uncertainties
The data sets used mostly lacked specific descriptions of worker tasks, exposure sources, and
possible engineering controls to provide context. EPA assumed that the 2016 BASF data are
PBZ measurements relevant to worker activities and are also 8-hour TWA measurements. This
assumption could underestimate exposures. The sampling rate was missing for some of the 2016
data, so EPA assumed the same sampling rate was applied for other data in the set. It is uncertain
to what extent the limited monitoring data used to estimate inhalation exposures for this scenario
that could be representative of occupational exposures in other manufacturing facilities of 1,4-
dioxane.
3.4.1.3 Import and Repackaging
The import of chemicals, such as 1,4-dioxane, involves activities of handling of chemical during
storage, transportation, distribution, and packaging and processing. In addition, 1,4-dioxane
shipped in bulk containers could be repackaged into smaller containers for resale, such as drums
or bottles using automatic, semi-automatic, or manual filling, sealing, labeling, and
wrapping. The shipment methods and regulations of 1,4-dioxane require the material to be
properly classed, described, packaged, marked, labeled, and in condition for shipment as
required or authorized by the hazardous materials regulations (49 CFR § 171-177). To avoid
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spilling, 1,4-dioxane needs to be transported in securely sealed glass bottles or equivalent
containers that should themselves be placed inside strong screw-cap or snap-top container that
will not open when dropped. Both the bottle and the outside container should be appropriately
labelled. Airtight packaging is required by the International Labor Organization's (ILO)
International Chemical Safety Cards (ICSC).
The information and data quality evaluation to assess occupational exposures from import and
repackaging is listed in Table 3-5. See Appendix G. 1 for more details about the data quality
evaluation.
Table 3-5. Import and Repackaging Data Source Evaluation
\\ orkcr Acli\ il\ or
S;ini|)liii!£ Locution
Diilii Tjpe
Number of Samples
l);il;i Ou;ili(> Killing
Source Reference
N/A
CDR Data - Number
of sites and workers
N/A
High
(IIS. EPA. 2016a")
EPA modeled central tendency and high-end occupational inhalation exposures for this scenario
using the EPA AP-42 Loading Model and the EPA Mass Balance Inhalation Model (
2013b) and the values listed in Appendix G.2. EPA used a Monte Carlo simulation to vary the
saturation factor (f), ventilation rate (Q), and mixing factor (k) and calculated the 95th percentile
and 50th percentile exposures during unloading directly in the simulation to assess the high-end
and central tendency exposures, respectively. See Appendix G.4 for more information about the
Monte Carlo simulation. Since some sites may only repackage into either bottles or drums and
some sites may use both types of containers, EPA estimated exposures for both bottles and
drums. EPA used these values to calculate acute and chronic inhalation exposures in the Monte
Carlo simulation, varying working years (WY) and the number of days, using the equations in
Appendix G.2. EPA determined once per day short-term exposures of 170 to 610 mg/m3 with a
duration of 30 minutes may occur during drum unloading as central tendency and high-end short-
term exposures. These estimates are presented in Table 3-6.
EPA estimated that the total number of potentially exposed workers could be between 38 to 149
workers, and occupational non-users could be between 12 to 49. EPA used worker number
estimates reported in CDR and refined them using BLS and SUSB data for the applicable
NAICS codes. See Appendix G.5 for more information about the steps used to estimate the
number of potentially exposed workers and ONUs. Additional information including specific
methodology and assumptions for modeling exposures are described in Appendix G.6.2.
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Table 3-6. Acute and Chronic Inhalation Exposures of Worker for Import and
Repackaging Based on Modeling
Exposure Type
Central Tendency
(50th Percentile)
(mg/m3)
High-end
(95th Percentile)
(mg/m3)
Data Quality Rating of
Associated Sourcea
Short-Term Exposure (0.5-hour
TWA)
170
610
N/A - Modeled Data
Bottle 8-hour TWA Exposure
Concentration
9.3
33
N/A - Modeled Data
Drum 8-hour TWA Exposure
11
38
N/A - Modeled Data
Bottle 8-hour Acute Exposure
Concentration (AEC)
9.3
33
N/A - Modeled Data
Drum 8-hour Acute Exposure
Concentration (AEC)
11
38
N/A - Modeled Data
Average Daily Concentration (ADC)
0.46
3.4
N/A - Modeled Data
Lifetime Average Daily
Concentration (LADC)
0.18
1.3
N/A - Modeled Data
a See Table 3-5 for corresponding references.
Exposure data for ONUs were not available. The ONU exposures are anticipated to be lower
than worker exposures, since ONUs do not typically directly handle the chemical. Only
inhalation exposures to vapors or incidental dermal exposures could be applicable to ONUs,
which will likely be less than worker exposures.
Key Uncertainties
EPA modeled inhalation exposures using the EPA AP-42 Loading Model and the EPA Mass
Balance Inhalation Model. Process specifics for import and repackaging at these sites were not
available, therefore, EPA assumed certain process details, such as container sizes and loading
and unloading frequency. Additionally, EPA assumed that the process steps associated with this
scenario occur indoors, without engineering controls, and in an open-system environment where
vapors freely escape. In the absence of industry-specific information, these assumptions provide
for conservative estimates for exposures during this operation. Actual exposures may be less due
to various factors including closed-system loading and unloading, the use of vapor recovery
systems, or the automation of various process steps.
3.4.1.4 Recycling
In the Problem Formulation of the Risk Evaluation for 1,4-Dioxane (U.S. EPA. 2018cl EPA
identified recycling as a separate occupational exposure scenario. After further review, EPA
assessed the recycling process as part of the Industrial Uses group, described in Section 3.4.1.5.
Any exposures from worker activities, such as unloading, maintenance, and drumming spent 1,4-
dioxane for disposal are assessed in Section 3.4.1.5.
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3.4.1.5 Industrial Uses
1,4-Dioxane is used as a process solvent, an intermediate, and a catalyst in several industrial
applications. For this assessment, these uses have been grouped into a broad category called
"industrial uses." The relevant industries and uses include the following:
• Process solvent in pharmaceutical and medicine manufacturing;
• Process solvent in basic organic chemical manufacturing;
• Wetting and dispersing agent in textile processing;
• Wood pulping;
• Extraction of animal and vegetable oils;
• Purification of pharmaceuticals;
• Etching of fluoropolymers;
• Pharmaceutical intermediate;
• Agricultural chemical intermediate;
• Polymerization catalyst;
• Plasticizer intermediate;
• Plastics modeling (thermoforming); and
• Catalysts and reagents for anhydrous acid reactions, brominations, and sulfonations.
EPA did not find specific details for most of these processes, but typical operations are expected
to be similar across these uses. For uses grouped in this "industrial uses" category, it is expected
that 1,4-dioxane is received as a solvent, intermediate, or catalyst in its final formulation and
requires no further processing. The 1,4-dioxane is unloaded and charged to intermediate storage
or directly used in the process. If it is being used as an intermediate, it will likely be consumed
during the reaction. For solvents or catalysts, spent 1,4-dioxane will be collected at the end of the
process for reuse or disposal.
The information and data quality evaluation to assess occupational exposures from industrial
uses is listed in Table 3-7. See Appendix G. 1 for more details about the data quality evaluation.
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Table 3-7. Industrial Uses Data Source Evaluation
\\ orkcr Acli\ il\ or Siiinplinii Locution
Diilii Tjpe
Nil in her
ol'
Siimplcs
Diilii
Qu;ili(\
Killing
Source
Reference
Medicine Manufacture
IT./and \rca
Monitoring
:u
II mh
i
Pharmaceutical Production
PBZ Monitoring
<30
High
(ECJRC,
2002)
Use (e.g. as solvent) in other productions
PBZ Monitoring
194
High
(ECJRC.
2002)
Use (e.g. as solvent) in other productions
PBZ Monitoring
49
High
(ECJRC,
2002)
Extractant in medicine manufacturing
EASE Modeling
N/A
- estimates
from
High
(ECJRC,
2002)
modeling
N/A
CDR Data - Number of
sites and workers
N/A
High
(U.S.
EPA.
20.1.6a)
N/A = Not Applicable.
Occupational exposure for 1,4-dioxane used as an industrial chemical was determined using
estimates provided in the EU Risk Assessment for 1,4-dioxane (ECJRC. 2002). The report
proposed a "typical concentration" of 5 mg/m3 and a "reasonable worst-case" concentration of
20 mg/m3 to estimate the inhalation exposures for various industrial uses. These estimates were
based on full-shift monitoring data provided by other sources cited in the report, which covered
use in the pharmaceutical industry and use as a solvent in industrial processes. However, the
report did not provide details about how these values were calculated, therefore, it is unclear
what percentile is represented when an exposure is described as "typical" or "reasonable worst
case" (i.e. 50th and 95th percentile).). These "typical" and "reasonable worst-case" full-shift
estimates were assumed to be 8-hour TWA values and equivalent to central tendency and high-
end values, respectively. Acute and chronic inhalation exposures for Industrial Uses are
calculated using the equations in Appendix G.2. Results of these calculations are summarized
below in Table 3-8.
EPA estimated a total of 1,385 workers and 545 occupational non-users may be exposed across
all sites. EPA estimated the number of potentially exposed workers and ONUs per site using
BLS and SUSB data for the applicable NAICS codes. EPA used the number of sites reported in
the 2016 TRI and 2016 DMR to estimate the total number of workers and ONUs that may be
exposed. Additional information including typical industrial use, monitoring data, and estimation
of high-end inhalation values for 1,4-dioxane used as an industrial chemical are described in
Appendix G.6.3.
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Table 3-8. Acute and Chronic Inhalation Exposures of Worker for Industrial Uses Based
on Monitoring Data
Exposure Type
Central Tendency a
(EU RAR: Typical
Concentration)
(mg/m3)
High-End a
(EU RAR: Reasonable
Worst Case
Concentration)
(mg/m3)
Data quality rating of
Associated Source b
8-hour TWA Exposure
Concentrations
5.0
20
High
8-hour TWA Acute
Exposure Concentration
(AEC)
5.0
20
High
Average Daily
Concentration (ADC)
4.8
19
High
Lifetime Average Daily
Concentration (LADC)
1.9
9.9
High
a The risk assessment did not provide details about how these values were calculated, therefore, it is unclear what
percentile is represented when an exposure is described as "typical" or "reasonable worst case" (i.e. 50th and 95th
percentile).
b See Table 3-7 for corresponding references.
Exposure data for ONUs were not available. ONU exposures are lower than worker exposures,
since ONUs do not typically directly handle the chemical. Only inhalation exposures to vapors
are expected, which will likely be less than worker exposures.
Key Uncertainties
EPA used estimates based on exposure data from the 2002 EU Risk Assessment for 1,4-dioxane
in order to estimate the inhalation exposures for this scenario. The data sets used are limited and
mostly lacked specific descriptions of worker tasks, exposure sources, and possible engineering
controls to provide context. Most of the datasets were only presented in ranges with key statistics
(i.e. median or average and 90th percentile), so EPA was unable to directly calculate final values
from the raw data and relied on estimates provided in the 2002 EU Risk Assessment. The
assessment also did not explain how the final 8-hour TWA exposure values of 5 and 20 mg/m3
were derived. These values were reported by the EU to be full-shift values, but EPA assumed
them to be 8-hour TWA values. These values may overestimate the exposures of some uses
within this Industrial Uses group due to additional regulations inherent to that use, such as the
pharmaceutical industry.
3.4.1.6 Functional Fluids (Open System)
1,4-Dioxane may be a component of functional fluids that are used in open systems such as
metalworking fluids and cutting and tapping fluids based on information safety data sheets
(SDSs) listed in Preliminary Information on Manufacturing, Processing, Distribution, Use, and
Disposal: 1,4-Dioxane (U.S. EPA. 2017c). OSHA's Hazard Communication Standard (29 CFR §
1910.1200(g)) requires that the chemical manufacturer, distributor, or importer provide SDSs for
each chemical to downstream users to communicate information on these hazards, and to provide
guidance to help workers who handle chemicals to become familiar with the format and
understand the contents of the SDSs. The information and data quality evaluation used to assess
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occupational exposures for functional fluids (open systems) are listed in Table 3-9. See
Appendix G.l for more details about the data quality evaluation.
Table 3-9. Functional Fluids (Open System) Data Evaluation
Worker Activity or
Sampling Location
Data Type
Number of Samples
Data quality rating
Source Reference
Threader, Broaching,
Apex Drill, and
Lunch Tables
Area Monitoring
4
High
(Burton and Driscoll.
1997)
Transfer Lines,
Roughing, Four-way,
Multiple, Screw
Machine-Lathing,
and Apex Drill
PBZ Monitoring
6
High
(Burton and Driscoll.
1997)
Occupational exposure for 1,4-dioxane use as an open system functional fluid was modeled
using the EPA AP-42 Loading Model and the EPA Mass Balance Inhalation Model. EPA used a
Monte Carlo simulation to vary the saturation factor (f), ventilation rate (Q), and mixing factor
(k). See Appendix G.4 for more information about the Monte Carlo simulation. EPA calculated
the 95th percentile and 50th percentile exposures during unloading directly in the simulation to
assess the high-end and central tendency exposures, respectively. EPA used these values to
calculate acute and chronic inhalation exposures in the Monte Carlo simulation, varying working
years (WY), using the equations in Appendix G.2. These results are summarized in Table 3-10.
A 1997 NIOSH Health Hazard Evaluation (HHE) report provided personal breathing zone (PBZ)
samples collected at a facility that manufactures axels for trucks and recreational vehicles
(Burton and Driscoll. 1997). The NIOSH HHE sample results were within the 10th percentile of
the distribution5 from the Monte Carlo simulation and contributed a minor effect to the overall
distribution.
Table 3-10. Acute and Chronic Inhalation Exposures of Worker for Open System
Functional Fluids Based on Modeling
Exposure Type
Central Tendency
(50th Percentile)
(mg/m3)
High-End
(95th Percentile)
(mg/m3)
Confidence Rating of
Associated Sourcea
Short-Term Exposure (Drum Unloading,
0.05 hr)
0.17
0.61
N/A - Modeled Data
8-hour TWA Exposure Concentrations
1.1E-03
3.8E-03
N/A - Modeled Data
8-hour TWA Acute Exposure
Concentration (AEC)
1.1E-03
3.8E-03
N/A - Modeled Data
Average Daily Concentration (ADC)
1.0E-03
3.7E-03
N/A - Modeled Data
Lifetime Average Daily Concentration
(LADC)
3.9E-04
1.5E-03
N/A - Modeled Data
a See Table 3-9 for corresponding references.
5 All points, except one from the HHE study (Burton and Driscoll. 1997). were within the 5th percentile from the
Monte Carlo simulation. Only one value was within the 10th percentile.
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The above values could be influenced by 1,4-dioxane's high vapor pressure (40 mm Hg at 25°C)
causing vapor to evaporate from droplets in the air, ventilation rate at the work facility, mixing
factor, vapor saturation factor and other working condition variables. The concentration of 1,4-
dioxane in the formulation could vary from 0.01 to 0.1 wt% resulting in a partial pressure that
likely represents an insignificant source of exposure (U.S. EPA. 2017c). EPA estimated acute
and chronic inhalation exposures using these values directly in the Monte Carlo simulation. EPA
estimated the total number of potentially exposed workers could be 4,094,000, and ONUs could
be 178,000. This estimate is based on worker numbers provided in the ESD (OECD. 2011).
Additional information including typical use, modeling methodology, and monitoring data are
described in Appendix G.6.4.
To assess ONU inhalation exposures, EPA combined the area measurements taken from a variety
of locations in the manufacturing facility into a single sample set with five datapoints (Burton
andDriscoll 1997). EPA calculated the 50th percentile of this data set to assess the central
tendency exposure and presents the maximum as the high-end exposure (see Section 3.4.1.1).
These results are summarized in Table 3-11. The ONU exposures were less than the estimated
central tendency and high-end values for workers, as expected.
Table 3-11. Acute and Chronic ONU Inhalation Exposures for Open System Functional
Fluids Based on Monitoring Data
Exposure Type
Central Tendency
(50th Percentile)
(mg/m3)
High-End
(Maximum)
(mg/m3)
Data quality rating of
Associated Sourcea
8-hour TWA Exposure
Concentrations
1.5E-4
2.5E-4
N/A - Modeled Data
8-hour TWA Acute
Exposure Concentration
(AEC)
1.5E-4
2.5E-4
N/A - Modeled Data
Average Daily
Concentration (ADC)
1.4E-04
2.4E-04
N/A - Modeled Data
Lifetime Average Daily
Concentration (LADC)
5.7E-05
1.2E-04
N/A - Modeled Data
a See Table 3-9 for corresponding references.
Key Uncertainties
EPA used exposure data for metalworking fluids from the 2011 OECD ESD on the Use of
Metalworking Fluids and from a 1997 NIOSH HHE. Neither dataset specifically addressed
exposures to 1,4-dioxane. EPA used concentrations provided in relevant SDSs to estimate these
exposures. In addition, the HHE was conducted to address concerns regarding adverse human
health effects reported following exposures during use and therefore the measured exposures
may be inherently biased high.
The data did not estimate exposures during chemical unloading, therefore, EPA estimated this
exposure using the EPA AP-42 Loading Model and the EPA Mass Balance Inhalation Model.
These models assume that the unloading of fluid containing 1,4-dioxane occurs indoors, without
engineering controls, and in an open-system environment where vapors freely escape. In the
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absence of industry-specific information, these assumptions provide for conservative estimates
for exposures during this unloading operation. Actual exposures may be less due to various
factors including closed-system unloading, the use of vapor recovery systems, or an automated
unloading process.
3.4.1.7 Functional Fluids (Closed System)
EPA identified closed system functional fluids as a condition of use for 1,4-dioxane in the
problem formulation ( 2018c). The Preliminary Information on Manufacturing,
Processing, Distribution, Use, and Disposal: 1,4-Dioxane presented three SDS's for closed
system functional fluids (hydraulic fluids). These SDS's did not list content information for 1,4-
dioxane, which suggests that it is not an intended component in these products (U.S. EPA.
2 ). BASF manufactures neat 1,4-dioxane (anhydrous, 99.8% minimum) as well as products
that contain 1,4-dioxane. In a public comment from 2017, BASF provided a table of products
that contain residual amounts of 1,4-dioxane. BASF specifically stated that the residual 1,4-
dioxane is a byproduct of the ethoxylation process and is not an intended component. One of
these products (Pluriol E 400™ or equivalent commercial polyethylene glycols) could be used as
a hydraulic or heat transfer fluid and has a residual level of less than 25 ppm (0.0025%) (BASF.
2017). This concentration is significantly lower than the concentration assessed for open system
functional fluids in Section 3.4.1.6, which was 0.1%, or 1,000 ppm. Additionally, EPA reviewed
91 literature sources and performed targeted internet searches and did not find any references to
the use of 1,4-dioxane in closed system functional fluids. A closed system precludes exposure as
the transfer device could prohibit the escape of chemicals outside the system. Due to the lack of
evidence supporting its intended use in closed system functional fluids, EPA did not assess
occupational exposures for this use of 1,4-dioxane.
3.4.1.8 Laboratory Chemicals
1,4-Dioxane is used in a variety of laboratory applications, which include, but are not limited to,
the following:
• Chemical reagent during lab scale reactions;
• Reference material for quality control or calibration;
• Medium for spectroscopic and photometric measurement;
• Liquid scintillation counting medium;
• Stable reaction medium;
• Cryoscopic solvent for molecular mass determinations; and
• Preparation of histological sections for microscopic examination.
Occupational exposure for 1,4-dioxane used as a laboratory chemical for research/development
and analytical applications was determined by evaluating available monitoring data including
short-term and 8-hour TWA exposures for workers in a laboratory setting (ECJRC. 2002;
NICNAS. 1998). The information and data evaluation for exposures to laboratory chemicals by
the workers are listed in Table 3-12. See Appendix G.l for more details about the data quality
evaluation.
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Table 3-12. Laboratory Chemicals Data Evaluation
Worker Aiiit il> or
S;iiii|)liiiii l ocution
Diilii Tjpe
Number of Samples
Diilii (|ii;ili(\ rsiling
Source Reference
Solvent extraction
and TLC
PBZ Monitoring
Data
Unknown
High
fNICNAS. 1998)
Laboratory Work
(HPLC)
PBZ and Area
Monitoring Data
1
High
(ECJRC. 2002)
Laboratory
PBZ and Area
Monitoring Data
305
High
(ECJRC. 2002)
Laboratory
PBZ and Area
Monitoring Data
29
High
(ECJRC. 2002)
N/A
CDR Data - Number
of sites and workers
N/A
High
(U.S. EPA. 20.1.6a)
N/A = Not Applicable.
From these monitoring data, EPA estimated concentrations representing central tendency and
high-end estimates of potential occupational inhalation exposures based on EU risk assessment
(ECJRC. 2002) of 1,4-dioxane as laboratory use (see Table 3-13). EPA used a mean value to
estimate the central tendency exposures. EPA calculated the high-end value by calculating an 8-
hour TWA of the 15-minute short-term peak exposure and the highest 90th percentile value. This
calculated value represents an exposure above the 90th percentile, which is equivalent to a high-
end exposure. Using these 8-hour TWA exposure concentrations, EPA calculated the ADC and
LADC. EPA determined a once per day short-term exposures of 166 mg/m3 may occur with a
15-minute duration during degassing of the high-performance liquid chromatography fluid based
on occupational exposures for laboratory use (ECJRC. 2002). A submitter to the 2016 CDR
reported 1,4-dioxane estimated that at least 50 but less than 100 laboratory workers could be
potentially exposed ( )16a). EPA used U.S. Census and BLS data for the NAICS
code 541380, Testing Laboratories, and relevant SOC codes to estimate a total of 6,844 sites,
6,610 workers, and 804 ONUs (see Appendix G.5), which corresponds to an estimated average
of one worker and 0.12 ONUs per site. EPA used these data to calculate a ratio of 8:1 workers to
ONUs. Additional information on various conditions of use including typical laboratory use,
number of workers and ONUs, monitoring data, and estimation of high-end inhalation value for
laboratory chemicals are described in Section 5.2 (Human Health Risk) and Appendix G.6.5.
Exposure data for ONUs were not available. ONU exposures could be lower than worker
exposures, since ONUs do not typically directly handle the chemical. Only inhalation exposures
to vapors are expected, which might be less than worker exposures.
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Table 3-13. Acute and Chronic Inhalation Exposures of Worker for Laboratory Chemicals
Based on Monitoring Data
Exposure Type
Central Tendency
(Mean Value)
(mg/m3)
High-end
(90th Percentile)
(mg/m3)
Data quality rating of
Associated Sourcea
Short-Term Exposure (15-
minutes)
N/A
166
High
8-hour TWA Exposure
Concentrations
0.11
5.8*
High
Acute Exposure Concentration
(AEC)
0.11
5.8
High
Average Daily Concentration
(ADC)
0.11
5.5
High
Lifetime Average Daily
Concentration (LADC)
0.042
2.8
High
N/A = not applicable.
* NICNAS (1998) did not provide occupational exposure 1,4-dioxane data, however, cited studies where the highest
8-hour TWA value from personal monitoring was 1.8 ppm (approximately 6.5 mg/m3) (Rimatori et al„ 1994:
Hertlein. 1980)
a See Table 3-12 for corresponding references.
Key Uncertainties
EPA used estimates based on exposure data from the 2002 EU Risk Assessment for 1,4-dioxane
to estimate the inhalation exposures for this scenario. The data sets used are limited, assumed to
be 8-hour TWA values, and mostly lacked specific descriptions of worker tasks, exposure
sources, and possible engineering controls to provide context. Most of the datasets were only
presented in ranges with key statistics (i.e. median or average and 90th percentile), so EPA was
unable to directly calculate final values from the raw data and relied on the statistics provided in
the report. Actual exposures could be less due to various factors in laboratory chemicals
including variations with respect to number of workers and ONUs, scale of operations, and tasks
performed for various process/analytical activities.
3.4.1.9 Film Cement
Film cement contains a mixture of solvents including 1,4-dioxane. Film cement is used in the
film processing and archiving industries to splice celluloid movie film together (U.S. EPA.
2017c). Occupational exposure to 1,4-dioxane used in film cement was determined using
monitoring data provided in a NIOSH HHE report (Okawa and Cove. 1982). The information
and data evaluation for worker exposures during use of film cement are presented in Table 3-14.
See Appendix G.l for more details about the data quality evaluation.
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Table 3-14. Film Cement Data Evaluation
Worker Activity or
Sampling Location
Data Type
Number of
Samples
Data quality rating3
Source Reference / Hero
ID
N/A
References data
provided in NIOSH,
1982
N/A
High
(NICNAS. 1998)
MovieLab
Area Monitoring
1
High
(Okawa and Cove. 1982)
MovieLab
PBZ Monitoring
1
High
(Okawa and Cove. 1982)
Technicolor
PBZ Monitoring
4
High
(Okawa and Cove. 1982)
a: NIOSH (1982) reported six points that were relevant to 1,4-dioxane. Five were personal breathing zone points
that were used to estimate worker inhalation exposures and one point was an area sample used to estimate the ONU
exposure. Because of the data being a single data set, it was scored as such instead of viewing the two types of
points each as their own data set. Thus, the sample size sub-score was "High" and that supported the overall score
of "High".
The NIOSH HHE report provided five PBZ samples and one area sample collected at two film
laboratories that develop and clean film. Worker activities included film splicing and manual
film cleaning. Due to the small size of the data set, EPA calculated the 50th percentile of this data
set to assess the central tendency exposure and presents the maximum as the high-end exposure.
These values were used to calculate acute and chronic inhalation exposures using the equations
in Appendix G.2. Results of these calculations are shown in Table 3-15. EPA estimated a total of
30 workers and 10 ONUs could be exposed across all the sites. EPA estimated the number of
potentially exposed workers and ONUs using BLS and SUSB data for the applicable NAICS
codes. See Appendix G.5 for more information about the steps used to estimate workers and
ONUs. Additional information including methodology for estimating the number of workers,
typical film cement use, monitoring data, and estimation of high-end inhalation values for 1,4-
dioxane used as a film cement are described in Appendix G.6.6.
Table 3-15. Acute and Chronic Inhalation Exposures of Worker for the Use of Film
Cement Based on Monitoring Data
Exposure Type
Central Tendency
(50th percentile)
(mg/m3 a)
High-end
(Maximum)
(mg/m3 a)
Data quality rating of
Associated Source bb
8-hour TWA Exposure
Concentrations
1.5
2.8
High
8-hour TWA Acute Exposure
Concentration (AEC)
1.5
2.8
High
Average Dailv Concentration
(ADC)
1.5
2.7
High
Lifetime Average Daily
Concentration (LADC)*
0.58
1.4
High
a Analytical detection limits are significantly lower than the concentrations shown in the table. The method detection
limits of 1,4-dioxane in air are 530 ppt (1.9E-6 mg/m3) and 0.01 ppb (3.6E-5 mg/m3) by selected ion flow tube-mass
spectrometry (SIFT-MS) and Gas Chromatography with Flame-Ionization detection (GC-FID), respectively. In
addition, NIOSH method 1602 could be used to determine the concentration of 1,4-dioxane in a 10-L air sample by
GC-FID. Samples are collected by drawing air through a solid sorbent tube containing coconut shell charcoal. The
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flow rate is between 0.01 and 0.2 L/minute for a total sample size of 0.5-15 L. 1,4-Dioxane is eluted from the solid
sorbent with agitation using carbon disulfide. The carbon disulfide eluent sample is then injected directly into the
GC-FID. The detection limit is 0.01 mg per sample.
b See Table 3-14 for corresponding references.
* Refer Equation 5.2 and Appendix G.2 for additional information on estimation of LADC.
Three out of six NIOSH HHE samples have detectable concentrations and three values were non-
detect (Okawa and Cove. 1982). The values of the three non-detects were considered as half the
detection limit assuming that the average non-detect values could be between the detection limit
and zero, and that the average value of non-detects could be as high as half the detection limit
(U.S. EPA, 1991; U.S. EPA, 2000). EPA calculated an upper bound for these measurements and
used it to calculate an 8-hour TWA value. EPA presented this as an 8-hour TWA inhalation
exposure value for ONUs (Table 3-16). This value was used to calculate acute and chronic
inhalation exposures as per the equations in Appendix G.2. These values are plausible, but EPA
cannot determine the statistical representativeness of the values given the small sample size.
Dermal exposures are not expected for ONUs since they are not expected to directly handle the
chemical.
Table 3-16. Acute and Chronic ONU Inhalation Exposures for the Use of Film Cement
Based on Monitoring Data
Exposure Type
Central Tendency a
(mg/m3)
High-End a
(mg/m3)
Data quality rating of
Associated Source b
8-hour TWA Exposure Concentrations
0.10
High
8-hour TWA Acute Exposure
Concentration (AEC)
0.10
High
Average Daily Concentration (ADC)
0.10
0.10
High
Lifetime Average Daily Concentration
(LADC)
0.040
0.051
High
a These values are plausible, but EPA cannot determine the statistical representativeness of the values given the
sample size of six data. High uncertainty is introduced given that these values are based on non-detects.
b See Table 3-14 for corresponding references.
Key Uncertainties
Three of the NIOSH HHE reported values were non-detects, while other three were detectable.
The values of the three non-detects were considered as half the detection limit as per the
considerations indicated earlier. The actual exposures could be overestimates for the film cement
due to the single area HHE study, lack of statistical representativeness of the values due to
limited sample size, and typical operations that might not involve direct handling of 1,4-dioxane.
3.4.1.10 Spray Foam Application
1,4-Dioxane is present in two-component high-pressure, two-component low-pressure, and one
component foam (OCF). The two-component, high-pressure spray polyurethane foams (SPFs),
which are typically used for larger insulation applications, as an air sealant in hybrid insulations,
and in roofing applications (U.S. EPA. 2017b. c). Monitoring data for worker inhalation
exposure to 1,4-dioxane from spray application of SPF was not identified. Instead, occupational
exposure to 1,4-dioxane used in SPFs was estimated.
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The information and data quality evaluation used to assess occupational exposures for spray
foam application are listed in Table 3-17. See Appendix G.l for more details about the data
quality evaluation.
Table 3-17. Spray Foam Application Data Source Evaluation
\\ orkcr Ac(i\ i(\ or Siiinplinii
Locution
l);il;i T\|K'
Number of Samples
Diilii
(|ii
r;iliu»
Source Reference'
A typical two-story, 2,300-square-foot
house with a medium-pitch roof with a
roof area of about 1,500 square feet
Parameters
used in
modeling
Not applicable -
Monitoring data not
provided
Medium
(Huber. 20.1.81
An average size house is 1,500 square
feet of roofing
Parameters
used in
modeling
Not applicable -
Monitoring data not
provided
Medium
(Home Advisor.
2018)
Mix A-side and B-side in 1:1 ratio
Parameters
used in
modeling
Not applicable -
Monitoring data not
provided
High
(OMG Roofing
Products. 2018)
0.1% 1,4-dioxane in B-Side
Parameters
used in
modeling
Not applicable -
Monitoring data not
provided
High
(GAP. 20.1.4)
EPA used assumptions and values from the GS on the Application of Spray Polyurethane Foam
Insulation, which used the EPA AP-42 Loading Model, the EPA Mass Balance Inhalation Model,
the EPA TotalPNOR I'l J-Limiting Model (U.S. EPA. 2018a) and surrogate data to estimate
inhalation exposures during container unloading, spray foam application, and thickness
verification. EPA used a Monte Carlo simulation to vary the saturation factor (f), ventilation rate
(Q), and mixing factor (k) and calculate 50th and 95th percentile 8-hour TWA exposures during
container unloading. See Appendix G.4 for more information about the Monte Carlo simulation.
The results from each activity were combined to construct an 8-hour TWA. EPA used these
values to calculate acute and chronic inhalation exposures in the Monte Carlo simulation,
varying working years (WY), using the equations in Appendix G.2. These exposure results are
shown in Table 3-18.
EPA estimated a total of 162,518 potentially exposed workers and 15,627 potentially exposed
non-sprayer workers. EPA estimated the number of potentially exposed workers and non-sprayer
workers using BLS and SUSB data for the applicable NAICS codes. EPA considered the total
number of establishments and potentially exposed workers and non-sprayer workers in this
NAICS code as bounding estimates of the number of establishments that use and the number of
workers and non-sprayer workers that are potentially exposed to 1,4-dioxane-based spray
polyurethane foam during insulation installation. These bounding estimates are likely
overestimates of the actual number of establishments and employees potentially exposed to 1,4-
dioxane during spray polyurethane foam insulation installation, since only a single spray
polyurethane foam product that contains 1,4-dioxane was identified. See Appendix G.5 for more
information about the steps used to estimate workers and non-sprayer workers. Additional
information including specific methodology for estimating worker numbers, typical spray foam
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application methods, modeling assumptions, and estimation of high-end and central tendency
inhalation values for 1,4-dioxane used in spray foam insulation are described in Appendix G.6.5.
Table 3-18. Acute and Chronic Inhalation Exposures of Worker for Spray Application
Based on Modeling
Exposure Type
Central Tendency
(50th Percentile)
(mg/m3)
High-end
(95th Percentile)
(mg/m3)
Data quality rating of
Associated Sourcea
8-hour TWA Exposure Concentrations
9.7E-03
1.2E-02
N/A - Modeled Data
8-hour TWA Acute Exposure
Concentration (AEC)
9.7E-03
1.2E-02
N/A - Modeled Data
Average Daily Concentration (ADC)
9.4E-03
1.1E-02
N/A - Modeled Data
Lifetime Average Daily Concentration
(LADC)
3.6E-03
5.3E-03
N/A - Modeled Data
a See Table 3-17 for corresponding references.
Exposure data from application of SPFs for non-sprayer workers were not available. Per the GS,
it is assumed that some non-sprayer workers could perform tasks related to trimming the cured
spray foam insulation. Exposures were estimated using the EPA Total PNOR PEL-Limiting
Model with the OSHA PEL for total particulates (15 mg/m3). EPA multiplied the OSHA PEL by
the expected concentration of 1,4-dioxane in the mixed SPF (0.0005) and averaged the exposure
over 8 hours, assuming non-sprayer workers are exposed during trimming and not exposed
during the remainder of the 8-hour period. Due to the small sample size of only one estimated
value, EPA calculated an 8-hour TWA inhalation exposure value for non-sprayer workers and
used this value to calculate acute and chronic inhalation exposures using the equations in
Appendix G.2. These values are summarized in Table 3-19. While these values may be plausible,
due to the small sample size of only one estimated value, EPA could not determine the statistical
representativeness.
Table 3-19. Acute and Chronic Non-Sprayer Workers Inhalation Exposures for Spray
Applications Based on Modeling
Exposure Type
Central Tendency a
(mg/m3)
High-End a
(mg/m3)
Data quality rating of
Associated Source b
8-hour TWA Exposure Concentrations
1.9E-03
N/A - Modeled Data
8-hour TWA Acute Exposure
Concentration (AEC)
1.9E-03
N/A - Modeled Data
Average Daily Concentration (ADC)
1.8E-03
N/A - Modeled Data
Lifetime Average Daily Concentration
(LADC)
7.2E-04
9.3E-04
N/A - Modeled Data
a These values are plausible, but EPA cannot determine the statistical representativeness of the values given the
small sample size.
b See Table 3-17 for corresponding references.
Key Uncertainties
Due to a lack of data specific to 1,4-dioxane for this use, EPA used assumptions and values from
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the GS on the Application of Spray Polyurethane Foam Insulation, which used the EPA AP-42
Loading Model, the EPA Mass Balance Inhalation Model, theEPA Total PNORPEL-Limiting
Model ( 2018a) and surrogate data to estimate inhalation exposures during container
unloading, spray foam application, thickness verification, and trimming. Values for the
parameters listed in Table G-21 were assumed based on general industry data. These parameter
values may not always be representative of applications specific to spray foam insulations
containing 1,4-dioxane. The estimate for exposures during application did not account for the
potential evaporation of 1,4-dioxane from the mist particulates and the potential inhalation
exposure of the evaporated vapors. EPA assumed that this is not a significant exposure given that
the partial pressure of 1,4-dioxane is likely very low due to the low concentration of 1,4-dioxane
in the mixed spray foam. EPA also estimated exposures during thickness verification using
surrogate data.
The EPA AP-42 Loading Model and the EPA Mass Balance Inhalation Model were used to
estimate inhalation exposures during container unloading. These models assume that the
unloading of fluid containing 1,4-dioxane occurs indoors, without engineering controls, and in an
open-system environment where vapors freely escape. In the absence of industry-specific
information, these assumptions provide for conservative estimates for exposures during this
unloading operation. Actual exposures may be less due to various factors including closed-
system unloading or the use of vapor recovery systems.
3.4.1.11 Printing Inks (3D)
1,4-Dioxane is used in solvent-based inks that are used in a type of additive manufacturing
known as material jetting or 3D printing (U.S. EPA. 2017c). A published literature review and
hazard assessment for material jetting measured exposures to a number of chemicals, including
1,4-dioxane, during additive manufacturing. This report provided a single data point from an 8-
hour sampling period for 1,4-dioxane exposure (Ryan and Hubbard. 2016). The sample was
collected inside a commercial grade photopolymerization 3D printer enclosure. Ryan and
Hubbard (2016) reported that the 1,4-dioxane concentrations could be higher than the observed
value in cases of lack of local exhaust ventilation and operation of multiple printers. Other
researchers also supported the observations indicating that the releases of volatile organic
carbons (VOCs) and particulate matters would move to higher concentration levels depending on
the temperature of the nozzle, extrusion temperature, the type of filament used, and type of 3D
printer (Zhang et at., 2017; 2018). The information and data evaluation for worker exposures
during use of printing inks are presented in Table 3-20. See Appendix G. 1 for more details about
the data quality evaluation.
Table 3-20. Use of Printing Inks Data Evaluation
\\ orkcr Acli\ il\ or
Siiiiiplin^ Locution
Diilii Tjpe
Number of Samples
Diilii (|iiiilil> rsiling
Source Reference
3-D printing
\rca Mniiiini'iiiu
Data
1
High
i
2016)
The scores for this source were assigned "High" and weighted higher than other sub-scores, including the sample
size, which was scored "Medium." The overall confidence score of this source was rated "High" despite single data
set.
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EPA used this sample value to calculate acute and chronic inhalation exposures (Table 3-21) per
the equations shown in Appendix G.2. EPA cannot determine the statistical representativeness of
the values given the small sample size. It is estimated that a total of 59,970 workers, and 20,430
ONUs could be exposed across all the sites. EPA estimated the number of potentially exposed
workers and ONUs using BLS and SUSB data for the applicable NAICS codes. See Appendix
G.5 for more information about the steps used to estimate workers and ONUs. Additional
information including specific methodology for estimating workers, typical use in printing inks,
and details about the monitoring data for 1,4-dioxane used in printing inks (3D) are described in
Appendix G.6.8.
Table 3-21. Acute and Chronic Inhalation Exposures of Worker for Use of Printing Inks
Based on Monitoring Data
Exposure Type
Central
Tendencya
(mg/m3)
High-End a
(mg/m3)
Data quality rating of Associated
Source b
8-hour TWA Exposure
Concentrations
0.097
High
8-hour TWA Acute Exposure
Concentration (AEC)
0097
High
Average Daily Concentration
(ADC)
0.093
High
Lifetime Average Daily
Concentration (LADC)
0.037
0.048
High
a These values are plausible, but EPA cannot determine the variability and uncertainty of the values due to lack of
data. High uncertainty is introduced given that these values are based on one point.
b See Table 3-20 for corresponding references.
Exposure data for ONUs were not available. EPA expected that ONU exposures may be lower
than worker exposures, since ONUs do not typically directly handle the chemical. Only
inhalation exposures to vapors are expected, which will likely be less than worker exposures to
vapors.
Key Uncertainties
The data source used only provided one data point that was used to estimate the inhalation
exposure of workers. EPA cannot determine the statistical representativeness due to limited data.
The representativeness of this value to other 3D printing sites is unknown. Additionally, the
sample provided is not a PBZ sample. Since the sample was taken within the 3D printing
enclosure, the exposure value is likely higher than a worker would typically experience while
operating the 3D printer. EPA considered the available monitoring data as no model is readily
available to predict the release of 1,4-dioxane under this work condition.
3.4.1.12 Dry Film Lubricant
1,4-Dioxane is used as a carrier in the manufacturing and application of a dry film lubricant.
Occupational exposures to 1,4-dioxane during manufacturing and application were estimated by
evaluating PBZ monitoring sample data provided by the U.S. Department of Defense, Kansas
City National Security Campus (KCNSC) (DOE. 2018a). The information and data evaluation
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for worker exposures during use of dry film lubricant are presented in Table 3-22. See Appendix
G. 1 for more details about the data quality evaluation.
Table 3-22. Dry Film Lubricant Data Source Evaluation
Worker Activity or Sampling
Location
Data Type
Number of Samples
Data
quality
rating
Source Reference
Non-nuclear parts manufacturing
for nuclear devices.
PBZ and Area
Monitoring Data
25
High
(DOE. 2018a)
Non-nuclear parts manufacturing
for nuclear devices.
Number of
Workers
N/A - Monitoring
data not provided
High
(DOE. 2018b)
These data were used to assess inhalation exposures to 1,4-dioxane for this condition of use. The
PBZ samples included two full shift 8-hour TWA samples and five 8-hour TWAs that are
derived from same-day task-based TWA samples, for a total of seven 8-hour TWA samples.
These data are shown in Appendix G.6.9. EPA calculated the 95th percentile and 50th percentile
of the available data. Acute and chronic inhalation exposures were calculated using the
assumptions and equations listed in Appendix G.2. The dry film lubricant was manufactured six
to eight days per year and the lubricant was applied about 48 days per year for a total exposure
frequency of 56 days per year at the KCNSC-reported facility (DOE. 2018a). This assumption
was used in place of the standard 250 days per year consideration as outlined in Appendix G.2.
The results are summarized in Table 3-23. Based on information provided by KCNSC, it is
estimated that 16 workers and 64 ONUs could be exposed across all sites (DOE. 2018b).
Additional information regarding this use, including monitoring data and assumptions made, are
included in Appendix G.6.9.
Table 3-23. Acute and Chronic Inhalation Exposures of Workers for the Use of Dry Film
Lubricant Based on Exposure Data
Exposure Type
Central Tendency
(50th Percentile)
(mg/m3)
High-end
(95th Percentile)
(mg/m3)
Data quality rating of
Associated Sourcea
8-hour TWA Exposure Concentrations
0.47
1.6
High
Acute Exposure Concentration (AEC)
0.47
1.6
High
Average Daily Concentration (ADC)
0.10
0.35
High
Lifetime Average Daily Concentration
(LADC)
0.040
0.18
High
a See Table 3-22 for corresponding references.
Information was not available as to whether other Department of Energy (DOE) facilities within
the National Nuclear Security Administration (NNSA) use 1,4-dioxane like the KCNSC.
However, it was assumed the other seven facilities in the NNSA use 1,4-dioxane in the same
manner and workers are exposed at the same levels as at the KCNSC.
Key Uncertainties
EPA confirmed with the KCNSC that the 8-hour TWAs from task samples were representative
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of the employee's entire 1,4-dioxane exposure during their shift. EPA was not, however, able to
confirm if other DOE facilities within the NNSA use 1,4-dioxane in addition to the KCNSC.
EPA assumed the other seven facilities in the NNSA use 1,4-dioxane in the same manner and
workers are exposed at the same levels as at the KCNSC.
3.4.1.13 Disposal
Each of the conditions of use of 1,4-dioxane could generate waste streams containing 1,4-
dioxane that are collected and transported to third-party sites for disposal, treatment, or
recycling. Industrial sites that treat or dispose onsite generated wastes were assessed for the
occupational exposure assessment for each condition of use in Sections 3.4.1.2 through 3.4.1.12
(except closed functional fluids). The information and data evaluation for worker exposures
during disposal are presented in Table 3-24. See Appendix G.l for more details about the data
quality evaluation.
Table 3-24. Disposal Data Source Evaluation
\\ orkcr Acli\ il\ or
Siiinplin^ Locution
l);il;i l\|H'
Niiiiihi-r of Siimpk-s
Diilii (|iiiilil> nilinii
Source Reference
N/A
TRI Data
N/A
Medium
(IIS. EPA. 2016b)
EPA modeled occupational exposures using the EPA AP-42 Loading Model and the EPA Mass
Balance Inhalation Model to estimate central tendency and high-end 8-hour TWA exposures.
EPA used a Monte Carlo simulation to vary the saturation factor (f), ventilation rate (Q), and
mixing factor (k). See Appendix G.4 for more information about the Monte Carlo simulation.
EPA also estimated the 3.2-minute (0.054 hr) exposures from drum unloading as central
tendency and high-end short-term exposures (see Table 3-25). EPA used these values to calculate
acute and chronic inhalation exposures in the Monte Carlo simulation, varying working years
(WY), using the equations in Appendix G.2.
A total of 124 workers and 45 ONUs could be exposed across all the sites. EPA estimated the
number of potentially exposed workers and ONUs using BLS and SUSB data for the applicable
NAICS codes. See Appendix G.5 for more information about the steps used to estimate workers
and ONUs. Additional information including typical disposal methods, TRI data, and
assumptions for estimating exposure values for the disposal of 1,4-dioxane are described in
Appendix G.6.10.
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Table 3-25. Acute and Chronic Inhalation Exposures of Worker for Disposal Based on
Modeling
Exposure Type
Central Tendency
(50th Percentile)
(mg/m3)
High-end
(95th Percentile)
(mg/m3)
Data quality rating of
Associated Sourcea
Short-Term Exposure Concentration
(0.054 hrs)
170
610
N/A - Modeled Data
8-hour TWA Exposure Concentrations
1.2
4.1
N/A - Modeled Data
8-hour TWA Acute Exposure
Concentration (AEC)
1.2
4.1
N/A - Modeled Data
Average Daily Concentration (ADC)
1.1
3.9
N/A - Modeled Data
Lifetime Average Daily Concentration
(LADC)
0.42
1.6
N/A - Modeled Data
a See Table 3-24 for corresponding references.
Exposure data for ONUs were not available. EPA did not model exposures for ONUs, but EPA
expects ONU exposures to be lower than worker exposures, since ONUs do not typically directly
handle the chemical. Only inhalation exposures to vapors are expected, which will likely be less
than worker exposures.
Key Uncertainties
EPA modeled inhalation exposures using the EPA AP-42 Loading Model and the EPA Mass
Balance Inhalation Model. Process specifics for disposal sites were not available, therefore, EPA
assumed certain process details, such as container sizes and unloading frequency. Additionally,
EPA assumed that the process steps associated with this scenario occur indoors, without
engineering controls, and in an open-system environment where vapors freely escape. In the
absence of industry-specific information, these assumptions provide for conservative estimates
for exposures during this operation. Actual exposures may be less due to various factors
including closed-system loading and unloading, the use of vapor recovery systems, or the
automation of various process steps.
3.4.1.14 Dermal Exposure Assessment
EPA estimated workers' dermal exposure to 1,4-dioxane for the industrial and commercial use
scenarios considering evaporation of liquid from the surface of the hands and conditions of use
with and without gloves. The OSHA recommends employers utilize the hierarchy of controls, a
general concept that OSHA accepts as good industrial hygiene practice, for reducing or removing
hazardous exposures. OSHA's hierarchy of controls (indicate that the most effective controls are
elimination, substitution, or engineering controls. Gloves are the last course of worker protection
in the hierarchy of controls and should only be considered when process design and engineering
controls cannot reduce workplace exposure to an acceptable level.
Vapor absorption during dermal exposure requires that 1,4-dioxane be capable of achieving
concentration in the media at the temperature and atmospheric pressure of the scenario under
evaluation to provide a significant driving force for skin penetration. Because 1,4-dioxane is a
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volatile liquid (VP = 40 mmHg and 25°C) the dermal absorption of 1,4-dioxane depends on the
type and duration of exposure. Only a fraction of 1,4-dioxane that contacts the skin will be
absorbed as the chemical readily evaporates from the skin. Dermal absorption may be significant
in cases of repeated contacts or dermal immersion. See Appendix G.7 for more information
about the incorporation of gloves in the dermal exposure assessment. EPA collected and
reviewed available SDSs to inform the evaluation of gloves used in the following conditions of
use:
• Manufacturing;
• Import and Repackaging;
• Spray Foam Application;
• Laboratory Chemicals; and
• Film Cement.
Except for spray foam use, the SDSs recommended the use of protective or chemical resistant
gloves during the handling of 1,4-dioxane or film cement. The spray foam related SDS indicated
that the selection of specific PPE depends on the operation. However, a specific glove material
or protection factor rating was not provided (BASF. 2.018b; , .a. 2014; Kodak.
2011). In case of incidental contacts (for example, a spill or splash, over spray from a dispensing
device), double nitrile gloves (8 mil) or single heavier nitrile gloves (15 mil) could be used. For
operations involving the use of larger amounts of 1,4-dioxane (for example, transferring dioxane
from one container to another) or for other potential extended contact, butyl rubber gloves could
be used (Viton™ or equivalent gloves need to be avoided as 1,4-dioxane degrades synthetic
fluoropolymer product). EPA also notes that the use of PPE, such as gloves, can vary from site-
to-site depending on factors such as availability, cost, worker compliance, and impact on job
performance. Therefore, EPA presents a range of glove usage scenarios with a variety of
protection factors in Table 3-27.
To assess dermal exposure, EPA used the EPA Dermal Exposure to Volatile Liquids model (See
Equation 3-1) to calculate the dermal retained dose. The equation modifies the EPA 2-Hand
Dermal Exposure to Liquids Model by incorporating a "fraction absorbed (fabs)" parameter to
account for the evaporation of volatile chemicals and a "protection factor (PF)" to account for
glove use. Default PF values, which vary depending on the type of glove used and the presence
of employee training program, are shown in Table 3-26. The additional details to calculate
dermal exposures are described in Sections 5.2.5 and 5.2.6, and Appendix G.7.
Equation 3-1. Dermal Dose Equation
'exp
D C V ( Qt xfabs) v V v PT
u pvri j a a ' derm
Where:
S
Qu
Y derm
FT
surface area of contact (cm2)
quantity remaining on the skin after bulk liquid has been wiped away (mg/cm2-
event)
weight fraction of the chemical of interest in the liquid (0 < Yderm < 1)
frequency of events (integer number per day)
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fabs = fraction of applied mass that is retained and potentially absorbed (Defaults for
1,4-dioxane: 0.78 for industrial use and 0.86 for commercial use)
PF = glove protection factor (Default: see Table 3-26.)
The fractional absorption (fabs) for 1,4-dioxane is estimated to be 0.86 in commercial settings
with lower indoor wind speeds and 0.78 in industrial settings with higher indoor wind flows
based on a theoretical framework provided by Kasting and Miller (2006). meaning that 86% or
78% of the applied dose is retained by the stratum corneum, the outermost layer of the epidermis
skin, and potentially absorbed. EPA used measured values for dermal absorption of 0.3% or
3.2% to calculate the amount of the retained dose that may be systemically absorbed when
determining potential risks to workers (Bronaugh. 1982; Marzulli etai. 1981). For example,
EPA calculated an applied dermal dose of 1,759 mg/day for workers in the manufacturing setting
(See Table 3-27). The applied dermal dose factored in the percentage of 1,4-dioxane lost (i.e.,
14%) or 22%), due to evaporation. For quantifying potential dermal risks to workers, EPA used
the measured absorption values of 0.3% for scenarios without gloves and 3.2% for scenarios with
gloves to quantify the amount of the applied dermal dose that would be systemically available.
Table 3-26. Glove Protection Factors for Different Dermal Protection Strategies
Dorniiil Pmk'Clion ( li;u ;ic(i'i is(ics
Selling
Pmlciiion I nclor.
PI-
a. No gloves used, or any glove / gauntlet without permeation data and
without employee training
Industrial and
Commercial Uses
1
b. Gloves with available permeation data indicating that the material of
construction offers good protection for the substance
5
c. Chemically resistant gloves (i.e., as b above) with "basic" employee
training
10
d. Chemically resistant gloves in combination with specific activity
training (e.g., procedure for glove removal and disposal) for tasks where
dermal exposure can be expected to occur
Industrial Uses
Only
20
Table 3-27 presents the estimated dermal absorbed dose for workers in various exposure
scenarios. The dose estimates assume one exposure event (applied dose) per work day and that
approximately seventy-eight to eighty-six percent6 of the applied dose is absorbed through the
skin. The exposure estimates are provided for each condition of use, where the conditions of use
are "binned" based on the maximum possible exposure concentration (Yderm), the likely level of
exposure. The exposure concentration is determined based on EPA's review of currently
available products and formulations containing 1,4-dioxane. For example, EPA found that 1,4-
dioxane concentration in film cements can be as high as 50 percent (Kodak. 2.011).
To streamline the dermal exposure assessment, the conditions of use were grouped based on
characteristics known to effect dermal exposure such as the maximum weight fraction of 1,4-
dioxane that could be present in that condition of use, open or closed system use of 1,4-dioxane,
6 The absorbed fraction (fabs) is a function of indoor air flow rate, which differs for industrial and commercial
settings.
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and large or small-scale use. Six different groups or "bins" were created to group conditions of
use based on this analysis.
• Bin 1 covers large-scale industrial uses that typically occur in a closed system. For these
uses, dermal exposure is likely limited to chemical loading/unloading activities (e.g.,
connecting hoses).
o No gloves used: Operators in these industrial uses, while working around closed-
system equipment, may not wear gloves or may wear gloves for abrasion
protection or gripping that are not chemical resistant.
o Gloves used with a protection factor of 5, 10, and 20: Operators may wear
chemical-resistant gloves when taking quality control samples or when
connecting and disconnecting hoses during loading/unloading activities. EPA
assumes gloves may offer a range of protection, depending on the type of glove
and employee training provided.
• Bin 2 covers open system functional fluids, which includes metalworking fluids and
cutting and tapping fluids. During these types of open-system operations, workers are
expected to be exposed during chemical loading/unloading; container cleaning; diluting
water-based metalworking fluids; metal shaping operations; rinsing, wiping, and/or
transferring the completed part; changing filters; transferring spent fluids; and cleaning
equipment.
o No gloves used: Due to the variety of shop types in these uses the actual use of
gloves is uncertain. EPA assumes workers may not wear gloves or may wear
gloves for abrasion protection or gripping that are not chemical resistant during
routine operations.
o Gloves used with a protection factor of 5, 10, and 20: Workers may wear
chemical-resistant gloves when charging and draining metal shaping equipment,
drumming spent metalworking fluid, and changing filters. EPA assumes gloves
may offer a range of protection, depending on the type of glove and employee
training provided.
• Bin 3 covers the use of 1,4-dioxane in small-scale industrial uses. Workers may unload
small volumes of nearly pure 1,4-dioxane and directly handle small quantities in research
labs.
o No gloves used: Operators in these small-scale industrial uses, while working
around small amounts of the chemical, may not wear gloves or may wear gloves
for abrasion protection or gripping that are not chemical resistant.
o Gloves used with a protection factor of 5, 10, and 20: Operators may wear
chemical-resistant gloves when taking quality control samples or when
transferring small quantities of the chemical. EPA assumes gloves may offer a
range of protection, depending on the type of glove and employee training
provided.
• Bin 4 covers the use of 1,4-dioxane in polyurethane spray foam insulation. Workers are
expected to be exposed during chemical unloading, spray application, and trimming
activities.
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o No gloves used: Actual use of gloves in this use is uncertain. EPA assumes
workers may not wear gloves or may wear gloves for abrasion protection or
gripping that are not chemical resistant during routine operations,
o Gloves used with a protection factor of 5, 10, and 20: Workers may wear
chemical-resistant gloves when charging application equipment, applying the
foam, and trimming cured spray foam insulation. EPA assumes gloves may offer
a range of protection, depending on the type of glove and employee training
provided.
• Bin 5 covers the use of 1,4-dioxane in film cements. Workers are exposed during manual
application of the film cement with a small brush. The NIOSH HHE observed splicer
operators had skin contact with 1,4-dioxane and recommended that employees wear
neoprene or other appropriate chemical resistant gloves when handling solvents,
including 1,4-dioxane (Okawa and Cove. 1982). The NICNAS report concludes that
exposures to skin are likely insignificant in comparison to inhalation exposures for this
use fNICNAS. 19981
o No gloves used: Operators in these small-scale photo shops, while working
around small amounts of the chemical, may not wear gloves or may wear gloves
for gripping that are not chemical resistant,
o Gloves used with a protection factor of 5, 10, and 20: Operators may wear
chemical-resistant gloves when transferring small quantities of the chemical,
applying the film cement, or trimming film coated with cured film cement. EPA
assumes gloves may offer a range of protection, depending on the type of glove
and employee training provided.
• Bin 6 covers the use of 1,4-dioxane in the manufacture and application of dry film
lubricants. Workers are expected to unload and handle small volumes of pure 1,4-dioxane
during dry film lubricant manufacture, mixing, and spray application. Although the
process is small-scale and involved handling of purity of 1,4-dioxane similar to Bin 3, Bin 6
is considered a separate industrial application as it is part of a larger manufacturing
process. The information available with respect to exposures due to glove
permeation/chemical breakthrough also allowed a separate bin.
o Gloves used with a protection factor of 5, 10, and 20: Operators may wear
chemical-resistant gloves when taking quality control samples, when transferring
small quantities of the chemical, mixing, or spray applying. EPA assumes gloves
may offer a range of protection, depending on the type of glove and employee
training provided.
o Scenarios not assessed: The "no gloves" exposure scenario is not included in Bin
6 because Kansas City National Security Campus, the only known manufacturer,
reports that their workers use gloves in their operation.
As shown in the Table 3-27, the calculated absorbed dose is high, which is due to high
absorption characteristics, miscibility with water, and a lower octanol-water coefficient (-0.27)
( 2014a). Dermal exposure to liquid is not likely for ON Us, as they do not directly
handle 1,4-dioxane unless there is incidental contact on surfaces due to improper handling or
improper work practice.
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Table 3-27. Estimated Dermal Absorbed Dose1 (mg/day) for Workers in All Conditions of
Use
Exposures due to Glove Permeation/Chemical
Weight
Fraction
(Max
Yderm)
Breakthrough (mg/day)
Protective
Protective
Condition of Use
Bin
No Gloves
(PF = 1)
Protective
Gloves2
(PF = 5)
Gloves2
(Commercial
uses, PF =
10)
Gloves2
(Industrial
uses,
PF = 20)
Manufacture
Import and Repackaging
Bin 1
1.00
1,759
N/A
N/A
Industrial Use
OO
Disposal
Functional Fluids (Open System)
Bin 2
0.001
1.76
N/A
N/A
0.09
Laboratory Chemicals
Bin 3
1.00
1,924
385
192
N/A
Use of Printing Inks (3D)
Spray Foam Application
Bin 4
0.001
1.92
0.39
0.19
N/A
Film Cement
Bin 5
0.50
962
192
96
N/A
Dry Film Lubricant
Bin 6
1.00
N/A
N/A
N/A
88
N/A = not applicable.
'The identified amounts are assumed to be retained by the stratum corneum, the outermost layer of the
epidermis skin, and potentially absorbed. The resistance of viable tissue layers underlying the stratum corneum may
reduce further absorption. Additional information available in Appendix G-27 and (Marquart et al.. 2017).
4 HAZARDS (Effects)
4.1 Environmental Hazards
4.1.1 Approach and Methodology
As part of problem formulation, EPA reviewed and characterized the environmental hazards
associated with 1,4-dioxane. EPA identified the following sources of environmental hazard data
for 1,4-dioxane: (Health Canada. 2010; ECJRC. 2002; OECD. 1999; NICNAS. 1998) and the
European Chemicals Agency (ECHA) Database. Studies published between 2003 and 2018 were
identified in the literature search for 1,4-dioxane (1,4-Dioxane (CASRN123-91-1) Bibliography:
Supplemental File for the TSCA Scope Document, EPA-HQ-QPPT-2016-0723) and were
reviewed as described in Application of Systematic Review in TSCA Risk Evaluations (U.S. EPA.
2018b) and Strategy for Assessing Data Quality in TSCA Risk Evaluations (U.S. EPA. 2018d).
EPA completed the review of environmental hazard data/information sources during risk
evaluation using the data quality evaluation metrics and the rating criteria described in the
Application of Systematic Review in TSCA Risk Evaluations (U.S. EPA. 2018b). The data quality
evaluation results for 1,4-dioxane environmental hazard are presented in Appendix F. Studies
with data quality evaluation results of 'high' were used to characterize the environmental hazards
of 1,4-dioxane.
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4.1.2 Hazard Identification- Toxicity to Aquatic Organisms
EPA identified and evaluated 1,4-dioxane ecological hazard data for fish, aquatic invertebrates
and aquatic plants exposed under acute and chronic exposure conditions. These data were
presented in the problem formulation and with no further hazard analyses in the analysis plan.
The results of the review are summarized in Appendix F.
Table F-l summarizes the acute toxicity of 1,4-dioxane to aquatic organisms. The toxicity for
aquatic plants ranges from an 8-day EC50 of 575 mg/L for Blue-green algae (Anacystis
aeruginosa) to a 10-day LOEC of 5,600 mg/L for Green algae (Scenedesmus quadricauda). The
acute toxicity of 1,4-dioxane to aquatic invertebrates ranges from a 24-hour EC50 of 2,274 mg/L
for Amphipod (Gammarus pseudolimnaeus) to 8,450 mg/L for the Water flea (Daphnia magna).
The acute 96-hour toxicity of 1,4-dioxane to fish ranges from 67,000 for Silversides (Menidia
beryllina) to 13,000 mg/L for the Fathead minnow (Pimephales promelas). These values indicate
that the acute toxicity of 1,4-dioxane to aquatic organisms is considered low.
Table F-2 summarizes the chronic toxicity of 1,4-dioxane to aquatic vertebrates (fish). The
chronic toxicity of 1,4-dioxane to fish ranges from a 32-day MATC of >145 mg/L for the
Fathead minnow (Pimephales promelas) to an 8-day LOEC of 565 mg/L for Medaka (Oryzias
latipes). These toxicity values indicate that the chronic toxicity of 1,4-dioxane to fish is low.
The acute and chronic concentrations of concern (COC) for 1,4-dioxane were calculated based
on the most sensitive species. The lowest acute toxicity value for aquatic organisms (i.e., most
sensitive species) for 1,4-dioxane is from a 96-hour fish toxicity study where the LC50 is 1,236
mg/L (Geieer et at.. 1990). For the chronic COC, the lowest chronic toxicity value is from a
chronic 32-day MATC fathead minnow study of > 145 mg/L (Brooke. 1987).
The acute COC for 1,4-dioxane is 247,200 ppb based on the lowest value LC50.The acute COC
for 1,4-dioxane is 247,200 ppb and the chronic COC is 14,500 ppb.
4.2 Human Health Hazards
4.2.1 Approach and Methodology
EPA used the approach described in Figure 4-1 to evaluate, extract and integrate 1,4-dioxane's
human health hazard and dose-response information. This approach is based on the Application
of Systematic Review in TSCA Risk Evaluations ( >) and the Framework for
Human Health Risk Assessment to Inform Decision Making ( 014d).
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Human Health Hazard Assessment
Risk Characterization
Systematic
Review
Stage
Data Evaluation
After full-text screening,
apply pre-detennined data
quality evaluation criteria
to assess the confidence of
key and supporting studies
identified from previous
assessments as well as
new studies not
considered in the previous
assessments
Output of
Systematic
Review
Stage
Study Quality
Summary
Table (High,
Medium and
Low)
(Appendix F-
1)
Data
Extraction
Extract data from
key, supporting
and new studies
Data Integration
Integrate hazard information by considering quality (i.e.,
strengths, limitations), consistency, relevancy, coherence and
biological plausibility
Hazard ID
Confirm potential
hazards identified
during
scoping/problem
formulation and
identify new hazards
from new literature (if
applicable)
Dose-Response
Analysis
Benchmark dose
modeling for
endpoints with
adequate data:
Selection ofPODs
Data
Summaries for
Adverse
Endpoints
(Appendix F
2)
Summary of
Results and
PODs
(Sections
4.2.5, 4.2.6
and 5.2.1)
WOE
Narrative by
Adverse
Endpoint
(Section 4.2.4)
Risk Characterization
Analysis
Determine the qualitative
and/or quantitative human
health risks and include, as
appropriate, a discussion of:
• Uncertainty and variability
• Data quality
• Alternative interpretations
Risk Estimates
and
Uncertainties
(Sections 5.2
and 5.3)
Figure 4-1. EPA Approach to Human Health Hazard Identification and Dose-Response for
1,4-Dioxane
Specifically, EPA reviewed key and supporting information from previous hazard assessments
[EPA IRIS Assessments (U.S. EPA. 2013 c. 20101 an AT SDR Toxicological Profile (AT SDR.
2012). a Canadian Screening Assessment (Health Canada. 2010). a European Union (EU) Risk
Assessment Report (ECJRC. 2002). and an Interim AEGL (U.S. EPA. 2005b)l. EPA also
screened and evaluated new studies that were published since these reviews, as identified in the
literature search conducted for 1,4-dioxane (1,4-Dioxane (CASRN123-91-1) Bibliography:
Supplemental File for the TSCA Scope Document, EPA-HQ-QPPT-2016-0723).
The new literature was screened against inclusion criteria in the PECO statement and the relevant
studies (e.g., useful for dose-response)7 were further evaluated using the data quality criteria for
human, animal, and in vitro studies described in the Application of Systematic Review in TSCA
Risk Evaluations (U.S. EPA. 2018b) (Figure 4-1). EPA skipped the screening step of the key and
supporting studies and entered them directly into the data evaluation step based on their
relevance to the risk evaluation. Hazard studies by all routes of exposure were included since
inhalation exposures are directly relevant to workers and oral exposures can be used in route-to-
route extrapolation for dermal risk to workers.
EPA considered studies of low, medium, or high confidence for hazard identification and dose-
response analysis. Information that was rated unacceptable was not included in the risk
evaluation. Appendix H presents the information on human health hazard endpoints (acute, non-
cancer, and cancer) for all acceptable studies (with low, medium, or high scores).
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EPA has not developed data quality criteria for all types of hazard information. This is the case
for toxicokinetics and many types of mechanistic data which EPA typically uses for qualitative
support when synthesizing evidence. As appropriate, EPA evaluated and summarized these data
to determine their utility with supporting the risk evaluation.
Following the data quality evaluation, EPA extracted the toxicological information from each
relevant study (Figure 4-1). In the last step, the strengths and limitations of the data are evaluated
for each endpoint and a weight-of-the-scientific evidence narrative is developed. Also, data for
each selected hazard endpoint is modeled to determine the dose-response relationship (Appendix
I). Finally, the results are summarized, and the uncertainties are presented.
Adverse health effects associated with inhalation exposure to 1,4-dioxane were identified by
considering the quality and weight-of-the-scientific evidence to identify key endpoints and the
potential mode of action (MOA) for cancer was evaluated according to the framework for MOA
analysis described in the EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA. 2.005a).
Information for each adverse hazard endpoint (acute and chronic non-cancer and cancer) was
evaluated and integrated with information on toxicokinetics and MOA in a weight-of-the-
scientific evidence narrative (Section 4.2.3). Information on MOA was evaluated in Section
4.2.4. The evidence for genotoxicity is summarized in Appendix H.1.5.
Data for the dose-response assessment were selected from the key studies and dose-response
modeling was performed, when the data were amenable to modeling, for adverse hazard
endpoints from those studies (Section 4.2.5). The dose-response assessment included analyses of
the non-cancer and cancer endpoints for inhalation and oral exposures identified in the hazard
identification. Limited toxicological data are available by the dermal route, so the dose-response
data from oral exposures were used to extrapolate to dermal exposures according to the European
Chemical Agency's Guidance on information requirements and chemical safety assessment,
Chapter R. 8: Characterisation of dose [concentration]-response for human health (ECHA.
2008V
4.2.2 Toxicokinetics
EPA accepted conclusions about the validity of toxicokinetic data and physiologically-based
pharmacokinetic (PBPK) models based on previous peer reviews. In the 2013 EPA/IRIS
assessment of l,4-dioxane( 13c). the quality of the toxicokinetic data (published
through 2013) and PBPK models were evaluated according to established standard operating
procedures (SOPs) and a quality assurance project plan. In addition, the IRIS assessment
followed procedures contained in Approaches for the Application of Physiologically Based
Pharmacokinetic (PBPK) Models and Supporting Data in Risk Assessment ( 2006a).
SOPs for identification, organization, and evaluation of absorption, distribution, metabolism, and
elimination (ADME) and toxicokinetic studies and models have since been updated and
consolidated into An Umbrella Quality Assurance Project Plan (QAPP) for PBPK Models (U.S.
EPA, 2018e). Two additional toxicokinetic studies identified in the literature search (Goem et al.
2016; Take et al.. 2012)were considered in the weight-of-the-scientific evidence evaluation.
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Absorption
Based on reasonably available absorption data, 1,4-dioxane could be absorbed via inhalation,
distributed to tissues, extensively metabolized, and rapidly eliminated in humans and animals. In
studies in a small number of human subjects, 1,4-dioxane was readily absorbed via inhalation,
metabolized to P-hydroxyethoxy-acetic acid (HEAA), and rapidly and extensively eliminated in
urine (Goen et ai. 2016; 1977; Young et at.. 1976). HEAA may tautomerize to the potentially
reactive lactone l,4-dioxane-2-one, but the equilibrium is heavily weighted towards metabolism
to HEAA under physiological conditions (Woo et at.. 1977; Young et at... 1977).
Studies in rats show 1,4-dioxane is readily absorbed via oral and inhalation exposures (Take et
at.. 2012.). Dermal absorption studies using human skin (/'// vitro) and nonhuman primates (in
vivo) measured reduced absorption compared to other routes of exposure, due in part to
evaporation of 1,4-dioxane. Bronaugh (1982) measured in vitro penetration of 1,4-dioxane
through excised human skin under occluded and unoccluded conditions. Absorption was
recorded 205 minutes after application of radiolabeled 1,4-dioxane dissolved in lotion. Dermal
penetration of 1,4-dioxane was 3.2% of the applied dose for the occluded condition, and 0.3%
for unoccluded. In this study, rapid evaporation was observed, decreasing the amount available
for dermal absorption and creating uncertainty in the data. Marzutti et 81) exposed rhesus
monkeys to radiolabeled 1,4-dioxane (in methanol or skin lotion vehicle) for 24 hours under
unoccluded conditions on the forearm. Approximately 2-3% of the original radiolabel was
cumulatively recovered in urine over a 5-day period, but it is not clear how the study accounted
for metabolism.
Distribution
1,4-Dioxane is expected to evenly distribute to major organs based on limited data in animal
studies. Intraperitoneal (i.p.) injection studies in rats found roughly even distribution in the
tissues observed (whole blood, brain, liver, kidney, spleen, lung, colon, testes and skeletal
muscle) with no evidence of appreciable accumulation of 1,4-dioxane or HEAA in tissues
(Mikheev et at.. 1990; Woo et at.. 1977). Take et at. (2012) observed distribution to multiple
systemic tissues in rats following administration via inhalation, oral, and combined inhalation
and oral exposures.
Metabolism
1,4-Dioxane is extensively metabolized in humans and rats by oxidation (Figure 4-2)(Goen et at..
2016; Braun and Young. 1977; Woo et at.. 1977). Induction of CYP450 increases the amount of
HEAA in urine and suppression of CYP450 decreases the amount of HEAA in urine,
demonstrating that 1,4-dioxane metabolism is in part mediated by CYP450 (1978, 1977). 1,4-
Dioxane induces several CYP450 isomers including CYP2B1/2, CYP2C11, CYP2E1, and
CYP3A, but not CYP4A1 (Nannetti et at.. 2005). EPA evaluated two new metabolism studies
(data evaluation summary in Appendix G. 1) that measured in vitro hepatic microsomal CYP2E1
enzyme activity (Patil et al.. 2015; Shah et at.. 2015). 1,4-Dioxane exhibited dose-dependent
inhibition of the CYP2E1-mediated p-nitrophenol hydrolase activity (Patil et al.. 2015) and
inhibited the metabolism of water-soluble substrates of CYP450 in liver microsomes (Shah et al.,
2015).
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While the extent of metabolism is high, there is evidence for metabolic saturation at high doses.
The extent of urinary elimination of the metabolite HEAA, and elimination of unchanged 1,4-
dioxane in exhaled air, exhibit dose-dependencies. In rats exposed intravenously, as dose
increases, the percentage of urinary HEAA decreases, while the percentage of 1,4-dioxane in
exhaled air increases (Young et at.. 1978a). Metabolic saturation in rats after a single intravenous
dose occurred when blood levels were near 100 (.ig/mL ("Young et at.. 1978b; Kociba et at..
1975). However, in a 13-week inhalation study, metabolic saturation was not observed at plasma
concentrations up to 730 and 1,054 (.ig/mL in male and female rats, respectively (Kasai et at..
2008). The lack of metabolic saturation in the Kasai et al. (2008) study is likely attributed to 1)
enhanced metabolism due to induction of P450 enzymes (including CYP2E1) by 13 weeks of
repeated inhalation exposure to 1,4-dioxane, and/or 2) toxicokinetic differences between oral and
inhalation exposures (first-pass metabolism following oral ingestion may enhance the saturation
effect, since the liver receives higher exposure). Take et al. (2012) exposed rats to 1,4-dioxane
by inhalation and oral gavage (single-route and simultaneous multi-route exposures) and
observed a synergistic effect of combined exposures on systemic concentrations. During multi-
route exposures (which resulted in high systemic concentrations of 1,4-dioxane), ingested 1,4-
dioxane was not cleared as rapidly as it was under oral-only exposure. This indicates the
importance of metabolic saturation and the first-pass effect. There was less of an impact of
combined exposures on the clearance of inhaled 1,4-dioxane.
Figure 4-2. 1,4-Dioxane Metabolism Pathways
1= 1,4-dioxane; II = diethylene glycol; 111 = p-hydroxyethoxy acetic acid (HEAA); IV = 1,4-
dioxane-2-one; V = l,4-dioxane-2-ol; VI = hydroxyethoxy acetaldehyde
Elimination
Elimination of 1,4-dioxane in humans and rats is primarily via urine in the form of the metabolite
HEAA(Goen et al. 2.016; 1978a; Young et al, 1976). The elimination half-life of 1,4-dioxane in
plasma was approximately 1 hour in humans and rats and elimination of HEAA in urine was 2.7
hours (Young et al.. 1977). These short half-lives of 1,4-dioxane and the metabolite HEAA
indicate that repeated daily exposures such as those that occur in typical workplace scenarios
would not be expected to result in the accumulation of 1,4-dioxane or HEAA in workers' bodies.
hoh2c
COOH
m
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Physiologically-Based Pharmacokinetic (PBPK) Models
EPA did not revise available PBPK models for the derivation of points of departure (PODs) for
1,4-dioxane or use a PBPK model for route-to-route or cross-species extrapolation in this risk
evaluation. The 2010 and 2013 EPA/IRIS assessments of 1,4-dioxane evaluated several
empirical toxicokinetic models, PBPK models, and supporting data (Sweeney et at... 2008; Fisher
et at.. 1997; Leung and Paustenbach. 1990; Reitz et at.. 1990; 1978a; Young et at.. 1977) and
concluded that none were adequate for use in dose-extrapolation between species.
Recent toxicokinetics studies include Take et al. (2012) and Goen et al. (2016). Take et al.
Q provides time course toxicokinetic data in multiple tissues for rats exposed via inhalation,
oral ingestion, and combined inhalation and oral ingestion. Goen. et al. (2016) provides blood and
urine data from human volunteers exposed via inhalation at a 1,4-dioxane concentration of 20
ppm for approximately 8 hours (with data spanning 24 hours). Because observations in Goen et
at. (2 are generally consistent with data from a previous study (Young et al.. 1977). EPA
concluded that model inadequacies and calibration issues for the human model identified in the
2013 IRIS assessment would not be resolved by the inclusion of the new data. Significant
uncertainties remain regarding the appropriate internal dose metric that would be used.
Specifically, there are uncertainties on whether the parent compound or metabolite (or some
combination of both) are responsible for the observed effects of 1,4-dioxane, and uncertainty
whether organ-specific or blood concentrations should be used.
4.2.3 Hazard Identification
For the human health hazard identification, EPA identified key and supporting studies from
previous peer reviewed assessments and new studies published since 2009 and evaluated them
against the data quality criteria. This section summarizes the key, supporting and new studies,
data on non-cancer hazards (Section 4.2.3.1), genetic toxicity and cancer hazards (Section
4.2.3.2) along with the results of the data quality evaluation (Appendix G.l). Potential modes of
action for 1,4-dioxane toxicity related to the cancer endpoints were evaluated (Section 4.2.4).
EPA reviewed the oral and inhalation studies to include in the weight-of-the-scientific evidence
analysis, route-to-route extrapolation, and for the cancer classification.
4.2.3.1 Non-Cancer Hazards
EPA reviewed the available toxicity data on 1,4-dioxane by the inhalation, oral, and dermal
routes of exposure from acute, short term, subchronic, and chronic studies. No short-term or
repeated-dose dermal toxicity studies were identified for 1,4-dioxane. The identified hazard
endpoints in the studies were evaluated for consistency and relevance to humans, according to
the Application of Systematic Review in TSCA Risk Evaluations ( 1018b). The results
of the data quality evaluation for the non-cancer studies (key and supporting studies and new
studies) are described here and included in the data extraction summary tables in Appendix G. A
few additional studies that have not been evaluated for data quality or included in data extraction
summary tables are discussed here as part of the knowledge regarding 1,4-dioxane toxicity.
Toxicity Following Acute and Short-Term Exposure
EPA evaluated studies describing the acute and short-term toxicity of 1,4-dioxane in humans and
in experimental animals. Each of these studies is discussed below, followed by a tabulated
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summary of the studies that EPA concluded were the highest quality and suitable for carrying
forward with evidence integration and evaluation under Section 4.2.5.
Controlled human studies have shown that acute exposures to 1,4-dioxane caused few
perceivable signs or symptoms or primarily irritation to the eyes, nose, and throat, depending on
the exposure duration and concentration. For example, Ernstgard et al. (2.006) reported that 12
volunteers (6 men and 6 women) exposed to 1,4-dioxane at 20 ppm (i.e., 72 mg/m3) for two
hours at rest produced no symptoms of irritation, headache, fatigue, or nausea, whereas Young et
al. (1977) reported eye irritation in 4 healthy male volunteers exposed for 6 hours to 50 ppm (180
mg/m3). Further.Yant et al. (1930) and Wirth and Klimmer (1936) reported that exposures of
greater than 1000 ppm (3603 mg/m3) for short durations (minutes) elicited irritation of mucous
membranes in human volunteers. In contrast to the controlled human volunteer studies,
Johnston reported the fatality of one worker after 1 week of occupational exposures to
1,4-dioxane, which was used as a cleaning agent. The mean measured air concentration in the
area was 470 ppm (1694 mg/m3) (range, 208-650 ppm, 749-2342 mg/m3). An autopsy on the
worker revealed pathological effects in the liver, kidney, lung, and brain.
In experimental animals, acute and short-term exposures to 1,4-dioxane have been shown to
cause comparable signs of toxicity as identified in acutely exposed humans, including eye and
nasal irritation, clinical signs of central nervous system (CNS) depression (including staggered
gait, narcosis, paralysis, coma, and death), liver and kidney degeneration and necrosis, and death
0 2013a, 2005b).
The available acute toxicity studies in experimental animals include inhalation studies aimed at
identifying adverse effects other than mortality (i.e., (Mattie et al.. 2012; Drew et al.. 1978)).
Drew et al. (1978) performed an acute 4-hour inhalation (whole body) exposure study in male
Sprague-Dawley rats. Animals (15 animals serving as their own controls)) were exposed to 1,4-
dioxane vapors (>99% pure) at concentrations of 0, 3603 or 7207 mg/m3. The authors reported
an increase in the activities of several serum enzymes associated with liver function in all treated
animals compared to controls.
Mattie et al. (2012.) performed an acute 6-hour inhalation (whole body) exposure study in
male/female F344/DuCrl rats. Animals (10/sex/group) were exposed to 1,4-dioxane vapors
(>99% pure) at 0, 429, 1013, 2875, 7920 or and 21,630 mg/m3. Effects were limited to vacuolar
changes in the nasal cavities (olfactory and respiratory epithelium) at two days post-exposure,
but not in rats after a two-week recovery period.
The available short-term toxicity studies in experimental animals include two-week inhalation
studies in adult rats (i.e., (Mattie et al.. 2012; Goldberg et al.. 1964) and one oral (gavage)
developmental toxicity study in female rats exposed on gestation days 9 to 15 (i.e., (Giavini et
al.. 1985)).
Mattie et al. (2012) performed a two-week inhalation (whole body) toxicity study in male/female
F344/DuCrl rats. Animals (16/sex/group) were exposed to 1,4-dioxane vapors (>99% pure) at 0,
378, 5599, and 11,690 mg/m3 for 6 hours/day, 5 days/week, for two weeks. Animals were
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sacrificed on post-exposure day 1 or day 14. The authors reported lesions in the nasal cavity,
kidney, and liver (including hepatic single cell necrosis) in the exposed animals on post-exposure
day 1. Liver effects were still present in exposed animals on post-exposure day 14. The authors
identified a LOAEC of 378 mg/m3, based on the liver effects.
In a separate two-week inhalation (whole body) toxicity study, (Goldberg et at.. 1964) exposed
female Sprague-Dawley (CFE) rats (8/group) to 1,4-dioxane vapors (purity not stated) at
concentrations of 0, 5405, 10,810, or 21,620 mg/m3 for 4 hours/day, 5 days/week, for two weeks.
The authors identified a NOAEC of 5405 mg/m3, based on CNS effects (i.e., decreased
avoidance behavior) in the mid- and high-concentration exposure groups.
In a developmental toxicity study, (Giavini et ai. 1985) administered 1,4-dioxane (99% pure) by
oral gavage to pregnant Sprague Dawley rats (18-20 per dose group) at dose levels of 0, 250,
500, or 1,000 mg/kg/d on gestation days 6-15. In the high-dose group, dams' food consumption
decreased at early timepoints and increased at later timepoints while maternal weight gain
slightly decreased. Fetal birth weight and ossification of the sternebrae significantly decreased at
the highest dose. There was a of doubling in the rate of hemisternibrae in the 500 mg/kg/d dose
group relative to the lower dose group, though this effect was not statistically significant. The
authors identified a NOAEL of 500 mg/kg/d and a LOAEL of 1,000 mg/kg/d based on the
reduced fetal weights and delayed ossification.
Of the available acute and short-term studies, EPA concluded that the studies performed in
experimental animals represented the highest quality data from which to assess potential risks to
workers. EPA considered the human exposure studies as supporting information, given the
general consistency of effects seen in humans and experimental animals. However, there were
limitations with the human studies that precluded their use for quantitative risk assessment,
including for example, the absence of measures of systemic effects (e.g., serum chemistry
panels). Therefore, EPA selected the studies listed in Table 4-1 with a data quality rating of
medium or high for evidence integration and evaluation, as discussed under Appendix H.l.
