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EPA Document# EPA-740-R1-8011
April 2020 DRAFT
Office of Chemical Safety and
Pollution Prevention
Draft Risk Evaluation for
Perchloroethylene
(Ethene, l,l»2,2-Tetrachloro)
CASRN: 127-18-4
CI CI
X
CI CI
ŁEPA
United States
Environmental Protection Agency
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18 TABLE OF CONTENTS
19 ACKNOWLEDGEMENTS 20
20 ABBREVIATIONS 21
21 EXECUTIVE SUMMARY 28
22 1 INTRODUCTION 38
23 1.1 Physical and Chemical Properties 39
24 1.2 Uses and Production Volume 40
25 1.3 Regulatory and Assessment History 42
26 1.4 Scope of the Evaluation 44
27 1.4,1 Conditions of Use Included in the Risk Evaluation 44
28 1.4.2 Conceptual Models 49
29 1.5 Systematic Review 53
30 1.5.1 Data and Information Collection 53
31 1.5.2 Data Evaluation 59
32 1.5.3 Data Integration 59
33 2 EXPOSURES 61
34 2.1 Fate and Transport 61
35 2.1.1 Fate and Transport Approach and Methodology 61
36 2.1.2 Summary of Fate and Transport 62
37 2.1,3 Key Sources of Uncertainty in Fate and Transport Assessment 63
38 2.2 Releases to the Environment 64
39 2.2.1 Environmental Discharges of Wastewater 64
40 2.2.1.1 Results for Daily Wastewater Discharge Estimates 64
41 2.2.1.2 Approach and Methodol ogy 70
42 2.2.1.2.1 Wastewater Discharge Estimates 70
43 2.2,1,2,2 Estimates of Number of Facilities 71
44 2.2.1.2.3 Estimates of Release Days 74
45 2.2.1.3 Assumptions, Key Sources of Uncertainty, and Overall Confidence for Environmental
46 Releases 75
47 2.3 Environmental Exposures Overview 86
48 2.3.1 Aquatic Exposure Modeling Approach 87
49 2.3.1.1 Exposure and Fate Assessment Screening (E-FAST) Tool 2014 Inputs 88
50 2.3.1.1.1 Chemical release to wastewater (WWR) 88
51 2.3.1.1.2 Release Days (days/year) 88
52 2.3.1.1.3 Removal from wastewater treatment (WWT%) 88
53 2.3.1.1.4 Facility or Industry Sector 89
54 2.3.1.2 E-FAST 2014 Equations 90
55 2.3.1.2.1 Surface Water Concentrations 90
56 2.3.1,2,2 Days of COC Exceedance 90
57 2.3.1.3 E-FAST 2014 Outputs 91
58 2,3.2 Surface Water Monitoring Data Gathering Approach 91
59 2.3.2.1 Method for Systematic Review of Surface Water Monitoring Data 91
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60 2.3.2.2 Method for Obtaining Surface Water Monitoring Data from WQX/WQP 91
61 2.3.2.2.1 Data Retrieval from WQP 92
62 2.3.2,2,2 Data Filtering and Cleansing 93
63 2,3.3 Geospatial Analysis Approach 93
64 2.3.3.1 Geographic Coordinates 94
65 2.3.4 Environmental Exposure Results 94
66 2.3.4.1 Aquatic Environmental Exposures 94
67 2.3.4.1.1 Predicted Surface Water Concentrations: E-FAST 2014 Modeling 94
68 2.3.4.1.2 Characterization of Modeled Releases 96
69 2.3.4.2 Monitored Surface Water Concentrations 98
70 2.3.4.2.1 Measured Surface Water Concentrations from WQX/WQP 98
71 2.3.4.2.2 Characterization of WQP Data 100
72 2.3.4.2,3 Measured Concentrations of PCE from Published Literature 101
73 2.3.4.2.4 Geospatial Analysis Comparing Predicted and Measured Surface Water
74 Concentrations 102
75 2.3.4,2.5 Co-location of PCE Releasing Facilities and Monitoring Stations 102
76 2.3.4.3 Biomonitoring Data 107
77 2.3.4.4 Assumptions and Key Sources of Uncertainty for Environmental Exposures 108
78 2.3.4.4.1 Confidence in Aquatic Exposure Scenarios 109
79 2.4 Human Exposures 110
80 2.4.1 Occupational Exposures 123
81 2.4.1.1 Approach to Workers and Occupational Non-Users 123
82 2.4.1.2 Number of Workers and Occupational Non-Users Approach and Methodology 123
83 2.4.1.3 Inhalation Exposures Approach and Methodology 124
84 2.4.1.4 Consideration of Engineering Controls and Personal Protective Equipment 131
85 2.4.1.5 Dermal Exposure Assessment Approach 132
86 2.4.1.6 Manufacturing 132
87 2.4.1.7 Repackaging 136
88 2.4.1.8 Processing as a Reactant 138
89 2.4.1.9 Incorporation into Formulation, Mixture, or Reactant Product 140
90 2.4.1.10 Batch Open-Top Vapor Degreasing 143
91 2.4.1.11 Batch Closed-Loop Vapor Degreasing 146
92 2.4.1.12 Conveyorized Vapor Degreasing 148
93 2.4.1.13 Web Degreasing 149
94 2.4.1.14 Cold Cleaning 151
95 2.4.1.15 Aerosol Degreasing and Aerosol Lubricants 154
96 2.4.1.16 Dry Cleaning and Spot Cleaning 156
97 2.4.1.17 Adhesives, Sealants, Paints, and Coatings 162
98 2.4.1.18 Maskant for Chemical Milling 164
99 2.4.1.19 Industrial Processing Aid 166
100 2.4.1.20 Metalworking Fluids 169
101 2.4.1.21 Wipe Cleaning and Metal/Stone Polishes 171
102 2.4.1.22 Other Spot Cleaning/Spot Removers (Including Carpet Cleaning) 172
103 2.4.1.23 Other Industrial Uses 173
104 2.4.1.24 Other Commercial Uses 175
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105 2.4.1.25 Laboratory Chemicals 178
106 2.4.1.26 Waste Handling, Disposal, Treatment, and Recycling 178
107 2.4.1.27 Other Department of Defense Uses 180
108 2.4.1.28 Summary of Inhalation Exposure Assessment 183
109 2.4.1.29 Dermal Exposure Assessment 191
110 2.4.1.30 Key Assumptions and Uncertainties of the Occupational Exposure Assessment 195
111 2,4,2 Consumer Exposures 199
112 2.4.2.1 Overview and Literature Summary 200
113 2.4.2.2 Consumer Exposure Approach and Methodology 207
114 2.4.2.2,1 Routes of Exposure 207
115 2,4,2,2,2 Modeling Approach 208
116 2.4.2.3 Consumer Product Exposure Scenarios 218
117 2.4.2.3.1 Degreasers 218
118 2.4.2.3.1.1 Aerosol Cleaners for Motors, Coils, Electrical Parts, Cables, Stainless Steel and
119 Marine Equipment, and Wire and Ignition Demoisturants 218
120 2.4.2.3.1.2 Aerosol Brake Cleaners 219
121 2,4,2,3,2 Parts Cleaners 221
122 2.4.2.3,3 Vandalism Stain Removers, Mold Cleaners, and Weld Splatter Protectants 222
123 2.4.2.3.4 Marble Polish 223
124 2.4.2,3.5 Cutting Fluid 224
125 2.4.2.3.6 Lubricants and Penetrating Oils (aerosol) 224
126 2.4.2,3.7 Adhesives 225
127 2,4,2,3.8 Livestock Grooming Adhesive (aerosol) 226
128 2.4,2,3.9 Caulks, Sealants and Column Adhesives 227
129 2.4.2,3.10 Outdoor Water Shield 227
130 2.4,2,3,11 Aerosol Coatings and Primers 229
131 2.4.2.3.12 Liquid Primers and Sealants 229
132 2.4.2.3.13 Metallic Overglaze 231
133 2.4,2,3,14 Metal and Stone Polish 231
134 2.4.2,3,15 Consumer Product Exposure Summary 233
135 2.4.2.4 Consumer Article Exposure Scenarios 233
136 2.4.2.4,1 Literature Summary 233
137 2.4.2,4.2 Dermal Exposure to Recently Dry cleaned Articles 238
138 2,4,2,4,3 Inhalation Exposure to Recently Dry cleaned Articles 241
139 2.4.2,4.4 Consumer Article Exposure Summary 243
140 2.4.2.5 Other Consumer Uses 243
141 2.4.2.5,1 New Clothing/Textile Industry 243
142 2.4.2,5.2 Coin Operated Dry Cleaners 244
143 2.4.2.5,3 Print Shops 244
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144 2.4.2.6 Consumer Exposure Assumptions and Key Sources of Uncertainty 244
145 2.4,3 Potentially Exposed or Susceptible Subpopulations 245
146 3 HAZARDS 249
147 3.1 Environmental Hazards 249
148 3,1.1 Approach and Methodology 249
149 3.1,2 Hazard Identification 249
150 3,1,3 Weight of Scientific Evidence 251
151 3.1.4 Concentrations of Concern (COC) 252
152 3,1,5 Summary of Environmental Hazard 254
153 3.2 Human Health Hazards 256
154 3,2,1 Approach and Methodology 256
155 3.2.2 Toxicokinetics 258
156 3.2.2.1 Absorption/Distribution/Metabolism/Elimination (ADME) 258
157 3.2.2.1.1 Absorption 258
158 3,2,2,1,2 Metabolism 258
159 3,2.2.1,3 Elimination 260
160 3.2.2.2 PBPK Modeling 260
161 3,2,3 Hazard Identification 261
162 3.2.3.1 Non-Cancer Hazards 261
163 3,2,3.1.1 Acute Toxicity and Irritation 261
164 3,2,3.1.2 Neurotoxicity 262
165 3.2.3.1.3 Kidney Toxicity 266
166 3.2.3,1.4 Liver Toxicity 267
167 3,2.3.1.5 Reproductive/Developmental Toxicity 267
168 3.2.3.1.6 Immune System and Hematological Effects 269
169 3.2.3.2 Genotoxicity and Cancer Hazards 270
170 3.2.3.2.1 Genotoxicity 270
171 3.2.3.2.2 Carcinogenicity Epidemiological Studies 272
172 3,2.3.2.3 Carcinogenicity Animal Studies 283
173 3.2.3.2.4 Mode of Action 283
174 3.2.4 Weight of Scientific Evidence 292
175 3.2,4.1.1 Acute Toxicity 292
176 3.2.4.1,2 Neurotoxicity 293
177 3,2.4.1,3 Kidney Toxicity 293
178 3,2,4,1,4 Liver Toxicity 293
179 3.2.4.1.5 Reproductive/Developmental Toxicity 294
180 3.2,4,1,6 Immune System and Hematological Effects 294
181 3.2.4.1.7 Cancer 294
182 3.2,5 Dose-Response Assessment 295
183 3.2.5.1 Selection of Studies for Dose-Response Assessment 295
184 3.2.5.1.1 Non-Cancer Toxicity from Acute/Short-Term Exposure 295
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3.2.5.1.2 Non-Cancer Toxicity from Chronic Exposure 296
3.2.5.1.3 Cancer 297
3.2.5.2 Potentially Exposed and Susceptible Subpopulations 299
3.2.5.3 Derivation of Points of Departure (PODs) 300
3.2.5.3.1 Non-Cancer PODs for Acute/Short-term Inhalation Exposure 300
3.2.5.3.2 Non-Cancer PODs for Chronic Inhalation Exposure 301
3.2.5.3.3 Cancer Slope Factor Derivation 303
3.2.5.4 Points of Departure for Human Health Hazard Endpoints and Confidence Levels 308
3,2,5.4.1 Route to Route Extrapolation for Dermal PODs 312
3.2.6 Key Assumptions and Uncertainties for Human Health Hazard 315
3.2.6.1 Hazard ID and Weight of Scientific Evidence 315
3.2.6.2 Derivation of PODs, UFs, and PBPK Results 316
3.2.6.3 Cancer Dose-Response 316
3.2.6.4 Confidence Ratings for Endpoints and Selected Representative PODs 317
4 RISK CHARACTERIZATION 318
4.1 Environmental Ri sk 318
4.1.1 Risk Estimation Approach 318
4.1.2 Risk Estimation for Aquatic Environment 326
4.1.3 Risk Estimation for Sediment Pathways 331
4.1.4 Risk Estimation for Land-Applied Biosolids Pathway 331
4.2 Human Health Ri sk 331
4.2.1 Risk Estimation Approach 331
4.2.2 Risk Estimation for Inhalation Exposures to Workers 333
4.2.2.1 PODs used for Occupational Inhalation Risk Estimates 333
4.2.2.2 Occupational Inhalation Exposure Summary and PPE Use Determination by OES ... 334
4.2.2.3 Manufacturing 337
4.2.2.4 Repackaging 339
4.2.2.5 Processing as Reactant 340
4.2.2.6 Incorporation into Formulation, Mixture, or Reactant Product 342
4.2.2.7 Batch Open-Top Vapor Degreasing 345
4.2.2.8 Batch Closed-Loop Vapor Degreasing 347
4.2.2.9 Conveyorized Vapor Degreasing 348
4.2.2.10 Web Degreasing 349
4.2.2.11 Cold Cleaning 351
4.2.2.12 Aerosol Degreasing and Aerosol Lubricants 353
4.2.2.13 Dry Cleaning and Spot Cleaning 355
4.2.2.14 Adhesives, Sealants, Paints, and Coatings 358
4.2.2.15 Maskant for Chemical Milling 360
4.2.2.16 Industrial Processing Aid 362
4.2.2.17 Metalworking Fluids 363
4.2.2.18 Wipe Cleaning and Metal/Stone Polishes 365
4.2.2.19 Other Spot Cleaning/Spot Removers (Including Carpet Cleaning) 366
4.2.2.20 Other Industrial Uses 367
4.2.2.21 Other Commercial Uses 369
4.2.2.22 Laboratory Chemicals 372
4.2.2.23 Waste Handling, Disposal, Treatment, and Recycling 373
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4.2.2.24 Other Department of Defense Uses 374
4.2.3 Risk Estimation for Dermal Exposures to Workers 376
4.2.3.1 Industrial Uses That Generally Occur in Closed Systems 378
4.2.3.2 Industrial Degreasing and Chemical Maskant Uses Which Are Not Closed Systems. 379
4.2.3.3 Aerosol Uses 380
4.2.3.4 Commercial Activities of Similar Maximum Concentration 381
4.2.3.5 Metalworking Fluids 383
4.2.3.6 Adhesives, Sealants, Paints, and Coatings 384
4.2.4 Risk Estimation for Exposures to Consumers 386
4.2.4.1 Aerosol Cleaners for Motors, Coils, Electrical Parts, Cables, Stainless Steel and marine
Equipment, and Wire and Ignition Demoisturants 386
4.2.4.2 Aerosol Brake Cleaners 387
4.2.4.3 Parts Cleaners 388
4.2.4.4 Vandalism Stain Removers, Mold Cleaners, and Weld Splatter Protectants 389
4.2.4.5 Marble Polish 390
4.2.4.6 Cutting Fluid 391
4.2.4.7 Lubricants and Penetrating Oils 392
4.2.4.8 Adhesives 392
4.2.4.9 Livestock Grooming Adhesive 393
4.2.4.10 Caulks, Sealants and Column Adhesives 393
4.2.4.11 Outdoor Water Shield 394
4.2.4.12 Aerosol Coatings and Primers 395
4.2.4.13 Liquid Primers and Sealants 396
4.2.4.14 Metallic Overglaze 397
4.2.4.15 Metal and Stone Polish 397
4.2.4.16 Dry Cleaned Clothing 398
4.3 Assumptions and Key Sources of Uncertainty for Risk Characterization 400
4.3.1 Environmental Risk Characterization Assumptions and Key Sources of Uncertainty 400
4.3.2 Human Health Risk Characterization Key Assumptions and Uncertainties 401
4.3.2.1 Human Health Hazard Considerations 401
4.3.2.2 Occupational Risk Considerations 401
4.3.2.3 Consumer Risk Considerations 402
4.4 Other Risk Related Considerations 402
4.4.1 Potentially Exposed or Susceptible Subpopulations 402
4.4.2 Aggregate and Sentinel Exposures 403
4.5 Risk Conclusions 403
4.5.1 Environmental Risk Conclusions 403
4.5.2 Human Health Risk Conclusions 426
4.5.2.1 Summary of Risk Estimates for Inhalation and Dermal Exposures to Workers and
ONUs 426
4.5.2.2 Summary of Risk Estimates for Inhalation and Dermal Exposures to Consumers and
Bystanders 449
5 RISK DETERMINATION 455
5.1 Unreasonable Risk 455
5.1.1 Overview 455
5.1.2 Risks to Human Health 456
5.1.2.1 Determining Non-Cancer Risks 456
5.1.2.2 Determining Cancer Risks 457
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5.1.3 Determining Environmental Risk 457
5.2 Risk Determinations for PCE 458
5.3 Detailed Risk Determinations by Condition of Use 469
5.3.1 Manufacture - Domestic manufacture 469
5.3.2 Manufacture - Import (includes repackaging and loading/unloading) 470
5.3.3 Processing - Processing as a reactant/intermediate in industrial gas manufacturing;
intermediate in basic organic chemical manufacturing; intermediate in petroleum refineries;
residual or byproduct reused as a reactant 471
5.3.4 Processing - Incorporation into formulation, mixture or reaction product - Cleaning and
degreasing products 473
5.3.5 Processing - Incorporation into formulation, mixture or reaction product - Adhesive and
sealant products 474
5.3.6 Processing - Incorporation into formulation, mixture or reaction product - Paint and coating
products 475
5.3.7 Processing - Incorporation into formulation, mixture or reaction product - Other chemical
products and preparations 477
5.3.8 Processing - Repackaging - Solvents (for cleaning or degreasing); intermediate 478
5.3.9 Processing - Recycling 479
5.3.10 Distribution in Commerce 481
5.3.11 Industrial Use - Solvents (for cleaning or degreasing) - Batch vapor degreaser (open-top)
481
5.3.12 Industrial Use - Solvents (for cleaning or degreasing) - Batch vapor degreaser (closed-loop)
483
5.3.13 Industrial Use - Solvents (for cleaning or degreasing) - In-line vapor degreaser
(convey orized) 484
5.3.14 Industrial Use - Solvents (for cleaning or degreasing) - In-line vapor degreaser (web
degreaser) 485
5.3.15 Industrial Use - Solvents (for cleaning or degreasing) - Cold cleaner 486
5.3.16 Industrial Use - Solvents (for cleaning or degreasing) - Aerosol spray degreaser/cleaner 487
5.3.17 Industrial Use - Solvents (for cleaning or degreasing) - Dry Cleaning and Spot Cleaning
Post-2006 Dry Cleaning 489
5.3.18 Industrial Use - Solvents (for cleaning or degreasing) - Dry Cleaning and Spot Cleaning
4th/5th Gen Only Dry Cleaning 490
5.3.19 Industrial Use - Lubricants and greases - Lubricants and greases (aerosol lubricants) 491
5.3.20 Industrial Use - Lubricants and greases - Lubricants and greases (e.g., penetrating
lubricants, cutting tool coolants) 493
5.3.21 Industrial Use - Adhesives and sealants - Solvent-based adhesives and sealants 494
5.3.22 Industrial Use - Paints and coatings - Solvent-based paints and coatings 495
5.3.23 Industrial Use - Paints and coatings - Maskant for Chemical Milling 496
5.3.24 Industrial Use - Processing aids, not otherwise listed - Pesticide, fertilizer and other
agricultural chemical manufacturing 497
5.3.25 Industrial Use - Processing aids, specific to petroleum production - Catalyst regeneration in
petrochemical manufacturing 498
5.3.26 Industrial Use - Other uses - Textile processing (spot cleaning) 499
5.3.27 Industrial Use - Other uses - Textile processing (other) 500
5.3.28 Industrial Use - Other uses - Wood furniture manufacturing 501
5.3.29 Industrial Use - Other uses - Laboratory chemicals 502
5.3.30 Industrial Use - Other uses - Foundry applications 503
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3.31 Commercial Use - Cleaning and furniture care products - Cleaners and degreasers (other)
(wipe cleaning) 504
3.32 Commercial Use - Cleaning and furniture care products - Cleaners and degreasers (other)
(Other Spot Cleaning/Spot Removers (Including Carpet Cleaning)) 505
3.33 Commercial Use - Cleaning and furniture care products - Cleaners and degreasers (other)
(Mold Release) 506
3.34 Commercial Use - Cleaning and furniture care products - Dry Cleaning and Spot Cleaning
Post-2006 Dry Cleaning 507
35 Commercial Use - Cleaning and furniture care products - Dry Cleaning and Spot Cleaning
4th/5th Gen Only Dry Cleaning 509
36 Commercial Use - Cleaning and furniture care products - Automotive care products (e.g.,
engine degreaser and brake cleaner) 510
37 Commercial Use - Cleaning and furniture care products - Aerosol cleaner 511
38 Commercial Use - Cleaning and furniture care products - Non-aerosol cleaner 512
39 Commercial Use - Lubricants and greases - Lubricants and greases (aerosol lubricants). 514
40 Commercial Use - Lubricants and greases - Lubricants and greases (e.g., penetrating
lubricants, cutting tool coolants) 515
41 Commercial Use - Adhesives and sealant chemicals - Light repair adhesives 516
42 Commercial Use - Paints and coatings - Solvent-based paints and coatings 517
43 Commercial Use - Other uses - Carpet cleaning 518
44 Commercial Use - Other uses - Laboratory chemicals 519
45 Commercial Use - Other uses - Metal (e.g., stainless steel) and stone polishes 520
46 Commercial Use - Other uses - Inks and ink removal products (based on printing) 521
47 Commercial Use - Other uses - Inks and ink removal products (based on photocopying) 522
48 Commercial Use - Other uses - Welding 523
49 Commercial Use - Other uses - Photographic film 525
50 Commercial Use - Other uses - Mold cleaning, release and protectant products 526
51 Consumer Use - Cleaning and furniture care products - Cleaners and degreasers (other) 527
52 Consumer Use - Cleaning and furniture care products - Dry cleaning solvent 528
53 Consumer Use - Cleaning and furniture care products - Automotive care products (Brake
cleaner) 528
54 Consumer Use - Cleaning and furniture care products - Automotive care products (Parts
cleaner) 529
55 Consumer Use - Cleaning and furniture care products - Aerosol cleaner (Vandalism Mark
& Stain Remover, Mold Cleaner, Weld Splatter Protectant) 530
56 Consumer Use - Cleaning and furniture care products - Non-aerosol cleaner (e.g., marble
and stone polish) 531
57 Consumer Use - Lubricants and greases - Lubricants and greases (cutting fluid) 532
58 Consumer Use - Lubricants and greases - Lubricants and greases (Lubricants and
Penetrating Oils) 533
59 Consumer Use - Adhesives and sealant chemicals - Adhesives for arts and crafts (includes
industrial adhesive, arts and crafts adhesive, gun ammunition sealant) 534
60 Consumer Use - Adhesives and sealant chemicals - Adhesives for arts and crafts (Livestock
Grooming Adhesive) 534
61 Consumer Use - Adhesives and sealant chemicals - Adhesives for arts and crafts (Column
Adhesive, Caulk and Sealant) 535
5.3.62 Consumer Use - Paints and coatings - Solvent-based paints and coatings (Outdoor water
shield (liquid)) 536
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375 5.3,63 Consumer Use - Paints and coatings - Solvent-based paints and coatings (Coatings and
376 primers (aerosol)) 537
377 5,3,64 Consumer Use - Paints and coatings - Solvent-based paints and coatings (Rust Primer and
378 Sealant (liquid)) 537
379 5,3.65 Consumer Use - Paints and coatings - Solvent-based paints and coatings (Metallic
380 Overglaze) 538
381 5.3.66 Consumer Use - Other Uses - Metal (e.g., stainless steel) and stone polishes 539
382 5.3.67 Consumer Use - Other Uses - Inks and ink removal products; welding; mold cleaning,
383 release and protectant products 540
384 5.3.68 Disposal 540
385 REFERENCES 543
386 APPENDICES 568
387 Appendix A REGULATORY HISTORY 568
388 A.l Federal Laws and Regulations .....568
389 A,2 State Laws and Regulations 574
390 A.3 International Laws and Regulations....... ..575
391 Appendix B LIST OF SUPPLEMENTAL DOCUMENTS 577
392 Appendix C FATE AND TRANSPORT 579
393 Appendix D ENVIRONMENTAL EXPOSURES 580
394 Appendix E BENCHMARK DOSE ANALYSIS 591
395 E.l Model Selection Details for Tumor Sites from J ISA (1993) 591
396 E.l.l Modeling Output for Male Mice, Hepatocellular Tumors (JISA, 1993) 592
397 E. 1.1.1 With total oxidative metabolism in liver as dose metric 592
398 E.l. 1.2 With TCA AUC in liver as dose metric 594
399 E. 1.1.3 With administered PCE concentration (ppm) as dose metric 596
400 E. 1.2 Modeling Output for Female Mice, Hepatocellular Tumors (JISA, 1993) 599
401 E. 1.2.1 With total oxidative metabolism in liver as dose metric 599
402 E.l.2.2 With TCA AUC in liver as dose metric 601
403 E. 1.2.3 With administered PCE concentration (ppm) as dose metric 603
404 Appendix F Cancer Study Summaries 605
405 F.l Epidemiological Data... 605
406 F.l.l Bladder 605
407 F.l.2 NHL 606
408 F.l.3 MM 606
409 F.l.4 Esophagus 607
410 F.l.5 Kidney 608
411 F.l.6 Lung 609
412 F.l.7 Liver 610
413 F.l.8 Cervix 611
414 F.l.9 Breast 611
415 F.l. 10 Other 612
416 F. 1.11 Detailed Summary Epidemiologic Evidence on Cancer Published after the 2012 IRIS
417 Toxicological Assessment on PCE 612
418 F.2 Animal Studies 630
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Appendix G Chronic Inhalation Risk Estimates Using Occupational HECs 633
LIST OF TABLES
Table 1-1 Physical and Chemical Properties of PCE 40
Table 1-2 Production Volume of PCE in CDR Reporting Period (2012 to 2015) a 42
Table 1-3 Assessment History of PCE 42
Table 1-4 Categories and Subcategories of Conditions of Use Included in the Scope of the Risk
Evaluation 46
Table 2-1. Environmental Fate Characteristics of PCE 61
Table 2-2. Summary of EPA's Daily Wastewater Discharge Estimates for Each OES 66
Table 2-3. Summary of EPA's Estimates for the Number of Facilities for Each OES 73
Table 2-4. Summary of EPA's Estimates for Release Days for Each OES 74
Table 2-5. Summary of Assumptions, Uncertainty, and Overall Confidence in Release Estimates by OES
75
Table 2-6 Summary of Surface Water Concentrations by OES for Maximum Days of Release Scenario
95
Table 2-7 Summary of Surface Water Concentrations by OES for 20 Days of Release Scenario for
Direct Releaser Facilities 95
Table 2-8 Summary of Surface Water Concentrations by OES for 20 Days of Release Scenario for
Indirect Releaser Facilities 96
Table 2-9. Measured Concentrations of PCE in Surface Water Obtained from the Water Quality Portal:
2013-2017 99
Table 2-2-10. Levels of PCE in U.S. Surface Water from Published Literature 101
Table 2-11. Co-Location of Facility Releases and Monitoring Sites within HUC 8 and HUC 12
Boundaries (Year 2016) 105
Table 2-12 Crosswalk of Subcategories of Use Listed in the Problem Formulation Document to
Exposure Scenarios Assessed in the Risk Evaluation Ill
Table 2-13. Data Evaluation of Sources Containing Number of Worker Estimates 123
Table 2-14. Data Evaluation of Sources Containing Occupational Exposure Monitoring Data 126
Table 2-15. A Summary of Approaches and Overall Confidence for Exposures Estimates for Each OES
128
Table 2-16. Assigned Protection Factors for Respirators in OSHA Standard 29 CFR 1910.134 132
Table 2-17. Estimated Number of Workers Potentially Exposed to PCE During Manufacturing 133
Table 2-18. Summary of Inhalation Monitoring Data for the Manufacture of PCE 135
Table 2-19. Estimated Number of Workers Potentially Exposed to PCE During Repackaging 136
Table 2-20. Summary of Inhalation Monitoring Data for Repackaging 137
Table 2-21. Estimated Number of Workers Potentially Exposed to PCE During Processing as a Reactant
138
Table 2-22. Summary of Inhalation Monitoring Results for Processing PCE as a Reactanta 139
Table 2-23. Estimated Number of Workers Potentially Exposed to PCE During Formulation 140
Table 2-24. Summary of Inhalation Exposure Monitoring Data for Aerosol Packing Formulation Sites
141
Table 2-25. Summary of Exposure Modeling Results for Formulation of PCE-Based Products 142
Table 2-26. Estimated Number of Workers Potentially Exposed to PCE During Use in Open-Top Vapor
Degreasing 144
Table 2-27. Summary of Worker Inhalation Exposure Monitoring Data for Open-Top Vapor Degreasing
145
Page 11 of 636
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Table 2-28. Estimated Number of Workers Potentially Exposed to PCE During Use in Closed-Loop
Vapor Degreasing 146
Table 2-29. Summary of Worker Inhalation Exposure Monitoring Data for Closed-Loop Vapor
Degreasing 147
Table 2-30. Estimated Number of Workers Potentially Exposed to PCE During Use in Conveyorized
Vapor Degreasing 148
Table 2-31. Summary of Exposure Modeling Results for Use of PCE in Conveyorized Vapor
Degreasing 149
Table 2-32. Estimated Number of Workers Potentially Exposed to PCE During Use in Web Degreasing
150
Table 2-33. Summary of Exposure Modeling Results for Use of PCE in Web Degreasing 150
Table 2-34. Estimated Number of Workers Potentially Exposed to PCE During Use in Cold Cleaning
152
Table 2-35. Summary of Worker Inhalation Exposure Monitoring Data for Use of PCE in Cold Cleaning
152
Table 2-36. Summary of Exposure Modeling Results for Use of PCE in Cold Cleaning 153
Table 2-37. Estimated Number of Workers Potentially Exposed to PCE During Use of Aerosol
Degreasers and Aerosol Lubricants 154
Table 2-38. Summary of Worker Inhalation Exposure Monitoring Data for Aerosol Degreasing 155
Table 2-39. Summary of Exposure Modeling Results for Use of PCE in Aerosol Degreasing and Aerosol
Lubricants 156
Table 2-40. Estimated Number of Workers Potentially Exposed to PCE During Dry Cleaning 157
Table 2-41. Summary of Inhalation Exposure Monitoring Data for Dry Cleaning 159
Table 2-42. Summary of Worker and Occupational Non-Uses Inhalation Exposure Modeling Results for
Dry Cleaning 161
Table 2-43. Estimated Number of Workers Potentially Exposed to PCE During of Use Adhesives,
Sealants, Paints, and Coatings 162
Table 2-44. Summary of Inhalation Exposure Monitoring Data for Use of PCE-Based Adhesives,
Sealants, Paints, and Coatings 163
Table 2-45. Estimated Number of Workers Potentially Exposed to PCE During Use of Chemical
Maskants 165
Table 2-46. Summary of Inhalation Exposure Monitoring Data for Chemical Maskants 166
Table 2-47. Estimated Number of Workers Potentially Exposed to PCE During Use of Processing Aids
167
Table 2-48. Summary of Worker Inhalation Exposure Monitoring Data for Use of PCE as a Processing
Aid 168
Table 2-49. Summary of Exposure Results for Use of PCE in Metalworking Fluids Based on ESD
Estimates 170
Table 2-50. Summary of Worker Inhalation Monitoring Data for Use of PCE as a Wipe Cleaning
Solvent and Metal/Stone Polish 172
Table 2-51. Summary of Worker Inhalation Exposure Monitoring Data for Other Spot Cleaning/Spot
Removers (Including Carpet Cleaning) 173
Table 2-52. Estimated Number of Workers Potentially Exposed to PCE During Other Industrial Usesl74
Table 2-53. Summary of Exposure Modeling Results for Other Industrial Uses of PCE 175
Table 2-54. Summary of Exposure Monitoring Data for Other Commercial Uses of PCE 176
Table 2-55. Estimated Number of Workers Potentially Exposed to PCE During Waste Handling,
Disposal, Treatment, and Recycling 179
Table 2-56. Summary of Exposure Modeling Results for Waste Handling, Disposal, Treatment, and
Recycling 179
Page 12 of 636
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Table 2-57. Summary of Inhalation Monitoring Data for Other DoD Uses (Oil Analysis) of PCE 181
Table 2-58. Summary of Inhalation Monitoring Data for Other DoD Uses (Water Pipe Repair) of PCE
182
Table 2-59. Summary of Inhalation Exposure Results 184
Table 2-60. Glove Protection Factors for Different Dermal Protection Strategies 191
Table 2-61. Estimated Dermal Acute Retained Dose for Workers in All Conditions of Use 193
Table 2-62. Residential Indoor Air Concentrations (|ig/m3) of PCE in the United States and Canada . 202
Table 2-63. Personal Breathing Zone Air Concentrations (|ig/m3) for PCE in the United States
(General/Residential) 205
Table 2-64. CEM Consumer Product Modeling Scenarios and Key Product Parameters 212
Table 2-65. Consumer Product Modeling Scenarios and Key Westat Product Use Parameters 215
Table 2-66. Consumer inhalation exposure to PCE during use in degreasers for motors, coils, electrical
parts, cables, stainless steel and marine equipment, and wire and ignition demoisturants
218
Table 2-67. Consumer dermal exposure to PCE during use in degreasers for motors, coils, electrical
parts, cables, stainless steel and marine equipment, and wire and ignition demoisturants
218
Table 2-68. Consumer inhalation exposure to PCE during use in brake cleaner 219
Table 2-69. Consumer dermal exposure to PCE during use in brake cleaner 220
Table 2-70. Consumer inhalation exposure to PCE during use in parts cleaners 221
Table 2-71. Consumer dermal exposure to PCE during use in parts cleaners 221
Table 2-72. Consumer inhalation exposure to PCE during use in vandalism stain removers, mold
cleaners, weld splatter protectants 222
Table 2-73. Consumer inhalation exposure to PCE during use in marble polish 223
Table 2-74. Consumer dermal exposure to PCE during use in marble polish 223
Table 2-75. Consumer inhalation exposure to PCE during use in cutting fluids 224
Table 2-76. Consumer inhalation exposure to PCE during use in lubricating and penetrating oils 225
Table 2-77. Consumer inhalation exposure to PCE during use in adhesives 225
Table 2-78. Consumer inhalation exposure to PCE during use in livestock grooming adhesive 226
Table 2-79. Consumer inhalation exposure to PCE during use in caulks, sealants and column adhesives
227
Table 2-80. Consumer inhalation exposure to PCE during use in outdoor water shield sealants 228
Table 2-81. Consumer dermal exposure to PCE during use in outdoor water shield sealants 228
Table 2-82. Consumer inhalation exposure to PCE during use in aerosol coatings and primers 229
Table 2-83. Consumer inhalation exposure to PCE during use in rust primers and sealants 230
Table 2-84. Consumer dermal exposure to PCE during use in rust primers and sealants 230
Table 2-85. Consumer inhalation exposure to PCE during use in metallic overglaze 231
Table 2-86. Consumer inhalation exposure to PCE during use in wax-based metal and stone polish... 232
Table 2-87. Consumer dermal exposure to PCE during use in wax-based metal and stone polish 232
Table 2-88 Concentrations (|ig/m3) of PCE in indoor air, personal breathing zones, and breath from
exposure studies with dry cleaned textiles placed in the home or automobile 235
Table 2-89. Cumulative mass released for number of days post dry cleaning and number of hours the
garment was worn (10 hr), based on Tichenor (1990) and Sherlach (2011). Values were
used as modeling inputs for the residual pool of PCE available for exposure 239
Table 2-90. Dermal exposure results to recently dry cleaned articles, based on CEM modeling 240
Table 2-91. Emission parameters for MCCEM modeling of PCE emissions from recently dry cleaned
clothing 241
Table 2-92. MCEEM calculated PCE air concentrations for storage of recently dry cleaned articles in a
generic house 242
Page 13 of 636
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Table 2-93. MCEEM calculated PCE maximum 24-hour TWAs for storage of recently dry cleaned
articles in a generic house 242
Table 2-94. Percentage of Employed Persons by Age, Sex, and Industry Sector 247
Table 2-95. Percentage of Employed Adolescent by Detailed Industry Sector 247
Table 3-1. Ecological Hazard Characterization of PCE for Aquatic Organisms 250
Table 3-2. COCs for Environmental Toxicity 255
Table 3-3. Summaries of Newer Epidemiologic Cancer Studies Published after the 2012 IRIS
Toxicological Review 274
Table 3-4. Tumor incidence in mice exposed to PCE 298
Table 3-5. Conversion of Acute PODs for Different Exposure Durations 301
Table 3-6. Human equivalent candidate unit risks, derived using PBPK-derived dose metrics and
multistage model; tumor incidence data from JISA (1993) for hepatocellular adenomas or
carcinomas 307
Table 3-7. Summary of PODs for Evaluating Human Health Non-Cancer Hazards from Acute Exposure
Scenarios 308
Table 3-8. Summary of PODs for Evaluating Human Health Non-Cancer Hazards from Chronic
Exposure Scenarios 310
Table 3-9. Summary of PODs for Evaluating Cancer Hazards from Chronic Inhalation Scenarios 311
Table 3-10. Derivation of Dermal PODs by Route-to-Route Extrapolation 313
Table 4-1. RQs Calculated using Monitored Environmental Concentrations from Water Quality Portal
320
Table 4-2. Selected Non-cancer PODs for Use in Risk Estimation of Inhalation Exposures 333
Table 4-3. Inhalation Exposure Data Summary and Respirator Use Determination 334
Table 4-4. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Manufacturing 337
Table 4-5. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Manufacturing 337
Table 4-6. Risk Estimation for Chronic, Cancer Inhalation Exposures for Manufacturing 338
Table 4-7. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Import/Repackaging 339
Table 4-8. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Import/Repackaging.. 339
Table 4-9. Risk Estimation for Chronic, Cancer Inhalation Exposures for Import/Repackaging 340
Table 4-10. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Processing as Reactant 340
Table 4-11. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Processing as Reactant
341
Table 4-12. Risk Estimation for Chronic, Cancer Inhalation Exposures for Processing as Reactant.... 342
Table 4-13. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Incorporation into
Formulation, Mixture, or Reactant Product 343
Table 4-14. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Incorporation into
Formulation, Mixture, or Reactant Product 343
Table 4-15. Risk Estimation for Chronic, Cancer Inhalation Exposures for Incorporation into
Formulation, Mixture, or Reactant Product 345
Table 4-16. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Batch Open-Top Vapor
Degreasing 346
Table 4-17. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Batch Open-Top Vapor
Degreasing 346
Table 4-18. Risk Estimation for Chronic, Cancer Inhalation Exposures for Batch Open-Top Vapor
Degreasing 347
Table 4-19. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Batch Closed-Loop Vapor
Degreasing 347
Table 4-20. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Batch Closed-Loop
Vapor Degreasing 347
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Table 4-21. Risk Estimation for Chronic, Cancer Inhalation Exposures for Batch Closed-Loop Vapor
Degreasing 348
Table 4-22. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Conveyorized Vapor
Degreasing 348
Table 4-23. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Convey orized Vapor
Degreasing 349
Table 4-24. Risk Estimation for Chronic, Cancer Inhalation Exposures for Convey orized Vapor
Degreasing 349
Table 4-25. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Web Degreasing 350
Table 4-26. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Web Degreasing 350
Table 4-27. Risk Estimation for Chronic, Cancer Inhalation Exposures for Web Degreasing 350
Table 4-28. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Cold Cleaning 351
Table 4-29. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Cold Cleaning 352
Table 4-30. Risk Estimation for Chronic, Cancer Inhalation Exposures for Cold Cleaning 353
Table 4-31. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Aerosol Degreasing and
Aerosol Lubricants 353
Table 4-32. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Aerosol Degreasing and
Aerosol Lubricants 354
Table 4-33. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Aerosol Degreasing and
Aerosol Lubricants 355
Table 4-34. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Dry Cleaning and Spot
Cleaning 356
Table 4-35. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Dry Cleaning and Spot
Cleaning 356
Table 4-36. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Dry Cleaning and Spot
Cleaning 358
Table 4-37. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Adhesives, Sealants,
Paints, and Coatings 359
Table 4-38. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Adhesives, Sealants,
Paints, and Coatings 359
Table 4-39. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Adhesives, Sealants,
Paints, and Coatings 360
Table 4-40. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Maskant for Chemical
Milling 361
Table 4-41. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Maskant for Chemical
Milling 361
Table 4-42. Risk Estimation for Chronic, Cancer Inhalation Exposures for Maskant for Chemical
Milling 362
Table 4-43. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Industrial Processing Aid
362
Table 4-44. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Industrial Processing
Aid 362
Table 4-45. Risk Estimation for Chronic, Cancer Inhalation Exposures for Industrial Processing Aid 363
Table 4-46. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Metalworking Fluids .. 364
Table 4-47. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Metalworking Fluids 364
Table 4-48 Risk Estimation for Chronic, Cancer Inhalation Exposures for Metalworking Fluids 365
Table 4-49. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Wipe Cleaning and
Metal/Stone Polishes 365
Page 15 of 636
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Table 4-50. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Wipe Cleaning and
Metal/Stone Polishes 365
Table 4-51. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Wipe Cleaning and
Metal/Stone Polishes 366
Table 4-52. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Other Spot Cleaning/Spot
Removers (Including Carpet Cleaning) 366
Table 4-53. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Other Spot
Cleaning/Spot Removers (Including Carpet Cleaning) 367
Table 4-54. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Other Spot Cleaning/Spot
Removers (Including Carpet Cleaning) 367
Table 4-55. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Other Industrial Uses.. 368
Table 4-56. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Other Industrial Uses368
Table 4-57. Risk Estimation for Chronic, Cancer Inhalation Exposures for Other Industrial Uses 369
Table 4-58. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Other Commercial Uses
369
Table 4-59. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Other Commercial Uses
370
Table 4-60. Risk Estimation for Chronic, Cancer Inhalation Exposures for Other Commercial Uses .. 372
Table 4-61. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Waste Handling, Disposal,
Treatment, and Recycling 373
Table 4-62. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Waste Handling,
Disposal, Treatment, and Recycling 373
Table 4-63. Risk Estimation for Chronic, Cancer Inhalation Exposures for Waste Handling, Disposal,
Treatment, and Recycling 374
Table 4-64. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Other Department of
Defense Uses 375
Table 4-65. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Other Department of
Defense Uses 375
Table 4-66. Risk Estimation for Chronic, Cancer Inhalation Exposures for Other Department of Defense
Uses 376
Table 4-67. Selected Non-cancer PODs for Use in Risk Estimation of Dermal Exposures 377
Table 4-68. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Industrial Uses That
Generally Occur in Closed Systems 378
Table 4-69. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Industrial Uses That
Generally Occur in Closed Systems 378
Table 4-70. Risk Estimation for Chronic, Cancer Dermal Exposures for Industrial Uses That Generally
Occur in Closed Systems 379
Table 4-71. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Industrial Degreasing and
Chemical Maskant Uses Which Are Not Closed Systems 379
Table 4-72. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Industrial Degreasing and
Chemical Maskant Uses Which Are Not Closed Systems 379
Table 4-73. Risk Estimation for Chronic, Cancer Dermal Exposures for Industrial Degreasing and
Chemical Maskant Uses Which Are Not Closed Systems 380
Table 4-74. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Aerosol Uses 380
Table 4-75. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Aerosol Uses 381
Table 4-76. Risk Estimation for Chronic, Cancer Dermal Exposures for Aerosol Uses 381
Table 4-77. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Commercial Activities of
Similar Maximum Concentration 382
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Table 4-78. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Commercial Activities of
Similar Maximum Concentration 382
Table 4-79. Risk Estimation for Chronic, Cancer Dermal Exposures for Commercial Activities of
Similar Maximum Concentration 383
Table 4-80. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Metalworking Fluids 383
Table 4-81. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Metalworking Fluids ... 383
Table 4-82. Risk Estimation for Chronic, Cancer Dermal Exposures for Metalworking Fluids 384
Table 4-83. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Adhesives, Sealants, Paints,
and Coatings 384
Table 4-84. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Adhesives, Sealants,
Paints, and Coatings 385
Table 4-85. Risk Estimation for Chronic, Cancer Dermal Exposures for Adhesives, Sealants, Paints, and
Coatings 386
Table 4-86. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Aerosol Cleaners for
Motors Consumer Use 387
Table 4-87. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Aerosol Cleaners for Motors
Consumer Use 387
Table 4-88. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Aerosol Brake Cleaners
Consumer Use 388
Table 4-89. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Aerosol Brake Cleaner
Consumer Use 388
Table 4-90. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Parts Cleaners Consumer
Use 389
Table 4-91. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Parts Cleaners Consumer Use
389
Table 4-92. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Vandalism Stain
Removers, Mold Cleaners, and Weld Splatter Protectants Consumer Use 390
Table 4-93. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Liquid-Based Marble
Polish Consumer Use 390
Table 4-94. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Liquid-Based Marble Polish
Consumer Use 391
Table 4-95. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Cutting Fluid Consumer
Use 391
Table 4-96. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Lubricants and Penetrating
Oils Consumer Use 392
Table 4-97. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Adhesives Consumer Use
393
Table 4-98. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Livestock Grooming
Adhesives Consumer Use 393
Table 4-99. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Caulks, Sealants and
Column Adhesives Consumer Use 394
Table 4-100. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Outdoor Water Shield
Consumer Use 394
Table 4-101. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Outdoor Water Shield
Consumer Use 395
Table 4-102. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Aerosol Coatings and
Primers Consumer Use 395
Table 4-103. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Liquid Primers and
Sealants Consumer Use 396
Page 17 of 636
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Table 4-104. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Liquid Primers and Sealants
Consumer Use 396
Table 4-105. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Metallic Overglaze
Consumer Use 397
Table 4-106. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Metal and Stone Polish
Consumer Use 398
Table 4-107. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Metal and Stone Polish
Consumer Use 398
Table 4-108. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Dry Cleaned Clothing
Consumer Use 399
Table 4-109. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Dry Cleaned Clothing
Consumer Use 399
Table 4-110. Modeled Facilities Showing RQs and Days of Exceedance from the Release of PCE to
Surface Water as Modeled in E-FAST. Acute risk = RQs > 1, chronic and algae risk =
RQs > 1 and > 20 days of exceedance. Shaded areas show risk 405
Table 4-111. PPE Protection Limits Considered for Risk Determination by Sector 426
Table 4-112 Summary of Risk Estimates for Inhalation and Dermal Exposures to Workers by Condition
of Use 427
Table 4-113 Summary of Risk Estimates for CNS effects from Acute Inhalation and Dermal Exposures
to Consumers by Conditions of Use 450
Table 5-1. Summary of Unreasonable Risk Determinations by Condition of Use 460
LIST OF FIGURES
Figure 1-1. PCE Life Cycle Diagram 45
Figure 1-2. PCE Conceptual Model for Industrial and Commercial Activities and Uses: Potential
Exposures and Hazards 50
Figure 1-3. PCE Conceptual Model for Consumer Activities and Uses: Potential Exposures and Hazards
51
Figure 1-4. PCE Conceptual Model for Environmental Releases and Wastes: Potential Ecological
Exposures and Hazards 52
Figure 1-5. Literature Flow Diagram for Environmental Fate Information 55
Figure 1-6. Literature Flow Diagram for Engineering Releases and Occupational Exposure 56
Figure 1-7. Literature Flow Diagram for Consumer and Environmental Exposure Data Sources 57
Figure 1-8. Literature Flow Diagram for Environmental Hazard Data Sources 58
Figure 1-9. Literature Flow Diagram for Human Health Hazard Data Sources 59
Figure 2-1. Diagram demonstrating the transport, partitioning, and degradation of PCE in the
environment 63
Figure 2-2. An overview of EPA's Approach to Estimate Daily Wastewater Discharges 64
Figure 2-3. WQP Search Option. Surface water data were obtained from the WQP by querying the
Sampling Parameters search option for the characteristic (STORET data), Parameter
Code (NWIS data), and date range parameter 93
Figure 2-4. Distribution of Active Facility Releases Modeled 97
Figure 2-5. Modeled Release Characteristics (Percent Occurrence) 98
Figure 2-6. Temporal WQX Sampling and Surface Water Concentration Trends: 2013 - 2017 100
Figure 2-7. Colocation of PCE Releasing Facilities and WQX Monitoring Stations at the HUC 8 and
IILC 12 Level 104
Figure 2-8. Colocation of PCE Releasing Facilities and WQX Monitoring Stations at the HUC 8 and
HUC 12 Level 104
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Figure 3-1. EPA Approach to Hazard Identification, Data Integration, and Dose-Response Analysis for
PCE 256
Figure 3-2. Sequence of steps for extrapolating from PCE bioassays in animals to human-equivalent
exposures expected to be associated with comparable cancer risk (combined interspecies
and route-to-route extrapolation) 305
Figure 4-1 Concentrations of PCE from PCE-Releasing Facilities (Maximum Days of Release Scenario)
and WQX Monitoring Stations: Year 2016, East US. All indirect releases are mapped at
the receiving facility unless the receiving 322
Figure 4-2 Concentrations of PCE from PCE-Releasing Facilities (Maximum Days of Release Scenario)
and WQX Monitoring Stations: Year 2016, West US. All indirect releases are mapped at
the receiving facility unless the receiving facility is unknown 322
Figure 4-3. Concentrations of PCE from PCE-Releasing Facilities (20 Days of Release Scenario) and
WQX Monitoring Stations: Year 2016, East US. All indirect releases are mapped at the
receiving facility unless the receiving facility is unknown 324
Figure 4-4. Concentrations of PCE from PCE-Releasing Facilities (20 Days of Release Scenario) and
WQX Monitoring Stations: Year 2016, West US. All indirect releases are mapped at the
receiving facility unless the receiving facility is unknown 325
LIST OF APPENDIX TABLES
Table_Apx A-l. Federal Laws and Regulations 568
Table_Apx A-2. State Laws and Regulations 574
Table_Apx A-3. Regulatory Actions by Other Governments and Tribes 575
TableApx D-l. Industry Sector Modeled for Facilities without Site-Specific Flow Data in E-FAST
2014 580
Table Apx D-2. Occurrence of PCE Releases (Facilities) and Monitoring Sites By HUC-8 581
Table Apx D-3. Occurrence of PCE Releases (Facilities) and Monitoring Sites By HUC-12 585
Table_Apx D-4. States with Monitoring Sites or Facilities in 2016 590
Table Apx E-l. Model predictions for hepatocellular tumors in male mice (JISA, 1993)a, using several
dose metrics and multistage cancer model 591
Table Apx E-2. Model predictions for hepatocellular tumors in female mice (JISA, 1993)a, using
several dose metrics and multistage cancer model 597
Table Apx G-l. Chronic Inhalation Risk Estimates by OES 633
LIST OF APPENDIX FIGURES
Figure Apx C-l. Screen capture of EPISuite™ parameters used to calculate fate and physical chemical
properties for PCE 579
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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).
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 68HERC19D0003), SRC (Contract No. EP-W-12-003 and
68HERH19D0022), and Abt Associates (Contract No. EPW-16-009).
Docket
Supporting information can be found in public docket:
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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864 ABBREVIATIONS
°C Degrees Celsius
|ig Microgram(s)
1-BP 1-Bromopropane
1Q10 Lowest 1-day average flow that occurs (on average) once every 10 years
30Q5 Lowest 30-day average flow that occurs (on average) once every 5 years
7Q10 Lowest 7-day average flow that occurs (on average) once every 10 years
AAP Alanine aminopeptidase
ABC ATP Binding Cassette
AC Acute Concentration
ACGIH® American Conference of Government Industrial Hygienists
ADC Average Daily Concentrations
ADME Absorption/Distribution/Metabolism/Elimination
ADR Acute Dose Rate
AEGL Acute Exposure Guideline Level
AF Assessment Factor
ALS Amyotrophic Lateral Sclerosis
ALT Aminotransferase
AML Acute Myeloid Leukemia
ANCA Antineutrophil-Cytoplasmic Antibody
APF Assigned Protection Factor
ASD Autism Spectrum Disorder
Atm Atmosphere(s)
ATSDR Agency for Toxic Substances and Disease Registries
AUC Area Under the Curve
Avg Average
BAF Bioaccumulation Factor
BCF Bioconcentration Factor
BIOWIN EPI Suite biodegredation module
BLS US Bureau of Labor Statistics
BMD Benchmark Dose
BMDL/BMCL Benchmark Dose/Concentration Lower Bound
BMR Benchmark Dose Response
BW Body Weight
CAA Clean Air Act
CARB California Air Resources Board
CASRN Chemical Abstracts Service Registry Number
CBI Confidential Business Information
CCI Color Confusion Index
CCL4 Carbon Tetrachloride
CD Cluster of Differentiation
CDC Centers for Disease Control
CDR Chemical Data Reporting
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CDSMF
California Death Statistical Master File
CEHD
Chemical Exposure Health Data
CEM
Consumer Exposure Model
CEPA
Canadian Environmental Protection Agency/Act
CERCLA
Comprehensive Environmental Response, Compensation and Liability Act
CF
Conversion Factor
CFC
Chi orofluorocarb on
CFR
Code of Federal Regulations
CHIRP
Chemical Risk Information Platform
ChV
Chronic Toxicity Value
CI
Confidence Interval
cm3
Cubic Centimeter(s)
CNS
Central Nervous System
CoA
Coenzyme A
COC
Concentration of Concern
COPD
Chronic Obstructive Pulmonary Disease
CoRAP
Community Rolling Action Plan
COU
Condition of Use
CP
Centipoise
CPCat
Chemical and Product Categories
CPS
Current Population Survey
CPSC
Consumer Product Safety Commission
CSCL
Chemical Substances Control Law
CT
central tendency
CWA
Clean Water Act
CYP
Cytochrome P
DCA
Dichloroacetic Acid
DF
Dilution Factor
DLBCL
Diffuse Large B-cell Lymphoma
DMR
Discharge Monitoring Report
DNA
Deoxyribonucleic Acid
DNAPL
Dense Non-Aqueous Phase Liquid
DNP
Dinitrophenol
DoD
Department of Defense
DQE
Data Quality Evaluation
EC50
Half Maximal Effective Concentration
ECHA
European Chemicals Agency
ECHO
Enforcement and Compliance History Online
ECOTOX
ECOTOXicology knowledgebase
EDC
Ethylene Dichloride
EEG
El ectrocochl eogram
E-FAST
Exposure and Fate Assessment Screening Tool
EG
Effluent Guidelines
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ELCR Excess Lifetime Cancer Risk
EPA Environmental Protection Agency
EPANET EPA water distribution system model
EPCRA Emergency Planning and Community Right-to-Know Act
EPISuite Estimation Programs Interface (EPI) Suite
ESD Emission Scenario Documents
EU European Union
FDA Food and Drug Administration
FFDCA Federal Food, Drug and Cosmetic Act
FHSA Federal Hazardous Substance Act
FIFRA Federal Insecticide, Fungicide and Rodenticide Act
FR(s) Federal Regulation
G Gram(s)
GACT Generally Available Control Technology
GD Gestation Day
GIS Geographical Information System
GM Geometric Mean
GPS Global Positioning System
GS Generic Scenario
GSD Geometric Standard Deviation
GSH Glutathione
GST Glutathione S-transferase
HAP Hazardous Air Pollutant
HCFC Hydrochlorofluorocarbon
HC1 Hydrochloric Acid
HE High End
HEC Human Equivalent Concentration
HED Human Equivalent Dose
HERO Health and Environmental Research Online (database)
HFC Hydrofluorocarbon
HPV High Production Volume
Hr Hour(s)
HRs Hazard Ratios
HSIA Halogenated Solvents Industry Association
HUC Hydrologic Unit Codes
i.p. Intraperitoneal
IARC International Agency for Research on Cancer
ICD International Classification of Diseases
IDLH Immediately Dangerous to Life and Health
IgA Immunoglobulin A
IgE Immunoglobulin E
IRIS Integrated Risk Information System
IRTA Institute for Research and Technical Assistance
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ISHA Industrial Safety and Health Act
IUR(s) Inhalation Unit Risk(s)
kg Kilogram(s)
L Liter(s)
LADC Lifetime Average Daily Concentration
lb Pound(s)
LC50 Lethal Concentration 50
LDH Lactate Dehydrogenase
LOAEC Lowest Observable Adverse Effect Concentration
LOAEL Lowest Observed Adverse Effect Level
LOD Limit of Detection
LOEC Lowest Observed Effect Concentration
Log Koc Logarithmic Organic Carbon:Water Partition Coefficient
Log Kow Logarithmic Octanol: Water Partition Coefficient
m3 Cubic Meter(s)
MACT Maximum Achievable Control Technology
Max. Maximum
MCCEM Multi-Chamber Concentration Exposure Model
MCL Mononuclear Cell Leukemia (Hazard sections)
MCL Maximum Contaminant Level (Surface Water sections)
MCLG Maximum Contaminant Level Goal
MF Mycosis Fungoides
Mfg Manufacturing
mg Milligram(s)
Min Minute
Min. Minimum
MLD Million Liters per Day
MM Multiple Myeloma
mmHg Millimeter(s) of Mercury
MO A Mode of Action
MOE Margin of Exposure
mRNA Messenger RNA
MSDS Material Safety Data Sheet
n Number variable (also N)
N/A Not Available; Not Applicable
NAAQS National Ambient Air Quality Standards
NAC National Advisory Committee
NAcTCVC N-acetylate TCVC
NAG N-acetyl glucuronidase
NAICS North American Industry Classification System
NATA National Air Toxics Assessment
NAWQA National Water-Quality Assessment
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NCEA
National Center for Environmental Assessment
NCHS
National Center for Health Statistics
ND
Non-detect
NDI
National Death Index
NEI
National Emissions Inventory
NESHAP
National Emission Standards for Hazardous Air Pollutants
NHANES
National Health and Nutrition Examination Survey
NHD
National Hydrological Dataset
NHEXAS
National Human Exposure Assessment Survey
NHL
non-Hodgkin lymphoma
NICNAS
National Industrial Chemicals Notification and Assessment Scheme
NIH
National Institutes of Health
NIOSH
National Institute for Occupational Safety and Health
NITE
National Institute of Technology and Evaluation
NOACC
Nordic Occupational Cancer Study
NOAEC
No Observable Adverse Effect Concentration
NOAEL
No Observed Adverse Effect Level
NOEC
No Observable Effect Concentration
NOEL
No Observable Effect Level
NPDES
National Pollutant Discharge Elimination System
NPDWR
National Primary Drinking Water Regulations
NPL
National Priorities List
NR
Not Reported
NRC
National Research Council
NTP
National Toxicology Program
NWIS
National Water Information Systems
OAQPS
Office of Air Quality Planning and Standards
OCPSF
Organic Chemicals, Plastics and Synthetic Fibers
OCSPP
Office of Chemical Safety and Pollution Prevention
ODS
Ozone Depleting Substance
OECD
Organisation for Economic Co-operation and Development
OEHHA
Office of Environmental Health Hazard Assessment
OEL
Occupational Exposure Limit
OEM
Original Equipment Manufacturer
OES
Occupational Exposure Scenarios
ONU
Occupational Non-User
OPPT
Office of Pollution Prevention and Toxics
ORs
Odds Ratios
OSHA
Occupational Safety and Health Administration
OTPR
Oily Type Paint Removers
OTVD
Open Top Vapor Degreasing
PAPR
Power Air-Purifying Respirator
RPB
Retinol-binding protein
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PBPK
Physiologically Based Pharmacokinetic
PBZ
Personal Breathing Zone
PCA
Passive Cutaneous Anaphylaxis
PCE
Perchloroethylene
PCO
Palmitoyl CoA Oxidation
PDM
Probabilistic Dilution Model
PECO
Populations, Exposures, Comparators and Outcomes
PEL
Permissible Exposure Limit
PESS
Potentially Exposed Susceptible Subpopulation
PF
Protection Factor
pH
Potential for Hydrogen (also Power of Hydrogen)
PND
Postnatal Day
POD
Point of Departure
POTW
Publicly Owned Treatment Works
PPARa
Peroxisome Proliferator-Activated Receptor alpha
ppb
Part(s) per Billion
PPE
Personal Protective Equipment
ppm
Part(s) per Million
Ptrend
P-value trend
PWS
Public Water System
RCRA
Resource Conservation and Recovery Act
RDD
Relative Delivered Dose
RESO
Receptors, Exposure, Setting (or Scenario), Outcome
RfC(s)
Reference Concentration(s)
RQ
Risk Quotient
RR
Risk Ratio
Fraction of an organ tissue homogenate used in biological assays to add
vjy
metabolic activity
SAR
Supplied-Air Respirator
SARA
Superfund Amendments and Reauthorization Act
SCBA
Self-Contained Breathing Apparatus
SCEs
Sister Chromatid Exchange(s)
SCHER
Scientific Committee on Health and Environmental Risks
SD
Standard Deviation
SDS
Safety Data Sheet
SDWA
Safe Drinking Water Act
SEMS
Superfund Enterprise Management System
SF
Stream Flow
SHIELD
School Health Initiative: Environment, Learning, Disease
SIC
Standard Industry Classification
SIDS
Screening Information Data Set
SIR
Standardized Incidence Ratios
SMR
Standard Mortality Ratio
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SNAP
Significant New Alternatives Policy
SpERC
Specific Environmental Release Category
SSADMF
Social Security Administration Death Master File
STEL
Short-Term Exposure Limit
STEWARDS
USDA ARS Sustaining the Earth's Watersheds - Agricultural research Database
System
STORET
EPA STORage and RETrieval data warehouse
STP
Standard Temperature and Pressure
SUSB
U.S. Census Statistics of US Businesses
SWC
Surface Water Concentration
tl/2
Half-life
TCA
Trichloroacetic Acid
TCAC
Trichloroacetyl Chloride
TCCR
Transparent, Clear, Consistent, and Reasonable
TCE
Trichl oroethy 1 ene
TCOH
Trichloroethanol
TCVC
S-(l,2,2-trichlorovinyl) cysteine
TCVCS
TCVC sulfoxide
TCVG
S-(l,2,2-trichlorovinyl) glutathione
TCVMA
N-acetyl-S-(trichlorovinyl)-l-cystine
TEAM
Total Exposure Assessment Methodology
TLV®
Threshold Limit Value
TRI
Toxics Release Inventory
TSCA
Toxic Substances Control Act
TTO
Total Toxic Organics
TWA
Time-Weighted Average
U.S.
United States
UFs
Uncertainty Factors
USGS
United States Geological Survey
VA
Veteran's Affairs
VACCR
Veteran's Affairs Central Cancer Registry
VOC
Volatile Organic Compound
WBC
White Blood Cells
WESTAT
National solvent usage survev fWes 7)
WHO
World Health Organization
WOE
Weight of Evidence
WQP
Water Quality Portal
WQX
Water Quality Exchange
WWR
Waste Water Release
WWTP
Wastewater Treatment Plants
Yr
Year(s)
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EXECUTIVE SUMMARY
This draft risk evaluation for perchloroethylene 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 (TSCA), 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 (82 FR 33726), EPA is taking comment on this draft, and will also obtain peer review on
this draft risk evaluation for PCE. 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. The preliminary conclusions, findings, and determinations in this draft
risk evaluation are for the purpose of identifying whether the chemical substance presents unreasonable
risk of injury to health or the environment under the conditions of use, including unreasonable risk to a
potentially exposed or susceptible subpopulation (PESS) in accordance with TSCA section 6, and are
not intended to represent any findings under TSCA section 7.
PCE is subject to federal and state regulations and reporting requirements. PCE has been a reportable
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 is subject to National Primary Drinking Water
Regulations (NPDWR) under the Safe Drinking Water Act (SDWA) and designated as a toxic pollutant
under the Clean Water Act (CWA) and as such is subject to effluent limitations.
PCE is currently manufactured, processed, distributed, used, and disposed of as part of industrial,
commercial, and consumer conditions of use. PCE has a wide-range of uses, including production of
fluorinated compounds, and as a solvent in dry cleaning and vapor degreasing. A variety of consumer
and commercial products use PCE such as adhesives (arts and crafts, as well as light repairs), aerosol
degreasing, brake cleaners, aerosol lubricants, sealants, stone polish, stainless steel polish and other wipe
cleaners (cleaners used for wiping surfaces). EPA evaluated the following categories of conditions of
use: manufacturing; processing; distribution in commerce, industrial, commercial and consumer uses
and disposal. The yearly aggregate production volume ranged from 388 to 324 million pounds between
2012 and 2015.
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 published since the publication of
previous analyses. EPA reviewed the information and evaluated the quality of the methods and
reporting of results of the individual studies using the evaluation strategies described in Application of
Systematic Review in TSCA Risk Evaluations ( 1018b).
In the problem formulation, EPA identified the conditions of use and presented three conceptual models
and an analysis plan for this draft risk evaluation. These have been carried into the draft risk evaluation
where EPA has quantitatively evaluated the risk to the environment and human health, using both
monitoring data and modeling approaches, for the conditions of use (identified in Section 1.4.1 of this
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draft risk evaluation) and exposure pathways within the scope of the risk evaluation. While PCE is
present in various environmental media, such as groundwater, surface water, and air, EPA stated in the
problem formulation that EPA did not expect to include in the risk evaluation certain exposure
pathways that are under the jurisdiction of other EPA-administered statutes in this draft risk evaluation
as described in Section 1.4.
EPA quantitatively evaluated the risk to aquatic species from exposure to surface water from the
manufacturing, processing, use, or disposal of PCE. EPA used environmental fate parameters,
physical-chemical properties, modelling, and monitoring data to assess ambient water exposure to
aquatic species. During the systematic review process, EPA identified and evaluated studies that
warranted further evaluation. Therefore, exposures to aquatic organisms from ambient surface water,
are assessed and presented in this draft risk evaluation and used to inform the risk determination.
These analyses are described in Sections 2.1, 2.3, 4.1.
EPA evaluated exposures to PCE in occupational and consumer settings for the conditions of use
included in the scope of the risk evaluation, listed in Section 1.4 (Scope of the Evaluation). In
occupational settings, EPA evaluated acute and chronic inhalation exposures to occupational users
(workers) and occupational non-users (ONUs)1, and acute and chronic dermal exposures to workers.
EPA used inhalation monitoring data from literature sources, where reasonably available and that met
data evaluation criteria, as well as modeling approaches, where reasonably available, to estimate
potential inhalation exposures. Dermal doses for workers were estimated in these scenarios since
dermal monitoring data was not reasonably available. In consumer settings, EPA evaluated acute
inhalation exposures to both consumers and bystanders, and acute dermal exposures to consumers.
Inhalation exposures and dermal doses for consumers and bystanders in these scenarios was estimated
since inhalation and dermal monitoring data were not reasonably available. These analyses are
described in Section 2.4 of this draft risk evaluation.
EPA reviewed the environmental hazard data using the data quality review evaluation metrics and the
rating criteria described in the Application of Systematic Review in TSCA Risk Evaluations (
2018b). EPA concluded that PCE poses a hazard to environmental aquatic receptors with algae being the
most sensitive taxa for exposures. The results of the environmental hazard assessment are in Section 3.1.
EPA evaluated reasonably available information for human health hazards and identified hazard
endpoints including acute and chronic toxicity for non-cancer effects and cancer. EPA used the
Framework for Human Health Risk Assessment to Inform Decision Making ( ) to
evaluate, extract, and integrate PCE's human health hazard and dose-response information. EPA
reviewed key and supporting information from previous hazard assessments, EPA IRIS Toxicologic
Review (U.S. EPA2012e). an AT SDR Toxicological Profile (AT SDR 20191 AEGL (NAC/AEGL
2009). and other international assessments listed in Table 1-3. EPA also screened and evaluated new
studies that were published since these reviews (i.e., from 2012 - 2018).
EPA developed a hazard and dose-response analysis using endpoints observed in inhalation and oral
hazard studies, evaluated the weight of the scientific evidence considering EPA and National Research
Council (NRC), risk assessment guidance and selected the points of departure (POD) for acute and
chronic, non-cancer endpoints, and inhalation unit risk and cancer slope factors for cancer risk
estimates. Potential health effects of PCE exposure analyses are described in Section 3.2.
1 ONUs are workers who do not directly handle PCE but perform work in an area where PCE is present.
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Risk Characterization
Environmental Risk
For environmental risk, EPA utilized a risk quotient (RQ) to compare the environmental concentration
to the effect level to characterize the risk to aquatic organisms. The results of the risk characterization
are in Section 4.1, including a table that summarizes the RQs for acute and chronic risks.
EPA identified expected environmental exposures for aquatic species under the conditions of use in the
scope of the risk evaluation. The estimated releases from specific facilities result in modeled surface
water concentrations that were equal to or exceed the aquatic benchmark (RQ > 1) for seven conditions
of use, indicating that exposures resulting from environmental concentrations were greater than the
effect concentration or the concentration of concern. Details of these estimates are in Section 4.1.2.
Human Health Risks
Risks were estimated following both acute and chronic exposure for representative endpoints from
every hazard domain. EPA identified potential cancer and non-cancer human health risks. The studies
that support the health concerns address neurotoxicity (CNS) effects from acute exposures, and
neurological, kidney, liver, immune system and developmental effects from chronic exposures and
cancer.
EPA estimated risk to workers from inhalation and dermal exposures, and risk to occupational non-
users (ONUs) from inhalation exposures by comparing the estimated exposures to acute and chronic
human health hazards For workers and ONUs, EPA estimated the cancer risk as the product of the
chronic exposure to PCE and the inhalation Unit Risk value for each COU. For dermal exposure to
workers, cancer risk was estimated as the product of the dermal exposure and the cancer slope factor for
each COU. For workers and ONUs, EPA estimated exposure and used the MOE approach to assess the
margin of exposure (MOE) for non-cancer health effects. For workers, EPA estimated risks using
several occupational exposure scenarios, which varied assumptions regarding the use of personal
protective equipment (PPE) for respiratory and dermal exposures for workers directly handling PCE.
More information on respiratory and dermal protection, including EPA's approach regarding the
occupational exposure scenarios for PCE, is in Section 2.4.1.
For occupational scenarios, using the MOE approach for non-cancer endpoints, risks were indicated for
all conditions of use, except for use of laboratory chemicals, under high-end inhalation or dermal
exposure scenarios if PPE was not used. For the majority of exposure scenarios, risk to workers were
identified for multiple endpoints in both acute and chronic exposure scenarios. Based on the PODs
selected from among the acute and chronic endpoints, acute and chronic non-cancer and cancer risks
were indicated for all but one exposure scenarios and occupational conditions of use under high-end
inhalation or dermal exposure levels without the use of PPE. Use of PPE during the assessed conditions
of use is expected to reduce worker exposure. This resulted in fewer conditions of use with estimated
risks for acute, chronic non-cancer, or cancer inhalation or dermal exposures. With assumed use of
respiratory protection, cancer risks from chronic inhalation exposures were not indicated for most
conditions of use. With assumed use of dermal protection, acute, chronic non-cancer, and cancer risks
were not indicated for some conditions of use. However, some conditions of use continued to present
non-cancer inhalation risks to workers under high end occupational exposure scenarios even with
assumed PPE (i.e., respirators APF 10, 25 or 50). EPA's estimates for worker risks for each
occupational exposure scenario are presented in Section 4.2.1 and summarized in Table 4-112.
ONUs are expected to have lower exposure levels than workers in most instances but exposures could
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not always be quantified based on reasonably available data and risk estimates for ONUs may be
similar to workers in some settings. While the difference between the exposures of ONUs and the
exposures of workers directly handling PCE generally cannot be quantified, ONU inhalation exposures
are expected to be lower than inhalation exposures for workers directly handling the chemical. In these
instances, EPA considered the ONU exposures to be equal to the central tendency risk estimates for
workers when determining ONU risk attributable to inhalation. While this is likely health protective as
it assumes ONU exposure is as high as it is for the majority of workers (greater numbers are likely to
be exposed near the middle of the distribution), this is uncertain. Dermal exposures are not expected
because ONUs do not typically directly handle PCE, nor they are in the immediate proximity of PCE.
Based on central-tendency exposure levels, acute and chronic non-cancer risks to ONUs were
indicated for the majority of exposure scenarios. ONUs are not assumed to be using PPE to reduce
exposures to PCE used in their vicinity. ONUs are not expected to be dermally exposed to
PCE and therefore dermal risks to ONUs were not assessed. EPA's estimates for ONU risks
for each occupational exposure scenario are presented alongside worker risk estimates in Section 4.2.2.
EPA also evaluated the risk to consumers from inhalation and dermal exposures, and to bystanders,
from inhalation exposures, by comparing the estimated exposures to acute human health hazards. For
consumers and bystanders for consumer use, EPA estimated non-cancer risks resulting from acute
inhalation or dermal exposures that were modeled with a range of user intensities, described in detail
in Section 2.4.1.30. EPA assumed that consumers or bystanders would not use PPE and that all
exposures would be acute rather than chronic.
For consumer users and bystanders, risks identified for acute exposures were indicated for some
conditions of use. For consumers, medium and high intensity acute inhalation and dermal exposure
scenarios indicated risk. Conditions of use that indicated risks following acute exposures to consumer
users (for inhalation and dermal exposure) also indicated risks to bystanders (primarily for inhalation
exposures only). One scenario, dry cleaning solvent, presented risks for bystanders in the dermal
scenario. Some consumer conditions of use did not indicate risks for consumer or bystanders. EPA's
estimates for consumer and bystander risks for each consumer use exposure scenario are presented in
Section 4.2.4 and summarized in Table 4-113 in Section 4.5.2.
Uncertainties
Key assumptions and uncertainties in the environmental risk estimation include the uncertainty around
modeled releases that have surface water concentrations greater than the highest concentration of
concern for algae. Data were reasonably available for three algal species and may not represent the
most sensitive species at a given site. For the human health risk estimation, key assumptions and
uncertainties are related to the estimates for ONU inhalation exposures because monitoring data were
not reasonably available for many of the conditions of use evaluated. Assumptions and key sources of
uncertainty for consumer exposure are detailed in Section 2.4.2.3 for consumer products, Section
2.4.2.4 for consumer articles, and Section 2.4.2.6 for overarching uncertainties.
Potentially Exposed and Susceptible Subpopulations
TSCA sec. 6(b)(4) requires that EPA evaluate risk to relevant potentially exposed or susceptible
subpopulations (PESS). TSCA sec. 3(12) states that "\t]he 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."
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In developing the risk evaluation, 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. For consideration of the most highly exposed
groups, EPA considered PCE exposures among both workers using PCE and ONUs in the vicinity of
PCE use to be higher than the exposures experienced by the general population. Consumer users and
bystanders are also expected to be more highly exposed than the general population. Potentially
susceptible subpopulations include the developing fetus (and by extension, women of childbearing
age) as well as those with pre-existing health conditions, higher body fat content, or particular genetic
polymorphisms.
Aggregate and Sentinel Exposures
Section 6 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).
Exposures to PCE were evaluated by inhalation and dermal routes separately. Inhalation and dermal
exposures are assumed to occur simultaneously for workers and consumers. EPA chose not to utilize
additivity of exposure pathways at this time within a condition of use because of the uncertainties
present in the current exposure estimation procedures and this may lead to an underestimate of exposure.
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 this risk evaluation, the EPA considered sentinel exposure the
highest exposure given the details of the conditions of use and the potential exposure scenarios.
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. 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 also takes into consideration the Agency's confidence in the data used
in the risk estimate. This includes an evaluation of the strengths, limitations, and uncertainties associated
with the information used to inform the risk estimate and the risk characterization. The rationale for the
risk determination is discussed in Section 5.1.
Environmental Risks
EPA evaluated environmental exposures for aquatic organisms and determined whether any risks are
unreasonable. The drivers for EPA's draft determination of unreasonable risks to aquatic organisms are
immobilization from acute exposure, growth effects from chronic exposure, and mortality to algae.
Algae was assessed separately and not incorporated into acute or chronic COCs, because durations
normally considered acute for other species (e.g., 48, 72 hours) can encompass several generations of
algae. EPA estimated site-specific surface water concentrations for discharges using upper and lower
bounds for the range of predicted surface water concentrations. For the percentage of the chemical
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removed from wastewater during treatment before discharge to a body of water, EPA estimated 80%
removal of PCE from indirect discharging facilities and estimated 0% removal of PCE for direct releases
to surface water. PCE has low bioaccumulation potential and moderate potential to accumulate in
wastewater biosolids, soil, or sediment.
For risks to the environment, EPA preliminarily determined that the conditions of use for PCE that
present unreasonable risks are processing as a reactant/intermediate, recycling, use as a processing aid in
petroleum production, and disposal. A full description of EPA's draft determination for each condition
of use is in Section 5.3.
Risks of Injury to Health
EPA's draft determination of unreasonable risk for specific conditions of use of PCE listed below are
based on health risks to workers, occupational non-users, consumers, or bystanders from consumer use.
As described below, risks to general population were not evaluated. PCE has a large database of human
health toxicity data. For each hazard domain there are several endpoints, and often a single endpoint was
examined by multiple studies. The non-cancer effects selected for risk estimation were neurotoxicity (i.e.,
increased latencies for pattern reversal visual-evoked potentials) from acute exposure and multiple effects
including CNS, kidney, liver, immune system and developmental toxicity from repeated and chronic
exposures. The evaluation of cancer includes estimates of risk of lung and liver tumors.
Risk to the General Population
General population exposures to PCE may occur from industrial and/or commercial uses; industrial
releases to air, water or land; and other conditions of use. As part of the problem formulation for PCE,
EPA found those exposure pathways are covered by other statutes and consist of: the ambient air
pathway (i.e., PCE is listed as a hazardous air pollutant (HAP) in the Clean Air Act (CAA)), the
drinking water pathway (i.e., National Primary Drinking Water Regulations (NPDWRs) are promulgated
for PCE under the Safe Drinking Water Act), ambient water pathways (i.e., PCE is a priority pollutant
with recommended water quality criteria for protection of human health under the CWA), and disposal
pathways (RCRA and SDWA regulations minimize further environmental exposure and associated risks
related to the disposal of PCE). As described in the problem formulation for PCE, other environmental
statutes administered by EPA adequately assess and effectively manage these exposures. EPA believes
that the TSCA risk evaluation should focus on those exposure pathways associated with TSCA
conditions of use that are not subject to the regulatory regimes discussed above because those pathways
are likely to represent the greatest areas of concern to EPA. 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.
Risk to Workers
EPA evaluated workers' acute and chronic inhalation and dermal exposures for cancer and non-cancer
risks and determined whether any risks are unreasonable. The drivers for EPA's draft determination of
unreasonable risk for workers are neurotoxicity from acute and chronic inhalation exposures,
neurotoxicity from chronic dermal exposures, and cancer resulting from chronic inhalation and dermal
exposures.
The determinations reflect the effects associated with the occupational exposures to PCE and
incorporate consideration of assumed PPE (frequently estimated to be a respirator of APF 10, 25, or 50
and gloves with PF 5, 10, or 20). Some conditions of use did not assume the use of respiratory PPE. For
workers, EPA determined that all applicable conditions of use for PCE presented unreasonable risks,
except for distribution in commerce, the industrial use of lubricants and greases (e.g., penetrating
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lubricants, cutting tool coolants), the industrial use of laboratory chemicals, the commercial use of
lubricants and greases (e.g., penetrating lubricants, cutting tool coolants), and the commercial use of
laboratory chemicals. A full description of EPA's draft determination of unreasonable risk for each
condition of use is in Section 5.3.
Risk to Occupational Non-Users (ONUs)
EPA evaluated ONU acute and chronic inhalation exposures for cancer and non-cancer risks and
determined whether any risks are unreasonable. The drivers for EPA's draft determination of
unreasonable risks to ONUs are neurotoxicity from acute and chronic inhalation, and cancer resulting
from chronic inhalation exposure. The draft determinations reflect the effects associated with the
occupational exposures to PCE and the assumed absence of PPE for ONUs. For dermal exposures,
because ONUs are not expected to be dermally exposed to PCE, dermal risks to ONUs were not
evaluated. For inhalation exposures, EPA, where possible, used monitoring or modeling information to
estimate ONU exposures and to describe the risks separately from workers directly exposed. For some
conditions of use, EPA did not separately calculate risk estimates for ONUs and workers. For these
conditions of use, there is uncertainty in the ONU risk estimates since the data or modeling did not
distinguish between worker and ONU inhalation exposure estimates. ONU inhalation exposures are
expected to be lower than inhalation exposures for workers directly handling the chemical substance;
however, the relative exposure of ONUs to workers in these cases cannot be quantified. To account for
this uncertainty, EPA considered the central tendency risk estimate when determining ONU risk for
those conditions of use for which ONU exposures were not separately estimated. EPA determined that
most applicable conditions of use do not present unreasonable risks. Estimated numbers of occupational
non-users are in Section 2.4.1.2.
Risk to Consumers
EPA evaluated consumer acute inhalation and dermal exposures for non-cancer risks and determined
whether any risks are unreasonable. The driver for EPA's draft determination of unreasonable risk is
neurotoxicity from acute inhalation and dermal exposure. Generally, risks for consumers were indicated
by acute inhalation and dermal exposure at low, medium, and high intensity use.
For consumers, EPA determined that most consumer conditions of use present unreasonable risks,
except for use of livestock grooming adhesive, aerosol paints and coatings, and metallic overglaze.
A full description of EPA's draft determination for each condition of use is in Section 5.3.
Risk to Bystanders (from consumer uses)
EPA evaluated bystander acute inhalation exposures for non-cancer risks and determined whether any
risks are unreasonable. The driver for EPA's determination of unreasonable risk are neurotoxicity from
acute inhalation exposure. Generally, risks for bystanders were indicated by acute inhalation exposure
scenarios at low, medium, and high intensity use. Because bystanders are not expected to be dermally
exposed to PCE, dermal non-cancer risks to bystanders were not evaluated. For bystanders, EPA
determined that most consumer conditions of use present unreasonable risks, except for use of dry
cleaned articles, arts and crafts adhesive, livestock grooming adhesive, caulks and sealants, aerosol
coatings and primers, liquid rust primer and sealant, and metallic overglaze.
A full description of EPA's draft determination for each condition of use is in Section 5.3.
Summary of Risk Determinations
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EPA has preliminarily determined that the following conditions of use of PCE do not present an
unreasonable risk of injury under any scenarios. The details of these determinations are presented in
Table 5-1 in Section 5.2.
Conditions of I so llisit Do Not Present sin I nre;is<>ii;ihie Kisk
• Distribution in commerce
• Industrial use of lubricants and greases (e.g., penetrating lubricants, cutting tool coolants)
• Industrial use of laboratory chemicals
• Commercial use of lubricants and greases (e.g., penetrating lubricants, cutting tool coolants)
• Commercial use of laboratory chemicals
• Consumer use of livestock grooming adhesive
• Consumer use of aerosol coating and primers
• Consumer use of metallic overglaze
EPA has preliminarily determined that the following conditions of use of PCE present an unreasonable
risk to the environment or unreasonable risk of injury to health to workers (including, in some cases,
occupational non-users) or to consumers (including, in some cases, bystanders). The details of these
determinations are presented in Table 5-1 in Section 5.2.
Msiniirsicliiring (lint Presents sin I nresisonsihle Kisk
• Domestic Manufacture
• Import (includes repackaging and loading/unloading)
Processing 1 h:il Presents :in I nre:ison:ihle Kisk
• Processing as a reactant/intermediate
• Incorporation into formulation, mixture or reaction product (cleaning and degreasing products)
• Incorporation into formulation, mixture or reaction product (adhesive and sealant products)
• Incorporation into formulation, mixture or reaction product (paint and coating products)
• Incorporation into formulation, mixture or reaction product (other chemical products and preparations)
• Repackaging
• Recycling
Indnslrisil I ses lliiil Present :i 11 I nresisoiiiihle Kisk
• As a solvent for batch vapor degreasing (open-top)
• As a solvent for batch vapor degreasing (closed-loop)
• As a solvent for in-line vapor degreasing (conveyorized)
• As a solvent for in-line vapor degreasing (web-cleaner)
• As a solvent for cold cleaning
• As a solvent for aerosol spray degreaser/cleaner
• In dry cleaning and spot cleaning (Post-2006 dry cleaning)
• In dry cleaning and spot cleaning (4th/5th Gen only dry cleaning)
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• As a lubricants and grease (aerosol lubricants)
• As a solvent-based adhesive and sealant
• As a solvent-based paint and coating
• As a maskant for chemical milling
• As a processing aids for pesticide, fertilizer and other agricultural chemical manufacturing
• As a processing aids specific to petroleum production (catalyst regeneration in petrochemical
manufacturing)
• In textile processing (spot cleaning)
• In textile processing (other)
• In wood furniture manufacturing
• As a laboratory chemical
• In foundry applications
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('ommercisil I ses 1 h;il Present ;i 11 Inrensonnhle Kisk
• As a cleaner and degreaser (wipe cleaning)
• As a cleaner and degreaser (other spot cleaning/spot removers (including carpet cleaning))
• As a cleaner and degreaser (mold release)
• In dry cleaning and spot cleaning (Post-2006 dry cleaning)
• In dry cleaning and spot cleaning (4th/5th Gen only dry cleaning)
• In automotive care products (e.g., engine degreaser and brake cleaner)
• As an aerosol cleaner
• As a non-aerosol cleaner
• As a lubricant and grease (aerosol lubricants)
• As a light repair adhesive
• As a solvent-based paint and coating
• In carpet cleaning
• In metal (e.g., stainless steel) and stone polishes
• In inks and ink removal products (printing)
• In inks and ink removal products (photocopying)
• In welding
• In photographic film
• In mold cleaning, release and protectant products
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Consumer I ses (lint Present sin I nresisonsihle Kisk
• As a cleaner and degreaser (other)
• In dry cleaning
• In automotive care products (brake cleaner)
• In automotive care products (parts cleaner)
• In aerosol cleaner (vandalism mark and stain remover, mold cleaner, weld splatter protectant)
• In non-aerosol cleaner (e.g., marble and stone polish)
• In lubricants and greases (cutting fluid)
• In lubricants and greases (lubricants and penetrating Oils)
• In adhesives for arts and crafts (includes industrial adhesive, arts and crafts adhesive, gun ammunition
sealant)
• In adhesives for arts and crafts (column adhesive, caulk and sealant)
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• In solvent-based paints and coatings (outdoor water shield (liquid))
• In rust primer and sealant (liquid)
• In metal (e.g., stainless steel) and stone polishes
• In inks and ink removal products; welding; mold cleaning, release and protectant products
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Disposal tlnil Presents sin I nrcnsonnblc Kisk
• Disposal
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1 INTRODUCTION
This document presents for comment the draft risk evaluation for PCE 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 PCE in June 2017 ( i), and
the problem formulation in June, 2018 ( i). These 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 problem
formulation identified conditions of use within the scope of the risk evaluation and presented three
conceptual models and an analysis plan. Based on EPA's analysis of the conditions of use, physical-
chemical and fate properties, environmental releases, and exposure pathways, the problem formulation
preliminarily concluded that further analysis was necessary for exposure pathways to aquatic receptors
exposed via surface water, workers, and consumers. The conclusions of the problem formulation were
that risk would not be evaluated for sediment, soil and land-applied biosolid pathways leading to
exposure to terrestrial and aquatic organisms. Risks would not be evaluated for land-applied biosolids
because PCE is currently being addressed in the Clean Water Act (CWA) regulatory analytical process.
EPA also excluded from risk evaluation ambient air, drinking water, land disposal, ambient water, and
waste incineration pathways leading to exposures to the general population and terrestrial organisms
since those pathways are regulated under other environmental statutes administered by EPA which
adequately assess and effectively manage exposures. EPA received comments on the published problem
formulation for PCE and has considered the comments specific to PCE, as well as more general
comments regarding EPA's chemical risk evaluation approach for developing the draft risk evaluations
for the first 10 chemicals EPA is evaluating.
In this draft risk evaluation, Section 1 presents the basic physical-chemical characteristics of PCE, as
well as a background on regulatory history, conditions of use, and conceptual models, with particular
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. Section 2 provides a
discussion and analysis of the exposures, both human health and environmental, that can be expected
based on the conditions of use for PCE. Section 3 discusses environmental and health hazards of PCE.
Section 4 presents the risk characterization, where EPA integrates and assesses reasonably available
information on 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
draft risk evaluation. Section 5 presents EPA's proposed determination of whether the chemical presents
an unreasonable risk under the conditions of use, as required under TSCA (15 U.S.C. 2605(b)(4)).
As per EPA's final rule, ( ), this draft risk evaluation will be subject to both public
comment and peer review, which are distinct but related processes. EPA is providing 60 days for public
comment on any and all aspects of this draft risk evaluation, including the submission of any additional
information that might be relevant to the science underlying the risk evaluation and the outcome of the
systematic review associated with PCE. This satisfies TSCA (15 U.S.C. 2605(b)(4)(H)), which requires
EPA to provide public notice and an opportunity for comment on a draft risk evaluation prior to
publishing a final risk evaluation.
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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
(I ), 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.
As EPA explained in the Risk Evaluation Rule (\ v < < \ _V I . it is important for peer reviewers to
consider how the underlying risk evaluation analyses fit together to produce an integrated risk
characterization, which forms the basis of an unreasonable risk determination. 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. 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. EPA will respond to public and peer review comments received on the draft risk
evaluation and will explain changes made to the draft risk evaluation for PCE in response to those
comments in the final risk evaluation.
EPA solicited input on the first 10 chemicals as it developed use documents, scope documents, and
problem formulations. At each step, EPA has 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
PCE. 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 feels 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.
1.1 Physical and Chemical Properties
Physical-chemical properties influence the environmental behavior and the toxic properties of a
chemical, thereby informing the potential conditions of use, exposure pathways and routes and hazards
that EPA intends to consider. For scope development, EPA considered the measured or estimated
physical-chemical properties set forth in Table 1-1; EPA found no additional information during
problem formulation or risk evaluation that would change these values.
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Table 1-1 Physical and Chemical Properties of PCE
Property
Value3
References
Data Quality
Rating
Molecular formula
C2CI4
Molecular weight
165.833
Physical form
Colorless liquid; chloroform-like
odor
Lewis (2007); NIOSH
(2005); U.S. Coast
Guard (1984)
High
Melting point
-22.3°C
Lide(2007)
High
Boiling point
121.3°C
Lide(2007)
High
Density
1.623 g/cm3 at 20°C
Lide(2007)
High
Vapor pressure
18.5 mmHg at 25°C
Riddick et al. (1985)
High
Vapor density
5.83 (relative to air)
(Lewis 1992)
High
Water solubility
206 mg/L at 20°C
Horvath (1982)
High
Octanol:water partition
coefficient (Kow)
3.40
Hansch et al. (1995)
High
Henry's Law constant
0.0177 atm-m3/mole
Gossett (1987)
High
Flash point
Not applicable
Nfoa (2010)
High
Autoflammability
Not readily available
Viscosity
0.839 cP at 25°C
Hickman (2000)
High
Refractive index
1.4775
Lide(2007)
High
Dielectric constant
2.30 at 25°C
(Lange and Dean
1985)
High
a Measured unless otherwise noted.
1.2 Uses and Production Volume
The uses of PCE include the production of fluorinated compounds, dry cleaning and vapor degreasing,
as well as a number of less produced uses. Nearly 65% of the production volume of PCE is used as an
intermediate in industrial gas manufacturing, more specifically to produce fluorinated compounds, such
as hydrofluorocarbons (HFCs) and hydrochlorofluorocarbons (HCFCs) (NTP 2014) (Icis 2011). HFCs
134a and 125 are alternatives to chlorofluorocarbons (CFCs) and HCFCs, which are ozone depleting
substances (ODSs), and the subject of a phase-out (https://www.epa.gov/ods-phaseout). HCFCs are
transitional substances in the phase-out of ODSs (Icis 2011). (Fay 2017). Previously, PCE was widely
used to manufacture CFCs (especially trichlorotrifluoroethane (CFC-113)) until production and
importation of CFCs for most uses were phased out in the United States by regulations implementing the
Montreal Protocol (40 CFR part 82). A relatively small amount of CFC-113 is still produced for
exempted uses (van Hook 2017).
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The second largest use of PCE (-15%) is as a solvent in dry cleaning facilities (NTP 2014). PCE is non-
flammable and effectively dissolves fats, greases, waxes and oils, without harming natural or human-
made fibers. These properties enabled it to replace traditional petroleum solvents (ATSDR 2014; Dow
Chemical Co 2008; Tirsell 2000). The demand for PCE dry cleaning solvents has steadily declined as a
result of the improved efficiency of dry cleaning equipment, increased chemical recycling and the
popularity of wash-and-wear fabrics that eliminate the need for dry cleaning (ATSDR 2019). PCE is
also used in dry cleaning detergent and dry cleaning sizing.
Approximately 60% of dry cleaning machines now use PCE as a solvent (DLI/Nt ). In 1991,
EPA estimated that 83% of all dry cleaning facilities used PCE as solvent 0 v i r \ I I) In 2008, the
Halogenated Solvents Industry Association (HSIA) estimated that 70% of dry cleaners used PCE as dry
cleaning solvent (Graul 2017). Similarly, in 201 1, King County, WA conducted a profile of the dry
cleaning industry and found that 69% of respondents (105 of the 152 respondents) used PCE in their
primary machine (Whittaker and Johanson 2011). Hence, there appears to be a trend towards alternatives
to PCE in dry cleaning. According to the dry cleaning industry, a majority of new PCE dry cleaning
machines are sold in locations where "local fire codes preclude the use of Class III combustible
alternative solvents or [where] the nature of the operation demands the use of PCE" (DLI/N ).
The third most prevalent use of PCE (-10%) is as a vapor degreasing solvent (NTP 2014). PCE can be
used to dissolve many organic compounds, select inorganic compounds and high-melting pitches and
waxes making it ideal for cleaning contaminated metal parts and other fabricated materials (ATSDR
2019). It is a very good solvent for greases, fats, waxes, oils, bitumen, tar and many natural and
synthetic resins for use in chemical cleaning systems, degreasing light and heavy metals, degreasing
pelts and leather (tanning), extraction of animal and vegetable fats and oils and textile dyeing (solvent
for dye baths) (Stove 2000). PCE is also used in cold cleaning, which is similar to vapor degreasing,
except that cold cleaning does not require the solvent to be heated to its boiling point in order to clean a
given component. Vapor degreasing and cold cleaning scenarios may include a range of open-top or
closed systems, conveyorized/enclosed/inline systems, spray wands, dip containers and wipes.
PCE has many other uses, which collectively constitute —10% of the production volume. EPA's search
of safety data sheets, government databases and other sources found over 375 products containing PCE.
These uses include (but are not limited to):
• Adhesives
• Aerosol degreasing
• Brake cleaner
• Laboratories
• Lubricants
• Mold cleaners, releases and protectants
• Oil refining
• Sealants
• Stainless steel polish
• Tire buffers and cleaners
• Vandal mark removers
Many of these uses include consumer products, such as adhesives (arts and crafts, as well as light
repairs), aerosol degreasing, brake cleaners, aerosol lubricants, sealants, sealants for gun ammunition,
stone polish, stainless steel polish and wipe cleaners. The uses of PCE in consumer adhesives and brake
cleaners are especially prevalent; EPA has found 16 consumer adhesive products and 14 consumer brake
cleaners containing PCE (see ( )).
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1357 The Chemical Data Reporting (CDR) Rule under TSCA requires U.S. manufacturers and importers to
1358 provide EPA with information on the chemicals they manufacture or import into the United States. For
1359 the 2016 CDR cycle, data collected per chemical include the company name, volume of each chemical
1360 manufactured/imported, the number of workers at each site, and information on whether the chemical is
1361 used in the Commercial, Industrial, and/or consumer sector. However, only companies that
1362 manufactured or imported 25,000 pounds or more at each of their sites during the 2015 calendar year
1363 were required to report information under the CDR rule ( 016d).
1364 The 2016 CDR reporting data for PCE are provided in Table 1-2 from EPA's CDR database (U.S. EPA.
1365 201 6c). This information has not changed from that provided in the scope document.
1366 Table 1-2 Production Volume of PCE in CDR Reporting Period (2012 to 2015) a
Reporting Year
2012
2013
2014
2015
Total Aggregate
Production Volume (lbs)
387,623,401
391,403,540
355,305,850
324,240,744
•' The CDR data for the 2016 rcoortinu period is available via ChemView (httDs://iava.eDa.gov/chemview) (ChemView
2019). The CDR data presented in the problem formulation is more specific than currently available in ChemView.
1367
1368
1369 1.3 Regulatory and Assessment History
1370 EPA conducted a search of existing domestic and international laws, regulations and assessments
1371 pertaining to PCE. EPA compiled this summary from data available from federal, state, international and
1372 other government sources, as cited in Appendix A.
1373 Federal Laws and Regulations
1374 PCE is subject to federal statutes or regulations, other than TSCA, that are implemented by other offices
1375 within EPA and/or other federal agencies/departments. A summary of federal laws, regulations and
1376 implementing authorities is provided in Appendix A.
1377 State Laws and Regulations
1378 PCE is subject to state statutes or regulations implemented by state agencies or departments. A summary
1379 of state laws, regulations and implementing authorities is provided in Appendix A.
1380 Laws and Regulations in Other Countries and International Treaties or Agreements
1381 PCE is subject to statutes or regulations in countries other than the United States. A summary of these
1382 laws and regulations is provided in Appendix A.
1383 Assessment History
1384 EPA identified assessments conducted by other EPA Programs and other organizations (see Table 1-3).
1385 Depending on the source, these assessments may include information on conditions of use, hazards,
1386 exposures and potentially exposed or susceptible subpopulations. EPA found no additional assessments
1387 beyond those listed in the Problem Formulation document.
1388 Table 1-3 Assessment History of PCE
Authoring Organization
Assessment
EPA Assessments
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Authoring Organization
Assessment
Integrated Risk Information System (IRIS)
Toxicological Review of Tetrachloroethylene
(Perchloroethylene) (CAS No. 127-18-4) (I; S
)
Office of Air Quality Planning and Standards
(OAQPS)
Perchloroethylene Dry Cleaners Refined Human
Health Risk Characterization ( 2005b)
National Center for Environmental Assessment
(NCEA)
Sources, Emission and Exposure for
Trichloroethylene (TCE) and Related Chemicals
( >00 n
Office of Air Toxics
Tetrachloroethylene (PCE, Perchloroethylene);
127-18-4 (US. EPA. 2000)
Office of Pesticides and Toxic Substances
(now, Office of Chemical Safety and Pollution
Prevention [OCSPP])
Occupational Exposure and Environmental
Release Assessment of Tetrachloroethylene (U.S.
35b)
Office of Health and Environmental Assessment
Final Health Effects Criteria Document for
Tetrachloroethylene (I v < < \ 1985a)
Office of Water (OW)
Update of Human Health Ambient Water Quality
Criteria: Tetrachloroethylene (Perchloroethylene)
127-18-4 ( b)
Office of Water (OW)
Ambient Water Quality Criteria for
Tetrachl oroethvl ene (TJ. S. EP A. 1980)
Other U.S.-Based Organizations
California Environmental Protection Agency,
Office of Environmental Health Hazard
Assessment (OEHHA), Air Toxics Hot Spots
Program
Perchloroethylene Inhalation Cancer Unit Risk
Factor ("OEHHA 2016)
Agency for Toxic Substances and Disease Registry
(AT SDR)
Toxicological Profile for Tetrachloroethylene
(PERCHATSD. )
National Advisory Committee for Acute Exposure
Guideline Levels for Hazardous Substances
(NAC/AEGL Committee)
Tetrachloroethylene (NAC/AEGL 2009)
California Environmental Protection Agency,
OEHHA, Pesticide and Environmental Toxicology
Section
Public Health Goal for Tetrachloroethylene in
Drinking Water (OEHHA 2001)
National Toxicology Program (NTP)
Toxicology and Carcinogenesis Studies of
Tetrachloroethylene (Perchloroethylene); (CAS
No. 127-18-4) in F344/N Rats and B6C3F1 Mice
(NTP 1986a)
International
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Authoring Organization
Assessment
International Agency for Research on Cancer
(IARC)
IARC Monographs on the Evaluation of
Carcinogenic Risks to Humans,
Tetrachloroethvlene (IARC 2014)
European Union (EU), Scientific Committee on
Health and Environmental Risks (SCHER)
SCHER, Scientific Opinion on the Risk
Assessment Report on Tetrachloroethylene,
Human Health Part, CAS No.: 127-18-4, 12
(Scher2008)
World Health Organization (WHO)
Concise International Chemical Assessment
Document 68; Tetrachloroethvlene (WHO 2006a)
EU, European Chemicals Bureau (ECB)
EU Risk Assessment Report; Tetrachloroethylene,
Part 1 - environment (ECB 2005)
National Industrial Chemicals Notification and
Assessment Scheme (NICNAS), Australia
Tetrachloroethylene; Priority Existing Chemical
Assessment Report No. 15 (NICNAS 2001)
1.4 Scope of the Evaluation
1.4.1 Conditions of Use Included in the Risk Evaluation
TSCA § 3(4) defines the Conditions of Use (COUs) 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 1-4. No additional information was received by EPA following the publication
of the problem formulation that would update or otherwise require changes to the use document
conditions of use ( d) Table 2-4) or the life cycle diagram as presented in the problem
formulation ( ). The life cycle diagram is presented in Figure 1-1.
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MFG/IMPORT
PROCESSING
INDUSTRIAL, COMMERCIAL, CONSUMER USES a RELEASES and WASTE DISPOSAL
Manufacture
(including Import)
(324,2 million lbs)
1401
Processing as
Reactant/lntermediate
(Volume CBI)
e.g., intermediate for
refrigerant manufacture
Incorporated into
Formulation, Mixture,
or Reaction Product
(>285,800 lb)
Incorporated into
Article
(Not reported to 2016
CDR)
Repackaging
(Volume CBI)
I
Recycling
(Volume CBI)
4
Cleaning and Furniture Care Products
(>348,770 lb)
e.g., dry cleaning, spot cleaning, aerosol cleaner 3nd
degreaser, aerosol spot remover, non-aerosol cleaner
Solvents for Cleaning and Degreasing
(>327,150 lb)
e.g., vapor degreaser, cold cleaner, aerosol degreaser
Lubricants and Greases
(316,716 lb)
e.g., penetrating lubricants
Adhesive and Sealant Chemicals
(Volume CBI)
e.g., solvent-based adhesives and sealants
Paints and Coatings
(Volume CBI)
e.g., solvent-based paints and coatings
Processing Aid for Agricultural Product
Manufacturing (Volume CBI)
e.g., pesticide, fertilizer, and other agricultural
product manufacturing
Processing Aid for Petrochemical
Manufacturing (Volume CBI)
e.g., catalyst regeneration
Other Uses
e.g., mold release product, metal polishes, inks
See F/gwe 2-4 for Environmental
Releases and Wastes
I ] Manufacture (Including Import)
Processing
Uses. At the scope level of detail in the life
cycle diagram EPA is not distinguishing
between industrial/commerciai/consumer
uses. The differences between these uses
will be further investigated and defined
during risk evaluation.
1402
1403
1404
1405
1406
1407
1408
Figure 1-1. PCE 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 (Table 1-2) (U.S. EPA 2016c). Activities related to distribution (e.g., loading, unloading) will be considered
throughout the PCE life cycle, rather than using a single distribution scenario.
a See Table 1-4 for additional uses not mentioned specifically in this diagram.
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1409 Table 1-4 Categories and Subcategories of Conditions of Use Included in the Scope of the Risk
1410 Evaluation
Life Cycle
Stage
Category 11
Subcategory h
References
Manufacture
Domestic
manufacture
Domestic manufacture
0 v < < \
2016c")
Import
Import
( >016c)
Processing
Processing as
a reactant or
intermediate
Intermediate in industrial gas
manufacturing
(U
20
20
20
); (U.S. EPA
17g); (Krock 2017a); (Krock
17b); (Cooper 2017); (Fav
17)
Intermediate in basic organic
chemical manufacturing
( 1016b"). (U.S. EPA.
jOi v);
Intermediate in petroleum refineries
( 1016b): (U.S. EPA
):fCoooer 2017")
Residual or byproduct
(Krock 2017a"); (Krock 2017b");
Incorporated
into
formulation,
mixture or
reaction
product
Cleaning and degreasing products
( >016b}; (Rudnick
2017a"). (Rudnick 2017b")
Adhesive and sealant products
( 10
16b)
Paint and coating products
( 10
16b)
Other chemical products and
preparations
(
16b)
Repackaging
Solvent for cleaning or degreasing
( 10
16b)
Intermediate
(
16b)
Recycling
Recycling
(
16b)
Distribution in
commerce
Distribution
Distribution
( 10
)
Industrial use
Solvents (for
cleaning or
degreasing)
Solvents and/or Degreasers (cold,
aerosol spray or vapor degreaser;
not specified in comment)
( ): (Holmes
2017"); (Tatman 2017")
Batch vapor degreaser (e.g., open-
top, closed-loop)
( >b); (Rieele
2017"); (HSIA 2018b")
In-line vapor degreaser (e.g.,
conveyorized, web cleaner)
( >b); (Dowell
201 7)
Solvents (for
cleaning or
degreasing)
Cold cleaner
( ): (Rudnick
2017a"). (Rudnick 2017b")
Aerosol spray degreaser/cleaner
(U
20
20
\ ); (U.S. EPA
L 7k); (Sass 2017); (Rudnick
17a), (Rudnic i :0l b)
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Life ('vole
Slsigc
Csilcgorv 11
SuhciiU'gorv h
UcfemuTS
Dry cleaning solvent
(u s i in i^i o: (u.s. epa.
2006a")
Spot cleaner
( ); (Sass 2017")
Lubricants
and greases
Lubricants and greases (e.g.,
penetrating lubricants, cutting tool
coolants, aerosol lubricants)
( ); (U.S. EPA
2017s"); (HSIA 2018b");
( nan 2017"); ffl'SIA 2018b");
(Tattnaii 2017)
Adhesive and
sealant
chemicals
Solvent-based adhesives and
sealants
( ). (U.S. EPA
v), (\ I r \ _<<| v);
rSass 2017"); (Rieele 2017");
(Holmes 2017"); ffl* . \
Paints and
coatings
including
paint and
coating
removers
Solvent-based paints and coatings,
including for chemical milling
(U
20
20
20
Ml6b); (U.S. EPA
17g); (Sass 2017); (Rieele
17); (Davis 2017); fflSIA
18b); 0 v Ih M» )
Processing
aids, not
otherwise
listed
Pesticide, fertilizer and other
agricultural chemical
manufacturing
( >016b}
Processing
aids, specific
to petroleum
production
Catalyst regeneration in
petrochemical manufacturing
( ); (U.S. EPA
2017s"); (Dow Chem 2008");
(Coooer :0i "); (ii^i \ :0tNh)
Other uses
Textile processing
(
)
Wood furniture manufacturing
(
)
Laboratory chemicals
( 10
2017")
); (Rieele
Foundry applications
0 ^ \ v)
Commercial/con
sumer use
Cleaning and
furniture care
products
Cleaners and degreasers (other)
(\ ^ \ ;oi O; (Sass 2017");
(Rudnick 2017a), (Rudnick
2017b); (Holmes 2017);
(McCormick 2017); (HSIA
2018b); (Tatman 2017)
Dry cleaning solvent
( X(
2006a); (DLI/NCA 2017); (Sass
2017)
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Life ('vole
Slsigc
Csilcgorv 11
SuhciiU'gorv h
UcfemuTS
Spot cleaner
rt; s i in i^i o: ru.s. epa.
2006a"); CSass 2017}
Automotive care products (e.g.,
engine degreaser and brake cleaner)
i v 11 \> 20i6d). a ; r \
); fRudnick 2017a").
fRudnick 2017b"); ffl'SIA
2018b")
Aerosol cleaner
( 10
); rSass 2017")
Non-aerosol cleaner
(
); rSass 2017")
Lubricants
and greases
Lubricants and greases (e.g.,
penetrating lubricants, cutting tool
coolants, aerosol lubricants)
(
2017s"); fflSI/
CTatman 2017
16b"); ai.S. EPA
12018b");
)
Adhesives
and sealant
chemicals
Adhesives for arts and crafts
( >016b"); ai.S. EPA.
:0t O; CSass 2017")
Light repair adhesives
( ); OJ.S. EPA
2017s")
Paints and
coatings
Solvent-based paints and coatings
( ); OJ.S. EPA
2017s"); rSass 2017"); TDavis
2017"); ffl'SIA 2018b")
Other uses
Carpet cleaning
( ); rSass 2017")
Laboratory chemicals
( )
Metal (e.g., stainless steel) and
stone polishes
0 ^ \ v)
Inks and ink removal products
(
)
Welding
( 10
)
Photographic film
( 10
)
Mold cleaning, release and
protectant products
(
2017a"). fRudr
); rRudnick
ick 2017b")
Disposal
Disposal
Industrial pre-treatment
0 ^ \ v)
Industrial wastewater treatment
Publicly owned treatment works
(POTW)
Underground injection
Municipal landfill
Hazardous landfill
Other land disposal
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Life ('vole
Slage
('allegory 11
S ii heal ego ry h
References
Municipal waste incinerator
Hazardous waste incinerator
Off-site waste transfer
Off-site waste transfer
a These categories of conditions of use appear in the life cycle diagram, reflect CDR codes and broadly represent conditions
of use for PCE in consumer, industrial, and/or commercial settings.
b These subcategories reflect more specific uses of PCE.
1.4.2 Conceptual Models
The conceptual models for this risk evaluation are shown in Figure 1-2, Figure 1-3, and Figure 1-4. EPA
considered the potential for hazards to human health and the environment resulting from exposure
pathways outlined in the preliminary conceptual models of the PCE scope document ( ).
These conceptual models considered potential exposures resulting from industrial and commercial
activities, consumer activities and uses and environmental releases and wastes. The problem formulation
documents refined the initial conceptual models and analysis plans that were provided in the PCE scope
document ( d).
For the purpose of this evaluation, EPA considered workers and occupational non-users, which includes
men and women of reproductive age (Figure 1-2). Consumer exposure was assessed for various
pathways for users age 11 and older along with bystanders of all ages (Figure 1-3).
The potential pathways that were determined to be included in the risk evaluation but not to warrant
further analysis in this draft risk evaluation were: exposure to both humans and ecological organisms
due to land application of biosolids following wastewater treatment leading to exposure terrestrial
organisms. In the problem formulation, EPA determined that risks would not be evaluated for land-
applied biosolids because PCE is currently being addressed in the Clean Water Act (CWA) regulatory
analytical process. Also, as outlined in Section 1.3 and Appendix A, PCE is regulated in various
environmental media.
The potential pathways that were determined to be included in the risk evaluation and further analyzed
include:
• Exposure to aquatic species (e.g. aquatic plants) via contaminated surface water.
• Inhalation and dermal exposures to workers and consumer users, and inhalation exposures to
ONUs and consumer bystanders, from industrial/commercial activities and consumer activities.
• Inhalation and dermal exposures to workers and inhalation exposures to ONUs from waste
handling, treatment and disposal.
Review and evaluation of reasonably available information on PCE confirmed the preliminary
conclusions in the problem formulation and as a result, the EPA confirms further analysis of the
pathways outlined in the conceptual models. The conceptual models for this risk evaluation are shown in
Figure 1-2, Figure 1-3, and Figure 1-4.
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INDUSTRIAL AND COMMERCIAL EXPOSURE PATHWAY EXPOSURE ROUTE RECEPTORS c HAZARDS
ACTIVITIES / USES
Figure 1-2. PCE 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 PCE.
a Some products are used in both commercial and consumer applications such adhesives and sealants. Additional uses of PCE are included in Table 1-4.
b Fugitive air emissions are those that are not stack emissions and include fugitive equipment leaks from valves, pump seals, flanges, compressors, sampling connections
and open-ended lines; evaporative losses from surface impoundment and spills; and releases from building ventilation systems.
0 Receptors include potentially exposed or susceptible subpopulations.
d Oral exposure may occur through mists that deposit in the upper respiratory tract however, based on physical chemical properties, mists of PCE will likely be rapidly
absorbed in the respiratory tract or evaporate and will be considered as an inhalation exposure.
e When data and information are available to support the analysis, EPA also considers the effect that engineering controls and/or personal protective equipment have on
occupational exposure levels
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CONSUMER ACTIVITIES/USESa EXPOSURE PATHWAY EXPOSURE ROUTE RECEPTORSb HAZARDS
Figure 1-3. PCE Conceptual Model for Consumer Activities and Uses: Potential Exposures and Hazards
The conceptual model presents the exposure pathways, exposure routes and hazards to human receptors from consumer activities and uses of
PCE.
a Some products are used in both commercial and consumer applications. Additional uses of PCE are included in Table 1-2.
b Receptors include potentially exposed or susceptible subpopulations.
0 Consumers oral exposure may occur through mists that deposit in the upper respiratory tract however, based on physical chemical properties, mists of PCE will likely be
rapidly absorbed in the respiratory tract or evaporate and will be considered as an inhalation exposure.
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1468
RELEASES AND WASTES FROM EXPOSURE PATHWAY RECEPTORS HAZARDS
INDUSTRIAL /COMMERCIAL USES
1469
1470 Figure 1-4. PCE Conceptual Model for Environmental Releases and Wastes: Potential Ecological Exposures and Hazards
1471 The conceptual model presents the exposure pathways, exposure routes and hazards to human and environmental receptors from
1472 environmental releases and wastes of PCE.
1473 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
1474 discharge).
1475
1476
1477
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1.5 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 under section 6 on the weight of 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
CFR 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 (US.
EPA. 2018c). 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 (40 CFR 702.33).
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 timelines of the statute.
1.5.1 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; environmental 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/abstract screening to
identify information potentially relevant for the risk evaluation process. The literature and
screening strategy as specifically applied to PCE is described in Strategy for Conducting
Literature Searches for Perchloroethylene (PCE) Supplemental File to the TSCA Scope
Document ( 017i) and the results of the title and abstract screening process were
published in PCE (CASRN127-18-4) Bibliography: Supplemental File for the TSCA Scope
Document; (U.S. EPA.: ).
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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framework2. Data sources that met the criteria were carried forward to the data evaluation stage.
The inclusion and exclusion criteria for full text screening for PCE are available in in Appendix
F of the Problem Formulation o f the Risk Evaluation for PCE ( 2018d).
Although EPA conducted a comprehensive search and screening process as described above,
EPA made the decision to leverage the literature published in previous assessments3 to identify
key and supporting data4 and information for developing the PCE risk evaluation. This is
discussed Strategy for Conducting Literature Searches for Perchloroethylene (PCE)
Supplemental File to the TSCA Scope Document (I v << \ ), In general, many of the key
and supporting data sources were identified in the comprehensive Perchloroethylene (CASRN
127-18-4) Bibliography: Supplemental File for the TSCA Scope Document; (U.S. EPA. ^ ).
However, there was an instance during the releases and occupational exposure data search for
which 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 Application of Systematic Review for TSCA Risk Evaluations
(I 018c). Other relevant key and supporting references were identified through targeted
supplemental searches to support the analytical approaches and methods in the PCE risk
evaluation (e.g., to locate specific information for exposure modeling).
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 Strategy for Conducting Literature Searches for Perchloroethylene
(PCE) Supplemental File 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 considered how evaluation of newer information in addition to the
key and supporting data and information would change the conclusions presented in previous
assessments.
2 A PESO statement was used during the full 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.
3 Examples of existing assessments are EPA's chemical assessments (e.g., previous work plan risk assessments,
problem formulation documents), ATSDR's Toxicological Profiles and EPA's IRIS assessments. This is described
in more detail in Strategy for Conducting Literature Searches for PCE (PCE) Supplemental File to the TSCA Scope
Document (U.S. EPA 20170.
4 Key and supporting data and information are those that support key analyses, arguments, and/or conclusions in the
risk evaluation.
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This pragmatic approach 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.
The figures below depict literature flow diagrams illustrating the results of this process for each
scientific discipline-specific evidence supporting the draft risk evaluation (Figure 1-5, Figure
1-6, Figure 1-7, Figure 1-8 and Figure 1-9). 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 releases and occupational exposure data sources that were
subject to a combined data extraction and evaluation step.
*Any relevant studies from prior assessments that were identified as potentially relevant for TSCA 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 1-5. Literature Flow Diagram for Environmental Fate Information
Note: Literature search results for the environmental fate and transport of PCE yielded 7,170 studies. During
problem formulation, following data screening, most environmental exposure pathways were removed from the
conceptual models. As a result, 7,091 studies were deemed off-topic and excluded. The remaining 79 studies related
to enviromnental exposure pathways retained in the conceptual models entered data evaluation, where 13 studies
were deemed unacceptable and 66 moved into data extraction and integration. Note: Data sources identified relevant
to physical-chemical properties were not included in this literature flow diagram. The data quality evaluation of
physical-chemical properties studies can be found in the supplemental document, (U.S. EPA 2019c) and the
extracted data are presented in Table 1-1.
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Figure 1-6. Literature Flow Diagram for Engineering Releases and Occupational Exposure
*The quality of data in these sources (n=201) were acceptable for risk assessment purposes, but they were ultimately
excluded from further consideration based on EPA's integration approach for enviromnental 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 or release limits). If
warranted, EPA may use data/information of lower rated quality as supportive evidence in the enviromnental release
and occupational exposure assessments.
Note: Literature search results for enviromnental release and occupational exposure yielded 7,342 data sources. Of
these data sources, 316 were determined to be relevant for the risk evaluation through the data screening process.
These relevant data sources were entered into the data extraction/evaluation phase. After data extraction/evaluation,
EPA identified several data gaps and performed a supplemental, targeted search to fill these gaps (e.g. to locate
information needed for exposure modeling). The supplemental search yielded 32 relevant data sources that bypassed
the data screening step and were evaluated and extracted in accordance with Appendix D: Data Quality Criteria for
Occupational Exposure and Release Data of the Application of Systematic Review for TSCA Risk Evaluations
document (U.S. EPA 2018c). Of the 348 sources from which data were extracted and evaluated, 90 sources only
contained data that were rated as unacceptable based on serious flaws detected during the evaluation. Of the 258
sources forwarded for data integration, data from 57 sources were integrated, and 201 sources contained data that were
not integrated (e.g., lower quality data that were not needed due to the existence of higher quality data, data for release
media that were removed from scope after data collection).
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'The quality of data in these sources were acceptable for risk assessment purposes and considered for
integration. The sources; however, were not extracted for a variety of reasons, such as they contained only
secondary source data, duplicate data, or non-extractable data (i.e., charts or figures). Additionally, some
data sources were not as relevant to the PECO as other data sources which were extracted.
Figure 1-7. Literature Flow Diagram for Consumer and Environmental Exposure Data
Sources
Note: EPA conducted a literature search to determine relevant data sources for assessing exposures for
perchloroethylene within the scope of the risk evaluation. This search identified 991 data sources including relevant
supplemental documents. Of these, 769 were excluded during the screening of the title, abstract, and/or full text and
222 data sources were recommended for data evaluation across up to five major study types in accordance with
Appendix E:Data Quality Criteria for Studies on Consumer, General Population and Environmental Exposure of
the Application of Systematic Re\>iew for TSCA Risk Evaluations document ( J.S. EPA 2018b). Following the
evaluation process, 120 references were forwarded for further extraction and data integration. EPA has not
developed data quality criteria for all types of exposure information, some of which may be relevant when
estimating consumer exposures. This is the case for absorption and permeability data and some product-specific data
such as density and weight fraction often reported in Safety Data Sheets. As appropriate, EPA evaluated and
summarized these data to determine their utility with supporting the risk evaluation.
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Figure 1-8. 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 PCE: Supplemental File for the TSCA Scope Document(\J.S. EPA
2017i). During problem formulation, EPA made refinements to the conceptual models resulting in the elimination of
the terrestrial exposure pathway. Thus, enviromnental hazard data sources on terrestrial organisms were considered
out of scope and excluded from data quality evaluation.
The literature search process for enviromnental hazard data found 3326 citations for PCE. At the title and abstract
screening phase, 3088 citations were excluded as off-topic using ECOTOXicology knowledgebase criteria. The
remaining 238 citations underwent a more thorough full text screening using the same criteria to determine which
citations should undergo data evaluation. For data evaluation, EPA developed data quality evaluation (DQE) criteria
to evaluate the data under TSCA, based on a combination of EPA's ECOTOXicology knowledgebase (ECOTOX)
criteria and the Criteria for Reporting and Evaluating ecotoxicity Data (CRED). There were 46 citations that went to
data evaluation for PCE. EPA analyzed each of these studies using the DQE results to determine overall study
quality. Thirty studies were considered acceptable and were rated high medium, or low quality during this analysis.
The extracted data from these 30 studies were used during data integration for PCE.
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Figure 1-9. Literature Flow Diagram for Human Health Hazard Data Sources
Note: The literature search results for human health hazard of PCE yielded 3794 studies. This included 40 key and
supporting studies identified from previous EPA assessments. Of the 3754 new studies screened for relevance, 3715
were excluded as off topic. The remaining 39 new studies together with the 40 key and supporting studies entered
data evaluation. Thirteen studies were deemed unacceptable based on the evaluation criteria for human health hazard
data sources and the remaining 66 studies were carried forward to data extraction/data integration. Additional details
can be found in the PCE Bibliography: Supplemental File for the TSCA Scope Document, (U.S. EPA 2017e).
1.5.2 Data Evaluation
During the data evaluation stage, the EPA assesses the quality of the methods and reporting of
results of the individual studies identified during problem formulation using the evaluation
strategies described in Application of Systematic Review in TSCA Risk Evaluations (U.S. EPA
2018b). The EPA evaluated the quality of the on-topic PCE study reports identified in
Perchloroethylene (CASRN127-18-4) Bibliography: Supplemental File for the TSCA Scope
Document; (U.S. EPA 2017e). and gave all studies an overall high, medium, low or unacceptable
confidence rating during data evaluation.
The results of the data quality evaluations for key studies are summarized in Section 2.1 (Fate and
Transport), Section 2.2 (Releases to the Environment), Section 2.3 (Environmental Exposures),
Section 2.4 (Human Exposures), Section 3 (Environmental Hazards) and Section 3.2 (Human
Health Hazards). Supplemental files (5.3.68Appendix B) also provide details of the data
evaluations including individual metric scores and the overall study score for each data source.
1.5.3 Data Integration
Data integration includes analysis, synthesis and integration of information for the risk
evaluation. During data integration, the EPA considers quality, consistency, relevancy,
coherence and biological plausibility to make final conclusions regarding the weight of the
scientific evidence. As stated in 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
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the major points of interpretation ( ). 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 (U.S. EPA.
2017h).
EPA used previous assessments (see Table 1-3) to identify key and supporting information and
then analyzed and synthesized available evidence regarding PCE'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
(1.5.1) 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 1.5.1. 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.
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1704 2 EXPOSURES
1705
1706 2.1 Fate and Transport
1707 Environmental fate includes both transport and transformation processes. Environmental
1708 transport is the movement of the chemical within and between environmental media.
1709 Transformation occurs through the degradation or reaction of the chemical with other species in
1710 the environment. Hence, knowledge of the environmental fate of the chemical informs the
1711 determination of the specific exposure pathways and potential human and environmental
1712 receptors EPA has considered during risk evaluation.
1713 2.1.1 Fate and Transport Approach and Methodology
1714 Fate data including biotic and abiotic degradation rates, removal during wastewater treatment,
1715 volatilization from lakes and rivers, and organic carbon:water partition coefficient (log Koc)
1716 were used when describing the fate of PCE. EPA gathered and evaluated environmental fate
1717 information according to the process described in the Application of Systematic Review in TSCA
1718 Risk Evaluations (U.S. EPA. 2018b). Table 2-1 provides environmental fate data that EPA
1719 considered while assessing the fate of PCE. This data was updated after problem formulation
1720 with information identified through systematic literature review. Additional study summaries are
1721 in the supplemental document, Draft Risk Evaluation for Perchloroethylene, Systematic Review
1722 Supplemental File: Data Extraction Tables for Environmental Fate and Transport Studies (
1723 )20h). and complete information on data quality evaluations for all identified fate data are
1724 available in the supplemental document, Draft Risk Evaluation for Perchloroethylene, Systematic
1725 Review Supplemental File: Data Quality Evaluation for Environmental Fate and Transport
1726 Studies ( 20j). Environmental fate properties not adequately reported in the literature
1727 were estimated using Estimation Programs Interface (EPI) Suite™ models, as described in
1728 Appendix C.
1729
1730 Table 2-1. Environmental Fate Characteristics of PCE
Properly or
Kndpoinl
Value 11
References
Data Quality
Ualing
Indirect
photodegradation
Atmospheric lifetime = 80-251 days,
equivalent to half-life = 55-174 days
(estimated for removal by reaction
with hydroxyl radical, •OH)
CCuoitt 1987)
High
Hydrolysis half-life
8.8 months
(Billing et al. 1975)
High
> Years
(Jeffers et al. 1989)
High
Aerobic
Biodegradation
86-87% in 28 days
(Tabak et al. 1981)
High
74% in batch-fed reactor
( eetal. 1993)
High
0% in continuous-flow system
(Bouwer and
McCartv 1982)
High
0% in 175 days
(Bouweret; 1)
Low
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Properly or
Kmlpoinl
Value 11
References
Data Quality
Rating
l.oss i)l"PCI- in sonic studies ma\ lie
due to volatilization
(Namkung and
Rittmann 1987;
Wakeham et al. 1983)
Medium.
Medium
Anaerobic
Biodegradation
100%) in 37 days
(Cabirol et al. 1996)
High
Approx. 38% in 30 days
fWoodetal. 1981)
High
44%-68% in 112 days
(Bouweret; 1)
High
Bioconcentration
factor (BCF)
25.8-77.1 (fish)
(Kawasa ))
High
49 (fish)
(Barrows et al. 1980)
High
39.7 (fish)
(Dow Chem 1973)
High
312 and 118 (marine algae)
(Wane et al. 1996)
High
Bioaccumulation
factor (BAF)
46 (estimated)13
(ECB 2005); (I * S
*r\
High
Organic carbon:water
partition coefficient
(log Koc)
2.95 (estimated)13
( )
High
a Measured unless otherwise noted.
b Information was estimated using EPI Suite™ (U.S. EPA 2012a")
1731 2,1.2 Summary of Fate and Transport
1732 The EPI Suite™ module that estimates chemical removal in sewage treatment plants ("STP"
1733 module) was run using default settings to evaluate the potential for PCE to be removed from
1734 wastewater. The STP module estimates that a total of 88% of PCE in wastewater will be
1735 removed, 82% by volatilization and 6% by adsorption to sludge organic matter. Based on the
1736 mixed aerobic biodegradation data reported for PCE (ranging from rapid to negligible
1737 biodegradation in aerobic environments; see Table 2-1) the overall removal of PCE in
1738 wastewater treatment plants is expected to range from 88% to complete. PCE has moderate
1739 potential to sorb to sludge organic matter and thus is expected to be present in biosolids
1740 (processed sludge). When biosolids are land applied, PCE will volatilize from solid and liquid
1741 phases during and after spraying, although some PCE may partition from biosolids into soil and
1742 groundwater.
1743
1744 In soil and aquifers, PCE has moderate potential to sorb to soil or sediment organic matter and
1745 may be transported to ground water. Anaerobic biodegradation, which is reported to be rapid to
1746 very slow depending on local conditions and microbial populations (WHO 2006a; ECB 2005).
1747 may be a significant degradation mechanism in soil and groundwater but. In anaerobic
1748 environments, PCE biodegradation products include potentially hazardous substances including
1749 trichloroethylene, cis-1,2 dichloroethene and vinyl chloride (de Bruin et al. 1992).
1750
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Based on its Henry's Law constant (0.0177 atm-m3/mole) and vapor pressure (18.5 mmHg at
20°C), PCE can be expected to volatilize from surface water to air and from soil to air. The EPI
Suite™ model that predicts volatilization for surface water ("Volatilization" module) estimated
the PCE volatilization half-life from a model river to be 1.4 hours, and the volatilization half-life
from a model lake to be 123 hours (5.1 days). In the vapor phase, PCE can be slowly
transformed by reaction with hydroxyl and other radicals with half-lives of months or greater,
and long-range transport may occur. In the atmosphere, PCE is expected to slowly degrade via
indirect photolysis (half-life > 80 days). Given its slow photodegradation, PCE is expected to
undergo long-range atmospheric transport.
With measured bioconcentration factors of 312 or lower and estimated bioaccumulation factor of
46, the bioaccumulation potential of PCE is low.
Overall, PCE has moderate potential to accumulate is wastewater biosolids, soil, and sediment,
and has low potential to biota and is expected to largely volatilize to the atmosphere where it
may undergo long-range transport and slowly degrade via indirect photolysis. The fate of PCE in
the environment is summarized in Figure 2-1.
Land-applied biosolids
7 atm-rrr/mole
Photolysis
t1/2 < 6 months
log Koc = 2.95
Aerobic Biodegradation
Rate = slow to rapid
Hydrolysis
t1/2 > 8.8 months
Surface Water
log Kqc = 2.95
Bioconcentration
BCF < 312
Groundwater Anaerobic Biodegradation Sediment
Rate = slow to rapid
Figure 2-1. Diagram demonstrating the transport, partitioning, and degradation of PCE in
the environment
In Figure 2-1, transport and partitioning are indicated by green arrows and degradation is
indicated by orange arrows. The width of the arrow is a qualitative indication of the likelihood
that the indicated partitioning will occur or the rate at which the indicated degradation will occur
(i.e., wider arrows indicate more likely partitioning or more rapid degradation). The question
marks over the aerobic and anaerobic biodegradation arrows indicate uncertainty regarding how
quickly PCE will biodegrade. Although transport and partitioning processes (green arrows) can
occur in both directions, the image illustrates the primary direction of transport indicated by
partition coefficients. Figure 2-1 considers only transport, partitioning, and degradation within
and among environmental media; sources to the environment such as discharge and disposal are
not illustrated.
2.1.3 Key Sources of Uncertainty in Fate and Transport Assessment
The experimentally determined PCE biodegradation rates in aerobic and anaerobic environments
ranged from slow to rapid (see Table 2-1). For comparison, the EPI Suite™ module that predicts
biodegradation rates ("BIOWIN" module) was run using default settings to estimate
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1787 biodegradation rates of PCE. The BIOWIN models for aerobic environments (BIOWIN 1-6)
1788 estimate that PCE will not rapidly biodegrade in aerobic environments. The BIOWIN model of
1789 anaerobic biodegradation (BIOWIN 7) predicts that PCE will biodegrade under anaerobic
1790 conditions. Overall, PCE biodegradation rates in the environment may vary based on factors
1791 including level of oxygenation, microorganisms present, and microorganisms' previous exposure
1792 and adaptation to PCE. This uncertainty in biodegradation rates was considered in the assessment
1793 of persistence in aerobic and anaerobic environments and estimates of removal from wastewater.
1794 2.2 Releases to the Environment
1795 2.2.1 Environmental Discharges of Wastewater
1796 EPA categorized the conditions of use (COUs) listed in Table 1-4 into 22 Occupational Exposure
1797 Scenarios (OES). For each OES, a daily wastewater discharge was estimated based on annual
1798 releases, release days, and the number of facilities (Figure 2-2). In this section, EPA describes its
1799 approach and methodology for estimating daily wastewater discharges, and for each OES,
1800 provides a summary of release days, number of facilities, and daily wastewater discharges. For
1801 detailed facility level results, see the "Water Release Assessment" section for each OES in the:
1802 Assessment of Occupational Exposure and Environmental Releases for Perchloroethylene
1803 (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) (U.S. EPA
1804 2020d).
1805
1806
1807 Figure 2-2. An overview of EPA's Approach to Estimate Daily Wastewater Discharges5.
1808 2.2.1.1 Results for Daily Wastewater Discharge Estimates
1809 EPA combined its estimates for annual releases, release days, and number of facilities to estimate
1810 a range for daily wastewater discharges for each OES. A summary of these ranges across
1811 facilities is presented in Table 2-2. Summary of EPA's Daily Wastewater Discharge Estimates
5 TRI = Toxics Release Inventory; DMR = Discharge Monitoring Report; NEI = National Emissions Inventory;
CDR = Chemical Data Reporting; EG = Effluent Guidelines; ESD = Emission Scenario Document; GS = Generic
Scenarios; SpERC = Specific Enviromnental Release Category
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for Each OES. For some OES, EPA was not able to estimate or did not expect water releases. For
example:
• OES Aerosol Degreasing and Aerosol Lubricants: Wastewater discharges containing
PCE were not expected due to its volatility; releases from this OES are expected to be to
air.
• OES Wipe Cleaning and Metal/Stone Polishes: Wastewater discharges containing
PCE were not expected due to its volatility and the nature of the wipe cleaning and
polishing process; releases from this OES are expected to be to air (volatilization) or with
shop rags to landfill/incineration.
• OES Other Spot Cleaning/Spot Removers (Including Carpet Cleaning): EPA did not
identify data to estimate wastewater discharges for this OES.
• OES Laboratory Chemicals: EPA did not identify data to estimate wastewater
discharges for this OES.
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Table 2-2. Summary of EPA's Daily Wastewater Discharge Estimates for Each PES6
Occupational
Kxposure
Scenario
(OKS)
Release
Media/
Treatment
l-'acility
Type"
N il in her of
Sites with
Wastewater
Discharges1'
Kslimaled Daily
Release Range
Across Sites
(kg/site-dav)1
Overall
Confidence
Corresponding Section
in the Supplemental
Knginccring Report
( )
Minimum'1
.Maximum
Manufacturing
Surface
Water
1
1.7E-03
M
Section 2.1.4
Non-POTW
WWT
1
4.1E-02
M
Surface
Water or
POTWe
4
8.9E-05
0.1
M
Repackaging
Surface
Water
3
9.1E-05
4.8E-03
M
Section 2.2.4
Non-POTW
WWT
1
1.1
M
Processing as a
Reactant
Surface
Water
18
1.2E-05
1.3
M
Section 2.3.4
POTW
1
0.1
M
Incorporation
into
Formulation,
Mixture, or
Reaction
Product
Surface
Water
1
1.7E-03
M
Section 2.4.4
POTW
1
1.5E-03
M
Non-POTW
WWT
1
5.3
M
Batch Open-
Top Vapor
Degreasingf
Surface
Water
16
9.0E-07
7.1E-02
M
Section 2.5.4
POTW
1
3.5E-04
M
6 Although EPA has identified both industrial and commercial uses here for purposes of distinguishing scenarios in this document, the Agency interprets the
authority over "any manner or method of commercial use" under TSCA section 6(a)(5) to reach both.
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Occupsilionsil
Kxposurc
Sccnsirio
(Ol-S)
Kelesise
Media/
Trcsilmcnl
l-'sicililv
N il in her of
Sites with
Wsislcwsilcr
Diselisirges1'
Kslimsiled Dsiilv
Uelesise Usinge
Across Siles
(kg/sile-dsiv)1'
Oversill
Confidence
('» rres po n d i n g Sec 1 io n
in llic Siippleinenlsil
Knginccring Ucporl
( )
Type11
Minimum'1
M si xi in ii in
Batch Closed-
Loop Vapor
Degreasing
Included with release estimates for Batch Open Top Vapor Degreasingf.
Section 2.6.4
Conveyorized
Vapor
Degreasing
Included with release estimates for Batch Open Top Vapor Degreasingf.
Section 2.7.4
Web Vapor
Degreasing
Included with release estimates for Batch Open Top Vapor Degreasingf.
Section 2.8.4
Cold Cleaning
Included with release estimates for Batch Open Top Va]
por Degreasingf.
Section 2.9.4
Aerosol
Degreasing
and Aerosol
Lubricants
EPA does not expect wastewater discharges containing
PCE from these sites.
H
Section 2.10.4
Dry Cleaning
and Spot
Cleaning
(commercial)
POTW
12,822
5.6E-04
1.7E-03
M
Section 2.11.4
Dry Cleaning
and Spot
Cleaning
(industrial)
Surface
Water
2
4.5E-05
2.1E-04
M
Section 2.11.4
Adhesives,
Sealants,
Paints, and
Coatings
POTW
41
2.0
370
M
Section 2.12.4
Maskant For
Chemical
Surface
Water
3
5.9E-06
8.6E-04
M
Section 2.13.4
Milling
POTW
2
2.6E-03
1.1E-02
M
Industrial
Processing Aid
Surface
Water
12
3.0E-04
8.6E-02
M
Section 2.14.4
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Occupsilionsil
Kxposurc
Sconsirio
(Ol-S)
Kelesise
Media/
Trcsilmcnl
l-'sicililv
Type11
N il in her of
Sites with
Wsislcwsilcr
Diselisirges1'
Kslimsiled Dsiilv
Uelesise Usinge
Across Siles
(kg/sile-dsiv)1'
Oversill
Confidence
('» rres po n d i n g Sec 1 io n
in llic Siipplcmcnlsil
Knginccring Ucporl
( )
Minimum'1
M si xi in ii in
POTW
2*
8.8E-02
U.4
M
Metalworking
Fluids
Included with release estimates for Batch Open Top Vapor Degreasingf.
Section 2.15.4
Wipe Cleaning
and
Metal/Stone
Polishes
EPA does not expect wastewater discharges containing
PCE from these sites.
H
Section 2.16.4
Other Spot
Cleaning/Spot
Removers
(Including
Carpet
Cleaning)
EPA did not identify data to estimate wastewater discharges for this OES.
Section 2.17.4
Other
Industrial Uses
Surface
Water
7
1.1E-06
0.3
M
Section 2.18.4
Other
Commercial
Uses
Surface
Water
7
1.3E-05
2.9E-03
M
Section 2.19.4
Laboratory
Chemicals
EPA did not identify data to estimate wastewater discharges for this OES.
Section 2.20.4
Waste
Handling,
Disposal,
Treatment, and
Recycling
Surface
Water
5
5.9E-05
3.8E-03
M
Section 2.21.4
POTW
4
3.6E-07
0.3
M
Non-POTW
WWT
4
5.4E-03
1.4
M
Other
Department of
Defense Uses
EPA did not identify data to estimate wastewater discharges for this OES.
Section 2.22.4
1828 a The daily discharge estimates presented in this table represent both direct discharges to surface water and indirect discharges to POTW and non-POTW WWT.
1829 Removal efficiencies at POTWs and non-POTW WWT are taking into account in the environmental exposure assessment.
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b For most conditions of use, only a subset of the sites use are expected to discharge wastewater containing PCE. Other sites may dispose of PCE-containing
wastes through other means such as via landfill or incineration.
0 Except for commercial dry cleaning estimates; the minimum and maximum daily discharge estimates are based on site-specific discharges (i.e., the minimum
corresponds to the site with the lowest discharge and the maximum corresponds to the site with the highest discharge). Minimum daily discharge at any given site
may be higher than the minimum presented, and the maximum daily discharge may be lower than the value presented.
d The minimum presented represents the minimum of the sites that have wastewater discharges, it does not include sites that dispose of PCE through other media
which would result in a minimum of zero for most OES.
e Discharges from these sites may be to either surface water or POTW but not both for a given site.
f EPA does not have enough information to distinguish whether these sites use PCE in OTVDs, closed-loop degreasers, conveyorized degreasers, web degreasers,
cold cleaners, or metalworking fluids. Therefore, the daily release estimates may include sites that perform any of these activities.
g These two sites reported both direct and indirect discharges.
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2.2.1.2 Approach and Methodology
2.2,1.2.1 Wastewater Discharge Estimates
EPA performed a literature search to identify process operations that could potentially result in
direct or indirect discharges to water for each condition of use. Where available, EPA used 2016
Toxics Release Inventory (TRI) ( ) and 2016 Discharge Monitoring Report
(DMR) (U.S. EPA. 2016a) data to provide a basis for estimating releases. 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 pounds for manufacturers and processors of PCE and 10,000
pounds for users of PCE). Due to these limitations, some sites that manufacture, process, or use
PCE may not report to TRI and are therefore not included in these datasets.
For the 2016 DMR, EPA used the Water Pollutant Loading Tool within EPA's Enforcement and
Compliance History Online (ECHO) to query all PCE point source water discharges in 2016.
DMR data are submitted by National Pollutant Discharge Elimination System (NPDES) permit
holders to states or directly to the EPA according to the monitoring requirements of the facility's
permit. States are only required to load major discharger data into DMR and may or may not
load minor discharger data. The definition of major vs. minor discharger is set by each state and
could be based on discharge volume or facility size. Due to these limitations, some sites that
discharge PCE may not be included in the DMR dataset.
Facilities reporting discharges in TRI and DMR also report associated NAICS and Standard
Industrial Classification (SIC) industry codes, respectively. Where possible, EPA reviewed the
NAICS and SIC descriptions for each reported discharge and mapped each facility to a potential
condition of use associated with occupational exposure scenarios (OES, see Table 2-12). For
facilities that did not report a NAICS or SIC code, EPA performed a supplemental internet
search of the specific facility to determine the mapping. Facilities that could not be mapped were
grouped together into an "Other" category.
EPA's preference was to use TRI or DMR data to assess wastewater discharges; however, due to
the reporting requirements for each dataset (described above in this section), these data may not
be available for all conditions of use or for all sites within a condition of use. In such cases, EPA
estimated wastewater discharges using release data from literature, relevant emission scenario
documents (ESD) or generic scenarios (GS), existing EPA/OPPT models, and/or relevant
Effluent Guidelines (EG). EG are national regulatory standards set forth by EPA for wastewater
discharges to surface water and municipal sewage treatment plants.
When possible for each OES covering conditions of use, EPA estimated annual releases, average
daily releases, and number of release days/yr. Where TRI and/or DMR were available, EPA used
the reported annual releases for each site and estimated the daily release by averaging the annual
release over the estimated release days/yr. Where ESDs, GSs, existing models, or EGs were used
EPA estimated a daily release and calculated the annual release by multiplying the daily release
by the number of release days per year.
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1925
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2.2.1.2,2 Estimates of Number of Facilities
Where available. EPA uSed 2016 CDR ( ), 2016 TRI ( ). 2016
Discharge Monitoring Report (DMR) (I v
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1930
1931 Table 2-3 summarizes the number of facilities estimates for each OES. Based on reasonably
1932 available data, EPA does not expect all sites within a condition of use will have wastewater
1933 discharges containing PCE; therefore, the number of facilities estimates in Table 2-3 may be
1934 greater than the number of sites presented in release summary in Table 2-2.
1935
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1936 Table 2-3. Summary of EPA's Estimates for the Number of Facilities for Each PES
Occupational Kxposure
Scenario (OES)
Number of
I'acililies
Notes
Manufacturing
8
Based on CDR reporting
Repackaging
51
Based on TRI and DMR reporting
Processing as a Reactant
117
Based on TRI and DMR reporting
Incorporation into
Formulation, Mixture, or
Reaction Product
39
Based on TRI and DMR reporting
Batch Open-Top Vapor
Degreasing
398 to 4,942
2017 Draft ESD on the Use of Vapor Degreasers
( CD 2017a)
Batch Closed-Loop Vapor
Degreasing
13,912 to
25,546
2017 Draft ESD on the Use of Vapor Degreasers
( CD 2017a)
Conveyorized Vapor
Degreasing
395 to 568
2017 Draft ESD on the Use of Vapor Degreasers
( CD 2017a)
Web Degreasing
395 to 568
2017 Draft ESD on the Use of Vapor Degreasers
( CD 2017a)
Cold Cleaning
17
Based on NEI reporting
Aerosol Degreasing and
Aerosol Lubricants
75,938
Based on Census data and a market penetration of
29.6% based on California Air Resources Board
(CARB) survey of automotive maintenance and
repair facilities
Dry Cleaning and Spot
Cleaning
12,822
(commercial)
12 (industrial)
Commercial estimate based on Census data and a
market penetration of 60% based on information
from the Dry Cleaning and Laundry Institute and the
National Cleaners Association
Industrial estimate based on U.S. EPA (2006b)
economics report
Adhesives, Sealants, Paints,
and Coatings
60
Based on NEI reporting
Maskant for Chemical Milling
71
Based on stakeholder information from AC Products
(2017)
Industrial Processing Aid
98
Based on TRI and DMR reporting
Metalworking Fluids
-
No information identified to estimate number of
facilities
Wipe Cleaning and
Metal/Stone Polishes
-
No information identified to estimate number of
facilities
Other Spot Cleaning/Spot
Removers (Including Carpet
Cleaning)
-
No information identified to estimate number of
facilities
Other Industrial Uses
130
Based on TRI and DMR reporting
Other Commercial Uses
-
No information identified to estimate number of
facilities
Laboratory Chemicals
-
No information identified to estimate number of
facilities
Waste Handling, Disposal,
Treatment, and Recycling
94
Based on TRI and DMR reporting
Other Department of Defense
Uses
-
No information identified to estimate number of
facilities
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1937
1938
1939
1940
1941
1942
1943
2.2.1.2.3 Estimates of Release Days
EPA referenced ESDs, NEI data, SpERCs, or needed to make assumptions when estimating
release days for each OES. A summary along with a brief explanation is presented in Table 2-4
below.
Table 2-4. Summary of EPA's Estimates for Release Days for Each OES
Occupational
Release
Days
Kxposure Scenario
Notes
(OKS)
Manufacturing
350
Assumes operation seven days/week and 50 weeks/yr with
two weeks down for shutdown activities
Repackaging
250
Assumed 5 days per week and 50 weeks per year
Processing as a
Reactant
350
Assumes operation seven days/week and 50 weeks/yr with
two weeks down for shutdown activities
Incorporation into
Formulation, Mixture,
or Reaction Product
300
SpERC for the formulation and (re)packing of substances
and mixtures (European Solvents Industry 2019)
Batch Open-Top Vapor
Degreasing
260
2017 Draft ESD on the Use of Vapor Deareasers (OECD
2017a)
Batch Closed-Loop
Vapor Degreasing
260
2017 Draft ESD on the Use of Vapor Deareasers (OECD
2017a)
Conveyorized Vapor
Degreasing
260
2017 Draft ESD on the Use of Vapor Deareasers (OECD
2017a)
Web Degreasing
260
2017 Draft ESD on the Use of Vapor Deareasers (OECD
2017a)
Cold Cleaning
260
2017 Draft ESD on the Use of Vapor Deareasers (OECD
2017a)
Aerosol Degreasing and
Aerosol Lubricants
-
Wastewater discharges not expected from this OES
Dry Cleaning and Spot
Cleaning
250 to 312
Assumes facilities may operate five days/week and 50
weeks/yr at the low-end up to six days/week and 52
weeks/yr at the high-end
Adhesives, Sealants,
Paints, and Coatings
250
Assumed 5 days per week and 50 weeks per year
Maskant for Chemical
Milling
172 to 208
Based on NEI reporting
Industrial Processing
Aid
300
SpERC for the manufacture of a substance (which includes
use as a process chemical or extraction aaent) (European
Solvents Industry 2012)
Metalworking Fluids
260
2017 Draft ESD on the Use of Vapor Deareasers (OECD
2017a)
Wipe Cleaning and
Metal/Stone Polishes
-
Wastewater discharges not expected from this OES
Other Spot
Cleaning/Spot
Removers (Including
Carpet Cleaning)
-
No information identified to estimate wastewater discharges
from this OES
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Occupational
Release
Days
Kxposure Scenario
Notes
(OKS)
Other Industrial Uses
250
Assumed 5 days per week and 50 weeks per year
Other Commercial Uses
250
Assumed 5 days per week and 50 weeks per year
Laboratory Chemicals
-
No information identified to estimate wastewater discharges
from this OES
Waste Handling,
Disposal, Treatment,
and Recycling
250
Assumed 5 days per week and 50 weeks per year
Other Department of
Defense Uses
-
No information identified to estimate wastewater discharges
from this OES
1944 2.2.1.3 Assumptions, Key Sources of Uncertainty, and Overall Confidence for
1945 Environmental Releases
1946 Table 2-5 provides a summary of the assumptions, key sources of uncertainty, and EPA's overall
1947 confidence in its release estimates for each of the OES assessed.
1948
1949 Table 2-5. Summary of Assumptions, Uncertainty, and Overall Confidence in Release
1950 Estimates by OES
Occupational
Kxposurc Scenario
(OKS)
Assumptions. 1 nccrlainty. and Overall Confidence in Release
r.stimatcs
Manufacturing
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI for four sites. TRI data were determined to
have a "medium" data quality rating through EPA's systematic review
process. Specifically, the data were scored high for representativeness of
geographic scope, applicability, and temporal representativeness but scored
low for methodology, accessibility/clarity, and variability/uncertainty
resulting in an overall quality of "medium". The "low" scores are a result of
the information available in each data source. For example, neither TRI nor
DMR include: data on how each reporter estimated their releases
(methodology); metadata (e.g., release frequency, process/unit operation that
is the source of the release) other than the media of release
(accessibility/clarity); or address variability/uncertainty in the reported
estimates.
Uncertainties in the Daily Discharge Estimates: EPA assumed 350 days/yr
of operation (7 days/week, 50 weeks/yr with two weeks for turnaround) and
averaged the annual discharges over the operating days. There is some
uncertainty that all sites manufacturing PCE will operate for this duration as
some sites may operate less than 7 days/wk or may have turnarounds greater
than or less than the assumed 2 weeks/yr. Therefore, the average daily
discharges may be higher if sites operate for fewer than 350 days/yr or lower
if they operate for greater than 350 days/yr. Furthermore, PCE
concentrations in wastewater discharges at each site may vary from day-to-
day due to changes in process conditions (e.g., total wastewater flow) such
that on any given day the actual daily discharges may be higher or lower
than the estimated average daily discharge.
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Omipsilionsil
Kxposurc Scciiiirio
(Ol-S)
Assumptions. 1 nccrlsiinlv. niul Ovcnill (onl'idciKT in Uclcsiso
Kslimsilcs
Strengths in Discharges Assessed Using Effluent Guidelines: The
discharges estimated using the EG are within an order of magnitude of the
discharges reported by sites in TRI. The exception to this is the Solvents &
Chemicals site which had a much lower production volume than the
averaged assessed at all other sites.
Uncertainties in Discharges Assessed Using Effluent Guidelines:
Water discharges from the remaining four sites were estimated using the
maximum daily and monthly discharge limits in the OCPSF (Organic
Chemicals, Plastics and Synthetic Fibers) EG and the estimated volume of
wastewater produced per pound of PCE production from the SpERC
developed by the European Solvent Industry Group for the manufacture of a
substance. The estimates assume the sites operate at the limits set by the EG;
actual releases may be lower for sites operating below the limits or higher
for sites not in compliance with the OCPSF EG. Furthermore, the
production volumes used to estimate discharges for three of the four sites
are based on the average production volume. Each site may manufacture
volumes greater than or less than the average resulting in higher or lower
discharge volumes, respectively.
Uncertainties in the Number of Sites Estimate: Information to determine
the activity at two of the assessed sites as manufacture or import was not
publicly available. It is possible these two sites are importers and not
manufacturers; thus, eliminating the wastewater discharges from
manufacturing at these sites (note: the sites may have other wastewater
discharges of PCE depending on the conditions of use at the site).
Overall Confidence Rating: Based on the data quality score and the
uncertainties in the daily discharge estimates, EPA has a medium confidence
in the wastewater discharge estimates for the four sites in the 2016 TRI.
Based on the uncertainties in using effluent guidelines and the number of
sites, EPA has a medium confidence in the wastewater discharge estimates
for the four sites assessed using the OCPSF EG.
Repackaging
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI and the 2016 DMR. TRI and DMR data were
determined to have a "medium" data quality rating through EPA's
systematic review process. Specifically, the TRI and DMR data were scored
high for representativeness of geographic scope, applicability, and temporal
representativeness but scored low for methodology, accessibility/clarity, and
variability/uncertainty resulting in an overall quality of medium. The "low"
scores are a result of the information available in each data source. For
example, neither TRI nor DMR include: data on how each reporter
estimated their releases (methodology); metadata (e.g., release frequency,
process/unit operation that is the source of the release) other than the media
of release (accessibility/clarity); or address variability/uncertainty in the
reported estimates.
Uncertainties in Number of Sites Estimate: Due to reporting requirements
for TRI and DMR, the number of sites in this OES may be underestimated.
It is uncertain the extent that sites not captured in these databases discharge
wastewater containing PCE and whether any such discharges would be to
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Omipsilionsil
Kxposurc Scciiiirio
(Ol-S)
Assumptions. 1 iK'crlsiintY. niul Ovcrsill (onl'idciKT in Uclcsiso
Kslimsilcs
surface water, POTW, or non-POTW WWT. Additionally, information on
the conditions of use of PCE at facilities in TRI and DMR is limited;
therefore, there is some uncertainty as to whether all of the sites assessed in
this section are performing repackaging activities rather than a different
condition of use. If the sites were categorized under a different OES, the
annual wastewater discharges for each site would remain unchanged;
however, average daily discharges may change depending on the number of
operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to TRI
and DMR only report annual discharges; to assess daily discharges, EPA
assumed 250 days/yr of operation and averaged the annual discharges over
the operating days. There is some uncertainty that all sites repackaging PCE
will repackage PCE for this duration as some sites may not repackage PCE
every day while others may operate more than 5 days/week and 50
weeks/yr. Therefore, the average daily discharges may be higher if sites
repackage for fewer than 250 days/yr or lower if they repackage for greater
than 250 days/yr. Furthermore, PCE concentrations in wastewater
discharges at each site may vary from day-to-day such that on any given day
the actual daily discharges may be higher or lower than the estimated
average daily discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Processing as a
Reactant
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI and the 2016 DMR. TRI and DMR data were
determined to have a "medium" data quality rating through EPA's
systematic review process. Specifically, the TRI and DMR data were scored
high for representativeness of geographic scope, applicability, and temporal
representativeness but scored low for methodology, accessibility/clarity, and
variability/uncertainty resulting in an overall quality of medium. The "low"
scores are a result of the information available in each data source. For
example, neither TRI nor DMR include: data on how each reporter
estimated their releases (methodology); metadata (e.g., release frequency,
process/unit operation that is the source of the release) other than the media
of release (accessibility/clarity); or address variability/uncertainty in the
reported estimates.
Uncertainties in Number of Sites Estimate: Due to reporting requirements
for TRI and DMR, the number of sites in this OES may be underestimated.
It is uncertain the extent that sites not captured in these databases discharge
wastewater containing PCE and whether any such discharges would be to
surface water, POTW, or non-POTW WWT. Additionally, information on
the conditions of use of PCE at facilities in TRI and DMR is limited;
therefore, there is some uncertainty as to whether all of the sites assessed in
this section are processing PCE as a reactant rather than a different
condition of use. If the sites were categorized under a different OES, the
annual wastewater discharges for each site would remain unchanged;
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Omipsilionsil
Kxposurc Scciiiirio
(Ol-S)
Assumptions. 1 nccrlsiinlv. nntl Ovcrsill (onl'idciKT in Uclcsiso
KslinisiU's
however, average daily discharges may change depending on the number of
operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to TRI
and DMR only report annual discharges; to assess daily discharges, EPA
assumed 350 days/yr of operation (7 days/week, 50 weeks/yr with two
weeks for turnaround) and averaged the annual discharges over the
operating days. There is some uncertainty that all sites processing PCE as a
reactant will operate for this duration as some sites may operate less than 7
days/wk, have turnarounds greater than or less than the assumed 2 weeks/yr,
or not manufacture products that use PCE as a reactant every day.
Therefore, the average daily discharges may be higher if sites operate for
fewer than 350 days/yr or lower if they operate for greater than 350 days/yr.
Furthermore, PCE concentrations in wastewater discharges at each site may
vary from day-to-day such that on any given day the actual daily discharges
may be higher or lower than the estimated average daily discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Incorporation into
Formulation, Mixture,
or Reaction Product
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI and the 2016 DMR. TRI and DMR data were
determined to have a "medium" data quality rating through EPA's
systematic review process. Specifically, the TRI and DMR data were scored
high for representativeness of geographic scope, applicability, and temporal
representativeness but scored low for methodology, accessibility/clarity, and
variability/uncertainty resulting in an overall quality of medium. The "low"
scores are a result of the information available in each data source. For
example, neither TRI nor DMR include: data on how each reporter
estimated their releases (methodology); metadata (e.g., release frequency,
process/unit operation that is the source of the release) other than the media
of release (accessibility/clarity); or address variability/uncertainty in the
reported estimates.
Uncertainties in Number of Sites Estimate: Due to reporting requirements
for TRI and DMR, the number of sites in this OES may be underestimated.
It is uncertain the extent that sites not captured in these databases discharge
wastewater containing PCE and whether any such discharges would be to
surface water, POTW, or non-POTW WWT. Additionally, information on
the conditions of use of PCE at facilities in TRI and DMR is limited;
therefore, there is some uncertainty as to whether all of the sites assessed in
this section are performing formulation activities rather than a different
condition of use. If the sites were categorized under a different OES, the
annual wastewater discharges for each site would remain unchanged;
however, average daily discharges may change depending on the number of
operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to TRI
and DMR only report annual discharges; to assess daily discharges, EPA
assumed 300 days/yr of operation and averaged the annual discharges over
the operating days. There is some uncertainty that all sites formulating PCE-
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Omipsilionsil
Kxposurc Scciiiirio
(Ol-S)
Assumptions. 1 iK'crlsiintY. niul Ovcrsill (onl'idciKT in Uclcsiso
Kslimsilcs
based products will operate for this duration as some sites may not make
products that contain PCE every day while others may operate more than
300 days/yr based on product demand and process needs. Therefore, the
average daily discharges may be higher if sites operate for fewer than 300
days/yr or lower if they operate for greater than 300 days/yr. Furthermore,
PCE concentrations in wastewater discharges at each site may vary from
day-to-day such that on any given day the actual daily discharges may be
higher or lower than the estimated average daily discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Batch Open-Top Vapor
Degreasing
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI and the 2016 DMR. TRI and DMR data were
determined to have a "medium" data quality rating through EPA's
systematic review process. Specifically, the TRI and DMR data were scored
high for representativeness of geographic scope, applicability, and temporal
representativeness but scored low for methodology, accessibility/clarity, and
variability/uncertainty resulting in an overall quality of medium. The "low"
scores are a result of the information available in each data source. For
example, neither TRI nor DMR include: data on how each reporter
estimated their releases (methodology); metadata (e.g., release frequency,
process/unit operation that is the source of the release) other than the media
of release (accessibility/clarity); or address variability/uncertainty in the
reported estimates.
Uncertainties in Number of Sites Estimate: Due to reporting requirements
for TRI and DMR, EPA does not expect all sites using PCE in OTVD to be
captured in the databases. It is uncertain the extent that sites not captured in
these databases discharge wastewater containing PCE and whether any such
discharges would be to surface water, POTW, or non-POTW WWT;
however, the sites may be required to comply with an EG depending on the
industry in which the OTVD is being used. Additionally, information on the
conditions of use of PCE at facilities in TRI and DMR is limited; therefore,
there is some uncertainty as to whether all of the sites assessed in this
section are using PCE in OTVD rather than a different condition of use
(including other vapor degreasing and cold cleaning operations and use of
PCE in metalworking fluids). If the sites were categorized under a different
OES, the annual wastewater discharges for each site would remain
unchanged; however, average daily discharges may change depending on
the number of operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to TRI
and DMR only report annual discharges; to assess daily discharges, EPA
assumed 260 days/yr of operation and averaged the annual discharges over
the operating days. There is some uncertainty that all sites using PCE in
OTVDs will operate for this duration as some sites may use degreasing
equipment more or less frequently than 260 days/yr depending on process
demands. Therefore, the average daily discharges may be higher if sites
operate for fewer than 260 days/yr or lower if they operate for greater than
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260 days/yr. Furthermore, PCE concentrations in wastewater discharges at
each site may vary from day-to-day such that on any given day the actual
daily discharges may be higher or lower than the estimated average daily
discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Batch Closed-Loop
Vapor Degreasing
Same as the Open-Top Vapor Degreasing (OTVD) OES.
Conveyorized Vapor
Degreasing
Same as the Open-Top Vapor Degreasing (OTVD) OES.
Web Degreasing
Same as the Open-Top Vapor Degreasing (OTVD) OES.
Cold Cleaning
Same as the Open-Top Vapor Degreasing (OTVD) OES.
Aerosol Degreasing and
Aerosol Lubricants
EPA assessed no wastewater discharges for this OES. There is some
uncertainty as to whether and how much PCE may deposit on shop floors.
However, due to the volatility of PCE, EPA expects PCE to evaporate from
any such deposit prior to it being discharged; thus, limiting any potential
discharges to surface water, POTW, or non-POTW WWT from this source.
Based on this information, EPA has a high confidence in the release
assessment.
Dry Cleaning and Spot
Cleaning
Data Quality Ratings: Wastewater discharges from industrial launderers are
assessed using reported discharges from the 2016 DMR. DMR data were
determined to have a "medium" data quality rating through EPA's
systematic review process. The "low" scores are a result of the information
available in DMR. For example, DMR does not include: data on how each
reporter estimated their releases (methodology); metadata (e.g., release
frequency, process/unit operation that is the source of the release) other than
the media of release (accessibility/clarity); or address variability/uncertainty
in the reported estimates.
Limitations to Release Data for Industrial Launderer: DMR does not
contain data for 4 of the 12 industrial launderer sites. These four sites may
not be in DMR because they may have no water discharges or because they
discharge to sewer rather than surface water (sewer discharges not reported
in DMR).
Uncertainties in the Daily Discharge Estimates: Facilities reporting to
DMR only report annual discharges; to assess daily discharges, EPA
assumed annual days of operation and averaged the annual discharges over
the operating days. There is some uncertainty that all industrial launderers
using PCE will operate for this duration as site-specific demands may result
in higher or lower operating days. Therefore, the average daily discharges
may be higher if sites operate for fewer than the operating days or lower if
they operate for greater than the operating days. Furthermore, PCE
concentrations in wastewater discharges at each site may vary from day-to-
day such that on any given day the actual daily discharges may be higher or
lower than the estimated average daily discharge. Based on this information,
EPA has a medium confidence in the wastewater discharge estimates at
industrial launderers.
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Strengths of the Release Model for Small Commercial Dry Cleaners:
Wastewater discharges from small commercial dry cleaners is assessed
using the Solvent Release in Water Discharge from Dry Cleaning Machines
Model. The model is based on the EPA/OPPT Water Saturation Loss
Model, which assumes that water contacted with the chemical becomes
saturated with the chemical and remains saturated at the time of disposal.
The primary difference between this model and the EPA/OPPT Water
Saturation Model is this model calculates the amount of produced
wastewater using data (and distributions, where available) obtained from
literature for the volume of water produced water per pound of clothes
cleaned, load size, and loads per day. Using these parameters and
distributions the model is able to capture variability in the amount of
produced wastewater at dry cleaners.
Uncertainties in the Release Model for Small Commercial Dry Cleaners:
There is some uncertainty on how sites will dispose of water containing-
PCE and some states may regulate the disposal; therefore, not all sites are
expected to discharge wastewater to POTW.
Overall Confidence Rating: Based on the data quality score, the limitations
to the release data, and the uncertainties in the daily discharge estimates,
EPA has a medium confidence in the wastewater discharge estimates at
industrial launderers. Based on the strengths and uncertainties of the model,
EPA has a medium level of confidence in the wastewater discharge
estimates at small commercial dry cleaners.
Adhesives, Sealants,
Paints, and Coatings
Uncertainties in the Release Model: Wastewater discharges from adhesive,
sealant, coating, and paint applications are assessed using loss fractions
from ESDs and the EPA/OPPT Automobile OEM (Original Equipment
Manufactuer) Coating Overspray Loss Model. These approaches represent
release estimates for the solids (i.e., non-volatile) portions of the coatings or
adhesives and do not account for potential evaporation of volatiles from the
mist prior to entering wastewater. Therefore, these estimates likely
overestimate actual wastewater discharges of PCE due to volatilization
(PCE vapor pressure is 18.5 mmHg at 25°C). This evaporation is difficult to
estimate and is not considered in this assessment.
Uncertainties in Number of Sites Estimate: There is further uncertainty that
the number of sites obtained from the 2014 NEI represent the total number
of sites using adhesives or coatings containing PCE. NEI data only covers
specific industries which may not capture the entirety of industries using
these products. NEI also does not include operations that are classified as
area sources because area sources are reported at the county level and do not
include site-specific information. It is uncertain the extent that sites not
captured in this assessment discharge wastewater containing PCE and
whether any such discharges would be to surface water, POTW, or non-
POTWWWT.
Overall Confidence Rating: Based on the uncertainties in the release model
and number of sites, EPA has a medium confidence in the wastewater
discharge estimates.
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Maskant for Chemical
Milling
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI and the 2016 DMR. TRI and DMR data were
determined to have a "medium" data quality rating through EPA's
systematic review process. Specifically, the TRI and DMR data were scored
high for representativeness of geographic scope, applicability, and temporal
representativeness but scored low for methodology, accessibility/clarity, and
variability/uncertainty resulting in an overall quality of medium. The "low"
scores are a result of the information available in each data source. For
example, neither TRI nor DMR include: data on how each reporter
estimated their releases (methodology); metadata (e.g., release frequency,
process/unit operation that is the source of the release) other than the media
of release (accessibility/clarity); or address variability/uncertainty in the
reported estimates.
Uncertainties in Number of Sites Estimate: The discharges in TRI and
DMR do not include 44 of the expected 71 sites that use PCE-based
maskants. It is uncertain the extent that sites not captured in these databases
discharge wastewater containing PCE and whether any such discharges
would be to surface water, POTW, or non-POTW WWT; however, the sites
may be required to comply with the Metal Finishing EG. Additionally,
information on the conditions of use of PCE at facilities in TRI and DMR is
limited; therefore, there is some uncertainty as to whether all of the sites
assessed in this section are performing maskant operations rather than a
different condition of use. If the sites were categorized under a different
OES, the annual wastewater discharges for each site would remain
unchanged; however, average daily discharges may change depending on
the number of operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to TRI
and DMR only report annual discharges; to assess daily discharges, EPA
used site-specific reported operating time from the 2014 NEI, where
available, or assumed 172 days/yr of operation (based on the average
operating time from the 2014 NEI) and averaged the annual discharges over
the operating days. There is some uncertainty that all sites using PCE-based
maskants will operate for this duration as, based on process needs, some
sites may perform masking activities more or less frequently than the
average days/yr from NEI or use other maskants not containing PCE for
certain operations. Therefore, the average daily discharges may be higher if
sites operate for fewer than the estimated operating days or lower if they
operate for greater than the estimated operating days. Furthermore, PCE
concentrations in wastewater discharges at each site may vary from day-to-
day such that on any given day the actual daily discharges may be higher or
lower than the estimated average daily discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Industrial Processing
Aid
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI and the 2016 DMR. TRI and DMR data were
determined to have a "medium" data quality rating through EPA's
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systematic review process. Specifically, the TRI and DMR data were scored
high for representativeness of geographic scope, applicability, and temporal
representativeness but scored low for methodology, accessibility/clarity, and
variability/uncertainty resulting in an overall quality of medium. The "low"
scores are a result of the information available in each data source. For
example, neither TRI nor DMR include: data on how each reporter
estimated their releases (methodology); metadata (e.g., release frequency,
process/unit operation that is the source of the release) other than the media
of release (accessibility/clarity); or address variability/uncertainty in the
reported estimates.
Uncertainties in Number of Sites Estimate: Due to reporting requirements
for TRI and DMR, the number of sites in this OES may be underestimated.
It is uncertain the extent that sites not captured in these databases discharge
wastewater containing PCE and whether any such discharges would be to
surface water, POTW, or non-POTW WWT. Additionally, information on
the conditions of use of PCE at facilities in TRI and DMR is limited;
therefore, there is some uncertainty as to whether all of the sites assessed in
this section are using PCE as a processing aid rather than a different
condition of use. If the sites were categorized under a different OES, the
annual wastewater discharges for each site would remain unchanged;
however, average daily discharges may change depending on the number of
operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to TRI
and DMR only report annual discharges; to assess daily discharges, EPA
assumed 300 days/yr of operation and averaged the annual discharges over
the operating days. There is some uncertainty that all sites using PCE as a
processing aid will operate for this duration as some sites may use PCE
processing aids more or less frequently than 300 days/yr based on process
needs. Therefore, the average daily discharges may be higher if sites operate
for fewer than 300 days/yr or lower if they operate for greater than 300
days/yr. Furthermore, PCE concentrations in wastewater discharges at each
site may vary from day-to-day such that on any given day the actual daily
discharges may be higher or lower than the estimated average daily
discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Mctalworking Fluids
Same as the Open-Top Vapor Degreasing (OTVD) OES.
Wipe Cleaning and
Metal/Stone Polishes
EPA assessed no wastewater discharges for this OES. There is some
uncertainty as to whether and how much PCE may drip from the rag/cloth or
the substrate surface onto shop floors or ground (for outdoor applications).
However, due to the volatility of PCE, EPA expects PCE to evaporate from
any such deposit prior to it being discharged; thus, limiting any potential
discharges to surface water, POTW, or non-POTW WWT from this source.
Based on this information, EPA has a high confidence in the release
assessment.
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Other Spot
Cleaning/Spot
Removers (Including
Carpet Cleaning)
No information identified to estimate wastewater discharges from this OES.
Other Industrial Uses
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI and the 2016 DMR. TRI and DMR data were
determined to have a "medium" data quality rating through EPA's
systematic review process. Specifically, the TRI and DMR data were scored
high for representativeness of geographic scope, applicability, and temporal
representativeness but scored low for methodology, accessibility/clarity, and
variability/uncertainty resulting in an overall quality of medium. The "low"
scores are a result of the information available in each data source. For
example, neither TRI nor DMR include: data on how each reporter
estimated their releases (methodology); metadata (e.g., release frequency,
process/unit operation that is the source of the release) other than the media
of release (accessibility/clarity); or address variability/uncertainty in the
reported estimates.
Uncertainties in Number of Sites Estimate: Due to reporting requirements
for TRI and DMR the number of sites in this OES may be underestimated.
It is uncertain the extent that sites not captured in these databases discharge
wastewater containing PCE and whether any such discharges would be to
surface water, POTW, or non-POTW WWT. Additionally, information on
the conditions of use of PCE at facilities in TRI and DMR is limited;
therefore, there is some uncertainty as to whether all of the sites assessed in
this section are performing other industrial uses rather than a different
condition of use. If the sites were categorized under a different OES, the
annual wastewater discharges for each site would remain unchanged;
however, average daily discharges may change depending on the number of
operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to TRI
and DMR only report annual discharges; to assess daily discharges, EPA
assumed 250 days/yr of operation and averaged the annual discharges over
the operating days. There is some uncertainty that all sites using PCE for
other industrial uses will operate for this duration as some sites may use
PCE more or less frequently than 250 days/yr based on process needs.
Therefore, the average daily discharges may be higher if sites operate for
fewer than 250 days/yr or lower if they operate for greater than 250 days/yr.
Furthermore, PCE concentrations in wastewater discharges at each site may
vary from day-to-day such that on any given day the actual daily discharges
may be higher or lower than the estimated average daily discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Other Commercial Uses
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 DMR. DMR data were determined to have a
"medium" data quality rating through EPA's systematic review process.
Specifically, the DMR data were scored high for representativeness of
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geographic scope, applicability, and temporal representativeness but scored
low for methodology, accessibility/clarity, and variability/uncertainty
resulting in an overall quality of medium. The "low" scores are a result of
the information available in DMR. For example, DMR does not include:
data on how each reporter estimated their releases (methodology); metadata
(e.g., release frequency, process/unit operation that is the source of the
release) other than the media of release (accessibility/clarity); or address
variability/uncertainty in the reported estimates.
Uncertainties in Number of Sites Estimate: Due to reporting requirements
for DMR, these sites are not expected to capture the entirety of water
releases from this OES. It is uncertain the extent that sites not captured in
DMR discharge wastewater containing PCE and whether any such
discharges would be to surface water, POTW, or non-POTW WWT.
Additionally, information on the conditions of use of PCE at facilities in
DMR is limited; therefore, there is some uncertainty as to whether all of the
sites assessed in this section are performing other commercial uses rather
than a different condition of use. If the sites were categorized under a
different OES, the annual wastewater discharges for each site would remain
unchanged; however, average daily discharges may change depending on
the number of operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to
DMR only report annual discharges; to assess daily discharges, EPA
assumed 250 days/yr of operation and averaged the annual discharges over
the operating days. There is some uncertainty that all sites using PCE in
other commercial uses will operate for this duration as some sites may use
PCE more or less frequently than 250 days/yr based on process needs.
Therefore, the average daily discharges may be higher if sites operate for
fewer than 250 days/yr or lower if they operate for greater than 250 days/yr.
Furthermore, PCE concentrations in wastewater discharges at each site may
vary from day-to-day such that on any given day the actual daily discharges
may be higher or lower than the estimated average daily discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Laboratory Chemicals
No information identified to estimate wastewater discharges from this OES.
Waste Handling,
Disposal, Treatment,
and Recycling
Data Quality Ratings: Wastewater discharges are assessed using reported
discharges from the 2016 TRI and the 2016 DMR. TRI and DMR data were
determined to have a "medium" data quality rating through EPA's
systematic review process. Specifically, the TRI and DMR data were scored
high for representativeness of geographic scope, applicability, and temporal
representativeness but scored low for methodology, accessibility/clarity, and
variability/uncertainty resulting in an overall quality of medium. The "low"
scores are a result of the information available in each data source. For
example, neither TRI nor DMR include: data on how each reporter
estimated their releases (methodology); metadata (e.g., release frequency,
process/unit operation that is the source of the release) other than the media
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of release (accessibility/clarity); or address variability/uncertainty in the
reported estimates.
Uncertainties in Number of Sites Estimate: Due to reporting requirements
for TRI and DMR, the number of sites in this OES may be underestimated.
It is uncertain the extent that sites not captured in these databases discharge
wastewater containing PCE and whether any such discharges would be to
surface water, POTW, or non-POTW WWT. Additionally, information on
the conditions of use of PCE at facilities in TRI and DMR is limited;
therefore, there is some uncertainty as to whether all of the sites assessed in
this section are performing waste treatment, disposal, and recycling
activities rather than a different condition of use. If the sites were
categorized under a different OES, the annual wastewater discharges for
each site would remain unchanged; however, average daily discharges may
change depending on the number of operating days expected for the OES.
Uncertainties in the Daily Discharge Estimates: Facilities reporting to TRI
and DMR only report annual discharges; to assess daily discharges, EPA
assumed 250 days/yr of operation and averaged the annual discharges over
the operating days. There is some uncertainty that all sites
disposing/treating/recycling wastes containing PCE will operate for this
duration as some sites may receive/treat PCE-containing wastes more or less
frequently than 250 days/yr based on customer demands. Therefore, the
average daily discharges may be higher if sites operate for fewer than 250
days/yr or lower if they operate for greater than 250 days/yr. Furthermore,
PCE concentrations in wastewater discharges at each site may vary from
day-to-day such that on any given day the actual daily discharges may be
higher or lower than the estimated average daily discharge.
Overall Confidence Rating: Based on the data quality score, and the
uncertainties in the number of sites and daily discharge estimates, EPA has a
medium confidence in the wastewater discharge estimates.
Other Department of
Defense Uses
No information identified to estimate wastewater discharges from this OES.
2.3 Environmental Exposures Overview
The manufacturing, processing, use and disposal of PCE can result in releases to the
environment. In this section, EPA presents what approach and methodology was used to evaluate
PCE exposures to aquatic organisms via surface water. The environmental exposure
characterization focuses on aquatic releases of PCE from facilities that use, manufacture, or
process PCE under industrial and/or commercial conditions of use subject to TSCA regulations.
To characterize environmental exposure, EPA identified and reviewed national scale monitoring
data. Measured surface water concentrations were obtained from EPA's Water Quality Exchange
(WQX) using the online Water Quality Portal (WQP) tool, which is the nation's largest source of
water quality monitoring data and includes results from EPA's STORage and RETrieval
(STORET) Data Warehouse, the United States Geological Survey (USGS), National Water
Information System (NWIS), and other federal, state, and tribal sources. A full systematic review
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of reasonably available surface water literature was also conducted to identify other peer-
reviewed or grey literature7 sources of measured surface water concentrations in the US. Point
estimate exposures were derived from both measured and predicted concentrations of PCE in
surface water in the United States. Predicted surface water concentrations were modeled for
facility releases in the EPA Lifecycle Release Analysis conducted for reporting year 2016, as
determined from EPA's Toxics Release Inventory (TRI), Discharge Monitoring Reports (DMR;
through EPA's Water Pollutant Loading Tool), and EPA's Chemical Data Reporting (CDR).
The aquatic modeling was conducted with EPA's Exposure and Fate Assessment Screening
Tool, version 2014 (E-FAST 2014) ( ), using reported annual release/loading
amounts (kg/yr) and estimates of the number of days per year that the annual load is released. As
appropriate, two scenarios were modeled per release: release of the annual load over an
estimated maximum number of operating days per year and over only 20 days per year. Twenty
days of release was modeled as the low-end release frequency at which possible ecologic chronic
risk could be determined. Additionally, the Probabilistic Dilution Model (PDM), a module of E-
FAST 2014 was run to estimate the number of days a stream concentration will exceed the
designated concentration of concern (COC) value.
The measured concentrations reflect localized ambient exposures at the monitoring sites, and the
modeled concentrations reflect near-site estimates at the point of release. A geospatial analysis at
the watershed level (HUC-8 and HUC-12; Hydrologic Unit Codes) was conducted to compare
the measured and predicted surface water concentrations and investigate if the facility releases
may be associated with the observed concentrations in surface water. Hydrologic Unit Codes
(HUCs) are a geographically hierarchical tiered approach to organizing stream networks across
the United States from regions to sub water sheds and part of the Watershed Boundary Dataset
developed by U.S. Geological Survey and U.S. Department of Agriculture ("LISGS 2013). HUC-8
and HUC-12 sized units were selected as they were expected to give a representative geographic
size range over which predicted surface water concentrations would be relevant to measured
concentrations.
2,3,1 Aquatic Exposure Modeling Approach
Surface water concentrations resulting from wastewater releases of PCE from facilities that use,
manufacture, or process PCE related to TSCA conditions of use were modeled using EPA's
Exposure and Fate Assessment Screening Tool, Version 2014 ( ). E-FAST 2014
is a model that estimates chemical concentrations in water to which aquatic life may be exposed
using upper percentile and/or mean exposure parametric values, resulting in high-end exposure
estimates. Other assumptions and uncertainties in the model, including ways it may be
underestimating or overestimating exposure, are discussed in the Sections 4.3.1. Advantages to
this model are that it requires minimal input parameters and it has undergone extensive peer
review by experts outside of EPA. A brief description of the calculations performed within the
7 Grey literature refers to sources of scientific information that are not formally published and distributed in peer
reviewed journal articles. These references are still valuable and consulted in the TSCA risk evaluation process.
Examples of grey literature are theses and dissertations, technical reports, guideline studies, conference proceedings,
publicly-available industry reports, unpublished industry data, trade association resources, and government reports.
(U.S. EPA 2018c)
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tool, as well as a description of required inputs and the methodology to obtaining and using
inputs specific to this assessment is described below. To obtain more detailed information on the
E-FAST 2014 tool from the user guide/background document (U.S. EPA. 2014b). as well as to
download the tool, visit this web address: https://www.epa.gov/tsca-screening-tools/e-fast-
exposure-and-fate-assessment-screening-tool-version-2014/. All model runs for this assessment
were conducted between December 2018 and June 2019.
2.3.1.1 Exposure and Fate Assessment Screening (E-FAST) Tool 2014 Inputs
Individual model inputs and accompanying considerations for the surface water modeling for E-
Fast 2014 ( b) are discussed in the following sections.
2.3.1.1.1 Chemical release to wastewater (WWR)
Annual wastewater loading estimates (kg/site/year or lb/site/year) were obtained from TRI, the Water
Pollutant Loading Tool, or CDR in the year 2016, as discussed in the lifecycle assessment in Section
2.2.1.1. To model these releases within E-FAST 2014 (U.S. EPA. 2014b). the annual release is
converted to a daily release using an estimated days of release per year. Below is an example
calculation:
WWR (kg/day) = Annual loading (kg/site/year) * Days released per year (days/year) (Eq. 2-3)
In cases where the total annual release amount from one facility was discharged via multiple
mechanisms (i.e., direct to surface water and/or indirectly through one or more WWTPs), the annual
release amount was divided accordingly based on reported information in TRI (Form R).
2.3.1.1.2 Release Days (days/year)
The number of days per year that the chemical is discharged is used to calculate a daily release amount
from annual loading estimates (see above). Current regulations do not require facilities to report the
number of days associated with reported releases. Therefore, two release scenarios were modeled for
direct discharging facilities to provide upper and lower bounds for the range of surface water
concentrations predicted by E-FAST 2014 ( 1014b). The two scenarios modeled are a
maximum release frequency (200 to 365 days) based on estimates specific to the facility's condition of
use and a low-end release frequency of 20 days of release per year. The 20-day chronic risk criterion is
derived from partial life cycle tests (e.g., daphnid chronic and fish early life stage tests) that typically
range from 21 to 28 days in duration. For indirect dischargers, only the maximum estimated days of
release per year was modeled because it was assumed that the actual release to surface water would
occur at receiving WWTPs which typically operate every day of the year.
2.3.1.1.3 Removal from wastewater treatment (\Y\YT%)
The WWT% is the percentage of the chemical removed from wastewater during treatment before
discharge to a body of water. As discussed in Section 2.1.2, Summary of Fate and Transport, the
WWT% for PCE was estimated as 80% using the "STP" module within The EPI Suite™, which
was run using default settings to evaluate the potential for PCE to volatilize to air or adsorb to
sludge during wastewater treatment. However, E-FAST does not consider volatilization of PCE
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therefore the removal percentage of 80% was slightly lower than what EPI suites estimated at
88%. EPA took a more conservative approach in the estimated removal of PCE using the E-
FAST model. The WWT% of 80% was applied to releases from indirect discharging facilities
because the releases are transferred off-site for treatment at a WWTP prior to discharge to
surface water. Direct discharging facilities that release PCE to surface water is not treated prior
to discharge, therefore EPA does not account for removal of PCE. If not enough release
information was available to determine if the release was direct or indirect, then E-FAST 2014
(I ) was run with and without the WWT%. These releases are typically those
identified through the OCSPF EGL data source and are from facilities that are not in DMR or
TRI.
2.3.1.1.4 Facility or Industry Sector
The required site-specific stream flow or dilution factor information is contained in the E-FAST
2014 database ( 3), which is accessed by querying a facility National Pollutant
Discharge Elimination System (NPDES) number, name, or reach code. For facilities that directly
discharge to surface water (i.e., "direct dischargers"), the NPDES of the direct discharger was selected
from the database. For facilities that indirectly discharge to surface water (i.e., "indirect dischargers"
because the release is sent to a waste-water treatment plant (WWTP) prior to discharge to surface water),
the NPDES of the receiving WWTP was selected. The receiving facility name and location was
obtained from the TRI database (Form R), if available. As TRI does not contain the NPDES of receiving
facilities, the NPDES was obtained using EPA's Envirofacts search tool
(https://www3.epa.gov/enviro/facts/multisvstem.html ( )). If a facility NPDES was not
available in the E-FAST-2014 database ( ), the release was modeled using water body
data for a surrogate NPDES (preferred) or an industry sector, as described below.
2.3.3.1.4.1 Surrogate NPDES
In cases where the site-specific NPDES was not available in the E-FAST 2014 database (U.S.
EPA 2014b). the preferred alternative was to select the NPDES for a nearby facility that
discharges to the same waterbody. Nearby facilities were identified using the Chemical Safety
Mapper within IGEMS and/or search of the E-FAST 2014 database ( b) by reach
code.
2.3.3.1.4.2 Industry Sector (SIC Code Option)
If the NPDES is unknown, no close analog could be identified, or the exact location of a
chemical loading is unknown, surface water concentrations were modeled using the "SIC Code
Option" within E-FAST 2014 ( ). This option uses the 10th and 50th percentile
receiving 7Q10 stream flows for dischargers in a given industry sector, as defined by the
Standard Industrial Classification (SIC) codes of the industry. The industrial sectors for each
condition of use category can be found in 5.3.68Appendix D.
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2.3.1.2 E-FAST 2014 Equations
2.3.1.2.1 Surface Water Concentrations
EPA used E-FAST 2014 ( ) estimate site-specific surface water concentrations
for discharges to both free-flowing water bodies (i.e., rivers and streams) and for still water
bodies (i.e., bays, lakes, and estuaries).
For free-flowing water body assessments, E-FAST 2014 ( ») calculates surface
water concentrations for four streamflow conditions (7Q10, harmonic mean, 30Q5, and 1Q10
flows) using the following equation:
where:
swc
WWR
WWT
SF
CF1
CF2
SWC =
( WWT \
WWRxCFlx
V 100 )
SF XCF2
(Eq. 2-1)
Day)
Surface water concentration (parts per billion (ppb) or |ig/L)
Chemical release to wastewater (kg/day)
Removal from wastewater treatment (%)
Estimated flow of the receiving stream (MLD, Million Liters per
Conversion factor (10 |ig/kg)
6
Conversion factor (10 L/day/MLD)
For still water body assessments, no simple streamflow value represents dilution in these types of
water bodies. As such, E-FAST 2014 (U.S. EPA. 2014b) accounts for dilution by incorporating an
acute or chronic dilution factor for the water body of interest instead of stream flows. Dilution
factors in E-FAST 2014 ( 2) are typically 1 (representing no dilution) to 200,
based on NPDES permits or regulatory policy. The following equation is used to calculate
surface water concentrations in still water bodies:
where:
SWC
WWR
WWT
PF
DF
CF1
CF2
SWC =
( WWT\
WWRx(l--^-)xCFl
V 100 )
PFXCF2XDF
(Eq. 2-2)
Surface water concentration (ppb or |ig/L)
Chemical release to wastewater (kg/day)
Removal from wastewater treatment (%)
Effluent flow of the discharging facility (MLD)
Acute or chronic dilution factor used for the water body (typically
between 1 and 200)
9
Conversion factor (10 |ig/kg)
6
Conversion factor (10 L/day/MLD)
2.3.1.2.2 Days of COC Exceedance
The Probabilistic Dilution Model (PDM) portion of E-FAST 2014 ( ) was also
run for free-flowing water bodies, which predicts the number of days per year a chemical's
concentration of concern (COC) in an ambient water body will be exceeded. The model is based
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on a simple mass balance approach presented by (Pi To 0 that uses probability
distributions as inputs to reflect that streams follow a highly variable seasonal flow pattern and
there are numerous variables in a manufacturing process can affect the chemical concentration
and flow rate of the effluent. PDM does not estimate exceedances for chemicals discharged to
still waters, such as lakes, bays, or estuaries. For these water bodies, the days of exceedance is
assumed be zero unless the predicted surface water concentration exceeds the COC. In these
cases, the days of exceedance is set to the number of release days per year (see required inputs
below).
2.3.1.3 E-FAST 2014 Outputs
There are two main results generated from E-FAST ( ) that EPA used in
characterizing environmental exposures: surface water concentration estimates, and the number of
days a certain surface water concentration was exceeded. Site-specific surface water concentration
estimates for free-flowing water bodies are reported for both the 7Q10 and harmonic mean stream
flows. The 7Q10 stream flow is the lowest consecutive 7-day average flow during any 10-year
period. The harmonic mean stream flow, a less conservative value, is the inverse mean of
reciprocal daily arithmetic mean flow values. Site-specific surface water concentration estimates
for still water bodies are reported for calculations using the acute dilution factors. In cases where
site-specific flow/dilution data were not available, the releases were modeled using stream flows
of a representative industry sector, as calculated from all facilities assigned to the industry sector
in the E-FAST database (U.S. EPA. 2014b) (discussed below). Estimates from this calculation
method are reported for the 10th percentile harmonic mean and 10th percentile 7Q10 stream flows.
2.3.2 Surface Water Monitoring Data Gathering Approach
To characterize environmental exposure in ambient water for PCE, EPA used two approaches to
obtain measured surface water concentrations. One approach was to conduct a search of
published literature for surface water concentrations in peer reviewed journals and the second
was to pull monitoring data on surface water concentrations from the WQP.
2.3.2.1 Method for Systematic Review of Surface Water Monitoring Data
EPA conducted a review of published literature to identify studies reporting concentrations of
PCE in surface water associated with background levels of contamination or potential releases
from facilities that manufacture, process, use and/or dispose of PCE in the United States. Studies
clearly associated with releases from Superfund sites, improper disposal methods, and landfills
were considered off-PECO and excluded from data evaluation and extraction. The systematic
review process is described in detail in Section 1.5. A total of 26 surface water studies were
extracted and the results are summarized in Section 2.3.4.2.3. A total of 3 U.S. surface water
studies were extracted and the results are summarized in Section 2.3.4.2.3
2.3.2.2 Method for Obtaining Surface Water Monitoring Data from
WQX/WQP
The primary source for the occurrence of PCE in surface water is monitoring data retrieved from
the Water Quality Portal (WQP), which integrates publicly available U.S. water quality data
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from multiple databases: 1) USGS NWIS, 2) STORET, and 3) the USDA ARS Sustaining The
Earth's Watersheds - Agricultural Research Database System (STEWARDS). For PCE the data
retrieved originated from the NWIS and STORET databases. NWIS is the Nation's principal
repository of water resources data USGS collects from over 1.5 million sites, including sites
from the National Water-Quality Assessment (NAWQA). STORET refers to an electronic data
system originally created by EPA in the 1960s to compile water quality monitoring data. NWIS
and STORET now use common web services, allowing data to be published through WQP tool.
The WQP tool and User Guide is accessed from the following website:
(http://www.waterqualitydata.us/portal j sp. (Nwqmc 2017))
2,3,2,2,1 Data Retrieval from WQP
Surface water data for PCE were downloaded from the WQP (Nwqmc 2017) on October 3, 2018.
The WQP can be searched through three different search options: Location Parameters, Site
Parameters, and Sampling Parameters. The PCE data were queried through the Sampling
Parameters search using the Characteristics parameter (selected "Tetrachloroethene (NWIS,
STORET)") and Date Range parameter (selected "01-01-2008 to 12-31-2017"). Both the "Site
data only" and "Sample results (physical/chemical metadata)" were selected for download in
"MS Excel 2007+" format. The "Site data only" file contains monitoring site information (i.e.,
location in hydrologic cycle, HUC and geographic coordinates); whereas the "Sample result" file
contains the sample collection data and analytical results for individual samples. An example of
WQP search option is shown below in Figure 2-3.
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Select data to download:
O Organization Data
® Site data only
O Project data
3 Project Monitoring Location Weighting data
O Sample results (physical/chemical metadata)
Sample results (biological metadata)
O Sample results (narrow)
O Sampling Activity
O Sampling Activity Metrics
Result Detection Quantitation Limit Data
O Biological Habitat Metrics
Copy to clipboard
File format:
J Comma-separated
O Tab-separated
® MS Excel 2007+
-' KML (Keyhole Markup Language - for Sites only)
SAMPLING PARAMETERS
Sample Media: All
Characteristic Group: All
Characteristics: \\» Tetrachloroethene *
Project ID: All
Parameter Code: inwisonly}
Minimum results per site: f|-j
Date range - from: 01-01-2008 to: 12-31-2017
Biological sampling parameters: ?
Assemblage: All
Taxonomic Name: All
Figure 2-3. WQP Search Option. Surface water data were obtained from the WQP by querying
the Sampling Parameters search option for the characteristic (STORET data), Parameter Code
(NWIS data), and date range parameter.
2,3.2.2.2 Data Filtering and Cleansing
The "Site data only" and "Sample results (physical/chemical metadata)" files were linked
together using the common field "Monitoring Location Identifier" and then filtered and cleansed
to obtain surface water samples for years 2013 through 2017. Specifically, cleansing focused on
obtaining samples were only for the media of interest (i.e., surface water), were not quality
control samples (i.e., field blanks), were of high analytical quality (i.e., no quality control issues,
sample contamination, or estimated values), and were not associated with contaminated sites
(i.e., Superfund).
The_following filtering to obtain the final dataset, the domains were examined to identify
samples with non-detect concentrations. All non-detect samples were tagged and the
concentrations were converted to V2 the reported detection limit for summary calculation
purposes. If a detection limit was not provided, calculations were performed using the average of
the reported detection limits in all samples (calculated as 0.3 |ig/L).
2.3.3 Geospatial Analysis Approach
Using 2016 data, the measured surface water concentrations from the WQP and predicted
concentrations from the modeled facility releases were mapped in ArcGIS to conduct a
watershed analysis at the HUC 8 and HUC 12 level. The purpose of the analysis was to identify
if any the observed surface water concentrations could be attributable to the modeled facility
releases. In addition, the analysis included a search for Superfund sites within 1 to 5 miles of the
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surface water monitoring stations to possible exclude these monitoring sites from the analysis. A
U.S. scale map was developed to provide a spatial representation of the measured and predicted
concentrations. HUCs with co-located monitoring stations and facility releases were identified
and examined further. Maps were developed on a U.S. scale to provide a spatial display of the
concentrations, as well as at the HUC scale to focus on co-located monitoring stations and
facility releases.
2.3.3.1 Geographic Coordinates
The location of the monitoring stations was determined from the geographic coordinates (latitude
and longitude) provided in WQP. Releases from facilities were located based on the geographic
coordinates for the NPDES, TRI, and/or FRS of the mapped facility, as provided by FRS. For
indirect dischargers, the location of the receiving facility was mapped if known. If not known,
the location of the indirect discharger was mapped. Superfund sites in 2016 were identified and
mapped using geographic coordinates of the "front door", as reported in the Superfund
Enterprise Management System (SEMS) database in Envirofacts,(I v << \ 201 M).
2.3.4 Environmental Exposure Results
In the section below, EPA summarizes what was identified in the evaluation of PCE in surface
water. To determine what potential PCE occurrence there is in surface water, EPA evaluated
both measured and modeled data using various approaches and methods. In the evaluation of
PCE there are certain limitations that need to be accounted for when interpreting PCE exposure
in the environment.
2.3.4.1 Aquatic Environmental Exposures
2.3,4.1.1 Predicted Surface Water Concentrations: E-FAST 2014 Modeling
A summary of the surface water concentration estimates modeled using E-FAST 2014 (U.S.
EPA 2014b). based on the lifecycle release analysis for the year 2016, is summarized by OES
category in Table 2-6 through Table 2-8. For the maximum release scenario (200-365 days of
release/year), surface water concentrations under 7Q10 flow conditions ranged from 9.6E-09 to
135 ppb (Table 2-6). For the 20 days of release/year scenario for direct dischargers, surface
water concentrations under 7Q10 flow conditions ranged from 4.0E-06 to 397 ppb (Table 2-7).
For comparison purposes, indirect releases to non-POTW WWTPs were also modeled for the 20
days of release/year scenario, resulting in surface water concentrations of 1.0E-02 to 2034 ppb
(Table 2-8). On a per facility basis, the 20 day release scenario yielded higher surface water
concentrations than the maximum days of release scenario.
Reported loadings were used to model surface water concentrations with E-FAST 2014 Qj.S.
EPA. 2014b). E-FAST was run using no further removal for wastewater treatment, this is
appropriate for direct release DMR data because DMRs are "submitted from facilities that have
NPDES permitted outfalls (which in most cases are discharges to surface waters)"
(https://echo.epa.gov/trends/loading-tool/resources/faq). and the top indirect dischargers were
themselves wastewater treatment facilities, reporting post-treatment release to surface water. TRI
reporting facilities must identify the name of water body (or receiving POTW) into which the
TRI chemical is being discharged.(https://www.epa.gov/toxics-release-inventorv-tri-
program/descriptions-tri-data-terms-text-version. ( )20m)) data may be transferred
through pipes or sewers to POTWs (18/24 top releasers identified as release to surface water,
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others were assumed to be surface water releases, using SIC code) National Pollutant Discharge
Elimination System (NPDES) permit codes were used to identify reach and flow characteristics
for discharges. If a NPDES code was not identified, the most applicable SIC (Standard Industrial
Classification) code was used. Surface water estimates were generated assuming an acute
scenario of a single day release, and chronic scenarios of 20 and 250 days of release. Wastewater
treatment plants and water pollution control plants were only assessed for chronic scenarios (20
and 250 days of release).
Table 2-6 Summary of Surface Water Concentrations by OES for Maximum Days of
Release Scenario
oi:s
No. of
Releases
Modeled
Surl'act
Concei
(7Q
(."Ł
Min
\Ysilcr
ilrsilion
>10)
;/l.)
Max
Processing as a Reactant
18
2.9E-05
5.0
OTVD
17
3.4E-06
5.9
Industrial Processing Aid
14
2.4E-05
11
Waste Handling, Disposal, Treatment, and Recycling
13
9.6E-09
34
Manufacturing
10
8.0E-06
18
Other Industrial Uses
8
1.7E-03
31
Other Commercial Uses
7
1.2E-03
3.9E-01
Chemical Maskant
5
5.3E-04
2.8E-01
Import/Repackaging
4
4.0E-07
28
Incorporation into Formulation
4
2.6E-04
135
Dry Cleaning (industrial only)
2
2.2E-02
1.1E-01
Commercial Dry Cleaning Sites
1
3.6E-02
3.6E-02
Overall
103
9.6E-09
135
1. Maximum and central annual release amounts were available for four facilities/sites
(Axiall Corporation, Greenchem, Solvents & Chemicals, and Commercial Dry Cleaning
Sites). This summary table only compiles the high-end release amount.
Table 2-7 Summary of Surface Water Concentrations by OES for 20 Days of Release
Scenario for Direct Releaser Facilities
Surface \\ siler
No. of
(onceiilrsilion
oi:s
Releases
(7QI0)
Modeled
(ii«/L)
Min
Max
Processing as a Reactant
17
7.2E-U4
1 uu
OTVD
16
1.3E-03
77
Industrial Processing Aid
12
6.6E-01
170
Other Industrial Uses
8
2.1E-02
397
Other Commercial Uses
7
2.1E-02
4.6
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OES
No. of
Releases
Modeled
Surface Water
Concentration
(7Q10)
fag/L)
Min
Max
Manufacturing
5
1.2E-04
99
Waste Handling, Disposal, Treatment, and Recycling
5
6.4E-01
6.0
Chemical Maskant
3
4.6E-03
1.3
Import/Repackaging
3
4.0E-06
2.1E-02
Dry Cleaning (industrial only)
2
3.9E-01
1.7
Overall
78
4.0E-06 397
Table 2-8 Summary of Surface Water Concentrations by OES for 20 Days of Release
Scenario for Indirect Releaser Facilities
OES
No. of
Releases
Modeled
Surf*
Cone
('
(
ice Water
entration
7Q10)
Lig/L)
Min
Max
Import/Repackaging
1
359
359
Incorporation into Formulation
2
1.0E-02
2034
Manufacturing
1
5.6E-02
5.6E-02
Waste Handling, Disposal, Treatment, and Recycling
4
1.7
436
Overall
8
1.0E-02 2034
2.3A1.2 Characterization of Modeled Releases
As discussed in Section 2.2.1.1, releases of PCE were determined from three data sources (TRI,
DMRs, and CDR) for the 2016 calendar year, and assigned to 16 TSCA condition of use COU
categories. Overall, modeling was conducted on 94 unique active releasing facilities plus one
industry with sites nationwide (12,822 commercial dry cleaning sites). As some facilities may be
in more than one OES category, and multiple facilities had both direct and indirect releases, a
total of 103 facilities releases were modeled for both the maximum days of release and 20 days
of release scenarios, as appropriate. The 94 active releasers were located in 28 states; states with
the highest number of facilities (5 to 14 each) were TX, LA, IL, CO, CA, NY, and OH. The
remaining 21 states had 1 to 4 facilities each. Figure 2-4 gives a graphical representation of the
number of active releasers were for each state.
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LA
IL
CO
CA, NY, OH
NJ, WV
AL, IN, Ml, PA, SC
AR, KS, KY, WA
CT, FL, ID, MA, MD, MN, OK, UT, VT, Wl ^
0 2 4 6 8 10 12 14 16
Number of Active Releaser Facilities Per State
Figure 2-4. Distribution of Active Facility Releases Modeled
The location of the actual releases, when accounting for indirect dischargers, occurred in 27
states (all states as the active releaser, except CT). With respect to watersheds, the releases
occurred across 66 HUC-8 areas and 82 HUC-12 areas. Over three quarters of the HUCs with
facilities contained only 1 release location (76% for HUC-8 and 93% for HUC-12). The
remaining HUCS contained 2 to 5 release locations each.
Direct and indirect dischargers accounted for 76% and 24% of the total releases modeled,
respectively. Site-specific waterbody flow/dilution data (identified via NPDES) were available in
E-FAST 2014 (U.S. EPA 2014b) for the majority of the releases (51%); surrogate site-specific
waterbody flow/dilution data were identified for 6% of the cases; and the remaining cases (43%)
were run using a representative industry sector SIC code. For releases modeled with a NPDES
(including a surrogate NPDES), surface water concentrations were calculated for free-flowing
water bodies in 81% of the cases, and still water bodies for the remaining cases (19%). Figure
2-5 gives a graphical representation of the modeled releases described above.
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76%
24%
Direct Releaser
Indirect Releaser
3
Site-Specific NPDES
51%
Industry Sector
Surrogate NPDES
7
Free-Flowing
81%
Still Water
19%
Figure 2-5. Modeled Release Characteristics (Percent Occurrence)
The predicted surface water concentrations for 65 modeled releases exceeded the lowest COC,
and the PDM days of exceedance for 41 modeled releases was 20 days or more. In general,
facilities with exceedances were facilities that had higher annual release amounts. Many releases,
but not all, were modeled using surrogate stream flows based on the industry sector.
Concentrations calculated using surrogate stream flows could be refined with the use of site-
specific data.
For indirect releasers, Lord Corp in Saegertown, PA (OES: Incorporation into Formulation), had
the highest surface water concentrations (both maximum days of release and 20 days of release
scenarios). The annual release at this facility was the highest of all active releasers, and generally
was an order of magnitude higher than all other releases. Stream flows for the receiving facility
(EQ DETROIT INC, as determined from TRI) was not available in E-FAST (U.S. EPA 2014b)
and therefore the indirect release was modeled using a surrogate industry sector (SIC Code
Option).
For direct releasers, GM Components Holdings LLC in Lockport, NY (OES: OTVD), had the
highest surface water concentrations (both maximum days of release and 20 days of release
scenarios). This facility had an annual release amount significantly lower than Lord Corp in
Saegertown, PA described above, but was modeled using site-specific stream flow data for a
free-flowing waterbody. A detailed summary table by facility is provided in the supplemental file
"Risk Evaluation for PCE Data Extraction for Consumer and Aquatic Exposure Monitoring
Studies".
2.3.4.2 Monitored Surface Water Concentrations
2.3.4.2.1 Measured Surface Water Concentrations from WQX/WQP
A summary of the WQX data obtained from the WQP is provided in Table 2-9 below for years
2013-2017. Per year, the cleansed datasets evaluated contained between 171 and 512 surface
water samples collected from 89 to 193 unique monitoring stations. Detection frequencies were
low, ranging from 5.5E-01 to 7.6%. Concentrations ranged from not detected (ND; <2.6E-02 to
5) to 9.2E-02 |ig/L in 2013, ND (<2.2E-02 to 5) to 1.6 |ig/L in 2014, ND (<3.4E-02 to 1.8) to
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3.2E-02 |ig/L in 2015, ND (<2.8E-02 to 5) to 5.2E-02 |ig/L in 2016, and ND (<3.6E-02 to 5) to
6.2E-01 |ig/L in 2017. The temporal trend based on the average and maximum concentrations of
all samples is graphically presented in Figure 2-6. A peak was observed in 2014, however
caution should be used in interpreting trends with this data due to the small number of samples
and the lack of samples collected from the same sites over multiple years.
Table 2-9. Measured Concentrations of PCE in Surface Water Obtained from the Water Quality
Portal: 2013-20178
Year
Detection
Frequency
Concentration in All Sam
)les (jig/L)
Concentrations (jig/L) in Only
Samples Above the Detection Limit
No. of
Samples
(No. of
Unique
Stations)
Range9
Average
±
Standard
Deviation
(SD)
No. of
Samples
(No. of
Unique
Stations)
Range
Average ±
SD10
2013
0.5%
366 (172)
ND (2.6E-02
to 5) to 9.2E-
02
2.3E-01 ±
5.8E-01
2(2)
7.2E-02 to
9.2E-02
8.2E-02 ±
1.4E-02
2014
7.6%
512 (193)
ND (2.2E-02
to 5) to 1.6
1.9E-01 ±
5.0E-01
39 (19)
1.1E-02 to
1.6
2.0E-01 ±
3.5E-01
2015
1.7%
347 (166)
ND (3.4E-02
to 1.8)to
3.2E-02
2.0E-01 ±
1.7E-01
6(2)
1.7E-02 to
3.2E-02
2.5E-02 ±
6.0E-03
2016
3.5%
201 (91)
ND (2.8E-02
to 5) to 5.2E-
02
2.9E-01 ±
7.6E-01
7(4)
1.4E-02 to
5.2E-01
2.9E-02 ±
1.3E-02
2017
5.9%
171 (89)
ND (3.6E-02
to 5) to 6.2E-
01
3.4E-01 ±
7.5E-01
10(5)
1.8E-02 to
6.2E-01
2.4E-01 ±
2.6E-01
All 5
Years
4.0%
1597 (454)
ND (2.2E-02
to 5) to 1.6
2.3E-01 ±
5.5E-01
64 (27)
1.1E-01 to
1.6
1.7E-01 ±
2.9E-01
2365
o
Data were downloaded from the Water Quality Portal ((Nwqmc 2017). www.waterqualitvdata.us) on 10/3/2018 by
selecting "Tetrachloroethene (NWIS, STORET)" for the Characteristic. Results were reviewed and filtered to obtain
a cleansed dataset (i.e., samples/sites were eliminated if identified as estimated, quality control, media type other
than surface water, Superfund, landfill, failed laboratory quality control, etc.).
9 ND = Not Detected. Reported detection limits varied between samples, as shown in parenthesis.
10 Calculations were performed using '/> the reported detection limit when results were reported as not detected. If a
detection limit was not provided, calculations were performed using 'A the average of the reported detection limits in
all samples (average = 0.3 |ig/L).
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600
500
400
!= 300
200
100
0
I | jj ¦
J 1.8
-- 1.6
-- 1.4 3
~5a
-- 1.2 3.
c
-- 1 o
-- 0.8 |
-- 0.6 S
-- 0.4 °
- 0.2
-- 0
2015
2016
2017
i Number of Samples
•Maximum Concentration (ug/L)
2013 2014
m Number of Sites
Number of Detections
Average Concentration (ug/L)
Figure 2-6. Temporal WQX Sampling and Surface Water Concentration Trends: 2013
2017
The quantitative ecological assessment used the 2016 data set only. For the 2016 data, only 7
samples from 4 monitoring sites (all in Tennessee) had PCE concentrations above the detection
limit. The concentrations ranged from 1.4E-02 to 5.2E-02 |ig/L, which are below the lowest
COC of 1.4 |ig/L.
Only one sample in the 2013-2017 dataset (Sample ID nwisnc.01.01400387) had a concentration
that exceeded the lowest COC of 1.4 |ig/L. This sample was collected in 2014 from Marsh Creek
near New Hope, NC (Site ID USGS-0208732885) and had a concentration of 1.6 |ig/L. The
sample site was not co4ocated with any 2016 active releaser facility.
2,3.4,2.2 Characterization of WQP Data
The original dataset downloaded contained 7,661 samples for years 2013 through 2017.
Following the filtering and cleansing procedure, only 21% of the samples remained (n = 1,604).
The majority of the samples (94%) were excluded because they were an off-topic media (i.e.,
groundwater, artificial, bulk deposition, leachate, municipal waste, or stormwater) or location
type (i.e., landfill, subsurface, spring, or well). A smaller number of samples were excluded
because they were quality control samples (-2%), estimated values (-1%), or had other quality
control issues (<1%). Samples associated with one Superfund site (Palermo Wellfield Superfund
Site) were also excluded.
For the 2016 cleansed dataset (n = 201 samples), observations were made in 19 states/territories
(AZ, IN, KS, LA, MD, MI, MN, MO, NJ, NM, NY, OH, OR, PA, PR, TN, TX, UT, and WI) at
91 unique monitoring sites, with 1 to 6 samples collected per sampling site. On a watershed
level, observations were made in 47 HUC-8 areas and 68 HUC-12 areas. The majority of HUCs
had only one monitoring site (68% for HUC-8; 78% for HUC-12). Up to 9 sites were present in a
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HUC-8 and up to 4 sites in a HUC-12. A list of individual HUCs, including the number of
monitoring sites and samples in each HUC, is provided in 5.3.68Appendix D, TableApx D-2 for
HUC-8 and Table Apx D-3 for HUC-12
An analysis of the 2016 cleansed dataset was also conducted to determine if any monitoring
station may be associated with Superfund sites that could be contributing to PCE releases, and
thus would not fall under the scope of this TSCA evaluation. For samples with concentrations
above the detection limit, there are four monitoring stations within 5 miles of a Superfund
site. However, there is no hydrologic connectivity as all four are located in a HUC that is
adjacent to the superfund site and not in the same HUC itself. For monitoring stations that were
also co-located in the same HUC as a facility, a search was also conducted for Superfund sites
within 1 mile. There are two co-located monitoring stations within one mile of a superfund site:
USGS-04092750 and USGS-04095090. While USGS-04092750 is found in the same HUC as a
facility it is on a separate portion of the stream network from the facility. The other station
USGS-04095090, is however immediately downstream of a superfund site and is closer to it (at
0.24 miles) than it is to the upstream facility (at 2.3 miles). Concentrations at this site were not-
detect (sampled in 2015-2017). No monitoring data from WQP was excluded based on proximity
to a Superfund site through this Superfund analysis.
2.3.4.2.3 Measured Concentrations of PCE from Published Literature
EPA's review of published literature yielded only a minimal amount of surface water monitoring
data for PCE in the U.S.; a summary of the individual studies is provided in Table 2-2-10.. Only
three studies were identified (USGS 2006). (USGS 20031 and (Singh et al. 1983)1 which
encompassed 416 surface water samples collected from rivers and oceans between 1979 and
2001. The reported concentrations of PCE ranged from below the detection limit (1.0E-04 to 0.2)
to 5.5 |ig/L, with reported central tendency values ranging from <0.2 to 0.7 |ig/L. The overall
detection frequency is a maximum of approximately 12%. The maximum concentration was
collected during a large nationwide survey of surface water for drinking water sources (rivers
and reservoirs) between 1999 and 2000 (USGS 2006)). in which PCE was only detected in 3 of
375 samples. The next highest reported concentration was only 2.8E-03 |ig/L, from a sample
collected in the Eastern Pacific Ocean in 1979-1981 (Singh et al. 1983).
Table 2-2-10. Levels of PCE in U.S. Surface Water from Published Literature
Country
Site
Informal ion
Dale
Sampled
N (Defection
frequency)
Concentration (u«/L)
IIKRO/
Source
Data
Quality
Score
Uange
Central
Tendency
(±SD)
United
States
Anchorage,
AK; Chester
Creek (6 urban
sampling sites)
1998-
2001
11(0)
All ND (<0.2)
3975042
Medium
United
States
Nation-wide;
Surface water
for drinking
1999-
2000
375 (8.0E-
03)
ND
(<0.2)-
5.5
NR
3975046
Medium
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Country
Site
Informal ion
Dale
Sampled
N (Defection
Krequencv)
('onccnlralion (ug/l.)
IIKRO/
Source
Data
Qualify
Score
Uange
Central
Tendency
(±SD) '
water sources
(rivers and
reservoirs)
United
States
Eastern Pacific
Ocean
(California, US
to Valparaiso,
Chile)
1979-
1981
30 (0.9)
ND
(ci.OE-
04)-
2.8E-03
Mean: 0.7
(7.0E-04);
Median:
4.0E-04
29192
Medium
NR = Not reported
ND = Not detected; detection limit reported in parenthesis if available.
2.3.4.2.4 Geospatial Analysis Comparing Predicted and Measured Surface
Water Concentrations
A geospatial analysis at the watershed level (HUC-8 and HUC-12) was conducted to compare
the measured and predicted surface water concentrations in 2016 and investigate if the facility
releases may be associated with the observed concentrations in surface water. A geographic
distribution of the concentrations can be found in Section 4, Figure 4-1 and Figure 4-2 (east and
west US, respectively) for the maximum days of release scenario, and in Figure 4-3 and Figure
4-4 (east and west US, respectively) for the 20-day s of release scenario. Overall, there are 33
U.S. states/territories with either a measured concentration or a predicted concentration; at the
watershed level, there are 109 HUC-8 areas and 149 HUC-12 areas with either measured or
predicted concentrations. Appendix D TableApx D-2 and TableApx D-3 provides a list of
states/territories with facility releases (as mapped) and/or monitoring sites.
2.3.4.2.5 Co-location of PCE Releasing Facilities and Monitoring Stations
The co-occurrence of PCE releasing facilities and monitoring stations in a HUC is shown in
Figure 2-7 (Little Arkansas and Rush-vermillion) and Figure 2-8 (Little Calument-Galien and
Lower Grand). There are four HUC-8 areas that have both measured and predicted
concentrations. As the measured concentrations were below the detection limit and the number
of samples collected was small, definitive conclusions could not be drawn on possible
associations between measured concentrations in surface water and predicted concentrations
from facility releases. The collocated facilities and monitoring stations are briefly described
below and summarized in
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Table 2-11.
A. HUC 11030012 (Little Arkansas in Kansas) has one facility with modeled 7Q10 surface
water concentrations ranging from 4.4E-02 to 6.6E-01 ppb, and 7 monitoring stations all
with concentrations less than the reported detection limit (<0.1 ppb). The monitoring
stations are over 20 miles downstream of the facility or are neither up nor downstream of
the facility.
B. HUC 07040001 (Rush-Vermillion in Minnesota) has one facility with modeled 7Q10
surface water concentrations ranging from 2.8E-03 to 5.6E-02 ppb, and 1 monitoring
station with a non-detect concentration (<0.1 ppb) that is located approximately 20 miles
downstream of the facility.
C. HUC 04040001 (Little Calumet-Galien in Indiana) has one receiving facility with
concentrations ranging from 0.1 to 1.7 ppb, and two monitoring stations with non-detect
concentrations (<0.1 ppb). The monitoring stations are either over 2 miles downstream of
the facility, or neither up nor downstream of the facility. It should be noted however, that
a modeled receiving facility (East Chicago Municipal Sewage Treatment Plant; FRS
110006645531) is located just outside of the HUC on the south side. Monitoring site
USGS-04092750 is located on a canal/ditch north of the facility; based on NHD water
flows south from the monitoring site toward the facility.
D. HUC 04050006 (Lower Grand in Michigan), has one receiving facility with
concentrations ranging from 0.1 to 1.0 ppb, and one monitoring station with non-detect
concentrations (<0.1 ppb).
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2480 Figure 2-7. Colocation of PCE Releasing Facilities and WQX Monitoring Stations at the
2481 HU C 8 and HUC 12 Level
2482
2483
2484 Figure 2-8. Colocation of PCE Releasing Facilities and WQX Monitoring Stations at the
2485 HUC 8 and HUC 12 Level
2486
2487
USGS-443840092400301
l.lkl
Saint
t IffV
SGS The National Map: National
Hydrography Dataset. Data refreshed
Octobefr 2018.
Marian'!
-Reservoir
USGS-07143672]
USGS-375338097290800
*
U.S. Locations
Concentrations
Measured - NWIS/STORET Monitoring Sites
® Not detected
Modeled - Direct Release (200 - 365 days/yr)
¦ < 1.4 pg/L (below all COCs)
l_J:HUC-8 boundary
USGS-3753480972628001
CHS McPherson Refinery
McPherson. KS
USGS 07144100|
T ! , Rcier\on
Little Arkansa
11030012
Flint Hills Resources Pine Bend LLC,
Rosemont, MN
Rush-Vermillion
07040001
Superfund (non-NPL)
East Chicago Waterways Mgt. Dist.
upfgr
Superfund (non-NPL)
Indianapolis Blvd. Bridge Mystery Oil
Tradebe Treatment
& Recycling LLC
East Chicago, IN
USGS-04095090
USGS-04092750
Concentrations
Measured - NWIS/STORET Monitoring Sites [•] A,Days of exceedance Ł 20 days
© Not detected _A_ _
Superfund site
Modeled - Indirect Release (200 - 365 days/yr)
~ < 1.4 |jg/L (below all COCs) I IHUC-12 boundary*
Modeled - Direct Release (200 - 365 days/yr) HUC-8 boundary
¦ < 1.4 pg/L (below all COCs)
C il
\i(> I U.S. Locations
Lower Grand
?j 04050006
Little Calumet-Galien
04040001
USGS-04119400
Superfund (non-NPL)
U.S. Steel Hexavalent Chromium Rel.
* Only one HUC-12 contains both
a facility and a monitoring station
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Table 2-11. Co-Location of Facility Releases and Monitoring Sites within HUC 8 and HUC 12 Boundaries (Year 2016)
Mnp
III ( S
l-'iicililies in III ('
Monitoring Sites in III C
Silo
(Niiine, l.ociilion.
1 RS)
Modeled 7QIO
Surface Wsiter
Concent riitions
¦' (Mli/U
Monitoring
Site II)
\o. or
Sii m pies
Measured Surhice
Wilier
Concenlriitions
(Mli/U
Lociilion keliilne
to l-'iicilitv1'
(Miles)'
A
11030012
Little
Arkansas
CHS McPherson
Refinery
McPherson, KS
(FRS 110015862440)
300 days: 4.4E-
02
20 days: 0.6
USGS-
07143672
4
<0.1 (all)
Downstream/23
USGS-
07144100
4
<0.1 (all)
Downstream/34
USGS-
3753380972
90800
2
<0.1 (all)
Downstream/33
USGS-
3753480972
62800
2
<0.1 (all)
Downstream/33
USGS-
3753380972
90800
2
<0.1 (all)
Neither/42
B
07040001
Rush-
Vermillion
Flint Hills Resources
Pine Bend LLC
Rosemount, MN
(FRS 110000424611)
350 days:2.8E-
03
20 days: 5.6E-
02
USGS-
4438400924
00301
1
<0.1
Downstream/20
C
04040001
Little
Calumet-
Galien
Tradebe Treatment &
Recycling LLC
East Chicago, IN
(FRS 110000397874)
Receiving Facility
(modeled site):
Advanced Waste
Services of Indiana
LLC/Covanta
Environmental
Solutions LLC
Portage, IN
250 days: 0.1
20 days: 1.7"
USGS-
04095090c
1
<0.1
Downstream/2.3
USGS-
04092750d
4
<0.1 (all)
Neither/14
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Map
III CS
l-'acilities in III ('
Monitoring Sites in III C
Silo
(Name, Locution,
1 RS)
Modeled 7QIO
Surface Water
Concentrations
' (MU/I-)
Monitoring
Site II)
\o. or
Ssiin pies
Measured Surface
Water
Concentrations
(MU/I-)
Location Rchilixc
to I'acility1'
(Miles)'
(FRS 110020159852)
D
04050006
Lower
Grand
Piano Factory-Grand
Haven
Grand Haven, MI
(FRS 110006739832)
260 days: 0.1*
20 days: 1.0
USGS-
04119400
4
<0.1 (all)
Upstream/10
2489 a Concentrations above the COC of 1.4 |ig/L are shown in bold. Concentrations leading to modeled days of exceedance >20 days are indicated by an
2490 asterisks (*).
2491 b The number of miles between the facility and monitoring site are based on Euclidean distance.
2492 0 The HUC 8 co-located facility and monitoring station are also in the same HUC 12 (040400010509; Willow Creek-Burns Ditch).
2493 d The East Chicago Municipal Sewage Treatment Plant (FRS 110006645531), which receives wastewater from Safety Kleen Systems, Inc. in East Chicago,
2494 IN is not located in the HUC, but is located just south of the HUC, near monitoring site USGS-04092750. This monitoring site is located on a canal/ditch,
2495 and according to NHD, the water flows south from the monitoring site toward the facility.
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2.3.4.3 Biomonitoring Data
EPA identified blood biomonitoring measurements from multiple sources. The most
comprehensive source is the National Health and Nutrition Examination Survey (NHANES)
conducted by CDC's National Center for Health Statistics (NCHS). The survey is "a complex,
stratified, multistage, probability-cluster design survey" designed to collect data on the health
and nutrition of a representative sample of the US population. NHANES measured PCE in whole
blood of males and females ages 12+ years. In the Fourth Report on Human Exposure to
Environmental Chemicals (CDC 2017). statistics were reported for the 50th, 75th, 90th, and 95th
percentiles for 2-year cycles starting in 2001 through 2008. Sample sizes ranged from 978 (2001-
2002) to 2,940 (2005-2006). The concentrations in all samples were less than the limit of
detection (0.048 ng/mL) at the 50th percentile for all years. At the 95th percentile, concentrations
ranged from 9.4E-02 |ig/L (2007-2008) to 1.9E-01 |ig/L (2001-2002).
For 1999-2004 (n=2577), the mean sample concentration was 8.1E-02 (J,g/L, and the median
sample concentration was 3.4E-02 (J,g/L. This study also reported regression statistics,
coefficients, and trends over time for each chemical reported. Another source (Sexton et al.
2005). measured concentrations of PCE in whole blood from 150 children from two poor,
minority neighborhoods in Minneapolis, Minnesota in four periods during 2000-2001. These
samples were collected as part of the School Health Initiative: Environment, Learning, Disease
(SHIELD) study. PCE was detected in 37 to 63% of the samples, with concentrations ranging
from 2.0E-02 - 3.0E-02 ng/mL (10th percentile) to 0.1-0.8 ng/mL (99th percentile). The limit of
detection was 2.2E-02 ng/mL. The SHIELD study also collected 2-day, integrated personal air
samples. Blood samples were also collected as part of the National Human Exposure Assessment
Survey (NHEXAS) Phase I conducted by EPA (Clayton et )). Samples were collected
from 147 people in six states (IL, IN, OH, MI, MN, and WI) in 1995-1997. PCE was detected in
37% of the samples, with a mean of 0.2 ng/mL, a 50th percentile of 5.0E-02 ng/mL, and a 90th
percentile of 0.1 ng/mL. NHEXAS Phase I also collected indoor air and personal air samples.
PCE concentrations in blood were similar between the NHANES, SHIELD, and NHEXAS
surveys conducted between 1995 and 2016.
In addition to blood samples, NHANES also collected urine samples for the PCE metabolite N-
Acetyl-S-(trichlorovinyl)-L-cysteine. Samples were collected for males and females ages 6+
years. Statistics were reported for both uncorrected urine concentrations and creatine corrected
urine concentrations. Data were reported for the survey years 2011-2012, and all samples
measured (n=2,464-2,466) were below the detection limit of 3.0 (J,g/L. The NHANES urine
metabolite data for PCE was also used in a 2015 study analyzing the reported data to develop
means and other descriptive statistics (Jain, 2015). In that paper, the urinary metabolite TCVMA
was reported in measurements of male (n=203) and female children (n=214) in 2011 and 2012.
The mean concentration for male children was reported as 6.9 ng/mL and 6.4 ng/mL for female
children. The 95% confidence interval around the mean was reported as 5.8 to 8.4 ng/mL for
male children and 5.2 to 8.0 ng/mL for female children
Breath samples were also collected as part of the Total Exposure Assessment Methodology
(TEAM) Study (Wallace 1987). which also collected concurrent personal inhalation monitoring
samples and outdoor air samples. In Phase II and III of the study conducted between 1981 and
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1984, samples were collected from adults conducting normal daily activities in
industrial/chemical manufacturing and /or petroleum refining regions of the US, including
Elizabeth and Bayonne, NJ, Los Angeles, CA, and Contra Costa, CA (n= 660). Arithmetic
means ranged from 8.3 to 13 |ig/m3, with detection in 58 to 100% of samples.
2.3.4.4 Assumptions and Key Sources of Uncertainty for Environmental
Exposures
The WQP Tools contains data from USGS-NWIS and STORET databases, and is one of the
largest environmental monitoring databases in the U.S. (Nwqmc 2017); however, comprehensive
information needed for data interpretation is not always reasonably available. In some instances,
proprietary information may be withheld, or specific details regarding analytical techniques may
be unclear, or not reported at all. As a result of all of these shortcomings, there are uncertainties
in the reported data that are difficult to quantify with regard to impacts on exposure estimates.
The quality of the data provided in the USGS-NWIS and STORET datasets varies, and some of
the information provided is non-quantitative. While a large number of individual sampling
results were obtained from these datasets, the monitoring studies used to collect the data were
not necessarily specifically designed to evaluate PCE distribution across the U.S. The available
data represent a variety of discrete locations and time periods; therefore, it is uncertain whether
the reported data are representative of all possible nationwide conditions. Nevertheless, these
limitations do not diminish the overall findings reported in this assessment that exposure data
showed very few instances {i.e., less than 0.01 percent) where measured PCE levels in the
ambient environment exceeded the identified concentrations of concern for water or organisms
(1.4 ppb). It is also important to note that only a few USGS-NWIS and STORET monitoring
stations aligned with the watersheds of the PCE releasing facilities identified under the scope of
this assessment, and the co-located monitoring stations had samples with concentrations below
the detection limit; therefore, no direct correlation can be made between them. To better
characterize instream concentrations of PCE in the environment and provide for more robust
confirmation of our modeled results, we would support the collection of collocated instream
measurements with known discharging facilities.
The DMR, TRI and CDR databases represent comprehensive sources of environmental release data
for the US; however, there are limitations and assumptions involved. These data are self-reported by
facilities and subject to minimum reporting thresholds; therefore, they may not capture releases from
smaller facilities {i.e., environmental releases may be underestimated). Some of the reported
information may be inaccurate because it reflects approximations rather than actual emissions or
release data. TRI is based on mass balances and emission factors, whereas DMR is based on
representative pollutant monitoring data at facility outfalls (mg/L) and corresponding wastewater
discharge (million gallons per day). The assumed maximum days per year of release from each
facility is uncertain and may in some cases lead to underestimation of daily release rates.
Use of release information from facility data used to estimate environmental exposures is
constrained by a number of uncertainties including: the heterogeneity of processes and releases
among facilities grouped within a given sector; assumptions made regarding sector definitions used
to select facilities covered under the scope; and fluctuations in the level of production and associated
environmental releases incurred as a result of changes in standard operating procedures. Uncertainty
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may also arise from omissions in the reporting data, such as sectors that are not required to report,
facilities that fall below the reporting threshold, or facilities for which forms simply are not filed.
A major limitation associated with use of the E-FAST 2014 ( >) model relates to the
assumptions made regarding missing information that was required for model input, such as site-
specific streamflow data. When site-specific or surrogate site-specific stream flow data were not
available, flow data based on a representative industry sector was used in the assessment. This
includes cases where a receiving facility for an indirect release could not be determined.
Additionally, the data currently available in E-FAST 2014 ( ) are 15 to 30 years old.
Although stream conditions do change over time, changes in the flow values are not expected to be
drastic. More recent flow data are available through the National Hydrological Dataset (NHD). It is
important to note however, that these limitations are unlikely to change the stated conclusions of this
assessment because they are based on a series of conservative assumptions that likely overestimate
exposure potential.
With respect to the geospatial analysis, a limitation is the accuracy of the latitudes and longitudes.
The geographic coordinates for facilities were obtained from the FRS Interests geodatabase, which
are assigned through various methods including photo-interpretation, address matching, and GPS.
These are considered "Best Pick" coordinates. While EPA does assign accuracy values for each
record based on the method used, the true accuracy of any individual point is unknown. Also, in
some cases the receiving facilities for indirect releases could not be determined. In these cases the
location of the active releaser was mapped. As such, the co-location of facilities and monitoring sites
may have been missed. As the number of unknown receiving facilities was small and most
monitoring sites had samples with concentrations below the detection limit, this would have minimal
impact on the watershed analysis.
2,3.4,4,1 Confidence in Aquatic Exposure Scenarios
Confidence ratings for aquatic exposure scenarios are informed by uncertainties surrounding inputs
and approaches used in modeling surface water concentrations. In Section 2.2.1.1, confidence ratings
are assigned to these estimated daily releases (kg/site-day) on a per occupational exposure scenario
(OES) basis and primarily reflect moderate confidence (one OES shows high confidence for this
estimate). As these release estimates serve as the key inputs into the exposure mode and are
therefore a key component of the overall aquatic exposure scenario confidence.
Other considerations that impact confidence in the aquatic exposure scenarios include the model
used E-FAST 2014, ( j) and its associated default and user-selected values and related
uncertainties. As described in Section 4.1.2, there are uncertainties related to the ability of E-FAST
2014 ( ) to incorporate downstream fate and transport; the likely number of release
days from given discharging facilities; and, in some cases (i.e., when the NPDES for the discharging
facility cannot be found within the E-FAST database), the applied stream flow distribution.
There are monitoring data available in surface water that reflect both near-facility and ambient (i.e.,
background) exposure levels in this media in the United States. Samples characterizing background
levels in surface water ranged from non-detect (ND) to 310 |ig/L, from both literature and the Water
Quality Portal database.
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2.4 Human Exposures
EPA evaluated acute and chronic exposures to workers by dermal and inhalation routes and
occupational non-users (ONUs) by inhalation routes in association with PCE use in industrial and
commercial applications. EPA also evaluated acute exposures to consumers by dermal and
inhalation routes in association with PCE use in consumer applications. The assessed conditions of
use are described above in Table 1-4; however, due to expected similarities in or lack of data to
distinguish some conditions of use, both exposures/releases and occupational and consumer
exposures for several of the subcategories of use in Table 1-4 were grouped and assessed together
during risk evaluation. For example, subcategories for intermediate uses in industrial gas
manufacturing, basic organic chemical manufacturing, and petroleum refineries may generally have
similar worker activities, and EPA does not have data to distinguish whether workers are exposed
differently for these subcategories. Therefore, EPA has grouped these intermediate conditions of use
into one occupational scenario. A crosswalk of the conditions of use in Table 1-4 to the occupational
and consumer scenarios assessed in this report is provided in Table 2-12 below.
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2647 Table 2-12 Crosswalk of Subcategories of Use Listed in the Problem Formulation Document to Exposure Scenarios Assessed in the
2648 Risk Evaluation
l.il'e Cvcle Stage
Category 11
Subcategory h
Occupational
Kxposurc Scenario
Associated
Condition of I se in
Uisk Calculator
Consumer
Kxposurc
Scenario
Manufacture
Domestic
manufacture
Domestic
manufacture
Section 2.4.1.6-
Manufacturing
Manufacturing
N/A
Import
Import
Section 2.4.1.7 -
Repackaging0
Repackaging
N/A
Processing
Processing as a
reactant/
intermediate
Intermediate in
industrial gas
manufacturing
Section 2.4.1.8 -
Processing as a
Reactant
Processing as
Reactant/
Intermediate
N/A
Intermediate in basic
organic chemical
manufacturing
Intermediate in
petroleum refineries
Residual or byproduct
reused as a reactantd
Incorporated into
formulation
mixture or reaction
product
Cleaning and
degreasing products
Section 2.4.1.9 -
Incorporation into
Formulation, Mixture,
or Reactant Product
Incorporation into
Formulation -
Aerosol Packing;
Incorporation into
Formulation -
Degreasing Solvent;
Incorporation into
Formulation - Dry
Cleaning Solvent;
Incorporation into
Formulation -
Miscellaneous
N/A
Adhesive and sealant
products
Paint and coating
products
Other chemical
products and
preparations
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Life Cycle Slsigc
Category 11
Subcategory h
C)ccii|):ilion:il
Kxposnre Scenario
Associated
Condition of I sc in
Uisk Calcnlalor
Consumer
Kxposnre
Scensirio
Processing -
Incorporated into
articles
Plastic and rubber
products
After further review,
EPA determined that
PCE is not incorporated
into plastic articles but
rather is used as a
degreasing solvent at
plastic manufacture
sites; therefore, no
exposure scenario was
developed for
incorporation into
articles. Use of PCE as
a degreasing solvent at
plastic manufacture
sites is assessed with
other degreasing
scenarios in Sections
2.4.1.10 through
2.4.1.13
N/A
N/A
Repackaging0
Solvent for cleaning
or degreasing
Section 2.4.1.7-
Repackaging
Repackaging
N/A
Intermediate
Recycling
Recycling
Section 2.4.1.26-
Waste Handling,
Disposal, Treatment,
and Recycling
Disposal/Recycling
N/A
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Life Cycle Slsigc
Category 11
Siihcsilegory h
C)ccii|):ilion:il
Kxposurc Scenario
Associated
Condition of I sc in
Uisk Calculator
Consumer
Kxposure
Scensirio
Distribution in commerce
Distribution
Distribution
Activities related to
distribution (e.g.,
loading, unloading) are
considered throughout
the life cycle, rather
than using a single
distribution scenario.
N/A
N/A
Industrial use
Solvents (for
cleaning or
degreasing)
Solvents and/or
Degreasers (cold,
aerosol spray or vapor
degreaser; not
specified in comment)
See sections for
specified degreasing
and cleaning
operations.
See sections for
specified degreasing
and cleaning
operations.
N/A
Batch vapor degreaser
(e.g., open-top,
closed-loop)
Section 2.4.1.10- Batch
Open-Top Vapor
Degreasing;
Section 2.4.1.11- Batch
Closed-Loop Vapor
Degreasing
Open-top Vapor
Degreasing;
Closed Loop Vapor
Degreasing
In-line vapor
degreaser (e.g.,
conveyorized, web
cleaner)
Section 2.4.1.12-
Conveyorized Vapor
Degreasing;
Section 2.4.1.13-Web
Degreasing
Conveyorized Vapor
Degreasing;
Web Degreasing
Cold cleaner
Section 2.4.1.14- Cold
Cleaning
Cold Cleaning
Aerosol spray
degreaser/cleaner
Section 2.4.1.15-
Aerosol Degreasing and
Aerosol Lubricants
Aerosol Degreasing/
Lubricants
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Life Cycle Slsigc
Category 11
Subcategory h
C)ccii|):ilion:il
Kxposnre Scenario
Associated
Condition of I sc in
Uisk Calcnlalor
Consumer
Kxposnre
Scensirio
Dry cleaning solvent
Spot cleaner
Section 2.4.1.16- Dry
Cleaning and Spot
Cleaning
Post-2006 Dry
Cleaning (including
spot cleaning);
4th/5th Gen Only Dry
Cleaning (including
spot cleaning)
Lubricants and
greases
Lubricants and
greases (e.g.,
penetrating lubricants,
cutting tool coolants,
aerosol lubricants)
Section 2.4.1.15-
Aerosol Degreasing and
Aerosol Lubricants;
Section 2.4.1.20-
Metalworking Fluids
Aerosol Degreasing/
Lubricants;
Metalworking Fluid
N/A
Adhesives and
sealants
Solvent-based
adhesives and sealants
Section 2.4.1.17-
Adhesive, Sealants,
Paints, and Coatings
Adhesives
N/A
Paints and coatings
including paint and
coating removers
Solvent-based paints
and coatings,
including for
chemical milling
Section 2.4.1.17 -
Adhesive, Sealants,
Paints, and Coatings;
Section 2.4.1.18-
Maskant for Chemical
Milling
Paints/Coatings;
Chemical Maskant
N/A
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Life Cycle Slsigc
Category 11
Siihcsilegory h
C)ccii|):ilion:il
Kxposurc Scenario
Associated
Condition of I sc in
Uisk Calculator
Consumer
Kxposure
Scensirio
Processing aids,
not otherwise listed
Pesticide, fertilizer
and other agricultural
chemical
manufacturing
Section 2.4.1.19-
Industrial Processing
Aid
Industrial Processing
Aid
N/A
Processing aids,
specific to
petroleum
production
Catalyst regeneration
in petrochemical
manufacturing
Section 2.4.1.19-
Industrial Processing
Aid
Industrial Processing
Aid
N/A
Other uses
Textile processing
Section 2.4.1.22- Other
Spot Cleaning/Spot
Removers (Including
Carpet Cleaning);
Section 2.4.1.23- Other
Industrial Uses
Other Spot
Cleaning/Spot
Removers (Including
Carpet Cleaning);
Other Industrial Uses
N/A
Wood furniture
manufacturing
Section 2.4.1.23- Other
Industrial Uses
Other Industrial Uses
Laboratory chemicals
Section 2.4.1.25-
Laboratory Chemicals
N/A - qualitative
assessment
Foundry applications
Section 2.4.1.23- Other
Industrial Uses
Other Industrial Uses
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Life Cycle Slsigc
Category 11
Siihcsilegory h
Occupational
Kxposure Scenario
Associated
Condition of I sc in
Uisk Calculator
Consumer
Kxposure
Scensirio
Commercial/consumer
use
Cleaning and
furniture care
products
Cleaners and
degreasers (other)
Section 2.4.1.21- Wipe
Cleaning and
Metal/Stone Polishes;
Section 2.4.1.22- Other
Spot Cleaning/Spot
Removers (Including
Carpet Cleaning);
Section 2.4.1.24 -
Other Commercial Uses
Wipe Cleaning and
Metal/Stone Polishes;
Other Spot
Cleaning/Spot
Removers (Including
Carpet Cleaning);
Other Commercial
Uses - Mold Release
Section
2.4.2.3.1-
Aerosol
Degreasers
(includes:
marine cleaner,
degreaser, coil
cleaner, electric
motor cleaner,
parts cleaner,
cable cleaner,
stainless steel
polish,
electrical/energi
zed cleaner,
wire and
ignition
demoisturants,
electric motor
cleaner; brake
cleaners)
Dry cleaning solvent
Section 2.4.1.16- Dry
Cleaning and Spot
Cleaning
Post-2006 Dry
Cleaning (including
spot cleaning);
Section 2.4.2.4-
Dry Cleaned
Articles
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Life Cycle Slsigc
Category 11
Siihcsilegory h
Occupational
Kxposure Scenario
Associated
Condition of I sc in
Uisk Calculator
Consumer
Kxposure
Scensirio
Spot cleaner
4th/5th Gen Only Dry
Cleaning (including
spot cleaning)
Combined
under Aerosol
Cleaner
Automotive care
products (e.g., engine
degreaser and brake
Section 2.4.1.15-
Aerosol Degreasing and
Aerosol Lubricants
Aerosol Degreasing/
Lubricants
Section
2.4.2.3.1-Brake
Cleaner
cleaner)
Section
2.4.2.3.2- Parts
Cleaner
Aerosol cleaner
Section
2.4.2.3.3-
Vandalism
Mark & Stain
Remover, Mold
Cleaner, Weld
Splatter
Protectant
Non-aerosol cleaner
Section 2.4.1.21- Wipe
Cleaning and
Metal/Stone Polishes
Wipe Cleaning and
Metal/Stone Polishes
Section
2.4.2.3.4-
Marble and
Stone Polish
(liquid)
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Life Cycle Slsigc
Category 11
Siihcsilegory h
Occupational
Kxposure Scenario
Associated
Condition of I sc in
Uisk Calculator
Consumer
Kxposure
Scensirio
Lubricants and
greases
Lubricants and
greases (e.g.,
penetrating lubricants,
cutting tool coolants,
aerosol lubricants)
Section 2.4.1.15-
Aerosol Degreasing and
Aerosol Lubricants;
Section 2.4.1.20 -
Metalworking Fluids
Aerosol Degreasing/
Lubricants;
Metalworking Fluid
Section
2.4.2.3.5-
Cutting Fluid
Section
2.4.2.3.6- Spray
Lubricant and
Penetrating Oil
Adhesives and
sealant chemicals
Adhesives for arts and
crafts
Not assessed in
occupational settings -
consumer use only
N/A
Section
2.4.2.3.7-
Adhesives
(includes
industrial
adhesive, arts
and crafts
adhesive, gun
ammunition
sealant)
Section
2.4.2.3.8 -
Livestock
Grooming
Adhesive
Light repair adhesives
Section 2.4.1.17-
Adhesive, Sealants,
Paints, and Coatings
Adhesives
Section
2.4.2.3.9-
Column
Adhesive,
Caulk and
Sealant
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Life Cycle Slsigc
Category 11
Siihcsilegory h
Occupational
Kxposure Scenario
Associated
Condition of I sc in
Uisk Calculator
Consumer
Kxposure
Scensirio
Paints and coatings
Solvent-based paints
and coatings
Section 2.4.1.17-
Adhesive, Sealants,
Paints, and Coatings
Paints/Coatings
Section
2.4.2.3.10-
Outdoor
watershield
(liquid)
Section
2.4.2.3.11-
Coatings and
primers
(aerosol)
Section
2.4.2.3.12-Rust
Primer and
Sealant (liquid)
Section
2.4.2.3.13-
Metallic
Overglaze
Other Uses
Carpet cleaning
Section 2.4.1.22- Other
Spot Cleaning/Spot
Removers (Including
Carpet Cleaning)
Other Spot
Cleaning/Spot
Removers (Including
Carpet Cleaning)
Not found as
consumer
product
Laboratory chemicals
Section 2.4.1.25-
Laboratory Chemicals
N/A - qualitative
assessment
Not assessed in
consumer
setting -
occupational
use only
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Life Cycle Slsigc
Category 11
Siihcsilegory h
Occupational
Kxposure Scenario
Associated
Condition of I sc in
Uisk Calculator
Consumer
Kxposure
Scensirio
Metal (e.g., stainless
steel) and stone
polishes
Section 2.4.1.21 - Wipe
Cleaning and
Metal/Stone Polishes
Wipe Cleaning and
Metal/Stone Polishes
Section
2.4.2.3.14-
Marble and
Stone Polish
(wax)
Inks and ink removal
products
Section 2.4.1.24 -
Other Commercial Uses
Other Commercial
Uses - Printing
Ink removal
combined under
Aerosol Cleaner
(vandalism and
stain remover);
use in printing
inks discussed
as "other use"
Welding®
Section 2.4.1.15-
Aerosol Degreasing and
Aerosol Lubricants'3
Aerosol Degreasing/
Lubricants
Combined
under Aerosol
Cleaner (weld
splatter
protectant)
Photographic film
Section 2.4.1.24- Other
Commercial Uses
Other Commercial
Uses - Photographic
Film
Not found as
consumer
product
Mold cleaning,
release and protectant
products
Section 2.4.1.24 -
Other Commercial Uses
Other Commercial
Uses - Mold Release
Combined
under Aerosol
Cleaner (mold
cleaner)
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Life Cycle Slsigc
Category 11
Siihcsilegory h
C)ccii|):ilion:il
Kxposurc Scenario
Associated
Condition of I sc in
Uisk Calculator
Consumer
Kxposure
Scensirio
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
Off-site waste transfer
Section 2.4.1.26 -
Waste Handling,
Disposal, Treatment
and Recycling
Process Solvent
Recycling and
Worker Handling of
Wastes
N/A
2649 a These categories of conditions of use appear in the Life Cycle Diagram, reflect CDR codes, and broadly represent conditions of use of PCE in industrial and/or
2650 commercial settings.
2651 b These subcategories reflect more specific uses of PCE.
2652 0 The repackaging scenario covers only those sites that purchase PCE or PCE containing products from domestic and/or foreign suppliers and repackage the PCE from
2653 bulk containers into smaller containers for resale. Sites that import and directly process/use PCE are assessed in the relevant condition of use. Sites that import and either
2654 directly ship to a customer site for processing or use or warehouse the imported PCE and then ship to customers without repackaging are assumed to have no exposures or
2655 releases and only the processing/use of PCE at the customer sites are assessed in the relevant conditions of use.
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2656 d EPA assessed PCE as a reactant where it was produced as a byproduct from EDC manufacture and reused as a reactant.
2657 e Identified welding products were anti-spatter aerosol products; therefore, the assessment is included with the assessment of other aerosol products.
2658 f Each of the conditions of use of PCE may generate waste streams of the chemical that are collected and transported to third-party sites for disposal, treatment, or
2659 recycling. Industrial sites that treat, dispose, or directly discharge onsite wastes that they themselves generate are assessed in each condition of use assessment. This
2660 section only assesses wastes of PCE that are generated during a condition of use and sent to a third-party site for treatment, disposal, or recycling.
2661
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2671
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2673
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2675
2676
2677
2678
2679
2680
2681
2682
2683
2684
2685
2686
2687
2688
2689
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2.4.1 Occupational Exposures
The following subsections describe EPA's approach to assessing occupational exposures and results for
each condition of use assessed. For additional details on development of approaches and results refer to
the Assessment of Occupational Exposure and Environmental Releases for Perchloroethylene (Ethene,
1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) ( |0d).
2.4.1.1 Approach to Workers and Occupational Non-Users
As described in the Problem Formulation of the Risk Evaluation for Perchloroethylene (Ethene, 1,1,2,2-
Tetrach/oro)( 18d), for each condition of use, EPA endeavors to distinguish exposures for
workers and occupational non-users (ONUs). Normally, a primary difference between workers and
ONUs is that workers may handle PCE and have direct contact with the chemical, while ONUs are
working in the general vicinity of workers but do not handle PCE and do not have direct contact with
PCE being handled by the workers. The size of the area that ONUs may work can vary across each OES
and across facilities within the same OES and will depend on the facility configuration, building and
room sizes, presence of vapor barrier, and worker activity pattern. For example, an ONU can be a
production employee whose workstation is located on the factory floor where a degreasing unit is
installed. Absence of any vapor barrier (e.g., walls) between the degreaser and the rest of the factory,
this "area" can be an entire factory floor. Alternately, the area can be in a specific room of a building
where a chemical is handled (e.g., a room in a dry cleaning shop where the dry cleaning machine is
installed and where dry cleaned loads are unloaded, pressed, and finished). Where possible, for each
condition of use, EPA identified job types and categories for workers and ONUs.
EPA evaluated inhalation exposures to workers and ONUs, and dermal exposures to workers. EPA did
not assess dermal exposures to ONUs as EPA does not expect ONUs to have routine dermal exposures
in the course of their work. Depending on the condition of use, ONUs may have incidental dermal
exposures due to surface contamination. However, data (e.g., frequency and amount of liquid on the skin
after contact) were not identified to assess this exposure.
2.4.1.2 Number of Workers and Occupational Non-Users Approach and
Methodology
Where available, EPA used CDR data to provide a basis to estimate the number of workers and ONUs.
EPA supplemented the available CDR data using available market data; NAICS and SIC code data from
TRI, DMR, and NEI sites identified for each condition of use (for number of sites estimates see Section
2.2.1.2.2); and analyzing Bureau of Labor Statistics (BLS) and U.S. Census data using the methodology
described in the Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report)
( 020d). Where market penetration data and site-specific N A ICS/SIC codes from
TRI/DMR/NEI were not available, EPA estimated the number of workers using data from GSs and
ESDs. For additional details on development of estimates of number of workers refer to Appendix A in
the Assessment of Occupational Exposure and Environmental Releases for Perchloroethylene (Ethene,
1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) ( :0d).
Table 2-13 presents the confidence rating of data that EPA used to estimate number of sites and workers.
Table 2-13. Data Evaluation of Sources Containing Number of Worker Estimates
Source Reference
Data Type
Dala Qualify Ualing
('ondhion(s) of I se
(US. EPA. 2016d")
Number of Workers
High
Manufacturing
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2705
2706
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( )
Number of Workers
High
Manufacturing; Repackaging;
Processing as a Reactant;
Incorporation into Formulation,
Mixture, or Reaction Product;
Cold Cleaning; Aerosol
Degreasing and Aerosol
Lubricants; Dry Cleaning and Spot
Cleaning; Adhesives, Sealants,
Paints, and Coatings; Chemical
Maskants; Industrial Processing
Aid; Other Industrial Uses;
Laboratory Chemicals; Waste
Handling, Disposal, Treatment,
and Recycling
(15. S. Census Bureau
2015)
Number of Workers
High
(( )
Number of Workers
N/A - ESD
OTVD, Closed-Loop Vapor
Degreasing, Conveyorized Vapor
Degreasing, Web Degreasing
COE' )
Number of Workers
N/A - ESD
Metalworking Fluids
(( )
Number of Workers
N/A - ESD
Other Spot Cleaning/Spot
Removers (Including Carpet
Cleaning)
( 0
Number of Workers
N/A - GS
ccarb imm
Market Penetration
Data
High
Aerosol Degreasing and Aerosol
Lubricants
(DIM. )
Market Penetration
Data
High
Dry Cleaning
2.4.1.3 Inhalation Exposures Approach and Methodology
To assess inhalation exposure, EPA reviewed exposure monitoring data identified through the
systematic review process (described in Section 1.5) and monitoring data provided to EPA by other
government agencies (e.g., OSHA and DOD) and mapped them to specific conditions of use.
Monitoring data used in the occupational exposure assessment include data collected by government
agencies such as OSHA and NIOSH, and data found in published literature. For each exposure scenario
and worker job category ("worker" or "occupational non-user"), where available, EPA provided results
representative of central tendency and high-end exposure levels. For datasets with six or more data
points, central tendency and high-end exposures were estimated using the 50th and 95th percentile value
from the observed dataset, respectively. For datasets with three to five data points, the central tendency
and high-end exposures were estimated using the median and maximum values. For datasets with two
data points, the midpoint and the maximum value were presented. Finally, datasets with only one data
point were presented as-is. For datasets including exposure data that were reported as below the limit of
detection (LOD), EPA estimated the exposure concentrations for these data, following guidance in
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EPA's Guidelines for Statistical Analysis of Occupational Exposure Data (U, ft)11. A dataset
comprises the combined exposure monitoring data from all studies applicable to that condition of use.
For exposure assessment, personal breathing zone (PBZ) monitoring data were used to determine the
time-weighted average (TWA) exposure concentration. The lone exception to this is exposures from
mold release products (assessed in "Other Commercial Uses") where the assessment was made with area
monitoring data as PBZ data were not available. TWA exposure concentrations are then used to
calculate the Acute Concentration (AC) used for estimating acute risks (i.e., risks associated from a
single day or 24-hr of exposure); Average Daily Concentrations (ADC) used for estimating chronic,
non-cancer risks; and Lifetime Average Daily Concentration (LADC) used for estimating chronic cancer
risks. AC, ADC, and LADC are calculated using the approach and equations described in Appendix B
and C of the Assessment of Occupational Exposure and Environmental Releases for Perchloroethylene
(Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) ( )20d).
Table 2-14 presents the confidence rating of monitoring data that EPA used to assess occupational
exposures. EPA evaluated monitoring data using the evaluation strategies laid out in the Application of
Systematic Review in TSCA Risk Evaluations (U. 1018b). All exposure monitoring data used in
the assessment have a "high" or "medium" confidence rating.
EPA also presented TWA concentrations based on shorter averaging times (e.g., 15-min, 30-min, 1-hr,
and 4-hr) in addition to full-shift (either 8- or 12-hour) TWAs for several conditions of use. Short-term
TWAs are only presented where data were available to do so. EPA's primary concern for this
assessment were full-shift exposures; therefore, no effort was made to estimate shorter-term exposure
values where data were not reasonably available. AC, ADC, and LADC values are only calculated based
on the full-shift (8- or 12-hr TWAs) as full-shift data represent the closest approximation to a worker's
exposure for a full day (i.e., 24-hr), assuming no exposure once the worker leaves the job site. The full-
shift exposure results can then be averaged over 24 hours, working years, or lifetime years to estimate
AC, ADC, and LADC, respectively. Short-term data may not be representative of a full day's exposure,
thus, underestimating AC, ADC, and LADC results.
For several conditions of use, EPA modeled exposure in occupational settings. The models were used to
either supplement existing exposure monitoring data or to provide exposure estimates where measured
data are unavailable. The use of modeling to supplement existing exposure monitoring data was
primarily used to aid EPA's understanding of the monitoring data's representativeness of actual
exposures within the condition of use. For example, where model results and monitoring data are
similar, it helps corroborate the representativeness of the data to actual exposures. When determining
unreasonable risks for scenarios with both monitoring data and modeling, EPA generally uses
monitoring data results over modeling unless the data quality score for the monitoring data is low, or
there were limited number of data points for the scenario such that the representativeness of the data is
limited. Where measured monitoring data and models were not available, EPA estimated exposures
using values from GSs and ESDs. A summary of approaches and EPA's overall confidence in the
exposure estimates are provided in Table 2-14.
11 Using the if the geometric standard deviation of the data is less than 3.0 and if the geometric standard deviation is
V2
3.0 or greater.
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2761 Table 2-14. Data Evaluation of Sources Containing Occupational Exposure Monitoring Data
Data Quality
Rating
Source Reference
Data Type
Condition of I se
(H.SIA.2018a)
PBZ
Monitoring
High
Manufacturing; Processing as a Reactant
(Dow Chem 1984)
PBZ
Monitoring
Medium
Repackaging
(Orris and Daniels
I98:n
PBZ
Monitoring
High
Incorporation into Formulation, Mixture, or
Reaction Product (Aerosol Packing Only)
(Gorman et al
PBZ
Monitoring
Medium
OTVD
(Ruhe 1982)
PBZ
Monitoring
Medium
OTVD
PBZ
Monitoring
High
OTVD
PBZ
Monitoring
High
OTVD
PBZ
Monitoring
High
OTVD; Closed-Loop Vapor Degreasing
PBZ
Monitoring
High
Closed-Loop Vapor Degreasing; Cold Cleaning
(Vulcan 1994)
PBZ
Monitoring
High
Cold Cleaning
(LIS. POD and
Environmental
Health Readiness
System - Industrial
2018)
PBZ
Monitoring
High
Aerosol Degreasing and Aerosol Lubricants; Dry
Cleaning and Spot Cleaning; Adhesives, Sealants,
Paints, and Coatings (Paints and Coatings Only);
Chemical Maskant; Other DoD Uses
(Coserove and
Hygiene 1994'
PBZ
Monitoring
High
Aerosol Degreasing and Aerosol Lubricants
(Vulcan 1992
PBZ
Monitoring
High
Aerosol Degreasing and Aerosol Lubricants
(Vulcan 1993
PBZ
Monitoring
High
Aerosol Degreasing and Aerosol Lubricants
(OSHA2Q17
PBZ
Monitoring
High
Dry Cleaning and Spot Cleaning
PBZ
Monitoring
High
Dry Cleaning and Spot Cleaning
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Source UiTcrencc
Type
Qusililv
Killing
Condition of I so
(Burroughs 1999a)
PBZ
Monitoring
High
Dry Cleaning and Spot Cleaning
( rroughs 1999b)
PBZ
Monitoring
High
Dry Cleaning and Spot Cleaning
( rroughs 1999b)
PBZ
Monitoring
High
Dry Cleaning and Spot Cleaning
(Burroughs 2000)
PBZ
Monitoring
High
Dry Cleaning and Spot Cleaning
(NIGSH 2000)
PBZ
Monitoring
High
Dry Cleaning and Spot Cleaning
(Gromiec et al.
2002)
PBZ
Monitoring
Medium
Adhesives, Sealants, Paints, and Coatings
(Adhesives Only)
(Chrostek and
Levis )
PBZ
Monitoring
High
Adhesives, Sealants, Paints, and Coatings (Paints
and Coatings Only)
(Stephenson and
Albrecht 1986)
PBZ
Monitoring
High
Adhesives, Sealants, Paints, and Coatings (Paints
and Coatings Only)
(Hani 3)
PBZ
Monitoring
Medium
Adhesives, Sealants, Paints, and Coatings (Paints
and Coatings Only)
(Ford Motor 1981)
PBZ
Monitoring
Medium
Adhesives, Sealants, Paints, and Coatings (Paints
and Coatings Only)
(Hervin et al. 1977)
PBZ
Monitoring
High
Chemical Maskant
(Dow Chem 1983b)
PBZ
Monitoring
Medium
Industrial Processing Aid
(Dow Chem 1983a)
PBZ
Monitoring
Medium
Industrial Processing Aid
(Dow Chem 1982)
PBZ
Monitoring
Medium
Industrial Processing Aid
(Dow Chem 1979)
PBZ
Monitoring
Medium
Industrial Processing Aid
(Gunter and
Lybarger 1979)
PBZ
Monitoring
High
Wipe Cleaning and Metal/Stone Polishes
(Moodv et al. 1983)
PBZ
Monitoring
High
Wipe Cleaning and Metal/Stone Polishes
(Burton and
Monesterskv 1996)
PBZ
Monitoring
High
Other Spot Cleaning/Spot Removers (Including
Carpet Cleaning)
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Source Reference
Data Type
Data Quality
Rating
Condition of I se
(Gold et al. 2008)
Area
Monitoring
High
Other Commercial Uses (Mold Release Only)
fNIOSH 1980)
PBZ
Monitoring
Medium
Other Commercial Uses (Printing Only)
CAool 1981)
PBZ
Monitoring
High
Other Commercial Uses (Printing Only)
CLove 1982)
PBZ
Monitoring
High
Other Commercial Uses (Printing Only)
CRuhe 1983)
PBZ
Monitoring
High
Other Commercial Uses (Printing Only)
( iter et al. 1984)
PBZ
Monitoring
High
Other Commercial Uses (Printing Only)
CBurotn 1994)
PBZ
Monitoring
Medium
Other Commercial Uses (Printing Only)
(Moseley 1980)
PBZ
Monitoring
Medium
Other Commercial Uses (Photographic Film Only)
(Stefaniak et al.
2000)
PBZ
Monitoring
High
Other Commercial Uses (Photocopying Only)
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Table 2-15. A Summary of Approaches and Overall Confidence for Exposures Estimates for Each
OES
Note: Where EPA was not able to estimate ONU inhalation exposure from monitoring data or models,
this was assumed equivalent to the central tendency experienced by workers for the corresponding OES;
dermal exposure for ONUs was not evaluated because they are not expected to be in direct contact with
Occupational
Kxposurc
Scenario
«)i:s)
Inhalation Kxposurc
Dermal
Kxposurc
Modeling1'
Monitoring
Modeling
Overall
Con fidcncc
Moniloriii" # Data .
, „ ¦ , Qiisililv Worker ()M
Data Points-' .
Katinu
Worker OM
Worker
OM
Worker OM
Manufacturing
~
152°
H
~
3c
3c
3C
H
L
~
-
Repackaging
~
10
M
~
3c
3C
M
L
~
-
Processing as a
Reactant
~
152d
H
~
3C
3c
3C
H
L
~
-
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Occupational
Exposure
Scenario
(OES)
Inhalation Exposure
Dermal
Monitoring
Modeling
Overall
Confidence
Exposure
Modelingb
Monitoring
Data
# Data
Points3
Data
Quality
Rating
Worker
ONU
Worker
ONU
Worker
ONU
Worker
ONU
Incorporation
into
Formulation,
Mixture, or
Reaction
S
5
H
3C
3c
3C
H
L
-
Product
(Aerosol
Packing Only)
Incorporation
into
Formulation,
Mixture, or
Reaction
-
-
3C
3C
3C
M
L
-
Product (Non-
Aerosol
Packing Only)
Batch Open-
Top Vapor
S
75
MtoH
3C
3C
MtoH
MtoH
Degreasing
Batch Closed-
Loop Vapor
Degreasing
S
15
H
3C
3C
H
H
-
Conveyorized
Vapor
3C
3C
M
M
Degreasing
Web
Degreasing
3C
-
-
3C
3C
M
M
-
Cold Cleaning
s
29
H
3C
MtoH
MtoH
-
Aerosol
Degreasing
and Aerosol
s
130
H
3C
H
H
-
Lubricants
Dry Cleaning
and Spot
s
140e
H
H
H
Cleaning
Adhesives,
Sealants,
Paints, and
s
28f
M; M
to H8
3C
3C
3C
M
L
-
Coatings
Maskant For
Chemical
s
24
H
3C
3C
3C
MtoH
L
-
Milling
Industrial
Processing Aid
s
89
M
3C
3C
3C
M
L
-
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Occupational
Exposure
Scenario
(OES)
Inhalation Exposure
Monitoring
Monitoring
Data
# Data
Points3
Data
Quality
Rating
Worker
ONU
Modeling
Worker
ONU
Overall
Confidence
Worker
ONU
Dermal
Exposure
Modelingb
Worker
ONU
Metalworking
Fluids'1
M
Wipe Cleaning
and
Metal/Stone
Polishes
10
H
MtoH
M to H
Other Spot
Cleaning/Spot
Removers
(Including
Carpet
Cleaning)
~
H
~
~
M
M
~
Other
Industrial Uses
M
Other
Commercial
Uses
~
921
M to H;
H; M;
HJ
~
M to H;
M
~
Laboratory
Chemicals
EPA did not identify data to assess this OES.
Waste
Handling,
Disposal,
Treatment, and
Recycling
M
Other
Department of
Defense Uses
~
H
~
H
~
This number only includes full-shift (8-hr and 12-hr TWAs) and does not include short-term samples (i.e., 15-min, 30-min,
i0-min, or 4-hr TWAs).
EPA has a medium level of confidence in its dermal exposure estimates which are based on high-end/central tendency
tarameters and commercial/industrial settings.
This count includes 75 8-hr TWA data points and 77 12-hr TWA data points.
The data for this OES are the same monitoring data from PCE manufacturing sites used as surrogate for sites processing
>CE as a reactant.
This count includes 22 data points for the post-2006 NESHAP mix of machine generations and 118 data points for fourth
md fifth generation machines only. See Section 2.4.1.16 for further discussion of the two data sets.
This count includes 13 data points for adhesives/sealants and 15 data points for paints/coatings.
For adhesives/sealants the data quality is M; for paints/coatings the data quality is M to H.
Exposure to metalworking fluids were assessed using estimates from an ESD.
This includes 23 data points for printing applications, 3 data points for photocopying, 62 data points for photographic film
pplications, and 4 for mold release products.
For printing applications the data quality is M to H; for photocopying the data quality is H; for photographic film
pplications the data quality is M; for mold release products the data quality is H.
This count includes one data point for oil analysis uses at DoD sites and one data point for water pipe repair uses at DoD
ites.
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2.4.1.4 Consideration of Engineering Controls and Personal Protective Equipment
OSHA and NIOSH recommend employers utilize the hierarchy of controls to address hazardous
exposures in the workplace. The hierarchy of controls strategy outlines, in descending order of priority,
the use of elimination, substitution, engineering controls, administrative controls, and lastly personal
protective equipment (PPE). The hierarchy of controls prioritizes the most effective measures first which
is to eliminate or substitute the harmful chemical (e.g., use a different process, substitute with a less
hazardous material), thereby preventing or reducing exposure potential. Following elimination and
substitution, the hierarchy recommends engineering controls to isolate employees from the hazard (e.g.,
source enclosure, local exhaust ventilation systems), followed by administrative controls (e.g. do not
open machine doors when running), or changes in work practices (e.g., maintenance plan to check
equipment to insure no leaks) to reduce exposure potential. Administrative controls are policies and
procedures instituted and overseen by the employer to limit worker exposures. As the last means of
control, the use of personal protective equipment (e.g., respirators, gloves) is recommended, when the
other control measures cannot reduce workplace exposure to an acceptable level.
OSHA's Respiratory Protection Standard (29 CFR § 1910.134) requires employers to address workplace
hazards by implementing engineering control measures and, if these are not feasible, provide respirators
that are applicable and suitable for the purpose intended. Respirator selection provisions are provided in
§ 1910.134(d) and require that appropriate respirators are selected based on the respiratory hazard(s) to
which the worker will be exposed and workplace and user factors that affect respirator performance and
reliability. Assigned protection factors (APFs) are provided in Table 1 under § 1910.134(d)(3)(i)(A) (see
below in Table 2-16) and refer to the 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 OSHA's Respiratory Protection
Standard.
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 may include air-purifying respirators with organic
vapor cartridges. Respirators must meet or exceed the required level of protection listed in Table 2-16.
Based on the APF, inhalation exposures may be reduced by a factor of 5 to 10,000, if respirators are
properly worn and fitted.
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Table 2-16. Assigned Protection Factors for Respirators in OSHA Standard 29 CFR 1910.134
Type of Respirator
Quarter
Mask
Half
Mask
Full
l-accpicce
Mclmcl/
Mood
Loose-fit ling
l-'acepiece
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 § 1910.134(d)(3)(i)(A)
The National Institute for Occupational Safety and Health (NIOSH) and the U.S. Department of Labor's
Bureau of Labor Statistics (BLS) conducted a voluntary survey of U.S. employers regarding the use of
respiratory protective devices between August 2001 and January 2002 (NIOSH 2 ). Results of the
survey include the number and percent of establishments and employees using respirators within 12
months prior to the survey. For additional information, please also refer to
[MemorandumNIOSHBLS Respirator Usage in Private Sector Firms, Docket: TBD],
The plausibility of regular respirator use by workers was considered on an OES-specific basis. See Table
4-3 for determinations of whether respirator use was assumed for each OES during risk characterization.
2.4.1.5 Dermal Exposure Assessment Approach
Dermal exposure data was not readily available for the conditions of use in the assessment. Because
PCE is a volatile liquid that readily evaporates from the skin, EPA estimated dermal exposures using the
Dermal Exposure to Volatile Liquids Model. This model determines a dermal potential dose rate based
on an assumed amount of liquid on skin during one contact event per day and the steady-state fractional
absorption for PCE based on a theoretical framework provided by Kasting (2006). The amount of liquid
on the skin is adjusted by the weight fraction of PCE in the liquid to which the worker is exposed.
Specific details of the dermal exposure assessment can be found in Section 2.4.1.29 and equations and
sample calculations for estimate dermal exposures can be found in Appendix K of the Assessment of
Occupational Exposure and Environmental Releases for Perchloroethylene (Ethene, 1,1,2,2,-
Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) ( ,020d).
2.4.1.6 Manufacturing
Worker Activities
During manufacturing, workers are potentially exposed while connecting and disconnecting hoses and
transfer lines to containers and packaging to be loaded with PCE product (e.g., railcars, tank trucks,
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totes, drums, bottles) and intermediate storage vessels (e.g., storage tanks, pressure vessels). 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 inhalation of vapors.
ONUs include employees that work at the site where PCE is manufactured, but they do not directly
handle the chemical and therefore are assumed to have lower inhalation exposures, and are not assumed
to have dermal 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
manufacturing workers.
Number of Workers and Occupational Non-Users
To determine the number of workers, EPA used the average of the ranges reported in the 2016 CDR for
four sites where data were available and worker and ONUs estimates from the BLS analysis for the
other four sites (see the Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report)
(U.S. EPA. 2020d) for number of sites estimate). For the BLS analysis EPA used the NAICS code
325199—All Other Basic Organic Chemical Manufacturing to estimate workers and ONUs. CDR data
do not differentiate between workers and ONUs; therefore, EPA assumed the ratio of workers to ONUs
would be similar as determined in the BLS data where approximately 68% of the exposed personnel are
workers and 32% are ONUs ( ). This resulted in approximately 640 workers and 300
ONUs (see Table 2-17).
Table 2-17. Estimated Number of Workers Potentially Exposed to PCE During Manufacturing
Number of
Sites
Kxposed
Workers per
Site
Kxposed
Occupational
Non-l sers per
Site
Total Kxposcd
Workers"
Total Kxposcd
Occupational
Non-l sers11
Total Kxposcd"
8
80
38
640
300
940
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
Table 2-18 summarizes 15-min, 30-min, 8-hr, and 12-hr TWA exposure results for manufacturing. The
high-ends are the 95th percentile of the respective data sets and the central tendencies are the 50th
percentile. EPA assessed exposures using data submitted for three companies by the Halogenated
Solvent Industry Alliance (HS1A) (HSIA 2018a). It should be noted that approximately 65% of the 8-hr
TWA exposure data, 73% of the 12-hr TWA exposure data, 24% of the 15-min TWA exposure data, and
55%) of the 30-min TWA exposure data were below the limit of detection (LOD). To estimate exposure
concentrations for these data, EPA followed the Guidelines for Statistical Analysis of Occupational
Exposure Data ( |4b) as discussed in Section 2.4.1.3. The geometric standard deviation for
the 8-hr TWA data, 12-hr TWA data, and 15-min TWA were all above 3.0; therefore, EPA used the
to estimate the exposure value as specified in the guidelines (U.S. EPA. 1994b). The geometric standard
deviation for the 30-min TWA was below 3.0; therefore, EPA used the ^j=- to estimate the exposure
value as specified in the guidelines (U. lb). Because over 50% of the data are below the LOD
for the 8-hr, 12-hr, and 30-min TWA data, calculating statistics from this data does present the potential
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to introduce biases into the results. Estimation of exposure values for results below the LOD may over-
or under-estimate actual exposure thus skewing the calculated statistics higher or lower, respectively.
The overall directional bias of the exposure assessment, accounting for both the overestimate and
underestimate, is not known.
It should also be noted that 18 8-hr TWA exposure data points and 5 30-min TWA data points from
Company C were not included in the results as they were reported as being below the detection limit, but
the company did not provide the value of the LOD. Therefore, EPA could not estimate a value for these
data using the guidelines described above. Data were not available to estimate ONU exposures; EPA
estimates that ONU exposures are lower than worker exposures, since ONUs do not typically directly
handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency exposure results
as a surrogate to estimate exposures for ONUs.
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2900 Table 2-18. Summary of Inhalation Monitoring Data for the Manufacture of PCE
Kxposure Concentration Type
W orker
Central
Tendency
(ppm)
iposurcs
lligli-
Ind
(ppm)
Nil m her
of
Samples
Occupational
Non-l ser
Kxposurcs
(ppm)11
Data Quality
Kilting of Air
Concentration
Data
8-hr TWA Exposure Concentration
3.3E-02
2.6
75b
3.3E-02
High
Acute Exposure Concentration (AC)
based on 8-hr TWA
1.1E-02
0.9
1.1E-02
Average Daily Concentration (ADC)
based on 8-hr TWA
7.4E-03
0.6
7.4E-03
Lifetime Average Daily
Concentration (LADC) based on 8-
hr TWA
2.9E-03
0.3
2.9E-03
12-hr TWA Exposure Concentration
2.1E-02
0.2
77
2.1E-02
Acute Exposure Concentration (AC)
based on 12-hr TWA
1.0E-02
0.1
1.0E-02
Average Daily Concentration (ADC)
based on 12-hr TWA
7.0E-03
7.3E-02
7.0E-03
Lifetime Average Daily
Concentration (LADC) based on 12-
hr TWA
2.8E-03
3.7E-02
2.8E-03
15-min TWA Exposure
Concentration
2.0
15
161
2.0
30-min TWA Exposure
Concentration
0.7
12
38°
0.7
2901 AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
2902 a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
2903 worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
2904 this value for ONUs is unknown.
2905 b Data does not include 18 data points that were reported as being below the detection limit, but for which the company did
2906 not provide the LOD for use in estimating an exposure value.
2907 0 Data does not include five data points that were reported as being below the detection limit, but for which the company did
2908 not provide the LOD for use in estimating an exposure value.
2909 Sources: (HSIA 2018a")
2910
2911 Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
2912 Exposure to workers is assessed using PCE personal breathing zone monitoring data collected at
2913 workplaces directly applicable to this condition of use, and the data were determined to have a "high"
2914 confidence rating through EPA's systematic review process. Specifically, the data were determined to be
2915 highly representative in geographic scope and reflective of current operations. The source also provides
2916 metadata including sample type and sample duration.
2917
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The data includes exposure concentrations for a variety of worker tasks at each of the three
manufacturing facilities from which the data were obtained. It is not known whether these data points
would also be representative of the worker exposure level at other domestic manufacturing facilities.
Despite this uncertainty, EPA has a high level of confidence in the assessed worker exposures based on
the strength of the monitoring data.
Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.7 Repackaging
Worker Activities
During repackaging, workers are potentially 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 inhalation of vapors.
ONUs include employees that work at the site where PCE 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 Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during
repackaging of PCE using Bureau of Labor Statistics" OES data ( S 2016) and the U.S. Census"
SUSB ( Tisus Bureau 2015) as well as the primary NAICS and SIC code reported by each site in
the 2016 TRI or 2016 DMR, respectively (see the Assessment of Occupational Exposure and
Environmental Releases for Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4
(Supplemental Engineering Report) ( !020d) for number of sites estimate). This resulted in
approximately 210 workers and 75 ONUs potentially exposed during repackaging of PCE (see Table
2-19).
Table 2-19. Estimated Number of Workers Potentially Exposed to PCE During Repackaging
Number
of Sites
Kxposed
Workers per
Nile
Kxposed
Occupational Non-
l sers per Site
Total
Kxposed
Workers"
Total Kxposed
Occupational Non-
l sers"
Total
Kxposcd"
51
4
1
210
75
280
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA assessed inhalation exposures during import/repackaging using identified monitoring data. Table
2-20 summarizes 15-min, 30-min, and 8-hr TWA results obtained from data submitted to EPA by Dow
Chemical under TSCA. (Dow Chem 1984). For the 8-hr TWA results the 95th percentile and 50th
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percentiles are presented as the high-end and central tendency exposure values, respectively. For the 15-
min TWA, only two data points were available; therefore, EPA presents two scenarios: 1) using the
maximum as a "higher value"; and 2) using the midpoint as a "midpoint value". For the 30-min TWA,
only five data points were available; therefore, the maximum is presented as the high-end and the
median is presented as the central tendency. It should be noted that two of the 30-min TWA samples
measured below the LOD (Dow Chem 1984). To estimate exposure concentrations for these data, EPA
followed the Guidelines for Statistical Analysis of Occupational Exposure Data (1994) as discussed in
Section 2.4.1.3. The geometric standard deviation for was above 3.0; therefore, EPA used the to
estimate the exposure value as specified in the guidelines (U.S. EPA. 1994b). Data were not available to
estimate ONU exposures; EPA estimates that ONU exposures are lower than worker exposures, since
ONUs do not typically directly handle the chemical. In lieu of ONU-specific data, EPA uses worker
central tendency exposure results as a surrogate to estimate exposures for ONUs.
Table 2-20. Summary of Inhalation Monitoring Data for Repackaging
Kxposure ('oncenlralion Type
W orker Kxposures
Nil m her
of
Samples
Occupational
Non-l ser
Data Quality
Uating of Air
Central
Tendency
(ppni)
lligli-
r.nd
(ppm)
Kxposures
(ppm)"
('oncenlralion
Dala
8-hr TWA Exposure Concentration
0.4
0.8
0.4
Acute Exposure Concentration (AC)
0.1
0.3
0.1
Average Daily Concentration (ADC)
9.9E-02
0.2
10
9.9E-02
Lifetime Average Daily
Concentration (LADC)
3.9E-02
9.6E-02
3.9E-02
Medium
15-min TWA Exposure
Concentration13
0.9
1.6
2
0.9
30-min TWA Exposure
Concentration
8.0E-02
5.7
5
8.0E-02
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
b Due to only two data points identified, EPA presents two scenarios: 1) using the higher of the two values; and 2) using the
midpoint of the two values.
Sources: (Dow Chem .1.984')
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure to workers is assessed using PCE personal breathing zone monitoring data collected at one
repackaging facility. The data were determined to have a "medium" confidence rating through EPA's
systematic review process. However, the data may not be representative of exposures across other
repackaging facilities (e.g., those repackaging from and into different container sizes than the used in the
identified data). Based on reasonably information above, EPA has a medium level of confidence in the
assessed worker exposure.
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Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.8 Processing as a Reactant
Worker Activities
At industrial facilities, workers are potentially exposed when unloading PCE from transport containers
into intermediate storage tanks and process vessels. Workers may be exposed via inhalation of vapor or
via dermal contact with liquids while connecting and disconnecting hoses and transfer lines. Once PCE
is unloaded into process vessels, it is consumed as a chemical intermediate.
ONUs are employees who work at the facilities that process and use PCE, but who do not directly
handle the material. ONUs may also be exposed to PCE but are expected to have lower inhalation
exposures and are not expected to have dermal exposures. ONUs for this condition of use may include
supervisors, managers, engineers, and other personnel in nearby production areas.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during processing
of PCE as a reactant using Bureau of Labor Statistics' OES data ("I ; S HI -S 2016) and the U.S. Census'
SUSB ( tisus Bureau 2015)as well as the primary NAICS and SIC code reported by each site in
the 2016 TRI or 2016 DMR, respectively (see the Assessment of Occupational Exposure and
Environmental Releases for Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4
(Supplemental Engineering Report) ("I ; S 1 T \ 2020d) for number of sites estimate). This resulted in
approximately 4,200 workers and 1,900 ONUs potentially exposed during processing of PCE as a
reactant (see Table 2-21).
Table 2-21. Estimated Number of Workers Potentially Exposed to PCE During Processing as a
Reactant
Number of
Sites
Kxposed
Workers per
Site
Kxposed Occupational
Non-l sers per Site
Total Kxposed
Workers"
Total
Kxposed
O.Mv1
Total
Kxposcd11
117
36
17
4,200
1,900
6,100
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA did not identify any inhalation monitoring data to assess exposures during processing PCE as a
reactant. EPA assumes that potential sources of exposure at sites using PCE as a reactant are similar to
sites manufacturing raw PCE. Therefore, EPA assessed inhalation exposures during processing PCE as a
reactant using monitoring data from manufacturing sites as a surrogate for sites processing PCE as a
reactant. The results from the surrogate inhalation monitoring data are provided in Table 2-22.
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Table 2-22. Summary of Inhalation Monitoring Results for Processing PCE as a Reactant"
Kxposure Concentration Type
Worker l.>
Central
Tendency
(ppm)
posurcs
High-
land
(ppm)
N il in her
of
Samples
Occupational
Non-l ser
Kxposurcs
(ppm )'*
Data Quality
Rating of Air
Concent rat ion
Data
8-hr TWA Exposure Concentration
3.3E-02
2.6
75°
3.3E-02
High
Acute Exposure Concentration (AC)
based on 8-hr TWA
1.1E-02
0.9
1.1E-02
Average Daily Concentration (ADC)
based on 8-hr TWA
7.4E-03
0.6
7.4E-03
Lifetime Average Daily Concentration
(LADC) based on 8-hr TWA
2.9E-03
0.3
2.9E-03
12-hr TWA Exposure Concentration
2.1E-02
0.2
77
2.1E-02
Acute Exposure Concentration (AC)
based on 12-hr TWA
1.0E-02
0.1
1.0E-02
Average Daily Concentration (ADC)
based on 12-hr TWA
7.0E-03
7.3E-02
7.0E-03
Lifetime Average Daily Concentration
(LADC) based on 12-hr TWA
2.8E-03
3.7E-02
2.8E-03
15-min TWA Exposure Concentration
2.0
15
161
2.0
30-min TWA Exposure Concentration
0.7
12
38d
0.7
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a These results are based on monitoring data from PCE manufacturing used as surrogate for sites processing PCE as a
reactant.
b EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
0 Data does not include 18 data points that were reported as being below the detection limit, but for which the company did
not provide the LOD for use in estimating an exposure value.
d Data does not include five data points that were reported as being below the detection limit, but for which the company did
not provide the LOD for use in estimating an exposure value.
Sources: (HSIA 2018a")
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure to workers is assessed using PCE personal breathing zone monitoring data collected at
facilities manufacturing PCE as a surrogate for facilities processing PCE as reactant. The data were
determined to have a "high" confidence rating through EPA's systematic review process. Although these
data are not directly applicable to processing of PCE as a reactant, EPA expects a high degree of overlap
of worker tasks at both manufacturing sites and sites processing PCE as a reactant. Based on this
expectation and the strength of the monitoring data, EPA has a medium to high level of confidence in
the assessed worker exposures.
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Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.9 Incorporation into Formulation, Mixture, or Reactant Product
Worker Activities
At formulation facilities, workers are potentially exposed when unloading PCE into mixing vessels,
taking QC samples, and packaging formulated products into containers and tank trucks. The exact
activities and associated level of exposure will differ depending on the degree of automation, presence
of engineering controls, and use of PPE at each facility.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during
formulation of PCE-containing products using Bureau of Labor Statistics' OES data ( )
and the U.S. Census' SUSB (V- S Census Bureau 2015) as well as the primary NAICS and SIC code
reported by each site in the 2016 TRI or 2016 DMR, respectively (see the Assessment of Occupational
Exposure and Environmental Releases for Per chloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN:
127-18-4 (Supplemental Engineering Report) ( )20d)for number of sites estimate). This
resulted in approximately 800 workers and 310 ONUs potentially exposed during formulation of PCE-
containing products (see Table 2-23).
Table 2-23. Estimated Number of Workers Potentially Exposed to PCE During Formulation
Number
of Sites
Kxposed
Workers per
Nile
Kxposed
Occupational Non-
l sers per Site
Total
Kxposed
Workers"
Total Kxposcd
Occupational Non-
l sers"
Total
Kxposcd"
39
21
8
800
310
1,100
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA identified inhalation exposure monitoring data related to the aerosol packing of PCE-containing
products (Orris and Daniels 1981). However, no monitoring data was identified for other formulation
sites and it is unlikely aerosol packing is representative of other formulation sites where workers are
exposed during unloading of bulk containers (i.e., tank trucks and rail cars) and loading of formulated
products into smaller containers (e.g., drums). Therefore, EPA used the monitoring data to assess
exposures at aerosol packing facilities and the EPA/OAQPS AP-42 Loading Model, EPA/OPPTMass
Balance Model and Monte Carlo analysis to assess exposures at other non-aerosol packing facilities.
Details of the model design and parameters is provided in Appendix F of the Assessment of
Occupational Exposure and Environmental Releases for Per chloroethylene (Ethene, 1,1,2,2,-
Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) ( ,020d).
Table 2-24 summarizes 8-hr TWA PBZ monitoring data for aerosol packing formulation sites. Due to
the limited number of data points (five), EPA used the maximum value as the high-end and the 50th
percentile as the central tendency. Data were not available to estimate short-term or ONU exposures;
EPA estimates that ONU exposures are lower than worker exposures, since ONUs do not typically
directly handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency exposure
results as a surrogate to estimate exposures for ONUs.
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3107
3108
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Table 2-24. Summary of Inhalation Exposure Monitoring Data for Aerosol Packing Formulation
Sites
Kxposurc Concentration Type
Work
Kxposi
Central
Tendency
(ppm)
ci-
rcs
High-
land
(ppm)
Nil in her
of
Sam pies
Occupational
Non-l scr
r.xposurcs
(ppm)"
Data Qualify
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration
8.3
13
5
8.3
High
Acute Exposure Concentration (AC)
2.8
4.4
2.8
Average Daily Concentration (ADC)
1.9
3.0
1.9
Lifetime Average Daily Concentration
(LADC)
0.8
1.5
0.8
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
Sources: (Orris and Daniels .1.98.1.1
The modeling approach used to assess exposures at non-aerosol packing formulation sites estimates
exposures to workers loading formulated PCE-based products into 55-gallon drums. Inhalation exposure
to chemical vapor during loading is a function of physical properties of PCE, various EPA default
constants, and other model parameters. While physical properties are fixed for a substance, some model
parameters, such as weight fraction of PCE in the product, ventilation rate, mixing factor, and vapor
saturation factor, are expected to vary from one facility to another. This approach addresses variability
for these parameters using a Monte Carlo analysis.
The modeling approach requires an input on the number of containers loaded per day which is
determined based on the throughput of PCE at each site and the weight fraction of PCE in the product.
To determine these values EPA divided each site identified in Section 2.2.1.2.2 into one of the following
categories: 1) sites formulating degreasing solvents; 2) sites formulating dry cleaning solvents, and 3)
sites formulating "miscellaneous" PCE-containing products, including coatings, adhesives,
metalworking fluids, and other niche use PCE-based products. The three categories were selected based
on available market data from HSIA (2008), where the first two categories (degreasing and dry cleaning
formulation) had market information indicating the percentage of the production volume used in those
types of products. The HSIA (2008) market data did not include detailed production volume data for the
third group so EPA could not divide the PCE production volume amongst the product types to calculate
per site throughputs. Therefore, EPA assessed as a single category.
Table 2-25 summarizes model results for workers at non-aerosol packing formulation sites with the 50th
percentile presented as the central tendency and the 95th percentile presented as the high-end. Data were
not available to incorporate ONU exposures into the model. EPA estimates that ONU exposures are
lower than worker exposures, since ONUs do not typically directly handle the chemical. In lieu of ONU-
specific data, EPA uses worker central tendency exposure results as a surrogate to estimate exposures
for ONUs.
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3126
3127 Table 2-25. Summary of Exposure Modeling Results for Formulation of PCE-Based Products
l''ormulalion
Type
Kxposure Concentration Type
Worker Kxposures
Occupational
Non-l ser
Kxposures
(ppm)"
Data Quality
Rating of Air
Concent ratio
n Data
Central
Tendency
(ppm)
lligli-
Knd
(ppm)
Degreasing
Solvent
8-hr TWA Exposure
Concentration
0.7
2.6
0.7
N/A-
modeled data
Acute Exposure Concentration
(AC)
0.1
0.4
0.1
Average Daily Concentration
(ADC)
1.6E-02
5.7E-02
1.6E-02
Lifetime Average Daily
Concentration (LADC)
2.3E-03
8.4E-03
2.3E-03
Dry Cleaning
Solvent
8-hr TWA Exposure
Concentration
4.0
14
4.0
Acute Exposure Concentration
(AC)
0.6
2.1
0.6
Average Daily Concentration
(ADC)
8.6E-02
0.3
8.6E-02
Lifetime Average Daily
Concentration (LADC)
1.3E-02
4.5E-02
1.3E-02
Miscellaneous
8-hr TWA Exposure
Concentration
0.4
1.4
0.4
Acute Exposure Concentration
(AC)
5.9E-02
0.2
5.9E-02
Average Daily Concentration
(ADC)
8.6E-03
3.1E-02
8.6E-03
Lifetime Average Daily
Concentration (LADC)
1.3E-03
4.5E-03
1.3E-03
3128 AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
3129 a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
3130 worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
3131 this value for ONUs is unknown.
3132
3133 Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
3134 Exposure to workers at aerosol packing formulation sites is assessed using PCE personal breathing zone
3135 monitoring data collected at workplaces directly applicable to this condition of use, and the data were
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determined to have a "high" confidence rating through EPA's systematic review process. Specifically,
the data were determined to be highly reliable, representative in geographic scope and reflective of
current operations. The source also provides metadata including sample type and sample duration. The
data includes exposure at a single aerosol packing facility. It is not known whether these data points
would also be representative of the worker exposure level at other similar facilities. Despite this
uncertainty, EPA has a high level of confidence in the assessed worker exposures based on the strength
of the monitoring data.
The EPA/OAQPS AP-42 Loading Model and EPA/OPPTMass Balance Model are used to estimate
worker exposures for non-aerosol packing facilities. The model uses a Monte Carlo analysis to
incorporate variability in the model input parameters. EPA believes the model exposures are likely to be
representative of worker exposure associated with loading 55-gallon drums. However, it assumes all
products are loaded into drums and does not consider the potential for loading of products into smaller
containers instead of or in addition to drums.
The model also does not consider worker exposure from unloading raw PCE from bulk containers (i.e.
tank trucks or railcars). Although EPA can estimate exposures during this unloading activity using the
Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model, it is unclear if
the same workers will perform both unloading and loading activities in the same day. Therefore, it may
not be accurate to combine estimates from each model to estimate a total exposure. In the case where a
worker is both unloading bulk containers and loading products into drums on the same day, the overall
error from not including exposures during unloading in the results is expected to be small as the Tank
Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model estimates an 8-hr
TWA exposure of 0.01 ppm for tank truck unloading and an 8-hr TWA of 0.04 ppm for railcar
unloading whereas the model for drum loading estimates 8-hr TWAs ranging from 0.60 to 14.1 ppm.
Furthermore, loading activities may be only a small part of the worker's day. The model does not
account for other potential sources of exposure at industrial facilities, such as sampling, equipment
cleaning, and other process activities that can contribute to a worker's overall 8-hr daily exposure. These
model uncertainties could result in an underestimate of the worker 8-hr exposure. Based on reasonably
available information above, EPA has a medium level of confidence in the assessed worker exposure.
Exposure to ONUs at both aerosol packing and non-aerosol packing facilities is assessed using the
worker central tendency exposure values from the respective facility types. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.10 Batch Open-Top Vapor Decreasing
Worker Activities
When operating OTVD, workers manually load or unload fabricated parts directly into or out of the
vapor cleaning zone. Worker exposure can occur from solvent dragout or vapor displacement when the
substrates enter or exit the equipment, respectively (Kanegsberg and Kanegsb ). The amount of
time a worker spends at the vapor degreaser can vary depending on the number of workloads needed to
be cleaned. Reports from NIOSH at three sites using OTVDs found degreaser operators may spend 0.5
to 2 hours per day at the degreaser (NIOSH 2002a. b, d).
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Worker exposure is also possible while charging new solvent or disposing spent solvent. The frequency
of solvent charging can vary greatly from site-to-site and is dependent on the type, size, and amount of
parts cleaned in the degreaser. NIOSH investigations found that one site added a 55-gallon drum of new
solvent to the degreaser unit everyone to two weeks; another site added one 55-gallon drum per month;
and another site added two 55-gallon drums per month to its large degreaser and three 55 gallon drums
per year to its small degreaser (NIOSH 2002a. b, d).
EPA defined ONU as an employee who does not regularly handle PCE or operate the degreaser but
performs work in the area around the degreaser.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during use of
PCE in OTVDs using the Draft ESD on the Use of Vapor Degreasers (OECD 2017a). The ESD
estimates seven workers and four ON Us per site (OECD 2017a). EPA multiplied these values by the
number of sites estimated in the Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report)
( 020d). This resulted in approximately 2,800 workers and 1,600 ON Us using the number of
sites estimated from the 95th percentile use-rate and 35,000 workers and 20,000 ONUs using the number
of sites estimated from the 50th percentile use-rate. Table 2-26 summarizes these results. Note: These are
bounding estimates and may overestimate actual number of workers.
Table 2-26. Estimated Number of Workers Potentially Exposed to PCE During Use in Open-Top
Vapor Degreasing
I se-Uate
Scenario
Number of
Sites
Kxposed
Workers
per Site
Kxposed
Occupational
Non-l sers per
Sile
Total
Kxposed
Workers"
Total Kxposcd
Occupational
Non-l sers"
Total
Kxposed"
95th
Percentile
398
7
4
2,800
1,600
4,400
50th
Percentile
4,942
7
4
35,000
20,000
54,000
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
Table 2-27 summarizes the 8-hr TWA monitoring data, 4-hr TWA monitoring data, and 15-minute
TWA monitoring data for the use of PCE in OTVDs. The high-end and central tendency values for the
8-hr TWA data represent the 95th and 50th percentile, respectively. Due to the limited number of data
points (three samples), the 4-hr TWA high-end is the maximum value and the central tendency is the
50th percentile. There is only a single 15-min TWA sample.
EPA recognizes that worker job titles and activities may vary significantly from site to site; therefore,
EPA typically identified samples as worker samples unless it was explicitly clear from the job title (e.g.,
inspectors) and the description of activities in the report that the employee was not operating the
degreaser during the sampling period. Samples from employees determined not to be operating the
degreasing equipment were designated as ONU samples.
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EPA identified inhalation exposure monitoring data from NIOSH investigations at five sites using PCE
as a degreasing solvent in OTVDs. Due to the large variety in shop types that may use PCE as a vapor
degreasing solvent, there is some uncertainty in how representative these data are of a "typical" shop.
Table 2-27. Summary of Worker Inhalation Exposure Monitoring Data for Open-Top Vapor
Degreasing
Kxposure
Concentration
Type
W orker Expo*
Central
Tendency
(ppm)
u res
High-
land
(ppm)
Nil m her
of
Worker
Samples
Occupational
I ser Kxposu
Central
Tendency
(ppm)
Non-
res
Nigh-
Em!
(ppm)
Nil m her
of OM
Samples
Data Quality
Rating of Air
Concent rat ion
Data
8-hr TWA
Exposure
Concentration
2.1
32
63
0.6
5.2
12
Medium to
High
Acute
Exposure
Concentration
(AC)
0.7
11
0.2
1.7
Average Daily
Concentration
(ADC)
0.5
7.3
0.1
1.2
Lifetime
Average Daily
Concentration
(LADC)
0.2
3.8
5.5E-02
0.6
15-min TWA
Exposure
Concentration
17
1
No 4-hr or 15-minute data
identified for ONUs
4-hr TWA
Exposure
Concentration
1.3
1.6
3
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
Source: (NIOSH 2002a. b, d; Gorman et at. .1.984: Ruhe 1982)
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using PCE personal breathing zone monitoring data from several different sources,
with confidence rating of the data ranging from "medium" to "high", as determined through EPA's
systematic review process. Due to the large variation amongst sites that operate OTVDs, there is some
uncertainty in how representative the monitoring data of typical shops. Despite this uncertainty, EPA has
a medium to high level of confidence in the assessed exposure for this condition of use, based on the
strength of the monitoring data.
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2.4.1.11 Batch Closed-Loop Vapor Decreasing
Worker Activities
For closed-loop vapor degreasing, worker activities can include placing or removing parts from the
basket, as well as general equipment maintenance. Workers can be exposed to residual vapor as the door
to the degreaser chamber opens after the cleaning cycle is completed. The amount of time workers spend
in the degreaser area can vary greatly by site. One NIOSH report (NIQSH. 2002c) reported workers
spent 1.5 to 2 hours per shift at the degreaser and another NIOSH report (NIOSH 2002a) indicating that
workers spent over 90% of their day in the degreaser area. Similarly, addition of fresh solvent to the
degreasing machine can vary significantly with one site indicating 50 gallons of PCE per month were
added and another site indicating 10 to 20 gallons of PCE per year were added to the machine (NIQSH.
2002a. c).
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during use of
PCE in closed-loop degreasing using the same methodology as described for OTVDs. This resulted in
approximately 97,000 workers and 56,000 ONUs using the number of sites estimated from the 95th
percentile use-rate and 180,000 workers and 100,000 ONUs using the number of sites estimated from
the 50th percentile use-rate (see the Assessment of Occupational Exposure and Environmental Releases
for Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering
Report) ( lOd) for number of sites estimate). Table 2-28 summarizes these results. Note:
These are bounding estimates and may overestimate actual number of workers.
Table 2-28. Estimated Number of Workers Potentially Exposed to PCE During Use in Closed-
Loop Vapor Degreasing
I se-Uale
Scenario
Number
of Sites
Kxposed
Workers
per Site
Kxposed
Occupational
Non-l sers
per Site
Total
Exposed
Workers"
Tolal Kxposcd
Occupational Non-
l sers"
Tolal
Kxposed"
95th
Percentile
13,912
7
4
97,000
56,000
150,000
50th
Percentile
25,546
7
4
180,000
100,000
280,000
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA identified inhalation exposure monitoring data from NIOSH investigations at two sites using PCE
as a degreasing solvent in batch closed-loop vapor degreasers. Due to the large variety in shop types that
may use PCE as a vapor degreasing solvent, it is unclear how representative these data are of a "typical"
shop. EPA does not have a model for estimating exposures from closed-loop degreasers; therefore, the
assessment is based on the identified monitoring data.
Worker samples were determined to be any sample taken on a person while performing the degreasing
tasks. ONUs samples were determined to be any sample taken on a person in the same location as the
degreaser but not performing the degreasing themselves.
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Table 2-29 summarizes the 8-hr TWA and 4-hr TWA monitoring data for the use of PCE in closed-loop
vapor degreasers. For workers, the 8-hr TWA high-end and central tendency are based on the 95th and
50th percentiles, respectively. Due to the limited data points for worker 4-hr TWAs, EPA used the
maximum and median as the high-end and central tendency, respectively. For ONUs, only two data
points were available; therefore, EPA presents two scenarios: 1) using the maximum as a "higher value,"
and 2) using the midpoint as a "midpoint value."
When comparing to monitoring data from OTVDs, the data show a decrease in worker exposure of
99.2% at the 95th percentile and 96.6% at the 50th percentile and a decrease in ONU exposure of 98.2%
at the 95th percentile and 89.2% at the 50th percentile. This is generally consistent with data in literature
which found that solvent purchases for closed-loop systems were reduced by 83% to over 98% as
compared to OTVDs and air emissions were reduced from 95% to over 99% as compared to OTVDs
(Purl I, fewmoa 2001).
Table 2-29. Summary of Worker Inhalation Exposure Monitoring Data for Closed-Loop Vapor
Degreasing
Kxposure
( oneoiHration Type
Worker !¦
(on (nil
Tendency
(ppm)
xposurcs
High-
land
(ppm)
Nil m her
of
Worker
Samples
Occupali<
I ser K\|
(en (nil
Tendency
(ppm)
nal Non-
)osures:i
lligli-
l.ml
(ppm)
N il in her
of ONI'
Samples
Data Qualify
Ualing of Air
(oncenl ration
Data
8-hr TWA Exposure
Concentration
7.2E-02
0.3
13
6.5E-02
9.6E-02
2
High
Acute Exposure
Concentration (AC)
2.4E-02
8.4E-02
2.2E-02
3.2E-02
Average Daily
Concentration (ADC)
1.6E-02
5.8E-02
1.5E-02
2.2E-02
Lifetime Average
Daily Concentration
(LADC)
6.6E-03
3.0E-02
5.9E-03
1.1E-02
4-hr TWA Exposure
Concentration
2.0E-02
8.6E-02
3
No 4-hr data identified for
ONUs
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a Due to only two data points identified, EPA presents two scenarios: 1) using the higher of the two values; and 2) using the
midpoint of the two values.
Source: fNIOSH 2002a. c)
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using PCE personal breathing zone monitoring data from two sources with the data
determined to have a "high" confidence rating, as determined through EPA's systematic review process.
The data show a decrease in exposure concentrations as compared to OTVD monitoring data that agrees
with literature expectations. Based on the reasonably available information above, EPA has a high level
of confidence in the assessed exposure for this condition of use.
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2.4.1.12 Conveyorized Vapor Decreasing
Worker Activities
For conveyorized vapor degreasing, worker activities can include placing or removing parts from the
basket, as well as general equipment maintenance. Depending on the level of enclosure and specific
conveyor design, workers can be exposed to vapor emitted from the inlet and outlet of the conveyor
portal.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during use of
PCE in conveyorized degreasing using the same methodology as described for OTVDs. This resulted in
approximately 2,800 workers and 1,600 ONUs using the number of sites estimated from the 95th
percentile use-rate and 4,000 workers and 2,300 ONUs using the number of sites estimated from the 50th
percentile use-rate (see the Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report)
( 020d) for number of sites estimate). Table 2-30 summarizes these results. Note: These are
bounding estimates and may overestimate actual number of workers.
Table 2-30. Estimated Number of Workers Potentially Exposed to PCE During Use in
Conveyorized Vapor Degreasing
I se-Uale
Scenario
Number of
Sites
Kxposed
Workers
per Site
Exposed
Occupational
Non-l sers
per Site
Total
Kxposed
Workers"
Total
Kxposed
Occupational
Non-l sers"
Tolal
Kxposed"
95th
Percentile
395
7
4
2,800
1,600
4,300
50th
Percentile
568
7
4
4,000
2,300
6,200
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA did not identify any inhalation exposure monitoring data related to the use of PCE in conveyorized
degreasing. Therefore, EPA assessed inhalation exposures during conveyorized degreasing using the
Conveyorized Degreasing Near-Field/Far-Field Inhalation Exposure Model. Details of the model design
and parameters is provided in Appendix G of the Assessment of Occupational Exposure and
Environmental Releases for Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4
(Supplemental Engineering Report) 0 ; S 1 T \ 2020d).
The key parameter in the model is the emission rate from the degreaser. Emission rates were modeled
using the reported unit emissions of PCE from the single conveyorized degreaser in the 2014 NEI (U.S.
EPA. 2018a). The model estimates exposures for both workers and ONUs. Workers estimates are based
on concentrations in the near-field where the conveyorized degreasing work occurs, and ONU exposures
are based on concentrations in the far-field away from the conveyorized degreaser. The results from the
inhalation model are provided in Table 2-31. The high-end and central tendency are the 95th and 50th
percentiles, respectively, calculated by the model.
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Table 2-31. Summary of Exposure Modeling Results for Use of PCE in Conveyorized Vapor
Degreasing
Kxposure Concentration Type
W orker K\|
Central
Tendency
(ppm)
)osurcs
lligli-
l.ml
(ppm)
Occupation
I ser Kxp<
Central
Tendency
(ppm)
al Non-
suits
High-
land
(ppm)
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure
Concentration
78
186
41
126
N/A - modeled
data
Acute Exposure Concentration
(AC)
26
62
14
42
Average Daily Concentration
(ADC)
18
42
9.3
29
Lifetime Average Daily
Concentration (LADC)
6.7
17
3.5
12
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using the Conveyorized Degreasing Near-Field/Far-Field Inhalation Exposure
Model. The model uses a Monte Carlo analysis, which incorporates variability in the model input
parameters. Only a single emission rate data point was available for PCE conveyorized degreasing for
use in the model and there is some uncertainty in how representative this data point is of a "typical"
conveyorized degreaser. Based on the reasonably available information above, EPA has a medium level
of confidence in the assessed exposure for this condition of use.
2.4.1.13 Web Degreasing
Worker Activities
Worker activities for web degreasing are expected to be similar to other degreasing uses and can include
placing or removing parts from the degreasing machine, as well as general equipment maintenance.
Depending on the level of enclosure and specific design, workers can be exposed to vapor emitted from
the inlet and outlet of the conveyor portal.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during use of
PCE in web degreasing using the same methodology as described for OTVDs. This resulted in
approximately 2,800 workers and 1,600 ONUs using the number of sites estimated from the 95th
percentile use-rate and 4,000 workers and 2,300 ONUs using the number of sites estimated from the 50th
percentile use-rate (see the Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report)
( 020d) for number of sites estimate). Table 2-32 summarizes these results. Note: These are
bounding estimates and may overestimate actual number of workers.
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Table 2-32. Estimated Number of Workers Potentially Exposed to PCE During Use in Web
Degreasing
I se-Uate
Scenario
Number of
Sites
Kxposed
Workers
per Site
Kxposed
Occupational
Non-l sers per
Site
Total
Kxposed
Workers"
Total Kxposcd
Occupational
Non-l sers"
Total
Kxposed"
95th
Percentile
395
7
4
2,800
1,600
4,300
50th
Percentile
568
7
4
4,000
2,300
6,200
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA did not identify any inhalation exposure monitoring data related to the use of PCE in web
degreasing. Therefore, EPA assessed inhalation exposures during web degreasing using the Web
Degreasing Near-Field/Far-Field Inhalation Exposure Model. Details of the model design and
parameters is provided in Appendix G of the Assessment of Occupational Exposure and Environmental
Releases for Per chloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental
Engineering Report) ( 320d).
The key parameter in the model is the emission rate from the degreaser. Emission rates were modeled
using the reported unit emissions of PCE from web degreasers in the 2014 NEI (U.S. EPA. 2018a). The
model estimates exposures for both workers and ONUs. Workers estimates are based on concentrations
in the near-field where the web degreasing work occurs, and ONU exposures are based on
concentrations in the far-field away from the web degreaser. The results from the inhalation model are
provided in Table 2-33. The high-end and central tendency are the 95th and 50th percentiles, respectively,
calculated by the model.
Table 2-33. Summary of Exposure Modeling Results for Use of PCE in Web Degreasing
Kxposurc Concentration Type
W orker Kx|
Central
Tendency
(ppm)
)osurcs
lligli-
Knd
(ppm)
Occupation
I ser Kxp<
Central
Tendency
(ppm)
al Non-
s ii res
lligli-
Knd
(ppm)
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure
Concentration
0.6
1.8
0.3
1.2
N/A - modeled
data
Acute Exposure Concentration
(AC)
0.2
0.6
0.1
0.4
Average Daily Concentration
(ADC)
0.1
0.4
7.3E-02
0.3
Lifetime Average Daily
Concentration (LADC)
5.3E-02
0.2
2.7E-02
0.1
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
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Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using the Web Degreasing Near-Field/Far-Field Inhalation Exposure Model. The
model uses a Monte Carlo analysis, which incorporates variability in the model input parameters. Due to
the limited number of data points, there is some uncertainty on the representativeness of emission rates
from the 2014 NEI (U.S. EPA. 2018a) of "typical" web degreasers. Based on the reasonably available
information above, EPA has a medium level of confidence in the assessed exposure for this condition of
use.
2.4.1.14 Cold Cleaning
Worker Activities
The general worker activities for cold cleaning include placing the parts that require cleaning into a
vessel. The vessel is usually something that will hold the parts but not the liquid solvent (i.e., a wire
basket). The vessel is then lowered into the machine, where the parts could be sprayed, and then
completely immersed in the solvent. After a short time, the vessel is removed from the solvent and
allowed to drip/air dry. Depending on the industry and/or company, these operations may be performed
manually (i.e., by hand) or mechanically. Sometimes parts require more extensive cleaning; in these
cases, additional operations are performed including directly spraying solvent on the part, agitation of
the solvent or parts, wipe cleaning and brushing (MOS1 \ 2(' ' i ,, v «« \ i ).
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during use of
PCE in cold cleaners using Bureau of Labor Statistics' OES data ( 1016) and the U.S. Census'
SUSB (I] S ("onsus Bureau 2015) as well as the NAICS code reported by the site in the 2014 NEI (see
the Assessment of Occupational Exposure and Environmental Releases for Perchloroethylene (Ethene,
1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) ( ,0d) for
number of sites estimate)(l 018a). In the 2014 NEI (U.S. EPA. 2018a). four sites reported
NAICS code for which there was no Census data available. To estimate the number of workers/ONUs at
these sites, EPA referenced the 2017 Emission Scenario Document (ESD) on the Use of Vapor
Degreasers (QEt O JO I j)12 There are approximately 710 workers and 420 ON Us potentially exposed
during use of PCE in cold cleaning (see Table 2-34).
It should be noted that this number is expected to underestimate the total number of workers and ONUs
exposed to PCE during cold cleaning as NEI data does not include cold cleaner operations that are
classified as area sources. Area sources are reported at the county level and do not include site-specific
information. Therefore, any sites operating a cold cleaning machine that is classified as an area source
would not be included in the count of sites in the 2014 NEI. EPA does not have sufficient information to
estimate the number of area sources that may operate cold cleaning machines.
12 Although the ESD covers vapor degreasers not cold cleaners, the types of industries using cold cleaners are assumed to be
similar to those using vapor degreasers. Therefore, the number of workers/ONUs are assumed to be similar.
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Table 2-34. Estimated Number of Workers Potentially Exposed to PCE During Use in Cold
Cleaning
Number
of Sites
Kxposed
Workers per
Site
Kxposed
Occupational Non-
l sers per Site
Total
Kxposed
Workers"
Total Kxposed
Occupational Non-
l sers"
Total
Kxposed"
17
42
25
710
420
1,100
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
Table 2-35 summarizes the 8-hr TWA and 4-hr TWA monitoring data for the use of PCE in cold
cleaners. For the 8-hr TWA, the 95th percentile and 50th percentile of the identified exposure data are
presented as the high-end and central tendency exposure values, respectively. Due to the limited number
of data points for the 4-hr TWA, the maximum and 50th percentile (median) of the data are presented as
the high-end and central tendency, respectively. The data were obtained from two sources: 1) aNIOSH
In-Depth Survey Report (NIQSH. 2002c); and 2) a study submitted to EPA by Vulcan Chemicals ( |)
under TSCA.
Worker samples were determined to be any sample taken on a person while performing the cold
cleaning tasks. ONUs samples were determined to be any sample taken on a person in the same location
as the cold cleaning machine but not performing the cold cleaning themselves. The results only include
values for workers as monitoring data for ONUs were not identified. EPA estimates that ONU exposures
are lower than worker exposures, since ONUs do not typically directly handle the chemical.
Table 2-35. Summary of Worker Inhalation Exposure Monitoring Data for Use of PCE in Cold
Cleaning
Kxposurc Concentration Type
Central
Tendency
(ppm)
High-
land
(ppm)
Number
of
Samples
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration
1.4
4.1
29
High
Acute Exposure Concentration (AC)
0.5
1.4
Average Daily Concentration (ADC)
0.3
0.9
Lifetime Average Daily Concentration
(LADC)
0.1
0.5
4-hr TWA Exposure Concentration
2.9
4.3
5
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
Source: fNIOSH 2002c: Vulcan 19941
Due to the large variety in shop types that may use PCE as a cold cleaning solvent, it is unclear how
representative these data are of a "typical" shop. Therefore, EPA supplemented the identified monitoring
data using the Cold Cleaning Near-Field/Far-Field Inhalation Exposure Model. Details of the model
design and parameters is provided in Appendix G of the Assessment of Occupational Exposure and
Environmental Releases for Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4
(Supplemental Engineering Report) ("I ; S 1 T \ 2020d). The results from the model are provided in
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Table 2-36. For model results, the high-end and central tendency are the 95th and 50th percentiles,
respectively.
The key parameter in the model is the emission rate from the cold cleaning machine. Emission rates
were modeled using a discrete distribution of reported cold cleaning machine unit emissions of PCE in
the 2014 NEI ( a). The model estimates exposures for both workers and ONUs. Workers
estimates are based on concentrations in the near-field where the cold cleaning work occurs, and ONU
exposures are based on concentrations in the far-field away from the cold cleaning machine.
The high-end results of the model are within the same order of magnitude as the high-end and central
tendency found in the monitoring data. However, the central tendency estimated by the model is three
orders of magnitude lower than the central tendency from the monitoring data. This may be due to the
limited number of sites from which the monitoring data were taken whereas the model is meant to
capture a broader range of scenarios.
Table 2-36. Summary of Exposure Modeling Results for Use of PCE in Cold Cleaning
W orker Kxposurcs
Occupational Non-
l ser Kxposurcs
Kxposurc Concentration Type
Central
Tendency
(ppm)
lligli-
Ind
(ppm)
Central
Tendency
(ppm)
lligli-
r.nd
(ppm)
8-hr TWA Exposure
Concentration
2.4E-03
1.5
1.2E-03
0.8
Acute Exposure Concentration
(AC)
8.0E-04
0.5
4.1E-04
0.3
Average Daily Concentration
(ADC)
5.5E-04
0.4
2.8E-04
0.2
Lifetime Average Daily
Concentration (LADC)
2.0E-04
0.1
1.1E-04
6.7E-02
Data Qualify
Rating of Air
Coiicenl ration
Data
N/A - modeled
data
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using PCE personal breathing zone monitoring data from two sources with the data
determined to have a "high" confidence rating, as determined through EPA's systematic review process.
The exposure data are supplemented with near-field/far-field exposure modeling using a Monte Carlo
analysis, which incorporates variability in the model input parameters. The high-end model results
generally agree with monitoring data high-end and central tendency. However, the central tendency
model results are three orders of magnitude lower than the monitoring data. This may be due to
uncertainty in the representativeness of the monitoring data of "typical" exposures from cold cleaning.
Based on the reasonably available information above, EPA has a medium to high level of confidence in
the assessed exposure for this condition of use.
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2.4.1.15 Aerosol Degreasing and Aerosol Lubricants
Worker Activities
PCE-based aerosol products include degreasers for applications such as brake cleaning, engine
degreasing, electric motor cleaners, cable cleaners, coil cleaners, and other metal product cleaning.
Additional aerosol products include penetrating lubricants and oils, high pressure non-melt red greases,
white lithium greases, silicone lubricants, chain and cable lubricants, vandal mark removers, mold
cleaners, and weld anti-spatter protectants. EPA expects significant overlap in the industry sectors that
use aerosol-based products; therefore, these uses are assessed together.
One example of a commercial setting with aerosol degreasing operations is repair shops, where service
items are cleaned to remove any contaminants that would otherwise compromise the service item's
operation. Internal components may be cleaned in place or removed from the service item, cleaned, and
then re-installed once dry (U.S. EPA 2014a).
Workers at these facilities are expected to be exposed through dermal contact with and inhalation of
mists during application of the aerosol product to the service item. ONUs are expected to have lower
inhalation exposures and are not expected to have dermal exposures.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed to aerosol
degreasers and aerosol lubricants containing PCE using Bureau of Labor Statistics' OES data (U.S. BLS
2016) and the U.S. Census' SUSB (U. S. Census Bureau 2015) (see the Assessment of Occupational
Exposure and Environmental Releases for Per chloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN:
127-18-4 (Supplemental Engineering Report) (U.S. EPA 2020d) for number of sites estimate). Based on
the market penetration of 29.6% and data from the BLS and U.S. Census, there are approximately
250,000 workers and 29,000 occupational non-users potentially exposed to PCE as an aerosol
degreasing solvent or aerosol lubricant (see Table 2-37) (U.S. BLS 2016; U. S. Census Bureau 2015;
CARB 2000).
Table 2-37. Estimated Number of Workers Potentially Exposed to PCE During Use of Aerosol
Degreasers and Aerosol Lubricants
Number
of Sites
Exposed
Workers per
Site
Exposed
Occupational Non-
Users per Site3
Total
Exposed
Workersb
Total Exposed
Occupational Non-
Users1'
Total
Exposedb
75,938
3
0.4
250,000
29,000
280,000
a Number of workers and occupational non-users per site are calculated by dividing the exposed number of workers or
occupational non-users by the number of establishments. The number of workers per site is rounded to the nearest integer.
The number of occupational non-users per site is shown as 0.4, as it rounds down to zero.
b Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA identified inhalation exposure monitoring data related to the use of PCE in aerosol degreasers for
brake servicing. However, PCE is used in a variety of other aerosol degreasing applications and other
aerosol products for which EPA did not identify any inhalation exposure monitoring data. Therefore,
EPA supplemented the identified monitoring data using the Brake Servicing Near-Field/Far-Field
Inhalation Exposure Model. EPA used the brake servicing model as a representative scenario for this
condition of use as there was ample data describing the brake servicing use and it is a significant use of
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PCE-based aerosol products. Details of the model design and parameters is provided in Appendix H of
the Assessment of Occupational Exposure and Environmental Releases for Perchloroethylene (Ethene,
1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) (U.S. EPA. 2020d).
Table 2-38 summarizes 8-hr TWA PBZ monitoring data and 15-min TWA PBZ monitoring data for the
use of PCE-based aerosol products. The 95th percentile of the identified monitoring data is presented as
the high-end exposure and the 50th percentile is presented as the central tendency. The data were
obtained from three studies on the use of aerosol brake cleaners during commercial brake servicing and
from data provided to EPA from the Department of Defense (DoD) (US OOP and Environmental
Health Readiness System - Industrial 2018; Cosgrove and Hygiene l I, l , l _) It should
be noted that one study evaluated various formulations of aerosol degreasers containing 25% PCE, and
another study evaluated one formulation containing 30% PCE, and one with 60% PCE. Based on data
from CARB ( >00) and modeling results, PCE concentration in brake cleaning products ranges
from 20%) to 99% with a median concentration of 78.4%. The monitoring data collected in these two
studies may underestimate "typical" exposures as the PCE concentration in the evaluated formulations
were all below the median concentration.
Worker samples were determined to be any sample taken on a person while performing the aerosol
degreasing tasks. ONUs samples were determined to be any sample taken on a person in the same
location as the aerosol degreasing but not performing the aerosol degreasing themselves. The results
only include values for workers as monitoring data for ONUs were not identified.
Table 2-38. Summary of Worker Inhalation Exposure Monitoring Data for Aerosol Degreasing
Kxposure Concentration Type
Central
Tendency
(ppm)
High-
land
(ppm)
N il in her
of
Samples
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration
1.4
7.8
Acute Exposure Concentration (AC)
0.5
2.6
Average Daily Concentration (ADC)
0.3
1.8
130
High
Lifetime Average Daily Concentration
(LADC)
0.1
0.9
15-min TWA Exposure Concentration
29
123
67
AC = Acute Concentration; ADC = Average Daily Concentration and LADC = Lifetime Average Daily Concentration.
Source: (U.S. DOD and Environmental Health Readiness System - Industrial 20.1.8; Cosgrove and Hygiene .1.994; Vulcan
.1.993. 1992)
Key model inputs include number of aerosol applications per job, the amount of degreaser applied per
brake job, and the concentration (weight fraction) of PCE in the aerosol degreaser. The values and
distributions for these inputs are largely based on site data from maintenance and auto repair shops
obtained by CARB (2000) for brake cleaning activities. The model estimates exposures for both workers
and ONUs. Workers estimates are based on concentrations in the near-field where the aerosol
degreasing work occurs, and ONU exposures are based on concentrations in the far-field away from the
aerosol degreasing applications.
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The results from model are provided in Table 2-39. It calculates both 8-hr TWA exposure concentrations
and maximum 1-hr TWA exposure concentrations. The high-end and central tendency are the 95th and
50th percentiles, respectively, calculated by the model. The model exposure levels at both the central
tendency and high-end for workers are higher than that found in the monitoring data but are within one
order of magnitude of the monitoring data. The discrepancy is not unexpected as the model is meant to
capture a wider range of shop conditions than is found in the monitoring data and the monitoring data
includes data for sites using brake cleaning formulations containing concentrations less than the median
concentration (78.4%) used in the model.
Table 2-39. Summary of Exposure Modeling Results for Use of PCE in Aerosol Degreasing and
Aerosol Lubricants
Kxposure Concentration Type
W orker Kx|
Central
Tendency
(ppm)
losures
High-
land
(ppm)
Occu patio
I ser l.x|
Central
Tendency
(ppm)
mil Non-
os ii res
High-
land
(ppm)
Data Quality
Rating of Air
Concent rat ion
Data
8-hr TWA Exposure
Concentration
5.5
17
0.1
0.7
N/A - modeled
data
Acute Exposure Concentration
(AC)
1.8
5.7
3.4E-02
0.2
Average Daily Concentration
(ADC)
1.3
3.9
2.0E-02
0.2
Lifetime Average Daily
Concentration (LADC)
0.5
1.6
1.0E-02
7.0E-02
Maximum 1-hr TWA Exposure
Concentration
17
50
0.3
2.2
AC = Acute Concentration; ADC = Average Daily Concentration and LADC = Lifetime Average Daily Concentration.
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using PCE personal breathing zone monitoring data from several different sources,
with confidence ratings of "high", as determined through EPA's systematic review process. The
exposure data are supplemented with near-field/far-field exposure modeling using a Monte Carlo
analysis, which incorporates variability in the model input parameters. Model results are generally
higher than monitoring data; however, the monitoring data includes data from three sources that had
concentrations of PCE in the aerosol formulation below the median value predicted by the model. Based
on the reasonably available information above, EPA has a high level of confidence in the assessed
exposure for this condition of use.
2.4.1.16 Dry Cleaning and Spot Cleaning
Worker Activities
Worker activities at dry cleaning shops can include:
• Receiving garments and tagging garments for identification;
• Inspecting and sorting garments by color, weight, finish;
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• Pre-treating any visible stain on the garment with a spotter, typically from a spray or squeeze
bottle;
• Loading garments into the machine, running the wash cycle, and unloading the cleaned
garments;
• Post-spotting any stain that was not already removed during the dry cleaning process; and
• Pressing and finishing, after which the pressed garment is returned to an overhead rack and
wrapped in plastic for customer pickup (NIOSH 1997a).
EPA expects worker exposure at dry cleaning facilities to primarily occur when workers are: 1)
unloading and loading garments from the machines; 2) performing manual stain removal (i.e., spot
cleaning); and 3) transferring solvent from a storage container to the machine. Workers can also be
exposed during maintenance activities, such as cleaning the machine lint trap, button trap and still,
changing solvent filters, and disposing hazardous wastes. However, these maintenance activities occur
on a much less frequent basis (NIOSH 1997a).
ONUs at dry cleaning facilities are employees who are not expected to handle PCE, operate dry cleaning
machines, or perform spotting or finishing operations. They include cashiers, counter clerks and other
similar employees.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed to PCE at dry
cleaners using Bureau of Labor Statistics' OES data (U.S. BLS 2016) and the U.S. Census' SUSB (U. S.
Census Bureau 2015). Based on a market penetration of 60% for commercial facilities, assuming 12
industrial dry cleaners (see the Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report)
(U.S. EPA 2020d) for number of sites estimate), and data from the BLS and U.S. Census, there are
approximately 44,000 workers and 14,000 occupational non-users potentially exposed to PCE at dry
cleaning facilities (see Table 2-40) (DLI/NCA 2017; U.S. BLS 2016; U. S. Census Bureau 2015; U.S.
EPA 2006b).
Table 2-40. Estimated Number of Workers Potentially Exposed to PCE During Dry Cleaning
Number
of Sites
Exposed
Workers per
Site
Exposed
Occupational Non-
Users per Site
Total
Exposed
Workers3
Total Exposed
Occupational Non-
Users3
Total
Exposed3
12,834
3
1
44,000
14,000
57,000
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
Table 2-41 summarizes the 8-hr TWA PBZ monitoring data for workers and ONUs at dry cleaners
obtained from OSHA facility inspections, NIOSH studies and data provided to EPA from DoD (U.S.
POD and Environmental Health Readiness System - Industrial 2018; OSHA 2017; Burroughs 2000;
NIOSH 2000; Burroughs 1999a. b; NIOSH 1995). The data are divided into two categories: 1) statistics
for data collected after the promulgation of the 2006 PCE NESHAP for Dry Cleaning Facilities; and 2)
data collected for fourth or fifth generation machines only. The post-2006 NESHAP data are expected to
contain exposures from shops using third, fourth and fifth generation machines as the purchase of new
first generation (transfer machines) and second generation (dry-to-dry, vented machines) dry cleaning
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machines were banned in the 1993 Perchloroethylene NESHAP for Dry Cleaning Facilities, the 2006
Perchloroethylene NESHAP for Dry Cleaning Facilities banned the use of PCE in all first-generation
machines, and the typical useful life of these machines is approximately 15 years ( 06b).
Third generation equipment are non-vented, dry-to-dry machines with refrigerated condensers. These
machines are essentially closed systems and are only open to the atmosphere when the machine door is
opened. In third generation machines, heated drying air is recirculated back to the drying drum through a
vapor recovery system CNIQSH. 1997b).
Fourth generation dry cleaning equipment are essentially third-generation machines with added
secondary vapor control. These machines "rely on both a refrigerated condenser and carbon adsorbent to
reduce the PCE concentration at the cylinder outlet below 300 ppm at the end of the dry cycle" and are
more effective at recovering solvent vapors CNIQSH. 1997b). Fifth generation equipment have the same
features as fourth generation machines, but also have a monitor inside the machine drum and an
interlocking system to ensure that the concentration is below approximately 300 ppm before the loading
door can be opened (NIOSH 1997b).
For workers, the 95th percentile is presented as the high-end and the 50th percentile is presented as the
central tendency. For the post-2006 NESHAP data, only a single data point was available for ONUs. For
fourth and fifth generation machines, there was only four ONU data points available; therefore, the
maximum is presented as the high-end and the median as the central tendency.
Approximately 28% of respondents to a 2003 survey of California dry cleaners indicated they used
fourth generation machines and approximately 61% of respondents to a 2010 survey of dry cleaners in
King County, WA reported using fourth or fifth generation machines CWhittaker and Joh an son 1 I;
California Air Resources 2006). EPA did not identify data for other locales or for the overall U.S.;
therefore, EPA used the California and King County, WA data to approximate the overall U.S. trends.
Based on these survey results, EPA expects the industry to be trending towards higher usage of fourth
and fifth generation machines as compared to third generation machines and expects current exposures
at dry cleaning shops to fall somewhere between the post-2006 exposure concentrations and the
concentrations from fourth and fifth generation machines only.
Worker samples were determined to be any sample taken on a person who engages in loading/unloading
clothes from dry cleaning equipment, finishing operations, spot cleaning, and/or maintenance activities
for the dry cleaning machine (e.g., replenishing spent solvent). ONUs samples were determined to be
any sample taken on a person not expected to perform these activities (e.g., cashiers).
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3668 Table 2-41. Summary of In
lalation Exposure Monitoring Data for Dry Cleaning
Data
Exposure
Concentratio
n Type
Worker
Exposures
Number
of
Occupational
Non-User
Exposures
Number
ofONU
Samples
Data
Quality
Rating of
Category
Central
Tendency
(ppm)
High-
End
(ppm)
Worker
Samples
Central
Tendency
(ppm)
High-
End
(ppm)
Air
Concentrati
on Data
8-hr TWA
Exposure
Concentration
3.6
20
0.3
C
Acute
Exposure
Concentration
(AC)
1.2
6.5
21
0.1
0.1
ld
Post-2006
NESHAP
Data3
Average Daily
Concentration
(ADC)
0.9
5.2
8.2E-02
9.3E-02
High
Lifetime
Average Daily
Concentration
(LADC)
0.3
2.7
3.3E-02
4.8E-02
15-min TWA
Exposure
Concentration
33
94
9
No 15-min data identified for
ONUs
8-hr TWA
Exposure
Concentration
1.0
5.6
1.4E-02
0.1
Fourth and
Acute
Exposure
Concentration
(AC)
0.3
1.9
114
4.7E-03
4.1E-02
4
Fifth
Generatio
n
Statistics13
Average Daily
Concentration
(ADC)
0.2
1.5
3.3E-03
3.3E-02
High
Lifetime
Average Daily
Concentration
(LADC)
9.2E-02
0.8
1.3E-03
1.7E-02
15-min TWA
Exposure
Concentration
48
899
6
No 15-min data identified for
ONUs
3669 AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
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a Post-2006 NESHAP data are air samples collected from OSHA inspections or DoD and, based on the date of collection,
EPA assumed to be representative of the post-2006 mix of machine types as provided in the 2010 King County, WA survey
(Whittaker and Jofaanson 20.1. D.
b Fourth and fifth generation data include only data where EPA could clearly identify the machine type in the study as fourth
or fifth generation. It does not include OSHA data, which are representative of a mix of machine generations but for which
machine types for individual samples could not be determined.
0 Only one data point was available for this scenario. However, different parameters are used for calculating high-end and
central tendency ADC and LADC. Therefore, a high-end and central tendency are presented based on the single data point.
d The single ONU data point comes from a sample taken on an inspector at a dry cleaning site. EPA assumes exposures to the
inspector would be similar to that of an ONU as inspectors are not expected to handle the chemical or operator dry cleaning
machines.
Source: (U.S. DOD and Environmental Health Readiness System - Industrial 20.1.8: OSHA 20.1.7: Burroughs 2000: NIOSH
2000: Burroughs 1999a. b; NIOSH 1995)
As estimated in Section 2.2.1.2.2, PCE is expected to be used in thousands of dry cleaning shops
throughout the U.S. and the monitoring data only captures a small fraction of those shops. Therefore,
EPA supplemented the identified monitoring data using the Dry cleaning Multi-Zone Inhalation
Exposure Model to capture variation amongst dry cleaning shops that may not be captured in the
monitoring data. Details of the model design and parameters are provided in Appendix I of Assessment
of Occupational Exposure and Environmental Releases for Perchloroethylene (Ethene, 1,1,2,2,-
Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) ( 020d).
Key model input parameters include solvent in concentration in the dry cleaning machine after the clean
cycle has complete, residual solvent in clothing removed from the dry cleaning machine, and spot
cleaning use rates. The value and distribution used for each of these parameters in the model are based
on data observed in literature. The model estimates exposures for workers, spot cleaners, and ONUs.
Workers estimates are based on concentrations in the near-field zone corresponding to unloading clothes
from the dry cleaning equipment and the near-field zone corresponding to where finishing and pressing
activities occur. Spot cleaner estimates are based on concentrations in the near-field zone corresponding
to where the spot cleaning activity occurs. ONU exposures are based on concentrations in the far-field
which corresponds to any area outside the near-field zones. The results from the model are provided in
Table 2-42. The high-end and central tendency are the 95th and 50th percentiles, respectively, calculated
by the model. It should be noted that the model calculates 12-hr TWAs based on suggestions from the
peer review of the 2016 Draft Risk Assessment for the TSCA Work Plan Chemical 1-Bromopropane
that dry cleaning workers may work up to 12 hours per day ( ).
It should be noted that EPA did not identify information to estimate the use rate of PCE in spot cleaners;
however, IRTA (2007) and ERG (2005) indicate that the use of PCE in spot cleaners is minimal.
Specifically, IRTA (2007) state that only 150 gal of PCE -based spotting agents are used annually in
California (compared to 42,000 gal of PCE -based spotting agents). ERG (2005) stated that many PCE
spotting agents are categorized as oily type paint removers (OTPR), but that the majority of OTPR
spotting agents contain no PCE. Therefore, EPA set the use rate of PCE spotting agents to zero causing
the spotting zone of the model to become part of the far-field with exposure concentrations equivalent to
ONUs.
When comparing the model results to the post-2006 NESHAP monitoring data results for workers, the
model high-end is higher than the monitoring data. This is likely because the model is meant to capture a
wider range of conditions than is likely captured in the monitoring data. The model central tendency for
workers is slightly less than half the central tendency for the post-2006 NESHAP monitoring data. This
may be due to the fact the majority of the post-2006 NESHAP data are from OSHA compliance
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inspections that are often performed as a result of worker complaints and, therefore, may not necessarily
be representative of PCE concentrations encountered in the typical commercial dry cleaning
establishment. Additionally, the assumption that post-2006 NESHAP data is representative of the 2010
King County, WA survey results may be inaccurate, and the data could actually represent sites with a
higher frequency of third generation machines, resulting in higher exposures. However, model results
and monitoring data for the post-2006 NESHAP are within the same order of magnitude.
When comparing the model results to the fourth/fifth generation monitoring data results for workers, the
model high-end and central tendency are both an order of magnitude greater than the monitoring data.
This is expected as the model captures exposures from facilities with third and fourth/fifth generation
machines.
Table 2-42. Summary of Worker and Occupational Non-Uses Inhalation Exposure Modeling
Results for Dry Cleaning
Kxposure ('oncenlralion Type
W orker K\|
(en (ml
Tendency
(ppm)
)osurcs
lligli-
Ind
(ppm)
Occupation
I ser Kxp<
Ccnlral
Tendency
(ppm)
al Non-
suits
High-
land
(ppm)
Data Qualify
Rating of Air
('oncenlralion
Dala
8-hr TWA Exposure
Concentration
1.4
30
0.1
1.5
N/A - modeled
data
Acute Exposure Concentration
(AC)
0.7
15
5.4E-02
0.8
Average Daily Concentration
(ADC)
0.5
10
3.8E-02
0.6
Lifetime Average Daily
Concentration (LADC)
0.2
4.1
1.4E-02
0.2
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using PCE personal breathing zone monitoring data from several different sources,
with confidence ratings of "high", as determined through EPA's systematic review process. The
exposure data are supplemented with multi-zone exposure modeling using a Monte Carlo analysis,
which incorporates variability in the model input parameters. This model was peer reviewed as part of
the 2016 1-BP draft Risk Assessment ( 16f) has been updated to address peer review
comments, incorporate additional available data, and use PCE-relevant data. Although the model results
differ from the monitoring data, they are the same order of magnitude as the post-2006 NESHAP data.
The model results are higher than the fourth and fifth generation machine monitoring data which is
expected as the model incorporates third generation machines. Based on the reasonably available
information above, EPA has a high level of confidence in the assessed exposure for this condition of
use.
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2.4.1.17 Adhesives, Sealants, Paints, and Coatings
Worker Activities
Worker activities may include unloading adhesive or coating products from containers into application
equipment, and, where used, manual application of the adhesive or coatings (e.g., use of spray guns or
brushes to apply product to substrate) (OECD 2015). Workers may be exposed to PCE during the
application process if mists are generated such as during spray and roll applications (OECD 2015).
Workers may also be exposed to PCE vapors that evaporate from the adhesive or coating as it is applied
or during the drying/curing process (OECD 2015). EPA expects ONUs may be exposed to mists or
vapors that enter their breathing zone during routine work in areas where coating applications are
occurring.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during use of
PCE-containing adhesives and coatings using Bureau of Labor Statistics' OES data (U.S. BLS 2016)
and the U.S. Census' SUSB (U. S. Census Bureau 2015) as well as the NAICS code reported by sites in
the 2014 NEI (see the Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report)
(U.S. EPA 2020d) for number of sites estimate) (U.S. EPA 2018a). In the 2014 NEI, there were two
sites with coating operations that reported a NAICS code for which no Census data were available. To
estimate the number of workers and ONUs at these sites, EPA used the average workers per site and
ONUs per site from the sites with known data. There are approximately 410 workers and 160 ONUs
potentially exposed during use of adhesives/sealants and 1,900 workers and 1,100 ONUs potentially
exposed during use of paints/coatings (see Table 2-43).
Table 2-43. Estimated Number of Workers Potentially Exposed to PCE During of Use Adhesives,
Sealants, Paints, and Coatings
Scenario
Number
of Sites
Exposed
Workers
per Site
Exposed
Occupational
Non-Users per
Site
Total
Exposed
Workers3
Total Exposed
Occupational
Non-Usersa
Total
Exposed3
Adhesives/Sealants
14
30
11
410
160
570
Paints/Coatings
46
41
24
1,900
1,100
3,000
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA identified inhalation exposure monitoring data from a study at a single site in Poland using a PCE-
based adhesive, from three NIOSH investigations at three sites using PCE-based coatings, a study
submitted to EPA under TSCA for a truck plant using PCE-based coatings, and data provided to EPA
from DoD for spray coating processes (U.S. POD and Environmental Health Readiness System -
Industrial 2018; Gromiec et al. 2002; Hanlev 1993; Stephenson and Albrecht 1986; Chrostek and Levine
1981; Ford Motor 1981). Due to the large variety in shop types that may use PCE-based adhesives and
coatings, it is unclear how representative these data are of a "typical" site using these products.
However, EPA does not have a model for estimating exposures from use of adhesives or paints/coatings;
therefore, the assessment is based on the identified monitoring data. Table 2-44 summarizes the
identified monitoring data.
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Worker samples were determined to be any sample taken on a person while performing adhesive or
coating applications. ONUs samples were determined to be any sample taken on a person in the same
location as the applications but not performing the adhesive/coating application themselves. The results
only include values for workers as monitoring data for ONUs were not identified. EPA estimates that
ONU exposures are lower than worker exposures, since ONUs do not typically directly handle the
chemical. In lieu of ONU-specific data, EPA uses worker central tendency exposure results as a
surrogate to estimate exposures for ONUs.
For adhesives, the study did not provide discrete sample results; therefore, the high-end exposure value
is based on the max concentration and the central tendency is based on the mean reported in the study
(Gromiec et al. 2002). For paints/coatings 8-hr TWA, the 95th percentile of the data is presented as the
high-end and the 50th percentile as the central tendency. Due to the limited number of data points for the
15-minute TWA, the maximum is presented as the high-end and the median is the central tendency.
Table 2-44. Summary of Inhalation Exposure Monitoring Data for Use of PCE-Based Adhesives,
Sealants, Paints, and Coatings
Scenario
Kxposure Concent ration
Type
W'orl
K \ pos
Central
Tendency
(ppni)
;er
ires
High-
land
(ppm)
N il in her
of
Samples
Occupational
Non-l ser
Kx pos ii res
(ppm)11
Data Quality
Rating of Air
Concentration
Data
Adhesives/
Sealants
8-hr TWA Exposure
Concentration13
8.8E-02
0.8
13
8.8E-02
Medium
Acute Exposure
Concentration (AC)
2.9E-02
0.3
2.9E-02
Average Daily
Concentration (ADC)
2.0E-02
0.2
2.0E-02
Lifetime Average Daily
Concentration (LADC)
8.0E-03
9.5E-
02
8.0E-03
Paints/
Coatings
8-hr TWA Exposure
Concentration
0.2
4.6
15
0.2
Medium to
High
Acute Exposure
Concentration (AC)
7.8E-02
1.5
7.8E-02
Average Daily
Concentration (ADC)
5.3E-02
1.0
5.3E-02
Lifetime Average Daily
Concentration (LADC)
2.1E-02
0.5
2.1E-02
15-min TWA Exposure
Concentration
4.1
7.9
5
4.1
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
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a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
b Exact sample times not given in study; however, study indicates that samples were taken for a minimum of 75% of the shift
(360 min). Therefore, EPA assumes that the results are representative of an 8-hr TWA exposure.
Source: (U.S. POD and Environmental Health Readiness System - Industrial 20.1.8: Gromiec et at. 2002: Hanlev .1.993:
Stephenson and Albrecht .1.986; Chrostek and Levine .1.981; Ford Motor 1981)
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure to workers is assessed using PCE personal breathing zone monitoring data from several
different sources, with confidence rating of the data ranging from medium to high, as determined
through EPA's systematic review process. Due to potential variations in the types of sites that may use
PCE-based adhesives, sealants, paints, and coatings, there is some uncertainty in how representative the
monitoring data are of other sites using these types of products. Despite this uncertainty, EPA has a
medium level of confidence in the assessed worker exposure for this condition of use.
Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.18 Maskant for Chemical Milling
Worker Activities
Information from stakeholder meetings and public comments indicate that in typical maskant application
processes the potential for exposure is low as the process is automated and performed in a dedicated
room (Ducommun 2017; Spirit Aero Systems 2017; Tech Met 2017). However, at least one stakeholder
indicated that employees may be exposed during maintenance operations (Spirit Aero Systems 2017).
Specific maintenance activities were not described but may include adding fresh maskant and handling
of re-captured maskants.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during use of
PCE as a chemical maskant using Bureau of Labor Statistics' OES data ( 016) and the U.S.
Census' SUSB (1; S ('ensus Bureau 2015) as well as the primary NAICS and SIC code reported by
sites in the 2016 TRI, 2016 DMR, and/or the 2014 NEI (see the Assessment of Occupational Exposure
and Environmental Releasesfor Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4
(Supplemental Engineering Report) ( ,020d) for number of sites estimate).
The data from the 2016 TRI, 2016 DMR, and 2014 NEI only covers 28 unique sites; however, market
data from ACP indicates there are up to 71 sites using PCE-based maskants (Products 2017). To
estimate the number of workers and ONUs at the remaining sites EPA calculated the average number of
workers and ONUs per site from the 28 known sites. This resulted in 95 workers per site and 75 ONUs
per site at the unknown sites and a total of approximately 6,700 workers and 5,300 ONUs potentially
exposed during maskant uses of PCE (see Table 2-45).
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Table 2-45. Estimated Number of Workers Potentially Exposed to PCE During Use of Chemical
Maskants
Number
of Sites
Kxposed
Workers per
Site
Kxposed
Occupational Non-
l sers per Site
Total
Kxposed
Workers"
Total Kxposed
Occupational Non-
l sers"
Total
Kxposed"
71
94
75
6,700
5,300
12,000
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA identified inhalation exposure monitoring data from a single NIOSH investigation at an aircraft
parts manufacturing site using a dip coating application process for the maskants (Hervin et 7).
The NIOSH report does not specify if PCE is the primary solvent in the maskant, the concentration of
PCE in the maskant, or the typical maskant use rates at the site. The identified monitoring data also
included 15-min TWA samples collected by the DoD between July 2013 and May 2017 during masking
activities (1; S OOP rind Environmental Health Readiness System - Industrial 2018). The DoD data
contained nine samples that were measured below the LOD ( id Environmental Health
Readiness System - Industrial 2018). To estimate exposure concentrations for data below the LOD, EPA
followed the Guidelines for Statistical Analysis of Occupational Exposure Data ( 4b) as
discussed in Section 1.4.5.2. The geometric standard deviation for the data was above 3.0; therefore,
EPA used the to estimate the exposure value as specified in the guidelines ( b).
Due to uncertainty in worker activities for chemical milling operations, EPA typically identified samples
as worker samples unless it was explicitly clear from the job title and the description of activities in the
report that the employee was not working with the maskant chemicals during the sampling period.
Samples from employees determined not to be working with the maskant chemicals were designated as
ONU samples. The results only include values for workers as monitoring data for ONUs were not
identified. EPA estimates that ONU exposures are lower than worker exposures, since ONUs do not
typically directly handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency
exposure results as a surrogate to estimate exposures for ONUs.
Due to the variety in both industry types and typical per site maskant use rates and the uncertainty of the
PCE concentration in the maskant, it is unclear if these data are representative of a "typical" site.
Additionally, the 8-hr and 4-hr data were collected prior to the promulgation of the Aerospace
Manufacturing and Rework Facilities NESHAP which regulates the emissions of hazardous air
pollutants (HAPs) from various operation at aerospace facilities including chemical milling. To the
extent that this NESHAP reduces emissions of PCE into the workroom worker exposures may be lower
than identified data. EPA does not have a model for estimating exposures from maskant uses; therefore,
the assessment is based on the identified monitoring data. Table 2-46 summarizes the 8-hr, 4-hr, and 15-
min TWA monitoring data for the use of PCE in maskants. The 95th percentile of the data is presented as
the high-end and the 50th percentile as the central tendency.
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Table 2-46. Summary of Inhalation Exposure Monitoring Data for Chemical Maskants
Kxposurc Concent ration Type
Work
Kxposi
Central
Tendency
(ppm)
ci-
rcs
High-
land
(ppm)
Nil m her
of
Sam pies
Occupational
Non-l scs
Kxposurcs
(ppm)11
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration
1.2
2.1
24
1.2
High
Acute Exposure Concentration (AC)
0.4
0.7
0.4
Average Daily Concentration (ADC)
0.3
0.5
0.3
Lifetime Average Daily Concentration
(LADC)
0.1
0.2
0.1
15-min TWA Exposure Concentration
0.6
28
20
0.6
4-hr TWA Exposure Concentration
2.4
3.2
9
2.4
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
Source: (U.S. POD and Environmental Health Readiness System - Industrial 20.1.8: Hervin et at. .1.977')
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure to workers is assessed using PCE personal breathing zone monitoring data from two sources
with a confidence rating of "high", as determined through EPA's systematic review process. However,
the 8-hr TWA data were collected prior to the Aerospace Manufacturing and Rework Facilities
NESHAP. There is some uncertainty in how implementing the requirements of the NESHAP may have
reduced worker exposures (if at all). Despite this uncertainty, EPA has a medium to high level of
confidence in the assessed worker exposure for this condition of use, based on the strength of the
monitoring data.
Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.19 Industrial Processing Aid
Worker Activities
At industrial facilities, workers are potentially exposed when unloading PCE from transport containers
into intermediate storage tanks and process vessels. Workers may be exposed via inhalation of vapor or
via dermal contact with liquids while connecting and disconnecting hoses and transfer lines. Once PCE
is unloaded into process vessels, it may be consumed in the process (e.g. when used for catalyst
regeneration) or be used until spent and sent for disposal.
ONUs are employees who work at the facilities that process and use PCE, but who do not directly
handle the material. ONUs may also be exposed to PCE but are expected to have lower inhalation
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exposures and are not expected to have dermal exposures. ONUs for this condition of use may include
supervisors, managers, engineers, and other personnel in nearby production areas.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during use of
PCE as a processing aid using Bureau of Labor Statistics' OES data (U.S. BLS 2016) and the U.S.
Census' SUSB (U. S. Census Bureau 2015) as well as the primary NAICS and SIC code reported by
each site in the 2016 TRI or 2016 DMR, respectively (see the Assessment of Occupational Exposure and
Environmental Releases for Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4
(Supplemental Engineering Report) (U.S. EPA 2020d) for number of sites estimate). This results in
approximately 14,000 workers and 6,000 ONUs potentially exposed during use of PCE as a processing
aid (see Table 2-47).
Table 2-47. Estimated Number of Workers Potentially Exposed to PCE During Use of Processing
Aids
Number
of Sites
Exposed
Workers per
Site
Exposed
Occupational Non-
Users per Site
Total
Exposed
Workers3
Total Exposed
Occupational Non-
Users3
Total
Exposed3
98
140
61
14,000
6,000
20,000
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA identified inhalation exposure monitoring data from four studies submitted to EPA under TSCA by
Dow ChemicaKDow Chem 1983a. b, 1982. 1979). The exact function of PCE is each study is not
explicitly stated; however, the data was collected in the agricultural chemical production and
distribution, trichloroethylene production, and chloropyridines process areas. Based on CDR reporting,
PCE is used as a processing aid in agricultural chemical manufacturing; therefore, monitoring data
collected in the agricultural chemical production area is assessed as a processing aid use of PCE.
Similarly, chloropyridines are used as intermediates in both the pharmaceutical and agrochemical
industries (Scriven and Murugan 2005). Both pharmaceutical and agrochemical industries are expected
to use PCE as a processing aid; therefore, monitoring data collected in the chloropyridine unit are also
assessed as a processing aid use. PCE can also be used as an inert material in trichloroethylene
production (Snedecor et al. 2004). Use as an inert material would fall under processing aid uses;
therefore, monitoring data collected during trichloroethylene production is assessed as a processing aid
use.
Worker samples were determined to be any sample taken on a person while directly handling PCE.
ONUs samples were determined to be any sample taken on a person in the same location as the PCE use
but not handling PCE. The results only include values for workers as monitoring data for ONUs were
not identified. EPA estimates that ONU exposures are lower than worker exposures, since ONUs do not
typically directly handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency
exposure results as a surrogate to estimate exposures for ONUs.
Table 2-48 presents a summary of the identified 8-hr TWA and 30-minute TWA monitoring data. For
the 8-hr TWA, the 95th percentile is presented as the high-end and the 50th percentile presented as the
central tendency. It should be noted that approximately 55% of the 8-hr TWA data were below the LOD.
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To estimate exposure concentrations for these data, EPA followed the Guidelines for Statistical Analysis
of Occupational Exposure Data ( to). The geometric standard deviation for the data was
above 3.0; therefore, EPA used the to estimate the exposure value as specified in the guidelines
(I b). Because over 50% of the data are below the LOD, calculating statistics from this
data does present the potential to introduce biases into the results. Estimation of exposure values for
results below the LOD may over- or under-estimate actual exposure thus skewing the calculated
statistics higher or lower, respectively. The overall directional bias of the exposure assessment,
accounting for both the overestimate and underestimate, is not known.
For the 30-minute TWA, only two data point were available, one of which measured below the LOD.
Because only a single data point with a measured value was available, EPA could not calculate a
geometric standard deviation. Therefore, EPA presents two scenarios: 1) using the maximum as a
"higher value"; and 2) using the midpoint between the maximum and the LOD as a "midpoint" value.
Table 2-48. Summary of Worker Inhalation Exposure Monitoring Data for Use of PCE as a
Processing Aid
Kxposure Concentration Type
Work
Kxposi
(en (nil
Tendency
(ppm)
er
res
High-
land
(ppm)
Nil m her
of
Samples
Occupational
Non-l ser
Kxposurcs
(ppm)"
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration
6.0E-02
1.2
89
6.0E-02
Medium
Acute Exposure Concentration (AC)
2.0E-02
0.4
2.0E-02
Average Daily Concentration (ADC)
1.4E-02
0.3
1.4E-02
Lifetime Average Daily Concentration
(LADC)
5.4E-03
0.1
5.4E-03
30-min TWA Exposure Concentration13
1.7
2.2
2
1.7
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
b Due to only two data points, one of which measured below the LOD, EPA presents two scenarios: 1) using the higher of the
two values; and 2) using the midpoint of the LOD and the maximum.
Source: (Dow Chem 1983a. b, .1.982. 1979)
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure to workers is assessed using PCE personal breathing zone monitoring data from several
different sources all with a confidence rating of "medium," as determined through EPA's systematic
review process. There is some uncertainty in how PCE is used within each process, but literature
corroborates categorizing the use as a processing aid. Based on the available information above, EPA
has a medium level of confidence in the assessed worker exposure for this condition of use.
Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
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expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.20 Metalworking Fluids
Worker Activities
Workers are expected to unload the metalworking fluid from containers; clean containers; dilute water-
based metalworking fluids; transfer fluids to the trough; performing metal shaping operations; rinse,
wipe, and/or transfer the completed part; change filters; transfer spent fluids; and clean equipment
(OECD 201 n.
ONUs include employees that work at the site where PCE is used in an industrial setting as a
metalworking fluid, but they typically do not directly handle the chemical and are therefore expected to
have lower exposures. ONUs for metalworking 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 PCE has a high vapor pressure (18.5 mmHg at 25°C), workers may be exposed to PCE when
handling liquid metalworking fluid, such as unloading, transferring, and disposing spent metalworking
fluids and cleaning machines and troughs. 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 can be exposed. Additionally, the high vapor pressure of PCE may lead to its evaporation
from the airborne mist droplets, potentially creating a fog of vapor and mist.
Number of Workers and Occupational Non-Users
The ESD on the Use of Metalworking Fluids cites a NIOSH study of 79 small machine shops, which
observed an average of 46 machinists per site (OECD 2011). The ESD also cites an EPA effluent limit
guideline development for the MP&M industry, which estimated a single shift supervisor per shift, who
may 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 (OECD 2011). The number of establishments that use PCE-based metalworking
fluids is unknown (see discussion in the Assessment of Occupational Exposure and Environmental
Releases for Per chloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental
Engineering Report) ( )20dV); therefore, EPA does not have data to estimate the total workers
and ONUs exposed to PCE from use of metalworking fluids.
Occupational Inhalation Exposure Results
EPA did not identify any inhalation exposure monitoring data related to the use of PCE-based
metalworking fluids. Therefore, EPA assessed inhalation exposures using the ESD on the Use of
Metalworking Fluids (OECD 2011). The ESD estimates typical and high-end exposures for different
types of metalworking fluids. The "typical" mist concentration is the geometric mean of the data and the
"high-end" is the 90th percentile of the data (< ). The recommended use of the PCE-based
metalworking fluid is an oil-based cutting and tapping fluid; therefore, EPA assesses exposure to the
PCE-based metalworking fluids using the straight oil mist concentrations and the max concentration of
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PCE in the metalworking fluid. Straight oils are not diluted; therefore, the concentration of PCE
specified in the identified SDS (<10%) is equal to the concentration of PCE in the mist.
Table 2-49 presents the exposure estimates for the use of PCE-based metalworking fluids. It should be
noted that these estimates may underestimate exposures to PCE during use of metalworking fluids as
they do not account for exposure to PCE that evaporates from the mist droplets into the air. This
exposure is difficult to estimate and is not considered in this assessment. However, due to the relatively
low concentration of PCE in the metalworking fluid, the partial pressure may be low enough such that
evaporation of PCE from the mist is limited and this not a significant route of exposure.
The results only include values for workers as the ESD does not include an approach for estimating
ONU exposures. EPA estimates that ONU exposures are lower than worker exposures, since ONUs do
not typically directly handle the chemical. In lieu of ONU-specific data, EPA uses worker central
tendency exposure results as a surrogate to estimate exposures for ONUs.
Table 2-49. Summary of Exposure Results for Use of PCE in Metalworking Fluids Based on ESD
Estimates
Kxposure Concent ration Type
Worker !¦
Central
Tendency
(ppm)
Ixposurc
lligli-
Ind
(ppm)
Occupational
Non-l scr
Kxposurcs
(ppm)11
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration13
5.8E-03
2.1E-02
5.8E-03
N/A - ESD
data
Acute Exposure Concentration (AC)
1.9E-03
7.0E-03
1.9E-03
Average Daily Concentration (ADC)
1.3E-03
4.8E-03
1.3E-03
Lifetime Average Daily Concentration (LADC)
5.2E-04
2.5E-03
5.2E-04
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
b The PCE exposure concentrations are calculated by multiplying the straight oil mist concentrations in the ESD by 10% (the
concentration of PCE in the metalworking fluid) and converting to ppm.
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure to workers is assessed using estimates from the Metalworking Fluid ESD for typical and high-
end mist exposures for straight oils. The ESD estimates are for a "generic" straight oil rather than a
PCE-specific metalworking fluid; therefore, there is some uncertainty in how this data applies to PCE-
based metalworking fluids. Additionally, the ESD estimates also only account for the exposure to mist;
however, PCE is volatile and expected to evaporate from the mist into the air. Therefore, the ESD
estimates may underestimate actual PCE exposure. Due to the low concentration of PCE in the
metalworking fluid, the partial pressure of PCE in the mist may be low enough such that this is not a
significant route of exposure, thus mitigating the overall underestimate. Based on the available
information above, EPA has a medium level of confidence in the assessed worker exposure for this
condition of use.
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Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.21 Wipe Cleaning and Metal/Stone Polishes
Worker Activities
Workers are expected to be exposed to PCE vapors that evaporate from the PCE-soaked rag or the
solvent residue left behind on the substrate after wiping. Additional activities and use patterns will vary
depending on the specific site at which the PCE cleaning product or polish is being used.
Number of Workers and Occupational Non-Users
EPA did not identify information to estimate the number of workers or ONUs exposed to PCE during
use for wipe cleaning and metal/stone polishes. It is possible some workers/ONUs at sites using vapor
degreasers or cold cleaners are also exposed to PCE from wipe cleaning activities.
Occupational Inhalation Exposure Results
EPA identified inhalation exposure monitoring data from NIOSH investigations at two sites using PCE
for wipe cleaning (Moody et al. 1983; Gunter and Lybareer 1979). EPA did not identify exposure data
specific to metal/stone polish applications; therefore, these data were also used to assess the use of
metal/stone polishes based on expected similarities in the uses. Due to the large variety in the types of
shops that may use PCE as a wipe cleaning solvent or metal/stone polish, it is unclear how
representative these data are of a "typical" site. EPA does not have a model for estimating exposures
from wipe cleaning or metal/stone polishes; therefore, the assessment is based on the identified
monitoring data. Table 2-50 summarizes 8-hr, 4-hr and 15-minute TWA monitoring data for the use of
PCE as a wipe cleaning solvent and metal/stone polish.
Worker samples were determined to be any sample taken on a person while performing the wipe
cleaning or polishing task. ONUs samples were determined to be any sample taken on a person in the
same location as the wipe cleaning or polishing task but were not performing the wipe cleaning or
polishing themselves.
Due to the limited number of data points for workers 8-hr and 15-minute TWA results, the maximum of
identified data is presented as the high-end and the median is presented as the central tendency. There is
only a single 4-hr TWA data point for workers. Results based on a single value are plausible exposure
concentrations, but EPA cannot determine the statistical representativeness of the value. For the ONU 8-
hr TWA, the 95th percentile is presented as the high-end and the 50th percentile as the central tendency.
The ONU data included four data points that are below the LOD. To estimate exposure concentrations
for these data, EPA followed the Guidelines for Statistical Analysis of Occupational Exposure Data
(U.S. EPA. 1994b). The geometric standard deviation for the data was above 3.0; therefore, EPA used
the to estimate the exposure value as specified in the guidelines ( b).
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Table 2-50. Summary of Worker Inhalation Monitoring Data for Use of PCE as a Wipe Cleaning
Solvent and Metal/Stone Polish
Kxposiire Concen 1 ralion
Type
Worki
Kxposu
(en (nil
Tendency
(ppni)
•r
res
lligli-
Ind
(ppni)
Number
of
Worker
Samples
Occupal
Noil-1
Kxposi
(en (nil
Tendency
(ppm)
ional
ser
res
lligli-
l.ml
(ppm)
.Number
of ONT
Samples
Data Quality
Rating of Air
Concent ration
Data
8-hr TWA Exposure
Concentration
132
228
4
2.2E-02
23
6
High
Acute Exposure
Concentration (AC)
44
76
7.3E-03
7.7
Average Daily
Concentration (ADC)
30
52
5.0E-03
5.3
Lifetime Average Daily
Concentration (LADC)
12
27
2.0E-03
2.7
15-min TWA Exposure
Concentration
66
103
9
No 15-min or 4-hr data
identified for ONUs
4-hr TWA Exposure
Concentration
9.5
1
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
Source: (Moody et a I. .1.983; Gunter and Lybarger 1979)
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using PCE personal breathing zone monitoring data from two sources with a
confidence rating of "high", as determined through EPA's systematic review process. There is some
uncertainty in how representative this data is of exposure at other facilities performing wipe cleaning or
polishing tasks. The data identified is also specific to wipe cleaning activities not polishing. Although
the application processes are expected to be similar, the frequency and duration of polish applications
may be less than those used for wipe cleaning. Therefore, the exposure values may overestimate
exposures during use of polishes. Despite these uncertainties, EPA has a medium level of confidence in
the assessed exposure for this condition of use.
2.4.1.22 Other Spot Cleaning/Spot Removers (Including Carpet Cleaning)
Worker Activities
As previously described, workers are expected to spray PCE on to the stained textiles and then manually
scrape away the stain using a brush or fingers.
Number of Workers and Occupational Non-Users
EPA did not identify information to estimate the total number of workers and ONUs exposed from use
of spot cleaners/spot removers. Both the Fabric Finishing GS ( la) and the ESD on the Use
of Textile Dyes (OECD 2017b) estimate three to six workers exposed per site. It is unknown how many
of those workers may be involved in the spot cleaning process.
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Occupational Inhalation Exposure Results
EPA identified inhalation exposure monitoring data from a single NIOSH investigation at a garment
manufacturer (Burton and Monestersky 1996). It is unclear how representative these data are of a
"typical" spot cleaning/spot remover scenario. Table 2-51 summarizes the 8-hr TWA monitoring data
for the use of PCE in spot cleaners/spot removers.
Worker samples were determined to be any sample taken on a person while directly handling PCE.
ONUs samples were determined to be any sample taken on a person in the same location as the PCE use
but not handling PCE.
Table 2-51. Summary of Worker Inhalation Exposure Monitoring Data for Other Spot
Cleaning/Spot Removers (Including Carpet Cleaning)
Kxposure
Concentration
Type
Worker K
Central
Tendency
(ppm)
xposures"
lligli-
Ind
(ppm)
Nil m her
of
Worker
Samples
Occupali<
I ser K\|
(en (nil
Tendency
(ppm)
>nal Non-
josures1'
High-
land
(ppm)
Nil m her
of OM
Samples
Data Qualify
Rating of Air
Concentration
Data
8-hr TWA Exposure
Concentration
0.2
0.2
2
3.0E-02
1
High
Acute Exposure
Concentration (AC)
5.7E-02
7.7E-02
1.0E-02
1.0E-02
Average Daily
Concentration
(ADC)
3.9E-02
5.3E-02
6.8E-03
6.8E-03
Lifetime Average
Daily Concentration
(LADC)
1.6E-02
2.7E-02
2.7E-03
3.5E-03
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a Due to only two data points identified for workers, EPA presents two scenarios: 1) using the higher of the two values; and
2) using the midpoint of the two values.
b Only one data point identified for ONUs; however, different parameters are used for calculating high-end and central
tendency ADC and LADC. Therefore, a high-end and central tendency are presented based on the single data point.
Source: (Burton and Monestersky 1996")
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure is assessed using PCE personal breathing zone monitoring data from a single source with a
confidence rating of "high", as determined through EPA's systematic review process. There is some
uncertainty in how representative this data is of exposure at other facilities performing carpet cleaning or
spot remover tasks. Based on the available information above, EPA has a medium level of confidence in
the assessed exposure for this condition of use.
2.4.1.23 Other Industrial Uses
Worker Activities
Based on information identified in EPA's preliminary data gathering and information obtained from TRI
and DMR, a variety of other industrial uses of PCE may exist. Based on information in the Use
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Document (U.S. EPA 2017f). market profile (U.S. EPA 2017bI and NAICS/SIC codes reported in TRI
(U.S. EPA 2017k) and DMR (U.S. EPA 2016a). examples of these uses include, but are not limited to,
uses in textile processing, wood furniture manufacturing, foundry applications, food manufacturing, and
scientific research and development. EPA did not identify information on how PCE may be used at these
facilities
Although information on worker activities at these sites was not identified, EPA expects workers to
perform activities similar to other industrial facilities. Therefore, workers may potentially be exposed
when unloading PCE from transport containers into intermediate storage tanks and process vessels.
Workers may be exposed via inhalation of vapor or via dermal contact with liquids while connecting and
disconnecting hoses and transfer lines.
ONUs are employees who work at the facilities that process and use PCE, but who do not directly
handle the material. ONUs may also be exposed to PCE but are expected to have lower inhalation
exposures and are not expected to have dermal exposures. ONUs for this condition of use may include
supervisors, managers, engineers, and other personnel in nearby production areas.
Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during processing
of PCE as a reactant using Bureau of Labor Statistics' OES data (U.S. BLS 2016) and the U.S. Census'
SUSB (U. S. Census Bureau 2015) as well as the primary NAICS and SIC code reported by each site in
the 2016 TRI or 2016 DMR, respectively (see the Assessment of Occupational Exposure and
Environmental Releases for Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4
(Supplemental Engineering Report) (U.S. EPA 2020d) for number of sites estimate). In the 2016 DMR
(U.S. EPA 2016a) there was one site that did not report a SIC code but after review of the company's
website, EPA determined that NAICS 311411 - Frozen Fruit, Juice, and Vegetable Manufacturing was
the most appropriate NAICS code to use for this site. There are approximately 2,700 workers and 1,300
ONUs potentially exposed during other industrial uses (see Table 2-52).
Table 2-52. Estimated Number of Workers Potentially Exposed to PCE During Other Industrial
Uses
Number
of Sites
Exposed
Workers per
Site
Exposed
Occupational Non-
Users per Site
Total
Exposed
Workers3
Total Exposed
Occupational Non-
Users3
Total
Exposed3
130
21
10
2,700
1,300
4,000
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA did not identify any inhalation exposure monitoring data for the other industrial uses. Therefore,
EPA assessed inhalation exposures during these uses using the Tank Truck and Railcar Loading and
Unloading Release and Inhalation Exposure Model, assuming PCE is present at 100 percent
concentration when used. Details of the model design and parameters is provided in Appendix E of the
Assessment of Occupational Exposure and Environmental Releases for Perchloroethylene (Ethene,
1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) (U.S. EPA 2020d). Table
2-53 summarizes the model results.
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The results only include values for workers as the model does not estimate ONU exposures. EPA
estimates that ONU exposures are lower than worker exposures, since ONUs do not typically directly
handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency exposure results
as a surrogate to estimate exposures for ONUs.
Table 2-53. Summary of Exposure Modeling Results for Other Industrial Uses of PCE
Kxposure Concentration Type
Worker 1.
Central
Tendency
(ppm)
xposures
Nigh-
End
(ppm)
Occupational
\on-l ser
Kxposures
(ppm)11
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration
8.0E-03
3.6E-02
8.0E-03
N/A - modeled
data
Acute Exposure Concentration (AC)
2.7E-03
1.2E-02
2.7E-03
Average Daily Concentration (ADC)
1.8E-03
8.2E-03
1.8E-03
Lifetime Average Daily Concentration (LADC)
7.2E-04
4.2E-03
7.2E-04
30-min TWA Exposure Concentration
0.1
_b
0.1
1-hr TWA Exposure Concentration
_b
0.3
_b
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
b High-end for short-term exposures is calculated as a 1-hr TWA and central tendency is calculated as a 30-min TWA.
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
The Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model is used to
estimate worker exposure. The model uses a combination of published EPA emission factors and
engineering judgment to estimate central tendency and high-end exposures. EPA believes the model
exposures are likely to be representative of exposure associated with bulk container loading. However,
the model does not account for other potential sources of exposure at industrial facilities, such as
sampling, equipment cleaning, and other process activities. The model also assumes only one container
is loaded per day, although larger facilities may have higher product loading frequencies. These model
uncertainties could result in an underestimate of the worker exposure. Based on reasonably available
information above, EPA has a medium level of confidence in the assessed worker exposure.
Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.24 Other Commercial Uses
Worker Activities
The worker activity, use pattern, and associated exposure will vary for each condition of use. For
polishes, ink removal products, and mold release, EPA expects workers may be exposed to PCE vapors
that evaporate from the application material (rag, brush, etc.) or the substrate surface during use. For
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inks, workers may be exposed to mists generated during the ink application process. For photographic
film, workers may be exposed to PCE that evaporates from the gating process.
Number of Workers and Occupational Non-Users
EPA has not identified information on the number of sites and potentially exposed workers associated
with these uses. The use of PCE for these conditions of use is expected to be minimal.
Occupational Inhalation Exposure Results
EPA assessed exposure to other commercial uses of PCE using data from identified studies. EPA
identified exposure data for printing uses (inks and ink removal products), photocopy shops,
photographic film, and mold release uses. Table 2-54 summarizes the 8-hr TWA and 15-min TWA data
identified for these uses. Note: Data for mold release products are area samples not worker breathing
zone samples; it is unclear how representative area samples are of actual exposures.
Worker samples were determined to be any sample taken on a person while directly handling PCE.
ONUs samples were determined to be any sample taken on a person in the same location as the PCE use
but not handling PCE. The results only include values for workers as monitoring data for ONUs were
not identified. EPA estimates that ONU exposures are lower than worker exposures, since ONUs do not
typically directly handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency
exposure results as a surrogate to estimate exposures for ONUs.
Table 2-54. Summary of Exposure Monitoring Data for Other Commercial Uses of PCE
Scenario
Kxposure
('onccnlralion Type
W orker K>
(on (nil
Tendency
(ppm)
.posures
lli«h-
l.ml
(ppm)
Number
of
Samples
Occupational
Non-l ser
Kxposurcs
(ppm)11
Data Qualify
Ualing of Air
Concent ralio
n Data
Printing
Applications
(Ink and Ink
Removal
Products)
8-hr TWA Exposure
Concentration
1.9
5.9
23
1.9
Medium to
High
Acute Exposure
Concentration (AC)
0.6
2.0
0.6
Average Daily
Concentration (ADC)
0.4
1.4
0.4
Lifetime Average
Daily Concentration
(LADC)
0.2
0.7
0.2
15-min TWA
Exposure
Concentration
0.2
1
0.2
Photocopying
8-hr TWA Exposure
Concentration
1.9E-04
5.0E-04
3
1.9E-04
High
Acute Exposure
Concentration (AC)
6.3E-05
1.7E-04
6.3E-05
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Scenario
Kxposure
Concentration Type
W orker K>
(on (nil
Tendency
(ppm)
.posures
lli«h-
Ind
(ppm)
N il in her
of
Samples
Occupational
Non-l ser
r.xposurcs
(ppm)"
Data Qualify
Rating of Air
Concent ratio
n Data
Average Daily
Concentration (ADC)
4.3E-05
1.1E-04
4.3E-05
Lifetime Average
Daily Concentration
(LADC)
1.7E-05
5.9E-05
1.7E-05
Photographic
Film
Applications
8-hr TWA Exposure
Concentration
6.3
56
62
6.3
Medium
Acute Exposure
Concentration (AC)
2.1
19
2.1
Average Daily
Concentration (ADC)
1.4
13
1.4
Lifetime Average
Daily Concentration
(LADC)
0.6
6.6
0.6
15-min TWA
Exposure
Concentration
13
117
40
13
Mold Release
Products
8-hr TWA Exposure
Concentration
0.1
0.2
4
0.1
High
Acute Exposure
Concentration (AC)
3.3E-02
6.7E-02
3.3E-02
Average Daily
Concentration (ADC)
2.3E-02
4.6E-02
2.3E-02
Lifetime Average
Daily Concentration
(LADC)
9.1E-03
2.3E-02
9.1E-03
4263 AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
4264 a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
4265 worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
4266 this value for ONUs is unknown.