Table 4-1. Acceptable Studies Evaluated for Toxicity of 1,4-Dioxane Following Acute or
Short-term Exposure"
ACUTE
Data Source
Study Description b
Hazards Evaluated; Effects reported;
POD
Data Quality Rating
(Drew et al.
1978)
4-hour inhalation
(whole body) study in
rats; 0, 3603 or 7207
mg/m3
Clinical Chemistry; Increased serum liver
enzymes; LOAEC = 3603 mg/m3
Medium
(Mattie et al.
2012)
6-hour inhalation
(whole body) study in
rats; 0, 429, 1013,
2875, 7920 and
21,630 mg/m3
Body Weight, Irritation, Hepatic, Renal,
Respiratory; Vacuolar change in olfactory
and respiratory epithelium (2 rats at two
days but not 2 weeks after exposure);
NOAEC = 2875 mg/m3
Medium
SHORT-TERM
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Data Source
Study Description
Hazards Evaluated; Effects reported;
POD
Data Quality Rating
(Mattie et al..
2012)
10-day inhalation
(whole body) study in
rats; 6 hours/day, 5
days/week for two
weeks; 0, 378, 5599
and 11,690 mg/m3
Irritation, Hepatic, Renal, Respiratory;
Lesions in nasal cavity, liver, and kidney;
hepatic single cell necrosis; LOAEC = 378
mg/m3
Medium
(Goldbere et al..
1964)
10-day inhalation
(whole body) study in
rats; 4 hours/day, 5
days/week for two
weeks; 0, 5405,
10,810 or 21,620
mg/m3
Body Weight, Neurological/ Behavior;
Decreased avoidance response; NOAEC =
5405 mg/m3
Medium
DEVELOPMENTAL
Data Source
Study Description
Hazards Evaluated; Effects reported;
POD
Data Quality Rating
(Giavini et al..
1985)
Oral (gavage)
developmental study
in rats (gestation days
6 to 15); 0, 250, 500,
or 1000 mg/kg-d
Prenatal Development; Delayed
ossification of the sternebrae and reduced
fetal body weight; NOAEL = 500 mg/kg-d
High
a For further details, see the data extraction summary table in Appendix G. 1.
b Concentrations in ppm were converted to mg/m3 using the following equation: ppm*mw (88. l)/24.45. 24.45 is
the gas constant at 760 mm Hg (101 kPa) atmospheric pressure and at 25 °C.
Subchronic and Chronic Non-Cancer Hazards- Inhalation
EPA evaluated studies describing the subchronic and chronic inhalation toxicity of 1,4-dioxane
in animal studies. The results of the data evaluation are given in Table 4-2 and in the data
extraction summary table in Appendix G. 1.
Table 4-2. Acceptable Studies Evaluated for Non-Cancer Subchronic or Chronic Toxicity
of 1,4-Dioxane Following Inhalation Exposure
Data Source
Study Description
Hazard Evaluated
Data
Quality
Rating
(Kasai et al..
2008)
13-week inhalation
study in rats
Mortality, Systemic Hepatic, Renal,
Respiratory, Hematology, Clinical Chemistry
High
(Kasai et al..
2009)
2-year chronic
toxicity/cancer
inhalation bioassay in
rats
Mortality, Systemic, Hepatic, Renal,
Respiratory, Hematological and Immune,
Clinical Chemistry/Biochemistry, Nutrition and
Metabolic, Reproductive, Cancer
High
In Kasai et al. (2008). 6-week-old F344/DuCij rats (10/sex/group) were exposed to vaporized
1,4-dioxane (>99% pure) at concentrations of 0, 100, 200, 400, 800, 1600, 3200, or 6400 ppm (0,
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360, 721, 1441, 2883, 5765, 11,530 or 23,060 mg/m3, respectively)8 for 6 hours/day, 5
days/week, for 13 weeks in whole body inhalation chambers. All rats in the 6400 ppm (23,060
mg/m3) group died by the end of the first week of exposure; at lower doses, mortality rates were
not affected. The study authors determined the most sensitive endpoint to be nuclear enlargement
in the respiratory epithelium, which was noted in both sexes, and identified a LOAEC of 100
ppm (360 mg/m3). As noted in the 2013 IRIS assessment of 1,4-dioxane, EPA considers this
effect of equivocal toxicological significance, as it is found in any cell responding to stress (i.e.,
adaptive response), transcribing mRNA (i.e., biomarker of exposure), or undergoing proliferation
(i.e., normal cell cycle) (U.S. EPA. 2013c). While the proliferation may be in response to a
carcinogenic agent, the impact on the progression from initiated cell to tumor remains unclear.
Therefore, EPA considers the NOAEC for this study to be 100 ppm (360 mg/m3) based on
statistically significantly increased relative lung weights (7-13%) in females at 200 ppm (721
mg/m3) and higher (p < 0.01 or 0.05). Dose-related increases in vacuolization of the olfactory
epithelium was observed at the same concentrations with statistically significant increased
observed at 800 ppm (2883 mg/m3) and higher (p < 0.01). Atrophy of the olfactory epithelium
was also seen, although the dose-response was less clear.
In a 2-year chronic study (Kasai et al. 2009). male 6-week-old F344/DuCrj rats were exposed to
vaporized 1,4-dioxane (>99% pure) at concentrations of 0, 50, 250, or 1250 ppm (0, 180, 900, or
4500 mg/m3, respectively) for 6 hours/day, 5 days/week, for 104 weeks in whole body inhalation
chambers. Increased mortality was seen in the 1250 ppm (4504 mg/m3) group. Noncancer effects
were seen in the nasal cavity, liver, and kidneys. Based on general chronic nasal toxicity, which
includes nuclear enlargement, atrophy, and respiratory metaplasia, the study authors identified
the LOAEC to be 50 ppm (180 mg/m3). The study authors did not identify a NOAEC. As
described above, the EPA does not consider nuclear enlargement alone to be an adverse effect.
EPA considers the nasal endpoints described in this study to be adverse because they are
consistent with the portal of entry and health endpoints that are most relevant to inhalation
exposure in an occupational setting. Thus, EPA concluded that the LOAEC for this study is 50
ppm (180 mg/m3) based on respiratory metaplasia and atrophy of the olfactory epithelium, which
were both statistically significantly increased from controls (p < 0.01).
In experimental animal studies, subchronic or chronic inhalation exposure to 1,4-dioxane was
associated with effects on the liver (histopathologic changes, including preneoplastic changes,
increased weight, and altered liver enzyme), kidney (including histopathologic lesions, changes
in kidney weight, serum chemistry, and urinalysis indices), and nasal/respiratory epithelium
(Kasai et al.. 2009). Other effects associated with subchronic or chronic exposure to inhaled 1,4-
dioxane included changes in body weight and relative lung weight (Kasai et al.. 2008). The most
sensitive endpoints—respiratory metaplasia and atrophy of the olfactory epithelium—occurred at
50 ppm (180 mg/m3) after chronic (2-year) exposure in rats(Kasai et al.. 2009). Liver and kidney
effects were generally observed at concentrations higher than those associated with
nasal/respiratory effects (Kasai et al.. 2.009).
8 Concentrations in ppm were converted to mg/m3 using the following equation: ppm*mw (88. l)/24.45. 24.45 is the
gas constant at 760 mm Hg (101 kPa) atmospheric pressure and at 25 °C.
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Subchronic and Chronic Non-Cancer Hazards - Dermal
No repeated-dose dermal toxicity studies were identified on 1,4-dioxane. However, the available
data suggest that delivery of 1,4-dioxane via the inhalation- (i.e., pulmonary/systemic
circulation) and oral- {i.e., portal circulation) routes of exposure results in comparable toxic
endpoints. Since dermally absorbed compounds enter the systemic circulation, route-to-route
extrapolations would generally be performed using the repeated-dose inhalation toxicity data.
However, the inhalation studies were performed by whole body exposure, rather than nose only
exposure, which may have led to additional dosing by the oral and dermal routes of exposure,
due to deposition on fur and the grooming behavior of rodents. Therefore, EPA considered the
oral studies more relevant in terms of actual dose received. The route-to-route extrapolations
enabled EPA to estimate applied dermal PODs. It should be noted that EPA was unable to
conclude with certainty that comparable toxic endpoints would be associated with the dermal
route of exposure, considering the expected quantitative ADME differences and the absence of
an adequate PBPK model. Notwithstanding these uncertainties, EPA considered this approach
appropriate considering the comparable toxic endpoints identified in the available repeated-dose
oral/inhalation toxicity studies and the uncertainty with the putative toxicant {i.e., 1,4-dioxane or
a metabolite(s)).
Subchronic and Chronic Non-Cancer Hazards - Oral
The toxicity of 1,4-dioxane following oral exposure was evaluated in several subchronic or
chronic drinking water studies(2009; Kano et at.. 2008; JBRC. 1998; NCI. 1978; Kociba et at..
1974; Argus et at.. 1965). These studies and results of the data quality evaluation are presented in
Table 4-3 and in Appendix G.l.
Table 4-3. Acceptable Subchronic and Chronic Studies Evaluated for Non-Cancer Toxicity
of 1,4-Dioxane Fol
owing Oral Exposure
l);il;i Source
Sintl> Description
llii/iii'd l.\;ilu;Kcd
Diilii
(,)u;ili(>
Killing
(Kociba et aL 19741
2-year drinking water study in rats
Mortality, Body Weight, Hepatic,
Renal, Cancer
High
(NCI. 1978)
110-week (rats) or 90-week
(mouse) chronic toxicity/ cancer
bioassay
Mortality, Gastrointestinal, Hepatic,
Renal, Respiratory, Cancer
Low
(Kano et al.. 2009);
also reported as
(JBRC, 1998)
2-year chronic toxicity/ cancer
bioassay in rats and mice
Body Weight, Hepatic, Renal,
Hematological, Respiratory, Cancer
High
(Argus et al. 1965)
64.5-week cancer bioassay in rats
Hepatic, Renal, Hematological,
Respiratory, Cancer
Medium
(Argus et al. 1973)
13 month drinking water study in
rats
Hepatic, Renal, Respiratory, Cancer
Low
(Kano et al. 2008)
13-week drinking water study in
rats
Body Weight, Hepatic, Renal,
Respiratory, Nervous System,
Hematological
Medium
(Dow Chemical.
1989b)
11-week repeat dose oral in vivo
DNA repair in rats
Body Weight, Hepatic, Genotoxicity
Medium
1 Male rat data were evaluated as unacceptable.
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1,4-Dioxane (purity not reported) was administered to 6-8-week-old Sherman rats (60/sex/dose)
for up to 716 days via drinking water at concentrations of 0, 0.01, 0.1, or 1% (Koctba et al.
1974). The authors calculated the mean daily doses for males and females to be 0, 9.6, 94, or
1015 mg/kg-d and 0, 19, 148, or 1599 mg/kg-d, respectively. Mortality was increased in the
high-dose groups. Noncancer effects occurred in the liver and kidneys. The most sensitive
endpoints, regeneration of the liver (as indicated by hepatocellular hyperplastic nodule
formation) and kidney (specifically, the renal tubular epithelium), were reported in male rats.
The authors identified a LOAEL of 94 mg/kg-d and a NOAEL of 9.6 mg/kg-d.
Male and female rats (35/sex/dose) and mice (50/sex/dose) were administered 1,4-dioxane
(>99.95% pure) for 110 or 90 weeks, respectively, via drinking water at concentrations of 0, 0.5,
or 1% (NCI. 1978). Investigators calculated the average daily intakes of 1,4-dioxane to be as
follows: male rats received 0, 240, or 530 mg/kg-d; female rats received 0, 350, or 640 mg/kg-d;
male mice received 0, 720, or 830 mg/kg-d (decreased dose spacing due to decreased water
consumption in high-dose mice); and female mice received 0, 360, or 860 mg/kg-d. Mortality
was increased among treated rats. Noncancer effects were observed in the stomach (males only),
liver (females only), and kidneys (both sexes). Based on gastric ulcers and renal cortical tubular
degeneration in male rats, the authors determined the LOAEL in this study is 240 mg/kg-d; a
NOAEL was not established (NCI. 1978). Increased mortality also occurred in mice. Noncancer
effects on the respiratory system (pneumonia and rhinitis) were noted in both sexes, resulting in a
LOAEL of 380 mg/kg-d. A NOAEL was not established in this study (NC |).
Results from a two-year drinking water study conducted on F344/DuCrj rats and Crj :BDF1 mice
(50/sex/dose) by the Japan Bioassay Research Center ( |) have also been published as
Yamazaki et al. (1994) and Kano et al. (2009). 1,4-Dioxane (>99% pure) was administered at
concentrations of 0, 200, 1000, or 5000 ppm; these concentrations were reported by Kano et al.
(2009) to be the following approximate doses: male rats received 0, 1 1, 55, or 274 mg/kg-d;
female rats received 0, 18, 83, or 429 mg/kg-d; male mice received 0, 49, 191, or 677 mg/kg-d;
and female mice received 0, 66, 278, or 964 mg/kg-d.
Slower growth rates and decreased terminal body weight were noted in high-dose rats of both
sexes, as were changes in hematology and clinical chemistry and increased relative liver weight.
Noncancer effects were observed in the nasal cavity, liver, and kidneys. Based on the nasal
cavity effects (olfactory epithelium atrophy, adhesion, and inflammation) in males, the LOAEL
in this study is 274 mg/kg-d; the NOAEL is 55 mg/kg-d (Kano et al.. 2009).
In mice, mortality was increased in females at the highest dose. Growth rates, terminal body
weights, and water consumption were decreased in both sexes. Changes in hematology and
clinical chemistry occurred in both sexes, as did increased lung weights. Respiratory, kidney, and
liver effects also were observed. The LOAEL in this study is 278 mg/kg-d, based on nasal
inflammation in females; the NOAEL is 66 mg/kg-d (Kano et al.. 2.009).
Argus et al. (1965) administered 1,4-dioxane (purity not reported) to 26 adult male Wistar rats
for 64.5 weeks via drinking water at a concentration of 1%, which was calculated to be
equivalent to 640 mg/kg-d. Noncancer effects were noted in the liver, kidney, and lungs. The
LOAEL is 640 mg/kg-d based on glomerulonephritis and histological changes (enlarged
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hyperchromic nuclei and large cells with reduced cytoplasmic basophilia) observed in the liver
the only dose tested.
A follow-up study (Argus et at.. 1973) exposed male Sprague Dawley rats (28-32/group) to 1,4-
dioxane (purity not reported) for up to 13 months via drinking water at concentrations of 0, 0.75,
1, 1.4, or 1.8%, which are calculated to be equivalent to 0, 430, 574, 803, or 1032 mg/kg-d.
Noncancer effects on the liver, kidney and lung were observed. The LOAEL is 430 mg/kg-d,
based on histopathological lesions in the liver and kidney at the lowest dose tested. A NOAEL
was not identified in this study.
Kano et al. (2008) administered 1,4-dioxane (>99% pure) to 6-week-old F344/DuCrj rats and
Crj:BDFl mice (10/sex/group) for 13 weeks via drinking water at concentrations of 0, 640, 1600,
4000, 10000, or 25000 ppm. The investigators calculated the approximate daily intake of 1,4-
dioxane to be as follows: male rats received doses of 0, 52, 126, 274, 657, or 1554 mg/kg-d;
female rats received 0, 83, 185, 427, 756, or 1614 mg/kg-d; male mice received 0, 86, 231, 585,
882, or 1570 mg/kg-day, and female mice received 0, 170, 387, 898, 1620, or 2669 mg/kg-day.
Significant decreases in food and water consumption were noted among high-dose rats of both
sexes, with final body weights reduced in the two highest dose levels. Respiratory, olfactory,
brain, liver, and kidney effects were noted in rats, with nuclear enlargement of the respiratory
epithelium of the nasal cavity and hepatocyte swelling occurring at the lowest doses in male rats.
As with the inhalation studies, the EPA does not consider nuclear enlargement to be an adverse
effect, thus, based on liver histopathology findings, the LOAEL is 126 mg/kg-day and the
NOAEL is 52 mg/kg-day.
Decreased body weights and water consumption were also noted in mice. Several clinical
chemistry parameters were changed and respiratory, olfactory, lung, and liver effects were seen.
The most sensitive effects in mice, nuclear enlargement and degeneration of bronchial
epithelium, occurred in females at 387 mg/kg-day, making the NOAEL 170 mg/kg-day (Kano et
al. 2008).
Male SD rats (4-6/group) were administered 1,4-dioxane (>99% pure) in drinking water at doses
of 0, 10, or 1000 mg/kg-d for 11 weeks, 7 days/week (Dow Chemical. 1989b). Positive {i.e.,
dimethylnitrosamine) and vehicle controls were run concurrently. Repeated dosing at 1000
mg/kg-day 1,4-dioxane resulted in increased liver to body weight ratio and increased (1.5 fold)
hepatic DNA synthesis with minimal hepatocellular swelling.
The EPA review of non-cancer oral hazards indicate that the key endpoints for 1,4-dioxane occur
in the nasal cavity, lungs, liver, kidneys, and brain. The most sensitive effects were in the liver
(degeneration and necrosis of hepatocytes) and kidneys (degeneration and necrosis of renal
tubular cells) and occurred at 94 mg/kg-d; the NOAEL for liver and kidney effects is 9.6 mg/kg-
d (Kociba et al. 1974).
4.2.3.2 Genetic Toxicity and Cancer Hazards
Genetic Toxicity
The genotoxicity of 1,4-dioxane has been tested in over 40 in vitro and in vivo studies. Briefly,
1,4-dioxane has been tested for genotoxic potential using various in vitro systems including
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prokaryotic organisms (S. typhimariam strains and E. coli strains), non-mammalian eukaryotic
organisms, and mammalian cells, and in vivo systems using several strains of mice and rats. EPA
previously evaluated these data in the IRIS assessment of 1,4-dioxane and concluded that 1,4-
dioxane is either nongenotoxic or weakly genotoxic based on a weight-of-the-evidence analysis
of the in vitro and in vivo genotoxicity studies (U.S. EPA. 2013c). EPA also concluded that 1,4-
dioxane was not genotoxic in the majority of the available in vivo mammalian assays, although
several studies have shown positive effects at or above doses of 1000 mg/kg/d.
In this document, EPA conducted study evaluations using systematic review tools on select
studies either as part of other endpoints, or independently for genotoxicity endpoints. EPA
evaluated studies that were published after 2013 and had a confidence level of either high or
medium quality. As shown in Table 4-4, two key publications were identified that met these
criteria including two in vivo micronucleus assays that assessed the genotoxic potential of 1,4-
dioxane in bone marrow and in liver (Itoh. 2019) and two in vivo mutagenicity assays (Itoh.
2019; Gi et al.. 2018). Each of these studies is summarized below, followed by EPA's
interpretation of how these studies add to the weight-of-the-scientific evidence evaluation from
the IRIS assessment on the potential for 1,4-dioxane to cause genotoxicity and/or mutagenicity.
Table 4-4. Acceptab
e New Studies Evaluated for Genetic Toxicity of 1,4-Dioxane
Data Source
Study Description
Hazards Evaluated
Data Quality
Rating
Itoh and Hattori (2019)
In vivo micronuclei in
rat bone marrow and
liver
Micronuclei cell damage
High
In vivo mutagenicity in
rats
Gene mutation with Pig-a assay
Gi et al. (2018)
In vivo mutagenicity in
transgenic rats
Gene mutation
GST-P-positive foci induction and cell
proliferation
High
Itoh and Hattori (2019) investigated the ability of 1,4-dioxane (purity not stated) to induce
micronuclei in the bone marrow of male F344 rats administered 1,4-dioxane by gavage (water
vehicle; 10 mL/kg) at dose levels of 1000, 2000, or 3000 mg/kg. Cyclophosphamide served as
the positive control. At 24 or 48 hours post dosing, bone marrow was harvested and the
incidence of micronucleated immature erythrocytes (MNIE) was counted in a total of 2000
immature erythrocytes (IE) from each animal. At 24 hours, a statistically significant increase in
the incidence of MNIE was observed in the 2000 mg/kg dose group. The authors concluded that
this change was not toxicologically relevant because the value was within the laboratory's
historical control range and no dose-dependency was observed. At 48 hours, a statistically
significant decrease in the percentage of IE was observed in the 3000 mg/kg dose group. The
positive control showed the expected statistically significant increase in MNIE at 24 hours.
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Based on these results, the authors concluded that 1,4-dioxane was not genotoxic in the bone
marrow of rats.
The above findings are consistent with some of the mixed results from the bone marrow
micronucleus studies summarized in the IRIS assessment. For example, Tinwell and Ashby
(1994) performed mouse bone marrow micronucleus assays using male CBA mice and male
C57BL6 mice. No increases in micronuclei were detected in male CBA mice dosed by oral
gavage with 1800 mg/kg, whereas a non-statistically significant increase in micronuclei {i.e., 1.6-
fold) was reported in male C57BL6 mice dosed by oral gavage with 3600 mg/kg. The authors
concluded that 1,4-dioxane was not clastogenic under their test conditions. Comparable negative
findings were reported by Mirkova (1994). The author reported no increases in bone marrow
micronuclei in male BALB/c mice dosed by oral gavage with 5,000 mg/kg. In contrast, Mirkova
(1994) reported a dose-dependent and statistically significant increase in the incidence of bone
marrow micronuclei in male and female C57BL6 mice dosed by oral gavage with 900, 1800, or
3600 mg/kg. No micronuclei were detected in bone marrow of animals receiving a dose of 450
mg/kg. Additionally, Roy et al. (2005) reported dose-dependent and statistically significant
increases in bone marrow micronuclei in male CD-I mice administered 1,4-dioxane for five days
at dose levels of 1500, 2500, or 3500 mg/kg-d. Based on the results of Itoh and Hattori (2019)
and the results of other investigations, noted above and summarized in the IRIS assessment, EPA
concluded that the available bone marrow micronucleus assays support that 1,4-dioxane is
genotoxic in vivo at high doses, and the discrepant findings may be due to methodological
differences in the studies and/or differences in the sensitivity between rats and mice.
In separate studies, Itoh and Hattori ( ) performed liver micronucleus assays to explore the
potential mode of action by which 1,4-dioxane induced liver adenomas and carcinomas in
chronically exposed rodents. The authors used three different study designs, including the
juvenile rat (JR) method, the dosing before partial hepatectomy (pre-PH) method, and the dosing
after PH (post-PH) method. In each of these studies, animals were administered either one or two
doses of 1,4-dioxane by gavage (water vehicle; 10 mL/kg) at dose levels of 1000, 2000, or 3000
mg/kg. Diethylnitrosamine served as the positive control for clastogenicity in the JR and pre-PH
studies, whereas carbendazim served as the positive control for aneugenicity in the post-PH
study. In the JR study, animals were dosed on days 1 and 2, and livers were harvested on day 6.
In the pre-PH study, animals were dosed on day 1, PH was performed on day 2, and livers were
harvested on day 6. In the post-PH study, PH was performed on day -1, animals were dosed on
day 1, and livers were harvested on day 4. For each of the studies, the authors evaluated liver-to-
body weight ratios {i.e., relative liver weight), micronucleated hepatocytes (MNH) among 2000
hepatocytes (excluding metaphase and nuclear fragment cells), and classified hepatocytes as
mononucleated, binucleated, or multinucleated {i.e., 3 or more nuclei). In the JR study, dose-
dependent and statistically significant increases in MNH were observed in all treated animals. No
changes were reported in relative liver weight or hepatocyte classifications. In the pre- and post-
PH studies, dose-dependent, statistically significant increases in MNH were observed in all
treated animals. In the pre-PH study, no changes in relative liver weights were reported, although
binucleated hepatocytes were increased, albeit not statistically, in the high dose group. In the
post-PH study, statistically significant increases in relative liver weights were reported in the
low- and mid-dose groups; however, no changes in hepatocyte classification were observed.
Based on these results, the authors concluded that 1,4-dioxane is clastogenic in the liver.
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The MNH findings reported by Itoh and Hattori (2019) are consistent with the MNH evaluations
summarized in the IRIS assessment. For example, Morita and Hayashi (1998) reported dose-
dependent and statistically significant increases in pre-PH male CD-I mice administered 1,4-
dioxane by gavage at dose levels of 2000 and 3000 mg/kg. However, unlike Itoh and Hattori
(2.019). Morita and Hayashi (1998) did not identify MNH in mice that received a dose of 1000
mg/kg. Additionally, Roy et al. (2005) reported dose-dependent and statistically significant
increases in MNH in male CD-I mice administered 1,4-dioxane for five days at dose levels of
2500 or 3500 mg/kg-d. The authors did not identify MNH in mice administered 1500 mg/kg-d.
Therefore, EPA concluded that the findings reported by Itoh and Hattori (2019) indicate that 1,4-
dioxane is genotoxic in vivo in high dose experiments.
Itoh and Hattori (2019) also evaluated the potential of 1,4-dioxane (purity not stated) to induce
gene mutations in the in vivo Pig-a assay. Male F344 rats were dosed by gavage (saline vehicle;
10 mL/kg-bw) on day 1 with 1000, 2000, or 3000 mg/kg. Prior to dosing (i.e., day -1), peripheral
blood was sampled, as pre-treatment control values. Animals were then dosed on day 1 and
peripheral blood was sampled on post-treatment days 15 and 20. 7,12-
Dimethylbenz[a]anthracene (DMBA) served as the positive control. Erythrocytes were screened
by flow cytometry analysis for CD59 negative cells, a marker of mutation in the Pig-a gene. No
statistically significant differences were found at any dose level of 1,4-dioxane or sampling time
compared to controls. DMBA-treated animals exhibited the expected statistically significant
increase in CD59 negative cells on post-treatment days 15 and 20.
In a separate in vivo gene mutation assay, Gi et al. (2018) administered various doses of 1,4-
dioxane (purity > 99.9%) to gpt delta transgenic F344 rats in drinking water for 16 weeks. The
daily intake values were 0, 18.7, 92.3, and 440.2 mg/kg-d in one experiment, and 0, 0.02, 0.2, 1.9
mg/kg-d in a second experiment. A positive control was not included in these experiments. Body
weights and liver-to-body weight ratios were statistically significantly decreased or increased,
respectively, in animals from the high-dose group (i.e., 440.2 mg/kg-d) compared to controls.
The gpt mutation frequency in packaged phages from hepatic DNA and GST-P-positive foci per
unit area of liver were increased in a dose-dependent manner and achieved statistical significance
in the high-dose group compared to controls. The spectra of mutations in the high-dose group
included statistically significant increases in A:T to G:C transitions and A:T to T:A transversions
in the high-dose group. In the mid-dose group (i.e., 92.3 mg/kg-d), the gpt mutation frequency
was not statistically significantly different than the control values, although a statistically
significant increase in A:T- to -T:A transversion frequency was reported. No additional
statistically significant changes in mutation frequency were identified in the low dose group for
transitions (i.e., G:C to A:T), transversions (i.e., A:T to C:G, G:C to C:G), deletions (i.e., single
or > double base pairs), or insertions (i.e., single base pairs). Among several cell proliferation,
cell cycle regulation, and DNA damage repair gene expression changes studied in the livers of
gpt delta transgenic rats, a significant increase in PCNA was observed in the high-dose group.
The authors interpreted these findings as support that 1,4-dioxane is a genotoxic carcinogen that
induces hepatocarcinogenesis through a mutagenic mode of action.
Based on the above studies, the negative results reported by Itoh and Hattori (2019) are
consistent with the negative results from the in vitro gene mutation studies summarized in the
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IRIS assessment. However, it is unclear whether the doses used by Itoh and Hattori (2019). albeit
significantly high (up to 3,000 mg/kg), provided sufficient delivery to the bone marrow to induce
mutations in the Pig-a gene. In contrast, Gi et al. (2018) reported positive in vivo mutagenicity
findings in transgenic rats administered 1,4-dioxane by drinking water at the highest intake dose
of 440 mg/kg/d. Importantly, the treatment duration was extremely long for this type of study,
which may lead to false positive findings in transgenic models (OECD. 2009). For example, the
Organisation for Economic Cooperation and Development (OECD) states the following in its
validated test guideline titled Transgenic Rodent Somatic and Germ Cell Gene Mutation Assays:
"... treatment times longer than 8 weeks should be explained clearly and justified, since longer
treatment times may produce an apparent increase in mutant frequency through clonal
expansion [OECD TG 488], Notwithstanding this limitation, the results reported by Gi et al.
(2018) showed that 1,4-dioxane was not mutagenic in animals in the low dose group. Therefore,
EPA concluded that the weight-of-the-scientific evidence supports that 1,4-dioxane is not
mutagenic but may elicit clastogenicity in vivo at high doses.
Carcinogenicity via Inhalation Exposure
A human study of breast cancer incidence in participants in the California Teacher Study (active
and retired female teachers and administrators) from 1995-2011, (n=l 12,378 women) examined
the association between breast cancer and exposure to ambient air concentrations of 1,4-dioxane
(Garcia et al.. 2015) (Table 4-5). Exposure was determined using the National-Scale Air Toxics
Assessment Modeled air concentrations. No significant association was found between breast
cancer incidence and modeled annual average ambient air concentrations of 1,4-dioxane based
on participant's residential address. Though these data provide some insight on low-level
exposures to 1,4-dioxane, they are not particularly informative with regard to any association
between occupational exposures and the potential for developing breast cancer.
In the key inhalation cancer study for this risk evaluation (Kasai et al.. 2009) groups of male
F344 rats (50/group) were exposed to 0, 50, 250 and 1250 ppm (0, 180, 900 and 4500 mg/m3) of
1,4-dioxane for 6 hours/day, 5 days/week, for 2 years. The incidences of the following tumors
were increased: hepatomas; nasal squamous cell carcinomas; renal cell carcinomas; peritoneal
mesotheliomas; mammary gland fibroadenomas; Zymbal gland adenomas; and subcutis
fibromas.
Table 4-5. Studies Evaluated for Cancer Following Inhalation Exposure to 1,4-Dioxane
Data
Source
Study
Description
Hazards Kvaluated
Data
Quality
K;il in«
(Garcia et
al.. 2015)
Cohort study of
hazardous air
pollutants and
breast cancer risk
in California
teachers
Breast cancer incidence
High
(Kasai et
al. 2.009)
2-year inhalation
bioassay- male
rats
Cancer- liver; nasal; renal; peritoneal;
mammary gland; Zymbal gland; and skin
High
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Carcinogenicity via Dermal Exposure
No dermal carcinogenicity studies were identified for 1,4-dioxane. Therefore, and as stated
above under Section 4.2.3.1, EPA applied a route-to-route extrapolation from the oral
carcinogenicity studies to derive dermal PODs.
Carcinogenicity via Oral Exposure
EPA evaluated the available carcinogenicity studies on 1,4-dioxane by the oral route of
exposure, including Kociba et al. (1974). JBRC (1998 )/Kano (2009). and NCI (1978). These
studies (Table 4-6) provide data regarding the carcinogenic effects of 1,4-dioxane by the oral
route of exposure and are summarized in Section 4.2.3.1. EPA used these studies for deriving
dermal PODs, after applying an absorption adjustment to account for route-to-route
extrapolations, as discussed under Section 4.2.6.
Table 4-6. Studies Evaluated for Cancer Following Oral and Inhalation Exposure to 1,4-
Dioxane
Source
Sliiilv Description
1 lii/iircls
Diitii Qiiiililv
killing
(Kociba et al.. 1974)
2-year drinking water
study- Sherman rats
(60/sex/group)
Cancer- liver, respiratory
High
(JBRC. 1998). (Kano
et al.. 2009)
2-year drinking water
study- F344/DuCrj rats
and Cij:BDFl mice
(50/sex/group)
Cancer- nasal, liver, peritoneum,
mammary gland, skin
High
(NCI. 1978)
testis/epididymis
Low
(Kasai et al.. 2009)
2-year inhalation
bioassay- male rats
Cancer- liver; nasal; renal;
peritoneal; mammary gland;
Zymbal gland; and skin
High
Kociba et al. (1974) administered 1,4-dioxane to 6-8-week old Sherman rats (60/sex/group) via
drinking water for two years. The incidences of hepatocellular carcinomas and squamous cell
carcinoma of the nasal turbinates were increased among the high-dose group (1%; equivalent to
an average dose (male and female) of 1,307 mg/kg/d). No increase in tumor formation was seen
in the mid-dose group. Zero tumors occurred in the low-dose group.
As noted previously, Kano et al. (2.009) is one of several publications based on a 2-year drinking
water study performed by the Japan Bioassay Research Center. Groups of F344/DuCrj rats and
Crj:BDFl mice (50/sex/group) were exposed to 1,4-dioxane (>99% pure) at levels of 0, 200,
1000, or 5000 ppm and 0, 500, 2000, or 8000 ppm, respectively. Increased incidences of
hepatocellular adenomas and carcinomas and tumors (squamous cell carcinomas) of the nasal
cavity occurred in high-dose male and female rats. Peritoneal mesotheliomas in males also were
increased at the highest dose, and males showed increasing trends in mammary gland
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fibroadenoma and subcutis fibroma, a fibroma or mass underneath the cutis layer of the skin.
Females showed an increased incidence of mammary gland adenoma or fibroadenoma.
4.2.4 Potential Modes of Action for 1,4-Dioxane Toxicity
EPA evaluated the mode of actions (MOA) for 1,4-dioxane carcinogenicity using the framework
for MOA analysis described in the EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA.
2005a) in order to inform the quantitative dose-response approach for the identified hazard
endpoints.
The principal tumor target for which the most information exists is for liver tumors. The MOA
for 1,4-dioxane induction of liver tumors was previously considered inconclusive (
2013c).
In this risk evaluation, EPA performed a new MOA analysis based on the genotoxicity data that
was previously reviewed, weighed and integrated in the EPA IRIS Toxicological Review of
1,4-Dioxane ( z), and on new genotoxicity studies and other relevant publications
on the MOA.
The MOA analysis presented here evaluates the strength of evidence for two of the most
developed proposed MO As of liver toxicity and cancer for 1,4-dioxane:
• Mutagenicity. In the absence of other information about MOA, EPA often takes the health
protective approach of assuming a linear no-threshold risk model consistent with a mutagenic
mode of action. As described in Section 4.2.3.2, there is little evidence for mutagenicity, but there
is some evidence that 1,4-dioxane may be genotoxic at high doses.
• Cytotoxicity. In this hypothesized MOA, liver toxicity is related to the accumulation of the
parent compound 1,4-dioxane leading to liver tumors through cytotoxicity and regenerative
proliferation This proposed MOA was informed by kociba et al. (1974). Dourson et al. (2014).
and McConnell (20.1.3). U.S. EPA (2013a) previously concluded that this hypothesis is not
supported because alternative metabolic pathways (e.g., not CYP450s) may be present at high
doses and no new data have been identified.
This analysis also considers whether the effects can be attributed to the parent compound or a
metabolite. No new bioassays were available to inform the MOA for liver carcinogenicity, and
no tumor specific data was available to evaluate the MOA for nasal, kidney, peritoneal,
mammary gland, Zymbal gland, or subcutis tumors. However, some reanalysis of previous
histopathology slides of preexisting bioassays is incorporated into MOA analysis that follows.
The main information considered to evaluate proposed MO As included: 1) genotoxicity results;
2) tumor promotion results; 3) liver histopathology; 4) dose-response for key events in liver
toxicity leading to cancer.
Genotoxicity data
Several studies show that 1,4-dioxane exposure increased DNA synthesis in rat hepatocytes at
dose levels (1,000 mg/kg/d) higher than doses that promoted liver tumors (Miyaeawa et al..
1999: Lino et al. t, oldsworthy et al.. 1991; Stott et al.. 1981) (Summary of Genotoxicity
Studies in Appendix H.1.5) and this result has been interpreted as increased cell proliferation.
However, it is unknown whether the increased rates of DNA synthesis observed in response to
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1,4-dioxane exposure represent a true increase in cellular proliferation, or if the increase is a
cellular response to DNA damage and the repair of hepatic lesions. In in vitro screening assays
(ToxCast), 1,4-dioxane was observed to increase the transcriptional activity of the p53 tumor
suppressor protein in human colon cancer cells (HCT116) 24 hours after 1,4-dioxane exposure,
indicative of an active DNA damage and repair response (https://comptox.epa.gov/dashboard
accessed 03/27/2019). These studies do not rule out MO As for either mutagenicity or
cytotoxicity and regenerative proliferation.
Tumor promotion data
Tumor promotion studies indicated 1,4-dioxane may promote the growth of previously initiated
cells (Lundberg et at.. 1987; King et at.. 1973). Tumor promoter activity of a chemical does not
preclude activity as a tumor initiator. Dose-response and temporal data support the occurrence of
cell proliferation and hyperplasia prior to the development of liver tumors (JBRC. 1998) in the
rat model. Conflicting data from rat and mouse bioassays ( 8; Kociba et at.. 1974)
suggest that cytotoxicity may not be a required precursor event for 1,4-dioxane-induced cell
proliferation. Liver tumors were observed in female rats and female mice in the absence of
lesions which argues against cytotoxicity by itself as a mode of action, (see Section 4.2.5) (Kama
et at.. 2.009; JBRC. 1998; NCI. 1978). However, available data do not rule out some role for
either genotoxicity or cytotoxicity (or both) in a possible mode of action.
Liver histopathology data
Liver tumors in some rodent bioassays occurred in the absence of reported lesions (Kano et at..
2008; JBRC. 1998; NCI. 1978). The liver histopathology data from translated Japanese study
reports (Kano et at.. 2008) were integrated with the re-evaluated mouse liver data to refine the
MOA hypothesis based on cytotoxicity (Dourson et at.. 2017). Based on toxicokinetic studies
demonstrating metabolic saturation and no increase in toxicity following induction of CYP450
metabolism, this paper concluded that the toxic moiety was the parent compound. However, 1,4-
dioxane is metabolized by CYP450s (Nannelli et at.. 2005; Woo et at. 1977) into beta-
hydroxyethoxyacetic acid (HEAA) that is then excreted through urine, alternative metabolic
pathways (e.g., not CYP450) may be present. Therefore, liver toxicity due to metabolites cannot
be ruled out. Further, there are no in vivo or in vitro assays that have identified the toxic moieties
resulting from 1,4-dioxane exposure.
Dose-response data
Liver tumors identified from rodent liver bioassays occurred in the absence of reported lesions
related to cytotoxicity (Kano et at.. 2008; JBRC. 1998; NCI. 1978). suggesting that cytotoxicity
may not be a key event after 1,4-dioxane exposure leading to liver carcinogenesis. Some data
support the occurrence of cell proliferation prior to liver tumor formation in rat models (JBRC.
1998; Kociba et at.. 1974). but the dose-response relationship for induction of cell proliferation
has not been characterized or the relationship between cell proliferation and liver tumors is
unknown. The doses of 1,4-dioxane at which cytotoxicity and cell proliferation were observed
were greater than the doses for tumor induction (U.S. EPA. 2013a). Also, Kociba et al. (1974)
reported hepatic degeneration and regenerative hyperplasia at or below dose levels that produced
liver tumors, but they did not report the incidence for these effects. Dose response data from the
two year inhalation and drinking water studies illustrate the relative potency of 1,4-dioxane for
cancerous lesions and non-cancerous lesions in the liver and other tissues (Table 4-7). Lesions
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that may be consistent with cytotoxicity, apoptosis and/or regenerative proliferation include
necrosis, atrophy, inflammation, hyperplasia, proliferation, nuclear enlargement, and cell foci.
Male mice at the mid and high dose levels in the two-year study had statistically elevated
incidence of both hepatocellular adenomas and carcinomas, combined (191 and 677 mg/kg-d)
and incidence of tumors also appeared to be elevated at 49 mg/kg-d. In females combined
adenoma and carcinoma tumor incidence was significantly elevated in all three tested doses (66,
278, and 964 mg/kg-d).
In male mice in the 12-week drinking water study hepatocellular swelling and single cell
necrosis were elevated at doses 585 mg/kg-d and higher, but not seen at 231 mg/kg-d or below.
Findings in females were similar with doses of 898 mg/kg-d showing hepatocellular swelling and
single cell necrosis, but doses of 387 mg/kg-d and lower not showing those effects. Except at the
highest doses, these findings were scored as "slight" in severity. Vacuolic cell change or other
degenerative histopathological effects were not reported in the subchronic mouse study. Elevated
plasma levels of AST and ALT were seen in both sexes at the highest doses with female mice
also showing a 2-fold increase in ALT at the intermediate 1,620 mg/kg-d dose. Thus,
hepatocellular tumors were seen in multiple male or female experimental groups at doses without
evidence of the reported toxic effects in the subchronic study.
Neither cellular swelling, necrosis, nor other hepatocellular pathological changes were reported
in the 2-year mouse bioassay (M or F). In males AST and ALT were slightly elevated at the
intermediate dose level and clearly elevated at the high dose group. In females these enzymes
were also elevated both intermediate and high dose levels. These observations may have been
influenced by the high incidence of hepatocellular tumors in these groups. However, these
enzyme levels were not elevated in the low dose chronic bioassay groups where there was still an
increase in hepatocellular tumors (statistically significant in females). Altered hepatic foci were
not reported in the mouse chronic study. Dose-response characteristics from this study that limit
support for a non-mutagenic MOA based on cytotoxicity include:
• Datasets were combined but not tested for compatibility;
• Control incidence and dose response relationship varied by foci type and sex and
therefore, should not be combined for dose response assessment;
• There was an absence of a dose response relationship for foci;
• The incidence of hepatocyte swelling and single cell necrosis increased at the same dose
that induced hyperplasia and increased the incidence above controls;
• Hypertrophy, foci, and adenoma formation all occur at the same dose;
• The mouse histopathology data are inconsistent among bioassays and across exposure
duration.
A re-evaluation of mouse pathology data from the NCI, 1978 study (McConnell. 2.013)
established the presence of non-neoplastic lesions in mice exposed chronically to 1,4-dioxane in
drinking water. However, the following study limitations limit confidence in the dose response
relationship between these effects and tumor formation:
• Dose spacing in males was not adequate for characterizing a dose-response relationship
likely due to decreased drinking water consumption in the high-dose male group leading
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to a high dose only slightly greater than the low-dose group (830 and 720 mg/kg/d,
respectively).
• A dose-response relationship was not apparent for hyperplastic foci in the liver of male
and female mice. The combined incidence for total foci in males was higher for the low
dose group than the high dose group, and in females the incidence for combined total foci
were approximately the same.
• Female mouse data are confounded by the presence of murine hepatitis infection and
should not be combined with male mice to evaluate dose response patterns.
MOA conclusions
The relationship between cell proliferation, hyperplasia, and 1,4-dioxane mediated tumor
formation has not been established. Though several publications (Dourson et at.. 2017; Dourson
et at.. 2.014; McConnett. 2.013) do provide evidence of cytoplasmic vacuolar degeneration and
hepatocellular necrosis in rat and non-neoplastic lesions, the animal data does not support a dose-
response relationship between cell proliferation, hyperplasia, and liver tumors in rat and mouse
studies. Kociba et al. (1974) reported hepatic degeneration and regenerative hyperplasia at or
below dose levels that produced liver tumors, but incidence for these effects was not reported.
Therefore, a dose-response relationship could not be evaluated, and the events cell proliferation
and hyperplasia are not supported by available data. Finally, the doses in hepatotoxicity studies
where cytotoxicity and cell proliferation were observed were greater than cancer bioassay dose
levels. Integrating data across studies, dose-response relationships between cytotoxicity and
tumor formation are not well established in the rat and mouse data and are inconsistent among
bioassays and across exposure duration.
EPA determined that evidence is not sufficient to support a MOA of cytotoxicity followed by
sustained cell proliferation as a required precursor to tumor formation related to the metabolic
saturation and accumulation of the parent compound, 1,4-dioxane (Dourson et at.. 2017; Kociba
et at.. 1975). In addition, while genotoxicity is evident from high doses with in vitro and in vivo
studies the occurrence at high doses and potential confounding with cytoxocity does not support
a mutagenic mode of action hypothesis at low doses in vivo. Other than liver tumors, no
plausible MOA has been hypothesized for the other tumor types associated with exposure to 1,4-
dioxane. As a result, the proposed dose response approach for liver and other tumors is to show
best fit of threshold and linear models applied to tumor data and linear default extrapolation in
the absence of known MOA. Though the proposed cytotoxicity MOA is further considered
through development of a threshold cancer model in Section 4.2.6 of this document, summary
cancer risk calculations in Section 5.2 are based on a linear no-threshold model.
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Table 4-7A. Incidence of carcinogenic and non-carcinogenic lesions reported at each dose
level in a two year inhalation study in rats
Lesions reported
Kiiscn 2<>()ir|'wn > car inhalation slud\ in mis
(\ 50 animals in each treatment group)
Control
50 ppni
250 ppni
1250 ppni
Liver- Carcinogenic lesions
Hepatocellular adenoma
1
2
3
21*
Hepatocellular carcinoma
0
0
1
2
Liver- Non-carcinogenic or pre-carcinogenic lesions
Nuclear enlargement- centrilobular
0
0
1
30*
Acidophilic cell foci
5
10
12
25*
Basophilic cell foci
17
20
15
44*
Clear cell foci
15
17
20
23
Mixed cell foci
5
3
4
14
Spongiosis hepatis
7
6
13
19*
Necrosis- centrilobular
1
3
6
12*
Nasal cavity- Carcinogenic Lesions
Squamous cell carcinoma
0
0
1
6*
Nasal cavity- Non-carcinogenic or pre-neoplastic lesions
Respiratory epithelium - nuclear enlargement
0
50*
48*
38*
Respiratory epithelium- squamous cell metaplasia
0
0
7*
44*
Respiratory epithelium- squamous cell hyperplasia
0
0
1
10*
Respiratory epithelium- inflammation
13
9
7
39*
Olfactory epithelium- nuclear enlargement
0
48*
48*
45*
Olfactory epithelium- atrophy
0
40*
47*
48*
Olfactory epithelium- respiratory metaplasia
11
34*
49*
48*
Olfactory epithelium- inflammation
0
2
32*
34*
Hydropic change- lamina propria
0
2
36*
49*
Sclerosis- lamina propria
0
0
22*
40*
Proliferation- nasal gland
0
1
0
6*
Kidney- carcinogenic lesions
Renal cell carcinoma
0
0
0
4
Kidney- Non-carcinogenic or pre-neoplastic lesions
Nuclear enlargement- proximal tubule
0
1
20*
47*
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Lesions reported
Kiiscn 2oowT\\n > ear inhalation slud\ in mis
(\ 5<> animals in each irealmenl *jroup)
Control
50 ppni
250 ppni
1250 ppni
Hydropic change- proximal tubule
0
0
5
6*
Other tissues- carcinogenic lesions
Peritoneum- mesothelioma
2
4
14*
41*
Mammary gland- fibroadenoma
1
2
3
5
Mammary gland- adenoma
0
0
0
1
Zymbal gland- adenoma
0
0
0
4
Subcutis - fibroma
1
4
9*
5
Table adapted from (Kasai et al. 2.009)
indicates authors reported a statistically significant difference from controls
Table 4-7B. Incidence of carcinogenic and non-carcinogenic lesions reported at each dose
level in a two year drinking water study in rats
Lesions reported - 111:1 lc nils
kano low Two \ ear drinking water slud\ in mis
(\ 50 animals in each irealmenl _»mup)
Control
200 ppm
11 1 mu ku d)
1000 ppni
(55 mu ku di
5000 ppni
i:_4
nm ku ill
Liver- Carcinogenic lesions
Hepatocellular adenoma
3
4
7
32*
Hepatocellular carcinoma
0
0
0
14*
Liver- Non-carcinogenic or pre-carcinogenic lesions
Acidophilic cell foci
12
8
7
5
Basophilic cell foci
7
11
8
16*
Clear cell foci
3
3
9
8
Mixed cell foci
2
8
13*
14*
Nasal cavity- Carcinogenic lesions
Squamous cell carcinoma
0
0
0
3
Esthesioneuroepithelioma
0
0
0
1
Rhabdomyosarcoma
0
0
0
1
Sarcoma NOS
0
0
0
2
Nasal cavity- Non-carcinogenic or pre-neoplastic lesions
Respiratory epithelium - nuclear enlargement
0
0
0
26*
Respiratory epithelium- squamous cell metaplasia
0
0
0
31*
Respiratory epithelium- squamous cell hyperplasia
0
0
0
2
Olfactory epithelium- nuclear enlargement
0
0
5
38*
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Lesions reported - msile nils
kano :oiW i\\(,u';ir drinking \\alerslud\ m rals
(\ 5<> animals in each irealmenl _*jroup)
Control
200 ppm
11 1 iiiu ku di
1000 ppm
(55 nm ku ill
5000 ppm
i:_4
mu ku di
Other tissues- carcinogenic lesions (Non-carcinogenic or pre-carcinogenic lesions not reported)
Peritoneum- mesothelioma
2
2
5
28*
Mammary gland- fibroadenoma
1
1
0
4
Mammary gland- adenoma
0
1
2
2
Subcutis fibroma
5
3
5
12
Lesions reported- I'eniiile r:ils
Kano low Two \ ear drinking walei slud> in rals
(\ 50 animals in each irealmenl group)
Liver- Carcinogenic lesions
Control
200 ppm
i IS mu ku di
1000 ppm
iS' mu ku di
5000 ppm
i42*J
II1U ku ill
Hepatocellular adenoma
3
1
6
48*
Hepatocellular carcinoma
0
0
0
10*
Liver- Non-carcinogenic or pre-carcinogenic lesions
Acidophilic cell foci
1
1
1
1
Basophilic cell foci
23
27
31
8*
Clear cell foci
1
1
5
4
Mixed cell foci
1
1
3
11*
Nasal cavity- Carcinogenic lesions
Squamous cell carcinoma
0
0
0
7*
Esthesioneuroepithelioma
0
0
0
1
Rhabdomyosarcoma
0
0
0
0
Sarcoma NOS
0
0
0
0
Nasal cavity- Non-carcinogenic or pre-neoplastic lesions
Respiratory epithelium - nuclear enlargement
0
0
0
13*
Respiratory epithelium- squamous cell metaplasia
0
0
0
35*
Respiratory epithelium- squamous cell hyperplasia
0
0
0
5
Olfactory epithelium- nuclear enlargement
0
0
28*
39*
Other tissues- carcinogenic lesions (Non-carcinogenic or pre-carcinogenic lesions not reported)
Peritoneum- mesothelioma
1
0
0
0
Mammary gland- fibroadenoma
3
2
1
3
Mammary gland- adenoma
6
7
10
16*
Subcutis - fibroma
0
2
1
0
Table adapted from (Kano et al.. 2009)
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indicates authors reported a statistically significant difference from controls
Table 4-7C. Incidence of carcinogenic and non-carcinogenic lesions reported at each dose
level in a two year drinking water study in mice
Lesions reported - untie mice
kano 20<)irrwo \ car drinking water sIikK in mice
(\ 5<> animals in each treatment group)
Control
200 ppm
<4l> mu ku di
1000 ppm
( M
nm ku di
5000 ppm
((>
mu ku di
Liver- Carcinogenic lesions (Non-carcinogenic or pre-carcinogenic liver lesions not reported)
Hepatocellular adenoma
9
17
23*
11
Hepatocellular carcinoma
15
20
23
36*
Nasal cavity- Carcinogenic lesions
Adenocarcinoma
0
0
0
0
Esthesioneuroepithelioma
0
0
0
1
Nasal cavity- Non-carcinogenic or pre-neoplastic lesions
Respiratory epithelium - nuclear enlargement
0
0
0
31*
O1lacloi'\ epithelium- nuclear enlargement
0
0
9*
40*
Lesions reported - leninle mice
Kano Two \e;tr drinking water slud\ in mice
(\ 50 animals in each treatment group)
Control
200 ppm
<4l> mu ku di
1000 ppm
( M
mu ku d i
5000 ppm
((>
mu ku di
Liver- Carcinogenic lesions (Non-carcinogenic or pre-carcinogenic liver lesions not reported)
Hepatocellular adenoma
5
31*
20*
3
Hepatocellular carcinoma
0
6*
30*
45*
Nasal cavity- Carcinogenic lesions
Adenocarcinoma
0
0
0
1
Esthesioneuroepithelioma
0
0
0
0
Nasal cavity- Non-carcinogenic or pre-neoplastic lesions
Respiratory epithelium - nuclear enlargement
0
0
0
41*
Olfactory epithelium- nuclear enlargement
0
0
41*
33*
Table adapted from (Kano et at... 2009)
indicates authors reported a statistically significant difference from controls
4.2.5 Evidence Integration and Evaluation of Human Health Hazards
The weight-of-the-scientific evidence evaluation provides a narrative concluding with the
recommended approach to dose-response assessment. The information on human health hazard
was integrated using a weight-of-the-scientific evidence strategy where the strengths, limitations
and relevance of the data were analyzed and summarized across studies within each hazard
endpoint in narrative form. The best available human health hazard science was selected for
dose-response modeling based on integrating the results of the data evaluation, MOA
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information and weight-of-the-scientific evidence. Liver, kidney, and nasal toxicity were the
primary noncancer health effects associated with exposure to 1,4-dioxane. The weight-of-the-
scientific evidence is presented for acute toxicity (2 studies), chronic toxicity (7 studies), and
carcinogenicity (4 studies).
Acute and Short-term Toxicity
EPA evaluated studies on the acute and short-term effects from exposures to 1,4-dioxane in
humans and experimental animals. The available human studies indicated that 1,4-dioxane
exposures at 72 mg/m3 for two hours was well tolerated in human volunteers, with no signs or
symptoms of adverse effects, whereas exposures at 180.2 mg/m3 for six hours caused eye
irritation in human volunteers (Emstgard et at.. 2006; Young et at.. 1977). Johnstone (1959)
reported the fatality of one worker after one week of exposures to high concentrations of 1,4-
dioxane (i.e., 1700 mg/m3). An autopsy on the worker showed pathological effects in the liver,
kidney, and brain. Each of these studies provide supporting information for comparable effects
seen in experimental animals; however, they were not carried forward for concentration-response
analyses because of inherent limitations with each. For example, the controlled human exposure
studies were based on single concentration exposures and only assessed visible signs of
impairment and participant reported symptoms. No evaluations were performed for signs of
potential systemic effects (e.g., serum chemistry panels). As shown in Table 4-1, acute and short-
term exposures to 1,4-dioxane in experimental animals have been shown to cause irritation of the
mucous membranes and adverse effects on the liver and kidney (Mattie et at... 2012). Of the
available studies on experimental animals, EPA selected the short-term exposure study
conducted by Mattie et al. (2012) over the short-term study conducted by Goldberg et al. (1964)
for the following reasons. Mattie et al. (2012) exposed male/female rats to 1,4-dioxane at
concentrations of 0, 378, 5599 or 11,690 mg/m3 for 6 hours/day, 5 days/week for two weeks and
assessed effects on the nasal cavity, liver, and kidney. In contrast, Goldberg et al. (1964) exposed
female rats to 1,4-dioxane at concentrations of 0, 5405, 10,810 or 21,620 mg/m3 for 4 hours/day,
5 days/week, for two weeks and only assessed effects on neurological function. EPA concluded
that the exposure duration used by Mattie et al. ( ) was more comparable to short-term
worker exposures (i.e., 8 hours/day, 5 days/week). Further, the range of exposure concentrations
used by Mattie et al. (2012.) encompassed the concentrations used in the acute, single exposure
studies, where liver effects (i.e., 4-hour LOAEC = 3603 mg/m3) or respiratory effects (i.e.,
NOAEC 2875 mg/m3) were reported (Mattie et at. 2012; Drew et at. 1978). In contrast, the
lowest concentration (i.e., 5405 mg/m3) used by Goldberg et al. (1964) exceeded both of these
concentrations, and as noted above, the authors only assessed effects on neurological function.
Therefore, EPA selected the short-term effect levels from Mattie et al. (2012) as the basis for
dose-response assessment and quantification of potential risks to workers from acute/short-term
exposures to 1,4-dioxane, as discussed under Section 4.2.6.
Chronic Toxicity
Key chronic non-cancer effects observed following inhalation and oral exposures to 1,4-dioxane
include centrilobular necrosis in the liver, and degeneration of the kidney and respiratory
epithelium (Kasai et al.. 2009; Kano et al.. 2.008; 2009; NCI. 1978; Kociba et al.. 1974; 1973;
Argus et at. 1965).
Non-cancer liver effects reported in the oral exposure studies included degeneration and
necrosis, hepatocyte swelling, cells with hyperchromic nuclei, spongiosis hepatis, hyperplasia,
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and clear and mixed cell foci of the liver (Kama et at.. 2008; NCI. 1978; Kociba et at... 1974;
-S et al.. 1973; 1965).
Kidney toxicity was noted following inhalation (Kasai et al.. 2009; NCI. 1978; Kociba et al...
1974; 1973; Argus et al.. 1965); and kidney damage at high doses is characterized by
degeneration of the cortical tubule cells, necrosis with hemorrhage, and glomerulonephritis (NCI.
1978; Kociba et al.. 1974; Argus et al.. 1965). The lowest dose reported to produce kidney
damage is 94 mg/kg-day (Kociba et al.. 1974). Cortical tubule degeneration was seen at higher
doses in the NCI (1978) bioassay (240 mg/kg-d, male rats), and glomerulonephritis was reported
for rats given doses of > 430 mg/kg-d (Argus et al.. 1973; 1965).
EPA evaluated seven studies that address the noncancer effects of 1,4-dioxane following oral
exposure, including one developmental toxicity study (Giavini et al.. 1985). There are data
limitations for the effects of 1,4-Dioxane on reproductive and developmental endpoints,
including a lack of multigenerational or neurodevelopmental studies. Kociba et al. (1974). and
Kano et al. (2009) received high data quality evaluation ratings. Kano et al. (2008), was rated
medium. Argus et al. (1973; 1965) and NCI (1978) did not identify a NOAEL but contribute to
the weight of evidence for hazard identification. NOAELs and LOAELs were determined in the
remaining four studies (2.009; Kano et al.. 2008; Giavini et al.. 1985; Kociba et al.. 1974). The
study NOAEL ranges from 9.6 mg/kg/d to 500 mg/kg-d and the LOAEL from 94 mg/kg/d to
1000 mg/kg-d [Kociba et al. (1974) and Giavini et al. (1985). respectively], Kociba et al. (1974)
detected liver effects at a lower dose than Kano et al. (2.009). EPA selected Kociba et al. (1974)
as the key study for dose-response assessment based on the most sensitive toxicologically
relevant endpoints associated with oral exposure to 1,4-dioxane.
Cancer Classification
EPA re-evaluated the reasonably available evidence according to the Guidelines for Carcinogen
Risk Assessment (\ S j -005a) previously summarized 0 \ „013c). Evidence from
human studies did not support or refute an association between occupational or general
population exposure and increased risk of cancer, and by itself does not establish a clear causal
relationship. 1,4-Dioxane exposure in animal studies leads to tumors in multiple tissues at
multiple sites (Table 4-6) other than the initial points of contact (oral and inhalation) in males
and females. There are data gaps for 1,4-dioxane inhalation and dermal exposure in humans and
1,4-dioxane dermal exposure in animals leading to carcinogenic effects.
Human occupational studies examining the association between 1,4-dioxane exposure and
increased cancer risk are inconclusive because they are limited by small cohort size and a small
number of reported cancer cases. A large, high quality cohort study (Garcia et al.. 2015) found
no association between 1,4-dioxane and breast cancer rates. This study looked only at breast
cancer and as such cannot be used to extrapolate to all cancers.
Studies in multiple animal species show that chronic exposure to 1,4-dioxane induces tumors in
multiple tissues by both oral and inhalation exposure (Table 4-6). EPA classifies 1,4-dioxane as
"likely to be carcinogenic to humans" based on animal evidence of carcinogenicity at multiple
sites, in multiple species, and multiple routes of (\l ^ l'P \ _013c). The National Toxicology
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Program classifies 1,4-dioxane as "reasonably anticipated to be a human carcinogen" (NTP.
2016) and NIOSH classifies it as a "potential occupational carcinogen'YATSDR. 2012).
4.2.6 Dose-Response Assessment
4.2.6.1 Potentially Exposed or Susceptible Subpopulations
Certain human subpopulations may be more susceptible to exposure to 1,4-dioxane than others.
Because the scope of this risk evaluation is limited to workplace exposures, this section focuses
on identifying subpopulations of workers that may be more susceptible and does not address
factors that may make children or other non-workers more susceptible to 1,4-dioxane. In the
workplace, some individuals may be more biologically susceptible to the effects of 1,4-dioxane
due to genetic variability or pre-existing health conditions that increase variability in human
response to chemical exposures. Variations in CYP enzyme expression may contribute to
susceptibility because multiple CYP enzymes are involved in metabolism of 1,4-dioxane,
including CYP2E1. There are large variations in CYP2E1 expression and functionality in
humans (Ligocka et at.. 2003) and similar variation in other CYPs involved in 1,4-dioxane
metabolism are possible.
Pre-existing conditions affecting the liver may also impair metabolism in some individuals. For
example, fatty liver disease has been associated with reduced CYP function. Other pre-existing
conditions affecting the kidneys, upper respiratory system, and other organs targeted by 1,4-
dioxane could make some individuals more susceptible to workplace exposures. Due to database
deficiencies for potential reproductive and developmental toxicity of 1,4-dioxane, it is not known
whether or not pregnant women in the workplace may be at greater risk from exposure. The
variability in human susceptibility to 1,4-dioxane, including variability in CYPs, is reflected in
the selection of the uncertainty factor for human variability included in the benchmark margin of
exposure (MOE).
4.2.6.2 Points of Departure for Human Health Hazard Endpoints
The dose-response assessment included analysis of all non-cancer and cancer endpoints,
followed by an overall synthesis that includes a characterization of the risk estimates across
endpoints, the strength of the mode of action information of each endpoint, and the anticipated
relevance of each endpoint to humans, including potentially exposed or susceptible populations
and lifestages (e.g., childhood). EPA evaluated the data from studies described in Section 4.2 to
characterize the dose-response relationships of 1,4-dioxane for oral and inhalation exposures.
EPA first determined whether each hazard endpoint in the key studies had adequate information
to perform dose-response analysis. This was informed by the IRIS assessment (
2013c). which evaluated dose-response data within the studies identified in Section 4.2. EPA
defines a POD as the dose-response point that marks the beginning of a low-dose extrapolation.
This point can be the lower bound on the dose for an estimated incidence, or a change in
response level from a dose-response model (i.e., BMD), a NOAEL or a LOAEL for an observed
incidence or change in the level of response.
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4.2.6.2.1 Acute/Short-term POD for Inhalation Exposures
EPA identified Mattie et al. (2012) as the highest quality study and most relevant for use in
deriving an acute inhalation point of departure (POD). Mattie et al. (2012) reported a LOAEC of
100 ppm (360 mg/m3) for liver effects in male/female rats exposed to 1,4-dioxane for 6-hour/day
for 5 days/week for 2 weeks. EPA assumed that the selection of this endpoint for dose-response
analysis and risk characterization would be protective of potential acute/short-term effects to the
nasal cavity, lungs, and brain, based on the lower concentration at which liver effects were
reported by Mattie et al. (2012). EPA applied a duration adjustment to the LOAEC to normalize
the concentration from the exposure conditions used by Mattie et al. (2012) to that of workers
(i.e., 8 hours/day, 5 days/week). The duration adjusted POD (PODadj) was calculated as follows:
„ „ „ „ „ „ 6 hours
PODadj = POD x —
8 hours
Where,
PODadj = the duration adjusted LOAECadj
POD = the LOAEC
Following EPA's Methods for Derivation of Inhalation Reference Concentrations and
Application of Inhalation Dosimetry ( 94), EPA converted the PODadj value of 75
ppm (270 mg/m3) to a human equivalent concentration (PODhec) using the regional gas dose
ratio (RGDR) approach for extrarespiratory effects by calculating a dosimetric adjustment factor
(DAF), which is based on the ratio between the animal and human blood:air partition
coefficients, as shown below:
DAP = ^-Hb/3)A
(Hb/g)H
where:
(Hb/g)A = the animal blood:air partition coefficient, and
(Hb/g)H = the human blood:air partition coefficient
Sweeney et al. (2008) measured the blood:air partition coefficients in rats (i.e., (Hb/g)A = 1861)
and humans (i.e., (Hb/g)A = 1666). The resulting DAF equates to 1.117; however, when the
DAF is greater than 1, EPA applies a default value of 1 (U.S. EPA. 1994) (see Table 4-8).
The resulting acute inhalation PODhec is 75 ppm (270 mg/m3) and was considered protective of
liver effects from short-term worker exposures.
EPA applied a composite uncertainty factor (UF) of 300 for the acute inhalation benchmark
MOE for short-term/acute effects, based on the following considerations:
• An interspecies uncertainty/variability factor of 3 (UFa) was applied for animal-to-human
extrapolation to account for toxicodynamic differences between species. This uncertainty
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factor is comprised of two separate areas of uncertainty to account for differences in the
toxicokinetics and toxicodynamics of animals and humans. In this assessment, the
toxicokinetic uncertainty was accounted for by the calculation of an HEC and application
of a DAF as outlined in the RfC methodology (U.S. EPA. 1994). As the toxicokinetic
differences are thus accounted for, only the toxicodynamic uncertainties remain, and an
UFa of 3 is retained to account for this uncertainty.
• A default intraspecies uncertainty/variability factor (UFh) of 10 was applied to account
for variation in sensitivity within human populations due to limited information on the
degree of humans of varying gender, age, health status, or genetic makeup might vary in
the disposition of, or response to, 1,4 dioxane.
• A LOAEC-to-NOAEC uncertainty factor (UFl) of 10 was applied because the POD from
the principle study was a LOAEC.
The acute inhalation benchmark MOE of 300 was used to interpret the MOE risk estimates for
each short-term/acute use scenario. The MOE estimate was interpreted as a potential human
health risk if the MOE estimate was less than the acute inhalation benchmark MOE (i.e., the
composite UF). On the other hand, the MOE estimate was interpreted as indicating negligible
risk concerns for adverse human health effects if the MOE estimate exceeded the benchmark
MOE.
4.2.6.2.2 Acute/Short-term POD for Dermal Exposures extrapolated from Inhalation
Studies
The Mattie et al. (2012) study used in deriving an acute inhalation POD was extrapolated from
an inhalation to dermal exposure to derive an human equivalent dose (HED).
The acute inhalation PODhec of 75 ppm (270 mg/m3) for liver effects from short-term worker
exposures was converted to an applied dermal HED using the following equation:
dermal HED (mg/kg-d) = inhalation PODhec (mg/m3) x inhalation volume x 100%
(inhalation absorption) ^ 3.2% (dermal absorption) ^ body weight
where the inhalation volume is for an 8-hour exposure x 1.25 m3/hour and the body weight is 80
kg. The absorption estimates were based on experimental data by the inhalation route (i.e.,
Young et al., (1977; 1976) where 1,4-dioxane is readily absorbed in humans, however the
available studies did not measure the parameters needed for a quantitative estimate of the
fraction absorbed. Given this qualitative estimate and the absence of quantitative inhalation
absorption data, 100% inhalation absorption is assumed. Dermal absorption was estimated in a
human in vitro skin assay described in Section 4.2.2. Bronaugh (1982) measured penetration of
1,4-dioxane through excised human skin to be 3.2% of the applied dose for occluded skin, and
0.3% for unoccluded skin. The occluded absorption value is also consistent with another
unoccluded measured absorption value in monkeys in vivo (2-3%) (Marzulli et al.. 1981).
Considering the uncertainties in the oral-to-dermal extrapolation, EPA chose to use 3.2% for the
dermal absorption factor. The actual absorption could be ten-fold lower based on the Bronaugh
in vitro study (Bronaug 0.
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The resulting acute dermal HED is 1055 mg/kg/day and was considered protective of liver
effects from short-term worker exposures.
EPA applied the same composite uncertainty factor (UF) of 300 for the acute dermal benchmark
MOE for short-term/acute effects as the inhalation because the dermal POD was extrapolated
from the inhalation study, based on the following considerations:
• An interspecies uncertainty/variability factor of 3 (UFa) was applied for animal-to-human
extrapolation to account for toxicodynamic differences between species. This uncertainty
factor is comprised of two separate areas of uncertainty to account for differences in the
toxicokinetics and toxicodynamics of animals and humans. In this assessment, the
toxicokinetic uncertainty in the inhalation study was accounted for by the calculation of
an HEC and application of a DAF as outlined in the RfC methodology (U.S. EPA. 1994)
and toxicokinetic differences in dermal absorption are accounted for in the HED
calculation by assuming 100% inhalation absorption and applying in vitro dermal
absorption data, only the toxicodynamic uncertainties remain, and an UFa of 3 is retained
to account for this uncertainty.
• A default intraspecies uncertainty/variability factor (UFh) of 10 was applied to account
for variation in sensitivity within human populations due to limited information on the
degree of humans of varying gender, age, health status, or genetic makeup might vary in
the disposition of, or response to, 1,4-dioxane.
• A LOAEC-to-NOAEC uncertainty factor (UFl) of 10 was applied because the POD from
the principle study was a LOAEC.
The acute inhalation benchmark MOE of 300 was used to interpret the MOE risk estimates for
each short-term/acute use scenario. The MOE estimate was interpreted as a potential human
health risk if the MOE estimate was less than the acute inhalation benchmark MOE (i.e., the
composite UF). On the other hand, the MOE estimate was interpreted as indicating negligible
risk concerns for adverse human health effects if the MOE estimate exceeded the benchmark
MOE.
4.2.6.2.3 Chronic Non-Cancer POD for Inhalation Exposures
EPA performed dose response analyses on the noncancer endpoints reported by Kasai et al.,
(2009). which included portal of entry effects in the respiratory tract (i.e., squamous cell
metaplasia of the nasal respiratory epithelium, squamous cell hyperplasia of the nasal respiratory
epithelium, respiratory metaplasia of the nasal olfactory epithelium, atrophy of the nasal
olfactory epithelium, hydropic change in the lamina propria and sclerosis in the lamina propria of
the nasal cavity) and systemic effects (i.e., centrilobular necrosis of the liver),. EPA selected the
two-year inhalation toxicity study because it is more relevant for deriving inhalation points of
departure (PODs) for long-term human exposures.
EPA evaluated the noncancer endpoints to determine whether the data were amenable to BMD
modeling. For the data sets that were amenable to BMD modeling, EPA followed the benchmark
dose modeling software (BMDS) guidance (U.S. EPA. 2012b) and used BMDS version 2.704. A
benchmark response (BMR) of 10% extra risk was used for all endpoints to estimate the
BMCLio (the lower 95% bound on the concentration estimated to produce a 10% increased
incidence over background) (see Table 4-8). For the data sets that were not amenable to BMD
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modeling, the NOAECs and LOAECs were used as the inhalation PODs (see Table 4-8).
Additional information on the BMD methods and criteria used for assessing adequacy of model
fit can be found in Appendix I (Benchmark Dose Analysis).
Duration adjustments were applied to the PODs (i.e., BMCLios, NOAECs, or LOAECs) to
normalize the concentrations from the exposure conditions used by (Kasai et al. 2009) (i.e., 6
hours/day, 5 days/week) to that of workers (i.e., 8 hours/day, 5 days/week) (see Table 4-8). The
adjusted PODs (i.e., PODadjs) were calculated as follows:
„ „ „ „ „ „ 6 hours
PODadj = POD x —
8 hours
Where,
PODadj = the duration adjusted BMCLadj, NOAECadj, or LOAECadj
POD = the BMCLio, NOAEC, or LOAEC
Following EPA's Methods for Derivation of Inhalation Reference Concentrations and
Application of Inhalation Dosimetry (U.S. EPA, 1994), human equivalent concentrations (HECs)
were determined using two separate methods, one for portal of entry effects and one for systemic
effects. For portal of entry effects, EPA derived a DAF using the RGDR method, which
considers the ventilation rate for animals and humans and the location of the effects in the
respiratory tract. The RGDR for 1,4-dioxane was calculated based on extrathoracic respiratory
effects (i.e., RGDRet) and was derived using a calculated ventilation rate of 0.1 m3/8-hours for
an average rat, and a default value of 10 m3/8-hours for workers, along with default extrathoracic
region surface area values of 15.0 cm2 for the rat and 200 cm2 for humans. The resulting
equation is shown below:
RGDR — Ventilation rate (rat) h- surface area (rat) _ 0.1 m3 h- 15.0 cm2 _ q jg
Ventilation rate (human) h- surface area (human) 10 m3 h- 200 cm2
Multiplying the RGDRet of 0.13 by the PODadj yields a dosimetrically adjusted human
equivalent concentration (HEC) or PODhec (i.e., BMCLiohec, NOAEChec, or LOAEChec) (See
Table 4-8).
For systemic effects, EPA used the RGDR approach for extrarespiratory effects by calculating a
DAF, which is based on the ratio between the animal and human blood:air partition coefficients,
as shown below:
DAF=smi
(Hb/g)H
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where:
(Hb/g)A = the animal blood:air partition coefficient, and
(Hb/g)H = the human blood:air partition coefficient
As noted previously, the measured blood:air partition coefficients in rats (i.e., (Hb/g)A = 1861)
and humans (i.e., (Hb/g)A = 1666) results in a DAF of 1.117. Therefore, EPA applied a default
value of 1 (U.S. EPA. 1994) (see Table 4-8).
Of the available PODhec values, EPA selected the PODhec of 1.67 mg/m3 for effects on the
olfactory epithelium (i.e., metaplasia and atrophy). These portal of entry effects were the most
pronounced and sensitive endpoints in the two-year inhalation study reported by Kasai et al.,
(2.009). EPA considered these effects as the most relevant for worker exposures, given that
systemic effects occurred at high concentration levels. Therefore, basing the PODhec on portal of
entry effects will be protective for workers against systemic effects.
EPA applied a composite UF of 30 for the chronic inhalation benchmark MOE, based on the
following considerations:
• An interspecies uncertainty factor (UFa) of 3 to account for species differences in animal
to human extrapolation. An interspecies uncertainty/variability factor of 3 (UFa) was
applied for animal-to-human extrapolation to account for toxicodynamic differences
between species. This uncertainty factor is comprised of two separate areas of uncertainty
to account for differences in the toxicokinetics and toxicodynamics of animals and
humans. In this assessment, the toxicokinetic uncertainty was accounted for by the
calculation of an HEC and application of a dosimetric adjustment factor as outlined in the
RfC methodology (U.S. EPA. 1994). As the toxicokinetic differences are thus accounted
for, only the toxicodynamic uncertainties remain, and an UFa of 3 is retained to account
for this uncertainty.
• A default intraspecies uncertainty/variability factor (UFh) of 10 was applied to account
for variation in sensitivity within human populations due to limited information on the
degree of humans of varying gender, age, health status, or genetic makeup might vary in
the disposition of or response to, 1,4 dioxane; and
A Subchronic-to-Chronic uncertainty factor (UFs) was not applied because the key study used a
chronic exposure protocol.
The chronic inhalation benchmark MOE of 30 was used to interpret the MOE risk estimates for
each chronic use scenario. The MOE estimate was interpreted as a potential human health risk if
the MOE estimate was less than the chronic inhalation benchmark MOE (i.e., the composite UF).
On the other hand, the MOE estimate was interpreted as indicating negligible risk concerns for
adverse human health effects if the MOE estimate exceeded the benchmark MOE.
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Table 4-8. Model selection and duration-adjusted HEC estimates for BMCLs (from best
fitting BMDS models) or NOAECs/LOAECs from the 2-year inhalation study by Kasai et
al. (2009) in Male F344/DuCrj rats".
Portal of Entry Effects
Endpoint
BMR
Modelb
BMC
10
(PPm)
C
BMCLio
or
NOAEC/
LOAEC
(PPm)c
BMCLadj
or
NOAECadj/
LOAECadj
(worker
ppm)d
BMCLhec
or
NOAEChec/
LOAEChec
(worker
mg/m3)e'f
Benchmark
MOE
Squamous
cell
metaplasia;
respiratory
epithelium
10%
Log
Probit
218
160
120
56.2
30
Squamous
cell
hyperplasia;
respiratory
epithelium
10%
Quantal
Linear
679
429
323
151.3
30
Respiratory
metaplasia;
olfactory
epithelium
10%
BMDL8
6.47
4.74
3.56
1.67
30
Atrophy;
olfactory
epithelium
"
LOAEC
--
50
37.5
17.6
300
Hydropic
change;
lamina
10%
Log
Logistic
68.5
46.8
35.1
16.4
30
propria
Sclerosis;
lamina
_
NOAEC
_
50
37.5
17.6
30
propria h
Systemic Effects
Endpoint
BMR
Modelb
BMC
(PPm)
C
BMCLio
(PPm)c
BMCLadj"
(worker
PPm)
BMCLhec6'8
(worker
mg/m3)
Bench mar
k MOE
Centrilobular
necrosis;
Liver
10%
Log
Logistic
232
44.0
33.0
119
30
aData quality evaluations for all endpoints are high (see Appendix G).
bBest fitting models were determined using current BMDS guidance (U.S. EPA, 201.2b).
cBMCio = Concentration at specified extra risk (benchmark dose); BMCLio = 95% lower bound on concentration at specified
extra risk.
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dPODADj (ppm) = BMCL or LOAEC or NOAEC x 6 hours 8 hours. TODadj (ppm) values were converted to mg/m3 values
based on the following: POD adj (ppm) x molecular weight of 1,4-dioxane (88.1 g/mole) 24.45 (gas constant at 760 mm Hg and
at 25 °C).
"PODhec (mg/m3) = BMCLadj or LOAEC adj or NOAEC adj x DAF (i.e., RGDRet)
bPODhec (mg/m3) = BMCLadj x DAF (i.e., (Hb/g)A - (Hb/g)H)
h Only one BMDS model (dichotomous Hill) could provide a statistically adequate fit to these data, however this model fit
implied a high degree of curvature immediately below the observed LOAEL, a pattern that the experimental data could not
support or refute. Due to the uncertainty in model shape, a BMDL value is not proposed for this endpoint.
4.2.6.2.4 Chronic Cancer Unit Risk for Inhalation Exposures i.e. Inhalation Unit Risk
(IUR)-
EPA performed dose response analyses on the cancer endpoints reported by Kasai et al. (2009).
1,4-dioxane produced a statistically significant increase in the incidences and/or statistically
significant dose-response trends for portal of entry tumors in the respiratory tract and auditory
canal (i.e., nasal cavity squamous cell carcinomas and Zymbal gland (auditory sebaceous gland)
adenomas) and systemic tumors (i.e., hepatocellular adenomas and carcinomas, renal cell
carcinomas, peritoneal mesotheliomas, and mammary gland fibroadenomas, and subcutis
fibromas). One assumption was to consider all tumors of independent origin and included in the
multi-tumor analysis. The incidence of adenomas and carcinomas were combined according to
EPA's Guidelines for Carcinogen Risk Assessment which advises that etiologically similar tumor
types, i.e., benign and malignant tumors of the same cell type, can be combined due to the
possibility that benign tumors could progress to the malignant form (U.S. EPA. 2005a;
McConnell et al.. 1986).
BMD modeling was used to fit the dose-response data and calculate the inhalation PODs. The
multistage cancer models available in the BMDS (version 2.704) were fit to the incidence data
for each tumor type observed in rats exposed to 1,4-dioxane via inhalation (Kasai et al.. 2009) to
determine the degree (e.g., 1st, 2nd, or 3rd) of the multistage model that best fit the data. In
accordance with the EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA. 2005a). a
benchmark response (BMR) of 10% was used to estimate the BMCLio (the lower 95% bound on
the concentration estimated to produce a 10% increase in tumor incidence over background). The
results of the model that best characterized the cancer incidences were selected (see Table 4-9).
Suitable multistage model fits were obtained for all tumor types included in the inhalation unit
risk analysis. Additional information on the BMD methods and criteria used for assessing
adequacy of model fit can be found in Appendix I (Benchmark Dose Analysis).
As discussed for the noncancer dose response analyses, the BMCLio values were converted to
duration adjusted values (i.e., BMCLadjs) and dosimetrically adjusted to BMCLhecs, using the
same methods applied to the noncancer endpoints (as discussed above under "Chronic
Inhalation - Non-Cancer") (see Table 4-9).
U.S. EPA (2013c) applied a linear low-dose approach to derive inhalation unit risk values. This
approach is used when the mode of action (MOA) is unknown or unclear. The inhalation unit
risk (IUR) for humans is defined as the slope of the line drawn from the inhalation POD
(BMCLhec) through the origin. To calculate the IUR, the benchmark response rate (0.1) was
divided by the BMCLhec values (see Table 4-9).
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Given the multiplicity of tumor sites, basing the overall IUR on one tumor site may
underestimate risk. Consistent with recommendations of the NRC (1994) and EPA's Guidelines
for Carcinogen Risk Assessment (U.S. EPA. 2005a). the total risk and upper bound risk for
multiple tumor sites was estimated. The MS-Combo model (which is implemented using BMDS)
was utilized to calculate the concentration associated with a specified composite risk (the risk of
developing any combination of tumors at any site), under the assumption that tumors in different
tissues arise independently. MS-Combo is a peer-reviewed (Versar. 2011) module within BMDS
that employs a combined probability function to calculate composite risk using the best-fitting
BMDS multistage model parameters determined for each individual tumor. MS-Combo was
applied to the best-fitting models for each tumor type from the Kasat et at. (2.009) study. To
evaluate uncertainties related to model choice and mechanisms, MS-Combo was applied to the
following datasets: one model run included all portal of entry tumors, a second model run
included all systemic tumors, a third model run included systemic tumors minus the liver tumors,
a fourth model run was performed on all portal of entry and systemic tumors, and a fifth model
run was performed on all portal of entry tumors and systemic tumors minus the liver tumors (see
Table 4-9). This approach of not including the liver tumors was predicated on liver tumors
response potentially being nonlinear.
Note that the BMCLadj, calculated assuming a worker exposure scenario of 40 hours per week
i.e. 8 hours per day for 5 days per week. Therefore, the BMCLhec and IUR estimates are
appropriate for comparison with exposure scenarios of comparable duration. Also, the IUR
estimate is not the same as the EPA IRIS assessment where the IUR is estimated for a continuous
exposure (i.e., 24 hours per day for 7 days per week).
Table 4-9. Dose-response modeling summary results for male rat tumors associated with
inhalation exposure to 1,4-dioxane for two years
Portal of Entry Effects
Tumor Type"
Multistage
Model
Degreeb
BMCio
(ppm)c
BMCLio
(ppm)c
BMCLadj
(worker
ppm)d
BMCLhec
(worker
mg/m3)ef
IUR
Estimate8
(Hg/m3)-'
Nasal cavity squamous
1
1107
630
473
221
4.52E-07
cell carcinoma
Zymbal gland adenoma
1
1975
958
719
337
2.97E-07
MS-Combo portal of entry
709
449
337
158
6.34E-07
Systemic Effects
Tumor Type3
Multistage
Model
Degreeb
BMCio
(ppm )c
BMCLio
(ppm )c
BMCLadj
(worker
ppm)d
BMCLhec
(worker
mg/m3)eh
IUR
Estimate8
(Hg/m3)-'
Hepatocellular adenoma
1
253
182
137
492
2.03E-07
or carcinoma
Renal cell carcinoma
1
1975
958
719
2589
3.86E-08
Peritoneal mesothelioma
1
82.2
64.4
48
174
5.75E-07
Mammary gland
fibroadenoma
1
1635
703
527
1900
5.26E-08
Subcutis fibroma
1
142
81.9
61.4
221
4.52E-07
MS-Combo systemic (including liver)
41.2
32.8
24.6
88.6
1.13E-06
MS-Combo systemic (omitting liver)
49.2
37.9
28.4
102
9.76E-07
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Portal of Entry and Systemic Effects
Tumor Type"
Multistage
Model
Degreeb
BMCio
(ppm)
BMCLio
(ppm)
BMCLadj
(worker
ppm)
BMCLhec
(worker
mg/m3)'
IUR
Estimate8
Oig/m3)1
MS-Combo portal of entry + systemic
(including liver)
38.9
31.3
23.5
84.6
1.18E-06
MS-Combo portal of entry + systemic
(omitting liver)
46.0
35.9
26.9
97.0
1.03E-06
aTumor incidence data from Kasai et al. (2009). Data quality evaluations for all endpoints are high (see Appendix G).
bBest-fitting multistage model degree following current BMDS guidance (U.S. EPA, 201.4b. 201.2b). Model selections for renal
cell carcinoma and Zymbal gland adenoma differ from the U.S. EPA (2013c) IRIS assessment.
cBMCio = Concentration at specified extra risk (benchmark dose); BMCLio = 95% lower bound on concentration at specified
extra risk.
dPODADj (ppm) = BMCLio x 6 hours 8 hours.
cPODadj (ppm) values were converted to mg/m3 values based on the following: BMCLadj (ppm) x molecular weight of 1,4-
dioxane (88.1 g/mole) gas constant at 760 mm Hg and at 25 °C).
"PODhec (mg/m3) = BMCLadj x DAF (i.e., RGDRet).
BThe inhalation unit risk ((ig/m3)"1 was derived from the BMCLhec, the 95% lower bound on the concentration associated with a
10%) extra cancer risk. Specifically, by dividing the BMR (0.10) by the BMCLhec. Thus, representing an upper bound,
continuous lifetime exposure estimate of cancer potency.
TODhec (mg/m3) = BMCLadj x DAF (i.e., (Hb/g)A - (Hb/g)H)
'PODhec (mg/m3) for the MS-Combo including both portal of entry and systemic effects used the DAF of (Hb/g)A (Hb/g)H
4.2.6.2.5 Chronic Non-Cancer POD for Dermal Exposures extrapolated from Chronic
Inhalation Studies
The Kasai et al., (2009) study used in deriving inhalation PODs for long-term human exposures
was extrapolated from an inhalation to dermal exposure to derive a human equivalent dose
(HED). The portal of entry effects in the respiratory tract (i.e., squamous cell metaplasia of the
nasal respiratory epithelium, squamous cell hyperplasia of the nasal respiratory epithelium,
respiratory metaplasia of the nasal olfactory epithelium, atrophy of the nasal olfactory
epithelium, hydropic change in the lamina propria and sclerosis in the lamina propria of the nasal
cavity) in the Kasai et al., (2009) study were not considered for route-to-route extrapolation.
Only systemic effects {i.e., centrilobular necrosis of the liver) were used for route-to-route
extrapolation. EPA selected the two-year inhalation toxicity study because it is more relevant for
deriving chronic dermal points of departure (PODs) following long-term human exposures.
The chronic inhalation BMCLhec of 119 mg/m3 for centrilobular necrosis (see Table 4-8) from
chronic inhalation exposures was converted to an applied dermal HED using the following
equation:
dermal HED (mg/kg-d) = inhalation BMDLhec (mg/m3) x inhalation volume x 100%
(inhalation absorption) ^ 3.2% (dermal absorption) ^ body weight
where the inhalation volume is for an 8-hour exposure x 1.25 m3/hour and the body weight is 80
kg. The absorption estimates were based on experimental data by the inhalation route {i.e.,
Young et al., (1977; 1976) where 1,4-dioxane is readily absorbed in humans, however the
available studies did not measure the parameters needed for a quantitative estimate of the
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fraction absorbed. Given this qualitative estimate and the absence of quantitative inhalation
absorption data, 100% inhalation absorption is assumed.
Dermal absorption was estimated in a human in vitro skin assay described in Section 4.2.2.
Bronaugh (1982) measured penetration of 1,4-dioxane through excised human skin to be 3.2% of
the applied dose for occluded skin, and 0.3% for unoccluded skin. The occluded absorption value
is also consistent with another unoccluded measured absorption value in monkeys in vivo (2-3%)
(Marzulli etal... 1981). Considering the uncertainties in the oral-to-dermal extrapolation, EPA
chose to use 3.2% for the dermal absorption factor. The actual absorption could be ten-fold lower
based on the Bronaugh in vitro study (Bronaugh. 1982).
The resulting chronic dermal HED is 465 mg/kg/day and was considered protective of liver
effects from chronic worker exposures.
EPA applied the same composite uncertainty factor (UF) of 30 for the chronic dermal benchmark
MOE as the chronic inhalation systemic because the dermal POD was extrapolated from the
systemic effects in the inhalation study, based on the following considerations:
• An interspecies uncertainty/variability factor of 3 (UFa) was applied for animal-to-human
extrapolation to account for toxicodynamic differences between species. This uncertainty
factor is comprised of two separate areas of uncertainty to account for differences in the
toxicokinetics and toxicodynamics of animals and humans. In this assessment, the
toxicokinetic uncertainty in the inhalation study was accounted for by the calculation of
an HEC and application of a DAF as outlined in the RfC methodology (U.S. EPA. 1994)
and toxicokinetic differences in dermal absorption are accounted for in the HED
calculation by assuming 100% inhalation absorption and applying in vitro dermal
absorption data, only the toxicodynamic uncertainties remain, and an UFa of 3 is retained
to account for this uncertainty.
• A default intraspecies uncertainty/variability factor (UFh) of 10 was applied to account
for variation in sensitivity within human populations due to limited information on the
degree of humans of varying gender, age, health status, or genetic makeup might vary in
the disposition of or response to, 1,4 dioxane; and
• A LOAEC-to-NOAEC uncertainty factor (UFl) was not needed, i.e. a value of 1 was
applied because a BMDL was derived and used.
A Subchronic-to-Chronic uncertainty factor (UFs) was not applied because the key study used a
chronic exposure protocol.
The chronic inhalation benchmark MOE of 30 was used to interpret the MOE risk estimates for
each chronic use scenario. The MOE estimate was interpreted as a potential human health risk if
the MOE estimate was less than the chronic inhalation benchmark MOE (i.e., the composite UF).
On the other hand, the MOE estimate was interpreted as indicating negligible risk concerns for
adverse human health effects if the MOE estimate exceeded the benchmark MOE.
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4.2.6.2.6 Chronic Non-Cancer POD for Dermal Exposures extrapolated from Chronic
Oral Studies
The repeated-dose (oral) combined chronic/carcinogenicity studies were used with route-to-route
extrapolations to derive applied human equivalent doses (HEDs). In the discussion that follows,
the non-cancer oral HEDs identified from the repeated-dose (oral) combined chronic/
carcinogenicity studies are discussed in the context of dose response analyses, followed by the
adjustments that were made for performing route-to-route extrapolations {i.e., oral to dermal) for
deriving the applied dermal HEDs. Thereafter, the justification for the benchmark MOE is
discussed.
The non-cancer endpoints for dose response analysis from the studies by Kano et al. (2009;
2008). Kociba et al. (1974). and NCI (1978) were increased liver enzymes, nasal inflammation
and other nasal effects (atrophy of nasal olfactory epithelium, nuclear enlargement of nasal
respiratory epithelium, nasal adhesion), hepatocellular mixed foci, hepatocyte swelling,
degeneration and necrosis of renal tubular cells and hepatocytes, and cortical tubule
degeneration. NOAELs and LOAELs were obtained from Appendix G for those data that were
not amenable to benchmark dose modeling (see Appendix I for guidance and criteria used for
assessing adequacy of model fit). The highest dose in Kano et al. (2009) was removed from all
analyses because of concerns regarding decreased water intake rate at the highest dose. Because
all LOAELs and NOAELs were in the low-dose region, the exclusion of this data point only
impacted BMD analyses. BMDS modeling was performed on the available data using BMDS
version 2.704 and following current BMDS guidance ( 2012b). Following EPA's
Recommended Use of Body Weight314 as the Default Method in Derivation of the Oral Reference
Dose ( ), human equivalent doses were calculated by multiplying rodent doses
by (BWa/BWh)0 25 (where BWa is the bioassay-specific rodent body weight, and BWh is the
default human body weight of 80 kg). The EPA IRIS assessment (U.S. EPA. ) did not
apply BW3/4 scaling to noncancer oral data since the guidance was finalized after the oral portion
of the 1,4-dioxane U.S. EPA. (2013 c) IRIS assessment was posted (2013 was the completion year
for the inhalation update).
As shown in Table 4-10, the oral HEDs were converted to applied dermal HEDs using the
following equation:
Applied dermal HED (mg/kg-d) = oral HED (mg/kg-d) x 100% (oral absorption) ^ 3.2%
(dermal absorption)
The absorption estimates were based on experimental data by the oral {i.e., Young et al., (1978a.
b) and dermal {i.e., Marzulli et al., (1981)) routes of exposure. Young et al. (1978a. b) estimated
the oral absorption of 1,4-dioxane in rats to be nearly complete. Given this qualitative estimate
and the absence of quantitative oral absorption data in experimental animals or humans, 100%
oral absorption was assumed. Dermal absorption was estimated in a human in vitro skin assay
described in Section 4.2.2. Bronaugh (1982) measured penetration of 1,4-dioxane through
excised human skin to be 3.2% of the applied dose for occluded skin, and 0.3% for unoccluded
skin. The occluded absorption value is also consistent with another unoccluded measured
absorption value in monkeys in vivo (2-3%) (Marzulli et al.. 1981). Considering the uncertainties
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in the oral-to-dermal extrapolation, EPA chose to use 3.2% for the dermal absorption factor. The
actual absorption could be ten-fold lower based on the Bronaugh in vitro study (Bronaugh.
1982).
EPA applied a composite UF of 30 for the chronic dermal benchmark MOE, based on the
following considerations:
• An interspecies uncertainty/variability factor of 3 (UFa) was applied for animal-to-
human extrapolation to account for pharmacodynamic differences between species.
This uncertainty factor is comprised of two separate areas of uncertainty to account
for differences in the toxicokinetics and toxicodynamics of animals and humans. In
this assessment, the toxicokinetic uncertainty was accounted for by the calculation of
an HED and application of BW3 4 scaling (U.S. EPA. 2 ). As the toxicokinetic
differences are thus accounted for, only the toxicodynamic uncertainties remain, and
an UFA of 3 is retained to account for this uncertainty.
• A default intraspecies uncertainty/variability factor (UFh) of 10 was applied to
account for variation in sensitivity within human populations due to limited
information on the degree of humans of varying gender, age, health status, or genetic
makeup might vary in the disposition of or response to, 1,4-dioxane
A Subchronic-to-Chronic uncertainty factor (UFs) was not applied because the key study used a
chronic exposure protocol.
The chronic dermal benchmark MOE of 30 was used to interpret the MOE risk estimates for
each use scenario. The MOE estimate was interpreted as a potential human health risk if the
MOE estimate was less than the chronic dermal benchmark MOE (i.e., the composite UF). On
the other hand, the MOE estimate was interpreted as indicating negligible concerns for adverse
human health effects if the MOE estimate exceeded the benchmark MOE.
Overall of the multiple dermal HEDs both from oral (Table 4-10) and inhalation (Section
4.2.6.2.5) studies the most sensitive is for degeneration and necrosis of renal tubular cells and
hepatocytes was 80 mg/kg/day and thus was considered protective of all effects (i.e. kidney, liver
and respiratory effects) from chronic dermal worker exposures.
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Table 4-10. Dose-response modeling summary results for oral non-cancer liver, kidney, and nasal effects and route-to-route
extrapolated applied dermal HEDs
Study (data
quality)
Gender/strain/
species
Endpoint
BMR
Model
BMD
(mg/kg-
d)
BMDL
or
NOAEL
(mg/kg-
d)
BWa
(g)2
Oral
HED3
(mg/kg-
d)
Applied
dermal
HED4
(mg/kg-d)
Kano et al. (2009)
(high)
Male F344/DuCij
rats
Increases in serum liver
enzymes (GOT, GPT,
LDH, and ALP)
NOAEL5
55
432
14.9
465.6
Atrophy of nasal olfactory
epithelium; nasal adhesion
and inflammation
NOAEL
55
14.9
465.6
Hepatocellular mixed cell
foci
10%
Log
Logistic6
16.7
9.57
2.59
80.9
—
NOAEL
—
11
2.98
93.1
Female Cij:BDFl
mice
Nasal inflammation
—
NOAEL
—
66
35.9
9.61
300.3
Male Cij:BDFl
mice
Increases in serum liver
enzymes (GOT, GPT,
LDH, and ALP)
NOAEL
49
47.9
7.66
239.4
Kano et al. (2008)
(medium)
Male F344/DuCij
rats
Nuclear enlargement of
nasal respiratory epithelium
—
NOAEL
—
52
335
13.2
412.5
Hepatocyte swelling
—
NOAEL
—
52
335
13.2
412.5
Kociba et al.
(high)
Male Sherman
rats
Degeneration and necrosis
of renal tubular cells and
hepatocytes
NOAEL
9.6
405
2.56
80.0
NCI (.1.978) (low)
Female OM rats
Cortical tubule
degeneration
10%
Weibull
596
452
310
113
3531.3
1 Applies to all of the endpoints listed in this table for each study. See Appendix G.
2 Body weights are study-specific time weighted averages. For Kano et al. (2009') and NCI (1978). these were obtained from Table 5-9 of the U.S. EPA (20.1.3c)
IRIS assessment. For Kano et al. (2008). the published body weight at the LOAEL or NOAEL for the species/sex was used. For Kociba et al. (.1.974). the time
weighted average BW of male rats was approximated by digitizing data from the published growth curve (low-dose and control animals).
3 POD=dose x (BWa/BWh)0 25. BWa = study-specific values (see above). BWh=80 kg. The oral assessment of U.S. EPA (2013c). which preceded the inhalation
update portion of the assessment and the B W3/4 scaling guidance (U.S. EPA. 20.1.1b) did not perform this conversion.
4 Applied dermal HED (mg/kg-d) = oral HED (mg/kg-d) x 100% (oral absorption) 3.2% (dermal absorption).
5 NOAELs listed in this table were obtained from Appendix G. These endpoints were not amenable to benchmark dose modeling.
6 Highest dose omitted.
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4.2.6.2.7 Chronic Cancer Unit Risk for Dermal Exposures i.e. Cancer Slope Factor (CSF)
extrapolated from Chronic Inhalation Studies
The repeated-dose (inhalation) combined chronic/carcinogenicity studies were used with route-
to-route extrapolations to derive dermal CSFs using all systemic effects. Effects identified as
portal of entry were not included. In the discussion that follows, the BMCLs that were used to
calculate inhalation IURs identified from the repeated-dose (inhalation) combined
chronic/carcinogenicity studies were adjusted for route-to-route extrapolation to derive the
dermal CSFs. The BMCLs were converted from inhalation air concentrations to doses based on
inhalation volume and body weights for the species in the study, rats. Following Guidelines for
Carcinogen Risk Assessment (U.S. EPA. 2005a). human equivalent doses were calculated for
each tumor type by multiplying rodent doses by (BWa/BWh)0 25 (where BWa is the bioassay-
specific rodent body weight, and BWn is the default human body weight of 80 kg). The human
equivalent doses were adjusted for dermal exposures by the ratio of relative inhalation to dermal
absorption. The human equivalent dose was used as the point of departure (POD). To calculate a
cancer slope factor (CSF), the benchmark response rate (0.1) was divided by the POD. A CSF is
a plausible upper bound lifetime cancer risk from chronic ingestion of a chemical per unit of
mass consumed per unit body weight, per day (mg/kg day).
The BMCLhecs (see Table 4-10) were converted to a dermal HED using the following
equations:
animal BMDL (mg/kg-d) = inhalation BMCL (mg/m3) x animal inhalation volume
animal body weight x 3.60 mg/m3 per ppm
BMDLhed (mg/kg-d) = animal BMDL (mg/kg-d) x animal body weight x (human body
weight ^ animal body weight) A 3/4 ^ human body weight
dermal BMDLhed (mg/kg-d) = human equivalent BMDL x (inhalation absorption ^
dermal absorption)
dermal CSF (mg/kg-d)"1 = BMR / dermal BMDLhed (mg/kg-d)
where the animal inhalation volume is for the exposure duration of the animal study (6 hours / 24
hours) x 0.36 m3/day for rats, the animal body weight for rats is 0.380 kg, the human body
weight is 80 kg.
The absorption estimates were based on experimental data by the inhalation route {i.e., Young el
al., (1977; 1976) where 1,4-dioxane is readily absorbed in humans, however the available studies
did not measure the parameters needed for a quantitative estimate of the fraction absorbed. Given
this qualitative estimate and the absence of quantitative inhalation absorption data, 100%
inhalation absorption is assumed. Dermal absorption was estimated in a human in vitro skin
assay described in Section 4.2.2. Bronaugh (1982.) measured penetration of 1,4-dioxane through
excised human skin to be 3.2% of the applied dose for occluded skin, and 0.3% for unoccluded
skin. The occluded absorption value is also consistent with another unoccluded measured
absorption value in monkeys in vivo (2-3%) (Marzutli etal... 1981). Considering the uncertainties
in the oral-to-dermal extrapolation, EPA chose to use 3.2% for the dermal absorption factor. The
actual absorption could be ten-fold lower based on the Bronaugh in vitro study (Bronaugh.
1982). The BMR used was 10%.
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The resulting cancer slope factors for dermal exposures are shown below in Table 4-11 and the
slope factors for the combined systemic tumors 4.3E-4 per mg/kg/day (including liver) and 3.8E-
4 per mg/kg/day (omitting liver) is considered protective of all tumor types for chronic worker
exposures.
Table 4-11. Cancer slope factor for dermal exposures extrapolated from studies for male
rat tumors associated with inhalation exposure to 1,4-dioxane for two years
Systemic Effects
Animal
BMDL
(mg/kg/day)d
BMDLhed
Dermal
BMDLhed
(worker
mg/kg/day
^e,h
CSF
Tumor Type3
BMCLio
(ppm)c
(worker
mg/kg/day)e'
h
Estimate8
(mg/kg/da
y)1
Hepatocellular adenoma or carcinoma
182
155
41
1281
7.8E-5
Renal cell carcinoma
958
817
214
6688
1.5E-5
Peritoneal mesothelioma
64.4
55
14
438
2.3E-4
Mammary gland fibroadenoma
703
599
157
4906
2.0E-5
Subcutis fibroma
81.9
70
18
563
1.8E-4
MS-Combo systemic (including liver)
32.8
28
7.4
231
4.3E-4
MS-Combo systemic (omitting liver)
37.9
32
8.4
263
3.8E-4
aTumor incidence data from Kasai et al. (2009). Data quality evaluations for all endpoints are high (see Appendix G).
cBMCLio = 95% lower bound on concentration at specified extra risk as shown in Table 4-8.
danimal BMDL (mg/kg/day) calculated with equations above
eBMDLHED mg/kg/day) calculated with equations above using allometric BW3/4 scaling
gThe CSF (mg/kg/day)"1 was derived from the BMCLhec, the 95% lower bound on the concentration associated with a 10% extra
cancer risk. Specifically, by dividing the BMR (0.10) by the BMDLhed. Thus, representing an upper bound, continuous lifetime
exposure estimate of cancer potency.
4.2.6.2.8 Chronic Cancer Unit Risk for Dermal Exposures i.e. Cancer Slope Factor (CSF)
extrapolated from Chronic Oral Studies
The repeated-dose (oral) combined chronic/carcinogenicity studies were used with route-to-route
extrapolations to derive dermal CSFs. In the discussion that follows, the oral CSFs identified
from the repeated-dose (oral) combined chronic/carcinogenicity studies are discussed in the
context of dose response analyses, followed by the adjustments that were made for performing
route-to-route extrapolations for deriving the dermal CSFs.
Based on data from chronic 2-year drinking water studies in F344 rats and Cij :BDF1 mice (Kama
et al.. 2.009). Sherman rats (Kociba et al. 1974). OM rats and B6C3Fi mice (NCI. 1978). 1,4
dioxane produced a statistically significant increase in incidence and/or a statistically significant
dose-response trend for the following tumor types: nasal squamous cell carcinomas, peritoneal
mesotheliomas, hepatomas, and subcutis fibromas. All tumors were considered of independent
origin and included in the multi-tumor analysis. The incidence of adenomas and carcinomas were
combined according to EPA's Guidelines for Carcinogen Risk Assessment which advises that
etiologically similar tumor types, i.e., benign and malignant tumors of the same cell type, can be
combined due to the possibility that benign tumors could progress to the malignant form (U.S.
EPA. 2005a; McConnell et al.. 1986).
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BMD modeling was used to fit the dose-response data and calculate the POD. The multistage
cancer models available in the BMDS (version 2.704) were fit to the incidence data for each
tumor type observed to determine the degree (e.g., 1st, 2nd, or 3rd) of the multistage model that
best fit the data. In accordance with the EPA Guidelines for Carcinogen Risk Assessment (U.S.
EPA. 2005a). a benchmark response (BMR) of 10% was used to estimate the BMDL10 (the
lower 95% bound on the dose estimated to produce a 10% increase in tumor incidence over
background) and the results of the model that best characterized the cancer incidences were
selected. Suitable multistage model fits were obtained for all tumor types included in the
analysis. Additional information on BMD methods and model selection, and guidance and
criteria used for assessing adequacy of model fit, can be found in Appendix I (Benchmark Dose
Analysis).
Following Guidelines for Carcinogen Risk Assessment (U.S. EPA. 2005a). human equivalent
doses were calculated for each tumor type by multiplying rodent doses by (BWa/BWh)0 25
(where BWa is the bioassay-specific rodent body weight, and BWh is the default human body
weight of 80 kg). The human equivalent dose was used as the point of departure (POD). To
calculate a cancer slope factor (CSF), the benchmark response rate (0.1) was divided by the
POD. A CSF is a plausible upper bound lifetime cancer risk from chronic ingestion of a chemical
per unit of mass consumed per unit body weight, per day (mg/kg day).
Given the multiplicity of tumor sites, basing the overall CSF on one tumor site may
underestimate risk. Consistent with recommendations of the NRC (1994) and EPA's Guidelines
for Carcinogen Risk Assessment (U.S. EPA. 2005a). the total risk and upper bound risk for
multiple tumor sites was estimated in a manner similar to that for inhalation (see above). Briefly,
MS-Combo model (which is implemented using BMDS) was utilized to calculate the dose
associated with a specified composite risk (the risk of developing any combination of tumors at
any site), under the assumption that tumors in different tissues arise independently. For studies
that observed liver tumors, MS-Combo was applied twice to evaluate uncertainties related to
model choice and mechanisms: one MS-Combo model run included all tumors, while an
additional model run excluded liver tumors.
The dose-response modeling results for cancer hazards from oral exposure (Table 4-12) indicate
that the CSF from MS-Combo including or excluding the liver tumors is within a factor of 2.
Female rats appear to be about two times less sensitive than males. The CSF from male rats was,
therefore, selected for the risk characterization.
As shown in Table 4-12, the oral CSFs were converted to dermal CSFs using the following
equation:
Dermal CSF (mg/kg-d)"1 = oral CSF (mg/kg-d)"1 x 3.2% (dermal absorption) ^ 100%
(oral absorption)
The absorption estimates were based on experimental data by the oral (i.e., Young et al., (1978a,
b) and dermal (i.e., Marzulli etal., (1981)) routes of exposure, as previously discussed.
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Overall comparing the calculation of cancer unit risks for dermal exposures by extrapolating
from inhalation (Section 4.2.6.2.7) and oral studies (Section 4.2.6.2.8) results in similar values.
For example, the combined systemic tumors including the liver from the inhalation study has a
CSF of 4.3E-4 mg/kg/day"1 and for the male rats in the Kano et al. 2009) oral study has a CSF of
6.7E-4 mg/kg/day"1. For combined systemic tumors omitting liver for the inhalation study has a
CSF of 3.8E-4 mg/kg/day"1 and for the male rats in the Kano et al. 2009) oral study has a CSF of
4.2E-4 mg/kg/day"1. These are shown in the summary Table 4-12.
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Table 4-12. Dose-response modeling summary results for oral CSFs and route-to-route extrapolated dermal CSFs.
Study (data quality)1
Gender/strain/
species
Endpoint
BMR
MS°
BMD
(mg/kg-
d)
BMDL
(mg/kg-
d)
BWa
(g)
POD2
(mg/kg-
d)
Oral CSF
(mg/kg-d)1
Dermal
CSF3
(mg/kg-
d)1
Nasal squamous cell
carcinoma
10%
2
365
242
65.6
1.5E-03
4.9E-05
Peritoneal
mesothelioma
10%
2
77.7
35.4
9.60
1.0E-02
3.3E-04
Male F344/
Hepatocellular
adenoma or
10%
2
61.7
28.3
432
7.67
1.3E-02
4.2E-04
DuCij rats
carcinoma
Subcutis fibroma
10%
1
154
85.0
23.0
4.3E-03
1.4E-04
MS-Combo
(excluding liver)
10%
N/A
55.2
28.1
7.62
1.3E-02
4.2E-04
MS-Combo
(including liver)
10%
N/A
35.1
17.8
4.83
2.1E-02
6.7E-04
Kano et al. (2009)
(high)
Nasal squamous cell
carcinoma
10%
1
376
214
51.4
1.9E-03
6.2E-05
Mammary gland
adenoma
10%
1
177
99.1
23.8
4.2E-03
1.3E-04
Female F344/
DuCij rats
Hepatocellular
adenoma or
carcinoma
10%
2
79.8
58.1
267
14.0
7.1E-03
2.3E-04
MS-Combo
(excluding liver)
10%
N/A
120
76.5
18.4
5.4E-03
1.7E-04
MS-Combo
(including liver)
10%
N/A
57.6
41.6
10.0
1.0E-02
3.2E-04
Male Crj:BDFl
mice
Hepatocellular
adenoma or
carcinoma
10%
1
71.0
44.0
47.9
6.88
1.5E-02
4.7E-04
Kociba ef al. (1974)
Sherman rats
Nasal squamous cell
carcinomas
10%
2
1981
1314
325
332
3.0E-04
9.6E-06
(high)
(M+F)
Hepatocellular
carcinoma
10%
1
940
584
147
6.8E-04
2.2E-05
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Study (data quality)1
Gender/strain/
species
Endpoint
BMR
MS°
BMD
(mg/kg-
d)
BMDL
(mg/kg-
d)
BWa
(g)
POD2
(mg/kg-
d)
Oral CSF
(mg/kg-d)1
Dermal
CSF3
(mg/kg-
d)1
Female OM
Nasal squamous cell
carcinoma
10%
1
176
122
310
30.4
3.3E-03
1.1E-04
rats
Hepatocellular
adenoma
10%
1
132
94.1
23.5
4.3E-03
1.4E-04
NCI (.1.978) (low)
Male B6C3Fi
mice
Hepatocellular
adenoma or
carcinoma
10%
1
164
117
32
16.5
6.1E-03
1.9E-04
Female B6C3Fi
mice
Hepatocellular
adenoma or
carcinoma
10%
1
49.1
38.8
30
5.40
1.9E-02
5.9E-04
1 Applies to all of the endpoints listed in this table for each study. See Appendix G.
2 POD=dose x (BWa/BWh)0 25. BWh=80 kg. BWa values are study-specific (obtained from Table 5-9 of the 1,4-Dioxane IRIS assessment)
3 Dermal CSF (mg/kg-d)"1 = Oral CSF (mg/kg-d)"1 x 3.2% (dermal absorption) 100% (oral absorption).
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4.2.7 Summary of Human Health Hazards
The results of the hazard identification and dose-response are summarized in Table 4-13.
Table 4-13. Summary of Hazard Identification and Dose-Response Values
KxpOSIII'C
Route
Kiulpoinl Type
1 hi/iiril
POD/MIX VSIopc
Tiiclor'
\ ill 110
I nils
Bench in;irk
moi:1'
liiisis lor Selection
Key Study
Inhalation
Short-term liver
effects
Acute inhalation
PODhec
270
mg/m3
300
(UFl= 10; UFa =
3; UFh = 10)
Study duration
relevant to worker
short-term exposures
(Mattie et aL
2012)
Dermal
Short-term liver
effects
Acute dermal
PODhed
extrapolated from
an inhalation study
1055
mg/kg/day
300
(UFl= 10; UFa =
3; UFh = 10)
Inhalation
Non-Cancer
Human Equivalent
Concentration
(HEC)
1.67
mg/m3
30
(UFa 3= 3; UFH
= 10)
POD relevant for
olfactory epithelium
effects (i.e., metaplasia
and atrophy)
(Kasai et aL
2009)
Cancer
Inhalation Unit
Risk (IUR)
1.18E-06
(Mg/m3)"1
N/A
Result of combined
cancer modeling
(including liver)
(Kasai et aL
2009)
1.03E-06
(Mg/m3)"1
N/A
Result of combined
cancer modeling
(excluding liver)
Dermal
Non-Cancer
Human Equivalent
Dose (HED)
80
mg/kg-d
30
(UFa = 3; UFh =
10)
POD relevant for liver
effects
(Kociba et aL,
1974)
Cancer
Cancer Slope
Factor (CSF)
6.7E-04 (males)
3.2E-4 (females)
(mg/kg-d)1
N/A
Result of combined
cancer modeling- male
rats (including liver)
(Kano et aL
2009)
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KxpOMIIT
Route
Knilpoinl Typo
1 hi/iiril
POD/III-X /Slope
rnctor'
\ ill no
I nils
lion cli m nrk
MOK1'
linsis lor Selection
Key Sluily
extrapolated from
oral studies
4.2E-4 (males)
1.7E-4 (females)
(mg/kg-d)1
N/A
Result of combined
cancer modeling- male
rats (excluding liver)
Cancer Slope
Factor (CSF)
extrapolated from
inhalation studies
4.3E-04 (males)
(mg/kg-d)1
N/A
Result of combined
cancer modeling- male
rats (including liver)
(Kasai et al..
2009)
3.8E-4 (males)
(mg/kg-d)1
N/A
Result of combined
cancer modeling- male
rats (excluding liver)
1 HECs are adjusted from the study conditions as described above in Section 4.2.6.2.
bUFs = subchronic to chronic UF; UFa = interspecies UF; UFh = intraspecies UF; UFl = LOAEL to NOAEL UF (U.S. EPA. 2002)
N/A is shown in the benchmark MOE column for cancer endpoints because EPA did not use MOEs for cancer risks, see Section 5.2 for more information.
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5 RISK CHARACTERIZATION
5.1 Environmental Risk
5.1.1 Aquatic Pathways
The purpose of the environmental risk characterization is to determine whether there are risks
above benchmarks to the aquatic environment from levels of 1,4-dioxane found in surface water
based on the fate properties, relatively high potential for release, and the availability of
environmental monitoring data and hazard data, and to describe any uncertainties or other
considerations relevant to the risk estimate. EPA estimated risks based on a qualitative
assessment of the physical-chemical properties and fate of 1,4-dioxane in the environment for
sediment and land-applied biosolids, and a quantitative comparison of hazards and exposures for
aquatic organisms. These analyses were conducted as part of problem formulation. The results of
the analyses are presented in Sections 3.3.1, 4.1.2, Appendix E and Appendix F.
The environmental risk of 1,4-dioxane is characterized by calculating risk quotients or RQs
(Barnthouse et at.. 1982); the RQ is defined as:
RQ = Environmental Concentration / Effect Level
An RQ equal to 1 indicates that the exposures are the same as the concentration that causes
effects. If the RQ is above 1, the exposure is greater than the effect concentration. If the RQ is
below 1, the exposure is less than the effect concentration. The Concentrations of Concern
(COCs) for aquatic organisms shown in Table 5-1 were used to calculate RQs. The
environmental concentration for surface water is determined based on experimental test data of
1,4-dioxane (Section 4.1.1 and Appendix E).
Table 5-1. Concentrations of Concern (COCs) for Environmental Toxicitv
Knviron menial Toxicity
Most Sensitive l est
( oncent ral ion of ( oncern
((()()
Acute Toxicity, aquatic organisms
96-hour Fish
247,200 |ig/L
Chronic Toxicity, aquatic
32-Day Fish
14,500 |ig/L
organisms
As described in Appendix E and Appendix F, EPA used modeled exposure data that was
calculated from E-FAST, monitored data from STORET, and aquatic concentrations of concern
(COCs) from the reasonably available hazard data to determine the risk of 1,4-dioxane to aquatic
species using risk quotients (RQs) method.
Table 5-2 summarizes the risk quotients (RQs) for the acute and chronic risk of 1,4-dioxane. The
RQ values for acute and chronic risks are 0.046 and 0.397, respectively. Because they are less
than 1, these values indicate that there are no risks of 1,4-dioxane to the aquatic pathways. As
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previously stated, an RQ below 1, indicates that the exposure concentrations of 1,4-dioxane are
less than the concentrations that would cause an effect to organisms in the aquatic pathways.
Table 5-2. Calculated Risk Quotients (RQs) for 1,4-Dioxane
('oncenirations of
Concern (CoC)
Maxiiniiin Concen1ralion
RQ
Acute Risk Scenario
247,200 |ig/L
11,500 |ig/L
0.046
Chronic Risk
Scenario
14,500 |ig/L
5,762 ng/L
0.397
For environmental release pathways, EPA quantitatively evaluated surface water exposure to
aquatic vertebrates, invertebrates and aquatic plants and included a qualitative assessment of
risks to sediment organisms and exposure to 1,4-dioxane in land-applied biosolids.
1,4-Dioxane is expected to be present in the aqueous fraction of biosolids and the pore water
within soil and sediment due to its water solubility (> 800 g/L) and low partitioning to organic
matter (log Koc = 0.4). Biosolids produced by wastewater treatment plants (WWTP) may
contain 1,4-dioxane and aquatic organisms may be exposed to 1,4-dioxane via runoff when
biosolids are applied to land. Although 1,4-dioxane is expected in biosolids, the mass of 1,4-
dioxane in biosolids are expected to be low compared to effluent water (<2% of influent 1,4-
dioxane in biosolids versus ~97>95% of influent 1,4-dioxane in effluent water) due to the water
solubility, partitioning coefficient and volatility of 1,4-dioxane. When 1,4-dioxane is released in
the environment, including with land-applied biosolids, it is expected to be mobile in soil and to
migrate to surface waters and groundwater or volatilize to air. 1,4-Dioxane is expected to
volatilize readily from dry soil and surfaces due to its vapor pressure (40 mm Hg). 1,4-Dioxane
has demonstrated low toxicity to aquatic organisms (acute COC >247 mg/L, chronic COC >14
mg/L), and overall the exposures to surface water from biosolids are estimated to be low.
Therefore, there would be no additional expected risk to aquatic organisms from biosolids.
Limited sediment monitoring data for 1,4-dioxane that are available suggest that 1,4-dioxane is
present in sediments, but just as 1,4-dioxane in biosolids is expected to be in the aqueous phase,
1,4-dioxane in sediment is expected to be in the pore water rather than adsorbed to the sediment
solids. 1,4-Dioxane concentrations in pore water are expected to be similar to the concentrations
in the overlying water. Overall, because 1,4-dioxane is not expected to accumulate in sediments,
sediment-dwelling organisms are not expected to be exposed to a greater concentration of 1,4-
dioxane than aquatic organisms and sediment is not expected to be a source of 1,4-dioxane to
overlying surface water.
5.2 Human Health Risk
5.2.1 Human Health Risk Estimation Approach
Development of the 1,4-dioxane hazard and dose-response assessments considered EPA,
National Research Council (NRC), and European Chemicals Agency (ECHA) risk assessment
guidance. Studies conducted via the inhalation and oral routes of exposure were evaluated in this
assessment. The dose-response assessment used for selection of PODs for non-cancer and cancer
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endpoints and the benchmark dose analyses used in the risk characterization are found in Section
4.2.6.
The use scenarios, populations of interest and toxicological endpoints that were selected for
determining potential risks from acute and chronic exposures presented in Table 5-3.
Table 5-3. Summary of Parameters for Risk Characterization
Populations and
Toxicological Approach
Occupational Exposure Scenarios for 1,4-Dioxane Uses at
Industrial or Commercial Facilities (see Section G.6)
Population of Interest and
Exposure Scenario:
Users:
Acute- Healthy female and male adult workers (>16 vears old)
exposed to 1,4-dioxane for a single 8-hour exposure
Chronic- Healthy female and male adult workers (>16 vears old)
exposed to 1,4-dioxane for the entire 8-hour workday for 260
days per year for 40 working years
Occupational Non-User:
Acute or Chronic- Healthy female and male adult workers (>16
years old) exposed to 1,4-dioxane indirectly by being in the same
work area of the building
Health Effects of Concern,
Concentration and Time
Duration
Acute/Short-term POD:
• Short-term inhalation HEC is 75 ppm (270 mg/m3)
• 2-Week duration of study is relevant to typical short-term
worker exposures
Non-Cancer PODs:
• Inhalation 8-hour HEC: 1.67 mg/m3 (olfactory epithelium
effects (i.e., metaplasia and atrophy) from Table 4-13)
• Dermal 8-hour HEC: 80 mg/kg-d
• Applied the oral 8-hour HEC: 2.56 mg/kg-d [based on
NOAEL for Degeneration and necrosis of renal tubular cells
and hepatocvtes (Kociba et aL 1974)1 adiusted for dermal
absorption (3.2%)
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Health Effects of Concern,
Concentration and Time
Duration (cont.)
Cancer Health Effects.
• Inhalation Unit Risk (from Table 4-9):
- MS-Combo portal of entry + systemic (including liver)
1.18E-6 (iig/m3)"1
- MS-Combo portal of entry + systemic (excluding liver)
1.0E-6 (iig/m3)"1
• Dermal cancer slope factor (from Table 4-12):1
Extrapolated from oral studies:
- MS-Combo, male, including liver: 6.7E-4 (mg/kg-d)"1
- MS-Combo, female, including liver: 3.2E-4 (mg/kg-d)"1
- MS-Combo, male, excluding liver: 4.2E-4 (mg/kg-d)"1
- MS-Combo, female, excluding liver: 1.7E-4 (mg/kg-d)"1
Extrapolated from inhalation studies:
- MS-Combo, male, including liver: 4.3E-4 (mg/kg-d)"1
- MS-Combo, male, excluding liver: 3.8E-4 (mg/kg-d)"1
Non-Cancer Margin of
Exposure (MOE)
Uncertainty Factors (UF)2
Acute/Short-term Inhalation Benchmark MOE = 300
• UFa = 3; UFh = 10; UFl= 10
Chronic Inhalation Benchmark MOE = 30
• UFa = 3; UFh =10
Chronic Dermal Benchmark MOE = 30
• UFa = 3; UFh =10
Cancer Benchmark
Inhalation and Dermal.
• 1 in 10"4 excess cancer risk for worker populations
1 A route-to-route extrapolation was performed on the oral and inhalation cancer slope factors as described above in
Section 4.2.6.2.
2UFA=interspecies uncertainty/variability; UFH=intraspecies uncertainty/variability; UFL=LOAEL-to-NOAEL
uncertainty.
EPA used a Margin of Exposure (MOE) approach to identify potential non-cancer risks. The
MOE is the ratio of the non-cancer POD divided by a human exposure dose, which is then
compared to a benchmark MOE. If the calculated MOE is less than the benchmark MOE, this
indicates potential risk to human health, whereas if the calculated MOE is equal to or greater
than the benchmark MOE, it suggests that the risks are negligible.
The acute and chronic MOE (MOEacute or MOEchronic) for non-cancer inhalation and dermal risk
were calculated using Equation 5-1.
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Equation 5-1 Equation to Calculate Margin of Exposure for Non-Cancer Risks Following
Acute or Chronic Exposures
Non — cancer Hazard value (POD)
M°EaCUte0r chrome = Human Exposure
Where:
MOE = Margin of exposure (unitless)
Hazard value (POD) = HEC (mg/m3) or HED (mg/kg-d)
Human Exposure = Exposure estimate (in mg/m3 or mg/kg-d) from
occupational exposure assessment
The Acute Exposure Concentration (AEC) was used to estimate acute/short-term inhalation risks,
whereas the Average Daily Concentration/Dose (ADC)/D) was used to estimate chronic non-
cancer inhalation/dermal.
EPA used MOEs9 to estimate acute and chronic risks for non-cancer based on the following:
1. the HECs/HEDs identified for the highest quality studies within each health effects domain;
2. the endpoint/study-specific UFs applied to the HECs/HEDs per the review of the EPA
Reference Dose and Reference Concentration Processes (U.S. EPA. 2002): and
3. the exposure estimates calculated for 1,4-dioxane conditions under the conditions of use
(see EXPOSURES Section 3).
MOEs allow for the presentation of a range of risk estimates. The occupational exposure
scenarios considered both acute and chronic exposures. Different adverse endpoints were used
based on the expected exposure durations. For occupational exposure calculations, the 8-hour
TWA was used to calculate MOEs for risk estimates for acute and chronic exposures. For acute
and chronic (non-cancer) effects, potential risks for adverse effects were based on liver toxicity
for both acute and chronic exposures to 1,4-dioxane.
Risk estimates were calculated for liver effects from studies that were rated under the data
quality criteria as "Medium" or "High". Liver toxicity was chosen as the basis from which to
estimate risks because of its human relevance, as discussed in the available acute/short-term
human exposure studies under Section 4.2.3.1.
EPA estimated potential cancer risks from chronic exposures to 1,4-dioxane using probabilistic
approaches, which consisted of calculating the extra cancer risk. Each of these approaches is
discussed below.
Extra cancer risks for repeated exposures to 1,4-dioxane were estimated using Equation 5-2.
Estimates of extra cancer risks are interpreted as the incremental probability of an individual
developing cancer over a lifetime following exposure to 1,4-dioxane (i.e., incremental or extra
individual lifetime cancer risk).
9 Margin of Exposure (MOE) = (Non-cancer hazard value, POD) (Human Exposure). Equation 5-1. The
benchmark MOE is used to interpret the MOEs and consists of the total UF shown in Table 5-3.
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Equation 5-2 Equation to Calculate Cancer Risks
Inhalation Cancer Risk = Human Exposure x IUR
or
Dermal Cancer Risk = Human Exposure x CSF
Where:
Risk = Extra cancer risk (unitless)
Human exposure = Occupational exposure estimate (LADC in |ig/m3)
IUR = Inhalation unit risk (1 x 10"6 per |ig/m3)
CSF = Cancer slope factor (6.7 x 10"4 per mg/kg-d)
The range of IURs considered in Table 5-3 were 1.18 x 10"6 to 1.0 x 10"6 (iig/m3)"1 both rounded
to 1 x 10"6 per |ig/m3 for calculation of inhalation cancer risks. The range of CSFs considered in
Table 5-3 were 1.7 x 10"4 to 6.7 x 10"4 (mg/kg-d)"1 for the different extrapolations from inhalation
or oral studies and for different combinations of tumor types and overall the value of 6.7 x 10"4
(mg/kg-d)"1 was used for calculation of dermal cancer risks
To determine the level of personal protection needed by workers to reduce the high-end
exposures to below the level of concern for non-cancer risks, EPA evaluated the impact of
respirator use. Typical APF values of 10, 25, 50, 100 and 1,000 were compared to the calculated
MOE and the benchmark MOE to determine the level of APF required to reduce exposure so that
risk is below the benchmark MOE. For high-end exposures occurring during industrial use
respirators with an APF of 10 can reduce exposure to levels where the calculated MOE will be
greater than the benchmark MOE.
5.2.2 Risk Estimation for Effects Acute/Short-term Inhalation Exposures
1,4-Dioxane exposure is associated with acute effects. Based on the weight of the scientific
evidence analysis of the reasonably available toxicity studies from humans and animals, the key
acute/short-term exposure effect is liver toxicity (i.e., single cell necrosis).
The study that serves as the basis for acute/short-term health concerns (Mattie et al.J ) is of
high data quality. Risk estimates for acute inhalation exposures to 1,4-dioxane were determined
for the occupational exposure scenarios. Based on the POD reported by Mattie et al. (2012) (i.e.,
LOAEC = 378 mg/m3), EPA calculated an acute HEC of 270 mg/m3 and an acute inhalation
benchmark MOE of 300.
Comparing the 8-hour acute exposures (AEC concentrations) for the use scenarios to the
acute/short-term HEC for liver effects gives the calculated MOEs shown in Table 5-4. The
calculated MOEs for import/repackaging, industrial use, film cement, and disposal were below
the benchmark MOE for both the central tendency and high-end exposures. The calculated MOEs
for manufacturing, laboratory chemicals, and dry film lubricants were below the benchmark
MOE for the high-end exposures.
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Table 5-4. MOE for Acute/Short-term Inhalation Exposures; Benchmark MOE = 300
Kisk Kslimale
Scenario
Kxposurc
Duration
for AIX
(I")
Central
Tendency
(( T) u:c
(nig/nr')
lligh-
end
(III)
AIX
(in «/nr!)
Calculated
moi:
(Central
Tendency)
Calculated
MOI.
(High-
land)
Calculated
moi:
(Central
Tendency)
UespiratoH
Calculated
MOI.
(Iligh-Knd)
UespiratoH
Manufacturing
8
0.42
7.73
651
35
6506
(APF 10)
349
(APF 10)
Import/Repackaging
(Bottle)
8
9.28
33.1
29
8
727
(APF 25)
408
(APF 50)
Import/Repackaging
(Drum)
8
10.6
38.2
25
7
634
(APF 25)
354
(APF 50)
Industrial Use
8
5.0
20
54
14
540
(APF 10)
338
(APF 25)
Open System
Functional Fluids
8
0.0011
0.0038
253339
71214
—
—
Spray Foam
Application
8
0.0097
0.012
27755
22845
—
—
Lab Chemicals
8
0.11
5.7
2455
47
24545
(APF 10)
470
(APF 10)
Film Cement
8
1.52
2.81
177
96
1774
(APF 10)
962
(APF 10)
Use of Printing Inks
(3D) c
8
0.0972*
2778
—
Dry Film Lubricant
8
0.47
1.60
577
169
5769
(APF 10)
1685
(APF 10)
Disposal
8
1.1
4.1
236
67
2357
(APF 10)
666
(APF 10)
Bold: Calculated MOEs were below the benchmark MOE.
In Scenarios where MOEs are greater than the benchmark MOE without a respirator not MOEs are shown.
* EPA cannot determine the statistical representativeness of the values given the small sample size.
* MOEs with respirator use were calculated by multiplying the MOE without a respirator by the respirator APF
5.2.3 Risk Estimation for Non-Cancer Effects Following Chronic Inhalation
Exposures
Chronic non-cancer risk estimates for inhalation exposures to 1,4-dioxane were derived for
occupational scenarios using estimated inhalation average daily concentrations (ADCs). The
central and high-end ADC exposure estimates were compared to the inhalation hazard POD of
1.67 mg/m3 using a benchmark MOE of 30. Table 5-5 shows the exposure estimates used. The
definition of high-end exposures varies by exposure scenario as to the percentile of the
distribution. Table 5-5 shows the calculated MOEs for central and high-end exposures. The
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calculated MOE for Open System Functional Fluids and Spray Application were greater than the
benchmark MOE for central tendency and high-end estimates. The calculated MOEs for other
exposure scenarios were below the benchmark MOE for central tendency and high-end
estimates.
To determine the level of personal protection needed by workers to reduce the high-end
exposures to below the level of concern for non-cancer risks, EPA evaluated the impact of
respirator use. Typical APF values of 10, 25, 50 and 1,000 were compared to the calculated
MOE and the benchmark MOE to determine the level of APF required to reduce exposure so that
risk is below the benchmark MOE. For dry film lubricant use respirators with APF 10 reduce
central tendency and high-end exposures to levels where the calculated MOEs are greater than
the benchmark MOE. For central tendency exposures occurring during all other uses except for
industrial use respirators with an APF of 50 can reduce exposure to levels where the calculated
MOE will be greater than the benchmark MOE. For high-end exposures respirators with an APF
of 50 except for film cement do not reduce exposure to levels where the calculated MOE will be
greater than the benchmark MOE. For industrial use exposures at central tendency and high-end
respirators with an APF of 50 do not reduce exposure to levels where the calculated MOE will be
greater than the benchmark MOE
Table 5-5. Chronic Inhalation Exposure Risk to Workers: Non-Cancer; benchmark
MOE=30
Kxposnre Scenario
Ccntr;il
Tendency
ADC
(111"/!!!'")
1 liuh-
eiid1
ADC
(m»/m()
Ciilcnhiled
moi:
(CoilI Till
Tendency)'1
Cidciihiled
moi:
(Ilioh-
Knd)'1
Cidciihiled
MOK (Central
Tendency)
kespirnlori
Cidcnhited
MOK (lli»h-
Knd)
kespimlori
Manufacturing
0.40
7.44
4.2
0.23
42
(APF 10)
11
(APF 50)
Import/Repackaging
0.46
3.39
3.6
0.49
36
(APF 10)
25
(APF 50)
Industrial Use
4.81
19.23**
0.35
0.09
17
(APF 50)
4.3
(APF 50)
Open System Functional
Fluids
0.0010
0.0037
1630
458
--
--
Spray Application
0.009
0.01
179
147
--
--
Lab Chemicals
0.11
5.53***
16
0.30
158
(APF 10)
15
(APF 50)
Film Cement
1.46
2 70****
1.1
0.62
57
(APF 50)
31
(APF 50)
Use of Printing Inks
(3D)
0.093*
18
179
(APF 10)
Dry Film Lubricant
0.1
0.35
17
4.8
166
(APF 10)
48
(APF 10)
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Kxposnre Scenario
Central
Tendency
ADC
(m»/m()
1 Moll-
end1
ADC
(m»/m()
Calculated
moi:
(CoilI Till
Tendency)-1
Cidciihiled
moi:
(Ilioh-
Knd)''
Calculated
MOK (Central
Tendency)
Respiratori
Cidciihiled
MOI-! (lli»h-
End)
Respiratori
Disposal
1.10
3.90
1.5
0.43
38
(APF 25)
21
(APF 50)
Bold: Calculated MOEs were below the benchmark MOE.
" Calculated MOEs were with Equation 5-1 briefly that is: "Central Tendency ADC (|ig/m3)" or "High-end ADC
(|ig/m;')" POD (ng/m3)
In Scenarios where MOEs are greater than the benchmark MOE without a respirator not MOEs are shown.
* EPA cannot determine the statistical representativeness of the values given the small sample size.
** The risk assessment did not provide details about how these values were calculated, therefore, it is unclear what
percentile is represented when an exposure is described as "reasonable worst case."
***For this scenario the high-end was the 90th percentile.
****Forthis scenario the high-end was the maximum value.
* MOEs with respirator use were calculated by multiplying the MOE without a respirator by the respirator APF
As shown in Table 5-6, all exposure scenarios for ONUs resulted in calculated MOEs that were
greater than the benchmark MOE. Exposure data for ONUs were not available for the exposure
scenarios: Manufacturing, Import/Repackaging, Industrial Use, Lab Chemicals, Use of Printing
Inks (3D) and Disposal and therefore these exposure scenarios are shown as " in Table 5-6
below.
Table 5-6. Inhalation Exposure Risk to Occupational Non-Users: Non-Cancer; Benchmark
MOE = 30
Exposure Scenario
Central
Tendency
A IK
(in «/m')
Nigh-end
A IK
(m«/m')
Calculated
moi:
(Central
Tendency)
Calculated
MOI. (lli«h-
Ind)
Ciilcnhiled
.MOK (Central
Tendency)
Respiratori
Calculated
MOI! (lli»li-
Knd)
Respiratori
Manufacturing
-
-
-
-
-
-
Import/Repackaging
-
-
-
-
-
-
Industrial Use
-
-
-
-
-
-
Open System
Functional Fluids
0.00014
0.00024
11,642
6902
-
-
Spray Application
0.0018*
926
-
Lab Chemicals
-
-
-
-
-
-
Film Cementc
0.10*
17
167
(APF 10)
Use of Printing Inks
(3D)
-
-
-
-
-
-
Disposal
-
-
-
-
-
-
* EPA cannot separately determine a central tendency and high-end estimate.
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* MOEs with respirator use were calculated by multiplying the MOE without a respirator by the respirator APF
5.2.4 Risk Estimation for Cancer Effects Following Chronic Inhalation Exposures
Chronic cancer risk estimates for inhalation exposures to 1,4-dioxane were derived for
occupational scenarios using estimated inhalation lifetime average dose concentrations (LADC).
Cancer risk was calculated for the central and high-end LADC exposure estimates. Table 5-7
shows the calculated cancer risks for central and high-end exposures. The definition of high-end
percentile of the exposure distribution varies by exposure scenario. The cancer risks for central
tendency and high-end exposures of the following scenarios were above the benchmark of 1E-
04: Manufacturing, Import/Repackaging, Industrial Use, Film Cement and Disposal. The cancer
risks for high-end exposures of the following scenarios were above the benchmark of 1E-04: Lab
Chemicals and Dry Film Lubricant. The cancer risks of the following scenarios were below the
benchmark of 1E-04: Open System Functional Fluids, Spray Foam Application and Use of
Printing Inks (3D).
To determine the level of personal protection needed by workers to reduce exposures to below
the level of concern for cancer risks, EPA evaluated the impact of respirator use. Typical APF
values of 10, 25, 50 and 1,000 were compared to the calculated cancer risks and the benchmark
of 1E-4 to determine the level of APF required to reduce exposure so that risk is below the
benchmark. For scenarios with central tendency cancer risks greater than 1E-4 respirators of APF
10 or 25 reduce exposures to levels where the cancer risks are less than the benchmark. For
scenarios with high-end cancer risks greater than 1E-4 respirators of APF 25 or 50 reduce
exposures to levels where the cancer risks are less than the benchmark. For industrial use high-
end exposures respirators with an APF of 50 have a cancer risk of 2E-4, exceeding the
benchmark of 1E-4.
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Table 5-7. Inhalation Exposure Risk Estimates to Workers: Cancer; Benchmark Risk = 1 in 104
Uisk Scenario
Central
Tendency
L A IK
(ii«/m')
Iligh-Knd
LA IX
(iiil/nr5)
Cenlral
Tendency
Cancer Uisk"
Iligh-Knd
Cancer Uisk"
Cenlral
Tendency
Cancer Uisk
Respirator1'
Iligh-Knd
Cancer Uisk
Respirator1'
Manufacturing
159
3814
1.6E-04
3.8E-03
1.6E-05
(APF 10)
7.6E-05
(APF 50)
Import/Repackaging
175
1,319
1.8E-04
1.3E-03
1.8E-05
(APF 10)
5.3E-05
(APF 25)
Industrial Use
1,911
9,862
1.9E-03
9.9E-03**
7.6E-05
(APF 25)
2.0E-04
(APF 50)
Open System
Functional Fluids
0.39
1.5
3.9E-07
1.5E-06
-
-
Spray Foam
Application
3.6
5.3
3.6E-06
5.3E-06
-
-
Lab Chemicals
42
2,835
4.2E-05
2.8E-03***
-
5.7E-05
(APF 50)
Film Cement
601
1,384
6.0E-04
1.4E-03****
6.0E-05
(APF 10)
5.5E-05
(APF 25)
Use of Printing Inks
(3D)
37
48
3.7E-05
4.8E-05*
-
-
Dry Film Lubricant
40
177
4.0E-05
1.8E-04
-
1.8E-05
(APF 10)
Disposal
417
1,545
4.2E-04
1.6E-03
4.2E-05
(APF 10)
6.2E-05
(APF 25)
Bold: Calculated MOEs were below the benchmark MOE.
" Cancer risk was calculated as follows: "Central Tendency LADC (|ig/nf')" or "High-end LADC (ng/m3)" x IUR (i.e., 1 x 10"6 per |ig/m3)
b Cancer risk with a respirator use was calculated by dividing the cancer risk by the APF
When calculated cancer risks were < 1E-4 without a respirator the risks with a respirator are not shown
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* EPA cannot determine the statistical representativeness of the values given the small sample size.
** The risk assessment did not provide details about how these values were calculated, therefore, it is unclear what percentile is represented when an exposure is
described as "reasonable worst case."
***For this scenario the high-end was the 90th percentile.
****For this scenario the high-end was the maximum value.
As shown in Table 5-8, all exposure scenarios for ONUs resulted in cancer risks less than or equal to 1E-4. Exposure data for ONUs
were not available for the exposure scenarios: Manufacturing, Import/Repackaging, Industrial Use, Lab Chemicals, Use of Printing
Inks (3D) and Disposal and therefore these exposure scenarios are shown as " in Table 5-8 below.
Table 5-8. Inhalation Exposures to Occupational Non-Users: Cancer; Benchmark Risk = 1 in 104
Uisk Scenario
OM population
Central Tendency
LADC
(ug/ni')
Nigh-Kml LADC
(u«/m')
Central Tendency
Cancer Uisk"
Nigh-Kml Cancer
Uisk1
Manufacturing
-
-
-
-
-
Import/Repackaging
-
-
-
-
-
Industrial Use
-
-
-
-
-
Open System
Functional Fluids
178,000
0.06
0.12
5.7E-08
1.2E-07
Spray Foam
Application
15627
0.72
0.92
7.2E-07
9.2E-07
Lab Chemicals
-
-
-
-
-
Film Cement
10
40
50
3.98E-05
5.14E-05
Use of Printing Inks
(3D)
-
-
-
-
-
Dry Film Lubricant
-
-
-
-
-
Disposal
-
-
-
-
-
a Cancer risk was calculated as follows: "Central Tendency LADC (|ig/m3)" or "High-end LADC (|ig/m3)" x IUR (i.e.. 1 x 10~6 per |ig/m3)
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5.2.5 Risk Estimation for Non-Cancer Effects Following Acute/Short-term Dermal
Exposures
1,4-Dioxane exposure is associated with acute effects. Based on the weight of the scientific
evidence analysis of the reasonably available toxicity studies from humans and animals, the key
acute/short-term exposure effect is liver toxicity (i.e., single cell necrosis).
The study that serves as the basis for acute/short-term health concerns from dermal exposures is
an inhalation study (Mattie et ai. ^ ) extrapolated to dermal exposures. Risk estimates for
acute dermal exposures to 1,4-dioxane were determined for the occupational exposure scenarios.
Based on the POD reported by Mattie et al. ( ) (i.e., LOAEC = 378 mg/m3), EPA calculated
an acute dermal HED of 1055 mg/kg/day and an acute dermal benchmark MOE of 300.
Comparing the 8-hour acute retained dose (ARD) for the use scenarios to the acute/short-term
HED for liver effects gives the calculated MOEs shown in Table 5-9. The calculated MOEs for
import/repackaging, industrial use, film cement, and disposal were below the benchmark MOE
for both the central tendency and high-end exposures. The calculated MOEs for manufacturing,
laboratory chemicals, and dry film lubricants were below the benchmark MOE for the high-end
exposures. The results are shown in Table 5-9.
Table 5-9. Dermal Exposure Risk Estimates to Workers: for Acute/Short-term Exposures
Non-Cancer; Benchmark MOE = 300
Condition ol° I so /
liin
No (iloM'N
(H; 1)
Pmlecli\e (ilo\os
(H; 5)
Pro(ec(i\e (Jo\es.
( ommoiviid I soi s
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5.2.6 Risk Estimation for Non-Cancer Effects Following Chronic Dermal
Exposures
The dermal 8-hour HEC is extrapolated from the oral 8-hour HEC of 2.56 mg/kg-d based on
degeneration and necrosis of renal tubular cells and hepatocytes were calculated using route-to-
route extrapolation from the oral POD (Kociba et at... 1974). The POD for hepatocellular effects
of 2.56 mg/kg/day for oral exposures was extrapolated to estimate a dermally applied dose by
adjusting for the differences in absorption between the oral and dermal routes. Oral absorption
was estimated to be nearly complete by Young et al. (1978a. b) in a study in rats, no data are
available in humans and so 100% oral absorption was used. Dermal absorption was estimated in
a human in vitro skin assay described in Section 4.2.2 (Bronaugh. 1982) measured penetration of
1,4-dioxane through excised human skin to be 3.2% of the applied dose for occluded skin, and
0.3%) for unoccluded skin. The occluded absorption value is also consistent with another
unoccluded measured absorption value in monkeys in vivo (2-3%) (Marzulli et al.. 1981).
Considering the uncertainties in the oral-to-dermal extrapolation, EPA chose to use 3.2% for the
dermal absorption factor. The actual absorption could be ten-fold lower based on the Bronaugh
in vitro study (Bronaug t). Therefore, the applied human equivalent dose was calculated as
follows: oral POD of 2.56 mg/kg/day X 100% oral absorption / 3.2% dermal absorption = 80
mg/kg/day.
The skin is a very complex and dynamic human organ composed of an outer epidermis and inner
dermis with functions well beyond that of just a barrier to the external environment. Dermal
absorption depends largely on the barrier function of the stratum corneum, the outermost
superficial layer of the epidermis, and is modulated by factors such as skin integrity, hydration,
density of hair follicles and sebaceous glands, thickness at the site of exposure assessment,
physiochemical properties of the substance, chemical exposure concentration, and duration of
exposure. The workplace protection factor for gloves is based on the ratio of uptake through the
unprotected skin to the corresponding uptake through the hands when protective gloves are worn.
Assessments using the mass loading of chemical on the skin and glove surface could be
undertaken by the mass or area of skin contamination with and without gloves would indicate a
reduction of mass loading or area exposure rather than protection. The exposure assessments
were conducted considering vapor pressure and other physical-chemical properties, of 1,4-
dioxane. Due to increased area of contact and reduced skin barrier properties, and repeated skin
contact with chemicals could have even higher than expected exposure if evaporation of the
carrier occurs and the concentration in contact with the skin increases. In the workplace the
wearing of gloves could have important consequences for dermal uptake. If worker is handling a
chemical without any gloves, a splash of the liquid or immersion of the hand in the chemical may
overwhelm the skin contamination layer so that the liquid chemical essentially comprises the
skin contamination layer. If the material is undiluted, then uptake could proceed rapidly as there
will be a large concentration difference between the skin contamination layer and the peripheral
blood supply. Conversely, if the contaminant material is in a dilute form, there will be relatively
slow uptake. If the worker is wearing a glove the situation will be different. In case the chemical
comes into contact with the outer glove surface, there will be no flux into the inner glove
contamination layer until the chemical breaks through. The chemical could partition into the
glove and then diffuse towards the inner glove surface; then it could partition into the skin
contamination layer. Diffusion through the stratum corneum is dependent on the concentration.
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The glove protection factor is unlikely to be constant for a glove type but could be influenced by
the work situation and the duration of the exposure.
Table 5-10 outlines the non-cancer dermal risk estimates to workers for endpoints with and
without gloves.
Table 5-10. Dermal Exposure Risk Estimates to Workers: Non-Cancer;
Benchmark MOE = 30
( nndilinn ol' I so /
Kin
No (iloM'N
(H; 1)
Pmiecihe (.lo\cs
(H; 5)
Prn(ec(i\e (Jo\es.
( ommorciiil I scrs
(Ml 10)
Prn(ec(i\e (Jn\es.
Iiidusli'iiil I sois
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Table 5-11. Dermal Exposure Risk Estimates to Workers: Cancer
Condition of I so /
Bin
No (iloM'S
(PI' 1)
IVotOClnO (ilo\OS
r in)
I'roloctno (llo\os,
Iniluslriiil I sors
d>r :<))
Manufacturing
7.3E-03
1.5E-03
7.3E-04
3.6E-04
Import/Repackagin
g (Bottles/Drum)
9.3E-04/ 1.7E-03
1.9E-04/ 3.4E-04
9.3E-05/ 1.7E-04
4.6E-05/ 8.4E-05
Industrial Use
7.3E-03
1.5E-03
7.3E-04
3.6E-04
Functional Fluids
(Open System)
7.3E-06
1.5E-06
7.3E-07
3.6E-07
Lab Chemical Use
8.0E-03
1.6E-03
8.0E-04
4.0E-04
Use of Printing
Inks (3D)
8.0E-03
1.6E-03
8.0E-04
4.0E-04
Spray Foam
Application
8.0E-06
1.6E-06
8.0E-07
4.0E-07
Film Cement
4.0E-03
7.9E-04
4.0E-04
2.0E-04
Dry Film Lubricant
1.6E-03
3.3E-04
1.6E-04
8.1E-05
Disposal
7.3E-03
1.5E-03
7.3E-04
3.6E-04
Bold: Cancer risk exceeds the benchmark of 1 x 10~4.
5.3 Assumptions and Key Sources of Uncertainty
The characterization of assumptions, variability and uncertainty may raise or lower the
confidence of the risk estimates. This section describes the assumptions and uncertainties in the
exposure assessment, hazard/dose-response and risk characterization.
5.3.1 Occupational Exposure Assumptions and Uncertainties
EPA addressed variability in the occupational exposure models by identifying key model
parameters to apply a statistical distribution that mathematically defines the parameter's
variability. EPA defined statistical distributions for parameters using documented statistical
variations where available. Uncertainty is "the imperfect knowledge or lack of precise knowledge
of the real world either for specific values of interest or in the description of the system" (40
CFR § 702.33). It can be described qualitatively or quantitatively (U.S. EPA. 2001). The
following sections discuss uncertainties in each of the assessed 1,4-dioxane use scenarios.
Number of Workers and ONUs
There are a number of uncertainties surrounding the estimated number of workers potentially
exposed to 1,4-dioxane, as outlined below.
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First, BLS' OES employment data for each industry/occupation combination are only available
at the 3-, 4-, or 5-digit NAICS level, rather than the full 6-digit NAICS level. This lack of
granularity could result in an overestimate of the number of exposed workers if some 6-digit
NAICS are included in the less granular BLS estimates but are not, in reality, likely to use 1,4-
dioxane for the assessed applications. EPA addressed this issue by refining the OES estimates
using total employment data from the U.S. Census' SUSB. However, this approach assumes that
the distribution of occupation types (SOC codes) in each 6-digit NAICS is equal to the
distribution of occupation types at the parent 5-digit NAICS level. If the distribution of workers
in occupations with 1,4-dioxane exposure differs from the overall distribution of workers in each
NAICS, then this approach will result in inaccuracy. Furthermore, market penetration data was
unavailable, therefore, EPA was unable to estimate the number of establishments within each
NAICS code that used 1,4-dioxane instead of other chemicals. This would result in a systematic
overestimation of the count of exposed workers. For manufacturing and import/re-packaging,
CDR data provided information to better estimate the number of workers.
Second, EPA's judgments about which industries (represented by NAICS codes) and
occupations (represented by SOC codes) are associated with the uses assessed in this report are
based on EPA's understanding of how 1,4-dioxane is used in each industry. Designations of
some industries/occupations with few exposures might erroneously be included, or some
industries/occupations with exposures might erroneously be excluded. This would result in
inaccuracy but would be unlikely to systematically either overestimate or underestimate the
count of exposed workers.
Analysis of Exposure Monitoring Data
This report uses existing worker exposure monitoring data to assess exposure to 1,4-dioxane
during manufacturing, industrial use, open system functional fluid, laboratory chemical, film
cement, and 3D printing ink applications. To analyze the exposure data, EPA categorized each
PBZ and area data point as either "worker" or "occupational non-user." The categorizations are
based on descriptions of worker job activity as provided in literature and EPA's judgment. In
general, PBZ samples are categorized as "worker" and area samples are categorized as
"occupational non-user."
Exposure data for ONUs were not available for most scenarios. EPA assumes that these
exposures are expected to be lower than worker exposures, since ONUs do not typically directly
handle the 1,4-dioxane nor are in the immediate proximity of 1,4-dioxane. Only inhalation
exposures to vapors are expected, which will likely be less than worker exposures.
Some data sources may be inherently biased. For example, NIOSH HHEs for the open system
functional fluids and film cement uses were conducted to address concerns regarding adverse
human health effects reported following exposures during use. Both HHEs were requested by
relevant workers' unions (United Paperworkers International Union and Film Technicians
Union, respectively).
The 2002 EU Risk Assessment (ECJRC. 2002). did not provide complete datasets. This
assessment provided limited summary statistics for different datasets, i.e. a range of the
monitoring data, an arithmetic average or median, and the 90th percentile. The report provided
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limited information about processes involved in each dataset with corresponding worker
activities. Finally, this report provided recommendations for "typical" and "reasonable worst
case" exposures but did not provide details for how these values were calculated.
Because of these limitations, EPA acknowledges that the reported inhalation exposure
concentrations for the industrial scenario uses may not be representative for the exposures in all
industries within that group, the pharmaceutical industry in particular.
Some scenarios have limited exposure monitoring data in literature, if any (i.e., use in 3D
printing inks). Where there are few data points available, it is unlikely the results will be
representative of worker exposure across the industry depending on the sample collection
location (PBZ or source zone), monitoring time and other conditions to represent the work
situation and the duration of the exposure.
The 95th and 50th percentile exposure concentrations were calculated using reasonably available
data. The 95th percentile exposure concentration is intended to represent a high-end exposure
level, while the 50th percentile exposure concentration represents typical exposure level. The
underlying distribution of the data, and the representativeness of the available data, are not
known.
EPA calculated ADC values assuming a high-end exposure duration of 260 days per year over
40 years and LADC values assuming a high-end exposure duration of 260 days per year over 78
years. Repackaging and import is an exception, since the exposure duration depends on the
number of containers being unloaded. The high-end exposure duration value for this exposure
scenario is 90 days (one container unloaded per day). See Section 3.4.1.3 for more information.
This assumes the workers and occupational non-users are regularly exposed during their entire
working lifetime, which likely results in an overestimate. Individuals may change jobs during
their career such that they are no longer exposed to 1,4-dioxane, and that actual ADC and LADC
values become lower than the estimates presented.
Modeling Dermal Exposures
The EPA Dermal Exposure to Volatile Liquids Model used for modeling dermal exposures offers
an improvement over the existing EPA 2-Hand Dermal Exposure models by accounting for the
effect of evaporation on dermal absorption for volatile chemicals and the potential exposure
reduction due to glove use. The passage of a chemical through the skin barrier is dependent on
many factors. The skin is not uniform in terms of thickness. For example, epidermis to dermis
ratio, density of hair follicles, and many other parameters could affect permeability. Other factors
that could influence the dermal uptake include temperature and the presence of other materials
on the skin. A detailed description of dermal exposure assessment method is shown in Appendix
G.7. To address the uncertainty due to lack of monitoring data, a film-thickness approach was
used. This approach considered a thin film of product on a defined skin area. A multiplicative
factor was incorporated to the EPA model to include the proportion of 1,4-dioxane remaining on
the skin after the bulk liquid has fallen from the hand that cannot be removed by wiping the skin.
The model assumes an infinite dose scenario and does not consider the transient exposure and
exposure duration effect.
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5.3.2 Environmental Hazard and Exposure Assumptions and Uncertainties
The available environmental toxicity data for 1,4-dioxane indicate that the hazard to aquatic
organisms is low. While the EPA has determined that sufficient data are available to characterize
the overall environmental hazards of 1,4-dioxane, there are limited chronic toxicity studies
available for assessing the long-term effects of 1,4-dioxane to aquatic species that may create
some uncertainty associated with this assessment.
As described in Appendix E and Section 3.3.1, a screening-level aquatic exposure assessment
was undertaken during problem formulation to evaluate ecological exposures in the U.S. that
may be associated with releases of 1,4-dioxane to surface waters.
This assessment was intended as a first-tier, or screening-level, evaluation. Discharging or
releasing facilities were chosen from two data sources: EPA's Discharge Monitoring Report
(DMR) and Toxic Release Inventory (TRI). The top ten (by annual release/discharge amount)
facilities were selected for use in exposure modeling; therefore, not all reporting sites were
modeled, and the selected sites were not cross-walked with the conditions of use included in the
occupational engineering assessment. These top dischargers were selected from two recent
complete years of TRI and DMR reporting, which at the time of modeling included 2014-2015
for TRI and 2015-2016 for DMR.
EPA's Exposure and Fate Assessment Screening Tool, Version 2014 ( 14c) was
used for predicting stream concentrations resulting from the selected releasers. The predicted
stream concentrations reflect concentrations in the receiving water body at the point of the
release, incorporating any immediate dilution based on stream flow. Downstream transport
and/or dilution are not modeled, nor are any post-release fate or removal processes such as
degradation, photolysis, hydrolysis, or volatilization.
For the purposes of this assessment, the number of release days was assumed, based on
conservative assumptions. The reported annual release amounts from TRI and DMR were
converted to kg and divided by the assumed number of release days (1, 20, or 250) to obtain the
necessary kg/site-day release input. The reported facility annual loading estimates in lbs/year are
provided in a supplemental file titled 1,4-D Supplemental - Aq Screen Facility Information
062419 and the release inputs are shown in Tables E-3 and E-4 of Appendix E. These
assumptions are not based on associated industry-specific data or standards, but on screening-
level assumptions to capture worst-case environmental concentrations for acute and chronic
release scenarios. 1 day of release is the worst-case release assumption for an acute scenario,
appropriate for comparison against an acute COC, while 20 days of release is the worst-case
release assumption for a chronic scenario, appropriate for comparison against a chronic COC.
250 days of release may be more typical for facilities that operate and release effluent frequently,
such as POTWs or treatment plants.
5.3.3 Human Health Hazard Assumptions and Uncertainties
Data are limited for some chronic toxicological endpoints; while not required here, there is no
multi-generation reproductive/developmental study. In the only available developmental study,
effects of 1,4-Dioxane (Giavini et al., 1985) included delayed ossification of the sternebrae and
reduced fetal body weight only at the highest dose (1000 mg/kg-day) in the presence of slight
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maternal toxicity. While no currently available data support the teratogenicity of 1,4-Dioxane,
data limitations exist for reproductive and developmental endpoints, including
neurodevelopmental effects.
The main source of uncertainty for the human health hazard is the mode of action (MO A) and
selection of linear or non-linear models for BMD modeling to determine the dose-response
relationship at low doses. MOA information was only available for liver effects, mutagenicity
and tumor formation with no information available to inform the MOA for other tumor types.
There is uncertainty on whether the toxic moiety is 1,4-dioxane or one or more metabolites and
whether the key events include cytotoxicity in the progression to observed tumors.
Metabolic saturation is a proposed event for 1,4-dioxane effects on the liver and tumor
formation. It is unknown whether metabolism is required or not for cancer induction. If
metabolism is required, then metabolic saturation may reduce rather than enhance potency at
high doses.
In the reasonably available studies for inhalation and oral cancer hazard, there were issues such
as mortality at the high doses (NCI. 1978; Kociba et al.. 1974). EPA was unable to use the data
from male rats in the NCI (1978) study due to high levels of mortality, and the doses were too
close together due to drinking water intake.
EPA performed BMD modeling for data on all endpoints (Kano et al.. 2009; Kasai et al.. 2.009)
as relevant to humans. EPA ran the multi-tumor BMD models with and without liver tumors to
determine the sensitivity of the result to the inclusion of liver tumors. For some tumors, the
human relevance and/or pathology is not well understood such as mixed cell foci and subcutis
fibroma, which is a skin tumor that occurred following both inhalation and oral exposure.
Subcutis fibromas were observed in both oral and inhalation studies of chronic duration. The
high concentration group for subcutis fibroma inhalation data (Kasai et al.. 2.009) was omitted
from the dose-response analysis ( 2013b). The incidence data were monotonic non-
decreasing functions of dose for the control (0 ppm), low (50 ppm), and mid-dose (250 ppm);
however, the incidence rate at the high dose (1,250 ppm) was lower than observed at the mid-
dose. No BMDS model exhibited reasonable fit to the data without dropping the high dose. The
need to drop the high dose creates uncertainty regarding the endpoint.
Nasal tumors were seen in both oral and inhalation studies of chronic duration. The MOA for
nasal tumors is uncertain. It has been suggested that direct exposure of the nasal tissues to liquid
during drinking water studies of 1,4-dioxane where sipper tubes have been used may
confounded findings at the portal of entry in the nose (Sweeney et al.. 2008). However, nasal
tumors occurred in both oral and inhalation studies and 1,4-dioxane is volatile chemical and it is
unknown how much of drinking water exposure may be due to liquid, vapor, or aerosols.
There are a number of datasets where effect incidence was only observed in the highest exposure
group [zymbal gland adenomas and renal cell carcinomas from the inhalation data by Kasai et al.
(2009). cortical tubule degeneration from the oral data by NCI (1978). and nasal tumors from the
oral data by Kano et al. (2009) and Kociba et al. (1974)1.
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5.3.4 Risk Characterization Assumptions and Uncertainties
For cancer risk estimates, in the absence of a known MOA for liver tumors or other tumor types,
a linear low-dose extrapolation approach was used to estimate the dose-response at doses below
the observable range. There was a high degree of uncertainty in any of the MOA hypotheses
considered in this evaluation (e.g., mutagenic mode of action or threshold response to
cytotoxicity and regenerative hyperplasia for liver tumors). Linear extrapolation is the default
approach when there is uncertainty about the MOA. 1,4-Dioxane is a multi-site carcinogen and
may have more than one MOA. EPA estimates for excess cancer risk were based on the
assumption of linearity in the relationship between 1,4-dioxane exposure and the probability of
cancer. However, to understand the impact of the liver tumors on the modeling, EPA presents
cancer risk estimates that do not include the liver tumors. As seen in Table 4-9, the impact of
assuming these tumors should not be modeled using a linear approach has a minimal impact on
the overall cancer risk estimate.
Chronic non-cancer risk estimates from inhalation exposures were based on portal of entry
effects in the respiratory tract. These effects are relevant to inhalation exposures and are more
sensitive than the observed systemic effects. The respiratory tract effects were based on a
LOAEC and a NOAEC were not able to be estimated with modeling. The LOAEC was used with
an uncertainty factor for LOAEC to NOAEC extrapolation. If EPA chose a non-cancer
benchmark with less uncertainty for chronic scenarios (e.g., liver endpoint with a MOE of 30),
EPA would not have risks for inhalation effects.
Several uncertainties affected the dermal risk assessment. Evaporation from skin is assumed to
occur (if in an aqueous solution, evaporation may be less likely). Route-to-route extrapolation
was used as recommended in the Risk Assessment Guidance for Super fund Volume I: Human
Health Evaluation Manual (Part E, Supplemental Guidance for Dermal Risk Assessment) (TJ. S.
EPA. 2004). Oral to dermal route-to-route extrapolation assumes that the oral route of exposure
is most relevant to dermal exposures. Metabolism occurs in both oral and dermal routes and
inhalation is not as relevant to dermal as absorption is more rapid by inhalation.
Dermal absorption was a source of uncertainty in the dermal risk assessment for both dermal
cancer and noncancer estimates of risk. Absorption was first modeled based on physical-
chemical properties, mainly the volatility and the chemical that is not evaporated is assumed to
be absorbed through the skin. EPA also applied measured dermal absorption values from in vitro
studies. The studies have uncertainties in the measurements- low number of animals used, did
not account for metabolism in the radiolabeled study- but are the best available data on dermal
absorption.
Workers were identified as relevant potentially exposed or susceptible subpopulations, but EPA
did not include women of reproductive age or pregnant women who may work with 1,4-dioxane
or children ages 16 to 21 because the acute effects on liver enzymes and CNS effects are not
expected to preferentially affect women or developing children.
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5.4 Potentially Exposed or Susceptible Subpopulations
TSCA § 6(b)(4) requires that EPA conduct a risk evaluation to "determine whether a chemical
substance presents an unreasonable risk of injury to health or the environment, without
consideration of cost or other non-risk factors, including an unreasonable risk to a potentially
exposed or susceptible subpopulation identified as relevant to the risk evaluation by the
Administrator, under the conditions of useTSCA § 3(12) states that "the term 'potentially
exposed or susceptible subpopulation' means a group of individuals within the general
population identified by the Administrator who, due to either greater susceptibility or greater
exposure, may be at greater risk than the general population of adverse health effects from
exposure to a chemical substance or mixture, such as infants, children, pregnant women,
workers, or the elderly " Previous EPA assessments for 1,4-dioxane found no direct evidence
that certain populations and lifestages may be more susceptible to 1,4-dioxane (EPA IRIS
Assessments ( .013c. 2010)). Information on induction of liver enzymes, genetic
polymorphisms and gender differences was inadequate to quantitatively assess toxicokinetic or
toxicodynamic differences in 1,4-dioxane hazard between animals and humans and the potential
variability in human susceptibility.
Workplaces are generally regulated under OSHA and employers may be required to ensure that
workers are adequately protected from workplace hazards and to provide workers with
appropriate personal protective equipment. For conditions of use where workers are the
potentially exposed subpopulations, EPA's determination of unreasonable risk is likely to
consider the risk estimates associated with the central tendency exposure scenarios. For
occupational exposures, the exposures associated with central tendencies are assumed to be
representative of typical average exposures over an 8-hour shift.
EPA develops exposures representative of central tendency conditions and high-end conditions.
A central tendency is assumed to be representative of exposures in the center of the distribution
(50th percentile) for a given condition of use. A high-end exposure estimate is assumed to be
representative of exposures to the individuals with the highest exposure (e.g. 95th percentile).
For purposes of determining unreasonable risk, EPA looks at risk estimates associated with both
types of exposures and is more likely to determine that an unreasonable risk exists where risks
greater than the acceptable benchmarks are identified for both the central tendency and high-end
exposure scenarios under the conditions of use.
In developing the risk evaluation, the EPA analyzed the reasonably available information to
ascertain whether some human receptor groups may have greater exposure than the general
population to the hazard posed by a chemical. The results of the available human health data for
all routes of exposure evaluated (i.e., dermal and inhalation) indicate that there is no evidence of
increased susceptibility for any single group relative to the general population. Exposures of 1,4-
dioxane would be expected to be higher amongst workers and ONUs using 1,4-dioxane as
compared to the general population.
For occupational scenarios where risks greater than the acceptable benchmarks for cancer are
identified for high-end exposures but not for central tendency exposures, EPA will take into
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account the conditions of use, the severity of the adverse outcome, and the existence of a
potentially exposed or susceptible subpopulation in determining whether the risk is unreasonable.
For occupational scenarios where risks are less than benchmark for noncancer MOE for high-end
exposures but not for central tendency exposures, EPA will take into account the conditions of
use, the severity of the adverse outcome, and the existence of a potentially exposed or
susceptible subpopulation in determining whether the risk is unreasonable. Where risks greater
than the acceptable benchmarks are identified for high-end exposures, but not for central
tendency exposures, and where EPA determines that a potentially exposed or susceptible
subpopulation is not expected to be affected under the conditions of use, EPA may determine
that while some risk exists, the risk is not unreasonable for the occupational conditions of use.