4267 Source: (Gold et at. 2008: NIOSH 1980)
4268
4269 Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
4270 For printing applications, photocopying, and photographic film applications, worker exposure is
4271 assessed using PCE personal breathing zone monitoring data from multiple sources with confidence
4272 ratings ranging from "medium" to "high", as determined through EPA's systematic review process. EPA
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4273
4274
4275
4276
4277
4278
4279
4280
4281
4282
4283
4284
4285
4286
4287
4288
4289
4290
4291
4292
4293
4294
4295
4296
4297
4298
4299
4300
4301
4302
4303
4304
4305
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has a medium to high level of confidence in the assessed worker exposure for these uses based on the
strength of the monitoring data.
For mold release products, worker exposure is assessed using PCE area monitoring data from a single
source with a confidence rating of "high", as determined through EPA's systematic review process.
There is some uncertainty in how representative the area samples are of actual exposures. Based on the
above information, EPA has a medium confidence in the assessed worker exposure for this use.
Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.25 Laboratory Chemicals
Worker Activities
Specific worker activities for using laboratory uses were not identified, but EPA expects that workers
may be potentially exposed to PCE in laboratories during multiple activities, including unloading of
PCE from the containers in which they were received, transferring PCE into laboratory equipment (i.e.,
beakers, flasks, other intermediate storage containers), dissolving substances into PCE or otherwise
preparing samples that contain PCE, analyzing these samples, and discarding the samples.
ONUs for this condition of use include supervisors, managers, and other employees that may be in the
laboratory but do not perform tasks that result in the same level of exposures as those workers that
engage in tasks related to the use of PCE.
Number of Workers and Occupational Non-Users
EPA did not identify information to estimate the total number of workers exposed to PCE at laboratory
facilities. However, EPA estimated the number of workers and ONUs per site using information from
the Bureau of Labor Statistics' OES data (V S HI S ) and the U.S. Census' SUSB ("LI. S. Census
Bureau 2015). EPA identified the NAICS code 541380, Testing Laboratories, as the code expected to
include laboratory chemical uses of PCE. Based on data from the BLS for this NAICS code and related
SOC codes, there are an average of one worker and nine ONUs per site, or a total of ten potentially
exposed workers and ONUs per site.
Occupational Inhalation Exposure Results
EPA does not have reasonable available information to assess worker exposures to PCE during
laboratory use. However, due to the expected safety practices when using chemicals in a laboratory
setting, PCE is expected to be applied in small amounts under a fume hood, thus reducing the potential
for inhalation exposures.
2.4.1.26 Waste Handling, Disposal, Treatment, and Recycling
Worker Activities
At waste disposal sites, workers are potentially exposed via dermal contact with waste containing PCE
or via inhalation of PCE vapor. Depending on the concentration of PCE in the waste stream, the route
and level of exposure may be similar to that associated with container unloading activities. See Section
2.4.1.23 for the assessment of worker exposure from chemical unloading activities.
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4319
4320
4321
4322
4323
4324
4325
4326
4327
4328
4329
4330
4331
4332
4333
4334
4335
4336
4337
4338
4339
4340
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Number of Workers and Occupational Non-Users
EPA estimated the number of workers and occupational non-users potentially exposed during
disposal/treatment of PCE using Bureau of Labor Statistics' OES data (1; S HI S 2016) and the U.S.
Census' SUSB ("LI. S. Census Bureau ) as well as the primary NAICS and SIC code reported by
each site in the 2016 TRI or 2016 DMR, respectively. There are approximately 1,600 workers and 700
ONUs potentially exposed during disposal/treatment of PCE wastes (see Table 2-55)
Table 2-55. Estimated Number of Workers Potentially Exposed to PCE During Waste Handling,
Disposal, Treatment, and Recycling
Number
of Sites
V.x posed
Workers per
Nile
K.\ posed
Occupational Non-
l sers per Site
Total
Kxposed
Workers"
Total Kxposcd
Occupational Non-
l sers"
Total
Kxposed"
94
17
7
1,600
700
2,300
a Totals have been rounded to two significant figures. Totals may not add exactly due to rounding.
Occupational Inhalation Exposure Results
EPA did not identify any inhalation exposure monitoring data for disposal/treatment. Therefore, EPA
assessed inhalation exposures during these uses using the Tank Truck and Railcar Loading and
Unloading Release and Inhalation Exposure Model, assuming PCE is present at 100 percent
concentration when used. Details of the model design and parameters is provided in Appendix E of the
Assessment of Occupational Exposure and Environmental Releases for Perchloroethylene (Ethene,
1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report) ( 2020d). Table
2-56 summarizes the model results.
The results only include values for workers as the model does not estimate ONU exposures. EPA
estimates that ONU exposures are lower than worker exposures, since ONUs do not typically directly
handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency exposure results
as a surrogate to estimate exposures for ONUs.
Table 2-56. Summary of Exposure Modeling Results for Waste Handling, Disposal, Treatment,
and Recycling
Kxposurc Concentration Type
Worker I-
Central
Tendency
(ppm)
xposurcs
High-
land
(ppm)
Occupational
Non-l ser
Kxposurcs
(ppm)"
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration
8.0E-03
3.6E-02
8.0E-03
N/A - modeled
data
Acute Exposure Concentration (AC)
2.7E-03
1.2E-02
2.7E-03
Average Daily Concentration (ADC)
1.8E-03
8.2E-03
1.8E-03
Lifetime Average Daily Concentration (LADC)
7.2E-04
4.2E-03
7.2E-04
30-min TWA Exposure Concentration
0.1
_b
0.1
1-hr TWA Exposure Concentration
_b
0.3
_b
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
Page 179 of 636
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4347
4348
4349
4350
4351
4352
4353
4354
4355
4356
4357
4358
4359
4360
4361
4362
4363
4364
4365
4366
4367
4368
4369
4370
4371
4372
4373
4374
4375
4376
4377
4378
4379
4380
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4382
4383
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4385
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a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
b High-end for Acute exposures is calculated as a 1-hr TWA and central tendency is calculated as a 30-min TWA.
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
The Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model is used to
estimate worker exposure. The model uses a combination of published EPA emission factors and
engineering judgment to estimate central tendency and high-end exposures. EPA believes the model
exposures are likely to be representative of exposure associated with bulk container loading. However,
the model does not account for other potential sources of exposure at industrial facilities, such as
sampling, equipment cleaning, and other process activities. The model also assumes only one container
is loaded per day, although larger facilities may have higher product loading frequencies. These model
uncertainties could result in an underestimate of the worker exposure. Based on reasonably available
information above, EPA has a medium level of confidence in the assessed worker exposure.
Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.27 Other Department of Defense Uses
EPA reached out to the Department of Defense (DoD) for monitoring data for the first 10 chemical
substances that are the subject of the Agency's initial chemical risk evaluations. 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 DoD provided inhalation monitoring data for three branches of the military: Army,
Air Force, and Navy ( D and Environmental Health Readiness System - Industrial 2018). These
data are not distinguished among the three branches.
Where the condition of use of the collected monitoring data could be clearly determined and fit into one
of the conditions of use assessed in Sections 2.4.1.6 through 2.4.1.26. The following conditions of use
include DoD data:
• Aerosol Degreasing;
• Dry Cleaning;
• Adhesives, Sealants, Paints, and Coatings; and
• Chemical Maskants.
This section provides analysis of additional DoD data that did not fit into another previously identified
condition of use.
Worker Activities
The DoD data did not provide worker activities for these data.
Number of Workers and Occupational Non-Users
The DoD data did not provide information to estimate the number of workers and ONUs exposed from
these uses.
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4393
4394
4395
4396
4397
4398
4399
4400
4401
4402
4403
4404
4405
4406
4407
4408
4409
4410
4411
4412
4413
4414
4415
4416
4417
4418
4419
4420
4421
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Occupational Inhalation Results
EPA assessed exposures from two processes in the DoD data: oil analysis and water pipe repair. The
sample times for other processes in the dataset were less than 50% of an 8-hr shift (assumed shift-time
for these activities) and, therefore, may not be representative of actual 8-hr TWA exposures. Therefore,
EPA could not estimate exposures for these processes.
Oil Analysis
For the oil analysis process, one data point was available; however, different parameters are used for
calculating high-end and central tendency ADC and LADC. Therefore, a high-end and central tendency
are presented based on the single data point.
EPA adjusted the exposure frequency when calculating ADC and LADC to reflect the expected number
of exposure days based on the process frequency reported by DoD. For the oil analysis the frequency
was two to three times per week. EPA used the midpoint of the ranges to estimate the central tendency
ADC and LADC and the maximum frequency to calculate the high-end ADC and LADC. This resulted
in 150 exposure days/yr at the high-end and 125 exposure days at the central tendency for the oil
analysis.
Worker samples were determined to be any sample taken on a person while directly handling PCE.
ONUs samples were determined to be any sample taken on a person in the same location as the PCE use
but not handling PCE. The results only include values for workers as monitoring data for ONUs were
not identified. EPA estimates that ONU exposures are lower than worker exposures, since ONUs do not
typically directly handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency
exposure results as a surrogate to estimate exposures for ONUs.
Kxposure Concentration Type
W'orl
K x pos
(en (nil
Tendency
(ppm)
ver
ii res
lli«h-
l.ml
(ppm)
N il in her
of
Samples
Occupational
Non-l ser
Kx pos ii res
(ppm)11
Data Qualify
Rating of Air
Concent ration
Data
8-hr TWA Exposure Concentration
0.9b
1
0.9
High
Acute Exposure Concentration (AC)
0.3
0.3
0.3
Average Daily Concentration (ADC)
0.1
0.1
0.1
Lifetime Average Daily Concentration
(LADC)
4.0E-02
6.2E-
02
4.0E-02
15-min TWA Exposure Concentration
4.2
1
4.2
1-hr TWA Exposure Concentration
6.6
1
6.6
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
b Only one data point identified for oil analysis. However, different parameters are used for calculating high-end and central
tendency ADC and LADC. Therefore, a high-end and central tendency are presented based on the single data point.
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4425
4426
4427
4428
4429
4430
4431
4432
4433
4434
4435
4436
4437
4438
4439
4440
4441
4442
4443
4444
4445
4446
4447
4448
4449
4450
4451
4452
4453
4454
4455
4456
4457
4458
4459
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Source: (U.S. POD and Environmental Health Readiness System - Industrial 2018)
Water Pipe Repair
For the water pipe repair, there was only one data point available as well; however, it measured below
the LOD. To estimate values below the LOD, EPA referenced the Guidelines for Statistical Analysis of
Occupational Exposure Data ( 4b). However, there is only a single data point, so the
geometric standard deviation is not statistically meaningful. Therefore, EPA assesses the exposure as
ranging from zero to the LOD (2.31 ppm) and presents two scenarios: 1) using the LOD as a "higher
value"; and 2) using half the LOD as a "midpoint" value.
EPA adjusted the exposure frequency when calculating ADC and LADC to reflect the expected number
of exposure days based on the process frequency reported by DoD. For the water pipe repair the
frequency was two to three times per month. EPA used the midpoint of the ranges to estimate the central
tendency ADC and LADC and the maximum frequency to calculate the high-end ADC and LADC. This
resulted in 36 exposure days/yr at the high-end and 30 exposure days at the central tendency for the
water pipe repair.
Worker samples were determined to be any sample taken on a person while directly handling PCE.
ONUs samples were determined to be any sample taken on a person in the same location as the PCE use
but not handling PCE. The results only include values for workers as monitoring data for ONUs were
not identified. EPA estimates that ONU exposures are lower than worker exposures, since ONUs do not
typically directly handle the chemical. In lieu of ONU-specific data, EPA uses worker central tendency
exposure results as a surrogate to estimate exposures for ONUs.
Table 2-58. Summary of Inhalation Monitoring Data for Other DoD Uses (Water Pipe Repair) of
PCE
Exposure Concentration Type
Worker l.>
Midpoint
Value
(ppm)
posures
Higher
Value
(ppm)
Nil m her
of
Sam pies
Occupational
Non-l ser
Exposures
(ppm)11
Data Quality
Rating of Air
Concentration
Data
8-hr TWA Exposure Concentration
1.2
2.3
1
1.2
High
Acute Exposure Concentration (AC)
0.4
0.8
0.4
Average Daily Concentration (ADC)
3.2E-02
7.6E-02
3.2E-02
Lifetime Average Daily Concentration
(LADC)
1.3E-02
3.9E-02
1.3E-02
AC = Acute Concentration; ADC = Average Daily Concentration; and LADC = Lifetime Average Daily Concentration.
a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses
worker central tendency exposure results as a surrogate to estimate exposures for ONUs. The statistical representativeness of
this value for ONUs is unknown.
Source: (U.S. DOD and Environmental Health Readiness System - Industrial 20.1.8)
Strength, Limitation, and Uncertainty of the Inhalation Exposure Assessment
Exposure to workers is assessed using PCE personal breathing zone monitoring data from DoD which
has a confidence rating of "high", as determined through EPA's systematic review process. The data is
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directly applicable to the use being assessed. For the water pipe repair there is some uncertainty in the
assessed values as the measurement was below the LOD. Despite this uncertainty, EPA has a high level
of confidence in the assessed worker exposure for these uses based on the strength of the monitoring
data.
Exposure to ONUs is assessed using the worker central tendency exposure values. The statistical
representativeness of this value for ONUs is unknown; however, the central tendency for ONUs is
expected to be lower than that of workers as EPA expects ONUs to be farther from the source of
exposure than workers. Therefore, EPA's confidence in the exposure estimate for ONUs is low.
2.4.1.28 Summary of Inhalation Exposure Assessment
The following table summarizes the inhalation exposure estimates for all occupational exposure
scenarios. Where statistics can be calculated, the central tendency estimate represents the 50th percentile
exposure level of the available data set, and the high-end estimate represents the 95th percentile exposure
level.
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4474 Table 2-59. Summary o
8- or 12-Hour TWA
Exposures (ppm)
AC (ppm)
ADC (ppm)
LADC (ppm)
Statistical
Value for
Condition of
Use
Category
High-End
Central
Tendency
High-End
Central
Tendency
High-End
Central
Tendency
High-End
Central
Tendency
Central
Tendency
and High-
End
Data Type
Manufacturing
(8-hr TWA)
Worker
2.6
3.3E-02
0.9
1.1E-02
0.6
7.4E-03
0.3
2.9E-03
50th and
95th
Percentile
Monitoring
Data
Manufacturing
(8-hr TWA)
ONUa
3.3E-02
1.1E-02
7.4E-03
2.9E-03
Unknown
Worker Central
Tendency
Manufacturing
(12-hr TWA)
Worker
0.2
2.1E-02
0.1
1.0E-02
7.3E-02
7.0E-03
3.7E-03
2.8E-03
50th and
95th
Percentile
Monitoring
Data
Manufacturing
(12-hr TWA)
ONUa
2.1E-02
1.0E-02
7.0E-03
2.8E-03
Unknown
Worker Central
Tendency
Repackaging
Worker
0.8
0.4
0.3
0.1
0.2
9.9E-02
9.6E-02
3.9E-02
50th and
95th
Percentile
Monitoring
Data
Repackaging
ONUa
0.4
0.1
9.9E-02
3.9E-02
Unknown
Worker Central
Tendency
Processing as
Reactant/
Intermediate (8-
hr TWA)
Worker
2.6
3.3E-02
0.9
1.1E-02
0.6
7.4E-03
0.3
2.9E-03
50th and
95th
Percentile
Monitoring
Data
Processing as
Reactant/
Intermediate (8-
hr TWA)
ONUa
3.3E-02
1.1E-02
7.4E-03
2.9E-03
Unknown
Worker Central
Tendency
Processing as
Reactant/
Intermediate
Worker
0.2
2.1E-02
0.1
1.0E-02
7.3E-02
7.0E-03
3.7E-03
2.8E-03
50th and
95th
Percentile
Monitoring
Data
(12-hr TWA)
Processing as
Reactant/
Intermediate
(12-hr TWA)
ONUa
2.1E-02
1.0E-02
7.0E-03
2.8E-03
Unknown
Worker Central
Tendency
Incorporation
into
Formulation -
Worker
13
8.3
4.4
2.8
3.0
1.9
1.5
0.8
Median and
Maximum
Monitoring
Data
Aerosol
Packing
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Condition of
I so
X-or 12-1
l'l\|)OMII
lliiih-r.nd
our TWA
OS (|)|)lll)
( oil (nil
ToihIoiio\
AC l
lliiih-r.nd
)|)in)
( oil I ml
ToihIoiio\
ADC (
lli»h-l.ii(l
ppiii)
Coulriil
1 oihIoiioj
I.ADC
Ili'Ji-l.nd
(|)|)in)
( oil (r;il
ToihIoiioj
Sliiiisiioiil
Yiiluo lor
( oil (nil
Tondono\
iiud lli«h-
l.nd
Diilii Tjpo
Incorporation
into
Formulation -
Aerosol
Packing
ONUa
8.3
2.8
1.9
0.8
Unknown
Worker Central
Tendency
Incorporation
into
Formulation -
Degreasing
Solvent
Worker
2.6
0.7
0.4
0.1
5.7E-02
1.6E-02
8.4E-03
2.3E-03
50th and
95th
Percentile
Model
(probabilistic)
Incorporation
into
Formulation -
Degreasing
Solvent
ONUa
0.7
0.1
1.6E-02
2.3E-03
Unknown
Worker Central
Tendency
Incorporation
into
Formulation -
Dry Cleaning
Solvent
Worker
14
4.0
2.1
0.6
0.3
8.6E-02
4.5E-02
1.3E-02
50th and
95th
Percentile
Model
(probabilistic)
Incorporation
into
Formulation -
Dry Cleaning
Solvent
ONUa
4.0
0.6
8.6E-02
1.3E-02
Unknown
Worker Central
Tendency
Incorporation
into
Formulation -
Miscellaneous
Worker
1.4
0.4
0.2
5.9E-02
3.1E-02
8.6E-03
4.5E-03
1.3E-03
50th and
95th
Percentile
Model
(probabilistic)
Incorporation
into
Formulation -
Miscellaneous
ONUa
0.4
5.9E-02
8.6E-03
1.3E-03
Unknown
Worker Central
Tendency
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Condition of
I so
X-or 12-1
l'l\|)OMII
lliiih-r.nd
our TWA
OS (|)|)lll)
( oil (nil
ToihIoiio\
AC l
lliiih-r.nd
)|)in)
( oil I ml
ToihIoiio\
ADC (
lli»h-l.ii(l
ppiii)
Coulriil
1 oihIoiioj
I.ADC
lli»h-i:ii(l
(|)|)in)
( oil (r;il
ToihIoiioj
Sliiiisiioiil
Yiiluo lor
( oil (nil
IoikIoiio>
iiud lli«h-
l.nd
Diilii Tjpo
OTVD
Worker
32
2.1
11
0.7
7.3
0.5
3.8
0.2
50th and
95th
Percentile
Monitoring
Data
OTVD
ONU
5.2
0.6
1.7
0.2
1.2
0.1
0.6
5.5E-02
50th and
95th
Percentile
Monitoring
Data
Closed Loop
Vapor
Decreasing
Worker
0.3
7.2E-02
8.4E-02
2.4E-02
5.8E-02
1.6E-02
3.0E-02
6.6E-03
50th and
95th
Percentile
Monitoring
Data
Closed Loop
Vapor
Decreasing
ONU
0.1
6.5E-02
3.2E-02
2.2E-02
2.2E-02
1.5E-02
1.1E-02
5.9E-03
Median and
Maximum
Monitoring
Data
Conveyorized
Vapor
Decreasing
Worker
186
78
62
26
42
18
17
6.7
50th and
95th
Percentile
Model
(probabilistic)
Conveyorized
Vapor
Degreasing
ONU
126
41
42
14
29
9.3
12
3.5
50th and
95th
Percentile
Model
(probabilistic)
Web
Degreasing
Worker
1.8
0.6
0.6
0.2
0.4
0.1
0.2
5.3E-02
50th and
95th
Percentile
Model
(probabilistic)
Web
Degreasing
ONU
1.3
0.3
0.4
0.1
0.3
7.3E-02
0.1
2.7E-02
50th and
95th
Percentile
Model
(probabilistic)
Cold Cleaning
Worker
4.1
1.4
1.4
0.5
0.9
0.3
0.5
0.1
50th and
95th
Percentile
Monitoring
Data
Cold Cleaning
Worker
1.5
2.4E-03
0.5
8.0E-04
0.4
5.5E-04
0.1
2.0E-04
50th and
95th
Percentile
Model
(probabilistic)
Cold Cleaning
ONU
0.8
1.2E-03
0.3
4.1E-04
0.2
2.8E-04
6.7E-02
1.1E-04
50th and
95th
Percentile
Model
(probabilistic)
Page 186 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Condition of
I si-
X-or 12-1
l'l\|)OMII
lliiih-r.nd
our TWA
OS (|)|)lll)
( oil (nil
ToihIoiio\
AC l
lliiih-r.nd
)|)in)
( oil I ml
ToihIoiic\
ADC (
lli»h-l.ii(l
ppiii)
Coulriil
1 oihIoiioj
I.ADC
lliiih-r.nd
(|)|)in)
( oil (r;il
ToihIoiioj
Sliii isi iciil
Yiiluo lor
( oil (nil
Tondono\
iiud lli«h-
l.nd
Diilii Tjpo
Aerosol
Degreasing/
Lubricants
Worker
7.8
1.4
2.6
0.5
1.8
0.3
0.9
0.1
50th and
95th
Percentile
Monitoring
Data
Aerosol
Degreasing/
Lubricants
Worker
17
5.5
5.7
1.8
3.9
1.3
1.6
0.5
50th and
95th
Percentile
Model
(probabilistic)
Aerosol
Degreasing/
Lubricants
ONU
0.7
0.1
0.2
3.4E-02
0.2
2.0E-02
7.0E-02
1.0E-02
50th and
95th
Percentile
Model
(probabilistic)
Post-2006
NESHAP Dry
Cleaning
Worker
20
3.6
6.5
1.2
5.2
0.9
2.7
0.3
50th and
95th
Percentile
Monitoring
Data
Post-2006
NESHAP Dry
Cleaning
ONU
0.3
0.3
0.1
0.1
9.3E-02
8.2E-02
4.8E-02
3.3E-02
N/A (one
data point)
Monitoring
Data
4th/5th Gen
Only Dry
Cleaning
Worker
5.6
1.0
1.9
0.3
1.5
0.2
0.8
9.2E-02
50th and
95th
Percentile
Monitoring
Data
4th/5th Gen
Only Dry
Cleaning
ONU
0.1
1.4E-02
4.1E-02
4.7E-03
3.3E-02
3.3E-03
1.7E-02
1.3E-03
Median and
Maximum
Monitoring
Data
Dry Cleaning
(12-hr TWA)
Worker
30
1.4
15
0.7
10
0.5
4.1
0.2
50th and
95th
Percentile
Model
(probabilistic)
Dry Cleaning
(12-hr TWA)
ONU
1.5
0.1
0.8
5.4E-02
0.6
3.8E-02
0.2
1.4E-02
50th and
95th
Percentile
Model
(probabilistic)
Paints/Coatings
Worker
4.6
0.2
1.5
7.8E-02
1.0
5.3E-02
0.5
2.1E-02
50th and
95th
Percentile
Monitoring
Data
Paints/Coatings
ONUa
0.2
7.8E-02
5.3E-02
2.1E-02
Unknown
Worker Central
Tendency
Page 187 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Condition of
I so
X-or 12-1
l'l\|)OSIII
lli»h-l.n(l
our TWA
OS (|)|)lll)
( oil (nil
ToihIoiio\
AC l
lliiih-r.nd
)|)in)
( oil I ml
ToihIoiio\
ADC (
lli»h-l.ii(l
ppm)
Coulriil
1 oihIoiioj
I.ADC
lliiih-r.nd
(ppm)
( oil (r;il
ToihIoiioj
Sliiiisiioiil
Yiiluo lor
( oil (nil
IoikIoiio>
iiud lli«h-
l.nd
Diilii Tjpo
Adhesives
Worker
0.8
8.8E-02
0.3
2.9E-02
0.2
2.0E-02
9.5E-02
8.0E-03
Arithmetic
Mean and
Maximum
Monitoring
Data
Adhesives
ONUa
8.8E-02
2.9E-02
2.0E-02
8.0E-03
Unknown
Worker Central
Tendency
Chemical
Maskant
Worker
2.1
1.2
0.7
0.4
0.5
0.3
0.2
0.1
50th and
95th
Percentile
Monitoring
Data
Chemical
Maskant
ONUa
1.2
0.4
0.3
0.1
Unknown
Worker Central
Tendency
Industrial
Processing Aid
Worker
1.2
6.0E-02
0.4
2.0E-02
0.3
1.4E-02
0.1
5.4E-03
50th and
95th
Percentile
Monitoring
Data
Industrial
Processing Aid
ONUa
6.0E-02
2.0E-02
1.4E-02
5.4E-03
Unknown
Worker Central
Tendency
Other Industrial
Uses
Worker
3.6E-02
8.0E-03
1.2E-02
2.7E-03
8.2E-03
1.8E-03
4.2E-03
7.2E-04
N/A-CT
and HEb
Model
(deterministic)
Other Industrial
Uses
ONUa
8.0E-03
2.7E-03
1.8E-03
7.2E-04
Unknown
Worker Central
Tendency
Metalworking
Fluid
Worker
2.1E-02
5.8E-03
7.0E-03
1.9E-03
4.8E-03
1.3E-03
2.5E-03
5.2E-04
Geometric
mean and
90th
percentile
ESD
Metalworking
Fluid
ONUa
5.8E-03
1.9E-03
1.3E-03
5.2E-04
Unknown
Worker Central
Tendency
Wipe Cleaning
and
Metal/Stone
Polishes
Worker
228
132
76
44
52
30
27
12
Median and
Maximum
Monitoring
Data
Wipe Cleaning
and
Metal/Stone
Polishes
ONU
23
2.2E-02
7.7
7.3E-03
5.3
5.0E-03
2.7
2.0E-03
50th and
95th
Percentile
Monitoring
Data
Page 188 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Condition of
I so
X-or 12-1
l'l\|)OMII
lliiih-r.nd
our TWA
OS (|)|)lll)
( oil (nil
ToihIoiio\
AC l
lliiih-r.nd
)|)in)
( oil I ml
ToihIoiio\
ADC (
lli»h-l.ii(l
ppm)
Coulriil
Toil(loilO\
I.ADC
Ili'Ji-l.nd
(ppm)
( oil (r;il
ToihIoiioj
Sliiiisiioiil
Yiiluo lor
( oil (nil
IoikIoiio>
iiud lli«h-
r. ikI
Diilii l>po
Other Spot
Cleaning/Spot
Removers
(Including
Carpet
Cleaning)
Worker
0.2
0.2
7.7E-02
5.7E-02
5.3E-02
3.9E-02
2.7E-02
1.6E-02
Median and
Maximum
Monitoring
Data
Other Spot
Cleaning/Spot
Removers
(Including
Carpet
Cleaning)
ONU
3.0E-020
1.0E-02
1.0E-02
6.8E-03
6.8E-03
3.5E-03
2.7E-03
N/A (one
data point)
Monitoring
Data
Other
Commercial
Uses - Printing
Worker
5.9
1.9
2.0
0.6
1.4
0.4
0.7
0.2
50th and
95th
Percentile
Monitoring
Data
Other
Commercial
Uses - Printing
ONUa
1.9
0.6
0.4
0.2
Unknown
Worker Central
Tendency
Other
Commercial
Uses -
Photocopying
Worker
5.0E-04
1.9E-04
1.7E-04
6.3E-05
1.1E-04
4.3E-05
5.9E-05
1.7E-05
Median and
Maximum
Monitoring
Data
Other
Commercial
Uses -
Photocopying
ONUa
1.9E-04
6.3E-05
4.3E-05
1.7E-05
Unknown
Worker Central
Tendency
Other
Commercial
Uses -
Photographic
Film
Worker
56
6.3
19
2.1
13
1.4
6.6
0.6
50th and
95th
Percentile
Monitoring
Data
Page 189 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Condition of
I so
X-or 12-1
l'l\|)OMII
lliiih-r.nd
our TWA
OS (|)|)lll)
( oil (nil
ToihIoiio\
AC l
lliiih-r.nd
)|)in)
( oil I ml
ToihIoiio\
ADC (
lli»h-l.ii(l
ppiii)
Coulriil
1 oihIoiioj
I.ADC
lliiih-r.nd
(|)|)in)
( oil (r;il
ToihIoiioj
Sliiiisiioiil
Yiiluo lor
( oil (nil
IoikIoiio>
iiud lli«h-
l.nd
Diilii Tjpo
Other
Commercial
Uses -
Photographic
Film
ONUa
6.3
2.1
1.4
0.6
Unknown
Worker Central
Tendency
Other
Commercial
Uses - Mold
Release
Worker
0.2
0.1
6.7E-02
3.3E-02
4.6E-02
2.3E-02
2.3E-02
9.1E-03
Arithmetic
Mean and
Maximum
Monitoring
Data
Other
Commercial
Uses - Mold
Release
ONUa
0.1
3.3E-02
2.3E-02
9.1E-03
Unknown
Worker Central
Tendency
Other DOD
Uses - Water
Pipe Repair
Worker
2.3
1.2
0.8
0.4
7.6E-02
3.2E-02
3.9E-02
1.3E-02
Half the
LOD and
the LOD
Monitoring
Data
Other DOD
Uses - Water
Pipe Repair
ONUa
1.2
0.4
3.2E-02
1.3E-02
Unknown
Worker Central
Tendency
Other DOD
Uses - Oil
analysis
Worker
©
VO
o
0.3
0.3
0.1
0.1
6.2E-02
4.0E-02
N/A (one
data point)
Monitoring
Data
Other DOD
Uses - Oil
analysis
ONUa
0.9
0.3
0.1
4.0E-02
Unknown
Worker Central
Tendency
Disposal/
Recycling
Worker
3.6E-02
8.0E-03
1.2E-02
2.7E-03
8.2E-03
1.8E-03
4.2E-03
7.2E-04
N/A-CT
and HEb
Model
(deterministic)
Disposal/
Recycling
ONUa
8.0E-03
2.7E-03
1.8E-03
7.2E-04
Unknown
Worker Central
Tendency
4475 a EPA did not identify monitoring data or models to estimate exposures for ONUs. In lieu of ONU-specific data, EPA uses worker central tendency exposure results as a
4476 surrogate to estimate exposures for ONUs. The statistical representativeness of this value for ONUs is unknown.
4477 b Based on distinct model scenarios that are likely representative of central tendency (CT) and high-end (HE) exposures.
4478 0 Only a single data point was available for this condition of use.
Page 190 of 636
-------
4479
4480
4481
4482
4483
4484
4485
4486
4487
4488
4489
4490
4491
4492
4493
4494
4495
4496
4497
4498
4499
4500
4501
4502
4503
4504
4505
4506
4507
4508
4509
4510
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
2.4.1.29 Dermal Exposure Assessment
Dermal absorption of PCE depends on the type and duration of exposure. Where exposure is non-
occluded, only a fraction of PCE that comes into contact with the skin will be absorbed as the chemical
readily evaporates from the skin. However, dermal exposure may be significant in cases of occluded
exposure, repeated contacts, or dermal immersion. For example, work activities with a high degree of
splash potential may result in PCE liquids trapped inside the gloves, inhibiting the evaporation of PCE
and increasing the exposure duration.
To assess exposure, EPA used the Dermal Exposure to Volatile Liquids Model (see following equation
and Appendix K of the Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2,-Tetrachloro) CASRN: 127-18-4 (Supplemental Engineering Report)
(I 020d)) to calculate the dermal retained dose. The equation modifies EPA OP PI' 2-Hand
Dermal Exposure to Liquids Model (peer reviewed) 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:
Dexp ~
S x ( Qu x fobs) x Yderm x FT
PF x BW
Where:
Dexp is the dermal retained dose (mg/kg-day)
S is the surface area of contact (cm2)
Qu is the quantity remaining on the skin after an exposure event (mg/cm2-event)
Yderm is the weight fraction of the chemical of interest in the liquid (0 < Yderm < 1)
FT is the frequency of events (integer number per day)
fabs is the fraction of applied mass that is absorbed (Default for PCE: 0.13 for industrial facilities
and 0.19 for commercial facilities13)
PF is the glove protection factor (Default: see Table 2-60)
BW is the body weight (Default: 80 kg)
Default glove PF values, which vary depending on the type of glove used and the presence of employee
training program, are shown in Table 2-60.
Table 2-60. Glove Protection Factors for Different Derma
Protection Strategies
Dermal Protect ion Characteristics
Sett in«
Protection Kaclor.
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
13 The absorbed fraction (fabs) is a function of indoor air speed, which differs for industrial and commercial settings.
Page 191 of 636
-------
4511
4512
4513
4514
4515
4516
4517
4518
4519
4520
4521
4522
4523
4524
4525
4526
4527
4528
4529
4530
4531
4532
4533
4534
4535
4536
4537
4538
4539
4540
4541
4542
4543
4544
4545
4546
4547
4548
4549
4550
4551
4552
4553
4554
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Source: (Margnart et at. 20.1.7')
Table 2-61 presents the estimated dermal acute retained dose for workers in various exposure scenarios,
including what-if scenarios for glove use. The dose estimates assume one exposure event (applied dose)
per work day and that 13 to 19 percent of the applied dose is absorbed through the skin. The exposure
estimates are provided for each condition of use, where the conditions of uses are "binned" based on the
maximum possible exposure concentration (Yderm) and the likely level of exposure. The exposure
concentration is determined based on EPA's review of currently available products and formulations
containing PCE:
• Bin 1: Bin 1 covers industrial uses that generally occur in closed systems. For these uses, dermal
exposure is likely limited to chemical loading/unloading activities (e.g. connecting hoses) and
taking quality control samples.
• Bin 2: Bin 2 covers industrial degreasing and chemical maskant uses, which are not closed
systems. For these uses, there is greater opportunity for dermal exposure during activities such as
charging and draining degreasing/milling equipment, drumming waste solvent, handling
recycled/re-captured maskants, and removing waste sludge.
• Bin 3: Bin 3 covers aerosol uses, where workers are likely to have direct dermal contact with
film applied to substrate and incidental deposition of aerosol to skin.
• Bin 4: Bin 4 covers commercial activities of similar maximum concentration. Most of these uses
are uses at dry cleaners, and/or uses expected to have direct dermal contact with bulk liquids. At
dry cleaning shops, workers may be exposed to bulk liquids while charging and draining solvent
to/from machines, removing and disposing sludge, and maintaining equipment. Workers can also
be exposed to PCE used in spot cleaning products at the same shop.
• Bin 5: Bin 5 covers uses of metalworking fluids containing PCE. These product formulations are
expected to be used in industrial settings and workers may be exposed when unloading the
metalworking fluid from containers; transferring fluids to the trough; and performing metal
shaping operations.
• Bin 6: Bin 6 covers uses of adhesives, sealants, paints, and coatings containing PCE. These
product formulations may have both industrial and commercial uses and workers may be
exposed when mixing coating/adhesive, charging products to application equipment (e.g., spray
guns, roll applicators, etc.), and cleaning application equipment. Other workers may also have
incidental contact with applied products during subsequent fabrication steps.
Dermal exposure to liquid is not expected for occupational non-users, as they do not directly handle
PCE.
Strength, Limitation, and Uncertainty of the Dermal Exposure Assessment
Dermal exposures are assessed using the Dermal Exposure to Volatile Liquids Model, which relies on
the theoretical framework presented by Kasting and Miller (2006) to estimate the fractional absorption
in accounting for chemical volatilization. EPA has a medium level of confidence in the assessed baseline
exposure. Glove protection factors are presented as what-if scenarios to show the potential effect of
glove use on exposure levels. EPA does not know the actual frequency, type, and effectiveness of glove
use in specific workplaces with PCE conditions of use.
Page 192 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
4555 Table 2-61. Estimated Dermal Acute Retained Dose for Workers in All Conditions of Use
Kxposure Scenario
liin
Max
^ (linn
Dermal Kxposurc (m«/kj»-dav)
No
Cloves
(PI = 1)
Protective
(•loves
(PI =5)
Protective (Jovcs
(PI = 10)
Protective (Jovcs
(Industrial uses.
PI- = 20)
Manufacture
Import/Repackaging
Processing as a Reactant
Incorporation into Formulation, Mixture, or
Reaction Product
Bin 1
1.0
1.2 (CT)
3.5(HE)
0.2 (CT)
0.7 (HE)
0.1 (CT)
0.4 (HE)
5.9E-02 (CT)
0.2 (HE)
Industrial Processing Aid
Other Industrial Uses
Waste Handling, Disposal, Treatment, and
Recycling
Batch Open-Top Vapor Degreasing
Batch Closed-Loop Vapor Degreasing
Conveyorized Vapor Degreasing
Bin 2
1.0
1.2(CT)
0.2 (CT)
0.1 (CT)
5.9E-02 (CT)
Web Degreasing
3 .5 (HE)
0.7 (HE)
0.4 (HE)
0.2 (HE)
Cold Cleaning
Maskant for Chemical Milling
Aerosol Degreasing and Aerosol Lubricants
Bin 3
1.0
1.8 (CT)
5 .3 ( HE )
0.4 (CT)
1.1 (HE)
0.2 (CT)
0.5 (HE)
N/A
Page 193 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Kxposurc Scenario
liin
Max
^ (linn
Dermal Kxposuro (mg/kg-riav)
Dry Cleaning and Spot Cleaning
Wipe Cleaning and Metal/Stone Polishes
Other Spot Cleaning/Spot Remover
Other Commercial Uses
Bin 4
1.0
1.8 (CT)
5 .4 ( HE )
0.4 (CT)
1.1 (HE)
0.2 (CT)
0.5 (HE)
N/A
Metal working Fluids
Bin 5
0.10
0.1 (CT)
0.4 (HE)
2.5E-02 (CT)
7.1E-02 (HE)
1.2E-02 (CT)
3.5E-02 (HE)
5.9E-03 (CT)
1.8E-02 (HE)
Adhesives, Sealants, Paints, and Coatings
(Industrial)
Bin 6
0.80
0.9 (CT)
2.8 (HE)
0.2 (CT)
0.6 (HE)
9.4E-02 (CT)
0.3 (HE)
4.7E-02 (CT)
0.1 (HE)
Adhesives, Sealants, Paints, and Coatings
(Commercial)
0.80
1.4 (CT)
4.3 (HE)
0.3 (CT)
0.9 (HE)
0.1 (CT)
0.4 (HE)
N/A
4556 CT = Central Tendency; HE = High-End
4557
Page 194 of 636
-------
4558
4559
4560
4561
4562
4563
4564
4565
4566
4567
4568
4569
4570
4571
4572
4573
4574
4575
4576
4577
4578
4579
4580
4581
4582
4583
4584
4585
4586
4587
4588
4589
4590
4591
4592
4593
4594
4595
4596
4597
4598
4599
4600
4601
4602
4603
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
2.4.1.30 Key Assumptions and Uncertainties of the Occupational Exposure
Assessment
EPA addressed variability in 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. Where the
statistical variation is not known, assumptions are made to estimate the parameter distribution
using available literature data. See the Draft Risk Evaluation for Perchloroethylene Supplemental
Information: Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (U.S. EPA. 2019a) for statistical distribution for each model input parameter.
The following sections discuss uncertainties in the occupational exposure assessment.
Number of Workers
There are a number of uncertainties surrounding the estimated number of workers potentially
exposed to PCE, as outlined below. Most are unlikely to result in a systematic underestimate or
overestimate but could result in an inaccurate estimate.
CDR data are used to estimate the number of workers associated with manufacturing. There are
inherent limitations to the use of CDR data as they are reported by manufacturers and importers
of PCE. Manufacturers and importers are only required to report if they manufactured or
imported PCE in excess of 25,000 pounds at a single site during any calendar from 2012 to 2015;
as such, CDR may not capture all sites and workers associated with any given chemical. Second,
the estimate is based on information that is known or reasonably ascertainable to the submitter.
CDR submitters (chemical manufacturers and importers) do not always have accurate
information on the number of potentially exposed workers at downstream processing sites.
There are also uncertainties with BLS data, which are used to estimate the number of workers for
the remaining conditions of use. 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 PCE for the assessed conditions of use. 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 PCE exposure differs from the overall distribution of workers in
each NAICS, then this approach will result in inaccuracy.
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 PCE is used in each industry. Designations of which
industries and occupations have potential exposures is nevertheless subjective, and 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.
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Analysis of Exposure Monitoring Data
To analyze the exposure data, EPA categorized individual PBZ data points 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, samples for employees that are expected
to have the highest exposure from direct handling of PCE are categorized as "worker" and
samples for employees that are expected to have lower exposure and do not directly handle PCE
are categorized as "occupational non-user".
Exposures for occupational non-users can vary substantially. Most data sources do not
sufficiently describe the proximity of these employees to the PCE exposure source. As such,
exposure levels for the "occupational non-user" category will have high variability depending on
the specific work activity performed. It is possible that some employees categorized as
"occupational non-user" have exposures similar to those in the "worker" category depending on
their specific work activity pattern.
Some data sources may have a bias. For example, bias may be present if exposure monitoring
was conducted to address concerns regarding adverse human health effects reported following
exposures during use. Similarly, OSHA Chemical Exposure Health Data (CEHD) are obtained
from OSHA inspections, which may be the result of worker complaints, and may provide
exposure results that are generally more conservative than the industry average.
Some scenarios have limited exposure monitoring data in literature, if any. Where few data are
available, the assessed exposure levels are unlikely to be representative of worker exposure
across the entire job category or industry. In addition, exposure data for compliance safety and
health officers may not be representative of typical exposure levels for occupational non-users.
In cases where there was no exposure monitoring data, EPA attempted to identify monitoring
data from similar conditions of use as surrogate. While these conditions of use have similar
worker activities contributing to exposures, it is unknown if the results will be fully
representative of worker exposure across different conditions of use.
Where the sample data set contains six or more data points, the 50th and 95th percentile exposure
concentrations were calculated from the sample to represent central tendency and high-end
exposure levels, using available data. The underlying distribution of the data, and the
representativeness of the available data, are not known. Where discrete data was not available,
EPA used reported statistics (i.e., median, mean, 90th percentile, etc.). Since EPA could not
verify these values, there is an added level of uncertainty.
Near-Field/Far-Field Model Framework
The near-field/far-field approach is used as a framework to model inhalation exposure for many
conditions of use. The following describe uncertainties and simplifying assumptions generally
associated with this modeling approach:
• There is some degree of uncertainty associated with each model input parameter. In
general, the model inputs were determined based on review of available literature. Where
the distribution of the input parameter is known, a distribution is assigned to capture
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uncertainty in the Monte Carlo analysis. Where the distribution is unknown, a uniform
distribution is often used. The use of a uniform distribution will capture the low-end and
high-end values but may not accurately reflect actual distribution of the input parameters.
• The model assumes the near-field and far-field are well mixed, such that each zone can
be approximated by a single, average concentration.
• All emissions from the facility are assumed to enter the near-field zone. This assumption
will overestimate exposures and risks in facilities where some emissions do not enter the
airspaces relevant to worker exposure modeling.
• The exposure models estimate airborne concentrations. Exposures are calculated by
assuming workers spend the entire activity duration in their respective exposure zones
(i.e., the worker in the near-field and the occupational non-user in the far-field). Since
vapor degreasing and cold cleaning involve automated processes, a worker may actually
walk away from the near-field during part of the process and return when it is time to
unload the degreaser. As such, assuming the worker is exposed at the near-field
concentration for the entire activity duration may overestimate exposure.
• For certain PCE applications (e.g. vapor degreasing and cold cleaning), PCE vapor is
assumed to emit continuously while the equipment operates (i.e. constant vapor
generation rate). Actual vapor generation rate may vary with time. However, small time
variability in vapor generation is unlikely to have a large impact in the exposure estimates
as exposures are calculated as a time-weighted average.
• The exposure models represent model workplace settings for each PCE condition of use.
The models have not been regressed or fitted with monitoring data.
Each subsequent section below discusses uncertainties associated with the individual model.
Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model
For the other industrial uses and waste handling, disposal, treatment, and recycling conditions of
use, the Tank Truck and Railcar Loading and Unloading Release and Inhalation Exposure
Model is used to estimate the airborne concentration associated with generic chemical loading
scenarios at industrial facilities. Specific uncertainties associated with this model are described
below:
• After each loading event, the model assumes saturated air containing PCE that remains in
the transfer hose and/or loading arm is released to air. The model calculates the quantity
of saturated air using design dimensions of loading systems published in the OPW
Engineered Systems catalog and engineering judgment. These dimensions may not be
representative of the whole range of loading equipment used at industrial facilities
handling PCE.
• The model estimates fugitive emissions from equipment leaks using total organic
compound emission factors from EPA's Protocol for Equipment Leak Emission
Estimates ( ), and engineering judgement on the likely equipment type
used for transfer (e.g. number of valves, seals, lines, and connections). The applicability
of these emission factors to PCE, and the accuracy of EPA's assumption on equipment
type are not known.
• The model assumes the use of a vapor balance system to minimize fugitive emissions.
Although most industrial facilities are likely to use a vapor balance system when
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loading/unloading volatile chemicals, EPA does not know whether these systems are used
by all facilities that potentially handle PCE.
Vapor Degreasing and Cold Cleaning Models
The conveyorized vapor degreasing, web degreasing, and cold cleaning assessments use a near-
field/far-field approach to model worker exposure. In addition to the uncertainties described
above, the vapor degreasing and cold cleaning models have the following uncertainties:
• To estimate vapor generation rate for each equipment type, EPA used a distribution of the
emission rates reported in the 2014 NEI for each degreasing/cold cleaning equipment
type. NEI only contains information on major sources not area sources. Therefore, the
emission rate distribution used in modeling may not be representative of degreasing/cold
cleaning equipment emission rates at area sources.
• The emission rate for conveyorized vapor degreasing is based on equipment at a single
site and the emission rates for web degreasing are based on equipment from two sites. It
is uncertain how representative these data are of a "typical" site.
• EPA assumes workers and occupational non-users remove themselves from the
contaminated near- and far-field zones at the conclusion of the task, such that they are no
longer exposed to any residual PCE in air.
Brake Servicing Model
The aerosol degreasing assessment also uses a near-field/far-field approach to model worker
exposure. Specific uncertainties associated with the aerosol degreasing scenario are presented
below:
• The model references a CARB study ( 00) on brake servicing to estimate use
rate and application frequency of the degreasing product. The brake servicing scenario
may not be representative of the use rates for other aerosol applications involving PCE.
• The CARB study (CARB 2000) presented 13 different aerosol degreasing formulations
containing PCE. For each Monte Carlo iteration, the model determines the PCE
concentration in product by selecting one of 13 possible formulations, assuming the
distribution for each formulation is equal to that found in a survey of brake cleaning
shops in California. It is uncertain if this distribution is representative of other geographic
locations within the U.S.
• Some of the aerosol formulations presented in the CARB study ( 000) were
provided as ranges. For each Monte Carlo iteration the model selects a PCE concentration
within the range of concentrations using a uniform distribution. In reality, the PCE
concentration in the formulation may be more consistent than the range provided.
Dry Cleaning Model
The multi-zone dry cleaning model also uses a near-field/far-field approach. Specific
uncertainties associated with the dry cleaning scenario are presented below (see also Section
2.4.1.16):
• The model assumes each facility only has one dry cleaning machine, cleaning one to
fourteen loads of garments per day. The number of machines is based on the 2010 King
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County, WA survey (Whittaker and Joh an son 2011) where 96 percent of 151 respondents
reported having only one machine at their facility. It is uncertain if this distribution is
representative of other geographic locations in the U.S. Larger facilities are likely to have
more machines, which could result in additional PCE exposures.
• The model conservatively uses a hemispherical volume based on the dry cleaning
machine door diameter as the near-field for machine unloading. The small near-field
volume results in a large spike in concentration when the machine door is opened, where
any residual PCE solvent is assumed to be instantaneously released into the near-field. In
reality, the residual solvent will likely be released continuously over a period of time. In
addition, the worker may move around while unloading the garments, such that the
worker's breathing zone will not always be next to the machine door throughout the
duration of this activity. Therefore, these assumptions may result in an overestimate of
worker exposure during machine unloading.
• Many of the model input parameters were obtained from von Grote (2003), which is a
German study. Aspects of the U.S. dry cleaning facilities may differ from German
facilities. However, it is not known whether the use of German data will under- or over-
estimate exposure.
• The model does not cover all potential worker activities at dry cleaners. For example,
workers could be exposed to PCE emitted due to equipment leaks, when re-filling PCE
solvent into dry cleaning machines, when interrupting a dry cleaning cycle, or when
performing maintenance activities (e.g., cleaning lint and button traps, raking out the still,
changing solvent filter, and handling solvent waste) (OSHA 2005). However, there is a
lack of information on these activities in the literature, and the frequency of these
activities is not well understood. The likelihood of equipment leaks is dependent on
whether the machines are properly maintained. The frequency of solvent re-filling
depends on a specific dry cleaner's workload and solvent consumption rate, which is also
affected by the presence of leaks. Based on observations reported by NIOSH (2010) and
Blando ( ), solvent charging is not performed every day. EPA was unable to develop
a modeling approach for these exposure activities due to the lack of available
information.
Modeled Dermal Exposures
The Dermal Exposure to Volatile Liquids Model used to estimate dermal exposure to PCE in
occupational settings. The model assumes a fixed fractional absorption of the applied dose;
however, fractional absorption may be dependent on skin loading conditions. The model also
assumes a single exposure event per day based on existing framework of the EPA/OPPT 2-Hand
Dermal Exposure to Liquids Model and does not address variability in exposure duration and
frequency.
2.4.2 Consumer Exposures
EPA evaluated PCE exposure resulting from the use of relevant consumer products and
consumer articles. EPA gathered and evaluated consumer exposure information according to the
process described in the Application of Systematic Review in TSCA Risk Evaluations (]j S J
2018b). PCE concentrations measured in residential air or personal breathing zone samples are
reported in Section 2.4.2.1. Monitoring and/or controlled laboratory data were available for a
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limited number of consumer use scenarios. To fill data gaps, EPA utilized a modeling approach
to estimate PCE exposure via use of consumer products and articles (Section 2.4.2.3 and Section
2.4.2.4, respectively).
2.4.2.1 Overview and Literature Summary
Concentrations of volatile organic compounds, such as PCE, are often higher in indoor air than
outdoor air due to their presence in consumer products and articles (Lehmann et al. 2002;
Fishbein 1992; Thomas et; [)• In developed counties, people generally spend 90% of their
time indoors (de Bias et al. 2012; Fishbein 1992). and indoor air quality can be greatly
compromised due to volatile emissions from cleaning agents, dry cleaned clothes, adhesives,
paints and other commercial and consumer products (Canada 2017; de Bias et al. 2012; D'Souza
et al. 2009; Lehmann et al. 2002; Thomas et 1).
Systematic review was conducted to identify consumer specific exposure data for PCE
containing products and articles (data evaluation tables are available in the Draft Risk Evaluation
for PCE Systematic Review Supplemental File Data Quality Evaluation of Consumer Exposure
Studies). The literature review returned limited information about chemical-specific consumer
monitoring. Most results from the systematic review pertained to indoor air and personal
breathing zone concentrations of PCE in residential and consumer settings. Monitoring sites
included the United States, Canada, Mexico, Sweden, Finland, Estonia, Lithuania, Belgium,
United Kingdom, France, Austria, Germany, Poland, Slovakia, Czech Republic, Hungary,
Romania, Bulgaria, Serbia, Bosnia and Herzegovina, Italy, Portugal, Malta, Greece, Cyprus,
Albania, Netherlands, China, Japan, Saudi Arabia and Hong Kong.
EPA identified 19 acceptable studies from the United States and Canada deemed to be in the
scope of this risk assessment, which monitored residential or commercial indoor air for PCE
concentrations, for a total of 3172 measured samples. Identified studies were conducted between
the years 1980 and 2013. The detection frequency of PCE in the identified studies ranged from
30% to 100%) detection, with a median of 95% detection (with 4 studies not reporting detection
frequency). Measured PCE concentrations in indoor air ranged from non-detects (detection limits
varied) 94985 ug/m3, with reported central tendency (mean) values ranging from 0.2 ug/m3 to
58348 ug/m3. The maximum air concentration of PCE was measured in a do-it-yourself laundry
facility with coin-operated dry cleaning machines (Howie 1981). Full data extraction details for
residential indoor air samples conducted in schools and commercial establishments in the US and
Canada is provided in the Draft Risk Evaluation for PCE Data Extraction for Consumer and
Aquatic Exposure Monitoring Studies.
Of the identified studies, 11 pertained to air concentrations of PCE limited to residential homes
in the United States and Canada (Table 2-61). Residential indoor air monitoring studies were
conducted between 1986 and 2010, with roughly 1,900 samples collected across eleven US states
(CA, CO, IL, IN, MA, MI, MN, NJ, NY, OH, and TX) and Canada (exact location not reported).
Concentrations ranged from non-detect (limits varied) to 171 |ig/m3. The highest concentration
was from the Canadian study (Chan et al. 1990). which sampled air concentration in Canadian
residences. The next highest concentration was 78 |ig/m3, collected from inner-city homes in
New York, New York (Sax et al. 2004). Maximum concentrations of approximately 30 |ig/m3
were detected in garages in Boston, Massachusetts (Podsom et al. 2008) and in living areas of
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4833 industrial, urban, and suburban homes in Michigan Ola et al. 2008a). All other maximum
4834 reported concentrations were less than 14 |ig/m3. Measures of central tendency (average or
4835 median) across all datasets were less than 7 |ig/m3, except for the Canadian study at 28.1 |ig/m3.
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4836
4837 Table 2-62 Residential Indoor Air Concentrations (liu'iii^) ofPCT. in (lie United Stales aiicl Canada
Sliulj 111lo
Silo Description
IH-lcclion
limit
Min.
Moiin
CM Moduli
M;i\.
\ iirhiiiiT
l);il;i Qu;ili(>
Killing
( ).
Dciroil. Ml area. Humes in I2<>)
U ()') I
\l)
u "I
()2(i
1 ^ "
1 (¦(¦
11 lull
US, 2009-2010
with asthmatic children, sampled
(SD)
(n= 126; DF = 0.91)
in living rooms and bedroom
(Batterman et al. 2007); US,
Southeast MI; Homes (n = 15)
0.069
--
0.6
..
4.4
1.2
High
2005
sampled in various locations in
(SD)
(n= 15; DF = 0.73)
the home (upstairs, downstairs)
(Batterman et al. 2007);
Southeast MI; Garages of
0.069
--
0.3
..
1.6
0.5
High
US, 2005
residences (n = 15)
(SD)
(n= 15; DF = 0.33)
(Jia et al. 2008a):
Ann Arbor, Ypsilanti, and
0.02
ND
0.93
0.39
27.84
--
Medium
US, 2004-2005
Dearborn MI; Homes (n=159) in
(n = 252; DF = 0.99)
industrial, urban, and suburban
cities over two seasons
(Dodson et al. 2008)a:
Boston, MA; Garage of
0.07-0.17
ND
2.8
0.3
31
7.8
High
US, 2004-2005
residences
(95th)
(SD)
(n= 16; DF = 0.81)
(Dodson et al. 2008)a;
US, 2004-2005
Boston, MA; Apartment hallway
of residences
0.07-0.17
ND
1.9
0.8
11
(95th)
3.4
(SD)
High
(n= 10; DF = 0.9)
(Dodson et al. 2008)a;
Boston, MA; Basement of
0.07-0.17
ND
1.7
0.5
1.7
0.92
High
US, 2004-2005
residences
(95th)
(SD)
(n = 52; DF = 0.98)
(Dodson et al. 2008)a;
Boston, MA; Interior room of
0.07-0.17
ND
1.9
0.6
8.6
3.1
High
US, 2004-2005
residences
(95th)
(SD)
(n = 83; DF = 0.92)
(Adeate et al. 2004);
US, 2000
Minneapolis, MN in spring;
Sampling from room where child
--
ND
(10th 0.02)
--
0.4
1
(90th)
--
Medium
(n= 113; DF = 0.949)
spent the most time.
(Adeate et al. 2004);
US, 2000 (n=113; DF = 0.98)
Minneapolis, MN in winter;
Sampling from room where child
spent the most time.
ND
(10th 0.02)
0.5
1.3
(90th)
Medium
(Sax et al. 2004);
Los Angeles, CA in fall; Homes
0.15
0.6
1.8
1.3
6.8
1.4
High
US, 2000
(n= 32; DF = 1)
in inner-city neighborhood
(SD)
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Siiulj Inlo
Silo Description
IH-lcclion
limit
Min.
Mo.iii
CM Moduli
M;i\.
\ iirhiiiiT
l);il;i Qu;ili(>
Killing
(Sax et al. 2004);
Los Angeles, CA in winter;
0.15
0.7
2.3
1.9
11
1.9
High
US, 2000
Homes in inner-city
(SD)
(n = 40; DF = 1)
neighborhood
(Sax et al. 2004);
New York, NY in summer;
0.15
ND
5.3
2
43
8.7
High
US, 1999
Homes in inner-city
(SD)
(n = 30; DF = 0.78)
neighborhood.
(Sax et al. 2004);
New York, NY in winter; Homes
0.15
0.8
6.7
3.5
78
13.1
High
US, 1999
(n= 36; DF = 1)
in inner-city neighborhood.
(SD)
(Clayton et al. .1.999);
IL, IN, OH, MI, MN, WI (Great
--
ND
5.82
1.89
6.83
--
High
US, 1995-1997
Lakes Region); Non-
(90th)
(n = 402; DF = 0.571)
institutionalized persons
fSu et al 20.1.3 V3:
Elizabeth, NJ; Houston, TX; and
0.21
--
1.85
0.82
6.03
4.53
Medium
US, 1999-2001
(n = 539; DF = NR)
Los Angeles, CA; Non-smoking
households (n=310)
(95th)
(SD)
(Van Winkle and Sctieff 2001);
Southeast Chicago, IL; Urban
--
0.54
2.61
2.17
4.74
2.15
High
US, 1994-1995
(n = 48; DF = 1)
homes (n=10) sampled over a 10-
month period from the kitchen in
the breathing zone.
(90th)
(SD)
(Lindstrom et al. .1.995);
Denver, CO; Homes, occupied
0.14
ND
0.66
0.33
1.99
--
Medium
US, 1994
(n=9)
(n = 9; DF = 0.89)
(Chan et al. .1.990);
Homes (n=6), main floor
--
2
6.2
..
18
--
Medium
CA, 1987
(n = 6; DF = 1)
(Chan et al. .1.990);
Homes (n=12), main floor
--
1
28.1
..
171
--
Medium
CA, 1986
(n= 12; DF = 1)
483 8 Study Info: The information provided includes the HERO ID and citation; country and year samples collected; number of samples and detection frequency.
4839 Abbreviations: If a value was not reported, it is shown in this table as ND = not detected at the reported detection limit. GM = geometric mean. DF =
4840 detection frequency. NR = Not reported. US = United States. CA = Canada
4841 Parameters: All statistics are shown as reported in the study. Some reported statistics may be less than the detection limit; the method of handling non-detects
4842 varied by study. All minimum values determined to be less than the detection limit are shown in this table as "ND". If a maximum value was not provided, the
4843 highest percentile available is shown (as indicated in parentheses); if a minimum value was not provided, the lowest percentile available is shown (as indicated in
4844 parentheses).
4845 a Samples from this study (Dodson et at. 2008) were collected as part of the BEAMS study.
4846 b Samples from this study (Su et at. 20.1.3) were collected as part of the RIOPA study.
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EPA identified 20 acceptable studies conducted outside of North America (Mexico, and the
previously listed countries in Europe, Asia and the Middle East), for a total of 4369 measured
samples. Identified studies were conducted between the years 1981 and 2015. The detection
frequency of PCE in the identified foreign studies ranged from 30% to 100% detection, with a
median of 100% detection (with 12 studies not reporting detection frequency). Measured PCE
concentrations in indoor air ranged from non-detects (detection limits varied) to 9.63xl04 ug/m3,
with reported central tendency (mean) values ranging from 0.46 ug/m3 to 4.95xl03 ug/m3. The
maximum air concentration of 9.63xl04 ug/m3 was measured near a photocopy shop (Kiurski et
al. 2016). The next highest reported concentration was 2.48xl04 ug/m3 in a vehicle exposed to
dry cleaned articles (Gulyas and Hemmerling 1990). The highest PCE concentration measured in
residential air was 245 ug/m3 measured in urban homes in Paris, France (Roda et al. ). Full
data extraction details for indoor residential air samples, from studies conducted within and
outside of North America, is provided in the Draft Risk Evaluation for PCE Data Extraction for
Consumer and Aquatic Exposure Monitoring Studies.
Personal Breathing Zone
Concentrations of PCE in personal breathing zone measurements are reported in Table 2-62 for
seven US studies. Overall, the measured concentration dataset contains approximately 3,000
samples that were collected between 1981 and 2001, and represents time spent in various
microenvironments (i.e., home, school, work, transit) during the monitoring period (48- to 72-hr
periods in four studies, and 3-hr, 12-hr, and/or 6-day periods for the remainder). Only the 3-hr
samples from Heavner (1995) represent time inside the home only. Concentrations ranged from
non-detects (detections limits varied) to 659 |ig/m3. The highest concentration was observed in
NHANES survey data from 1999-2000 (Jia et al. 2008a). The study notes that two participants
had exposure to highly elevated levels of PCE; one participant spent more time than usual at
work/school and the other participant worked with paint thinners, brush cleaners, or strippers as
well as glues, adhesives, hobbies or crafts, and also reported having new carpet installed in the
past 6 months. The 95th percentile concentration for the NHANES study was 18.5 |ig/m3.
Maximum reported concentrations in other studies were less than 11 |ig/m3 (including the 90th or
95th percentile if a maximum was not provided). Median values ranged from 0.4 to 2 |ig/m3;
whereas, average values were higher, reaching a maximum of approximately 30 |ig/m3 (Sexton
et al. 2007; Clayton et al. 1999). Full data extraction details for personal breathing zone samples,
from studies conducted within and outside of North America, is provided in the Draft Risk
Evaluation for PCE Data Extraction for Consumer and Aquatic Exposure Monitoring Studies.
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Table 2-63. Personal Breathing Zone Air Concentrations (|ig/m3) for
JCE in the United States (General/Residential)
Study Info
Type
Site/Population Description
Detection
Limit
Min. Mean GM Median Max. Variance
Data Eval.
Score
(Su etal. 2013 V
US, 1999-2001
(n=544; DF = NR)
48-hr
Elizabeth, NJ; Houston, TX;
and Los Angeles, CA;
Adults (n=309) and children
(n=l 18) from 310 non-
smoking households.
0.21
7.17 - 0.89 6.82 112.35
(95th) (SD)
Medium
(Jia et al. 2008b)1,
US, 1999-2000
(n=665; DF = 0.69)
48- to
72-lir
Nation-wide; Adults (ages
20-59 years) in NHANES
study
0.42
ND 5.2 1.0 0.7 659.1 31.2 (SD);
(0.1) (18.5- 4.1 (GSD)
95th)
Medium
(Adeate et al. 2004)
US, 2000
(n=113; DF = 1)
48-hr
Minneapolis, MN in winter;
children ages 6-10 yrs
0.2 (10th) - 0.4 1.3
(90th)
Medium
(Adeate et al. 2004)
US, 2000
(n=113;DF = 0.966)
48-hr
Minneapolis, MN in spring;
children ages 6-10 yrs
ND - 0.4 0.9
(0.2 10th) (90th)
Medium
(Sexton et al. 2007)
US, 1999
(n=333;DF = 0.997)
48-hr
Minneapolis -St. Paul, MN;
Adults, non-smoking (n=70)
living in three neighborhoods:
(inner-city, blue-collar/near
manufacturing plants, and
affluent)
ND 27.8 - 0.9 6.4 (90th)
(0.3 10th)
High
(Clavtonet al. 1999)°
US, 1995-1997
(n=386;DF = 0.613)
6-day
IL, IN, OH, MI, MN, WI
(Great Lakes Region); Non-
institutionalized persons
ND 31.92 - 1.98 10.78
(90th)
High
(Hcavncr et al. 1995)d
US, 1991
(n=25; DF = NR)
3-lirs (in
home
only)
Columbus, OH; Non-smoking
(n=25) women with smoking
husbands
ND 0.89 - 0.68 3.78 0.96
(SD)
Medium
(Hcavncr et al. 1995)d
US, 1991
(n=24; DF = NR)
3-lirs (in
home
only)
Columbus, OH; Non-smoking
women (n=24) with non-
smoking husbands
ND 1.24 - 0.7 5.13 1.46
(SD)
Medium
(Wallace 1987Y5
US, 1981-1984
(n=772; DF = 0-0.97)
12-lirs
Elizabeth and Bayonne, NJ,
Los Angeles, CA, and Contra
Costa, CA; Adults s in
industrial/chemical
manufacturing and /or
petroleum refining regions of
the US.
5.6 to 45 -
High
4882
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Abbreviations: If a value was not reported, it is shown in this table as ND = not detected at the reported detection limit. GM = geometric mean. GSD =
geometric standard deviation. DF = detection frequency. NR = Not reported. US = United States.
Parameters: All statistics are shown as reported in the study. Some reported statistics may be less than the detection limit; the method of handling non-detects
varied by study. All minimum values determined to be less than the detection limit are shown in this table as "ND". If a maximum value was not provided, the
highest percentile available is shown (as indicated in parentheses); if a minimum value was not provided, the lowest percentile available is shown (as indicated in
parentheses).
a Samples from this study (Su et a I. 20.1.3) were collected as part of the RIOPA study. The study notes that PCE exposures increased by visiting a drvcleaner.
b Samples from this study (Jia et at. 2008b) were collected as part of the NHANES 1999-2000. Two measurements with high values (659 and 490 (ig /m3) were
more than five times higher than the next measurement. These two participants did not report dry cleaning exposure, breathing fumes from or using dry cleaning
fluid or spot remover. One participant spent an unusually large amount of time at work/school and another subject worked with paint thinners, brush cleaners, or
strippers as well as glues, adhesives, hobbies or crafts, and also reported having new carpet installed in the past 6 months.
0 Samples from this study (Clayton et a I. .1.999) were collected as part of the N HEX AS Phase 1 field study.
d In Heavner (.1.995). elevated concentrations of PCE were associated with wearing dry cleaned clothes (p<0.05) when all homes were combined, but not for
smoking and non-smoking separately. Statistical power was low since only 2 of 49 participants wore dry cleaned clothes within the previous week.
e Samples from this study (Wallace .1.987) were collected as part of the TEAMS study.
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4907
4908
4909
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2.4.2.2 Consumer Exposure Approach and Methodology
Consumer exposures to PCE are expected via inhalation and dermal routes based on physical-
chemical properties and identified consumer uses. PCE can be found in consumer and/or
commercial products that are readily available for public purchase at common retailers ((U.S.
EPA. 2017f). Sections 3, 4 and 5) and can therefore result in exposures to consumers and
bystanders (non-product users that are incidentally exposed to the product). The magnitude of
exposure depends upon the concentration of PCE products, use patterns (including frequency,
duration, amount of product used, room of use) and application methods. Several consumer
product use scenarios were analyzed based on identified PCE products and articles available to
consumers, including solvents for cleaning and degreasing, lubricants and greases, adhesives and
sealant chemicals, paints and coatings, mold release products, metal and stone polishes, and
exposure to recently dry cleaned articles. Consumer exposure to elevated indoor air
concentrations of PCE due to the use of coin-operated dry cleaning machines and retail print-
shops was summarized based on available literature.
Consumer product application activities include using aerosol and liquid products for spraying,
wiping, immersive cleaning and painting. Other activities include pouring and applying various
types of liquids and pastes. Information regarding use patterns and application methods was
obtained from national solvent usage surveys (Westat 1987). as well as EPA's Consumer
Exposure Model (CEM) Version 2.1 (see CEM 2.1 User Guide ( )). PCE weight
fractions and product densities of PCE containing products were compiled from publicly
available product MSDS or SDS documents (Material Safety Data Sheet or Safety Data Sheet,
see EPAs Preliminary Information on Manufacturing, Processing, Distribution, use and Disposal:
Tetrachloroethylene (2017fT). If product densities were not reported, the product density was
estimated based on reported mass percent composition of the product relative to constituent
densities. Other physical-chemical parameters for PCE are referenced in the Scoping and
Problem Formulation documents.
2.4.2.2,1 Routes of Exposure
Inhalation
Consumer and bystander inhalation exposure to PCE-containing products primarily include
direct inhalation of vapors, mists and aerosols (e.g., aerosols from spray applications) and
indirect inhalation exposures after application. EPA assumed mists are absorbed via inhalation,
rather than ingestion, due to deposition of vapors and mists in the upper respiratory tract. The
magnitude of inhalation exposure depends upon the concentration of PCE in products, use
patterns (including frequency, duration, amount of product used, room of use) and application
methods. Several product types and scenarios were analyzed for inhalation exposure including
spray adhesives, spray lubricants, spray paints and primers, spray degreasers (brake and engine
cleaning, parts cleaning and electronics cleaning), spray protectants and stain removers.
Consumer inhalation exposure to PCE emitted from recently dry cleaned articles was also
evaluated. Given the high vapor pressure of PCE, products used in the liquid form are also likely
to result in inhalation exposure to consumers and bystanders. PCE containing liquid product use
categories include parts cleaners and degreasers, stone and marble polishes, adhesives and
sealants, ceramic overglaze, and paint primers.
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4950
4951
4952
4953
4954
4955
4956
4957
4958
4959
4960
4961
4962
4963
4964
4965
4966
4967
4968
4969
4970
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Dermal
Consumer dermal exposure to PCE-containing products occurs via vapor or mist deposition onto
the skin, or via direct contact with liquids during product use, and direct contact with treated
articles (U.S. EPA. 2012d). PCE is absorbed dermally, and exposure magnitude depends on
exposure characteristics such as skin surface area, product volume, chemical loading and weight
fraction, and exposure duration. PCE is a volatile solvent, expected to evaporate from skin
quickly. However, there are certain consumer use scenarios for which product evaporation may
be limited, for example due to immersion of hands into a reservoir of cleaning solvent
(reasonable given that consumers are not assumed to use PPE, as well as the nature of PCE
containing products and uses), the wearing of recently dry cleaned fabrics, or handling/wiping
using a solvent soaked rag. Consumer uses analyzed for dermal exposure with impeded
evaporation include immersive parts cleaning, aerosol degreasers, liquid stone and marble
polishes, liquid sealants, liquid paint primers and the wearing of recently dry cleaned articles.
Ingestion
Consumers may be exposed to PCE via transfer of chemical from hand to mouth. However, this
exposure pathway is expected to be limited by a combination of dermal absorption and high
volatilization of PCE. Due to the expected very low magnitude of accidental hand to mouth
exposure, EPA did not further assess this pathway.
from Disposal
EPA does not expect exposure to consumers from disposal of consumer products. It is
anticipated that most products will be disposed of in original containers, particularly those
products that are purchased as aerosol cans.
2.4,2,2,2 Modeling Approach
EPA estimated consumer exposures for all currently known use scenarios for products containing
PCE. A variety of sources were reviewed during the Systematic Review process to identify these
products and/or articles, including Safety Data Sheets (SDS), National Institutes of Health (NIH)
Household Products Database, the Chemical and Products (CPCat) Database, Peer-reviewed and
gray literature and the Kirk-Othmer Encyclopedia of Chemical Technology.
Consumer exposures were assessed for all PCE containing products identified as available for
consumer purchase, as described in EPAs Preliminary Information on Manufacturing,
Processing, Distribution, use and Disposal: Tetrachloroethylene (201 If). No chemical-specific
personal monitoring data was identified during Systematic Review, except in the case of
exposure to PCE from recently dry cleaned articles, and indoor air concentrations from coin-
operated laundry and printshop proximity. Due to the lack of consumer monitoring data, a
modeling approach was used to estimate potential consumer exposures. EPA's Consumer
Exposure Model ( ) was selected as the most appropriate model for PCE
consumer product use scenarios, as described in below and in the Draft Risk Evaluation for PCE
Supplemental Information on Consumer Exposure. CEM was used to estimate indoor air
concentrations of PCE and dermal exposure to PCE in certain scenarios, generated from the use
of consumer products. Consumer exposure to recently dry cleaned fabrics was also estimated,
based on reasonably available monitoring data. Inhalation exposure due to off-gassing from
recently dry cleaned articles was assessed using EPA's Multi-Chamber Concentration and
Page 208 of 636
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4990
4991
4992
4993
4994
4995
4996
4997
4998
4999
5000
5001
5002
5003
5004
5005
5006
5007
5008
5009
5010
5011
5012
5013
5014
5015
5016
5017
5018
5019
5020
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Exposure Model (MCCEM, ( e)), and dermal exposure due to wearing dry cleaned
articles was assessed using CEM, as described in the Draft Risk Evaluation for PCE
Supplemental Information on Consumer Exposure.
EPA's Consumer Exposure Model was chosen based on model relevance to consumer use
scenarios, the in-model database of consumer relevant default parameters, and model flexibility
to modify parameters when chemical-specific information is available. CEM was also preferred
because it does not require chemical- and/or product-specific emission data, as is required to run
more complex indoor/consumer models. CEM is a deterministic model utilizing user provided
input parameters and/or assumptions to generate exposure estimates. A full discussion of CEM
features and general parameterization can be found in the Draft Risk Evaluation for
Perchloroethylene Supplemental Information on Consumer Exposure ( JOf).
Model parameters were determined based on physical chemical properties and product
information (e.g., product density, water solubility, vapor pressure, etc.), use-specific consumer
survey data (Westat (1987); e.g., duration of use, frequency of use, mass of product used per
event, etc.), and where applicable, model scenario defaults (e.g., room of use, activity patterns,
air exchange rates, environment volume). A negligible background concentration of PCE was
assumed for all scenarios. Room of use was selected based on either CEM scenario default room
of use or a Westat survey category room of use (often in agreement with one another), based on
professional judgement. The CEM model does not currently accommodate outdoor scenarios.
For products that are intended to be used outdoors, modifications to the CEM inputs were made
to simulate an outdoor scenario by adjusting Zone 1 parameters (which represents the room of
use or use environment). In modeling caulk and column adhesives, the garage was selected as the
room of use, but the room volume was changed to 16 m3 to represent a half-dome chemical cloud
around the person using the product. Additionally, the air exchange rate for Zone 1 was set to
100 to reflect the high rate between the cloud and the rest of outside. The interzonal ventilation
rate was set to 0, which effectively blocks the exchange of air between Zone 1 and the rest of the
house. Thus, the concentrations users are exposed to inside the home after product use is zero. In
the outside scenario, bystanders in the home are assumed to have zero exposures. However,
bystanders in the outdoor environment were not modeled, but could potentially be exposed to
similar levels as the user.
While inhalation exposure can be acute or chronic in nature, EPA does not expect consumer
exposure to be chronic in nature because product use patterns tend to be infrequent with
relatively short durations of use. As a result, we only present the acute consumer results in this
risk evaluation. Acute exposures were defined as those occurring within a single day; whereas
chronic exposures were defined as exposures comprising 10% or more of a lifetime (
201 la). In addition to exposure doses, indoor air concentrations were estimated and reported as
maximum 24 hour time-weighted-averages (24 hr TWA).
Thirteen distinct product categories were identified for CEM modeling. Product categories were
assigned based on the physical form of the product (aerosol, liquid, wipe, etc.) and intended use.
See Table 2-64 and Table 2-65 for groupings and the corresponding CEM parameters for each
scenario.
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5049
5050
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5053
5054
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5057
5058
5059
5060
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To characterize the potential range of consumer exposures, modeling for each scenario was
conducted by varying three key parameters while keeping all other input parameters constant.
The key parameters included duration of use per event (minutes/use), amount of chemical in the
product or article (weight fraction), and mass of product or article used per event (gram/use).
Duration of use and mass of product used were assigned to each use category based on the
Westat (1987) survey of consumer behavior patterns. Each scenario was evaluated at a low,
medium, and high value (10th, 50th, and 95th percentiles) for duration of use and mass of product
used, based on the most representative product use category. Product weight fractions were
determined from review of product Safety Data Sheets and any other information identified
during Systematic Review. This input parameter was varied using minimum, mean and
maximum values, unless only a single product was identified for a given use scenario. Input
parameters for PCE containing consumer product scenarios modeled in CEM are given in Table
2-63 and Table 2-64. For full parametrization details see the Draft Risk Evaluation for
Perchloroethylene Supplemental Information on Consumer Exposure ( JOf).
Inhalation Exposure Estimation
Inhalation exposure to PCE containing products was estimated using CEM, which predicts
indoor air concentrations by implementing a deterministic, mass-balance calculation selected by
the user (see CEM 2.1 User Guide ( >) and Draft Risk Evaluation for
Perchloroethylene Supplemental Information on Consumer Exposure ( J0f)). The
model uses a two-zone representation of the building of use, with Zone 1 representing the room
where the consumer product is used and Zone 2 being the remainder of the building. Product
users and bystanders follow prescribed activity patterns and inhale airborne concentrations
determined by the activity zone. All PCE scenarios were assessed using the near-field/far-field
model option to capture the potentially higher concentration in the breathing zone of a product
user during use.
Inhalation exposure to PCE as a result of proximity to recently dry cleaned articles was estimated
using MCCEM ( ), which utilizes chemical- and article-specific emission
parameters to predict indoor air concentrations (see Section 2.4.2.2.2 for further details).
Dermal Exposure Estimation
Dermal exposure to PCE from consumer product use was estimated using CEM's permeability
method (P_DER2b). The permeability method is based on the ability of a chemical to penetrate
the skin layer once contact occurs. The model assumes a constant supply of chemical, directly in
contact with the skin, throughout the exposure duration. Evaporative loss of PCE from the skin
during product use is expected to be considerable, except in cases where the nature of use limits
evaporation, such as from the use of a solvent soaked rag, or immersion of hands in a container
of PCE based cleaner. Only product use scenarios where a reasonable assumption could be made
for limited evaporation from skin were assessed for dermal exposure. A chemical-specific skin
permeability coefficient of 1.8xl0"2 cm/hr was used for permeability estimates CNakai et al.
1999).
Dermal exposure to PCE from recently dry cleaned fabrics was estimated using CEM's direct-
contact article model (A DER2). This model estimates dermal exposure based on the migration
rate of a chemical from an article to the skin, which is governed by the solid phase diffusion
coefficient, in combination with age-specific activity patterns to estimate potential loading on the
skin.
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5077 Exposure Receptors
5078 Consumer use scenarios were assessed for adults (age 21+) and two youth age-groups (16-20
5079 years and 11-15 years) as product users. All other individuals were considered as non-users
5080 (treated as bystanders). CEM was parameterized based on characteristics of exposed populations
5081 and receptor factors (such as age-specific body weight, skin surface area, inhalation rates, etc. all
5082 based on Exposure Factors Handbook ( )); user and bystander activity patterns;
5083 building volumes and air exchange rates; and product use considerations.
5084
5085
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5086 Table 2-64. CEM Consumer Product Modeling Scenarios and Key Product Parameters
Consumer Conditions of
I so
Form
No. or
Products
1 don li lied1
K:iiiiie of
Woiiihl
I'ructions
Identified
c:;. PCF.r
Weight Fi'iielions
Selected lor I so in
Modeling
pei!)
Soloolod
Product
Density
(
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Consumer Conditions of
I so
Form
No. of
Products
Identified'
Riiniic of
\\ eiiilit
I'ructions
Identified
r ;. pc i-:»-
Weight l iiictions
Selected lor I so in
Modeling
("n PCI!)
Selected
Product
Density
(g/ciiiV
Soloolod
( T.M 2.1
Modeling
Scenario4
I'lniission
Model
Applied*
Dorm ;il
l-lxposure
Model
Applied''
Dorm ;il
SA/IJW"
Mill
Mean
Ma\
Livestock Grooming
Adhesive
Aerosol
1
15
15
...
—
1.45
Spray
Fixative
and
Finishing
Spray
Coatings
E3
none
n/a
Column Adhesive; Caulk;
Sealant
Gel/
Liquid
16
5-75
5
48
75
1.19
Caulk
El
None
n/a
Coatings and Primers
Aerosol
10
9-14
9
10
14
1.3952
Aerosol
Spray
Paints
E3
none
n/a
Rust primer; Sealant
Liquid
9
9-11
9
10
11
1.3952
Solvent-
Based Wall
Paint
E2
PDERlb
Face,
hands
and arms
Sealant (Water Shield)
Liquid
1
45
45
...
...
1.28
Solvent-
Based Wall
Paint
E2
PDERlb
Face,
hands
and arms
Metallic Overglaze (for
ceramics)
Liquid
1
20-30
20
30
...
1
Lacquers
and Stains
E2
none
n/a
Marble Polish, Stone
Cleaner
Liquid
Wax
1
85-100
85
95
100
1.4
All
Purpose
Waxes and
Polishes
El
PDERlb
Inside of
both
hands
5087 1 The number of products identified is based on the product lists inEPA's 2017 Preliminary Information on Manufacturing, Processing, Distribution, Use, and
5088 Disposal: Tetrachloroethylene (PCE) (2017:0. It is possible that specific products and/or formulations identified in those reports and used herein to select
5089 appropriate weight fractions, formulation types, and formulation densities for use in modeling no longer contain PCE or are no longer readily available to
5090 consumers for purchase; however, they were still considered for sourcing such information since they were identified as in these recent EPA publications and
5091 therefore represent reasonably-foreseen uses. See Draft Risk Evaluation for Perchloroethylene Supplemental Information for Consumer Exposure (U.S. EPA
5 092 2020D for the full product list utilized.
5093 2 The range in weight fractions is reflective of the identified products containing PCE and not reflective of hypothetical levels or theoretical functionality-based
5094 limits. Weight fractions were sourced from product Safety Data Sheets (SDSs) or Material Safety Data Sheets (MSDSs).
5095 3 Product densities were identified from product SDSs or MSDSs. When density was not reported in product MSDS or SDSs, products with high PCE weight
5096 fractions (>90% PCE) were assumed to have the density of pure PCE (1.62 g/cm3), otherwise the product density was calculated based on the percent
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contribution of each ingredient per the MSDS ingredient list. See See Draft Risk Evaluation for Perchloroethylene Supplemental Information for Consumer
Exposure (U.S. EPA 2020:f) for the full product list utilized.
4 The listed CEM 2.1 modeling scenario reflects the default product options within the model, which are prepopulated with certain default parameters. However,
due to EPA choosing to select and vary many key inputs, the specific model scenario matters less than the associated emission and dermal exposure models (e.g.,
El, E3, P_DER2a).
5 Emission models used for PCE include El - Emission from Product Applied to a Surface Indoors Incremental Source Model, E2 - Emission from Product
Applied to a Surface Indoors Double Exponential Model, E3 - Emission from Product Sprayed, and E5 - Emission from Product Placed in Environment.
6 All product scenarios utilized the P DERlb model for dermal exposure - Dermal Dose from Product Applied to Skin, Permeability Model.
7Suface Area to Body Weight (SA/BW) ratios are default parameters for the selected CEM use scenarios, values are based on central tendency (mean) values
(Exposure Factors Handbook (U.S. EPA 20.1.1a'). CEM 2.1 User Guide (U.S. EPA 2019bV)
8CEM default dermal SABW ratio for the All-Purpose Liquid Cleaner category is one hand, however both hands were modeled for consistency between wax vs.
liquid stone polish use categories.
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5110
Table 2-65. Consumer Product Modeling Scenarios and Key Westat Product Use Parameters
Consumer Conditions of
Use
l-'orm
Selected
W'estat (1987)
Su r\ ev
Scenario1
Room
or I se:
Duration of I se
(Percentile)
(mill)
(lOlli)-* 50th
«>5lh
Mass of Product I sed
(Percentile)
(ii)"1
1 Otli 50th <>5th
Solvent; Cleaner; Marine
cleaner; Degreaser; Coil
cleaner; Electric motor
cleaner ; Parts cleaner; Cable
cleaner; Stainless Steel
Polish; Electrical/Energized
Cleaner; Wire and ignition
demoisturants; Electric
motor cleaner
Aerosol
Solvent-Type
Cleaning Fluids
or Degreasers
Utility
Room
2
15
120
26.83
155.69
1532.91
Parts cleaner
Liquid
Spot Remover
Utility
Room
0.5
(0.25)
5
30
9.91
52.70
441.01
Brake Cleaner
Aerosol
Brake Quieters/
Cleaners
Garage
1
15
120
39.03
156.13
624.52
Vandalism Mark & Stain
Remover; Mold Cleaner;
Weld Splatter Protectant
Aerosol
Solvent-Type
Cleaning Fluids
or Degreasers
Utility
Room
2
15
120
26.83
155.69
1532.91
Stone Polish
Liquid
Solvent-Type
Cleaning Fluids
or Degreasers
Utility
Room
2
15
120
26.83
155.69
1532.91
Cutting Fluid
Liquid
Other
Lubricants
(Excluding
Automotive)
Utility
Room
0.5
(0.08)
2
30
26.83
155.69
1532.91
Spray Lubricant; Penetrating
Oil
Aerosol
Other
Lubricants
(Excluding
Automotive)
Utility
Room
0.5
(0.08)
2
30
4.79
26.35
239.51
Industrial adhesive;
Adhesive; Arts and crafts
Liquid
Contact
Cement, Super
Glues, and
Utility
Room
0.5
(0.33)
4.25
60
1.16
9.68
167.34
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Consumer Conditions of
I se
adhesive; Gun ammunition
sealant
l-'orm
Selected
Westat (1987)
Su r\ ev
Scenario1
Spray
Adhesive s
Room
or I se:
Dura
(l>e
(lot
ion of
rccntili
mill)
i)( 5<
95th
I se
.')
tli
Mas
lOth
s ol' Product
(Percentile)
(Ji)4
501 h
I sed
95th
Livestock Grooming
Adhesive
Aerosol
Contact
Cement, Super
Glues, and
Spray
Adhesive s
Utility
Room
0.5
(0.33)
4.25
60
1.29
10.72
185.23
Column Adhesive; Caulk;
Sealant
Gel/
Liquid
Primers and
Special Primers
(excluding
automotive)
Garage
5
30
360
45.39
387.07
8121.46
Coatings and Primers
Aerosol
Aerosol Spray
Paint
Utility
Room
5
20
120
61.88
330.05
1608.99
Rust primer; Sealant
Liquid
Primers and
Special Primers
(excluding
automotive)
Garage
5
30
360
53.22
453.82
9521.90
Sealant (Water Shield)
Liquid
Outdoor Water
Repellent
Garage
15
60
300
302.8
2422.37
24223.7
4
Metallic Overglaze (for
ceramics)
Liquid
Contact
Cement, Super
Glues, and
Spray
Adhesive s
Utility
Room
0.5
(0.33)
4.25
60
0.89
7.39
127.74
Marble and Stone Polish
Wax
Solvent-Type
Cleaning Fluids
or Degreasers
Utility
Room
2
15
120
23.18
134.54
1324.74
5111 1 (Westat .1.9871
5112 2 Room of use is either default scenario option within CEM or based on Westat survey data for the specific product use category.
Page 216 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
5113 3 CEM has a minimum timestep of 0.5 min. If the 10th percentile duration of use was less than 0.5 min, then the actual 10th percentile is reported in
5114 parenthesis.
5115 4 Westat Survey scenario data for mass of product used is reported in ounces. The product density was used to convert percentile results from ounces to
5116 grams for use in CEM. As a result, mass of product used will be different for product categories with the same identified Westat Survey use scenario,
5117 but different product densities.
Page 217 of 636
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5118
5119
5120
5121
5122
5123
5124
5125
5126
5127
5128
5129
5130
5131
5132
5133
5134
5135
5136
5137
5138
5139
5140
5141
5142
5143
5144
5145
5146
5147
5148
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
2.4.2.3 Consumer Product Exposure Scenarios
Consumer products were assessed for human user and bystander inhalation exposure, and for user
dermal exposure when it was reasonable to assume that use characteristics would limit product
evaporation from skin. The results of modeled consumer scenarios are presented below, in order of the
consumer product Categories of Use (COUs) identified in Table 2-12 (Crosswalk of Subcategories of
Use).
2.4.2.3.1 Degreasers
PCE containing aerosol-based degreasers were identified as available for consumer use. Two sub-
categories of degreasers were identified, general aerosol degreasers and brake cleaners, based on the
most appropriate use scenario.
2.4.2.3.1.1 Aerosol Cleaners for Motors, Coils, Electrical Parts, Cables, Stainless
Steel and Marine Equipment, and Wire and Ignition Demoisturants
Aerosol-based degreasers for motors, coils, electrical parts, cables, stainless steel and marine equipment,
and wire and ignition demoisturants were identified as available for consumer use, with reported PCE
weight fractions of 10% to 100%. Inhalation and dermal exposures were evaluated users, and inhalation
exposures were evaluated bystanders, for three use scenarios ( Table 2-66 and Table 2-67). Dermal
exposure was considered relevant for this product category due to the large volume of liquid emitted
from the spray can during use, and likelihood of handling product-soaked rags during normal product
use, as per manufacturer instructional videos. Indoor maximum 24-hour time weighted average (TWA)
air concentrations ranged from 1.5 to 869 mg/m3 for users, and 0.3 to 216 mg/m3 for bystanders. Dermal
acute dose rate (ADR) ranged from 0.1 to 74 mg/kg/day across all user age groups.
Table 2-66. Consumer inhalation exposure to PCE during use in degreasers for motors, coils,
electrical parts,
cables, stainless steel and marine equipment, and wire anc
ignition demois
Duration
Weight
Mass I sed
24 hr Max
Scenario
Percentile
l-'raction
Percentile
Kxposed
TWA
Description
(mill)
(%)
21 yr)
0.1
User
(2)
(10)
(26.83)
User, Youth (16-20 yr)
0.1
Page 218 of 636
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5149
5150
5151
5152
5153
5154
5155
5156
5157
5158
5159
5160
5161
5162
5163
5164
5165
5166
5167
5168
5169
5170
5171
5172
5173
5174
5175
5176
5177
5178
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Scenario
Description
Duration
Percentile
(mill)
Weight
l-'raction
(%)
Mass
I sed
Percentile
(S)
Kxposed Ueceptor
(age group)
ADU
(mg/kg/d)
User, Youth (11-15 yr)
0.1
Moderate
Intensity User
50th
(15)
Mean
(80)
50th
(155.69)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
7.2
6.8
7.4
High Intensity
User
95th
(120)
Max
(100)
95th
(1532.91)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
72
68
74
Confidence in the selected model and default parameters is high for inhalation exposure during aerosol
degreasing. The selected model underwent peer review, was designed explicitly for the purpose of this
type of estimation and applied in the manner intended. Confidence in the selected inhalation emission
scenario is high, as there was a good match in CEM. Confidence in the selected model is medium for
dermal exposure during aerosol degreasing. CEM's permeability model assumes limited evaporation,
which is appropriate for aerosol degreasing considering the common use of solvent soaked rags when
using aerosol degreasing products. However, if consumers used this product in such a way that
evaporation was not impeded, then the selected model would be an overestimate of dermal exposure.
Confidence in dermal model default parameters is high due to the high quality of source data.
Confidence in the weight fraction is high as this information was pulled directly from product safety
data sheets (SDSs). Confidence in mass used and duration of use is high due to a good match in the
Westat survey data, which received a high- quality rating during data evaluation and has been applied in
previous agency assessments. The overall confidence in the aerosol degreaser inhalation exposure
estimations is high. The overall confidence in the aerosol degreaser dermal exposure estimations is
medium with possible overestimation of dermal exposures in use scenarios where chemical evaporation
from the hands is not impeded.
2.4.2.3.1.2 Aerosol Brake Cleaners
Aerosol-based degreasers in the form of brake cleaners were identified as available for consumer use,
with reported PCE weight fractions of 40% to 100%. Inhalation and dermal exposures were evaluated
for users, and inhalation exposures were evaluated for bystanders, for three use scenarios (Table 2-68
and Table 2-69). Dermal exposure was considered relevant for this product category due to the large
volume of liquid emitted from the spray can during use, and likelihood of handling product-soaked rags
during normal product use, as per manufacturer instructional videos. Indoor maximum 24-hour time
weighted average (TWA) air concentrations ranged from 5.7 to 250 mg/m3 for users, and 1.6 to 73
mg/m3 for bystanders. Dermal acute dose rate (ADR) ranged from 0.2 to 60 mg/kg/day across all user
age groups.
Table 2-68. Consumer inhalation exposure to PCE during use in brake cleaner
Scenario
Description
Duration
Percentile
(mill)
Weight
l-'raction
(%)
Mass I sed
Percentile
(g)
Kxposed
Ueceptor
24 lir Max
TWA
(nig/nr*)
10th
Min
10th
User
5.7
Page 219 of 636
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5179
5180
5181
5182
5183
5184
5185
5186
5187
5188
5189
5190
5191
5192
5193
5194
5195
5196
5197
5198
5199
5200
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Duration
Weight
Msiss I 'sell
24 hr M;ix
Scenario
Percent ile
l-'raction
Percentile
Kxposed
TWA
Description
(mill)
(%)
(g)
Ueceptor
(ing/nr*)
Low Intensity
User
(1)
(40)
(39.03)
Bystander
1.6
Moderate
50th
Mean
50th
User
59
Intensity User
(15)
(91)
(156.13)
Bystander
15
High Intensity
User1
95th
(120)
Max
(100)
95th
(624.52)
User
Bystander
250
73
'The maximum 24 hr TWI air concentration for the User was the 50th percentile duration -maximum weight fraction-95lh
percentile mass used iteration, with a PCE concentration of 259 mg/m3.
Table 2-69. Consumer dermal exposure
to PCE durin
g use in brake cleaner
Scenario
Description
Duration
Percentile
(mill)
\\ eight
l-'raction
(%)
Mass I seil
Percentile
Kxposctl Ueceptor
(age group)
ADU
(mg/kg/d)
Low Intensity
User
10th
(1)
Min
(40)
10th
(39.03)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
0.2
0.2
0.2
Moderate
Intensity User
50th
(15)
Mean
(91)
50th
(156.13)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
6.7
6.3
6.9
High Intensity
User
95th
(120)
Max
(100)
95th
(624.52)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
59
55
60
Confidence in the selected model and default parameters is high for inhalation exposure during brake
cleaning. The selected model underwent peer review, was designed explicitly for the purpose of this
type of estimation and applied in the manner intended. Confidence in the selected inhalation emission
scenario is high, as there was a good match in CEM. Confidence in the selected model is medium for
dermal exposure during brake cleaning. CEM's permeability model assumes limited evaporation, which
is appropriate for brake cleaning considering the common use of solvent soaked rags when using brake
cleaning products. However, if consumers used this product in such a way that evaporation was not
impeded, then the selected model would be an overestimate of dermal exposure. Confidence in dermal
model default parameters is high due to the high quality of source data. Confidence in the weight
fraction is high as this information was pulled directly from product safety data sheets (SDSs).
Confidence in mass used and duration of use data is high due to a good match in the Westat survey data,
which received a high- quality rating during data evaluation and has been applied in previous agency
assessments. The overall confidence in the brake cleaner inhalation exposure estimations is high. The
overall confidence in the brake cleaner dermal exposure estimations is medium with possible
overestimation of dermal exposures in use scenarios where chemical evaporation from the hands is not
impeded.
Page 220 of 636
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5201
5202
5203
5204
5205
5206
5207
5208
5209
5210
5211
5212
5213
5214
5215
5216
5217
5218
5219
5220
5221
5222
5223
5224
5225
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
2,4.2,3,2 Parts Cleaners
Liquid-based parts cleaner (wipe or immersive) was identified as available for consumer use, with
reported PCE weight fraction of 50% to 60%. Inhalation and dermal exposures were evaluated users,
and inhalation exposures were evaluated for bystanders, for three use scenarios (Table 2-70 andTable
2-71). Indoor maximum 24-hour time weighted average (TWA) air concentrations ranged from 0.4 to
161 mg/m3 for users, and 6.5E-02 to 29 mg/m3 for bystanders. Dermal acute dose rate (ADR) ranged
from 25 to 2030 mg/kg/day across all user age groups.
Table 2-70. Consumer inhalation exposure to PCE during use in parts cleaners
Duration
Weight
Mass I sed
24 lir Max
Scenario
Percentile
l-'raction
Percentile
K\posed
TWA
Description
(min)
(%)
21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 vr)
25
26
28
Moderate
Intensity User
50th
(5)
Max
(60)1
50th
(52.70)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
296
310
338
High Intensity
User
95th
(30)
Max
(60)
95th
(441.01)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
1780
1860
2030
1A single product was identified for immersive and/or wipe cleaning, with a range given for the weight fraction. The weight
fraction range was evaluated as minimum and maximum, with no average weight fraction used in modeling.
2CEM has a minimum timestep of 0.5 minutes. If the 10th percentile duration is less 0.5 min, then the minimum timestep was
used for modeling, rather than the percentile.
Confidence in the selected model and default parameters is high for inhalation exposure during
immersive parts cleaning estimation, as this model underwent peer review, was designed explicitly for
the purpose of this type of estimation and applied in the manner intended. Confidence in the selected
inhalation emission scenario is high. A generic emission model (E5) was selected in CEM due to the
lack of an existing scenario that would represent a good fit for immersive parts cleaning. However, the
Page 221 of 636
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5226
5227
5228
5229
5230
5231
5232
5233
5234
5235
5236
5237
5238
5239
5240
5241
5242
5243
5244
5245
5246
5247
5248
5249
5250
5251
5252
5253
5254
5255
5256
5257
5258
5259
5260
5261
5262
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
selected emission model is a good fit for this condition of use. Confidence in the selected model is
medium for dermal exposure during immersive parts cleaning. CEM's permeability model assumes
limited evaporation, which is appropriate considering the likelihood of a user immersing their hands in
an immersive cleaning product during use. However, if consumers used this product in such a way that
evaporation was not impeded, then the selected model would be an overestimate of dermal exposure.
Confidence in dermal model default parameters is high due to the high quality of source data.
Confidence in the weight fraction is high as this information was pulled directly from product safety
data sheets (SDSs). Confidence in the mass used and duration of use is medium. Lacking an exact match
in the Westat survey for immersive parts cleaning, the spot remover scenario was selected to
parameterize CEM. The spot remover scenario was of relatively short duration and low mass of product
used, and thus the results may underestimate the inhalation exposure for immersive parts cleaning. The
overall confidence in the immersive parts cleaner inhalation exposure estimations is medium, with
possible underestimation of inhalation exposures. The overall confidence in the immersive parts cleaner
dermal exposure estimations is medium with possible overestimation of dermal exposures in use
scenarios where chemical evaporation from the hands is not impeded.
2.4.2,3.3 Vandalism Stain Removers, Mold Cleaners, and Weld Splatter
Protectants
Aerosol-based mark and stain removers and splatter protectors were identified as available for consumer
use, with reported PCE weight fractions of 5% to 100%. Inhalation exposures were evaluated for users,
and for bystanders, for three use scenarios ( Table 2-72). Indoor maximum 24-hour time weighted
average (TWA) air concentrations ranged from 0.7 to 869 mg/m3 for users, and 0.2 to 216 mg/m3 for
bystanders.
Table 2-72. Consumer inhalation exposure to PCE during use in vandalism stain removers, mold
cleaners, weld s
platter protectants
Duration
Weight
Mass Used
Scenario
Percentile
Fraction
Percentile
Exposed
24 hr Max TWA
Description
(min)
(%)
(?)
Receptor
(mg/m3)
Low Intensify
10th
Min
10th
User
0.7
User
(2)
(5)
(26.83)
Bystander
0.2
Moderate
50th
Mean
50th
User
37
Intensity User
(15)
(40)
(155.69)
Bystander
7.2
High Intensity
95th
Max
95th
User
869
User
(120)
(100)
(1532.91)
Bystander
216
Confidence in the selected model and default parameters is high for estimation of inhalation exposure
during use of stain removers, mold cleaner and splatter protectors, as this model underwent peer review,
was designed explicitly for the purpose of this type of estimation and applied in the manner intended.
Confidence in the selected inhalation emission scenario is high, as there was a good match in CEM.
Confidence in the weight fraction is high as this information was pulled directly from product safety
data sheets (SDSs). Confidence in mass used and duration of use data is high due to a good match in the
Westat survey data, which received a high quality rating during data evaluation and has been applied in
previous agency assessments. The overall confidence in the inhalation exposure estimation for use of
stain removers, mold cleaners and splatter protectors is high.
Page 222 of 636
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5263
5264
5265
5266
5267
5268
5269
5270
5271
5272
5273
5274
5275
5276
5277
5278
5279
5280
5281
5282
5283
5284
5285
5286
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
2,4,2.3,4 Marble Polish
A liquid-based stone polish was identified as available for consumer use, with reported PCE weight
fraction of 10% to 100%. Inhalation and dermal exposures were evaluated users, and inhalation
exposures were evaluated for bystanders, for three use scenarios (Table 2-73 andTable 2-74). Indoor
maximum 24-hour time weighted average (TWA) air concentrations ranged from 3.4 to 911 mg/m3 for
users, and 0.7 to 227 mg/m3 for bystanders. Dermal acute dose rate (ADR) ranged from 1.1 to 739
mg/kg/day across all user age groups.
Table 2-73. Consumer inhalation exposure to PCE during use in marble polish
Duration
Weight
Mass I sed
Scenario
Percentile
Traction
Percentile
Kxposed
24 lir Max TWA
Description
(mill)
(%)
(S)
Receptor
(nig/nr*)
Low Intensity
10th
Min
10th
User
3.4
User
(2)
(10)
(26.83)
Bystander
0.7
Moderate
50th
Mean
50th
User
166
Intensity User
(15)
(85)
(155.69)
Bystander
32
High Intensity
95th
Max
95th
User
911
User
(120)
(100)
(1532.91)
Bystander
227
Table 2-74. Consumer dermal exposure to PCE during use in marble polish
Scenario
Description
Duration
Percentile
(min)
Weight
l-'raction
(%)
Mass I sed
Percentile
te)
Kxposcd Receptor
(age group)
ADR
(mg/kg/d)
Low Intensity
User
10th
(2)
Min
(10)
10th
(26.83)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
1.2
1.1
1.2
Moderate
Intensity User
50th
(15)
Mean
(85)
50th
(155.69)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
77
72
79
High Intensity
User
95th
(120)
Max
(100)
95th
(1532.91)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
722
676
739
Confidence in the selected model and default parameters is high for inhalation exposure during marble
polish use. The selected model underwent peer review, was designed explicitly for the purpose of this
type of estimation and applied in the manner intended. Confidence in the selected inhalation emission
scenario is high, as there was a good match in CEM. The utility room was selected as the room of use
for this scenario. While it is also reasonable to assume that marble polish may be used in the kitchen, the
room volumes are similar and air exchange rates identical, resulting in similar user inhalation exposure.
However, a difference may occur for the bystander inhalation exposure when considering utility room
use versus kitchen use, based on bystander activity patterns. For example, amount of time the bystander
spends in the kitchen is greater than time spent in the utility room, resulting in a lower bystander
inhalation exposure for the utility room scenario. If the product was used in the kitchen, the bystander
inhalation exposure would be greater than estimated, up to the air concentration experienced by the user.
Confidence in the selected model is medium for dermal exposure during marble polish use. CEM's
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5287
5288
5289
5290
5291
5292
5293
5294
5295
5296
5297
5298
5299
5300
5301
5302
5303
5304
5305
5306
5307
5308
5309
5310
5311
5312
5313
5314
5315
5316
5317
5318
5319
5320
5321
5322
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
permeability model assumes limited evaporation, which is appropriate for marble polish considering the
common use of solvent soaked rags when using marble cleaning products. However, if consumers used
this product in such a way that evaporation was not impeded, then the selected model would be an
overestimate of dermal exposure. Confidence in dermal model default parameters is high due to the high
quality of source data. Confidence in the weight fraction is high as this information was pulled directly
from product safety data sheets (SDSs). Confidence in mass used and duration of use data is high due to
a good match in the Westat survey data, which received a high- quality rating during data evaluation and
has been applied in previous agency assessments. The overall confidence in the marble polish user
inhalation exposure estimations is high, with possible underestimation of bystander inhalation exposures
if the room of use changed. The overall confidence in the marble polish use dermal exposure estimations
is medium with possible overestimation of dermal exposures in use scenarios where chemical
evaporation from the hands is not impeded.
2.4.2.3.5 Cutting Fluid
Cutting fluid was identified as available for consumer use, with a reported PCE weight fraction of 10%.
Inhalation exposures were evaluated for users, and inhalation exposures were evaluated for bystanders,
for three use scenarios ( Table 2-75). Indoor maximum 24-hour time weighted average (TWA) air
concentrations ranged from 1.4 to 91 mg/m3 for users, and 0.3 to 19 mg/m3 for bystanders.
Table 2-75. Consumer inhalation exposure to PCE during use in cutting fluids
Duration
Weight
Mass Used
24 hr Max
Scenario
Percentile
Fraction1
Percentile
Exposed
TWA
Description
(min)
(%)
(g)
Receptor
(mg/m3)
Low Intensify
10th
Single
10th
User
1.4
User
(0.08)2
(10)
(26.83)
Bystander
0.3
Moderate
50th
Single
50th
User
8.5
Intensity User
(2)
(10)
(155.69)
Bystander
1.7
High Intensity
95th
Single
95th
User
91
User
(30)
(10)
(1532.91)
Bystander
19
1A single product was identified for cutting fluid, with a single weight fraction reported.
2CEM has a minimum timestep of 0.5 minutes. If the 10th percentile duration is less 0.5 min then the minimum timestep was
used for modeling, rather than the percentile.
Confidence in the selected model and default parameters is high for estimation of inhalation exposure
during use of cutting fluids, as this model underwent peer review, was designed explicitly for the
purpose of this type of estimation and applied in the manner intended. Confidence in the selected
inhalation emission scenario is high, as there was a good match in CEM. Confidence in the weight
fraction is high as this information was pulled directly from product safety data sheets (SDSs).
Confidence in mass used and duration of use data is high due to a good match in the Westat survey data,
which received a high quality rating during data evaluation and has been applied in previous agency
assessments. The overall confidence in the inhalation exposure estimation during use of cutting fluids is
high.
2.4.2.3.6 Lubricants and Penetrating Oils (aerosol)
Aerosol-based lubricants and penetrating oils were identified as available for consumer use, with
reported PCE weight fractions of 5% to 100%. Inhalation exposures were evaluated for users, and
Page 224 of 636
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5324
5325
5326
5327
5328
5329
5330
5331
5332
5333
5334
5335
5336
5337
5338
5339
5340
5341
5342
5343
5344
5345
5346
5347
5348
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
inhalation exposures were evaluated for bystanders, for three use scenarios ( Table 2-76). Indoor
maximum 24-hour time weighted average (TWA) air concentrations ranged from 0.1 to 142 mg/m3 for
users, and 2.6E-02 to 29 mg/m3 for bystanders.
Table 2-76. Consumer inhalation exposure to PCE during use in lubricating and penetrating oils
Duration
Weight
24 lir Max
Scenario
Percentile
Fraction
Mass I sed
F.x posed
TWA
Description
(min)
(%)
Percentile (g)
Ueceptor
(mg/iir*)
Low Intensity
10th
Min
10th
User
0.1
User
(0.08)1
(5)
(4.79)
Bystander
2.6E-02
Moderate
50th
Mean
50th
User
7.9
Intensity User
(2)
(54)
(26.35)
Bystander
1.6
High Intensity
95th
Max
95th
User
142
User
(30)
(100)
(239.51)
Bystander
29
1CEM has a minimum timestep of 0.5 minutes. If the 10th percentile duration is less 0.5 min, then the minimum timestep was
used for modeling, rather than the percentile.
Confidence in the selected model and default parameters is high for estimation of inhalation exposure
during use of aerosol lubricants and penetrating oils, as this model underwent peer review, was designed
explicitly for the purpose of this type of estimation and applied in the manner intended. Confidence in
the selected inhalation emission scenario is high, as there was a good match in CEM. Confidence in the
weight fraction is high as this information was pulled directly from product safety data sheets (SDSs).
Confidence in mass used and duration of use data is high due to a good match in the Westat survey data,
which received a high quality rating during data evaluation and has been applied in previous agency
assessments. The overall confidence in the inhalation exposure estimation during use of aerosol
lubricants and penetrating oils is high.
2.4.2.3.7 Adhesives
Industrial adhesives, arts and crafts adhesives, and gun ammunition sealant was identified as available
for consumer use, with PCE weight fractions of 10% to 100%. Inhalation exposures were evaluated for
users, and inhalation exposures were evaluated for bystanders, for three use scenarios ( Table 2-77).
Indoor maximum 24-hour time weighted average (TWA) air concentrations ranged from 0.2 to 90
mg/m3 for users, and 3.8E-02 to 23 mg/m3 for bystanders.
Table 2-77. Consumer inhalation exposure to PCE during use in adhesives
Duration
Weight
Mass I sed
24 lir Max
Scenario
Percentile
l-'raction
Percentile
Kxposed
TWA
Description
(min)
(%)
(g)
Ueceptor
(mg/iir")
Low Intensity
10th
Min
10th
User
0.2
User
(0.33)2
(30)
(1.16)
Bystander
3.8E-02
Moderate
50th
Mean
50th
User
4.9
Intensity User
(4.25)
(89)
(9.68)
Bystander
1.0
High Intensity
95th
Max
95th
User
90
User1
(60)
(100)
(167.34)
Bystander
23
Page 225 of 636
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5350
5351
5352
5353
5354
5355
5356
5357
5358
5359
5360
5361
5362
5363
5364
5365
5366
5367
5368
5369
5370
5371
5372
5373
5374
5375
5376
5377
5378
5379
5380
5381
5382
5383
5384
5385
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
'The maximum 24 lir TWA air concentration for the User was the 50th percentile duration-maximum weight fraction-95th
percentile mass used iteration, with a PCE concentration of 94 mg/m3.
2CEM has a minimum timestep of 0.5 minutes. If the 10th percentile duration is less 0.5 min then the minimum timestep was
used for modeling, rather than the percentile.
Confidence in the selected model and default parameters is high for estimation of inhalation exposure
during adhesive use, as this model underwent peer review, was designed explicitly for the purpose of
this type of estimation and applied in the manner intended. Confidence in the selected inhalation
emission scenario is high, as there was a good match in CEM. Confidence in the weight fraction is high
as this information was pulled directly from product safety data sheets (SDSs). Confidence in mass used
and duration of use data is high due to a good match in the Westat survey data, which received a high
quality rating during data evaluation and has been applied in previous agency assessments. The overall
confidence in the inhalation exposure estimation during use of adhesives is high.
2.4.2,3.8 Livestock Grooming Adhesive (aerosol)
Livestock grooming adhesive spray was identified as available for consumer use, with a reported PCE
weight fraction of 15%. Inhalation exposures were evaluated for users, and inhalation exposures were
evaluated for bystanders, for three use scenarios ( Table 2-78). Use was modeled indoors, as product
may be used a or horse stable or other enclosed space. Indoor maximum 24-hour time weighted average
(TWA) concentrations ranged from 0.1 to 15 mg/m3 for users, and 2.1E-02 to 3.7 mg/m3 for bystanders.
Table 2-78. Consumer inhalation exposure to PCE during use in livestock grooming adhesive
Duration
Weight
Mass Used
24 hr Max
Scenario
Percentile
Fraction1
Percentile
Exposed
TWA
Description
(min)
(%)
(?)
Receptor
(mg/m3)
Low Intensify
10th
Single
10th
User
0.1
User
(0.33)3
(15)
(1.29)
Bystander
2.1E-02
Moderate
50th
Single
50th
User
0.9
Intensity User
(4.25)
(15)
(10.72)
Bystander
0.2
High Intensity
95th
Single
95th
User
15
User
(60)
(15)
(185.23)
Bystander
3.7
1A single product was identified for livestock grooming adhesive, with a single reported weight fraction.
2CEM has a minimum timestep of 0.5 minutes. If the 10th percentile duration is less 0.5 min then the minimum timestep was
used for modeling, rather than the percentile.
3The maximum 24 lir TWA air concentration for the User was the 50th percentile duration -single weight fraction-95th
percentile iteration, with a PCE concentration of 16 mg/m3.
Confidence in the selected model and default parameters is high for estimation of inhalation exposure
during livestock grooming adhesive use, as this model underwent peer review, was designed explicitly
for the purpose of this type of estimation and applied in the manner intended. Confidence in the selected
inhalation emission scenario is high, as there was a good match in CEM. The utility room was selected
as the room of use for this scenario, assuming the product was used as a general spray fixative. If the
product was used in a barn the inhalation exposure would be reduced. Confidence in the weight fraction
is high as this information was pulled directly from product safety data sheets (SDSs). Confidence in
mass used and duration of use data is high due to a good match in the Westat survey data, which
received a high quality rating during data evaluation and has been applied in previous agency
assessments. The overall confidence in the inhalation exposure estimation during use of livestock
Page 226 of 636
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5388
5389
5390
5391
5392
5393
5394
5395
5396
5397
5398
5399
5400
5401
5402
5403
5404
5405
5406
5407
5408
5409
5410
5411
5412
5413
5414
5415
5416
5417
5418
5419
5420
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
grooming adhesive is high, but overestimate exposures if the product is used in a barn rather than a
utility room.
2.4.2.3.9 Caulks, Sealants and Column Adhesives
Caulks, sealants and column adhesives were identified as available for consumer use, with reported PCE
weight fractions of 5% to 75%. Inhalation exposures were evaluated for users, for three use scenarios
(Table 2-79). Area of use was assumed to be outdoors, so bystander exposure was not estimated. A
modified garage with a high air exchange rate was used to model outdoor use. Maximum 24-hour time
weighted average (TWA) air concentrations ranged from 5.9E-02 to 159 mg/m3 for users.
Table 2-79. Consumer inhalation exposure to PCE during use in caulks, sealants and column
adhesives
Duration
Weight
Mass I sed
24 lir Max
Scenario
Percentile
Traction
Percentile
K\posed
TWA
Description
(mill)
(%)
(S)
Ueceptor
(m g/nr')
Low Intensity
User
10th
(5)
Min
(5)
10th
(45.39)
User
5.9E-02
Moderate
50th
Mean
50th
User
A Q
Intensity User
(30)
(48)
(387.07)
4.0
High Intensity
User
95th
(360)
Max
(75)
95th
(8121.46)
User
159
Confidence in the selected model and default parameters is high for estimation of inhalation exposure
from caulks, sealants and column adhesives, as this model underwent peer review, was designed
explicitly for the purpose of this type of estimation and applied in the manner intended. Confidence in
the selected inhalation emission scenario is high, as there was a good match in CEM. A modified garage
with a high air exchange rate was used to model outdoor use, resulting in no bystander exposure. Greater
user and bystander inhalation exposure would be expected for use of caulk and column adhesive
products indoors. Confidence in the weight fraction is high as this information was pulled directly from
product safety data sheets (SDSs). Confidence in mass used and duration of use data is medium as there
was not an exact match in the Westat survey data. As such, the primers and special primers (non-
automotive) scenario was selected. It may be that primers are used for longer periods and in larger
quantities than caulks, sealants and column adhesives, and thus the selected scenario may overestimate
inhalation exposure. The overall confidence in the inhalation exposure estimation from caulks, sealants
and column adhesives is medium with the possibility of overestimation based on selected scenario mass
used and duration of use parameters, and/or underestimation of exposures, particularly for bystanders,
based on the assumption of outdoor product use.
2.4.2.3.10 Outdoor Water Shield
Liquid-based outdoor water sealant was identified as available for consumer use, with a reported weight
fraction of 45%. Inhalation and dermal exposures were evaluated for users, and inhalation exposures
were evaluated for bystanders, for three use scenarios ( Table 2-80 andTable 2-81). Indoor maximum
24-hour time weighted average (TWA) air concentrations
ranged from 1.5 to 127 mg/m3 for users, and 0.4 to 33 mg/m3 for bystanders. Dermal acute dose rate
(ADR) ranged from 39 to 851 mg/kg/day across all user age groups.
Page 227 of 636
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5424
5425
5426
5427
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5429
5430
5431
5432
5433
5434
5435
5436
5437
5438
5439
5440
5441
5442
5443
5444
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 2-80. Consumer inhalation exposure to PCE during use in outdoor water shield sealants
Duration
Weight
24 hr Max
Scenario
Percentile
Traction1
Mass I 'sod
Kxposed
TWA
Description
(mill)
(%)
Percentile (g)
Ueceptor
(ing/nr*)
Low Intensity
10th
Single
10th
User
1.5
User2
(15)
(45)
(302.8)
Bystander
0.4
Moderate
50th
Single
50th
User
10
Intensity User
(60)
(45)
(2422.37)
Bystander
3.4
High Intensity
95th
Single
95th
User
127
User3
(300)
(45)
(24223.74)
Bystander
33
1A single product was identified for outdoor water shield, with a single reported weight fraction.
2The minimum 24 hr TWA air concentration for the User was the 50th percentile duration-single weight fraction-10lh
percentile mass used iteration, with a PCE concentration of 1.3 mg/m3.
3The maximum 24 hr TWA air concentration for the Bystander was the 50th percentile duration-single weight fraction-95th
percentile mass used iteration, with a PCE concentration of 34 mg/m3.
Table 2-81. Consumer dermal exposure to PCE during use in outdoor water shield sealants
Scenario
Description
Duration
Percentile
(mill)
\\ eight
Traction1
(%)
Mass I sod
Percentile
(S)
Kxposcd Ueceptor
(age group)
ADU
(mg/kg/d)
Low Intensity
User
10th
(15)
Single
(45)
10th
(302.8)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
41
39
42
Moderate
Intensity User
50th
(60)
Single
(45)
50th
(2422.37)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
163
155
170
High Intensity
User
95th
(300)
Single
(45)
95th
(24223.74)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
815
774
851
1A single product was identified for outdoor water shield, with a single reported weight fraction.
Confidence in the selected model and default parameters is high for inhalation exposure during use of an
outdoor water sealant. The selected model underwent peer review, was designed explicitly for the
purpose of this type of estimation and applied in the manner intended. Confidence in the selected
inhalation emission scenario is high, as there was a good match in CEM. The garage was selected as the
room of use for this scenario, assuming application of waterproofing sealant to an item that will later be
installed outside. If the product were used outside inhalation exposures would be reduced. Confidence in
the selected model is medium for dermal exposure during use of an outdoor water sealant. CEM's
permeability model assumes limited evaporation, which may be appropriate for liquid sealant
considering a large volume is generally used with significant potential for coating of skin during use.
However, if consumers used this product in such a way that evaporation was not impeded, or dermal
exposure was limited, then the selected model would be an overestimate of dermal exposure. Confidence
in dermal model default parameters is high due to the high quality of source data. Confidence in the
weight fraction is high as this information was pulled directly from product safety data sheets (SDSs).
Confidence in mass used and duration of use data is high due to a good match in the Westat survey data,
which received a high quality rating during data evaluation and has been applied in previous agency
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5448
5449
5450
5451
5452
5453
5454
5455
5456
5457
5458
5459
5460
5461
5462
5463
5464
5465
5466
5467
5468
5469
5470
5471
5472
5473
5474
5475
5476
5477
5478
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
assessments. The overall confidence in inhalation exposure estimations during use of an outdoor water
sealant is high, but possibly overestimates inhalation exposure if the product were to be used outside,
rather than inside a garage. The overall confidence in dermal exposure estimations during use of an
outdoor water sealant is medium with possible overestimation of dermal exposures in use scenarios
where chemical evaporation is not impeded or dermal contact is limited.
2.4.2.3.11 Aerosol Coatings and Primers
Aerosol-based rust primers and battery reconditioners were identified as available for consumer use,
with reported PCE weight fractions of 9% to 14%. Inhalation exposures were evaluated for users and
bystanders, for three use scenarios ( Table 2-82). Indoor maximum 24-hour time weighted average
(TWA) air concentrations ranged from 2.2E-02 to 1.9 mg/m3 for users, and 8.4E-04 to 5.4E-02 mg/m3
for bystanders.
Table 2-82. Consumer inhalation exposure
to PCE during use in aerosol coatings and primers
Duration
Weight
Mass I sed
Scenario
Percentile
Iraction
Percentile
Ex posed
24 lir Max TWA
Description
(mill)
(%)
(Ł)
Ueceptor
(nig/nr*)
Low Intensity
10th
Min
10th
User
2.2E-02
User
(5)
(9)
(61.88)
Bystander
8.4E-04
Moderate
50th
Mean
50th
User
0.2
Intensity User
(20)
(10)
(330.05)
Bystander
5.3E-03
High Intensity
95th
Max
95th
User
1.9
User
(120)
(14)
(1608.99)
Bystander
5.4E-02
Confidence in the selected model and default parameters is high for estimation of inhalation exposure
from use of aerosol coatings and primers, as this model underwent peer review, was designed explicitly
for the purpose of this type of estimation and applied in the manner intended. Confidence in the selected
inhalation emission scenario is high, as there was a good match in CEM. Confidence in the weight
fraction is high as this information was pulled directly from product safety data sheets (SDSs).
Confidence in mass used and duration of use data is high as there is a good match in the Westat survey
data. The overall confidence in the inhalation exposure estimation from use of aerosol coatings and
primers is high.
2.4.2.3.12 Liquid Primers and Sealants
Rust Primer
Liquid-based rust primer and sealant was identified as available for consumer use, with reported PCE
weight fractions of 9% to 11%. Inhalation and dermal exposures were evaluated for users, and inhalation
exposures were evaluated for bystanders, for three use scenarios (Table 2-83andTable 2-84). Indoor use
was assumed as a more conservative estimate of consumer exposure. Consumer exposure would likely
be lower if the product was used outdoors. Indoor maximum 24-hour time weighted average (TWA) air
concentrations ranged from 1.1E-03 to 0.3 mg/m3 for users, and 8.8E-05 to 4.9E-02 mg/m3 for
bystanders. Dermal acute dose rate (ADR) ranged from 2.8 to 272 mg/kg/day across all user age groups.
Page 229 of 636
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5481
5482
5483
5484
5485
5486
5487
5488
5489
5490
5491
5492
5493
5494
5495
5496
5497
5498
5499
5500
5501
5502
5503
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 2-83. Consumer inhalation exposure to PCE during use in rust primers and sealants
Duration
Weight
24 hr Max
Scenario
Percentile
Traction
Mass I sed
Kxposed
TWA
Description
(mill)
(%)
Percentile (g)
Ueceptor
(ing/nr*)
Low Intensity
10th
Min
10th
User
1.1E-03
User1
(5)
(9)
(53.22)
Bystander
8.8E-05
Moderate
50th
Mean
50th
User
9.7E-03
Intensity User
(30)
(10)
(453.82)
Bystander
9.1E-04
High Intensity
95th
Max
95th
User
0.3
User
(360)
(11)
(9521.90)
Bystander
4.9E-02
'The minimum 24 hr TWA air concentration for the User was the 50th percentile duration-minimum weight fraction-10lh
percentile mass used iteration, with a PCE concentration of 1.0E-03 mg/m3.
Table 2-84. Consumer dermal exposure to PCE during use in rust primers and sealants
Scenario
Description
Duration
Percentile
(min)
\\ eight
Kraclion
(%)
Mass I sed
Percentile
(S)
Kxposcd Ueceptor
(age group)
ADU
(mg/kg/d)
Low Intensity
User
10th
(5)
Min
(9)
10
(53.22)
I scr. Adult ( 21 \ i )
User, Youth (16-20 yr)
User, Youth (11-15 yr)
3 i)
2.8
3.1
Moderate
Intensity User
50th
(30)
Mean
(10)
50th
(453.82)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
237
225
247
High Intensity
User
95th
(360)
Max
(11)
95th
(9521.90)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
261
248
272
Confidence in the selected model and default parameters is high for inhalation exposure during use of
liquid rust primers. The selected model underwent peer review, was designed explicitly for the purpose
of this type of estimation and applied in the manner intended. Confidence in the selected inhalation
emission scenario is high as there was a good match in CEM. Confidence in the selected model is
medium for dermal exposure during use of liquid rust primers. CEM's permeability model assumes
limited evaporation, which may be appropriate for liquid rust primers considering a large volume may
be used with potential for coating of skin during use. However, if consumers used this product in such a
way that evaporation was not impeded, or dermal exposure was limited, then the selected model would
be an overestimate of dermal exposure. Confidence in dermal model default parameters is high due to
the high quality of source data. Confidence in the weight fraction is high as this information was pulled
directly from product safety data sheets (SDSs). Confidence in mass used and duration of use data is
high due to a good match in the Westat survey data, which received a high quality rating during data
evaluation and has been applied in previous agency assessments. The product was assumed to be used
indoors, which represents a reasonable, but likely more conservative, exposure estimate than if outdoor
use had been assumed. The overall confidence in inhalation exposure estimations during use of liquid
rust primers is high, however outdoor use would likely result in lower consumer inhalation exposure.
The overall confidence in dermal exposure estimations during use liquid rust primers is medium with
possible overestimation of dermal exposures in use scenarios where chemical evaporation is not
impeded or dermal contact is limited.
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5507
5508
5509
5510
5511
5512
5513
5514
5515
5516
5517
5518
5519
5520
5521
5522
5523
5524
5525
5526
5527
5528
5529
5530
5531
5532
5533
5534
5535
5536
5537
5538
5539
5540
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
2,4,2,3,13 Metallic Overglaze
Metallic overglaze for ceramics was identified as available for consumer use, with a reported PCE
weight fractions of 20 to 30%. Inhalation and dermal exposures were evaluated for users, and inhalation
exposures were evaluated for bystanders, for three use scenarios (Table 2-85. Indoor maximum 24-hour
time weighted average (TWA) air concentrations ranged from 2.6E-03 to 0.5 mg/m3 for users, and 5.4E-
04 to 0.1 mg/m3 for bystanders.
Table 2-85. Consumer inhalation exposure to PCE during use in metallic overglaze
Dm ration
Weight
Mass I sed
24 hr Max
Scenario
Percentile
l-'raction
Percentile
K\posed
TWA
Description
(min)
(%)
(S)
Ueceptor
(ing/nr*)
Low Intensity
10th
Min
10th
User
2.6E-03
User1
(0.33)4
(20)
(0.89)
Bystander
5.4E-04
Moderate
50th
Max
50th
User
3.4E-02
Intensity User2
(4.25)
(30)
(7.39)
Bystander
6.8E-03
High Intensity
95th
Max
95th
User
0.5
User3
(60)
(30)
(127.74)
Bystander
0.1
'The minimum 24 hr TWA air concentration for the User was the 95th percentile duration-minimum weight fraction-10lh
percentile mass used iteration, with a PCE concentration of 2.5E-03 mg/m3.
2 A single product was identified for metallic overglaze, with a range given for the weight fraction. The weight fraction range
was evaluated as minimum and maximum, with no average weight fraction used in modeling.
3The maximum 24 hr TWA air concentration for the User was the 50th percentile duration-maximum weight fraction-95th
percentile mass used iteration, with a PCE concentration of 0.6 mg/m3.
4CEM has a minimum timestep of 0.5 minutes. If the 10th percentile duration is less 0.5 min, then the minimum timestep was
used for modeling, rather than the percentile.
Confidence in the selected model and default parameters is high for estimation of inhalation exposure
from use of metallic overglaze, as this model underwent peer review, was designed explicitly for the
purpose of this type of estimation and applied in the manner intended. Confidence in the selected
inhalation emission scenario is high, as there was a good match in CEM. Confidence in the weight
fraction is high as this information was pulled directly from product safety data sheets (SDSs).
Confidence in mass used and duration of use data is medium as there was not an exact match in the
Westat survey data. As such, the Contact Cement, Super Glues and Spray Adhesives scenario was
selected. Metallic overglaze is sold in small quantities, and thus the 95th percentile mass used for the
selected scenario is likely an overestimate for pottery glazing applications. The overall confidence in the
inhalation exposure estimation from use of metallic overglaze is medium due to possible overestimation
of inhalation exposure for the high intensity user.
2,4,2,3.14 Metal and Stone Polish
Liquid wax-based polishes for metal and stone were identified as available for consumer use, with
reported PCE weight fraction of 85% to 100%. Inhalation and dermal exposures were evaluated for
users, and inhalation exposures were evaluated for bystanders, for three use scenarios (Table 2-86and
Table 2-87). Indoor maximum 24-hour time weighted average (TWA) air concentrations ranged from 11
to 750 mg/m3 for users, and 2.2 to 187 mg/m3 for bystanders. Dermal acute dose rate (ADR) ranged
from 4.1 to 319 mg/kg/day across all user age groups.
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5547
5548
5549
5550
5551
5552
5553
5554
5555
5556
5557
5558
5559
5560
5561
5562
5563
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 2-86. Consumer inhalation exposure to PCE during
use in wax-based metal and stone polish
Duration
Weight
Mass I sed
24 lir Max
Scenario
Percentile
Traction
Percentile
Kxposed
TWA
Description
(mill)
(%)
(S)
Ueceptor
(nig/nr')
Low Intensity
10th
Min
10th
User
11
User
(2)
(85)
(23.18)
Bystander
2.2
Moderate
50th
Mean
50th
User
76
Intensity User
(15)
(95)
(134.54)
Bystander
15
High Intensity
95th
Max
95th
User
750
User
(120)
(100)
(1324.74)
Bystander
187
Table 2-87. Consumer dermal exposure to PCE during use in wax-based metal and stone polish
Scenario
Description
Duration
Percentile
(min)
Weight
Kraclion
(%)
Mass I sed
Percentile
(S)
Kxposed
Ueceptor
(age group)
ADU
(mg/kg/d)
Low Intensity
User
10th
(2)
Min
(85)
10th
(23.18)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
4.4
4.1
4.5
Moderate
Intensity User
50th
(15)
Mean
(95)
50th
(134.54)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
37
35
38
High Intensity
User
95th
(120)
Max
(100)
95th
(1324.74)
User, Adult (>21 yr)
User, Youth (16-20 yr)
User, Youth (11-15 yr)
312
292
319
Confidence in the selected model and default parameters is high for inhalation exposure during use of
liquid wax polishes for metal and stone. The selected model underwent peer review, was designed
explicitly for the purpose of this type of estimation and applied in the manner intended. Confidence in
the selected inhalation emission scenario is high, as there was a good match in CEM. The utility room
was selected as the room of use for this scenario. While it is also reasonable to assume that marble
polish may be used in the kitchen, the room volumes are similar and air exchange rates identical,
resulting in similar user inhalation exposure. However, a difference may occur for the bystander
inhalation exposure when considering utility room use versus kitchen use, based on bystander activity
patterns. For example, amount of time the bystander spends in the kitchen is greater than time spent in
the utility room, resulting in a lower bystander inhalation exposure for the utility room scenario. If the
product was used in the kitchen, the bystander inhalation exposure would be greater than estimated, up
to the air concentration experienced by the user. Confidence in the selected model is medium for dermal
exposure during use of liquid wax polishes for metal and stone. CEM's permeability model assumes
limited evaporation, which is appropriate for marble polish considering the common use of solvent
soaked rags when using marble cleaning products. However, if consumers used this product in such a
way that evaporation was not impeded, then the selected model would be an overestimate of dermal
exposure. Confidence in dermal model default parameters is high due to the high quality of source data.
Confidence in the weight fraction is high as this information was pulled directly from product safety
data sheets (SDSs). Confidence in mass used and duration of use data is high due to a good match in the
Westat survey data, which received a high quality rating during data evaluation and has been applied in
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previous agency assessments. The overall confidence in the liquid wax polishes for metal and stone user
inhalation exposure estimations is high, with possible underestimation of bystander inhalation exposures
if the room of use changed. The overall confidence in the liquid wax polishes for metal and stone dermal
exposure estimations is medium with possible overestimation of dermal exposures in use scenarios
where chemical evaporation from the hands is not impeded.
2.4.2,3.15 Consumer Product Exposure Summary
Consumer exposure to PCE due to use of PCE-containing products was evaluated for 15 product
scenarios. A modeling approach was taken, based heavily on empirical and survey data, to estimate
dermal and inhalation exposures. Ideally, consumer product exposure estimates would be compared to
monitoring data for product use, however such monitoring data was not available in the literature. Air
monitoring data for PCE were collected as background indoor air concentrations, i.e. not during product
use. The North American residential background indoor maximum concentration was 0.17 mg/m3, with
central tendencies at or below 0.028 mg/m3. Modeling estimates represent exposure during active
product use and immediately after. The "moderate intensity user" estimates returned maximum 24-hour
TWA indoor air concentrations for product users between 0.0097 and 166 mg/m3 and bystander
maximum 24-hour TWA indoor air concentrations between 0.009 and 32.2 mg/m3. These estimated
central values are in some instances below monitored central tendency background levels of PCE in
residential air. Estimated central values for users and bystanders exceed the maximum monitored
background concentration by three and two orders of magnitude, respectively, which is reasonable for
direct product contact.
2.4.2.4 Consumer Article Exposure Scenarios
2.4.2.4.1 Literature Summary
PCE is a common dry cleaning solvent used to clean a wide variety of clothing and fabrics. Residual
solvent is emitted from cleaned fabrics during transportation, storage and wear; and the introduction of
dry cleaned articles into residences has been shown to increase indoor PCE. EPA identified
concentrations of PCE in residential indoor air, personal air, and exhaled breath due to the controlled
and monitored introduction of freshly dry cleaned garments in residential homes and apartments (results
summarized in Table 2-88). These studies were conducted in the United States, China, and Japan,
between 1980 and 1996. In all studies, the dry cleaned garments were placed in the bedroom closet, hall
closet, or dresser drawer. Following introduction of the dry cleaned clothes, reported concentrations of
PCE in the indoor air (excluding the storage closet or drawer) ranged from 0.93 to 692 |ig/m3. The
maximum concentration was from a US study ((Hw I), conducted in a rural residential area
outside of Washington DC) in which samples were collected from a closed bedroom after freshly dry
cleaned garments were placed in the bedroom closet. Two other US studies reported slightly lower
maximum concentrations, including 297 |ig/m3 in an experiment conducted in nine homes in NJ by
Thomas (1991) and 195 |ig/m3 in a series of experiments conducted in one test house by Tichenor
(1990). The data in Thomas (1991) showed that PCE levels can increase after bringing freshly dry
cleaned clothes into the home (seven of the nine test homes showed PCE concentrations increases). This
study includes a calculated source strength at four homes and determined that sources of PCE outside
the house were not responsible for observed concentration increases after introduction of dry cleaned
clothing. Personal air concentrations of PCE were higher when test subjects spent more time in the
home, and wearing dry cleaned garments was a less important predictor of personal air concentration
than the number of garments per home volume and number of hours spent in the home. The Tichenor
(1990) study investigated concentrations over a seven-day period for multiple scenarios: storing clothes
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with and without a plastic bag cover, and "airing out" the clothes before bringing them inside. A wide
variation of concentrations was observed in this study. All the experiments, however, showed that PCE
concentrations increased with the introduction of dry cleaned clothes, and levels dropped to near or
below the detection limit after the clothes were removed. The authors also concluded that "airing out" of
the clothing for short time periods does not reduce emissions. Concurrent to measuring concentrations in
a test house, a chamber study was conducted, and modeled concentrations were calculated based on
empirical data. Modeled concentrations were similar to measured concentration, reaching a maximum of
approximately 100 |ig/m3. In the storage location within the homes, the maximum concentration (daily
average) observed in this dataset was 2,900 |ig/m3, as reported by Tichenor ( )).
In addition to homes, a German study (Gulvas and Hemmerling 1990) investigated the concentration of
PCE in a car after driving with a freshly dry cleaned down jacket placed in the car. Prior to introduction,
the concentration inside the car was the same as background ambient concentrations (1 to 2 |ig/m3).
Concentrations increased to a maximum 24,800 |ig/m3 at 108 minutes after article introduction. Another
study. Park (1998). predicted PCE concentration in a car containing freshly dry cleaned clothes, using
the EPA Indoor Air Quality model set to simulate driving a car. The model used emission data from
Tichenor (1990) (initial emission rate of 1.2 mg nr hr"1 and first order rate constant of 3.3 x 10"2 hr"1)
combined with air exchange rates experimentally determined in the study (1 per hour while stopped or
10 per hour while driving). Concentrations peaked at 2,300 |ig/m3 which occurred at the end of a 30-
minute stopped/parking period.
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5630 Table 2-88 Concentrations (jig/m3) of PCE in indoor air, personal breathing zones, and breath from exposure studies with dry
cleaned textiles placed in the
lome or automobile
Siiulj Info
Modiii
Tj |>0
Silo Dosoi'iplion
Dolooliun
l.imil
Siimplo 1)1-'
Si/o
Mill. Moiin M:i\. Diilii
l'.\iiliiiilion
Scoro
Kosirionlhil Homos
rChao et al. 1999V
CN, 1996
24-hr
(indoor
air)
Hong Kong, CN; Residential Home (Site A)
with dry cleaned clothes in closet. Four tests
(each 7 days) in urban 5th floor apartment
bedroom. Windows open and no AC unit.
28 1
1
1
-t
Medium
Hong Kong, CN; Residential Home (Site B)
with dry cleaned clothes in closet. Four tests
(each 7 days) in suburban 2nd floor apartment
bedroom. Windows never opened and AC
occasionally on.
28 1
21 - 494
Medium
Hong Kong, CN; Residential Home (Site C)
with dry cleaned clothes in closet. Four tests
(each 7 days) in urban 10th floor apartment
bedroom. Windows closed when AC on and
windows open when AC off.
28 1
0.93 - 100
Medium
("Thomas et al. 1991)b
US
12-hr
(indoor
air)
Bayonne and Elizabeth, NJ; Living rooms and
bedrooms of nine homes. Six to ten 12-hr
sampling periods per home. Two to ten sets of
dry cleaned clothes were brought into the homes
during the third monitoring period and stored
based on the participants normal procedures. A
resident wore a set of dry cleaned clothes during
a later period. Number of maximum
observations = 18.
8 - 297
(mean of
max =
96±88)
High
12-hr
(personal
air)
Bayonne and Elizabeth, NJ; Six to ten 12-hr
sampling periods per home. Two to ten sets of
dry cleaned clothes were brought into the homes
during the third monitoring period and stored
based on the participants normal procedures.
The resident monitored wore a set of dry cleaned
clothes during a later period. Number of
maximum observations = 7.
1
8 - 303
(mean of
max =
127±108)
High
n/a
(exhaled
breath)
Bayonne and Elizabeth, NJ; Six to ten 12-hr
sampling periods per home. Two to ten sets of
dry cleaned clothes were brought into the homes
during the third monitoring period and stored
based on the participants normal procedures. A
9-61
(mean of
max =
27±20)
High
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Sluclj InIo
Media
1 J pc
Silo Descriplion
Ik-led ion
1 Jin il
Sample 1)1-'
Si/e
Mill. Mean Max. Data
l-'.\a In a I ion
Score
breadi sample was collected al end ol each 12-hr
monitoring period. The resident monitored wore
a set of dry cleaned clothes during a later period.
Number of maximum observations = 9.
("Tichenor et al. 1990)°
US
(indoor
air)
Single story residential house with dry cleaning
placed in closet. Closet door was closed and all
other doors were open. HVAC fan operated.
Samples collected from the closet.
1
100-2,900
(daily avg.)
[model est.
= 200-1,000]
High
Single story residential house with dry cleaning
placed in closet. Closet door was closed and all
other doors were open. HVAC fan operated.
Samples collected from the bedroom.
1
20-195
(daily avg.)
[model est.
= 30-100]
High
Single story residential house with dry cleaning
placed in closet. Closet door was closed and all
other doors were open. HVAC fan operated.
Samples collected from the den.
1
10-80
(daily avg.)
[model est.
= 15-501
High
(Kawauchi and
Nishivama 1989)d
JP
2-hr
(indoor
air)
Consumer homes in Japan (n=4). Dry cleaned
clothes placed in chest of drawers. Samples
collected from 2 to 4 pm during the weekday
inside chest of drawers.
9 1
2.9 - 326.6
Medium
Consumer homes in Japan (n=4). Dry cleaned
clothes placed in chest of drawers. Room air
samples collected from 2 to 4 pm during the
weekday in same room as chest of drawers.
6 1
1.3 - 7.4
Medium
(Howie 1981)e
US, 1980
24-hr
(indoor
air)
Washington, D.C., in late summer; Private home
in rural residential area. Samples collected over
7 days after placing dry cleaned clothing in the
house.
7 1
42.0 - 692
High
Aiilomnhiles
(Gulvas and
Hemmerling 1990")
Germany, 1990
Vehicle with a dry cleaned down jacket placed
in the car.
3 1
9,300 - 24,800
(Park et al. 1998)
n/a
Modeled air concentration in vehicle with dry
cleaned jacket. Assumptions: Volume = 3.24 m3;
surface area of jacket =3.32 m2 initial emission
rate of 1.2 mg/m2/hr and first order rate constant
of 3.3 x 10-2/hr (from Tichenor et al., 1990);
n/a
n/a n/a
2,300
High
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Sluclj InIo
Modi;i
Tj po
Silo Description
Ik'lccl ion
1 Jin il
S;implo Dl-
Si/o
Mill. Moiin M;i\. Diilii
l-'.\;i In ;i 1 ion
Scoro
AER of 1/lu' wliile stopped or lU/lir wliile
driving
Study Info: The information provided includes the HERO ID and citation; country and year samples collected.
Abbreviations: If a value was not reported, it is shown in this table as ND = not detected at the reported detection limit. DF = detection frequency. NR = Not
reported. CN = China. US = United States. JP = Japan. AC = air -conditioning.
Parameters: All statistics are shown as reported in the study.
a Results from this study (Cfaao et a I. .1.999) represent four tests at each of three test sites. Test 1: male clothes kept inside dry cleaner's original plastic bags. Test 2: male
clothes kept outside dry cleaner's plastic bag. Test 3: male and female clothes kept inside dry cleaner's plastic bags. Test 4: male and female clothes kept outside dry
cleaner's plastic bags. Site A: min from Test 2 Day 7 and max from Test 4 Day 2. Site B: min from Test 1 Day 7 and max from Test 4 Day 1. Site C: min from Test 1 Day
2 and max from Test 4 Day 1.
b Results from this study (Thomas et at. .1.99.1.1 represent a summary of the maximum indoor air. personal air. and breath concentrations measured at nine homes after
introduction of dry cleaned clothes. Individual concentration values were not reported in the study. Indoor air (living area/bedroom): min from bedroom and max from
living room. Concentrations before introduction of dry cleaned clothes were also measured for two 12-hr periods. Maximum concentrations ranged from 5 to 64 |ig/m3 in
living room or bedroom, 8 to 35 |ig/m3 in personal air, and 3 to 30 |ig/m3 in breath.
0 Results from this study (Tichenor et at 1990")° represent a summary of daily average indoor air concentrations from a closet (with dry cleaned clothes), bedroom and den
inside a residential home over seven days. The study provided the results (in graph form) for four tests performed during each day of sampling: (1) bag off; (2) bag on; (3)
aired out; and (4) repeat of bag off. Closet: min from Test 1 Day 7 and max from Test 3 Day 1. Bedroom: min from Test 1 Day 7 and max from Test 3 Day 1. Den: min
from Test 1 Day 7 and max from Test 3 Day 2. Model estimates were calculated using a source term based on small chamber data
d Results from this study (Kawauchi and Nishivama .1.989') represent indoor air concentrations from a chest of drawers and a bedroom in four homes.
e Results from this study (Howie .1.98.1.') represent measured indoor air concentrations over a 7 day period (24-hr samples).
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Inhalation exposure to PCE in indoor air due to emissions from storage of dry cleaned articles was
assessed for consumer users and bystanders, using measurements of PCE emissions from fabrics cleaned
with older dry cleaning technologies (2nd and 3rd generation) as a worst-case emission scenario. Dermal
exposure due to direct skin contact with recently dry cleaned fabrics during article wear was assessed for
consumer users, for older and more modern dry cleaning technologies (2nd-5th generation). Preliminary
estimations of inhalation exposure to PCE emissions during article wear was found to be much lower
than either the storage or dermal exposure scenarios and was not further pursued. Dry cleaning
consumer exposures could be cumulative for the user, including inhalation exposure during transport of
dry cleaned articles in an automobile, inhalation exposure from dry cleaned articles stored in the home,
and inhalation and dermal exposure from wearing dry cleaned articles.
Modeling Approach
Dermal exposure to PCE resulting from direct skin contact with recently dry cleaned articles, i.e.
wearing dry cleaned clothing, was modeled with CEM. Inhalation exposure to PCE emitted from
recently dry cleaned articles stored in a home was modeled using EPA's Multi-Chamber Concentration
and Exposure Model (MCCEM). MCCEM is a higher tier model and utilizes chemical-specific
emissions data to estimate air concentrations and inhalation exposure.
2.4.2.4,2 Dermal Exposure to Recently Dry cleaned Articles
EPA's CEM 2.1 dermal sub-model A DER2: Dermal Dose from Skin Contact with Article, as presented
in the CEM user guide ( ) was used to model dermal exposure to PCE from direct
contact with recently dry cleaned articles. This model calculates dermal exposure due to migration of a
chemical within an article to the skin via direct article contact.
Residual Mass
Residual mass of PCE remaining in recently in dry cleaned articles can be thought of as the chemical
"pool", or the amount of chemical potentially available for dermal exposure. Residual PCE mass was
calculated from two sources (see Section 2.4.2.4.2) The first data source, based on Tichenor (1990)
applies to 1st, 2nd and 3rd generation dry cleaning machines, due to the date the study was conducted14.
Tichenor (1990) conducted chamber tests and test house studies to measure emission rates and emission
half-lives of PCE from various commercially dry cleaned fabrics. Residual PCE was calculated using a
simple exponential model based on measured PCE emissions. The second data source, based on
Sherlach (2011). likely applies to 4th and 5th generation dry cleaning machines, due to the date the study
was conducted. Sherlach (2011) extracted perchloroethylene residues from commercially dry cleaned
fabrics after a single cleaning event, multiple cleaning events, and after one week of storage. Cotton,
Polyester and wool fabric were shown to accumulate PCE with subsequent dry cleaning cycles. Multiple
dry cleaning cycle estimates were included to model a high-end user (albeit using more modern
commercial dry cleaners) who has their wool suit dry cleaned weekly, such that residual PCE
14 Perchloroethylene related NESHAPs from 1993 and 2006 banned 1st generation machine and required
more modern technologies for new dry cleaning machines but allowed certain 2nd and 3rd generation
machines to continue to be used. Given the age of 2nd generation dry cleaning technology, it is likely that
only a very small number of these machines are still in use today, but EPA cannot definitively rule out
the possibility of their continued use. Similarly, an unknown but likely small number of 3rd generation
dry cleaning machines may still be in use.
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concentrations become saturated in the fabric (Sherlach (2011) showed that wool continued to
accumulate PCE for at least 6 cleaning cycles). Residual PCE was calculated using reported residual
concentration data and a simple emission model. Residual mass of PCE in dry cleaned fabrics was
calculated for the first three days after the dry cleaning event15. Details of the calculation can be found in
the Draft Risk Evaluation for Perchloroethylene Supplemental Information for Consumer Exposure
(I 020f).
Table 2-89. Cumulative mass released for number of days post dry cleaning and number of hours
the garment was worn (10 hr), based on Tichenor (1990) and Sherlach (2011). Values were used as
modeling inputs for the residual pool of PCE available for exposure.
Data Source
(est. machine generation)
Kabric
Type
Dry cleaning
evenIs
Average Residual Mass (1112)
Time since sirticlc \\;is dry
ck'iiiiod
1 day 2 days 3 days
Tichenor(1990)
(1st-3rd)
Polyester-
wool
blend
Single
105
81
63
Sherlach (201 1)
Polyester1
Single
18
14
11
Sherlach (201 1)
Wool2
Repeat3
58
45
35
1 Based on average maximum measured PCE concentration in polyester fabric samples after single cleaning event
2 Based on average maximum measured PCE concentration in wool fabric samples after multiple cleaning events
3 Residual value used to parameterize model is based on 6th cycle data for wool from Sherlach (2011))
Factors affecting the value of residual mass include fabric type, number and proximity of dry cleaning
events, total number of dry cleaned articles, total article surface area, the type (generation) of dry
cleaning machine used and number of days elapsed since the fabric was dry cleaned. Different fabrics
retain different amounts of PCE, the values estimated here are based on measured emissions from a
variety of fabrics reported in Tichenor (1990) and Sherlach (2011).
Dry cleaned article parameters
An article with a surface area of lm2 and 1.5m2 was assumed to calculate residual mass, with a wearer
donning the garment(s) 1 to 3 days after dry cleaning, for a total duration of 10 hours (assumption of 8-
hour work day, plus commute). An average fabric thickness of 0.1 cm was assumed based on the fabrics
used in the Tichenor (1990) and Sherlach (2011) studies and thickness measurements of various types of
fabrics (based on KiiQiik and Korkmaz (2012); Marolleau (2017); Van Amber (2010). Thickness of
fabric is inversely proportional to dermal dose (as thinner fabrics require less diffusion distance to reach
skin). A single, multi-hour contact per day was assumed for acute exposure.
CEM Dermal Results
15 Measured PCE emissions from recently dry-cleaned fabrics were fit to a simple exponential model to describe the rate of
emission, and thus calculate the residual mass of PCE remaining in the fabric at a certain time after the dry cleaning event.
Residuals were calculated for days 1-3 post-cleaning, as 3 days was roughly one half-life in the fitted decay curve. A
consumer that wore a garment more than three days after dry cleaning would have less potential dermal PCE exposure,
although elevated air concentrations in the home and inhalation exposures would remain unchanged.
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Dermal exposure to PCE due to direct contact with recently dry cleaned articles was evaluated for 1-3
days after dry cleaning, assuming different dry cleaning technologies and for four article thickness
values, for both half-body (1 article) and full body (2 articles) exposure (Table 2-90). ADR results for
half-body exposure ranged from 5.1E-02 to 0.5 mg kg^ day"1. ADR results for full-body exposure
ranged from 0.2 to 1.5 mg kg^ day"1.
Table 2-90. Dermal exposure results to recently dry cleaned articles, based on CEM modeling
Assumed dry
cleaning
technology
Dry
('leaiiin<>
K\ents
Days Alter
Dry
('leaning
1 InM-body Dermal ADR
(Surface Area 1 in .
lull-body Dermal ADR
(Sui lace Aiva 1.5 in .
sAim i:: w)
niij kg-ila\
SAUW M.VM
niij
1
0.5
1.5
2nd and 3rd
generation
Single
2
0.3
1.1
3
0.3
0.9
1
8.7E-02
0.3
4th and 5th
generation
Single
2
6.7E-02
0.2
3
5.1E-02
0.2
1
0.3
0.8
4th and 5th
generation
Repeat1
2
0.2
0.6
3
0.2
0.5
1 Based on maximum average PCE concentration in wool after 6 dry cleaning cycles from Sherlach (2011): PCE
concentration was still increasing in wool fabric after 6 cycles and had not yet reached saturation.
Confidence in the selected model and default parameters is medium to high for dermal exposure due to
wearing recently dry cleaned articles. The selected model underwent peer review, was designed
explicitly for the purpose of this type of estimation and applied in the manner intended. Confidence in
dermal model default parameters is high due to the high quality of source data. Residual PCE remaining
in dry cleaned clothing was determined from high quality test chamber emission data from early
generation dry cleaning machines (dates from 1990), and high-quality analytical data on PCE residuals
from more modern dry cleaning technologies, which leave less residual PCE in dry cleaned fabrics.
CEM's article diffusion model is sensitive to the thickness of material selected. An effort was made to
best match the fabric type and assumed article thickness of the Tichenor (1990) and Sherlach (2011) test
swatches to minimize over- or underestimating residual PCE. The quantity of residual PCE in articles
varies based on fabric type and how much time has elapsed between subsequent dry cleaning events.
Dermal exposure results may differ for other types of fabrics. The overall confidence in dermal exposure
estimations due to wearing recently dry cleaned articles is medium to high with possible overestimation
or underestimation based on differences in PCE retention in various fabric types and frequency of dry
cleaning events.
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2,4.2,4.3 Inhalation Exposure to Recently Dry cleaned Articles
MCCEM Modeling Approach
Inhalation exposure due to emissions of PCE from recently dry cleaned clothing was modeled using
EPA's Multi-Chamber Concentration and Exposure Model (MCCEM, ( ;)) single-
exponential emission model and emissions data available in published literature.
Tichenor (1990) measured PCE air concentrations due to emissions from recently dry cleaned articles in
a test house (EPA's Air and Energy Engineering Research Laboratory, Indoor Air Quality test home). It
is assumed, given the date of the study, that results likely reflect commercial cleaners using 2nd or 3rd
generation dry cleaning machines. Newer technologies are presumed to result in lower residual PCE
concentrations in dry cleaned fabrics, but EPA cannot definitely say that older model machines have
been completely replaced with 4th generation (or later) technologies. As such, Tichenor (1990) was used
for model parameterization as a high end estimate, and based on risk results (see Section 4.2.4.16),
further modeling for 4th and 5th generation technologies was not done. Test house measurements were
conducted by placing freshly dry cleaned garments (wool skirt, two polyester/rayon blouses and a two-
piece wool-blend suit) in a bedroom closet. Indoor air samples were collected at three locations (closet,
bedroom, and den), four times a day.
EPA used this data as a modeling basis to parameterize the MCCEM indoor air model for a generic
residential house (Table 2-91). The EPA/Tichenor test house layout, along with reported house volume
and whole-house air exchange rate (Chang etal. 1998; Tichenor et al. 1990) were used as the basis for a
generic home. EPA assumed the zone of use to be a bedroom closet containing dry cleaned articles,
defined as the near-field volume. The bedroom containing the closet was defined as the far-field volume.
The third zone was termed the "rest of the house" (ROH) and included all areas outside of the bedroom.
A user in this scenario was assumed to be a person who places dry cleaned articles in their bedroom
closet and spends some short amount of time dressing in that closet, twice per day. The CEM activity
pattern for a stay-at-home adult was selected as the basis for an MCCEM adult "user" pattern, with an
addition of 5 minutes spent in the closet (near-field) in the morning and in the evening. A bystander in
this scenario was considered to be a youth or child that remained in the rest of the house. PCE air
concentrations were modeled over a ten-day period. Further details of the MCCEM model
parameterization are given in the Draft Risk Evaluation for Perchloroethylene Supplemental Information
for Consumer Exposure ( 020f).
Table 2-91. Emission parameters for MCCEM modeling of PCE emissions from recently dry
Pa ram el er Name
Value
Source
First order decay rate
0.011 hr"1
Scaled from Tichenor (Tichenor et al.
1990)
Emission rate
7.38 mg/hr
Scaled from Tichenor (Tichenor et al.
1990)
Article surface area1
12.6 m2
Scaled from Tichenor (Tichenor et al.
1990)
MCCEM model house
volume
446 m3
Scaled from Chang (1998)
Closet volume (near-field)
5 m3
Scaled from Chang, (1998)
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Pa ram el er Name
Value
Source
Near-field: far-field air
flow rate
8 m3/hr
Scaled from Chang, (1998)
Whole house air exchange
rate
0.45 hr"1
CEMv2.1 default2
Length of run
240 hr
(10 days)
EPA choice
Background concentration
0 mg/m3
EPA choice
'An article surface area of 12.6 m2 corresponds to roughly seven articles of adult clothing
EPA s Consumer Exposure Model version 2.0 ("2017a)
MCCEM Inhalation Results
Peak PCE air concentrations and maximum 24-hour TWAs for the dry cleaned article storage scenario
are summarized in Table 2-92 and Table 2-93. Maximum PCE air concentrations occurred in the closet
roughly 4 hours after placement of clothing (9.67x10"' mg/m3). Air concentrations in the surrounding
bedroom peaked roughly 7 hours after clothing placement (8.72xl0"2 mg/m3), and 10 hours after
placement for the rest of the house (2.98xl0"2 mg/m3). The maximum 24-hour TWA PCE air
concentrations were 7.24xl0"2 mg/m3 for the user and 2.33xl0"2 mg/m3 for the bystander. Indoor air
concentrations of PCE remained elevated above pre-exposure levels for the duration of the 10-day
modeling window.
Table 2-92. MCEEM calculated PCE air concentrations for storage of recently dry cleaned
articles in a generic house.
/one
.Maximum
Concentration
(mg/iir*)
l ime Klapsed al
.Maximum
(I")
Hour 10
Concentration
(mg/nr')
Closet (near-field)
9.7E-01
3.85
7.3E-02
Bedroom (far-field)
8.7E-02
7.27
6.9E-03
ROH
3.0E-02
9.62
2.4E-03
Table 2-93. MCEEM calculated PCE maximum 24-hour TWAs for storage of recently dry cleaned
articles in a generic house.
Exposure Ueceptor
.Maximum 24-hour
TW A Concentration
(nig/in^)
User (stay-at-home adult)
7.2E-02
Bystander (stay-at-home child or youth)
2.3E-02
Confidence in the selected model and default parameters is medium to high for inhalation exposure
during storage of recently dry cleaned articles in a home closet. Estimated exposures represent a higher-
end scenario where articles have been cleaned at a commercial dry cleaner still employing older
technology. The selected model underwent peer review, was designed explicitly for the purpose of this
type of estimation and applied in the manner intended. Confidence in the parameterization of the
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inhalation emission scenario is high, as there was a high-quality test chamber emission data and test
house monitoring data available, however the total number of studies was limited. The master bedroom
room was selected as the room of use for this scenario. This may underestimate bystander inhalation
exposure, based on activity patterns, relative to storage of dry cleaned articles in a common area of the
house. Residual PCE remining in dry cleaned clothing was determined from high quality test chamber
emission data, using emissions parameters based on older (2nd and 3rd generation) dry cleaning
technologies. More modern dry cleaning technologies presumably leave less residual PCE in dry cleaned
fabrics. Based on risk results (see Section 4.2.4.16), further modeling for more modern dry cleaning
technologies was unnecessary. The quantity of residual PCE in articles varies based on fabric type and
how much time has elapsed between subsequent dry cleaning events. Inhalation exposure results may
differ for other types of fabrics, for more or less frequently dry cleaned articles and based on the number
of dry cleaned items stored. The overall confidence in inhalation exposure estimations due to storage of
recently dry cleaned articles in a home is medium to high with possible overestimation based on the
availability of more modern dry cleaning technologies, and possible overestimation or underestimation
based on differences in PCE retention in various fabric types, frequency of dry cleaning events and
number of dry cleaned items stored.
2.4.2,4.4 Consumer Article Exposure Summary
Consumer exposure to PCE due to off-gassing from recently dry cleaned articles was evaluated for two
scenarios, direct dermal contact with clothing, and inhalation exposure from article storage in a home
closet. A modeling approach was taken, based heavily on empirical data, to estimate dermal and
inhalation exposures. No direct measurements were found for consumer dermal exposure to PCE from
dry cleaned fabrics. Dermal exposure estimates ranged from 5.1E-02 to 1.5 mg/kg/day. Measurements
of PCE concentrations in indoor air from storage of recently dry cleaned articles are in good agreement
with modeling results. Elevated PCE concentrations measured in bedroom air, shortly after dry cleaned
articles were stored in a dresser or closet, were reported as between 9.3E-03 and 0.7 mg/m3, with
modeling estimates for maximum PCE air concentration in the bedroom after article storage of 8.7E-02
mg/m3. Dry cleaning consumer exposures could be cumulative for the user, including inhalation
exposure during transport of dry cleaned articles in an automobile, inhalation exposure from dry cleaned
articles stored in the home, and inhalation and dermal exposure from wearing dry cleaned articles.
2.4.2.5 Other Consumer Uses
Additional potential consumer exposures to PCE were identified, including off-gassing from new
clothing and apparel, due to use of PCE in the textile industry; use of coin operated dry cleaning
machines; and emissions from photocopy and printing equipment. Available data is summarized below.
Due to limited available information on these conditions of use, risk for these scenarios will not be
further assessed.
2.4.2.5.1 New Clothing/Textile Industry
PCE is used to remove spinning oils, lubricants and naturally occurring dirt and oils from yarn and
fabric used in clothing manufacturing, and as a carrier solvent for dyes in the textile industry (Morrison
and Murphy ). While a high percentage of PCE applied to textiles during manufacturing is expected
volatize, there is potential for consumer exposure due to off-gassing from new textiles and fabrics. Chan
(2014) measured PCE in indoor air in apparel stores, with a detection frequency of 30% (120 samples),
and reported mean air concentration of 0.2 |ig/m3.
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2.4.2.5.2 Coin Operated Dry Cleaners
Howie (1981) measured indoor air PCE concentrations in coin-operated dry cleaning facilities in the
United States (6 facilities). PCE was detected in 100% of collected samples, with air concentration range
from 508 to 94984 |ig/m3. EPA was not able to determine if coin operated dry cleaning machines were
still in use in the United States.
2.4.2.5.3 Print Shops
Stefaniak (2000) measured PCE in area and personal breathing zone air samples, in three commercial
print shops in Baltimore, MD. A total of 17 area samples and 4 personal breathing zone samples were
collected, with detection frequencies of 94% and 100%, respectively. PCE concentrations in personal
breathing zone samples ranged from 0.7 to 3.4 |ig/m3, and in area samples from non-detection to 21
|ig/m3.
Ryan (2002) measured PCE in indoor air in a printmaking art studio in a university building in the
United States. 18 samples were collected, with reported PCE concentration mean of 0.4 |ig/m3.
Kiurski (2016) measured elevated PCE levels in a small commercial photocopy shop in Serbia,
containing two copiers and a printer. PCE concentrations were attributed to the usage of photocopying
equipment. A total of 225 samples were collected, with a PCE detection frequency of 64%, and
measured concentration rage of 6.8 to 96341 |ig/m3.
Kowalska and Gierczak (2013) measured volatile emissions from disintegrated office equipment (11
items). PCE was detected most frequently in office equipment samples, with 68.7% detection.
2.4.2.6 Consumer Exposure Assumptions and Key Sources of Uncertainty
Overall, there is medium to high or high confidence in the consumer inhalation exposure modeling
approach and results. This is based on the strength of the model employed, as well as the quality and
relevance of the default, user-selected and varied modeling inputs. CEM 2.1 (U.S. EPA. 2019b) is a peer
reviewed, publicly available model that was designed to estimate inhalation and dermal exposures from
household products and articles. CEM uses central-tendency default values for sensitive inputs such as
building and room volumes, interzonal ventilation rate, and air exchange rates. These parameters were
not varied by EPA due to EPA having greater confidence in the central tendency inputs for such factors
that are outside of a user's control (unlike, e.g., mass of product used or use duration). These central
tendency defaults are sourced from EPA's Exposure Factors Handbook ( 01 la). The
confidence in the user-selected varied inputs (i.e., mass used, use duration, and weight fraction) are
medium to high, depending on the condition of use. The sources of these data are U.S. EPA (1987)
(high-quality) and company-generated SDSs (see EPAs Preliminary Information on Manufacturing,
Processing, Distribution, use and Disposal: Tetrachloroethylene (2Q17D). What reduces confidence for
particular conditions of use is the relevance or similarity of the U.S. EPA (1987) survey product
category for the modeled condition of use. For instance, the evaluated brake cleaner scenario had
surveyed information directly about this condition of use within U.S. EPA (1987). resulting in a high
confidence in model default values. In contrast, the parts cleaner scenario did not have an exact match
within U.S. EPA (1987). resulting in use of a surrogate scenario selected by professional judgement that
most closely approximates the use amount and duration associated with this condition of use.
Additionally, in some cases, professional judgment or surveyed information from U.S. EPA (1987) was
used in selection of room of use, which sets the volume for modeling zone 1.
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Dermal exposure modeling results overall were rated as medium or medium to high confidence. The
processes and inputs described for the inhalation scenarios above are also valid for the dermal exposure
scenarios. While the model used for product dermal exposure estimates was the same as used for the
product inhalation exposure estimates, there is overall medium (vs. high for inhalation) confidence in the
model used due to the used dermal submodel. As described in Section 2.4.2.2.2, the evaluation of dermal
exposures used a permeability submodel, which ignores evaporation and thus is only applicable to use
scenarios for which evaporation is limited, such as during immersion or when handling a solvent-soaked
rag. As a result, model results may overestimate dermal exposure when evaporation is significant, or the
actual contact volume cannot be modeled using a constant bath assumption. This evaluation assumes
consumer exposure under each condition of use is not chronic in nature due to the infrequent use and
short duration of use for a given product. There is a medium uncertainty associated with this assumption
because, although information found during EPA's systematic review process supports infrequent use
and short durations of use, there is a growing consumer practice to complete projects or activities as do
it yourselfers. Do it yourself activities could lead to an increased frequency of product use as well as
using more than one product containing a chemical of concern within a given day. These and other
factors associated with do it yourself activities could result in underestimating consumer exposure
concentrations modeled in this evaluation for the do it yourself consumer.
2.4.3 Potentially Exposed or Susceptible Subpopulations
TSCA requires the risk evaluation "determine whether a chemical substance presents an unreasonable
risk of injury to health or the environment, without consideration of cost of other non-risk factors,
including an unreasonable risk to a potentially exposures of 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."
During problem formulation ( ,018d). EPA identified potentially exposed or susceptible
subpopulations for further analysis during the development and refinement of the life cycle, conceptual
models, exposure scenarios, and analysis plan. In this section, EPA addresses the potentially exposed or
susceptible subpopulations identified as relevant based on greater exposure. EPA addresses the
subpopulations identified as relevant based on greater susceptibility in Section 3.2.5.2.
In developing the draft 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 PCE. Exposures of PCE would be expected to be higher amongst groups living
near industrial facilities, groups with PCE containing products in their homes, workers who use PCE as
part of typical processes, and groups who have higher age and route specific intake rates compared to
the general population.
Of the human receptors identified in the previous sections, EPA identifies the following as potentially
exposed or susceptible subpopulations due to their greater exposure to PCE and considered them in the
risk evaluation:
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Workers and Occupational Non-Users (ONUs)
EPA reviewed monitoring data found in published literature including both personal exposure
monitoring data (direct exposure) and area monitoring data (indirect exposures) and identified data
sources that contain measured monitoring data and or/estimated data for the various conditions of use
(including import and processing of PCE). Exposure estimates were developed for users (males and
female workers of reproductive age) exposed to PCE as well as non-users or workers exposed to PCE
indirectly by being in the same work area of the building. Also, adolescents and female workers of
reproductive age (>16 to less than 50 years old) were also considered as a potentially exposed or
susceptible subpopulations
Consumers/Product Users and Bystanders Associated with Consumer Use
PCE has been identified as being used in products available to consumers. Section 2.4.2.2 provides an
overview of exposure pathways considered for the consumer assessment. Furthermore, EPA identified
consumers and bystanders associated with use of PCE containing consumer products as a potentially
exposed and susceptible subpopulation due to greater exposure. For example, higher-intensity users (i.e.,
those using consumer products for longer durations and in greater amounts) were considered and
evaluated. In addition, consumers are considered to include children and adults over age 11, but
bystanders in the home exposed via inhalation are considered to include any age group, from infant to
adult, including pregnant women and/or women of reproductive age. However, only some individuals
within the general population may use these products. Therefore, those who do use these products are a
potentially exposed or susceptible subpopulation due to greater exposure. Exposures for these
subpopulations are considered and/or evaluated in Section 2.4.2.2.
In developing dermal exposure scenarios, EPA quantified age and sex-specific differences. For PCE,
exposure scenarios that involve potentially exposed or susceptible subpopulations considered age-
specific behaviors, activity patterns, and exposure factors unique to those subpopulations. EPA used the
Exposure Factors Handbook ( ) to inform body weights, intake rates, and body surface
areas for children and adults. Distinct dermal exposure estimates are provided for are provided for adults
(including women of reproductive age) and children (Section 2.4).
For occupational exposures, EPA assessed exposures to workers and ONUs from all PCE conditions of
use (Section 2.4.1). Table 2-94 presents the percentage of employed workers and ONUs whom may
experience either greater exposure or biological susceptibility within select industry sectors relevant to
PCE conditions of use. The percentages were calculated using Current Population Survey (CPS) data for
2017 ( ). CPS is a monthly survey of households conducted by the Bureau of Census for
the Bureau of Labor Statistics and provides a comprehensive body of data on the labor force
characteristics. Statistics for the following subpopulations of workers and ONUs are provided:
adolescents, men and women of reproductive age, and the elderly. For the purpose of this assessment,
EPA considers "reproductive age" as age >16 to less than 50 years old.
As shown in Table 2-95, men make up the majority of the workforce in manufacturing sectors. In other
sectors, women (including those of reproductive age and elderly women) make up nearly half of the
workforce. Adolescents are generally a small part of the total workforce. Table 2-95 presents further
breakdown on the percentage of employed adolescents by industry subsectors. As shown in the tables,
they comprise only 1.2% percent of the manufacturing workforce, and only as high as 3.7% for other
services such as dry cleaning that fall under a COU for PCE.
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Table 2-94. Percentage of Employed Persons by Age. Sex, and Industry Sector
A»c untilp
Sex
Maniilai'luring
\\ holcsalc and
Rclail Trade
Professional and
Business Sen ices
Oilier Sen ices
Adolescent
(16-19 years)
Male
0.8%
3.0%
0.7%
1.4%
Female
0.4%
3.2%
0.5%
1.7%
Reproductive
age3
(16-54 years)
Male
52.9%
42.8%
44.4%
35.2%
Female
22.2%
35.4%
32.8%
38.4%
Elderly (55+)
Male
17.5%
12.3%
13.4%
13.1%
Female
7.3%
9.6%
9.4%
13.3%
a The World Health Organization defines women of reproductive age as ages 15-49 (WHO 2006b")While statistics on
pregnant women are not reasonably available, Labor Force Statistics from the Current Population Survey provides data on the
number of employed female workers by age group, which allows for determination of the number of employed women of
reproductive age. The Bureau of Labor Statistics breaks apart age groups such that age 15 is combined with children, and
ages 44-54 are clustered (U.S. 6LS 20.1.7"). Percentages were calculated using CPS Table 14. "Employed persons in
nonagricultural industries by age, sex, race, and Hispanic or Latino ethnicity", for ages 16-64.
Table 2-95. Percentage o
' Employed Adolescent by Detailed Industry Sector
Sector
Suhseclor
Adolescenl
(l(i-l') >cars)
Manufacturing
All
1.2%
Wholesale and retail trade
Wholesale trade
1.4%
Professional and business
services
Waste management and
remediation services
0.9%
Other services
Repair and maintenance
3.1%
Dry cleaning and laundry services
3.7%
Source: (U.S. 6LS 20.1.7"). Percentage of adolescent calculated using CPS table 18b, "Employed persons by detailed industry
and age."
The CPS uses 2012 Census industry classification, which was derived from the 2012 NAICS. The
Census classification uses the same basic structure as NAICS but is generally less detailed. PCE
conditions of use fall under the following Census industry sectors:
Manufacturing
The Manufacturing sector comprises establishments engaged in the mechanical, physical, or chemical
transformation of materials, substances, or components into new products. Establishments in the sector
are often described as plants, factories, or mills. For PCE, this sector covers most conditions of use that
occur in an industrial setting, including: Manufacturing, Processing as a Reactant, Formulation of
Aerosol and Non-Aerosol Products, the vast majority of facilities likely engaged in Vapor Degreasing
(all degreaser types), Cold Cleaning, Metalworking Fluids, Adhesives, Sealants, Paints and Coatings,
Other Industrial Uses, Industrial Processing Aids and Printing and Copying. This sector also covers
cement manufacturing facilities that may burn waste containing PCE for energy recovery. Also -
Printing and Copying worker information may also be captured under the Information sector (see
below).
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Wholesale and Retail Trade
The wholesale trade sector comprises establishments engaged in wholesaling merchandise, generally
without transformation, and rendering services incidental to the sale of merchandise. Wholesalers
normally operate from a warehouse or office. This sector likely covers facilities that are engaged in the
repackaging PCE or products and formulations containing PCE. The retail trade sector comprises
establishments engaged in retailing merchandise and rendering services incidental to the sale of
merchandise.
Professional and Business Services
This sector comprises establishments that specialize in a wide range of services. This sector covers
waste management and remediation services, which includes establishments that may handle, dispose,
treat, and recycle wastes containing PCE.
Other Services
This sector comprises establishments engaged in providing services not specifically provided for
elsewhere in the classification system. For PCE, this sector covers the vast majority of commercial
repair and maintenance facilities that are likely to use PCE for Aerosol Applications (spray degreasing).
The sector also covers the use of PCE in dry cleaning.
The EPA IRIS Assessment for PCE ( ) also identified the developing fetus as potentially
exposed, as well as infants consuming breastmilk, particularly for mothers with occupational exposure
to PCE or exposure due to proximity to industrial or commercial sources ( ). Infants fed
by formula may also experience increased PCE exposure if PCE is present in drinking water supplies
(i ; r \ :o i _v).
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3 HAZARDS
3.1 Environmental Hazards
3.1.1 Approach and Methodology
EPA reviewed potential environmental health hazards associated with PCE. EPA identified the
following sources of environmental hazard data for PCE: European Chemicals Bureau (ECB) EU Risk
Assessment Report Tetrachloroethylene. Part 1 - environment (ECB 2005) and World Health
Organization (WHO) Concise International Chemical Assessment Document 68; Tetrachloroethylene
WHO (WH02006a).
EPA completed the review of environmental hazard data/information sources during risk evaluation
using the data quality review evaluation metrics and the rating criteria described in the Application of
Systematic Review in TSCA. Risk Evaluations ( !b). The data quality evaluation results
indicated the quality of the studies is mostly 'high' and 'moderate', and these studies were used to
characterize the environmental hazards of PCE. The data evaluation results for PCE environmental
hazard are summarized in Table 3-1.
3.1.2 Hazard Identification
Toxicity to Aquatic Organisms
EPA assigned an overall quality level of high, medium or low to 30 acceptable studies. These studies
contained relevant aquatic toxicity data for fish, aquatic invertebrates, and aquatic plants. As shown in
Table 3-1, EPA identified 10 aquatic toxicity studies as the most relevant for quantitative assessment.
Four of the 10 studies were carried forward for characterizing the potential environmental risks from
PCE. The rationale for selecting these studies is provided in Section 3.1.3 Weight of Scientific
Evidence.
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Table 3-1. Ecological Hazard Characterization of PCE for Aquatic Organisms
Endpoint
Duiitlion
Test
oiliitiiism
I lit/itid
\ ill no'
(m»/l.)
I-! fleet
Kndpoint
(ieomet rie
Mean2
(m a/l.)
References
Diitii Qiiiility
K\ :ilii:i(ion
Acute
Fish
LCsi
4.82-28.1
Mortality
12
Aquatic
invertebrates
LC/EC5l
2.49-18.1
Immobilization
6.7
(Home et at
.1.983: Call et at.
.1.979)
High
(Niederlehner et
at. .1.998:
Richter et at
.1.983: Call et at
1980)
High
Chronic
Fish
ChV
0.5-1.4
Mortality
0.84
Aquatic
invertebrates
ChV
0.37-0.67
Growth
0.5
(Ahmad et at
.1.984)
High
(Call et at
.1.983: Richter et
at .1.983:
Hollister et at
.1.968)
High
EC's,
3.64->500
Biomass
Algae
NOEC/
LOEC
(Brack and
Rottter .1.994:
Hollister et at
High
0.01-0.02
Mortality
1.4E-2
(Labra et at
20.1.0)
Medium
1 Values in the tables are presented as reported by the study authors
2 Geometric mean of definitive values only (i.e. > 48 mg/L was not used in the calculation).
Aquatic Environmental Hazards from Acute Exposures to PCE
Fish: EPA assigned an overall quality level of high for two acute (96-hour; flow-through) fish toxicity
studies, which evaluated the median lethal concentrations (LC50s) of PCE to Oncorhynchus mykiss
(rainbow trout) orMenidia beryllina (inland silverside) (Home et jl Call ci M I0"0). The acute
96-hour LC50 values for fish range from 4.82 mg/L (Call et al. 1979) for (). mykiss to 28 mg/L (Home
et al. 1983) for inland silverside A/, beryllina. As previously identified in the Problem Formulation
document, the acute 96-hour LC 50 value of 4 mg/L (Smith et al. 1991) for flagfish (.Jordanella
floridae) was determined to be a reporting error from the study.
Aquatic Invertebrates: Three studies were assigned an overall quality level of high for acute (48-hour)
toxicity to aquatic invertebrates Ceriodaphnia dubia and Daphnia magna. The studies indicate the 48-
hour EC/LC50 values range from 2.5 mg/L (Niederlehner et al. 1998) to 18 mg/L (Richter et al. 1983;
Call et al. 1980). The geometric mean was calculated from the 48-hour EC50 and LC50 values as 6.7
mg/L. Other salt water aquatic invertebrate toxicities range from 96-hour LC 50 of 2.9 mg/L (Hollister
et al. 1968) for mysid shrimp (Mysidopsis bahia) to 24-hour LC 50 of 23 mg/L (Sanchez-Fortun et al.
1997) for Brine shrimp (Artemia salina). The 48-hour acute toxicity to midge larvae (Tanytarsus
dissimilis) show LC 50 of 31 mg/L and EC50 of 7.0 mg/L (Call et M I ^"9).
Aquatic Environmental Hazards from Chronic Exposures to PCE:
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Fish: A single chronic 32-day toxicity study on exposure of Pimphalespromelas (fathead minnow) to
PCE was assigned an overall quality level of high (Ahmad et al. 1984). The reported NOEL - LOEL
values of 0.5 - 1.4 mg/1, respectively, based on growth and mortality of P. promelas exposure to PCE
(Ahmad etal. 1984). The geometric mean was used to calculate the chronic toxicity value of 0.84 mg/L.
Aquatic Invertebrates: Three studies were assigned an overall quality level of high for chronic (28-day)
toxicity to aquatic invertebrates Daphnia magna (Richter et al. 1983; Call et al. 1980). Americamysis
bahia (opossum shrimp) (Hollister et al. 1968) from exposure to PCE. The D. magna 28-day study
reported a NO EC value of 0.5 mg/L using reproduction based on measured concentrations (Richter et al.
1983; Call et al. 1980). The 28-day A. bahia reported NOEC value of 0.4 mg/L and LOEC of 0.7 mg/L
(Hollister et al. 1968). The geometric mean was calculated from the NOEC and LOEC values to derive
the chronic toxicity value of 0.5 mg/L.
Aquatic Plants: Three studies were assigned an overall quality level of high for EC50 endpoint (Brack
and Rottlci J • >/ 4; Hollister et al. 1968) and medium for NOEC/LOEC (Labra et a I JO 10) from exposure
to PCE. The algal toxicity 72/96-hr EC50 values were 3.6 for Chlamydomonas reinhardtii (Brack 1994)
to greater than 500 mg/L for fresh and saltwater algae (Hollister, 1968) based on biomass and
abundance. The algal species in the Hollister study were not specified. The most conservative toxicity
values were reported for Pseudokirchneriella subcapitata (green microalgae) 72-hour study using
NOEC - 1.0E-2 mg/L and LOEC - 2.0E-2 mg/L based on mortality (Labra et al. 2010). The geometric
mean was calculated from the NOEC and LOEC values to derive the algal toxicity value of 1.4E-2
mg/L.
As noted in the Problem Formulation, EPA did not include PCE hazard toxicity to terrestrial mammals
in this risk evaluation. Observed effects in laboratory mammals that occurred at much higher
concentrations that have been measured or are predicted to occur in the environment. Additionally, as
noted in Section 2.1, the bioconcentration factor and bioaccumulation potential of PCE is low.
Therefore, it is unlikely that adverse effects will occur on the terrestrial mammalian exposure pathway
(Eu 2001).
3.1.3 Weight of Scientific Evidence
During the data integration stage of systematic review EPA analyzed, synthesized, and integrated the
data/information into Table 3-1. This involved weighing scientific evidence for quality and relevance,
using a weight-of-scientific-evidence approach, as defined in 40 CFR 702.33, and noted in TSCA 26(i)
( 018b).
During data evaluation, EPA assigned studies an overall quality level of high, medium, or low based on
the TSCA criteria described in the Application of Systematic Review in TSCA Risk Evaluations (U.S.
EPA. 2018b). While integrating environmental hazard data for PCE, EPA gave more weight to relevant
data/information that were assigned an overall quality level of high or medium. Only data/ information
that EPA assigned an overall quality level of high or medium was used for the environmental risk
assessment. Data that EPA assigned an overall quality level of low was used to provide qualitative
characterization of the effects of PCE exposures in aquatic organisms. Any information that EPA
assigned an overall quality of unacceptable was not used. EPA determined that data and information
were relevant based on whether it had biological, physical/chemical, and environmental relevance (U.S.
I «):
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• Biological relevance: correspondence among the taxa, life stages, and processes measured or
observed and the assessment endpoint.
• Physical/chemical relevance: correspondence between the chemical or physical agent tested and
the chemical or physical agent constituting the stressor of concern.
• Environmental relevance: correspondence between test conditions and conditions in the
environment (U.S. EPA .1.998).
To calculate COCs, EPA derived geometric means for each trophic level that had comparable toxicity
values (e.g., multiple ECsos measuring the same or comparable effects from various species within a
trophic level). EPA did not use non-definitive toxicity values (e.g., ECso > 48 mg/L) to derive geometric
means because these concentrations of PCE were not high enough to establish an effect on the test
organism.
To assess aquatic toxicity from acute exposures, data for two taxonomic groups were available: fish, and
aquatic invertebrates. For each taxonomic group, data were available for multiple species, and geometric
means were calculated as shown in Table 3-1. The geometric mean of the ECsos and LCsos for aquatic
invertebrates, 6.7mg/L, represented the most sensitive toxicity value derived from each of the two
taxonomic groups, and this value was used to derive an acute COC as described in Section 3.1.4. This
value is from two studies that EPA assigned an overall quality of high.
To assess aquatic toxicity from chronic exposures, data for two taxonomic groups were described in the
acceptable literature: fish, and aquatic invertebrates. Aquatic invertebrates were also the most sensitive
taxonomic group for chronic exposures. The chronic 72-hour NOEC = 0.01 mg/L and LOEC = 2.0E-2
mg/L values were used to derive a chronic COC in Section 3.1.4. This value was from two studies that
EPA assigned an overall quality level of high.
To assess the toxicity of PCE to algae, data from three species were available from studies that EPA
assigned an overall quality level of high and medium. ECsos measuring biomass ranged from 3.6 mg/L
to >500 mg/L. A NOEC = 1.0E-2 mg/L and LOEC = 2.0E-2 mg/L was also reported. Because these
values varied by greater than an order of magnitude, EPA used the NOEC/LOEC mortality endpoint for
the most sensitive algal species to represent algae as a whole. These values, from one medium quality
algae study, was used to derive an algae COC in Section 3.1.4.
Based on the estimated bioconcentration factor and bioaccumulation potential described in Section 2.1,
PCE does not bioaccumulate in biological organisms. Therefore, EPA did not assess hazards to aquatic
species from trophic transfer and bioconcentration or accumulation of PCE.
3.1.4 Concentrations of Concern (COC)
EPA calculated the COCs for aquatic species based on the environmental hazard data for PCE, using
EPA methods (\ c. < ^ \ JO I JO I Jb). While there was data representing fish, aquatic invertebrates,
and aquatic plants, the data were not robust enough to conduct a more detailed species sensitivity
distribution analysis. Therefore, EPA chose to establish COC as protective cut-off standards above
which acute or chronic exposures to PCE are expected to cause effects for each taxonomic group in the
aquatic environment. The COC is typically based on the most sensitive species or the species with the
lowest toxicity value reported in that environment. For PCE, EPA derived an acute and a chronic COC
for fish and aquatic invertebrates. Algae was assessed separately and not incorporated into acute or
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chronic COCs, because durations normally considered acute for other species (e.g. 48, 72 hours) can
encompass several generations of algae.
After weighing the scientific evidence and selecting the appropriate toxicity values from the integrated
data to calculate acute, chronic, and algal COCs, EPA applied an assessment factor (AF) according to
EPA methods ( 013. 2012b). when possible. An assessment factor (AF) is applied to the acute
and chronic hazard endpoints for aquatic species to calculate a Concentration of Concern (COC) for use
in the screening-level analysis of environmental hazards. 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 can also account for differences in inter- and intra-species variability,
as well as laboratory-to-field variability. These AFs are dependent on the availability of datasets that can
be used to characterize relative sensitivities across multiple species within a given taxa or species group.
They are often standardized in risk assessments conducted under TSCA, since the data available for
most industrial chemicals are limited. 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. The COC for algae, where
multiple generations can be present over the course of a standard toxicity test, an AF of 10 is used. The
use of these assessment factors are consistent with EPA methodology for the screening and assessment
of industrial chemicals ( 13, 2012b).
After applying AFs, EPA converts COC units from mg/L to |ig/L (or ppb) in order to more easily
compare COCs to surface water concentrations during risk characterization.
Acute COC
To derive an acute COC for PCE, EPA used the geometric mean of the ECsos and LCsos for aquatic
invertebrates, which is the most sensitive acute value for aquatic species from the data integrated for
PCE, from two studies EPA assigned overall quality ratings of high (Niederlehner et al. 1998; Call et al.
1980). The geometric mean of 6.7 mg/L was divided by the AF of five for aquatic invertebrates and
multiplied by 1,000 to convert from mg/L to |ig/L, or ppb.
The acute COC = (6.7 mg/L) / AF of 5 = 1.3 mg/L x 1,000 = 1,342 |ig/L or ppb.
• The acute COC for PCE is 1,342 ppb.
Chronic COC
EPA derived the aquatic invertebrates chronic COC was from the lowest chronic toxicity value from the
integrated data using the geometric mean of NOEC and LOEC for growth effects in opossum shrimp
(Hollister et al. 1968). The geometric mean was then divided by an assessment factor of 10, and then
multiplied by 1,000 to convert from mg/L to |ig/L, or ppb.
The chronic COC = (0.5 mg/L) / AF of 10 = 5.0E-2 mg/L x 1,000 = 50 |ig/L or ppb.
• The aquatic invertebrates chronic COC for PCE is 50 ppb.
EPA also derived a chronic COC for fish for comparison to the aquatic invertebrate chronic data. The
fish chronic COC was derived from the most sensitive chronic toxicity value (ChV) from the integrated
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data using the geometric mean of NOEC and LOEC for measuring mortality in fathead minnow from a
study that EPA assigned a quality level of high (Ahmad et al. 1984). The ChV was then divided by an
assessment factor of 10, and then multiplied by 1,000 to convert from mg/L to |ig/L, or ppb.
The chronic COC = (0.84 mg/L) / AF of 10 = 0.084 mg/L x 1,000 = 84 |ig/L or ppb.
• The fish chronic COC for PCE is 84 ppb.
Algal COC
The algal COC was derived from the integrated data using the geometric mean of NOEC and LOEC
value for algae mortality (Labra et al. ). The algal toxicity value of 0.014 mg/L was then divided by
an assessment factor of 10, and then multiplied by 1,000 to convert from mg/L to |ig/L, or ppb.
The algal COC = (1.4E-2 mg/L) / AF of 10 = 1.4E-3 mg/L x 1000 = 1.4 |ig/L or ppb.
• The algal COC is 1.4 ppb.
3,1,5 Summary of Environmental Hazard
Acute and Chronic Aquatic Toxicity
EPA concludes that PCE presents a hazard for acute exposure duration in aquatic invertebrates, with
acute toxicity values as low as 2.5 mg/L, based on immobilization in Ceriodaphnia dubia and Daphnia
magna (Niederlehner et al. 1998) to 18 mg/L (Call et al. 1980). Acute 96-hour exposures to PCE for fish
based on mortality LCso toxicity values for rainbow trout of 4.8 mg/L to inland silverside of 28 mg/L
(resulting in a geometric mean of 12 mg/L). For chronic exposures to fish, PCE has a hazard values as
low as 0.8 mg/L. For chronic exposure to aquatic invertebrates, PCE has a chronic toxicity value of 0.5
mg/L. In algal species, where exposure durations are considered separate from chronic as they can
encompass several generations of algae, PCE has a chronic toxicity value of 1.4E-2 mg/L.
Concentrations of Concern
The acute and chronic COCs derived for aquatic organisms are summarized in Table 3-2. EPA
calculated the acute COC for PCE exposures in aquatic invertebrates as 1,342 ppb, based on the
geometric mean of ECsos and LCsos from two studies that EPA assigned an overall quality level of high
(Niederlehner et al. 1998; Call et al. 1980). EPA calculated the chronic COC for PCE exposures in
aquatic invertebrates as 50 ppb, based on the geometric mean of NOEC and LOEC for growth from a
single study that EPA assigned an overall quality level of high (Hollister et al. 1968).
For comparison with other trophic levels, EPA calculated the fish chronic COC for PCE of 84 ppb,
based on the geometric mean of the NOEL and LOEL from a single study that EPA assigned an overall
quality level of high (Hollister et al. 1968). As noted previously, algal hazard values from exposures to
PCE, for 96-hour durations, are considered separately from other aquatic species because algae can
cycle through several generations in this time frame. The algal COC of 1.4 ppb is based on the
geometric mean of the NOEL and LOEL from a single study that EPA assigned an overall quality level
of medium (Labra et al. 2010).
Confidence in COCs
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6262 Based on the data quality, weight of scientific evidence, and uncertainties (see Section 4.3.1),
6263 confidence in acute and chronic COCs for fish and invertebrates are high. The COC for algae is based
6264 on a single study that EPA assigned an overall quality level of medium. Additionally, algae species tend
6265 to vary widely in their sensitivity to chemical pollutants, and data were only available for three algal
6266 species and may not represent the most sensitive species at a given site. Therefore, confidence in algae
6267 COC is medium.
6268
6269 Table 3-2. COCs for Environmental Toxicity
Knvironnienlal Aquatic
Toxicity
Hazard Value
(MS/'-)
Assessment
l-'aclor
COC
(u«/l. or pph)
Toxicity to Aquatic Invertebrates
from Acute Exposures
6,710
5
1,342
Toxicity to Aquatic Invertebrates
from Chronic Exposures
500
10
50
Toxicity to Fish from Chronic
Exposures
840
10
84
Algal Toxicity
14
10
1.4
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3.2 Human Health Hazards
3.2.1 Approach and Methodology
EPA used the approach described in Section 1.5 to evaluate, extract and integrate PCE's human health
hazard and dose-response information.
Figure 3-1. EPA Approach to Hazard Identification, Data Integration, and Dose-Response
Analysis for PCE
Specifically, EPA reviewed key and supporting information from previous human health hazard
assessments as well as the existing body of knowledge on PCE's human health hazards. These data
sources included an existing EPA IRIS Assessment ( J.S. EPA 2012c) and an ATSDR Toxicological
Profile (since finalized as (ATSDR 2019)); hence, many of the human health hazards of PCE have been
previously compiled and systematically reviewed.
All human health hazards of PCE previously identified in these reviews were described and reviewed in
this risk evaluation, including: acute toxicity, neurotoxicity, kidney toxicity, liver toxicity,
reproductive/developmental toxicity, immune and hematological effects, irritation, and cancer. EPA
relied heavily on the aforementioned existing reviews along with scientific support from the Office of
Research and Development in preparing this risk evaluation. Development of the PCE hazard and dose-
response assessments considered EPA and National Research Council (NRC) risk assessment guidance.
Any identified new literature published since these previous assessments was screened against inclusion
criteria in the PECO statement and the relevant studies (e.g., useful for dose-response)16 were further
evaluated using the data quality criteria for human, animal, and m vitro studies described in the
16 Some of the studies that were excluded based on the PECO statement were considered later during the systematic review
process as needed. For example, EPA reviewed mode of action information to qualitatively support the health hazard
assessment.
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Application of Systematic Review in TSCA Risk Evaluations document ( )). EPA skipped
the screening step (for relevance to PCE) of the key and supporting studies identified in previous
assessments and entered them directly into the data evaluation step based on their previously identified
relevance to the chemical (U.S. EPA. 2018b). EPA skipped the screening step (for relevance to PCE) of
the key and supporting studies identified in previous assessments and entered them directly into the data
quality evaluation step based on their previously identified relevance to the chemical.
EPA considered studies of low, medium, or high confidence for the weight of scientific evidence (WOE)
for hazard identification and dose-response analysis. Information from studies that were rated
unacceptable were only discussed on a case-by-case basis for hazard ID and weight-of-scientific-
evidence assessment but were not considered for dose-response analysis.
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. In the last step, the strengths and limitations of the data were evaluated for each endpoint and a
weight-of-the-scientific evidence narrative was developed. Data for each selected hazard endpoint
underwent dose-response analysis. Finally, the results were summarized, and the uncertainties were
presented. The process is described in Figure 3-1. The WOE analysis included integrating information
from toxicokinetics, toxicodynamics in relation to the key hazard endpoints: acute overt toxicity, liver
toxicity, kidney toxicity, neurotoxicity, immunotoxicity (including sensitization), reproductive toxicity,
developmental toxicity, and cancer. EPA selected human health studies that were of high quality and
relevance to move forward for dose-response analysis in order to quantitatively assess each key hazard
endpoint.
Summaries for all studies considered for this draft risk evaluation, the no-observed- or lowest-observed-
adverse-effect levels (NOAEL and LOAEL) for non-cancer health endpoints by target organ/system, the
incidence for cancer endpoints, and the results of the data quality evaluation are provided in Draft Risk
Evaluation for Perchloroethylene Data Quality Evaluation of Human Health Hazard Studies and Data
Extraction for Human Health Hazard Studies. ( 020g).
EPA considered points of departure (POD) from studies that were PECO relevant, scored acceptable in
the data quality evaluation, and contained adequate dose-response information. The POD is a dose or
concentration near the lower end of the observed range without significant extrapolation to lower doses.
It is used as the starting point for subsequent dose-response (or concentration-response) extrapolations
and analyses. PODs can be a no-observed-adverse-effect level (NOAEL), a lowest-observed-adverse-
effect level (LOAEL) for an observed incidence, or change in level of response, or the lower confidence
limit on the dose at the benchmark dose (BMDL)17. PODs were adjusted as appropriate to conform to
the specific exposure scenarios evaluated. Section 3.2.5 describes the dose-response assessment guiding
the selection of PODs for non-cancer endpoints.
17
The benchmark dose (BMD) is a dose or concentration that produces a predetermined change in response range or rate of
an adverse effect (called the benchmark response or BMR) compared to baseline.
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3.2.2 Toxicokinetics
The toxicokinetics and PBPK modeling of PCE were thoroughly described in the 2012 EPA IRIS
Assessment (U.S. EPA. ). This discussion is summarized below.
3.2.2.1 Absorption/Distribution/Metabolism/Elimination (ADME)
3.2.2.1.1 Absorption
Inhalation
Inhalation is considered to be the major exposure route, and studies on both humans and animals
confirm that PCE is both rapidly and readily absorbed via pulmonary uptake (with equilibrium occurring
after several hours). The blood:gas coefficient ranges from -10-20, indicating that PCE readily moves
from alveoli into the bloodstream. For the purposes of this risk evaluation, EPA conservatively assumes
100% absorption through the lungs.
Oral
For oral exposures, studies in mice, rats, and dogs demonstrate that absorption of PCE through the gut is
essentially complete (i.e. 100%).
Dermal
Dermal exposure to PCE vapors is estimated to result in minimal dermal uptake compared to inhalation
of those vapors (only -1% absorbed dermally compared to inhaled). However, studies indicate that
dermal absorption may be significant for direct skin application of PCE. Complete (i.e. 100%)
absorption may be achieved in scenarios of impeded evaporation or complete immersion, and this risk
evaluation assumes that up to 100% of the delivered dermal dose (i.e. after accounting for evaporation or
in scenarios with impeded evaporation) is absorbed. Volatilization from the skin is accounted for in the
occupational exposure assessment by the Dermal Exposure to Volatile Liquids Model based on a
theoretical framework provided by Kasting and Miller (2006). The amount of liquid on the skin is
adjusted by the weight fraction of PCE in the liquid to which the worker is exposed. Specific details of
the dermal occupational exposure assessment can be found in Section 2.4.1.29. For the consumer risk
assessment, dermal exposure is assessed using the Consumer Exposure Model (CEM; (
2017a)) permeability dermal sub-model based on the ability of a chemical to penetrate the skin layer
once contact occurs. The CEM permeability model assumes a constant supply of chemical, directly in
contact with the skin, throughout the exposure duration. This model was applied only to consumer
COUs where evaporation is inhibited, or prohibited, or full immersion of a body part occurs during use.
The permeability method does NOT consider evaporation and is more representative of these COU
types. For the consumer risk assessment, absorption is assessed using permeability model which uses an
absorption rate as opposed to a steady-state percentage (Section 2.4.2.2.2).
Distribution
PCE is broadly distributed to all tissues and can cross both the blood:brain barrier and placenta. The
highest concentrations are found in adipose tissues due to the lipophilicity of the chemical. Accordingly,
PCE concentrations are higher in the brain and liver than many other tissues and it becomes
concentrated in human breast milk. Skeletal muscle has been measured to contain the lowest
concentration of any tissue. Long residence time in adipose tissue can result in increasing body burden
with continuous or repeated exposures.
3.2.2.1.2 Metabolism
PCE is metabolized in laboratory animals and in humans through at least two distinct pathways:
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1) oxidative metabolism via the cytochrome P450 (CYP [also abbreviated as P450]) mixed-function
oxidase system;
2) glutathione (GSH) conjugation followed by subsequent further biotransformation and processing,
either through the cysteine conjugate P-lyase pathway or by other enzymes including flavin-containing
monooxygenase 3 (FM03) and CYP3A.
The conjugative pathway is toxicologically significant because it yields relatively potent toxic
metabolites, however studies in both animals and humans indicate that overall metabolism of PCE is
relatively limited—particularly at higher exposures. Oxidative metabolism is the more dominant
pathway in rodents, however the relative contribution of each in humans has not been determined.
Available data presents a wide range of estimates for amount of PCE metabolized, depending on dose
level and species (less metabolized at higher doses, and less metabolized in mice compared to rats).
PBPK modeling estimated that at existing occupational regulatory levels only 1.5% of inhaled PCE
would be metabolized, while at air concentrations of only 0.001 ppm a median estimate of 23-36%
would be metabolized.
Oxidative Metabolism
CYP-mediated oxidative metabolism occurs predominantly in the liver, irrespective of the exposure
route, and oxidative metabolites are generally responsible for PCE liver toxicity. The major oxidative
metabolite is trichloroacetic acid (TCA), which is believed to derive primarily from the upstream
metabolite of trichloroacetyl chloride (through hydrolysis or interaction with peptide amino groups).
Dichloroacetic acid (DCA) has also been detected in urine, and DCA may form either due to further
metabolism of TCA or via bioactivation of GSH conjugates. Oxalic acid is also believed to be a major
urinary metabolite (at least in rats). Trichloroethanol (TCOH) may also be produced, but conflicting data
suggests that detected TCOH may only be due to cross-contamination from the closely related chemical,
trichloroethylene. Oxidative metabolism occurs at a faster and greater overall rate in rodents compared
to humans, however the half-life of these metabolites is much greater in humans (up to 15x longer).
Variability in CYP metabolic capacity is generally believed to vary by approximately 10-fold among all
humans, however individual variations in in vitro CYP2E1 activity as high as 20-50 fold have also been
reported. There is also large variability in CYP2E1 activity across different tissues. For ingested
chemical, first pass through the liver would be expected to be responsible for the majority of oxidative
metabolism and subsequent metabolites would travel through the blood to reach target sites. For other
routes, these tissue-specific differences may result in varying downstream toxicological activity. The
PBPK model is expected to account for the majority of tissue variability via oral or inhalation routes.
Conjugative Metabolism
The GSH-mediated conjugative pathway begins in the liver, with transport of the initial GSH conjugate
(S-(l,2,2-trichlorovinyl) glutathione or TCVG) and its cysteine counterpart (TCVC) to the kidney target
organ. While the pathway was originally demonstrated only in rodents, it has since been confirmed to
exit in humans, although the relative susceptibility of humans for TCVG production compared to
rodents is unclear. Transport to the kidney (primarily) results in further processing and associated renal
toxicity. This toxicity is associated at least in part with the activity of P-lyases, which cleave TCVC to
yield an unstable thiol, resulting in cytotoxic and mutagenic reactive metabolites. FM03 can also
produce another reactive metabolite, TCVC sulfoxide (TCVCSO), and other sulfoxide species can be
produced through CYP3 A metabolism of other conjugative metabolites.
Species Differences
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The rate of metabolism of PCE is faster in rodents than humans resulting in higher metabolite
concentrations in blood. The half-life of these metabolites is significantly longer for humans however
(144 hrs in humans vs 10 hrs or less in rodents), meaning that they can impart toxicological effects over
a longer period of time. TCA is the major oxidative metabolite produced in both rats and humans as
indicated by it's detection in urine, however as mentioned it is detected at much higher blood
concentrations (3-8 fold) in rats with a much faster half-life (>4-fold). These results are in agreement
with known differences in metabolic rates in general between species, for which mice are faster than rats
which are faster than humans.
Additional tissue and MOA-specific details on PCE metabolites are also provided in the Mode of Action
section, Section 3.2.3.2.4
3.2.2.1.3 Elimination
PCE is primarily eliminated through pulmonary excretion of the parent compound independent of
exposure route. Urinary excretion is the primary route for metabolites, although metabolites are also
excreted through the lungs as a minor pathway.
Half-life of PCE from blood-rich tissues, muscle, and adipose tissue is 12-16 hours, 30-40 hours, and
55-65 hours, respectively. In rodents, as body burden increases the percentage excreted as unchanged
parent compound also increases (due to decreased metabolism, see Section 3.2.2.1.2). Pulmonary
excretion rate is dose-independent, related instead to ventilation rate, cardiac output, and the relative
solubility of PCE in blood and tissue. In contrast, contrast, urinary excretion of metabolites is dose-
dependent and rate-limited.
3.2.2.2 PBPK Modeling
The 2012 EPA IRIS Assessment ( ) contains a Physiologically Based Pharmacokinetic
(PBPK) model for PCE. The most recent analysis by Chiu and Ginsberg ( ) improved on several
earlier models. EPA has made the model code available for download via the internet. The detailed
code is publicly available through EPA's HERO database (Chiu and Ginsberg 201 lb).
The model structure allowed it to be used to calculate internal dose metrics for inhaled and oral exposure
to PCE for mice, rats, and humans. Thus, the analysis could be used for route-to-route extrapolation or
interspecies extrapolation, comparison of parent and metabolite toxicity based on a common internal
dose metric, and investigation of the shape of the dose-response curve. The following dose metrics could
be determined using this model:
• Daily area-under-the-curve (AUC) of PCE in blood
• Fraction of PCE intake metabolized by oxidation
• Fraction of PCE intake metabolized by GSH conjugation
• Equivalent daily production of TCA per kg body weight.
Of note, a full Bayesian uncertainty/variability analysis was not performed. Therefore, the model could
not be used to represent the range of intraspecies human variability and was of limited utility for human
studies not requiring route-to-route extrapolation.
The highest confidence dose metric is AUC in blood, with the main source of uncertainty for the metric
being the residual difference between model predictions and the calibration/validation data (about 2-fold
for each species). The next highest confidence is for estimates of PCE oxidation and TCA formation,
again with approximately a 2-fold residual difference between predictions and data. There is large
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interindividual variability in PCE oxidation that is not captured by the model in the absence of a
Bayesian analysis. The model predicts decreasing oxidative metabolism from mice to rats to humans,
meaning that humans are predicted to receive a smaller internal dose for the same applied dose
compared to rodents, after accounting for body weight scaling. For cross-species extrapolation, the
default assumption of equivalent air concentrations leading to equivalent internal doses appears correct
based on AUC estimates.
There is greater uncertainty for estimates of GSH conjugation, especially in humans. The data suggests
an approximate 2-fold range of uncertainty in rats, however there is minimal available data in mice
leading to a ~60-fold range. The human estimates are extremely uncertain, with two local maxima in the
model fits resulting in model predictions differing by up to 3,000-fold based on results of different
optimization runs. Due to this very broad uncertainty range, the model can result in humans having
either equal or greater GSH conjugation compared to rats, for which only -1% of dosed PCE undergoes
GSH metabolism.
3.2,3 Hazard Identification
3.2.3.1 Non-Cancer Hazards
The 2012 EPA IRIS Assessment ( ) evaluated the following non-cancer hazards that may
be associated with PCE exposures: the central nervous system (neurotoxicity), kidney, liver and
development and reproduction. In general, neurological effects were found to be associated with lower
PCE inhalation exposures than what produced other noncancer adverse effects. According to the 2012
EPA IRIS Assessment ( ), support for an association with immune and blood effects
were less well characterized. In their Toxicological Profile for PCE, ATSDR (2019) identified similar
hazard concerns. The National Advisory Committee for Acute Exposure Guideline Levels for
Hazardous Substances ( 2009) also identified irritation as a hazard concern. Since the EPA
IRIS Assessment 13 new studies were identified and evaluated during the systematic review process.
These new studies add further evidence to support the conclusions established in the EPA IRIS and
ATSDR assessments (ATSDR 2019).
3.2.3.1.1 Acute Toxicity and Irritation
Data from acute exposure studies in animals and human incidents indicate that short term exposure to
PCE may cause irritation and neurotoxicity and can impair cognitive function in humans (
2012c). An Acute Exposure Guidance Limit (AEGL) values, established by the National Advisory
Committee for Acute Exposure Guideline Levels for Hazardous Substances ( 3), has been
developed based on irritation to humans (AEGL-1), ataxia in rodents (AEGL-2), and lethality in mice
(AEGL-3) (U.S. EPA. 2009). Epidemiological studies since the EPA IRIS Assessment focused on
chronic exposures.
There is sufficient evidence from controlled human exposure studies that acute-duration (< 24 hours)
inhalation exposure to PCE induces symptoms of CNS depression and prolonged visual evoked potential
latencies (ATSDR 2^n , I * n \ , 2009; Altmann et al. 1990; Hake and Stewart 1977). While
more limited, case reports show that CNS depression (including coma/ unconsciousness at sufficiently
high doses) also occurs in humans after oral exposure to PCE (ATSDR 2019)). Sufficient information in
acute-duration studies in animals exposed by inhalation or oral gavage also shows CNS depression
(ATSDR 2019;, Z009) as well as reduced amplitude of visual evoked potentials, impaired
sustained attention, prolongation of escape-directed behaviors after inhalation exposure (ATSDR 2019;
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;; Boves et al. 2009; Oshiro et al. 2008) and reduce operant response behavior or
increased seizure threshold (A.TSI )) after oral exposure.
Human controlled-exposure studies and case reports demonstrated concentration-related increases in the
incidence and severity of eye and upper respiratory tract irritation (AP v H \ .^09).
There are also reports of greater excitement and struggling in beagle dogs exposed to PCE by facemask
(ATSDR 2019). however this is not adequate evidence to indicate an association with respiratory tract
irritation in animals.
Data pertaining to hepatic effects in humans exposed acutely to PCE consist of only a single case report
(I )). Dose-related hepatic effects following acute gavage administration to mice
including increased serum ALT, fatty degeneration and necrosis, and cytoplasmic vacuolation (ATSDR
2019).
3.2.3.1.2 Neurotoxicity
The neurological effects of PCE in humans have been extensively studied. Findings in humans are
supported by a more limited number of animal studies. The EPA IRIS Toxicological Review for PCE
(I ) provides the basis for the information below from studies published up to that time;
more recent studies are also discussed. The review performed by EPA IRIS ( 1012c) identified
visual deficits in human studies, especially diminished color discrimination, as the most sensitive
endpoint of PCE exposure. With one exception, newer human studies have not materially added to the
database of PCE effects on visual function; instead, these studies have focused on symptoms of
neurotoxicity (Lucas et al. 2015). risks of neurodegenerative diseases (Bove et al. 2014b; Goldman et al.
2012). risks of autism spectrum disorder (Aschengrau et al. 2016a; Aschengrau et al. 2011) or risky
behaviors and head injuries (Aschengrau et al. 2016a; Aschengrau et al. 2011) after prenatal or early
childhood exposure. One study published since the 2012 IRIS Assessment ( ) assessed
visual function of a residential population exposed to PCE in contaminated drinking water (Getz et al.
2012). There have been no oral or inhalation repeated-exposure animal studies published after the IRIS
Assessment that evaluated sensitive neurological endpoints.
Human Evidence
Visual Function
Human studies have documented an association between impairments in visual contrast sensitivity and
color discrimination and PCE exposure in both occupational and residential settings ( ).
Cavalleri et al. (1994) and Gobba et al. (1998). inform the relationship between impaired color
discrimination and PCE exposure. Cavalleri et al. (1994) observed a significant positive correlation
between time-weighted average concentrations of PCE and the Color Confusion Index (CCI) score on
the Lanthony D-15 desaturated panel test among dry cleaning workers in Italy. The 35 workers made
many more mistakes in the color vision test when compared with 35 unexposed factory workers, with
most errors occurring in the blue-yellow range. Exposure to PCE was measured using passive personal
air sampling, yielding a time-weighted (8-hour) average concentration of 6 ppm (41 mg/m3) for the
workers; the mean exposure duration was 8.8 years. Vision testing was performed at the same time of
day for workers and controls by an investigator who was blinded to exposure status. When tested two
years later, color visual impairment was again significantly associated with exposure concentration
among the workers; furthermore, those workers whose exposure to PCE had increased in the two-year
interim exhibited a decline in performance from the initial testing, while performance was unchanged
among those whose exposure decreased (Gobba etal. 1998). Schreiber at al. (2002) reported diminished
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color discrimination or visual contrast sensitivity compared with unexposed referent groups among
small groups of children and adults living or working in a building with a co-located dry cleaning
establishment. EPA IRIS ( ) identified potential confounders in this study, including
diagnoses of learning or developmental delays among some of the exposed children, and correlations
between exposure and children's ages and races.
Only one study published after the EPA IRIS Toxicological Review ( ) examined visual
function in humans exposed to PCE. Getz et al. ( ) measured color vision and visual contrast
sensitivity among adult residents of Cape Cod, MA who were exposed prenatally and during early
childhood to PCE-contaminated drinking water. Tests administered to the 25 exposed and 25 unexposed
subjects included the Farnsworth D-15 and Lanthony D-15d for color discrimination, as well as tests of
near acuity and near contrast sensitivity. The investigator who administered the tests was blinded to
exposure status. A statistically significant difference in color discrimination was detected using the
Farnsworth test (mean difference 0.05, 95% CI = 0.003, 0.10), but the difference observed in the
Lanthony D-15d test was not statistically significant (mean difference 0.07, 95% CI = -0.02, 0.15).
Contrast sensitivity at the highest spatial frequency test (18.0 cpd) was also diminished (mean difference
-6.47; 95% CI = -12.33, -0.62).
Cognition
Several occupational studies of dry cleaning employees, as well as one study of individuals residing near
dry cleaning facilities, have documented relationships between PCE exposure and adverse effects on
visuospatial memory, attention, vigilance, and information processing speed ( 2012c). In one
key study, a cohort of 65 dry cleaning workers in Michigan, high PCE exposure (TWA of 41 ppm or
278 mg/m3) was associated with statistically significantly (p<0.01) reduced scores for pattern
recognition, pattern memory, and visual reproduction tests (compared with low exposure workers whose
mean exposure was 11 ppm or 75 mg/m3 (Echeverria et al. 1995). The investigations by Echeverria et al.
provided more robust evidence for the findings of Seeber et al. (1989). who reported dose-related,
statistically significant effects on the threshold for perceptual speed test, digit reproduction, digit
symbol, and cancellations among 101 German dry cleaning employees with low (8-hr TWA 12 ppm or
81 mg/m3) or high (8-hr TWA 53 ppm or 359 mg/m3) exposure to PCE (compared with 84 unexposed
controls). Of note, EPA identified several shortcomings in this study, including lack of detail on
methods used to select subjects, missing information related to testing procedures, differences in alcohol
use between exposed and control subjects that were not accounted for in the models, and nonmonotonic
dose-response relationships with some test scores. PCE exposure may also be associated with an
increase in reaction time, as reported in a study of dry cleaners (Ferroni et al. 1992).
Neurodegenerative diseases
Goldman et al. ( ) examined the association between Parkinson's disease and exposure to solvents
(including PCE) among discordant twin pairs. In the cohort of 99 twin pairs, each having only one twin
diagnosed with Parkinson's disease, self-reported exposure (ever exposed) to PCE was associated with a
large but very imprecise increased OR (10.5; 95% CI = 0.97, 113). Evaluation of each twin's cumulative
PCE exposure did not materially change the findings.
In a retrospective cohort mortality study, Bove et al. (2014b) reported a nonsignificant elevation in the
SMR for mortality due to ALS (Amyotrophic Lateral Sclerosis; SMR = 1.14; 95% CI = 0.70, 1.74)
among PCE-exposed military personnel at Camp LeJeune (North Carolina) when compared with age,
sex, race, and calendar period-specific national mortality rates. Furthermore, the hazard ratio for ALS
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mortality increased with cumulative PCE exposure category (HRs of 0.69, 1.58, and 1.96 for low [>1-
155 ug/L-months], medium [>155 - 380 ug/L-months], and high [>380 ug/L-months] exposures,
respectively) in analyses restricted to the Camp LeJeune cohort. A borderline significant (p=0.06)
positive association (P = 0.00039, 95% CI = -0.00002, 0.00080) was observed between cumulative PCE
exposure (as a continuous variable) and ALS mortality in the cohort.
Neurodevelopment
Aschengrau et al. (2016a; 2011) conducted a series of studies examining neurological outcomes of early
life (prenatal and early childhood) exposure to drinking water contaminated by PCE (cumulative
exposures ranging from 11 to 4668 g). Individuals residing in Cape Cod, MA were exposed to PCE
leaching from water distribution pipes; a model was used to estimate individual exposures to each
residence from leaching. In analyses of 831 persons with prenatal and early childhood exposure
compared with 547 unexposed subjects, any exposure to PCE was associated with statistically
significant increased risks of engaging in risky behaviors (Aschengrau et al. 2016a). Analyses included
adjustment for demographic characteristics, key risk factors for the behavioral and health outcomes
under study, and nondrinking water sources of solvent exposure. Odds ratios for use of more than one
major illicit drug (crack/cocaine, psychedelics, heroin, Ritalin without a prescription, and club/designer
drugs) in the highest exposure groups were 1.6 (95% CI = 1.2, 2.2) for use during adolescence and 1.5
(95% CI = 1.2, 1.9) for use during adulthood. Early and heavy smoking, and frequent or heavy drinking
behaviors were also increased among highly exposed subjects (ORs 1.3-1.6, with statistically
significantly increased ORs for drinking, but not smoking patterns). In the same population, a significant
increased risk was observed for development of bipolar disorder among highly exposed (> 67th
percentile) subjects (RR = 2.7, 95% CI = 1.3, 5.6). Nonsignificant increased RRs were also seen for
post-traumatic stress disorder (1.7, 95% CI = 0.9, 3.2 for exposure > 67th percentile) and schizophrenia
(2.1; 95% CI = 0.2, 20.0 for any vs. no exposure, based on 3 cases; (Aschengrau et al. 2016a).
Neuropsychological findings in a subset of the Aschengrau et al. cohort (35 exposed and 28 unexposed
adults) who were willing to undergo testing showed modest, nonsignificant differences in performance
on tests for visuospatial function, learning and memory, mood alteration, and attention and executive
function (mean differences of -0.2 or - 0.3, with confidence intervals in the range of -0.5 to +0.1 or -0.6
to +0.1; (Aschengrau et al. ). The largest magnitude of difference was observed for motor
functioning (mean difference in the finger tapping test was -1.8), but the difference was imprecise (95%
CI = -5.7 to +2.2). Other studies within the cohort evaluated whether PCE exposure was associated with
altered brain MRI findings in a subset of the cohort (26 exposed and 16 unexposed adult subjects). There
were no significant differences in MRI findings (e.g., white and gray matter volumes and white matter
hypointensities) between the groups. Postulating that neurological sequelae of early PCE exposure could
increase the likelihood of unintentional head injuries, Aschengrau et al. (2016b) evaluated the frequency
of self-reported head injuries among members of the cohort (828 exposed and 544 unexposed). No
increase in the risk of head injuries was observed for any exposure, or in the highest exposure group
(RRs 0.8-1.0).
Stingone et al. (2016) evaluated the relationship between standardized test scores in math and English
language arts among 3rd graders in New York City schools and modeled air concentrations of PCE
(median concentration 0.68 |ig/m3) and diesel particulate matter from EPA's National Air Toxics
Assessment (NATA) in 1996 (assessment closest to the children's birth years) to correspond with the
mothers address at time of birth. Prenatal exposure to PCE in the highest quartile was associated with
lower math test scores and increased risk of failing to meet test standards for math (1.03 95% CI = 1.00,
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1.06). In analyses of English language arts test results, prenatal PCE exposure was associated with
decreased test scores only in the upper tail of the distribution of test scores (75th quantile and above);
there was no association with failure to meet test standards. Due to the use of an exposure model based
on census tract data and uncertainties surrounding the actual location of mothers during pregnancy, there
was potential for exposure misclassification.
Four case-control studies of autism spectrum disorders (ASD) and prenatal exposure to hazardous air
pollutants, including PCE, were identified in the literature searches (Talbott et al. 2015; von Ehrenstein
et al. JO I I; kcberts et al. 2013; Kalkbrenner et al. 2010). Three of the studies used modeled air
concentrations of toxicants at the place of maternal or birth residence based on EPA's NAT A, while von
Ehrenstein et al. (2014) used measured air concentrations from monitoring stations within 5 km of the
subjects" residences (Los Angeles County CA). Two studies (Roberts et al. 2013) and (von Ehrenstein et
al. 2014) reported significant positive associations between the odds of ASD and PCE exposure. Roberts
et al. (2013) reported an OR of 1.60 (95% CI = 1.07, 2.41) comparing the highest to lowest quintiles of
PCE exposure in a case-control study nested within the Nurses' Health Study II. In the study by von
Ehrenstein et al. (2014). significantly increased ORs were observed for an interquartile range increase in
exposure concentration across the pregnancy (OR = 1.40, 95% CI = 1.09, 1.80 for stations within 5 km
of the residence and OR =1.61, 95% CI = 1.14, 2.26 for stations within 3.5 km). Stratification by ASD
severity and by gender showed stronger associations for milder ASD and in males. Kalkbrenner et al.
(2010) and Talbott et al. (2015) did not report significant associations between ASD and PCE exposure
in case control studies in NC and WV or PA (respectively).
Clinical Signs of Neurotoxicity
Lucas et al. ( ) observed no significant differences (p > 0.01) in the prevalence of self-reported
symptoms of neurotoxicity (e.g., fatigue at end of day, difficulty sleeping) when comparing 50 dry
cleaning workers with exposure to PCE with symptoms reported by 95 workers who were not exposed.
The median airborne concentration of PCE was 7 ppm (47 mg/m3) (range 0.22-33 ppm) in the dry
cleaning establishments, and workers had blood levels of PCE ranging between 11.8 and 544 |ig/L
(median 73.6 |ig/L).
Animal Evidence
Animal studies provide support for the effects seen in humans, but the database is much more limited.
Effects recorded in studies of rats, mice, and gerbils include clinical signs of neurotoxicity,
neurophysiological changes, and alterations in brain chemistry or brain weight ( \ l1* PR 2019; 1 v « « \
2012c). Other studies reported decreases in brain fatty acid and DNA content, alterations in taurine and
glutamine content, and decreased brain weight in gerbils and impaired nociception in rats (
2012c).
Limited information is reasonably available on developmental neurotoxicity in animals exposed to PCE,
however existing data suggests that gestational exposure can impair neurobehavior, motor performance,
and neurotransmitter signaling ( ).
No studies examining sensitive neurological endpoints in adult animals were published after the EPA
IRIS Toxicological Review ( ). No clinical signs of neurotoxicity were noted in female
Sprague-Dawley rats exposed to PCE concentrations up to 1000 ppm (6783 mg/m3) for four weeks in a
study focused on immunotoxicity (Boverhof et al. 2013).
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3,2,3,1,3 Kidney Toxicity
Human Evidence
Most of the available epidemiological studies, conducted in populations of dry cleaning workers,
examined markers of kidney toxicity without including standard tests for kidney function (
2012c; Mutti et I). Based on the observed increases in urinary RBP, p2-glucuronidase, lysozyme,
and glutamine synthetase, EPA believes that PCE has its primary effect on the proximal tubules, as these
are markers of proximal tubular injury. Other markers of tubular injury, including N-acetyl
glucuronidase (NAG) and alanine aminopeptidase (AAP) were not associated with exposure (U„S JIH
2012c). however NAG is a relatively insensitive measure of tubular dysfunction, and AAP was assessed
in only one study. One epidemiological study published after the EPA IRIS Toxicological Review (U.S.
EPA. 2012c) examined non-cancer renal toxicity and found that PCE was not significantly associated
with chronic renal diseases (Silver et al. 2014).
Animal evidence
Animals exposed to PCE by inhalation exhibit renal effects such as increased kidney weights, and
tubular histopathology (ATSOK r1 S < r \ 1 _v). Effects have been reported in both male and
female rats and male and female mice. In a multigeneration study of Alpk:APfSD rats exposed for -19
weeks, renal effects including minimal chronic progressive glomerulonephropathy and increased
pleomorphism in proximal tubular nuclei were seen at 1000 ppm (6783 mg/m3; the highest concentration
tested) (Tinston 1994). With two years of exposure to 200 ppm (1357 mg/m3), male and female rats
showed increased relative kidney weights and karyomegaly of the proximal tubules (USA. 1993; NTP
1986b). In a four-week immunotoxicity study published after the EPA IRIS Toxicological Review (U.S.
EPA 2012c). no changes in kidney weight or histology were observed in female Sprague-Dawley rats
exposed by whole-body inhalation to PCE concentrations up to 1000 ppm (6783 mg/m3; (Boverhof et al.
2013)).
Mice exposed to 609 ppm (4131 mg/m3) for 13 weeks exhibited histopathology changes (not further
described) in the proximal tubules; at 200 ppm (1357 mg/m3) for 13 weeks, karyomegaly of the renal
tubular epithelial cells was observed (USA 1993; Nr 5b). Chronic (2 years) inhalation exposure
resulted in nephrosis (karyomegaly and cytomegaly of the proximal tubules) in both sexes of B6C3F1
mice exposed to 100 ppm (678 mg/m3; the lowest concentration tested) (NTP 1986b) and karyomegaly
with atypical dilation of the proximal tubules in male and female hybrid mice exposed to 250 ppm (1696
mg/m3; (USA 1993).
After 78 weeks of exposure to doses > 386 mg/kg-day (mice) or > 475 mg/kg-day (rats) administered
by gavage in corn oil, both sexes of Osborne-Mendel rats and B6C3F1 mice exhibited toxic
nephropathy, with higher incidences in rats than mice (NCI 1977). Mixed evidence including both
positive and negative findings for signs of kidney toxicity were observed in other mice studies (U.S.
EPA. 2012c). while increased kidney weight, urinary markers of damage, and histopathology was
reported in rats (Jonker et al. 1996).
A group of studies in F344 rats showed accumulation of a2u-globulin and hyaline droplets in the
proximal tubules of male rats exposed to PCE by gavage in corn oil for 10 days to four weeks (U.S. EPA.
2012c). These changes were correlated with cell proliferation, formation of granular tubular casts, and
tubular cell regeneration, suggesting the involvement of male rat-specific a2u-globulin accumulation in
the mode of action for some renal effects of PCE. However, the kidney effects seen in female rats and in
mice of both sexes show that other mechanisms (e.g., peroxisome proliferation and/or cytotoxicity
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mediated by reactive metabolites produced from glutathione conjugation in the kidney; see Section
3.2.3.2.4) also play a role in the renal toxicity of this compound.
3.2.3.1.4 Liver Toxicity
Human evidence
There is limited information on the hepatic effects of PCE in humans, with conflicting evidence across
several occupational studies of dry cleaning workers. Sonographic changes in the liver and alterations in
hepatic enzyme levels in serum (compared with unexposed workers) were noted in two studies of dry
cleaners with exposure to PCE; however other studies noted no differences in enzyme levels (
2012c). Exposure levels in the negative studies were comparable to those in the ones reporting effects,
but workers in the studies reporting effects had been exposed for much longer (12-20 yrs vs 3-6 yrs in
negative studies. In Silver et al. (2014). the only human study of PCE published after EPA IRIS (US
EPA. 2012c) that examined noncancer liver effects, there was a statistically significant deficit of
cirrhosis and chronic liver disease in male workers at a microelectronics and business machine facility.
Animal evidence
Liver toxicity (i.e., necrosis, vacuolation, etc) has been reported in multiple animal species by inhalation
and oral exposures to PCE, with the mouse typically being more sensitive than the rat. The liver effects
are characterized by increased liver weight, necrosis, inflammatory cell infiltration, triglyceride
increases proliferation, cytoplasmic vacuolation (fatty changes), pigment in cells, oval cell hyperplasia
and regenerative cellular foci (U.S. EPA.: ).
In mice exposed to PCE by oral gavage, increased serum ALT levels, increased liver weight,
hepatocellular hypertrophy, fatty degeneration and necrosis, and regenerative repair/increased DNA
synthesis were observed after exposure to doses of 20 - 2000 mg/kg-day for 6 weeks (Buben and
O'Flahertv 1985). Rats exposed orally to 600 or 2,400 mg/kg-day PCE for 32 days showed increased
relative liver weight as well (Jomkeretal. 1996). In inhalation studies of PCE, both mice and rats
exhibited hepatic effects, but mice appear to be more sensitive. Mice displayed increases in palmitoyl
CoA, peroxisome proliferation, mitochondrial proliferation, increased relative weight, centrilobular lipid
accumulation/fatty degeneration, and liver necrosis/degeneration. Effects observed in rats were limited
to increased liver weight after subchronic exposure and spongiosis hepatis and hyperplasia following
chronic exposure ( ). In rats, increased liver weight was observed after 90 days of
continuous exposure, while spongiosis hepatis and hyperplasia were noted to occur at increased
incidences after 110 weeks of exposure 0 v << T \ I ).
A four-week inhalation immunotoxicity study in rats (Boverhof et al.: ) that was published after
EPA IRIS (U.S. EPA. 2012c) also reported hepatic effects. Female Sprague-Dawley exposed whole-
body to 1000 ppm (6783 mg/m3) exhibited increased relative liver weights (in conjunction with
decreased body weight at this exposure level) and an increased incidence of centrilobular hepatocellular
hypertrophy. At lower exposure levels, no biologically significant hepatic effects were noted.
3.2.3.1.5 Reproductive/Developmental Toxicity
The EPA IRIS Assessment for PCE ( ) evaluated the developmental and reproductive
toxicity of PCE in humans and animals.
Human evidence
Reproductive
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Studies of PCE exposure in humans have evaluated several reproductive outcomes including effects on
menstrual disorders, semen quality, fertility, time to pregnancy, and risk of adverse pregnancy outcomes
including spontaneous abortion, low birth weight or gestational age, birth anomalies, and stillbirth Qj.S.
EPA. 2012c).
Sperm concentration, morphology and motility were examined in California men who worked as dry
cleaners (n = 34) compared with aged matched laundry workers (n= 48) (Eskenazi et al. 1991). The
three measures of exposure in this study were dry cleaners vs. laundry workers, exhaled breath
concentrations of PCE and an exposure score assigned by an industrial hygienist. Clinically relevant
changes in sperm concentration, morphology and motility were not associated with any measure of PCE
exposure. Fertility rates were examined among wives of dry cleaners and laundry workers in this study;
however, the small sample size in this study precluded a determination of findings.
The potential association between PCE exposure and time to pregnancy was evaluated in several studies
including a Danish case-control study of couples treated for infertility, a retrospective time-to-pregnancy
study in Finnish women, and a Finnish case-control study ( 2012c). Some evidence of an
association was identified in these studies, however the presence of confounders, absence of PCE-
specific data in all values, and possibility of bias diminish the impact of the results.
Developmental
The epidemiological evidence for developmental effects associated with PCE exposure is suggestive
based on several studies of maternal occupational exposure to PCE that suggest an increased risk of
spontaneous abortion at high concentrations (01 sen et al. 1990; Kvvronen et al. 1989). In addition,
drinking water studies have suggested associations between PCE exposure and pre-term birth, low birth
weight, eye and ear anomalies, and oral cleft defects ( ).
Animal evidence
Data from animal studies identified various manifestations of developmental toxicity including
increased mortality and decreased body weight in the offspring of rodents exposed via inhalation.
Reproductive
A multi-generation study (Tinston 1994) exposed rats to 0, 100, 300, or 1,000 ppm (0, 678, 2035, 6783
mg/m3) PCE, 6 hours/day, 5 days/week, for 11 weeks prior to mating and then for 6 hours/day during
mating and through GD 20. First generation dams and litters were exposed from PND 6 through PND 29
but were not exposed from GD 21 through PND 5. This study did not evaluate estrous cyclicity, sperm
parameters, age to sexual maturation or enhanced reproductive organ histopathology. The only
significant reproductive effect reported in this study was reduced testes weight in F1A and F1 males at
1000 ppm (6783 mg/m3). Sperm abnormalities were not observed in rats exposed to 100 or 500 ppm
(678 or 3391 mg/m3), 7 hours/day for 5 days (measured at 1, 4 and 10 weeks after the last exposure).
Sperm head abnormalities were increased in mice exposed to 500 ppm (3391 mg/m3) PCE at 4 weeks
only (B elites et; )). The temporal pattern of this effect suggests that spermatocytes and/or
spermatogonia may be sensitive to PCE exposure. Female reproductive toxicity was also observed based
on reduced fertilization of oocytes from exposed female rats ( ).
Developmental
Animals studies generally support the findings from the epidemiological literature for developmental
effects associated with PCE. Inhalation exposure to PCE resulted in increases in pre- and post-
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implantation losses, increased incidence of total malformations, decreased fetal weight, increased
incidence of skeletal retardations or delayed ossification, and/or decreased postnatal survival in rats
( Ł; Carney et al. 2006). increased incidence of visceral malformations or decreased fetal
weight and delayed ossification in mice, and increases in abortions, total litter resorptions, post-
implantation losses, and the incidence of malformations in rabbits ( ).
3.2.3.1.6 Immune System and Hematological Effects
Immune System Effects
Human Evidence
The association between PCE exposure and alterations in lymphocyte subpopulations, immunoglobulin
and cytokine levels, and other markers of inflammation has been indicated in dry cleaning workers and
in children in Germany. Studies of the relationship between serum cytokine and IgE levels in infants or
toddlers and volatile organic compounds in the children's bedroom air reported no association with IgE
but did report reduced interferon-y levels for PCE exposure above the 75th percentile ( ).
No relevant studies were identified that were published after the EPA IRIS Assessment (
2012c).
There is conflicting data on whether there is a link between increasing PCE exposure and asthma
symptoms. While there is limited evidence of exacerbation of asthma symptoms, other data found no
association with either ambient or exhaled concentrations after adjustment for co-exposure to criteria
pollutants ( ).
A number of studies have been conducted to evaluate the potential link between systemic autoimmune
conditions and exposure to solvents as a category, however limited data is available to evaluate whether
PCE exposure alone is associated with these conditions. Case reports and population based studies have
examined incidences of sclerosis, localized scleroderma, rheumatoid arthritis, and other conditions
without any statistically significant associations obtained ( 012c).
Animal Evidence
There is conflicting limited data from animal studies concerning effects on the immune organs of
thymus and spleen (U.S. EPA. 2012c). Two animal studies published after EPA IRIS ( )
examined immune system effects (Boverhof et al. 2013; Seo et al. ). Seo et al. ( ) evaluated
potential immune adjuvant effects of PCE in ICR mice exposed to 0.01 and 1 mg/L in drinking water for
2 or 4 weeks. Twenty-four hours before assessment (at 2 or 4 weeks), mice were sensitized by
intradermal injection with anti-dinitrophenol (DNP) IgE antibody. At assessment, mice were challenged
with a solution of Evans blue and anti-DNP IgE antibody via intravenous injection; after 30 minutes, the
passive cutaneous anaphylaxis (PCA) reaction was measured by removal of skin dyed blue and
quantification of pigment. The PCA reaction was significantly increased at 0.01 and 1 mg/L by 2.1- and
2.4-fold, respectively, at 4 weeks. No significant immune adjuvant effect was observed at 2 weeks.
Boverhof et al. ( ) did not observe immunotoxicity effects in female Sprague-Dawley rats
(16/group) exposed whole-body to PCE concentrations up to 1000 ppm (6783 mg/m3) for 4 weeks (6
hours/day, 5 days/week). No exposure-related changes were noted in total protein concentration, LDH
enzyme activity, or leukocyte differential cell distribution in bronchoalveolar lavage fluid. In addition,
treatment did not alter the number of spleen cells, or spleen or thymus weight or histology, and there
were no treatment-related changes in immune reaction in the SRBC antigen assay.
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Hematological Effects
Human Evidence
In a single study, decreased erythrocyte counts and hemoglobin levels and increased total white cell and
lymphocyte counts were indicated in PCE-exposed dry cleaning workers (\ v < < JO I „v). Among
human studies published after the EPA IRIS Toxicological Review ( ;), no information
pertaining to hematological effects was identified.
Animal Evidence
Animal studies showing effects on hematological parameters are restricted to mice with evidence of
diminished erythropoiesis and increased leukocytes ( ). PCE exposure resulted exhibited
a temporal increase in reticulocytes and a small reduction in erythroid committed cells in the bone
marrow as well as increased spleen weight with hemosiderin deposits and red pulp congestion and
increased serum LDH isozyme I (A.TSDR 2019). When NMRI mice were exposed to PCE in drinking
water for 7 weeks starting at 2 weeks of age, Hemolytic anemia with evidence of splenic involvement
was observed in mice, with no evidence that hepatic toxicity contributed to the effect ( ;).
Hematologic effects were not reported in rat studies reviewed by EPA IRIS ( ). In the 4-
week rat study by Boverhof et al. (2013) that was published after the EPA IRIS Toxicological Review
( ), no exposure-related changes to hematological parameters were observed at exposure
concentrations up to 1000 ppm (6800 mg/m3).
3.2.3.2 Genotoxicity and Cancer Hazards
EPA has identified several human studies published subsequent to the 2012 IRIS assessment of PCE and
has evaluated these studies as well as key and supporting studies from the IRIS assessment (U.S. EPA.
2012c) according to the data quality criteria published in ( b). The key and supporting
studies that were evaluated include the studies that were considered for dose-response modeling and
heavily considered in the overall IRIS assessment ( 012c). The full list of studies evaluated
for data quality is identified in the supplemental file Draft Risk Evaluation for Perchloroethylene
Systematic Review Supplemental File: Data Quality Evaluation of Human Health Hazard Studies -
Animal Studies (U.S. EPA. 20201).
A summary of genotoxicity studies is also included here. Note that EPA has not re-evaluated
genotoxicity studies for quality but is relying on previous assessments, such as the IRIS assessment
conclusions. A discussion of these studies follows.
3.2.3.2.1 Genotoxicity
( ), ( ) and ( ) pio\ ide compidiuisix e ie\ icws on ihe
genotoxicity of PCE. The discussion of PCE genotoxicity here is based on these previous assessments,
supplemented by information from a few individual genotoxicity studies (Everatt et al. 2013; Irvine and
Elfarra 2013; Tucker et al. ).
In vivo human
A handful of cross-sectional studies evaluating genotoxicity endpoints in exposed workers suggested
that PCE may induce increases in micronuclei and DNA damage. Significant increases in the frequency
of micronuclei and in DNA damage (mean tail length by comet assay) were observed in human
lymphocytes from dry cleaning workers (Everatt et al. 2013). The frequency of chromosomal
aberrations was not significantly different between workers and controls, but regression analysis of these
results in the exposed group showed significant positive associations with PCE exposure duration and
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frequency (Everatt et al. 2013). A recent study by Azimi et al. published after the conclusion of the
TSCA literature search (as cited in ( \ P PR _ Or)) provided some support for the finding of DNA
damage reported by (Everatt et al. 2013). Azimi et al. observed significant increases in comet assay tail
length, percent DNA in tail, and tail moment in 33 dry cleaners employed for at least 3 months (median
duration 8 years), when compared with 26 controls; exposure levels were not reported. (Tucker et al.
2011) observed statistically significant increases in the frequencies of acentric fragments and in a group
of dry cleaning workers exposed for at least 1 year compared to controls, but no statistically significant
difference was observed for chromosomal translocations. A previous study of these subjects reported
reductions in oxidative DNA damage in leukocytes from exposed workers compared with controls, and
there was no statistically significant increase in sister chromatid exchanges observed in studies on
workers compared to ONUs or controls ( ).
In vivo animal
Few in vivo animal studies of PCE genotoxicity have been performed, and the results of the available
studies are inconclusive. A marginal but dose-related increase in DNA damage, as measured by comet
assay tail intensity, was reported to occur in hepatocytes, but not kidney cells of mice given PCE orally
and the significance of this results has been questioned (\ v < < JO I „v). In an earlier study, single
strand DNA breaks were reported in mouse liver and kidney (but not lung) after intraperitoneal injection
of PCE, but the observed effect was no longer apparent after 24 hours. No DNA strand breaks were
observed in the kidneys of male rats given PCE orally for a week. No increase in oxidative DNA
damage was reported in urine, lymphocytes, or liver of rats exposed by intraperitoneal injection, but
there was significant morbidity and mortality among the animals at the higher doses ( ).
In one study investigating micronucleus induction, no increase in the frequency of micronuclei was
observed in reticulocytes or hepatocytes after intraperitoneal injection of PCE before partial
hepatectomy, while an increase in micronuclei was seen in hepatocytes when treatment occurred after
partial hepatectomy (ATSDR 2019). Examinations for DNA binding in rats and mice after
intraperitoneal exposure to radiolabeled PCE showed DNA labelling in mouse liver and stomach and, at
lower levels, in mouse kidney and rat stomach. An earlier study using a less sensitive method showed no
DNA binding in mouse liver after oral or inhalation exposure ( 2012c).
In vitro mutagenicity
A test for gene mutations in mouse lymphoma L5178Y cells was negative both with and without
metabolic activation ( :). In vitro non-mammalian testing for mutagenicity suggests that
PCE itself is not mutagenic, in contrast to some oxidative and conjugated metabolites of PCE. PCE has
been extensively tested for forward and reverse mutations in Salmonella typhimurium, Escherichia coli,
and Saccharomyces cerevisiae, both with and without metabolic activation. In the preponderance of
tests, the results were unequivocally negative, except for one strong exception ( PR 2019; IARC
2pi i; i ; r \ :o c»o.
In that exception study, a clear positive response was observed in S typhimurium TA100 with metabolic
activation and supplied glutathione (GSH), with an even stronger response when purified GSH S-
transferase was also added. These results suggest that metabolites of PCE in the glutathione conjugation
pathway are mutagenic. Support for this finding is seen in testing of PCE metabolites for mutagenicity.
Ames testing of TCVG yielded positive results with metabolic activation, and equivocal or negative
results without activation ( 2012c). However, positive results were observed in Ames testing of
TCVC ( ), NAcTCVC (N-acetylated TCVC) ( ), and TCVC sulfoxide
(Irvine and Elfarra ! ) without metabolic activation. The mutagenicity of NAcTCVC in Salmonella is
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believed to result from bacterial deacetylation to TCVC ( ). Irving et al. (2013) showed
that TCVC was a more potent mutagen than TCVC sulfoxide, but concluded that the latter was a
definite, albeit weak, mutagen.
Oxidative metabolites of PCE have also shown some evidence for mutagenic activity. Trichloroacetyl
chloride exposure increased revertants in S. typhimurium TA100 with or without activation in one study
but not in another (U.S. EPA. 2012c). In addition, PCE oxide was positive for reverse mutations in S.
typhimurium TA1535 without activation, but not in E. coli WP2uvrA. Testing of the oxidative
metabolite trichloroacetic acid (TCA), is ambiguous because interpretation of TCA in vitro test results is
complicated by pH changes induced by the compound ( ).
PCE has been tested for gene conversion, mitotic combination, and reverse mutation in S. cerevisiae.
Positive results were observed only when log-phase cultures, in which xenobiotic metabolism is
stimulated, were used. When stationary cultures were used, exposure did not induce gene conversion,
mitotic combination, or reverse mutation (IARC 2014). In growing cells of the D61.M strain, PCE
exposure, both with or without metabolic activation, induced aneuploidy (IARC 2014). No evidence for
sex-linked recessive lethal mutations was observed in tests of Drosophila melanogaster exposed to PCE
by feeding, inhalation, or injection ( ).
In vitro Micronuclei, SCEs and Chromosomal Aberrations
In mammalian cell systems tested in vitro, no evidence for SCEs or chromosomal aberrations was
observed in Chinese hamster ovary cells, Chinese hamster lung cells, or human lymphocytes. Assays for
induction of micronuclei in vitro yielded mixed results. Induction of micronuclei were reported in
Chinese hamster ovary cells exposed to PCE without metabolic activation, but not in Chinese hamster
lung cells. Experiments in metabolically enhanced cells yielded positive results for micronucleus
induction. Increases in micronuclei were seen in human AHH-1 lymphoblastoid cells (which have high
GST activity) and in daughter cell lines that express human CYP2E1 (h2El cells) or CYPs 1A2, 2A6,
3A4, 2E1, and microsomal epoxide hydrolase (MCL-5 cells) ( ).
In vitro DNA damage and morphological cell transformation
Few experiments examining DNA damage in cell systems in vitro after exposure to PCE have been
performed. Equivocal results were reported in tests of human WI38 fibroblasts for unscheduled DNA
synthesis: low doses yielded results comparable to the positive control, while high doses were negative,
although the positive control response was weak and cytotoxicity was observed at high doses (
2012c). In other studies of unscheduled DNA synthesis in rat and mouse hepatocytes and human
lymphocytes and fibroblasts, PCE did not yield positive results ( ). A more recent study
reported no increase in 8-OHdG (a measure of oxidative DNA damage) or y-H2AX levels (indicative of
double strand DNA breaks) in HepG2 cells exposed to PCE (Deferme et al. 2015); however, the
capacity of HepG2 cells to metabolize PCE is unknown.
PCE exposure resulted in morphological cell transformation when RLV/Fischer rat embryo cells were
exposed for 2 days, but not when BALB/c-3T3 cells were exposed for 3 days followed by a 30-day
incubation period (U.S. EPA. 2012c).
3.2.3.2.2 Carcinogenicity Epidemiological Studies
(I ) performed a thorough review of the epidemiological data pertaining to
carcinogenicity of PCE available from studies conducted through 2011. This review concluded that there
was a pattern of evidence associating PCE exposure with several types of cancer, specifically bladder
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7021 cancer, non-Hodgkin's lymphoma (NHL), and multiple myeloma (MM), and that more limited data
7022 supporting a suggestive effect were available for cancer at other sites, including esophageal, kidney,
7023 lung, liver, cervical, and breast cancer.
7024
7025 Descriptions of the data supporting these conclusions can be found in the IRIS Toxicological Review for
7026 PCE ( ). Newer epidemiological studies not available at the time of the IRIS review are
7027 summarized in Table 3-3 along with the outcome of EPA's data quality evaluation ( 20k). A
7028 detailed description of all epidemiological data can be found in Appendix 5.3.68F.1.11.
7029
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7030 Table 3-3. Summaries of Newer Epidemiologic Cancer Studies Published a
'ter the 2012 IRIS Toxicological Review
Outcome/
fjidpoint
Study E'opuEitfion
Kxposure
[Results
Reference
i);it:t Quniity
K\ iiiuiition
Cause-specific
mortality:
kidney cancer,
Hodgkin's
lymphoma,
Leukemias,
ALS
Camp Lejeune, North
Carolina cohort;
n=154,932
median age, start of
follow-up: 20 median age,
end of follow-up: 49
Camp Pendleton,
California cohort
n= 154,969 median age,
start of follow-up: 20
median age, end of follow-
up: 49 exposure period:
1975-1985; mortality
follow-up period: 1979-
2008
Chemical name:
Tetrachloroethylene (PCE);
exposure matrix: estimated
monthly average PCE
concentration in Tarawa Terrace
water system (1975-1985) Mean:
75.7 ug/L, Median: 84.9 ug/L,
Range: 0-158.1 ug/L; estimated
monthly average PCE
concentration in Hadnot Point
water system (1975-1985) Mean:
15.7 ug/L, Median: 15.4 ug/L,
Range: 0-38.7 ug/L); Duration:
On average an individual in the
Camp Lejeune cohort resided at
the base for 18 months.
Positive, non-significant
associations observed
between cumulative exposure
to PCE and mortality due to
kidney cancer.
(Bove et al
2014b)
High
Diffuse large
B-cell
lymphoma
Georgia population (2000
census)
Geocoded toxic release sites data
for Perc from 1988-1998 EPA's
TRI
Significantly decreased risk
for diffuse large B-cell
lymphoma with increasing
mean distance (per 1 mile) to
Perc TRI sites.
(Bulka et al
2016)
Medium
Mortality from
lymphatic and
haematopoietic
cancer
1704 dry cleaning workers
in four US cities (San
Francisco/Oakland,
Chicago, Detroit, and New
York)
Employment in a shop using Perc,
mean (sd) years of employment
for exposed workers 6.2 (5.0)
Significant elevated SMRs
were observed for all cancers,
esophageal cancer, and
trachea, bronchus, and lung
cancer. SMRs were
significantly lower for liver
cancer. No significant
association was found for
kidney cancer, lymphatic and
haematopoietic cancer, and
bladder cancer.
("Calvert et al.
20.1.1)
Medium
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Outcome/
E-jtdpoint
Study E'opuhtfion
Kxposure
[Results
Reference
i);it:t Quniity
K\ iiiuiition
Diagnosis of
cancer in oral
cavity,
oropharynx,
hypopharynx,
oral cavity, and
larynx (detailed
list of codes in
text)
Case-control, women only,
296 cases, 775 controls,
diagnosed 2001-2007,
general population, 18-85
years, subset of ICARE
cohort
Perc, exposure qualitatively
stated, modeled as cumulative
exposure index (CEI)
Statistically significant
positive association between
Perc and head/neck cancers in
ever/never analysis; null
association in continuous
cumulative exposure
assessment
("Carton et al.
2 )
Medium
Cancers of the
bladder,
prostate, colon,
stomach,
rectum, kidney,
pancreas,
esophagus, and
liver, as well as
melanoma and
non-Hodgkin's
lymphoma.
3730 male, Canadian
patients aged 35 to 70
years diagnosed 1979-
1985 in 18 largest
Montreal hospitals; 533
controls from electoral
lists in Quebec. A second
control group consisted of
the population controls
together with patients with
cancers at sites distal to
the primary cancer being
assessed.
PERC exposure determined from
self-reported job history
categorized by chemists and
industrial hygienists based on
degree of confidence, frequency,
and relative levels (not
quantitative)
Significant increase in the OR
for prostate cancer associated
with Perc exposure
(substantial), non-significant
OR for all other cancers
(Christensen
et al. 2013)
Medium
Breast cancer
incidence
920 incident breast cancer
cases, 1293 controls, Cape
Cod, Massachusetts, 1983-
1993,
Water distribution modeled
exposure to Perc-lined public
water distribution pipelines
Perc was not significantly
associated with breast cancer,
but there was a modest
increase in risk in women
with high perc exposure
(Gallagher et
)
Medium
Bladder cancer
113,343 cases and 566,715
matched controls from the
Nordic Occupational
Cancer (NOCCA) project
(through 2005)
Perc exposure estimated via
linkage between occupational
codes and Nordic Occupational
Cancer (NOCCA) project job
exposure matrix (JEM)
No significant trend in risk
with increasing Perc
exposure, significant increase
in hazard ratio was only
observed in the mid exposure
group
(Hadkhale et
al. 2017)
Medium
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Outcome/
E-jtdpoint
Study E'opuhtfion
Kxposure
[Results
Reference
i);it:t Quniity
K\ iiiuiition
Neuroblastoma
Children (75 cases, 14602
controls), ages <6 born in
1990-2007 in California
within 5 km of exposure
monitoring stations, cases
from California Cancer
Registry
Perc (0.186 ppbV) in ambient air,
pollution monitoring stations used
to estimate maternal exposure
during pregnancy from birth
certificate address
Non-significant positive
association between Perc and
neuroblastomas per
interquartile increase in
exposure at 5km radius
(Heck et al.
2013)
Medium
Astrocytic
brain cancer
risk
Men in southern
Louisiana, United States,
exposed from 1978 - 1980;
in northern New Jersey
and Philadelphia,
Pennsylvania, United
States, exposed from 1979
- 1981 (n=620, 300 cases,
320 controls)
Tetrachloroethylene, low
exposure (1)
Chi trend= -0.65. Exposure
not significantly associate
with astrocytic brain cancer
(Heineman et
i! (no-!)
Medium
Cancer
mortality
Lockheed Martin aircraft
manufacturing factory
workers in Burbank,
California (employed after
January 1, 1960; followed
up through December 31,
2008)
Years of exposure to Perc based
on job histories and industrial
hygiene surveys
No significant trend for any
specific cancer or total cancer
by increasing years of
exposure.
(Liowortli et
al. 2011)
High
Lung cancer
Investigation of
occupational exposure and
environmental causes of
respiratory cancers
(ICARE) study subjects,
population-based case-
control study in France
2001-2007 (2274 men
cases and 2780 men
controls)
Cumulative Exposure Index
(CEI) based on self-reported job
histories and probability,
intensity, and frequency of
exposure to Perc based on jobs
Perc was not significantly
associated with lung cancer in
men.
(Mattei et al.
2014)
Medium
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Outcome/
E-jtdpoint
Study E'opuhtfion
Kxposure
[Results
Reference
i);it:t Quniity
K\ iiiuiition
Mycosis
fungoides (MF)
100 patients with Mycosis
Fungoides and 2846
controls, 35-69 years of
age, from Denmark,
Sweden, France, Germany,
Italy, and Spain, 1995-
1997
Occupational exposure to Perc
assessed with job exposure matrix
A positive, non-significant
association was observed
between Mycosis Fungoides
and male subjects with
exposure to Perc >= median
of control exposure vs.
unexposed male subjects
(Morales-
Suarez-
Yarela et al.
2013)
High
Brain cancer:
glioma and
meningioma
cases
489 glioma cases, 197
meningioma cases, and
799 controls from three
USA hospitals in Arizona,
Massachusetts and
Pennsylvania
Occupational exposure to Perc via
self-reported occupational history
and industrial hygienist assigned
level of exposure
Perc was not significantly
associated with glioma or
meningioma
fNeta et al.
2012)
High
Cancer of the
liver
15 million people
participating in a decennial
census in Denmark,
Finland, Iceland, Norway,
and Sweden. Aged 30-64
in years 1960-1990.
Employment in dry cleaning
and/or laundering during time
period of predominant Perc use
Significantly elevated SIRs
were observed in women for
stomach, liver, cervical, oral
cavity, and lung cancers. No
association was found for
kidney, bladder, and non-
Hodgkin's lymphoma cancer
incidence in women.
(Pukkala et
al. 2009)
Medium
Diagnosis of
kidney cancer
General population case-
control study of kidney
cancer (1217 cases; 1235
controls). Detroit (2002 -
2007) and Chicago (2003).
lob exposure matrix was used to
determine years exposed, average
weekly exposure and cumulative
hours exposed, to perc
Increased risk of kidney
cancer for high intensity
exposure group; OR 3.0 (1.3 -
7.4) for 3rd tertile (>1820
hours) vs. unexposed for
cumulative hours exposed.
No significant associations
observed in for other levels of
perc exposure.
(Purdue et al.
2 )
High
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Outcome/
E-jtdpoint
Study E'opuhtfion
Kxposure
[Results
Reference
i);it:t Quniity
K\ iiiuiition
Mortality from
multiple
myeloma
Aircraft maintenance
workers (n = 14,457;
10,730 men and 3725
women) at Hill Air Force
Base (Utah. USA), for at
least one year from 1952-
1956, and followed up
through 2000
Occupational exposure to Perc
(yes/no) based on job-exposure
matrix; no quantitative
assessment available
Positive association between
mortality from multiple
myeloma and occupational
exposure to Perc compared to
no exposure (statistically
significant for females, non-
statistically significant for
males)
(Radican et
H :008)
Medium
Childhood
cancers, neural
tube defects,
oral clefts,
Children born to mothers
with exposure to
contaminated drinking
water at Camp Lejeune: 51
cases and 526 controls
Perchloroethylene (perc) in
drinking water during 1st
trimester of pregnancy; modelled
exposure high (>=44 ppb), low
(<44 ppb)
Positive, non-significant
associations observed
between childhood cancers
and any, high or low 1st
trimester exposure to perc
compared to unexposed).
(Ruckart et
al. 2013)
High
Age of
diagnosis of
breast cancer
(male only).
Case-control, male
Marines born before 1969,
diagnosed 1995-2013,
with identifiable tour
dates/locations
Perc, residential drinking water at
Camp Lejeune, cumulative
exposure >159 ppb
Non-significant positive
association between Perc
exposure and breast cancer
diagnosis and age of
diagnosis
(Ruckart et
al. 2015)
High
Glioma
Non-farm workers from
the Upper Midwest Health
Study (798 cases and 1141
controls from lawa,
Michigan, Minnesota, and
Wisconsin 1995-1997)
Perc (tetrachloroethylene) use
(self-reported occupational
history through 1992,
bibliographic database of
published exposure)
Perc was associated with a
significant decrease in
gliomas.
(Ruder et al.
2013)
High
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Outcome/
E-jtdpoint
Study E'opuhtfion
Kxposure
[Results
Reference
i);it:t Quniity
K\ iiiuiition
Total
lymphoma,
HL. B-NHL.
T-NHL. B-
NHL
subentities
(DLBCL. FL.
CLL, multiple
myeloma,
marginal zone
lymphoma)
710 participating cases
(matched to 710 controls)
with malignant lymphoma
among men and women
aged 18 to 80 years in 6
regions in Germany
Cumulative occupational
exposure to Perc [ppm*years]
based on intensity, the frequency,
and duration of Perc exposure (0
to >78.8 ppm*years)
Perc was not significantly
associated with malignant
lymphoma or any specific
type of lymphoma; however,
there was an increase (non-
significant) in risk of total
lymphoma in the highest
exposure group (>78.8
ppm* years).
(SeidJer et al.
2007)
High
Kidney,
bladder, liver,
NHL. overall
cancer
incidence
Swedish national cohort of
dry cleaning and laundry
workers (n = 10,389)
assembled in 1984
followed up for new cases
of cancer by matching
with the Swedish cancer
register from 1985 to 2006
Occupation as dry cleaners and
laundry workers exposed to
perchloroethylene; exposure
levels in the 1970s were of the
order of 100-200 mg/m3 (15-30
ppm)
Non-significant elevated risk
of Hodgkin's lymphoma,
kidney and liver cancer,
significantly elevated risk of
Non-Hodgkin's lymphoma
and lung cancer; no elevated
risk of bladder cancer
(Seidell and
Ah 1 bore
2 )
Medium
Kidney cancer
incidence
Greater Montreal
metropolitan area. Case-
control study of
occupationally-exposed
men aged 35 to 70 year
old (4263 cases, 533
population controls; also
hospital and cancer
controls).
Any or substantial exposure
ORs were not significantly
elevated for PCE exposure
and kidney cancer (no
quantitative data were
provided).
(Siemiatvcki
)
Medium
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Outcome/
E-jtdpoint
Study E'opuhtfiott
Kxposure
[Results
Reference
i);it:t Quniity
K\ iiiuiition
Bladder and
other urinary
cancer
mortality
National Institute for
Occupational Safety and
Health (NIOSH) Cohort.
34494 workers at NY
microelectronics and
business machine facility,
2009, 52-65yrs
Cumulative Perc exposure score
based on department-exposure
matrix
Perc was not significantly
associated with bladder and
other urinary cancers
mortality.
(Silver et al.
2014)
Medium
Testicular
cancer
National Institute for
Occupational Safety and
Health (NIOSH) Cohort.
34494 workers at NY
microelectronics and
business machine facility,
2009, 52-65yrs
Cumulative Perc exposure score
based on department-exposure
matrix
Perc was not significantly
associated with testicular
cancer incidence.
(Silver et al.
2014)
Medium
Acute myeloid
lymphoma
Cases of acute myeloid
leukemia (n= 14,3 3 7)
diagnosed between 1961
and 2005, and controls
(n=71.027) matched by
age, sex, and country
identified from the Nordic
Occupational Cancer
Study cohort
Cumulative Perc exposure
estimated using job exposure
matrix, Median (ppm-yr) 12.1
No significant increase in
acute myeloid leukemia risk
was observed with low,
moderate, or high exposure to
Perc, compared to referent
group when hazard ratios
were calculated using a 10-
year lag (p-value = 0.39).
Findings for analysis
stratified by sex or age were
not reported
(Talibov et
al. 2014)
High
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Outcome/
E-jtdpoint
Study E'opuhtfion
Kxposure
[Results
Reference
i);it:t Quniity
K\ iiiuiition
Cancer
diagnosis:
liver/biliary,
kidney,
bladder,
pancreas, lung,
cervix,
Hodgkin's
lymphoma, and
non-Hodgkin's
lymphoma
Adults working in the
Sweden during the 1960
and 1970 census,
including 31,418 women
and 15,515 men working
as launderers, dry cleaners,
or pressers
Occupation as a dry cleaner,
launderer, or presser served as
surrogate for Perc exposure
Increased incidence of
Hodgkin's disease
(significant), lung
(significant), cervix
(significant), liver/biliary
passages, kidney, and bladder
cancer, all other outcomes
were non-significant
(Travier et al.
2002)
High
Lung cancer
Lung cancer cases and
randomly selected
population-based controls
frequency matched by sex
and age in Montreal
Canada
Perc exposure (any or substantial)
was assessed by a team of
industrial chemists and hygienists
based on self-reported job
histories
Increase in OR for any
exposure or substantial
exposure to Perc, results were
only significant for any
exposure in Study I and in the
pooled analysis
(Vizcava et
al. 2013)
Medium
Liver and
kidney cancer,
non-Hodgkin's
lymphoma
(NHL) and
multiple
myeloma
(MM)
All subjects aged 30-64
years who participated in
1960 through 1990
censuses in Finland,
Iceland, Norway and
Sweden; five matched
controls per case
Job-exposure matrix, intensity x
prevalence of perchloroethylene
exposure (90th percentile: 0.05
units)
A positive, non-significant
association was observed
between high cumulative
perchloroethylene exposure
(intensity x prevalence) and
kidney cancer in men and
women.
(Vlaanderen
et al. 2013)
High
Renal pelvis
cancer, bladder
cancer
Employed Swedish
residents (1,014 and 360
renal
pelvis cancers and 18,244
and 3,347 bladder cancers
among
men and women,
respectively)
Occupation type (workers in
laundry, ironing, dyeing) or
industry
Non-significant excess risk of
renal pelvis cancer among
men working in laundry,
ironing, dyeing industry.
("Wilson et al.
2008)
Medium
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3.2.3.2.3 Carcinogenicity Animal Studies
(I ) performed a review of the animal toxicity data pertaining to carcinogenicity of PCE
from studies conducted through 2011. No additional animal cancer studies were located in U.S. EPA's
current systematic review. A summary of the database reviewed by ( ) for each cancer is
provided as follows. Full study details are provided in Appendix F.2.
Liver
Hepatocellular adenomas and carcinomas exhibited a dose-related increase in male and female B6C3F1
mice exposed by inhalation to PCE at 100 or 200 ppm for 103 weeks, with significant increases in
incidence of hepatocellular carcinoma and combined hepatocellular adenomas or carcinomas observed
at both exposure concentrations CNTP 1986a). A dose-related increase in hepatocellular adenomas or
carcinomas was also observed in male and female Crj:BDFl mice in a 2-year inhalation study, with
increases achieving statistical significance in both sexes at 250 ppm PISA 1993). A significant increase
in the combined incidence of hemangiosarcomas or hemangiomas, occurring in the liver, spleen, fat,
subcutaneous skin, and heart, was observed in male mice at 250 ppm PISA. 1993). In an oral study, the
incidence of hepatocellular carcinoma was significantly increased in male and female B6C3F1 mice
administered time-weighted average doses of 536 or 1,072 mg/kg-day in males and 386 or 772 mg/kg-
day in females for 78 weeks, with a decreased time to first tumor in treated male and female mice,
compared to controls (NCI 1977).
Kidney
Renal tubular adenomas and adenocarcinomas were observed in male, but not female, F344/N rats
exposed to PCE by inhalation at 200 or 400 ppm for 103 weeks CNTP 1986a); although incidence was
low, the rarity of renal tubular carcinomas in this strain of rat, in combination with the proliferative
lesions (renal tubular cell hyperplasia) observed in male rats and one female rat, suggest that these
findings are biologically significant.
Blood
A dose-related increase in the incidence and severity of MCL was observed in male and female F344/N
rats exposed to PCE by inhalation at concentrations up to 400 ppm for 103 weeks, with decreased time
to onset in exposed females CNTP 1986a). The incidence of advanced stage MCL was significantly
increased in both sexes at 400 ppm CNTP 1986a). (II ) also observed a positive dose-related
trend in the incidence of MCL in male and female F344/DuCrj rats exposed by inhalation for 2 years,
reaching statistical significance in males only at 600 ppm. The time to first occurrence of MCL was
reduced in exposed female rats, relative to controls (USA. 1993).
Brain
A slight, but biologically significant, increase in brain gliomas was observed in male and female F344/N
rats exposed to PCE by inhalation at 400 ppm for 103 weeks CNTP 1986a). The fact that this is a rare
tumor type, along with a decreased time to first tumor in exposed rats, support the biological
significance of this finding.
Testis
F344/N rats exposed to PCE vapors at 200 or 400 ppm for 103 weeks exhibited a significant positive
dose-related trend in the incidence of testicular interstitial cell tumors CNTP 1986a).
3.2.3.2.4 Mode of Action
Liver
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Modes of action considered by ( ) for liver cancer induced by PCE in mice include: (1)
genotoxicity; (2) epigenetic changes (altered DNA methylation); (3) cytotoxicity and oxidative stress;
and (4) peroxisome proliferator-activated receptor (PPAR) activation/peroxisome proliferation. Based
on their review of available data, both ( ) and ( ,014) determined that multiple
modes of action were likely responsible for liver tumors induced by PCE. A number of newer
publications (Luo et al. 2018b; Luo et al. 2018a; Cichocki et al. 2017; Luo et al. 201 ; Ihou et al. 2017;
Lacev et al. 1999) examining toxicokinetic and toxicodynamic responses in the livers of mice exposed to
PCE and the related compound, trichloroethylene, provide additional insight into the modes of action for
PCE liver cancers in mice.
Much of the research on liver carcinogenicity associated with PCE exposure has focused on the role of
the metabolite TCA. Further information on modes of action for TCA hepatocarcinogenicity can be
found in the ( ) Toxicological Review for TCA.
Role of metabolism
Available information on the metabolism of PCE in the liver suggests that the oxidative metabolism is
likely the dominant pathway, with glutathione conjugation occurring to a much lesser degree (IJ..S J_TA
2012c). Metabolism through the oxidative pathway was -30-fold higher than through the conjugation
pathway in male mice of three strains after single oral doses of 1,000 mg/kg PCE (Luo et al. 2018b). The
primary oxidative metabolite of PCE is trichloroacetyl chloride (TCAC) which is subsequently
hydrolyzed to TCA. Dechlorination of TCA could yield dichloroacetic acid (DCA); however, most of
the DCA excreted after exposure to PCE is believed to be produced in the kidney as an end product of P-
lyase metabolism (reviewed by (Guvton et al. 2014). Initially, oxidative metabolism of PCE was
believed to be mediated primarily by CYP2E1. However, (Luo et al. 2018a) observed TCA formation in
the livers of CYP2E1 knock-out mice (albeit at lower levels than in wild-type), showing that other CYPs
can also metabolize PCE to TCA.
Metabolites of the glutathione conjugation pathway also occur in the liver. In C57BL/65J mice given a
single dose of 100, 300, or 1,000 mg/kg PCE, dose-dependent increases in the concentrations of S-
(1,2,2-trichlorovinyl) glutathione TCVG and N-acetyl-S-(l,2,2-trichlorovinyl)-L-cysteine (NAcTCVC)
in the liver were seen, and the concentrations were higher in the liver than in kidney or serum in these
animals (Luo et al. , ). At 1,000 mg/kg, but not lower doses, S-(l,2,2-trichlorovinyl)-L-cysteine
(TCVC) was also detected in the liver (Luo et al. 2017). likely because oxidative metabolism was
saturated at this dose.
Genotoxicity in the liver
Individual studies of PCE genotoxicity are discussed above under Genotoxicity. As discussed in that
section, PCE shows little to no genotoxic activity in the absence of metabolic activation. Several
metabolites resulting from both the oxidative and conjugation pathways have shown some indication of
mutagenic activity in vitro, including TCAC, TCVG, TCVC, TCVC sulfoxide (TCVCS), NAcTCVC,
and PCE oxide. Among these, TCVG and NAcTCVC have been detected in the livers of C57BL/65J
mice. The primary metabolite in the liver, TCA, has shown little to no genotoxic activity in vitro, but
testing of this compound is confounded by the pH changes it induces. In vivo studies examining
genotoxicity have shown negative or equivocal effects (i.e. modest increases in DNA damage and DNA
binding in mouse) ( ). There is also general positive epidemiological evidence (not
kidney-specific) of genotoxicity from chronic PCE exposure in humans (Section 3.2.3.2.1).
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Epigenetic changes
Changes in the methylation of DNA have been shown to occur early in the development of most tumors
(I ). There are no studies examining mouse liver DNA methylation or other epigenetic
changes after exposure to PCE. A role for DNA hypomethylation in the hepatocarcinogenicity of PCE
has been postulated based on observations of hypomethylation, especially in the proto-oncogenes c-myc
and c-jun, in mouse liver after exposure to the metabolites TCA and DCA (IARC 2014; U.S. EPA.
2012c). Notably, c-myc DNA hypomethylation occurred earlier than increases in liver cell proliferation
(I c- 1 ^ :012c).
Cytotoxicity and oxidative stress
Studies in mice and rats exposed for at least 4 weeks provide clear evidence for the hepatotoxic effects
of PCE (see Section 3.2.3.1.4), and demonstrate that mice are more sensitive to these effects than are
rats. In mice, oral exposure to PCE has resulted in increased serum alanine aminotransferase (ALT)
levels, increased liver weight, hepatocellular hypertrophy, fatty degeneration and necrosis, and
regenerative cell proliferation/increased DNA synthesis ( ), while inhalation exposure
induced peroxisome proliferation, mitochondrial proliferation, increased relative liver weight,
centrilobular lipid accumulation/fatty degeneration, necrosis, and degeneration ( ). A
more recent study of male mice from 45 mouse strains given a single oral dose of PCE (1,000 mg/kg)
showed a range of hepatic effects at sacrifice within 24 hours postdosing; most strains showed
significant increases in liver triglycerides, and about one-third of the strains exhibited hepatosteatosis of
varying severities (Cichocki et al. ). PCE-induced accumulation of triglycerides in the liver appears
to require the presence of CYP2E1, as knock-out mice did not show this effect after 5 days of oral
exposure while wild-type mice and those expressing humanized CYP2E1 did.
In the one study that examined the relationship between hepatocyte toxicity and regenerative cell
proliferation in mice ( c), toxicity (manifested as increased plasma ALT) was evident
within 24 hours of exposure at all three dose levels (150, 500, and 1,000 mg/kg-day for 30 days). DNA
synthesis was increased at all doses after 7 days of exposure (the earliest time point measured), and
histopathologic evidence of regenerative repair was seen after 30 days of exposure to the two higher
doses(U ,S. EPA. 2012c). demonstrating that hepatocyte injury occurred early and may have preceded
cell proliferation.
In addition to regenerative cell proliferation, other sequelae of hepatotoxicity, including inflammation
and oxidative stress, could play a role in liver tumors induced by PCE. In humans, fatty liver resulting
from a high-fat diet is thought to increase oxidative stress, leading to genetic instability and release of
inflammatory mediators that contribute to the induction of hepatocellular carcinoma (reviewed by
(Takakura et al. )). As discussed above, hepatic triglyceride accumulation and fatty degeneration
are hallmarks of PCE exposure in mice. Limited data pertaining to the role of oxidative stress in PCE-
induced mouse liver toxicity or carcinogenicity are available, showing that administration of the
antioxidants vitamin E and taurine mitigated hepatic effects (increases in liver to body weight,
alterations in glycolytic and gluconeogenic enzyme and ATPase activities, and/or hepatocyte
degeneration and necrosis) in Swiss mice exposed to 3,000 mg/kg-day PCE for 15 days (
2012c).
Deferme et al. Q ) reported no increase in oxygen radical formation (measured by electron spin
resonance spectroscopy) in HepG2 cells exposed to 2 mM PCE in vitro for up to 72 hours. Consistent
with this result, (Deferme et al. 2015) did not observe a significant induction of genes related to
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oxidative stress after PCE exposure in this system. However, in B6C3F1 mice exposed via gavage, a
dose-related upregulation of genes involved in oxidation/reduction was observed after exposure to PCE
(Zhou et al. ^ ).
PPAR activation
PPARa is a ligand-activated transcription factor involved in the regulation of hepatic lipid metabolism.
In response to fasting, PPARa activation in mammals leads to upregulation of genes involved in fatty
acid P-oxidation, mitochondrial P-oxidation, gluconeogenesis, and autophagy, all aimed at providing the
fasted body with adequate glucose (reviewed by (Preidis et al.: )). Activation of the PPARa receptor
as a mechanism for hepatocarcinogenesis is proposed to operate through perturbations in cell
proliferation and apoptotic pathways, leading to clonal expansion of initiated cells ( ).
In laboratory animals exposed to PCE, several effects indicative of PPARa activation have been
observed, including increases in the number and size of liver peroxisomes ( ;), increased
expression of CYP4A peroxisomal marker enzymes (Cichocki et al. 2017; Zhou -n A JO I ; Hiilip et al.
2007). and increased hepatic levels of palmitoyl coenzyme A oxidase (PCO, also known as acyl CoA
oxidase) ( ). Studies comparing results in rats and mice have shown greater increases in
PCO in the livers of mice exposed to PCE than in rat livers after exposure to the same doses (
2012c). In vitro testing indicates that activation of mouse and human PPARa after exposure to PCE is
likely mediated primarily by the metabolites, TCA and/or DC A, as PCE itself was essentially inactive
(I ).
(I ) also reviewed the dose-response and temporal concordance between PPARa
activation and cell proliferation in SW mice exposed to PCE. The original study showed that cell
proliferation occurred at lower doses (>150 mg/kg-day after 7 days after exposure) and persisted longer
(14-30 days after exposure at 500 and 1,000 mg/kg-day) than increased expression of PPARa marker
CYP4A (1,000 mg/kg-day and only after 7 days of exposure). The study authors suggested that their
findings argued against a significant role of PPARa activation in PCE-induced liver carcinogenicity.
Citing other studies in mice and rats, ( ) noted that PCE induces a modest peroxisome
proliferating response in both species, but only mice develop liver tumors, indicating a lack of
concordance between peroxisome proliferation and occurrence of liver tumors across species.
Several notable papers probing the role of PPARa activation in mouse liver after PCE exposure were
published after the literature searches were performed for the (A.TSDR 2019). (IARC 2014). and (U.S.
E ) reviews. In a study comparing mouse liver and kidney transcriptomic responses to
equimolar oral doses of trichlorethylene and PCE, (Zhou et al. 2017) observed dose-related upregulation
of genes involved in PPARa signaling, fatty acid metabolism, and oxidation/reduction in the livers of
male B6C3F1 mice exposed to PCE. Genes related to the ATP binding cassette (ABC) family of
transporters were also upregulated by PCE; some of these transporters are involved in transportation of
cholesterol and lipids, and some are expressed exclusively in peroxisomes. Genes in mitochondria-
related pathways and nucleotide metabolism pathways were downregulated. The dose-related alterations
in gene expression were correlated both with external PCE dose and hepatic levels of TCA. While gene
expression changes related to PPARa signaling were common to both trichloroethylene and PCE, effects
on genes related to ABC transporters, mitochondrial pathways, and nucleotide metabolism were unique
to PCE (Zhou et al. ).
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Cichocki et al. (. ) published a seminal paper examining mouse strain variability in toxicokinetic and
toxicodynamic responses to PCE exposure. Male mice of 45 strains (Collaborative Cross) received a
single oral dose of 1,000 mg/kg PCE and were sacrificed at several time points up to 24 hours after
dosing. In this study, variability in liver TCA levels after exposure spanned almost an order of
magnitude. In addition, the toxicodynamic response to PCE varied: some strains exhibited significantly
lower body weight (as much as 15%); only a few showed significant differences in liver to body weight
ratio. Most strains showed significant increases in liver triglycerides with concomitant decreases in
serum triglycerides, and about one-third exhibited hepatic steatosis. Similarly, most strains showed
increased hepatic expression of PPARa markers CYP4A10 and Acoxl (the gene that encodes acyl CoA
oxidase or PCO); however, the degree of upregulation varied almost 600-fold across the strains.
(Cichocki et al.: ) noted that none of the significant effects of PCE on hepatic endpoints (including
CYP2E1 protein and triglyceride levels, expression of PPARa responsive genes, and histopathology
changes) was correlated with hepatic TCA levels across the tested strains. The reason why dose-related
gene expression changes were correlated with hepatic TCA levels in male B6C3F1 mice (Zhou et al.
2017) but not correlated across the strains tested by (Cichocki et al. 2017) is unclear, but could include
strain differences in CYP isozyme activities and saturation as well as toxicodynamic differences across
the strains.
Two studies of PPAR knock-out mice and mice expressing humanized PPARa exposed to the closely
related compound trichloroethylene provide insight into the role of PPARa activation in PCE-induced
liver effects in mice. PCE and trichloroethylene share the common metabolite TCA, which is believed to
play a role in the hepatic toxicity and carcinogenicity of both compounds. (Ramdhan et al. 2010)
compared the effects of trichloroethylene exposure via inhalation at 1,000 or 2,000 ppm (8 hours/day)
for 7 days in male Sv/129 wild type mice, PPARa(-/-) knock-out mice, and mice modified to express
human PPARa cDNA (hPPARa). Hepatic effects of trichloroethylene exposure that did not differ
significantly among the three strains included increased liver weight, increased plasma aspartate
aminotransferase (AST) and ALT, and histopathology evidence of liver necrosis. Hepatic inflammation
was observed at the highest exposure in all strains (and not in controls) but was of lesser severity in both
PPARa-null and hPPARa mice. Only wild type mice exhibited a significant increase in hepatocyte
proliferation, and only at the highest exposure. In contrast, only PPARa-null and hPPARa mice
exhibited significant increases in liver triglycerides (at both exposure levels in hPPARa mice, and at the
highest exposure only in PPARa-null) and hepatic steatosis (at both exposure levels in both strains). No
change in hepatic triglycerides or steatosis was seen in wild-type mice. Both wild-type and hPPARa
mice exhibited upregulation of PPARa target genes, while PPARa-null mice did not. Interestingly,
urinary excretion of TCA was significantly lower (by about half) in PPARa-null mice compared with
wild type and hPPARa mice, indicating that toxicokinetics may explain some of the differences in
effects.
To investigate the role of toxicokinetics, (Yoo et al. 2015) administered trichloroethylene by gavage
(400 mg/kg) to male and female mice (129Sl/SvImJ, PPARa-null, and hPPARa) once or 5 days/week
for 4 weeks and measured metabolite levels in liver, kidney, and serum, and their relationship to PPARa
activation. Marked sex-related differences in tissue levels of trichloroethylene, trichloroethanol (TCOH),
and TCA were observed after single or repeat dosing, with males exhibiting significantly higher
metabolite levels in liver, kidney, and serum. No differences between the strains were seen in levels of
TCOH in the liver, kidney, or serum, or in levels of TCA in serum after single or repeat dosing. After
both single and repeat dosing, TCA levels in the liver were significantly lower in PPARa-null and
hPPARa mice of both sexes compared with wild-type mice; in addition, with repeat dosing, the level of
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hepatic TCA in hPPARa males was significantly lower than in PPARa-null males. Despite much lower
levels of TCA, trichloroethylene-treated hPPARa mice of both sexes showed induction of CYP4A10 (a
marker of PPARa activation) expression in the liver, and the mRNA levels were comparable to those
seen in wild-type mice.
Summary
In summary, PCE appears to induce liver tumors in mice through multiple, potentially interdependent
modes of action mediated largely by metabolites, including mutagenicity, epigenetic changes,
cytotoxicity and oxidative stress, PPARa activation, and possibly also through other changes in gene
expression. TCA appears to be an important hepatic metabolite but is probably not the only metabolite
involved in hepatic effects of PCE. Available data show that the metabolism of PCE in the liver varies
by sex, strain, and CYP2E1 and PPARa genotypes, and that several PCE metabolites are genotoxic.
Based on limited data on PCE and studies of the related compound trichloroethylene, PPARa activation
is probably not a necessary event for PCE-induced liver tumors but may influence both the metabolism
and the nature of the hepatic effects induced. In addition to PPARa activation, PCE exposure also
upregulates genes involved in ABC transporters, and downregulates nucleotide metabolism and
mitochondrial-related genes. The relationship, if any, of these changes to the mode(s) of action for PCE
liver carcinogenicity is unknown.
Kidney
(I ) considered four potential modes of action for PCE-induced kidney cancers in rats: (1)
genotoxicity; (2) a2u-globulin accumulation; (3) PPARa agonism/peroxisome proliferation; and (4)
cytotoxicity not related to a2u-globulin accumulation. ( ) considered it likely that several
mechanisms contribute to renal carcinogenesis, but found evidence insufficient to draw further
conclusions, whereas (IARC 2014) concluded that genotoxicity resulting from PCE metabolites in the
kidney was the most likely mechanism for kidney cancers based on data available at the time of their
review.
Role of metabolism
(Irvine and Elfarra ! ) reviewed the available literature and concluded that the nephrotoxicity and
nephrocarcinogenicity of PCE are mediated primarily through P-lyase-dependent bioactivation of the
cysteine S-conjugate metabolite TCVC. The steps involved are as follows: PCE is conjugated to GSH in
the liver to form TCVG; TCVG is processed into the cysteine conjugate (TCVC) in the kidney, bile duct
epithelium, intestinal lumen, or bile canalicular membrane of hepatocytes; TCVC enters the circulatory
system and is translocated to the kidney; and P-lyase acts on TCVC to form dichlorothioketene, a
reactive electrophilic sulfur species. While TCVC has been found to be mutagenic in the Ames
Salmonella mutagenicity assay, the addition of an inhibitor of P-lyase to the test system has been found
to reduce the mutagenicity of TCVC, suggesting that the P-lyase-derived metabolites are primarily
responsible for the mutagenicity of TCVC.
TCVC may be N-acetylated in the kidney to form the mercapturic acid, NAcTCVC (Luo et al.: ).
Both TCVC and NAcTCVC may be further metabolized to form reactive sulfoxides (Luo et al. ).
TCVCS has been observed to have greater nephrotoxicity than TCVC (Elfarra and Krause 2007):
however, the mutagenic activity of TCVCS in Salmonella is 30-fold lower than that of TCVC (Irvine
and Elfarra 2013).
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In a study comparing glutathione-pathway metabolites of PCE in male mice of 45 different strains
administered PCE as a single gavage dose of 1,000 mg/kg, area under the kidney tissue concentration-
time curves (AUC) estimates for TCVG, TCVC, and NAcTCVC varied by at least 29-fold across the
strains (Luo et al. 2019). demonstrating marked variability in the metabolism of PCE. Tissue
concentrations of metabolites of the GSH pathway (liver TCVG, serum TCVG, liver NAcTCVC, and
kidney NAcTCVC) were found to be significantly correlated with increased kidney levels of Kim-1
(kidney injury molecule-1), a protein marker of proximal tubular injury (Luo et al. 2019). supporting a
link between this metabolic pathway and kidney toxicity.
PCE is also subject to oxidation, yielding TCA. Zhou et al. (2017) found quantifiable concentrations of
TCA in the kidneys of mice at single gavage doses of 300 mg/kg and higher. TCA levels in the kidney
were highly correlated with dose-related gene expression changes, including those related to
peroxisomal fatty acid P oxidation, in the kidney.
Genotoxicity in the kidney
As discussed above under Section 3.2.3.2.1, several metabolites of PCE are genotoxic, while the parent
compound itself shows little to no genotoxic activity in the absence of metabolic activation. The
evidence for genotoxicity of the primary renal metabolites of PCE is stronger than that for hepatic
metabolites, as reflected in the IARC conclusion that genotoxicity was the likely mode of action for the
renal tumors. Specifically, the renal metabolites TCVG, TCVC, TCVCS, and NAcTCVC have all shown
mutagenic activity in vitro. The mutagenicity of TCVG appears to depend on further metabolism via
cysteine conjugation, while NAcTCVC is mutagenic following deacetylation ( ),
suggesting that conversion to TCVC may be necessary for the mutagenic activity of these two
compounds. TCVC is mutagenic without metabolic activation in cell systems with P-lyase activity, and
the mutagenic action is blocked by inhibition of P-lyase (Irving and Elfarra 2013). indicating that P-
lyase-derived metabolites appear to be primarily responsible for the mutagenicity of TCVC. Species-
and sex-related differences in the activities of P-lyase and other enzymes in the glutathione pathway may
explain the sex- and species-specific renal carcinogenicity of PCE. As noted earlier, metabolic
differences among strains resulted in at least 29-fold differences in AUC estimates for TCVG, TCVC,
and NAcTCVC in the kidneys of male mice of 45 strains exposed to PCE (Luo et al. 2019). There is also
general positive epidemiological evidence (not kidney-specific) of genotoxicity from chronic PCE
exposure in humans (Section 3.2.3.2.1).
A2u-Globulin accumulation
Accumulation of a2u-globulin was considered as a mode of action for PCE-induced kidney cancer. This
mode of action is unique to the male rats because female rats and other mammalian species do not
accumulate a2u-globulin in the kidney. ( ) hypothesized the following sequence of key
events: excessive accumulation of a2u-globulin-containing hyaline droplets in renal proximal tubules,
cytotoxicity and single-cell necrosis of tubule epithelium, sustained regenerative tubule cell
proliferation, development of intralumenal granular casts containing sloughed cellular debris associated
with tubule dilatation and papillary mineralization, foci of tubule hyperplasia in convoluted proximal
tubules, and formation of renal tubule tumors.
Evidence of hyaline droplet nephropathy has been observed in male rats exposed to PCE (Bergamaschi
et al. 1992; Green et al. 1990; Gotdsworthy et al. 1988). Male F344 rats administered PCE via gavage at
1,000 mg/kg-day for 10 days showed increases in a2u-globulin, protein droplet accumulation,
crystalloid accumulation, and cell replication in proximal tubules (Gotdsworthy et al. 1988). The
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increased cell replication, which was correlated with a2u-globulin accumulation and occurred in the
same segment of the proximal tubule, is suggestive of a link between a2u-globulin accumulation and
kidney tumors ( ). Accumulation of a2u-globulin was also observed in the kidneys of
male rats exposed by gavage to PCE at 500 mg/kg-day for 4 weeks (Bergamaschi et al. 1992). (Green et
al. 1990) observed increased hyaline droplets in the proximal tubules of male rats exposed by gavage to
PCE at 1,500 mg/kg-day for 42 days, as well as in male rats exposed by inhalation to PCE at 1,000 ppm
for 10 days. Formation of granular tubular casts and evidence of tubular cell regeneration were also
observed in rats dosed with PCE at 1,500 mg/kg-day for 42 days (Green et al. 1990). However,
accumulation of a2u-globulin was not observed in the kidneys of male rats exposed by inhalation to 400
ppm for 6 hours/day for 28 days (Green et al. 1990). although (U.S. EPA.: ) notes that recovery
may have occurred during the 18-hour period between the final exposure and sacrifice. It is also possible
that a longer exposure at this concentration might be required for accumulation of a2u-globulin.
(I 012c) noted that a2u-globulin accumulation in response to PCE exposure has only been
observed at doses higher than those associated with kidney tumors. In addition, non-neoplastic kidney
lesions are not exclusively observed in male rats, as they have also been observed in female rats and
male and female mice, in which a2u-globulin accumulation does not occur. In addition, nephrotoxicity
has been observed in male and female rats and mice without hyaline droplet formation. (
2012c) concluded that there are insufficient data to demonstrate that PCE-induced renal cancers are
caused by a2u-globulin accumulation.
PPARa agonism/peroxisome proliferation
Another possible mode of action for kidney cancer examined by ( ) is PPARa
agonism/peroxisome proliferation. The following steps are hypothesized: activation of the PPARa
receptor by one or more reactive metabolites of PCE (e.g., TCA), resulting in alterations in cell
proliferation and apoptosis, followed by clonal expansion of initiated cells ( ).
In an in vitro study, PPARa derived from humans and mice was found to be activated by PCE
metabolites dichloroacetate and trichloroacetate, although not by PCE itself (Malonev and Waxman
1999).
In vivo, the activity of PCO, a marker for peroxisomal P-oxidation, was found to be increased (1.2 to
1.6-fold) in pooled kidneys of mice exposed to PCE by inhalation (6 hours/day) at 200 ppm for 28 days
or 400 ppm for 14-28 days, significantly increased (1.3-fold) in male rat kidneys at 200 ppm at 28 days
but not at 400 ppm, and significantly increased (1.2 to 1.6-fold) in female rat kidneys at 200 ppm at 28
days or 400 ppm at 14-28 days; however, there was no effect on renal catalase activity in rats or mice
and no peroxisome proliferation was observed in rat or mouse kidney at microscopic examination
(Odum et al. 1988). PCO activity was also increased in the kidneys of male rats (1.7-fold, not
significant) and male mice (2.3-fold, significant) administered PCE by gavage at 1,000 mg/kg-day for
10 days (Goldsworthy and Popp 1987). In addition, mice treated with a single dose of 1,000 mg/kg PCE
showed increased mRNA expression of PPARa-responsive genes in kidney tissue (Luo et al. 2019).
Similarly, by measuring gene expression in the kidney, (Zhou et al. 2017) observed dose-dependent
induction of genes associated with peroxisomal fatty acid P-oxidation pathways in a manner in mice
administered a single dose of PCE.
Overall, only modest effects on PPARa-activation, as indicated by peroxisomal enzyme activity, have
been observed after PCE exposure at doses exceeding those associated with kidney tumors (Odum et al.
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1988; Goldsworthy and Popn I''N7). (U.S. EPA. ^01 _v) concluded that there is no evidence for PCE (or
other compounds) that causally links PPARa-activation to kidney tumorigenesis.
Cytotoxicity not related to a2u-globulin accumulation
(I ) also examined renal cytotoxicity as a possible mode of action for kidney cancer. It
was suggested that sustained cytotoxicity and necrosis cause activation of repair processes and cellular
regeneration that may lead to renal neoplasms. Reactive metabolites of PCE, including TCVC and
TCVG, produced upon glutathione conjugation are known to result in kidney toxicity ( ).
TCVC has been observed to cause dose-related cytotoxicity, measured by release of lactate
dehydrogenase, in a porcine renal cell line (Vamvakas et al. 1989a) and in renal proximal tubule cells
isolated from male rats (Vamvakas et al. 1989b). 1,2,2-trichlorovinylthiol, an unstable thiol produced by
cleaving TCVC, may give rise to a highly reactive thioketene, which can form covalent adducts with
cellular nucleophiles ( c; Vamvakas et al. 1989b). In another in vitro study, (Lash et al.
2002) observed that PCE and its TCVG metabolite caused increased acute renal cytotoxicity in isolated
renal cortical cells from rats with the effect being greater in cells isolated from males, as compared to
females. In addition, TCVC was found to cause acute cytotoxicity in primary cultures of proximal
tubular cells from rat and human kidneys (IARC 2014).
Observed signs of non-neoplastic kidney toxicity in rodents exposed to PCE in vivo have included:
karyomegaly of the proximal tubules in male and female rats and mice (Jomkeretal. 1996; USA 1993;
N 6a), tubular cell hyperplasia in male and female rats (NTP 1986a). nephrosis (non-
inflammatory degenerative kidney disease) in female mice (NTP 1986a). casts in male and female mice
(NTP 1986a). atypical tubular dilation of the proximal tubules in male and female rats and mice (USA
1993). changes in urinary markers related to kidney function (total protein and N-acetyl-P-
glucosaminidase) in female rats (Jonker et al. 1996). glomerular nephrosis and degeneration in male and
female mice (Ebrahim et al. 1996). exacerbation of chronic renal disease in male rats (II O), and
toxic nephropathy in male and female rats and mice (NCI 1977). Male rats exposed to TCVC or
TCVCS, metabolites of PCE, by a single intraperitoneal injection showed visible acute renal tubular
necrosis, intratubular casts and interstitial congestion and hemorrhage (TCVCS only), increased urinary
glucose concentration and y-glutamyl transpeptidase activity, and increased blood urea nitrogen
(TCVCS only), with TCVCS exhibiting greater nephrotoxicity than TCVC (Elfarra and Krause 2007).
Although nephrotoxicity has been observed in both sexes of rats and mice, renal tubular neoplasia have
been observed only in male rats (NTP 1986a). In addition, signs of non-neoplastic kidney damage were
observed in rats and mice of both sexes in the early stages of the (NTP 1986a) inhalation study,
suggesting that animals of both species and sexes surviving to scheduled termination had sustained
nephrotoxicity for the majority of the study period; however, neoplasms were only observed in male
rats. This is inconsistent with nephrotoxicity being the primary mode of action for kidney neoplasms.
In humans, symptoms of renal dysfunction, including proteinuria and hematuria, have been observed in
patients administered PCE via inhalation as an anesthetic (IARC 2014). One study found an increased
incidence (>2.5-fold) of end-stage renal disease in dry cleaning workers exposed to PCE by inhalation.
Urinary markers of renal damage were found to be altered in dry cleaning workers by Mutti et al.
(1992); effects included increased prevalence of abnormal values for brush-border antigens, a higher
geometric mean concentration of brush-border antigens, and a higher concentration of tissue non-
specific alkaline phosphatase in urine. In addition, dry cleaning workers were observed to have
significantly increased urinary concentrations of P-glucuronidase and lysozyme, indicators of kidney
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function (IARC 2014). Effects on urinary indicators of renal tubule function, including significantly
increased prevalence of abnormal values of retinol-binding protein (Mutti et al. 1992) and a higher
geometric mean concentration of retinol-binding protein (IARC 2014) were observed in two of six
studies of dry cleaning workers.
Summary
In summary, available data provide evidence for mutagenicity as a likely mode of action for renal
carcinogenicity induced by PCE, while data supporting other candidate modes of action are more limited
and have unclear causal links to tumorigenesis.
Blood
There is no specific information pertaining to potential modes of action for PCE-induced hematopoietic
or immune system cancers. Limited data from studies investigating immunotoxicity suggest that PCE
exposure can alter white cell counts and immune system markers in humans and in mice (US J1.1A
2012c). A more recent in vitro study showed that PCE exposure increased the mRNA expression of
cytokines IL-6 and IL-10 in murine macrophages, albeit at cytotoxic concentrations (Kido et al. 2013).
IL-6 is a pro-inflammatory cytokine but is involved in other reactions as well; IL-10 is an anti-
inflammatory cytokine that may have been elevated as a response to the increase in IL-6. The role, if
any, of these immune system perturbations in carcinogenicity induced by PCE is unknown. (U.S. EPA.
2012c) noted that evidence for effects of PCE on hemolysis and bone marrow function in mice provides
some support for a leukemogenic effect in rodents but concluded that data were inadequate to establish a
mechanism for mononuclear cell leukemia in rats exposed to PCE.
Overall Conclusions
Overall, the reasonably available evidence for all three tumor sites likely supports a complex MO A, with
multiple contributing mechanisms of varying significance. There is evidence of kidney and liver-specific
genotoxicity from PCE metabolites and evidence of PCE genotoxicity in humans from epidemiological
studies. Induction of other non-genotoxic mechanisms including cytotoxicity and PPARa activation are
supported by various evidence, however there is insufficient causal link between these pathways and
tumorigenesis. Induction of these pathways is often at doses higher than which have been shown to
promote tumorigenesis, and the effects are not consistent across sex, dose, and time relative to the
results of cancer bioassays. While a-2u-globulin-based kidney toxicity in male rats is not relevant to
humans and the PPARa pathway is of reduced significant in humans, the reasonably available data does
not support a clear indication that these are major contributors to the tumorigenesis observed in animal
cancer bioassays. Therefore, animal carcinogenicity data is considered relevant to humans.
According to EPA's 2005 Guidelines for Carcinogen Risk Assessment (U.S. EPA. 2005a). "a linear
extrapolation approach is used when the mode of action information is supportive of linearity or mode of
action is not understood". The evidence for at least a significant contribution of a genotoxic MOA
supports use of the low-dose linear assumption, while other mechanisms are not well-enough supported
to suggest a potential threshold approach. Therefore, EPA used the low-dose linear default non-
threshold assumption for derivation of cancer slope factors (Section 3.2.5.3.3).
3.2.4 Weight of Scientific Evidence
3.2,4.1.1 Acute Toxicity
Acute exposures to PCE result in neurotoxicity effects that include central nervous system depression
and visual processing, including loss of consciousness which can result in death. These acute
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neurological effects are supported by both human and animal studies as described below in Section
3.2.4.1.2. There is only limited available information concerning acute irritation and hepatic effects and
the available evidence is insufficiently quantitative for use in dose-response analysis. Therefore, acute
toxicity other than neurological effects were not carried forward to dose-response analysis.
3.2.4.1.2 Neurotoxicity
The hazard database includes reported human evidence of visual deficits (Getz et al. 2012; Schreiber et
al. 2002; Gobba et al. 1998; Cavalleri et al. 1994; Altmann et al. 1990). impaired cognition (Echeverria
et al. 1995; Seet 3), increased risky behaviors with associated head injuries following prenatal or
early childhood PCE exposure (Aschengrau et al. 2016a; Aschengrau et al. 2011). and decreased math
test scores (Stineone et al.: ). Ambiguous or conflicting evidence was found for increased risk of
neurodegenerative diseases (Bove et al. 2014b; Goldman et al. ) and autism spectrum disorders
(Talbott et al. 2015; von Ehrenstein et al. s, 1 herts et ai. ^ alkbrenner et al. 2010). Clinical,
biochemical, and neurophy siological signs of neurotoxicity were observed in adult rodents (Mattsson et
al. 1998; Jonker et al. 1996; Tinston 1994; Kiellstrand et al. 1984) as well as indications of impaired
neurobehavior and motor function in developing rats (Nelson et al. 1979). A single 4-week inhalation
study in rats did not observe any clinical signs of neurotoxicity (Boverhof et al. 2013). however that
study was primarily focused on immunological endpoints. Overall, based on numerous identified
functional outcomes in human studies supported by both clinical and mechanistic findings in animals,
neurotoxicity following PCE exposure is supported by the weight of evidence. Based on consistent
supporting evidence and sufficient quantitative information, the endpoint of impaired visual function
(including delayed neurological signaling, color confusion, and visual memory) was carried forward for
dose-response analysis to represent the neurotoxicity hazard domain.
3.2.4.1.3 Kidney Toxicity
Mutti et al., (1992) and several other epidemiological studies from ( ) suggest likely
proximal tubular injury following long-term occupational exposure to PCE. Additionally, multiple
animal studies on both rats and mice demonstrated renal effects in both sexes, including increased
kidney weights, tubular histopathology, and other indications of kidney toxicity (Jonker et al. 1996;
Tinston I • > 4; USA. 1993; NTP 1986b; N> S l 7). Since the publication of the IRIS Assessment, a
single 4-week inhalation study in rats did not observe any effects on kidney weight or histology
(Boverhof et al. ). Overall, based on effects seen in multiple studies in both animals and humans,
kidney toxicity following PCE exposure is supported by the weight of evidence. Based on consistent
supporting evidence and sufficient quantitative information, the endpoints of urinary biomarkers for
nephrotoxicity and nuclear enlargement of proximal tubules were carried forward for dose-response
analysis to represent the kidney hazard domain.
3.2.4.1.4 Liver Toxicity
The human literature database is limited, with some indication that PCE exposure affects human liver
function as well as evidence of negative associations (Silver et al. 201 I; I c. < ^ \ JO I „v). The animal
database shows very strong support for liver toxicity following PCE exposure, with reports of necrosis,
vacuolization, inflammation, increased liver weight, biochemical markers, and other indicators of liver
toxicity in both rats (Jonker et al. 1996; \ s ) and mice (Buben and O'Flahern h'^85). A four-
week inhalation study in rats (Boverhof et al. 2013) that was published after the IRIS Assessment also
reported hepatic effects (increased relative liver weights and hepatocellular hypertrophy) at the highest
dose. Overall, based on strong and consistent evidence in animals, liver toxicity following PCE exposure
is supported by the weight of evidence. Based on consistent supporting evidence and sufficient
quantitative information, the endpoints of increased angiectasis, increased degeneration/necrosis, and
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increased liver/body-weight ratio were carried forward for dose-response analysis to represent the liver
hazard domain.
3.2.4.1.5 Reproductive/Developmental Toxicity
The EPA IRIS Assessment ( ) reported strong epidemiological evidence of adverse
pregnancy outcomes in women associated with PCE exposure. Human evidence was too limited to
conclude anything about sperm quality or infertility (\ c. < i1 \ JO I _V; Eskenazi et al. 1991). Data from
multiple human studies indicate an increased risk of spontaneous abortion ( ;). Animal
evidence supports effects on both male and female reproductive systems (U.S. EPA. 1:01 _v; Tinston
1994; Bellies et al. 1980) as well as developmental outcomes (I. c. < i1 \ JO I _v; Carney et al. 2006).
There were not any relevant studies published after the IRIS Assessment. Overall, evidence of both male
and female reproductive effects in animals as and associations between exposure and female
reproductive in humans along with indications of developmental effects in both study types, both
reproductive and developmental toxicity following PCE exposure are supported by the weight of
evidence. Based on consistent supporting evidence and sufficient quantitative information, the
reproductive endpoint of reduced sperm quality and the developmental endpoints of decreased
fetal/placental weight, developmental neurotoxicity, and skeletal effects were carried forward for dose-
response analysis to represent the reproductive/developmental hazard domain.
3.2.4.1.6 Immune System and Hematological Effects
Immune System Effects
The EPA IRIS Assessment ( ) summarized a large dataset of human studies, some of
which examined PCE as part of a class of solvents, as well as a few short-term animal studies. While
some indications of immune effects were observed, the available data was not robust or consistent
enough to conclude that immune effects are likely to result from PCE exposure. Studies published after
the IRIS Assessment provide conflicting evidence of immunotoxicity based on no effects observed on
immune organs (Boverhof et al. 2013) and positive indications of allergic reaction (Seo et al. 2012)
following PCE exposure. Overall, based on the absence of consistently observed effects in animals or
humans, the data for immune effects is inconclusive is not supported by the weight of evidence.
Therefore, this hazard domain was not carried forward for dose-response analysis.
Hematological Effects
Decreased red blood cells and hemoglobin levels with increased total white blood cell and lymphocyte
counts were observed in a single occupational epidemiology study as described in the EPA IRIS
Assessment ( ). Evidence of anemia was observed in mice but not rat studies (.
2012e) and the more recent 4-week inhalation study published after the IRIS assessment (Boverhof et al.
2013) also did not observe any hematological effects. Overall, while there is some indication of
hematological evidence in humans and mice, the human data is limited and conflicting results were
observed in rats and mice. Therefore, hematological effects following PCE exposure is insufficiently
supported by the weight of evidence and this hazard domain was not carried forward for dose-response
analysis.
3.2.4.1.7 Cancer
Weight of Evidence Conclusion
In accordance with EPA Guidelines for Carcinogen Risk Assessment ( [5a), PCE is
considered "likely to be carcinogenic in humans" by all routes of exposure based on conclusive evidence
in animals and suggestive evidence in humans.
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There is conclusive evidence of the carcinogenicity of PCE, administered by ingestion or inhalation, in
rats and mice. The most notable findings were statistically significant increases in the incidence of liver
tumors (hepatocellular adenomas and/or carcinomas) in male and female B6C3F1 and Crj:BDFl mice
exposed by inhalation PISA 1993; '.NT 5a) and male and female B6C3F1 mice exposed by
ingestion (N 7). Significant increases were also observed in the incidences of mononuclear cell
leukemia (MCL) in male and female rats (F344/N and/or F344/DuCrj) exposed to PCE by inhalation
(JV \ I , x I < 1986a). Additional findings potentially related to treatment included increases in
testicular interstitial cell tumors and renal tubular adenomas and adenocarcinomas in male F344/N rats
exposed by inhalation (NTP 1986a). brain gliomas in male and female F344/N rats exposed by
inhalation (NTP 1986a). hemangiosarcomas/ hemangiomas in male Crj:BDFl mice exposed by
inhalation ( ), and adenomas of the Harderian gland in male Crj:BDFl mice exposed by
inhalation ( ).
There is a pattern of evidence associating PCE exposure with several types of cancer, specifically
bladder cancer, NHL, and MM. Additional data were available showing weaker support for cancers at
other sites, including esophageal, lung, and blood (lymphoma). Studies provide more limited support for
associations with bladder and breast cancer, with little or no support for associations with kidney,
esophagus, or liver cancer or MM, and no useful information for cervical cancer.
Available data indicate that multiple modes of action are likely to be involved in PCE-induced liver
cancers in male and female mice and possibly renal cancers in male rats as well (Section 3.2.3.2.4).
Metabolism is a key event in the modes of action for both liver and kidney carcinogenicity. Importantly,
there appear to be marked sex- and strain-related differences, and possibly species differences, in the
degrees of oxidative and glutathione conjugative metabolism of PCE, which could explain the species
and sex specificity of liver and kidney tumors induced by this compound. Several PCE metabolites
originating from the glutathione pathway are mutagenic, particularly the electrophilic sulfur species that
result from P-lyase activation of TCVC in the kidney. There is less evidence for non-mutagenic modes
of action for kidney carcinogenicity associated with PCE exposure; available data do not support
significant roles for a-2u globulin accumulation, cytotoxicity unrelated to a-2u globulin accumulation or
PPARa agonism in renal tumor formation. In contrast, there is evidence suggesting that several modes
of action, in addition to mutagenicity, may be operant in the liver, including: epigenetic changes leading
to oncogene activation; cytotoxicity, inflammation, and oxidative stress; activation of PPARa leading to
perturbations in cell proliferation or apoptosis; and other changes in gene expression that may influence
cellular energetics, growth, and/or cell cycle. The importance of any one of these modes of action likely
depends on dose, species, sex, and strain, given the variability in and importance of PCE metabolism to
the various modes of action.
3.2,5 Dose-Response Assessment
3.2.5.1 Selection of Studies for Dose-Response Assessment
Dose-response analysis started with the consideration of all acceptable toxicity studies identified in the
prior sections and selection of the studies that reported both adverse effects and data amenable to dose-
response assessment. Dose-response assessment was organized into 5 domains: (1) acute toxicity, (2)
neurotoxicity, (3) kidney toxicity, (4) liver toxicity and (5) reproductive/developmental toxicity.
3.2.5.1.1 Non-Cancer Toxicity from Acute/Short-Term Exposure
Based on the weight of the scientific evidence evaluation neurotoxicity was selected for dose-response
analysis for effects from acute/short-term exposure. Quantitative data amenable to dose-response
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assessment from human studies (controlled experiments) are available for this endpoint. Studies
available for evaluating acute exposures include controlled human exposures (Altmann etal. 1990).
Data are also available from animal studies to support this health effect domain following acute
exposure. The human studies are considered adequate and are preferable to animal studies.
In the study by Altmann et al. (1990). male volunteers were exposed to PCE at 10 or 50 ppm,
4 hours/day for 4 days. At 50 ppm, increased latencies in pattern reversal visual-evoked potential
(/;<0,05) were observed. No effects on brainstem auditory-evoked potential were noted at either
concentration. Because faint odor was reported by 33% of the subjects at 10 ppm and 29% of the
subjects at 50 ppm on the first day of testing, and by 15% of the subjects at 10 ppm and 36% of the
subjects at 50 ppm on the last day of testing, the investigators concluded that only a few subjects could
identify their exposure condition. PCE in the blood increased with exposure duration, and based on
linear regression, PCE was associated with increased pattern reversal visual-evoked potential latencies
(r=-0.45,/><0.03) (Altmann et al. 1990). EPA considered a no-observed-adverse-effect level (NO A EL)
of 10 ppm for exposures of 4 hours/day. The study scored a medium in data quality.
Other studies assessed different endpoints in the spectrum of neurotoxicity effects. Hake and Stewart
(1977) exposed 4 male subjects sequentially to 0, 20, 100, and 150 ppm (each concentration 1 week)
PCE 7.5 hours/day for 5 days. Changes in flash-evoked potentials or equilibrium tests were not
observed. Subjective evaluation of EEG (electroencephalogram) scores suggested cortical depression in
subjects exposed at 100 ppm. Decreases in the Flanagan coordination test were observed at >100 ppm.
Rovve et al. (1952) exposed 6 volunteers to 106 ppm PCE for 1 hr. Eye irritation and a slight fullness in
the head was noted by one subject, but other neurotoxicity endpoints were not evaluated.
The National Research Council (NRC) (2 ) review of the PCE IRIS assessment included a
recommendation of five studies for consideration in deriving the reference concentration (RfC) (Boyes
et al. 2009; Gobba et al. 1998; Echeverria et ;il Cavalleri et ;il l""t; Altmann et al. 1990). Of
these studies recommended for consideration by NRC two are acute studies [the human chamber study
of Altmann et al. (1990) and the rodent study of Boyes et al. (2009)1. These were judged by EPA in the
IRIS assessment to be supportive, but were not considered further for deriving candidate RfCs because
of the preference to use quality studies of chronic, human exposures over studies of acute exposures. For
the dose-response assessment of effects from acute exposures the Altmann et al. (1990) study in humans
is preferred rather than the Boyes et al. (2009) study in rodents.
Based on these considerations, EPA chose the effects observed in Altmann et al. (1990) for dose-
response analysis of acute effects. These studies identified increased latencies for pattern reversal visual-
evoked potentials at 50 ppm and a NOAEL of 10 ppm.
3,2,5,1,2 Non-Cancer Toxicity from Chronic Exposure
The studies presented below are the principal studies containing adequate quantitative dose-response
information for various endpoints within each health domain. See Section 3.2.5.4 for selection of the
most representative studies within each domain.
Neurotoxicity
Based on the review in the EPA IRIS Assessment for PCE ( 2012c) and NRC (2010), two
studies, Cavalleri et al. (1994) and Echeverria et al. (1995). are considered the principal studies for the
evaluation of chronic neurotoxicity. Endpoints selected were reaction time measures (Echeverria et al.
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1995). cognitive changes (Echeverria et al. 1995). and visual function changes (Cavalier! etal. 1994).
EPA's data quality evaluations of these studies were both medium. The 2012 Perchloroethylene IRIS
Assessment ( ) additionally calculated the midpoint of the range from these two studies,
and this value was also brought forward to dose-response analysis.
Kidney
Two acceptable studies were identified that contained adequate dose-response information: (Mutti et al.
1992) and ( 93). Mutti et al. (1992) was an epidemiological study that identified urinary markers
of neprotoxicity. J IS A (1993) observed nuclear enlargement of proximal tubules in both rats and mice.
Mutti et al. (1992) scored a Medium in data quality and J1SA (1993) scored a High.
Liver
Three studies were considered for dose-response analysis of liver effects. The same J1SA (1993) study
that examined kidney effects also observed increased liver angiectasis (extreme dilation of blood or
lymph vessels) in mice. An NTP study (1986b) that also scored high in data quality identified increased
liver degeneration and necrosis in mice, while the medium-quality study (Buben and O'Flah 85)
reported increased liver/body weight ratio in mice following PCE administration.
Reproductive/Developmental
A single reproductive study reported adequate dose-response information. Beliles et al. (1980) identified
reduced sperm quality following 5 days of PCE exposure in mice. The study scored a high in data
quality.
For developmental effects, three relevant studies were identified. Nelson et al. (1979) identified
decreased weight gain and developmental neurotoxicity in the form of altered behavior and changes in
brain acetylcholine. The study only scored a Low in data quality, however it was still considered for
dose-response analysis because it is the only identified study with adequate dose-response information
relating to functional and molecular indicators of developmental neurotoxicity, and the CNS is an
important target of perchloroethylene. The other two studies both scored a High in data quality and were
also utilized for dose-response analysis. Tinston et al. ( |) identified increased neonatal pup death and
CNS depression in a two-generation study, and (Carney et al. 2006) observed decreased fetal/placental
weight and skeletal effects in a short-term developmental toxicity study.
3.2.5.1.3 Cancer
As discussed in the Weight of Evidence Section 3.2.4.1.7, based on EPA Guidelines for Carcinogen
Risk Assessment ( 305a). PCE is characterized as "likely to be carcinogenic in humans by all
routes of exposure," based on conclusive evidence in mice and rats and suggestive evidence in humans.
No available human studies of cancer were found to be suitable for dose-response assessment.
Therefore, the following dose-response assessment is based on data from rodent bioassays. Multiple
MO As for PCE carcinogenicity were considered in the MOA Section 3.2.3.2.4 specific to each tumor
type. Overall, the tumors reported in rodent bioassays are considered relevant to humans and human
cancer risks are estimated from the rodent dose-response data.
As discussed in Section 3.2.3.2.3 three chronic exposure studies in rats and mice include an oral gavage
study in mice and female rats by the National Cancer Institute (NC ) and two inhalation studies in
mice and rats (USA 1993; NTP 1986b) established that the administration of PCE, either by ingestion or
by inhalation to sexually mature rats and mice, results in increased incidence of tumors. Mouse liver
tumors (hepatocellular adenomas and carcinomas) and rat mononuclear cell leukemia (MCL) were
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reported in both sexes in two lifetime inhalation bioassays employing different rodent strains (JISA
1993; NTP 1986bI and mouse liver tumors were also reported in both sexes in an oral bioassay (NCI
1977). Tumors reported in a single inhalation bioassay include kidney and testicular interstitial cell
tumors in male F344 rats (NTP 1986b). brain gliomas in male and female F344 rats (NTP 1986b). and
hemangiomas or hemangiosarcomas in male Crj:BDFl mice (JISA 1993). The NCI (1977) study was
considered to be inconclusive because of the high incidence of respiratory disease, and high mortality
with PCE exposure. See (U.S. EPA 2012e) for more discussion.
All three bioassays (JISA 1993; NTP 1986b; NCI 1977) showed increases in hepatocellular tumors in
male and female mice. Hemangiomas also increased in male mice and MCL increased in both sexes of
rats. The data is summarized in Table 3-4 below.
Despite the positive results, the NCI (1977) study was considered to be inconclusive because of the high
incidence of respiratory disease, and high mortality with PCE exposure. Therefore considered the JISA
(1993) and NTP (1986b) studies for dose-response analysis. Both studies scored a High for data quality,
however (JISA 1993) examined an additional dose level and covers a broader dose range. Therefore, the
JISA (1993) study was selected for use in dose-response analysis and POD derivation. It is bolded in
Table 3-4 below.
Table 3-4. Tumor incidence in mice exposed to PCE
Doses/Exposures
Body
Survival-adjusted
Administered
Continuous
Weight3
tumor incidenceb
Bioassay
Equivalent
Sex
(kg)
(%)
Hepatocellular adenomas or carcinomas
NCI (1977)°
B6C3Fi mice
Gavage:
5 d/wk,
78 wk
Vehicle control
450 mg/kg-day
900
0e mg/kg-day
332
663
Male
0.030
2/20
32/48
27/45
(10)
(67)
(60)
Vehicle control
300 mg/kg-dayd
600
0e mg/kg-day
239
478
Female
0.025
0/20
19/48
19/45
(0)
(40)
(42)
NTP (1986b)
B6C3Fi mice
Inhalation:
0 ppm
100
200
0 ppm
18
36
Male
0.037
17/49
31/47
41/50
(35)
(70)
(82)
6 lir/d,
5 d/wk,
104 wk
0 ppm
100
200
0 ppm
18
36
Female
0.032
4/45
17/42
38/48
(9)
(40)
(79)
JISA(1993)
Crj:BDFl mice
Inhalation:
0 ppm
10
50
250
0 ppm
1.8
9.0
45
Male
0.048
13/46
21/49
19/48
40/49
(28)
(43)
(40)
(82)
6 hr/d,
5 d/wk,
104 wk
0 ppm
10
50
250
0 ppm
1.8
9.0
45
Female
0.035
3/50
3/47
7/48
33/49
(6)
(6)
(15)
(67)
Hemangiosarcomas6, liver or spleen
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Doses/ r.\|)osu res
Sex
IJod>
Weigh l-1
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During problem formulation ( :018d). EPA identified potentially exposed or susceptible
subpopulations during the development and refinement of the life cycle, conceptual models, exposure
scenarios, and analysis plan. In this section, EPA addresses the potentially exposed or susceptible
subpopulations identified as relevant based on greater susceptibility. EPA addresses the subpopulations
identified as relevant based on greater exposure in Section 2.4.3.
Factors affecting susceptibility examined in the available studies on PCE include lifestage, biological
sex, genetic polymorphisms, race/ethnicity, preexisting health status, lifestyle factors, and nutrition
status. PCE is lipophilic and accumulates in fatty fluids and tissues in the human body (Section 0).
Additionally, the PCE half-life is substantially higher in adipose tissue compared to others (55-65 hours
in adipose, <12-40 hours in others, see Section 3.2.2.1.3). Subpopulations that may have higher body fat
composition, and therefore may be more highly exposed to sustained internal PCE concentrations/doses,
include pubescent and adult women (including women of child-bearing age) as well as any individual
with an elevated body-mass-index. Based on evidence of developmental toxicity from PCE exposure,
pregnant women, the developing fetus and newborn infants are all considered highly susceptible
subpopulations, and therefore women of childbearing age are susceptible by proxy. Effects on male
fertility are more likely to present in older men, while kidney and liver effects are of most concern to
subpopulations with pre-existing liver or kidney dysfunction. The partitioning of PCE to fatty tissue is of
particular concern for those with fatty liver disease. Neurological endpoints are primarily related to
visual function, pattern recognition, and memory. Therefore, subpopulations with poor vision or
neurocognitive deficiencies may be especially susceptible to these hazards.
Variability in CYP metabolic capacity is generally believed to vary by approximately 10-fold among all
humans, however individual variations in in vitro CYP2E1 activity as high as 20-50 fold have also been
reported. Diagnoses of polymorphisms in carcinogen-activating and -inactivating enzymes and cancer
susceptibility have been noted, and GST polymorphisms have been associated with increased risk of
kidney cancer in the related chemical trichloroethylene. Co-exposure to other pollutants and drugs may
also have either an activating or inhibitory effect on PCE-metabolizing enzymes ( ).
3.2.5.3 Derivation of Points of Departure (PODs)
3.2.5.3.1 Non-Cancer PODs for Acute/Short-term Inhalation Exposure
Workers and consumers can be exposed to a single acute exposure to PCE under various conditions of
use via inhalation and dermal routes. EPA identified PODs for several acute inhalation exposure
durations based on both hazard and exposure considerations. The duration of 4 hrs/day is based on the
study conditions of Altmann et al. (1990). Longer durations of 8 hrs/day and 12 hrs/day are
representative of typical work shifts and are used for occupational settings. For consumers, EPA also
evaluated a 24-hr exposure to account for exposure scenarios when a user remains in the house after
using a PCE-containing product, i.e., a consumer product used for a specific length of time, with
subsequent exposure to dissipating concentrations of PCE in the indoor environment over the course of a
day. Conversion of the acute PODs for different exposure durations are shown in Table 3-5.
Altmann et al. (1990) is a relatively well-conducted study of 10 volunteers each that identified increased
latencies for pattern reversal visual-evoked potentials after 4 hrs/day for 4 days exposure to 50 ppm and
no effects at 10 ppm. EPA's data quality evaluation rated this study medium quality. EPA used the
NOAEC of 10 ppm. The ATSDR Toxicity Profile included this NOAEC among endpoints for derivation
of the acute MRL (minimum risk level) (ATSDR 2019). The acute MRL is derived for exposures up to
14 days and additional information was considered for exposures longer than the 4 days of the Altmann
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et al. (1990). This is consistent with how EPA is considering Altmann et al. (1990) for acute exposures
to workers and consumers.
Table 3-5. Conversion of Acute POPs for Different Exposure Durations
I'1\|)umiiv Dui'iilion
POI)
r.riWi
Tol;il I nccrliiiiiM
l";iclor (I I") lor
liciichniiirk MOI.
Reference
Diilii Qu;ilil\
4 hrs/day
duration of the study
10 ppm
(68 mg/m3)
Neurotoxicity
increased
latencies for
pattern reversal
visual-evoked
potentials
UFA=1;
UFh=10;
UFl=1
Total UF=10
Altmann et al.
(1990)
Medium
8 hrs/day
5 ppm
(34 mg/m3)
12 hrs/day
3.3 ppm
(22 mg/m3)
24 hrs/day
1.7 ppm
(11 mg/m3)
EPA applied a composite UF of 10 for the acute inhalation benchmark MOE, based on the following
considerations:
1) Interspecies uncertainty/variability factor (UFa) of 1 - Accounting for differences
between animals and humans is not needed because the POD is based on data from humans
2) A default intraspecies uncertainty/variability factor (UFh) of 10 - To account for
variation in sensitivity within human populations due to limited information regarding the
degree to which human variability may impact the disposition of or response to PCE. Some
of the specific variabilities/uncertainties for PCE are accounted for with this UFh include
toxicokinetic differences.
3) A LOAEC-to-NOAEC uncertainty factor (UFl) of 1 - The POD is based on a NOAEC so
this factor is not needed.
3.2.5.3.2 Non-Cancer PODs for Chronic Inhalation Exposure
All chronic PODs were derived as 24hr Human Equivalent Concentration (HEC) values, with results
from animal studies adjusted for continuous exposure based on the output from the PBPK model as
presented in ( ). All PODs are presented in
Table 3-8.
Neurotoxicity
EPA identified LOAELs for color confusion from (Cavalleri et al. 1994) and impaired pattern
recognition and reaction time in pattern memory from (Echeverria et al. 1995) as relevant endpoints for
POD derivation. For the studies and endpoints selected, it was determined that PODs could not be
derived using dose-response modeling (described in more detail in ( )). Therefore, the
midpoint of the range of the two LOAELs from each study was also derived as a representative POD.
This is consistent with the use of the midpoint for the reference concentration/dose in ( ).
For occupational human studies such as these, the HEC derivation also involved adjusting the breathing
rate from 10 m3/day over 8 hrs to 20m3/day over 24 hrs, and multiplying the PODs by 5/7 to adjust from
weekday working hours to continuous exposure ( ).
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EPA applied a composite UF of 100 for the inhalation benchmark MOE for neurotoxicity, based on the
following considerations:
1) Interspecies uncertainty/variability factor (UFa) of 1
Accounting for differences between animals and humans is not needed because the POD is based
on data from humans
2) An intraspecies uncertainty/variability factor (UFh) of 10
To account for variation in sensitivity within human populations due to limited information
regarding the degree to which human variability may impact the disposition of or response to,
PCE.
3) A LOAEC-to-NOAEC uncertainty factor (UFl) of 10
The POD is based on a LOAEC so this factor is needed.
4) Subchronic to chronic factor (UFs) of 1
The data for these endpoints come from chronic studies covering greater than 10% of human
lifetime, so an additional adjustment for shorter-duration studies is not required.
Alternative HEC for Occupational Scenarios
In addition to the HEC derived from the 2012 IRIS Assessment ( ), EPA derived 8 hr
HEC values for the above endpoints based on occupational exposure.
The 24 hr HEC as originally derived was applicable to the general population, who would be
continuously exposed to PCE at a resting breathing rate. The data for these endpoints are from
epidemiological studies of dry cleaning and laundry workers exposed to PCE. In order to account for
increased breathing rate of workers (i.e. 10 m3 over 8 hr as opposed to 20 m3 over 24 hr, according to
(I 012e), EPA additionally derived 8 hr occupational HECs using the 8 hr LOAEC values
from the original studies. 12 hr HECs were also derived based on adjustment from the 8 hr values for
use with 12 hr Occupational Exposure Scenarios (OES). These additional derivations did not result in
any change to the uncertainty factors.
Kidney
EPA identified a LOAEL from (Mutti et; ) for urinary biomarkers along with NOAELs from
PISA 1993) for proximal tubule nuclear enlargement in both mice and rats. Cumulative UFs for the two
NOAELs is 30, with a UFh =10 for human uncertainty/variability and UFa = 3 for interspecies
toxicodynamic uncertainty/variability, because only toxicokinetic differences are captured by the PBPK
model. The LOAEL from (Mutti et al. 1992) is a human study and therefore has a UFa of 1, however it
has an additional UFl of 10 for being based on a LOAEL and therefore the cumulative UF is 100. All
studies are of chronic duration, so UFs = 1.
Liver
EPA identified three distinct liver endpoints in mice as suitable for dose-response analysis. The NOAEL
from ( 3) for increased angiectasis (abnormal dilation of blood vessels) has a cumulative UF of
30 based on UFa and UFh as described above. A LOAEL was obtained for increased liver
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7899
7900
7901
7902
7903
7904
7905
7906
7907
7908
7909
7910
7911
7912
7913
7914
7915
7916
7917
7918
7919
7920
7921
7922
7923
7924
7925
7926
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degeneration/necrosis from (N 6b), resulting in a cumulative UF of 300 due to the added UFi of
10. These two studies are of chronic duration, so UFs = 1. A LOAEL for increased liver/body-weight
ratio from subchronic data in (Buben and O'Flahertv 1985) has a cumulative UF of 3000 due to the
added UFl of 10 and UFs = 10.
Reproductive/Developmental
A reproductive NOAEL for reduced sperm quality in mice was obtained from (Bellies et al. 1980).
Despite being of only 5 days exposure, this duration this exposure duration covers the window of sperm
production while the observation period up to 10 weeks covered the full period of spermatogenesis.
Therefore, longer exposure would not be expected to result in additional sensitivity and UFs = 1. The
cumulative UF is 30 based on UFa and UFh as described above. PODs from three developmental
toxicity studies in rats (Carney et al. 2006; Tinsti I; Nelson et al. 1979) were derived. The
durations were sufficient to cover the developmental window, so UFs = 1 and cumulative UF= 30 based
on NOAELs from animals as previously described.
3.2,5.3.3 Cancer Slope Factor Derivation
This section provides details of the dose-response modeling carried out for developing cancer risk values
and is summarized from the EPA IRIS Assessment for PCE ( ;). This summary focuses
on hepatocellular tumors, the tumor type that was observed in all three animal bioassays and was the
basis of the cancer slope factors in the EPA IRIS Assessment for PCE ( ). The steps
include estimation of dose metrics using relevant PBPK modeling, suitable adjustment to continuous
daily exposures from intermittent bioassay exposures, dose-response modeling in the range of
observation, interspecies extrapolation, extrapolation to low exposures, and route-to-extrapolation. An
overview of these steps is provided in Figure 3-2.
As stated previously, the available evidence likely supports a complex MOA for PCE tumorigenesis,
with multiple contributing mechanisms of varying significance. Based on EPA's 2005 Guidelines for
Carcinogen Risk Assessment ( 5a), a low-dose linear default approach is supported
because the "mode of action information is supportive of linearity or mode of action is not understood."
Therefore, EPA derived cancer PODs as an inhalation unit risk (IUR) and oral slope factor (OSF) based
on this linear modeling approach.
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Administered dose in
inhalation/oral animal
bioassay
Animal PBPK model
Lifetime average daily dose metric
Preferred Dose Metrics
Alternative Dose Metrics
AUC of
Rate of
Rate of
tetra-
AUC of
kidney
liver
chloro-
TCAin
GSH
oxidation
ethylene
blood
conjuga-
in blood
tion
Fit dose response model
y to observed response
POD in units of lifetime
average daily dose
metric
BMR -f POD
V
Slope Factor in units of
risk/(lifetime average
_ciail\KJosfMTTetn^l
If dose metric is
rate of oxidation or
of conjugation,
apply BW3/4 scaling.
Otherwise assume
. equal AUCs,
Slope Factors as
risk/(Human Equivalent
lifetime daily dose metric)
Human PBPK model
V
7928
Slop^arto^^nr^is^^sSc7(Human
Equivalent continuous inhalation or oral
^^envimnmenta^xposui^Jevel^^^
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7929 Figure 3-2. Sequence of steps for extrapolating from PCE bioassays in animals to human-
7930 equivalent exposures expected to be associated with comparable cancer risk (combined
7931 interspecies and route-to-route extrapolation).
Page 305 of 636
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7932
7933
7934
7935
7936
7937
7938
7939
7940
7941
7942
7943
7944
7945
7946
7947
7948
7949
7950
7951
7952
7953
7954
7955
7956
7957
7958
7959
7960
7961
7962
7963
7964
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Several metabolites of PCE are genotoxic both in vivo and in vitro (Section 3.2.3.2.1), and it is thought
that the hepatocarcinogenicity of the parent compound is mediated through the action of one or more of
its metabolites (Section 3.2.3.2.4). Oxidative metabolism is thought to predominate in the liver, and
TCA is the major resultant urinary excretion product. As discussed in Section 3.2.3.2.1, TCA appears to
be formed from spontaneous decomposition of trichloroacetyl chloride, which is known to bind to
macromolecules. Dichloroacetic acid (DCA) may be formed from dechlorination of TCA, but DCA
produced from this pathway is likely to be rapidly metabolized in the liver and not detected in blood or
urine. DCA that has been detected in urine is thought to be the result of kidney- specific P-lyase
metabolism of the results of GSH conjugation of PCE, and DCA produced from this pathway is
presumed to not play a role in liver toxicity or cancer. The potential role of GST conjugates of PCE in
liver carcinogenicity, although unknown, is presumed to be less important than the role of oxidative
metabolites.
As described in ( ) EPA modeled the J IS A bioassay data PISA 1993) for male and
female mice using the dose metrics of total liver oxidative metabolism, PCE AUC, and TCA AUC in
blood. Total liver oxidative metabolism is considered the most relevant dose-metric for liver cancer and
TCA AUC in liver was an alternative dose metric. Total liver oxidative metabolism was selected as the
primary dose metric over TCA AUC because while TCA is the major resultant urinary excretion product
of oxidative metabolism, TCA is not formed directly but instead from hydrolysis of trichloroacetyl
chloride (Section 3.2.3.2.4). Tumor phenotype data also suggest that TCA may not be the sole
tumorigenic metabolite of PCE, although the limited available data precludes any definitive conclusions.
PCE AUC in blood was considered the best dose metric for hemangiomas/ hemangiosarcomas in female
mice and MCL in both male and female rats. Modeling for both dose metrics generated fits for one-,
two-, and three-stage models (details for hepatocellular cancer in Appendix E). All model fits had
adequate goodness-of-fit p-values (p > 0.05), and overall adequate fit. A summary of the results for
hepatocellular adenomas or carcinomas, hemangiomas/hemangiosarcomas, and MCL from J IS A (1993)
are shown in Table 3-6 based on the preferred dose metric. Extrapolation to humans using total
oxidative metabolism led to a BMDio of 2.9, and its lower bound benchmark dose (BMDLio) was 1.4-
fold lower at 2.1 mg/kg3/4-day liver oxidative metabolism. Linear extrapolation from the POD to low
internal dose, followed by conversion to human exposures, led to a human equivalent unit risk of 1.8 x
10"3 per ppm. Extrapolation to humans using TCA AUC in liver led to a human equivalent internal dose
POD (BMCLio) of 69 mg-hr/L-day TCA in blood. Linear extrapolation from the POD to low internal
dose, followed by conversion to human exposures, led to a human equivalent unit risk of 1.5 x 10"3 per
ppm, slightly lower than the estimate using total liver oxidative metabolism. Dose-response modeling of
the male mouse liver tumor data using administered exposure fit the data points similarly to when using
total oxidative metabolism or TCA AUC in liver (details in ( )).
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7969 Table 3-6. Human equivalent candidate unit risks, derived using PBPK-derived dose metrics and
7970 multistage model; tumor incidence data from JISA (1993) for hepatocellular adenomas or
7971 carcinomas
Human l-'(|iii\;ilenIs
Studj (.roup
Tumor tj pc
(niuliisiaue model u nil
all dose uioups unless
nlhcrw isc specified)
POD ' in internal dose units and
dose metric used
Candidate
SI-
/internal
dose unit1'
Candidate
IUR
/ppm
(IT.I'k
ranuei'
Primary dose metrics
Male mice
JISA (1993)
Hepatocellular
adenomas or carcinomas
BMDio
BMDLio
2.9
2.1
Total liver oxidative
metabolism,
mg/kg0.75-d
49E-3
1.8E-3
(1.6-1.8)
Hemangiomas,
hemangiosarcomas
BMDio
BMDLio
63
34
PCE AUC in blood,
mg-hr/L-d
2.9E-3
5.9E-3
(5.9-6.9)
Female mice
JISA (1993)
Hepatocellular
adenomas or carcinomas
BMDio
BMDLio
8.4
4.0
Total liver oxidative
metabolism,
mg/kg0.75-d
25E-3
0.90E-3
(0.84-0.93)
Male rats
MCL
BMDio
BMDLio
46
30
PCE AUC in blood,
mg-hr/L-d
3.4
8.8
(6.8-8.0)
JISA (1993)
MCL (Michaelis-
Menten)
BMDio
BMDLio
20
5.0
PCE AUC in blood,
mg-hr/L-d
20
40
(40-47)
Female rats
MCL
BMDio
BMDLio
136
61
PCE AUC in blood,
mg-hr/L-d
1.6
3.3
(3.3-3.9)
JISA (1993)
MCL (control and low
dose groups only)
BMDio
BMDLio
11
5.2
PCE AUC in blood,
mg-hr/L-d
19
39
(39-45)
Female and male
rats combined
JISA (1993)
MCL (Michaelis-
Menten)
BMDio
BMDLio
17
3.0
PCE AUC in blood,
mg-hr/L-d
33
68
(67-71)
7972 Note: From Table 5-18 in the U.S. EPA (2012e) IRIS assessment of PCE; SF = Slope Factor; IUR = Inhalation Unit Risk;
7973 MCL= Mononuclear cell leukemias.
7974 a PODs were estimated at the indicated BMRs in terms of extra risk; i.e., BMDL10 = lower bound for the level of the internal
7975 dose metric associated with 10% extra risk. Dose metric units are in the first column and include cross-species scaling to a
7976 human equivalent internal dose metric. Refer to Appendix D for dose-response modeling details.
7977 b Slope Factor = BMR/BMDLBMR in units of risk per dose metric unit (as given in the first column).
7978 0 Inhalation unit risk (IUR) is given by the product of the slope factor in units of risk per dose metric unit and an inhalation
7979 dose metric conversion factor (DMCFppm): IUR = BMR/BMDLBMR x DMCFppm, where the DMCFppm is derived from
7980 the PBPK model.
7981
7982 Human inhalation cancer risk was assessed using several different sex-specific animal tumor data sets
7983 and the PBPK model in U.S. EPA (20_12e). These results, and their uncertainties are discussed in detail
7984 there.
7985
7986 The majority of the National research Council (NRC) peer review panel for the IRIS assessment (U.S.
7987 ) recommended that the male mouse hepatocellular tumors be used for cancer risk
7988 estimation. Therefore, the primary inhalation unit risk is 2 x 10"3 per ppm or 3 x 10"7 per |ig/m3
7989 (rounding to one significant digit), based on the male mouse hepatocellular tumor data from the JISA
7990 (1993) bioassay. Some members of the NRC peer review panel recommended that the MCL data be
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7991
7992
7993
7994
7995
7996
7997
7998
7999
8000
8001
8002
8003
8004
8005
8006
8007
8008
8009
8010
8011
8012
8013
8014
8015
8016
8017
8018
8019
8020
8021
8022
8023
8024
8025
8026
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used for cancer risk estimation. The inhalation unit risk would be 7 x 10~2 per ppm, or 1 x 10~5 per
[j,g/m3 (rounding to one significant digit) if it were based on the combined male and female rat MCL
data, which provided increased statistical power and improved model fit compared to either sex alone.
3.2.5.4 Points of Departure for Human Health Hazard Endpoints and Confidence
Levels
Confidence Levels
For the acute endpoint, the value used in this risk evaluation is from Altmann et al. (1990). a medium
quality short-term study demonstrating neurotoxicity based on impaired visual function associated with
delayed neurological signaling. This endpoint is robustly supported by multiple human and animal
studies. The data from Altmann et al. (1990) is based on 4 days of 4 hr/day exposure, so applying the
dose-response analysis to a single day of exposure involves some uncertainty, however it is unlikely that
outcomes would substantially differ between a single day and 4 days of exposure. Overall, there is
medium-high confidence in this endpoint.
For chronic non-cancer endpoints, multiple endpoints are available representing the health domains of
neurotoxicity, kidney toxicity, liver toxicity, immune toxicity, and reproductive/developmental toxicity.
These endpoints are supported by data in both humans and animals and the range of PODs is within
~10-fold for most endpoints, although the full set of endpoints range by as much as 150-fold. Overall,
there is medium-high confidence in the chronic endpoints.
For cancer, there is evidence of carcinogenicity in multiple tissues. The IUR (Inhalation Unit Risk) was
developed from a High-quality animal study, however the limited available human data was ambiguous.
Overall, there is medium confidence in the cancer endpoint.
Table 3-7. Summary of PODs for Evaluating Human Health Non-Cancer Hazards from Acute
Exposure Scenarios
Tar;;cl Origin
S\s(cm
Speck's -
mule
lluniiiii l'l(|iii\iik'iil
Conccnlralion (MIX )
l.llecl
loliil I nccrlaiiiM
l-aclnr (I I") for
licnchmark MOI.
Reference
Dalii
Qu;ili(\
CNS
Humans -
Inhalation
4 hrs/day = 10 ppm
(68 mg/m3)
Neurotoxicity
increased latencies
for pattern reversal
visual-evoked
potentials
UFA=1;
UFh=10;
UFl=1
Total UF=10
Altmann et
al. (1990)
Medium
8 hrs/day = 5 ppm
(34 mg/m3)
12 hrs/day = 3.3 ppm
(22 mg/m3)
24 hrs/day =1.7 ppm
(11 mg/m3)
Best Representative Chronic Studies For Each Health Domain
From among all chronic studies, EPA selected the most robust studies or PODs from within each health
domain to serve as representative endpoints for risk estimation. These studies are highlighted in blue in
Table 3-8 below. There is High confidence in these robust PODs. Justification for the selections for each
health domain are provided below:
CNS (Neurotoxicity)
PODs were derived from two studies (Echeverria et al. 1995; Cavalleri et al. 1994) that both observed
CNS effects presenting as visual deficits. Both studies scored a Medium in data quality and both studies
are based on human data with equivalent cumulative UFs. Therefore, the midpoint of the range as
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8028
8029
8030
8031
8032
8033
8034
8035
8036
8037
8038
8039
8040
8041
8042
8043
8044
8045
8046
8047
8048
8049
8050
8051
8052
8053
8054
8055
8056
8057
8058
8059
8060
8061
8062
8063
8064
8065
8066
8067
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
derived in (U.S. EPA. 2012c) is the best representative POD for this endpoint and the neurotoxicity
domain overall. EPA additionally derived occupational HECs for this POD, as described in Section
3.2.5.3.2. These HECs are provided in a separate row highlighted in green.
Kidney Effects
While there was a Medium-quality human study that reported urinary markers of nephrotoxicity (Mutti
etal. 1992). this POD was derived from a LOAEL, which resulted in a cumulative UF of 100. The
rodent study by J IS A (1993) score a High in data quality and only had a combined UF of 30, indicating
reduced uncertainty surrounding the POD. Therefore this study was used to represent the kidney
domain. There was no discernible difference among the mice and rat data from that study, so the POD
derived from mice was used in order to represent the most sensitive and robust endpoint.
Liver Effects
Three studies provided sufficient dose-response information for liver effects in mice ( 3; NTP
1986b; Bub en and O'Flahe 5). Only the data from (II ) did not require a LOAEL-to-
NOAEL UF, and that study was additionally of High quality. Additionally, increased liver/body weight
ratio is not considered adverse on its own and may be due to induction of PPARa, which is less active in
humans. Therefore, the POD from ( 6) for increased angiectasis was selected to represent the
liver domain.
Reproductive/Developmental
Reproductive
There is only a single adequate study examining reproductive effects (Beliles et al. 1980). which
observed reduced sperm quality in males following only 5 days exposure. This study scored High in data
quality and was therefore used to represent reproductive effects. Of note, despite this study only
examining 5 days of exposure, this exposure duration covers the window of sperm production while the
observation period up to 10 weeks covered the full period of spermatogenesis. Since PCE is not
bioaccumulative, continuous exposure is not expected to result in a more sensitive toxicological
response.
Developmental
Three studies demonstrated adequate dose-response information for developmental endpoints, each
reporting varying but overlapping effects. Nelson et al. (1979) observed decreased weight gain in
offspring along with indications of developmental neurotoxicity. Tinston et al. (1994) reported neonatal
mortality as well as CNS effects in a multigenerational study. Carney et al. (2006) observed decreased
placental and fetal weight along with skeletal effects. Nelson et al. (1979) scored a low in data quality
while the other two studies scored a high. Among the two high-quality studies, the POD from (Tinston
1994) was selected to represent the domain because the data comes from a 2-generation study which
would be expected to capture all potential developmental outcomes, as opposed to the short-duration
study used in (Carney et al. 2006).
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8069 Table 3-8. Summary of PODs for Evaluating Human Health Non-Cancer Hazards from Chronic
8070 Exposure Scenarios
Target Organ
System
Species -
route
Human
Equivalent
Concentration
(HEC)
Effect
Total Uncertainty
Factor (UF) for
Benchmark MOE
Reference
Data
Quality
Score
CNS
Humans -
Inhalation
2.2 ppm
(15 mg/m3)
Neurotoxicity - Color
confusion
UFa=1;
UFh=10;
UFl=10
UFS= 1
Total UF=100
Cavalleri et
al. (1994)
Medium
Humans -
Inhalation
(inferred)
8.3 ppm
(56 mg/m3)
Visual reproduction,
pattern memory, pattern
recognition and reaction
time in pattern memory
UFA=1;
UFh=10;
UFl=10
UFS= 1
Total UF=100
Echeverria
et al. (1995)
Medium
Humans -
Inhalation
5.2 ppm
(36 mg/m3)
Midpoint of the range of
the two neurotoxicity
studies
UFA=1;
UFh=10;
UFl=10
UFS= 1
Total UF=100
Based on
U.S. EPA
(2012c)
Medium
Humans -
Inhalation
14.5 ppm [8 lir]
(99 mg/m3)
9.7 ppm [12 lir]
(66 mg/m3)
Midpoint of the range of
the two neurotoxicity
studies
(adjusted for 8 and 12 lir
occupational TWAs)
UFA=1;
UFh=10;
UFl=10
UFS= 1
Total UF=100
Based on
U.S. EPA
(2012c)
Medium
Kidney
Humans -
Inhalation
(inferred)
5.0 ppm
(34 mg/m3)
Urinary markers of
nephrotoxicity
UFA=1;
UFh=10;
UFl=10
UFS= 1
Total UF=100
Mutti et al.
(1992)
Medium
Rats -
Inhalation
9.0 ppm
(61 mg/m3)
Nuclear enlargement in
proximal tubules
UFA=3;
UFh=10;
UFl=1
UFS= 1
Total UF=30
JISA (1993)
High
Mice -
Inhalation
2.1 ppm
(14 mg/m3)
Nuclear enlargement in
proximal tubules
UFA=3;
UFh=10;
UFl=1
UFS= 1
Total UF=30
JISA (1993)
High
Liver
Mice -
Inhalation
31 ppm
(210 mg/m3)
Increased angiectasis in
liver
UFA=3;
UFh=10;
UFl=1
UFS= 1
Total UF=30
JISA (1993)
High
Mice -
Inhalation
310 ppm
(2100 mg/m3)
Increased liver
degeneration/necrosis
UFA=3;
UFh=10;
UFl=10
UFS= 1
Total UF=300
NTP
(1986b)
High
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Target Organ
System
Species -
route
Human
Equivalent
Concentration
(HEC)
Effect
Total Uncertainty
Factor (UF) for
Benchmark MOE
Reference
Data
Quality
Score
Mice -
Oral
(gavage)
40 ppm
(270 mg/m3)
Increases liver/body-
weight ratio
UFa=3;
UFh=10;
UFl=10
UFS = 10
Total UF=3000
Buben
(1985)
Medium
Reproductive/
Developmental
Reproductive
Mice -
Inhalation
21 ppm
(140 mg/m3)
Reduced sperm quality
following 5 days
exposure
UFa=3;
UFh=10;
UFl=1
UFS= 1
Total UF=30
Beliles et al.
(1980)
High
Developmental
Rats
29 ppm
(200 mg/m3)
Decreased weight gain;
altered behavior, brain
acetylcholine
UFa=3;
UFh=10;
UFl=1
UFS= 1
Total UF=30
Nelson et al.
(1979)
Low
Rats -
Inhalation
18 ppm
(122 mg/m3)
Increased F2a pup deaths
by Day 29, CNS
depression in Fi and F2
UFa=3;
UFh=10;
UFl=1
UFS= 1
Total UF=30
Tinston et
al. (1994)
High
Rats -
Inhalation
16 ppm
(110 mg/m3)
Decreased fetal and
placental weight,
skeletal effects
UFa=3;
UFh=10;
UFl=1
UFS= 1
Total UF=30
Carney et al.
(2006)
High
8071 Notes: Rows shaded in blue indicate PODs selected as most robust and representative for the associated health domain.
8072 Row shaded in green indicates occupational HECs for the chronic neurotoxicity domain.
8073
8074 As explained in Section 3.2.5.3.3, the primary IUR is derived from male mouse hepatocellular tumor
8075 data, while the alternative IUR is from combined male and female rat MCL data. Both values are shown
8076 in Table 3-9.
8077
8078 Table 3-9. Summary of PODs for Evaluating Cancer Hazards from Chronic Inhalation Scenarios
Exposure
Duration for
Risk Analysis
Hazard Value
Effect
Total
Uncertainty
Factor (UF) for
Benchmark
MOE
Reference
Data
Quality
Score
CHRONIC
EXPOSURE
IUR
2 x 10 3 per ppm
(3 x 10"4 per mg/m3)
male mouse
hepatocellular tumors
Not applicable
JISA (1993)
High
Alternate IUR:
7 x 10~2 per ppm
(1 x 10 2 per mg/m3)
Male and female rat
mononuclear cell
leukemia (MCL)
Not applicable
JISA (1993)
High
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8079
8080
8081
8082
8083
8084
8085
8086
8087
8088
8089
8090
8091
8092
8093
8094
8095
8096
8097
8098
8099
8100
8101
8102
8103
8104
8105
8106
8107
8108
8109
8110
8111
8112
8113
8114
8115
8116
8117
8118
8119
8120
8121
8122
8123
8124
8125
8126
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Notes:
The inhalation unit risk should not be used with exposures exceeding 60 ppm, or 400 mg/m3 (the equivalent ambient
exposures corresponding to the POD for male mouse hepatocellular tumors), because above this exposure level, the dose-
response relationship is not linear, and the unit risk would tend to overestimate risk.
Cancer risks following acute exposures were not estimated. The relationship between a single short-term exposure to PCE
and the induction of cancer in humans is not known.
3.2,5.4.1 Route to Route Extrapolation for Dermal PODs
Workers and consumers can be exposed to PCE under various exposure scenarios via dermal routes.
EPA did not identify toxicity studies by the dermal route that were adequate for dose-response
assessment. Dermal candidate values derived by two methods were compared and the results are shown
in Table 3-10. Dermal candidate values were calculated based on route-to-route extrapolation from two
different routes either inhalation or oral PODs. For all endpoints previously derived from animal or
human studies in the EPA IRIS Assessment ( ), both oral and inhalation PODs (as HECs
or HEDs) were derived from the original study data using the best available approaches for
incorporating PCE specific toxicokinetic data (i.e. the PBPK model) when possible. Extrapolation to
oral HEDs was not available for all endpoints.
Extrapolating from inhalation PODs to the dermal route account for human inhalation and body weight
and assume average exposure factors from the Exposure Factors Handbook ( ) shown in
the equations below. Extrapolating from oral PODs to the dermal route considered differences in oral
and dermal absorption. EPA assumed 100% oral and inhalation absorption, supported by studies in
animals (ATSDR JO T"; 1 c. « i1 \ JO I _v). EPA accounted for dermal absorption in the dermal exposure
estimate (see Section 2.4.1.29). Therefore, the oral HEDs were used directly for dermal exposures.
Inhalation to dermal extrapolation for non-cancer effects:
dermal POD = inhalation POD [mg/m3] x inhaled volume (m3) ^ body weight (kg)
Inhalation to dermal extrapolation for cancer effects:
dermal slope factor = IUR [per mg/m3] ^ inhaled volume (m3) x body weight (kg) ,
where the inhaled volume was the ventilation rate 1.25 m3/hr (for light activity) times the
appropriate exposure duration (4 hours from Altmann et al. (1990)) for acute endpoints, or 20 m3 per
day for 24 hrs duration and the chronic endpoints and a body weight of 80 kg. These exposure factors
are based on EPA RfC Guidance (I! S 1T \ \ l)l)4c) for inhalation rates and the 2011 Exposure Factors
Handbook (U.S. EPA. 201 la) for body weight. EPA assumes that activities involving PCE exposure
involve some movement, and thus, assumed a ventilation rate for light activity.
PODs were derived from Altmann et al. (1990) for a range of inhalation exposure durations, the route to
route extrapolation for dermal used the duration of the experimental study (4 hrs) and the air
concentration in the study (a NOAEC of 10 ppm or 68 mg/m3) for extrapolation to the dermal route.
There is uncertainty regarding the likelihood that dermal exposure will result in cancer, but because
humans may experience different cancers than rodents, EPA has assumed that the slope factor can be
considered generally representative of the potential for cancers of other types and that this is relevant to
model via the dermal route. When both an HEC and HED value was available for a given endpoint, EPA
derived dermal PODs via extrapolation from both values. For all endpoints the difference in the derived
dermal POD between routes is no more than approximately 2-fold. In considering the relative
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uncertainties involved in extrapolation via either route, the most robust and sensitive POD was selected
for use in risk estimation. The dermal POD value to be used for risk estimates is bold in the table below,
and the selected representative studies are highlighted in blue, as was done for HEC values.
Differences in absorption across routes are accounted for in the occupational (Section 2.4.1.29) and
consumer (Section 2.4.2.2.2) dermal exposure assessments, respectively. While EPA assumes 100%
absorption via oral and inhalation routes (Section 3.2.2.1.1), the volatility of PCE significantly decreases
the expected dermal absorption under non-occluded conditions. The occupational exposure estimates
incorporated modeled absorption under non-occluded conditions through the Dermal Exposure to
Volatile Liquids Model while consumer dermal exposure utilizes the permeability module from the
Consumer Exposure Model (CEM) was used to estimate dermal exposure only for COUs under which
impeded evaporation is expected.
Table 3-10. Derivation of Dermal POPs by Route-to-Route Extrapolation
Total
Uncertainty
Inhalation
Oral to
Factor (UF)
Inhalation
Inhalation
to Dermal
Dermal3
for
Target Organ
POD and
to Dermal
HEP
HEP
Benchmark
Pata
System and Effect
Duration
Adjustments
(mg/kg-day)
(mg/kg-day)
MOE
Reference
Quality
Acute Exposures
CNS
Neurotoxicity
UFa=1;
increased
10 ppm
1.25 m3/hr
UFh=10;
Altmann et
al. (1990)
latencies for
pattern reversal
(68 mg/m3)
4 hrs/day
4 hrs/day
80 kg B W
4.25b
N/A°
UFl=1
Total
Medium
visual-evoked
UF=10
potentials
Chronic Exposures
UFA=1;
CNS
Neurotoxicity
Color confusion
2.2 ppm
(15 mg/m3)
24 hrs/day
20 m3/day
80 kg B W
3.75
2.6
UFh=10;
UFl=10
Total
UF=100
Cavalleri
et al.
(1994)
Medium
CNS
Neurotoxicity
Visual
UFA=1;
reproduction,
pattern memory,
pattern
8.3 ppm
(56 mg/m3)
24 hrs/day
20 m3/day
80 kg B W
14
9.7
UFh=10;
UFl=10
Total
Echeverria
et al.
(1995)
Medium
recognition and
UF=100
reaction time in
pattern memory
Midpoint of the
range of the two
neurotoxicity
endpoints
5.2 ppm
(36 mg/m3)
20 m3/day
80 kg B W
9.0
6.2
UFA=1;
UFh=10;
UFl=10
Total
UF=100
Based on
U.S. EPA
(2012c)
Medium
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Target Organ
System and Effect
Inhalation
POD and
Duration
Inhalation
to Dermal
Adjustments
Inhalation
to Dermal
HEP
(mg/kg-day)
Oral to
Dermal3
HEP
(mg/kg-day)
Total
Uncertainty
Factor (UF)
for
Benchmark
MOE
Reference
Pata
Quality
Kidney
Urinary Markers
of nephrotoxicity
5.0 ppm
(34 mg/m3)
24 hrs/day
20 m3/day
80 kg B W
8.5
5.4
UFa=1;
UFh=10;
UFl=10
Total
UF=100
Mutti et al.
(1992)
Medium
Kidney
Nuclear
enlargement in
proximal tubules
9.0 ppm
(61 mg/m3)
24 hrs/day
20 m3/day
80 kg B W
15
9.5
UFa=3;
UFh=10;
UFl=1
Total
UF=30
JISA (,
1993,
630653)
High
Kidney
Nuclear
enlargement in
proximal tubules
2.1 ppm
(14 mg/m3)
24 hrs/day
20 m3/day
80 kg B W
3.5
2.2
UFa=3;
UFh=10;
UFl=1
Total
UF=30
JISA (,
1993,
630653)
High
Liver
Increased
angiectasis in
liver
31 ppm
(210
mg/m3) 24
hrs/day
20 m3/day
80 kg B W
52.5
24.5
UFa=3;
UFh=10;
UFl=1
Total
UF=30
JISA
(1993)
High
Liver
Increased liver
degeneration/
necrosis
310 ppm
(2100
mg/m3) 24
hrs/day
20 m3/day
80 kg B W
525
252
UFa=3;
UFh=10;
UFl=10
Total
UF=300
NTP
(1986b)
High
Liver
Increases
liver/body-weight
ratio
40 ppm
(270
mg/m3) 24
hrs/day
20 m3/day
80 kg B W
67.5
32
UFa=3;
UFh=10;
UFl=1
Total
UF=30
Buben
(1985)
Medium
Developmental
Decreased weight
gain; altered
behavior, brain
acetylcholine
29 ppm
(200
mg/m3)
20 m3/day
80 kg B W
50
N/A
UFa=3;
UFh=10;
UFl=1
Total
UF=30
Nelson et
al. (1979)
Low
Developmental
Reduced sperm
quality following
5 days exposure
21 ppm
(140
mg/m3)
20 m3/day
80 kg B W
35
22
UFa=3;
UFh=10;
UFl=1
Total
UF=30
Beliles et
al. (1980)
High
Developmental
Increased F2a pup
deaths by Day 29,
CNS depression
inFi and F:
18 ppm
(122
mg/m3)
20 m3/day
80 kg B W
31
N/A
UFa=3;
UFh=10;
UFl=1
Total
UF=30
Tinston et
al. (1994)
High
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Target Organ
System and Effect
Inhalation
POD and
Duration
Inhalation
to Dermal
Adjustments
Inhalation
to Dermal
HEP
(mg/kg-day)
Oral to
Dermal3
HEP
(mg/kg-day)
Total
Uncertainty
Factor (UF)
for
Benchmark
MOE
Reference
Pata
Quality
Developmental
Decreased fetal
and placental
weight, skeletal
effects
16 ppm
(110
mg/m3)
20 m3/day
80 kg B W
28
N/A
UFa=3;
UFh=10;
UFl=1
Total
UF=30
Carney et
al. (2006)
High
Cancer
male mouse
hepatocellular
tumors
3 x 10"4per
mg/m3
20 m3/day
80 kg B W
1 x 103 per
mg/kg/day
2 x 103 per
mg/kg/day
Not
applicable
JISA
(1993)
High
Male and female
rat MCL
1 x 10~2per
mg/m3
20 m3/day
80 kg B W
4 x lO 2 per
mg/kg/day
6 x 10 2per
mg/kg/day
Not
applicable
JISA
(1993)
High
Notes:
a The oral to dermal slope factors should not be used with exposures exceeding 50 mg/kg/day (the equivalent ambient
exposures corresponding to the POD for male mouse hepatocellular tumors), because above this exposure level, the
dose-response relationship is not linear, and the unit risk would tend to overestimate risk.
b The PODs highlighted in bold are used in calculating risks
0 N/A an acute oral to dermal POD was not calculated since an acute oral POD was not identified and the inhalation to
dermal POD was used for assessing risk from dermal exposures
Note: Cancer risks following acute exposures were not estimated. The relationship between a single short-term exposure
to PCE and the induction of cancer in humans is not known.
3.2.6 Key Assumptions and Uncertainties for Human Health Hazard
3.2.6.1 Hazard ID and Weight of Scientific Evidence
There is medium-high confidence in the database and WOE determinations for human health hazard. All
but one of the studies considered for dose-response analysis scored either Medium or High in data
quality evaluation and were determined to be highly relevant to the pertinent health outcome. EPA
selected the best representative chronic study for each identified endpoint to use for risk estimation,
taking into account factors such as data quality evaluation score, species, cumulative uncertainty factor,
and relevance. The only study considered for dose-response analysis that scored a Low in data
evaluation was (Nelson et al. 1979). however the health outcomes observed in this study were covered
by the other two high-quality developmental toxicity studies, (Tinston 1994) and (Carney et al. 2006).
For most health domains, the weight of scientific evidence was very clear, with consistent results
observed across multiple species and representing multiple endpoints within the health domain. The data
was a bit more ambiguous for immune and hematological effects however. While there was some
indication of specific endpoints related to immunotoxicity or blood effects, EPA determined that the
database was not fully consistent and there was an absence of adequate quantitative information
available to conclude that the domains supported dose-response analysis (Section 0). There is
uncertainty whether the PODs for other endpoints carried forward are sufficiently protective of any
potential immune or hematological effects that were not accounted for in this risk evaluation.
Additionally, there is some uncertainty as to the weight of the evidence for liver effects relating to
human relevance. Consistent effects were only observed in rodents and the potential influence of certain
MOA that are more highly active in rodents (i.e. PPARa, Section 3.2.3.2.4) suggests that observed liver
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toxicity may have reduced significance to the majority of human populations. However, susceptible
subpopulations such as those with liver disease (Section 3.2.5.2) may still be of high risk of liver toxicity
from sustained PCE exposure.
3.2.6.2 Derivation of PODs, UFs, and PBPK Results
Conceptually, the POD should represent the maximum exposure level at which there is no appreciable
risk for an adverse effect in the study population under study conditions (i.e., the threshold in the dose-
response relationship). In fact, it is not possible to know that exact exposure level even for a laboratory
study because of experimental limitations (e.g. the ability to detect an effect, the doses used and dose
spacing, measurement errors, etc.), and POD approximations like the doses used (i.e., a NOAEL) an
exposure level which is modeled from the reasonably available doses used (i.e., BMDL) are used. The
application of UFs is intended to account for this uncertainty/variability to allow for estimating risk for
sensitive human subgroups exposed continuously for a lifetime. While the selection of UFs is informed
by reasonably available data, the true necessary extent of adjustment most appropriate for capturing all
relevant uncertainty and variability is unknown.
For this draft risk evaluation, non-cancer PODs were all based on NOAELs and LOAELs because the
data for the selected endpoints was unable to be BMD modeled. This results in reduced precision in
POD estimates because the POD is dependent on the dose selection of the study as opposed to the
response rate/level for the effect of interest.
For each of these types of PODs, there are additional uncertainties pertaining to adjustments to the
administered exposures (doses). Typically, administered exposures (doses) are converted to equivalent
continuous exposures (daily doses) over the study exposure period under the assumption that the effects
are related to concentration x time, independent of the daily (or weekly) exposure regimen (i.e., a daily
exposure of 6 hours to 4 ppm is considered equivalent to 24 hours of exposure to 1 ppm). However, the
validity of this assumption is generally unknown, and, if there are dose-rate effects, the assumption of C
x t equivalence would tend to bias the POD downwards.
For the PBPK analyses in this assessment (Section 3.2.2.2), the actual administered exposures are taken
into account in the PBPK modeling, and equivalent daily values (averaged over the study exposure
period) for the dose-metrics are obtained. EPA determined that the peer-reviewed PBPK model
sufficiently accounted for any variability and uncertainties in route-to-route extrapolation, and therefore
inhalation and oral data were considered equivalently relevant. Nonetheless, this PBPK model, like any
model, does not incorporate all possible sources of biological uncertainty or variability.
Use of the PBPK model resulted in data derived HEC and HED values replacing default assumptions
and uncertainty factors that would have otherwise been used such as allometric scaling and a UFtk of 3
in accounting for interspecies toxicokinetic variability. Data-derived values are always preferred to
default uncertainty adjustments and improve confidence in the adjusted PODs. There is additional
uncertainty for dermal PODs which required route-to-route extrapolation based on assumed exposure
factors without the availability of a dermal compartment in the PBPK model.
3.2.6.3 Cancer Dose-Response
There is uncertainty concerning the selected POD for cancer dose-response. EPA derived an IUR and
dermal SF based on the low dose linear assumption. The MOA (Section 3.2.3.2.4) concludes that
genotoxicity is likely to be at least a partial contributor to the MOA and any non-mutagenic mechanisms
for carcinogenesis that would be associated with a threshold are likely only relevant at higher doses
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above those associated with tumorigenesis. Nonetheless, the linear assumption always has some inherent
uncertainty.
Additionally, EPA selected the male mouse data for hepatocellular adenoma/carcinoma to use as the
representative cancer POD based on the majority recommendation from the NRC peer review panel of
the IRIS Assessment (U.S. EPA. 2012e) (Section 3.2.5.3.3). This is further supported based on a stronger
weight of evidence for liver effects compared to immune outcomes. However, the NRC panel was not
unanimous and some members believed that the MCL data was better representative. The MCL IUR for
the combined male and female dataset is 35x higher than the hepatocellular cancer IUR selected for use
as the representative cancer POD. An adjustment was not made to account for the additional risk from
MCL or hemangiomas and therefore the selected cancer POD may underestimate total cancer risk from
PCE.
3.2.6.4 Confidence Ratings for Endpoints and Selected Representative PODs
There is medium-high confidence in the acute non-cancer endpoint and POD based on neurotoxicity,
medium-high confidence in the chronic non-cancer endpoints and PODs, and medium confidence in the
cancer endpoint. There is high confidence in the robust chronic non-cancer PODs selected to represent
each health domain for risk estimation. Confidence ratings are a half-step lower (e.g. medium instead of
medium-high) for all dermal PODs because derivation required extrapolation across routes without the
availability of a PBPK model dermal compartment. See Section 3.2.5.4 for more details on the
confidence descriptions for each category.
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4 RISK CHARACTERIZATION
4.1 Environmental Risk
EPA took fate, exposure, and environmental hazard into consideration to characterize environmental risk
of PCE. As stated in Section 2.1, PCE has low potential to bioconcentrate in biota and moderate
potential to accumulate in wastewater biosolids, soil, or sediment. Releases of PCE to the environment
are likely to volatilize to the atmosphere, where it will slowly photooxidize. It may migrate to
groundwater, where it will slowly hydrolyze. Additionally, the bioconcentration potential of PCE is low.
EPA modeled environmental exposure with surface water concentrations of PCE ranging from 9.7E-09
ppb to 2,034 ppb from facilities releasing the chemical to surface water. Measured surface water
concentrations in ambient water range from below the detection limit to 1.7 ppb. The modeled data
represents estimated concentrations near facilities that are actively releasing PCE to surface water, while
the reported measured concentrations represent sampled ambient water concentrations of PCE.
Differences in magnitude between modeled and measured concentrations may be due to measured
concentrations not being geographically or temporally close to known releasers of PCE.
As stated in Section Summary of Environmental Hazard 3.1.5, EPA concludes that PCE poses a hazard
to environmental aquatic receptors to include: aquatic invertebrates, fish, and aquatic plants. The most
sensitive species for acute toxicity were two daphnid species, Ceriodaphnia dubia and Daphnia magna.
The acute toxicity value was as low as 2.5 mg/L based on immobilization of daphnia. PCE presents an
acute hazard to fish based on mortality of rainbow trout as the most sensitive species with acute toxicity
values as low as 4.8 mg/L for mortality LC50. For chronic exposures, PCE is a hazard to aquatic
invertebrates, with a chronic toxicity value of 0.5 mg/L; and a chronic toxicity value of 0.8 mg/L for
fish. PCE is also a hazard for green microalgae with toxicity values as low as 2.0E-02 mg/L.
EPA assigned an overall quality level of high, medium or low to 30 acceptable studies. These studies
contained relevant aquatic toxicity data for fish, aquatic invertebrates, and aquatic plants. As shown in
Table 3-1, EPA identified 10 aquatic toxicity studies as the most relevant for quantitative assessment.
Four of the 10 studies were carried forward for characterizing the potential environmental risks from
PCE. The rationale for selecting these studies is provided in Section 3.1.3 Weight of Scientific
Evidence.
A total of 10 acceptable aquatic environmental hazard studies were identified for PCE. EPA assigned
nine high, and one medium for overall quality levels during data evaluation (See Table 3-1 in Section
3.1.2 and the Draft Risk Evaluation for Perchloroethylene: Systematic Review Supplemental File: Data
Quality Evaluation of Environmental Hazard Studies ( 020i). The Draft Risk Evaluation for
Perchloroethylene: Systematic Review Supplemental File: Data Quality Evaluation of Environmental
Hazard Studies (U.S. EPA. 20201) presents details of the data evaluations for each study, including
scores for each metric and the overall study score.
Given PCE's conditions of use under TSCA outlined in problem formulation ( 18d), EPA
determined that environmental exposures are expected for aquatic species, and risk estimation is
discussed in Section 4.1.2.
4,1,1 Risk Estimation Approach
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To assess environmental risk, EPA evaluates environmental hazard and exposure data. EPA used
modeled exposure data from E-FAST ( ), as well as monitored data from the WQP
(Nwqmc ), to characterize the exposure of PCE to aquatic species. Environmental risks are
estimated by calculating a risk quotients (RQ). As stated previously, modeled data were used to
represent surface water concentrations near facilities actively releasing PCE to surface water. The
modeled concentrations were used to represent ambient water concentrations of PCE. RQs were
calculated using surface water concentrations and the COCs calculated in the hazard section of this
document (Section 3.1.4). The RQ is defined as:
RQ = Predicted Environmental Concentration / Effect Level or COC
RQs equal to 1 indicate that environmental exposures are the same as the COC. If the RQ is above 1, the
exposure is greater than the COC. If the RQ is below 1, the exposure is less than the COC. The COCs
for aquatic invertebrates and algae shown in Table 3-2, and the environmental concentrations described
in Table 4-1, were used to calculate RQs (I! S 1T \ h">98).
EPA considered the biological relevance of the species that the COCs were based on when integrating
the COCs with the location of surface water concentration data to produce RQs. For example, certain
biological factors affect the potential for adverse effects in aquatic organisms. Life-history and the
habitat of aquatic organisms influences the likelihood of exposure above the hazard benchmark in an
aquatic environment.
Frequency and duration of exposure also affect the potential for adverse effects in aquatic organisms.
Therefore, the number of days that a COC was exceeded was also calculated using E-FAST (U.S. EPA.
2014b). as described in Section 2.3.1.2. The days of exceedance modeled in E-FAST are not necessarily
consecutive and could occur sporadically throughout the year, continuous aquatic exposures are more
likely for the longer exposure scenarios (i.e., 100-365 days/yr of exceedance of a COC), and more of an
interval or pulse exposure for shorter exposure scenarios (i.e., 1-99 days/yr of exceedances of a COC).
Calculation of Days of COC Exceedance
The Probabilistic Dilution Model (PDM) portion of E-FAST 2014 ( 14b) was also run for
free-flowing water bodies, which predicts the number of days per year a chemical's concentration of
concern (COC) in an ambient water body will be exceeded. The model is based on a simple mass
balance approach presented by Di Toro ( |) that uses probability distributions as inputs to reflect that
streams follow a highly variable seasonal flow pattern and there are numerous variables in a
manufacturing process can affect the chemical concentration and flow rate of the effluent. PDM does not
estimate exceedances for chemicals discharged to still waters, such as lakes, bays, or estuaries. For these
water bodies, the days of exceedance is assumed be zero unless the predicted surface water
concentration exceeds the COC. In these cases, the days of exceedance is set to the number of release
days per year (see required inputs below).