5.5 Aggregate and Sentinel Exposures
Section 2605(b)(4)(F)(ii) of TSCA requires the EPA, as a part of the risk evaluation, to describe
whether aggregate or sentinel exposures under the conditions of use were considered and the
basis for their consideration. The EPA has defined aggregate exposure as "the combined
exposures to an individual from a single chemical substance across multiple routes and across
multiple pathways (40 CFR § 702.33)." As a result of the limited nature of all routes of exposure
to individuals (i.e., occupational) resulting from the conditions of use of 1,4-dioxane, a
consideration of aggregate exposures of 1,4-dioxane was deemed not to be applicable for this
risk evaluation. The EPA defines sentinel exposure as "the exposure to a single chemical
substance that represents the plausible upper bound of exposure relative to all other exposures
within a broad category of similar or related exposures (40 CFR § 702.33)." In terms of this risk
evaluation, the EPA considered sentinel exposure the highest exposure given the details of the
conditions of use and the potential exposure scenarios.
6 RISK DETERMINATION
6.1 Unreasonable Risk
6.1.1 Overview
In each risk evaluation under TSCA section 6(b), EPA determines whether a chemical substance
presents an unreasonable risk of injury to health or the environment, under the conditions of use.
The determination does not consider costs or other non-risk factors. In making this
determination, EPA considers relevant risk-related factors, including, but not limited to: the
effects of the chemical substance on health and human exposure to such substance under the
conditions of use (including cancer and non-cancer risks); the effects of the chemical substance
on the environment and environmental exposure under the conditions of use; the population
exposed (including any potentially exposed or susceptible subpopulations); the severity of hazard
(including the nature of the hazard, the irreversibility of the hazard); and uncertainties. EPA
takes into consideration the Agency's confidence in the data used in the risk estimate. This
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includes an evaluation of the strengths, limitations and uncertainties associated with the
information used to inform the risk estimate and the risk characterization. This approach is in
keeping with the Agency's final rule, Procedures for Chemical Risk Evaluation Under the
Amended Toxic Substances Control Act (82 FR 33726).10
Under TSCA, conditions of use are defined as the circumstances, as determined by the
Administrator, under which the substance is intended, known, or reasonably foreseen to be
manufactured, processed, distributed in commerce, used, or disposed of. TSCA §3(4).
An unreasonable risk may be indicated when health risks under the conditions of use are greater
than the risk benchmarks and where the risks affect the general population or certain potentially
exposed or susceptible subpopulations (PESS), such as consumers. For other PESS, such as
workers, an unreasonable risk may be indicated when health risks under the conditions of use are
greater than the risk benchmarks and where risks are not adequately addressed through expected
use of workplace practices and exposure controls, including engineering controls or use of
personal protective equipment (PPE). An unreasonable risk may also be indicated when
environmental risks under the conditions of use are greater than ecological risk benchmarks.
Throughout TSCA risk evaluation documents, EPA uses the terms "greater than risk
benchmarks" or "exceeds risk benchmarks" to indicate EPA concern for potential unreasonable
risk. For non-cancer endpoints, this occurs if an MOE value is less than the benchmark MOE
(e.g., MOE is .3 and benchmark MOE is 30); for cancer endpoints, this occurs if the lifetime
cancer risk value is greater than 1 in 10,000 (e.g., cancer risk value is 5xl0"2 which is greater
than the standard range of acceptable cancer risk benchmarks of lxlO"4 to lxlO"6); for ecological
endpoints, this occurs if the risk quotient (RQ) value is >1. Conversely, this risk determination
uses the term "below risk benchmarks" to indicate no EPA concern for potential unreasonable
risk. More details are described below.
The degree of uncertainty surrounding these indications is a factor in determining whether or not
unreasonable risk is present. Where uncertainty is low and EPA has high confidence in the
hazard and exposure characterizations (for example, the basis for the characterizations is
measured or monitoring data or a robust model and the hazards identified for risk estimation are
relevant for conditions of use), the Agency has a higher degree of confidence in its risk
determination. EPA may also consider other risk factors, such as severity of endpoint,
reversibility of effect, or exposure-related considerations such as magnitude or number of
exposures, in determining that the risks are unreasonable under the conditions of use. Where
EPA has made assumptions in the scientific evaluation, whether or not those assumptions are
protective will also be a consideration. Additionally, EPA considers the central tendency and
high-end scenarios when determining the unreasonable risk. High-end risk estimates (e.g. 95th
percentile) are generally intended to cover the most exposed individuals or sub-populations and
central tendency risk estimates are generally estimates of average or typical exposure.
10 This risk determination is being issued under TSCA section 6(b) and the terms used, such as unreasonable risk,
and the considerations discussed are specific to TSCA. Other statutes have different authorities and mandates and
may involve risk considerations other than those discussed here.
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Conversely, EPA may make a no unreasonable risk determination for conditions of use where
the substance's hazard and exposure potential, or where the risk-related factors described
previously, lead EPA to determine that the risks are not unreasonable.
6.1.2 Risks to Human Health
6.1.2.1 Determining Non-Cancer Risks
Margins of exposure (MOEs) are used in EPA's risk evaluations as a starting point to estimate
non-cancer risks for acute and chronic exposures. The non-cancer evaluation refers to potential
adverse health effects associated with health endpoints other than cancer, including to the body's
organ systems, such as reproductive/developmental effects, cardiac and lung effects, kidney and
liver effects. The MOE is the point of departure (an approximation of the no-observed adverse
effect level (NOAEL) or benchmark dose level (BMDL)) for a specific health endpoint divided
by the exposure concentration for the specific scenario of concern. The benchmark MOE that is
used accounts for the total uncertainty in a point of departure, including, as appropriate: (1) the
variation in sensitivity among the members of the human population (i.e., intrahuman/
intraspecies variability); (2) the uncertainty in extrapolating animal data to humans (i.e.,
interspecies variability); (3) the uncertainty in extrapolating from data obtained in a study with
less-than-lifetime exposure to lifetime exposure (i.e., extrapolating from subchronic to chronic
exposure); and (4) the uncertainty in extrapolating from a lowest observed adverse effect level
rather than from a NOAEL. MOEs provide a non-cancer risk profile by presenting a range of
estimates for different non-cancer health effects for different exposure scenarios and are a widely
recognized point estimate method for evaluating a range of potential non-cancer health risks
from exposure to a chemical.
A calculated MOE value that is under the benchmark MOE indicates the possibility of risk to
human health. Whether those risks are unreasonable will depend upon other risk-related factors,
such as severity of endpoint, reversibility of effect, exposure-related considerations (e.g.
duration, magnitude, frequency of exposure, population exposed), and the confidence in the
information used to inform the hazard and exposure values. If the calculated MOE is greater than
the benchmark MOE, generally it is less likely that there is risk.
Uncertainty factors also play an important role in the risk estimation approach and in
determining unreasonable risk. A lower benchmark MOE (e.g. 30) indicates greater certainty in
the data (because fewer of the default uncertainty factors are relevant to a given point of
departure as described above were applied). A higher benchmark MOE (e.g. 1000) would
indicate more uncertainty in risk estimation and extrapolation for the MOE for specific endpoints
and scenarios. However, these are often not the only uncertainties in a risk evaluation.
6.1.2.2 Determining Cancer Risks
EPA estimates cancer risks by determining the incremental increase in probability of an individual
in an exposed population developing cancer over a lifetime (excess lifetime cancer risk (ELCR))
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following exposure to the chemical under specified use scenarios. Standard cancer benchmarks
used by EPA and other regulatory agencies are an increased cancer risk above benchmarks ranging
from 1 in 1,000,000 to 1 in 10,000 (i.e., lxlO"6 to lxlO"4) depending on the subpopulation exposed.
Generally, EPA considers 1 x 10"6 to lx 10"4 as the appropriate benchmark for the general
population, consumer users, and non-occupational potentially exposed or susceptible
subpopulations (PESS).11
For 1,4-dioxane, EPA, consistent with 2017 NIOSH guidance12, used 1 x 10"4as the benchmark for
the purposes of this risk determination for individuals in industrial and commercial work
environments subject to Occupational Safety and Health Act (OSHA) requirements. It is important
to note that lxlO"4 is not a bright line and EPA has discretion to find unreasonable risks based on
other benchmarks as appropriate based on analysis. It is important to note that exposure related
considerations (duration, magnitude, population exposed) can affect EPA's estimates of the ELCR.
6.1.3 Determining Environmental Risk
To assess environmental risk, EPA identifies and evaluates environmental hazard data for aquatic,
sediment-dwelling, and terrestrial organisms exposed under acute and chronic exposure
conditions. The environmental risk includes any risks that exceed benchmarks to the aquatic
environment from levels of the evaluated chemical found in the environmental (e.g., surface
water, sediment, soil, biota) based on the fate properties, relatively high potential for release, and
the availability of environmental monitoring data and hazard data.
Environmental risks are estimated by calculating a risk quotient (RQ). The RQ is defined as:
RQ = Environmental Concentration / Effect Level
An RQ equal to 1 indicates that the exposures are the same as the concentration that causes
effects. If the RQ exceeds 1, the exposure is greater than the effect concentration and there is
potential for risk presumed. If the RQ does not exceed 1, the exposure is less than the effect
concentration and there is no risk presumed. The Concentrations of Concern or hazard value for
certain aquatic organisms are used to calculate RQs for acute and chronic exposures. For
environmental risk, EPA is more likely to determine that there is unreasonable risk if the RQ
11 As an example, when EPA's Office of Water in 2017 updated the Human Health Benchmarks for Pesticides, the
benchmark for a "theoretical upper-bound excess lifetime cancer risk" from pesticides in drinking water was
identified as 1 in 1,000,000 to 1 in 10,000 over a lifetime of exposure (EPA Human Health Benchmarks for
Pesticides: Updated 2017 Technical Document. January 2017. https://www.epa.gov/sites/production/files/2015-
10/documents/hh-benchmarks-techdoc.pdf). Similarly, EPA's approach under the Clean Air Act to evaluate residual
risk and to develop standards is a two-step approach that includes a "limit on maximum individual lifetime [cancer]
risk (MIR) of approximately 1 in 10 thousand" (54 FR 38045, September 14, 1989) and consideration of whether
emissions standards provide an ample margin of safety to protect public health "in consideration of all health
information, including the number of persons at risk levels higher than approximately 1 in 1 million, as well as other
relevant factors" (54 FR 38045, September 14, 1989).
12 International Union, UAW v. Pendergrass, 878 F.2d 389 (D.C. Cir. 1989), citing Industrial Union Department,
AFL-CIO v. American Petroleum Institute, 448 U.S. 607 ("Benzene decision"), in which a lifetime cancer risk of 1
in 1,000 was found to be clearly significant; and NIOSH [2017], Current intelligence bulletin 68: NIOSH chemical
carcinogen policy, available at https://www.cdc.gov/niosh/docs/2017-100/pdf/2017-100.pdf.
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exceeds 1 for the conditions of use being evaluated. Consistent with EPA's human health
evaluations, the RQ is not always treated as a bright line and other risk-based factors may be
considered (e.g., exposure scenario, uncertainty, severity of effect) for purposes of making a risk
determination.
6.2 Risk Determination for 1,4-Dioxane
EPA's determination of unreasonable risk for the conditions of use of 1,4-dioxane listed below is
based on health risks to workers during occupational exposures. As described below, risks to the
environment, general population, consumers, and occupational non-users either were not relevant
for these conditions of use or were evaluated and not found to be unreasonable.
• Environmental risks: For all conditions of use, EPA did not identify any exceedances of
benchmarks to aquatic vertebrates, aquatic invertebrates, and aquatic plants from
exposures to 1,4-dioxane in surface waters. The RQ values for acute and chronic risks are
0.046 and 0.397, respectively (See Table 5-2). An RQ that does not exceed 1 indicates
that the exposure concentrations of 1,4-dioxane are less than the concentrations that
would cause an effect to organisms in the aquatic pathways. Because the RQ values do
not exceed 1, and because EPA used a conservative screening level approach, these
values indicate there are no risks of 1,4-dioxane to the aquatic pathways. As a result, EPA
does not find unreasonable risks to the environment from the conditions of use for 1,4-
dioxane.
• General population: As part of the problem formulation for 1,4-dioxane, EPA
identified exposure pathways under other environmental statutes, administered by EPA,
which adequately assess and effectively manage exposures and for which long-standing
regulatory and analytical processes already exist, i.e., the Clean Air Act (CAA), the Safe
Drinking Water Act (SDWA), the Clean Water Act (CWA) and the Resource
Conservation and Recovery Act (RCRA). OCSPP works closely with the offices within
EPA that administer and implement the regulatory programs under these statutes. In
some cases, EPA has determined that chemicals present in various media pathways (i.e.,
air, water, land) fall under the jurisdiction of existing regulatory programs and associated
analytical processes carried out under other EPA-administered statutes and have been
assessed and effectively managed under those programs. EPA believes that the TSCA
risk evaluation should focus on those exposure pathways associated with TSCA uses that
are not subject to the regulatory regimes discussed above because these pathways are
likely to represent the greatest areas of concern to EPA. Exposures to 1,4-dioxane to
receptors (i.e., general population) may occur from industrial and/or commercial uses;
industrial releases to air, water or land; and other conditions of use. As described above,
other environmental statutes administered by EPA adequately assess and effectively
manage these exposures. Therefore, EPA did not evaluate hazards or exposures to the
general population in this risk evaluation, and there is no risk determination for the
general population. [Problem Formulation of the Risk Evaluation for 1,4-Dioxane, (U.S.
EPA. 2018c)"I
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• Consumers: EPA did not identify any expected consumer uses from the conditions of
use of 1,4-dioxane. Therefore, EPA did not evaluate hazards or exposures to consumers
in this risk evaluation, and there is no risk determination for this population.
• Occupational non-users: EPA evaluated inhalation risks for acute and chronic
exposures for occupational non-users. Dermal exposures were not evaluated because
occupational non-users do not typically directly handle the 1,4-dioxane nor are they in
the immediate proximity of 1,4-dioxane. For all conditions of use, inhalation exposure
scenarios for occupational non-users resulted in calculated MOEs and cancer risk levels
did not indicate risk relative to the respective benchmarks (Tables 5-7 and 5-9). As a
result, EPA does not find unreasonable risks to the health of occupational non-users from
the conditions of use for 1,4-dioxane.
Table 6-1. Risk Determination by Conditions of Use
Condition of
l.il'e Cycle
Sla«e
I se
Category
Sub-Cale«ory
I treasonable Risk Dclcrminalion1
"Exceeds Agency risk benchmarks" = indicates
potential risk
• Human Health
o Non-cancer MOE value < MOE
benchmark (e.g., MOE=0.3;
benchmark=30)
o Cancer value >1.0E-04 to 1.0E-06 cancer
benchmark (e.g., cancer value= lxl0"3;
b enchmark= 1 x 10"6)
• Environmental
o RQ value >1 (e.g., RQ=5; benchmark=l)
Manufacture
Domestic
Manufacture
Domestic
Manufacture
Section 6(b)(4)(A) unreasonable risk determination for
domestic manufacture of 1.4-dioxane:
- Presents an unreasonable risk of injury to health
(workers)
- Does not present an unreasonable risk of injury to health
(occupational non-users) or to aquatic vertebrates, aquatic
invertebrates, and aquatic plants from exposures to 1,4-
dioxane in surface waters.
Unreasonable risk driver: Cancer resulting from chronic
dermal occupational exposure and noncancer portal of entry
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Condition of
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effects resulting from chronic inhalation occupational
exposure.
Driver benchmarks: 1.0E-04 to 1.0E-06 for cancer. For this
evaluation, the Agency is using 1.0E-04 for occupational
exposures. MOE = 30 for noncancer portal of entry effects.
Risk estimates: 3.6E-04 with workers using PPE (gloves
where PF = 20) (see Table 5-11); MOE =11 with workers
using PPE (respirator where APF = 50) (see Table 5-5).
(High-end estimates)
Svstematic Review confidence ratine (hazard): High
Systematic Review confidence rating (dermal exposure): N/A
(risks estimates derived using the EPA Dermal Exposure to
Volatile Liquids model).
Svstematic Review confidence rating (inhalation exposure):
High
Risk Considerations: The modeling used to calculate dermal
risk estimates has some uncertainties that could overestimate
risk. For example, to address the uncertainty due to lack of
monitoring data, the model considered a thin film of product
on a defined skin area. A multiplicative factor was
incorporated to the model to include the proportion of 1,4-
dioxane remaining on the skin after wiping. In order to be
protective, the value used for the amount of 1,4-dioxane
remaining on the skin is a default high-end value of a limited
dataset. The dermal absorption value, a critical input used to
calculate risk, is based on human in vitro and primate data
rather than default assumptions. Considering the uncertainties
in the oral-to-dermal extrapolation, EPA chose to use 3.2%,
the higher value, for the dermal absorption factor. The actual
absorption could be ten-fold lower based on the Bronaugh in
vitro studv (Bronaush. 1982). For this Dathwav. EPA expects
that the risks are not underestimated.
The hazard data used to calculate chronic noncancer
inhalation risk estimates could overestimate risk. Chronic
noncancer inhalation risks for workers were estimated based
on portal of entry effects from a two-year inhalation study in
rats (Kasai et ah, 2009). This studv used whole bodv
exposures, introducing uncertainty with respect to the actual
doses the animals received such that the effect levels reported
may overestimate the potential inhalation toxicity. For this
pathway, EPA expects that the risks are not underestimated.
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Condition of I so
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Slsigc
Csilcsorv
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For a detailed discussion of the uncertainties related to the
risk evaluation see the section 5.3.
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic cancer
inhalation exposures and noncancer dermal exposures)
exceed the Agency's risk benchmarks in the absence of PPE
(indicating risk), risk estimates for these pathways do not
indicate risk when PPE was considered (see Tables 5-8, 5-
10).
Estimated exposed population: 78 workers, 36 occupational
non-users
Manufacture
Import
Import
Section 6(b)(4)(A') unreasonable risk determination for
import of 1.4-dioxane:
- Does not present an unreasonable risk of injury to health
(workers and occupational non-users) or to aquatic
vertebrates, aquatic invertebrates, and aquatic plants from
exposures to 1,4-dioxane in surface waters.
Exposure scenario with highest risk estimate: Noncancer
portal of entry effects resulting from chronic inhalation
occupational exposure.
Benchmark: MOE = 30 for noncancer portal of entry effects.
Risk estimate: MOE = 25 with workers using PPE (respirator
where APF = 50) (see Table 5-5). (High-end estimate)
Systematic Review confidence rating (hazard): High
Systematic Review confidence rating (inhalation exposure):
N/A (risks estimates derived using the EPA AP-42 Loading
Model and the EPA Mass Balance Inhalation Model).
Risk Considerations: The hazard data used to calculate
chronic noncancer inhalation risk estimates have
uncertainties that could overestimate risk. Chronic noncancer
inhalation risks for workers were estimated based on portal of
entry effects from a two-year inhalation study in rats (Kasai
et ah. 2009). This study used whole body exposures,
introducing uncertainty with respect to the actual doses the
animals received such that the effect levels reported may
overestimate the potential inhalation toxicity.
The modeling used to calculate inhalation risk estimates has
some uncertainties that could overestimate risk. EPA
assumed certain process details, such as container sizes and
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Condition of
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loading and unloading frequency. Additionally, EPA
assumed that the process steps associated with this scenario
occur indoors, without engineering controls, and in an open-
system environment where vapors freely escape. In the
absence of industry-specific information, these assumptions
provide for conservative estimates for exposures. Actual
exposures may be less due to various factors including
closed-system loading and unloading, the use of vapor
recovery systems, or the automation of various process steps.
For this pathway, EPA expects that the risks are not
underestimated. For a detailed discussion of the uncertainties
related to the risk evaluation see the section 5.3.
EPA considered the uncertainties described above for both
hazard and exposure, the expected use of PPE, the fact that
the risk estimates using central tendency exposure
assumptions are below the benchmark, and the proximity of
the calculated risk estimate using high-end exposure
assumptions to the benchmark to determine that this
condition of use does not present an unreasonable risk via
this pathway.
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic cancer
inhalation exposures and chronic cancer and noncancer
dermal exposures) exceed the Agency's risk benchmarks in
the absence of PPE, risk estimates for these pathways do not
indicate risk relative to those benchmarks when PPE was
considered (see Tables 5-8, 5-10, 5-11).
Estimated exposed population: 18 workers. 198 occupational
non-users
Processing
Repackaging
Bulk to
packages, then
Distribute
Section 6(b)(4)(A) unreasonable risk determination for
processing of 1.4-dioxane bv repackaging: Section 6(b)(4)(A)
unreasonable risk determination for processing of 1.4-
dioxane bv repackaging:
- Does not present an unreasonable risk of injury to health
(workers and occupational non-users) or to aquatic
vertebrates, aquatic invertebrates, and aquatic plants from
exposures to 1,4-dioxane in surface waters.
Exposure scenario with highest risk estimate: Noncancer
portal of entry effects resulting from chronic inhalation
occupational exposure.
Benchmark: MOE = 30 for noncancer portal of entrv effects.
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Risk estimate: MOE = 25 with workers using PPE (respirator
where APF = 50) (see Table 5-5). (High-end estimate)
Systematic Review confidence rating (hazard): High
Systematic Review confidence ratine (inhalation exposure):
N/A (risks estimates derived using the EPA AP-42 Loading
Model and the EPA Mass Balance Inhalation Model).
Risk Considerations: The hazard data used to calculate
chronic noncancer inhalation risk estimates have
uncertainties that could overestimate risk. Chronic noncancer
inhalation risks for workers were estimated based on portal of
entry effects from a two-year inhalation study in rats (Kasai
et ah, 2009). This studv used whole bodv exposures,
introducing uncertainty with respect to the actual doses the
animals received such that the effect levels reported may
overestimate the potential inhalation toxicity.
The modeling used to calculate inhalation risk estimates has
some uncertainties that could overestimate risk. EPA
assumed certain process details, such as container sizes and
loading and unloading frequency. Additionally, EPA
assumed that the process steps associated with this scenario
occur indoors, without engineering controls, and in an open-
system environment where vapors freely escape. In the
absence of industry-specific information, these assumptions
provide for conservative estimates for exposures. Actual
exposures may be less due to various factors including
closed-system loading and unloading, the use of vapor
recovery systems, or the automation of various process steps.
For this pathway, EPA expects that the risks are not
underestimated. For a detailed discussion of the uncertainties
related to the risk evaluation see the section 5.3.
EPA considered the uncertainties described above for both
hazard and exposure, the expected use of PPE, the fact that
the risk estimates using central tendency exposure
assumptions are not below the benchmark, and the proximity
of the calculated risk estimate using high-end exposure
assumptions to the benchmark to determine that this
condition of use does not present an unreasonable risk via
this pathway.
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Condition of I so
I.ilc Cycle
Slsigc
Csilcsorv
Suh-CsiU'gorv
I nronsonnhlo Kisk Dclcrniinsilion1
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic cancer
inhalation exposures and chronic cancer and noncancer
dermal exposures) exceed the Agency's risk benchmarks in
the absence of PPE, risk estimates for these pathways do not
indicate risk relative to those benchmarks when PPE was
considered (see Tables 5-8, 5-10, 5-11).
Estimated exposed population: 18 workers, 198 occupational
non-users
Processing
Processing as
a reactant
Pharmaceutical
intermediate
Polymerization
catalyst
Non-
incorporative
Pharmaceutical
and
medicine
manufacturing
(process solvent)
Basic organic
chemical
manufacturing
(process solvent)
Recycling
Recycling
Section 6(b)(4)(A) unreasonable risk determinations for 1.4-
dioxane for processing as a reactant. non-incorporative
processing, and recycling:
- Presents an unreasonable risk of injury to health
(workers)
- Does not present an unreasonable risk of injury to health
(occupational non-users) or to aquatic vertebrates, aquatic
invertebrates, and aquatic plants from exposures to 1,4-
dioxane in surface waters.
Unreasonable risk driver: Cancer resulting from chronic
dermal occupational exposure and noncancer portal of entry
effects resulting from chronic inhalation occupational
exposure.
Driver benchmarks: 1.0E-04 to 1.0E-06 for cancer. For this
evaluation, the Agency is using 1.0E-04 for occupational
exposures. MOE = 30 for noncancer portal of entry effects.
Risk estimates: 3.6E-04 with workers using PPE (gloves
where PF=20) (see Table 5-11); MOE = 4 with workers using
PPE (respirator where APF = 50) (see Table 5-5). (High-end
estimates)
Systematic Review confidence rating (hazard): High
Systematic Review confidence rating (dermal exposure): N/A
(risks estimates derived using the EPA Dermal Exposure to
Volatile Liquids model).
Systematic Review confidence rating (inhalation exposure):
High
Risk Considerations: The modeling used to calculate dermal
risk estimates has some uncertainties that could overestimate
risk. For example, to address the uncertainty due to lack of
monitoring data, the model considered a thin film of product
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Condition of I so
I.ilc Cycle
Slsigc
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on a defined skin area. A multiplicative factor was
incorporated to the model to include the proportion of 1,4-
dioxane remaining on the skin after wiping. To be protective,
the value used for the amount of 1,4-dioxane remaining on
the skin is a default high-end value of a limited dataset. The
dermal absorption value, a critical input used to calculate
risk, is based on human in vitro and primate data rather than
default assumptions. Considering the uncertainties in the
oral-to-dermal extrapolation, EPA chose to use 3.2%, the
higher value, for the dermal absorption factor. The actual
absorption could be ten-fold lower based on the Bronaugh in
vitro study (Bronaugh, .1.982). For this pathway, EPA expects
that the risks are not underestimated.
The hazard data used to calculate chronic noncancer
inhalation risk estimates could overestimate risk. Chronic
noncancer inhalation risks for workers were estimated based
on portal of entry effects from a two-year inhalation study in
rats (Kasai et ah. 2009). This study used whole body
exposures, introducing uncertainty with respect to the actual
doses the animals received such that the effect levels reported
may overestimate the potential inhalation toxicity. For this
pathway, EPA expects that the risks are not underestimated.
For a detailed discussion of the uncertainties related to the
risk evaluation see the section 5.3.
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic cancer
inhalation exposures and noncancer dermal exposures)
exceed the Agency's risk benchmarks in the absence of PPE,
risk estimates for these pathways do not indicate risks relative
to those benchmarks when PPE was considered (see Tables
5-8, 5-10).
EPA developed risk estimates for a single processing use
scenario, with the exception of repackaging. The results of
this scenario are intended to broadly address the potential
exposures associated with each of the sub-categories for this
condition of use.
Estimated exposed population: 1,400 workers, 545
occupational non-users. The assumption for number of
workers and occupational non-users covers multiple
categories and sub-categories across processing of 1,4-
dioxane.
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Condition of I so
I.ilc Cycle
Slsigc
Csilcsorv
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Industrial use
Intermediate
use
Processing
aids, not
otherwise
listed
Agricultural
chemical
intermediate
Plasticizer
intermediate
Wood pulping
Extraction of
animal and
vegetable oils
Polymerization
catalyst
Purification of
pharmaceuticals
Section 6(b)(4)(A) unreasonable risk determinations for 1.4-
dioxane for intermediate use and processing aids, not
otherwise listed:
Catalysts and
reagents for
anhydrous acid
reactions,
brominations
and sulfonations
- Presents an unreasonable risk of injury to health
(workers)
- Does not present an unreasonable risk of injury to health
(occupational non-users) or to aquatic vertebrates, aquatic
invertebrates, and aquatic plants from exposures to 1,4-
dioxane in surface waters.
Unreasonable risk driver: Cancer resulting from chronic
dermal occupational exposure and noncancer portal of entry
effects resulting from chronic inhalation occupational
exposure.
Driver benchmarks: 1.0E-04 to 1.0E-06 for cancer. For this
Wetting and
dispersing agent
in textile
processing
evaluation, the Agency is using 1.0E-04 for occupational
exposures. MOE = 30 for noncancer portal of entry effects.
Risk estimates: 3.6E-04 with workers using PPE (gloves
where PF=20) (see Table 5-11); MOE = 4 with workers using
PPE (respirator where APF = 50) (see Table 5-5). (High-end
estimates)
Systematic Review confidence rating (hazard): High
Systematic Review confidence rating (dermal exposure): N/A
(risks estimates derived using the EPA Dermal Exposure to
Volatile Liquids model).
Systematic Review confidence rating (inhalation exposure):
High
Risk Considerations: The modeling used to calculate dermal
risk estimates has some uncertainties that could overestimate
risk. For example, to address the uncertainty due to lack of
monitoring data, the model considered a thin film of product
on a defined skin area. A multiplicative factor was
incorporated to the model to include the proportion of 1,4-
dioxane remaining on the skin after wiping. To be protective,
the value used for the amount of 1,4-dioxane remaining on
the skin is a default high-end value of a limited dataset. The
dermal absorption value, a critical input used to calculate
risk, is based on human in vitro and primate data rather than
default assumptions. Considering the uncertainties in the
oral-to-dermal extrapolation, EPA chose to use 3.2%, the
higher value, for the dermal absorption factor. The actual
absorption could be ten-fold lower based on the Bronaugh in
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Condition of
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vitro studv (Bronaueh. 1982). For this pathway. EPA expects
that the risks are not underestimated.
The hazard data used to calculate chronic noncancer
inhalation risk estimates could overestimate risk. Chronic
noncancer inhalation risks for workers were estimated based
on portal of entry effects from a two-year inhalation study in
rats (Kasai et aL 2009). This studv used whole bodv
exposures, introducing uncertainty with respect to the actual
doses the animals received such that the effect levels reported
may overestimate the potential inhalation toxicity. For this
pathway, EPA expects that the risks are not underestimated.
For a detailed discussion of the uncertainties related to the
risk evaluation see the section 5.3.
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic cancer
inhalation exposures and noncancer dermal exposures)
exceed the Agency's risk benchmarks in the absence of PPE,
risk estimates for these pathways do not indicate risk relative
to those benchmarks when PPE was considered (see Tables
5-8, 5-10).
EPA developed risk estimates for a single processing use
scenario. The results of this scenario are intended to broadly
address the potential exposures associated with each of the
sub-categories for this condition of use.
Estimated exposed population: 1.400 workers. 545
occupational non-users. The assumption for number of
workers and occupational non-users covers multiple
categories and sub-categories across processing of 1,4-
dioxane.
Distribution in
commerce
Distribution
Distribution
Section 6(b)(4)(A) unreasonable risk determination for
distribution of 1.4-dioxane: Does not present an unreasonable
risk of injury to health (workers and occupational non-users)
or to aquatic vertebrates, aquatic invertebrates, and aquatic
plants from exposures to 1,4-dioxane in surface waters.
Risk Considerations: A quantitative evaluation of distribution
of 1,4-dioxane was not included in the risk evaluation
because chemicals are packaged in closed-system containers
during distribution in commerce and no exposures or releases
to the environment are expected.
Industrial Use
Polyalkylene -
glycol lubricant
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Functional
fluids (open
system);
Suh-CsiU'gorv
Synthetic
metalworking
fluid
Cutting and
tapping fluid
Hydraulic fluid
I nrcnsonnblc Kisk Dclcrniinsilion1
Section 6(b)(4)(A) unreasonable risk determination for the
industrial use of 1.4-dioxane in functional fluids (open
systems):
- Does not present an unreasonable risk of injury to health
(workers and occupational non-users) or to aquatic
vertebrates, aquatic invertebrates, and aquatic plants from
exposures to 1,4-dioxane in surface waters.
Risk assessment: Human health risk estimates for all
pathways are not below Agency benchmarks. Environmental
risk estimates for all pathways do not exceed the benchmark.
Exposure scenario with highest risk estimate: Cancer
resulting from chronic inhalation occupational exposure.
Driver benchmark: 1.0E-04to 1.0E-06. For this evaluation,
the Agency is using 1.0E-04 for occupational exposures.
MOE = 30 for noncancer portal of entry effects.
Risk estimate: 1.5E-06 with workers using no PPE (see Table
5-8) (High-end estimate)
Systematic Review confidence rating (hazard): High
Systematic Review confidence rating (exposure): N/A (risks
estimates derived using the EPA AP-42 Loading Model and
the EPA Mass Balance Inhalation model.
Risk Considerations: The modeling used to calculate
inhalation risk estimates has some uncertainties that could
overestimate risk. EPA assumed certain process details, such
as container sizes and loading and unloading frequency.
Additionally, EPA assumed that the process steps associated
with this scenario occur indoors, without engineering
controls, and in an open-system environment where vapors
freely escape. In the absence of industry-specific information,
these assumptions provide for conservative estimates for
exposures. Actual exposures may be less due to various
factors including closed-system loading and unloading, the
use of vapor recovery systems, or the automation of various
process steps. For this pathway, EPA expects that the risks
are not underestimated. For a detailed discussion of the
uncertainties related to the risk evaluation see the section 5.3.
EPA developed risk estimates for a single open system
functional fluid use scenario. The results of this scenario are
intended to broadly address the potential exposures
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associated with each of the sub-categories for this condition
of use.
Estimated exposed population: over 4 million workers.
178,000 occupational non-users.
Industrial use
Functional
fluid, closed
system
Due to the lack of evidence supporting its use in closed
system functional fluids, EPA has determined that this is not
a condition of use and therefore did not assess occupational
exposures for functional fluid use in closed systems.
Industrial use,
potential
commercial
use
Laboratory
chemicals
Chemical
reagent
Section 6(b)(4)(A) unreasonable risk determination for the
industrial use and potential commercial use of 1.4-dioxane as
Reference
material
a laboratory chemical:
- Presents an unreasonable risk of injury to health
(workers)
- Does not present an unreasonable risk of injury to health
(occupational non-users) or to aquatic vertebrates, aquatic
invertebrates, and aquatic plants from exposures to 1,4-
dioxane in surface waters.
Unreasonable risk driver: Cancer resulting from chronic
dermal occupational exposure and noncancer portal of entry
effects resulting from chronic inhalation occupational
exposure.
Driver benchmarks: 1.0E-04 to 1.0E-06. For this evaluation,
the Agency is using 1.0E-04 for occupational exposures.
MOE = 30 for noncancer portal of entry effects.
Risk estimate: 4.0E-04 with workers using PPE (gloves
where PF=20) (see Table 5-11); MOE = 15 with workers
using PPE (respirator where APF = 50) (see Table 5-5).
(High-end estimates)
Systematic Review confidence ratine (hazard): High
Systematic Review confidence ratine (exposure): Hieh
Risk Considerations: The modeline used to calculate dermal
risk estimates has some uncertainties that could overestimate
risk. For example, to address the uncertainty due to lack of
monitoring data, the model considered a thin film of product
on a defined skin area. A multiplicative factor was
incorporated to the model to include the proportion of 1,4-
dioxane remaining on the skin after wiping. In order to be
protective, the value used for the amount of 1,4-dioxane
remaining on the skin is a default high-end value of a limited
dataset. The dermal absorption value, a critical input used to
Spectroscopic
and photometric
measurement
Liquid
scintillation
counting
medium
Stable reaction
medium
Cryoscopic
solvent for
molecular mass
determinations
Preparation of
histological
sections for
microscopic
examination
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calculate risk, is based on human in vitro and primate data
rather than default assumptions. Considering the uncertainties
in the oral-to-dermal extrapolation, EPA chose to use 3.2%,
the higher value, for the dermal absorption factor. The actual
absorption could be ten-fold lower based on the Bronaugh in
vitro studv (Bronaugh, 1982). For this pathway. EPA expects
that the risks are not underestimated.
The hazard data used to calculate chronic noncancer
inhalation risk estimates could overestimate risk. Chronic
noncancer inhalation risks for workers were estimated based
on portal of entry effects from a two-year inhalation study in
rats (Kasai et aL 2009). This studv used whole bodv
exposures, introducing uncertainty with respect to the actual
doses the animals received such that the effect levels reported
may overestimate the potential inhalation toxicity. For a
detailed discussion of the uncertainties related to the risk
evaluation see the section 5.3.
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic cancer
inhalation exposures and noncancer dermal exposures)
exceed the Agency's risk benchmarks in the absence of PPE,
risk estimates for these pathways do not indicate risk relative
to those benchmarks when PPE was considered (see Tables
5-8, 5-10).
EPA developed risk estimates for a single laboratory use
scenario. The results of this scenario are intended to broadly
address the potential exposures associated with each of the
sub-categories for this condition of use.
Estimated exposed population: 89 workers. 11 occupational
non-users.
Industrial use,
potential
commercial
use
Adhesives and
sealants
Film cement
Section 6(b)(4)(A) unreasonable risk determination for the
industrial use and potential commercial use of 1.4-dioxane in
adhesives and sealants:
- Presents an unreasonable risk of injury to health
(workers)
- Does not present an unreasonable risk of injury to health
(occupational non-users) or to aquatic vertebrates, aquatic
invertebrates, and aquatic plants from exposures to 1,4-
dioxane in surface waters.
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Unreasonable risk driver: Cancer resulting from chronic
dermal occupational exposure.
Driver benchmark: 1.0E-04to 1.0E-06. For this evaluation,
the Agency is using 1.0E-04 for occupational exposures.
MOE = 30 for noncancer portal of entry effects.
Risk estimate: 2.0E-04 with workers using PPE (gloves
where PF=20) (See table 5-11) (High-end estimate)
Systematic Review confidence rating (hazard): High
Systematic Review confidence rating (exposure): N/A (risks
estimates derived using the EPA Dermal Exposure to Volatile
Liquids model.
Risk Considerations: The modeling used to calculate dermal
risk estimates has some uncertainties that could overestimate
risk. For example, to address the uncertainty due to lack of
monitoring data, the model considered a thin film of product
on a defined skin area. A multiplicative factor was
incorporated to the model to include the proportion of 1,4-
dioxane remaining on the skin after wiping. In order to be
protective, the value used for the amount of 1,4-dioxane
remaining on the skin is a default high-end value of a limited
dataset. The dermal absorption value, a critical input used to
calculate risk, is based on human data rather than default
assumptions. The Agency chose to use the upper end of the
range of possible values derived from the data for a worst-
case scenario. For this pathway, EPA expects that the risks
are not underestimated. For a detailed discussion of the
uncertainties related to the risk evaluation see the section 5.3.
The risk estimate for noncancer effects via chronic inhalation
exposure to occupational non-users is below (MOE =17) the
Agency benchmark (MOE = 30). However, this estimate was
based on a monitoring study that provided a single area
sample point. This value was a non-detect (Okawa and Cove.
1982). EPA cannot determine the statistical
representativeness of the values given the limited sample size
and reliance on non-detect measurements at the LOD
introduces significant conservatism into this risk estimate.
EPA considered the uncertainties described above and the
proximity of the calculated risk estimate to the benchmark to
determine that this condition of use does not present an
unreasonable risk for occupational non-users.
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic cancer
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inhalation exposures and noncancer dermal exposures)
exceed the Agency's risk benchmarks in the absence of PPE,
risk estimates for these pathways do not indicate risk relative
to those benchmarks when PPE was considered (see Tables
5-8, 5-10).
Estimated exposed population: 30 workers. 10 occupational
non-users
Industrial use,
potential
commercial
use
Other uses
Spray
polyurethane
foam
compositions
Section 6(b)(4)(A) unreasonable risk determination for the
industrial use and potential commercial use of 1.4-dioxane
for other uses, including sprav polvurethane foam
compositions:
-Does not present an unreasonable risk of injury to health
(occupational non-users) or to aquatic vertebrates, aquatic
invertebrates, and aquatic plants from exposures to 1,4-
dioxane in surface waters.
Risk assessment: Human health risk estimates for all
pathways are not below Agency benchmarks. Environmental
risk estimates for all pathways do not exceed the benchmark.
Exposure scenario with highest risk estimate: Cancer
resulting from chronic inhalation occupational exposure.
Benchmark: 1.0E-04to 1.0E-06. For this evaluation, the
Agency is using 1.0E-04 for occupational exposures. MOE =
30 for noncancer portal of entry effects.
Risk estimate: 5.3E-06 with workers using no PPE (see Table
5-8) (High-end estimate)
Systematic Review confidence rating (hazard): High
Systematic Review confidence ratine (exposure): N/A (risks
estimates derived using the EPA AP-42 Loading model, the
EPA Mass Balance Inhalation model and the EPA Total
PNOR PEL-Limiting model.
Risk Considerations: Due to a lack of data specific to 1.4-
dioxane for this use, EPA used assumptions and surrogate
data to estimate inhalation exposures during container
unloading, spray foam application, thickness verification, and
trimming. The estimate for exposures during application did
not account for the potential evaporation of 1,4-dioxane from
the mist particulates and the potential inhalation exposure of
the evaporated vapors. EPA assumed that this is not a
significant exposure given that the partial pressure of 1,4-
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dioxane is likely very low due to the low concentration of
1,4-dioxane in the mixed spray foam. EPA also estimated
exposures during thickness verification using surrogate data.
The models also assume that the unloading of fluid
containing 1,4-dioxane occurs indoors, without engineering
controls, and in an open-system environment where vapors
freely escape. In the absence of industry-specific information,
these assumptions provide for conservative estimates for
exposures during this unloading operation. Actual exposures
may be less due to various factors including closed-system
unloading or the use of vapor recovery systems. For this
pathway, EPA expects that the risks are not underestimated.
For a detailed discussion of the uncertainties related to the
risk evaluation see the section 5.3.
Estimated exposed population: 162.520 workers; 15.260
occupational non-users
Industrial use,
potential
commercial
use
Other uses
printing and
printing
compositions
Section 6(b)(4)(A) unreasonable risk determination for the
industrial use and potential commercial use of 1.4-dioxane
for other uses, including printing and printing compositions:
- Presents an unreasonable risk of injury to health
(workers)
- Does not present an unreasonable risk of injury to health
(occupational non-users) or to aquatic vertebrates, aquatic
invertebrates, and aquatic plants from exposures to 1,4-
dioxane in surface waters.
Unreasonable risk driver: Cancer resulting from chronic
dermal occupational exposure
Benchmark: 1.0E-04to 1.0E-06. For this evaluation, the
Agency is using 1.0E-04 for occupational exposures. MOE =
30 for noncancer portal of entry effects.
Risk estimate: 4.0E-04 with workers using PPE (gloves
where PF=20) (see Table 5-11) (High-end estimate)
Svstematic Review confidence rating (hazard): High
Svstematic Review confidence rating (exposure): N/A (risks
estimates derived using the EPA Dermal Exposure to Volatile
Liquids model.
Risk Considerations: The modeling used to calculate dermal
risk estimates has some uncertainties that could overestimate
risk. For example, to address the uncertainty due to lack of
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monitoring data, the model considered a thin film of producl
on a defined skin area. A multiplicative factor was
incorporated to the model to include the proportion of 1,4-
dioxane remaining on the skin after wiping. In order to be
protective, the value used for the amount of 1,4-dioxane
remaining on the skin is a default high-end value of a limited
dataset. The dermal absorption value, a critical input used to
calculate risk, is based on human data rather than default
assumptions. The Agency chose to use the upper end of the
range of possible values derived from the data for a worst-
case scenario. For this pathway, EPA expects that the risks
are not underestimated. For a detailed discussion of the
uncertainties related to the risk evaluation see the section 5.3.
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic noncancer
inhalation exposures and noncancer dermal exposures) are
exceed the Agency's risk benchmarks in the absence of PPE,
risk estimates for these pathways do not indicate risk relative
to those benchmarks when PPE was considered (see Tables
5-8, 5-10).
Estimated exposed population: 60.000 workers. 20.430
occupational non-users.
Industrial use,
potential
commercial
use
Other uses
Dry film
lubricant
Section 6(b)(4¥A) unreasonable risk determination for the
industrial use and potential commercial use of 1.4-dioxane
for other uses including as a drv film lubricant:
- Does not present an unreasonable risk of injury to health
(workers and occupational non-users) or to aquatic
vertebrates, aquatic invertebrates, and aquatic plants from
exposures to 1,4-dioxane in surface waters.
Risk assessment: Human health risk estimates for all
pathways do not indicate risk relative to Agency benchmarks.
Environmental risk estimates for all pathways do not indicate
risk relative to the benchmark.
Exposure scenario with highest risk estimate: Cancer
resulting from chronic dermal occupational exposure.
Benchmark: 1.0E-04to 1.0E-06. For this evaluation, the
Agency is using 1.0E-04 for occupational exposures. MOE =
30 for noncancer portal of entry effects.
Risk estimate: 8.1E-05 with workers using PPE (gloves
where PF=20) (see Table 5-11) (High-end estimate)
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Systematic Review confidence rating (hazard): High
Systematic Review confidence rating (exposure): N/A (risks
estimates derived using the EPA Dermal Exposure to Volatile
Liquids model.
Risk Considerations: The modeling used to calculate dermal
risk estimates has some uncertainties that could overestimate
risk. For example, to address the uncertainty due to lack of
monitoring data, the model considered a thin film of product
on a defined skin area. A multiplicative factor was
incorporated to the model to include the proportion of 1,4-
dioxane remaining on the skin after wiping. In order to be
protective, the value used for the amount of 1,4-dioxane
remaining on the skin is a default high-end value of a limited
dataset. The dermal absorption value, a critical input used to
calculate risk, is based on human data rather than default
assumptions. The Agency chose to use the upper end of the
range of possible values derived from the data for a worst-
case scenario. For this pathway, EPA expects that the risks
are not underestimated. For a detailed discussion of the
uncertainties related to the risk evaluation see the section 5.3.
Estimated exposed population: 16 workers, 64 occupational
non-users
Disposal
Disposal
Industrial pre-
treatment
Section 6(b)(4)(A) unreasonable risk determination for
disposal of 1.4-dioxane:
Industrial
wastewater
treatment
Publicly owned
treatment works
(POTW)
Underground
injection
Municipal
landfill
Hazardous
landfill
-Presents an unreasonable risk of injury to health
(workers)
-Does not present an unreasonable risk of injury to health
(workers and occupational non-users) or to aquatic
vertebrates, aquatic invertebrates, and aquatic plants from
exposures to 1,4-dioxane in surface waters.
Unreasonable risk driver: Cancer resulting from chronic
dermal occupational exposure and noncancer portal of entry
effects resulting from chronic inhalation occupational
exposure
Benchmark: 1.0E-04 to 1.0E-06. For this evaluation, the
Other land
disposal
Agency is using 1.0E-04 for occupational exposures. MOE =
30 for noncancer portal of entry effects.
Risk estimate: 3.6E-04 with workers using PPE (gloves
where PF=20) (see Table 5-11) (High-end estimate) MOE =
Municipal waste
incinerator
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21 with workers using PPE (respirator where APF = 50) (set-
Table 5-5).
Systematic Review confidence ratine (hazard): High
Systematic Review confidence rating (exposure): N/A (risks
estimates derived using the EPA Dermal Exposure to Volatile
Liquids model.
Risk Considerations: The modeling used to calculate dermal
risk estimates has some uncertainties that could overestimate
risk. For example, to address the uncertainty due to lack of
monitoring data, the model considered a thin film of product
on a defined skin area. A multiplicative factor was
incorporated to the model to include the proportion of 1,4-
dioxane remaining on the skin after wiping. In order to be
protective, the value used for the amount of 1,4-dioxane
remaining on the skin is a default high-end value of a limited
dataset. The dermal absorption value, a critical input used to
calculate risk, is based on human data rather than default
assumptions. The Agency chose to use the upper end of the
range of possible values derived from the data for a worst-
case scenario. For this pathway, EPA expects that the risks
are not underestimated.
The hazard data used to calculate chronic noncancer
inhalation risk estimates could overestimate risk. Chronic
noncancer inhalation risks for workers were estimated based
on portal of entry effects from a two-year inhalation study in
rats (Kasai et al.„ 2009). This study used whole body
exposures, introducing uncertainty with respect to the actual
doses the animals received such that the effect levels reported
may overestimate the potential inhalation toxicity.
The modeling used to calculate inhalation risk estimates has
some uncertainties that could overestimate risk. EPA
assumed certain process details, such as container sizes and
loading and unloading frequency. Additionally, EPA
assumed that the process steps associated with this scenario
occur indoors, without engineering controls, and in an open-
system environment where vapors freely escape. In the
absence of industry-specific information, these assumptions
provide for conservative estimates for exposures. Actual
exposures may be less due to various factors including
closed-system loading and unloading, the use of vapor
recovery systems, or the automation of various process steps.
For this pathway, EPA expects that the risks are not
underestimated. For a detailed discussion of the uncertainties
Hazardous waste
incinerator
Off-site waste
transfer
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related to the risk evaluation see the section 5.3.
While risk estimates for other pathways of occupational
exposure for this condition of use (such as chronic cancer
inhalation exposures and noncancer dermal exposures)
exceed the Agency's risk benchmarks in the absence of PPE,
risk estimates for these pathways do not indicate risk relative
to those benchmarks when PPE was considered (see Tables
5-8, 5-10).
EPA developed risk estimates for a single disposal scenario.
The results of this scenario are intended to broadly address
the potential exposures associated with each of the sub-
categories for this condition of use.
Estimated exposed population: 124 workers. 45 occupational
non-users
1 EPA expects there is compliance with federal and state laws, such as worker protection standards, unless case-
specific facts indicate otherwise, and therefore existing OSHA regulations for worker protection and hazard
communication will result in use of appropriate PPE consistent with the applicable SDSs in a manner adequate to
protect workers.
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APPENDICES
Appendix A REGULATORY HISTORY
A.l Federal Laws and Regulations
Table A-l. Federal Laws and Regulations
Statutes/
Regulations
Description of Authority/Regulation
Description of Regulation
EPA Regulations
TSCA - Section
6(b)
EPA is directed to identify and begin risk
evaluations on 10 chemical substances
drawn from the 2014 update of the TSCA
Work Plan for Chemical Assessments.
1,4-Dioxane is on the initial
list of chemicals to be
evaluated for risk under TSCA
(81 FR 91927, December 19,
2016).
TSCA - Section
8(a)
The TSCA section 8(a) CDR Rule requires
manufacturers (including importers) to give
EPA basic exposure-related information on
the types, quantities and uses of chemical
substances produced domestically and
imported into the United States.
1,4-Dioxane manufacturing
(including importing),
processing distribution and use
information is reported under
the CDR rule information
about chemicals in commerce
in the United States.
TSCA - Section
8(b)
EPA must compile, keep current and
publish a list (the TSCA Inventory) of each
chemical substance manufactured or
processed in the United States.
1,4-Dioxane was on the initial
TSCA Inventory and therefore
was not subject to EPA's new
chemicals review process.
TSCA - Section
8(e)
Manufacturers (including importers),
processors and distributors must
immediately notify EPA if they obtain
information that supports the conclusion
that a chemical substance or mixture
presents a substantial risk of injury to
health or the environment.
Ten substantial risk reports
from 1989 to 2004 U.S. EPA.
(2.014a) Accessed April 13,
2017.
EPCRA - Section
313
Requires annual reporting from facilities in
specific industry sectors that employ 10 or
more full time equivalent employees and
that manufacture, process or otherwise use
a TRI-listed chemical in quantities above
threshold levels.
1,4-Dioxane is a listed
substance subject to reporting
requirements under 40 CFR §
372.65 effective as of January
01, 1987.
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Si :i lull's/
Kciziihil ions
Description of Aiilhorily/Ucgiihilion
Description of Ucgiihilion
I'cclei"ill rood,
Drug, and
Cosmetic Act
(FFDCA) -
Section 408
ITDC A go\erns the ill low ah le residues of
pesticides in food. Section 408 of the
FFDCA provides EPA with the authority to
set tolerances (rules that establish
maximum allowable residue limits) or
exemptions from the requirement of a
tolerance, for all residues of a pesticide
(including both active and inert
ingredients) that are in or on food. Prior to
issuing a tolerance or exemption from
tolerance, EPA must determine that the
tolerance or exemption is "safe." Sections
408(b) and (c) of the FFDCA define "safe"
to mean the Agency has reasonable
certainty that no harm will result from
aggregate exposures to the pesticide
residue, including all dietary exposure and
all other exposure (e.g., non-occupational
exposures) for which there is reliable
information. Pesticide tolerances or
exemptions from tolerance that do not meet
the FFDCA safety standard are subject to
revocation. In the absence of a tolerance or
an exemption from tolerance, a food
containing a pesticide residue is considered
adulterated and may not be distributed in
interstate commerce.
In I1WS, 1,4-dio\ane was
removed from the list of
pesticide product inert
ingredients because it was no
longer being used in pesticide
products. 1,4-Dioxane is also
no longer exempt from the
requirement of a tolerance (the
maximum residue level that
can remain on food or feed
commodities under 40 CFR
Part 180, Subpart D).
CAA - Section
111(b)
Requires EPA to establish new source
performance standards (NSPS) for any
category of new or modified stationary
sources that EPA determines causes, or
contributes significantly to, air pollution,
which may reasonably be anticipated to
endanger public health or welfare. The
standards are based on the degree of
emission limitation achievable through the
application of the best system of emission
reduction (BSER) which (considering the
cost of achieving reductions and
environmental impacts and energy
requirements) EPA determines has been
adequately demonstrated.
1,4-Dioxane is subject to the
NSPS for equipment leaks of
volatile organic compounds
(VOCs) in the synthetic
organic chemicals
manufacturing industry for
which construction,
reconstruction or modification
began after 1/5/1981 and on or
before 11/7/2006 (40 CFR Part
60, Subpart VV).
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Si :i lull's/
Kciziihil ions
Description of Aiilhorily/Ucgiihilion
Description of Ucgiihilion
CAA Section
112(b)
Defines llie original list of 189 hazardous
air pollutants (HAP). Under 112(c) of the
CAA, EPA must identify and list source
categories that emit HAP and then set
emission standards for those listed source
categories under CAA section 112(d).
CAA section 112(b)(3)(A) specifies that
any person may petition the Administrator
to modify the list of HAP by adding or
deleting a substance.
1,4-Dioxanc is listed as a 1LYP
under section 112 (42 U.S.C. §
7412) of the CAA.
CAA - Section
112(d)
Section 112(d) states that the EPA must
establish (NESHAPs for each category or
subcategory of major sources and area
sources of HAPs [listed pursuant to
Section 112(c)], The standards must
require the maximum degree of emission
reduction that the EPA determines to be
achievable by each particular source
category. Different criteria for maximum
achievable control technology (MACT)
apply for new and existing sources. Less
stringent standards, known as generally
available control technology (GACT)
standards, are allowed at the
Administrator's discretion for area sources.
There are a number of source-
specific NESHAPs that are
applicable to 1,4-dioxane,
including:
Organic Hazardous Air
Pollutants from the
Synthetic Organic Chemical
Manufacturing Industry (40
CFR Part 63, Subpart F),
Organic Hazardous Air
Pollutants from the
Synthetic Organic Chemical
Manufacturing Industry for
Process Vents, Storage
Vessels, Transfer
Operations, and Wastewater
(40 CFR Part 63, Subpart G)
Off-Site Waste and Recovery
Operations (40 CFR Part 63,
Subpart DD),
Wood Furniture
Manufacturing Operations
(40 CFR Part 63, Subpart
JJ),
Pharmaceuticals Production
(40 CFR Part 63, Subpart
GGG),
Group IV Polymers and
Resins (thermoplastic
product manufacturing) (40
CFR Part 63, Subpart JJJ),
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Si :i lull's/
Kciziihil ions
Description of Aiilhorily/Ucgiihilion
Description of Ucgiihilion
Organic Liquids Distribution
(Non-gasoline) (40 CFR
Part 63, Subpart EEEE),
Miscellaneous Organic
Chemical Manufacturing
(40 CFR Part 63, Subpart
FFFF),
Site Remediation (40 CFR
Part 63, Subpart GGGGG),
and
Miscellaneous Coating
Manufacturing (40 CFR Part
63, Subpart HHHHH).
Comprehensive
Environmental
Response,
Compensation
and Liability Act
(CERCLA) -
Sections 102(a)
and 103
Authorizes EPA to promulgate regulations
designating as hazardous substances those
substances which, when released into the
environment, may present substantial
danger to the public health or welfare or
the environment. EPA must also
promulgate regulations establishing the
quantity of any hazardous substance the
release of which must be reported under
Section 103.
Section 103 requires persons in charge of
vessels or facilities to report to the National
Response Center if they have knowledge of
a release of a hazardous substance above
the reportable quantity threshold.
1,4-Dioxane is a hazardous
substance under CERCLA.
Releases of 1,4-dioxane in
excess of 100 pounds must be
reported (40 CFR 302.4).
Safe Drinking
Water Act
(SDWA) -
Section 1412(b)
Every 5 years, EPA must publish a list of
contaminants that: (1) are currently
unregulated, (2) are known or anticipated
to occur in public water systems (PWSs)
and (3) may require regulations under
SDWA. EPA must also determine whether
to regulate at least five contaminants from
the list every 5 years.
1,4-dioxane was identified on
both the Third (2009) and
Fourth (2016) Contaminant
Candidate List (CCL) (74 FR
51850, October 8, 2009) (81
FR 81099, November 17,
2016).
SDWA - Section
1445(a)
Every 5 years, EPA must issue a new list of
no more than 30 unregulated contaminants
to be monitored by PWSs. The data
obtained must be entered into the National
Drinking Water Contaminant Occurrence
Database.
1,4-dioxane was identified in
the third Unregulated
Contaminant Monitoring Rule
(UCMR3), issued in 2012 (77
FR 26072, May 2, 2012).
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Si :i lull's/
Kciziihil ions
Description of Aiilhorily/Ucgiilalion
Description of Uegiilalion
RCRA Section
3001
Directs EPA to de\ elop and promulgate
criteria for identifying the characteristics of
hazardous waste, and for listing hazardous
waste, considering toxicity, persistence,
and degradability in nature, potential for
accumulation in tissue and other related
factors such as flammability, corrosiveness,
and other hazardous characteristics.
In 1980, 1,4-dioxane became a
listed hazardous waste in 40
CFR§ 261.33 - Discarded
commercial chemical products,
off-specification species,
container residues, and spill
residues thereof (U108) (45 FR
33084).
Other federal regulations
FFDCA
Provides the U.S. Food and Drug
Administration (FDA) with authority to
oversee the safety of food, drugs and
cosmetics.
FDA established a limit of
10 mg/kg on the amount of
1,4-dioxane that can be present
in the food additive glycerides
and polyglycides of
hydrogenated vegetable oils
(21 CFR § 172.736 and 71 FR
12618, March 13,2006).
Occupational
Safety and Health
Act
Requires employers to provide their
workers with a place of employment free
from recognized hazards to safety and
health, such as exposure to toxic chemicals,
excessive noise levels, mechanical dangers,
heat or cold stress or unsanitary conditions.
Under the Act, OSHA can issue
occupational safety and health standards
including such provisions as PELs,
exposure monitoring, engineering and
administrative control measures and
respiratory protection.
In 1989, OSHA established a
PEL for 1,4-dioxane of 100
ppm or 360 mg/m3 as an 8-
hour, TWA (29 CFR §
1910.1001).
While OSHA has established a
PEL for 1,4-dioxane, OSHA
has recognized that many of its
PELs are outdated and
inadequate for ensuring the
protection of worker health.
1,4-Dioxane appears in
OSHA's annotated PEL tables,
wherein OSHA recommends
that employers follow the
California OSHA limit of 0.28
ppm, the NIOSH REL of 1
ppm as a 30-minute ceiling or
the ACGIH TLV of 20 ppm (8-
hour TWA).
Atomic Energy
Act
The Atomic Energy Act authorizes the
Department of Energy to regulate the
health and safety of its contractor
employees
10 CFR § 851.23, Worker
Safety and Health Program,
requires the use of the 2005
ACGIH TLVs if they are more
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Statutes/
Regulations
Description of Authority/Regulation
Description of Regulation
protective than the OSHA
PEL.
Federal
Hazardous
Materials
Transportation
Act
Section 5103 of the Act directs the
Secretary of Transportation to:
Designate material (including an
explosive, radioactive material,
infectious substance, flammable or
combustible liquid, solid or gas, toxic,
oxidizing or corrosive material and
compressed gas) as hazardous when the
Secretary determines that transporting
the material in commerce may pose an
unreasonable risk to health and safety
or property.
Issue regulations for the safe
transportation, including security, of
hazardous material in intrastate,
interstate and foreign commerce.
The Department of
Transportation (DOT) has
designated 1,4-dioxane as a
hazardous material, and there
are special requirements for
marking, labeling and
transporting it (49 CFR Part
171, 40 CFR § 173.202 and 40
CFR § 173.242).
A.2 State Laws and Regulations
Table A-2. State Laws and Regulations
State Actions
Description of Action
State PELs
California PEL: 0.28 ppm (Cal Code Regs. Title 8, § 5155).
State Right-to-Know
Acts
New Jersey (8:59 N.J. Admin. Code § 9.1), Pennsylvania (34 Pa.
Code § 323).
State air regulations
Allowable Ambient Levels (AAL): New Hampshire (RSA 125-1:6,
ENV-A Chap. 1400), Rhode Island (12 R.I. Code R. 031-022).
State drinking/ground
water limits
Massachusetts (310 Code Mass. Regs. § 22.00), Michigan (Mich.
Admin. Code r.299.44 and r.299.49, 2017).
Chemicals of high
concern to children
Several states have adopted reporting laws for chemicals in children's
products that include 1,4-dioxane, such as Oregon (Toxic-Free Kids
Act, Senate Bill 478, 2015) Vermont (Code Vt. R. § 13-140-077) and
Washington State (Wash. Admin. Code § 173-334-130).
Other
In California, 1,4-dioxane was added to the Proposition 65 list in
1988 (Cal. Code Regs, title 27, § 27001).
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A.3 International Laws and Regulations
Country /Organization
Requirements and Restrictions
Canada
1,4-Dioxane is on the Cosmetic Ingredient Hotlist as a substance
prohibited for use in cosmetics. 1,4-Dioxane is also included in
Canada's National Pollutant Release Inventory (NPRI), the
publicly-accessible inventory of pollutants released, disposed of
and sent for recycling by facilities across the country
[Government of Canada (1 1,4-Dioxane. Accessed April
18, 2017],
Australia
In 1994, 1,4-dioxane was assessed. A workplace product
containing more than 0.1% 1,4-dioxane is classed as a
hazardous substance. 1,4-Dioxane is in Class 3, (Packing Group
II) under the Australian Dangerous Goods Code [1,4-Dioxane.
Priority Existing Chemical No. 7. Full Public Report][l,4-
Dioxane. Priority Existing Chemical No. 7. Full Public Report
(1998)].
Japan
1,4-dioxane is regulated in Japan under the following
legislation:
Act on the Evaluation of Chemical Substances and
Regulation of Their Manufacture, etc. (Chemical
Substances Control Law; CSCL)
Act on Confirmation, etc. of Release Amounts of Specific
Chemical Substances in the Environment and Promotion
of Improvements to the Management Thereof
Industrial Safety and Health Act (ISHA)
Air Pollution Control Law
Water Pollution Control Law
[National Institute of Technology and Evaluation (NITE)
Chemical Risk Information Platform (CHIRPHMTH. 2015),
Accessed April 18, 2017],
Republic of Korea
The Ministry of the Environment recently adopted a provisional
water quality standard for human health of 50 |ig/L 1,4-dioxane
in drinking water (An et a'L 2014).
Australia, Austria, Belgium,
Canada, Denmark, European
Union (EU), Finland, France,
Germany, Hungary, Ireland,
Italy, Japan, Latvia, New
Zealand, People's Republic of
China, Poland, Singapore,
South Korea, Spain, Sweden,
Occupational exposure limits for 1,4-dioxane (Insitut fur
\rheitsschutz der (IFA) Deutschen Gesetzlichen
Unfallversicherung. 2.017)(GESTIS International limit values
for chemical agents (Occupational exposure limits, OELs)
database. Accessed April 18, 2017).
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Country/Organization
Requirements and Restrictions
Switzerland, The
Netherlands, Turkey, United
Kingdom
WHO
Established a tolerable daily intake of 16 |ig 1,4-dioxane/kg
body weight based on a no-observed-adverse-effect level
(NOAEL) of 16 mg/kg body weight per day for hepatocellular
tumors observed in a long-term drinking-water study in rats.
The WHO water quality guideline is 0.05 mg/L 1,4-dioxane in
drinking water fWI 35).
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Appendix B - Exposure Scenario Mapping to COU
As part of the Problem Formulation, EPA considered if each unique combination of exposure pathway, route, and receptor in the
lifecycle of 1,4-dioxane would be further evaluated and includes all possible exposure scenarios for each condition of use. EPA
provided the mapping tables that described all possible scenarios developed during problem formulation in tables B-l and B2. EPA
used readily available fate, engineering, exposure and/or toxicity information to determine whether to conduct further analysis on each
exposure scenario.
Industrial and Commercial Occupational Exposure Scenarios for 1,4-Dioxane
EPA has identified release/occupational exposure scenarios and mapped them to relevant conditions of use in Table B-l below. As
presented in the Release/Exposure Scenario column of this table, representative release/exposure scenarios each with 5-6 unique
combinations of exposure pathway, route, and receptor will be further analyzed. EPA further refined the mapping/grouping of
industrial and commercial occupational exposure scenarios based on factors (e.g., process equipment and handling, magnitude of
production volume used, and exposure/release sources) corresponding to conditions of use as additional information is identified
during risk evaluation.
Table B-l. Industrial and Commercial Occupational Ex
josure Scenarios for 1,4-Dioxane
l.il'e ( \ck'
S(;i»c
Siihciilciion
Kck'sisi'/
l'l\pOMIIV
Scenario
Kxposur
c
l\i(h\\;i\
r.\|)ONIMY
Route
Rm-plor
I'll rl her
r.\;ilu;ilion?
Kiilioiiiilo lor I nrlher l.\;ilu;ilion / no
I-'iii'IIkt l-'.\iiliiiiiion
Manufacture
Domestic
Manufacture
or Import
Domestic
Manufacture or
Import
Manufacture of
1,4-dioxane via
acid catalyzed
conversion of
ethylene glycol
by ring closure
Repackaging of
import
containers
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Manufacture
Domestic
Manufacture
or Import
Domestic
Manufacture or
Import
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Manufacture
Domestic
Manufacture
or Import
Domestic
Manufacture or
Import
Vapor
Inhalation
Workers
Yes
Due to high volatility (VP = 40 mmHg)
at room temperature, inhalation exposure
from \ ;i|k>r should bo fuillicr c\ alualcd
Manufacture
Domestic
Manufacture
or Import
Domestic
Manufacture or
Import
Liquid
( nuiacl
Dermal
<>\l
(()ccupaii
oual \ou-
1 sci)
\n
Dermal c\pnsurc is c\pcclcd In he
primarily lo uorkci's dircclk ui\ ol\ ed mi
haiidliuu I lie chemical
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Manufacture
Domestic
Manufacture
or Import
Domestic
Manufacture or
Import
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Domestic
Domestic
Due to high volatility (VP = 40 mmHg)
Manufacture
Manufacture
or Import
Manufacture or
Import
Vapor
Inhalation
ONU
Yes
at room temperature, inhalation exposure
from vapor should be further evaluated.
Domestic
Domestic
Dermal In
Workers.
()\l
Manufacture
Manufacture
Manufacture or
\lls|
halation ()
\n
Misi ueiieraliou is imi e\pecled
or Import
Import
nil
Processing
Processing
as a Reactant
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
The absorption of 1,4-dioxane vapor via
Processing
Processing
as a Reactant
Vapor
Dermal
Workers
No
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Due to high volatility at room
temperature, inhalation exposure from
Processing
as a Reactant
vapor should be further evaluated.
Processing
Pharmaceutical
Intermediate
Pharmaceutical
product
manufacture
Polymer
manufacture
Vapor
Inhalation
Workers
Yes
However, potential for exposure may be
low in scenarios where 1,4-dioxane is
consumed as a chemical intermediate or
used as a catalyst.
Processing
Processing
as a Reactant
Polymerization
catalyst
Liquid
( ouiacl
Dermal
<>\l
\n
Dermal e\posure is e\pecled in he
primariK in worker direclls iii\nl\edni
liaiidlmu I lie chemical
The absorption nf 1,4-din vaiie \ apnr \ la
Processing
Processing
as a Reactant
Vapor
Dermal
ONU
No
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Due to high volatility at room
temperature, inhalation exposure from
Processing
as a Reactant
vapor should be further evaluated.
Processing
Vapor
Inhalation
ONU
Yes
However, potential for exposure may be
low in scenarios where 1,4-dioxane is
consumed as a chemical intermediate or
used as a catalyst.
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Processing
Processing
as a Reactant
\lls|
Dermal lu
halation ()
nil
Workers.
<>\l
\o
Misi ucueralmu is uoi e\pecled
Processing
Liquid
Contact
Dermal
Workers
\ es
W orkers are e\pecled in inuiiueK handle
liquids containing 1,4-dioxane.
Processing
Pharmaceutical
and medicine
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Processing
Non-
incorporativ
e
manufacturing
(process
solvent)
Pharmaceutical
product
manufacture
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Processing
Basic organic
chemical
Basic organic
chemical
Liquid
Couiacl
Dermal
<>\l
\o
Dermal e\pnsuic is e\pecled in he
primarily In wnrkeis ducclK ui\nl\ediu
haiidliuu I lie chemical
Processing
Repackaging
manufacturing
(process
solvent)
manufacture
Repackaging to
Vapor
Dermal
ONU
No
The absorption of l,4-dw\ane \ apor \ la
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Processing
Bulk to
packages, then
large and small
containers
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Processing
distribute
\lisi
Dermal lu
halalmu ()
nil
Workers.
<>\l
\o
Misi ueiieralinu is unl e\pecled
Processing
Recycling
Recycling
Liquid
Contact
Dermal
Workers
Yes
\\ nrkei's are e\pecled In inuiiueK handle
liquids cniilaiiun^ l,4-din\ane.
Processing
Recycling
Recycling
Recycling of
process solvents
containing 1,4-
dioxane
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Processing
Recycling
Recycling
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Processing
Recycling
Recycling
Liquid
Cnuiacl
Dermal
<>\l
\o
Dermal e\pnsure is e\pecled In he
priniariK in workers tlircclK ui\nl\cdiu
haiidliuu ihc chemical
Processing
Recycling
Recycling
Vapor
Dermal
OM
No
The ahsnrpiinii nf 1,4-din\aue \ apnr \ la
skin is expected to be orders of
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magnitude lower than via inhalation and
will not be further analyzed.
Processing
Recycling
Recycling
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Processing
Recycling
Recycling
Mist
Dermal/In
halation/O
ral
Workers,
ONU
Yes
EPA requires additional information on
industry practices for recycling waste
solvents containing 1,4-dioxane to
determine if exposures to mists are
possible.
Distribution
in commerce
Distribution
Distribution
Distribution of
bulk shipment
of 1,4-dioxane
Liquid
Contact,
Vapor,
Mist
Dermal/In
halation/O
ral
Workers,
ONU
Yes
EPA will further analyze activities
resulting in exposures associated with
distribution in commerce (e.g. loading,
unloading) throughout the various
lifecycle stages and conditions of use
(e.g. manufacturing, processing,
industrial use) rather than as a single
distribution scenario.
Industrial use
Intermediate
Use
Agricultural
chemical
Agricultural
product
manufacture
Plasticizer
manufacture
Anhydrous acid,
bromination and
sulfonation
reaction
chemical
manufacture
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Industrial use
intermediate
Plasticizer
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Processing
aids, not
otherwise
listed
intermediate
Catalysts and
reagents for
anhydrous acid
reactions,
brominations
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
However, potential for exposure may be
low in scenarios where 1,4-dioxane is
consumed as a chemical intermediate or
used as a cnlnh s|
Industrial use
and sulfonations
Liquid
( milnel
Dermal
<>\l
\n
Domini e\posure is e\peeled In he
primarih lo workers direelK iu\ ol\ ed in
liaiidluiu I lie chemical
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Industrial use
Polymerization
catalyst
Polymer
Manufacture
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial use
Vapor
Inhalation
ONU
Yes
However, potential for exposure may be
low in scenarios where 1,4-dioxane is
consumed as a chemical intermediate or
used as a catalyst.
Industrial use
\lisi
Dermal In
halation ()
nil
Workers.
()\l
\o
Misi ueueialinu is uoi e\pecled
Industrial use
Processing
aids, not
otherwise
listed
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Industrial use
Processing
aids, not
otherwise
listed
Wood pulping
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Processing
aids, not
otherwise
listed
Extraction of
animal and
vegetable oils
Wood pulping
Extraction of
animal and
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial use
Processing
aids, not
otherwise
listed
Wetting and
dispersing agent
in textile
vegetable oils
Textile
processing
Liquid
( nuiacl
Dermal
()\l
Yes
Dermal e\posuie is e\pecled In he
pi'imai'iK lo woikeis direclk ui\ ol\ ed in
haiidluiu ilie chemical
Industrial use
Processing
aids, not
otherwise
listed
processing
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Processing
aids, not
otherwise
listed
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
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Industrial use
Processing
aids, not
otherwise
listed
Mist
Dermal/In
halation/O
ral
Workers,
ONU
Yes
Mist generation may occur during these
processes.
Industrial use
Processing
aids, not
otherwise
listed
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Industrial use
Processing
aids, not
otherwise
listed
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Processing
aids, not
otherwise
listed
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial use
Processing
aids, not
otherwise
listed
Purification of
pharmaceuticals
Pharmaceutical
product
manufacture
Liquid
( nnlacl
Dermal
<>\l
\n
Dermal e\pnsiire is e\pecleil in he
priiiiariK iii workers tlireelK m\ ol\ ed mi
haiiilliiiu 11 ic chemical
Industrial use
Processing
aids, not
otherwise
listed
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Processing
aids, not
otherwise
listed
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial use
Processing
aids, not
otherwise
listed
\lls|
Dermal In
halation ()
ral
Workers.
<>\l
\n
Misi ueiieraluHi is mil e\peeled
Industrial use
Processing
aids, not
otherwise
listed
Etching of
fluoropolymers
Etching of
fluoropolymers
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Industrial use
Processing
aids, not
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
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otherwise
listed
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Processing
aids, not
otherwise
listed
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial use
Processing
aids, not
otherwise
listed
Liquid
( nulacl
Dermal
<>\l
\n
Dermal c\pnsui'c is e\pecled In he
priuiaiiK iii workeiN dueclK ui\ ol\ ed m
haiidliuu 11 ic chemical
Industrial use
Processing
aids, not
otherwise
listed
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Processing
aids, not
otherwise
listed
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial use
Processing
aids, not
otherwise
listed
Mist
Dermal/In
halation/O
ral
Workers,
ONU
Yes
Mist generation may occur during these
processes.
Industrial use
Functional
fluids
(closed/open
system)
Polyalkylene
glycol lubricant
Cutting and
Tapping Fluid
Synthetic
metalworking
fluid
Hydraulic fluid
Use of
lubricants
Use of
metalworking
fluids
Servicing
hydraulic
equipment and
charging
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Industrial use
Functional
fluids
(closed/open
system)
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Functional
fluids
(closed/open
system)
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial use
Functional
fluids
(closed/open
system)
Liquid
(nulacl
Dermal
()\l
\n
Dermal c\pnsui'c is e\pecled in he
pi'imai'iK lo workeiN dueclK m\ ol\ ed in
haudlum ilie chemical
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Industrial use
Functional
fluids
(closed/open
system)
hydraulic fluids
in original
equipment
manufacture
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial use
Functional
fluids
(closed/open
system)
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial use
Functional
fluids
(closed/open
system)
Mist
Dermal/In
halation/O
ral
Workers,
ONU
Yes
Mist exposure can occur during open
system uses and potentially while
charging and servicing equipment with
hydraulic fluid.
Industrial
use, potential
commercial
use
Laboratory
chemicals
Chemical
reagent
Reference
material
Spectroscopic
and photometric
measurement
Liquid
scintillation and
counting
medium
Stable reaction
medium
Cryoscopic
solvent for
molecular mass
determinations
Preparation of
histological
sections for
microscopic
examination
Laboratory
chemical use
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Industrial
use, potential
commercial
use
Laboratory
chemicals
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial
use, potential
commercial
use
Laboratory
chemicals
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial
use, potential
commercial
use
Laboratory
chemicals
Liquid
( nulacl
Dermal
()\l
\n
Dermal e\posuie is e\pecled in he
piiniariK lo woikeis dueclK ui\ ol\ ed in
haiidluiu I lie chemical
Industrial
use, potential
commercial
use
Laboratory
chemicals
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial
use, potential
commercial
use
Laboratory
chemicals
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial
use, potential
Laboratory
chemicals
\llsl
Dermal In
halation ()
ral
Workers.
()\l
\n
Misi ueiieralKiu is uoi e\pecled
Page 205 of 407
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commercial
use
Industrial
use, potential
commercial
use
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Industrial
use, potential
commercial
use
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial
use, potential
commercial
use
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial
use, potential
commercial
use
Adhesives
and sealants
Other Uses
Film cement
Industrial and
commercial
small brush
application
Liquid
( nulacl
Dermal
()\l
\o
Dermal e\posure is e\pecled In he
primarily lo woikeis direclk ui\ ol\ ed in
haiidliuu I lie chemical
Industrial
use, potential
commercial
use
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial
use, potential
commercial
use
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial
use, potential
commercial
use
\lls|
Dermal In
halaliou ()
nil
Workers.
<>\l
\o
Misi ueueralKHi is ik>i e\pecled
Industrial
use, potential
commercial
use
Other Uses
Spray
polyurethane
foam
Application of
spray
polyurethane
foam through a
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Industrial
use, potential
commercial
use
Printing and
nozzle
Use of Printing
Inks
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
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Industrial
use, potential
commercial
use
printing
compounds
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated
Industrial
use, potential
commercial
use
Liquid
( nulacl
Dermal
()\l
\n
Dermal c\pnsuic is e\pecled in he
primai'iK iii wiirkeis direclK m\ i»l\ ed in
haiidlum 11 ic chemical
Industrial
use, potential
commercial
use
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Industrial
use, potential
commercial
use
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Industrial
use, potential
commercial
use
Mist
Dermal/In
halation/O
ral
Workers,
ONU
Yes
Mist generation may occur during these
processes.
Manufacture,
processing,
use, Disposal
Emissions to
air
Air
Industrial pre-
Liquid
Contact
Dermal
Workers
Yes
Workers are expected to routinely handle
liquids containing 1,4-dioxane.
Manufacture,
processing,
use, Disposal
Wastewater
treatment
Industrial
wastewater
Vapor
Dermal
Workers
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
Manufacture,
processing,
use, Disposal
Solid wastes
and liquid
treatment
Publicly owned
Worker
Handling of
wastes
Vapor
Inhalation
Workers
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Manufacture,
processing,
use, Disposal
wastes
treatment works
(POTW)
Liquid
(nulacl
Dermal
<>\l
\n
Dermal c\pnsuic is e\pecled In he
priiiiai'iK lo woikeis dueclK iu\iil\ediu
haiidlum 11 ic chemical.
Manufacture,
processing,
use, Disposal
Underground
Injection
Municipal
Vapor
Dermal
ONU
No
The absorption of 1,4-dioxane vapor via
skin is expected to be orders of
magnitude lower than via inhalation and
will not be further analyzed.
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Manufacture,
processing,
use, Disposal
landfill
Hazardous
landfill
Vapor
Inhalation
ONU
Yes
Due to high volatility at room
temperature, inhalation exposure from
vapor should be further evaluated.
Manufacture,
processing,
use, Disposal
\lls|
Dermal In
halalion ()
nil
Workers.
<>\l
\o
Misi ueiieralimi is imi especial
Environmental Releases and Wastes Exposure Scenarios for 1,4-Dioxane
Table B-2. During problem formulation, EPA used readily available fate, exposure and/or toxicity information to determine whether to
conduct further analysis on each exposure scenario. EPA has identified release/environmental exposure scenarios and mapped them to
relevant conditions of use in the table below.
Table B-2. Environmental Releases and Wastes Exposure Scenarios for 1,4-Dioxane
l.il'eock- Si;i»e
I si-
CsiU-fion
Ri-kiisi-
l'l\|)OMIIV
PillllNilV
l'l\|)OMIIV
Rouk-
Rm-plor
l"ii rllii-r
l.\;ilu;i(inn?
Kiilioiiiik- lor l-'urlhi-r
1-1 \iiliiiilion / no I'llrlher
l.\;ilu;Uion
Manufacturing
and Processing
TBD
Industrial wastewater
treatment operations
Water
N/A
Aquatic
Species
No
Conservative screening indicates
low potential for risk to aquatic
organisms.
Manufacturing
and Processing
TBD
Industrial wastewater
treatment operations
Water, Air
N/A
Terrestrial
Species
No
Ingestion of water and inhalation
of air are not expected to be
primary exposure routes for
terrestrial organisms (see OPP
tool).
Manufacturing
and Processing
TBD
Industrial wastewater
treatment operations
Sediment
N/A
Terrestrial
Species
No
1,4-Dioxane has low sorption to
soil, sludge, and sediment and
will instead stay in the associated
aqueous phases.
Manufacturing
and Processing
TBD
Industrial wastewater
treatment operations
Sediment
Aquatic
Species
No
Manufacturing
and Processing
TBD
Industrial wastewater
treatment operations
Biosolids
disposed to soil,
migration to
groundwater
N/A
Terrestrial
Species
No
1,4 dioxane is not expected to
remain in soil for long periods of
time due to migration to
groundwater and volatilization
from soil.
Manufacturing
and Processing
TBD
Industrial pre-treatment,
then transfer to Publicly
Water
N/A
Aquatic
Species
No
Conservative screening indicates
low potential for risk to aquatic
organisms.
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Owned Treatment
Works (POTW)
Manufacturing
and Processing
TBD
Industrial pre-treatment,
then transfer to Publicly
Owned Treatment
Works (POTW)
Water, Air
N/A
Terrestrial
Species
No
Ingestion of water and inhalation
of air are not expected to be
primary exposure routes for
terrestrial organisms (see OPP
tool).
Manufacturing
and Processing
TBD
Industrial pre-treatment,
then transfer to Publicly
Owned Treatment
Works (POTW)
Sediment
N/A
Terrestrial
Species
No
1,4-Dioxane has low sorption to
soil, sludge, and sediment and
will instead stay in the associated
aqueous phases.
Manufacturing
and Processing
TBD
Industrial pre-treatment,
then transfer to Publicly
Owned Treatment
Works (POTW)
Sediment
Aquatic
Species
No
Manufacturing
and Processing
TBD
Industrial pre-treatment,
then transfer to Publicly
Owned Treatment
Works (POTW)
Biosolids
disposed to soil,
migration to
groundwater
N/A
Terrestrial
Species
No
1,4-dioxane is not expected to
remain in soil for long periods of
time due to migration to
groundwater and volatilization
from soil.
Disposal
TBD
Municipal landfill,
Hazardous Landfill, and
other land disposal
Soil
N/A
Terrestrial
Species
No
2015 TRI data indicates 3 sites
reporting 13,422 lbs to landfill.
However, 1,4-dioxane has low
sorption to soil.
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Appendix C LIST OF SUPPLEMENTAL DOCUMENTS
1. Associated Systematic Review Data Evaluation Documents - Provides additional detail
and information on individual study evaluations including criteria and scoring results.
a. Risk Evaluation for 1,4-Dioxane, Systematic Review Supplemental File: Updates
to the Data Quality Criteria for Epidemiological Studies
b. Risk Evaluation for 1,4-Dioxane, Systematic Review Supplemental File: Data
Quality Evaluation for Engineering Releases and Occupational Exposure Data
Sources
c. Risk Evaluation for 1,4-Dioxane, Systematic Review Supplemental File: Data
Quality Evaluation of Environmental Hazard Studies
d. Risk Evaluation for 1,4-Dioxane, Systematic Review Supplemental File: Data
Quality Evaluation of Environmental Fate and Transport Studies
e. Risk Evaluation for 1,4-Dioxane, Systematic Review Supplemental File: Data
Quality Evaluation of Human Health Hazard Studies, Animal and In Vitro Studies
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Appendix D Fate and Transport
EPI Suite™ model inputs
To set up EPI Suite™ for estimating fate properties of 1,4-dioxane, 1,4-dioxane was identified
using the "Name Lookup" function. The physical-chemical properties were input based on the
values in Table 2-1. Water solubility was not entered because it is listed as >800 g/L. a value that
is not valid to input. EPI Suite™ was run using default settings (i.e., no other parameters were
changed or input).
PhysProp
Input CAS #
Input Smiles:
Show
Structure
Output
Fugacity
Help
EPI Suite - Welcome Screen
Clear Input Fields
-Output
C Full
(* Summary
0(CC0C1)C1
Input Chem Name: |1-4-Dioxane
Name Lookup
3
EPI Links
Henry LC:
Melting Point:
Boiling Point:
Water Depth:
Wind Velocity:
Current Velocity:
0.0000048 atm-m /mole
Water Solubility:
101.1 Celsius
Vapor Pressure: |
Log Kow:
mg/L
40 mm Hg
-0.27j
~r
meters
meters/sec
meters/sec
o
c
The Estimation Programs Interface (EPI) SuiteTM was developed by the OS Environmental Protection Agency's Office of Pollution Prevention
and Toxics and Syracuse Research Corporation (SRC). It is a screening-level tool, intended for use in applications such as to quickly screen
chemicals for release potential and "bin" chemicals by priority for future work. Estimated values should not be used when experimental
(measured) values are available.
EPI SuiteTM cannot be used for all chemical substances. The intended application domain is organic chemicals. Inorganic and organometallic
chemicals generally are outside the domain.
Important information on the performance, development and application of EPI SuiteTM and the individual programs within it can be
found under the Help tab. Copyright 2000-2012 Onited States Environmental Protection Agency for EPI SuiteTM and all component
programs except BioHCWIN and KOAWIN.
Figure D-l. EPI Suite™ welcome screen set up for 1,4-dioxane model run
As part of problem formulation, EPA also analyzed the sediment, land application and biosolids
pathways. The results of the analyses are described in the 2018 problem formulation for 1,4-
dioxane (U.S. EPA 2018c) and presented below. Fate and Transport were not further analyzed in
this risk evaluation.
Sediment Pathways
1,4-Dioxane is expected to remain in aqueous phases and not adsorb to sediment due to its water
solubility (> 800 g/L) and low partitioning to organic matter (log Koc = 0.4). Limited sediment
monitoring data for 1,4-dioxane that are available suggest that 1,4-dioxane is present in
sediments, but because 1,4-dioxane does not partition to organic matter (log Koc = 0.4) and
biodegrades slowly [<10% biodegradation in 29 days (ECHA 1996)1. 1,4-dioxane
concentrations in sediment pore water are expected to be similar to the concentrations in the
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overlying water. Thus, the 1,4-dioxane detected in sediments is likely from the pore water and
not 1,4-dioxane that was sorbed to the sediment solids.
Land-Applied Biosolids Pathway
1,4-Dioxane is not expected to adsorb to soil and sediment due to its low partitioning to organic
matter (estimated log Koc = 0.4), so 1,4-dioxane in biosolids is expected to be in the aqueous
phase associated with the biosolids rather than adsorbed to the organic matter. The aqueous
phase represents > 95% of biosolids, or > 70% if the biosolids are dewatered, and at the time of
removal the water in the biosolids will contain the same concentration of 1,4-dioxane as the rest
of the wastewater at the activated sludge stage of treatment. However, the volume of water
removed with biosolids represents < 2% of wastewater treatment plant influent volume (U.S.
EPA. 1974). and is < 1% of influent volume when the sludge is dewatered and the excess water
is returned to treatment, a process that is commonly used (NRC. 1996). Thus, the water released
from a treatment plant via biosolids is negligible compared to that released as effluent. By
extension the 1,4-dioxane released from wastewater treatment via biosolids is expected to be
negligible compared to the 1,4-dioxane released with effluents: of the 1,4-dioxane in influent
wastewater, it is expected that < 2% will be removed with biosolids and associated water and >
95% will be present in the effluent (see Section 3.1, Fate and Transport). Further, the
concentrations of 1,4-dioxane in biosolids may decrease through volatilization to air during
transport, processing (including dewatering and digestion), handling, and application to soil
(which may include spraying). When 1,4-dioxane is released in the environment, it is expected to
be mobile in soil and migrate to surface waters and groundwater or volatilize to air. 1,4-Dioxane
is expected to volatilize readily from dry soil and surfaces due to its vapor pressure (40 mm Hg).
Overall, the exposures to surface water from biosolids will be negligible compared to the direct
release of WWTP effluent to surface water.
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Appendix E ENVIRONMENTAL EXPOSURES
Systematic Review for Environmental Exposures
The flow of publications on environmental exposure through systematic review is illustrated in
Section 2.5.1. On-topic literature obtained from Systematic Review were screened via
title/abstract screening and full-text screening for relevance and usability. Through scoping and
problem formulation, EPA determined that no environmental pathways would be further
analyzed. Therefore, none of the 272 studies proceeded to data evaluation per the environmental
exposure PECO statement, which was updated to reflect the results of the aquatic exposure
screen and the determination not to further analyze this pathway.
First-tier Ecological Aquatic Exposure Assessment for 1,4-Dioxane
While recent monitoring data on ambient surface water levels indicate relatively low levels, EPA
used release estimates and measured effluent concentrations from EPA's Toxics Release
Inventory (TRI) and Discharge Monitoring Report (DMR) Pollutant Loading Tool, respectively,
to predict surface water concentrations near such discharging facilities. This first-tier aquatic
exposure assessment evaluates ecological exposures in the US associated with releases of 1,4-
dioxane to surface water. This first-tier, screening approach uses conservative assumptions and
readily-available data and models. In this assessment, conservative surface water concentrations
are estimated for facilities that release the 1,4-dioxane to surface water bodies. The assessment
was conducted using the top ten discharging facilities that submit DMRs, as well as the top ten
releasers that report to the TRI. Both sets of facilities and associated release amounts were
identified using EPA's Enforcement and Compliance History Online (ECHO) Water Pollutant
Loading Tool. Surface water concentrations were estimated for the two most recent years with
complete data sets and EPA's Exposure and Fate Assessment Screening Tool. Version 201 •_)_
(I S * • \ _. <' i_1 ). The two most recent years with complete data at the time of this analysis
were 2014 and 2015 for TRI and 2015 and 2016 for DMR. However, EPA has since reviewed
data for the top ten discharging facilities from more recent complete reporting years, through
2017. Most of the top ten dischargers are similar across the years analyzed (2014-2015) and the
more recent reporting years (2016-2017). The overall range of annual release amounts across
these top ten dischargers remained relatively stable, with the exception of a few sites. One site
(M&G polymers), which did not show up in the list of top dischargers in the years analyzed
(2014-2015), shows up as the top discharger in 2016 and 2017. However, this site was accounted
for in the analysis of 2016 DMR dischargers. It is not expected that the incorporation of the more
recent TRI reporting years would have altered the conclusions of the screening-level assessment
undertaken in problem formulation. Similarly, in looking at the DMR top ten discharging
facilities from 2017, the overall range of annual release amounts across sites remained relatively
stable, with the exception of a few sites. Two sites reported much lower releases in 2017
compared with 2016 and one site (Beacon Heights Landfill) reported much higher releases in
2017. Based on the screening-level analysis, it is unlikely that this increased release would have
led to any exceedance of the COCs. It is not expected that the incorporation of the more recent
DMR reporting year would have altered the conclusions of the screening-level assessment
undertaken in problem formulation.
Table E-l shows the environmental release data from TRI reported in the 1,4-Dioxane Problem
Formulation document.
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Table E-]
. Summary of 1,4-Dioxane TRI Releases to the Environment in 2015 (1
bs)
Number of
Facilities
Air Releases
Water
Releases
Land Disposal
Other
Releases
Total On-
and Off-site
Disposal or
Other
Releases b'
Stack Air
Releases
Fugitive
Air
Releases
Class I
Underground
Injection
RCRA
Subtitle C
Landfills
All other
Land
Disposal"
Subtotal
46,219
16,377
563,976
13,376
49
Totals
49
62,596
35,402
577,400
0
675,399
Data source: 2015 TRI Data (undated March 20171 (IIS, EPA. 2017eY
3 Terminology used in these columns may not match the more detailed data element names used in the TRI public data and analysis access points.
b These release quantities include releases due to one-time events not associated with production such as remedial actions or earthquakes.
c Counts release quantities once at final disposition, accounting for transfers to other TRI reporting facilities that ultimately dispose of the chemical waste.
Predicted surface water concentrations ranged from 0.006 to 11,500 |ig/L for the set of top
dischargers modeled, based on the two complete years of most recent data available at the time
the analysis was conducted during problem formulation (2014-2016). These concentrations were
predicted using conservative assumptions to inform whether or not further evaluation of the
aquatic exposure pathway is supported.
Facility Selection
This assessment predicts conservative surface water concentrations for a set of facilities
reporting recent releases of 1,4-dioxane via DMR and/or TRI. Both sets of facilities were queried
from ECHO'S Water Pollutant Loading Tool. DMR includes pollutant loading information for
more than 60,000 DMR reporting facilities (industrial and municipal point source dischargers)
regulated under the Clean Water Act. It contains wastewater monitoring and other facility data,
as reported on facility-specific DMRs. TRI contains reporting information on facilities in
specific industry sectors which employ more than 10 full-time equivalent employees and
manufacture, process, or use more than 25,000 lbs per year of a TRI-listed chemical.
The analysis was conducted on ten DMR facilities and ten TRI facilities covering the two most
current and complete reporting years available (i.e., 2015 and 2016 for DMR and 2014 and 2015
for TRI). Overall, this represents facilities in the 64th to 100th percentiles, based on annual
loading/release estimates. As many of the facilities overlapped between the DMR and TRI sets,
and between the assessment years, a total of 21 unique facilities were assessed.
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Table E-2 below summarizes characterizing information.
Table E-2. Facility Selection Characterization
Parameter
DMR - 2015
DMR - 2016
TRI - 2014
TRI - 2015
Universe of Facilities
No. of Facilities
54
61
2270
2338
No. of Facilities with annual
loading >0
26
31
154
165
Annual Loading:
Maximum
95th percentile
50th percentile
Minimum
20,974
20,733
38.6
0.000074
30,319
25,047
16.6
0.15
18,188
798.1
5.0
0.01
17,857
820.40
5.0
0.01
No. of Facilities in Top 5th
percentile for discharging
1
2
9
9
Facilities Selected
Number Selected
10
10
10
10
Annual Loading/Release
Percentile % (Range)
64-100%
70-100%
94-100%
94-100%
SIC Represented
N=5
2821,4952,
2869, 2899,
3861
N=5
2821, 4952,
2869, 3861,
blank (landfill)
N=6
2821, 2869,
2819, 2911,
2812, blank
N-5
2821, 2819, 2869,
2812, 2879
NAICS Represented
N=5
325211, 325180,
325199, 324110,
486990
N=4
325211,325199,
486990,328180
No. ofPOTWs
4
5
0
0
No. of non-POTWs
6
5
10
10
-No. of direct dischargers
(non- POTW)
6
4
10
10
-No of indirect dischargers
(non- POTW)
0
1 (Beacon
landfill -
discharges to
POTW)
0
0
States Represented
N=5
CA, NY, MO,
sc, wv
N=6
CA, CT, PA,
NY, SC, WV
N=4
KY, LA, SC, TX
N=4
KY, LA, SC, TX
The following basic information was collected for each facility and is shown in the supplemental
file titled 1,4-D Supplemental - Aq Screen Facility Information 062419:
• DMR: Site name, location (city, state, latitude, longitude), NPDES code, SIC code, NAICS
Code, FRS ID, average effluent concentration (mg/L), maximum effluent concentration (mg/L),
total pounds (lbs/yr), average flow (MGD), flag for potential outlier, and max allowable load
(lbs/yr).
• TRI: Site name, location (city, state, latitude, longitude), NPDES code, NAICS Code, FRS ID,
TRI Facility ID, and Direct TRI Pounds (lbs/yr).
• Receiving Water Information: Waterbody Number (REACH code) and Waterbody Name (from
GNIS).
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Estimating Surface Water Concentrations
Surface water concentrations were estimated for multiple scenarios using E-FAST (
2014c) which can be used to estimate site-specific surface water concentrations based on
estimated loadings of 1,4-dioxane into receiving water bodies. The reported annual loading
estimates for DMR facilities are calculated by using the reported effluent concentrations and
facility effluent flows. For TRI, the reported releases are based on monitoring, emission factors,
mass balance and/or other engineering calculations. These reported annual loading amounts
(lbs/year) were first converted to release inputs required by E-FAST (kg/day) by converting from
lbs to kgs and dividing by the number of release days for a given scenario. The reported annual
loading amounts (lbs/year) are shown in the supplemental file, Supplemental File: Aquatic
Exposure Screen Facility Information, while the release inputs (kg/day) are shown in Tables E-3
and E-4.
E-FAST (U ,S. EPA. ) incorporates stream dilution at the point of release using stream flow
distribution data contained within the model. The stream flow data have not been updated
recently and may differ from current values obtained from NHD or USGS gages. Site-specific
stream flow data are applied using a National Pollutant Discharge Elimination System (NPDES)
code. If a specific discharger's NPDES code could not be identified within the E-FAST database,
a surrogate site or generic Standard Industrial Classification (SIC) code was applied (i.e.,
Industrial POTW).
E-FAST 2014 can incorporate wastewater treatment removal efficiencies. Wastewater treatment
removal is assumed to be 0% for this exercise, as reported direct loadings/releases are assumed
to account for any pre-release treatment. Because the days of release and/or operation are not
reported in these sources, E-FAST (U S_ rPA 20] Jc) is run assuming hypothetical release-day
scenarios (i.e., assuming 1, 20, and 250 days for facilities and 250 days for Wastewater or
Sewage Treatment Plants [WWT/STP]). For WWTP/STP facilities, it is assumed that a lower
number of release and/or operation days is unlikely. Refer to the E-FAST 2014 Documentation
Manual for equations used in the model to estimate surface water concentrations (U.S. EPA.
2014c).
The modeled surface water concentrations presented in Tables E-3 and E-4 are associated with a
low flow - 7Q10, which is an annual minimum seven-day average stream flow over a ten-year
recurrence interval. The 10th percentile 7Q10 stream flow is used to derive the presented surface
water concentrations. No post-release degradation or removal mechanisms (e.g., hydrolysis,
aerobic degradation, photolysis, volatilization) are applied in the calculation of the modeled
surface water concentrations.
Modeled Surface Water Concentrations
Tables E-3 and E-4 present the results of this first-tier aquatic exposure assessment. Based on the
top ten DMR discharging facilities in 2015 and 2016, predicted surface water concentrations,
which were based on the 10th percentile 7Q10 stream flow, ranged from 0.095 to 11,500 |ig/L.
Based on the top ten TRI discharging facilities in 2014 and 2015, predicted surface water
concentrations ranged from 0.006 to 9,734 |ig/L. The estimated 10th percentile surface water
concentrations derived from chronic release scenarios (i.e., those assuming 20 days or more of
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annual release days) were compared against the chronic COC using E-FAST's high-end
Probabilistic Dilution Model (PDM).
It is assumed that these modeled surface water concentrations are higher than those that would be
present from non-point sources based on the conservative nature of the estimation approaches
including the following: surface water concentrations would be expected to decrease downstream
and this modeling analysis does not account for downstream transport and fate processes; non-
zero wastewater removal rates would be applied for any indirect releases that pass through a
treatment facility before release; and assuming a low-end number of release days (i.e., 1 day per
year) assumes the total annual loading estimate occurs over 1 day.
Table E-3. Summary of Modeled Surface Water Concentrations for DMR Facilities
Facility
E-FAST Inputs and Results
NPDES Used in E-F AST
Name
Days of
Releasea
Releasea
(kg/day)
10th Percentile
7Q10
Concentration
(Hg/L)
Days Exceedance
(days/yr)
COC = 14,500 fig/L
Reporting Year 2016
WV0000132
(SIC 2821)
M and G Polymers
USA, LLC
1
13,752.5
968.17
NA
20
687.6
48.41
0
250
55.0
3.87
0
SC0026506
(SIC 2821)
10 b
976.7 b
11.500 b
NA
Dak Americas LLC
20
488.3
5.761.65
0
250
39.1
461.36
0
SC0046311c
(SIC 4952)
Lake City
Wastewater
Treatment Plant
250
5.4
695.88
0
WV0000086
(SIC 2869)
1
271.2
81.19
NA
Institute Plant
20
13.6
4.07
0
250
1.1
0.33
0
NY0001643
(SIC 3861)
1
78.5
74.46
NA
Eastman Kodak
20
3.9
3.7
0
250
0.3
0.28
0
PA0026492
The Scranton
250
0.2
1.85
0
(SIC 4952)
Sewer Authority
CA0054011
(SIC 4952)
Los Coyotes Water
Reclamation Plant
250
0.2
1.45
20
CTMIU0161
(SIC Blank) ¦=> CT0101061 d
Beacon Heights
Landfill ¦=> Beacon
Falls WPCF
250
0.16
1.10
0
CA0053911
(SIC 4952)
San Jose Creek
Water Reclamation
Plant
250
0.1
0.47
20
CA0056227
Donald C Tillman
250
0.1
1.49
0
(SIC 4952)
WRP
Reporting Year 2016
Min
0.28
Max
11.500 ''
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Facility
E-FAST Inputs and Results
NPDES Used in E-FAST
Name
Days of
Releasea
Releasea
(kg/day)
10th Percentile
7Q10
Concentration
(Ug/L)
Days Exceedance
(days/yr)
COC = 14,500 fig/L
Reporting Year 2015
WV0000132
(SIC 2821)
M and G Polymers
USA, LLC
1
9,513.6
669.75
NA
20
475.7
33.49
0
250
38.1
2.68
0
SC0026506
(SIC 2821)
10b
920.2 b
10,900 b
NA
Dak Americas LLC
20
460.1
5.428.91
0
250
36.8
434.22
0
SC0046311c
(SIC 4952)
Lake City
Wastewater
Treatment Plant
250
4.3
554.12
0
SC0002798
(SIC 2821)
Auriga Polymers,
Inc.
1
155.1
521.38
NA
20
7.8
26.22
0
250
0.6
2.02
0
WV0000086
(SIC 2869)
1
91.6
27.42
NA
Institute Plant
20
4.6
1.38
0
250
0.4
0.12
0
CA0054011
(SIC 4952)
Los Coyotes Water
Reclamation Plant
250
0.1
0.73
20
CA0053953
(SIC 4952)
LA-Glendale WRP
250
0.1
2.93
0
CA0056227
(SIC 4952)
Donald C Tillman
WRP
250
0.1
1.49
0
M00101184
(SIC 2899)
Buckman
Laboratories, Inc.
1
20.0
1.819.84
NA
20
1.0
90.99
0
250
0.1
9.1
0
NY0001643
(SIC 3861)
1
19.8
18.78
NA
Eastman Kodak
20
1.0
0.95
0
250
0.1
0.0949
0
Reporting Year 2015
Min
0.0949
Mac
10,900 b
a. Days of release (1, 20, or 250) are EPA assumptions that provide a range of potential surface water concentrations; days of release were not
reported in DMR. The release (kg/day) is based on the per day based on total annual loading (lbs/yr), as reported in DMR Pollutant Loading
Tool, and is divided by the assumed number of release days prior to modeling.
b. The Dak chemicals site acute scenario was re-run for a 10-day acute scenario based on input from EPA engineers related to the lowest
number of operating days assumed for facilities falling within this standard industrial category (i.e., 10 days per year). Therefore, maximum
surface water concentrations based on this site reflect an assumed 10 days per year of release instead of 1 day.
c. Flow data was not available in E-FAST 2014 for NPDES SC0046311 (Lake City Wastewater Treatment Plant) and an appropriate surrogate
was not readily identified. Therefore, a generic SIC code (4952 - Industrial POTW) was applied in E-FAST.
d. NPDES CTMIU0161 (Beacon Heights Landfill) is not in the E-FAST 2014 database. This site is a landfill and is in the Superfund program.
Leachate collected from this site is sent through a leachate transportation line to the local sewer system and to the Beacon Falls Treatment
Plant (Beacon Falls WPCF; NPDES CT0101061).
https://cumulis.epa.gov/supercpad/SiteProfiles/index.cfm?fuseaction=second.Cleanup&id=0100180#bkground
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Table E-4. Summary of Modeled Surface Water Concentrations for TRI Facilities
NPDES Used in E-
FAST
Name
Days of
Release"
Releasea
(kg/day)
7Q10
Concentration
(Mg/L)
Days Exceedance
(days/yr)
COC = 14,500
Hg/L
Reporting Year 2015
SC0026506
DAK AMERICAS LLC
COOPER RIVER
PLANT
10 b
809.98 b
9,557 b
NA
20
404.99
4778.64
0
250
32.40
382.3
0
LA0036421c
BASF CORP
1
5361.46
21.7
NA
20
268.07
1.09
0
250
21.45
0.0868
0
LA0036421 d
HONEYWELL
INTERNATIONAL
INC-BATON ROUGE
PLANT
1
1036.00
4.19
NA
20
51.80
0.21
0
250
4.14
0.0168
0
TX0124915
DOW CHEMICAL CO
FREEPORT FACILITY
1
942.11
361.13
NA
20
47.11
18.06
0
250
3.77
1.45
0
LA0000191
ST CHARLES
OPERATIONS
(TAFT/STAR) UNION
CARBIDE CORP
1
817.37
3.31
NA
20
40.87
0.17
0
250
3.27
0.0132
0
KY0003484
WESTLAKE VINYLS
INC
1
735.27
31.88
NA
20
36.76
1.59
0
250
2.94
0.13
0
TX0002844e
UNION CARBIDE
CORP SEADRIFT
PLANT
1
640.02
7685.62
NA
20
32.00
96.07
NA
250
2.56
7.69
NA
NC0003719
DAK AMERICAS LLC
1
439.08
561.96
NA
20
21.95
28.09
0
250
1.76
2.25
0
LA0003301f
THE DOW CHEMICAL
CO - LOUISIANA
OPERATIONS
1
398.71
1.61
NA
20
19.94
0.0807
0
250
1.59
0.00644
0
KY0003603
ARKEMA INC
1
265.80
11.53
NA
20
13.29
0.58
0
250
1.06
0.046
0
Reporting Year 2015
Min
0.006
Max
9,557 b
Reporting Year 2014
SC0026506
DAK AMERICAS LLC
COOPER RIVER
PLANT
10 b
824.99 b
9.734 b
NA
20
412.50
4.873
0
250
33.00
389.4
0
LA0000761
EAGLE US 2 LLC
1
1886.94
2.137
NA
20
94.35
107.4
0
250
7.55
9
0
LA0036421c
BASF CORP
1
1198.84
4.85
NA
20
59.94
0.24
0
250
4.80
0.0194
0
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NPDES Used in E-
FAST
Name
Days of
Releasea
Release"
(kg/day)
7Q10
Concentration
(Hg/L)
Days Exceedance
(days/yr)
COC = 14,500
Ug/L
LA0036421 d
HONEYWELL
INTERNATIONAL
INC-BATON ROUGE
PLANT
1
1030.56
4.18
NA
20
51.53
0.21
0
250
4.12
0.02
0
LA0000191
ST CHARLES
OPERATIONS
(TAFT/STAR) UNION
CARBIDE CORP
1
783.81
3.2
NA
20
39.19
0.16
0
250
3.14
0.012
0
KY0070718
CATLETTSBURG
REFINING LLC
1
744.80
1.019
NA
20
37.24
50.6
0
250
2.98
4.1
0
TX0124915
DOW CHEMICAL CO
FREEPORT FACILITY
1
686.28
264
NA
20
34.31
13
0
250
2.75
1
0
LA0003301f
THE DOW CHEMICAL
CO - LOUISIANA
OPERATIONS
1
469.92
1.9
NA
20
23.50
0.0951
0
250
1.88
0.00761
0
KY0003484
WESTLAKE VINYLS
INC
1
303.91
13.23
NA
20
15.20
0.65
0
250
1.22
0.0434
0
KY0003603
ARKEMA INC
1
299.37
13.01
NA
20
14.97
0.65
0
250
1.20
0.0434
0
Reporting Year 2014
Min
0.012
Max
9.734 b
a. Days of release (1, 20, or 250) are EPA assumptions that provide a range of potential surface water concentrations; days of release were not
reported to TRI. The release (kg/day) is based on the per day based on annual releases to surface water (lbs/yr), as reported to TRI, and is
divided by the assumed number of release days prior to modeling.
b. The Dak chemicals site acute scenario was re-run for a 10-day acute scenario based on input from EPA engineers related to the lowest
number of operating days assumed for facilities falling within this standard industrial category (i.e., 10 days per year). Therefore, maximum
surface water concentrations based on this site reflect an assumed 10 days per year of release instead of 1 day.
c. For facility BASF CORP (LA0004057), E-FAST appears to show that this facility discharging to Bayou Baton Rouge. Communications
with the Louisiana Department of Environmental Quality confirmed this site discharges process waters to the Mississippi River via pipeline,
so an appropriate surrogate, the Baton Rouge POTW (NPDES LA0036421), was used in E-FAST for the purposes of applying stream flow.
d. For facility HONEYWELL INTERNATIONAL INC-BATON ROUGE PLANT (LA0000329), the receiving stream identified differs
between E-FAST (Monte Sano Bayou) and DMR (Mississippi River). EPA confirmed through the online USGS NHD tool, as well as
through communication with the Louisiana Department of Environmental Quality, that the receiving water based on the REACH code for
the Honeywell International Plant is indeed the Mississippi River and not the Monte Sano Bayou, a small stream flowing through Baton
Rouge, Louisiana. An appropriate surrogate is the Baton Rouge POTW (NPDES LA0036421).
e. The facility UNION CARBIDE CORP SEADRIFT PLANT does not have a NPDES listed in DMR; however, a facility name and location
search within E-FAST 2014 returned a NPDES (TX0002844), which was used for modeling.
f. The NPDES provided in DMR's Pollutant Loading Tool for the facility THE DOW CHEMICAL CO - LOUISIANA OPERATIONS
(NPDES LA0116602) was not found in E-FAST 2014; however, a facility name and location search within E-FAST 2014 returned a
different NPDES (LA0003301) associated with this facility name and location, so it was applied for modeling.
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Appendix F ENVIRONMENTAL HAZARDS
F.l Systematic Review
EPA reviewed ecotoxicity studies for 1,4-dioxane according to the data quality evaluation
criteria found in The Application of Systematic Review in TSCA Risk Evaluations (U.S. EPA.
2018b). The results of these ecotoxicity study evaluations can be found in 1,4-Dioxane (123-91-
1) Systematic Review: Supplemental File for the TSCA Risk Evaluation Document.
The data quality evaluation indicated these studies are of high confidence and are used to
characterize the environmental hazards of 1,4-dioxane. These studies support that hazard of 1,4-
dioxane to aquatic organisms is low and that no further evaluation is required.
The aquatic studies that were evaluated for 1,4-dioxane are summarized in Table F-l. The hazard
of these studies have been reported in (Health Canada. 2010; ECJRC. 2002; OE( )9;
NICNAS. 1998); and the European Chemicals Agency (ECHA) Database as stated in the
Problem Formulation of the Risk Evaluation for 1,4-Dioxane (EPA-HQ-OPPT-2016-0723).
Table F-l. Acceptable acute aquatic toxicity studies that were evaluated for of 1.4-Dioxane
IVsi Spii iis
\k'ili;i
T\ pi-
l)iir;ilinii
I!\|)iisiiiv
' > lK"
(iK'iiiiiiil
All;il\sis
i:nwiis)
Cihiiiiin
l):il;i
Qu;ilil\
R;ilin»
Plants
Blue-Green
Algae
(,Microcystis
aeruginosa)
Fresh
water
8-day
LOEC = 575
AI mg/L
Static
Unmeasured
Population,
growth rate
(Brineman
and Kulin,
High
1977)
EC5o = 575
AI mg/L
Not
reported
Population
changes,
fBringiiiaiin
and Kulin,
High
Blue-Green
Algae (Anacystis
aeruginosa)
EC5o= 575
AI mg/L
Static
Population
1978)
Green Algae
(Scenedesmus
quadricauda)
LOEC =
5,600 AI
mg/L
Static
Population,
growth rate
Green Algae
(.Scenedesmus
quadricauda)
8-day
5,600 AI
mg/L
Static
Population
10-day
5,600 AI
mg/L
Not
reported
Biomass
Invertebrates
Water flea
(Daphnia
magna)
Fresh
water
24-hour
ECso = 8450
AI mg/L
Static
Not reported
Behavior,
Equilibrium
fBringiiiaiin
and Kuehn.
1982)
High
Water flea
(.Daphnia
magna)
Fresh
water
24-hour
LCso = 4700
AI mg/L
Static
Unmeasured
Intoxication
rBrinaiiiaiin
and Kulin,
High
1977)
Water flea
(.Daphnia
magna)
Fresh
water
48-hour
EC50 = 4269
AI mg/L
Static
Unmeasured
Mortality
(Brooke,
1987)
High
Amphipod
(Gammarus
pseudolimnaeus)
Fresh
water
96-hour
LC50 = 2,274
AI mg/L
Flow-
through
Measured
Mortality
(Brooke,
1987)
Fish
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IVsi Spii iis
T\ pi-
l)iir;ilinii
I!\|)iisiiiv
' > lK"
(iK'iiiiiiil
All;il\sis
i:nwiis)
Cihiiiiin
l):il;i
Qu;ilil\
R;ilin»
Fathead minnow
(.Pimephales
promelas)
Fresh
water
96-hour
LC50 =
13,000 AI
mg/L
Static
Unmeasured
Mortality
(Dow
Chemical.
1989a-)
High
LOEC =
10,000 AI
mg/L
Bluegill sunfish
(Lepomis
macrochirus)
Fresh
water
96-hour
LC50 =
10,000 AI
mg/L
Static
Unmeasured
Mortality
(Dawson et
)
High
Silverside
(,Menidia
beryllina)
Salt
water
96-hour
LC50 = 6,700
AI mg/L
Fathead minnow
(.Pimephales
promelas)
Fresh
water
96-hour
LC5o= 1,236
AI mg/L
Static
Measured
Mortality
(Brooke,
1987)
High
LC50 = 9,872
AI mg/L
Flow-
through
Fathead minnow
(.Pimephales
promelas)
Fresh
water
96-hour
LC50 = 9,850
AI mg/L
Flow-
through
Measured
Mortality
(Geieer et
aL 1990)
High
LC50 =
10,800 AI
mg/L
F.2 Hazard Identification- Aquatic
Table F-l provides the species, media, duration, endpoint, effects, etc. for the acceptable acute
toxicity studies that were evaluated. To characterize acute toxicity for aquatic plants, two short-
term toxicity studies in Microcystis aeruginosa and Scenedesmus quadricauda reported EC50
cell inhibition of 575 and 5,600 mg/L after eight days of exposure to 1,4-dioxane (Bringmann
and Kuhn. 1978; Blineman andKuhn. 1977).
Three studies characterize the toxicity of 1,4-dioxane to aquatic invertebrates. Brooke (1987)
reported a 48-hour EC50 of 4,269 mg/L to Daphnia magna and a 96-hour LC50 of 2,274mg/L to
amphipods (Gammaruspseudolimnaeus). Also, a 24-hour EC50 of 4,700 was reported by
Bringmann and Kuhn (1977).
The acute 96-hour LC50 values for fish range from 1,236 mg/L for fathead minnow {Pimephales
promelas) to 6,700 mg/L for inland silversides (Menidia beryllina).
Table F-2 provides the species, media, duration, endpoint, effects, etc. for the acceptable chronic
toxicity studies that were evaluated. In a chronic study, medaka (Oryzias latipes) were exposed
to measured concentrations of 1,4-dioxane ranging from 50 mg/L to 6,933 mg/L for 28 days
under flow-through conditions. There were effects on growth and survival (Johnson ?).
A low observed effect concentration (LOEC) of 565 mg/L was reported. In another study,
fathead minnows (P. promelas) were exposed to 1,4-dioxane for 32 days to mean measured
concentrations of 3, 27.6, 40.3, 65.3, 99.7 and 145 mg/L to observe the effects on embryonic
development (i.e., hatching, larval development, and larval survival) under flow-through
conditions. No effects were observed based on larval survival so a maximum acceptable toxicant
concentration (MATC) of 145 mg/L was calculated (Dow Chemical. 1989a).
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Table F-2. Acceptable chronic aquatic toxicity studies that were evaluated for of 1,4-
Dioxane
1 es( Spocios
Mcriiii
Tj po
Dui'iiliun
I'liulpuinl
l'l\|)OMIIV
Tj \W
( homiciil
An;il\sis
r.lTocl(s)
( iliiliun
l);il;i
Qu;ilil\
l!\;ilii;ilii>n
/7 s//
Fathead
minnow
(Pimephales
promelas)
Fresh
water
32-day
MATC =
>145 AI
mg/L
Flow-
through
Measured
Growth/
Weight
Hatchability
Survival
Development
(Dow
Chemical.
1989a")
High
Medaka
(O ryzias
latipes)
Fresh
water
28-day
LOEC =
565 AI
mg/L
Flow-
through
Measured
Survival
("Johnson et
aL 1993)
High
F.3 Concentrations of Concern (CQC)
The concentrations of concern (COCs) for aquatic species were calculated based on the
summarized environmental hazard data for 1,4-dioxane. The analysis of the environmental COCs
are based on EPA methods ( d). The acute and chronic COC for 1,4-dioxane are
based on the lowest toxicity value in the dataset. For a particular environment (e.g., aquatic
environment), the COC is based on the most sensitive species or the species with the lowest
toxicity value reported in that environment.
After selecting the lowest toxicity value, an assessment factor (AF) is applied according to EPA
methods (U.S. EPA. 2012d). The application of AFs provides a lower bound effect level that
would likely encompass more sensitive species not specifically represented by the available
experimental data. AFs are also account for differences in inter- and intra-species variability, as
well as laboratory-to-field variability. These assessment factors are dependent upon the
availability of datasets that can be used to characterize relative sensitivities across multiple
species within a given taxa or species group but are often standardized in risk assessments
conducted under TSCA, since the data available for most industrial chemicals is limited. The
acute COC for the aquatic plant endpoint is determined based on the lowest value in the dataset
divided by an assessment factor (AF) of 4. For fish and aquatic invertebrates (e.g., daphnia) the
acute COC values are divided by an AF of 5. For chronic COCs, an AF of 10 is used.
F.3.1 COC for Acute Aquatic Toxicity
The lowest acute toxicity value for aquatic organisms (i.e., most sensitive species) for 1,4-
dioxane is from a 96-hour fish toxicity study where the LC.mi is 1,236 mg/L (Geiger et at.. 1990).
The lowest value was then divided by the assessment factor (AF) of 5 for fish.
The acute concentration of concern for 1,4-dioxane is based on a 96-hour fish toxicity study
(ECHA. 2014; Geieeretai. 1990). The lowest value for the 96-hour fish toxicity LCso 1,236
mg/L) / AF of 5 = 247 mg/L or 247,200 |ig/L or ppb. The acute COC for 1,4-dioxane is 247,200
ppb based on the lowest value LCso.
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F.3.2 COC for Chronic Aquatic Toxicity
For the chronic COC, the lowest chronic toxicity value is from a chronic 32-day MATC fathead
minnow study of > 145 mg/L (Brooke. 1987). This value was divided by an assessment factor of
10 then multiplied by 1,000 to convert from mg/L to |ig/L or ppb.
The lowest value for 32-day fish MATC = 145 mg/L / 10 = 14.5 x 1000 = 14,500 |ig/L or ppb.
Therefore, the chronic COC for 1,4-dioxane is 14,500 ppb based on the lowest chronic toxicity
value.
Appendix G OCCUPATIONAL EXPOSURES
G.l Systematic Review Summary Tables
G.l.l Evaluation of Inhalation Data Sources Specific to 1,4-Dioxane
EPA has reviewed acceptable sources for 1,4-dioxane inhalation exposure data according to the data
quality evaluation criteria found in The Application of Systematic Review in TSCA Risk Evaluations
(U.S. EPA. 2018b). Table G-l summarizes the results of this evaluation. The data quality evaluation
indicated the sources included are of medium to high confidence and are used to characterize the
occupational inhalation exposures of 1,4-dioxane.
Page 224 of 407
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Page 225 of 407
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Table G-l. Summary of Inhalation Monitoring Data Sources Specific to 1,4-Dioxane i
Rim
()i'i'll|l;ilinll;i
1 l!\|)iisuiv
Sii-ii;ii'in
T\ pi- ill'
S;ini|ik-
Worker Aiii\ ii\
HI' S;i111|> 1 ill<^
l.iii;iiiiin
l.4-l)iii\;iiu-
Airluiriu-
(iiiHviilniliiin
f iiifi/m-'i ¦'
NiiihIkt ill'
S;ini|)k's
T\ |K" III'
Mi';isumiU'iil
S;illl|ik-
liliu-
S( ill I'll'
Diici
Idi'lllililT
I'l l Mil |);||;|
l'\li';iiiiiin
;iiul
l!\;illl;iliiill
()\i'l';ill l):il;i
(|ll;ilil\ i';i 1 in<^
I'l'iilll l);il:i
I'.Ml'iiiliiill
;ill(l
l'.\;ilu;iliiin
K;ilimi;ik' I'm'
1 nclusiiill /
I'.M'liisiiui
1
Laboratory
Chemicals
Personal
Solvent extraction
and TLC
1.8 ppm
(highest value)
Unknown
Unknown
Unknown
NICNA
S, 1998
(MCNA5,
1.998)
High
Included -
Referenced in
comparison to
other available
data in the
Laboratory
Chemical
OES.
2
Film Cement
Personal
Film cement
application
<1 ppm
Unknown
Unknown
Unknown
NICNA
S, 1998
fNICNAS,
1998)
High
Included -
Referenced in
comparison to
other available
data in the
Film Cement
OES.
3
Industrial
Use
Area and
Personal
Metal cleaning
surface, Medicine
manufacture, Shirt
cleaning area,
textile
industry,
Pharmaceutical
production
Manufacture of
magnetic tapes,
Use (e.g. as
solvent) in other
productions
Central
Tendency: 5
mg/m3
High-end: 20
mg/m3
Eight
datasets -
each has
between 2
and 194
samples per
set
Full-shift and
Short term
6-8 hour
for full
shift,
0-0.5 hour
for short
term
ECJRC,
2002
(ECJRC.
2002)
High
Included -
Recommended
central
tendency and
high-end
values used to
estimate
inhalation
exposures for
industrial use
4
Industrial
Use
EASE
Modeling
Extractant in
medicine
manufacturing
36-180 mg/m3
Not
applicable -
estimates
from
modeling
unknown
Not
applicable
- estimates
from
modeling
ECJRC,
2002
(ECJRC.
2002)
High
Included -
Modeling
estimates are
considered/ref
erenced, but
not used in
exposure
calculations.
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Rim
()i'i'll|l;ilinll;i
1 l!\|)iisuiv
Si'i'ii;irin
T\ |K" III'
S;ini|ik-
Worker .Uii\ ii\
HI' S;i111|> 1 ill<^
l.iii;iliiin
l.4-l)iii\;iiu-
Airluiriu-
(iiiHviilniliiin
f iiifi/m-'i ¦'
NiiihIkt ill'
S;ini|)k's
T\ |K" III'
Mi';isumiU'iil
S;illl|ik-
li nu-
S( ill I'll'
Diici
IdinliliiT
I'l l Mil |);||;|
l'\li';iiiiiin
;iiul
l!\;illl;iliiill
Omt;iII I);iI;i
(|ii;ilil\ i';i 1 in<^
I'l'iilll l);il:i
I'.Mi'iiiliiui
mid
l!\;ilu;iliiin
k;ilinll;ik' I'm'
1 nclusiiill /
I'.M'liisiiui
5
Laboratory
Chemicals
Area and
Personal
Laboratory Work
0-166 mg/m3
Three
datasets -
each has
between 1
and 305
samples per
set
Full-shift and
Short term
ll-X hour
for full
shift,
0-0.5 hour
for short
term
ECJRC,
2002
("ECJRC.
2002)
High
Included -
Mean, 90th
percentile, and
short-term
peak values
used to
estimate
inhalation
exposures for
laboratory
chemical use
6
Open System
Functional
Fluids
Area and
Personal
Threader,
broaching, Apex
drill, lunch tables
(for area)
Transfer lines,
roughing, four-
way, multiple,
screw machine-
lathing, and apex
drill (for pbz)
0.14 to 0.23
mg/m3 (area)
0.24 to 0.53
(PBZ)
These are
exposures to
MWF, not
dioxane
specifically
6 PBZ, 4 area
Full-shift
~ 7 hours
sample
time
Burton,
1997
(Burton and
Driscoll,
1997)
High
Included -
Used in
conjunction
with 1,4-
dioxane
weight
fraction to
estimate
inhalation
exposures
during use of
metalworking
fluids
7
Printing Inks
(3D)
Area
3-D printing
27 ppbv
1
Full-shift
8
Ryan &
Hubbard
,2016
("Rvan and
Hubbard,
2016)
High
Included -
Used to
estimate
inhalation
exposures for
3-D printing
ink use
8
Film Cement
Area and
Personal
Splicing
less than 1 ppm
4 pbz, 1 area
Full-shift
6 hours
Okawa,
1982
(Okawa and
Cove, 1982)
High
Included -
Data used to
estimate
exposures for
film cement
application.
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Rim
()i'i'll|l;ilinll;i
1 I!\|IiiMIIV
Si'i'ii;irin
T\ |K" III'
S;ini|ik-
Worker .Uii\ ii\
HI' S;i111|> 1 ill<^
1 .i ic:i 1 ii ill
l.4-l)iii\;iiu-
Airlmriu-
('iiiHviilmliiin
f iiifi/m-'i ¦'
NiiihIkt ill'
S;ini|)k's
T\ |K" III'
Mi';isumiU'iil
S;illl|ik-
liliu-
Si ill I'll"
Diici
Idi-iiliHiT
I'l l Mil |);||;|
llMniiiiiin
;iiul
l!\;illl;ilinll
Omt;iII I);iI;i
(|ii;ilil\ r;ilin»
I'i'iiiii l);il;i
I'.MiiKliiui
mid
l!\:ilii;ilinn
R;ilimi;ik- 1'iir
1 nclusiiill /
I'.M'liisiiui
9
Manufacturin
g
Personal
Unknown
provided in
report, most
less than 2
ug/sample
28
Full-shift
Time listed
for each
sample
BASF,
2016
(BASF,
2016)
High
Included -
Data used to
estimate
exposures for
manufacturing
10
Manufacturin
g
Personal
Routine duties,
neutralization,
evaporator dump
0.39 ppm (15-
min STEL)
<0.056 ppm (8-
hour TWA)
38 ppm (15-min
STEL)
0.23 ppm (8-
hour TWA)
4
Short-term,
Full-shift
15-min
STEL, 8-
hour TWA
BASF,
2017
(BASF,
20171
High
Included -
Data used to
estimate
exposures for
manufacturing
11
Spray Foam
Application
Not
applicable
Monitorin
g data not
provided
a typical two-
story, 2,300-
square-foot
house with a
medium-pitch roof
— has a roof area
of about 1,500
square
feet
Not applicable
- Monitoring
data not
provided
Not
applicable -
Monitoring
data not
provided
Not applicable
- Monitoring
data not
provided
Not
applicable
Monitorin
g data not
provided
Huber,
2018
(Huber,
201.81
Medium
Included -
Used as an
input in
calculations to
model
exposures
during spray
foam use
12
Spray Foam
Application
Not
applicable
Monitorin
g data not
provided
an average size
house is 1,500
square feet of
roofing
Not applicable
- Monitoring
data not
provided
Not
applicable -
Monitoring
data not
provided
Not applicable
- Monitoring
data not
provided
Not
applicable
Monitorin
g data not
provided
HomeA
dvisor,
2018
(HomeAdvis
or, 2018)
Medium
Included -
Used as an
input in
calculations to
model
exposures
during spray
foam use
13
Spray Foam
Application
Not
applicable
Monitorin
g data not
provided
Mix A-side and B-
side in 1:1 ratio
Not applicable
- Monitoring
data not
provided
Not
applicable -
Monitoring
data not
provided
Not applicable
- Monitoring
data not
provided
Not
applicable
Monitorin
g data not
provided
OMG
Roofing
Products
,2018
(OMG
Products,
2018)
High
Included -
Used as an
input in
calculations to
model
exposures
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Diici
()M'i';ill I):iI;i
()i'i'll|>;ilinll;i
1 l!\|)iisuiv
Si'i'ii;irin
Worker .Uii\ ii\
hi' S;ini|>lin
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G.1.2 Evaluation of Cross-Cutting Data Sources
EPA has reviewed acceptable sources for data that are relevant to all chemicals in this first wave of risk
evaluations under the amended TSC A according to the data quality evaluation criteria found in The
Application of Systematic Review in TSCA Risk Evaluations (U.S. EPA. 2018b). Table G-2 summarizes
the results of this evaluation. The data quality evaluation indicated the sources included are of medium
to high confidence and are used to characterize the occupational inhalation exposures of 1,4-dioxane.
Table G-2. Summary of Cross-Cutting Data Sources
Row
Data Source
Reference
Overall
Data quality
rating from
Data
Extraction
and
Evaluation
1
Chemical Data Reporting (CDR) Data
(U.S. EPA,
2016a)
High
2
RY 2016 Toxics Release Inventory (TRI) Data
(U.S. EPA.
2016c)
Medium
3
Defense Occupational and Environmental Health Readiness System -
Industrial Hygiene (DOEHRS-IH); Provided to EPA from DOD; 2018
(DoD,
2018)
High
4
Bureau of Labor Statistics (BLS). 2014b. Employee Tenure News
Release, September 18, 2014.
http://www.bls.gov/news.release/archives/tenure_09182014.htm
(Accessed February 19, 2016).
(BLS,
2014)
High
5
Bureau of Labor Statistics (BLS). 2015. Hours and Employment by
Industry Tables - August 6, 2015. Available at
http://www.bls.gov/lpc/tables.htm (Accessed December 30, 2015).
(BLS,
2015)
High
6
Census Bureau. 2012b. Code Lists and Crosswalks - Census 2012
Detailed Industry Code List. Available at
http://www.census.gov/people/io/methodology/ (Accessed January 28,
2016).
(U.S.
Census
Bureau,
2012)
N/Aa
7
Census Bureau. 2016a. Survey of Income and Program Participation -
Data. Available at http://www.census.gov/programs-
surveys/sipp/data.html (Accessed February 1, 2016).
(U.S.
Census
Bureau,
2016a)
High
8
Census Bureau. 2016b. Survey of Income and Program Participation -
SIPP Introduction and History. Available at
http://www.census.gov/programs-surveys/sipp/about/sipp-introduction-
history.html (Accessed February 1, 2016).
(U.S.
Census
Bureau,
2016b)
N/Ab
9
Bureau of Labor Statistics (BLS). 2016. May 2016 Occupational
Employment and Wage Estimates: National Industry-Specific Estimates.
(BLS,
2016)
High
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Row
Data Source
Reference
Overall
Data quality
rating from
Data
Extraction
and
Evaluation
Available at http://www.bls.gov/oes/tables.htm (Accessed May 14,
2018).
10
Census Bureau. 2015. Statistics of U.S. Businesses (SUSB). Available at
https://www.census.gov/data/tables/2015/econ/susb/2015-susb-
annual.html (Accessed May 14, 2018).
(Bureau,
2015)
High
11
Cherrie JW, Semple S, Brouwer D (2004) Gloves and dermal exposure
to chemicals: Proposals for Evaluating Workplace Effectiveness. Annals
of Occupational Hygiene 48: 607-615.
(Cherrie et
al.. 2004)
High
12
Dancik Y, Bigliardi PL, Bigliardi-Qi M (2015) What happens in the
skin? Integrating skin permeation kinetics into studies of developmental
and reproductive toxicity following topical exposure. Reproductive
Toxicology. 58: 252-281.
(Dancik et
al.. 2015)
High
13
Environmental Protection Agency [EPA] (2013) ChemSTEERUser
Guide: Chemical Screening Tool for Exposures and Environmental
Release.
(U.S. EPA.
2013b)
High
14
Frasch HF, Bunge AL (2015). The Transient Dermal Exposure II: Post-
Exposure Absorption and Evaporation of Volatile Compounds. Journal
of Pharmaceutical Sciences 104: 1499-1507.
(Frasch and
Bunse,
2015)
High
15
Frasch HF (2012). Dermal Absorption of Finite Doses of Volatile
Compounds. JPharm Sci. 2012 July; 101(7): 2616-2619.
(Frasch,
2012)
High
16
Frasch HF, Dotson GS, Barbero AM (2011). In Vitro Human Epidermal
Penetration of 1-Bromopropane. Journal of Toxicology and
Environmental Health, Part A, 74:1249-1260.
(Frasch et
al., 2011)
High
17
Garrod ANI, Phillips AM, Pemberton JA (2001). Potential Exposure of
Hands Inside Protective Gloves - a Summary of Data from Non-
Agricultural Pesticide Surveys. Ann. Occup Hyg., Vol. 45, No. 1, pp. 55-
60.
(Garrod et
al.. 2001)
High
18
Kasting GB, Miller MA (2006) Kinetics of finite dose absorption
through skin 2: Volatile Compounds. Journal of Pharmaceutical Sciences
95: 268-280.
(Kastins
and Miller,
2006)
High
19
Marquart H, Franken R, Goede H, Fransman W, Schinkel (2017)
Validation of the dermal exposure model in ECETOC TRA. Annals of
Work Exposures and Health. 61: 854-871.
(Marquart
etal.. 2017)
High
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Uow
Data Source
Reference
Overall
Data quality
rutin" from
Data
Extraction
and
Evaluation
20
Baldwin, P. E., and A. D. Maynard. 1998. A Survey of Wind Speeds in
Indoor Workplaces. The Annals of Occupational Hygiene, 42(5), SOS-
SIS.
(
and
Maynard,
1998")
High
aThis is a crosswalk of codes. Does not provide data. Does not need to be evaluated.
b This is a history and introduction of the U.S. Census Bureau's SIPP program. Does not provide data. Does
not need to be evaluated.
G.2 Equations for Calculating Acute and Chronic Inhalation
Exposures
This report assessed 1,4-dioxane exposures to workers in occupational settings, presented as 8-
hour time weighted average (TWA). The 8-hour TWA exposures were used to calculate acute
exposure, average daily concentration (ADC) for chronic, non-cancer risks, and lifetime average
daily concentration (LADC) for chronic, cancer risks.
Acute workplace exposures were assumed to be equal to the contaminant concentration in air (8-
hour TWA), per Equation G-l.
Equation G-l
C X ED
AEC = 1T?
AT
711 acute
Where:
AEC = acute exposure concentration
C = contaminant concentration in air (8-hour TWA)
ED = exposure duration (8 hour/day)
ATacute = acute averaging time (8 hour/day)
ADC and LADC were used to estimate workplace chronic exposures for non-cancer and cancer
risks, respectively. These exposures were estimated as follows:
Equation G-2
C x ED x EF x WY
ADC or LADC = — —
AT or ATc
Where:
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ADC = average daily concentration (8-hour TWA) used for chronic non-cancer risk
calculations
LADC = lifetime average daily concentration (8-hour TWA) used for chronic cancer risk
calculations
C = contaminant concentration in air (8-hour TWA)
ED = exposure duration (8 hour/day)
EF = exposure frequency (250 days/year, except where noted)
WY = exposed working years per lifetime (50th percentile = 31; 95th percentile = 40)
AT = averaging time, non-cancer risks (WY x 260 days/yr x 8 hour/day)
ATc = averaging time, cancer risks (LT x 260 days/year x 8 hour/day; where LT = 78
years)
Exposure Duration (ED)
EPA used an exposure duration of 8 hours per day for averaging full-shift exposures.
Exposure Frequency (EF)
Exposure frequency (EF) is expressed as the number of days per year a worker is exposed to the
chemical being assessed. In some cases, it could be reasonable to assume a worker is exposed to
the chemical on each working day. In other cases, it could be more appropriate to estimate a
worker's exposure to the chemical occurs during a subset of the worker's annual working days.
The relationship between exposure frequency and annual working days could be described as
follows:
Equation G-3
EF = fx AWD
Where:
EF = exposure frequency, the number of days per year a worker is exposed to the
chemical (day/yr)
f = fractional number of annual working days during which a worker is exposed to
the chemical (dimensionless)
AWD = annual working days, the number of days per year a worker works (day/yr)
BLS (2015) provides data on the total number of hours worked and total number of employees
by each industry NAICS code13. These data are available from the 3- to 6-digit NAICS level.
Dividing the total, annual hours worked by the number of employees yields the average number
of hours worked per employee per year for each NAICS.
EPA has identified approximately 140 NAICS codes applicable to the multiple conditions of use
for the ten chemicals currently undergoing risk evaluation. For each NAICS code of interest,
13 NAICS is a 2- through 6-digit hierarchical classification system, offering five levels of detail. Each digit in the
code is part of a series of progressively narrower categories, and the more digits in the code signify greater
classification detail. The first two digits designate the economic sector, the third digit designates the subsector, the
fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit
designates the national industry.
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EPA looked up the average hours worked per employee per year at the more specific NAICS
code hierarchy (i.e., 4-digit, 5-digit, or 6-digit). EPA converted the working hours per employee
to working days per year per employee assuming employees work an average of eight hours per
day. The average number of days per year worked, or AWD, ranged from 169 to 282 days per
year, with a 50th percentile value of 250 days per year. EPA repeated this analysis for all NAICS
codes at the 4-digit level. The average AWD for all 4-digit NAICS codes ranges from 111 to 282
days per year, with a 50th percentile value of 228 days per year. Two hundred fifty days per year
is approximately the 75th percentile.
In the absence of industry-specific data, EPA assumed that the fractional number of annual
working days during which a worker is exposed to the 1,4-dioxane (f) is equal to one for all
conditions of use.
EPA used an exposure frequency of 250 days per year for all exposure scenarios in this
assessment with the exception of the import and re-packaging scenario. EPA estimated 1 to 18
sites could import and re-package 1,4-dioxane (see Section 3.4.1.3 for additional details). These
sites could receive the chemical in totes and may re-package it in bottles or drums. For central
tendency exposures, EPA assumed 18 sites and that each site repackaged into either bottles or
drums. Based on standard loading and unloading rates, EPA used an exposure frequency of 2
days for sites that repackaged into bottles and 3 days for sites that repackaged into drums to
calculate ADC and LADC. For high-end exposures, EPA assumed 1 site re-packaged into both
bottles and drums. EPA used a weighted exposure frequency the account for 32 days for re-
packaging into bottles and 58 days for re-packaging into drums to calculate ADC and LADC.
Working Years (WY)
Table G-3 lists the various worker exposure durations considered/recommended for risk and
exposure assessments. The variations in worker exposure duration could be caused by various
factors including issues of individual risk, population risk, type and nature of exposure, duration
of time at a single location, activity patterns, and other factors. A more realistic portrayal of the
reasonable length of exposure that would occur at the location(s) of maximal impact requires
consideration of newer data and assessment of more realistic exposure scenario.
Table G-3. Representative Worker Exposure Durations Considered for Risk Assessments
Worker Exposure
Duration (years)
Remarks
Reference
45
OSHA performed critical analysis and addressed
comments of American Chemistry Council (ACC),
Chamber of Commerce, and others.
ral Register.
2016
40
Based on threshold of toxicological concern
classification to Cramer classes that requires detailed
knowledge about structural chemical classes.
Protective for a worker population, which consists
ffiCETOC. 2006)
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Worker Exposure
Duration (years)
Remarks
Reference
typically of people who are healthy and within
certain age limits.
30
-
(Mallonsi et al.,
2018; NRC. 1994)
25-30
-
{Nazaroff, 2000,
##} (Baciocchi et
al.. 2010)
25
Supplemental guidance to provide a standard set of
default values that were intended to be used for
calculating reasonable maximum exposure levels for
use in exposure assessments when site-specific data
are lacking. Exposure assessments were based on
recommendations in Exposure Factors Handbook
(U.S. EPA, 2011a).
(U.S. EPA, 2014f,
1991)
25
Offsite worker based on point estimate and
stochastic risks. Risk assessments were conducted
for different durations of exposure based on
estimates of how long people live at a single location
(9 years for the average, 30 years for a high-end
estimate, and 70 years for a lifetime).
(OEHHA. 2012)
20
Monte Carlo Analysis
(Washburn et al.,
1998)
EPA utilized a triangular distribution for exposed working years per lifetime (also could be
referred as worker exposure duration) values considering the recent information available at the
Current Population Survey (CPS) from the Bureau of Labor Statistics (BLS), Survey of Income
and Program Participation (SIPP) and relevant resources from U.S. Census Bureau (Census). The
key parameters of the triangular distribution are following:
• Minimum value: BLS CPS tenure data with current employer as a low-end estimate of
the number of lifetime working years: 10.4 years;
• Mode value: The 50th percentile tenure data with all employers from SIPP as a mode
value for the number of lifetime working years: 36 years; and
• Maximum value: The maximum average tenure data with all employers from SIPP as a
high-end estimate on the number of lifetime working years: 44 years.
This triangular distribution revealed a 50th percentile value of 31 years and a 95th percentile value
of 40 years. These values were used for central tendency and high-end ADC and LADC
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calculations, respectively (see Appendix G.4 on Modeling Approach and Parameters for High-
end and Central Tendency Inhalation Exposure Estimates).
The BLS (2014) provided information on employee tenure with current employer obtained from
the CPS. The CPS is a monthly sample survey of about 60,000 households that provides
information on the labor force status of the civilian non-institutional population age 16 and over;
CPS data are released every two years. The data are available by demographics and by generic
industry sectors but are not available by NAICS codes.
The U.S. Census" (2016a) SIPP provided information on lifetime tenure with all employers. S1PP
is a household survey that collects data on income, labor force participation, social program
participation and eligibility, and general demographic characteristics through a continuous series
of national panel surveys of between 14,000 and 52,000 households ( nsus Bureau.
2016b). EPA analyzed the 2008 SIPP Panel Wave14 1, a panel that began in 2008 and covers the
interview months of September 2008 through December 2008 (U.S. Census Bureau. 2016a. b).
For this panel, lifetime tenure data are available by Census Industry Codes, which could be
cross-walked with NAICS codes.
SIPP data included fields for the industry in which each surveyed, size and characteristics of this
population, work patterns, worker age, and years of work experience with all employers over the
surveyed individual's lifetime.15 Census household surveys used different industry codes than
the NAICS codes used in its firm surveys, so these were converted to NAICS using a published
crosswalk (U.S. Census Bureau. 2012). EPA calculated the average tenure for the following age
groups: 1) workers age 50 and older; 2) workers age 60 and older; and 3) workers of all ages
employed at time of survey. EPA used tenure data for age group "50 and older" to determine the
high-end lifetime working years, because the sample size in this age group is often substantially
higher than the sample size for age group "60 and older". For some industries, the number of
workers surveyed, or the sample size, was too small to provide a reliable representation of the
worker tenure in that industry. The data with sample size of less than five were excluded from
this analysis.
Table G-4 summarized the average tenure for workers age 50 and older from SIPP data.
Although the tenure could differ for any given industry sector, no significant variability was
observed between the 50th and 95th percentile values of average tenure across manufacturing and
non-manufacturing sectors.
14 SIPP is administered in panels and conducted in waves. Within a SIPP panel, the entire sample is interviewed over
a 4-year period which includes a group of annual interviews conducted during a 4-month period. These groups of
interviews are called waves. The first time an interviewer contacts a household is Wave 1; the second time is Wave
2, and so forth.
15 The number of years of work experience was calculated considering the difference between the year first worked
and the current data year (i.e., 2008). Any intervening months, when not working, were subtracted thereafter.
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Tnhlc G-4. Overview of Average Worker Tenure from F.S. Census STPP (Age Croup 50+
Industry Sectors
Working Years
Average
50"'
Percentile
95"'
Percentile
.Maximum
\11 industry sectors relevant to the
10 chemicals undergoing risk
evaluation
35.9
36
39
44
Manufacturing sectors (NAICS 31-
33)
35.7
36
39
40
Non-manufacturing sectors
(NAICS 42-81)
36.1
36
39
44
Source: (U .S. Census Bureau. 2016a")
Note: Industries where sample size is less than five are excluded from this analysis.
BLS CPS data provided the median years of tenure that wage and salary workers had been with
their current employer. Table G-5 presented CPS data for all demographics (men and women) by
age group from 2008 to 2012. To estimate the low-end value on number of working years, EPA
used the available recent (U.S. EPA.: ) CPS data for workers age 55 to 64 years, which
indicated a median tenure of 10.4 years with their current employer. The use of this low-end
value represented a scenario where workers were only exposed to the chemical of interest for a
portion of their lifetime working years, as they could change job(s) or move from one industry to
another throughout their career.
Table G-5. Median Years of Tenure with Current Employer by Age Group
Age
January 2008
January 2010
January 2012
January 2014
16 years and over (<25)
4.1
4.4
4.6
4.6
16 to 17 years
0.7
0.7
0.7
0.7
18 to 19 years
0.8
1.0
0.8
0.8
20 to 24 years
1.3
1.5
1.3
1.3
25 years and over (<65)
5.1
5.2
5.4
5.5
25 to 34 years
2.7
3.1
3.2
3.0
35 to 44 years
4.9
5.1
5.3
5.2
45 to 54 years
7.6
7.8
7.8
7.9
55 to 64 years
9.9
10.0
10.3
10.4
65 years and over
10.2
9.9
10.3
10.3
Source: (BLS. 20.1.4")
G.3 Sample Calculations for Calculating Acute and Chronic
Inhalation Exposures
Sample calculations for high-end and central tendency acute and chronic exposure
concentrations for one setting, Industrial Uses, are demonstrated below. The explanation of the
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equations and parameters used is provided in Appendix G.2. The final values will have two
significant figures since they are based on values from modeling.
G.3.1 Example High-End ADC and LADC
Calculate AEChe:
AEChe —
Che x ED
AT,
acute
20^4 x 8 —
aeche —
m*
day
8
AEChe = 20
hr
day
mg
m3
Calculate ADChe:
ADChe —
CHE xEDxEFx EWY
AT
20 ^fx 8^- x 250^^ x 40 years
ADChe = mf day year _ ^ = ^mg
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5mgxehr_
m3 day
/iCUCT ~ 7
8
day
mg
AECct = 5—j
Ll m3
Calculate ADCct:
Cct xEDxEF x EWY
ADCrr =
CT a j,
/li ,
ADC
5mx8J^x2S0i2yix31years
m3 day year * _ A „mg
(Slyearsx 260^x8^)
V 17 year day J
Calculate LADCct:
Cct xEDxEFx EWY
LADCct = —
AT,
LADC
5 2!|x8^Lx 250^x31 years
m3 day year * _ ^ nmg
" (78 years x 260^x8^)
V 17 year day J
G.4 Modeling Approach and Parameters for High-End and Central
Tendency Inhalation Exposure Estimates for Import and
Repackaging, Functional Fluids (Open System), Spray Foam
Application, and Disposal
This appendix presents the approach for high-end and typical inhalation exposure estimation. This
approach is based on the application of established EPA AP-42 Loading Model, EPA Mass Balance Model
(Fehrenbacher, M.C.), and Monte Carlo simulation.
This approach is intended to assess air releases and associated inhalation exposures associated with
interior container loading scenarios at industrial and commercial facilities. Inhalation exposure to
chemical vapor is a function of physical properties of substance, various EPA default constants, and other
model parameters. While physical properties are fixed for a substance, some model parameters, such as
ventilation rate (Q), mixing factor (k) and vapor saturation factor (f), are expected to vary from one facility
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to another. This approach addresses variability for these parameters using a Monte Carlo simulation.
An individual model input parameter could either have a discrete value or a distribution of values. EPA
assigned statistical distributions based on available literature data or engineering judgment to address the
variability in Q, k, f, and exposed working years per lifetime (WY). A Monte Carlo simulation (a type of
stochastic simulation) was conducted to capture variability in the model input parameters. The simulation
was conducted using the Latin hypercube sampling, a statistical method for generating a near-random
sample of parameter values from a multidimensional distribution, in @RISK Industrial Edition, Version
7.0.0 (Palisade, Ithaca, New York). The Latin hypercube sampling method is a statistical method for
generating a sample of possible values from a multi-dimensional distribution forces the samples drawn to
correspond more closely with the input distribution and thus converges faster on the true statistics of the
input distribution. Latin hypercube sampling is a stratified method, meaning it guarantees that its
generated samples are representative of the probability density function (variability) defined in the model.
EPA performed 100,000 iterations of the model to capture the range of possible input values (i.e.,
including values with low probability of occurrence).
From the distribution resulted from the Monte Carlo simulation, the 95th and 50th percentile values are
selected to represent a high-end exposure, and central tendency exposure level respectively. The statistics
were calculated directly in @RISK. The following subsections detail the model design equations and
parameters used for Inhalation exposure estimates.
G.4.1 Model Design Equations
The EPA Mass Balance Model includes the following equations for estimating mass concentration of the
chemical vapor in air (mg/m3):
Equation G-4
MW
Cm ~ Cv X —
* m
Where
Cm = =mass concentration of chemical vapor in air [mg/m3]
Cv = =volumetric concentration of chemical vapor in air [ppm]
MW = molecular weight of chemical [g/mol]
Vm =molar volume [L/mol]
Equation G-5
170,000 xTxG
C =
v MWxQxk
T = temperature [K]
G = average vapor generation rate [gm/sec]
MW = molecular weight of chemical [g/mol]
Q = ventilation rate [ftVmin]
k = mixing factor [Dimensionless]
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Average vapor generation rate needed for EPA Mass Balance Model, is calculated from following EPA
AP-42 Loading Model:
Equation G-6
f x MW x (3,785.4 x Vc) xrxXx
G ~ 3,600 xTxR
G = average vapor generation rate [gm/sec]
f = saturation factor [Dimensionless]
MW = molecular weight of chemical [g/mol]
Vc =container volume [gallon]
r =container loading/unloading rate [number of containers/hr]
X =vapor pressure correction factor [ Dimensionless], assumed to be equal to weight fraction
of component
VP = vapor pressure (at temperature, T) [mm Hg]
T = temperature [K]
R = universal gas constant [atm-cm3/mol-K]
Mass concentration of the chemical vapor in air calculated from Equation G-4, subsequently used in
following equations to estimate acute exposure concentration (AEC), average daily concentration (8-hour
TWA) used for chronic non-cancer risk calculations (ADC) and lifetime average daily concentration (8-
hour TWA) used for chronic cancer risk calculations (LADC):
Equation G-7
C X ED
AEC = 1T?
AT
711 acute
Where:
AEC = acute exposure concentration [mg/m3]
C = contaminant concentration in air (8-hour TWA) [mg/m3]
ED = exposure duration [hr/day]
ATacute = acute averaging time [hr/day]
ADC and LADC are used to estimate workplace chronic exposures for non-cancer and cancer risks,
respectively. These exposures are estimated as follows:
Equation G-8
C x ED x EF x WY
ADC or LADC = — —
AT or ATc
Where:
ADC = average daily concentration (8-hour TWA) used for chronic non-cancer risk calculations
[mg/m3]
LADC = lifetime average daily concentration (8-hour TWA) used for chronic cancer risk
calculations [mg/m3]
C = contaminant concentration in air (8-hour TWA) [mg/m3]
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ED = exposure duration [hour/day]
EF = exposure frequency [days/yr]
WY = exposed working years per lifetime [yr/LT]
AT = averaging time, non-cancer risks [hr]
ATC = averaging time, cancer risks [hr]
Equation G-9
AT = WY X 260
d i
hr
x 8
day
yr
AT = averaging time, non-cancer risks [hr]
WY = exposed working years per lifetime [yr/LT]
Equation G-10
ATc = LT X 260
d i
hr
x 8
day
yr
ATc = averaging time, cancer risks [hr]
LT = lifetime = 78 [yr]
Refer to Appendix G.2 for equations used to calculate acute and chronic inhalation exposures, details
about Equation G-8 and Equation G-9, and the basis for various parameters used in the calculations.
G.4.2 Model Parameters
Table G-6 summarizes the model parameters and their values for the Monte Carlo simulation. High-end
and typical exposure are estimated by selecting the 50th and 95th percentile values from the output
distribution.
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Table G-6. Summary of Parameter Values and Distributions Used in the Inhalation Exposure Model
Input Parameter
Symbol
Unit
Constant
Model
Parameter
Values
Variable Model Parameter Values
Rational / Basis
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distributio
n Type
Molecular Weight
MW
g/mol
88.1
—
—
—
—
—
Physical Property
Vapor Pressure
VP
lnrnHg
—
30
40
—
—
Physical Property. The vapor pressure of 1,4-
dioxane was needed at 293K (30 mmHg) and
at 298K (40 mmHg).
Molar Volume at 298
K
Vm
L/mol
24.45
—
—
—
—
—
Physical Constant
Gas Constant
R
atm-cm3/mol-
K
82.05
—
—
—
—
—
Temperature
T
K
298
—
—
—
—
—
Process Parameter
Container Volume
Vc
gallons
1 or 55
—
—
—
—
—
Value is determined by the selected container
type for given exposure scenario
Container
Loading/Unloading
Rate
r
Containers / lir
20 or
60
—
—
—
—
—
Value is determined by the selected container
type
Ventilation Rate16
Q
ft3/min
—
—
500
10000
3000
Triangular
1. General ventilation rates in industry ranges
from a low of 500 ft3/min to over 10,000
ft3/min; a typical value is 3,000.
2. Mixing Factor ranges from 0.1 to 1.
3. Saturation factor ranges from 0.5 for
submerged loading to 1.45 for splash loading.
Underlying distribution of these parameters
are not known, EPA assigned triangular
distributions, since triangular distribution
requires least assumptions and is completely
defined by range and mode of a parameter.
Mixing Factor
k
Dimensionless
—
—
0.1
1
0.5
Triangular
Saturation Factor
f
Dimensionless
—
—
0.5
1.45
0.5
Triangular
16 Ventilation rate procedure is a prescriptive design procedure in which air rates are dependent on space type, occupancy, and floor area. Airflow for ventilation could be
calculated by various methods including area method, air change method, occupancy method, and heat removal method.
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Input Parameter
Symbol
Unit
Constant
Model
Parameter
Values
Variable Model Parameter Values
Rational / Basis
Value
Basis
Lower
Bound
Upper
Bound
Mode
Distributio
n Type
(ASHRAE. 2016 ; ACGIH. 2019)
Vapor Pressure
Correction Factor
X
Dimensionless
1
—
—
—
—
—
For Import & Repackaging and Disposal
Vapor Pressure
Correction Factor
X
Dimensionless
0.001
—
—
—
—
—
For Functional Fluids (open System) and
Spray Foam Application
Exposed Working
Years per Lifetime
MY
years
—
—
10
44
31
Triangular
See Appendix G.2 of this Report
Contaminant
concentration in air
(8-hour TWA)
C
mg/m3
—
—
—
—
—
Calculated
Refer Appendix G.2 for "Equations for
Calculating Acute and Chronic Inhalation
Exposures"
Exposure Duration
ED
lir/day
8
—
—
—
—
—
Acute averaging
Time
A t'acute
lir/day
8
—
—
—
—
—
Averaging Time,
non-cancer risks
AT
hr
—
—
—
—
—
Calculated
Averaging Time,
cancer risks
ATC
hr
—
—
—
—
—
Calculated
Exposure Frequency
EF
days/yr
250
—
—
—
—: Not Applicable
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G.4.3 Sample Monte Carlo Simulation Result
Average Daily Concentration (ADC)
35%
30% -
25%
£T 20% -
* 15% -
10%
5% -
0%
50th Percentile Value = 0.36 mg/m3
95th Percentile Value = 0.93 mg/m3
0.0
0.5
1.0
ADC (mg/m3)
1.5
2.0
Figure G-l. Example of Monte Carlo Simulation results for the Disposal Scenario
G.5 Approach for Estimating the Number of Workers
This appendix summarizes the methods that EPA used to estimate the number of workers who
are potentially exposed to 1,4-dioxane in each of its conditions of use. The method consists of
the following steps:
7. Identify the North American Industry Classification System (NAICS) codes for the
industry sectors associated with each condition of use.
8. Estimate total employment by industry/occupation combination using the Bureau of
Labor Statistics' Occupational Employment Statistics (OES) data ( >LS, 2016).
9. Refine the OES estimates where they are not sufficiently granular by using the U.S.
Census' ("2016b) Statistics of U.S. Businesses (SUSB) data on total employment by 6-
digit NAICS.
10. Estimate the percentage of employees likely to be using 1,4-dioxane instead of other
chemicals (i.e., the market penetration of 1,4-dioxane in the condition of use).
11. Estimate the number of sites and number of potentially exposed employees per site.
12. Estimate the number of potentially exposed employees within the condition of use.
Step 1: Identifying Affected NAICS Codes
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As a first step, EPA identified NAICS industry codes associated with each condition of use. EPA
generally identified NAICS industry codes for a condition of use by:
• Querying the U.S. Census Bureau's NAICS Search tool using keywords associated
with each condition of use to identify NAICS codes with descriptions that match the
condition of use.
• Referencing EPA Generic Scenarios (GS's) and Organisation for Economic Co-
operation and Development (OECD) Emission Scenario Documents (ESDs) for a
condition of use to identify NAICS codes cited by the GS or ESD.
• Reviewing Chemical Data Reporting (CDR) data for the chemical, identifying the
industrial sector codes reported for downstream industrial uses, and matching those
industrial sector codes to NAICS codes using Table D-2 provided in the CDR
reporting instructions.
Each condition of use section in the main body of this report identifies the NAICS codes EPA
identified for the respective condition of use.
Step 2: Estimating Total Employment by Industry and Occupation
BLS's (2016) OES data provide employment data for workers in specific industries and
occupations. The industries are classified by NAICS codes (identified previously), and
occupations are classified by Standard Occupational Classification (SOC) codes.
Among the relevant NAICS codes (identified previously), EPA reviewed the occupation
description and identified those occupations (SOC codes) where workers are potentially exposed
to 1,4-dioxane. Table G-7 shows the SOC codes EPA classified as occupations potentially
exposed to 1,4-dioxane. These occupations are classified into workers (W) and occupational non-
users (O). All other SOC codes are assumed to represent occupations where exposure is unlikely.
Table G-7. SOCs with Worker and ONU Designations for All Conditions of Use Except
Dry Cleaning
S()(
Occn p;il ion
l)i'sii£iiiilion
1 1 -9020
Construction Managers
O
17-2000
Engineers
O
17-3000
Drafters, Engineering Technicians, and Mapping Technicians
O
19-2031
Chemists
O
19-4000
Life, Physical, and Social Science Technicians
O
47-1000
Supervisors of Construction and Extraction Workers
O
47-2000
Construction Trades Workers
w
49-1000
Supervisors of Installation, Maintenance, and Repair Workers
O
49-2000
Electrical and Electronic Equipment Mechanics, Installers, and
Repairers
w
49-3000
Vehicle and Mobile Equipment Mechanics, Installers, and Repairers
w
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49-9010
Control and Valve Installers and Repairers
W
49-9020
Heating, Air Conditioning, and Refrigeration Mechanics and Installers
W
49-9040
Industrial Machinery Installation, Repair, and Maintenance Workers
W
49-9060
Precision Instrument and Equipment Repairers
W
49-9070
Maintenance and Repair Workers, General
W
49-9090
Miscellaneous Installation, Maintenance, and Repair Workers
W
51-1000
Supervisors of Production Workers
0
51-2000
Assemblers and Fabricators
w
51-4020
Forming Machine Setters, Operators, and Tenders, Metal and Plastic
w
51-6010
Laundry and Dry-Cleaning Workers
w
51-6020
Pressers, Textile, Garment, and Related Materials
w
51-6030
Sewing Machine Operators
0
51-6040
Shoe and Leather Workers
0
51-6050
Tailors, Dressmakers, and Sewers
0
51-6090
Miscellaneous Textile, Apparel, and Furnishings Workers
0
51-8020
Stationary Engineers and Boiler Operators
w
51-8090
Miscellaneous Plant and System Operators
w
51-9000
Other Production Occupations
w
W = worker designation
O = ONU designation
For dry cleaning facilities, due to the unique nature of work expected at these facilities and that
different workers may be expected to share among activities with higher exposure potential (e.g.,
unloading the dry-cleaning machine, pressing/finishing a dry-cleaned load), EPA made different
SOC code worker and ONU assignments for this condition of use. Table G-8 summarizes the
SOC codes with worker and ONU designations used for dry cleaning facilities.
Table G-8. SOCs with Worker and ONU Designations for Dry Cleaning Facilities
SOC
Occupation
Designation
41-2000
Retail Sales Workers
O
49-9040
Industrial Machinery Installation, Repair, and Maintenance Workers
w
49-9070
Maintenance and Repair Workers, General
w
49-9090
Miscellaneous Installation, Maintenance, and Repair Workers
w
51-6010
Laundry and Dry-Cleaning Workers
w
51-6020
Pressers, Textile, Garment, and Related Materials
w
51-6030
Sewing Machine Operators
0
51-6040
Shoe and Leather Workers
0
51-6050
Tailors, Dressmakers, and Sewers
0
51-6090
Miscellaneous Textile, Apparel, and Furnishings Workers
0
W = worker designation
O = ONU designation
After identifying relevant NAICS and SOC codes, EPA used BLS data to determine total
employment by industry and by occupation based on the NAICS and SOC combinations. For
example, there are 110,640 employees associated with 4-digit NAICS 8123 (Drycleaning and
Laundry Services) and SOC 51-6010 (Laundry and Dry-Cleaning Workers).
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Using a combination of NAICS and SOC codes to estimate total employment provides more
accurate estimates for the number of workers than using NAICS codes alone. Using only NAICS
codes to estimate number of workers typically result in an overestimate, because not all workers
employed in that industry sector will be exposed. However, in some cases, BLS only provide
employment data at the 4-digit or 5-digit NAICS level; therefore, further refinement of this
approach may be needed (see next step).
Step 3: Refining Employment Estimates to Account for lack of NAICS Granularity
The third step in EPA's methodology was to further refine the employment estimates by using
total employment data in the U.S. Census Bureau's (2016b) SUSB. In some cases, BLS OES's
occupation-specific data are only available at the 4-digit or 5-digit NAICS level, whereas the
SUSB data are available at the 6-digit level (but are not occupation-specific). Identifying specific
6-digit NAICS will ensure that only industries with potential 1,4-dioxane exposure are included.
As an example, OES data are available for the 4-digit NAICS 8123 Dryclecming and Laundry
Services, which includes the following 6-digit NAICS:
• NAICS 812310 Coin-Operated Laundries and Dry cleaners;
• NAICS 812320 Drycleaning and Laundry Services (except Coin-Operated);
• NAICS 812331 Linen Supply; and
• NAICS 812332 Industrial Launderers.
In this example, only NAICS 812320 is of interest. The Census data allow EPA to calculate
employment in the specific 6-digit NAICS of interest as a percentage of employment in the BLS
4-digit NAICS.
The 6-digit NAICS 812320 comprises 46% of total employment under the 4-digit NAICS 8123.
This percentage can be multiplied by the occupation-specific employment estimates given in the
BLS OES data to further refine our estimates of the number of employees with potential
exposure.
Table G-9 illustrates this granularity adjustment for NAICS 812320.
Table G-9. Estimated Number of Potentially Exposed Workers and ONUs under NAICS
812320
NAIC
S
SOC
CODE
SOC Description
Occupation
Designation
Employment
by SOC at 4-
% of Total
Employmen
t
Estimated
Employmen
t by SOC at
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digit NAICS
level
6-digit
NAICS level
8123
41-2000
Retail Sales Workers
O
44,500
46.0%
20,459
8123
49-9040
Industrial Machinery
Installation, Repair, and
Maintenance Workers
w
1,790
46.0%
823
8123
49-9070
Maintenance and Repair
Workers, General
w
3,260
46.0%
1,499
8123
49-9090
Miscellaneous Installation,
Maintenance, and Repair
Workers
w
1,080
46.0%
497
8123
51-6010
Laundry and Dry-Cleaning
Workers
w
110,640
46.0%
50,867
8123
51-6020
Pressers, Textile, Garment,
and Related Materials
w
40,250
46.0%
18,505
8123
51-6030
Sewing Machine Operators
0
1,660
46.0%
763
8123
51-6040
Shoe and Leather Workers
0
Not Reported for this NAICS Code
8123
51-6050
Tailors, Dressmakers, and
Sewers
0
2,890
46.0%
1,329
8123
51-6090
Miscellaneous Textile,
Apparel, and Furnishings
Workers
0
0
46.0%
0
Total Potentially Exposed Employees
206,070
94,740
Total Workers
72,190
Total Occupational Non-Users
22,551
Note: numbers may not sum exactly due to rounding.
W = worker
O = occupational non-user
Source:(BLS. 2016: U.S. Census Bureau. 2016b)
Step 4: Estimating the Percentage of Workers Using 1,4-Dioxane Instead of Other
Chemicals
In the final step, EPA accounted for the market share by applying a factor to the number of
workers determined in Step 3. This accounts for the fact that 1,4-dioxane may be only one of
multiple chemicals used for the applications of interest. EPA was unable to identify market
penetration data for any of the conditions of use. In the absence of market penetration data for a
given condition of use, EPA assumed 1,4-dioxane may be used at up to all sites and by up to all
workers calculated in this method as a bounding estimate. This assumes a market penetration of
100%. Market penetration is discussed for each condition of use in the main body of this report.
Step 5: Estimating the Number of Workers per Site
EPA calculated the number of workers and occupational non-users in each industry/occupation
combination using the formula below (granularity adjustment is only applicable where SOC data
are not available at the 6-digit NAICS level):
Number of Workers or ONUs in NAICS SOC (Step 2) x Granularity Adjustment Percentage
(Step 3) = Number of Workers or ONUs in the Industry Occupation Combination
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EPA then estimated the total number of establishments by obtaining the number of
establishments reported in the U.S. Census Bureau's SUSB (2016b) data at the 6-digit NAICS
level.