Geospatial Analysis
A geospatial analysis at the watershed level (HUC-8 and HUC-12) was conducted to compare the
measured and predicted surface water concentrations in 2016 and investigate if the facility releases may
be associated with the observed concentrations in surface water. A geographic distribution of the
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concentrations is shown in Figure 4-land Figure 4-2 (east and west U.S.) for the maximum days of
release scenario, and in Figure 4-3and Figure 4-4 (east and west U.S.) for the 20-days of release
scenario. Overall, there are 33 U.S. states/territories with either a measured concentration or a predicted
concentration; at the watershed level, there are 109 HUC-8 areas and 149 HUC-12 areas with either
measured or predicted concentrations. 5.3.68Appendix D provides a list of states/territories with facility
releases (as mapped) and/or monitoring sites.
EPA also used surface water monitoring data from the Water Quality Portal (Nwqmc 2017) and from the
published literature to characterize the risk of PCE to aquatic organisms. These monitored surface water
concentrations reflect concentrations of PCE in ambient water. EPA's Storage and Retrieval (STORET)
data and USGS's National Water Information System (NWIS) data were extracted on Oct 3rd, 2018 from
the WQP. These data show an average concentration for PCE of 0.2 ± 0.6 |ig/L or ppb in surface water
from 1,597 measurements taken throughout the U.S. between 2013 and 2017. The highest value
recorded during these years was 1.7 |ig/L or ppb, which was measured in 2014. Table 4-1 shows that
algae RQ were greater 1 at the maximum observed concentration. All other RQs were close to zero.
Table 4-1. RQs Calculated using Monitored Environmental Concentrations from Water Quality
Portal
Monitored Surface \\aler
Concentrations (ppb) from
2013-2017
UQ using Acute
COC of 1.342 ppb
UQ using Chronic
COC of 50 ppb
UQ using algae
COC of 1.4 ppb
Mean (SD): 0.23 (0.55) ppb
0.0
0.0
0.2
Maximum: 1.69 ppb
0.0
0.0
1.2
Surface Water Concentrations
The surface water concentrations associated with the monitoring stations and facility releases are
denoted on the maps using COCs (Section 3.1.4) to determine the concentration thresholds:
>1,342 |ig/L (exceeds all COC for algae, aquatic invertebrate, and fish
orange 50-1,341 |ig/L (exceeds the COC for algae and aquatic invertebrate, but not for fish)
green 1.4 to 49 |ig/L (exceeds the COC for algae, but not for aquatic invertebrate or fish)
Muc Detected, but less than 1.4 |ig/L (less than all COC)
purple Not Detected (applies only to measured concentrations; detection limits vary)
For the predicted concentrations, the concentrations represent conditions under low flow conditions (i.e.,
7Q10 flows). The harmonic mean concentrations were not mapped but are presented in the detailed
summary tables.
Symbols and Layering
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Due to the scale of the maps found in Section 4, some symbols may overlap each other if the monitoring
stations and facilities are near each other or there are multiple releases modeled for the same facility
(i.e., one facility is both a direct discharger and a receiving facility). As such, the maps are layered to
make sure that the most important information is always be visible. The following rules were applied:
• Monitoring stations (small circles) are always on top of indirect discharge releases (medium
triangles), which are always on top of direct discharge releases (large squares), and
• Within each symbol type (monitoring station, direct release, and indirect release), a higher
concentration level is always on top of a lower concentration level (i.e., from top to bottom:
>1,342 |ig/L (red), 50-1,341 |ig/L (orange), 1.4-49 |ig/L (green), <1.4|ig/L (blue), and not
detected (purple).
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8374 Figure 4-1 Concentrations of PCE from PCE-Releasing Facilities (Maximum Days of Release Scenario) and WQX
8375 Monitoring Stations: Year 2016, East US. All indirect releases are mapped at the receiving facility unless the receiving.
Concentration Levels Concentration Type
50 - 1341 pg/L ~ Modeled - Direct Release (200 - 350 days/yr)
¦ 1.4-49pg/L A Modeled - Indirect Release (200 - 350 days/yr)
¦ < 1.4 (jg/L (below all COCs) Measured - NWIS/STORET Monitoring Sites
Not detected 0 A Days of exceedance a 20 days
States with no modeled or measured
concentrations
ijj
300
Miles
8376
8377
8378 Figure 4-2 Concentrations of PCE from PCE-Releasing Facilities (Maximum Days of Release Scenario) and WQX
8379 Monitoring Stations: Year 2016, West US. All indirect releases are mapped at the receiving facility unless the receiving
8380 facility is unknown.
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Concentration Levels
1,4 - 49 |jg/L
fcS < 1.4 (jg/L (below ail COCs)
mi Not detected
Concentration Type
Modeled • Direct Release (200 - 350 days/yr)
Modeled - Indirect Release {200 - 350 days/yr)
Measured - NWIS/STORET Monitoring Sites
•! Days of exceedance a 20 days
States with no modeled or measured
concentrations
8381
8382
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8383 Figure 4-3. Concentrations of PCE from PCE-Releasing Facilities (20 Days of Release Scenario) and WQX Monitoring
8384 Stations: Year 2016, East US. All indirect releases are mapped at the receiving facility unless the receiving facility is
8385 unknown.
Concentration Levels Concentration Type
¦ 2: 1342 pg/L ~ Modeled - Direct Release (20 days/yr)
50-1341 pg/L A Modeled - Indirect Release (20 days/yr)
¦ 1.4 - 49 pg/L Measured - NWIS/STORET Monitoring Sites
¦ < 1.4 (jg/L (below all COCs) 0 A Days of exceedance 2 20 days
Not detected States with no modeled or measured
concentrations
8386
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8387 Figure 4-4. Concentrations of PCE from PCE-Releasing Facilities (20 Days of Release Scenario) and WQX Monitoring
8388 Stations: Year 2016, West US. All indirect releases are mapped at the receiving facility unless the receiving facility is
8389 unknown.
Concentration Levels Concentration Type
50 - 1341 pg/L ~ Modeled - Direct Release (20 days/yr)
¦ 1.4 - 49 pg/L Measured - NWIS/STORET Monitoring Sites
¦ < 1.4 pg/L (below all COCs) H Days of exceedance 2 20 days
Not detected r^-r States with no modeled or measured
concentrations
8390
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4.1.2 Risk Estimation for Aquatic Environment
To characterize potential risk due to PCE exposure, RQs were calculated based on modeled data from E-
FAST ( 3) for sites that had surface water discharges of PCE according to TRI and DMR
data (Table 4-1). Surface water concentrations of PCE were modeled for 97 releases: six manufacturing
releases, four import/repackaging, 18 processing as a reactant releases, four incorporation into
formulation, 17 open top vapor degreasing releases, two industrial dry cleaning releases, One
commercial dry cleaning release (based on data from 12,822 facilities), five maskants for chemical
milling releases, 12 industrial processing aid releases, eight other industrial use releases, seven other
commercial uses releases, and 13 waste handling, disposal, treatment, and recycling releases. Direct
releases facilities (releasees from an active facility directly to surface water) were modeled with two
scenarios based on high-end and low-end days of release. Indirect facilities (transfer of wastewater from
an active facility to a receiving POTW or non-POTW WWTP) were only modeled with a high-end days
of releases scenario. As stated in Section 2.3.1.1, the maximum releases frequency (200 to 365 days) is
based on release estimates specific to the facility's condition of use and the low-end releases frequency
(20 days) is an estimate of releases that could lead to chronic risk for aquatic organisms.
As stated previously, the frequency and duration of exposure affects potential for adverse effects in
aquatic organisms. Therefore, the number of days a COC was exceeded was also calculated using E-
FAST. Facilities with RQs and days of exceedance that indicate risk for aquatic organisms (facilities
with an acute RQ > 1, or a chronic or algae RQ > 1 and 20 days or more of exceedance for the chronic or
algae COC) are presented in Table 4-110.
Confidence in Risk Estimation for Aquatic Environment
Confidence ratings for aquatic exposure scenarios are informed by uncertainties surrounding inputs and
approaches used in modeling surface water concentrations. Other considerations that impact confidence
in the aquatic exposure scenarios include the model used (E-FAST 2014, ( )) and its
associated default and user-selected values and related uncertainties. As described in Section 2.3.4.4,
there are uncertainties related to the ability of E-FAST 2014 (U.S. EPA. 2014b) to incorporate
downstream fate and transport; the likely number of release days from given discharging facilities; and
in some cases (i.e., when the NPDES for the discharging facility cannot be found within the E-FAST
database), the applied stream flow distribution. Based on the data quality, uncertainties, and weight of
scientific evidence, confidence in the surface water concentration estimate is medium.
Based on the data quality, weight of scientific evidence, and uncertainties, confidence in acute and
chronic COCs for fish and invertebrates are high. The COC for algae is based on a single study that EPA
assigned an overall quality level of medium. Additionally, algae species tend to vary widely in their
sensitivity to chemical pollutants, and data were only available for three algal species and may not
represent the most sensitive species at a given site. Therefore, confidence in algae COC is medium.
The overall confidence in the risk estimate to aquatic organisms from exposure to PCE is medium based
on the surface water PCE concentration and COC confidence levels.
Manufacturing
Six facilities were manufacturing PCE. Two of these facilities had RQs > 1 and 20 days or more of
exceedance for algae. Exceedances occurred using direct and indirect scenarios.
• Greenchem, West Palm Beach, FL: Using the scenario of 350 days of maximum direct release to
surface water resulted in a surface water concentration of 18 ppb, algae had an RQ = 13 and 189
days of exceedance, with average direct release concentration resulted in a surface water
concentration of 5.6 ppb, algae had an RQ = 4.0 and 100 days of exceedance. Using the
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maximum indirect release (80% removal) release scenario to surface water resulted in a surface
water concentration of 3.7 ppb, algae had an RQ = 2.7 and 77 days of exceedance.
• Univar USA Inc, Redmond, WA: Using the scenario of 350 days of maximum direct release to
surface water resulted in a surface water concentration of 18 ppb, algae had an RQ = 13 and 189
days of exceedance. With average direct release concentration from 350 days of direct release
resulted in a surface water concentration of 5.6 ppb, algae had an RQ = 4.0 and 100 days of
exceedance. Using the maximum indirect release (80% removal) scenario to surface water
resulted in a surface water concentration of 3.7 ppb, algae had an RQ = 2.6 and 100 days of
exceedance.
Four of the six facilities in the Manufacturing COU did not have NPDES permits. Lack of a NPDES
permit increases the uncertainty in the surface water release estimate for those facilities. EPA identified
risk to algae from direct and indirect release ofPCE to surface water from two of the facilities without
NPDES permits. Based on the data quality, uncertainties and weight of scientific evidence, confidence in
the risk estimate is medium.
Import/Repackaging
Of the four facilities importing/repackaging PCE, a single facility, Hubbard-Hall Inc, Waterbury, CT,
had RQs > 1 and 20 days or more of exceedance for algae. Using the scenario of 250 days of indirect
release (80% removal) to surface water resulted in a surface water concentration of 29 ppb, algae had an
RQ = 21 and 230 days of exceedance. Using the scenario of 20 days of indirect release (80% removal) to
surface water resulted in a surface water concentration of 360 ppb, algae had an RQ = 257 and 20 days
of exceedance.
EPA identified risk to algae with 80% PCE removal from waste water treatment at one of the four
facilities in the Import/Repackaging COU. Indicating that with the Import/Repackaging COU, risk to
algae can exist even with waste water treatment if the rate ofPCE release to surface water is high. This
was also the only facility lacking a NPDES permit which increases the uncertainty associated with the
surface water release estimate. Based on the data quality, uncertainties and weight of scientific
evidence, confidence in the risk estimate is medium.
Processing as a Reactant
Of the 18 facilities processing PCE as a reactant, six facilities had RQs > 1 and 20 days or more of
exceedance for aquatic organisms. All exceedances occurred using the direct release to surface water
scenario.
Dupont-Chemours Montague Site, Montague, MI: Using the scenario of 350 days of direct
release to still surface water resulted in a surface water concentration of 2.4 ppb, algae had an
RQ =1.7 and 350 days of exceedance. Using the scenario of 20 days of direct release to still
surface water resulted in a surface water concentration of 35 ppb, algae had an RQ = 25 and 20
days of exceedance.
Eagle U.S. 2 LLC - Lake Charles Complex, Lake Charles, LA: Using the scenario of 350 days of
direct release to surface water resulted in a surface water concentration of 1.5 ppb, algae had an
RQ =1.1 and 29 days of exceedance.
Flint Hills Resources Corpus Christi LLC - West Plant, Corpus Christi, TX: Using the scenario
of 350 days of direct release to still surface water resulted in a surface water concentration of 3.0
ppb, algae had an RQ = 2.2 and 350 days of exceedance. Using the scenario of 20 days of direct
release to still surface water resulted in a surface water concentration of 52 ppb, algae had an RQ
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= 37 and 20 days of exceedance, and aquatic invertebrates had a chronic RQ =1.0 and 20 days of
exceedance.
Honeywell International Inc-Baton Rouge Plant, Baton Rouge, LA: Using the scenario of 350
days of direct release to surface water resulted in a surface water concentration of 4.9 ppb, algae
had an RQ = 3.5 and 193 days of exceedance. Using the scenario of 20 days of direct release to
surface water resulted in a surface water concentration of 85 ppb, algae had an RQ = 61 and 20
days of exceedance.
Keeshan And Bost Chemical Co., Inc., Manvel, TX: Using the scenario of 350 days of direct
release to still surface water resulted in a surface water concentration of 5.0 ppb, algae had an
RQ = 3.6 and 350 days of exceedance. Using the scenario of 20 days of direct release to still
surface water resulted in a surface water concentration of 100 ppb, algae had an RQ = 71 and 20
days of exceedance, and aquatic invertebrates had a chronic RQ = 2.0 and 20 days of
exceedance.
Premcor Refining Group Inc Port Arthur, Port Arthur, TX: Using the scenario of 350 days of
direct release to surface water resulted in a surface water concentration of 2.0 ppb, algae had an
RQ =1.4 and 67 days of exceedance.
EPA identified risk to algae and a chronic risk to aquatic organisms from direct release of PCE to
surface water from the Processing as a Reactant COU at six facilities. Based on the data quality,
uncertainties and weight of scientific evidence, confidence in the risk estimate is medium.
Incorporation into Formulation
Of the four facilities using PCE for incorporation into formulations, a single facility, Lord Corp,
Saegertown, PA, had RQs > 1 for acute risks, and RQs > 1 and 20 days or more of exceedance for
chronic and algae risks. Using the scenario of 300 days of indirect release (80% removal) to surface
water resulted in a surface water concentration of 136 ppb, algae had an RQ = 97 and 299 days of
exceedance, and aquatic invertebrates had a chronic RQ = 2.7 and 127 days of exceedance. Using the
scenario of 20 days of indirect release (80% removal) to surface water resulted in a surface water
concentration of 2034 ppb, algae had an RQ = 1,453 and 20 days of exceedance, aquatic invertebrates
had an acute RQ =1.5 and a chronic RQ = 41 with 20 days of exceedance.
EPA identified elevated acute and chronic risk to aquatic organisms from direct release of PCE to
surface water from the Incorporation into Formulation COU at a single facility. The facility showing
risk has a NPDES permit. However, one of the facilities that was not identified with risk lacked a
NPDES permit. Based on the data quality, uncertainties and weight of scientific evidence, confidence in
the risk estimate is medium.
Open Top Vapor Degreasing
Of the 17 open-top vapor degreasing facilities, two facilities had RQs > 1 and 20 days or more of
exceedance for algae.
• Equistar Chemicals LP, La Porte, TX: Using the scenario of 20 days of direct release to still
surface water resulted in a surface water concentration of 3.2 ppb, algae had an RQ = 2.3 and 20
days of exceedance.
• GM Components Holdings LLC, Lockport, NY: Using the scenario of 260 days of direct release
to surface water resulted in a surface water concentration of 5.9 ppb, algae had an RQ = 4.2 and
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131 days of exceedance. Using the scenario of 20 days of direct release to surface water resulted
in a surface water concentration of 78 ppb, algae had an RQ = 56 and 20 days of exceedance.
EPA identified risk to algae from direct release of PCE to surface water from the Open Top Vapor
Degreasing COU at two facilities. Based on the data quality, uncertainties and weight of scientific
evidence, confidence in the risk estimate is medium.
Dry Cleaning (Industrial and Commercial)
Two industrial and One commercial dry cleaning releases (based on data from 12,822 facilities) were
modeled for the risk estimate. The model used both high-end and central tendency release data for direct
and indirect releases. None of the facility releases show a surface water concentration that resulted in an
RQs > 1 for acute risk or RQs > 1 and 20 days of exceedance for chronic or algal risk.
No risks were identifiedfor aquatic organisms with this COU. Based on the data quality, uncertainties
and weight of scientific evidence, confidence in the risk estimate is medium.
Maskants for Chemical Milling
Releases from five maskants for chemical milling facilities were modeled for the risk estimate. The
model used direct and indirect releases to surface water including still water bodies. None of the facility
releases show a surface water concentration that resulted in an RQs > 1 or any days of exceedance.
No risks were identifiedfor aquatic organisms with this COU. Based on the data quality, uncertainties
and weight of scientific evidence, confidence in the risk estimate is medium.
Industrial Processing Aid
Of the 12 industrial processing aid facilities, six facilities had RQs > 1 and 20 days or more of
exceedance for algae.
• Chevron Products Co Richmond Refinery, Richmond, CA: Using the scenario of 20 days of
direct release to surface water resulted in a surface water concentration of 2.7 ppb, algae had an
RQ =1.9 and 20 days of exceedance.
• ExxonMobil Oil Beaumont Refinery Beaumont, TX: Using the scenario of 300 days of direct
release to surface water resulted in a surface water concentration of 5.5 ppb, algae had an RQ =
4.0 and 55 days of exceedance. Using the scenario of 20 days of direct release to surface water
resulted in a surface water concentration of 97 ppb, algae had an RQ = 69 and 20 days of
exceedance.
• Marathon Petroleum Co LP, Garyville, LA: Using the scenario of 20 days of direct release to still
surface water resulted in a surface water concentration of 6.6 ppb, algae had an RQ = 4.7 and 20
days of exceedance.
• Occidental Chemical Corp Niagara Plant, Niagara Falls, NY: Using the scenario of 300 days of
indirect release (80% removal) to surface water resulted in a surface water concentration of 6.3
ppb, algae had an RQ = 4.5 and 92 days of exceedance. Using the scenario of 20 days of direct
release to still surface water resulted in a surface water concentration of 20 ppb, algae had an RQ
= 14 and 20 days of exceedance.
• Tesoro Los Angeles Refinery-Carson Operations, Carson, CA: Using the scenario of 300 days of
direct release to surface water resulted in a surface water concentration of 12 ppb, algae had an
RQ = 8.5 and 169 days of exceedance.
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• Valero Refining Co -Oklahoma Valero Ardmore Refinery, Ardmore, OK: Using a surrogate
organic chemicals manufacturer, with 300 days of direct release to surface water resulted in a
surface water concentration of 1.9 ppb, algae had an RQ = 1.3 and 42 days of exceedance.
EPA identified risk to algae from direct and indirect releases ofPCE to surface water from the
Industrial Processing Aid COU at six facilities. Based on the data quality, uncertainties and weight of
scientific evidence, confidence in the risk estimate is medium.
Other Industrial Uses
Releases from seven with other industrial use facilities were modeled for the risk estimate. The model
used direct releases to surface water. None of the facility releases show a surface water concentration
that resulted in an RQs > 1 or RQs > 1 and 20 days of exceedance for chronic or algal risk.
No risks were identifiedfor aquatic organisms with this COU. Based on the data quality, uncertainties
and weight of scientific evidence, confidence in the risk estimate is medium.
Other Commercial Uses
Releases from seven other commercial use facilities were modeled for the risk estimate. The model used
direct releases to surface water. None of the facility releases show a surface water concentration that
resulted in an RQs > 1 or RQs > 1 and 20 days of exceedance for chronic or algal risk.
No risks were identifiedfor aquatic organisms with this COU. Based on the data quality, uncertainties
and weight of scientific evidence, confidence in the risk estimate is medium.
Waste Handling, Disposal, Treatment, and Recycling
Of the 13 facilities engaged in waste handling, disposal, treatment, and recycling ofPCE, three facilities
had RQs > 1 and 20 days of exceedance for algae.
• Clean Harbors Deer Park LLC, La Porte, TX: Using the scenario of 250 days of indirect release
(80% removal) to surface water resulted in a surface water concentration of 9.0 ppb, algae had an
RQ = 6.4 and 172 days of exceedance. Using the scenario of 20 days of indirect release (80%
removal) to surface water resulted in a surface water concentration of 113 ppb, algae had an RQ
= 80 and 20 days of exceedance.
• Safety-Kleen Systems Inc, Smithfield, KY: Using the scenario of 250 days of indirect release
(80%) removal) to surface water resulted in a surface water concentration of 35 ppb, algae had an
RQ = 25 and 235 days of exceedance. Using the scenario of 20 days of indirect release (80%>
removal) to surface water resulted in a surface water concentration of 436 ppb, algae had an RQ
= 311 and 20 days of exceedance.
• Tier Environmental LLC, Bedford, OH: Using the scenario of 250 days of indirect release (80%>
removal) to surface water resulted in a surface water concentration of 3.1 ppb, algae had an RQ =
2.2 and 90 days of exceedance.
EPA identified risk to algae with 80% PCE removal from waste water treatment at three facilities.
Indicating that with the Waste Handling, Disposal, Treatment, and Recycling COU, risk to algae can
exist even with waste water treatment if the rate ofPCE release to surface water is high. Based on the
data quality, uncertainties and weight of scientific evidence, confidence in the risk estimate is medium.
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4.1.3 Risk Estimation for Sediment Pathways
EPA did not quantitatively analyze exposure to sediment organisms. PCE is expected to be moderately
retained in sediment due to its water solubility (206 mg/L) and moderate partitioning to organic matter
(log KOC = 2.95). Because PCE has moderate partitioning to organic matter, in sediments PCE is
expected to be both adsorbed to the sediment organic matter and present in the pore water. However,
depending on the microbial consortia present and their previous exposure and adaptation to PCE, PCE
may undergo rapid biodegradation in sediment. Thus, PCE concentrations in sediment may be lower or
somewhat greater than concentrations in overlying water. While no ecotoxicity studies were available
for sediment-dwelling organisms (e.g., Lumbriculus variegatus, Hyalella azteca, Chironomus riparius),
the toxicity of PCE to sediment invertebrates is expected to be similar to the toxicity to aquatic
invertebrates because of the similarities in PCE concentrations. EPA calculated an acute aquatic
invertebrate COC of 1,342 ppb, and a chronic aquatic invertebrate COC of 50 ppb to assess hazards to
sediment organisms.
4.1.4 Risk Estimation for Land-Applied Biosolids Pathway
EPA did not analyze PCE for other releases to land during risk evaluation, including biosolids
application to soil as indicated in the Problem Formulation.
EPA did not assess exposure to terrestrial organisms through soil, land-applied biosolids, or ambient air.
PCE has moderate potential to partition to or accumulate in soil, but is primarily expected to volatilize to
air or migrate through soil into groundwater based on its physical-chemical properties (log Koc = 3,
Henry's Law constant = 0.018 atm-m3/mole, vapor pressure = 19 mmHg at 20°C). Therefore, physical-
chemical properties do not support an exposure pathway through water and soil pathways to terrestrial
organisms.
4.2 Human Health Risk
PCE exposure is associated with a variety of cancer and non-cancer adverse effects deemed relevant to
humans for risk estimations for the scenarios and populations addressed in this risk evaluation. Based on
a weight-of-evidence analysis of the available toxicity studies from animals and humans, the non-cancer
effects selected for risk estimation because of their robustness and sensitivity were neurotoxicity (i.e.
increased latencies for pattern reversal visual-evoked potentials) from acute exposure, developmental
toxicity from repeated exposures (i.e. longer than acute, single day exposures and shorter than chronic,
many year exposures) and multiple effects including CNS, kidney, liver and immune system toxicity from
chronic exposures. The evaluation of cancer includes estimates of risk of lung and liver tumors.
4.2.1 Risk Estimation Approach
Equation 4-1 was used to calculate non-cancer risks using margins of exposure for acute or chronic
exposure durations.
Equation 4-1 Equation to Calculate Non-Cancer Risks Following Acute or Chronic Exposures
Using Margin of Exposures
Non — cancer Hazard value (POD)
MOEacute or chronic 7r ^
Human Exposure
Where:
MOE = Margin of exposure (unitless)
Hazard value (POD) = HEC (ppm)
Human Exposure = Exposure estimate (in ppm) from occupational or consumer exposure
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assessment. ADCs were used for non-cancer chronic risks and acute
concentrations were used for acute risks (see Section 3.2.5)
EPA/OPPT used margin of exposures (MOEs)18 to estimate acute or chronic risks for non-cancer based
on the following:
1. the lowest HECs within each health effects domain reported in the literature;
2. the endpoint/study-specific UFs applied to the HECs per the EPA Guidance (U.S. EPA, 2002);
and
3. the exposure estimates calculated for PCE uses examined in this risk assessment (see Section 2
Exposures).
MOEs allow for the presentation of a range of risk estimates. The occupational exposure scenarios
considered both acute and chronic exposures. All consumer uses considered only acute exposure
scenarios. Different adverse endpoints were used based on the expected exposure durations. For non-
cancer effects, risks for neurotoxicity (i.e. increased latencies for pattern reversal visual-evoked
potentials) from acute exposure were evaluated.
For occupational exposure calculations, the 8 hr or 12 hr TWA was used to calculate inhalation MOEs
for risk estimates for acute exposures and the chronic average daily concentration (ADC) was used for
chronic exposures. For dermal estimates, acute and chronic retained doses were used. The total UF for
each non-cancer POD was the benchmark MOE used to interpret the MOE risk estimates for each use
scenario. The MOE estimate was interpreted as human health risk if the MOE estimate was less than
the benchmark MOE (i.e. the total UF). On the other hand, the MOE estimate indicated negligible
concerns for adverse human health effects if the MOE estimate exceeded the benchmark MOE.
Typically, the larger the MOE, the more unlikely it is that a non-cancer adverse effect would occur.
Risk estimates were calculated for all of the studies per health effects domain that EPA/OPPT
considered suitable for the risk evaluation of acute and chronic exposure scenarios in the work plan risk
assessment for PCE.
The PBPK model (Section 3.2.2.2) allowed it to be used to calculate internal dose metrics for inhaled
and oral exposure to PCE for mice, rats, and humans and therefore was used for route-to-route
extrapolation between oral and inhalation routes. Dermal candidate values were calculated based on
route-to-route extrapolation from two different routes either inhalation or oral PODs. The PODs were
extrapolated from POD values based on either human data or human equivalent values (e.g. BMDLhec)
which have already been adjusted to account for animal to human extrapolation using the best available
approaches for incorporating PCE specific toxicokinetic data (i.e. the PBPK model) when possible.
When dermal HEDs were derived by both methods, the most sensitive resulting HED was selected for
use in risk estimation in order to be health-protective.
Added cancer risks for repeated exposures to PCE were estimated using Equation 4-2. Estimates of
added cancer risks should be interpreted as the incremental probability of an individual developing
cancer over a lifetime as a result of exposure to the potential carcinogen (i.e., incremental or added
individual lifetime cancer risk).
18 Margin of Exposure (MOE) = (Non-cancer hazard value, POD) (Human Exposure). Equation 4-1. The benchmark MOE
is used to interpret the MOEs and consists of the total UF shown in Table 3-5.
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8708
8709
8710
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8714
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Equation 4-2 Equation to Calculate Added Cancer Risks
Risk = Human Exposure x IUR
Where:
Risk = Added cancer risk (unitless)
Human exposure = Exposure estimate (LADC in mg/m3) from occupational exposure assessment
IUR = Inhalation unit risk (2 x 10"3 per mg/m3)
4.2.2 Risk Estimation for Inhalation Exposures to Workers
4.2.2.1 PODs used for Occupational Inhalation Risk Estimates
The risk assessment used the inhalation exposure estimates in Section 2.4.1 and the hazard PODs
summarized in Table 3-7, Table 3-8, and Table 3-9. For acute exposure scenarios, PODs for 8 and 12hr
exposure durations were used because those durations are most applicable to occupational exposure
scenarios. From among all chronic studies, EPA selected the most robust studies and non-cancer PODs
from within each health domain to serve as representative endpoints for risk estimation (Section 3.2.5.4).
These representative PODs are presented below in Table 4-2 along with the acute POD. Non-cancer risk
estimates were calculated with equation 4-1 and cancer risks were calculated with equation 4-2. Risk is
indicated for each OES or COU by bold text and a shaded cell in the table.
Table 4-2. Selected Non-cancer PODs for Use in Risk Estimation of Inhalation Exposures
Target Organ
System
Species
Human Equivalent
Concentration
(HEC)
Effect
Total Uncertainty
Factor (UF) for
Benchmark MOE
Reference
Data
Quality
Score
ACUTE EXPOSURE
CNS
Humans
8 hrs/day = 5 ppm
(34 mg/m3)
12 hrs/day = 3.3 ppm
(22 mg/m3)
Neurotoxicity increased
latencies for pattern
reversal visual-evoked
potentials
UFa=1;
UFh=10;
UFl=1
Total UF=10
Altmann et
al. (1990)
Medium
CHRONIC EXPOSURE
CNS
Humans
5.2 ppm
(36 mg/m3)
Midpoint of the range of
the two neurotoxicity
studies
UFA=1;
UFh=10;
UFl=10
Total UF=100
Based on
U.S. EPA
(2012c)
Medium
Kidney
Mice
2.1 ppm
(14 mg/m3)
Nuclear enlargement in
proximal tubules
UFA=3;
UFh=10;
UFl=1
Total UF=30
JISA (1993)
High
Liver
Mice
31 ppm
(210 mg/m3)
Increased angiectasis in
liver
UFA=3;
UFh=10;
UFl=1
Total UF=30
JISA (1993)
High
Reproductive/
Developmental
Reproductive
Mice
21 ppm
(140 mg/m3)
Reduced sperm quality
following 5 days
exposure
UFA=3;
UFh=10;
UFl=1
Total UF=30
Beliles et al.
(1980)
High
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8729
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1 arsicl Or^an
Sjsiem
Species
lluiiiiiii l'l(|iii\alenl
Concenlralion
(MIX)
1. flee I
Tolal I ncort;iinl>
l-aclor (I I") for
licnchmark MOI.
Reference
Dalii
Qu;ili(>
Score
Developmental
Rats
18 ppm
(122 mg/m3)
Increased F2a pup
deaths by Day 29, CNS
depression in Fi and F2
UFa=3;
UFh=10;
UFl=1
Total UF=30
Tinston et
al. (1994)
High
CANCER
Liver
Mouse
IUR
2 x 10"3 per ppm
(3 x 10"4 per mg/m3)
Hepatocellular tumors
(males)
N/A
JISA (1993)
High
EPA also provided chronic inhalation risk estimates as a sensitivity analysis based on 8 hr and 12 hr
occupational neurotoxicity HECs (14.5 ppm and 9.7 ppm, respectively, see Table 3-8) compared to 8 hr
or 12 hr TWA exposures. These risk estimates are approximately 36% lower than the risk estimates
using the chronic HECs based on continuous 24 hr exposure. See Appendix G for risk estimates for all
OES.
4.2.2.2 Occupational Inhalation Exposure Summary and PPE Use Determination by
OES
EPA considered all reasonably available data for estimating exposures for each OES. EPA also
determined whether respirator use up to APF = 50 was plausible for those OES based on expert
judgement and reasonably available information. Table 4-3 presents this information below, which is
considered in the risk characterization for each OES in the following sections.
Table 4-3. Inhalation Exposure Data Summary and Respirator Use Determination
Occnpalional
l.xposuic Scenario
Inhalation
l-lxpoMirc
Approach
Nil in her
of Dala
Points
Model I seel
Approach for
OM s
Kcspiralor
I se
liulnsli'ial oi'
Coin niercial
OI.S
Manufacturing
Monitoring
data
152 (75
8-hr
TWA and
77 12-hr
TWA)
N/A - monitoring
data only
Equal to workers
(assumes
employees may be
workers or ONUs
throughout their
shift)
May use
respirators
Industrial
Repackaging
Monitoring
data
10
N/A - monitoring
data only
Not assessed
May use
respirators
Industrial
Processing as a
Reactant
Surrogate
monitoring
data from
manufacturing
152 (75
8-hr
TWA and
77 12-hr
TWA)
N/A - monitoring
data only
Equal to workers
(assumes
employees may be
workers or ONUs
throughout their
shift)
May use
respirators
Industrial
Incorporation into
Formulation -
Aerosol Packing
Monitoring
data
5
N/A - monitoring
data only
Not assessed
May use
respirators
Industrial
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Occiipiilioiiiil
l-l\posuiv Scciiiii'io
liihiiliilion
l'l\|)OMIIV
Approach
Number
ol' l)iil;i
Points
Model I sod
Approach for
OM s
Kcspii'iiloi*
I si-
Induslriiil or
( ommciviid
OI'.S
Incorporation into
Formulation - Non-
Aerosol Formulations
Modeling
N/A-
model
only
EPA/OAQPS AP-42
Loading Model &
EPA/OPPT Mass
Balance Model
Not assessed
May use
respirators
Industrial
Open-Top Vapor
Degreasing
Monitoring
data
75 (63
worker
and 12
ONUs)
N/A - monitoring
data only
ONU monitoring
data available
May use
respirators
Industrial/
Commercial
Closed-Loop Vapor
Degreasing
Monitoring
data
15 (13
worker
and 2
ONU)
N/A - monitoring
data only
ONU monitoring
data available
May use
respirators
Industrial/
Commercial
Conveyorized Vapor
Degreasing
Model
N/A-
model
only
Conveyorized
Degreasing Near-
Field/Far-Field
Inhalation Exposure
Model
Far-field model
results
May use
respirators
Industrial/
Commercial
Web Degreasing
Model
N/A-
model
only
Web Degreasing
Near-Field/Far-Field
Inhalation Exposure
Model
Far-field model
results
May use
respirators
Industrial/
Commercial
Cold Cleaning
Monitoring
data
supplemented
by model
29
Cold Cleaning Near-
Field/Far-Field
Inhalation Exposure
Model
Far-field model
results
May use
respirators
Industrial/
Commercial
Aerosol Degreasing
and Aerosol
Lubricants
Monitoring
data
supplemented
by model
130
Brake Servicing
Near-Field/Far-Field
Inhalation Exposure
Model
Far-field model
results
No respirator
use -
commercial
use
Commercial
Dry Cleaning
Monitoring
data
supplemented
by model
140(135
workers
and 5
ONUs)
Dry Cleaning Multi-
Zone Inhalation
Exposure Model
ONU monitoring
data available
supplemented by
far-field model
results
No respirator
use -
commercial
use
Commercial
Paint and Coatings
Monitoring
data
15
N/A - monitoring
data only
Not assessed
May use
respirators
Industrial/
Commercial
Adhesives
Monitoring
data
13
N/A - monitoring
data only
Not assessed
May use
respirators
Industrial/
Commercial
Chemical Maskant
Monitoring
data
24
N/A - monitoring
data only
Not assessed
May use
respirators
Industrial
Industrial Processing
Aid
Monitoring
data
89
N/A - monitoring
data only
Not assessed
May use
respirators
Industrial
Page 335 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Occiipiilioiiiil
l-l\posuiv Scciiiii'io
liihiiliilion
l'l\|)OMIIV
Approach
Number
ol' l)iil;i
Points
Model I sod
Approach for
OM s
Kcspii'iiloi*
I si-
Induslriiil or
( ommciviid
OI'.S
Other Industrial Uses
Model
N/A-
model
only
Tank Truck and
Railcar Loading and
Unloading Release
and Inhalation
Exposure Model
Not assessed
May use
respirators
Industrial
Metalworking Fluid
Emission
scenario
document
N/A-
emission
scenario
document
Estimates from Use
of Metalworking
Fluids ESD
Not assessed
No respirator
use - ESD
indicates
respirators
are not
generally
used
Industrial/
Commercial
Wipe Cleaning
Monitoring
data
10(4
workers
and 6
ONUs)
N/A - monitoring
data only
ONU monitoring
data available
No respirator
use -
commercial
use
Commercial
Other Spot
Cleaning/Spot
Removers (including
Carpet Cleaning)
Monitoring
data
3 (2
workers
and 1
ONU)
N/A - monitoring
data only
ONU monitoring
data available
No respirator
use -
commercial
use
Commercial
Other Commercial
Uses
Monitoring
data
92
N/A - monitoring
data only
Not assessed
No respirator
use -
commercial
use
Commercial
Other DoD Uses
Monitoring
data
2
N/A - monitoring
data only
Not assessed
May use
respirators
Industrial/
Commercial
Disposal/Recycling
Model
N/A-
model
only
Tank Truck and
Railcar Loading and
Unloading Release
and Inhalation
Exposure Model
Not assessed
May use
respirators
Industrial
8734
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8743
8744
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8746
8747
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4.2.2.3 Manufacturing
For manufacturing, exposure estimates for TWAs of 15 mins, 30 mins, 8 hrs, and 12 hrs are available
based on personal monitoring data samples, including 351 data points from one source. EPA calculated
50th and 95th percentiles to characterize the central tendency and high-end exposure estimates,
respectively. Data were not available to estimate ONU exposures; EPA estimates that ONU exposures
are lower than worker exposures, since ONUs do not typically directly handle the chemical. In lieu of
data, EPA uses worker central tendency values as a surrogate to estimate risks for ONUs.
Considering the overall strengths and limitations of the data, EPA's overall confidence in the
occupational inhalation estimates in this scenario is high for workers and low for ONUs. Section 2.4.1.6
describes the justification for this occupational scenario confidence rating.
Table 4-4. Risk Estimation for Acute. Non-Cancer Inhalation Exposures for Manufacturing
MIX Time
Period
l.nripoinl =
cns r.nwis'
Acule
MIX
<|)|)in)
I'ApOMII'C
l.e\el
\\ orker
No
respiralor
MO
ON I
No
respiralor
¦!s for Acule
Worker
API- 10
l'!\posures
Worker API-
25
Worker API-
50
licnchmark
moi:
(= Toliil I 1")
8-hr
5.0
llid.-
Lnd
l.'J
154
19
48
96
10
Central
Tendency
154
1,538
3,846
7,692
12-hr
3.3
High-
End
16
161
156
389
778
10
Central
Tendency
161
1,610
4,024
8,049
1 Data from Altmann et al. (1990)
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-5. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Manufacturing
r.mlpoini
Chronic
MIX
(ppm)
Kxposure
1 .e\ el
Worker
No
respiralor
MOI-'.s lor
ONI
No
respirator1
Chronic 11
W orker
API- 10
iposurc
W orker
API- 25
W orker
API- 50
licnchmark
MOI.
(= Toial
I 1)
liaso.1 i'ii exposure dala li»rX In TW \
CiNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
8.7
701
87
218
436
100
Central
Tendency
"u|
3.5
7,008
17,520
35,040
Kidney -
Histopathology
(USA 1993)
2.1
High-
End
283
35
88
176
30
Central
Tendency
283
2,830
7,075
14,151
Liver -
Vessel dilation
(USA 1993)
31
High-
End
52
4,178
520
1,300
2,599
30
Central
Tendency
4,178
41,778
104,446
208,892
Reproductive -
Sperm effects
(Bellies et al.
1980)
21
High-
End
35
2,830
352
880
1,761
30
Central
Tendency
2,830
28,302
70,754
141,508
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Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 10
Worker
APF 25
Worker
APF 50
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
30
2,426
302
755
1,509
30
Central
Tendency
2,426
24,258
60,646
121,292
Based on exposure data for 12 lir TWA
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
72
741
716
1,791
3,581
100
Central
Tendency
741
7,407
18,517
37,034
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
29
299
289
723
1,446
30
Central
Tendency
299
2,991
7,478
14,956
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
427
4,416
4,270
10,675
21,349
30
Central
Tendency
4,416
44,156
110,390
220,780
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
289
2,991
2,892
7,231
14,462
30
Central
Tendency
2,991
29,912
74,780
149,561
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
30
2,426
302
755
1,509
30
Central
Tendency
2,426
24,258
60,646
121,292
8752
8753
8754
8755
8756
1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-6. Risk Estimation for Chronic, Cancer Inhalation Exposures for Manufacturing
IUR
Cancer Risk Estimates
Endpoint,
(risk
Worker
ONU
Tumor
per
Exposure
No
No
Worker
Worker
Worker
Types1
ppm)
Level
respirator
respirator2
APF 10
APF 25
APF 50
Benchmark
Based on exposure data for 8 lir TWA
Cancer Risk
liver tumors
High-End
6.1E-4
6.1E-5
2.4E-5
1.2E-5
2.0E-3
Central
Tendency
5.9E-6
5.9E-6
5.9E-7
2.4E-7
1.2E-7
10"4
Based on exposure data for 12 lir TWA
Cancer Risk
liver tumors
High-End
7.5E-5
7.5E-6
3.0E-6
1.5E-6
2.0E-3
Central
Tendency
5.6E-6
5.6E-6
5.6E-7
2.2E-7
1.1E-7
10"4
8757 1 Data from JISA (1993)
8758 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
8759 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Page 338 of 636
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8767
8768
8769
8770
8771
8772
8773
8774
8775
8776
8777
8778
8779
8780
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
4.2.2.4 Repackaging
For repackaging, exposure estimates for TWAs of 15 mins, 30 mins, and 8 hrs are available based on
personal monitoring data samples, including 17 data points from 1 source. EPA calculated 50th and 95th
percentiles to characterize the central tendency and high-end exposure estimates, respectively, for the 8-
hr TWAs. Due to the limited number of data points, EPA used the median and maximum to characterize
the central tendency and high-end exposure estimates, respectively, for the 15- and 30-min TWAs. EPA
has not identified reasonably available data on potential ONU inhalation exposures from PCE
repackaging. ONU inhalation exposures are expected to be lower than worker inhalation exposures
however the relative exposure of ONUs to workers cannot be quantified as described in more detail
above in Section 2.4.1.7. In lieu of data, EPA uses worker central tendency values as a surrogate to
estimate risks for ONUs. Considering the overall strengths and limitations of the data, EPA's overall
confidence in the occupational inhalation estimates in this scenario is medium for workers and low for
ONUs. Section 2.4.1.7 describes the justification for this occupational scenario confidence rating.
Table 4-7. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Import/Repackaging
NIX' Time Period
Kndpoinl = ( NS
I-! Heels'
Aeule
MIX
(|)|)in)
l-'.\posiire l.e\el
Worker
No
respiralor
moi-'.s r»
OM
No
respinilor
r Aeule l'.\
Worker
API- 10
posures
W orker
API- 25
Worker
API- 50
lienchmark
MOI.
(= Tolal
I 1)
8-hr
5.0
High-
End
(•.1
11
61
153
305
10
Central Tendency
11
115
287
574
1 Data from Altmann et al. (1990)
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-8. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for
I'lndpoinl
Chronic
MIX
(ppm)
l-'.\posiire
l.e\el
Worker
No
respinilor
MOI-'.s for (
ONI
No
respinilor1
hronic 1"\j
Worker
API 10
)osure
Worker
API- 25
Worker
API- 50
lienchmark
MOI!
(= Total
I 1)
CNS -
Visual effects
(U.S. EPA 2012c)
5.2
High-
End
2X
52
278
695
1,390
100
Central
Tendency
52
523
1,308
2,617
Kidney -
Histopathology
(USA 1993)
2.1
High-
End
II
21
112
281
561
30
Central
Tendency
21
211
528
1,057
Liver -
Vessel dilation
(USA 1993)
31
High-
End
166
312
1,657
4,413
8,287
30
Central
Tendency
312
3,120
7,799
15,599
Reproductive -
Sperm effects
(Bellies et al.
1980)
21
High-
End
112
211
1,123
2,807
5,614
30
Central
Tendency
211
2,113
5,283
10,567
Developmental -
18
High-
96
181
962
2,406
4,812
30
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8786
8787
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8789
8790
8791
8792
8793
8794
8795
8796
8797
8798
8799
8800
8801
8802
8803
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
r.mlpoinl
Chronic
MIX
(ppiii)
l'l\posurc
1 .c\ el
Worker
No
rcspiralor
MOI-'.s lor
()\l
No
respiralor1
h roilic l'.\
Worker
API- 10
)osure
Worker
API- 25
Worker
API- 50
licnchmark
MOI.
(= Tolal
I 1)
Mortality/
CNS effects
("Tinston 1994)
End
Central
Tendency
181
1,811
4,529
9,057
1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-9. Risk Estimation for Chronic, Cancer Inhalation Exposures for Import/Repackaging
r.mlpoinl. Tumor
Tjpes"
11 K
(risk per
ppm)
l'l\posiirc
l.e\el
W orker
No
rcspiralor
Cancer
ONI
No
respiralor
Risk l.sliin
Worker
API- 10
ales
W orker
API- 25
Worker
API 50
licnchmark
Cancer Risk
liver tumors
2.0E-3
High-End
1.91.-4
7.9E-5
1.9E-5
7.7E-6
3.8E-6
10"4
Central
Tendency
7.9E-5
7.9E-6
3.2E-6
1.6E-6
1 Data from JISA (.1.9931
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
4.2.2.5 Processing as Reactant
For processing as a reactant, exposure estimates for TWAs of 15 mins, 30 mins, and 8 hrs are available
based on surrogate personal monitoring data samples, including 351 data points from one source. EPA
uses surrogate data for PCE manufacturing to approximate exposures during processing as a reactant as
monitoring data specific to this condition of use were not available and manufacturing sites and sites
processing PCE as a reactant are expected to have similar operations. EPA calculated 50th and 95th
percentiles to characterize the central tendency and high-end exposure estimates, respectively. Data were
not available to estimate ONU exposures; EPA estimates that ONU exposures are lower than worker
exposures, since ONUs do not typically directly handle the chemical. In lieu of data, EPA uses worker
central tendency values as a surrogate to estimate risks for ONUs. Considering the overall strengths and
limitations of the data, EPA's overall confidence in the occupational inhalation estimates in this scenario
is medium to high for workers and low for ONUs. Section 2.4.1.8 describes the justification for this
occupational scenario confidence rating.
Table 4-10. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Processing as
Reactant
MIX Time
Period
I'lmlpoini =
CNS r.lTccls1
Acule
MIX
(ppm)
l-lxposurc
1 .c\ el
W orker
No
respirator
MO
ONI
No
respiralor
¦Is lor Acule
Worker
API- 10
Mxposures
Worker API-
25
Worker API-
50
licnchmark
MOI!
(= Tolal I 1)
8-hr
5.0
High-
End
i.y
154
19
48
96
10
Central
Tendency
154
1,538
3,846
7,692
12-hr
3.3
High-
End
16
161
156
389
778
10
Page 340 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HEC Time
Period
Endpoint =
CNS Effects1
Acute
HEC
(ppm)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator2
Worker
APF 10
Worker APF
25
Worker APF
50
Central
Tendency
161
1,610
4,024
8,049
8804 1 Data from Altmann et al. (1990)
8805 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
8806 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
8807
8808 Table 4-11. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Processing as
8809 Reactant
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 10
Worker
APF 25
Worker
APF 50
Based on exposure data for 8 hr TWA
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
8.7
701
87
218
436
100
Central
Tendency
701
7,008
17,520
35,040
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
3.5
283
35
88
176
30
Central
Tendency
283
2,830
7,075
14,151
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
52
4,178
520
1,300
2,599
30
Central
Tendency
4,178
41,778
104,446
208,892
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
35
2,830
352
880
1761
30
Central
Tendency
2,830
28,302
70,754
141,508
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
30
2,426
302
755
1,509
30
Central
Tendency
2,426
24,258
60,646
121,292
Based on exposure data for 12 hr TWA
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
72
741
716
1,791
3,581
100
Central
Tendency
741
7,407
18,517
37,034
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
29
299
289
723
1,446
30
Central
Tendency
299
2,991
7,478
14,956
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
427
4,416
4,270
10,675
21,349
30
Central
Tendency
4,416
44,156
110,390
220,780
Reproductive -
Sperm effects
21
High-
End
289
2,991
2,892
7,231
14,462
30
Page 341 of 636
-------
8810
8811
8812
8813
8814
8815
8816
8817
8818
8819
8820
8821
8822
8823
8824
8825
8826
8827
8828
8829
8830
8831
8832
8833
8834
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
r.mlpoinl
(
)
Chronic
MIX
(ppnn
l'l\poMirc
1 .c\ cl
\\ orkcr
No
rcspiralor
MOI-'.s I'm
()\l
No
rcspiralor1
Chronic 1.
\\ orkcr
API 10
\posnrc
\\ orkcr
API- 25
Worker
API- 50
Benchmark
MOI.
(= Toial
1 1 )
("cm nil
TcildcilCN
:.'wi
"4. "S()
I4'J.5<> 1
Developmental -
Mortality/
CNS effects
("Tinston 1994)
18
High-
End
248
2,564
2,479
6,198
12,396
30
Central
Tendency
2,564
25,639
64,098
128,195
1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-12.1
lisk Estimation
'or Chronic, Cancer Inhalation Exposures for Processing as Reactant
r.mlpoinl.
Tumor
Tjpes"
11 K
(risk
per
ppm)
l-lxposiirc
l.c\cl
Worker
No
rcspiralor
C
ONI
No
rcspiralor
nicer Risk l-'.s
W orkcr
API- 10
imalcs
Worker
API- 25
Worker
API- 50
Bench in a rk
Based on exposure data for 8 hr TWA
Cancer Risk
liver tumors
2.0E-3
High-End
11.-4
5.9E-6
6.1E-5
2.4E-5
1.2E-5
10"4
Central
Tendency
5.9E-6
5.9E-7
2.4E-7
1.2E-7
Based on exposure data for 12 hr TWA
Cancer Risk
liver tumors
2.0E-3
High-End
7.5E-5
5.6E-6
7.5E-6
3.0E-6
1.5E-6
10"4
Central
Tendency
5.6E-6
5.6E-7
2.2E-7
1.1E-7
1 Data from JISA (.1.9931
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
4.2.2.6 Incorporation into Formulation, Mixture, or Reactant Product
For incorporation into formulation, mixture, or reaction product, exposure estimates for TWAs of 8 hrs
are available based on personal monitoring data samples for aerosol packing, including 5 data points
from one source, and modeling for degreasing solvent, dry cleaning solvent, and miscellaneous product
formulations. For aerosol packing, EPA calculated the median and maximum to characterize the central
tendency and high-end exposure estimates, respectively. For the other formulation types, EPA calculated
50th and 95th percentiles to characterize the central tendency and high-end exposure estimates,
respectively. EPA has not identified reasonably available data to estimate potential ONU inhalation
exposures from PCE incorporation into formulation, mixture, or reaction product using monitoring data
or modeling. ONU inhalation exposures are expected to be lower than worker inhalation exposures
however the relative exposure of ONUs to workers cannot be quantified as described in more detail
above in Section 2.4.1.9. In lieu of data, EPA uses worker central tendency values as a surrogate to
estimate risks for ONUs. Considering the overall strengths and limitations of the data, EPA's overall
confidence in the aerosol packing inhalation estimates in this scenario is high for workers and low for
ONUs and EPA's overall confidence in the modeled exposures for other formulation types is medium
for workers and low for ONUs. Section 2.4.1.9 describes the justification for this occupational scenario
confidence rating.
Page 342 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
8835 Table 4-13. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Incorporation into
8836 Formulation, Mixture, or Reactant Product
HEC Time
Period
Endpoint = CNS
Effects1
Acute
HEC
(ppm)
Exposure Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator2
Worker
APF 10
Worker
APF 25
Worker
APF 50
Aerosol Packing
8-hr
5.0
High-End
0.4
0.6
3.8
9.5
19
10
Central Tendency
0.6
6.0
15
30
Degreasing Solvent
8-hr
5.0
High-End
1.9
6.9
19
48
96
10
Central Tendency
6.9
69
171
343
Dry Cleaning Solvent
8-hr
5.0
High-End
0.4
1.3
3.5
8.9
18
10
Central Tendency
1.3
13
32
63
Miscellaneous
8-hr
5.0
High-End
3.5
13
35
89
177
10
Central Tendency
13
126
315
629
8837 1 Data from Altmann et al. (1990)
8838 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
8839 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
8840
8841 Table 4-14. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Incorporation into
8842 Formulation, Mixture, or Reactant Product
MOEs for Chronic Exposure
Benchmark
Chronic
Worker
ONU
MOE
HEC
Exposure
No
No
Worker
Worker
Worker
(= Total
Endpoint
(ppm)
Level
respirator
respirator1
APF 10
APF 25
APF 50
UF)
Aerosol Packing
CNS -
Visual Effects
High-End
1.7
17
43
87
5.2
Central
Tendency
2.7
2.7
27
69
137
100
Kidney -
Histopathology
High-End
0.7
7.0
18
35
2.1
Central
Tendency
1.1
1.1
11
28
55
30
Liver -
Vessel dilation
High-End
10
103
258
517
31
Central
Tendency
16
16
164
410
819
30
Reproductive -
Sperm Effects
High-End
7.0
70
175
350
21
Central
Tendency
11
11
111
277
555
30
Developmental
High-End
6.0
60
150
300
Mortality/CNS
18
Central
Tendency
9.5
9.5
95
237
475
30
Page 343 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 10
Worker
APF 25
Worker
APF 50
Degreasing Solvent
CNS -
Visual Effects
5.2
High-End
92
328
918
2,296
4,591
100
Central
Tendency
328
3,277
8,194
16,387
Kidney -
Histopathology
2.1
High-End
37
132
371
927
1,854
30
Central
Tendency
132
1,324
3,309
6,618
Liver -
Vessel dilation
31
High-End
547
1,954
5,474
13,685
27,371
30
Central
Tendency
1,954
19,539
48,846
97,693
Reproductive -
Sperm Effects
21
High-End
371
1,324
3,708
9,271
18,542
30
Central
Tendency
1,324
13,236
33,089
66,179
Developmental
Mortality/CNS
18
High-End
318
1,134
3,179
7,946
15,893
30
Central
Tendency
1,134
11,345
28,362
56,725
Dry Cleaning Solvent
CNS -
Visual Effects
5.2
High-End
17
60
169
423
847
100
Central
Tendency
60
604
1,509
3,018
Kidney -
Histopathology
2.1
High-End
6.8
24
68
171
342
30
Central
Tendency
24
244
609
1,219
Liver -
Vessel dilation
31
High-End
101
360
1,009
2,523
5,047
30
Central
Tendency
360
3,599
8,996
17,993
Reproductive -
Sperm Effects
21
High-End
68
244
684
1,709
3,419
30
Central
Tendency
244
2,438
6,094
12,189
Developmental
Mortality/CNS
18
High-End
59
209
586
1,465
2,930
30
Central
Tendency
209
2,089
5,224
10,447
Miscellaneous
CNS -
Visual Effects
5.2
High-End
169
602
1,693
4,231
8,463
100
Central
Tendency
602
6,016
15,041
30,082
Kidney -
Histopathology
2.1
High-End
68
243
684
1,709
3,418
30
Central
Tendency
243
2,430
6,074
12,149
Liver -
Vessel dilation
31
High-End
1,009
3,587
10,090
25,226
50,451
30
Central
Tendency
3,587
35,868
89,669
179,338
Reproductive -
Sperm Effects
21
High-End
684
2,430
6,835
17,088
34,177
30
Central
Tendency
2,430
24,297
60,744
121,487
18
High-End
586
2,083
5,859
14,647
29,294
30
Page 344 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 10
Worker
APF 25
Worker
APF 50
Developmental
Mortality/CNS
Central
Tendency
2,083
20,826
52,066
104,132
8843 1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
8844 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
8845
8846 Table 4-15. Risk Estimation for Chronic, Cancer Inhalation Exposures for Incorporation into
8847 Formulation, Mixture, or Reactant Product
Endpoint,
Tumor
Types1
IUR
(risk per
ppm)
Exposure Level
Cancer Risk Estimates
Benchmark
Worker
No
respirator
ONU
No
respirator2
Worker
APF 10
Worker
APF 25
Worker
APF 50
Aerosol Packing
Cancer Risk
liver tumors
2.0E-3
High-End
3.1E-3
1.5E-3
3.1E-4
1.2E-4
6.2E-5
10"4
Central Tendency
1.5E-3
1.5E-4
6.0E-5
3.0E-5
Degreasing Solvent
Cancer Risk
liver tumors
2.0E-3
High-End
1.7E-5
4.7E-6
1.7E-6
6.7E-7
3.3E-7
10"4
Central Tendency
4.7E-6
4.7E-7
1.9E-7
9.4E-8
Dry Cleaning Solvent
Cancer Risk
liver tumors
2.0E-3
High-End
9.1E-5
2.5E-5
9.1E-6
3.6E-6
1.8E-6
10"4
Central Tendency
2.5E-5
2.5E-6
1.0E-6
5.1E-7
Miscellaneous
Cancer Risk
liver tumors
2.0E-3
High-End
9.1E-6
2.6E-6
9.1E-7
3.6E-7
1.8E-7
10"4
Central Tendency
2.6E-6
2.6E-7
1.0E-7
5.1E-8
8848 1 Data from JISA (1993)
8849 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
8850 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
8851 4.2.2.7 Batch Open-Top Vapor Degreasing
8852 For OTVDs, exposure estimates for TWAs of 15 mins, 4 hrs, and 8 hrs are available based on personal
8853 monitoring data samples, including 79 data points from multiple sources. For 8-hr TWAs, EPA
8854 calculated 50th and 95th percentiles to characterize the central tendency and high-end exposure estimates,
8855 respectively. Due to the limited number of data points, EPA used the median and maximum to
8856 characterize the central tendency and high-end exposure estimates, respectively, for the 4-hr TWA. For
8857 the 15-min TWA, exposures are based on the single data point that was available. EPA identified 12 of
8858 the 79 data points to be for ONU exposures at sites operating OTVDs as described in more detail above
Page 345 of 636
-------
8859
8860
8861
8862
8863
8864
8865
8866
8867
8868
8869
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
in Section 2.4.1.10. Considering the overall strengths and limitations of the data, EPA's overall
confidence in the occupational inhalation estimates in this scenario is medium to high. Section 2.4.1.10
describes the justification for this occupational scenario confidence rating.
Table 4-16. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Batch Open-Top
Vapor Degreasing
HEC Time
Period
Endpoint =
CNS Effects1
Acute
HEC
(ppm)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total
UF)
Worker
No respirator
ONU
No respirator
Worker
APF 10
Worker
APF 25
Worker
APF 50
8-hr
5.0
High-End
0.2
1.0
1.6
3.9
7.8
10
Central
Tendency
2.4
8.2
24
60
119
1 Data from Altmann et al. (1990)
Table 4-17. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Batch Open-Top
Vapor Degreasing
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 10
Worker
APF 25
Worker
APF 50
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
0.7
4.4
7.1
18
35
100
Central
Tendency
11
38
108
271
542
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
0.3
1.8
2.9
7.2
14
30
Central
Tendency
4.4
15
44
110
219
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
4.2
26
42
106
212
30
Central
Tendency
65
224
647
1,616
3,233
Reproductive -
Sperm effects
(Bclilcs et al.
1980)
21
High-
End
2.9
18
29
72
143
30
Central
Tendency
44
152
438
1,095
2,190
Developmental -
Mortality/
CNS effects
(Tinston 1994)
21
High-
End
2.5
15
25
61
123
30
Central
Tendency
38
130
375
939
1,877
Page 346 of 636
-------
8870
8871
8872
8873
8874
8875
8876
8877
8878
8879
8880
8881
8882
8883
8884
8885
8886
8887
8888
8889
8890
8891
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-18. Risk Estimation for Chronic, Cancer Inhalation Exposures for Batch Open-Top
Vapor Degreasing i
11 K
Cancer Risk I'.slimak
s
lindpoinl.
(risk
Tumor
per
Exposure
\\ orkcr
OM
\\ orkcr
\\ orkcr
\\ orkcr
Tjpes"
ppm)
l.c\cl
No rcspiralor
No respirator
API- 10
API- 25
API 50
benchmark
Cancer Risk
liver tumors
1 liull-l Jill
7.51.-3
1.21.-3
_7.5i-:-4
3.01.-4
1.51.-4
2.0E-3
Central
Tendency
3.8E-4
I.I 1.-4
' si :-5
15i :-5
~ (.1 -(.
io-4
1 Data from JISA (.1.9931
4.2.2.8 Batch Closed-Loop Vapor Degreasing
For batch closed-loop vapor degreasing, exposure estimates for TWAs of 4 hrs and 8 hrs are available
based on personal monitoring data samples, including 18 data points from two sources. For worker 8-hr
TWAs, EPA calculated 50th and 95th percentiles to characterize the central tendency and high-end
exposure estimates. Due to the limited number of data points, for 4-hr TWAs and ONU 8-hr TWAs,
EPA calculated the median and maximum to characterize the central tendency and high-end exposure
estimates. EPA identified 2 of the 18 data points to be for ONU exposures at sites operating batch
closed-loop vapor degreasers as described in more detail above in Section 2.4.1.11. Considering the
overall strengths and limitations of the data, EPA's overall confidence in the occupational inhalation
estimates in this scenario is high. Section 2.4.1.11 describes the justification for this occupational
scenario confidence rating.
Table 4-19. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Batch Closed-Loop
Vapor Degreasing
MIX Time
Period
I'.ndpoini =
cns i-nwis1
Aculc
MIX
(ppm)
Exposure
l.c\cl
Worker
No respirator
MOI-'.s lor
ONI
No ivspinilor
Vculc ll\pos
W orkcr
API- 10
IIIVS
Worker
API- 25
W orkcr
API- 50
licnchmark
MOI.
(= Tolal I 1)
8-hr
5.0
High-End
20
52
198
494
988
10
Central
Tendency
69
76
693
1,732
3,463
1 Data from Altmann et al. (1990)
Table 4-20. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Batch Closed-
Loop Vapor Degreasing
I'.ndpoini
Chronic
MIX
(ppm)
Exposure
1 .c\ el
Worker
No
respiralor
MOHs lor<
ONI
No
rcspiralor
lironic l'.\
Worker
API- 10
)osure
W orkcr
API- 25
W orkcr
API- 50
licnchniark
MOI.
(= loial
1 1 )
CNS -
Visual effects
(U.S. EPA 2012c)
5.2
lligh-
End
«)0
238
900
2,250
4,501
100
Central
Tendency
316
348
3,155
7,888
15,776
Kidney -
Histopathology
(JISA 1993)
2.1
High-
End
1(1
96
364
909
1,818
30
Central
Tendency
127
141
1,274
3,185
6,371
Liver -
31
High-
537
1,418
5,366
13,416
26,832
30
Page 347 of 636
-------
8892
8893
8894
8895
8896
8897
8898
8899
8900
8901
8902
8903
8904
8905
8906
8907
8908
8909
8910
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Vessel dilation
(JISA 1993)
End
Central
Tendency
1,881
2,075
18,809
47,023
94,047
Reproductive -
Sperm effects
(Bellies et al.
1980)
21
High-
End
364
961
3,635
9,088
18,176
30
Central
Tendency
1,274
1,406
12,742
31,855
63,709
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
312
823
3,116
7,790
15,580
30
Central
Tendency
1,092
1,205
10,922
27,304
54,608
Table 4-21. Risk Estimation for Chronic, Cancer Inhalation Exposures for Batch Closed-Loop
Vapor Degreasing
I'lndpninl.
Tumor
Tjpes"
11 K
(risk pei'
ppm)
l'l\posure
1 .c\ el
Worker
No respirator
( anccr K
ON I
No rcspiralor
isk l-lslimalc
Worker
API- 10
s
W orker
API- 25
Worker
API- 50
licnchmark
Cancer
Risk
2.0E-3
High-End
5.9E-5
2.2E-5
5.9E-6
2.4E-6
1.2E-6
10"4
Central
Tendency
1.3E-5
1.2E-5
1.3E-6
5.2E-7
2.6E-7
1 Data from JISA (.1.9931
4.2.2.9 Conveyorized Vapor Degreasing
For conveyorized vapor degreasing, exposure estimates for TWAs of 8 hrs are available based on
modeling with a near-field and far-field approach. EPA calculated 50th and 95th percentiles to
characterize the central tendency and high-end exposure estimates, respectively. EPA used the near-field
air concentrations for worker exposures and the far-field air concentrations for potential ONU inhalation
exposures from PCE conveyorized vapor degreasing as described in more detail above in Section
2.4.1.12. Considering the overall strengths and limitations of the data, EPA's overall confidence in the
occupational inhalation estimates in this scenario is medium. Section 2.4.1.12 describes the justification
for this occupational scenario confidence rating.
Table 4-22. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Conveyorized Vapor
Degreasing
MIX Time
MOI-'.s for
Aculc llxposu
vs
benchmark
Period
Acule
MOI.
I'.ndpoini =
MIX
Kxposurc
W orker
ONI
Worker
Worker
Worker
(= Toial
CNS l-.ITeels1
(ppm)
l.e\el
No rcspiralor
No rcspiralor
API- 10
API- 25
API- 50
I 1)
X-lir
11 iuli-1 nd
2.T.-2
4.0I-.-2
0.3
0.T
I.J
lu
(i
( culial
Tendenc}
(..41 >2
0.1
0.6
l.(»
J. 2
1 Data from Altmann et al. (1990)
Page 348 of 636
-------
8911
8912
8913
8914
8915
8916
8917
8918
8919
8920
8921
8922
8923
8924
8925
8926
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-23. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Conveyorized
Vapor Degreasing
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 10
Worker
APF 25
Worker
APF 50
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
0.1
0.2
1.2
3.1
6.1
100
Central
Tendency
0.3
0.6
2.9
7.3
15
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
4.9E-2
7.3E-2
0.5
1.2
2.5
30
Central
Tendency
0.1
0.2
1.2
2.9
5.9
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
0.7
1.1
7.3
18
37
30
Central
Tendency
1.7
3.3
17
43
87
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
0.5
0.7
4.9
12
25
30
Central
Tendency
1.2
2.3
12
29
59
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
0.4
0.6
4.2
11
21
30
Central
Tendency
1.0
1.9
10
25
50
Table 4-24. Risk Estimation for Chronic, Cancer Inhalation Exposures for Conveyorized Vapor
Degreasing
Endpoint, Tumor
Types1
IUR
(risk per
ppm)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No
respirator
ONU
No
respirator
Worker
APF 10
Worker
APF 25
Worker
APF 50
Cancer Risk
liver tumors
2.0E-3
High-End
3.5E-2
2.3E-2
3.5E-3
1.4E-3
7.0E-4
10"4
Central
Tendency
1.3E-2
7.0E-3
1.3E-3
5.4E-4
2.7E-4
1 Data from JISA (1993)
4.2.2.10 Web Degreasing
For web degreasing, exposure estimates for TWAs of 8 hrs are available based on modeling with a near-
field and far-field approach. EPA calculated 50th and 95th percentiles to characterize the central tendency
and high-end exposure estimates, respectively. EPA used the near-field air concentrations for worker
exposures and the far-field air concentrations for potential ONU inhalation exposures from PCE web
degreasing as described in more detail above in Section 2.4.1.13. Considering the overall strengths and
limitations of the data, EPA's overall confidence in the occupational inhalation estimates in this scenario
is medium. Section 2.4.1.13 describes the justification for this occupational scenario confidence rating.
Page 349 of 636
-------
8927
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-25. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Web Degreasing
HEC Time
Period
Endpoint =
CNS Effects1
Acute
HEC
(ppm)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No respirator
ONU
No respirator
Worker
APF 10
Worker
APF 25
Worker
APF 50
8-hr
5.0
High-End
2.8
4.3
28
69
139
10
Central
Tendency
8.2
16
82
205
409
1 Data from Altmann et al. (1990)
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 10
Worker
APF 25
Worker
APF 50
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
13
19
126
316
632
100
Central
Tendency
37
71
373
932
1,864
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
5.1
7.9
51
128
255
30
Central
Tendency
15
29
151
376
753
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
75
116
754
1,884
3,768
30
Central
Tendency
222
425
2,223
5,557
11,113
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
51
79
510
1,276
2,552
30
Central
Tendency
151
288
1,506
3,764
7,528
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
44
67
438
1,094
2,188
30
Central
Tendency
129
247
1,291
3,226
6,453
Table 4-27. Risk Estimation for Chronic, Cancer Inhalation Exposures for Web Degreasing
Endpoint,
Tumor
Types1
IUR
(risk
per
ppm)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No
respirator
ONU
No
respirator
Worker
APF 10
Worker
APF 25
Worker
APF 50
Cancer
Risk
liver
tumors
2.0E-3
High-End
3.3E-4
2.1E-4
3.3E-05
1.3E-5
6.6E-6
10"4
Central
Tendency
1.1E-4
5.5E-5
1.1E-05
4.2E-6
2.1E-6
8933
8934
1 Data from JISA (1993)
Page 350 of 636
-------
8935
8936
8937
8938
8939
8940
8941
8942
8943
8944
8945
8946
8947
8948
8949
8950
8951
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
4.2.2.11 Cold Cleaning
For cold cleaning, exposure estimates for TWAs of 4 hrs and 8 hrs are available based on personal
monitoring data samples, including 34 data points from two sources. EPA supplemented the identified 8-
hr TWA exposure monitoring data using modeling with a near-field and far-field approach. For 8-hr
TWAs from both monitoring data and modeling, EPA calculated 50th and 95th percentiles to characterize
the central tendency and high-end exposure estimates, respectively. Due to the limited number of data
points for 4-hr TWAs, EPA used the median and maximum to characterize the central tendency and
high-end exposure estimates, respectively. EPA did not identify monitoring data for ONUs; therefore,
EPA used the modeled near-field air concentrations for worker exposures and the modeled far-field air
concentrations for potential ONU inhalation exposures from PCE cold cleaning as described in more
detail above in Section 2.4.1.14. Considering the overall strengths and limitations of the data, EPA's
overall confidence in the occupational inhalation estimates in this scenario is medium to high. Section
2.4.1.14 describes the justification for this occupational scenario confidence rating.
Table 4-28. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Cold Cleaning
MIX Time
Period
l.nripoinl = ( NS
I'llccls1
Aculc
lll(
(ppm)
l'l\|)OMIIV
l.e\el
Worker
No ivs|>ir;ilor
MOI.slor Ac
OM
No rcspimlor
lie llxposi
W orkcr
API- 10
res
W orkcr
API- 25
W orkcr
API- 50
licnchniiirk
\ioi-:
(= loliil I 1)
Based on exposure monitoring data
8-hr
5.0
High-End
1.2
3.(i
EPA did not
identify
monitoring
data for ONUs
12
30
61
10
Central
Tendencs
36
89
179
Based on exposure modeling
8-hr
5.0
High-End
3.3
(..4
33
81
163
10
Central
Tendency
2,086
4,029
20,857
52,142
104,284
1 Data from Altmann et al. (1990)
Page 351 of 636
-------
8952
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-29. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Cold Cleaning
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 10
Worker
APF 25
Worker
APF 50
Based on exposure monitoring data
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
5.5
EPA did
not identify
monitoring
data for
ONUs
55
138
276
100
Central
Tendency
16
163
407
813
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
2.2
22
56
111
30
Central
Tendency
6.6
66
164
329
Liver -
Vessel dilation
(JISA 1993)
31
High-End
33
329
822
1,644
30
Central
Tendency
97
970
2,425
4,849
Reproductive -
Sperm effects
(Bclilcs et al.
1980)
21
High-End
22
223
557
1,114
30
Central
Tendency
66
657
1,643
3,285
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-End
19
191
477
955
30
Central
Tendency
56
563
1,408
2,816
Based on exposure modeling
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
15
29
148
371
741
100
Central
Tendency
9,501
18,354
95,007
237,516
475,033
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
6.0
12
60
150
299
30
Central
Tendency
3,837
7,412
38,368
95,920
191,840
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
88
174
884
2,210
4,420
30
Central
Tendency
56,639
109,419
566,385
1,415,963
2,831,927
Reproductive -
Sperm effects
(Bclilcs et al.
1980)
21
High-
End
60
118
599
1497
2,994
30
Central
Tendency
38,368
74,123
383,680
959,201
1,918,402
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-End
51
101
513
1,283
2,567
30
Central
Tendency
32,887
63,534
328,869
822,172
1,644,345
8953
Page 352 of 636
-------
8954
8955
8956
8957
8958
8959
8960
8961
8962
8963
8964
8965
8966
8967
8968
8969
8970
8971
8972
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-30. Risk Estimation for Chronic. Cancer Inhalation Exposures for Cold Cleaning
I'.ndpoini.
Tumor
T> IK'S1
11 K
(risk per
ppm)
Exposure
l.c\cl
\\ orkcr
No
rcspiralor
Cancel
OM
No
respirator
Risk I 'sl i in a
\\ orkcr
API- 10
(es
Worker
API- 25
Worker
API- 50
licnchniark
Based on exposure monitoring data
Cancer
Risk
liver tumors
2.0E-3
High-End
EPA did
not identify
monitoring
data for
ONUs
9.7E-5
3.9E-5
1.9E-5
10"4
Central
Tendency
2.5 E-4
2.4E-05
1.0E-5
5.1E-6
liased mi exposure modeling
Cancer
Risk
liver tumors
2.0E-3
High-End
2.61 >4
1.31.-4
2.6E-5
1.0E-5
5.2E-6
10"4
Central
Tendency
4 11 :-~
2.1E-7
4.1E-8
1.6E-8
8.1E-9
1 Data from JISA (.1.9931
4.2.2.12 Aerosol Decreasing and Aerosol Lubricants
For aerosol degreasing and aerosol lubricants, exposure estimates for TWAs of 15 mins and 8 hrs are
available based on personal monitoring data samples, including 197 data points from multiple sources.
EPA supplemented the identified exposure monitoring data using modeling with a near-field and far-
field approach to estimate 1- and 8-hr TWAs. For both monitoring data and modeling, EPA calculated
50th and 95th percentiles to characterize the central tendency and high-end exposure estimates,
respectively. EPA did not identify monitoring data for ONUs; therefore, EPA used the modeled near-
field air concentrations for worker exposures and the modeled far-field air concentrations for potential
ONU inhalation exposures from PCE aerosol degreasing and aerosol lubricants as described in more
detail above in Section 2.4.1.15. Considering the overall strengths and limitations of the data, EPA's
overall confidence in the occupational inhalation estimates in this scenario is high. Section 2.4.1.15
describes the justification for this occupational scenario confidence rating
Table 4-31. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Aerosol Degreasing
and Aerosol Lubricants
MIX Time
Period
I'.ndpoini =
CNS r.lTccls1
Acnlc
MIX
(ppm)
Exposure
1 .c\ el
W orkcr
No
respirator
MOI
ONI
No
rcspiralor
!s lor Acnlc 1-1
W orkcr
API- 10-
\posurcs
W orkcr
API- 25;
Worker
API-'50=
licnchmark
MOI.
(= loial I 1)
Based on exposure monitoring data
8-hr
5.0
High-End
0.6
1TA did
ik'I identify
monitoring
data for
ONUs
6.4
16
32
10
Central
Tendency
3.5
35
87
174
I'.asal mi exposure modeling
8-hr
5.0
High-End
0.3
6.8
2.9
"\3
15
10
Central
Tendency
0.9
50
9.1
23
46
1 Data from Altmann et al. (1990)
Page 353 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
8973
8974
8975
8976
2 EPA does not expect routine use of PPE with this exposure scenario.
Table 4-32. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Aerosol
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 101
Worker
APF 251
Worker
APF 501
Based on exposure monitoring data
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
2.9
EPA did
not
identify
monitoring
data for
ONUs
29
73
146
100
Central
Tendency
16
158
396
792
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
1.2
12
30
59
30
Central
Tendency
6.4
64
160
320
Liver -
Vessel dilation
(JISA 1993)
31
High-End
17
175
436
873
30
Central
Tendency
94
944
2,360
4,720
Reproductive -
Sperm effects
(Beliles et al.
1980)
29
High-
End
12
118
296
591
30
Central
Tendency
64
639
1,599
3,197
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
10
101
253
507
30
Central
Tendency
55
548
1,370
2,740
Based on exposure modeling
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
1.3
31
13
33
66
100
Central
Tendency
4.2
260
42
104
208
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
0.5
12
5.4
13
27
30
Central
Tendency
1.7
105
17
42
84
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
7.9
182
79
198
395
30
Central
Tendency
25
1,550
248
620
1,240
Reproductive -
Sperm effects
(Beliles et al.
1980)
29
High-
End
5.4
124
54
134
268
30
Central
Tendency
17
1,050
168
420
840
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
4.6
106
46
115
230
30
Central
Tendency
14
900
144
360
720
8977 1 EPA does not expect routine use of PPE with this exposure scenario.
8978
Page 354 of 636
-------
8979
8980
8981
8982
8983
8984
8985
8986
8987
8988
8989
8990
8991
8992
8993
8994
8995
8996
8997
8998
8999
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-33. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Aerosol Degreasing
and Aerosol Lubricants
Endpoint,
Tumor
Types1
IUR
(risk
per
PPm)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No
respirator
ONU
No respirator
Worker
APF 102
Worker
APF 252
Worker
APF 502
Based on exposure monitoring data
Cancer Risk
liver tumors
2.0E-3
High-End
1.8E-3
EPA did not identify
monitoring data for
ONUs
1.8E-4
7.3E-5
3.6E-5
10"4
Central
Tendency
2.6E-4
2.6E-5
1.0E-5
5.2E-6
Based on exposure modeling
Cancer Risk
liver tumors
2.0E-3
High-End
3.1E-3
1.4E-4
3.14E-4
1.3E-4
6.3E-5
10"4
Central
Tendency
9.4E-4
2.0E-5
9.40E-5
3.8E-5
1.9E-5
1 Data from JISA (1993)
2 EPA does not expect routine use of PPE with this exposure scenario.
4.2.2.13 Dry Cleaning and Spot Cleaning
For dry cleaning, exposure estimates for TWAs of 15 mins and 8 hrs are available based on personal
monitoring data samples, including 31 data points from two sources for post-2006 NESHAP data and
124 data points from multiple sources for fourth and fifth generation machine data. EPA supplemented
the identified 8-hr TWA exposure monitoring data using modeling with a near-field and far-field
approach. For both monitoring data and modeling, EPA calculated 50th and 95th percentiles to
characterize the central tendency and high-end exposure estimates, respectively. The lone exception to
this is for ONU monitoring data where, due to the limited number of data points, EPA used the median
and maximum to characterize the central tendency and high-end exposure estimates, respectively, for
fourth and fifth generation machine data and a single data point for the post-2006 NESHAP data. EPA
used both monitoring data and the modeled far-field air concentrations for potential ONU inhalation
exposures from PCE dry cleaning as described in more detail above in Section 2.4.1.16. Considering the
overall strengths and limitations of the data, EPA's overall confidence in the occupational inhalation
estimates in this scenario is high. Section 2.4.1.16 describes the justification for this occupational
scenario confidence rating.
Page 355 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
9000 Table 4-34. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Dry Cleaning and
9001 Spot Cleaning
HEC Time
Period
Endpoint =
CNS Effects1
Acute
HEC
(ppm)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No respirator
ONU
No respirator
Worker
APF 102
Worker
APF 252
Worker
APF 502
Post-2006 Dry Cleaning (including spot cleaning) - Based on exposure monitoring data
8-hr
5.0
High-End
0.3
143
2.6
6.4
13
10
Central
Tendency
1.4
14
34
69
Post-2006 Dry Cleaning (including spot cleaning) - Based on exposure modeling
12-hr
3.3
High-End
0.1
2.1
1.1
2.8
5.6
10
Central
Tendency
2.4
30
24
59
118
4th/5th Gen Only Dry Cleaning (including spot cleaning) - Based on exposure monitoring data
8-hr
5.0
High-End
0.9
41
8.9
22
45
10
Central
Tendency
5.1
358
51
128
256
9002
9003
9004
9005
9006
9007
1 Data from Altmann et al. (1990)
2 EPA does not expect routine use of PPE with this exposure scenario.
3 ONU exposure data for Post-2006 Dry Cleaning did not distinguish between central tendency and high-end.
Table 4-35. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Dry Cleaning and
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 101
Worker
APF 251
Worker
APF 501
Post-2006 Dry Cleaning (including spot cleaning) - Based on exposure monitoring data
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
1.0
56
10
25
50
100
Central
Tendency
6.1
64
61
152
303
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
0.4
23
4.0
10
20
30
Central
Tendency
2.4
26
24
61
122
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
5.9
334
59
148
297
30
Central
Tendency
36
379
361
903
1,806
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
4.0
226
40
101
201
30
Central
Tendency
24
257
245
612
1,224
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
3.4
194
86
172
34
30
Central
Tendency
21
220
524
1,049
210
Page 356 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 101
Worker
APF 251
Worker
APF 501
Post-2006 Dry Cleaning (including spot cleaning) - Based on exposure modeling
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
0.5
9.5
5.0
12
25
100
Central
Tendency
11
136
105
263
527
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
0.2
3.8
2.0
5.0
10
30
Central
Tendency
4.3
55
43
106
213
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
3.0
56
30
74
148
30
Central
Tendency
63
809
628
1,569
3,139
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
2.0
38
20
50
100
30
Central
Tendency
43
548
425
1,063
2,126
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
1.7
33
17
43
86
30
Central
Tendency
36
470
365
911
1,823
4th/5th Gen Only Dry Cleaning (including spot cleaning) - Based on exposure monitoring data
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
3.5
158
35
87
174
100
Central
Tendency
23
1,582
226
564
1,129
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
1.4
64
14
35
70
30
Central
Tendency
9.1
639
91
228
456
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
21
944
207
518
1,036
30
Central
Tendency
135
9,432
1,346
3,364
6,728
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
14
639
140
351
702
30
Central
Tendency
91
6,389
912
2,279
4,558
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
12
548
120
301
602
30
Central
Tendency
78
5,476
781
1,953
3,907
9008 1 EPA does not expect routine use of PPE with this exposure scenario.
9009
Page 357 of 636
-------
9010
9011
9012
9013
9014
9015
9016
9017
9018
9019
9020
9021
9022
9023
9024
9025
9026
9027
9028
9029
9030
9031
9032
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-36. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Dry Cleaning and
Spot Cleaning
Endpoint,
Tumor Types1
IUR
(risk per
mg/m3)
Exposure Level
Cancer Risk Estimates
Benchmark
Worker
No
respirator
ONU
No
respirator
Worker
APF 102
Worker
APF 252
Worker
APF 502
Post-2006 Dry Cleaning (including spot cleaning) - Based on exposure monitoring data
Cancer Risk
liver tumors
2.0E-3
High-End
5.4E-3
9.5E-5
5.4E-4
2.1E-4
1.1E-4
10"4
Central Tendency
6.8E-4
6.5E-5
6.8E-5
2.7E-5
1.4E-5
Post-2006 Dry Cleaning (including spot cleaning) - Based on exposure modeling
Cancer Risk
liver tumors
2.0E-3
High-End
8.1E-3
4.3E-4
8.1E-4
3.3E-4
1.6E-4
10"4
Central Tendency
3.8E-4
2.9E-5
3.8E-5
1.5E-5
7.6E-6
4th/5th Gen Only Dry Cleaning (including spot cleaning) - Based on exposure monitoring data
Cancer Risk
liver tumors
2.0E-3
High-End
1.5E-3
3.4E-5
1.5E-4
6.1E-5
3.1E-5
10"4
Central Tendency
1.8E-4
2.6E-6
1.8E-5
7.3E-6
3.7E-6
1 Data from JISA (1993)
2 EPA does not expect routine use of PPE with this exposure scenario.
4.2.2.14 Adhesives, Sealants, Paints, and Coatings
For adhesives, sealants, paints, and coatings, exposure estimates for TWAs of 15 mins and 8 hrs are
available based on personal monitoring data samples, including 13 data points from one source for
adhesives/sealants and 20 data points from multiple sources. For adhesives/sealants, discrete data points
were not available; therefore, EPA used the mean and maximum reported in the study to characterize the
central tendency and high-end, respectively. For 8-hr TWAs for paints/coatings, EPA calculated 50th and
95th percentiles to characterize the central tendency and high-end exposure estimates, respectively. Due
to the limited number of data points for 15-min TWAs, EPA used the median and maximum to
characterize the central tendency and high-end exposure estimates, respectively. EPA has not identified
reasonably available data on potential ONU inhalation exposures from PCE adhesives, sealants, paints,
and coatings. ONU inhalation exposures are expected to be lower than worker inhalation exposures
however the relative exposure of ONUs to workers cannot be quantified as described in more detail
above in Section 2.4.1.17. In lieu of data, EPA uses worker central tendency values as a surrogate to
estimate risks for ONUs. Considering the overall strengths and limitations of the data, EPA's overall
confidence in the occupational inhalation estimates in this scenario is medium for workers and low for
ONUs. Section 2.4.1.17 describes the justification for this occupational scenario confidence rating.
Page 358 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
9033 Table 4-37. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Adhesives, Sealants,
9034 Paints, and Coatings
HEC Time
Period
Endpoint = CNS
Effects1
Acute HEC
(ppm)
Exposure Level
MOEs for Acute Exposures
Benchmark MOE
(= Total UF)
Worker
No respirator
ONU
No
respirator2
Worker
APF 10
Worker
APF 25
Worker
APF 50
Paints/Coatings
8-hr
5.0
High-End
1.1
21
11
27
55
10
Central
Tendency
21
214
536
1,071
Adhesives
8-hr
5.0
High-End
6.2
57
62
154
308
10
Central
Tendency
57
565
1,413
2,825
9035
9036
9037
9038
9039
9040
1 Data from Altmann et al. (1990)
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-38. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Adhesives,
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 10
Worker
APF 25
Worker
APF 50
Paints/Coatings
CNS -
Visual effects
(U.S. EPA 2012c)
5.2
High-
End
5.0
98
50
125
250
100
Central
Tendency
98
976
2,440
4,881
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
2.0
39
20
50
101
30
Central
Tendency
39
394
986
1,971
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
30
582
298
744
1,489
30
Central
Tendency
582
5,819
14,548
29,096
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
20
394
202
504
1,009
30
Central
Tendency
394
3,942
9,855
19,710
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
17
338
173
432
864
30
Central
Tendency
338
3,379
8,447
16,894
Adhesives
CNS -
5.2
High- 28
257
281
702
1,404
100
Page 359 of 636
-------
9041
9042
9043
9044
9045
9046
9047
9048
9049
9050
9051
9052
9053
9054
9055
9056
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
l-'.nd ixiiiil
Chronic
NIC
(ppni)
Exposure
1 .e\ el
\\ orker
No
respiralor
MOI-'.s lor
ONI
No
respirator1
Chronic l'.\
\\ orker
API- 10
posurc
\\ orker
API- 25
\\ orker
API- 50
lienchmark
MOI.
(= l oial I 1)
\ isiiiil effects
1 lid
Central
Tendency
257
2,574
6,434
12,868
Kidney -
Histopathology
OISA 1993)
2.1
High-
End
II
104
113
283
567
30
Central
Tendency
104
1,039
2,598
5,197
Liver -
Vessel dilation
~ISA 1993)
31
High-
End
167
1,534
1,674
4,184
8,369
30
Central
Tendency
1,534
15,343
38,358
76,716
Reproductive -
Sperm effects
ffieliles et al.
1980)
21
High-
End
113
1,039
1,134
2,835
5,669
30
Central
Tendency
1,039
10,394
25,984
51,969
Developmental -
Mortality/
CNS effects
("Tinston 1994)
18
High-
End
97
891
972
2,430
4,859
30
Central
Tendency
891
8,909
22,272
44,545
1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-39. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Adhesives, Sealants,
Paints, and Coatings
11 K
Cancer Risk I'.slimales
(risk
Worker
ONI
I'lndpoini. Tumor
per
No
No
Worker
W orker
Worker
Tjpes"
ppni)
Exposure l.e\el
respiralor
respiraloi"
API- 10
API- 25
API- 50
licnchmark
Paints/Coalings
High-End
I.II.-3
1.1 E-4
4.3E-5
2.1E-5
Cancer Risk
2.0E-3
Central
Tendency
4.2E-5
4.2E-5
4.2E-6
1.7E-6
8.5E-7
10"4
Adhesives
High-End
i.'m:-4
1.9E-5
7.6E-6
3.8E-6
Cancer Risk
2.0E-3
Central
Tendency
1.6E-5
1.6E-5
1.6E-6
6.4E-7
3.2E-7
10"4
1 Data from JISA (.1.9931
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
4.2.2.15 Maskant for Chemical Milling
For maskant for chemical milling, exposure estimates for TWAs of 15 mins, 4 hrs, and 8 hrs are
available based on personal monitoring data samples, including 53 data points from two sources. EPA
calculated 50th and 95th percentiles to characterize the central tendency and high-end exposure estimates,
respectively. EPA has not identified reasonably available data on potential ONU inhalation exposures
from PCE maskants for chemical milling. ONU inhalation exposures are expected to be lower than
worker inhalation exposures however the relative exposure of ONUs to workers cannot be quantified as
described in more detail above in Section 2.4.1.18. In lieu of data, EPA uses worker central tendency
Page 360 of 636
-------
9057
9058
9059
9060
9061
9062
9063
9064
9065
9066
9067
9068
9069
9070
9071
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
values as a surrogate to estimate risks for ONUs. Considering the overall strengths and limitations of the
data, EPA's overall confidence in the occupational inhalation estimates in this scenario is medium to
high for workers and low for ONUs. Section 2.4.1.18 describes the justification for this occupational
scenario confidence rating.
Table 4-40. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Maskant for
Chemical Milling
HEC Time Period
Endpoint = CNS
Effects1
Acute
HEC
(ppm)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No respirator
ONU
No respirator2
Worker
APF 10
Worker
APF 25
Worker
APF 50
8-hr
5.0
High-End
2.4
4.1
24
59
119
10
Central
Tendency
4.1
41
103
206
1 Data from Altmann et al. (1990)
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-41. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Maskant for
Chemical Milling
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 10
Worker
APF 25
Worker
APF 50
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
11
19
108
271
541
100
Central
Tendency
19
188
470
939
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
4.4
7.6
44
109
219
30
Central
Tendency
7.6
76
190
379
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
65
112
645
1,614
3,227
30
Central
Tendency
112
1,120
2,800
5,601
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
44
76
437
1,093
2,186
30
Central
Tendency
76
759
1,897
3,794
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
37
65
375
937
1,874
30
Central
Tendency
65
650
1,626
3,252
1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Page 361 of 636
-------
9072
9073
9074
9075
9076
9077
9078
9079
9080
9081
9082
9083
9084
9085
9086
9087
9088
9089
9090
9091
9092
9093
9094
9095
9096
9097
9098
9099
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-42. Risk Estimation for Chronic, Cancer Inhalation Exposures for Maskant for Chemical
Milling
11 K
( aneer Risk llsliiiiales
(risk
OM
l-'udpitinl. Tumor
per
l-lxposurc
\\ orker
No
Worker
W orker
Worker
Tjpes"
ppm)
l.e\el
No rcspiralor
respiralor
API- 10
API- 25
API- 50
licnchmark
High-Liid
4.') 1.-4
4.9L-5
2.0L-5
9.9L-0
Cancer Risk
2.0E-3
Central
Tendency
2.21.-4
2.21.-4
2.2E-5
8.8E-6
4.4E-6
10"4
1 Data from JISA (.1.9931
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
4.2.2.16 Industrial Processing Aid
For industrial processing aid, exposure estimates TWAs of 30 mins and 8 hrs are available based on
personal monitoring data samples, including 91 data points from multiple sources. For 8-hr TWAs, EPA
calculated 50th and 95th percentiles to characterize the central tendency and high-end exposure estimates,
respectively. Due to the limited number of data points, EPA used the median and maximum to
characterize the central tendency and high-end exposure estimates for the 30-min TWA. EPA has not
identified reasonably available data on potential ONU inhalation exposures from PCE industrial
processing aids. ONU inhalation exposures are expected to be lower than worker inhalation exposures
however the relative exposure of ONUs to workers cannot be quantified as described in more detail
above in Section 2.4.1.19. In lieu of data, EPA uses worker central tendency values as a surrogate to
estimate risks for ONUs. Considering the overall strengths and limitations of the data, EPA's overall
confidence in the occupational inhalation estimates in this scenario is medium for workers and low for
ONUs. Section 2.4.1.19 describes the justification for this occupational scenario confidence rating.
Table 4-43. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Industrial
Processing Aid
MIX l ime Period
I'lnripoim = CNS
l-llccls'
Acule
MIX
(ppm)
l-lxposurc l.c\cl
W orker
No
rcspiralor
MOI-'.s
ONI
No
respiralor
or Acule l-'.\
Worker
API- 10
)osurcs
W orker
API- 25
Worker
API- 50
licnchmark
MOI.
(= loial I 1)
8-hr
5.0
High-End
4.2
83
42
106
212
10
Central
Tendency
83
833
2,083
4,167
1 Data from Altmann et al. (1990)
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-44. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Industrial
Processing Aid i
I'lndpoinl
Chronic
MIX
(ppm)
l-lxposurc
1 .c\ el
W orker
No
rcspiralor
MOI-'.s lor
ONI
No
respirator1
Chronic l-'.x
W orker
API- 10
|)osurc
Worker
API- 25
Worker
API- 50
licnchmark
MOI.
(= Tolal
I 1)
CNS -
5.2
High-
19
380
193
483
965
100
Page 362 of 636
-------
9100
9101
9102
9103
9104
9105
9106
9107
9108
9109
9110
9111
9112
9113
9114
9115
9116
9117
9118
9119
9120
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Visual effects
(U.S. EPA
2012c)
End
Central
Tendencs
380
3,796
9,490
18,980
Kidney -
Histopathology
OISA 1993)
2.1
High-
End
"'.X
153
78
195
390
30
Central
Tendency
153
1,533
3,833
7,665
Liver -
Vessel dilation
~ISA 1993)
31
High-
End
115
2,263
1,151
2,877
5,753
30
Central
Tendency
2,263
22,630
56,575
113,150
Reproductive -
Sperm effects
ffieliles et al.
1980)
21
High-
End
78
1,533
779
1,949
3,897
30
Central
Tendency
1,533
15,330
38,325
76,650
Developmental -
Mortality/
CNS effects
("Tinston 1994)
18
High-
End
67
1,314
668
1,670
3,341
30
Central
Tendency
1,314
13,140
32,850
65,700
1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a surrogate
to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-45. Risk Estimation for Chronic, Cancer Inhalation Exposures for Industrial Processing
Aid
11 K
( ancer Risk llslimales
(risk
Worker
<)M
l-lndpoinl. Tumor
per
l'l\posure
No
No
Worker
Worker
W orker
Tjpes"
ppm)
l.e\el
respiralor
respiralor
API- 10
API- 25
API- 50
benchmark
1 liuh-l !nd
2.Si:-4
: si :-5
i ii:-5
5 51:-(.
Cancer Risk
2.0E-3
Central
Tendency
1.1E-5
1.1E-5
1.1E-6
4.4E-7
2.2E-7
io-4
1 Data from JISA (.1.9931
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
4.2.2.17 Metalworking Fluids
For metalworking fluids, exposure estimates for TWAs of 8 hrs are available based on estimates from
the Emission Scenario Document (ESD) on the Use of Metalworking Fluids (OE ). EPA uses
the geometric mean and 90th percentile as presented in the ESD to characterize the central tendency and
high-end exposure estimates, respectively. EPA has not identified reasonably available data on potential
ONU inhalation exposures from PCE metalworking fluids. ONU inhalation exposures are expected to be
lower than worker inhalation exposures however the relative exposure of ONUs to workers cannot be
quantified as described in more detail above in Section 2.4.1.20. In lieu of data, EPA uses worker central
tendency values as a surrogate to estimate risks for ONUs. Considering the overall strengths and
limitations of the data, EPA's overall confidence in the occupational inhalation estimates in this scenario
is medium for workers and low for ONUs. Section 2.4.1.20 describes the justification for this
occupational scenario confidence rating.
Page 363 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
9121 Table 4-46. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Metalworking
9122 Fluids
MIX Time Period
l.ndpoinl = ( NS
i-nwis1
Aciile
MIX
ippni)
I'Aposiirc l.c\cl
\\ orkcr
No
rcspiralor
MOI-'.s for A
ONI
No
respiralor
culc l-'.\p
Worker
API III'
ISIII'CS
Worker
API 25'
W orkcr
API 50'
licnchmark
moi:
(= Tolal I I )
8-hr
5.U
1 liuh-l !nd
869
:.^s_
.VK.X
1 I.T,"
lu
Central Tendency
869
8,692
21,731
43,462
9123 1 Data from Altmann et al. (1990)
9124 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
9125 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
9126 3 EPA does not assume routine use of PPE with this exposure scenario.
9127
9128 Table 4-47. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Metalworking
9129 Fluids
Kndpoinl
Chronic
MIX
(ppm)
l-'.\posurc
1 .e\ el
W orkcr
No
rcspiralor
MOI-'.s for
ONI
No
respiralor1
Chronic !¦'.>
W orkcr
API- I0:
posurc
Worker
API- 25;
Worker
API-" 50-
licnchmark
MOI.
(= Tolal
I 1)
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
1,087
3,960
10,875
27,187
54,374
100
Central
Tendency
3,960
39,595
98,988
197,976
Kidney -
Histopathology
(USA 1993)
2.1
High-
End
439
1,599
4,392
10,979
21,959
30
Central
Tendency
1,599
15,990
39,976
79,952
Liver -
Vessel dilation
(USA 1993)
31
High-
End
6,483
23,605
64,830
162,075
324,151
30
Central
Tendency
23,605
236,048
590,121
1,180,242
Reproductive -
Sperm effects
(Bellies et al.
1980)
21
High-
End
4,392
15,990
43,917
109,793
219,586
30
Central
Tendency
15,990
159,904
399,759
799,518
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
3,764
13,706
37,643
94,108
188,217
30
Central
Tendency
13,706
137,060
342,651
685,302
9130 1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
9131 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
9132 2 EPA does not expect routine use of PPE with this exposure scenario.
9133
Page 364 of 636
-------
9134
9135
9136
9137
9138
9139
9140
9141
9142
9143
9144
9145
9146
9147
9148
9149
9150
9151
9152
9153
9154
9155
9156
9157
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-48 Risk Estimation for Chronic. Cnnccr Tnhnlntion Exposures for Metnlworking Fluids
linripoinl.
Tumor
T\ pes'
11 K
(risk per
ppm)
l-lxposure
l.c\cl
\\ orker
No
respirator
(a
()\l
No
rcspiralor
nccr Risk l-lsli
Worker
API- 10'
males
\\ orker
API- 25'
Worker
API 50'
benchmark
Cancer
Risk
liver tumors
2.0E-3
High-End
4.9E-6
1.0E-6
4.9E-7
2.0E-7
9.8E-8
10"4
Central
Tendency
1.0E-6
1.0E-7
4.2E-8
2.1E-8
1 Data from JISA (.1.9931
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
3 EPA does not expect routine use of PPE with this exposure scenario.
4.2.2.18 Wipe Cleaning and Metal/Stone Polishes
For wipe cleaning and metal/stone polishes, exposure estimates for TWAs of 15 mins, 4 hrs, and 8 hrs
are available based on personal monitoring data samples, including 20 data points from two sources. For
8-hr TWAs for ONUs and 15-min TWAs for workers, EPA uses the 50th and 95th percentiles to
characterize the central tendency and high-end exposure estimates, respectively. Due to the limited
number of data points, EPA used the median and maximum to characterize the central tendency and
high-end exposure estimates, respectively, for worker 8-hr TWAs. The 4-hr TWA estimates are based
on a single data point. EPA identified 6 of the 20 data points to be for ONU exposures for wipe cleaning
as described in more detail above in Section 2.4.1.21. Considering the overall strengths and limitations
of the data, EPA's overall confidence in the occupational inhalation estimates in this scenario is medium.
Section 2.4.1.21 describes the justification for this occupational scenario confidence rating.
Table 4-49. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Wipe Cleaning and
Metal/Stone Polishes
MIX Time
Period
I'lnripoinl =
CNS I!Heels'
Aeule
MIX
(ppm)
l-lxposurc l.e\el
Worker
No
respiralor
\ior.s
ONI
No
respiralor
'or Aeule l'.\
W orker
API- 10-
>osiires
Worker
API- 25;
W orker
API 50-
benchmark
MOI.
(= loial I 1)
8-hr
5 u
1 liuh-l !nd
2.21.-2
0.2
0.2
0.5
l.l
10
Central Tendency
j.xi:-2
0.4
0.')
i.y
1 Data from Altmann et al. (1990)
2 EPA does not expect routine use of PPE with this exposure scenario
Table 4-50. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Wipe Cleaning
and Metal/Stone Polishes
I'lmlpoini
Chronic
MIX
(ppm)
I'lxposiii'e
1 .e\ el
W orker
No
rcspiralor
MOI
ONI
No
rcspiralor
-Is lor Chronic
Worker
API- 10'
l-lxposurc
Worker
API 25'
W orker
API- 50'
lienchinark
MOI!
(= Toial
1 1 )
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
0.1
1.0
1.0
2.5
5.0
100
Central
Tendency
0.2
1 ,t)4'
IS
4.3
X.(.
Kidney -
Histopathology
2.1
High-
End
4.0i:-2
0.4
0.4
1.0
2.0
30
Page 365 of 636
-------
9158
9159
9160
9161
9162
9163
9164
9165
9166
9167
9168
9169
9170
9171
9172
9173
9174
9175
9176
9177
9178
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
(JISA 1993)
Central
Tendency
¦\or.-2
4:1
0.T
\.->
3.5
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
».(.
5.«)
(..0
15
}<)
30
Central
Tendency
1.0
10
2(.
51
Reproductive -
Sperm effects
(Bellies et al.
1980)
21
High-
End
0.4
4.0
4.0
10
20
30
Central
Tendency
0.7
4.2 n
¦'.O
r
35
Developmental -
Mortality/
CNS effects
(Huston 1994)
18
High-
End
0.3
3.4
3.5
X.(.
r
30
Central
Tendency
0.(.
v(.| 1
(..0
15
1 EPA does not expect routine use of PPE with this exposure scenario
Table 4-51. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Wipe Cleaning and
Metal/Stone Polishes
11 K
Cancel
Risk l-lslimalcs
r.ndpoinl.
(risk
Tumor
per
l'l\pusurc
Worker
ON I
\\ orkcr
\\ orkcr
\\ orkcr
Tjpes"
ppm)
l.c\cl
No rcspiralor
No rcspiralor
API- 10-
API- 25:
API- 50-
licnchmark
1 liuh-l nd
5.31.-2
5.41.-3
5.31.-3
2.II.-3
I.II.-3
Cancer Risk
2 ni:-;
( enlial
Tcndcncv
2.41.-2
4 r Aculc l.\
Worker
API- 10*
)osurcs
W orkcr
API- 25*
W orkcr
API- 50*
licnchmark
MOI.
(= lolal I 1)
8-hr
5.0
High-End
22
167
217
542
1,084
10
Central
Tendency
29
291
727
1,455
1 Data from Altmann et al. (1990)
2 ONU exposure data did not distinguish central tendency and high-end.
Page 366 of 636
-------
9179
9180
9181
9182
9183
9184
9185
9186
9187
9188
9189
9190
9191
9192
9193
9194
9195
9196
9197
9198
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
3 EPA does not expect routine use of PPE with this exposure scenario.
Table 4-53. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Other Spot
Cleaning/Spot Removers (Including Carpet Cleaning) i
l-liid ixiinl
Chronic
MIX
(ppni)
l-lxposure
1 .e\ el
Worker
No
respiralor
MOHs for Chi
OM 1
No
respiralor
onic l-'.\po
W orker
API-
10-
¦ill IV
Worker
API-
25:
W orker
API-
50;
benchmark
\ioi-:
(= Toial
1 1 )
CNS-
Visual effects
(IIS. EPA
2012c)
5.2
11 iuli-1 iid
')')
759
<>X"
:.4(.s
4.T,(,
100
Central
Tendency
133
1,325
3,313
6,627
Kidney -
Histopathology
OISA 1993)
2.1
High-End
40
307
399
997
1,993
30
Central
Tendency
54
535
1,338
2,676
Liver -
Vessel dilation
~ISA 1993)
31
High-End
588
4,526
5,885
14,712
29,424
30
Central
Tendency
790
7,901
19,752
39,504
Reproductive -
Sperm effects
ffieliles et al.
1980)
21
High-End
399
3,066
3,986
9,966
19,932
30
Central
Tendency
535
5,352
13,381
26,761
Developmental -
Mortality/
CNS effects
("Tinston 1994)
18
High-End
342
2,628
3,417
8,542
17,085
30
Central
Tendency
459
4,588
11,469
22,938
1 ONU exposure data did not distinguish central tendency and high-end
2 EPA does not expect routine use of PPE with this exposure scenario.
Table 4-54. of Risk Estimation for Chronic, Cancer Inhalation Exposures for Other Spot
Cleaning/Spot I
tern overs
Including Carpet Cleaning)
Indpoinl.
Tumor T\ pes'
11 K
(risk per
ppm)
l-lxposure
1 .e\ el
Worker
No
respiralor
Cancer
ONI
No
respirator
tisk r.slim
W orker
API-
10-
lies
Worker
API-
25:
Worker
API-
5»-
licnchmark
Cancer Risk
2.0E-3
High-End
5.4E-5
7.0E-6
5.4E-6
2.2E-6
1.1E-6
10"4
Central
Tendency
3.1E-5
5.4E-6
3.1E-6
1.2E-6
6.2E-7
1 Data from JISA (.1.9931
2 EPA does not expect routine use of PPE with this exposure scenario.
4.2.2.20 Other Industrial Uses
For other industrial uses, exposure estimates for TWAs of 30 mins, 1 hrs, and 8 hrs are available based
on modeling. EPA characterized the central tendency exposure estimates assuming unloading/loading of
a tank truck and the high-end assuming unloading/loading of a railcar. EPA has not identified reasonably
available data on potential ONU inhalation exposures from other industrial uses. ONU inhalation
exposures are expected to be lower than worker inhalation exposures however the relative exposure of
ONUs to workers cannot be quantified as described in more detail above in Section 2.4.1.23. In lieu of
data, EPA uses worker central tendency values as a surrogate to estimate risks for ONUs. Considering
the overall strengths and limitations of the data, EPA's overall confidence in the occupational inhalation
Page 367 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
9199 estimates in this scenario is medium for workers and low for ONUs. Section 2.4.1.23 describes the
9200 justification for this occupational scenario confidence rating.
9201
9202 Table 4-55. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Other Industrial
9203 Uses
MIX Time Period
l-'udpitin 1 = ( NS
r.riwis1
Acule
MIX
(ppm)
l''.\poslll'C
l.e\el
M
\\ orker
No respiralor
Oils lor Acule 1
ON I
No respiralor
Ixposiliv
\\ orker
API- 10
s
Worker
API- 25
Worker
API- 50
licnchmark
\ioi-:
(= Toliil I 1)
8-hr
5.0
High-End
139
628
1,390
3,475
6,949
10
Central
Tendency
628
6,284
15,710
31,419
9204 1 Data from Altmann et al. (1990)
9205 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
9206 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
9207
9208 Table 4-56. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Other Industrial
9209 Uses
I'lnripoini
('limine
MIX
(ppm)
l''.\posure
1 .e\ el
MOI'.s lor Chronic I'.xposure
licnchmark
MOI.
(= Tolal
I 1)
Worker
No
respiralor
ONI
No
respirator1
W orker
API- 10
W orker
API- 25
Worker
API- 50
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-End
633
2,862
6,331
15,828
31,656
100
Central
Tendency
2,862
28,624
71,560
143,120
Kidney -
Histopathology
OISA 1993)
2.1
High-End
256
1,156
2,557
6,392
12,784
30
Central
Tendency
1,156
11,560
28,899
57,798
Liver -
Vessel dilation
(JIS A 1993)
31
High-End
3,774
17,064
37,743
94,358
188,716
30
Central
Tendency
17,064
170,643
426,608
853,216
Reproductive -
Sperm effects
(Bellies et al.
1980)
21
High-End
2,557
11,560
25,568
63,920
127,840
30
Central
Tendency
11,560
115,597
288,992
577,985
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-End
2,192
9,908
21,915
54,788
109,577
30
Central
Tendency
9,908
99,083
247,708
495,416
9210 1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
9211 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
9212
9213
Page 368 of 636
-------
9214
9215
9216
9217
9218
9219
9220
9221
9222
9223
9224
9225
9226
9227
9228
9229
9230
9231
9232
9233
9234
9235
9236
9237
9238
9239
9240
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-57. H
.isk Estimation for Chronic. Cancer Inhalation Exposures for Other Tndusi
trial Uses
l.ndpoinl.
Tumor T\ pes'
IUR
(risk per
ppni)
I'Aposlll'C
1 .c\ el
Worker
No respirator
Cancer Risk
()\l
No respirator
I'.sliinales
Worker
API- 10
W orkcr
API- 25
Worker
API- 50
licnchmark
Cancer Risk
2.0E-3
lligh-Lnd
S.4L-0
1.4E-6
S.4L-"
3.4L-"
1.7E-7
10"4
Central
Tendency
1.4E-6
1.4E-7
5.8E-8
2.9E-8
1 Data from JISA (.1.9931
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
4.2.2.21 Other Commercial Uses
For other commercial uses, exposure estimates for TWAs of 15 mins and 8 hrs are available based on
personal monitoring data samples, including 24 data points for printing applications, 3 data points for
photocopying, and 102 data points for photographic film applications. Exposure estimates for mold
release products are based on area monitoring data samples, including 4 data points from one source.
EPA calculated the 50th and 95th percentiles to characterize the central tendency and high-end exposure
estimates, respectively, for 8-hr TWAs for printing applications and 15-min and 8-hr TWAs for
photographic film applications. Due to the limited number of data points, EPA used the median and
maximum to characterize the central tendency and high-end exposure estimates, respectively,
photocopying. The 15-min TWA exposure estimates for printing applications is based on a single data
point. For mold release products, discrete data points were not available; therefore, EPA used the mean
and maximum reported in the study to characterize the central tendency and high-end, respectively. EPA
has not identified reasonably available data on potential ONU inhalation exposures from other
commercial uses. ONU inhalation exposures are expected to be lower than worker inhalation exposures
however the relative exposure of ONUs to workers cannot be quantified as described in more detail
above in Section 2.4.1.24. In lieu of data, EPA uses worker central tendency values as a surrogate to
estimate risks for ONUs. Considering the overall strengths and limitations of the data, EPA's overall
confidence in the occupational inhalation estimates in this scenario is medium to high for printing,
photographic film, and photocopying workers, medium for mold release workers, and low for ONUs.
Section 2.4.1.24 describes the justification for this occupational scenario confidence rating.
Table 4-58. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Other Commercial
Uses
MIX l ime Period
I'.ndpoini = CNS
Tiled s1
Acute
MIX
(ppni)
l-lxposiirc
l.c\cl
Worker
No respirator
MOI-'.s lo
ONI
No respirator
• Acule l.\po>
Worker
API- 10*
ii res
W orkcr
API- 25*
Worker
API- 50'
licnchmark
MOT.
(= Total
I 1)
Printing
8-hr
5.0
High-End
0.8
2.(i
8.4
21
42
10
Central
Tendency
2.(i
:<•
65
130
Photocopying
8-hr
5.0
High-End
10,000
26,667
100,000
250,000
500,000
10
Central
Tendency
26,667
266,667
666,667
1,333,333
Page 369 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HEC Time Period
Endpoint = CNS
Effects1
Acute
HEC
(ppm)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total
UF)
Worker
No respirator
ONU
No respirator2
Worker
APF 103
Worker
APF 253
Worker
APF 503
Photographic Film
8-hr
5.0
High-End
8.9E-2
0.8
0.9
2.2
4.4
10
Central
Tendency
0.8
7.9
20
40
Mold Release
8-hr
5.0
High-End
25
50
250
625
1,250
10
Central
Tendency
50
500
1,250
2,500
9241 1 Data from Altmann et al. (1990)
9242 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
9243 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
9244 3 EPA does not expect routine use of PPE with this exposure scenario (including all sub-scenarios).
9245
9246 Table 4-59. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Other
9247 Commercial Uses
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 102
Worker
APF 252
Worker
APF 502
Printing
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
3.8
12
38
96
192
100
Central
Tendency
12
119
297
594
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
1.5
4.8
15
39
77
30
Central
Tendency
4.8
48
120
240
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
23
71
228
571
1,142
30
Central
Tendency
71
708
1,770
3,541
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
15
48
155
387
774
30
Central
Tendency
48
480
1,199
2,399
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
13
41
133
332
663
30
Central
Tendency
41
411
1,028
2,056
Photocopying
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
45,552
121,472
455,520
1,138,800
2,277,600
100
Central
Tendency
121,472
1,214,720
3,036,800
6,073,600
Kidney -
Histopathology
2.1
High-
End
18,396
49,056
183,960
459,900
919,800
30
Page 370 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 102
Worker
APF 252
Worker
APF 502
(JISA 1993)
Central
Tendency
49,056
490,560
1,226,400
2,452,800
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
271,560
724,160
2,715,600
6,789,000
13,578,000
30
Central
Tendency
724,160
7,241,600
18,104,000
36,208,000
Reproductive -
Sperm effects
(Bclilcs et al.
1980)
21
High-
End
183,960
490,560
1,839,600
4,599,000
9,198,000
30
Central
Tendency
490,560
4,905,600
12,264,000
24,528,000
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
157,680
420,480
1,576,800
3,942,000
7,884,000
30
Central
Tendency
420,480
4,204,800
10,512,000
21,024,000
Photographic Film
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-End
0.4
3.6
4.0
10
20
100
Central
Tendency
3.6
36
90
181
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
0.2
1.5
1.6
4.1
8.2
30
Central
Tendency
1.5
15
37
73
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
2.4
22
24
60
120
30
Central
Tendency
22
216
539
1,079
Reproductive -
Sperm effects
(Bclilcs et al.
1980)
21
High-
End
1.6
15
16
41
82
30
Central
Tendency
15
146
365
731
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
1.4
13
14
35
70
30
Central
Tendency
13
125
313
626
Mold Release
CNS -
Visual effects
(U.S. EPA
2012c)
5.2
High-
End
114
228
1,139
2,847
5,694
100
Central
Tendency
228
2,278
5,694
11,388
Kidney -
Histopathology
(JISA 1993)"
2.1
High-
End
46
92
460
1,150
2,300
30
Central
Tendency
92
920
2,300
4,599
Liver -
Vessel dilation
(JISA 1993)
31
High-
End
679
1,358
6,789
16,973
33,945
30
Central
Tendency
1,358
13,578
33,945
67,890
Page 371 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Endpoint
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 102
Worker
APF 252
Worker
APF 502
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-
End
460
920
4,599
11,498
22,995
30
Central
Tendency
920
9,198
22,995
45,990
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-
End
394
788
3,942
9,855
19,710
30
Central
Tendency
788
7,884
19,710
39,420
9248 1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a surrogate
9249 to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
9250 2 EPA does not expect routine use of PPE with this exposure scenario (including all sub-scenarios).
9251
9252 Table 4-60. Risk Estimation for Chronic, Cancer Inhalation Exposures for Other Commercial
9253 Uses
Endpoint,
Tumor Types1
IUR
(risk per
ppm)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No
respirator
ONU
No
respirator2
Worker
APF 103
Worker
APF 253
Worker
APF 503
Printing
Cancer Risk
2.0E-3
High-End
1.4E-3
3.5E-4
1.4E-4
5.6E-5
2.8E-5
10"4
Central
Tendency
3.5E-4
3.5E-5
1.4E-5
7.0E-6
Photocopying
Cancer Risk
02.0E-3
High-End
1.2E-7
3.4E-8
1.2E-8
4.7E-9
2.3E-9
10"4
Central
Tendency
3.4E-8
3.4E-9
1.4E-9
6.8E-10
Photographic Film
Cancer Risk
2.0E-3
High-End
1.3E-2
1.1E-3
1.3E-3
5.3E-4
2.6E-4
10"4
Central
Tendency
1.1E-3
1.1E-4
4.6E-5
2.3E-5
Mold Release
Cancer Risk
2.0E-3
High-End
4.7E-5
1.8E-5
4.7E-6
1.9E-6
9.4E-7
10"4
Central
Tendency
1.8E-5
1.8E-6
7.3E-7
3.6E-7
9254 1 Data from JISA (1993)
9255 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
9256 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
925 7 3 EPA does not expect routine use of PPE with this exposure scenario (including all sub-scenarios).
9258 4.2.2.22 Laboratory Chemicals
9259 EPA does not have data to assess worker exposures to PCE during laboratory use. However, due to the
9260 expected safety practices when using chemicals in a laboratory setting, PCE is expected to be applied in
9261 small amounts under a fume hood, thus reducing the potential for inhalation exposures.
Page 372 of 636
-------
9262
9263
9264
9265
9266
9267
9268
9269
9270
9271
9272
9273
9274
9275
9276
9277
9278
9279
9280
9281
9282
9283
9284
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
4.2.2.23 Waste Handling, Disposal, Treatment, and Recycling
For waste handling, disposal, treatment, and recycling, exposure estimates for TWAs of 30 mins, 1 hrs,
and 8 hrs are available based on modeling. EPA characterized the central tendency exposure estimates
assuming unloading/loading of a tank truck and the high-end assuming unloading/loading of a rail car.
EPA has not identified reasonably available data on potential ONU inhalation exposures from waste
handling, disposal, treatment, and recycling. ONU inhalation exposures are expected to be lower than
worker inhalation exposures however the relative exposure of ONUs to workers cannot be quantified as
described in more detail above in Section 2.4.1.26. In lieu of data, EPA uses worker central tendency
values as a surrogate to estimate risks for ONUs. Considering the overall strengths and limitations of the
data, EPA's overall confidence in the occupational inhalation estimates in this scenario is medium for
workers and low for ONUs. Section 2.4.1.26 describes the justification for this occupational scenario
confidence rating.
Table 4-61. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Waste Handling,
Disposal, Treatment, and Recycling
MIX Time
Period
Kndpoinl =
( NS r.nvcis1
Anile
MIX
(ppni)
I'Aposlll'C
1 .c\ el
Worker
No
respirator
\ior.s i
OM
No
rcspiralor
or Aculc l'.\
Worker
API- 10
posures
Worker
API- 25
W orker
API- 50
licnchmark
MOI.
(= Tolal I 1)
8-hr
5.0
High-End
139
628
1,390
3,475
6,949
10
Central
Tendency
628
6,284
15,710
31,419
1 Data from Altmann et al. (1990)
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-62. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Waste Handling,
I'lndpoini1
Chronic
HEC
(ppm)
Exposure
1 .c\ el
Worker
No
rcspiralor
MOI-'.s lor (
ONI
No
respirator1
lironic l-'.\
Worker
API- 10
)osurc
Worker
API- 25
W orker
API- 50
licnchmark
MOI.
(= Total
I 1)
CNS -
Visual effects
(U.S. EPA 2012c)
5.2
High-
End
633
2,862
6,331
15,828
31,656
100
Central
Tendency
2,862
28,624
71,560
143,120
Kidney -
Histopathology
(USA 1993)
2.1
High-
End
256
1,156
2,557
6,392
12,784
30
Central
Tendency
1,156
11,560
28,899
57,798
Liver -
Vessel dilation
(USA 1993)
31
High-
End
3,774
17,064
37,743
94,358
188,716
30
Central
Tendency
17,064
170,643
426,608
853,216
21
High-
3,531
15,963
35,308
88,270
176,540
30
Page 373 of 636
-------
9285
9286
9287
9288
9289
9290
9291
9292
9293
9294
9295
9296
9297
9298
9299
9300
9301
9302
9303
9304
9305
9306
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
l-'.nd ptiini1
Chronic
MIX
(ppm)
I'lxposiiiv
1 .e\ el
Worker
No
respirator
MOI-'.s for (
()\l
No
respirator1
'lironic l-'.\
Worker
API- 10
)osure
Worker
API- 25
W orker
API- 50
lienchmark
MOI.
(= Total
I 1)
Reproductive -
Sperm effects
ffieliles et al.
1980)
End
Central
Tendency
15,963
159,634
399,085
798,170
Developmental -
Mortality/
CNS effects
("Tinston 1994)
18
High-
End
2,557
11,560
25,568
63,920
127,840
30
Central
Tendency
11,560
115,597
288,992
577,985
1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
Table 4-63. Risk Estimation for Chronic, Cancer Inhalation Exposures for Waste Handling,
Disposal, Treatment, and Recycling i
11 K
Cancel' Kisk l-lslimales
(risk
W orker
ONI
I'.ndpoini.
per
No
No
W orker
W orker
Worker
Tumor Tjpes'
ppm)
l-lxposurc l.e\el
rcspiralor
respirator
API 10
API- 25
API- 50
licnchmark
High-End
8.4E-6
8.4E-7
3.4E-7
1.7E-7
Cancer Risk
2.0E-3
Central Tendency
1.4E-6
1.4E-6
1.4E-7
5.8E-8
2.9E-8
10"4
1 Data from JISA (.1.9931
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
4.2.2.24 Other Department of Defense Uses
For other department of defense uses, exposure estimates TWAs of 15 mins, 1 hr, and 8 hrs are available
based on personal monitoring data samples, including 4 data points from multiple sources. For the oil
analysis results exposure results are based on a single data point (one for each TWA duration). For the
water pipe repair, only one data point was available that measured below the LOD; therefore, EPA
characterized the central tendency and high-end exposures as half the LOD and the LOD, respectively.
EPA has not identified reasonably available data on potential ONU inhalation exposures from other
department of defense uses. ONU inhalation exposures are expected to be lower than worker inhalation
exposures however the relative exposure of ONUs to workers cannot be quantified as described in more
detail above in Section 2.4.1.27. In lieu of data, EPA uses worker central tendency values as a surrogate
to estimate risks for ONUs. Considering the overall strengths and limitations of the data, EPA's overall
confidence in the occupational inhalation estimates in this scenario is high for workers and low for
ONUs. Section 2.4.1.27 describes the justification for this occupational scenario confidence rating.
Page 374 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
9307 Table 4-64. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Other Department
9308 of Defense Uses
HEC Time Period
Endpoint = CNS
Effects1
Acute
HEC
(ppm)
Exposure Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator2
Worker
APF 10
Worker
APF 25
Worker
APF 50
Water Pipe Repair
8-hr
5.0
High-End
2.2
4.3
22
54
108
10
Central Tendency
4.3
43
108
216
Oil Analysis3
8-hr
5.0
High-End
5.7
5.7
57
142
284
10
Central Tendency
9309
9310
9311
9312
9313
9314
9315
1 Data from Altmann et al. (1990)
2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
3 Oil analysis exposure data did not distinguish between central tendency and high-end.
Table 4-65. Risk Estimation for Chronic, Non-Cancer Inhalation Exposures for Other
Endpoint1
Chronic
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No
respirator
ONU
No
respirator1
Worker
APF 10
Worker
APF 25
Worker
APF 50
Water Pipe Repair
CNS -
Visual effects
(U.S. EPA 2012c)
5.2
High-End
68
164
684
1,710
3,420
100
Central
Tendency
164
1,642
4,104
8,208
Kidney -
Histopathology
(JISA 1993)"
2.1
High-End
28
66
276
691
1,381
30
Central
Tendency
66
663
1,657
3,315
Liver -
Vessel dilation
(JISA 1993)
31
High-End
408
979
4,077
10,194
20,387
30
Central
Tendency
979
9,786
24,465
48,930
Reproductive -
Sperm effects
(Beliles et al.
1980)
21
High-End
276
633
2,762
6,905
13,811
30
Central
Tendency
663
6,629
16,573
33,146
Developmental -
Mortality/
CNS effects
(Tinston 1994)
18
High-End
237
568
2,368
5,919
11,838
30
Central
Tendency
568
5,682
14,205
28,411
Oil Analysis
CNS -
Visual effects
(U.S. EPA 2012c)
5.2
High-End
43
52
431
1,077
2,154
100
Central
Tendency
52
517
1,293
2,585
Page 375 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
I'.iidpniiil1
('limine
MIX
(ppm)
Exposure
l.e\el
Worker
No
respiralor
\l()l-'.s lor (
OM
No
respiralor1
limine l'.\
Worker
API- 10
insure
Worker
API- 25
Worker
API- 50
liciichmark
MOF.
(= Tnlal
1 1 )
ki(liK'\ -
Histopathology
01SA 1993)
2.1
1 hull-Did
r
21
1 "4
4'5
S"(l
30
Central
Tendency
21
209
522
1,044
Liver -
Vessel dilation
01SA 1993)
31
High-End
257
308
2,569
6,422
12,843
30
Central
Tendency
308
3,082
7,706
15,412
Reproductive -
Sperm effects
©elites et al.
1980)
21
High-End
240
288
2,403
6,007
12,014
30
Central
Tendency
288
2,883
7,209
14,417
Developmental -
Mortality/
CNS effects
("Tinston 1994)
18
High-End
174
209
1740
4350
8700
30
Central
Tendency
209
2088
5220
10440
9316 1 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
9317 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
9318
9319 Table 4-66. Risk Estimation for Chronic, Cancer Inhalation Exposures for Other Department of
9320 Defense Uses
l-liidpniiil. Tumor
Tjpes"
11 K
(risk per
ppm)
Exposure
l.e\el
Worker
Nn
rcspiralnr
Cancer K
ONI
Nn
respiralor
isk I'.slimal
W nrker
API- 10
es
W nrker
API- 25
Wnrker
API- 50
lienchmark
Water Pipe Repair
Cancer Risk
2.0E-3
High-End
7.8E-05
2.5E-05
7.8E-06
3.1E-6
1.6E-6
10"4
Central
Tendency
2.5E-05
2.5E-06
1.0E-6
5.0E-7
Oil Analysis
Cancer Risk
2.0E-3
High-End
1.2E-04
8.0E-05
1.2E-05
5.0E-6
2.5E-6
10"4
Central
Tendency
8.0E-05
8.0E-06
3.2E-6
1.6E-6
9321 1 Data from JISA (19931
9322 2 EPA is unable to estimate ONU exposures separately from workers. EPA used worker central tendency values as a
9323 surrogate to assess risk for ONUs; however, the statistical representativeness of this value for ONUs is unknown.
9324 4,2.3 Risk Estimation for Dermal Exposures to Workers
9325 To assess dermal exposure, EPA used the Dermal Exposure to Volatile Liquids Model (see Section
9326 2.4.1.5 ) to calculate the dermal retained dose. EPA "binned" exposure scenarios based on likely level of
9327 exposure. Overall, EPA has a medium level of confidence in the assessed baseline exposure.
9328 The hazard HEDs are summarized in Table 3-7,
9329 Table 3-8 and Table 3-9. From among all chronic studies, EPA selected the most robust studies and non-
9330 cancer PODs from within each health domain to serve as representative endpoints for risk estimation
9331 (Section 3.2.5.4). These representative PODs are presented below in Table 4-2 along with the single
9332 acute POD. Dermal PODs were calculated as extrapolated from both inhalation and oral POD values,
Page 376 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
9333 when possible (Section 3.2.5.4.1 and Table 3-10). When extrapolation was available via both routes, the
9334 more sensitive POD was selected in order to be health-protective given the relative similarity in
9335 magnitude of uncertainties via either route. Of note, in all cases the difference in the derived dermal
9336 POD between routes is no more than approximately 2-fold. The dermal POD value to be used for risk
9337 estimates is bold in the table below. Non-cancer risk estimates were calculated with equation 4-1 and
9338 cancer risks were calculated with equation 4-2.
9339 Table 4-67. Selected Non-cancer POPs for Use in Risk Estimation of Dermal Exposures
Toliil
Inhiiliiliun lo
Oi'iil lo
I nccrliiinl\
Inhalation
Inhalation lo
Dorm ill
Dorm ill
I'aclor (I I") for
Targel Organ S\sk'in
POD <111(1
Derm ;il
Mil)
Mil)
licnchniiirk
Dalii
iiml I'.ITecl
Duration
Ari.jiiMim-nls
(ing/kg-(la\)
(mg/kg-(la\)
MOI.
KoIVivikt
Qu;ili(>
ACHE EXPOSURE
CNS
Neurotoxicity
increased latencies
for pattern reversal
visual-evoked
10 ppm
(68 mg/m3)
4 hrs/day
1.25 m3/hr
4 hrs/day
80 kg BW
4.25
N/A
UFa=1;
UFh=10;
UFl=1
Total UF=10
Altmann et
al. (1990)
Medium
potentials
CHRONIC EXPOSURE
Midpoint of the range
of the two
neurotoxicity
endpoints
5.2 ppm
(36 mg/m3)
20 m3/day
80 kg BW
9.0
6.2
UFa=1;
UFh=10;
UFl=10
Total UF=100
Based on
U.S. EPA
(2012c)
Medium
Kidney
Nuclear enlargement
in proximal tubules
2.1 ppm
(14 mg/m3)
24 hrs/day
20 m3/day
80 kg BW
3.5
2.2
UFa=3;
UFh=10;
UFl=1
Total UF=30
JISA (,
1993,
630653)
High
Liver
Increased angiectasis
in liver
31 ppm
(210 mg/m3)
24 hrs/day
20 m3/day
80 kg BW
52.5
24.5
UFa=3;
UFh=10;
UFl=1
Total UF=30
JISA
(1993)
High
Developmental
UFa=3;
Reduced sperm
quality following 5
21 ppm
(140 mg/m3)
20 m3/day
80 kg BW
35
22
UFh=10;
UFl=1
Beliles et
al. (1980)
High
days exposure
Total UF=30
Developmental
Increased F2a pup
deaths by Day 29,
CNS depression in Fi
andF2
18 ppm
(122 mg/m3)
20 m3/day
80 kg BW
31
N/A
UFa=3;
UFh=10;
UFl=1
Total UF=30
Tinston et
al. (1994)
High
CANCER
male mouse
hepatocellular tumors
3 x 10"4
per mg/m3
20 m3/day
80 kg BW
1 x 10"3 per
mg/kg/day
2 x 10 3
per
mg/kg/day
Not applicable
JISA
(1993)
High
9340
Page 377 of 636
-------
9341
9342
9343
9344
9345
9346
9347
9348
9349
9350
9351
9352
9353
9354
9355
9356
9357
9358
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
4.2.3.1 Industrial Uses That Generally Occur in Closed Systems
For these uses, dermal exposure is likely limited to chemical loading/unloading activities (e.g.
connecting hoses) and taking quality control samples. The exposure scenarios include:
• Manufacture
• Import/Repackaging
• Processing as a Reactant
• Incorporation into Formulation, Mixture, or Reaction Product
• Industrial Processing Aid
• Other Industrial Uses
• Waste Handling, Disposal, Treatment, and Recycling
Table 4-68. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Industrial Uses That
Generally Occur in Closed Systems
limlpoinl 1
Acule II111)
(mii/k*i/(l;i\)
Mxposure
1 .e\ el
M
Worker
Nit "hues
)l.s for Aci
Worker
PI- 5
(e l-'.xposure
W orker
PI 10
s
Worker
PI- 20
lienchmark
\ioi-:
(= lolal I 1)
CNS -
Visual effects
(U.S. EPA
2012c)
4.3
High-
End
1.2
(..»
12
24
10
Central
Tendency
3.(i
IS
36
72
1 Based on route to route extrapolation from inhalation exposure data from Altmann et al. (1990) see
Table 3-7
Table 4-69. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Industrial Uses That
Generally Occur in Closed Systems
I'lmlpoini
Chronic
Mil)
(m»/k»/
d;i\)
l'l\poMirc
1 .e\ el
M
W orker
No »lo\es
Ol-'.s I'orC hi-
Worker
PI- 5
inic l'l\posui
W orker
PI- 10
e
W orker
PI- 20
lienchmark
MOI.
(= lolal I 1")
CJNS-
Visual effects
(U.S. EPA
2012c)
6.2
High-
End
2.(i
13
2(.
51
100
Central
Tendency
7.7
3X
77
154
Kidney -
Histopathology
(USA 1993)
2.2
High-
End
0.')
4.(i
'U
IS
30
Central
Tendency
2.7
10
14
27
55
Liver -
Vessel dilation
(USA 1993)
24.5
High-
End
51
101
203
30
Central
Tendency
}<)
152
304
608
Reproductive -
Sperm effects
(Bellies et al.
1980)
22
High-
End
'U
45
91
182
30
Central
Tcndcncx
27
136
273
546
Developmental -
Mortality/
CNS effects
(Tinston 1994)
31
High-
End
13
64
128
256
30
Central
Tendency
3X
192
384
769
Page 378 of 636
-------
9359
9360
9361
9362
9363
9364
9365
9366
9367
9368
9369
9370
9371
9372
9373
9374
9375
9376
9377
9378
9379
9380
9381
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-70. Risk Estimation for Chronic, Cancer Dermal Exposures for Industrial Uses That
Generally Occur in Closed Systems
Endpoint,
Tumor Types1
Dermal slope
factor
(risk per
mg/kg/day)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
Cancer Risk
liver tumors
2.0E-3
High-End
2.5E-3
5.0E-4
2.5E-4
1.2E-4
10"4
Central
Tendency
6.4E-4
1.3E-4
6.4E-5
3.2E-5
1 Based on route to route extrapolation from the oral slope factor using data from JISA (1993)
4.2.3.2 Industrial Degreasing and Chemical Maskant Uses Which Are Not Closed
Systems
For these uses, there is greater opportunity for dermal exposure during activities such as charging and
draining degreasing/milling equipment, drumming waste solvent, handling recycled/re-captured
maskants, and removing waste sludge. The exposure scenarios include:
• Batch Open-Top Vapor Degreasing
• Batch Closed-Loop Vapor Degreasing
• Conveyorized Vapor Degreasing
• Web Degreasing
• Cold Cleaning
• Maskant for Chemical Milling
Table 4-71. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Industrial Degreasing
and Chemical Maskant Uses Which Are Not Closed Systems
Endpoint1
Acute HED
(mg/kg/day)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
CNS -
Visual effects
(U.S. EPA
2012c)
4.3
High-
End
1.2
6.0
12
24
10
Central
Tendency
3.6
18
36
72
1 Based on route to route extrapolation from inhalation exposure data from Altmann et al. (1990) see
Table 3-7
Table 4-72. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Industrial
Endpoint
Chronic
HED
(mg/kg/
day)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
CNS -
Visual effects
(U.S. EPA
2012c)
6.2
High-
End
2.6
13
26
51
100
Central
Tendency
7.7
38
77
154
Kidney -
Histopathology
2.2
High-
End
0.9
4.5
9.1
18
30
Page 379 of 636
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9383
9384
9385
9386
9387
9388
9389
9390
9391
9392
9393
9394
9395
9396
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Endpoint
Chronic
HED
(mg/kg/
day)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
(JISA 1993)
Central
Tendency
2.7
14
27
55
Liver -
Vessel dilation
(JISA 1993)
24.5
High-
End
10
51
101
203
30
Central
Tendency
30
152
304
608
Reproductive -
Sperm effects
(Beliles et al.
1980)
22
High-
End
9.1
45
91
182
30
Central
Tendency
27
136
273
546
Developmental -
Mortality/
CNS effects
(Tinston 1994)
31
High-
End
13
64
128
256
30
Central
Tendency
38
192
384
769
Table 4-73. Risk Estimation for Chronic, Cancer Dermal Exposures for Industrial Degreasing and
Chemical Maskant Uses Which Are Not Closed Systems
Endpoint,
Tumor Types1
Dermal
slope factor
(risk per
mg/kg/day)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
Cancer Risk
liver tumors
2.0E-3
High-End
2.5E-3
5.0E-4
2.5E-4
1.2E-4
10"4
Central
Tendency
6.4E-4
1.3E-4
6.4E-5
3.2E-5
1 Based on route to route extrapolation from the oral slope factor using data from JISA (1993)
4.2.3.3 Aerosol Uses
For these uses, workers are likely to have direct dermal contact with film applied to substrate and
incidental deposition of aerosol to skin. The exposure scenario is specific to aerosol degreasing and
aerosol lubricants. EPA does not expect routine use of dermal PPE with this exposure scenario for
commercial use.
Table 4-74. E
Lisk Estimation for Acute, Non-Cancer Dermal Exposures for Aeroso
Uses
Endpoint1
Acute HED
(mg/kg/day)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 53
Worker
PF 10
Worker
PF 20
CNS -
Visual effects
(U.S. EPA
2012c)
4.3
High-End
0.8
4.0
8.0
16
10
Central
Tendency
2.4
12
24
48
1 Based on route to route extrapolation from inhalation exposure data from Altmann et al. (1990) see
Table 3-7
Page 380 of 636
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9397
9398
9399
9400
9401
9402
9403
9404
9405
9406
9407
9408
9409
9410
9411
9412
9413
9414
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-75. Risk Estimaf
ion for Chronic, Non-Cancer Dermal Exposures for Aerosol Uses
Endpoint
Chronic
HED
(mg/kg/
day)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
CNS -
Visual effects
(U.S. EPA
2012c)
6.2
High-
End
1.7
8.6
17
34
100
Central
Tendency
5.1
26
51
103
Kidney -
Histopathology
(JISA 1993)"
2.2
High-
End
0.6
3.0
6.1
12
30
Central
Tendency
1.8
9.1
18
36
Liver -
Vessel dilation
(JISA 1993)
24.5
High-
End
6.8
34
68
135
30
Central
Tendency
20
101
203
406
Reproductive -
Sperm effects
(Beliles et al.
1980)
22
High-
End
6.1
30
61
121
30
Central
Tendency
18
91
182
364
Developmental -
Mortality/
CNS effects
(Tinston 1994)
31
High-
End
8.6
43
86
171
30
Central
Tendency
26
128
257
513
Table 4-76. B
Jsk Estimaf
ion for Chronic, Cancer Dermal Exposures for Aerosol Uses
Endpoint,
Tumor Types1
Dermal
slope factor
(risk per
mg/kg/day)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
Cancer Risk
liver tumors
2.0E-3
High-End
3.7E-3
7.4E-4
3.7E-4
1.9E-4
10"4
Central
Tendency
9.6E-4
1.9E-4
9.6E-5
4.8E-5
1 Based on route to route extrapolation from the oral slope factor using data from JISA (1993)
4.2.3.4 Commercial Activities of Similar Maximum Concentration
Most of these uses are uses with concentrations up to 100% PCE and occur at dry cleaners, and/or uses
expected to have direct dermal contact with bulk liquids. At dry cleaning shops, workers may be
exposed to bulk liquids while charging and draining solvent to/from machines, removing and disposing
sludge, and maintaining equipment. Workers can also be exposed to PCE used in spot cleaning products
at the same shop. The exposure scenarios include:
• Dry Cleaning and Spot Cleaning
• Wipe Cleaning and Metal/Stone Polishes
• Other Spot Cleaning/Spot Remover
• Other Commercial Uses
EPA does not expect routine use of dermal PPE with these exposure scenarios for commercial use.
Page 381 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
9415 Table 4-77. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Commercial Activities
9416 of Similar Maximum Concentration
Endpoint1
Acute HED
(mg/kg/day)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 52
Worker
PF 102
Worker
PF 202
CNS -
Visual effects
(U.S. EPA
2012c)
4.3
High-End
0.8
3.9
7.9
16
10
Central
Tendency
2.4
12
24
47
9417 1 Based on route to route extrapolation from inhalation exposure data from Altmann et al. (1990) see
9418 Table 3-7
9419 2 EPA does not expect routine use of PPE with this exposure scenario.
9420
9421
9422 Table 4-78. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Commercial
9423 Activities of Similar Maximum Concentration
Endpoint
Chronic
HED
(mg/kg/
day)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 51
Worker
PF 101
Worker
PF 201
CNS -
Visual effects
(U.S. EPA
2012c)
6.2
High-
End
1.7
8.4
17
34
100
Central
Tendency
5.0
25
50
101
Kidney -
Histopathology
(JISA 1993)"
2.2
High-
End
0.6
3.0
6.0
12
30
Central
Tendency
1.8
8.9
18
36
Liver -
Vessel dilation
(JISA 1993)
24.5
High-
End
6.6
33
66
133
300
Central
Tendency
20
99
199
398
Reproductive -
Sperm effects
(Beliles et al.
1980)
22
High-
End
6.0
30
60
119
30
Central
Tendency
18
89
179
357
Developmental -
Mortality/
CNS effects
(Tinston 1994)
31
High-
End
8.4
42
84
168
30
Central
Tendency
25
126
252
503
9424 1 EPA does not expect routine use of PPE with this exposure scenario.
9425
Page 382 of 636
-------
9426
9427
9428
9429
9430
9431
9432
9433
9434
9435
9436
9437
9438
9439
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-79. Risk Estimation for Chronic, Cancer Dermal Exposures for Commercial Activities of
Similar Maximum Concentration
Endpoint,
Tumor Types1
Dermal
slope
factor
(risk per
mg/kg/day)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No gloves
Worker
PF 52
Worker
PF 102
Worker
PF 202
Cancer Risk
liver tumors
2.0E-3
High-End
3.8E-3
7.6E-4
3.8E-4
1.9E-4
10"4
Central
Tendency
9.8E-4
2.0E-4
9.8E-5
4.9E-5
1 Based on route to route extrapolation from the oral slope factor using data from JISA (1993)
2 EPA does not expect routine use of PPE with this exposure scenario.
4.2.3.5 Metalworking Fluids
These product formulations are expected to be used in industrial settings and workers may be exposed
when unloading the metalworking fluid from containers; transferring fluids to the trough; and
performing metal shaping operations. The exposure scenario is specific to metalworking fluids.
Table 4-80. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Metalworking Fluids
Endpoint1
Acute HED
(mg/kg/day)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
CNS -
Visual effects
(U.S. EPA
2012c)
4.3
High-End
12
60
120
241
10
Central
Tendency
36
181
361
722
1 Based on route to route extrapolation from inhalation exposure data from Altmann et al. (1990) see
Table 3-7
Table 4-81. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Metalworking Fluids
Endpoint
Chronic
HED
(mg/kg/ day)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
CNS -
Visual effects
(U.S. EPA
2012c)
6.2
High-
End
26
128
256
513
100
Central
Tendency
77
384
769
1,538
Kidney -
Histopathology
(JISA 1993)"
2.2
High-
End
9.1
45
91
182
30
Central
Tendency
27
136
273
546
Liver -
Vessel dilation
(JISA 1993)
24.5
High-
End
101
506
1,013
2,026
30
Central
Tendency
304
1,519
3,039
6,077
Reproductive -
Sperm effects
(Beliles et al.
1980)
22
High-
End
91
455
910
1819
30
Central
Tendency
273
1364
2729
5457
Developmental -
Mortality/
31
High-
End
128
641
1282
2563
30
Page 383 of 636
-------
9440
9441
9442
9443
9444
9445
9446
9447
9448
9449
9450
9451
9452
9453
9454
9455
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Endpoint
Chronic
HED
(mg/kg/ day)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
CNS effects
(Tinston 1994)
Central
Tendency
384
1922
3845
7690
Table 4-82. B
Jsk Estimat
ion for Chronic, Cancer Dermal Exposures for Metalworking Fluids
Endpoint,
Tumor Types1
Dermal
slope factor
(risk per
mg/kg/day)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
Cancer Risk
liver tumors
2.0E-3
High-End
2.5E-4
5.0E-5
2.5E-5
1.2E-5
10"4
Central
Tendency
6.4E-5
1.3E-5
6.4E-6
3.2E-6
1 Based on route to route extrapolation from the oral slope factor using data from JISA (1993)
4.2.3.6 Adhesives, Sealants, Paints, and Coatings
These product formulations may have both industrial and commercial uses and workers may be exposed
when mixing coating/adhesive, charging products to application equipment (e.g., spray guns, roll
applicators, etc.), and cleaning application equipment. Other workers may also have incidental contact
with applied products during subsequent fabrication steps. The exposure scenario is specific to
adhesives, sealants, paints, and coatings.
Table 4-83. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Adhesives, Sealants,
Paints, and Coatings
Endpoint1
Acute HED
(mg/kg/day)
Exposure
Level
MOEs for Acute Exposures
Benchmark
MOE
(= Total UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
Commercial Uses
CNS -
Visual effects
(U.S. EPA
2012c)
4.3
High-End
1.0
4.9
9.8
20
10
Central
Tendency
3.0
15
30
59
Industrial Uses
CNS -
Visual effects
(U.S. EPA
2012c)
4.3
High-End
1.5
7.5
15
30
10
Central
Tendency
4.5
23
45
90
1 Based on route to route extrapolation from inhalation exposure data from Altmann et al. (1990) see
Table 3-7
Page 384 of 636
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9456
9457
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Table 4-84. Risk Estimation for Chronic, Non-Cancer Dermal Exposures for Adhesives, Sealants,
Endpoint
Chronic
HED
(mg/kg/
day)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total
UF)
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
Commercial Uses
CNS -
Visual effects
(U.S. EPA
2012c)
6.2
High-
End
2.1
10
21
42
100
Central
Tendency
6.3
31
63
126
Kidney -
Histopathology
(JISA 1993)"
2.2
High-
End
0.7
3.7
7.4
15
30
Central
Tendency
2.2
11
22
45
Liver -
Vessel dilation
(JISA 1993)
24.5
High-
End
8.3
41
83
166
30
Central
Tendency
25
124
248
497
Reproductive -
Sperm effects
(Bclilcs et al.
1980)
22
High-
End
7.4
37
74
149
30
Central
Tendency
22
112
223
446
Developmental -
Mortality/
CNS effects
(Tinston 1994)
31
High-
End
10
52
105
210
30
Central
Tendency
31
157
314
629
Industrial Uses
CNS -
Visual effects
(U.S. EPA
2012c)
6.2
High-
End
3.2
16
32
64
100
Central
Tendency
9.6
48
96
192
Kidney -
Histopathology
(JISA 1993)"
2.2
High-
End
1.1
5.7
11
23
30
Central
Tendency
3.4
17
34
68
Liver -
Vessel dilation
(JISA 1993)
24.5
High-
End
13
63
127
253
30
Central
Tendency
38
190
380
760
Reproductive -
Sperm effects
(Bclilcs et al.
1980)
22
High-
End
11
57
114
227
30
Central
Tendency
34
171
341
682
Developmental -
Mortality/
CNS effects
(Tinston 1994)
31
High-
End
16
80
160
320
30
Central
Tendency
48
240
481
961
9458
Page 385 of 636
-------
9459
9460
9461
9462
9463
9464
9465
9466
9467
9468
9469
9470
9471
9472
9473
9474
9475
9476
9477
9478
9479
9480
9481
9482
9483
9484
9485
9486
9487
9488
9489
9490
9491
9492
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table 4-85. Risk Estimation for Chronic, Cancer Dermal Exposures for Adhesives, Sealants,
Paints, and Coatings
Endpoint,
Tumor
Types1
Dermal
slope factor
(risk per
mg/kg/day)
Exposure
Level
Cancer Risk Estimates
Benchmark
Worker
No gloves
Worker
PF 5
Worker
PF 10
Worker
PF 20
Commercial Uses
Cancer Risk
liver tumors
2.0E-3
High-End
3.0E-3
6.1E-4
3.0E-4
1.5E-4
10"4
Central
Tendency
7.8E-4
1.6E-4
7.8E-5
3.9E-5
Industrial Uses
Cancer Risk
liver tumors
2.0E-3
High-End
2.0E-3
4.0E-4
2.0E-4
9.9E-5
10"4
Central
Tendency
5.1E-4
1.0E-4
5.1E-5
2.6E-5
1 Based on route to route extrapolation from the oral slope factor using data from JISA (1993)
4.2.4 Risk Estimation for Exposures to Consumers
Risk estimates for consumers were calculated for consumers for acute inhalation and dermal exposures.
Risk estimates for chronic exposures were not calculated because it is unknown how the available
toxicological data relates to the human exposures expected in consumer exposure scenarios. The toxicity
studies are based on human worker studies or continuous sub chronic-to-chronic repeated dose animal
studies. In contrast, the consumer exposure scenarios are expected to be intermittent and it is unlikely
that the expected use patterns would cumulatively be equivalent to these scenarios. It therefore cannot be
ruled out whether there is any risk for chronic non-cancer or cancer associated with regular, intermittent
exposures at the very high end of use frequency, however this scenario cannot be adequately evaluated
and is unlikely to apply to the vast majority of users.
Risk estimates were presented for differing acute exposure assumptions, categorized as high, moderate,
or low intensity users based on variation in weight fraction, mass of product used, and duration of
use/exposure duration. Risk estimates primarily utilized central tendency values for other modeling
parameters (e.g., room volume, air exchange rate, building volume) and therefore do not necessarily
represent an upper bound of possible exposures. For more details on the characterization of consumer
exposure see Section 2.4.2.2. For MOE estimates of all modeled scenarios see supplemental files: Draft
Risk Evaluation for Perchloroethylene Consumer Inhalation Risk Calculations (U.S. EPA 2020c) and
Draft Risk Evaluation for Perchloroethylene Consumer Dermal Risk Calculations (U.S. EPA 2020b).
The HEC (Table 3-7) and HED values (Table 3-10) for neurotoxicity from (Altmann et al. 1990) was
used for estimating of all acute consumer risks.
4.2.4.1 Aerosol Cleaners for Motors, Coils, Electrical Parts, Cables, Stainless Steel
and marine Equipment, and Wire and Ignition Demoisturants
Estimates of MOEs for acute inhalation and dermal exposures for the aerosol cleaners for motors, coils
and electrical parts, etc. consumer use are presented in Table 4-86 and Table 4-87, respectively.
Consumer inhalation and dermal exposures were modeled across a range of low, moderate, and high
user intensities as described in detail in Section 2.4.2.2. For inhalation, low, moderate and high intensity
users are characterized by the 10th, 50th, and 95th percentile duration of use and mass of product used
respectively and minimum, midpoint, and maximum reported weight fractions where possible
Page 386 of 636
-------
9493
9494
9495
9496
9497
9498
9499
9500
9501
9502
9503
9504
9505
9506
9507
9508
9509
9510
9511
9512
9513
9514
9515
9516
9517
9518
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
respectively. Characterization of low intensity, moderate intensity and high intensity users for dermal
followed the same protocol as those described for the inhalation results, but only encompassing the two
varied duration of use and weight fraction parameters. Inhalation exposures are presented for users and
bystanders for 24-hour TWAs and dermal exposure results are presented for users as acute ADRs in
Section 2.4.2.3.1.1.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate and medium for the dermal estimate, as discussed in Section 2.4.2.3.1.1.
Table 4-86. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Aerosol Cleaners for
Motors Consumer Use
Anile MIX lorCNS F. Heels' (11 niii/nr1)
lienehm;irk \1()F = 10
r.\|)(isui\' SiTiiiiriu
I ser
moi:
IVtsliimler
MOI.
Low Intensity User
7.7
39
Moderate Intensity User
0.2
0.8
High Intensity User
1.3E-02
5.2E-02
1 24 hrs HEC based on data from Altmann et al. (1990)
Table 4-87. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Aerosol Cleaners for
Motors Consumer Use
( oiisiinier Keeeplor
Fxposure Seen;irio
I SOI"
MOI.
Adult (>21 years)
35
Low Intensity User
Youth (16-20 years)
38
Youth (11-15 years)
35
Adult (>21 years)
0.6
Moderate Intensity User
Youth (16-20 years)
0.6
Youth (11-15 years)
0.6
Adult (>21 years)
5.9E-02
High Intensity User
Youth (16-20 years)
6.3E-02
Youth (11-15 years)
5.8E-02
1 HED extrapolated from inhalation exposures based on data from Altmann et al. (1990) described in Section 3.2.5.4.1
The MOEs are below the benchmark MOE for high and moderate intensity users and bystanders by
inhalation and dermal exposures. The MOEs are below the benchmark MOE for the low intensity user
by inhalation not dermal exposure and not for the low-intensity bystander.
4.2.4.2 Aerosol Brake Cleaners
Estimates of MOEs for acute inhalation and dermal exposures for the aerosol brake cleaners consumer
use are presented in Table 4-88 and Table 4-89, respectively. Consumer inhalation and dermal exposures
were modeled across a range of low, moderate, and high user intensities as described in detail in Section
2.4.2.2. For inhalation, low, moderate and high intensity users are characterized by the 10th, 50th, and
95th percentile duration of use and mass of product used respectively and minimum, midpoint, and
Page 387 of 636
-------
9519
9520
9521
9522
9523
9524
9525
9526
9527
9528
9529
9530
9531
9532
9533
9534
9535
9536
9537
9538
9539
9540
9541
9542
9543
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
maximum reported weight fractions where possible respectively. Characterization of low intensity,
moderate intensity and high intensity users for dermal followed the same protocol as those described for
the inhalation results, but only encompassing the two varied duration of use and weight fraction
parameters. Inhalation exposures are presented for users and bystanders for 24-hour TWAs and dermal
exposure results are presented for users as acute ADRs in Section 2.4.2.3.1.2.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate and medium for the dermal estimate, as discussed in Section 2.4.2.3.1.2.
Table 4-88. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Aerosol Brake
Cleaners Consumer Use
r.\|)(isui\' SiTiiiiriu
Aculc MIX lorCNS F.ITcds" (11 niii/nr1)
licnchm;irk M()l.= 10
I ser
moi:
IVksfiiiiricr
MOI.
Low Intensity User
2.0
7.1
Moderate Intensity User
0.2
0.8
High Intensity User
4.5E-02
0.2
1 24 hrs HEC based on data from Altmann et al. (1990)
Table 4-89. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Aerosol Brake Cleaner
Consumer Use
I'1\])omiiv Sccn.irio
Consumer Rcccplor
Aculc lll.l) lorCNS I ITccls1
(4.25 m»/k^/(lii>)
Bcnchiiiiirk MOI. = 10
I SCI"
moi:
Low Intensity User
Adult (>21 years)
22
Youth (16-20 years)
23
Youth (11-15 years)
21
Moderate Intensity User
Adult (>21 years)
0.6
Youth (16-20 years)
0.7
Youth (11-15 years)
0.6
High Intensity User
Adult (>21 years)
7.2E-02
Youth (16-20 years)
7.7E-02
Youth (11-15 years)
7.1E-02
1 HED extrapolated from inhalation exposures based on data from Altmann et al. (1990) described in Section 3.2.5.4.1
The MOEs are below the benchmark MOE for all users and bystanders by inhalation exposures. The
MOEs are below the benchmark MOE for the high and Moderate Intensity Users by dermal exposure
and not for low intensity dermal exposures.
4.2.4.3 Parts Cleaners
Estimates of MOEs for acute inhalation and dermal exposures for the immersive parts cleaner consumer
use are presented in Table 4-90 and Table 4-91, respectively. Consumer inhalation and dermal exposures
were modeled across a range of low, moderate, and high user intensities as described in detail in Section
2.4.2.2. For inhalation, low, moderate and high intensity users are characterized by the 10th, 50th, and
Page 388 of 636
-------
9544
9545
9546
9547
9548
9549
9550
9551
9552
9553
9554
9555
9556
9557
9558
9559
9560
9561
9562
9563
9564
9565
9566
9567
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
95th percentile duration of use and mass of product used respectively and minimum, midpoint, and
maximum reported weight fractions where possible respectively. Characterization of low intensity,
moderate intensity and high intensity users for dermal followed the same protocol as those described for
the inhalation results, but only encompassing the two varied duration of use and weight fraction
parameters. Inhalation exposures are presented for users and bystanders for 24-hour TWAs and dermal
exposure results are presented for users as acute ADRs in Section 2.4.2.3.2.
Considering the overall strengths and limitations of the data, EPA's overall confidence is medium for the
consumer inhalation estimate and medium for the dermal estimate, as discussed in Section 2.4.2.3.2.
Table 4-90. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Parts Cleaners
Consumer Use
I'1\|)omiiy Seen;iriu
Aeule MIX lorCNS F. Heels' (11 niii/nr1)
lienehm;irk \1()F = 10
1 SIT
MOI.
B>sl;ni(ler
MOF
Low Intensity User
31
174
Moderate Intensity User
0.6
3.3
High Intensity User
7.1E-02
0.4
1 24 hrs HEC based on data from Altmann et al. (1990)
Table 4-91. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Parts Cleaners
Consumer Use
Fxposure Seen.irio
Consumer Keeeplor
Acme IIF.I) lor ( \S r.Heels'
(4.25 )
lienehm;irk MOF = 10
I ser
MOF
Low Intensity User
Adult (>21 years)
0.2
Youth (16-20 years)
0.2
Youth (11-15 years)
0.2
Moderate Intensity User
Adult (>21 years)
1.4E-02
Youth (16-20 years)
1.4E-02
Youth (11-15 years)
1.3E-02
High Intensity User
Adult (>21 years)
2.4E-03
Youth (16-20 years)
2.3E-03
Youth (11-15 years)
2.1E-03
1 HED extrapolated from inhalation exposures based on data from Altmann et al. (1990) described in Section 3.2.5.4.1
The MOEs are below the benchmark MOE for high and moderate intensity users and bystanders by
inhalation exposures and not for low intensity inhalation exposures. The MOEs are below the
benchmark MOE for all users by dermal exposure.
4.2.4.4 Vandalism Stain Removers, Mold Cleaners, and Weld Splatter Protectants
Estimates of MOEs for acute inhalation exposures for the vandalism stain removers, mold cleaners, and
weld splatter protectants consumer use are presented in Table 4-92. Dermal exposures to consumers are
Page 389 of 636
-------
9568
9569
9570
9571
9572
9573
9574
9575
9576
9577
9578
9579
9580
9581
9582
9583
9584
9585
9586
9587
9588
9589
9590
9591
9592
9593
9594
9595
9596
9597
9598
9599
9600
9601
9602
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
not expected for vandalism stain removers, mold cleaners, and weld splatter protectants as described in
Section 2.4.2.3.3. Consumer inhalation exposures were modeled across a range of low, moderate, and
high user intensities as described in detail in Section 2.4.2.2. For inhalation, low, moderate and high
intensity users are characterized by the 10th, 50th, and 95th percentile duration of use and mass of product
used respectively and minimum, midpoint, and maximum reported weight fractions where possible
respectively. Inhalation exposures are presented for users and bystanders for 24-hour TWAs are
presented in Section 2.4.2.3.3.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate, as discussed in Section 2.4.2.3.3.
Table 4-92. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Vandalism Stain
I'1\|)omiiy Scoiiiii'io
Acuk' MIX lorCNS r.lTccls1 (11 niii/nr1)
liciichiiiiirk MOI. = 10
I scr
moi:
IVksfiiiiricr
MOI.
Low Intensity User
15
77
Moderate Intensity User
0.3
1.6
High Intensity User
1.3E-02
5.2E-02
1 24 hrs HEC based on data from Altmann et al. (1990)
The MOEs are below the benchmark MOE for high and moderate intensity users and bystanders by
inhalation exposures and not for low intensity inhalation exposures.
4.2.4.5 Marble Polish
Estimates of MOEs for acute inhalation and dermal exposures for the liquid-based marble polish
consumer use are presented in Table 4-93 and Table 4-94, respectively. Consumer inhalation and dermal
exposures were modeled across a range of low, moderate, and high user intensities as described in detail
in Section 2.4.2.2. For inhalation, low, moderate and high intensity users are characterized by the 10th,
50th, and 95th percentile duration of use and mass of product used respectively and minimum, midpoint,
and maximum reported weight fractions where possible respectively. Characterization of low intensity,
moderate intensity and high intensity users for dermal followed the same protocol as those described for
the inhalation results, but only encompassing the two varied duration of use and weight fraction
parameters. Inhalation exposures are presented for users and bystanders for 24-hour TWAs and dermal
exposure results are presented for users as acute ADRs in Section 2.4.2.3.4.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate and medium for the dermal estimate, as discussed in Section 2.4.2.3.4.
Table 4-93. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Liquid-Based
Marble Polish Consumer Use
Acuk' MIX lorCNS r.lTccls1 (11 niii/nr1)
liciichm;irk MOI. = 10
1 SCI"
B\sl;ni(lcr
r.\|)(isui\' SiTiiiiriu
MOI.
MOI.
Low Intensity User
3.3
17
Page 390 of 636
-------
9603
9604
9605
9606
9607
9608
9609
9610
9611
9612
9613
9614
9615
9616
9617
9618
9619
9620
9621
9622
9623
9624
9625
9626
9627
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Fxposure Scenario
Acuk' MIX lorCNS FITects1 (11 niii/nr1)
licnchm;irk \1()F = 10
I ser
moi:
IVtsliinricr
MOI.
Moderate Intensity User
6.8E-02
0.4
High Intensity User
1.2E-02
5.0E-02
1 24 hrs HEC based on data from Altmann et al. (1990)
Table 4-94. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Liquid-Based Marble
Polish Consumer Use
Fxposure Scenario
Consumer Receptor
Acule III.I) lorCNS FITeds"
(4.25 m»/ku/(lii>)
licnchniiirk MOT. = 10
1 SCI"
MOI.
Low Intensity User
Adult (>21 years)
3.5
Youth (16-20 years)
3.8
Youth (11-15 years)
3.5
Moderate Intensity User
Adult (>21 years)
5.5E-02
Youth (16-20 years)
5.9E-02
Youth (11-15 years)
5.4E-02
High Intensity User
Adult (>21 years)
5.8E-03
Youth (16-20 years)
6.3E-03
Youth (11-15 years)
5.8E-03
1 HED extrapolated from inhalation exposures based on data from Altmann et al. (1990) described in Section 3.2.5.4.1
The MOEs are below the benchmark MOE for high and Moderate Intensity Users and bystanders by
inhalation exposures and not for low intensity inhalation exposures. The MOEs are below the
benchmark MOE for all users by dermal exposures.
4.2.4.6 Cutting Fluid
Estimates of MOEs for acute inhalation exposures for the cutting fluid consumer use are presented in
Table 4-95. Dermal exposures for cutting fluid consumer use are not expected as described in Section
2.4.2.3.5. Consumer inhalation exposures were modeled across a range of low, moderate, and high user
intensities as described in detail in Section 2.4.2.2. For inhalation, low, moderate and high intensity
users are characterized by the 10th, 50th, and 95th percentile duration of use and mass of product used
respectively and minimum, midpoint, and maximum reported weight fractions where possible
respectively. Inhalation exposures are presented for users and bystanders for 24-hour TWAs are
presented in Section 2.4.2.3.5.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate, as discussed in Section 2.4.2.3.5.
Table 4-95. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Cutting Fluid
Consumer Use
l-'.\|)osiirc Scenario
Anile MIX lorCNS F. fleets1 (I I niii/nr1)
licnchm;irk \1()F = 10
Page 391 of 636
-------
9628
9629
9630
9631
9632
9633
9634
9635
9636
9637
9638
9639
9640
9641
9642
9643
9644
9645
9646
9647
9648
9649
9650
9651
9652
9653
9654
9655
9656
9657
9658
9659
9660
9661
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
I SOI"
moi:
IVtshnuk-r
moi:
Low Intensity User
8.1
39
Moderate Intensity User
1.3
6.7
High Intensity User
0.1
0.6
1 24 hrs HEC based on data from Altmann et al. (1990)
The MOEs are below the benchmark MOE for all users and high and moderate intensity bystanders by
inhalation exposures and not for low intensity bystanders.
4.2.4.7 Lubricants and Penetrating Oils
Estimates of MOEs for acute inhalation exposures for the lubricants and penetrating oils consumer use
are presented in Table 4-96. Dermal exposures for the lubricants and penetrating oils consumer use are
not expected as described in Section 2.4.2.3.6. Consumer inhalation exposures were modeled across a
range of low, moderate, and high user intensities as described in detail in Section 2.4.2.2. For inhalation,
low, moderate and high intensity users are characterized by the 10th, 50th, and 95th percentile duration of
use and mass of product used respectively and minimum, midpoint, and maximum reported weight
fractions where possible respectively. Inhalation exposures are presented for users and bystanders for
24-hour TWAs are presented in Section 2.4.2.3.6
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate, as discussed in Section 2.4.2.3.6.
Table 4-96. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Lubricants and
I'1\|)omiiy Scoiiiii'io
Anile MIX lorCNS F. Heels' (11 niii/nr1)
lienehm;irk \1()F = 10
1 SIT
MOI.
B>sl;ni(ler
MOI.
Low Intensity User
90
435
Moderate Intensity User
1.4
7.3
High Intensity User
8.0E-02
0.4
1 24 hrs HEC based on data from Altmann et al. (.1.990)
The MOEs are below the benchmark MOE for high and moderate intensity users and bystanders by
inhalation exposures and not for low intensity users and bystanders.
4.2.4.8 Adhesives
Estimates of MOEs for acute inhalation exposures for the adhesives consumer use are presented in Table
4-97. Dermal exposures for the adhesives consumer use are not expected as described in Section
2.4.2.3.7. Consumer inhalation exposures were modeled across a range of low, moderate, and high user
intensities as described in detail in Section 2.4.2.2. For inhalation, low, moderate and high intensity
users are characterized by the 10th, 50th, and 95th percentile duration of use and mass of product used
respectively and minimum, midpoint, and maximum reported weight fractions where possible
respectively. Inhalation exposures are presented for users and bystanders for 24-hour TWAs are
presented in Section 2.4.2.3.7
Page 392 of 636
-------
9662
9663
9664
9665
9666
9667
9668
9669
9670
9671
9672
9673
9674
9675
9676
9677
9678
9679
9680
9681
9682
9683
9684
9685
9686
9687
9688
9689
9690
9691
9692
9693
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate, as discussed in Section 2.4.2.3.7.
Table 4-97. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Adhesives
Consumer Use
I'1\|)omiiy Scoiiiii'io
Acuk' MIX lorCNS r.lTccls1 (11 niii/nr1)
liciichniiirk MOI. = 10
1 SCI"
MOI.
B>M;ni(k-r
MOI.
Low Intensity User
62
299
Moderate Intensity User
2.3
12
High Intensity User
0.1
0.5
1 24 hrs HEC based on data from Altmann et al. (1990)
The MOEs are below the benchmark MOE for high and moderate intensity users and high intensity
bystanders by inhalation exposures and not for low intensity users and medium and low intensity
bystanders.
4.2.4.9 Livestock Grooming Adhesive
Estimates of MOEs for acute inhalation exposures for the livestock grooming adhesive consumer use are
presented in Table 4-98. Dermal exposures for the livestock grooming adhesive consumer use are not
expected as described in Section 2.4.2.3.8. Consumer inhalation exposures were modeled across a range
of low, moderate, and high user intensities as described in detail in Section 2.4.2.2. For inhalation, low,
moderate and high intensity users are characterized by the 10th, 50th, and 95th percentile duration of use
and mass of product used respectively and minimum, midpoint, and maximum reported weight fractions
where possible respectively. Inhalation exposures are presented for users and bystanders for 24-hour
TWAs are presented in Section 2.4.2.3.8
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate, as discussed in Section 2.4.2.3.8.
Table 4-98. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Livestock Grooming
Adhesives Consumer Use
I'1\|)omiiy Sccii;iriu
Acuk' MIX lorCNS r.lTccls1 (11 niii/nr1)
liciichm;irk MOI. = 10
I scr
moi:
IVtsfiinricr
MOI.
Low Intensity User
112
539
Moderate Intensity User
12
64
High Intensity User
0.8
3.0
1 24 hrs HEC based on data from Altmann et al. (.1.990)
The MOEs are below the benchmark MOE for high intensity users and bystanders by inhalation
exposures and not for medium and low intensity users and bystanders.
4.2.4.10 Caulks, Sealants and Column Adhesives
Estimates of MOEs for acute inhalation exposures for the caulks, sealants and column adhesives
consumer use are presented in Table 4-99. Dermal exposures for the caulks, sealants and column
adhesives consumer use are not expected and the area of use was assumed to be outdoors, so bystander
Page 393 of 636
-------
9694
9695
9696
9697
9698
9699
9700
9701
9702
9703
9704
9705
9706
9707
9708
9709
9710
9711
9712
9713
9714
9715
9716
9717
9718
9719
9720
9721
9722
9723
9724
9725
9726
9727
9728
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
exposure was not estimated (see Section 2.4.2.3.9). Consumer inhalation exposures were modeled across
a range of low, moderate, and high user intensities as described in detail in Section 2.4.2.2. For
inhalation, low, moderate and high intensity users are characterized by the 10th, 50th, and 95th percentile
duration of use and mass of product used respectively and minimum, midpoint, and maximum reported
weight fractions where possible respectively. Inhalation exposures are presented for users and
bystanders for 24-hour TWAs are presented in Section 2.4.2.3.9.
Considering the overall strengths and limitations of the data, EPA's overall confidence is medium for the
consumer inhalation estimate, as discussed in Section 2.4.2.3.9.
Table 4-99. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Caulks, Sealants and
Column Adhesives Consumer Use
I'A])omiiv Scciiiirio
Aculc NIX for C\S Fffccls1
(11 niii/niM
licnchniiirk MOT. = 10
I SCI"
MOF
Low Intensity User
192
Moderate Intensity User
2.3
High Intensity User
7.2E-02
1 24 hrs HEC based on data from Altmann et al. (1990)
The MOEs are below the benchmark MOE for high and moderate intensity users by inhalation
exposures and now for low intensity users.
4.2.4.11 Outdoor Water Shield
Estimates of MOEs for acute inhalation and dermal exposures for the outdoor water shield consumer use
are presented in Table 4-100 and Table 4-101, respectively. Consumer inhalation and dermal exposures
were modeled across a range of low, moderate, and high user intensities as described in detail in Section
2.4.2.2. For inhalation, low, moderate and high intensity users are characterized by the 10th, 50th, and
95th percentile duration of use and mass of product used respectively and minimum, midpoint, and
maximum reported weight fractions where possible respectively. Characterization of low intensity,
moderate intensity and high intensity users for dermal followed the same protocol as those described for
the inhalation results, but only encompassing the two varied duration of use and weight fraction
parameters. Inhalation exposures are presented for users and bystanders for 24-hour TWAs and dermal
exposure results are presented for users as acute ADRs in Section 2.4.2.3.10.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate and medium for the dermal estimate, as discussed in Section2.4.2.3.4
2.4.2.3.10.
Table 4-100. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Outdoor Water
Shield Consumer Use
Fxposurc Scciiiii'io
Aciile NI C I'orCNS Fffccls1 (11 niii/nr1)
liciichniiirk MOF = 10
I SCI"
MOF
B>sl;ni(lcr
MOF
Page 394 of 636
-------
9729
9730
9731
9732
9733
9734
9735
9736
9737
9738
9739
9740
9741
9742
9743
9744
9745
9746
9747
9748
9749
9750
9751
9752
9753
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Low Intensity User
7.6
29
Moderate Intensity User
1.1
3.3
High Intensity User
8.9E-02
0.4
1 24 lirs HEC based on data from Altmann et al. (1990)
Table 4-101. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Outdoor Water Shield
Consumer Use
Exposure Scenario
Consumer Receptor
Acute HED for CNS Effects1
(4.25 mg/kg/day)
Benchmark MOE = 10
User
MOE
Low Intensity User
Adult (>21 years)
0.1
Youth (16-20 years)
0.1
Youth (11-15 years)
0.1
Moderate Intensity User
Adult (>21 years)
2.6E-02
Youth (16-20 years)
2.8E-02
Youth (11-15 years)
2.5E-02
High Intensity User
Adult (>21 years)
5.2E-03
Youth (16-20 years)
5.5E-03
Youth (11-15 years)
5.0E-03
1 HED extrapolated from inhalation exposures based on data from Altmann et al. (1990) described in Section 3.2.5.4.1
The MOEs are below the benchmark MOE for all users and high and moderate intensity bystanders by
inhalation exposures and not for low intensity bystanders. The MOEs are below the benchmark MOE for
all users by dermal exposures.
4.2.4.12 Aerosol Coatings and Primers
Estimates of MOEs for acute inhalation exposures for the aerosol coatings and primers consumer use are
presented in Table 4-102. Dermal exposures for the aerosol coatings and primers consumer use are not
expected as described in Section 2.4.2.3.11. Consumer inhalation exposures were modeled across a
range of low, moderate, and high user intensities as described in detail in Section 2.4.2.2. For inhalation,
low, moderate and high intensity users are characterized by the 10th, 50th, and 95th percentile duration of
use and mass of product used respectively and minimum, midpoint, and maximum reported weight
fractions where possible respectively. Inhalation exposures are presented for users and bystanders for
24-hour TWAs are presented in Section 2.4.2.3.112.4.2.3.92.4.2.3.8.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate, as discussed in Section 2.4.2.3.11.
Table 4-102. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Aerosol Coatings and
Primers Consumer Use
Acute HEC for CNS Effects1 (11 mg/m3)
Benchmark MOE = 10
User
Bystander
Exposure Scenario
MOE
MOE
Page 395 of 636
-------
9754
9755
9756
9757
9758
9759
9760
9761
9762
9763
9764
9765
9766
9767
9768
9769
9770
9771
9772
9773
9774
9775
9776
9777
9778
9779
9780
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Low Intensity User
522
13448
Moderate Intensity User
62
2143
High Intensity User
5.9
209
1 24 hrs HEC based on data from Altmann et al. (1990)
The MOEs are below the benchmark MOE for high intensity users by inhalation exposures. The MOEs
are above the benchmark MOE for medium and low intensity users and all bystanders by inhalation
exposures.
4.2.4.13 Liquid Primers and Sealants
Estimates of MOEs for acute inhalation and dermal exposures for the liquid primers and sealants
consumer use are presented in Table 4-103 and Table 4-104, respectively. Consumer inhalation and
dermal exposures were modeled across a range of low, moderate, and high user intensities as described
in detail in Section 2.4.2.2. For inhalation, low, moderate and high intensity users are characterized by
the 10th, 50th, and 95th percentile duration of use and mass of product used respectively and minimum,
midpoint, and maximum reported weight fractions where possible respectively. Characterization of low
intensity, moderate intensity and high intensity users for dermal followed the same protocol as those
described for the inhalation results, but only encompassing the two varied duration of use and weight
fraction parameters. Inhalation exposures are presented for users and bystanders for 24-hour TWAs and
dermal exposure results are presented for users as acute ADRs in Section 2.4.2.3.12.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate and medium for the dermal estimate, as discussed in Section 2.4.2.3.12.
Table 4-103. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Liquid Primers
and Sealants Consumer Use
I'A])omiiv Sceiiiirio
Anile MIX lor ( NS l-'.ITccls1 (11 mii/iir1)
licnchm;iik MOI. = 10
1 SCI"
MOI.
IVtsliinricr
MOI.
Low Intensity User
10600
128556
Moderate Intensity User
1163
12434
High Intensity User
36
229
1 24 hrs HEC based on data from Altmann et al. (.1.990)
Table 4-104. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Liquid Primers and
Sealants Consumer Use
Consumer Rcccplor
Aculc III.I) lorCNS I'.ITeds"
(4.25 m»/ku/(lii>)
licnchiiiiirk MOT. = 10
I'1\|)omiiv Scenario
I SCI"
MOI.
Adult (>21 years)
1.4
Low Intensity User
Youth (16-20 years)
1.5
Youth (11-15 years)
1.4
Moderate Intensity User
Adult (>21 years)
1.8E-02
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Youth (16-20 years)
1.9E-02
Youth (11-15 years)
1.8E-02
High Intensity User
Adult (>21 years)
1.6E-02
Youth (16-20 years)
1.7E-02
Youth (11-15 years)
1.6E-02
1 HED extrapolated from inhalation exposures based on data from Altmann et al. (1990) described in Section 3.2.5.4.1
The MOEs are above the benchmark MOE for all users and bystanders by inhalation exposures. The
MOEs are below the benchmark MOE for all users by dermal exposures.
4.2.4.14 Metallic Overglaze
Estimates of MOEs for acute inhalation exposures for the metallic overglaze consumer use are presented
in Table 4-105. Dermal exposures for the caulks, sealants and column adhesives consumer use are not
expected as described in Section 2.4.2.3.13. Consumer inhalation exposures were modeled across a
range of low, moderate, and high user intensities as described in detail in Section 2.4.2.2. For inhalation,
low, moderate and high intensity users are characterized by the 10th, 50th, and 95th percentile duration of
use and mass of product used respectively and minimum, midpoint, and maximum reported weight
fractions where possible respectively. Inhalation exposures are presented for users and bystanders for
24-hour TWAs are presented in Section 2.4.2.3.13.
Considering the overall strengths and limitations of the data, EPA's overall confidence is medium for the
consumer inhalation estimate, as discussed in Section 2.4.2.3.13.
Table 4-105. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Metallic Overglaze
Consumer Use
r.\|)osui\' Scoiiiii'io
Anile MIX lorCNS F. Heels' (11 niii/nr1)
lienehm;irk \1()F = 10
1 SIT
MOI.
B>sl;ni(ler
MOI.
Low Intensity User
4372
21107
Moderate Intensity User
337
1674
High Intensity User
21
81
1 24 hrs HEC based on data from Altmann et al. (1990)
The MOEs are above the benchmark MOE for all users and bystanders by inhalation exposures.
4.2.4.15 Metal and Stone Polish
Estimates of MOEs for acute inhalation and dermal exposures for the liquid wax-based metal and stone
polish consumer use are presented in Table 4-106 and Table 4-107, respectively. Consumer inhalation
and dermal exposures were modeled across a range of low, moderate, and high user intensities as
described in detail in Section 2.4.2.2. For inhalation, low, moderate and high intensity users are
characterized by the 10th, 50th, and 95th percentile duration of use and mass of product used respectively
and minimum, midpoint, and maximum reported weight fractions where possible respectively.
Characterization of low intensity, moderate intensity and high intensity users for dermal followed the
same protocol as those described for the inhalation results, but only encompassing the two varied
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duration of use and weight fraction parameters. Inhalation exposures are presented for users and
bystanders for 24-hour TWAs and dermal exposure results are presented for users as acute ADRs in
Section 2.4.2.3.14.
Considering the overall strengths and limitations of the data, EPA's overall confidence is high for the
consumer inhalation estimate and medium for the dermal estimate, as discussed in Section 2.4.2.3.14.
Table 4-106. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Metal and Stone
Polish Consumer Use
r.\|)(isui\' SiTiiiiriu
Aculc MIX lorCNS F.ITccls" (11 niii/nr1)
licnchm;irk M()l.= 10
I ser
moi:
IVksfiiiiricr
MOI.
Low Intensity User
1.1
5.3
Moderate Intensity User
0.2
0.8
High Intensity User
1.5E-02
6.1E-02
1 24 hrs HEC based on data from Altmann et al. (1990)
Table 4-107. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Metal and Stone
Polish Consumer Use
r.\|)osiMY Sccn;irio
Consumer Rcccplor
Aculc lll.l) lorCNS I'.ITccls"
(4.25 m»/k^/(lii>)
Bcnchiiiiirk MOI. = 10
I SCI"
moi:
Low Intensity User
Adult (>21 years)
1.0
Youth (16-20 years)
1.0
Youth (11-15 years)
1.0
Moderate Intensity User
Adult (>21 years)
0.1
Youth (16-20 years)
0.1
Youth (11-15 years)
0.1
High Intensity User
Adult (>21 years)
1.4E-02
Youth (16-20 years)
1.5E-02
Youth (11-15 years)
1.3E-02
1 HED extrapolated from inhalation exposures based on data from Altmann et al. (1990) described in Section 3.2.5.4.1
The MOEs are below the benchmark MOE for all users and bystanders by inhalation and dermal
exposures.
4.2.4.16 Dry Cleaned Clothing
Estimates of MOEs for acute inhalation and dermal exposures for the dry cleaned clothing consumer use
are presented in Table 4-108 and Table 4-109, respectively. Consumer inhalation and dermal exposures
were modeled as described in Section 2.4.2.4. Inhalation exposures are presented for users and
bystanders for 24-hour TWAs in Section 2.4.2.4.3 and dermal exposure results are presented for users as
acute ADRs in Section 2.4.2.4.2.
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Considering the overall strengths and limitations of the data, EPA's overall confidence is medium to
high for the consumer inhalation estimate and medium to high for the dermal estimate, as discussed in
Section 2.4.2.4.2.
Table 4-108. Risk Estimation for Acute, Non-Cancer Inhalation Exposures for Dry Cleaned
l-lxposure Seen;irio
Anile MIX for C\S F. Heels' (11 mii/mM
lienehniiirk MOI. = 10
I ser (Ariiill)
MOI.
IVtsfiinrier (Youili or Child)
MOI.
Stay-at-home Adult and Child
156
486
1 24 hrs HEC based on data from Altmann et al. (1990)
Table 4-109. Risk Estimation for Acute, Non-Cancer Dermal Exposures for Dry Cleaned Clothing
Consumer Use
Aeule IIFI) for ( \S Flfeels' (4
lienehniiirk MOI. =
.25 mii/k}i/(l;i\)
10
Ass limed dry
ele:inin<>
leeli n olo<>>
Dry C lciiiiiiiji
K\enls
l);i\s Al'ler l)i \
( leiininu
I ser. lliilf-lio(l>
MOI.
I ser. Full-limit
MOI.
2nd and 3rd
generation
Single
1
2
3
8.6
11
15
2.9
3.7
4.9
1
49
16
4th and 5th generation
Single
2
64
21
3
83
28
1
16
5.2
4th and 5th generation
Repeat2
2
20
6.7
3
26
8.7
1 HED extrapolated from inhalation exposures based on data from Altmann et al. (1990) described in Section 3.2.5.4.1
2 Based on maximum average PCE concentration in wool after 6 dry cleaning cycles from Sherlach (2011): PCE
concentration was still increasing in wool fabric after 6 cycles and had not yet reached saturation.
The MOEs are above the benchmark MOE for stay-at-home adults and children by inhalation. The
MOEs are above the benchmark MOE for users exposed to half-body garments one day after dry
cleaning, and full-body garments one to three days after dry cleaning for 2nd and 3rd generation dry
cleaning technologies, and below the benchmark MOE for users exposed to half-body garments two and
three days after dry cleaning for 2nd and 3rd generation dry cleaning technologies. The MOEs are above
benchmark MOE for users exposed to full-body garments one to three days after multiple dry cleaning
cycles for 4th and 5th generation dry cleaning technologies, and below the benchmarck MOE for users
exposed to half- and full-body garments, one to three days after dry cleaning, for single event and
multiple dry cleaning cycles, for 4th and 5th generation dry cleaning technologies.
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9878
9879
9880
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9888
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4.3 Assumptions and Key Sources of Uncertainty for Risk Characterization
4.3,1 Environmental Risk Characterization Assumptions and Key Sources of Uncertainty
PCE is toxic to aquatic organisms. The EPA has determined that data are sufficient to characterize the
environmental hazards of PCE and that the exposure pathways to the terrestrial environment are not
likely. The following uncertainties are associated with the hazard characterization. Assessment factors
(AFs) were used to calculate the acute and chronic COC for PCE. As described in Section 3.1.4, AFs
address the inter- and intra-species variability, as well as lab oratory-to-fi eld variability and are routinely
used within TSCA for assessing chemical hazards with limited environmental data. Additionally, AFs
account for potential data gaps in the literature in which data for more sensitive species were not
available. Use of AFs increases the confidence that the hazard characterizations were not
underestimated, resulting in false negative conclusions. Although the toxicity values for fish, and
invertebrates are relatively consistent, algae species tend to vary widely in their sensitivity to chemical
pollutants. Data were only available for three algal species and may not represent the most sensitive
species at a given site. Additionally, there were no PCE toxicity data available for amphibians.
Measured Surface Water Data and Watershed Analysis
The physical properties of PCE can lead to monitoring data showing limited occurrence in surface water.