EPA then summed the number of workers and occupational non-users over all occupations
within a NAICS code and divided these sums by the number of establishments in the NAICS
code to calculate the average number of workers and occupational non-users per site.
Step 6: Estimating the Number of Workers and Sites for a Condition of Use
EPA estimated the number of workers and occupational non-users potentially exposed to 1,4-
dioxane and the number of sites that use 1,4-dioxane in a given condition of use through the
following steps:
6. A. Obtaining the total number of establishments by:
i. Obtaining the number of establishments from SUSB (20.1.6b) at the 6-digit NAICS
level (Step 5) for each NAICS code in the condition of use and summing these
values; or
ii. Obtaining the number of establishments from the Toxics Release Inventory (TRI),
Discharge Monitoring Report (DMR) data, National Emissions Inventory (NEI),
or literature for the condition of use.
6.B. Estimating the number of establishments that use 1,4-dioxane by taking the total
number of establishments from Step 6. A and multiplying it by the market penetration
factor from Step 4.
6.C. Estimating the number of workers and occupational non-users potentially exposed to
1,4-dioxane by taking the number of establishments calculated in Step 6.B and
multiplying it by the average number of workers and occupational non-users per site
from Step 5.
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G.6 Occupational Exposure Scenario Grouping
OES grouping corresponds to the defined use scenarios for the occupational exposure
assessment.
Table G-10. Occupational Exposure Scenario Groupings
Life Cycle Stage
Category
Subcategory
OLS Grouping
Manufacture
Domestic Manufacture
Domestic Manufacture
Manufacturing
Manufacture
Import
Import
Import and
Repackaging
Repackaging
Processing
Recycling
Recycling
Non-Incorporative
Pharmaceutical and
medicine manufacturing
(process solvent)
Processing
Basic organic chemical
manufacturing (process
solvent)
Processing as a
reactant
Pharmaceutical
intermediate
Polymerization catalyst
Agricultural chemical
intermediate
Intermediate Use
Plasticizer intermediate
Industrial Use
Catalysts and reagents for
anhydrous acid reactions,
brominations and
sulfonations
Industrial Use
Wood pulping
Extraction of animal and
vegetable oils
Processing aids, not
otherwise listed
Wetting and dispersing
agent in textile processing
Purification of
pharmaceuticals
Etching of fluoropolymers
Functional Fluids,
Open System
Metal working fluid
Functional Fluids,
Open System
Industrial Use
Cutting and Tapping Fluid
Polyalkylene Glycol Fluid
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1 -ile ( vole Slsigc
CsiU'gorv
Suhesilogorv
OKS (Grouping
Industrial Use
Functional Fluids,
Closed System a
Hydraulic Fluid a
Functional Fluids,
Closed System a
Industrial Use,
Potential
Commercial Use
Laboratory Chemicals
Chemical Reagent
Reference material
Spectroscopic and
photometric measurement
Liquid scintillation
counting medium
Stable Reaction medium
Cryoscopic solvent for
molecular mass
determinations
Preparation of histological
sections for microscopic
examination
Laboratory Chemicals
Industrial Use,
Potential
Commercial Use
Adhesives and
Sealants
Film Cement
Film Cement
Industrial Use,
Potential
Commercial Use
Other Uses
Spray Polyurethane Foam
Spray Application
Industrial Use,
Potential
Commercial Use
Other Uses
Printing and Printing
Compositions
Use of Printing Inks
(3D)
Industrial Use,
Potential
Commercial Use
Other Uses
Dry Film Lubricant
Dry Film Lubricant
Disposal
Disposal
Wastewater
Underground Injection
Landfill
Recycling
Incineration
Disposal
a EPA did not find evidence to support the intended use of 1,4-dioxane in closed-system functional fluids;
therefore, occupational exposures and environmental releases were not assessed for this scenario. See Section
3.4.1.7.
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G.6.1 Manufacturing
There are three methods to produce 1,4-dioxane, but it is typically manufactured for industrial
purposes via an acid-catalyzed conversion of ethylene glycols in a closed system. The other two
methods17 are used to make substituted 1,4-dioxane and are not known to be used for industrial
production {ECJRC, 2002, 196351}.
A typical acid-catalyzed conversion of ethylene glycols process is carried out in a heated vessel
at a temperature between 266 and 392 °F (130 and 200 °C) and a pressure between 0.25 and 1.1
atm (25 and 110 kPa) {ECJRC, 2002, 196351}. At the BASF Facility inZachary, Louisiana, 1,4-
dioxane is produced using this method with diethylene glycol and concentrated sulfuric acid
(Figure G-2). After synthesis, 1,4-dioxane is further purified in a multi-step process that includes
multiple distillation and neutralization steps to remove water and volatile by-products {BASF,
2017, 3827415}.
Feed
Tank
Feed
Tank
Storage
Final
Product
Tank
Reactor
Condenser
Neutralizer
Tank
Settling
Tank
Distillation
Column
Evaporator
Boiler
Multiple
Distillation Steps
Figure G-2. Generic Manufacturing Process Flow Diagram
Source: Modeled after (.6 A 17)
Number of Potentially Exposed Workers and Occupational Non-Users
The CDR (U ,S. EPA. 2016a) reports two manufacturing sites, each reporting 50 to 100 workers.
Based on data from the Bureau of Labor Statistics (BLS) for NAICS code 325199 (All Other
Basic Organic Chemical Manufacturing and related SOC codes), there could be an average of 39
17 Substituted 1,4-Dioxane can be prepared by ring closure of 2-chloro-2'-hydroxydiethyl ether through heating with
20% sodium hydroxide, and by catalyzed cyclo-dimerization of ethylene oxide either over NaHSO/i, SiF4, or BF3, or
at an elevated temperature with an acidic cation-exchange resin.
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workers and 19 ONUs per site ( |). The BLS data indicated that there could be an
average of 57 potentially exposed workers and ONUs per site, which is consistent with the range
reported in CDR (2016a). Using the BLS data, EPA estimated that 78 workers and 36 ONUs
could be exposed over all sites that manufacture 1,4-dioxane in the U.S., 2018, BASF provided
additional information regarding the manufacture of 1,4-dioxane. In this public comment, BASF
indicated that the Zachary, Louisiana site would cease manufacturing of 1,4-dioxane by the end
of 2018; and BASF might direct its customers to import the chemical from a BASF site in
Germany. Though the public comment stated that BASF is the sole domestic producer of 1,4-
dioxane, CDR (2016a) lists a second domestic manufacturer; therefore, EPA assesses exposures
from the two 1,4-dioxane manufacturing sites in the US (<1 \ r P. 2018a; * \ N \ _v i >a).
Worker and Occupational Non-User Activities
BASF provided limited monitoring data related to certain steps in the production process, such as
neutralization and evaporator dumping. However, specific descriptions of these worker tasks
were not provided (BASF. 2.017). The European Union Risk Assessment Report (ECJRC. 2002)
provided detailed description of the 1,4-Dioxane manufacturing processes at the sites in Europe.
The report stated that the primary ways workers could be exposed are during drumming,
maintenance, sampling, and from the system "breathing." Dermal and inhalation exposures are
expected during drumming from connecting and disconnecting the transfer line, and during any
leakages (ECJRC. 2002).
ONUs include employees that work at the site where 1,4-dioxane is manufactured, but they do
not directly handle the chemical and are therefore expected to have lower exposures. ONUs for
manufacturing include supervisors, managers, and tradesmen that may be in the manufacturing
area, but do not perform tasks that result in the same level of exposures as production workers.
Worker and Occupational Non-User Exposure Assessment
EPA used full-shift, personal breathing zone (PBZ) monitoring data provided by BASF to assess
occupational inhalation exposures. These data ranged from 2006 to 2011 and covered the
manufacturing facility under two different corporate ownerships, Ferro Corp and BASF. BASF
also provided monitoring data in a public comment from 2017. The public comment states that
these data are from "periodic monitoring of employees performing tasks that could present
exposure to Dioxane" (BASF. 2017). EPA assumed that these monitoring data were originated
via PBZ measurements. In addition, EPA reviewed European manufacturing monitoring data
cited in the European Union Risk Assessment (ECJRC. 2002) for 1,4-dioxane ranging between
1976 to 1998. After the review, EPA chose monitoring data from the more recent time period in
this risk evaluation that are representative of U.S. manufacturing over the older European data.
The production monitoring data of 1,4-dioxane from BASF plant at Zachary, Louisiana is
summarized in Table G-l 1 (BASF. 2017). BASF (2016) provided additional monitoring data
from multiple Industrial Hygiene Analyses (IHA) reports from 2008 to 2011. It also provided
monitoring data from 2006 and 2007 from the previous owner of the manufacturing site (Ferro
Corp), but did not provide job descriptions, exposure sources, or possible engineering controls
used in relation to these data points to refine the exposure assessment ( ). The data
are summarized in Table G-12.
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Table G-11 2017 1.4-Dioxane Production Monitoring Data (RAKK 21117)
D.ilc Monitored
Process Tsisk Monitored
Res
ppm
nils
ill "i/m' •'
S.implc Tjpe
2/24/2017
Neutralization step
0.39
1.4
15-min TWA
2/24/2017
Routine duties during production
(including neutralization step)
<0.056
<0.20
8-hour TWA
2/28/2017
Evaporator dump step
38
137
15-min TWA
2/28/2017
Routine duties during production
(including evaporator dump step)
0.23
0.828
8-hour TWA
a Calculated using 3.6 (mg/m3)/ppm conversion factor (NIOSH. 2005
Source: (BASF. 2017)
Table G-l2. 2007-2011 l.4-l)ioxane Production Monitoring Data ( )
Kcporl
Miiss of
l.4-dio\;inc
(Ulil
Siiiiiplinii lime
(mill)
How rsile
(cm 7m in)
1 oliil iiir
\oliimc
s;impled (1.)
Kiiw nil"
coiiccnlriilion
(inii/in1) •'
K:i\\ :iir
coiiccnlriilion
(ppm) ¦'
Adjusted ;iir
coiiccnlriilion
(in ii/iii-4)
IHA
13
487
34.5
16.8
0.77
0.21
0.85
12/18/2008
26
484
34.5
16.7
1.56
0.43
1.71
IHA
<2
490
34.5
16.9
<0.12
<0.04
<0.13
01/12/2010
6
508
34.5
17.5
0.34
0.1
0.38
6
397
34.5
13.7
0.44
0.12
0.48
<2
487
34.5
16.8
<0.12
0.04
<0.13
<2
471
34.5
16.2
<0.12
0.04
<0.14
IHA
<2
480
34.5c
-
<0.12 d
0.0335
<0.13
05/14/2010
7
480
34.5c
-
0.42 d
0.117
0.46
120
483
34.5c
-
7.20 d
2.00
7.91
IHA
<2
419
34.5c
-
<0.14 d
<0.038
<0.15
11/09/2010
<2
445
34.5c
-
<0.13 d
<0.036
<0.14
<2
443
34.5c
-
<0.13 d
<0.036
<0.14
<2
450
34.5c
-
<0.13 d
<0.036
<0.14
IHA
21
493
34.5c
-
1.23 d
0.342
1.36
08/05/2011
6
443
34.5c
-
0.39d
0.109
0.43
<2
474
34.5c
-
<0.12 d
<0.033
<0.13
Ferro summary
-
480
-
-
0.25e
0.07
0.28
(2006 - 2007)
-
480
-
-
3.63 e
1.01
4.00
-
480
-
-
0.36e
0.1
0.40
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Kcpori
Miiss of
l.4-dio\;mc
(iilil
Siimpliiiii lime
(mill)
Hon rsilc
(cm 7m in)
1 olid iiir
\ollllllC
mimplod (1.)
Kiiw :iir
concciilr;ilion
(ing/ni'¦') •'
K:i\\ iiir
coiiccnlmlion
(ppm) ¦'
Adjusted iiir
concciili'iilioii
(iiiii/in1)
-
480
-
-
1.8e
0.5
1.98
-
480
-
-
0.43 e
0.12
0.47
-
480
-
-
0.9e
0.25
0.99
-
480
-
-
6.84e
1.9
7.52
-
480
-
-
24.1e
6.7
26.5
<2 b'c
480
34.5 c
-
<0.14e
0.04c
<0.16
<2b,c
480
34.5c
-
<0.14e
0.04c
<0.16
-
-
-
-
1.55
0.43
1.7
a The duration corresponds to the sample time listed for this concentration.
b Non-detect
0 Assumed values
dEPA calculated raw air concentrations in mg/m3 by using sampling durations on the associated chain of custody sheets and assuming
the same sampling rate (34.5 cc/min) given in the other two IHA reports.
e Converted ppm results to units of mg/m3 by multiplying by 3.60 mg/m3 per ppm.
fEPA divided the 28 raw TWA air concentrations by 0.91 (assuming the same desorption efficiency for all samples) to generate
adjusted air concentrations in mg/m3.
The cells marked are not available and/or not applicable.
Source: (BASF. 2016)
BASF provided data from 28 PBZ samples (BASF. I o) Based on the provided sampling
durations, EPA assumed that these samples were 8-hour TWAs. Of the 28 samples, the 11
samples dated 2006 and 2007 showed results only in units of ppm in a tabular summary from the
previous owner of the manufacturing site (Ferro Corp). EPA converted these ppm results to units
of mg/m3 by multiplying by 3.60 mg/m3 per ppm for 1,4-dioxane.
The two BASF Industrial Hygiene Analysis (IHA) reports dated 12/18/2008 and 1/12/2010
showed a total of 7 samples with mass units in |ig, sampling rates of 34.5 cc/min, sampling
durations in minutes (ranging from 6.5 to >8 hours) and calculated sample volumes in units of
liters and TWA air concentrations in ppm.
The remaining 10 samples in the three IHA reports dated 05/14/2010, 11/09/2010 and
08/05/2011 were given as |ig/sample mass results only without sampling rates, sample volumes,
or other parameters or units. EPA calculated raw air concentrations in mg/m3 by using sampling
durations on the associated chain of custody sheets and assuming the same sampling rate (34.5
cc/min) given in the two older IHA reports (dated 12/18/2008 and 1/12/2010).
The IHA report (dated 12/18/2008) indicates that the sampling results do not account for
desorption efficiency, shown as 0.91. It appears that none of the reports make such a correction.
EPA divided the 28 raw TWA air concentrations by 0.91 (assuming the same desorption
efficiency for all samples) to generate adjusted air concentrations in mg/m3.
To assess occupational inhalation exposures, EPA assembled the BASF 8-hour TWA monitoring
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data from Table G-l 1 and the adjusted air concentration values from Table G-12 to a single
sample set with 30 data points. EPA calculated the 95th percentile and 50th percentile of this data
set to assess the high-end and central tendency exposures, respectively. EPA estimated acute and
chronic inhalation exposures using these values and the equations in Appendix G.2. The EU Risk
Assessment (ECJRC. 2002) estimated that the central tendency inhalation exposure was 0.2
mg/m3 and a reasonable high-end exposure was 10 mg/m3 (full-shift) (ECJRC. 2002). These
values were based on measured data and support the values that EPA calculated for this
assessment. These values are summarized in Section 3.4.1.2.
BASF reported two 15-minute short-term exposures (refer Table G-l 1). EPA used the higher of
these two values, 137 mg/m3 from the evaporator dump step, as a high-end short-term exposure
value in this risk assessment. EPA did not use the other short-term exposure value (1.4 mg/m3) to
estimate a central tendency, short-term exposure, since the statistical significance of this sample
is unclear (i.e. low end of range, median, etc.).
Although BASF stated that they would cease manufacturing 1,4-dioxane at their Zachary,
Louisiana site by the end of 2018, EPA used the exposure monitoring data from this site as
representative of 1,4-dioxane manufacturing across the U.S. manufacturing facilities.
G.6.2 Import and Repackaging
Commodity chemicals are typically imported into the United States in bulk via water, air, land,
and intermodal shipments (Tomer and Kane. 2015). These shipments take the form of
oceangoing chemical tankers, railcars, tank trucks, and intermodal tank containers. Chemicals
shipped in bulk containers may be repackaged into smaller containers for resale, such as drums
or bottles. Domestically manufactured commodity chemicals may be shipped within the United
States in liquid cargo barges, railcars, tank trucks, tank containers, intermediate bulk containers
(IBCs)/totes, and drums. Both imported, and domestically manufactured commodity chemicals
may be repackaged by wholesalers for resale; for example, repackaging bulk packaging into
drums or bottles. The exact shipping and packaging methods specific to 1,4-dioxane are not
known, so for this risk evaluation, EPA assessed the repackaging of 1,4-dioxane from bulk
packaging to drums and bottles at wholesale repackaging sites (see Figure G-3). The import and
repackaging uses are grouped because repackaging is the only routine activity of an importer that
would lead to an exposure.
Smaller containers
shipped to customers
for use
1,4-Dioxane received
in rail cars, tanks, or
totes
Unloaded from larger
containers and loaded
into smaller containers
Figure G-3. General Process Flow Diagram for Import and Repackaging
During repackaging, workers could be exposed while connecting and disconnecting hoses and
transfer lines to containers and packaging to be unloaded (e.g., railcars, tank trucks, totes),
intermediate storage vessels (e.g., storage tanks, pressure vessels), and final packaging containers
(e.g., drums, bottles). Workers near loading racks and container filling stations are potentially
exposed to fugitive emissions from equipment leaks and displaced vapor as containers are filled.
These activities are potential sources of worker exposure through dermal contact with liquid and
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inhalation of vapors. In addition, ONUs may include employees that work at the site where 1,4-
dioxane is repackaged, but they do not directly handle the chemical and are therefore expected to
have lower inhalation exposures and are not expected to have dermal exposures. ONUs for
repackaging include supervisors, managers, and tradesmen that may be in the repackaging area
but do not perform tasks that result in the same level of exposures as repackaging workers.
Number of Potentially Exposed Workers and Occupational Non-Users
Two companies reported selling a portion of their PV to Industry Sector (IS) code IS46 for
wholesale and retail sale in the 2016 CDR. While one CDR submitter reported the industrial use
type for the wholesale sites as "processing - repackaging", the other reported "not known or
reasonably ascertainable." EPA assumes both sets of wholesale sites repackage their shipments
of 1,4-dioxane. Each CDR submitter reported selling 1,4-dioxane to fewer than 10 wholesale
sites with at least 50 but less than 100 workers potentially exposed. It is possible some portion of
the wholesale sites indicated by the two CDR submitters may overlap; for example, both CDR
submitters may sell to the same wholesaler. Therefore, EPA assesses an overall range of
wholesale sites repackaging 1,4-dioxane of one to 18. Similarly, the range of reported potentially
exposed workers is 50 to 198 (I _ S » V-\ .a'16a).
CDR IS code IS46 corresponds to NAICS codes for wholesale and retail trade and transportation
and warehousing. EPA assumes NAICS Code 424690, other chemical and allied products
merchant wholesalers, is the most relevant NAICS code for wholesalers who repackage and sell
1,4-dioxane. Using U.S. Census and BLS data, EPA estimates a total of 9,517 establishments,
27,214 workers, 10,359 ONUs, a ratio of 3:1 workers to ONUs for this NAICS code. Using the
range of one to 18 sites, EPA calculates a range of three to 51 workers and one to 20 ONUs over
all sites (a total of four to 71 potentially exposed employees). This range is less than the
estimated range reported to CDR of 50 to 198 potentially exposed employees. Therefore, EPA
assesses the range of total potentially exposed employees of 50 to 198 and applies the ratio of 3:1
workers to ONUs to estimate a range of 38 to 149 workers and 12 to 49 ONUs.
Worker and Occupational Non-User Exposure Assessment
Exposure data for this scenario are not available. Therefore, EPA modeled inhalation exposures
using the EPA AP-42 Loading Model and the EPA Mass Balance Inhalation Model and varied
the saturation factor (f), ventilation rate (Q), mixing factor (k) using a Monte Carlo simulation.
See Appendix G.4 for more information about the Monte Carlo simulation. These models use
default parameter values and standard assumptions to develop estimates of inhalation exposures
for container loading and unloading operations.
Table G-13 summarizes the 2016 CDR data reported for the PV of 1,4-dioxane sold to
wholesalers and the container types assumed by EPA for the purposes of this risk evaluation
( 2016a). EPA assumed Tedia and BASF both ship 1,4-dioxane to wholesalers using
550-gal totes. This assumption yields a similar order of magnitude of the number of shipping
containers sent to wholesalers: approximately 32 totes for Tedia and approximately 58 totes for
BASF. EPA assumes Tedia's shipments are repackaged into 1-gal bottles since this volume is
often sold for laboratory use. EPA assumes BASF's shipments are repackaged into 55-gal drums
as the market for this volume is unknown. Table G-14 estimates the number of each type of
container per site.
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Table G-13. 2016 CDR Data and Assumed Container Types for Repackaging
( iimp;un
PV(ll>/\r)
V-ii of PV Sold in
\\ holos;ilors iiiid
Kcpiickiiuoil
Assumed luiliiil
( uiiliiiiicr l \|K'
iind Volume h
Assumed
Kopiickiiuod
( iiiiliiiuor T\pe
iiud Volume
Number iiI'
Uop;iek;itiod
( lllllililKTS
Tedia
151,265
Up to 100%a
Totes
(550 gal)
Bottles
(1 gal)
17,598
BASF
908,710
30%
Totes
(550 gal)
Drums
(55 gal)
577
a In the 2016 CDR, Tedia appears to report that up to 100% of its PV is shipped to each of its two end-use markets:
shipped directly to pharmaceutical and medicine manufacturing and shipped to wholesalers for resale to laboratory
use. Therefore, EPA assesses the entire PV (Manufacture + Imports) as the upper bound for repackaging for
laboratory use.
b Container types are not specified. These types are assumed based on PV and market.
Source: ( " 1.016a)
Table G-14. Number of Totes and Containers per Site
( oinp;m\
Number of I n
1 silo
les I uliiiiik'd per
•iile
IS silos
Number of Kop;ickiii£0(
Silo
1 silo
1 ( iiiiliiiuiTs pol-
ls silos
Tedia
32
2
17,598
978
BASF
58
3
577
32
To calculate central tendency and high-end exposures from repackaging 1,4-dioxane from totes
to drums and small containers, EPA modeled full-shift and short-term exposures using the
equations and parameters in Appendix G.2 and a Monte Carlo simulation. EPA assumed that
workers may be exposed to vapors from the breathing of smaller containers as they are loaded;
therefore, EPA assessed exposures for loading bottles and drums.
EPA assumed that one tote could be unloaded per day and the totes could be loaded directly into
the bottles or drums; therefore, the rate of unloading would be equal to the rate at which the
bottles or drums are loaded. Assuming default loading rates of 60 bottles per hour and 20 drums
per hour, it would take an estimated 9.2 hours to unload one tote into 550 bottles and 0.5 hours to
unload one tote into 10 drums. EPA assumed the bottles are loaded over the course of a full-shift.
Using the Monte Carlo simulation, EPA estimated the central tendency and high-end exposures
for unloading totes into bottles were 9.3 and 33 mg/m3, respectively. For repackaging into drums,
EPA averaged the 30-minute exposure over an 8-hour shift, assuming the workers are exposed to
1,4-dioxane while repackaging and then not exposed for the rest of the shift. The central
tendency and high-end 8-hour TWA exposures for unloading from totes into drums are 11 and
38 mg/m3, respectively. EPA also considered the 30-minute exposures of 170 and 610 mg/m3 to
be central tendency and high-end short-term exposures.
Since different container types may be used, the number of sites may range from 1 to 18 sites,
which also affects the number of days used to calculate acute and chronic inhalation exposures.
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To account for this, EPA used the equations in Appendix G.4 along with a Monte Carlo
simulation to vary the number of sites using a uniform distribution (i.e. integers only). The
results of these calculations are summarized in Section 3.4.1.3.
G.6.3 Industrial Uses
In the absence of available information, EPA assumes that industrial operations are similar in
this category. For uses grouped in the Industrial Uses category, EPA expected that 1,4-dioxane is
received as a solvent, intermediate, or catalyst in its final formulation and requires no further
processing. The 1,4-dioxane is then unloaded and sent to intermediate storage or used
immediately in the process. If used as an intermediate, 1,4-dioxane is likely consumed during the
reaction. For solvents or catalysts, spent 1,4-dioxane would be collected at the end of the process
for reuse, disposal, or recycling. Figure G-4 shows a basic process flow diagram for Industrial
Use.
Filtering/Recycling
(Optional)
Collection and
disposal of waste
1,4-Dioxane
received and
unloaded
Process Steps
(Intermediate
Destroyed)
Collection of spent
1,4-dioxane
(Optional)
Charged to
intermediate storage
(Optional)
Figure G-4. Generic Industrial Use Process Flow Diagram
Specific process description information is available for some uses of 1,4-dioxane. For example,
during wood pulping, 1,4-dioxane is used in an aqueous solution in organosolv pulping to extract
lignin from chipped wood. The solution is usually mixed in a ratio of 96 parts 1,4-dioxane to
four parts water (by volume). A ratio of 9:1, 1,4-dioxane to water, may also be used to increase
lignin yield, but the product will also have a higher carbohydrate content. During this process,
milled wood is mechanically stirred in an aqueous dioxane solution. The wood chip-dioxane
suspension is centrifuged and the remaining solids are washed again in a fresh aqueous dioxane
solution. The extract is dried to produce crude milled wood lignin (Obst and Kirk, 1988).
In pharmaceutical and medicine manufacturing, 1,4-dioxane is used as an intermediate, a process
solvent, and a solvent for purification. Pharmaceutical processes vary across the industry, but
nearly all process are batch operations. In general, pharmaceutical manufacture includes one or
more chemical reactions, followed by product separation, purification, and drying (U.S. EPA.
1978).
Specific worker exposure scenarios in the US are unknown but could be similar to those
described in the 2002 EU Risk Assessment for 1,4-Dioxane. Possible exposure scenarios
described in this assessment in industrial processes that use 1,4-dioxane as a solvent include
unloading 1,4-dioxane, sampling, maintenance activities, and drumming or loading spent 1,4-
dioxane for disposal (ECJRC, 2002). These exposure activities are related to the process flow
diagram shown in Figure G-4.
ONUs include employees that work at the site where 1,4-dioxane is used in an industrial setting
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as a solvent, chemical intermediate, or catalyst, but they do not directly handle the chemical and
are therefore expected to have lower exposures. ONUs for industrial use include supervisors,
managers, and tradesmen that may be in the processing area, but do not perform tasks that result
in the same level of exposures as production workers.
In Table 2-9 of Problem Formulation of the Risk Evaluation for 1,4-Dioxane ( 1),
EPA identified several conditions of use that may produce a mist. Some of those uses were
included within this Industrial Uses group; namely, wood pulping, extraction of animal and
vegetable oils, wetting and dispersing agent in textile processing, etching of fluoropolymers, and
recycling. Mist generation is not expected from the process steps shown in Figure G-4 or the
wood pulping process description. Therefore, exposures to mists from any use within the
industrial uses group were not assessed for workers or ONUs.
Number of Potentially Exposed Workers and Occupational Non-Users
The 2016 Chemical Data Reporting (CDR) database reported one site with 50 to 100 workers
and two sites with 250 to 1,000 workers each. These three sites only estimate workers for two of
the industries that may fall in this category: pharmaceutical and medicine manufacturing and all
other basic inorganic chemical manufacturing One site reported 50 to 100 workers and two sites
reported 250 to 1,000 workers each in the 2016 Chemical Data Reporting (CDR) database. These
three sites only estimate workers for two of the industries that may fall in this category:
pharmaceutical and medicine manufacturing and all other basic inorganic chemical
manufacturing ( ). Therefore, this range of 550 to 2,100 total workers could
underrepresents the workers exposed in all the industries related to this use category. Industries
that may fall in this category: pharmaceutical and medicine manufacturing and all other basic
inorganic chemical manufacturing ( a).
EPA identified NAICS code that were relevant to this condition of use and refined the number of
workers using relevant SOC codes. Table G-15 identifies the relevant NAICS. BLS data indicate
an average of 32 workers and 13 ONUs per site. The number of establishments within these
NAICS codes that use 1,4-dioxane-based solvents, intermediates, and catalysts are unknown. A
total of 43 sites in these NAICS codes reported discharging 1,4-dioxane in the 2016 TRI and
2016 DMR. EPA assumed this represents the total number of sites that use 1,4-dioxane in this
condition of use and estimates a total of 1,385 workers and 545 ONUs may be exposed during
this operations.
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Table G-15. Industrial Use NAICS Codes
NAICS Cock-
NAICS l)i-MTi|>lion
311224
Soybean and Other Oilseed Processing
311613
Rendering and Meat Byproduct Processing
313110
Fiber, Yarn and Thread Mills
322121
Pulp and Paper (except groundwood, newsprint) combined Manufacturing
325110
Petrochemical Manufacturing
325180
Other Basic Inorganic Chemical Manufacturing
325199
All Other Basic Organic Chemical Manufacturing
325211
Plastics Material and Resin Manufacturing
325320
Pesticide and Other Agricultural Chemical Manufacturing
32541 la
Medicinal and Botanical Manufacturing
325412
Pharmaceutical Preparation Manufacturing
325510
Paint and Coating Manufacturing
325520
Adhesive Manufacturing
3256133
Surface Active Agent Manufacturing
325992a
Photographic Film, Paper, Plate, and Chemical Manufacturing
325998
All Other Miscellaneous Chemical Product and Preparation Manufacturing
326113a
Unlaminated Plastics Film and Sheet (except Packaging) Manufacturing
3261303
Laminated Plastics Plate, Sheet (except Packaging), and Shape Manufacturing
327910b
Abrasive Product Manufacturing
334413
Semiconductor and Related Device Manufacturing
33599P
Carbon and Graphite Product Manufacturing
a - Data only available at the 4-digit NAICS level. Workers/site and ONUs/site numbers account for
%granularity.
b - BLS data unavailable (total workers and ONUs). Averaged workers/site and ONUs/site for the other
NAICS Codes.
Worker and Occupational Non-User Exposure Assessment
The 2002 EU Risk Assessment provided a summary of some exposure data relevant to the
conditions of use outlined in Section 3.4.1.5. The Finnish Environmental Institute and an
unnamed company provided the datasets, and the data provided ranged from 1989 to 1998. Some
of the exposure data cover uses that are not applicable to this Industrial Uses group; therefore,
EPA selected data for the uses related to this group. Select data specific to this Industrial Uses
group are summarized in Table G-16.
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Table G-16. DoD and 2002 EXT Risk Assessment Industrial Use Inhalation Exposure Data
Industries or Tsisk
Number ol°
Siimplos
r.\
U untie
posurc l.c\cls (ii
A \ er;iiie
lii/ni1)
yo"1 piTCCIllilc
Source
Medicine manufacture3
20 b
1.8-18
6.5
(ECJRC. 2002)
Pharmaceutical
production3
<30c
<3.6
("ECJRC. 2002)
Use (e.g. as solvent) in
other productions'1
194°
<0.01-184
0.11e
1.8
rECJRC. 2.002)
Use (e.g. as solvent) in
other productions'1
49°
<0.04-7.2
0.07 e
0.62
rECJRC. 2002)
Plastic Thermoforming
1
<72
(DoD, 2018)
" The 2002 EU Risk Assessment does not provide information about these uses to describe the difference between
medicine and pharmaceutical manufacture. EPA assumes the processes are similar. These datasets also come from
different sources in the report.
b Fixed and personal samples.
0 Personal samples.
d These datasets were provided by the same company, but as separate datasets from different time periods.
e These were medians.
The 2002 European Union Risk Assessment provided calculated exposure estimates using
exposure data from similar scenarios and the Estimation and Assessment of Substance Exposure
(EASE) model. The EASE model was developed by the US Health and Safety Executive with
the Health and Safety Laboratory. It predicts expected dermal and inhalation exposures for a
wide range of substances and scenarios using situational information related to the chemical
(Tickmer et at.. 2005). The scenario considers exposures specifically from activities related to the
use of 1,4-dioxane as an extractant medicine manufacturing. The assessment assumes that it is an
essentially closed system which may be breached and local exhaust ventilation (LEV) is used.
Using these assumptions, the model calculated an inhalation exposure of 36 to 180 mg/m3
(ECJRC. 2002).
EPA reached out to the Department of Defense (DoD) for monitoring data for TSCA chemicals.
The DoD provided monitoring data from its Defense Occupational and Environmental Health
Readiness System - Industrial Hygiene (DOEHRS-IH), which collects occupational and
environmental health risk data from each service branch. The dataset provided by the DoD to
EPA included one sample for 1,4-dioxane exposure. The sample was a personal sample taken
December 4, 2015 from a plastic thermoforming process. The total sampling time was 104
minutes and the measured result was <20,000 ppb (72 mg/m3) (DoD. 2018).
The 2002 EU Risk Assessment states that the inhalation estimates from EASE appear to
considerably overestimate the exposures and recommends a central tendency exposure of 5
mg/m3 (full- shift) and a reasonable high-end exposure of 20 mg/m3 (full-shift) for the end use of
1,4-dioxane, mainly based on the highest exposure level during medicine manufacture (ECJRC.
2002). This recommended range agrees well with the exposure data in Table G-16, except for
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one of the data points. The exposure level of 184 mg/m3 is likely an outlier, considering the 90th
percentile of that range is 1.8 mg/m3. Therefore, the proposed range of 5 to 20 mg/m3 was used
to estimate the inhalation exposures for the Industrial Uses group. These central tendency and
reasonable high-end estimates were assumed to be equivalent to central tendency and high-end
values, respectively and representing an 8-hour TWA value. Acute and chronic inhalation
exposures for Industrial Uses were calculated using the equations in Appendix G.2. Results of
these calculations are summarized in Section 3.4.1.5.
G.6.4 Functional Fluids (Open System)
EPA assessed the industrial use of metalworking fluids in the metal products and machinery
(MP&M) industry (U.S. EPA. 2017c). Metalworking fluids (formulations ranging from straight
oils to water-based fluids, which include soluble oils and semisynthetic/synthetic fluids) are used
to reduce heat and friction and to remove metal particles in industrial machining and grinding
operations. Cutting and tapping fluids are a subset of metalworking fluids that are used for the
machining of internal and external threads using cutting tools like taps and thread-mills. In
general, industrial metal shaping operations include machining, grinding, deformation, blasting,
and other operations and may use different types of metalworking fluids to provide cooling and
lubrication and to assist in metal shaping and protect the part being shaped from oxidation
(OECD. ). Of the three open-system functional fluids identified in the Preliminary
Information on Manufacturing, Processing, Distribution, Use, and Disposal: 1,4-Dioxane (U.S.
EPA. 2017c). only one (a cutting and tapping fluid) has a safety data sheet (SDS) with
information indicating the 1,4-dioxane content ranges from 0.01 to 0.1 wt%. While some cutting
and tapping fluids may be used by consumers in a DIY setting, there are no consumer uses
reported to the CDR (\ >_ I \ -OTr).
The Emission Scenario Document (ESD) on the Use of Metalworking Fluids provided a generic
process description of the industrial use of metalworking fluids in the metal products and
machinery (MP&M) industries (OECD. 2011). Metalworking fluids are typically received in
containers ranging from 5-gallon pails to bulk containers. Water-based metalworking fluids are
unloaded and diluted with water on-site before being transferred into the trough of the
metalworking machine. Straight oils are not diluted and instead transferred directly into the
trough. The metalworking fluids are pumped from the trough and usually sprayed directly on the
part during metal shaping. The fluid stays on the part and may drip dry before being rinsed or
wiped clean. Any remaining metalworking fluid is usually removed during a cleaning or
degreasing operation (OECD. ). A generic process flow diagram is shown in Figure G-5.
Workers could unload the metalworking fluid from containers; clean containers; dilute water-
based metalworking fluids; transfer fluids to the trough; perform metal shaping operations; rinse,
wipe, and/or transfer the completed part; change filters; transfer spent fluids; and clean
equipment (OECD. 2011Y
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Filtering/Recycling
Metalworking
Fluid
Part
Rinsed/Dried
Dilute with Water
(Water-Based Only)
Disposal of Spent
Metalworking Fluid
Sprayed onto
Part During
Metal Shaping
Charged to Metal
Shaping Machine
Trough
Figure G-5. Process Flow Diagram for Open System Functional Fluids
ONUs include employees that work at the site where 1,4-dioxane is used in an industrial setting
as an open-system functional fluid, but these employees typically do not directly handle the
chemical and are therefore expected to have lower exposures. ONUs for open-system functional
fluids include supervisors, managers, and tradesmen that may be in the processing area but do
not perform tasks that result in the same level of exposures as machinists.
Since 1,4-dioxane has a high vapor pressure (40 mm Hg at 2525°C), workers could be exposed
to 1,4-dioxane when handling liquid metalworking fluid, such as unloading, transferring, and
diluting neat fluids, and disposing spent fluids and cleaning machines and troughs. However, due
to 1,4-dioxane's low content in metalworking fluids (0.01 to 0.1 wt%), the 1,4-dioxane partial
pressure could be low and would reduce exposure to 1,4-dioxane vapors.
The greatest source of potential exposure is during metal shaping operations. The high machine
speeds can generate airborne mists of the metalworking fluids to which workers could be
exposed. Additionally, the high vapor pressure of 1,4-dioxane could lead to its evaporation from
the airborne mist droplets, potentially creating a fog of vapor and mist. However, the low
concentration of 1,4-dioxane in metalworking fluids could lead to a low partial pressure, which
would mitigate the evaporation of the 1,4-dioxane from the mist droplets.
Number of Potentially Exposed Workers and Occupational Non-Users
EPA estimated 89,000 MP&M industrial sites in the in the US (OECD. 2011). The ESD does not
provide total workers in the industry but cites a NIOSH study of 79 small machine shops, which
observed an average of 46 machinists per site. The ESD also cites an EPA effluent limit
guideline development for the MP&M industry, which estimated a single shift supervisor per
shift, who could perform tasks such as transferring and diluting neat metalworking fluids,
disposing spent metalworking fluids, and cleaning the machines and troughs (OECD. 2011).
Since the machinists perform the metal shaping operations, during which metalworking fluid
mists are generated, EPA assesses the machinists as workers, as they have the highest potential
exposure. EPA assessed the single shift supervisor per site as an ONU, as this employee is not
expected to have as high an exposure as the machinists. Assuming two shifts per day (hence two
shift supervisors per day), EPA assesses 46 workers and two ONUs per site (OB ).
Although, per the ESD, it is possible the shift supervisors may perform some tasks that may lead
to direct handling of the metalworking fluid, EPA assesses these shift supervisors as ONUs as
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their exposures are expected to be less than the machinist exposures and EPA is already
assessing the machinists as workers, which yields a high worker-to-ONU ratio of 23-to-l. The
number of establishments within this NAICS code that use metalworking fluids and the number
of those establishments that use 1,4-dioxane-based metalworking fluids are unknown. EPA
estimates 89,000 total sites per the ESD and estimates a total of 4,094,000 workers and 178,000
ONUs. Therefore, EPA provides the total number of establishments and potentially exposed
workers and ONUs as bounding estimates of the number of establishments that use and the
number of workers and ONUs that are potentially exposed to 1,4-dioxane-based metalworking
fluids during metal shaping operations. These bounding estimates are likely overestimates of the
actual number of establishments and employees potentially exposed to 1,4-dioxane during metal
shaping operations.
Worker and Occupational Non-Users Exposure Assessment
EPA assessed worker exposures EPA AP-42 Loading Model and the EPA Mass Balance
Inhalation Model and varied the saturation factor (f), ventilation rate (Q), mixing factor (k) using
a Monte Carlo simulation (see Appendix G.4) These models use default parameter values and
assumptions to provide screening level assessments of inhalation exposures for container
unloading operations. EPA estimated 77 containers per site per year using default values and
equations provided in the ESD and assumes that one container is unloaded per day, resulting in
an exposure duration of 3 minutes (0.054 hours). EPA presents these values, 0.17 and 0.61
mg/m3, as central tendency and high-end short-term exposures, respectively. The simulation also
estimated 0.0011 and 0.0038 mg/m3 as 50th and 95th percentile 8-hour TWA exposures. EPA
used these values to calculate acute and chronic inhalation exposures in the Monte Carlo
simulation, varying working years (WY), using the equations in Appendix G.2. See Section
3.4.1.6 for a summary of the results.
A 1997 NIOSH HHE provided PBZ and area data for workers at the Dana Corporation, Spicer
Axle Division facility in Fort Wayne, Indiana. NIOSH conducted PBZ and area measurements of
water-soluble synthetic metalworking fluids and oil mists from conventional metalworking
fluids. These data are of the total concentration of oil mists or synthetic metalworking fluid
particulates in the air (Burton andDriscoll, 1997). The NIOSH HHE does not identify 1,4-
dioxane as a component of the metalworking fluids used at the facility (although NIOSH did
identify 1,4-dioxane as a component of a flow-coat paint used at the facility). To estimate
potential 1,4-dioxane exposures, the concentration of the synthetic metalworking fluid or oil mist
was multiplied by 0.1%, the high-end concentration of 1,4-dioxane in metalworking fluids
identified by EPA (U.S. EPA. ). These data are summarized in Table G-17.
Table G-17.1997 NIOSH HHE PBZ and Area Sampling Data for Metalworking Fluids
Jul) l)eseriplion/.\rea
Sample
lime (lir)
Sample
Volume
(1.)
( oneenlralion img/m');|
( oneenlralion of
l.4-l)io\ane
(ing/m M •' h
Sample
Tj pe
Metalworking Fluids
Several Operations at
Transfer Lines/ Dept.
661
6.70
804
0.53
0.00053
Personal
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Roughing/Dept. 661
6.77
812
0.43
0.00043
Personal
Four-Way/Dept. 541
6.53
784
0.46
0.00046
Personal
Multiple/ Dept. 373
5.98
718
0.22
0.00022
Personal
Screw Machine-
Lathing/Dept. 171
6.28
754
0.24
0.00024
Personal
Apex Drill/Dept. 151
6.22
746
0.24
0.00024
Personal
Threader/ Dept. 373
6.08
730
0.14
0.00014
Area
Broaching/ Dept. 375
5.82
698
0.17
0.00017
Area
Apex Drill/Dept. 354
6.15
738
0.23
0.00023
Area
Lunch Tables/ Dept.
375
5.68
682
0.21
0.00021
Area
Oil Mists
Lathing/H3
6.92
830
0.08
0.00008
Personal
Burr Drill/H6
6.63
796
0.1
0.0001
Personal
Gear Cutter/K6
6.50
780
0.23
0.00023
Personal
Burnisher/K6
6.48
778
0.13
0.00013
Personal
Screw Machine
6.32
758
0.13
0.00013
Personal
Gear Cutter/N9
6.37
764
0.3
0.0003
Personal
Gear Cutter/N7
6.40
768
0.25
0.00025
Personal
Gear Cutter/Grinder
6.03
724
0.26
0.00026
Personal
Gleason Cutting
Machines/N5
6.10
732
0.33
0.00033
Area
a The duration corresponds to the sample time listed for this concentration.
b Calculated by multiplying concentration by 0.1%, the expected concentration of 1,4-dioxane.
Source: (Burton and Priscoll. 1997)
EPA compared the distribution of 8-hour TWA results produced by the Monte Carlo simulation
with the 8-hour TWA values calculated from the NIOSH HHE sample measurements and
observed that all of the NIOSH HHE results are less than the 10th percentile of the Monte Carlo
distribution. This indicates that the NIOSH HHE sample results are insignificant compared to the
distribution produced by the Monte Carlo simulation and contribute a minor effect on the overall
final estimate.
EPA compiled the five area measurements from Table G-17 into a single dataset and calculated
the 50th and 95th percentile to estimate central tendency and high-end ONU inhalation exposures.
EPA used these values to calculate acute and chronic exposures using the equations in Appendix
G.2. See Section 3.4.1.6 for a summary of the results.
The 2011 OECD ESD on the Use of Metalworking Fluids estimates typical and high-end
exposures for different types of metalworking fluids. These estimates are provided in Table G-18
and are based on a NIOSH study of 79 small metalworking facilities. The concentrations for
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these estimates are for the solvent-extractable portion and do not include water contributions.
EPA assumes the concentration data available is before dilution and is therefore already equal to
the concentration of the dioxane in the mist.
Table G-18. 2011 ESP on Metalworking Fluids Inhalation Exposure Estimates
Tj po of
Mel;il\\orkinii f luid
T>l>ic;il Misl
( nniTiili'iiliuii
(mii inisl/inM ¦'
Ttpii'iil 1.4-1) io\;i tie
( niKTiilnilioii
(niii/iii M h
lliuh-l nd Misl
( oiKTiili'iilion
(nili inisl/ni V
Nigh-l-ind 1.4-
l)io\iino
( OllCCIIII'illioil
(m*i /in') h
Conventional
Soluble
0.19
0.00019
0.87
0.00087
Semi-Synthetic
0.20
0.00020
0.88
0.00088
Synthetic
0.24
0.00024
1.10
0.0011
Straight Oil
0.39
0.00039
1.42
0.0014
a Geometric Mean
b Calculated by multiplying concentration by 0.1%, the expected concentration of 1,4-dioxane.
0 90th Percentile
Source: (OEC )
G.6.5 Laboratory Chemical Use
The laboratory worker activities may include preparing the mobile phase by degassing with
helium, nitrogen, or processing reactions in an ultrasonic bath (ECJRC. 2002). In addition to
these applications and others listed in Section 3.4.1.8, EPA expects conditions of use could
involve activities such as unloading small quantities of chemicals; applications/filling and
emptying using small volumes for laboratory activities such as preparing samples, performing
small scale reactions, or for quality control or calibration purposes; and loading waste 1,4-
dioxane into containers for recycling or disposal. TWA exposures typically are small, as the
majority of workers could only be exposed intermittently to 1,4-dioxane due to the infrequency
of such applications and filling and emptying of the solvent reservoir is reportedly carried out in
a fume cupboard. In addition to laboratory analysts/workers, ONUs may include supervisors,
laboratory managers, and laboratory analysts and technicians that perform other tasks in a
laboratory setting where 1,4-dioxane is used but do not directly handle the chemical and are
therefore expected to have lower exposures.
Descriptions of the specific process for how 1,4-dioxane is used in each of these conditions of
use are not available. In general, 1,4-dioxane could be received in small containers and used in
small quantities on a lab bench under a fume cupboard or hood. After use, the waste 1,4-dioxane
is collected and disposed of or recycled (see Figure G-6). Quantities used in laboratory use could
be disposed of with other laboratory liquid waste and/or diluted under certain occasions, but
quantities used by individual laboratories would be typically small.
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1,4-Dioxane
received in sma
containers
Waste 1,4-dioxane
collected and disposed
of or recycled
Used in small
quantities for various
lab uses
Figure G-6. General Laboratory Use Process Flow Diagram
Number of Potentially Exposed Workers and Occupational Non-Users
A single submitter to the 2016 CDR reported selling an unknown volume of 1,4-dioxane for use
as a laboratory chemical. The submitter estimated selling 1,4-dioxane to fewer than 10 sites
(through the use of wholesalers and retailers). The submitter further estimated that at least 50 but
less than 100 laboratory workers could be potentially exposed ( .). EPA used
U.S. Census and BLS data for the NAICS code 541380, Testing Laboratories, and relevant SOC
codes to estimate a total of 6,844 sites, 6,610 workers, and 804 ONUs, which corresponds to an
estimated average of one worker and 0.12 ONUs per site. EPA used these data to calculate a
ratio of 8:1 workers to ONUs. EPA applied this ratio to the total number of workers reported in
CDR to estimate total of 44 to 89 workers and 6 to 11 ONUs.
The number of establishments within this NAICS code that use 1,4-dioxane-based laboratory
chemicals are unknown. Therefore, EPA used the total number of establishments and potentially
exposed workers and ONUs in this NAICS code as bounding estimates for the number of
establishments that use and the number of workers and ONUs that are potentially exposed to 1,4-
dioxane-based laboratory chemicals in a laboratory setting. These bounding estimates likely
overestimate the actual number of establishments and employees potentially exposed during the
use of 1,4-dioxane as a laboratory chemical.
Worker and Occupational Non-User Exposure Assessment
The Ell Risk Assessment (2002) provides monitoring data for laboratory work activities from
the Finnish Environmental Institute (FEI) and an unnamed company. Table G-19 summarizes the
exposure levels. The assessment states that the first data point (laboratory work) is probably from
the use of 1,4-dioxane as the mobile phase in HPLC and dilution ventilation was present but does
not provide any context about specific worker activities for the rest of the data (ECJRC. 2002)
reported: "[t]he Finnish Environmental Institute (FEI, 1996) provided some exposure data
during the use of 1,4-dioxane in a cleaning agent, during the use in a laboratory (probably as
the mobile phase in HPLC), and during medicine manufacturing (as an extractant). Company A
(1997/1998) provided exposure data during the use of the substance in a laboratory, in the
pharmaceutical industry ...". The EU risk assessment grouped the laboratory use with
pharmaceutical manufacturing; therefore, the risk assessment did not provide recommended
central tendency or high-end values specific to laboratory use. The high concentrations in the
monitoring data were considered outliers and the highest concentrations short-term peak
exposures. An additional risk assessment report for 1,4-dioxane (NUCHAS. 1998) did not provide
occupational exposure data but cited a study where the highest 8-hour TWA value from personal
monitoring was 1.8 ppm (approximately 6.5 mg/m3) KRimatori et at. 1994; Hertlein. 1980).
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Table G-19. Monitoring Data for Laboratory Chemicals
Industries or Tusk
Number of Samples
K\po>
U:in»e
lire I.cm
Mosul
'Is (111 "/ill"4)
l) percentile
Laboratory Work (HPLC)
1
165 3
Laboratory
305
0-166
0.11
0.58
Laboratory
29
<0.07-0.18
<0.07
0.15
a Only a single measurement was provided for laboratory work associated with HPLC use.
Source: (ECJRC. 2002)
Based on the monitoring data available from the EU risk assessment (ECJRC. 2002). EPA used
0.11 mg/m3 and 5.7 mg/m3 to assess the central tendency and high-end exposures, respectively.
EPA calculated the high-end value by calculating an 8-hour TWA of the 15-minute short-term
peak exposure and the 90th percentile value of 0.58 mg/m3 per Equation G-l 1.
Equation G-ll. High-End Inhalation Value for Laboratory Chemicals
(o.25 hr Xl66^) + (7.75 hr x 0.58^) __ ^mg
8 hours m3
This calculated, high-end value compares with the highest 8-hour TWA reported in the NICNAS
report of 6.5 mg/m3. Acute and chronic inhalation exposures for laboratory uses are calculated
using the equations in Appendix G.2 and sample calculations are found in Appendix G.3. Results
of these calculations are summarized in Section 3.4.1.8.
G.6.6 Film Cement
The Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal:
1,4-Dioxane lists one SDS for film cement, which contains 1,4-dioxane at a concentration of
45% to 50% ( )17c). Film cement is used in the film processing and archiving
industries to splice celluloid movie film together. This splicing processing is typically done by
hand in an open process. Film is cut using a special tool, then the cement is applied to the edges
of the film by hand using a small brush. The pieces of film are joined together by closing the tool
and heating to 35 °C to dry the cement. Film is also cleaned, which may be done using a sonic
cleaner or as a manual operation. One site in Australia reports using 12 liters of the cement per
year (NICNAS. 1998; Okawa and Cove. 1982.). A 1980 NIOSH HHE of two U.S. film
laboratories observed upwards of 100 splices conducted by an employee per day and estimated
less than 10 mL of cement used by an employee per shift (Okawa and Co' 2). See Figure
G-l.
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Film cement
containing 1,4-
Dioxane received in
bottles
Film cut using special
tool
Film cement manually
applied to the film
edge using a small
brush
Cut and glued film
edges joined, heated
to facilitate drying
Automated or manual
film cleaning
Figure G-7. Process Flow Diagram for Film Cement Application
The National Industrial Chemicals Notification and Assessment Scheme (NICNAS) reported that
the splicing operation at a site in Australia was manual (NICNAS. 1998). Workers processed and
cut the film, applied the cement, and joined the cut film pieces together using the heated tool.
Workers would also manually clean the film using solvents. Two American film laboratories also
used a similar process; therefore, EPA expects worker activities in the U.S. to be similar. These
exposures are based on the activities shown in the process flow diagram in Figure G-7.
ONUs include employees that work at the film processing lab where 1,4-dioxane is used in a
film cement, but they do not directly handle the chemical and are therefore expected to have
lower exposures. ONUs for film laboratories include supervisors, laboratory managers, and
laboratory workers that perform other tasks but do not directly handle 1,4-dioxane.
Number of Potentially Exposed Workers and Occupational Non-Users
NICNAS estimated up to 10 laboratories perform the film cement processing in Australia, with
about three workers potentially exposed up to eight hours per day per site (NICNAS. 1998). The
report also stated that an unknown additional number of workers could be exposed at these sites.
The film laboratory could deploy up to four workers to handle duties related to film splicing
(Okawa and Co 2). EPA identified NAICS code 512199, Other Motion Picture and Video
Industries, as the relevant NAICS code for this use. Data from the U.S. Census Bureau for the
Statistics for U.S. Businesses (SUSB) for this code indicated 211 sites and 1,238 total
employees. Due to the diversity of operations covered by this NAICS code, this could be an
overestimate for the total number of sites and workers that perform this specific operation using
film cement containing 1,4-dioxane. It is assumed that all U.S. film laboratories use a process
similar to the one outlined in the NICNAS report and therefore have a similar number of workers
per site. EPA estimated a total of 30 workers and 10 ONUs for all sites.
The number of establishments within this NAICS code that splice film and the number of those
establishments that use 1,4-dioxane-based film cement are unknown. Therefore, EPA provides
the total number of establishments and potentially exposed workers and ONUs in this NAICS
code as bounding estimates of the number of establishments that use and the number of workers
and ONUs that are potentially exposed to 1,4-dioxane-based film cement during film splicing
operations. These bounding estimates could overestimate the actual number of establishments
and employees potentially exposed to 1,4-dioxane during film splicing operations.
Worker and Occupational Non-User Exposure Assessment
The NICNAS report (NICNAS. 1998) did not have Australian air monitoring data but referenced
a NIOSH HHE that collected data in 1980 from two U.S. film laboratories (Okawa and Cove.
1982). EPA noted that these are historic monitoring data and that processing technologies may
have changed. The HHE identified 1,4-dioxane as a component in the film cement used in film
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splicing. However, the HHE did not specify the concentration of 1,4-dioxane in the formulation.
EPA calculated values for samples that were non-detects using the flow rate, and limit of
detection from NIOSH Method 1602 (NIOSH. 1994). From the measured and calculated values,
EPA calculated 8-hour TWA values (see Table G-20).
Table G-20. NIOSH HHE PBZ and Area Samples for Film Cement Use
l.ociilion
Job 1 iilo or
Opoi'iilion
Siimplo
Tj \W
Siimplo
Diirnlion
(hi)
( oiicenlr;i(ion
(inii/in1) •'
( iilciiliilod
(onceii Initio n
(inii/in1) •'
X-lloiir
T\\ A
(in •j/iir')
Technicolor
Splicer
(Behind glass
doors)
PBZ
5.67
3.1
3.1
2.2
Technicolor
Splicer (Main
Room)
PBZ
1.67
NDb
1.0 c
0.95 d
Technicolor
Splicer (Main
Room)
PBZ
4.25
1.4
1.4
Technicolor
Manual Film
Cleaning
PBZ
6.42
3.5
3.5
2.81
MovieLab
Splicer
PBZ
5.58
NDb
0.30 c
0.21
MovieLab
Splicing
General Area
Area
5.50
NDb
0.30 c
0.21
a The duration corresponds to the sample time listed for this concentration.
b ND - non-detect
0 EPA calculated a value for non-detects using limit of detection of 0.01 mg/sample (NIOS 4).
d These two samples are for the same operator; therefore, EPA averaged them together for the 8-hour TWA
calculation.
Source: (Okawa and Co 2)
Due to the small size of the data set (five data points), EPA calculated the 50th percentile to
assess the central tendency exposure and presented the maximum as the high-end exposure. EPA
used these values to calculate acute and chronic inhalation exposures using the equations in
Appendix G.2. The results of these calculations are summarized in Section 3.4.1.9.
The one area sample result was a non-detect (Okawa and Cove. 1982). which means the
concentration was lower than the level of detection for the method at that time. EPA calculated
an upper bound for this value using half of the method detection limit. EPA considered this value
as an 8-hour TWA exposure value for ONUs. This value is plausible, but EPA cannot determine
the statistical representativeness of the value given the small sample size. This value was used to
calculate acute and chronic inhalation exposures as per the equations in Appendix G.2. The
results of these calculations are summarized in Section 3.4.1.9. Dermal exposures are not
expected for ONUs.
G.6.7 Spray Foam Application
There are three main types of spray polyurethane foam (SPF): two-component high-pressure,
two-component low-pressure, and one OCF. The low-pressure and OCF types are available for
DIY-use, but the high-pressure type is only available for professional use. A safety data sheet
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(SDS) identified in the Preliminary Information on Manufacturing, Processing, Distribution,
Use, and Disposal: 1,4-Dioxane indicate that 1,4-dioxane is present in open- and closed-cell
SPFs, which are subsets of two-component high-pressure SPFs (U.S. EPA. 2.017b. c). While one
SDS has been identified where 1,4-dioxane was listed as an ingredient, it could also be an
impurity/byproduct and the concentration could vary by the type of SPF.
This type of SPF is used for larger insulation applications, as an air sealant in hybrid insulations,
and in roofing applications. The components are typically stored in 55-gallon drums. The
operator pumps both components (sides A and B) through heated tubes from the supply tanks
into a nozzle. 1,4-Dioxane is a component in Side B with concentrations typically around 0.1%
{U.S. EPA, 2017, 3986663;U.S.EPA, 2017, 3970070}. Sides A and B begin to react in the
nozzle and are sprayed at elevated pressures and temperatures (>150 °F and 1,200 psi). Closed-
cell foam could be applied in layers. As the foam cures, it expands up to 120 times its original
size. After curing, the foam could be trimmed or cut. Trimmings and waste foam are collected
and disposed. See Figure G-8 for a typical process flow diagram for spray foam application.
Figure G-8. Process Flow Diagram for Spray Application
Worker activities for the application of high-pressure SPF include transferring the component
containing 1,4-dioxane from the drum to the supply tank, applying the spray foam mixture,
trimming foam after it cures, and disposing of trimmings and waste that may contain 1,4-dioxane
(I. * n \ 2018a. I b).
Non-sprayer workers include employees that work at the site where 1,4-dioxane is used during
spray foam application, but do not directly handle the chemical and are therefore expected to
have lower exposures. Non-sprayer workers for spray foam application include construction
managers, engineers, drafters, supervisors, and workers performing other tasks that may be in the
area where the spray foam is being applied, but do not perform tasks that result in the same level
of exposures as workers. Non-sprayer workers may also perform trimming tasks after the
insulation has cured.
Number of Potentially Exposed Workers and Non-Sprayer Workers
Data for the number of potentially exposed workers and non-sprayer workers are unknown. EPA
reviewed BLS data for NAICS code 238310, Drywall and Insulation Contractors, along with
relevant SOC codes, which estimated 17,857 establishments, 162,518 workers, and 15,627 non-
Spny Rtg f
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sprayer workers. EPA estimated nine workers and one non-sprayer worker per establishment.
The number of establishments within this NAICS code that install spray polyurethane foam
installation and the number of those establishments that use 1,4-dioxane-based spray
polyurethane foam are unknown. Therefore, EPA considered the total number of establishments
and potentially exposed workers and non-sprayer workers in this NAICS code as bounding
estimates of the number of establishments that use and the number of workers and non-sprayer
workers that are potentially exposed to 1,4-dioxane-based spray polyurethane foam during
insulation installation. These bounding estimates are likely overestimates of the actual number of
establishments and employees potentially exposed to 1,4-dioxane during spray polyurethane
foam insulation installation, since only a single spray polyurethane foam product that contains
1,4-dioxane was identified.
Worker and Non-Sprayer Worker Exposure Assessment
Monitoring data for inhalation exposure to 1,4-dioxane from spray application of SPF is not
known. EPA assumed that the spray foam containing 1,4-dioxane is only used for roofing
applications, per the technical data sheet for the spray polyurethane foam identified in the
Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal: 1,4-
Dioxane ( ). EPA used assumptions and values from the 2018 GS on the
Application of Spray Polyurethane Foam Insulation to calculate the use rate per site (U.S. EPA.
2018a). These values and relevant parameters are summarized in Table G-21.
Table G-21. Values Used for Daily Site Use Rate for SPF Application
I'simmeler
Svin hoi
Value
I nil
Operating days per site
ODsite
3 a
days/site
Roofing area
A
1500 b
ft2
SPF density
P
3.2 c
lb/ft3
SPF thickness
t
0.33a
ft
Mass fraction of 1,4-dioxane in B-side
F chem, B-Side
0.001 d
dimensionless
Mass fraction of B-side in mixed SPF
FB-Side
0.5 c
dimensionless
Mass fraction of 1,4-dioxane in mixed
SPF
F chem, SPF
0.0005 a
dimensionless
Use rate of SPF per site
Q SPF, site
718.5a
kg spf/site
Daily Use Rate of 1,4-dioxane per site
Qchem,site
0.12 a
kg chem/site-day
Number of drums B-side unloaded per
site-job
NDrums
1.7 a
drums/site-job
Unloading rate for drums
r
20 a
drums/hour
a( 18a)
b (HomeAdvisor. 2018; Huber. 2018)
0 (OMG Roofing Products. 2018)
d (GAF. 20141
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Per the GS, EPA modeled inhalation exposures from unloading using the EPA AP-42 Loading
Model and the EPA Mass Balance Inhalation Model and varied the saturation factor (f),
ventilation rate (Q), mixing factor (k) using a Monte Carlo simulation. See Appendix G.4 for
more information about the Monte Carlo simulation. These models use default parameter values
and assumptions to provide screening level assessments of inhalation exposures for container
unloading operations. Assuming an unloading rate of 20 drums/hour and one drum/site, EPA
estimates that workers will be exposed for less than two minutes during drum unloading.
EPA also used the EPA Total PNOR PEL-LimitingModel with the OSHA PEL for particulates
(15 mg/m3) to estimate inhalation exposures to mists during application. EPA estimates an
exposure of 0.0075 mg/m3 to mists during application. This estimate does not account for the
potential evaporation of 1,4-dioxane from the mist particulates and the potential inhalation
exposure of the evaporated vapors. 1,4-Dioxane has a high vapor pressure (40 mmHg at25 °C);
however, the weight % of 1,4-dioxane in the SPF particulates is very low (0.05 wt% in the mixed
SPF. Therefore, the partial pressure of 1,4-dioxane is low enough so that inhalation might not be
a significant route of exposure.
EPA estimated exposures from thickness verification using surrogate exposure data provided in
the GS from a different chemical with similar properties. 1,2-Dichloroethane (1,2-DCE) has a
vapor pressure of 61 mmHg and a molecular weight of 98.96 grams per mole, which is similar to
the physical properties of 1,4-dioxane (VP = 40 mmHg at 25 °C, MW = 88.1 g/mol). The
exposure data for the surrogate chemical showed a central tendency exposure of 0.044 mg/m3
and a high-end exposure of 0.077 mg/m3. EPA used Equation G-12 to estimate central tendency
and high-end exposures to 1,4-dioxane during foam thickness verification. EPA assumes an
exposure duration of one hour.
Equation G-12
w MWchem interest ^ VPchem interest ^ ^chem interest
^•m_chem interest ~ ^m_surrogate * MTAZ y i/d 3 y
M W surrogate * v"surrogate * A surrogate
EPA calculated central tendency and high-end 8-hour TWA exposure assuming that the drum is
unloaded at the beginning of the day and the remainder of the 8-hour shift is spent applying the
spray foam insulation and verifying the thickness of the insulation. See Table G-22 for estimated
exposure durations for each activity. EPA used these values to calculate acute and chronic
inhalation exposures in the Monte Carlo simulation, varying working years (WY), using the
equations in Appendix G.2. See Section 3.4.1.7 for a summary of the results.
Table G-22. Estimated Activity Exposure Durations
Activity
Kxposurc Duration (hours)
Drum Unloading
0.028
Spray Foam Application
6.97
Thickness Verification
1.0
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Exposure data for non-sprayer workers were not available. Per the GS, EPA assumed that some
non-sprayer workers may perform tasks related to trimming the cured spray foam insulation.
EPA used the EPA Total PNOR PEL-LimitingModel with the OSHA PEL for particulates (15
mg/m3) to estimate inhalation exposures to particulates during trimming. An exposure of
particulates at the rate of 0.0075 mg/m3 considered to occur during trimming. EPA averaged this
exposure over an 8-hour shift, assuming this exposure occurs over one hour and that non-sprayer
workers are not exposed to 1,4-dioxane during the rest of the shift. EPA presents this as an 8-
hour TWA inhalation exposure value for non-sprayer workers. This value is plausible, but EPA
cannot determine the statistical representativeness of the value given the small sample size. This
value was used to calculate acute and chronic inhalation exposures as per the equations in
Appendix G.2. Only inhalation exposures to vapors are expected, which could be less than
worker exposures.
G.6.8 Printing Inks (3D)
The Preliminary Information on Manufacturing, Processing, Distribution, Use, and Disposal:
1,4-Dioxane identified one SDS for an inkjet printing cartridge used in standard inkjet printers
that may contain 1,4-dioxane. However, the SDS does not indicate that 1,4-dioxane is an
intended ingredient in this cartridge ( ). Recent articles identified 1,4-dioxane as
a major component in inks used in additive manufacturing, also known as three-dimensional
(3D) printing (He et al., 2016; Ryan and Hubbard, 2016; Ruggiero et al., 201Ue et at., 2013).
Therefore, EPA assessed exposures related to the use of 1,4-dioxane as a component in printing
inks in additive printing manufacturing.
1,4-Dioxane could be present in solvent-based inks that are used in a type of additive
manufacturing known as material jetting. The concentration of 1,4-dioxane in these inks ranges
from 75% to 99.5%, based on the solvent system (He et al., 2016; Ruggiero et al., 2.015; He et
al.. 2013). In this process, the ink could be made on site or received in cartridges or syringes
(Figure G-9). The liquid ink is charged to a cartridge in the material printer. The printing head
deposits the ink one drop at a time on the substrate. Each drop is cured to form a solid structure
using an outside energy source, such as ultraviolet light or heat. The final product is cleaned in a
bath of a concentrated, highly corrosive material to remove support structures (He et al.. 2016).
Finished products cleaned
with corrosives, packaged,
and sent to customers
Printing ink containing
1,4-Dioxane received in
cartridges, or syringes or
made on site
Cartridge installed or
printing ink injected into
the cartridge in material
printer
Printing ink applied to
substrate via material jetting,
ink cured as it is applied
(1,4-dioxane evaporated)
Figure G-9. Process Flow Diagram for Printing Inks (3D)
This type of 3D printing ink is used in research labs to print biomedical products, such as
bioresorbable or biodegradable stents, implants, and scaffolds for tissue recovery. Making these
devices using this method allows for lower production costs and increased customization
(Ruggiero et al.. 2015; He et al.. 2013). Workers could be exposed while charging the ink to the
cartridges in the material printer, during the 3D printing process, and when disposing of spent
cartridges and syringes. If the ink is made on site, workers could be exposed during this step in
the process. ONUs include employees that work at the site where 1,4-dioxane is used in a
laboratory setting, but they do not directly handle the chemical and are therefore expected to
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have lower exposures. ONUs for laboratory use include supervisors, laboratory managers, and
laboratory workers that perform other tasks but do not directly handle 1,4-dioxane.
Number of Potentially Exposed Workers and Occupational Non-Users
EPA uses U.S. Census and BLS data for the NAICS code 339113, surgical appliance and
supplies manufacturing, and relevant SOC codes to estimate a total of 10,767 sites, 59,970
workers, and 20,430 ONUs, which corresponds to an estimated average of six workers and two
ONUs per site. The number of establishments within this NAICS code that print biomedical
products and the number of those establishments that use 1,4-dioxane-based 3D printing inks are
unknown. Therefore, EPA provided the total number of establishments and potentially exposed
workers and ONUs in this NAICS code as bounding estimates of the number of establishments
that use and the number of workers and ONUs that are potentially exposed to 1,4-dioxane-based
3D printing ink in biomedical product 3D printing. These bounding estimates could overestimate
the actual number of establishments and employees potentially exposed to 1,4-dioxane during
biomedical product 3D printing.
Worker and Occupational Non-User Exposure Assessment
A literature review and hazard assessment for material jetting identified exposure data for a
number of chemicals, including 1,4-dioxane, during additive manufacturing. A piece of tubing
was placed inside the unventilated 3D printer enclosure and attached to a 1.4-L Toxic Organic-
15 (TO-15) canister, which was placed directly adjacent to the printer. Air Method, Toxic
Organics-15 (TO-15) is an EPA method for sampling and analyzing volatile organic compounds
(VOCs) using specially prepared canisters and gas chromatography/mass spectrometry. The air
was sampled for an 8-hour period while the printer ran continuously. Since there was only a
single sample run, only a single data point is available. 1,4-Dioxane was present inside the
printer enclosure at a level of 27 ppb (0.097 mg/m3). The printer did not have local exhaust
ventilation and relied on general ventilation. 1,4-dioxane levels could be higher if more printers
were operating in the same area without local exhaust ventilation and could reach the NIOSH
REL of 1 ppm. However, Ryan and Hubbard (2016) indicated that the results were based on a
preliminary study and acknowledged that more statistically defensible sampling could be
performed to better understand exposures during this process.
EPA presented this value as an 8-hour TWA exposure for workers. This value is plausible, but
EPA cannot determine the statistical representativeness of the value given the small sample size.
Additionally, this sample was taken inside the 3D printing enclosure and likely represents a
higher exposure than what workers operating the 3D printer would typically experience. EPA
used this value to calculate acute and chronic inhalation exposures as per the equations in
Appendix G.2. Results of these calculations are summarized in Section 3.4.1.11.
Exposure data for ONUs were not available. EPA expects that ONU exposures are expected to
be lower than worker exposures, since ONUs do not typically directly handle the chemical. Only
inhalation exposures to vapors are expected, which could be less than worker exposures.
G.6.9 Dry Film Lubricant
The DOE's KCNSC indicated use of 1,4-dioxane as a carrier in the manufacture and application
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of a dry film lubricant. The KCNSC is one of eight sites that comprise the DOE's NNSA, which
manufacture 85% of non-nuclear components of nuclear weapons (KCNSC. 2018).
The facility stated that the dry film lubricant was used on non-nuclear components for nuclear
weapons. The manufacture of the dry film typically initiated by mixing 1,4-dioxane and other
solvents to create a solvent blend, which generally contained 16% 1,4-dioxane. The solvent
blend was used to manufacture concentrated dry film lubricant with a final 1,4-dioxane
concentration of 4% to 5%. Twelve half-pint containers of concentrated dry film lubricant were
produced in each run (DOE. 2018a).
Prior to spray application of the dry film lubricant, the facility mixed about 1.5 pints of pure 1,4-
dioxane with a half-pint container of concentrated dry film lubricant. The dry film lubricant and
dioxane mixture was sprayed in a vented paint booth either by hand or an automated system onto
the applicable parts. If the dry film lubricant needed to be removed from a part immediately after
spraying, it was cleaned in an ultrasonic bath filled with one gallon of dioxane for three to five
minutes and then rinsed in alcohol. The dioxane from the ultrasonic cleaner was disposed of in
chemical waste containers. After application, parts were cured in an oven for one hour during
which the 1,4-dioxane was evaporated and vented from the oven stack (DOE. 2018a).
Dry Film Manufacture
Dry Film Application
Send to
chemical
storage
location
1,4-dioxane
disposed of
in waste
containers
Package
into >2 pint
containers,
yield 12.
Receive
1,4-dioxane
in 1 gal
container
Receive
1,4-dioxane
in 1 gal
container
Clean spray
equipment with
1,4-dioxane
Cure dry film in oven.
1,4-dioxane vented
from oven stack
Manufacturedry
film concentrate.
Contains 4-5%
1,4-dioxane
Use 1 gallon of
1,4-dioxane in
ultrasoniccleaner
to remove dry film
1,4-dioxane blended
with other solvents.
Solution contains
16% 1,4-dioxane
Mix 1,4-dioxane with
concentrated dry
film in half gallon
containerin 3:1 ratio
Spray dry film and
1,4-dioxane mixture.
1,4-dioxane is vented
through fume hood
Figure G-10. Process Flow Diagram for Dry Film Lubricant in Nuclear Weapon
Applications
Process flow diagram for dry film lubricant at the KCNSC is shown in Figure G-10. Workers
activities included mixing, packaging, pouring, and spraying the dry film lubricant. If any part
needed to have the dry film lubricant removed soon after spraying, the worker could use a small
ultrasonic bath containing 1,4-dioxane. In addition, workers routinely cleaned the spray gun with
1,4-dioxane. KCNSC estimated that the dry film lubricant was manufactured six to eight times
per year in one-gallon batches and each batch could take about an hour to manufacture.
According to KCNSC, the dry film lubricant was applied, on average, once per week for a
minimum of two hours and a maximum of six hours. These estimates included the mixing,
application, and clean-up steps as described in Figure G-10. Factoring in holidays and down
time, KCNSC estimated dry film lubricant application to be about 48 times per year (DOE,
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2018a). It was assumed this process and these worker activities could be similar to other sites
that produce and use 1,4-dioxane-based dry film lubricants.
ONUs include employees that work at the site where 1,4-dioxane is used in dry film lubricants,
but they do not directly handle the chemical and are therefore expected to have lower exposures.
ONUs for dry film lubricant manufacture and use include supervisors, managers, and workers
that perform other tasks but do not directly handle 1,4-dioxane.
Number of Potentially Exposed Workers and Occupational Non-Users
KCNSC provided an estimate of ten exposed or potentially exposed workers at the facility. This
estimate includes three to four employees in the chemical material area where the dry film
lubricant is formulated and another five to six employees who work in the paint shop where the
dry film lubricant is spray applied ( 18b). KCNSC estimated that only one employee in
each area is exposed as a worker with the rest considered ONUs.
The KCNSC is one of eight facilities in DOE's NNSA (KCNSC. 2018). EPA believes that the
operations at different DOE/NNSA facilities vary substantially and that it is unlikely that the
operations at the KCNSC are similar to any of the other facilities. However, the KCNSC (2.018)
does not have additional information on operations at the other DOE facilities, so it is unknown
if other DOE NNSA sites use 1,4-dioxane in a similar way. As conservative, EPA assumed all
eight facilities could use 1,4-dioxane for this application and therefore, EPA assessed a total of
16 workers and 64 ONUs potentially exposed to 1,4-dioxane across all NNSA sites. This may be
an overestimate of workers and ONUs.
Worker and Occupational Non-User Exposure Assessment Methodology and Results
KCNSC provided the results of 20 area samples and 12 PBZ monitoring sample measurements to
EPA (DOE. 2018a). EPA used these data to assess inhalation exposures to 1,4-dioxane for this
condition of use. The PBZ samples included two full shift 8-hour TWA samples and five 8-hour
TWAs that are derived from same-day task-based TWA samples, for a total of seven 8-hour
TWA results, which are included below in Table G-23.
The 20 area samples KCNSC provided were gathered using a direct reading method. Direct
reading instruments provide real-time monitoring using calibrated devices that record multiple
single point readings. These readings do not provide time-weighted average results. Therefore,
EPA did not use the area measurements.
Table G-23. PBZ Task and TWA Monitoring Data for Dry Film Lubricant Manufacture
Process
Tsisk
Siiinplc
Collection
D.ile
Siiinple
Duration
(mill)
Siimple
Result
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Process
Tsisk
Siimplc
Collection
l):ilc
Siimplc
Duration
(mill)
Snmplc
Result
(in "/m4)
C:ilcul:ilcil S-
liour TWA
(mg/iir*)
material into cans for
packaging
Application
Mixing material, hand
spray application,
cleaning spray gun
2/11/2005
62
NP
0.11
Application
Material mixing, spray
application
9/14/2010
30
2.1
0.47
Application
Spray application
9/14/2010
17
3.2
Application
Equipment cleaning,
pour material into step
can
9/14/2010
62
1.6
Application
Material preparation
inside hood or closed
mixing
9/21/2010
60
1.8
0.68
Application
Spray application
9/21/2010
60
1.8
Application
All cleaning steps with
exception of pouring
material into
equipment reservoir;
opening step can (step
can is mixed VOCs)
9/21/2010
50
2.2
Application
Material preparation
inside hood or closed
mixing, pouring
material into
equipment container
inside the hood, and
spray application
10/11/2010
60
1.1
0.25
Application
All cleaning steps
10/11/2010
23
2.5
Application
Material preparation
and spray application
12/1/2011
395
np
1.9
Application
Material preparation,
spray application, and
cleanup
5/16/2013
425
np
0.97
SIP: not provided.
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EPA estimated the 95th percentile and 50th percentile of the calculated 8-hour TWA results to
assess the high-end and central tendency exposures, respectively. These values were used to
calculate acute and chronic inhalation exposures as per the equations in Appendix G.2. As
referenced in Section 3.4.1.12, KCNSC indicated that the facility manufactured the dry film
lubricant six to eight days per year and applied it about 48 days per year for a total exposure
frequency of 56 days per year. This value was used in place of the standard 250 days per year
assumption outlined in Appendix G.2. Results of these calculations are summarized in Section
3.4.1.12.
G.6.10 Disposal
Each of the conditions of use of 1,4-dioxane may generate waste streams of the chemical that are
collected and transported to third-party sites for disposal, treatment, or recycling. Industrial sites
that treat or dispose onsite wastes that they themselves generate are assessed in each condition of
use assessment in Sections 3.4.1.2 through 3.4.1.13. Wastes containing 1,4-dioxane that are
generated during a condition of use and sent to a third-party site for treatment, disposal, or
recycling could include the following:
• Wastewater: 1,4-Dioxane may be contained in wastewater discharged to POTW or
other, non-public treatment works for treatment. Industrial wastewater containing 1,4-
dioxane discharged to a POTW may be subject to EPA or authorized NPDES state
pretreatment programs. The assessment of wastewater discharges to POTWs and non-
public treatment works of 1,4-dioxane is included in each of the condition of use
assessments in Sections 3.4.1.2 through 3.4.1.13.
• Solid Wastes: Solid wastes are defined under RCRA as any material that is discarded by
being: abandoned; inherently waste-like; a discarded military munition; or recycled in
certain ways (certain instances of the generation and legitimate reclamation of secondary
materials are exempted as solid wastes under RCRA). Solid wastes may subsequently
meet RCRA's definition of hazardous waste by either being listed as a waste at 40 CFR §
261.30 to § 261.35 or by meeting waste-like characteristics as defined at 40 CFR §
261.20 to 261.24. Solid wastes that are hazardous wastes are regulated under the more
stringent requirements of Subtitle C of RCRA, whereas non-hazardous solid wastes are
regulated under the less stringent requirements of Subtitle D of RCRA.
o 1,4-Dioxane is listed as a hazardous waste on the U list at 40 CFR § 261.30. This
list designates specific unused commercial chemical products (CCP) that are pure
or a commercial grade formulation as hazardous waste. The hazardous waste code
for 1,4-dioxane is U108.
• Wastes Exempted as Solid Wastes under RCRA: Certain conditions of use of 1,4-
dioxane may generate wastes of 1,4-dioxane that are exempted as solid wastes under 40
CFR § 261.4(a). For example, the generation and legitimate reclamation of hazardous
secondary materials of 1,4-dioxane may be exempt as a solid waste.
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2016 TRI data lists off-site transfers of 1,4-dioxane to land disposal, wastewater treatment,
incineration, and recycling facilities (see Figure G-l 1). About 57% of off-site transfers were
incinerated, 42% sent to land disposal, and less than 1% is recycled off-site U.S. (U.S. EPA.
2016a).
Recycling
Hazardous Waste Hazardous Waste
Generation Transportation
*
Treatment
pn cu
Disposal
Figure G-ll. Typical Waste Disposal Process
Source: (J.S. EPA. 2017c)
Municipal Waste Incineration
Municipal waste combustors (MWCs) that recover energy are generally located at large facilities
comprising an enclosed tipping floor and a deep waste storage pit. Typical large MWCs may
range in capacity from 250 to over 1,000 tons per day. Workers do not generally directly handle
waste materials at the large facilities. Trucks may dump the waste directly into the pit, or waste
may be tipped to the floor and later pushed into the pit by a worker operating a front-end loader.
A large grapple from an overhead crane is used to grab waste from the pit and drop it into a
hopper, where hydraulic rams feed the material continuously into the combustion unit at a
controlled rate. The crane operator also uses the grapple to mix the waste within the pit, in order
to provide a fuel consistent in composition and heating value, and to pick out hazardous or
problematic waste.
Facilities burning refuse-derived fuel (RDF) conduct on-site sorting, shredding, and inspection of
the waste prior to incineration to recover recyclables and remove hazardous waste or other
unwanted materials. Sorting is usually an automated process that uses mechanical separation
methods, such as trommel screens, disk screens, and magnetic separators. Once processed, the
waste material could be transferred to a storage pit, or it could be conveyed directly to the hopper
for combustion.
Tipping floor operations may generate dust. Air from the enclosed tipping floor, however, is
continuously drawn into the combustion unit via one or more forced air fans to serve as the
primary combustion air and minimize odors. Dust and lint present in the air is typically captured
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in filters or other cleaning devices in order to prevent the clogging of steam coils, which are used
to heat the combustion air and help dry higher-moisture inputs (Kitto, 1992).
Hazardous Waste Incineration
Commercial scale hazardous waste incinerators are generally two-chamber units, a rotary kiln
followed by an afterburner, that accept both solid and liquid waste. Liquid wastes are pumped
through pipes and are fed to the unit through nozzles that atomize the liquid for optimal
combustion. Solids may be fed to the kiln as loose solids gravity fed to a hopper, or in drums or
containers using a conveyor (ETC. 2018; Heritage. 2018).
Incoming hazardous waste is usually received by truck or rail, and an inspection is required for
the waste received. Receiving areas for liquid waste generally consist of a docking area,
pumphouse, and storage facilities. For solids, conveyor devices are typically used to transport
incoming waste (ETC. 2018; Heritage. 2018).
Smaller scale units that burn municipal solid waste or hazardous waste (such as infectious and
hazardous waste incinerators at hospitals) could require more direct handling of the materials by
facility personnel. Units that are batch-loaded require the waste to be placed on the grate prior to
operation and may involve manually dumping waste from a container or shoveling waste from a
container onto the grate. See Figure G-12.
Emissions Stack
Heat Recovery
Wable Storage
Feed Preparation
Combustion
Gas Temperature j ^
Reduction i
Air Pollution Control L
Ash Handling
Disposal
Scrubber Water or
Ash Handling
Disposal
Figure G-12. Typical Industrial Incineration Process
Municipal Waste Landfill
Municipal solid waste landfills are discrete areas of land or excavated sites that receive
household wastes and other types of non-hazardous wastes (e.g. industrial and commercial solid
wastes). Standards and requirements for municipal waste landfills include location restrictions,
composite liner requirements, leachate collection and removal system, operating practices,
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groundwater monitoring requirements, closure-and post-closure care requirements, corrective
action provisions, and financial assurance. Non-hazardous solid wastes are regulated under
RCRA Subtitle D, but states may impose more stringent requirements.