PCE in surface waters can be expected to volatilize into the atmosphere. However, PCE is denser than
water and only slightly soluble in water. In soil and aquifers, it will tend to remain in the aqueous phase
and be transported to ground water.
WQX surface water monitoring data for the following years of 2013-2017 showed that PCE occurrence
was relatively low. For the 2016 data, only 4 monitoring sites had PCE concentrations above the
monitoring detection limit. The concentrations ranged from 1.4E-2 to 5.2E-2 |ig/L, which are below the
lowest COC of 1.4 |ig/L that is used in the ecological assessment.
When evaluating surface water monitoring data, it must be noted that EPA only looked at surface water
data that excluded other major sources of water data, e.g., drinking water, superfund sites, and ground
water. The quality of the data provided in the USGS-NWIS and STORET datasets varies, and some of
the information provided is non-quantitative. While a large number of individual sampling results were
obtained from these datasets, the monitoring studies used to collect the data were not specifically
designed to evaluate PCE distribution across the U.S. As a result, there are uncertainties in the reported
data that are difficult to quantify with regard to impacts on exposure estimates.
The available data represent a variety of discrete locations and time periods; therefore, it is unclear
whether the data are representative of other locations in the U.S.; however, this limitation does not
diminish the overall findings reported in this assessment, as the exposure data show very few instances
{i.e., less than 0.01 percent) where measured PCE levels in the ambient environment exceeded the
identified hazard benchmarks for aquatic organisms.
The surface water monitoring results were further validated through data acquired via EPA's systematic
review of surface water literature and biomonitoring data. Minimum results came from the systematic
review on PCE in surface water. Data from three U.S. studies indicated that PCE occurrence and related
concentrations in surface water were relatively low as well. The reported concentrations of PCE ranged
from below the detection limit and reported central tendency values ranging from <0.2 to 0.7 |ig/L
which is below the lowest COC of 1.4 |ig/L. The systematic review of biomonitoring data yielded three
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viable studies that contained PCE concentration measurements in blood. These studies did indicate that
PCE was detected moderately (37-60%) in samples evaluated. However, the concentration of PCE was
not higher than the detection limits of the respective studies.
Modeled Surface Water Concentrations
To further evaluate PCE exposure in surface water EPA modeled indirect and direct releases of PCE in
surface water by facilities. EPA modeled releasing facilities plus one industry with sites nationwide that
was obtained by three data sources (TRI, DMRs, and CDR) for the 2016 calendar year.
The modeled estimations of PCE releases and surface water monitoring data were merged and mapped
to reflect where PCE occurrence and related concentrations are with respect to each other in the U.S.
The maps show that there is minimum PCE exposure at the respective COC in regard to environmental
exposure assessment for aquatic species. The co-location of PCE releasing facilities and surface water
monitoring stations in an HUC were also mapped via geospatial analysis to illustrate both measured and
predicted concentrations PCE. The maps indicate that even though there are estimated releases from
facilities, some of which have concentrations higher than the COC, the data from monitoring stations are
not detecting PCE within the same HUC. It must be noted that the use geospatial analysis has a
limitation with the accuracy of the latitudes and longitudes therefore affecting placement of facilities and
monitoring stations.
4.3.2 Human Health Risk Characterization Key Assumptions and Uncertainties
4.3.2.1 Human Health Hazard Considerations
There is medium-high confidence in the acute non-cancer POD, high confidence in the chronic non-
cancer PODs selected to represent each health domain, and medium confidence in the cancer POD.
Confidence is reduced for dermal PODs due to the use of route-to-route extrapolation in the absence of a
dermal compartment in the PBPK model (Section 3.2.6.4). Major uncertainties include the selection of
cancer endpoint for IUR selection and inconclusive human evidence for a few health domains.
4.3.2.2 Occupational Risk Considerations
EPA estimated inhalation risk to workers and ONUs based on monitoring and/or modeling data, as
reasonably available. For the majority of OES, only one source was available so the results could not be
compared. Despite the absence of both types of data for most OES, overall confidence in worker
inhalation estimates ranged from Medium to High for all OES (Table 2-15). For ONUs, modeling or
monitoring data was available in 9 of 22 OES. For the other 13, in the absence of reasonably available
data EPA applied the worker central tendency estimates to ONUs. When ONU data was not available,
there is low confidence in ONU risk estimates. There is medium confidence in dermal exposure
estimates, which are based on the Dermal Exposure to Volatile Liquids Model (Section 2.4.1.29).
There are significant uncertainties associated with PPE usage across OES. For the majority of OES,
EPA assumes that workers will responsibly wear gloves and respirators and that employers implement a
continuing, effective respiratory protection program according to the requirements of OSHA's
Respiratory Protection Standard. This results in respiratory protection up to APF = 50 and glove
protection up to PF = 20 (or PF = 10 for commercial scenarios). Respiratory protection factors can be
confirmed through regular fit testing, however glove PFs represent a what-if scenario and EPA cannot
confirm the actual frequency, type, and effectiveness of globe use in specific workplaces with PCE
conditions of use. Risks may be underestimated by these assumptions. EPA also identified OES for
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which regular respirator use is not expected (Table 4-8), and risks may be overestimated for these
scenarios if even mild respiratory protection is employed.
4.3.2.3 Consumer Risk Considerations
There is medium to high or high confidence in both the consumer inhalation and dermal exposure
estimates (Section 2.4.2.6). All exposure estimates are based on modeling, and there is uncertainty based
on the application of surrogate product categories from the Westat survey (Westat 1987) when there was
not an exact match for the COU. Professional judgement was also required for determining the most
appropriate room of use, which affects the area volume and in turn inhalation exposure estimates. A key
uncertainty for the dermal estimates is the accuracy of the assumption of which COUs are likely to result
in exposure with impeded evaporation, and whether evaporation is truly fully impeded for those
scenarios.
EPA only evaluated acute risks for consumer COUs. While the expected sparse and intermittent use
frequency for the vast majority of users indicates that only acute risks are relevant to consumer uses,
there is uncertainty whether chronic risks may be of concern for consumers at the very high end of the
range for frequency of use, especially if a product is used several days consecutively. Without continued
consecutive use, chronic hazards are unlikely due to the relatively short half life of TCE (Section
3.2.2.1.3).
4.4 Other Risk Related Considerations
4,4,1 Potentially Exposed or Susceptible Subpopulations
TSCA requires that the determination of whether a chemical substance presents an unreasonable risk
include consideration of unreasonable risk to "a potentially exposed or susceptible subpopulation
identified as relevant to the risk evaluation" by EPA. 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."
EPA identified workers, ONUs, consumers, and bystanders as potentially exposed populations. EPA
provided risk estimates for workers and ONUs at both central tendency and high-end exposure levels for
all COUs. Consumer and bystander risk estimates were provided for low, medium, and high intensities
of use, accounting for differences in duration, weight fraction, and mass used. Occupational dermal risk
estimates were calculated for both average workers and women of childbearing age (see Draft Risk
Evaluation for Perchloroethylene Supplemental File: Occupational Exposure Risk Calculator (U.S.
EPA. 2020e)) and consumer dermal risk estimates were calculated for both adult and children (see Draft
Risk Evaluation for Perchloroethylene Consumer Dermal Risk Calculations ( 0b). EPA
determined that bystanders may include lifestages of any age. These groups exhibit differences in
delivered dose accounting for differing body weight and hand size, accounting for differences in
exposure, and providing risk estimates for women of childbearing age protects the susceptible
subpopulation of the developing fetus.
For inhalation exposures, risk estimates did not differ between sexes or across lifestages because both
exposures and inhalation hazard values are expressed as an air concentration. EPA expects that
variability in human physiological factors (e.g., breathing rate, body weight, tidal volume) which may
affect internal delivered concentration or dose is sufficiently accounted for through the use of a 1 Ox UF
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10002
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10009
10010
10011
10012
10013
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for human intraspecies variability, although some differences among lifestages or between working and
at-rest individuals may not have been accounted for by this value. EPA identified lifestage, biological
sex, genetic polymorphisms, race/ethnicity, preexisting health status, and lifestyle factors and nutrition
status as factors affecting biological susceptibility. Similarly, most but not all of these factors are
expected to be covered by the inclusion of a 1 Ox UFh.
EPA was unable to directly account for all possible PESS considerations and subpopulations in the risk
estimates. It is unknown whether the lOx UF to account for human variability will cover the full breadth
of human responses, and subpopulations with particular disease states or genetic predispositions may fall
outside of the range covered by this UF. As previously discussed, EPA also only considered acute
effects from consumer exposure. While typical use patterns are unlikely to result in any chronic effects
for the vast majority of consumers, EPA cannot rule out that consumers at very high frequencies of use
may be at risk for chronic hazards, especially if those consumers also exhibit biological susceptibilities.
EPA can also not rule out that certain subpopulations, whether due to very elevated exposure or
biological susceptibility, may be at risk for hazards that were not fully supported by the weight of
evidence or could not be quantified (e.g. immune and blood effects). However, in these circumstances
EPA assumes that these effects are likely to occur at a higher dose than more sensitive endpoints that
were accounted for by risk estimates.
4.4.2 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. Due to deference
to existing environmental statutes, administered by EPA, a detailed analysis of environmental pathways
to the general population was not deemed appropriate 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." In terms of this risk evaluation, the EPA considered sentinel exposure in the form of
a high-end screening level scenario for occupational exposure resulting from dermal and inhalation
exposures, as these exposure routes are the most likely to result in the highest exposure given the details
of the manufacturing process and the potential exposure scenarios discussed above. The calculation for
dermal exposure is especially conservative given that it assumes full contact/immersion.
4.5 Risk Conclusions
4.5.1 Environmental Risk Conclusions
Aquatic Pathways
Table 4-110 displays risk quotients for each of the facilities by COU. No risks were identified for
aquatic organisms from PCE release to surface water from the Maskants for Chemical Milling, Dry
Cleaning (Industrial and Commercial), Other Industrial, and Other Commercial Uses COUs. Based on
the data quality, uncertainties and weight of scientific evidence, confidence in the risk estimate is
medium.
Risks from acute PCE exposures were identified for aquatic organisms based on indirect releases from
the Incorporation into Formulations COU. Therefore, EPA concludes there is an acute risk to aquatic
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organisms from release ofPCE to surface water from facilities using PCE from the Incorporation into
Formulations COU. Based on the data quality, uncertainties and weight of scientific evidence,
confidence in the risk estimate is medium.
Risks from chronic PCE exposures were identified for aquatic organisms based on direct releases from
the Processing as a Reactant COU, and indirect releases from Incorporation into Formulations COU.
Therefore, EPA concludes there is a chronic risk to aquatic organisms from release of PCE to surface
water from facilities using PCE for the CO Us listed above. Based on the data quality, uncertainties and
weight of scientific evidence, confidence in the risk estimate is medium.
Risks from PCE exposures were identified for algae based on direct releases from the following COUs:
Manufacturing; Processing as a Reactant; Open-Top Vapor Degreasing; and Industrial Processing Aid.
In addition, indirect release (80% removal) from Manufacturing, Importing/Repackaging, Industrial
Processing Aid; Incorporation into Formulations; and Waste Handling, Disposal, Treatment, and
Recycling COUs resulted in risks to algae from PCE exposure. Therefore, EPA concludes there is a risk
to algae from release ofPCE to surface water from facilities using PCE for the COUs listed above.
Based on the data quality, uncertainties and weight of scientific evidence, confidence in the risk estimate
is medium.
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Table 4-110. Modeled Facilities Showing RQs and Days of Exceedance from the Release of PCE to Surface Water as Modeled in E-
Modeled
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
SWC
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
OES: Manufacturing
Acute
1,342
0
8.2E-5
0
0.1
Chronic
50
0
2.2E-3
Direct (0%
WWT
removal):
LA0000761
350
0.1 (max)
Algae
1.4
0
7.9E-2
Acute
1,342
0
1.7E-5
80
2.3E-2
Chronic
50
0
4.5E-5
Axiall
Surface
Water
or
POTW
Algae
1.4
0
1.6E-2
Corporation
Surface
Water
Acute
1,342
0
2.5E-5
Westlake, LA
Indirect (80%
0
3.4E-2
Chronic
50
0
6.8E-4
NPDES:
WWT
350
3.0E-2
Algae
1.4
0
2.4E-2
LA0000761
removal):
(avg)
Acute
1,342
0
8.2E-4
Organic
80
1.1
Chronic
50
0
2.2E-2
Chemicals
Mfg
Algae
1.4
0
0.8
Acute
1,342
0
4.6E-4
20
0.5
0
0.6
Chronic
50
0
1.2E-2
Algae
1.4
0
0.4
Acute
1,342
0
1.4E-2
0
18
Chronic
50
25
0.4
350
0.1 (max)
Algae
1.4
189
13
Direct and
Acute
1,342
0
2.8E-3
Greenchem
West Palm Beach,
FL
NPDES: None
(FRS
110056959634)
Indirect
Surrogate:
Organic
Chemicals
Mfg
80
3.7
Chronic
50
7
7.5E-2
Surface
Water
or
POTW
Algae
1.4
77
2.7
Surface
Water
Acute
1,342
0
4.1E-3
0
5.6
Chronic
50
11
0.1
350
3.0E-2
Algae
1.4
100
4.0
Receiving
Facility:
(avg)
Acute
1,342
0
8.3E-04
80
1.1
Chronic
50
1
2.2E-2
Unknown
Algae
1.4
37
0.8
Acute
1,342
0
7.4E-2
20
0.5
0
100
Chronic
50
4
2.0
Algae
1.4
17
71
Occidental
Surface
LA0002933
Surface
350
2.0E-3
0
8.1E-6
Acute
1,342
0
6.0E-9
Chemical Corp
Water
Water
Chronic
50
0
1.6E-7
Page 405 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Niimc. locution.
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Release
Media1'
Modeled
l';icili(\ oi*
Indusln
Seelor in H-
FAST1
EFAST
\\a(erl>od>
Tj pe'1
DjIJS ol
Release'
Release
\\ \\ 1
remo\al
0/
/<)
7Q10
SWC
(pph)-
COC Tjpe
coc
(|)|)b)
l)il>S ol
I'.xceedanee
(dajs/jear)'1
Risk
Quotient
Geismar Plant
Geismar, LA
NPDES:
LA0002933
Algae
1.4
0
5.8E-6
20
3.0E-2
0
1.2E-4
Acute
1,342
0
9.0E-8
Chronic
50
0
2.4E-6
Algae
1.4
0
8.6E-5
Olin Blue Cube
Freeport, TX
NPDES: None
(FRS
110066943605)
Non-
POTW
WWT
Receiving
Facility:
TX0006483
Surface
Water
350
4.0E-2
80
3.1E-3
Acute
1,342
0
2.3E-6
Chronic
50
0
2.3E-6
Algae
1.4
0
6.1E-5
20
0.7
80
5.6E-2
Acute
1,342
0
2.2E-3
Chronic
50
0
1.1E-3
Algae
1.4
0
4.2E-5
Solvents &
Chemicals
Pearland, TX
NPDES: Not
available
(TRI:
77588SLVNT470
4S)
Surface
Water
or
POTW
Direct and
Indirect
Surrogate:
Organic
Chemicals
Mfg
Receiving
Facility:
Unknown
Surface
Water
350
3.0E-4
(max)
0
5.6E-2
Acute
1,342
0
1.1E-3
Chronic
50
0
4.0E-2
Algae
1.4
2
4.0E-2
80
1.1E-3
Acute
1,342
0
4.1E-5
Chronic
50
0
1.1E-3
Algae
1.4
0
4.0E-2
350
1.0E-4
(avg)
0
1.9E-2
Acute
1,342
0
8.3E-7
Chronic
50
0
2.2E-5
Algae
1.4
0
7.9E-4
80
3.7E-3
Acute
1,342
0
1.4E-5
Chronic
50
0
3.7E-4
Algae
1.4
0
1.3E-2
20
2.0E-3
0
0.4
Acute
1,342
0
2.8E-6
Chronic
50
0
7.4E-5
Algae
1.4
1
0.3
UnivarUSA Inc
Redmond, WA
NPDES: None
(FRS:
110036000000)
Surface
Water
or
POTW
Direct and
Indirect
Surrogate:
Organic
Chemicals
Mfg
Receiving
Surface
Water
350
0.1 (max)
0
18
Acute
1,342
0
1.4E-2
Chronic
50
25
0.4
Algae
1.4
IX'J
13
80
3.7
Acute
1,342
0
2.8E-3
Chronic
50
7
7.4E-2
Algae
1.4
2.6
350
3.0E-2
(avg)
0
5.6
Acute
1,342
0
4.1E-3
Chronic
50
11
0.1
Page 406 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE
OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
SWC
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
Facility:
Unknown
Algae
1.4
100
4.0
80
1.1
Acute
1,342
0
8.3E-4
Chronic
50
1
2.2E-2
Algae
1.4
37
0.8
20
0.5
0
100
Acute
1,342
0
7.4E-2
Chronic
50
4
2.0
Algae
1.4
17
71
OES: Import/Repackaging
Chemtool
Rockton, IL
NPDES:
IL0064564
Surface
Water
IL0064564
Surface
Water
250
1.0E-3
0
1.5E-3
Acute
1,342
0
1.1E-6
Chronic
50
0
2.9E-5
Algae
1.4
0
1.0E-3
20
1.5E-2
0
2.2E-2
Acute
1,342
0
1.6E-5
Chronic
50
0
4.4E-4
Algae
1.4
0
1.6E-2
Harvey Terminal
Harvey, LA
NPDES:
LA0056600
Surface
Water
Surrogate
based on
location:
LA0005291
Surface
Water
250
1.0E-4
0
4.1E-07
Acute
1,342
0
3.0E-10
Chronic
50
0
8.1E-9
Algae
1.4
0
2.9E-7
20
1.0E-3
0
4.1E-06
Acute
1,342
0
3.0E-9
Chronic
50
0
8.1E-8
Algae
1.4
0
2.9E-6
Hubbard-Hall Inc
Waterbury, CT
NPDES: None
(FRS
110000317194
Non-
POTW
WWT
Surrogate:
Industrial
POTW (for
receiving
facility FRS
11000425054
1)
Surface
Water
250
1.1
80
29
Acute
1,342
0
2.2E-2
Chronic
50
16
0.6
Algae
1.4
230
21
20
14
80
360
Acute
1,342
0
0.27
Chronic
50
14
7.2
Algae
1.4
20
257
Vopak Terminal
Westwego Inc
Westwego, LA
NPDES:
LAO 124583
Surface
Water
Surrogate
based on
location:
LA0003093
Surface
Water
250
5.0E-3
0
2.1E-05
Acute
1,342
0
1.5E-8
Chronic
50
0
4.0E-7
Algae
1.4
0
1.4E-5
20
0.1
0
2.4E-04
Acute
1,342
0
1.8E-7
Chronic
50
0
4.9E-6
Algae
1.4
0
1.7E-4
OES: Processing as a Reactant
Page 407 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE
OR QUOTE
Niimc. locution.
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Release
Media1'
Modeled
l';icili(\ oi*
Indusln
Seelor in H-
FAST1
EFAST
\\a(erl>od>
Tj pe'1
DjIJS ol
Release'
Release
\\ \\ 1
remo\al
0/
/<)
7Q10
swe
(ppl))-
COC Tjpe
coc
(|)|)b)
l)il>S ol
I'.xceedanee
(dajs/jear)'1
Risk
Quotient
Akzo Nobel
Surface
Chemistry LLC
Morris, IL
NPDES:
IL0026069
Surface
Water
IL0026069
Surface
Water
350
1.0E-4
0
2.1E-4
Acute
1,342
0
1.6E-7
Chronic
50
0
4.2E-6
Algae
1.4
0
1.49E-04
20
2.5E-3
0
5.2E-3
Acute
1,342
0
3.88E-06
Chronic
50
0
1.04E-04
Algae
1.4
0
0.00372
Atkemix Ten Inc
Louisville, KY
NPDES:
KY0002780
Surface
Water
KY0002780
Surface
Water
350
7.0E-2
0
3.8E-3
Acute
1,342
0
2.79E-06
Chronic
50
0
7.50E-05
Algae
1.4
0
0.0027
20
1.3
0
6.9E-2
Acute
1,342
0
5.153E-05
Chronic
50
0
0.0014
Algae
1.4
0
0.049
Bayer
Corporation
Haledon, NJ
NPDES:
NJG104451
Surface
Water
Surrogate:
Organic
Chemical
MfgSIC
Surface
Water
350
4.0E-5
0
7.4E-3
Acute
1,342
0
5.51E-06
Chronic
50
0
1.48E-04
Algae
1.4
0
0.00528
20
5.0E-4
0
9.2E-2
Acute
1,342
0
6.88525E-05
Chronic
50
0
0.001848
Algae
1.4
0
0.066
Bayer
MaterialScience
New Martinsville,
WV
NPDES:
WV0005169
Surface
Water
WV0005169
Surface
Water
350
1.0E-3
0
1.2E-4
Acute
1,342
0
8.86736E-08
Chronic
50
0
2.38E-06
Algae
1.4
0
8.50E-05
20
0.013
0
1.6E-3
Acute
1,342
0
1.15E-06
Chronic
50
0
3.10E-05
Algae
1.4
0
0.0011
Chemtura North
and South Plants
Morgantown, WV
NPDES:
WV0004740
Surface
Water
WV0004740
Surface
Water
350
2.0E-5
0
2.9E-5
Acute
1,342
0
2.16E-08
Chronic
50
0
5.80E-07
Algae
1.4
0
2.07E-05
20
5.0E-4
0
7.3E-4
Acute
1,342
0
5.40E-07
Chronic
50
0
1.45E-05
Algae
1.4
0
5.18E-04
Dupont-Chemours
Montague Site
Montague, MI
Surface
Water
MI0000884
Still Water
350
2.0E-2
0
2.4
Acute
1,342
0
0.0018
Chronic
50
0
0.0484
Algae
1.4
"oil
1.73
Page 408 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE
OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
swc
(PI'b)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
NPDES:
MI0000884
20
0.3
0
35
Acute
1,342
0
0.026
Chronic
50
0
0.7014
Algae
1.4
20
25.05
Eagle US 2 LLC -
Lake Charles
Complex
Lake Charles, LA
NPDES:
LA0000761
Surface
Water
LA0000761
Surface
Water
350
1.3
0
1.5
Acute
1,342
0
1.1E-3
Chronic
50
0
3.0E-2
Algae
1.4
29
1.1
20
23
0
26
Acute
1,342
0
2.0E-2
Chronic
50
0
0.5
Algae
1.4
17
19
Flint Hills
Resources Corpus
Cliristi LLC - West
Plant
Corpus Cliristi, TX
NPDES:
TXU001146,
TX0006289
Surface
Water
TX0006289
Still Water
350
7.0E-2
0
3.0
Acute
1,342
0
2.2E-3
Chronic
50
0
6.0E-2
Algae
1.4
350
2.15
20
1.2
0
52
Acute
1,342
0
3.8E-2
Chronic
50
20
1.0
Algae
1.4
20
37
Flint Hills
Resources Pine
Bend LLC
Rosemount, MN
NPDES:
MN0070246,
MN0000418
Surface
Water
MN0000418
Surface
Water
350
1.0E-2
0
2.8E-3
Acute
1,342
0
2.1E-6
Chronic
50
0
5.7E-5
Algae
1.4
0
2.0E-3
20
0.2
0
5.7E-2
Acute
1,342
0
4.2E-5
Chronic
50
0
1.1E-3
Algae
1.4
0
4.0E-2
Honeywell
International Inc -
Geismar Complex
Geismar, LA
NPDES:
LA0006181
Surface
Water
LA0006181
Surface
Water
350
2.0E-2
0
8.1E-5
Acute
1,342
0
6.0E-8
Chronic
50
0
1.6E-6
Algae
1.4
0
5.8E-5
20
0.36
0
1.5E-3
Acute
1,342
0
1.1E-6
Chronic
50
0
2.9E-5
Algae
1.4
0
1.0E-3
Honeywell
International Inc-
Baton Rouge Plant
Surface
Water
LA0000329
Surface
Water
350
5.0E-2
0
4.9
Acute
1,342
0
3.7E-3
Chronic
50
0
9.9E-2
Algae
1.4
193
3.53
Page 409 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Niimc. locution.
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Release
Media1'
Modeled
l';icili(\ oi*
Indusln
Seelor in H-
FAST1
EFAST
\\a(erl>od>
Tj pe'1
DjIJS ol
Release'
Release
\\ \\ 1
remo\al
0/
/<)
7Q10
SWC
(pph)-
COC Tjpe
coc
(|)|)b)
l)il>S ol
I'.xceedanee
(dajs/jear)'1
Risk
Quotient
Baton Rouge, LA
NPDES:
LAR10E873,
LA0000329
20
0.9
0
85
Acute
1,342
0
6.0E-2
Chronic
50
7
1.7
Algae
1.4
:d
61
Indorama
Ventures Olefins,
LLC
Sulphur, LA
NPDES:
LA0069850
Surface
Water
Surrogate:
Organic
Chemical
MfgSIC
Surface
Water
350
1.0E-5
0
1.9E-3
Acute
1,342
0
1.4E-6
Chronic
50
0
3.7E-5
Algae
1.4
0
1.3E-3
20
2.0E-4
0
3.7E-2
Acute
1,342
0
2.8E-5
Chronic
50
0
7.4E-4
Algae
1.4
0
2.6E-2
Keeshan And
Bost Chemical
Co., Inc.
Manvel, TX
NPDES:
TX0072168
Surface
Water
TX0072168
Still Water
350
5.0E-5
0
5.0
Acute
1,342
0
3.7E-3
Chronic
50
0
0.1
Algae
1.4
"ou
3.6
20
1.0E-3
0
100
Acute
1,342
0
7.5E-2
Chronic
50
:d
2.0
Algae
1.4
2(1
71
Phillips 66 Lake
Charles Refinery
Westlake, LA
NPDES:
LAR05P540,
LA0003026
Surface
Water
LA0003026
Surface
Water
350
6.0E-2
0
9.5E-2
Acute
1,342
0
7.0E-5
Chronic
50
0
1.9E-3
Algae
1.4
0
6.8E-2
20
1.0
0
1.6
Acute
1,342
0
1.2E-3
Chronic
50
0
3.2E-2
Algae
1.4
1
1.2
Phillips 66 Los
Angeles Refinery
Wilmington Plant
Wilmington, CA
NPDES:
CA0000035
POTW
Receiving
Facility:
CA0053856
Still Water
350
0.1
80
0.3
Acute
1,342
0
2.4E-4
Chronic
50
0
6.4E-3
Algae
1.4
0
0.2
Premcor Refining
Group Inc Port
Arthur
Port Arthur, TX
Surface
Water
TX0005991
Surface
Water
350
0.1
0
2.0
Acute
1,342
0
1.5E-3
Chronic
50
0
4.0E-2
Algae
1.4
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
SWC
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
NPDES:
Algae
1.4
17
25
Solutia Nitro Site
Nitro. WV
NPDES:
WV0116181
Surface
Water
Surrogate:
WV0000868
Surface
Water
350
2.0E-4
0
5.9E-5
Acute
1,342
0
4.4E-8
Chronic
50
0
1.2E-6
Algae
1.4
0
4.2E-5
20
3.0E-3
0
8.8E-4
Acute
1,342
0
6.6E-7
Chronic
50
0
1.8E-5
Algae
1.4
0
6.3E-4
Solvay - Houston
Plant Houston,
TX
NPDES:
TX0007072
Surface
Water
TX0007072
Surface
Water
350
2.0E-2
0
3.7
Acute
1,342
0
2.8E-3
Chronic
50
0
7.4E-2
Algae
1.4
8
2.6
20
0.4
0
76
Acute
1,342
0
5.7E-2
Chronic
50
0
1.5
Algae
1.4
8
54
OES: Incorporation into Formulation
Lord Corp
Saegertown, PA
NPDES:
PA0101800
Non-
POTW
WWT
Surrogate:
Industrial
POTW
Surface
Water
300
5.3
80
136
Acute
1,342
1
0.1
Chronic
50
127
2.7
Algae
1.4
299
97
20
79
80
2034
Acute
1,342
5
1.5
Chronic
50
20
41
Algae
1.4
20
1453
Stepan Co
Millsdale Road
Elwood, IL
NPDES:
IL0002453
Surface
Water
IL0002453
Surface
Water
300
2.0E-3
0
8.4E-4
Acute
1,342
0
1.5E-6
Chronic
50
0
4.0E-5
Algae
1.4
0
1.4E-3
20
2.5E-2
0
1.1E-2
Acute
1,342
0
7.8E-6
Chronic
50
0
2.1E-4
Algae
1.4
0
7.5E-3
Tesoro Los
Angeles Refinery-
Carson
Operations
Carson, CA
POTW
Receiving
Facility:
CA0053813
Still Water
300
0.3
80
2.7E-4
Acute
1,342
0
2.0E-7
Chronic
50
0
5.3E-6
Algae
1.4
0
1.9E-4
Page 411 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
SWC
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
NPDES:
CA0000680
Weatherford
Aerospace LLC
Weatherford, TX
NPDES: None
(FRS 110000743740)
POTW
Receiving
Facility:
TX0047724
Surface
Water
300
2.0E-3
80
6.5E-2
Acute
1,342
0
4.9E-5
Chronic
50
0
1.3E-3
Algae
1.4
0
4.7E-2
OES: Open Top Vapor Degreasing
601 Nassau St
Assoc LLC
North Brunswick
Twp, NJ
NPDES:
NJG129127
Surface
Water
Surrogate:
Primary
Metal
Forming
Manufacture
Surface
Water
260
1.0E-5
0
1.1E-3
Acute
1,342
0
8.3E-7
Chronic
50
0
2.2E-5
Algae
1.4
0
7.9E-4
20
1.0E-3
0
0.1
Acute
1,342
0
8.2E-5
Chronic
50
0
2.2E-3
Algae
1.4
2
7.9E-2
ASCO Valve
Manufacturing
Aiken, SC
NPDES:
SC0049026
Surface
Water
SC0049026
Surface
Water
260
1.0E-4
0
l.E-2
Acute
1,342
0
8.3E-6
Chronic
50
0
2.2E-4
Algae
1.4
7
7.9E-3
20
1.9E-3
0
0.2
Acute
1,342
0
1.6E-4
Chronic
50
0
4.2E-3
Algae
1.4
2
0.2
Chemours -
Beaumont Works
Beaumont, TX
NPDES:
TX0004669
Surface
Water
TX0004669
Surface
Water
260
1.0E-2
0
1.4E-2
Acute
1,342
0
1.1E-5
Chronic
50
0
2.8E-4
Algae
1.4
0
1.0E-2
20
8.4E-2
0
0.1
Acute
1,342
0
8.9E-5
Chronic
50
0
2.4E-3
Algae
1.4
0
8.6E-2
Delphi Harrison
Thermal Systems
Dayton, OH
NPDES:
OH0009431
Surface
Water
OH0009431
Surface
Water
260
1.0E-2
0
1.9E-2
Acute
1,342
0
1.4E-5
Chronic
50
0
3.8E-4
Algae
1.4
0
1.3E-2
20
8.4E-2
0
0.2
Acute
1,342
0
1.2E-4
Chronic
50
0
3.2E-3
Algae
1.4
0
0.1
Still Water
260
1.0E-2
0
0.2
Acute
1,342
0
1.5E-4
Page 412 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
SWC
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
Equistar
Chemicals LP
La Porte, TX
NPDES:
TXO119792
Surrogate:
TX0002836
Chronic
50
0
4.0E-3
Algae
1.4
0
0.1
20
0.2
0
3.2
Acute
1,342
0
2.4E-3
Chronic
50
0
6.5E-2
Algae
1.4
20
2.3
Fairfield Works
Fairfield, AL
NPDES:
AL0003646
Surface
Water
AL0003646
Surface
Water
260
4.0E-3
0
5.1E-3
Acute
1,342
0
3.7E-6
Chronic
50
0
1.0E-4
Algae
1.4
0
3.6E-3
20
5.3E-2
0
6.7E-2
Acute
1,342
0
5.0E-5
Chronic
50
0
1.3E-3
Algae
1.4
0
4.8E-2
Gayston Corp
Dayton, OH
NPDES:
OHO 127043
POTW
Surrogate:
Primary
Metal
Fonning
Manufacture
Surface
Water
260
3.0E-3
0
0.3
Acute
1,342
0
2.5E-4
Chronic
50
5
6.6E-3
Algae
1.4
25
0.2
20
4.1E-2
0
4.6
Acute
1,342
0
3.4E-3
Chronic
50
2
9.1E-2
Algae
1.4
8
3.26
Getzen Co Inc
Elkhorn, WI
NPDES: None
(FRS11000041729
1)
POTW
Surrogate:
Primary
Metal
Fonning
Manufacture
Surface
Water
260
3.0E-4
80
6.7E-3
Acute
1,342
0
5.0E-6
Chronic
50
0
1.3E-4
Algae
1.4
3
4.8E-3
GM Components
Holdings LLC
Lockport, NY
NPDES:
NY0000558
Surface
Water
NY0000558
Surface
Water
260
7.0E-2
0
5.9
Acute
1,342
0
4.4E-3
Chronic
50
0
0.1
Algae
1.4
131
4.2
20
0.9
0
78
Acute
1,342
0
5.8E-2
Chronic
50
3
1.6
Algae
1.4
20
55.46
HB Fuller Co
Morris, IL
Surface
Water
Surrogate:
Primary
Metal
Surface
Water
260
1.0E-3
0
0.1
Acute
1,342
0
8.2E-5
Chronic
50
1
2.2E-3
Algae
1.4
21
7.9E-2
Page 413 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Niimc. locution.
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Release
Media1'
Modeled
l';icili(\ oi*
Indusln
Seelor in I-'.-
FAST1
EFAST
\\a(erl>od>
Tj pe'1
DjIJS ol
Release'
Release
\\ \\ 1
remo\al
0/
/<)
7Q10
swe
(ppl))-
COC Tjpe
coc
(|)|)b)
l)il>S ol
I'.xceedanee
(dajs/jear)'1
Risk
Quotient
NPDES:
IL0079758
Forming
Manufacture
20
1.0E-2
0
1.1
Acute
1,342
0
8.3E-4
Chronic
50
1
2.2E-2
Algae
1.4
3
0.8
Hyster-Yale
Group, Inc
Sulligent, AL
NPDES:
AL0069787
Surface
Water
Surrogate:
Primary
Metal
Forming
Manufacture
Surface
Water
260
1.0E-6
0
1.1E-4
Acute
1,342
0
8.3E-8
Chronic
50
0
2.22E-6
Algae
1.4
0
7.9E-05
20
1.2E-5
0
1.3E-3
Acute
1,342
0
9.7E-7
Chronic
50
0
2.6E-5
Algae
1.4
0
9.3E-4
MEMC Electronic
Materials
Incorporated
Moore, SC
NPDES:
SC0036145
Surface
Water
SC0036145
Surface
Water
260
3.0E-4
0
1.0E-2
Acute
1,342
0
7.5E-6
Chronic
50
0
2.0E-4
Algae
1.4
0
7.2E-3
20
3.4E-3
0
0.1
Acute
1,342
0
8.2E-5
Chronic
50
0
2.2E-3
Algae
1.4
0
7.9E-2
Piano Factory-
Grand Haven
Grand Haven, MI
NPDES:
MI0054399
Surface
Water
Surrogate:
Primary
Metal
Forming
Manufacture
Surface
Water
260
1.0E-3
0
0.1
Acute
1,342
0
8.2E-5
Chronic
50
1
2.2E-3
Algae
1.4
21
7.9E-2
20
9.3E-3
0
1.0
Acute
1,342
0
7.7E-4
Chronic
50
1
2.1E-2
Algae
1.4
3
0.7
Rex Heat Treat
Lansdale Inc
Lansdale, PA
NPDES:
PA0052965
Surface
Water
Surrogate:
PA0026182
Surface
Water
260
2.0E-3
0
5.4E-2
Acute
1,342
0
4.0E-5
Chronic
50
0
1.1E-3
Algae
1.4
0
0.03.9E-2
20
2.5E-2
0
0.7
Acute
1,342
0
5.0E-4
Chronic
50
0
1.3E-2
Algae
1.4
0
0.5
Styrolution
America LLC
Channahon, IL
Surface
Water
IL0001619
Surface
Water
260
1.0E-5
0
3.5E-6
Acute
1,342
0
2.6E-9
Chronic
50
0
6.9E-8
Algae
1.4
0
2.5E-6
Page 414 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
SWC
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
NPDES:
IL0001619
20
8.3E-3
0
2.9E-3
Acute
1,342
0
2.2E-6
Chronic
50
0
5.8E-5
Algae
1.4
0
2.1E-3
Trane Residential
Solutions - Fort
Smith
Fort Smith, AR
NPDES:
AR0052477
Surface
Water
Surrogate:
Primary
Metal
Forming
Manufacture
Surface
Water
260
1.0E-5
0
1.1E-3
Acute
1,342
0
8.3E-7
Chronic
50
0
2.2E-5
Algae
1.4
0
7.9E-4
20
1.7E-4
0
1.9E-2
Acute
1,342
0
1.4E-5
Chronic
50
0
3.8E-4
Algae
1.4
1
1.4E-2
US Steel Fairless
Hills Facility
Fairless Hills, PA
NPDES:
PA0013463
Surface
Water
PA0013463
Surface
Water
260
1.0E-3
0
1.7E-4
Acute
1,342
0
1.2E-7
Chronic
50
0
3.3E-6
Algae
1.4
0
1.2E-4
20
1.3E-2
0
2.2E-3
Acute
1,342
1.6E-6
Chronic
50
0
4.3E-5
Algae
1.4
0
1.5E-3
OES: Dry Cleaninj
i (Commercial and Industrial)
12,822
Commercial Dry
cleaning Sites
Surrogate:
Laundry/Dry
Cleaner SIC
Surface
Water
307
2.0E-2
(high-end)
80
0.4
Acute
1,342
0
2.8E-4
Chronic
50
0
7.6E-3
Algae
1.4
0
0.3
289
1.0E-3
(central
tendency)
80
0.2
Acute
1,342
0
1.4E-4
Chronic
50
0
3.8E-3
Algae
1.4
0
0.1
Boise State
University
Boise, ID
NPDES:
IDG911006
Surface
Water
Surrogate:
Laundry/Dry
Cleaner SIC
Surface
Water
289
2.0E-4
(high-end)
0
0.1
Acute
1,342
0
8.2E-5
Chronic
50
0
2.2E-3
Algae
1.4
0
7.9E-2
307
2.0E-4
(central
tendency)
0
0.1
Acute
1,342
0
8.2E-5
Chronic
50
0
0.002.2E-3
Algae
1.4
0
7.9E-2
20
3.0E-3
0
1.7
Acute
1,342
0
1.3E-3
Chronic
50
0
3.4E-2
Algae
1.4
1
1.2
Page 415 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Niimc. locution.
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Release
Media1'
Modeled
l';icili(\ oi*
Indusln
Seelor in I-'.-
FAST1
EFAST
\\a(erl>od>
Tj pe'1
DjIJS ol
Release'
Release
(kii/d;i>)'
\\ \\ 1
remo\al
0/
/<)
7Q10
SWC
(pph)-
COC Tjpe
coc
(|)|)b)
l)il>S ol
I'.xceedanee
(dajs/jear)'1
Risk
Quotient
Unifirst
Williamstown,
VT
NPDES:
VT0000850
Surface
Water
Surrogate:
Laundry/Dry
Cleaner SIC
Surface
Water
289
5.0E-5
(high-end)
0
2.8E-2
Acute
1,342
0
2.1E-5
Chronic
50
0
5.7E-4
Algae
1.4
0
0.2
307
4.0E-5
(central
tendency)
0
2.3E-2
Acute
1,342
0
1.7E-5
Chronic
50
0
4.5E-4
Algae
1.4
0
1.6E-2
20
6.8E-4
0
0.4
Acute
1,342
0
2.9E-4
Chronic
50
0
7.8E-3
Algae
1.4
0
0.3
OI'.S: ( homiciil Miiskiinl
Alliant
Techsy stems
Operations LLC
Elkton, MD
NPDES:
MD0000078
Surface
Water
MD0000078
Surface
Water
172
5.8E-6
0
5.3E-4
Acute
1,342
0
4.0E-7
Chronic
50
0
1.1E-5
Algae
1.4
0
3.8E-4
20
5.0E-5
0
4.6E-3
Acute
1,342
0
3.4E-6
Chronic
50
0
9.2E-5
Algae
1.4
0
3.3E-3
Ducommun
Aerostructures Inc
Orange Facility
Orange, CA
NPDES: None
(110070089239)
POTW
Surrogate:
Metal
Finishing SIC
(surrogate for
receiving
facility
CAO110604)
Surface
Water
172
2.6E-3
80
6.8E-2
Acute
1,342
0
5.0E-5
Chronic
50
0
1.4E-3
Algae
1.4
0
4.8E-2
GE Aviation
Lynn, MA
NPDES:
MA0003905
Surface
Water
MA0003905
Still Water
172
8.7E-4
0
3.7E-3
Acute
1,342
0
2.8E-6
Chronic
50
0
7.4E-5
Algae
1.4
0
2.6E-3
20
7.5E-3
0
3.2E-2
Acute
1,342
0
2.4E-5
Chronic
50
0
6.4E-4
Algae
1.4
0
2.2E-2
McCanna Inc.
Carpentersville,
IL
Surface
Water
Surrogate:
Metal
Finishing SIC
Surface
Water
172
4.1E-4
0
0.2
Acute
1,342
0
1.3E-4
Chronic
50
0
3.4E-3
Algae
1.4
0
0.1
20
3.5E-3
0
1.3
Acute
1,342
0
9.9E-4
Page 416 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE
OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
SWC
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
NPDES:
IL0071340
Chronic
50
0
2.7E-2
Algae
1.4
0
1.0
Weatherford
Aerospace LLC
Weatherford, TX
NPDES: None
(FRS
110000743740)
POTW
Receiving
Facility:
TX0047724
Surface
Water
208
1.1E-2
80
0.3
Acute
1,342
0
2.1E-4
Chronic
50
0
5.6E-3
Algae
1.4
0
0.2
OES: Industrial Processing Aid
Chevron Products
Co - Salt Lake
Refinery Salt
Lake City, UT
NPDES:
UTG070261,
UT0000175
Surface
Water
UT0000175
Surface
Water
300
1.0E-2
0
0.3
Acute
1,342
0
2.3E-4
Chronic
50
0
6.2E-3
Algae
1.4
0
0.2
20
8.7E-2
0
2.7
Acute
1,342
0
2.0E-3
Chronic
50
0
5.4E-2
Algae
1.4
0
1.9
Chevron Products
Co Richmond
Refinery
Riclunond, CA
NPDES:
CA0005134
Surface
Water
CA0005134
Surface
Water
300
3.0E-3
0
0.2
Acute
1,342
0
1.3E-4
Chronic
50
0
3.4E-3
Algae
1.4
0
0.1
20
4.6E-2
0
2.7
Acute
1,342
0
2.0E-3
Chronic
50
0
5.3E-2
Algae
1.4
20
1.9
CHS McPherson
Refinery
McPherson, KS
NPDES:
KS0000337
Surface
Water
KS0000337
Surface
Water
300
3.0E-4
0
4.4E-2
Acute
1,342
0
3.3E-5
Chronic
50
0
8.8E-4
Algae
1.4
0
3.2E-2
20
4.5E-3
0
0.7
Acute
1,342
0
4.9E-4
Chronic
50
0
1.3E-2
Algae
1.4
0
0.5
ExxonMobil Oil
Beaumont
Refinery
Beaumont, TX
NPDES: None
Surface
Water
TX0068934
Surface
Water
300
20E-2
0
5.5
Acute
1,342
0
4.1E-3
Chronic
50
0
0.11
Algae
1.4
55
4.0
20
0.4
0
97
Acute
1,342
0
7.2E-2
Chronic
50
2
1.9
Algae
1.4
20
69
Page 417 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Niimc. locution.
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Release
Media1'
Modeled
l';icili(\ oi*
Indusln
Seelor in H-
FAST1
EFAST
\\a(erl>od>
Tj pe'1
DjIJS ol
Release'
Release
\\ \\ 1
remo\al
0/
/<)
7Q10
SWC
(pph)-
COC Tjpe
coc
(|)|)b)
l)il>S ol
I'.xceedanee
(dajs/jear)'1
Risk
Quotient
(IKS
110056963683)
HollyFrontier El
Dorado Refining
LLC
El Dorado, KS
NPDES:
KS0000761
Surface
Water
KS0000761
Surface
Water
300
3.0E-3
0
0.6
Acute
1,342
0
4.4E-4
Chronic
50
0
1.2E-2
Algae
1.4
2
0.4
20
4.6E-2
0
9.1
Acute
1,342
0
6.8E-3
Chronic
50
0
0.2
Algae
1.4
6
6.5
Hunt Refining Co
- Tuscaloosa
Refinery
Tuscaloosa, AL
NPDES:
AL0000973
Surface
Water
AL0000973
Surface
Water
300
1.1E-2
0
3.3E-2
Acute
1,342
0
2.5E-5
Chronic
50
0
6.6E-4
Algae
1.4
0
2.4E-2
20
0.2
0
0.7
Acute
1,342
0
4.9E-4
Chronic
50
0
1.3E-2
Algae
1.4
0
0.5
Marathon
Petroleum Co LP
Garyville, LA
NPDES:
LAU009485,
LA0045683
Surface
Water
LA0045683
Still Water
300
1.0E-2
0
0.5
Acute
1,342
0
3.5E-4
Chronic
50
0
9.4E-3
Algae
1.4
0
0.3
20
0.1
0
6.6
Acute
1,342
0
4.9E-3
Chronic
50
0
0.1
Algae
1.4
2(1
4.7
Occidental
Chemical Corp
Niagara Plant
Niagara Falls, NY
NPDES:
NY0003336
Surface
Water
and
POTW
Direct (0%
WWT
Removal):
NY0003336
Indirect (80%
WWT
Removal):
Organic
Chemicals
Mfg
(surrogate for
NY0026336)
Still Water
300
0.2
0
1.3
Acute
1,342
0
9.0L-4
Chronic
50
0
2.6E-2
Algae
1.4
0
0.9
Surface
Water
300
0.2
80
6.3
Acute
1,342
0
4.7E-3
Chronic
50
11
0.1
Algae
1.4
4.5
Still Water
20
2.6
0
20
Acute
1,342
0
1.5E-2
Chronic
50
0
0.4
Algae
1.4
:n
14
300
3.0E-2
0
12
Acute
1,342
0
8.9E-3
Page 418 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
SWC
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
Tesoro Los
Angeles Refinery-
Carson
Operations
Carson, CA
NPDES:
CA0000680
Surface
Water
and
POTW
Direct (0%
WWT
removal):
Petroleum
Refining
Indirect (80%
WWT
removal):
CA0053813
Surface
Water
Chronic
50
17
0.2
Algae
1.4
169
8.5
Surface
Water
300
3.0E-2
80
2.4E-5
Acute
1,342
0
1.8E-8
Chronic
50
0
4.8E-7
Algae
1.4
0
1.7E-5
Surface
Water
20
0.4
0
171
Acute
1,342
1
0.1
Chronic
50
7
3.4
Algae
1.4
19
122
The Dow
Chemical Co
Midland, MI
NPDES:
MI0000868
Surface
Water
MI0000868
Surface
Water
300
3.0E-2
0
4.8E-2
Acute
1,342
0
3.5E-5
Chronic
50
0
9.5E-4
Algae
1.4
0
3.4E-2
20
0.5
0
0.8
Acute
1,342
0
6.1E-4
Chronic
50
0
1.6E-2
Algae
1.4
1
0.6
Valero Refining
Co -Oklahoma
Valero Ardmore
Refinery
Ardmore, OK
NPDES:
OK0001295
Surface
Water
OK0001295
Surface
Water
300
1.0E-2
0
0.7
Acute
1,342
0
4.8E-4
Chronic
50
0
1.3E-2
Algae
1.4
6
0.5
20
0.1
0
7.1
Acute
1,342
0
5.3E-3
Chronic
50
0
0.1
Algae
1.4
9
5.1
Valero Refining
Co -Oklahoma
Valero Ardmore
Refinery
Ardmore, OK
NPDES:
OK0001295
Surface
Water
Surrogate:
Organic
Chemicals
Mfg
Surface
Water
300
1.0E-2
0
1.9
Acute
1,342
0
1.4E-3
Chronic
50
2
3.7E-2
Algae
1.4
42
1.3
20
0.1
0
26
Acute
1,342
0
1.9E-2
Chronic
50
2
0.5
Algae
1.4
12
18
OES: Other Industrial Uses
ExxonMobil Oil
Corp Joilet
Refinery
Channahon IL
Surface
Water
ILR10H432
Surface
Water
250
5.0E-3
0
1.7E-3
Acute
1,342
0
1.3E-6
Chronic
50
0
3.5E-5
Algae
1.4
0
1.2E-3
20
5.9E-2
0
2.1E-2
Acute
1,342
0
1.5E-5
Page 419 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Modeled
Niimc. locution.
Release
Media1'
l';icili(\ oi*
EFAST
DjIJS ol
Release'
Release
\\ \\ 1
7Q10
coc
(|)|)b)
l)il\S ol
Risk
Quotient
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Indusln
Seelor in H-
FAST1
\\a(erl>od>
Tj pe'1
remo\al
0/
/<)
swe
(ppl))-
COC Tjpe
I'.xceedanee
(dajs/jear)'1
NPDES:
Chronic
50
0
4.1E-4
ILR10H432
Algae
1.4
0
1.5E-2
Natrium Plant
New Martinsville,
WV
NPDES:
WV0004359
Acute
1,342
0
2.7E-6
250
3.0E-2
0
3.6E-3
Chronic
50
0
7.1E-5
Surface
WV0004359
Surface
Algae
1.4
0
2.6E-3
Water
Water
Acute
1,342
0
3.5E-5
20
0.4
0
4.6E-2
Chronic
50
0
9.3E-4
Algae
1.4
0
3.3E-2
Oxy Vinyls LP -
Deer Park PVC
Deer Park, TX
NPDES:
TX0007412
Acute
1,342
0
7.5E-4
250
0.3
0
1.0
Chronic
50
0
2.0E-2
Surface
TX0007412
Surface
Algae
1.4
38
0.7
Water
Water
Acute
1,342
0
9.4E-3
20
3.9
0
13
Chronic
50
0
0.3
Algae
1.4
17
9.0
Princeton Plasma
Physics Lab (FF)
Princeton, NJ
NPDES:
NJ0023922
Acute
1,342
0
9.7E-5
Surrogate:
Industrial
POTW
250
1.0E-3
0
0.1
Chronic
50
0
2.6E-3
Surface
Surface
Algae
1.4
0
9.3E-2
Water
Water
Acute
1,342
0
6.3E-4
20
6.6E-3
0
0.9
Chronic
50
0
1.7E-2
Algae
1.4
1
0.6
Tree Top Inc
Wenatchee Plant
Wenatchee, WA
NPDES:
WA0051527
Acute
1,342
0
2.9E-6
250
3.0E-5
0
3.9E-3
Chronic
50
0
7.7E-5
Surface
Industrial
Surface
Algae
1.4
0
2.8E-3
Water
POTW
Water
Acute
1,342
0
3.6E-5
20
3.8E-4
0
4.9E-2
Chronic
50
0
9.8E-4
Algae
1.4
0
3.5E-2
Vesuvius USA
Acute
1,342
0
9.7E-5
Corp Buffalo
Surrogate:
Industrial
POTW
250
1.0E-3
0
0.1
Chronic
50
0
2.6E-3
Plant
Surface
Surface
Algae
1.4
0
9.3E-2
Buffalo, NY
Water
Water
Acute
1,342
0
1.4E-4
NPDES:
20
1.5E-3
0
0.2
Chronic
50
0
3.8E-3
NY0030881
Algae
1.4
0
0.1
CA0059188
250
1.0E-6
0
0.1
Acute
1,342
0
7.5E-5
Page 420 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Name, Location,
and ID of Active
Releaser Facility"
Release
Mediab
Modeled
Facility or
Industry
Sector in E-
FASTC
EFAST
Waterbody
Typed
Days of
Release6
Release
(kg/day)f
WWT
removal
%
7Q10
swc
(ppb)g
COC Type
COC
(ppb)
Days of
Exceedance
(days/year)11
Risk
Quotient
William E. Warne
Power Plant
Los Angeles
County, CA
NPDES:
CA0059188
Surface
Water
Surface
Water
Chronic
50
0
2.0E-3
Algae
1.4
0
7.1E-2
20
1.4E-5
0
1.4
Acute
1,342
0
1.1E-3
Chronic
50
0
2.8E-2
Algae
1.4
0
1.1
OES: Other Commercial Uses
Union Station
North Wing Office
Building
Denver, CO
NPDES:
COG315293
Surface
Water
Surrogate:
Industrial
POTW
Surface
Water
250
3.0E-3
0
0.4
Acute
1,342
0
2.9E-4
Chronic
50
0
7.8E-3
Algae
1.4
4
0.3
20
3.6E-2
0
4.6
Acute
1,342
0
3.5E-3
Chronic
50
0
9.3E-2
Algae
1.4
10
3.3
Confluence Park
Apartments
Denver, CO
NPDES:
COG315339
Surface
Water
Surrogate:
Industrial
POTW
Surface
Water
250
3.0E-4
0
3.9E-2
Acute
1,342
0
2.9E-5
Chronic
50
0
7.7E-4
Algae
1.4
0
2.8E-2
20
3.7E-3
0
0.5
Acute
1,342
0
3.6E-4
Chronic
50
0
9.6E-3
Algae
1.4
0
0.3
Wynkoop Denver
LLCP St
Denver, CO
NPDES:
COG603115
Surface
Water
Surrogate:
Industrial
POTW
Surface
Water
250
2.0E-4
0
2.6E-2
Acute
1,342
0
1.9E-5
Chronic
50
0
5.2E-4
Algae
1.4
0
1.8E-2
20
1.9E-3
0
0.2
Acute
1,342
0
1.8E-4
Chronic
50
0
4.8E-3
Algae
1.4
0
0.2
100 Saint Paul
Denver County,
CO
NPDES:
COG315289
Surface
Water
Surrogate:
Industrial
POTW
Surface
Water
250
4.0E-5
0
5.2E-3
Acute
1,342
0
3.8E-6
Chronic
50
0
1.0E-4
Algae
1.4
0
3.7E-3
20
5.3E-4
0
6.8E-2
Acute
1,342
0
5.1E-5
Chronic
50
0
1.4E-3
Algae
1.4
0
4.9E-2
BPI-Westminster,
LLC(Owner)/Arc
Surface
Water
Surface
Water
250
3.0E-5
0
3.9E-3
Acute
1,342
0
2.9E-6
Chronic
50
0
7.7E-5
Page 421 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE
OR QUOTE
Modeled
Niimc. locution.
Release
Media1'
l';icili(\ oi*
EFAST
DjIJS ol
Release'
Release
(kti/d;i\)'
\\ \\ 1
7Q10
coc
(ppl>)
l)il\S ol
Risk
Quolii'iU
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Indusln
Seelor in I-'.-
FAST1
\\a(erl>od>
Tj pe'1
remo\al
0/
/<)
SWC
(pph)-
COC Tjpe
l-'.xeeedanee
ulajs/jear)1'
adis (Op) Denver,
Surrogate:
Industrial
POTW
Algae
1.4
0
2.8E-3
CO
Acute
1,342
0
4.1E-5
NPDES:
20
4.3E-4
0
5.5E-2
Chronic
50
0
1.1E-3
COG315146
Algae
1.4
0
4.0E-2
Acute
1,342
0
1.9E-6
Safeway Inc
Surrogate:
Industrial
POTW
250
2.0E-5
0
2.6E-3
Chronic
50
0
5.2E-5
Denver, CO
Surface
Surface
Algae
1.4
0
1.8E-3
NPDES:
Water
Water
Acute
1,342
0
1.9E-5
COG315260
20
2.0E-4
0
2.6E-2
Chronic
50
0
5.2E-4
Algae
1.4
0
1.8E-2
Illinois Central
Acute
1,342
0
9.6E-7
Railroad
Surrogate:
Industrial
POTW
250
1.0E-5
0
1.3E-3
Chronic
50
0
2.6E-5
Thompsonville,
Surface
Surface
Algae
1.4
0
9.2E-4
IL
Water
Water
Acute
1,342
0
1.5E-5
NPDES:
20
1.6E-4
0
2.1E-2
Chronic
50
0
4.1E-4
IL0070696
Algae
1.4
0
1.5E-2
OI-'.S: \\;isio Ihindlin^. l)ispos;il. Tiv;ilim*nl.
iihI Uccvcliii'j
Clean Harbors
Deer Park LLC
La Porte, TX
NPDES:
TX0005941
Acute
1,342
0
6.7E-3
Non-
POTW
WWT
Surrogate:
Industrial
POTW
250
0.4
80
9.1
Chronic
50
2
0.2
Surface
Algae
1.4
r:
6.4
Water
Acute
1,342
0
8.4E-2
20
4.4
80
113
Chronic
50
7
2.3
Algae
1.4
:
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Niimc. locution.
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Release
Media1'
Modeled
l';icili(\ oi*
Indusln
Seelor in H-
FAST1
EFAST
\\a(erl>od>
Tj pe'1
DjIJS ol
Release'
Release
\\ \\ 1
remo\al
0/
/<)
7Q10
SWC
(pph)-
COC Tjpe
coc
(|)|)b)
l)il>S ol
I'.xceedanee
(dajs/jear)'1
Risk
Quotient
NPDES: None
(FRS 110070118494)
Algae
1.4
0
2.3E-4
Clean Water Of
New York Inc
Staten Island, NY
NPDES:
NY0200484
Surface
Water
Surrogate:
Industrial
POTW SIC
code
Surface
Water
250
4.0E-3
0
0.5
Acute
1,342
0
3.9E-4
Chronic
50
0
1.0E-2
Algae
1.4
7
0.4
20
4.7E-2
0
6.1
Acute
1,342
0
4.5E-3
Chronic
50
0
0.1
Algae
1.4
11
4.3
Clifford G Higgins
Disposal Service
Inc SLF
Kingston, NJ
NPDES:
NJG160946
Surface
Water
Surrogate:
Industrial
POTW SIC
code
Surface
Water
250
2.0E-4
0
2.6E-2
Acute
1,342
0
1.9E-5
Chronic
50
0
5.2E-4
Algae
1.4
0
1.8E-2
20
2.5E-3
0
0.3
Acute
1,342
0
2.4E-4
Chronic
50
0
6.4E-3
Algae
1.4
0
0.2
Durez North
Tonawanda
Occidental
Chemical
Corporation
North Tonawanda,
NY
NPDES:
NY0001198
Surface
Water
NY0001198
Surface
Water
250
1.0E-4
0
5.3E-2
Acute
1,342
0
4.0E-5
Chronic
50
0
1.1E-3
Algae
1.4
0
3.8E-2
20
5.0E-4
0
0.3
Acute
1,342
0
2.0E-4
Chronic
50
0
5.4E-3
Algae
1.4
0
0.2
Heritage Thermal
Services
East Liverpool, OH
NPDES:
OHO 107298
POTW
Receiving
Facility:
OH0024970
Surface
Water
250
3.6E-7
80
9.7E-9
Acute
1,342
0
7.2E-12
Chronic
50
0
1.9E-10
Algae
1.4
0
6.9E-9
Oiltanking
Houston Inc
Houston, TX
NPDES:
TX0091855
Surface
Water
Surrogate
location:
TX0005941
Surface
Water
250
3.0E-3
0
0.3
Acute
1,342
0
2.5E-4
Chronic
50
0
6.6E-3
Algae
1.4
0
0.2
20
4.2E-2
0
4.6
Acute
1,342
0
3.4E-3
Chronic
50
0
9.2E-2
Algae
1.4
1
3.3
Page 423 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Niimc. locution.
;ind II) ol' Aiii\c
Koloiisor l-iicilily1
Release
Media1'
Modeled
l';icili(\ oi*
Indusln
Seelor in H-
FAST1
EFAST
\\a(erl>od>
Tj pe'1
DjIJS ol
Release'
Release
\\ \\ 1
remo\al
0/
/<)
7Q10
SWC
(pph)-
COC Tjpe
coc
(|)|)b)
l)il>S ol
I'.xceedanee
(dajs/jear)'1
Risk
Quotient
Pinewood Site
Custodial Trust
Pinewood, SC
NPDES:
SC0042170
Surface
Water
Surrogate:
Industrial
POTW SIC
code
Surface
Water
250
1.0E-3
0
0.1
Acute
1,342
0
9.7E-5
Chronic
50
0
2.6E-3
Algae
1.4
0
9.3E-2
20
7.5E-3
0
1.0
Acute
1,342
0
7.2E-4
Chronic
50
0
1.9E-2
Algae
1.4
2
0.7
Safety-Kleen
Systems Inc
Smithfield, KY
NPDES:
KY0098345
Non-
POTW
WWT
Surrogate:
Industrial
POTW SIC
code (surrogate
for receiving
facility
MDU000011)
Surface
Water
250
1.4
80
35
Acute
1,342
0
2.6E-2
Chronic
50
22
0.7
Algae
1.4
2 "5
25
20
17
80
436
Acute
1,342
0
0.3
Chronic
50
15
8.7
Algae
1.4
2(1
^ 1
Safety-Kleen
Systems Inc, East
Chicago, IN
NPDES:
Unknown
POTW
Receiving
Facility:
IN0022829
Surface
Water
250
0.3
80
0.8
Acute
1,342
3
6.0E-4
Chronic
50
10
1.6E-2
Algae
1.4
148
0.6
Tier Environmental
LLC
Bedford, OH
NPDES: None
(FRS
110000388232)
POTW
Surrogate:
Industrial
POTW SIC
code
Surface
Water
250
0.1
80
3.1
Acute
1,342
0
2.3E-3
Chronic
50
0
6.2E-2
Algae
1.4
'JO
? 7
Tradebe Treatment
& Recycling LLC
East Chicago, IN
NPDES: None
(FRS
110070334821)
Non-
POTW
WWT
Surrogate:
Industrial
POTW SIC
code (surrogate
for FRS
110020159852
Surface
Water
250
5.0E-3
80
0.1
Acute
1,342
0
9.7E-5
Chronic
50
0
2.6E-3
Algae
1.4
0
9.3E-2
20
6.8E-2
80
1.8
Acute
1,342
0
1.3E-3
Chronic
50
0
3.5E-2
Algae
1.4
4
1.3
10058 a. Facilities actively releasing PCE were identified via DMR, TRI and CDR databases for the 2016 reporting year.
10059 b. Release media are either direct (release from active facility directly to surface water) or indirect (transfer of wastewater from active facility to a receiving POTW
10060 or non-POTW WWTP facility). A wastewater treatment removal rate of 80% is applied to all indirect releases, as well as direct releases from WWTPs.
Page 424 of 636
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10061
10062
10063
10064
10065
10066
10067
10068
10069
10070
10071
10072
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
c. If a valid NPDES of the direct or indirect releaser was not available in EFAST, the release was modeled using either a surrogate representative facility in EFAST
(based on location) or a representative industry sector. If available in TRI, the NPDES of the receiving facility is provided.
d. E-FAST 2014 (U.S. EPA 2014b') uses the "surface water" model for free-flowing water bodies such as rivers and streams, and the "still water" model for lakes,
bays, and oceans. The surface water model uses stream flow values to calculate the concentration, whereas the still water model uses dilution factors. The
dilution factor used in E-FAST is provided in parenthesis.
e. Modeling was conducted with the maximum days of release per year estimated. For direct releasing facilities, a minimum of 20 days was also modeled.
f. The daily release amount was calculated from the reported annual release amount divided by the number of release days per year.
g. The harmonic mean is not applicable for discharges to still water. For discharges to free-flowing water using an industry sector flow, the 10th percentile harmonic
mean is reported.
h. For releases discharging to lakes, bays, estuaries, and oceans, the acute scenario mixing zone water concentration was reported in place of the 7Q10 SWC. For
discharges to free-flowing water using an industry sector flow, the 10th percentile 7Q10 is reported.
Page 425 of 636
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10073
10074
10075
10076
10077
10078
10079
10080
10081
10082
10083
10084
10085
10086
10087
10088
10089
10090
10091
10092
10093
10094
10095
10096
10097
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
4.5.2 Human Health Risk Conclusions
4.5.2.1 Summary of Risk Estimates for Inhalation and Dermal Exposures to
Workers and ONUs
Table 4-112 summarizes the risk estimates for inhalation and dermal exposures for all occupational
exposure scenarios. Risk estimates that exceed the benchmark (i.e. MOEs less than the benchmark MOE
or cancer risks greater than the cancer risk benchmark) are highlighted by bolding the number and
shading the cell both with and without assumed PPE. The PPE protection factor is listed in
parentheticals beneath the risk value. The lowest APF/glove PF that eliminated risk (or APF 50/glove PF
20 if risk was not eliminated) was presented. The risk characterization is described in more detail in
Section 4.2.2 and specific links to the exposure and risk characterization sections are listed in Table
4-112 in the column headed Occupational Exposure Scenario.
Of note, the risk summary below is based on the most sensitive acute and chronic non-cancer endpoints
(neurotoxicity) as well as cancer. For the majority of exposure scenarios, when risks were identified for
the chronic non-cancer endpoint (neurotoxicity), risks were also identified for kidney (urinary markers
of nephrotoxicity) and immune system toxicity.
EPA made OES-specific determinations of assumed respirator use (see Section 4.2.2.2). When respirator
use was considered plausible for the use scenario, the following PPE protection limits were considered
for purposes of risk determination (Section 5.3), displayed in Table 4-111. Risk estimates are shown for
all OES in Table 4-112 as a what-if scenario, even if those limits are not used for risk determination.
Footnotes indicate for which individual OES respirator use is not assumed.
Table 4-111. PPE Protection Limits Considered for Risk Determination by Sector
Sector
APF
Glove PF
Manufacturing
50
20
Import/Processing/Disposal
25
20
Industrial
25
10
Commercial
10
5
Consumer
None
None
Page 426 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
10098 Table 4-112 Summary of Risk Estimates for Inhalation and Dermal Ex
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Manufacture/
Domestic
manufacture
Domestic manufacture
Section 2.4.1.6 -
Manufacturing and Section
4.2.2.3 for inhalation risks
and Section 4.2.3 for dermal
risks
Worker
Inhalation
8 hr
High-End
1.9
8.7
6.1E-4
19
(APF 10)
218
(APF 25)
6.1E-5
(APF 10)
Central
Tendency
154
701
5.9E-6
1538
(APF 10)
17,520
(APF 25)
5.9E-7
(APF 10)
Inhalation
12 hr
High-End
16
72
7.5E-5
156
(APF 10)
716
(APF 10)
7.5E-6
(APF 10)
Central
Tendency
161
741
5.6E-6
1610
(APF 10)
7407
(APF 10)
5.6E-7
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 hr
High-End
1.9
8.7
6.1E-4
N/A
N/A
N/A
Central
Tendency
154
701
5.9E-6
N/A
N/A
N/A
Inhalation
12 hr
High-End
16
72
7.5E-5
N/A
N/A
N/A
Central
Tendency
161
741
5.6E-6
N/A
N/A
N/A
Manufacture/
Import
Import
Section 2.4.1.7 -
Repackaging
and Section 0 -
2 EPA is unable to estimate
ONU exposures separately
from workers. EPA used
worker central tendency
values as a surrogate to
assess risk for ONUs;
however, the statistical
representativeness of this
value for ONUs is unknown.
Repackaging for inhalation
risks and Section 4.2.3 for
dermal risks
Worker
Inhalation
8 hr
High-End
6.1
28
1.9E-4
61
(APF 10)
278
(APF 10)
1.9E-5
(APF 10)
Central
Tendency
11.5
52
7.9E-5
115
(APF 10)
523
(APF 10)
7.9E-6
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 hr
High-End
6.1
28
1.9E-4
N/A
N/A
N/A
Central
Tendency
11.5
52
7.9E-5
N/A
N/A
N/A
josures to Workers by Condition of Use
Page 427 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
l.ilc (>ele
Siaue ( aleuors
Siihcaleuois
()ccnpalioiial 1 Aposiiiv
Scenario and 1 Aposiiic and
Risk Section \iimheis
Population
1 Aposlll'C
koine and
1 )iiialioii
1 Aposlll'C
I.CNCl
Risk 1 Aiimalcs lor \o I'I'I
Risk 1 !siimales w nil I'l'l!
\cule
\on-
cancer
i he lie li-
ma i'k
\I()L
KM
Chronic
\on-
cancer
(hencli-
mark
\I()L
Kill)
( ancer
(bench-
mark
|u )
\cnie
\oii-
cancer
(hencli-
IIKII'k
\k )i:
mi
( limine
\oii-
cancer
(he nc li-
ma rk
\I()L
1
Cancer
(bench-
mark
In )
Processing,
Processing as a
reactant/
intermediate
Intermediate 111 industrial gab
manufacturing
Section 2.4.l.S Processing
as a Reactant
and Section 4.2.2.5 -
Processing as Reactant for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 hr
High-Ei id
l.«)
S.^
(..11-4
19
(APF 10)
218
(APF 25)
o.lL-5
(APF 10)
Central
Tendency
154
701
5.9E-6
1538
(APF 10)
17520
(APF 25)
5.9E-7
(APF 10)
Intermediate in basic organic
chemical manufacturing
Inhalation
12 hr
High-End
15.6
72
7.5E-5
156
(APF 10)
716
(APF 10)
7.5E-6
(APF 10)
Central
Tendencs
161
741
5.6E-6
1610
(APF 10)
7407
(APF 10)
5.6E-7
(APF 10)
Intermediate in petroleum
refineries
Dermal
High-Ei id
1.2
2.(.
2.51.-3
24
(PF 20)
51
(pi :ii)
i.2i:-4
(PI 20)
Residual or byproduct reused as a
reactanta
Central
Tendencs
3.(.
7.7
(..41-4
72
rPF 20)
154
(PF 20)
3.2L-5
(PF 20)
ONUs
Inhalation
8 hr
High-Ei id
1.9
X."7
(..11-4
NT/A
N/A
N/A
Central
Tendency
154
701
5.9E-6
N/A
N/A
N/A
Inhalation
12 hr
High-End
15.6
72
7.5E-5
N/A
N/A
N/A
Central
Tendency
l(.|
"41
5 (.i:-(.
N/A
\ \
VA
Processing/
Incorporated
into formulation
mixture or
reaction product
Cleaning and degreasing products
Section 2.4.1.9 -
Incorporation into
Formulation, Mixture, or
Reactant Product
and Section 4.2.2.6 -
Incorporation into
Formulation, Mixture, or
Reactant Product
Based on Aerosol Packing
for inhalation risks and
Section 4.2.3 for dermal risks
Worker
Inhalation
8 hr
High-End
0.3X
\r
3.11.-3
19
(APF 50)
X4
( \H' 50)
(. 2E-5
( \PF50)
Adhesive and sealant products
Central
Tendency
II.(.11
2.7
1.51.-3
30
(APF 50)
i
( \\>\: 5(1)
^ oE-5
( \PI 50)
Paint and coating products
Dermal
High-End
1.2
2.(.
2.5I--3
24
(PF 20)
51
(PI 2(H
1.21.-4
( PI 20)
Other chemical products and
preparations
Central
Tendency
3.(.
7.7
(..4I.-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 hr
High-End
0.3X
\r
3.11.-3
N/A
N/A
N/A
Central
Tendency
11.611
2.7
1.51.-3
N/A
N/A
N/A
Section 2.4.1.9 -
Incorporation into
Worker
Inhalation
8 hr
High-End
l.'J
*)2
1 "L-5
19
(APF 10)
918
(APF 10)
1.7E-6
(APF 10)
Page 428 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Formulation, Mixture, or
Reactant Product and Section
4.2.2.6 - Incorporation into
Formulation, Mixture, or
Reactant Product
Based on Degreasing Solvent
for inhalation risks and
Section 4.2.3 for dermal risks
Central
Tendency
6.9
328
4.7E-6
69
(APF 10)
3277
(APF 10)
4.7E-7
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
1.9
92
1.7E-5
N/A
N/A
N/A
Central
Tendency
6.9
328
4.7E-6
N/A
N/A
N/A
Section 2.4.1.9 -
Incorporation into
Formulation, Mixture, or
Reactant Product
and Section 4.2.2.6 -
Incorporation into
Formulation, Mixture, or
Reactant Product Based on
Dry Cleaning Solvent for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.35
17
9.1E-5
18
(APF 50)
169
(APF 10)
9.1E-6
(APF 10)
Central
Tendency
1.3
60
2.5E-5
63
(APF 50)
604
(APF 10)
2.5E-6
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
0.35
17
9.1E-5
N/A
N/A
N/A
Central
Tendency
1.3
60
2.5E-5
N/A
N/A
N/A
Section 2.4.1.9 -
Incorporation into
Formulation, Mixture, or
Reactant Product
and Section 4.2.2.6 -
Incorporation into
Formulation, Mixture, or
Reactant Product
Based on Miscellaneous for
inhalation risks and Section
4.2.34.2.3.1 for dermal risks
Worker
Inhalation
8 lir
High-End
3.5
169
9.1E-6
89
(APF 25)
1693
(APF 10)
9.1E-7
(APF 10)
Central
Tendency
13
602
2.6E-6
315
(APF 25
6017
(APF 10)
2.6E-7
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
3.5
169
9.1E-6
N/A
N/A
N/A
Central
Tendency
13
602
2.6E-6
N/A
N/A
N/A
Page 429 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Processing/
Incorporated
into articles
Plastic and rubber products
Not assessed - after further review, EPA determined that PCE is not incorporated into plastic articles but rather is used as a
degreasing solvent at plastic manufacture sites which are assessed in Sections 2.4.1.10 through 2.4.1.15
Processing/
Repackaging
Solvent for cleaning or
degreasing
Section 2.4.1.7 -
Repackaging
and Section 0 -
2 EPA is unable to estimate
ONU exposures separately
from workers. EPA used
worker central tendency
values as a surrogate to
assess risk for ONUs;
however, the statistical
representativeness of this
value for ONUs is unknown.
Repackaging for inhalation
risks and Section 4.2.3 for
dermal risks
Worker
Inhalation
8 lir
High-End
6.1
28
1.9E-4
61
(APF 10)
278
(APF 10)
1.9E-5
(APF 10)
Intermediate
Central
Tendency
11.5
52
7.9E-5
115
(APF 10)
523
(APF 10)
7.9E-6
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
6.1
28
1.9E-4
N/A
N/A
N/A
Central
Tendency
11.5
52
7.9E-5
N/A
N/A
N/A
Processing/
Recycling
Recycling
Section 2.4.1.26 - Waste
Handling, Disposal,
Treatment, and Recycling
and Section 4.2.2.23 - Waste
Handling, Disposal,
Treatment, and Recycling for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
139
633
8.4E-6
1390
(APF 10)
6331
(APF 10)
8.4E-7
(APF 10)
Central
Tendency
628
2862
1.4E-6
6284
(APF 10)
28,624
(APF 10)
1.4E-7
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
139
633
8.4E-6
N/A
N/A
N/A
Central
Tendency
628
2862
1.4E-6
N/A
N/A
N/A
Distribution in
commerce
Distribution
Activities related to distribution (e.g., loading, unloading) are considered throughout the life cycle, rather than using a single
distribution scenario.
Page 430 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Industrial use/
Solvents (for
cleaning or
degreasing)
Batch vapor degreaser (e.g.,
open-top, closed-loop)
Section 2.4.1.10 - Batch
Open-Top Vapor Degreasing
and Section 4.2.2.7 - Batch
Open-Top Vapor Degreasing
for inhalation risks and
Section 4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.16
0.71
7.5E-3
7.8
(APF 50)
35
(APF 50)
1.5E-4
(APF 50)
Central
Tendency
2.4
11
3.8E-4
119
(APF 50)
542
(APF 50)
7.6E-6
(APF 50)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
0.96
4.4
1.2E-3
N/A
N/A
N/A
Central
Tendency
8.3
38
1.1E-4
N/A
N/A
N/A
Section 2.4.1.11 - Batch
Closed-Loop Vapor
Degreasing
And Section 4.2.2.8 - Batch
Closed-Loop Vapor
Degreasing for inhalation
risks and Section 4.2.3 for
dermal risks
Worker
Inhalation
8 lir
High-End
20
90
5.9E-5
198
(APF 10)
238
(APF 10)
5.9E-6
(APF 10)
Central
Tendency
69
316
1.3E-5
693
(APF 10)
348
(APF 10)
1.3E-6
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
52
238
2.2E-5
N/A
N/A
N/A
Central
Tendency
76
348
1.2E-5
N/A
N/A
N/A
In-line vapor degreaser (e.g.,
conveyorized, web cleaner)
Section 2.4.1.12-
Conveyorized Vapor
Degreasing
and Section 4.2.2.9 -
Conveyorized Vapor
Degreasing for inhalation
risks and Section 4.2.3 for
dermal risks
Worker
Inhalation
8 lir
High-End
0.03
0.12
3.5E-2
1.3
(APF 50)
6.1
(APF 50)
7.0E-4
(APF 50)
Central
Tendency
0.06
0.29
1.3E-2
3.2
(APF 50)
15
(APF 50)
2.7E-
(APF 50)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
High-End
0.04
0.18
2.3E-2
N/A
N/A
N/A
Page 431 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Inhalation
8 lir
Central
Tendency
0.12
0.56
7.0E-3
N/A
N/A
N/A
Section 2.4.1.13 - Web
Degreasing
and Section 4.2.2.10 - Web
Degreasing for inhalation
risks and Section 4.2.3 for
dermal risks
Worker
Inhalation
8 lir
High-End
2.8
13
3.3E-4
139
(APF 10)
126
(APF 10)
3.3E-05
(APF 10)
Central
Tendency
8.2
37
1.1E-4
409
(APF 10)
373
(APF 10)
1.1E-05
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
4.3
19
2.1E-4
N/A
N/A
N/A
Central
Tendency
16
71
5.5E-5
N/A
N/A
N/A
Cold cleaner
Section 2.4.1.14- Cold
Cleaning
and Section 4.2.2.11 - Cold
Cleaning
Based on inhalation*
exposure monitoring data for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
1.2
5.5
9.7E-4
12
(APF 10)
138
(APF 25)
9.7E-5
(APF 10)
Central
Tendency
3.6
16
2.5E-4
36
(APF 10)
407
(APF 25)
2.4E-05
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
1.2
5.5
9.7E-4
N/A
N/A
N/A
Central
Tendency
3.6
16
2.5E-4
N/A
N/A
N/A
Section 2.4.1.14- Cold
Cleaning
and Section 4.2.2.11 - Cold
Cleaning
Based on inhalation*
exposure modeling for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
3.3
15
2.6E-4
33
(APF 10)
148
(APF 10)
2.6E-5
(APF 10)
Central
Tendency
2086
9501
4.1E-7
20857
(APF 10)
95,007
(APF 10)
4.1E-8
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
Page 432 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
ONUs
Inhalation
8 lir
High-End
6.4
29
1.3E-4
N/A
N/A
N/A
Central
Tendency
4029
18,354
2.1E-7
N/A
N/A
N/A
Aerosol spray degreaser/cleaner
Section 2.4.1.15- Aerosol
Degreasing and Aerosol
Lubricants
and Section 4.2.2.12 -
Aerosol Degreasing and
Aerosol Lubricants 0
Based on inhalation*
exposure monitoring data for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.64
2.9
1.8E-3
32
(APF 50)
146
(APF 50)
3.6E-5
(APF 50)
Central
Tendency
3.5
16
2.6E-4
174
(APF 50)
792
(APF 50)
5.2E-6
(APF 50)
Dermal
High-End
0.80
1.7
3.7E-3
16
(PF 20)
34
(PF 20)
1.9E-4
(PF 20)
Central
Tendency
2.4
5.1
9.6E-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
0.64
2.9
1.8E-3
N/A
N/A
N/A
Central
Tendency
3.5
16
2.6E-4
N/A
N/A
N/A
Section 2.4.1.15 - Aerosol
Degreasing and Aerosol
Lubricants
and Section 4.2.2.12 -
Aerosol Degreasing and
Aerosol Lubricants 0
Based on inhalation*
exposure modeling for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.29
1.3
3.1E-3
15
(APF 50)
66
(APF 50)
6.3E-5
(APF 50)
Central
Tendency
0.91
4.2
9.4E-4
46
(APF 50)
208
(APF 50)
1.9E-5
(APF 50)
Dermal
High-End
0.80
1.7
3.7E-3
16
(PF 20)
34
(PF 20)
1.9E-4
(PF 20)
Central
Tendency
2.4
5.1
9.6E-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
6.8
31
1.4E-4
N/A
N/A
N/A
Central
Tendency
50
260
2.0E-5
N/A
N/A
N/A
Dry cleaning solvent
Section 2.4.1.16 - Dry
Cleaning and Spot Cleaning
Post-2006 Dry Cleaning
(including spot cleaning)
and Section 4.2.2.13 - Dry
Cleaning and Spot Cleaning0
Worker
Inhalation
8 lir
High-End
0.26
1.0
5.4E-3
13
(APF 50)
50
(APF 50)
1.1E-4
(APF 50)
Spot cleaner
Central
Tendency
1.4
6.1
6.8E-4
69
(APF 50)
303
(APF 50)
1.4E-5
(APF 50)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Page 433 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk 1 Aiimales lor \o I'I'I
Risk 1 Isimiales u nil
m:
\cule
Chronic
\cnie
( liromc
l.ilc (>ele
Siaue ( aleuors
Snhcaleuors
()cciipalional 1 Aposnre
Scenario and 1 Aposnre and
Population
1 Aposnre
koine and
1 Aposnre
l.c\el
Non-
cancer
i he nc li-
ma rk
\oii-
cancer
(hencli-
mark
Cancer
(bench-
Non-
cancer
(hencli-
iiKirk
NiHI-
cancer
(he nc li-
ma rk
Cancer
(bench-
Risk Section Numbers
1 )nralioii
mark
|u )
mark
In )
\I()L
\I()L
\ioi:
\I()L
KM
Kill)
mi
1
Uu^ed on inhalation*
Central
2.4
5.0
1.01-3
4"
101
5.1L-5
exposure monitoring data for
Tendencs
(PF 20)
(PF 20)
(PF 20)
inhalation risks and Section
Inhalation
8 hr
High-End
5(>
5 E-5
N/A
N/A
N/A
4.2.3 for dermal risks
ONUs
Central
Tendency
14
(.4
(. 5L-5
\ \
N \
N \
Section 2.4.1.16- Dry
Cleaning and Spot Cleaning
Inhalation
High-End
O.I"7
0.50
S.I 1.-2
S.4
( \IT 5(1)
25
( \IT' 50)
i.(.i:-4
( \IT' 5(1)
Post-2006 Dry Cleaning
(including spot cleaning)
Worker
8 hr
Central
Tendency
3.(i
II
3.XI.-4
r<>
( \IT' 5(1)
52"
( \IT' 5(1)
~ <>l !-<>
( \PI" 5(1)
and Section 4.2.2.13 - Dry
Cleaning and Spot Cleaning0
Dermal
High-End
0."")
\r
4.41.-3
l(.
(PF 20)
34
(pi :oi
2.2I--4
(PI 20)
Based on inhalation*
exposure modeling for
Central
Tendency
2.4
5.0
1.01-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
inhalation risks and Section
Inhalation
8 hr
High-End
3.2
•>.5
4.31.-4
N/A
N/A
N/A
4.2.3 for dermal risks
ONUs
Central
Tendencs
46
136
2.9E-5
N/A
N/A
N/A
Section 2.4.1.16- Dry
Cleaning and Spot Cleaning
Inhalation
High-Ei id
O.X<)
3.5
1.51.-3
45
(APF 50)
174
(APF 50)
3.1E-5
(APF 50)
4th/5th Gen Only Dry
Cleaning (including spot
Worker
8 hr
Central
Tendencs
5.1
23
I.SI-4
256
(APF 50)
1129
(APF 50)
3.7E-6
(APF 50)
cleaning)
and Section 4.2.2.13 - Dry
Dermal
High-Ei id
0."")
1.7
4.41.-3
16
(PF 20)
34
(pi :iD
2.21.-4
(IT' 2d)
Cleaning and Spot Cleaning0
Based on inhalation*
Central
Tendencs
2.4
5.0
1.01-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
exposure monitoring data for
Inhalation
8 hr
High-End
41
158
3.4E-5
N/A
N/A
N/A
inhalation risks and Section
4.2.3 for dermal risks
ONUs
Central
Tendency
'5X
I5x:
: (.i:-(.
N/A
N/A
N/A
Industrial use/
Lubricants and
Lubricants and greases (e.g.,
penetrating lubricants, cutting
Section 2.4.1.15 - Aerosol
Degreasing and Aerosol
Worker
Inhalation
High-End
0.(»4
2.')
I.SI-3
32
(APF 50)
146
(APF 50)
3.6E-5
(APF 50)
greases
tool coolants, aerosol lubricants)
Lubricants
8 hr
Central
Tendency
3.5
I(.
2.(.i:-4
174
(APF 50)
792
(APF 50)
5.2E-6
(APF 50)
Page 434 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
and Section 4.2.2.12 -
Aerosol Degreasing and
Aerosol Lubricants 0
Based on inhalation*
exposure monitoring data for
inhalation risks and Section
4.2.3 for dermal risks
Dermal
High-End
0.80
1.7
3.7E-3
16
(PF 20)
34
(PF 20)
1.9E-4
(PF 20)
Central
Tendency
2.4
5.1
9.6E-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
0.64
2.9
1.8E-3
N/A
N/A
N/A
Central
Tendency
3.5
16
2.6E-4
N/A
N/A
N/A
Section 2.4.1.15- Aerosol
Degreasing and Aerosol
Lubricants
and Section 4.2.2.12 -
Aerosol Degreasing and
Aerosol Lubricants 0
Based on inhalation*
exposure modeling for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.29
1.3
3.1E-3
15
(APF 50)
66
(APF 50)
6.3E-5
(APF 50)
Central
Tendency
0.91
4.2
9.4E-4
46
(APF 50)
208
(APF 50)
1.9E-5
(APF 50)
Dermal
High-End
0.80
1.7
3.7E-3
16
(PF 20)
34
(PF 20)
1.9E-4
(PF 20)
Central
Tendency
2.4
5.1
9.6E-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
6.8
31
1.4E-4
N/A
N/A
N/A
Central
Tendency
50
260
2.0E-5
N/A
N/A
N/A
Section2.4.1.20-
Metalworking Fluids
and Section 4.2.2.17 -
Metalworking Fluids 0 for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
239
1087
4.9E-6
2387
(APF 10)
10,875
(APF 10)
4.9E-7
(APF 10)
Central
Tendency
869
3960
1.0E-6
8692
(APF 10)
39,595
(APF 10)
1.0E-7
(APF 10)
Dermal
High-End
12
26
2.5E-4
60
(PF 5)
128
(PF 5)
5.0E-5
(PF 5)
Central
Tendency
36
77
6.4E-5
181
(PF 5)
384
(PF 5)
1.3E-5
(PF 5)
ONUs
Inhalation
8 lir
High-End
239
1087
4.9E-6
N/A
N/A
N/A
Central
Tendency
869
3960
1.0E-6
N/A
N/A
N/A
Solvent-based adhesives and
sealants
Section 2.4.1.17- Adhesive,
Sealants, Paints, and
Worker
Inhalation
8 lir
High-End
6.2
28
1.9E-4
62
(APF 10)
281
(APF 10)
1.9E-5
(APF 10)
Page 435 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Industrial use/
Adhesives and
sealants
Coatings
and Section 4.2.2.14
Adhesives, Sealants, Paints,
and Coatings
Based on Adhesives for
inhalation risks and Section
4.2.3 for dermal risks
Central
Tendency
57
257
1.6E-5
565
(APF 10)
2574
(APF 10)
1.6E-6
(APF 10)
Dermal
Commerci
al use
High-End
0.98
2.1
3.0E-3
20
(PF 20)
42
(PF 20)
1.5E-4
(PF 20)
Central
Tendency
3.0
6.3
7.8E-4
59
(PF 20)
126
(PF 20)
3.9E-5
(PF 20)
Dermal
Industrial
use
High-End
1.5
3.2
2.0E-3
30
(PF 20)
64
(PF 20)
9.9E-5
(PF 20)
Central
Tendency
4.5
9.6
5.1E-4
90
(PF 20)
192
(PF 20)
2.6E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
6.2
28
1.9E-4
N/A
N/A
N/A
Central
Tendency
57
257
1.6E-5
N/A
N/A
N/A
Industrial use/
Paints and
coatings
including paint
and coating
removers
Solvent-based paints and
coatings, including for chemical
milling
Section 2.4.1.17- Adhesive,
Sealants, Paints, and
Coatings
and Section 4.2.2.14
Adhesives, Sealants, Paints,
and Coatings
Based on Paints/ Coatings
for inhalation risks and
Section 4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
1.1
5.0
1.1E-3
11
(APF 10)
125
(APF 25)
4.3E-5
(APF 25)
Central
Tendency
21
98
4.2E-5
214
(APF 10)
2440
(APF 25)
1.7E-6
(APF 25)
Dermal
Commerci
al use
High-End
0.98
2.1
3.0E-3
20
(PF 20)
42
(PF 20)
1.5E-4
(PF 20)
Central
Tendency
3.0
6.3
7.8E-4
59
(PF 20)
126
(PF 20)
3.9E-5
(PF 20)
Dermal
Industrial
use
High-End
1.5
3.2
2.0E-3
30
(PF 20)
64
(PF 20)
9.9E-5
(PF 20)
Central
Tendency
4.5
9.6
5.1E-4
90
(PF 20)
192
(PF 20)
2.6E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
1.1
5.0
1.1E-3
N/A
N/A
N/A
Central
Tendency
21
98
4.2E-5
N/A
N/A
N/A
Section 2.4.1.18 - Maskant
for Chemical Milling
and Section 4.2.2.15 -
Maskant for Chemical
Worker
Inhalation
8 lir
High-End
2.4
11
4.9E-4
24
(APF 10)
108
(APF 10)
4.9E-5
(APF 10)
Central
Tendency
4.1
19
2.2E-4
41
(APF 10)
188
(APF 10)
2.2E-5
(APF 10)
Page 436 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Milling for inhalation risks
and Section 4.2.3 for dermal
risks
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
2.4
11
4.9E-4
N/A
N/A
N/A
Central
Tendency
4.1
19
2.2E-4
N/A
N/A
N/A
Industrial use/
Processing aids,
not otherwise
listed
Pesticide, fertilizer and other
agricultural chemical
manufacturing
Section 2.4.1.19 - Industrial
Processing Aid
And Section 4.2.2.16 -
Industrial Processing Aid for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
4.2
19
2.8E-4
42
(APF 10)
193
(APF 10)
2.8E-5
(APF 10)
Central
Tendency
83
380
1.1E-5
833
(APF 10)
3796
(APF 10)
1.1E-6
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
4.2
19
2.8E-4
N/A
N/A
N/A
Central
Tendency
83
380
1.1E-5
N/A
N/A
N/A
Industrial use/
Processing aids,
specific to
petroleum
production
Catalyst regeneration in
petrochemical manufacturing
Section 2.4.1.19 - Industrial
Processing Aid
And Section 4.2.2.16 -
Industrial Processing Aid for
inhalation risks and
Section4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
4.2
19
2.8E-4
42
(APF 10)
193
(APF 10)
2.8E-5
(APF 10)
Central
Tendency
83
380
1.1E-5
833
(APF 10)
3796
(APF 10)
1.1E-6
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
4.2
19
2.8E-4
N/A
N/A
N/A
Central
Tendency
83
380
1.1E-5
N/A
N/A
N/A
Industrial use/
Other uses
Textile processing
Section 2.4.1.22 - Other
Spot Cleaning/Spot
Worker
Inhalation
8 lir
High-End
22
99
5.4E-5
217
(APF 10)
987
(APF 10)
5.4E-6
(APF 10)
Page 437 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Removers (Including Carpet
Cleaning)
and Section 4.2.2.19 - Other
Spot Cleaning/Spot
Removers (Including Carpet
Cleaning)0 for inhalation
risks and Section 4.2.3 for
dermal risks
Central
Tendency
29
133
3.1E-5
291
(APF 10)
1325
(APF 10)
3.1E-6
(APF 10)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
167
759
7.0E-6
N/A
N/A
N/A
Central
Tendency
5.4E-6
Section 2.4.1.23 - Other
Industrial Uses
and Section 4.2.2.20 - Other
Industrial Uses for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
139
633
8.4E-6
1390
(APF 10)
6331
(APF 10)
8.4E-7
(APF 10)
Central
Tendency
628
2862
1.4E-6
6284
(APF 10)
28,624
(APF 10)
1.4E-7
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
139
633
8.4E-6
N/A
N/A
N/A
Central
Tendency
628
2862
1.4E-6
N/A
N/A
N/A
Wood furniture manufacturing
Section 2.4.1.23 - Other
Industrial Uses
and Section 4.2.2.20 - Other
Industrial Uses for inhalation
risks and Section 4.2.3 for
dermal risks
Worker
Inhalation
8 lir
High-End
139
633
8.4E-6
1390
(APF 10)
6331
(APF 10)
8.4E-7
(APF 10)
Central
Tendency
628
2862
1.4E-6
6284
(APF 10)
28,624
(APF 10)
1.4E-7
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
139
633
8.4E-6
N/A
N/A
N/A
Central
Tendency
628
2862
1.4E-6
N/A
N/A
N/A
Page 438 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Laboratory chemicals
Section 2.4.1.25 -
Laboratory Chemicals
N/A - qualitative assessment
Foundry applications
Section 2.4.1.23 - Other
Industrial Uses
and Section 4.2.2.20 - Other
Industrial Uses for inhalation
risks and Section 4.2.3 for
dermal risks
Worker
Inhalation
8 lir
High-End
139
633
8.4E-6
1390
(APF 10)
6331
(APF 10)
8.4E-7
(APF 10)
Central
Tendency
628
2862
1.4E-6
6284
(APF 10)
28,624
(APF 10)
1.4E-7
(APF 10)
Dermal
High-End
1.2
2.6
2.5E-3
24
(PF 20)
51
(PF 20)
1.2E-4
(PF 20)
Central
Tendency
3.6
7.7
6.4E-4
72
(PF 20)
154
(PF 20)
3.2E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
139
633
8.4E-6
N/A
N/A
N/A
Central
Tendency
628
2862
1.4E-6
N/A
N/A
N/A
Commercial use/
Cleaning and
furniture care
products
Cleaners and degreasers (other)
Section 2.4.1.21 - Wipe
Cleaning and Metal/Stone
Polishes
and Section 4.2.2.18 - Wipe
Cleaning and Metal/Stone
Polishes 0 for inhalation risks
and Section 4.2.3 for dermal
risks
Worker
Inhalation
8 lir
High-End
0.02
0.10
5.3E-2
1.1
(APF 50)
5.0
(APF 50)
1.1E-3
(APF 50)
Central
Tendency
0.04
0.17
2.4E-2
1.9
(APF 50)
8.6
(APF 50)
4.8E-4
(APF 50)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
0.22
0.98
5.4E-3
N/A
N/A
N/A
Central
Tendency
229
1043
4.0E-6
N/A
N/A
N/A
Section 2.4.1.22 - Other
Spot Cleaning/Spot
Removers (Including Carpet
Cleaning)
and Section 4.2.2.19 - Other
Spot Cleaning/Spot
Removers (Including Carpet
Cleaning)0 for inhalation
Worker
Inhalation
8 lir
High-End
22
99
5.4E-5
217
(APF 10)
987
(APF 10)
5.4E-6
(APF 10)
Central
Tendency
29
133
3.1E-5
291
(APF 10)
1325
(APF 10)
3.1E-6
(APF 10)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
Page 439 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk 1 Aiinialcs lor \o I'I'I
Risk 1 Isiimales w nil
I'i'i:
\cnic
Chrome
\cnie
( limine
l.ilc (>clc
Siauc ( alcuors
Siihcalcuors
()cciipalional 1 Aposiirc
Scenario and 1 Aposnre and
Risk Section \iinihers
Population
1 Aposnrc
Runic and
1 )iiralioii
1 Aposnrc
I.CNCl
Noil-
cancer
i he nc li-
ma rk
\oii-
canccr
(hencli-
mark
Cancer
(bench-
mark
|u )
\oii-
cancer
(hencli-
mai'k
\oii-
canccr
i he nc li-
ma rk
(ancer
(bench-
mark
In )
\I()L
\I()L
\k )i:
\l()L
KM
Kill)
mi
1
risks and Section 4.2.3 for
dermal risks
ONUs
Inhalation
High-End
167
759
7.0E-6
N/A
N/A
N/A
8 hr
Central
5.4E-6
Tendency
Section 2.4.1.24 - Other
Commercial Uses
Inhalation
High-End
25
114
4.7E-5
250
(APF10)
1139
(APF 10)
4.7E-6
(APF 10)
and Section 4.2.2.21 - Other
Commercial Uses Based on
Worker
8 hr
Central
Tcndcnc\
50
228
1.8E-5
500
(APF10)
2278
( \\>\: KM
1.8E-6
( \\>\: Id)
Mold Release 0 for inhalation
risks and Section 4.2.3 for
Dermal
High-End
0."")
1.7
4.41.-3
16
(PF 20)
34
)
2.2I--4
ipi:!))
dermal risks
Central
2.4
5.0
1.01-3
47
101
5.1E-5
Tcndcnc\
(PF 20)
(PF 20)
(PF 20)
Inhalation
8 hr
High-End
25
114
4.7E-5
N/A
N/A
N/A
ONUs
Central
Tendency
50
228
1.8E-5
N/A
N/A
N/A
Dry cleaning solvent
Section 2.4.1.16 - Dry
Cleaning and Spot Cleaning
Inhalation
High-End
0.2(.
1.0
5.41.-3
13
(APF 50)
50
( \IJI 50)
I.I 1.-4
( \\>\: 5(1)
Spot cleaner
Post-2006 Dry Cleaning
(including spot cleaning)
Worker
8 hr
Central
Tendency
1.4
(>.l
(..Xi:-4
69
(APF 50)
( \IT' 5(1)
1 41 :-5
i \IT' 5(1)
and Section 4.2.2.13 - Dry
Cleaning and Spot Cleaning0
Dermal
High-End
0."")
\r
4.41.-3
16
(PF 20)
34
(iji; :ii)
2.21.-4
CPI 20;
Based on inhalation*
exposure monitoring data for
Central
Tendency
2.4
5.0
1.01-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
inhalation risks and Section
4.2.3 for dermal risks
ONUs
Inhalation
8 hr
High-End
14
56
5 E-5
N/A
N/A
N/A
Central
Tcndcnc\
(.4
(. 5R-5
N'\
N'\
N'\
Section 2.4.1.16 - Dry
Cleaning and Spot Cleaning
Worker
Inhalation
8 hr
High-End
0.I"7
0.50
S.I 1.-2
S.4
( \H ' 5(1)
25
( \PI ' 50)
i.(.i-:-4
( API" 5(1)
Page 440 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Post-2006 Dry Cleaning
(including spot cleaning)
and Section 4.2.2.13 - Dry
Cleaning and Spot Cleaning0
Based on inhalation*
exposure modeling for
inhalation risks and Section
4.2.3 for dermal risks
Central
Tendency
3.6
11
3.8E-4
179
(APF 50)
527
(APF 50)
7.6E-6
(APF 50)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
3.2
9.5
4.3E-4
N/A
N/A
N/A
Central
Tendency
46
136
2.9E-5
N/A
N/A
N/A
Section 2.4.1.16 - Dry
Cleaning and Spot Cleaning
4th/5th Gen Only Dry
Cleaning (including spot
cleaning)
and Section 4.2.2.13 - Dry
Cleaning and Spot Cleaning0
Based on inhalation*
exposure monitoring data for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.89
3.5
1.5E-3
45
(APF 50)
174
(APF 50)
3.1E-5
(APF 50)
Central
Tendency
5.1
23
1.8E-4
256
(APF 50)
1129
(APF 50)
3.7E-6
(APF 50)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
41
158
3.4E-5
N/A
N/A
N/A
Central
Tendency
358
1582
2.6E-6
N/A
N/A
N/A
Automotive care products (e.g.,
engine degreaser and brake
cleaner)
Section 2.4.1.15 - Aerosol
Degreasing and Aerosol
Lubricants
and Section 4.2.2.12 -
Aerosol Degreasing and
Aerosol Lubricants 0
Based on inhalation*
exposure monitoring data for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.64
2.9
1.8E-3
32
(APF 50)
146
(APF 50)
3.6E-5
(APF 50)
Aerosol cleaner
Central
Tendency
3.5
16
2.6E-4
174
(APF 50)
792
(APF 50)
5.2E-6
(APF 50)
Dermal
High-End
0.80
1.7
3.7E-3
16
(PF 20)
34
(PF 20)
1.9E-4
(PF 20)
Central
Tendency
2.4
5.1
9.6E-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
ONUs
High-End
0.64
2.9
1.8E-3
N/A
N/A
N/A
Page 441 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk 1 Aiimalcs lor \o I'I'I
Risk 1 Isiimales w nil
ppi :
\cule
( limine
\cnie
( limine
l.ilc (>ele
Siaue ( nleuois
Siihcnlcuois
()cciipalioiial 1 Aposiiiv
Scenario and 1 Aposiiic and
Population
1 Aposinc
koine and
1 Aposurc
I.CNCl
\on-
cancer
i he lie li-
ma i'k
\on-
caiicer
(hencli-
niark
Cancer
(bench-
\oii-
caiicer
(bench-
mark
\oii-
cancer
(he lie li-
ma rk
(ancer
(bench-
Risk Section \iimheis
1 )iiialioii
mark
|u )
mark
lo )
\ioi:
\ioi:
\ioi:
\ioi:
KM
Kill)
Hi)
1
liihalalion
8 hr
Central
Tendency
3.5
K.
2.(.i:-4
N/A
N/A
N/A
Section 2.4.1.15- Aerosol
Degreasing and Aerosol
Inhalation
High-End
0.2«>
1.3
3.11.-3
15
(APF 50)
(>(>
( \\'\: 50)
6.3E-5
( \PF50)
Lubricants
and Section 4.2.2.12 -
Worker
8 hr
Central
Tendency
O.'Jl
4.2
y.41.-4
46
(APF 50)
:ox
( \\'\: 50)
1 «®-5
( \PI 50)
Aerosol Degreasing and
Aerosol Lubricants 0
Dermal
High-End
II.SII
\r
3."'1.-3
16
(PF 20)
34
(pi :oi
i.«)i:-4
(PI 20)
Based on inhalation*
exposure modeling for
Central
Tendency
2.4
5.1
•).6i:-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
inhalation risks and Section
Inhalation
8 hr
High-End
(..S
31
i.4i:-4
N/A
N/A
N/A
4.2.3 for dermal risks
ONUs
Central
Tendencs
50
260
2.0E-5
N/A
N/A
N/A
Section 2.4.1.21 - Wipe
Cleaning and Metal/Stone
Polishes
Inhalation
High-Ei id
0.02
0.10
5.31.-2
I.I
( \H ' 50)
5.0
( \H' 50)
I.I 1.-3
( \PI ' 50)
Worker
8 hr
Central
Tendencs
0.04
0.17
2.41.-2
l.'J
( \\>\: 50)
X.(.
( \IJI 50)
4.SI-4
( \PI ' 50)
16
(PF 20)
34
(pi :oi
2.21.-4
( PI 20)
Non-aerosol cleaner
and Section 4.2.2.18 Wipe
Cleaning and Metal/Stone
Polishes 0 for inhalation risks
and Section 4.2.3 for dermal
risks
Dermal
High-Ei id
0."")
\r
4.41.-3
Central
Tendencs
2.4
5.0
1.01-3
47
rPF 20)
101
(PF 20)
5.1L-5
(PF 20)
Inhalation
High-Ei id
0.22
o.ys
5.41.-3
N/A
N/A
N/A
ONUs
Central
Tendencs
8 hr
::<>
1 < >4 -
4 <)| -(.
N/A
N/A
N/A
Lubricants and greases (e.g.,
penetrating lubricants, cutting
Section 2.4.1.15 - Aerosol
Degreasing and Aerosol
Inhalation
High-Ei id
0.(»4
2.')
I.SI-3
32
(APF 50)
146
(APF 50)
3.6E-5
(APF 50)
Commercial use/
Lubricants and
greases
tool coolants, aerosol lubricants)
Lubricants
and Section 4.2.2.12 -
Worker
8 hr
Central
Tendencs
3.5
I(.
2.(.i:-4
174
(APF 50)
792
( \\>\: 50)
5.2E-6
( \PI' 50)
Aerosol Degreasing and
Aerosol Lubricants 0
Dermal
High-Ei id
O.SO
\r
3."'1.-3
16
(PF 20)
34
(pi :oi
i.«)i:-4
(PI 20)
Based on inhalation*
exposure monitoring data for
Central
Tendencs
2.4
5.1
').6l.-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
Page 442 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
inhalation risks and Section
4.2.3 for dermal risks
ONUs
Inhalation
8 lir
High-End
0.64
2.9
1.8E-3
N/A
N/A
N/A
Central
Tendency
3.5
16
2.6E-4
N/A
N/A
N/A
Section 2.4.1.15 - Aerosol
Degreasing and Aerosol
Lubricants
and Section 4.2.2.12 -
Aerosol Degreasing and
Aerosol Lubricants 0
Based on inhalation*
exposure modeling for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.29
1.3
3.1E-3
15
(APF 50)
66
(APF 50)
6.3E-5
(APF 50)
Central
Tendency
0.91
4.2
9.4E-4
46
(APF 50)
208
(APF 50)
1.9E-5
(APF 50)
Dermal
High-End
0.80
1.7
3.7E-3
16
(PF 20)
34
(PF 20)
1.9E-4
(PF 20)
Central
Tendency
2.4
5.1
9.6E-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
6.8
31
1.4E-4
N/A
N/A
N/A
Central
Tendency
50
260
2.0E-5
N/A
N/A
N/A
Section 2.4.1.20 -
Metalworking Fluids
and Section 4.2.2.17 -
Metalworking Fluids 0 for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
239
1087
4.9E-6
2387
(APF 10)
10,875
(APF 10)
4.9E-7
(APF 10)
Central
Tendency
869
3960
1.0E-6
8692
(APF 10)
39,595
(APF 10)
1.0E-7
(APF 10)
Dermal
High-End
12
26
2.5E-4
60
(PF 5)
128
(PF 5)
5.0E-5
(PF 5)
Central
Tendency
36
77
6.4E-5
181
(PF 5)
384
(PF 5)
1.3E-5
(PF 5)
ONUs
Inhalation
8 lir
High-End
239
1087
4.9E-6
N/A
N/A
N/A
Central
Tendency
869
3960
1.0E-6
N/A
N/A
N/A
Commercial use/
Adhesives and
sealant
chemicals
Light repair adhesives
Section 2.4.1.17 - Adhesive,
Sealants, Paints, and
Coatings
and Section 4.2.2.14
Adhesives, Sealants, Paints,
and Coatings
Worker
Inhalation
8 lir
High-End
6.2
28
1.9E-4
62
(APF 10)
281
(APF 10)
1.9E-5
(APF 10)
Central
Tendency
57
257
1.6E-5
565
(APF 10)
2574
(APF 10)
1.6E-6
(APF 10)
High-End
0.98
2.1
3.0E-3
20
(PF 20)
42
(PF 20)
1.5E-4
(PF 20)
Page 443 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Based on Adhesives for
inhalation risks and Section
4.2.3 for dermal risks
Dermal
Commerci
al use
Central
Tendency
3.0
6.3
7.8E-4
59
(PF 20)
126
(PF 20)
3.9E-5
(PF 20)
Dermal
Industrial
use
High-End
1.5
3.2
2.0E-3
30
(PF 20)
64
(PF 20)
9.9E-5
(PF 20)
Central
Tendency
4.5
9.6
5.1E-4
90
(PF 20)
192
(PF 20)
2.6E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
6.2
28
1.9E-4
N/A
N/A
N/A
Central
Tendency
57
257
1.6E-5
N/A
N/A
N/A
Commercial use/
Paints and
coatings
Solvent-based paints and coatings
Section 2.4.1.17- Adhesive,
Sealants, Paints, and
Coatings
and Section 4.2.2.14
Adhesives, Sealants, Paints,
and Coatings
Based on Paints/ Coatings
for inhalation risks and
Section 4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
1.1
5.0
1.1E-3
11
(APF 10)
125
(APF 25)
4.3E-5
(APF 25)
Central
Tendency
21
98
4.2E-5
214
(APF 10)
2440
(APF 25)
1.7E-6
(APF 25)
Dermal
Commerci
al use
High-End
0.98
2.1
3.0E-3
20
(PF 20)
42
(PF 20)
1.5E-4
(PF 20)
Central
Tendency
3.0
6.3
7.8E-4
59
(PF 20)
126
(PF 20)
3.9E-5
(PF 20)
Dermal
Industrial
use
High-End
1.5
3.2
2.0E-3
30
(PF 20)
64
(PF 20)
9.9E-5
(PF 20)
Central
Tendency
4.5
9.6
5.1E-4
90
(PF 20)
192
(PF 20)
2.6E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
1.1
5.0
1.1E-3
N/A
N/A
N/A
Central
Tendency
21
98
4.2E-5
N/A
N/A
N/A
Commercial use/
Other uses
Carpet cleaning
Section 2.4.1.22- Other Spot
Cleaning/Spot Removers
(Including Carpet Cleaning)
and Section 4.2.2.19 - Other
Spot Cleaning/Spot
Removers (Including Carpet
Worker
Inhalation
8 lir
High-End
22
99
5.4E-5
217
(APF 10)
987
(APF 10)
5.4E-6
(APF 10)
Central
Tendency
29
133
3.1E-5
291
(APF 10)
1325
(APF 10)
3.1E-6
(APF 10)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Page 444 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Cleaning)0 for inhalation
risks and Section 4.2.3 for
dermal risks
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
167
759
7.0E-6
N/A
N/A
N/A
Central
Tendency
5.4E-6
N/A
N/A
N/A
Laboratory chemicals
Section 2.4.1.25- Laboratory
Chemicals
N/A - qualitative assessment
Metal (e.g., stainless steel) and
stone polishes
Section 2.4.1.21- Wipe
Cleaning and Metal/Stone
Polishes
and Section 4.2.2.18 - Wipe
Cleaning and Metal/Stone
Polishes 0 for inhalation risks
and Section 4.2.3 for dermal
risks
Worker
Inhalation
8 lir
High-End
0.02
0.10
5.3E-2
1.1
(APF 50)
5.0
(APF 50)
1.1E-3
(APF 50)
Central
Tendency
0.04
0.17
2.4E-2
1.9
(APF 50)
8.6
(APF 50)
4.8E-4
(APF 50)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
0.22
0.98
5.4E-3
N/A
N/A
N/A
Central
Tendency
229
1043
4.0E-6
N/A
N/A
N/A
Inks and ink removal products
Section 2.4.1.24- Other
Commercial Uses
and Section 4.2.2.21 - Other
Commercial Uses Based on
Printing0 for inhalation risks
and Section 4.2.3 for dermal
risks
Worker
Inhalation
8 lir
High-End
0.84
3.8
1.4E-3
21
(APF 25)
192
(APF 50)
5.6E-5
(APF 25)
Central
Tendency
2.6
12
3.5E-4
65
(APF 25)
594
(APF 50)
1.4E-5
(APF 25)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
0.84
3.8
1.4E-3
N/A
N/A
N/A
Central
Tendency
2.6
12
3.5E-4
N/A
N/A
N/A
Section 2.4.1.24- Other
Commercial Uses
Worker
Inhalation
8 lir
High-End
10,000
45,552
1.17E-7
100,000
(APF 10)
455,520
(APF 10)
1.17E-8
(APF 10)
Page 445 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle
Stage/ Category
Subcategory
Occupational Exposure
Scenario and Exposure and
Risk Section Numbers
Population
Exposure
Route and
Duration
Exposure
Level
Risk Estimates for No PPE
Risk Estimates with PPE
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
Acute
Non-
cancer
(bench-
mark
MOE =
10)
Chronic
Non-
cancer
(bench-
mark
MOE =
100)
Cancer
(bench-
mark =
10"4)
and Section 4.2.2.21 - Other
Commercial Uses Based on
Photocopying0 for inhalation
risks and Section 4.2.3 for
dermal risks
Central
Tendency
26,667
121,472
3.40E-8
266,667
(APF 10)
1214,720
(APF 10)
3.40E-9
(APF 10)
Dermal
High-End
0.79
1.7
4.4E-3
16
(PF 20)
34
(PF 20)
2.2E-4
(PF 20)
Central
Tendency
2.4
5.0
1.0E-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
10,000
45,552
1.17E-7
N/A
N/A
N/A
Central
Tendency
26,667
121,472
3.40E-8
N/A
N/A
N/A
Welding
Section 2.4.1.15 - Aerosol
Degreasing and Aerosol
Lubricants
and Section 4.2.2.12 -
Aerosol Degreasing and
Aerosol Lubricants 0
Based on inhalation*
exposure monitoring data for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.64
2.9
1.8E-3
32
(APF 50)
146
(APF 50)
3.6E-5
(APF 50)
Central
Tendency
3.5
16
2.6E-4
174
(APF 50)
792
(APF 50)
5.2E-6
(APF 50)
Dermal
High-End
0.80
1.7
3.7E-3
16
(PF 20)
34
(PF 20)
1.9E-4
(PF 20)
Central
Tendency
2.4
5.1
9.6E-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
0.64
2.9
1.8E-3
N/A
N/A
N/A
Central
Tendency
3.5
16
2.6E-4
N/A
N/A
N/A
Section 2.4.1.15- Aerosol
Degreasing and Aerosol
Lubricants
and Section 4.2.2.12 -
Aerosol Degreasing and
Aerosol Lubricants 0
Based on inhalation*
exposure modeling for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 lir
High-End
0.29
1.3
3.1E-3
15
(APF 50)
66
(APF 50)
6.3E-5
(APF 50)
Central
Tendency
0.91
4.2
9.4E-4
46
(APF 50)
208
(APF 50)
1.9E-5
(APF 50)
Dermal
High-End
0.80
1.7
3.7E-3
16
(PF 20)
34
(PF 20)
1.9E-4
(PF 20)
Central
Tendency
2.4
5.1
9.6E-4
48
(PF 20)
103
(PF 20)
4.8E-5
(PF 20)
ONUs
Inhalation
8 lir
High-End
6.8
31
1.4E-4
N/A
N/A
N/A
Central
Tendency
50
260
2.0E-5
N/A
N/A
N/A
Page 446 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
l.ilc (>ele
Siaue ( aleuors
SuhealeuoiA
()cciipalional 1 Aposiiiv
Scenario and 1 Aposiiic and
Risk Section \iimheis
Population
1 Aposlll'C
Runic and
1 )iiralioii
1 Aposlll'C
l.c\el
Risk 1 Aiimales lor \o I'I'I
Risk 1 !simiales u nil PPI!
\cule
\on-
cancer
i he lie li-
ma i'k
\I()L
KM
Chronic
\on-
cancer
(hencli-
niark
\I()L
Kill)
Cancer
(bench-
mark
In )
\cnie
Noil-
cancer
(bench-
mark
\l()L
Hi)
( limine
\oii-
cancer
(he nc li-
ma rk
\I()L
1
Cancer
(bench-
mark
In )
Pholograpliic film
Section 2.4.1.24 Oilier
Commercial Uses
and Section 4.2.2.21 - Other
Commercial Uses Based on
Photographic Film0 for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 hr
High-End
O.OX'J
0.40
1.31.-2
4.4
( \PI' 5(1)
20
( \IJI" 50)
2.(.i:-4
( \PI" 50)
Central
Tendency
0.-")
3.(i
i.i i :-3
40
(APF 50)
181
(APF 5(1)
2.3E-5
( \\>\: 50)
Dermal
High-End
0.7')
\r
4.41.-3
16
(PF 20)
34
(pi :oi
2.2I--4
(PI 20)
Central
Tendency
2.4
5.0
1.01-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 hr
High-End
0.0X«>
0.40
1.31.-2
N/A
N/A
N/A
Central
Tendency
3.(i
I.I 1.-3
N/A
N/A
N/A
Mold cleaning, release and
protectant products
Section 2.4.1.24- Other
Commercial Uses
and Section 4.2.2.21 - Other
Commercial Uses Based on
Mold Release 0 for inhalation
risks and Section 4.2.3 for
dermal risks
Worker
Inhalation
8 hr
High-End
25
114
4.7E-5
250
(APF10)
1139
(APF 10)
4.7E-6
(APF 10)
Central
Tendencv
5(1
::s
i si :-5
500
(APF10)
2278
( \\>\: Id)
1.8E-6
( \PI 10)
Dermal
High-Ei id
0."")
\r
4.41.-3
16
(PF 20)
34
(pf :iD
2.21.-4
(PL 20)
Central
Tendencs
2.4
5.0
1.01-3
47
(PF 20)
101
(PF 20)
5.1E-5
(PF 20)
ONUs
Inhalation
8 hr
High-Ei id
25
114
4,~L-5
N/A
N/A
N/A
Central
Tendency
50
228
1.8E-5
N/A
N/A
N/A
Disposal/
Disposal
Industrial pre-treatment
Industrial wastewater treatment
Publicly owned treatment works
(POTW)
Section 2.4.1.26- Waste
Handling, Disposal,
Treatment, and Recycling
and Section 4.2.2.23 - Waste
Handling, Disposal,
Treatment, and Recycling for
inhalation risks and Section
4.2.3 for dermal risks
Worker
Inhalation
8 hr
High-End
139
633
8.4E-6
1390
(APF 10)
6331
(APF 10)
8.4E-7
(APF 10)
Underground injection
Central
Tendency
<.:x
:s(.:
1 41:-(.
6284
(APF 10)
28,624
( \\>\: Id)
1.4E-7
( \PI' 10)
Municipal landfill
Hazardous landfill
Dermal
High-End
1.2
2.(i
2.51.-3
24
(PF 20)
51
1 PI" 20)
1.21.-4
(PI- 20)
Other land disposal
Central
Tendency
3.(i
7.7
(..41-4
72
(PF 20))
154
(PF 20)
3.2E-5
(PF 20)
Page 447 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk 1 Aiimales lor \o I'I'I
Risk 1 Isimiales u nil
m:
\eule
( limine
\enle
( limine
l.ilc (>ele
Siaue ( aleuors
SuhealeuoiA
()cciipalioiial 1 \posiirc
Scenario and 1 Aposnre and
Risk Section Numbers
Kipiilalion
1 \posure
koine and
1 )nralioii
1 Aposure
l.e\el
\on-
eaueer
i he lie li-
ma rk
\on-
eaneer
(bench-
mark
Cancer
(bench-
mark
In )
Noil-
cancer
(bench-
mark
\on-
eaneer
(be lie li-
ma rk
(aneer
(bench-
mark
In )
\I()L
\I()L
\1( )l:
\I()L
KM
Kill)
Hi)
1
Municipal waste incinerator
High-End
139
633
8.4E-6
N/A
N/A
N/A
Hazardous waste incinerator
ONUs
Inhalation
Off-site waste transfer
8 hr
Central
Tendency
628
2862
1.4E-6
N/A
N/A
N/A
10099 N/A = not assessed because ONUs are not assumed to be wearing PPE
10100 * exposure scenarios with both inhalation exposure monitoring data and inhalation exposure modeling present risk calculations for both exposure results, note that all
10101 dermal exposures were modeled
10102 a EPA assessed PCE as a reactant where it was produced as a byproduct from EDC manufacture and reused as a reactant
10103 b Identified welding products were anti-spatter aerosol products; therefore, the assessment is included with the assessment of other aerosol products.
10104 0 EPA believes that small commercial facilities using PCE for aerosol degreasing and lubrication, dry cleaning, metalworking fluid, wipe cleaning, spot cleaning, or other
10105 commercial uses are unlikely to have a respiratory protection program. Therefore, the use of respirators is unlikely for workers in these facilities.
Page 448 of 636
-------
10106
10107
10108
10109
10110
10111
10112
10113
10114
10115
10116
10117
10118
10119
10120
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
4.5.2.2 Summary of Risk Estimates for Inhalation and Dermal Exposures to
Consumers and Bystanders
Table 4-113 summarizes the risk estimates for inhalation and dermal exposures for all consumer
exposure scenarios. Risk estimates that exceed the benchmark (i.e. MOEs less than the benchmark
MOE) are highlighted by bolding the number and shading the cell. The risk characterization is described
in more detail in Section 4.2.2 and specific links to the exposure and risk characterization sections are
listed in Table 4-113 in the column headed Consumer Exposure Scenario.
Dermal risk estimates for all three consumer age groups (11-15 years, 16 - 20 years) and adults (>21)
are presented for each exposure scenario in Section 4.2.4. Overall the differences in the MOEs between
age groups are approximately 10% or less and none of the exposure scenarios have MOEs close enough
to the benchmark MOE to result in different risk results depending on the age group selected. Table
4-113 presents dermal exposures for the most sensitive age group (11-15 years).
Page 449 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
10121 Table 4-113 Summary of Risk Estimates for CNS effects from Acute Inhalation and Dermal Exposures to Consumers by Conditions
10122 of Use
Category
Sub Category
Consumer Exposure Scenario
Exposure Route
and Duration
Scenario Description
User MOE
(benchmark
MOE = 10)
Bystander
MOE
(benchmark
MOE = 10)
Cleaning and
furniture care
products
Cleaners and
degreasers
(other)
Section 2.4.2.3.1- Aerosol Degreasers
(includes: marine cleaner, degreaser, coil
cleaner, electric motor cleaner, parts cleaner,
cable cleaner, stainless steel polish,
electrical/energized cleaner, wire and
ignition demoisturants, electric motor
cleaner; brake cleaners)
Section 4.2.4.1 Aerosol Cleaners for Motors,
Coils, Electrical Parts, Cables, Stainless
Steel and marine Equipment, and Wire and
Ignition Demoisturants
Inhalation 24-hr
Low Intensity User
7.7
39
Moderate Intensity User
0.2
0.8
High Intensity User
1.3E-02
5.2E-02
Dermal1
Low Intensity User
35
N/A
Moderate Intensity User
0.6
N/A
High Intensity User
5.8E-02
N/A
Dry cleaning
solvent
Section 2.4.2.4.2 and Section 2.4.2.4.3- Dry
Cleaned Articles
Section 4.2.4.16 Dry Cleaned Clothing
Inhalation 24-hr
Stay-at-home Adult and
Child
156
486
Dermal1
Assumed dry cleaning
Technology
(Events, days after
cleaning)
User, Half-
Body MOE
User, Full-
Body MOE
2nd and 3rd genearation
(single, 1 day)
8.6
2.9
2nd and 3rd genearation
(single, 2 day)
11
3.7
2nd and 3rd genearation
(single, 3 day)
15
4.9
4nd and 5th genearation
(single, 1 day)
49
16
4nd and 5th genearation
(single, 2 day)
64
21
4nd and 5th genearation
(single, 3 day)
83
28
4nd and 5th genearation
(repeat, 1 day)
16
5.2
4nd and 5th genearation
(repeat, 2 day)
20
6.7
Page 450 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Category
Sub Category
Consumer Exposure Scenario
Exposure Route
and Duration
Scenario Description
User MOE
(benchmark
MOE = 10)
Bystander
MOE
(benchmark
MOE = 10) |
4nd and 5th genearation
(repeat, 3 day)
26
8.7
Automotive care
products (e.g.,
engine degreaser
and brake
cleaner)
Section 2.4.2.3.1 - Brake Cleaner
Section 4.2.4.2 Aerosol Brake Cleaners
Inhalation 24-hr
Low Intensity User
2.0
7.1
Moderate Intensity User
0.2
0.8
High Intensity User
4.5E-02
0.2
Dermal1
Low Intensity User
21
N/A
Moderate Intensity User
0.6
N/A
High Intensity User
7.1E-02
N/A
Section 2.4.2.3.2 - Parts Cleaner
Section 4.2.4.3 Parts Cleaners
Inhalation 24-hr
Low Intensity User
31
174
Moderate Intensity User
0.6
3.3
High Intensity User
7.1E-02
0.4
Dermal1
Low Intensity User
0.2
N/A
Moderate Intensity User
1.3E-02
N/A
High Intensity User
2.1E-02
N/A
Aerosol cleaner
Section 2.4.2.3.3 - Vandalism Mark & Stain
Remover, Mold Cleaner, Weld Splatter
Protectant
Section 4.2.4.4 Vandalism Stain Removers,
Mold Cleaners, and Weld Splatter
Protectants
Inhalation 24-hr
Low Intensity User
15
77
Moderate Intensity User
0.3
1.6
High Intensity User
1.3E-02
5.2E-02
Dermal1
Low Intensity User
N/E
N/A
Moderate Intensity User
N/E
N/A
High Intensity User
N/E
N/A
Non-aerosol
cleaner
Section 2.4.2.3.4 - Marble and Stone Polish
(liquid)
Section 4.2.4.5 Marble Polish
Inhalation 24-hr
Low Intensity User
3.3
17
Moderate Intensity User
6.8E-02
0.4
High Intensity User
1.2E-02
5.0E-02
Dermal1
Low Intensity User
3.5
N/A
Moderate Intensity User
5.4E-02
N/A
High Intensity User
5.8E-03
N/A
Section 2.4.2.3.5-Cutting Fluid
Inhalation 24-hr
Low Intensity User
8.1
39
Page 451 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
( iilejion
Siih ( 'iiU'iion
Consumi'i- l.\|)osiirc Scoiiiirio
Mxposuiv Knuli*
iiml Diinilion
Scoiiiirio Dcscriplion
I ser MOI.
(bench in ;uk
M()l.= 10)
litMiimk'r
moi:
(hencli in ;i rk
MOI. = 10)
Lubricants and
greases
Lubricants and
greases (e.g.,
penetrating
lubricants,
cutting tool
coolants, aerosol
lubricants)
Seclioii 4 2 4 <> ('lining I'luid
Moderate liiioiis>il\ I ser
1.3
(i.-7
High Intensity I ser
0.1
!!.(>
Dermal1
Low Intensity User
N/E
N/A
Moderate Intensity User
N/E
N/A
High Intensity User
N/E
N/A
Section 2.4.2.3.6- Spray Lubricant and
Penetrating Oil
Section 4.2.4.7 Lubricants and Penetrating
Oils
Inhalation 24-hr
Low Intensity User
90
435
Moderate Intensity User
1.4
"\3
High Intensity User
s.oi:-o2
0.4
Dermal1
Low Intensity User
\ L
\ A
Moderate Intensity User
N/E
N/A
High Intensity User
N/E
N/A
Adhesives and
sealant
chemicals
Adhesives for
arts and crafts
Section 2.4.2.3.7-Adhesives (includes
industrial adhesive, arts and crafts adhesive,
gun ammunition sealant)
Section 4.2.4.8 Adhesives
Inhalation 24-hr
Low Intensity User
29
Moderate Intensity User
2.3
12
High Intensity User
0.1
0.5
Dermal1
Low Intensity User
N/E
N/A
Moderate Intensity User
N/E
N/A
High Intensity User
N/E
N/A
Section 2.4.2.3.8-Livestock Grooming
Adhesive
Section 4.2.4.9 Livestock Grooming
Adhesive
Inhalation 24-hr
Low Intensity User
112
539
Moderate Intensity User
12
64
High Intensity User
O.S
3.0
Dermal1
Low Intensity User
N/E
N/A
Moderate Intensity User
N/E
N/A
High Intensity User
N/E
N/A
Light repair
adhesives
Section2.4.2.3.9-Column Adhesive, Caulk
and Sealant
Section 4.2.4.10 Caulks, Sealants and
Column Adhesives
Inhalation 24-hr
Low Intensity User
i<>:
N/E
Moderate Intensity User
2.3
N/E
High Intensity User
"7.2i:-02
N/E
Dermal1
Low Intensity User
N/E
N/A
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QUOTE
I ser MOI.
(bench in ;uk
M()l.= 10)
IS\M;ni(k'r
( iilejion
Siih ( 'iiU'iion
Consumi'i- l.\|)osiirc Scoiiiirio
Mxposuiv Knuli*
iiml Diinilion
Scoiiiirio Dcscriplion
moi:
(hencli in ;i rk
MOI. = 10)
Moderate Intensity User
XL
XA
High Intensity User
XT
N/A
Section 2.4.2.3.10-Outdoor Water Shield
Low Intensity User
:<>
(liquid)
Section 4.2.4.11 Outdoor Water Shield
Inhalation 24-hr
Moderate Intensity User
1.1
3.3
High Intensity User
s.')i:-o2
0.4
Low Intensity User
0.1
\ \
Dermal1
Moderate Intensity User
2.5I-.-02
\ \
High Intensity User
5.01-:-02
XA
Low Intensity User
522
13448
Section2.4.2.3.11 - Coatings and primers
(aerosol)
Inhalation 24-hr
Moderate Intensity User
62
2143
High Intensity User
5.')
209
Section 4.2.4.12 Aerosol Coatings and
Low Intensity User
N/E
N/A
Solvent-based
paints and
coatings
Primers
Dermal1
Moderate Intensity User
N/E
N/A
Paints and
High Intensity User
N/E
N/A
coatings
Low Intensity User
10600
128556
Section 2.4.2.3.12 - Rust Primer and Sealant
(liquid)
Section 4.2.4.13 Liquid Primers and Sealants
Inhalation 24-hr
Moderate Intensity User
1163
12434
High Intensity User
36
229
Low Intensity User
1.4
N/A
Dermal1
Moderate Intensity User
i.si:-o2
N/A
High Intensity User
1.(.1.-02
N/A
Low Intensity User
4372
21107
Inhalation 24-hr
Moderate Intensity User
337
1674
Section 2.4.2.3.13-Metallic Overglaze
High Intensity User
21
81
Section 4.2.4.14 Metallic Overglaze
Low Intensity User
N/E
N/A
Dermal1
Moderate Intensity User
N/E
N/A
High Intensity User
N/E
N/A
Other Uses
Inhalation 24-hr
Low Intensity User
I.I
5.3
Page 453 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
( iilejion
Siih ( 'iiU'iion
Consumi'i- l.\|)osiirc Scoiiiirio
Mxposuiv Knuli*
iiml Diinilion
Scoiiiirio Dcscriplion
I ser MOI.
(bench in ;uk
M()l.= 10)
|}\s(;iii(kr
moi:
(hencli in ;i rk
M()i:= lot
Metal (e.g.,
stainless steel)
and stone
polishes
Section 2.4.2.3.14-Marble and Stone Polish
(wax)
Section 4.2.4.15 Metal and Stone Polish
Moderate liiLcut? 11 \ I ser
0.2
o.s
High Intensity I ser
1.51.-02
11.-02
Dermal1
Low Intensity User
1.0
N/A
Moderate Intensity User
0.1
N/A
High Intensity User
I.JF.-02
N/A
Inks and ink
removal products
Ink removal combined under Aerosol Cleaner (vandalism and stain remover); use in printing inks discussed as "other use"
Welding
Identified welding products were anti-spatter aerosol products; therefore, the assessment is included with the assessment of
other aerosol products combined under Aerosol Cleaner (weld splatter protectant)
Mold cleaning,
release and
protectant
products
Combined under Aerosol Cleaner (mold cleaner)
10123 1 Dermal exposure presented here are the youth age group (11-15 years). Three age groups are presented for each COU in section 4.2.4. Overall the differences in the
10124 MOEs between age groups are approximately 10% or less.
10125 N/A = not assessed because bystanders are assumed to not have dermal contact with liquid PCE
10126 N/E = not evaluated because dermal exposures to consumers are not expected for these uses because for the caulks, sealants and column adhesives consumer use the area
10127 of use was assumed to be outdoors, so bystander exposure was not estimated.
10128
10129
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10130
10131
10132
10133
10134
10135
10136
10137
10138
10139
10140
10141
10142
10143
10144
10145
10146
10147
10148
10149
10150
10151
10152
10153
10154
10155
10156
10157
10158
10159
10160
10161
10162
10163
10164
10165
10166
10167
10168
10169
10170
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5 RISK DETERMINATION
5.1 Unreasonable Risk
5.1.1 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. These
determinations do not consider costs or other non-risk factors. In making these determinations, 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 (PESS)); the severity of hazard (including the nature of the hazard, the irreversibility of
the hazard); and uncertainties. EPA also takes into consideration the Agency's confidence in the data
used in the risk estimate. This 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, ( 2017h)).19
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 of injury to health may be indicated when health risks under the conditions of use
are identified by comparing the estimated risks with the risk benchmarks and where the risks affect the
general population or PESS, identified as relevant. For workers (which are one example of PESS), an
unreasonable risk may be indicated when 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 of injury to the environment may be indicated when
environmental risks under the conditions of use are greater than environmental risk benchmarks. The
risk estimates contribute to the evidence EPA uses to determine unreasonable risk.
EPA uses the term "indicates unreasonable risk" to indicate EPA concern for potential unreasonable
risk. For non-cancer endpoints, "less than the MOE benchmark" is used to indicate potential
unreasonable risk; this occurs if an MOE value is less than the benchmark MOE (e.g., MOE 0.3 <
benchmark MOE 30). For cancer endpoints, EPA uses the term "greater than risk benchmark" to
indicate potential unreasonable risk; this occurs, for example, 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 environmental endpoints, to indicate potential
unreasonable risk EPA uses a risk quotient (RQ) value "greater than 1" (i.e., RQ >1). Conversely, EPA
uses the term "does not indicate unreasonable risk" to indicate that it is unlikely that EPA has a concern
for potential unreasonable risk. More details are described below.
19 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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10171
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10173
10174
10175
10176
10177
10178
10179
10180
10181
10182
10183
10184
10185
10186
10187
10188
10189
10190
10191
10192
10193
10194
10195
10196
10197
10198
10199
10200
10201
10202
10203
10204
10205
10206
10207
10208
10209
10210
10211
10212
10213
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
The degree of uncertainty surrounding the MOEs, cancer risk or RQs 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 (i.e., 95th percentile) are generally intended to cover individuals or sub-populations
with greater exposure (PESS) and central tendency risk estimates are generally estimates of average or
typical exposure.
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.
5.1.2 Risks to Human Health
5.1.2.1 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, and kidney and liver effects. The
MOE is the point of departure (POD) (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 for the MOE that is used accounts for
the total uncertainty in a POD, 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 (LOAEL) rather than from a NOAEL. MOEs can 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 that is less than the benchmark MOE indicates the possibility of non-cancer 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 non-cancer risk.
Uncertainty factors (UFs) 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 UFs relevant to a given POD as described above were applied). A higher benchmark
Page 456 of 636
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10217
10218
10219
10220
10221
10222
10223
10224
10225
10226
10227
10228
10229
10230
10231
10232
10233
10234
10235
10236
10237
10238
10239
10240
10241
10242
10243
10244
10245
10246
10247
10248
10249
10250
10251
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
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.
5.1.2.2 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)) 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 PESS.20
For the subject chemical substance, the EPA, consistent with 2017 NIOSH guidance,21 used 1 x 10"4 as
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 make risk determinations based on other
benchmarks as appropriate. It is important to note that exposure-related considerations (duration,
magnitude, population exposed) can affect EPA's estimates of the excess lifetime cancer risk.
5.1.3 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 released to the environment (e.g., surface water, sediment, soil, biota) under the
conditions of use, based on the fate properties, release potential, and reasonably available environmental
monitoring and hazard data.
Environmental risks are estimated by calculating a 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 is greater than 1, the exposure is greater than the effect concentration and there is potential for risk.
If the RQ is less than 1, the exposure is less than the effect concentration and unreasonable risk is not
likely. The Concentrations of Concern (COC) 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 exceeds 1 for the conditions of use being evaluated. Consistent
with EPA's human health evaluations, the RQ is not treated as a bright line and other risk-based factors
20 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 (U.S. EPA 2017d). 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 "presumptive limit on maximum individual
lifetime [cancer] risk (MIR) of approximately 1 in 10 thousand" 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 38044, 38045, (Federal Register
1989)).
21 NIOSH Current intelligence bulletin 68: NIOSH chemical carcinogen policy (Whittaker et at 20.1.6').
Page 457 of 636
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10253
10254
10255
10256
10257
10258
10259
10260
10261
10262
10263
10264
10265
10266
10267
10268
10269
10270
10271
10272
10273
10274
10275
10276
10277
10278
10279
10280
10281
10282
10283
10284
10285
10286
10287
10288
10289
10290
10291
10292
10293
10294
10295
10296
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
may be considered (e.g., exposure scenario, uncertainty, severity of effect) for purposes of making a risk
determination.
5.2 Risk Determinations for PCE
EPA's draft determinations of unreasonable risk for specific conditions of use of PCE listed below are
based on environmental risks to aquatic organisms, health risks to workers and occupational non-users
(ONUs) during occupational exposures, and health risks to consumers and bystanders during exposures
to consumer uses.
For risks to the environment, as described in Section 4, EPA identified environmental risks to aquatic
organisms (aquatic invertebrates, fish, and aquatic plants). In Table 5-1 and Section 5.3 below, the driver
endpoints for EPA's preliminary determination of unreasonable risks to aquatic organisms are
immobilization from acute exposure, growth effects from chronic exposure, and mortality to algae.
For risks to health, as described in Section 4, significant risks associated with more than one adverse
effect (e.g. central nervous system, kidney, liver, immune system and developmental toxicity) were
identified for particular conditions of use. The evaluation of cancer included estimates of risk of lung
and liver tumors. In Table 5-1 and Section 5.3 below, EPA identifies neurotoxicity as the driver
endpoint for the conditions of use that EPA has preliminarily determined present unreasonable risks.
This is the effect that is most sensitive, and it is expected that addressing risks for this effect would
address other identified risks.
• Workers: EPA evaluated workers' acute and chronic inhalation and dermal exposures for cancer
and non-cancer risks and determined whether any risks are unreasonable. The drivers for EPA's
determination of unreasonable risk for workers are neurotoxicity from acute and chronic
inhalation and dermal exposures and cancer from chronic inhalation and dermal exposures. The
determinations reflect the effects associated with the occupational exposures to PCE and
incorporate consideration of assumed PPE. 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. Estimated numbers of workers
are in Section 2.4.1.2. EPA estimated dermal exposures using the Dermal Exposure to Volatile
Liquids Model because dermal exposure data were not reasonably available for the conditions of
use.
• Occupational Non-Users (ONUs): EPA considers occupational non-users to be a subset of
workers for whom the potential inhalation exposures may differ based on proximity to the
exposure source. ONU inhalation exposures are expected to be lower than inhalation exposures
for workers directly handling the chemical substance. EPA evaluated ONU acute and chronic
inhalation exposures for cancer and non-cancer risks and determined whether any risks are
unreasonable. The drivers for EPA's determination of unreasonable risks to ONUs are
neurotoxicity from acute and chronic inhalation exposures and cancer from chronic inhalation
exposures. The determinations reflect the effects associated with the occupational exposures to
PCE and the assumed absence of PPE for ONUs. For dermal exposures, because ONUs are not
expected to be dermally exposed to PCE, dermal risks to ONUs were not evaluated. For
inhalation exposures, EPA, where possible, used monitoring or modeling information to estimate
ONU exposures and to describe the risks separately from workers directly exposed. For some
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10297
10298
10299
10300
10301
10302
10303
10304
10305
10306
10307
10308
10309
10310
10311
10312
10313
10314
10315
10316
10317
10318
10319
10320
10321
10322
10323
10324
10325
10326
10327
10328
10329
10330
10331
10332
10333
10334
10335
10336
10337
10338
10339
10340
10341
10342
10343
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
conditions of use, EPA did not separately calculate risk estimates for ONUs and workers. For
these conditions of use, there is uncertainty in the ONU risk estimates since the data or modeling
did not distinguish between worker and ONU inhalation exposure estimates. ONU inhalation
exposures are expected to be lower than inhalation exposures for workers directly handling the
chemical substance; however, the relative exposure of ONUs to workers in these cases cannot be
quantified. To account for this uncertainty, EPA considered the central tendency risk estimate for
workers when determining ONU risk for those conditions of use for which ONU exposures were
not separately estimated. Estimated numbers of occupational non-users are in Section 2.4.1.2.
• Consumers: EPA evaluated consumer acute inhalation and dermal exposures for non-cancer risks
and determined whether any risks are unreasonable. The driver for EPA's determination of
unreasonable risk is neurotoxicity from acute inhalation and dermal exposures. Generally, risks
for consumers were indicated by acute inhalation and dermal exposure at low, medium, and high
intensity use. For nearly half of the consumer uses, dermal exposure was not evaluated because
PCE is a volatile solvent and is expected to quickly evaporate from skin. However, for certain
consumer use scenarios product evaporation may be limited (e.g., handling/wiping using a
solvent soaked rag). For these conditions of use, consumer dermal exposure was evaluated.
Estimated numbers of consumers are in Section 2.4.2.2.
• Bystanders (from consumer uses): EPA evaluated bystander acute inhalation exposures for non-
cancer risks and determined whether any risks are unreasonable. The driver for EPA's
determination of unreasonable risk are neurotoxicity from acute inhalation exposure. Generally,
risks for bystanders were indicated by acute inhalation exposure scenarios at low, medium, and
high intensity use. Because bystanders are not expected to be dermally exposed to PCE, dermal
non-cancer risks to bystanders were not evaluated. Estimated numbers of bystanders are in
Section 2.4.2.2.
• Environmental risks: EPA determined that environmental exposures are expected for aquatic
organisms for the conditions of use within the scope of the risk evaluation. EPA's evaluation
assessed risks to aquatic organisms because PCE has low bioconcentration potential and
moderate potential to accumulate in wastewater biosolids, soil, or sediment. The drivers for
EPA's draft determination of unreasonable risks to aquatic organisms are immobilization from
acute exposure, growth effects from chronic exposure, and mortality to algae. Algae was
assessed separately and not incorporated into acute or chronic COCs, because durations normally
considered acute for other species (e.g. 48, 72 hours) can encompass several generations of
algae. Confidence in acute and chronic COCs for fish and invertebrates are high. The confidence
in algae COC is medium given that the COC for algae is based on a single study and that data
were only available for three algal species that may not represent the most sensitive species at a
given site. Algae species tend to vary widely in their sensitivity to chemical pollutants and the
sites assessed included both free-flowing water bodies (i.e., rivers and streams) and still water
bodies (i.e., bays, lakes, and estuaries). Because current regulations do not require facilities to
report the number of days associated with reported releases, EPA estimated site-specific surface
water concentrations for discharges using upper and lower bounds for the range of predicted
surface water concentrations. Details of EPA's estimates are in Section 4.1.2 and include
consideration of the number of facility operating days per year, partial removal of PCE from
industrial wastes or wastewater following treatment, and the impacts of any direct releases of
wastes to surface waters without treatment. Site-specific surface water concentration estimates
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10344 for free-flowing water bodies were reported for both the 7Q10 (the lowest consecutive 7-day
10345 average flow during any 10-year period) and harmonic mean stream flows. Based on the
10346 estimated surface water PCE concentration and COC confidence levels, the overall confidence in
10347 the risk estimate to aquatic organisms from exposure to PCE is medium. In general, the majority
10348 of releases of PCE to the aquatic environment do not exceed the aquatic benchmark. However,
10349 there are specific facilities for given COUs where estimated or reported releases result in
10350 modeled surface water concentrations that exceed the aquatic benchmark (see Section 4.1.2).
10351 While nine COUs had RQs > 1, indicating risk, no risks were identified for aquatic organisms for
10352 all other COUs. EPA's preliminary determination regarding unreasonable risks for each of the
10353 nine COUs indicating risks is discussed further under the specific COU in Section 5.3.
10354
10355 As described below, risks to the general population were not evaluated.
10356 • General population: Exposure pathways to the general population are covered by other statutes and
10357 consist of: the ambient air pathway (i.e., PCE is listed as a hazardous air pollutant (HAP) in the
10358 Clean Air Act (CAA)), the drinking water pathway (i.e., National Primary Drinking Water
10359 Regulations (NPDWRs) are promulgated for PCE under the Safe Drinking Water Act), ambient
10360 water pathways (i.e., PCE is a priority pollutant with recommended water quality criteria for
10361 protection of human health under the CWA), biosolids pathways (i.e., PCE has been identified in
10362 biosolids biennial reviews under the CWA), disposal pathways (PCE disposal is managed and
10363 prevented from further environmental release by RCRA and SDWA regulations). As described
10364 above, other environmental statutes administered by EPA adequately assess and effectively manage
10365 these exposures. EPA believes that the TSCA risk evaluation should focus on those exposure
10366 pathways associated with TSCA conditions of use that are not subject to the regulatory regimes
10367 discussed above because those pathways are likely to represent the greatest areas of concern to EPA.
10368 Therefore, EPA did not evaluate hazards or exposures to the general population in this risk
10369 evaluation, and there is no risk determination for the general population.
10370
10371 Table 5-1 below presents an overview of risk determinations by condition of use. An in-depth
10372 explanation of each determination follows the table, in Section 5.3. For the conditions of use where EPA
10373 found no unreasonable risk, EPA describes the estimated risks in Section 4.4 (or Section 2.4.3).
10374
10375 Table 5-1. Summary of Unreasonable Risk Determinations by Condition of Use
Condition of Use
Unreasonable Risk Determination
Manufacture - Domestic Manufacture
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present an unreasonable risk of injury
to the environment (aquatic organisms).
Manufacture - Import (includes repackaging and
loading/unloading)
Presents an unreasonable risk of injury to
health (workers and occupational non-users
(ONUs)).
Does not present an unreasonable risk of injury
to the environment (aquatic organisms).
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Condition of Use
Unreasonable Risk Determination
Processing - Processing as a reactant/intermediate in
industrial gas manufacturing; intermediate in basic organic
chemical manufacturing; intermediate in petroleum
refineries; residual or byproduct reused as a reactant
Presents an unreasonable risk of injury to
health (workers).
Presents an unreasonable risk to the
environment (aquatic organisms).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Processing - Incorporation into formulation, mixture or
reaction product - Cleaning and degreasing products
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Processing - Incorporation into formulation, mixture or
reaction product - Adhesive and sealant products
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Processing - Incorporation into formulation, mixture or
reaction product - Paint and coating products
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Processing - Incorporation into formulation, mixture or
reaction product - Other chemical products and preparations
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Processing - Repackaging - Solvents (for cleaning or
degreasing); intermediate
Presents an unreasonable risk of injury to
health (workers and occupational non-users
(ONUs)).
Does not present an unreasonable risk of injury
to the environment (aquatic organisms).
Processing - Recycling
Presents an unreasonable risk of injury to
health (workers).
Presents an unreasonable risk to the
environment (aquatic organisms).
Does not present an unreasonable risk of injury
to health (occupational non-users).
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Condition of Use
Unreasonable Risk Determination
Distribution in Commerce
Does not present an unreasonable risk of injury
to health (workers and occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Solvents (for cleaning or degreasing) -
Batch vapor degreaser (open-top)
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Solvents (for cleaning or degreasing) -
Batch vapor degreaser (closed-loop)
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Solvents (for cleaning or degreasing) - In-
line vapor degreaser (conveyorized)
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Solvents (for cleaning or degreasing) - In-
line vapor degreaser (web cleaner)
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Solvents (for cleaning or degreasing) - Cold
cleaner
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Solvents (for cleaning or degreasing) -
Aerosol spray degreaser/cleaner
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial Use - Cleaning and furniture care products - Dry
Cleaning and Spot Cleaning Post-2006 Dry Cleaning
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
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Condition of Use
Unreasonable Risk Determination
Industrial Use - Cleaning and furniture care products - Dry
Cleaning and Spot Cleaning 4th/5th Gen Only Dry Cleaning
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Lubricants and greases - Lubricants and
greases (aerosol lubricants)
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Lubricants and greases - Lubricants and
greases (e.g., penetrating lubricants, cutting tool coolants)
Does not present an unreasonable risk of injury
to health (workers and occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Adhesives and sealants - Solvent-based
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).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Paints and coatings - Solvent-based paints
and coatings
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Paints and coatings - Maskant for Chemical
Milling
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Processing aids, not otherwise listed -
Pesticide, fertilizer and other agricultural chemical
manufacturing
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
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Condition of Use
Unreasonable Risk Determination
Industrial use - Processing aids, specific to petroleum
production - Catalyst regeneration in petrochemical
manufacturing
Presents an unreasonable risk of injury to
health (workers).
Presents an unreasonable risk to the
environment (aquatic organisms).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Industrial use - Other uses - Textile processing (spot
cleaning)
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Other uses - Textile processing (other)
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Other uses - Wood furniture manufacturing
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Other uses - Laboratory chemicals
Does not present an unreasonable risk of injury
to health (workers and ONUs).
Does not present unreasonable risk to the
environment (aquatic organisms).
Industrial use - Other uses - Foundry applications
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Cleaning and furniture care products -
Cleaners and degreasers (other) (wipe cleaning)
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
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Condition of Use
Unreasonable Risk Determination
Commercial Use - Cleaning and furniture care products -
Cleaners and degreasers (other) (Other Spot Cleaning/Spot
Removers (Including Carpet Cleaning))
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Cleaning and furniture care products -
Cleaners and degreasers (other) (Mold Release)
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Cleaning and furniture care products -
Dry Cleaning and Spot Cleaning Post-2006 Dry Cleaning
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Cleaning and furniture care products -
Dry Cleaning and Spot Cleaning 4th/5th Gen Only Dry
Cleaning
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Cleaning and furniture care products -
Automotive care products (e.g., engine degreaser and brake
cleaner)
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Cleaning and furniture care products -
Aerosol cleaner
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Cleaning and furniture care products -
Non-aerosol cleaner
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
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Condition of Use
Unreasonable Risk Determination
Commercial Use - Lubricants and greases - Lubricants and
greases (aerosol lubricants)
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Lubricants and greases - Lubricants and
greases (e.g., penetrating lubricants, cutting tool coolants,
aerosol lubricants)
Does not present an unreasonable risk of injury
to health (workers and occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Adhesives and sealant chemicals - Light
repair adhesives
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial Use - Paints and coatings - Solvent-based
paints and coatings
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial use - Other uses - Carpet cleaning
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial use - Other uses - Laboratory chemicals
Does not present an unreasonable risk of injury
to health (workers and occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial use - Other uses - Metal (e.g., stainless steel)
and stone polishes
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial use - Other uses - Inks and ink removal
products (based on printing)
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
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Condition of Use
Unreasonable Risk Determination
Commercial use - Other uses - Inks and ink removal
products (based on photocopying)
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial use - Other uses - Welding
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial use - Other uses - Photographic film
Presents an unreasonable risk of injury to
health (workers and occupational non-
users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Commercial use - Other uses - Mold cleaning, release and
protectant products
Presents an unreasonable risk of injury to
health (workers).
Does not present an unreasonable risk of injury
to health (occupational non-users).
Does not present unreasonable risk to the
environment (aquatic organisms).
Consumer Use - Cleaning and furniture care products -
Cleaners and degreasers (other)
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Consumer Use - Cleaning and furniture care products - Dry
cleaning solvent
Presents an unreasonable risk of injury to
health (consumers).
Does not present an unreasonable risk of injury
to health (bystanders).
Consumer Use - Cleaning and furniture care products -
Automotive care products (Brake cleaner)
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Consumer Use - Cleaning and furniture care products -
Automotive care products (Parts cleaner)
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Consumer Use - Cleaning and furniture care products -
Aerosol cleaner (Vandalism Mark & Stain Remover, Mold
Cleaner, Weld Splatter Protectant)
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Consumer Use - Cleaning and furniture care products -
Non-aerosol cleaner (e.g., marble and stone polish)
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Consumer Use - Lubricants and greases - Lubricants and
greases (Cutting Fluid)
Presents an unreasonable risk of injury to
health (consumers and bystanders).
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Condition of Use
Unreasonable Risk Determination
Consumer Use - Lubricants and greases - Lubricants and
greases (Lubricants and Penetrating Oils)
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Consumer Use - Adhesives and sealant chemicals -
Adhesives for arts and crafts (includes industrial adhesive,
arts and crafts adhesive, gun ammunition sealant)
Presents an unreasonable risk of injury to
health (consumers).
Does not present an unreasonable risk of injury
to health (bystanders).
Consumer Use - Adhesives and sealant chemicals -
Adhesives for arts and crafts (Livestock Grooming
Adhesive)
Does not present an unreasonable risk of injury
to health (consumers and bystanders).
Consumer Use - Adhesives and sealant chemicals -
Adhesives for arts and crafts (Column Adhesive, Caulk and
Sealant)
Presents an unreasonable risk of injury to
health (consumers).
Does not present an unreasonable risk of injury
to health (bystanders).
Consumer Use - Paints and coatings - Solvent-based paints
and coatings (Outdoor water shield (liquid))
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Consumer Use - Paints and coatings - Solvent-based paints
and coatings (Coatings and primers (aerosol))
Does not present an unreasonable risk of injury
to health (consumers and bystanders).
Consumer Use - Paints and coatings - Solvent-based paints
and coatings (Rust Primer and Sealant (liquid))
Presents an unreasonable risk of injury to
health (consumers).
Does not present an unreasonable risk of injury
to health (bystanders).
Consumer Use - Paints and coatings - Solvent-based paints
and coatings (Metallic Overglaze)
Does not present an unreasonable risk of injury
to health (consumers and bystanders).
Consumer Use - Other Uses - Metal (e.g., stainless steel)
and stone polishes
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Consumer Use - Other Uses - Inks and ink removal
products; welding; mold cleaning, release and protectant
products
Presents an unreasonable risk of injury to
health (consumers and bystanders).
Disposal
Presents an unreasonable risk of injury to
health (workers).
Presents an unreasonable risk to the
environment (aquatic organisms).
Does not present an unreasonable risk of injury
to health (occupational non-users).
10376
10377
10378
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10379
10380
10381
10382
10383
10384
10385
10386
10387
10388
10389
10390
10391
10392
10393
10394
10395
10396
10397
10398
10399
10400
10401
10402
10403
10404
10405
10406
10407
10408
10409
10410
10411
10412
10413
10414
10415
10416
10417
10418
10419
10420
10421
10422
10423
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5.3 Detailed Risk Determinations by Condition of Use
5,3,1 Manufacture - Domestic manufacture
Section 6(b)(4)(A) unreasonable risk determination of domestic manufacture of PCE:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present an unreasonable risk of injury to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), the dermal chronic non-cancer risk
estimate (high-end) indicates risk even with assumed dermal protection (PF 20). Risk estimates for
ONUs for acute and chronic inhalation do not indicate risk at the central tendency. EPA did not
separately calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk estimate
since the data did not distinguish between worker and ONU inhalation exposure estimates. ONU
inhalation exposures are expected to be lower than inhalation exposures for workers directly handling
the chemical substance; however, the relative exposure of ONUs to workers in these cases cannot be
quantified. To account for this uncertainty, EPA considered the central tendency estimate when
determining ONU risk. EPA assessed inhalation exposures during manufacturing using monitoring data
submitted by the Halogenated Solvents Industry Alliance (HSIA).
While EPA identified environmental risk for this COU, given the uncertainties in the data, EPA does not
consider these risks unreasonable. Of the six facilities assessed as manufacturing PCE, there were two
facilities with releases indicating risk to aquatic organisms (RQ > 1 and 20 days or more of exceedance
for algae). RQ values ranged from 2.64 (100 days of exceedance, indirect discharge) to 13.2 (189 days
of exceedance, direct discharge). 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).
EPA estimated 80% removal of PCE from indirect discharging facilities and 0% removal for direct
releases to surface water. Exceedances occurred using direct and indirect release scenarios but were
highest for direct release scenarios. Four of the six facilities assessed as manufacturing PCE did not have
NPDES permits. EPA identified risk to algae from direct and indirect release of PCE to surface water
from two of the facilities without NPDES permits. Lack of a NPDES permit increases the uncertainty in
the surface water release estimate for a facility. Based on the surface water PCE concentration and COC
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10424
10425
10426
10427
10428
10429
10430
10431
10432
10433
10434
10435
10436
10437
10438
10439
10440
10441
10442
10443
10444
10445
10446
10447
10448
10449
10450
10451
10452
10453
10454
10455
10456
10457
10458
10459
10460
10461
10462
10463
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10465
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confidence levels, the overall confidence in the risk estimate to aquatic organisms from exposure to PCE
is medium.
Life Cycle Stage
Category
Subcategory
Manufacture
Domestic manufacture
Domestic manufacture
5.3.2 Manufacture - Import (includes repackaging and loading/unloading)
Section 6(b)(4)(A) unreasonable risk determination for manufacture - import of PCE (includes
repackaging and loading/unloading):
• Presents an unreasonable risk of injury to health (workers and occupational non-users
(ONUs)).
• Does not present an unreasonable risk of injury to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk estimate - ONUs:
• Neurotoxicity:
o Chronic inhalation MOE 52 (central tendency). (Table 4-8)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), the dermal chronic non-cancer risk
estimate (high-end) indicates risk even with assumed dermal protection (PF 20). Risk estimates for
ONUs for chronic inhalation exposures indicated non-cancer risk at the central tendency, while acute
inhalation exposures did not indicate risk. EPA did not separately calculate risk estimates for ONUs and
workers. There is uncertainty in the ONU risk estimate since the data did not distinguish between
worker and ONU inhalation exposure estimates. ONU inhalation exposures are expected to be lower
than inhalation exposures for workers directly handling the chemical substance; however, the relative
exposure of ONUs to workers in these cases cannot be quantified. To account for this uncertainty, EPA
considered the central tendency estimate when determining ONU risk.
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10467
10468
10469
10470
10471
10472
10473
10474
10475
10476
10477
10478
10479
10480
10481
10482
10483
10484
10485
10486
10487
10488
10489
10490
10491
10492
10493
10494
10495
10496
10497
10498
10499
10500
10501
10502
10503
10504
10505
10506
10507
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While EPA identified environmental risks for this COU, given the uncertainties in the data, EPA does
not consider these risks unreasonable. Of the four facilities assessed as importing or repackaging PCE, a
single facility had releases indicating risk to aquatic organisms (RQ > 1 and 20 days or more of
exceedance for algae). RQ values were 20.62 (230 days of exceedance, indirect release) and 256.8 (20
days of exceedance, indirect release). 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). EPA estimated 80% removal of PCE from indirect discharging facilities and 0% removal for
direct releases to surface water. The exceedance occurred for indirect release. An exceedance from
indirect release indicates that risk can exist even with waste water treatment if the rate of PCE release to
surface water is high. One of the facilities assessed as manufacturing PCE did not have NPDES permits.
EPA only identified risk to algae from the one facility lacking a NPDES permit. Lack of a NPDES
permit increases the uncertainty in the surface water release estimate for a facility. Based on the surface
water PCE concentration and COC confidence levels, the overall confidence in the risk estimate to
aquatic organisms from exposure to PCE is medium.
Life Cycle Stage
Category
Subcategory
Manufacture
Import
Import
5.3.3 Processing - Processing as a reactant/intermediate in industrial gas manufacturing;
intermediate in basic organic chemical manufacturing; intermediate in petroleum
refineries; residual or byproduct reused as a reactant
Section 6(b)(4)(A) unreasonable risk determination for processing of PCE as a reactant/intermediate in
industrial gas manufacturing; intermediate in basic organic chemical manufacturing; intermediate in
petroleum refineries; and as a residual or byproduct and reused as a reactant:
• Presents an unreasonable risk of injury to health (workers).
• Presents an unreasonable risk to the environment (aquatic organisms).
• Does not present an unreasonable risk of injury to health (occupational non-users).
Unreasonable risk driver - workers and aquatic organisms:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
• Growth effects to aquatic invertebrates from chronic exposure.
• Algae mortality from exposure.
Driver benchmarks - workers and aquatic organisms:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
• Growth effects: Chronic (aquatic invertebrates) RQ > 1.
• Mortality: Algae RQ > 1.
Risk estimate - workers:
• Neurotoxicity:
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10510
10511
10512
10513
10514
10515
10516
10517
10518
10519
10520
10521
10522
10523
10524
10525
10526
10527
10528
10529
10530
10531
10532
10533
10534
10535
10536
10537
10538
10539
10540
10541
10542
10543
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10547
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o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk estimate for facilities with exceedances - aquatic organisms: (Table 4-110)
• Growth effects to aquatic invertebrates from chronic exposure:
o RQ =1.0 (chronic, aquatic invertebrates, 20 days of exceedance, direct release),
o RQ = 2.0 (chronic, aquatic invertebrates, 20 days of exceedance, direct release).
• Algae mortality from exposure: (some facilities had exceedances for multiple scenarios)
o RQ =1.7 (algae, 350 days of exceedance, direct release),
o RQ = 25 (algae, 20 days of exceedance, direct release),
o RQ =1.1 (algae, 29 days of exceedance, direct release),
o RQ = 2.2 (algae, 350 days of exceedance, direct release),
o RQ = 37 (algae, 20 days of exceedance, direct release),
o RQ = 3.5 (algae, 193 days of exceedance, direct release),
o RQ = 61 (algae, 20 days of exceedance, direct release),
o RQ = 3.6 (algae, 350 days of exceedance, direct release),
o RQ = 71 (algae, 20 days of exceedance, direct release),
o RQ =1.4 (algae, 67 days of exceedance, direct release).
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), the dermal chronic non-cancer risk
estimate (high-end) indicates risk even with assumed dermal protection (PF 20). Risk estimates for
ONUs for acute and chronic inhalation exposures do not indicate risk at the central tendency. EPA did
not separately calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk
estimate since the data did not distinguish between worker and ONU inhalation exposure estimates.
ONU inhalation exposures are expected to be lower than inhalation exposures for workers directly
handling the chemical substance; however, the relative exposure of ONUs to workers in these cases
cannot be quantified. To account for this uncertainty, EPA considered the central tendency estimate
when determining ONU risk. Exposure is assessed using PCE personal breathing zone monitoring data
collected at facilities manufacturing PCE as a surrogate for facilities processing PCE as reactant. The
data were determined to have a "high" confidence rating through EPA's systematic review process.
Although these data are not directly applicable to processing of PCE as a reactant, EPA expects a high
degree of overlap of worker tasks at both manufacturing sites and sites processing PCE as a reactant.
EPA assessed PCE as a reactant where it was produced as a byproduct from manufacture of 1,2-
dichloroethane (CASRN 107-06-2) and reused as a reactant.
Environmental releases for this condition of use indicate chronic risk to aquatic organisms and risk to
algae. Of the 18 facilities processing PCE as a reactant, six facilities had releases indicating risk to
aquatic organisms (RQs > 1 and 20 days or more of exceedance for aquatic organisms) with the highest
RQ being 71 (algae, 20 days of exceedance, direct release). For the six facilities indicating risk, EPA
identified risk to algae from all six facilities and chronic risk to aquatic organisms from two facilities.
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). EPA estimated 80% removal of
PCE from indirect discharging facilities and 0% removal for direct releases to surface water. All
exceedances occurred using the direct release to surface water scenario. All of the facilities assessed as
processing PCE as a reactant had NPDES permits. Based on the surface water PCE concentration and
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COC confidence levels, the overall confidence in the risk estimate to aquatic organisms from exposure
to PCE is medium.
l.il'e Cycle Stage
Category
Sii heal egory
Processing
Processing as a reactant or
intermediate
• Intermediate in industrial gas
manufacturing
• Intermediate in basic organic
chemical manufacturing
• Intermediate in petroleum refineries
• Residual or byproduct as a reactant
5.3.4 Processing - Incorporation into formulation, mixture or reaction product -
Cleaning and degreasing products
Section 6(b)(4)(A) unreasonable risk determination for processing PCE for incorporation into a
formulation, mixture, or reaction product - cleaning and degreasing products:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 1.3 (central tendency). (Table 4-13) (dry cleaning solvent)
o Chronic inhalation MOEs 60 (central tendency). (Table 4-14) (dry cleaning solvent)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), the dermal chronic non-cancer risk
estimate (high-end) indicates risk even with assumed dermal protection (PF 20). Risk estimates for
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10599
10600
10601
10602
10603
10604
10605
10606
10607
10608
10609
10610
10611
10612
10613
10614
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ONUs for acute and chronic inhalation exposures (central tendency) indicate risk. Two exposure
scenarios, degreasing solvent and dry cleaning solvent, apply to this condition of use. EPA made its
draft determination based on the dry cleaning solvent scenario, which was more representative of the
condition of use. EPA did not separately calculate risk estimates for ONUs and workers. There is
uncertainty in the ONU risk estimate since the data did not distinguish between worker and ONU
inhalation exposure estimates. ONU inhalation exposures are expected to be lower than inhalation
exposures for workers directly handling the chemical substance; however, the relative exposure of
ONUs to workers in these cases cannot be quantified. To account for this uncertainty, EPA considered
the central tendency estimate when determining ONU risk.
While EPA identified environmental risks for this COU, given the uncertainties in the data, EPA does
not consider these risks unreasonable. Of the four facilities assessed as using PCE for incorporation into
formulations, a single facility had releases indicating RQs > 1 for acute, chronic, and algae risks. RQ
values for algae were 96.84 (299 days of exceedance, indirect release) and 1,453.06 (20 days of
exceedance, indirect release). RQ values for chronic effects to aquatic organisms were 2.71 (127 days of
exceedance, indirect release) and 40.69 (20 days of exceedance, indirect release). The RQ value for the
acute effect to aquatic organisms was 1.52 (acute, aquatic invertebrates, 20 days of exceedance, direct
release). 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). EPA estimated 80%
removal of PCE from indirect discharging facilities and 0% removal for direct releases to surface water.
The exceedance occurred for indirect release. The facility indicating risk had the highest surface water
concentrations for all indirect releases evaluated (both maximum days of release and 20 days of release
scenarios). The annual release at this facility was the highest of all active releasers, and generally was an
order of magnitude higher than all other releases. The facility showing risk has a NPDES permit.
l.il'e Cycle Stage
Category
Sii heal egorv
Processing
Incorporated into
formulation, mixture or
reaction product
Cleaning and degreasing products
5,3.5 Processing - Incorporation into formulation, mixture or reaction product
Adhesive and sealant products
Section 6(b)(4)(A) unreasonable risk determination for processing PCE for incorporation into a
formulation, mixture, or reaction product - adhesive and sealant products:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
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10632
10633
10634
10635
10636
10637
10638
10639
10640
10641
10642
10643
10644
10645
10646
10647
10648
10649
10650
10651
10652
10653
10654
10655
10656
10657
10658
10659
10660
10661
10662
10663
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• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), the dermal chronic non-cancer risk
estimate (high-end) indicates risk even with assumed dermal protection (PF 20). Risk estimates for
ONUs for acute and chronic inhalation exposures do not indicate risk at the central tendency. EPA did
not separately calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk
estimate since the data did not distinguish between worker and ONU inhalation exposure estimates.
ONU inhalation exposures are expected to be lower than inhalation exposures for workers directly
handling the chemical substance; however, the relative exposure of ONUs to workers in these cases
cannot be quantified. To account for this uncertainty, EPA considered the central tendency estimate
when determining ONU risk.
While EPA identified environmental risks for this COU, given the uncertainties in the data, EPA does
not consider these risks unreasonable. Of the four facilities assessed as using PCE for incorporation into
formulations, a single facility had releases indicating RQs > 1 for acute, chronic, and algae risks. RQ
values for algae were 96.84 (299 days of exceedance, indirect release) and 1,453.06 (20 days of
exceedance, indirect release). RQ values for chronic effects to aquatic organisms were 2.71 (127 days of
exceedance, indirect release) and 40.69 (20 days of exceedance, indirect release). The RQ value for the
acute effect to aquatic organisms was 1.52 (acute, aquatic invertebrates, 20 days of exceedance, direct
release). 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). EPA estimated 80%
removal of PCE from indirect discharging facilities and 0% removal for direct releases to surface water.
The exceedance occurred for indirect release. The facility indicating risk had the highest surface water
concentrations for all indirect releases evaluated (both maximum days of release and 20 days of release
scenarios). The annual release at this facility was the highest of all active releasers, and generally was an
order of magnitude higher than all other releases. The facility showing risk has a NPDES permit.
l.il'e Cycle Stage
Category
Sii heal egory
Processing
Incorporated into
formulation, mixture or
reaction product
Adhesive and sealant products
5,3,6 Processing - Incorporation into formulation, mixture or reaction product - Paint
and coating products
Section 6(b)(4)(A) unreasonable risk determination for processing PCE for incorporation into a
formulation, mixture, or reaction product - adhesive and sealant products:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
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10677
10678
10679
10680
10681
10682
10683
10684
10685
10686
10687
10688
10689
10690
10691
10692
10693
10694
10695
10696
10697
10698
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10700
10701
10702
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• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), the dermal chronic non-cancer risk
estimate (high-end) indicates risk even with assumed dermal protection (PF 20). Risk estimates for
ONUs for acute and chronic inhalation exposures do not indicate risk at the central tendency. EPA did
not separately calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk
estimate since the data did not distinguish between worker and ONU inhalation exposure estimates.
ONU inhalation exposures are expected to be lower than inhalation exposures for workers directly
handling the chemical substance; however, the relative exposure of ONUs to workers in these cases
cannot be quantified. To account for this uncertainty, EPA considered the central tendency estimate
when determining ONU risk.
While EPA identified environmental risks for this COU, given the uncertainties in the data, EPA does
not consider these risks unreasonable. Of the four facilities assessed as using PCE for incorporation into
formulations, a single facility had releases indicating RQs > 1 for acute, chronic, and algae risks. RQ
values for algae were 96.84 (299 days of exceedance, indirect release) and 1,453.06 (20 days of
exceedance, indirect release). RQ values for chronic effects to aquatic organisms were 2.71 (127 days of
exceedance, indirect release) and 40.69 (20 days of exceedance, indirect release). The RQ value for the
acute effect to aquatic organisms was 1.52 (acute, aquatic invertebrates, 20 days of exceedance, direct
release). 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). EPA estimated 80%
removal of PCE from indirect discharging facilities and 0% removal for direct releases to surface water.
The exceedance occurred for indirect release. The facility indicating risk had the highest surface water
concentrations for all indirect releases evaluated (both maximum days of release and 20 days of release
scenarios). The annual release at this facility was the highest of all active releasers, and generally was an
order of magnitude higher than all other releases. The facility showing risk has a NPDES permit.
Life ( vole
(si logon
Siihcsilc«orv
Processing
Incorporated into
formulation, mixture or
reaction product
Paint and coating products
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10723
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10726
10727
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10729
10730
10731
10732
10733
10734
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10737
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10741
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5.3,7 Processing - Incorporation into formulation, mixture or reaction product - Other
chemical products and preparations
Section 6(b)(4)(A) unreasonable risk determination for processing PCE for incorporation into a
formulation, mixture, or reaction product - other chemical products and preparations:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic inhalation and dermal exposures.
• Cancer resulting from chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic inhalation MOEs 69 and 43 (central tendency and high-end) with PPE (respirator
APF 25). (Table 4-14) (aerosol packing)
o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 0.6 (central tendency). (Table 4-13) (aerosol packing)
o Chronic inhalation MOEs 2.7 (central tendency). (Table 4-14) (aerosol packing)
• Cancer (liver tumors):
o Inhalation: 1.5E-03 (central tendency) without PPE. (Table 4-15) (aerosol packing)
Risk Considerations: For workers, all pathways of occupational exposure for this condition of use
indicate risk, even with assumed respiratory protection (APF 25) and dermal protection (PF 20). Risk
estimates for ONUs for acute, chronic, and cancer inhalation exposures (central tendency) indicate risk.
EPA made its determination based on the aerosol packing scenario, which used personal breathing zone
monitoring data. While aerosol packing may not be representative of other formulation, EPA has a high
level of confidence in the assessed exposures based on the strength of the monitoring data. EPA did not
separately calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk estimate
since the data did not distinguish between worker and ONU inhalation exposure estimates. ONU
inhalation exposures are expected to be lower than inhalation exposures for workers directly handling
the chemical substance; however, the relative exposure of ONUs to workers in these cases cannot be
quantified. To account for this uncertainty, EPA considered the central tendency estimate when
determining ONU risk.
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10772
10773
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10776
10777
10778
10779
10780
10781
10782
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
While EPA identified environmental risks for this COU, given the uncertainties in the data, EPA does
not consider these risks unreasonable. Of the four facilities assessed as using PCE for incorporation into
formulations, a single facility had releases indicating RQs > 1 for acute, chronic, and algae risks. RQ
values for algae were 96.84 (299 days of exceedance, indirect release) and 1,453.06 (20 days of
exceedance, indirect release). RQ values for chronic effects to aquatic organisms were 2.71 (127 days of
exceedance, indirect release) and 40.69 (20 days of exceedance, indirect release). The RQ value for the
acute effect to aquatic organisms was 1.52 (acute, aquatic invertebrates, 20 days of exceedance, direct
release). 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). EPA estimated 80%
removal of PCE from indirect discharging facilities and 0% removal for direct releases to surface water.
The exceedance occurred for indirect release. The facility indicating risk had the highest surface water
concentrations for all indirect releases evaluated (both maximum days of release and 20 days of release
scenarios). The annual release at this facility was the highest of all active releasers, and generally was an
order of magnitude higher than all other releases. The facility showing risk has a NPDES permit.
l.il'e Cycle Stage
Category
S ii heat ego ry
Processing
Incorporated into
formulation, mixture or
reaction product
Other chemical products and
preparations
5,3.8 Processing - Repackaging - Solvents (for cleaning or degreasing); intermediate
Section 6(b)(4)(A) unreasonable risk determination for processing PCE by repackaging - solvent for
cleaning or degreasing; intermediate:
• Presents an unreasonable risk of injury to health (workers and occupational non-users
(ONUs)).
• Does not present an unreasonable risk of injury to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
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10801
10802
10803
10804
10805
10806
10807
10808
10809
10810
10811
10812
10813
10814
10815
10816
10817
10818
10819
10820
10821
10822
10823
10824
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10826
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o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk estimate - ONUs:
• Neurotoxicity:
o Chronic inhalation MOE 52 (central tendency). (Table 4-8)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), the dermal chronic non-cancer risk
estimate (high-end) indicates risk even with assumed dermal protection (PF 20). Risk estimates for
ONUs for chronic inhalation exposures indicated non-cancer risk at the central tendency, while acute
inhalation exposures did not indicate risk. EPA did not separately calculate risk estimates for ONUs and
workers. There is uncertainty in the ONU risk estimate since the data did not distinguish between
worker and ONU inhalation exposure estimates. ONU inhalation exposures are expected to be lower
than inhalation exposures for workers directly handling the chemical substance; however, the relative
exposure of ONUs to workers in these cases cannot be quantified. To account for this uncertainty, EPA
considered the central tendency estimate when determining ONU risk.
While EPA identified environmental risks for this COU, given the uncertainties in the data, EPA does
not consider these risks unreasonable. Of the four facilities assessed as importing or repackaging PCE, a
single facility had releases indicating risk to aquatic organisms (RQ > 1 and 20 days or more of
exceedance for algae). RQ values were 20.62 (230 days of exceedance, indirect release) and 256.8 (20
days of exceedance, indirect release). 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). EPA estimated 80% removal of PCE from indirect discharging facilities and 0% removal for
direct releases to surface water. The exceedance occurred for indirect release. An exceedance from
indirect release indicates that risk can exist even with waste water treatment if the rate of PCE release to
surface water is high. One of the facilities assessed as manufacturing PCE did not have NPDES permits.
EPA only identified risk to algae from the one facility lacking a NPDES permit. Lack of a NPDES
permit increases the uncertainty in the surface water release estimate for a facility. Based on the surface
water PCE concentration and COC confidence levels, the overall confidence in the risk estimate to
aquatic organisms from exposure to PCE is medium.
Life Cvcle Stage
Category
Subcategory
Processing
Repackaging
• Solvent for cleaning or degreasing
• Intermediate
5,3.9 Processing - Recycling
Section 6(b)(4)(A) unreasonable risk determination for processing PCE by recycling:
• Presents an unreasonable risk of injury to health (workers).
• Presents an unreasonable risk to the environment (aquatic organisms).
• Does not present an unreasonable risk of injury to health (occupational non-users).
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10843
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10846
10847
10848
10849
10850
10851
10852
10853
10854
10855
10856
10857
10858
10859
10860
10861
10862
10863
10864
10865
10866
10867
10868
10869
10870
10871
10872
10873
10874
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Unreasonable risk driver - workers and aquatic organisms:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
• Growth effects to aquatic invertebrates from chronic exposure.
• Algae mortality from exposure.
Driver benchmarks - workers and aquatic organisms:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
• Mortality: Algae RQ > 1.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
Risk estimate for facilities with exceedances - aquatic organisms: (Table 4-110)
• Algae mortality from exposure: (some facilities had exceedances for multiple scenarios)
o RQ = 6.4 (algae, 172 days of exceedance, indirect release).
o RQ = 80 (algae, 20 days of exceedance, indirect release),
o RQ = 25 (algae, 235 days of exceedance, indirect release),
o RQ = 311 (algae, 20 days of exceedance, indirect release),
o RQ = 2.2 (algae, 90 days of exceedance, indirect release).
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), the dermal chronic non-cancer risk
estimate (high-end) indicates risk even with assumed dermal protection (PF 20). Risk estimates for
ONUs for acute and chronic inhalation exposures do not indicate risk at the central tendency. EPA did
not separately calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk
estimate since the data did not distinguish between worker and ONU inhalation exposure estimates.
ONU inhalation exposures are expected to be lower than inhalation exposures for workers directly
handling the chemical substance; however, the relative exposure of ONUs to workers in these cases
cannot be quantified. To account for this uncertainty, EPA considered the central tendency estimate
when determining ONU risk.
Environmental releases for this condition of use indicate chronic risk to aquatic organisms and risk to
algae. Of the 13 facilities assessed for the waste handling, disposal, treatment, and recycling of PCE,
three facilities had releases indicating risk to aquatic organisms (RQs > 1 and 20 days of exceedance for
algae). RQ values ranged from 2.2 (90 days of exceedance, indirect discharge) to 311 (20 days of
exceedance, indirect discharge). 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).
EPA estimated 80% removal of PCE from indirect discharging facilities and 0% removal for direct
releases to surface water. Exceedances occurred using indirect release scenarios. An exceedance from
indirect release indicates that risk can exist even with waste water treatment if the rate of PCE release to
surface water is high. Four of the 13 facilities assessed for the waste handling, disposal, treatment, and
recycling of PCE did not have NPDES permits. EPA identified risk to algae from indirect release of
PCE to surface water from one of the facilities without a NPDES permit. Lack of a NPDES permit
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10890
10891
10892
10893
10894
10895
10896
10897
10898
10899
10900
10901
10902
10903
10904
10905
10906
10907
10908
10909
10910
10911
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increases the uncertainty in the surface water release estimate for a facility. Based on the surface water
PCE concentration and COC confidence levels, the overall confidence in the risk estimate to aquatic
organisms from exposure to PCE is medium.
Life Cycle Stage
Category
Subcategory
Processing
Recycling
Recycling
5.3,10 Distribution in Commerce
Section 6(b)(4)(A) unreasonable risk determination of distribution of PCE in commerce:
1 Does not present an unreasonable risk of injury to health (workers and occupational non-users).
2 Does not present unreasonable risk to the environment (aquatic organisms).
Risk Considerations: A quantitative evaluation of the distribution of PCE was not included in the risk
evaluation because exposures and releases from distribution were considered within each condition of
use.
l.il'e Cycle Stage
Category
Subcategory
Distribution in commerce
Distribution
Distribution
5.3.11 Industrial Use - Solvents (for cleaning or degreasing) - Batch vapor degreaser
(open-top)
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a solvent (for cleaning
or decreasing) - batch vapor degreaser (open-top):
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and chronic dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
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10937
10938
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10941
10942
10943
10944
10945
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10947
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10951
10952
10953
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• Neurotoxicity:
o Acute inhalation MOEs 60 and 3.9 (central tendency and high-end) with PPE (respirator
APF 25). (Table 4-16)
o Chronic inhalation MOEs 271 and 18 (central tendency and high-end) with PPE
(respirator APF 25). (Table 4-17)
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-72)
• Cancer (liver tumors):
o Inhalation: 1.5E-05 and 3.0E-04 (central tendency and high-end) with PPE (respirator
APF 25). (Table 4-18)
o Dermal: 6.4E-05 and 2.5E-04 (central tendency and high-end) with PPE (gloves PF =
10). (
o Table 4-73)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 8.2 and 1.0 (central tendency and high-end). (Table 4-16)
o Chronic inhalation MOEs 38 and 4.4 (central tendency and high-end). (Table 4-17)
• Cancer (liver tumors):
o Inhalation: 1.1E-04 and 1.2E-03 (central tendency and high-end). (Table 4-18)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of PPE. For workers, non-cancer and cancer risk estimates for
inhalation and dermal exposures indicate risks even with assumed respiratory protection (APF 25) and
dermal protection (PF 10). EPA separately calculated risk estimates for ONUs and workers based on
monitoring data. Risk estimates for ONUs for acute (high-end), chronic (high-end and central tendency),
and cancer (high-end) inhalation exposures indicate risk. EPA defined ONU as an employee who does
not regularly handle PCE or operate the degreaser but performs work in the area around the degreaser.
Samples from employees determined not to be operating the degreasing equipment were designated as
ONU samples. EPA identified inhalation exposure monitoring data from NIOSH investigations at five
sites using PCE as a degreasing solvent in OTVDs. Due to the large variety in shop types that may use
PCE as a vapor degreasing solvent, there is some uncertainty in how representative these data are of a
"typical" shop.
While EPA identified environmental risk for this COU, given the uncertainties in the data, EPA does not
consider these risks unreasonable. Of the 17 facilities assessed for this COU, two facilities had releases
indicating risk to risk to aquatic organisms (RQs > 1 and 20 days or more of exceedance for algae). RQ
values ranged from 2.3 (20 days of exceedance, direct discharge) to 55.5 (20 days of exceedance, direct
discharge). 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). EPA estimated 80%
removal of PCE from indirect discharging facilities and 0% removal for direct releases to surface water.
The exceedance occurred for direct release. All of the facilities assessed as using PCE in open top vapor
degreasing had NPDES permits. Based on the surface water PCE concentration and COC confidence
levels, the overall confidence in the risk estimate to aquatic organisms from exposure to PCE is medium.
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l.il'e Cycle Stage
Category
Sii heal egorv
Industrial use
Solvents (for cleaning or
degreasing)
Batch vapor degreaser (e.g., open-top.
closed-loop)
5.3.12 Industrial Use - Solvents (for cleaning or degreasing) - Batch vapor degreaser
(closed-loop)
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a solvent (for cleaning
or decreasing) - batch vapor degreaser (closed-loop):
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-72)
• Cancer (liver tumors):
o Dermal: 6.4E-05 and 2.5E-04 (central tendency and high-end) with PPE (gloves PF =
10). (
o Table 4-73)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risks even with assumed
dermal protection (PF 10). EPA separately calculated risk estimates for ONUs and workers based on
monitoring data. Risk estimates for ONUs for acute and chronic inhalation exposures do not indicate
risk at the central tendency or high-end. Worker samples were determined to be any sample taken on a
person while performing the degreasing tasks. ONUs samples were determined to be any sample taken
on a person in the same location as the degreaser but not performing the degreasing themselves. EPA
identified inhalation exposure monitoring data from NIOSH investigations at two sites using PCE as a
degreasing solvent in batch closed-loop vapor degreasers. Due to the large variety in shop types that
may use PCE as a vapor degreasing solvent, there is some uncertainty in how representative these data
are of a "typical" shop. No environmental risks were identified for this COU.