Municipal solid wastes may be first unloaded at waste transfer stations for temporary storage,
prior to being transported to the landfill or other treatment or disposal facilities.
Hazardous Waste Landfill
Hazardous waste landfills are excavated or engineered sites specifically designed for the final
disposal of non-liquid hazardous wastes. Design standards for these landfills require double liner,
double leachate collection and removal systems, leak detection system, run on, runoff and wind
dispersal controls, and construction quality assurance program (U.S. EPA. 2018a). There are also
requirements for closure and post-closure of a landfill facility, such as the addition of a final
cover over the landfill and continued monitoring and maintenance. These standards and
requirements prevent potential contamination of groundwater and nearby surface water
resources. Hazardous waste landfills are regulated under Part 264/265, Subpart N.
Solvent Recovery
Waste solvents are generated when it becomes contaminated with suspended and dissolved
solids, organics, water, or other substances (l__S UjNO). Waste solvents could be restored
to a condition that permits reuse via solvent reclamation/recycling (U.S. EPA. 1980). The
recovery process could involve an initial vapor recovery (e.g., condensation, adsorption and
absorption) or mechanical separation (e.g., decanting, filtering, draining, setline and
centrifuging) step followed by distillation, purification and final packaging ( 3).
Worker activities include unloading of waste solvents and loading of reclaimed solvents. Figure
G-13 illustrates a typical solvent recovery process flow diagram (U.S. EPA. 1980).
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Storage
Tank
Vent
Reclaimed
Solvent
~ Incinerator Stack
* Fugitive Emissions
Storage
and
Handling
Storage
and
Handling
Waste
Disposal
Initial
Treatment
Figure G-13. General Process Flow Diagram for Solvent Recovery Processes
U.S. Source: (U.S. EPA. 1980)
Number of Potentially Exposed Workers and Occupational Non-Users
The total number of sites that treat and dispose wastes containing 1,4-dioxane is unknown. For
reporting year 2016, five hazardous waste treatment and disposal facilities, one solid waste
combustor and incinerator, and three cement plants report released of 1,4-dioxane to the TRI
(U.S. EPA. 2016a). Table G-24 presented the estimated number of workers and ONUs at these
facilities based on EPA's analysis of typical employment in those industry sectors. It is possible
that additional hazardous waste treatment facilities treated and disposed 1,4-dioxane but did not
meet the TRI reporting threshold for reporting year 2016. Therefore, the total number of workers
and ONUs potentially exposed to 1,4-dioxane could be greater than 124 workers and 45 ONUs.
Table G-24. NAICS Codes with Wor
ters and ONUs
'or Disposal
NAICS
Code
NAICS Description
Total
Sites
Total
Workers
Total
ONUs
Number of
Sites that
Reported 1,4-
Dioxane
Workers
Potentially
Exposed to
1,4-Dioxane
ONUs
Potentially
Exposed to
1,4-Dioxane
562211
Hazardous Waste
Treatment and Disposal
892
8,054
4,836
5
45
27
562213
Solid Waste Combustors
and Incinerators
102
1,356
814
1
13
8
562219
Other Nonhazardous
Waste Treatment and
Disposal
283
790
474
0
0
0
562212
Solid Waste Landfill
1,311
4,540
2,726
0
0
0
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NAICS
Cock'
NAICS Description
Toial
Silcs
Tolal
\\ or Iters
lolal
OM s
Number ol°
Silos llial
Kcporu-ri 1.4-
l)io\ane
\\ or Iters
Polcnliall.t
r.xposcd lo
l.4-l)io\anc
ONI s
Poion 1 ia ll>
I'.xposed lo
l.4-l)io\ane
562213
Solid Waste Combustors
and Incinerators
102
1,356
814
0
0
0
327310
Cement Manufacturing
233
5,080
781
3
65
10
Grand Totals
2,923
21,176
10,445
9
124
45
Worker and Occupational Non-User Activities
At waste disposal sites, workers are potentially exposed via dermal contact with wastes
containing 1,4-dioxane or via inhalation of 1,4-dioxane vapor. Depending on the concentration
of 1,4-dioxane in the waste stream, the route and level of exposure could be similar to that
associated with container unloading activities. The assessments of worker exposure from
chemical unloading activities are in the following sections.
Municipal Waste Incineration
At municipal waste incineration facilities, there could be one or more technicians present on the
tipping floor to oversee operations, direct trucks, inspect incoming waste, or perform other tasks
as warranted by individual facility practices. These workers may wear protective gear such as
gloves, safety glasses, or dust masks. Specific worker protocols are largely up to individual
companies, although state or local regulations may require certain worker safety standards be
met. Federal operator training requirements pertain more to the operation of the regulated
combustion unit rather than operator health and safety.
Workers are potentially exposed via inhalation to vapors while working on the tipping floor.
Potentially-exposed workers include workers stationed on the tipping floor, including front-end
loader and crane operators, as well as truck drivers. The potential for dermal exposures is
minimized by the use of trucks and cranes to handle the wastes.
Hazardous Waste Incineration
More information is needed to determine the potential for worker exposures during hazardous
waste incineration and any requirements for personal protective equipment. There is likely a
greater potential for exposures while operating smaller scale incinerators that involve more direct
handling of the wastes by the worker.
Municipal and Hazardous Waste Landfill
At landfills, typical worker activities may include operating refuse vehicles to weigh and unload
the waste materials, operating bulldozers to spread and compact wastes, and monitoring,
inspecting, and surveying and landfill site (CalRecvcle. 2018).
Worker and Occupational Non-User Exposure Assessment
Bulk Shipments of Liquid Hazardous Waste
It is assumed that the 1,4-dioxane wastes that are generated, transported, and treated or disposed
as hazardous waste are done so via bulk liquid shipments. For example, a facility that uses 1,4-
dioxane as a processing aid could generate and store the waste processing aid as relatively pure
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1,4-dioxane and have it shipped to hazardous waste treatment, storage and disposal facilities
(TSDFs).
Exposure data for this scenario are not known; therefore, the EPA AP-42 Loading Model and the
EPA Mass Balance Inhalation Model were used to estimate inhalation exposures. These models
use default parameter values and assumptions to provide screening level assessments of
inhalation exposures for container loading and unloading operations. EPA used a Monte Carlo
simulation to vary the saturation factor (f), ventilation rate (Q), mixing factor (k), and working
years (WY). See Appendix G.4 for more information about the Monte Carlo simulation.
It is assumed that any exposures related to on-site waste treatment and disposal are addressed in
the assessments for those uses in this report; therefore, this section assesses exposures to workers
for wastes transferred from the use site to an off-site waste treatment and disposal facility. Table
G-25 lists the off-site waste transfers reported in the 2016 TRI. EPA used the total value reported
in this table as the PV for this assessment. It is assumed that the waste chemical is typically
transported to the treatment and disposal sites in 55-gallon drums that estimated 2,427 drums per
year. The 2016 TRI reported nine waste treatment and disposal sites, resulting in an average of
270 drums per site per year. Facilities are only required to report to TRI if the facility has 10 or
more full-time employees, is included in an applicable NAICS code, and manufactures,
processes, or uses the chemical in quantities greater than a certain threshold (25,000 lb/yr for the
manufacture or processing of the chemical, or 10,000 lb/yr for otherwise use of the chemical).
Some sites that use 1,4-dioxane in this Industrial Uses category may not meet these
qualifications and therefore are not required to report to TRI.
Table G-25. 2016 TRI Off-Site Transfers for 1,4-Dioxane
Oil-She 1 rnnsfi'r
lolal Ou;iiilil> Ki'porli'd (II))
Land Disposal
486,124
Incineration
655,309
Recycled
4,790
Other
1,139
Total
1,147,362
U.S. Source: (U.S. EPA. 2016a-)
EPA assumed that one drum is unloaded per site per day. Assuming a default unloading rate of
20 drums per hour, it would take an estimated 3.2 minutes (0.054 hours) for each site to a single
drum each day. EPA estimated this exposure using the equations and parameters in Appendix
G.2 and averaged the 3.2-minute exposures over an 8-hour shift, assuming the workers are
exposed to 1,4-dioxane while unloading and then not exposed for the rest of the shift. The central
tendency and high-end 8-hour TWA exposures for unloading drums are 1.15 and 4.09 mg/m3,
respectively. EPA also presents the 3.2-minute exposures as central tendency and high-end short-
term exposures EPA used these values to calculate acute and chronic inhalation exposures in the
Monte Carlo simulation, varying working years (WY), using the equations in Appendix G.2.
Results of these calculations are summarized in Section 3.4.1.13.
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Modeling was not performed to estimate exposures for ONUs. ONU exposures would be lower
than worker exposures, since ONUs do not typically directly handle the chemical. Only
inhalation exposures to vapors are expected, which would be less than worker exposures.
Municipal Solid Wastes
Certain commercial conditions of use of 1,4-dioxane could generate solid wastes that might be
sent to municipal waste combustors or landfills. For example, spent spray polyurethane foam
insulation containers or spray foam trimmings containing residual 1,4-dioxane used by
contractors and technicians could be disposed as household hazardous waste as it is exempted as
a hazardous waste under RCRA. While some municipalities may have collections of household
hazardous wastes to prevent the comingling of household hazardous wastes with municipal waste
streams, some users could inappropriately dispose of household hazardous wastes in the
municipal waste stream.
EPA was not able to quantitatively assess worker or ONU exposures to 1,4-dioxane within
municipal solid waste streams. The quantities of 1,4-dioxane could be diluted among the
comingled municipal solid waste stream.
G.7 Dermal Exposure Assessment Method
This proposed method was developed through review of relevant literature and consideration of
existing exposure models, such as EPA models and the European Centre for Ecotoxicology and
Toxicology of Chemicals Targeted Risk Assessment (ECETOC TRA).
G.7.1 Incorporating the Effects of Evaporation
Current EPA dermal models do not incorporate the evaporation of material from the dermis. The
dermal potential dose rate, Dexp (mg/day), is calculated as (U.S. EPA. 2013b):
Equation G-13
Dexp — S x Qu x Yderm x FT
Where:
5 is the surface area of contact (cm2)
Qu is the quantity remaining on the skin (mg/cm2-event)
Yderm's the weight fraction of the chemical of interest in the liquid (0 < Yderm < 1)
FT is the frequency of events (integer number per day).
Here Qu does not represent the quantity remaining after evaporation, but represents the quantity
remaining after the bulk liquid has fallen from the hand that cannot be removed by wiping the
skin (e.g., the film that remains on the skin).
One way to account for evaporation of a volatile solvent would be to add a multiplicative factor
to the EPA model to represent the proportion of chemical that remains on the skin after
evaporation,/abs (0
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Equation G-14
Dexp — S X [ Qu X f abs) X Yderm X FT
This approach simply removes the evaporated mass from the calculation of dermal uptake.
Evaporation is not instantaneous, but the EPA model already has a simplified representation of
the kinetics of dermal uptake.
G.7.2 Calculation of fabs
Kasting and Miller (2.006) developed a diffusion model to describe the absorption of volatile
compounds applied to the skin. As of part of the model, Kasting and Miller define a ratio of the
liquid evaporation to absorption, %. They derive the following definition of % (which is
dimensionless) at steady-state:
Equation G-15
P MW3A
X = 3.4 X 10~3u° 78 „
|/0.76c
Oct
Where:
u is the air velocity (m/s)
Koct is the octanol:water partition coefficient
MW is the molecular weight
5^ is the water solubility (|ag/cm3)
Pvp is the vapor pressure (torr)
Chemicals for which % » 1 will largely evaporate from the skin surface, while chemicals for
which %« I will be largely absorbed; % = 1 represents a balance between evaporation and
absorption. Equation G-15 is applicable to chemicals having a log octanol/water partition
coefficient less than or equal to three (Log Kow = -0.27)18. The equations that describe the
fraction of the initial mass that is absorbed (or evaporated) are rather complex (Equations 20 and
21 of Kasting and Miller, (2006)) but can be solved.
Small Doses (Case 1: M0 < Msat)
In the small dose scenario, the initial dose (Mo) is less than that required to saturate the upper
layers of the stratum corneum (Mo < Msat), and the chemical is assumed to evaporate from the
skin surface at a rate proportional to its local concentration.
For this scenario, Frasch (2.012) calculated the fraction of applied mass that is absorbed, based on
the infinite limit of time (i.e. infinite amount of time available for absorption after exposure):
18 For simplification, Kasting and Miller (2006) does not consider the resistance of viable tissue layers underlying
the stratum corneum, and the analysis is applicable to hydrophilic-to-moderately lipophilic chemicals. For small
molecules, this limitation is equivalent to restricting the analysis to compounds where Log Kow < 3 (in the current
assessment Log Kow = -0.27).
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Equation G-16
mabs(oo) 2+fx
Tabs ~ M0 ~ 2 + 2x
Where:
Mabs is the mass absorbed
M o is the initial mass applied
f is the relative depth of penetration in the stratum corneum (f= 0.1 can be assumed)
X is as previously defined
Note the simple algebraic solution in Equation G-16 provides a theoretical framework for the
total mass that is systemically absorbed after exposure to a small finite dose (mass/area) of
chemical, which depends on the relative rates of evaporation, permeation, and the initial load. At
"infinite time", the applied dose is either absorbed or evaporated (Frasch. 2012). The finite dose
is a good model for splash-type exposure in the workplace (Frasch. and Bunge. 2015).
The fraction of the applied mass that evaporates is simply the complement of that absorbed:
Equation G-17
^•evapC00) , _ _ 2x ~ fX
jjYq - - Jabs - 2 + 2x
Where:
mevap is the mass evaporated
The fraction absorbed can also be represented as a function of dimensionless time x (Dt/h2), as
shown in Equation G-18.
Equation G-18
2tn ( X +K \ (COS( 1 -f)kn~ COSln\
™-abs v 1 -a / X'^ + K \ ft
fabs =^T~ = 2 > T^-e T) — —2 ¦ - f.
n=l 71 \X + + X/ \ f
where the eigenvalues 2n are the positive roots of the equation:
Equation G-19
2n ¦ cot(An) + x = 0
Equation G-18 and Equation G-19 must be solved analytically. It should be noted that the
dimensionless time x is not a representation of exposure duration for a work activity; rather, it
represents the amount of time available for absorption after the initial exposure dose is applied.
Since most dermal risk assessments are typically more concerned with the quantity absorbed,
rather than the time course of absorption, the simple algebraic solution is recommended over the
analytical solution.
Large Doses (Case 2: MO > Msat)
For large doses (Mo > Msat), the chemical saturates the upper layers of the stratum corneum, and
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any remaining amount forms a residual layer (or pool) on top of the skin. The pool acts as a
reservoir to replenish the top layers of the membrane as the chemical permeates into the lower
layer. In this case, absorption and evaporation approach steady-state values as the dose is
increased, similar to an infinite dose scenario.
The steady-state fraction absorbed can be approximated by Equation G-20:
Equation G-20
/afts(00) = J+l
Table G-26 presents the estimated absorbed fraction calculated using the steady-state
approximation for large doses (Equation G-20) for 1,4-dioxane.
Table G-26. Estimated Fraction Evaporated and Absorbed (fabs) using Equation G-20
Chemical Name
1,4-Dioxane
CASRN
123-91-1
Molecular Formula
C4H8O2
Molecular Weight (g/mol)
88.1
Pvp (torr)
40
Universal gas constant, R (L*atm/K*mol)
0.0821
Temperature, T (K)
303
Log Kow
-0.27
Koct
0.5
Sw (g/L)
800
Sw (|ig/cm3)
800,000
Industrial Setting
u (m/s)a
0.1674
Evaporative Flux, y
0.28
Fraction Evaporated
0.22
Fraction Absorbed
0.78
Commercial Setting
u (m/s)a
0.0878
Evaporative Flux, y
0.17
Fraction Evaporated
0.14
Fraction Absorbed
0.86
a EPA used air speeds from Baldwin and Maynard (1998): the 50th percentile of industrial
occupational environments of 16.74 cm/s is used for industrial settings and the 50th percentile
of commercial occupational environments of 8.78 cm/s is used for commercial settings.
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G.7.3 Potential for Occlusion
Occlusion refers to skin covered directly or indirectly by impermeable films or substances.
Chemical protective gloves are one of the most widely used forms of PPE intended to prevent
skin exposure to chemicals. Gloves can prevent the evaporation of volatile chemicals from the
skin. Chemicals trapped in the glove may be broadly distributed over the skin (increasing S in
Equation G-13), or if not distributed within the glove, the chemical mass concentration on the
skin at the site of contamination may be maintained for prolonged periods of time (increasing Qu
in Equation G-13). Conceptually, occlusion is similar to the "infinite dose" study design used in
in vitro and ex vivo dermal penetration studies, in which the dermis is exposed to a large,
continuous reservoir of chemical.
The protective measures could produce negative events due to the nature of occlusion, which
often causes stratum corneum hyper-hydration and reduces the protective barrier properties of
the skin. Many gloves do not resist the penetration of low molecular weight chemicals: those
chemicals may enter the glove and become trapped on the skin under occlusion for many hours.
Breakthrough times for glove materials are often underestimates of the true breakthrough times,
because the measurements do not consider increased temperature and flexing of the material
during use, which is not accounted for in tests to determine breakthrough times. Occlusion by
gloves raises skin temperature and hydration leading to a reduction in its natural barrier
properties. The impact of occlusion on dermal uptake is complex: continuous contact with the
chemical may degrade skin tissues, increasing the rate of uptake, but continuous contact may
also saturate the skin, slowing uptake (Dancik et at.. 2015). Wearing gloves which are internally
contaminated can lead to increased systemic absorption due to increased area of contact and
reduced skin barrier properties, and repeated skin contact with chemicals can give higher than
expected exposure if evaporation of the carrier occurs and the concentration in contact with the
skin increases. These phenomena are dependent upon the chemical, the conditions of use and
environmental conditions. It is probably not feasible to incorporate these sources of variability in
a screening-level population model of dermal exposure without chemical-specific studies.
EPA does not expect occlusion scenarios to be a reasonable occurrence for all conditions of use.
Specifically, occlusion is not expected at sites using chemicals in closed systems where the only
potential of dermal exposure is during the connecting/disconnecting of hoses used for
unloading/loading of bulk containers (e.g., tank trucks or rail cars) or while collecting quality
control samples including manufacturing sites, repackaging sites, sites processing the chemical
as a reactant, formulation sites, and other similar industrial sites. Occlusion is also not expected
to occur at highly controlled sites, such as pharmaceuticals manufacturing sites, where, due to
purity requirements, the use of engineering controls is expected to limit potential dermal
exposures. EPA also does not expect occlusion at sites where contact with bulk liquid chemical
is not expected such as research laboratories where workers are only expected to handle the
small quantities of the chemical in controlled environments and not the actual bulk liquid
chemical.
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G.7.4 Incorporating Glove Protection
Data about the frequency of effective glove use - that is, the proper use of effective gloves - is
very limited in industrial settings. Initial literature review suggests that there is unlikely to be
sufficient data to justify a specific probability distribution for effective glove use for a chemical
or industry. Instead, the impact of effective glove use should be explored by considering
different percentages of effectiveness (e.g., 25% vs. 50% effectiveness).
Gloves only offer barrier protection until the chemical breaks through the glove material. Using a
conceptual model, Cherrie et al. (2004) proposed a glove workplace protection factor - the ratio
of estimated uptake through the hands without gloves to the estimated uptake though the hands
while wearing gloves: this protection factor is driven by flux, and thus varies with time. The
ECETOC TRA model represents the protection factor of gloves as a fixed, assigned protection
factor equal to 5, 10, or 20 (Marquart et al.. 2017V Where, similar to the APR for respiratory
protection, the inverse of the protection factor is the fraction of the chemical that penetrates the
glove.
The protection afforded by gloves can be incorporated into the EPA model (Equation G-13) by
modification of Qu with a protection factor, PF (unitless, PF > 1):
Equation G-21
Dexp = s x x Yderm x FT
Given the limited state of knowledge about the protection afforded by gloves in the workplace, it
is reasonable to utilize the PF values of the ECETOC TRA model (Marquart et al.. 2.017). rather
than attempt to derive new values. Table G-27 presents the PF values from ECETOC TRA
model (version 3). In the exposure data used to evaluate the ECETOC TRA model, Marquart et
al- (2017) reported that the observed glove protection factor was 34, compared to PF values of 5
or 10 used in the model.
Table G-27. Exposure Control Efficiencies and Protection Factors for Different Dermal
Protection Strategies from ECETOC TRA v3
Dcrniiil Prolcclion ( h;iics
AflVvk'd I sit
(.roup
Indiciilod
r.fl'ick'iio (Vii)
Prolciiion
1 iicloi-. PI
a. Any glove / gauntlet without permeation data and
without employee training
Both industrial and
professional users
0
1
b. Gloves with available permeation data indicating that
the material of construction offers good protection for
the substance
80
5
c. Chemically resistant gloves (i.e., as b above) with
"basic" employee training
90
10
d. Chemically resistant gloves in combination with
specific activity training (e.g., procedure for glove
removal and disposal) for tasks where dermal exposure
can be expected to occur
Industrial users only
95
20
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G.7.5 Proposed Dermal Dose Equation
Accounting for all parameters above, the proposed, overall equation for estimating dermal
exposure is:
Equation G-22
( Qu x fabs)
Dexp = S x x Yderm x FT
EPA proposes to present exposure estimates for the following deterministic dermal exposure
scenarios:
• Dermal exposure without the use of protective gloves (Equation G-22, PF = 1)
• Dermal exposure with the use of protective gloves (Equation G-22, PF = 5)
• Dermal exposure with the use of protective gloves and employee training (Equation G-22,
PF = 20 for industrial users and PF = 10 for professional users)
•
EPA assumes the following parameter values for Equation G-22 in addition to the parameter
values presented in Table G-26:
• 5, the surface area of contact: 1,070 cm2, representing the total surface area of both
hands.
• Qu, the quantity remaining on the skin: 2.1 mg/cm2-event. This is the high-end default
value used in the EPA dermal models ( 013b).
• Yderm, the weight fraction of the chemical of interest in the liquid: EPA will assess a
unique value of this parameter for each occupational scenario or group of similar
occupational scenarios.
• FT, the frequency of events: 1 event per day
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Appendix H HUMAN HEALTH HAZARDS
n=7
"Key trusted
references (n = 17 )
Excluded References (n = 2655)
Data Search Results (n = 2,679 )
Excluded: Ref that are
unacceptable based on
evaluation criteria (n = 2)
Data Extraction;Data Integration (n = 22)
Data Evaluation (n = 24)
Data Screening (r = 2.662
*Any relevant studies from prior assessments that were identified as potentially relevant forTSCA assessment
needs bypassed the data screening step and moved directly to the data evaluation step (e.g. key/supporting
studies from IRIS assessments, ATSDR assessments, ECHA dossiers, etc.).
Figure H-l. Literature Flow Diagram for Human Health Hazard
H.l Hazard and Data Quality Summary Tables by study duration/endpoint
H.l.l Hazard and Data Evaluation Summary for Human Studies
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Target Organ/
System
Outcome/ Endpoint
Study Population
Exposure
Results
Reference
Data Quality
Evaluation
ADME/PBPK
Half-lives of 1,4-dioxane
determined in plasma and urine
4 Caucasian males, ages 40-
49, scientists and
businessmen at Dow
Chemical, Freeport, Texas
Subjects exposed to 50ppm
1,4-dioxane in air for 6 hrs
Half-life determined for
1,4-D in plasma, statistical
significance relative to an
unexposed population is not
applicable
(Young et
a )
Medium
Cancer
Breast cancer incidence
Participants in the California
Teacher Study cohort, 1995-
2011, (n=l 12,378 women)
National-Scale Air Toxics
Assessment Modeled air
concentrations
No significant association
between breast cancer
incidence and 1,4-D
exposure
(Garcia et
High
H.1.2 Hazard and Data Quality Evaluation Summary for Acute and Short-Term Studies
The acute, short-term table focuses on a single IS
OAEL or LOAEL per study wit
i footnotes related to other effects measured/observed.
Target Organ/
System1
Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations"
Duration
Effect Dose or
Concentration
(NOAEL,
LOAEL, LCso)
(mg/m3 or
mg/kg-bw/day)
(Sex)
Effect
Reference
Data
Quality
Evaluation
Hepatic
Acute
Rat, CD-I, M
(n= unknown
treated and
controls)
Inhalation,
vapor,
whole-
body
3603 or 7207
mg/m3 (1000 or
2000 ppm)
4 hours
LOAEC = 3603
mg/m3 (M)
Increased
serum liver
enzymes
(Drew et
¦A 8)
Medium
Respiratory b-0
Acute
Rat,
F344/DuCrl
(n =
10/sex/conc.)
Inhalation,
vapor,
whole-
body
0, 429, 1013,
2875, 7920,
21,630 mg/m3 (0,
119, 281,798,
2198, 6002 ppm)
6 hours
NOAEC = 2875
mg/m3
Vacuolar
change in
olfactory and
respiratory
epithelium (2
rats at two days
but not 2 weeks
after exposure)
(Mattie et
al. 2012.)
Medium
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Target Organ/
System1
Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations3
Duration
Effect Dose or
Concentration
(NOAEL,
LOAEL, LCso)
(mg/m3 or
mg/kg-bw/day)
(Sex)
Effect
Reference
Data
Quality
Evaluation
Hepatic, renal,
respiratory b c
Short-term
Rat, Fischer
344 rats (n=
64 treated and
controls)
Inhalation,
vapor,
whole-
body
0, 378, 5599,
11,690 mg/m3 (0,
105, 1554, 3245
ppm)
6h/d,
5 d/wk for
2 wk,
assessed
Id and
2wk post
exposure
LOAEC = 378
mg/m3
Lesions in nasal
cavity, liver,
and kidney;
hepatic single
cell necrosis
(Mattie et
at- 20121
Medium
Neurological d
Short-term
Rat, CFE,e
F (n = 8)
Inhalation,
vapor,
whole-
body
5405, 10,810,
21,620 mg/m3
(1500, 3000, 6000
ppm)
4 hrs/day,
5 days a
week for
10
exposures
NOAEC = 5405
mg/m3
Decreased
avoidance
response
(Goldberg
et al„
!)
Medium
a Concentrations in ppm were converted to mg/m3 using the following equation: ppm*mw (88. l)/24.45. 24.45 is the gas constant at 760 mm Hg (101 kPa) atmospheric pressure
and at 25 °C.
b The neurological/behavioral endpoints from these studies received an unacceptable rating and therefore, were not included in the above table and body weight changes
not reported.
0 No effects on hepatic, renal, hematology, clinical chemistry endpoints.
d Body weight changes were observed at the highest concentration.
e Presumed to be Sprague-Dawley rats.
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H.1.3 Hazard and Data Evaluation Summary for the Developmental Toxicity Study
Target Organ/
System
Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Effect Dose or
Concentration
(NOAEL,
LOAEL, LCso)
(mg/m3 or
mg/kg-bw/day)
(Sex)
Effect
Reference
Data
Quality
Evaluation
Reproductive
toxicity (adverse
effects on
development of
the offspring)
Developm
ental
Rat, Sprague
Dawley, F
(n=18-
20/group)
Oral,
gavage
0, 250, 500 or
1000 mg/kg-
bw/day
GDs 6-15
NOAEL=500
mg/kg-bw/day
(F)
LOAEL= 1,000
mg/kg-bw/day
(F)
Delayed
ossification of
the sternebrae
and reduced
fetal body
weight
(Giavini et
1)
High
H.1.4 Hazard and Data Evaluation Summary for Subchronic and Chronic Non-Cancer Studies
The endpoints in the tables below focus on hepatic, renal and respiratory endpoints, the critical endpoints for 1,4-dioxane. NOAELs (or
LOAELs) are provided for each critical endpoint; BMD modeling has also been conducted for some studies (as presented elsewhere).
Although additional endpoints may have been reported or examined in these studies, they are observed less often or are less sensitive and
have not been included in this table.
INHALATION
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Target Organ/
System
Study Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations"
Duration
Effect Dose or
Concentration
(NOAEL,
LOAEL, LCso)
(mg/m3 or
mg/kg-bw/day)
(Sex)
Effect
Reference
Data Quality
Evaluation
Respiratory
Subchronic
Rat,
F344/DuCij,
M/F
(n=20/group)
Inhalation,
vapor,
whole
body
0, 360, 721, 1441,
2883, 5765,
11,530 or 23,060
mg/m3
(0, 100, 200, 400,
800, 1600, 3200
or 6400 ppm)
6
hours/day,
5
days/week
for 13
weeks
NOAEC= 360
(M/F) mg/m3
Increased
relative lung
weight
(Kasai et
al.. 2008)
High
Respiratory
Chronic
Rat,
F344/DuCij,
M
(n=50/group)
Inhalation,
vapor,
whole
body
0, 180, 900 or
4500 mg/m3
(0, 50, 250 or
1250 ppm)
6
hours/day,
5
days/week
for 2 years
LOAEC= 180
mg/m3 (M)
Nasal cavity:
atrophy and
metaplasia in
olfactory
epithelium
(Kasai et
High
Hepatic
Subchronic
Rat,
F344/DuCij,
M/F
(n=20/group)
Inhalation,
vapor,
whole
body
0, 360, 721, 1441,
2883, 5765,
11,530 or 23,060
mg/m3
(0, 100, 200, 400,
800, 1600, 3200
or 6400 ppm)
6
hours/day,
5
days/week
for 13
weeks
NOAEC (F) =
2883
mg/m3
Liver focib
(Kasai et
al. 2008)
High
Hepatic
Chronic
Rat,
F344/DuCij,
M
(n=50/group)
Inhalation,
vapor,
whole
body
0, 180, 900 or
4500 mg/m3
(0, 50, 250 or
1250 ppm)
6
hours/day,
5
days/week
for 2 years
NOAEC = 901
mg/m3
Liver foci,
spongiosis
hepatis,
necrosis,
increased
enzymes and
liver weight
(Kasai et
al.. 2009)
High
Page 299 of 407
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Target Organ/
System
Study Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations"
Duration
Effect Dose or
Concentration
(NOAEL,
LOAEL, LCso)
(mg/m3 or
mg/kg-bw/day)
(Sex)
Effect
Reference
Data Quality
Evaluation
Renal
Subchronic
Rat,
F344/DuCij,
M/F
(n=20/group)
Inhalation,
vapor,
whole
body
0, 360, 721, 1441,
2883, 5765,
11,530 or 23,060
mg/m3
(0, 100, 200, 400,
800, 1600, 3200
or 6400 ppm)
6
hours/day,
5
days/week
for 13
weeks
NOAEC (F) =
5765
mg/m3
Hydropic
change in
proximal
tubule
(Kasai et
at.. 2008)
High
Renal
Chronic
Rat,
F344/DuCr j,
M
(n=50/group)
Inhalation,
vapor,
whole
body
0, 180, 900 or
4500 mg/m3
(0, 50, 250 or
1250 ppm)
6
hours/day,
5
days/week
for 2 years
NOAEC = 901
mg/m3 0
hydropic
change and
decreased
urine pH
(Kasai et
al. 2.009)
High
a Concentrations in ppm were converted to mg/m3 using the following equation: ppm*mw (88. l)/24.45. 24.45 is the gas constant at 760 mm Hg (101 kPa) atmospheric pressure
and at 25 °C.
b Liver weights were increased at > 2912 mg/mg3 (800 ppm); single cell necrosis, centrilobular swelling and increased liver enzymes seen at 11,650 mg/m3
0 Nuclear enlargement of proximal tubule observed at 910 mg/m3
ORAL
Target Organ/
System1
Study
Type
Species/
Strain/Sex
(Number/
group)2
Exposure
Route
Doses/
Concentrations3
Duration4
Effect Dose or
Concentration
(NOAEL,
LOAEL,
LCso)5 (mg/m3
or mg/kg-
bw/day) (Sex)
Effect6
Reference7
Data Quality
Evaluation8
Hepatic
Chronic
Rat, Wistar, M
(n=26 treated, 9
controls)
Oral,
drinking
water
0 or 640 mg/kg-
bw/day
63 weeks
LOAEL= 640
mg/kg-bw/day
(M)
Hepatocytes
with enlarged
hyperchromic
nuclei
(Argus et
al. 1965)
Medium
Page 300 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Target Organ/
System1
Study
Type
Species/
Strain/Sex
(Number/
group)2
Exposure
Route
Doses/
Concentrations3
Duration4
Effect Dose or
Concentration
(NOAEL,
LOAEL,
LCso)5 (mg/m3
or mg/kg-
bw/day) (Sex)
Effect6
Reference7
Data Quality
Evaluation8
Hepatic
Chronic
Rat, Sprague
Dawley, M
(n=30/group)
Oral,
drinking
water
0, 430, 574, 803
or 1032 mg/kg-
bw/day
13 months
LOAEL= 430
mg/kg-bw/day
(M)
Hepatocyto-
megaly
(Argus et
I 3)
Low
Hepatic
Chronic
Rat, Sherman,
M/F
(n=120/group)
Oral,
drinking
water
0, 9.6, 94 or 1015
mg/kg-bw/day
(M);
0, 19, 148 or 1599
mg/kg-bw/day (F)
2 years
NOAF.I ,= 9.6
mg/kg-bw/day
(M)
LOAEL = 94
mg/kg-bw/day
(M)
Degeneration
and necrosis
of
hepatocytes
(Kociba
et at.,
V 1)
High
Hepatic
Sub
chronic
Rat,
F344/DuCij,
M/F
(n=20/group)
Oral,
drinking
water
0, 52, 126, 274,
657 or 1554
mg/kg-bw/day
(M);
0, 83, 185, 427,
756 or 1614
mg/kg-bw/day (F)
13 weeks
NOAEL= 52
mg/kg-bw/day
(M)
LOAEL= 126
mg/kg-bw/day
(M)
Hepatocyte
swelling
(Kano et
al.. 2008)
Medium
Hepatic
Chronic
Rat,
F344/DuCij,
M/F
(n=100/group)
Oral,
drinking
water
0, 11, 55 or 274
mg/kg-bw/day
(M);
0, 18, 83 or 429
mg/kg-bw/day (F)
2 years
NOAF.I .= 11
mg/kg-bw/day
(M)
LOAEL= 55
mg/kg-bw/day
(M)
Mixed cell
liver foci
(Kano et
al. 2.009;
3)
High/High
Hepatic
Chronic
Rat,
F344/DuCij,
M/F
(n=100/group)
Oral,
drinking
water
0, 11, 55 or 274
mg/kg-bw/day
(M);
0, 18, 83 or 429
mg/kg-bw/day (F)
2 years
NOAEL= 55
mg/kg-bw/day
(M)
LOAEL= 274
mg/kg-bw/day
(M)
Increases in
serum liver
enzymes
(GOT, GPT,
LDH and
ALP)
(Kano et
al.. 2009;
jbrc4
i)
High/High
Hepatic
Chronic
Mouse,
Crj:BDFl,M/F
(n=100/group)
Oral,
drinking
water
0, 49, 191 or 677
mg/kg-bw/day
(M);
0, 66, 278 or 964
mg/kg-bw/day (F)
2 years
NOAEL= 49
mg/kg-bw/day
(M)
LOAEL= 191
mg/kg-bw/day
(M)
Increases in
serum liver
enzymes
(GOT, GPT,
LDH and
ALP)
(Kano et
al. 2009;
3)
High/High
Page 301 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Target Organ/
System1
Study
Type
Species/
Strain/Sex
(Number/
group)2
Exposure
Route
Doses/
Concentrations3
Duration4
Effect Dose or
Concentration
(NOAEL,
LOAEL,
LCso)5 (mg/m3
or mg/kg-
bw/day) (Sex)
Effect6
Reference7
Data Quality
Evaluation8
Renal
Chronic
Rat, Wistar, M
(n=26 treated, 9
controls)
Oral,
drinking
water
0 or 640 mg/kg-
bw/day
63 weeks
LOAEL= 640
mg/kg-bw/day
(M)
Glomerulo-
nephritis
(Argus et
al. 1965)
Medium
Renal
Chronic
Rat, Sprague
Dawley, M
(n=30/group)
Oral,
drinking
water
0, 430, 574, 803
or 1032 mg/kg-
bw/day
13 months
LOAEL= 430
mg/kg-bw/day
(M)
Glomerulo-
nephritis
(Argus et
al. 1973)
Low
Renal
Chronic
Rat, Sherman,
M/F
(n=120/group)
Oral,
drinking
water
0, 9.6, 94 or 1015
mg/kg-bw/day
(M);
0, 19, 148 or 1599
mg/kg-bw/day (F)
2 years
NOAEL= 9.6
mg/kg-bw/day
(M)
LOAEL= 94
mg/kg-bw/day
(M)
Degeneration
and necrosis
of renal
tubular cells
(Kociba
et al..
i' I)
High
Respiratory
Chronic
Rat,
F344/DuCij,
M/F
(n=20/group)
Oral,
drinking
water
0, 52, 126, 274,
657 or 1554
mg/kg-bw/day
(M);
0, 83, 185, 427,
756 or 1614
mg/kg-bw/day (F)
13 weeks
NOAEL= 52
mg/kg-bw/day
(M)
LOAEL= 126
mg/kg-bw/day
(M)
(Kano et
al.. 2008)
Medium
Respiratory
Chronic
Rat,
F344/DuCij,
M/F
(n=100/group)
Oral,
drinking
water
0, 11, 55 or 274
mg/kg-bw/day
(M);
0, 18, 83 or 429
mg/kg-bw/day (F)
2 years
NOAEL= 55
mg/kg-bw/day
(M)
LOAEL= 274
mg/kg-bw/day
(M)
Atrophy of
nasal
olfactory
epithelium;
nasal
adhesion and
inflammation
(Kano et
al.. 2.009;
3)
High; High
Respiratory
Sub
chronic
Mouse,
Crj:BDFl,M/F
(n=20/group)
Oral,
drinking
water
0, 86, 231,585,
882 or 1570
mg/kg-bw/day
(M);
0, 170, 387, 898,
1620 or 2669
mg/kg-bw/day (F)
13 weeks
NOAEL= 170
mg/kg-bw/day
(F)
LOAEL= 387
mg/kg-bw/day
(F)
(Kano et
al.. 2008)
Medium
Page 302 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Target Organ/
System1
Study
Type
Species/
Strain/Sex
(Number/
group)2
Exposure
Route
Doses/
Concentrations3
Duration4
Effect Dose or
Concentration
(NOAEL,
LOAEL,
LCso)5 (mg/m3
or mg/kg-
bw/day) (Sex)
Effect6
Reference7
Data Quality
Evaluation8
Respiratory
Chronic
Mouse,
B6C3F1, M/F
(n=100/group)
Oral,
drinking
water
0, 720 or 830
mg/kg-bw/day
(M);
0, 380 or 860
mg/kg-bw/day (F)
90 weeks
LOAEL= 380
mg/kg-bw/day
(F)
Pneumonia
and rhinitis
(NCI,
I • >78)
Low
Respiratory
Chronic
Mouse,
Crj:BDFl,M/F
(n=100/group)
Oral,
drinking
water
0, 49, 191 or 677
mg/kg-bw/day
(M);
0, 66, 278 or 964
mg/kg-bw/day (F)
2 years
NOAEL= 66
mg/kg-bw/day
(F)
LOAEL= 278
mg/kg-bw/day
(F)
Nasal
inflammation
(Kano et
at.. 2.009;
JBRC,
ll,f>8)
High
H.1.5 Hazard and Data Evaluation Summary for Genotoxicity Studies
Page 303 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Target Organ/
System
Study Type
Species/
Strain/Cell
type (Number/
Group if
relevant)
Exposure
Route
Doses /
Concentrations
Duration
Effect
Concentration
/ Result
Effect
measured
Reference
Data Quality
Evaluation
Genotoxicity
Short Term
S. typhimurium
strains TA98,
TA100,
TA1535,
TA1537
In vitro
0, 10,000
ug/plate
1 week
Negative
Reverse
Mutation
Haworth et at
11
Genotoxicity
Short Term
S. typhimurium
strains TA98,
TA100,
TA1530,
TA1535,
TA1537
In vitro
ND
NR
False-negative
Mutagenesis
(Ames assay)
Khudolev et al.
7)
Genotoxicity
Acute
S. typhimurium
strains TA98,
TA100,
TA1535,
TA1537
In vitro
0, 5,000 (ig/plate
30 minutes
Negative
Reverse
mutation
Merita and
Havashi (1998)
Genotoxicity
Acute
S. typhimurium
strains TA100,
TA1535
In vitro
0, 103 mg
24 hours
Negative
Reverse
mutation
Nestmann et al.
Genotoxicity
Short Term
S. typhimurium
strains TA98,
TA100,
TA1535,
TA1537,
TA1538
In vitro
0, 5.17, 15.5,
31.0, 62, 103 mg
48 hours
Negative
Reverse
mutation
Stott et al.
f 1 (>81); Dow
Chemical.
D
Genotoxicity
Short Term
E. coli K-12
uvrB/recA
In vitro
1,150 mmol/L
1 day
Negative
DNA Repair
Heltmer and
Bolcsfoldi
(1992)
Genotoxicity
Acute
E. coli
WP2/WP2uvrA
In vitro
0, 5,000 ug/plate
24 hours
Negative
Reverse
Mutation
Morita and
Havashi (1998)
Genotoxicity
Acute
P.
phosphoreum
M169
In vitro
ND
18 hours
Negative
Mutagenicity,
DNA damage
Kwan et al.
i1990)
Page 304 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Genotoxicity
Short Term
S. cerevisiae
D61.M
In vitro
0, 1.48, 1.96,
2.44,2.91,3.38,
4.31,4.75%
7 days
Negative
Aneuploidy
Zimmerman et
al. (1985)
unacceptable
Genotoxicity
Acute
D.
melanogaster
In vitro
0, 1, 1.5,2, 3,
3.5% in sucrose
media
24 hours
I.OAF.I. at 2%
Meiotic
nondisjunction
Munoz and
Barnett (2002)
High
Genotoxicity
D.
melanogaster
In vitro
35,000 ppm in
feed, 7 days or
50,000 ppm (5%
in water) by
injection
Sex-linked
recessive lethal
test
Yoon et al.
< 1985)
Genotoxicity
Acute
Male CDF
Fischer 344 rat
hepatocytes
In vitro
10° to 10"8 Molar
18 hours
Negative
Unscheduled
DNA synthesis
Stott et al.
1); Dow
Chemical.
* [1*52)
High
Genotoxicity
Acute
Rat hepatocytes
In vitro
0,0.03,0.3,3,
10, 30 mM
3 hours
I.OAF.I. at 0.3
mM
DNA damage;
single-strand
breaks
measured by
alkaline elution
Sina et al.
Genotoxicity
Short Term
Primary
hepatocyte
culture from
male F344 rats
In vitro
0,0.001,0.01,
0.1, 1 mM
5 days
Negative
DNA repair
Gotdswortfav et
al. (1991)
Genotoxicity
Short Term
L5178Y mouse
lymphoma cells
In vitro
0, 5,000 ug/mL
48 hours
Negative
Forward
mutation assay
Genotoxicity
Acute
L5178Y mouse
lymphoma cells
In vitro
0, 5,000 ug/mL
24 hours
Negative
Forward
mutation assay
Morita and
Havashi (1998)
Genotoxicity
Short Term
BALB/3T3
cells
In vitro
0,0.25,0.5, 1.0,
2.0 mg/mL
48 hours
I.OAF.I. at 0.5
mg/mL
Cell
transformation
Sheu et al.
tl"<8)
Genotoxicity
Acute
CHO cells
In vitro
0, 1,050, 3,500,
10,500 ug/L
2 hours
Negative
SCE
Gallowav et al.
11
Genotoxicity
Short Term
CHO cells
In vitro
0, 1,050, 3,500,
10,500 ug/L
26 hours
Negative
Chromosomal
aberration
Gallowav et al.
7}
Genotoxicity
Short Term
CHO cells
In vitro
0, 5,000 ug/mL
26 hours
Negative
SCE
Morita and
Havashi (1998)
Genotoxicity
Short Term
CHO cells
In vitro
0, 5,000 ug/mL
44 hours
Negative
Chromosomal
aberration
Morita and
Havashi {1998)
Genotoxicity
Short Term
CHO cells
In vitro
0, 5,000 ug/mL
44 hours
Negative
Micronucleus
formation
Morita and
Havashi (1998)
Page 305 of 407
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Genotoxicity
Acute
Calf thymus
DNA
In vitro
0.04
pmol/mg/DNA
16 hours
Negative
Covalent
binding to
DNA
Woo et al.
lei
Genotoxicity
Acute
Female
Sprague
Dawley Rat
In vivo
0, 168, 840,
2,550, 4,200
mg/kg
21 hours
LOAEL at
2,550 mg/kg
DNA damage;
single-strand
breaks
measured by
alkaline elution
Kitchin and
Genotoxicity
Subchronic
Male Sprague
Dawley Rat
In vivo
0, 10, 100, 1000
mg/kg
11 weeks
Negative
DNA
alkylation in
hepatocytes
Stott et al.
1); Dow
Chemical.
•))
Genotoxicity
Short Term
Male B6C3F1
Mouse
In vivo
0, 500, 1,000,
2,000 mg/kg
daily dose; 0,
2,000, 3,000,
4,000 mg/kg
single injection
48 hours
Negative up to
daily doses of
2,000, Single
dose of 4,000
mg/kg
Micronucleus
formation in
bone marrow
McFee et al.
11
Genotoxicity
Short Term
Male and
female
C57BL6
Mouse; Male
BALB/c Mouse
In vivo
0, 450, 900,
1,800, 3,600
mg/kg
(C57BL6); 0,
5,000 mg/kg
(BALB/c)
48 hours
LOAEL of 900
mg/kg
(C57BL6);
Negative up to
5,000 mg/kg
(BALB/c)
Micronucleus
formation in
bone marrow
Mirkova (1994)
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 500, 1,000,
2,000, 3,200
mg/kg
72 hours
Negative up to
3,200 mg/kg
Micronucleus
formation in
peripheral
blood
MonJaXLmi
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 1,000, 2,000,
or 3,000 mg/kg
7 days
LOAEL at
2,000 mg/kg
Micronucleus
formation in
hepatocytes
Morita and
Havashi (1998)
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 1,000, 2,000,
or 3,000 mg/kg
7 days
Negative
Micronucleus
formation in
peripheral
blood
Morita and
Havashi (1998)
Genotoxicity
Acute
Male CBA and
C57BL6
Mouse
In vivo
0, 1,800, 3,600
mg/kg
24 hours
Negative
Micronucleus
formation in
bone marrow
Tinwell and
Ashbv (1994)
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 1,500, 2,500,
3,500 mg/kg per
day for 5 days
6 days
LOAEL of
1,500 mg/kg-
day for 5 days
Micronuclei
formation in
bone marrow
Rov et al.
(2005)
High
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 1,500, 2,500,
3,500 mg/kgper
day for 5 days
6 days
I.OAF.I. of
2,500 mg/kg-
day for 5 days
Micronuclei
formation in
hepatocytes
III
High
Genotoxicity
Subchronic
Male Sprague
Dawley Rat
In vivo
0, 10, 100, 1,000
mg/kg-day for
11 weeks
11 weeks
Negative
DNA repair in
hepatocytes
Stott et at.
1); Dow
Chemical.
D
Genotoxicity
Acute
Male F344 Rat
In vivo
0, 10, 100, 1,000
gm/kg for 2 or
12 hours;
12 hours
Negative
DNA repair in
hepatocytes
(autoradiograp
h)
Goldsworthv et
£
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,500 mg/kg-
day for 8 days +
1,000 mg/kg
gavage dose 12
hours prior to
sacrifice
8 days
Negative
DNA repair in
nasal epithelial
cells from the
nasoturbinate
or
maxilloturbinat
e
Goldsworthv ef
£
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,000 mg/kg
for 24 or 48
hours; 1,500
mg/kg-day for 1
or 2 weeks
2 weeks
I.OAF.I. of
1,000 mg/kg
for 24 or 48
hours; 1,500
mg/kg-day for
1 or 2 weeks
Replicative
DNA synthesis
(i.e., cell
proliferation) in
hepatocytes
Goldsworthv et
£
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,500 mg/kg-
day for 2 weeks
2 weeks
1,500 mg/kg-
day for 2 weeks
Replicative
DNA synthesis
(i.e., cell
proliferation) in
nasal epithelial
cells
Goldsworthv et
al. (1991)
Genotoxicity
Acute
Male Sprague
Dawley Rat
In vivo
0, 10, 100 mg/rat
24 hours
I.OAF.I. of 10
mg/rat
RNA synthesis;
inhibition of
RNA
polymerase A
andB
Kurt et al.
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,000, 1,500,
2,000, 4,000
mg/kg
48 hours
LOAEL of
1,000 mg/kg
DNA synthesis
in hepatocytes
Mivaeawa et
al (1999)
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,000, 2,000
mg/kg
48 hours
I.OAF.I. of
2,000 mg/kg
DNA synthesis
in hepatocytes
Uno et al.
1)
Medium
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Genotoxicity
Short Term
Male Sprague
Dawley Rat
In vivo
0, 10, 100, or
1,000 mg/kg.
11 weeks
I.OAF.I. of
1,000 mg/kg-
day for 11
weeks
DNA synthesis
in hepatocytes
Stott et at.
< Dow
Chemical.
¦))
Genotoxicity
Short term
Male
F344/DuCrlCrl
j rats
In vivo
1000, 2000,
3000 mg/kg
6 days
I.OAF.I. of
1,000 mg/kg
Liver
micronucleus
test by juvenile
rat method
Itoli and
Hattori (2019)
High
Genotoxicity
Short term
Male
F344/DuCrlCrl
j rats
In vivo
1000, 2000,
3000 mg/kg
24 or 48 hours
LOAEL of
3,000 mg/kg
Bone marrow
micronucleus
test
Itoli and
Hattori (2019)
High
Genotoxicity
Short term
Male
F344/DuCrlCrl
j rats
In vivo
1000, 2000,
3000 mg/kg
15 or 30 days
No effect at
any doses
tested
Mutagenicity
by Pig-a gene
mutation assay
Itohand
jHillQiLOillJ)
High
Genotoxicity
Long Term
Male gpt delta
transgenic
F344 rats
In vivo
0, 200, 1,000,
5,000 ppm
16 weeks
Positive at
5,000 ppm
Increased
relative mRNA
expression
levels
(Gi et al. 2018)
Genotoxicity
Long Term
Male gpt delta
transgenic
F344 rats
In vivo
0, 0,2, 2, or 20
ppm
16 weeks
Negative up to
20 ppm
Mutagenesis
I'Gi et al. 20.1.8)
Genotoxicity
Long Term
Male gpt delta
transgenic
F344 rats
In vivo
0, 2, 20, 200,
2,000, 5,000
ppm
16 weeks
Positive at
2,000 ppm
Increased GST-
P-positive foci
induction and
cell
proliferation
(Gi et al. 20.1.8)
NR- not reported; ND - not determined
H.1.6 Data Evaluation Summary for Chronic Cancer Studies
Cancer Incidence for 1,4-Dioxane Studies with Acceptable Data Quality Ratings1
Page 308 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data
Quality
Evaluation
Chronic
Rat, Wistar,
M
(n=26 treated,
9 controls)
Oral,
drinking
water
0 or 640 mg/kg-
bw/day
63 weeks
6/26
treated
rats
Hepatocellular
carcinomas
{Argus, 1965,
17009}
Medium
Chronic
Rat, Wistar,
M
(n=26 treated,
9 controls)
Oral,
drinking
water
0 or 640 mg/kg-
bw/day
63 weeks
1/26
treated
rats
Transitional cell
carcinoma in kidney's
pelvis
{Argus, 1965,
17009}
Medium
Chronic
Rat, Wistar,
M
(n=26 treated,
9 controls)
Oral,
drinking
water
0 or 640 mg/kg-
bw/day
63 weeks
1/26
treated
rats
Leukemia
{Argus, 1965,
17009}
Medium
Chronic
Rat, Sprague
Dawley, M
(n=30/group)
Oral,
drinking
water
0, 430, 574, 803
or 1032 mg/kg-
bw/day
13
months
5/28-32
rats (dose
not
specified)
Liver
{Argus, 1973,
62912}
Low
Chronic
Rat,
F344/DuCrj ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or
274 mg/kg-
bw/day (M) 0,
18, 83, or 429
mg/kg-bw/day
(F)
2 years
3,4,7,32
(M, 50
rats/
dose)
3,1,6,48
(F, 50
rats/
dose)
Hepatocellular adenoma
{JBRC, 1998,
196240;Kano,
2009,
594539}
High
Page 309 of 407
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Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data
Quality
Evaluation
Chronic
Rat,
F344/DuCrj ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or
274 mg/kg-
bw/day (M) 0,
18, 83, or 429
mg/kg-bw/day
(F)
2 years
0,0,0,14
(M, 50
rats/
dose)
0,0,0,10
(F, 50
rats/
dose)
Hepatocellular carcinoma
{JBRC, 1998,
196240;Kano,
2009,
594539}
High
Chronic
Rat,
F344/DuCrj ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or
274 mg/kg-
bw/day (M) 0,
18, 83, or 429
mg/kg-bw/day
(F)
2 years
3,4,7,39
(M, 50
rats/
dose)
3,1,6,48
(F, 50
rats/
dose)
Either hepatocellular
adenoma or carcinoma
{JBRC, 1998,
196240;Kano,
2009,
594539}
High
Chronic
Rat,
F344/DuCrj ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or
274 mg/kg-
bw/day (M) 0,
18, 83, or 429
mg/kg-bw/day
(F)
2 years
1,1,0,4
(M, 50
rats/
dose)
3,2,1,3
(F, 50
rats/
dose)
Mammary gland-
Fibroadenoma
{JBRC, 1998,
196240;Kano,
2009,
594539}
High
Page 310 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data
Quality
Evaluation
Chronic
Rat,
F344/DuCrj ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or
274 mg/kg-
bw/day (M) 0,
18, 83, or 429
mg/kg-bw/day
(F)
2 years
0,1,2,2
(M, 50
rats/
dose)
6,7,10,16
(F, 50
rats/
dose)
Mammary gland-
Adenoma
{JBRC, 1998,
196240;Kano,
2009,
594539}
High
Chronic
Rat,
F344/DuCrj ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or
274 mg/kg-
bw/day (M) 0,
18, 83, or 429
mg/kg-bw/day
(F)
2 years
1,2,2,6
(M, 50
rats/
dose)
8,8,11,18
(F, 50
rats/
dose)
Mammary gland- Either
fibroadenoma or
adenoma
{JBRC, 1998,
196240;Kano,
2009,
594539}
High
Chronic
Rat,
F344/DuCrj ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or
274 mg/kg-
bw/day (M) 0,
18, 83, or 429
mg/kg-bw/day
(F)
2 years
2,2,5,28
(M, 50
rats/
dose)
1,0,0,0
(F, 50
rats/
dose)
Peritoneum-
Mesothelioma
{JBRC, 1998,
196240;Kano,
2009,
594539}
High
Page 311 of 407
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Study
Species/
Exposure
Doses/
Duration
Cancer
Effect
Reference
Data
Type
Strain/Sex
Route
Concentrations
Incidence
Quality
(Number/
Evaluation
group)
Chronic
Rat,
Oral,
0, 11, 55, or
2 years
0,0,0,3
Nasal- Squamous cell
{JBRC, 1998,
High
F344/DuCrj ,
drinking
274 mg/kg-
(M, 50
carcinoma
196240;Kano,
M/F, (n=
water
bw/day (M) 0,
rats/
2009,
100/group)
18, 83, or 429
dose)
594539}
mg/kg-bw/day
0,0,0,7
(F)
(F, 50
rats/
dose)
Chronic
Rat,
Oral,
0, 11, 55, or
2 years
0,0,0,2
Nasal- Sarcoma
{JBRC, 1998,
High
F344/DuCrj ,
drinking
274 mg/kg-
(M, 50
196240;Kano,
M/F, (n=
water
bw/day (M) 0,
rats/
2009,
100/group)
18, 83, or 429
dose)
594539}
mg/kg-bw/day
0,0,0,0
(F)
(F, 50
rats/
dose)
Chronic
Rat,
Oral,
0, 11, 55, or
2 years
0,0,0,1
Nasal-
{JBRC, 1998,
High
F344/DuCrj ,
drinking
274 mg/kg-
(M, 50
Rhabdomyosarcoma
196240;Kano,
M/F, (n=
water
bw/day (M) 0,
rats/
2009,
100/group)
18, 83, or 429
dose)
594539}
mg/kg-bw/day
0,0,0,0
(F)
(F, 50
rats/
dose)
Page 312 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data
Quality
Evaluation
Chronic
Rat,
F344/DuCrj ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or
274 mg/kg-
bw/day (M) 0,
18, 83, or 429
mg/kg-bw/day
(F)
2 years
0,0,0,1
(M, 50
rats/
dose)
0,0,0,1
(F, 50
rats/
dose)
Nasal-
Esthesioneuroepithelioma
{JBRC, 1998,
196240;Kano,
2009,
594539}
High
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3
(0, 50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
0,0,1,6
(50 rats
per dose
group)
Nasal squamous cell
carcinoma
{Kasai, 2009,
193803}
High
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3 (0,
50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
1,2,3,21
(50 rats
per dose
group)
Hepatocellular adenoma
{Kasai, 2009,
193803}
High
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3 (0,
50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
0,0,1,2
(50 rats
per dose
group)
Hepatocellular carcinoma
{Kasai, 2009,
193803}
High
Page 313 of 407
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Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data
Quality
Evaluation
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3 (0,
50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
0,0,0,4
(50 rats
per dose
group)
Renal cell carcinoma
{Kasai, 2009,
193803}
High
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3 (0,
50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
2,4,14,41
(50 rats
per dose
group)
Peritoneal mesothelioma
{Kasai, 2009,
193803}
High
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3 (0,
50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
1,2,3,5
(50 rats
per dose
group)
Mammary gland
fibroadenoma
{Kasai, 2009,
193803}
High
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3 (0,
50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
0,0,0,1
(50 rats
per dose
group)
Mammary gland
adenoma
{Kasai, 2009,
193803}
High
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3 (0,
50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
0,0,0,4
(50 rats
per dose
group)
Zymbal gland adenoma
{Kasai, 2009,
193803}
High
Page 314 of 407
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Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data
Quality
Evaluation
Chronic
Rat,
F344/DuCrj,
M (n=
50/group)
Inhalation,
vapor,
whole
body
0, 180, 900, or
4500 mg/m3 (0,
50, 250, or
1250 ppm)
6
hours/dy,
5
days/wk,
for 2
years
1,4,9,5
(50 rats
per dose
group)
Subcutis fibroma
{Kasai, 2009,
193803}
High
Chronic
Rat, Sherman,
M/F,
(n=120/group)
Oral,
drinking
water
0, 9.6, 94, or
1015 mg/kg-
bw/day (M)
0, 19, 148, or
1599 mg/kg-
bw/day (F)
2 years
2/106,
0/110,
1/106,
12/66
Hepatic tumors (all
types)
{Kociba,
1974, 62929}
High
Chronic
Rat, Sherman,
M/F,
(n=120/group)
Oral,
drinking
water
0, 9.6, 94, or
1015 mg/kg-
bw/day (M)
0, 19, 148, or
1599 mg/kg-
bw/day(F)
2 years
1/106,
0/110,
1/106,
10/66
Hepatocellular carcinoma
{Kociba,
1974, 62929}
High
Chronic
Rat, Sherman,
M/F,
(n=120/group)
Oral,
drinking
water
0, 9.6, 94, or
1015 mg/kg-
bw/day (M)
0, 19, 148, or
1599 mg/kg-
bw/day (F)
2 years
0/106,
0/110,
0/106,
3/66
Nasal carcinoma
{Kociba,
1974, 62929}
High
Chronic
Mouse,
B6C3F1, M/F
(n=100/group)
Oral,
drinking
water
0, 720 or 830
mg/kg-bw/day
(M);
0, 380 or 860
mg/kg-bw/day
(F)
90 weeks
2/49,
18/50,
24/47 (M)
0/50,
12/48,
29/37 (F)
Hepatocellular carcinoma
{NCI, 1978,
62935}
Low
Page 315 of 407
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Study
Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data
Quality
Evaluation
Chronic
Mouse,
B6C3F1, M/F
(n=100/group)
Oral,
drinking
water
0, 720 or 830
mg/kg-bw/day
(M);
0, 380 or 860
mg/kg-bw/day
(F)
90 weeks
8/49,
19/50,
28/47 (M)
0/50,
21/48,
35/37 (F)
Hepatocellular adenoma
or carcinoma
{NCI, 1978,
62935}
Low
Chronic
Rat, Osborne-
Mendel, F2
(n=70/group)
Oral,
drinking
water
0, 350 or 640
mg/kg-bw/day
(F)
110
weeks
0/34,
10/35,
8/35 (F)
Nasal cavity squamous
cell carcinoma
{NCI, 1978,
62935}
Low
Chronic
Rat, Osborne-
Mendel, F2
(n=70/group)
Oral,
drinking
water
8 0, 350 or
640 mg/kg-
bw/day (F)
110
weeks
0/31,
10/33,
11/32 (F)
Hepatocellular carcinoma
{NCI, 1978,
62935}
Low
1 Unacceptable studies are not included in this table.
2The results for male rats were considered unacceptable and are not included in this table.
Page 316 of 407
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H.1.7 Data Evaluation Summary for Mechanistic Studies
Table H-l. Summary of Mechanistic Data for 1,4-Dioxane
Target Organ/
System
Study
Type
Species/
Strain/Cell type
(Number/
Group if
relevant)
Exposure
Route
Doses/
Concentrations
Duration
Effect
Concentration/
Result
Effect
measured
Reference
Data Quality
Evaluation
Genotoxicity
Short-
term
Fly, Drosphilia
melanogaster, F
(n=50/treatment
group)
In vitro
1, 1.5,2, 3 or
3.5% 1,4-dioxane
(in 4% sucrose
aqueous solution)
24 hrs
LOAEL = 1.5%
solution (F)
Increased
meiotic non-
disjunction
in oocytes
Munoz et
aL 2002
High
Genotoxicity
Acute
Male CDF
Fischer 344 rat
hepatocytes
In vitro
10° to 10"8 Molar
18 hours
Negative for
DNA damage
Unscheduled
DNA
synthesis
(Dow
Chemical
Co.. 1989a)
Medium
Hepatic
Acute
Rat liver
microsomes (n =
3 trials/dose)
In vitro
0,0.1,0.25,0.5,
0.75 or l%v/v
10 min
ACso (MET) =
0.25% v/v; 29.4
mM
ACso (IMI) =
0.10% v/v; 11.7
mM
Decrease in
CYP450
activity
measured
with
metoprolol
(MET) or
imipramine
(IMI)
metabolism
Shah et aL
2015
High
Hepatic
Not
reported
Rat liver
microsomes
(n = 3
trials/dose)
In vitro
0,0.1,0.25,0.5,
0.75 or 1 %v/v
Not
Reported
ACso = <0.10%
v/v; <11.7 mM
Decrease in
P-
nitrophenol
hydroxylase
activity
measured
with p-
nitrophenol
metabolism
Patil et aL.
20.1.5
High
Page 317 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Target
Organ/
System
Study
Type
Species/
Strain/Cell
type (Number/
Group if
relevant)
Exposure
Route
Doses/
Concentrations
Duration
Effect
Concentration/
Result
Effect measured
Reference
Data
Quality
Evaluation
Genotoxicity
Acute
Male CDF
Fischer 344 rat
hepatocytes
In vitro
10° to 10"8 Molar
18 hours
Negative for
DNA damage
Unscheduled
DNA synthesis
(Dow
Chemical,
1989) (pg
248-261)
Medium
Genotoxicity
Short Term
S. typhimurium
strains TA98,
TA100,
TA1535,
TA1537
In vitro
0, 10,000
ug/plate
1 week
Negative up to
10,000 ug/plate
Reverse
Mutation
Haworth et
al. (1983)
Genotoxicity
Short Term
S. typhimurium
strains TA98,
TA100,
TA1530,
TA1535,
TA1537
In vitro
ND
NR
False-negative
Mutagenesis
(Ames assay)
Khudolev ef
al (1987)
Genotoxicity
Acute
S. typhimurium
strains TA98,
TA100,
TA1535,
TA1537
In vitro
0, 5,000 (ig/plate
30
minutes
Negative up to
5,000 (ig/plate
Reverse mutation
Morita and
owsT
Genotoxicity
Acute
S. typhimurium
strains TA100,
TA1535
In vitro
0, 103 mg
24 hours
Negative up to
103 mg
Reverse mutation
Nestmann et
Genotoxicity
Short Term
S. typhimurium
strains TA98,
TA100,
TA1535,
TA1537,
TA1538
In vitro
0, 5.17, 15.5,
31.0, 62, 103 mg
NR
Negative up to
103 mg
Reverse mutation
Stott et al.
Genotoxicity
Short Term
E. coliK-12
uvrB/recA
In vitro
1,150 mmol/L
1 day
Negative up to
1,150 mmol/L
DNA Repair
Hellmer and
Bolcsfoldi
(1992)
Genotoxicity
Acute
E. coli
WP2/WP2uvrA
In vitro
0, 5,000 ug/plate
24 hours
Negative up to
5,000 ug/plate
Reverse
Mutation
Morita and
Havashi
(1998)
Genotoxicity
Acute
P. phosphoreum
M169
In vitro
ND
18 hours
Negative
Mutagenicity,
DNA damage
Kwan et al.
(1990)
Page 318 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Genotoxicity
Short Term
S. cerevisiae
D61.M
In vitro
0, 1.48, 1.96,
2.44,2.91,3.38,
4.31,4.75%
7 days
Negative up to
4.75%
Aneuploidy
Zimmerman
Genotoxicity
Acute
D. melanogaster
In vitro
0, 1, 1.5,2,3,
3.5% in sucrose
media
24 hours
LOAEL at 2%
Meiotic
nondisjunction
Munoz and
Baniett
Genotoxicity
D. melanogaster
In vitro
35,000 ppm in
feed, 7 days or
50,000 ppm (5%
in water) by
injection
Sex-linked
recessive lethal
test
Yoon et al.
(1985)
Genotoxicity
Acute
Rat hepatocytes
In vitro
0,0.03,0.3,3,
10, 30 mM
3 hours
LOAEL at 0.3
mM
DNA damage;
single-strand
breaks measured
by alkaline
elution
Sina et al.
(1983)
Genotoxicity
Short Term
Primary
hepatocyte
culture from
male F344 rats
In vitro
0,0.001,0.01,
0.1, 1 mM
5 days
Negative up to
ImM
DNA repair
Goldsworthv
ef al. (1991)
Genotoxicity
Short Term
L5178Y mouse
lymphoma cells
In vitro
0, 5,000 ug/mL
48 hours
Negative up to
5,000 ug/mL
Forward
mutation assay
McGregor et
Genotoxicity
Acute
L5178Y mouse
lymphoma cells
In vitro
0, 5,000 ug/mL
24 hours
Negative up to
5,000 ug/mL
Forward
mutation assay
Morita and
Havashi
(1998)
Genotoxicity
Short Term
BALB/3T3 cells
In vitro
0,0.25,0.5, 1.0,
2.0 mg/mL
48 hours
LOAEL at 0.5
mg/mL
Cell
transformation
Sheu et al.
(1988)
Genotoxicity
Acute
CHO cells
In vitro
0, 1,050, 3,500,
10,500 ug/L
2 hours
Negative up to
10,500 ug/mL
SCE
Galloway et
al. (1987)
Genotoxicity
Short Term
CHO cells
In vitro
0, 1,050, 3,500,
10,500 ug/L
26 hours
Negative up to
10,500 ug/mL
Chromosomal
aberration
Galloway et
Genotoxicity
Short Term
CHO cells
In vitro
0, 5,000 ug/mL
26 hours
Negative up to
5,000 ug/mL
SCE
Morita and
Havashi
(1998)
Genotoxicity
Short Term
CHO cells
In vitro
0, 5,000 ug/mL
44 hours
Negative up to
5,000 ug/mL
Chromosomal
aberration
Morita and
Havashi
(1998)
Genotoxicity
Short Term
CHO cells
In vitro
0, 5,000 ug/mL
44 hours
Negative up to
5,000 ug/mL
Micronucleus
formation
Morita and
Havashi
(1998)
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Genotoxicity
Acute
Calf thymus
DNA
In vitro
0.04
pmol/mg/DNA
16 hours
Negative up to
0.04
pmol/mg/DNA
(bound)
Covalent binding
to DNA
Woo et at
Genotoxicity
Acute
Female Sprague
Dawley Rat
In vivo
0, 168, 840,
2,550, 4,200
mg/kg
21 hours
LOAEL at 2,550
mg/kg
DNA damage;
single-strand
breaks measured
by alkaline
elution
Kitchin and
Brown
(1990)
Genotoxicity
Subchronic
Male Sprague
Dawley Rat
In vivo
0, 10, 100, 1000
mg/kg
11 weeks
Negative up to
1,000 mg/kg
DNA alkylation
in hepatocytes
Sfoff ef al.
(1981)
Genotoxicity
Short Term
Male B6C3F1
Mouse
In vivo
0, 500, 1,000,
2,000 mg/kg
daily dose; 0,
2,000, 3,000,
4,000 mg/kg
single injection
48 hours
Negative up to
daily doses of
2,000, Single
dose of 4,000
mg/kg
Micronucleus
formation in
bone marrow
McFee et al.
(1994)
Genotoxicity
Short Term
Male and
female C57BL6
Mouse; Male
BALB/c Mouse
In vivo
0, 450, 900,
1,800, 3,600
mg/kg
(C57BL6); 0,
5,000 mg/kg
(BALB/c)
48 hours
LOAEL of 900
mg/kg
(C57BL6);
Negative up to
5,000 mg/kg
(BALB/c)
Micronucleus
formation in
bone marrow
Mirkova
(1994)
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 500, 1,000,
2,000, 3,200
mg/kg
72 hours
Negative up to
3,200 mg/kg
Micronucleus
formation in
peripheral blood
Morita
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 1,000, 2,000,
or 3,000 mg/kg
7 days
LOAEL at 2,000
mg/kg
Micronucleus
formation in
hepatocytes
Morita and
Havashi
(1998)
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 1,000, 2,000,
or 3,000 mg/kg
7 days
Negative up to
3,000 mg/kg
Micronucleus
formation in
peripheral blood
Morita and
Havashi
(1998)
Genotoxicity
Acute
Male CBA and
C57BL6 Mouse
In vivo
0, 1,800, 3,600
mg/kg
24 hours
Negative up to
3,600 mg/kg
Micronucleus
formation in
bone marrow
Ti nwell and
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 1,500, 2,500,
3,500 mg/kg per
day for 5 days
6 days
LOAEL of
1,500 mg/kg-
day for 5 days
Micronuclei
formation in
bone marrow
Rov et al.
(2005)
Genotoxicity
Short Term
Male CD1
Mouse
In vivo
0, 1,500, 2,500,
3,500 mg/kg per
day for 5 days
6 days
LOAEL of
2,500 mg/kg-
day for 5 days
Micronuclei
formation in
hepatocytes
Rov et al.
(2005)
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Genotoxicity
Subchronic
Male Sprague
Dawley Rat
In vivo
0, 10, 100, 1,000
mg/kg-day for
11 weeks
11 weeks
Negative up to
1,000 mg/kg-
day for 11
weeks
DNA repair in
hepatocytes
Stott et a I.
(198.1.)
Genotoxicity
Acute
Male F344 Rat
In vivo
0, 10, 100, 1,000
gm/kg for 2 or
12 hours;
12 hours
Negative up to
1,000 mg/kg for
2 or 12 hours
DNA repair in
hepatocytes
(autoradiograph)
Goldsworthv
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,500 mg/kg-
day for 8 days +
1,000 mg/kg
gavage dose 12
hours prior to
sacrifice
8 days
Negative up to
1,500 mg/kg-
day for 8 days +
1,000 mg/kg
gavage dose 12
hours prior to
sacrifice
DNA repair in
nasal epithelial
cells from the
nasoturbinate or
maxilloturbinate
Goldsworthv
et al. (1991)
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,000 mg/kg
for 24 or 48
hours; 1,500
mg/kg-day for 1
or 2 weeks
2 weeks
1 .OAF.I, of
1,000 mg/kg for
24 or 48 hours;
1,500 mg/kg-
day for 1 or 2
weeks
Replicative DNA
synthesis (i.e.,
cell proliferation)
in hepatocytes
Goldsworthv
et al. (1991)
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,500 mg/kg-
day for 2 weeks
2 weeks
1,500 mg/kg-
day for 2 weeks
Replicative DNA
synthesis (i.e.,
cell proliferation)
in nasal epithelial
cells
Goldsworthv
Genotoxicity
Acute
Male Sprague
Dawley Rat
In vivo
0, 10, 100 mg/rat
24 hours
1 .OAF.I, of 10
mg/rat
RNA synthesis;
inhibition of
RNA polymerase
A andB
Kurt et at.
(1981)
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,000, 1,500,
2,000, 4,000
mg/kg
48 hours
LOAEL of
1,000 mg/kg
DNA synthesis
in hepatocytes
Mivaeawa et
al. (1999)
Genotoxicity
Short Term
Male F344 Rat
In vivo
0, 1,000, 2,000
mg/kg
48 hours
LOAEL of
2,000 mg/kg
DNA synthesis
in hepatocytes
Uno et al.
Genotoxicity
Short Term
Male Sprague
Dawley Rat
In vivo
0, 10, 100, or
1,000 mg/kg.
11 weeks
LOAEL of
1,000 mg/kg-
day for 11
weeks
DNA synthesis
in hepatocytes
Stott et at.
(1981)
Genotoxicity
Long Term
Male gpt delta
transgenic F344
rats
In vivo
0, 200, 1,000,
5,000 ppm
16 weeks
Positive at
5,000 ppm
Increased relative
mRNA
expression levels
(Gi et al..
2018)
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Genotoxicity
Long Term
Male gpt delta
transgenic F344
rats
In vivo
0, 0,2, 2, or 20
ppm
16 weeks
Negative up to
20 ppm
Mutagenesis
(Gi et at..
Genotoxicity
Long Term
Male gpt delta
transgenic F344
rats
In vivo
0, 2, 20, 200,
2,000, 5,000
ppm
16 weeks
Positive at 2,000
ppm
Increased GST-
P-positive foci
induction and
cell proliferation
(Gi et al.
Table H-2. Cancer Incidence for 1,4-Dioxane Studies with Acceptable Data Quality Ratings1
Study Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data Quality
Evaluation
Chronic
Rat, Wistar, M
(n=26 treated, 9
controls)
Oral,
drinking
water
0 or 640 mg/kg-
bw/day
63 weeks
6/26 treated
rats
Hepatocellular carcinomas
( is et
at.. 1965)
Medium
Chronic
Rat, Wistar, M
(n=26 treated, 9
controls)
Oral,
drinking
water
0 or 640 mg/kg-
bw/day
63 weeks
1/26 treated
rats
Transitional cell
carcinoma in kidney's
pelvis
(Argus et
at... 1965)
Medium
Chronic
Rat, Wistar, M
(n=26 treated, 9
controls)
Oral,
drinking
water
0 or 640 mg/kg-
bw/day
63 weeks
1/26 treated
rats
Leukemia
(Argus et
at... 1965)
Medium
Chronic
Rat, Sprague
Dawley, M
(n=30/group)
Oral,
drinking
water
0, 430, 574, 803 or
1032 mg/kg-
bw/day
13 months
5/28-32 rats
(dose not
specified)
Liver
(Argus et
at... 1973)
Low
Chronic
Rat, F344/DuCij
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
3,4,7,32 (M,
50 rats/ dose)
3,1,6,48 (F,
50 rats/ dose)
Hepatocellular adenoma
(Kano et
High
Chronic
Rat, F344/DuCij
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
0,0,0,14 (M,
50 rats/ dose)
0,0,0,10 (F,
50 rats/ dose)
Hepatocellular carcinoma
(Kano et
High
Chronic
Rat, F344/DuCij
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
3,4,7,39 (M,
50 rats/ dose)
3,1,6,48 (F,
50 rats/ dose)
Either hepatocellular
adenoma or carcinoma
(Kano et
High
Page 322 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Study Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data Quality
Evaluation
Chronic
Rat, F344/DuCij ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
1,1,0,4 (M,
50 rats/ dose)
3,2,1,3 (F, 50
rats / dose)
Mammary gland-
Fibroadenoma
CKano et
al, 2009;
JBRC.
s »)
High
Chronic
Rat, F344/DuCij ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
0,1,2,2 (M,
50 rats/ dose)
6,7,10,16 (F,
50 rats/ dose)
Mammary gland-
Adenoma
flCamo et
al, 2009;
JBRC,
High
Chronic
Rat, F344/DuCij ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
1,2,2,6 (M,
50 rats/ dose)
8,8,11,18 (F,
50 rats/ dose)
Mammary gland- Either
fibroadenoma or adenoma
flCamo et
al, 2009;
JBRC,
High
Chronic
Rat, F344/DuCij ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
2,2,5,28 (M,
50 rats/ dose)
1,0,0,0 (F, 50
rats / dose)
Peritoneum-
Mesothelioma
flCamo et
al. 2009;
JBRC.
High
Chronic
Rat, F344/DuCij ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
0,0,0,3 (M,
50 rats/ dose)
0,0,0,7 (F, 50
rats / dose)
Nasal- Squamous cell
carcinoma
flCamo et
al. 2009;
JBRC.
High
Chronic
Rat, F344/DuCij ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
0,0,0,2 (M,
50 rats/ dose)
0,0,0,0 (F, 50
rats / dose)
Nasal- Sarcoma
flCamo et
al. 2009;
JBRC.
High
Chronic
Rat, F344/DuCij ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
0,0,0,1 (M,
50 rats/ dose)
0,0,0,0 (F, 50
rats/ dose)
Nasal-
Rhabdomyosarcoma
flCamo et
al. 2009;
JBRC.
High
Page 323 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Study Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data Quality
Evaluation
Chronic
Rat, F344/DuCij ,
M/F, (n=
100/group)
Oral,
drinking
water
0, 11, 55, or 274
mg/kg-bw/day (M)
0, 18, 83, or 429
mg/kg-bw/day (F)
2 years
0,0,0,1 (M,
50 rats/ dose)
0,0,0,1 (F, 50
rats / dose)
Nasal-
Esthesioneuroepithelioma
(Kano et
al, 2009;
JBRC.
s .)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3
(0, 50, 250, or 1250
ppm)
6 hours/dy,
5 days/wk,
for 2 years
0,0,1,6 (50
rats per dose
group)
Nasal squamous cell
carcinoma
(Kasai et
al, 2009)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3 (0, 50,
250, or 1250 ppm)
6 hours/dy,
5 days/wk,
for 2 years
1,2,3,21 (50
rats per dose
group)
Hepatocellular adenoma
(Kasai et
al., 2009)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3 (0, 50,
250, or 1250 ppm)
6 hours/dy,
5 days/wk,
for 2 years
0,0,1,2 (50
rats per dose
group)
Hepatocellular carcinoma
(Kasai et
al., 2009)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3 (0, 50,
250, or 1250 ppm)
6 hours/dy,
5 days/wk,
for 2 years
0,0,0,4 (50
rats per dose
group)
Renal cell carcinoma
(Kasai et
al. 2009)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3 (0, 50,
250, or 1250 ppm)
6 hours/dy,
5 days/wk,
for 2 years
2,4,14,41 (50
rats per dose
group)
Peritoneal mesothelioma
(Kasai et
al, 2009)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3 (0, 50,
250, or 1250 ppm)
6 hours/dy,
5 days/wk,
for 2 years
1,2,3,5 (50
rats per dose
group)
Mammary gland
fibroadenoma
(Kasai et
al. 2009)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3 (0, 50,
250, or 1250 ppm)
6 hours/dy,
5 days/wk,
for 2 years
0,0,0,1 (50
rats per dose
group)
Mammary gland adenoma
(Kasai et
al, 2009)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3 (0, 50,
250, or 1250 ppm)
6 hours/dy,
5 days/wk,
for 2 years
0,0,0,4 (50
rats per dose
group)
Zymbal gland adenoma
(Kasai et
al. 2009)
High
Chronic
Rat, F344/DuCij,
M (n= 50/group)
Inhalation,
vapor, whole
body
0, 180, 900, or
4500 mg/m3 (0, 50,
250, or 1250 ppm)
6 hours/dy,
5 days/wk,
for 2 years
1,4,9,5 (50
rats per dose
group)
Subcutis fibroma
(Kasai et
al. 2009)
High
Chronic
Rat, Sherman,
M/F,
(n=120/group)
Oral,
drinking
water
0, 9.6, 94, or 1015
mg/kg-bw/day (M)
0, 19, 148, or 1599
mg/kg-bw/day (F)
2 years
2/106, 0/110,
1/106, 12/66
Hepatic tumors (all types)
(Kociba et
r " i)
High
Page 324 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Study Type
Species/
Strain/Sex
(Number/
group)
Exposure
Route
Doses/
Concentrations
Duration
Cancer
Incidence
Effect
Reference
Data Quality
Evaluation
Chronic
Rat, Sherman,
M/F,
(n=120/group)
Oral,
drinking
water
0, 9.6, 94, or 1015
mg/kg-bw/day (M)
0, 19, 148, or 1599
mg/kg-bw/day(F)
2 years
1/106, 0/110,
1/106, 10/66
Hepatocellular carcinoma
(Kociba et
r i)
High
Chronic
Rat, Sherman,
M/F,
(n=120/group)
Oral,
drinking
water
0, 9.6, 94, or 1015
mg/kg-bw/day (M)
0, 19, 148, or 1599
mg/kg-bw/day (F)
2 years
0/106, 0/110,
0/106, 3/66
Nasal carcinoma
(Kociba et
aL 1974)
High
Chronic
Mouse, B6C3F1,
M/F
(n=100/group)
Oral,
drinking
water
0, 720 or 830
mg/kg-bw/day (M);
0, 380 or 860
mg/kg-bw/day (F)
90 weeks
2/49, 18/50,
24/47 (M)
0/50, 12/48,
29/37 (F)
Hepatocellular carcinoma
(NCI.
i)
Low
Chronic
Mouse, B6C3F1,
M/F
(n=100/group)
Oral,
drinking
water
0, 720 or 830
mg/kg-bw/day (M);
0, 380 or 860
mg/kg-bw/day (F)
90 weeks
8/49, 19/50,
28/47 (M)
0/50, 21/48,
35/37 (F)
Hepatocellular adenoma
or carcinoma
(NCI.
i)
Low
Chronic
Rat, Osborne-
Mendel, F2
(n=70/group)
Oral,
drinking
water
0, 350 or 640
mg/kg-bw/day (F)
110 weeks
0/34, 10/35,
8/35 (F)
Nasal cavity squamous
cell carcinoma
(NCI,
3)
Low
Chronic
Rat, Osborne-
Mendel, F2
(n=70/group)
Oral,
drinking
water
0, 350 or 640
mg/kg-bw/day (F)
110 weeks
0/31, 10/33,
11/32 (F)
Hepatocellular carcinoma
(NCI,
8)
Low
1 Unacceptable studies are not included in this table.
2The results for male rats were considered unacceptable and are not included in this table.