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11023
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Life Cycle Singe
("si lego in-
S ii heal ego rv
Industrial use
solvents (for cleaning or
degreasing)
Batch vapor degreaser (e.g., open-top.
closed-loop)
5.3.13 Industrial Use - Solvents (for cleaning or degreasing) - In-line vapor degreaser
(conveyorized)
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a solvent (for cleaning
or degreasing) - in-line vapor degreaser (conveyorized):
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and chronic dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 1.6 and 0.7 (central tendency and high-end) with PPE (respirator
APF 25). (Table 4-22)
o Chronic inhalation MOEs 7.3 and 3.1 (central tendency and high-end) with PPE
(respirator APF 25). (Table 4-23)
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-72)
• Cancer (liver tumors):
o Inhalation: 5.4E-04 and 1.4E-03 (central tendency and high-end) with PPE (respirator
APF 25). (Table 4-24)
Dermal: 6.4E-05 and 2.5E-04 (central tendency and high-end) with PPE (gloves PF = 10). (
o Table 4-73)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 0.1 and 4.0E-02 (central tendency and high-end). (Table 4-22)
o Chronic inhalation MOEs 0.6 and 0.2 (central tendency and high-end). (Table 4-23)
• Cancer (liver tumors):
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11061
11062
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11064
11065
11066
11067
11068
11069
11070
11071
11072
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11074
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o Inhalation: 7.0E-03 and 2.3E-02 (central tendency and high-end). (Table 4-24)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of PPE. For workers, non-cancer and cancer risk estimates for
inhalation and dermal exposures indicate risks even with assumed respiratory protection (APF 25) and
dermal protection (PF 10). EPA separately calculated risk estimates for ONUs and workers. Risks for
ONUs for acute, chronic, and cancer inhalation exposures are indicated at the high-end and central
tendency estimates. EPA assessed inhalation exposures during conveyorized degreasing using the
Conveyorized Degreasing Near-Field/Far-Field Inhalation Exposure Model. Workers' risk estimates are
based on concentrations in the near-field where the conveyorized degreasing work occurs, and ONU
exposures are based on concentrations in the far-field, away from the conveyorized degreaser. No
environmental risks were identified for this COU.
l.il'e Cycle Stage
Category
Subcategory
Industrial use
Solvents (for cleaning or
degreasing)
In-line vapor degreaser (e.g.,
conveyorized, web cleaner)
5,3.14 Industrial Use - Solvents (for cleaning or degreasing) - In-line vapor degreaser (web
degreaser)
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a solvent (for cleaning
or decreasing) - in-line vapor degreaser (web degreaser):
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-72)
• Cancer (liver tumors):
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1103
1104
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1106
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1111
1112
1113
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o Dermal: 6.4E-05 and 2.5E-04 (central tendency and high-end) with PPE (gloves PF =
10). (
o Table 4-73)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 16 and 4.3 (central tendency and high-end). (Table 4-25)
o Chronic inhalation MOEs 71 and 19 (central tendency and high-end). (Table 4-26)
• Cancer (liver tumors):
o Inhalation: 5.5E-05 and 2.1E-04 (central tendency and high-end). (Table 4-27)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risk even with assumed
dermal protection (PF 10). EPA separately calculated risk estimates for ONUs and workers. Risk
estimates for ONUs for acute (high-end), chronic (high-end and central tendency), and cancer (high-end)
inhalation exposures indicate risk. EPA assessed inhalation exposures during web degreasing using the
Web Degreasing Near-Field/Far-Field Inhalation Exposure Model. Workers' estimates are based on
concentrations in the near-field where the web degreasing work occurs, and ONU exposures are based
on concentrations in the far-field, away from the web degreaser. No environmental risks were identified
for this COU.
l.il'e Cycle Stage
Category
Sii heal egory
Industrial use
Solvents (for cleaning or
degreasing)
In-line vapor degreaser (e.g.,
conveyorized, web cleaner)
5.3.15 Industrial Use - Solvents (for cleaning or degreasing) - Cold cleaner
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a solvent (for cleaning
or degreasing) - cold cleaner:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
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• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-72)
• Cancer (liver tumors):
o Dermal: 6.4E-05 and 2.5E-04 (central tendency and high-end) with PPE (gloves PF =
10). (
o Table 4-73)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 3.6 (central tendency). (Table 4-28) (monitoring)
o Chronic inhalation MOEs 16 (central tendency). (Table 4-29) (monitoring)
• Cancer (liver tumors):
o Inhalation: 2.5E-04 (central tendency). (Table 4-30) (monitoring)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risk even with assumed
dermal protection (PF 10). Risks for ONUs for acute, chronic, and cancer inhalation exposures are
indicated at the central tendency. For workers and ONUs, EPA used monitoring data to make the risk
determination on the use of PCE in cold cleaners. While EPA modeled the use of PCE in cold cleaning,
the model showed large variation in modeled results as a result of the large variation in unit emissions
reported in NEI. There is uncertainty in the ONU risk estimate since the monitoring data did not
distinguish between worker and ONU inhalation exposure estimates. ONU inhalation exposures are
expected to be lower than inhalation exposures for workers directly handling the chemical substance;
however, the relative exposure of ONUs to workers in these cases cannot be quantified. To account for
this uncertainty, EPA considered the central tendency estimate when determining ONU risk from the
monitoring data. No environmental risks were identified for this COU.
Life Cycle Singe
("si lego in-
S ii heal ego rv
Industrial use
solvents (for cleaning or
degreasing)
Cold cleaner
5.3,16 Industrial Use - Solvents (for cleaning or degreasing) - Aerosol spray
degreaser/cleaner
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a solvent (for cleaning
or degreasing) - aerosol spray degreaser/cleaner:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
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11192
11193
11194
11195
11196
11197
11198
11199
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11201
11202
11203
11204
11205
11206
11207
11208
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Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 3.5 and 0.6 (central tendency and high-end) without PPE. (Table
4-31) (monitoring)
o Chronic inhalation MOEs 16 and 2.9 (central tendency and high-end) without PPE.
(Table 4-32) (monitoring)
o Acute dermal MOEs 24 and 8.0 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-74)
o Chronic dermal MOEs 51 and 17 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-75)
• Cancer (liver tumors):
o Inhalation: 2.6E-04 and 1.8E-03 (central tendency and high-end) without PPE. (Table
4-33) (monitoring)
o Dermal: 9.6E-04 and 3.7E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-76)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 50 and 6.8 (central tendency and high-end). (Table 4-31)
(modeling)
o Chronic inhalation MOEs 260 and 31 (central tendency and high-end). (Table 4-32)
(modeling)
• Cancer (liver tumors):
o Inhalation: 2.0E-05 and 1.4E-04 (central tendency and high-end). (Table 4-33)
(modeling)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of PPE. While EPA does not assume routine use of PPE with this
exposure scenario, risk was still present to workers with APF 50 for acute and chronic inhalation. The
estimates based on monitoring data only include values for workers as monitoring data for ONUs were
not identified. To account for lack of monitoring data for ONUs, EPA considered risk estimates from
exposure modeling when determining ONU risk. The near-field/far-field exposure modeling
incorporates variability in the model input parameters and distinguishes between workers and ONUs.
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Model results are generally higher than monitoring data; however, the monitoring data includes data
from three sources that had concentrations of PCE in the aerosol formulation below the median value
predicted by the model. EPA has a high level of confidence in the assessed exposure for this condition
of use. EPA separately evaluated risks to consumers from dry cleaned articles as part of the COU,
Consumer Use - Cleaning and furniture care products - Dry cleaning solvent, in Section 5.3.52. No
environmental risks were identified for this COU.
l.il'e Cycle Stage
Category
Sii heal egorv
Industrial use
Solvents (for cleaning or
degreasing)
Aerosol spray degreaser/cleaner
5.3.17 Industrial Use - Solvents (for cleaning or degreasing) - Dry Cleaning and Spot
Cleaning Post-2006 Dry Cleaning
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a solvent (for cleaning
or degreasing) - dry cleaning and spot cleaning post-2006 dry cleaning:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 1.4 and 0.3 (central tendency and high-end) without PPE. (Table
4-34) (monitoring)
o Chronic inhalation MOEs 6.1 and 1.0 (central tendency and high-end) without PPE.
(Table 4-35) (monitoring)
o Acute dermal MOEs 24 and 7.9 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-77)
o Chronic dermal MOEs 50 and 17 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-78)
• Cancer (liver tumors):
o Inhalation: 6.8E-04 and 5.4E-03 (central tendency and high-end) without PPE. (Table
4-36) (monitoring)
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11277
11278
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11280
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11282
11283
11284
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o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-79)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 30 and 2.1 (central tendency and high-end). (Table 4-34)
(modeling)
o Chronic inhalation MOEs 136 and 9.5 (central tendency and high-end). (Table 4-35)
(modeling)
• Cancer (liver tumors):
o Inhalation: 2.9E-05 and 4.3E-04 (central tendency and high-end). (Table 4-36)
(modeling)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of respiratory PPE. While EPA does not assume routine use of
respiratory PPE with this exposure scenario, risk was still present to workers with APF 50 for chronic
inhalation at the high-end, for monitoring and modeled data. Because the monitoring data only contained
one data point representing an ONU for this scenario, EPA made its determination on ONUs using
modeled data. Modeled ONU exposures are based on concentrations in the far-field which corresponds
to any area outside the near-field zones. Risk estimates for ONUs for acute (high-end), chronic (high-
end and central tendency), and cancer (high-end) inhalation exposures indicate risk. EPA separately
evaluated risks to consumers from dry cleaned articles as part of the COU, Consumer Use - Cleaning
and furniture care products - Dry cleaning solvent, in Section 5.3.52. No environmental risks were
identified for this COU.
Life Cycle Stage
Category
Subcategory
Industrial use
Solvents (for cleaning or
degreasing)
• Dry cleaning solvent
• Spot cleaner
5.3.18 Industrial Use - Solvents (for cleaning or degreasing) - Dry Cleaning and Spot
Cleaning 4th/5th Gen Only Dry Cleaning
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a solvent (for cleaning
or degreasing) - dry cleaning and spot cleaning 4th/5th Gen only dry cleaning:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Driver benchmarks - workers:
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11313
11314
11315
11316
11317
11318
11319
11320
11321
11322
11323
11324
11325
11326
11327
11328
11329
11330
11331
11332
11333
11334
11335
11336
11337
11338
11339
11340
11341
11342
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• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 5.1 and 0.9 (central tendency and high-end) without PPE. (Table
4-34) (monitoring)
o Chronic inhalation MOEs 23 and 3.5 (central tendency and high-end) without PPE.
(Table 4-35) (monitoring)
o Acute dermal MOEs 24 and 7.9 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-77)
o Chronic dermal MOEs 50 and 17 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-78)
• Cancer (liver tumors):
o Inhalation: 1.8E-04 and 1.5E-03 (central tendency and high-end) without PPE. (Table
4-36) (monitoring)
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-79)
Risk Considerations: For workers, all pathways of occupational exposure for this condition of use
indicate risk in the absence of respiratory PPE. Risk estimates for ONUs for acute and chronic inhalation
exposures do not indicate risk at the central tendency and high-end. EPA based its risk determination on
monitoring data. EPA does not assume routine use of respiratory PPE with this exposure scenario. When
comparing the model results to the fourth/fifth generation monitoring data results for workers, the model
high-end and central tendency are both an order of magnitude greater than the monitoring data. This is
expected as the model captures exposures from facilities with third and fourth/fifth generation machines.
No environmental risks were identified for this COU.
Life Cycle Stage
Category
Subcategory
Industrial use
Solvents (for cleaning or
degreasing)
• Dry cleaning solvent
• Spot cleaner
5.3,19 Industrial Use - Lubricants and greases - Lubricants and greases (aerosol
lubricants)
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE in lubricants and greases -
lubricants and greases (aerosol lubricants):
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
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Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 3.5 and 0.6 (central tendency and high-end) without PPE. (Table
4-31) (monitoring)
o Chronic inhalation MOEs 16 and 2.9 (central tendency and high-end) without PPE.
(Table 4-32) (monitoring)
o Acute dermal MOEs 24 and 8.0 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-74)
o Chronic dermal MOEs 51 and 17 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-75)
• Cancer (liver tumors):
o Inhalation: 2.6E-04 and 1.8E-03 (central tendency and high-end) without PPE. (Table
4-33) (monitoring)
o Dermal: 9.6E-04 and 3.7E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-76)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 50 and 6.8 (central tendency and high-end). (Table 4-31)
(modeling)
o Chronic inhalation MOEs 260 and 31 (central tendency and high-end). (Table 4-32)
(modeling)
• Cancer (liver tumors):
o Inhalation: 2.0E-05 and 1.4E-04 (central tendency and high-end). (Table 4-33)
(modeling)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of respiratory PPE. While EPA does not assume routine use of PPE
with this exposure scenario, risk was still present to workers with APF 50 for acute and chronic
inhalation. The estimates based on monitoring data only include values for workers as monitoring data
for ONUs were not identified. To account for lack of monitoring data for ONUs, EPA considered risk
estimates from exposure modeling when determining ONU risk. The near-field/far-field exposure
modeling incorporates variability in the model input parameters and distinguishes between workers and
ONUs. Model results are generally higher than monitoring data; however, the monitoring data includes
data from three sources that had concentrations of PCE in the aerosol formulation below the median
value predicted by the model. EPA has a high level of confidence in the assessed exposure for this
condition of use. No environmental risks were identified for this COU.
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l.il'e Cycle Stage
Category
Subcategory
Industrial use
Solvents (for cleaning or
degreasing)
Lubricants and greases (e.g.,
penetrating lubricants, cutting tool
coolants, aerosol lubricants)
5.3.20 Industrial Use - Lubricants and greases - Lubricants and greases (e.g., penetrating
lubricants, cutting tool coolants)
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE in lubricants and greases -
lubricants and greases (e.g.. penetrating lubricants, cutting tool coolants):
• Does not present an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 869 and 239 (central tendency and high-end) without PPE.
(Table 4-46)
o Chronic inhalation MOEs 3,960 and 1,087 (central tendency and high-end) without PPE.
(Table 4-47)
o Acute dermal MOEs 361 and 120 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-80)
o Chronic dermal MOEs 769 and 256 (central tendency and high-end) with PPE (gloves PF
= 10). (Table 4-81)
• Cancer (liver tumors):
o Inhalation: 1.0E-06 and 4.9E-06 (central tendency and high-end) without PPE. (Table
4-48)
o Dermal: 6.4E-05 and 2.5E-04 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-82)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 869 and 239 (central tendency and high-end). (Table 4-46)
o Chronic inhalation MOEs 3,960 and 1,087 (central tendency and high-end). (Table 4-47)
• Cancer (liver tumors):
o Inhalation: 1.0E-06 and 4.9E-06 (central tendency and high-end). (Table 4-48)
Risk Considerations: Risk estimates for workers and ONUs for acute and chronic exposures do not
indicate acute or chronic risks from any route of exposure, including cancer risks, in the absence of
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respiratory PPE and with assumed dermal protection (PF 10) for workers. EPA did not separately
calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk estimate since the
data did not distinguish between worker and ONU inhalation exposure estimates. ONU inhalation
exposures are expected to be lower than inhalation exposures for workers directly handling the chemical
substance; however, the relative exposure of ONUs to workers in these cases cannot be quantified. To
account for this uncertainty, EPA considered the central tendency estimate when determining ONU risk.
No environmental risks were identified for this COU.
Life ('vole S(a«e
C'silogorv
Subcategory
Industrial use
Lubricants and greases
Lubricants and greases (e.g.,
penetrating lubricants, cutting tool
coolants, aerosol lubricants)
5.3.21 Industrial Use - Adhesives and sealants - Solvent-based adhesives and sealants
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE in adhesives and sealants -
solvent-based 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).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 96 and 32 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-84)
• Cancer (liver tumors):
o Dermal: 5.1E-05 and 2.0E-04 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-85)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risk even with assumed
dermal protection (PF 10). Risk estimates for ONUs for acute and chronic inhalation exposures do not
indicate risk at the central tendency or high-end. EPA identified inhalation exposure monitoring data
related to the use of PCE-based adhesives, sealants, paints, and coatings. The results in the monitoring
data only include values for workers as monitoring data for ONUs were not identified. To account for
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this uncertainty when using monitoring data, EPA considered the central tendency estimate when
determining ONU risk. Due to the large variety in shop types that may use PCE-based adhesives and
coatings, it is unclear how representative these data are of a "typical" site using these products. No
environmental risks were identified for this COU.
Life Cycle Singe
Cnlcgorv
Subcategory
Industrial use
Adhesives and sealant
chemicals
Solvent-based adhesives and sealants
5.3.22 Industrial Use - Paints and coatings - Solvent-based paints and coatings
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE in paints and coatings -
solvent-based paints and coatings:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 96 and 32 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-84)
• Cancer (liver tumors):
o Dermal: 5.1E-05 and 2.0E-04 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-85)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end and central tendency) indicate risk
even with assumed dermal protection (PF 10). Risk estimates for ONUs for acute and chronic inhalation
exposures do not indicate risk at the central tendency. EPA identified inhalation exposure monitoring
data related to the use of PCE-based adhesives, sealants, paints, and coatings. The results in the
monitoring data only include values for workers as monitoring data for ONUs were not identified. ONU
inhalation exposures are expected to be lower than inhalation exposures for workers directly handling
the chemical substance but the relative exposure of ONUs to workers in these cases were not
quantifiable. To account for this uncertainty when using monitoring data, EPA considered the central
tendency estimate when determining ONU risk. Due to the large variety in shop types that may use
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PCE-based adhesives and coatings, it is unclear how representative these data are of a "typical" site
using these products. No environmental risks were identified for this COU.
Life Cycle Singe
(nlegorv
Subcategory
Industrial use
Paints and coatings
including paint and coating
removers
Solvent-based paints and coatings,
including for chemical milling
5.3.23 Industrial Use - Paints and coatings - Maskant for Chemical Milling
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE in paints and coatings -
maskant for chemical milling:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-72)
• Cancer (liver tumors):
o Dermal: 6.4E-04 and 2.5E-03 (central tendency and high-end) with PPE (gloves PF =
10). (
o
o Table 4-73)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 4.1 (central tendency). (Table 4-40)
o Chronic inhalation MOEs 19 (central tendency). (Table 4-41)
• Cancer (liver tumors):
Inhalation: 2.2E-04 (central tendency). (
o Table 4-42)
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Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risk even with assumed
dermal protection (PF 10). Risks for ONUs for acute, chronic, and cancer inhalation exposures are
indicated at the central tendency. EPA identified inhalation exposure monitoring data from a single
NIOSH investigation and samples collected by the DoD. EPA did not separately calculate risk estimates
for ONUs and workers. ONU inhalation exposures are expected to be lower than inhalation exposures
for workers directly handling the chemical substance; however, the relative exposure of ONUs to
workers in these cases cannot be quantified. To account for this uncertainty, EPA considered the central
tendency estimate when determining ONU risk. Due to the variety in industry types and typical per site
maskant use rates and the uncertainty of the PCE concentration in the maskant, it is unclear if these data
are representative of a "typical" site. No environmental risks were identified for this COU.
Life Cycle Stage
Category
Subcategory
Industrial use
Paints and coatings
including paint and coating
removers
Solvent-based paints and coatings,
including for chemical milling
5.3.24 Industrial Use - Processing aids, not otherwise listed - Pesticide, fertilizer and other
agricultural chemical manufacturing
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE in processing aids, not
otherwise listed - pesticide, fertilizer and other agricultural chemical manufacturing:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-69)
• Cancer (liver tumors):
o Dermal: 6.4E-04 and 2.5E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-70)
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Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic cancer and non-
cancer risk estimates (high-end and central tendency) indicate risk even with assumed dermal protection
(PF 10). Risk estimates for ONUs for acute and chronic inhalation exposures do not indicate risk at the
central tendency. EPA identified inhalation exposure monitoring data from four studies submitted to
EPA. EPA did not separately calculate risk estimates for ONUs and workers. There is uncertainty in the
ONU risk estimate since the data did not distinguish between worker and ONU inhalation exposure
estimates. ONU inhalation exposures are expected to be lower than inhalation exposures for workers
directly handling the chemical substance; however, the relative exposure of ONUs to workers in these
cases cannot be quantified. To account for this uncertainty, EPA considered the central tendency
estimate when determining ONU risk. No environmental risks were identified for this COU.
Life Cycle Singe
Category
Subcategory
Industrial use
Processing aids, not
otherwise listed
Pesticide, fertilizer, and other
agricultural chemical manufacturing
5.3.25 Industrial Use - Processing aids, specific to petroleum production - Catalyst
regeneration in petrochemical manufacturing
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE as a processing aids,
specific to petroleum production - catalyst regeneration in petrochemical manufacturing processing aid:
• Presents an unreasonable risk of injury to health (workers).
• Presents an unreasonable risk to the environment (aquatic organisms).
• Does not present an unreasonable risk of injury to health (occupational non-users).
Unreasonable risk driver - workers and aquatic organisms:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
• Algae mortality from exposure.
Driver benchmarks - workers and aquatic organisms:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
• Mortality: Algae RQ > 1.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-69)
• Cancer (liver tumors):
o Dermal: 6.4E-04 and 2.5E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-70)
Risk estimate for facilities with exceedances - aquatic organisms: (Table 4-110)
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11655
11656
11657
11658
11659
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11661
11662
11663
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• Algae mortality from exposure: (some facilities had exceedances for multiple scenarios)
o RQ =1.9 (algae, 20 days of exceedance, direct release),
o RQ = 4 (algae, 55 days of exceedance, direct release),
o RQ = 69 (algae, 20 days of exceedance, direct release),
o RQ = 4.7 (algae, 20 days of exceedance, direct release),
o RQ = 4.5 (algae, 92 days of exceedance, indirect release),
o RQ = 14 (algae, 20 days of exceedance, direct release),
o RQ = 8.5 (algae, 169 days of exceedance, direct release),
o RQ =1.3 (algae, 42 days of exceedance, direct release).
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic cancer and non-
cancer risk estimates (high-end and central tendency) indicate risk even with assumed dermal protection
(PF 10). Risk estimates for ONUs for acute and chronic inhalation exposures do not indicate risk at the
central tendency. EPA identified inhalation exposure monitoring data from four studies submitted to
EPA. EPA did not separately calculate risk estimates for ONUs and workers. There is uncertainty in the
ONU risk estimate since the data did not distinguish between worker and ONU inhalation exposure
estimates. ONU inhalation exposures are expected to be lower than inhalation exposures for workers
directly handling the chemical substance; however, the relative exposure of ONUs to workers in these
cases cannot be quantified. To account for this uncertainty, EPA considered the central tendency
estimate when determining ONU risk. No environmental risks were identified for this COU.
Environmental releases for this condition of use indicate chronic risk to aquatic organisms and risk to
algae. Of the 12 facilities assessed as using PCE as an industrial processing aid, six facilities had
releases indicating risk to aquatic organisms (RQs > 1 and 20 days or more of exceedance for algae). RQ
values ranged from 1.3 (42 days of exceedance, direct discharge) to 69 (20 days of exceedance, direct
discharge). 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). EPA estimated 80%
removal of PCE from indirect discharging facilities and 0% removal for direct releases to surface water.
Exceedances occurred using direct and indirect release scenarios but were highest for direct release
scenarios. All of the facilities assessed as processing PCE as a reactant had NPDES permits. Based on
the surface water PCE concentration and COC confidence levels, the overall confidence in the risk
estimate to aquatic organisms from exposure to PCE is medium.
Life Cvcle Stage
Category
S ii heat ego rv
Industrial use
Processing aids, specific to
petroleum production
Catalyst regeneration in petrochemical
manufacturing
5.3,26 Industrial Use - Other uses - Textile processing (spot cleaning)
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE for other uses - textile
processing (spot cleaning):
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
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11696
11697
11698
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11701
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11703
11704
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Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute dermal MOEs 24 and 7.9 (central tendency and high-end) with PPE (gloves PF =
10) (Table 4-77)
o Chronic dermal MOEs 50 and 17 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-78)
• Cancer (liver tumors):
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-79)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks, dermal acute non-cancer (high-end), dermal chronic non-cancer (high-end and
central tendency), and dermal cancer risk estimates (high-end) indicate risk even with assumed dermal
protection (PF 10). EPA does not assume routine use of respiratory PPE with this exposure scenario.
EPA separately calculated risk estimates for ONUs and workers based on monitoring data. Risk
estimates for ONUs for acute and chronic inhalation exposures do not indicate risk. EPA identified
inhalation exposure monitoring data from a single NIOSH investigation at a garment manufacturer.
Worker samples were determined to be any sample taken on a person while directly handling PCE.
ONUs samples were determined to be any sample taken on a person in the same location as the PCE use
but not handling PCE. ONU exposure data did not distinguish central tendency and high-end. There is
some uncertainty in how representative this data are of exposure at other facilities performing carpet
cleaning or spot remover tasks. No environmental risks were identified for this COU.
l.ile ('vole Stage
Category
S ii heat ego rv
Industrial use
Other uses
Textile processing
5.3.27 Industrial Use - Other uses - Textile processing (other)
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE for other uses - textile
processing (other):
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
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Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-69)
• Cancer (liver tumors):
o Dermal: 6.4E-04 and 2.5E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-70)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risk even with assumed
dermal protection (PF 10). Risk estimates for ONUs for acute and chronic inhalation exposures do not
indicate risk at the central tendency. EPA did not identify any inhalation exposure monitoring data for
other industrial uses, and therefore assessed inhalation exposures for workers and ONUs using the Tank
Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model. Due to other
potential sources of exposure at industrial facilities, there are some model uncertainties that could result
in an underestimate of worker exposure. EPA did not separately calculate risk estimates for ONUs and
workers. There is uncertainty in the ONU risk estimate since the data did not distinguish between
worker and ONU inhalation exposure estimates. ONU inhalation exposures are expected to be lower
than inhalation exposures for workers directly handling the chemical substance; however, the relative
exposure of ONUs to workers in these cases cannot be quantified. To account for this uncertainty, EPA
considered the central tendency estimate when determining ONU risk. No environmental risks were
identified for this COU.
Life ('vole S(a«e
C'silogorv
Subcategory
Industrial use
Other uses
Textile processing
5.3.28 Industrial Use - Other uses - Wood furniture manufacturing
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE for other uses - wood
furniture manufacturing:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
Page 501 of 636
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11771
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11773
11774
11775
11776
11777
11778
11779
11780
11781
11782
11783
11784
11785
11786
11787
11788
11789
11790
11791
11792
11793
11794
11795
11796
11797
11798
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11801
11802
11803
11804
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-69)
• Cancer (liver tumors):
o Dermal: 6.4E-04 and 2.5E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-70)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risk even with assumed
dermal protection (PF 10). Risk estimates for ONUs for acute and chronic inhalation exposures do not
indicate risk at the central tendency. EPA did not identify any inhalation exposure monitoring data for
other industrial uses, and therefore assessed inhalation exposures for workers and ONUs using the Tank
Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model. Due to other
potential sources of exposure at industrial facilities, there are some model uncertainties that could result
in an underestimate of worker exposure. EPA did not separately calculate risk estimates for ONUs and
workers. There is uncertainty in the ONU risk estimate since the data did not distinguish between
worker and ONU inhalation exposure estimates. ONU inhalation exposures are expected to be lower
than inhalation exposures for workers directly handling the chemical substance; however, the relative
exposure of ONUs to workers in these cases cannot be quantified. To account for this uncertainty, EPA
considered the central tendency estimate when determining ONU risk. No environmental risks were
identified for this COU.
Lile Cycle Stage
Category
Subcategory
Industrial use
Other uses
Wood furniture manufacturing
5.3.29 Industrial Use - Other uses - Laboratory chemicals
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE for other uses - laboratory
chemical:
• Does not present an unreasonable risk of injury to health (workers and ONUs).
• Does not present unreasonable risk to the environment (aquatic organisms).
Page 502 of 636
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11809
11810
11811
11812
11813
11814
11815
11816
11817
11818
11819
11820
11821
11822
11823
11824
11825
11826
11827
11828
11829
11830
11831
11832
11833
11834
11835
11836
11837
11838
11839
11840
11841
11842
11843
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk Considerations: As discussed in Section 2.4.1.25, EPA does not have data to assess worker
exposures to PCE during laboratory use. However, due to the expected safety practices when using
chemicals in a laboratory setting, PCE is expected to be applied in small amounts under a fume hood,
thus reducing the potential for inhalation exposures. No environmental risks were identified for this
cou.
Life ('vole Stage
Category
Subcategory
Industrial/commercial use
Other uses
Laboratory chemicals
5.3,30 Industrial Use - Other uses - Foundry applications
Section 6(b)(4)(A) unreasonable risk determination for industrial use of PCE for other uses - foundry
applications:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 77 and 26 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-69)
• Cancer (liver tumors):
o Dermal: 6.4E-04 and 2.5E-03 (central tendency and high-end) with PPE (gloves PF =
10). (Table 4-70)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risk even with assumed
dermal protection (PF 10). Risk estimates for ONUs for acute and chronic inhalation exposures do not
indicate risk at the central tendency. EPA did not identify any inhalation exposure monitoring data for
other industrial uses, and therefore assessed inhalation exposures for workers and ONUs using the Tank
Truck and Railcar Loading and Unloading Release and Inhalation Exposure Model. Due to other
potential sources of exposure at industrial facilities, there are some model uncertainties that could result
in an underestimate of worker exposure. EPA did not separately calculate risk estimates for ONUs and
workers. There is uncertainty in the ONU risk estimate since the data did not distinguish between
worker and ONU inhalation exposure estimates. ONU inhalation exposures are expected to be lower
Page 503 of 636
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11852
11853
11854
11855
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11857
11858
11859
11860
11861
11862
11863
11864
11865
11866
11867
11868
11869
11870
11871
11872
11873
11874
11875
11876
11877
11878
11879
11880
11881
11882
11883
11884
11885
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
than inhalation exposures for workers directly handling the chemical substance; however, the relative
exposure of ONUs to workers in these cases cannot be quantified. To account for this uncertainty, EPA
considered the central tendency estimate when determining ONU risk. No environmental risks were
identified for this COU.
l.il'e Cvcle Stage
Category
S ii heat ego rv
Industrial/commercial use
Other uses
Foundry applications
5,3,31 Commercial Use - Cleaning and furniture care products - Cleaners and degreasers
(other) (wipe cleaning)
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in cleaning and furniture
care products - cleaners and degreasers (other)(wipe cleaning):
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 3.8E-02 and 2.2E-02 (central tendency and high-end) without
PPE. (Table 4-49)
o Chronic inhalation MOEs 0.2 and 0.1 (central tendency and high-end) without PPE.
(Table 4-50)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Inhalation: 2.4E-02 and 5.3E-02 (central tendency and high-end) without PPE. (Table
4-51)
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Page 504 of 636
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11892
11893
11894
11895
11896
11897
11898
11899
11900
11901
11902
11903
11904
11905
11906
11907
11908
11909
11910
11911
11912
11913
11914
11915
11916
11917
11918
11919
11920
11921
11922
11923
11924
11925
11926
11927
11928
11929
11930
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 229 and 0.2 (central tendency and high-end). (Table 4-49)
o Chronic inhalation MOEs 1043 and 1.0 (central tendency and high-end). (Table 4-50)
• Cancer (liver tumors):
o Inhalation: 4.0E-06 and 5.4E-03 (central tendency and high-end). (Table 4-51)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of respiratory and dermal PPE. While EPA does not assume routine
use of PPE with this exposure scenario, risk was still present to workers with APF 50 for chronic
inhalation at the high-end. EPA identified inhalation exposure monitoring data from NIOSH
investigations at two sites using PCE for wipe cleaning. EPA separately calculated risk estimates for
ONUs and workers based on monitoring data. Due to the large variety in shop types that may use PCE
as a wipe cleaning solvent, it is unclear how representative these data are of a "typical" shop. EPA does
not have a model for estimating exposures from wipe cleaning; therefore, the assessment is based on the
identified monitoring data. No environmental risks were identified for this COU.
Life Cycle Singe
Category
S u heal ego ry
Commercial Use
Cleaning and furniture care
products
Cleaners and degreasers (other) (wipe
cleaning)
5.3.32 Commercial Use - Cleaning and furniture care products - Cleaners and degreasers
(other) (Other Spot Cleaning/Spot Removers (Including Carpet Cleaning))
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in cleaning and furniture
care products - cleaners and degreasers (other)(other spot cleaning/spot removers (including carpet
cleaning)):
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
Page 505 of 636
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11933
11934
11935
11936
11937
11938
11939
11940
11941
11942
11943
11944
11945
11946
11947
11948
11949
11950
11951
11952
11953
11954
11955
11956
11957
11958
11959
11960
11961
11962
11963
11964
11965
11966
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Dermal: 9.8E-04 and 3.8E-04 (central tendency and high-end) without PPE. (Table 4-79)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks, dermal acute non-cancer (high-end), dermal chronic non-cancer (high-end and
central tendency), and dermal cancer risk estimates (high-end) indicate risk. EPA does not assume
routine use of respiratory or dermal PPE with this exposure scenario. EPA separately calculated risk
estimates for ONUs and workers based on monitoring data. Risk estimates for ONUs for acute and
chronic inhalation exposures do not indicate risk. EPA identified inhalation exposure monitoring data
from a single NIOSH investigation at a garment manufacturer. Worker samples were determined to be
any sample taken on a person while directly handling PCE. ONUs samples were determined to be any
sample taken on a person in the same location as the PCE use but not handling PCE. ONU exposure data
did not distinguish central tendency and high-end. There is some uncertainty in how representative this
data are of exposure at other facilities performing carpet cleaning or spot remover tasks. No
environmental risks were identified for this COU.
Life Cycle Singe
Category
S u heal ego ry
Commercial Use
Cleaning and furniture care
products
Cleaners and degreasers (other) (other
spot cleaning/spot removers (including
carpet cleaning))
5.3.33 Commercial Use - Cleaning and furniture care products - Cleaners and degreasers
(other) (Mold Release)
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in cleaning and furniture
care products - cleaners and degreasers (other) (mold release):
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic dermal exposures
• Cancer resulting from chronic dermal exposures
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
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11979
11980
11981
11982
11983
11984
11985
11986
11987
11988
11989
11990
11991
11992
11993
11994
11995
11996
11997
11998
11999
12000
12001
12002
12003
12004
12005
12006
12007
12008
12009
12010
12011
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk estimate - workers:
• Neurotoxicity:
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Dermal: 9.8E-04 and 3.8E-04 (central tendency and high-end) without PPE. (Table 4-79)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks, dermal acute non-cancer (high-end), dermal chronic non-cancer (high-end and
central tendency), and dermal cancer risk estimates (high-end) indicate risk. EPA does not assume
routine use of respiratory or dermal PPE with this exposure scenario. Risk estimates for ONUs for acute
and chronic inhalation exposures do not indicate risk at the central tendency. Data for this condition of
use are area samples, not worker breathing zone samples. ONU inhalation exposures are expected to be
lower than inhalation exposures for workers directly handling the chemical substance; however, the
relative exposure of ONUs to workers in these cases cannot be quantified. To account for this
uncertainty, EPA considered the central tendency estimate when determining ONU risk. No
environmental risks were identified for this COU.
Life Cycle Singe
(nlegorv
Subcategory
Commercial Use
Cleaning and furniture care
products
Cleaners and degreasers (other) (mold
release)
5.3,34 Commercial Use - Cleaning and furniture care products - Dry Cleaning and Spot Cleaning
Post-2006 Dry Cleaning
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in cleaning and furniture
care products - dry cleaning and spot cleaning post-2006 dry cleaning:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
Page 507 of 636
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12013
12014
12015
12016
12017
12018
12019
12020
12021
12022
12023
12024
12025
12026
12027
12028
12029
12030
12031
12032
12033
12034
12035
12036
12037
12038
12039
12040
12041
12042
12043
12044
12045
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12047
12048
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 1.4 and 0.3 (central tendency and high-end) without PPE. (Table
4-34) (monitoring)
o Chronic inhalation MOEs 6.1 and 1.0 (central tendency and high-end) without PPE.
(Table 4-35) (monitoring)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Inhalation: 6.8E-04 and 5.4E-03 (central tendency and high-end) without PPE. (Table
4-36) (monitoring)
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 30 and 2.1 (central tendency and high-end). (Table 4-34)
(modeling)
o Chronic inhalation MOEs 136 and 9.5 (central tendency and high-end). (Table 4-35)
(modeling)
• Cancer (liver tumors):
o Inhalation: 2.9E-05 and 4.3E-04 (central tendency and high-end). (Table 4-36)
(modeling)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of respiratory and dermal PPE. While EPA does not assume routine
use of respiratory PPE with this exposure scenario, risk was still present to workers with APF 50 for
chronic inhalation at the high-end, for monitoring and modeled data. Because the monitoring data only
contained one data point representing an ONU for this scenario, EPA made its determination on ONUs
using modeled data. Modeled ONU exposures are based on concentrations in the far-field which
corresponds to any area outside the near-field zones. Risk estimates for ONUs for acute (high-end),
chronic (high-end and central tendency), and cancer (high-end) inhalation exposures indicate risk. EPA
separately evaluated risks to consumers from dry cleaned articles as part of the COU, Consumer Use -
Cleaning and furniture care products - Dry cleaning solvent, in Section 5.3.52. No environmental risks
were identified for this COU.
Life ( vole
(si logon
Siihcsilc«orv
Commercial Use
Cleaning and furniture care
products
Dry cleaning and spot cleaning post-
2006 dry cleaning
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12066
12067
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12071
12072
12073
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
5.3.35 Commercial Use - Cleaning and furniture care products - Dry Cleaning and Spot Cleaning
4th/5th Gen Only Dry Cleaning
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in cleaning and furniture
care products - dry cleaning and spot cleaning 4th/5th Gen only dry cleaning:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and chronic dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 5.1 and 0.9 (central tendency and high-end) without PPE. (Table
4-34) (monitoring)
o Chronic inhalation MOEs 23 and 3.5 (central tendency and high-end) without PPE.
(Table 4-35) (monitoring)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Inhalation: 1.8E-04 and 1.5E-03 (central tendency and high-end) without PPE. (Table
4-36) (monitoring)
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Risk Considerations: For workers, all pathways of occupational exposure for this condition of use
indicate risk in the absence of respiratory and dermal PPE. Risk estimates for ONUs for acute and
chronic inhalation exposures do not indicate risk at the central tendency and high-end. EPA based its
risk determination on monitoring data. When comparing the model results to the fourth/fifth generation
monitoring data results for workers, the model high-end and central tendency are both an order of
magnitude greater than the monitoring data. This is expected as the model captures exposures from
facilities with third and fourth/fifth generation machines. EPA separately evaluated risks to consumers
from dry cleaned articles as part of the COU, Consumer Use - Cleaning and furniture care products -
Dry cleaning solvent, in Section 5.3.52. No environmental risks were identified for this COU.
Page 509 of 636
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12100
12101
12102
12103
12104
12105
12106
12107
12108
12109
12110
12111
12112
12113
12114
12115
12116
12117
12118
12119
12120
12121
12122
12123
12124
12125
12126
12127
12128
12129
12130
12131
12132
12133
12134
12135
12136
12137
12138
12139
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle Singe
Category
S u heal ego ry
Commercial Use
Cleaning and furniture care
products
Dry cleaning and spot cleaning 4th/5th
Gen only dry cleaning
5.3,36 Commercial Use - Cleaning and furniture care products - Automotive care products (e.g.,
engine degreaser and brake cleaner)
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in cleaning and furniture
care products - automotive care products (e.g.. engine degreaser and brake cleaner):
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 3.5 and 0.6 (central tendency and high-end) without PPE. (Table
4-31) (monitoring)
o Chronic inhalation MOEs 16 and 2.9 (central tendency and high-end) without PPE.
(Table 4-32) (monitoring)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE (Table
4-74)
o Chronic dermal MOEs 5.1 and 1.7 (central tendency and high-end) without PPE. (Table
4-75)
• Cancer (liver tumors):
o Inhalation: 2.6E-04 and 1.8E-03 (central tendency and high-end) without PPE. (Table
4-33) (monitoring)
o Dermal: 9.6E-04 and 3.7E-03 (central tendency and high-end) without PPE. (Table 4-76)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 50 and 6.8 (central tendency and high-end). (Table 4-31)
(modeling)
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12146
12147
12148
12149
12150
12151
12152
12153
12154
12155
12156
12157
12158
12159
12160
12161
12162
12163
12164
12165
12166
12167
12168
12169
12170
12171
12172
12173
12174
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
o Chronic inhalation MOEs 260 and 31 (central tendency and high-end). (Table 4-32)
(modeling)
• Cancer (liver tumors):
o Inhalation: 2.0E-05 and 1.4E-04 (central tendency and high-end). (Table 4-33)
(modeling)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of respiratory and dermal PPE. While EPA does not assume routine
use of PPE with this exposure scenario, risk was still present to workers with APF 50 for acute and
chronic inhalation. The estimates based on monitoring data only include values for workers as
monitoring data for ONUs were not identified. To account for lack of monitoring data for ONUs, EPA
considered risk estimates from exposure modeling when determining ONU risk. The near-field/far-field
exposure modeling incorporates variability in the model input parameters and distinguishes between
workers and ONUs. Model results are generally higher than monitoring data; however, the monitoring
data includes data from three sources that had concentrations of PCE in the aerosol formulation below
the median value predicted by the model. EPA has a high level of confidence in the assessed exposure
for this condition of use. No environmental risks were identified for this COU.
l.il'e Cvcle Stage
Category
S ii heat ego rv
Commercial Use
Cleaning and furniture care
products
Automotive care products (e.g. engine
degreaser and brake cleaner)
5,3,37 Commercial Use - Cleaning and furniture care products - Aerosol cleaner
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in cleaning and furniture
care products - aerosol cleaner:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
Page 511 of 636
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12187
12188
12189
12190
12191
12192
12193
12194
12195
12196
12197
12198
12199
12200
12201
12202
12203
12204
12205
12206
12207
12208
12209
12210
12211
12212
12213
12214
12215
12216
12217
12218
12219
12220
12221
12222
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
o Acute inhalation MOEs 3.5 and 0.6 (central tendency and high-end) without PPE. (Table
4-31) (monitoring)
o Chronic inhalation MOEs 16 and 2.9 (central tendency and high-end) without PPE.
(Table 4-32) (monitoring)
o Acute dermal 2.4 and 0.8 (central tendency and high-end) without PPE. (Table 4-74)
o Chronic dermal MOEs 5.1 and 1.7 (central tendency and high-end) without PPE. (Table
4-75)
• Cancer (liver tumors):
o Inhalation: 2.6E-04 and 1.8E-03 (central tendency and high-end) without PPE. (Table
4-33) (monitoring)
o Dermal: 9.6E-04 and 3.7E-04 (central tendency and high-end) without PPE. (Table 4-76)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 50 and 6.8 (central tendency and high-end). (Table 4-31)
(modeling)
o Chronic inhalation MOEs 260 and 31 (central tendency and high-end). (Table 4-32)
(modeling)
• Cancer (liver tumors):
o Inhalation: 2.0E-05 and 1.4E-04 (central tendency and high-end). (Table 4-33)
(modeling)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of respiratory and dermal PPE. While EPA does not assume routine
use of PPE with this exposure scenario, risk was still present to workers with APF 50 for acute and
chronic inhalation. The estimates based on monitoring data only include values for workers as
monitoring data for ONUs were not identified. To account for lack of monitoring data for ONUs, EPA
considered risk estimates from exposure modeling when determining ONU risk. The near-field/far-field
exposure modeling incorporates variability in the model input parameters and distinguishes between
workers and ONUs. Model results are generally higher than monitoring data; however, the monitoring
data includes data from three sources that had concentrations of PCE in the aerosol formulation below
the median value predicted by the model. EPA has a high level of confidence in the assessed exposure
for this condition of use. No environmental risks were identified for this COU.
Life Cycle S(a«e
C'silogorv
Subcategory
Commercial Use
Cleaning and furniture care
products
Aerosol cleaner
5.3.38 Commercial Use - Cleaning and furniture care products - Non-aerosol cleaner
Section 6(b)(4)(A) unreasonable risk determination of PCE for commercial use - cleaning and furniture
care products - non-aerosol cleaner:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Page 512 of 636
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12228
12229
12230
12231
12232
12233
12234
12235
12236
12237
12238
12239
12240
12241
12242
12243
12244
12245
12246
12247
12248
12249
12250
12251
12252
12253
12254
12255
12256
12257
12258
12259
12260
12261
12262
12263
12264
12265
12266
12267
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 3.8E-02 and 2.2E-02 (central tendency and high-end) without
PPE. (Table 4-49)
o Chronic inhalation MOEs 0.2 and 0.1 (central tendency and high-end) without PPE.
(Table 4-50)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Inhalation: 2.4E-02 and 5.3E-02 (central tendency and high-end) without PPE. (Table
4-51)
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 229 and 0.2 (central tendency and high-end). (Table 4-49)
o Chronic inhalation MOEs 1043 and 1.0 (central tendency and high-end). (Table 4-50)
• Cancer (liver tumors):
o Inhalation: 4.0E-06 and 5.4E-03 (central tendency and high-end). (Table 4-51)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of PPE. While EPA does not assume routine use of PPE with this
exposure scenario, risk was still present to workers with APF 50 for chronic inhalation at the high-end.
EPA identified inhalation exposure monitoring data from NIOSH investigations at two sites using PCE
for wipe cleaning. EPA separately calculated risk estimates for ONUs and workers based on monitoring
data. Due to the large variety in shop types that may use PCE as a wipe cleaning solvent, it is unclear
how representative these data are of a "typical" shop. EPA does not have a model for estimating
exposures from wipe cleaning; therefore, the assessment is based on the identified monitoring data. No
environmental risks were identified for this COU.
Page 513 of 636
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12270
12271
12272
12273
12274
12275
12276
12277
12278
12279
12280
12281
12282
12283
12284
12285
12286
12287
12288
12289
12290
12291
12292
12293
12294
12295
12296
12297
12298
12299
12300
12301
12302
12303
12304
12305
12306
12307
12308
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
I.ill' Cvcli' Singe
(si logon
Subcategory
Commercial Use
Cleaning and furniture care Non-aerosol cleaner
products
5.3,39 Commercial Use - Lubricants and greases - Lubricants and greases (aerosol lubricants)
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in lubricants and greases
- lubricants and greases (aerosol lubricants):
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 3.5 and 0.6 (central tendency and high-end) without PPE. (Table
4-31) (monitoring)
o Chronic inhalation MOEs 16 and 2.9 (central tendency and high-end) without PPE.
(Table 4-32) (monitoring)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-74)
o Chronic dermal MOEs 5.1 and 1.7 (central tendency and high-end) without PPE. (Table
4-75)
• Cancer (liver tumors):
o Inhalation: 2.6E-04 and 1.8E-03 (central tendency and high-end) without PPE. (Table
4-33) (monitoring)
o Dermal: 9.6E-04 and 3.7E-03 (central tendency and high-end) without PPE. (Table 4-76)
Risk estimate - ONUs:
• Neurotoxicity:
-------
12309
12310
12311
12312
12313
12314
12315
12316
12317
12318
12319
12320
12321
12322
12323
12324
12325
12326
12327
12328
12329
12330
12331
12332
12333
12334
12335
12336
12337
12338
12339
12340
12341
12342
12343
12344
12345
12346
12347
12348
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
o Chronic inhalation MOEs 260 and 31 (central tendency and high-end). (Table 4-32)
(modeling)
• Cancer (liver tumors):
o Inhalation: 2.0E-05 and 1.4E-04 (central tendency and high-end). (Table 4-33)
(modeling)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of PPE. While EPA does not assume routine use of PPE with this
exposure scenario, risk was still present to workers with APF 50 for acute and chronic inhalation. The
estimates based on monitoring data only include values for workers as monitoring data for ONUs were
not identified. To account for lack of monitoring data for ONUs, EPA considered risk estimates from
exposure modeling when determining ONU risk. The near-field/far-field exposure modeling
incorporates variability in the model input parameters and distinguishes between workers and ONUs.
Model results are generally higher than monitoring data; however, the monitoring data includes data
from three sources that had concentrations of PCE in the aerosol formulation below the median value
predicted by the model. EPA has a high level of confidence in the assessed exposure for this condition
of use. No environmental risks were identified for this COU.
Life Cycle Singe
Category
Subcategory
Commercial Use
Lubricants and greases
Lubricants and greases (aerosol
lubricants)
5.3.40 Commercial Use - Lubricants and greases - Lubricants and greases (e.g., penetrating
lubricants, cutting tool coolants)
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in lubricants and greases
- lubricants and greases (e.g.. penetrating lubricants, cutting tool coolants):
• Does not present an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 869 and 239 (central tendency and high-end) without PPE.
(Table 4-46)
o Chronic inhalation MOEs 3,960 and 1,087 (central tendency and high-end) without PPE.
(Table 4-47)
o Acute dermal MOEs 181 and 60 (central tendency and high-end) with PPE (gloves PF =
5). (Table 4-80)
Page 515 of 636
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12352
12353
12354
12355
12356
12357
12358
12359
12360
12361
12362
12363
12364
12365
12366
12367
12368
12369
12370
12371
12372
12373
12374
12375
12376
12377
12378
12379
12380
12381
12382
12383
12384
12385
12386
12387
12388
12389
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
o Chronic dermal MOEs 384 and 128 (central tendency and high-end) with PPE (gloves PF
= 5). (Table 4-81)
• Cancer (liver tumors):
o Inhalation: 1.0E-06 and 4.9E-06 (central tendency and high-end) without PPE. (Table
4-48)
o Dermal: 1.3E-05 and 5.0E-05 (central tendency and high-end) with PPE (gloves PF = 5).
(Table 4-82)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 869 and 239 (central tendency and high-end). (Table 4-46)
o Chronic inhalation MOEs 3,960 and 1,087 (central tendency and high-end). (Table 4-47)
• Cancer (liver tumors):
o Inhalation: 1.0E-06 and 4.9E-06 (central tendency and high-end). (Table 4-48)
Risk Considerations: Risk estimates for workers and ONUs for acute and chronic exposures do not
indicate acute or chronic risks from any route of exposure, including cancer risks. EPA did not
separately calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk estimate
since the data did not distinguish between worker and ONU inhalation exposure estimates. ONU
inhalation exposures are expected to be lower than inhalation exposures for workers directly handling
the chemical substance; however, the relative exposure of ONUs to workers in these cases cannot be
quantified. To account for this uncertainty, EPA considered the central tendency estimate when
determining ONU risk. No environmental risks were identified for this COU.
Life Cycle Slage
Category
Subcategory
Commercial use
Lubricants and greases
Lubricants and greases (e.g.,
penetrating lubricants, cutting tool
coolants)
5.3.41 Commercial Use - Adhesives and sealant chemicals - Light repair adhesives
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in adhesives and sealant
chemicals - light repair adhesives:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
Page 516 of 636
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12393
12394
12395
12396
12397
12398
12399
12400
12401
12402
12403
12404
12405
12406
12407
12408
12409
12410
12411
12412
12413
12414
12415
12416
12417
12418
12419
12420
12421
12422
12423
12424
12425
12426
12427
12428
12429
12430
12431
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute dermal MOEs 15 and 4.9 (central tendency and high-end) with PPE (gloves PF =
5). (Table 4-83)
o Chronic dermal MOEs 31 and 10 (central tendency and high-end) with PPE (gloves PF =
5). (Table 4-84)
• Cancer (liver tumors):
o Dermal: 1.6E-04 and 6.1E-04 (central tendency and high-end) with PPE (gloves PF = 5).
(Table 4-85)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 10), dermal chronic non-cancer (high-
end and central tendency) and dermal cancer risk estimates (high-end) indicate risk even with assumed
dermal protection (PF 5). Risk estimates for ONUs for acute and chronic inhalation exposures do not
indicate risk at the central tendency or high-end. EPA identified inhalation exposure monitoring data
related to the use of PCE-based adhesives, sealants, paints, and coatings. The results in the monitoring
data only include values for workers as monitoring data for ONUs were not identified. To account for
this uncertainty when using monitoring data, EPA considered the central tendency estimate when
determining ONU risk. Due to the large variety in shop types that may use PCE-based adhesives and
coatings, it is unclear how representative these data are of a "typical" site using these products. No
environmental risks were identified for this COU.
Life Cycle Singe
(nlegorv
Subcategory
Commercial use
Adhesives and sealant
chemicals
Light repair adhesives
5,3.42 Commercial Use - Paints and coatings - Solvent-based paints and coatings
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in paints and coatings -
solvent-based paints and coatings:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from chronic inhalation and acute and chronic dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Page 517 of 636
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12432
12433
12434
12435
12436
12437
12438
12439
12440
12441
12442
12443
12444
12445
12446
12447
12448
12449
12450
12451
12452
12453
12454
12455
12456
12457
12458
12459
12460
12461
12462
12463
12464
12465
12466
12467
12468
12469
12470
12471
12472
12473
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk estimate - workers:
• Neurotoxicity:
o Chronic inhalation MOEs 976 and 50 (central tendency and high-end) with PPE
(respirator APF 10). (Table 4-38)
o Acute dermal MOEs 15 and 4.9 (central tendency and high-end) with PPE (gloves = 5).
(Table 4-83)
o Chronic dermal MOEs 31 and 10 (central tendency and high-end) with PPE (gloves PF =
5). (Table 4-84)
• Cancer (liver tumors):
o Dermal: 1.6E-04 and 6.1E-04 (central tendency and high-end) with PPE (gloves PF = 5).
(Table 4-85)
Risk Considerations: For workers, while acute non-cancer and cancer risk estimates for inhalation
exposures do not indicate risks with assumed respiratory protection (APF 10), chronic non-cancer (high-
end), dermal chronic non-cancer (high-end and central tendency) and dermal cancer risk estimates (high-
end and central tendency) indicate risk even with assumed dermal protection (PF 5). Risk estimates for
ONUs for acute and chronic inhalation exposures do not indicate risk at the central tendency. EPA
identified inhalation exposure monitoring data related to the use of PCE-based adhesives, sealants,
paints, and coatings. The results in the monitoring data only include values for workers as monitoring
data for ONUs were not identified. ONU inhalation exposures are expected to be lower than inhalation
exposures for workers directly handling the chemical substance but the relative exposure of ONUs to
workers in these cases were not quantifiable. To account for this uncertainty when using monitoring
data, EPA considered the central tendency estimate when determining ONU risk. Due to the large
variety in shop types that may use PCE-based adhesives and coatings, it is unclear how representative
these data are of a "typical" site using these products. No environmental risks were identified for this
cou.
Life Cycle Slage
Category
Subcategory
Commercial use
Paints and coatings
Solvent-based paints and coatings
5.3.43 Commercial Use - Other uses - Carpet cleaning
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE for other uses - carpet
cleaning:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Page 518 of 636
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12476
12477
12478
12479
12480
12481
12482
12483
12484
12485
12486
12487
12488
12489
12490
12491
12492
12493
12494
12495
12496
12497
12498
12499
12500
12501
12502
12503
12504
12505
12506
12507
12508
12509
12510
12511
12512
12513
12514
12515
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks, dermal acute non-cancer, dermal chronic non-cancer, and dermal cancer risk
estimates (high-end and central tendency) indicate risk. EPA does not assume routine use of respiratory
or dermal PPE with this exposure scenario. EPA separately calculated risk estimates for ONUs and
workers based on monitoring data. Risk estimates for ONUs for acute and chronic inhalation exposures
do not indicate risk. EPA identified inhalation exposure monitoring data from a single NIOSH
investigation at a garment manufacturer. Worker samples were determined to be any sample taken on a
person while directly handling PCE. ONUs samples were determined to be any sample taken on a
person in the same location as the PCE use but not handling PCE. ONU exposure data did not
distinguish central tendency and high-end. There is some uncertainty in how representative this data are
of exposure at other facilities performing carpet cleaning or spot remover tasks. No environmental risks
were identified for this COU.
Life Cycle S(a«e
C'silegorv
Subcategory
Commercial use
Other uses
Carpet cleaning
5,3.44 Commercial Use - Other uses - Laboratory chemicals
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE for other uses -
laboratory chemicals:
• Does not present an unreasonable risk of injury to health (workers and ONUs).
• Does not present unreasonable risk to the environment (aquatic organisms).
Risk Considerations: As discussed in Section 2.4.1.25, EPA does not have data to assess worker
exposures to PCE during laboratory use. However, due to the expected safety practices when using
chemicals in a laboratory setting, PCE is expected to be applied in small amounts under a fume hood,
Page 519 of 636
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12516
12517
12518
12519
12520
12521
12522
12523
12524
12525
12526
12527
12528
12529
12530
12531
12532
12533
12534
12535
12536
12537
12538
12539
12540
12541
12542
12543
12544
12545
12546
12547
12548
12549
12550
12551
12552
12553
12554
12555
12556
12557
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
thus reducing the potential for inhalation exposures. No environmental risks were identified for this
cou.
Life Cvcle Stage
Category
S ii heat ego rv
Commercial use
Other uses
Laboratory Chemicals
5,3,45 Commercial Use - Other uses - Metal (e.g., stainless steel) and stone polishes
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE for other uses - metal
(e.g.. stainless steel) and stone polishes:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and chronic dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 3.8E-02 and 2.2E-02 (central tendency and high-end) without
PPE. (Table 4-49)
o Chronic inhalation MOEs 0.2 and 0.1 (central tendency and high-end) without PPE.
(Table 4-50)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Inhalation: 2.4E-02 and 5.3E-02 (central tendency and high-end) without PPE. (Table
4-51)
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Risk estimate - ONUs:
• Neurotoxicity:
Page 520 of 636
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12558
12559
12560
12561
12562
12563
12564
12565
12566
12567
12568
12569
12570
12571
12572
12573
12574
12575
12576
12577
12578
12579
12580
12581
12582
12583
12584
12585
12586
12587
12588
12589
12590
12591
12592
12593
12594
12595
12596
12597
12598
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
o Acute inhalation MOEs 229 and 0.2 (central tendency and high-end). (Table 4-49)
o Chronic inhalation MOEs 1043 and 1.0 (central tendency and high-end). (Table 4-50)
• Cancer (liver tumors):
o Inhalation: 4.0E-06 and 5.4E-03 (central tendency and high-end). (Table 4-51)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of PPE. While EPA does not assume routine use of PPE with this
exposure scenario, risk was still present to workers with APF 50 for chronic inhalation at the high-end.
EPA identified inhalation exposure monitoring data from NIOSH investigations at two sites using PCE
for wipe cleaning. EPA separately calculated risk estimates for ONUs and workers based on monitoring
data. Due to the large variety in shop types that may use PCE as a wipe cleaning solvent, it is unclear
how representative these data are of a "typical" shop. EPA does not have a model for estimating
exposures from wipe cleaning; therefore, the assessment is based on the identified monitoring data. No
environmental risks were identified for this COU.
Life Cycle Stage
Category
Subcategory
Commercial Use
Other uses
Metal (e.g., stainless steel) and stone
polishes
5.3.46 Commercial Use - Other uses - Inks and ink removal products (based on printing)
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE in other uses - inks and
ink removal products (based on printing):
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 2.6 and 0.8 (central tendency and high-end) without PPE. (Table
4-58)
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12603
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12606
12607
12608
12609
12610
12611
12612
12613
12614
12615
12616
12617
12618
12619
12620
12621
12622
12623
12624
12625
12626
12627
12628
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
o Chronic inhalation MOEs 12 and 3.8 (central tendency and high-end) without PPE.
(Table 4-59)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Inhalation: 3.5E-04 and 1.4E-03 (central tendency and high-end) without PPE. (Table
4-60)
o Dermal: 9.8E-04 and 3.8E-04 (central tendency and high-end) without PPE. (Table 4-79)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 2.6 (central tendency). (Table 4-58)
o Chronic inhalation MOEs 12 (central tendency). (Table 4-59)
• Cancer (liver tumors):
o Inhalation: 3.5E-04 (central tendency). (Table 4-60)
Risk Considerations: For workers, all pathways of occupational exposure for this condition of use
indicate risk (central tendency and high-end) in the absence of respiratory and dermal PPE. Acute,
chronic, and cancer inhalation risk estimates for ONUs indicate risk at the central tendency. EPA does
not assume routine use of respiratory or dermal PPE with this exposure scenario. EPA did not separately
calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk estimate since the
data did not distinguish between worker and ONU inhalation exposure estimates. ONU inhalation
exposures are expected to be lower than inhalation exposures for workers directly handling the chemical
substance; however, the relative exposure of ONUs to workers in these cases cannot be quantified. To
account for this uncertainty, EPA considered the central tendency estimate when determining ONU risk.
No environmental risks were identified for this COU.
Life Cycle Slage
Category
Subcategory
Commercial Use
Other uses
Inks and ink removal products (based
on printing)
5.3.47 Commercial Use - Other uses - Inks and ink removal products (based on
photocopying)
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE for other uses - inks and
ink removal products (based on photocopying):
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
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12644
12645
12646
12647
12648
12649
12650
12651
12652
12653
12654
12655
12656
12657
12658
12659
12660
12661
12662
12663
12664
12665
12666
12667
12668
12669
12670
12671
12672
12673
12674
12675
12676
12677
12678
12679
12680
12681
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks in the absence of respiratory PPE, dermal acute and chronic non-cancer (high-end
and central tendency), and dermal cancer (high-end) risk estimates indicate risk in the absence of dermal
PPE. EPA does not assume routine use of respiratory or dermal PPE with this exposure scenario. Risk
estimates for ONUs for acute and chronic inhalation do not indicate risk at the central tendency. EPA
did not separately calculate risk estimates for ONUs and workers. There is uncertainty in the ONU risk
estimate since the data did not distinguish between worker and ONU inhalation exposure estimates.
ONU inhalation exposures are expected to be lower than inhalation exposures for workers directly
handling the chemical substance; however, the relative exposure of ONUs to workers in these cases
cannot be quantified. To account for this uncertainty, EPA considered the central tendency estimate
when determining ONU risk. No environmental risks were identified for this COU.
Life Cycle Stage
Category
S ii heat ego rv
Commercial Use
Other uses
Inks and ink removal products (based
on photocopying)
5.3,48 Commercial Use
- Other uses - Welding
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE for other uses - welding:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation and dermal exposures.
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12684
12685
12686
12687
12688
12689
12690
12691
12692
12693
12694
12695
12696
12697
12698
12699
12700
12701
12702
12703
12704
12705
12706
12707
12708
12709
12710
12711
12712
12713
12714
12715
12716
12717
12718
12719
12720
12721
12722
12723
12724
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
• Cancer resulting from chronic inhalation and dermal exposures.
Unreasonable risk driver - ONUs:
• Neurotoxicity resulting from acute and chronic inhalation exposures.
• Cancer resulting from chronic inhalation exposures.
Driver benchmarks - workers and ONUs:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 3.5 and 0.6 (central tendency and high-end) without PPE. (Table
4-31) (monitoring)
o Chronic inhalation MOEs 16 and 2.9 (central tendency and high-end) without PPE.
(Table 4-32) (monitoring)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-74)
o Chronic dermal MOEs 5.1 and 1.7 (central tendency and high-end) without PPE. (Table
4-75)
• Cancer (liver tumors):
o Inhalation: 2.6E-04 and 1.8E-03 (central tendency and high-end) without PPE. (Table
4-33) (monitoring)
o Dermal: 9.6E-04 and 3.7E-03 (central tendency and high-end) without PPE. (Table 4-76)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 50 and 6.8 (central tendency and high-end). (Table 4-31)
(modeling)
o Chronic inhalation MOEs 260 and 31 (central tendency and high-end). (Table 4-32)
(modeling)
• Cancer (liver tumors):
o Inhalation: 2.0E-05 and 1.4E-04 (central tendency and high-end). (Table 4-33)
(modeling)
Risk Considerations: For workers and ONUs, all pathways of occupational exposure for this condition
of use indicate risk in the absence of PPE. While EPA does not assume routine use of PPE with this
exposure scenario, risk was still present to workers with APF 50 for acute and chronic inhalation. The
estimates based on monitoring data only include values for workers as monitoring data for ONUs were
not identified. To account for lack of monitoring data for ONUs, EPA considered risk estimates from
exposure modeling when determining ONU risk. The near-field/far-field exposure modeling
incorporates variability in the model input parameters and distinguishes between workers and ONUs.
Model results are generally higher than monitoring data; however, the monitoring data includes data
from three sources that had concentrations of PCE in the aerosol formulation below the median value
predicted by the model. EPA has a high level of confidence in the assessed exposure for this condition
of use. No environmental risks were identified for this COU.
Page 524 of 636
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12737
12738
12739
12740
12741
12742
12743
12744
12745
12746
12747
12748
12749
12750
12751
12752
12753
12754
12755
12756
12757
12758
12759
12760
12761
12762
12763
12764
12765
12766
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12768
12769
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
l.il'e Cycle Stage
Category
S ii heal ego rv
Commercial Use
Other uses
Welding
5.3,49 Commercial Use - Other uses - Photographic film
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE for other uses -
photographic film:
• Presents an unreasonable risk of injury to health (workers and occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic inhalation, and acute and chronic dermal
exposures.
• Cancer resulting from chronic inhalation and chronic dermal exposures.
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute inhalation MOEs 0.8 and 8.9E-02 (central tendency and high-end) without PPE.
(Table 4-58)
o Chronic inhalation MOEs 3.6 and 0.4 (central tendency and high-end) without PPE.
(Table 4-59)
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Inhalation: 1.1E-03 and 1.3E-02 (central tendency and high-end) without PPE. (Table
4-60)
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Risk estimate - ONUs:
• Neurotoxicity:
o Acute inhalation MOEs 0.8 (central tendency). (Table 4-58)
o Chronic inhalation MOEs 3.6 (central tendency). (Table 4-59)
• Cancer (liver tumors):
o Inhalation: 1.1E-03 (central tendency). (Table 4-60)
Page 525 of 636
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12772
12773
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12775
12776
12777
12778
12779
12780
12781
12782
12783
12784
12785
12786
12787
12788
12789
12790
12791
12792
12793
12794
12795
12796
12797
12798
12799
12800
12801
12802
12803
12804
12805
12806
12807
12808
12809
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Risk Considerations: For workers, all pathways of occupational exposure for this condition of use
indicate risk (central tendency and high-end) in the absence of respiratory and dermal PPE. EPA does
not assume routine use of respiratory or dermal PPE with this exposure scenario. Risk estimates for
ONUs for acute and chronic non-cancer and cancer inhalation exposures indicate risk at the central
tendency EPA did not separately calculate risk estimates for ONUs and workers. There is uncertainty in
the ONU risk estimate since the data did not distinguish between worker and ONU inhalation exposure
estimates. ONU inhalation exposures are expected to be lower than inhalation exposures for workers
directly handling the chemical substance; however, the relative exposure of ONUs to workers in these
cases cannot be quantified. To account for this uncertainty, EPA considered the central tendency
estimate when determining ONU risk. No environmental risks were identified for this COU.
Life Cvcle Stage
Category
Subcategory
Commercial Use
Other uses
Photographic Film
5.3.50 Commercial Use - Other uses - Mold cleaning, release and protectant products
Section 6(b)(4)(A) unreasonable risk determination for commercial use of PCE for other uses - mold
cleaning, release and protectant products:
• Presents an unreasonable risk of injury to health (workers).
• Does not present an unreasonable risk of injury to health (occupational non-users).
• Does not present unreasonable risk to the environment (aquatic organisms).
Unreasonable risk driver - workers:
• Neurotoxicity resulting from acute and chronic dermal exposures
• Cancer resulting from chronic dermal exposures
Driver benchmarks - workers:
• Neurotoxicity: Acute non-cancer benchmark MOE = 10.
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
Risk estimate - workers:
• Neurotoxicity:
o Acute dermal MOEs 2.4 and 0.8 (central tendency and high-end) without PPE. (Table
4-77)
o Chronic dermal MOEs 5.0 and 1.7 (central tendency and high-end) without PPE. (Table
4-78)
• Cancer (liver tumors):
o Dermal: 9.8E-04 and 3.8E-03 (central tendency and high-end) without PPE. (Table 4-79)
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks, dermal acute non-cancer (high-end), dermal chronic non-cancer (high-end and
central tendency), and dermal cancer risk estimates (high-end) indicate risk. EPA does not assume
routine use of respiratory or dermal PPE with this exposure scenario. Risk estimates for ONUs for acute
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12819
12820
12821
12822
12823
12824
12825
12826
12827
12828
12829
12830
12831
12832
12833
12834
12835
12836
12837
12838
12839
12840
12841
12842
12843
12844
12845
12846
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
and chronic inhalation exposures do not indicate risk at the central tendency. Data for this condition of
use are area samples, not worker breathing zone samples. ONU inhalation exposures are expected to be
lower than inhalation exposures for workers directly handling the chemical substance; however, the
relative exposure of ONUs to workers in these cases cannot be quantified. To account for this
uncertainty, EPA considered the central tendency estimate when determining ONU risk. No
environmental risks were identified for this COU.
Life Cycle Singe
Category
Subcategory
Commercial Use
Other uses
Mold cleaning, release and protectant
products
5,3,51 Consumer Use - Cleaning and furniture care products - Cleaners and degreasers
(other)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in cleaning and furniture
care products - cleaners and degreasers (other):
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation and dermal exposures.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity:
o Acute inhalation MOE 0.2 (moderate intensity user). (Table 4-86)
o Acute dermal MOE 0.6 (moderate intensity user). (Table 4-87)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 0.8 (moderate intensity user). (Table 4-86)
Risk Considerations: All pathways of consumer and bystander exposure for this condition of use
indicate risk. Consumer and bystander risk determinations reflect the effects associated with acute
exposures. Risk estimates for consumer users at the medium intensity use scenarios of acute inhalation
and dermal exposures indicate risk. For bystanders, the risk estimates for the medium intensity use
scenario of acute inhalation indicate risk. Because bystanders are not expected to be dermally exposed to
PCE, dermal risks to bystanders were not evaluated. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
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12857
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12862
12863
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12865
12866
12867
12868
12869
12870
12871
12872
12873
12874
12875
12876
12877
12878
12879
12880
12881
12882
12883
12884
12885
12886
12887
12888
12889
12890
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Life Cycle Stage
Category
Subcategory
Consumer use
Cleaning and furniture care
products
Cleaners and degreasers (other)
5.3.52 Consumer Use - Cleaning and furniture care products - Dry cleaning solvent
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in cleaning and furniture
care products - dry cleaning solvent:
• Presents an unreasonable risk of injury to health (consumers).
• Does not present an unreasonable risk of injury to health (bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute dermal exposures.
Driver benchmarks - consumers:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Half-body acute dermal MOE 8.6 (Table 4-109, 1 day after dry cleaning, 2nd and 3rd generation).
• Full-body acute dermal MOE 2.9, 3.7, and 4.9 (Table 4-109, 1, 2, and 3 days after dry cleaning,
2nd and 3rd generation).
Risk Considerations: Consumer exposure to perchloroethylene due to off-gassing from recently dry
cleaned articles was evaluated for two scenarios, direct dermal contact with clothing to consumers and
inhalation exposure to bystanders from article storage in a home closet. Modeling was used to estimate
dermal and inhalation exposures. Measurements of PCE concentrations in indoor air from storage of
recently dry cleaned articles are in good agreement with modeling results. No direct measurements were
found for consumer dermal exposure to PCE from dry cleaned fabrics. Dermal exposure due to direct
skin contact with recently dry cleaned fabrics during article wear was assessed for consumer users, for
older and more modern dry cleaning technologies (2nd-5th generation). Risk estimates for consumer users
from articles dry cleaned with 2nd and 3rd generation machines indicate risk for half-body dermal
exposure to dry cleaned clothing (1 day after dry cleaning) and for full-body dermal exposure (1, 2, and
3 days after dry cleaning). EPA did not find risk to bystanders.
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Cleaning and furniture care
products
Dry cleaning solvent
5.3.53 Consumer Use - Cleaning and furniture care products - Automotive care products
(Brake cleaner)
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12897
12898
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12900
12901
12902
12903
12904
12905
12906
12907
12908
12909
12910
12911
12912
12913
12914
12915
12916
12917
12918
12919
12920
12921
12922
12923
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12925
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in cleaning and furniture
care products - automotive care products (brake cleaner):
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation and dermal exposures.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity:
o Acute inhalation MOE 0.2 (moderate intensity user). (Table 4-88)
o Acute dermal MOE 0.6 (moderate intensity user). (Table 4-89)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 0.8 (moderate intensity user). (Table 4-88)
Risk Considerations: All pathways of consumer and bystander exposure for this condition of use
indicate risk. Consumer and bystander risk determinations reflect the effects associated with acute
exposures. Risk estimates for consumer users at the medium intensity use scenarios of acute inhalation
and dermal exposures indicate risk. For bystanders, the risk estimates for the medium intensity use
scenario of acute inhalation indicate risk. Because bystanders are not expected to be dermally exposed to
PCE, dermal risks to bystanders were not evaluated. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Cleaning and furniture care
products
Automotive care products (Brake
cleaner)
5.3,54 Consumer Use - Cleaning and furniture care products - Automotive care products (Parts
cleaner)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in cleaning and furniture
care products - automotive care products (parts cleaner):
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation and dermal exposures.
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12936
12937
12938
12939
12940
12941
12942
12943
12944
12945
12946
12947
12948
12949
12950
12951
12952
12953
12954
12955
12956
12957
12958
12959
12960
12961
12962
12963
12964
12965
12966
12967
12968
12969
12970
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12974
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity:
o Acute inhalation MOE 0.6 (moderate intensity user). (Table 4-90)
o Acute dermal MOE 1.3E-02 (moderate intensity user). (Table 4-91)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 3.3 (moderate intensity user). (Table 4-90)
Risk Considerations: All pathways of consumer and bystander exposure for this condition of use
indicate risk. Consumer and bystander risk determinations reflect the effects associated with acute
exposures. Risk estimates for consumer users at the medium intensity use scenarios of acute inhalation
and dermal exposures indicate risk. For bystanders, the risk estimates for the medium intensity use
scenario of acute inhalation indicate risk. Because bystanders are not expected to be dermally exposed to
PCE, dermal risks to bystanders were not evaluated. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
l.il'e Cycle Stage
Category
S ii beat ego rv
Consumer use
Cleaning and furniture care
products
Automotive care products (Parts
cleaner)
5,3,55 Consumer Use - Cleaning and furniture care products - Aerosol cleaner
(Vandalism Mark & Stain Remover, Mold Cleaner, Weld Splatter Protectant)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in cleaning and furniture
care products - aerosol cleaner (vandalism mark & stain remover, mold cleaner, weld splatter
protectant):
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
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12978
12979
12980
12981
12982
12983
12984
12985
12986
12987
12988
12989
12990
12991
12992
12993
12994
12995
12996
12997
12998
12999
13000
13001
13002
13003
13004
13005
13006
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13008
13009
13010
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 0.3 (moderate intensity user). (Table 4-92)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 1.6 (moderate intensity user). (Table 4-92)
Risk Considerations: Risk estimates for consumer users and bystanders indicate risk from acute
inhalation exposures. Consumer and bystander risk determinations reflect the effects associated with
acute exposures. Dermal exposures were not quantified for this scenario, as consumer dermal exposure
with impeded evaporation is not expected, and bystanders are not expected to be dermally exposed to
PCE. For the consumer exposure scenario for bystanders, inhalation exposures were estimated using the
same model (CEM 2.1) used to estimate exposure to users. CEM 2.1 is a two-zone model that allows for
the estimation of air concentrations a user and bystander(s) would be exposed to following an exposure
event.
l.il'e Cycle Stage
Category
S ii beat ego rv
Consumer use
Cleaning and furniture care
products
Aerosol cleaner (Vandalism Mark &
Stain Remover, Mold Cleaner, Weld
Splatter Protectant)
5.3,56 Consumer Use - Cleaning and furniture care products - Non-aerosol cleaner (e.g.,
marble and stone polish)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in cleaning and furniture
care products - non-aerosol cleaner (e.g.. marble and stone polish):
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity:
o Acute inhalation MOE 6.8E-02 (moderate intensity user). (Table 4-93)
o Acute dermal MOE 5.4E-02 (moderate intensity user). (Table 4-94)
Risk estimate - bystanders:
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13019
13020
13021
13022
13023
13024
13025
13026
13027
13028
13029
13030
13031
13032
13033
13034
13035
13036
13037
13038
13039
13040
13041
13042
13043
13044
13045
13046
13047
13048
13049
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
• Neurotoxicity: Acute inhalation MOE 0.4 (moderate intensity user). (Table 4-93)
Risk Considerations: All pathways of consumer and bystander exposure for this condition of use
indicate risk. Consumer and bystander risk determinations reflect the effects associated with acute
exposures. Risk estimates for consumer users at the medium intensity use scenarios of acute inhalation
and dermal exposures indicate risk. For bystanders, the risk estimates for the medium intensity use
scenario of acute inhalation indicate risk. Because bystanders are not expected to be dermally exposed to
PCE, dermal risks to bystanders were not evaluated. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
Life Cycle Sla«e
Category
Subcategory
Consumer use
Cleaning and furniture care
products
Non-aerosol cleaner (e.g., marble and
stone polish)
5,3,57 Consumer Use - Lubricants and greases - Lubricants and greases (cutting fluid)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in lubricants and greases -
lubricants and greases (cutting fluid):
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 1.3 (moderate intensity user). (Table 4-95)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 6.7 (moderate intensity user). (Table 4-95)
Risk Considerations: Risk estimates for consumer users and bystanders at the medium intensity use
scenarios of acute inhalation exposures indicate risk. Consumer and bystander risk determinations
reflect the effects associated with acute exposures. Dermal exposures were not quantified for this
scenario, as consumer dermal exposure with impeded evaporation is not expected, and bystanders are
not expected to be dermally exposed to PCE. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
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13073
13074
13075
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users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Cleaning and furniture care
products
Lubricants and greases (cutting fluid)
5.3.58 Consumer Use - Lubricants and greases - Lubricants and greases (Lubricants and
Penetrating Oils)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in lubricants and greases -
lubricants and greases (lubricants and penetrating oils):
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 1.4 (moderate intensity user). (Table 4-96)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 7.3 (moderate intensity user). (Table 4-96)
Risk Considerations: Risk estimates for consumer users and bystanders at the medium intensity use
scenarios of acute inhalation exposures indicate risk. Consumer and bystander risk determinations
reflect the effects associated with acute exposures. Dermal exposures were not quantified for this
scenario, as consumer dermal exposure with impeded evaporation is not expected, and bystanders are
not expected to be dermally exposed to PCE. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Cleaning and furniture care
products
Lubricants and greases (lubricants and
penetrating oils)
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13104
13105
13106
13107
13108
13109
13110
13111
13112
13113
13114
13115
13116
13117
13118
13119
13120
13121
13122
13123
13124
13125
13126
13127
13128
13129
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5.3.59 Consumer Use - Adhesives and sealant chemicals - Adhesives for arts and crafts
(includes industrial adhesive, arts and crafts adhesive, gun ammunition sealant)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in adhesives and sealant
chemicals - adhesives for arts and crafts (includes industrial adhesive, arts and crafts adhesive, gun
ammunition sealant):
• Presents an unreasonable risk of injury to health (consumers).
• Does not present an unreasonable risk of injury to health (bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 2.3 (moderate intensity user). (Table 4-97)
Risk Considerations: Risk estimates for consumer users at the medium intensity use scenarios of acute
inhalation exposures indicate risk. EPA did not find risk to bystanders. Consumer risk determinations
reflect the effects associated with acute exposures. Dermal exposures were not quantified for this
scenario, as consumer dermal exposure with impeded evaporation is not expected, and bystanders are
not expected to be dermally exposed to PCE. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
l.il'e Cycle Stage
Category
Sii heal egorv
Consumer use
Adhesive and sealant
chemicals
Adhesives for arts and crafts (includes
industrial adhesive, arts and crafts
adhesive, gun ammunition sealant)
5.3,60 Consumer Use - Adhesives and sealant chemicals - Adhesives for arts and crafts
(Livestock Grooming Adhesive)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in adhesives and sealant
chemicals - adhesives for arts and crafts (livestock grooming adhesive):
• Does not present an unreasonable risk of injury to health (consumers and bystanders).
Benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
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13139
13140
13141
13142
13143
13144
13145
13146
13147
13148
13149
13150
13151
13152
13153
13154
13155
13156
13157
13158
13159
13160
13161
13162
13163
13164
13165
13166
13167
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13169
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Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 12 (moderate intensity user). (Table 4-98)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 64(moderate intensity user). (Table 4-98)
Risk Considerations: Risk estimates for consumer users and bystanders at the medium intensity use
scenarios of acute inhalation exposures do not indicate risk. Dermal exposures were not quantified for
this scenario, as consumer dermal exposure with impeded evaporation is not expected, and bystanders
are not expected to be dermally exposed to PCE. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Adhesive and sealant
chemicals
Adhesives for arts and crafts (Livestock
grooming adhesive)
5.3.61 Consumer Use - Adhesives and sealant chemicals - Adhesives for arts and crafts
(Column Adhesive, Caulk and Sealant)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in adhesives and sealant
chemicals - adhesives for arts and crafts (column adhesive, caulk and sealant):
• Presents an unreasonable risk of injury to health (consumers).
• Does not present an unreasonable risk of injury to health (bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 2.3 (moderate intensity user). (Table 4-99)
Risk Considerations: Risk estimates for consumer users at the medium intensity use scenarios of acute
inhalation exposures indicate risk. Consumer risk determinations reflect the effects associated with acute
exposures. Acute inhalation exposure for bystanders was not evaluated, as the consumer area of use was
assumed to be similar conditions as outside the home. Dermal exposures were not quantified for this
scenario, as consumer dermal exposure with impeded evaporation is not expected, and bystanders are
not expected to be dermally exposed to PCE.
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13184
13185
13186
13187
13188
13189
13190
13191
13192
13193
13194
13195
13196
13197
13198
13199
13200
13201
13202
13203
13204
13205
13206
13207
13208
13209
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Life Cycle Stage
Category
Subcategory
Consumer use
Adhesive and sealant
chemicals
Light Repair Adhesives - Adhesives for
arts and crafts (Column Adhesive,
Caulk and Sealant)
5,3,62 Consumer Use - Paints and coatings - Solvent-based paints and coatings (Outdoor
water shield (liquid))
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in paints and coatings -
solvent-based paints and coatings (outdoor water shield (liquid)):
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation and dermal exposures.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity:
o Acute inhalation MOE 1.1 (moderate intensity user). (Table 4-100)
o Acute dermal MOE 2.5E-02 (moderate intensity user) (Table 4-101)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 3.3 (moderate intensity user). (Table 4-100)
Risk Considerations: All pathways of consumer and bystander exposure for this condition of use
indicate risk. Consumer and bystander risk determinations reflect the effects associated with acute
exposures. Risk estimates for consumer users at the medium intensity use scenarios of acute inhalation
and dermal exposures indicate risk. For bystanders, the risk estimates for the medium intensity use
scenario of acute inhalation indicate risk. Because bystanders are not expected to be dermally exposed to
PCE, dermal risks to bystanders were not evaluated. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Paints and coatings
Solvent-based paints and coatings
(Outdoor water shield (liquid))
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13227
13228
13229
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13241
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
5.3.63 Consumer Use - Paints and coatings - Solvent-based paints and coatings (Coatings
and primers (aerosol))
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in paints and coatings -
solvent-based paints and coatings (coatings and primers (aerosol)):
• Does not present an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers and bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 62 (moderate intensity user). (Table 4-102)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 2143 (moderate intensity user). (Table 4-102)
Risk Considerations: Risk estimates for consumer users and bystanders at the medium intensity use
scenarios of acute inhalation exposures do not indicate risk. Dermal exposures were not quantified for
this scenario, as consumer dermal exposure with impeded evaporation is not expected, and bystanders
are not expected to be dermally exposed to PCE. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
Life Cycle Stage
Category
Subcategory
Consumer use
Paints and coatings
Solvent-based paints and coatings
(Coatings and primers (aerosol))
5.3.64 Consumer Use - Paints and coatings - Solvent-based paints and coatings (Rust
Primer and Sealant (liquid))
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in paints and coatings -
solvent-based paints and coatings (rust primer and sealant (liquid)):
• Presents an unreasonable risk of injury to health (consumers).
• Does not present an unreasonable risk of injury to health (bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from dermal exposures.
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13261
13262
13263
13264
13265
13266
13267
13268
13269
13270
13271
13272
13273
13274
13275
13276
13277
13278
13279
13280
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13282
13283
13284
13285
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13288
13289
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Driver benchmarks - consumers:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Acute dermal MOE 1.8E-02 (moderate intensity user) (Table 4-104)
Risk Considerations: Risk estimates for consumer users at the medium intensity use scenarios of dermal
exposures indicate risk. EPA did not find risk to bystanders. Consumer risk determinations reflect the
effects associated with dermal exposures. Because bystanders are not expected to be dermally exposed
to PCE, dermal risks to bystanders were not evaluated. For the consumer exposure scenario for
bystanders, inhalation exposures were estimated using the same model (CEM 2.1) used to estimate
exposure to users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a
user and bystander(s) would be exposed to following an exposure event.
Life Cycle Stage
Category
Sii heal egory
Consumer use
Paints and coatings
Solvent-based paints and coatings (Rust
Primer and Sealant (liquid))
5,3,65 Consumer Use - Paints and coatings - Solvent-based paints and coatings (Metallic
Overglaze)
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in paints and coatings -
solvent-based paints and coatings (metallic overglaze):
• Does not present an unreasonable risk of injury to health (consumers and bystanders).
Benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 337 (moderate intensity user). (Table 4-105)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 1674 (moderate intensity user). (Table 4-105)
Risk Considerations: Risk estimates for consumer users and bystanders at the medium intensity use
scenarios of acute inhalation exposures do not indicate risk. Dermal exposures were not quantified for
this scenario, as consumer dermal exposure with impeded evaporation is not expected, and bystanders
are not expected to be dermally exposed to PCE. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
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13300
13301
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13304
13305
13306
13307
13308
13309
13310
13311
13312
13313
13314
13315
13316
13317
13318
13319
13320
13321
13322
13323
13324
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Paints and coatings
Solvent-based paints and coatings
(Metallic Overglaze)
5.3,66 Consumer Use - Other Uses - Metal (e.g., stainless steel) and stone polishes
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in other uses - metal (e.g..
stainless steel) and stone polishes:
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation and dermal exposures.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity:
o Acute inhalation MOE 0.2 (moderate intensity user). (Table 4-106)
o Acute dermal MOE 0.1 (moderate intensity user) (Table 4-107)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 0.8 (moderate intensity user). (Table 4-106)
Risk Considerations: All pathways of consumer and bystander exposure for this condition of use
indicate risk. Consumer and bystander risk determinations reflect the effects associated with acute
exposures. Risk estimates for consumer users at the medium intensity use scenarios of acute inhalation
and dermal exposures indicate risk. For bystanders, the risk estimates for the medium intensity use
scenario of acute inhalation indicate risk. Because bystanders are not expected to be dermally exposed to
PCE, dermal risks to bystanders were not evaluated. For the consumer exposure scenario for bystanders,
inhalation exposures were estimated using the same model (CEM 2.1) used to estimate exposure to
users. CEM 2.1 is a two-zone model that allows for the estimation of air concentrations a user and
bystander(s) would be exposed to following an exposure event.
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Other Uses
Metal (e.g., stainless steel) and stone
polishes
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13342
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13345
13346
13347
13348
13349
13350
13351
13352
13353
13354
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13359
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13361
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
5.3.67 Consumer Use - Other Uses - Inks and ink removal products; welding; mold
cleaning, release and protectant products
Section 6(b)(4)(A) unreasonable risk determination for consumer use of PCE in other uses - inks and
ink removal products; welding; mold cleaning, release and protectant products;
• Presents an unreasonable risk of injury to health (consumers and bystanders).
Unreasonable risk driver - consumers:
• Neurotoxicity resulting from acute inhalation.
Unreasonable risk driver - bystanders:
• Neurotoxicity resulting from acute inhalation.
Driver benchmarks - consumers and bystanders:
• Neurotoxicity: Benchmark MOE =10.
Risk estimate - consumers:
• Neurotoxicity: Acute inhalation MOE 0.3 (moderate intensity user). (Table 4-92)
Risk estimate - bystanders:
• Neurotoxicity: Acute inhalation MOE 1.6 (moderate intensity user). (Table 4-92)
Risk Considerations: Risk estimates for consumer users and bystanders indicate risk from acute
inhalation exposures. Consumer and bystander risk determinations reflect the effects associated with
acute exposures. Dermal exposures were not quantified for this scenario, as consumer dermal exposure
with impeded evaporation is not expected, and bystanders are not expected to be dermally exposed to
PCE. For the consumer exposure scenario for bystanders, inhalation exposures were estimated using the
same model (CEM 2.1) used to estimate exposure to users. CEM 2.1 is a two-zone model that allows for
the estimation of air concentrations a user and bystander(s) would be exposed to following an exposure
event.
l.il'e Cycle Stage
Category
Subcategory
Consumer use
Other Uses
• Inks and ink removal products
• Welding
• Mold cleaning, release and
protectant products
5.3.68 Disposal
Section 6(b)(4)(A) unreasonable risk determination for the disposal of PCE:
• Presents an unreasonable risk of injury to health (workers).
• Presents an unreasonable risk to the environment (aquatic organisms).
• Does not present an unreasonable risk of injury to health (occupational non-users).
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13379
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13381
13382
13383
13384
13385
13386
13387
13388
13389
13390
13391
13392
13393
13394
13395
13396
13397
13398
13399
13400
13401
13402
13403
13404
13405
13406
13407
13408
13409
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Unreasonable risk driver - workers and aquatic organisms:
• Neurotoxicity resulting from chronic dermal exposures.
• Cancer resulting from chronic dermal exposures.
• Growth effects to aquatic invertebrates from chronic exposure.
• Algae mortality from exposure.
Driver benchmarks - workers and aquatic organisms:
• Neurotoxicity: Chronic non-cancer benchmark MOE = 100.
• Cancer (liver tumors): Benchmark = lxlO"4.
• Mortality: Algae RQ > 1.
Risk estimate - workers:
• Neurotoxicity:
o Chronic dermal MOEs 154 and 51 (central tendency and high-end) with PPE (gloves PF
= 20). (Table 4-69)
• Cancer (liver tumors):
o Dermal: 3.2E-05 and 1.2E-04 (central tendency and high-end) with PPE (gloves PF =
20). (Table 4-70)
Risk estimate for facilities with exceedances - aquatic organisms: (Table 4-110)
• Algae mortality from exposure: (some facilities had exceedances for multiple scenarios)
o RQ = 6.4 (algae, 172 days of exceedance, indirect release).
o RQ = 80 (algae, 20 days of exceedance, indirect release),
o RQ = 25 (algae, 235 days of exceedance, indirect release),
o RQ = 311 (algae, 20 days of exceedance, indirect release),
o RQ = 2.2 (algae, 90 days of exceedance, indirect release).
Risk Considerations: For workers, while non-cancer and cancer risk estimates for inhalation exposures
do not indicate risks with assumed respiratory protection (APF 25), dermal chronic non-cancer and
dermal cancer risk estimates (high-end) indicate risk even with assumed dermal protection (PF 20). Risk
estimates for ONUs for acute and chronic inhalation exposures do not indicate risk at the central
tendency. EPA did not separately calculate risk estimates for ONUs and workers. There is uncertainty in
the ONU risk estimate since the data did not distinguish between worker and ONU inhalation exposure
estimates. ONU inhalation exposures are expected to be lower than inhalation exposures for workers
directly handling the chemical substance; however, the relative exposure of ONUs to workers in these
cases cannot be quantified. To account for this uncertainty, EPA considered the central tendency
estimate when determining ONU risk.
Environmental releases for this condition of use indicate chronic risk to aquatic organisms and risk to
algae. Of the 13 facilities assessed for the waste handling, disposal, treatment, and recycling of PCE,
three facilities had releases indicating risk to aquatic organisms (RQs > 1 and 20 days of exceedance for
algae). RQ values ranged from 2.2 (90 days of exceedance, indirect discharge) to 311 (20 days of
exceedance, indirect discharge). 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).
EPA estimated 80% removal of PCE from indirect discharging facilities and 0% removal for direct
releases to surface water. Exceedances occurred using indirect release scenarios. An exceedance from
indirect release indicates that risk can exist even with waste water treatment if the rate of PCE release to
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13416 surface water is high. Four of the 13 facilities assessed as for the waste handling, disposal, treatment,
13417 and recycling of PCE did not have NPDES permits. EPA identified risk to algae from indirect release of
13418 PCE to surface water from one of the facilities without a NPDES permit. Lack of a NPDES permit
13419 increases the uncertainty in the surface water release estimate for a facility. Based on the surface water
13420 PCE concentration and COC confidence levels, the overall confidence in the risk estimate to aquatic
13421 organisms from exposure to PCE is medium.
13422
Life ( vole
(si logon
Siihcsilc«orv
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
13423
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13442
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13449
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13453
13454
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
REFERENCES
,H Huh."It \ K, Rum M >, R.mtachandun * I_'i c»li ioksoii \1 C.t<.
Apol. (1981). Health hazard evaluation report no. HETA 81-105-831, Labels West, Inc., Redmond,
Washington. (HETA 81-105-831). Cincinnati, OH: National Institute for Occupational Safety
and Health.
Aschengi \ lUagher. LG: Winter. MR; Vieira. VM; Janulewi-' ^ \ Webster. TF; Ozonoff. DM.
(2016a). No association between unintentional head injuries and early-life exposure to
tetrachloroethylene (PCE)-contaminated drinking water. J Occup Environ Med 58: 1040-1045.
http://dx.doi.ore 10 10^ K *\[.0000000000000850.
Aschengrau. A; Janule\\ > I \ \\ bite. RF; Vieira. VM; Gallagher * >z. KD; Webster. TF;
Ozonoff. DM. (2016b). Long-term neurotoxic effects of early-life exposure
to tetrachloroethylene-contaminated drinking water. 82: 169-179.
http://dx.doi.ore 10 101 i.aogh.201 01 01 '<
Aschengniu \ <15 on off. D; Paulu. C; Coogan. P; Vezina. R; Heeren. T; Zhang "S (1993). Cancer risk
and tetrachloroethylene-contaminated drinking water in Massachusetts. Arch Environ Health 48:
284-292. http://dx.doi.cnv 10 10X0/00039896.1993.993. t>
Aschengrau. A; Paulu t _ Ozonoff 1 > (1998). Tetrachloroethylene-contaminated drinking water and the
risk of breast cancer. Environ Health Perspect 106: 947-953.
Aschengrau. A; Rogers. S; Ozonoff. D (2003). Perchloroethylene-contaminated drinking water and the
risk of breast cancer: Additional results from Cape Cod, Massachusetts, USA. Environ Health
Perspect 111: 167-173. http://dx.doi.org/ ?/ehp.4980.
Aschengrau. A; Weinberg. JM; Janulewk P \ Kcmano Ul illagher. LG; Winter. MR; Martin. BR;
Vieira. VM; Webster. TF; Wh ;onoff. DM. (2011). Affinity for risky behaviors
following prenatal and early childhood exposure to tetrachloroethylene (PCE)-contaminated
drinking water: A retrospective cohort study. Environ Health 10: 102.
http://dx.doi.ore 10 I is n 0 \ 10 102.
AT SDR. (2014). Toxicological profile for tetrachloroethylene (Draft for public comment). Atlanta, GA:
US Department of Health and Human Services, Public Health Service.
http://www.atsdr.cdc. gov/ToxProfiles/tp.asp?id=265&tid=48.
AT SDR. (2019). Toxicological profile for tetrachloroethylene. Atlanta, GA: U.S. Department of Health
and Human Services. https://www.atsdr.cdc.gov/ToxProfiles/tp 18.pdf.
Barrows. ME; Petrocelli. SR; Macek. 1. II. (1980). Bioconcentration and elimination of
selected water pollutants by bluegill sunfish (Lepomis macrochirus). In R Haque (Ed.), (pp. 379-
392). Ann Arbor, MI: Ann Arbor Science.
Barul. C; Favosi 'arton. M; Pilorget. C; Woronoff. AS; Stucker. I; Luce. D; group. is, (2017).
Occupational exposure to chlorinated solvents and risk of head and neck cancer in men: a
population-based case-control study in France. Environ Health 16: 77.
http://dx.doi.org 10 I 186/sl29 10 01 0:86-5.
Page 543 of 636
-------
13471
13472
13473
13474
13475
13476
13477
13478
13479
13480
13481
13482
13483
13484
13485
13486
13487
13488
13489
13490
13491
13492
13493
13494
13495
13496
13497
13498
13499
13500
13501
13502
13503
13504
13505
13506
13507
13508
13509
13510
13511
13512
13513
13514
13515
13516
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Batterman. S; Jia. C; Hatzivasilis. G. (2007). Migration of volatile organic compounds from attached
garages to residences: A major exposure source. Environ Res 104: 224-240.
http://dx.doi.ore 10 101 i.envres.AV 01 008.
Beliles. RP; Brusict feeler. FJ. (1980). Teratogenic-mutagenic risk of workplace contaminants:
trichloroethylene, perchloroethylene, and carbon disulfide. (210-77-0047). Cincinnati, OH:
National Institute for Occupation Safety and Health.
Bereamaschi. E; Minn \ <'<»cchi. MC: Alinovi. " < Hivetti. G: Ghieeeri. GM; Franchini. I. (1992V Rat
model of perchloroethylene-induced renal dysfunctions. Environ Res 59: 427-439.
http://dx.doi.ore 10 101 c-001 '< ^ I ..0 -080046-5.
Blando. ID; Schill MP 1 K' 1 j 1 tuz. MP; Zknn 1 'hang. J. (2010). Preliminary study of propyl
bromide exposure among New Jersey dry cleaners as a result of a pending ban on
perchloroethylene. J Air Waste Manag Assoc 60: 1049-1056. http://dx.doi.or
3289.60.9.1049.
Boice 11 * h Vlarano. D; Frvzek. J; Sadln t McLaughlin. IK. (1999). Mortality among aircraft
manufacturing workers. Occup Environ Med 56: 581-597.
http://dx.doi.ore >em.56.9.581.
Boiro tv. PL. (1982). Removal of trace chlorinated organic compounds by activated carbon
and fixed-film bacteria. Environ Sci Technol 16: 836-843.
http://dx.doi.ore/10J02 i/es00106a003.
Boiro tmann. BE; McCartv. PL. (1981). Anaerobic degradation of halogenated 1- and 2-carbon
organic compounds. Environ Sci Technol 15: 596-599. http://dx.doi.ore/10.1021/es00087a012.
Bove. ickart. PZ; Maslia. M; Larson. TC. (2014a). Electronic supplementary material: Evaluation
of mortality among marines and navy personnel exposed to contaminated drinking water at
USMC base Camp Lejeune: A retrospective cohort study. Environ Health 13.
B ickart. PZ; Maslia. M; Larson. TC. (2014b). Evaluation of mortality among marines and
navy personnel exposed to contaminated drinking water at USMC base Camp Lejeune: A
retrospective cohort study. Environ Health 13: 10. http://dx.doi.on i 0 lis II 0/s \ l'< 10
Boverhol ger. SM; Hotchkiss. J; Stebbins. KE; Thomas. J; Woolhiser. MR. (2013).
Assessment of the immunotoxic potential of trichloroethylene and perchloroethylene in rats
following inhalation exposure. J Immunotoxicol 10: 311-320.
http://dx.doi. ore/10.3109/1 •» i
Boves. WK; Berceeeay. M; Oshiro. WM; Krantz. QT; Kenyon. EM; Bushnel enignus. VA.
(2009). Acute perchloroethylene exposure alters rat visual-evoked potentials in relation to brain
concentrations. Toxicol Sci 108: 159-172. http://dx.doi.ore/10.1093/toxsci/kfn265.
Brack. W; Rottler. H. (1994). Toxicity testing of highly volatile chemicals with green algae: A new
assay. Environ Sci PollutRes Int 1: 223-228.
Bub en J \. P'lr'hiici t \ < > (1985). Delineation of the role of metabolism in the hepatotoxicity of
trichloroethylene and perchloroethylene: A dose-effect study. Toxicol Appl Pharmacol 78: 105-
122.
Bulka. C; Nastoupil * 1 Uoff. JL; Bernal-Mizrachi. L; Ward. KC; Williai > 1 x M .yakh \k
Switchenko. JM; Waller. LA; Flowers. CR. (2016). Relations between residential proximity to
EPA-designated toxic release sites and diffuse large B-cell lymphoma incidence. South Med J
109: 606-614. http://dx.doi.on 10 I I L >/SMI 0000000000000 > I >
Burotn. NC. (1994). Health hazard evaluation report no. HETA 93-035 1-2413, Goodwill Industires of
America, Inc. Bethesda, Maryland. (HETA 93-0351-2413). Cincinnati, OH: National Institute
for Occupational Safety and Health.
Page 544 of 636
-------
13517
13518
13519
13520
13521
13522
13523
13524
13525
13526
13527
13528
13529
13530
13531
13532
13533
13534
13535
13536
13537
13538
13539
13540
13541
13542
13543
13544
13545
13546
13547
13548
13549
13550
13551
13552
13553
13554
13555
13556
13557
13558
13559
13560
13561
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Burroughs. GE. (1999a). Evaluation of Eight Dry Cleaning Shops with State-of-the-Art Control
Equipment. Report on Task 1. Perchloroethylene in Dry Cleaning Shops. NIOSH.
https://ntrl.ntis.eov/NTRL/dashboard/searchResiilts/titleDetail/PB99168890.xhtml.
Burroughs. GE. (1999b). In-depth survey report evaluation of control technology for perchlorethylene in
dry cleaning shops. (ECTB 240-11). Cincinnati, OH: NIOSH.
https://www.cdc.gov/niosh/siirveyreports/pdl )df.
Burroughs. GE. (2000). In-depth survey report evaluation of control technology for perchlorethylene in
dry cleaning shops. (ECTB 240-12). Cincinnati, OH: NIOSH.
https://www.cdc.gov/niosh/siirveyreports/pdl )df.
Burton. NC: Monesterskv. J. (1996). Health hazard evaluation report No. HETA 96-0135-2612, Eagle
Knitting Mills, Inc., Shawano, Wisconsin. Cincinnati, OH: U.S. National Institute for
Occupational Safety and Health.
Cabirol. N: Pen>n 1 -acoh I', I'ouill^i •.'hambon. P. (1996). Role of methanogenic and sulfate-
reducing bacteria in the reductive dechlorination of tetrachloroethylene in mixed culture. Bull
Environ Contam Toxicol 56: 817-824. http://dx.doi.org/10J007/s001289900119.
California Air Resources. B (2006). California Dry Cleaning Industry Technical Assessment Report.
Stationary Source Division, Emissions Assessment Branch.
https://www.arb.ca.gov/toxics/dryclean/finaldrycleantechreport.pdf.
G iad. N. (1979). Toxicity, bioconcentration and metabolism of selected
chemicals in aquatic organisms: Third quarterly progress report to EPA (1 October - 31
December 1979). (EPA Cooperative Agreement No.CR 806864020). Superior, WI: University of
Wisconsin.
< I Uiioad. N. (1980). Toxicity, bioconcentration, and metabolism of selected
chemicals in aquatic organisms: Fourth quarterly progress report to EPA (1 January - 31 March
1980). (U.S. EPA Cooperative Agreement No. CR 806864020). Superior, WI: University of
Wisconsin.
< l Unpad. N: Richter. IE. (1983). Toxicity and metabolism studies with EPA
(Environmental Protection Agency) priority pollutants and related chemicals in freshwater
organisms (pp. 120 p.). (EPA/600/3-83/095 (NTIS PB83263665)). Duluth, MN: U.S.
Environmental Protection Agency.
Calvert.. GM; Ruder. AM; Petersen. MR. (201 1). Mortality and end-stage renal disease incidence among
dry cleaning workers. Occup Environ Med 68: 709-716.
http://dx.doi.org 10 I l'< oem. JO 10 060665.
Canada. C. (2017). Profiles & estimates: Tetrachloroethylene.
http://www.carexcanada.ca/en/tetrachloroethylene/.
CA.RB. (2000). Initial statement of reasons for the proposed airborne toxic control measure for
emissions of chlorinated toxic air contaminants from automotive maintenance and repair
activities.
Carnt i or said. BA; Dugard. PH.; Zablotny. CL. (2006). Developmental toxicity studies in
Crl:CD (SD) rats following inhalation exposure to trichloroethylene and perchloroethylene. Birth
Defects Res B Dev Reprod Toxicol 77: 405-412. http://dx.doi.org/10.1002/bdrb.20091.
Carton. M; Barul. C; Menvielb' 1 w n Sanchez. M; Pilorg^t t _ v ntcke> i 1 uee. I.)
(2017). Occupational exposure to solvents and risk of head and neck cancer in women: A
population-based case-control study in France. BMJ Open 7: e012833.
http://dx.doi.ore tmi open-2016-012833.
Page 545 of 636
-------
13562
13563
13564
13565
13566
13567
13568
13569
13570
13571
13572
13573
13574
13575
13576
13577
13578
13579
13580
13581
13582
13583
13584
13585
13586
13587
13588
13589
13590
13591
13592
13593
13594
13595
13596
13597
13598
13599
13600
13601
13602
13603
13604
13605
13606
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Cavalier! \ obba I <\tltrinieri. M; Fantuzzi. G; Righi. E; Aeeazzotti. G. (1994). Perchloroethylene
exposure can induce colour vision loss. Neurosci Lett 179: 162-166.
http://dx.doi.ors >304-3940(94)90959-8.
CDC. (2017). National report on human exposure to environmental chemicals.
https://www.cdc.eov/exposurereport/.
Chan. CC; Vainer. L; Martin. JW; Williams. DT. (1990). Determination of organic contaminants in
residential indoor air using an adsorption-thermal desorption technique. J Air Waste Manag
Assoc 40: 62-67.
Chan. WR; Cohn. S: Sidheswaran. M; Sullivan. DP; Fisk. WJ. (2014). Contaminant levels, source
strengths, and ventilation rates in California retail stores. Indoor Air 25: 381-392.
http://dx.doi.ore 10 I I I I uu IJ I
Chane. JC; Guo. Z; Sparks. LE. (1998). Exposure and emission evaluations of methyl ethyl ketoxime
(MEKO) in alkyd paints. Indoor Air 8: 295-300. http://dx.doi.c
0668.1998.0
Chao. CYH; Tung. TCW; Niu. vL (1999). Indoor perchloroethylene
accumulation from dry cleaned clothing on residential premises. Build Environ 34: 319-328.
ChemView. (2019). 1-Naphthol. https://chemview.epa.eov/chemview/ 'it
'< i's\5&as=3-10-9-8&a ill - 99&ma=4-l 1-
l_(ss\ ' IOAtasl=l&tas2=asc&tas3=undefined&tss=&modal=detail&modalId= 12
ir Awodah I
Clim i* ' M»S\\in. C; Parker. E: Robin*- < 1 is. 1 . Harbin. P; Batterman. S. (2014). Levels and
sources of volatile organic compounds in homes of children with asthma. Indoor Air 24: 403-
415. http://dx.doi.oi ^na. 12086.
Chiu. WA; Ginsbere. GL. (201 la). Development and evaluation of a harmonized physiologically based
pharmacokinetic (PBPK) model for perchloroethylene toxicokinetics in mice, rats, and humans.
Toxicol Appl Pharmacol 253: 203-234.
http://dx.doi.ors taap.2011.03.020. https://heronet.epa. eov/heronet/index.cfm?action=s
earch.view&reference id 784005Christensen. KY; Vizcaya, D; Richardson, H; Lavoue, J;
Aronson, K; Siemiatycki, J. (2013). Risk of selected cancers due to occupational exposure to
chlorinated solvents in a case-control study in Montreal. J Occup Environ Med 55: 198-208.
http://dx.doi.ors L0b013e3182728eab.
Chrostek. WJ; Levine. MS. (1981). Health Hazard Evaluation Report 80-154-1027: Bechtel Power
Corporation. (HHE 80-154-1027). NIOSH. https://www.cdc.gov/niosh/hhe/reports/pdfs/80-154-
1027.pdf?id=! 0.26616/NIO SHHHE801541027.
Cichcx I > <\ i muya. S; Venkatratnam \ VlcDonald. TJ; Knap. AH; Wade. T; Sweet. S; Chiu. WA;
Threadei isyn. I. (2017). Characterization of Variability in Toxicokinetics and
Toxicodynamics of Tetrachloroethylene Using the Collaborative Cross Mouse Population.
Environ Health Perspect 125: 057006. http://dx.doi. 9/EHP788.
Clayton. ffizzari. ED; Whitmore. RW; Perritt. RL; Ouackenboss. II. (1999). National Human
Exposure Assessment Survey (NHEXAS): Distributions and associations of lead, arsenic, and
volatile organic compounds in EPA Region 5. J Expo Anal Environ Epidemiol 9: 381-392.
http://dx.doi.ors ?8/si.iea.7500Q55.
Cooper. J. (2017). Comment submitted by James Cooper, Senior Petrochemical Advisor, American Fuel
& Petrochemical Manufacturers (AFPM) [Comment],
https://www.reeiilations.eov/dociimeni * < PA-HQ-OIT 1 .01 0 II OOP'
Page 546 of 636
-------
13607
13608
13609
13610
13611
13612
13613
13614
13615
13616
13617
13618
13619
13620
13621
13622
13623
13624
13625
13626
13627
13628
13629
13630
13631
13632
13633
13634
13635
13636
13637
13638
13639
13640
13641
13642
13643
13644
13645
13646
13647
13648
13649
13650
13651
13652
13653
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Cosgrove. H; Hygiene. I. (1994). Perchloroethylene Survey, Radiator Specialty Company. (EPA-HQ-
OPPT-2016-0732-0027). Charlotte, NC: Cosgrove Health & Hygiene Inc.
https://www.reeiilations.eov/documeiii * < '.PA-HQ-Ql « I I _ ^027.
Cupit (1987). Atmospheric persistence of eight air toxics. (EPA600S387004). Cupitt, LT.
D'Souza. JC . Jia. C; Mukhcu^' <1 < 'dtterman. S. (2009). Ethnicity, housing and personal factors as
determinants of VOC exposures. Atmos Environ 43: 2884-2892.
http://dx.doi.ore 10 101 i.atmosenv.l.00*" 0 '< 01
Davis. R. (2017). Comment submitted by Raleigh Davis, Assistant Director, Environmental Health and
Safety, American Coatings Association (ACA) [Comment],
https://www.regulations.gov/document?D=EPA-HQ-Q] < I _ ^ l ^ L < '025.
de Bias. M; Navazo. M; Alonso. L; Durana. N: Gomez. MC: Iza. J. (2012). Simultaneous indoor and
outdoor on-line hourly monitoring of atmospheric volatile organic compounds in an urban
building. The role of inside and outside sources. Sci Total Environ 426: 327-335.
http://dx.doi.ore 10 101 i.scitotenv.201 J 0 I 003.
de Bruin. WP; Kotterman. Ml; Posthumus. MA; Schraa hnder. A J. (1992). Complete biological
reductive transformation of tetrachloroethene to ethane. Appl Environ Microbiol 58: 1996-2000.
Deferme. L; Wolters. J: Claessen. S: Briede. J; Kleinians. J. (2015). Oxidative Stress Mechanisms Do
Not Discriminate between Genotoxic and Nongenotoxic Liver Carcinogens. Chem Res Toxicol
28: 1636-1646. http://dx.doi.ore/10.1021/acs.chemrestox.5b00222.
Di Toro. DM. (1984). Probability model of stream quality due to runoff. J Environ Eng 1 10: 607-628.
http://dx.doi. ore/10.1061/f ASCE)0733-9372( 191 :3(607).
Pilling. WL; Tefertiller. NB; Kallos. GJ. (1975). Evaporation rates and reactivities of methylene
chloride, chloroform, 1,1,1-trichloroethane, trichloroethylene, tetrachloroethylene, and other
chlorinated compounds in dilute aqueous solutions. Environ Sci Technol 9: 833-838.
http://dx.doi.ore/10.102 i/es60107a008.
DLI/NCA. (2017). Public comment on tetrachloroethylene. TSCA review and scoping. (EPA-HQ-
OPPT-2016-0732). https://www.reeulations.eov/document?D=EPA-HQ-OPPT-^
Dodson. RT, I \ u v f nglei J1), Shine J]!, Bennett. DH. (2008). Influence ofbasements, garages,
and common hallways on indoor residential volatile organic compound concentrations. Atmos
Environ 42: 1569-1581. http://dx.doi.ore/10 101 i atmosenv.200 I00\8.
Dosemeci. M; Cocco. P; Chow. WH. (1999). Gender differences in risk of renal cell carcinoma and
occupational exposures to chlorinated aliphatic hydrocarbons. Am J Ind Med 36: 54-59.
http://dx.doi.ore 10 100: * SICDl097-0274(199907) K54::AID-AJIM8>3.0.CO;2-0.
Dow Chem. C. (1973). Uptake, clearance and bioconcentration of dow-per (perchloroethy 1 ene) in
rainbow trout, Salmo gairdneri richardson. (8EHQ Num: NA; DCN: 86-870002077; TSCATS
RefID: 309906; CIS: NA).
Dow Chem. C. (1979). Evaluation of work exposures in ag production and distribution department
(apd2) operations, pittsburg, for 1978 with cover letter. (OTS: OTS0206690; 8EHQ Num: NA;
DCN: 878214806; TSCATS RefID: 25878; CIS: NA). Dow Chem Co.
Dow Chem. C. (1982). CHLOR-PYRIDINES - 1981 INDUSTRIAL HYGIENE SURVEY
(SANITIZED). (OTS: OTS0515873; 8EHQ Num: NA; DCN: 86-870002349; TSCATS RefID:
309318; CIS: NA).
Dow Chem. C. (1983a). 1982 INDUSTRIAL HYGIENE MONITORING - CHLOROPYRIDINES
(SANITIZED). (OTS: OTS0515889; 8EHQ Num: NA; DCN: 86-870002365; TSCATS RefID:
309350; CIS: NA).
Dow Chem. C. (1983b). Chemical exposure evaluation - Trichloroethylene production plant (sanitized).
(EPA/OTS; Doc #86-870002355). Dow Chem Co.
Page 547 of 636
-------
13654
13655
13656
13657
13658
13659
13660
13661
13662
13663
13664
13665
13666
13667
13668
13669
13670
13671
13672
13673
13674
13675
13676
13677
13678
13679
13680
13681
13682
13683
13684
13685
13686
13687
13688
13689
13690
13691
13692
13693
13694
13695
13696
13697
13698
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Dow Chem. C. (1984). INDUSTRIAL HYGIENE SURVEYS DURING 1983 AT THE EASTERN
DIVISION MARINE TERMINAL AT JOLIET, ILLINOIS (SANITIZED). (OTS: OTS0515882;
8EHQNum: NA; DCN: 86-870002358; TSCATS RefID: 309336; CIS: NA).
Dow Chem. C. (2008). Product safety assessment: Perchloroethylene. http://N/A.
Dow Chemical Co (Dow Chemical Company). (2008). Product safety assessment: Perchloroethylene.
Powell. R. (2017). Comment submitted by Robert Dowel 1, President, Plasma Technology Inc. (PTI)
[Comment], https://www.reeulations.eov/document?D=EPA-HQ-OPPT-!
Ducommun. I. (2017). HSIA Support Ducommun. (EPA-HQ-OPPT-2016-0732-0027). Washington,
D.C.: Ducommun Inc. https://www.reeulations.eov/document?D=< " \ S iQ~0> < I .
0027.
Durkee. J. (2014). Cleaning with solvents: Methods and machinery. Oxford, UK: Elsevier Inc.
https://www.sciencedirect.com/book/978Q3232252Q5/cleaning~with~solvents~methods~and~
machinery.
Ebrahim. AS: Babakrishnan. K; Sakthisekara (1996). Perchloroethylene-induced alterations in
glucose metabolism and their prevention by 2-deoxy-D-glucose and vitamin E in mice. J Appl
Toxicol 16: 339-348. http://dx.doi.on 02/fSICI)1099-1263f 199607) 16:4<339::AID-
JAT3 52>3 O.CO;2-3.
ECB. (2005). European Union risk assessment report: Tetrachloroethylene. Part 1 - Environment.
(EINECS No: 204-825-9). United Kingdom: European Commission - Joint Research Centre
Institute for Health and Consumer Protection European Chemicals Bureau.
Echeverria. D; White. RP; Sampaio. C. (1995). A behavioral evaluation of PCE exposure in patients and
dry cleaners: A possible relationship between clinical and preclinical effects. J Occup Environ
Med 37: 667-680.
Eisenberg. J: Ramsey. J. (2010). Health hazard evaluation report no. HETA 2008-0175-3 111, Evaluation
of 1-Bromopropane use in four New Jersey commercial dry cleaning facilities. (HETA 2008-
0175-3111). Cincinnati, OH: National Institute for Occupational Safety and Health.
Elfan mse. RJ. (2007). S-( l,2,2-trichlorovinyl)-L-cysteine sulfoxide, a reactive metabolite of
S-(l,2,2-Trichlorovinyl)-L-cysteine formed in rat liver and kidney microsomes, is a potent
nephrotoxicant. J Pharmacol Exp Ther 321: 1095-1101.
http://dx.doi.ore 10 I IJ I t pet. 10 IJ0444.
ERG. (2005). [Letter from Eric Goehl and Jennifer O'Neil, Eastern Research group, Inc, to Dry Cleaning
Docket, Subject: Background information document] [Personal Communication],
http ://www3. epa. gov/airtoxics/dryper ibackgroumd.pdf.
Eskenazi r% i ^nster. L; Hudes. M; Wvrobek \< Lit 1U erson. J: Rempel. DM. (1991). A study of
the effect of perchloroethylene exposure on the reproductive outcomes of wives of dry-cleaning
workers. Am J Ind Med 20: 593-600. http://dx.doi.ore/10.1002/aiim.4700200503.
Eu. (2001). Draft risk assessment report: Tetrachloroethylene. United Kingdom.
European Solvents Industry. G (2012). SPERC fact sheet: Manufacture of substance - industrial
(solvent-borne). Brussels, Belgium: European Solvents Industry Group (ESIG).
https://www.esie.ore/reach~ees/environment/.
European Solvents Indt (2019). Industrial - solvent-borne (formulation and (re)packaging of
substances and mixtures), https://www.esie.ore/reach~ees/environment/.
Everatt. R; Slapsvte. G: Mierauskiene. J: Dedonvte. V: Bakiene. L. (2013). Biomonitoring study of dry
cleaning workers using cytogenetic tests and the comet assay. J Occup Environ Hyg 10: 609-621.
http://dx.doi.ore 10 1080/1 I x . i ..013.818238.
Page 548 of 636
-------
13699
13700
13701
13702
13703
13704
13705
13706
13707
13708
13709
13710
13711
13712
13713
13714
13715
13716
13717
13718
13719
13720
13721
13722
13723
13724
13725
13726
13727
13728
13729
13730
13731
13732
13733
13734
13735
13736
13737
13738
13739
13740
13741
13742
13743
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Fay. K. (2017). Comment submitted by Kevin Fay, Executive Director, Alliance for Responsible
Atmospheric Policy (Alliance) [Comment], https://www.regulations.gov/document?D=EPA-HQ-
Federal Register. (1989). National emissions standards for hazardous air pollutants; benzene emissions
from maleic anhydride plants, ethylbenzene/styrene plants, benzene storage vessels, benzene
equipment leaks, and coke by-product recovery plants. Fed Reg 54: 38044-38072.
Ferroni. C; Selis. L; Mimi \. I'oili. D; Bergamaschi 1I'ranchini. I. (1992). Neurobehavioral and
neuroendocrine effects of occupational exposure to perchloroethylene. Neurotoxicology 13: 243-
247.
Fishbein. L. (1992). Exposure from occupational versus other sources [Review], Scand J Work Environ
Health 18: 5-16.
Ford Motor. C. (1981). Industrial hygiene survey - spray booths, oil house, roll weld, bonderite deck,
trimline. (OTS: OTS0206239; 8EHQ Num: NA; DCN: 878210810; TSCATS RefID: 17580;
CIS: NA).
Gallaehe ra. VM; Ozonoff. D; Webster. TF; Aschengrau. A. (2011). Risk of breast cancer
following exposure to tetrachloroethylene-contaminated drinking water in Cape Cod,
Massachusetts: Reanalysis of a case-control study using a modified exposure assessment.
Environ Health 10: 47. http://dx.doi.ore/10.H8C-: II 069'. \ 10 I .
Getz. KD; Janulewicz. PA; Rowe. S; Weinberg. JM; Winter. MR; Martin. BR; Vieira. VM; White. RF;
Aschengrau. A. (2012). Prenatal and early childhood exposure to tetrachloroethylene and adult
vision. Environ Health Perspect 120: 1327-1332. http://dx.doL ^ s o s _ '9/eht> I 10 >996.
Gobba. F; Right E; Fantuz ieri. G; Cavazzuti. L; Aggazzotti. G. (1998). Two-year evolution
of perchloroethylene-induced color-vision loss. Arch Environ Health 53: 196-198.
http://dx.doi.orE 30/00039899809605695.
Gel*! < v De Roos. \ J W aters. M; Stewju P (2008). Systematic literature review of uses and levels of
occupational exposure to tetrachloroethylene [Review], J Occup Environ Hyg 5: 807-839.
http://dx.doi.orE 30/15459620802510866.
Goldman. SM; Quinlan 3ss. GW; Marras. C; Memg. C; Bhudhikanok. GS; Comyns. K; Korell. M;
Chade. AR; Kasten. M; Priestley. B; Chou. KL; Fernandez. HH; Cam :ston. JW;
Tanner. CM. (2012). Solvent exposures and Parkinson disease risk in twins. Ann Neurol 71: 776-
784. http://dx.doi.org/10.1002/ana.22629.
Goldsworthy. TL; Lyght. O; Burn pp. J A. (1988). Potential role of [alpha]-2[mu]-globulin,
protein droplet accumulation, and cell replication in the renal carcinogenicity of rats exposed to
trichloroethylene, perchloroethylene, and pentachloroethane. Toxicol Appl Pharmacol 96: 367-
379. http://dx.doi.oi /Q0414)08X(88)90095-6.
Goldsworthy. TL; Pope (1987). Chlorinated hydrocarbon-induced peroxisomal enzyme activity in
relation to species and organ carcinogenicity. Toxicol Appl Pharmacol 88: 225-233.
http://dx.doi.ore 10 101 00 II 008X(87)90008-1.
Gorman. R; Rinskv. R; Stein. G; Anderson. K. (1984). Health hazard evaluation report no. HETA 82-
075-1545, Pratt & Whitney Aircraft, West Palm Beach, Florida. (HETA 82-075-1545).
Cincinnati, OH: National Institute for Occupational Safety and Health.
Gossett. JM. (1987). Measurement of Henry's law constants for C 1 and C2 chlorinated hydrocarbons.
Environ Sci Technol 21: 202-208. http://dx.doL 00156a012.
Graul. F. (2017). Comment submitted by Faye Graul, Executive Director, Halogenated Solvents
Industry Alliance, Inc. (HSIA) regarding Docket No. EPA-HO-OPPT-20 I 6-0732.
Page 549 of 636
-------
13744
13745
13746
13747
13748
13749
13750
13751
13752
13753
13754
13755
13756
13757
13758
13759
13760
13761
13762
13763
13764
13765
13766
13767
13768
13769
13770
13771
13772
13773
13774
13775
13776
13777
13778
13779
13780
13781
13782
13783
13784
13785
13786
13787
13788
13789
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Green V, i >dum. J; Nat it > \ I <<- ter. JR. (1990). Perchloroethylene-induced rat kidney tumors: An
investigation of the mechanisms involved and their relevance to humans. Toxicol Appl
Pharmacol 103: 77-89. http://dx.doi.o >/0041 -008X(90)90264-U.
Gromiec. IP; Wesolowski. leznicki. S; Wroblewska-Jakubowska. K; Kucharska. M. (2002).
Occupational exposure to rubber vulcanization products during repair of rubber conveyor belts in
a brown coal mine. J Environ Monit 4: 1054-1059. http://dx.doi.ore/10.1039/b209207e.
Gulyas. H; Hemmerline. L. (1990). Tetrachloroethene air pollution originating from coin-operated dry
cleaning establishments. Environ Res 53: 90-99.
Gutrtci Mi i \ bareei J \ (1979). Health Hazard Evaluation Determination Report No. HHE-78-95-596.
Jonas Brothers Taxidermy Co., Denver, Colorado (pp. 78-95). (NIOSH/00091563). Gunter, BJ;
Lybarger, JA.
Gutrti bum. TW; London. M. (1984). Health Hazard Evaluation Report HETA 83-425-1500:
Westview Press. (HETA 83-425-1500). NIOSH.
https://www.cdc.eov/niosh/hhe/reports/pdfs/1983-0425-1500.pdf.
Guy ton t Uoean. KA; Scott. CS; Cooi-n v V i opyl' 1 r^iione. S: Makris. SL; Glenn.
B; Subramaniam. RP; Gwinn. MR; Dzubow. RC: Chiu. WA. (2014). Human health effects of
tetrachloroethylene: key findings and scientific issues. Environ Health Perspect 122: 325-334.
http://dx.doi.ore I _ 39/elin \ .'07359.
Hadkhale. K; Martinsen U Weiderpass. E; Kiaerheim. K; Sparen. P; Tryeevadottir. L; Lym >•' «
Pukkala. E. (2017). Occupational exposure to solvents and bladder cancer: A population-based
case control study in Nordic countries. Int J Cancer 140: 1736-1746.
http://dx.doi.ore/10.1002/iic.30593.
Hake. CL; Stew; (1977). Human exposure to tetrachloroethylene: Inhalation and skin contact.
Environ Health Perspect 21: 231-238.
Hanley. KW. (1993). Health hazard evaluation report no. HETA 91-004-23 16, Daubert Coated Products,
Inc., Dixon, Illinois. (HETA 91-004-2316). Cincinnati, OH: National Institute for Occupational
Safety and Health.
Hansch. C; Leo. A; Hoekman. D. (1995). Exploring QSAR: Hydrophobic, electronic, and steric
constants. In C Hansch; A Leo; DH Hoekman (Eds.), ACS Professional Reference Book.
Washington, DC: American Chemical Society.
Heavner. PL; Morean. WT; Oeden. MW. (1995). Petermination of volatile organic compounds and
ETS apportionment in 49 homes. Environ Int 21: 3-21. http://dx.doio: /0160-
(94)00018-3.
Heck. JE; Park. AS; Pit* 1 v ockburn. M; Rit K (2013). An exploratory study of ambient air toxics
exposure in pregnancy and the risk of neuroblastoma in offspring. Environ Res 127: 1-6.
http://dx.doi.ore 10 101 i .envres. JO I '< 0*" 00 J.
Heinema ^ ^ co. P; Gomez. MR; Dosemeci. M; Stew\in " \ Hayes. RB; Zahm. SH; Thomas. TL;
Blair. A. (1994). Occupational exposure to chlorinated aliphatic hydrocarbons and risk of
astrocytic brain cancer. Am J Ind Med 26: 155-169. http://dx.doi.ore/10.1002/aiim.4700260203.
Hervin. RL; Strom an. R; Bel anger. P; Ruhe. R; Collins, v * \ ;hes. T. (1977). Health Hazard Evaluation
Petermination, Report No. HHE-77-63-449, McPonnell Aircraft Company, St. Louis, Missouri
(pp. 77-63). (NIOSH/00076128). Hervin, RL; Stroman, R; Belanger, P; Ruhe, R; Collins, C;
Pyches, T.
Hickman (2000). Kirk-Othmer Encyclopedia of Chemical Technology
Tetrachloroethylene. New York, NY: John Wiley & Sons.
http://dx.doi.orE >47123 8961.2005201808090311 ,a01.
Page 550 of 636
-------
13790
13791
13792
13793
13794
13795
13796
13797
13798
13799
13800
13801
13802
13803
13804
13805
13806
13807
13808
13809
13810
13811
13812
13813
13814
13815
13816
13817
13818
13819
13820
13821
13822
13823
13824
13825
13826
13827
13828
13829
13830
13831
13832
13833
13834
13835
13836
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Hollister. TA; Parkt fish. PR. (1968). Acute and chronic toxicity of five chemicals to
mysid shrimp (Mysidopsis bahia) (pp. 15). (Published in Part as 4809, 5184, 5590, 9607, 10366,
83162, 83925). Pensacola, FL: EG&G Bionomics, Marine Research Lab.
Holmes. L. (2017). Comment submitted by Laurie Holmes, Senior Director, Environmental Policy,
Motor & Equipment Manufacturers Association (MEMA).
https://www.reeiilations.eov/documeiii * < PA-HQ-Ol < I .*-«! ,3-0017.
Home. ID; Swirskv. MA; Hollister. TA; Obk. >
-------
13837
13838
13839
13840
13841
13842
13843
13844
13845
13846
13847
13848
13849
13850
13851
13852
13853
13854
13855
13856
13857
13858
13859
13860
13861
13862
13863
13864
13865
13866
13867
13868
13869
13870
13871
13872
13873
13874
13875
13876
13877
13878
13879
13880
13881
13882
13883
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Jonker. D; W outer sen. J ron. VI. (1996). Toxicity of mixtures of nephrotoxi cants with similar or
dissimilar mode of action. Food Chem Toxicol 34: 1075-1082. http://dx.doi.ore/ )/S0278-
6915(97)00077-X.
Kalkbrenner. AE; Daniels. XL; Chen. JC: Poole. C; Emch. M; Morrissev. J. (2010). Perinatal exposure to
hazardous air pollutants and autism spectrum disorders at age 8. Epidemiology 21: 631-641.
http://dx.doi.ore 10 10" rniLObm sm J6.
Kaneesbi leesbere. E. (2011). Handbook for critical cleaning, cleaning agents and systems
(2nd ed.). Boca Raton, FL: CRC Press.
Kasti iller. MA. (2006). Kinetics of finite dose absorption through skin 2: Volatile
compounds. J Pharm Sci 95: 268-280. http://dx.doij >s.20497.
Kawasaki. M. (1980). Experiences with the test scheme under the chemical control law of Japan: An
approach to structure-activity correlations. Ecotoxicol Environ Saf 4: 444-454.
http://dx.doi.ore 10 101 Oil -1 '<>80)^00 kv\>.
Kawauchi. T; Nishiyama. K. (1989). Residual tetrachloroethy 1 ene in dry-cleaned clothes. Environ Res
48: 296-301.
Kido. T; Sueaya. C; Ikeuchi. R; Kudo \ IHrooda. M \i awa. Y. (2013). The Increases in mRNA
Expressions of Inflammatory Cytokines by Adding Cleaning Solvent or Tetrachl oroethy 1 ene in
the Murine Macrophage Cell Line J774.1 Evaluated by Real-time PCR. Ind Health 51: 319-325.
Kiursl > iHn' hi Uv >c. VS: Kovacevic. IM; Aksentiievic. SM. (2016). The temporal variation of
indoor pollutants in photocopying shop. Stoch Environ Res Risk Assess 30: 1289-1300.
http://dx.doi.orE
Kiellstrand. P; Holmqun r% tCanie. M; Aim. P; Romare. S: Jonsson. I; Mansson 3 . Hjcil-omo. M.
(1984). Perchloroethylene: Effects on body and organ weights and plasma butyrylcholinesterase
activity in mice. Acta Pharmacol Toxicol 54: 414-424. http://dx.doi.oi :
0773.1984.tb01951.x.
Kowalsk erczak. T. (2013). Qualitative and quantitative analyses of the halogenated volatile
organic compounds emitted from the office equipment items. Indoor Built Environ 22: 920-931.
http://dx.doi.orE )326X12458299.
Krock. R. (2017a). Comment submitted by Richard Krock, Vice President, Regulatory and Technical
Affairs, The Vinyl Institute (VI) [Comment], https://www.regulations.gov/document?D=EPA-
HO-OPP '36-0063.
Krock. R. (2017b). Comment submitted by Richard Krock, Vice President, Regulatory and Technical
Affairs, The Vinyl Institute (VI), Part 2 [Comment],
https://www.reeiilations.eov/documeiii * i ,PA-HQ-Q]T 1 _0l 0 '3-0027.
Kilcilk. M; Korkmaz. Y. (2012). The effect of physical parameters on sound absorption properties of
natural fiber mixed nonwoven composites. Text Res J 82: 2043-2053.
http://dx.doi.ore 10 I I 00 10-1 M_nrs7.
Kyyronen. P; Taskinen. H; Lindbohm. ML; Hemminki. K; Heinonen. OP. (1989). Spontaneous
abortions and congenital malformations among women exposed to tetrachloroethylene in dry
cleaning. J Epidemiol Community Health 43: 346-351. http://dx.doi.oi ^ 10 I l'< /iecli I '< I 346.
Labra. M; Mattia I', Hernasconi. M; Bertaccln i* t '¦•¦¦¦¦[ i < iitcrio, S. (2010). The Combined
Toxic and Genotoxic Effects of Chromium and Volatile Organic Contaminants to
Pseudokirchneriella subcapitata. Water Air Soil Pollut 213: 57-70.
http://dx.doi.orE 67-3.
Lace> i\ it \iiabrant. DH; Lai>^ if diesis' Mayes. MP; Cooper. BC: Schottenfel* f
(1999). Petroleum distillate solvents as risk factors for undifferentiated connective tissue disease
(UCTP). Am J Epidemiol 149: 761-770.
Page 552 of 636
-------
13884
13885
13886
13887
13888
13889
13890
13891
13892
13893
13894
13895
13896
13897
13898
13899
13900
13901
13902
13903
13904
13905
13906
13907
13908
13909
13910
13911
13912
13913
13914
13915
13916
13917
13918
13919
13920
13921
13922
13923
13924
13925
13926
13927
13928
13929
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Lange. NA; Pea (1985). Lange's handbook of chemistry (13th ed.). New York, NY: McGraw-Hill.
Lash. LH; Qian. W; Putt. DA; Hueni. SE; Elfarra. AA; Sicuri. AR; Parker. JC. (2002). Renal toxicity of
perchloroethylene and S-(l,2,2-trichlorovinyl)glutathione in rats and mice: sex- and species-
dependent differences. Toxicol Appl Pharmacol 179: 163-171.
http://dx.doi.ore 36/taap. 2001.9358.
Lehmann L i lioelke. A; Rehwagen. M; Rolle-Kampczyk. II; Schlink. II; Schulz. R; Borte. \ 1. Oiez. U;
Herbarth. O. (2002). The influence of maternal exposure to volatile organic compounds on the
cytokine secretion profile of neonatal T cells. Environ Toxicol 17: 203-210.
http://dx.doi.ore ox. 10055.
Lewis. RJ. Sr. (2007). Hawley's condensed chemical dictionary (15th ed.). Hob ok en, NJ: John Wiley &
Sons. http://dx.doi.org/i0J002/978Q470114735.
Lewis. RJ. Sr. (1992). Sax's dangerous properties of industrial materials: v III (8th ed.). New York, NY:
Van Nostrand Reinhold.
Lide. DR. (2007). CRC handbook of chemistry and physics: A ready-reference book of chemical and
physical data. In DR Lide (Ed.), (88th ed.). Boca Raton, FL: CRC Press.
Lindstrom. AB; Proffitl rtune. CR. (1995). Effects of modified residential construction on indoor
air quality. Indoor Air 5: 258-269. http://dx.doi.oi ^ 10 I I I I | I 00-06 s 00005.x.
Lipworth. L; Son derm an. IS; Mum ma. MT; Tar one. RE; Marano. DE: Boice. ID; McLaughlin. IK.
(2011). Cancer mortality among aircraft manufacturing workers: An extended follow-up. J
Occup Environ Med 53: 992-1007. http://dx.doi. >7/JQM.0b013e31822e0940.
Long. JL; Stensi guson. JF; Strand. SE; Ongerth. IE. (1993). Anaerobic and aerobic treatment
of chlorinated aliphatic compounds. J Environ Eng 119: 300-320.
http://dx.doi. org/10.1061/f A.SCE)0733-9372 :2(300Y
Love. JR. (1982). Health hazard evaluation report no. HETA 81-310-1039, King-Smith Printing
Company, Detroit, Michigan. (HETA 81-310-1039). Cincinnati, OH: National Institute for
Occupational Safety and Health.
Luca; arve ;cas. jioc 'apellmann. P; Nicolas. A; Bodenes. A; Jegadei (2015).
Assessment of exposure to perchloroethylene and its clinical repercussions for 50 dry-cleaning
employees. J Occup Environ Hyg 12: 767-773.
http://dx.doi.org 10 1080/15459624.201 •> 10 l\'46.
Luo. Y; Cichoclu <\ i>oh. N; Lewi 1 s. \ < lireadgill. DW; Chiu. WA; Rusyn. I. (2019).
Using collaborative cross mouse population to fill data gaps in risk assessment: a case study of
population-based analysis of toxicokinetics and kidney toxicodynamics of tetrachloroethylene.
Environ Health Perspect 127: 067011. http://dx.doi.org/ 9/EHP5105.
Luo. YS; Cichocki. J A; McDonald. TJ; Rusv (2017). Simultaneous detection of the
tetrachloroethylene metabolites S-(l,2,2-trichlorovinyl) glutathione, S-(l,2,2-trichlorovinyl)-L-
cysteine, and N-acetyl-S-(l,2,2-trichlorovinyl)-L-cysteine in multiple mouse tissues via ultra-
high performance liquid chromatography electrospray ionization tandem mass spectrometry. J
Toxicol Environ Health A 80: 513-524. http://dx.doi.org/10.1080/15287394.^
Luo. YS; Furuva. S; Soldatov. VY; Kosvk. O; Yoo. HS; Fukushima. H; Lewr 1 \ Kusvn. I.
(2018a). Metabolism and Toxicity of Trichloroethylene and Tetrachloroethylene in Cytochrome
P450 2E1 Knockout and Humanized Transgenic Mice. Toxicol Sci 164: 489-500.
http://dx.doi.ore oxsci/kfvQ99.
Luo. Yu; Hsieh. N; Sol date liu. WA; Rusyn. I. (2018b). Comparative analysis of metabolism
of trichloroethylene and tetrachloroethylene among mouse tissues and strains. Toxicology 409:
33-43. hJH;
-------
13930
13931
13932
13933
13934
13935
13936
13937
13938
13939
13940
13941
13942
13943
13944
13945
13946
13947
13948
13949
13950
13951
13952
13953
13954
13955
13956
13957
13958
13959
13960
13961
13962
13963
13964
13965
13966
13967
13968
13969
13970
13971
13972
13973
13974
13975
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Malonev. EK; Waxmar (1999). trans-Activation of PPARalpha and PPARgamma by structurally
diverse environmental chemicals. Toxicol Appl Pharmacol 161: 209-218.
http://dx.doi.ors 36/taap. 1999.8809.
Marano. DE; Boi»v it , I'rvzek. IP; Morrison i \ Sadler. CI; McLaughlin. IK. (2000). Exposure
assessment for a large epidemiological study of aircraft manufacturing workers. Appl Occup
Environ Hyg 15: 644-656.
http://dx.doi.org/10.1080/10473220050075653. https://heronet.epa.eov/heronet/mdex.cfm7acti on
=search.view&reference id=5098227Marqu iken. R; Goede. H; Fransman. W;
Schinkel. J. (2017). Validation of the dermal exposure model in ECETOC TRA. Ann Work Expo
Health 61: 854-871. http://dx.doi.' 3/annweh/wxx059.
Matte> t uida. F; Matrat. M; Cenee v 1 u I* v anchez. M; Radoi. L; Menviell-' ^ U'llouli. F;
Carton. M; Bara. S: Marrei J , 1 uce. D: Stucker. I. (2014). Exposure to chlorinated solvents and
lung cancer: Results of the ICARE study. Occup Environ Med 71: 681-689.
http://dx.doi.org 10 I l'< oemed-201 I iOJ 182.
Mattsson < Uhee. RR; Yano. BL; Bi . d \ < v i^ancer 111 (1998). Neurotoxicologic examination of
rats exposed to 1,1,2,2-tetrachloroethylene (perchloroethylene) vapor for 13 weeks. Neurotoxicol
Teratol 20: 83-98.
McCormick. L. (2017). Comment submitted by Lindsay McCormick, Chemicals and Health Project
Manager on behalf of Environmental Defense Fund (EDF) [Comment],
https://www.regulations.gov/document?D=EPA~HQ~QPPT~2016-0723-0021.
Moody. PL; Kramkowski. R; Kevserling. M. (1983). Health Hazard Evaulation Report HETA 81-409-
1290: The Donaldson Company, Inc. (HETA 81-409-1290). NIOSH.
https://www.cdc.gov/niosh/hhe/reports/pdfs/81-409-
1290.pdi 3.
Moral es - Suarez-Varela. MM, UUen. J; Villeneuve. S; Johansen. P; Kaerlev. L; Llopis-Gonzale \
Wingren n irdell. L; Ahrens. W; Stang. A; Meriktu i tnini. G; Aurrekoetxea. J J. rcvotte.
< t vr. D; Guen-'i P (2013). Occupational exposure to chlorinated and petroleum solvents and
mycosis fungoides. J Occup Environ Med 55: 924-931.
http://dx.doi.ors L0b013e3182941alc.
Morrison. RD; Murphy (2013). Chlorinated solvents: A forensic evaluation. Cambridge, UK: The
Royal Society of Chemistry.
Moseley. CL. (1980). Health hazard evaluation report no. HHE 79-42-685, Motion Picture Screen
Cartoonists, Local 841, New York, New York. (HHE 79-42-685). Cincinnati, OH: National
Institute for Occupational Safety and Health.
Mutti \ Uinovi. R; Bergamaschi « < 'iagitii ;izzini. S; Franchini I, 1 ;mwervs. RR; Bernard.
AM; Roels. H; Gelpi. E; Rosetto. J; Ram aylor. SA; de Broe. M; Nuyts. GD;
Stolte. H; Fels. LM; Herbc (1992). Nephropathies and exposure to perchloroethylene in
dry-cleaners. Lancet 330: 189-193. http://dx.doi.org/10.1016/0140-6736(92)90463-0.
N (2009). Tetrachloroethylene (CAS reg. no. 127-18-4): Interim acute exposure guideline
levels (AEGLs). (Interim 1 modified without modeling results) [AEGL], Washington, DC:
National Advisory Committee for Acute Exposure Guideline Levels.
https://www.epa. gov/sites/production/files/2014-
08/documents/tetrachloroethy 1 ene interim ornl dec2009c.pdf.
Nakai. IS; Stathopulos. PB; Campbell. GL; Chu. I; Li-Mull oin. R. (1999). Penetration of
chloroform, trichloroethylene, and tetrachloroethylene through human skin. J Toxicol Environ
Health A 58: 157-170. http://dx.doi.org/10.1080/009841Q99157368.
Page 554 of 636
-------
13976
13977
13978
13979
13980
13981
13982
13983
13984
13985
13986
13987
13988
13989
13990
13991
13992
13993
13994
13995
13996
13997
13998
13999
14000
14001
14002
14003
14004
14005
14006
14007
14008
14009
14010
14011
14012
14013
14014
14015
14016
14017
14018
14019
14020
14021
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Namkung. E; Rittmann. BE. (1987). Estimating Volatile Organic Compound Emissions from Publicly
Owned Treatment Works (pp. 670-678). (NIOSH/00172323). Namkung, E; Rittmann, BE.
NCI (1977). Bioassay of tetrachloroethylene for possible carcinogenicity. (NCI-CGTR-13; DHEW
Publication No. (NIH) 77-813). Bethesda, Md: National Institutes of Health.
http://ntp.niehs.nih.eov/ntp/htdocs/LT rpih jxtf.
Net so (i
-------
14022
14023
14024
14025
14026
14027
14028
14029
14030
14031
14032
14033
14034
14035
14036
14037
14038
14039
14040
14041
14042
14043
14044
14045
14046
14047
14048
14049
14050
14051
14052
14053
14054
14055
14056
14057
14058
14059
14060
14061
14062
14063
14064
14065
14066
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
NIQSH. (2002c). In-depth survey report: control of perchloroethylene (PCE) in vapor degreasing
operations, site #4. (EPHB 256-18b). Cincinnati, Ohio: National Institute for Occupational
Safety and Health (NIOSH).
NIQSH. (2002d). In-depth survey report: Control of perchloroethylene exposure (PCE) in vapor
degreasing operations, site #3. (EPHB 256-17b). CDC.
https://www.cdc.eov/niosh/siirveyreports/pdfs/ECTB-2
NIQSH. (2005). NIOSH pocket guide to chemical hazards & other databases CD-ROM. (DHHS-2005-
151). Cincinnati, OH.
NRC. (2010). Review of the Environmental Protection Agency's draft IRIS assessment of
tetrachloroethylene. Washington, DC: National Academies Press.
NTP. (1986a). Toxicology and carcinogenesis studies of tetrachloroethy 1 ene (perchloroethy 1 ene) (CAS
No. 127-18-4) in F344 rats and B6C3F1 mice (inhalation studies). (NTP TR 311). Research
Triangle Park, NC: U.S. Department of Health and Human Services.
http://ntp.niehs.nih.eov/ntp/htdocs/LT rpts/t If.
NTP. (1986b). Toxicology and carcinogenesis studies of tetrachl oroethy 1 ene (perchl oroethy 1 en e) (CAS
no. 127-18-4) in F344/N rats and B6C3F1 mice (inhalation studies). (NTP TR 311). Research
Triangle Park, NC: U.S. Department of Health and Human Services, National Toxicology
Program, http://ntp.niehs.nih.gov/ntp/htdocs/< I t <'ti tt > I I pi If.
NTP. (2014). 13th Report on carcinogens [NTP], Research Triangle Park, NC: U.S. Department of
Health and Human Services, Public Health Service.
Nwqmc. (2017). Water quality portal. https://www.waterqualitydata.iis/.
Odum J, utccii, I' I ester. JR; Hext. PM. (1988). The role of trichloroacetic acid and peroxisome
proliferation in the differences in carcinogenicity of perchloroethylene in the mouse and rat.
Toxicol Appl Pharmacol 92: 103-112. http://dx.doijnv io to t <\)4i-008X(88)90232-3.
QECD. (201 1). Emission scenario document on the use of metalworking fluids. (JT03304938).
Organization for Economic Cooperation and Development.
QECD. (2015). Emission scenario document on use of adhesives. In Series on Emission Scenario
Documents No 34. (Number 34). Paris, France.
http://www.oecd. ore/officialdocuments/publicdisplaydocumentpdf/?cote=ENV/JM/MQNQ(2015
)4& docl an guage=en.
QECD. (2017a). Draft ESD on Vapor Degreasing - Internal EPA document. Organization for Economic
Co-operation and Development (OECD).
QECD. (2017b). Emission Scenario Document (ESD) on the use of textile dyes.
http://www.oecd.org/chemicalsafetv/risk-assessment/emissionscenariodocuments.htm.
OEHHA. (2001). Public health goal for tetrachloroethylene in drinking water. Sacramento, CA.
https://oehha.ca.eov/media/downloads/water/chemicals/phe/pceaue20 df.
OEHHA. (2016). Air Toxics Hot Spots Program: Perchloroethylene Inhalation Cancer Unit Risk Factor.
https://oehha.ca.eov/media/downloads/cmr/pceurf090816.pdf.
Olsen. J: Hemminki. K; Ahlbo kedal. T; Kyyronen. P; Taskinen. H; Lindbohm. ML;
Heinonen. OP; Brandt L; Kolstad. H; Halvorser naes. J. (1990). Low birthweight,
congenital malformations, and spontaneous abortions among dry-cleaning workers in
Scandinavia. Scand J Work Environ Health 16: 163-168.
Orris. P; Daniels. W. (1981). Health Hazard Evaluation Report 80-201-816: Peterson/Puritan Company.
(HE 80-201-816). NIOSH. https://www.cdc.eov/niosh/hhe/reports/pdfs/80-201-
x I !':< K 'id= 10.26616/NIQSHHBE802ol 8 i 6.
Page 556 of 636
-------
14067
14068
14069
14070
14071
14072
14073
14074
14075
14076
14077
14078
14079
14080
14081
14082
14083
14084
14085
14086
14087
14088
14089
14090
14091
14092
14093
14094
14095
14096
14097
14098
14099
14100
14101
14102
14103
14104
14105
14106
14107
14108
14109
14110
14111
14112
14113
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
OSH.A. (2005). Reducing worker exposure to perchloroethylene (PERC) in dry cleaning. (OSHA 3253-
05N). Washington, DC: U.S. Department of Labor, Occupational Safety & Health
Administration, https://www.osha.gov/dsg/guidance/perc.html.
OSHA.. (2017). Chemical Exposure Health Data (CEHD) provided by OSHA to EPA. U.S. Occupational
Safety and Health Administration.
Oshiro. WM; Krantz. QT; Bushne (2008). Characterization of the effects of inhaled
perchloroethylene on sustained attention in rats performing a visual signal detection task.
Neurotoxicol Teratol 30: 167-174. http://dx.doi.tnv 10 101 | ntt.2008 01 002.
Park. JH; Spengler. ID; Yoon. DW; Dumyah avnak. H. (1998). Measurement of air
exchange rate of stationary vehicles and estimation of in-vehicle exposure. J Expo Anal Environ
Epidemiol 8: 65-78.
Paulu. C; Aschengrau. A: Ozonoff. D. (1999). Tetrachloroethylene-contaminated drinking water in
Massachusetts and the risk of colon-rectum, lung, and other cancers. Environ Health Perspect
107: 265-271.
Philip. BK; Mumtaz. MM; Latendresse. JR; Mehenc vl (2007). Impact of repeated exposure on
toxicity of perchloroethylene in Swiss Webster mice. Toxicology 232: 1-14.
http://dx.doi.ore 10 101 i.tox.200 I _ « I *
Preidis. GA; Kim. KH; Moore. DP. (2017). Nutrient-sensing nuclear receptors PPARa and FXR control
liver energy balance [Review], J Clin Invest 127: 1193-1201.
http://dx.doi.orE 8893.
Products. AC. (2017). Maskants and their use in aerospace: Regulatory compliance of the industry.
(EPA-HQ-OPPT-2016-0732-0077). Washington, D.C.: AC Products.
https://www.regulations.gov/document?D=EPA-HQ-Q]
Pukkala. E; Martinsen. J; Lynge. E; Gunnarsdottir. H; Sparen. ~ :gvadottir. L; Weiderpass. E;
Kiaerheim. K. (2009). Occupation and cancer - follow-up of 15 million people in five Nordic
countries. Acta Oncol 48: 646-790. http://dx.doi.ore 30/02841860902913546.
Purdue. MP; Stewaii I u^sem. MC; Colt. JS; Locke. SI; Hein. Ml; Water \P, ^aubaixl HI.
EX* r t Kuterbuscb f v irwMn 1 liow. WH; Rothman. N; Hofmann. IN. (2017).
Occupational exposure to chlorinated solvents and kidney cancer: A case-control study. Occup
Environ Med 74: 268-274. http://dx.doi.org/)0 I I '< )/oemet! .01 10 «849.
Radican. L; Blaii \ * tewart. P; Wartenb-nv 1} (2008). Mortality of aircraft maintenance workers
exposed to trichloroethylene and other hydrocarbons and chemicals: Extended follow-up. J
Occup Environ Med 50: 1306-1319. http://dx.doi.org/10.1097/JQM.01
Ramdhan. PH.; Kamijima. M; Wai^ < ? [to. Y; Naito. H; Yanagiba. Y; Hayashi. N < juaka. N;
Aoyama. nzalez. FJ; Nakaiima. T. (2010). Differential response to trichloroethylene-
induced hepatosteatosis in wild-type and PPARalpha-humanized mice. Environ Health Perspect
118: 1557-1563. http://dx.doi.. 9/ehp. 1001928.
Richt ;rson. SF; Kleiner. CF. (1983). Acute and chronic toxicity of some chlorinated benzenes,
chlorinated ethanes, and tetrachloroethylene to Daphnia magna. Arch Environ Contam Toxicol
12: 679-684. http://dx.dou
Riddi nger. WB; Sakano. TK. (1985). Techniques of chemistry. Fourth edition. Organic
solvents. New York, NY: John Wiley and Sons.
Riegle. L. (2017). Comment submitted by Leslie Riegle, Director, Environmental Policy, Aerospace
Industries Association (AIA) [Comment], https://www.regulations.gov/document?D=EPA-HQ-
)011.
Roberts. A.L; Lyall. K; Hart. JE; Laden. F; Just. AC; Bobb. JF; Koenen. KC; Ascherio. A; Weisskopf.
MG. (2013). Perinatal air pollutant exposures and autism spectrum disorder in the children of
Page 557 of 636
-------
14114
14115
14116
14117
14118
14119
14120
14121
14122
14123
14124
14125
14126
14127
14128
14129
14130
14131
14132
14133
14134
14135
14136
14137
14138
14139
14140
14141
14142
14143
14144
14145
14146
14147
14148
14149
14150
14151
14152
14153
14154
14155
14156
14157
14158
14159
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Nurses' Health Study II participants. Environ Health Perspect 121: 978-984.
http://dx.doi.ore I _ 39/elin 1.06187.
Roda. C; Kousignian i ampin! \ Vlomas. 1. (2013). Indoor tetrachloroethylene levels and
determinants in Paris dwellings. Environ Res 120: 1-6.
http://dx.doi.ore 10 101 i.envres.2012.09.005.
Rowe. VK; McCollister. DP; Spencer. HC: Adams. EM; Irish. DP. (1952). Vapor toxicity of
tetrachloroethylene for laboratory animals and human subjects. Arch Environ Occup Health 5:
566-579.
Ruck: >ve. FJ; Maslia. M. (2013). Evaluation of exposure to contaminated drinking water and
specific birth defects and childhood cancers at Marine Corps Base Camp Lejeune, North
Carolina: A case-control study. Environ Health 12: 104. http://dx.doij 6/1476-069X-
12-104.
Ruckjh P rsnve. FJ; Shanb \ ^ Maslia. M. (2015). Evaluation of contaminated drinking water
and male breast cancer at Marine Corps Base Camp Lejeune, North Carolina: A case-control
study. Environ Health 14: 74. http://dx.doi.org/10.1 186/sl2" 10 01 00 I I
Ruder. AM; Yiin. JH; Waters. MA; Carreon. T; Hein. Ml; Butl :rt. GM; Pavis-King. KE;
Schulte. PA; Mandel. IS; Morton. RT. Rcdim Kt^enman. KD; Stew; in P \ I'lain Cancer
Collaborative Study. G. (2013). The Upper Midwest Health Study: Gliomas and occupational
exposure to chlorinated solvents. Occup Environ Med 70: 73-80.
http://dx.doi.ore >emed-2011-100588.
Rudnick. M. (2017a). Comment submitted by Michelle Rudnick, Senior Manager Regulatory Affairs,
CRC Industries, Inc [Comment], https://www.regutations.gov/document?P=EPA-H'
Rudnick. M. (2017b). Comment submitted by Michelle Rudnick, Senior Manager Regulatory Affairs,
CRC Industries, Inc., Part 2 [Comment], https://www.regulations.gov/document?P=EPA-HQ-
QPPT-2016-0743-0025.
Ruhe. R.L. (1982). Health hazard evaluation report no. HETA 82-040-1 19, Synthes Ltd. (USA),
Monument, Colorado. (HETA 82-040-119). Cincinnati, OH: National Institute for Occupational
Safety and Health.
Ruhe. R.L. (1983). Health Hazard Evaluation Report No. HETA-83-266-1391, McCourt Label
Company, Bradford, Pennsylvania (pp. 83-266). (NIOSH/00137711). Ruhe, RL.
Ryan. TJ; Hart. EM; Kappler. IX. (2002). VOC exposures in a mixed-use university art building. A1HA
J 63: 703-708. http://dx.doi.org/10.1202/0002-8894f2002)063<0703:VEIAMU>2.0.CQ:2.
Sanchez-Fortun. S; Sanz. F; Santa-Maria. A; Ros. If arte. ML; Encinas. MT; Vinagre. E;
Barahona. MV. (1997). Acute sensitivity of three age classes of Artemia salina larvae to seven
chlorinated solvents. Bull Environ Contam Toxicol 59: 445-451.
http://dx.doi.org/10.1007/sQ01289900498.
Sass. J. (2017). Comment submitted by Jennifer Sass, Ph.P., Senior Scientist, Natural Resources
Pefense Council (NRPC) [Comment], https://www.regulations.gov/documen t'?D=EPA-HQ-
QPPT-2016-073 7-0020.
S^v v x rennet! DH, Ciiillrud. SN; Kinney. PL; Spengler JH (2004). Pifferences in source emission
rates of volatile organic compounds in inner-city residences of New York City and Los Angeles.
J Expo Anal Environ Epidemiol 14: S95-109. http://dx.doi. 8/si.iea.7500364.
Scher. (2008). Scientific opinion on the risk assessment report on tetrachloroethylene (CAS no. 127-18-
4; EINECS no. 204-825-9). Human health part. European Union.
https://ec.eiiropa.eu/health/archive/ph risk/committees/04 scher/docs/scher o 088.pdf.
Page 558 of 636
-------
14160
14161
14162
14163
14164
14165
14166
14167
14168
14169
14170
14171
14172
14173
14174
14175
14176
14177
14178
14179
14180
14181
14182
14183
14184
14185
14186
14187
14188
14189
14190
14191
14192
14193
14194
14195
14196
14197
14198
14199
14200
14201
14202
14203
14204
14205
14206
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Schreiber. IS; Hudnell. HK; Geller. AM; House. DE; Aldous. KM; Force. MS; Langguth. K; Prohonic.
arker. JC. (2002). Apartment residents' and day care workers' exposures to
tetrachloroethylene and deficits in visual contrast sensitivity. Environ Health Perspect 110: 655-
664.
Scriven. EFV; Murugan. R (2005). Pyridine and Pyridine Derivatives.
http://dx.doi.ora 10 100: 0471238961.1625180919031809.,101 |':iib2.
Seeber. A. (1989). Neurobehavioral toxicity of long-term exposure to tetrachloroethylene. Neurotoxicol
Teratol 11: 579-583. http://dx.doi.org, 892-0362(89)90041-X.
Seidlei \ Mohner. M; Berger. J; Mester. B; Deeg. E; Elsn^n ls ^ners. A; Becker. N. (2007). Solvent
exposure and malignant lymphoma: A population-based case-control study in Germany. J Occup
Med Toxicol 2: 2. http://dx.doi.org/iO. i 186/1745-6673-2-2.
Selde )org. G. (201 1). Cancer morbidity in Swedish dry-cleaners and laundry workers:
Historically prospective cohort study. Int Arch Occup Environ Health 84: 435-443.
http://dx.doi.org 00420-010-0582-7.
Seo. M; Kobavashi. R; Okamura. T; Ikeda. K; Sat oh. M; Inagaki. N; Nagai. H; Nagase. H. (2012).
Enhancing effects of trichloroethylene and tetrachloroethylene on type I allergic responses in
mice [Letter], J Toxicol Sci 37: 439-445. http://dx.doi.oi ^ 10 _ l'< I/its. '< I
Sexton. K; Adgate. JL; Church. TR; Ashln 'x oedham. LL; Ramachandr o Irickson \<
Ryan (2005). Children's exposure to volatile organic compounds as determined by
longitudinal measurements in blood. Environ Health Perspect 113: 342-349.
http://dx.doi.Org/10.1289/e
Sexton. K; Mongin. SI; Ad ?; Ramachandran. G; Stock. TH; Morandi. MT. (2007).
Estimating volatile organic compound concentrations in selected microenvironments using time-
activity and personal exposure data. J Toxicol Environ Health A 70: 465-476.
http://dx.doi.org 10/15287390600870858.
Sherlach. KS; Gorki i \P Damtzlei \ Koepe. PP. (2011). Quantification of perchloroethylene residues
in dry-cleaned fabrics. Environ Toxicol Chem 30: 2481-2487. http://dx.doi.org/10.1002/etc.665.
Siemiatvcki. J. (1991). Risk factors for cancer in the workplace. In J Siemiatycki (Ed.). Boca Raton, FL:
CRC Press.
Silver. SR.; Pinkerton. LE; Fleming U\ Jones. JH, Mice S, I uo. L; Bertke. SJ. (2014). Retrospective
cohort study of a microelectronics and business machine facility. Am J Ind Med 57: 412-424.
http://dx.doi.org/10.1002/aiim.22288.
Singh. HB; Sal a; tiles. RE. (1983). Selected man-made halogenated chemicals in the air and
oceanic environment. J Geophys Res 88: 3675-3683.
Smitl- rath. A; Mallard. C; Pit. D; Smith. K; Sutton. J A; Vukmanich. J; McCartv. LS; Ozburn.
GW. (1991). The acute and chronic toxicity of 10 chlorinated organic-compounds to the
american flagfish (jordanella-floridae). Arch Environ Contam Toxicol 20: 94-102.
Snedecor. G; Hickman. JC; Mertens. JA. (2004). Chloroethylenes and chloroethanes.
Spirit Aero Systems. 1. (2017). Perchloroethylene usage at Spirit AeroSystems, Inc. (EPA-HQ-OPPT-
2016-0732-0077). Washington, D.C.: Spirit AeroSystems Inc.
https://www.regulations.gov/document'?D=EPA-HQ-OPPT-2Q 16-0732-0077.
Stefaniak -sse. FN; Murray. MPM; Rooney. BC; Schaefer. J. (2000). An evaluation of
employee exposure to volatile organic compounds in three photocopy centers. Environ Res 83:
162-173. http://dx.doi.org/* 3/enrs.2000.4061.
Stephen Si ;ht. WN. (1986). Health Hazard Evaluation Report No. HETA-85-482-86-1 16-
1730, Winters Industry Foundry, Canton, Ohio (pp. 85-482). (NIOSH/00166571). Stephenson,
RL; Albrecht, WN.
Page 559 of 636
-------
14207
14208
14209
14210
14211
14212
14213
14214
14215
14216
14217
14218
14219
14220
14221
14222
14223
14224
14225
14226
14227
14228
14229
14230
14231
14232
14233
14234
14235
14236
14237
14238
14239
14240
14241
14242
14243
14244
14245
14246
14247
14248
14249
14250
14251
14252
14253
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Stingone. J A; McVeigh. KH; CI audio. L. (2016). Association between prenatal exposure to ambient
diesel particulate matter and perchloroethylene with children's 3rd grade standardized test scores.
Environ Res 148: 144-153. http://dx.doi.Hv 10 10 l6/i.envres.2Q I 0 '< 0 '< ^
Stove. D. (2000). Ulmann's Encyclopedia of Industry Chemistry
Solvents, [online]: John Wiley & Sons.
Si vlukherjee. B; Batterman. S. (2013). Determinants of personal, indoor and outdoor VOC
concentrations: An analysis of the RIOPA data. Environ Res 126: 192-203.
http: //dx. doi. or e/10.1016/i. envres. 8.005.
Tabak. HH; Qua ashni. CI: Barth. EF. (1981). Biodegradability studies with organic priority
pollutant compounds. J Water Pollut Control Fed 53: 1503-1518.
Takakura. K: Oikawa. T: Nakano. M: Sac su. Y: Kaiihara. M: Samta. M. (2019). Recent
insights into the multiple pathways driving non-alcoholic steatohepatitis-derived hepatocellular
carcinoma [Review], Front Oncol 9: 762. http://dx.doi.Org/10.3389/fonc.2
Talbott. EO: Marshall. LP: Raeer. JR: Arena. VC: Sharma. RK: Stacy. SL. (2015). Air toxics and the
risk of autism spectrum disorder: The results of a population based case-control study in
southwestern Pennsylvania. Environ Health 14: 80. http://dx.doi.org/10.1 1 S6/sl2940~015-0064-
1.
Talibov. M: Lehtinen-Jacks. S: Martin sen. J I: Iviaerheim. K: Lynge. E: Sparen. P: Tryggvadottir. L:
Weiderpass. E: Kauppinen. T: Kyyronen. P: Pukkala. E. (2014). Occupational exposure to
solvents and acute myeloid leukemia: A population-based, case-control study in four Nordic
countries. Scand J Work Environ Health 40: 511-517. http://dx.doi.ori siweh.3436.
Tatman. S. (2017). Comment submitted by Stacy Tatman, MS, JD, Director, Environmental Affairs,
Alliance of Automobile Manufacturers (Alliance) [Comment],
https://www.regiilations.gov/dociimeiii * < .PA-HQ-Ol < I ,3-0010.
Tech Met. I. (2017). Tech Met letter to HSIA. (EPA-HQ-OPPT-2016-0732-0027). Washington, D.C.:
Tech Met Inc. https://www.regulations.gov/documein'"'0 liPA-HQ-OPPT-2016-0732-0027.
Thomas. KW: Pellizzari. ED: Perritt. RL: Nelson. WC. (1991). Effect of dry-cleaned clothes on
tetrachloroethylene levels in indoor air, personal air, and breath for residents of several New
Jersey homes. J Expo Anal Environ Epidemiol 1: 475-490.
Tichenor. BA: Sparks. LE: Jackson. M* * uo. Z: Mason. M \ Hunket. CM: Rasor. SA. (1990).
Emissions of perchloroethylene from dry cleaned fabrics. Atmos Environ 24: 1219-1229.
http://dx.doi.ore 10 101 0960-1686(90)900N I.
Tinston. DJ (1994). Perchloroethylene: A multigeneration inhalation study in the rat. (CTL/P/4097,
86950000190). Cheshire, UK: Zeneca Central Toxicology Laboratory.
https://www.epa.gov/iris/supporting-documents-tetrachloroethylene-perchloroethylene.
Tirsel (2000). Ulmann's Encyclopedia of Industry Chemistry Dry cleaning, [online]: John Wiley &
Sons.
Travi Roos. AJ: Plato. N: Moradi. T: BofFetta. P. (2002). Cancer incidence of dry
cleaning, laundry and ironing workers in Sweden. Scand J Work Environ Health 28: 341-348.
Tuckm 11 * Sorensen. KJ: Ruti^'i WI: McKernan < I' I cirestor (1 . Butler. MA. (2011). Cytogenetic
analysis of an exposed-referent study: perchloroethylene-exposed dry cleaners compared to
unexposed laundry workers. Environ Health 10: 16. http://dx.doi.oiv 10 I IV I I 0 °\ 10 I
tsus Bureau. (2015). Statistics of U.S. Businesses (SUSB).
https://www.census.gov/data/tables/2015/econ/susb/2015-susb-annual.html.
y. (2016). May 2016 Occupational Employment and Wage Estimates: National Industry-
ttpsv/heronet.epa
Page 560 of 636
-------
14254
14255
14256
14257
14258
14259
14260
14261
14262
14263
14264
14265
14266
14267
14268
14269
14270
14271
14272
14273
14274
14275
14276
14277
14278
14279
14280
14281
14282
14283
14284
14285
14286
14287
14288
14289
14290
14291
14292
14293
14294
14295
14296
14297
14298
14299
14300
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
&reference id= st Guard. (1984). The chemical hazards response information
system (CHRIS) hazardous chemical data. Washington, DC: Department of Transportation.
POD. (2017). Comment submitted by OASD (EI&E), ESOH Directorate, CMRM Program,
Department of Defense (DOD) Re: Tetrachloroethylene (perchloroethylene); TSCA Review and
Risk Evaluation, EPA-HQ-OPPT-2016-0732. (EPA-HQ-OPPT-2016-0732-0062).
https://www.regulations.gov/document'?D=EPA-HQ-Q] < I _ ^ l ^ _ < '062.
POD. O; Environmental Health Readiness System - Industrial. H. (2018). Email between DOD and
EPA: RE: [Non-DoD Source] Update: DoD exposure data for EPA risk evaluation - EPA request
for additional information [Personal Communication], Washington, D.C.: U.S. Department of
Defense.
(1980). Ambient water quality criteria for tetrachloroethylene [EPA Report], (EPA/440/5-
80/073). Office of Water, http://nepis.epa. gov/Exe/ZyPURL.cgi?Dockey=2000M4GG.txt.
(1985a). Health assessment document for tetrachloroethylene (perchloroethylene) Final
report [EPA Report], (EPA/600/8-82/005F). Research Triangle Park, NC: U.S. Environmental
Protection Agency, Office of Health and Environmental Assessment.
http://cfpub.epa. eov/ncea/cfm/recordisplay.cfm?deid=38082.
(1985b). Occupational exposure and environmental release assessment of
tetrachloroethylene. Office of Pesticides and Toxic Substances.
(1991). Dry cleaning facilities - Draft background information for proposed standards. (EPA
450/3-91-020a). Research Triangle Park,NC: U.S. Environmental Protection Agency, Office of
Air Quality Planning and Standards.
https://nepis.epa. gov/Exe/ZyPDF.cgi/00002H9E.PDF?Dockey=00002H9E.PDF.
(1994a). Fabric finishing - generic scenario for estimating occupational exposures and
environmental releases -final.
(1994b). Guidelines for Statistical Analysis of Occupational Exposure Data: Final. United
States Environmental Protection Agency :: U.S. EPA.
(1994c). Methods for derivation of inhalation reference concentrations and application of
inhalation dosimetry [EPA Report], (EPA/600/8-90/066F). Research Triangle Park, NC: U.S.
Environmental Protection Agency, Office of Research and Development, Office of Health and
Environmental Assessment, Environmental Criteria and Assessment Office.
https://cfpub.epa.gov/ncea/risk/recordisplav.cfm?deid=71993<Ł 329&CFTOKEN=2
300b3 1 7.
1 c. i i1 \ (1995). Protocol for Equipment Leak Emission Estimates. (EPA-453/R-95-017). Research
Triangle Park, NC: Office of Air and Radiation, Office of Air Quality and Planning Standards.
https://www3.epa.eov/ttn/chief/efdocs/equiplks.pdf.
(1997). Solvent Cleaning. Volume III, Chapter 6. pp. 6.2.1. Washington, DC.
http://www3.epa.eov/ttnchiel/eiip/techreport/volume03/iii06fin.pdf.
(1998). Guidelines for ecological risk assessment [EPA Report], (EPA/630/R-95/002F).
Washington, DC: U.S. Environmental Protection Agency, Risk Assessment Forum.
https://www.epa.eov/risk/euidelines-ecoloeical-risk-assessment.
U.S. EPA. (2000). T etrachloroethylene (perchl oroethy 1 ene) 127-18-4 [Fact Sheet], Office of Air Toxics.
https://www.epa.eov/sites/prodiiction/files/2016-09/dociiments/tetrachloroethylene.pdf.
(2001). Sources, emission and exposure for trichloroethylene (TCE) and related chemicals
[EPA Report] (pp. 138). (EPA/600/R-00/099). Washington, DC.
https://cfpub.epa.gov/ncea/risk/recordisplav.cfm?deid=21006.
U.S. EPA. (2005a). Guidelines for Carcinogen Risk Assessment [EPA Report], (EPA/630/P-03/00IB).
Washington, DC: U.S. Environmental Protection Agency, Risk Assessment Forum.
Page 561 of 636
-------
14301
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https://www.epa.eov/sites/prodiiction/files/2013-09/dociiments/cancer guidelines final 3-25-
05.pdf.
U.S. EPA. (2005b). Perchloroethylene dry cleaners refined human health risk characterization.
https://www.epa.gov/sites/production/files/2015-06/docurnents/riskassessrnent dry cleaners.pdf.
(2006a). Economic impact analysis of the final perchloroethylene dry cleaning residual risk
standard. (EPA-HQ-OAR-2005-0155-0505). Research Triangle Park, NC: U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards, Health and Environmental
Impact Division. https://www.reeiilations.eov/dociiment?D=EPA-HQ-OAR-200v' 01"-^ 0^05.
U.S. EPA. (2006b). Economic impact analysis of the perchloroethylene dry cleaning residual risk
standard (pp. 1-19). (EPA 452/R-06-005). Research Triangle Park,NC: U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards, Health and Environmental
Impacts Division.
https://nepis.epa. eov/Exe/ZvPDF.cei/P100QFLJ.PDF?Dockev=P100(
U.S. EPA. (2009). INTERIM ACUTE EXPOSURE GUIDELINE LEVELS (AEGLs) -
Tetrachloroethylene. U.S. Environmental Protection Agency :: U.S. EPA.
https://www.epa.eov/aeel/tetrachloroethylene-resiilts-aeel-proeram.
U.S. EPA. (201 la). Exposure factors handbook: 201 1 edition [EPA Report], (EPA/600/R-090/052F).
Washington, DC. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=236252.
(2011b). Toxicological review of Trichloroacetic acid [EPA Report], (EPA/635/R-09/003F).
Washington, DC. http://www.epa.eov/iris/toxreviews/0655tr.pdf.
(2012a). Estimation Programs Interface Suite™ for Microsoft® Windows, v 4.11.
Washington, DC. https://www.epa.gov/tsca-screening-tools/epi-suitetm-estimation-program-
interface.
U.S. EPA. (2012b). Sustainable futures P2 framework manual [EPA Report], (EPA-748-B12-001).
Washington DC. http://www.epa.gov/sustainable-futures/sustainable-futures-p2-framework-
manual.
U.S. EPA. (2012c). Toxicological review of tetrachloroethylene (perchloroethylene). (EPA/63 5/R-
08/01 IF). Washington, DC. https://cfpub.epa.eov/ncea/iris/search/.
(2012d). Toxicological review of tetrachloroethylene (perchloroethylene) (CAS No. 127-18-
4) In support of summary information on the Integrated Risk Information System (IRIS) (pp.
1077).
U.S. EPA. (2012e). Toxicological Review of Tetrachloroethylene (Perchloroethylene) (CAS No. 127-
18-4) In Support of Summary Information on the Integrated Risk Information System (IRIS).
(NTIS/10860149).
U.S. EPA. (2013). Interpretive assistance document for assessment of discrete organic chemicals.
Sustainable futures summary assessment [EPA Report], Washington, DC.
http://www.epa.eov/sites/production/files/2015-05/documents/05-ind discretes iuneJO I '
U.S. EPA. (2014a). Degreasing with TCE in commercial facilities: Protecting workers [EPA Report],
Washington, DC: U.S. Environmental Protection Agency, Office of Pollution Prevention and
Toxics.
U.S. EPA. (2014b). Exposure and Fate Assessment Screening Tool Version 2014 (E-FAST 2014).
Washington, DC: Office of Pollution Prevention and Toxics. https://www.epa.gov/tsca-
screening-tools/e-fast-exposure-and-fate-assessment-screening-tool-version-z
U.S. EPA. (2014c). Framework for human health risk assessment to inform decision making. Final
[EPA Report], (EPA/100/R-14/001). Washington, DC: U.S. Environmental Protection, Risk
Assessment Forum, https://www.epa.gov/risk/frarnework-hurnan-health-risk-assessrnent-inforrn-
decision-making.
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U.S. EPA. (2014d). The Superfund Enterprise Management System (SEMS) [Website],
https://www.epa. gov/enviro/ sem s-overview.
1 v M \ (2015a). Peer review handbook [EPA Report] (4th ed.). (EPA/100/B-15/001). Washington,
DC: U.S. Environmental Protection Agency, Science Policy Council.
https://www.epa.eov/osa/peer-review-handbook-4th-edition-2015.
U.S. EPA. (2015b). Update of human health ambient water quality criteria: Tetrachloroethylene
(Perchloroethy 1 ene) 127-18-4. (EPA 820-R-15-
063). https://heronet.epa. eov/heronet/index.cfm?action=search.view&reference i
« \ (2016b). Instructions for Reporting 2016 TSCA Chemical Data Reporting. (EPA/600/R-
09/052F). Washington, DC: U.S. Environmental Protection Agency (EPA).
https://www.epa.gov/chemical~data-reporting/instructions-reporting-2Q16~tsca-chemical~data-
reporting.
U.S. EPA. (2016c). Non-confidential 2016 Chemical Data Reporting (CDR) Database [Website],
http ://www. epa. gov/cdr/.
1 v M \ (2016d). Public database 2016 chemical data reporting (May 2017 release). Washington, DC:
US Environmental Protection Agency, Office of Pollution Prevention and Toxics.
https://www.epa.gov/chemical~data-reporting.
U.S. EPA. (2016e). A Set of Scientific Issues Being Considered by the Environmental Protection
Agency Regarding the Draft Risk Assessment for TSCA Work Plan Chemical 1-Bromopropane
(CASRN-106-94-5). (Chemical Safety Advisory Committee Minutes No. 2016-02).
U.S. EPA. (2016f). TSCA work plan chemical risk assessment: Peer review draft 1 -bromopropane: (n-
Propyl bromide) spray adhesives, dry cleaning, and degreasing uses CASRN: 106-94-5 [EPA
Report], (EPA 740-R1-5001). Washington, DC.
https://www.epa.gov/sites/production/files/2016-03/documents/l-
bp report, and appendices finat.pdf.
U.S. EPA. (2017a). Consumer Exposure Model (CEM) version 2.0: User guide. U.S. Environmental
Protection Agency, Office of Pollution Prevention and Toxics.
https://www.epa.gov/sites/prodiiction/files/2i 'documents/cem2.0 user guide.pdf.
U.S. EPA. (2017b). EPA Use and Market Profile. (EPA-HQ-OPPT-2016-0732-0058).
U.S. EPA. (2017c). Federal Register: Procedures for chemical risk evaluation under the amended toxic
substances control act. Fed Reg 82: 33726-33753.
(2017d). Human Health Benchmarks for Pesticides: Updated 2017 Technical Document (pp.
5). (EPA 822-R -17 -001). Washington, DC: U.S. Environmental Protection Agency, Office of
Water, https://www.epa.gov/sites/production/files/2Q15-lQ/documents/hh-benchmarks-
techdoc.pdf.
U.S. EPA. (2017e). Perchl oroethy 1 ene (CASRN: 127-18-4) bibliography: Supplemental file for the
TSCA Scope Document [EPA Report], https://www.epa.gOv/sites/production/files/2
06/docum ents/perc comp bib.pdf.
U.S. EPA. (2017f). Preliminary Information on Manufacturing, Processing, Distribution, Use, and
Disposal: Tetrachloroethylene (Perchloroethylene) [Comment],
https://www.regiilations.gov/documei11 * < ,PA-H.Q~01 « I l _ ^003.
U.S. EPA. (2017g). Preliminary information on manufacturing, processing, distribution, use, and
disposal: tetrachloroethylene (perchloroethylene). (EPA-HQ-OPPT-2016-0732-0003).
https://www.epa.gov/sites/prodiiction/files/2i 'docum ents/perchloroethyl en e. pdf.
U.S. EPA. (2017h). Procedures for chemical risk evaluation under the amended Toxic Substances
Control Act. Final Rule Federal Registrar 82: 33726-33753. Fed Reg 82.
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
U.S. EPA. (2017i). Scope of the risk evaluation for perchloroethylene (ethene, 1,1,2,2-tetrachloro).
CASRN: 127-18-4 [EPA Report], (EPA-740-R1-7007).
https://www.epa.eov/sites/production/files/201 0 'documents/perc scop-' J J I |-df.
U.S. EPA. (2017j). Strategy for conducting literature searches for tetrachloroethylene (perc):
Supplemental document to the TSCA Scope Document. CASRN: 127-18-4 [EPA Report],
https://www.epa.gov/sites/production/files/2Q17-
06/documents/perc lit search stratee ittps://heronet.epa.eov/heronet/index.cfm
?action=search.view&reference id=504i 14SU.S. EPA. (2018a). 2014 National Emissions
Inventory (NEI) data (2 ed.). Washington, DC. https://www.epa.gov/air-emissions-
inventories/^ itional-emissions-inventorv-nei-data.
U.S. EPA. (2018b). Application of systematic review in TSCA risk evaluations. (740-P1 -8001).
Washington, DC: U.S. Environmental Protection Agency, Office of Chemical Safety and
Pollution Prevention. https://www.epa.gov/sites/production/files/2Q18-
06/documents/final application of sr in tsc if.
U.S. EPA. (2018c). Application of systematic review in TSCA risk evaluations: DRAFT Version 1.0.
(740P18001). Washington, D.C.: U.S. Environmental Protection Agency, Office of Chemical
Safety and Pollution Prevention.
U.S. EPA. (2018d). Problem formulation of the risk evaluation for perchloroethylene (ethene, 1,1,2,2-
tetrachloro). (EPA-740-R1-7017). Washington, DC: Office of Chemical Safety and Pollution
Prevention, United States Environmental Protection Agency.
https://www.epa.gov/sites/production/files/2018-06/documents/perc problem formulati
2018v3.pdf.
U.S. EPA. (2018e). Strategy for assessing data quality in TSCA risk evaluations. Washington DC: U.S.
Environmental Protection Agency, Office of Pollution Prevention and Toxics.
(2019a). Assessment of Occupational Exposure and Environmental Releases for
Perchloroethylene (Ethene, 1,1,2,2-Tetrachloro), CASRN: 127-18-4 [draft] [EPA Report] (pp.
302). Washington D.C.: U. S. Environmental Protection Agency, Office of Chemical Safety and
Pollution Prevention.
U.S. EPA. (2019b). Consumer Exposure Model (CEM) 2.1 User Guide. (EPA Contract # EP-W-12-
010). Washington, DC.
(2019c). Draft risk evaluation for perchloroethylene. Systematic review supplemental file:
data quality evaluation of physical-chemical properties studies. Washington, D.C.: U.S.
Environmental Protection Agency. Office of Chemical Safety and Pollution
Prevention.https://heronet.epa. gov/heronet/index.cfm?action=search.view&reference id 34
J.U.S. EPA. (2019e). Multi-Chamber Concentration and Exposure Model (MCCEM) User Guide.
U.S. EPA.
U.S. EPA. (2020a). Draft risk evaluation for perchloroethylene. Washington, D C.: U.S. Environmental
Protection Agency. Office of Chemical Safety and Pollution Prevention.
(2020b). Draft risk evaluation for perchloroethylene consumer dermal risk calculations.
Washington, D.C.: U.S. Environmental Protection Agency. Office of Chemical Safety and
Pollution Prevention.
U.S. EPA. (2020c). Draft risk evaluation for perchloroethylene consumer inhalation risk calculations.
Washington, D.C.: U.S. Environmental Protection Agency. Office of Chemical Safety and
Pollution Prevention.
U.S. EPA. (2020d). Draft risk evaluation for perchloroethylene engineering report. Washington, D C.:
U.S. Environmental Protection Agency. Office of Chemical Safety and Pollution Prevention.
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
U.S. EPA. (2020e). Draft risk evaluation for perchloroethylene occupational risk calculations.
Washington, D.C.: U.S. Environmental Protection Agency. Office of Chemical Safety and
Pollution Prevention.
U.S. EPA. (2020f). Draft risk evaluation for perchl oroethy 1 ene supplemental information on consumer
exposure. Washington, D.C.: U.S. Environmental Protection Agency. Office of Chemical Safety
and Pollution Prevention.
U.S. EPA. (2020g). Draft risk evaluation for perchl oroethy 1 ene, systematic review supplemental file:
Data extraction data for human health hazard studies. Washington, D.C.: U.S. Environmental
Protection Agency. Office of Chemical Safety and Pollution Prevention.
U.S. EPA. (2020h). Draft risk evaluation for perchl oroethy 1 ene, systematic review supplemental file:
Data extraction tables for environmental fate and transport studies. Washington, D.C.: U.S.
Environmental Protection Agency. Office of Chemical Safety and Pollution Prevention.
U.S. EPA. (2020i). Draft risk evaluation for perchloroethylene, systematic review supplemental file:
Data quality evaluation of ecological hazard studies. Washington, D.C.: U.S. Environmental
Protection Agency. Office of Chemical Safety and Pollution Prevention.
U.S. EPA. (2020j). Draft risk evaluation for perchloroethylene, systematic review supplemental file:
Data quality evaluation of environmental fate and transport studies. Washington, D.C.: U.S.
Environmental Protection Agency. Office of Chemical Safety and Pollution Prevention.
U.S. EPA. (2020k). Draft risk evaluation for perchloroethylene, systematic review supplemental file:
Data quality evaluation of epidemiological studies. Washington, D.C.: U.S. Environmental
Protection Agency. Office of Chemical Safety and Pollution Prevention.
U.S. EPA. (20201). Draft risk evaluation for perchloroethylene, systematic review supplemental file:
Data quality evaluation of human health hazard studies-animal and in vitro studies. Washington,
D.C.: U.S. Environmental Protection Agency. Office of Chemical Safety and Pollution
Prevention.
U.S. EPA. (2020m). TIll-listed chemicals. Washington, DC. https://www.epa.gov/toxics-release-
inventorv-tri-proeram/tri-listed-chemicals.
LISGS. (2003). A national survey of methyl tert-butyl ether and other volatile organic compounds in
drinking-water sources: Results of the random survey. Reston, VA: U.S. Department of the
Interior, U.S. Geological Survey, https://piibs.er.iises.eov/publication/wri024079.
LISGS. (2006). Water-quality conditions of Chester Creek, Anchorage, Alaska, 1998-2001. Reston, VA:
U.S. Department of the Interior, U.S. Geological Survey.
https://pubs.er.usgs.gov/publication/sir20065229.
LISGS. (2013). Federal Standards and Procedures for the National Watershed Boundary Dataset (WBD):
Techniques and Methods 11-A3 (4th ed., pp. 63). U.S. Geological Survey and U.S. Department
of Agriculture, Natural Resources Conservation Service. https://pubs.usgs.gOv/tm/l l/a3/.
Vamvakas. S: Dekant W: Henschler. D. (1989a). Assessment of unscheduled DNA synthesis in a
cultured line of renal epithelial cells exposed to cysteine S-conjugates of haloalkenes and
haloalkanes. Mutat Res 222: 329-335. http://dx.dou ;9190108-0.
Vamvakas. S: Kochlime \ < 'orth(4 » U * K'kant. W. (1989b). Cytotoxicity of cysteine S-conjugates:
structure-activity relationships. Chem Biol Interact 71: 79-90.
Van Amber. RR; Niven. BE; Wilson. CA. (2010). Effects of laundering and water temperature on the
properties of silk and silk-blend knitted fabrics. Text Res J 80: 1557-1568.
http://dx.doi.ore 10 I I M I ?0r
van Hook. DE. (2017). Comment submitted by D. Evan van Hook, Corporate Vice President, Health
Safety, and Environment, Product Stewardship and Sustainability, Honeywell International Inc
[Comment], https://www.reeulations.eov/document?D=EPA-HQ-OPPT-!
Page 565 of 636
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14492
14493
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14499
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14503
14504
14505
14506
14507
14508
14509
14510
14511
14512
14513
14514
14515
14516
14517
14518
14519
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14525
14526
14527
14528
14529
14530
14531
14532
14533
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Van Winkle. MR; Scheff. PA. (2001). Volatile organic compounds, polycyclic aromatic hydrocarbons
and elements in the air of ten urban homes. Indoor Air 11: 49-64.
http://dx.doi.Org/10.1034/i.1600-0668.20 jc.
Vizcava. D; Christensen. KY; Lavoue. J; Siemiatvcki. J. (2013). Risk of lung cancer associated with six
types of chlorinated solvents: Results from two case-control studies in Montreal, Canada. Occup
Environ Med 70: 81-85. http://dx.doi.oiv 10 I I »6/oemed-2^ l _ h'll
Vlaanderen. J; Straif. K; Pukkala. E; Kauppinen. T; Kyyronen. P; Martinsen. J; Kiaerheim. K;
Tryggvadottir. L; Hansen. J; Sparen. P; Weiderpass. E. (2013). Occupational exposure to
trichloroethylene and perchloroethylene and the risk of lymphoma, liver, and kidney cancer in
four Nordic countries. Occup Environ Med 70: 393-401. http://dx.doi.< 10 I I »6/oemed-201 J
101188.
von Ehrenstein. OS; Aralis. H; Cockburn. M; Rii (2014). In utero exposure to toxic air pollutants
and risk of childhood autism. Epidemiology 25: 851-858.
http://dx.doi.org 10 10" I HI L00000000000001 x\
Von Grote. J. (2003) Occupational Exposure Assessment in Metal Degreasing and Dry Cleaning -
Influences of Technology Innovation and Legislation. A dissertation submitted to the Swiss
Federal Institute of Technology Zurich for the degree of Doctor of Natural Sciences. (Swiss
Federal Institute of Technology Zurich, Retrieved from https://www.research-
col 1 ecti on. eth z. ch/h an dl e/2 0.51 >0/116460
Vulcan. C. (1992). INDUSTRIAL HYGIENE STUDY OF
PERCHLOROETHYLENE/METHYLCHLOROFORM BLENDED AEROSOL BRAKE
CLEANERS (FINAL REPORT) WITH COVER LETTER DATED 031292. (OTS:
OTS0535416; 8EHQ Num: NA; DCN: 86-920000858; TSCATS RefID: 422422; CIS: NA).
Vulcan. C. (1993). INDUSTRIAL HYGIENE STUDY OF METHYLENE
CHLORIDE/PERCHLOROETHYLENE/METHYLCHLOROFORM BLENDED AEROSOL
BRAKE CLEANERS. (OTS: OTS0556634; 8EHQ Num: NA; DCN: 86940000038; TSCATS
RefID: NA; CIS: 86940000038).
Vulcan. C. (1994). Task Report- Cold Cleaning Field Tests of Perchloroethylene / Alcohol Blends
Vickers Electromechanical, Wichita, KS. (OTS: OTS0556807; 8EHQ Num: NA; DCN: 86-
940000212; TSCATS RefID: NA; CIS: 86940000212).
Wakeham. SG; Day ras. JA. (1983). Mesocosm experiments to determine the fate and
persistence of volatile organic compounds in coastal seawater. Environ Sci Technol 17: 611-617.
http://dx.doi.org/10.102 i/esOOl 16a009.
Walk „ (1987). The total exposure assessment methodology (TEAM) study: Summary and
analysis: Volume I [EPA Report], (EPA/600/6-87/002a). Washington, DC: U.S. Environmental
Protection Agency; Office of Acid Deposition, Environmental Monitoring, and Quality
Assurance.
Warn irada. S; Watanabe. M; Koshikawa. H; Sato. K; Kimura. T. (1996). Determination of
bioconcentration potential of tetrachloroethylene in marine algae by 13C. Chemosphere 33: 865-
877. http://dx.doi.org/10. i 0 i 6/0045-6535(96)00230-5.
Westat. (1987). Household solvent products: A national usage survey [EPA Report], (EPA-OTS 560/5-
87-005). Washington, DC: Office of Toxic Substances, Office of Pesticides and Toxic
Substances, https://nepis.epa.gov/Exe/ZyPLIRL.< ckev=Pl 00754Q.txt.
Whittaker. C; Rt ^ t VIcKernan. L; Danko\i»- 1 ciitz. T; Macmahon. K; Kuempel. E; Zumwalde. R;
Schulte. P (2016). Current Intelligence Bulletin 68: NIOSH Chemical Carcinogen Policy. US
Department of Health and Human Services.
https://ntrl.ntis.gov/NTRL/dashboard/searchResults/titleDetail/PB: html.
Page 566 of 636
-------
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14539
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14551
14552
14553
14554
14555
14556
14557
14558
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Whittaker. SG; Johansc (2011). A profile of the dry cleaning industry in King County,
Washington: Final report. (LHWMP 0048). Seattle, WA: Local Hazardous Waste Management
Program in King County.
http://www.hazwastehelp.ore/piiblications/publications detail. aspx?D 3h 73 %2fQil e9Q%3
d.
WHO. (2006a). Concise international chemical assessment document 68: Tetrachloroethene. Geneva,
Switzerland: World Health Organization, International Programme on Chemical Safety.
http://www.inchem.ore/documents/cicads/cicads/cicad68.htm.
WHO. (2006b). Reproductive health indicators: guidelines for their generation, interpretation and
analysis for global monitoring.
Wilson. R; Donahue. M n \ > i.mi. J; El Ghoriuli 1 . Oosemeci. M. (2008). Shared
occupational risks for transitional cell cancer of the bladder and renal pelvis among men and
women in Sweden. Am J Ind Med 51: 83-99.
http://dx.doi.ore/10.1002/aiim.20522. https://heronet.epa.eov/heronet/index. cfm?action=search.vi
ew&reference id=9881Yoo. HS; Cichocki, JA; Kim, S; Venkatratnam, A; Iwata, Y; Kosyk, O;
Bodnar, W; Sweet, S; Knap, A; Wade, T; Campbell, J; Clewell, HJ; Melnyk, SB; Chiu, WA;
Rusyn, I. (2015). The Contribution of Peroxisome Proliferator-Activated Receptor Alpha to the
Relationship Between Toxicokinetics and Toxicodynamics of Trichloroethylene. Toxicol Sci
147: 339-349. http://dx.doi.on 93/toxsci/kfvl34.
Zhou. YH; Cichocki. JA; Sold>no\\ \ "s v holl. EH; Gallirr H j'ima. D; Yoo. HS; Chiu. AN \ NN right,
FA; Rusyn. I. (2017). Editor's Highlight: Comparative Dose-Response Analysis of Liver and
Kidney Transcriptomic Effects of Trichloroethylene and Tetrachloroethylene in B6C3F1 Mouse.
Toxicol Sci 160: 95-110. http://dx.doi.ore/10.1093/toxsci/kfxl65.
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14559 APPENDICES
14560 Appendix A REGULATORY HISTORY
14561
14562 A.l Federal Laws and Regulations
14563
14564 Table Apx A-l. Federal Laws and Regulations
Mat ulcs/Uegulat ions
Description of Authority/Regulation
Description of Regulation
EPA Regulations
Toxics Substances
Control Act (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.
PCE is on the initial list of chemicals
to be evaluated for unreasonable risk
under TSCA (81 FR 91927, December
19, 2016).
Toxics Substances
Control Act (TSCA)
- Section 8(a)
The TSCA Section 8(a) Chemical Data
Reporting (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.
PCE manufacturing (including
importing), processing, and use
information is reported under the
Chemical Data Reporting (CDR) rule
(40 CFR711).
Toxics Substances
Control Act (TSCA)
- Section 8(b)
EPA must compile, keep current, and
publish a list (the TSCA Inventory) of
each chemical substance manufactured,
processed or imported in the United
States.
PCE was on the initial TSCA
Inventory and therefore was not
subject to EPA's new chemicals
review process (60 FR 16309, March
29, 1995).
Toxics Substances
Control Act (TSCA)
- Section 8(e)
Manufacturers (including imports),
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.
Eleven risk reports received for PCE
(1978-2010) (US EPA, ChemView.
Accessed April 13, 2017).
Toxics Substances
Control Act (TSCA)
- Section 4
Provides EPA with authority to issue
rules and orders requiring
manufacturers (including importers)
and processors to test chemical
substances and mixtures.
Nine chemical data submissions from
test rules received for PCE (1978-
1980) (US EPA, ChemView.
Accessed April 13, 2017).
Emergency Planning
and Community
Right-to-Know Act
Requires annual reporting from
facilities in specific industry sectors
that employ 10 or more full time
PCE is a listed substance subject to
reporting requirements under 40 CFR
372.65 effective as of January 1, 1987.
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Slsiliilcs/Ucgiihitions
Description of Aiithorhy/Ucgiihilion
Description ol' Requisition
(EPCRA) - Section
313
equivalent employees and that
manufacture, process or otherwise use a
TRI-listed chemical in quantities above
threshold levels.
Federal Insecticide,
Fungicide, and
Rodenticide Act
(FIFRA) - Sections 3
and 6
FIFRA governs the sale, distribution
and use of pesticides. Section 3 of
FIFRA generally requires that pesticide
products be registered by EPA prior to
distribution or sale. Pesticides may only
be registered if, among other things,
they do not cause "unreasonable
adverse effects on the environment."
Section 6 of FIFRA provides EPA with
the authority to cancel pesticide
registrations if either (1) the pesticide,
labeling or other material does not
comply with FIFRA; or (2) when used
in accordance with widespread and
commonly recognized practice, the
pesticide generally causes unreasonable
adverse effects on the environment.
EPA removed PCE and other chemical
substances from its list of pesticide
product inert ingredients used in
pesticide products (63 FR 34384, June
24, 1998).
Clean Air Act (CAA)
- Section 112(b)
Defines the 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. Since
1990 EPA has removed two pollutants
from the original list leaving 187 at
present.
Lists PCE as a Hazardous Air
Pollutant (42 U.S. Code § 7412), and
is considered an "urban air toxic"
(CAA Section 112(k)).
Clean Air Act (CAA)
- Section 112(d)
Section 112(d) states that the EPA must
establish national emission standards
for HAP (NESHAP) 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
There are a number of source-specific
CAA, Section 112, NESHAPs for
PCE, including:
Dry cleaners (73 FR 39871, July 11,
2008)
Organic liquids distribution (non-
gasoline) (69 FR 5038, February 3,
2004)
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Slsiliilcs/Ucgiihitions
Description of Aiithorhy/Ucgiihilion
Description ol' Requisition
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.
Off-site waste and recovery operations
(64 FR 38950, July 20, 1999)
Rubber Tire Manufacturing (67 FR
45588, July 9, 2002)
Wood furniture manufacturing (60 FR
62930, December 7, 1995)
Synthetic organic chemical
manufacturing (59 FR 19402, April
22,1994)
Chemical Manufacturing Area Source
Categories (74 FR 56008, October 29,
2009)
Publicly Owned Treatment Works (64
FR 57572, October 26, 1999)
Site Remediation includes PCE (68
FR 58172, October 8, 2003)
Clean Air Act (CAA)
- Section 112(d) and
112(f)
Risk and technology review (RTR) of
section 112(d) MACT standards.
Section 112(f)(2) requires EPA to
conduct risk assessments for each
source category subject to section
112(d) MACT standards, and to
determine if additional standards are
needed to reduce remaining risks.
Section 112(d)(6) requires EPA to
review and revise the MACT standards,
as necessary, taking into account
developments in practices, processes
and control technologies."
EPA has promulgated a number of
RTR NESHAP (e.g., the RTR
NESHAP for PCE Dry Cleaning (71
FR 42724; July 27, 2006) and the RTR
NESHAP for Halogenated Solvent
Cleaning (72 FR 25138; May 3, 2007)
and will do so, as required, for the
remaining source categories with
NESHAP
Clean Air Act (CAA)
- Section 183(e)
Section 183(e) requires EPA to list the
categories of consumer and commercial
products that account for at least
80 percent of all VOC emissions in
areas that violate the National Ambient
Air Quality Standards (NAAQS) for
ozone and to issue standards for these
categories that require "best available
controls." In lieu of regulations, EPA
may issue control techniques guidelines
if the guidelines are determined to be
substantially as effective as regulations.
PCE is listed under the National
Volatile Organic Compound Emission
Standards for Aerosol Coatings (40
CFR part 59, subpart E). PCE has a
reactivity factor of 0.04g 03/g VOC.
Clean Air Act (CAA)
- Section 612
Under Section 612 of the Clean Air Act
(CAA), EPA's Significant New
Alternatives Policy (SNAP) program
Under the SNAP program, EPA listed
PCE as an acceptable substitute in
cleaning solvent for metal cleaning,
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Slsiliilcs/Ucgiihitions
Description of Aiithorhy/Ucgiihilion
Description ol' Requisition
reviews substitutes for ozone depleting
substances within a comparative risk
framework. EPA publishes lists of
acceptable and unacceptable
alternatives. A determination that an
alternative is unacceptable or
acceptable only with conditions, is
made through rulemaking.
electronics cleaning and precision
cleaning (59 FR 13044, March 18,
1994). PCE is cited as an alternative to
methyl chloroform and CFC-113 for
metals, electronics and precision
cleaning. PCE was also noted to have
no ozone depletion potential and cited
as a VOC-exempt solvent and
acceptable ozone-depleting substance
substitute (72 FR 30142, May 30,
2007).
Clean Water Act
(CWA) - Section
301(b), 304(b), 306,
and 307(b)
Requires establishment of Effluent
Limitations Guidelines and Standards
for conventional, toxic, and
non-conventional pollutants. For toxic
and non-conventional pollutants, EPA
identifies the best available technology
that is economically achievable for that
industry after considering statutorily
prescribed factors and sets regulatory
requirements based on the performance
of that technology.
PCE is designated as a toxic pollutant
under section 307(a)(1) of CWA and
as such is subject to effluent
limitations. Also under section 304,
PCE is included in the list of total
toxic organics (TTO) (40 CFR
413.02(i)).
Clean Water Act
(CWA) 304(a)
Section 304(a)(1) of the Clean Water
Act (CWA) requires EPA to develop
and publish, and from time to time
revise, recommended criteria for the
protection of water quality that
accurately reflect the latest scientific
knowledge. Water quality criteria
developed under section 304(a) are
based solely on data and scientific
judgments on the relationship between
pollutant concentrations and
environmental and human health
effects.
Clean Water Act
(CWA) - Section
307(a)
Establishes a list of toxic pollutants or
combination of pollutants under the
CWA. The statute specifies a list of
families of toxic pollutants also listed in
the Code of Federal Regulations at 40
CFR 401.15. The "priority pollutants"
specified by those families are listed in
40 CFR part 423, Appendix A. These
are pollutants for which best available
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Slsiliilcs/Ucgiihitions
Description of Aiithorhy/Ucgiihilion
Description ol' Requisition
technology effluent limitations must be
established on either a national basis
through rules (Sections 301(b), 304(b),
307(b), 306), or on a case-by-case best
professional judgement basis in NPDES
permits (Section 402(a)(1)(B)).
Safe Drinking Water
Act (SDWA) -
Section 1412
Requires EPA to publish a non-
enforceable maximum contaminant
level goals (MCLGs) for contaminants
which 1. may have an adverse effect on
the health of persons; 2. are known to
occur or there is a substantial likelihood
that the contaminant will occur in
public water systems with a frequency
and at levels of public health concern;
and 3. in the sole judgment of the
Administrator, regulation of the
contaminant presents a meaningful
opportunity for health risk reductions
for persons served by public water
systems. When EPA publishes an
MCLG, EPA must also promulgate a
National Primary Drinking Water
Regulation (NPDWR) which includes
either an enforceable maximum
contaminant level (MCL) or a required
treatment technique. Public water
systems are required to comply with
NPDWRs
PCE is subject to National Primary
Drinking Water Regulations
(NPDWR) under SDWA with a
MCLG of zero and an enforceable
maximum contaminant level (MCL) of
0.005 mg/L (40 CFR 141.61). On
January 11, 2017, EPA announced a
review of the eight existing NPDWRs
(82 FR 3518). PCE is one of the eight
NPDWRs. EPA requested comment
on the eight NPDWRs identified as
candidates for revision.
Comprehensive
Environmental
Response,
Compensation and
Liability Act
(CERCLA) - Section
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
PCE is a hazardous substance under
CERCLA. Releases of PCE in excess
of 100 pounds must be reported (40
CFR 302.4).
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Slaliilcs/Ucgulations
Description of AiithoritY/Ucgulalion
Description of Regulation
knowledge of a release of a hazardous
substance above the reportable quantity
threshold.
Resource
Conservation and
Recovery Act
(RCRA) - Section
3001
Directs EPA to develop and promulgate
criteria for governing hazardous waste
identification, classification, generation,
management and disposal.
RCRA Subtitle C, Section 3001
identifies PCE as a characteristic and
listed hazardous waste. RCRA
Hazardous Waste Code: D039
(Toxicity); F001, F002; U210.
In 2013, EPA modified its hazardous
waste management regulations to
conditionally exclude solvent-
contaminated wipes that have been
cleaned and reused from the definition
of solid waste under RCRA (78 FR
46447, July 31,2013).
Superfund
Amendments and
Reauthorization Act
(SARA) -
Requires the Agency to revise the
hazardous ranking system and update
the National Priorities List of hazardous
waste sites, increases state and citizen
involvement in the superfund program
and provides new enforcement
authorities and settlement tools.
PCE is listed on SARA, an
amendment to CERCLA and the
CERCLA Priority List of Hazardous
Substances. This list includes
substances most commonly found at
facilities on the CERCLA National
Priorities List (NPL) that have been
deemed to pose the greatest threat to
public health.
Other Federal Regulations
Federal Hazardous
Substance Act
(FHSA)
Allows the Consumer Product Safety
Commission (CPSC) to (1) require
precautionary labeling on the
immediate container of hazardous
household products or (2) to ban certain
products that are so dangerous or the
nature of the hazard is such that
required labeling is not adequate to
protect consumers.
Under the Federal Hazardous
Substance Act, section 1500.83(a)(31),
visual novelty devices containing PCE
are regulated by CPSC.
Federal Food, Drug,
and Cosmetic Act
(FFDCA)
Provides the U.S. FDA (Food and Drug
Administration) with authority to
oversee the safety of food, drugs and
cosmetics.
The FDA regulates PCE in bottled
water. The maximum permissible
level of PCE in bottled water is
0.005 mg/L (21 CFR 165.110).
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Slalulcs/Uegulations
Description of AiithoritY/Ucgulalion
Description of Regulation
Occupational Safety
and Health Act (OSH
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,
the Occupational Safety and Health
Administration can issue occupational
safety and health standards including
such provisions as Permissible
Exposure Limits (PELs), exposure
monitoring, engineering and
administrative control measures and
respiratory protection.
In 1970, OSHA issued occupational
safety and health standards for PCE
that included a Permissible Exposure
Limit (PEL) of 100 ppm 8 hr. TWA,
with a ceiling level of 200 ppm for 5
minutes in any 3 hr. period with a
maximum peak of 300 ppm (29 CFR
1910.1000).
Atomic Energy Act
Department of
Energy (DOE)
The Atomic Energy Act authorizes
DOE 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 ACGM® TLV®s if they are
more protective than the OSHA PEL.
The 2005 TLV® for PCE is 25 ppm
(8hr Time Weighted Average) and 100
ppm Short Term Exposure
Limit(STEL).
14565
14566 A.2 State Laws and Regulations
14567
14568 Table Apx A-2. State Laws and Regulations
State Actions
Description of Action
State actions
State Permissible
Exposure Limits
California has a workplace PEL of 25 ppm (California, OEHHA, 1988)
State Right-to-
Know Acts
Massachusetts (454 CMR 21.00), New Jersey (42 N.J.R 1709(a)), Pennsylvania
(Chapter 323, Hazardous Substance List), Rhode Island (RI Gen. Laws Sec. 28-21-
let seq).
Volatile Organic
Compound
(VOC)
Regulations for
Consumer
Products
Many states regulate PCE as a VOC. These regulations may set VOC limits for
consumer products and/or ban the sale of certain consumer products as an ingredient
and/or impurity. Regulated products vary from state to state, and could include
contact and aerosol adhesives, aerosols, electronic cleaners, footwear or leather care
products, and general degreasers, among other products. California (Title 17,
California Code of Regulations, Division 3, Chapter 1, Subchapter 8.5, Articles 1, 2,
3 and 4), Connecticut (R.C.S.A Sections 22a-174-40, 22a-l74-41, and 22a-174-44),
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Slate Actions
Description of Action
Delaware (Adm. Code Title 7, 1141), District of Columbia (Rules 20-720, 20-721,
20-735, 20-736, 20737), Illinois (35 Adm Code 223), Indiana ( 326 IAC 8-15),
Maine (Chapter 152 of the Maine Department of Environmental Protection
Regulations), Maryland (COMAR 26.11.32.00 to 26.11.32.26), Michigan (R
336.1660 and R 336. 1661), New Hampshire (Env—A 4100) New Jersey (Title 7,
Chapter 27, Subchapter 24), New York (6 CRR-NY III A 235), Rhode Island (Air
Pollution Control Regulation No. 31), and Virginia (9VAC5 CHAPTER 45) all have
VOC regulations or limits for consumer products. Some of these states also require
emissions reporting.
Other
There are several state level NESHAPs for dry cleaning and restrictions or phase
outs of PCE (e.g. California, Maine, Massachusetts). Numerous states list PCE on a
list of chemical substances of high concern to children (e.g. Oregon, Vermont,
Washington). Under the California Proposition 65 list (California OEHHA), PCE is
known to the state of California to cause cancer.
14569
14570 A.3 International Laws and Regulations
14571
14572 Table Apx A-3. Regulatory Actions by Other Governments and Tribes
Con n try/Organization
Requirements and Restrictions
Canada
PCE is on the Canadian List of Toxic Substances (CEPA 1999 Schedule 1).
The use and sale of PCE in the dry cleaning industry is regulated under Use in
Dry Cleaning and Reporting Requirements Regulations (Canada Gazette, Part
II on March 12, 2003. PCE is also regulated for use and sale for solvent
degreasing under Solvent Degreasing Regulations (SOR/2003-283) (Canada
Gazette, Part II on August 13, 2003). The purpose of the regulation is to reduce
releases of PCE into the environment from solvent degreasing facilities using
more than 1,000 kilograms of PCE per year. The regulation includes a market
intervention by establishing tradable allowances for the use of PCE in solvent
degreasing operations that exceed the 1,000 kilograms threshold per year.
European Union
PCE was evaluated under the 2013 Community Rolling Action Plan (CoRAP).
The conclusion was no additional regulatory action was required (European
Chemicals Agency (ECHA) database. Accessed April, 18 2017).
Australia
In 2011, a preliminary assessment of PCE was conducted (National Industrial
Chemicals Notification and Assessment Scheme, NICNAS, 2016,
Tetrachloroethylene. Accessed April, 18 2017).
Japan
PCE 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
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Con ill rv/Orgsinizsit ion
Requirements iiikI Restrictions
• Industrial Safety and Health Act (ISHA)
• Air Pollution Control Law
• Water Pollution Control Law
• Soil Contamination Countermeasures Act
• Law for the Control of Household Products Containing Harmful
Substances
(National Institute of Technology and Evaluation (NITE) Chemical Risk
Information Platform (CHIRP). Accessed April 18, 2017)
Australia, Austria,
Belgium, Canada,
Denmark, European
Union, Finland, France,
Germany, Hungary,
Ireland, Israel, Japan,
Latvia, New Zealand,
People's Republic of
China, Poland,
Singapore, South
Korea, Spain, Sweden,
Switzerland, United
Kingdom
Occupational exposure limits for PCE (GESTIS International limit values for
chemical agents (Occupational exposure limits, OELs) database. Accessed
April 18, 2017).
Basel Convention
Halogenated organic solvents (Y41) are listed as a category of waste under the
Basel Convention - Annex I. Although the United States is not currently a
party to the Basel Convention, this treaty still affects U.S. importers and
exporters.
OECD Control of
Transboundary
Movements of Wastes
Destined for Recovery
Operations
Halogenated organic solvents (A3150) are listed as a category of waste subject
to The Amber Control Procedure under Council Decision C (2001) 107/Final.
14573
14574
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14575 Appendix B LIST OF SUPPLEMENTAL DOCUMENTS
1. Draft Risk Evaluation for Perchloroethylene ( 3a)
2. Draft Charge to the Panel for Perchloroethylene
3. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental
Tables for Environmental Fate and Transport Studies
4. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental
Evaluation of Environmental Fate and Transport Studies
5. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental
Evaluation of Physical Chemical Properties
6. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental
Evaluation of Environmental Releases and Occupational Exposure Data Common
7. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental
Evaluation of Environmental Releases and Occupational Exposure
8. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental
Evaluation for Consumer and Environmental Exposure
9. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental
for Consumer and Environmental Exposure
10. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental File: Data Quality
Evaluation of Ecological Hazard Studies
11. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental File: Data
Extraction Tables for Environmental Hazard Studies
12. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental File: Updates to the
Data Quality Criteria for Epidemiological Studies
13. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental File: Data Quality
Evaluation of Human Health Hazard Studies - Epidemiological Studies
14. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental File: Data
Extraction for Human Health Hazard Studies
15. Draft Risk Evaluation for Perchloroethylene, Systematic Review Supplemental File: Data Quality
Evaluation of Human Health Hazard Studies - Animal Studies
16. Draft Risk Evaluation for Perchloroethylene Assessment of Occupational Exposure and
Environmental Releases for Perchloroethylene
17. Draft Risk Evaluation for Perchloroethylene Occupational Risk Calculations
18. Draft Risk Evaluation for Perchloroethylene Consumer Inhalation Risk Calculations
19. Draft Risk Evaluation for Perchloroethylene Consumer Dermal Risk Calculations
20. Draft Risk Evaluation for Perchloroethylene Supplemental Information on Consumer Exposure
Page 577 of 636
File: Data Extraction
File: Data Quality
File: Data Quality
File: Data Quality
Sources
File: Data Quality
File: Data Quality
File: Data Extraction
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21. Draft Risk Evaluation for Perchloroethylene Supplemental Information on E-Fast Surface Water
Modeling Outputs
14576
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14577 Appendix C FATE AND TRANSPORT
14578
14579 EPISuite™Model Inputs
14580
14581 To set up EPI Suite™ for estimating fate properties of PCE, PCE was identified using the "Name
14582 Lookup" function. The physical-chemical properties were input based on the values in Table 1-1. EPI
14583 Suite™ was run using default settings (i.e., no other parameters were changed or input).
14584
14585
14586
14587
14588
14589
If® EPI Suite
Batch Mode
Show
Structure
Output
Fugacity
Help
EPI Suite - Welcome Screen
Clear Input Fields
EPI Links
Output
C Full
(* Summary
C(=C(CI)CI)(CI)CI
Input Chem Name: Ethene, tetiachloro-
Name Lookup
Henry LC
Melting Point
Boiling Point:
Water Depth:
Wind Velocity:
Current Velocity:
atm-m /mole
Celsius
121.3 Celsius
Water Solubility:
Vapor Pressure:
Log Kow:
meters
meters/sec
meters/sec
206 mg/L
18.5 mm Hg
3.4t(
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.
!_if^
Figure_Apx C-l. Screen capture of EPlSuite™ parameters used to calculate fate and physical chemical
properties for PCE.
Page 579 of 636
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14590
14591
14592
14593
14594
14595
14596
14597
14598
14599
14600
14601
14602
14603
14604
14605
14606
14607
14608
14609
14610
14611
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Appendix D ENVIRONMENTAL EXPOSURES
EPA presents the industrial sectors for each condition of use category below. In cases where the
NPDES is unknown, no close analog could be identified, or the exact location of a chemical
loading is unknown, surface water concentrations were modeled using the "SIC Code Option"
within E-FAST 2014 ( 014b) to estimate potential occurrence of PCE shown in
TableApx D-l.
EPA also conducted a geospatial analysis at the watershed level (HUC-8 and HUC-12) to
compare the measured and predicted surface water concentrations and investigate if the facility
releases may be associated with the observed concentrations in surface water. Below in
Table Apx D-2, Table Apx D-3 and Table Apx D-4 EPA has broken out the occurrence of PCE
by facility, monitoring sites and location by State.
TableApx D-l provides the industrial sectors for each condition of use.
Table Apx D-l. Industry Sector Modeled for Facilities without Site-Specific Flow Data in
E-FAST 2014
Condition of Use
Industry Sector (SIC
Code Option)
OES: Manufacturing
Organic Chemicals
Manufacture
OES: Import/Repackaging
POTW (Industrial)
OES: Processing as a Reactant
Organic Chemicals
Manufacture
OES: Incorporation into Formulation
n/a
OES: OTVD (Includes releases for Closed-Loop Degreasing, Conveyorized
Degreasing, Web Degreasing, Cold Cleaning, and Metalworking Fluids)
Primary Metal Forming
Manufacture
OES: Aerosol Degreasing/Lubricants
n/a
OES: Dry Cleaning (commercial only)
n/a
OES: Dry Cleaning (industrial only)
n/a
OES: Adhesives, Paints, and Coatings
n/a
OES: Chemical Maskant
Metal Finishing
OES: Industrial Processing Aid
POTW (Industrial)
OES: Wipe Cleaning and Metal/Stone Polishes
n/a
OES: Other Spot Cleaning/Spot Removers (Including Carpet Cleaning)
n/a
OES: Other Industrial Uses
POTW (Industrial)
OES: Other Commercial Uses
POTW (Industrial)
OES: Waste Handling, Disposal, Treatment, and Recycling
POTW (Industrial)
n/a = Not applicable because a NPDES or surrogate NPDES was available in E-FAST 2014 (U.S. EPA 20.1.4b') to
obtain a site-specific stream flow for all facilities within the OES.
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14612
14613
14614
14615
TableApx D-2 and TableApx D-3 show the occurrence of PCE release via facilities and
monitoring sites for HUC 8 and HUC 12 respectively.
Table Apx D-2. Occurrence of P(
E Releases (Facilities) and Monitoring Sites By HUC-8.
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
Co-located PCE Releases (Facilities) and Monitoring Sites (n = 4 HUCs)
04040001
Little Calumet-Galien
440799.0
1783.8
IL.IN.MI
1
2
5
04050006
Lower Grand
1293837.6
5236.0
MI
1
1
4
07040001
Rush-Vermillion
711813.5
2880.6
MN.WI
1
1
1
11030012
Little Arkansas
910452.3
3684.5
KS
1
5
14
PCE Releases (Facilities) Only (n = 66 HUCs)
10190003
Middle South Platte-Cherry
Creek
1838438.0
7439.9
CO
5
0
0
02030105
Raritan
707463.2
2863.0
NJ
4
0
0
08080206
Lower Calcasieu
812177.5
3286.8
LA
4
0
0
12040104
Buffalo-San Jacinto
756769.3
3062.5
TX
4
0
0
02060003
Gunpowder-Patapsco
907202.4
3671.3
MD.PA
3
0
0
07120004
Des Plaines
931517.4
3769.7
IL.WI
3
0
0
08070204
Lake Maurepas
456253.8
1846.4
LA
3
0
0
02040201
Crosswicks-Neshaininy
347995.5
1408.3
NJ.PA
2
0
0
04120104
Niagara
871679.6
3527.6
CN.NY
2
0
0
05030201
Little Muskingum-Middle
Island
1161545.0
4700.6
OH.WV
2
0
0
07090002
Middle Rock
1172085.4
4743.3
IL.WI
2
0
0
07120005
Upper Illinois
644077.9
2606.5
IL
2
0
0
08090301
East Central Louisiana
Coastal
1728228.3
6993.9
LA
2
0
0
12020003
Lower Neches
709968.8
2873.1
TX
2
0
0
12040204
West Galveston Bay
776232.4
3141.3
TX
2
0
0
18070106
San Gabriel
579966.3
2347.0
CA
2
0
0
01090001
Charles
955681.2
3867.5
MA
1
0
0
02030103
Hackensack-Passaic
725724.6
2936.9
NJ.NY
1
0
0
02030104
Sandy Hook-Staten Island
454261.8
1838.3
NJ.NY
1
0
0
02060002
Chester-Sassafras
833436.9
3372.8
DE.MD.PA
1
0
0
03050107
Tyger
517390.6
2093.8
SC
1
0
0
03050111
Lake Marion
351158.0
1421.1
SC
1
0
0
03050204
South Fork Edisto
555149.8
2246.6
SC
1
0
0
03090206
Florida Southeast Coast
2352752.2
9521.3
FL
1
0
0
03160103
Buttahatchee
553396.1
2239.5
AL.MS
1
0
0
03160112
Upper Black Warrior
797270.7
3226.4
AL
1
0
0
Page 581 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
03160113
Lower Black Warrior
929969.4
3763.5
AL
1
0
0
04060101
Pere Marquette-White
1333169.6
5395.1
MI
1
0
0
04080201
Tittabawassee
926364.9
3748.9
MI
1
0
0
04110003
Ashtabula-Chagrin
401605.3
1625.2
OH,PA
1
0
0
04120103
Buffalo -Eighteenmile
457151.3
1850.0
NY
1
0
0
04120200
Lake Erie
6483450.8
26237.6
CN,MI,NY,OH,P
A
1
0
0
04130001
Oak Orchard-Twelvemile
685684.0
2774.9
CN,NY
1
0
0
04150403
Winooski River
680464.2
2753.7
VT
1
0
0
05020003
Upper Monongahela
296728.7
1200.8
PA,WV
1
0
0
05030101
Upper Ohio
1271402.1
5145.2
OH,PA,WV
1
0
0
05040006
Licking
499187.6
2020.1
OH
1
0
0
05050008
Lower Kanawha
591554.2
2393.9
wv
1
0
0
05080001
Upper Great Miami,
Indiana, Ohio
1607903.9
6507.0
IN,OH
1
0
0
05080002
Lower Great Miami,
Indiana, Ohio
883871.2
3576.9
IN,OH
1
0
0
05120201
Upper White
1740657.8
7044.2
IN
1
0
0
05140101
Silver-Little Kentucky
807385.6
3267.4
IN,KY
1
0
0
07120003
Chicago
419754.7
1698.7
IL,IN
1
0
0
07120006
Upper Fox
988245.7
3999.3
IL,WI
1
0
0
07140106
Big Muddy
1526746.1
6178.5
IL
1
0
0
08070201
Bayou Sara-Thompson
444709.9
1799.7
LA,MS
1
0
0
10190004
Clear
365027.3
1477.2
CO
1
0
0
11030017
Upper Walnut River
620982.8
2513.0
KS
1
0
0
11110104
Robert S. Kerr Reservoir
1128010.3
4564.9
AR,OK
1
0
0
11130303
Middle Washita
1605161.6
6495.9
OK
1
0
0
12030102
Lower West Fork Trinity
969001.7
3921.4
TX
1
0
0
12040201
Sabine Lake
636218.6
2574.7
LA,TX
1
0
0
12070104
Lower Brazos
1051241.4
4254.2
TX
1
0
0
12110201
North Corpus Christi Bay
111266.8
450.3
TX
1
0
0
12110202
South Corpus Christi Bay
322454.2
1304.9
TX
1
0
0
16020204
Jordan
520846.5
2107.8
UT
1
0
0
17020010
Upper Columbia-Entiat
958508.9
3878.9
WA
1
0
0
17050114
Lower Boise
850233.1
3440.8
ID
1
0
0
17110012
Lake Washington
388533.5
1572.3
WA
1
0
0
18050002
San Pablo Bay
784983.8
3176.7
CA
1
0
0
18070102
Santa Clara
1040515.7
4210.8
CA
1
0
0
18070203
Santa Ana
1084241.9
4387.8
CA
1
0
0
Page 582 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
PCE Monitoring Sites Only (n = 47 HUCs)
02020004
Mohawk
1632666.9
6607.2
NY
0
1
1
02040105
Middle Delaware-
Musconetcong
869995.3
3520.8
NJ.PA
0
1
3
02050205
Pine
627641.5
2540.0
PA
0
1
2
02050206
Lower West Branch
Susquehanna
1158170.9
4687.0
PA
0
1
3
02050301
Lower Susquehanna-Penns
926808.1
3750.7
PA
0
1
6
02070004
Conococheague-Opequon
1457399.0
5897.9
MD.PAVAWV
0
6
04010201
St. Louis
1882043.1
7616.4
MN.WI
0
1
4
04010302
Bad-Montreal
832709.3
3369.9
MI.WI
0
1
4
04030101
Manitowoc-Sheboygan
1043247.9
4221.9
WI
0
1
4
04030204
Lower Fox
414795.8
1678.6
WI
0
1
3
04040002
Pike-Root
267751.0
1083.5
IL.WI
0
1
4
04050001
St. Joseph
3016829.4
12208.7
IN.MI
0
1
4
04050003
Kalamazoo
1300194.9
5261.7
MI
0
1
1
04080206
Saginaw
160773.8
650.6
MI
0
1
4
04090003
Clinton
510065.3
2064.2
MI
0
1
4
04090004
Detroit
567874.0
2298.1
CN.MI
0
1
4
04100009
Lower Maumee
689823.7
2791.6
OH
0
17
04100012
Huron-Vermilion
488453.3
1976.7
OH
0
1
3
04110001
Black-Rocky
572567.0
2317.1
OH
0
1
1
04110002
Cuyahoga
519309.5
2101.6
OH
0
1
3
04130003
Lower Genesee
682891.3
2763.6
NY
0
1
4
04140101
Irondequoit-Ninemile
445757.0
1803.9
NY
0
1
3
04140203
Oswego
93064.4
376.6
NY
0
1
4
06030003
Upper Elk
821468.2
3324.4
AL.TN
0
8
07090004
Sugar
486750.9
1969.8
IL.WI
0
1
3
07140102
Meramec
1375977.1
5568.4
MO
0
7
08040302
Castor
612659.1
2479.3
LA
0
3
10300102
Lower Missouri-Moreau
2176536.7
8808.1
MO
0
1
1
11140207
Lower Red-Lake Iatt
912489.8
3692.7
LA
0
3
11140209
Black Lake Bayou
579878.2
2346.7
LA
0
1
2
12100303
Lower San Antonio
950344.1
3845.9
TX
0
1
1
13020201
Rio Grande-Santa Fe
1197851.1
4847.5
NM
0
1
3
13020203
Rio Grande-Albuquerque
2057935.0
8328.2
NM
0
1
3
14030005
Upper Colorado-Kane
Springs
1455869.5
5891.7
COUT
0
5
9
14060008
Lower Green
1195181.0
4836.7
UT
0
1
2
Page 583 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
15010008
Upper Virgin
13972074
5654.3
UT
0
2
2
15060106
Lower Salt
666211.2
2696.1
AZ
0
5
12
15070102
Aqua Fria
1758350.5
7115.8
AZ
0
7
11
17090001
Middle Fork Willamette
874861.9
3540.4
OR
0
1
1
17090002
Coast Fork Willamette
426542.2
1726.2
OR
0
2
2
17090003
Upper Willamette
1198500.4
4850.2
OR
0
3
5
17090004
Mckenzie
857010.6
3468.2
OR
0
4
5
21010005
Eastern Puerto Rico
914478.3
3700.8
PR
0
1
2
14616
14617
Page 584 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Table Apx D-3. Occurrence of PCE Releases (Facilities) and Monitoring Sites By HUC-12.
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
Co-located PCE Releases (Facilities) and Monitoring Sites (n = 1 HUC)
040400010509
Willow Creek-Burns Ditch
13501.8
54.6
IN
1
1
1
PCE Releases
(Facilities) Only (n =81 HUCs)
010900010402
Outlet Saugus River
17633.5
71.4
MA
1
0
0
020301030802
Peckman River-Passaic River
22354.8
90.5
NJ
1
0
0
020301040204
Morses Creek-Arthur Kill
18931.5
76.6
NJ.NY
1
0
0
020301050306
Devils Brook
9890.5
40.0
NJ
1
0
0
020301050312
Lower Millstone River
31839.8
128.8
NJ
1
0
0
020301050504
Green Brook
32590.3
131.9
NJ
1
0
0
020301050505
Lawrence Brook
29837.9
120.8
NJ
1
0
0
020402010202
West Branch Neshaminy Creek
15964.6
64.6
PA
1
0
0
020402010404
Van Sciver Lake-Delaware River
16914.3
68.5
NJ.PA
1
0
0
020600020202
Little Elk Creek
26942.3
109.0
MD.PA
1
0
0
020600030902
Dead Run-Gywnns Falls
31450.3
127.3
MD
0
0
030501070305
Lower South Tyger River
29288.0
118.5
SC
1
0
0
030501110109
Lake Marion-Santee River
165146.
0
668.3
SC
1
0
0
030502040108
Lower Shaw Creek
32220.3
130.4
SC
1
0
0
030902061003
Lake Worth Inlet-Boynton Inlet
Frontal
39017.9
157.9
FL
1
0
0
031601030202
Cannon Mill Creek-Beaver Creek
28263.4
114.4
AL
1
0
0
031601120101
Headwaters Valley Creek
34201.6
138.4
AL
1
0
0
031601130204
Goose Pond-Black Warrior River
25818.5
104.5
AL
1
0
0
040500060712
Lloyd Bayou-Grand River
31929.6
129.2
MI
1
0
0
040601010904
White Lake-White River
39040.6
158.0
MI
1
0
0
040802010604
Prairie Creek-Tittabawassee River
25251.7
102.2
MI
1
0
0
041100030504
Doan Brook-Frontal Lake Erie
28193.7
114.1
OH
1
0
0
041201030401
Smoke Creek
21267.2
86.1
NY
1
0
0
041201040604
City of North Tonawanda-Niagara
River
8541.4
34.6
NY
1
0
0
041201040605
Niagara Falls-Niagara River
21666.5
87.7
CN.NY
1
0
0
041202000300
Lake Erie
6359988
.3
25738.
0
CN.MI.NY.
OH.PA
1
0
0
041300010703
Headwaters Eighteeninile Creek
15270.7
61.8
NY
1
0
0
041504030101
Headwaters Stevens Branch
22103.3
89.5
VT
1
0
0
050200030307
Cobun Creek-Monongahela River
21730.5
87.9
WV
1
0
0
050301011103
Carpenter Run-Ohio River
23323.8
94.4
OH.PAWV
1
0
0
050302011004
Haynes Run-Ohio River
19386.4
78.5
OH.WV
2
0
0
050400060409
Beaver Run-South Fork Licking
River
19150.9
77.5
OH
1
0
0
Page 585 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
050500080304
Scary Creek-Kanawha River
20472.1
82.8
WV
1
0
0
050800012005
Poplar Creek-Great Miami River
34854.0
141.1
OH
1
0
0
050800020105
Town of Oakwood-Great Miami
River
16944.9
68.6
OH
1
0
0
051202011205
Dollar Hide Creek-White River
30882.8
125.0
IN
1
0
0
051401010903
Mill Creek Cutoff
20966.7
84.8
KY
1
0
0
070400010206
Town of Pine Bend
31880.6
129.0
MN
1
0
0
070900021402
Delavan Lake
22265.1
90.1
WI
1
0
0
070900021502
City of Beloit-Rock River
30612.6
123.9
IL,WI
1
0
0
071200030407
Grand Calumet River-Little
Calumet River
17191.8
69.6
IL,IN
1
0
0
071200040905
Des Plaines River
23822.3
96.4
IL
0
0
071200050106
Walley Run-Aux Sable Creek
12878.4
52.1
IL
1
0
0
071200050705
Bills Run-Illinois River
33003.8
133.6
IL
1
0
0
071200061206
Jelkes Creek-Fox River
25551.9
103.4
IL
1
0
0
071401060407
Ewing Creek
14114.5
57.1
IL
1
0
0
080702010402
Devils Swamp-Bayou Baton Rouge
17328.4
70.1
LA
1
0
0
080702040101
Bayou Francois
16194.6
65.5
LA
1
0
0
080702040103
Grand Goudine Bayou-New River
17644.3
71.4
LA
1
0
0
080702040302
Hope Canal-Pipeline Canal
18663.6
75.5
LA
1
0
0
080802060301
Maple Fork-Bayou d'Inde
22308.4
90.3
LA
0
0
080802060302
Bayou Verdine-Calcasieu River
24546.0
99.3
LA
1
0
0
080802060303
Prien Lake-Calcasieu River
29606.9
119.8
LA
1
0
0
080903010307
Town of Westwego-Main Canal
39569.2
160.1
LA
0
0
101900030304
Cherry Creek-South Platte River
35554.2
143.9
CO
0
0
101900040404
Outlet Clear Creek
19355.3
78.3
CO
1
0
0
110300120204
Headwaters Dry Turkey Creek
30940.1
125.2
KS
1
0
0
110300170403
Constant Creek-Walnut River
28347.5
114.7
KS
1
0
0
111101040611
Massard Creek
10720.0
43.4
AR
1
0
0
111303030708
Outlet Caddo Creek
26104.7
105.6
OK
1
0
0
120200030406
Union Canal-Neches River
26733.6
108.2
TX
1
0
0
120200030407
Grays Bayou-Neches River
39760.5
160.9
TX
1
0
0
120301020206
Brogden Branch-Town Creek
14887.3
60.3
TX
1
0
0
120401040703
Vince Bayou-Buffalo Bayou
38130.8
154.3
TX
0
0
120401040706
Goose Creek-Frontal Galveston
Bay
37289.7
150.9
TX
1
0
0
120402010300
Salt Bayou
212334.
8
859.3
TX
1
0
0
120402040100
Clear Creek-Frontal Galveston Bay
190566.
3
771.2
TX
1
0
0
Page 586 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
120402040400
Mustang Bayou
183973.
7
744.5
TX
1
0
0
120701040505
Outlet Barzos River
35803.4
144.9
TX
1
0
0
121102010001
Rincon Bayou
28406.5
115.0
TX
1
0
0
121102020107
Tule Lake
12284.3
49.7
TX
1
0
0
160202040304
City Creek
11166.6
45.2
UT
1
0
0
170200100307
Rainey Spring-Columbia River
21142.9
85.6
WA
1
0
0
170501140403
Crane Creek-Boise River
18624.7
75.4
ID
1
0
0
171100120301
Bear Creek
30140.7
122.0
WA
1
0
0
180500020801
San Pablo Bay Estuaries
85721.1
346.9
CA
1
0
0
180701020507
Gorman Creek
23547.6
95.3
CA
1
0
0
180701060102
Lower Dominguez Channel
36125.6
146.2
CA
1
0
0
180701060701
Long Beach Harbor
33394.5
135.1
CA
1
0
0
180701060703
San Pedro Bay
40623.1
164.4
CA
1
0
0
180702031003
Greenville Banning Channel-Santa
Ana River
22359.3
90.5
CA
1
0
0
PCE Monitoring Sites Only (n = 67 HUCs)
020200040908
Lower Canajoharie Creek
13216.2
53.5
NY
0
1
1
020401050911
Buck Creek-Delaware River
15442.9
62.5
NJ,PA
0
1
3
020502050607
Furnace Run-Pine Creek
27631.1
111.8
PA
0
1
2
020502061103
Beaver Run-Chillisquaque Creek
26019.5
105.3
PA
0
1
3
020503010603
Lower West Branch Mahantango
Creek
13445.1
54.4
PA
0
1
6
020700040702
Dennis Creek-Back Creek
32533.8
131.7
PA
0
1
4
020700041009
Sharmans Branch-Antietam Creek
36619.8
148.2
MD
0
1
2
040102011503
City of Cloquet-Saint Louis River
36671.5
148.4
MN
0
1
4
040103020702
Camerons Creek-Bad River
13498.0
54.6
WI
0
1
4
040301010605
Manitowoc River
11648.4
47.1
WI
0
1
4
040302040405
City of Green Bay-Fox River
19046.2
77.1
WI
0
1
3
040400010603
Calumet River-Frontal Lake
Michigan
34563.8
139.9
IL,IN
0
1
4
040400020101
Wind Point-Frontal Lake Michigan
16148.3
65.3
WI
0
1
4
040500012210
City of Niles-Saint Joseph River
8758.5
35.4
MI
0
1
4
040500030911
Peach Orchid Creek-Kalamazoo
River
15046.6
60.9
MI
0
1
1
040500060708
Jubb Bayou-Grand River
11389.8
46.1
MI
0
1
4
040802060201
Crow Island-Saginaw River
33918.2
137.3
MI
0
1
4
040900030402
Cranberry Marsh Drain-Clinton
River
21236.7
85.9
MI
0
1
4
040900040406
Ashcroft Sherwood Drain-River
Rouge
12735.6
51.5
MI
0
1
4
Page 587 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
041000090509
Lower Beaver Creek
10727.3
43.4
OH
0
1
2
041000090510
Lick Creek-Maumee River
14952.3
60.5
OH
0
1
2
041000090603
Haskins Road Ditch-Maumee River
10054.5
40.7
OH
0
1
1
041000090804
Heilman Ditch-Swan Creek
23569.6
95.4
OH
0
1
2
041000090903
Crooked Creek-Maumee River
12075.0
48.9
OH
0
2
5
041000090904
Delaware Creek-Maumee River
10576.9
42.8
OH
0
3
5
041000120204
Town of Vermilion-Vermilion
River
17985.5
72.8
OH
0
1
3
041100010203
Rocky River
16199.9
65.6
OH
0
1
1
041100020602
Village of Independence-Cuyahoga
River
10848.3
43.9
OH
0
1
3
041300030704
Genesee River
14336.9
58.0
NY
0
1
4
041401010703
Allen Creek
20188.5
81.7
NY
0
1
3
041402030204
Oswego River
11026.9
44.6
NY
0
1
4
060300030201
Bradley Creek
30268.8
122.5
TN
0
8
070400010102
Lock and Dam Number Three-
Mississippi River
40106.3
162.3
MN,WI
0
1
1
070900040201
Badger Mill Creek
21661.8
87.7
WI
0
1
3
071401020703
Stater Creek-Meramec River
28521.9
115.4
MO
0
1
2
071401021001
Hamilton Creek-Meramec River
34956.9
141.5
MO
0
1
2
071401021002
Grand Glaize Creek-Meramec
River
29896.0
121.0
MO
0
1
2
071401021004
Meramec River
27977.7
113.2
MO
0
1
1
080403020401
Caney Creek Reservoir
26803.0
108.5
LA
0
3
103001020709
Black Branch-Perche Creek
12012.4
48.6
MO
0
1
1
110300120303
110300120303-Little Arkansas
River
23920.3
96.8
KS
0
1
4
110300120408
City of Sedgwick-Little Arkansas
River
27404.6
110.9
KS
0
4
10
111402070401
Sibley Lake
24862.2
100.6
LA
0
3
3
111402090404
Grand Bayou
34707.7
140.5
LA
0
1
2
121003030306
Salt Creek-Ecleto Creek
18817.5
76.2
TX
0
1
1
130202010209
Canada de Cochiti-Rio Grande
20418.4
82.6
NM
0
1
3
130202030107
Town of Corrales-Rio Grande
26313.8
106.5
NM
0
1
3
140300050205
Outlet Courthouse Wash
18177.4
73.6
UT
0
1
1
140300050307
Negro Bill Canyon-Colorado River
19473.5
78.8
UT
0
1
2
140300051001
Little Canyon-Colorado River
32843.3
132.9
UT
0
4
140300051002
Bull Canyon-Colorado River
32166.0
130.2
UT
0
1
2
140600080708
Upheaval Canyon-Green River
20259.5
82.0
UT
0
1
2
150100080109
Lower North Fork Virgin River
34874.9
141.1
UT
0
2
2
150601060202
Upper Indian Bend Wash
27058.2
109.5
AZ
0
1
3
Page 588 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
HUC8
Name
Acres
Square
km
States
No. of
Facilities
No. of
Monitoring
Sites
No. of
Monitoring
Samples in
HUC
150601060306
City of Phoenix-Salt River
87618.1
354.6
AZ
0
2
4
150601060307
Town of Santa Maria-Salt River
34122.5
138.1
AZ
0
2
5
150701020606
Upper Arizona Canal Diversion
Channel
15465.9
62.6
AZ
0
1
3
150701020607
Lower Arizona Canal Diversion
Channel
19739.1
79.9
AZ
0
1
1
150701020806
Middle Skunk Creek
28304.4
114.5
AZ
0
1
3
150701020807
Lower Skunk Creek
24449.6
98.9
AZ
0
2
2
150701020809
City of Peoria-New River
38282.5
154.9
AZ
0
2
2
170900011003
Mill Race-Middle Fork Willamette
River
12666.2
51.3
OR
0
1
1
170900020405
Papenfus Creek-Coast Fork
Willamette River
17460.5
70.7
OR
0
2
2
170900030601
Sring Creek-Willamette River
29305.8
118.6
OR
0
3
5
170900040705
Camp Creek
16999.1
68.8
OR
0
1
1
170900040706
Walterville Canal-McKenzie River
33735.2
136.5
OR
0
3
4
210100050503
Cienaga de las Cucharillas
Drainage Watershed
6557.0
26.5
PR
0
1
2
14619
14620
Page 589 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
14621 Table Apx D-4 provides a list of states/territories with facilities that have releases of PCE and/or
14622 monitoring sites for the year of 2016
14623 Table Apx D-4. States with Monitoring Sites or Facilities in 2016
State Name
PCE Facility3
PCE Monitoring Site
PCE Facility or
Monitoring Site
Alabama
X
X
Arizona
X
X
Arkansas
X
X
California
X
X
Colorado
X
X
Florida
X
X
Idaho
X
X
Illinois
X
X
Indiana
X
X
X
Kansas
X
X
X
Kentucky
X
X
Louisiana
X
X
X
Maryland
X
X
X
Massachusetts
X
X
Michigan
X
X
X
Minnesota
X
X
X
Missouri
X
X
New Jersey
X
X
X
New Mexico
X
X
New York
X
X
X
Ohio
X
X
X
Oklahoma
X
X
Oregon
X
X
Pennsylvania
X
X
X
Puerto Rico
X
X
South Carolina
X
X
Tennessee
X
X
Texas
X
X
X
Utah
X
X
X
Vermont
X
X
Washington
X
X
West Virginia
X
X
Wisconsin
X
X
X
Total
27
19
33
14624
14625
a. PCE Facility is based
facility was mapped
on the location of the facility mapped. For indirect releasers, the receiving
if known.
Page 590 of 636
-------
14626
14627
14628
14629
14630
14631
14632
14633
14634
14635
14636
14637
14638
14639
14640
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Appendix E BENCHMARK DOSE ANALYSIS
The following is a summary of the cancer dose response modeling from Appendix D of U.S. EPA
(2012e).
E.l Model Selection Details for Tumor Sites from JISA (1993)
TableApx E-l. Model predictions for hepatocellular tumors in male mice (JISA, 1993)a, using
several dose metrics and multistage cancer model
Goodness of fit
Model
stages
/>-valucb
Largest standardized
residual(s)
AIC
BMDio
BMDLio
Conclusion
Total liver oxidative metabolism (mg/kg° 75-day)
One
0.24
1.1, low-dose
-1.2, mid-dose
239.7
2.9
2.1
All three fits were adequate by
conventional criteria.13 There was no
Two
0.16
-0.7, control
1.1, low-dose
240.8
6.4
2.2
statistical improvement in adding
higher-order coefficients (using
likelihood ratio test); one-stage fit
Three
0.18
-0.7, control
1.0, low-dose
240.6
6.5
2.2
was selected.
TCA AUC in liver (mg-hr/L-day)
One
0.25
1.0, low-dose
-1.2, mid-dose
239.7
97.1
68.8
All three fits were adequate by
conventional criteria.13 There was no
Two
0.17
-0.7, control
1.1, low-dose
240.8
209.9
72.8
statistical improvement in adding
higher-order coefficients (using
likelihood ratio test); one-stage fit
Three
0.19
-0.7, control
1.0, low-dose
240.6
213.9
73.8
was selected.
Administered PCE concentration (ppm)
One
0.27
1.2, low-dose
-1.0, mid-dose
239.5
3.9
2.7
All three fits were adequate by
conventional criteria.13 There was no
Two
0.16
-0.8, control
1.1, low-dose
240.9
9.0
2.8
statistical improvement in adding
higher-order coefficients (using
likelihood ratio test); one-stage fit
Three
0.17
-0.8, control
1.1, low-dose
240.8
8.2
2.9
was selected.
a Incidence data and human equivalent continuous exposure estimates provided in Table 3-6.
b Goodness-of-fit p-valucs <0.05 for a preferred model, or <0.10 when considering many models, fail to
meet conventional goodness-of-fit criteria. In addition, visual fit and residuals (within +2 units) are
considered. Best-fit model is highlighted in bold; output for best-fit models provided in following
pages.
AIC = Akaike's Information Criteria, BMD = benchmark dose, BMDL = lower bound benchmark dose.
Page 591 of 636
-------
14641
E.i.i
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Modeling Output for Male Mice, Hepatocellular Tumors (JISA, 1993)
E. 1.1.1 With total oxidative metabolism in liver as dose metric
Qj8
07
0.6
05
DA
03
02
0.1
Mu ft stage Cancer Mate! wttft C.S5 Oonlldsftoe Level
Muldstage Cancer
LIp earejfTacoi3Dcri
.5 VOL... ESC
20 25
tfcee
30 35 4B Ł5
Figure D-l One-degree multistage model fit to hepatocellular tumors in male
mice (JISA, 1993). with HMD and BMDL at 109 b extra risk, using total
oxidative metabolism ill liver (mg/kg®' "-day)
Multistage Cancer Model. (Version: 1-7; Date: 05/16/2009)
The forre. of the probability function is:
Piresponse! ¦ background 4 (1-background I 4 f1-EXP(
-beta1 * dose A1J]
The pnrr^roter net an are restricted to be positive
Dependent variable ¦ Response
Independent variable ¦ lose
Total mxfccr cf observations ¦ 4
Total nunber of records with missing valises ¦ 0
Total number of parameters in model m 2
Total nimber of specified parameters ¦ 0
Degree of polynomial ¦ 1
Page 592 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Maximum nunber of iterations ¦ 250
Relative Function Convergence has been net to: ie-000
Parameter Convergence has been net to: le-000
Default Initial Parameter Values
Background ¦ 0.265739
Beta 1.1) - 0.0395060
HsynptOtic Correlation Har.rix of Parameter Estinates
Background Beta111
Background 1 -0.53
Bet a(1) -0.53 1
Parameter Estusates
Variable
Background
Beta 11)
Estimate
0.301266
0.03Ł1674
95.0% Wald Confidence Interval
Lower Conf. Limit r.rppnr Conf. Limit
Indicates that this value is not calculated.
Model
Full node!
Fitted nodel
Reduced isodel
AIC:
Analysis of Deviance Table
Deviance
Log 111kellhoodJ
-lit.442
-117.644
-112.99
234.$66
~ Far am'
4
2
1
2.30477
33.097?
P-valne
0.246
<.0001
Goodness of Fit
Dose
Est. Prob.
Expected
Observed
Size
Scaled
Residual
0.0000
0.3013
13.650
13.000
46
-0.276
2.2500
0.3559
17.430
21.000
49
1.063
9.3000
0.4625
23.150
19.000
40
-,.201
33.6000
0.7927
36.fi 4 4
40.000
4 9
0.400
Chi"2 - 2.01
?-value ® 0.244 0
Benchmark Dose Computation.
Specified effect ¦
Risk Type
Confidence level ¦
BHD -
HM.jL ¦
BHDCI -
0.1
Extra risk
0.95
2.91314
2.06167
4.<9464
Taken together, [2.06107, 4.4 94641 is a 90
interval"for the HID
1* two - n: ded ccr.f l dence
Multistage Cancer Slope Factor
0.0464996
Page 593 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
E.1.1.2 With TCA AUC in liver as dose metric
Multistage Cancer Moot wnrD.95 Cwfllderce Lews
Mu *: stage C-arcer
Lre ar e*trap:« ac or
/f
emcl
500
dose
Figure D-2, One-degree multistage model St to hepatocellular tumors in
male mice (JISA, 1993), yvitli BMD and BMDL at 10% extra risk, using TC A
AUC as dose metric (mg-lir/L-d).
t-?jl 11 stage Cancer Modal. (Var9i.cn: 1.7; Data: 05/16/20083
Tiie form at tlie probability Junction la:
F[response]
TSie parameter betas arc rea trietod to be positive
baok.ground + < 1 -background) * [ 1 -EXP
-beŁal+dose*l) J
Dependent variable « Basponae
Independent variable ¦ Do-ae
Total r.i'fher of obaervations — 4
Total nusaber of records with nu.aai.ng values
Total m Tiber of parameters ir. model — 2
Total nuaber of apeoi.fi.ed parameters * 0
Degree of polynomial *¦ 1
Maximum nuaber of iterations * 250
Relative Function Convergence has been aet to: le-008
Parameter Convergence has been, set to: le-008
14647
Default Initial Parameter Values
Background = 0.283935
Beta(1) » 0.0611S591
Asymptotic Correlation Matrix of Paramoter Estimates
Page 594 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Bainii.n1 Bi-.i i-
BackgzauMl 1 -u jj
BstaU} -0.S3 1
War ubl( lituita
«tSK
r»aa>ur ¦atua.tiM
9S„« BM CcBtiduca Intwml
ami. Krr. Imr Cent. Limit Qfcpax Con*. Limit
tint Una wmlam l.» not omloiiLatad.
of Dor lane* TuMa
tftliWilllmmH I kai'i Daruncm xaat d.f. MHw
-11« «« 4
1 2.M3M 2 #.24
-132. M 1 33,#MT 3
AIC: 23S. SiS
Bat._Frob.
s3:S 8:8S
1121. lftM a.ttm
Ott-2 - 2.*IS d.f. « 2 Hiln - O.UTf
Si.iifjiixk EC.SO r^mpuLmtim
Bpaslfimd «Łfaet « 0 1
* Ex 1.xa i~i.sk
Iftvoj. - %-.M
BŁ - ft. 1142
14®,'M
together, (Ł8.7915, 14b. !k i i* a *G * two-Jiidad e®mŁŁ«Sane»
lotKcval far th» a®
Cas«®r Slop® Factor * Q.&M.4SM7
14648
14649
Page 595 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
E.1.1.3 With administered PCE concentration (ppm) as dose metric
MMUSageCancer Mode «tth G.95 Cwir dence .ft'e;
Mj tstage Cancer
UrwarextapcfaOan
/
B^-L Ej.C
CI 5 ID 15 20 25 30 35 40 45
¦dose
Figure D-3. One-decree multistage model fit to hepatocellular tumors ill
male mice (JISA, 1993), with BMD and BMDL at 10% eitra risk, using
administered tetrachloioediyleue concentration (ppm),
Mult-:.stage Cancer Model. (Version: 1.7; Date: Q5/1€/2QQB)
The form of the probability f-or.cti.ori is:
P [response] = background + (1—background) * [1—EXE1 (—betal*dose"!J ]
The parameter betas are restricted to be positive
Dependent variable — Response
Independent variable — Dose
her of observations! — 4
sber of records with missing values = 0
_ota_
Total
Total number or parace^ers m rociel
Total r.fjrrber of specified parameters
Degree of polynomial — 1
HaKizr.um number of iterations — 250
Relative Function Convergence has been sec to: le—000
Parameter Convergence has beer, se- to: le—000
Default Initial Parar.eter Val
Background = Q.3071&3
Beta(l) = 0.0250722
14651
Page 596 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Asymptotic CarrelŁ7 - :r. litEiK of r'araoeter Estimates
Background 2e~Ł il)
- -Q.4B
r;:« - -:.i: I
Paraamstfer Estimates
55 . 0% Wa.ld Ccr.f idenze
IliteEVm 1
"sr-arle Istirsm StcL. Err. Low: I or. 5 L-Js.it C^-cer Conf.
Limit
* - I'ndaca-e? that- fchi? —alue is r^at csl:v™5,ted.
Ar.al -sis of D«viar.ce Table
Lrdel Log iiiieliL-c rd f Param's Ceviar.ce Test- d. f. F~ya.lue
Fvill rrdel -11 Ł .. 4-a .2 4
fitted rcwl -ll1-.-;: 2 Ł.55226 2 0.2^
7 til-zee. rc^l _1 ;1. ; : 1 -13 ..CPv'? 2- < „ C C C
-oae
C.DC00
. :..;
5.DC CO
-i: ....
Chx"2 — Z,€-Z
Sooc^s¦¦
i.:": e :t - : I: s
d,Ł.
-1: -r 4:.:,
F—lvalue = 0.2704
Sise
= tv : .'ft.
4€
49
1. _c-i
m
-,,-5:
49
Bes-ckmaxk Base Ccrasutst-icss
Z'ieffect = C„1
Ri?h T^'C = Eittra risk
C:r.Ł*ce level = I.?z
E..I1 =
Talce;-. tc rether ,• Z.~-
i:r.ter""al for the r!II
Cascex Slope Factor
is a 5*C % cwo—aided confidence
4
TableApx E-2. Model predictions for hepatocellular tumors in female mice (JISA, 1993)a, using
Goodness of fit
Model
stage
/>-valucb
Largest
standardized
residual(s)
AIC
BMDio
BMDLio
Comments
Conclusions
Total liver oxidative metabolism (mg/kg
075-day)
One-stage
0.14
-1.4, mid-dose
154.9
3.7
2.8
Adequate fit
Selected two-
Two-stage
0.82
-0.18, low-dose
152.8
8.4
4.0
Adequate fit
degree multistage,
based on likelihood
Three-stage
0.82
-0.18, low-dose
152.8
8.4
3.9
Adequate fit
ratio test.
TCA AUC in liver (mg-hr/L-day)
One-stage
0.13
-1.4, mid-dose
155.1
129
98
Adequate fit
Selected two-
Page 597 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Two-stage
0.82
-0.18, low-dose
152.9
292
141
Adequate fit
degree multistage,
based on likelihood
ratio test.
Three-stage
0.82
-0.18, low-dose
152.9
292
139
Adequate fit
Administered PCE concentration (ppm)
One-stage
0.36
-1.1, mid-dose
153.0
5.0
3.8
Adequate fit
Selected one-
degree multistage;
no statistical
improvement in
adding higher order
parameters.
Two-, three-
stage
0.83
-0.1, low-dose
152.8
9.7
4.3
Identical fits
resulted from both
models
14656
14657 incidence data provided in Table 5-13, and dose metrics provided in Table 3-6; both are included in
14658 following output.
14659 b Values <0.05 for a preferred model, or <0.10 when considering a suite of models, fail to meet
14660 conventional goodness-of-fit criteria. In addition, visual fit and residuals (within +2 units) are
14661 considered. Best-fit model is highlighted in bold; output for best-fit models provided in following
14662 pages.
14663
Page 598 of 636
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PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
E.1.2 Modeling Output for Female Mice, Hepatocellular Tumors (JISA, 1993)
Ą
I
E. 1.2.1 With total oxidative metabolism in liver as dose metric
MuHstage Cancer Mocsel wifrO.'SS Confidence Level
D.e
D.7
D.6
D.5
0.4
D.3
0.2
D.1
0
Multistage Cancer
Linear exfanclaticn
10
15
cose
20
25
30
Figure D-4, Two-degree multistage model fit to hepatocellular tumors in
female mice (USA. 1993). yrith BMD and BMDL at 10% extra risk.
Kultistage Cancer Model. (Version: 1,7; Dare: 05/16/200Q;<
Input Cata F1 le: C: \tfsepaSBHDS2 l\m5C_.TISA: WHFJSepAC jnxnset_Ferc-1_h5LiltiCanc2jQ.1. (dI
The fom of the probability function Is:
F | response 1 = background ¦+ (i-baclcgcoisncl] 4 ^ I-EXPt;
—betal* dose'"' 1 -beta2*dbr,.us"21 ]
The parajacster betas are restricted to be positive
Dependent variable ¦ Response
Independent variable ¦ Dose
Total nunsber of observations ¦ 4
Total nrazber of records with missing values ¦ 0
Total number of parameters in model ¦ 3
Total mmber of specified par.imer.ers ¦ 0
Degree of polynomial ¦ 2
Haaciimmi nunher of iterations * 250
Relative Function Convergence has been set r.o: le-OOS
Parameter Convergence has been set to: ie-000
Page 599 of 636
-------
PEER REVIEW DRAFT. DO NOT CITE OR QUOTE
Derate* Initial l'ar.r,»r»r Va,;u«3
tor.tqcountfl <-
Sera d i . u,«5:>6OT2»
SetaC'i » O.OM.MXM
flsynptrfi- >:orr«i3f s«s Xsrrjx si Karameter txniate.i
Ssctgrounrt fates s.i ItRTsiS;
Bsatcfraiaxl ; -0.fi!* 0,14
a»t»a> -fc.« S -<).»>
8cta.;2i ft. >9 -(>,« I
ta.3» llils Hont*j.-»r»M -r«r,eru\n
Vsrtafcie Bst»,af« ; rr . tower Cost. Lisa? trpj»jr rtonf, Ltatt
S3-|Ł5|Tf«lfSa
arr.a:;; a.OSWC Jig
sera;?: u..M4»C?S«:
• - Indicates ttvtr ents vnmc is not :"s;ls?#ri.
ficaiysiJi at swisin^e *Txt3.«
i,55;.tiM!iiho3<1i ~ farsa'sr Eevjanse test tt.t.
-M.i-I: 4
*2U 3 =;.0i63i:« t a.Kit
-lie. 26 .1 «S.K32 ;i <.J00l
iS2.MŁ
Ci-iotl-ess or Fit
iScsied
:*«#
. ^PrAt>.
Erasers t»fl
•auiMM"»3
?» :m
Hessauai
O.otet
a.
*. h ^
1.000
i-J
C. :04
2.liftt
3.0&C
4V
-fi.
;,sŁ»&
i.MW
?.Ł«
49
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14667
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E.1.2.2 With TCA AUC in liver as dose metric
Multistat Cancer Modei wift 0.95 Confidence Level
D.3
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Lin ear extrapolation
BMD
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Figure D-5. Two-degree multistage model fit to hepatocellular tumors in
female mice (USA, 1993), with BMD and BMDL at 10% eitra risk,
Multistage Cancer Model. (VersLon: 1.7; Da-o: 05/16/2005)
Input Cata Flic: C:\UscpaVEHD521\msc_JISAi933_MF_HepAC_tcaADC_Perc3jSultiCanc2_0. 1.
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Beta 1.21 » 3
.feriwsptotie Carraia&tar. Hsr.rlx c
Background Bet*!;: w.-r.a
Hacfcgraawf 1 -O.S» 0.6
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With administered PCE concentration (ppm) as dose metric
i1
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0.6
D.7
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Figure
female
D-6. One-degree multistage model fit to hepatocellular tumors in
mice (JISA. 1993), with BMD and BMDL at 10% extra risk.
hSiltlstagc Cancer Model- (Version; 1 .h Date: Q5/i6/20flfi3i
The form at the probability function is:
P[ response! ¦ background + (l-baclcground| * ( i-EXP(-beta 1 * dose'-11 I
The parane-er betas are restricted to be positive
Dependent variable ¦ Response
Independent variable ¦ Dose
Total mznber of observations ¦ 4
Total nisnber of records with missing valises ¦ 0
Total nrmher of parameters in model ¦ 2
Total r.ohcr of specified parage-era * 0
Degree of polynoaiial ¦ 1
Kaximun nnnher of iterations ¦ 250
Relative Function Convergence has been set tor le-008
Parameter Convergence has been net. to* le-008
Default Initial Parameter Values
Background ¦ (1.012:4442
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Beta 1.1! »
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Cancer Study Summaries
F.l Epidemiological Data
This section is a synthesis of the findings from the older epidemiological literature, as presented in the
2012 IRIS Assessment ( ) combined with the results of the newer studies described
above. Epidemiological studies provide suggestive evidence for an association between PCE exposure
and tumor development in humans. Tumor types in humans with varying degrees of supporting evidence
for an association with PCE exposure include NHL, MM, and bladder, esophagus, lung, liver, cervical,
and breast cancer according to ( ) and references cited therein, as well as the newer
studies (Purdue et al. 2017; Mattel et al. 2014; Silver et al. I I, ' t ava et al. 2013; Vlaanderen et al.
2013; Gallagher et a I JO I I; 1 tpworth et a I JO I I).
F.l.l Bladder
(I 012c) concluded that, with respect to bladder cancer, the pattern of results from the studies
available at that time was consistent with an elevated risk for PCE of a relatively modest magnitude (i.e.,
a 10-40% increased risk). The effect estimates from five of the six studies with relatively high-quality
exposure assessment methodologies ranged from 1.44 to 4.03 ( ). An exposure-response
gradient was observed in a large case-control study using a semiquantitative cumulative exposure
assessment, with adjusted ORs of 0.8 (95% CI = 0.6-1.2), 1.3 (95% CI = 0.9-1.7), and 1.8 (95% CI =
1.2-2.7) for medium, high, and substantial exposure, respectively, compared to low exposure. A similar
exposure-response pattern was not observed in a different study that examined exposure duration, in
contrast with the previously described data based on varied exposure concentration. Relative risk
estimates between bladder cancer risk and ever having a job title of dry cleaner or laundry worker in
four large cohort studies ranged from 1.01 to 1.44. As expected, the results from the smaller studies are
more variable and less precise, reflecting their reduced statistical power. Confounding by smoking is an
unlikely explanation for the findings, given the included adjustment for smoking in several case-control
studies ( ),.
More recent studies provide little support for an association between bladder cancer and PCE exposure.
The SMR was 0.84 (95% CI = 0.49-1.35) based on 17 observed deaths from bladder and other urinary
cancers and 20.2 expected in the subset (n=5,830, sex and race combined) of a cohort of aircraft
manufacturing workers judged based on detailed exposure assessment to have had routine or intermittent
exposure to PCE while employed for at least 1 year between 1960 and 1996 at the Lockheed Martin
aircraft manufacturing facilities in Burbank, California and followed for mortality experience through
2008 (Lipworth et al. 2011). Similarly, a cohort of workers employed 91 days or more at a
microelectronics and business machine facility in New York state between 1969 and 2001 and followed
through 2009 showed no association between cumulative PCE exposure score estimated from detailed
exposure assessment and deaths from malignant neoplasms of the bladder and other urinary organs (HR
= 0.89, 95% CI = 0.37-2.13) relative to internal referents (Silver et al. 2014). A large case-control study
of incident bladder cancer cases extracted from the NOCCA cohort, which relied on a standardized j ob
exposure matrix to estimate cumulative occupational exposure to PCE (and other agents), reported HRs
of 1.00 (95% CI = 0.92-1.09, 747 cases/3,560 controls), 1.12 (95% CI = 1.02-1.23, 660 cases/2,783
controls), and 0.94 (95% CI = 0.73-1.22, 159 cases/702 controls) in low, medium, and high PCE
exposure groups, respectively; the p-level for dose-response trend was 0.10 (Hadkhale et al. 2017).
These results show a slight significant increase in risk of bladder cancer in the medium PCE exposure
category, but no increase in the high-exposure group and no significant dose-related trend, suggesting a
cause other than PCE exposure for the slight association observed in the medium-exposure group.
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Results from other newer studies were not informative due to small numbers of bladder cancer cases
with exposure to PCE (Bove et al. 2014a. b; Christen sen et al. , ).
F.1.2 Mil
(I ) concluded that results from studies of NHL available at that time indicated an
elevated risk for PCE. The results from five cohort studies that used a relatively high-quality exposure
assessment methodology generally reported relative risks between 1.7 and 3.8 ( ). There
is some evidence of exposure-response gradients, with higher NHL risks observed in the highest
exposure categories, in studies with PCE-specific exposure measures based on intensity, duration, or
cumulative exposure. Effect estimates in studies with broader exposure assessments showed a more
variable pattern. Confounding by life-style factors is an unlikely explanation for the observed results
because common behaviors, such as smoking and alcohol use, are not strong risk factors for NHL (U.S.
E ).
Newer studies provide some support for an association between NHL and PCE exposure. In the cohort
of aircraft manufacturing workers initially studied by (Boiceet.nl h>"»9) and updated by (Lipworth et al.
2011). there was a marginally significant increase in risk of death due to NHL among workers with
routine or intermittent exposure to PCE (SMR = 1.43, 95% CI = 1.00-1.98) based on 36 observed cases
and 25.1 expected. An internal analysis based on duration of exposure (<1, 1-4, >5 years) to PCE,
however, did not support an association with NHL; relative risks were 1.26 (95% CI = 0.65-2.45, 11
observed), 1.00 (95% CI = 0.05-2.00, 10 observed), and 1.02 (95% CI = 0.53-1.99, 12 observed) in the
low- to high-duration exposure groups compared with unexposed factory workers (Ptrend>0.2). In the
New York state cohort studied by (Silver et al. 2014). there was a nonsignificant increase in NHL risk
(HR = 1.25, 95% CI = 0.90-1.73) associated with cumulative exposure to PCE relative to internal
referents that is noteworthy because hourly male workers from the cohort as a whole showed a
significant increase in mortality due to NHL (SMR = 1.49, 95% CI = 1.15-1.89, 65 observed) and all of
the other chemical exposures assessed (trichloroethylene, methylene chloride, chlorinated hydrocarbons,
and other hydrocarbons) showed nonsignificant decreases in NHL risk with increasing cumulative
exposure in the internal analysis. A large case-control study of incident NHL cases extracted from the
NOCCA cohort found no association with cumulative PCE exposure in men, women, or both sexes
combined when analyzed by tertiles, but did find a significant or near significant risk increase in men
(but not women) with high (90th percentile) PCE exposure (HR = 1.54, 95% CI = 0.99-2.42 based on 25
cases using a cumulative exposure metric; HR = 1.74, 95% CI = 1.15-2.64 based on 30 cases using a
metric of average intensity x prevalence) (Vlaanderen et al. 2013). A study of Marine and Navy
personnel exposed to contaminated drinking water at Camp Lejeune, North Carolina between 1975 and
1985 found no association between NHL deaths (1979-2008) and exposure to PCE, as estimated by
water system modeling and housing records, but is preliminary because fewer than 6% of the cohort had
died by the end of the study (Bove et al. 2014a. b). Results from other newer studies were not
informative, primarily due to small numbers of NHL cases with exposure to PCE (Bulka et al. 2016;
Christen sen et al. 2013; Morale s- Suarez-V arel a et al. 2013; Ruckart et al. ).
F.1.3 MM
(I ) concluded that results from studies of MM available at that time indicated an elevated
risk for PCE, although this was based on a smaller set of studies than available for NHL. The larger
cohort studies that used a relatively nonspecific exposure measure (broad occupational title of launderers
and dry cleaners, based on census data) did not report an increased risk of MM, with effect estimates
ranging from 0.99 to 1.07. Some uncertainty in these estimates arises from these studies' broader
exposure assessment methodology. ( ) cited a set of results from cohort and case-control
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studies as providing evidence of an association between PCE exposure and MM. The strongest evidence
of association was from a case-control study that reported a nonsignificant increase in risk of MM
among those ever exposed to PCE (OR = 1.5, 95% CI = 0.8-2.9) based on 16 cases, with a significantly
increasing trend for risk with cumulative PCE exposure (Ptrend = 0.02) and a significant increase in risk
in the highest exposure quartile (OR = 3.3, 95% CI = 1.2-9.5) based on 10 cases. A second case-control
study had too few MM cases with PCE exposure (n=3) to perform a meaningful analysis (
2012c).
Among the newer studies, the large case-control study by (Vlaanderen et al. 2013) derived from the
NOCCA cohort found no association of MM with cumulative PCE exposure in men, women, or both
sexes combined when analyzed by tertiles; slight nonsignificant risk increases were seen in women with
high (90th percentile) PCE exposure (HR = 1.14, 95% CI = 0.84-1.54 based on 52 cases using a
cumulative exposure metric; HR = 1.28, 95% CI = 0.92-1.78 based on 44 cases using a metric of
average intensity x prevalence). Results in men were based on smaller numbers of cases and were less
stable, with high exposure based on the cumulative metric giving a HR of 1.22 (95% CI = 0.65-2.30,
12 cases) and high exposure based on average intensity x prevalence giving a HR of 0.85 (95% CI =
0.42-1.72, 9 cases). The newer cohort studies provided no support for an association between MM and
PCE exposure, (Lipworth et al. 2011) reported an SMR of 1.07 (95% CI = 0.58-1.79) for MM in aircraft
manufacturing workers with routine or intermittent exposure to PCE based on 14 observed and 13.2
expected cases, and no relation to duration of exposure among observed cases (RR = 0.87, 1.14, and
0.34 in low-, medium-, and high-exposure duration groups). Studies by (Silver et al. 2014). (Bove et al.
2014a). and (Bove et al. 2014b) were also negative for an association between PCE exposure and MM.
F.l.4 Esophagus
(I 012c) concluded there was limited suggestive evidence for an association between
esophageal cancer and PCE exposure, based on studies available at that time. The SIR in a large cohort
study (n=95 cases) using broad exposure categories was 1.18 (95% CI = 0.96-1.46). The point estimates
of the association in seven of eight smaller studies, four studies with specific exposure assessments, and
four other studies with less precise assessments were between 1.16 and 2.44 (U.S. EPA.: ). Two
small case-control studies with relatively high-quality exposure assessment approaches reported ORs of
0.76 (95%) CI = 0.34-1.69) based on 8 exposed cases and 6.4 (95% CI = 0.6-68.9) based on 2 exposed
cases, respectively. Some uncertainties in these estimates arise from the lack of job title information for
25% of the cases and 19% of the controls in one study and the small number of exposed cases in the
other study. One study examining exposure-response suggested a positive relationship, with SMRs of
2.16 (95% CI = 0.85-4.54, 5 cases) and 4.78 (95% CI = 2.68-7.91, 11 cases) for durations of <5 years
and >5 years, respectively ( ). In contrast, one study did not did not find a trend with
exposure duration, but included only 0-3 cases per duration category, and another study found similar
risks in subjects with little to no exposure (RR = 2.1, 95% CI = 0.9-4.4, 7 cases) and medium to high
exposure (RR = 2.2, 95% CI = 1.2-3.5, 16 cases). None of the cohort studies can exclude possible
confounding from alcohol and smoking—risk factors for squamous cell carcinoma of the esophagus,
however based on smoking rates in blue-collar workers, the 2-fold estimated increase in relative risk
reported in another set of studies (RR = 2.44, 95% CI = 1.40-3.97, RR = 2.2, 95% CI = 1.5-3.3) were
higher than levels which could reasonably be attributed solely to smoking.
Findings in newer studies were generally unsupportive of an association between esophageal cancer and
PCE exposure. In an update of the (Boice et al. 1999) study, (Lipworth et al.: ) reported an SMR of
1.13 (95%) CI = 0.72-1.68) for esophageal cancer among aircraft manufacturing workers with routine or
intermittent exposure to PCE (24 cases versus 21.3 expected). In the internal analysis from this study
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based on duration of exposure, relative risk for esophageal cancer was significantly increased in workers
with less than 1 year of exposure (RR = 2.30, 95% CI = 1.14-4.66, 11 cases), but decreased with
increasing exposure duration (in the high-duration group with exposure of 5 years or more, RR = 0.66,
95% CI = 0.22-1.96, 4 cases). Similarly, (Bove et al. 2014a) and (Bove et al. 2014b) reported decreasing
HRs of 1.27 (95% CI = 0.57-2.81, 11 cases), 0.55 (95% CI = 0.20-1.55, 5 cases), and 0.41 (95% CI =
0.13-1.26, 4 cases) for esophageal cancer in low, medium, and high cumulative PCE exposure groups,
respectively, in the Camp Lejeune cohort exposed by drinking water. The only other newer study that
evaluated this endpoint was not informative due to lack of observed cases with PCE exposure
(Christensen et al. 2013).
F.1.5 Kidney
(I ) acknowledged mixed results in studies of kidney cancer available at that time,
concluding that overall the evidence was suggestive but limited. One primary study supporting an
association between PCE exposure and kidney cancer, a large international case-control study (245
exposed cases from Australia, Denmark, Germany, Sweden, and the United States), reported a relative
risk of 1.4 (95% CI = 1.1-1.7) for any exposure to dry cleaning solvents. This study was able to adjust
for smoking history, body mass index, and other risk factors for kidney cancer. Results from the large
cohort studies, using a more general exposure classification based on national census occupation data,
presented more variable results, with relative risks of 0.94, 1.11, and 1.15 ( 12c). The results
from the smaller studies using a relatively specific exposure assessment approach to refine classification
of potential PCE exposure in dry cleaning settings were mixed, with some studies reporting little or no
evidence of an association and other studies reporting elevated risks ( ). An increasing
trend in relative risk with increasing exposure surrogate was not observed in any of the larger
occupational exposure studies with three or more exposure categories but some indication of higher risk
with higher exposure (or duration) was observed in other studies ( :012c).
Mixed results were obtained in newer studies as well. A case-control study of kidney cancer cases from
Detroit, Michigan and Chicago, Illinois using detailed exposure assessment methodology found no
significant association with probability of exposure to PCE, or with PCE exposure duration, average
weekly exposure or cumulative exposure for those with >50% probability of exposure, but did observe a
significant increase in kidney cancer risk for those in the highest tertile of cumulative hours exposed
when the analysis was restricted to those with high-intensity exposure to PCE (OR = 3.1, 95% CI = 1.3-
7.4, 14 cases/8 controls, Ptrend = 0.03) (Purdue et al.: ). This relationship was also seen in additional
analyses that incorporated 5-year (OR = 3.5, 95% CI = 1.3-10.0, Ptrend = 0.03) or 15-year (OR = 6.2,
95% CI = 1.8-21.3, Ptrend = 0.003) exposure lag periods, included only jobs assigned an exposure
probability with high confidence (OR = 5.1, 95% CI = 1.5-7.2, Ptrend = 0.12), or excluded participants
with >50% probability of exposure to trichloroethylene (OR = 3.0, 95% CI = 0.99-9.0, 17 cases/
14 controls, Ptrend = 0.08), a potential confounder. Results in other newer studies were negative. The
large case-control study by (Vlaanderen et al. 2013) derived from the NOCCA cohort found no
association of kidney cancer with cumulative PCE exposure in men, women, or both sexes combined
when analyzed by tertiles or when the analysis was restricted to those with high (90th percentile)
exposure (HR = 0.81, 95% CI = 0.65-1.01 based on 88 cases using a cumulative exposure metric; HR =
1.01, 95% CI = 0.82-1.25 based on 103 cases using a metric of average intensity x prevalence). In
cohort studies, (Lipworth et al. 2011) found no association between kidney cancer mortality and routine
or intermittent exposure to PCE in aircraft manufacturing workers (SMR = 0.80, 95% CI = 0.43-1.37, 13
cases versus 16.3 expected) and no relation to exposure duration among the observed cases, and (Silver
et al. 2014) found no association between kidney cancer and cumulative PCE exposure among
electronics workers (HR = 0.15, 95% CI = 0.01-4.04). (Bove et al. ) and (Bove et al. 2014b)
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reported nonsignificant elevations in HR for kidney cancer that were, however, unrelated to cumulative
PCE exposure in the Camp Lejeune cohort (HR = 1.40, 95% CI = 0.54-3.58, 8 cases; 1.82, 95% CI =
0.75-4.42, 11 cases; and 1.59, 95% CI = 0.66-3.86, 11 cases in low, medium, and high groups,
respectively). The only other newer study that evaluated this endpoint was not informative due to few
observed cases with PCE exposure (Christensen et al. 2013).
A meta-analysis of five selected epidemiologic studies (Purdue et al. 2017; Silver et al. 201 I;
Vlaanderen et al. 2013; Dosemeci et al. 1999; Aschengrau et al. 1993) considered to be reliable and
informative for the association of kidney cancer and exposure to PCE was performed as part of the
current assessment. Applying a fixed-effects model to the five informative studies produced a meta-RR
of 0.96 (95%) CI = 0.85-1.07) for overall exposure to PCE, with no heterogeneity among studies
(I2=0.0%, p=0.72). Estimates of the association of kidney cancer with high exposure to PCE were
available for two studies (Purdue et al. 2017; Vlaanderen et al. ). A fixed-effects model based on
the association of kidney cancer with high exposure in those two studies and with any exposure in the
remaining studies produced a meta-RR of 1.07 (95% CI = 0.89-1.28) with moderate heterogeneity
(I2=45.9%, p=0.12). These results are consistent with no association or weak positive association
between the occurrence of kidney cancer and exposure to PCE, but should be interpreted with caution
due to the small number of informative studies.
F.1.6 Lung
(I 012c) concluded there was limited suggestive evidence for an association between lung
cancer risk and PCE exposure. The results from seven large cohort studies of dry cleaners available at
that time were consistent with an elevated lung cancer risk of 10-40%. Similar results were observed in
four of the five occupational studies that were identified as having a relatively strong exposure
assessment methodology, with slightly higher relative risks identified for laundry workers compared
with dry cleaning workers in a separate comparison. These studies were unable to control for potential
confounding from cigarette smoking, however, and the magnitude of the association in these studies is
consistent with that expected assuming the prevalence of smoking among dry cleaners and laundry
workers was slightly higher (e.g., 10% higher) than among the general population. Features of the
selection of study participants and study analysis in the available case-control studies reduce the
potential for confounding by smoking. Two case-control studies were limited to either nonsmokers or
ex-smokers and both of these studies indicate an approximate 2-fold increased risk with a history of
work in the dry cleaning industry (OR= 1.8, 95% CI= 1.1-3.0; OR= 1.83, 95% CI = 0.98-3.40 among
women). The other case-control studies adjusted for smoking history, and the results for these
(somewhat smaller studies) are similar to the previously cited estimates. Among the studies that
evaluated exposure-response gradients, the evidence for a trend in risk estimates was mixed (
2012c).
Newer case-control studies of lung cancer support a relationship with PCE exposure. A study of lung
cancer cases from Montreal that included adjustment for smoking (Comprehensive Smoking Index)
reported ORs of 2.5 (95% CI = 1.2-5.6, 23 cases) for "any" exposure to PCE and 2.4 (95% CI = 0.8-7.7,
10 cases) for "substantial" exposure (Vizcava et al. , ). A larger study from France that also included
adjustment for smoking (Comprehensive Smoking Index) reported ORs of 1.26 (95% CI = 0.87-1.82,
107 cases) in men and 2.74 (95% CI = 1.23-6.09, 26 cases) in women ever exposed to PCE (Mattei et al.
2014). In additional analyses by cumulative PCE exposure (split into high and low groups based on
median cumulative exposure), ORs for men were 1.14 (95% CI = 0.67-1.94, 45 cases) in the low-dose
group and 1.36 (95% CI = 0.84-2.22, 62 cases) in the high-dose group, while ORs for women were 3.80
(95% CI = 1.41-10.24, 21 cases) in the low-dose group and 1.43 (95% CI = 0.37-5.50, 5 cases) in the
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high-dose group. Further analyses stratified by overlapping exposure to multiple solvents suggested that
the observed increase in lung cancer risk was due to PCE, and not co-exposure to other chlorinated
solvents (trichloroethylene, methylene chloride, chloroform, carbon tetrachloride). Newer cohort studies
that investigated lung cancer risk were negative. (Lipworth et al. 2011) found no association between
lung cancer mortality and routine or intermittent exposure to PCE in aircraft manufacturing workers
(SMR = 0.94, 95% CI = 0.81-1.07, 206 cases versus 220.3 expected) and no relation to exposure
duration among the observed cases. (Bove et al. 2014a) and (Bove et al. 2014b) reported nonsignificant
elevations in HR for lung cancer that were, however, unrelated to cumulative PCE exposure in the Camp
Lejeune drinking water cohort (HR = 1.33, 95% CI = 0.93-1.90, 56 cases; 1.27, 95% CI = 0.88-1.83, 55
cases; and 1.08, 95% CI = 0.75-1.57, 51 cases in low, medium, and high groups, respectively).
F.1.7 Liver
(I 012c) cited results available at that time showing a mixed pattern of results for liver cancer,
concluding that there was suggestive but limited evidence of an association. One case-control study with
a large number of exposed liver cancer cases and a relatively high-quality exposure assessment
methodology reported an OR estimate of 0.76 (95% CI = 0.38-1.72) for liver cancer and dry cleaning.
Cohort studies of Nordic subjects with broad exposure assessment approaches reported SIRs of
1.02 (95% CI = 0.84-1.24), 1.22 (95% CI = 1.03-1.45), and 1.23 (95% CI = 1.02-1.49) for liver and
biliary tract cancer and work as a dry cleaner or laundry worker. Three other studies with strong
exposure assessment approaches specific to PCE, but whose risk estimates are based on fewer observed
liver cancer cases or deaths, reported risk estimates of 1.21-2.05 for the association between liver cancer
and PCE. However, dry cleaning workers did not have a higher liver cancer risk estimate than laundry
workers. Exposure response was not observed, and the SIR for PCE-exposed subjects with the longest
employment duration was lower than that for subjects with shorter employment duration. Potential
confounding may be an alternative explanation, as no study adjusted for known and suspected risk
factors for liver cancer ( ). Nine other cohort and case-control studies with fewer
observed events and/or a broad exposure assessment methodology carried less weight in the analysis and
reported a mixed pattern of results ( ). One of these reported a risk estimate of 2.57 (95%
CI = 1.21-5.46) for the association between liver cancer and residence in a village with groundwater
contamination, but subjects were from a region with a high prevalence of hepatitis C infection, and
hepatitis C status may confound the observed association.
Among the newer studies, the large case-control study by (Vlaanderen et al. 2013) derived from the
NOCCA cohort reported slight nonsignificant increases in liver cancer risk in the second (HR = 1.18,
95% CI = 0.97-1.44, 121 cases) and third (HR = 1.13, 95% CI = 0.92-1.38, 114 cases) tertiles,
respectively, of cumulative PCE exposure (both sexes combined), and in those with high (90th
percentile) PCE exposure (HR = 1.11, 95% CI = 0.79-1.57 based on 40 cases using a cumulative
exposure metric; HR = 1.26, 95% CI = 0.88-1.80 based on 38 cases using a metric of average intensity x
prevalence). (Lipworth et al. 2011) found no association between liver cancer mortality and routine or
intermittent exposure to PCE in aircraft manufacturing workers (SMR = 0.93, 95% CI = 0.56-1.45, 19
cases versus 20.5 expected). There was no significant relationship with exposure duration among the
observed cases (Ptrend >0.20) in this study, but relative risk was highest in workers with the longest (>5
years) duration of exposure (RR = 1.29, 95% CI = 0.60-2.78, 10 cases). (Silver et al. 2014) found no
association between liver cancer and cumulative PCE exposure among electronics workers (HR = 0.79,
95% CI = 0.27-2.30). (Bove et al. 2014a) and (Bove et al. 2014b) reported decreasing HRs of 1.17 (95%
CI = 0.55-2.49, 12 cases), 0.96 (95% CI = 0.43-2.14, 10 cases), and 0.82 (95% CI = 0.36-1.89, 9 cases)
for liver cancer in low, medium, and high cumulative PCE exposure groups, respectively, in the Camp
Lejeune cohort exposed by drinking water. The only other newer study that evaluated this endpoint was
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not informative because there was only a single observed case with PCE exposure (Christensen et al.
2013).
F.1.8 Cervix
(I 012c) included cervical cancer among the tumor types with limited suggestive evidence for
an association with PCE exposure. The results from two large cohort studies with a broad exposure
assessment were consistent with an elevated cervical cancer risk of 20-30%: SIR = 1.20 (95% CI = 1.08-
1.34) and SIR = 1.34 (95% CI = 1.12-1.60). Results from four smaller cohort and case-control studies
with a relatively high-quality exposure assessment methodology presented a pattern of more variable
results, with relative risks of 0.98 (95% CI = 0.65-1.47), 1.19 (95% CI = 0.64-1.93), 2.10 (95% CI =
0.68-4.90), and 3.20 (95% CI = 0.39-11.6). A fourth study with higher quality exposure assessment
specific to PCE did not observe any cervical cancer deaths among women, but less than one death was
expected. Only a single study reported an increasing exposure response gradient with employment
duration. Dry cleaning workers did not have higher cervical cancer risks compared with laundry
workers. None of the cohort studies of cervical cancer considered socioeconomic or lifestyle factors
such as smoking or exposure to the human papilloma virus (HPV), a known risk factor for cervical
cancer that is correlated with socioeconomic status. A case-control study included controls similar in
socioeconomic status as cases, and the OR estimate in that study for dry cleaners did not support an
association with PCE (U.S. EPA. 2012c). The only newer study that evaluated this endpoint ((Lipworth
et al. ), update of (j •- xe et al. 1999)) was not informative because there was only a single observed
case with PCE exposure.
F.1.9 Breast
Breast cancer was among the endpoints considered by ( Ł012c) to have suggestive but limited
evidence of an association with PCE exposure based on studies available at that time. Results from the
large studies of breast cancer risk in women in relation to PCE exposure were mixed. The largest study,
based on 1,757 breast cancer cases in female dry cleaners and laundry workers, reported a statistically
significant deficit in the risk of breast cancer incidence compared to the populations of Nordic countries.
Findings in the other four studies were based on fewer events or exposed cases; two of four studies with
a nonspecific exposure assessment methodology provided evidence for association between breast
cancer in females and PCE exposure, but no association to PCE was observed in two other large cohort
studies with a relatively high-quality exposure assessment methodology (U.S. EPA. 2012c). Small
studies also observed mixed findings. Although cohort studies were unable to control for potential
confounding from reproductive history or menopausal status, observations in case-control studies
controlled for these potential confounders in statistical analyses and provided support for an association
between female breast cancer and PCE compared to controls. Three studies examined exposure-response
relationships ( ;), and two of these studies with semiquantitative or quantitative exposure
assessment approaches reported that risk estimates in females were monotonically increased in higher
exposure groups. A third study examining exposure duration observed an inverse relation, but exposure
duration is more uncertain than use of a semiquantitative surrogate given increased potential for bias
associated with exposure misclassification.
Few data on breast cancer were found in newer studies. (Gallagher et al. 2011) conducted a case-control
study that included an updated exposure assessment and reanalysis of breast cancer data previously
evaluated by (Aschengrau et al. 2003). (Aschengrau et al. 1998). and (Paulu et al. 1999). They found no
increase in breast cancer risk for women "ever" exposed to PCE versus unexposed, but modest
nonsignificant risk increases in women with high cumulative exposure defined as 90th percentile (ORs
mostly 1.3-1.5 depending on latency) or as a higher cut point identified by curve smoothing analysis
(ORs 1.3-1.4 with 0-7-year latency and 1.6-2.0 with 9-15-year latency). In the (Lipworth et al. , )
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update of the (Boice et al. 1999) cohort of aircraft manufacturing workers, there was also a
nonsignificant increase in breast cancer risk (SMR = 1.52, 95% CI = 0.78-2.65) based on only 12 cases
(versus 7.9 expected), but no significant trend based on exposure duration (Ptrend>0.20) in an analysis
limited by the small number of cases per exposure duration category. The only other newer study that
evaluated this endpoint was not informative due to few observed cases with PCE exposure ( /e et al.
2014a. bY
Because of the limitation in statistical power, none of the older ( ) or newer (Ruckart et
al. 2015) studies reporting on male breast cancer was adequate to examine PCE exposure.
F.1.10 Other
No other cancers were identified by ( ) as having potential associations with PCE
exposure. Among the newer studies, case-control studies by (Barul et al. 2017). (Carton et al. 2017) and
(Christensen et al. 2013) presented results suggesting potential associations between PCE exposure and
prostate cancer in men and pharyngeal/laryngeal cancers in both sexes. However, these findings were
based on small numbers of cases (<10) and so are highly uncertain. Other studies did not report
supporting results. (Lipworth et al. 2011) found no increase in risk of death due to cancers of the buccal
cavity and pharynx (SMR = 0.77, 95% CI = 0.41-1.32, 13 observed and 16.8 expected), larynx (SMR =
0.90, 95% CI = 0.36-1.84, 7 observed and 7.8 expected), or prostate (SMR = 0.92, 95% CI = 0.72-1.16,
71 observed and 77.1 expected) in their cohort of aircraft manufacturing workers exposed to PCE. No
significant relationship between cumulative exposure to PCE and risk of prostate or oral cancers was
evident in the Camp Lejeune cohort (Bove et al. JO I U, h).
F.l.ll Detailed Summary Epidemiologic Evidence on Cancer Published after the 2012
IRIS Toxicological Assessment on PCE
Lipworth et al. ( ) conducted a follow-up analysis of the aircraft manufacturing worker cohort
originally evaluated by (Boice etal. 1999) and described in ( ). The cohort consisted of
77,943 employees who had worked for at least 1 year at a Lockheed Martin manufacturing facility in
California on or after January 1, 1960. The cohort included both exposed factory workers (n=45,318)
and unexposed non-factory workers (n=32,625). Subjects were identified using employee work history
records, personnel files, and retirement records. Deaths through December 31, 2008 (n=34,298) were
determined using the California Death Statistical Master File (CDSMF), National Death Index (NDI),
and Social Security Administration Death Master File (SSADMF), as well as company pension records
and a commercial service specializing in death record location. Workers for whom no death records
were identified were traced using Social Security Administration Service to Epidemiologic Researchers
and LexisNexis records to confirm that they were alive; these methods confirmed the identification of
42,309 living workers. The vital status of the remaining 1,336 workers (1.7% of cohort) was not
determined. For deaths after 1978, underlying cause of death was available in the NDI; the CDSMF
provided cause of death for subjects who died in California, and death certificates were obtained for the
remaining subjects (and for a small number of subjects whose records in NDI were incomplete).
Exposures were determined based on historical job descriptions, chemical usage patterns, environmental
assessment reports, industrial hygiene records, interviews with long-term workers, and walk-throughs of
aircraft manufacturing facilities; details of the exposure assessment were published by (Marano et al.
2000). Approximately 12.9% of factory workers (n=5,830) had some exposure to PCE. According to
(Marano et al. 2000). many PCE-exposed workers also had exposure to chromate (76%),
trichloroethylene (39%), mixed solvents (56%), and/or asbestos (5%). Relative exposure to each worker
was assigned based on length of time in specific jobs with potential for exposure to each substance.
(Marano et al. 2000) indicated that exposures were categorized as either routine or intermittent, and that
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approximately 55% of the PCE-exposed workers were classified as having intermittent exposure. Thus,
there may have been a wide range of cumulative exposure levels in the group exposed to PCE, which
could bias the analysis toward the null. No information was available to the researchers regarding
smoking, alcohol consumption, or other lifestyle factors.
For standard mortality ratio (SMR) calculations, expected numbers of deaths were obtained using age,
race, calendar year, and sex-specific rates from California (for white workers) or the U.S. general
population (for non-white workers, to better match the racial composition of the worker population)
(Lipworth et al. ). For internal analyses examining the influence of exposure duration, the
comparison group consisted of factory workers without exposure to solvents or chromates (n=9,520).
The model included date of birth, date of hire, date of termination, sex, and race. There was no explicit
consideration of latency.
There were 2,641 deaths among the workers exposed to PCE (Lipworth et al. 2011). SMRs for all causes
of death and all malignant neoplasms were reduced slightly (0.93 and 0.96, respectively), consistent with
a healthy worker effect. A marginally significant increase in the SMR for NHL (SMR = 1.43; 95%
confidence interval [CI] = 1.00-1.98; n=36 cases) was observed. Nonsignificant increases in SMRs for
cancers of the breast (SMR = 1.52, 95% CI = 0.78-2.65, n=12 cases), connective and other soft tissues
(SMR = 1.58; 95% CI = 0.58-3.43; n=6 cases), ovary and other female genital (SMR = 1.28, 95% CI =
0.26-3.74; n=3 cases), and testes and other male genital (SMR = 2.18, 95% CI = 0.45-6.37; n=3 cases)
were based on small numbers of cases. Other sites, including bladder, kidney, liver, lung, esophagus,
and cervix and MM had SMRs below or close to 1.0 (SMR <1.13).
Analyses based on duration of exposure (<1, 1-4, >5 years) to PCE did not support an association
between PCE and NHL or any other tumor type examined, including MM and cancers of the breast,
kidney, liver, lung, or esophagus (Lipworth et al. 2011). For NHL, relative risks were 1.26 (95% CI =
0.65-2.45, 11 observed), 1.00 (95% CI = 0.05 2.00, 10 observed), and 1.02 (95% CI = 0.53-1.99, 12
observed) in the low- to high-duration exposure groups compared with unexposed factory workers
(Ptrend >0.2). Interpretation of the duration of exposure analysis was limited for most other tumor types
(all of those listed above, except lung) by small numbers of observed tumors (<4) in one or more of the
duration groups.
In another cohort study, (Silver et al. , ) evaluated the association between PCE exposure and cancer
mortality in a cohort of 34,494 microelectronics workers in New York state. The workers were engaged
in business machine production and manufacture of circuit boards and substrates between 1906 and
2001. Machine production involved exposure to dust, solvents, and metals, while circuit board
production involved exposure to chlorinated solvents and other industrial chemicals. Facility records
indicated that use of trichloroethylene in circuit board production began in the mid-1960s, and that use
of PCE increased in 1974 when substrate manufacturing began.
Members of the cohort included all direct employees who had worked at least 91 days between January
1, 1969 and December 31, 2001 and were U.S. citizens (Silver et al. 2014). The Social Security
Administration, NDI, and Internal Revenue Service were used to determine vital status of cohort
members through December 31, 2009. Cause of death was determined from the NDI for deaths after
1979 and from death certificates for earlier deaths and coded according to the International
Classification of Diseases (ICD) revision in effect at the time of death.
Higher percentages of hourly than salaried workers were ever potentially exposed to a compound
considered in the study; however, even among hourly workers, the prevalence of PCE exposure was low
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(Silver et al. 2014). Among male hourly workers, 15.1% were exposed to PCE, compared with 60.5%
exposed to "other hydrocarbons." Chemical exposure was estimated using work histories from
electronic personnel databases, chemical use and exposure information from the company, industrial
hygiene monitoring results/documents, and company environmental impact assessments, as well as
interviews of former employees and results from an Agency for Toxic Substances and Disease Registry
(ATSDR) study of volatile organic compound (VOC) use at the plant from 1969 to 1980. An exposure
database linking chemical use with department and year was developed and used to assign each subject
to an exposed/unexposed category for PCE, trichloroethylene, methylene chloride, and chlorinated
hydrocarbons as a class. Cumulative exposure duration was modified by a parameter categorizing the
extent of chemical use in a department and another that categorized the extent of exposure by job
function.
SMRs were calculated for all cohort members, but these analyses were not chemical-specific (Silver et
al. 2014). Internal analyses by chemical exposure were performed using conditional logistic regression
based on full risk sets (equivalent to Cox proportional hazards analysis). In these analyses, chemical
exposure of cases was compared with those of "controls": workers who began at an age younger than
the cases and survived longer (these could include cases from other risk sets). Age was controlled using
risk set selection, and models were adjusted for sex and pay code (as it is potentially associated with
exposure, smoking, and other potential confounders). Smoking, alcohol consumption, and other lifestyle
factors were not explicitly considered. The authors did not control for other chemical exposures or
evaluate correlations among them. Hazard ratios (HRs) at 5 modified exposure years were reported,
along with the regression coefficient, with a 10-year lag time incorporated for all outcomes apart from
leukemia (for which a 2-year lag was used).
SMRs for all cause and all cancer mortality were significantly decreased in the cohort relative to U.S.
general population rates, showing the expected healthy worker effect (Silver et al. 2014). Also among
the cohort as a whole, the SMR for NHL was significantly increased in hourly male workers (SMR =
1.49, 95% CI = 1.15-1.89, 65 observed). In the analyses for specific chemical exposures, PCE showed a
small nonsignificant increase in HR for NHL (HR = 1.25, 95% CI = 0.90-1.73), while the other
exposures examined (trichloroethylene, methylene chloride, chlorinated hydrocarbons, and other
hydrocarbons) showed nonsignificant decreases. PCE showed no association (HR <1.0) with other
cancers, including bladder, kidney, liver, brain, or MM. The study was limited by the young age of the
cohort (only 17% had died at the end of follow-up), as well as by the low prevalence of PCE exposure
and failure to control for co-exposures.
(Gallagher et al. 2011) performed a case-control study that included a reanalysis of breast cancer data
previously evaluated by (Aschengrau et al. 1998). (Aschengrau et al. 2003). and (Paulu et al. 1999) and
described in ( ), updating the exposure assessment of the Cape Cod population exposed
to PCE leaching from the vinyl lining of drinking water distribution pipes. Briefly, while earlier
assessments used the Webler and Brown model to estimate residential PCE exposures based on the
configuration, size, age, and water flow rate in contaminated pipe serving each residence, (Gallagher et
al. 2011) employed the EPANET software to provide more robust modeling of water flow throughout
the entire distribution system. Participant selection was identical to earlier assessments, except that
subjects from the earlier analyses were excluded if information needed for EPANET modeling was
missing. Eligible persons consisted of permanent female residents of eight affected towns in Cape Cod.
Incident breast cancer cases between 1983 and 1993 were identified using the state cancer registry;
controls of comparable age and vital status were identified through random digit dialing (for controls up
to 64 years of age), Medicare records (65 years of age and older), or death certificates (deceased
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controls). Of 1,192 cases and 7,869 controls initially identified, 87 cases and 1,125 controls could not be
located; 31 cases and 4,404 controls were not eligible based on residential criteria; 8 cases and 34
controls lacked exposure information; and 136 cases and 338 controls declined to participate (or their
physicians declined consent). Finally, 666 eligible controls identified by random digit dialing were
excluded because the target number of controls had already been reached. Of the 930 cases and 1,302
controls included in previous analyses, 19 lacked information needed for EPANET exposure modeling
and were excluded, leaving 920 cases and 1,293 controls for the reanalysis.
From each subject, detailed residential history, history of occupational exposure to PCE, risk factors for
breast cancer, and other demographic information was obtained via interview (Gallagher et al. 2011).
Using the EPANET software to model water flow in the distribution system and leaching components
from the Webler-Brown model, the study authors estimated relative delivered dose (RDD) to each
residence. The RDD is a relative dose estimate intended to approximate the amount of PCE delivered to
each residence. Odds ratios (ORs) were evaluated using multiple logistic regression controlling for the
following variables: age at diagnosis or index year, vital status at interview, family history of breast
cancer, personal history of prior breast cancer, age at first live birth or stillbirth, occupational PCE
exposure, and study of origin (first study or second expanded study). Use of bottled water was
considered by stratifying the results. Other potential confounders, including education, hormone use, and
parity were considered, but did not modify effect estimates by at least 10% and were excluded from the
final model. ORs were calculated with and without latency periods of 5-19 years, based on ever/never
exposed, cumulative RDD, peak RDD, and duration of exposure to PCE. The impact of PCE leaching
rate was evaluated by sensitivity analysis, and smoothing analysis was used to refine the cut points for
high exposure.
The updated exposure assessment using the EPANET software categorized larger percentages of cases
and controls as exposed (48.8% and 50.1%, respectively) compared to the earlier method (20.5% and
16.7%), respectively), which had assumed that residences not in close proximity to a source pipe were
not exposed (Gallagher et al. 2011). Because most of the participants whose status shifted from non-
exposed to exposed were exposed at low levels, the EPANET method yielded a downward shift in RDD
distribution percentiles compared to the earlier method; for example, 75th and 90th percentile RDD
estimates (unitless) with no latency period were 7.1 and 19.5, compared with 15.5 and 41.8
(respectively) using the earlier method.
Using the updated exposure estimates, no increases in the adjusted ORs for breast cancer were observed
for women "ever" versus never exposed, regardless of latency period considered (adjusted OR =1.0 for
all latencies) (Gallagher et al. 2011). Compared to unexposed subjects, modest nonsignificant increases
in the adjusted ORs were observed for cumulative RDDs above the 90th percentile (adjusted ORs
mostly 1.3-1.5 depending on latency) and for peak RDD above the 90th percentile (adjusted ORs 0.9-
1.5), but not the lower exposure levels. Analysis for duration of exposure showed a nonsignificant
increase in breast cancer risk in women with more than 10 years of exposure when a 13-year latency
period was included (adjusted OR = 1.8, 95% CI = 0.7-4.4); none of the women had more than 10 years
of exposure when longer latency periods were considered. No associations were found between shorter
durations of exposure and breast cancer, regardless of latency period. When the cut points for higher
cumulative exposure were redefined based on smoothing analysis (RDD >35), adjusted ORs (none
significant) were 1.3-1.4 with 0-7-year latency and 1.6-2.0 with 9-15-year latency. Results were reported
to be similar for peak exposure, but data were not shown. Finally, slightly higher risks were seen for
exposed women who did not drink bottled water regularly (adjusted ORs =1.1 1.3 across latency
periods) when compared with those who did (adjusted ORs = 0.6-0.8). As in the previous studies
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conducted on these data, this study suggests a modest association between high drinking water exposure
to PCE and breast cancer risk in women.
(Ruckart et al. 2013) conducted a case-control study of childhood hemopoietic cancers (leukemia and
NHL) in children exposed prenatally and in early childhood to contaminated drinking water at the
Marine Corps Base at Camp Lejeune, North Carolina. Contaminated water at the camp, which opened in
the 1940s, was discovered in the early 1980s in wells of the Camp's Hadnot Point and Tarawa Terrace
distribution systems. The Tarawa Terrace system was primarily contaminated with PCE (up to 215
(j,g/L) from a nearby dry cleaner, while Hadnot Point was primarily contaminated with trichloroethylene
(up to 1,400 |ig/L), with lesser amounts of vinyl chloride, 1,2-dichlorethylene, PCE, and benzene. These
authors did not detail other contaminants in the Tarawa Terrace system; however, (Ruckart et al. 2015)
estimated that low levels (<20 (J,g/L) of dichloroethylene, trichloroethylene, and vinyl chloride were
present along with PCE.
The study population consisted of children born alive between 1968, when North Carolina began
computerizing birth certificates, and 1985, when the contaminated wells were closed, and whose
mothers had lived at Camp Lejeune during pregnancy (Ruckart et al. 2013). A total of 12,493 children
whose mothers lived on base when they delivered were identified by birth certificates, and an additional
4,000 children whose mothers had moved off base prior to delivery were identified via media campaigns
and referrals from enrolled subjects. Telephone interviews of parents were conducted by ATSDRto
obtain information on childhood (before age 20) leukemia and NHL and residential histories. Of 12,498
subjects whose parents were contacted, 76% agreed to participate, including 10,044 identified by birth
certificates and 2,554 identified by referral.
Exposures to contaminated water were estimated by ATSDR via base-wide models of groundwater fate
and transport and drinking water distribution systems, which yielded monthly average concentration
estimates at each residence (Ruckart et al. 2013). Base housing records and parental interview
information were combined with the concentrations to estimate average exposure to each subject across
pregnancy and the first year of life. The study authors did not isolate subjects by water distribution
system, so the study population included those using the Hadnot Point system with exposure primarily to
trichloroethylene. Exposures were estimated for each trimester, for the whole gestation period, and for
the first year of life.
A total of 14 childhood hematopoietic cancers were reported by parents (Ruckart et al. 2013). Of these,
13 cases were confirmed via vital and medical records, including 11 leukemias and 2 NHL. The parents
of 651 potential control subjects were contacted; 103 refused or could not be contacted, so 548 were
interviewed. Subsequently, 14 control children were excluded because their parents reported in the
interview that the mother had not resided on the base during pregnancy; 6 were excluded because the
parents were interviewed about the wrong child; and two lacked residential history during pregnancy,
leaving 526 controls. ORs were estimated using unconditional logistic regression. Potential confounders
considered in the analysis were not reported, and adjusted results were only reported if the difference
from the crude estimates was more than 20%.
The median estimated average PCE exposure of subjects was 44 (.ig/L (Ruckart et al. 2013). Using the
average first trimester exposure estimate, the unadjusted OR for exposed versus unexposed was 1.6
(95%) CI = 0.5-4.8) based on 7 cases (total for childhood leukemia and NHL combined), and the
unadjusted ORs for exposure above and below the median, compared with unexposed, were similar and
also imprecise (OR = 1.4, 95%> CI 0.3-5.6 for exposure >44 [j,g/L based on 3 cases; OR=1.8, 95%> CI =
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0.5-6.6 for exposure >0 and <44 [j,g/L based on 4 cases). Other metrics for first trimester exposure
(maximum, unexposed including exposure <1 (J,g/L) yielded comparable effect estimates (data not
reported), while no association with childhood leukemia and NHL was seen using cumulative exposure
to PCE through pregnancy or the first year of life (data not reported). These data are highly uncertain
due to the small number of observed cases exposed to PCE.
(Ruckart et al. 2015) assessed male breast cancer risk in a case-control study of U.S. Marine Corps
personnel stationed at Camp Lejeune. Cases and controls were identified using the Veteran's Affairs
Central Cancer Registry (VACCR). The study population was defined as male Marines diagnosed or
treated for cancers between January 1, 1995 (when the VACCR began) and May 5, 2013 at a medical
facility run by the Veterans Administration (VA). Those who were not old enough to have been at Camp
Lejeune during the time of water contamination (e.g., at least 17 years old by December 31, 1985) were
excluded. A total of 78 incident cases of male breast cancer were identified. Controls were diagnosed
with cancers not known to be related to solvent exposure, including non-melanoma skin cancer, bone
cancer, and pleural or peritoneal mesothelioma. To achieve the targeted 5 controls per case, the study
authors included all 32 bone cancer cases, all 76 mesothelioma cases, and a random sample of 292 skin
cancers from among the 555 identified in VACCR, yielding a total of 400 controls.
All information was obtained from databases; no subject interviews were conducted (Ruckart et al.
2015). Military personnel records were used to determine whether and when subjects had been stationed
at Camp Lejeune before 1986, as well as their marital status at each time period stationed there; these
records were missing for 7 cases and 27 controls. The VACCR and VA patient treatment files were
examined for information on tumor histological confirmation, date of birth, age at diagnosis, race, and
medical conditions (e.g., diabetes, obesity, gynecomastia, and Klinefelter syndrome) potentially related
to male breast cancer development. Finally, information on service in Vietnam (with potential exposure
to dioxin via Agent Orange) and military occupational specialties with potential exposure to solvents
and electromagnetic fields was obtained from military personnel records.
The same historical reconstruction method used by (Ruckart et al.: ) was used to estimate monthly
average exposure concentrations at each residence (Ruckart et al. 2015). The residential histories of
cases and controls were developed from base housing records, military personnel records, and unit-
specific housing records. Exposure began with the earliest time each subject was stationed at Lejeune
and ended either when his tour ended or on December 31, 1985. Cumulative and average exposures
were estimated for each subject; exposure-response analysis was performed by categorizing exposures
above and below the median. The study authors employed exact logistic and conditional regression
methods to estimate associations, but since results were similar, only the exact logistic method results
were presented. Results were adjusted for age at diagnosis, race, and service in Vietnam; other potential
covariates (case/control status, ethnicity, rank, diabetes, or gynecomastia) did not alter risk estimates by
at least 10%. Finally, proportional hazards analysis, adjusted for race and service in Vietnam, was used
to assess whether PCE exposure resulted in earlier age at breast cancer diagnosis. While latency was not
explicitly included in the assessment, the authors noted that an implicit latency of at least 10 years was
considered, because exposures ended in 1985, and cases were diagnosed after 1995 (when the VACCR
commenced operation).
The final analysis included 71 cases and 373 controls, but only 4 cases exposed to PCE (Ruckart et al.
2015). For cumulative PCE exposure, the adjusted ORs for low (>0 and <36 ng/L-months) and high
(>36 (^g/L-months) exposure were 1.05 (95% CI = 0.14-5.14) and 1.20 (95% CI = 0.16-5.89),
respectively. For monthly average exposure, the adjusted ORs for low (>0 and <2 (J,g/L) and high (>2
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(j,g/L) exposure were 0.91 (95% CI = 0.13-4.21) and 1.47 (95% CI = 0.18-7.91). In the evaluation for
reduced age at diagnosis, the adjusted HRs were 1.19 (95% CI = 0.2-7.07) for low and 2.08 (95% CI =
0.31 14.00) for high cumulative exposures. All of these results are highly uncertain, as they are based on
only 2 cases per exposure group.
A retrospective cohort study of military personnel at Camp Lejeune was conducted by (Bove et al.
2014a) and (Bove et al. 2014b). A primary focus of the study was standardized mortality analysis of
personnel stationed at Camp Lejeune (with exposure to drinking water contaminated with PCE,
trichloroethylene, and other solvents) and analyses comparing personnel at Camp Lejeune with those
stationed at Camp Pendleton (without exposure to contaminated water); these analyses are not discussed
here, because they do not provide hazard identification information specific to PCE. The study authors
also conducted an internal analysis of Camp Lejeune with chemical-specific effect estimates, as
described here.
The study population was defined as all Marine and Navy personnel who were stationed for active duty
at Camp Lejeune between April 1975 and December 1985 (Bove et al. 2014a. b). A total of 154,932
subjects were identified using personnel files that included date of birth, sex, race/ethnicity, marital
status, rank, active duty start date, total months of service, and military occupation. Vital status was
determined using Social Security Administration data and a commercial tracing service, and deaths and
causes (underlying and contributing) were identified using the NDI. Subjects whose vital status could
not be determined contributed person-years until the last date known to be alive.
Exposure assessment employed the same historical reconstruction methods used by (Ruckart et al. 2015)
and (Ruckart et al. 2013). Residential histories were determined using base housing records together
with rank, gender, marital status, and dates of service. For each subject, monthly average exposure
concentrations at each residence were combined with duration at each residence to estimate cumulative
exposure. Exposure estimates for PCE exhibited correlations (0.44-0.53) with other contaminants; the
authors noted that the Tarawa Terrace system, with the highest PCE levels (up to 158 (J,g/L, with mean
monthly average estimate of 75.7 (J,g/L), had low levels of other contaminants (e.g., mean estimated
monthly averages of 3.1 [j,g/L trichlorethylene and 5.6 [j,g/L vinyl chloride). The other contaminated
system at the Camp, Hadnot Point, was primarily contaminated with trichloroethylene (mean monthly
average estimate of 358.7 (J,g/L; means for PCE, vinyl chloride, and benzene were 15.7, 24.0, and 5.4
[j,g/L, respectively).
The study authors analyzed the association between cancer mortality and PCE exposure as HRs using
Cox extended regression models with age as the time variable and cumulative exposure as a time-
varying variable (Bove et al. 2014a. b). Lag periods of 0, 10, 15, and 20 years were considered in
assessments of cumulative exposures. Confounders were incorporated into the model if they altered the
effect estimate by 10% or more; these included sex, race, rank, and education. Because the data sources
used for the study lacked information on smoking, the HR for smoking-related diseases (stomach cancer,
cardiovascular disease, chronic obstructive pulmonary disease [COPD]) were subtracted from the HR
for the disease of interest to assess potential confounding by smoking. The validity of this method to
control for confounding by smoking is uncertain. No information on alcohol consumption or non-
service-related occupational exposures was available in the data sources used in the study.
The analysis based on cumulative exposure to PCE showed no significant exposure-related increase in
cancer risk for any tumor type, including bladder, kidney, liver, esophagus, breast, brain, lung, MM,
NHL, Hodgkin's disease, and leukemia (Bove et al. 2014a. b). Nonsignificant Increases in kidney cancer
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risk were observed for all cumulative exposure levels of PCE, but risk did not increase with estimated
exposure: HRs were 1.40 (95% CI = 0.54-3.58, 8 cases), 1.82 (95% CI = 0.75-4.42, 11 cases), and 1.59
(95% CI = 0.66-3.86, 11 cases) for low (>1 to 155 (j,g/L-month), medium (>155-380 (j,g/L-month), and
high (>380 8,585 (j,g/L-month) exposures, respectively. The authors reported that similar results were
observed when exposure was quantified as average exposure or duration of exposure (data not shown).
Findings from this study should be considered preliminary, as fewer than 6% of the cohort had died by
the end of the study, with 97% remaining under the age of 55 years.
(Christensen et al. 2013) performed a case-control study to examine the relationship between
occupational solvent exposure and multiple cancer types in residents of Montreal, Canada. Among 4,576
eligible Canadian males aged 35-70 years diagnosed with any of 11 different types of cancer (bladder,
NHL, liver, pancreas, kidney, esophagus, stomach, colon, rectum, prostate, melanoma) between 1979
and 1985 in the 18 largest hospitals in Montreal, 3,730 (82%) were successfully interviewed (proportion
by proxy varied with tumor type from low of 11.6% for melanoma to high of 60.4% for liver cancer).
Population controls, stratified by sex and age to the distribution of cases, were randomly sampled from
electoral lists; 533 {12%) of 740 eligible controls were interviewed (12.6% by proxy). Interviews were
conducted to obtain information on lifestyle factors and job history (company, products, nature of work
site, subject's main and secondary tasks, use of protective equipment, etc.), which was translated into
potential exposures to chlorinated solvents (PCE and 5 other individual chemicals, chlorinated alkanes,
chlorinated alkenes) by a team of chemists and industrial hygienists, blinded to a subject's case or
control status. Exposures were graded with respect to confidence that the exposure had occurred
(possible, probable, definite), frequency of exposure in a normal work week (<5%, 5-30%, >30% of the
time), and intensity of exposure (low, medium, or high). Exposures that were probable or definite, with
frequency and intensity of medium or high and duration of 5 or more years were considered to be
"substantial" for the analysis.
The authors did not discuss the extent of overlap of exposures (Christensen e1 ), but review of
the occupations with highest prevalence of exposure for each material analyzed showed considerable
overlap in occupations that is likely to have extended to exposures as well. Analyses were performed
using both population and cancer controls, as well as a pooled control group with cancer controls given
equal weight to population controls. Cancer controls for a given tumor type were cancer cases with other
tumors that were: (1) not lung cancer, (2) not from adjacent sites in the body to the site in question, and
(3) selected so that no more than 20% were from any one cancer site. All models were adjusted for age,
ethnicity (French Canadian or other), socioeconomic status, and respondent (proxy or self). Models for
some cancer types (not NHL) were also adjusted for smoking and consumption of alcohol, coffee,
and/or tea. Models were not adjusted for co-exposures to other solvents. Most cases and controls were
current or former smokers.
Numbers of cases and population controls with "substantial" or even "any" exposure to PCE were low
for all tumor types, 4 or lower in most cases (Christensen et al. 20131 which limits the conclusions that
can be drawn based on reported ORs for most endpoints in this study, whether above or below 1.0.
However, a significant increase was found for risk of prostate cancer with "substantial" exposure to PCE
relative to both population controls (OR = 6.0, 95% CI = 1.2-30 based on 9/449 cases and 2/533
controls) and cancer controls (OR = 4.3, 95% CI = 1.4-13 based on 9/1,550 controls). None of the other
chemicals evaluated showed a significant association with prostate cancer, and neither did chlorinated
alkenes or alkanes collectively. Confidence in the suggested association between PCE exposure and
prostate cancer is low due to small numbers of cases and controls.
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(Vizcava et al. 2013) published separate and pooled analyses of lung cancer from two population-based
case-control studies performed in Montreal, Quebec. Analyses of non-pulmonary cancer types in one of
the case-control studies (referred to as Study I) were published by (Christensen et al. 2013); details of
the case and control selection, participation rates, and exposure assessment for Study I are discussed in
that study description. Study II was conducted using nearly identical procedures but from 1995 to 2001
(Study I was 1980-1986). A total of 851 male lung cancer cases and 533 male controls (79% and 70% of
eligible subjects, respectively) were identified in Study I, while 735 male and 430 female lung cancer
cases and 898 male and 570 female controls (86% and 70% of eligible subjects, respectively) were
identified in Study II. Next-of-kin proxies responded for about one-third of cases and one-tenth of
controls. ORs were calculated using unconditional logistic regressions adjusted for age, income,
ethnicity, educational attainment, questionnaire respondent (self versus proxy), tobacco smoking
(Comprehensive Smoking Index), exposure to occupational lung carcinogens (never, ever, or substantial
occupational exposure to any of the 8 known or probable International Agency for Research on Cancer
(IARC) lung carcinogens: asbestos, crystalline silica, chromium VI, arsenic compounds, diesel exhaust
emissions, soot, wood dust, or benzo[a]pyrene), and in the pooled analysis, study (I versus II). The
authors noted that sample sizes were limited and there was overlapping exposure to multiple solvents,
and thus it was not possible to evaluate risks to subjects exposed to only one solvent.
Prevalence of exposure to any chlorinated solvent was 14.4% in male and 9.6% in female population
controls across both studies (Vizcava et al. 2013). Because there were fewer women included and their
exposure prevalence was lower, the study had little power to detect an effect in women and results were
presented for men only. The lifetime prevalence of PCE exposure in controls was very low (0.9% across
both studies). ORs for lung cancer with PCE exposure were 4.3 (95% CI = 1.1-16) based on 11/667
cases and 4/403 controls with "any" exposure and 5.7 (95% CI = 0.9-36) based on 6/667 cases and 2/403
controls with "substantial" exposure in Study I, 2.3 (95% CI = 0.8-6.2) based on 12/646 cases and 9/822
controls with "any" exposure and 1.6 (95% CI = 0.3-8.3) based on 4/646 cases and 4/822 controls with
"substantial" exposure in Study II, and 2.5 (95% CI = 1.2 5.6) based on 23/1,313 cases and 13/1,225
controls with "any" exposure and 2.4 (95% CI = 0.8-7.7) based on 10/1,313 cases and 6/1,225 controls
with "substantial" exposure in the pooled analysis. Similar results were observed when the analysis was
restricted to subjects who completed the questionnaires themselves (no proxy respondents). Among the
other chemicals evaluated, only carbon tetrachloride showed a significant association with lung cancer,
with results comparable to those for PCE among those with "substantial" exposure. There was no
association with lung cancer for chlorinated alkenes or alkanes collectively. These findings suggest an
association between exposure to PCE and lung cancer, but are limited by the low numbers of cases and
controls with PCE exposure.
(Mattei et al. 2014) performed a large, multicenter population-based case-control study of lung cancer
and solvent exposure in France. Cases were recruited from health care providers associated with French
cancer registries. A total of 4,865 eligible cases (ages 18-75 years) of incident, histologically-confirmed
lung cancer were identified between 2001 and 2007; of these, 3,357 living subjects were located and
healthy enough to be interviewed, and 2,926 (87%) were willing to participate. Controls were selected
by incidence density sampling and frequency-matched by age and gender. Investigators were able to
contact 4,411 (94%) of 4,673 eligible controls and 3,555 (81%) agreed to participate. Analyses were
based on 2,274 male and 622 female cases, and 2,780 male and 760 female controls. Exposure
assessment employed standardized questionnaires administered by trained interviewers for collection of
data regarding smoking history, sociodemographic characteristics, and lifetime occupational history
(company, tasks, specific exposures). The only chlorinated solvent specifically listed in the
questionnaire was trichloroethylene, although subjects could self-report other known exposures, such as
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PCE. A short-form questionnaire without the detailed job information was used for proxy interviews
(5% of men and 3% of women). Job histories were mapped to a job-exposure matrix to classify solvent
exposures by probability, intensity, frequency, and duration. Cumulative exposure indices were
calculated as the product of probability, frequency, intensity, and duration for each job, and then
categorized using deciles of the distribution in the control subjects. Lag times of 0, 5, and 10 years were
analyzed. Covariates considered in the analyses included age at interview, location, smoking history
(Comprehensive Smoking Index), number of jobs held, occupational exposure to asbestos, and in some
cases, socioeconomic status.
Among controls, prevalence of lifetime exposure to chlorinated solvents was 8.5% for men and 2.1% for
women (Mattel et al. 2014). The individual solvent with the highest prevalence of exposure was
trichloroethylene (7.6% of male and 1.1% of female controls). Only 0.3% of male and 0.9% of female
controls had any exposure to PCE, and almost all of these were exposed to other solvents as well. Men
were exposed to PCE primarily as printers, while women were exposed primarily as launderers and dry
cleaners. Trichloroethylene was the only individual solvent with a significant number of study subjects
that were not exposed to any other chlorinated solvents. In order to elucidate effects of other solvents
(such as PCE) individually, despite the multiple overlapping chemical exposures, the researchers
performed stratified analysis of mutually exclusive multiple solvent exposures (e.g., trichloroethylene
alone, versus trichloroethylene plus PCE, versus trichloroethylene plus PCE and methylene chloride,
etc.).
After adjustment for covariates, including socioeconomic status, the OR for PCE comparing ever
exposed to never exposed was 1.26 for men (95% CI = 0.87-1.82) based on 107 lung cancer cases and
94 controls with PCE exposure and 2.74 for women (95% CI = 1.23-6.09) based on 26 cases and 13
controls (Mattel et al. 2014). In analyses by cumulative PCE exposure (split into high and low groups
based on median cumulative exposure), ORs for men were 1.14 in the low-dose group (95% CI = 0.67-
1.94, 45 cases and 47 controls) and 1.36 in the high-dose group (95% CI = 0.84-2.22, 62 cases and 47
controls), while ORs for women were 3.80 in the low-dose group (95% CI = 1.41-10.24, 21 cases and 7
controls) and 1.43 in the high-dose group (95% CI = 0.37-5.50, 5 cases and 6 controls). In analyses
stratified by overlapping exposure to multiple solvents, ORs were elevated for women exposed to PCE
with trichloroethylene (2.39, 95% CI = 0.47 12.18, 6 cases and 3 controls) and with both
trichloroethylene and methylene chloride (4.57, 95% CI = 1.14-18.34, 12 cases and 3 controls), but not
those exposed to trichloroethylene alone (1.16, 95% CI = 0.64-2.11, 49 cases and 32 controls) or with
methylene chloride (0.73, 95% CI = 0.29-1.87, 12 cases and 17 controls) or methylene chloride and
chloroform and carbon tetrachloride (1.12, 95% CI = 0.31-4.08, 6 cases and 7 controls). In men, ORs
were also higher in the PCE groups (OR = 1.28-1.32) than the others (OR = 0.79-0.95), although the
difference was less pronounced than in women. These findings suggest an association between lung
cancer and PCE exposure, but are limited by low prevalence of PCE exposure among study subjects.
(Ruder et al. ) conducted a population-based case-control study focused on the association between
exposure to chlorinated aliphatic solvents, including PCE, and risk of glioma. Eligible participants were
residents of non-metropolitan counties in the states of Iowa, Michigan, Minnesota, and Wisconsin who
were diagnosed with glioma between 1995 and 1997 (cases) or were residents of the counties on January
1, 1995 (controls). Histologically-confirmed primary intracranial glioma cases were identified from
neurosurgery offices and other participating health care facilities. A pool of candidate controls was
established prior to case enrollment based on the age and sex distribution of glioma cases from an earlier
time period, using state driver license records (ages 18-64 years) or Medicare data tapes (ages 65 80
years). Persons diagnosed with cancers other than glioma (20.6% of controls) were eligible to
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participate. Participants included 798 cases (91.5% of eligible cases) and 1,175 controls (70.4% of
eligible controls). Interviews of cases (n=438), case next-of-kin (n=360), and controls (n=l,141) were
performed to obtain occupational history. Standardized questionnaires were used to establish details
(employer name, industry, job title, tasks, materials used, and employment frequency) of jobs held for at
least 1 year between 16 years of age and 1992; the questionnaires asked explicit questions regarding
exposures to solvents, thinners, glues, inks, varnishes, stains, and paint strippers. An industrial hygienist
blinded to case status combined the job history information with the authors' exposure database (from
published literature sources) to estimate probability, frequency, and intensity of exposure, as well as
confidence in the probability and frequency of exposure. Cumulative exposures were estimated as the
product of employment duration, employment frequency, exposure frequency, and exposure intensity.
Analyses were adjusted for sex, age, and education. Sensitivity analyses were performed excluding cases
with job history based on proxy questionnaires (to improve validity of the exposure estimates) or
limiting the exposed group to those with high probability (>0.5) of exposure. Types of gliomas observed
in cases included glioblastoma multiforme (equivalent to stage 4 glioma) (58%), astrocytoma (22%),
oligodendroglioma (11%), and other (8%). A subset of participants agreed to provide blood samples for
GST genotyping; these data were used to analyze the influence of GST on the association between
glioma risk and chlorinated solvent exposure.
ORs for PCE exposure and glioma risk were <1.0 in all analyses, including: when all subjects were
considered together (OR = 0.75, 95% CI = 0.62-0.91, 299 cases and 500 controls); when stratified by
sex; when analyzed as "any" versus no exposure; when analyzed by cumulative exposure; when cases
with proxy exposure data were excluded; and when exposed subjects were limited to those with high
probability of exposure (Ruder et al. 2013). GST genotype did not influence the relationship between
solvent exposure and glioma risk. Results were similarly negative for any chlorinated solvent and for the
other solvents considered individually. In this study, the large proportion of case questionnaires
completed by proxy (next of kin) is problematic, although excluding proxy interviews did not affect
results. Potential memory impairment (induced by glioma) among cases who did complete the
questionnaires may have affected exposure estimates in cases relative to controls. In addition, controls
were older than cases, and thus had greater chance of higher exposure from working during earlier eras,
and cases had slightly more education than controls, and therefore lower probability of solvent-related
employment. These limitations would tend to bias the risk estimates toward the null.
(Neta et; ) evaluated associations between solvent exposure and risk of glioma and meningioma
in a hospital-based study. Cases were patients at one of four hospitals (referral centers for brain cancers
in Massachusetts, Pennsylvania, and Arizona) who had received a histologically-confirmed diagnosis of
primary glioma or other neuroepitheliomatous neoplasm or meningioma within the previous 8 weeks. A
total of 484 cases of glioma (92% of eligible cases) and 197 cases of meningioma (94% of eligible
cases) agreed to participate. Controls were patients at the same hospitals who were receiving treatment
for non-cancer conditions. Controls were frequency matched on sex, age at interview, race/ethnicity,
hospital, and residential proximity to the hospital. A total of 797 controls (86% of eligible subjects)
agreed to participate. Trained interviewers administered questionnaires to patients (or a proxy if the
patient was too ill or deceased) to document jobs in which the patients worked for at least 6 months after
the age of 16 years; details included employer, dates of employment, job title, full or part time work
status, type of business, tasks, and materials and equipment used. Proxy interviews were conducted for
16%) (n=78) of glioma cases, 8% (n=15) of meningioma cases and 3% (n=23) of controls. When
respondents indicated employment in jobs with chemical exposures, more detailed industry- or job-
specific questions were asked to obtain information on frequency and duration of solvent-related tasks as
well as other information pertaining to exposure (e.g., potential for dermal exposure, sensory
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descriptions) or mitigation of exposure (engineering controls, personal protective equipment). Results
were reviewed by expert industrial hygienists who identified incomplete or inconsistent answers;
investigators followed up with supplementary subject phone interviews to resolve these discrepancies.
Using the finalized job histories and exposure data from occupational health literature, industrial
hygienists assigned exposure levels for six solvents including PCE. Analyses were adjusted for age at
diagnosis, sex, race/ethnicity, hospital site, residential zone/proximity to hospital, and estimated
cumulative occupational exposure to potential confounders: lead, magnetic fields, herbicides, and
insecticides. Analyses by any/no exposure to a given solvent were also adjusted for exposure to other
solvents. The investigators determined that adjustment for education and smoking did not result in
changes to the effect estimates, so these covariates were not included in the final models. ORs
comparing high to low exposure were also calculated (in addition to any/none) to control for potential
unidentified differences between exposed and unexposed subjects. Finally, a lag time of 10 years was
analyzed by excluding exposures in the 10 years prior to diagnosis.
The OR for glioma was 0.7 (95% CI = 0.5-0.9, 136 cases and 255 controls) for study subjects with
"possible" exposure to PCE and 0.7 (95% CI = 0.3-1.6, 9 cases and 20 controls) for those with
"probable" exposure (Neta et al. 2012). Results were similar when stratified by sex and various
measures of exposure (years exposed, cumulative exposure, average weekly exposure, highest
exposure). For meningioma, the ORs for "possible" and "probable" exposure were 0.9 (95% CI = 0.6-
1.3, 52 cases and 255 controls) and 0.5 (95% CI = 0.1-1.7, 3 cases and 20 controls), respectively,
without adjustment for exposure to other solvents and 1.0 (95% CI = 0.5-2.2) and 0.3 (95% CI = 0.1-
1.7), with the adjustment. Similarly, no clear associations were seen for the other solvents analyzed or
for the solvents collectively. Because relatively few subjects had exposures characterized as high, the
study had limited power to evaluate dose-response relationships (e.g., only 10 controls and 3 glioma
cases were classified as having high cumulative PCE exposure). The researchers noted that the
complexity of use of these solvents, which have been used interchangeably and at times together, makes
evaluation of specific exposures difficult. Exposure misclassification and potential memory impairment
(induced by glioma) among cases would tend to bias the risk estimates toward the null.
(Carton et al. 2017) investigated the relationship between occupational solvent exposure and head and
neck cancer in a case-control study in France. The final study group included 296 women with
squamous cell carcinoma of the oral cavity, oropharynx, hypopharynx, or larynx and 775 controls.
Incident cases were women aged 18-75 years at diagnosis between 2001 and 2007 identified from
cancer registries in 10 geographic areas in France and whose cancers were histologically confirmed.
Controls were chosen at random from the same geographic areas with age and sex distribution
comparable to cases and distribution of socioeconomic status similar to the general population.
Participation rate was 82.5% for cases and 80.6% for controls. Subjects were interviewed in person
using a standardized questionnaire for detailed occupation history, residential history, and lifetime
alcohol and tobacco consumption. Job-exposure matrices developed for the French population by the
French Institute of Health Surveillance were used to estimate probability, intensity, and frequency of
exposure to PCE and other solvents for each job held at least 1 month. The products of duration,
probability, intensity, and frequency of exposure for each job were summed to give cumulative
exposure, and cumulative exposure was divided by total duration of employment to calculate the mean
intensity of exposure.
Controls smoked significantly less and drank alcohol significantly less than cases and were of
significantly higher socioeconomic status (Carton et al. 2017). Age and geographic distributions differed
significantly as well. Analyses were performed by unconditional logistic regression and adjusted for
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geographical area, age, smoking status (never smoker, former smoker, and current smoker), tobacco
consumption in pack-years, and alcohol consumption in drink-years. Socioeconomic status, assessed by
the last occupation held and by the longest held occupation, was included in preliminary models, but
removed from the final models because it did not significantly affect results.
There was a significant association between "ever" exposed to PCE and head and neck cancer (OR =
2.97, 95% CI = 1.05-8.45), based on 10 cases and 13 controls (Carton et al. 2017). Of these, however, no
cases and only 3 controls were exposed to PCE alone without other chlorinated solvents. The rest were
exposed to PCE in combination with trichloroethylene (OR = 4.47, 95% CI = 1.27-15.8, 9 cases and 7
controls) or with trichloroethylene and methylene chloride (OR = 2.16, 95% CI = 0.19-24.1, 1 case and
3 controls). "Ever" exposed to trichloroethylene was also significantly associated with head and neck
cancer (OR = 2.15, 95% CI = 1.21-3.81) based on many more subjects (38 cases and 60 controls). For
"ever" exposed to trichloroethylene alone, the OR was 1.81 (95% CI = 0.81 4.04) based on 20 cases and
32 controls. The 10 cases "ever" exposed to PCE (with trichloroethylene and/or methylene chloride)
included 1 oral cavity (OR = 0.98, 95% CI = 0.11-8.47), 5 oropharynx (OR = 3.43, 95% CI = 1.01-11.8),
0 hypopharynx, and 4 larynx (OR = 7.95, 95% CI = 1.92-32.9). The 38 trichloroethylene cases were
split primarily between oral cavity (12 cases, OR = 2.12, 95% CI = 0.97-4.60), oropharynx (13 cases,
OR = 1.66, 95% CI = 0.78-3.54), and larynx (10 cases, OR = 3.80, 95% CI = 1.55-9.32). There was no
association between duration, mean intensity of exposure, or cumulative exposure index for PCE and
head and neck cancer. There was a small significant relationship between mean intensity of
trichloroethylene exposure and head and neck cancer (OR = 1.30, 95% CI = 1.01-1.66). These results
suggest a relationship between trichloroethylene and head and neck cancer. The apparent relationship for
"ever" exposed to PCE may reflect co-exposure to trichloroethylene.
A companion analysis of head and neck cancers in men was performed as part of the same study (Barul
et al. 2017). Methods were the same as reported by (Carton et al. 2017). The analysis included a total of
1,857 cases and 2,780 controls. As for the women, cases smoked more than controls and had higher
alcohol consumption. There was no relationship between "ever" exposed to PCE and head and neck
cancer in men (OR = 1.04, 95% CI = 0.69-1.59, 70 cases/89 controls). Analysis based on cumulative
PCE exposure, however, showed a nonsignificant increase in head and neck cancer risk in the high-
exposure group (OR = 1.81, 95% CI = 0.68-4.82, 14 cases/11 controls) that was traced to a significant
increase in laryngeal cancer in this group (OR = 3.86, 95% CI = 1.30-11.48, 8 cases). All subjects
exposed to PCE were exposed to other chlorinated solvents as well, primarily trichloroethylene. In
contrast to the results in women, however, there was no evidence in the men of an association between
trichloroethylene exposure and laryngeal cancer or head and neck cancers more broadly.
(Talibov et al. 2014) studied occurrence of acute myeloid leukemia (AML) relative to occupational
solvent exposure in a large population-based case-control study in four Nordic countries. The study
population comprised a subset of the NOCCA (Nordic Occupational Cancer Study) cohort of 14.9
million individuals from Finland, Iceland, Norway, Denmark, and Sweden who participated in
population censuses in 1960, 1970, 1980/1981, and/or 1990. For this study, all incident AML cases
diagnosed from 1961 to 2005 were extracted from the NOCCA cohort (the researchers did not have
access to individual records from Denmark, so those data were not included). Cases included in the
study were at least 20 years of age at diagnosis and had occupational information from at least one
census record (n=14,982). Five controls were randomly selected per case, matched for year of birth, sex,
and country (n=74,505). Controls were alive and free from AML on the date of diagnosis of the case.
Cases and controls could have a history of any cancer other than AML. Occupational exposures to
solvents were estimated based on the NOCCA job exposure matrix (developed by national experts from
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the Nordic countries), which characterizes proportion of exposed (P) and mean level of exposure for
exposed persons (L) for 29 exposure agents in 300 specific occupations over 4 time periods from 1945
to 1994, but does not account for heterogeneity of exposure within an occupation (e.g., with tasks
performed or workplace). Cumulative exposure for each subject was calculated by multiplying
employment period (T) in years by P x L for each job held and summing the products over their working
career (assumed to be ages 20-65 years), based on occupational codes in census records for each subject.
The census records provide snapshots in time, but do not provide a complete picture of work history; for
this study, it was assumed that when occupation changed from one census to the next that the change
occurred in the middle of the time period between censuses. Exposures in the 10 years prior to diagnosis
were not counted (alternative lag times of 0, 3, 5, 7, and 20 years were also used, but these data were not
shown). Subjects were split into low (0-50th percentile), moderate (50-90th percentile), and high (>90th
percentile) cumulative exposure groups in the analysis for each agent. Unexposed subjects served as the
reference group, although these data were not shown. Conditional logistic regression was used to
estimate HRs. Models included adjustment for exposure to other solvents and also ionizing radiation and
formaldehyde. The models did not adjust for suspected lifestyle (e.g., smoking) or genetic risk factors
because that information was not available for study subjects.
No significant association was found between PCE exposure and A ML (Tallboy et al. 2014). HRs in the
low (>0-<12.1 ppm/year), medium (12.1-106 ppm/year), and high (>106 ppm/year) cumulative exposure
groups were 1.07 (95% CI = 0.83-1.38, 89 cases/472 controls), 0.83 (95% CI = 0.61-1.12, 67 cases/381
controls), and 0.72 (95% CI = 0.39-1.34, 16 cases/96 controls), respectively, and the p-level for dose-
response trend was 0.39. There were also no significant findings for other solvents in this study,
including benzene, which has shown evidence of a positive association in other studies. A small
nonsignificant elevation of AML risk was seen for high cumulative exposure to toluene (HR = 1.35,
95% CI = 0.74-2.46, 76 cases/400 controls). Although the study included a large number of subjects, the
low prevalence of occupational exposure to solvents in general, and PCE in particular, limits confidence
in these results.
A similar study was performed by (Vlaanderen et al. 2013) to investigate the association between
solvent exposure and NHL, MM, and kidney and liver cancer in a subset of the NOCCA cohort. For this
study, incident cases of NHL, MM, kidney and liver cancer were extracted from the cohort, which
included all NOCCA subjects aged 30-64 years who participated in the 1960, 1970, 1980-1981, and/or
1990 census in Finland, Iceland, Norway, or Sweden and were still alive on January 1 of the year
following the census. The study included 76,130 kidney cancer cases, 23,896 liver cancer cases, 69,254
NHL cases, and 35,534 MM cases. For each case, five controls were randomly selected from all cohort
members alive and cancer free at the time of diagnosis of the case, matched for age, sex, and country.
Occupational exposures to solvents were estimated based on the NOCCA job exposure matrix, as
described above. Cumulative exposure was calculated by adding annual exposures, starting at age 20
years or start of working career, whichever occurred later, and ending at incidence date of case or at age
65 years, whichever occurred first. For this study, it was assumed that individuals continued in the same
occupation reported in the census until the calendar year in which the census was updated, and that
workers had worked in the job they reported in the first census since age of entry into the cohort (30
years). Conditional logistic regression was used to estimate HRs. For analysis, subjects were split into
tertiles with approximately equal numbers of exposed controls based on cumulative exposure.
Alternatively, high-exposure groups were defined based on 90th percentile of cumulative exposure or
90th percentile of average intensity x prevalence of exposure (calculated by dividing cumulative
exposure by duration of exposure). Unexposed subjects served as the reference group in all analyses,
although these data were not shown. Pearson correlation coefficients were calculated to describe the
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association between potential confounding exposures between agents (solvents and ionizing radiation).
The models did not adjust for lifestyle (e.g., smoking, alcohol intake) risk factors because that
information was not available for study subjects. Model fit was not affected by lagging calculation of
cumulative exposure by 0, 1, 5, 10, or 20 years, so untagged results were presented.
In the analysis by tertiles of cumulative exposure, no significant associations were found between first,
second, or third tertile of cumulative exposure to PCE and NHL, MM, or liver or kidney cancer in men,
women, or both sexes combined (Vlaanderen et al. 2013). In the analysis of high-exposure groups,
significant or near significant associations were found for NHL in men (HR = 1.54, 95% CI = 0.99-2.42
based on 25 cases using the cumulative exposure metric; HR = 1.74, 95% CI = 1.15-2.64 based on 30
cases using the average intensity x prevalence metric), but not in women (HR = 0.94, 95% CI = 0.74-
1.20 based on 77 cases using the cumulative exposure metric; HR = 1.12, 95% CI = 0.88-1.42 based on
83 cases using the average intensity x prevalence metric). PCE findings for other tumors were limited to
slight nonsignificant increases in HR for MM and liver cancer in men and/or women based on one or the
other of the high-exposure metrics. Among the other agents analyzed, slight associations were noted
between ionizing radiation and liver cancer and MM and between benzene and liver cancer. Although
PCE exposure in this study was correlated with exposure to trichloroethylene and other chlorinated
solvents (no tumor associations found for these agents), it was not correlated with exposure to ionizing
radiation or benzene. These results suggest an association between exposure to PCE and NHL in men,
and possibly to MM and liver cancer as well, although those data are much weaker. As in the previously
described study, the low prevalence of occupational exposure to PCE is a limiting factor for this study.
In another case-control study based on the NOCCA cohort, (Hadkhale et al. 2017) studied the potential
link between solvent exposure and bladder cancer. All incident cases of bladder cancer were extracted
from the NOCCA cohort, and persons with a minimum age of 20 years at diagnosis and having
occupation information from at least one census record before diagnosis were included in the study. Five
controls were randomly selected for each case from among individuals alive and free from bladder
cancer at the date of diagnosis of the case, matched by birth year and sex. Cases and controls could have
a history of any cancer type other than bladder cancer. A total of 113,343 cases and 566,715 controls
were included. Occupational exposures to solvents were estimated based on the NOCCA job exposure
matrix, as described above. Exposure was assumed to start at the age of 20 years and end at the date of
diagnosis or at 65 years, whichever occurred first. If there were different occupational codes in the
census records for a given person, the individual was assumed to have changed occupations at the mid-
point between two known census years. Cumulative exposure was estimated by summing annual
exposure estimates for the entire employment period. In addition to organic solvents, other exposures
assessed were ionizing radiation, asbestos, benzo[a]pyrene, diesel engine exhaust, and sulfur dioxide, all
considered to be potential confounders. Subjects were split into low (0-50th percentile), moderate (50-
90th percentile), and high (>90th percentile) cumulative exposure groups in the analysis for each agent,
which was performed by conditional logistic regression. Unexposed subjects served as the reference
group. Exposures in the 10 years prior to diagnosis were not counted (lag times of 0 or 20 years were
also performed, but these results were not presented). Models were adjusted for exposure to other
solvents and agents, but not nonoccupational risk factors (e.g., smoking, alcohol consumption) because
that information was not available for study subjects.
HRs for bladder cancer in the low (>0<13.6 ppm/year), medium (13.6-87.55 ppm/year), and high (>87.5
ppm/year) cumulative PCE exposure groups were 1.00 (95% CI = 0.92-1.09, 747 cases/3,560 controls),
1.12 (95% CI = 1.02-1.23, 660 cases/2,783 controls), and 0.94 (95% CI = 0.73-1.22, 159 cases/702
controls), respectively, and the p-level for dose-response trend was 0.10 (Hadkhale et al. 2017). These
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results show a slight significant increase in risk of bladder cancer in the medium PCE exposure
category, but no increase in the high-exposure group and no significant dose-related trend, suggesting a
cause other than PCE exposure for the slight association observed in the medium-exposure group.
Bladder cancer risks were significantly elevated in the high-exposure groups for trichloroethylene,
benzene, toluene, and ionizing radiation. Although the models included adjustment for co-exposure to
other agents, the researchers noted the difficulty of disentangling the effects of PCE and
trichloroethylene (structurally similar chemicals with overlapping uses) using the available data. There
were approximately 5 times more cases with trichloroethylene exposure than PCE exposure.
(Morales-Suarez-Varela et al.: ) studied the potential association between occupational solvent
exposure and mycosis fungoides (MF, the most common form of cutaneous T-cell lymphoma, a
heterogenous group of NHL). Cases were patients aged 35 to 69 years diagnosed with MF in 25 selected
areas from six European countries between January 1, 1995, and June 30, 1997. Of 118 pathologically-
confirmed cases, 100 agreed to be interviewed for this study (85% participation rate). Population
controls were randomly selected from the same areas as cases, frequency matched by sex and age. The
study was part of a larger study of seven cancers: MF, gall bladder, small intestine, bone, eye melanoma,
thymus, and breast cancer. The controls served as a common pool of controls for all seven groups of
cancer cases included in the larger study. In all, 4,629 eligible controls were identified and 3,156 were
interviewed (participation rate = 68%). For the MF study, only controls in the strata defined by age and
study area where at least one MF case was diagnosed were included (2,846 controls, including 1,957
men and 889 women). Due to illness, 4 case and 95 control interviews were conducted with surrogates.
Interviews were performed using standardized questionnaires that included questions on lifestyle factors
(smoking, alcohol consumption, etc.) and lifelong occupational history, including details regarding
specific tasks performed, products used, etc. Occupational exposures to solvents were assessed for each
job held over 6 months using a job exposure matrix developed by the French Institute of Health
Surveillance, which provided semiquantitative indicators of exposure probability, frequency, and
intensity for each solvent and occupation. A cumulative exposure score for each solvent was calculated
for each study subject as the sum of the job-specific exposure scores over his or her lifetime job history.
Subjects were split into high- and low-exposure groups based on median cumulative exposure in the
analysis for each agent. Unexposed subjects served as the reference group. The analysis was conducted
by unconditional logistic regression, with adjustments for age, sex, country, smoking habit, alcohol
intake, body mass index, and level of education. No adjustment for co-exposure to other chemicals was
noted. Alternative analyses were performed introducing lag times of 5, 10, or 15 years and excluding
jobs with low probability of exposure, but these were not shown because they did not affect findings.
For PCE, the results suggested a significant elevation of MF risk in high-dose women (OR = 11.38, 95%
CI = 1.04-124.85), but this finding is highly uncertain, as indicated by the extremely wide confidence
interval, because it is based on only 2 cases (Morales-Suarez-Varela et al. 2013). There were no female
cases with low-dose exposure to PCE. Among men, there were 2 cases with low-dose exposure (OR =
1.80, 95% CI = 0.22-14.80) and 2 with high-dose exposure (OR = 1.60, 95% CI = 0.30-13.60). The low
prevalence of PCE exposure and small number of cases in this study limit interpretation of these
findings.
(Purdue et al. 2017) conducted an analysis for associations between exposure to PCE and other
chlorinated solvents and kidney cancer within the U.S. Kidney Cancer Study, a population-based case-
control study conducted in Detroit, Michigan and Chicago, Illinois. Cases were histologically confirmed
incident kidney cancer newly diagnosed in Detroit from February 2002 until July 2006 (white cases) or
January 2007 (black cases) and in Chicago during 2003. Eligible controls in both locations were selected
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from the general population, frequency matched to cases based on sex, age (5-year intervals), and race.
The study was designed to maximize the number of black participants. Controls were frequency
matched to cases at a 2:1 ratio for blacks and a 1:1 ratio for whites. A total of 1,217 cases (77% of the
1,571 that the researchers attempted to recruit) and 1,235 controls (54% of the 2,269 that the researchers
attempted to recruit) participated in the study. Copies of medical records were obtained for all cases to
confirm the kidney cancer diagnosis, and the original diagnostic slides were obtained for 706 cases for
review by an experienced pathologist. Participants were interviewed for a wide variety of topics
including work history for all jobs held for at least 12 months starting at age 16 years. For selected
occupations, detailed histories were collected related to solvent exposures.
Job and task exposure matrices were developed for each of the six solvents included in the study by an
industrial hygienist using information from a systematic review of the industrial hygiene literature
(Purdue et al. 2017). Using the literature review, the exposure matrices, the occupational histories, and
the information collected in the job modules, the industrial hygienist assessed levels of exposure
probability, frequency, and intensity for each chlorinated solvent for each job. The job-specific estimates
of probability, frequency, and intensity for each participant were integrated to develop metrics of
exposure for each participant for each chlorinated solvent, including duration of exposure (sum of
number of years worked at each job across all jobs with exposure probability >50%), cumulative hours
exposed (sum of the product of the job-specific frequency midpoint and the job duration in weeks across
all jobs with an exposure probability >50%), and average weekly exposure (cumulative hours exposed
divided by the duration of exposure in weeks).
For the analysis, solvent exposures were split into tertiles among exposed controls, and unexposed
participants were used as referents (Purdue et al. 2017). Unconditional logistic regression modelling was
performed, including adjustment for location, age, race, sex, education, smoking history, body mass
index, and self-reported history of hypertension. Additional analyses incorporated 5- or 15-year
exposure lags, restricted participants to individuals with high confidence of exposure, or excluded
participants with >50% probability of exposure to trichloroethylene.
Prevalence of PCE exposure was low, with <4% of cases and controls assessed as having exposure
probability >50% (Purdue et al. 2017). Prevalence of exposure was low for other solvents as well,
including trichloroethylene. The most common tasks associated with PCE exposure were degreasing and
dry cleaning, accounting for 41% and 32% of exposures, respectively. Degreasing also accounted for
most exposures to trichloroethylene, carbon tetrachloride, and 1,1,1-trichloroethane. In analyses among
controls, after excluding participants unexposed to any chlorinated solvent, solvent exposure
probabilities were moderately correlated with one another.
No significant association was found between kidney cancer risk and probability of exposure to PCE
(e.g., OR = 1.2, 95% CI = 0.6-2.3, 22 cases/16 controls for those with probability of exposure >90%) or
PCE exposure duration (e.g., OR= 1.1, 95% CI = 0.5-2.5, 13 cases/11 controls for those exposed >10
years), average weekly exposure (e.g., OR =1.1, 95% CI = 0.4-3.1, 11 cases/14 controls for those
exposed >15 hours/week), or cumulative hours of exposure (e.g., OR = 0.9, 95% CI = 0.3-3.3, 8
cases/11 controls for those in highest tertile) for those with >50% probability of exposure (Purdue et al.
2017). When the analysis was restricted to those with high-intensity exposure to PCE, however, there
was a statistically significant increase in kidney cancer risk for those in the highest tertile of cumulative
hours exposed (OR = 3.1, 95% CI = 1.3-7.4, 14 cases/8 controls, Ptrend = 0.03). This relationship was
also seen in additional analyses that incorporated 5-year (OR = 3.5, 95% CI = 1.3 10.0, Ptrend = 0.03) or
15-year (OR = 6.2, 95% CI = 1.8-21.3, Ptrend = 0.003) exposure lag periods, included only jobs
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assigned an exposure probability with high confidence (OR = 5.1, 95% CI = 1.5-7.2, Ptrend = 0.12), or
excluded participants with >50% probability of exposure to trichloroethylene (OR = 3.0, 95% CI = 0.99-
9.0, 17 cases/14 controls, Ptrend = 0.08). Similar analyses performed for trichloroethylene found no
significant associations or exposure-response trends, although a nonsignificant increase in kidney cancer
risk was seen in the high tertile of cumulative hours exposed among those with high-intensity exposure
(OR = 1.7, 95% CI = 0.8-3.8, 18 cases and 8 controls, Ptrend = 0.28).
This study found no evidence of association between kidney cancer risk and exposure to chlorinated
solvents other than PCE and trichloroethylene, and only limited evidence for trichloroethylene (Purdue
et al. 2017). High exposure to PCE, however, was associated with kidney cancer, and the result was
independent of exposure to trichloroethylene.
(Heck et al. , ) conducted an exploratory study of exposure to air toxics during pregnancy in relation
to risk of neuroblastoma in offspring. Cases of neuroblastoma among California residents younger than
6 years old, born and diagnosed between 1990 and 2007, and listed in the California Cancer Registry
were matched to California birth certificates using first and last names and date of birth (89% matching
rate). Controls, frequency matched by year of birth to all childhood cancer cases for the same time
period, were randomly selected from California birth records of children who had no cancer diagnosis
before the age of 6 years and matched to California death records to exclude those (n=l,522) who died
of other causes prior to the age of 6. Birth address, as listed on the birth certificate, was used to estimate
exposure to air toxics, including PCE, based on distance from each address to monitors in California's
air toxics monitoring network (39 air monitors across the state, primarily positioned near heavily
trafficked highways, industrial areas, and agriculturally intense rural regions) and measurements made at
the nearest monitor to each residence, which were used to calculate average exposures for each trimester
and the entire pregnancy period for each participant using date of birth and gestational age obtained
from the birth certificate. The study included a total of 75 cases and 14,602 controls who lived within 5
km of a monitor and had measurement values for at least one pollutant. Unconditional logistic regression
was used to calculate ORs and CIs, adjusted for mother's age, mother's race, birth year, and method of
payment for prenatal care (proxy for family income). No increase in risk of neuroblastoma was seen
with PCE exposure for cases within 5 km of a monitor (OR = 1.06, 95% CI = 0.84-1.33, 67 cases/12,041
controls) or within 2.5 km of a monitor (OR = 1.01, 95% CI = 0.62-1.64, 21 cases/3,635 controls).
(Bulka et al. ) looked at spatial patterns of diffuse large B-cell lymphoma (DLBCL) incidence in
relation to residential proximity to toxic release sites in Georgia. The Georgia Comprehensive Cancer
Registry was used to identify all DLBCL cases in adults (>20 years) residing in Georgia at diagnosis
during 1999-2008. Subjects without age, sex, or race information were excluded from the analysis.
Included cases (n=3581) were aggregated by census tract, and standardized incidence ratios (SIR) were
calculated for each tract by dividing the number of observed cases by expected cases, derived by
standardizing DLBCL incidence rates from Georgia to national DLBCL incidence rates by age, sex, and
race. GIS (geographic information system) software was used to examine the spatial distribution of TRI
(Toxics Release Inventory) sites and SIRs by census tract. From 1988 to 1998, Georgia facilities
reported the release of PCE at 33 TRI sites, with releases ranging from 5 to 1,575,644 lb. TRI sites for
the other chemicals studied ranged from 3 to 86 sites. The study found that relative risk of DLBCL
decreased as mean distance to TRI sites increased for TRI sites for most (8/9) of the contaminants
studied, including PCE. The strongest such relationship was found for formaldehyde, which showed a
0.58%) decrease in DLBCL risk for every mile of increase in distance to release site. For PCE, the
decrease in risk was 0.21% per mile. The effect of mean distance on DLBCL incidence from all of the
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release sites was strongest for African Americans. Quantity of chemicals released was not included in
the analysis.
F.2_ Animal Studies
In a 2-year inhalation study by ( 6a), F344/N rats were exposed to PCE vapors at 0, 200, or 400
ppm for 6 hours/day, 5 days/week for 103 weeks. The incidence of mononuclear cell leukemia (MCL)
showed a positive trend in males (control: 28/50, 200 ppm: 37/50, 400 ppm: 37/50) and females
(control: 18/50, 200 ppm: 30/50, 400 ppm: 29/50), with a dose-related increase in severity of MCL in
both sexes. In addition, the time to onset was decreased in exposed females, compared to controls. When
only advanced (stage 3) MCL was considered, the incidence was statistically significantly increased in
male and female rats exposed to 400 ppm (males - control: 20/50, 200 ppm: 24/50, 400 ppm: 27/50;
females - control: 10/50, 200 ppm: 18/50, 400 ppm: 21/50). The incidence of testicular interstitial cell
tumors was increased in exposed male rats, with a statistically significant positive trend (control: 35/50,
200 ppm: 39/49, 400 ppm: 41/50). Renal tubular cell hyperplasia was observed in exposed male rats
(control: 0/49, 200 ppm: 3/49, 400 ppm: 5/50) and in one treated female rat (1/50 at 400 ppm only), and
renal tubular adenomas and adenocarcinomas were observed in males (combined incidence - control:
1/49, 200 ppm: 3/49, 400 ppm: 4/50) but not females. Although the increase in kidney tumors was not
statistically significant, renal tubular carcinomas are considered rare in this strain of rat and (
2012c) concluded that a dose-response relationship is apparent when the combined incidence of
proliferative and neoplastic lesions was considered in combination with tumor severity. A biologically
significant elevation of brain gliomas, another rare tumor type, was observed in male (control: 1/50, 200
ppm: 0/50, 400 ppm: 4/50) and female (control: 1/50, 200 ppm: 0/50, 400 ppm: 2/50) rats. The
significance of the brain glioma findings is supported by the earlier occurrence of brain tumors in
exposed animals (week 88 in males, week 75 in females), compared to controls (week 99 in males, week
104 in females) ( ).
In the same study by (NTP 1986a). B6C3F1 mice were exposed to concentrations of PCE of 100 or 200
ppm for 6 hours/day, 5 days/week for 103 weeks. Statistically significant dose-related increases were
observed in the incidence of hepatocellular carcinoma (males - control: 7/49, 100 ppm: 25/49, 200 ppm:
26/50; females - control: 1/48, 100 ppm: 13/50, 200 ppm: 36/50) and combined incidence of
hepatocellular adenomas or carcinomas in male and female mice (males - control: 17/49, 100 ppm:
31/49, 200 ppm: 41/50; females - control: 4/48, 100 ppm: 17/50, 200 ppm: 38/50). The incidences of
hepatocellular carcinoma and hepatocellular adenomas or carcinomas combined were significantly
increased, compared to controls, at both 100 and 200 ppm in males and females. In several instances,
hepatocellular carcinomas metastasized to the lungs in males (control: 2/49, 100 ppm: 7/49, 200 ppm:
1/50) and females (control: 0/48, 100 ppm: 2/50, 200 ppm: 7/50).
In a 2-year inhalation study conducted by F344/DuCij rats were exposed to PCE vapors at
0, 50, 200, or 600 ppm. A statistically significant dose-related increase (statistical analysis by statistical
analysis by statistical analysis by statistical analysis ) was observed in the incidence
of MCL in males (control: 11/50, 50 ppm: 14/50, 200 ppm: 22/50, 600 ppm: 27/50) and females
(control: 10/50, 50 ppm: 17/50, 200 ppm: 16/50, 600 ppm: 19/50). The increase in MCL incidence
achieved statistical significance in males exposed to 600 ppm, compared to control males. The time to
first occurrence of MCL was decreased in exposed female rats (weeks 66-74 in exposed groups)
compared to control female rats (week 100). Also, there was a dose-related increase in the overall
number of unscheduled deaths attributed to MCL in males and females.
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PISA 1993) also exposed Crj:BDFl mice to PCE at 0, 10, 50, or 250 ppm for 6 hours/day, 5 days/week
for 104 weeks. Dose-related increases in the incidences of hepatocellular adenomas (males - control:
7/50, 10 ppm: 13/50, 50 ppm: 8/50, 250 ppm: 26/50; females - control: 3/50, 10 ppm: 3/47, 50 ppm:
7/49, 250 ppm: 26/49), hepatocellular carcinomas (males - control: 7/50, 10 ppm: 8/50, 50 ppm: 12/50,
250 ppm: 25/50; females - control: 0/50, 10 ppm: 0/47, 50 ppm: 0/49, 250 ppm: 14/49), and combined
hepatocellular adenomas or carcinomas were observed in males and females (males - control: 13/50, 10
ppm: 21/50, 50 ppm: 19/50, 250 ppm: 40/50; females - control: 3/50, 10 ppm: 3/47, 50 ppm: 7/49, 250
ppm: 33/49). The incidences of hepatocellular adenoma, hepatocellular carcinoma, and combined
hepatocellular adenoma or carcinoma were statistically significantly increased at 250 ppm, relative to
controls, in both sexes. A small increase in liver and spleen hemangiosarcomas (reported as malignant
hemangioendotheliomas) was also observed in treated male mice (liver - control: 1/50, 10 ppm: 1/50, 50
ppm: 5/50, 250 ppm: 5/50; spleen - control: 1/50, 10 ppm: 1/50, 50 ppm: 3/50, 250 pm: 5/50). The
combined incidence of hemangiosarcomas or hemangiomas (reported as malignant or benign
hemangioendotheliomas, respectively) occurring in the liver, spleen, fat, subcutaneous skin, and heart
was statistically significantly increased in male mice (combined incidence - control: 4/50, 10 ppm: 2/50,
50 ppm: 7/50, 250 ppm: 11/50) (analysis by ( 2012c)). In addition, there was a statistically
significant positive dose-related trend in the incidence of adenoma of the Harderian gland in male mice
(control: 2/50, 10 ppm: 2/50, 50 ppm: 2/50, 250 ppm: 8/50).
In a lifetime bioassay by (NCI 1977). Osborne-Mendel rats were administered PCE for 78 weeks via
gavage in corn oil for 5 days/week, followed by a 32-week observation period. Dose adjustments were
made throughout the exposure period depending upon the tolerance of treated animals to the existing
dose level. Administered doses were 500-700 mg/kg-day in the low dose and 1,000-1,400 mg/kg-day in
the high-dose males, with 7 dose-free weeks occurring intermittently during the last 33 weeks of
exposure. Time-weighted average (TWA) doses during the 78-week treatment period were
approximately 470 mg/kg-day at the low dose and approximately 950 mg/kg-day at the high dose. Rats
showed no significant treatment-related increases in neoplastic lesions, compared to controls, and there
were no significant positive dose-related trends. A high rate of early death was observed in treated rats.
At the high dose, mortality was 50% in males by week 44 and in females by week 66. Respiratory
disease and pneumonia were observed in both treated and control rats, while toxic nephropathy occurred
only in treated animals (males - low dose: 43/49, high dose: 47/50; females - low dose: 29/50, high dose:
39/50). Due to the high rate of early death in treated rats, (NCI 1977) determined that the
carcinogenicity of PCE in rats could not be evaluated from the results of this study.
(NCI 1977) also exposed B6C3F1 mice to PCE by gavage in corn oil for 78 weeks (5 days/week),
followed by a 12-week observation period. Male mice were administered 450 or 900 mg/kg-day for the
first 11 weeks, after which the doses were increased to 550 or 1,100 mg/kg-day, respectively, for the
next 67 weeks. Female mice received 300 or 600 mg/kg-day during the first 11 weeks, and doses were
increased to 400 or 800 mg/kg-day, respectively, for the subsequent 67 weeks. The TWA doses (5
days/week for 78 weeks) were 536 and 1,072 mg/kg-day for males and 386 and 772 mg/kg-day for
females. The incidence of hepatocellular carcinoma was statistically significantly increased in treated
male and female mice of both dose groups, compared with controls (males - untreated control: 2/17,
vehicle control: 2/20, 536 mg/kg-day: 32/49, 1,072 mg/kg-day: 27/48; females - untreated control: 2/20,
vehicle control: 0/20, 386 mg/kg-day: 19/48, 772 mg/kg-day: 19/48); the time to first tumor was also
decreased in treated mice (weeks 27-40 in males, weeks 41-50 in females) compared to controls (weeks
90-91 in males, week 91 in females). Metastasis of hepatocellular carcinomas to the lung was observed
in 3/49 low-dose males, 1/49 low-dose females, and 1/48 high-dose females.
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Appendix G Chronic Inhalation Risk Estimates Using Occupational
HECs
Table Apx G-l presents risk chronic inhalation risk estimates for each OES based on the occupational
HECs for neurotoxicity presented in Table 3-8. These HECs are based on 8 hr or 12 hr LOAEC PODs
and were compared to 8 or 12 hr TWA exposures for calculating MOEs. Risk estimates are shown
without a respirator as well as with APF = 50 for workers, the highest plausible respiratory protection
expected to be used by workers on a regular basis. Occupational Exposure Scenarios (OES) that are
highlighted in gold demonstrate differing risk conclusions than shown in Section 4.3 (i.e. not using
occupational HECs) based either on worker risk estimates with APF = 50 or ONU estimates without a
respirator. Of note, occupational HECs were derived based on an expected normal, full time work
schedule. For OES where exposure is expected for significantly less than 250 days/year (both of Other
DOD uses), these HEC values are likely to overestimate risk.
Table Apx G-l. Chronic Inhalation Risk Estimates by OES
8 hr HEC = 14.5 ppm
12 hr HEC = 9.7 ppm
Benchmark MOE = 100
Occupational
Exposure Scenario
Occupational
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 50
Manufacturing
(8 hr)
14.5
High-
End
5.6
446
278
100
Central
Tendency
446
22308
Manufacturing
(12 hr)
9.7
High-
End
46
472
2280
100
Central
Tendency
472
23577
Repackaging
14.5
High-
End
18
33
885
100
Central
Tendency
33
1666
Processing as a
react ant
(8hr)
14.5
High-
End
5.6
446
278
100
Central
Tendency
446
22308
Processing as a
react ant
(12hr)
9.7
High-
End
46
472
2280
100
Central
Tendency
472
23577
Incorporation into
Formulation -
Aerosol Packing
14.5
High-
End
1.1
1.7
55
100
Central
Tendency
1.7
87
Incorporation into
Formulation -
Degreasing Solvent
14.5
High-
End
5.6
20
279
100
Central
Tendency
20
994
Incorporation into
Formulation - Dry
Cleaning Solvent
14.5
High-
End
1.0
3.7
51
100
Central
Tendency
3.7
183
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8 hr HEC = 14.5 ppm
12 hr HEC = 9.7 ppm
Benchmark MOE = 100
Occupational
Exposure Scenario
Occupational
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 50
Incorporation into
Formulation -
Miscellaneous
14.5
High-
End
10
36
513
100
Central
Tendency
36
1825
Batch Open-Top
Vapor Degreasing
14.5
High-
End
0.5
2.8
23
100
Central
Tendency
6.9
24
345
Batch Closed-Loop
Vapor Degreasing
14.5
High-
End
57
151
2865
100
Central
Tendency
201
222
10043
Conveyorized
Vapor Degreasing
14.5
High-
End
7.80E-2
0.1
3.9
100
Central
Tendency
0.2
0.4
9.3
Web Degreasing
14.5
High-
End
8.0
12
402
100
Central
Tendency
24
45
1187
Cold Cleaning
(Monitoring)
14.5
High-
End
3.5
EPA did not
identify ONU
monitoring
data
176
100
Central
Tendency
10
518
Cold Cleaning
(Modeling)
14.5
High-
End
9.4
19
472
100
Central
Tendency
6048
11685
302423
Aerosol Degreasing/
Lubricants
(Monitoring)
14.5
High-
End
1.9
EPA did not
identify ONU
monitoring
data
93
100
Central
Tendency
10
504
Aerosol Degreasing/
Lubricants
(Modeling)
14.5
High-
End
0.8
20
42
100
Central
Tendency
2.6
145
132
Dry Cleaning and
Spot Cleaning -
Post-2006
(Monitoring)
14.5
High-
End
0.7
42
37
100
Central
Tendency
4.0
42
199
Dry Cleaning and
Spot Cleaning -
Post-2006
(Modeling)
14.5
High-
End
0.3
6.2
16
100
Central
Tendency
6.9
89
346
Dry Cleaning and
Spot Cleaning -
4th/5th Gen Only
14.5
High-
End
2.6
118
130
100
Central
Tendency
15
1039
741
Paints/Coatings
14.5
High-
End
3.2
62
159
100
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8 hr HEC = 14.5 ppm
12 hr HEC = 9.7 ppm
Benchmark MOE = 100
Occupational
Exposure Scenario
Occupational
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 50
Central
Tendency
62
3107
Adhesives
14.5
High-
End
18
164
894
100
Central
Tendency
164
8193
Maskant for
Chemical Milling
14.5
High-
End
6.9
12
345
100
Central
Tendency
12
598
Industrial
Processing Aid
14.5
High-
End
12
242
614
100
Central
Tendency
242
12083
Metalworking
Fluids
14.5
High-
End
692
2521
34616
100
Central
Tendency
2521
126038
Wipe Cleaning and
Metal/Stone
Polishes
14.5
High-
End
6.36E-02
0.6
3.2
100
Central
Tendency
0.1
664
5.5
Other Spot
Cleaning/Spot
Removers
14.5
High-
End
63
483
3142
100
Central
Tendency
84
4219
Other Industrial
Uses
14.5
High-
End
403
1822
20153
100
Central
Tendency
1822
91115
Other Commercial
Uses -
Printing
14.5
High-
End
2.4
7.6
122
100
Central
Tendency
7.6
378
Other Commercial
Uses - Photocopying
14.5
High-
End
29000
77333
1450000
100
Central
Tendency
77333
3866667
Other Commercial
Uses - Photographic
Film
14.5
High-
End
0.3
2.3
13
100
Central
Tendency
2.3
115
Other Commercial
Uses -
Mold Release
14.5
High-
End
73
145
3625
100
Central
Tendency
145
7250
Waste Handling,
Disposal, Treatment,
Recycling
14.5
High-
End
403
1822
20153
100
Central
Tendency
1822
91115
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8 hr HEC = 14.5 ppm
12 hr HEC = 9.7 ppm
Benchmark MOE = 100
Occupational
Exposure Scenario
Occupational
HEC
(ppm)
Exposure
Level
MOEs for Chronic Exposure
Benchmark
MOE
(= Total UF)
Worker
No
respirator
ONU
No
respirator
Worker
APF 50
Other DOD Uses -
Water Pipe Repair
14.5
High-
End
6.3
13
314
100
Central
Tendency
13
627
Other DOD Uses -
Oil Analysis
14.5
High-
End
16
16
823
Central
Tendency
15967
15968
15969
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