H.1.8 Hazard Data Tables
Page 325 of 407
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Table H-3. Incidences of non-neoplastic lesions in male F344 rats exposed to 1,4-dioxane via inhalation for 2 years (6 hours/day, 5
days/week) (I
vasai et al.. 2009)
Tissue
Endpoint
Concentration (ppm) and incidence
0 ppm
50 ppm
250 ppm
1250 ppm
Liver
Centrilobular necrosis
1
3
6
12
Squamous cell metaplasia; respiratory epithelium
0
0
7
44
Squamous cell hyperplasia; respiratory epithelium
0
0
1
10
Nasal
Respiratory metaplasia; olfactory epithelium
11
34
49
48
Atrophy; olfactory epithelium
0
40
47
48
Hydropic change; lamina propia
0
2
36
49
Sclerosis, lamina propia
0
0
22
40
Data quality evaluations for this study were determined to high (see Appendix G)
N=50 for all data.
Table H-4. Altered hepatocellular foci data in F344/DuCrj rats exposed to 1,4-dioxane via drinking water for 2 years (ad libitum)
(Kano et a!.. 2009)
Endpoint
Male
Female
ppm
mg/kg-d
Mixed cell
foci
0 200 1000 5000
0 11 55 274
2 8 14 13
0 200 1000 5000
0 18 83 429
1 1 3 11
Data quality evaluations for this study were determined to high (see Appendix G)
N=50 for all data.
Table H-5. Incidence of cortical tubule degeneration in female Osborne-Mendel rats exposed to 1,4-dioxane via drinking water for 2
years (ad libitum) ( 8)
Species and endpoint
Dose (mg/kg-d) and incidence
Female Osborne-Mendel
rats
Page 326 of 407
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Species and endpoint
Dose (mg/kg-d) and incidence
Dose (mg/kg-d)
0 mg/kg-d
350 mg/kg-d
640 mg/kg-d
Kidney
Cortical tubule degeneration
0/31
0/34
10/32
Data quality evaluations for B6C3F1 mice (male and female) and OM rats (female) from this study were determined to be low (see Appendix G). Data in for male OM
rats were determined to be unacceptable and are not included in this table.
Table H-6. Tumor incidence data in male F344 rats exposed to 1,4-dioxane via inhalation for 2 years (6 hours/day, 5 days/week)
'Kasai et al.« 2009)
Endpoint
Concentration (ppm) and incidence (%)
Concentration (ppm)
0 ppm
50 ppm
250 ppm
1250 ppm
Nasal cavity
Squamous cell carcinoma
0/50 (0%)
0/50 (0%)
1/50 (2%)
6/50 (12%)
Liver
Hepatocellular adenoma
1/50 (2%)
2/50 (4%)
3/50 (6%)
21/50 (42%)
Hepatocellular carcinoma
0/50 (0%)
0/50 (0%)
1/50 (2%)
2/50 (4%)
Hepatocellular adenoma or
carcinoma*
1/50 (2%)
2/50 (4%)
4/50 (8%)
22/50 (44%)
Kidney
Renal cell carcinoma
0/50 (0%)
0/50 (0%)
0/50 (0%)
4/50 (8%)
Peritoneum
Mesothelioma
2/50 (4%)
4/50 (8%)
14/50 (28%)
41/50 (82%)
Mammary gland
Fibroadenoma
1/50 (2%)
2/50 (4%)
3/50 (6%)
5/50 (10%)
Adenoma
0/50 (0%)
0/50 (0%)
0/50 (0%)
1/50 (2%)
Zymbal gland
Adenoma
0/50 (0%)
0/50 (0%)
0/50 (0%)
4/50 (8%)
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Endpoint
Concentration (ppm) and incidence (%)
Subcutis
Fibroma
1/50 (2%)
4/50 (8%)
9/50 (18%)
5/50 (10%)
Data quality evaluations for this study were determined to high (see Appendix G).
incidences of hepatocellular adenomas or carcinomas were corrected to account for rats that exhibited both adenomas and carcinomas (data were provided to U.S. EPA
by communication with the study author (Kasai. 2008)
Table H-7. Tumor Incidence data in male and female F344/DuCrj rats and CrjrBDFl mice exposed to 1,4-dioxane via drinking water
Species and endpoint
Dose (mg/kg-d) and incidence (%)
Male F344/DuCrj rats
Dose (mg/kg-d)
0 mg/kg-d
11 mg/kg-d
55 mg/kg-d
274 mg/kg-d
Nasal cavity
Squamous cell carcinoma
0/50 (0%)
0/50 (0%)
0/50 (0%)
3/50 (6%)
Liver
Hepatocellular adenoma
3/50 (6%)
4/50 (8%)
7/50(14%)
32/50 (64%)
Hepatocellular carcinoma
0/50 (0%)
0/50 (0%)
0/50 (0%)
14/50 (28%)
Hepatocellular adenoma or
3/50 (6%)
4/50 (8%)
7/50 (14%)
39/50 (78%)
carcinoma
Subcutis
Fibroma
5/50 (10%)
3/50 (6%)
5/50 (10%)
12/50 (24%)
Peritoneum
Mesothelioma
2/50 (4%)
2/50 (4%)
5/50 (10%)
28/50 (56%)
Female F344/DuCrj rats
Dose (mg/kg-d)
0 mg/kg-d
18 mg/kg-d
83 mg/kg-d
429 mg/kg-d
Nasal cavity
Squamous cell carcinoma
0/50 (0%)
0/50 (0%)
0/50 (0%)
7/50 (14%)
Liver
Hepatocellular adenoma
3/50 (6%)
1/50 (2%)
6/50 (12%)
48/50 (96%)
Hepatocellular carcinoma
0/50 (0%)
0/50 (0%)
0/50 (%)
10/50 (20%)
Hepatocellular adenoma or
3/50 (6%)
1/50 (2%)
6/50 (12%)
48/50 (96%)
carcinoma
Mammary gland
Adenoma
6/50 (12%)
7/50 (14%)
10/50 (20%)
16/50 (32%)
Female Crj:BDFl mice
Dose (mg/kg-d)
0 mg/kg-d
66 mg/kg-d
278 mg/kg-d
964 mg/kg-d
Liver
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Hepatocellular adenoma
5/50 (10%)
31/50 (62%)
20/50 (40%)
3/50 (6%)
Hepatocellular carcinoma
0/50 (0%)
6/50 (12%)
30/50 (60%)
45/50 (90%)
Hepatocellular adenoma or
carcinoma
5/50 (10%)
35/50 (70%)
41/50 (82%)
46/50 (92%)
Male Crj:BDFl mice
0 mg/kg-d
49 mg/kg-d
191 mg/kg-d
677 mg/kg-d
Liver
Hepatocellular adenoma
9/50 (18%)
17/50 (34%)
23/50 (46%)
11/50 (22%)
Hepatocellular carcinoma
15/50 (30%)
20/50 (40%)
23/50 (46%)
36/50 (72%)
Hepatocellular adenoma or
carcinoma
23/50 (46%)
31/50 (62%)
37/50 (74%)
40/50 (80%)
Data quality evaluations for this study were determined to high (see Appendix G).
Table H-8. Tumor Incidence data in in male and female Sherman rats (combined) exposed to 1,4-dioxane via drinking water for 2
years (ad libitum)(fvociba et ai„ 1974)
Endpoint
Dose (mg/kg-d, average of male and female) and incidence (%)
Dose (mg/kg-d):
0 mg/kg-d
14 mg/kg-d
121 mg/kg-d
1307 mg/kg-d
Liver
Hepatic tumors (all types)
2/106 (2%)
0/110 (0%)
1/106 (0.9%)
12/66(18%)
Hepatocellular carcinoma
1/106 (0.9%)
0/110 (0%)
1/106 (0.9%)
10/66(15%)
Cholangiocarcinoma
1/106 (0.9%)
0/110 (0%)
0/106(0%)
0/66(0%)
Cholangioma
0/106 (0%)
0/110 (0%)
0/106(0%)
2/66 (3%)
Nasal turbinates
Squamous cell carcinoma
0/106 (0%)
0/110 (0%)
0/106(0%)
3/66 (5%)
Data quality evaluations for this study were determined to high (see Appendix G).
Table H-9. Tumor Incidence data in male and female B6C3F1 mice, and female Osborne-Mendel rats exposed to 1,4-dioxane via
Species and endpoint
Dose (mg/kg-d) and incidence (%)
Male B6C3F1 mice
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Species and endpoint
Dose (mg/kg-d) and incidence (%)
Dose (mg/kg-d)
0 mg/kg-d
720 mg/kg-d
830 mg/kg-d
Liver
Hepatocellular adenoma
6/49 (12%)
1/50 (2%)
4/47 (9%)
Hepatocellular carcinoma
2/49 (4%)
18/50 (36%)
24/47 (51%)
Hepatocellular adenoma or carcinoma
8/49 (16%)
19/50 (38%)
28/47 (60%)
Female B6C3F1 mice
Dose (mg/kg-d)
0 mg/kg-d
380 mg/kg-d
860 mg/kg-d
Liver
Hepatocellular adenoma
0/50 (0%)
9/48 (19%)
6/37 (16%)
Hepatocellular carcinoma
0/50 (0%)
12/48 (25%)
29/37 (78%)
Hepatocellular adenoma or carcinoma
0/50 (0%)
21/48 (44%)
35/37 (95%)
Female Osborne-Mendel rats
Dose (mg/kg-d)
0 mg/kg-d
350 mg/kg-d
640 mg/kg-d
Nasal turbinate
Squamous cell carcinoma
0/34 (0%)
10/35 (29%)
8/35 (23%)
Liver
Hepatocellular adenoma
0/31 (0%)
10/33 (30%)
11/32 (34%)
Data quality evaluations for B6C3F1 mice (male and female) and OM rats (female) from this study were determined to be low (see Appendix G). Data in for male OM
rats were determined to be unacceptable and are not included in this table.
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Appendix I BENCHMARK DOSE ANALYSIS
U.S. U.S. EPA relied on the following guidance and support documents for data requirements and other
considerations for dose-response modeling: EPA's Benchmark Dose Technical Guidance (U.S. EPA.
2012b). EPA's Methods for Derivation of Inhalation Reference Concentrations and Application of
Inhalation Dosimetry (U.S. EPA... 1994). EPA's Review of the Reference Dose and Reference
Concentration Processes (U.S. EPA. 2002). Guidelines for Carcinogen Risk Assessment (
2005a), and EPA's Recommended Use of Body Weight4 as the Default Method in Derivation of the
Oral Reference Dose (! < <* \ _YU lb).
For studies that had suitable data, dose-response analysis was performed and point of departures (PODs)
were identified. The POD, an estimated dose (expressed in human-equivalent terms) near the lower end
of the observed range without significant extrapolation to lower doses, is used as the starting point for
subsequent extrapolations and analyses. PODs can be a NOAEL or LOAEL for an observed incidence,
or change in level of response, or the lower confidence limit on the dose at the benchmark dose (BMD).
The preferred approach is to use dose response modeling to incorporate as much of the data set as
possible into the analysis to yield a POD. EPA evaluates a range of dose response models thought to be
consistent with underlying biological processes to determine how best to empirically model the dose
response relationship in the range of the observed data. If the procedure fails to yield reliable results,
expert judgment or alternative analyses are used. For example, a model fit may be considered poor if the
goodness-of-fit p value is below a critical value (i.e., <0.1), or the largest scaled residual exceeds 2 in
absolute value [( )) §2.3.5], If none of the models provide a reasonable fit to certain
datasets, the dose-response modeling may be re-done using only data for the lower doses, or the
NOAEL/LOAEL could be used as the POD.
In general, the benchmark response level (BMR) at which the POD is calculated is guided by the
severity of the endpoint. As stated in EPA's Benchmark Dose Technical Guidance (U.S. EPA. 2012b).
EPA does not currently have explicit guidance to assist in making such judgments for the selection of
response levels for most applications (e.g., for calculating reference doses). However, the guidance
provides general principles to consider for different types of data. For dichotomous data, a response
level of 10% extra risk is generally used for minimally adverse effects, 5% or lower for more severe
effects. For continuous data, a response level is ideally based on an established definition of biologic
significance. In the absence of such definition, one control standard deviation from the control mean is
often used for minimally adverse effects, one-half standard deviation for more severe effects. For cancer
data, U.S. EPA's Guidelines for Carcinogen Risk Assessment (U.S. EPA. 2005a) address BMRs for
cancer risk estimation. Standard values near the low end of the observable range are generally used (for
example, 10% extra risk for cancer bioassay data, 1% for epidemiologic data, lower for rare cancers).
For 1,4-dioxane, both linear and nonlinear approaches were evaluated for the human health endpoints
because comparing both approaches can provide insights into uncertainties related to model choice and
mechanisms. Information regarding the degree of change in the selected endpoints that is considered
biologically significant was not available. Therefore, a BMR of 10% extra risk was selected under the
assumption that it represents a minimally biologically significant response level ( >).
Decision trees summarizing the general progression of steps in a BMD/BMDL calculation are presented
below.
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Noncancer
Basic statistical background and guidance on choosing a model structure for the data being analyzed,
fitting models, comparing models, and calculating confidence limits to derive a BMDL to use as a POD
is outlined in EPA's Benchmark Dose Technical Guidance ( )) Sections 2.3.9 and 2.5.
Empirical models that provide the best fit to the dose-response data are typically used in the absence of
data to develop a biologically-based model. While these models are empirical, parameters are typically
constrained on some of them for the purposes of strengthening the biological plausibility of the results
(i.e., many toxic effects exhibit a monotonic dose-response), and to prevent imprecise BMDs/BMDLs
resulting from steeply supralinear models lYIJ.S. EPA. 2012b) §2.3.3.3], Consistent with EPA's
Benchmark Dose Technical Guidance (U. S. EPA. 2012b). initial runs of the LogProbit and
Dichotomous Hill models did not constrain their slope parameter, whereas initial runs of the Gamma,
Weibull, and LogLogistic models constrained their slope or power parameters to be >1.
For each candidate endpoint/study the following steps were taken:
1) Goodness-of-fit was assessed for all models ITU.S. EPA., 20.1.2b) §2.3.5]
a. Models having a goodness-of-fit p value of less than 0.1 were rejected.19
b. Models not adequately describing the dose response relationship (especially in the low-
dose region) were rejected based on examining the dose-group scaled residuals20 and
graphs of models and data.
The models that remained (after rejecting those that did not meet the recommended default statistical
criteria for adequacy and fail in visual inspection of model fit) were used for determining the BMDL.
The default selection criteria are listed below [( 21012b) §2.3.9]:
2) If the BMDL estimates from the remaining models were sufficiently close (generally defined as
being within threefold, as in the case of this assessment), it was assumed there was no particular
influence of the individual models on the estimates. In this case, the model with the lowest AIC
was chosen.
3) If the BMDL estimates from the remaining models were not sufficiently close, it was assumed
there was some model dependence (i.e., model uncertainty) of the estimate. In this case, if there
was no clear remaining biological or statistical basis on which to choose among them, the lowest
BMDL was selected as a reasonable conservative estimate ((U.S. EPA. 2012b) Section 2.3.9).
4) In some cases, modeling attempts did not yield useful results. When this occurred, the NOAEL
(or LOAEL) was used as a candidate POD.
Modeling considerations specific to noncancer data
19 For the yl goodness-of-fit test and a p-value of a, the critical value is the 1- a percentile of the yl distribution at the
appropriate degrees of freedom. Models are rejected if there are large values of yl corresponding to p-values less than 0.1, the
limiting probability of a Type I error (false positive) selected for this purpose.
20 Scaled residuals reported by BMDS for dichotomous responses are defined as (Observed - Expected)/SE, where
"Expected" is the predicted number of responders and SE equals the estimated standard error of that predicted number. For
dichotomous models, the estimated standard error is equal to V[n xppx(l-pp)], where n is the sample size, and p is the
model-predicted probability of response. Model fit is considered questionable if the scaled residual value for any dose group,
particularly the control or low dose group, is greater than 2 or less than -2.
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The highest dose in the oral study by Kano et al. (2009) was removed from all analyses because of
concerns regarding decreased water intake rate at the highest dose. Data in male OM rats from the NCI
3} study were not modeled, because the data quality was determined to be unacceptable (see
Appendix G).
For inhalation data that were not amenable to BMD modeling, NOAECs/NOAELs and
LOAECs/LOAELs were obtained from Appendix G.
Cancer
Following EPA's Benchmark Dose Technical Guidance ( 012b) Sections 2.3.9 and 2.5, and
EPA" s Choosing Appropriate Stage of a Multistage Model for Cancer Modeling ( ^ 14b):
1. All orders of the Multistage model up to two less than the number of dose groups were fit (e.g.,
up to model order k-2 if there are k dose groups).
a. If all parameter (y, pi, .., pk-2) estimates were positive, then the model with the lowest
AIC was chosen as the best-fitting model if at least one of the models provides an
adequate fit to the data. Consistent with EPA's guidance when there is an a priori reason
to prefer a specific model(s) ITlJ.S. EPA. 20.1.2b) §2.3.5 and §2.3.9], Multistage models
having a goodness-of-fit p value of less than 0.05 were rejected.
b. Otherwise (i.e., if any parameter is estimated to be zero and is thus at a boundary), the
following procedure (2) was followed:
2. Model fits of order 1 and 2 (linear and quadratic, respectively) were examined for adequate fit.
The linear model parameters (y, pi), and the quadratic model parameters (y, pi, P2) were
examined.
a. If only one of the models exhibited adequate fit, that model was chosen.
b. If both models exhibited adequate fit:
i. The model with the lowest AIC was chosen if all of the parameters (y , pi,and P2)
were positive.
ii. Otherwise, the model with the lower BMDL (more health protective) was chosen.
If the BMD/BMDL ratio is larger than 3, the matter was referred to EPA
statisticians and health assessors for a decision.
The MS-Combo model (which is implemented using BMDS) was utilized to calculate the dose
associated with a specified composite risk (the risk of developing any combination of tumors at any
site), under the assumption that tumors in different tissues arise independently. MS-Combo is a peer-
reviewed (Versar, 2011) module within BMDS that employs a combined probability function to
calculate composite risk using the best-fitting BMDS multistage model parameters determined for each
individual tumor.
Modeling considerations specific to cancer data for the oral route
The 2013c) IRIS assessment applied all available noncancer models and did not evaluate
multiple tumors using MS-Combo. Thus, points of departure differ from the U.S. EPA. (2.013c) IRIS
assessment.
Sub cutis fibroma in male rats exposed via drinking water from the Kano et al. (2009) study exhibited a
statistically significant (p<0.01) increasing trend by the Peto test. It should be noted that these data were
not used for dose-response of the oral portion of the IRIS assessment. However, data
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for subcutis fibroma from the Kasai et al. (2.009) study was modeled for the inhalation update of the
EPA. (2013c) IRIS assessment.
Female mouse hepatocellular carcinoma data from Kano et al. (2009) were not modeled due to the
difficulties that were previously noted in the U.S. EPA. (2013c) IRIS assessment. Specifically, this
endpoint exhibited a low control group incidence, and a high (70% incidence) response rate at the lowest
dose followed by a plateau. While the U.S. EPA. (2013c) IRIS assessment did perform BMD modeling
on these data, it was necessary to increase the BMR, omit the highest dose group, and apply a non-
multistage model.
For studies that observed liver tumors, which were amenable to BMD modeling, MS-Combo was
applied twice to evaluate uncertainties related to model choice and mechanisms: one MS-Combo model
run included all tumors, while an additional model run excluded liver tumors.
The Kano et al. (2009) data are based on the data of the laboratory report by JBRC (1998). which were
also published as conference proceedings (Yamazaki et al.. 1994). There are data discrepancies between
these publications. This is explained in Appendix F of the U.S. EPA. (2013 c) IRIS assessment. It was
determined that the differences in tumor counts have a negligible impact on the final PODs. The
analysis presented here assumes that the data by Kano et al. (2009) (which was used in the IRIS
assessment) are a suitable representation of the 2-year drinking water bioassay data.
Data in male OM rats from the NE 8) study were not modeled, because the data quality was
determined to be unacceptable (see Appendix G).
Modeling considerations specific to cancer data for the inhalation route
The U.S. EPA. (2013c) IRIS assessment applied MS-Combo to the inhalation cancer data (the model was
not available during the development of the oral assessment, which preceded the inhalation update).
However, MS-Combo under BMDS version 2.704 produced slightly different results from the U.S. EPA.
(2013c) IRIS assessment. This was due to differences in multistage model selection using current
guidance ( 014b. 2012b). and differences in software versions (MS-Combo under BMDS
version 2.2Beta was used for the U.S. EPA. (2013c) IRIS assessment).
MS-Combo was applied to the BMD modeling results from the Kasai et al. (2009) study. To evaluate
uncertainties related to model choice and mechanisms, MS-Combo was applied twice: one model run
included all tumors, while an additional model run excluded liver tumors.
Incidences of tumors in rats (hepatocellular adenomas or carcinomas) from the Kasai et al. (2009) study
were corrected to account for rats that exhibited both adenomas and carcinomas. These data were
provided to U.S. EPA by a personal communication with the study author (Kasai. 2008). and were
extracted from Table 5-8 of 013c).
The high concentration group for subcutis fibroma was omitted from the dose-response analysis. As
noted in the U.S. 1\ \ tP \ 12013c) IRIS assessment, the incidence data for subcutis fibroma were
monotonic non-decreasing functions of dose for the control (0 ppm), low (50 ppm), and mid-dose (250
ppm); however, the incidence rate at the high dose (1,250 ppm) was lower than observed at the mid-
dose. No BMDS model exhibited a reasonable fit to the data without dropping the high dose.
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BMDS Summary of Centrilobular necrosis of the liver in male F344/DuCrj rats (Kasat et at.. 2.009)
Table 1-1. Summary of BMD Modeling Results for Centrilobular necrosis of the liver in male
F344/DuCrj rats i
Kasai et al.. 2009
Model3
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
Gammab
0.510
129.69
502
308
Lowest BMDL model chosen
when adequate-fitting models
are not sufficiently close in
range.
Dichotomous-Hill
0.746
130.40
220
59.6
Logistic
0.279
131.04
795
609
LogLogistic
0.568
129.47
453
259
Probit
0.299
130.89
756
567
LogProbit
0.952
130.31
232
44.0
Wcibuir
Quantal-Lineard
0.510
129.69
502
308
Multistage 3oe
Multistage 2of
0.510
129.69
502
308
The restricted dichotomous Hill results are reported here because the unrestricted dichotomous Hill model resulted in zero
degrees of freedom (number of estimated parameters equal to number of dose groups), precluding the derivation of a p-value
and AIC for that model.
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were -0.01, 0.03, -0.04, 0.02,
respectively.
b The Gamma model may appear equivalent to the Weibull model, however differences exist in digits not displayed in the table.
This also applies to the Multistage 3° model. This also applies to the Multistage 2° model. This also applies to the Quantal-
Linear model.
c For the Weibull model, the power parameter estimate was 1. The models in this row reduced to the Quantal-Linear model.
d The Quantal-Linear model may appear equivalent to the Gamma model, however differences exist in digits not displayed in
the table. This also applies to the Multistage 3° model. This also applies to the Multistage 2° model.
e For the Multistage 3° model, the beta coefficient estimates were 0 (boundary of parameters space). The models in this row
reduced to the Multistage 2° model.
f The Multistage 2° model may appear equivalent to the Gamma model, however differences exist in digits not displayed in the
table. This also applies to the Weibull model. This also applies to the Quantal-Linear model.
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LogProbit Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
LogProbit
. BljlDL
Log-Logistic Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Log-Logistic
i j?MDL| i
Figure 1-1. Plot of incidence rate by dose with fitted curve for the unrestricted LogProbit (left) and
restricted LogLogistic (right) models for Centrilobular necrosis of the liver in male F344/DuCrj
rats (Kasai et al., 2009); dose shown in ppm. Restricted LogLogistic has the lowest AIC but
exhibits higher residuals for all dose groups.
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LogProbit Model. (Version: 3.4; Date: 5/21/2017)
The form of the probability function is: P[response] = Background + (1-Background) *
CumNorm(Intercept+Slope*Log(Dose)),where CumNormQ is the cumulative normal distribution
function
Slope parameter is not restricted
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 232.245
BMDL at the 95% confidence level = 43.9928
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
background
0.0201374
0.02
intercept
-2.9660E+00
-2.9443E+00
slope
0.309189
0.305751
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-62.15
4
Fitted model
-62.15
3
0.00361134
1
0.95
Reduced
model
-69.3
1
14.305
3
0
AIC: = 130.305
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0201
1.007
1
50
-0.01
50
0.0589
2.943
3
50
0.03
250
0.1221
6.105
6
50
-0.04
1250
0.2389
11.946
12
50
0.02
ChiA2 = 0 d.f = 1 P-value = 0.9521
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1.1 BMDS Summary of Squamous cell metaplasia of respiratory
epithelium in male F433/DuCrj rats (KasaietaLi2009)
Table 1-2. Summary of BMD Modeling Results for Squamous cell metaplasia of respiratory
epithelium in male F433/DuCrj rats (Kasai et al., 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
Gamma
0.868
81.687
218
150
Lowest AIC. BMDL estimates
for models not excluded (based
on goodness-of-fit p values
less than 0.1, or high scaled
residuals) are sufficiently
close.
Dichotomous-Hill
1.000
83.189
241
162
Logistic
0.0464
89.415
370
289
LogLogistic
0.914
81.525
218
158
Probit
0.0779
87.936
338
268
LogProbit
0.989
81.230
218
160
Weibull
0.768
82.124
218
145
Multistage 3°
0.619
82.688
231
140
Multistage 2°
0.619
82.688
231
141
Quantal-Linear
0.0198
92.922
87.7
68.8
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were 0, -0.14, 0.03, -0.02,
respectively.
LogProbit Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
1
0.8
0.2
O
LogProbit
600
dose
14:41 08/10 2018
Figure 1-2. Plot of incidence rate by dose with fitted curve for LogProbit model for Squamous cell
metaplasia of respiratory epithelium in male F433/DuCrj rats (Kasai et al., 2009); dose shown in
ppm.
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LogProbit Model. (Version: 3.4; Date: 5/21/2017)
The form of the probability function is: P[response] = Background + (1-Background) *
CumNorm(Intercept+Slope*Log(Dose)),where CumNormQ is the cumulative normal distribution
function
Slope parameter is not restricted
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 217.79
BMDL at the 95% confidence level = 159.619
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
background
0
0
intercept
-8.8618E+00
-6.7651E+00
slope
1.40803
1.09006
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-38.59
4
Fitted model
-38.62
2
0.041197
2
0.98
Reduced
model
-113.55
1
149.916
3
<.0001
AIC: = 81.23
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
50
0.0004
0.02
0
50
-0.14
250
0.1384
6.922
7
50
0.03
1250
0.8808
44.038
44
50
-0.02
ChiA2 = 0.02 d.f = 2 P-value = 0.9894
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1.2 BMDS Summary of Squamous cell hyperplasia of respiratory
epithelium in male F433/DuCrj rats
Table 1-3. Summary of BMD Modeling Results for Squamous cell hyperplasia of respiratory
epithelium in male F433/DuCrj rats (Masai et ai.. 2009)
Model3
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
Gamma
0.961
63.981
761
487
Lowest AIC. BMDL estimates
for models not excluded (based
on goodness-of-fit p values
less than 0.1, or high scaled
residuals) are sufficiently
close.
Note: Dichotomous Hill did
not converge
Dichotomous-Hill
1.000
65.844
316
280
Logistic
0.582
65.208
1013
847
LogLogistic
0.960
63.988
760
473
Probit
0.631
65.018
962
786
LogProbit
0.987
63.893
704
437
Weibull
0.956
64.001
776
486
Multistage 3ob
0.926
64.099
812
481
Multistage 2oc
0.926
64.099
812
481
Quantal-Linear
0.795
63.342
679
429
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were 0, -0.62, -0.67, 0.44,
respectively.
b The Multistage 3° model may appear equivalent to the Multistage 2° model; however, differences exist in digits not displayed
in the table.
c The Multistage 2° model may appear equivalent to the Multistage 3° model; however, differences exist in digits not displayed
in the table.
For results based on a power or slope parameter that hits the bound of 1, EPA (201.2b) states (footnote 10) ".. .the nominal
coverage of the confidence interval is not exact (asymptotically) and could be much less than intended if the true (unknown)
parameter is <1, and this should also be reported"
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Quantal Linear Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
.35
.3
.25
.2
5
1
.05
0
0 200 400 600
dose
11:08 03/18 2019
Figure 1-3. Plot of incidence rate by dose with fitted curve for Quantal-Linear model for
Squamous cell hyperplasia of respiratory epithelium in male F433/DuCrj rats; dose shown in
ppm.
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Quantal Linear Model using Weibull Model (Version: 2.17; Date: 6/23/2017)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
slope*dose)]
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 679.311
BMDL at the 95% confidence level = 429.287
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0.0192308
Slope
0.000155099
0.000174603
Power
n/a
1
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-29.92
4
Fitted model
-30.67
1
1.49818
3
0.68
Reduced
model
-42.6
1
25.3487
3
<.0001
AIC: =63.3423
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
50
0.0077
0.386
0
50
-0.62
250
0.038
1.902
1
50
-0.67
1250
0.1762
8.812
10
50
0.44
ChiA2 =1.03 d.f = 3 P-value = 0.7945
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1.3 Benchmark dose analysis of respiratory metaplasia of the olfactory
epithelium in the nasal cavity of male F344/DuCrj rats (Kasai et al,
2009)
As reported in the EPA 1,4-dioxane IRIS assessment, no models in the software provided adequate fits
to the data for the incidence of respiratory metaplasia of the olfactory epithelium in male rats (%2 p >
0.1) when all dose groups are included in the analysis (( 13c) Table F-8). While the model
uncertainty associated with data for which the response at the lowest non-control dose (34/50) is 46%
higher than the control response (11/50) was acknowledged, the IRIS assessment determined that
modeling this dataset without the high dose group would be consistent with BMD Technical Guidance
Document ( 2012b). As a result, all models were fit to the incidence data with the highest dose
group omitted ((U.S. EPA. 2013c). Table F-9). Using BMDS 2.1.1, it was determined that, of the
adequately fitting models (p-value > 0.1), "the AIC values for gamma, multistage, quantal-linear, and
Weibull models in Table F-9 are equivalent and the lowest and, in this case, essentially represent the
same model" and, because they all result in the same BMDL value of 4.7 ppm, "consistent with the
Benchmark Dose Technical Guidance ( 012b). any of them with equal AIC values (gamma,
multistage, quantal-linear, or Weibull) could be used to identify a POD for this endpoint." This report
confirms these findings of BMDS 2.1.1 for this dataset using the latest version of BMDS, BMDS 3.1.
The table below shows the BMR, BMD, BMDL, p-value, AIC and scaled residual for the dose-group
nearest the BMD (the 50 ppm dose group) for the suite of BMDS dichotomous models available in
BMDS 3.1 using standard model restriction settings (default settings in BMDS 3.1) recommended in the
EPA BMD technical guidance ( )12b). The Gamma, Multistage and Weibull models all
converge to the same BMD and goodness-of-fit results, the same (lowest) AIC value and the same
BMDL estimate of 4.7 ppm, which is virtually the same result obtained from BMDS 2.1.1 in the 2013
IRIS assessment ((U.S. EPA. 2013 c) Table F-9). Several aspects of this analysis support dropping the
highest dose group data, including the inability to adequately fit the dose-response data for all four dose
groups (see (U.S. EPA. 2013c) Table F-8), acceptable fit (p-value >0.1) to the dose-response data when
the highest dose group is removed (see table summary of BMD modeling results below), visual
inspection of the plots for the acceptable models with the three models with the lowest AIC (see detailed
results for individual Gamma, Multistage and Weibull models below), and the low scaled residuals (-
0.106) reported for these models at the (50 ppm) dose group nearest the BMD. In general, models that
result in low scaled residuals for dose groups near the BMD are preferred (( 012b) Sections
2.3.5 and 2.5.). The concern over model uncertainty due to the nearly 10-fold difference between the
BMD and the lowest non-control dose group is partially offset in this case by the fact that six different
models, including three saturated models (models for which p-values could not be derived due to the use
of as many or more parameters than dose groups, resulting in 0 degrees of freedom), reported BMDLs
within a very small range of 3-5 ppm.
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Summary of BMD modeling results for respiratory metaplasia of olfactory epithelium in the nasal
cavity of male F344/DuCrj rats i
Kasai et a
[.. 2009)1
Model
Restriction
BM
R
BMD
(ppm)
BMDL
(ppm)
P - Value
AIC
Scaled
Residual
for Dose
Group near
BMD
BMDS Recommendation Notes
Gamma
Restricted
0.1
6.468
4.737
0.581
129.46
-0.106
Multistage
Degree 22
Restricted
0.1
6.468
4.737
0.581
129.46
-0.106
Lowest AIC
BMDL lOx lower than lowest non-zero
dose
Multistage
Degree 1
Restricted
0.1
6.468
4.737
0.581
129.46
-0.106
Weibull
Restricted
0.1
6.468
4.737
0.581
129.46
-0.106
Log-Logistic
Restricted
0.1
14.207
3.771
NA
131.18
-1.24E-05
BMDL lOx lower than lowest non-zero
dose
d.f.=0, saturated model (Goodness of fit test
cannot be calculated)
Dichotomous
Hill
Restricted
0.1
14.204
3.771
NA
131.18
-0.0002
Log-Probit
Unrestricted
0.1
12.211
3.075
NA
131.18
-8.44E-07
Logistic
Unrestricted
0.1
12.520
9.345
0.012
133.58
-1.031
Goodness of fit p-value <0.1
Probit
Unrestricted
0.1
15.288
11.687
0.007
136.12
-1.511
1 High dose response was not included because of inadequate model fits and the fact that maximal response was reached at the mid-dose.
2 Multistage 2 is the same model as Multistage 1 due to parameter convergence.
Data
Respiratory metaplasia
Respiratory metaplasia of the olfactory epithelium (male F344 rats,
Kasai et al.. 2009)
Dose
N
Incidence
[Dose]
[N]
[Incidence]
0
50
11
50
50
34
250
50
49
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Restricted Gamma
User Input
Info
Model
Restricted Gamma
Dataset
Name
Respiratory metaplasia
User
notes
Respiratory metaplasia
of olfactory epithelium
(male F344 rats, Kasai et
al., 2009)
Model Options
Risk Type
Extra Risk
BMR
0.1
Confidence
Level
0.95
Background
Estimated
Model Data
Dependent
Variable
ppm
Independent
Variable
Respiratory
metaplasia
Total # of
Observations
3
Model Results
Benchmark Dose
BMD
6.468479372
BMDL
4.737250177
BMDU
15.58341107
AIC
129.46256
P-value
0.581473595
D.O.F.
1
Chi2
0.303858409
Model Parameters
# of Parameters
4
Variable
Estimate
g
0.226248926
a
1
b
0.016288297
Goodness of Fit
Dose
Estimated
Probability
Expected
Observed
Size
Scaled
Residual
0
0.226248926
11.31244628
11
50
-0.105608
50
0.657306883
32.86534417
34
50
0.3380978
250
0.986813734
49.34068668
49
50
-0.422369
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User Input
Analysis of Deviance
Model
Log Likelihood
# of Parameters
Deviance
Test d.f.
P Value
Full Model
-62.59082662
0
_
_
_
Fitted Model
-62.73127999
2
0.28090675
1
0.5961075
Reduced Model
-99.1058899
1
73.0301266
2
<0.0001
Frequentist Gamma Model with BMR of 10% Extra Risk for the
BMD and 0.95 Lower Confidence Limit for the BMDL
0.9
0.8
0.7
| 0.6
g. 0.5
t/i
0.4
0.3
0.2
200
250
0
50
100
150
Dose
Estimated Probability Response at BMD • Data BMD BMDL
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Restricted Multistage 1
User Input
Info
Model
Restricted Multistage 1
Dataset
Name
Respiratory metaplasia
User
notes
Respiratory metaplasia
of olfactory epithelium
(male F344 rats, Kasai et
al., 2009)
Model Options
Risk Type
Extra Risk
BMR
0.1
Confidence
Level
0.95
Background
Estimated
Model Data
Dependent
Variable
ppm
Independent
Variable
Respiratory
metaplasia
Total # of
Observations
3
Model Results
Benchmark Dose
BMD
6.468474487
BMDL
4.737235003
BMDU
9.087463619
AIC
129.46256
P-value
0.581473253
D.O.F.
1
Chi2
0.303858959
Model Parameters
# of Parameters
2
Variable
Estimate
g
0.226248831
bl
0.01628831
Goodness of Fit
Dose
Estimated
Probability
Expected
Observed
Size
Scaled
Residual
0
0.226248831
11.31244157
11
50
-0.105606
50
0.657307053
32.86535263
34
50
0.3380953
250
0.986813773
49.34068863
49
50
-0.422372
Analysis of Deviance
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User Input
Model
Log Likelihood
# of Parameters
Deviance
Test d.f.
P Value
Full Model
-62.59082662
0
_
_
_
Fitted Model
-62.73127999
2
0.28090675
1
0.5961075
Reduced Model
-99.1058899
1
73.0301266
2
<0.0001
1
Frequentist Multistage Degree 1 Model with BMR of 10% Extra
Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
0.9
0.8
0.7
8 0.6
g. 0.5
tn
£ 0.4
0.3
n 9 i
u.z
0.1
0
50 100 150 200 250
Dose
Estimated Probability Response at BMD Linear Extrapolation • Data BMDL
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Restricted Weibull
User Input
Info
Model
Restricted Weibull
Dataset
Name
Respiratory metaplasia
User
notes
Respiratory metaplasia
of olfactory epithelium
(male F344 rats, Kasai et
al., 2009)
Model Options
Risk Type
BMR
Confidence
Level
Background
Extra Risk
0.1
0.95
Estimated
Model Data
Dependent
Variable
Independent
Variable
Total # of
Observations
ppm
Respiratory
metaplasia
3
Model Results
Benchmark Dose
BMD
6.468485055
BMDL
4.737254339
BMDU
13.26149794
AIC
129.46256
P-value
0.581473996
D.O.F.
1
Chi2
0.303857764
Model Parameters
# of Parameters
3
Variable
Estimate
g
0.226249018
a
1
b
0.016288283
Goodness of Fit
Dose
Estimated
Probability
Expected
Observed
Size
Scaled
Residual
0
0.226249018
11.31245092
11
50
-0.105609
50
0.657306679
32.86533396
34
50
0.3381008
250
0.986813688
49.3406844
49
50
-0.422365
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User Input
Analysis of Deviance
Model
Log Likelihood
# of Parameters
Deviance
Test d.f.
P Value
Full Model
-59.3166114
0
-
-
-
Fitted Model
-59.31661362
2
4.4538E-06
2
0.9999978
Reduced Model
-123.8201329
1
129.007043
3
<0.0001
1
Frequentist Weibull Model with BMR of 10% Extra Risk for the
BMD and 0.95 Lower Confidence Limit for the BMDL
0.9
0.8
0.7
8 0.6
I 0.5
tn
& 0.4
0.3
n 9 i
u.z
0.1
0
50 100 150 200 250
Dose
Estimated Probability Response at BMD • Data ^^—BMD BMDL
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1.4 BMDS Summary of Hydropic change (lamina propria) (Kasai et al.,
2009)
Table 1-4. Summary of BMD Modeling Results for Hydropic change (lamina propria) (Kasai et
al.. 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
Gamma
2.00E-
04
98.344
52.0
28.8
Lowest AIC. BMDL estimates
for models not excluded (based
on goodness-of-fit p values
less than 0.1, or high scaled
residuals) are sufficiently
close.
Dichotomous-Hill
1.000
91.894
73.1
49.3
Logistic
0
117.96
89.3
70.6
LogLogistic
0.682
90.539
68.5
46.8
Probit
0
136.59
92.6
74.4
LogProbit
0.346
91.588
63.1
44.6
Weibull
0.0033
100.23
39.1
24.0
Multistage 3ob
Multistage 2°
Quantal-Linear
0.0256
99.348
28.8
22.7
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were 0, -0.33, 0.32, -0.74,
respectively.
b For the Multistage 3° model, the beta coefficient estimates were 0 (boundary of parameters space). The models in this row
reduced to the Multistage 2° model.
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1
0.8
M °-6
= 1
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 68.5266
BMDL at the 95% confidence level = 46.7808
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
background
0
0
intercept
-1.2132E+01
-1.1575E+01
slope
2.3501
2.19638
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-42.95
4
Fitted model
-43.27
2
0.645129
2
0.72
Reduced
model
-136.94
1
187.976
3
<.0001
Log-Logistic Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Log-Logistic
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AIC: =90.5388
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
50
0.0503
2.515
2
50
-0.33
250
0.6994
34.969
36
50
0.32
1250
0.9903
49.515
49
50
-0.74
ChiA2 = 0.77 d.f = 2 P-value = 0.6819
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1.5 BMDS Summary of Nasal cavity squamous cell carcinoma (male
F344/DuCrj rats) (Kasai et al., 2009)
Table 1-5. Summary of BMD Modeling Results for Nasal cavity squamous cell carcinoma (male
F344/DuCrj rats) (Kasai et al., 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
One
0.961
49.031
1107
630
Lowest AIC. All parameter
estimates positive in both models.
Two
0.909
50.828
1087
642
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were 0, -0.49, -0.16,0.18,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
0.25
0.2
0.15
0.1
0.05
O
Multistage Cancer
Linear extrapolation
600
dose
09:07 08/09 2018
Figure 1-5. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Nasal cavity squamous cell carcinoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown in
ppm.
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Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 1107.04
BMDL at the 95% confidence level = 629.948
BMDU at the 95% confidence level = 2215.11
Taken together, (629.948, 2215.11) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000158743
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0
Beta(l)
0.0000951733
0.000104666
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-23.25
4
Fitted model
-23.52
1
0.534383
3
0.91
Reduced
model
-30.34
1
14.1894
3
0
AIC: =49.0308
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
50
0.0047
0.237
0
50
-0.49
250
0.0235
1.176
1
50
-0.16
1250
0.1122
5.608
6
50
0.18
ChiA2 = 0.3 d.f = 3 P-value = 0.9607
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1.6 BMDS Summary of Zymbal gland adenoma (male F344/DuCrj rats)
(Kasai et al., 2009)
Table 1-6. Summary of BMD Modeling Results for Zymbal gland adenoma (male F344/DuCrj
rats) (Kasai et al., 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
One
0.800
31.663
1975
958
Lowest BMDL. Some parameter
values were zero for both models.
Two
0.982
30.217
1435
999
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were 0, -0.36, -0.82, 0.45,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.2
0.15
0.1
0.05
O
O
500
1000
1500
2000
Figure 1-6. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Zymbal gland adenoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown in ppm.
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Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 1974.78
BMDL at the 95% confidence level = 957.63
BMDU at the 95% confidence level = 5118.88
Taken together, (957.63, 5118.88) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000104424
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0
Beta(l)
0.0000533531
0.0000700345
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-13.94
4
Fitted model
-14.83
1
1.78598
3
0.62
Reduced
model
-19.61
1
11.3387
3
0.01
AIC: =31.6629
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
50
0.0027
0.133
0
50
-0.36
250
0.0132
0.662
0
50
-0.82
1250
0.0645
3.226
4
50
0.45
ChiA2 = 1 d.f = 3 P-value = 0.8004
1.7 MS-Combo portal of entry tumors
Portal of entry tumors (nasal cavity squamous cell carcinoma, zymbal gland adenoma)
Output information
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Tumor Output Directory
C:\Users\
\Documents\MODELS\14dioxane\inhalation\
Tumor Output File Name
kasai noliv POE.out
Combined BMD and BMDL Calculations
Combined Log-Likelihood
-38.34685652
Combined Log-likelihood Constant
32.84040568
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
709.372
BMDL
448.544
Multistage Cancer Slope Factor
0.000222944
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -38.346856517733208
Combined Log-likelihood Constant 32.840405681643567
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 709.372
BMDL = 448.544
BMDU = 1218.18
Multistage Cancer Slope Factor = 0.000222944
1.8 BMDS Summary of Hepatocellular adenoma or carcinoma (male
F344/DuCrj rats) (Kasai et al., 2009)
Table 1-7. Summary of BMD Modeling Results for Hepatocellular adenoma or carcinoma (male
F344/DuCrj rats) (Kasai et al., 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
One
0.693
127.86
253
182
Lowest AIC. All parameter
estimates positive in both models.
Two
0.764
129.16
377
190
a Selected model in bold; scaled residuals for selected model lordoses 0, 50, 250, and 1250 ppm were 0.16, 0.1, -0.76, 0.34,
respectively.
Page 358 of 407
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Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.6
0.5
0.4
0.3
0.2
0.1
0
0
200
400
600
800
1000
1200
Figure 1-7. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenoma or carcinoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown in
ppm.
Page 359 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 252.799
BMDL at the 95% confidence level = 182.256
BMDU at the 95% confidence level = 371.457
Taken together, (182.256, 371.457) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000548678
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.0170678
0.00480969
Beta(l)
0.000416776
0.0004548
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-61.53
4
Fitted model
-61.93
2
0.792109
2
0.67
Reduced
model
-82.79
1
42.5066
3
<.0001
AIC: = 127.86
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0171
0.853
1
50
0.16
50
0.0373
1.867
2
50
0.1
250
0.1143
5.716
4
50
-0.76
1250
0.4162
20.81
22
50
0.34
ChiA2 = 0.73 d.f = 2 P-value = 0.6928
Page 360 of 407
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1.9 BMDS Summary of Renal cell carcinoma (male F344/DuCrj rats)
(Kasai et al., 2009)
Table 1-8. Summary of BMD Modeling Results for Renal cell carcinoma (male F344/DuCrj rats)
(Kasai et al., 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
One
0.800
31.663
1975
958
Lowest BMDL. Some parameter
values were zero for both models.
Two
0.982
30.217
1435
999
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were 0, -0.36, -0.82, 0.45,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.2
0.15
0.1
0.05
O
O
500
1000
1500
2000
Figure 1-8. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Renal cell carcinoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown in ppm.
Page 361 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 1974.78
BMDL at the 95% confidence level = 957.63
BMDU at the 95% confidence level = 5118.88
Taken together, (957.63, 5118.88) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000104424
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0
Beta(l)
0.0000533531
0.0000700345
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-13.94
4
Fitted model
-14.83
1
1.78598
3
0.62
Reduced
model
-19.61
1
11.3387
3
0.01
AIC: =31.6629
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
50
0.0027
0.133
0
50
-0.36
250
0.0132
0.662
0
50
-0.82
1250
0.0645
3.226
4
50
0.45
ChiA2 = 1 d.f = 3 P-value = 0.8004
Page 362 of 407
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1.10 BMDS Summary of Peritoneal mesothelioma (male F344/DuCrj
rats) (Kasai et al., 2009)
Table 1-9. Summary of BMD Modeling Results for Peritoneal mesothelioma (male F344/DuCrj
rats) (Kasai et al., 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
One
0.851
155.43
82.2
64.4
Lowest AIC. All parameter
estimates positive in both models.
Two
0.805
157.17
96.2
65.1
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were 0.25, -0.33, -0.29, 0.26,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
1
Multistage Cancer
Linear extrapolation
0.8
0.6
0.4
0.2
O
O
200
400
600
800
1000
1200
Figure 1-9. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Peritoneal mesothelioma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown in ppm.
Page 363 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 82.2057
BMDL at the 95% confidence level = 64.3808
BMDU at the 95% confidence level = 107.497
Taken together, (64.3808, 107.497) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00155326
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.033631
0.0172414
Beta(l)
0.00128167
0.00135351
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-75.55
4
Fitted model
-75.72
2
0.326905
2
0.85
Reduced
model
-123.01
1
94.9105
3
<.0001
AIC: = 155.433
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0336
1.682
2
50
0.25
50
0.0936
4.681
4
50
-0.33
250
0.2986
14.928
14
50
-0.29
1250
0.8053
40.265
41
50
0.26
ChiA2 = 0.32 d.f = 2 P-value = 0.8509
Page 364 of 407
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1.11 BMDS Summary of Mammary gland fibroadenoma (male
F344/DuCrj rats) (Kasai et al., 2009)
Table 1-10. Summary of BMD Modeling Results for Mammary gland fibroadenoma (male
F344/DuCrj rats) (Kasai et al., 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
One
Two
0.790
86.290
1635
703
All (equivalent) models provide
adequate fit.
a Selected model in bold; scaled residuals for selected model for doses 0, 50, 250, and 1250 ppm were -0.47, 0.2, 0.43, -0.15,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.2
0.15
0.1
0.05
O
O
200
400
600
800
1000
1200
1400
1600
dose
09:21 08/09 2018
Figure 1-10. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Mammary gland fibroadenoma (male F344/DuCrj rats) (Kasai et al., 2009); dose shown in ppm.
Page 365 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 1635.46
BMDL at the 95% confidence level = 703.034
BMDU at the 95% confidence level = 1247200000
Taken together, (703.034, 1247200000) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000142241
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.0315836
0.0335609
Beta(l)
0.0000644224
0.0000591694
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-40.9
4
Fitted model
-41.14
2
0.486662
2
0.78
Reduced
model
-42.6
1
3.3895
3
0.34
AIC: = 86.29
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0316
1.579
1
50
-0.47
50
0.0347
1.735
2
50
0.2
250
0.0471
2.353
3
50
0.43
1250
0.1065
5.326
5
50
-0.15
ChiA2 = 0.47 d.f = 2 P-value = 0.7904
Page 366 of 407
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1.12 BMDS Summary of Subcutis fibroma (male F344/DuCrj rats, high
dose dropped) (Kasai et al., 2009)
Table 1-11. Summary of BMD Modeling Results for Subcutis fibroma (male F344/DuCrj rats, high
dose dropped) (Kasai et al., 2009)
Model8
Goodness of fit
BMDiopct
(ppm)
BMDLiopct
(ppm)
Basis for model selection
/?-value
AIC
One
0.525
89.209
142
81.9
Model provides adequate fit.
a Selected model in bold; scaled residuals for selected model for doses 0, 50, and 250 ppm were -0.28, 0.54, -0.2, respectively.
0.35
0.3
0.25
"S 02
% °-15
0.1
0.05
O
O 50 100 150 200 250
dose
09:27 08/09 2018
Figure 1-11. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Subcutis fibroma (male F344/DuCrj rats, high dose dropped) (Kasai et al., 2009); dose shown in
ppm.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
Page 367 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 141.762
BMDL at the 95% confidence level = 81.9117
BMDU at the 95% confidence level = 364.364
Taken together, (81.9117, 364.364) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00122083
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.0262055
0.0327631
Beta(l)
0.00074322
0.000673665
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-42.41
3
Fitted model
-42.6
2
0.389155
1
0.53
Reduced
model
-46.53
1
8.23466
2
0.02
AIC: = 89.2094
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0262
1.31
1
50
-0.28
50
0.0617
3.086
4
50
0.54
250
0.1913
9.566
9
50
-0.2
ChiA2 = 0.41 d.f = 1 P-value = 0.5245
1.13 MS-Combo Systemic (including liver)
Systemic tissue tumors, including liver (hepatocellular adenoma or carcinoma, renal cell carcinoma,
peritoneal mesothelioma, mammary gland fibroadenoma, subcutis fibroma)
Output information
Tumor Output Directory
C :\Users\ \Documents\MODELS\14dioxane\inhalation\
Page 368 of 407
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Tumor Output File Name
kasai systemic wliver.out
Combined BMD and BMDL Calculations
Combined Log-Likelihood
-236.2277997
Combined Log-likelihood Constant
209.8734852
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
41.1654
BMDL
32.7682
Multistage Cancer Slope Factor
0.00305174
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -236.22779970471757
Combined Log-likelihood Constant 209.87348521364675
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 41.1654
BMDL = 32.7682
BMDU = 53.265
Multistage Cancer Slope Factor = 0.00305174
1.14 MS-Combo Systemic (omitting liver)
Systemic tissue tumors, excluding liver (renal cell carcinoma, peritoneal mesothelioma, mammary gland
fibroadenoma, subcutis fibroma)
Output information
Tumor Output Directory
C :\Users\ \Documents\MODELS\14dioxane\inhalation\
Tumor Output File Name
Kasai noliv systemic.out
Combined BMD and BMDL Calculations
Combined Log-Likelihood
-174.2976237
Combined Log-likelihood Constant
154.3867855
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
49.1727
BMDL
37.8668
Multistage Cancer Slope Factor
0.00264083
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -174.29762368979428
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Combined Log-likelihood Constant 154.38678553667452
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 49.1727
BMDL = 37.8668
BMDU = 66.6769
Multistage Cancer Slope Factor = 0.00264083
1.15 MS-Combo portal of entry + systemic (including liver)
Portal of entry tumors (nasal cavity squamous cell carcinoma, zymbal gland adenoma) and systemic
tissue tumors, including liver (hepatocellular adenoma or carcinoma, renal cell carcinoma, peritoneal
mesothelioma, mammary gland fibroadenoma, subcutis fibroma)
Output information
Tumor Output Directory
C: \Users\ \Documents\MODELS\ 14dioxane\inhalation\
Tumor Output File Name
Kasai all.out
Combined BMD and BMDL Calculations
Combined Log-Likelihood
-274.5746562
Combined Log-likelihood Constant
242.7138909
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
38.9076
BMDL
31.2841
Multistage Cancer Slope Factor
0.00319651
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -274.57465622245081
Combined Log-likelihood Constant 242.71389089529029
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 38.9076
BMDL = 31.2841
BMDU = 49.6547
Multistage Cancer Slope Factor = 0.00319651
Page 370 of 407
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1.16 MS-Combo portal of entry + systemic (omitting liver)
Portal of entry tumors (nasal cavity squamous cell carcinoma, zymbal gland adenoma) and systemic
tissue tumors, excluding liver (renal cell carcinoma, peritoneal mesothelioma, mammary gland
fibroadenoma, subcutis fibroma)
Output information
Tumor Output Directory
C: \Users\ \Documents\MODELS\ 14dioxane\inhalation\
Tumor Output File Name
kasai noliv.out
Combined BMD and BMDL Calculations
Combined Log-Likelihood
-212.6444802
Combined Log-likelihood Constant
187.2271912
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
45.985
BMDL
35.8978
Multistage Cancer Slope Factor
0.00278569
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -212.64448020752749
Combined Log-likelihood Constant 187.22719121831807
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 45.985
BMDL = 35.8978
BMDU = 61.1203
Multistage Cancer Slope Factor = 0.00278569
1.17 BMDS Summary of Hepatocellular mixed foci in male F344/DuCrj
rats (Kano et al., 2009)
Table 1-12. Summary of BMD Modeling Results for Hepatocellular mixed foci in male
F344/DuCrj rats (Kano et al., 2009)
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Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
Gammab
Wcibuir
Multistage 2°
Quantal-Linear
0.220
125.50
19.2
11.8
Lowest AIC. BMDL estimates
for models not excluded (based
on goodness-of-fit p values
less than 0.1, or high scaled
residuals) are sufficiently
close.
Logistic
0.107
126.75
30.9
23.3
LogLogistic
0.275
125.20
16.7
9.57
Probit
0.114
126.61
29.4
21.8
LogProbit
(restricted)
0.0555
127.84
33.2
21.8
LogProbit
N/Ad
126.06
7.06
error6
Note: There were not enough degrees of freedom to run the Dichotomous Hill model
a Selected model in bold; scaled residuals for selected model lordoses 0, 11, and 55 mg/kg-d were -0.44, 0.91, -0.42,
respectively.
b For the Gamma and Weibull models, the power parameter estimates were 1 (boundary of parameter space).For the Gamma
model, the power parameter estimate was 1. The model is equivalent to the Quantal-Linear model.
c For the Weibull and Gamma models, the power parameter estimates were 1 (boundary of parameter space).For the Weibull
model, the power parameter estimate was 1. The models in this row reduced to the Quantal-Linear model.
d No available degrees of freedom to calculate a goodness of fit value.
e BMD or BMDL computation failed for this model.
For results based on a power or slope parameter that hits the bound of 1, EPA (2012b) states (footnote 10) "...the nominal
coverage of the confidence interval is not exact (asymptotically) and could be much less than intended if the true (unknown)
parameter is <1, and this should also be reportecT'
Log-Logistic Model, with BMR of 10% Extra Riskfor the BMD and 0.95 Lower Confidence Limit for the BMDL
Log-Logistic
0.4
0.3
0.2
0.1
O
O
10
20
30
40
50
14:08 08/10 2018
Figure 1-12. Plot of incidence rate by dose with fitted curve for LogLogistic model for
Hepatocellular mixed foci in male F344/DuCrj rats (Kano et al., 2009); dose shown in mg/kg-d.
LogLogistic Model. (Version: 2.15; Date: 3/20/2017)
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The form of the probability function is: P[response] = background+(l-background)/[l+EXP(-intercept-
slope*Log(dose))]
Slope parameter is restricted as slope >= 1
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 16.7141
BMDL at the 95% confidence level = 9.56614
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
background
0.054099
0.04
intercept
-5.0135E+00
-4.7777E+00
slope
1
1
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-60.03
3
Fitted model
-60.6
2
1.14263
1
0.29
Reduced
model
-65.95
1
11.8442
2
0
AIC: = 125.199
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0541
2.705
2
50
-0.44
11
0.1186
5.928
8
50
0.91
55
0.3073
15.367
14
50
-0.42
ChiA2 =1.19 d.f = 1 P-value = 0.275
Page 373 of 407
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1.18 BMDS Summary of Cortical tubule degeneration in female OM rats
(NCI. 1978)
Table 1-13. Summary of BMD Modeling Results for Cortical tubule degeneration in female OM
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
Gamma
0.945
41.971
525
437
Lowest AIC. BMDL estimates for
models not excluded (based on
goodness-of-fit p values less than
0.1, or high scaled residuals) are
sufficiently close.
For the two models that have
identical (lowest) AICs, the
difference in BMDLs is minor
(452 vs 447).
Logistic
1.000
43.750
617
472
LogLogistic
1.000
41.750
592
447
Probit
1.000
43.750
596
456
LogProbit
1.000
43.750
584
436
Weibull
1.000
41.750
596
452
Multistage 2°
0.144
48.197
399
298
Quantal-Linear
0.0300
52.304
306
189
Note: There were not enough degrees of freedom to run the Dichotomous Hill model
a Selected model in bold; scaled residuals for selected model for doses 0, 350, and 640 mg/kg-d were 0, -0.02, 0, respectively.
Weibull Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
300
dose
14:12 08/10 2018
Figure 1-13. Plot of incidence rate by dose with fitted curve for Weibull model for Cortical tubule
degeneration in female OM rats (NCI, 1978); dose shown in mg/kg-d.
Page 374 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Weibull Model using Weibull Model (Version: 2 17; Date: 6/23/2017)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
slope*doseApower)]
Power parameter is restricted as power >=1
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 596.445
BMDL at the 95% confidence level = 452.359
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0.030303
Slope
1.1545E-51
7.5210E-10
Power
18
3.09322
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-19.87
3
Fitted model
-19.88
1
0.000487728
2
1
Reduced
model
-32.19
1
24.6247
2
<.0001
AIC: =41.75
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
31
0
350
0
0
0
34
-0.02
640
0.3125
9.999
10
32
0
ChiA2 = 0 d.f = 2 P-value = 0.9999
Page 375 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.19 BMDS Summary of Nasal squamous cell carcinoma in Male
F344/DuCrj rats (Kano et al., 2009)
Table 1-14. Summary of BMD Modeling Results for Nasal squamous cell carcinoma in Male
F344/DuCrj rats (Kano et al., 2009)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.862
26.028
582
256
Lowest BMDL. Some parameter
values were zero for both models.
Two
0.988
24.951
365
242
a Selected model in bold; scaled residuals for selected model lordoses 0, 11, 55, and 274 mg/kg-d were 0, -0.07, -0.35, 0.07,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.15
0.1
0.05
O
O
50
100
150
200
250
300
350
Figure 1-14. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for
Nasal squamous cell carcinoma in Male F344/DuCrj rats (Kano et al., 2009); dose shown in
mg/kg-d.
Page 376 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 365.191
BMDL at the 95% confidence level = 242.296
BMDU at the 95% confidence level = 1348.53
Taken together, (242.296, 1348.53) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000412718
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0
Beta(l)
0
0
Beta(2)
7.9002E-07
8.3465E-07
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-11.35
4
Fitted model
-11.48
1
0.253836
3
0.97
Reduced
model
-15.58
1
8.45625
3
0.04
AIC: = 24.9506
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
11
0.0001
0.005
0
50
-0.07
55
0.0024
0.119
0
50
-0.35
274
0.0576
2.879
3
50
0.07
ChiA2 = 0.13 d.f = 3 P-value = 0.988
Page 377 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.20 BMDS Summary of Peritoneum mesothelioma in Male F344/DuCrj
rats (Kano et al., 2009)
Table 1-15. Summary of BMD Modeling Results for Peritoneum mesothelioma in Male
F344/DuCrj rats (Kano et al., 2009)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.362
140.83
41.0
30.5
Lowest AIC. All parameter
estimates positive in both models.
Two
0.814
140.75
77.7
35.4
a Selected model in bold; scaled residuals for selected model lordoses 0, 11, 55, and 274 mg/kg-d were 0.13, -0.19, 0.07, -0.01,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
0.7
0.6
0.5
0.4
0.3
0.2
0.1
O
Multistage Cancer
Linear extrapolation
15:45 08/08 2018
Figure 1-15. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for
Peritoneum mesothelioma in Male F344/DuCrj rats (Kano et al., 2009); dose shown in mg/kg-d.
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 77.7277
BMDL at the 95% confidence level = 35.4296
BMDU at the 95% confidence level = 118.349
Taken together, (35.4296, 118.349) is a 90% two-sided confidence interval for the BMD
Page 378 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Cancer Slope Factor = 0.0028225
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.0366063
0.0358706
Beta(l)
0.000757836
0.000816174
Beta(2)
7.6893E-06
7.4706E-06
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-67.35
4
Fitted model
-67.37
3
0.056567
1
0.81
Reduced
model
-95.78
1
56.8663
3
<.0001
AIC: = 140.747
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0366
1.83
2
50
0.13
11
0.0455
2.275
2
50
-0.19
55
0.0972
4.859
5
50
0.07
274
0.5605
28.027
28
50
-0.01
ChiA2 = 0.06 d.f = 1 P-value = 0.8135
Page 379 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.21 BMDS Summary of Hepatocellular adenoma or carcinoma in Male
F344/DuCrj rats (Kano et al., 2009)
Table 1-16. Summary of BMD Modeling Results for Hepatocellular adenoma or carcinoma in
Male F344/DuCrj rats (Kano et al., 2009)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.0978
152.84
23.8
18.3
Lowest AIC. All parameter
estimates positive in both models.
Two
0.816
149.81
61.7
28.3
a Selected model in bold; scaled residuals for selected model lordoses 0, 11, 55, and 274 mg/kg-d were -0.13, 0.18, -0.06, 0.01,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.8
0.6
0.4
0.2
O
O
50
100
150
200
250
Figure 1-16. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for
Hepatocellular adenoma or carcinoma in Male F344/DuCrj rats (Kano et al., 2009); dose shown in
mg/kg-d.
Page 380 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 61.6807
BMDL at the 95% confidence level = 28.2577
BMDU at the 95% confidence level = 85.9896
Taken together, (28.2577, 85.9896) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00353886
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.0645254
0.0651805
Beta(l)
0.000672524
0.000611007
Beta(2)
0.0000167903
0.0000170394
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-71.88
4
Fitted model
-71.91
3
0.0535945
1
0.82
Reduced
model
-115.64
1
87.528
3
<.0001
AIC: = 149.814
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0645
3.226
3
50
-0.13
11
0.0733
3.665
4
50
0.18
55
0.1431
7.157
7
50
-0.06
274
0.7794
38.971
39
50
0.01
ChiA2 = 0.05 d.f = 1 P-value = 0.8161
Page 381 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.22 BMDS Summary of Subcutis fibroma in Male F344/DuCrj rats
(Kano et al., 2009)
Table 1-17. Summary of BMD Modeling Results for Subcutis fibroma in Male F344/DuCrj rats
(Kano et al., 2009)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.662
147.64
154
85.0
Lowest AIC. All parameter
estimates positive for both models.
Two
0.440
149.44
198
86.6
a Selected model in bold; scaled residuals for selected model lordoses 0, 11, 55, and 274 mg/kg-d were 0.66, -0.57, -0.21, 0.11,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
O
O
50
100
150
200
250
dose
16:03 08/08 2018
Figure 1-17. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Subcutis fibroma in Male F344/DuCrj rats (Kano et al., 2009); dose shown in mg/kg-d.
Page 382 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 153.921
BMDL at the 95% confidence level = 84.9898
BMDU at the 95% confidence level = 443.236
Taken together, (84.9898, 443.236) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00117661
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.0752804
0.0733151
Beta(l)
0.00068451
0.000713137
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-71.41
4
Fitted model
-71.82
2
0.818155
2
0.66
Reduced
model
-75.35
1
7.88672
3
0.05
AIC: = 147.639
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0753
3.764
5
50
0.66
11
0.0822
4.111
3
50
-0.57
55
0.1094
5.472
5
50
-0.21
274
0.2334
11.671
12
50
0.11
ChiA2 = 0.82 d.f = 2 P-value = 0.6624
Page 383 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.23 BMDS Summary of Nasal squamous cell carcinoma in female
F344/DuCrj rats (Kano et al., 2009)
Table 1-18. Summary of BMD Modeling Results for Nasal squamous cell carcinoma in female
F344/DuCrj rats (Kano et al., 2009)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.618
45.660
376
214
Lowest BMDL. Some parameter
values were zero for both models.
Two
0.961
43.075
366
275
a Selected model in bold; scaled residuals for selected model for doses 0, 18, 83, and 429 mg/kg-d were 0, -0.5, -1.08, 0.6,
respectively.
0.3
0.25
0.2
H 0.15
-------
PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 375.811
BMDL at the 95% confidence level = 213.836
BMDU at the 95% confidence level = 752.01
Taken together, (213.836, 752.01) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000467648
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0
Beta(l)
0.000280355
0.00036949
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-20.25
4
Fitted model
-21.83
1
3.16408
3
0.37
Reduced
model
-30.34
1
20.1894
3
0
AIC: =45.6604
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
18
0.005
0.252
0
50
-0.5
83
0.023
1.15
0
50
-1.08
429
0.1133
5.666
7
50
0.6
ChiA2 = 1.78 d.f = 3 P-value = 0.6184
Page 385 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.24 BMDS Summary of Mammary adenoma in female F344/DuCrj rats
(Kano et al., 2009)
Table 1-19. Summary of BMD Modeling Results for Mammary adenoma in female F344/DuCrj
rats (Kano et al., 2009)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
Two
0.856
194.22
177
99.1
All (equivalent) models have
adequate fit.
a Selected model in bold; scaled residuals for selected model for doses 0, 18, 83, and 429 mg/kg-d were -0.27, -0.05, 0.46, -
0.13, respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
.5
Multistage Cancer
Linear extrapolation
.4
.3
.2
1
200
dose
16:37 08/08 2018
Figure 1-19. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Mammary adenoma in female F344/DuCrj rats (Kano et al., 2009); dose shown in mg/kg-d.
Page 386 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 176.663
BMDL at the 95% confidence level = 99.1337
BMDU at the 95% confidence level = 501.523
Taken together, (99.1337, 501.523) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00100874
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.133161
0.136033
Beta(l)
0.000596394
0.000570906
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-94.96
4
Fitted model
-95.11
2
0.305898
2
0.86
Reduced
model
-98.68
1
7.4409
3
0.06
AIC: = 194.222
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.1332
6.658
6
50
-0.27
18
0.1424
7.121
7
50
-0.05
83
0.175
8.751
10
50
0.46
429
0.3288
16.442
16
50
-0.13
ChiA2 = 0.31 d.f = 2 P-value = 0.8559
Page 387 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.25 BMDS Summary of Hepatocellular adenomas or carcinomas female
F344/DuCrj rats (Kano et al., 2009)
Table 1-20. Summary of BMD Modeling Results for Hepatocellular adenomas or carcinomas
female F344/DuCrj rats (Kano et al., 2009)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
1.00E-
04
114.09
25.6
19.9
lst-degree multistage has inadequate
p-value. 2nd-degree multistage
exhibits adequate fit.
Two
0.452
91.590
79.8
58.1
a Selected model in bold; scaled residuals for selected model for doses 0, 18, 83, and 429 mg/kg-d were 0.9, -0.76, -0.41, 0.2,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
1
0.8
0.6
0.4
0.2
O
BMpL
O
50
100
150
200
250
300
350
400
450
Figure 1-20. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for
Hepatocellular adenomas or carcinomas female F344/DuCrj rats (Kano et al., 2009); dose shown
in mg/kg-d.
Page 388 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 79.8299
BMDL at the 95% confidence level = 58.085
BMDU at the 95% confidence level = 94.0205
Taken together, (58.085, 94.0205) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00172161
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.0362773
0.0281572
Beta(l)
0
0
Beta(2)
0.0000165328
0.0000173306
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-42.99
4
Fitted model
-43.79
2
1.60218
2
0.45
Reduced
model
-120.43
1
154.873
3
<.0001
AIC: =91.5898
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0363
1.814
3
50
0.9
18
0.0414
2.071
1
50
-0.76
83
0.14
7.001
6
50
-0.41
429
0.954
47.701
48
50
0.2
ChiA2 =1.59 d.f = 2 P-value = 0.4516
Page 389 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.26 BMDS Summary of Hepatocellular adenomas or carcinomas in male
CrjBDFl mice (Kano et al., 2009)
Table 1-21. Summary of BMD Modeling Results for Hepatocellular adenomas or carcinomas in
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
Two
0.153
250.55
71.0
44.0
All (equivalent) models have
adequate fit.
a Selected model in bold; scaled residuals for selected model for doses 0, 49, 191, and 677 mg/kg-d were -1.22, 0.6, 1.22, -0.64,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.9
0.8
0.7
0.6
0.5
0.4
0.3
O
100
200
300
400
500
600
700
Figure 1-21. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenomas or carcinomas in male CrjBDFl mice (Kano et al.. 2009); dose shown in
mg/kg-d.
Page 390 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 70.9911
BMDL at the 95% confidence level = 44.0047
BMDU at the 95% confidence level = 150.117
Taken together, (44.0047, 150.117) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00227248
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.545889
0.573756
Beta(l)
0.00148414
0.00123152
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-121.37
4
Fitted model
-123.28
2
3.80413
2
0.15
Reduced
model
-128.86
1
14.9718
3
0
AIC: =250.551
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.5459
27.294
23
50
-1.22
49
0.5777
28.887
31
50
0.6
191
0.658
32.899
37
50
1.22
677
0.8337
41.687
40
50
-0.64
ChiA2 = 3.76 d.f=2 P-value = 0.1527
Page 391 of 407
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1.27 BMDS Summary of Nasal cavity tumors in Sherman rats (Kociba et
al., 1974)
Table 1-22. Summary of BMD Modeling Results for Nasal cavity tumors in Sherman rats (Kociba
et al.. 1974)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.916
27.352
3465
1525
Lowest BMDL. Both models have
some parameter values of zero
Two
0.998
26.493
1981
1314
a Selected model in bold; scaled residuals for selected model for doses 0, 14, 121, and 1307 mg/kg-d were 0, -0.02, -0.2, 0.02,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
0.12
0.1
0.08
0.06
0.04
0.02
Multistage Cancer
Linear extrapolation
O 500 1OOO
dose
11:22 08/10 2018
Figure 1-22. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 2° model for
Nasal cavity tumors in Sherman rats (Kociba et al.. 1974); dose shown in mg/kg-d.
Page 392 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 1980.96
BMDL at the 95% confidence level = 1314.37
BMDU at the 95% confidence level = 8538.89
Taken together, (1314.37, 8538.89) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.0000760821
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0
Beta(l)
0
0
Beta(2)
2.6849E-08
2.7310E-08
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-12.2
4
Fitted model
-12.25
1
0.0850948
3
0.99
Reduced
model
-17.58
1
10.7433
3
0.01
AIC: = 26.4929
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
106
0
14
0
0.001
0
110
-0.02
121
0.0004
0.042
0
106
-0.2
1307
0.0448
2.959
3
66
0.02
ChiA2 = 0.04 d.f = 3 P-value = 0.9977
Page 393 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.28 BMDS Summary of Liver tumors in Sherman rats (male and female
combined) (Kociba et al., 1974)
Table 1-23. Summary of BMD Modeling Results for Liver tumors in Sherman rats (male and
female combined) (Kociba et al., 1974)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.384
85.119
940
584
Lowest AIC. All parameter
estimates positive in both models.
Two
0.311
86.287
1042
629
a Selected model in bold; scaled residuals for selected model for doses 0, 14, 121, and 1307 mg/kg-d were 0.92, -0.78, -0.62,
0.28, respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
0.25
0.2
0.15
0.1
0.05
O
O
200
400
600
800
1000
1200
Figure 1-23. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Liver tumors in Sherman rats (male and female combined) (Kociba et al., 1974); dose shown in
mg/kg-d.
Page 394 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 940.125
BMDL at the 95% confidence level = 583.576
BMDU at the 95% confidence level = 1685.88
Taken together, (583.576, 1685.88) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000171357
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.00386835
0.000925988
Beta(l)
0.000112071
0.000124518
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-39.39
4
Fitted model
-40.56
2
2.34056
2
0.31
Reduced
model
-53.53
1
28.2732
3
<.0001
AIC: = 85.1187
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.0039
0.41
1
106
0.92
14
0.0054
0.597
0
110
-0.78
121
0.0173
1.832
1
106
-0.62
1307
0.1396
9.213
10
66
0.28
ChiA2 =1.92 d.f = 2 P-value = 0.3838
Page 395 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.29 BMDS Summary of Nasal squamous cell carcinomas in female OM
rats (MS models) (NCI. 1978)
Table 1-24. Summary of BMD Modeling Results for Nasal squamous cell carcinomas in female
OM rats (MS models) (>
CI, 1978)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.180
84.800
176
122
Model has adequate fit.
a Selected model in bold; scaled residuals for selected model lordoses 0, 350, and 640 were 0, 1.47, -1.13, respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
0.5
Multistage Cancer
Linear extrapolation
0.4
0.3
0.2
0.1
O
O
100
300
400
500
600
Figure 1-24. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Nasal squamous cell carcinomas in female OM rats (MS models) (NCI, 1978); dose shown in
mg/kg-d.
Page 396 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 176.281
BMDL at the 95% confidence level = 122.274
BMDU at the 95% confidence level = 271.474
Taken together, (122.274, 271.474) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000817837
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0.0569154
Beta(l)
0.000597685
0.00042443
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-39.75
3
Fitted model
-41.4
1
3.29259
2
0.19
Reduced
model
-47.92
1
16.3252
2
0
AIC: = 84.7996
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
34
0
350
0.1888
6.607
10
35
1.47
640
0.3179
11.125
8
35
-1.13
ChiA2 = 3.44 d.f=2 P-value = 0.1795
Page 397 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.30 BMDS Summary of Hepatocellular adenoma in female OM rats
(NCI. 1978)
Table 1-25. Summary of BMD Modeling Results for Hepatocellular adenoma in female OM rats
(NCI, 1978)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.591
84.697
132
94.1
Model has adequate fit.
a Selected model in bold; scaled residuals for selected model for doses 0, 350, and 640 mg/kg-d were 0, 0.8, -0.64, respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
0.5
0.4
0.3
0.2
0.1
O
Multistage Cancer
Linear extrapolation
O 100 200 300
dose
17:08 08/08 2018
Figure 1-25. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenoma in female OM rats (NCI, 1978); dose shown in mg/kg-d.
Page 398 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 132.359
BMDL at the 95% confidence level = 94.0591
BMDU at the 95% confidence level = 194.33
Taken together, (94.0591, 194.33) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00106316
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0.0385912
Beta(l)
0.00079602
0.000670869
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-40.83
3
Fitted model
-41.35
1
1.02868
2
0.6
Reduced
model
-50.43
1
19.1932
2
<.0001
AIC: = 84.6972
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
31
0
350
0.2432
8.024
10
33
0.8
640
0.3992
12.774
11
32
-0.64
ChiA2 =1.05 d.f = 2 P-value = 0.5908
Page 399 of 407
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1.31 BMDS Summary of Hepatocellular adenomas or carcinomas in male
B6C3F1 mice (NCI. 1978)
Table 1-26. Summary of BMD Modeling Results for Hepatocellular adenomas or carcinomas in
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.0762
180.62
164
117
Model has adequate fit.
a Selected model in bold; scaled residuals for selected model for doses 0, 720, and 830 mg/kg-d were 0.08,-1.28, 1.23,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
BMD
17:11 08/08 2018
Figure 1-26. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenomas or carcinomas in male B6C3F1 mice (NCI, 1978); dose shown in mg/kg-
d.
Page 400 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 164.285
BMDL at the 95% confidence level = 117.371
BMDU at the 95% confidence level = 265.631
Taken together, (117.371, 265.631) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.000851999
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0.15914
0.142253
Beta(l)
0.000641327
0.000710746
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-86.72
3
Fitted model
-88.31
2
3.17505
1
0.07
Reduced
model
-96.72
1
19.9875
2
<.0001
AIC: = 180.618
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0.1591
7.798
8
49
0.08
720
0.4701
23.505
19
50
-1.28
830
0.5062
23.792
28
47
1.23
ChiA2 = 3.14 d.f = 1 P-value = 0.0762
Page 401 of 407
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1.32 BMDS Summary of Hepatocellular adenomas or carcinomas in
female B6C3F1 mice (NCI, 1978)
Table 1-27. Summary of BMD Modeling Results for Hepatocellular adenomas or carcinomas in
'em ale
B6C3F1 mice (NCI, 1978)
Model8
Goodness of fit
BMDiopct
(mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model selection
/?-value
AIC
One
0.0548
89.986
49.1
38.8
Model has adequate fit.
a Selected model in bold; scaled residuals for selected model for doses 0, 380, and 860 mg/kg-d were 0, -1.67, 1.73,
respectively.
Multistage Cancer Model, with BMR of 10% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
Multistage Cancer
Linear extrapolation
1
0.8
0.6
0.4
0.2
O
,3MDL
O
100
200
300
400
500
600
700
800
900
Figure 1-27. Plot of incidence rate by dose with fitted curve for Multistage-Cancer 1° model for
Hepatocellular adenomas or carcinomas in female B6C3F1 mice (NCI, 1978); dose shown in
mg/kg-d.
Page 402 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Multistage Model. (Version: 3.4; Date: 05/02/2014)
The form of the probability function is: P[response] = background + (1-background)* [1-EXP(-
beta 1 * doseA 1 -beta2 * doseA2..)]
The parameter betas are restricted to be positive
Benchmark Dose Computation.
BMR = 10% Extra risk
BMD = 49.1018
BMDL at the 95% confidence level = 38.8015
BMDU at the 95% confidence level = 62.9223
Taken together, (38.8015, 62.9223) is a 90% two-sided confidence interval for the BMD
Multistage Cancer Slope Factor = 0.00257722
Parameter Estimates
Variable
Estimate
Default Initial
Parameter Values
Background
0
0
Beta(l)
0.00214576
0.00345682
Analysis of Deviance Table
Model
Log(likelihoo
d)
# Param's
Deviance
Test d.f.
p-value
Full model
-40.68
3
Fitted model
-43.99
1
6.63483
2
0.04
Reduced
model
-91.61
1
101.861
2
<.0001
AIC: = 89.986
Goodness of Fit Table
Dose
Est. Prob.
Expected
Observed
Size
Scaled Resid
0
0
0
0
50
0
380
0.5575
26.762
21
48
-1.67
860
0.842
31.155
35
37
1.73
ChiA2 = 5.81 d.f = 2 P-value = 0.0548
Page 403 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
1.33 MS-Combo Result (Kano et al., 2009), Male F344/ DuCrj rats,
excluding liver
Output information
Tumor Output Directory
C:\Users\ \Documents\MODELS\14dioxane\oral\kano MSC\
Tumor Output File Name
Kano M nasal perit subcut.out
Combined BMD and BMDL Calculations
Combined Log-Likelihood
-150.6683784
Combined Log-likelihood
Constant
135.326183
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
55.1605
BMDL
28.1197
Multistage Cancer Slope
Factor
0.00355622
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -150.66837843809108
Combined Log-likelihood Constant 135.32618295034047
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 55.1605
BMDL = 28.1197
BMDU = 88.9926
Multistage Cancer Slope Factor = 0.00355622
1.34 MS-Combo Result (Kano et al., 2009), Male F344/ DuCrj rats,
including liver
Output information
Page 404 of 407
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PEER REVIEW DRAFT, DO NOT CITE OR QUOTE
Tumor Output Directory
C:\Users\ \Documents\MODELS\14dioxane\oral\kano MSC\
Tumor Output File Name
Kano M all.out
Combined BMD and BMDL Calculations
Combined Log-Likelihood
-222.5755927
Combined Log-likelihood
Constant
200.3198288
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
35.099
BMDL
17.8487
Multistage Cancer Slope
Factor
0.00560264
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -222.57559271275764
Combined Log-likelihood Constant 200.31982880189281
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 35.099
BMDL = 17.8487
BMDU = 55.9726
Multistage Cancer Slope Factor = 0.00560264
1.35 MS-Combo Result (Kano et al., 2009), Female F344/ DuCrj rats,
excluding liver
\Users\ \Documents\MODELS\14dioxane\oral\kano MSC\
Kano Frat mam nas.out
-116.9411818
Page 405 of 407
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Combined Log-likelihood
Constant
105.6980867
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
120.172
BMDL
76.5303
Multistage Cancer Slope
Factor
0.00130667
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -116.94118175960915
Combined Log-likelihood Constant 105.69808670837932
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 120.172
BMDL = 76.5303
BMDU = 231.101
Multistage Cancer Slope Factor = 0.00130667
1.36 MS-Combo Result (Kano et al., 2009), Female F344/ DuCrj rats,
including liver
Output information
Tumor Output Directory
C:\Users\ \Documents\MODELS\14dioxane\oral\kano MSC\
Tumor Output File Name
kano F all.out
Combined BMD and BMDL Calculations
Combined Log-Likelihood
-160.736061
Page 406 of 407
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Combined Log-likelihood
Constant
143.1853353
Benchmark Dose Computation
Specified effect
0.1
Risk Type
Extra risk
Confidence level
0.95
BMD
57.6028
BMDL
41.6426
Multistage Cancer Slope
Factor
0.00240139
**** Start of combined BMD and BMDL Calculations.****
Combined Log-Likelihood -160.73606100858856
Combined Log-likelihood Constant 143.18533527241118
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 57.6028
BMDL = 41.6426
BMDU = 70.5585
Multistage Cancer Slope Factor = 0.00240139
Page 407 of 407
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